libs/g722_1-*/
libs/ilbc-*/
libs/broadvoice-*/
+libs/libcodec2-*/
EndProject\r
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "Download broadvoice", "libs\win32\Download broadvoice.2015.vcxproj", "{46502007-0D94-47AC-A640-C2B5EEA98333}"\r
EndProject\r
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "libcodec2", "libs\win32\libcodec2\libcodec2.2015.vcxproj", "{19E934D6-1484-41C8-9305-78DC42FD61F2}"\r
+EndProject\r
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "mod_codec2", "src\mod\codecs\mod_codec2\mod_codec2.vcxproj", "{CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}"\r
+EndProject\r
+Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "Download libcodec2", "libs\win32\Download libcodec2.2015.vcxproj", "{9CFA562C-C611-48A7-90A2-BB031B47FE6D}"\r
+EndProject\r
Global\r
GlobalSection(SolutionConfigurationPlatforms) = preSolution\r
All|Win32 = All|Win32\r
{46502007-0D94-47AC-A640-C2B5EEA98333}.Release|Win32.Build.0 = Release|Win32\r
{46502007-0D94-47AC-A640-C2B5EEA98333}.Release|x64.ActiveCfg = Release|Win32\r
{46502007-0D94-47AC-A640-C2B5EEA98333}.Release|x64.Build.0 = Release|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.All|Win32.ActiveCfg = Release|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.All|Win32.Build.0 = Release|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.All|x64.ActiveCfg = Release|x64\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.All|x64.Build.0 = Release|x64\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Debug|Win32.ActiveCfg = Debug|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Debug|Win32.Build.0 = Debug|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Debug|x64.ActiveCfg = Debug|x64\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Debug|x64.Build.0 = Debug|x64\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Release|Win32.ActiveCfg = Release|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Release|Win32.Build.0 = Release|Win32\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Release|x64.ActiveCfg = Release|x64\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2}.Release|x64.Build.0 = Release|x64\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.All|Win32.ActiveCfg = Release|Win32\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.All|Win32.Build.0 = Release|Win32\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.All|x64.ActiveCfg = Release|x64\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.All|x64.Build.0 = Release|x64\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Debug|Win32.ActiveCfg = Debug|Win32\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Debug|Win32.Build.0 = Debug|Win32\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Debug|x64.ActiveCfg = Debug|x64\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Debug|x64.Build.0 = Debug|x64\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Release|Win32.ActiveCfg = Release|Win32\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Release|Win32.Build.0 = Release|Win32\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Release|x64.ActiveCfg = Release|x64\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}.Release|x64.Build.0 = Release|x64\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.All|Win32.ActiveCfg = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.All|Win32.Build.0 = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.All|x64.ActiveCfg = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.All|x64.Build.0 = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Debug|Win32.ActiveCfg = Debug|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Debug|Win32.Build.0 = Debug|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Debug|x64.ActiveCfg = Debug|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Debug|x64.Build.0 = Debug|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Release|Win32.ActiveCfg = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Release|Win32.Build.0 = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Release|x64.ActiveCfg = Release|Win32\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D}.Release|x64.Build.0 = Release|Win32\r
EndGlobalSection\r
GlobalSection(SolutionProperties) = preSolution\r
HideSolutionNode = FALSE\r
{36603FE1-253F-4C2C-AAB6-12927A626135} = {C120A020-773F-4EA3-923F-B67AF28B750D}\r
{53AADA60-DF12-46FF-BF94-566BBF849336} = {C120A020-773F-4EA3-923F-B67AF28B750D}\r
{46502007-0D94-47AC-A640-C2B5EEA98333} = {C120A020-773F-4EA3-923F-B67AF28B750D}\r
+ {19E934D6-1484-41C8-9305-78DC42FD61F2} = {EB910B0D-F27D-4B62-B67B-DE834C99AC5B}\r
+ {CB4E68A1-8D19-4B5E-87B9-97A895E1BA17} = {F881ADA2-2F1A-4046-9FEB-191D9422D781}\r
+ {9CFA562C-C611-48A7-90A2-BB031B47FE6D} = {C120A020-773F-4EA3-923F-B67AF28B750D}\r
EndGlobalSection\r
EndGlobal\r
+++ /dev/null
-src/codebookvq.c
+++ /dev/null
- GNU LESSER GENERAL PUBLIC LICENSE
- Version 2.1, February 1999
-
- Copyright (C) 1991, 1999 Free Software Foundation, Inc.
- 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- Everyone is permitted to copy and distribute verbatim copies
- of this license document, but changing it is not allowed.
-
-[This is the first released version of the Lesser GPL. It also counts
- as the successor of the GNU Library Public License, version 2, hence
- the version number 2.1.]
-
- Preamble
-
- The licenses for most software are designed to take away your
-freedom to share and change it. By contrast, the GNU General Public
-Licenses are intended to guarantee your freedom to share and change
-free software--to make sure the software is free for all its users.
-
- This license, the Lesser General Public License, applies to some
-specially designated software packages--typically libraries--of the
-Free Software Foundation and other authors who decide to use it. You
-can use it too, but we suggest you first think carefully about whether
-this license or the ordinary General Public License is the better
-strategy to use in any particular case, based on the explanations below.
-
- When we speak of free software, we are referring to freedom of use,
-not price. Our General Public Licenses are designed to make sure that
-you have the freedom to distribute copies of free software (and charge
-for this service if you wish); that you receive source code or can get
-it if you want it; that you can change the software and use pieces of
-it in new free programs; and that you are informed that you can do
-these things.
-
- To protect your rights, we need to make restrictions that forbid
-distributors to deny you these rights or to ask you to surrender these
-rights. These restrictions translate to certain responsibilities for
-you if you distribute copies of the library or if you modify it.
-
- For example, if you distribute copies of the library, whether gratis
-or for a fee, you must give the recipients all the rights that we gave
-you. You must make sure that they, too, receive or can get the source
-code. If you link other code with the library, you must provide
-complete object files to the recipients, so that they can relink them
-with the library after making changes to the library and recompiling
-it. And you must show them these terms so they know their rights.
-
- We protect your rights with a two-step method: (1) we copyright the
-library, and (2) we offer you this license, which gives you legal
-permission to copy, distribute and/or modify the library.
-
- To protect each distributor, we want to make it very clear that
-there is no warranty for the free library. Also, if the library is
-modified by someone else and passed on, the recipients should know
-that what they have is not the original version, so that the original
-author's reputation will not be affected by problems that might be
-introduced by others.
-\f
- Finally, software patents pose a constant threat to the existence of
-any free program. We wish to make sure that a company cannot
-effectively restrict the users of a free program by obtaining a
-restrictive license from a patent holder. Therefore, we insist that
-any patent license obtained for a version of the library must be
-consistent with the full freedom of use specified in this license.
-
- Most GNU software, including some libraries, is covered by the
-ordinary GNU General Public License. This license, the GNU Lesser
-General Public License, applies to certain designated libraries, and
-is quite different from the ordinary General Public License. We use
-this license for certain libraries in order to permit linking those
-libraries into non-free programs.
-
- When a program is linked with a library, whether statically or using
-a shared library, the combination of the two is legally speaking a
-combined work, a derivative of the original library. The ordinary
-General Public License therefore permits such linking only if the
-entire combination fits its criteria of freedom. The Lesser General
-Public License permits more lax criteria for linking other code with
-the library.
-
- We call this license the "Lesser" General Public License because it
-does Less to protect the user's freedom than the ordinary General
-Public License. It also provides other free software developers Less
-of an advantage over competing non-free programs. These disadvantages
-are the reason we use the ordinary General Public License for many
-libraries. However, the Lesser license provides advantages in certain
-special circumstances.
-
- For example, on rare occasions, there may be a special need to
-encourage the widest possible use of a certain library, so that it becomes
-a de-facto standard. To achieve this, non-free programs must be
-allowed to use the library. A more frequent case is that a free
-library does the same job as widely used non-free libraries. In this
-case, there is little to gain by limiting the free library to free
-software only, so we use the Lesser General Public License.
-
- In other cases, permission to use a particular library in non-free
-programs enables a greater number of people to use a large body of
-free software. For example, permission to use the GNU C Library in
-non-free programs enables many more people to use the whole GNU
-operating system, as well as its variant, the GNU/Linux operating
-system.
-
- Although the Lesser General Public License is Less protective of the
-users' freedom, it does ensure that the user of a program that is
-linked with the Library has the freedom and the wherewithal to run
-that program using a modified version of the Library.
-
- The precise terms and conditions for copying, distribution and
-modification follow. Pay close attention to the difference between a
-"work based on the library" and a "work that uses the library". The
-former contains code derived from the library, whereas the latter must
-be combined with the library in order to run.
-\f
- GNU LESSER GENERAL PUBLIC LICENSE
- TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
-
- 0. This License Agreement applies to any software library or other
-program which contains a notice placed by the copyright holder or
-other authorized party saying it may be distributed under the terms of
-this Lesser General Public License (also called "this License").
-Each licensee is addressed as "you".
-
- A "library" means a collection of software functions and/or data
-prepared so as to be conveniently linked with application programs
-(which use some of those functions and data) to form executables.
-
- The "Library", below, refers to any such software library or work
-which has been distributed under these terms. A "work based on the
-Library" means either the Library or any derivative work under
-copyright law: that is to say, a work containing the Library or a
-portion of it, either verbatim or with modifications and/or translated
-straightforwardly into another language. (Hereinafter, translation is
-included without limitation in the term "modification".)
-
- "Source code" for a work means the preferred form of the work for
-making modifications to it. For a library, complete source code means
-all the source code for all modules it contains, plus any associated
-interface definition files, plus the scripts used to control compilation
-and installation of the library.
-
- Activities other than copying, distribution and modification are not
-covered by this License; they are outside its scope. The act of
-running a program using the Library is not restricted, and output from
-such a program is covered only if its contents constitute a work based
-on the Library (independent of the use of the Library in a tool for
-writing it). Whether that is true depends on what the Library does
-and what the program that uses the Library does.
-
- 1. You may copy and distribute verbatim copies of the Library's
-complete source code as you receive it, in any medium, provided that
-you conspicuously and appropriately publish on each copy an
-appropriate copyright notice and disclaimer of warranty; keep intact
-all the notices that refer to this License and to the absence of any
-warranty; and distribute a copy of this License along with the
-Library.
-
- You may charge a fee for the physical act of transferring a copy,
-and you may at your option offer warranty protection in exchange for a
-fee.
-\f
- 2. You may modify your copy or copies of the Library or any portion
-of it, thus forming a work based on the Library, and copy and
-distribute such modifications or work under the terms of Section 1
-above, provided that you also meet all of these conditions:
-
- a) The modified work must itself be a software library.
-
- b) You must cause the files modified to carry prominent notices
- stating that you changed the files and the date of any change.
-
- c) You must cause the whole of the work to be licensed at no
- charge to all third parties under the terms of this License.
-
- d) If a facility in the modified Library refers to a function or a
- table of data to be supplied by an application program that uses
- the facility, other than as an argument passed when the facility
- is invoked, then you must make a good faith effort to ensure that,
- in the event an application does not supply such function or
- table, the facility still operates, and performs whatever part of
- its purpose remains meaningful.
-
- (For example, a function in a library to compute square roots has
- a purpose that is entirely well-defined independent of the
- application. Therefore, Subsection 2d requires that any
- application-supplied function or table used by this function must
- be optional: if the application does not supply it, the square
- root function must still compute square roots.)
-
-These requirements apply to the modified work as a whole. If
-identifiable sections of that work are not derived from the Library,
-and can be reasonably considered independent and separate works in
-themselves, then this License, and its terms, do not apply to those
-sections when you distribute them as separate works. But when you
-distribute the same sections as part of a whole which is a work based
-on the Library, the distribution of the whole must be on the terms of
-this License, whose permissions for other licensees extend to the
-entire whole, and thus to each and every part regardless of who wrote
-it.
-
-Thus, it is not the intent of this section to claim rights or contest
-your rights to work written entirely by you; rather, the intent is to
-exercise the right to control the distribution of derivative or
-collective works based on the Library.
-
-In addition, mere aggregation of another work not based on the Library
-with the Library (or with a work based on the Library) on a volume of
-a storage or distribution medium does not bring the other work under
-the scope of this License.
-
- 3. You may opt to apply the terms of the ordinary GNU General Public
-License instead of this License to a given copy of the Library. To do
-this, you must alter all the notices that refer to this License, so
-that they refer to the ordinary GNU General Public License, version 2,
-instead of to this License. (If a newer version than version 2 of the
-ordinary GNU General Public License has appeared, then you can specify
-that version instead if you wish.) Do not make any other change in
-these notices.
-\f
- Once this change is made in a given copy, it is irreversible for
-that copy, so the ordinary GNU General Public License applies to all
-subsequent copies and derivative works made from that copy.
-
- This option is useful when you wish to copy part of the code of
-the Library into a program that is not a library.
-
- 4. You may copy and distribute the Library (or a portion or
-derivative of it, under Section 2) in object code or executable form
-under the terms of Sections 1 and 2 above provided that you accompany
-it with the complete corresponding machine-readable source code, which
-must be distributed under the terms of Sections 1 and 2 above on a
-medium customarily used for software interchange.
-
- If distribution of object code is made by offering access to copy
-from a designated place, then offering equivalent access to copy the
-source code from the same place satisfies the requirement to
-distribute the source code, even though third parties are not
-compelled to copy the source along with the object code.
-
- 5. A program that contains no derivative of any portion of the
-Library, but is designed to work with the Library by being compiled or
-linked with it, is called a "work that uses the Library". Such a
-work, in isolation, is not a derivative work of the Library, and
-therefore falls outside the scope of this License.
-
- However, linking a "work that uses the Library" with the Library
-creates an executable that is a derivative of the Library (because it
-contains portions of the Library), rather than a "work that uses the
-library". The executable is therefore covered by this License.
-Section 6 states terms for distribution of such executables.
-
- When a "work that uses the Library" uses material from a header file
-that is part of the Library, the object code for the work may be a
-derivative work of the Library even though the source code is not.
-Whether this is true is especially significant if the work can be
-linked without the Library, or if the work is itself a library. The
-threshold for this to be true is not precisely defined by law.
-
- If such an object file uses only numerical parameters, data
-structure layouts and accessors, and small macros and small inline
-functions (ten lines or less in length), then the use of the object
-file is unrestricted, regardless of whether it is legally a derivative
-work. (Executables containing this object code plus portions of the
-Library will still fall under Section 6.)
-
- Otherwise, if the work is a derivative of the Library, you may
-distribute the object code for the work under the terms of Section 6.
-Any executables containing that work also fall under Section 6,
-whether or not they are linked directly with the Library itself.
-\f
- 6. As an exception to the Sections above, you may also combine or
-link a "work that uses the Library" with the Library to produce a
-work containing portions of the Library, and distribute that work
-under terms of your choice, provided that the terms permit
-modification of the work for the customer's own use and reverse
-engineering for debugging such modifications.
-
- You must give prominent notice with each copy of the work that the
-Library is used in it and that the Library and its use are covered by
-this License. You must supply a copy of this License. If the work
-during execution displays copyright notices, you must include the
-copyright notice for the Library among them, as well as a reference
-directing the user to the copy of this License. Also, you must do one
-of these things:
-
- a) Accompany the work with the complete corresponding
- machine-readable source code for the Library including whatever
- changes were used in the work (which must be distributed under
- Sections 1 and 2 above); and, if the work is an executable linked
- with the Library, with the complete machine-readable "work that
- uses the Library", as object code and/or source code, so that the
- user can modify the Library and then relink to produce a modified
- executable containing the modified Library. (It is understood
- that the user who changes the contents of definitions files in the
- Library will not necessarily be able to recompile the application
- to use the modified definitions.)
-
- b) Use a suitable shared library mechanism for linking with the
- Library. A suitable mechanism is one that (1) uses at run time a
- copy of the library already present on the user's computer system,
- rather than copying library functions into the executable, and (2)
- will operate properly with a modified version of the library, if
- the user installs one, as long as the modified version is
- interface-compatible with the version that the work was made with.
-
- c) Accompany the work with a written offer, valid for at
- least three years, to give the same user the materials
- specified in Subsection 6a, above, for a charge no more
- than the cost of performing this distribution.
-
- d) If distribution of the work is made by offering access to copy
- from a designated place, offer equivalent access to copy the above
- specified materials from the same place.
-
- e) Verify that the user has already received a copy of these
- materials or that you have already sent this user a copy.
-
- For an executable, the required form of the "work that uses the
-Library" must include any data and utility programs needed for
-reproducing the executable from it. However, as a special exception,
-the materials to be distributed need not include anything that is
-normally distributed (in either source or binary form) with the major
-components (compiler, kernel, and so on) of the operating system on
-which the executable runs, unless that component itself accompanies
-the executable.
-
- It may happen that this requirement contradicts the license
-restrictions of other proprietary libraries that do not normally
-accompany the operating system. Such a contradiction means you cannot
-use both them and the Library together in an executable that you
-distribute.
-\f
- 7. You may place library facilities that are a work based on the
-Library side-by-side in a single library together with other library
-facilities not covered by this License, and distribute such a combined
-library, provided that the separate distribution of the work based on
-the Library and of the other library facilities is otherwise
-permitted, and provided that you do these two things:
-
- a) Accompany the combined library with a copy of the same work
- based on the Library, uncombined with any other library
- facilities. This must be distributed under the terms of the
- Sections above.
-
- b) Give prominent notice with the combined library of the fact
- that part of it is a work based on the Library, and explaining
- where to find the accompanying uncombined form of the same work.
-
- 8. You may not copy, modify, sublicense, link with, or distribute
-the Library except as expressly provided under this License. Any
-attempt otherwise to copy, modify, sublicense, link with, or
-distribute the Library is void, and will automatically terminate your
-rights under this License. However, parties who have received copies,
-or rights, from you under this License will not have their licenses
-terminated so long as such parties remain in full compliance.
-
- 9. You are not required to accept this License, since you have not
-signed it. However, nothing else grants you permission to modify or
-distribute the Library or its derivative works. These actions are
-prohibited by law if you do not accept this License. Therefore, by
-modifying or distributing the Library (or any work based on the
-Library), you indicate your acceptance of this License to do so, and
-all its terms and conditions for copying, distributing or modifying
-the Library or works based on it.
-
- 10. Each time you redistribute the Library (or any work based on the
-Library), the recipient automatically receives a license from the
-original licensor to copy, distribute, link with or modify the Library
-subject to these terms and conditions. You may not impose any further
-restrictions on the recipients' exercise of the rights granted herein.
-You are not responsible for enforcing compliance by third parties with
-this License.
-\f
- 11. If, as a consequence of a court judgment or allegation of patent
-infringement or for any other reason (not limited to patent issues),
-conditions are imposed on you (whether by court order, agreement or
-otherwise) that contradict the conditions of this License, they do not
-excuse you from the conditions of this License. If you cannot
-distribute so as to satisfy simultaneously your obligations under this
-License and any other pertinent obligations, then as a consequence you
-may not distribute the Library at all. For example, if a patent
-license would not permit royalty-free redistribution of the Library by
-all those who receive copies directly or indirectly through you, then
-the only way you could satisfy both it and this License would be to
-refrain entirely from distribution of the Library.
-
-If any portion of this section is held invalid or unenforceable under any
-particular circumstance, the balance of the section is intended to apply,
-and the section as a whole is intended to apply in other circumstances.
-
-It is not the purpose of this section to induce you to infringe any
-patents or other property right claims or to contest validity of any
-such claims; this section has the sole purpose of protecting the
-integrity of the free software distribution system which is
-implemented by public license practices. Many people have made
-generous contributions to the wide range of software distributed
-through that system in reliance on consistent application of that
-system; it is up to the author/donor to decide if he or she is willing
-to distribute software through any other system and a licensee cannot
-impose that choice.
-
-This section is intended to make thoroughly clear what is believed to
-be a consequence of the rest of this License.
-
- 12. If the distribution and/or use of the Library is restricted in
-certain countries either by patents or by copyrighted interfaces, the
-original copyright holder who places the Library under this License may add
-an explicit geographical distribution limitation excluding those countries,
-so that distribution is permitted only in or among countries not thus
-excluded. In such case, this License incorporates the limitation as if
-written in the body of this License.
-
- 13. The Free Software Foundation may publish revised and/or new
-versions of the Lesser General Public License from time to time.
-Such new versions will be similar in spirit to the present version,
-but may differ in detail to address new problems or concerns.
-
-Each version is given a distinguishing version number. If the Library
-specifies a version number of this License which applies to it and
-"any later version", you have the option of following the terms and
-conditions either of that version or of any later version published by
-the Free Software Foundation. If the Library does not specify a
-license version number, you may choose any version ever published by
-the Free Software Foundation.
-\f
- 14. If you wish to incorporate parts of the Library into other free
-programs whose distribution conditions are incompatible with these,
-write to the author to ask for permission. For software which is
-copyrighted by the Free Software Foundation, write to the Free
-Software Foundation; we sometimes make exceptions for this. Our
-decision will be guided by the two goals of preserving the free status
-of all derivatives of our free software and of promoting the sharing
-and reuse of software generally.
-
- NO WARRANTY
-
- 15. BECAUSE THE LIBRARY IS LICENSED FREE OF CHARGE, THERE IS NO
-WARRANTY FOR THE LIBRARY, TO THE EXTENT PERMITTED BY APPLICABLE LAW.
-EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR
-OTHER PARTIES PROVIDE THE LIBRARY "AS IS" WITHOUT WARRANTY OF ANY
-KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE
-IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE
-LIBRARY IS WITH YOU. SHOULD THE LIBRARY PROVE DEFECTIVE, YOU ASSUME
-THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-
- 16. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN
-WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY
-AND/OR REDISTRIBUTE THE LIBRARY AS PERMITTED ABOVE, BE LIABLE TO YOU
-FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR
-CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
-LIBRARY (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING
-RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A
-FAILURE OF THE LIBRARY TO OPERATE WITH ANY OTHER SOFTWARE), EVEN IF
-SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
-DAMAGES.
-
- END OF TERMS AND CONDITIONS
-\f
- How to Apply These Terms to Your New Libraries
-
- If you develop a new library, and you want it to be of the greatest
-possible use to the public, we recommend making it free software that
-everyone can redistribute and change. You can do so by permitting
-redistribution under these terms (or, alternatively, under the terms of the
-ordinary General Public License).
-
- To apply these terms, attach the following notices to the library. It is
-safest to attach them to the start of each source file to most effectively
-convey the exclusion of warranty; and each file should have at least the
-"copyright" line and a pointer to where the full notice is found.
-
- <one line to give the library's name and a brief idea of what it does.>
- Copyright (C) <year> <name of author>
-
- This library is free software; you can redistribute it and/or
- modify it under the terms of the GNU Lesser General Public
- License as published by the Free Software Foundation; either
- version 2.1 of the License, or (at your option) any later version.
-
- This library is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
- Lesser General Public License for more details.
-
- You should have received a copy of the GNU Lesser General Public
- License along with this library; if not, see
- <http://www.gnu.org/licenses/>.
-
-Also add information on how to contact you by electronic and paper mail.
-
-You should also get your employer (if you work as a programmer) or your
-school, if any, to sign a "copyright disclaimer" for the library, if
-necessary. Here is a sample; alter the names:
-
- Yoyodyne, Inc., hereby disclaims all copyright interest in the
- library `Frob' (a library for tweaking knobs) written by James Random Hacker.
-
- <signature of Ty Coon>, 1 April 1990
- Ty Coon, President of Vice
-
-That's all there is to it!
+++ /dev/null
-AM_CFLAGS = -Isrc -fPIC -Wall -O3 -lm
-AUTOMAKE_OPTIONS = gnu
-NAME = codec2
-AM_CPPFLAGS = $(AM_CFLAGS)
-
-EXTRA_DIST = octave/glottal.m \
-octave/lsp_pdf.m \
-octave/phase.m \
-octave/pl2.m \
-octave/plinterp.m \
-octave/plnlp.m \
-octave/plpitch.m \
-octave/postfilter.m \
-octave/load_raw.m \
-octave/phase2.m \
-octave/pitch_test.m \
-octave/plamp.m \
-octave/pl.m \
-octave/plphase.m \
-octave/png.m \
-octave/pulse.m \
-raw/b0067.raw \
-raw/forig_speex_8k.raw \
-raw/hts1.raw \
-raw/hts2.raw \
-raw/mmt1.raw \
-raw/morig_speex_8k.raw \
-raw/f2400.raw \
-raw/hts1a_g729a.raw \
-raw/hts2a_g729a.raw \
-raw/hts.raw \
-raw/mmt1_speex_8k.raw \
-raw/forig_g729a.raw \
-raw/hts1a_gsm13k.raw \
-raw/hts2a_gsm13k.raw \
-raw/m2400.raw \
-raw/morig_g729a.raw \
-raw/forig_gsm13k.raw \
-raw/hts1a.raw \
-raw/hts2a.raw \
-raw/mmt1_g729a.raw \
-raw/morig_gsm13k.raw \
-raw/forig.raw \
-raw/hts1a_speex_8k.raw \
-raw/hts2a_speex_8k.raw \
-raw/mmt1_gsm13k.raw \
-raw/morig.raw \
-script/menu.sh \
-script/playraw.sh \
-script/raw2wav.sh \
-script/wav2raw.sh \
-wav/f2400.wav \
-wav/hts1a_c2_v0.1.wav \
-wav/hts1a.wav \
-wav/hts2a_speex_8k.wav \
-wav/mmt1_speex_8k.wav \
-wav/morig.wav \
-wav/forig_speex_8k.wav \
-wav/hts1a_g729a.wav \
-wav/hts2a_c2_v0.1.wav \
-wav/hts2a.wav \
-wav/mmt1.wav \
-wav/forig.wav \
-wav/hts1a_speex_8k.wav \
-wav/hts2a_g729a.wav \
-wav/m2400.wav \
-wav/morig_speex_8k.wav \
-src/globals.c \
-unittest/lsp2.txt \
-unittest/lsp7.txt \
-unittest/lspd78.txt \
-unittest/lsp3.txt \
-unittest/lsp8.txt \
-unittest/lspd910.txt \
-unittest/lsp4.txt \
-unittest/lsp9.txt \
-unittest/lsp10.txt \
-unittest/lsp5.txt \
-unittest/lspd123.txt \
-unittest/lsp1.txt \
-unittest/lsp6.txt \
-unittest/lspd456.txt \
-src/codebook/lsp1.txt \
-src/codebook/lsp2.txt \
-src/codebook/lsp3.txt \
-src/codebook/lsp4.txt \
-src/codebook/lsp5.txt \
-src/codebook/lsp6.txt \
-src/codebook/lsp7.txt \
-src/codebook/lsp8.txt \
-src/codebook/lsp9.txt \
-src/codebook/lsp10.txt
-
-SUBDIRS = src unittest
+++ /dev/null
-Codec 2 README
---------------
-
-Codec 2 is an open source (LGPL licensed) speech codec for 2400 bit/s
-and below. For more information please see:
-
- http://rowetel.com/codec2.html
-
-Also included is a FDMDV modem, see README_fdmdv.txt
-
-Quickstart
-----------
-
-1/ Listen to Codec 2:
-
- $ ./configure && make
- $ cd src
- $ ./c2demo ../raw/hts1a.raw hts1a_c2.raw
- $ ../script/menu.sh ../raw/hts1a.raw hts1a_c2.raw
-
- NOTE: For playback testing, menu.sh requires either the 'play',
- 'aplay' or 'ossplay' programs to be installed (see
- http://sox.sourceforge.net/, http://www.alsa-project.org/, or
- http://www.opensound.com/ respectively).
-
-2/ Compress and Decompress a file:
-
- $ ./c2enc 2400 ../raw/hts1a.raw hts1a_c2.bit
- $ ./c2dec 2400 hts1a_c2.bit hts1a_c2.raw
-
-3/ Same thing with pipes:
-
- $ ./c2enc 1400 ../raw/hts1a.raw - | ./c2dec 1400 - - | play -t raw -r 8000 -s -2 -
-
-Programs
---------
-
-1/ c2demo encodes a file of speech samples, then decodes them and
-saves the result.
-
-2/ c2enc encodes a file of speech samples to a compressed file of
-encoded bits.
-
-3/ c2dec decodes a compressed file of bits to a file of speech
-samples.
-
-4/ c2sim is a simulation/development version of Codec 2. It allows
-selective use of the various Codec 2 algorithms. For example
-switching phase modelling or LSP quantisation on and off.
-
-Debugging
----------
-
-1/ For dump file support:
-
- $ cd codec2
- $ CFLAGS=-DDUMP ./configure
- $ make clean && make
-
-2/ To use gdb:
-
- $ libtool --mode=execute gdb c2sim
-
-Directories
------------
-
- fltk - FLTK GUI programs(s)
- octave - Octave scripts used for visualising internal signals
- during development
- portaudio - Portaudio test programs
- script - shell scripts for playing and converting raw files
- src - C source code
- raw - speech files in raw format (16 bits signed linear 8 kHz)
- unittest - unit test source code
- voicing - hand-estimated voicing files, used for development
- wav - speech files in wave file format
- win32 - Support for building Windows DLL version of Codec 2 and FDMDV libraries
-
-TODO
-----
-
-[ ] Get win32/Makefile integrated into Automake system, such that if
- i586-mingw32msvc exists the Win32 code gets automatically built.
-[ ] Same for fltk & portaudio, build these conditionally if libs exist
\ No newline at end of file
+++ /dev/null
-
-README_fdmdv.txt
-David Rowe
-Created March 2012
-
-Introduction
-------------
-
-A 1400 bit/s Frequency Division Multiplexed Digital Voice (FDMDV) modem
-based on [1]. Used for digital audio over HF SSB.
-
-The FDMDV modem was first implemented in GNU Octave, then ported to C.
-Algorithm development is generally easier in Octave, but for real time
-work we need the C version. Automated units tests ensure the
-operation of the Octave and C versions are identical.
-
-Quickstart
-----------
-
-$ cd codec2-dev
-$ ./configure && make
-$ cd src
-
-1. Generate some test bits and modulate them:
-
- $ ./fdmdv_get_test_bits test.c2 1400
- $ ./fdmdv_mod test.c2 test.raw
- $ play -r 8000 -s -2 test.raw
-
-2. Two seconds of test frame data modulated and sent out of sound device:
-
- $ ./fdmdv_get_test_bits - 2800 | ./fdmdv_mod - - | play -t raw -r 8000 -s -2 -
-
-3. Send 14000 modulated bits (10 seconds) to the demod and count errors:
-
- $ ./fdmdv_get_test_bits - 14000 | ./fdmdv_mod - - | ./fdmdv_demod - - demod_dump.txt | ./fdmdv_put_test_bits -
-
- Use Octave to look at plots of 1 second (1400 bits) of modem operation:
-
- $ cd ../octave
- $ octave
- octave:1> fdmdv_demod_c("../src/demod_dump.txt",1400)
-
-4. Run Octave simulation of entire modem and AWGN channel:
-
- $ cd ../octave
- $ octave
- octave:1> fdmdv_ut
-
-5. NOTE: If you would like to play modem samples over the air please
- convert the 8 kHz samples to 48 kHz. Many PC sound cards have
- wildly inaccurate sample clock rates when set to 8 kHz, but seem to
- perform OK when set for 48 kHz. If playing and recording files you
- can use the sox utility:
-
- $ sox -r 8000 -s -2 modem_sample_8kHz.raw -r 48000 modem_sample_48kHz.wav
-
- For real time applications, the fdmdv.[ch] library includes functions to
- convert between 48 and 8 kHz sample rates.
-
-References
-----------
-
-[1] http://n1su.com/fdmdv/FDMDV_Docs_Rel_1_4b.pdf
-[2] http://n1su.com/fdmdv/
-[3] http://www.rowetel.com/blog/?p=2433 "Testing a FDMDV Modem"
-[4] http://www.rowetel.com/blog/?p=2458 "FDMDV Modem Page" on David's web site
-
-C Code
-------
-
-src/fdmdv_mod.c - C version of modulator that takes a file of bits and
- converts it to a raw file of modulated samples.
-
-src/fdmdv_demod.c - C version of demodulator that takes a raw file of
- modulated samples and outputs a file of bits.
- Optionally dumps demod states to a text file which
- can be plotted using the Octave script
- fdmdv_demod_c.m
-
-src/fdmdv.h - Header file that exposes FDMDV C API functions. Include
- this file in your application program.
-
-src/fdmdv.c - C functions that implement the FDMDV modem.
-
-src/fdmdv-internal.h - internal states and constants for FDMDV modem,
- shouldn't be exposed to application program.
-
-
-unittest/tfdmdv.c - Used to conjunction with unittest/tfdmdv.m to
- automatically test C FDMDV functions against
- Octave versions.
-
-Octave Scripts
---------------
-
-(Note these require some Octave packages to be installed, see
-octave/README.txt).
-
-fdmdv.m - Functions and variables that implement the Octave version of
- the FDMDV modem.
-
-fdmdv_ut.m - Unit test for fdmdv Octave code, useful while
- developing algorithm. Includes tx/rx plus basic channel
- simulation.
-
- Typical run:
-
- octave:6> fdmdv_ut
- Eb/No (meas): 7.30 (8.29) dB
- bits........: 2464
- errors......: 20
- BER.........: 0.0081
- PAPR........: 13.54 dB
- SNR.........: 4.0 dB
-
- It also outputs lots of nice plots that show the
- operation of the modem.
-
- For a 1400 bit/s DQPSK modem we expect about 1% BER for
- Eb/No = 7.3dB, which corresponds to SNR = 4dB (3kHz
- noise BW). The extra dB of measured power is due to the
- DBPSK pilot. Currently the noise generation code
- doesn't take the pilot power into account, so in this
- example the real SNR is actually 5dB.
-
-fdmdv_mod.m - Octave version of modulator that outputs a raw file.
- The modulator is driven by a test frame of bits. This
- can then be played over a real channel or through a
- channel simulator like PathSim. The sample rate can be
- changed using "sox" to simulate differences in tx/rx
- sample clocks.
-
- To generate 10 seconds of modulated signal:
-
- octave:8> fdmdv_mod("test.raw",1400*10);
-
-fdmdv_demod.m - Demodulator program that takes a raw file as input,
- and works out the bit error rate using the known test
- frame. Can be used to test the demod performs with
- off-air signals, or signals that have been passed
- through a channel simulator.
-
- To demodulate 2 seconds of the test.raw file generated
- above:
-
- octave:9> fdmdv_demod("test.raw",1400*2);
- 2464 bits 0 errors BER: 0.0000
-
- It also produces several plots showing the internal
- states of the demod. Useful for debugging and
- observing what happens with various channels.
-
-fdmdv_demod_c.m - Takes an output text file from the C demod
- fdmdv_demod.c and produces plots and measures BER.
- Useful for evaluating fdmdv_demod.c performance.
- The plots produced are identical to the Octave
- version fdmdv_demod.m, allowing direct comparison of
- the C and Octave versions.
-
-tfdmdv.m - Automatic tests that compare the Octave and C versions of
- the FDMDV modem functions. First run unittest/tfdmdv, this
- will generate a text file with test vectors from the C
- version. Then run the Octave script tfdmdv and it will
- generate Octave versions of the test vectors and compare
- each vector with the C equivalent. Its plots the vectors
- and and errors (green). Its also produces an automatic
- check list based on test results. If the Octave or C modem
- code is changed, this script should be used to ensure the
- C and Octave versions remain identical.
-
-Modelling sample clock errors using sox
----------------------------------------
-
-This introduces a simulated 1000ppm error:
-
- sox -r 8000 -s -2 mod_dqpsk.raw -s -2 mod_dqpsk_8008hz.raw rate -h 8008
-
-TODO
-----
-
-[ ] implement ppm measurements in fdmdv_get_demod_stats()
-[ ] try interfering sine wave
- + maybe swept
- + does modem fall over?
-[ ] try non-flat channel, e.g. 3dB difference between hi and low tones
- + make sure all estimators keep working
-[ ] test rx level sensitivity, i.e. 0 to 20dB attenuation
-[ ] make fine freq indep of amplitude
- + use angle rather than imag coord
-[ ] document use of fdmdv_ut and fdmdv_demod + PathSim
-[ ] more positive form of sync reqd for DV frames?
- + like using coarse_fine==1 to decode valid DV frame bit?
- + when should we start decoding?
-[ ] more robust track/acquite state machine?
- + e.g. hang on thru the fades?
-[ ] PAPR idea
- + automatically tweak phases to reduce PAPR, e.g. slow variations in freq...
-[ ] why is pilot noise_est twice as big as other carriers
+++ /dev/null
-README for codec2/asterisk
-Asterisk Codec 2 support
-
-Test Configuration
-------------------
-
-Codec 2 is used to trunk calls between two Asterisk boxes:
-
- A - SIP phone - Asterisk A - Codec2 - Asterisk B - SIP Phone - B
-
-The two SIP phones are configured for mulaw.
-
-Building
----------
-
-Asterisk must be patched so that the core understand Codec 2 frames.
-
-1/ First install Codec 2:
-
- david@cool:~$ svn co https://freetel.svn.sourceforge.net/svnroot/freetel/codec2-dev codec2-dev
- david@cool:~/codec2-dev$ cd codec2-dev
- david@cool:~/codec2-dev$ ./configure && make && sudo make install
- david@bear:~/codec2-dev$ sudo ldconfig -v
- david@cool:~/codec2-dev$ cd ~
-
-2/ Then build Asterisk with Codec 2 support:
-
- david@cool:~$ tar xvzf asterisk-1.8.9.0.tar.gz
- david@cool:~/asterisk-1.8.9.0$ patch -p4 < ~/codec2-dev/asterisk/asterisk-codec2.patch
- david@cool:~/asterisk-1.8.9.0$ cp ~/codec2-dev/asterisk/codec_codec2.c .
- david@cool:~/asterisk-1.8.9.0$ cp ~/codec2-dev/asterisk/ex_codec2.h ./codecs
- david@cool:~/asterisk-1.8.9.0$ ./configure && make ASTLDFLAGS=-lcodec2
- david@cool:~/asterisk-1.8.9.0$ sudo make install
- david@cool:~/asterisk-1.8.9.0$ sudo make samples
-
-3/ Add this to the end of sip.conf on Asterisk A:
-
- [6013]
- type=friend
- context=default
- host=dynamic
- user=6013
- secret=6013
- canreinvite=no
- callerid=6013
- disallow=all
- allow=ulaw
-
- [potato]
- type=peer
- username=potato
- fromuser=potato
- secret=password
- context=default
- disallow=all
- dtmfmode=rfc2833
- callerid=server
- canreinvite=no
- host=cool
- allow=codec2
-
-3/ Add this to the end of sip.conf on Asterisk B:
-
- [6014]
- type=friend
- context=default
- host=dynamic
- user=6014
- secret=6014
- canreinvite=no
- callerid=6014
- disallow=all
- allow=ulaw
-
- [potato]
- type=peer
- username=potato
- fromuser=potato
- secret=password
- context=default
- disallow=all
- dtmfmode=rfc2833
- callerid=server
- canreinvite=no
- host=bear
- allow=codec2
-
-4/ Here is the [default] section of extensions.conf on Asterisk B:
-
- [default]
-
- exten => 6013,1,Dial(SIP/potato/6013)
- ;
- ; By default we include the demo. In a production system, you
- ; probably don't want to have the demo there.
- ;
- ;include => demo
-
-5/ After booting see if the codec2_codec2.so module is loaded with "core show translate"
-
-6/ To make a test call dial 6013 on the SIP phone connected to Asterisk B
-
-7/ If codec_codec2.so won't load and you see "can't find codec2_create" try:
-
- david@cool:~/asterisk-1.8.9.0$ touch codecs/codec_codec2.c
- david@cool:~/asterisk-1.8.9.0$ make ASTLDFLAGS=-lcodec2
- david@cool:~/asterisk-1.8.9.0$ sudo cp codecs/codec_codec2.so /usr/lib/asterisk/modules
- david@cool:~/asterisk-1.8.9.0$ sudo asterisk -vvvcn
-
+++ /dev/null
---- /home/david/asterisk-1.8.9.0-orig/include/asterisk/frame.h 2011-12-23 05:08:46.000000000 +1030
-+++ /home/david/asterisk-1.8.9.0-codec2/include/asterisk/frame.h 2012-03-27 13:16:55.623452431 +1030
-@@ -299,6 +299,7 @@
- #define AST_FORMAT_G719 (1ULL << 32)
- /*! SpeeX Wideband (16kHz) Free Compression */
- #define AST_FORMAT_SPEEX16 (1ULL << 33)
-+#define AST_FORMAT_CODEC2 (1ULL << 34)
- /*! Raw mu-law data (G.711) */
- #define AST_FORMAT_TESTLAW (1ULL << 47)
- /*! Reserved bit - do not use */
---- /home/david/asterisk-1.8.9.0-orig/main/frame.c 2010-06-18 02:53:43.000000000 +0930
-+++ /home/david/asterisk-1.8.9.0-codec2/main/frame.c 2012-03-28 15:16:16.975581316 +1030
-@@ -102,6 +102,7 @@
- { AST_FORMAT_ADPCM, "adpcm" , 8000, "ADPCM", 40, 10, 300, 10, 20 }, /*!< codec_adpcm.c */
- { AST_FORMAT_SLINEAR, "slin", 8000, "16 bit Signed Linear PCM", 160, 10, 70, 10, 20, AST_SMOOTHER_FLAG_BE }, /*!< Signed linear */
- { AST_FORMAT_LPC10, "lpc10", 8000, "LPC10", 7, 20, 20, 20, 20 }, /*!< codec_lpc10.c */
-+ { AST_FORMAT_CODEC2, "codec2", 8000, "Codec 2", 7, 20, 20, 20, 20 }, /*!< codec_codec2.c */
- { AST_FORMAT_G729A, "g729", 8000, "G.729A", 10, 10, 230, 10, 20, AST_SMOOTHER_FLAG_G729 }, /*!< Binary commercial distribution */
- { AST_FORMAT_SPEEX, "speex", 8000, "SpeeX", 10, 10, 60, 10, 20 }, /*!< codec_speex.c */
- { AST_FORMAT_SPEEX16, "speex16", 16000, "SpeeX 16khz", 10, 10, 60, 10, 20 }, /*!< codec_speex.c */
-@@ -1475,6 +1476,9 @@
- samples = 22 * 8;
- samples += (((char *)(f->data.ptr))[7] & 0x1) * 8;
- break;
-+ case AST_FORMAT_CODEC2:
-+ samples = 160 * (f->datalen / 7);
-+ break;
- case AST_FORMAT_ULAW:
- case AST_FORMAT_ALAW:
- case AST_FORMAT_TESTLAW:
-@@ -1519,6 +1523,9 @@
- case AST_FORMAT_GSM:
- len = (samples / 160) * 33;
- break;
-+ case AST_FORMAT_CODEC2:
-+ len = (samples / 160) * 7;
-+ break;
- case AST_FORMAT_G729A:
- len = samples / 8;
- break;
---- /home/david/asterisk-1.8.9.0-orig/main/channel.c 2011-12-17 10:21:13.000000000 +1030
-+++ /home/david/asterisk-1.8.9.0-codec2/main/channel.c 2012-03-28 15:05:22.395293391 +1030
-@@ -1075,6 +1075,7 @@
- /*! Ick, LPC10 sounds terrible, but at least we have code for it, if you're tacky enough
- to use it */
- AST_FORMAT_LPC10,
-+ AST_FORMAT_CODEC2,
- /*! G.729a is faster than 723 and slightly less expensive */
- AST_FORMAT_G729A,
- /*! Down to G.723.1 which is proprietary but at least designed for voice */
---- /home/david/asterisk-1.8.9.0-orig/main/rtp_engine.c 2011-12-30 01:43:03.000000000 +1030
-+++ /home/david/asterisk-1.8.9.0-codec2/main/rtp_engine.c 2012-03-28 16:42:02.880872891 +1030
-@@ -101,6 +101,7 @@
- {{1, AST_FORMAT_SLINEAR}, "audio", "L16", 8000},
- {{1, AST_FORMAT_SLINEAR16}, "audio", "L16", 16000},
- {{1, AST_FORMAT_LPC10}, "audio", "LPC", 8000},
-+ {{1, AST_FORMAT_CODEC2}, "audio", "CODEC2", 8000},
- {{1, AST_FORMAT_G729A}, "audio", "G729", 8000},
- {{1, AST_FORMAT_G729A}, "audio", "G729A", 8000},
- {{1, AST_FORMAT_G729A}, "audio", "G.729", 8000},
-@@ -178,6 +179,7 @@
- [117] = {1, AST_FORMAT_SPEEX16},
- [118] = {1, AST_FORMAT_SLINEAR16}, /* 16 Khz signed linear */
- [121] = {0, AST_RTP_CISCO_DTMF}, /* Must be type 121 */
-+ [121] = {1, AST_FORMAT_CODEC2},
- };
-
- int ast_rtp_engine_register2(struct ast_rtp_engine *engine, struct ast_module *module)
+++ /dev/null
-/*
- * Codec 2 module for Asterisk.
- *
- * Credit: codec_gsm.c used as a starting point.
- *
- * Copyright (C) 2012 Ed W and David Rowe
- *
- * This program is free software, distributed under the terms of
- * the GNU General Public License Version 2. See the LICENSE file
- * at the top of the source tree.
- */
-
-/*! \file
- *
- * \brief Translate between signed linear and Codec 2
- *
- * \ingroup codecs
- */
-
-/*** MODULEINFO
- <support_level>core</support_level>
- ***/
-
-#include "asterisk.h"
-
-#include "asterisk/translate.h"
-#include "asterisk/config.h"
-#include "asterisk/module.h"
-#include "asterisk/utils.h"
-
-#include <codec2.h>
-
-#define BUFFER_SAMPLES 8000
-#define CODEC2_SAMPLES 160
-#define CODEC2_FRAME_LEN 7
-
-/* Sample frame data */
-
-#include "asterisk/slin.h"
-#include "ex_codec2.h"
-
-struct codec2_translator_pvt { /* both codec2tolin and codec2togsm */
- struct CODEC2 *codec2;
- short buf[BUFFER_SAMPLES]; /* lintocodec2, temporary storage */
-};
-
-static int codec2_new(struct ast_trans_pvt *pvt)
-{
- struct codec2_translator_pvt *tmp = pvt->pvt;
-
- tmp->codec2 = codec2_create(CODEC2_MODE_2400);
-
- return 0;
-}
-
-/*! \brief decode and store in outbuf. */
-static int codec2tolin_framein(struct ast_trans_pvt *pvt, struct ast_frame *f)
-{
- struct codec2_translator_pvt *tmp = pvt->pvt;
- int x;
- int16_t *dst = pvt->outbuf.i16;
- int flen = CODEC2_FRAME_LEN;
-
- for (x=0; x < f->datalen; x += flen) {
- unsigned char *src;
- int len;
- len = CODEC2_SAMPLES;
- src = f->data.ptr + x;
-
- codec2_decode(tmp->codec2, dst + pvt->samples, src);
-
- pvt->samples += CODEC2_SAMPLES;
- pvt->datalen += 2 * CODEC2_SAMPLES;
- }
- return 0;
-}
-
-/*! \brief store samples into working buffer for later decode */
-static int lintocodec2_framein(struct ast_trans_pvt *pvt, struct ast_frame *f)
-{
- struct codec2_translator_pvt *tmp = pvt->pvt;
-
- if (pvt->samples + f->samples > BUFFER_SAMPLES) {
- ast_log(LOG_WARNING, "Out of buffer space\n");
- return -1;
- }
- memcpy(tmp->buf + pvt->samples, f->data.ptr, f->datalen);
- pvt->samples += f->samples;
- return 0;
-}
-
-/*! \brief encode and produce a frame */
-static struct ast_frame *lintocodec2_frameout(struct ast_trans_pvt *pvt)
-{
- struct codec2_translator_pvt *tmp = pvt->pvt;
- int datalen = 0;
- int samples = 0;
-
- /* We can't work on anything less than a frame in size */
- if (pvt->samples < CODEC2_SAMPLES)
- return NULL;
- while (pvt->samples >= CODEC2_SAMPLES) {
- /* Encode a frame of data */
- codec2_encode(tmp->codec2, (unsigned char*)(pvt->outbuf.c + datalen), tmp->buf + samples);
- datalen += CODEC2_FRAME_LEN;
- samples += CODEC2_SAMPLES;
- pvt->samples -= CODEC2_SAMPLES;
- }
-
- /* Move the data at the end of the buffer to the front */
- if (pvt->samples)
- memmove(tmp->buf, tmp->buf + samples, pvt->samples * 2);
-
- return ast_trans_frameout(pvt, datalen, samples);
-}
-
-static void codec2_destroy_stuff(struct ast_trans_pvt *pvt)
-{
- struct codec2_translator_pvt *tmp = pvt->pvt;
- if (tmp->codec2)
- codec2_destroy(tmp->codec2);
-}
-
-static struct ast_translator codec2tolin = {
- .name = "codec2tolin",
- .srcfmt = AST_FORMAT_CODEC2,
- .dstfmt = AST_FORMAT_SLINEAR,
- .newpvt = codec2_new,
- .framein = codec2tolin_framein,
- .destroy = codec2_destroy_stuff,
- .sample = codec2_sample,
- .buffer_samples = BUFFER_SAMPLES,
- .buf_size = BUFFER_SAMPLES * 2,
- .desc_size = sizeof (struct codec2_translator_pvt ),
-};
-
-static struct ast_translator lintocodec2 = {
- .name = "lintocodec2",
- .srcfmt = AST_FORMAT_SLINEAR,
- .dstfmt = AST_FORMAT_CODEC2,
- .newpvt = codec2_new,
- .framein = lintocodec2_framein,
- .frameout = lintocodec2_frameout,
- .destroy = codec2_destroy_stuff,
- .sample = slin8_sample,
- .desc_size = sizeof (struct codec2_translator_pvt ),
- .buf_size = (BUFFER_SAMPLES * CODEC2_FRAME_LEN + CODEC2_SAMPLES - 1)/CODEC2_SAMPLES,
-};
-
-/*! \brief standard module glue */
-static int reload(void)
-{
- return AST_MODULE_LOAD_SUCCESS;
-}
-
-static int unload_module(void)
-{
- int res;
-
- res = ast_unregister_translator(&lintocodec2);
- if (!res)
- res = ast_unregister_translator(&codec2tolin);
-
- return res;
-}
-
-static int load_module(void)
-{
- int res;
-
- res = ast_register_translator(&codec2tolin);
- if (!res)
- res=ast_register_translator(&lintocodec2);
- else
- ast_unregister_translator(&codec2tolin);
- if (res)
- return AST_MODULE_LOAD_FAILURE;
- return AST_MODULE_LOAD_SUCCESS;
-}
-
-AST_MODULE_INFO(ASTERISK_GPL_KEY, AST_MODFLAG_DEFAULT, "Codec 2 Coder/Decoder",
- .load = load_module,
- .unload = unload_module,
- .reload = reload,
- );
+++ /dev/null
-/*! \file
- * \brief 8-bit raw data
- *
- * Copyright (C) 2012, 2012 Ed W and David Rowe
- *
- * Distributed under the terms of the GNU General Public License
- *
- */
-
-static uint8_t ex_codec2[] = {
- 0x3e,0x06,0x4a,0xbb,0x9e,0x40,0xc0
-};
-
-static struct ast_frame *codec2_sample(void)
-{
- static struct ast_frame f = {
- .frametype = AST_FRAME_VOICE,
- .subclass.codec = AST_FORMAT_CODEC2,
- .datalen = sizeof(ex_codec2),
- .samples = CODEC2_SAMPLES,
- .mallocd = 0,
- .offset = 0,
- .src = __PRETTY_FUNCTION__,
- .data.ptr = ex_codec2,
- };
-
- return &f;
-}
+++ /dev/null
-#!/bin/sh
-# Create patch for Codec 2 support inside Asterisk
-
-ORIG=~/asterisk-1.8.9.0-orig
-CODEC2=~/asterisk-1.8.9.0-codec2
-diff -ruN $ORIG/include/asterisk/frame.h $CODEC2/include/asterisk/frame.h > asterisk-codec2.patch
-diff -ruN $ORIG/main/frame.c $CODEC2/main/frame.c >> asterisk-codec2.patch
-diff -ruN $ORIG/main/channel.c $CODEC2/main/channel.c >> asterisk-codec2.patch
-diff -ruN $ORIG/main/rtp_engine.c $CODEC2/main/rtp_engine.c >> asterisk-codec2.patch
-
-
+++ /dev/null
-# -*- Autoconf -*-
-# Process this file with autoconf to produce a configure script.
-
-AC_PREREQ([2.59])
-AC_INIT(codec2, 0.2, david@rowetel.com)
-AM_INIT_AUTOMAKE
-
-# Checks for programs.
-AC_PROG_CC
-AC_PROG_LIBTOOL
-
-# Checks for libraries.
-# FIXME: Replace `main' with a function in `-lm':
-AC_CHECK_LIB([m], [main])
-
-# Checks for header files.
-AC_CHECK_HEADERS([stdlib.h string.h])
-
-# Checks for typedefs, structures, and compiler characteristics.
-
-# Checks for library functions.
-AC_FUNC_MALLOC
-AC_CHECK_FUNCS([floor pow sqrt])
-
-AC_CONFIG_FILES([Makefile src/Makefile unittest/Makefile])
-AC_OUTPUT
+++ /dev/null
-#! /bin/sh
-srcpath=$(dirname $0 2>/dev/null ) || srcpath="."
-$srcpath/configure "$@" --disable-shared --with-pic
-
+++ /dev/null
-s(n)=A_1cos(\omega_0+\phi_1)+A_2cos(2\omega_0+\phi_2)+...+A_Lcos(L\omega_0+\phi_L)
+++ /dev/null
-# Requires FLTK 1.3 & Portaudio V19
-
-FLTK_VER = $(shell fltk-config --api-version)
-ifneq ($(FLTK_VER),1.3)
-$(error Must use FLTK version 1.3, you have $(FLTK_VER))
-endif
-
-FLTK_CFLAGS += $(shell fltk-config --ldstaticflags)
-CFLAGS = -O3 -g -Wall
-LIBS = ../src/.libs/libcodec2.a -lm -lrt -lportaudio -pthread
-LC2POC_C = fl_fdmdv.cxx
-
-all: fl_fdmdv
-
-fl_fdmdv: Makefile $(LC2POC_C)
- g++ $(LC2POC_C) -I../src/ -o fl_fdmdv $(CFLAGS) $(FLTK_CFLAGS) $(LIBS)
-
-clean:
- rm -f fl_fdmdv
+++ /dev/null
-/*
- fl_fdmdv.cxx
- Created 14 June 2012
- David Rowe
-
- Fltk 1.3 based GUI program to prototype FDMDV & Codec 2 integration
- issues such as:
-
- + spectrum, waterfall, and other FDMDV GUI displays
- + integration with real time audio I/O using portaudio
- + what we do with audio when out of sync
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <unistd.h>
-
-#include <FL/Fl.H>
-#include <FL/Fl_Window.H>
-#include <FL/Fl_Box.H>
-#include <FL/fl_draw.H>
-#include <FL/Fl_Group.H>
-#include <FL/names.h>
-
-#include "portaudio.h"
-
-#include "fdmdv.h"
-#include "codec2.h"
-
-#define MIN_DB -40.0
-#define MAX_DB 0.0
-#define BETA 0.1 // constant for time averageing spectrum data
-#define MIN_HZ 0
-#define MAX_HZ 4000
-#define WATERFALL_SECS_Y 5 // number of seconds respresented by y axis of waterfall
-#define DT 0.02 // time between samples
-#define FS 8000 // FDMDV modem sample rate
-
-#define SCATTER_MEM (FDMDV_NSYM)*50
-#define SCATTER_X_MAX 3.0
-#define SCATTER_Y_MAX 3.0
-
-// main window params
-
-#define W 1200
-#define W3 (W/3)
-#define H 600
-#define H2 (H/2)
-#define SP 20
-
-// sound card
-
-#define SAMPLE_RATE 48000 /* 48 kHz sampling rate rec. as we
- can trust accuracy of sound
- card */
-#define N8 FDMDV_NOM_SAMPLES_PER_FRAME /* processing buffer size at 8 kHz */
-#define MEM8 (FDMDV_OS_TAPS/FDMDV_OS)
-#define N48 (N8*FDMDV_OS) /* processing buffer size at 48 kHz */
-#define NUM_CHANNELS 2 /* I think most sound cards prefer stereo,
- we will convert to mono */
-
-#define BITS_PER_CODEC_FRAME (2*FDMDV_BITS_PER_FRAME)
-#define BYTES_PER_CODEC_FRAME (BITS_PER_CODEC_FRAME/8)
-
-// forward class declarations
-
-class Spectrum;
-class Waterfall;
-class Scatter;
-class Scalar;
-
-// Globals --------------------------------------
-
-char *fin_name = NULL;
-char *fout_name = NULL;
-char *sound_dev_name = NULL;
-FILE *fin = NULL;
-FILE *fout = NULL;
-struct FDMDV *fdmdv;
-struct CODEC2 *codec2;
-float av_mag[FDMDV_NSPEC]; // shared between a few classes
-
-// GUI variables --------------------------------
-
-Fl_Group *agroup;
-Fl_Window *window;
-Fl_Window *zoomSpectrumWindow = NULL;
-Fl_Window *zoomWaterfallWindow = NULL;
-Spectrum *aSpectrum;
-Spectrum *aZoomedSpectrum;
-Waterfall *aWaterfall;
-Waterfall *aZoomedWaterfall;
-Scatter *aScatter;
-Scalar *aTimingEst;
-Scalar *aFreqEst;
-Scalar *aSNR;
-int zoom_spectrum = 0;
-
-// Main processing loop states ------------------
-
-float Ts = 0.0;
-short input_buf[2*FDMDV_NOM_SAMPLES_PER_FRAME];
-int n_input_buf = 0;
-int nin = FDMDV_NOM_SAMPLES_PER_FRAME;
-short *output_buf;
-int n_output_buf = 0;
-int codec_bits[2*FDMDV_BITS_PER_FRAME];
-int state = 0;
-
-// Portaudio states -----------------------------
-
-PaStream *stream = NULL;
-PaError err;
-
-typedef struct {
- float in48k[FDMDV_OS_TAPS + N48];
- float in8k[MEM8 + N8];
-} paCallBackData;
-
-// Class for each window type ------------------
-
-class Spectrum: public Fl_Box {
-protected:
- int handle(int event) {
-
- // detect a left mouse down if inside the spectrum window
-
- if ((event == FL_NO_EVENT) && (Fl::event_button() == 1)) {
- if ((Fl::event_x() > x()) && (Fl::event_x() < (x() + w())) &&
- (Fl::event_y() > y()) && (Fl::event_y() < (y() + h()))) {
-
- // show zoomed spectrum window
-
- zoomSpectrumWindow->show();
- }
-
- }
- return 0;
- }
-
- void draw() {
- float x_px_per_point = 0.0;
- float y_px_per_dB = 0.0;
- int i, x1, y1, x2, y2;
- float mag1, mag2;
- char label[20];
- float px_per_hz;
-
- Fl_Box::draw();
- fl_color(FL_BLACK);
- fl_rectf(x(),y(),w(),h());
- fl_color(FL_GREEN);
- fl_line_style(FL_SOLID);
-
- fl_push_clip(x(),y(),w(),h());
- //printf("%d %d\n", w(), h());
- x_px_per_point = (float)w()/FDMDV_NSPEC;
- y_px_per_dB = (float)h()/(MAX_DB - MIN_DB);
-
- // plot spectrum
-
- for(i=0; i<FDMDV_NSPEC-1; i++) {
- mag1 = av_mag[i];
- mag2 = av_mag[i+1];
-
- x1 = x() + i*x_px_per_point;
- y1 = y() + -mag1*y_px_per_dB;
- x2 = x() + (i+1)*x_px_per_point;
- y2 = y() + -mag2*y_px_per_dB;
- fl_line(x1,y1,x2,y2);
- }
-
- // y axis graticule
-
- fl_line_style(FL_DOT);
- for(i=MIN_DB; i<MAX_DB; i+=10) {
- x1 = x();
- y1 = y() + -i*y_px_per_dB;
- x2 = x() + w();
- y2 = y1;
- //printf("%d %d %d %d\n", x1, y1, x2, y2);
- fl_line(x1,y1,x2,y2);
- sprintf(label, "%d", i);
- fl_draw(label, x1, y1);
- }
-
- // x axis graticule
-
- px_per_hz = (float)w()/(MAX_HZ-MIN_HZ);
- fl_line_style(FL_DOT);
- for(i=500; i<MAX_HZ; i+=500) {
- x1 = x() + i*px_per_hz;
- y1 = y();
- x2 = x1;
- y2 = y() + h();
- //printf("i=%d %d %d %d %d\n", i, x1, y1, x2, y2);
- fl_line(x1,y1,x2,y2);
- sprintf(label, "%d", i);
- fl_draw(label, x1, y2);
- }
-
- fl_pop_clip();
- }
-
-public:
- Spectrum(int x, int y, int w, int h): Fl_Box(x, y, w, h, "Spectrum")
- {
- align(FL_ALIGN_TOP);
- labelsize(10);
- };
-
-};
-
-
-/*
-
- Notes:
-
- The height h() pixels represents WATERFALL_SECS_Y of data. Every DT
- seconds we get a vector of FDMDV_NSPEC spectrum samples which we use
- to update the last row. The height of each row is dy pixels, which
- maps to DT seconds. We call each dy high rectangle of pixels a
- block.
-
-*/
-
-class Waterfall: public Fl_Box {
-protected:
-
- int prev_w, prev_h;
- unsigned *pixel_buf;
- unsigned heatmap_lut[256];
- int greyscale;
-
- void new_pixel_buf(int w, int h) {
- int buf_sz, i;
-
- prev_w = w; prev_h = h;
- buf_sz = h*w;
- pixel_buf = new unsigned[buf_sz];
- for(i=0; i<buf_sz; i++)
- pixel_buf[i] = 0;
- }
-
- int handle(int event) {
-
- // detect a left mouse down if inside the window
-
- if ((event == FL_NO_EVENT) && (Fl::event_button() == 1)) {
- if ((Fl::event_x() > x()) && (Fl::event_x() < (x() + w())) &&
- (Fl::event_y() > y()) && (Fl::event_y() < (y() + h()))) {
-
- // show zoomed spectrum window
-
- zoomWaterfallWindow->show();
- }
-
- }
- return 0;
- }
-
- // map val to a rgb colour
- // from http://eddiema.ca/2011/01/21/c-sharp-heatmaps/
-
- unsigned heatmap(float val, float min, float max) {
- unsigned r = 0;
- unsigned g = 0;
- unsigned b = 0;
-
- val = (val - min) / (max - min);
- if(val <= 0.2) {
- b = (unsigned)((val / 0.2) * 255);
- } else if(val > 0.2 && val <= 0.7) {
- b = (unsigned)((1.0 - ((val - 0.2) / 0.5)) * 255);
- }
- if(val >= 0.2 && val <= 0.6) {
- g = (unsigned)(((val - 0.2) / 0.4) * 255);
- } else if(val > 0.6 && val <= 0.9) {
- g = (unsigned)((1.0 - ((val - 0.6) / 0.3)) * 255);
- }
- if(val >= 0.5) {
- r = (unsigned)(((val - 0.5) / 0.5) * 255);
- }
-
- //printf("%f %x %x %x\n", val, r, g, b);
-
- return (b << 16) + (g << 8) + r;
- }
-
- void draw() {
- float spec_index_per_px, intensity_per_dB;
- int px_per_sec;
- int index, dy, dy_blocks, bytes_in_row_of_blocks, b;
- int px, py, intensity;
- unsigned *last_row, *pdest, *psrc;
-
- /* detect resizing of window */
-
- if ((h() != prev_h) || (w() != prev_w)) {
- delete pixel_buf;
- new_pixel_buf(w(), h());
- }
-
- Fl_Box::draw();
-
- // determine dy, the height of one "block"
-
- px_per_sec = (float)h()/WATERFALL_SECS_Y;
- dy = DT*px_per_sec;
-
- // number of dy high blocks in spectrogram
-
- dy_blocks = h()/dy;
-
- // shift previous bit map
-
- bytes_in_row_of_blocks = dy*w()*sizeof(unsigned);
-
- for(b=0; b<dy_blocks-1; b++) {
- pdest = pixel_buf + b*w()*dy;
- psrc = pixel_buf + (b+1)*w()*dy;
- memcpy(pdest, psrc, bytes_in_row_of_blocks);
- }
-
- // create a new row of blocks at bottom
-
- spec_index_per_px = (float)FDMDV_NSPEC/(float)w();
- intensity_per_dB = (float)256/(MAX_DB - MIN_DB);
- last_row = pixel_buf + dy*(dy_blocks - 1)*w();
-
- for(px=0; px<w(); px++) {
- index = px*spec_index_per_px;
- intensity = intensity_per_dB * (av_mag[index] - MIN_DB);
- if (intensity > 255) intensity = 255;
- if (intensity < 0) intensity = 0;
-
- if (greyscale) {
- for(py=0; py<dy; py++)
- last_row[px+py*w()] = intensity<<8;
- }
- else {
- for(py=0; py<dy; py++)
- last_row[px+py*w()] = heatmap_lut[intensity];
- }
- }
-
- // update bit map
-
- fl_draw_image((uchar*)pixel_buf, x(), y(), w(), h(), 4, 0);
-
- }
-
-public:
-
- Waterfall(int x, int y, int w, int h): Fl_Box(x, y, w, h, "Waterfall")
- {
- int i;
-
- for(i=0; i<255; i++) {
- heatmap_lut[i] = heatmap((float)i, 0.0, 255.0);
- }
- greyscale = 0;
-
- align(FL_ALIGN_TOP);
- labelsize(10);
- new_pixel_buf(w,h);
- };
-
- ~Waterfall() {
- delete pixel_buf;
- }
-};
-
-
-class Scatter: public Fl_Box {
-protected:
- COMP mem[SCATTER_MEM];
- COMP new_samples[FDMDV_NSYM];
- int prev_w, prev_h, prev_x, prev_y;
-
- void draw() {
- float x_scale;
- float y_scale;
- int i, j, x1, y1;
-
- Fl_Box::draw();
-
- /* detect resizing of window */
-
- if ((h() != prev_h) || (w() != prev_w) || (x() != prev_x) || (y() != prev_y)) {
- fl_color(FL_BLACK);
- fl_rectf(x(),y(),w(),h());
- prev_h = h(); prev_w = w(); prev_x = x(); prev_y = y();
- }
-
- fl_push_clip(x(),y(),w(),h());
-
- x_scale = w()/SCATTER_X_MAX;
- y_scale = h()/SCATTER_Y_MAX;
-
- // erase last samples
-
- fl_color(FL_BLACK);
- for(i=0; i<FDMDV_NSYM; i++) {
- x1 = x_scale * mem[i].real + x() + w()/2;
- y1 = y_scale * mem[i].imag + y() + h()/2;
- fl_point(x1, y1);
- mem[i] = mem[i+FDMDV_NSYM];
- }
-
- // shift memory
-
- for(i=FDMDV_NSYM; i<SCATTER_MEM-FDMDV_NSYM; i++) {
- mem[i] = mem[i+FDMDV_NSYM];
- }
-
- // draw new samples
-
- fl_color(FL_GREEN);
- for(i=SCATTER_MEM-FDMDV_NSYM, j=0; i<SCATTER_MEM; i++,j++) {
- x1 = x_scale * new_samples[j].real + x() + w()/2;
- y1 = y_scale * new_samples[j].imag + y() + h()/2;
- fl_point(x1, y1);
- mem[i] = new_samples[j];
- }
- fl_pop_clip();
- }
-
-public:
- Scatter(int x, int y, int w, int h): Fl_Box(x, y, w, h, "Scatter")
- {
- int i;
-
- align(FL_ALIGN_TOP);
- labelsize(10);
-
- for(i=0; i<SCATTER_MEM; i++) {
- mem[i].real = 0.0;
- mem[i].imag = 0.0;
- }
-
- prev_w = 0; prev_h = 0; prev_x = 0; prev_y = 0;
- };
-
- void add_new_samples(COMP samples[]) {
- int i;
-
- for(i=0; i<FDMDV_NSYM; i++)
- new_samples[i] = samples[i];
- }
-
-};
-
-
-// general purpose way of plotting scalar values that are
-// updated once per frame
-
-class Scalar: public Fl_Box {
-protected:
- int x_max, y_max;
- float *mem; /* array of x_max samples */
- float new_sample;
- int index, step;
- int prev_w, prev_h, prev_x, prev_y;
-
- int clip(int y1) {
- if (y1 > (h()/2 - 10))
- y1 = h()/2 - 10;
- if (y1 < -(h()/2 - 10))
- y1 = -(h()/2 - 10);
- return y1;
- }
-
- void draw() {
- float x_scale;
- float y_scale;
- int i, x1, y1, x2, y2;
- char label[100];
-
- Fl_Box::draw();
-
- /* detect resizing of window */
-
- if ((h() != prev_h) || (w() != prev_w) || (x() != prev_x) || (y() != prev_y)) {
- fl_color(FL_BLACK);
- fl_rectf(x(),y(),w(),h());
- prev_h = h(); prev_w = w(); prev_x = x(); prev_y = y();
- }
-
- fl_push_clip(x(),y(),w(),h());
-
- x_scale = (float)w()/x_max;
- y_scale = (float)h()/(2.0*y_max);
-
- // erase last sample
-
- fl_color(FL_BLACK);
- x1 = x_scale * index + x();
- y1 = y_scale * mem[index];
- y1 = clip(y1);
- y1 = y() + h()/2 - y1;
- fl_point(x1, y1);
-
- // draw new sample
-
- fl_color(FL_GREEN);
- x1 = x_scale * index + x();
- y1 = y_scale * new_sample;
- y1 = clip(y1);
- y1 = y() + h()/2 - y1;
- fl_point(x1, y1);
- mem[index] = new_sample;
-
- index++;
- if (index >= x_max)
- index = 0;
-
- // y axis graticule
-
- step = 10;
-
- while ((2.0*y_max/step) > 10)
- step *= 2.0;
- while ((2.0*y_max/step) < 4)
- step /= 2.0;
-
- fl_color(FL_DARK_GREEN);
- fl_line_style(FL_DOT);
- for(i=-y_max; i<y_max; i+=step) {
- x1 = x();
- y1 = y() + h()/2 - i*y_scale;
- x2 = x() + w();
- y2 = y1;
- fl_line(x1,y1,x2,y2);
- }
-
- // y axis graticule labels
-
- fl_color(FL_GREEN);
- fl_line_style(FL_SOLID);
- for(i=-y_max; i<y_max; i+=step) {
- x1 = x();
- y1 = y() + h()/2 - i*y_scale;
- sprintf(label, "%d", i);
- fl_draw(label, x1, y1);
- }
- fl_pop_clip();
- }
-
-public:
- Scalar(int x, int y, int w, int h, int x_max_, int y_max_, const char name[]): Fl_Box(x, y, w, h, name)
- {
- int i;
-
- align(FL_ALIGN_TOP);
- labelsize(10);
-
- x_max = x_max_; y_max = y_max_;
- mem = new float[x_max];
- for(i=0; i<x_max; i++) {
- mem[i] = 0.0;
- }
-
- prev_w = 0; prev_h = 0; prev_x = 0; prev_y = 0;
- index = 0;
- };
-
- ~Scalar() {
- delete mem;
- }
-
- void add_new_sample(float sample) {
- new_sample = sample;
- }
-
-};
-
-
-// update average of each spectrum point
-
-void new_data(float mag_dB[]) {
- int i;
-
- for(i=0; i<FDMDV_NSPEC; i++)
- av_mag[i] = (1.0 - BETA)*av_mag[i] + BETA*mag_dB[i];
-}
-
-
-/*------------------------------------------------------------------*\
-
- FUNCTION: per_frame_rx_processing()
- AUTHOR..: David Rowe
- DATE....: July 2012
-
- Called every rx frame to take a buffer of input modem samples and
- convert them to a buffer of output speech samples.
-
- The sample source could be a sound card or file. The sample source
- supplies a fixed number of samples with each call. However
- fdmdv_demod requires a variable number of samples for each call.
- This function will buffer as appropriate and call fdmdv_demod with
- the correct number of samples.
-
- The processing sequence is:
-
- collect demod input samples from sound card 1 A/D
- while we have enough samples:
- demod samples into bits
- decode bits into speech samples
- output a buffer of speech samples to sound card 2 D/A
-
- Note that sound card 1 and sound card 2 will have slightly different
- sample rates, as their sample clocks are not syncronised. We
- effectively lock the system to the demod A/D (sound card 1) sample
- rate. This ensures the demod gets a continuous sequence of samples,
- maintaining sync. Sample underflow or overflow will instead occur on
- the sound card 2 D/A. This is acceptable as a buffer of lost or
- extra speech samples is unlikely to be noticed.
-
- The situation is actually a little more complex than that. Through
- the demod timing estimation the buffers supplied to sound card D/A 2
- are effectively clocked at the remote modulator sound card D/A clock
- rate. We slip/gain buffers supplied to sound card 2 to compensate.
-
- The current demod handles varying clock rates by having a variable
- number of input samples, e.g. 120 160 (nominal) or 200. However the
- A/D always delivers a fixed number of samples.
-
- So we currently need some logic between the A/D and the demod:
- + A/D delivers fixed number of samples
- + demod processes a variable number of samples
- + this means we run demod 0,1 or 2 times, depending
- on number of buffered A/D samples
- + demod always outputs 1 frame of bits
- + so run demod and speech decoder 0, 1 or 2 times
-
- The ouput of the demod is codec voice data so it's OK if we miss or
- repeat a frame every now and again.
-
- TODOs:
-
- + this might work with arbitrary input and output buffer lengths,
- 0,1, or 2 only apply if we are inputting the nominal number of
- samples on every call.
-
- + so the I/O buffer sizes might not matter, as long as they of
- reasonable size (say twice the nominal size).
-
-\*------------------------------------------------------------------*/
-
-void per_frame_rx_processing(short output_buf[], /* output buf of decoded speech samples */
- int *n_output_buf, /* how many samples currently in output_buf[] */
- int codec_bits[], /* current frame of bits for decoder */
- short input_buf[], /* input buf of modem samples input to demod */
- int *n_input_buf, /* how many samples currently in input_buf[] */
- int *nin, /* amount of samples demod needs for next call */
- int *state, /* used to collect codec_bits[] halves */
- struct CODEC2 *c2 /* Codec 2 states */
- )
-{
- struct FDMDV_STATS stats;
- int sync_bit;
- float rx_fdm[FDMDV_MAX_SAMPLES_PER_FRAME];
- int rx_bits[FDMDV_BITS_PER_FRAME];
- uchar packed_bits[BYTES_PER_CODEC_FRAME];
- float rx_spec[FDMDV_NSPEC];
- int i, nin_prev, bit, byte;
- int next_state;
-
- assert(*n_input_buf <= (2*FDMDV_NOM_SAMPLES_PER_FRAME));
-
- /*
- This while loop will run the demod 0, 1 (nominal) or 2 times:
-
- 0: when tx sample clock runs faster than rx, occasionally we
- will run out of samples
-
- 1: normal, run decoder once, every 2nd frame output a frame of
- speech samples to D/A
-
- 2: when tx sample clock runs slower than rx, occasionally we will
- have enough samples to run demod twice.
-
- With a +/- 10 Hz sample clock difference at FS=8000Hz (+/- 1250
- ppm), case 0 or 1 occured about once every 30 seconds. This is
- no problem for the decoded audio.
- */
-
- while(*n_input_buf >= *nin) {
-
- // demod per frame processing
-
- for(i=0; i<*nin; i++)
- rx_fdm[i] = (float)input_buf[i]/FDMDV_SCALE;
- nin_prev = *nin;
- fdmdv_demod(fdmdv, rx_bits, &sync_bit, rx_fdm, nin);
- *n_input_buf -= nin_prev;
- assert(*n_input_buf >= 0);
-
- // shift input buffer
-
- for(i=0; i<*n_input_buf; i++)
- input_buf[i] = input_buf[i+nin_prev];
-
- // compute rx spectrum & get demod stats, and update GUI plot data
-
- fdmdv_get_rx_spectrum(fdmdv, rx_spec, rx_fdm, nin_prev);
- fdmdv_get_demod_stats(fdmdv, &stats);
- new_data(rx_spec);
- aScatter->add_new_samples(stats.rx_symbols);
- aTimingEst->add_new_sample(stats.rx_timing);
- aFreqEst->add_new_sample(stats.foff);
- aSNR->add_new_sample(stats.snr_est);
-
- /*
- State machine to:
-
- + Mute decoded audio when out of sync. The demod is synced
- when we are using the fine freq estimate and SNR is above
- a thresh.
-
- + Decode codec bits only if we have a 0,1 sync bit
- sequence. Collects two frames of demod bits to decode
- one frame of codec bits.
- */
-
- next_state = *state;
- switch (*state) {
- case 0:
- /* mute output audio when out of sync */
-
- if (*n_output_buf < 2*codec2_samples_per_frame(c2) - N8) {
- for(i=0; i<N8; i++)
- output_buf[*n_output_buf + i] = 0;
- *n_output_buf += N8;
- }
- assert(*n_output_buf <= (2*codec2_samples_per_frame(c2)));
-
- if ((stats.fest_coarse_fine == 1) && (stats.snr_est > 3.0))
- next_state = 1;
-
- break;
- case 1:
- if (sync_bit == 0) {
- next_state = 2;
-
- /* first half of frame of codec bits */
-
- memcpy(codec_bits, rx_bits, FDMDV_BITS_PER_FRAME*sizeof(int));
- }
- else
- next_state = 1;
-
- if (stats.fest_coarse_fine == 0)
- next_state = 0;
-
- break;
- case 2:
- next_state = 1;
-
- if (stats.fest_coarse_fine == 0)
- next_state = 0;
-
- if (sync_bit == 1) {
- /* second half of frame of codec bits */
-
- memcpy(&codec_bits[FDMDV_BITS_PER_FRAME], rx_bits, FDMDV_BITS_PER_FRAME*sizeof(int));
-
- /* pack bits, MSB received first */
-
- bit = 7; byte = 0;
- memset(packed_bits, 0, BYTES_PER_CODEC_FRAME);
- for(i=0; i<BITS_PER_CODEC_FRAME; i++) {
- packed_bits[byte] |= (codec_bits[i] << bit);
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == BYTES_PER_CODEC_FRAME);
-
- /* add decoded speech to end of output buffer */
-
- if (*n_output_buf <= codec2_samples_per_frame(c2)) {
- codec2_decode(c2, &output_buf[*n_output_buf], packed_bits);
- *n_output_buf += codec2_samples_per_frame(c2);
- }
- assert(*n_output_buf <= (2*codec2_samples_per_frame(c2)));
-
- }
- break;
- }
- *state = next_state;
- }
-}
-
-
-/*
- Redraw windows every DT seconds.
-*/
-
-void update_gui(int nin, float *Ts) {
-
- *Ts += (float)nin/FS;
-
- *Ts += (float)nin/FS;
- if (*Ts >= DT) {
- *Ts -= DT;
- if (!zoomSpectrumWindow->shown() && !zoomWaterfallWindow->shown()) {
- aSpectrum->redraw();
- aWaterfall->redraw();
- aScatter->redraw();
- aTimingEst->redraw();
- aFreqEst->redraw();
- aSNR->redraw();
- }
- if (zoomSpectrumWindow->shown())
- aZoomedSpectrum->redraw();
- if (zoomWaterfallWindow->shown())
- aZoomedWaterfall->redraw();
- }
-}
-
-
-/*
- idle() is the FLTK function that gets continusouly called when FLTK
- is not doing GUI work. We use this function for providing file
- input to update the GUI when simulating real time operation.
-*/
-
-void idle(void*) {
- int ret, i;
-
- if (fin_name != NULL) {
- ret = fread(&input_buf[n_input_buf],
- sizeof(short),
- FDMDV_NOM_SAMPLES_PER_FRAME,
- fin);
- n_input_buf += FDMDV_NOM_SAMPLES_PER_FRAME;
-
- per_frame_rx_processing(output_buf, &n_output_buf,
- codec_bits,
- input_buf, &n_input_buf,
- &nin, &state, codec2);
-
- if (fout_name != NULL) {
- if (n_output_buf >= N8) {
- ret = fwrite(output_buf, sizeof(short), N8, fout);
- n_output_buf -= N8;
- assert(n_output_buf >= 0);
-
- /* shift speech sample output buffer */
-
- for(i=0; i<n_output_buf; i++)
- output_buf[i] = output_buf[i+N8];
- }
- }
- }
-
- update_gui(nin, &Ts);
-
- // simulate time delay from real world A/D input, and pause betwen
- // screen updates
-
- usleep(20000);
-}
-
-
-/*
- This routine will be called by the PortAudio engine when audio is
- available.
-*/
-
-static int callback( const void *inputBuffer, void *outputBuffer,
- unsigned long framesPerBuffer,
- const PaStreamCallbackTimeInfo* timeInfo,
- PaStreamCallbackFlags statusFlags,
- void *userData )
-{
- paCallBackData *cbData = (paCallBackData*)userData;
- uint i;
- short *rptr = (short*)inputBuffer;
- short *wptr = (short*)outputBuffer;
- float *in8k = cbData->in8k;
- float *in48k = cbData->in48k;
- float out8k[N8];
- float out48k[N48];
- short out48k_short[N48];
-
- (void) timeInfo;
- (void) statusFlags;
-
- assert(inputBuffer != NULL);
-
- /* Convert input model samples from 48 to 8 kHz ------------ */
-
- /* just use left channel */
-
- for(i=0; i<framesPerBuffer; i++,rptr+=2)
- in48k[i+FDMDV_OS_TAPS] = *rptr;
-
- /* downsample and update filter memory */
-
- fdmdv_48_to_8(out8k, &in48k[FDMDV_OS_TAPS], N8);
- for(i=0; i<FDMDV_OS_TAPS; i++)
- in48k[i] = in48k[i+framesPerBuffer];
-
- /* run demod, decoder and update GUI info ------------------ */
-
- for(i=0; i<N8; i++)
- input_buf[n_input_buf+i] = (short)out8k[i];
- n_input_buf += FDMDV_NOM_SAMPLES_PER_FRAME;
-
- per_frame_rx_processing(output_buf, &n_output_buf,
- codec_bits,
- input_buf, &n_input_buf,
- &nin, &state, codec2);
-
- /* if demod out of sync copy input audio from A/D to aid in tuning */
-
- if (n_output_buf >= N8) {
- if (state == 0) {
- for(i=0; i<N8; i++)
- in8k[MEM8+i] = out8k[i]; /* A/D signal */
- }
- else {
- for(i=0; i<N8; i++)
- in8k[MEM8+i] = output_buf[i]; /* decoded spech */
- }
- n_output_buf -= N8;
- }
- assert(n_output_buf >= 0);
-
- /* shift speech samples in output buffer */
-
- for(i=0; i<(uint)n_output_buf; i++)
- output_buf[i] = output_buf[i+N8];
-
- /* Convert output speech to 48 kHz sample rate ------------- */
-
- /* upsample and update filter memory */
-
- fdmdv_8_to_48(out48k, &in8k[MEM8], N8);
- for(i=0; i<MEM8; i++)
- in8k[i] = in8k[i+N8];
-
- assert(outputBuffer != NULL);
-
- /* write signal to both channels */
-
- for(i=0; i<N48; i++)
- out48k_short[i] = (short)out48k[i];
- for(i=0; i<framesPerBuffer; i++,wptr+=2) {
- wptr[0] = out48k_short[i];
- wptr[1] = out48k_short[i];
- }
-
- return paContinue;
-}
-
-
-int arg_callback(int argc, char **argv, int &i) {
- if (argv[i][1] == 'i') {
- if ((i+1) >= argc)
- return 0;
- fin_name = argv[i+1];
- i += 2;
- return 2;
- }
- if (argv[i][1] == 'o') {
- if ((i+1) >= argc)
- return 0;
- fout_name = argv[i+1];
- i += 2;
- return 2;
- }
- if (argv[i][1] == 's') {
- if ((i+1) >= argc)
- return 0;
- sound_dev_name = argv[i+1];
- i += 2;
- return 2;
- }
- return 0;
-}
-
-/*------------------------------------------------------------*\
-
- MAIN
-
-\*------------------------------------------------------------*/
-
-int main(int argc, char **argv) {
- int ret;
- int i;
- PaStreamParameters inputParameters, outputParameters;
- paCallBackData cbData;
-
- i = 1;
- Fl::args(argc,argv,i,arg_callback);
-
- if (argc == 1) {
- printf("usage: %s [-i inputFdmdvRawFile] [-o outputRawSoundFile] [-s inputSoundDevice]\n", argv[0]);
- exit(0);
- }
-
- if (fin_name != NULL) {
- fin = fopen(fin_name,"rb");
- if (fin == NULL) {
- fprintf(stderr, "Error opening input fdmdv raw file %s\n", fin_name);
- exit(1);
- }
- }
-
- if (fout_name != NULL) {
- fout = fopen(fout_name,"wb");
- if (fout == NULL) {
- fprintf(stderr, "Error opening output speech raw file %s\n", fout_name);
- exit(1);
- }
- }
-
- for(i=0; i<FDMDV_NSPEC; i++)
- av_mag[i] = -40.0;
-
- fdmdv = fdmdv_create();
- codec2 = codec2_create(CODEC2_MODE_1400);
- output_buf = (short*)malloc(2*sizeof(short)*codec2_samples_per_frame(codec2));
-
- /*------------------------------------------------------------------------*\
-
- Init Sound Card I/O
-
- \*------------------------------------------------------------------------*/
-
- if (sound_dev_name != NULL) {
- for(i=0; i<MEM8; i++)
- cbData.in8k[i] = 0.0;
- for(i=0; i<FDMDV_OS_TAPS; i++)
- cbData.in48k[i] = 0.0;
-
- err = Pa_Initialize();
- if( err != paNoError ) goto pa_error;
- inputParameters.device = Pa_GetDefaultInputDevice(); /* default input device */
- if (inputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default input device.\n");
- goto pa_error;
- }
- inputParameters.channelCount = NUM_CHANNELS; /* stereo input */
- inputParameters.sampleFormat = paInt16;
- inputParameters.suggestedLatency = Pa_GetDeviceInfo( inputParameters.device )->defaultLowInputLatency;
- inputParameters.hostApiSpecificStreamInfo = NULL;
-
- outputParameters.device = Pa_GetDefaultOutputDevice(); /* default output device */
- if (outputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default output device.\n");
- goto pa_error;
- }
- outputParameters.channelCount = NUM_CHANNELS; /* stereo output */
- outputParameters.sampleFormat = paInt16;
- outputParameters.suggestedLatency = Pa_GetDeviceInfo( outputParameters.device )->defaultLowOutputLatency;
- outputParameters.hostApiSpecificStreamInfo = NULL;
-
- err = Pa_OpenStream(
- &stream,
- &inputParameters,
- &outputParameters,
- SAMPLE_RATE,
- N48,
- paClipOff,
- callback,
- &cbData);
-
- if( err != paNoError ) goto pa_error;
- }
-
- /*------------------------------------------------------------------------*\
-
- Init GUI
-
- \*------------------------------------------------------------------------*/
-
- // recommended to prevent dithering and stopped display being
- // covered by black flickering squares
-
- Fl::visual(FL_RGB);
-
- // set up main window
-
- window = new Fl_Window(W, SP+H2+SP+SP+H2+SP, "fl_fmdv");
- //window->size_range(100, 100);
- //window->resizable();
- aSpectrum = new Spectrum(SP, SP, W3-2*SP, H2);
- aWaterfall = new Waterfall(SP, SP+H2+SP+SP, W3-2*SP, H2);
- aScatter = new Scatter(W3+SP, SP, W3-2*SP, H2);
- aTimingEst = new Scalar(W3+SP, SP+H2+SP+SP, W3-2*SP, H2, 100, 80, "Timing Est");
- aFreqEst = new Scalar(2*W3+SP, SP, W3-2*SP, H2, 100, 100, "Frequency Est");
- aSNR = new Scalar(2*W3+SP, SP+H2+SP+SP, W3-2*SP, H2, 100, 20, "SNR");
-
- Fl::add_idle(idle);
-
- window->end();
-
- // set up zoomed spectrum window
-
- zoomSpectrumWindow = new Fl_Window(W, H, "Spectrum");
- aZoomedSpectrum = new Spectrum(SP, SP, W-2*SP, H-2*SP);
- zoomSpectrumWindow->end();
-
- // set up zoomed waterfall window
-
- zoomWaterfallWindow = new Fl_Window(W, H, "Waterfall");
- aZoomedWaterfall = new Waterfall(SP, SP, W-2*SP, H-2*SP);
- zoomWaterfallWindow->end();
-
- if (sound_dev_name != NULL) {
- err = Pa_StartStream( stream );
- if( err != paNoError ) goto pa_error;
- }
-
- // show the main window and start running
-
- window->show(argc, argv);
- Fl::run();
-
- if (sound_dev_name != NULL) {
- err = Pa_StopStream( stream );
- if( err != paNoError ) goto pa_error;
- Pa_CloseStream( stream );
- Pa_Terminate();
- }
-
- fdmdv_destroy(fdmdv);
- codec2_destroy(codec2);
- free(output_buf);
-
- if (fin_name != NULL)
- fclose(fin);
- if (fout_name != NULL)
- fclose(fout);
-
- return ret;
-
- // Portaudio error handling
-
-pa_error:
- if( stream ) {
- Pa_AbortStream( stream );
- Pa_CloseStream( stream );
- }
- Pa_Terminate();
- fprintf( stderr, "An error occured while using the portaudio stream\n" );
- fprintf( stderr, "Error number: %d\n", err );
- fprintf( stderr, "Error message: %s\n", Pa_GetErrorText( err ) );
- return -1;
-}
+++ /dev/null
-README.txt
-For codec2/octave directory
-Created 24 June 2012 by David Rowe
-
-1/ To support some of the Octave scripts (in particular fdmdv) in this
- directory the following Octave packages need to be installed:
-
- control image miscellaneous optim signal specfun struct
-
-2/ Download these tar balls from:
-
- http://octave.sourceforge.net/packages.php
-
-3/ Install each package from the Octave command line with:
-
- octave:3> pkg install package_file_name.tar.gz
-
+++ /dev/null
-% av_imp.m
-% David Rowe Aug 2012
-% Averages the impulse response samples
-
-function imp = av_imp(imp_filename, period_in_secs, st, en)
- f = fopen(imp_filename,"rb");
- s = fread(f, Inf, "short")';
-
- Fs = 8000;
- n = period_in_secs * Fs;
-
- [r c] = size(s);
-
- imp = zeros(1,n);
- for i=1:n:c-n
- imp = imp + s(i:i+n-1);
- endfor
-
- % user supplies start and end samples after viweing plot
-
- if (nargin == 4)
- imp = imp(st:en);
- end
-
- % normalise
-
- imp /= sqrt(sum(imp .^ 2));
-
- [h w] = freqz(imp, 1, 4000);
-
- figure(1);
- clf;
- plot(imp);
-
- figure(2);
- clf;
- subplot(211)
- plot(10*log10(abs(h)))
- subplot(212)
- plot(angle(h))
-
-endfunction
-
+++ /dev/null
-% cbphase.m
-% David Rowe Aug 2012
-% Used to experiment with critical band phase perception and smoothing
-
-function cbphase
-
- Wo = 100.0*pi/4000;
- L = floor(pi/Wo);
-
- A = zeros(1,L);
- phi = zeros(1,L);
-
- % three harmonics in this band
-
- b = 4; a = b-1; c = b+1;
-
- % set up phases and mags for 2nd order system (see phasesecord.m)
-
- wres = b*Wo;
- phi(a) = 3*pi/4 + wres;
- phi(b) = pi/2 + wres;
- phi(c) = pi/4 + wres;
-
- A(a) = 0.707;
- A(b) = 1;
- A(c) = 0.707;
-
- % add linear component
-
- phi(1) = pi;
- phi(2:L) = phi(2:L) + (2:L)*phi(1);
- phi = phi - 2*pi*(floor(phi/(2*pi)) + 0.5);
-
- N = 16000;
- Nplot = 250;
- s = zeros(1,N);
-
- for m=a:c
- s_m = A(m)*cos(m*Wo*(0:(N-1)) + phi(m));
- s = s + s_m;
- endfor
-
- figure(2);
- clf;
- subplot(211)
- plot((1:L)*Wo*4000/pi, A,'+');
- subplot(212)
- plot((1:L)*Wo*4000/pi, phi,'+');
-
- %v = A(a)*exp(j*phi(a)) + A(b)*exp(j*phi(b)) + A(c)*exp(j*phi(c));
- %compass(v,"r")
- %hold off;
-
- % est phi1
-
- diff = phi(b) - phi(a)
- sumi = sin(diff);
- sumr = cos(diff);
- diff = phi(c) - phi(b)
- sumi += sin(diff);
- sumr += cos(diff);
- phi1_ = atan2(sumi, sumr)
- s_v = cos(Wo*(0:(N-1)) + phi1_);
-
- figure(1);
- clf;
- subplot(211)
- plot(s(1:Nplot));
- hold on;
- plot(s_v(1:Nplot),"r");
- hold off;
-
- % build (hopefully) perceptually similar phase
-
- phi_(a) = a*phi1_;
- phi_(b) = b*phi1_;
- phi_(c) = c*phi1_;
-
- s_ = zeros(1,N);
-
- for m=a:c
- s_m = A(m)*cos(m*Wo*(0:(N-1)) + phi_(m));
- s_ = s_ + s_m;
- endfor
-
- subplot(212)
- plot(s_(1:Nplot));
-
- gain = 8000;
- fs=fopen("orig_ph.raw","wb");
- fwrite(fs,gain*s,"short");
- fclose(fs);
- fs=fopen("mod_ph.raw","wb");
- fwrite(fs,gain*s_,"short");
- fclose(fs);
-
-endfunction
-
+++ /dev/null
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% codec2_demo.m
-
-% Designed as an educational tool to explain the operation of Codec 2
-% for conference and user group presentations on a projector. An
-% alternative to static overhead slides.
-%
-% Derived from codec2-dev/octave/plamp.m
-%
-% usage:
-% octave:1> plamp("../src/hts2a",40)
-%
-% Then press:
-% c - to cycle through the wavform being displayed on the figure
-% n - next frame
-% b - back one frame
-%
-% tip: hold down n or b to animate the display
-%
-% The text files used as input are generated using c2sim:
-%
-% /codec2-dev/src$ c2sim ../raw/hts2a.raw --dump hts2a
-%
-% The Codec 2 README explains how to build c2sim with dump files
-% enabled.
-
-function codec2_demo(samname, f)
-
- sn_name = strcat(samname,"_sn.txt");
- Sn = load(sn_name);
-
- sw_name = strcat(samname,"_sw.txt");
- Sw = load(sw_name);
-
- model_name = strcat(samname,"_model.txt");
- model = load(model_name);
-
- figure(1);
-
- k = ' ';
- wf = "Sn";
- do
-
- if strcmp(wf,"Sn")
- clf;
- s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- plot(s);
- axis([1 length(s) -20000 20000]);
- end
-
- if (strcmp(wf,"Sw"))
- clf;
- plot((0:255)*4000/256, Sw(f,:),";Sw;");
- end
-
- if strcmp(wf,"SwAm")
- Wo = model(f,1);
- L = model(f,2);
- Am = model(f,3:(L+2));
- plot((0:255)*4000/256, Sw(f,:),";Sw;");
- hold on;
- plot((1:L)*Wo*4000/pi, 20*log10(Am),"+;Am;r");
- axis([1 4000 -10 80]);
- hold off;
- end
-
- if strcmp(wf,"Am")
- Wo = model(f,1);
- L = model(f,2);
- Am = model(f,3:(L+2));
- plot((1:L)*Wo*4000/pi, 20*log10(Am),"+;Am;r");
- axis([1 4000 -10 80]);
- end
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back w-cycle window q-quit", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- end
- if (k == 'b')
- f = f - 1;
- end
- if (k == 'w')
- if strcmp(wf,"Sn")
- next_wf = "Sw";
- end
- if strcmp(wf,"Sw")
- next_wf = "SwAm";
- end
- if strcmp(wf,"SwAm")
- next_wf = "Am";
- end
- if strcmp(wf,"Am")
- next_wf = "Sn";
- end
- wf = next_wf;
- end
-
- until (k == 'q')
- printf("\n");
-
-endfunction
+++ /dev/null
-% cspec.m
-% David Rowe Aug 2012
-% Used to compare spectromgrams while experimenting with phase
-
-function cspec(s1,s2)
- f1 = fopen(s1,"rb");
- s1 = fread(f1,Inf,"short");
- f2 = fopen(s2,"rb");
- s2 = fread(f2,Inf,"short");
-
- Fs = 8000;
- spec_win = 512;
-
- state = 's1';
- do
- if strcmp(state,'s1')
- spec(s1,Fs,spec_win);
- %title(s1);
- end
- if strcmp(state,'s2')
- spec(s2,Fs,spec_win);
- %title(s2);
- end
- if strcmp(state,'diff')
- spec(s1-s2,Fs,spec_win);
- %title("difference");
- end
-
- printf("\rstate: %s space-toggle d-diff q-quit", state);
- fflush(stdout);
- k = kbhit();
-
- if k == ' '
- if strcmp(state,"diff")
- next_state = 's1';
- end
- if strcmp(state,"s1")
- next_state = 's2';
- end
- if strcmp(state,'s2')
- next_state = 's1';
- end
- end
-
- if k == 'd'
- next_state = 'diff';
- end
-
- state = next_state;
- until (k == 'q')
-
- printf("\n");
-
-endfunction
+++ /dev/null
-% fdmdv.m
-%
-% Functions that implement a Frequency Divison Multiplexed Modem for
-% Digital Voice (FDMDV) over HF channels.
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-% reqd to mak sure we get same random bits at mod and demod
-
-rand('state',1);
-randn('state',1);
-
-% Constants
-
-global Fs = 8000; % sample rate in Hz
-global T = 1/Fs; % sample period in seconds
-global Rs = 50; % symbol rate in Hz
-global Nc = 14; % number of carriers
-global Nb = 2; % Bits/symbol for QPSK modulation
-global Rb = Nc*Rs*Nb; % bit rate
-global M = Fs/Rs; % oversampling factor
-global Nsym = 6; % number of symbols to filter over
-global Fsep = 75; % Separation between carriers (Hz)
-global Fcentre = 1200; % Centre frequency, Nc/2 carriers below this, N/c carriers above (Hz)
-global Nt = 5; % number of symbols we estimate timing over
-global P = 4; % oversample factor used for rx symbol filtering
-global Nfilter = Nsym*M;
-global Nfiltertiming = M+Nfilter+M;
-alpha = 0.5;
-global snr_coeff = 0.9 % SNR est averaging filter coeff
-
-% root raised cosine (Root Nyquist) filter
-
-global gt_alpha5_root;
-gt_alpha5_root = gen_rn_coeffs(alpha, T, Rs, Nsym, M);
-
-
-% Functions ----------------------------------------------------
-
-
-% generate Nc+1 QPSK symbols from vector of (1,Nc*Nb) input bits. The
-% Nc+1 symbol is the +1 -1 +1 .... BPSK sync carrier
-
-function tx_symbols = bits_to_qpsk(prev_tx_symbols, tx_bits, modulation)
- global Nc;
- global Nb;
- global pilot_bit;
-
- % re-arrange as (Nc,Nb) matrix
-
- tx_bits_matrix = zeros(Nc,Nb);
- tx_bits_matrix(1:Nc,1) = tx_bits(1:Nb:Nb*Nc);
- tx_bits_matrix(1:Nc,2) = tx_bits(2:Nb:Nb*Nc);
-
- if (strcmp(modulation,'dqpsk'))
-
- % map to (Nc,1) DQPSK symbols
-
- for c=1:Nc
- msb = tx_bits_matrix(c,1); lsb = tx_bits_matrix(c,2);
-
- if ((msb == 0) && (lsb == 0))
- tx_symbols(c) = prev_tx_symbols(c);
- endif
- if ((msb == 0) && (lsb == 1))
- tx_symbols(c) = j*prev_tx_symbols(c);
- endif
- if ((msb == 1) && (lsb == 0))
- tx_symbols(c) = -prev_tx_symbols(c);
- endif
- if ((msb == 1) && (lsb == 1))
- tx_symbols(c) = -j*prev_tx_symbols(c);
- endif
- end
- else
- % QPSK mapping
- tx_symbols = -1 + 2*tx_bits_matrix(:,1) - j + 2j*tx_bits_matrix(:,2);
- endif
-
- % +1 -1 +1 -1 BPSK sync carrier, once filtered becomes two spectral
- % lines at +/- Rs/2
-
- if pilot_bit
- tx_symbols(Nc+1) = -prev_tx_symbols(Nc+1);
- else
- tx_symbols(Nc+1) = prev_tx_symbols(Nc+1);
- end
- if pilot_bit
- pilot_bit = 0;
- else
- pilot_bit = 1;
- end
-
-endfunction
-
-
-% Given Nc*Nb bits construct M samples (1 symbol) of Nc filtered
-% symbols streams
-
-function tx_baseband = tx_filter(tx_symbols)
- global Nc;
- global M;
- global tx_filter_memory;
- global Nfilter;
- global gt_alpha5_root;
-
- tx_baseband = zeros(Nc+1,M);
-
- % tx filter each symbol, generate M filtered output samples for each symbol.
- % Efficient polyphase filter techniques used as tx_filter_memory is sparse
-
- tx_filter_memory(:,Nfilter) = sqrt(2)/2*tx_symbols;
-
- for i=1:M
- tx_baseband(:,i) = M*tx_filter_memory(:,M:M:Nfilter) * gt_alpha5_root(M-i+1:M:Nfilter)';
- end
- tx_filter_memory(:,1:Nfilter-M) = tx_filter_memory(:,M+1:Nfilter);
- tx_filter_memory(:,Nfilter-M+1:Nfilter) = zeros(Nc+1,M);
-
-endfunction
-
-
-% Construct FDM signal by frequency shifting each filtered symbol
-% stream. Returns complex signal so we can apply frequency offsets
-% easily.
-
-function tx_fdm = fdm_upconvert(tx_filt)
- global Fs;
- global M;
- global Nc;
- global Fsep;
- global phase_tx;
- global freq;
-
- tx_fdm = zeros(1,M);
-
- % Nc/2 tones below centre freq
-
- for c=1:Nc/2
- for i=1:M
- phase_tx(c) = phase_tx(c) * freq(c);
- tx_fdm(i) = tx_fdm(i) + tx_filt(c,i)*phase_tx(c);
- end
- end
-
- % Nc/2 tones above centre freq
-
- for c=Nc/2+1:Nc
- for i=1:M
- phase_tx(c) = phase_tx(c) * freq(c);
- tx_fdm(i) = tx_fdm(i) + tx_filt(c,i)*phase_tx(c);
- end
- end
-
- % add centre pilot tone
-
- c = Nc+1;
- for i=1:M
- phase_tx(c) = phase_tx(c) * freq(c);
- pilot(i) = 2*tx_filt(c,i)*phase_tx(c);
- tx_fdm(i) = tx_fdm(i) + pilot(i);
- end
-
- % Scale such that total Carrier power C of real(tx_fdm) = Nc. This
- % excludes the power of the pilot tone.
- % We return the complex (single sided) signal to make frequency
- % shifting for the purpose of testing easier
-
- tx_fdm = 2*tx_fdm;
-endfunction
-
-
-% Frequency shift each modem carrier down to Nc+1 baseband signals
-
-function rx_baseband = fdm_downconvert(rx_fdm, nin)
- global Fs;
- global M;
- global Nc;
- global Fsep;
- global phase_rx;
- global freq;
-
- rx_baseband = zeros(1,nin);
-
- % Nc/2 tones below centre freq
-
- for c=1:Nc/2
- for i=1:nin
- phase_rx(c) = phase_rx(c) * freq(c);
- rx_baseband(c,i) = rx_fdm(i)*phase_rx(c)';
- end
- end
-
- % Nc/2 tones above centre freq
-
- for c=Nc/2+1:Nc
- for i=1:nin
- phase_rx(c) = phase_rx(c) * freq(c);
- rx_baseband(c,i) = rx_fdm(i)*phase_rx(c)';
- end
- end
-
- % Pilot
-
- c = Nc+1;
- for i=1:nin
- phase_rx(c) = phase_rx(c) * freq(c);
- rx_baseband(c,i) = rx_fdm(i)*phase_rx(c)';
- end
-
-endfunction
-
-
-% Receive filter each baseband signal at oversample rate P
-
-function rx_filt = rx_filter(rx_baseband, nin)
- global Nc;
- global M;
- global P;
- global rx_filter_memory;
- global Nfilter;
- global gt_alpha5_root;
- global Fsep;
-
- rx_filt = zeros(Nc+1,nin*P/M);
-
- % rx filter each symbol, generate P filtered output samples for each symbol.
- % Note we keep memory at rate M, it's just the filter output at rate P
-
- N=M/P;
- j=1;
- for i=1:N:nin
- rx_filter_memory(:,Nfilter-N+1:Nfilter) = rx_baseband(:,i:i-1+N);
- rx_filt(:,j) = rx_filter_memory * gt_alpha5_root';
- rx_filter_memory(:,1:Nfilter-N) = rx_filter_memory(:,1+N:Nfilter);
- j+=1;
- end
-endfunction
-
-
-% LPF and peak pick part of freq est, put in a function as we call it twice
-
-function [foff imax pilot_lpf S] = lpf_peak_pick(pilot_baseband, pilot_lpf, nin)
- global M;
- global Npilotlpf;
- global Npilotcoeff;
- global Fs;
- global Mpilotfft;
- global pilot_coeff;
-
- % LPF cutoff 200Hz, so we can handle max +/- 200 Hz freq offset
-
- pilot_lpf(1:Npilotlpf-nin) = pilot_lpf(nin+1:Npilotlpf);
- j = 1;
- for i = Npilotlpf-nin+1:Npilotlpf
- pilot_lpf(i) = pilot_baseband(j:j+Npilotcoeff-1) * pilot_coeff';
- j++;
- end
-
- % decimate to improve DFT resolution, window and DFT
-
- Mpilot = Fs/(2*200); % calc decimation rate given new sample rate is twice LPF freq
- h = hanning(Npilotlpf);
- s = pilot_lpf(1:Mpilot:Npilotlpf) .* h(1:Mpilot:Npilotlpf)';
- s = [s zeros(1,Mpilotfft-Npilotlpf/Mpilot)];
- S = fft(s, Mpilotfft);
-
- % peak pick and convert to Hz
-
- [imax ix] = max(S);
- r = 2*200/Mpilotfft; % maps FFT bin to frequency in Hz
-
- if ix > Mpilotfft/2
- foff = (ix - Mpilotfft - 1)*r;
- else
- foff = (ix - 1)*r;
- endif
-
-endfunction
-
-
-% Estimate frequency offset of FDM signal using BPSK pilot. This is quite
-% sensitive to pilot tone level wrt other carriers
-
-function [foff S1 S2] = rx_est_freq_offset(rx_fdm, pilot, pilot_prev, nin)
- global M;
- global Npilotbaseband;
- global pilot_baseband1;
- global pilot_baseband2;
- global pilot_lpf1;
- global pilot_lpf2;
-
- % down convert latest nin samples of pilot by multiplying by
- % ideal BPSK pilot signal we have generated locally. This
- % peak of the resulting signal is sensitive to the time shift between
- % the received and local version of the pilot, so we do it twice at
- % different time shifts and choose the maximum.
-
- pilot_baseband1(1:Npilotbaseband-nin) = pilot_baseband1(nin+1:Npilotbaseband);
- pilot_baseband2(1:Npilotbaseband-nin) = pilot_baseband2(nin+1:Npilotbaseband);
- for i=1:nin
- pilot_baseband1(Npilotbaseband-nin+i) = rx_fdm(i) * conj(pilot(i));
- pilot_baseband2(Npilotbaseband-nin+i) = rx_fdm(i) * conj(pilot_prev(i));
- end
-
- [foff1 max1 pilot_lpf1 S1] = lpf_peak_pick(pilot_baseband1, pilot_lpf1, nin);
- [foff2 max2 pilot_lpf2 S2] = lpf_peak_pick(pilot_baseband2, pilot_lpf2, nin);
-
- if max1 > max2
- foff = foff1;
- else
- foff = foff2;
- end
-endfunction
-
-
-% Estimate optimum timing offset, re-filter receive symbols
-
-function [rx_symbols rx_timing env] = rx_est_timing(rx_filt, rx_baseband, nin)
- global M;
- global Nt;
- global Nc;
- global rx_filter_mem_timing;
- global rx_baseband_mem_timing;
- global P;
- global Nfilter;
- global Nfiltertiming;
- global gt_alpha5_root;
-
- % nin adjust
- % --------------------------------
- % 120 -1 (one less rate P sample)
- % 160 0 (nominal)
- % 200 1 (one more rate P sample)
-
- adjust = P - nin*P/M;
-
- % update buffer of Nt rate P filtered symbols
-
- rx_filter_mem_timing(:,1:(Nt-1)*P+adjust) = rx_filter_mem_timing(:,P+1-adjust:Nt*P);
- rx_filter_mem_timing(:,(Nt-1)*P+1+adjust:Nt*P) = rx_filt(:,:);
-
- % sum envelopes of all carriers
-
- env = sum(abs(rx_filter_mem_timing(:,:))); % use all Nc+1 carriers for timing
- %env = abs(rx_filter_mem_timing(Nc+1,:)); % just use BPSK pilot
- [n m] = size(env);
-
- % The envelope has a frequency component at the symbol rate. The
- % phase of this frequency component indicates the timing. So work out
- % single DFT at frequency 2*pi/P
-
- x = env * exp(-j*2*pi*(0:m-1)/P)';
-
- % map phase to estimated optimum timing instant at rate M
- % the M/4 part was adjusted by experiment, I know not why....
-
- rx_timing = angle(x)*M/(2*pi) + M/4;
- if (rx_timing > M)
- rx_timing -= M;
- end
- if (rx_timing < -M)
- rx_timing += M;
- end
-
- % rx_baseband_mem_timing contains M + Nfilter + M samples of the
- % baseband signal at rate M this enables us to resample the filtered
- % rx symbol with M sample precision once we have rx_timing
-
- rx_baseband_mem_timing(:,1:Nfiltertiming-nin) = rx_baseband_mem_timing(:,nin+1:Nfiltertiming);
- rx_baseband_mem_timing(:,Nfiltertiming-nin+1:Nfiltertiming) = rx_baseband;
-
- % sample right in the middle of the timing estimator window, by filtering
- % at rate M
-
- s = round(rx_timing) + M;
- rx_symbols = rx_baseband_mem_timing(:,s+1:s+Nfilter) * gt_alpha5_root';
-
-endfunction
-
-
-% Phase estimation function - probably won't work over a HF channel
-% Tries to operate over a single symbol but uses phase information from
-% all Nc carriers which should increase the SNR of phase estimate.
-% Maybe phase is coherent over a couple of symbols in HF channel,not
-% sure but it's worth 3dB so worth experimenting or using coherent as
-% an option.
-
-function rx_phase = rx_est_phase(prev_rx_symbols, rx_symbols)
-
- % modulation strip
-
- rx_phase = angle(sum(rx_symbols .^ 4))/4;
-
-endfunction
-
-
-% convert symbols back to an array of bits
-
-function [rx_bits sync_bit f_err phase_difference] = qpsk_to_bits(prev_rx_symbols, rx_symbols, modulation)
- global Nc;
- global Nb;
- global Nb;
-
- if (strcmp(modulation,'dqpsk'))
- % extra 45 degree clockwise lets us use real and imag axis as
- % decision boundaries
-
- phase_difference = zeros(Nc+1,1);
- phase_difference(1:Nc) = rx_symbols(1:Nc) .* conj(prev_rx_symbols(1:Nc)) * exp(j*pi/4);
-
- % map (Nc,1) DQPSK symbols back into an (1,Nc*Nb) array of bits
-
- for c=1:Nc
- d = phase_difference(c);
- if ((real(d) >= 0) && (imag(d) >= 0))
- msb = 0; lsb = 0;
- endif
- if ((real(d) < 0) && (imag(d) >= 0))
- msb = 0; lsb = 1;
- endif
- if ((real(d) < 0) && (imag(d) < 0))
- msb = 1; lsb = 0;
- endif
- if ((real(d) >= 0) && (imag(d) < 0))
- msb = 1; lsb = 1;
- endif
- rx_bits(2*(c-1)+1) = msb;
- rx_bits(2*(c-1)+2) = lsb;
- end
-
- % Extract DBPSK encoded Sync bit
-
- phase_difference(Nc+1,1) = rx_symbols(Nc+1) .* conj(prev_rx_symbols(Nc+1));
- if (real(phase_difference(Nc+1)) < 0)
- sync_bit = 1;
- f_err = imag(phase_difference(Nc+1));
- else
- sync_bit = 0;
- f_err = -imag(phase_difference(Nc+1));
- end
-
- % pilot carrier gets an extra pi/4 rotation to make it consistent with
- % other carriers, as we need it for snr_update and scatter diagram
-
- phase_difference(Nc+1) *= exp(j*pi/4);
- else
- % map (Nc,1) QPSK symbols back into an (1,Nc*Nb) array of bits
-
- rx_bits(1:Nb:Nc*Nb) = real(rx_symbols) > 0;
- rx_bits(2:Nb:Nc*Nb) = imag(rx_symbols) > 0;
- endif
-
-endfunction
-
-
-% given phase differences update estimates of signal and noise levels
-
-function [sig_est noise_est] = snr_update(sig_est, noise_est, phase_difference)
- global snr_coeff;
- global Nc;
-
- % mag of each symbol is distance from origin, this gives us a
- % vector of mags, one for each carrier.
-
- s = abs(phase_difference);
-
- % signal mag estimate for each carrier is a smoothed version
- % of instantaneous magntitude, this gives us a vector of smoothed
- % mag estimates, one for each carrier.
-
- sig_est = snr_coeff*sig_est + (1 - snr_coeff)*s;
-
- % noise mag estimate is distance of current symbol from average
- % location of that symbol. We reflect all symbols into the first
- % quadrant for convenience.
-
- refl_symbols = abs(real(phase_difference)) + j*abs(imag(phase_difference));
- n = abs(exp(j*pi/4)*sig_est - refl_symbols);
-
- % noise mag estimate for each carrier is a smoothed version of
- % instantaneous noise mag, this gives us a vector of smoothed
- % noise power estimates, one for each carrier.
-
- noise_est = snr_coeff*noise_est + (1 - snr_coeff)*n;
-endfunction
-
-
-% calculate current SNR estimate (3000Hz noise BW)
-
-function snr_dB = calc_snr(sig_est, noise_est)
- global Rs;
-
- % find total signal power by summing power in all carriers
-
- S = sum(sig_est .^2);
- SdB = 10*log10(S);
-
- % Average noise mag across all carriers and square to get an average
- % noise power. This is an estimate of the noise power in Rs = 50Hz of
- % BW (note for raised root cosine filters Rs is the noise BW of the
- % filter)
-
- N50 = mean(noise_est).^2;
- N50dB = 10*log10(N50);
-
- % Now multiply by (3000 Hz)/(50 Hz) to find the total noise power in
- % 3000 Hz
-
- N3000dB = N50dB + 10*log10(3000/Rs);
-
- snr_dB = SdB - N3000dB;
-
-endfunction
-
-% returns nbits from a repeating sequence of random data
-
-function bits = get_test_bits(nbits)
- global Ntest_bits; % length of test sequence
- global current_test_bit;
- global test_bits;
-
- for i=1:nbits
- bits(i) = test_bits(current_test_bit++);
- if (current_test_bit > Ntest_bits)
- current_test_bit = 1;
- endif
- end
-
-endfunction
-
-
-% Accepts nbits from rx and attempts to sync with test_bits sequence.
-% if sync OK measures bit errors
-
-function [sync bit_errors] = put_test_bits(rx_bits)
- global Ntest_bits; % length of test sequence
- global test_bits;
- global rx_test_bits_mem;
-
- % Append to our memory
-
- [m n] = size(rx_bits);
- rx_test_bits_mem(1:Ntest_bits-n) = rx_test_bits_mem(n+1:Ntest_bits);
- rx_test_bits_mem(Ntest_bits-n+1:Ntest_bits) = rx_bits;
-
- % see how many bit errors we get when checked against test sequence
-
- bit_errors = sum(xor(test_bits,rx_test_bits_mem));
-
- % if less than a thresh we are aligned and in sync with test sequence
-
- ber = bit_errors/Ntest_bits;
-
- sync = 0;
- if (ber < 0.2)
- sync = 1;
- endif
-endfunction
-
-
-
-% Generate M samples of DBPSK pilot signal for Freq offset estimation
-
-function [pilot_fdm bit symbol filter_mem phase] = generate_pilot_fdm(bit, symbol, filter_mem, phase, freq)
- global M;
- global Nfilter;
- global gt_alpha5_root;
-
- % +1 -1 +1 -1 DBPSK sync carrier, once filtered becomes two spectral
- % lines at +/- Rs/2
-
- if bit
- symbol = -symbol;
- else
- symbol = symbol;
- end
- if bit
- bit = 0;
- else
- bit = 1;
- end
-
- % filter DPSK symbol to create M baseband samples
-
- filter_mem(Nfilter) = (sqrt(2)/2)*symbol;
- for i=1:M
- tx_baseband(i) = M*filter_mem(M:M:Nfilter) * gt_alpha5_root(M-i+1:M:Nfilter)';
- end
- filter_mem(1:Nfilter-M) = filter_mem(M+1:Nfilter);
- filter_mem(Nfilter-M+1:Nfilter) = zeros(1,M);
-
- % upconvert
-
- for i=1:M
- phase = phase * freq;
- pilot_fdm(i) = sqrt(2)*2*tx_baseband(i)*phase;
- end
-
-endfunction
-
-
-% Generate a 4M sample vector of DBPSK pilot signal. As the pilot signal
-% is periodic in 4M samples we can then use this vector as a look up table
-% for pilot signal generation in the demod.
-
-function pilot_lut = generate_pilot_lut()
- global Nc;
- global Nfilter;
- global M;
- global freq;
-
- % pilot states
-
- pilot_rx_bit = 0;
- pilot_symbol = sqrt(2);
- pilot_freq = freq(Nc+1);
- pilot_phase = 1;
- pilot_filter_mem = zeros(1, Nfilter);
- %prev_pilot = zeros(M,1);
-
- pilot_lut = [];
-
- F=8;
-
- for f=1:F
- [pilot pilot_rx_bit pilot_symbol pilot_filter_mem pilot_phase] = generate_pilot_fdm(pilot_rx_bit, pilot_symbol, pilot_filter_mem, pilot_phase, pilot_freq);
- %prev_pilot = pilot;
- pilot_lut = [pilot_lut pilot];
- end
-
- % discard first 4 symbols as filter memory is filling, just keep last
- % four symbols
-
- pilot_lut = pilot_lut(4*M+1:M*F);
-
-endfunction
-
-
-% grab next pilot samples for freq offset estimation at demod
-
-function [pilot prev_pilot pilot_lut_index prev_pilot_lut_index] = get_pilot(pilot_lut_index, prev_pilot_lut_index, nin)
- global M;
- global pilot_lut;
-
- for i=1:nin
- pilot(i) = pilot_lut(pilot_lut_index);
- pilot_lut_index++;
- if pilot_lut_index > 4*M
- pilot_lut_index = 1;
- end
- prev_pilot(i) = pilot_lut(prev_pilot_lut_index);
- prev_pilot_lut_index++;
- if prev_pilot_lut_index > 4*M
- prev_pilot_lut_index = 1;
- end
- end
-endfunction
-
-
-
-% Change the sample rate by a small amount, for example 1000ppm (ratio
-% = 1.001). Always returns nout samples in buf_out, but uses a
-% variable number of input samples nin to accomodate the change in
-% sample rate. nin is nominally set to nout, but may use nout +/- 2
-% samples to accomodate the different sample rates. buf_in should be
-% of length nout+6 samples to accomodate this, and buf_in should be
-% updated externally based on the nin returned each time. "ratio" is
-% Fs_in/Fs_out, for example 48048/48000 = 1.001 (+1000ppm) or
-% 47952/48000 = 0.999 (-1000ppm). Uses linear interpolation to
-% perform the resampling. This requires a highly over-sampled signal,
-% for example 48000Hz sample rate for the modem signal centred on
-% 1kHz, otherwise linear interpolation will have a low pass filter effect
-% (for example an 8000Hz sample rate for modem signal centred on 1kHz
-% would cause problems).
-
-function [buf_out t nin] = resample(buf_in, t, ratio, nout)
-
- for i=1:nout
- c = floor(t);
- a = t - c;
- b = 1 - a;
- buf_out(i) = buf_in(c)*b + buf_in(c+1)*a;
- t += ratio;
- end
-
- t -= nout;
-
- % adjust nin and t so that on next call we start with 3 < t < 4,
- % this gives us +/- 2 samples room to move before we hit start or
- % end of buf_in
-
- delta = floor(t - 3);
- nin = nout + delta;
- t -= delta;
-
-endfunction
-
-
-% freq offset state machine. Moves between acquire and track states based
-% on BPSK pilot sequence. Freq offset estimator occasionally makes mistakes
-% when used continuously. So we use it until we have acquired the BPSK pilot,
-% then switch to a more robust tracking algorithm. If we lose sync we switch
-% back to acquire mode for fast-requisition.
-
-function [track state] = freq_state(sync_bit, state)
-
- % acquire state, look for 6 symbol 010101 sequence from sync bit
-
- next_state = state;
- if state == 0
- if sync_bit == 0
- next_state = 1;
- end
- end
- if state == 1
- if sync_bit == 1
- next_state = 2;
- else
- next_state = 0;
- end
- end
- if state == 2
- if sync_bit == 0
- next_state = 3;
- else
- next_state = 0;
- end
- end
- if state == 3
- if sync_bit == 1
- next_state = 4;
- else
- next_state = 0;
- end
- end
- if state == 4
- if sync_bit == 0
- next_state = 5;
- else
- next_state = 0;
- end
- end
- if state == 5
- if sync_bit == 1
- next_state = 6;
- else
- next_state = 0;
- end
- end
-
- % states 6 and above are track mode, make sure we keep getting 0101 sync bit sequence
-
- if state == 6
- if sync_bit == 0
- next_state = 7;
- else
- next_state = 0;
- end
- end
- if state == 7
- if sync_bit == 1
- next_state = 6;
- else
- next_state = 0;
- end
- end
-
- state = next_state;
- if state >= 6
- track = 1;
- else
- track = 0;
- end
-endfunction
-
-
-% Save test bits to a text file in the form of a C array
-
-function test_bits_file(filename)
- global test_bits;
- global Ntest_bits;
-
- f=fopen(filename,"wt");
- fprintf(f,"/* Generated by test_bits_file() Octave function */\n\n");
- fprintf(f,"const int test_bits[]={\n");
- for m=1:Ntest_bits-1
- fprintf(f," %d,\n",test_bits(m));
- endfor
- fprintf(f," %d\n};\n",test_bits(Ntest_bits));
- fclose(f);
-endfunction
-
-
-% Saves RN filter coeffs to a text file in the form of a C array
-
-function rn_file(filename)
- global gt_alpha5_root;
- global Nfilter;
-
- f=fopen(filename,"wt");
- fprintf(f,"/* Generated by rn_file() Octave function */\n\n");
- fprintf(f,"const float gt_alpha5_root[]={\n");
- for m=1:Nfilter-1
- fprintf(f," %g,\n",gt_alpha5_root(m));
- endfor
- fprintf(f," %g\n};\n",gt_alpha5_root(Nfilter));
- fclose(f);
-endfunction
-
-function pilot_coeff_file(filename)
- global pilot_coeff;
- global Npilotcoeff;
-
- f=fopen(filename,"wt");
- fprintf(f,"/* Generated by pilot_coeff_file() Octave function */\n\n");
- fprintf(f,"const float pilot_coeff[]={\n");
- for m=1:Npilotcoeff-1
- fprintf(f," %g,\n",pilot_coeff(m));
- endfor
- fprintf(f," %g\n};\n",pilot_coeff(Npilotcoeff));
- fclose(f);
-endfunction
-
-
-% Saves hanning window coeffs to a text file in the form of a C array
-
-function hanning_file(filename)
- global Npilotlpf;
-
- h = hanning(Npilotlpf);
-
- f=fopen(filename,"wt");
- fprintf(f,"/* Generated by hanning_file() Octave function */\n\n");
- fprintf(f,"const float hanning[]={\n");
- for m=1:Npilotlpf-1
- fprintf(f," %g,\n", h(m));
- endfor
- fprintf(f," %g\n};\n", h(Npilotlpf));
- fclose(f);
-endfunction
-
-
-function png_file(fig, pngfilename)
- figure(fig);
-
- pngname = sprintf("%s.png",pngfilename);
- print(pngname, '-dpng', "-S500,500")
- pngname = sprintf("%s_large.png",pngfilename);
- print(pngname, '-dpng', "-S800,600")
-endfunction
-
-% Initialise ----------------------------------------------------
-
-global pilot_bit;
-pilot_bit = 0; % current value of pilot bit
-
-global tx_filter_memory;
-tx_filter_memory = zeros(Nc+1, Nfilter);
-global rx_filter_memory;
-rx_filter_memory = zeros(Nc+1, Nfilter);
-
-% phasors used for up and down converters
-
-global freq;
-freq = zeros(Nc+1,1);
-for c=1:Nc/2
- carrier_freq = (-Nc/2 - 1 + c)*Fsep + Fcentre;
- freq(c) = exp(j*2*pi*carrier_freq/Fs);
-end
-for c=Nc/2+1:Nc
- carrier_freq = (-Nc/2 + c)*Fsep + Fcentre;
- freq(c) = exp(j*2*pi*carrier_freq/Fs);
-end
-
-freq(Nc+1) = exp(j*2*pi*Fcentre/Fs);
-
-% Spread initial FDM carrier phase out as far as possible. This
-% helped PAPR for a few dB. We don't need to adjust rx phase as DQPSK
-% takes care of that.
-
-global phase_tx;
-%phase_tx = ones(Nc+1,1);
-phase_tx = exp(j*2*pi*(0:Nc)/(Nc+1));
-global phase_rx;
-phase_rx = ones(Nc+1,1);
-
-% Freq offset estimator constants
-
-global Mpilotfft = 256;
-global Npilotcoeff = 30; % number of pilot LPF coeffs
-global pilot_coeff = fir1(Npilotcoeff-1, 200/(Fs/2))'; % 200Hz LPF
-global Npilotbaseband = Npilotcoeff + M + M/P; % number of pilot baseband samples reqd for pilot LPF
-global Npilotlpf = 4*M; % number of samples we DFT pilot over, pilot est window
-
-% pilot LUT, used for copy of pilot at rx
-
-global pilot_lut;
-pilot_lut = generate_pilot_lut();
-pilot_lut_index = 1;
-prev_pilot_lut_index = 3*M+1;
-
-% Freq offset estimator states
-
-global pilot_baseband1;
-global pilot_baseband2;
-pilot_baseband1 = zeros(1, Npilotbaseband); % pilot baseband samples
-pilot_baseband2 = zeros(1, Npilotbaseband); % pilot baseband samples
-global pilot_lpf1
-global pilot_lpf2
-pilot_lpf1 = zeros(1, Npilotlpf); % LPF pilot samples
-pilot_lpf2 = zeros(1, Npilotlpf); % LPF pilot samples
-
-% Timing estimator states
-
-global rx_filter_mem_timing;
-rx_filter_mem_timing = zeros(Nc+1, Nt*P);
-global rx_baseband_mem_timing;
-rx_baseband_mem_timing = zeros(Nc+1, Nfiltertiming);
-
-% Test bit stream constants
-
-global Ntest_bits = Nc*Nb*4; % length of test sequence
-global test_bits = rand(1,Ntest_bits) > 0.5;
-
-% Test bit stream state variables
-
-global current_test_bit = 1;
-current_test_bit = 1;
-global rx_test_bits_mem;
-rx_test_bits_mem = zeros(1,Ntest_bits);
-
+++ /dev/null
-% fdmdv_demod.m
-%
-% Demodulator function for FDMDV modem (Octave version). Requires
-% 8kHz sample rate raw files as input
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-function fdmdv_demod(rawfilename, nbits, pngname)
-
- fdmdv; % include modem code
-
- modulation = 'dqpsk';
-
- fin = fopen(rawfilename, "rb");
- gain = 1000;
- frames = nbits/(Nc*Nb);
-
- prev_rx_symbols = ones(Nc+1,1);
- foff_phase = 1;
-
- % BER stats
-
- total_bit_errors = 0;
- total_bits = 0;
- bit_errors_log = [];
- sync_log = [];
- test_frame_sync_log = [];
- test_frame_sync_state = 0;
-
- % SNR states
-
- sig_est = zeros(Nc+1,1);
- noise_est = zeros(Nc+1,1);
-
- % logs of various states for plotting
-
- rx_symbols_log = [];
- rx_timing_log = [];
- foff_log = [];
- rx_fdm_log = [];
- snr_est_log = [];
-
- % misc states
-
- nin = M; % timing correction for sample rate differences
- foff = 0;
- track_log = [];
- track = 0;
- fest_state = 0;
-
- % Main loop ----------------------------------------------------
-
- for f=1:frames
-
- % obtain nin samples of the test input signal
-
- for i=1:nin
- rx_fdm(i) = fread(fin, 1, "short")/gain;
- end
-
- rx_fdm_log = [rx_fdm_log rx_fdm(1:nin)];
-
- % frequency offset estimation and correction
-
- [pilot prev_pilot pilot_lut_index prev_pilot_lut_index] = get_pilot(pilot_lut_index, prev_pilot_lut_index, nin);
- [foff_coarse S1 S2] = rx_est_freq_offset(rx_fdm, pilot, prev_pilot, nin);
-
- if track == 0
- foff = foff_coarse;
- end
- foff_log = [ foff_log foff ];
- foff_rect = exp(j*2*pi*foff/Fs);
-
- for i=1:nin
- foff_phase *= foff_rect';
- rx_fdm(i) = rx_fdm(i)*foff_phase;
- end
-
- % baseband processing
-
- rx_baseband = fdm_downconvert(rx_fdm, nin);
- rx_filt = rx_filter(rx_baseband, nin);
-
- [rx_symbols rx_timing] = rx_est_timing(rx_filt, rx_baseband, nin);
-
- rx_timing_log = [rx_timing_log rx_timing];
- nin = M;
- if rx_timing > 2*M/P
- nin += M/P;
- end
- if rx_timing < 0;
- nin -= M/P;
- end
-
- if strcmp(modulation,'dqpsk')
- rx_symbols_log = [rx_symbols_log rx_symbols.*conj(prev_rx_symbols)*exp(j*pi/4)];
- else
- rx_symbols_log = [rx_symbols_log rx_symbols];
- endif
- [rx_bits sync f_err pd] = qpsk_to_bits(prev_rx_symbols, rx_symbols, modulation);
- [sig_est noise_est] = snr_update(sig_est, noise_est, pd);
- snr_est = calc_snr(sig_est, noise_est);
- snr_est_log = [snr_est_log snr_est];
- foff -= 0.5*f_err;
- prev_rx_symbols = rx_symbols;
- sync_log = [sync_log sync];
-
- % freq est state machine
-
- [track fest_state] = freq_state(sync, fest_state);
- track_log = [track_log track];
-
- % count bit errors if we find a test frame
-
- [test_frame_sync bit_errors] = put_test_bits(rx_bits);
- if (test_frame_sync == 1)
- total_bit_errors = total_bit_errors + bit_errors;
- total_bits = total_bits + Ntest_bits;
- bit_errors_log = [bit_errors_log bit_errors/Ntest_bits];
- else
- bit_errors_log = [bit_errors_log 0];
- end
-
- % test frame sync state machine, just for more informative plots
-
- next_test_frame_sync_state = test_frame_sync_state;
- if (test_frame_sync_state == 0)
- if (test_frame_sync == 1)
- next_test_frame_sync_state = 1;
- test_frame_count = 0;
- end
- end
-
- if (test_frame_sync_state == 1)
- % we only expect another test_frame_sync pulse every 4 symbols
- test_frame_count++;
- if (test_frame_count == 4)
- test_frame_count = 0;
- if ((test_frame_sync == 0))
- next_test_frame_sync_state = 0;
- end
- end
- end
- test_frame_sync_state = next_test_frame_sync_state;
- test_frame_sync_log = [test_frame_sync_log test_frame_sync_state];
-
- end
-
- % ---------------------------------------------------------------------
- % Print Stats
- % ---------------------------------------------------------------------
-
- ber = total_bit_errors / total_bits;
-
- printf("%d bits %d errors BER: %1.4f\n",total_bits, total_bit_errors, ber);
-
- % ---------------------------------------------------------------------
- % Plots
- % ---------------------------------------------------------------------
-
- xt = (1:frames)/Rs;
- secs = frames/Rs;
-
- figure(1)
- clf;
- [n m] = size(rx_symbols_log);
- plot(real(rx_symbols_log(1:Nc+1,15:m)),imag(rx_symbols_log(1:Nc+1,15:m)),'+')
- axis([-2 2 -2 2]);
- title('Scatter Diagram');
-
- figure(2)
- clf;
- subplot(211)
- plot(xt, rx_timing_log)
- title('timing offset (samples)');
- subplot(212)
- plot(xt, foff_log, '-;freq offset;')
- hold on;
- plot(xt, track_log*75, 'r;course-fine;');
- hold off;
- title('Freq offset (Hz)');
- grid
-
- figure(3)
- clf;
- subplot(211)
- [a b] = size(rx_fdm_log);
- xt1 = (1:b)/Fs;
- plot(xt1, rx_fdm_log);
- title('Rx FDM Signal');
- subplot(212)
- spec(rx_fdm_log,8000);
- title('FDM Rx Spectrogram');
-
- figure(4)
- clf;
- subplot(311)
- stem(xt, sync_log)
- axis([0 secs 0 1.5]);
- title('BPSK Sync')
- subplot(312)
- stem(xt, bit_errors_log);
- title('Bit Errors for test frames')
- subplot(313)
- plot(xt, test_frame_sync_log);
- axis([0 secs 0 1.5]);
- title('Test Frame Sync')
-
- figure(5)
- clf;
- plot(xt, snr_est_log);
- title('SNR Estimates')
-
-endfunction
+++ /dev/null
-% fdmdv_demod_c.m
-%
-% Plots Octave dump file information from C FDMDV demodulator program,
-% to give a similar set of plots to fdmdv_demod.m. Useful for off
-% line analysis of demod performance.
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-function fdmdv_demod_c(dumpfilename, bits)
-
- fdmdv; % include modem code
-
- frames = bits/(Nc*Nb);
-
- load(dumpfilename);
-
- % BER stats
-
- total_bit_errors = 0;
- total_bits = 0;
- bit_errors_log = [];
- sync_log = [];
- test_frame_sync_log = [];
- test_frame_sync_state = 0;
-
- % Run thru received bits to look for test pattern
-
- bits_per_frame = Nc*Nb;
-
- for f=1:frames
-
- rx_bits = rx_bits_log_c((f-1)*bits_per_frame+1:f*bits_per_frame);
-
- % count bit errors if we find a test frame
-
- [test_frame_sync bit_errors] = put_test_bits(rx_bits);
- if (test_frame_sync == 1)
- total_bit_errors = total_bit_errors + bit_errors;
- total_bits = total_bits + Ntest_bits;
- bit_errors_log = [bit_errors_log bit_errors/Ntest_bits];
- else
- bit_errors_log = [bit_errors_log 0];
- end
-
- % test frame sync state machine, just for more informative plots
-
- next_test_frame_sync_state = test_frame_sync_state;
- if (test_frame_sync_state == 0)
- if (test_frame_sync == 1)
- next_test_frame_sync_state = 1;
- test_frame_count = 0;
- end
- end
-
- if (test_frame_sync_state == 1)
- % we only expect another test_frame_sync pulse every 4 symbols
- test_frame_count++;
- if (test_frame_count == 4)
- test_frame_count = 0;
- if ((test_frame_sync == 0))
- next_test_frame_sync_state = 0;
- end
- end
- end
- test_frame_sync_state = next_test_frame_sync_state;
- test_frame_sync_log = [test_frame_sync_log test_frame_sync_state];
- end
-
- % ---------------------------------------------------------------------
- % Plots
- % ---------------------------------------------------------------------
-
- xt = (1:frames)/Rs;
- secs = frames/Rs;
-
- figure(1)
- clf;
- plot(real(rx_symbols_log_c(1:Nc+1,15:frames)),imag(rx_symbols_log_c(1:Nc+1,15:frames)),'+')
- axis([-2 2 -2 2]);
- title('Scatter Diagram');
-
- figure(2)
- clf;
- subplot(211)
- plot(xt, rx_timing_log_c(1:frames))
- title('timing offset (samples)');
- subplot(212)
- plot(xt, foff_log_c(1:frames), '-;freq offset;')
- hold on;
- plot(xt, coarse_fine_log_c(1:frames)*75, 'r;course-fine;');
- hold off;
- title('Freq offset (Hz)');
- grid
-
- figure(3)
- clf;
- subplot(211)
- b = M*frames;
- xt1 = (1:b)/Fs;
- plot(xt1, rx_fdm_log_c(1:b));
- title('Rx FDM Signal');
- subplot(212)
- spec(rx_fdm_log_c(1:b),8000);
- title('FDM Rx Spectrogram');
-
- figure(4)
- clf;
- subplot(311)
- stem(xt, sync_bit_log_c(1:frames))
- axis([0 secs 0 1.5]);
- title('BPSK Sync')
- subplot(312)
- stem(xt, bit_errors_log);
- title('Bit Errors for test frames')
- subplot(313)
- plot(xt, test_frame_sync_log);
- axis([0 secs 0 1.5]);
- title('Test Frame Sync')
-
- figure(5)
- clf;
- plot(xt, snr_est_log_c(1:frames));
- title('SNR Estimates')
-
-endfunction
+++ /dev/null
-% fdmdv_mod.m
-%
-% Modulator function for FDMDV modem, uses test frames as input and
-% outputs a raw file of 16 bit shorts at a sample rate of 8 kHz.
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-function tx_fdm = fdmdv_mod(rawfilename, nbits)
-
- fdmdv; % include modem code
-
- frames = floor(nbits/(Nc*Nb))
- tx_fdm = [];
- gain = 1000; % Scale up to 16 bit shorts
- prev_tx_symbols = ones(Nc+1,1);
-
- for i=1:frames
- tx_bits = get_test_bits(Nc*Nb);
- tx_symbols = bits_to_qpsk(prev_tx_symbols, tx_bits,'dqpsk');
- prev_tx_symbols = tx_symbols;
- tx_baseband = tx_filter(tx_symbols);
- tx_fdm = [tx_fdm real(fdm_upconvert(tx_baseband))];
- end
-
- tx_fdm *= gain;
- fout = fopen(rawfilename,"wb");
- fwrite(fout, tx_fdm, "short");
- fclose(fout);
-endfunction
+++ /dev/null
-% fdmdv_ut.m
-%
-% Unit Test program for FDMDV modem. Useful for general development as it has
-% both tx and rx sides, and basic AWGN channel simulation.
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-fdmdv; % load modem code
-
-% Simulation Parameters --------------------------------------
-
-frames = 25;
-EbNo_dB = 7.3;
-Foff_hz = 0;
-modulation = 'dqpsk';
-hpa_clip = 150;
-
-% ------------------------------------------------------------
-
-tx_filt = zeros(Nc,M);
-rx_symbols_log = [];
-rx_phase_log = 0;
-rx_timing_log = 0;
-tx_pwr = 0;
-noise_pwr = 0;
-rx_fdm_log = [];
-rx_baseband_log = [];
-rx_bits_offset = zeros(Nc*Nb*2);
-prev_tx_symbols = ones(Nc+1,1);
-prev_rx_symbols = ones(Nc+1,1);
-ferr = 0;
-foff = 0;
-foff_log = [];
-tx_baseband_log = [];
-tx_fdm_log = [];
-
-% BER stats
-
-total_bit_errors = 0;
-total_bits = 0;
-bit_errors_log = [];
-sync_log = [];
-test_frame_sync_log = [];
-test_frame_sync_state = 0;
-
-% SNR estimation states
-
-sig_est = zeros(Nc+1,1);
-noise_est = zeros(Nc+1,1);
-
-% fixed delay simuation
-
-Ndelay = M+20;
-rx_fdm_delay = zeros(Ndelay,1);
-
-% ---------------------------------------------------------------------
-% Eb/No calculations. We need to work out Eb/No for each FDM carrier.
-% Total power is sum of power in all FDM carriers
-% ---------------------------------------------------------------------
-
-C = 1; % power of each FDM carrier (energy/sample). Total Carrier power should = Nc*C = Nc
-N = 1; % total noise power (energy/sample) of noise source across entire bandwidth
-
-% Eb = Carrier power * symbol time / (bits/symbol)
-% = C *(1/Rs) / 2
-Eb_dB = 10*log10(C) - 10*log10(Rs) - 10*log10(2);
-
-No_dBHz = Eb_dB - EbNo_dB;
-
-% Noise power = Noise spectral density * bandwidth
-% Noise power = Noise spectral density * Fs/2 for real signals
-N_dB = No_dBHz + 10*log10(Fs/2);
-Ngain_dB = N_dB - 10*log10(N);
-Ngain = 10^(Ngain_dB/20);
-
-% C/No = Carrier Power/noise spectral density
-% = power per carrier*number of carriers / noise spectral density
-CNo_dB = 10*log10(C) + 10*log10(Nc) - No_dBHz;
-
-% SNR in equivalent 3000 Hz SSB channel
-
-B = 3000;
-SNR = CNo_dB - 10*log10(B);
-
-% freq offset simulation states
-
-phase_offset = 1;
-freq_offset = exp(j*2*pi*Foff_hz/Fs);
-foff_phase = 1;
-t = 0;
-foff = 0;
-fest_state = 0;
-track = 0;
-track_log = [];
-
-
-% ---------------------------------------------------------------------
-% Main loop
-% ---------------------------------------------------------------------
-
-for f=1:frames
-
- % -------------------
- % Modulator
- % -------------------
-
- tx_bits = get_test_bits(Nc*Nb);
- tx_symbols = bits_to_qpsk(prev_tx_symbols, tx_bits, modulation);
- prev_tx_symbols = tx_symbols;
- tx_baseband = tx_filter(tx_symbols);
- tx_baseband_log = [tx_baseband_log tx_baseband];
- tx_fdm = fdm_upconvert(tx_baseband);
- tx_pwr = 0.9*tx_pwr + 0.1*real(tx_fdm)*real(tx_fdm)'/(M);
-
- % -------------------
- % Channel simulation
- % -------------------
-
- % frequency offset
-
- %Foff_hz += 1/Rs;
- Foff = Foff_hz;
- for i=1:M
- % Time varying freq offset
- %Foff = Foff_hz + 100*sin(t*2*pi/(300*Fs));
- %t++;
- freq_offset = exp(j*2*pi*Foff/Fs);
- phase_offset *= freq_offset;
- tx_fdm(i) = phase_offset*tx_fdm(i);
- end
-
- tx_fdm = real(tx_fdm);
-
- % HPA non-linearity
-
- tx_fdm(find(abs(tx_fdm) > hpa_clip)) = hpa_clip;
- tx_fdm_log = [tx_fdm_log tx_fdm];
-
- rx_fdm = tx_fdm;
-
- % AWGN noise
-
- noise = Ngain*randn(1,M);
- noise_pwr = 0.9*noise_pwr + 0.1*noise*noise'/M;
- rx_fdm += noise;
- rx_fdm_log = [rx_fdm_log rx_fdm];
-
- % Delay
-
- rx_fdm_delay(1:Ndelay-M) = rx_fdm_delay(M+1:Ndelay);
- rx_fdm_delay(Ndelay-M+1:Ndelay) = rx_fdm;
- %rx_fdm_delay = rx_fdm;
-
- % -------------------
- % Demodulator
- % -------------------
-
- % frequency offset estimation and correction, need to call rx_est_freq_offset even in track
- % mode to keep states updated
-
- [pilot prev_pilot pilot_lut_index prev_pilot_lut_index] = get_pilot(pilot_lut_index, prev_pilot_lut_index, M);
- [foff_course S1 S2] = rx_est_freq_offset(rx_fdm_delay, pilot, prev_pilot, M);
- if track == 0
- foff = foff_course;
- end
- foff_log = [ foff_log foff ];
- foff_rect = exp(j*2*pi*foff/Fs);
-
- for i=1:M
- foff_phase *= foff_rect';
- rx_fdm_delay(i) = rx_fdm_delay(i)*foff_phase;
- end
-
- % baseband processing
-
- rx_baseband = fdm_downconvert(rx_fdm_delay(1:M), M);
- rx_baseband_log = [rx_baseband_log rx_baseband];
- rx_filt = rx_filter(rx_baseband, M);
-
- [rx_symbols rx_timing] = rx_est_timing(rx_filt, rx_baseband, M);
- rx_timing_log = [rx_timing_log rx_timing];
-
- %rx_phase = rx_est_phase(rx_symbols);
- %rx_phase_log = [rx_phase_log rx_phase];
- %rx_symbols = rx_symbols*exp(j*rx_phase);
-
- [rx_bits sync foff_fine pd] = qpsk_to_bits(prev_rx_symbols, rx_symbols, modulation);
- if strcmp(modulation,'dqpsk')
- %rx_symbols_log = [rx_symbols_log rx_symbols.*conj(prev_rx_symbols)*exp(j*pi/4)];
- rx_symbols_log = [rx_symbols_log pd];
- else
- rx_symbols_log = [rx_symbols_log rx_symbols];
- endif
- foff -= 0.5*ferr;
- prev_rx_symbols = rx_symbols;
- sync_log = [sync_log sync];
-
- % freq est state machine
-
- [track fest_state] = freq_state(sync, fest_state);
- track_log = [track_log track];
-
- % Update SNR est
-
- [sig_est noise_est] = snr_update(sig_est, noise_est, pd);
-
- % count bit errors if we find a test frame
- % Allow 15 frames for filter memories to fill and time est to settle
-
- [test_frame_sync bit_errors] = put_test_bits(rx_bits);
- if test_frame_sync == 1
- total_bit_errors = total_bit_errors + bit_errors;
- total_bits = total_bits + Ntest_bits;
- bit_errors_log = [bit_errors_log bit_errors];
- else
- bit_errors_log = [bit_errors_log 0];
- end
-
- % test frame sync state machine, just for more informative plots
-
- next_test_frame_sync_state = test_frame_sync_state;
- if (test_frame_sync_state == 0)
- if (test_frame_sync == 1)
- next_test_frame_sync_state = 1;
- test_frame_count = 0;
- end
- end
-
- if (test_frame_sync_state == 1)
- % we only expect another test_frame_sync pulse every 4 symbols
- test_frame_count++;
- if (test_frame_count == 4)
- test_frame_count = 0;
- if ((test_frame_sync == 0))
- next_test_frame_sync_state = 0;
- end
- end
- end
- test_frame_sync_state = next_test_frame_sync_state;
- test_frame_sync_log = [test_frame_sync_log test_frame_sync_state];
-end
-
-% ---------------------------------------------------------------------
-% Print Stats
-% ---------------------------------------------------------------------
-
-ber = total_bit_errors / total_bits;
-
-% Peak to Average Power Ratio calcs from http://www.dsplog.com
-
-papr = max(tx_fdm_log.*conj(tx_fdm_log)) / mean(tx_fdm_log.*conj(tx_fdm_log));
-papr_dB = 10*log10(papr);
-
-% Note Eb/No set point is for Nc data carriers only, exclduing pilot.
-% This is convenient for testing BER versus Eb/No. Measured Eb/No
-% includes power of pilot. Similar for SNR, first number is SNR excluding
-% pilot pwr for Eb/No set point, 2nd value is measured SNR which will be a little
-% higher as pilot power is included.
-
-printf("Eb/No (meas): %2.2f (%2.2f) dB\n", EbNo_dB, 10*log10(0.25*tx_pwr*Fs/(Rs*Nc*noise_pwr)));
-printf("bits........: %d\n", total_bits);
-printf("errors......: %d\n", total_bit_errors);
-printf("BER.........: %1.4f\n", ber);
-printf("PAPR........: %1.2f dB\n", papr_dB);
-printf("SNR...(meas): %2.2f (%2.2f) dB\n", SNR, calc_snr(sig_est, noise_est));
-
-% ---------------------------------------------------------------------
-% Plots
-% ---------------------------------------------------------------------
-
-figure(1)
-clf;
-[n m] = size(rx_symbols_log);
-plot(real(rx_symbols_log(1:Nc+1,15:m)),imag(rx_symbols_log(1:Nc+1,15:m)),'+')
-axis([-3 3 -3 3]);
-title('Scatter Diagram');
-
-figure(2)
-clf;
-subplot(211)
-plot(rx_timing_log)
-title('timing offset (samples)');
-subplot(212)
-plot(foff_log, '-;freq offset;')
-hold on;
-plot(track_log*75, 'r;course-fine;');
-hold off;
-title('Freq offset (Hz)');
-
-figure(3)
-clf;
-subplot(211)
-plot(real(tx_fdm_log));
-title('FDM Tx Signal');
-subplot(212)
-Nfft=Fs;
-S=fft(rx_fdm_log,Nfft);
-SdB=20*log10(abs(S));
-plot(SdB(1:Fs/4))
-title('FDM Rx Spectrum');
-
-figure(4)
-clf;
-subplot(311)
-stem(sync_log)
-axis([0 frames 0 1.5]);
-title('BPSK Sync')
-subplot(312)
-stem(bit_errors_log);
-title('Bit Errors for test frames')
-subplot(313)
-plot(test_frame_sync_log);
-axis([0 frames 0 1.5]);
-title('Test Frame Sync')
-
+++ /dev/null
-% gen_rn_coeffs.m
-% David Rowe 13 april 2012
-%
-% Generate root raised cosine (Root Nyquist) filter coefficients
-% thanks http://www.dsplog.com/db-install/wp-content/uploads/2008/05/raised_cosine_filter.m
-
-function coeffs = gen_rn_coeffs(alpha, T, Rs, Nsym, M)
-
- Ts = 1/Rs;
-
- n = -Nsym*Ts/2:T:Nsym*Ts/2;
- Nfilter = Nsym*M;
- Nfiltertiming = M+Nfilter+M;
-
- sincNum = sin(pi*n/Ts); % numerator of the sinc function
- sincDen = (pi*n/Ts); % denominator of the sinc function
- sincDenZero = find(abs(sincDen) < 10^-10);
- sincOp = sincNum./sincDen;
- sincOp(sincDenZero) = 1; % sin(pix/(pix) =1 for x =0
-
- cosNum = cos(alpha*pi*n/Ts);
- cosDen = (1-(2*alpha*n/Ts).^2);
- cosDenZero = find(abs(cosDen)<10^-10);
- cosOp = cosNum./cosDen;
- cosOp(cosDenZero) = pi/4;
- gt_alpha5 = sincOp.*cosOp;
- Nfft = 4096;
- GF_alpha5 = fft(gt_alpha5,Nfft)/M;
-
- % sqrt causes stop band to be amplified, this hack pushes it down again
-
- for i=1:Nfft
- if (abs(GF_alpha5(i)) < 0.02)
- GF_alpha5(i) *= 0.001;
- endif
- end
- GF_alpha5_root = sqrt(abs(GF_alpha5)) .* exp(j*angle(GF_alpha5));
- ifft_GF_alpha5_root = ifft(GF_alpha5_root);
- coeffs = real((ifft_GF_alpha5_root(1:Nfilter)));
-endfunction
+++ /dev/null
-% glottal.m
-% David Rowe 12 Sep 2009
-% Matlab script to generate the phase spectra of a glottal pulse
-
-% lpc10 pulse from spandsp. When the file glottal.c was used as a part of the
-% excitation phase component in phase.c, phase_synth_zero_order(), no difference
-% in speech quality was apparent. So left out of code for now.
-
-sh=12
-kexc = [ 8, -16, 26, -48, 86, -162, 294, -502, 718, -728, 184 672, -610, -672, 184, 728, 718, 502, 294, 162, 86, 48, 26, 16, 8];
-kexc = shift(kexc,sh);
-kexc = [kexc(1:sh) zeros(1,512-25) kexc(sh+1:25)];
-figure(1)
-clf
-plot(kexc)
-figure(2)
-G = fft(kexc);
-subplot(211)
-plot((1:256)*(4000/256),unwrap(angle(G(1:256))))
-subplot(212)
-plot(20*log10(abs(G)))
-
-f=fopen("glottal.c","wt");
-fprintf(f,"const float glottal[]={\n");
-for m=1:255
- fprintf(f," %f,\n",angle(G(m)));
-endfor
-fprintf(f," %f};\n",angle(G(256)));
-fclose(f);
+++ /dev/null
-% hp_filt.m
-% David Rowe 20 Feb 2012
-
-function hp_filt(in_file, out_file)
- fin = fopen(in_file,"rb");
- s = fread(fin,Inf,"short");
- b = fir1(256, 300/4000, "high");
- freqz(b);
- s_hpf = filter(b,1,s);
- fout = fopen(out_file,"wb");
- fwrite(fout, s_hpf, "short");
-endfunction
+++ /dev/null
-% load_raw.m
-% David Rowe 7 Oct 2009
-
-function s = load_raw(fn)
- fs=fopen(fn,"rb");
- s = fread(fs,Inf,"short");
- plot(s)
-endfunction
+++ /dev/null
-% lpcpf.m
-% David Rowe Aug 27 2012
-% Experiments with LPC post filtering
-
-function lpcpf(ak_filename, f)
- aks = load(ak_filename);
-
- ak = aks(f,:);
- [tmp p] = size(ak);
- p -= 1;
-
- A = freqz(1,ak, 4000);
- AdB = 20*log10(abs(A));
-
- gamma = 0.5;
- gammas = gamma .^ (0:p);
- W = freqz(ak .* gammas,1, 4000);
- WdB = 20*log10(abs(W));
-
- beta = 0.2;
- R = abs(freqz(ak .* gammas, ak, 4000));
- %P = (R/max(R)) .^ beta;
- P = R .^ beta;
- AP = abs(A) .* P;
-
- eA = sum(abs(A) .^ 2);
- eAP = sum(AP .^ 2);
- gain = sqrt(eA/eAP)
- AP *= gain;
-
- PdB = 20*log10(P);
-
- APdB = 20*log10(AP);
- 10*log10(sum(AP .^ 2))/10*log10(sum(abs(A) .^ 2))
-
- figure(1);
- clf;
- plot(AdB);
- hold on;
- plot(WdB,'g');
- plot(PdB,'r');
- plot(APdB,'b.');
- hold off;
-
-endfunction
-
+++ /dev/null
-% lsp_pdf.m
-% David Rowe 2 Oct 2009
-% Plots histograms (PDF estimates) of LSP training data
-
-function lsp_pdf(lsp)
- [r,c] = size(lsp);
-
- % LSPs
-
- figure(1);
- clf;
- [x,y] = hist(lsp(:,1),100);
- plot(y*4000/pi,x,"+;1;");
- hold on;
- for i=2:5
- [x,y] = hist(lsp(:,i),100);
- legend = sprintf("+%d;%d;",i,i);
- plot(y*4000/pi,x,legend);
- endfor
- for i=6:c
- [x,y] = hist(lsp(:,i),100);
- legend = sprintf("+%d;%d;",i-5,i);
- plot(y*4000/pi,x,legend);
- endfor
- hold off;
- grid;
-
- % LSP differences
-
- figure(2);
- clf;
- subplot(211)
- [x,y] = hist(lsp(:,1),100);
- plot(y*4000/pi,x,"1;1;");
- hold on;
- for i=2:5
- [x,y] = hist(lsp(:,i) - lsp(:,i-1),100);
- legend = sprintf("%d;%d;",i,i);
- plot(y*4000/pi,x,legend);
- endfor
- hold off;
- grid;
-
- subplot(212)
- [x,y] = hist(lsp(:,6)-lsp(:,5),100);
- plot(y*4000/pi,x,"1;6;");
- hold on;
- for i=7:c
- [x,y] = hist(lsp(:,i) - lsp(:,i-1),100);
- legend = sprintf("%d;%d;",i-5,i);
- plot(y*4000/pi,x,legend);
- endfor
- hold off;
- grid;
-
- % LSP differences delta from last frame
-
- lspd(:,1) = lsp(:,1);
- lspd(:,2:10) = lsp(:,2:10) - lsp(:,1:9);
-
- [m,n] = size(lspd);
- lspdd = lspd(5:m,:) - lspd(1:m-4,:);
-
- figure(3);
- clf;
- subplot(211)
- for i=1:5
- [x,y] = hist(lspdd(:,i),100);
- legend = sprintf("%d;%d;",i,i);
- plot(y*4000/pi,x,legend);
- hold on;
- endfor
- hold off;
- grid;
- axis([-200 200 0 35000]);
-
- subplot(212)
- for i=6:10
- [x,y] = hist(lspdd(:,i),100);
- legend = sprintf("%d;%d;",i-5,i);
- plot(y*4000/pi,x,legend);
- hold on;
- endfor
- hold off;
- grid;
- axis([-200 200 0 16000]);
-
- figure(4);
- clf;
- plot((4000/pi)*(lsp(2:r,3)-lsp(1:r-1,3)))
-endfunction
+++ /dev/null
-% lspwarp.m
-% David Rowe Sep 2012
-%
-% Experimenting with non-linear LSP frequency axis for LSP quantisation
-% Plots a scaled mel axis.
-
-1;
-
-function mel = freq2mel(f)
- mel = 70*log10(1 + f/700);
-endfunction
-
-function freq = mel2freq(m)
- freq = 700*(10 ^ (m/70) - 1);
-endfunction
-
-x = []; y = [];
-
-for freq = 100:25:4000
- mel = freq2mel(freq);
- x = [x freq];
- y = [y mel];
-end
-
-plot(x,y)
-grid
-
-mel_start = floor(freq2mel(100));
-mel_end = floor(freq2mel(4000));
-
-x = []; y = [];
-for mel=mel_start:mel_end
- freq = mel2freq(mel);
- x = [x freq];
- y = [y mel];
-end
-
-hold on;
-plot(x,y, '+')
-hold off;
+++ /dev/null
-% phase.m
-% David Rowe August 2009
-% experiments with phase for sinusoidal codecs
-
-function phase(samname, F0, png)
- Wo=2*pi*F0/8000;
- P=2*pi/Wo;
- L = floor(pi/Wo);
- Nsam = 16000;
- N = 80;
- F = Nsam/N;
- A = 10000/L;
- phi = zeros(1,L);
- s = zeros(1,Nsam);
-
- for m=floor(L/2):L
- phi_off(m) = -m*Wo*8;
- end
-
- for f=1:F
- phi(1) = phi(1) + Wo*N;
- phi(1) = mod(phi(1),2*pi);
-
- for m=1:L
- phi(m) = m*phi(1);
- end
-
- x = zeros(1,N);
- for m=1:L
- x = x + A*cos(m*Wo*(0:(N-1)) + phi(m));
- endfor
- s((f-1)*N+1:f*N) = x;
- endfor
-
- figure(1);
- clf;
- plot(s(1:250));
-
- fs=fopen(samname,"wb");
- fwrite(fs,s,"short");
- fclose(fs);
-
- if (nargin == 3)
- % small image to fit blog
-
- __gnuplot_set__ terminal png size 450,300
- ss = sprintf("__gnuplot_set__ output \"%s.png\"", samname);
- eval(ss)
- replot;
-
- % for some reason I need this to stop large plot getting wiped
- __gnuplot_set__ output "/dev/null"
- endif
-
-endfunction
-
+++ /dev/null
-% phase2.m
-% David Rowe Sep 2009
-% experiments with phase for sinusoidal codecs, looking at phase
-% of excitation with real Am samples from hts1
-
-function phase2(samname, png)
- N = 16000;
-
- f=43;
- model = load("../src/hts1a_phase_model.txt");
- phase = load("../src/hts1a_phase_phase.txt");
- Wo = model(f,1);
- P=2*pi/Wo;
- L = model(f,2);
- A = model(f,3:(L+2));
- phi = phase(f,1:L);
- phi = zeros(1,L);
- phi(3) = -pi/2;
- phi(4) = -pi/4;
- phi(5) = pi/2;
-
- s = zeros(1,N);
-
- for m=3:5
- s_m = A(m)*cos(m*Wo*(0:(N-1)) + phi(m));
- s = s + s_m;
- endfor
-
- figure(1);
- clf;
- plot(s(1:250));
-
- figure(2);
- clf;
- subplot(211)
- plot((1:L)*Wo*4000/pi, 20*log10(A),'+');
- subplot(212)
- plot((1:L)*Wo*4000/pi, phi,'+');
-
- fs=fopen(samname,"wb");
- fwrite(fs,s,"short");
- fclose(fs);
-
- if (nargin == 2)
- % small image to fit blog
-
- __gnuplot_set__ terminal png size 450,300
- ss = sprintf("__gnuplot_set__ output \"%s.png\"", samname);
- eval(ss)
- replot;
-
- % for some reason I need this to stop large plot getting wiped
- __gnuplot_set__ output "/dev/null"
- endif
-
-endfunction
-
+++ /dev/null
-% phasesecord.m
-% David Rowe Aug 2012
-% Used to experiment with aproximations of phase of 2nd order systems
-
-function phasesecord(w,beta)
-
- a = [1 -2*cos(w)*beta beta*beta];
- b = 1;
-
- [h w1] = freqz(b,a);
-
- figure(1)
- subplot(211)
- plot(abs(h))
- subplot(212)
- plot(angle(h))
-
- % for beta close to 1, we approximate 3 dB points as 1-beta above
- % and below the resonance freq. Note this fails if w=0 as there is a
- % double pole. Lets sample the freq response at the 3dB points and
- % w:
-
- ws = [w-(1-beta) w w+(1-beta)];
- [h w1] = freqz(b,a,ws);
-
- % gain as a fraction of max, should be 3dB. Within 1.3 dB or for w > pi/8,
- % gets innacurate near w=0 due to 2nd pole
-
- printf("mag measured...:"); printf("% 4.3f ", abs(h)/max(abs(h)));
-
- % measured angle, 45 deg from angle at w
-
- printf("\nangle measured.: "); printf("% 5.3f ", angle(h));
-
- % Our estimate of angle, (pi+w) is phase at resonance, at lower 3dB
- % phase is pi/4 ahead, at upper 3B pi/4 behind. -pi/2 is contribution of
- % other pole at at -w to phase
-
- ph_lower = (pi+w) + pi/4 - pi/2;
- ph_res =(pi+w) - pi/2;
- ph_upper = (pi+w) - pi/4 - pi/2;
- ph_ests = [ph_lower ph_res ph_upper];
- ph_ests = ph_ests - 2*pi*(floor(ph_ests/(2*pi)) + 0.5);
- printf("\nangle estimated:"); printf("% 5.3f ", ph_ests);
- printf("\n");
-endfunction
-
+++ /dev/null
-% pitch_test.m
-% David Rowe Sep 2009
-% Constructs a sequence to test the pitch estimator
-
-function pitch_test(samname)
- M=320;
- F=200;
-
- fs=fopen(samname,"wb");
-
- f0 = 100;
- for f=1:200
- Wo=2*pi*f0/8000;
- P=2*pi/Wo;
- L = floor(pi/Wo);
- A = 10000/L;
- phi = zeros(1,L);
- s = zeros(1,M);
-
- for m=1:L
- s = s + A*cos(m*Wo*(0:(M-1)) + phi(m));
- endfor
-
- figure(1);
- clf;
- plot(s);
-
- fwrite(fs,s,"short");
-
- f0 = f0 + 5;
- if (f0 > 400)
- f0 = 100;
- endif
- endfor
-
- fclose(fs);
-
-endfunction
-
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plots a raw speech sample file, you can optionally specify the start and end
-% samples and create a large and small PNGs
-
-function pl(samname1, start_sam, end_sam, pngname)
-
- fs=fopen(samname1,"rb");
- s=fread(fs,Inf,"short");
-
- st = 1;
- en = length(s);
- if (nargin >= 2)
- st = start_sam;
- endif
- if (nargin >= 3)
- en = end_sam;
- endif
-
- figure(1);
- clf;
- plot(s(st:en));
- axis([1 en-st 1.1*min(s) 1.1*max(s)]);
-
- if (nargin == 4)
-
- % small image
-
- __gnuplot_set__ terminal png size 420,300
- ss = sprintf("__gnuplot_set__ output \"%s.png\"", pngname);
- eval(ss)
- replot;
-
- % larger image
-
- __gnuplot_set__ terminal png size 800,600
- ss = sprintf("__gnuplot_set__ output \"%s_large.png\"", pngname);
- eval(ss)
- replot;
-
- endif
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-
-function pl2(samname1, samname2, start_sam, end_sam, pngname)
-
- fs1=fopen(samname1,"rb");
- s1=fread(fs1,Inf,"short");
- fs2=fopen(samname2,"rb");
- s2=fread(fs2,Inf,"short");
-
- st = 1;
- en = length(s1);
- if (nargin >= 3)
- st = start_sam;
- endif
- if (nargin >= 4)
- en = end_sam;
- endif
-
- figure(1);
- clf;
- subplot(211);
- l1 = strcat("r;",samname1,";");
- plot(s1(st:en), l1);
- axis([1 en-st min(s1(st:en)) max(s1(st:en))]);
- subplot(212);
- l2 = strcat("r;",samname2,";");
- plot(s2(st:en),l2);
- axis([1 en-st min(s1(st:en)) max(s1(st:en))]);
-
- if (nargin == 5)
-
- % small image
-
- __gnuplot_set__ terminal png size 420,300
- s = sprintf("__gnuplot_set__ output \"%s.png\"", pngname);
- eval(s)
- replot;
-
- % larger image
-
- __gnuplot_set__ terminal png size 800,600
- s = sprintf("__gnuplot_set__ output \"%s_large.png\"", pngname);
- eval(s)
- replot;
-
- endif
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot ampltiude modelling information from dump files.
-
-function plamp(samname, f, samname2)
-
- % switch some stuff off to unclutter display
-
- plot_lsp = 0;
- plot_snr = 0;
- plot_vsnr = 0;
- plot_sw = 0;
- plot_pw = 0;
-
- sn_name = strcat(samname,"_sn.txt");
- Sn = load(sn_name);
-
- sw_name = strcat(samname,"_sw.txt");
- Sw = load(sw_name);
-
- sw__name = strcat(samname,"_sw_.txt");
- if (file_in_path(".",sw__name))
- Sw_ = load(sw__name);
- endif
-
- ew_name = strcat(samname,"_ew.txt");
- if (file_in_path(".",ew_name))
- Ew = load(ew_name);
- endif
-
- rk_name = strcat(samname,"_rk.txt");
- if (file_in_path(".",rk_name))
- Rk = load(rk_name);
- endif
-
- model_name = strcat(samname,"_model.txt");
- model = load(model_name);
-
- modelq_name = strcat(samname,"_qmodel.txt");
- if (file_in_path(".",modelq_name))
- modelq = load(modelq_name);
- endif
-
- pw_name = strcat(samname,"_pw.txt");
- if (file_in_path(".",pw_name))
- Pw = load(pw_name);
- endif
-
- lsp_name = strcat(samname,"_lsp.txt");
- if (file_in_path(".",lsp_name))
- lsp = load(lsp_name);
- endif
-
- phase_name = strcat(samname,"_phase.txt");
- if (file_in_path(".",phase_name))
- phase = load(phase_name);
- endif
-
- phase_name_ = strcat(samname,"_phase_.txt");
- if (file_in_path(".",phase_name_))
- phase_ = load(phase_name_);
- endif
-
- snr_name = strcat(samname,"_snr.txt");
- if (file_in_path(".",snr_name))
- snr = load(snr_name);
- endif
-
- % optional second file, for exploring post filter
-
- model2q_name = " ";
- if nargin == 3
- model2q_name = strcat(samname2,"_qmodel.txt");
- if file_in_path(".",modelq_name)
- model2q = load(model2q_name);
- end
- end
-
- Ew_on = 1;
- k = ' ';
- do
- figure(1);
- clf;
-% s = [ Sn(2*(f-2)-1,:) Sn(2*(f-2),:) ];
- s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- size(s);
- plot(s);
- axis([1 length(s) -20000 20000]);
-
- figure(2);
- Wo = model(f,1);
- L = model(f,2);
- Am = model(f,3:(L+2));
- plot((1:L)*Wo*4000/pi, 20*log10(Am),";Am;r");
- axis([1 4000 -10 80]);
- hold on;
- if plot_sw
- plot((0:255)*4000/256, Sw(f,:),";Sw;");
- end
-
- if (file_in_path(".",modelq_name))
- Amq = modelq(f,3:(L+2));
- plot((1:L)*Wo*4000/pi, 20*log10(Amq),";Amq;g" );
- if (file_in_path(".",pw_name) && plot_pw)
- plot((0:255)*4000/256, 10*log10(Pw(f,:)),";Pw;c");
- endif
- signal = Am * Am';
- noise = (Am-Amq) * (Am-Amq)';
- snr1 = 10*log10(signal/noise);
- Am_err_label = sprintf(";Am error SNR %4.2f dB;m",snr1);
- plot((1:L)*Wo*4000/pi, 20*log10(Amq) - 20*log10(Am), Am_err_label);
- endif
-
- if file_in_path(".",model2q_name)
- Amq2 = model2q(f,3:(L+2));
- plot((1:L)*Wo*4000/pi, 20*log10(Amq2),";Amq2;m" );
- end
-
- if (file_in_path(".",snr_name) && plot_vsnr)
- snr_label = sprintf(";Voicing SNR %4.2f dB;",snr(f));
- plot(1,1,snr_label);
- endif
-
- % phase model - determine SNR and error spectrum for phase model 1
-
- if (file_in_path(".",phase_name_))
- orig = Am.*exp(j*phase(f,1:L));
- synth = Am.*exp(j*phase_(f,1:L));
- signal = orig * orig';
- noise = (orig-synth) * (orig-synth)';
- snr_phase = 10*log10(signal/noise);
-
- %phase_err_label = sprintf(";phase_err SNR %4.2f dB;",snr_phase);
- %plot((1:L)*Wo*4000/pi, 20*log10(orig-synth), phase_err_label);
- endif
-
- if (file_in_path(".",lsp_name) && plot_lsp)
- for l=1:10
- plot([lsp(f,l)*4000/pi lsp(f,l)*4000/pi], [60 80], 'r');
- endfor
- endif
-
- hold off;
-
- %if (file_in_path(".",phase_name))
- %figure(3);
- %plot((1:L)*Wo*4000/pi, phase(f,1:L), ";phase;");
- %axis;
- %if (file_in_path(".",phase_name_))
- %hold on;
- %plot((1:L)*Wo*4000/pi, phase_(f,1:L), ";phase_;");
- %hold off;
- %endif
- %figure(2);
- %endif
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back p-png q-quit e-toggle Ew", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- endif
- if (k == 'b')
- f = f - 1;
- endif
- if (k == 'e')
- if (Ew_on == 1)
- Ew_on = 0;
- else
- Ew_on = 1;
- endif
- endif
-
- % optional print to PNG
-
- if (k == 'p')
- figure(1);
- pngname = sprintf("%s_%d_sn.png",samname,f);
- print(pngname, '-dpng', "-S500,500")
- pngname = sprintf("%s_%d_sn_large.png",samname,f);
- print(pngname, '-dpng', "-S800,600")
-
- figure(2);
- pngname = sprintf("%s_%d_sw.png",samname,f);
- print(pngname, '-dpng', "-S500,500")
- pngname = sprintf("%s_%d_sw_large.png",samname,f);
- print(pngname, '-dpng', "-S1200,800")
- endif
-
- until (k == 'q')
- printf("\n");
-
-endfunction
+++ /dev/null
-load ../unittest/tinterp_prev.txt;
-load ../unittest/tinterp_interp.txt;
-load ../unittest/tinterp_next.txt;
-
-clf;
-plot(tinterp_prev(:,1), 20.0*log10(tinterp_prev(:,2)),";prev;")
-hold on;
-plot(tinterp_interp(:,1), 20.0*log10(tinterp_interp(:,2)),'g+-;interp;')
-plot(tinterp_next(:,1), 20.0*log10(tinterp_next(:,2)),'ro-;next;')
-hold off;
-axis([0 pi 0 80])
+++ /dev/null
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot amplitude modelling information from dump files to test and develop
-% LPC post filter.
-
-function pllpcpf(samname, f)
-
- % switch some stuff off to unclutter display
-
- plot_Am = 0;
- plot_Amq = 0;
- plot_err = 0;
- plot_lsp = 0;
- plot_snr = 0;
- plot_vsnr = 0;
- plot_sw = 0;
- plot_pw = 1;
- plot_pwb = 1;
- plot_rw = 1;
-
- sn_name = strcat(samname,"_sn.txt");
- Sn = load(sn_name);
-
- sw_name = strcat(samname,"_sw.txt");
- Sw = load(sw_name);
-
- sw__name = strcat(samname,"_sw_.txt");
- if (file_in_path(".",sw__name))
- Sw_ = load(sw__name);
- endif
-
- model_name = strcat(samname,"_model.txt");
- model = load(model_name);
-
- modelq_name = strcat(samname,"_qmodel.txt");
- if (file_in_path(".",modelq_name))
- modelq = load(modelq_name);
- endif
-
- % Pw (LPC synth filter spectrum) before post filter
-
- pwb_name = strcat(samname,"_pwb.txt");
- if (file_in_path(".",pwb_name))
- Pwb = load(pwb_name);
- endif
-
- % Rw (Post filter spectrum)
-
- rw_name = strcat(samname,"_rw.txt");
- if (file_in_path(".",rw_name))
- Rw = load(rw_name);
- endif
-
- % Pw (LPC synth filter spectrum) after post filter
-
- pw_name = strcat(samname,"_pw.txt");
- if (file_in_path(".",pw_name))
- Pw = load(pw_name);
- endif
-
-
- Ew_on = 1;
- k = ' ';
- do
- figure(1);
- clf;
- s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- size(s);
- plot(s);
- axis([1 length(s) -20000 20000]);
-
- figure(2);
- clf;
- Wo = model(f,1);
- L = model(f,2);
- Am = model(f,3:(L+2));
- if plot_Am
- plot((1:L)*Wo*4000/pi, 20*log10(Am),";Am;r");
- end
- axis([1 4000 -10 80]);
- hold on;
- if plot_sw
- plot((0:255)*4000/256, Sw(f,:),";Sw;");
- end
-
- if (file_in_path(".",modelq_name))
-
- Amq = modelq(f,3:(L+2));
- if plot_Amq
- plot((1:L)*Wo*4000/pi, 20*log10(Amq),";Amq;g" );
- end
-
- if (file_in_path(".",pwb_name) && plot_pwb)
- plot((0:255)*4000/256, 10*log10(Pwb(f,:)),";Pwb;r");
- endif
-
- if (file_in_path(".",rw_name) && plot_rw)
- plot((0:255)*4000/256, 10*log10(Rw(f,:)),";Rw;b");
- endif
-
- if (file_in_path(".",pw_name) && plot_pw)
- plot((0:255)*4000/256, 10*log10(Pw(f,:)),";Pw;g.");
- endif
-
- signal = Am * Am';
- noise = (Am-Amq) * (Am-Amq)';
- snr1 = 10*log10(signal/noise);
- Am_err_label = sprintf(";Am error SNR %4.2f dB;m",snr1);
- if plot_err
- plot((1:L)*Wo*4000/pi, 20*log10(Amq) - 20*log10(Am), Am_err_label);
- end
- endif
-
-
- hold off;
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back p-png q-quit", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- endif
- if (k == 'b')
- f = f - 1;
- endif
-
- % optional print to PNG
-
- if (k == 'p')
- figure(1);
- pngname = sprintf("%s_%d_sn.png",samname,f);
- print(pngname, '-dpng', "-S500,500")
- pngname = sprintf("%s_%d_sn_large.png",samname,f);
- print(pngname, '-dpng', "-S800,600")
-
- figure(2);
- pngname = sprintf("%s_%d_sw.png",samname,f);
- print(pngname, '-dpng', "-S500,500")
- pngname = sprintf("%s_%d_sw_large.png",samname,f);
- print(pngname, '-dpng', "-S1200,800")
- endif
-
- until (k == 'q')
- printf("\n");
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2010
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plots a bunch of information related to LSP quantisation:
-% - speech file
-% - LSPs before and after quantisation
-% - SNR for each frame
-%
-% Note: there is a 160 sample (two frame delay) from the when a sample
-% enters the input buffer until it is at the centre of the analysis window
-
-function pllsp(rawfile,
- dumpfile_prefix_lpc_only,
- dumpfile_prefix_lsp,
- start_f, end_f)
-
- fs=fopen(rawfile,"rb");
- s=fread(fs,Inf,"short");
-
- lpc_snr_name = strcat(dumpfile_prefix_lpc_only,"_lpc_snr.txt");
- lpc10_snr = load(lpc_snr_name);
- lpc_snr_name = strcat(dumpfile_prefix_lsp,"_lpc_snr.txt");
- lsp_snr = load(lpc_snr_name);
-
- lsp_name = strcat(dumpfile_prefix_lsp,"_lsp.txt");
- lsps = load(lsp_name);
- [m,n]=size(lsps);
- lsp = lsps(1:2:m,:);
- lsp_ = lsps(2:2:m,:);
-
- figure(1);
- clf;
- subplot(211);
- sp = s((start_f-2)*80:(end_f-2)*80);
- plot(sp);
-
- subplot(212);
- plot(lpc10_snr((start_f+1):end_f)-lsp_snr((start_f+1):end_f));
-
- figure(2);
- plot((4000/pi)*lsp((start_f+1):end_f,:));
- hold on;
- plot((4000/pi)*lsp_((start_f+1):end_f,:),'+-');
- hold off;
-endfunction
+++ /dev/null
-% pllspdt.m
-% Copyright David Rowe 2010
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Test script to plot differences in LSps between frames
-
-function pllspdt(rawfile,dumpfile_prefix_lsp,lspn, start_f, end_f)
-
- fs=fopen(rawfile,"rb");
- s=fread(fs,Inf,"short");
-
- lsp_name = strcat(dumpfile_prefix_lsp,"_lsp.txt");
- lsps = load(lsp_name);
- [m,n]=size(lsps);
- lsp = lsps(1:2:m,:);
- lsp_ = lsps(2:2:m,:);
- lspdt = lsp(2:m/2,:) - lsp(1:m/2-1,:);
-
- figure(1);
- clf;
- sp = s((start_f-2)*80:(end_f-2)*80);
- plot(sp);
-
- figure(2);
- plot((4000/pi)*lspdt((start_f+1):end_f,lspn));
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot NLP states from dump files.
-
-function plnlp(samname, f)
-
- sn_name = strcat(samname,"_sn.txt");
- Sn = load(sn_name);
-
- sw_name = strcat(samname,"_sw.txt");
- Sw = load(sw_name);
-
- fw_name = strcat(samname,"_fw.txt");
- if (file_in_path(".",fw_name))
- fw = load(fw_name);
- endif
-
- e_name = strcat(samname,"_e.txt");
- if (file_in_path(".",e_name))
- e = load(e_name);
- endif
-
- p_name = strcat(samname,".p");
- if (file_in_path(".",p_name))
- p = load(p_name);
- endif
-
- sq_name = strcat(samname,"_sq.txt");
- if (file_in_path(".",sq_name))
- sq = load(sq_name);
- endif
-
- dec_name = strcat(samname,"_dec.txt");
- if (file_in_path(".",dec_name))
- dec = load(dec_name);
- endif
-
- do
- figure(1);
- clf;
- s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- plot(s, ";Sn;");
- grid
- axis([1 length(s) -20000 20000]);
-
- figure(2);
- plot((0:255)*4000/256, Sw(f,:),";Sw;");
- grid
- axis([1 4000 -10 80]);
- hold on;
-
- f0 = 8000/p(f);
- Wo = 2*pi/p(f);
- L = floor(pi/Wo);
- f0_label = sprintf("b;P=%3.1f F0=%3.0f;",p(f),f0);
- for m=1:L-1
- plot([ m*Wo*4000/pi m*Wo*4000/pi], [10 60], 'b');
- endfor
- plot([ L*Wo*4000/pi L*Wo*4000/pi], [10 60], f0_label);
-
- hold off;
-
- if (file_in_path(".",fw_name))
- figure(3);
- if (file_in_path(".",e_name))
- subplot(211);
- endif
- plot((0:255)*800/256, fw(f,:)/max(fw(f,:)), ";Fw;");
- axis([1 400 0 1]);
- if (file_in_path(".",e_name))
- subplot(212);
- e_concat = [ e(2*f-1,:) e(2*f,:) ];
- plot(e_concat(1:400)/max(e_concat(1:400)), "+;MBE E(f);");
- axis([1 400 0 1]);
- endif
- endif
-
- if (file_in_path(".",sq_name))
- figure(4);
- sq_concat = [ sq(2*f-1,:) sq(2*f,:) ];
- axis
- plot(sq_concat, ";sq;");
- endif
-
- if (file_in_path(".",dec_name))
- figure(5);
- plot(dec(f,:), ";dec;");
- endif
-
- figure(2);
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back p-png q-quit ", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- endif
- if (k == 'b')
- f = f - 1;
- endif
-
- % optional print to PNG
-
- if (k == 'p')
-
- pngname = sprintf("%s_%d",samname,f);
-
- % small image
-
- __gnuplot_set__ terminal png size 420,300
- ss = sprintf("__gnuplot_set__ output \"%s.png\"", pngname);
- eval(ss)
- replot;
-
- % larger image
-
- __gnuplot_set__ terminal png size 800,600
- ss = sprintf("__gnuplot_set__ output \"%s_large.png\"", pngname);
- eval(ss)
- replot;
-
- % for some reason I need this to stop large plot getting wiped
- __gnuplot_set__ output "/dev/null"
-
- endif
-
- until (k == 'q')
- printf("\n");
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot phase modelling information from dump files.
-
-function plphase(samname, f)
-
- sn_name = strcat(samname,"_sn.txt");
- Sn = load(sn_name);
-
- sw_name = strcat(samname,"_sw.txt");
- Sw = load(sw_name);
-
- model_name = strcat(samname,"_model.txt");
- model = load(model_name);
-
- sw__name = strcat(samname,"_sw_.txt");
- if (file_in_path(".",sw__name))
- Sw_ = load(sw__name);
- endif
-
- pw_name = strcat(samname,"_pw.txt");
- if (file_in_path(".",pw_name))
- Pw = load(pw_name);
- endif
-
- ak_name = strcat(samname,"_ak.txt");
- if (file_in_path(".",ak_name))
- ak = load(ak_name);
- endif
-
- phase_name = strcat(samname,"_phase.txt");
- if (file_in_path(".",phase_name))
- phase = load(phase_name);
- endif
-
- phase_name_ = strcat(samname,"_phase_.txt");
- if (file_in_path(".",phase_name_))
- phase_ = load(phase_name_);
- endif
-
- snr_name = strcat(samname,"_snr.txt");
- if (file_in_path(".",snr_name))
- snr = load(snr_name);
- endif
-
- sn_name_ = strcat(samname,".raw");
- if (file_in_path(".",sn_name_))
- fs_ = fopen(sn_name_,"rb");
- sn_ = fread(fs_,Inf,"short");
- endif
-
- k = ' ';
- do
- figure(1);
- clf;
- s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- plot(s);
- grid;
- axis([1 length(s) -20000 20000]);
- if (k == 'p')
- pngname = sprintf("%s_%d_sn",samname,f);
- png(pngname);
- endif
-
- figure(2);
- Wo = model(f,1);
- L = model(f,2);
- Am = model(f,3:(L+2));
- plot((1:L)*Wo*4000/pi, 20*log10(Am),"r;Am;");
- axis([1 4000 -10 80]);
- hold on;
- plot((0:255)*4000/256, Sw(f,:),";Sw;");
- grid;
-
- if (file_in_path(".",sw__name))
- plot((0:255)*4000/256, Sw_(f,:),"g;Sw_;");
- endif
-
- if (file_in_path(".",pw_name))
- plot((0:255)*4000/256, 10*log10(Pw(f,:)),";Pw;");
- endif
-
- if (file_in_path(".",snr_name))
- snr_label = sprintf(";phase SNR %4.2f dB;",snr(f));
- plot(1,1,snr_label);
- endif
-
- % phase model - determine SNR and error spectrum for phase model 1
-
- if (file_in_path(".",phase_name_))
- orig = Am.*exp(j*phase(f,1:L));
- synth = Am.*exp(j*phase_(f,1:L));
- signal = orig * orig';
- noise = (orig-synth) * (orig-synth)';
- snr_phase = 10*log10(signal/noise);
-
- phase_err_label = sprintf("g;phase_err SNR %4.2f dB;",snr_phase);
- plot((1:L)*Wo*4000/pi, 20*log10(orig-synth), phase_err_label);
- endif
-
- hold off;
- if (k == 'p')
- pngname = sprintf("%s_%d_sw",samname,f);
- png(pngname);
- endif
-
- if (file_in_path(".",phase_name))
- figure(3);
- plot((1:L)*Wo*4000/pi, phase(f,1:L)*180/pi, "-o;phase;");
- axis;
- if (file_in_path(".", phase_name_))
- hold on;
- plot((1:L)*Wo*4000/pi, phase_(f,1:L)*180/pi, "g;phase after;");
- grid
- hold off;
- endif
- if (k == 'p')
- pngname = sprintf("%s_%d_phase",samname,f);
- png(pngname);
- endif
- endif
-
- % synthesised speech
-
- if (file_in_path(".",sn_name_))
- figure(4);
- s_ = sn_((f-3)*80+1:(f+1)*80);
- plot(s_);
- axis([1 length(s_) -20000 20000]);
- if (k == 'p')
- pngname = sprintf("%s_%d_sn_",samname,f)
- png(pngname);
- endif
- endif
-
- if (file_in_path(".",ak_name))
- figure(5);
- axis;
- akw = ak(f,:);
- weight = 1.0 .^ (0:length(akw)-1);
- akw = akw .* weight;
- H = 1./fft(akw,8000);
- subplot(211);
- plot(20*log10(abs(H(1:4000))),";LPC mag spec;");
- grid;
- subplot(212);
- plot(angle(H(1:4000))*180/pi,";LPC phase spec;");
- grid;
- if (k == 'p')
- % stops multimode errors from gnuplot, I know not why...
- figure(2);
- figure(5);
-
- pngname = sprintf("%s_%d_lpc",samname,f);
- png(pngname);
- endif
- endif
-
-
- % autocorrelation function to research voicing est
-
- %M = length(s);
- %sw = s .* hanning(M)';
- %for k=0:159
- % R(k+1) = sw(1:320-k) * sw(1+k:320)';
- %endfor
- %figure(4);
- %R_label = sprintf(";R(k) %3.2f;",max(R(20:159))/R(1));
- %plot(R/R(1),R_label);
- %grid
-
- figure(2);
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back p-png q-quit ", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- endif
- if (k == 'b')
- f = f - 1;
- endif
-
- % optional print to PNG
-
- if (k == 'p')
- pngname = sprintf("%s_%d",samname,f);
- png(pngname);
- endif
-
- until (k == 'q')
- printf("\n");
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% plpitch.m
-% Plots two pitch tracks on top of each other, used for comparing pitch
-% estimators
-
-function plpitch(pitch1_name, pitch2_name, start_fr, end_fr)
-
- pitch1 = load(pitch1_name);
- pitch2 = load(pitch2_name);
-
- st = 1;
- en = length(pitch1);
- if (nargin >= 3)
- st = start_fr;
- endif
- if (nargin >= 4)
- en = end_fr;
- endif
-
- figure(1);
- clf;
- l1 = strcat("r;",pitch1_name,";")
- l1
- st
- en
- plot(pitch1(st:en), l1);
- axis([1 en-st 20 160]);
- l2 = strcat("g;",pitch2_name,";");
- hold on;
- plot(pitch2(st:en),l2);
- hold off;
-endfunction
-
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot two sparse phase prediction error text files.
-% Generate data from print_pred_error, print_pred_error_sparse_wo_correction1 etc
-
-function plppe(ppe1_file, ppe2_file, f)
-
- ppe1 = load(ppe1_file);
- ppe2 = load(ppe2_file);
-
- std1 = std(nonzeros(ppe1(:,40:80)));
- std2 = std(nonzeros(ppe2(:,40:80)));
-
- printf("std dev for %s is %4.3f\n", ppe1_file, std1);
- printf("std dev for %s is %4.3f\n", ppe2_file, std2);
-
- figure(1);
- clf;
- subplot(211)
- hist(nonzeros(ppe1(:,40:80)),20);
- subplot(212)
- hist(nonzeros(ppe2(:,40:80)),20);
-
- k = ' ';
- do
- figure(2);
- clf;
- subplot(211)
- L = length(nonzeros(ppe1(f,:)));
- x = (1:L)*4000/L;
- std1 = std(nonzeros(ppe1(f,:)));
- legend = sprintf(";std dev %4.3f;", std1);
- plot(x, nonzeros(ppe1(f,:)),legend);
- axis([0 4000 -pi pi]);
- subplot(212)
- std2 = std(nonzeros(ppe2(f,:)));
- legend = sprintf(";std dev %4.3f;", std2);
- plot(x, nonzeros(ppe2(f,:)),legend);
- axis([0 4000 -pi pi]);
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back p-png q-quit ", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- endif
- if (k == 'b')
- f = f - 1;
- endif
-
- % optional print to PNG
-
- if (k == 'p')
- pngname = sprintf("%s_%d",samname,f);
- png(pngname);
- endif
-
- until (k == 'q')
- printf("\n");
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2010
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-% plots the difference of two files
-
-function plsub(samname1, samname2, start_sam, end_sam, pngname)
-
- fs1=fopen(samname1,"rb");
- s1=fread(fs1,Inf,"short");
- fs2=fopen(samname2,"rb");
- s2=fread(fs2,Inf,"short");
-
- st = 1;
- en = length(s1);
- if (nargin >= 3)
- st = start_sam;
- endif
- if (nargin >= 4)
- en = end_sam;
- endif
-
- figure(1);
- clf;
- l1 = strcat("r;",samname1,";");
- plot(s1(st:en) - s2(st:en), l1);
- %axis([1 en-st min(s1(st:en)) max(s1(st:en))]);
-
- if (nargin == 5)
- pngname = sprintf("%s.png",pngname);
- print(pngname, '-dpng', "-S500,500")
- pngname = sprintf("%s_large.png",pngname);
- print(pngname, '-dpng', "-S800,600")
- endif
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot voicing information from sample and dump files.
-%
-% samfilename is the raw source file, e.g. "../raw/hts1a.raw"
-% samname is the dumpfile prefix, e.g. "../src/hts1a"
-%
-% There is a 160 sample (two frame delay) from the when a sample
-% enters the input buffer until it is at the centre of the analysis window
-
-function plvoicing(samfilename, samname, start_f, end_f, pngname)
-
- fs=fopen(samfilename,"rb");
- s=fread(fs,Inf,"short");
-
- snr_name = strcat(samname,"_snr.txt");
- snr = load(snr_name);
- model_name = strcat(samname,"_model.txt");
- model = load(model_name);
-
- Wo = model((start_f+1):end_f,1);
- F0 = Wo*4000/pi;
- dF0 = F0(1:length(Wo)-1) - F0(2:length(Wo));
-
- % work out LP and HP energy
-
- for f=(start_f+1):end_f
- L = model(f,2);
- Am = model(f,3:(L+2));
- L2 = floor(L/2);
- elow = Am(1:L2) * Am(1:L2)';
- ehigh = Am(L2:L) * Am(L2:L)';
- erat(f-(start_f+1)+1) = 10*log10(elow/ehigh);
- endfor
-
- figure(1);
- clf;
- sp = s((start_f-2)*80:(end_f-2)*80);
- plot(sp);
- hold on;
- vhigh = snr((start_f+1):end_f) > 7;
- vlow = snr((start_f+1):end_f) > 4;
-
- % test correction based on erat
-
- vlowadj = vlow;
-
- for f=1:length(erat)-1
- if (vlow(f) == 0)
- if (erat(f) > 10)
- vlowadj(f) = 1;
- endif
- endif
- if (vlow(f) == 1)
- if (erat(f) < -10)
- vlowadj(f) = 0;
- endif
- if (abs(dF0(f)) > 15)
- vlowadj(f) = 0;
- endif
- endif
- endfor
-
- x = 1:(end_f-start_f);
- plot(x*80,snr((start_f+1):end_f)*1000,';SNRdB x 1000;g+');
- plot(x*80,-8000 + vhigh*2000,';7dB thresh;g');
- plot(x*80,-11000 + vlowadj*2000,';vlow with corr;g');
- plot(x*80,erat*1000,';elow/ehigh in dB;r');
- plot(x*80,-14000 + vlow*2000,';4dB thresh;r');
- hold off;
- grid
- if (nargin == 5)
- print(pngname, "-dpng", "-S500,500")
- endif
-
- figure(2)
- Wo = model((start_f+1):end_f,1);
- F0 = Wo*4000/pi;
- dF0 = F0(1:length(Wo)-1) - F0(2:length(Wo));
- %plot(dF0,'+--')
- %hold on;
- %plot([ 1 length(dF0) ], [10 10] ,'r')
- %plot([ 1 length(dF0) ], [-10 -10] ,'r')
- %axis([1 length(dF0) -50 50])
- %hold off;
- plot(F0,'+--')
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Replot current plot as a png, generates small and large versions
-
-function png(pngname)
- % small image
-
- __gnuplot_set__ terminal png size 420,300
- ss = sprintf("__gnuplot_set__ output \"%s.png\"", pngname);
- eval(ss)
- replot;
-
- % larger image
-
- __gnuplot_set__ terminal png size 800,600
- ss = sprintf("__gnuplot_set__ output \"%s_large.png\"", pngname);
- eval(ss)
- replot;
-
- % for some reason I need this to stop large plot getting wiped
- __gnuplot_set__ output "/dev/null"
-
-endfunction
+++ /dev/null
-% Copyright David Rowe 2009
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-% Plot postfilter doing its thing
-
-function postfilter(samname)
- p = load(samname);
- figure(1);
- plot(p(:,1),";energy;");
- hold on;
- plot(p(:,2),";bg_est;");
- hold off;
- grid;
- pngname=sprintf("%s_postfilter_1", samname);
- png(pngname);
-
- figure(2);
- plot(p(:,3),";% unvoiced;");
- grid;
- pngname=sprintf("%s_postfilter_2", samname);
- png(pngname);
-endfunction
-
+++ /dev/null
-% pulse.m
-% David Rowe August 2009
-%
-% Experiments with human pulse perception for sinusoidal codecs
-
-function pulse(samname)
-
- A = 1000;
- K = 16000;
- N = 80;
- frames = K/N;
- s = zeros(1,K);
-
- for f=1:frames
- % lets try placing np random pulses in every frame
-
- P = 20 + (160-20)*rand(1,1);
- Wo = 2*pi/P;
- L = floor(pi/Wo);
- sf = zeros(1,N);
- for m=1:L/2:L
- pos = floor(rand(1,1)*N)+1;
- %pos = 50;
- for l=m:m+L/2-1
- sf = sf + A*cos(l*Wo*((f-1)*N+1:f*N) - pos*l*Wo);
- endfor
- endfor
- s((f-1)*N+1:f*N) = sf;
- endfor
-
- plot(s(1:250));
-
- fs=fopen(samname,"wb");
- fwrite(fs,s,"short");
- fclose(fs);
-endfunction
-
+++ /dev/null
-% sd.m
-% David Rowe Aug 2012
-% Plots the spectal distorion between twofiles of LPCs. Used for LSP
-% quantisation tuning.
-
-function sd(raw_filename, dump_file_prefix, f)
-
- ak1_filename = sprintf("%s_ak.txt", dump_file_prefix);
- ak2_filename = sprintf("%s_ak_.txt", dump_file_prefix);
- ak1 = load(ak1_filename);
- ak2 = load(ak2_filename);
-
- [ak1_r, ak1_c] = size(ak1);
- [ak2_r, ak2_c] = size(ak1);
-
- frames = max([ak1_r ak2_r]);
- sd = zeros(1,frames);
- Ndft = 512;
- A1 = zeros(frames, Ndft);
- A2 = zeros(frames, Ndft);
-
- % initial helicopter view of all frames
-
- for i = 1:frames
- A1(i,:) = -20*log10(abs(fft(ak1(i,:),Ndft)));
- A2(i,:) = -20*log10(abs(fft(ak2(i,:),Ndft)));
- sd(i) = sum((A1(i,:) - A2(i,:)).^2)/Ndft;
- end
- printf("sd av %3.2f dB*dB\n", sum(sd)/frames);
-
- figure(1);
- clf;
- subplot(211)
- fs=fopen(raw_filename,"rb");
- s = fread(fs,Inf,"short");
- plot(s);
- subplot(212)
- plot(sd);
-
- % now enter single step mode so we can analyse each frame
-
- sn_name = strcat(dump_file_prefix,"_sn.txt");
- Sn = load(sn_name);
-
- lsp1_filename = sprintf("%s_lsp.txt", dump_file_prefix);
- lsp2_filename = sprintf("%s_lsp_.txt", dump_file_prefix);
- lsp1 = load(lsp1_filename);
- lsp2 = load(lsp2_filename);
-
- weights_filename = sprintf("%s_weights.txt", dump_file_prefix);
- if file_in_path(".",weights_filename)
- weights = load(weights_filename);
- end
-
- k = ' ';
- do
- figure(2);
- clf;
- subplot(211)
- s = [ Sn(2*f-1,:) Sn(2*f,:) ];
- size(s);
- plot(s);
- axis([1 length(s) -20000 20000]);
-
- subplot(212);
- plot((1:Ndft/2)*4000/(Ndft/2), A1(f,1:(Ndft/2)),";A1;r");
- axis([1 4000 -20 40]);
- hold on;
- plot((1:Ndft/2)*4000/(Ndft/2), A2(f,1:(Ndft/2)),";A2;");
- if file_in_path(".",weights_filename)
- plot(lsp1(f,:)*4000/pi, weights(f,:),";weights;g+");
- end
-
- for l=1:10
- plot([lsp1(f,l)*4000/pi lsp1(f,l)*4000/pi], [0 -10], 'r');
- plot([lsp2(f,l)*4000/pi lsp2(f,l)*4000/pi], [-10 -20], 'b');
- endfor
- plot(0,0,';lsp1;r');
- plot(0,0,';lsp2;b');
- sd_str = sprintf(";sd %3.2f dB*dB;", sd(f));
- plot(0,0,sd_str);
-
- hold off;
-
- % interactive menu
-
- printf("\rframe: %d menu: n-next b-back q-quit", f);
- fflush(stdout);
- k = kbhit();
- if (k == 'n')
- f = f + 1;
- endif
- if (k == 'b')
- f = f - 1;
- endif
-
- until (k == 'q')
- printf("\n");
-
-endfunction
-
+++ /dev/null
-% spec.m
-% Jean Marc Valin
-%
-% Spectrogram function for Octave
-%
-% Copyright (c) John-Marc Valin 2012
-%
-% Redistribution and use in source and binary forms, with or without
-% modification, are permitted provided that the following conditions
-% are met:
-%
-% - Redistributions of source code must retain the above copyright
-% notice, this list of conditions and the following disclaimer.
-%
-% - Redistributions in binary form must reproduce the above copyright
-% notice, this list of conditions and the following disclaimer in the
-% documentation and/or other materials provided with the distribution.
-%
-% - Neither the name of Jean Marc Valin nor the names of its
-% contributors may be used to endorse or promote products derived from
-% this software without specific prior written permission.
-%
-% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-% ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-% LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
-% A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE FOUNDATION OR
-% CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-% EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-% PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
-% PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
-% LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
-% NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
-% SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-function X = spec(x, Fs, framesize, start, stop)
-
-
-gr=[zeros(1024,1),[0:1023]'/1023,.68*[0:1023]'/1023];
-
-%gr=[.4*[0:1023]'/1023,[0:1023]'/1023,.68*[0:1023]'/1023];
-
-%t=[0:1023]'/1023;
-%t=(1+.25*t-cos(pi*t))/2.25;
-%gr = [zeros(1024,1),t,.68*t];
-
-
-%colormap(gr);
-
-if nargin < 2 || isempty(Fs)
- Fs = 44100;
-end
-
-if nargin < 3 || isempty(framesize)
- framesize = 2048;
-endif
-
-offset = framesize/4;
-
-X = 20*log10(abs(specgram(x, framesize, 48000, blackmanharris(framesize)', framesize-offset)));
-
-XM=max(max(X));
-X = max(XM-120,X);
-%size(X)
-F = -[framesize/2-1:-1:0]/framesize*Fs;
-%F = [0:127]/128*24000;
-T=[1:size(X,2)]/Fs*offset;
-%imagesc(X(end:-1:1,:));
-
-if nargin < 4 || isempty(start)
- istart=1;
-else
- istart = round(start*Fs/offset);
-end
-
-if nargin < 5 || isempty(stop)
- istop = size(X,2);
-else
- istop = round(stop*Fs/offset);
-endif
-
-istart = max(1,istart);
-istop = min(istop, size(X,2));
-
-imagesc(T(1+istart:istop), F, X(end:-1:1,1+istart:istop));
-
-X = X(:,1+istart:istop);
+++ /dev/null
-% tfdmdv.m
-%
-% Octave script that tests the C port of the FDMDV modem. This script loads
-% the output of unittest/tfdmdv.c and compares it to the output of the
-% reference versions of the same functions written in Octave.
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-fdmdv; % load modem code
-
-% Generate reference vectors using Octave implementation of FDMDV modem
-
-global passes;
-global fails;
-passes = fails = 0;
-frames = 25;
-prev_tx_symbols = ones(Nc+1,1);
-prev_rx_symbols = ones(Nc+1,1);
-foff_phase_rect = 1;
-coarse_fine = 0;
-fest_state = 0;
-channel = [];
-channel_count = 0;
-next_nin = M;
-sig_est = zeros(Nc+1,1);
-noise_est = zeros(Nc+1,1);
-
-% Octave outputs we want to collect for comparison to C version
-
-tx_bits_log = [];
-tx_symbols_log = [];
-tx_baseband_log = [];
-tx_fdm_log = [];
-pilot_baseband1_log = [];
-pilot_baseband2_log = [];
-pilot_lpf1_log = [];
-pilot_lpf2_log = [];
-S1_log = [];
-S2_log = [];
-foff_coarse_log = [];
-foff_fine_log = [];
-foff_log = [];
-rx_baseband_log = [];
-rx_filt_log = [];
-env_log = [];
-rx_timing_log = [];
-rx_symbols_log = [];
-rx_bits_log = [];
-sync_bit_log = [];
-coarse_fine_log = [];
-nin_log = [];
-sig_est_log = [];
-noise_est_log = [];
-
-for f=1:frames
-
- % modulator
-
- tx_bits = get_test_bits(Nc*Nb);
- tx_bits_log = [tx_bits_log tx_bits];
- tx_symbols = bits_to_qpsk(prev_tx_symbols, tx_bits, 'dqpsk');
- prev_tx_symbols = tx_symbols;
- tx_symbols_log = [tx_symbols_log tx_symbols];
- tx_baseband = tx_filter(tx_symbols);
- tx_baseband_log = [tx_baseband_log tx_baseband];
- tx_fdm = fdm_upconvert(tx_baseband);
- tx_fdm_log = [tx_fdm_log tx_fdm];
-
- % channel
-
- nin = next_nin;
- %nin = 120;
- %nin = M;
- %if (f == 3)
- % nin = 120;
- %elseif (f == 4)
- % nin = 200;
- %else
- % nin = M;
- %end
- channel = [channel real(tx_fdm)];
- channel_count += M;
- rx_fdm = channel(1:nin);
- channel = channel(nin+1:channel_count);
- channel_count -= nin;
-
- % demodulator
-
- [pilot prev_pilot pilot_lut_index prev_pilot_lut_index] = get_pilot(pilot_lut_index, prev_pilot_lut_index, nin);
-
- [foff_coarse S1 S2] = rx_est_freq_offset(rx_fdm, pilot, prev_pilot, nin);
- if coarse_fine == 0
- foff = foff_coarse;
- end
- foff_coarse_log = [foff_coarse_log foff_coarse];
-
- pilot_baseband1_log = [pilot_baseband1_log pilot_baseband1];
- pilot_baseband2_log = [pilot_baseband2_log pilot_baseband2];
- pilot_lpf1_log = [pilot_lpf1_log pilot_lpf1];
- pilot_lpf2_log = [pilot_lpf2_log pilot_lpf2];
- S1_log = [S1_log S1];
- S2_log = [S2_log S2];
-
- foff_rect = exp(j*2*pi*foff/Fs);
-
- for i=1:nin
- foff_phase_rect *= foff_rect';
- rx_fdm_fcorr(i) = rx_fdm(i)*foff_phase_rect;
- end
-
- rx_baseband = fdm_downconvert(rx_fdm_fcorr, nin);
- rx_baseband_log = [rx_baseband_log rx_baseband];
-
- rx_filt = rx_filter(rx_baseband, nin);
- rx_filt_log = [rx_filt_log rx_filt];
-
- [rx_symbols rx_timing env] = rx_est_timing(rx_filt, rx_baseband, nin);
- env_log = [env_log env];
-
- rx_timing_log = [rx_timing_log rx_timing];
- rx_symbols_log = [rx_symbols_log rx_symbols];
-
- next_nin = M;
- if rx_timing > 2*M/P
- next_nin += M/P;
- end
- if rx_timing < 0;
- next_nin -= M/P;
- end
- nin_log = [nin_log nin];
-
- [rx_bits sync_bit foff_fine pd] = qpsk_to_bits(prev_rx_symbols, rx_symbols, 'dqpsk');
-
- [sig_est noise_est] = snr_update(sig_est, noise_est, pd);
- sig_est_log = [sig_est_log sig_est];
- noise_est_log = [noise_est_log noise_est];
-
- prev_rx_symbols = rx_symbols;
- rx_bits_log = [rx_bits_log rx_bits];
- foff_fine_log = [foff_fine_log foff_fine];
- sync_bit_log = [sync_bit_log sync_bit];
- foff -= 0.5*foff_fine;
- foff_log = [foff_log foff];
-
- % freq est state machine
-
- [coarse_fine fest_state] = freq_state(sync_bit, fest_state);
- coarse_fine_log = [coarse_fine_log coarse_fine];
-end
-
-% Compare to the output from the C version
-
-load ../unittest/tfdmdv_out.txt
-
-% Helper functions to plot output of C verson and difference between Octave and C versions
-
-function stem_sig_and_error(plotnum, subplotnum, sig, error, titlestr, axisvec)
- figure(plotnum)
- subplot(subplotnum)
- stem(sig);
- hold on;
- stem(error,'g');
- hold off;
- if nargin == 6
- axis(axisvec);
- end
- title(titlestr);
-endfunction
-
-function plot_sig_and_error(plotnum, subplotnum, sig, error, titlestr, axisvec)
- figure(plotnum)
- subplot(subplotnum)
- plot(sig);
- hold on;
- plot(error,'g');
- hold off;
- if nargin == 6
- axis(axisvec);
- end
- title(titlestr);
-endfunction
-
-% ---------------------------------------------------------------------------------------
-% Plot output and test each C function
-% ---------------------------------------------------------------------------------------
-
-% fdmdv_get_test_bits() & bits_to_dqpsk_symbols()
-
-n = 28;
-stem_sig_and_error(1, 211, tx_bits_log_c(1:n), tx_bits_log(1:n) - tx_bits_log_c(1:n), 'tx bits', [1 n -1.5 1.5])
-stem_sig_and_error(1, 212, real(tx_symbols_log_c(1:n/2)), real(tx_symbols_log(1:n/2) - tx_symbols_log_c(1:n/2)), 'tx symbols real', [1 n/2 -1.5 1.5])
-
-% tx_filter()
-
-diff = tx_baseband_log - tx_baseband_log_c;
-c=15;
-plot_sig_and_error(2, 211, real(tx_baseband_log_c(c,:)), real(sum(diff)), 'tx baseband real')
-plot_sig_and_error(2, 212, imag(tx_baseband_log_c(c,:)), imag(sum(diff)), 'tx baseband imag')
-
-% fdm_upconvert()
-
-plot_sig_and_error(3, 211, real(tx_fdm_log_c), real(tx_fdm_log - tx_fdm_log_c), 'tx fdm real')
-plot_sig_and_error(3, 212, imag(tx_fdm_log_c), imag(tx_fdm_log - tx_fdm_log_c), 'tx fdm imag')
-
-% generate_pilot_lut()
-
-plot_sig_and_error(4, 211, real(pilot_lut_c), real(pilot_lut - pilot_lut_c), 'pilot lut real')
-plot_sig_and_error(4, 212, imag(pilot_lut_c), imag(pilot_lut - pilot_lut_c), 'pilot lut imag')
-
-% rx_est_freq_offset()
-
-st=1; en = 3*Npilotbaseband;
-plot_sig_and_error(5, 211, real(pilot_baseband1_log(st:en)), real(pilot_baseband1_log(st:en) - pilot_baseband1_log_c(st:en)), 'pilot baseband1 real' )
-plot_sig_and_error(5, 212, real(pilot_baseband2_log(st:en)), real(pilot_baseband2_log(st:en) - pilot_baseband2_log_c(st:en)), 'pilot baseband2 real' )
-
-st=1; en = 3*Npilotlpf;
-plot_sig_and_error(6, 211, real(pilot_lpf1_log(st:en)), real(pilot_lpf1_log(st:en) - pilot_lpf1_log_c(st:en)), 'pilot lpf1 real' )
-plot_sig_and_error(6, 212, real(pilot_lpf2_log(st:en)), real(pilot_lpf2_log(st:en) - pilot_lpf2_log_c(st:en)), 'pilot lpf2 real' )
-
-plot_sig_and_error(7, 211, real(S1_log), real(S1_log - S1_log_c), 'S1 real' )
-plot_sig_and_error(7, 212, imag(S1_log), imag(S1_log - S1_log_c), 'S1 imag' )
-
-plot_sig_and_error(8, 211, real(S2_log), real(S2_log - S2_log_c), 'S2 real' )
-plot_sig_and_error(8, 212, imag(S2_log), imag(S2_log - S2_log_c), 'S2 imag' )
-
-plot_sig_and_error(9, 211, foff_coarse_log, foff_coarse_log - foff_coarse_log_c, 'Coarse Freq Offset' )
-plot_sig_and_error(9, 212, foff_fine_log, foff_fine_log - foff_fine_log_c, 'Fine Freq Offset' )
-
-plot_sig_and_error(10, 211, foff_log, foff_log - foff_log_c, 'Freq Offset' )
-plot_sig_and_error(10, 212, coarse_fine_log, coarse_fine_log - coarse_fine_log_c, 'Freq Est Coarse(0) Fine(1)', [1 frames -0.5 1.5] )
-
-c=15;
-plot_sig_and_error(11, 211, real(rx_baseband_log(c,:)), real(rx_baseband_log(c,:) - rx_baseband_log_c(c,:)), 'Rx baseband real' )
-plot_sig_and_error(11, 212, imag(rx_baseband_log(c,:)), imag(rx_baseband_log(c,:) - rx_baseband_log_c(c,:)), 'Rx baseband imag' )
-
-plot_sig_and_error(12, 211, real(rx_filt_log(c,:)), real(rx_filt_log(c,:) - rx_filt_log_c(c,:)), 'Rx filt real' )
-plot_sig_and_error(12, 212, imag(rx_filt_log(c,:)), imag(rx_filt_log(c,:) - rx_filt_log_c(c,:)), 'Rx filt imag' )
-
-st=1; en=3*Nt*P;
-plot_sig_and_error(13, 211, env_log(st:en), env_log(st:en) - env_log_c(st:en), 'env' )
-stem_sig_and_error(13, 212, real(rx_symbols_log(c,:)), real(rx_symbols_log(c,:) - rx_symbols_log_c(c,:)), 'rx symbols' )
-
-st=10*28;
-en = 12*28;
-plot_sig_and_error(14, 211, rx_timing_log, rx_timing_log - rx_timing_log_c, 'Rx Timing' )
-stem_sig_and_error(14, 212, sync_bit_log_c, sync_bit_log - sync_bit_log_c, 'Sync bit', [1 n -1.5 1.5])
-
-stem_sig_and_error(15, 211, rx_bits_log_c(st:en), rx_bits_log(st:en) - rx_bits_log_c(st:en), 'RX bits', [1 en-st -1.5 1.5])
-stem_sig_and_error(15, 212, nin_log_c, nin_log - nin_log_c, 'nin')
-
-c = 1;
-plot_sig_and_error(16, 211, sig_est_log(c,:), sig_est_log(c,:) - sig_est_log_c(c,:), 'sig est for SNR' )
-plot_sig_and_error(16, 212, noise_est_log(c,:), noise_est_log(c,:) - noise_est_log_c(c,:), 'noise est for SNR' )
-
-% ---------------------------------------------------------------------------------------
-% AUTOMATED CHECKS ------------------------------------------
-% ---------------------------------------------------------------------------------------
-
-function check(a, b, test_name)
- global passes;
- global fails;
-
- [m n] = size(a);
- printf("%s", test_name);
- for i=1:(25-length(test_name))
- printf(".");
- end
- printf(": ");
-
- if sum(abs(a - b))/n < 1E-3
- printf("OK\n");
- passes++;
- else
- printf("FAIL\n");
- fails++;
- end
-endfunction
-
-check(tx_bits_log, tx_bits_log_c, 'tx_bits');
-check(tx_symbols_log, tx_symbols_log_c, 'tx_symbols');
-check(tx_baseband_log, tx_baseband_log_c, 'tx_baseband');
-check(tx_fdm_log, tx_fdm_log_c, 'tx_fdm');
-check(pilot_lut, pilot_lut_c, 'pilot_lut');
-check(pilot_baseband1_log, pilot_baseband1_log_c, 'pilot lpf1');
-check(pilot_baseband2_log, pilot_baseband2_log_c, 'pilot lpf2');
-check(S1_log, S1_log_c, 'S1');
-check(S2_log, S2_log_c, 'S2');
-check(foff_coarse_log, foff_coarse_log_c, 'foff_coarse');
-check(foff_fine_log, foff_fine_log_c, 'foff_fine');
-check(foff_log, foff_log_c, 'foff');
-check(rx_baseband_log, rx_baseband_log_c, 'rx baseband');
-check(rx_filt_log, rx_filt_log_c, 'rx filt');
-check(env_log, env_log_c, 'env');
-check(rx_timing_log, rx_timing_log_c, 'rx_timing');
-check(rx_symbols_log, rx_symbols_log_c, 'rx_symbols');
-check(rx_bits_log, rx_bits_log_c, 'rx bits');
-check(sync_bit_log, sync_bit_log_c, 'sync bit');
-check(coarse_fine_log, coarse_fine_log_c, 'coarse_fine');
-check(nin_log, nin_log_c, 'nin');
-check(sig_est_log, sig_est_log_c, 'sig_est');
-check(noise_est_log, noise_est_log_c, 'noise_est');
-
-printf("\npasses: %d fails: %d\n", passes, fails);
+++ /dev/null
-% tget-spec.m
-%
-% Used in conjunction with src/fdmdv_demod to test the
-% fdmdv_get_rx_spectrum() function.
-%
-% codec2-dev/src$ ./fdmdv_demod fdmdv_mod.raw tmp.c2 dump.txt
-% octave:3> tget_spec("../src/dump.txt")
-%
-% Copyright David Rowe 2012
-% This program is distributed under the terms of the GNU General Public License
-% Version 2
-%
-
-function tfft_log(dumpfilename)
-
- load(dumpfilename);
-
- [rows cols] = size(rx_spec_log_c);
- Fs = 8000; low_freq = 0; high_freq = 2500;
- res = (Fs/2)/cols;
- st_bin = low_freq/res + 1;
- en_bin = high_freq/res;
- xaxis = (st_bin:en_bin)*res;
-
- f_start = 2; f_end = 100;
- beta = 0.1;
-
- av = zeros(f_end, en_bin-st_bin+1);
- for r=f_start:f_end
- x = (1-beta)*av(r-1,:) + beta*rx_spec_log_c(r,st_bin:en_bin);
- av(r,:) = x;
- end
-
- % spectrogram (waterfall)
-
- figure(1)
- clf;
- imagesc(av,[-40 0]);
-
- % animated spectrum display
-
- figure(2)
- clf;
- for r=f_start:f_end
- plot(xaxis, av(r,:))
- axis([ low_freq high_freq -40 0])
- sleep(0.1)
- end
-endfunction
+++ /dev/null
-% twotone.m
-% David Rowe Aug 2012
-% Used to experiment with combining phase of two tones
-
-function cbphase
-
- Wo = 100.0*pi/4000;
- L = floor(pi/Wo);
- phi = zeros(1,L);
-
- % two harmonics
-
- a = 20; b = 21;
-
- % set up phases to whatever
-
- phi(a) = -pi;
- phi(b) = -pi/2;
-
- % synthesis the two-tone signal
-
- N = 16000;
- Nplot = 250;
- s = zeros(1,N);
-
- for m=a:b
- s_m = cos(m*Wo*(0:(N-1)) + phi(m));
- s = s + s_m;
- endfor
-
- % now our theory says that this signal should be the same perceptually
-
- phi_(a) = (phi(a) - phi(b))/2;
- phi_(b) = (phi(b) - phi(a))/2;
-
- s_ = zeros(1,N);
- for m=a:b
- s_m = cos(m*Wo*(0:(N-1)) + phi_(m));
- s_ = s_ + s_m;
- endfor
-
- % plot them and see if envelope has the same phase, but "carriers"
- % have different phase
-
- figure(1);
- clf;
- subplot(211);
- plot(s(1:Nplot));
- subplot(212);
- plot(s_(1:Nplot),'r');
-endfunction
-
+++ /dev/null
-% twotone1.m
-% David Rowe Aug 17 2012
-%
-% Used to experiment with combining phase of two tones. This version
-% sets up a complete synthetic speech signal then tries to combine the
-% phase of high frequency tones. Lets see if we can do this and keep perceptual
-% nature of signal the same.
-
-function twotone1
-
- % hts1a frame 47
-
- Wo = 0.093168;
- L = 33;
- %A = [69.626907 460.218536 839.677429 2577.498047 972.647888 712.755066 489.048553 364.830536 409.230652 371.767487 489.112854 893.127014 2447.596680 752.878113 475.720520 234.452271 248.161606 232.171051 202.669891 323.914490 678.749451 362.958038 211.652512 170.764435 148.631790 169.261673 272.254150 176.872375 67.344391 99.022301 60.812035 34.319073 14.864757];
- A = zeros(1,L)*100;
- phi = [1.560274 1.508063 -1.565184 1.289117 -2.547365 1.412528 -1.303992 3.121130 1.087573 -1.158161 -2.928007 0.995093 -2.614023 0.246136 -2.267406 2.143802 -0.273431 -2.266897 1.685171 -0.668712 2.699722 -1.151891 2.406379 -0.046192 -2.718611 0.761067 -2.305014 0.133172 -1.428978 1.492630 -1.668385 1.539734 -1.336615];
- %phi = zeros(1,L);
- st = floor(L/2);
- %st = 1;
-
- A(st:st+5) = 1000;
-
- % now set up phase of signal with phase of upper frequency harmonic
- % pairs combined
-
- phi_ = phi;
- for m=floor(L/2):2:L
- phi_(m) = (phi(m) - phi(m+1))/2;
- phi_(m+1) = (phi(m+1) - phi(m))/2;
- %phi_(m+1) = 0;
- end
-
- % synthesise the signals
-
- N = 16000;
- Nplot = 250;
-
- s = zeros(1,N);
- for m=st:L
- s_m = A(m)*cos(m*Wo*(0:(N-1)) + phi(m));
- s = s + s_m;
- endfor
-
- s_ = zeros(1,N);
- for m=st:L
- s_m = A(m)*cos(m*Wo*(0:(N-1)) + phi_(m));
- s_ = s_ + s_m;
- endfor
-
- % plot them, expect to see similar time domain waveforms
-
- figure(1);
- clf;
- subplot(211);
- plot(s(1:Nplot));
- subplot(212);
- plot(s_(1:Nplot),'r');
-
- figure(2);
- clf;
- subplot(211);
- plot(s(1:Nplot)-s_(1:Nplot));
-
- % save to disk
-
- gain = 1;
- fs=fopen("twotone1_orig.raw","wb");
- fwrite(fs,gain*s,"short");
- fclose(fs);
- fs=fopen("twotone1_comb.raw","wb");
- fwrite(fs,gain*s_,"short");
- fclose(fs);
-
-endfunction
-
+++ /dev/null
-% undersample.m
-% David Rowe 5 Nov 2012
-% Testing algorithms for plotting undersampled data for fdmdv2 waveform displays
-
-fs=fopen("../raw/hts1a.raw","rb");
-s = fread(fs,Inf,"short");
-
-Fs1=8000;
-Fs2=200;
-
-M=Fs1/Fs2;
-
-samples=length(s)/M;
-s1=zeros(1,2*samples);
-for b=1:samples
- st = (b-1)*M + 1;
- en = b*M;
- s1(2*b-1) = max(s(st:en));
- s1(2*b) = min(s(st:en));
-end
-
-subplot(211)
-plot(s)
-subplot(212)
-plot(s1);
-
+++ /dev/null
-111.627907\r
-97.959183\r
-97.959183\r
-97.959183\r
-87.272736\r
-78.048775\r
-112.280701\r
-120.000008\r
-61.538464\r
-68.817207\r
-84.210526\r
-90.140846\r
-90.140846\r
-90.140846\r
-101.587303\r
-80.000000\r
-72.727272\r
-95.522392\r
-90.140846\r
-90.140846\r
-101.587303\r
-90.140846\r
-85.333336\r
-86.486488\r
-91.428574\r
-91.428574\r
-91.428574\r
-91.428574\r
-91.428574\r
-90.140846\r
-86.486488\r
-86.486488\r
-85.333336\r
-85.333336\r
-85.333336\r
-81.012657\r
-74.418610\r
-71.111115\r
-71.111115\r
-71.111115\r
-71.111115\r
-68.085106\r
-68.085106\r
-67.368423\r
-67.368423\r
-70.329674\r
-70.329674\r
-70.329674\r
-71.111115\r
-74.418610\r
-74.418610\r
-75.294121\r
-79.012352\r
-85.333336\r
-96.969704\r
-111.627907\r
-111.627907\r
-120.000008\r
-111.627907\r
-104.347832\r
-104.347832\r
-97.959183\r
-104.347832\r
-104.347832\r
-104.347832\r
-104.347832\r
-104.347832\r
-104.347832\r
-104.347832\r
-104.347832\r
-97.959183\r
-97.959183\r
-112.280701\r
-112.280701\r
-96.969704\r
-96.969704\r
-96.969704\r
-110.344841\r
-104.347832\r
-97.959183\r
-97.959183\r
-104.347832\r
-97.959183\r
-104.347832\r
-120.000008\r
-104.347832\r
-120.000008\r
-120.000008\r
-97.959183\r
-83.116882\r
-75.294121\r
-71.910118\r
-71.910110\r
-71.910110\r
-71.910110\r
-75.294121\r
-76.190483\r
-80.000008\r
-80.000008\r
-84.210526\r
-85.333336\r
-90.140846\r
-101.587303\r
-108.474571\r
-104.347832\r
-120.000008\r
-120.000008\r
-104.347832\r
-104.347832\r
-71.111115\r
-88.888893\r
-75.294121\r
-111.627907\r
-120.000008\r
-120.000008\r
-97.959183\r
-111.627907\r
-111.627907\r
-111.627907\r
-97.959183\r
-92.307693\r
-92.307693\r
-92.307693\r
-92.307693\r
-120.000008\r
-111.627907\r
-111.627907\r
-86.486488\r
-85.333336\r
-85.333336\r
-90.140846\r
-95.522392\r
-101.587311\r
-101.587311\r
-104.918037\r
-104.347832\r
-104.347832\r
-111.627907\r
-120.000008\r
-97.959183\r
-104.347832\r
-111.627907\r
-88.888893\r
-80.000000\r
-81.012657\r
-85.333336\r
-85.333336\r
-86.486488\r
-91.428574\r
-90.140846\r
-91.428574\r
-96.969704\r
-96.969704\r
-95.522392\r
-95.522392\r
-95.522392\r
-96.969704\r
-96.969704\r
-98.461533\r
-104.918022\r
-97.959183\r
-97.959183\r
-97.959183\r
-104.347832\r
-120.000008\r
-120.000008\r
-92.307693\r
-92.307693\r
-77.108429\r
-79.012344\r
-75.294121\r
-75.294121\r
-76.190483\r
-76.190483\r
-80.000008\r
-81.012657\r
-85.333336\r
-85.333336\r
-85.333336\r
-85.333336\r
-85.333336\r
-90.140846\r
-90.140846\r
-91.428574\r
-96.969704\r
-98.461533\r
-120.000008\r
-120.000008\r
-104.347832\r
-97.959183\r
-97.959183\r
-104.918037\r
-120.000008\r
-120.000008\r
-120.000008\r
-104.347832\r
-92.307693\r
-72.727272\r
-72.727272\r
-76.190483\r
-84.210533\r
-88.888901\r
-120.000008\r
-104.347832\r
-120.000008\r
-120.000008\r
-111.627907\r
-92.307693\r
-97.959183\r
-97.959183\r
-111.627907\r
-120.000008\r
-120.000008\r
-97.959183\r
-97.959183\r
-104.347832\r
-104.347832\r
-104.347832\r
-111.627907\r
-120.000008\r
-97.959183\r
-104.347832\r
-97.959183\r
-97.959183\r
-84.210526\r
-94.117653\r
-96.969704\r
-110.344841\r
-120.000008\r
-97.959183\r
-97.959183\r
-104.347832\r
-97.959183\r
-104.347832\r
-97.959183\r
-97.959183\r
-111.627907\r
-120.000008\r
-92.307693\r
-92.307693\r
-98.461533\r
-98.461533\r
-104.918022\r
-111.627907\r
-111.627907\r
-92.307693\r
-97.959183\r
-92.307693\r
-92.307693\r
-92.307693\r
-92.307693\r
-92.307693\r
-57.657658\r
-90.140846\r
-90.140846\r
-95.522392\r
-101.587311\r
-101.587311\r
-108.474586\r
-111.627907\r
-97.959183\r
-111.627907\r
-120.000008\r
-92.307693\r
-74.418610\r
-74.418610\r
-74.418610\r
-74.418610\r
-76.190483\r
-72.727280\r
-76.190483\r
-76.190483\r
-69.565224\r
-66.666672\r
-54.700855\r
-56.637169\r
-56.637169\r
-71.910110\r
-90.140846\r
-90.140846\r
-72.727272\r
-72.727272\r
-72.727272\r
-72.727272\r
-55.172413\r
-57.142857\r
-55.172413\r
-90.140846\r
-95.522392\r
-101.587311\r
-101.587311\r
-71.910110\r
-74.418610\r
-46.376812\r
-40.000000\r
-95.522392\r
-0\r
-0\r
+++ /dev/null
- 0.0000000e+000\r
- 9.2753623e+001\r
- 5.4237288e+001\r
- 8.5906040e+001\r
- 7.0329670e+001\r
- 5.5652174e+001\r
- 5.4237288e+001\r
- 5.4935622e+001\r
- 5.4700855e+001\r
- 7.5739645e+001\r
- 7.3563218e+001\r
- 1.2307692e+002\r
- 1.1428571e+002\r
- 7.3563218e+001\r
- 7.7108434e+001\r
- 1.8550725e+002\r
- 1.2673267e+002\r
- 1.0847458e+002\r
- 7.8527607e+001\r
- 8.8888889e+001\r
- 8.3116883e+001\r
- 8.1012658e+001\r
- 1.0756303e+002\r
- 1.3061224e+002\r
- 4.8301887e+001\r
- 4.7940075e+001\r
- 4.8120301e+001\r
- 4.9230769e+001\r
- 4.9420849e+001\r
- 4.6886447e+001\r
- 4.2953020e+001\r
- 3.9263804e+001\r
- 3.7869822e+001\r
- 3.5457064e+001\r
- 3.4224599e+001\r
- 3.3333333e+001\r
- 3.2820513e+001\r
- 3.2000000e+001\r
- 3.1295844e+001\r
- 2.9906542e+001\r
- 2.9493088e+001\r
- 2.9090909e+001\r
- 2.8699552e+001\r
- 2.8131868e+001\r
- 2.7826087e+001\r
- 2.7826087e+001\r
- 2.7826087e+001\r
- 2.8193833e+001\r
- 2.7467811e+001\r
- 2.6890756e+001\r
- 5.4468085e+001\r
- 5.4237288e+001\r
- 6.4974619e+001\r
- 1.0756303e+002\r
- 8.8888889e+001\r
- 1.0406504e+002\r
- 4.4599303e+001\r
- 5.4468085e+001\r
- 3.6260623e+001\r
- 3.6260623e+001\r
- 8.1012658e+001\r
- 7.0329670e+001\r
- 1.2929293e+002\r
- 9.9224806e+001\r
- 4.3097643e+001\r
- 4.4137931e+001\r
- 4.5714286e+001\r
- 4.7407407e+001\r
- 4.8301887e+001\r
- 4.9230769e+001\r
- 4.9420849e+001\r
- 5.0996016e+001\r
- 5.1405622e+001\r
- 5.1405622e+001\r
- 5.2244898e+001\r
- 5.2459016e+001\r
- 5.2459016e+001\r
- 5.2244898e+001\r
- 5.3333333e+001\r
- 5.2459016e+001\r
- 5.2244898e+001\r
- 5.1405622e+001\r
- 5.1405622e+001\r
- 5.1200000e+001\r
- 5.0996016e+001\r
- 5.0196078e+001\r
- 4.9230769e+001\r
- 4.9230769e+001\r
- 4.9230769e+001\r
- 4.9420849e+001\r
- 4.9230769e+001\r
- 4.9042146e+001\r
- 9.8461538e+001\r
- 1.0158730e+002\r
- 5.1821862e+001\r
- 9.0140845e+001\r
- 1.0491803e+002\r
- 1.4382022e+002\r
- 5.2459016e+001\r
- 5.2459016e+001\r
- 1.2929293e+002\r
- 1.6410256e+002\r
- 8.0000000e+001\r
- 7.3563218e+001\r
- 1.0158730e+002\r
- 9.9224806e+001\r
- 4.9042146e+001\r
- 4.9042146e+001\r
- 4.9042146e+001\r
- 5.9259259e+001\r
- 1.4382022e+002\r
- 7.2316384e+001\r
- 1.0847458e+002\r
- 1.1228070e+002\r
- 1.6202532e+002\r
- 8.1528662e+001\r
- 7.2727273e+001\r
- 1.8550725e+002\r
- 6.0093897e+001\r
- 1.0847458e+002\r
- 8.9510490e+001\r
- 7.1508380e+001\r
- 4.0125392e+001\r
- 4.0634921e+001\r
- 4.0634921e+001\r
- 4.0251572e+001\r
- 4.0506329e+001\r
- 4.3986254e+001\r
- 4.0506329e+001\r
- 9.8461538e+001\r
- 5.6140351e+001\r
- 6.5641026e+001\r
- 5.4237288e+001\r
- 1.1636364e+002\r
- 3.4316354e+001\r
- 3.4972678e+001\r
- 3.7758112e+001\r
- 4.0634921e+001\r
- 4.0506329e+001\r
- 4.1290323e+001\r
- 4.2524917e+001\r
- 4.3389831e+001\r
- 4.4599303e+001\r
- 4.4912281e+001\r
- 4.6545455e+001\r
- 4.7232472e+001\r
- 4.8301887e+001\r
- 4.9230769e+001\r
- 4.9420849e+001\r
- 5.0393701e+001\r
- 5.1405622e+001\r
- 5.3333333e+001\r
- 5.3112033e+001\r
- 1.1034483e+002\r
- 9.7709924e+001\r
- 1.4382022e+002\r
- 5.0996016e+001\r
- 5.1821862e+001\r
- 5.0996016e+001\r
- 5.2032520e+001\r
- 5.3112033e+001\r
- 5.3556485e+001\r
- 5.4468085e+001\r
- 5.5652174e+001\r
- 5.4700855e+001\r
- 5.4700855e+001\r
- 5.4935622e+001\r
- 5.4700855e+001\r
- 5.4700855e+001\r
- 5.4468085e+001\r
- 5.4468085e+001\r
- 5.4468085e+001\r
- 5.4468085e+001\r
- 5.3333333e+001\r
- 5.1405622e+001\r
- 5.0996016e+001\r
- 5.0000000e+001\r
- 4.8120301e+001\r
- 4.8669202e+001\r
- 4.7058824e+001\r
- 4.6376812e+001\r
- 4.5070423e+001\r
- 4.4912281e+001\r
- 4.4137931e+001\r
- 4.2809365e+001\r
- 4.2666667e+001\r
- 4.2105263e+001\r
- 4.1423948e+001\r
- 4.1290323e+001\r
- 4.1290323e+001\r
- 4.1290323e+001\r
- 4.0634921e+001\r
- 4.0634921e+001\r
- 4.0634921e+001\r
- 4.0634921e+001\r
- 4.0764331e+001\r
- 4.1423948e+001\r
- 4.2953020e+001\r
- 4.5551601e+001\r
- 1.7534247e+002\r
- 4.7232472e+001\r
- 1.3763441e+002\r
- 1.3061224e+002\r
- 4.5551601e+001\r
- 4.3686007e+001\r
- 4.8669202e+001\r
- 9.4117647e+001\r
- 8.1012658e+001\r
- 1.1228070e+002\r
- 1.3617021e+002\r
- 4.3097643e+001\r
- 4.3835616e+001\r
- 4.6376812e+001\r
- 4.6545455e+001\r
- 4.6043165e+001\r
- 4.8301887e+001\r
- 4.9042146e+001\r
- 4.9420849e+001\r
- 5.1200000e+001\r
- 5.1405622e+001\r
- 5.2244898e+001\r
- 1.2929293e+002\r
- 1.2929293e+002\r
- 1.5238095e+002\r
- 1.5238095e+002\r
- 1.3913043e+002\r
- 9.0140845e+001\r
- 1.0940171e+002\r
- 9.0140845e+001\r
- 1.2307692e+002\r
- 8.9510490e+001\r
- 6.9565217e+001\r
- 7.3142857e+001\r
- 1.1034483e+002\r
- 7.8048780e+001\r
- 7.2727273e+001\r
- 1.0078740e+002\r
- 1.0940171e+002\r
- 1.1743119e+002\r
- 8.7074830e+001\r
- 1.8550725e+002\r
- 6.5306122e+001\r
- 1.3617021e+002\r
- 5.2674897e+001\r
- 1.0940171e+002\r
- 1.5238095e+002\r
- 1.4065934e+002\r
- 1.0756303e+002\r
- 1.0406504e+002\r
- 5.0793651e+001\r
- 4.9420849e+001\r
- 4.4444444e+001\r
- 7.0329670e+001\r
- 7.2727273e+001\r
- 7.4418605e+001\r
- 1.1636364e+002\r
- 1.0406504e+002\r
- 1.2307692e+002\r
- 1.2549020e+002\r
- 1.7297297e+002\r
- 4.5878136e+001\r
- 4.9805447e+001\r
- 6.2745098e+001\r
- 9.2086331e+001\r
- 9.1428571e+001\r
- 5.7142857e+001\r
- 4.8484848e+001\r
- 4.1157556e+001\r
- 2.2857143e+001\r
- 3.0046948e+001\r
- 9.4814815e+001\r
- 5.7918552e+001\r
- 9.0140845e+001\r
- 7.4418605e+001\r
- 7.4418605e+001\r
- 5.4700855e+001\r
- 9.5522388e+001\r
- 7.4853801e+001\r
- 9.4117647e+001\r
- 9.5522388e+001\r
- 9.9224806e+001\r
- 8.1012658e+001\r
- 1.1851852e+002\r
- 6.8817204e+001\r
- 8.5906040e+001\r
- 6.7015707e+001\r
- 4.3537415e+001\r
- 6.5306122e+001\r
- 3.1295844e+001\r
- 7.5739645e+001\r
- 6.2135922e+001\r
- 9.9224806e+001\r
- 5.7657658e+001\r
- 5.2244898e+001\r
- 5.8447489e+001\r
- 0.0000000e+000\r
- 0.0000000e+000\r
- 0.0000000e+000\r
- 0.0000000e+000\r
- 0.0000000e+000\r
+++ /dev/null
-# Makefile for Portaudio test programs
-# Requires Portaudio V19
-
-CFLAGS = -g -Wall -I../src
-LIBS = -lm -lportaudio -pthread
-SRC = ../src/fdmdv.c ../src/kiss_fft.c ../src/fifo.c
-
-all: pa_rec pa_play pa_recplay pa_impresp
-
-pa_rec: Makefile pa_rec.c $(SRC)
- gcc $(CFLAGS) pa_rec.c $(SRC) -o pa_rec $(LIBS)
-
-pa_play: Makefile pa_play.c $(SRC)
- gcc $(CFLAGS) pa_play.c $(SRC) -o pa_play $(LIBS)
-
-pa_recplay: Makefile pa_recplay.c $(SRC)
- gcc $(CFLAGS) pa_recplay.c $(SRC) -o pa_recplay $(LIBS)
-
-pa_impresp: Makefile pa_impresp.c $(SRC)
- gcc $(CFLAGS) pa_impresp.c $(SRC) -o pa_impresp $(LIBS)
-
-clean:
- rm -f pa_rec pa_play pa_recplay
+++ /dev/null
-/*
- pa_impresp.c
- David Rowe
- August 29 2012
-
- Measures the impulse reponse of the path between the speaker and
- microphone. Used to explore why Codec audio quality is
- different through a speaker and headphones.
-
- Modified from pa_playrec.c
-*/
-
-/*
- * $Id: paex_record.c 1752 2011-09-08 03:21:55Z philburk $
- *
- * This program uses the PortAudio Portable Audio Library.
- * For more information see: http://www.portaudio.com
- * Copyright (c) 1999-2000 Ross Bencina and Phil Burk
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include "portaudio.h"
-#include "fdmdv.h"
-
-#define SAMPLE_RATE 48000 /* 48 kHz sampling rate rec. as we
- can trust accuracy of sound
- card */
-#define N8 160 /* processing buffer size at 8 kHz */
-#define N48 (N8*FDMDV_OS) /* processing buffer size at 48 kHz */
-#define MEM8 (FDMDV_OS_TAPS/FDMDV_OS)
-#define NUM_CHANNELS 2 /* I think most sound cards prefer
- stereo, we will convert to mono
- as we sample */
-
-#define IMPULSE_AMP 16384 /* amplitide of impulse */
-#define IMPULSE_PERIOD 0.1 /* period (dly between impulses) in secs */
-
-/* state information passed to call back */
-
-typedef struct {
- float in48k[FDMDV_OS_TAPS + N48];
- float in8k[MEM8 + N8];
- FILE *fimp;
- float *impulse_buf;
- int impulse_buf_length;
- int impulse_sample_count;
- int framesLeft;
-} paTestData;
-
-
-/*
- This routine will be called by the PortAudio engine when audio is
- required. It may be called at interrupt level on some machines so
- don't do anything that could mess up the system like calling
- malloc() or free().
-*/
-
-static int callback( const void *inputBuffer, void *outputBuffer,
- unsigned long framesPerBuffer,
- const PaStreamCallbackTimeInfo* timeInfo,
- PaStreamCallbackFlags statusFlags,
- void *userData )
-{
- paTestData *data = (paTestData*)userData;
- int i;
- short *rptr = (short*)inputBuffer;
- short *wptr = (short*)outputBuffer;
- float *in8k = data->in8k;
- float *in48k = data->in48k;
- float out8k[N8];
- float out48k[N48];
- short out48k_short[N48];
- short out8k_short[N8];
-
- (void) timeInfo;
- (void) statusFlags;
-
- assert(inputBuffer != NULL);
-
- /* just use left channel */
-
- for(i=0; i<framesPerBuffer; i++,rptr+=2)
- data->in48k[i+FDMDV_OS_TAPS] = *rptr;
-
- /* downsample and update filter memory */
-
- fdmdv_48_to_8(out8k, &in48k[FDMDV_OS_TAPS], N8);
- for(i=0; i<FDMDV_OS_TAPS; i++)
- in48k[i] = in48k[i+framesPerBuffer];
-
- /* write impulse response to disk */
-
- for(i=0; i<N8; i++)
- out8k_short[i] = out8k[i];
- fwrite(out8k_short, sizeof(short), N8, data->fimp);
-
- /* play side, read from impulse buffer */
-
- for(i=0; i<N8; i++) {
- in8k[MEM8+i] = data->impulse_buf[data->impulse_sample_count];
- data->impulse_sample_count++;
- if (data->impulse_sample_count == data->impulse_buf_length)
- data->impulse_sample_count = 0;
- }
-
- /* upsample and update filter memory */
-
- fdmdv_8_to_48(out48k, &in8k[MEM8], N8);
- for(i=0; i<MEM8; i++)
- in8k[i] = in8k[i+N8];
-
- assert(outputBuffer != NULL);
-
- /* write signal to both channels */
-
- for(i=0; i<N48; i++)
- out48k_short[i] = (short)out48k[i];
- for(i=0; i<framesPerBuffer; i++,wptr+=2) {
- wptr[0] = out48k_short[i];
- wptr[1] = out48k_short[i];
- }
-
- data->framesLeft -= framesPerBuffer;
- if (data->framesLeft > 0)
- return paContinue;
- else
- return paComplete;
-}
-
-int main(int argc, char *argv[])
-{
- PaStreamParameters inputParameters, outputParameters;
- PaStream* stream;
- PaError err = paNoError;
- paTestData data;
- int i, numSecs;
-
- if (argc != 3) {
- printf("usage: %s impulseRawFile time(s)\n", argv[0]);
- exit(0);
- }
-
- data.fimp = fopen(argv[1], "wb");
- if (data.fimp == NULL) {
- printf("Error opening impulse output file %s\n", argv[1]);
- exit(1);
- }
-
- numSecs = atoi(argv[2]);
- data.framesLeft = numSecs * SAMPLE_RATE;
-
- /* init filter states */
-
- for(i=0; i<MEM8; i++)
- data.in8k[i] = 0.0;
- for(i=0; i<FDMDV_OS_TAPS; i++)
- data.in48k[i] = 0.0;
-
- /* init imupulse */
-
- data.impulse_buf_length = IMPULSE_PERIOD*(SAMPLE_RATE/FDMDV_OS);
- printf("%d\n",data.impulse_buf_length);
- data.impulse_buf = (float*)malloc(data.impulse_buf_length*sizeof(float));
- assert(data.impulse_buf != NULL);
- data.impulse_buf[0] = IMPULSE_AMP;
- for(i=1; i<data.impulse_buf_length; i++)
- data.impulse_buf[i] = 0;
- data.impulse_sample_count = 0;
-
- err = Pa_Initialize();
- if( err != paNoError ) goto done;
-
- inputParameters.device = Pa_GetDefaultInputDevice(); /* default input device */
- if (inputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default input device.\n");
- goto done;
- }
- inputParameters.channelCount = NUM_CHANNELS; /* stereo input */
- inputParameters.sampleFormat = paInt16;
- inputParameters.suggestedLatency = Pa_GetDeviceInfo( inputParameters.device )->defaultLowInputLatency;
- inputParameters.hostApiSpecificStreamInfo = NULL;
-
- outputParameters.device = Pa_GetDefaultOutputDevice(); /* default output device */
- if (outputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default output device.\n");
- goto done;
- }
- outputParameters.channelCount = NUM_CHANNELS; /* stereo output */
- outputParameters.sampleFormat = paInt16;
- outputParameters.suggestedLatency = Pa_GetDeviceInfo( outputParameters.device )->defaultLowOutputLatency;
- outputParameters.hostApiSpecificStreamInfo = NULL;
-
- /* Play some audio --------------------------------------------- */
-
- err = Pa_OpenStream(
- &stream,
- &inputParameters,
- &outputParameters,
- SAMPLE_RATE,
- N48,
- paClipOff,
- callback,
- &data );
- if( err != paNoError ) goto done;
-
- err = Pa_StartStream( stream );
- if( err != paNoError ) goto done;
-
- while( ( err = Pa_IsStreamActive( stream ) ) == 1 )
- {
- Pa_Sleep(100);
- }
- if( err < 0 ) goto done;
-
- err = Pa_CloseStream( stream );
- if( err != paNoError ) goto done;
-
-
-done:
- Pa_Terminate();
- if( err != paNoError )
- {
- fprintf( stderr, "An error occured while using the portaudio stream\n" );
- fprintf( stderr, "Error number: %d\n", err );
- fprintf( stderr, "Error message: %s\n", Pa_GetErrorText( err ) );
- err = 1; /* Always return 0 or 1, but no other return codes. */
- }
-
- fclose(data.fimp);
-
- return err;
-}
-
+++ /dev/null
-/*
- pa_play.c
- David Rowe
- July 8 2012
-
- Converts samples from a 16 bit short 8000 Hz rawfile to 480000Hz
- sample rate and plays them using the default sound device. Used as
- an intermediate step in Portaudio integration.
-
- Modified from paex_record.c Portaudio example. Original author
- author Phil Burk http://www.softsynth.com
-*/
-
-/*
- * $Id: paex_record.c 1752 2011-09-08 03:21:55Z philburk $
- *
- * This program uses the PortAudio Portable Audio Library.
- * For more information see: http://www.portaudio.com
- * Copyright (c) 1999-2000 Ross Bencina and Phil Burk
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include "portaudio.h"
-#include "fdmdv.h"
-
-#define SAMPLE_RATE 48000 /* 48 kHz sampling rate rec. as we
- can trust accuracy of sound
- card */
-#define N8 160 /* processing buffer size at 8 kHz */
-#define N48 (N8*FDMDV_OS) /* processing buffer size at 48 kHz */
-#define MEM8 (FDMDV_OS_TAPS/FDMDV_OS)
-#define NUM_CHANNELS 2 /* I think most sound cards prefer
- stereo, we will convert to mono
- as we sample */
-
-/* state information passed to call back */
-
-typedef struct {
- FILE *fin;
- float in8k[MEM8 + N8];
-} paTestData;
-
-
-/*
- This routine will be called by the PortAudio engine when audio is
- required. It may be called at interrupt level on some machines so
- don't do anything that could mess up the system like calling
- malloc() or free().
-*/
-
-static int playCallback( const void *inputBuffer, void *outputBuffer,
- unsigned long framesPerBuffer,
- const PaStreamCallbackTimeInfo* timeInfo,
- PaStreamCallbackFlags statusFlags,
- void *userData )
-{
- paTestData *data = (paTestData*)userData;
- FILE *fin = data->fin;
- int i, nread;
- int finished;
- short *wptr = (short*)outputBuffer;
- float *in8k = data->in8k;
- float out48k[N48];
- short out48k_short[N48];
- short in8k_short[N8];
-
- (void) outputBuffer; /* Prevent unused variable warnings. */
- (void) timeInfo;
- (void) statusFlags;
- (void) userData;
-
- /* note Portaudio docs recs. against making systems calls like
- fwrite() in this callback but seems to work OK */
-
- nread = fread(in8k_short, sizeof(short), N8, fin);
- if (nread == N8)
- finished = paContinue;
- else
- finished = paComplete;
-
- for(i=0; i<N8; i++)
- in8k[MEM8+i] = in8k_short[i];
-
- /* upsample and update filter memory */
-
- fdmdv_8_to_48(out48k, &in8k[MEM8], N8);
- for(i=0; i<MEM8; i++)
- in8k[i] = in8k[i+N8];
-
- assert(outputBuffer != NULL);
-
- /* write signal to both channels */
-
- for(i=0; i<N48; i++)
- out48k_short[i] = (short)out48k[i];
- for(i=0; i<framesPerBuffer; i++,wptr+=2) {
- wptr[0] = out48k_short[i];
- wptr[1] = out48k_short[i];
- }
-
- return finished;
-}
-
-int main(int argc, char *argv[])
-{
- PaStreamParameters outputParameters;
- PaStream* stream;
- PaError err = paNoError;
- paTestData data;
- int i;
-
- if (argc != 2) {
- printf("usage: %s rawFile\n", argv[0]);
- exit(0);
- }
-
- data.fin = fopen(argv[1], "rt");
- if (data.fin == NULL) {
- printf("Error opening input raw file %s\n", argv[1]);
- exit(1);
- }
-
- for(i=0; i<MEM8; i++)
- data.in8k[i] = 0.0;
-
- err = Pa_Initialize();
- if( err != paNoError ) goto done;
-
- outputParameters.device = Pa_GetDefaultOutputDevice(); /* default input device */
- if (outputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default output device.\n");
- goto done;
- }
- outputParameters.channelCount = NUM_CHANNELS; /* stereo input */
- outputParameters.sampleFormat = paInt16;
- outputParameters.suggestedLatency = Pa_GetDeviceInfo( outputParameters.device )->defaultLowOutputLatency;
- outputParameters.hostApiSpecificStreamInfo = NULL;
-
- /* Play some audio --------------------------------------------- */
-
- err = Pa_OpenStream(
- &stream,
- NULL,
- &outputParameters,
- SAMPLE_RATE,
- N48,
- paClipOff,
- playCallback,
- &data );
- if( err != paNoError ) goto done;
-
- err = Pa_StartStream( stream );
- if( err != paNoError ) goto done;
-
- while( ( err = Pa_IsStreamActive( stream ) ) == 1 )
- {
- Pa_Sleep(100);
- }
- if( err < 0 ) goto done;
-
- err = Pa_CloseStream( stream );
- if( err != paNoError ) goto done;
-
- fclose(data.fin);
-
-
-done:
- Pa_Terminate();
- if( err != paNoError )
- {
- fprintf( stderr, "An error occured while using the portaudio stream\n" );
- fprintf( stderr, "Error number: %d\n", err );
- fprintf( stderr, "Error message: %s\n", Pa_GetErrorText( err ) );
- err = 1; /* Always return 0 or 1, but no other return codes. */
- }
- return err;
-}
-
+++ /dev/null
-/*
- pa_rec.c
- David Rowe
- July 6 2012
-
- Records at 48000 Hz from default sound device, convertes to 8 kHz,
- and saves to raw file. Used to get experience with Portaudio.
-
- Modified from paex_record.c Portaudio example. Original author
- author Phil Burk http://www.softsynth.com
-
- To Build:
-
- gcc paex_rec.c -o paex_rec -lm -lrt -lportaudio -pthread
-*/
-
-/*
- * $Id: paex_record.c 1752 2011-09-08 03:21:55Z philburk $
- *
- * This program uses the PortAudio Portable Audio Library.
- * For more information see: http://www.portaudio.com
- * Copyright (c) 1999-2000 Ross Bencina and Phil Burk
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include "portaudio.h"
-#include "fdmdv.h"
-
-#define SAMPLE_RATE 48000 /* 48 kHz sampling rate rec. as we
- can trust accuracy of sound
- card */
-#define N8 160 /* processing buffer size at 8 kHz */
-#define N48 (N8*FDMDV_OS) /* processing buffer size at 48 kHz */
-#define NUM_CHANNELS 2 /* I think most sound cards prefer
- stereo, we will convert to mono
- as we sample */
-
-/* state information passed to call back */
-
-typedef struct {
- FILE *fout;
- int framesLeft;
- float in48k[FDMDV_OS_TAPS + N48];
-} paTestData;
-
-
-/*
- This routine will be called by the PortAudio engine when audio is
- available. It may be called at interrupt level on some machines so
- don't do anything that could mess up the system like calling
- malloc() or free().
-*/
-
-static int recordCallback( const void *inputBuffer, void *outputBuffer,
- unsigned long framesPerBuffer,
- const PaStreamCallbackTimeInfo* timeInfo,
- PaStreamCallbackFlags statusFlags,
- void *userData )
-{
- paTestData *data = (paTestData*)userData;
- FILE *fout = data->fout;
- int framesToCopy;
- int i;
- int finished;
- short *rptr = (short*)inputBuffer;
- float out8k[N8];
- short out8k_short[N8];
-
- (void) outputBuffer; /* Prevent unused variable warnings. */
- (void) timeInfo;
- (void) statusFlags;
- (void) userData;
-
- if (data->framesLeft < framesPerBuffer) {
- framesToCopy = data->framesLeft;
- finished = paComplete;
- }
- else {
- framesToCopy = framesPerBuffer;
- finished = paContinue;
- }
- data->framesLeft -= framesToCopy;
-
- assert(inputBuffer != NULL);
-
- /* just use left channel */
-
- for(i=0; i<framesToCopy; i++,rptr+=2)
- data->in48k[i+FDMDV_OS_TAPS] = *rptr;
-
- /* downsample and update filter memory */
-
- fdmdv_48_to_8(out8k, &data->in48k[FDMDV_OS_TAPS], N8);
- for(i=0; i<FDMDV_OS_TAPS; i++)
- data->in48k[i] = data->in48k[i+framesToCopy];
-
- /* save 8k to disk */
-
- for(i=0; i<N8; i++)
- out8k_short[i] = (short)out8k[i];
-
- /* note Portaudio docs recs. against making systems calls like
- fwrite() in this callback but seems to work OK */
-
- fwrite(out8k_short, sizeof(short), N8, fout);
-
- return finished;
-}
-
-int main(int argc, char *argv[])
-{
- PaStreamParameters inputParameters;
- PaStream* stream;
- PaError err = paNoError;
- paTestData data;
- int i;
- int numSecs;
-
- if (argc != 3) {
- printf("usage: %s rawFile time(s)\n", argv[0]);
- exit(0);
- }
-
- data.fout = fopen(argv[1], "wt");
- if (data.fout == NULL) {
- printf("Error opening output raw file %s\n", argv[1]);
- exit(1);
- }
-
- numSecs = atoi(argv[2]);
- data.framesLeft = numSecs * SAMPLE_RATE;
-
- for(i=0; i<FDMDV_OS_TAPS; i++)
- data.in48k[i] = 0.0;
-
- err = Pa_Initialize();
- if( err != paNoError ) goto done;
-
- printf( "PortAudio version number = %d\nPortAudio version text = '%s'\n",
- Pa_GetVersion(), Pa_GetVersionText() );
-
- inputParameters.device = Pa_GetDefaultInputDevice(); /* default input device */
- if (inputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default input device.\n");
- goto done;
- }
- inputParameters.channelCount = NUM_CHANNELS; /* stereo input */
- inputParameters.sampleFormat = paInt16;
- inputParameters.suggestedLatency = Pa_GetDeviceInfo( inputParameters.device )->defaultLowInputLatency;
- inputParameters.hostApiSpecificStreamInfo = NULL;
-
- /* Record some audio --------------------------------------------- */
-
- err = Pa_OpenStream(
- &stream,
- &inputParameters,
- NULL, /* &outputParameters, */
- SAMPLE_RATE,
- N48,
- paClipOff, /* we won't output out of range samples so don't bother clipping them */
- recordCallback,
- &data );
- if( err != paNoError ) goto done;
-
- err = Pa_StartStream( stream );
- if( err != paNoError ) goto done;
-
- while( ( err = Pa_IsStreamActive( stream ) ) == 1 )
- {
- Pa_Sleep(100);
- }
- if( err < 0 ) goto done;
-
- err = Pa_CloseStream( stream );
- if( err != paNoError ) goto done;
-
- fclose(data.fout);
-
-
-done:
- Pa_Terminate();
- if( err != paNoError )
- {
- fprintf( stderr, "An error occured while using the portaudio stream\n" );
- fprintf( stderr, "Error number: %d\n", err );
- fprintf( stderr, "Error message: %s\n", Pa_GetErrorText( err ) );
- err = 1; /* Always return 0 or 1, but no other return codes. */
- }
- return err;
-}
-
+++ /dev/null
-/*
- pa_recplay.c
- David Rowe
- July 8 2012
-
- Echos audio from sound card input to sound card output. Samples at
- 48 kHz, converts to 8 kHz, converts back to 48kHz, and plays using
- the default sound device. Used as an intermediate step in
- Portaudio integration.
-
- Modified from paex_record.c Portaudio example. Original author
- author Phil Burk http://www.softsynth.com
-*/
-
-/*
- * $Id: paex_record.c 1752 2011-09-08 03:21:55Z philburk $
- *
- * This program uses the PortAudio Portable Audio Library.
- * For more information see: http://www.portaudio.com
- * Copyright (c) 1999-2000 Ross Bencina and Phil Burk
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include "portaudio.h"
-#include "fdmdv.h"
-#include "fifo.h"
-
-#define SAMPLE_RATE 48000 /* 48 kHz sampling rate rec. as we
- can trust accuracy of sound
- card */
-#define N8 160 /* processing buffer size at 8 kHz */
-#define N48 (N8*FDMDV_OS) /* processing buffer size at 48 kHz */
-#define MEM8 (FDMDV_OS_TAPS/FDMDV_OS)
-#define NUM_CHANNELS 2 /* I think most sound cards prefer
- stereo, we will convert to mono
- as we sample */
-#define MAX_FPB 2048 /* maximum value of framesPerBuffer */
-
-/* state information passed to call back */
-
-typedef struct {
- float in48k[FDMDV_OS_TAPS + N48];
- float in8k[MEM8 + N8];
- struct FIFO *infifo;
- struct FIFO *outfifo;
-} paTestData;
-
-
-/*
- This routine will be called by the PortAudio engine when audio is
- required. It may be called at interrupt level on some machines so
- don't do anything that could mess up the system like calling
- malloc() or free().
-*/
-
-static int callback( const void *inputBuffer, void *outputBuffer,
- unsigned long framesPerBuffer,
- const PaStreamCallbackTimeInfo* timeInfo,
- PaStreamCallbackFlags statusFlags,
- void *userData )
-{
- paTestData *data = (paTestData*)userData;
- int i;
- short *rptr = (short*)inputBuffer;
- short *wptr = (short*)outputBuffer;
- float *in8k = data->in8k;
- float *in48k = data->in48k;
- float out8k[N8];
- float out48k[N48];
- short out48k_short[N48];
- short in48k_short[N48];
- short indata[MAX_FPB];
- short outdata[MAX_FPB];
-
- (void) timeInfo;
- (void) statusFlags;
-
- assert(inputBuffer != NULL);
- assert(outputBuffer != NULL);
-
- /*
- framesPerBuffer is portaudio-speak for number of samples we
- actually get from the record side and need to provide to the
- play side. On Linux (at least) it was found that
- framesPerBuffer may not always be what we ask for in the
- framesPerBuffer field of Pa_OpenStream. For example a request
- for 960 sample buffers lead to framesPerBuffer = 1024.
-
- To perform the 48 to 8 kHz conversion we need an integer
- multiple of FDMDV_OS samples to support the interpolation and
- decimation. As we can't guarantee the size of framesPerBuffer
- we do a little FIFO buffering.
- */
-
- //printf("framesPerBuffer: %d N48 %d\n", framesPerBuffer, N48);
-
- /* assemble a mono buffer (just use left channel) and write to FIFO */
-
- assert(framesPerBuffer < MAX_FPB);
- for(i=0; i<framesPerBuffer; i++,rptr+=2)
- indata[i] = *rptr;
- fifo_write(data->infifo, indata, framesPerBuffer);
-
- /* while we have enough samples available ... */
-
- //printf("infifo before: %d\n", fifo_n(data->infifo));
- while (fifo_read(data->infifo, in48k_short, N48) == 0) {
-
- /* convert to float */
-
- for(i=0; i<N48; i++)
- in48k[FDMDV_OS_TAPS + i] = in48k_short[i];
-
- /* downsample and update filter memory */
-
- fdmdv_48_to_8(out8k, &in48k[FDMDV_OS_TAPS], N8);
- for(i=0; i<FDMDV_OS_TAPS; i++)
- in48k[i] = in48k[i+N48];
-
- /* play side, back up to 8k */
-
- for(i=0; i<N8; i++)
- in8k[MEM8+i] = out8k[i];
-
- /* upsample and update filter memory */
-
- fdmdv_8_to_48(out48k, &in8k[MEM8], N8);
- for(i=0; i<MEM8; i++)
- in8k[i] = in8k[i+N8];
-
- /* write signal to both channels */
-
- for(i=0; i<N48; i++)
- out48k_short[i] = (short)out48k[i];
-
- fifo_write(data->outfifo, out48k_short, N48);
- }
- //printf("infifo after: %d\n", fifo_n(data->infifo));
- //printf("outfifo : %d\n", fifo_n(data->outfifo));
-
-
- /* OK now set up output samples */
-
- if (fifo_read(data->outfifo, outdata, framesPerBuffer) == 0) {
-
- /* write signal to both channels */
-
- for(i=0; i<framesPerBuffer; i++,wptr+=2) {
- wptr[0] = outdata[i];
- wptr[1] = outdata[i];
- }
- }
- else {
- //printf("no data\n");
- /* zero output if no data available */
- for(i=0; i<framesPerBuffer; i++,wptr+=2) {
- wptr[0] = 0;
- wptr[1] = 0;
- }
- }
-
- return paContinue;
-}
-
-int main(int argc, char *argv[])
-{
- PaStreamParameters inputParameters, outputParameters;
- PaStream* stream;
- PaError err = paNoError;
- paTestData data;
- int i;
-
- /* init callback data */
-
- for(i=0; i<MEM8; i++)
- data.in8k[i] = 0.0;
- for(i=0; i<FDMDV_OS_TAPS; i++)
- data.in48k[i] = 0.0;
-
- data.infifo = fifo_create(2*N48);
- data.outfifo = fifo_create(2*N48);
-
- /* init port audio */
-
- err = Pa_Initialize();
- if( err != paNoError ) goto done;
-
- inputParameters.device = Pa_GetDefaultInputDevice(); /* default input device */
- if (inputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default input device.\n");
- goto done;
- }
- inputParameters.channelCount = NUM_CHANNELS; /* stereo input */
- inputParameters.sampleFormat = paInt16;
- inputParameters.suggestedLatency = Pa_GetDeviceInfo( inputParameters.device )->defaultLowInputLatency;
- inputParameters.hostApiSpecificStreamInfo = NULL;
-
- outputParameters.device = Pa_GetDefaultOutputDevice(); /* default output device */
- if (outputParameters.device == paNoDevice) {
- fprintf(stderr,"Error: No default output device.\n");
- goto done;
- }
- outputParameters.channelCount = NUM_CHANNELS; /* stereo output */
- outputParameters.sampleFormat = paInt16;
- outputParameters.suggestedLatency = Pa_GetDeviceInfo( outputParameters.device )->defaultLowOutputLatency;
- outputParameters.hostApiSpecificStreamInfo = NULL;
-
- /* Play some audio --------------------------------------------- */
-
- err = Pa_OpenStream(
- &stream,
- &inputParameters,
- &outputParameters,
- SAMPLE_RATE,
- 512,
- paClipOff,
- callback,
- &data );
- if( err != paNoError ) goto done;
-
- err = Pa_StartStream( stream );
- if( err != paNoError ) goto done;
-
- while( ( err = Pa_IsStreamActive( stream ) ) == 1 )
- {
- Pa_Sleep(100);
- }
- if( err < 0 ) goto done;
-
- err = Pa_CloseStream( stream );
- if( err != paNoError ) goto done;
-
-
-done:
- Pa_Terminate();
- if( err != paNoError )
- {
- fprintf( stderr, "An error occured while using the portaudio stream\n" );
- fprintf( stderr, "Error number: %d\n", err );
- fprintf( stderr, "Error message: %s\n", Pa_GetErrorText( err ) );
- err = 1; /* Always return 0 or 1, but no other return codes. */
- }
-
- fifo_destroy(data.infifo);
- fifo_destroy(data.outfifo);
-
- return err;
-}
-
+++ /dev/null
-#!/bin/bash
-# ./menu.sh
-#
-# David Rowe
-# Created August 2009
-#
-# Presents a menu of sound files, press 1 to play file1, 2 to play file2 etc
-#
-# The aim is to make comparing files with different processing easier than
-# using up-arrow on the command line. Based on cdialog.
-#
-# usage:
-# menu.sh file1.raw file2.raw ........ [-d playbackdevice]
-#
-# for example:
-#
-# ../script/menu.sh hts1a.raw hts1a_uq.raw
-#
-# or:
-#
-# ../script/menu.sh hts1a.raw hts1a_uq.raw -d /dev/dsp1
-#
-
-# Copyright (C) 2007 David Rowe
-#
-# All rights reserved.
-#
-# This program is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License version 2, as
-# published by the Free Software Foundation.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, see <http://www.gnu.org/licenses/>.
-
-files=0
-items="Q-Quit\n"
-while [ ! -z "$1" ]
-do
- case "$1" in
- -d) dsp="${1} ${2}"; shift;;
- *) files=`expr 1 + $files`;
- new_file=$1;
- file[$files]=$new_file;
- items="${items} ${files}-${new_file}\n";;
- esac
- shift
-done
-
-echo -n -e "\r" $items"- "
-while true ; do
- echo -n -e "\r -"
- stty cbreak # or stty raw. Stty uses file descriptor 0, not /dev/tty.
- readchar=`dd bs=1 count=1 2>/dev/null`
- stty -cbreak
- if [ -n "$readchar" ] ; then
- if [ x$readchar == 'xq' -o x$readchar == 'xQ' ] ; then
- echo
- exit 0
- fi
- if [ -z ${file[$readchar]} ] ; then
- echo -n -e "\nUnknown input\n" $items"- "
- continue
- fi
- if ( play --version ) >/dev/null 2>&1; then
- play -r 8000 -s -2 ${file[$readchar]} $dsp 2> /dev/null
- elif ( aplay --version ) > /dev/null 2>&1; then
- aplay -r 8000 -f S16_LE ${file[$readchar]} 2> /dev/null
- elif ( ossplay -f? ) > /dev/null 2>&1; then
- ossplay -s8000 -fS16_LE ${file[$readchar]} 2> /dev/null
- else
- echo "could not find play, aplay or ossplay program"
- fi
- fi
-done
-echo
+++ /dev/null
-#!/bin/sh
-# Plays a raw file
-# usage:
-# playraw file.raw
-# playraw file.raw -d /dev/dsp1 (e.g. for USB headphones)
-play -r 8000 -s -2 $1 $2 $3
+++ /dev/null
-#!/bin/sh
-# Converts 16 bit signed short 8 kHz raw (headerless) files to wave
-sox -r 8000 -s -2 $1 $2
+++ /dev/null
-#!/bin/sh
-# Converts wave files to raw (headerless) files
-sox $1 -t raw $2
+++ /dev/null
-AM_CFLAGS = -I../src -fPIC -Wall -O3 -g
-AUTOMAKE_OPTIONS = gnu
-NAME = codec2
-AM_CPPFLAGS = $(AM_CFLAGS)
-
-D=$(abs_srcdir)/codebook
-
-# lsp quantisers
-
-CODEBOOKS= \
- $D/lsp1.txt \
- $D/lsp2.txt \
- $D/lsp3.txt \
- $D/lsp4.txt \
- $D/lsp5.txt \
- $D/lsp6.txt \
- $D/lsp7.txt \
- $D/lsp8.txt \
- $D/lsp9.txt \
- $D/lsp10.txt
-
-# lspd quantisers
-
-CODEBOOKSD= \
- $D/dlsp1.txt \
- $D/dlsp2.txt \
- $D/dlsp3.txt \
- $D/dlsp4.txt \
- $D/dlsp5.txt \
- $D/dlsp6.txt \
- $D/dlsp7.txt \
- $D/dlsp8.txt \
- $D/dlsp9.txt \
- $D/dlsp10.txt
-
-# lspd VQ quantisers
-
-CODEBOOKSVQ= \
- $D/lsp1.txt \
- $D/lsp2.txt \
- $D/lsp3.txt \
- $D/lsp4.txt \
- $(top_srcdir)/unittest/lsp45678910.txt
-
-CODEBOOKSJND= \
- $D/lsp1.txt \
- $D/lsp2.txt \
- $D/lsp3.txt \
- $D/lsp4.txt \
- $(top_srcdir)/unittest/lspjnd5-10.txt
-
-CODEBOOKSDT= \
- $D/lspdt1.txt \
- $D/lspdt2.txt \
- $D/lspdt3.txt \
- $D/lspdt4.txt \
- $D/lspdt5.txt \
- $D/lspdt6.txt \
- $D/lspdt7.txt \
- $D/lspdt8.txt \
- $D/lspdt9.txt \
- $D/lspdt10.txt
-
-CODEBOOKSJVM= \
- $D/lspjvm1.txt \
- $D/lspjvm2.txt \
- $D/lspjvm3.txt
-
-CODEBOOKSVQANSSI= \
- $D/lspvqanssi1.txt \
- $D/lspvqanssi2.txt \
- $D/lspvqanssi3.txt \
- $D/lspvqanssi4.txt
-
-CODEBOOKSGE= \
- $D/gecb.txt
-
-noinst_PROGRAMS = generate_codebook genlspdtcb
-
-codebook.$(OBJEXT): codebook.c
-codebookd.$(OBJEXT): codebookd.c
-codebookdt.$(OBJEXT): codebookdt.c
-codebookvq.$(OBJEXT): codebookvq.c
-codebookjnd.$(OBJEXT): codebookjnd.c
-codebookjvm.$(OBJEXT): codebookjvm.c
-codebookvqanssi.$(OBJEXT): codebookvqanssi.c
-codebookge.$(OBJEXT): codebookge.c
-
-codebook.lo: codebook.c
-
-codebook.c: generate_codebook $(CODEBOOKS)
- ./generate_codebook lsp_cb $(CODEBOOKS) > codebook.c
-
-codebookd.c: generate_codebook $(CODEBOOKSD)
- ./generate_codebook lsp_cbd $(CODEBOOKSD) > codebookd.c
-
-codebookdt.c: generate_codebook $(CODEBOOKSDT)
- ./generate_codebook lsp_cbdt $(CODEBOOKSDT) > codebookdt.c
-
-codebookvq.c: generate_codebook $(CODEBOOKSVQ)
- ./generate_codebook lsp_cbvq $(CODEBOOKSVQ) > codebookvq.c
-
-codebookjnd.c: generate_codebook $(CODEBOOKSJND)
- ./generate_codebook lsp_cbjnd $(CODEBOOKSJND) > codebookjnd.c
-
-codebookjvm.c: generate_codebook $(CODEBOOKSJVM)
- ./generate_codebook lsp_cbjvm $(CODEBOOKSJVM) > codebookjvm.c
-
-codebookvqanssi.c: generate_codebook $(CODEBOOKSVQANSSI)
- ./generate_codebook lsp_cbvqanssi $(CODEBOOKSVQANSSI) > codebookvqanssi.c
-
-codebookge.c: generate_codebook $(CODEBOOKSGE)
- ./generate_codebook ge_cb $(CODEBOOKSGE) > codebookge.c
-
-clean-local:
- -rm -f codebook.c codebookd.c codebookdvq.c codebookjnd.c codebookdt.c codebookjvm.c codebookge.c codebookvqanssi.c
-
-lib_LTLIBRARIES = libcodec2.la
-libcodec2_la_SOURCES = dump.c \
-lpc.c \
-nlp.c \
-postfilter.c \
-sine.c \
-codec2.c \
-fifo.c \
-fdmdv.c \
-kiss_fft.c \
-interp.c \
-lsp.c \
-phase.c \
-quantise.c \
-pack.c \
-codebook.c \
-codebookd.c \
-codebookvq.c \
-codebookjnd.c \
-codebookjvm.c \
-codebookvqanssi.c \
-codebookdt.c \
-codebookge.c
-
-
-libcodec2_la_CFLAGS = $(AM_CFLAGS)
-libcodec2_la_LDFLAGS = $(LIBS)
-
-library_includedir = $(prefix)/include
-library_include_HEADERS = codec2.h
-
-bin_PROGRAMS = c2demo c2enc c2dec c2sim fdmdv_get_test_bits fdmdv_mod fdmdv_demod fdmdv_put_test_bits fdmdv_interleave
-
-c2demo_SOURCES = c2demo.c
-c2demo_LDADD = $(lib_LTLIBRARIES)
-c2demo_LDFLAGS = $(LIBS)
-
-c2enc_SOURCES = c2enc.c
-c2enc_LDADD = $(lib_LTLIBRARIES)
-c2enc_LDFLAGS = $(LIBS)
-
-c2dec_SOURCES = c2dec.c
-c2dec_LDADD = $(lib_LTLIBRARIES)
-c2dec_LDFLAGS = $(LIBS)
-
-c2sim_SOURCES = c2sim.c ampexp.c phaseexp.c
-c2sim_LDADD = $(lib_LTLIBRARIES)
-c2sim_LDFLAGS = $(LIBS)
-
-fdmdv_get_test_bits_SOURCES = fdmdv_get_test_bits.c fdmdv.c kiss_fft.c
-fdmdv_get_test_bits_LDFLAGS = $(LIBS)
-
-fdmdv_mod_SOURCES = fdmdv_mod.c fdmdv.c kiss_fft.c
-fdmdv_mod_LDFLAGS = $(LIBS)
-
-fdmdv_demod_SOURCES = fdmdv_demod.c fdmdv.c kiss_fft.c octave.c
-fdmdv_demod_LDFLAGS = $(LIBS)
-
-fdmdv_put_test_bits_SOURCES = fdmdv_put_test_bits.c fdmdv.c kiss_fft.c
-fdmdv_put_test_bits_LDFLAGS = $(LIBS)
-
-fdmdv_interleave_SOURCES = fdmdv_interleave.c
-fdmdv_interleave_LDFLAGS = $(LIBS)
-
+++ /dev/null
-/*
-Copyright (c) 2003-2010, Mark Borgerding
-
-All rights reserved.
-
-Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
- * Neither the author nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-*/
-
-/* kiss_fft.h
- defines kiss_fft_scalar as either short or a float type
- and defines
- typedef struct { kiss_fft_scalar r; kiss_fft_scalar i; }kiss_fft_cpx; */
-#include "kiss_fft.h"
-#include <limits.h>
-
-#define MAXFACTORS 32
-/* e.g. an fft of length 128 has 4 factors
- as far as kissfft is concerned
- 4*4*4*2
- */
-
-struct kiss_fft_state{
- int nfft;
- int inverse;
- int factors[2*MAXFACTORS];
- kiss_fft_cpx twiddles[1];
-};
-
-/*
- Explanation of macros dealing with complex math:
-
- C_MUL(m,a,b) : m = a*b
- C_FIXDIV( c , div ) : if a fixed point impl., c /= div. noop otherwise
- C_SUB( res, a,b) : res = a - b
- C_SUBFROM( res , a) : res -= a
- C_ADDTO( res , a) : res += a
- * */
-#ifdef FIXED_POINT
-#if (FIXED_POINT==32)
-# define FRACBITS 31
-# define SAMPPROD int64_t
-#define SAMP_MAX 2147483647
-#else
-# define FRACBITS 15
-# define SAMPPROD int32_t
-#define SAMP_MAX 32767
-#endif
-
-#define SAMP_MIN -SAMP_MAX
-
-#if defined(CHECK_OVERFLOW)
-# define CHECK_OVERFLOW_OP(a,op,b) \
- if ( (SAMPPROD)(a) op (SAMPPROD)(b) > SAMP_MAX || (SAMPPROD)(a) op (SAMPPROD)(b) < SAMP_MIN ) { \
- fprintf(stderr,"WARNING:overflow @ " __FILE__ "(%d): (%d " #op" %d) = %ld\n",__LINE__,(a),(b),(SAMPPROD)(a) op (SAMPPROD)(b) ); }
-#endif
-
-
-# define smul(a,b) ( (SAMPPROD)(a)*(b) )
-# define sround( x ) (kiss_fft_scalar)( ( (x) + (1<<(FRACBITS-1)) ) >> FRACBITS )
-
-# define S_MUL(a,b) sround( smul(a,b) )
-
-# define C_MUL(m,a,b) \
- do{ (m).r = sround( smul((a).r,(b).r) - smul((a).i,(b).i) ); \
- (m).i = sround( smul((a).r,(b).i) + smul((a).i,(b).r) ); }while(0)
-
-# define DIVSCALAR(x,k) \
- (x) = sround( smul( x, SAMP_MAX/k ) )
-
-# define C_FIXDIV(c,div) \
- do { DIVSCALAR( (c).r , div); \
- DIVSCALAR( (c).i , div); }while (0)
-
-# define C_MULBYSCALAR( c, s ) \
- do{ (c).r = sround( smul( (c).r , s ) ) ;\
- (c).i = sround( smul( (c).i , s ) ) ; }while(0)
-
-#else /* not FIXED_POINT*/
-
-# define S_MUL(a,b) ( (a)*(b) )
-#define C_MUL(m,a,b) \
- do{ (m).r = (a).r*(b).r - (a).i*(b).i;\
- (m).i = (a).r*(b).i + (a).i*(b).r; }while(0)
-# define C_FIXDIV(c,div) /* NOOP */
-# define C_MULBYSCALAR( c, s ) \
- do{ (c).r *= (s);\
- (c).i *= (s); }while(0)
-#endif
-
-#ifndef CHECK_OVERFLOW_OP
-# define CHECK_OVERFLOW_OP(a,op,b) /* noop */
-#endif
-
-#define C_ADD( res, a,b)\
- do { \
- CHECK_OVERFLOW_OP((a).r,+,(b).r)\
- CHECK_OVERFLOW_OP((a).i,+,(b).i)\
- (res).r=(a).r+(b).r; (res).i=(a).i+(b).i; \
- }while(0)
-#define C_SUB( res, a,b)\
- do { \
- CHECK_OVERFLOW_OP((a).r,-,(b).r)\
- CHECK_OVERFLOW_OP((a).i,-,(b).i)\
- (res).r=(a).r-(b).r; (res).i=(a).i-(b).i; \
- }while(0)
-#define C_ADDTO( res , a)\
- do { \
- CHECK_OVERFLOW_OP((res).r,+,(a).r)\
- CHECK_OVERFLOW_OP((res).i,+,(a).i)\
- (res).r += (a).r; (res).i += (a).i;\
- }while(0)
-
-#define C_SUBFROM( res , a)\
- do {\
- CHECK_OVERFLOW_OP((res).r,-,(a).r)\
- CHECK_OVERFLOW_OP((res).i,-,(a).i)\
- (res).r -= (a).r; (res).i -= (a).i; \
- }while(0)
-
-
-#ifdef FIXED_POINT
-# define KISS_FFT_COS(phase) floor(.5+SAMP_MAX * cos (phase))
-# define KISS_FFT_SIN(phase) floor(.5+SAMP_MAX * sin (phase))
-# define HALF_OF(x) ((x)>>1)
-#elif defined(USE_SIMD)
-# define KISS_FFT_COS(phase) _mm_set1_ps( cos(phase) )
-# define KISS_FFT_SIN(phase) _mm_set1_ps( sin(phase) )
-# define HALF_OF(x) ((x)*_mm_set1_ps(.5))
-#else
-# define KISS_FFT_COS(phase) (kiss_fft_scalar) cos(phase)
-# define KISS_FFT_SIN(phase) (kiss_fft_scalar) sin(phase)
-# define HALF_OF(x) ((x)*.5)
-#endif
-
-#define kf_cexp(x,phase) \
- do{ \
- (x)->r = KISS_FFT_COS(phase);\
- (x)->i = KISS_FFT_SIN(phase);\
- }while(0)
-
-
-/* a debugging function */
-#define pcpx(c)\
- fprintf(stderr,"%g + %gi\n",(double)((c)->r),(double)((c)->i) )
-
-
-#ifdef KISS_FFT_USE_ALLOCA
-// define this to allow use of alloca instead of malloc for temporary buffers
-// Temporary buffers are used in two case:
-// 1. FFT sizes that have "bad" factors. i.e. not 2,3 and 5
-// 2. "in-place" FFTs. Notice the quotes, since kissfft does not really do an in-place transform.
-#include <alloca.h>
-#define KISS_FFT_TMP_ALLOC(nbytes) alloca(nbytes)
-#define KISS_FFT_TMP_FREE(ptr)
-#else
-#define KISS_FFT_TMP_ALLOC(nbytes) KISS_FFT_MALLOC(nbytes)
-#define KISS_FFT_TMP_FREE(ptr) KISS_FFT_FREE(ptr)
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: ampexp.c
- AUTHOR......: David Rowe
- DATE CREATED: 7 August 2012
-
- Functions for experimenting with amplitude quantisation.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not,see <http://www.gnu.org/licenses/>.
-*/
-
-
-#include <assert.h>
-#include <ctype.h>
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-
-#include "ampexp.h"
-
-
-#define PRED_COEFF 0.9
-
-/* states for amplitude experiments */
-
-struct codebook {
- unsigned int k;
- unsigned int log2m;
- unsigned int m;
- float *cb;
- unsigned int offset;
-};
-
-struct AEXP {
- float A_prev[MAX_AMP];
- int frames;
- float snr;
- int snr_n;
- float var;
- int var_n;
- float vq_var;
- int vq_var_n;
- struct codebook *vq1,*vq2,*vq3,*vq4,*vq5;
-
- int indexes[5][3];
- MODEL model[3];
- float mag[3];
- MODEL model_uq[3];
-};
-
-
-/*---------------------------------------------------------------------------*\
-
- Bruce Perens' funcs to load codebook files
-
-\*---------------------------------------------------------------------------*/
-
-
-static const char format[] =
-"The table format must be:\n"
-"\tTwo integers describing the dimensions of the codebook.\n"
-"\tThen, enough numbers to fill the specified dimensions.\n";
-
-static float get_float(FILE * in, const char * name, char * * cursor, char * buffer, int size)
-{
- for ( ; ; ) {
- char * s = *cursor;
- char c;
-
- while ( (c = *s) != '\0' && !isdigit(c) && c != '-' && c != '.' )
- s++;
-
- /* Comments start with "#" and continue to the end of the line. */
- if ( c != '\0' && c != '#' ) {
- char * end = 0;
- float f = 0;
-
- f = strtod(s, &end);
-
- if ( end != s )
- *cursor = end;
- return f;
- }
-
- if ( fgets(buffer, size, in) == NULL ) {
- fprintf(stderr, "%s: Format error. %s\n", name, format);
- exit(1);
- }
- *cursor = buffer;
- }
-}
-
-static struct codebook *load(const char * name)
-{
- FILE *file;
- char line[2048];
- char *cursor = line;
- struct codebook *b = malloc(sizeof(struct codebook));
- int i;
- int size;
-
- file = fopen(name, "rt");
- assert(file != NULL);
-
- *cursor = '\0';
-
- b->k = (int)get_float(file, name, &cursor, line, sizeof(line));
- b->m = (int)get_float(file, name ,&cursor, line, sizeof(line));
- size = b->k * b->m;
-
- b->cb = (float *)malloc(size * sizeof(float));
-
- for ( i = 0; i < size; i++ ) {
- b->cb[i] = get_float(file, name, &cursor, line, sizeof(line));
- }
-
- fclose(file);
-
- return b;
-}
-
-
-/*---------------------------------------------------------------------------* \
-
- amp_experiment_create()
-
- Inits states for amplitude quantisation experiments.
-
-\*---------------------------------------------------------------------------*/
-
-struct AEXP *amp_experiment_create() {
- struct AEXP *aexp;
- int i,j,m;
-
- aexp = (struct AEXP *)malloc(sizeof(struct AEXP));
- assert (aexp != NULL);
-
- for(i=0; i<MAX_AMP; i++)
- aexp->A_prev[i] = 1.0;
- aexp->frames = 0;
- aexp->snr = 0.0;
- aexp->snr_n = 0;
- aexp->var = 0.0;
- aexp->var_n = 0;
- aexp->vq_var = 0.0;
- aexp->vq_var_n = 0;
-
- //aexp->vq1 = load("amp_1_80_1024a.txt");
- //aexp->vq1 = load("../unittest/st1_10_1024.txt");
- //aexp->vq1 = load("../unittest/amp41_80_1024.txt");
- //aexp->vq1->offset = 40;
- aexp->vq1 = load("../unittest/amp1_10_1024.txt");
- aexp->vq1->offset = 0;
- aexp->vq2 = load("../unittest/amp11_20_1024.txt");
- aexp->vq2->offset = 10;
-
- aexp->vq3 = load("../unittest/amp21_40_1024.txt");
- aexp->vq3->offset = 20;
- aexp->vq4 = load("../unittest/amp41_60_1024.txt");
- aexp->vq4->offset = 40;
- aexp->vq5 = load("../unittest/amp61_80_256.txt");
- aexp->vq5->offset = 60;
-
- #ifdef CAND2_GS
- //aexp->vq1 = load("../unittest/t1_amp1_20_1024.txt");
- //aexp->vq1 = load("../unittest/t2_amp1_20_1024.txt");
- aexp->vq1 = load("../unittest/amp1_20_1024.txt");
- aexp->vq1->offset = 0;
- aexp->vq2 = load("../unittest/amp21_40_1024.txt");
- aexp->vq2->offset = 20;
- aexp->vq3 = load("../unittest/amp41_60_1024.txt");
- aexp->vq3->offset = 40;
- aexp->vq4 = load("../unittest/amp61_80_32.txt");
- aexp->vq4->offset = 60;
- #endif
-
- //#define CAND2_GS
- #ifdef CAND2_GS
- aexp->vq1 = load("../unittest/amp1_20_1024.txt");
- aexp->vq2 = load("../unittest/amp21_40_1024.txt");
- aexp->vq3 = load("../unittest/amp41_80_1024.txt");
- aexp->vq4 = load("../unittest/amp61_80_32.txt");
- aexp->vq1->offset = 0;
- aexp->vq2->offset = 20;
- aexp->vq3->offset = 40;
- aexp->vq4->offset = 60;
- #endif
-
- //#define CAND1
- #ifdef CAND1
- aexp->vq1 = load("../unittest/amp1_10_128.txt");
- aexp->vq2 = load("../unittest/amp11_20_512.txt");
- aexp->vq3 = load("../unittest/amp21_40_1024.txt");
- aexp->vq4 = load("../unittest/amp41_60_1024.txt");
- aexp->vq5 = load("../unittest/amp61_80_32.txt");
- aexp->vq1->offset = 0;
- aexp->vq2->offset = 10;
- aexp->vq3->offset = 20;
- aexp->vq4->offset = 40;
- aexp->vq5->offset = 60;
- #endif
-
- for(i=0; i<3; i++) {
- for(j=0; j<5; j++)
- aexp->indexes[j][i] = 0;
- aexp->mag[i] = 1.0;
- aexp->model[i].Wo = TWO_PI*100.0/8000.0;
- aexp->model[i].L = floor(PI/aexp->model[i].Wo);
- for(m=1; m<=MAX_AMP; m++)
- aexp->model[i].A[m] = 10.0;
- aexp->model_uq[i] = aexp->model[i];
- }
-
- return aexp;
-}
-
-
-/*---------------------------------------------------------------------------* \
-
- amp_experiment_destroy()
-
-\*---------------------------------------------------------------------------*/
-
-void amp_experiment_destroy(struct AEXP *aexp) {
- assert(aexp != NULL);
- if (aexp->snr != 0.0)
- printf("snr: %4.2f dB\n", aexp->snr/aexp->snr_n);
- if (aexp->var != 0.0)
- printf("var...: %4.3f std dev...: %4.3f (%d amplitude samples)\n",
- aexp->var/aexp->var_n, sqrt(aexp->var/aexp->var_n), aexp->var_n);
- if (aexp->vq_var != 0.0)
- printf("vq var: %4.3f std dev...: %4.3f (%d amplitude samples)\n",
- aexp->vq_var/aexp->vq_var_n, sqrt(aexp->vq_var/aexp->vq_var_n), aexp->vq_var_n);
- free(aexp);
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- Various test and experimental functions ................
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Quantisation noise simulation. Assume noise on amplitudes is a uniform
- distribution, of +/- x dB. This means x = sqrt(3)*sigma.
-
- Note: for uniform distribution var = = sigma * sigma = (b-a)*(b-a)/12.
-*/
-
-static void add_quant_noise(struct AEXP *aexp, MODEL *model, int start, int end, float sigma_dB)
-{
- int m;
- float x_dB;
- float noise_sam_dB;
- float noise_sam_lin;
-
- x_dB = sqrt(3.0) * sigma_dB;
-
- for(m=start; m<=end; m++) {
- noise_sam_dB = x_dB*(1.0 - 2.0*rand()/RAND_MAX);
- //printf("%f\n", noise_sam_dB);
- noise_sam_lin = pow(10.0, noise_sam_dB/20.0);
- model->A[m] *= noise_sam_lin;
- aexp->var += noise_sam_dB*noise_sam_dB;
- aexp->var_n++;
- }
-
-}
-
-/*
- void print_sparse_pred_error()
-
- use to check pred error stats (e.g. of first 1kHz) in Octave:
-
- $ ./c2sim ../raw/hts1a.raw --ampexp > amppe.txt
-
- octave> load ../src/amppe.txt
- octave> std(nonzeros(amppe(:,1:20)))
- octave> hist(nonzeros(amppe(:,1:20)),20);
-
- */
-
-
-static void print_sparse_pred_error(struct AEXP *aexp, MODEL *model, float mag_thresh)
-{
- int m, index;
- float mag, error;
- float sparse_pe[MAX_AMP];
-
- mag = 0.0;
- for(m=1; m<=model->L; m++)
- mag += model->A[m]*model->A[m];
- mag = 10*log10(mag/model->L);
-
- if (mag > mag_thresh) {
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe[m] = 0.0;
- }
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
- error = PRED_COEFF*20.0*log10(aexp->A_prev[m]) - 20.0*log10(model->A[m]);
- //error = 20.0*log10(model->A[m]) - mag;
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe[index] = error;
- }
-
- /* dump sparse amp vector */
-
- for(m=0; m<MAX_AMP; m++)
- printf("%f ", sparse_pe[m]);
- printf("\n");
- }
-}
-
-
-static float frame_energy(MODEL *model, float *enormdB) {
- int m;
- float e, edB;
-
- e = 0.0;
- for(m=1; m<=model->L; m++)
- e += model->A[m]*model->A[m];
- edB = 10*log10(e);
-
- #define VER_E0
-
- #ifdef VER_E0
- *enormdB = 10*log10(e/model->L); /* make high and low pitches have similar amps */
- #endif
-
- #ifdef VER_E1
- e = 0.0;
- for(m=1; m<=model->L; m++)
- e += 10*log10(model->A[m]*model->A[m]);
- *enormdB = e;
- #endif
-
- #ifdef VER_E2
- e = 0.0;
- for(m=1; m<=model->L; m++)
- e += 10*log10(model->A[m]*model->A[m]);
- *enormdB = e/model->L;
- #endif
- //printf("%f\n", enormdB);
-
- return edB;
-}
-
-static void print_sparse_amp_error(struct AEXP *aexp, MODEL *model, float edB_thresh)
-{
- int m, index;
- float edB, enormdB, error, dWo, Am;
- float sparse_pe[MAX_AMP];
-
- edB = frame_energy(model, &enormdB);
- //printf("%f\n", enormdB);
- dWo = fabs((aexp->model_uq[2].Wo - aexp->model_uq[1].Wo)/aexp->model_uq[2].Wo);
-
- if ((edB > edB_thresh) && (dWo < 0.1)) {
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe[m] = 0.0;
- }
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
- error = 20.0*log10(model->A[m]) - enormdB;
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe[index] = error;
- }
-
- /* dump sparse amp vector */
-
- for(m=0; m<MAX_AMP; m++)
- printf("%f ", sparse_pe[m]);
- printf("\n");
- }
-}
-
-
-int vq_amp(float cb[], float vec[], float weights[], int d, int e, float *se)
-{
- float error; /* current error */
- int besti; /* best index so far */
- float best_error; /* best error so far */
- int i,j;
- float diff, metric, best_metric;
-
- besti = 0;
- best_metric = best_error = 1E32;
- for(j=0; j<e; j++) {
- metric = error = 0.0;
- for(i=0; i<d; i++) {
- if (vec[i] != 0.0) {
- diff = (cb[j*d+i] - vec[i]);
- error += diff*diff;
- metric += weights[i]*diff*diff;
- }
- }
- if (metric < best_metric) {
- best_error = error;
- best_metric = metric;
- besti = j;
- }
- }
-
- *se += best_error;
-
- return(besti);
-}
-
-
-static int split_vq(float sparse_pe_out[], struct AEXP *aexp, struct codebook *vq, float weights[], float sparse_pe_in[])
-{
- int i, j, non_zero, vq_ind;
- float se;
-
- vq_ind = vq_amp(vq->cb, &sparse_pe_in[vq->offset], &weights[vq->offset], vq->k, vq->m, &se);
- printf("\n offset %d k %d m %d vq_ind %d j: ", vq->offset, vq->k, vq->m, vq_ind);
-
- non_zero = 0;
- for(i=0, j=vq->offset; i<vq->k; i++,j++) {
- if (sparse_pe_in[j] != 0.0) {
- printf("%d ", j);
- sparse_pe_in[j] -= vq->cb[vq->k * vq_ind + i];
- sparse_pe_out[j] += vq->cb[vq->k * vq_ind + i];
- non_zero++;
- }
- }
- aexp->vq_var_n += non_zero;
- return vq_ind;
-}
-
-
-static void sparse_vq_pred_error(struct AEXP *aexp,
- MODEL *model
-)
-{
- int m, index;
- float error, amp_dB, edB, enormdB;
- float sparse_pe_in[MAX_AMP];
- float sparse_pe_out[MAX_AMP];
- float weights[MAX_AMP];
-
- edB = frame_energy(model, &enormdB);
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_in[m] = 0.0;
- sparse_pe_out[m] = 0.0;
- }
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
- error = PRED_COEFF*20.0*log10(aexp->A_prev[m]) - 20.0*log10(model->A[m]);
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_in[index] = error;
- weights[index] = model->A[m];
- }
-
- /* vector quantise */
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_out[m] = sparse_pe_in[m];
- }
-
- //#define SIM_VQ
- #ifndef SIM_VQ
- split_vq(sparse_pe_out, aexp, aexp->vq1, weights, sparse_pe_in);
- #else
- for(m=aexp->vq->offset; m<aexp->vq->offset+aexp->vq->k; m++) {
- if (sparse_pe_in[m] != 0.0) {
- float error = 8*(1.0 - 2.0*rand()/RAND_MAX);
- aexp->vq_var += error*error;
- aexp->vq_var_n++;
- sparse_pe_out[m] = sparse_pe_in[m] + error;
- }
- }
- #endif
-
- if (edB > -100.0)
- for(m=0; m<MAX_AMP; m++) {
- if (sparse_pe_in[m] != 0.0)
- aexp->vq_var += pow(sparse_pe_out[m] - sparse_pe_in[m], 2.0);
- }
-
- /* transform quantised amps back */
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- amp_dB = PRED_COEFF*20.0*log10(aexp->A_prev[m]) - sparse_pe_out[index];
- //printf("in: %f out: %f\n", sparse_pe_in[index], sparse_pe_out[index]);
- //printf("amp_dB: %f A[m] (dB) %f\n", amp_dB, 20.0*log10(model->A[m]));
- model->A[m] = pow(10.0, amp_dB/20.0);
- }
- //exit(0);
-}
-
-
-static void split_error(struct AEXP *aexp, struct codebook *vq, float sparse_pe_in[], int ind)
-{
- int i, j;
-
- for(i=0, j=vq->offset; i<vq->k; i++,j++) {
- if (sparse_pe_in[j] != 0.0) {
- sparse_pe_in[j] -= vq->cb[vq->k * ind + i];
- }
- }
-}
-
-
-static void sparse_vq_amp(struct AEXP *aexp, MODEL *model)
-{
- int m, index;
- float error, amp_dB, edB, enormdB;
- float sparse_pe_in[MAX_AMP];
- float sparse_pe_out[MAX_AMP];
- float weights[MAX_AMP];
-
- edB = frame_energy(model, &enormdB);
-
- aexp->mag[2] = enormdB;
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_in[m] = 0.0;
- sparse_pe_out[m] = 0.0;
- }
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
- error = 20.0*log10(model->A[m]) - enormdB;
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_in[index] = error;
- weights[index] = pow(model->A[m],0.8);
- }
-
- /* vector quantise */
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_out[m] = sparse_pe_in[m];
- }
-
- for(m=0; m<80; m++)
- sparse_pe_out[m] = 0;
-
- #define SPLIT
- #ifdef SPLIT
- aexp->indexes[0][2] = split_vq(sparse_pe_out, aexp, aexp->vq1, weights, sparse_pe_in);
-
- aexp->indexes[1][2] = split_vq(sparse_pe_out, aexp, aexp->vq2, weights, sparse_pe_in);
- aexp->indexes[2][2] = split_vq(sparse_pe_out, aexp, aexp->vq3, weights, sparse_pe_in);
- aexp->indexes[3][2] = split_vq(sparse_pe_out, aexp, aexp->vq4, weights, sparse_pe_in);
- aexp->indexes[4][2] = split_vq(sparse_pe_out, aexp, aexp->vq5, weights, sparse_pe_in);
- #endif
- //#define MULTISTAGE
- #ifdef MULTISTAGE
- aexp->indexes[0][2] = split_vq(sparse_pe_out, aexp, aexp->vq1, weights, sparse_pe_in);
- aexp->indexes[1][2] = split_vq(sparse_pe_out, aexp, aexp->vq2, weights, sparse_pe_in);
- aexp->indexes[2][2] = split_vq(sparse_pe_out, aexp, aexp->vq3, weights, sparse_pe_in);
- //aexp->indexes[3][2] = split_vq(sparse_pe_out, aexp, aexp->vq4, weights, sparse_pe_in);
- #endif
-
- for(m=0; m<MAX_AMP; m++) {
- if (sparse_pe_in[m] != 0.0)
- aexp->vq_var += pow(sparse_pe_out[m] - sparse_pe_in[m], 2.0);
- }
-
- /* transform quantised amps back */
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- amp_dB = sparse_pe_out[index] + enormdB;
- model->A[m] = pow(10.0, amp_dB/20.0);
- }
- //exit(0);
-}
-
-
-static void update_snr_calc(struct AEXP *aexp, MODEL *m1, MODEL *m2)
-{
- int m;
- float signal, noise, signal_dB;
-
- assert(m1->L == m2->L);
-
- signal = 0.0; noise = 1E-32;
- for(m=1; m<=m1->L; m++) {
- signal += m1->A[m]*m1->A[m];
- noise += pow(m1->A[m] - m2->A[m], 2.0);
- //printf("%f %f\n", before[m], model->phi[m]);
- }
- signal_dB = 10*log10(signal);
- if (signal_dB > -100.0) {
- aexp->snr += 10.0*log10(signal/noise);
- aexp->snr_n++;
- }
-}
-
-
-/* gain/shape vq search. Returns index of best gain. Gain is additive (as we use log quantisers) */
-
-int gain_shape_vq_amp(float cb[], float vec[], float weights[], int d, int e, float *se, float *best_gain)
-{
- float error; /* current error */
- int besti; /* best index so far */
- float best_error; /* best error so far */
- int i,j,m;
- float diff, metric, best_metric, gain, sumAm, sumCb;
-
- besti = 0;
- best_metric = best_error = 1E32;
- for(j=0; j<e; j++) {
-
- /* compute optimum gain */
-
- sumAm = sumCb = 0.0;
- m = 0;
- for(i=0; i<d; i++) {
- if (vec[i] != 0.0) {
- m++;
- sumAm += vec[i];
- sumCb += cb[j*d+i];
- }
- }
- gain = (sumAm - sumCb)/m;
-
- /* compute error */
-
- metric = error = 0.0;
- for(i=0; i<d; i++) {
- if (vec[i] != 0.0) {
- diff = vec[i] - cb[j*d+i] - gain;
- error += diff*diff;
- metric += weights[i]*diff*diff;
- }
- }
- if (metric < best_metric) {
- best_error = error;
- best_metric = metric;
- *best_gain = gain;
- besti = j;
- }
- }
-
- *se += best_error;
-
- return(besti);
-}
-
-
-static void gain_shape_split_vq(float sparse_pe_out[], struct AEXP *aexp, struct codebook *vq, float weights[], float sparse_pe_in[], float *best_gain)
-{
- int i, j, non_zero, vq_ind;
- float se;
-
- vq_ind = gain_shape_vq_amp(vq->cb, &sparse_pe_in[vq->offset], &weights[vq->offset], vq->k, vq->m, &se, best_gain);
- //printf("\n offset %d k %d m %d vq_ind %d gain: %4.2f j: ", vq->offset, vq->k, vq->m, vq_ind, *best_gain);
-
- non_zero = 0;
- for(i=0, j=vq->offset; i<vq->k; i++,j++) {
- if (sparse_pe_in[j] != 0.0) {
- //printf("%d ", j);
- sparse_pe_out[j] = vq->cb[vq->k * vq_ind + i] + *best_gain;
- non_zero++;
- }
- }
- aexp->vq_var_n += non_zero;
-}
-
-
-static void gain_shape_sparse_vq_amp(struct AEXP *aexp, MODEL *model)
-{
- int m, index;
- float amp_dB, best_gain;
- float sparse_pe_in[MAX_AMP];
- float sparse_pe_out[MAX_AMP];
- float weights[MAX_AMP];
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_in[m] = 0.0;
- sparse_pe_out[m] = 0.0;
- }
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_in[index] = 20.0*log10(model->A[m]);
- weights[index] = model->A[m];
- }
-
- /* vector quantise */
-
- for(m=0; m<=MAX_AMP; m++) {
- sparse_pe_out[m] = sparse_pe_in[m];
- }
-
- gain_shape_split_vq(sparse_pe_out, aexp, aexp->vq1, weights, sparse_pe_in, &best_gain);
- gain_shape_split_vq(sparse_pe_out, aexp, aexp->vq2, weights, sparse_pe_in, &best_gain);
- gain_shape_split_vq(sparse_pe_out, aexp, aexp->vq3, weights, sparse_pe_in, &best_gain);
- gain_shape_split_vq(sparse_pe_out, aexp, aexp->vq4, weights, sparse_pe_in, &best_gain);
-
- for(m=0; m<MAX_AMP; m++) {
- if (sparse_pe_in[m] != 0.0)
- aexp->vq_var += pow(sparse_pe_out[m] - sparse_pe_in[m], 2.0);
- }
-
- /* transform quantised amps back */
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- amp_dB = sparse_pe_out[index];
- model->A[m] = pow(10.0, amp_dB/20.0);
- }
- //exit(0);
-}
-
-
-static void interp_split_vq(float sparse_pe_out[], struct AEXP *aexp, struct codebook *vq, float sparse_pe_in[], int ind)
-{
- int i, j;
- float amp_dB;
-
- for(i=0, j=vq->offset; i<vq->k; i++,j++) {
- if (sparse_pe_in[j] != 0.0) {
- amp_dB = 0.5*(aexp->mag[0] + vq->cb[vq->k * aexp->indexes[ind][0] + i]);
- amp_dB += 0.5*(aexp->mag[2] + vq->cb[vq->k * aexp->indexes[ind][2] + i]);
- sparse_pe_out[j] = amp_dB;
- }
- }
-}
-
-
-static void vq_interp(struct AEXP *aexp, MODEL *model, int on)
-{
- int i, j, m, index;
- float amp_dB;
- //struct codebook *vq = aexp->vq1;
- float sparse_pe_in[MAX_AMP];
- float sparse_pe_out[MAX_AMP];
-
- /* replace odd frames with interp */
- /* once we get an even input frame we can interpolate and output odd */
- /* using VQ to interpolate. This assumes some correlation in
- adjacent VQ samples */
-
- memcpy(&aexp->model[2], model, sizeof(MODEL));
-
- /* once we get an even input frame we have enough information to
- replace prev odd frame with interpolated version */
-
- if (on && ((aexp->frames % 2) == 0)) {
-
- /* copy Wo, L, and phases */
-
- memcpy(model, &aexp->model[1], sizeof(MODEL));
- //printf("mags: %4.2f %4.2f %4.2f Am: \n", aexp->mag[0], aexp->mag[1], aexp->mag[2]);
-
- /* now replace Am by interpolation, use similar design to VQ
- to handle different bands */
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_in[index] = 20.0*log10(model->A[m]);
- }
-
- /* this can be used for when just testing partial interpolation */
-
- for(m=0; m<MAX_AMP; m++) {
- //sparse_pe_out[m] = sparse_pe_in[m];
- sparse_pe_out[m] = 0;
- }
-
- interp_split_vq(sparse_pe_out, aexp, aexp->vq1, sparse_pe_in, 0);
- interp_split_vq(sparse_pe_out, aexp, aexp->vq2, sparse_pe_in, 1);
- interp_split_vq(sparse_pe_out, aexp, aexp->vq3, sparse_pe_in, 2);
- interp_split_vq(sparse_pe_out, aexp, aexp->vq4, sparse_pe_in, 3);
- interp_split_vq(sparse_pe_out, aexp, aexp->vq5, sparse_pe_in, 4);
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- amp_dB = sparse_pe_out[index];
- //printf(" %4.2f", 10.0*log10(model->A[m]));
- model->A[m] = pow(10.0, amp_dB/20.0);
- //printf(" %4.2f\n", 10.0*log10(model->A[m]));
- }
-
- #ifdef INITIAL_VER
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
-
- if (index < vq->k) {
- amp_dB = 0.5*(aexp->mag[0] + vq->cb[vq->k * aexp->indexes[0] + index]);
- amp_dB += 0.5*(aexp->mag[2] + vq->cb[vq->k * aexp->indexes[2] + index]);
- //printf(" %4.2f", 10.0*log10(model->A[m]));
- //amp_dB = 10;
- model->A[m] = pow(10.0, amp_dB/20.0);
- printf(" %4.2f\n", 10.0*log10(model->A[m]));
- }
- }
-
- #endif
- }
- else
- memcpy(model, &aexp->model[1], sizeof(MODEL));
-
- /* update memories */
-
- for(i=0; i<2; i++) {
- memcpy(&aexp->model[i], &aexp->model[i+1], sizeof(MODEL));
- for(j=0; j<5; j++)
- aexp->indexes[j][i] = aexp->indexes[j][i+1];
- aexp->mag[i] = aexp->mag[i+1];
- }
-
-}
-
-
-/*
- This functions tests theory that some bands can be combined together
- due to less frequency resolution at higher frequencies. This will
- reduce the amount of information we need to encode.
-*/
-
-void smooth_samples(struct AEXP *aexp, MODEL *model, int mode)
-{
- int m, i, j, index, step, nav, v, en;
- float sparse_pe_in[MAX_AMP], av, amp_dB;
- float sparse_pe_out[MAX_AMP];
- float smoothed[MAX_AMP], smoothed_out[MAX_AMP];
- float weights[MAX_AMP];
- float edB, enormdB;
-
- edB = frame_energy(model, &enormdB);
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_in[m] = 0.0;
- sparse_pe_out[m] = 0.0;
- }
-
- /* set up sparse array */
-
- for(m=1; m<=model->L; m++) {
- assert(model->A[m] > 0.0);
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_out[index] = sparse_pe_in[index] = 20.0*log10(model->A[m]) - enormdB;
- }
-
- /* now combine samples at high frequencies to reduce dimension */
-
- step=4;
- for(i=MAX_AMP/2,v=0; i<MAX_AMP; i+=step,v++) {
-
- /* average over one band */
-
- av = 0.0; nav = 0;
- en = i+step;
- if (en > (MAX_AMP-1))
- en = MAX_AMP-1;
- for(j=i; j<en; j++) {
- if (sparse_pe_in[j] != 0.0) {
- av += sparse_pe_in[j];
- nav++;
- }
- }
- if (nav) {
- av /= nav;
- smoothed[v] = av;
- weights[v] = pow(10.0,av/20.0);
- //weights[v] = 1.0;
- }
- else
- smoothed[v] = 0.0;
-
- }
-
- if (mode == 1) {
- for(i=0; i<v; i++)
- printf("%5.2f ", smoothed[i]);
- printf("\n");
- }
-
- if (mode == 2) {
- for(i=0; i<v; i++)
- smoothed_out[i] = 0;
- split_vq(smoothed_out, aexp, aexp->vq1, weights, smoothed);
- for(i=0; i<v; i++)
- smoothed[i] = smoothed_out[i];
- }
-
- /* set all samples to smoothed average */
-
- step = 4;
- for(i=MAX_AMP/2,v=0; i<MAX_AMP; i+=step,v++) {
- en = i+step;
- if (en > (MAX_AMP-1))
- en = MAX_AMP-1;
- for(j=i; j<en; j++)
- sparse_pe_out[j] = smoothed[v];
- }
-
- /* convert back to Am */
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- amp_dB = sparse_pe_out[index] + enormdB;
- //printf("%d %4.2f %4.2f\n", m, 10.0*log10(model->A[m]), amp_dB);
- model->A[m] = pow(10.0, amp_dB/20.0);
- }
-
-}
-
-#define MAX_BINS 40
-static float bins[] = {
- /*1000.0, 1200.0, 1400.0, 1600.0, 1800,*/
- 2000.0, 2400.0, 2800.0,
- 3000.0, 3400.0, 3600.0, 4000.0};
-
-void smooth_amp(struct AEXP *aexp, MODEL *model) {
- int m, i;
- int nbins;
- int b;
- float f;
- float av[MAX_BINS];
- int nav[MAX_BINS];
-
- nbins = sizeof(bins)/sizeof(float);
-
- /* clear all bins */
-
- for(i=0; i<MAX_BINS; i++) {
- av[i] = 0.0;
- nav[i] = 0;
- }
-
- /* add amps into each bin */
-
- for(m=1; m<=model->L; m++) {
- f = m*model->Wo*FS/TWO_PI;
- if (f > bins[0]) {
-
- /* find bin */
-
- for(i=0; i<nbins; i++)
- if ((f > bins[i]) && (f <= bins[i+1]))
- b = i;
- assert(b < MAX_BINS);
-
- av[b] += model->A[m]*model->A[m];
- nav[b]++;
- }
-
- }
-
- /* use averages to est amps */
-
- for(m=1; m<=model->L; m++) {
- f = m*model->Wo*FS/TWO_PI;
- if (f > bins[0]) {
-
- /* find bin */
-
- for(i=0; i<nbins; i++)
- if ((f > bins[i]) && (f <= bins[i+1]))
- b = i;
- assert(b < MAX_BINS);
-
- /* add predicted phase error to this bin */
-
- printf("L %d m %d f %4.f b %d\n", model->L, m, f, b);
-
- printf(" %d: %4.3f -> ", m, 20*log10(model->A[m]));
- model->A[m] = sqrt(av[b]/nav[b]);
- printf("%4.3f\n", 20*log10(model->A[m]));
- }
- }
- printf("\n");
-}
-
-/*---------------------------------------------------------------------------* \
-
- amp_experiment()
-
- Amplitude quantisation experiments.
-
-\*---------------------------------------------------------------------------*/
-
-void amp_experiment(struct AEXP *aexp, MODEL *model, char *arg) {
- int m,i;
-
- memcpy(&aexp->model_uq[2], model, sizeof(MODEL));
-
- if (strcmp(arg, "qn") == 0) {
- add_quant_noise(aexp, model, 1, model->L, 1);
- update_snr_calc(aexp, &aexp->model_uq[2], model);
- }
-
- /* print training samples that can be > train.txt for training VQ */
-
- if (strcmp(arg, "train") == 0)
- print_sparse_amp_error(aexp, model, 00.0);
-
- /* VQ of amplitudes, no interpolation (ie 10ms rate) */
-
- if (strcmp(arg, "vq") == 0) {
- sparse_vq_amp(aexp, model);
- vq_interp(aexp, model, 0);
- update_snr_calc(aexp, &aexp->model_uq[1], model);
- }
-
- /* VQ of amplitudes, interpolation (ie 20ms rate) */
-
- if (strcmp(arg, "vqi") == 0) {
- sparse_vq_amp(aexp, model);
- vq_interp(aexp, model, 1);
- update_snr_calc(aexp, &aexp->model_uq[1], model);
- }
-
- /* gain/shape VQ of amplitudes, 10ms rate (doesn't work that well) */
-
- if (strcmp(arg, "gsvq") == 0) {
- gain_shape_sparse_vq_amp(aexp, model);
- vq_interp(aexp, model, 0);
- update_snr_calc(aexp, &aexp->model_uq[1], model);
- }
-
- if (strcmp(arg, "smooth") == 0) {
- smooth_samples(aexp, model, 0);
- update_snr_calc(aexp, &aexp->model_uq[2], model);
- }
-
- if (strcmp(arg, "smoothtrain") == 0) {
- smooth_samples(aexp, model, 1);
- //update_snr_calc(aexp, &aexp->model_uq[2], model);
- }
-
- if (strcmp(arg, "smoothvq") == 0) {
- smooth_samples(aexp, model, 2);
- update_snr_calc(aexp, &aexp->model_uq[2], model);
- }
-
- if (strcmp(arg, "smoothamp") == 0) {
- smooth_amp(aexp, model);
- update_snr_calc(aexp, &aexp->model_uq[2], model);
- }
-
- /* update states */
-
- for(m=1; m<=model->L; m++)
- aexp->A_prev[m] = model->A[m];
- aexp->frames++;
- for(i=0; i<3; i++)
- aexp->model_uq[i] = aexp->model_uq[i+1];
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: ampexp.h
- AUTHOR......: David Rowe
- DATE CREATED: & August 2012
-
- Functions for experimenting with amplitude quantisation.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not,see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __AMPEX__
-#define __AMPEXP__
-
-#include "defines.h"
-
-struct AEXP;
-
-struct AEXP *amp_experiment_create();
-void amp_experiment_destroy(struct AEXP *aexp);
-void amp_experiment(struct AEXP *aexp, MODEL *model, char *arg);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: c2dec.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/8/2010
-
- Decodes a file of bits to a file of raw speech samples using codec2.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "codec2.h"
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <errno.h>
-
-#define NONE 0 /* no bit errors */
-#define UNIFORM 1 /* random bit errors */
-#define TWO_STATE 2 /* Two state error model */
-
-int main(int argc, char *argv[])
-{
- int mode;
- void *codec2;
- FILE *fin;
- FILE *fout;
- short *buf;
- unsigned char *bits;
- int nsam, nbit, nbyte, i, byte, frames, bit_errors, error_mode;
- int state, next_state;
- float ber, r, pstate0, pstate1;
-
- if (argc < 4) {
- printf("basic usage...............: c2dec 3200|2400|1400|1200 InputBitFile OutputRawSpeechFile\n");
- printf("uniform errors usage.......: c2dec 3200|2400|1400|1200 InputBitFile OutputRawSpeechFile uniformBER\n");
- printf("two state fading usage....: c2dec 3200|2400|1400|1200 InputBitFile OutputRawSpeechFile probGood probBad\n");
- printf("e.g c2dec 1400 hts1a.c2 hts1a_1400.raw\n");
- printf("e.g c2dec 1400 hts1a.c2 hts1a_1400.raw 0.9\n");
- printf("e.g c2dec 1400 hts1a.c2 hts1a_1400.raw 0.99 0.9\n");
- exit(1);
- }
-
- if (strcmp(argv[1],"3200") == 0)
- mode = CODEC2_MODE_3200;
- else if (strcmp(argv[1],"2400") == 0)
- mode = CODEC2_MODE_2400;
- else if (strcmp(argv[1],"1400") == 0)
- mode = CODEC2_MODE_1400;
- else if (strcmp(argv[1],"1200") == 0)
- mode = CODEC2_MODE_1200;
- else {
- fprintf(stderr, "Error in mode: %s. Must be 4800, 3200, 2400, 1400 or 1200\n", argv[1]);
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[2],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input bit file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[3], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[3],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output speech file: %s: %s.\n",
- argv[3], strerror(errno));
- exit(1);
- }
-
- error_mode = NONE;
- ber = 0.0;
- pstate0 = pstate1 = 0.0;
-
- if (argc == 5) {
- error_mode = UNIFORM;
- ber = atof(argv[4]);
- }
-
- if (argc == 6) {
- error_mode = TWO_STATE;
- pstate0 = atof(argv[4]);
- pstate1 = atof(argv[5]);
- state = 0;
- }
-
- codec2 = codec2_create(mode);
- nsam = codec2_samples_per_frame(codec2);
- nbit = codec2_bits_per_frame(codec2);
- buf = (short*)malloc(nsam*sizeof(short));
- nbyte = (nbit + 7) / 8;
- bits = (unsigned char*)malloc(nbyte*sizeof(char));
- frames = bit_errors = 0;
-
- while(fread(bits, sizeof(char), nbyte, fin) == (size_t)nbyte) {
- frames++;
- if (error_mode == UNIFORM) {
- for(i=0; i<nbit; i++) {
- r = (float)rand()/RAND_MAX;
- if (r < ber) {
- byte = i/8;
- //printf("nbyte %d nbit %d i %d byte %d\n", nbyte, nbit, i, byte);
- bits[byte] ^= 1 << (i - byte*8);
- bit_errors++;
- }
- }
- }
-
- if (error_mode == TWO_STATE) {
- next_state = state;
- switch(state) {
- case 0:
-
- /* clear channel state - no bit errors */
-
- r = (float)rand()/RAND_MAX;
- if (r > pstate0)
- next_state = 1;
- break;
-
- case 1:
-
- /* burst error state - 50% bit error rate */
-
- for(i=0; i<nbit; i++) {
- r = (float)rand()/RAND_MAX;
- if (r < 0.5) {
- byte = i/8;
- bits[byte] ^= 1 << (i - byte*8);
- bit_errors++;
- }
- }
-
- r = (float)rand()/RAND_MAX;
- if (r > pstate1)
- next_state = 0;
- break;
-
- }
-
- state = next_state;
- }
-
- codec2_decode(codec2, buf, bits);
- fwrite(buf, sizeof(short), nsam, fout);
- //if this is in a pipeline, we probably don't want the usual
- //buffering to occur
- if (fout == stdout) fflush(stdout);
- if (fin == stdin) fflush(stdin);
- }
-
- if (ber != 0.0)
- fprintf(stderr, "actual BER: %1.3f\n", (float)bit_errors/(frames*nbit));
-
- codec2_destroy(codec2);
-
- free(buf);
- free(bits);
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: c2demo.c
- AUTHOR......: David Rowe
- DATE CREATED: 15/11/2010
-
- Encodes and decodes a file of raw speech samples using Codec 2.
- Demonstrates use of Codec 2 function API.
-
- Note to convert a wave file to raw and vice-versa:
-
- $ sox file.wav -r 8000 -s -2 file.raw
- $ sox -r 8000 -s -2 file.raw file.wav
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "codec2.h"
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <errno.h>
-
-#define BITS_SIZE ((CODEC2_BITS_PER_FRAME + 7) / 8)
-
-int main(int argc, char *argv[])
-{
- struct CODEC2 *codec2;
- FILE *fin;
- FILE *fout;
- short *buf;
- unsigned char *bits;
- int nsam, nbit;
-
- if (argc != 3) {
- printf("usage: %s InputRawSpeechFile OutputRawSpeechFile\n", argv[0]);
- exit(1);
- }
-
- if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input speech file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- if ( (fout = fopen(argv[2],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output speech file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- /* Note only one set of Codec 2 states is required for an encoder
- and decoder pair. */
-
- codec2 = codec2_create(CODEC2_MODE_1400);
- nsam = codec2_samples_per_frame(codec2);
- buf = (short*)malloc(nsam*sizeof(short));
- nbit = codec2_bits_per_frame(codec2);
- bits = (unsigned char*)malloc(nbit*sizeof(char));
-
- while(fread(buf, sizeof(short), nsam, fin) == (size_t)nsam) {
- codec2_encode(codec2, bits, buf);
- codec2_decode(codec2, buf, bits);
- fwrite(buf, sizeof(short), nsam, fout);
- }
-
- free(buf);
- free(bits);
- codec2_destroy(codec2);
-
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: c2enc.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/8/2010
-
- Encodes a file of raw speech samples using codec2 and outputs a file
- of bits.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "codec2.h"
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <errno.h>
-
-int main(int argc, char *argv[])
-{
- int mode;
- void *codec2;
- FILE *fin;
- FILE *fout;
- short *buf;
- unsigned char *bits;
- int nsam, nbit, nbyte;
-
- if (argc != 4) {
- printf("usage: c2enc 3200|2400|1400|1200 InputRawspeechFile OutputBitFile\n");
- printf("e.g c2enc 1400 ../raw/hts1a.raw hts1a.c2\n");
- exit(1);
- }
-
- if (strcmp(argv[1],"3200") == 0)
- mode = CODEC2_MODE_3200;
- else if (strcmp(argv[1],"2400") == 0)
- mode = CODEC2_MODE_2400;
- else if (strcmp(argv[1],"1400") == 0)
- mode = CODEC2_MODE_1400;
- else if (strcmp(argv[1],"1200") == 0)
- mode = CODEC2_MODE_1200;
- else {
- fprintf(stderr, "Error in mode: %s. Must be 3200, 2400, 1400 or 1200\n", argv[1]);
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[2],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input speech file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[3], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[3],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output compressed bit file: %s: %s.\n",
- argv[3], strerror(errno));
- exit(1);
- }
-
- codec2 = codec2_create(mode);
- nsam = codec2_samples_per_frame(codec2);
- nbit = codec2_bits_per_frame(codec2);
- buf = (short*)malloc(nsam*sizeof(short));
- nbyte = (nbit + 7) / 8;
-
- bits = (unsigned char*)malloc(nbyte*sizeof(char));
-
- while(fread(buf, sizeof(short), nsam, fin) == (size_t)nsam) {
- codec2_encode(codec2, bits, buf);
- fwrite(bits, sizeof(char), nbyte, fout);
- // if this is in a pipeline, we probably don't want the usual
- // buffering to occur
- if (fout == stdout) fflush(stdout);
- if (fin == stdin) fflush(stdin);
- }
-
- codec2_destroy(codec2);
-
- free(buf);
- free(bits);
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: c2sim.c
- AUTHOR......: David Rowe
- DATE CREATED: 20/8/2010
-
- Codec2 simulation. Combines encoder and decoder and allows
- switching in and out various algorithms and quantisation steps. Used
- for algorithm development.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <errno.h>
-#include <math.h>
-#include <unistd.h>
-#include <getopt.h>
-
-#include "defines.h"
-#include "sine.h"
-#include "nlp.h"
-#include "dump.h"
-#include "lpc.h"
-#include "lsp.h"
-#include "quantise.h"
-#include "phase.h"
-#include "postfilter.h"
-#include "interp.h"
-#include "ampexp.h"
-#include "phaseexp.h"
-
-void synth_one_frame(kiss_fft_cfg fft_inv_cfg, short buf[], MODEL *model, float Sn_[], float Pn[], int prede, float *de_mem, float gain);
-void print_help(const struct option *long_options, int num_opts, char* argv[]);
-
-
-/*---------------------------------------------------------------------------*\
-
- MAIN
-
-\*---------------------------------------------------------------------------*/
-
-int main(int argc, char *argv[])
-{
- FILE *fout = NULL; /* output speech file */
- FILE *fin; /* input speech file */
- short buf[N]; /* input/output buffer */
- float Sn[M]; /* float input speech samples */
- float Sn_pre[M]; /* pre-emphasised input speech samples */
- COMP Sw[FFT_ENC]; /* DFT of Sn[] */
- kiss_fft_cfg fft_fwd_cfg;
- kiss_fft_cfg fft_inv_cfg;
- float w[M]; /* time domain hamming window */
- COMP W[FFT_ENC]; /* DFT of w[] */
- MODEL model;
- float Pn[2*N]; /* trapezoidal synthesis window */
- float Sn_[2*N]; /* synthesised speech */
- int i; /* loop variable */
- int frames;
- float prev_Wo, prev__Wo, uq_Wo, prev_uq_Wo;
- float pitch;
- int voiced1 = 0;
- char out_file[MAX_STR];
- char ampexp_arg[MAX_STR];
- char phaseexp_arg[MAX_STR];
- float snr;
- float sum_snr;
-
- int lpc_model = 0, order = LPC_ORD;
- int lsp = 0, lspd = 0, lspvq = 0;
- int lspres = 0;
- int lspdt = 0, lspdt_mode = LSPDT_ALL;
- int dt = 0, lspjvm = 0, lspanssi = 0, lspjnd = 0, lspmel = 0;
- int prede = 0;
- float pre_mem = 0.0, de_mem = 0.0;
- float ak[LPC_MAX];
- COMP Sw_[FFT_ENC];
- COMP Ew[FFT_ENC];
-
- int phase0 = 0;
- float ex_phase[MAX_AMP+1];
-
- int postfilt;
- float bg_est;
-
- int hand_voicing = 0, phaseexp = 0, ampexp = 0, hi = 0, simlpcpf = 0;
- int lpcpf = 0;
- FILE *fvoicing = 0;
-
- MODEL prev_model, interp_model;
- int decimate = 0;
- float lsps[LPC_MAX];
- float prev_lsps[LPC_MAX], prev_lsps_[LPC_MAX];
- float lsps__prev[LPC_MAX];
- float lsps__prev2[LPC_MAX];
- float e, prev_e;
- float ak_interp[LPC_MAX];
- int lsp_indexes[LPC_MAX];
- float lsps_[LPC_MAX];
- float Woe_[2];
-
- void *nlp_states;
- float hpf_states[2];
- int scalar_quant_Wo_e = 0;
- int vector_quant_Wo_e = 0;
- int dump_pitch_e = 0;
- FILE *fjvm = NULL;
- #ifdef DUMP
- int dump;
- #endif
- struct PEXP *pexp = NULL;
- struct AEXP *aexp = NULL;
- float gain = 1.0;
-
- char* opt_string = "ho:";
- struct option long_options[] = {
- { "lpc", required_argument, &lpc_model, 1 },
- { "lspjnd", no_argument, &lspjnd, 1 },
- { "lspmel", no_argument, &lspmel, 1 },
- { "lsp", no_argument, &lsp, 1 },
- { "lspd", no_argument, &lspd, 1 },
- { "lspvq", no_argument, &lspvq, 1 },
- { "lspres", no_argument, &lspres, 1 },
- { "lspdt", no_argument, &lspdt, 1 },
- { "lspdt_mode", required_argument, NULL, 0 },
- { "lspjvm", no_argument, &lspjvm, 1 },
- { "lspanssi", no_argument, &lspanssi, 1 },
- { "phase0", no_argument, &phase0, 1 },
- { "phaseexp", required_argument, &phaseexp, 1 },
- { "ampexp", required_argument, &exp, 1 },
- { "postfilter", no_argument, &postfilt, 1 },
- { "hand_voicing", required_argument, &hand_voicing, 1 },
- { "dec", no_argument, &decimate, 1 },
- { "dt", no_argument, &dt, 1 },
- { "hi", no_argument, &hi, 1 },
- { "simlpcpf", no_argument, &simlpcpf, 1 },
- { "lpcpf", no_argument, &lpcpf, 1 },
- { "prede", no_argument, &prede, 1 },
- { "dump_pitch_e", required_argument, &dump_pitch_e, 1 },
- { "sq_pitch_e", no_argument, &scalar_quant_Wo_e, 1 },
- { "vq_pitch_e", no_argument, &vector_quant_Wo_e, 1 },
- { "rate", required_argument, NULL, 0 },
- { "gain", required_argument, NULL, 0 },
- #ifdef DUMP
- { "dump", required_argument, &dump, 1 },
- #endif
- { "help", no_argument, NULL, 'h' },
- { NULL, no_argument, NULL, 0 }
- };
- int num_opts=sizeof(long_options)/sizeof(struct option);
-
- for(i=0; i<M; i++) {
- Sn[i] = 1.0;
- Sn_pre[i] = 1.0;
- }
- for(i=0; i<2*N; i++)
- Sn_[i] = 0;
-
- prev_uq_Wo = prev_Wo = prev__Wo = TWO_PI/P_MAX;
-
- prev_model.Wo = TWO_PI/P_MIN;
- prev_model.L = floor(PI/prev_model.Wo);
- for(i=1; i<=prev_model.L; i++) {
- prev_model.A[i] = 0.0;
- prev_model.phi[i] = 0.0;
- }
- for(i=1; i<=MAX_AMP; i++) {
- //ex_phase[i] = (PI/3)*(float)rand()/RAND_MAX;
- ex_phase[i] = 0.0;
- }
- for(i=0; i<LPC_ORD; i++) {
- lsps_[i] = prev_lsps[i] = prev_lsps_[i] = i*PI/(LPC_ORD+1);
- lsps__prev[i] = lsps__prev2[i] = i*PI/(LPC_ORD+1);
- }
- e = prev_e = 1;
- hpf_states[0] = hpf_states[1] = 0.0;
-
- nlp_states = nlp_create();
-
- if (argc < 2) {
- print_help(long_options, num_opts, argv);
- }
-
- /*----------------------------------------------------------------*\
-
- Interpret Command Line Arguments
-
- \*----------------------------------------------------------------*/
-
- while(1) {
- int option_index = 0;
- int opt = getopt_long(argc, argv, opt_string,
- long_options, &option_index);
- if (opt == -1)
- break;
- switch (opt) {
- case 0:
- if(strcmp(long_options[option_index].name, "lpc") == 0) {
- order = atoi(optarg);
- if((order < 4) || (order > 20)) {
- fprintf(stderr, "Error in LPC order: %s\n", optarg);
- exit(1);
- }
- #ifdef DUMP
- } else if(strcmp(long_options[option_index].name, "dump") == 0) {
- if (dump)
- dump_on(optarg);
- #endif
- } else if(strcmp(long_options[option_index].name, "lsp") == 0
- || strcmp(long_options[option_index].name, "lspd") == 0
- || strcmp(long_options[option_index].name, "lspvq") == 0) {
- assert(order == LPC_ORD);
- } else if(strcmp(long_options[option_index].name, "lspdt_mode") == 0) {
- if (strcmp(optarg,"all") == 0)
- lspdt_mode = LSPDT_ALL;
- else if (strcmp(optarg,"low") == 0)
- lspdt_mode = LSPDT_LOW;
- else if (strcmp(optarg,"high") == 0)
- lspdt_mode = LSPDT_HIGH;
- else {
- fprintf(stderr, "Error in lspdt_mode: %s\n", optarg);
- exit(1);
- }
- } else if(strcmp(long_options[option_index].name, "hand_voicing") == 0) {
- if ((fvoicing = fopen(optarg,"rt")) == NULL) {
- fprintf(stderr, "Error opening voicing file: %s: %s.\n",
- optarg, strerror(errno));
- exit(1);
- }
- } else if(strcmp(long_options[option_index].name, "dump_pitch_e") == 0) {
- if ((fjvm = fopen(optarg,"wt")) == NULL) {
- fprintf(stderr, "Error opening pitch & energy dump file: %s: %s.\n",
- optarg, strerror(errno));
- exit(1);
- }
- } else if(strcmp(long_options[option_index].name, "phaseexp") == 0) {
- strcpy(phaseexp_arg, optarg);
- } else if(strcmp(long_options[option_index].name, "ampexp") == 0) {
- strcpy(ampexp_arg, optarg);
- } else if(strcmp(long_options[option_index].name, "gain") == 0) {
- gain = atof(optarg);
- } else if(strcmp(long_options[option_index].name, "rate") == 0) {
- if(strcmp(optarg,"3200") == 0) {
- lpc_model = 1; order = 10;
- scalar_quant_Wo_e = 1;
- lspd = 1;
- phase0 = 1;
- postfilt = 1;
- decimate = 1;
- lpcpf = 1;
- } else if(strcmp(optarg,"2400") == 0) {
- lpc_model = 1; order = 10;
- vector_quant_Wo_e = 1;
- lsp = 1;
- phase0 = 1;
- postfilt = 1;
- decimate = 1;
- lpcpf = 1;
- } else if(strcmp(optarg,"1400") == 0) {
- lpc_model = 1; order = 10;
- vector_quant_Wo_e = 1;
- lsp = 1; lspdt = 1;
- phase0 = 1;
- postfilt = 1;
- decimate = 1;
- dt = 1;
- lpcpf = 1;
- } else if(strcmp(optarg,"1200") == 0) {
- lpc_model = 1; order = 10;
- scalar_quant_Wo_e = 1;
- lspjvm = 1; lspdt = 1;
- phase0 = 1;
- postfilt = 1;
- decimate = 1;
- dt = 1;
- lpcpf = 1;
- } else {
- fprintf(stderr, "Error: invalid output rate %s\n", optarg);
- exit(1);
- }
- }
- break;
-
- case 'h':
- print_help(long_options, num_opts, argv);
- break;
-
- case 'o':
- if (strcmp(optarg, "-") == 0) fout = stdout;
- else if ((fout = fopen(optarg,"wb")) == NULL) {
- fprintf(stderr, "Error opening output speech file: %s: %s.\n",
- optarg, strerror(errno));
- exit(1);
- }
- strcpy(out_file,optarg);
- break;
-
- default:
- /* This will never be reached */
- break;
- }
- }
-
- /* Input file */
-
- if ((fin = fopen(argv[optind],"rb")) == NULL) {
- fprintf(stderr, "Error opening input speech file: %s: %s.\n",
- argv[optind], strerror(errno));
- exit(1);
- }
-
- ex_phase[0] = 0;
- bg_est = 0.0;
- Woe_[0] = Woe_[1] = 1.0;
-
- /*
- printf("lspd: %d lspdt: %d lspdt_mode: %d phase0: %d postfilt: %d "
- "decimate: %d dt: %d\n",lspd,lspdt,lspdt_mode,phase0,postfilt,
- decimate,dt);
- */
-
- /* Initialise ------------------------------------------------------------*/
-
- fft_fwd_cfg = kiss_fft_alloc(FFT_ENC, 0, NULL, NULL); /* fwd FFT,used in several places */
- fft_inv_cfg = kiss_fft_alloc(FFT_DEC, 1, NULL, NULL); /* inverse FFT, used just for synth */
- make_analysis_window(fft_fwd_cfg, w, W);
- make_synthesis_window(Pn);
- quantise_init();
- if (phaseexp)
- pexp = phase_experiment_create();
- if (ampexp)
- aexp = amp_experiment_create();
-
- /*----------------------------------------------------------------*\
-
- Main Loop
-
- \*----------------------------------------------------------------*/
-
- frames = 0;
- sum_snr = 0;
- while(fread(buf,sizeof(short),N,fin)) {
- frames++;
- //printf("frame: %d ", frames);
-
- /* Read input speech */
-
- for(i=0; i<M-N; i++) {
- Sn[i] = Sn[i+N];
- Sn_pre[i] = Sn_pre[i+N];
- }
- for(i=0; i<N; i++)
- Sn[i+M-N] = buf[i];
-
- pre_emp(&Sn_pre[M-N], &Sn[M-N], &pre_mem, N);
-
-
- /*------------------------------------------------------------*\
-
- Estimate Sinusoidal Model Parameters
-
- \*------------------------------------------------------------*/
-
- nlp(nlp_states,Sn,N,M,P_MIN,P_MAX,&pitch,Sw,W,&prev_uq_Wo);
- model.Wo = TWO_PI/pitch;
-
- dft_speech(fft_fwd_cfg, Sw, Sn, w);
- two_stage_pitch_refinement(&model, Sw);
- estimate_amplitudes(&model, Sw, W);
- uq_Wo = model.Wo;
-
- #ifdef DUMP
- dump_Sn(Sn); dump_Sw(Sw); dump_model(&model);
- #endif
-
- if (ampexp)
- amp_experiment(aexp, &model, ampexp_arg);
-
- if (phaseexp) {
- #ifdef DUMP
- dump_phase(&model.phi[0], model.L);
- #endif
- phase_experiment(pexp, &model, phaseexp_arg);
- #ifdef DUMP
- dump_phase_(&model.phi[0], model.L);
- #endif
- }
-
- if (hi) {
- int m;
- for(m=1; m<model.L/2; m++)
- model.A[m] = 0.0;
- for(m=3*model.L/4; m<=model.L; m++)
- model.A[m] = 0.0;
- }
-
- /*------------------------------------------------------------*\
-
- Zero-phase modelling
-
- \*------------------------------------------------------------*/
-
- if (phase0) {
- float Wn[M]; /* windowed speech samples */
- float Rk[LPC_MAX+1]; /* autocorrelation coeffs */
- int ret;
-
- #ifdef DUMP
- dump_phase(&model.phi[0], model.L);
- #endif
-
- /* find aks here, these are overwritten if LPC modelling is enabled */
-
- if (prede) {
- for(i=0; i<M; i++)
- Wn[i] = Sn_pre[i]*w[i];
- }
- else {
-
- for(i=0; i<M; i++)
- Wn[i] = Sn[i]*w[i];
- }
- autocorrelate(Wn,Rk,M,order);
- levinson_durbin(Rk,ak,order);
-
- /* determine voicing */
-
- snr = est_voicing_mbe(&model, Sw, W, Sw_, Ew, prev_uq_Wo);
-
- if (dump_pitch_e)
- fprintf(fjvm, "%f %f %d ", model.Wo, snr, model.voiced);
-
- //printf("snr %3.2f v: %d Wo: %f prev_Wo: %f\n", snr, model.voiced,
- // model.Wo, prev_uq_Wo);
- #ifdef DUMP
- dump_Sw_(Sw_);
- dump_Ew(Ew);
- dump_snr(snr);
- #endif
-
- /* just to make sure we are not cheating - kill all phases */
-
- for(i=0; i<=MAX_AMP; i++)
- model.phi[i] = 0;
-
- if (hand_voicing) {
- ret = fscanf(fvoicing,"%d\n",&model.voiced);
- }
- }
-
- /*------------------------------------------------------------*\
-
- LPC model amplitudes and LSP quantisation
-
- \*------------------------------------------------------------*/
-
- if (lpc_model) {
-
- if (prede)
- e = speech_to_uq_lsps(lsps, ak, Sn_pre, w, order);
- else
- e = speech_to_uq_lsps(lsps, ak, Sn, w, order);
-
- #ifdef DUMP
- dump_ak(ak, LPC_ORD);
- #endif
-
- /* tracking down -ve energy values with BW expansion */
- /*
- if (e < 0.0) {
- int i;
- FILE*f=fopen("x.txt","wt");
- for(i=0; i<M; i++)
- fprintf(f,"%f\n", Sn[i]);
- fclose(f);
- printf("e = %f frames = %d\n", e, frames);
- for(i=0; i<order; i++)
- printf("%f ", ak[i]);
- exit(0);
- }
- */
-
- if (dump_pitch_e)
- fprintf(fjvm, "%f\n", e);
-
- #ifdef DUMP
- /* dump order is different if we are decimating */
- if (!decimate)
- dump_lsp(lsps);
- for(i=0; i<LPC_ORD; i++)
- prev_lsps[i] = lsps[i];
- #endif
-
- /* various LSP quantisation schemes */
-
- if (lsp) {
- encode_lsps_scalar(lsp_indexes, lsps, LPC_ORD);
- decode_lsps_scalar(lsps_, lsp_indexes, LPC_ORD);
- bw_expand_lsps(lsps_, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- if (lspd) {
- encode_lspds_scalar(lsp_indexes, lsps, LPC_ORD);
- decode_lspds_scalar(lsps_, lsp_indexes, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- if (lspvq) {
- lspvq_quantise(lsps, lsps_, LPC_ORD);
- bw_expand_lsps(lsps_, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- if (lspjvm) {
- /* Jean-Marc's multi-stage, split VQ */
- lspjvm_quantise(lsps, lsps_, LPC_ORD);
- {
- float lsps_bw[LPC_ORD];
- memcpy(lsps_bw, lsps_, sizeof(float)*LPC_ORD);
- bw_expand_lsps(lsps_bw, LPC_ORD);
- lsp_to_lpc(lsps_bw, ak, LPC_ORD);
- }
- }
-
- if (lspanssi) {
- /* multi-stage VQ from Anssi Ramo OH3GDD */
-
- lspanssi_quantise(lsps, lsps_, LPC_ORD, 5);
- bw_expand_lsps(lsps_, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- /* experimenting with non-linear LSP spacing to see if
- it's just noticable */
-
- if (lspjnd) {
- for(i=0; i<LPC_ORD; i++)
- lsps_[i] = lsps[i];
- locate_lsps_jnd_steps(lsps_, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- /* Another experiment with non-linear LSP spacing, this
- time using a scaled version of mel frequency axis
- warping. The scaling is such that the integer output
- can be directly sent over the channel.
- */
-
- if (lspmel) {
- float f, f_;
- int mel[LPC_ORD];
-
- for(i=0; i<LPC_ORD; i++) {
- f = (4000.0/PI)*lsps[i];
- mel[i] = floor(100.0*log10(1.0 + f/700.0) + 0.5);
- }
-
- for(i=1; i<LPC_ORD; i++) {
- if (mel[i] == mel[i-1])
- mel[i]++;
- }
-
- for(i=0; i<LPC_ORD; i++) {
- f_ = 700.0*( pow(10.0, (float)mel[i]/100.0) - 1.0);
- lsps_[i] = f_*(PI/4000.0);
- }
- for(i=5; i<10; i++) {
- lsps_[i] = lsps[i];
- }
-
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- /* we need lsp__prev[] for lspdt and decimate. If no
- other LSP quantisation is used we use original LSPs as
- there is no quantised version available. TODO: this is
- mess, we should have structures and standard
- nomenclature for previous frames values, lsp_[]
- shouldn't be overwritten as we may want to dump it for
- analysis. Re-design some time.
- */
-
- if (!lsp && !lspd && !lspvq && !lspres && !lspjvm && !lspanssi && !lspjnd && !lspmel)
- for(i=0; i<LPC_ORD; i++)
- lsps_[i] = lsps[i];
-
- /* Odd frames are generated by quantising the difference
- between the previous frames LSPs and this frames */
-
- if (lspdt && !decimate) {
- if (frames%2) {
- lspdt_quantise(lsps, lsps_, lsps__prev, lspdt_mode);
- bw_expand_lsps(lsps_, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
- for(i=0; i<LPC_ORD; i++)
- lsps__prev[i] = lsps_[i];
- }
-
- /*
- When decimation is enabled we only send LSPs to the
- decoder on odd frames. In the Delta-time LSPs case we
- encode every second odd frame (i.e. every 3rd frame out
- of 4) by quantising the difference between the 1st
- frames LSPs and the 3rd frames:
-
- 10ms, frame 1: discard (interpolate at decoder)
- 20ms, frame 2: send "full" LSP frame
- 30ms, frame 3: discard (interpolate at decoder)
- 40ms, frame 4: send LSPs differences between frame 4 and frame 2
- */
-
- if (lspdt && decimate) {
- /* print previous LSPs to make sure we are using the right set */
- if ((frames%4) == 0) {
- //printf(" lspdt ");
- //#define LSPDT
- #ifdef LSPDT
- lspdt_quantise(lsps, lsps_, lsps__prev2, lspdt_mode);
- #else
- for(i=0; i<LPC_ORD; i++)
- lsps_[i] = lsps__prev2[i];
- #endif
- bw_expand_lsps(lsps_, LPC_ORD);
- lsp_to_lpc(lsps_, ak, LPC_ORD);
- }
-
- for(i=0; i<LPC_ORD; i++) {
- lsps__prev2[i] = lsps__prev[i];
- lsps__prev[i] = lsps_[i];
- }
- }
- #ifdef DUMP
- /* if using decimated (20ms) frames we dump interp
- LSPs below */
- if (!decimate)
- dump_lsp_(lsps_);
- #endif
-
- if (scalar_quant_Wo_e) {
-
- e = decode_energy(encode_energy(e));
-
- if (!decimate) {
- /* we send params every 10ms, delta-time every 20ms */
- if (dt && (frames % 2))
- model.Wo = decode_Wo_dt(encode_Wo_dt(model.Wo, prev_Wo),prev_Wo);
- else
- model.Wo = decode_Wo(encode_Wo(model.Wo));
- }
-
- if (decimate) {
- /* we send params every 20ms */
- if (dt && ((frames % 4) == 0)) {
- /* delta-time every 40ms */
- model.Wo = decode_Wo_dt(encode_Wo_dt(model.Wo, prev__Wo),prev__Wo);
- }
- else
- model.Wo = decode_Wo(encode_Wo(model.Wo));
- }
-
- model.L = PI/model.Wo; /* if we quantise Wo re-compute L */
- }
-
- if (vector_quant_Wo_e) {
-
- /* JVM's experimental joint Wo & LPC energy quantiser */
-
- //printf("\nWo %f e %f\n", model.Wo, e);
- quantise_WoE(&model, &e, Woe_);
- //printf("Wo %f e %f\n", model.Wo, e);
-
- }
-
- aks_to_M2(fft_fwd_cfg, ak, order, &model, e, &snr, 1, simlpcpf, lpcpf, 1, LPCPF_BETA, LPCPF_GAMMA);
- apply_lpc_correction(&model);
-
- #ifdef DUMP
- dump_ak_(ak, LPC_ORD);
- #endif
-
- /* note SNR on interpolated frames can't be measured properly
- by comparing Am as L has changed. We can dump interp lsps
- and compare them,
- */
- #ifdef DUMP
- dump_lpc_snr(snr);
- #endif
- sum_snr += snr;
- #ifdef DUMP
- dump_quantised_model(&model);
- #endif
- }
-
- /*------------------------------------------------------------*\
-
- Decimation to 20ms frame rate
-
- \*------------------------------------------------------------*/
-
- if (decimate) {
- float lsps_interp[LPC_ORD];
-
- if (!phase0) {
- printf("needs --phase0 to resample phase for interpolated Wo\n");
- exit(0);
- }
- if (!lpc_model) {
- printf("needs --lpc 10 to resample amplitudes\n");
- exit(0);
- }
-
- /*
- Each 20ms we synthesise two 10ms frames:
-
- frame 1: discard except for voicing bit
- frame 2: interpolate frame 1 LSPs from frame 2 and frame 0
- synthesise frame 1 and frame 2 speech
- frame 3: discard except for voicing bit
- frame 4: interpolate frame 3 LSPs from frame 4 and frame 2
- synthesise frame 3 and frame 4 speech
- */
-
- if ((frames%2) == 0) {
- //printf("frame: %d\n", frames);
-
- /* decode interpolated frame */
-
- interp_model.voiced = voiced1;
-
- interpolate_lsp(fft_fwd_cfg, &interp_model, &prev_model, &model,
- prev_lsps_, prev_e, lsps_, e, ak_interp, lsps_interp);
- apply_lpc_correction(&interp_model);
-
- /* used to compare with c2enc/c2dec version
-
- printf(" Wo: %1.5f L: %d v1: %d prev_e: %f\n",
- interp_model.Wo, interp_model.L, interp_model.voiced, prev_e);
- printf(" lsps_interp: ");
- for(i=0; i<LPC_ORD; i++)
- printf("%5.3f ", lsps_interp[i]);
- printf("\n A..........: ");
- for(i=0; i<10; i++)
- printf("%5.3f ",interp_model.A[i]);
-
- printf("\n Wo: %1.5f L: %d e: %3.2f v2: %d\n",
- model.Wo, model.L, e, model.voiced);
- printf(" lsps_......: ");
- for(i=0; i<LPC_ORD; i++)
- printf("%5.3f ", lsps_[i]);
- printf("\n A..........: ");
- for(i=0; i<10; i++)
- printf("%5.3f ",model.A[i]);
- printf("\n");
- */
-
- #ifdef DUMP
- /* do dumping here so we get lsp dump file in correct order */
- dump_lsp(prev_lsps);
- dump_lsp(lsps_interp);
- dump_lsp(lsps);
- dump_lsp(lsps_);
- #endif
-
- if (phase0)
- phase_synth_zero_order(fft_fwd_cfg, &interp_model, ak_interp, ex_phase,
- order);
- if (postfilt)
- postfilter(&interp_model, &bg_est);
- synth_one_frame(fft_inv_cfg, buf, &interp_model, Sn_, Pn, prede, &de_mem, gain);
- //printf(" buf[0] %d\n", buf[0]);
- if (fout != NULL)
- fwrite(buf,sizeof(short),N,fout);
-
- /* decode this frame */
-
- if (phase0)
- phase_synth_zero_order(fft_fwd_cfg, &model, ak, ex_phase, order);
- if (postfilt)
- postfilter(&model, &bg_est);
- synth_one_frame(fft_inv_cfg, buf, &model, Sn_, Pn, prede, &de_mem, gain);
- //printf(" buf[0] %d\n", buf[0]);
- if (fout != NULL)
- fwrite(buf,sizeof(short),N,fout);
-
- /* update states for next time */
-
- prev_model = model;
- for(i=0; i<LPC_ORD; i++)
- prev_lsps_[i] = lsps_[i];
- prev_e = e;
- }
- else {
- voiced1 = model.voiced;
- }
- }
- else {
- /* no decimation - sythesise each 10ms frame immediately */
-
- if (phase0)
- phase_synth_zero_order(fft_fwd_cfg, &model, ak, ex_phase, order);
-
- if (postfilt)
- postfilter(&model, &bg_est);
- synth_one_frame(fft_inv_cfg, buf, &model, Sn_, Pn, prede, &de_mem, gain);
- if (fout != NULL) fwrite(buf,sizeof(short),N,fout);
- }
-
- prev__Wo = prev_Wo;
- prev_Wo = model.Wo;
- prev_uq_Wo = uq_Wo;
- //if (frames == 8) {
- // exit(0);
- //}
- }
-
- /*----------------------------------------------------------------*\
-
- End Main Loop
-
- \*----------------------------------------------------------------*/
-
- fclose(fin);
-
- if (fout != NULL)
- fclose(fout);
-
- if (lpc_model)
- printf("SNR av = %5.2f dB\n", sum_snr/frames);
-
- if (phaseexp)
- phase_experiment_destroy(pexp);
- if (ampexp)
- amp_experiment_destroy(aexp);
- #ifdef DUMP
- if (dump)
- dump_off();
- #endif
-
- if (hand_voicing)
- fclose(fvoicing);
-
- nlp_destroy(nlp_states);
-
- return 0;
-}
-
-void synth_one_frame(kiss_fft_cfg fft_inv_cfg, short buf[], MODEL *model, float Sn_[], float Pn[], int prede, float *de_mem, float gain)
-{
- int i;
-
- synthesise(fft_inv_cfg, Sn_, model, Pn, 1);
- if (prede)
- de_emp(Sn_, Sn_, de_mem, N);
-
- for(i=0; i<N; i++) {
- Sn_[i] *= gain;
- if (Sn_[i] > 32767.0)
- buf[i] = 32767;
- else if (Sn_[i] < -32767.0)
- buf[i] = -32767;
- else
- buf[i] = Sn_[i];
- }
-
-}
-
-void print_help(const struct option* long_options, int num_opts, char* argv[])
-{
- int i;
- char *option_parameters;
-
- fprintf(stderr, "\nCodec2 - low bit rate speech codec - Simulation Program\n"
- "\thttp://rowetel.com/codec2.html\n\n"
- "usage: %s [OPTIONS] <InputFile>\n\n"
- "Options:\n"
- "\t-o <OutputFile>\n", argv[0]);
- for(i=0; i<num_opts-1; i++) {
- if(long_options[i].has_arg == no_argument) {
- option_parameters="";
- } else if (strcmp("lpc", long_options[i].name) == 0) {
- option_parameters = " <Order>";
- } else if (strcmp("lspdt_mode", long_options[i].name) == 0) {
- option_parameters = " <all|high|low>";
- } else if (strcmp("hand_voicing", long_options[i].name) == 0) {
- option_parameters = " <VoicingFile>";
- } else if (strcmp("dump_pitch_e", long_options[i].name) == 0) {
- option_parameters = " <Dump File>";
- } else if (strcmp("rate", long_options[i].name) == 0) {
- option_parameters = " <4800|2400|1400|1200>";
- } else if (strcmp("dump", long_options[i].name) == 0) {
- option_parameters = " <DumpFilePrefix>";
- } else {
- option_parameters = " <UNDOCUMENTED parameter>";
- }
- fprintf(stderr, "\t--%s%s\n", long_options[i].name, option_parameters);
- }
- exit(1);
-}
+++ /dev/null
-#!/bin/sh
-# codeall.sh
-# David Rowe 24 sep 2009
-# Code all samples using various processing steps
-./code.sh hts1a
-./code.sh hts2a
-./code.sh mmt1
-./code.sh morig
-./code.sh forig
+++ /dev/null
-#ifndef CODEBOOK_H
-#define CODEBOOK_H
-
-extern float codebook_lsp1[];
-extern float codebook_lsp2[];
-extern float codebook_lsp3[];
-extern float codebook_lsp4[];
-extern float codebook_lsp5[];
-extern float codebook_lsp6[];
-extern float codebook_lsp7[];
-extern float codebook_lsp8[];
-extern float codebook_lsp9[];
-extern float codebook_lsp10[];
-
-#endif
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-250
-300
-350
-400
-450
-500
-550
-600
-650
-700
-750
-800
-850
-900
-950
-1000
-1050
-1100
-1150
-1200
-1250
-1300
-1350
-1400
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-250
-300
-350
-400
-450
-500
-550
-600
-650
-700
-750
-800
-850
-900
-950
-1000
-1050
-1100
-1150
-1200
-1250
-1300
-1350
-1400
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-250
-300
-350
-400
-450
-500
-550
-600
-650
-700
-750
-800
-850
-900
-950
-1000
-1050
-1100
-1150
-1200
-1250
-1300
-1350
-1400
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-1 32
-25
-50
-75
-100
-125
-150
-175
-200
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
-725
-750
-775
-800
-
-
+++ /dev/null
-2 256
-2.709998 12.018395
-0.046750 -2.738813
-0.120993 8.388947
--1.580275 -0.892307
-1.193065 -1.915609
-0.187101 -3.276788
-0.332251 -7.664550
--1.479436 31.246122
-1.527612 27.709463
--0.524379 5.250122
-0.553330 7.438797
--0.843451 -1.952987
-2.263885 8.610286
-0.143143 2.365493
-0.616506 1.284268
--1.711327 22.096672
-1.008128 17.396519
--0.106718 1.418905
--0.136246 14.273605
--1.709087 -20.531881
-1.657866 -3.391068
-0.138049 -4.957845
-0.536729 -1.943748
-0.196307 36.851948
-1.272479 22.556494
--0.670219 -1.906045
-0.382092 6.401132
--0.756911 -4.901017
-1.829313 4.613800
-0.318794 0.736830
-0.612815 -2.075045
--0.410151 24.787077
-1.776016 13.190924
-0.106457 -0.104492
-0.192206 10.183844
--1.824423 -7.715654
-0.931346 4.348355
-0.308813 -4.086001
-0.397143 -11.808859
--0.048715 41.227314
-0.877342 35.850311
--0.759794 0.476634
-0.978593 7.674673
--1.195056 3.038826
-2.639894 -3.411063
-0.191127 3.603507
-0.402932 1.084298
--2.152022 18.107616
-1.546802 8.322713
--0.143089 -4.075922
--0.150142 5.866741
--1.408444 -3.250696
-1.566148 -10.413164
-0.178171 -10.226697
-0.362164 -0.028556
--0.070125 24.390722
-0.594752 17.482765
--0.286980 -6.904069
-0.464818 10.205451
--1.006841 -14.357209
-2.329569 -3.691613
-0.335745 2.407139
-1.019658 -3.155647
--1.259455 7.991899
-2.383695 19.680567
--0.094947 -2.413742
-0.209330 6.664768
--2.221034 1.379860
-1.292387 2.046333
-0.243626 -0.890741
-0.428773 -7.193658
--1.113744 41.341354
-2.609799 31.140514
--0.446468 2.534188
-0.490104 4.627575
--1.117226 -3.241744
-1.791562 8.414926
-0.156012 0.183336
-0.532447 3.154545
--0.764484 18.513958
-0.952395 11.771298
--0.332567 0.346987
-0.202165 14.716752
--2.129240 -15.558954
-1.353583 -1.926790
--0.010963 -16.336386
-0.399053 -2.790569
-0.750657 31.148336
-0.655743 24.481859
--0.453210 -0.735879
-0.286900 6.546703
--0.715673 -12.357815
-1.548488 3.872171
-0.271874 0.802339
-0.502073 -4.854850
--0.497037 17.761904
-1.191161 13.954446
-0.015630 1.331566
-0.341867 8.935369
--2.316009 -5.395058
-0.758610 1.964505
-0.241320 -3.237686
-0.267151 -11.234388
--0.273126 32.624771
-1.753523 40.431995
--0.784011 3.045757
-0.705987 5.661178
--1.386400 1.353557
-2.376458 1.674851
-0.242973 4.732178
-0.491227 0.354061
--1.606762 8.658955
-1.167111 5.987103
--0.137601 -12.041750
--0.251375 10.397204
--1.431514 -8.904108
-0.988280 -13.208963
-0.261484 -6.354970
-0.395932 -0.702529
-0.283704 26.899563
-0.420959 15.441778
--0.355804 -13.727784
-0.527372 12.398515
--1.169559 -15.998457
-1.906688 -5.816055
-0.354492 3.851572
-0.825760 -4.162642
--0.490190 13.057229
-2.255773 13.526449
--0.004956 -3.237127
-0.026709 7.866448
--1.810372 -0.451183
-1.083827 -0.183620
-0.135836 -2.266582
-0.375812 -5.512248
--1.966443 38.682854
-1.977988 24.565481
--0.704656 6.358810
-0.480786 7.051749
--0.976417 -2.422727
-2.502148 6.759346
-0.083588 3.258795
-0.543629 0.910013
--1.231959 23.091507
-0.785492 14.807000
--0.213554 1.688002
-0.004748 18.171820
--1.547192 -16.116837
-1.501045 -3.281141
-0.080133 -4.634724
-0.476592 -2.180929
-0.442470 40.303989
-1.072766 27.592009
--0.594738 -4.166807
-0.422480 7.616091
--0.927521 -7.274406
-1.991623 1.296359
-0.291307 2.398781
-0.721081 -1.950625
--0.804256 24.929474
-1.648388 19.119692
-0.060852 -0.590639
-0.266085 9.103249
--1.957399 -2.884607
-1.116929 2.672397
-0.354580 -2.748541
-0.330733 -14.156131
--0.527851 39.575626
-0.991152 43.194984
--0.589619 1.269186
-0.787401 8.730713
--1.013800 1.025075
-2.825403 1.895381
-0.240890 2.745566
-0.427195 2.544456
--1.953109 12.243958
-1.448616 12.060747
--0.210492 -3.379058
--0.056713 10.204020
--1.652370 -5.102737
-1.294748 -12.270802
-0.111608 -8.675921
-0.326634 -1.167627
-0.021781 31.125782
-0.455335 21.468430
--0.375440 -3.371207
-0.393620 11.301987
--0.851456 -19.414892
-2.107030 -2.228865
-0.373233 1.924056
-0.884438 -1.720581
--0.975127 9.840128
-2.003303 17.395407
--0.036915 -1.111372
-0.148456 5.399970
--1.914412 4.773819
-1.447907 0.537122
-0.194979 -1.038179
-0.495771 -9.955025
--1.058987 32.947052
-2.011222 32.454418
--0.309650 4.719106
-0.436082 4.635524
--1.237105 -1.254284
-2.022740 9.428345
-0.190342 1.460767
-0.479017 2.484788
--1.078483 16.221748
-1.207642 9.654212
--0.258087 -1.672358
-0.071852 13.415978
--1.877228 -16.072031
-1.289568 -4.871185
-0.067713 -13.442700
-0.435551 -4.165503
-0.466140 30.589535
-0.904895 21.597990
--0.518369 -2.532048
-0.337363 5.637264
--0.554975 -17.400511
-1.691879 1.145742
-0.227934 0.889297
-0.587303 -5.729732
--0.262133 18.666620
-1.395048 17.002878
--0.019090 4.308379
-0.304235 12.669943
--2.074059 -6.460845
-0.920546 1.212957
-0.284927 -1.785466
-0.209724 -16.023964
--0.636067 31.576820
-1.349887 34.677502
--0.971625 5.300859
-0.590249 4.449709
--1.567867 3.602385
-2.145497 4.516663
-0.296022 4.120170
-0.445299 0.868772
--1.441931 14.128431
-1.355752 6.007401
--0.012814 -7.496573
--0.430000 8.500124
--1.204693 -7.113256
-1.101018 -6.836818
-0.196463 -6.234002
-0.436747 -1.129788
-0.141052 22.854876
-0.290821 18.811443
--0.529536 -7.732510
-0.634280 10.789847
--1.334721 -20.325773
-1.815645 -1.903316
-0.394778 3.797577
-0.732682 -8.183819
--0.741244 11.768337
+++ /dev/null
-1 16
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
+++ /dev/null
-1 4
-2900
-3100
-3300
-3500
-
+++ /dev/null
-1 16
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
+++ /dev/null
-1 16
-500
-550
-600
-650
-700
-750
-800
-850
-900
-950
-1000
-1050
-1100
-1150
-1200
-1250
+++ /dev/null
-1 16
-700
-800
-900
-1000
-1100
-1200
-1300
-1400
-1500
-1600
-1700
-1800
-1900
-2000
-2100
-2200
+++ /dev/null
-1 16
- 950
-1050
-1150
-1250
-1350
-1450
-1550
-1650
-1750
-1850
-1950
-2050
-2150
-2250
-2350
-2450
-
-
+++ /dev/null
-1 16
-1100
-1200
-1300
-1400
-1500
-1600
-1700
-1800
-1900
-2000
-2100
-2200
-2300
-2400
-2500
-2600
-
-
+++ /dev/null
-1 16
-1500
-1600
-1700
-1800
-1900
-2000
-2100
-2200
-2300
-2400
-2500
-2600
-2700
-2800
-2900
-3000
-
-
+++ /dev/null
-1 8
-2300
-2400
-2500
-2600
-2700
-2800
-2900
-3000
-
-
+++ /dev/null
-3 64
-2.048073 2.534502 2.645915
-2.019670 2.269744 2.605462
-1.961101 2.329646 2.562857
-1.968573 2.532712 2.616918
-2.183480 2.514381 2.629582
-2.259379 2.516615 2.620410
-2.172791 2.462460 2.567064
-2.097666 2.303933 2.421685
-2.052990 2.353242 2.546992
-2.043642 2.232362 2.499262
-2.106151 2.393131 2.488401
-2.099167 2.437862 2.558655
-2.013877 2.422875 2.530071
-2.033848 2.483776 2.584598
-2.114474 2.516856 2.602372
-2.229214 2.584056 2.678855
-2.131151 2.584299 2.674845
-1.472721 2.477091 2.630241
-2.010907 2.598415 2.682989
-2.353653 2.524066 2.619773
-2.419897 2.623938 2.699605
-2.319080 2.602148 2.689044
-1.860342 2.503881 2.616576
-1.910517 2.386693 2.610126
-1.748689 2.371809 2.496542
-1.618495 2.403425 2.554956
-1.844073 2.437026 2.533443
-1.924810 2.388543 2.502698
-1.937227 2.258363 2.501697
-1.687554 2.209123 2.545239
-1.851950 2.278628 2.565632
-1.868154 2.330150 2.444883
-1.874180 2.213118 2.351940
-1.757311 2.030626 2.433836
-1.650306 2.152371 2.243421
-1.612794 1.884686 2.339313
-1.745431 2.278895 2.389449
-1.590923 2.304155 2.408510
-1.475982 2.275548 2.509897
-1.508695 2.045463 2.455520
-1.872054 2.061777 2.246202
-1.983947 2.159155 2.445535
-1.745180 2.483765 2.593698
-1.900116 2.079600 2.407479
-1.841672 2.167042 2.486827
-1.932912 2.148464 2.569850
-2.134174 2.363673 2.584252
-2.106094 2.450645 2.638417
-1.954135 2.460313 2.666512
-1.907634 2.573801 2.674025
-1.625579 2.539569 2.656363
-1.785866 2.572616 2.676082
-1.798447 2.376454 2.624298
-2.020033 2.397244 2.619868
-1.946581 2.468791 2.564185
-2.008920 2.342400 2.469132
-1.983846 2.271044 2.395408
-1.988039 2.154150 2.317920
-2.077197 2.216622 2.389101
-2.117255 2.283907 2.512242
-2.177233 2.334622 2.458268
-2.214655 2.425510 2.620013
-2.199931 2.390272 2.520731
-2.271755 2.448682 2.552649
+++ /dev/null
-1 8
-2500
-2600
-2700
-2800
-2900
-3000
-3100
-3200
-
-
+++ /dev/null
-10 1024
-0.030214 0.087393 0.142625 0.204661 0.257804 -0.327911 -0.183571 -0.089661 -0.082036 0.025268
--0.033840 -0.025382 -0.057646 -0.130479 -0.015028 0.079375 0.023958 -0.042556 0.025167 0.021076
--0.073420 -0.085623 -0.081920 -0.021710 0.198196 0.213754 0.075391 0.063551 0.148094 0.083181
--0.041674 -0.061116 0.004116 0.233349 0.204616 0.256279 0.009337 0.091744 0.269872 0.132698
-0.052679 0.067955 -0.025147 -0.235718 -0.347647 -0.215019 -0.083526 -0.130404 -0.047058 -0.054917
-0.092221 0.063837 -0.170673 -0.451538 -0.521231 -0.416413 -0.184510 -0.192721 -0.288125 -0.164375
-0.006250 0.010339 0.023315 0.024258 0.142234 -0.023847 -0.063944 -0.036040 -0.024266 -0.035798
--0.020755 -0.016434 0.023770 0.104903 0.239031 0.135658 0.065827 0.089679 0.036949 0.038796
-0.001522 -0.000005 -0.007255 0.023717 0.061706 0.088603 0.132864 0.102913 0.070440 0.039429
-0.001258 0.000603 0.009813 -0.001694 0.005052 0.011061 0.010448 0.056755 0.026658 0.027529
-0.004858 0.005431 0.002243 0.029427 0.009784 -0.059830 -0.056032 -0.073592 -0.040853 -0.021115
--0.002325 -0.002455 -0.001604 -0.003935 0.006266 -0.017584 -0.006597 -0.081987 -0.029412 -0.020403
-0.003736 0.007595 0.003562 0.002215 0.038401 0.037702 0.057607 0.034182 0.061992 0.048736
-0.004115 0.003260 0.006737 0.006828 0.006008 0.017779 0.052389 0.095893 0.035851 0.020458
-0.004843 0.003379 -0.002271 0.004288 -0.016977 -0.071627 0.001830 -0.009209 -0.058428 -0.015245
-0.003678 0.005406 -0.012417 -0.039528 -0.027589 -0.087800 -0.041500 -0.100739 -0.090422 -0.098089
--0.006186 -0.001434 -0.000199 0.014062 -0.004642 -0.003832 -0.055350 -0.074491 -0.108642 -0.095712
--0.062269 -0.084747 -0.093203 0.112714 0.168813 0.101357 -0.009236 0.035940 0.011374 0.010907
--0.038490 -0.040302 -0.031450 0.072307 0.185540 0.151074 0.158257 0.172376 0.166965 0.130124
-0.024048 0.030137 0.067105 0.160669 0.280202 0.278831 -0.002242 -0.103298 -0.003234 -0.000831
-0.008185 -0.000241 -0.014130 -0.061306 -0.110704 -0.109917 -0.202806 -0.452824 -0.041963 -0.019083
--0.033700 -0.101513 -0.377325 -0.378713 -0.270962 -0.241062 0.104950 0.068237 -0.095025 -0.089500
--0.183828 -0.244672 -0.355586 -0.243172 -0.240034 -0.087034 0.217483 0.165276 -0.008586 0.016224
-0.060764 0.066368 0.055613 0.148443 0.151302 0.049670 -0.047198 -0.126028 0.102264 0.107377
-0.140469 0.157391 0.161672 0.291984 0.153641 0.206359 0.231297 -0.073781 -0.033312 0.032766
-0.037540 0.039307 0.047739 0.107267 0.132807 0.107693 0.042636 -0.020420 -0.007591 0.008364
-0.002125 0.003080 0.000635 0.016240 0.059410 -0.006820 -0.024315 0.045605 0.005290 0.013830
-0.001139 0.003902 -0.012139 -0.035295 -0.049090 -0.084221 -0.087992 0.088975 -0.009197 -0.025713
-0.001317 -0.001288 0.003646 -0.006079 -0.003929 -0.018558 -0.039808 -0.029046 -0.076413 -0.005992
--0.001049 -0.001621 0.017015 -0.009393 -0.008427 0.037335 0.028549 0.022359 0.064850 0.021301
-0.002963 -0.003009 0.009769 0.088745 0.016440 0.046255 0.050722 0.016491 0.102227 0.050278
-0.000385 0.004489 -0.005224 0.040397 0.015902 -0.044661 -0.134052 -0.164920 -0.013437 0.018856
-0.000290 -0.014145 -0.104000 -0.098790 -0.086725 -0.130471 -0.147043 -0.075812 -0.148688 -0.129942
-0.003604 -0.001264 -0.025302 -0.034198 -0.106991 0.017613 0.131491 0.142840 -0.079925 -0.049736
-0.017871 0.046436 0.144657 0.014979 0.031321 0.118093 0.144907 0.171921 -0.007429 0.020121
-0.142113 0.303403 0.318919 -0.068887 0.044887 0.169177 0.174048 0.135839 0.202516 0.173113
--0.029056 -0.028800 0.024667 0.151956 0.143322 0.182400 0.182489 0.061789 0.433122 0.337578
--0.028250 -0.053393 -0.035536 0.350750 0.353500 -0.226571 -0.259464 0.038214 -0.015607 -0.023786
-0.046375 0.008135 -0.162187 -0.193417 0.024875 -0.111500 -0.262979 -0.088667 -0.355750 -0.246906
--0.009274 0.006357 0.017345 -0.232327 -0.217667 -0.057851 -0.091655 -0.007185 -0.045440 -0.041536
--0.012885 -0.008218 -0.020385 -0.037269 -0.156679 0.011269 0.055346 -0.146987 0.100295 0.142756
-0.005348 -0.001366 -0.027875 0.004330 -0.023464 -0.004911 -0.020777 -0.216223 -0.080589 -0.144991
-0.009843 0.011329 0.028114 -0.003471 0.016571 0.057543 0.073629 -0.089014 0.018186 -0.106900
--0.001929 -0.013671 0.019657 0.021129 0.096800 0.106571 0.054843 0.074429 0.010871 0.280614
--0.014482 -0.008564 -0.019482 -0.051300 -0.020509 -0.035591 0.020536 0.039991 0.078036 0.278591
-0.000642 -0.000081 -0.000885 -0.022764 -0.011689 0.014764 -0.015169 -0.002595 0.001311 -0.189811
-0.002994 0.009073 0.002983 -0.006096 -0.004567 -0.008534 -0.067904 -0.029798 -0.104129 -0.246034
-0.032685 0.027630 0.024074 0.079759 0.095704 -0.028565 0.018815 0.037528 -0.002676 0.038213
-0.009344 0.011533 0.016039 0.052300 0.033783 0.042361 0.019544 0.017133 0.100200 0.159617
--0.001124 0.002658 0.005416 0.011698 0.014386 -0.031792 -0.046644 -0.050950 0.071530 0.002807
-0.008698 0.022123 -0.003025 0.021395 -0.003148 -0.121864 -0.001346 -0.023710 0.186920 0.047278
--0.006202 -0.000833 -0.039193 -0.118149 -0.047640 -0.050868 0.046018 0.032368 0.254702 0.106246
--0.027820 -0.044190 0.017040 -0.094260 -0.087840 0.088060 0.009070 -0.032400 -0.270150 -0.055890
--0.011581 -0.025468 0.025290 -0.017984 0.153194 0.222645 0.073710 0.045758 -0.472597 -0.306532
--0.014798 -0.020808 -0.008481 0.007394 -0.031663 0.104115 0.064538 0.072702 -0.218635 -0.153481
-0.027705 0.091167 0.045423 0.146718 0.020526 -0.143910 0.073154 0.128346 0.529487 0.308731
-0.030128 0.035233 -0.070384 -0.018698 -0.075535 -0.220372 -0.079291 -0.111209 0.256581 0.101105
--0.004150 -0.008144 -0.006750 0.004239 0.028372 -0.001983 -0.040928 -0.019661 -0.338700 -0.169967
--0.004707 -0.006595 0.004500 0.026767 -0.029819 0.169034 -0.002560 0.033819 -0.088190 -0.050612
--0.006173 0.002647 -0.001513 -0.015320 0.010533 0.053747 0.082887 0.059393 0.183313 0.057387
--0.000616 -0.004636 0.006606 0.024414 0.051409 0.021773 0.060692 -0.006798 -0.043394 -0.038828
--0.008696 -0.000618 0.042500 0.037216 0.071137 -0.060206 0.015157 -0.015108 -0.045157 -0.016010
-0.007144 0.005253 0.010336 0.010548 0.009610 -0.013199 -0.071445 0.067541 -0.007733 -0.059884
-0.000036 0.002778 -0.003443 -0.009706 -0.047371 -0.014098 -0.101768 -0.080778 -0.068814 -0.051469
-0.003981 0.007944 0.004537 -0.030662 -0.110694 -0.136056 -0.114219 -0.178281 -0.146781 -0.054756
-0.018125 0.014090 -0.006389 0.069208 -0.085715 -0.056646 0.058569 0.044424 0.070618 0.039938
-0.003460 0.000508 0.014437 0.031119 -0.038722 0.008254 0.073587 0.122825 0.189159 0.163968
--0.008440 -0.013664 -0.024448 -0.034284 -0.116739 0.058746 -0.085433 -0.144358 -0.008843 0.005045
--0.014613 -0.019969 -0.015219 -0.052462 0.007394 0.052406 -0.003019 0.003319 -0.151588 -0.158712
--0.005918 -0.001090 0.014866 -0.032642 0.009075 -0.008806 0.190575 0.273537 -0.036231 -0.026127
-0.012026 0.021332 0.014184 0.012795 0.060216 0.034547 0.069368 0.168979 0.131626 0.105816
--0.003224 0.001730 -0.013697 -0.012401 0.010480 0.043882 -0.202132 -0.213039 -0.017875 -0.005474
-0.002079 -0.002329 -0.014679 0.042800 -0.053314 -0.068564 -0.097750 -0.222214 -0.053271 -0.046371
-0.002171 0.004986 0.011274 0.009952 0.005562 -0.001692 0.073185 -0.143664 0.102568 0.088301
--0.012564 0.010821 -0.012821 -0.029090 0.047154 0.091513 -0.049474 0.180192 0.086333 0.017423
-0.002909 -0.028327 -0.148755 -0.080791 -0.206173 -0.356100 -0.022609 -0.061236 -0.157227 -0.113336
--0.079046 -0.172583 -0.199454 -0.048157 -0.225296 -0.309278 -0.112435 -0.235102 -0.046222 0.006269
--0.045984 0.018047 0.164258 0.202680 0.263172 0.566937 0.206742 0.329023 0.292391 0.123086
-0.019192 0.112609 0.335853 0.302641 0.400333 0.472173 0.329000 0.377808 0.018436 0.015635
-0.026673 0.004462 -0.162096 0.037442 0.079019 -0.215942 -0.060442 -0.189962 -0.162654 -0.052058
-0.022508 -0.090762 -0.239238 -0.171444 -0.440913 -0.380135 -0.159310 -0.258468 -0.129913 -0.088238
--0.028069 -0.014437 -0.010850 -0.050656 -0.285669 -0.268906 -0.101344 -0.029094 -0.023888 -0.023181
-0.004862 0.006414 0.001345 -0.063621 -0.052741 -0.180931 -0.238224 0.173172 -0.092862 -0.104207
-0.004697 0.026947 0.086934 0.072974 0.262303 0.283618 -0.096250 0.027066 0.188803 0.149026
--0.030421 -0.042868 -0.039697 -0.017447 0.021250 0.061789 0.107342 -0.302829 0.010276 0.037605
--0.002333 0.000385 -0.012577 -0.066256 -0.013564 -0.019269 -0.036936 -0.418756 -0.123474 -0.102654
-0.008575 0.004952 0.005500 0.052904 0.022890 -0.023158 0.154486 0.176897 -0.002651 0.045822
--0.010061 -0.004970 0.027457 0.013524 0.049537 0.110189 0.103811 0.291598 0.041030 0.020659
--0.010786 0.000000 -0.026364 -0.123214 -0.022757 -0.047179 -0.121571 -0.019329 -0.032657 0.011214
--0.011300 -0.010793 -0.028993 -0.133667 -0.052173 -0.109933 -0.172947 -0.209893 -0.044780 0.033867
--0.000296 0.002438 0.000217 0.048783 -0.025752 -0.011934 0.048301 0.018323 -0.006841 -0.006119
--0.019991 -0.026871 0.043069 0.164517 0.080086 0.197466 0.212026 0.240767 0.076388 -0.010440
-0.021657 0.030662 0.048081 0.141298 0.130939 0.132485 0.191273 0.032157 -0.015273 -0.007192
-0.007325 0.011669 -0.012494 -0.100969 -0.153569 -0.106119 -0.121781 -0.157719 0.033100 0.027981
--0.020244 -0.020987 0.002609 -0.130609 -0.150897 -0.197853 -0.238596 -0.012750 -0.034442 -0.025506
-0.003443 0.006460 0.003278 0.014966 0.037915 0.007864 -0.006432 0.067182 -0.049813 -0.092665
--0.007296 -0.004959 0.010561 0.022714 0.059469 0.054949 0.248225 -0.023347 -0.184122 -0.075653
--0.076207 -0.095685 -0.078185 0.012696 0.049402 0.032489 0.050826 0.081348 0.123554 0.104446
-0.033461 0.077447 0.156368 0.110447 0.152500 0.047816 -0.081474 0.154829 0.174026 0.149316
--0.015549 0.010430 0.074415 0.118507 0.195859 0.269563 -0.010204 0.049169 0.015049 -0.026859
-0.040961 0.062588 0.039324 0.109118 0.247696 0.324627 0.319804 -0.049529 -0.021539 -0.003265
-0.043783 0.026833 0.085183 0.210517 -0.340767 -0.259850 0.112733 0.034617 0.036000 0.067850
-0.083529 0.079779 0.005183 -0.208740 -0.354154 -0.443635 -0.417827 0.039221 -0.039269 -0.078413
-0.021417 0.026286 0.001595 -0.051750 -0.054988 -0.357821 -0.359548 -0.067250 -0.058357 -0.043310
--0.018575 -0.013198 0.025019 0.058547 0.056660 0.223057 -0.061415 0.017830 0.007094 -0.060821
-0.001306 -0.001291 0.017164 0.053478 -0.007545 0.118478 0.178015 0.100440 -0.004933 -0.053530
--0.001737 -0.002491 0.000614 0.058211 0.043728 0.023728 0.111026 0.098482 -0.078500 -0.067474
-0.004230 0.005440 0.003488 0.008855 -0.008145 -0.014681 -0.009133 0.045972 0.163347 0.068315
--0.010959 -0.005849 -0.007315 -0.014390 0.006158 0.090856 -0.012445 0.022890 0.158986 0.056925
-0.000749 -0.001213 -0.006018 -0.004422 -0.009865 -0.007207 -0.017749 -0.000249 -0.092991 -0.109251
-0.005029 -0.005757 -0.004360 -0.009669 -0.008691 -0.071544 -0.097934 -0.110368 -0.185699 0.011404
--0.007715 0.003778 -0.031069 -0.036444 -0.025951 -0.044931 -0.047000 -0.135299 0.146458 0.088236
-0.001761 0.000421 0.007793 0.012389 0.010661 0.025464 0.009525 0.012075 0.122568 0.020621
-0.001769 0.004204 0.008458 0.013602 -0.004023 0.019630 0.023745 0.041588 -0.088407 -0.073875
-0.004633 0.004633 0.020223 -0.006181 0.021078 0.115759 0.078301 0.039090 -0.092398 -0.076898
--0.002416 -0.001845 0.000173 -0.038956 0.011274 0.029049 0.065712 0.009987 0.029796 0.005615
--0.002492 -0.004292 -0.031175 -0.060358 -0.026058 -0.109742 -0.029850 -0.074383 -0.080908 0.042942
--0.002215 -0.002694 -0.002368 0.008698 -0.017256 -0.012021 -0.009492 0.009773 -0.044764 0.018318
--0.023070 -0.002325 -0.026219 0.008693 -0.018991 0.021789 0.004035 0.107798 0.332026 0.079456
-0.000155 -0.001041 -0.008629 -0.012809 -0.005175 0.001830 -0.000088 0.085892 0.085634 0.039732
--0.008221 -0.024926 -0.014309 0.013941 -0.022912 -0.097382 -0.000265 -0.141250 -0.313073 0.018647
-0.002872 -0.003733 -0.009488 0.016860 -0.040814 -0.091547 0.116430 -0.175616 -0.024884 0.040326
--0.008020 0.021970 0.088080 0.111170 0.057580 0.171240 0.092760 0.302830 0.373290 0.143470
--0.016063 -0.022650 0.036400 -0.175538 -0.357975 -0.198500 -0.256112 -0.126062 0.144225 0.100450
-0.075009 0.047603 -0.037655 -0.129095 -0.251948 -0.360069 -0.312207 -0.445293 -0.496000 -0.212534
--0.032464 -0.028929 -0.006339 0.207125 0.557589 0.518964 0.543321 0.249214 -0.000589 0.026018
--0.054765 0.032643 0.199878 0.324673 0.502725 0.640980 0.604908 0.581459 0.316602 0.184429
-0.115611 0.119583 -0.062069 -0.135861 -0.395542 -0.371653 -0.019708 -0.018028 0.313139 0.152028
-0.054066 0.018539 -0.058382 -0.216724 -0.636342 -0.630671 -0.271105 -0.194711 0.044303 0.016355
-0.060100 0.045158 0.113933 0.056442 0.023808 -0.021950 -0.399325 -0.126858 -0.111158 -0.110000
-0.025462 0.025667 0.060218 0.078923 0.231410 0.120885 -0.330885 -0.370833 -0.307731 -0.152218
--0.010160 -0.013991 -0.024783 -0.012509 0.003821 0.062425 0.184236 -0.088340 -0.045774 -0.025868
--0.027839 -0.005367 0.082450 0.116321 0.161436 0.232105 0.309069 0.377041 0.202248 0.091963
--0.028529 -0.008750 -0.003904 -0.076702 0.130596 0.250337 0.239163 0.413154 0.135740 0.016308
--0.032553 -0.029079 0.012000 -0.010605 0.068842 0.005237 -0.262474 0.205684 -0.058632 -0.013079
-0.038676 0.039985 0.026735 0.179235 0.105368 -0.038294 -0.291868 -0.364471 0.002426 0.050265
-0.082714 0.051690 0.067024 0.003524 -0.244452 0.071381 0.217595 -0.169405 0.056619 0.101190
--0.014476 -0.009119 -0.074310 -0.216810 -0.273786 -0.212286 0.358714 0.308857 -0.015429 0.012619
-0.055256 0.077333 0.025308 0.062231 0.184090 -0.211680 0.056308 0.154897 0.052615 0.041731
-0.016750 -0.006848 -0.039634 0.201089 0.167759 0.022482 0.016536 0.019232 0.241009 0.112500
--0.031711 -0.053316 -0.067474 -0.301500 -0.215763 0.395053 0.006316 -0.019132 -0.259737 -0.234632
--0.033432 -0.059386 0.019295 -0.121341 -0.094205 0.239114 -0.043330 -0.044818 -0.353034 -0.236864
-0.089880 0.101220 0.058980 0.407420 0.200060 -0.299180 -0.042020 -0.004800 0.348860 0.226780
-0.063535 0.105081 -0.007512 0.121267 0.036744 -0.301674 0.020547 0.087756 0.279884 0.140686
--0.036721 -0.075988 -0.116081 -0.208663 -0.207733 0.048419 0.044802 -0.027035 -0.141651 -0.105349
--0.028942 -0.024733 -0.114267 -0.168860 0.001767 0.024430 -0.182547 0.006686 0.003116 0.012442
--0.010038 -0.007665 -0.017722 -0.016968 -0.001627 -0.027013 -0.216025 -0.041468 0.037778 0.051987
-0.002445 0.000783 0.004083 0.035189 0.009283 -0.014559 0.097984 -0.008587 0.066528 0.081354
--0.001479 0.004418 0.038329 0.046507 0.011096 0.003842 0.252521 0.015459 0.023130 0.096048
-0.000695 -0.002314 0.000295 -0.005229 -0.000771 0.037271 -0.112343 0.036733 -0.082638 -0.066776
-0.005429 -0.000423 -0.015468 0.016917 0.006423 0.007667 -0.216154 -0.041026 -0.113365 -0.150474
-0.002106 0.000589 0.001199 0.014114 -0.001144 0.009093 -0.022373 -0.010568 -0.001915 -0.092614
--0.007700 -0.009280 0.004070 0.005150 0.014830 0.006340 0.147690 0.018210 0.104050 0.000040
--0.018965 -0.031535 -0.027744 -0.002988 -0.064337 -0.003465 0.084384 0.036512 0.074326 -0.066721
--0.001037 0.001463 -0.032152 -0.024066 -0.009885 -0.038361 -0.027086 -0.071250 0.012451 -0.019582
-0.000221 -0.003004 0.008726 -0.003018 0.005336 0.011566 0.030712 0.007863 0.038854 0.107819
--0.001273 -0.002756 0.004256 0.000318 -0.005261 0.040545 0.000835 0.036057 -0.047239 0.077119
--0.001737 -0.003442 -0.007500 -0.003781 -0.017844 -0.035866 -0.074321 -0.000629 -0.064170 -0.047701
--0.000865 -0.001496 0.000354 -0.007527 0.041396 -0.031923 -0.006762 -0.033335 -0.018812 -0.025296
-0.004362 0.001993 0.008519 0.001571 0.017772 -0.017836 0.074396 0.044884 0.014146 0.013418
-0.005041 0.003486 0.002358 0.030174 0.004454 -0.017583 0.066216 0.011294 -0.018147 0.049486
-0.098609 0.056130 -0.083848 0.065065 0.035913 -0.070478 0.000326 -0.083761 0.033696 0.087087
--0.006835 -0.006643 -0.002096 0.013983 -0.004148 0.007100 -0.049617 -0.069874 0.144304 0.050204
--0.036358 -0.027594 0.042113 0.034425 0.020057 0.114915 -0.039651 -0.027500 0.117424 0.033953
--0.036453 -0.048538 -0.012575 -0.072726 0.092472 0.117302 0.013311 -0.088906 -0.205519 -0.027972
-0.080906 0.049094 -0.253469 -0.093781 0.050094 0.012375 0.052594 -0.018031 -0.266562 -0.083219
-0.037921 0.053237 0.031947 0.055237 -0.065842 -0.081947 -0.089368 0.034605 0.020500 -0.208053
-0.051783 0.166457 0.347870 0.082783 -0.110196 -0.038891 0.095239 0.377783 0.013913 -0.021783
--0.000538 0.005625 0.035154 -0.008760 0.017404 0.027721 0.112288 0.256471 0.104548 0.212971
--0.026529 -0.052029 -0.034824 0.046559 0.129794 0.208882 -0.038324 -0.364971 0.089353 0.164235
--0.088931 -0.130208 -0.082486 -0.052222 -0.003667 0.174014 -0.141236 -0.257597 -0.115292 -0.141833
-0.002280 0.010667 0.014080 -0.006000 -0.023200 -0.172953 0.117553 0.058087 -0.019380 -0.005773
-0.101485 0.125258 0.048667 0.014303 -0.150364 -0.389121 -0.019788 0.181545 0.030909 0.035652
--0.021477 -0.026577 -0.008262 -0.001515 0.036408 -0.184946 -0.200123 -0.032215 -0.062277 -0.037985
--0.030958 -0.037604 -0.002083 -0.009073 -0.000729 0.256958 0.014604 -0.118438 -0.055438 -0.000802
--0.027083 -0.051708 -0.031653 -0.091722 -0.062014 0.324194 0.196431 0.120806 0.034556 -0.031875
-0.009636 0.010093 0.017856 -0.005153 0.040102 0.040983 -0.066271 -0.099381 0.058881 0.007881
-0.132500 0.150554 0.177839 0.235321 -0.002214 -0.252696 -0.331750 -0.136554 0.123411 0.067375
-0.023070 0.035640 0.053767 0.124349 0.040721 0.026500 0.116186 0.271256 0.194547 0.035500
-0.001511 0.030878 0.008922 -0.003600 -0.014778 -0.022233 0.320467 0.462356 0.113289 0.039033
--0.002833 0.002567 -0.035367 -0.121433 0.120900 -0.298700 -0.125667 0.031267 0.204133 0.227500
--0.087482 -0.144643 -0.111518 -0.391786 -0.326607 -0.065250 -0.175911 -0.304214 -0.538625 -0.389071
--0.028617 -0.069150 -0.040133 -0.101550 -0.441367 0.076333 -0.076517 -0.169083 -0.356467 -0.191600
--0.037909 -0.026932 -0.005739 -0.064750 0.012568 0.065080 0.130000 0.049648 0.036273 0.180920
-0.020429 0.047571 0.156480 0.491847 0.329459 0.164786 0.201163 0.245724 0.411480 0.191173
-0.046603 0.153465 0.329621 0.480948 0.254552 -0.051948 0.006879 0.124345 0.195052 0.064207
-0.064943 0.049343 -0.109214 -0.169521 -0.139050 -0.326821 -0.120729 -0.222421 -0.199921 -0.054193
-0.097793 0.029086 -0.172138 -0.229103 -0.186569 -0.017190 -0.131138 -0.189759 -0.084310 -0.040586
--0.028429 -0.033558 -0.010962 -0.037135 0.003635 0.259936 0.076269 0.121449 0.158077 0.029449
--0.002591 -0.002159 0.034122 0.053927 0.035512 0.072043 0.003890 0.079787 -0.038762 -0.037805
--0.007474 -0.005542 -0.016305 -0.025963 -0.010647 -0.028416 -0.005437 -0.082868 -0.089074 -0.016589
-0.007697 -0.002359 -0.008169 0.015887 0.022697 0.031535 0.046972 -0.041028 -0.012831 0.021176
--0.003731 0.003090 0.059583 0.103763 0.022141 0.115519 0.029179 0.083558 0.049718 0.018327
--0.008056 0.004766 -0.027331 -0.029758 -0.110411 -0.045073 -0.045476 -0.005403 -0.023113 -0.110976
--0.059971 -0.081745 -0.041696 -0.042245 -0.137373 -0.157725 -0.148039 -0.236588 -0.112608 -0.111529
--0.019759 -0.023935 -0.006306 0.012102 -0.020259 0.011241 0.091259 -0.050176 -0.004454 0.092991
--0.001988 0.003628 0.075360 0.059779 0.041337 0.052640 0.055174 0.421140 0.029523 0.020570
--0.005745 -0.007896 0.008038 0.007830 0.020094 0.003302 -0.112208 0.117764 -0.012943 0.025623
--0.002147 -0.003566 -0.004250 0.013301 -0.034485 -0.005022 -0.046176 -0.214603 0.102353 0.015221
-0.004726 0.003258 0.006605 0.011677 0.020250 0.045435 0.033323 -0.045040 0.079436 0.047145
--0.003679 -0.016330 -0.003062 0.005607 -0.008018 0.005491 -0.074223 -0.197536 -0.323250 -0.114929
--0.008114 -0.048614 -0.099018 -0.037044 -0.049912 -0.124193 -0.164088 -0.363325 -0.310351 -0.216658
--0.019828 -0.024500 -0.046828 -0.065414 -0.234859 -0.152266 -0.080797 -0.063445 0.169914 0.076594
--0.051619 -0.044857 -0.015643 -0.088929 -0.162429 0.028500 0.197690 0.432952 0.321357 0.112452
--0.021411 -0.009625 0.035554 0.044625 0.280000 0.367500 0.594429 0.622232 0.012473 -0.010839
-0.065200 0.025433 -0.185200 0.034333 0.172600 0.112033 0.257900 -0.247667 -0.057967 -0.027133
-0.052604 -0.015573 -0.146427 -0.089854 -0.148490 -0.284812 -0.383000 -0.623250 -0.117167 -0.030635
-0.010178 0.001711 0.074167 0.051633 -0.081333 -0.014689 -0.139767 0.036767 0.011200 -0.029811
--0.011123 -0.013965 0.041360 -0.006649 0.107246 0.104482 0.001956 0.101281 0.048351 0.086842
--0.008518 -0.006877 -0.014095 -0.045659 -0.011573 -0.014714 0.010405 -0.025550 -0.044900 -0.090964
--0.006465 -0.003227 -0.017219 -0.067123 -0.000727 -0.022958 -0.029050 -0.029381 -0.045496 -0.028827
-0.002947 0.000654 0.007673 0.014638 0.011365 -0.007292 0.023487 -0.006947 0.063934 0.020057
-0.010012 0.006801 0.018313 0.044687 0.014964 0.002892 0.129042 0.031343 -0.116873 -0.021072
-0.003000 -0.006600 0.001167 0.005844 -0.004389 -0.007944 0.020622 0.008278 -0.087733 0.134178
-0.021690 0.021905 -0.002034 -0.020750 -0.060767 -0.101422 -0.137379 0.037319 0.169293 0.090086
-0.010665 0.024394 0.007065 -0.032147 -0.152188 -0.073382 -0.073171 -0.038235 0.107412 -0.021276
--0.010141 -0.007592 -0.000345 0.009176 -0.030162 -0.013493 0.092930 -0.046155 -0.122746 -0.100711
--0.019129 -0.019053 -0.007300 -0.056406 -0.006559 -0.009906 0.096847 -0.014329 -0.057535 -0.002618
--0.006023 -0.003099 -0.007942 -0.055076 -0.022442 -0.017302 -0.024372 0.024244 -0.052012 -0.020442
--0.001764 -0.002947 0.012634 0.007509 -0.001444 0.040596 -0.029075 -0.010115 -0.013671 -0.020975
-0.004643 0.003214 0.033058 0.038091 0.032539 0.186831 0.011903 0.050208 0.084909 0.043773
-0.011918 0.006448 0.019332 0.038603 0.008931 0.023879 0.000966 -0.007513 -0.060487 -0.017276
-0.000802 -0.003381 -0.057722 -0.102310 -0.043278 -0.232444 -0.004675 -0.075857 0.067659 0.048516
-0.022830 0.036489 -0.018523 -0.039295 -0.088034 -0.234284 0.067557 0.032761 0.157216 0.140830
--0.027531 -0.031500 -0.009347 -0.015867 -0.129592 -0.069816 0.041286 0.139673 0.075357 0.036143
--0.058598 -0.085457 -0.062185 -0.035750 0.018500 0.338848 0.211783 0.151435 0.306717 0.144859
-0.003990 -0.014490 0.030125 0.200990 0.394031 0.336115 0.020583 -0.001042 -0.193021 -0.130427
-0.065655 0.064369 0.066869 0.063988 0.025500 -0.247405 -0.359155 -0.222571 -0.383119 -0.206083
-0.011047 0.014733 0.009627 -0.060247 -0.208713 -0.198127 -0.266340 -0.261493 -0.012473 0.008893
-0.000814 0.006486 -0.013586 -0.057714 -0.089071 0.008514 0.357029 0.222214 0.421671 0.320100
--0.024246 -0.015106 -0.024444 -0.022761 -0.016366 0.051380 0.213641 0.222944 0.118190 0.062296
-0.012047 -0.000609 -0.036078 -0.112906 -0.110055 -0.154563 -0.341305 -0.163672 -0.308563 -0.154023
--0.011217 -0.041671 -0.037184 0.044184 -0.038086 -0.072882 -0.274671 -0.294520 -0.121211 -0.088862
-0.014457 0.007743 -0.028314 0.002743 0.020600 0.112271 0.258557 -0.115857 0.143500 0.099457
--0.018966 -0.050190 -0.014914 0.014000 -0.078241 0.058759 0.087776 0.027276 -0.022517 -0.286052
-0.015717 0.022902 -0.000717 0.002457 -0.024989 -0.124141 0.054065 0.056543 -0.092696 -0.160391
--0.018395 -0.021302 0.012070 0.068942 0.108314 0.043151 0.198256 0.135686 0.181523 0.310233
-0.017176 0.022135 0.008282 0.029400 0.007165 -0.004400 0.194371 0.056929 0.140588 0.187412
-0.007560 -0.003000 -0.013083 -0.030560 -0.112345 -0.029583 -0.192048 -0.133107 -0.013190 -0.218952
--0.087780 -0.085585 0.018256 -0.057634 -0.070061 0.047000 -0.109598 0.010146 -0.034585 -0.054207
--0.051962 -0.034558 0.115365 -0.047654 -0.014750 0.280192 0.086308 0.151019 0.024577 0.069750
--0.027452 -0.034437 0.079937 0.016984 0.081587 0.218762 0.005008 0.020849 -0.120206 -0.055198
-0.004566 -0.000187 -0.024777 0.003825 -0.020386 -0.010813 -0.061428 -0.323717 -0.024928 0.002482
-0.048830 0.060170 -0.076182 -0.000045 -0.007886 -0.244114 -0.021636 -0.240284 -0.042909 -0.004136
-0.124042 0.152875 -0.058896 0.011563 -0.048792 -0.169938 -0.016604 0.114979 -0.079646 -0.131375
--0.005101 0.002550 0.028239 0.061706 0.167417 0.108211 0.158606 0.204560 -0.032014 -0.016528
--0.038852 -0.045639 0.037361 0.013083 0.067556 0.111167 0.102907 0.062259 -0.053231 0.045361
--0.020021 -0.007264 0.011107 -0.120686 0.005171 0.012750 -0.022007 -0.000193 0.053871 0.038593
--0.003418 -0.000870 0.003767 -0.016205 0.009301 0.030007 -0.081452 -0.011801 0.083904 0.127952
-0.000346 0.000453 0.005026 -0.005474 0.004017 -0.003761 -0.021564 -0.075017 0.036103 0.086560
--0.034250 -0.043723 -0.035518 -0.196161 -0.024098 0.035554 -0.110509 -0.210902 -0.186991 -0.051268
-0.012764 0.008126 0.008109 -0.002046 -0.022787 -0.052557 -0.209782 -0.120937 -0.224333 -0.158891
-0.010952 0.033119 0.035786 0.219857 0.015119 0.029857 0.223833 0.355214 0.024310 -0.017286
--0.000092 0.021000 0.008250 -0.044566 0.023566 0.268224 0.521763 0.535605 0.388184 0.227566
--0.013077 0.028327 -0.022212 -0.192231 0.035212 0.011481 -0.091385 -0.101538 0.238673 0.096962
-0.052638 0.034319 -0.011468 0.007266 -0.038830 -0.332064 -0.312585 -0.389660 -0.121340 -0.025660
-0.118404 0.100558 -0.021212 -0.149231 -0.007327 -0.069269 -0.021673 -0.087750 -0.178423 -0.135250
--0.020158 -0.019921 0.034553 0.035342 0.041197 0.112684 0.119158 0.372250 -0.188487 -0.175645
-0.009542 -0.006500 0.088917 0.264896 0.208250 0.193687 0.060438 0.370917 -0.009708 -0.054688
--0.036500 -0.065600 -0.040133 0.217689 0.211800 0.110133 -0.132022 -0.159067 0.053744 0.049333
-0.019846 0.034692 -0.009000 -0.265538 -0.207288 -0.026212 0.159212 -0.120192 -0.015558 0.029442
-0.050740 0.074144 0.038712 -0.225173 -0.276789 -0.197058 0.093067 0.116760 0.000808 -0.011702
-0.030008 0.008515 0.023062 0.188315 0.023023 -0.036569 -0.101577 -0.046085 -0.050469 -0.045662
--0.033362 -0.046569 0.035672 0.297517 0.059879 0.119259 0.006293 -0.102759 -0.091948 -0.052207
--0.009295 -0.013779 -0.002689 0.024770 -0.124943 0.050484 0.016631 -0.048434 -0.051221 -0.055205
--0.021381 -0.004356 -0.017932 -0.165839 -0.110102 -0.156237 -0.077500 0.032195 0.062280 0.028907
-0.011200 0.031329 0.044343 -0.183014 -0.021386 -0.073743 0.035114 0.074343 0.024471 0.016714
-0.013485 0.009005 0.040668 0.041327 0.034569 0.041351 0.092342 0.116787 -0.012881 -0.017673
--0.019654 -0.039154 -0.091423 0.022833 0.086179 0.182603 0.128141 0.112397 0.013538 0.021000
--0.065336 -0.074533 -0.121320 -0.077869 0.148352 0.126754 -0.035475 -0.113885 0.049049 0.030705
-0.024107 0.010918 0.027951 0.044869 -0.121607 -0.118828 -0.242148 -0.189000 0.028582 0.021770
-0.023872 0.047262 0.046549 0.005067 -0.293226 -0.291049 -0.271433 -0.214348 -0.183579 -0.102561
-0.012484 -0.006500 -0.007079 0.120468 0.217817 -0.002683 -0.057643 0.018405 -0.153659 -0.152460
-0.142986 0.313500 0.476458 0.442840 0.482167 0.624812 0.582910 0.538771 0.336389 0.201347
--0.049764 -0.092333 -0.072125 -0.281236 -0.221861 0.191694 0.130875 0.063153 0.080097 0.113542
--0.143675 -0.325431 -0.482415 -0.520117 -0.633729 -0.644894 -0.440042 -0.386516 -0.237027 -0.134096
-0.049981 0.057904 0.073192 0.216423 -0.097250 -0.204596 0.123404 0.179192 0.008981 -0.027846
-0.189562 0.333948 0.483245 0.451479 0.402672 0.534490 0.260958 0.228979 0.238719 0.114005
-0.009744 -0.011674 0.040244 0.030721 0.099302 0.246837 -0.268360 -0.150756 0.014640 -0.031849
-0.028585 -0.047754 -0.212185 -0.249115 -0.331231 -0.572423 -0.377815 -0.407792 -0.291192 -0.139769
-0.029125 0.030860 0.021838 0.048794 -0.356581 -0.334713 -0.102846 -0.126493 0.021529 0.017331
-0.008423 0.007803 0.059577 0.046535 0.095923 0.272373 0.105317 0.193465 -0.000585 -0.022070
--0.028200 -0.006645 0.083791 0.101918 0.135282 0.456100 0.205891 0.271345 0.095273 0.030127
--0.003351 0.001805 -0.011325 -0.016610 0.153532 -0.001558 -0.005188 -0.002500 0.014169 0.028279
-0.003327 0.020806 0.019949 0.042990 0.076490 -0.180796 -0.098388 -0.148622 -0.013745 0.001633
--0.014939 -0.007015 0.098061 0.096152 -0.035152 0.046121 0.008667 -0.080515 0.034773 0.025439
--0.001100 -0.012933 -0.008000 0.021400 -0.102578 0.221611 0.041311 0.021922 0.035689 -0.009189
-0.020726 0.027538 -0.100972 0.003717 -0.026566 -0.263981 0.021925 -0.011066 -0.129868 -0.062557
--0.003357 -0.008946 -0.091304 -0.030321 -0.046393 -0.497393 0.038268 -0.002196 0.020571 0.075518
-0.020074 0.056882 0.067912 -0.120279 -0.029618 -0.070912 -0.107279 -0.048206 0.089441 0.100324
--0.004276 -0.007303 0.050382 -0.032487 0.017658 0.424921 -0.019737 0.071132 -0.025013 -0.061316
--0.012562 -0.035937 0.045531 -0.018875 -0.038406 0.317609 0.178125 0.036094 -0.150219 -0.102594
--0.010892 -0.008142 -0.057378 -0.114912 -0.003628 0.040439 0.057885 0.073581 0.097520 0.062514
--0.005542 -0.002734 -0.009177 -0.065479 0.051271 0.022156 0.032417 0.027151 0.053104 0.053203
-0.005500 0.004373 0.074582 0.033036 0.012164 0.015755 -0.024100 -0.048709 -0.045209 -0.050855
-0.037098 0.067561 0.160220 0.069171 -0.050866 -0.075659 -0.068476 -0.093012 -0.027000 0.001512
-0.013098 0.023991 0.016509 0.013482 -0.006179 -0.173857 -0.054759 0.003250 0.075143 0.098875
-0.013380 0.019296 -0.055333 0.074389 0.100991 -0.141583 0.006722 0.047019 0.097398 0.068009
--0.000488 -0.004612 0.002853 0.083282 0.044488 0.071588 0.070453 0.025218 0.022459 -0.007506
-0.001106 -0.006149 -0.061340 0.013436 0.109213 0.196851 0.042681 -0.040819 -0.015234 0.002713
--0.023723 -0.026089 -0.062732 -0.009125 0.100804 -0.032598 0.022000 0.004759 -0.048571 -0.027768
--0.037734 -0.019141 -0.053297 -0.069688 -0.013141 -0.161938 0.006508 0.014953 -0.021930 0.018398
--0.008436 -0.000300 0.000800 -0.082777 -0.106409 -0.048686 -0.054459 -0.027023 -0.018545 -0.036991
-0.008468 0.003195 0.000357 0.020013 -0.013039 0.082942 -0.105091 -0.023987 -0.010760 -0.026318
-0.005458 0.004168 0.015821 0.039747 0.017921 0.092763 0.000974 -0.020484 -0.014053 -0.012868
-0.006193 0.001489 0.009850 0.032904 0.008698 0.011497 0.041382 0.011556 0.023425 0.014374
--0.004102 -0.002455 -0.010353 -0.012098 -0.017985 -0.025086 0.022368 0.086789 0.005064 0.007782
--0.000397 -0.003799 0.042552 -0.024362 -0.041161 -0.000241 -0.003184 0.051287 -0.005006 -0.009580
-0.001854 0.002447 -0.008000 -0.004841 -0.067664 -0.044239 -0.054770 -0.125885 -0.008558 -0.021283
--0.015254 -0.033918 -0.138082 -0.072388 -0.059799 -0.075716 -0.080448 -0.263463 0.001754 -0.026284
--0.025086 -0.034121 -0.044036 -0.132057 0.050836 0.059671 0.135036 0.156807 -0.006500 0.003193
--0.023875 -0.019229 0.010583 -0.187063 -0.095271 0.093729 0.126042 0.369333 -0.070667 -0.019625
--0.000728 -0.024404 0.001368 -0.119507 -0.199412 0.009294 -0.080794 -0.107662 -0.199618 -0.151544
--0.014456 -0.018971 0.024868 0.371015 0.417897 0.095632 0.024279 -0.120103 0.245000 0.158015
-0.023479 0.084135 -0.001677 0.199719 0.384448 -0.046490 0.141104 0.161542 0.431865 0.293594
--0.048895 -0.050093 -0.024453 -0.280000 -0.163663 -0.059430 -0.127930 -0.152698 -0.420093 -0.139023
--0.052188 -0.084297 -0.056375 -0.181516 -0.119547 0.100719 -0.001922 -0.035578 -0.517734 -0.364969
-0.065688 0.079708 0.107937 0.061750 -0.027833 -0.065687 -0.012500 0.079833 0.216271 -0.156896
-0.050583 0.076278 0.032264 0.111264 0.001042 -0.193764 -0.082722 -0.009042 0.382167 0.140597
--0.003895 -0.000193 -0.020368 0.014982 -0.018886 -0.052632 -0.007096 -0.149544 0.283219 0.177982
--0.052750 -0.075625 -0.107028 -0.224958 -0.082514 0.252764 -0.017250 -0.033361 0.004014 -0.027750
--0.089171 -0.101886 -0.016229 -0.004857 0.086171 0.235314 0.042943 0.001543 -0.241571 -0.192371
-0.033000 0.050067 0.044300 0.148450 0.139633 -0.171150 0.108600 0.164217 -0.116817 -0.069700
-0.055811 0.090962 0.176698 0.103745 -0.010472 -0.028047 0.114170 0.093208 0.096255 0.107679
--0.014517 -0.005948 -0.004707 -0.156362 -0.051879 0.098741 0.009569 -0.013810 0.071828 0.140379
-0.001036 -0.017274 -0.146881 -0.029333 -0.077607 -0.003607 -0.094214 -0.051012 -0.064060 -0.051881
-0.007267 -0.005802 -0.047914 0.016966 -0.033509 -0.054647 -0.244233 -0.272862 0.090940 0.054897
--0.042609 -0.042609 -0.008707 -0.012446 0.074109 0.089543 -0.127141 -0.197533 0.129913 0.082674
--0.035304 -0.025990 0.042500 0.060882 0.174804 0.201549 0.357157 0.347628 -0.177549 -0.097196
--0.002926 0.019485 0.044250 -0.034868 -0.018544 0.024926 0.434294 0.403897 -0.136132 -0.096353
-0.098830 0.073045 0.041591 0.005239 -0.230159 -0.369841 -0.508295 -0.304511 0.196443 0.138216
-0.022670 -0.002180 -0.001750 -0.040810 -0.087830 -0.082820 -0.467400 -0.381280 0.107830 0.036940
--0.032533 -0.030956 -0.010000 -0.070633 0.054422 0.195256 0.156244 0.065278 -0.029356 -0.062533
--0.037480 -0.013531 -0.047735 -0.040173 0.019459 0.070755 0.220153 0.205541 0.233082 0.215306
--0.009748 -0.011446 -0.019824 -0.027234 -0.011108 -0.058743 0.012644 -0.020450 0.095869 0.114248
--0.007333 -0.004402 0.010470 0.004386 0.001992 -0.013348 -0.010455 0.113848 -0.145909 -0.136402
--0.002235 -0.001000 0.020549 -0.001284 0.085392 0.077382 -0.009951 0.056412 -0.122529 -0.029598
--0.000090 -0.003082 0.009806 0.036597 0.054761 0.006851 0.019373 -0.187672 -0.004948 0.021313
-0.044766 0.037032 0.101573 0.149363 0.044653 0.009363 0.001702 0.009363 0.078992 -0.000089
-0.015833 0.034056 -0.037431 -0.028292 -0.085750 -0.015042 -0.023750 0.276000 -0.039722 -0.108667
--0.108808 -0.129333 -0.209717 -0.241283 -0.072617 -0.074900 0.016717 -0.019583 -0.056658 -0.058058
--0.023478 -0.015957 -0.092217 -0.246380 -0.086587 -0.065478 -0.005989 -0.003315 0.133859 0.144533
-0.006000 0.072367 0.224641 0.100898 0.104313 0.133883 0.095148 0.072195 0.104383 0.087195
-0.022337 0.010255 0.162867 0.431622 0.262061 0.276571 0.245133 0.184388 -0.028082 -0.073020
--0.002388 -0.017632 0.045447 0.235447 0.068171 0.089658 0.063520 0.054263 0.017487 -0.017789
--0.006012 -0.030640 -0.154591 -0.167134 -0.169988 -0.159677 -0.113323 -0.100750 -0.044299 -0.027274
--0.011145 -0.099819 -0.233217 -0.408703 -0.200130 -0.256406 -0.241739 -0.119841 -0.102986 -0.042029
-0.000442 0.005175 -0.004433 -0.184242 -0.006300 -0.015142 -0.093867 -0.127725 -0.064842 -0.023842
-0.000261 0.002142 0.039343 0.151194 0.024627 0.065239 -0.030216 -0.017552 -0.008485 -0.015448
-0.015540 0.015605 0.045194 0.146218 0.052056 0.033758 0.064355 0.136742 0.012565 0.018710
-0.006541 0.001245 0.017755 0.085132 -0.012736 -0.007455 0.024095 0.042541 0.049459 0.013164
--0.004965 -0.008015 -0.010050 -0.008663 -0.010743 0.012332 0.013970 -0.151876 -0.030074 -0.052188
--0.011272 -0.020935 -0.007826 -0.081978 0.071978 -0.001326 -0.030196 -0.113239 -0.064663 -0.050217
--0.007769 -0.002093 0.025357 0.008813 0.038231 0.029434 0.080357 0.199863 -0.094269 -0.030852
--0.054650 -0.050129 -0.015471 0.023621 0.062579 0.096657 0.276857 0.182300 -0.096236 -0.030571
-0.159857 0.216964 0.108768 0.097179 -0.065161 -0.043714 -0.020000 -0.079179 0.104875 0.115661
-0.147474 0.163263 0.082158 -0.095711 -0.070895 -0.050921 -0.303079 -0.135632 0.144447 0.049474
--0.081539 -0.091237 -0.097039 -0.159276 0.058882 0.052566 -0.076934 0.020303 -0.090092 -0.112605
--0.052706 -0.082221 -0.040250 0.112338 0.092118 0.123544 0.134838 -0.057618 -0.184397 -0.081912
-0.008912 -0.000158 0.024662 0.082759 -0.002399 0.034890 0.019311 0.002570 -0.003991 0.009579
-0.001253 -0.000900 -0.014013 -0.092000 -0.020560 -0.054600 -0.045020 0.033647 0.042680 0.044447
--0.027895 -0.017352 -0.031593 -0.111932 -0.003302 -0.050636 0.063272 0.054759 0.013926 -0.000210
--0.011859 -0.020359 -0.031672 0.125234 0.104125 0.026672 -0.007656 -0.071680 -0.076211 -0.035086
-0.019305 -0.003085 -0.006110 0.117049 0.164902 0.026780 -0.195354 -0.191366 -0.119122 -0.109829
-0.001032 -0.017809 -0.049894 -0.007862 -0.059926 -0.083543 -0.188362 0.033000 -0.021404 0.081862
-0.001869 0.028344 0.051402 -0.099607 -0.251615 -0.108869 0.036008 0.040697 0.147270 0.070336
--0.014261 -0.012870 -0.044793 -0.128293 -0.191674 0.087891 0.320554 0.198924 -0.012087 -0.013011
--0.017946 -0.026674 -0.067315 0.000685 0.246217 0.095761 0.168565 0.086750 -0.077326 -0.029370
--0.000175 0.017008 0.023992 0.016050 0.374000 0.110758 0.076983 0.110992 0.178383 0.098492
--0.017779 -0.020195 -0.014379 0.008800 0.060747 0.032474 0.281953 0.107000 0.056689 0.048711
-0.094692 0.099417 0.077733 0.069758 -0.339492 -0.437242 -0.122958 -0.068417 -0.180900 -0.080242
-0.066095 0.038776 -0.041397 -0.073914 -0.306983 -0.429483 -0.640009 -0.541293 -0.247250 -0.224586
--0.069660 -0.155860 -0.149080 -0.028500 0.149940 0.021300 -0.261240 -0.389000 0.054540 0.011040
--0.050097 -0.050370 -0.015006 0.033403 0.184851 0.176234 0.174084 -0.092351 -0.002916 0.042364
--0.004410 0.005560 -0.020980 -0.006750 -0.030710 -0.067060 0.087660 0.144290 0.014320 -0.054800
-0.004478 0.012311 0.025511 -0.049722 -0.088778 -0.046578 0.068767 0.340800 0.123489 0.061233
--0.027567 0.000462 0.013163 -0.007615 0.106692 0.079731 0.305923 0.303750 -0.004221 0.115029
-0.024243 0.033676 0.045270 0.051230 0.089243 0.077973 -0.008311 -0.236973 -0.121730 -0.007959
-0.071810 0.053220 0.019940 -0.019150 -0.096820 -0.091230 -0.408370 -0.376440 -0.245770 -0.276870
--0.090048 -0.103548 -0.126365 -0.174381 -0.176016 -0.176111 -0.221778 -0.032262 -0.119159 -0.164921
--0.098912 -0.105426 -0.049324 0.014956 0.112559 0.079456 0.456485 0.287412 0.234147 0.253794
--0.028986 -0.015732 0.135261 0.207979 0.062486 0.089472 0.288324 0.102627 0.200120 0.171085
-0.037500 0.048085 -0.058793 0.093171 0.046646 0.045939 0.082073 -0.101427 0.019171 -0.008427
-0.188586 0.286828 0.285431 0.114500 0.178397 0.139776 -0.098879 -0.022172 -0.170172 -0.151155
-0.175304 0.259761 0.124152 -0.095413 0.042717 -0.002326 -0.211413 0.028957 -0.145935 -0.193978
--0.196676 -0.352027 -0.517730 -0.501878 -0.552041 -0.314851 -0.214257 -0.241351 0.011122 -0.021689
--0.106619 -0.214214 -0.182429 -0.180714 -0.432619 -0.223214 -0.045000 -0.206048 0.155500 0.187643
-0.026014 0.034401 0.082042 0.175282 0.266606 0.122937 0.044141 -0.014535 -0.164218 -0.067162
-0.067250 0.115797 0.060031 -0.069016 0.212391 0.112188 -0.072734 0.094281 -0.130578 -0.181391
-0.001891 -0.004475 0.011847 -0.026153 -0.001079 0.040045 0.012970 0.111069 -0.009569 -0.035421
-0.003003 0.000083 0.013473 0.013286 0.017607 0.020054 0.008690 0.183232 0.003307 0.005357
-0.000694 0.000519 0.001344 0.007860 0.003341 0.000545 -0.020854 0.068433 -0.009080 0.005962
--0.003118 -0.001682 -0.011497 0.013417 -0.009242 0.008860 -0.002408 -0.116850 0.012780 0.002223
-0.002542 0.001380 -0.026739 -0.013859 -0.033704 -0.143937 -0.042655 -0.180211 0.051394 0.031824
--0.002743 0.030600 0.147771 -0.020200 0.034200 -0.030086 0.065214 -0.029629 -0.023686 -0.000686
-0.008250 -0.034781 0.206031 -0.026250 -0.107406 0.028000 -0.096156 -0.003125 -0.048094 -0.004531
--0.067492 -0.114339 -0.195585 -0.200754 -0.210483 -0.198322 -0.067288 -0.053678 0.075780 0.062254
--0.046803 -0.092682 -0.360727 -0.252758 -0.081288 -0.214833 0.006106 -0.068561 -0.048727 0.051030
-0.093023 0.162731 0.192623 0.221300 0.367115 0.283808 0.098715 0.096223 0.037615 -0.009154
-0.029810 0.048464 0.210024 0.289214 0.215607 0.100798 -0.169012 -0.039881 -0.053107 -0.040333
-0.000112 -0.002762 0.024100 -0.011475 -0.297662 -0.096187 0.118425 0.150825 0.046250 -0.002100
--0.047788 -0.060750 -0.053856 -0.202508 -0.244606 -0.023576 -0.000523 0.120159 0.061348 -0.008864
--0.011912 -0.041103 -0.162544 -0.187074 0.129485 -0.103500 -0.108353 -0.187500 -0.137074 -0.061956
-0.001868 0.004029 -0.046132 0.016676 0.217603 -0.030706 0.031985 -0.111397 -0.069926 -0.004000
-0.079500 0.136266 0.248989 0.244202 -0.086138 0.044543 -0.025096 0.017245 0.076532 0.026213
-0.010151 0.008212 0.007486 -0.004589 -0.142397 0.005610 -0.071363 -0.039425 0.043856 0.028993
--0.004537 -0.002079 -0.072732 0.005256 0.000207 0.012433 -0.005213 -0.050896 -0.015884 -0.015848
-0.001773 -0.002472 0.001756 0.170892 0.023318 0.037676 0.022580 0.018523 0.034784 0.021159
--0.027390 -0.025220 -0.092707 -0.132122 0.107817 -0.012707 0.109171 -0.004341 0.058268 0.094402
--0.038530 -0.034348 -0.144621 -0.380091 0.075500 0.048258 0.017318 -0.014348 -0.004833 0.029061
-0.115036 0.182357 0.231018 -0.042161 -0.187393 -0.101000 -0.146375 -0.183411 -0.038964 -0.029661
-0.038790 0.073403 0.214645 0.075774 -0.205597 -0.184710 -0.276790 0.024000 -0.066742 -0.097742
--0.093382 -0.148882 -0.187412 -0.113029 -0.029824 -0.004882 0.037588 0.290559 0.065029 0.059941
--0.114557 -0.107830 -0.125545 -0.152989 0.026057 0.127011 0.272739 0.125693 0.015716 -0.013955
-0.008712 0.019250 0.084865 0.150673 0.261442 0.280327 -0.126404 -0.325058 -0.083712 -0.015827
-0.172133 0.258767 0.400000 0.301100 0.141767 0.112233 -0.320100 -0.218267 0.018700 0.019733
-0.007398 0.017531 -0.009776 -0.029480 0.013786 -0.149745 0.158735 0.185582 0.053449 0.065816
--0.003563 0.004663 0.017050 -0.099087 -0.068825 -0.104000 0.010575 0.174112 -0.038550 -0.019738
--0.002526 -0.002626 0.014300 -0.069979 -0.027142 -0.053632 0.011121 0.018368 -0.003011 -0.014842
-0.021558 0.023151 -0.087512 -0.055081 -0.052640 -0.067942 0.019744 0.023535 0.010244 0.009186
-0.003184 0.004194 -0.001378 0.031214 -0.050888 0.040944 -0.020918 0.014939 -0.031587 -0.011985
-0.062032 0.048479 0.089202 0.060160 -0.064394 0.061766 0.004032 0.008915 0.042926 -0.006521
-0.009985 -0.000085 0.082154 0.041854 0.026115 0.023977 -0.015277 0.017085 0.013346 -0.007938
-0.012921 0.006393 0.021517 0.122023 -0.017354 -0.031933 0.012983 -0.022017 0.008326 0.020573
--0.001250 -0.019276 -0.102013 -0.014500 -0.031250 -0.056605 -0.046842 -0.028224 -0.214974 -0.037132
--0.028898 -0.024608 -0.088823 -0.244753 -0.021253 -0.018392 -0.066672 -0.035457 -0.108403 -0.021296
--0.016841 -0.008205 0.018530 0.036197 0.106326 0.052515 0.025515 0.083576 0.152848 0.034735
-0.009542 0.003873 0.023763 0.124195 0.065602 0.117466 0.018356 0.005661 -0.078093 -0.104508
--0.006559 0.001068 0.005780 -0.049517 0.023949 0.005136 0.011161 -0.011186 0.049695 -0.054873
--0.009385 -0.002230 -0.012500 0.027203 -0.010304 -0.007588 0.172182 0.052459 0.350649 0.128791
--0.014190 -0.010332 -0.030185 -0.069957 -0.024016 -0.011717 -0.015614 -0.015413 0.043326 0.024087
--0.008397 -0.014801 0.000412 -0.038801 0.025934 0.051412 -0.101618 -0.068199 -0.198618 -0.136853
-0.010333 -0.002402 0.026713 0.085644 0.026006 0.014598 0.021684 0.041305 -0.026621 -0.039724
-0.024034 0.028836 0.027671 0.067192 0.079678 0.018925 0.064027 0.064877 0.059274 0.058637
-0.002885 -0.001236 -0.002791 -0.028358 0.036669 0.019466 -0.049554 -0.015723 -0.045595 0.069203
--0.009005 -0.005563 0.003353 -0.084011 -0.017358 0.009132 -0.084547 -0.065921 -0.024316 -0.024711
--0.001307 0.000214 -0.004532 0.001257 -0.013046 -0.011639 0.075671 -0.044261 -0.003350 -0.014146
-0.011852 0.000074 0.031287 0.229352 -0.016602 -0.035500 0.124963 0.028185 0.036769 0.011056
-0.016628 0.005686 0.058163 0.172674 -0.035570 -0.058442 -0.075337 -0.065209 0.117500 0.043163
--0.019224 -0.024612 -0.091629 -0.383698 -0.106388 -0.149259 -0.097284 -0.057983 0.020379 0.060336
-0.027871 -0.018000 -0.186290 -0.101468 -0.127371 -0.114161 0.019371 0.154742 0.013048 -0.038645
-0.012705 -0.017090 0.126692 0.414872 0.029603 0.003256 0.032526 0.002026 0.004346 0.008218
--0.009635 0.075625 0.356531 0.297427 0.201344 0.316500 0.073385 0.068719 0.157010 0.099708
-0.048153 0.121226 0.176565 0.135839 0.228694 0.345887 0.572903 0.345911 0.199734 0.165798
-0.093352 0.125296 0.003056 -0.331815 -0.284611 -0.124907 0.109722 0.062167 -0.282741 -0.185019
--0.002518 -0.130693 -0.287851 -0.337254 -0.528404 -0.675640 -0.742026 -0.683816 -0.344833 -0.202307
-0.045010 -0.057010 -0.064927 -0.087333 -0.189885 -0.290615 -0.623375 -0.238927 -0.063406 -0.088417
--0.040113 -0.025662 0.109620 0.293458 0.253099 0.350099 0.416338 0.097000 0.213627 0.191373
--0.005240 0.012444 0.042480 0.084730 0.177520 0.235995 0.337612 0.216842 -0.010964 0.004878
--0.005946 -0.003804 0.019824 -0.012108 -0.139189 -0.093209 -0.110635 -0.003709 -0.139378 -0.098041
--0.020409 -0.016795 0.028102 0.035330 0.067602 -0.133170 0.031852 -0.022864 -0.223261 -0.083750
--0.033507 -0.030629 -0.027136 0.072679 0.238193 0.211593 0.346021 0.159629 0.146929 0.165193
--0.021422 0.018017 0.078233 0.154638 0.209267 0.303845 0.326776 0.346914 0.508569 0.245431
--0.018264 -0.005791 -0.007245 -0.230009 -0.400064 -0.202227 -0.349655 -0.276064 -0.091736 -0.074800
-0.090320 0.058795 -0.073402 -0.271451 -0.231238 -0.323393 -0.373082 -0.215262 -0.307975 -0.247582
-0.003605 0.006149 0.015570 0.095105 0.188009 -0.003851 0.099368 0.050842 -0.061930 0.011289
--0.062364 -0.090761 -0.048193 0.138273 0.063977 0.056352 0.194182 -0.003034 0.080386 0.109886
-0.002359 0.003590 0.005237 0.031667 0.005083 0.026256 0.011660 0.092378 0.021885 0.094513
--0.004858 -0.006421 0.025384 -0.000053 -0.004389 0.013195 0.056000 0.081874 0.087158 0.099484
--0.008455 -0.002980 -0.000145 -0.035610 0.005050 -0.038490 0.032485 -0.019125 0.064110 0.019120
--0.003113 -0.003158 -0.002698 -0.021797 -0.005622 -0.022122 -0.037910 0.018198 0.005649 -0.023221
--0.000570 0.001000 -0.001164 -0.019055 -0.016094 0.065539 -0.037219 0.042672 -0.007789 -0.055961
--0.002731 -0.001594 -0.009623 -0.001142 -0.078104 0.020104 0.000712 -0.012165 0.021009 -0.023028
-0.005598 0.008422 -0.041554 -0.014848 -0.026250 -0.096490 -0.025103 -0.054093 0.068103 0.033324
--0.001569 -0.000693 -0.004020 -0.002980 -0.008936 -0.027124 -0.017842 -0.001149 -0.000465 0.086936
-0.003681 0.002007 -0.006785 0.003938 0.041812 -0.005319 -0.000931 0.004042 -0.084340 0.032410
-0.005540 0.002391 0.003866 0.023144 0.059005 0.031540 -0.007995 -0.025718 -0.141505 -0.061990
-0.010007 0.013187 0.009792 0.005375 0.029618 -0.046701 -0.070368 -0.022514 -0.041403 -0.137090
--0.021724 -0.013053 -0.068671 -0.039197 -0.111105 -0.210276 -0.045329 0.058908 0.072711 0.059750
-0.002197 -0.002426 -0.002164 0.001295 -0.262311 0.036418 0.048148 -0.049033 0.003844 -0.009328
--0.010382 0.015816 0.186697 0.052947 0.139013 0.455539 -0.009605 0.006039 -0.164539 -0.120921
--0.013022 -0.010846 0.043015 0.270757 0.508669 0.237706 0.165213 0.141588 0.174507 0.149235
--0.010500 -0.017111 -0.157611 0.007722 0.023556 -0.435278 0.191333 0.087778 0.258833 0.241833
-0.073236 0.099403 0.078028 -0.129958 -0.218799 -0.195993 -0.094597 -0.084444 -0.069986 -0.000181
-0.130550 0.129175 0.126900 -0.138112 -0.117313 0.074750 -0.025625 -0.023600 -0.057462 -0.058050
--0.011613 -0.012006 -0.030232 -0.061155 -0.025756 -0.037565 -0.056220 -0.121155 0.034030 0.035690
--0.004011 -0.023356 0.005133 0.122922 -0.067767 0.026356 -0.051067 -0.091889 -0.001122 -0.021167
--0.080174 -0.080000 0.016717 0.098304 0.039804 0.220348 -0.034957 0.196435 0.070717 -0.019304
--0.014048 -0.009766 0.007234 -0.112210 -0.039500 0.059363 0.016435 0.166290 0.020371 -0.002363
--0.001434 -0.000481 -0.040981 -0.015264 0.009491 -0.122425 0.110613 -0.054972 -0.021151 -0.005962
-0.077793 0.061183 0.052085 0.151207 -0.015037 -0.061549 0.083317 -0.081061 -0.085598 -0.039732
-0.007553 0.010513 -0.011167 0.064127 -0.045333 -0.044533 -0.035913 -0.041113 -0.052140 -0.118633
--0.037845 -0.033491 -0.081690 -0.054991 -0.008250 -0.031828 0.020552 0.065310 -0.065595 -0.057966
--0.012241 -0.020907 -0.038102 -0.123074 0.166685 0.134157 0.060509 0.022963 -0.030435 0.006417
--0.013462 -0.007424 0.017304 -0.008804 0.223215 0.149854 -0.048506 0.012778 0.014873 0.013076
--0.003212 -0.000075 -0.001325 -0.055775 -0.087013 -0.016425 -0.164825 0.158112 0.113312 0.040162
-0.008300 -0.007829 -0.019143 -0.052400 -0.492514 0.001143 0.062271 0.033586 0.083129 0.038386
--0.016588 -0.047020 -0.007804 0.009725 -0.386882 -0.100078 -0.100274 -0.151559 -0.099461 -0.048039
--0.024750 0.047500 -0.060417 0.081083 0.410000 -0.025167 0.077750 0.000000 -0.299333 0.027833
--0.072250 -0.082500 0.037142 0.042267 0.287967 0.259775 0.137267 0.163967 -0.219200 -0.121500
-0.007739 -0.031630 -0.079304 0.031826 -0.329304 -0.263587 0.118043 0.209022 0.351804 0.159152
-0.136744 0.158395 -0.130919 -0.045116 -0.246628 -0.168733 -0.087640 0.032895 0.200070 0.029674
-0.210487 0.322649 0.359987 0.278189 0.323324 0.271095 -0.012716 -0.002432 0.019230 0.000338
-0.024413 0.069087 0.116522 0.320000 0.422000 -0.036130 -0.201565 -0.169391 -0.248152 -0.165957
--0.189829 -0.322632 -0.303039 -0.195026 -0.315789 -0.126697 -0.094592 -0.085592 -0.072132 -0.092184
--0.087553 -0.128500 -0.197829 -0.022474 -0.037184 -0.023724 0.098092 0.037579 0.228263 0.142289
-0.070338 0.061779 -0.060838 -0.076103 0.134088 0.037515 0.199647 0.122279 0.057000 0.096838
--0.024842 0.005724 0.027500 -0.255066 0.081382 0.142487 0.011789 0.056776 -0.165974 -0.082329
-0.007213 0.011638 0.007415 -0.012074 0.060628 0.126160 -0.149330 -0.012032 -0.051277 -0.130574
-0.014458 0.024764 0.090458 0.229833 -0.143486 -0.167722 -0.013292 -0.092833 -0.041069 0.049736
-0.020702 0.022574 -0.028117 -0.021745 -0.053543 -0.143564 -0.103840 -0.270638 0.157787 0.136223
--0.041216 -0.058635 -0.055919 -0.108541 -0.008770 0.151703 -0.083014 0.024554 0.078108 0.025892
--0.019974 -0.027205 -0.014756 -0.109872 0.002974 0.111577 0.016885 0.173718 -0.110795 -0.118128
--0.008900 -0.008864 0.015391 -0.051927 0.050464 0.022073 0.062855 -0.044773 -0.124482 -0.030273
--0.006979 0.002830 0.050915 0.193989 0.086415 -0.029426 0.079702 0.027234 0.139043 0.180394
-0.042280 0.047682 -0.014333 0.146848 -0.020045 -0.091841 0.021871 0.085780 0.153985 0.041561
-0.001812 0.003266 0.003836 0.026734 -0.062641 -0.031695 0.009680 0.062492 -0.041258 -0.065008
-0.002273 -0.005155 0.030736 0.019973 0.010773 0.126136 0.075636 -0.072855 -0.039882 0.008673
--0.041420 -0.054340 0.019700 -0.063000 0.016500 0.098860 0.010500 -0.133340 0.001780 0.144800
--0.003470 0.001590 -0.038888 -0.158731 -0.046873 -0.092007 -0.055873 -0.066194 0.037933 0.010933
--0.019340 -0.015902 -0.034881 -0.126351 -0.070732 -0.186660 -0.067732 -0.064129 -0.100015 -0.019711
-0.011367 0.005117 -0.052820 0.130594 -0.008641 0.012094 0.000398 0.010211 -0.017539 -0.006461
--0.067569 -0.172216 -0.228010 0.059059 0.000392 -0.055373 -0.072549 -0.173255 0.041549 0.061333
--0.091788 -0.138627 -0.138458 -0.048534 -0.094415 -0.052390 -0.040763 -0.096568 -0.080042 -0.016492
-0.161488 0.316233 0.399895 0.054605 0.046291 0.170767 0.394640 0.421651 0.036012 0.014872
-0.185316 0.356816 0.450551 0.196331 0.242581 0.316169 0.238235 0.305051 0.058838 0.014721
--0.127400 -0.285619 -0.417350 -0.354163 -0.332456 -0.404900 -0.522600 -0.477613 -0.430612 -0.269838
--0.185608 -0.329823 -0.356438 -0.085746 -0.197985 -0.292939 -0.328438 -0.329485 -0.148654 -0.117508
-0.098071 0.193390 0.193630 0.153506 0.194338 0.171344 0.274519 0.244766 0.243669 0.109812
-0.082905 0.135484 0.094770 0.056738 0.109270 0.135056 0.148690 0.104230 0.153365 0.151937
--0.025256 -0.022488 -0.047360 0.114988 0.018302 -0.020930 -0.083965 -0.062314 0.006419 -0.014663
--0.006808 -0.001894 0.006394 0.054173 0.183038 0.068817 -0.041202 0.007442 0.112692 0.057183
--0.009323 0.017435 -0.071500 -0.224903 0.166081 0.238984 0.172726 0.127919 0.179548 0.101371
--0.003368 -0.018382 -0.037824 -0.175985 -0.366103 -0.133294 -0.093074 -0.038721 -0.219147 -0.155279
--0.006917 -0.012528 0.105639 0.117028 -0.260944 -0.071667 0.004972 -0.094944 -0.339500 -0.202694
--0.031095 -0.049310 0.066988 0.041845 0.099571 0.044060 0.018738 -0.023226 0.013893 0.035833
-0.011600 0.037467 0.002178 0.002078 0.202000 -0.037689 -0.041144 0.031722 0.164822 0.150378
--0.004696 0.014393 0.035527 0.017679 0.003938 -0.100411 0.043938 0.055634 0.089429 0.163107
--0.032000 -0.034742 -0.094806 -0.327903 -0.116710 -0.038065 0.123500 0.148855 0.044081 0.054435
--0.132575 -0.269633 -0.506317 -0.532825 -0.117367 -0.132350 -0.228183 -0.185775 -0.127425 -0.109908
-0.032868 0.005515 -0.004132 0.236221 0.017074 0.031471 -0.092324 -0.269868 0.012824 -0.032147
-0.180188 0.289237 0.484300 0.527987 0.271637 0.162050 0.125200 0.118675 0.004350 0.008600
--0.010043 -0.001574 0.000862 -0.000117 0.044574 -0.006479 0.018734 0.132521 -0.230277 -0.062223
--0.021023 -0.043341 -0.100750 -0.107875 -0.205670 0.067375 0.130898 0.059955 0.187500 0.090386
--0.009800 -0.006822 -0.014144 0.010489 -0.032133 0.042200 -0.051344 0.006611 0.218067 -0.042522
-0.017066 0.026789 -0.007921 -0.020553 0.122013 -0.028053 -0.168592 0.047632 -0.023605 -0.050289
--0.004894 -0.013830 0.007543 0.013553 0.010468 0.015138 0.061979 -0.000894 -0.191128 0.075904
--0.045868 -0.054640 0.020158 0.002088 -0.071833 0.114825 0.215333 0.057588 0.150211 0.115158
--0.000649 0.028189 -0.021230 -0.128905 0.147716 0.045162 -0.024811 0.065284 0.129689 0.003662
-0.001171 0.002614 0.002014 0.039371 0.002614 -0.056214 -0.163300 0.071257 -0.168100 -0.063371
--0.037750 -0.054917 0.104048 0.161226 0.033631 0.153857 0.071095 0.074524 -0.098190 -0.031893
--0.068062 -0.145812 -0.232984 -0.215625 -0.235625 0.086375 0.043391 -0.126578 0.009672 0.023609
-0.004924 -0.024253 -0.147506 -0.208265 -0.192882 -0.347318 -0.276406 -0.265653 -0.051482 -0.021741
-0.081432 0.106041 0.139432 0.326838 0.035257 -0.179513 -0.029027 0.029811 0.052041 0.022811
-0.004523 0.064314 0.166091 0.160559 0.206491 0.226773 0.129095 0.168732 0.104768 0.067664
--0.008586 -0.007093 0.000123 -0.030698 -0.009753 0.106623 0.016389 -0.000685 -0.039969 -0.021500
--0.035319 -0.031379 -0.067690 -0.019569 -0.014776 -0.009716 -0.019940 -0.037871 -0.099767 -0.065871
--0.004134 -0.005069 -0.000178 -0.060327 0.055421 0.000233 -0.026193 0.027495 -0.024589 0.009916
--0.003634 -0.001919 -0.005221 -0.016930 0.118355 0.001058 0.060320 0.062686 0.012523 0.028453
-0.013780 -0.001305 -0.060263 0.132042 0.070788 0.067856 0.082610 0.053508 0.098839 0.026864
-0.020060 0.011600 0.189640 0.069440 -0.065620 0.185640 -0.049860 -0.013000 0.245020 0.117580
--0.093754 -0.124203 -0.147619 -0.185127 -0.112644 -0.212754 -0.035339 -0.095203 -0.181178 -0.031229
--0.009285 -0.018023 -0.048669 -0.174485 -0.038008 -0.133385 -0.072654 -0.098015 -0.316592 -0.048769
-0.128483 0.130379 -0.033483 0.094190 0.143155 0.078655 0.066569 0.110759 0.006552 0.004655
--0.017352 -0.000195 0.045133 0.063578 0.047805 0.143891 0.058859 0.080555 0.299711 0.023484
--0.006931 -0.002621 0.015569 0.033560 -0.011293 -0.067000 -0.096629 -0.093543 0.101466 0.178862
--0.041358 -0.051403 -0.041164 -0.050172 -0.004336 -0.083000 -0.211179 -0.093500 -0.069470 -0.069896
--0.003583 -0.002500 -0.021962 -0.025841 -0.054674 -0.049500 -0.061811 -0.022417 -0.250371 -0.333000
--0.002953 0.003818 -0.014277 -0.019270 -0.007473 -0.023264 0.260892 0.051345 -0.054581 -0.047095
--0.036862 -0.045362 -0.026569 -0.079086 0.074983 0.066259 0.172655 0.049707 0.205190 0.299655
-0.009602 0.007220 0.002585 0.008987 0.008924 -0.003263 -0.001148 0.009780 0.218932 0.175991
-0.051917 0.046300 0.024000 0.127383 0.059467 0.060967 -0.141233 0.094567 0.144383 -0.002017
-0.036573 0.030371 0.008621 0.075782 0.032315 -0.052194 -0.070661 0.006242 -0.061508 -0.021194
--0.000047 -0.002041 -0.006169 -0.030432 0.013736 -0.016709 -0.049318 -0.018628 -0.238399 -0.037973
--0.003013 0.000458 -0.001000 -0.014042 -0.005623 -0.009865 0.063800 0.022652 -0.034729 -0.025268
--0.003426 0.007303 0.008057 0.001098 0.020533 -0.029910 0.102869 0.013992 0.186352 0.117041
-0.002862 0.001424 0.006865 0.020429 -0.012318 -0.001071 0.000359 -0.020094 0.015694 0.023368
--0.010474 -0.006716 -0.007608 -0.056379 -0.015004 -0.021466 -0.107909 -0.040405 -0.125884 -0.066207
-0.001787 0.003128 -0.044574 -0.093447 -0.001351 -0.007617 -0.089340 -0.023170 0.128223 0.036064
--0.001844 0.002754 -0.001492 0.082852 0.005270 0.023287 0.070230 0.053607 0.163377 0.003803
-0.014962 0.008449 -0.013397 0.159090 -0.002513 -0.004256 0.070487 0.050077 -0.115692 -0.107064
-0.009945 0.004571 0.028934 0.068467 0.019495 0.024731 -0.038418 -0.012148 -0.208923 -0.128445
--0.042800 -0.062075 0.035050 -0.096800 -0.005425 0.097750 -0.103200 -0.040075 -0.169750 0.051550
--0.076047 -0.094438 -0.133813 -0.114297 0.027766 0.091641 -0.011391 -0.043828 0.206672 0.197063
--0.005171 -0.003276 -0.061342 -0.013776 -0.066342 0.019421 0.028724 0.164434 0.173250 -0.003605
-0.012258 0.017275 -0.058942 -0.198558 0.018250 0.042883 -0.140675 -0.051450 -0.179533 -0.162567
--0.073746 -0.092841 -0.176444 -0.228436 -0.150476 -0.182603 -0.253278 -0.232786 -0.185627 -0.114032
-0.047689 0.058933 0.058589 0.300344 0.252044 0.029778 0.314300 0.112933 0.043989 0.046744
-0.101493 0.259416 0.435592 0.465500 0.168838 0.246937 0.377289 0.210000 0.209739 0.161197
--0.038057 -0.036321 -0.068632 -0.139641 -0.172679 -0.043726 -0.116925 0.047208 0.054792 0.030896
--0.053153 -0.057235 -0.047857 -0.162969 -0.246847 0.012163 -0.139510 -0.099765 0.008235 -0.028133
--0.069488 -0.075988 0.155402 0.087963 0.187256 0.098207 0.015890 0.004915 -0.049049 -0.023561
--0.011185 0.022913 0.161761 0.199609 0.151511 0.013620 -0.000293 0.101424 -0.032413 0.005750
-0.028889 0.025824 -0.037481 0.088019 0.006287 -0.078722 -0.127324 -0.038500 0.074037 0.005972
--0.074831 -0.147608 -0.260008 -0.200785 -0.068392 -0.090877 -0.199277 -0.173569 0.036277 0.038800
--0.053474 -0.032447 -0.018184 -0.411737 -0.070224 0.042434 -0.030553 -0.062303 -0.198566 -0.103763
-0.012852 0.100389 0.247648 -0.029167 -0.026481 -0.007981 0.087648 0.151815 0.016167 0.016148
-0.052000 0.044094 0.037179 0.385462 0.104915 0.018123 0.097717 0.116953 0.218283 0.041491
--0.014217 -0.040983 -0.046667 0.283317 0.129633 0.108317 0.135617 0.180033 -0.012267 -0.048100
--0.027250 -0.008597 -0.016847 -0.202597 0.009569 0.105333 0.155361 0.021833 -0.057681 0.023458
-0.037775 0.035125 -0.080200 -0.482250 -0.350850 -0.219100 -0.186850 -0.272300 0.087800 0.064750
-0.012099 0.013645 -0.024678 -0.047829 -0.050329 -0.096691 -0.255757 -0.105145 0.030368 -0.012934
-0.069385 0.051692 0.120519 0.257423 -0.051288 -0.027058 -0.053385 0.132596 -0.067615 -0.096000
-0.013500 0.028914 0.116971 0.085200 -0.090843 -0.020200 0.043929 0.117429 -0.001614 -0.043086
--0.009279 -0.010651 0.048151 -0.028581 -0.147767 0.084802 -0.000419 0.052953 -0.102814 -0.101116
--0.028956 -0.036149 0.001886 -0.081684 -0.063965 0.176333 -0.015912 -0.029202 -0.054061 -0.114781
--0.024234 -0.008285 -0.056095 -0.087810 -0.055272 -0.036475 0.003443 -0.101241 -0.024000 -0.024443
--0.041276 -0.027966 -0.071276 -0.055397 0.037276 -0.037345 -0.006466 -0.079879 -0.136655 0.195672
-0.003592 0.002282 0.002099 0.011134 0.023204 -0.018817 0.030479 0.024965 0.004190 0.159859
-0.006156 0.005484 0.000812 0.007022 0.028613 -0.007495 0.033409 0.249484 0.049070 0.025070
-0.005434 0.006566 -0.001730 0.020984 -0.005648 -0.088082 0.011320 0.005738 0.048500 -0.063541
-0.031023 0.081114 0.154818 0.119045 0.050705 0.056477 0.050523 -0.240568 0.065250 0.051568
-0.009300 -0.025214 -0.043257 0.177843 0.059086 0.067500 -0.062129 -0.129514 0.233200 0.107529
--0.017946 -0.012375 -0.076411 -0.221964 -0.184036 -0.091536 0.004339 0.174500 -0.154393 -0.114696
-0.015296 0.044204 0.113130 -0.095704 -0.163037 -0.077574 0.065796 0.317833 -0.289241 -0.157389
-0.016413 0.032946 0.120348 0.068761 0.037326 0.067304 -0.136174 -0.135304 -0.103826 -0.077641
-0.027253 0.018089 0.014880 0.124342 0.198133 0.079506 0.210177 0.142316 0.120867 0.091348
--0.022413 -0.030613 0.027413 0.234987 0.441475 0.318300 0.424813 0.394662 0.215425 0.155400
--0.013829 -0.053573 -0.171354 -0.112049 -0.083073 -0.067829 -0.259671 -0.221000 0.206976 0.129037
--0.054054 -0.148464 -0.316071 -0.276375 -0.365161 -0.458705 -0.583929 -0.521964 0.056830 0.046312
-0.017833 -0.000206 0.017500 0.008500 -0.265775 -0.065176 0.067951 0.000167 -0.172392 -0.113529
-0.044409 0.118664 0.176600 0.147755 0.199918 0.188382 0.260191 0.368555 -0.045273 -0.020145
-0.007352 0.005932 0.022685 0.015475 0.116809 0.056062 -0.017432 0.023852 -0.003759 -0.001173
--0.004315 -0.003948 -0.021310 -0.015887 -0.012992 -0.021778 -0.030177 -0.192298 -0.001540 0.008734
-0.005403 0.001990 0.003260 -0.012255 -0.012776 -0.144515 0.014383 -0.001423 -0.034418 -0.032173
-0.001422 -0.000709 0.001384 0.001922 0.002969 -0.007860 0.007283 0.109911 -0.054740 -0.029326
-0.003028 0.003506 -0.001676 0.009631 -0.006460 0.102097 0.033199 0.047932 -0.004017 -0.001415
--0.007667 -0.007523 0.003316 -0.003287 0.015270 0.118529 0.033477 0.059466 0.055632 0.047414
-0.002559 0.000697 -0.003928 0.002855 0.003414 0.096651 -0.011684 -0.059026 0.044645 0.040559
--0.024068 -0.037318 -0.002568 -0.022148 -0.110898 -0.059625 0.002625 -0.182534 -0.110852 0.008000
-0.004233 -0.005100 0.001053 0.009087 -0.036020 -0.224273 -0.031660 -0.119833 -0.124653 -0.056727
-0.029000 0.041643 0.025929 0.023560 -0.012690 -0.100786 -0.062369 0.129774 0.076083 0.011500
-0.007040 0.011581 -0.017331 -0.008379 0.030548 -0.014669 -0.113895 0.082629 0.083306 0.054484
--0.001044 -0.001246 0.005261 -0.011335 -0.000831 0.038493 0.003827 -0.051268 -0.033471 -0.021790
-0.014247 0.003123 0.029918 0.010603 0.012959 0.254212 0.053877 0.029452 0.003541 0.005719
-0.036492 0.044943 -0.031811 -0.355262 -0.465680 -0.206779 -0.031549 0.049279 0.015730 -0.020607
-0.057756 0.094802 0.107628 -0.090093 -0.406977 -0.401058 -0.116744 0.076407 0.136291 0.024151
-0.184270 0.321010 0.437260 0.537590 0.672380 0.371880 0.219380 0.218040 0.086710 0.042220
--0.006141 -0.050234 0.026828 0.351906 0.663781 0.448031 0.146781 -0.067063 0.027359 0.028078
--0.000453 -0.044814 -0.143884 -0.478547 -0.661070 -0.213326 -0.227988 -0.217686 -0.057291 -0.051488
-0.050242 0.012606 0.065576 -0.120121 -0.331712 0.178015 -0.025712 0.017197 -0.031864 -0.083106
-0.001820 0.007205 0.018344 0.041992 0.363943 0.023861 0.022123 0.036016 -0.007336 -0.008139
--0.020678 -0.013911 -0.057767 -0.074444 -0.060878 -0.406222 -0.072511 -0.087256 -0.024867 0.016333
-0.085190 0.061707 0.004086 0.265138 -0.094397 -0.355828 -0.119431 -0.060569 0.053931 0.001931
-0.025722 0.013784 0.103531 0.273228 0.124395 0.248630 0.149617 0.117679 0.180691 0.045951
-0.004470 0.002333 0.096091 0.086303 0.053038 0.390848 0.035159 0.032636 0.093045 0.023598
--0.006891 -0.000768 -0.005681 -0.117862 0.090957 0.074688 -0.052370 -0.023435 -0.046326 -0.023087
--0.007547 -0.003682 -0.011964 -0.126047 -0.014229 -0.034224 -0.021479 -0.041240 -0.092328 -0.021333
-0.004316 0.017032 0.007380 -0.139114 -0.104013 -0.084608 0.014304 0.014203 -0.050013 -0.032943
-0.041707 0.052026 0.004509 -0.003224 -0.138707 -0.046379 -0.000474 0.076552 0.001759 -0.001888
-0.008398 0.007949 0.012720 0.035457 0.021665 0.053701 0.035630 0.076055 0.010276 0.003217
--0.026354 -0.021948 -0.005302 -0.087740 0.063323 0.174583 -0.003562 0.008146 0.039583 0.029010
--0.096891 -0.094709 -0.039027 -0.079791 -0.091573 -0.026427 -0.043564 -0.090300 0.094164 0.060500
--0.010027 -0.011345 -0.030554 0.007311 -0.164926 -0.189155 -0.072358 -0.134331 0.026473 0.008230
-0.013559 0.014428 0.006757 0.043599 0.007145 0.013849 -0.007954 -0.116625 -0.049026 -0.064059
-0.009093 0.020465 0.005419 0.050965 0.033721 0.040105 -0.059872 0.193477 -0.099046 -0.076023
--0.032074 -0.032766 -0.002362 -0.008713 0.005447 -0.093138 -0.072606 0.211777 -0.032574 -0.006915
--0.029674 -0.022849 -0.003512 0.003337 0.193477 0.033721 0.050058 0.191500 0.018512 0.045047
--0.051433 -0.051010 -0.005010 -0.018798 0.060490 0.264760 0.066865 -0.069692 0.123125 0.116183
-0.110907 0.078759 -0.000111 0.097500 -0.255778 -0.092833 -0.062185 -0.233796 0.044574 0.002741
-0.267000 0.312354 0.135188 0.138083 0.048500 -0.002604 0.028521 -0.031063 -0.053750 -0.016563
-0.004336 0.006486 0.004829 0.022893 0.123921 0.050321 0.001886 0.123750 -0.030557 -0.006279
--0.023226 -0.024381 0.043131 -0.005167 0.065774 -0.008524 -0.018083 0.108488 0.040726 0.028143
--0.006643 -0.010955 -0.022026 0.005896 -0.070558 -0.158740 0.019929 -0.001195 0.041208 0.019929
--0.000862 -0.001147 -0.000839 -0.009321 -0.015339 -0.078193 0.037647 0.048922 -0.002885 0.007596
-0.001797 0.001769 0.006734 -0.004589 0.009929 0.047054 -0.003269 0.026554 -0.002089 0.002026
-0.005743 0.002605 0.014819 0.010671 0.027881 0.051524 -0.062695 0.015943 -0.024871 0.009971
--0.001884 -0.001869 -0.003037 -0.015687 0.007897 -0.002422 -0.095312 -0.020094 -0.017834 -0.022597
--0.009531 -0.004000 -0.010382 -0.021316 -0.024333 -0.009294 -0.060930 -0.040588 -0.014276 -0.078110
--0.004457 0.003506 0.004346 -0.001401 0.026870 0.096599 0.154481 0.004784 0.043827 0.019914
--0.004714 0.000145 -0.004559 -0.007000 -0.018759 -0.018914 0.177318 0.064973 0.027618 0.047991
-0.001250 -0.006436 -0.019203 -0.009855 -0.040657 -0.106558 -0.090930 -0.029971 -0.061610 -0.052593
--0.003919 -0.002265 0.004015 0.008415 0.000958 -0.014715 -0.174146 -0.048227 -0.030269 -0.049696
-0.009301 0.005724 0.033612 0.016872 0.034755 0.163311 0.040597 0.030643 0.007929 -0.021357
-0.001819 0.008112 0.022675 0.023606 0.072575 0.012969 0.143281 0.055044 -0.002894 0.041800
-0.001732 0.010375 -0.033420 -0.004205 -0.030116 -0.145205 0.054795 0.091134 0.027902 0.053554
--0.016948 -0.009078 -0.059905 -0.030440 -0.067129 -0.062483 -0.020164 0.044578 0.091138 0.054103
--0.004038 -0.002604 0.007075 0.019849 0.016953 0.017113 -0.227019 -0.114925 0.165689 0.053500
--0.002102 -0.005102 -0.000046 0.013676 0.030991 0.098704 -0.041315 -0.161444 0.036278 0.008630
--0.053149 -0.090541 0.055568 -0.041703 0.010986 0.129108 0.052041 -0.011811 -0.450000 -0.153851
-0.011750 -0.011845 -0.019774 -0.045774 -0.027155 -0.066095 -0.080667 -0.088607 -0.501571 -0.277548
-0.003011 0.023174 -0.005478 -0.065033 -0.178457 -0.108989 -0.037707 -0.020620 0.363869 0.201261
--0.013268 -0.009963 -0.030744 -0.044415 0.037598 0.070720 0.012085 0.029098 0.485976 0.203061
--0.022900 -0.028083 0.059483 -0.049200 0.020750 0.288100 0.109267 0.149533 -0.161417 -0.236367
-0.009394 -0.015926 0.081362 0.078372 0.116702 0.102340 0.035585 0.056670 -0.341851 -0.037660
--0.043394 -0.022333 0.033909 0.056561 0.217742 -0.121273 -0.031652 0.032485 0.004136 0.088136
--0.016239 -0.023813 -0.031396 -0.004030 -0.105821 -0.134328 0.149007 0.007134 0.096910 0.120806
--0.013833 -0.014689 -0.023750 -0.015894 -0.217394 -0.148378 0.026511 -0.013489 -0.001978 -0.004594
-0.004176 0.008507 -0.009155 -0.028423 -0.090944 -0.046444 -0.209056 0.010190 -0.023711 -0.069197
-0.004243 0.008191 0.004647 0.022390 -0.008618 0.077206 -0.263176 -0.039728 -0.002551 -0.047360
-0.006581 0.004157 0.010657 0.000329 0.036519 0.035329 -0.134257 0.005543 0.025862 0.015605
-0.003385 0.002622 0.004392 0.023395 0.012941 0.024976 0.020909 0.020287 0.025944 0.057612
--0.006261 -0.000565 0.000935 0.011609 -0.018804 -0.026812 0.113384 0.015580 -0.024101 -0.082036
--0.032761 -0.058967 0.000076 0.012272 0.010739 0.063978 0.040793 -0.140304 -0.191467 -0.244424
--0.002402 -0.001880 0.014185 -0.016707 -0.018054 0.063989 -0.007359 -0.163293 -0.148370 -0.054946
-0.021384 0.027638 0.041775 0.089065 0.079225 0.059703 0.059638 0.065913 0.289029 0.269761
-0.075389 0.101153 0.145347 0.145028 0.004681 -0.022000 0.208639 0.262195 0.361389 0.269556
-0.012109 0.014406 -0.039937 -0.100656 -0.056906 -0.215984 0.154828 0.104578 -0.191875 -0.091812
--0.000317 -0.010667 -0.026133 -0.012800 -0.099792 0.012017 -0.042700 -0.048692 -0.121483 -0.156817
--0.045480 -0.039539 0.037971 -0.006529 0.015863 0.117157 -0.148598 -0.090706 0.020343 0.011206
--0.001388 -0.000044 -0.006131 0.002694 -0.024898 -0.051694 -0.100243 -0.002738 0.034801 0.021825
--0.003100 -0.001300 -0.012485 -0.005774 -0.024096 0.003226 0.040259 0.022730 0.001189 0.014856
-0.001557 -0.004116 0.020582 -0.010698 -0.001491 0.063230 -0.000013 -0.016097 0.002330 0.007843
-0.012824 0.007808 0.037907 -0.001225 0.017956 -0.026434 -0.003813 0.010368 -0.023445 -0.009621
--0.001600 0.003753 -0.015384 0.019568 0.036889 -0.108195 -0.002295 -0.012789 -0.022484 0.002863
--0.021278 -0.010460 -0.084167 0.026619 0.003929 -0.065016 -0.026992 -0.015397 -0.019246 0.004532
--0.008147 -0.011787 0.073073 0.004127 -0.001120 0.102687 -0.023867 0.024340 -0.033773 -0.030347
-0.033000 0.059336 0.144721 0.037025 0.064525 0.113582 -0.034164 0.015418 0.065361 0.014287
--0.005375 0.002111 -0.024181 0.036326 0.095736 -0.032271 0.006799 -0.029951 0.034576 0.015326
-0.008000 -0.013762 -0.100437 0.071925 0.057312 -0.034862 0.125025 0.034387 -0.003413 0.000612
-0.093821 0.084244 -0.089256 -0.024192 -0.107885 -0.257423 0.045821 0.051000 0.029333 -0.007410
-0.007302 0.016965 -0.075163 -0.083500 -0.143570 -0.392186 -0.133686 -0.113895 0.152128 0.107802
--0.175771 -0.213958 0.063396 -0.122792 0.076354 0.314167 -0.022271 -0.074417 -0.167542 -0.027479
-0.045853 0.160647 0.481941 0.485559 0.613853 0.415618 -0.153412 -0.085382 -0.029618 -0.006000
-0.039571 0.011768 -0.067500 0.054018 0.073946 0.186786 0.101964 0.023464 -0.018982 -0.225375
--0.099618 -0.251368 -0.413412 -0.432735 -0.560662 -0.521265 0.001191 0.029397 -0.050441 -0.003000
-0.042980 -0.031235 -0.116133 -0.161255 -0.385214 -0.455133 0.136490 0.029276 0.012010 0.068990
--0.009442 -0.012135 -0.127692 -0.227135 0.243269 0.060096 -0.078577 0.027058 -0.009827 -0.050058
--0.004410 -0.009885 -0.041654 -0.025308 0.328051 0.385487 -0.115628 -0.045167 0.038179 -0.048372
-0.214181 0.354104 0.541776 0.457078 0.069233 0.039155 0.069078 0.109621 0.231603 0.166741
-0.160830 0.341574 0.416734 0.136096 -0.034138 -0.067149 0.131862 0.159160 -0.034872 -0.042968
--0.112851 -0.198311 -0.173595 -0.125459 -0.034257 0.026351 -0.132405 -0.106500 -0.161892 -0.160392
--0.096607 -0.157393 -0.092845 -0.027714 0.067476 0.054929 -0.007857 0.018143 -0.008750 -0.037524
-0.077854 0.147677 0.056573 -0.070865 0.000979 0.012771 0.013594 0.054260 0.055385 0.031885
--0.003318 -0.001693 -0.000159 -0.037918 -0.022625 -0.030503 -0.009554 -0.036841 -0.019616 -0.008378
-0.003737 0.009435 -0.041291 0.026025 0.004493 0.003705 0.010076 0.016568 -0.006795 -0.005094
-0.003355 -0.001776 -0.146711 0.014934 -0.014776 0.025921 0.007671 0.050776 0.014855 0.010987
--0.045019 -0.023991 -0.022925 -0.025566 -0.024415 -0.003953 0.000358 -0.002717 0.009698 -0.014981
--0.046216 -0.050830 0.051989 -0.043989 -0.001614 0.014875 -0.028409 -0.047239 -0.028182 -0.005466
--0.017721 -0.023279 0.041827 -0.050885 0.079538 0.037654 0.035298 0.017769 -0.006058 0.008942
-0.000029 -0.000511 0.001004 -0.004445 0.049191 0.012618 -0.031136 -0.021614 0.019529 0.024107
-0.003830 0.008610 -0.008632 0.075022 -0.059489 -0.041330 -0.036291 -0.011269 0.005060 -0.016165
-0.007312 0.003279 0.023558 0.048968 -0.129370 -0.048318 0.018162 -0.013084 -0.043377 0.012227
-0.001801 0.000012 0.006349 0.002398 -0.067253 0.035633 0.034018 0.013361 0.023054 0.047265
--0.042630 -0.056100 -0.097790 -0.010760 -0.033250 0.125790 0.099250 0.011160 0.084780 0.058650
--0.019973 0.022662 -0.139068 -0.171041 -0.000230 -0.229122 -0.003743 0.020757 -0.087216 0.012486
-0.053818 0.129045 0.081477 -0.068773 0.112682 -0.247727 -0.063682 0.002568 -0.160068 -0.089932
-0.010377 -0.003331 0.142546 0.298108 0.151223 0.161177 0.005838 -0.010708 0.076200 0.016446
--0.085900 -0.151300 -0.057520 0.121000 -0.050900 0.139740 -0.063560 -0.101160 0.078460 -0.004840
-0.050750 0.014933 -0.132117 -0.324917 -0.346233 0.137817 0.165217 0.019550 -0.052717 -0.083317
-0.136606 0.141106 0.047455 -0.064045 -0.171561 -0.111212 0.096333 0.151000 -0.103121 -0.043061
-0.008115 0.018656 0.026500 0.180531 0.147271 -0.167552 -0.046750 -0.065781 -0.035312 -0.020823
--0.075940 -0.094400 0.025850 0.056480 0.176060 0.040370 -0.046940 -0.092550 -0.013380 0.023520
--0.002714 -0.003187 -0.001313 -0.015011 0.025687 0.120121 -0.060648 -0.027819 0.008341 -0.009280
--0.004375 -0.001625 -0.012362 -0.007506 -0.006588 -0.143100 -0.017769 0.028500 0.014188 0.011200
--0.002634 0.005128 -0.038977 0.025535 -0.016279 -0.065273 0.033395 0.007006 -0.002965 -0.017017
-0.006018 0.004974 0.004287 0.009669 0.006989 0.048140 0.068379 0.019904 -0.010853 -0.008096
-0.006892 -0.000575 0.051986 0.020429 0.018042 0.070943 0.028108 0.041382 0.014146 0.017264
--0.001965 0.000791 -0.006287 0.018858 -0.017626 0.046098 -0.015035 -0.004606 0.031154 0.009268
--0.000570 -0.001705 -0.003311 -0.007500 -0.000036 -0.043606 -0.005964 0.006831 -0.035742 -0.052692
--0.002836 -0.006388 -0.018280 -0.007056 -0.004346 -0.105981 -0.018668 -0.028019 -0.104234 -0.044388
-0.017152 0.008455 0.030015 0.073985 0.054455 0.022182 -0.014553 -0.065144 -0.019659 0.009629
--0.002798 -0.003921 0.046545 0.139225 0.090118 0.177197 0.066539 -0.016657 0.131331 0.061472
-0.011862 0.027687 0.003125 0.146787 0.239913 -0.138588 -0.171450 -0.115838 0.118200 0.087762
--0.009185 -0.012352 -0.024759 0.210852 0.268852 -0.341074 -0.371537 -0.369759 -0.147926 -0.069278
-0.018933 0.007017 -0.067800 -0.480050 -0.567567 0.057200 0.195300 0.199500 0.064417 0.075600
--0.004214 -0.026143 -0.011571 -0.217881 -0.161476 0.337000 0.475857 0.415452 0.074048 0.038548
-0.008514 0.005020 0.014385 0.320196 0.392453 0.029324 0.033851 0.017689 -0.005791 0.015095
-0.010763 0.015816 0.031500 0.249092 0.276237 -0.051803 -0.013224 -0.151118 -0.101750 -0.044421
-0.006668 -0.003826 0.060804 0.003234 -0.034375 -0.021832 -0.000967 -0.019250 -0.008935 -0.003609
--0.002211 -0.000725 -0.005763 -0.005243 0.000632 -0.066836 -0.014348 0.002357 0.000591 0.001690
--0.005605 0.000880 -0.040275 -0.032645 -0.017135 -0.082090 0.011020 -0.017120 0.003110 0.008130
--0.001875 -0.000208 -0.006584 -0.005323 -0.004818 0.006117 0.006784 0.001483 0.012628 0.010504
--0.000615 -0.002010 0.002647 -0.009829 0.005752 0.094371 0.006986 0.008042 0.022350 0.017822
--0.002955 -0.002721 -0.000805 -0.016006 0.004377 0.017864 -0.043104 -0.047383 -0.000471 0.005455
-0.003698 0.002401 0.004843 0.007519 -0.004472 -0.022173 -0.033515 -0.033599 -0.003870 -0.007966
--0.003271 -0.003602 0.000071 0.010410 -0.049564 -0.029519 -0.008301 -0.049128 0.055455 0.033857
--0.001424 -0.005076 -0.024946 -0.020087 -0.118783 -0.147848 -0.013478 -0.071717 0.025239 0.137413
--0.003856 0.002040 -0.007057 -0.031000 -0.050080 -0.106523 0.029856 0.020063 -0.127149 -0.039592
-0.009808 0.016400 0.020692 0.036100 0.080000 0.033583 0.041275 0.052942 -0.108642 -0.141492
--0.013506 -0.004801 0.048712 0.004801 0.169462 0.163064 0.086705 0.064981 0.085577 0.044346
-0.005885 0.010123 -0.002269 -0.042831 -0.135677 0.000177 0.009254 -0.008862 0.086708 0.114177
--0.007121 -0.005667 -0.052201 -0.087454 -0.229046 -0.073264 -0.028615 -0.063874 -0.074523 -0.056109
--0.049612 -0.043776 0.005633 0.066908 0.386949 0.207245 -0.096153 -0.087255 -0.098551 -0.042122
-0.007417 -0.004810 0.098393 0.386179 0.592643 0.214940 -0.196488 -0.131786 -0.034714 -0.011512
--0.039753 -0.068063 -0.044139 0.172696 0.291297 0.231494 0.037006 -0.003000 0.069677 0.040101
--0.076897 -0.115192 -0.164244 -0.048462 0.125154 0.015103 -0.129820 -0.152833 -0.040231 0.013064
-0.062543 0.092000 -0.038529 -0.456600 -0.711672 -0.453143 0.028471 0.066129 -0.045057 -0.016129
-0.085650 0.118983 0.076150 -0.181017 -0.532267 -0.311950 0.212300 0.227583 0.068900 0.055150
--0.079574 -0.110382 -0.103191 -0.004721 0.383971 0.480191 0.223912 0.217191 0.221441 0.080250
--0.203395 -0.298263 -0.258947 0.024289 0.287579 0.237789 0.158868 0.104632 -0.021763 -0.043158
-0.100903 0.133161 0.124935 0.148613 0.067919 -0.139726 -0.092081 -0.154000 -0.233113 -0.111645
-0.057020 0.070461 0.096275 0.126186 0.191559 -0.048108 -0.080873 -0.009735 -0.077059 -0.021010
-0.007764 0.002397 0.008580 0.006713 -0.019385 0.072724 -0.019971 0.058310 0.057144 0.011172
--0.004052 -0.006414 0.079121 -0.038759 -0.023328 -0.018448 0.011302 -0.021043 0.053802 0.051198
--0.001127 0.003290 -0.031571 -0.010067 -0.020996 -0.146488 -0.024313 -0.085897 -0.010869 -0.014409
--0.019683 -0.027793 -0.107317 -0.037238 -0.071628 -0.157994 -0.036585 -0.098585 -0.043610 -0.030537
--0.001324 -0.002370 -0.015639 -0.006954 -0.026880 0.109000 -0.019648 0.111333 0.004102 -0.002296
-0.005493 0.011118 0.054603 0.038809 0.015132 0.141662 0.049132 0.167103 0.102971 0.048066
--0.001552 0.001035 -0.004058 0.001924 0.022355 -0.071901 0.076360 -0.006669 0.002762 0.016634
--0.007608 -0.000366 -0.014414 -0.029247 0.020247 0.002349 0.039441 -0.079769 0.022602 0.010742
--0.001919 -0.009517 0.010587 -0.045250 -0.037279 0.051634 -0.036988 -0.028669 0.035593 0.021134
--0.004728 -0.003076 -0.007008 -0.015100 -0.046736 0.001164 -0.079296 -0.003848 -0.002736 0.002888
-0.010773 0.006101 -0.028490 0.059348 0.067010 0.037364 -0.014722 0.009318 -0.014894 -0.020753
--0.001348 -0.009366 -0.005304 -0.083795 -0.148420 0.090857 0.111509 0.016080 0.045036 0.042446
--0.027104 -0.020348 -0.047616 -0.170732 -0.205262 -0.218146 0.019841 0.037591 -0.059543 -0.023366
-0.037714 0.034929 -0.031821 0.084036 0.091500 -0.331589 -0.048232 -0.067607 -0.199339 -0.148946
-0.101633 0.096117 0.068233 0.244700 0.213000 0.075525 0.067242 0.043400 0.074900 0.077475
--0.048125 -0.009080 0.114107 0.048491 0.141161 0.373170 0.118625 0.161348 0.290830 0.153545
-0.000514 0.023458 0.085486 -0.112431 0.008097 0.088736 0.038972 0.075417 0.064833 0.056292
--0.010239 -0.007261 0.026193 0.153080 0.028375 -0.105784 0.014091 0.026852 0.011250 0.002659
-0.034875 0.033429 -0.149875 0.012982 -0.109929 -0.059018 0.009964 -0.029286 -0.068214 0.009161
--0.031942 -0.088212 -0.278423 -0.359308 -0.066317 -0.033404 -0.091423 -0.136019 -0.255087 -0.170135
--0.008269 -0.005857 -0.024891 -0.139597 -0.014122 -0.013319 -0.013336 -0.008626 -0.026655 -0.011374
-0.043679 0.072538 0.216085 0.246538 0.023538 0.087802 0.134132 0.202340 0.090613 0.045934
--0.032072 -0.054289 0.007902 0.253350 0.324722 0.247443 0.209340 0.128644 0.000160 -0.000515
--0.112767 -0.219667 -0.350700 -0.217950 0.125500 0.046783 0.049683 -0.030217 -0.252500 -0.136333
-0.064419 0.061927 0.054710 -0.161734 -0.606532 -0.406718 -0.192944 -0.139742 -0.167177 -0.115710
-0.178280 0.306480 0.410660 0.100420 -0.313060 -0.213480 -0.003460 0.165680 0.231740 0.118580
--0.014806 0.004917 0.063046 0.220991 0.495796 0.494759 0.068194 0.073806 0.064870 0.000398
--0.112880 -0.263100 -0.433440 -0.176090 0.011180 -0.127630 -0.204240 -0.209740 -0.221260 -0.105410
--0.104924 -0.232169 -0.436907 -0.334288 -0.310110 -0.502729 -0.240212 -0.297670 -0.090415 -0.034559
-0.005170 0.027740 0.076850 0.087880 0.104610 0.165770 0.085110 0.150810 0.133040 -0.051800
-0.041011 0.066130 0.132815 0.128141 0.136815 0.221848 0.144435 0.132793 -0.133435 -0.082902
--0.000008 -0.001043 -0.000791 0.003189 0.010795 0.014925 -0.003732 0.028343 -0.063405 -0.013760
-0.006713 0.003713 0.004262 0.032354 -0.019659 0.021939 -0.088531 0.010799 0.074707 0.019165
-0.001586 0.000657 0.005131 0.004123 -0.002724 0.017817 0.017194 -0.058593 0.031269 0.010526
-0.000142 -0.001939 0.002835 -0.002830 0.001222 -0.008038 0.023458 -0.035939 -0.041778 0.030915
--0.004182 -0.004482 -0.001158 -0.020227 0.001848 -0.009094 0.014106 -0.002021 -0.077539 -0.035212
-0.000746 0.000717 -0.003783 0.000402 0.000610 0.006292 0.006237 0.011543 -0.029697 -0.047113
-0.003366 0.002763 0.006305 0.014268 -0.004097 0.008347 -0.012582 0.019737 0.028305 0.016358
-0.001207 0.000553 -0.002813 0.002957 0.012697 -0.010987 -0.016720 -0.008860 0.064260 0.059973
-0.006075 0.004595 0.001972 0.008115 0.023706 -0.038964 0.013794 0.040556 0.052433 0.053036
-0.010793 0.014598 0.025674 0.034000 0.039022 0.037065 0.078924 0.080630 0.055902 -0.111283
-0.002763 -0.000026 0.001612 0.014599 0.017428 0.075914 0.030697 -0.001882 -0.057717 -0.087605
--0.006159 -0.008971 -0.001376 0.014824 0.047600 0.077153 -0.061418 -0.099406 -0.054382 -0.007141
--0.002724 -0.005586 -0.003810 -0.018448 -0.021974 -0.031517 -0.075543 -0.072026 -0.057638 0.056345
-0.001583 0.003090 -0.009226 0.005545 -0.011274 -0.066996 0.002981 -0.006143 0.058823 0.033195
--0.001360 -0.000728 -0.000664 -0.004356 0.010088 0.015076 -0.038940 -0.007928 0.026688 -0.015752
-0.001356 0.000406 -0.002772 -0.000722 0.001000 0.042639 0.014472 0.041439 -0.151728 -0.027711
--0.002087 -0.001855 0.000855 -0.012326 -0.001831 -0.027888 0.082831 0.085479 -0.068719 -0.011095
-0.006795 0.010609 -0.014205 0.001532 -0.020141 -0.064622 0.099942 0.071673 0.128462 0.037840
--0.005100 -0.002653 -0.002141 0.004865 -0.013000 -0.026224 0.008359 -0.009406 0.147859 -0.014576
-0.000990 0.000720 -0.019890 0.015520 0.015780 0.065610 0.009120 -0.005060 0.024090 -0.068260
--0.015131 -0.017619 -0.006091 -0.002415 0.035392 0.099494 -0.032011 -0.043045 -0.082557 -0.069989
--0.001912 -0.002494 0.000967 -0.013158 0.015645 0.027661 -0.039448 -0.011015 -0.068873 -0.040970
--0.008172 -0.007994 0.016374 -0.005770 0.013971 0.143707 0.057782 0.154667 -0.024489 -0.032862
--0.002478 -0.002809 -0.003743 -0.013043 0.006426 0.026222 0.108548 0.113922 -0.014513 0.044670
--0.013655 -0.011474 -0.035052 -0.023284 -0.064345 -0.294302 -0.123112 -0.162991 -0.028440 0.046147
-0.042238 0.039548 -0.039762 0.061893 -0.027595 -0.481012 -0.170083 -0.182405 -0.015714 0.016083
-0.021930 -0.002260 0.002730 0.025490 -0.144510 -0.221450 0.210810 0.117630 -0.005800 0.001040
-0.011939 -0.020348 -0.020152 -0.094227 -0.074727 0.544258 0.376879 0.151182 0.043212 0.012591
--0.009926 0.005296 0.130278 0.127019 0.390537 0.736463 0.079185 -0.016667 0.047204 0.031722
-0.024109 0.098793 0.157228 0.160630 0.305587 0.077500 -0.044663 -0.021565 0.041826 0.058217
-0.098042 0.118000 0.095875 0.132083 -0.367792 -0.595708 0.016625 0.114667 -0.016917 0.037125
-0.050713 -0.005981 -0.160546 -0.155537 -0.266611 -0.589306 -0.117787 -0.133130 -0.226731 -0.129278
--0.030696 -0.050411 -0.078143 -0.150036 0.166679 0.285929 -0.030393 -0.076875 -0.187661 -0.067750
--0.040712 -0.055515 0.014053 0.008727 0.204599 0.354780 0.142651 0.053394 -0.010598 0.010515
--0.018292 -0.014177 0.062723 0.075662 -0.012054 0.053954 0.138308 0.083154 0.107300 0.035738
--0.005433 -0.004732 0.000970 -0.081140 -0.009726 -0.014518 -0.006689 -0.016537 0.153177 0.056726
--0.014786 -0.010464 -0.004429 -0.127274 -0.020435 -0.002827 -0.018167 -0.028780 -0.179607 -0.097238
--0.004944 -0.012112 -0.000851 0.012478 -0.019549 -0.018810 -0.004642 0.002545 -0.190019 -0.073746
-0.004615 0.001797 -0.001236 0.002152 0.003787 0.003118 0.029959 -0.004713 0.116226 0.084135
--0.003201 0.001244 -0.021671 -0.050680 -0.011709 -0.020637 -0.023419 -0.010748 -0.000081 0.005551
-0.004291 0.004296 0.001937 0.049985 -0.010927 -0.020927 0.027223 -0.019282 -0.057456 -0.035053
-0.006867 0.013171 0.052506 0.127089 -0.004405 0.010785 0.030981 0.055316 0.200930 0.084462
-0.000332 0.000889 -0.000630 -0.011712 -0.012842 0.002582 -0.027323 -0.016494 0.061006 0.013437
--0.017842 -0.010411 -0.016856 -0.113084 -0.051505 -0.074698 -0.049980 0.002624 -0.147995 -0.060614
--0.036365 -0.026548 -0.080905 -0.116810 -0.079563 -0.062937 0.068413 0.000675 0.060825 0.078468
--0.000642 0.003167 0.017556 0.009951 0.019716 0.121920 0.045111 0.036506 0.213420 0.138839
-0.015230 0.063257 0.209189 0.063743 0.028608 0.086784 -0.036811 0.032635 -0.111338 -0.090189
--0.071484 -0.125459 -0.151557 -0.104164 -0.156861 -0.199836 -0.116467 -0.145934 -0.331148 -0.258279
--0.104328 -0.205948 -0.366345 -0.163638 0.097328 0.103603 0.062069 0.003328 0.134397 0.047690
-0.142062 0.272494 0.418216 0.402957 0.239265 0.361722 0.400809 0.415210 0.490099 0.290463
-0.062518 0.060625 0.029625 -0.063321 -0.003339 -0.180411 -0.167482 -0.188821 -0.273036 -0.022661
--0.098154 -0.250231 -0.414452 -0.373673 -0.194779 -0.231692 -0.294962 -0.453923 -0.319865 -0.125365
--0.007230 0.011836 0.064033 0.217025 0.035811 0.101779 0.161926 0.146148 0.373197 0.127779
--0.268893 -0.217893 0.036429 -0.093786 -0.039250 -0.032214 0.048214 0.063964 0.121286 0.025714
--0.043619 -0.076964 0.029607 -0.094726 -0.067964 0.057976 -0.259952 -0.170345 -0.354250 -0.393679
-0.062336 0.095031 0.158016 0.156297 0.124312 0.194844 0.027148 0.027156 -0.003141 -0.022398
-0.156955 0.173545 -0.024455 0.053136 -0.065152 -0.107318 0.172803 0.131045 0.169530 0.098833
-0.008745 -0.001968 -0.184989 -0.030074 -0.031723 -0.156160 -0.077532 -0.024628 0.109638 0.068340
--0.080500 -0.098097 -0.008274 -0.001597 0.079984 -0.033097 0.035452 -0.032226 0.062032 0.050161
--0.033098 -0.046461 -0.038627 -0.045686 -0.064078 0.112255 0.157373 0.012951 -0.013814 -0.034716
--0.002198 -0.001299 0.001858 -0.008096 -0.008864 -0.015204 -0.005824 -0.006364 -0.128488 -0.025062
-0.005184 0.012857 0.086684 0.007449 0.045592 -0.040571 -0.117163 -0.018327 0.014398 0.046449
-0.011670 0.005106 0.024638 0.024482 0.001963 0.051353 -0.008679 0.007950 0.065385 0.069147
--0.000672 -0.000181 -0.011690 -0.029422 -0.094440 0.020103 0.127216 0.013000 -0.017690 -0.034957
--0.014961 -0.018844 -0.017000 -0.074578 -0.100883 0.000786 0.059623 0.070883 0.022045 0.008584
--0.087510 -0.108625 -0.099010 -0.093779 -0.084548 -0.116423 -0.082865 0.037308 -0.028875 -0.039702
--0.002520 -0.008364 -0.030081 -0.003540 -0.056641 -0.099884 -0.014818 -0.049288 -0.198687 -0.157838
-0.014619 0.018000 0.015774 0.005071 0.089286 0.002226 -0.110857 -0.062500 -0.145190 0.041226
-0.011560 0.014190 0.036976 0.061286 0.038405 0.131119 -0.091048 -0.062786 0.205964 0.233048
-0.001085 0.009457 0.006646 0.006585 0.006970 -0.004061 -0.033701 -0.034732 0.287866 0.050652
-0.002116 0.010488 -0.016663 -0.016360 -0.036047 -0.131337 -0.038581 -0.072116 0.051326 -0.118605
--0.039740 -0.027894 0.002385 -0.025692 -0.095519 -0.084798 -0.054308 -0.020077 -0.014587 0.053596
--0.028877 -0.029500 -0.004877 -0.072575 0.063085 0.133991 0.072311 0.060868 -0.173170 -0.008858
--0.007779 0.000314 0.015860 0.002360 0.076140 0.014070 0.151907 0.156849 -0.270023 -0.163279
-0.115757 0.153176 0.100703 0.036608 0.027851 -0.111297 0.059257 0.088878 -0.027365 0.003689
-0.005651 0.005314 0.013628 0.085128 -0.029733 -0.023942 -0.016215 -0.014733 0.099430 0.086942
--0.007665 -0.008813 -0.007659 -0.007500 0.015352 0.045126 -0.018769 0.006297 0.070022 0.052429
--0.002822 -0.000780 -0.009629 -0.000171 0.009027 -0.026959 -0.001551 -0.028615 0.019800 0.012029
--0.001954 -0.001802 0.000660 -0.003731 -0.015753 -0.035785 0.020177 0.008323 -0.000228 -0.003408
--0.002350 0.000324 -0.014718 -0.030510 0.010503 -0.024710 0.015715 0.018826 -0.008987 -0.000044
--0.004361 -0.003962 -0.002820 -0.055244 0.005589 0.031332 -0.002908 0.005184 -0.002968 -0.007528
--0.001146 -0.000782 -0.001478 0.003246 -0.028160 -0.003854 0.001311 -0.028498 0.000378 -0.009242
-0.004580 0.003674 -0.005045 0.055969 0.002444 -0.005507 -0.006308 -0.009596 -0.001379 -0.004007
-0.006414 0.001939 0.010273 0.019871 0.013050 0.041842 -0.000032 -0.003403 0.010273 0.014187
-0.002212 -0.005414 0.023106 -0.008332 0.012479 0.008702 -0.010493 -0.009637 0.001695 0.006010
--0.009308 -0.004902 -0.016013 -0.001363 0.011299 -0.044590 -0.053124 -0.038372 -0.001936 0.012419
--0.000102 0.000734 -0.003380 0.011482 0.028570 0.003627 0.006918 -0.002998 -0.002077 -0.006086
-0.004382 0.002838 0.008794 0.003917 0.038285 0.014772 0.019513 0.038794 -0.013570 -0.013781
-0.006551 0.004193 0.009784 0.063635 0.027517 0.035959 0.006872 0.004429 0.040520 0.007429
--0.004698 0.004864 -0.039346 0.032673 0.012821 0.017525 -0.002451 -0.019333 0.035525 0.032802
--0.000776 0.016872 -0.053128 -0.031244 0.012321 0.012840 -0.010603 -0.005186 -0.007372 -0.005462
--0.014492 -0.015811 -0.018432 -0.057538 -0.088614 0.042636 -0.024530 -0.022364 -0.077364 -0.009705
--0.037273 -0.056791 0.010691 0.033900 -0.158409 -0.052882 -0.049991 -0.083382 0.024091 0.016627
--0.003157 -0.001150 -0.006483 0.004017 -0.014930 -0.073450 -0.003423 -0.054793 -0.009897 -0.014997
-0.014386 0.010920 -0.034102 -0.047693 0.082648 -0.058148 -0.015705 0.007443 -0.147352 -0.122011
-0.002500 0.001875 0.024760 -0.016708 0.061958 -0.056042 0.034615 0.108573 -0.007490 0.024563
-0.012351 0.010014 0.007973 0.024291 -0.019041 -0.043709 -0.012095 0.121439 0.036466 0.049230
-0.000342 -0.000125 0.000776 0.030243 -0.027276 -0.005605 0.006342 -0.026217 0.046211 -0.066461
--0.003454 0.004880 -0.054972 -0.038722 -0.088667 0.051815 0.014176 -0.070306 0.071944 -0.007667
--0.008877 -0.018849 -0.016255 -0.100170 -0.144396 0.187594 0.039142 0.078123 0.016160 -0.023142
-0.012598 0.000902 0.022484 0.006311 -0.010484 0.184672 -0.039934 -0.033164 0.040221 0.051902
--0.000157 -0.000491 0.000109 -0.001157 -0.022535 -0.032426 -0.024443 0.041774 0.042700 0.022378
-0.000731 0.002894 0.002750 0.016692 -0.009606 -0.304721 0.004077 0.106317 -0.040837 -0.032433
-0.008609 0.013482 0.010973 0.051173 0.078527 -0.173145 -0.047255 0.006055 -0.091164 -0.053864
-0.016363 0.016157 0.033588 0.075637 0.102637 0.065765 -0.162118 -0.059931 -0.050814 -0.041520
-0.004143 -0.000714 0.027850 0.108086 0.137864 0.168607 -0.114871 -0.078593 0.042264 0.012364
--0.001169 -0.007077 -0.012261 0.119070 0.095099 -0.001958 -0.023824 -0.031310 0.093606 0.054282
--0.112548 -0.105355 0.047371 0.147452 0.069323 0.047242 0.084258 0.088790 0.062032 0.030806
--0.018911 -0.003573 -0.015879 -0.245605 -0.005565 0.003339 -0.007403 0.014379 -0.003153 0.006710
-0.001047 0.019102 -0.123906 -0.161578 -0.133852 -0.041984 0.001398 -0.022477 0.024969 0.002875
-0.151359 0.136875 0.153422 0.150484 0.008484 0.038781 0.214688 0.096250 -0.102266 -0.085531
-0.013304 0.012837 0.096924 0.142239 0.005913 0.003272 -0.019750 -0.008076 -0.127609 -0.040565
--0.010875 -0.004243 -0.049396 -0.138590 -0.077472 -0.059028 -0.418618 -0.122486 -0.080278 -0.135271
--0.008542 -0.004621 -0.001826 -0.039784 0.015626 0.005153 -0.097305 -0.013795 0.057232 -0.032000
-0.028654 0.026654 0.026269 -0.017513 -0.078115 0.057179 0.510628 0.158269 0.092321 0.133692
--0.015689 -0.021613 -0.049745 -0.018491 -0.062717 -0.039151 0.229198 -0.049377 0.018453 0.029877
--0.022100 -0.033433 0.046650 0.159933 0.111100 -0.107133 -0.188417 0.076250 0.060567 0.046183
-0.022317 0.008769 0.035423 0.035952 -0.016567 -0.103587 -0.377731 0.013683 0.075269 0.005096
--0.010863 -0.018443 -0.020137 -0.095571 -0.120325 -0.048316 -0.158090 -0.123802 -0.078557 -0.083217
-0.009895 0.031018 0.059974 0.107088 0.088939 0.144623 0.377421 0.013728 -0.001535 0.000816
-0.014911 0.040911 0.033060 0.070518 0.073375 0.198756 0.254149 0.091732 0.088583 0.072976
--0.029500 -0.019702 -0.059714 -0.027310 0.045095 0.050702 -0.061143 -0.012667 0.033417 0.067500
--0.019462 -0.018863 -0.011104 -0.041066 -0.024286 -0.113115 -0.123242 -0.059560 0.033538 0.013110
--0.004582 -0.003159 0.002644 -0.022000 0.000577 -0.091260 -0.062649 -0.004428 -0.029139 -0.006457
--0.009761 -0.020489 0.108693 -0.003614 0.033273 -0.001443 -0.007227 0.061182 -0.081250 -0.036227
-0.002879 0.001188 0.008374 0.009087 -0.008248 0.022235 0.020351 -0.001260 -0.009347 -0.011696
-0.001505 0.003924 -0.004460 0.008475 0.002298 0.002242 0.007455 0.019995 0.054848 -0.034742
-0.004005 0.003559 -0.012050 -0.000658 0.013964 0.005748 -0.065086 0.026680 -0.006144 -0.006982
--0.007611 -0.007382 -0.007046 -0.011918 -0.024854 -0.007818 -0.125982 -0.096900 0.032779 -0.000204
-0.000788 -0.000888 0.006073 -0.004958 0.001085 -0.026469 -0.030473 -0.090969 0.022712 0.013408
--0.000191 0.001113 0.000907 0.027758 0.021428 0.011454 0.140706 -0.003613 -0.004825 0.004711
-0.007053 0.004000 0.008876 0.012920 0.010690 0.030664 0.043597 0.041093 -0.053562 0.012332
--0.003291 -0.004170 0.021635 -0.053326 0.003170 -0.006486 -0.016149 0.001355 0.001730 0.007968
--0.000113 -0.000435 0.008659 -0.005267 0.001118 0.003918 0.006401 0.016138 0.002400 -0.001376
-0.000301 0.000564 -0.002722 0.008336 -0.007193 0.001900 -0.022967 -0.005035 0.000973 0.000444
-0.001097 0.005055 -0.004500 -0.000024 -0.071517 -0.048776 -0.006762 0.004786 0.011883 -0.000155
--0.003252 -0.000345 -0.007000 -0.005248 -0.032965 -0.019226 0.093310 0.015168 0.036695 0.039195
-0.002221 0.000884 -0.021471 0.027773 0.081360 0.082134 -0.016448 0.007401 0.064064 0.014727
--0.000250 -0.003789 0.004500 0.014852 0.123883 0.069969 0.050391 -0.010133 0.034609 0.116531
--0.081438 -0.132734 -0.121688 -0.060547 -0.115609 -0.053234 0.240844 0.008266 -0.147344 -0.025813
--0.030973 -0.018108 -0.017000 -0.084365 -0.073959 -0.123311 0.034581 0.009784 -0.317514 -0.202459
-0.009861 -0.017306 0.063944 0.228806 0.226694 0.057333 -0.632389 -0.398083 -0.032667 -0.074139
-0.067204 0.028481 0.055148 0.144704 -0.117722 -0.015944 -0.265167 -0.164741 0.361519 0.218222
--0.013508 -0.006525 -0.049347 -0.111754 -0.120322 -0.097568 0.197381 0.087068 0.021729 0.041686
--0.022805 -0.014208 -0.048188 -0.098214 -0.011883 -0.017617 0.149987 0.057383 -0.156922 -0.078208
--0.000310 -0.008580 0.028971 -0.080109 -0.005517 0.029184 0.009534 0.024931 -0.052086 -0.053115
-0.000418 -0.001366 -0.014228 -0.055767 -0.059996 0.048978 0.030185 0.036983 -0.000711 0.006487
--0.007821 -0.005150 -0.009073 -0.030996 0.025394 0.021012 0.038065 0.059358 -0.004679 0.004785
--0.022178 -0.020747 -0.033086 -0.006236 0.112184 0.088333 0.024655 -0.028759 -0.020874 -0.011971
--0.000537 0.000945 -0.019799 0.034640 -0.010470 0.070128 -0.019110 -0.073213 0.013030 -0.005274
-0.052197 0.053227 0.054106 0.093258 -0.165136 -0.204417 -0.040000 -0.025205 0.080470 0.037159
--0.002116 0.004306 -0.010926 0.000926 -0.016278 -0.260074 -0.021583 -0.022000 -0.015727 -0.004690
-0.003129 -0.001082 0.001314 0.008206 0.039387 0.145510 -0.006959 0.032474 -0.015474 0.006119
--0.000679 0.009962 0.035972 -0.052443 0.108255 0.271255 -0.011736 0.030972 0.014038 0.010783
-0.000118 -0.005253 -0.008446 -0.050000 0.060849 0.071817 0.018253 0.017984 -0.014731 -0.015134
--0.000931 -0.003356 -0.013600 0.002400 -0.090169 -0.031413 0.026006 -0.067425 -0.007369 -0.015650
-0.009578 0.014375 0.061492 0.030234 -0.151516 -0.143352 -0.033188 0.011844 -0.041852 -0.056078
-0.010290 0.012466 0.031500 0.049949 0.022648 -0.091051 -0.012261 -0.008489 0.022920 0.019398
-0.002930 0.003994 -0.011576 0.052740 0.037962 -0.148203 -0.000063 -0.083582 0.023089 0.033424
-0.026090 0.037634 0.028933 0.043896 -0.083530 -0.141007 -0.054851 -0.058037 0.018731 0.039052
--0.008333 0.001096 -0.124939 -0.084833 0.036719 -0.020377 -0.092868 -0.083518 -0.001351 -0.000474
--0.072463 -0.048667 -0.051972 -0.038944 0.179315 0.152667 -0.154870 -0.091018 -0.127444 -0.093093
--0.023201 -0.038718 -0.021356 0.015034 0.191230 0.160759 0.032052 0.042908 -0.086609 -0.048845
-0.032660 0.022500 0.086021 0.168069 0.058806 0.057368 0.129528 0.095965 0.141097 0.083097
-0.028906 0.062302 0.181566 0.260613 -0.115170 -0.100415 0.103387 0.034594 0.228151 0.148509
--0.007206 0.000882 -0.017581 -0.046426 -0.101493 -0.047897 0.062581 -0.040309 0.026324 0.011176
--0.021840 -0.016360 -0.139930 -0.184890 0.042730 -0.043850 0.081070 -0.000750 -0.074710 -0.017290
--0.025636 -0.009791 -0.063827 -0.096209 0.052973 0.028055 0.022736 0.032509 -0.015855 -0.026173
-0.008083 0.004481 0.022526 0.062571 0.027295 0.012904 -0.046974 -0.007346 0.013615 0.047147
--0.063062 -0.084677 -0.128521 -0.133771 0.248875 0.309917 0.079062 0.060417 -0.035750 -0.006000
--0.035389 -0.064722 -0.112444 -0.102708 0.250903 0.348833 0.334000 0.181806 -0.081458 -0.066958
-0.196828 0.304891 0.394312 0.185578 -0.172781 -0.311922 -0.165938 -0.110766 -0.141313 -0.045609
-0.049304 0.066235 0.057745 -0.057539 -0.478784 -0.518245 -0.457784 -0.401853 0.041029 0.052176
--0.215232 -0.372821 -0.503357 -0.402196 -0.094429 0.080214 0.064946 -0.022000 -0.024125 -0.035571
-0.031287 0.061550 0.034500 -0.011600 0.378344 0.343594 0.182544 0.233300 0.066463 0.019875
-0.078412 0.126684 0.140368 0.083833 0.148386 0.075070 0.071588 0.153947 -0.020860 -0.017070
--0.012571 -0.010048 -0.069936 -0.006063 0.014492 -0.032087 -0.059865 -0.132778 -0.052754 -0.052254
-0.011247 0.013521 0.003521 0.028699 0.023842 -0.073527 0.004178 0.092274 -0.029678 -0.021856
-0.007302 0.014167 0.088468 0.020881 0.023278 0.014484 0.028524 0.111770 0.017849 0.031413
--0.010462 -0.016330 0.014849 0.000877 0.079708 0.074057 0.066698 -0.087868 0.022236 0.007472
-0.005718 0.001076 0.004672 0.008794 0.064248 0.030328 0.029727 0.011664 0.013803 0.021239
--0.010291 -0.000664 -0.045530 0.047284 0.030799 0.005560 0.042515 0.077672 0.048612 0.026590
--0.002549 -0.001993 -0.008345 -0.025069 -0.004023 -0.012214 0.020914 0.001046 0.013234 0.043602
--0.012025 -0.006348 -0.004696 -0.091377 0.019564 -0.007250 0.027686 -0.012740 0.000010 0.013956
--0.004826 -0.003963 -0.014659 -0.004307 0.008578 0.024811 -0.002893 -0.029663 -0.000885 -0.001778
-0.004443 0.005004 0.006916 0.038592 -0.013126 0.006218 -0.061294 -0.063542 -0.013172 -0.013206
-0.005406 0.003194 0.002928 0.025270 -0.016712 -0.005115 -0.039640 -0.002165 -0.038496 -0.021619
-0.003625 0.001327 0.010344 0.020050 -0.000505 0.004615 0.015089 0.040858 -0.005901 -0.007690
--0.001634 -0.000171 -0.000049 -0.010739 0.021666 0.012590 0.009888 0.009773 0.029907 0.028388
--0.000422 -0.000967 0.000594 -0.016157 0.003204 0.006825 -0.013016 -0.005873 -0.028749 -0.010878
--0.000617 0.000162 -0.008543 0.002525 -0.017168 -0.008345 -0.019513 -0.030891 -0.034013 -0.044150
--0.000729 -0.000051 -0.007470 -0.000436 -0.005617 -0.015837 0.001477 -0.003394 -0.012528 -0.013152
-0.000965 -0.000105 0.006930 -0.010845 0.000073 -0.028816 -0.005041 -0.003307 0.005307 0.013374
-0.001742 0.001509 0.001773 0.027170 0.000170 -0.038142 0.015288 0.016573 0.018052 0.010894
-0.003766 0.005500 0.008172 0.022156 0.013258 0.054641 0.025641 0.050242 0.116070 -0.069453
-0.001413 -0.004971 0.015616 0.008233 0.005977 0.094279 0.079192 0.011983 0.094453 0.092570
-0.088679 0.110083 0.077655 -0.037679 -0.029762 -0.119024 -0.133440 -0.004714 -0.083762 -0.028417
-0.015284 0.014784 -0.039060 -0.035043 -0.043172 -0.221310 -0.091103 -0.049414 -0.257957 -0.108966
--0.125500 -0.141045 -0.110545 0.047758 0.067258 -0.086015 -0.076197 -0.045561 -0.124576 -0.110030
--0.202641 -0.210422 -0.122672 -0.091016 -0.107922 -0.096672 -0.251766 -0.055625 0.013422 -0.017750
-0.034361 0.005583 0.011153 -0.199556 -0.239333 0.191097 0.059236 0.111458 0.252347 0.063792
-0.087687 0.088979 0.053458 -0.098812 -0.154812 0.228188 0.348062 0.145396 0.277583 0.182979
-0.045933 0.049167 0.007767 0.136717 0.118083 -0.294317 0.055150 -0.065883 0.103700 0.124733
--0.046137 -0.041975 0.011087 0.095025 0.077200 -0.097212 -0.192937 -0.093737 -0.196788 -0.178563
-0.031244 0.009633 0.042856 0.106978 0.120600 0.173856 -0.140756 -0.133022 -0.293156 -0.227689
--0.060940 -0.059520 -0.037930 -0.019450 0.054650 0.090280 0.081460 0.069270 -0.048150 -0.108680
-0.023337 0.038477 -0.022384 -0.108930 -0.156349 -0.175465 0.237535 0.129151 0.195698 0.203360
--0.041489 -0.027362 0.084543 0.021723 0.089798 0.090213 0.032862 0.058319 0.166862 0.162117
--0.033176 -0.027882 0.078941 -0.084382 -0.081794 0.225485 -0.154750 -0.008044 0.080103 0.043088
-0.039200 0.031838 0.026546 0.123977 -0.115923 -0.186231 -0.195354 -0.111400 -0.092485 -0.091885
-0.105263 0.128645 0.092289 -0.024132 -0.193303 -0.287118 -0.122645 -0.101132 -0.319566 -0.245329
-0.021955 -0.002205 -0.036000 -0.044432 0.066386 -0.104455 0.027341 0.047614 0.033909 -0.040545
-0.016083 0.049202 0.012119 0.055429 0.046810 -0.080143 0.004726 0.021857 0.320440 0.337369
--0.015130 -0.019050 -0.008980 -0.014840 0.071910 0.002050 0.023410 -0.053970 0.123670 0.238070
--0.012875 -0.002104 0.068312 0.157250 0.052896 0.140771 0.011271 0.007021 -0.286354 -0.268750
--0.009167 0.002833 0.127267 0.245767 0.038667 0.057167 0.038167 0.036733 -0.090267 -0.283567
--0.111673 -0.135865 -0.179144 -0.031587 -0.000356 -0.077615 0.089760 0.019260 0.026135 0.020587
--0.095335 -0.245500 -0.413513 -0.452595 -0.267405 -0.350696 -0.306392 -0.165956 -0.365291 -0.259848
-0.017043 0.074424 -0.018924 -0.361609 -0.203250 -0.240739 -0.145098 -0.086500 -0.210696 -0.137598
-0.124238 0.207238 0.284440 0.252714 0.202845 0.164381 0.010536 0.089786 0.383036 0.251000
+++ /dev/null
-10 512
--8.250528 28.414351 28.947056 -22.260431 -20.641552 -23.655972 33.499699 29.162037 -26.777473 20.152264
--13.087674 -29.244776 28.531864 1.223712 -17.642572 -29.978474 10.884624 -23.874582 29.987656 30.394098
--29.912476 16.450739 -17.856684 21.637835 -26.373550 28.072887 -28.736387 -30.523342 -26.430317 5.712189
-26.232023 17.242741 24.208025 29.041113 23.456097 26.209288 -20.043627 4.131552 30.379368 -30.294384
-29.174519 26.290936 -26.386543 26.420618 30.329287 -27.889307 1.440385 -29.503519 -25.965733 13.266431
-26.815336 21.980131 -23.962013 26.248177 22.603453 -26.797499 24.757118 24.917711 -21.201101 -31.104151
-26.990334 30.932030 29.902292 -26.111679 10.720449 27.045002 -30.309986 -25.548256 -12.764328 15.942853
--27.131104 7.627721 -23.845989 -24.196527 31.534019 21.284435 2.196042 26.895460 -29.873121 31.457081
-23.783720 31.103455 -16.321165 28.371029 27.756580 -22.705223 28.902239 12.486597 -24.326632 17.364750
-26.624371 29.318468 12.003039 22.658562 28.986195 18.075884 -27.618345 27.107302 -24.388067 -22.760424
-13.515237 -26.350586 25.129314 -30.786650 32.847569 -30.016973 -24.524342 -22.618462 25.237829 -11.466196
--7.106867 17.136097 3.030111 -16.934315 -29.622986 26.248684 24.710110 -9.607081 34.604813 -28.588524
-15.662686 -27.542521 28.252190 -29.866125 -33.910301 27.976837 6.867967 -28.312788 -10.601373 -21.302893
--10.193929 14.391588 24.278387 -28.975214 28.665323 30.877426 25.230631 22.649166 34.657333 12.617115
-27.801043 -6.528720 29.821329 -26.306427 31.756905 19.847202 -28.467939 -21.040308 26.433147 22.401430
-30.631275 24.535563 31.284803 9.835046 -9.955822 -21.007423 -28.907034 -6.312805 31.747091 -20.082104
--23.180269 27.280735 -1.648219 18.616158 -28.962486 16.385414 27.848301 30.031059 -2.877421 30.454214
-28.448109 19.146063 30.305185 -21.223429 -28.729210 4.121464 -32.124985 16.542374 26.426540 25.656050
--17.137257 29.191708 30.093775 15.418388 -26.740789 4.192141 30.161688 -20.539837 -27.132601 30.135859
--25.917549 -22.641289 24.594221 13.821900 -22.764513 34.653595 25.676662 -2.283436 -28.713104 21.475290
--34.803772 16.627371 24.532631 0.507513 -0.351332 -29.709391 -11.731549 26.970554 30.765701 -17.942686
--21.305920 16.795202 -8.171767 4.816957 -32.731911 29.083702 -15.778113 27.838266 -35.286331 -2.821167
-25.230614 8.306693 30.379696 9.017179 -27.834126 24.510019 29.685558 -29.855885 -24.964121 22.693756
--24.019381 -24.911600 29.932642 26.527115 24.229420 -25.979359 -24.631037 -26.388783 26.211708 9.389849
--18.861231 -33.228931 29.733133 30.216154 29.167511 15.435679 25.305086 19.504105 -25.545568 17.099970
--28.352892 21.202972 -28.220776 -25.223660 -27.102163 -27.997780 -15.985667 -31.684175 8.520580 32.364357
-27.376833 -20.802015 20.907457 30.482269 30.754896 -28.857952 12.509435 13.060081 -28.310965 18.305183
-25.157576 25.038042 -21.250418 28.748077 30.768257 26.917866 7.294786 -21.357422 -20.052004 29.755259
--24.358604 29.996195 10.147661 15.117146 -25.059454 26.876207 29.655886 1.598995 -31.368891 -24.860382
--23.087124 -30.624411 26.872061 -25.430162 -27.082129 20.720413 -28.692017 30.691967 -21.279165 -2.551623
--24.353456 -31.981487 21.236629 -24.626516 28.659883 -25.651659 17.860260 22.199923 -20.723352 31.429373
--25.257303 31.413050 2.180641 -21.803225 31.604710 26.447760 -3.937415 17.640810 6.967419 29.346401
--26.361465 -29.989614 6.612124 23.398020 28.787786 26.224808 -32.942394 23.286501 -19.532110 24.959354
--27.878630 29.734219 19.966755 30.198826 19.773518 -17.789425 -27.085190 31.225122 -28.529303 1.141312
--30.901060 0.391270 -2.896986 30.007690 27.838476 26.702936 11.228483 25.069935 35.403259 -18.549868
-24.425106 30.878494 -14.288082 -28.314743 30.358965 16.484238 18.017254 -16.166327 -30.419704 -28.554745
-2.113087 19.104361 24.900944 -27.797613 2.455245 -30.316483 -31.873756 -29.685768 25.493534 -25.001156
-12.640694 27.439734 31.413740 28.351887 28.250576 -31.200777 -1.919832 -25.808199 -17.301651 27.257868
-24.302240 -31.663763 -8.108189 31.926470 26.079449 -17.886381 -5.920022 -31.881042 29.882542 9.564315
-26.885803 28.647747 -30.219711 25.136871 28.128950 21.675436 -28.413626 8.504551 15.025225 -19.844286
--25.595650 -27.307159 25.095547 -7.531783 17.902473 -24.060442 -29.581953 21.509615 -19.275269 -29.422474
--32.989773 -24.240007 26.426277 26.318930 -30.240437 -30.340971 9.496776 -0.216958 -30.049471 26.236687
-25.384636 -6.275255 -18.597488 -32.691147 29.291729 -27.610168 -21.210382 -30.417465 -17.904039 -27.208693
--22.291912 13.350454 -28.847847 -27.335732 -24.619164 -25.186035 -31.240126 25.411316 27.413515 26.526279
--11.963379 -31.066198 9.782462 33.931267 29.914045 33.128548 6.134001 26.757753 24.343744 12.870527
--25.266705 28.371819 -17.242594 -0.061756 -23.222466 25.648582 -29.380426 -25.207943 30.648054 25.205875
--28.429790 29.742310 -29.492258 24.673662 -5.577706 -30.121881 24.641495 -5.271527 -28.554474 -25.347298
-30.674225 23.665363 26.509443 -28.156471 -19.652834 -30.558514 3.050400 22.467127 -12.157305 25.608335
-28.007099 -23.921940 -28.883001 16.383432 30.184158 5.257059 -27.107363 -18.662508 30.094419 29.672953
--4.148671 32.244709 -31.177191 -3.107982 30.788345 -19.094992 -17.701006 21.321257 -28.870909 -22.307236
--27.787346 21.979095 -28.086067 27.094601 -22.926842 -26.618746 -25.764585 30.389841 9.124823 -20.803688
--28.622871 14.273782 -18.527746 32.811272 28.237886 26.638952 -29.631285 -21.763582 29.762817 23.678711
-28.507240 -28.432800 24.060392 0.475232 33.547039 10.758526 -3.632491 -28.713354 -29.390940 -21.657669
--8.461226 -20.445940 20.312346 1.126397 27.891205 -8.802555 29.181444 -33.473057 -24.317173 27.094810
-18.385647 -18.681868 -34.019363 -16.016193 32.892334 30.348473 -18.076117 -17.677099 29.281147 -6.462004
--27.232441 29.584328 25.616709 -7.832103 22.537663 27.604885 -24.377760 -26.233315 23.746206 -26.995077
-23.928440 27.366444 31.684374 -26.476540 -2.046179 -28.640903 17.716154 -28.665686 20.821653 19.822582
-29.407177 -29.962450 -25.928570 -20.161171 -21.076260 -26.830011 -23.238630 -28.696051 -26.628510 11.198109
-23.762690 -3.135408 -10.013238 -25.964376 31.742970 -25.495323 23.754967 27.876976 23.058678 -27.804108
--29.595732 -26.108103 -32.855850 -0.777961 26.280220 4.676180 -21.124659 -30.380817 9.198297 -31.738487
--18.257301 -29.640936 -30.950096 3.669302 -26.327230 -27.560867 -28.221474 21.425386 -23.974077 -27.058352
-22.203074 27.736471 28.689638 -30.763041 18.591822 18.732649 28.202400 21.263161 -14.076660 -28.537773
-24.311007 -19.661934 -30.559019 27.831297 23.832487 23.034298 -19.796577 25.609159 -28.970860 21.383129
--25.099157 -25.529819 5.853761 -6.068099 -7.706121 11.039868 -8.481035 21.795696 -28.756374 29.722593
--30.324696 -26.820206 -2.094729 -20.414989 -28.300838 29.801680 25.661100 22.089428 12.858266 -23.677881
--28.310026 24.394686 26.970953 -19.291451 18.713287 31.958241 20.112799 25.449312 6.026050 -31.284294
-29.731031 -7.458796 -2.055046 -9.766047 -24.399158 25.549126 -17.113363 23.141628 -33.150452 -28.483871
--28.091705 28.946104 26.639599 26.441015 -5.776271 -31.776129 3.699637 3.309000 -27.088848 28.434065
-24.877413 24.131851 -28.485380 -23.670988 26.915024 -18.530895 22.305233 29.780357 -21.399794 23.557825
-27.733376 -23.716413 -21.622772 30.487514 -7.450827 14.006124 -27.437721 29.446697 18.505186 32.935650
--24.420240 -22.155836 30.738674 -30.658985 -25.938389 -18.666609 -4.351988 19.271080 27.065073 -24.776644
-29.156111 -28.483194 26.807344 -32.169819 32.677620 -18.160120 -22.820723 19.154898 -25.966934 -15.867821
--32.402512 28.791231 -19.376459 -33.458790 -4.591619 -2.483457 -26.426649 -11.451970 -3.489601 26.589520
-17.709406 28.119827 -9.284810 33.072849 -3.393136 -13.898425 33.350590 -30.098577 -25.904646 -23.073343
-24.880932 -25.761850 -28.084831 22.513605 -31.395102 -29.289019 26.686272 -6.293370 -24.953367 -14.749125
-16.803219 22.737221 28.072466 -30.104748 -33.386768 -29.029961 -21.493002 -17.387140 -1.687227 -26.739874
--8.849285 -8.653768 32.022827 -22.359735 29.513790 24.547321 28.248760 -29.673279 -20.694735 -23.920599
-18.995764 -32.690716 -24.981482 31.671928 -22.609871 -27.155401 1.049363 -27.188822 24.030592 30.201191
--20.475941 26.728388 20.333851 -5.874790 -25.067295 -29.538239 -22.953407 -26.601837 -31.151222 25.098551
--11.856617 4.262431 -28.877539 26.230621 -30.327372 27.634954 10.315826 -32.939442 -24.725647 -27.897846
--5.141058 -0.384487 27.112600 15.110576 -11.309449 32.180965 -30.647289 -27.716377 -34.215122 -25.215185
--28.122921 -28.624094 -8.308435 -27.449034 -31.472042 -27.381563 -21.243340 -18.023628 -22.585512 27.566639
-28.504580 22.803720 21.843224 -27.465639 25.226137 -26.931309 -29.118799 8.342940 19.081705 30.757061
--16.422394 27.782209 -29.507763 27.667814 -25.478991 15.812572 -31.803295 -8.327382 12.915374 -26.977285
--13.047698 -24.075064 18.757490 30.889606 13.036374 31.280357 34.008266 -2.397495 27.773239 -4.738329
--28.075832 31.486786 9.875986 -12.495639 28.213650 20.669672 -20.154669 -27.666166 -29.830408 28.754074
--20.817934 25.465155 21.660789 30.018974 -33.024593 -26.851126 22.427879 -18.918964 27.513636 -13.117702
-32.712883 20.105747 11.499645 11.480800 -31.893333 -33.761261 26.434597 -16.045656 28.441851 16.275194
-25.468031 -27.301338 14.702893 -21.335854 -22.459711 -32.798584 -27.640146 22.849913 21.499794 12.194662
-27.247601 27.541500 -28.059675 21.635532 11.560982 -27.964947 9.155243 14.273994 28.268442 28.711775
-28.157682 24.629513 -25.688036 -20.681528 27.016497 27.786137 3.006814 -24.266685 26.347130 28.307236
-33.590897 26.544954 -13.754819 10.255233 -8.044541 30.658283 25.738869 -22.977711 8.164171 -24.753832
-31.092783 13.342126 -7.211920 -2.049561 30.282135 -30.253843 -23.966923 -21.516727 32.113659 6.814880
-23.287216 18.627256 -0.295165 -32.785515 1.387961 -33.989265 33.773190 -8.199713 17.003393 -17.363035
-25.101440 28.455503 -8.158275 30.860847 -29.289976 -25.225998 -23.423073 -9.182380 26.093452 -30.787434
--24.068687 28.119608 -10.572042 23.238905 -30.614655 -23.620752 -22.369682 -24.210314 -24.525866 -28.179277
--29.210775 9.336824 -27.031591 -29.950668 -22.957783 -28.333061 -14.290992 30.638340 -9.514547 -18.259357
-29.051676 29.304520 -27.803989 20.112759 -23.854359 26.400883 -22.467255 31.361710 24.536663 11.645331
-25.958706 28.463490 -24.367929 10.579311 -25.545280 -29.809126 20.846022 -29.060047 -27.663929 23.973812
-9.121296 30.801323 26.039162 -16.843090 15.986970 -27.447987 1.624425 32.649300 31.067707 28.746941
-27.518221 -30.770910 -21.445694 -25.869053 31.146349 29.838579 -24.894156 16.136885 -18.003977 -7.402350
--27.305534 -21.246096 -26.871511 27.852213 -11.644767 -31.164965 -30.935816 -26.874981 -30.399879 16.253309
--6.632153 8.097020 -31.116461 -29.224577 1.844677 33.240108 -17.944588 27.793501 22.504580 -2.187771
-28.788109 24.887934 -12.195354 -26.807501 -18.840614 12.666108 29.015575 30.759928 -26.548164 26.759972
-7.593760 -23.918388 31.474106 -21.832027 23.403120 -29.994598 21.056564 25.481445 28.109774 24.279013
-22.547098 -30.332420 30.663147 22.894178 15.532843 24.273546 -29.101322 12.098467 26.230379 28.198549
--29.239477 -21.581753 27.146959 30.019226 -6.244174 29.899210 28.713047 -26.166416 -8.515326 -29.176779
-28.122040 -21.038881 23.960810 -16.589050 28.675232 27.318020 26.743977 5.758596 22.055302 23.182400
--18.961840 -10.698790 -28.763069 28.437471 -35.400574 24.652515 22.043573 14.510972 -23.194159 -30.208973
--31.020939 22.423620 -30.354576 27.677849 21.787552 24.156179 25.448776 6.797812 23.857073 -10.583152
-28.035105 -8.365502 23.218433 28.703245 29.323349 31.770390 4.667182 -30.053162 19.615248 22.585283
-20.907743 32.282700 20.469995 -2.092622 32.593643 -28.172235 17.193794 -13.688399 23.971102 -29.084644
--27.821463 -23.167927 -20.422800 -32.688595 20.012943 -5.708320 25.155785 -25.669615 -31.714989 10.813772
-21.059443 22.325644 8.813952 -31.869465 -25.340435 -22.912552 25.651350 -30.096390 -12.251925 27.824656
-33.124298 24.970509 -22.883692 -24.787495 20.120363 27.808098 -24.764261 29.295557 -20.974461 18.732210
-27.873919 13.170330 26.616785 30.360901 23.720774 -28.773775 -32.039742 14.245504 10.406815 23.114937
--29.642006 21.243027 28.496279 -29.954308 16.027828 28.209349 24.253197 -15.291070 -24.008448 21.691130
--30.420097 21.261686 23.687590 -29.134315 26.098228 -23.065153 24.013599 11.358426 27.619350 19.153673
--28.520651 -20.618023 23.632936 20.879873 -28.919048 -27.908325 -29.355772 -29.885509 0.446875 -13.041409
--23.555792 -30.753073 26.267303 6.488521 22.797260 -26.167721 16.045740 -24.451176 -29.071766 -21.936409
--2.366049 24.333763 -21.207254 26.385887 32.747791 25.520645 -30.213165 15.314766 -24.096134 30.081877
-27.522026 -25.469622 24.750177 -31.094889 -12.456142 -5.652915 -26.168478 -29.880280 -23.040524 -25.145845
-31.086567 0.399763 -27.909199 -27.119717 12.772094 25.539625 30.645590 19.174603 -7.188969 -17.428612
--25.660950 -27.140112 -10.629828 -27.045063 -27.010494 -28.772854 -19.600899 -28.375753 -25.870188 -30.110542
--21.292349 -21.289106 -21.501253 21.520546 15.719978 15.368153 31.115133 23.528603 -29.798271 -28.217384
--26.340864 -30.756704 25.837341 22.221676 -17.646425 17.593237 -22.739998 -27.202002 -27.505981 23.860538
-11.569932 28.003872 -25.262947 31.434067 -22.080194 7.423393 30.620216 -12.076071 28.589949 30.061836
--30.388857 24.292381 26.421072 30.324377 20.356447 9.037641 -28.085680 17.950548 25.793188 28.759373
--23.263527 18.627926 -30.141863 7.740365 22.029932 28.499783 30.285429 -26.274853 -20.482277 23.133362
-32.813244 -20.900084 -24.991117 16.317175 25.896717 -30.170595 -20.606852 -4.947311 -27.353762 -17.023895
-28.343552 -27.288149 -24.964575 32.622482 15.900583 28.223110 -4.864933 -12.131302 -28.233732 -30.439581
--24.307573 -30.622923 -27.477850 -28.684631 30.428198 -28.051462 -9.877420 19.513367 21.287836 -22.723270
-29.043144 22.876682 -27.117975 30.219616 -26.863281 -17.694811 -23.721672 -30.955458 -23.429083 -10.684244
-11.060363 -26.773920 -22.583313 27.121037 25.142149 23.520163 -35.005611 -30.745600 -23.574781 8.635379
-11.357567 30.427563 20.701384 24.337975 26.384836 26.677534 -7.507456 -30.599634 -28.048975 -28.365108
-23.339508 20.602566 -33.920498 -10.787850 -27.863245 -21.197025 24.051607 -29.691181 28.696939 -16.355665
-27.156740 16.964241 5.571268 -27.733831 -30.067137 21.884510 -21.251928 -30.481337 30.485355 24.729668
--26.687622 23.605410 -20.949074 24.506336 22.576454 -28.776810 28.682386 8.076501 30.059227 -23.765211
-19.499861 19.529318 31.583889 25.157722 -26.286268 -34.550621 -23.867632 26.800932 -6.820005 12.327001
--17.908678 -15.761912 23.849796 25.471844 -27.772625 -23.331366 23.346025 -20.287111 -19.387089 -21.679003
--29.713295 -7.165277 25.469320 -32.656456 -31.675169 -20.736795 22.852297 -27.023853 28.455851 -4.415093
--31.419279 28.685366 -25.388046 29.722818 15.015548 25.824671 0.442656 25.495337 -24.566687 -24.969934
-27.788668 23.789171 -15.574149 -23.203178 -29.012049 32.678471 25.480368 11.069133 22.169937 17.818844
-27.556049 -14.146981 27.893488 -0.205255 -29.667313 27.449438 -27.657949 -30.545671 -24.696152 24.537466
-22.982018 33.590633 21.231791 19.734377 17.219254 7.570241 20.145592 33.318871 27.775024 -16.882725
-15.009192 29.450502 4.686261 -3.324030 -34.471027 -33.349808 25.874115 5.478483 -20.379084 -5.739206
-13.428425 -26.141970 20.602623 14.879295 -27.248064 -28.260799 -31.781689 -25.459976 -25.936277 -28.731651
--21.017727 25.616560 32.629795 29.306215 -23.032677 27.910164 -23.108871 19.208513 -30.069599 -23.484737
--23.726578 -29.088511 16.016588 12.965228 -26.729847 -29.126991 25.498001 25.654112 -29.098560 -28.284170
--27.480677 5.697550 -30.919975 32.190777 11.537769 -30.228153 26.874218 32.551582 16.837023 12.355412
--25.134735 28.210272 -28.118145 -27.915285 -31.248295 -29.046194 24.636982 -18.550402 11.327372 -20.042549
--27.592712 -26.467159 -30.820688 -12.226371 25.467739 28.521854 3.692282 15.284110 14.373300 31.233538
-7.177904 11.423222 -25.810898 -26.818068 35.479370 -25.740366 -30.163752 15.037313 -12.527069 25.534302
--2.638413 30.585152 25.912683 -18.014620 33.231594 -16.783199 -17.315958 28.074158 -25.544659 29.678978
-26.285452 26.749672 -33.995316 26.974787 -8.064065 21.458660 32.709496 -30.895699 0.037257 2.178612
-28.732716 -23.296423 -18.691906 -31.023714 -23.567375 27.788317 -26.552231 19.305607 27.235626 19.013712
--28.392611 -29.439262 28.464724 -19.999983 29.721647 21.496183 3.553029 -24.798029 23.571009 -25.178368
--25.590965 19.625475 32.139542 12.308794 -33.614574 -24.932693 -12.018950 14.945961 -28.347635 -11.778281
--23.936697 -30.939325 8.649321 -24.380640 -21.523420 24.172867 -21.442892 -28.130402 -26.865345 -18.526720
-23.959433 -15.302689 -28.791048 12.541603 28.438076 -25.868076 31.533470 -28.832186 -25.802338 -18.020861
-29.430056 -13.753139 -30.351770 -19.868355 28.745502 16.640471 -14.774107 26.327574 16.127264 31.980478
--29.641502 -17.705847 24.447769 -24.623304 -16.330515 26.228224 29.003815 -31.477066 14.041460 -27.526264
--15.739707 28.716131 2.340807 26.645828 13.053572 -23.754354 17.074375 -34.384674 27.854647 -31.704470
--27.404348 -28.118250 -33.941959 -30.466818 -11.816746 25.685192 -18.100304 -30.087223 22.637438 13.770916
-30.122972 -29.118546 24.532595 7.057877 30.036701 29.099798 -7.071823 24.592756 11.401652 -26.073618
--28.692404 -27.009842 11.905396 -28.387501 21.222261 25.882669 31.801846 -29.021738 22.581629 22.886696
--23.964380 -30.042795 11.303555 -25.320282 27.864023 32.828209 28.997120 16.339516 -28.981457 20.930676
-18.626646 -29.582371 -27.551277 -27.697216 12.197803 18.428934 24.812458 -26.544010 28.405891 -19.468340
--26.839275 29.005001 -26.756369 -24.117373 25.626078 -5.748903 -33.437027 31.553396 16.725538 -7.001272
--28.237995 29.670803 6.692709 17.942415 -30.868332 29.001917 -14.060006 23.688519 26.160295 -24.409889
--17.979515 30.931259 25.636486 -31.712921 -25.322096 30.303371 19.788139 -14.276178 -5.861047 -31.922964
-29.199034 -28.819431 -12.205784 -31.307295 -6.876378 -7.332343 25.940901 31.060841 -32.258877 -20.013409
-6.463464 -32.547859 28.319059 28.421572 -20.190582 33.658432 -17.270596 16.164312 -22.368608 -26.789709
--27.753912 25.124001 -24.065769 31.459173 -25.951307 -0.960714 22.520782 -28.286674 -23.691193 25.823711
--32.022495 32.072910 -24.703007 -29.224352 -27.904415 28.083996 -5.967274 27.038555 18.721811 3.493615
--24.128891 -22.292822 -12.250476 -23.735218 -31.929567 -25.620970 28.912012 27.308689 9.154576 -27.708202
--2.529298 -27.601696 -29.463570 -36.215473 16.249651 -17.557255 -29.444719 -11.908958 -6.184426 23.358080
-22.185682 28.216541 24.036819 19.887381 -31.464809 -26.278393 -26.571669 -31.595316 7.374464 20.975615
--19.376390 -12.690674 28.849831 -25.717209 -15.535289 35.125530 -7.713222 23.484344 28.977058 23.431211
-33.227535 -27.833324 24.351425 25.713518 -28.399006 -17.730026 -1.729472 27.119209 -21.333033 -21.328016
--26.771830 -28.014515 32.189442 -25.928280 20.033003 13.710388 -26.982601 -3.500313 -1.506497 32.057953
--15.927268 -14.658901 -31.679316 -22.644035 -30.882013 25.508205 -3.187066 10.148254 12.417383 34.725166
--22.061447 28.227926 -18.534262 -30.699667 15.779271 -29.329414 28.158079 29.011202 19.597822 -26.136396
--12.276376 15.892327 -13.182528 33.299500 10.344028 -27.171360 -28.183661 -29.153164 2.250963 23.829035
-31.585875 -12.671778 27.297150 26.335220 -31.710556 25.913471 -8.017223 -21.332951 -17.157022 -30.292700
-29.741533 29.534622 26.601515 -25.145164 -24.681961 15.980844 9.520965 -27.243650 -19.263262 -22.375216
-25.433943 -24.467484 -28.143906 25.495886 -14.842226 27.493128 24.425079 -18.644470 22.826246 -24.302608
--11.835747 30.136255 19.106735 30.824072 24.703981 27.172768 30.038048 29.186287 14.920562 -25.028795
--24.752653 12.587847 -24.860634 -29.029341 -27.967066 25.020454 29.418030 27.942430 -30.215551 -5.299477
-30.899067 10.949029 30.686211 1.537882 -29.977716 -26.814390 27.016579 -25.541710 -11.079510 -30.835358
--23.126663 25.899948 -17.426580 -17.390171 -30.503218 26.251877 27.270002 -22.473648 18.283787 30.123409
-26.261578 28.262335 -11.489004 25.436064 -26.994009 -12.419476 -31.502707 29.040253 -27.648924 -25.962418
--23.910925 -25.429150 32.867672 -24.749254 -7.415473 -30.704737 -21.911823 -22.141689 -15.827194 16.446846
-32.822388 -26.108095 23.612616 -26.657368 8.439564 24.641146 -6.179613 33.014786 10.439384 29.579102
-28.725666 -33.654274 22.856649 22.741859 25.022173 -5.115507 19.444532 -21.232260 26.221478 -29.678156
-11.633716 -25.277298 28.206738 19.001387 -18.242786 -17.984953 26.639774 29.904631 -25.861620 30.963205
-26.100559 -31.884655 -24.972794 20.931379 4.227546 -17.869324 30.058016 32.515915 -28.206936 12.626034
--32.133125 -16.602737 20.367025 -31.185806 -19.106474 22.728912 -8.192968 -31.767912 11.123755 24.181980
--28.589380 29.538591 22.653214 -0.282040 -20.724344 -27.879545 21.328064 -28.110569 25.765228 29.024187
-30.860882 -36.364681 32.781525 3.949558 11.079511 5.537791 -25.393511 -25.208115 22.980810 3.930116
--27.158617 -31.621920 -30.083405 5.409239 28.529272 29.010754 10.388368 -1.306479 -30.552919 23.308531
-30.734177 -11.201901 26.037382 -29.200989 19.392895 28.737637 21.011969 -10.357248 21.548880 -32.679043
--30.674662 27.818089 -29.203140 -19.854593 17.044485 20.876467 -25.747786 -28.878233 24.511505 -23.141962
-15.673603 23.288090 -27.818857 -32.513565 12.726074 -23.733049 6.036387 -27.862049 31.193783 28.119864
--25.304333 -10.877955 -31.227898 -16.382595 -28.835913 25.393698 -28.896641 30.803068 10.476258 -26.465452
-23.626778 23.357811 -21.206614 -29.721647 -28.852413 -21.211292 23.961103 28.441339 28.036560 14.108786
--30.235542 -16.326653 27.562990 18.357885 -28.368156 25.471575 31.773487 3.734513 26.049023 27.969463
-16.980251 9.390479 -26.069489 7.320188 -28.113647 -23.642582 -30.748701 -23.248289 30.193817 29.133545
--15.223531 29.817465 25.503374 26.672890 -30.908064 19.442265 -24.689878 -2.461775 -11.962740 30.012175
-26.024065 -28.097883 28.531002 -26.941986 -9.108933 -23.738096 26.942194 -32.118740 -21.525244 0.961816
--21.030514 -29.363424 -29.957251 -3.642823 25.494364 -27.320837 29.038359 20.022373 -21.875433 -12.396379
--2.554545 -19.473997 -29.914202 -25.034857 28.580915 22.604307 34.856983 9.326077 32.951740 22.441561
-24.712944 -26.632645 -28.892635 -31.333563 -14.416006 4.310412 -0.897436 25.962732 24.652559 -30.673096
-6.788627 -21.653187 -6.069960 12.866386 -27.860754 -26.680700 30.156889 30.329958 30.810295 29.371235
-21.382395 -22.684311 23.297520 33.335854 -27.297352 -17.233984 -31.350203 13.568316 -24.140413 28.863089
-31.643314 27.707121 -29.477461 -9.803405 -3.628554 -7.854528 -23.128674 -24.773476 2.337460 -32.242786
--28.357882 -29.080982 27.726603 -32.353439 -22.851774 17.860350 26.096420 12.912831 -27.845894 -11.446677
--17.905165 -28.183750 19.077509 18.199484 -28.807766 -32.092926 -22.621668 26.957857 23.457119 -25.195761
-29.155462 -25.485563 -30.272305 -16.998955 15.935428 -27.434748 16.272764 32.845551 25.275352 20.979900
-32.467125 2.939564 -31.076166 27.574575 30.052773 16.918018 29.306002 23.624807 19.740393 19.112986
--8.465060 31.190577 -19.820602 25.919401 25.398651 -25.740845 -29.263819 26.071243 16.005625 20.981049
-26.799908 31.759245 13.203218 30.501919 -30.048819 27.405413 -20.117563 -24.532503 -17.605293 -1.400979
-25.599031 -25.007303 -23.524038 -23.979019 11.082253 26.192183 -31.115137 -30.058470 2.727974 -27.772297
--24.374161 -27.365503 19.043154 30.259495 26.966307 24.007391 -26.921694 -27.449593 -0.693423 -26.959122
--16.835014 26.655935 -29.384642 -20.400610 16.875422 -9.288965 24.921650 28.477253 27.882397 31.178291
--27.775560 11.304965 -30.917141 -23.896084 -27.252436 -5.768191 24.565573 25.989275 30.708174 -27.192362
--21.059984 29.560249 11.736514 6.236456 -22.555840 -11.700287 29.706589 -32.870235 -30.064922 -32.728569
-29.824356 27.638718 -26.119389 -25.752388 -7.091943 29.872379 -25.563438 -20.491268 -15.487212 28.308151
-25.054296 -31.876778 -9.431026 20.878891 11.869048 -26.002031 -29.155945 -26.587269 21.408344 -27.389734
-13.360140 -28.607838 17.558054 29.380537 -31.186047 26.913769 -29.970146 -22.124077 15.529097 28.936937
--26.935667 -27.751474 -25.886803 24.869987 29.632679 4.262222 26.330482 27.695890 20.406704 26.952892
-27.773643 27.070660 29.386000 -15.045194 29.023048 -14.664932 -26.053480 -28.607267 -29.265291 19.901291
-25.224318 30.863043 -7.171692 -26.044735 25.731773 7.060417 24.963589 -31.946568 -24.867212 23.922573
--24.416780 -3.127780 26.428778 -31.601528 -28.607794 -32.702267 -30.195272 19.899616 -32.712517 -13.622476
-23.834667 -20.505260 18.961716 -27.534723 19.927999 -27.138330 31.404387 10.160913 -26.514894 28.471298
--32.579205 -29.109819 -23.370672 0.175204 4.152793 26.609514 -30.408527 20.083223 30.345333 -30.777744
--25.165133 26.590651 15.164800 34.035385 24.890318 27.121458 -30.423645 6.241826 -13.916649 -20.982605
-24.287477 -4.930229 -29.895758 31.450027 -18.431036 -30.184004 -14.347340 -25.172152 25.120384 -5.390819
-34.449562 -26.830839 -22.914642 26.217722 16.639507 1.244331 33.186203 -28.394007 -10.429307 18.779203
-27.026775 24.603586 -27.057831 -28.173298 -25.732758 21.497812 -24.456360 25.356434 -5.640959 -28.189854
-28.458910 26.698551 10.737266 -30.727051 -14.385382 -3.846819 20.652956 -28.468721 32.331146 -34.411369
-29.262314 -32.190617 26.086044 28.936239 -25.675840 -22.062592 -5.182319 -31.989595 9.402879 6.248139
-28.646204 -26.018677 21.673767 30.117731 -24.644100 -25.889296 30.692308 -22.026123 -28.589268 4.404716
--22.393431 -21.427132 -31.853867 16.146013 -24.506269 27.188745 30.711731 -34.057224 27.288538 14.982982
-20.574594 -15.383286 20.906435 -28.355043 32.379101 -12.020234 28.393415 -29.822983 31.416735 17.007446
--25.502262 -9.228008 -3.837359 12.872238 -26.151907 -25.499598 -32.324112 29.786247 -25.967714 28.234489
--23.084305 -13.282383 19.637316 -28.958052 32.728695 24.140638 -25.476992 -10.069501 -29.599485 -28.257629
--25.001698 -25.255516 -32.657532 24.237925 -20.142313 -31.082474 16.980850 -25.324553 -24.850039 -22.198929
--30.783539 21.704845 22.750927 -26.120293 28.412706 -29.031534 25.596516 -13.815741 -21.302029 28.485952
--11.812229 -23.016167 23.444263 31.846100 -23.763472 -24.157795 30.420347 27.766439 22.159620 -26.217464
--30.269299 23.074360 -17.584850 -24.882748 -28.447580 -9.149231 -28.034163 -20.211983 28.957960 -28.144926
--28.273239 31.753962 -31.849707 -24.950897 29.024555 -30.823227 24.291180 -20.824249 -22.976759 9.613055
--19.141724 -18.903481 33.267681 -29.076090 22.744261 -21.670807 20.176722 21.742088 -27.476349 -20.208090
--21.814678 26.229355 -22.394960 -23.985876 -22.850430 -11.157884 25.720003 -11.150975 -29.975357 20.922470
--24.818188 -27.971861 -24.304016 33.115723 -7.687469 18.482296 25.003521 -28.380758 -27.353703 10.670769
-34.711102 18.940998 -8.904346 -29.782681 17.538698 28.884752 -30.254866 -7.674024 26.520487 -22.265539
-20.902689 8.025566 18.674671 -14.390745 34.189243 25.087580 -26.964514 -30.336157 29.974638 -32.069538
-27.297630 32.444088 23.818474 13.905664 13.886219 33.197960 19.602440 -5.438952 -29.282585 4.220894
--31.047628 -5.967454 -15.532126 31.632353 18.968309 -20.643166 25.451929 -29.252943 25.353363 31.446577
--29.480902 26.957392 2.875650 -30.756542 28.904150 -30.677294 -7.803256 -3.807869 24.872663 -29.877567
--22.565489 30.024027 22.170925 27.085526 -26.759377 -20.698097 24.962259 30.733471 -6.988181 -26.746565
--26.527519 -32.189098 12.014070 6.617297 18.855453 -31.615606 22.567261 5.846895 30.375355 -26.095812
--27.512320 28.680782 14.500208 21.156994 32.140953 -3.669570 5.279128 -24.266092 29.650183 23.805666
-8.043905 -12.737823 4.512187 15.255741 33.115318 28.959831 31.735544 9.968329 -23.206686 30.895378
-26.174623 26.838005 -26.408766 2.086205 -19.624910 30.056616 -26.491264 -15.869252 -27.731758 -28.084812
-33.798901 9.602103 5.424158 28.581442 -28.910339 31.374783 -21.994387 4.254702 31.387598 -16.908768
--22.995621 -29.013706 -3.134014 34.395058 18.291862 -14.794615 -25.759489 29.110916 32.434479 6.428141
-22.396238 28.856667 24.694206 29.728733 17.439247 -24.605965 2.835178 32.425121 -29.118446 32.634369
-21.048349 28.621387 29.156994 26.189903 -29.382019 23.461313 28.266794 -0.439052 23.495407 -24.725916
--27.643070 -24.467356 -24.125101 12.355736 -31.026474 -11.452502 29.360916 26.205215 -27.469412 28.773991
-17.492985 2.943702 27.385895 17.119638 35.015461 -8.329785 -29.867542 -22.840242 6.396861 -29.727692
-14.143679 -29.546240 25.005054 -32.755421 4.263321 12.211868 -25.658663 22.994242 29.143982 -22.893181
-24.109888 -27.497812 -27.954905 32.443611 -3.344005 -31.847933 -11.106377 29.914062 -13.352994 27.370584
-29.769308 -27.634550 10.123406 -0.666036 27.717897 -22.755526 -21.831999 29.521137 -19.971655 31.803200
--27.502804 34.955513 22.627068 -26.192478 -30.501144 25.425434 -17.472500 33.547077 -21.327307 9.094096
--30.031528 24.495207 29.067213 27.323195 27.462391 -4.872978 30.398762 -25.902514 -27.583355 10.717492
--2.095082 11.889703 -10.809792 30.213783 1.781955 -29.186869 -11.892235 25.833742 -32.324806 -32.079998
--29.235382 30.834251 30.403370 -11.315332 -24.759306 31.109966 31.431036 28.520866 11.053640 3.461449
--30.244762 -27.393930 28.511477 29.816730 -27.471121 -7.608500 26.504629 -28.544924 9.468965 17.659010
-31.055311 25.810459 -26.201794 -27.467518 -26.213955 -27.562859 -29.694899 21.291172 6.601510 21.115910
--24.484440 14.377709 27.141979 -24.846848 29.676838 19.359415 -26.188015 -28.933739 27.068943 28.852873
--1.777584 28.690315 -30.685251 -25.811670 -26.726999 22.073185 30.474836 -26.577009 -1.388977 -24.970066
--23.217674 -9.603335 25.585693 32.880417 17.636166 -26.905874 29.450474 17.441338 -29.926682 -2.519353
--18.993116 -17.049662 -29.117178 26.266535 27.745338 -24.618834 -32.491642 21.682329 -15.290477 25.305677
-21.594990 18.116844 -22.970961 26.803097 -28.312132 -25.754536 28.784237 23.493803 -23.988674 24.755627
-26.273111 20.164145 -30.960867 10.705051 -32.859798 -8.560682 27.298222 26.350872 -22.881374 -29.441200
--22.493010 23.351444 28.667454 -25.100960 -27.100527 26.709175 -27.322639 -25.643158 -23.143845 20.998848
-33.212540 -22.807255 -8.209283 -23.595226 -29.341192 24.369164 27.328712 -26.528467 13.444833 -27.852577
-0.897182 -18.460764 13.430999 25.243839 -22.347672 26.362997 1.497149 -28.266176 35.687267 17.992989
-10.311977 32.574795 -0.212680 -30.948067 -28.844055 -13.601215 1.557753 25.845419 -26.258997 -30.565941
--31.612873 -9.108874 -26.461384 -20.205444 -30.433044 25.255568 26.380428 -26.816496 -26.852779 9.175333
--23.040833 -31.964855 -25.077463 -28.732893 -24.889439 26.744467 -26.337885 25.007233 -24.697218 22.533663
-30.737677 14.543345 -26.202257 -15.591269 -22.377333 28.348845 29.444912 -24.730145 -28.503851 18.424576
--26.413193 28.465033 23.083967 30.347820 12.164445 -25.689840 -32.023987 -12.430599 19.589396 -26.604269
-24.747435 -25.146259 -8.288306 -26.737041 -12.364920 -30.125212 -30.506683 13.233122 -27.001324 -25.677553
--23.593397 2.490179 30.440943 -25.393753 16.548756 -32.422806 -30.887869 30.479034 -17.930670 22.131184
--22.438736 8.358352 16.260340 -32.475449 -32.186527 7.956705 22.723034 18.579256 28.241919 32.100170
-19.554148 -27.834885 -22.022249 21.876564 23.675402 27.664116 -25.391336 26.641520 21.600826 -25.006041
--25.975653 20.819170 25.681568 -14.112076 30.400187 -26.938988 -31.833731 -24.777851 -23.332275 -6.757283
--22.558081 -30.685102 -29.712374 23.001144 14.667596 17.613012 25.100410 24.326008 24.480333 -29.273287
--26.562567 28.114670 -24.706234 30.221634 -28.659506 -30.630051 -5.832726 5.143960 -9.164999 28.023228
--5.923516 -11.563029 -24.251698 -33.599762 11.713305 -26.949112 -18.838186 30.039885 -29.089350 -27.182583
--28.901306 -31.126938 17.398819 -26.592638 30.544956 3.800116 29.343433 25.095493 9.057474 -27.154503
-25.736546 -13.424304 30.470133 20.869114 18.423546 24.845211 -29.066833 23.181301 -30.541372 25.994198
-27.423670 -27.840143 13.429342 31.628370 27.305670 -15.566775 21.208973 30.164932 26.405418 22.738131
-27.583424 17.739641 -28.972815 27.014660 22.040768 28.733265 5.443688 24.076410 -30.501183 -22.660669
-29.299047 21.763460 -25.778793 -30.054329 18.825420 -28.253668 -18.830385 25.444197 27.765272 -11.697937
--16.964239 -30.562384 30.909069 11.853930 25.537861 9.847809 -1.116659 28.196758 35.026066 -25.823643
--27.128920 -31.256323 21.659021 24.397120 -25.733042 20.490381 -23.214678 29.172058 10.333962 9.034096
-14.474123 -23.810432 -24.891966 18.942736 -28.131004 -9.560011 21.164343 -31.593370 -23.664772 30.311522
--30.458584 -13.034205 0.747105 6.969122 32.300362 -27.568441 19.547087 26.822100 -33.261684 -30.514378
--32.572960 -16.802517 -21.750109 -26.299847 10.077271 -26.800924 27.696951 -11.072599 26.649021 33.732758
-25.869362 -14.049567 -31.227896 -16.428043 25.684437 26.808477 22.170685 -32.006725 -27.951071 -26.857271
-25.632647 31.340467 -10.101071 -27.868580 28.392941 -30.367975 -24.844458 18.878220 -28.495523 -23.132236
-1.986802 -28.611712 -26.413385 -26.797050 -25.955442 -30.128197 -26.639410 -14.373254 28.916788 19.168682
--19.165081 11.260596 31.176182 9.450422 31.285467 -20.239744 21.123598 21.685785 29.227621 -31.673935
-0.587843 22.940138 28.678320 25.398922 -18.522312 12.439598 -29.282730 33.175476 21.039089 -26.045649
--25.681229 -5.916020 24.594976 -27.655167 -19.081779 17.430195 -26.535902 21.330406 -29.509890 -34.709892
--24.813129 19.791067 26.324507 -33.118763 -18.493454 -25.687447 26.396252 -1.613418 -28.247681 -27.283630
--25.763205 -18.964548 -24.838812 -18.957668 30.600906 -24.606560 10.967690 -30.789375 28.121155 5.437460
--28.941336 30.519905 -28.119589 -23.024672 28.105591 29.297325 -1.960685 17.279530 -29.578667 -17.794458
--14.513925 24.624935 -23.667196 27.040792 3.144825 28.194065 17.492538 28.565624 30.727345 29.069174
--23.433559 -5.516361 30.931314 25.211166 7.632286 28.322212 0.928505 33.286747 -0.994150 33.493996
-23.183256 27.546146 3.295649 20.680958 32.848858 14.191882 -20.808727 18.313766 28.677576 34.206108
-7.304214 -26.545599 21.813995 -29.120394 -32.868858 -30.856737 24.989367 -3.438031 -10.098872 30.483994
--1.543379 -9.049648 29.524065 29.556068 30.132706 31.693953 8.643419 16.408585 -29.715712 -27.209595
--1.318370 -28.632818 -5.848276 -19.451675 27.203268 29.918613 -27.557243 -29.160196 11.098360 30.477375
-30.259293 31.887877 28.997480 -26.240725 29.429012 -0.215187 31.697910 18.112293 7.368057 26.644302
--28.542744 32.168686 28.398161 -25.519390 21.313173 24.417574 -23.385223 23.575758 -24.957533 -11.581442
--29.584984 -22.043736 -19.973017 -13.154330 27.776617 28.880579 24.541265 -26.868013 -23.242449 -26.350306
-27.122181 26.698082 -16.079922 -30.070417 -15.069088 -32.086346 -6.156638 -21.599962 -29.905394 -22.629557
-23.463209 -25.001377 -24.783054 -28.923738 -32.481968 -22.494843 22.910870 -24.435270 23.247295 18.574396
--16.888866 29.557543 25.438974 16.747263 23.634312 30.699593 31.858620 -22.419878 20.923744 27.286860
-23.698317 -28.092585 17.806080 -27.186083 4.859796 30.562733 -21.827574 -19.261030 -30.630808 22.816006
-8.570764 -26.789154 17.791445 -28.964176 -29.611862 30.816334 25.552217 8.495584 -19.825544 30.543760
-10.111639 -19.598457 23.963257 -30.313669 26.156183 -25.989300 27.614353 -24.404526 20.948635 -30.697847
-23.499454 28.296463 28.447521 -23.573496 8.948705 -27.488176 -21.296618 33.204815 -1.533401 -32.551239
--28.905920 -28.724876 -11.068836 23.758741 -27.164768 2.238347 25.200848 -21.659460 31.813583 -25.553432
-24.451195 23.192873 17.820963 28.785830 -26.175900 -20.575638 -19.249416 24.187832 33.765800 27.542351
-31.044796 18.402918 30.415819 22.584785 5.366678 1.192327 27.368513 27.835930 -29.189474 -26.132465
--25.984489 -25.897291 -24.572817 -27.869888 35.358978 0.409840 -29.416412 23.666075 -25.127134 0.175234
--11.632380 1.468935 -12.562681 -4.036163 -17.348457 3.709737 12.364988 -29.359982 13.158352 3.583840
--31.037598 -23.666887 7.681589 -15.789920 -18.904598 -27.841438 25.454210 28.760548 18.029247 16.851074
-26.357662 -25.009775 -29.791250 14.314116 -28.555151 0.319603 -28.451876 23.641190 29.803474 -19.127604
-20.317736 11.170012 26.932655 -15.372322 20.496868 -30.759846 12.953140 30.441490 -35.144604 -22.444994
-4.470020 -14.852816 -28.201660 30.268980 33.456806 26.419891 16.373205 -28.011635 10.045803 -28.102468
--29.568325 -19.445253 -23.598480 32.237045 -11.473091 -27.800039 -18.787716 -6.833638 25.951796 -29.994253
-2.175416 18.538134 -15.958865 -26.025406 -28.610727 -23.338968 -29.128931 28.077280 29.938484 -31.821379
-13.321897 -23.288567 25.899305 27.282066 -29.057159 7.306644 -16.628313 19.552446 28.743105 -33.372395
-25.663147 -24.316936 30.338200 0.198456 26.764936 -28.802996 -24.417147 26.743793 26.973076 -22.167675
--24.675283 -29.163818 4.554856 29.763702 -23.107208 -4.606274 -25.717699 30.389217 -26.685402 -24.885359
-17.466875 22.449562 -30.188108 28.243744 30.856178 -26.148636 -4.465913 -22.124397 24.865055 -26.878393
-13.763696 19.437191 -4.767939 -30.196630 26.213408 27.918175 -29.278442 26.010557 -18.770628 -34.011822
--29.065424 24.655348 -31.381573 -26.498888 23.706768 1.163733 32.557743 29.334454 -25.294851 0.571252
-2.821732 -29.741623 -25.697899 4.740164 -2.629756 -24.113411 -33.509792 -23.366123 -22.589396 32.119278
-27.928167 -28.453217 -27.783646 28.721386 30.288094 -7.694778 26.734276 20.536390 12.432297 -27.357151
-29.255533 -28.615919 -30.009079 -26.702307 -26.329327 3.907118 14.859112 -0.607094 -32.211464 21.356220
--18.793222 -3.798059 -26.758448 28.500853 34.239231 -22.307819 -26.285475 27.232656 9.680526 -31.123280
--22.048409 19.472820 -27.342068 -3.084518 31.052856 28.628109 -18.369673 -6.574208 26.069016 2.390783
-30.838614 -31.065832 -23.328526 -27.681437 28.729666 5.293194 22.912565 -24.776793 -3.040089 23.239820
-24.948847 -29.624977 -18.823366 22.120489 -19.881227 -27.936697 23.355516 13.080451 31.027403 -27.728983
--27.207590 -31.597433 -12.881650 -6.010530 9.100506 -29.575729 -26.902830 23.663296 30.666758 31.928682
--21.830980 -31.940022 -27.536440 25.065334 22.005463 27.432138 -18.701872 -23.727381 25.942179 11.190812
--2.231342 -18.594671 0.143037 -13.649037 -17.063463 -30.886179 15.078956 -32.989906 24.989979 -31.739000
-25.452377 -27.772600 -27.105972 25.484657 -25.555532 -0.991211 -20.596451 -24.194292 -28.303204 -24.034193
--20.308994 26.506071 -22.997358 -27.003933 27.493284 -1.058701 27.859604 -27.349453 26.765139 -28.524254
--16.797264 -24.915733 -15.681656 -26.831530 -30.325777 31.558727 -5.553338 -24.391125 31.935699 -28.778387
-31.743446 26.157917 28.448555 -18.487127 7.345466 1.489666 -29.501638 11.606647 -27.396669 -13.608665
--27.674065 22.803783 -23.587780 -5.956399 17.851345 -29.958305 -2.373573 32.541912 -29.145765 32.780499
-23.156601 -31.936874 -23.037279 23.210339 -16.066366 28.110289 18.845188 30.645571 -26.768814 -16.099922
-27.679998 -20.325911 25.808142 -25.733467 -28.541807 0.567349 28.784498 26.622042 28.476433 -1.516529
-26.030373 -16.593649 22.357252 26.293604 28.905434 -27.011293 26.409996 -18.414158 -21.725388 -33.704205
--24.948288 -25.220125 -20.178833 -7.443022 9.836597 34.162106 -27.491079 27.349024 -30.223257 -23.430996
-18.110004 -27.612009 -26.904844 -24.353579 4.394511 31.755394 27.892437 27.468506 -19.308678 27.300795
--27.026585 27.288965 -7.176413 10.046975 25.635988 23.404205 -28.872671 31.483458 29.834528 -28.559134
-30.009659 -11.481675 27.223341 19.816360 4.897099 -24.425240 -28.176208 -27.415291 -29.087711 21.933622
-29.687820 22.965918 27.730066 31.794384 9.901048 4.573306 20.007175 -29.642658 -26.747276 28.268198
--0.865210 -19.871767 -19.929611 -7.993979 18.854616 -28.328897 -34.383411 22.391741 31.597097 -22.520195
-18.711977 -36.071030 27.292971 15.776377 -27.944176 2.161903 16.054998 3.965790 13.864322 31.318604
-32.407635 5.166471 16.989594 27.554375 27.841732 26.678566 31.432329 28.344770 25.829052 -4.596391
--27.288744 -30.192442 -24.259874 28.172007 22.895628 -0.534298 -19.668987 -6.121844 -27.388472 -26.192146
--29.263872 -30.790047 19.891373 -21.585848 -25.329546 -19.121740 27.868361 -25.622396 -13.165931 -27.882870
-22.623146 23.712912 31.028137 20.355440 25.867502 29.143358 -27.648264 28.304945 17.928005 15.036697
--26.480713 -10.525772 22.626904 -30.745777 -24.995880 -13.706410 23.108267 -30.951660 -27.589741 26.716717
-31.877645 -26.776035 -30.638912 -11.357694 27.723171 -14.465068 -13.479167 29.104784 -25.188648 -26.069992
--27.348982 15.839380 27.952333 28.053581 21.310860 29.003035 -17.415442 -17.901690 -26.812763 28.250551
--2.292844 -14.367384 31.270039 -2.544875 -3.583298 34.580555 -30.110287 -25.307888 26.263306 -18.783525
-25.580534 19.344273 24.519999 -27.579952 -28.082302 26.304674 -7.087376 20.679804 -28.221176 25.788729
-26.403370 0.119673 30.563673 -25.678677 23.550240 26.026884 25.694942 -15.687905 -26.583086 28.904022
--26.024733 -9.991076 -26.260162 -32.388321 25.972918 26.600454 24.502594 25.001644 27.591122 -23.150839
--20.381500 29.739450 29.266190 -19.060871 31.730856 -27.851404 -29.299297 22.886538 20.299524 -5.612797
--30.245682 9.170924 27.835001 28.510269 -26.989723 -29.905684 -21.079306 -4.574450 27.621330 26.835732
--11.741691 -21.096174 -31.672081 -26.892820 -20.835611 26.145498 -19.070086 -8.344960 -25.313398 -28.809412
-27.975668 29.217541 -21.093300 -24.969948 24.385786 27.821079 12.356703 29.299297 31.538540 -18.826864
--0.011608 -21.470102 -21.539015 26.133718 -24.347315 14.058448 -29.397707 -32.114067 27.519901 -28.864784
-7.751823 25.806000 32.901085 -18.736755 -30.452698 31.745525 -19.301916 23.036520 -1.871948 -13.531702
--25.096243 -22.490328 -29.185835 29.310244 -22.384819 25.474823 -23.745300 6.527666 -25.035147 26.242929
-31.915901 -17.114971 33.850632 -23.008661 -20.975691 31.195967 -20.159695 25.620447 -9.417980 -21.470547
--20.885433 -26.098394 -34.525181 -27.231531 -22.594303 -19.190878 -17.335438 -22.200954 23.105984 -27.633783
--25.089838 27.039967 -29.545822 -26.537960 16.975136 23.591961 27.614595 -26.206774 26.214140 24.426662
-24.727230 9.407478 -19.955605 -30.136086 32.399204 -29.649614 31.909718 -7.453758 -6.022649 21.740572
-12.958760 24.706667 -23.926395 -30.368166 29.662342 14.598271 -25.140099 -27.388971 -21.885681 -8.899488
--14.913486 5.755036 29.146093 30.288597 26.944231 -23.483667 28.112745 23.703074 26.498447 25.958067
-11.558963 31.078140 20.723763 -30.646187 9.957328 27.129442 -30.294744 21.838882 30.638649 -5.043203
--29.248917 17.624363 31.224365 30.660954 10.486515 -23.798962 1.554539 -28.965864 -12.215902 -22.325430
-7.900054 -26.661585 27.479298 31.024197 26.996269 -25.794918 -28.789604 20.071230 -26.860794 -21.076006
--27.726221 -28.307617 34.196552 19.789654 31.658072 9.052336 20.067137 -24.075565 22.948666 33.775368
--18.119324 -15.809902 27.389950 14.877948 -23.965155 22.419680 31.682259 30.595205 -31.514141 -24.590290
--18.131638 -31.149517 22.957989 27.805208 29.596313 -18.579456 26.984100 31.832233 -0.351689 -22.661404
--19.898781 14.091078 -16.836910 -23.718222 26.494846 7.629979 9.194495 19.305960 -2.738285 -35.370060
--25.090359 25.073004 -29.615166 22.081806 24.856117 13.964811 -28.084621 -24.082621 -25.604486 -24.462408
-30.246601 -5.769229 -5.193548 29.170889 11.829287 -25.503380 -30.386749 30.259050 19.686636 -26.349174
-28.390156 -24.656689 -12.252963 25.772734 -30.656946 29.966541 -27.206295 26.297985 -12.604877 -3.371529
-26.495270 25.092012 -26.570024 29.583403 -12.035311 22.394245 -19.207348 -28.881124 19.397552 26.818882
--13.935023 -29.313412 -33.118549 -29.540964 9.710785 -26.418322 -15.709097 30.511360 -27.285845 30.564705
--1.097461 -29.774305 -24.169292 -29.655241 27.834856 19.809050 23.895390 26.617266 -22.941202 -32.466064
-27.327742 -26.427551 27.262140 -21.368608 23.675949 28.715414 28.391165 27.343777 -29.445198 -16.981379
-12.984652 -25.212948 -25.955906 -33.128109 3.915369 32.641487 16.643110 -28.839380 -29.649031 20.084105
-29.169926 -29.581917 -9.146402 26.112736 21.341251 22.479158 2.133000 -27.415180 -27.825184 29.289385
-15.334047 30.304628 -10.422917 -10.776401 -28.027750 22.465811 -27.439026 -30.379057 30.532068 -22.980307
-6.460567 24.801245 27.595768 -18.807585 26.529850 -28.904119 27.325108 -26.231388 -27.992422 -19.203676
-4.858919 9.724921 26.735258 -29.821846 23.857037 28.866035 -28.931206 30.675814 -18.045187 26.510839
--23.896399 -29.940565 -29.135975 25.415710 -31.608906 26.104200 9.917217 18.043379 26.905247 17.197084
--32.659801 24.501835 11.548573 24.957283 17.654007 23.903896 30.063805 -25.241699 15.368115 -28.222347
--21.819532 28.157255 26.924294 -2.496731 -32.710079 28.959297 17.546373 -31.157272 4.777966 13.330534
--33.874298 -22.775492 -23.086416 23.421789 -26.284649 12.585775 -29.640625 -25.766966 17.247511 16.120251
--30.796759 -24.995079 -19.737066 13.902723 19.905830 -31.017385 15.919159 -27.547905 -23.628786 28.600891
-28.395857 -14.105124 23.998751 30.859987 -21.012695 28.477846 20.331127 29.432749 22.459372 23.770639
-9.352928 -31.270706 -29.708103 18.127703 29.772743 -31.743284 9.090717 -6.822830 3.621120 25.464043
--28.046972 -19.711567 -28.521206 16.062174 -18.660967 -32.186073 29.525179 -18.658434 25.409454 3.064334
-29.735567 27.620518 24.151989 29.720812 -32.017345 8.971922 13.413472 28.063982 -21.506521 13.922566
--29.474632 -19.652834 32.006847 24.401064 24.865980 25.338604 -30.355970 22.534678 2.968681 -22.344526
--30.064535 28.272619 -11.764478 -28.267519 -9.421213 24.136015 -6.741315 -32.448353 -29.630991 -25.437532
--26.516050 26.305784 -25.274731 -23.731672 -6.135195 -21.882580 -30.837490 -15.397966 -29.641878 -26.116444
--17.967083 -36.490044 -21.267710 -29.521482 -20.714117 10.630355 2.775754 32.427319 29.701410 22.186726
-19.387829 -31.321960 6.491024 -3.254502 -9.085204 22.054094 31.965021 -22.539881 -29.751919 -27.778631
-27.144449 28.251413 -27.894733 18.980383 -16.955488 -24.369068 19.126995 24.730665 28.388189 -30.265663
--22.823879 -16.743576 -0.855249 -20.405294 27.509684 21.952494 -32.309036 30.639891 30.141865 26.804674
--24.074057 1.584005 -10.435838 -21.381445 27.189999 -23.158571 -31.572952 -11.807989 31.084354 29.657049
--22.285618 14.744546 30.259914 26.419849 -29.737955 25.760761 -21.247749 26.240458 29.567011 21.174404
-8.155906 24.326309 30.161058 10.056418 -23.279669 -28.574661 32.762390 30.282391 29.276430 3.936939
--29.147345 31.067495 -32.088154 16.249660 26.796309 -26.572680 -12.852500 -13.132098 23.243259 20.810740
--26.896341 20.438314 26.042990 19.506247 20.804615 27.008863 32.395691 30.100246 -26.771997 21.191238
-7.246809 27.760994 29.059271 27.027941 3.511128 12.881917 -25.996683 -31.800346 29.468363 20.971094
-13.394855 -22.939171 -32.371952 -11.730799 -26.592562 31.801849 -23.234404 -28.626965 -23.670897 29.706806
-14.622396 29.198448 -11.544444 -7.621999 -4.405611 32.631290 28.775391 28.799553 -29.890314 -29.841303
-21.813150 21.489521 -10.591779 -27.987438 -29.199821 -7.887535 -26.221470 -27.671728 -29.797443 20.302853
-30.639811 13.334771 -8.900882 28.202700 12.857843 -6.109283 30.157297 -15.369250 31.276281 -31.603954
-7.694522 -20.468029 -0.725897 -17.788485 -34.178978 23.927425 -33.732220 4.955217 20.375965 -24.123995
--16.236792 28.180031 -27.844164 -24.859165 -23.890783 -28.153116 -21.531990 22.802910 -27.761011 23.846361
-28.526554 -27.008692 -30.810272 16.839460 -24.733376 28.403906 -15.245345 -22.803564 23.127598 24.632538
-25.869368 3.164432 26.618368 29.791756 -30.799095 13.229739 26.083759 -33.614803 26.977602 15.521008
-14.767395 -23.872744 18.893583 -25.599060 29.511194 -26.763277 -14.523918 -18.442045 -29.616571 27.419004
-23.568420 -27.056763 24.325432 -23.938623 -28.297735 -6.575099 -26.447481 24.425529 -29.128120 23.467936
-27.782188 30.725523 -1.994576 20.232574 23.253380 31.770685 25.011625 29.346586 -18.634232 24.028671
--2.991406 30.011583 -28.977139 19.140427 31.104210 25.743391 27.864761 -26.303442 5.711771 -24.898342
-23.080534 32.841953 27.434668 -26.967560 24.944504 23.324984 21.113098 -24.822979 26.371103 3.247402
-10.371755 -28.783300 30.557535 9.852886 -21.892038 29.397787 30.194834 23.821756 23.221987 -29.185167
-27.725525 20.331497 29.906160 29.985994 4.673646 -33.141441 17.755194 19.337343 11.178561 -30.378700
--29.022953 32.298927 30.623846 -27.330795 -26.317472 -13.545459 -31.038189 14.862134 6.394091 -23.130997
--27.122976 24.278252 -3.923284 -4.505970 7.424839 -33.698040 28.509602 29.525066 -14.325845 -3.606597
--23.049450 -26.757929 28.846226 -15.622251 -26.292234 12.927630 -32.268642 -23.362898 33.380123 16.713203
--26.834475 -25.778423 -25.374941 -33.272823 -8.950101 -26.951784 30.359373 23.437349 -23.741333 17.970463
-23.584236 29.477566 30.482859 24.227072 -0.161754 -28.249121 -25.205200 -22.896660 -26.021072 -27.754309
-24.359877 -15.766882 -22.589453 -28.795191 -22.054977 -25.591492 28.914436 -16.483168 -29.730721 -29.069077
-28.374998 -10.337638 -24.898254 -8.696457 -29.906717 -30.577459 -11.940366 31.599871 -23.696524 16.888037
-28.412569 -11.547874 -23.385649 5.188973 -26.594147 28.829832 30.491238 31.156525 24.449814 -22.396378
--24.123362 10.227979 -33.093067 -26.940413 19.241301 26.934536 -30.959558 -29.113039 -25.290173 24.200045
--25.407791 -28.724577 3.698982 -1.167456 32.141792 -3.179670 -27.368929 -31.284103 -29.620163 17.914351
--26.139801 -23.038982 22.281845 -17.640434 21.039083 16.812750 31.378922 30.040468 20.431204 24.787907
-8.001920 29.006453 -29.817034 -16.471649 24.109184 -22.226015 -31.618090 -31.567238 28.035131 -17.240200
-31.732470 31.900095 27.778193 -4.249768 -15.619086 24.138508 24.233559 14.618389 25.075472 30.349316
--28.288677 32.652050 -12.559782 -5.508770 -30.175503 -27.688131 6.298277 17.481476 31.894840 12.626587
--0.359956 29.207279 28.969049 -29.720470 -11.271438 0.406908 17.933264 31.816317 31.016989 -29.226896
--29.037714 31.317698 29.765678 10.190748 27.784094 -20.760891 19.971119 28.424423 -21.875158 -30.634502
-17.454336 27.734694 -28.182638 22.936987 -30.864325 24.006058 -22.265110 18.289276 -29.283976 23.994133
--28.076096 24.803003 31.810873 -28.802849 16.174349 -12.161655 -0.723460 -30.066971 -4.219203 -27.094242
--25.232018 -26.122824 8.917661 30.416269 25.667267 -23.732468 27.151720 -31.532894 21.933271 -24.658945
-4.607127 25.353094 -31.823626 18.221535 -9.143847 28.309465 27.168276 28.348866 4.025306 -16.054871
-24.069939 -6.346677 -18.416504 20.772797 29.109146 -22.270210 28.348614 -25.223400 28.465523 33.228703
--22.829838 31.330181 2.640439 23.182808 29.689547 -25.471079 31.577196 23.975561 -16.879004 27.922268
-29.727743 -26.793751 4.074662 -26.435411 9.276300 -30.378164 -22.027834 -29.494093 17.942389 32.048019
-12.443921 -31.355478 -20.997168 -26.298655 13.543483 -22.858194 27.675776 -9.945221 27.362482 27.321886
--22.948797 -16.643089 24.180367 -28.334538 30.239267 25.488913 -27.400799 27.946491 12.241156 -26.680285
--26.742994 -32.847370 0.372974 29.170841 19.595181 25.148224 25.905928 -27.588221 5.420761 22.849968
--31.289413 -25.980698 10.574203 -26.781279 23.723721 -16.573223 -29.030935 -27.023516 26.670540 -28.518023
--20.405828 2.004235 -29.175016 31.777958 18.817739 3.310179 24.954983 23.126196 -33.089378 25.994604
-24.361629 -24.034267 27.114393 -22.175446 -21.102106 26.505531 28.671572 -27.174116 27.081461 17.971365
-23.356621 -5.383027 -5.395381 30.386618 -26.971796 35.123657 25.429768 3.912057 -28.749304 27.695974
-5.089523 30.756739 -18.651115 -29.794476 -11.307332 15.305420 -30.898745 26.515871 -26.690683 31.057924
--27.608395 2.751207 31.480362 -6.192355 -15.776289 14.917231 -26.300941 -31.236757 -9.482904 -31.367132
--29.525408 13.207518 30.402412 -27.161982 -16.195581 -8.314233 6.639257 26.347960 -12.045978 31.111658
--25.366018 20.475132 27.603605 30.567028 -27.804394 21.405256 -6.385581 -26.473637 23.634207 -25.096960
-29.934078 -27.561596 21.638102 -26.487444 -7.843333 -32.990967 25.479225 23.726942 1.743223 -23.586367
--18.529795 -14.682743 -11.309550 29.943205 -32.861969 -24.109367 -11.641270 30.234364 27.131487 27.869272
-32.296886 16.968967 -28.056850 17.463118 4.709224 -25.974831 -25.367235 1.224072 -26.906301 29.314491
--25.831589 27.744438 28.279171 -23.356329 5.997526 13.055943 27.772594 -29.972574 30.874453 -6.439247
--27.270761 -26.999367 17.389296 29.682049 25.536079 -31.437716 -17.270382 18.765409 -14.157981 25.990219
--25.644127 24.661541 -30.554047 20.114891 -23.111427 22.993216 -27.149054 23.140715 20.203518 27.635824
--25.846523 22.715874 -12.718971 -3.160396 -14.715969 35.330879 -30.877163 15.205578 -22.881746 29.061197
--15.076153 23.229858 -33.552963 -0.534045 -26.019924 -30.503695 -30.021885 -26.314020 -0.870840 6.176859
--31.264351 21.678905 -23.063509 30.365349 32.470901 -10.662707 -8.933731 -26.195234 -25.810390 24.120329
-27.617683 -26.467562 24.821156 -18.866934 -30.946278 -19.225807 -19.320507 -27.095076 29.887562 -27.905640
-29.890749 -16.860283 31.453899 14.095822 6.417044 -24.313219 30.336508 -22.971561 22.078314 15.273052
-10.796197 25.368275 -14.171386 -28.335548 16.275265 -31.915974 -18.500086 -33.356716 -19.192612 33.692402
--27.123287 27.355597 -30.336468 28.779318 -32.750500 10.814196 24.501240 3.015838 23.269903 -25.158703
--21.149429 -13.080396 -28.024158 -25.943312 23.708012 -28.325745 26.544689 -25.332069 -15.316700 -32.523273
-13.809246 29.555386 19.702276 28.850292 27.295843 -28.034163 27.024630 -24.833534 26.612434 19.731405
-28.613760 -29.762756 -30.633032 9.729327 -30.736677 4.846626 25.470345 24.346096 11.554205 23.544035
--26.353815 -0.544388 26.486794 -28.141678 -28.819151 -19.970861 -30.929327 22.311621 27.651613 26.565744
-1.227070 10.043915 -22.600807 26.245567 25.942457 -30.712118 -27.150064 -30.792393 -24.804663 -30.143036
-26.438381 12.739036 29.980673 29.757868 17.797293 25.890196 28.367943 -28.205496 16.972397 -27.318939
+++ /dev/null
-4 81
- -25 -25 -50 -50
- 0 -25 -50 -50
- 25 -25 -50 -50
- -25 0 -50 -50
- 0 0 -50 -50
- 25 0 -50 -50
- -25 25 -50 -50
- 0 25 -50 -50
- 25 25 -50 -50
- -25 -25 0 -50
- 0 -25 0 -50
- 25 -25 0 -50
- -25 0 0 -50
- 0 0 0 -50
- 25 0 0 -50
- -25 25 0 -50
- 0 25 0 -50
- 25 25 0 -50
- -25 -25 50 -50
- 0 -25 50 -50
- 25 -25 50 -50
- -25 0 50 -50
- 0 0 50 -50
- 25 0 50 -50
- -25 25 50 -50
- 0 25 50 -50
- 25 25 50 -50
- -25 -25 -50 0
- 0 -25 -50 0
- 25 -25 -50 0
- -25 0 -50 0
- 0 0 -50 0
- 25 0 -50 0
- -25 25 -50 0
- 0 25 -50 0
- 25 25 -50 0
- -25 -25 0 0
- 0 -25 0 0
- 25 -25 0 0
- -25 0 0 0
- 0 0 0 0
- 25 0 0 0
- -25 25 0 0
- 0 25 0 0
- 25 25 0 0
- -25 -25 50 0
- 0 -25 50 0
- 25 -25 50 0
- -25 0 50 0
- 0 0 50 0
- 25 0 50 0
- -25 25 50 0
- 0 25 50 0
- 25 25 50 0
- -25 -25 -50 50
- 0 -25 -50 50
- 25 -25 -50 50
- -25 0 -50 50
- 0 0 -50 50
- 25 0 -50 50
- -25 25 -50 50
- 0 25 -50 50
- 25 25 -50 50
- -25 -25 0 50
- 0 -25 0 50
- 25 -25 0 50
- -25 0 0 50
- 0 0 0 50
- 25 0 0 50
- -25 25 0 50
- 0 25 0 50
- 25 25 0 50
- -25 -25 50 50
- 0 -25 50 50
- 25 -25 50 50
- -25 0 50 50
- 0 0 50 50
- 25 0 50 50
- -25 25 50 50
- 0 25 50 50
- 25 25 50 50
+++ /dev/null
-1 8
--75
--50
--25
- 0
- 25
- 50
- 75
-100
+++ /dev/null
-1 2
--50
- 50
+++ /dev/null
-1 8
--75
--50
--25
- 0
- 25
- 50
- 75
-100
+++ /dev/null
-1 4
--50
- 0
- 50
- 100
+++ /dev/null
-1 4
--50
- 0
- 50
- 100
+++ /dev/null
-6 729
- -50 -50 -50 -50 -50 -50
- 0 -50 -50 -50 -50 -50
- 50 -50 -50 -50 -50 -50
- -50 0 -50 -50 -50 -50
- 0 0 -50 -50 -50 -50
- 50 0 -50 -50 -50 -50
- -50 50 -50 -50 -50 -50
- 0 50 -50 -50 -50 -50
- 50 50 -50 -50 -50 -50
- -50 -50 0 -50 -50 -50
- 0 -50 0 -50 -50 -50
- 50 -50 0 -50 -50 -50
- -50 0 0 -50 -50 -50
- 0 0 0 -50 -50 -50
- 50 0 0 -50 -50 -50
- -50 50 0 -50 -50 -50
- 0 50 0 -50 -50 -50
- 50 50 0 -50 -50 -50
- -50 -50 50 -50 -50 -50
- 0 -50 50 -50 -50 -50
- 50 -50 50 -50 -50 -50
- -50 0 50 -50 -50 -50
- 0 0 50 -50 -50 -50
- 50 0 50 -50 -50 -50
- -50 50 50 -50 -50 -50
- 0 50 50 -50 -50 -50
- 50 50 50 -50 -50 -50
- -50 -50 -50 0 -50 -50
- 0 -50 -50 0 -50 -50
- 50 -50 -50 0 -50 -50
- -50 0 -50 0 -50 -50
- 0 0 -50 0 -50 -50
- 50 0 -50 0 -50 -50
- -50 50 -50 0 -50 -50
- 0 50 -50 0 -50 -50
- 50 50 -50 0 -50 -50
- -50 -50 0 0 -50 -50
- 0 -50 0 0 -50 -50
- 50 -50 0 0 -50 -50
- -50 0 0 0 -50 -50
- 0 0 0 0 -50 -50
- 50 0 0 0 -50 -50
- -50 50 0 0 -50 -50
- 0 50 0 0 -50 -50
- 50 50 0 0 -50 -50
- -50 -50 50 0 -50 -50
- 0 -50 50 0 -50 -50
- 50 -50 50 0 -50 -50
- -50 0 50 0 -50 -50
- 0 0 50 0 -50 -50
- 50 0 50 0 -50 -50
- -50 50 50 0 -50 -50
- 0 50 50 0 -50 -50
- 50 50 50 0 -50 -50
- -50 -50 -50 50 -50 -50
- 0 -50 -50 50 -50 -50
- 50 -50 -50 50 -50 -50
- -50 0 -50 50 -50 -50
- 0 0 -50 50 -50 -50
- 50 0 -50 50 -50 -50
- -50 50 -50 50 -50 -50
- 0 50 -50 50 -50 -50
- 50 50 -50 50 -50 -50
- -50 -50 0 50 -50 -50
- 0 -50 0 50 -50 -50
- 50 -50 0 50 -50 -50
- -50 0 0 50 -50 -50
- 0 0 0 50 -50 -50
- 50 0 0 50 -50 -50
- -50 50 0 50 -50 -50
- 0 50 0 50 -50 -50
- 50 50 0 50 -50 -50
- -50 -50 50 50 -50 -50
- 0 -50 50 50 -50 -50
- 50 -50 50 50 -50 -50
- -50 0 50 50 -50 -50
- 0 0 50 50 -50 -50
- 50 0 50 50 -50 -50
- -50 50 50 50 -50 -50
- 0 50 50 50 -50 -50
- 50 50 50 50 -50 -50
- -50 -50 -50 -50 0 -50
- 0 -50 -50 -50 0 -50
- 50 -50 -50 -50 0 -50
- -50 0 -50 -50 0 -50
- 0 0 -50 -50 0 -50
- 50 0 -50 -50 0 -50
- -50 50 -50 -50 0 -50
- 0 50 -50 -50 0 -50
- 50 50 -50 -50 0 -50
- -50 -50 0 -50 0 -50
- 0 -50 0 -50 0 -50
- 50 -50 0 -50 0 -50
- -50 0 0 -50 0 -50
- 0 0 0 -50 0 -50
- 50 0 0 -50 0 -50
- -50 50 0 -50 0 -50
- 0 50 0 -50 0 -50
- 50 50 0 -50 0 -50
- -50 -50 50 -50 0 -50
- 0 -50 50 -50 0 -50
- 50 -50 50 -50 0 -50
- -50 0 50 -50 0 -50
- 0 0 50 -50 0 -50
- 50 0 50 -50 0 -50
- -50 50 50 -50 0 -50
- 0 50 50 -50 0 -50
- 50 50 50 -50 0 -50
- -50 -50 -50 0 0 -50
- 0 -50 -50 0 0 -50
- 50 -50 -50 0 0 -50
- -50 0 -50 0 0 -50
- 0 0 -50 0 0 -50
- 50 0 -50 0 0 -50
- -50 50 -50 0 0 -50
- 0 50 -50 0 0 -50
- 50 50 -50 0 0 -50
- -50 -50 0 0 0 -50
- 0 -50 0 0 0 -50
- 50 -50 0 0 0 -50
- -50 0 0 0 0 -50
- 0 0 0 0 0 -50
- 50 0 0 0 0 -50
- -50 50 0 0 0 -50
- 0 50 0 0 0 -50
- 50 50 0 0 0 -50
- -50 -50 50 0 0 -50
- 0 -50 50 0 0 -50
- 50 -50 50 0 0 -50
- -50 0 50 0 0 -50
- 0 0 50 0 0 -50
- 50 0 50 0 0 -50
- -50 50 50 0 0 -50
- 0 50 50 0 0 -50
- 50 50 50 0 0 -50
- -50 -50 -50 50 0 -50
- 0 -50 -50 50 0 -50
- 50 -50 -50 50 0 -50
- -50 0 -50 50 0 -50
- 0 0 -50 50 0 -50
- 50 0 -50 50 0 -50
- -50 50 -50 50 0 -50
- 0 50 -50 50 0 -50
- 50 50 -50 50 0 -50
- -50 -50 0 50 0 -50
- 0 -50 0 50 0 -50
- 50 -50 0 50 0 -50
- -50 0 0 50 0 -50
- 0 0 0 50 0 -50
- 50 0 0 50 0 -50
- -50 50 0 50 0 -50
- 0 50 0 50 0 -50
- 50 50 0 50 0 -50
- -50 -50 50 50 0 -50
- 0 -50 50 50 0 -50
- 50 -50 50 50 0 -50
- -50 0 50 50 0 -50
- 0 0 50 50 0 -50
- 50 0 50 50 0 -50
- -50 50 50 50 0 -50
- 0 50 50 50 0 -50
- 50 50 50 50 0 -50
- -50 -50 -50 -50 50 -50
- 0 -50 -50 -50 50 -50
- 50 -50 -50 -50 50 -50
- -50 0 -50 -50 50 -50
- 0 0 -50 -50 50 -50
- 50 0 -50 -50 50 -50
- -50 50 -50 -50 50 -50
- 0 50 -50 -50 50 -50
- 50 50 -50 -50 50 -50
- -50 -50 0 -50 50 -50
- 0 -50 0 -50 50 -50
- 50 -50 0 -50 50 -50
- -50 0 0 -50 50 -50
- 0 0 0 -50 50 -50
- 50 0 0 -50 50 -50
- -50 50 0 -50 50 -50
- 0 50 0 -50 50 -50
- 50 50 0 -50 50 -50
- -50 -50 50 -50 50 -50
- 0 -50 50 -50 50 -50
- 50 -50 50 -50 50 -50
- -50 0 50 -50 50 -50
- 0 0 50 -50 50 -50
- 50 0 50 -50 50 -50
- -50 50 50 -50 50 -50
- 0 50 50 -50 50 -50
- 50 50 50 -50 50 -50
- -50 -50 -50 0 50 -50
- 0 -50 -50 0 50 -50
- 50 -50 -50 0 50 -50
- -50 0 -50 0 50 -50
- 0 0 -50 0 50 -50
- 50 0 -50 0 50 -50
- -50 50 -50 0 50 -50
- 0 50 -50 0 50 -50
- 50 50 -50 0 50 -50
- -50 -50 0 0 50 -50
- 0 -50 0 0 50 -50
- 50 -50 0 0 50 -50
- -50 0 0 0 50 -50
- 0 0 0 0 50 -50
- 50 0 0 0 50 -50
- -50 50 0 0 50 -50
- 0 50 0 0 50 -50
- 50 50 0 0 50 -50
- -50 -50 50 0 50 -50
- 0 -50 50 0 50 -50
- 50 -50 50 0 50 -50
- -50 0 50 0 50 -50
- 0 0 50 0 50 -50
- 50 0 50 0 50 -50
- -50 50 50 0 50 -50
- 0 50 50 0 50 -50
- 50 50 50 0 50 -50
- -50 -50 -50 50 50 -50
- 0 -50 -50 50 50 -50
- 50 -50 -50 50 50 -50
- -50 0 -50 50 50 -50
- 0 0 -50 50 50 -50
- 50 0 -50 50 50 -50
- -50 50 -50 50 50 -50
- 0 50 -50 50 50 -50
- 50 50 -50 50 50 -50
- -50 -50 0 50 50 -50
- 0 -50 0 50 50 -50
- 50 -50 0 50 50 -50
- -50 0 0 50 50 -50
- 0 0 0 50 50 -50
- 50 0 0 50 50 -50
- -50 50 0 50 50 -50
- 0 50 0 50 50 -50
- 50 50 0 50 50 -50
- -50 -50 50 50 50 -50
- 0 -50 50 50 50 -50
- 50 -50 50 50 50 -50
- -50 0 50 50 50 -50
- 0 0 50 50 50 -50
- 50 0 50 50 50 -50
- -50 50 50 50 50 -50
- 0 50 50 50 50 -50
- 50 50 50 50 50 -50
- -50 -50 -50 -50 -50 0
- 0 -50 -50 -50 -50 0
- 50 -50 -50 -50 -50 0
- -50 0 -50 -50 -50 0
- 0 0 -50 -50 -50 0
- 50 0 -50 -50 -50 0
- -50 50 -50 -50 -50 0
- 0 50 -50 -50 -50 0
- 50 50 -50 -50 -50 0
- -50 -50 0 -50 -50 0
- 0 -50 0 -50 -50 0
- 50 -50 0 -50 -50 0
- -50 0 0 -50 -50 0
- 0 0 0 -50 -50 0
- 50 0 0 -50 -50 0
- -50 50 0 -50 -50 0
- 0 50 0 -50 -50 0
- 50 50 0 -50 -50 0
- -50 -50 50 -50 -50 0
- 0 -50 50 -50 -50 0
- 50 -50 50 -50 -50 0
- -50 0 50 -50 -50 0
- 0 0 50 -50 -50 0
- 50 0 50 -50 -50 0
- -50 50 50 -50 -50 0
- 0 50 50 -50 -50 0
- 50 50 50 -50 -50 0
- -50 -50 -50 0 -50 0
- 0 -50 -50 0 -50 0
- 50 -50 -50 0 -50 0
- -50 0 -50 0 -50 0
- 0 0 -50 0 -50 0
- 50 0 -50 0 -50 0
- -50 50 -50 0 -50 0
- 0 50 -50 0 -50 0
- 50 50 -50 0 -50 0
- -50 -50 0 0 -50 0
- 0 -50 0 0 -50 0
- 50 -50 0 0 -50 0
- -50 0 0 0 -50 0
- 0 0 0 0 -50 0
- 50 0 0 0 -50 0
- -50 50 0 0 -50 0
- 0 50 0 0 -50 0
- 50 50 0 0 -50 0
- -50 -50 50 0 -50 0
- 0 -50 50 0 -50 0
- 50 -50 50 0 -50 0
- -50 0 50 0 -50 0
- 0 0 50 0 -50 0
- 50 0 50 0 -50 0
- -50 50 50 0 -50 0
- 0 50 50 0 -50 0
- 50 50 50 0 -50 0
- -50 -50 -50 50 -50 0
- 0 -50 -50 50 -50 0
- 50 -50 -50 50 -50 0
- -50 0 -50 50 -50 0
- 0 0 -50 50 -50 0
- 50 0 -50 50 -50 0
- -50 50 -50 50 -50 0
- 0 50 -50 50 -50 0
- 50 50 -50 50 -50 0
- -50 -50 0 50 -50 0
- 0 -50 0 50 -50 0
- 50 -50 0 50 -50 0
- -50 0 0 50 -50 0
- 0 0 0 50 -50 0
- 50 0 0 50 -50 0
- -50 50 0 50 -50 0
- 0 50 0 50 -50 0
- 50 50 0 50 -50 0
- -50 -50 50 50 -50 0
- 0 -50 50 50 -50 0
- 50 -50 50 50 -50 0
- -50 0 50 50 -50 0
- 0 0 50 50 -50 0
- 50 0 50 50 -50 0
- -50 50 50 50 -50 0
- 0 50 50 50 -50 0
- 50 50 50 50 -50 0
- -50 -50 -50 -50 0 0
- 0 -50 -50 -50 0 0
- 50 -50 -50 -50 0 0
- -50 0 -50 -50 0 0
- 0 0 -50 -50 0 0
- 50 0 -50 -50 0 0
- -50 50 -50 -50 0 0
- 0 50 -50 -50 0 0
- 50 50 -50 -50 0 0
- -50 -50 0 -50 0 0
- 0 -50 0 -50 0 0
- 50 -50 0 -50 0 0
- -50 0 0 -50 0 0
- 0 0 0 -50 0 0
- 50 0 0 -50 0 0
- -50 50 0 -50 0 0
- 0 50 0 -50 0 0
- 50 50 0 -50 0 0
- -50 -50 50 -50 0 0
- 0 -50 50 -50 0 0
- 50 -50 50 -50 0 0
- -50 0 50 -50 0 0
- 0 0 50 -50 0 0
- 50 0 50 -50 0 0
- -50 50 50 -50 0 0
- 0 50 50 -50 0 0
- 50 50 50 -50 0 0
- -50 -50 -50 0 0 0
- 0 -50 -50 0 0 0
- 50 -50 -50 0 0 0
- -50 0 -50 0 0 0
- 0 0 -50 0 0 0
- 50 0 -50 0 0 0
- -50 50 -50 0 0 0
- 0 50 -50 0 0 0
- 50 50 -50 0 0 0
- -50 -50 0 0 0 0
- 0 -50 0 0 0 0
- 50 -50 0 0 0 0
- -50 0 0 0 0 0
- 0 0 0 0 0 0
- 50 0 0 0 0 0
- -50 50 0 0 0 0
- 0 50 0 0 0 0
- 50 50 0 0 0 0
- -50 -50 50 0 0 0
- 0 -50 50 0 0 0
- 50 -50 50 0 0 0
- -50 0 50 0 0 0
- 0 0 50 0 0 0
- 50 0 50 0 0 0
- -50 50 50 0 0 0
- 0 50 50 0 0 0
- 50 50 50 0 0 0
- -50 -50 -50 50 0 0
- 0 -50 -50 50 0 0
- 50 -50 -50 50 0 0
- -50 0 -50 50 0 0
- 0 0 -50 50 0 0
- 50 0 -50 50 0 0
- -50 50 -50 50 0 0
- 0 50 -50 50 0 0
- 50 50 -50 50 0 0
- -50 -50 0 50 0 0
- 0 -50 0 50 0 0
- 50 -50 0 50 0 0
- -50 0 0 50 0 0
- 0 0 0 50 0 0
- 50 0 0 50 0 0
- -50 50 0 50 0 0
- 0 50 0 50 0 0
- 50 50 0 50 0 0
- -50 -50 50 50 0 0
- 0 -50 50 50 0 0
- 50 -50 50 50 0 0
- -50 0 50 50 0 0
- 0 0 50 50 0 0
- 50 0 50 50 0 0
- -50 50 50 50 0 0
- 0 50 50 50 0 0
- 50 50 50 50 0 0
- -50 -50 -50 -50 50 0
- 0 -50 -50 -50 50 0
- 50 -50 -50 -50 50 0
- -50 0 -50 -50 50 0
- 0 0 -50 -50 50 0
- 50 0 -50 -50 50 0
- -50 50 -50 -50 50 0
- 0 50 -50 -50 50 0
- 50 50 -50 -50 50 0
- -50 -50 0 -50 50 0
- 0 -50 0 -50 50 0
- 50 -50 0 -50 50 0
- -50 0 0 -50 50 0
- 0 0 0 -50 50 0
- 50 0 0 -50 50 0
- -50 50 0 -50 50 0
- 0 50 0 -50 50 0
- 50 50 0 -50 50 0
- -50 -50 50 -50 50 0
- 0 -50 50 -50 50 0
- 50 -50 50 -50 50 0
- -50 0 50 -50 50 0
- 0 0 50 -50 50 0
- 50 0 50 -50 50 0
- -50 50 50 -50 50 0
- 0 50 50 -50 50 0
- 50 50 50 -50 50 0
- -50 -50 -50 0 50 0
- 0 -50 -50 0 50 0
- 50 -50 -50 0 50 0
- -50 0 -50 0 50 0
- 0 0 -50 0 50 0
- 50 0 -50 0 50 0
- -50 50 -50 0 50 0
- 0 50 -50 0 50 0
- 50 50 -50 0 50 0
- -50 -50 0 0 50 0
- 0 -50 0 0 50 0
- 50 -50 0 0 50 0
- -50 0 0 0 50 0
- 0 0 0 0 50 0
- 50 0 0 0 50 0
- -50 50 0 0 50 0
- 0 50 0 0 50 0
- 50 50 0 0 50 0
- -50 -50 50 0 50 0
- 0 -50 50 0 50 0
- 50 -50 50 0 50 0
- -50 0 50 0 50 0
- 0 0 50 0 50 0
- 50 0 50 0 50 0
- -50 50 50 0 50 0
- 0 50 50 0 50 0
- 50 50 50 0 50 0
- -50 -50 -50 50 50 0
- 0 -50 -50 50 50 0
- 50 -50 -50 50 50 0
- -50 0 -50 50 50 0
- 0 0 -50 50 50 0
- 50 0 -50 50 50 0
- -50 50 -50 50 50 0
- 0 50 -50 50 50 0
- 50 50 -50 50 50 0
- -50 -50 0 50 50 0
- 0 -50 0 50 50 0
- 50 -50 0 50 50 0
- -50 0 0 50 50 0
- 0 0 0 50 50 0
- 50 0 0 50 50 0
- -50 50 0 50 50 0
- 0 50 0 50 50 0
- 50 50 0 50 50 0
- -50 -50 50 50 50 0
- 0 -50 50 50 50 0
- 50 -50 50 50 50 0
- -50 0 50 50 50 0
- 0 0 50 50 50 0
- 50 0 50 50 50 0
- -50 50 50 50 50 0
- 0 50 50 50 50 0
- 50 50 50 50 50 0
- -50 -50 -50 -50 -50 50
- 0 -50 -50 -50 -50 50
- 50 -50 -50 -50 -50 50
- -50 0 -50 -50 -50 50
- 0 0 -50 -50 -50 50
- 50 0 -50 -50 -50 50
- -50 50 -50 -50 -50 50
- 0 50 -50 -50 -50 50
- 50 50 -50 -50 -50 50
- -50 -50 0 -50 -50 50
- 0 -50 0 -50 -50 50
- 50 -50 0 -50 -50 50
- -50 0 0 -50 -50 50
- 0 0 0 -50 -50 50
- 50 0 0 -50 -50 50
- -50 50 0 -50 -50 50
- 0 50 0 -50 -50 50
- 50 50 0 -50 -50 50
- -50 -50 50 -50 -50 50
- 0 -50 50 -50 -50 50
- 50 -50 50 -50 -50 50
- -50 0 50 -50 -50 50
- 0 0 50 -50 -50 50
- 50 0 50 -50 -50 50
- -50 50 50 -50 -50 50
- 0 50 50 -50 -50 50
- 50 50 50 -50 -50 50
- -50 -50 -50 0 -50 50
- 0 -50 -50 0 -50 50
- 50 -50 -50 0 -50 50
- -50 0 -50 0 -50 50
- 0 0 -50 0 -50 50
- 50 0 -50 0 -50 50
- -50 50 -50 0 -50 50
- 0 50 -50 0 -50 50
- 50 50 -50 0 -50 50
- -50 -50 0 0 -50 50
- 0 -50 0 0 -50 50
- 50 -50 0 0 -50 50
- -50 0 0 0 -50 50
- 0 0 0 0 -50 50
- 50 0 0 0 -50 50
- -50 50 0 0 -50 50
- 0 50 0 0 -50 50
- 50 50 0 0 -50 50
- -50 -50 50 0 -50 50
- 0 -50 50 0 -50 50
- 50 -50 50 0 -50 50
- -50 0 50 0 -50 50
- 0 0 50 0 -50 50
- 50 0 50 0 -50 50
- -50 50 50 0 -50 50
- 0 50 50 0 -50 50
- 50 50 50 0 -50 50
- -50 -50 -50 50 -50 50
- 0 -50 -50 50 -50 50
- 50 -50 -50 50 -50 50
- -50 0 -50 50 -50 50
- 0 0 -50 50 -50 50
- 50 0 -50 50 -50 50
- -50 50 -50 50 -50 50
- 0 50 -50 50 -50 50
- 50 50 -50 50 -50 50
- -50 -50 0 50 -50 50
- 0 -50 0 50 -50 50
- 50 -50 0 50 -50 50
- -50 0 0 50 -50 50
- 0 0 0 50 -50 50
- 50 0 0 50 -50 50
- -50 50 0 50 -50 50
- 0 50 0 50 -50 50
- 50 50 0 50 -50 50
- -50 -50 50 50 -50 50
- 0 -50 50 50 -50 50
- 50 -50 50 50 -50 50
- -50 0 50 50 -50 50
- 0 0 50 50 -50 50
- 50 0 50 50 -50 50
- -50 50 50 50 -50 50
- 0 50 50 50 -50 50
- 50 50 50 50 -50 50
- -50 -50 -50 -50 0 50
- 0 -50 -50 -50 0 50
- 50 -50 -50 -50 0 50
- -50 0 -50 -50 0 50
- 0 0 -50 -50 0 50
- 50 0 -50 -50 0 50
- -50 50 -50 -50 0 50
- 0 50 -50 -50 0 50
- 50 50 -50 -50 0 50
- -50 -50 0 -50 0 50
- 0 -50 0 -50 0 50
- 50 -50 0 -50 0 50
- -50 0 0 -50 0 50
- 0 0 0 -50 0 50
- 50 0 0 -50 0 50
- -50 50 0 -50 0 50
- 0 50 0 -50 0 50
- 50 50 0 -50 0 50
- -50 -50 50 -50 0 50
- 0 -50 50 -50 0 50
- 50 -50 50 -50 0 50
- -50 0 50 -50 0 50
- 0 0 50 -50 0 50
- 50 0 50 -50 0 50
- -50 50 50 -50 0 50
- 0 50 50 -50 0 50
- 50 50 50 -50 0 50
- -50 -50 -50 0 0 50
- 0 -50 -50 0 0 50
- 50 -50 -50 0 0 50
- -50 0 -50 0 0 50
- 0 0 -50 0 0 50
- 50 0 -50 0 0 50
- -50 50 -50 0 0 50
- 0 50 -50 0 0 50
- 50 50 -50 0 0 50
- -50 -50 0 0 0 50
- 0 -50 0 0 0 50
- 50 -50 0 0 0 50
- -50 0 0 0 0 50
- 0 0 0 0 0 50
- 50 0 0 0 0 50
- -50 50 0 0 0 50
- 0 50 0 0 0 50
- 50 50 0 0 0 50
- -50 -50 50 0 0 50
- 0 -50 50 0 0 50
- 50 -50 50 0 0 50
- -50 0 50 0 0 50
- 0 0 50 0 0 50
- 50 0 50 0 0 50
- -50 50 50 0 0 50
- 0 50 50 0 0 50
- 50 50 50 0 0 50
- -50 -50 -50 50 0 50
- 0 -50 -50 50 0 50
- 50 -50 -50 50 0 50
- -50 0 -50 50 0 50
- 0 0 -50 50 0 50
- 50 0 -50 50 0 50
- -50 50 -50 50 0 50
- 0 50 -50 50 0 50
- 50 50 -50 50 0 50
- -50 -50 0 50 0 50
- 0 -50 0 50 0 50
- 50 -50 0 50 0 50
- -50 0 0 50 0 50
- 0 0 0 50 0 50
- 50 0 0 50 0 50
- -50 50 0 50 0 50
- 0 50 0 50 0 50
- 50 50 0 50 0 50
- -50 -50 50 50 0 50
- 0 -50 50 50 0 50
- 50 -50 50 50 0 50
- -50 0 50 50 0 50
- 0 0 50 50 0 50
- 50 0 50 50 0 50
- -50 50 50 50 0 50
- 0 50 50 50 0 50
- 50 50 50 50 0 50
- -50 -50 -50 -50 50 50
- 0 -50 -50 -50 50 50
- 50 -50 -50 -50 50 50
- -50 0 -50 -50 50 50
- 0 0 -50 -50 50 50
- 50 0 -50 -50 50 50
- -50 50 -50 -50 50 50
- 0 50 -50 -50 50 50
- 50 50 -50 -50 50 50
- -50 -50 0 -50 50 50
- 0 -50 0 -50 50 50
- 50 -50 0 -50 50 50
- -50 0 0 -50 50 50
- 0 0 0 -50 50 50
- 50 0 0 -50 50 50
- -50 50 0 -50 50 50
- 0 50 0 -50 50 50
- 50 50 0 -50 50 50
- -50 -50 50 -50 50 50
- 0 -50 50 -50 50 50
- 50 -50 50 -50 50 50
- -50 0 50 -50 50 50
- 0 0 50 -50 50 50
- 50 0 50 -50 50 50
- -50 50 50 -50 50 50
- 0 50 50 -50 50 50
- 50 50 50 -50 50 50
- -50 -50 -50 0 50 50
- 0 -50 -50 0 50 50
- 50 -50 -50 0 50 50
- -50 0 -50 0 50 50
- 0 0 -50 0 50 50
- 50 0 -50 0 50 50
- -50 50 -50 0 50 50
- 0 50 -50 0 50 50
- 50 50 -50 0 50 50
- -50 -50 0 0 50 50
- 0 -50 0 0 50 50
- 50 -50 0 0 50 50
- -50 0 0 0 50 50
- 0 0 0 0 50 50
- 50 0 0 0 50 50
- -50 50 0 0 50 50
- 0 50 0 0 50 50
- 50 50 0 0 50 50
- -50 -50 50 0 50 50
- 0 -50 50 0 50 50
- 50 -50 50 0 50 50
- -50 0 50 0 50 50
- 0 0 50 0 50 50
- 50 0 50 0 50 50
- -50 50 50 0 50 50
- 0 50 50 0 50 50
- 50 50 50 0 50 50
- -50 -50 -50 50 50 50
- 0 -50 -50 50 50 50
- 50 -50 -50 50 50 50
- -50 0 -50 50 50 50
- 0 0 -50 50 50 50
- 50 0 -50 50 50 50
- -50 50 -50 50 50 50
- 0 50 -50 50 50 50
- 50 50 -50 50 50 50
- -50 -50 0 50 50 50
- 0 -50 0 50 50 50
- 50 -50 0 50 50 50
- -50 0 0 50 50 50
- 0 0 0 50 50 50
- 50 0 0 50 50 50
- -50 50 0 50 50 50
- 0 50 0 50 50 50
- 50 50 0 50 50 50
- -50 -50 50 50 50 50
- 0 -50 50 50 50 50
- 50 -50 50 50 50 50
- -50 0 50 50 50 50
- 0 0 50 50 50 50
- 50 0 50 50 50 50
- -50 50 50 50 50 50
- 0 50 50 50 50 50
- 50 50 50 50 50 50
+++ /dev/null
-1 4
--50
- 0
- 50
- 100
+++ /dev/null
-1 4
--50
- 0
- 50
- 100
+++ /dev/null
-1 2
--50
- 50
+++ /dev/null
-1 2
--50
- 50
+++ /dev/null
-1 2
--50
- 50
+++ /dev/null
-10 512
-0.435217 0.668864 1.010296 1.220420 1.503978 1.784675 2.135458 2.357467 2.618905 2.738042
-0.179285 0.333160 0.500638 0.796950 1.039987 1.234969 1.652301 1.848233 2.625555 2.804968
-0.268785 0.356576 0.595753 1.044339 1.249382 1.428680 1.686986 1.864689 2.339905 2.513801
-0.120070 0.165585 0.484694 0.959160 1.237528 1.529146 1.837513 2.107730 2.487495 2.766846
-0.150214 0.229487 0.628240 0.961255 1.337065 1.598306 1.919745 2.217861 2.537318 2.759560
-0.268624 0.345980 0.569637 0.754737 0.916538 1.508543 1.786354 1.954418 2.369530 2.501822
-0.246064 0.468874 0.662711 0.890015 1.147153 1.510431 1.781056 2.095943 2.655391 2.800369
-0.191631 0.280628 0.393229 0.611761 1.420170 1.707741 1.873032 2.101553 2.280348 2.499488
-0.361668 0.507047 0.789974 1.045992 1.502378 1.677032 1.905337 2.162555 2.432259 2.590873
-0.208160 0.294285 0.448634 0.694229 0.872517 1.070315 1.703352 2.168742 2.426189 2.603657
-0.316939 0.513618 0.705487 0.917036 1.175989 1.311140 1.618599 2.037840 2.450523 2.579395
-0.241068 0.377728 0.521595 0.717203 1.310414 1.539991 1.736431 2.098926 2.297917 2.587348
-0.234937 0.281875 0.780422 1.440733 1.609428 1.756430 1.977206 2.148605 2.602032 2.722501
-0.178679 0.242672 0.416988 0.708348 0.955620 1.176671 1.781798 2.054488 2.281591 2.448112
-0.345036 0.421080 0.740887 1.165442 1.324944 1.488798 1.763463 1.906174 2.395050 2.649158
-0.249586 0.357494 0.520747 0.847195 1.428408 1.597779 1.778194 2.178502 2.413437 2.564662
-0.295235 0.574231 1.249097 1.464097 1.727559 1.926790 2.095363 2.284830 2.567065 2.722480
-0.341930 0.427307 0.634001 0.804212 0.905629 1.333373 1.790329 1.892756 2.445823 2.602828
-0.363948 0.508985 0.667357 0.946354 1.437562 1.626545 1.811141 2.039091 2.291882 2.435493
-0.163514 0.277407 0.409207 0.902065 1.189070 1.339636 1.802411 1.960770 2.652930 2.818987
-0.302643 0.359753 0.651207 1.208021 1.423702 1.548149 1.882130 2.015591 2.260535 2.578896
-0.155928 0.216908 0.381812 0.654803 1.112373 1.589935 1.847562 1.976716 2.224078 2.725337
-0.274981 0.347675 0.572000 0.736046 0.894248 1.632373 1.891391 2.056890 2.602900 2.721779
-0.154496 0.243461 0.348174 0.689505 1.573807 1.700306 1.943182 2.101580 2.564661 2.773169
-0.292612 0.466612 0.795936 1.047468 1.413693 1.750848 2.062894 2.340073 2.613612 2.769493
-0.242896 0.361500 0.555859 0.793597 0.932291 1.409467 1.863863 2.009534 2.464500 2.677491
-0.221646 0.344724 0.554564 0.729403 1.136575 1.301772 1.529181 2.163590 2.395821 2.610805
-0.160969 0.224467 0.371545 0.626879 1.160953 1.444229 1.675966 1.879779 2.478590 2.672023
-0.214172 0.341585 0.676575 0.977397 1.325429 1.720096 2.072595 2.369539 2.635285 2.778792
-0.203311 0.289438 0.458739 0.914153 1.122885 1.302925 1.583844 1.886828 2.187869 2.427039
-0.280383 0.371600 0.824827 1.100246 1.236225 1.398923 1.578041 2.016000 2.368973 2.506732
-0.170627 0.251778 0.393686 0.608347 1.287599 1.446665 1.793278 2.036554 2.310153 2.752439
-0.180580 0.288746 0.987854 1.431706 1.677216 1.915661 2.124939 2.289452 2.589612 2.754264
-0.176335 0.266263 0.445421 0.706403 0.875402 1.422918 1.758670 1.960910 2.410676 2.601751
-0.216173 0.287404 0.480696 1.009765 1.291304 1.476644 1.895584 2.064286 2.284064 2.483108
-0.176523 0.273934 0.403407 0.966139 1.304724 1.436612 1.944728 2.084836 2.544458 2.762416
-0.311836 0.550501 0.879591 1.096228 1.276661 1.477859 1.817706 2.154340 2.560467 2.779841
-0.179765 0.250560 0.455939 1.023886 1.225132 1.475662 1.734617 1.918713 2.147342 2.438235
-0.271033 0.457235 0.599622 0.821049 0.940125 1.200937 1.849716 1.986656 2.548168 2.751578
-0.179326 0.248002 0.426405 0.817060 1.285888 1.565019 2.117359 2.298712 2.572404 2.752701
-0.374409 0.535936 0.897009 1.185070 1.591569 1.757202 1.967944 2.179985 2.457394 2.622641
-0.185472 0.282752 0.409439 0.657499 0.856446 1.029396 1.879933 2.069323 2.344742 2.753103
-0.375964 0.578457 0.758945 0.929339 1.127475 1.259437 1.704109 2.122973 2.336031 2.498298
-0.225641 0.361030 0.501679 0.783379 1.314851 1.452621 1.714150 1.987157 2.225703 2.724361
-0.144996 0.252919 0.632145 1.226038 1.575343 1.901549 2.171481 2.390554 2.682293 2.809834
-0.172022 0.263338 0.448634 0.729435 0.984007 1.171597 1.757049 1.990232 2.321305 2.771210
-0.235731 0.351117 0.796871 1.055711 1.300224 1.591818 1.895875 2.122918 2.417888 2.599817
-0.254053 0.319371 0.455623 1.086141 1.664667 1.915882 2.059084 2.233416 2.452037 2.586788
-0.375538 0.742993 1.139911 1.337758 1.735562 2.013906 2.315012 2.483433 2.651575 2.755211
-0.247245 0.481131 0.710366 0.897602 1.121094 1.271709 1.787346 2.199502 2.429663 2.740668
-0.226103 0.311441 0.501648 0.844424 1.362818 1.531338 1.777474 1.989925 2.187493 2.358501
-0.195862 0.296224 0.609554 0.783241 1.243472 1.445477 1.637032 2.022645 2.483557 2.646137
-0.233302 0.299441 0.472792 1.249457 1.457875 1.601860 1.831433 1.993719 2.597193 2.755433
-0.168096 0.224183 0.382700 0.596214 1.060587 1.294418 1.605760 1.848489 2.357695 2.569186
-0.330050 0.445912 0.661713 0.874446 1.000792 1.452973 1.943987 2.076916 2.423883 2.612359
-0.226382 0.287303 0.517631 0.806229 1.309009 1.885280 2.160514 2.286410 2.526377 2.660822
-0.203170 0.499314 0.887358 1.235074 1.462922 1.698260 1.999316 2.229225 2.571613 2.766691
-0.307531 0.378353 0.573606 0.712218 0.850169 1.308996 2.059092 2.263816 2.497943 2.676815
-0.276203 0.510250 0.686800 0.902844 1.205197 1.327979 1.718894 2.038947 2.256393 2.697149
-0.161948 0.229115 0.393619 0.683613 1.137811 1.322692 1.783723 1.961584 2.389073 2.636082
-0.201334 0.276773 0.468994 0.967017 1.475971 1.632424 1.965774 2.197278 2.480593 2.701553
-0.214587 0.315421 0.469498 0.733397 1.146003 1.277911 1.727839 2.227135 2.440264 2.681122
-0.255602 0.394609 0.743393 0.977796 1.199085 1.405972 1.918336 2.224828 2.479187 2.663394
-0.245989 0.352625 0.517055 0.802830 1.558712 1.795653 1.944055 2.133640 2.333267 2.479982
-0.337423 0.480433 0.869036 1.139571 1.630764 1.822959 2.074843 2.292613 2.479130 2.625317
-0.220974 0.358850 0.571640 0.752791 0.937013 1.151721 1.674398 2.062466 2.558717 2.784838
-0.267518 0.331708 0.541111 1.116547 1.411121 1.532868 1.792949 1.933520 2.248940 2.628644
-0.084613 0.105083 0.297424 0.916949 1.256301 1.567029 1.885388 2.189875 2.522795 2.792102
-0.205328 0.287223 0.724462 1.032395 1.457708 1.642169 1.925628 2.175524 2.429638 2.605488
-0.232554 0.338724 0.502115 0.859975 1.044090 1.245652 1.806555 1.999641 2.261164 2.459984
-0.291638 0.379172 0.626072 0.792796 0.959124 1.504886 1.734465 1.919612 2.614359 2.722709
-0.191554 0.263114 0.426797 0.610628 1.077406 1.829543 2.021948 2.210572 2.427652 2.613828
-0.389151 0.679476 0.915414 1.036635 1.250846 1.586610 2.040972 2.281500 2.567941 2.718815
-0.203200 0.301280 0.470357 0.668716 0.851737 0.980327 1.570862 2.037617 2.289067 2.693877
-0.304064 0.405934 0.710274 0.962705 1.128820 1.341667 1.635050 1.845382 2.079916 2.507510
-0.171777 0.240705 0.409371 0.786432 1.223202 1.375689 1.691760 1.866080 2.350406 2.493942
-0.231251 0.277994 0.557867 1.325822 1.660352 1.779477 2.007138 2.172322 2.440457 2.652308
-0.188101 0.259494 0.412543 0.624843 0.839549 1.033700 1.634128 1.931944 2.246076 2.425773
-0.361304 0.419465 0.795676 1.184605 1.296796 1.578447 1.841746 1.997361 2.540538 2.687139
-0.274372 0.338938 0.492443 0.963516 1.509514 1.706378 1.869885 2.077166 2.261281 2.444183
-0.415990 0.652103 1.031293 1.269551 1.572746 1.772975 2.004659 2.175272 2.430606 2.596553
-0.242045 0.370942 0.534392 0.763529 1.001165 1.129764 1.682192 2.144644 2.324478 2.715697
-0.377438 0.588168 0.765394 0.976873 1.356652 1.490088 1.737970 2.006774 2.213691 2.389973
-0.191625 0.284123 0.405342 1.016777 1.432730 1.547592 1.813930 1.958317 2.470765 2.649257
-0.272672 0.349555 0.633911 1.152234 1.303938 1.547640 1.919504 2.047696 2.562779 2.730575
-0.168423 0.236330 0.421468 0.831345 1.083543 1.553448 1.880726 2.064701 2.370864 2.632945
-0.219318 0.301481 0.513617 0.765086 1.026019 1.514647 2.048203 2.248568 2.499810 2.657069
-0.232695 0.347947 0.495203 0.718830 1.423013 1.722493 1.879584 2.165044 2.420251 2.589658
-0.270284 0.336865 0.684929 1.155789 1.690421 1.876744 2.027359 2.226178 2.446748 2.582000
-0.149701 0.193747 0.352019 0.520123 0.823974 1.434753 1.686592 1.961148 2.370914 2.693067
-0.254818 0.412303 0.601514 0.771438 1.175450 1.376569 1.539029 1.937039 2.408576 2.563621
-0.233713 0.355886 0.593725 0.762880 1.271479 1.563900 1.797523 2.094688 2.538627 2.711734
-0.179028 0.237103 0.396818 1.042021 1.633539 1.762676 2.123935 2.322391 2.588193 2.751345
-0.182027 0.251039 0.434581 0.714302 0.950997 1.437895 1.813570 1.969103 2.145882 2.353968
-0.501538 0.692148 0.848860 1.071308 1.350543 1.489476 1.841643 2.104284 2.341536 2.515294
-0.274530 0.381470 0.526682 0.922143 1.444946 1.573605 1.858767 2.066747 2.284796 2.626819
-0.360617 0.583131 0.979491 1.254083 1.488351 1.797557 2.219518 2.482176 2.742366 2.862025
-0.140913 0.220301 0.619552 0.818307 1.052429 1.339972 1.830726 2.133953 2.536378 2.751128
-0.293514 0.391691 0.790080 0.962740 1.160319 1.526602 1.805491 2.041462 2.361619 2.564962
-0.199542 0.290571 0.452891 0.689515 1.258530 1.409879 1.886242 2.228126 2.465677 2.726646
-0.296920 0.356356 0.784287 0.996540 1.146175 1.623865 1.815498 2.038297 2.600627 2.705700
-0.206451 0.276025 0.537547 0.802572 1.220407 1.642060 1.863625 2.001978 2.215339 2.585384
-0.333650 0.464751 0.653772 0.966306 1.103865 1.340203 1.784701 1.914591 2.470171 2.686916
-0.181861 0.244870 0.376456 0.554383 1.329897 1.810440 2.047836 2.202318 2.660855 2.817057
-0.450565 0.647291 0.951172 1.229431 1.519644 1.686812 2.049107 2.267169 2.501284 2.650596
-0.219996 0.320591 0.427747 0.601183 0.753448 0.929578 1.741979 2.285789 2.472633 2.749566
-0.333848 0.423373 0.658791 1.031299 1.222625 1.365771 1.901889 2.121101 2.290306 2.531185
-0.166064 0.233902 0.383355 0.661806 1.226567 1.399684 1.771269 1.974537 2.173487 2.566344
-0.189286 0.243602 0.390584 1.387930 1.588719 1.763237 2.091118 2.316314 2.593526 2.755080
-0.158404 0.224878 0.385000 0.668463 0.942954 1.411967 1.700313 1.828069 2.059396 2.692546
-0.325989 0.461263 0.851471 1.045709 1.284028 1.516199 1.797341 2.088387 2.437669 2.627215
-0.223709 0.289190 0.632812 0.858738 1.541903 1.746766 1.935738 2.184816 2.404330 2.583013
-0.545842 0.952420 1.340820 1.516838 1.838879 2.012890 2.244968 2.403170 2.592285 2.691119
-0.238526 0.349079 0.494582 0.987665 1.170746 1.348229 1.468645 2.296964 2.644160 2.787381
-0.270857 0.442003 0.655998 0.881913 1.259254 1.428358 1.769867 1.998528 2.395589 2.652840
-0.154384 0.211806 0.489481 0.997257 1.249817 1.541232 1.778865 1.949397 2.319136 2.623391
-0.268258 0.312888 0.589114 1.258625 1.572705 1.675430 1.912780 2.070458 2.279933 2.564230
-0.170715 0.224965 0.374011 0.540197 1.161887 1.499072 1.925865 2.082569 2.246619 2.469724
-0.324358 0.391989 0.706816 0.833614 1.015725 1.568995 1.735976 2.127068 2.558411 2.653871
-0.178059 0.258575 0.374125 0.536831 1.334827 1.798628 1.986978 2.189252 2.432266 2.626696
-0.198857 0.420955 0.817664 1.178363 1.466742 1.821295 2.207327 2.474411 2.738275 2.851185
-0.188344 0.324302 0.470468 0.790033 0.934101 1.188722 1.887171 2.052833 2.448325 2.630236
-0.201295 0.365646 0.526513 0.758388 1.140096 1.267331 1.650173 1.879342 2.102889 2.600286
-0.135058 0.169428 0.307348 0.503160 1.018083 1.447946 1.810984 2.134002 2.480277 2.759846
-0.178006 0.266610 0.390327 0.928681 1.501613 1.621327 1.871356 2.025864 2.580442 2.770801
-0.246182 0.424290 0.644023 0.801168 1.114876 1.277757 1.503317 2.074888 2.295695 2.501380
-0.322996 0.430355 0.631600 1.047698 1.221840 1.426726 1.903081 2.032223 2.516726 2.708452
-0.292994 0.430599 0.619178 0.794567 1.283029 1.652817 1.840836 2.069946 2.385375 2.528246
-0.525494 0.787797 1.121816 1.387482 1.674574 1.936221 2.224042 2.390624 2.634276 2.743234
-0.299504 0.409196 0.602235 0.892336 1.056426 1.253766 1.489136 1.639876 2.427480 2.650368
-0.423758 0.520480 0.758987 1.041257 1.173655 1.423676 1.818235 1.936407 2.363001 2.626644
-0.155042 0.247496 0.641445 0.954509 1.224970 1.465850 1.837841 2.090456 2.451501 2.716155
-0.251949 0.421094 0.706797 0.975659 1.259906 1.520067 1.816310 2.122017 2.474913 2.716671
-0.215220 0.302248 0.730598 0.896343 1.145567 1.370192 1.700685 2.022563 2.283265 2.489220
-0.285230 0.453559 0.663670 0.861526 1.011602 1.247419 1.655985 1.861291 2.578936 2.731333
-0.162067 0.219409 0.373433 0.544669 1.103298 1.597178 1.921040 2.143402 2.406499 2.660484
-0.342367 0.511499 0.931350 1.163219 1.393645 1.611146 1.972769 2.194416 2.470766 2.649264
-0.251010 0.364125 0.560956 0.746545 1.019837 1.170725 1.532945 2.288671 2.577088 2.723074
-0.315001 0.489412 0.720682 0.877607 1.090466 1.253848 1.448221 1.922954 2.255887 2.408634
-0.174666 0.235793 0.387644 0.554402 1.231089 1.456137 1.688034 2.127450 2.367035 2.597270
-0.215113 0.341915 1.043717 1.322751 1.495414 1.741895 1.961164 2.239824 2.544905 2.703945
-0.219852 0.301770 0.513912 0.705474 0.877540 1.295896 1.699002 1.987057 2.287968 2.496966
-0.290638 0.366442 0.655155 1.044990 1.172154 1.532536 1.800791 1.948931 2.509679 2.660055
-0.232252 0.313770 0.658552 0.941977 1.463174 1.665488 1.862461 2.027843 2.534016 2.701236
-0.326539 0.552681 1.121731 1.331381 1.520072 1.867084 2.082861 2.332474 2.606039 2.737092
-0.190254 0.340428 0.492777 0.739738 0.895461 1.079371 1.643156 1.795290 2.491822 2.729382
-0.283586 0.418440 0.587306 0.870866 1.418553 1.577030 1.799498 2.069398 2.274484 2.438103
-0.235752 0.357650 0.502891 1.012434 1.258853 1.407789 1.820057 1.955830 2.505903 2.734330
-0.278412 0.343137 0.849977 1.232895 1.350504 1.590626 1.787519 2.091578 2.541360 2.663856
-0.162966 0.243159 0.439238 0.684821 0.887783 1.462899 1.881739 2.044253 2.289393 2.705002
-0.235063 0.371799 0.578210 0.752199 1.008546 1.476284 1.804912 2.271399 2.655042 2.789653
-0.154939 0.223696 0.344718 0.667555 1.495659 1.669436 2.069883 2.307215 2.627692 2.811343
-0.239702 0.335917 0.716616 1.131805 1.452514 1.639133 2.105515 2.279822 2.502030 2.669220
-0.226818 0.331261 0.472705 0.651974 0.781639 1.219798 1.822904 2.082732 2.439327 2.610900
-0.223413 0.359594 0.534704 0.741518 1.225894 1.389874 1.618191 2.009911 2.207000 2.459844
-0.171308 0.268378 0.383799 0.858926 1.376293 1.519165 1.780601 1.922915 2.623094 2.802402
-0.140134 0.212320 0.443224 0.967457 1.264241 1.562153 1.929148 2.217388 2.668341 2.830751
-0.221323 0.322124 0.485563 0.818589 1.011837 1.198984 1.423616 1.669403 2.157523 2.363190
-0.369687 0.525655 0.719213 0.939654 1.137631 1.312217 1.599935 1.826813 2.355221 2.580680
-0.211975 0.314411 0.489148 0.739213 1.377801 1.554504 1.824373 2.158875 2.352992 2.722621
-0.170698 0.296368 0.934285 1.243133 1.555900 1.866544 2.159940 2.363436 2.585032 2.738530
-0.189263 0.305887 0.439912 0.784610 1.227264 1.342508 1.587650 1.754907 2.439893 2.721315
-0.296339 0.385169 0.612012 1.081322 1.276361 1.437178 1.871470 2.001718 2.339094 2.640217
-0.229588 0.320544 0.517278 0.969137 1.142560 1.626089 1.877916 2.115461 2.546741 2.708025
-0.248869 0.420193 0.732388 1.049015 1.303410 1.601458 1.949210 2.239464 2.648223 2.822614
-0.207600 0.292320 0.496539 0.857149 1.182294 1.399849 1.714165 1.868238 2.027936 2.200737
-0.225558 0.396897 0.541783 0.873366 1.178972 1.299579 1.677191 1.849602 2.330475 2.752717
-0.176821 0.231377 0.372767 0.508565 1.152819 1.808050 2.112679 2.250073 2.571342 2.748550
-0.352149 0.515765 1.023238 1.260221 1.443565 1.622067 1.872804 2.100177 2.489280 2.671043
-0.166138 0.263444 0.370151 0.590066 0.754819 0.940533 1.761870 1.946611 2.445015 2.758191
-0.342082 0.476411 0.656223 0.851774 1.003992 1.153372 1.694401 2.065625 2.255642 2.440148
-0.227237 0.376514 0.514329 0.894887 1.141673 1.283052 1.831377 1.985902 2.334470 2.784878
-0.215891 0.269548 0.684111 1.405658 1.674813 1.800925 2.172085 2.339395 2.591569 2.730100
-0.236240 0.400377 0.533684 0.750343 0.910405 1.089112 1.737729 1.912807 2.192519 2.688733
-0.169242 0.284879 0.916252 1.169769 1.433683 1.644376 1.919124 2.161625 2.482664 2.682591
-0.270731 0.336506 0.477594 1.042714 1.605840 1.796859 1.945909 2.160039 2.354913 2.520950
-0.420586 0.652563 1.117162 1.406006 1.747537 1.947424 2.203094 2.359970 2.547902 2.682168
-0.281552 0.395037 0.640181 0.944531 1.193959 1.330492 1.718657 2.188389 2.444591 2.578673
-0.311824 0.476892 0.633431 0.845825 1.332518 1.491656 1.693614 2.041082 2.289317 2.439399
-0.133945 0.200790 0.647237 0.927687 1.188883 1.369658 1.699557 1.972777 2.295259 2.678185
-0.204796 0.278215 0.443465 1.270484 1.405209 1.640920 1.824252 2.327085 2.599637 2.772533
-0.183970 0.244116 0.410594 0.639103 1.221589 1.404867 1.628358 1.902439 2.168632 2.306804
-0.343622 0.434735 0.666599 0.868069 1.048942 1.532778 1.819835 1.971884 2.288701 2.448745
-0.238017 0.320361 0.657255 0.917611 1.303306 1.727361 1.988909 2.181455 2.442965 2.613322
-0.323613 0.545056 0.930173 1.226059 1.440181 1.772300 2.056890 2.347811 2.689382 2.820616
-0.288930 0.401387 0.617124 0.836453 0.990306 1.261227 1.913283 2.110049 2.324584 2.557162
-0.332670 0.480804 0.656147 0.880536 1.029566 1.230493 1.769063 1.932296 2.200370 2.585210
-0.185551 0.265352 0.409432 0.608847 1.034698 1.222821 1.876965 2.171647 2.403502 2.666441
-0.155026 0.223348 0.401684 1.079141 1.415789 1.620021 2.045515 2.258512 2.631625 2.802291
-0.183461 0.263081 0.425694 0.635685 1.188664 1.357556 1.574991 2.085982 2.288725 2.511108
-0.314738 0.463011 0.648733 0.877651 1.002890 1.265811 2.005414 2.198095 2.481535 2.714178
-0.244411 0.318444 0.546578 0.793615 1.326150 1.735479 1.945598 2.114662 2.315350 2.478535
-0.326237 0.543540 0.987361 1.304413 1.684932 1.902147 2.207172 2.374273 2.557527 2.716216
-0.157795 0.283302 0.430398 0.660379 0.811060 1.142539 1.479298 1.718714 2.670264 2.847556
-0.220856 0.283872 0.779935 1.074940 1.312211 1.626329 1.837609 1.968885 2.155988 2.602381
-0.140763 0.205719 0.406561 0.762459 1.041266 1.486993 1.838306 2.114606 2.552810 2.772285
-0.140451 0.395920 0.792110 1.108001 1.402642 1.623079 1.943151 2.227952 2.546163 2.773998
-0.229862 0.336462 0.546590 0.810150 1.201906 1.346787 1.825323 2.092925 2.285730 2.473359
-0.224913 0.328246 0.517269 0.874793 1.012587 1.452178 1.695778 2.014930 2.511447 2.672574
-0.247745 0.335741 0.546558 0.710177 1.170556 1.727789 1.970678 2.158532 2.482819 2.628913
-0.398252 0.555087 0.890367 1.121205 1.381533 1.601228 1.866647 2.066612 2.405164 2.588016
-0.198563 0.288867 0.478054 0.658477 0.851841 1.027105 1.539739 2.021106 2.579462 2.784184
-0.304271 0.371642 0.661590 1.068976 1.224249 1.411927 1.680524 1.869770 2.100073 2.308554
-0.188223 0.257939 0.432402 0.735050 1.318038 1.485528 1.828110 2.046435 2.307018 2.457237
-0.246723 0.297276 0.604475 1.310901 1.570442 1.688851 1.913658 2.051334 2.556011 2.714965
-0.158309 0.234509 0.435792 0.667900 0.957567 1.235918 1.592945 1.818158 2.307389 2.768973
-0.419843 0.501412 0.766892 1.073173 1.189374 1.480225 1.766597 1.922151 2.537937 2.694771
-0.275140 0.335563 0.678421 1.081521 1.592379 1.772635 1.931245 2.140699 2.333804 2.490857
-0.372056 0.856814 1.239538 1.409989 1.690297 1.863018 2.072702 2.273547 2.532657 2.690517
-0.321254 0.422981 0.604856 0.793437 0.912112 1.128454 1.795979 2.173232 2.360146 2.536137
-0.395214 0.598779 0.771997 0.946713 1.213777 1.330433 1.660335 1.977154 2.165056 2.344018
-0.225286 0.317828 0.464801 1.112329 1.369512 1.511999 1.921954 2.053407 2.593519 2.777285
-0.330612 0.407807 0.730129 1.259731 1.459811 1.605671 1.981307 2.137009 2.465971 2.679722
-0.213145 0.305305 0.507016 0.662299 1.056848 1.479862 1.671904 2.102707 2.369871 2.581994
-0.219658 0.296096 0.443507 0.610973 0.799691 1.676579 1.965487 2.153235 2.502228 2.692999
-0.174947 0.257739 0.373547 0.552567 1.405316 1.614249 1.848917 2.117795 2.317884 2.711904
-0.209667 0.297529 0.756195 1.095304 1.564196 1.844775 2.103697 2.292657 2.520051 2.679489
-0.170138 0.240310 0.452247 0.684414 0.880102 1.366921 1.741648 2.131295 2.505730 2.732611
-0.278164 0.468635 0.707518 0.853693 1.054780 1.210458 1.540941 2.174562 2.410662 2.612138
-0.155738 0.238890 0.352836 0.621012 1.441438 1.619698 1.825165 1.975331 2.525373 2.748574
-0.223776 0.274424 0.479048 0.797871 1.694190 1.878135 2.135285 2.373726 2.595422 2.729787
-0.151088 0.198286 0.326558 0.536276 0.845893 1.141653 1.460565 1.762868 2.025851 2.177303
-0.434445 0.614208 0.887657 1.028446 1.191359 1.392204 1.786886 2.062481 2.423405 2.619356
-0.180755 0.275311 0.397787 0.859366 1.409762 1.523325 1.908846 2.082319 2.389720 2.743887
-0.275975 0.508416 0.889894 1.318925 1.633314 1.904728 2.169012 2.374655 2.726973 2.847666
-0.156239 0.262624 0.406657 0.739074 1.044495 1.201234 1.810887 2.005600 2.581700 2.804889
-0.195391 0.258771 0.654924 0.824371 1.315259 1.500728 1.765938 2.063992 2.341176 2.513659
-0.178034 0.301047 0.463020 0.716172 1.198868 1.340454 1.834558 2.022132 2.400750 2.776294
-0.340368 0.404236 0.843747 1.039238 1.202107 1.708051 1.914952 2.169509 2.521521 2.623348
-0.218465 0.289694 0.528045 0.817051 1.132337 1.580464 1.838891 1.983392 2.147493 2.348131
-0.322509 0.458058 0.654679 0.958976 1.118211 1.321565 1.901390 2.046409 2.360931 2.664215
-0.191821 0.252321 0.389176 0.581111 1.529667 1.931689 2.083614 2.270465 2.566855 2.713879
-0.493961 0.710827 0.982260 1.196274 1.419327 1.620910 1.928015 2.145652 2.429769 2.601973
-0.213148 0.311589 0.424636 0.602664 0.736895 1.022165 1.992278 2.218533 2.611628 2.850324
-0.288129 0.434441 0.629313 0.856153 1.289667 1.424520 1.875795 2.150240 2.351814 2.536843
-0.160031 0.230716 0.406654 0.870424 1.156517 1.392317 1.804098 1.951437 2.210479 2.735164
-0.229340 0.293962 0.503222 1.242097 1.475824 1.624647 1.998680 2.144499 2.578549 2.753270
-0.158770 0.220035 0.363386 0.577761 0.963090 1.174939 1.738169 1.979202 2.162436 2.661916
-0.346062 0.444816 0.716985 1.180717 1.370580 1.522996 1.892173 2.066682 2.395796 2.627659
-0.307495 0.389330 0.612607 0.969283 1.557708 1.839939 1.996737 2.172382 2.420627 2.539195
-0.437804 0.726957 1.291168 1.503297 1.765428 1.962121 2.163647 2.336227 2.579616 2.708524
-0.232184 0.333678 0.528368 0.706749 1.203280 1.379018 1.611161 2.154678 2.592903 2.750319
-0.272652 0.461710 0.625777 0.839609 1.342021 1.496726 1.715376 2.137572 2.370040 2.597390
-0.184908 0.302324 0.454883 0.880307 1.104383 1.292526 1.777203 1.943364 2.444174 2.622726
-0.265644 0.341261 0.553228 1.139475 1.427148 1.560441 1.933941 2.084129 2.393307 2.654135
-0.167920 0.207301 0.370331 0.525538 1.030891 1.368163 1.782474 2.062404 2.332762 2.526299
-0.343172 0.433912 0.717501 0.889734 1.052060 1.695278 2.053156 2.208456 2.608869 2.718320
-0.216527 0.305247 0.445890 0.729271 1.639736 1.903284 2.053351 2.221254 2.432253 2.568018
-0.110545 0.209955 0.844788 1.174205 1.492201 1.810243 2.177274 2.440496 2.697294 2.835232
-0.217384 0.337412 0.488999 0.761842 0.879715 1.209528 1.970747 2.120795 2.611654 2.791762
-0.190459 0.296484 0.469967 0.800649 1.105561 1.278527 1.516938 1.693066 2.114420 2.716739
-0.134814 0.175978 0.300425 0.496817 1.244295 1.485308 1.861721 2.131233 2.485046 2.773884
-0.210174 0.278266 0.435508 0.927538 1.606908 1.753898 1.957554 2.166283 2.398518 2.749609
-0.213766 0.315300 0.509924 0.709930 0.964724 1.106776 1.382615 2.001070 2.323214 2.565314
-0.400615 0.524954 0.798552 1.012852 1.135488 1.474850 1.989029 2.130909 2.507971 2.679460
-0.249400 0.377023 0.519635 0.754227 1.459559 1.642762 1.828961 2.077882 2.298228 2.467534
-0.473365 0.683973 1.052341 1.375830 1.548106 1.747589 2.139299 2.318768 2.609977 2.739255
-0.203877 0.341791 0.485180 0.884069 1.097592 1.269532 1.479924 1.757879 2.648399 2.822387
-0.273046 0.404254 0.555403 0.954547 1.291233 1.399022 1.722890 1.903441 2.171984 2.645312
-0.040369 0.117266 0.617136 0.892043 1.260331 1.541653 1.859383 2.153096 2.498232 2.761886
-0.132414 0.211358 0.742445 1.066857 1.331084 1.570793 1.867458 2.132535 2.479624 2.731076
-0.237329 0.326529 0.612538 0.790663 0.990133 1.413736 1.738235 1.936914 2.167728 2.451626
-0.273960 0.405794 0.572530 0.933672 1.057816 1.397952 1.856531 1.997548 2.599486 2.760042
-0.199334 0.298380 0.442931 0.628638 1.303213 1.640138 1.804023 2.113020 2.375455 2.548946
-0.350188 0.502010 0.821298 1.038639 1.369294 1.592404 1.910815 2.156486 2.460508 2.653260
-0.281558 0.399892 0.573105 0.753299 0.900613 1.054574 1.581987 2.178437 2.430354 2.616044
-0.344653 0.543532 0.703715 0.862285 1.198215 1.338208 1.579080 2.060769 2.306749 2.485749
-0.220701 0.326795 0.520618 0.755133 1.295552 1.451886 1.690502 2.200045 2.414271 2.615909
-0.279478 0.332193 0.801527 1.345966 1.487477 1.678499 1.922202 2.100025 2.585571 2.713387
-0.163502 0.212169 0.365096 0.525464 0.869846 1.208807 1.793988 2.040314 2.297180 2.469797
-0.285531 0.341488 0.754059 1.170016 1.300835 1.513696 1.699861 1.889918 2.581459 2.706874
-0.249595 0.366997 0.626427 0.945219 1.407043 1.560558 1.831657 2.231149 2.466354 2.654518
-0.271671 0.443136 1.156412 1.406456 1.676521 1.856481 2.063218 2.230498 2.475840 2.639575
-0.286620 0.427806 0.637320 0.803409 0.996161 1.266383 1.681751 2.003968 2.394651 2.588547
-0.314906 0.440519 0.612129 0.896126 1.472415 1.717693 1.881351 2.099437 2.369166 2.495466
-0.170277 0.251270 0.405477 0.915641 1.126887 1.436630 1.714771 1.893198 2.552995 2.738519
-0.279410 0.337137 0.734563 1.281046 1.480602 1.611880 1.853215 1.994883 2.416054 2.654827
-0.165776 0.226083 0.417544 0.744574 1.044468 1.534891 1.808494 1.944946 2.138491 2.601790
-0.264579 0.336652 0.542033 0.710190 0.913338 1.655751 1.817762 2.231956 2.524436 2.658519
-0.158194 0.235588 0.338347 0.541657 1.583377 1.766293 2.009135 2.243336 2.503941 2.775158
-0.332612 0.509620 0.822935 1.075876 1.454286 1.650788 1.974450 2.251279 2.537342 2.745115
-0.262817 0.359709 0.520893 0.707667 0.818364 1.438849 1.971249 2.087666 2.497014 2.646442
-0.233200 0.399599 0.612456 0.775547 1.199192 1.355765 1.646901 2.136245 2.342490 2.695742
-0.149687 0.238538 0.372248 0.634520 1.255813 1.433790 1.770041 1.928752 2.611905 2.824930
-0.137016 0.210297 0.591489 1.125451 1.375648 1.685296 2.089612 2.390888 2.704458 2.844434
-0.213490 0.341024 0.541716 0.750061 1.088199 1.244576 1.555338 1.965568 2.187900 2.383714
-0.300159 0.489291 0.825022 1.037100 1.194088 1.347375 1.684747 2.024936 2.465611 2.740973
-0.170029 0.255033 0.392758 0.727117 1.382065 1.579676 1.800912 1.959072 2.282335 2.728796
-0.175883 0.365509 1.112175 1.385866 1.720391 1.977810 2.245295 2.421614 2.629567 2.754004
-0.162590 0.248164 0.454630 0.763209 0.966031 1.282338 1.730743 1.938052 2.479376 2.667563
-0.258043 0.345866 0.556520 0.981312 1.361528 1.482377 1.872244 2.158226 2.362269 2.555030
-0.234139 0.348843 0.528234 0.987884 1.195217 1.422145 1.960028 2.127365 2.603321 2.793004
-0.179699 0.559209 0.867682 1.088835 1.316888 1.571498 1.922198 2.197391 2.501118 2.728679
-0.216784 0.310791 0.487492 0.932903 1.201954 1.366554 1.800398 1.977499 2.174265 2.537065
-0.186878 0.400655 0.580952 0.846287 1.103872 1.266778 1.842772 2.019592 2.488005 2.717222
-0.164641 0.248712 0.389358 0.772822 1.212561 1.369916 2.025869 2.277615 2.617524 2.809527
-0.351899 0.520326 0.926597 1.219651 1.509839 1.676837 1.921744 2.111253 2.356380 2.545934
-0.242182 0.365285 0.506156 0.716020 0.865221 1.011688 1.786917 2.122981 2.350877 2.767729
-0.413776 0.559566 0.735800 0.928997 1.079117 1.267179 1.880069 2.152492 2.324834 2.539856
-0.210597 0.329568 0.469735 0.788590 1.215495 1.319810 1.711456 2.058991 2.245438 2.653727
-0.197937 0.254148 0.477985 1.227090 1.629920 1.767432 2.186975 2.385104 2.594869 2.725544
-0.205489 0.333855 0.523915 0.706275 1.102152 1.246608 1.648901 2.026835 2.281695 2.759313
-0.230328 0.322431 0.861834 1.145614 1.347211 1.576111 1.807275 2.004824 2.354365 2.572251
-0.224898 0.282022 0.506636 1.152298 1.626560 1.752095 2.028178 2.218821 2.488955 2.670460
-0.313732 0.625469 1.164472 1.499077 1.749612 2.018528 2.262230 2.429601 2.692165 2.822502
-0.375623 0.575307 0.791200 0.935770 1.096937 1.343393 1.807992 2.187306 2.519720 2.694803
-0.236981 0.332412 0.479270 0.844461 1.347641 1.490733 1.683942 2.039143 2.297619 2.458431
-0.129047 0.206250 0.636751 0.865101 1.136893 1.356610 1.704798 1.916685 2.518358 2.756320
-0.195171 0.266517 0.414793 1.239561 1.452906 1.608357 1.833045 2.047802 2.473522 2.621994
-0.165853 0.212720 0.372757 0.536136 1.013938 1.339627 1.555122 1.945745 2.236281 2.440949
-0.256981 0.368868 0.635878 0.802543 1.084757 1.439120 1.814729 2.120519 2.458154 2.621456
-0.214382 0.297135 0.445091 0.702050 1.365102 1.851262 2.067026 2.207298 2.470728 2.612432
-0.340710 0.532103 0.935278 1.171022 1.377886 1.638598 1.965274 2.246164 2.631266 2.806341
-0.310524 0.412051 0.582478 0.768755 0.871594 1.119854 1.926346 2.207508 2.407091 2.636633
-0.249349 0.443517 0.631532 0.810096 1.205129 1.357206 1.607396 1.984157 2.208016 2.645111
-0.143090 0.185312 0.325214 0.504000 1.134467 1.327913 1.673654 2.006903 2.389284 2.746094
-0.226575 0.298946 0.453938 0.998061 1.394600 1.597283 2.064183 2.223246 2.425469 2.569458
-0.183924 0.255181 0.415834 0.624247 1.042338 1.203077 1.555240 2.125309 2.400352 2.661916
-0.275610 0.365968 0.654909 0.990108 1.170799 1.455333 2.077561 2.252672 2.502315 2.685945
-0.204334 0.287844 0.394810 0.761295 1.501200 1.784709 1.935569 2.152830 2.349263 2.545639
-0.342976 0.527539 0.917466 1.160585 1.499531 1.761830 2.095272 2.301872 2.540570 2.694692
-0.202374 0.333367 0.480179 0.708677 0.819505 1.105285 1.806641 1.953348 2.610844 2.797497
-0.307033 0.368471 0.602486 1.108611 1.413347 1.528636 1.798519 1.986138 2.169052 2.437256
-0.144073 0.196932 0.386988 0.819061 1.289767 1.625073 1.901924 2.136105 2.483019 2.707970
-0.176760 0.268627 0.662082 1.056866 1.547973 1.711386 1.972939 2.249909 2.544471 2.761094
-0.191409 0.292985 0.492193 0.800526 1.041836 1.278546 1.836626 2.028677 2.249387 2.627785
-0.324102 0.399146 0.687435 0.868704 1.022957 1.582084 1.853847 1.981885 2.554914 2.677057
-0.229172 0.302836 0.481418 0.704363 0.967567 1.828269 2.097295 2.258467 2.549112 2.704652
-0.467124 0.696788 0.939500 1.094987 1.277543 1.488496 1.896279 2.158470 2.474182 2.659994
-0.175418 0.234039 0.367674 0.513586 0.747619 1.008405 1.583161 2.053114 2.363292 2.681153
-0.410273 0.561949 0.736215 0.956685 1.135688 1.288424 1.750612 1.937714 2.151318 2.489336
-0.204541 0.277613 0.529607 0.722971 1.199975 1.447336 1.715634 1.921054 2.357781 2.507488
-0.253116 0.311907 0.696982 1.320082 1.575418 1.705324 2.005068 2.168666 2.461879 2.665053
-0.163657 0.237902 0.393374 0.609490 0.854272 1.089980 1.526387 1.842337 2.126252 2.679051
-0.448627 0.530664 0.812719 1.095201 1.207641 1.575411 1.884209 2.034297 2.553007 2.688355
-0.262717 0.338748 0.512685 1.003543 1.480178 1.622083 1.828518 2.142415 2.356457 2.511530
-0.417111 0.636688 1.036571 1.319877 1.679924 1.873389 2.073722 2.249396 2.507732 2.651054
-0.263698 0.461151 0.618737 0.830471 1.004041 1.158874 1.801566 2.020222 2.306558 2.743041
-0.387779 0.575108 0.729791 0.932981 1.361163 1.505161 1.751183 2.068466 2.338260 2.487637
-0.181510 0.265666 0.454631 1.082382 1.287303 1.579202 1.851178 2.096963 2.467237 2.646930
-0.277668 0.345119 0.602341 1.179200 1.378990 1.545625 1.813861 1.962590 2.491799 2.664453
-0.179320 0.248080 0.456925 0.722589 1.126932 1.579450 1.799397 1.950668 2.484125 2.707238
-0.314322 0.381145 0.608651 0.727613 0.890472 1.610280 2.136172 2.258358 2.596376 2.709780
-0.189539 0.266068 0.419729 0.651693 1.410161 1.643106 1.854810 2.275582 2.492054 2.722009
-0.254466 0.313038 0.594149 1.012536 1.688813 1.935465 2.119184 2.287869 2.535543 2.667926
-0.134691 0.171906 0.302740 0.492936 0.899551 1.229188 1.733940 2.012878 2.446339 2.742762
-0.231556 0.365068 0.680761 0.889142 1.111338 1.295904 1.542636 1.971784 2.427562 2.631912
-0.222525 0.305606 0.527193 0.687519 1.181381 1.671764 1.863683 2.072023 2.634517 2.779272
-0.178770 0.237415 0.375160 0.856692 1.673680 1.813743 2.016791 2.272421 2.522601 2.735959
-0.193532 0.268731 0.451328 0.753471 0.984854 1.285349 1.685647 1.884123 2.091677 2.243418
-0.476037 0.651610 0.801054 1.010162 1.241374 1.355840 1.775976 2.086152 2.272907 2.454351
-0.211657 0.308331 0.421366 0.865966 1.418774 1.556743 1.786149 2.020332 2.198585 2.631981
-0.203789 0.490794 1.010137 1.275006 1.472213 1.810140 2.170639 2.437660 2.662122 2.788061
-0.174355 0.252095 0.674715 0.842194 1.055087 1.278000 1.698680 2.070561 2.399385 2.657430
-0.245109 0.324049 0.628822 0.927910 1.123601 1.580066 1.878640 2.054601 2.358721 2.546838
-0.182644 0.253804 0.386248 0.614056 1.364821 1.545877 2.040174 2.218827 2.419010 2.624609
-0.295605 0.367794 0.690701 1.055162 1.186600 1.644453 1.944154 2.101444 2.562120 2.691268
-0.220878 0.289573 0.640307 0.822072 1.144055 1.567797 1.766410 1.908109 2.103459 2.560489
-0.403453 0.526298 0.732204 0.901150 1.035869 1.339383 1.783990 1.941961 2.371032 2.626653
-0.212825 0.258570 0.471588 0.685549 1.263740 1.821051 2.163822 2.288398 2.628063 2.788155
-0.401181 0.642053 1.032473 1.236110 1.444450 1.686678 2.006722 2.228515 2.572112 2.723964
-0.239433 0.341091 0.492629 0.707630 0.881426 1.030816 1.719255 2.344056 2.579063 2.756942
-0.294093 0.382770 0.577412 1.009281 1.313036 1.419303 1.744673 2.094230 2.289039 2.475843
-0.169805 0.236922 0.403314 0.638995 1.176446 1.352145 1.665573 1.909756 2.150120 2.716243
-0.210447 0.277913 0.452474 1.402686 1.513430 1.720944 1.903938 2.278499 2.583756 2.743179
-0.159574 0.225382 0.374008 0.714137 1.011253 1.371713 1.699162 1.871587 2.027056 2.491194
-0.258602 0.557253 0.819720 1.038856 1.301470 1.445358 1.830613 2.098171 2.320809 2.541075
-0.232756 0.282242 0.631974 0.898694 1.537444 1.869217 2.063967 2.234463 2.498226 2.633517
-0.580133 0.997946 1.320956 1.481874 1.731605 1.898579 2.120712 2.290128 2.530088 2.651657
-0.211840 0.307093 0.453360 0.945579 1.250815 1.490290 1.724135 2.281097 2.562699 2.752602
-0.314276 0.493555 0.667782 0.896500 1.323006 1.482618 1.667487 1.974415 2.427345 2.555679
-0.182455 0.261592 0.418011 1.050927 1.261387 1.443370 1.665467 1.939030 2.444695 2.638451
-0.241570 0.306934 0.491293 1.105950 1.554827 1.666520 1.923917 2.087652 2.367600 2.654889
-0.190084 0.254850 0.454062 0.724519 1.083362 1.393887 1.892335 2.088856 2.321764 2.484299
-0.306497 0.389831 0.721793 0.839714 1.124754 1.652401 1.822919 2.273310 2.569195 2.669599
-0.186200 0.273460 0.383201 0.564758 1.511073 1.845018 1.998284 2.194096 2.388693 2.587923
-0.300722 0.478218 0.823364 1.127490 1.591141 1.871349 2.174720 2.403181 2.624785 2.782405
-0.228884 0.358342 0.504622 0.795874 1.005622 1.152613 1.908053 2.124794 2.372473 2.797584
-0.171885 0.248234 0.432842 0.833143 1.040892 1.269289 1.661635 1.918629 2.158962 2.653403
-0.140943 0.193684 0.343025 0.562303 1.069552 1.543330 1.824473 1.961637 2.463513 2.770537
-0.173053 0.245656 0.360656 0.960618 1.589535 1.689906 1.984141 2.142998 2.588389 2.759403
-0.240180 0.429951 0.637440 0.786596 1.069147 1.226573 1.470883 1.952052 2.195064 2.615973
-0.367862 0.471897 0.730834 1.082320 1.226293 1.462927 1.928169 2.052466 2.406737 2.662458
-0.247175 0.358209 0.535946 0.781876 1.363697 1.635239 1.807233 1.993776 2.452769 2.601039
-0.445578 0.687898 1.114108 1.301027 1.577397 1.886042 2.224903 2.436534 2.659695 2.761031
-0.214389 0.336025 0.487794 0.759534 0.970518 1.141100 1.457335 1.624644 2.306922 2.715265
-0.377300 0.466775 0.716121 1.083781 1.256543 1.411238 1.789433 1.936372 2.205572 2.562355
-0.148362 0.214593 0.545023 0.840437 1.193325 1.480659 1.791868 2.083419 2.410537 2.676129
-0.150403 0.278398 0.792676 0.976680 1.218845 1.405245 1.775056 2.162458 2.547861 2.746383
-0.236301 0.328633 0.630867 0.839915 1.042349 1.298870 1.627752 1.839491 2.298928 2.493962
-0.337889 0.497920 0.711277 0.850420 0.992027 1.246884 1.710746 2.086682 2.527158 2.707162
-0.172215 0.236540 0.372897 0.525146 1.182577 1.735727 1.927035 2.114619 2.319170 2.542782
-0.415304 0.624807 0.906616 1.117841 1.446155 1.669417 1.948413 2.172815 2.504530 2.670754
-0.265417 0.407241 0.613894 0.816534 0.980063 1.156061 1.756747 2.274851 2.497193 2.712242
-0.276440 0.468209 0.649518 0.816686 1.195171 1.355517 1.549226 1.935272 2.217871 2.426979
-0.188925 0.277012 0.412665 0.672627 1.354807 1.514523 1.699988 2.144554 2.382186 2.586077
-0.242630 0.352485 0.912974 1.343781 1.604428 1.801867 2.014791 2.193072 2.460809 2.631999
-0.190903 0.285841 0.449070 0.760328 0.954285 1.182936 1.692638 1.878163 2.276840 2.465963
-0.220659 0.300374 0.721694 0.947306 1.298330 1.562980 1.760618 1.888247 2.506445 2.689675
-0.213168 0.290928 0.695227 0.918179 1.378186 1.631987 1.847886 2.003072 2.358358 2.619347
-0.328586 0.517244 0.937320 1.376238 1.574840 1.764347 2.058630 2.224334 2.584444 2.756653
-0.248486 0.367007 0.562147 0.750632 0.902785 1.147563 1.637415 1.912062 2.413993 2.605696
-0.310691 0.477895 0.670796 0.940507 1.418293 1.563497 1.805141 2.114076 2.376358 2.535155
-0.256555 0.414210 0.559427 0.981289 1.191646 1.378307 1.678398 1.849306 2.576704 2.756630
-0.291424 0.335003 0.750149 1.289655 1.437209 1.599989 1.803177 1.967415 2.601748 2.733761
-0.195254 0.279513 0.451755 0.649111 0.828694 1.609509 1.914906 2.091219 2.319589 2.534899
-0.222304 0.332624 0.475678 0.685205 1.030332 1.737223 1.920979 2.378290 2.706719 2.817726
-0.164833 0.240093 0.359862 0.801929 1.513677 1.641713 2.040524 2.248843 2.488659 2.714025
-0.214777 0.287322 0.572644 1.145070 1.367112 1.752687 2.042424 2.222067 2.543047 2.697885
-0.226099 0.330382 0.474439 0.687757 0.799187 1.319837 1.944566 2.078099 2.367800 2.508460
-0.244540 0.392163 0.553692 0.729765 1.247865 1.448376 1.617590 2.074636 2.340052 2.518064
-0.175381 0.314231 0.446023 0.797404 1.328458 1.439727 1.793346 1.939571 2.468800 2.721651
-0.205808 0.293670 0.452447 1.074268 1.288235 1.655635 1.857504 2.364687 2.639812 2.798144
-0.253926 0.392653 0.587584 0.800134 0.976310 1.185587 1.570687 1.821414 2.090893 2.349021
-0.322461 0.410912 0.723569 1.060644 1.201524 1.400360 1.579189 1.788759 2.460242 2.616602
-0.211266 0.304981 0.436011 0.771978 1.490623 1.677748 1.886227 2.113497 2.326353 2.727265
-0.235012 0.406911 0.864785 1.291485 1.708295 1.938554 2.179896 2.352404 2.563792 2.711446
-0.176814 0.268620 0.445837 0.823113 1.029776 1.271571 1.623388 1.811215 2.402140 2.614165
-0.241865 0.339268 0.507509 1.003677 1.204347 1.372561 1.940795 2.101371 2.385606 2.669975
-0.230878 0.334743 0.500370 0.879929 1.021894 1.533770 1.970789 2.128971 2.567262 2.717288
-0.297505 0.451574 0.748848 0.988527 1.366237 1.606668 1.894660 2.174481 2.521427 2.759168
-0.199265 0.271145 0.498160 0.854679 1.172103 1.364148 1.762079 1.969095 2.173538 2.311630
-0.222173 0.424864 0.564942 0.829809 1.038172 1.194055 1.720601 1.858086 2.431760 2.741461
-0.181961 0.226819 0.390513 0.556339 1.056596 1.553065 2.128349 2.258018 2.602497 2.802121
-0.357600 0.565047 1.153012 1.350312 1.533576 1.718542 1.957892 2.175347 2.505650 2.678495
-0.162257 0.236808 0.374039 0.570569 0.748034 1.172262 1.823392 2.053032 2.513769 2.772072
-0.305794 0.465870 0.645121 0.882650 1.141294 1.266856 1.701581 2.002881 2.184124 2.411254
-0.231652 0.380738 0.549642 0.837410 1.225266 1.332971 1.851582 2.119371 2.315077 2.732108
-0.235449 0.286771 0.684809 1.346663 1.526630 1.703476 2.101486 2.254546 2.577181 2.718994
-0.233870 0.446515 0.605080 0.814654 1.054963 1.178801 1.633158 1.849743 2.139379 2.732772
-0.271706 0.335152 0.857227 1.253741 1.387189 1.702170 1.896767 2.191114 2.479999 2.601359
-0.237386 0.314549 0.438339 0.912164 1.577764 1.877791 2.032790 2.197037 2.412322 2.536484
-0.361168 0.574093 1.023843 1.468517 1.690562 1.917374 2.187368 2.334035 2.669095 2.806291
-0.278480 0.398742 0.573342 0.839212 1.073888 1.222093 1.691681 2.165258 2.377410 2.536882
-0.286018 0.447947 0.615060 0.849446 1.319465 1.463583 1.769948 2.001035 2.189431 2.450384
-0.219440 0.301601 0.668534 0.861094 1.210001 1.498673 1.745120 1.877765 2.314377 2.619597
-0.223591 0.352153 0.598841 1.217893 1.359082 1.591744 1.771089 2.213856 2.561538 2.735416
-0.176857 0.236601 0.395107 0.634632 1.133495 1.335116 1.770374 1.981313 2.206556 2.339716
-0.334735 0.402265 0.659168 0.781639 0.975228 1.664999 1.872069 2.047533 2.476961 2.573979
-0.215968 0.284755 0.524241 0.781460 1.334811 1.772379 1.953878 2.194209 2.578250 2.741939
-0.298193 0.489879 0.812985 1.183691 1.496418 1.679975 2.108792 2.316557 2.673779 2.851610
-0.312989 0.415446 0.618011 0.899096 1.083683 1.263384 1.887396 2.243064 2.419448 2.570481
-0.244471 0.431115 0.601512 0.813139 1.102163 1.221061 1.692440 2.033163 2.221795 2.619838
-0.150949 0.219060 0.349217 0.611327 1.077112 1.250547 1.915518 2.083980 2.449999 2.792543
-0.161611 0.218964 0.445377 0.927863 1.451151 1.768464 2.130012 2.366724 2.666003 2.814049
-0.196000 0.297256 0.497266 0.691900 1.089877 1.273685 1.513723 2.006472 2.273782 2.572221
-0.335268 0.460795 0.685187 0.867664 1.013807 1.479554 2.011994 2.168476 2.572643 2.717564
-0.257604 0.340872 0.499757 0.843052 1.396548 1.831688 2.034226 2.170332 2.422618 2.540496
-0.417663 0.631718 0.955424 1.197319 1.659797 1.879883 2.168797 2.359053 2.578087 2.698249
-0.162052 0.251583 0.439900 0.660911 0.903902 1.320296 1.624758 1.778577 2.530531 2.799705
-0.256861 0.322803 0.685370 1.086437 1.263276 1.569879 1.851654 2.014946 2.264711 2.447006
-0.125192 0.176171 0.336135 0.781600 1.200220 1.439966 1.805419 2.077525 2.462470 2.738186
-0.102286 0.191322 0.774556 1.076151 1.369456 1.627146 1.973015 2.236001 2.609367 2.812985
-0.173442 0.232622 0.491622 0.844157 1.095241 1.370797 1.696966 2.051411 2.316061 2.502053
-0.257531 0.343598 0.654071 0.838985 1.048102 1.487473 1.725385 1.897417 2.430505 2.585998
-0.197900 0.276312 0.440283 0.705103 1.267341 1.740297 1.934483 2.154007 2.400200 2.624136
-0.409590 0.596785 0.983751 1.181770 1.371153 1.502380 1.758280 2.018571 2.380053 2.592151
-0.231819 0.332890 0.483514 0.644585 0.816808 0.926308 1.403298 2.233007 2.467857 2.678461
-0.258610 0.340064 0.670485 0.908467 1.107611 1.456243 1.759580 1.932179 2.113118 2.310135
-0.184377 0.249203 0.410806 0.587907 1.302501 1.510319 1.724432 1.981890 2.282904 2.422125
-0.254110 0.313328 0.659859 1.265819 1.412949 1.665930 1.927154 2.101984 2.551446 2.673030
-0.161592 0.237480 0.376535 0.637094 0.823028 1.137613 1.696425 1.875770 2.403632 2.639617
-0.384501 0.466812 0.740791 0.938093 1.062352 1.509284 1.749143 1.917797 2.548157 2.671506
-0.333872 0.419367 0.638994 1.092624 1.520550 1.649447 1.866619 2.148941 2.346723 2.506140
-0.426216 0.686997 1.235881 1.428854 1.611591 1.792860 2.017593 2.233715 2.547773 2.696609
-0.262949 0.367509 0.530429 0.741867 0.872474 1.069602 1.745566 2.061187 2.283843 2.494178
-0.335782 0.547236 0.716211 0.919077 1.275686 1.408437 1.685118 1.967394 2.217639 2.446679
-0.227629 0.330991 0.486068 1.117571 1.304983 1.510130 1.757258 1.946972 2.625557 2.782597
-0.359850 0.436633 0.750634 1.201513 1.337571 1.594835 1.970273 2.113840 2.573808 2.729963
-0.211871 0.304028 0.512758 0.663762 1.086354 1.633335 1.818017 2.129577 2.391080 2.600766
-0.196092 0.279726 0.434488 0.624802 0.772358 1.404377 1.948777 2.160918 2.629996 2.775175
-0.176304 0.262521 0.373719 0.581101 1.520108 1.736172 1.933230 2.140172 2.358130 2.753524
-0.254932 0.381411 0.806187 1.102292 1.534523 1.750280 1.970904 2.159871 2.455922 2.658405
-0.190385 0.288656 0.449066 0.678174 0.812376 1.449326 1.728657 1.966320 2.638812 2.789546
-0.251178 0.386509 0.609363 0.797102 1.024159 1.181726 1.454661 2.012630 2.493092 2.698933
-0.166654 0.266226 0.385171 0.711990 1.397897 1.532347 1.915974 2.088003 2.565270 2.789532
-0.238453 0.306036 0.449309 0.876277 1.521437 1.933982 2.134420 2.267986 2.537601 2.658253
-0.161634 0.219919 0.353206 0.524346 0.961806 1.207713 1.687918 1.916939 2.161870 2.320657
-0.413612 0.597095 0.793763 0.986290 1.281786 1.412660 1.652465 2.016091 2.384164 2.528578
-0.228655 0.341562 0.480989 0.988605 1.371003 1.477423 1.861026 2.015852 2.339752 2.773153
-0.259092 0.597012 0.985224 1.321740 1.643354 1.957367 2.288682 2.497474 2.716492 2.844467
-0.185652 0.304664 0.446232 0.864434 1.091795 1.273770 1.942575 2.095543 2.524648 2.768245
-0.176687 0.256678 0.745652 0.934909 1.283760 1.440062 1.765242 2.122092 2.388099 2.590551
-0.189805 0.275637 0.440995 0.821356 1.256020 1.410985 1.929781 2.120144 2.396030 2.604643
-0.266823 0.337688 0.819408 1.134754 1.289204 1.777028 1.982886 2.221748 2.590286 2.698098
-0.205348 0.276512 0.527305 0.727412 1.024647 1.653979 1.904178 2.046613 2.217922 2.455661
-0.293498 0.424494 0.613795 0.956130 1.133981 1.324804 1.809031 1.953922 2.293854 2.575884
-0.183120 0.249650 0.376204 0.543914 1.350827 1.907220 2.092551 2.255705 2.514391 2.687901
-0.541205 0.789796 1.058955 1.269415 1.503899 1.702191 1.970176 2.175444 2.496810 2.652238
-0.229326 0.339475 0.451881 0.661210 0.795832 1.073796 2.027104 2.206371 2.478903 2.726784
-0.330006 0.506868 0.673076 0.887406 1.228765 1.349226 1.781290 2.086583 2.277762 2.480029
-0.138389 0.200001 0.396259 0.811975 1.090712 1.460413 1.745493 1.904269 2.348250 2.699886
-0.176584 0.242161 0.378270 1.177848 1.564718 1.678166 1.951618 2.121413 2.580109 2.737132
-0.145852 0.198423 0.335644 0.550505 1.019727 1.371188 1.797635 1.943825 2.207490 2.746470
-0.385078 0.503696 0.703239 1.069987 1.365736 1.472054 1.825827 2.159636 2.371283 2.520972
-0.284950 0.388050 0.507352 0.879125 1.523530 1.776238 1.929597 2.157558 2.447986 2.586398
-0.491116 0.756155 1.255200 1.522460 1.776579 2.028121 2.286059 2.429774 2.679106 2.776164
-0.252477 0.396081 0.713022 0.861502 1.152223 1.370802 1.614010 2.144798 2.574072 2.712530
-0.282756 0.438437 0.613566 0.847746 1.260772 1.379059 1.642202 2.137540 2.368369 2.522163
-0.203971 0.322195 0.479842 0.953133 1.211278 1.397635 1.800812 1.954516 2.403478 2.573713
-0.264533 0.358424 0.628768 1.111242 1.340246 1.506485 1.999590 2.194109 2.461411 2.667361
-0.177730 0.223680 0.394553 0.556177 0.947415 1.500640 1.733528 1.926046 2.261466 2.436054
-0.314223 0.363636 0.727886 0.851880 1.053844 1.798132 1.974354 2.182595 2.537995 2.629683
-0.201778 0.275500 0.404891 0.747466 1.500050 1.841184 1.998843 2.226807 2.481989 2.669506
-0.132164 0.314955 0.821473 1.196038 1.426590 1.699934 2.036856 2.323497 2.685471 2.828965
-0.223374 0.347335 0.507730 0.773547 0.967916 1.134129 1.991403 2.306567 2.521364 2.788746
-0.312742 0.449784 0.583287 0.934234 1.268567 1.365063 1.569295 1.687046 2.077299 2.595022
-0.124286 0.162126 0.290730 0.654031 1.231658 1.538458 1.893070 2.184784 2.562637 2.798224
-0.177049 0.251654 0.367891 0.912504 1.557576 1.693045 1.898991 2.072136 2.350163 2.646045
-0.240517 0.378333 0.547809 0.754272 0.973321 1.103670 1.574418 2.028049 2.211127 2.562709
-0.427795 0.519003 0.771284 0.937240 1.086617 1.609879 1.878750 2.052791 2.534118 2.657149
-0.224370 0.317969 0.439666 0.812931 1.398497 1.626632 1.794178 2.114000 2.309157 2.496836
+++ /dev/null
-5 512
-0.005167 -0.037310 -0.002159 0.016849 0.130396
-0.039445 0.031680 -0.074412 -0.031499 0.060536
-0.019479 -0.030564 -0.048137 -0.056279 -0.027829
-0.020585 -0.011270 0.023913 -0.005706 0.011407
--0.023217 0.107455 -0.037777 0.004070 -0.017279
--0.090444 0.007641 0.099001 -0.047913 -0.017199
-0.022700 -0.063865 0.047213 0.043843 -0.036225
-0.001312 -0.123861 -0.038988 0.058666 0.074541
-0.039508 0.110300 0.013954 -0.119228 -0.035807
--0.047392 0.027035 -0.004412 -0.032650 -0.037150
-0.002491 -0.045447 0.158260 0.022828 -0.030124
--0.047856 0.088744 -0.009678 0.106688 0.087690
--0.027941 0.044084 -0.028500 0.018736 -0.069969
--0.035358 -0.051568 -0.030459 -0.017899 0.027632
--0.018607 -0.123557 0.019228 0.057485 -0.028907
-0.019057 0.038151 -0.080220 0.034222 0.023081
-0.021312 0.041905 0.112903 0.024092 0.093974
--0.116679 0.015344 -0.066059 -0.096437 0.004041
--0.022464 -0.116260 0.047819 -0.003921 -0.073504
-0.001975 -0.025869 0.028200 0.122690 0.010627
--0.035672 0.078963 -0.009686 0.000743 -0.147582
-0.016932 -0.020291 -0.096896 -0.237875 -0.029121
-0.017376 -0.040130 -0.053865 0.154060 -0.013215
-0.015215 -0.019023 -0.070604 0.032265 0.040340
-0.102365 -0.022746 0.019895 0.050570 0.008845
--0.034134 0.044441 -0.049387 -0.140481 0.072570
-0.013023 -0.006079 0.037574 0.004937 -0.081501
-0.003696 0.049908 0.007355 0.000403 0.026006
--0.008466 0.080680 0.061382 -0.108985 -0.088060
--0.012275 -0.081061 0.020333 -0.079001 0.068724
--0.014081 -0.042609 0.093365 0.044120 0.000303
-0.063391 0.096574 -0.105424 0.039041 0.010412
--0.054031 -0.084948 0.080406 -0.035883 0.137428
-0.063037 0.050562 0.024690 -0.031394 0.130320
--0.015501 -0.078884 -0.076886 -0.013864 -0.073587
-0.048778 0.003814 -0.031125 0.046897 0.028304
-0.048692 0.132795 0.065450 0.059487 -0.042396
--0.176999 0.056943 -0.004135 -0.049378 -0.041083
--0.039445 -0.016292 -0.004550 0.062010 -0.079613
--0.054566 -0.008476 -0.016710 0.049202 0.025758
--0.078723 0.092091 0.096536 -0.065079 0.021161
-0.076657 0.009203 -0.036866 -0.016559 0.012823
-0.008225 -0.003006 0.108033 0.043120 -0.060870
--0.019346 0.022790 -0.001728 0.062304 -0.016965
--0.001302 -0.014490 -0.041803 -0.034058 -0.197066
--0.033655 -0.127217 -0.108681 -0.010571 -0.004705
--0.015553 -0.086069 0.034109 -0.101379 0.002068
--0.004003 -0.044637 -0.068617 0.052228 -0.047812
--0.043307 0.035681 0.042207 -0.055946 0.055944
--0.026792 -0.012601 -0.056710 -0.021094 0.105842
--0.025598 -0.078858 -0.013487 0.030728 -0.031956
-0.031444 0.022763 0.025364 0.121366 0.070736
--0.084556 0.098118 -0.024301 -0.058655 -0.043194
--0.011752 -0.043781 0.091051 -0.071201 -0.020980
-0.082904 -0.031657 -0.088247 0.066709 -0.079182
--0.012151 0.011796 -0.010589 0.100656 0.094539
-0.035967 0.025338 0.071826 0.009741 -0.040209
-0.006866 -0.015095 -0.168469 -0.056133 0.060145
-0.045830 -0.068969 0.034551 0.015842 -0.092809
-0.054699 0.138744 0.001726 0.006927 0.005167
-0.016978 0.046384 -0.060183 -0.040742 -0.072692
--0.022489 -0.029728 -0.065018 -0.124741 0.044927
--0.029057 -0.037154 0.031068 0.060086 0.009984
-0.009311 -0.006957 -0.105508 0.059637 -0.019564
--0.068154 -0.066443 0.000799 0.028579 0.097063
-0.096936 0.030230 -0.034623 -0.088918 0.040334
-0.019439 -0.050707 -0.003294 -0.028505 -0.053599
-0.062460 -0.070688 -0.016465 -0.035680 0.017378
-0.009363 0.048761 0.043374 0.039587 -0.023232
--0.067033 0.042663 0.054070 -0.042797 -0.089391
--0.030497 -0.050249 0.059528 0.089089 -0.029633
-0.064125 -0.086614 -0.002005 0.080620 0.000502
--0.003490 0.097336 0.099565 0.015648 0.006691
-0.077668 0.016572 0.035404 -0.046026 0.017237
--0.048631 0.009314 0.141479 0.017079 0.043796
--0.106474 0.145951 0.057740 0.011250 -0.059443
-0.027572 0.026650 0.008527 0.002949 -0.037680
--0.077991 -0.090617 0.003420 -0.046010 0.007354
-0.019056 -0.128651 0.016464 0.004584 -0.030883
--0.092069 0.038976 -0.081840 0.066695 -0.047340
-0.003513 0.040613 0.046815 -0.023406 0.062389
-0.021759 0.024928 -0.018922 -0.048006 0.063800
--0.014416 -0.050333 0.042628 -0.114934 -0.101450
-0.062139 0.029295 -0.065908 0.111463 0.050781
--0.022707 0.135414 0.003548 0.134535 -0.048259
--0.092344 -0.027727 0.016343 -0.060786 -0.081502
--0.005412 -0.026229 -0.143331 0.052404 -0.077298
--0.035919 -0.041968 -0.106108 -0.004369 0.065028
-0.096370 -0.053299 0.043317 -0.049735 0.049815
-0.032324 0.051309 -0.009607 -0.205917 0.005023
--0.054316 -0.022895 0.099327 -0.006927 -0.076574
--0.111024 0.111026 0.038381 -0.060368 0.064238
--0.034316 0.026846 0.025740 -0.076162 -0.163904
-0.055955 -0.056885 0.014831 -0.120715 0.090938
-0.035289 -0.036439 0.060012 0.080302 0.036215
-0.065250 0.083030 -0.058784 0.104826 -0.051805
--0.011099 -0.006420 0.053042 0.024127 0.092534
-0.058569 -0.033442 0.025186 -0.018222 0.117744
-0.044345 -0.042456 -0.043767 -0.021378 -0.121965
-0.027371 0.052731 -0.020316 0.036912 0.115357
-0.031150 0.041547 0.059267 -0.039672 -0.086918
--0.162369 0.024801 0.031725 0.083400 -0.034463
-0.000272 -0.008147 -0.002016 0.131953 -0.092911
--0.091944 -0.062864 -0.005221 0.063647 -0.012658
-0.042685 0.067952 0.038644 -0.153221 0.096841
-0.108299 0.089446 -0.047164 0.004196 -0.043268
--0.035456 0.050838 0.070444 0.084465 -0.079980
--0.048916 0.057726 0.023894 0.027653 0.017775
-0.015461 -0.030287 -0.022245 0.052081 -0.150947
--0.002682 -0.056774 -0.123366 -0.091754 0.006536
-0.006473 -0.143025 0.054690 -0.043189 0.032970
-0.027446 0.033127 -0.132722 -0.010417 -0.080097
--0.018187 0.001858 0.111290 -0.090749 0.059434
--0.068738 0.090679 -0.145070 -0.065277 0.063514
--0.003982 -0.056382 -0.003673 0.015845 -0.073396
-0.043688 0.002836 0.069211 0.124852 -0.053313
--0.040946 0.070440 -0.107024 -0.019199 -0.033672
--0.001440 0.021680 0.110595 -0.053452 -0.052426
-0.035461 -0.028179 -0.049041 0.022580 -0.010989
--0.002913 -0.051691 -0.075881 0.037241 0.076377
-0.034735 -0.031556 0.073516 -0.001427 0.016296
--0.017537 0.003346 -0.099774 -0.067624 -0.044257
--0.018202 0.030622 0.012773 0.046475 -0.121785
--0.057265 0.116179 -0.079916 0.066396 0.050104
--0.013177 0.057766 -0.047879 -0.109526 -0.146491
-0.032675 -0.049318 -0.057045 -0.080068 0.089621
--0.046564 -0.029992 0.040828 0.029281 -0.037369
--0.009731 -0.082145 -0.117622 0.117077 0.037369
-0.000820 -0.106634 -0.007967 0.000812 0.140637
-0.036530 0.062121 -0.065504 -0.094930 0.121336
-0.017530 -0.017330 -0.040402 -0.018255 0.010992
-0.019746 -0.027564 0.033588 0.042466 -0.003143
-0.013767 0.084179 0.033753 -0.017279 -0.009676
--0.006452 0.032645 0.031852 -0.030975 -0.043384
--0.005433 -0.015258 0.053273 0.054748 -0.064736
-0.008959 -0.141223 -0.032957 -0.015079 0.018198
--0.001681 0.143079 0.076000 0.001037 -0.048744
-0.022062 0.026030 -0.008263 -0.050353 -0.023037
--0.036477 -0.051733 0.137823 -0.034438 -0.007573
--0.004256 0.064218 0.075183 0.095106 0.026497
-0.026360 0.009791 -0.058039 0.053315 -0.077817
--0.033283 -0.081151 -0.055220 0.004268 0.017539
--0.007329 -0.117200 0.093220 0.037359 0.002718
-0.010749 0.018281 -0.075800 -0.024889 0.005720
-0.022129 0.035613 0.036187 0.032246 0.105439
--0.073766 0.016887 -0.059934 -0.049471 0.073520
--0.024041 -0.104642 0.023557 -0.059746 -0.043871
-0.022311 -0.000250 -0.074027 0.198593 0.102732
-0.024478 0.077658 -0.060042 -0.018229 -0.149648
--0.009871 -0.105822 0.007585 -0.161459 -0.041121
--0.021460 0.009020 -0.065018 0.111801 -0.024953
-0.074594 -0.026041 -0.062859 0.009199 0.069609
-0.078672 -0.033414 0.054128 0.005408 -0.016273
-0.052076 0.107610 -0.067518 -0.096400 0.033703
--0.014350 -0.024676 0.056254 -0.043770 -0.060847
--0.004185 0.073550 -0.057830 -0.016644 0.029096
-0.005755 0.026472 0.040449 -0.091950 -0.048538
--0.034439 -0.107938 0.090712 -0.117001 0.043170
--0.006505 -0.035277 0.117316 0.127002 0.047906
--0.001441 0.118379 -0.132165 0.007380 0.023823
--0.020120 -0.083725 0.047284 0.023795 0.074123
--0.013439 0.024994 0.060254 -0.069120 0.166373
--0.024228 -0.063150 -0.046506 -0.077202 -0.054592
--0.006571 0.010335 -0.006568 0.003982 0.075837
-0.008643 0.136339 -0.005502 0.033910 -0.066379
--0.127371 -0.006954 0.039770 -0.070123 0.060925
--0.046386 -0.026420 -0.005280 0.103509 -0.022310
--0.003740 -0.014999 -0.037770 0.080005 0.025231
--0.054995 0.071017 0.009442 -0.075737 0.013441
-0.051947 0.027097 -0.070351 -0.055705 -0.021115
-0.021387 0.029232 0.163331 -0.032380 0.010008
--0.011987 -0.028631 0.002665 0.014770 -0.009558
--0.034325 0.015830 -0.091253 -0.012677 -0.107378
--0.034624 -0.047725 -0.102330 0.042525 -0.006869
-0.014048 -0.043127 0.052384 -0.047473 0.055102
-0.009744 -0.033646 -0.081755 -0.001464 -0.016223
--0.036697 -0.002279 0.023279 -0.036221 0.101478
--0.058454 0.065074 0.003524 0.005010 0.097182
--0.038171 -0.037943 -0.009994 -0.033355 -0.044552
-0.041318 0.065041 0.000092 0.100816 0.029007
--0.031803 0.183537 -0.009617 -0.010544 -0.028465
-0.006900 -0.014988 0.090490 -0.174817 0.027464
-0.063314 -0.049281 -0.001567 0.091421 -0.078603
--0.004869 -0.063266 -0.001922 0.069338 0.081771
-0.058737 0.073195 0.081676 -0.047808 -0.025797
--0.004185 0.033203 -0.125472 -0.108148 0.031258
-0.035192 0.029957 0.046675 0.047238 -0.088197
-0.033315 0.114919 -0.049180 0.025707 0.053843
-0.035182 0.140206 -0.058660 -0.025978 -0.019658
--0.014847 -0.021051 -0.034385 -0.121789 0.173406
--0.112251 -0.022333 0.071206 0.028998 0.046468
-0.067704 -0.026159 -0.158316 0.014936 0.040216
--0.010137 -0.053492 0.004935 -0.011277 0.073852
-0.091261 0.114794 -0.014060 -0.051545 0.077316
-0.101258 -0.046137 0.022994 -0.066767 -0.065537
-0.049952 -0.043582 0.012823 0.009313 0.036343
-0.054885 0.037796 0.021940 0.013211 0.006019
--0.099578 0.058596 -0.045463 -0.015632 -0.087141
--0.019273 -0.033140 0.043796 0.119057 -0.081813
--0.021538 -0.070453 -0.052551 0.077213 0.000094
-0.050268 0.092271 0.051688 -0.025224 0.075437
-0.027983 0.069205 0.031787 -0.099975 0.004387
--0.002747 -0.056567 0.161394 0.000164 0.084189
--0.124844 0.050329 0.009844 0.055877 0.055701
-0.030479 0.028843 -0.001076 -0.017173 -0.102770
--0.038426 -0.133841 -0.035840 -0.072046 0.020206
-0.016438 -0.097885 0.041857 0.034601 0.030422
--0.089192 -0.014112 -0.052276 0.012005 -0.029335
--0.011331 0.101833 0.063827 0.044288 0.101597
--0.034689 -0.027434 -0.017801 -0.079224 0.067103
--0.027456 -0.098034 0.009448 -0.038986 -0.156729
-0.085023 0.033136 -0.021343 0.110701 -0.011901
--0.006484 0.082023 -0.027094 0.091208 -0.013163
--0.012223 0.005933 0.010653 -0.098119 -0.005304
--0.021061 -0.058077 -0.073035 0.097856 -0.102847
--0.035329 -0.092754 -0.101463 -0.048671 0.055015
-0.102145 0.062017 0.016002 0.036489 0.059000
-0.042861 0.025447 -0.019735 -0.107841 -0.033752
--0.043982 -0.067059 0.051092 0.025235 -0.147107
--0.016269 0.123009 0.035894 -0.020453 0.040013
-0.015557 0.015825 0.080712 -0.069630 -0.149739
-0.022006 -0.008848 0.040169 -0.095688 0.059575
--0.030641 -0.061353 0.046302 0.104489 0.043372
--0.001579 0.059737 -0.104073 0.042342 -0.048611
--0.013811 -0.056255 0.107179 0.057433 0.084815
-0.030217 0.022360 -0.040342 -0.028775 0.120588
-0.041270 -0.045775 -0.030195 -0.106859 -0.104349
-0.072418 -0.003603 -0.013072 0.040728 0.086869
-0.091943 0.066517 0.024442 -0.030929 -0.032920
--0.160336 -0.010347 -0.068458 0.017458 0.044823
-0.050694 0.067625 0.040303 0.113164 -0.038747
--0.065558 -0.106357 -0.028352 0.121488 0.026548
--0.007820 0.054872 0.094674 -0.099533 0.005231
-0.118132 0.042780 -0.065079 0.031440 0.043229
--0.050024 0.015943 0.073917 0.034049 0.010548
--0.024979 0.022639 0.027795 0.049491 0.048762
--0.002738 -0.010783 -0.027637 -0.006986 -0.104141
--0.066719 -0.061742 -0.067028 -0.053057 -0.003478
--0.050948 -0.122196 0.022082 0.002595 0.015094
-0.006014 0.005784 -0.184537 -0.034872 -0.036104
-0.055412 0.006886 0.103488 -0.063001 0.096665
--0.035533 0.009847 -0.095114 0.008588 0.023736
--0.034278 -0.111970 -0.041172 0.039730 -0.102952
-0.063775 0.039273 0.109863 0.091800 0.030306
--0.082206 0.089449 -0.058478 -0.029341 0.038389
-0.061057 -0.024711 0.111044 -0.035079 -0.027985
-0.014570 0.002046 -0.031545 0.058848 -0.019500
--0.002475 -0.025589 -0.144358 0.063478 0.124927
--0.014094 -0.010970 0.031621 -0.040043 0.004389
-0.025003 0.052397 -0.054526 -0.073469 0.026795
--0.024697 0.024739 0.118299 0.014948 -0.132109
-0.020192 0.037815 -0.090270 0.049313 0.082764
--0.022642 -0.006053 -0.038073 -0.057363 -0.107347
-0.033166 -0.027556 -0.019765 -0.111958 0.027773
--0.063001 -0.052998 0.019353 -0.009646 -0.011270
-0.011872 -0.006508 -0.122226 0.059824 0.041779
-0.016445 -0.031890 -0.036310 0.013085 0.091631
-0.062866 0.054501 -0.117523 -0.010907 0.087026
--0.014974 -0.035920 -0.048565 -0.019246 -0.043405
--0.006959 0.006211 0.042370 0.014603 -0.006435
-0.019149 0.078038 -0.020556 0.018114 -0.036521
--0.054036 0.007325 0.056349 -0.033497 -0.025960
-0.050184 -0.066536 0.091501 0.071356 -0.049044
--0.032263 -0.095268 -0.008784 0.049033 0.036929
-0.020357 0.152151 0.040814 -0.063159 -0.024324
--0.017084 0.011876 -0.015442 -0.019811 -0.000366
--0.002700 -0.072981 0.109288 0.007473 -0.049442
--0.054040 0.051947 0.019359 0.129160 0.021981
-0.002248 0.035262 -0.023141 0.064666 -0.078273
--0.031663 -0.031343 -0.006058 -0.045421 0.017466
--0.067122 -0.130784 0.067057 0.052460 -0.041165
--0.004411 0.046453 -0.055461 0.048162 -0.009687
-0.021530 0.007211 0.104764 0.079849 0.086248
--0.072791 0.001112 -0.027964 -0.071233 -0.013339
-0.007979 -0.118231 0.076826 -0.060762 -0.084358
--0.011447 0.009765 0.014163 0.164784 -0.015892
--0.020756 0.152509 -0.014014 -0.041853 -0.117008
--0.011755 -0.005766 -0.086896 -0.139650 -0.032342
-0.025651 -0.007843 -0.039073 0.103397 -0.042591
--0.005971 -0.001324 -0.053945 -0.000716 0.048977
-0.130185 0.028226 0.061179 0.024489 -0.021939
--0.007019 0.054336 -0.010040 -0.095411 0.082406
--0.032130 -0.015054 0.033059 0.002802 -0.080159
--0.022452 0.077426 -0.015314 0.033583 0.028479
-0.023293 0.035078 0.006442 -0.110541 -0.106244
--0.034737 -0.104140 -0.034570 -0.114316 0.079382
-0.006009 0.003901 0.080081 0.055082 0.012896
-0.064981 0.057219 -0.112986 0.003906 -0.028414
--0.012383 -0.054541 0.077483 0.004267 0.123567
-0.007369 0.099856 0.023273 -0.028194 0.122030
--0.036635 -0.126589 -0.034567 -0.028288 -0.065040
-0.014280 0.011435 -0.004867 0.043901 0.035395
-0.028599 0.075858 0.118460 0.070581 -0.051903
--0.170905 0.050352 0.053514 -0.017139 0.021748
--0.096610 0.008904 -0.001049 0.078787 -0.101201
--0.026229 -0.019757 -0.035771 0.054142 0.068041
--0.020328 0.099979 0.096623 -0.046957 -0.001733
-0.049586 0.052458 -0.031724 -0.028332 -0.005418
-0.046710 0.014238 0.133125 -0.005428 -0.080055
--0.033226 0.034007 0.025272 0.033924 -0.044662
--0.034690 -0.079173 -0.160689 -0.153893 -0.228771
--0.002450 -0.083966 -0.168294 0.010694 -0.012167
-0.000004 -0.044377 0.023373 -0.077437 0.012178
--0.015899 -0.010828 -0.062847 0.029927 -0.074557
--0.053306 0.049688 0.057017 -0.022571 0.015337
--0.046545 0.018895 -0.024848 -0.004424 0.165442
--0.060201 -0.098629 -0.065190 0.036582 -0.038566
-0.051453 0.093478 0.039619 0.117535 0.090386
--0.029366 0.108075 -0.016568 -0.093576 -0.048799
--0.045599 -0.023619 0.070072 -0.109294 0.001548
-0.076285 -0.091274 -0.068829 0.000215 -0.046519
--0.022512 -0.027067 0.014905 0.079017 0.140699
-0.061141 0.009178 0.097811 0.033468 -0.006666
-0.007163 -0.007578 -0.124238 -0.025271 0.017581
-0.042405 -0.034252 0.064890 0.002500 -0.139083
-0.009733 0.158179 0.014474 0.038913 0.056290
--0.004998 0.075401 -0.030557 -0.038595 -0.049070
--0.014680 -0.076306 -0.132365 -0.177693 0.091760
--0.057238 -0.072379 0.050877 0.051489 0.028125
-0.004991 0.032621 -0.167359 0.041002 -0.007072
--0.086405 -0.042263 -0.019757 -0.011524 0.066004
-0.085670 0.008071 -0.013614 -0.062142 0.083280
-0.000887 -0.075820 0.008295 -0.020136 -0.016886
-0.089657 -0.106260 -0.051491 -0.012687 0.054778
-0.011535 0.086613 0.053803 0.027164 -0.023825
--0.040009 0.080987 0.026309 -0.000334 -0.085288
--0.024208 -0.085040 0.096077 0.120527 -0.044181
-0.003034 -0.091142 0.006471 0.115971 -0.026358
-0.003489 0.083633 0.109975 -0.029425 0.061726
-0.056115 -0.006711 0.013158 -0.062917 -0.015029
-0.003354 0.031574 0.119045 0.022859 0.023777
--0.068292 0.115604 0.031617 0.008953 0.006943
-0.014420 0.008569 -0.031547 -0.006857 -0.051690
--0.086683 -0.108339 0.005093 -0.108646 -0.034720
-0.054273 -0.096753 0.050806 -0.021115 -0.025278
--0.079997 0.027008 -0.034211 0.090949 0.005678
-0.019288 0.042083 0.062119 0.019301 0.040859
--0.009113 0.022427 -0.004019 -0.060890 0.032884
--0.012373 -0.037976 0.017625 -0.079369 -0.050788
-0.079720 -0.039347 -0.085324 0.091044 0.026653
--0.063122 0.099371 -0.024736 0.084631 -0.100421
--0.073313 0.014317 0.022555 -0.116051 -0.063966
--0.009688 -0.063666 -0.131709 0.016744 -0.135028
--0.003708 -0.043685 -0.121631 -0.036930 0.125776
-0.084333 0.010114 0.071231 -0.010395 0.059391
-0.017760 0.033034 -0.018996 -0.130540 0.025758
--0.018261 -0.060044 0.127025 -0.032724 -0.107299
--0.064538 0.090073 -0.010186 -0.066127 0.107025
--0.010940 0.003083 0.019030 -0.023935 -0.140176
-0.003549 -0.042402 -0.010695 -0.185915 0.060835
-0.005405 -0.013822 0.029205 0.079338 0.068155
-0.071485 0.030282 -0.087207 0.073480 -0.027940
-0.004896 -0.033246 0.072637 0.018017 0.054712
-0.026184 -0.005287 0.034456 -0.036753 0.079232
-0.072707 0.004506 -0.039353 -0.015560 -0.071466
-0.010257 0.067446 -0.006598 0.047396 0.072218
-0.023405 0.082663 0.015319 -0.035436 -0.075461
--0.124036 -0.032046 0.060837 0.010231 -0.053024
-0.022800 0.042891 -0.041549 0.132395 -0.095330
--0.077091 -0.058554 -0.070632 0.047570 0.031856
-0.000127 0.114996 0.058660 -0.092472 0.064503
-0.096450 0.066200 -0.001059 0.039487 -0.032859
--0.065721 0.001601 0.088037 0.059828 -0.047411
--0.077714 0.010275 0.013629 0.003304 0.005407
-0.000665 0.012927 -0.077525 0.069202 -0.157417
-0.014547 -0.095965 -0.087546 -0.067375 -0.027867
-0.005458 -0.095839 0.105294 -0.044892 0.045151
--0.001349 0.038356 -0.127152 -0.080503 -0.105423
--0.018484 0.008439 0.104398 -0.027959 0.082086
--0.020605 0.042785 -0.109139 -0.025958 0.079733
-0.036289 -0.083773 -0.033819 0.032566 -0.065556
-0.006659 0.002090 0.097027 0.115715 -0.013271
--0.067514 0.128365 -0.089129 0.026160 -0.040584
--0.002443 -0.017254 0.129204 -0.110078 -0.064943
-0.089215 -0.022299 -0.034959 0.022446 -0.019254
--0.038900 -0.069862 -0.070540 0.069949 0.111993
--0.006311 -0.009057 0.094278 -0.014932 0.003657
--0.019323 0.026145 -0.062611 -0.073753 -0.007182
-0.014101 0.015776 0.052537 0.064728 -0.160187
--0.005122 0.076356 -0.104763 0.091493 0.020225
--0.000433 0.062698 -0.060457 -0.147540 -0.066168
-0.007195 -0.061498 -0.037801 -0.039763 0.059551
--0.028410 -0.074510 0.057667 0.020584 -0.042510
--0.025311 -0.037825 -0.188010 0.077423 0.030749
--0.025465 -0.067541 0.003073 -0.049778 0.127789
-0.002786 0.120009 -0.067812 -0.026565 0.111272
-0.023219 -0.024403 -0.014507 -0.048624 0.022163
-0.014596 -0.052136 0.001580 0.064595 0.017963
-0.021330 0.098862 -0.009253 -0.041062 0.008903
--0.013829 0.031967 0.076571 -0.005348 -0.044010
-0.031252 0.000369 0.036818 0.072854 -0.038569
-0.004161 -0.128017 -0.053152 0.050896 -0.015212
--0.036159 0.097995 0.068397 -0.048472 -0.056131
--0.011920 0.059188 0.010215 -0.061152 -0.011717
--0.035949 -0.057039 0.090859 -0.029682 0.041466
--0.025106 0.131191 0.059327 0.085383 0.021699
-0.049230 0.036630 -0.077086 0.017806 -0.088790
-0.004040 -0.069533 -0.026785 0.009666 0.014017
--0.055897 -0.096299 0.120693 0.029995 0.032602
--0.001365 0.034015 -0.053512 0.001573 -0.019170
-0.003956 0.006452 0.067313 0.028301 0.160615
--0.053111 0.013990 -0.027060 -0.013638 0.039376
--0.054462 -0.096553 0.079994 -0.043791 -0.025051
--0.003222 0.019418 -0.049525 0.151136 0.034123
-0.055117 0.058918 -0.017393 0.026169 -0.126380
--0.019008 -0.028939 -0.014027 -0.173373 -0.032841
--0.003370 0.039680 -0.118311 0.114094 -0.041869
-0.041121 -0.038391 -0.096074 -0.032479 0.060222
-0.063968 -0.024528 0.018158 -0.009892 -0.043882
--0.005004 0.129800 -0.025438 -0.121186 0.049860
-0.010448 -0.040388 0.061853 -0.017304 -0.035088
--0.008678 0.061476 -0.039493 -0.005055 0.079169
-0.046134 0.009770 0.068294 -0.078965 -0.043792
--0.030529 -0.053845 0.053853 -0.140682 0.111461
-0.003549 -0.014939 0.148955 0.072861 0.004332
-0.015386 0.062006 -0.122325 -0.032529 0.010241
--0.047982 -0.126440 0.055840 0.067128 0.101189
--0.002630 0.031969 0.046076 -0.080194 0.104740
--0.033486 -0.077818 -0.058697 -0.095258 -0.111074
-0.037236 0.011711 0.001113 -0.005664 0.048588
-0.041131 0.098257 0.033126 0.029317 -0.095311
--0.071555 -0.039999 0.026678 -0.072182 0.035031
--0.007997 -0.048174 -0.006796 0.075959 -0.052060
--0.007645 0.037076 -0.035574 0.085576 0.034126
--0.050676 0.051430 0.031999 -0.134308 -0.001489
-0.084564 -0.018394 -0.097410 -0.042931 -0.025608
--0.025489 0.041919 0.142482 0.004617 -0.041085
--0.028816 -0.015527 -0.031005 0.028405 -0.022240
--0.067737 -0.025241 -0.052578 0.012322 -0.120556
-0.016278 -0.081744 -0.099160 0.025144 0.025441
-0.003176 -0.073871 0.031718 -0.028622 0.029031
-0.017910 -0.030693 -0.104215 -0.015422 -0.065738
--0.048346 -0.012847 0.046849 -0.008621 0.058771
--0.054495 0.031597 -0.038844 0.043138 0.092588
--0.071371 -0.059093 -0.001197 0.001766 -0.074762
-0.029470 0.089616 0.005009 0.052977 0.015899
--0.045424 0.158466 -0.038717 -0.032506 0.028687
-0.011435 -0.006772 0.047605 -0.144659 -0.031229
-0.073577 0.011530 -0.008172 0.058883 -0.088412
-0.033615 -0.034120 -0.030701 0.101215 0.096645
-0.027368 0.041249 0.081502 -0.025440 0.007592
-0.059893 0.012106 -0.112009 -0.114692 0.016397
-0.087068 0.016199 0.051263 0.011915 -0.085364
-0.026046 0.145258 -0.047521 0.077134 -0.000345
-0.034532 0.099801 -0.087591 -0.059719 -0.058671
-0.022737 -0.001887 -0.107049 -0.116757 0.134115
--0.055403 0.005157 0.067618 0.081074 0.071787
-0.063802 -0.003430 -0.106491 0.017543 0.002214
--0.013785 -0.032962 0.010084 0.024325 0.045963
-0.059883 0.072282 -0.008608 -0.015127 0.048225
-0.041752 -0.068845 0.012227 -0.090748 -0.035309
-0.045353 -0.078624 -0.019489 0.035531 0.058571
-0.045414 0.039032 -0.011106 0.048787 -0.025336
--0.084893 0.031896 0.010850 0.012526 -0.053205
-0.016952 -0.044041 0.068766 0.097328 -0.122229
-0.027016 -0.051759 -0.057246 0.074566 0.006201
-0.069904 0.100068 0.076124 0.004278 0.029466
-0.045229 0.055683 0.018790 -0.067806 0.039373
-0.029179 -0.036787 0.129921 -0.028993 0.037711
--0.105011 0.138747 -0.004370 0.052080 0.050835
-0.025511 -0.002962 0.007852 -0.055234 -0.075055
-0.000460 -0.089231 -0.030467 -0.080347 0.007488
-0.067460 -0.076368 0.084991 0.039544 0.033391
--0.044318 0.006390 -0.079387 -0.002909 -0.029708
--0.047882 0.063040 0.065719 0.021811 0.070945
--0.007571 -0.001302 -0.064119 -0.068005 0.051040
--0.017747 -0.063938 0.018673 -0.038391 -0.099966
-0.057475 -0.007669 0.009384 0.109283 0.012248
--0.048858 0.092498 0.011967 0.061525 -0.028819
--0.015131 -0.024160 -0.033220 -0.101648 -0.017980
--0.003342 -0.049829 -0.125096 0.128241 -0.047377
--0.028943 -0.109072 -0.066133 -0.015454 0.098334
-0.053371 0.011324 0.042781 0.044313 0.062510
-0.098408 0.065410 -0.040693 -0.116351 -0.032327
--0.013634 -0.058591 0.081507 0.042019 -0.099770
--0.018275 0.084624 -0.007512 -0.041113 0.054203
-0.017879 -0.029747 0.059865 -0.048281 -0.111513
--0.022478 0.002059 0.022383 -0.125360 0.058216
-0.002386 -0.081600 0.049288 0.157428 0.057724
-0.005046 0.102125 -0.083473 0.044059 -0.094864
-0.039120 -0.063306 0.057341 0.060519 0.107383
-0.007076 -0.009373 -0.012555 -0.066630 0.117121
-0.025254 -0.008796 -0.062102 -0.083164 -0.079007
-0.084839 0.042308 -0.055353 0.036386 0.132641
-0.084464 0.056288 -0.011636 -0.059554 -0.087748
--0.147377 -0.052414 -0.010203 -0.009159 -0.018829
-0.009621 0.061633 0.015716 0.086332 -0.061465
--0.011833 -0.062998 -0.021168 0.125194 0.045025
-0.052316 0.025720 0.095155 -0.093252 0.028720
-0.056113 0.063321 -0.045315 0.025199 0.023591
--0.070481 0.072350 0.092458 0.047973 -0.025439
--0.001281 0.021028 0.034576 0.084779 0.006867
--0.010323 -0.046330 -0.009172 0.030485 -0.117679
--0.021782 -0.034737 -0.086292 -0.045885 0.009655
--0.037167 -0.123331 0.017291 -0.028319 0.071447
--0.057180 -0.032912 -0.139418 -0.025966 -0.039305
-0.009411 -0.054017 0.076307 -0.060252 0.110087
--0.061366 0.038897 -0.098107 0.046119 0.043021
--0.029130 -0.096885 0.007623 0.090513 -0.097416
-0.053264 0.058296 0.054372 0.060769 0.015586
--0.067956 0.059996 -0.037850 0.005986 0.000778
-0.045873 -0.065546 0.077900 -0.085638 0.000698
-0.027694 -0.021241 -0.002777 0.034509 -0.048173
-0.009988 0.001008 -0.077434 0.026002 0.139490
-0.008910 0.007791 0.059292 -0.057047 0.014127
--0.022959 0.085710 -0.068087 -0.081561 0.005935
-0.007577 0.061544 0.076542 0.001660 -0.113279
-0.024973 0.086750 -0.061674 0.095059 0.089352
--0.024436 0.024181 -0.016117 -0.073634 -0.067986
-0.074701 -0.046868 -0.054634 -0.092485 0.006662
--0.033256 -0.053774 0.049001 -0.002339 0.013545
--0.006432 -0.012089 -0.086842 0.104105 0.061991
+++ /dev/null
-5 512
-0.007066 0.075781 -0.070082 -0.092014 -0.066477
-0.090510 0.106622 0.025911 -0.016760 0.003724
--0.024628 0.058332 0.012876 0.059557 -0.002092
--0.065092 -0.096975 -0.041837 -0.002432 0.058918
-0.014358 0.080049 -0.008803 -0.002091 -0.097584
-0.085323 -0.026053 -0.086585 -0.009541 0.130555
-0.045391 0.037557 0.074726 -0.050453 0.033517
--0.035576 -0.084211 -0.086430 0.008910 -0.072674
--0.098699 -0.024540 -0.048972 -0.066975 -0.048791
-0.032184 0.070992 -0.014416 0.141892 -0.044249
--0.108921 -0.020450 0.115988 0.011287 -0.026273
-0.024341 0.138519 -0.036467 0.020684 0.074258
--0.053563 0.077463 0.072166 0.032112 -0.079303
--0.025039 0.079675 0.094211 -0.115754 0.038892
-0.050897 -0.024639 0.057826 -0.110429 0.071184
-0.015309 -0.034027 -0.055726 0.043179 -0.063089
-0.043359 -0.011698 0.006637 0.002751 0.030110
--0.001261 0.111470 0.043277 -0.004205 -0.021599
--0.005698 0.058842 0.168422 0.059313 -0.007971
--0.087599 0.073891 -0.083238 0.099279 -0.017364
--0.018429 0.014040 -0.014864 -0.111512 0.089450
--0.028498 -0.087983 -0.077320 -0.062602 0.000328
--0.027152 -0.093796 0.111381 -0.018603 0.092394
--0.007256 0.025391 0.011454 0.012802 -0.041680
-0.008078 0.020905 -0.105401 -0.083265 0.027756
--0.049630 -0.044085 -0.051424 0.104125 -0.000779
--0.063079 -0.130699 0.070500 0.033468 -0.019802
--0.061011 0.094839 -0.040122 0.118409 0.056950
-0.086391 -0.006615 0.045337 -0.044190 -0.106474
--0.081912 0.067557 -0.031649 -0.014437 0.057585
--0.121755 -0.049113 0.057109 -0.049872 0.044104
-0.064705 -0.091589 0.037286 -0.048606 -0.045398
-0.003456 0.057230 0.006262 -0.055206 -0.063871
--0.005249 0.081783 0.134969 -0.002331 0.052643
--0.093346 0.072093 0.116025 -0.031453 -0.006012
--0.038574 -0.030841 0.010288 0.024420 0.051657
--0.086584 0.046381 0.005410 0.052622 -0.072741
-0.079023 0.078099 -0.093912 0.005477 -0.006721
-0.100232 -0.017587 0.044819 0.036655 0.021580
--0.006829 -0.050076 -0.003020 0.088246 0.013560
--0.015690 0.012477 -0.052595 -0.048861 -0.033688
-0.055615 0.092298 -0.066194 0.016416 -0.066059
-0.046976 0.003023 0.104646 0.109136 0.018293
--0.016507 -0.006859 0.004326 0.070843 0.140750
-0.025774 0.034730 -0.079590 0.050054 -0.107950
-0.002378 0.097498 0.027111 -0.122953 -0.002423
--0.020539 -0.063263 -0.095493 -0.157361 -0.039183
-0.025721 0.026897 -0.001200 0.033997 -0.001749
-0.061593 -0.013053 -0.106317 -0.068190 0.046352
--0.056060 0.157084 -0.049365 0.053959 -0.051065
--0.047672 0.081570 0.064342 -0.030705 -0.070806
--0.076503 -0.059471 0.012419 0.073968 -0.026179
--0.038473 0.059013 -0.035783 -0.030057 -0.036346
--0.052692 -0.015346 -0.022687 -0.035279 0.013314
-0.068397 -0.046609 -0.009593 -0.040796 0.157438
--0.075360 -0.110464 0.031839 -0.029035 -0.015222
-0.041013 -0.099212 -0.108920 -0.008627 0.012095
-0.020855 0.009935 -0.086917 0.058827 -0.006536
-0.022104 -0.005013 0.003496 0.046663 -0.051061
--0.036803 -0.067317 -0.007075 0.180870 -0.027434
--0.025056 -0.039341 -0.073918 -0.003180 -0.110930
--0.042711 0.005519 -0.035005 -0.088419 0.170942
-0.001503 -0.121485 0.066383 -0.067346 0.005643
-0.080088 -0.042562 -0.006668 -0.036538 0.020683
-0.042848 0.027852 -0.029088 -0.156468 0.006503
-0.037716 0.032082 0.038416 0.021835 -0.106963
--0.043017 0.018166 0.070409 -0.005426 -0.035585
--0.111071 -0.039986 0.050430 0.035157 0.066902
--0.040684 0.060527 0.036225 0.002527 -0.015087
-0.059243 0.021268 -0.010682 -0.018434 0.059128
-0.111314 -0.054070 0.105744 -0.051476 -0.012970
--0.000358 -0.099249 -0.077385 0.069924 -0.039101
--0.072139 -0.049069 -0.088018 0.006144 0.000712
-0.081030 0.021987 -0.046031 0.058087 -0.001320
--0.046851 -0.011062 0.108321 -0.001146 -0.071193
-0.044973 -0.002915 -0.003323 0.041735 0.094566
-0.053530 0.035927 0.100282 0.059082 -0.054059
--0.012158 -0.035417 0.020412 -0.073193 0.059296
--0.040489 -0.095250 -0.003821 -0.084904 0.053925
-0.109183 -0.005862 -0.036538 0.080962 -0.040647
-0.020070 0.057778 -0.020197 -0.079626 -0.003186
--0.050855 0.128185 0.034731 0.057460 -0.035236
--0.057096 -0.001238 0.122018 -0.071204 -0.047253
--0.051767 0.048301 -0.052678 0.025990 -0.017481
--0.029379 0.030738 0.047207 -0.047864 -0.033561
-0.029884 -0.091175 -0.085446 -0.026140 0.092628
-0.067706 -0.085617 0.081433 0.047305 0.031945
--0.048728 -0.040387 0.046206 0.010578 -0.037639
-0.011328 -0.042458 -0.149597 0.033882 -0.061869
-0.008800 0.057754 -0.095876 0.038230 0.096876
--0.033487 -0.141669 -0.014172 0.028439 -0.092764
--0.053714 0.086926 0.034786 0.136053 -0.005569
-0.028753 0.009630 0.044114 -0.050365 -0.066224
-0.006017 0.014348 0.024471 0.000489 0.067234
--0.021678 -0.118760 0.036349 -0.040295 0.076358
--0.008444 -0.086082 -0.044018 -0.025804 0.028971
--0.009233 0.053026 -0.035341 -0.182193 -0.102515
-0.089210 0.066812 0.032417 0.046882 -0.034815
--0.052293 0.022814 0.129622 0.128232 -0.012105
--0.087084 0.004762 0.086538 0.046566 0.098359
--0.018713 0.039204 -0.021707 -0.060110 -0.117527
--0.005459 0.060994 -0.057718 -0.021783 0.035154
-0.100557 -0.015470 -0.025818 0.008450 0.051535
--0.001388 -0.114610 -0.057903 0.041862 0.061778
-0.045701 -0.078563 -0.070166 -0.048450 -0.088530
-0.021375 -0.004598 -0.090710 -0.009399 -0.073952
--0.035575 -0.050280 0.114780 0.137866 0.065234
-0.003594 -0.066802 -0.144989 0.166201 0.039564
--0.022457 -0.030090 0.016187 0.115443 -0.097331
--0.019139 0.099440 0.002198 -0.030953 0.021099
--0.045399 -0.046871 0.022533 -0.064657 0.005776
-0.049063 -0.028478 0.019268 0.054265 0.028042
-0.045559 -0.005541 -0.014410 -0.024165 -0.054976
--0.073258 0.084205 0.036077 -0.068683 0.004708
--0.085228 0.001234 0.046261 -0.050496 -0.028227
--0.086828 -0.001218 0.021865 0.003791 -0.000568
--0.088733 -0.040041 -0.035891 -0.054915 0.073463
--0.132031 -0.012844 -0.068544 0.013052 0.087335
-0.038603 -0.115382 -0.010433 -0.007113 0.095126
--0.047378 -0.081353 0.018021 -0.021156 -0.120774
-0.040038 0.007633 -0.088728 -0.009928 0.020142
-0.052024 -0.021063 -0.118121 0.102739 -0.055837
-0.005253 -0.061924 0.063680 -0.014512 -0.020259
-0.029493 -0.013435 -0.020638 0.089342 0.001092
--0.046491 -0.145634 -0.083159 -0.158142 -0.279281
-0.003611 0.055863 -0.064655 -0.088773 0.089283
--0.029619 -0.089949 0.017197 -0.066633 -0.052347
-0.090828 -0.087551 0.000338 0.085238 -0.005313
-0.096211 0.071381 -0.076546 -0.077927 -0.040864
-0.062936 0.041559 0.016235 -0.017513 0.014773
--0.025734 0.028586 0.070292 0.055794 -0.026131
--0.076954 -0.082228 0.043947 -0.035921 0.152668
--0.049510 0.023159 0.008506 -0.044773 -0.160358
-0.024984 -0.025587 -0.071627 -0.038376 0.088478
-0.120568 0.046723 0.086731 0.000695 -0.015751
--0.027837 -0.160937 -0.095031 0.036271 -0.009061
--0.015078 -0.036281 -0.103665 -0.058258 -0.049573
-0.022021 0.108296 -0.002586 0.065655 -0.018584
--0.046441 -0.031018 0.067350 0.014328 0.008860
--0.000245 0.063400 -0.001810 0.043515 0.090344
--0.063845 0.020485 0.079401 0.070558 -0.116428
-0.032628 0.068949 0.052238 -0.044530 0.096813
-0.029911 -0.008814 0.044352 -0.168172 0.009604
-0.055828 -0.100739 -0.026013 0.021193 -0.051425
-0.035891 -0.004085 0.030216 -0.060801 0.037202
-0.007262 0.120686 0.026846 0.058464 -0.100792
--0.009176 0.027589 0.123957 -0.011283 -0.025744
--0.105081 0.118244 -0.042122 -0.025404 0.000873
--0.012703 0.084159 -0.067539 -0.140536 0.041637
--0.014485 -0.043382 -0.048004 -0.075416 0.054401
--0.018651 -0.032908 0.164231 -0.053236 0.033946
--0.021681 -0.012655 -0.037049 -0.001613 -0.053393
--0.014635 0.017954 -0.116115 -0.027232 0.034005
--0.035376 0.026492 -0.037250 0.070733 0.074835
--0.021378 -0.142980 0.123195 0.003699 0.025398
-0.015629 0.077370 0.032623 0.121580 0.097100
-0.000946 -0.056355 0.042065 0.008184 -0.081824
--0.101937 0.065473 0.003360 0.069241 0.073002
--0.053844 -0.044301 0.080351 -0.091833 0.044288
-0.007447 -0.120723 -0.013806 -0.023636 -0.064616
-0.030556 0.072630 0.074428 -0.087759 -0.026440
-0.064840 0.049162 0.091053 0.023891 0.033811
--0.027746 0.116392 0.106126 -0.056644 -0.014781
-0.036137 -0.002632 0.055512 0.070077 0.067819
--0.030625 0.053772 -0.078457 -0.021351 -0.113011
-0.052797 0.044875 -0.077269 -0.009867 0.101493
-0.073477 -0.024103 0.049145 -0.004706 -0.025211
--0.053731 -0.049009 -0.035786 0.054430 0.046515
-0.025154 -0.043569 -0.034789 -0.058610 0.006931
-0.012049 0.046809 -0.129441 0.025541 -0.030933
-0.000297 -0.054058 0.179837 0.081515 0.004932
--0.028445 -0.073753 0.010629 0.080042 0.098710
--0.014017 0.057597 0.001010 0.071658 -0.067570
-0.074384 0.110366 -0.018121 -0.108754 0.037793
-0.028041 -0.047508 -0.031359 -0.098913 -0.036486
--0.017311 -0.001279 -0.013694 0.051968 0.036512
-0.088201 0.031155 -0.043442 -0.065045 0.023486
-0.027000 0.104768 -0.015176 -0.038754 -0.004178
-0.003732 0.062166 0.085438 -0.077368 -0.101645
--0.118347 0.007589 -0.056489 0.082268 0.020253
--0.035623 0.034235 -0.099354 -0.061237 -0.024285
-0.005441 -0.039694 -0.025957 -0.004411 0.049903
-0.003040 0.036243 0.023552 -0.007334 0.128963
--0.077727 -0.059175 -0.019437 -0.024872 0.004339
-0.084006 -0.076605 -0.102261 0.036714 -0.035205
--0.007642 -0.005125 -0.030525 0.096390 -0.053138
--0.002192 -0.024851 0.050645 0.041490 -0.043183
-0.046796 -0.050894 0.055023 0.133834 -0.024013
-0.000872 -0.057072 -0.000630 0.042070 -0.129339
--0.064283 0.037836 -0.066393 0.004438 0.125379
--0.062213 -0.067468 0.090177 -0.046094 -0.025725
-0.079101 -0.074909 -0.043730 -0.073483 0.069672
--0.020413 -0.000079 -0.049725 -0.120751 -0.046980
-0.039894 0.072305 0.009798 0.005613 -0.045217
-0.006862 0.036285 0.074819 -0.006747 0.015144
--0.071562 0.012324 -0.001082 0.014835 0.079960
--0.027804 0.103358 -0.017203 0.014914 -0.056687
-0.030827 0.028076 0.003395 -0.073255 0.110310
-0.056498 -0.044893 0.110122 -0.109058 -0.052302
--0.001604 -0.089977 -0.060548 0.107808 0.025463
--0.070203 -0.000513 -0.123913 0.046247 -0.085392
-0.096343 0.095890 -0.064950 0.070363 0.034272
-0.037773 -0.076950 0.124858 -0.009008 -0.010115
-0.083868 0.051242 0.039149 0.015185 0.083375
-0.029773 -0.045961 0.100395 0.003743 -0.138294
--0.041755 0.010806 0.057797 -0.147374 0.095858
--0.009929 -0.103347 -0.032310 -0.110560 0.121377
-0.145244 0.017079 -0.080587 0.020516 -0.044939
--0.010477 0.038347 -0.003466 -0.001618 0.019600
--0.021762 0.125482 0.011074 0.065815 0.040298
-0.009202 -0.051686 0.129684 -0.131135 0.044536
-0.009313 0.102518 -0.075351 0.054338 0.020273
--0.045753 0.031345 0.000407 -0.097294 -0.000416
--0.007466 -0.044972 -0.078744 0.042414 0.066624
-0.030318 -0.067852 0.061416 -0.028992 0.056606
-0.004038 -0.036253 -0.014279 0.023123 -0.007832
--0.000137 -0.027684 -0.127648 -0.007713 -0.008746
--0.026500 0.049032 -0.183319 0.059107 0.066500
-0.016902 -0.093331 0.090129 0.016648 -0.083492
--0.023669 -0.010473 0.027614 0.145068 0.000681
-0.044133 -0.035809 0.005668 -0.090461 -0.090732
--0.033927 0.042997 0.021700 -0.046955 0.044487
--0.026444 -0.061011 0.010110 -0.023804 0.030427
--0.015195 -0.155603 -0.016584 0.021461 -0.003528
--0.059784 0.032214 0.000847 -0.098859 -0.078980
-0.043188 0.066433 0.062309 0.144507 0.006865
--0.068953 0.046698 0.099369 0.043354 -0.014309
--0.033202 -0.002950 0.040734 0.083454 0.039319
-0.051358 0.006074 -0.073465 -0.090554 -0.120787
--0.040676 0.092412 -0.085151 -0.021699 0.005813
-0.103135 0.024964 0.025832 -0.075982 0.035699
--0.027310 -0.153007 0.036420 0.057600 0.081630
-0.001605 -0.054191 -0.033043 -0.014390 -0.071383
-0.036180 0.035860 -0.046980 0.038541 -0.044757
--0.078032 -0.029878 0.078183 0.082251 0.010549
-0.053317 -0.038231 -0.065610 0.055798 0.037504
-0.076317 -0.027605 0.010349 0.095361 -0.088636
-0.049089 0.113316 0.051084 0.038589 0.034330
--0.055948 -0.037217 -0.015418 -0.139976 0.036306
-0.039306 -0.009889 -0.044910 0.016559 -0.000050
-0.106073 0.015280 -0.002563 -0.109085 -0.048475
--0.035319 0.163860 0.032981 -0.044932 0.003227
--0.123233 -0.010638 0.055479 -0.003666 -0.072249
--0.111158 0.065365 0.010691 0.039119 -0.001837
--0.118729 0.061470 -0.002077 -0.033335 -0.060165
--0.026081 -0.001806 -0.079616 -0.000075 0.080598
-0.032908 -0.035140 -0.003136 -0.029024 0.094622
--0.075773 -0.022898 -0.014817 0.058393 -0.111505
-0.036794 -0.015760 -0.112602 0.030323 0.085897
--0.020834 0.056079 -0.103762 0.117671 -0.041205
-0.041684 -0.084336 0.034186 0.011973 -0.006313
-0.040836 -0.035709 0.034170 0.122672 0.090973
--0.053182 -0.059371 0.091017 -0.090998 -0.116986
-0.001405 0.138364 0.017107 -0.064076 0.103486
--0.031142 -0.030068 0.046547 -0.133471 -0.042055
-0.140418 -0.125084 0.035218 -0.001162 -0.021130
--0.012034 0.097413 -0.079006 -0.039030 -0.054011
-0.143887 0.078835 -0.000601 -0.021173 -0.039895
--0.025050 0.075865 0.039221 0.032458 0.038206
--0.038873 -0.085003 -0.032736 -0.026956 0.113525
--0.023933 0.120794 -0.003862 -0.026459 -0.138724
-0.089559 0.029002 -0.052098 -0.085692 0.115174
-0.083497 0.024179 0.119021 -0.067541 0.019047
--0.027720 -0.086083 -0.055329 0.020087 -0.027086
--0.047858 -0.051975 -0.035205 -0.059342 -0.068582
-0.058936 0.044141 -0.080315 0.119744 -0.046518
--0.064588 -0.027212 0.147823 0.032404 0.016690
-0.024302 0.085560 -0.001525 0.016469 0.038891
--0.020146 0.019943 0.045067 0.038070 -0.086274
--0.025769 0.044192 0.102141 -0.064765 0.055849
-0.048803 -0.030066 -0.009220 -0.116655 0.068295
-0.047580 -0.076138 -0.070307 0.047582 -0.111342
-0.004656 -0.004452 0.029703 -0.004259 0.011130
-0.014446 0.166086 0.059565 0.000985 -0.052607
-0.013251 0.094476 0.106216 0.016715 -0.025581
--0.101244 0.072897 -0.114526 0.024681 0.010784
--0.051759 0.032389 -0.050202 -0.083316 0.052334
--0.035100 -0.116721 -0.110336 -0.053391 0.065541
--0.029790 -0.020457 0.135285 -0.004142 0.111508
--0.030936 0.018549 -0.016034 0.018572 -0.084336
--0.048615 -0.018739 -0.096815 -0.090162 0.019410
--0.040821 -0.009925 -0.097427 0.091891 0.031793
--0.024598 -0.132848 0.078353 0.089339 -0.068562
--0.020779 0.040974 -0.055675 0.169131 0.029649
-0.078165 -0.050679 -0.005881 -0.004983 -0.104324
--0.069096 0.127960 0.011392 -0.000769 0.062168
--0.079842 0.001606 0.089284 -0.035465 0.031075
-0.029519 -0.102956 -0.010902 -0.064030 -0.019669
-0.057492 0.075802 -0.008904 -0.060743 -0.053144
-0.005126 0.062980 0.085674 0.019895 0.104448
--0.086473 0.056906 0.056795 -0.012940 0.036606
--0.008604 -0.040450 0.042062 0.041810 0.027680
--0.092256 0.091237 -0.039500 0.024761 -0.088978
-0.068585 0.088295 -0.048033 -0.017808 0.045370
-0.124600 -0.035320 0.056751 0.092751 0.054025
--0.015725 -0.061938 0.036806 0.078768 -0.016065
-0.002444 -0.023887 -0.072177 -0.029790 -0.005860
-0.015478 0.129142 -0.091024 0.071482 -0.065445
-0.005867 -0.006051 0.098646 0.054089 0.018713
-0.033837 -0.008355 -0.051959 0.057440 0.160305
--0.001863 0.016738 -0.033705 0.062233 -0.140759
-0.027342 0.060074 0.030362 -0.117875 0.061020
--0.028026 -0.088238 -0.003782 -0.146288 -0.080395
-0.050048 0.036136 0.019500 0.066902 0.020355
-0.024817 -0.056254 -0.140918 -0.085803 0.020540
--0.003730 0.161411 -0.049408 0.000219 -0.002348
--0.055021 0.067820 0.126483 -0.031063 -0.119299
--0.102834 0.001133 0.010172 0.107707 -0.029106
--0.059813 0.036698 -0.021720 -0.043189 -0.002270
--0.031694 0.009605 -0.022459 -0.036417 0.053675
-0.061561 -0.012723 0.050040 -0.029450 0.131044
--0.124516 -0.107579 -0.012171 0.011761 0.002599
-0.016327 -0.060854 -0.080910 0.030875 -0.002997
--0.020970 -0.011880 -0.086096 0.037912 0.012421
-0.055253 -0.007250 0.041740 0.055596 -0.024420
--0.017564 -0.079202 0.008897 0.180091 0.054490
-0.001772 -0.022151 -0.082048 -0.010559 -0.163377
--0.020660 -0.017827 -0.030800 -0.045856 0.122405
--0.052946 -0.130490 0.097383 -0.116737 0.039855
-0.056504 -0.059549 -0.059931 -0.018658 0.034898
-0.054889 0.005373 -0.066796 -0.127360 0.047960
-0.071746 0.027410 -0.006212 0.024132 -0.094062
-0.005369 -0.008926 0.073085 -0.014265 -0.029204
--0.100025 -0.072076 0.014651 0.069368 0.048275
--0.066823 0.086074 0.014921 -0.015395 -0.045138
-0.026224 0.000902 -0.038208 -0.035221 0.057397
-0.097606 -0.073195 0.051626 -0.033488 0.027813
-0.002070 -0.097510 -0.057877 0.126680 -0.082194
--0.072597 0.006014 -0.093185 -0.016853 -0.022790
-0.138461 0.005394 -0.056485 0.102778 0.028918
--0.045604 -0.060041 0.121251 0.029260 -0.101404
-0.061194 0.033039 -0.016798 0.064263 0.065144
-0.010925 0.023151 0.107623 0.027977 -0.090356
--0.024863 -0.006440 0.047870 -0.047486 0.088211
--0.012139 -0.116121 -0.000525 -0.140961 0.016604
-0.063490 -0.022732 -0.046944 0.066970 -0.068838
-0.016143 0.026202 -0.043344 -0.064881 0.024877
--0.072845 0.120531 0.077901 0.047272 0.011713
--0.044646 0.040932 0.076164 -0.101233 -0.029615
--0.065118 0.050966 -0.023273 0.053517 0.023710
--0.007489 0.035822 0.023439 -0.055528 -0.004033
--0.007662 -0.096546 -0.081662 0.037141 0.137562
-0.075526 -0.097496 0.123990 0.013996 0.087005
--0.019788 -0.082043 0.020524 0.007027 -0.021537
--0.036264 -0.090952 -0.177722 -0.009306 -0.031473
--0.009287 0.047557 -0.090241 0.089347 0.056375
--0.005506 -0.112128 0.004356 0.064421 -0.038478
--0.035674 0.040616 0.007731 0.160236 -0.054199
--0.007537 0.012434 0.022001 -0.021567 -0.075163
--0.026053 0.015909 0.041015 0.021832 0.034152
--0.048539 -0.086655 0.047465 0.000682 0.042640
-0.023697 -0.095971 -0.022874 -0.000369 0.003413
-0.046005 0.064807 0.010131 -0.129517 -0.092254
-0.116469 0.053796 0.038110 0.094470 0.018435
--0.034803 0.073591 0.108348 0.104096 0.049884
--0.021274 0.022097 0.065347 0.065555 0.089319
-0.000474 -0.004186 -0.040493 -0.065543 -0.083167
--0.017425 0.049177 -0.044248 0.008399 0.068180
-0.154778 0.027549 -0.008012 0.014950 0.043254
-0.039599 -0.136415 -0.018716 0.061900 0.031263
-0.058118 -0.037200 -0.114692 -0.080876 -0.053238
-0.077436 0.015015 -0.092517 0.005804 -0.065541
--0.005653 -0.073184 0.095594 0.082470 0.060989
--0.000262 -0.035766 -0.083441 0.122634 0.088429
--0.014397 -0.055434 -0.005659 0.069697 -0.064892
-0.008824 0.082498 0.051866 -0.036070 0.033403
--0.082855 -0.087376 0.002714 -0.097121 -0.019170
-0.027179 -0.069870 -0.009316 0.047450 0.040657
-0.060527 0.004620 -0.040264 -0.051228 -0.029023
--0.071384 0.101421 0.009538 -0.099185 0.060100
--0.048395 -0.024677 0.025125 -0.056043 -0.058045
--0.054059 0.008107 0.021078 0.045290 -0.018459
--0.113359 0.014009 -0.006826 -0.052747 0.046922
--0.075976 0.008538 -0.084411 -0.004369 0.045801
-0.075392 -0.067340 0.014454 0.032407 0.092478
--0.061859 -0.083458 0.051442 0.031695 -0.080233
-0.054028 0.027000 -0.073549 0.032300 0.036501
--0.011384 -0.020780 -0.124142 0.093905 -0.028332
-0.039139 -0.030944 0.079952 -0.001717 0.013976
-0.038005 -0.001751 -0.044097 0.129827 0.014385
--0.001682 -0.063458 -0.002511 -0.078150 -0.141236
-0.021955 0.104851 -0.093246 -0.060019 0.069998
-0.004399 -0.096408 0.059327 -0.062268 -0.074327
-0.108063 -0.090534 -0.045654 0.048119 0.049187
-0.042105 0.043964 -0.091516 -0.047999 -0.028881
-0.070471 0.055401 -0.025605 0.011176 0.008475
-0.022254 0.038266 0.048106 0.047176 -0.017967
--0.010978 -0.088762 0.034806 0.019311 0.126815
--0.010571 0.053073 0.032162 -0.000780 -0.152200
--0.014253 -0.021954 -0.131040 -0.061376 0.113838
-0.060725 0.020201 0.102533 -0.011392 -0.052046
--0.069625 -0.091011 -0.097954 0.067847 0.017856
--0.053461 -0.040679 -0.121664 -0.077208 -0.106919
-0.057996 0.069756 -0.012433 0.069569 -0.055159
--0.024801 -0.060448 0.101700 0.014619 0.036580
--0.004526 0.093977 -0.028211 0.045261 0.149736
--0.014691 -0.007959 0.097708 0.107128 -0.079723
-0.029157 0.020116 0.104828 -0.064208 0.119172
-0.039583 -0.029446 0.006628 -0.110398 0.004062
-0.048132 -0.060601 0.009448 0.051777 -0.053127
-0.050551 -0.001924 0.028079 -0.050618 -0.013698
-0.001920 0.088162 0.073078 0.085795 -0.066788
-0.014025 0.042699 0.176241 -0.046674 -0.034822
--0.051433 0.121729 -0.057076 0.023901 0.045075
--0.057182 0.054780 -0.017280 -0.146674 0.002090
--0.016223 -0.044841 -0.084524 -0.152479 0.072688
--0.006962 0.008711 0.127455 -0.003876 0.053162
--0.013682 -0.025386 -0.000427 -0.024811 -0.024474
--0.056267 0.062116 -0.121311 -0.053011 0.065651
--0.075385 -0.008680 -0.063033 0.083039 0.110577
--0.000152 -0.127017 0.055904 0.013659 0.005664
--0.002852 0.047248 0.001128 0.100773 0.037274
-0.026368 -0.042205 0.021887 -0.020247 -0.056678
--0.077475 0.089799 0.058003 0.039741 0.106663
--0.016853 -0.015972 0.075741 -0.048829 0.015374
--0.032657 -0.125677 -0.062060 -0.057409 -0.061287
-0.073151 0.050357 0.053547 -0.059886 -0.051298
-0.057954 -0.003817 0.076028 0.006757 0.061109
--0.038030 0.143209 0.092207 -0.018493 0.062291
-0.005751 -0.036449 0.067582 0.031449 0.101894
--0.080754 0.011515 -0.049485 -0.016137 -0.087818
-0.108851 0.038222 -0.099315 -0.003117 0.052278
-0.107517 -0.036233 0.065370 0.040409 -0.057029
--0.033167 -0.081758 -0.019502 0.033438 0.013365
--0.017760 -0.025906 -0.020244 -0.078722 -0.011697
--0.028246 0.068647 -0.106417 0.026956 -0.064914
-0.062711 -0.017857 0.151539 0.044613 -0.017820
-0.009085 -0.032785 -0.025795 0.075790 0.075667
--0.040398 0.058556 -0.042634 0.093973 -0.099529
-0.057103 0.073562 0.012640 -0.066141 0.029558
-0.060219 -0.083699 -0.054799 -0.120442 -0.000374
-0.006521 0.034512 -0.039558 0.042191 0.033865
-0.103992 -0.014977 -0.077384 -0.051340 0.001873
-0.047451 0.140612 -0.024885 -0.021420 -0.046604
-0.030606 0.100660 0.076356 -0.019288 -0.098570
--0.114463 -0.010855 -0.034657 0.025618 -0.003356
--0.087913 0.064346 -0.075540 -0.091569 -0.024965
--0.021232 -0.017255 -0.056931 -0.003104 0.030219
--0.020112 -0.012334 0.035298 0.001405 0.161753
--0.064618 -0.064401 -0.007218 -0.000120 -0.047208
-0.116105 -0.056464 -0.069645 -0.007032 -0.012090
--0.023237 0.016000 -0.039802 0.074319 -0.012604
-0.014863 -0.058081 0.093219 0.062253 -0.040302
-0.027405 -0.128683 0.039923 0.116808 -0.011706
-0.012483 -0.017698 0.003645 -0.007588 -0.120662
--0.032868 0.066217 -0.031343 -0.034166 0.146334
--0.031228 -0.125921 0.117756 -0.042686 -0.062094
-0.049375 -0.112262 0.010166 -0.073599 0.048690
-0.028292 0.020076 -0.062865 -0.106114 -0.025300
-0.066916 0.029279 0.028191 -0.003599 -0.040614
-0.020491 0.060238 0.052747 -0.010390 -0.022389
--0.063358 -0.028707 0.035907 -0.011898 0.079703
--0.003758 0.078051 -0.017869 0.009045 -0.018982
-0.034974 0.069405 -0.018909 -0.038613 0.083909
-0.033935 -0.036607 0.088891 -0.052599 -0.059839
-0.052758 -0.068308 -0.063615 0.126093 -0.009460
--0.042175 -0.011113 -0.073071 0.052086 -0.052619
-0.049226 0.066898 -0.045666 0.117923 0.053656
--0.010739 -0.043962 0.141903 0.001792 -0.035469
-0.090671 0.043993 -0.013655 0.018989 0.127223
-0.001030 -0.001154 0.081839 -0.024979 -0.103704
--0.077920 0.036083 0.068220 -0.062210 0.113730
--0.010501 -0.065801 0.050885 -0.104304 0.121937
-0.111850 0.009680 -0.011791 0.001677 -0.035029
-0.010677 0.024572 -0.012860 -0.030323 -0.010466
-0.011279 0.167752 0.003136 0.109709 0.007292
-0.000987 0.004572 0.108706 -0.113192 -0.012431
--0.015225 0.073653 -0.051275 0.077928 -0.012752
--0.011708 0.014172 0.025162 -0.095378 0.026382
--0.028889 -0.058569 -0.129329 0.011087 0.061452
-0.056893 -0.058004 0.103586 -0.060752 0.081824
--0.042805 -0.015991 -0.024444 0.028952 -0.013528
-0.042851 0.019988 -0.165741 -0.031012 -0.014713
--0.026059 0.031698 -0.134343 0.032090 0.020828
-0.051674 -0.128006 0.050856 0.022220 -0.073513
--0.009340 0.013756 0.036163 0.098407 -0.023495
-0.023858 0.008121 0.022220 -0.103489 -0.046663
--0.033000 0.063565 0.029224 -0.012693 0.084202
-0.012187 -0.051000 0.026126 -0.043293 0.008675
--0.019812 -0.165070 -0.014555 -0.047431 0.017990
--0.040073 0.107192 0.022228 -0.089023 -0.066885
-0.014630 0.073186 0.069902 0.072634 0.019593
--0.041539 0.031788 0.092310 0.027223 0.034027
--0.051855 0.000391 0.007869 0.131910 0.069384
-0.046276 0.040440 -0.037093 -0.031393 -0.112828
-0.015709 0.096749 -0.103205 -0.021284 0.011405
-0.158287 -0.021028 0.042219 -0.050759 0.069715
--0.042907 -0.116980 0.014224 0.094648 0.028395
-0.041535 -0.057033 -0.047607 -0.024419 -0.034905
-0.010125 0.036728 -0.052503 -0.001839 -0.033477
--0.053414 -0.070394 0.092895 0.100600 -0.026352
-0.080574 -0.028763 -0.059548 0.094571 0.091787
-0.041437 0.014312 0.045792 0.108269 -0.081586
-0.056288 0.137447 0.054718 -0.032474 0.054502
--0.100144 -0.006460 0.024739 -0.117043 -0.008919
-0.070299 -0.036862 -0.014543 0.024500 -0.015222
-0.114975 -0.043705 0.000421 -0.061872 -0.035148
--0.022797 0.128575 -0.031798 -0.086718 -0.007172
--0.071706 -0.006833 0.028645 -0.007011 -0.096745
--0.142269 0.027996 0.065210 0.061381 0.000741
--0.140531 0.017480 -0.014986 -0.040893 -0.012718
--0.012494 -0.021869 -0.032923 0.016456 0.104475
-0.010792 -0.066178 0.019097 -0.001893 0.067513
--0.092673 -0.059851 -0.045936 0.052642 -0.062500
-0.065013 -0.025659 -0.149301 0.051705 0.035692
--0.045790 -0.007482 -0.069141 0.149365 -0.042039
-0.018492 -0.081315 0.055880 0.058158 0.019669
-0.063836 -0.012391 0.007057 0.155454 0.033854
--0.016532 -0.007661 0.043113 -0.080283 -0.108670
--0.029344 0.093781 -0.015840 -0.068134 0.091804
-0.004148 -0.058507 0.059633 -0.095883 -0.004939
-0.086151 -0.113571 -0.019466 -0.009167 0.003662
+++ /dev/null
-1 4
-35
-80
-140
-250
+++ /dev/null
-1 8
-50
-100
-200
-400
-500
-600
-800
-1000
-
+++ /dev/null
-1 8
-300
-350
-400
-450
-500
-550
-600
-650
+++ /dev/null
-1 8
-500
-600
-750
-900
-1100
-1300
-1500
-1700
-
+++ /dev/null
-10 256
-0.5862 0.7213 0.9146 1.0909 1.2910 1.4954 1.8370 2.0840 2.3771 2.5518
-0.0871 0.2049 0.5849 0.8552 1.2096 1.4686 1.8210 2.0926 2.4508 2.7389
-0.2274 0.3126 0.6088 0.8338 1.1824 1.5948 1.8228 1.9856 2.1832 2.4793
-0.1827 0.2706 0.5842 0.7761 1.0301 1.2462 1.6313 1.9786 2.3479 2.6790
-0.3055 0.3863 0.7194 1.1609 1.3303 1.5017 1.7265 1.9412 2.4659 2.6315
-0.1794 0.2522 0.5477 0.7892 1.3887 1.7101 1.9471 2.1667 2.4361 2.6310
-0.1825 0.2729 0.4185 0.6024 1.2531 1.7291 1.9937 2.1849 2.5865 2.7748
-0.3219 0.4045 0.7357 1.2708 1.4626 1.6439 1.9388 2.1212 2.5005 2.6749
-0.2234 0.3496 0.5054 0.6981 0.8672 1.0431 1.7091 2.0690 2.3290 2.6195
-0.3009 0.3957 0.7576 0.9751 1.1955 1.7727 2.0383 2.2474 2.5612 2.7188
-0.3841 0.5544 0.9209 1.1811 1.5441 1.8126 2.1175 2.3192 2.5486 2.6935
-0.2153 0.3105 0.5597 0.8313 1.2168 1.4512 1.7012 1.8962 2.3893 2.5852
-0.3196 0.4814 0.7629 1.0869 1.5517 1.7780 2.0462 2.2547 2.5023 2.6706
-0.1964 0.3055 0.4307 0.7178 1.4260 1.6240 1.8392 2.0576 2.2976 2.5492
-0.4260 0.6888 1.2019 1.4194 1.6437 1.8221 2.0469 2.2508 2.5142 2.6795
-0.3004 0.3944 0.5847 1.0050 1.1812 1.3559 1.5479 1.7847 2.4924 2.6703
-0.1595 0.2398 0.4336 0.9228 1.2602 1.5064 1.7915 1.9840 2.2320 2.5692
-0.1832 0.2985 0.4205 0.5980 0.7620 0.9894 1.7499 2.1151 2.4814 2.7214
-0.2234 0.3207 0.5457 0.9799 1.2074 1.7079 1.9734 2.1742 2.4575 2.6366
-0.3598 0.4819 0.6385 0.8878 1.3226 1.4910 1.7257 1.9456 2.2061 2.4579
-0.4671 0.5911 0.8513 1.0923 1.5104 1.7043 1.9727 2.1839 2.4484 2.6111
-0.2418 0.3937 0.5420 0.8971 1.1152 1.3054 1.7928 1.9796 2.5441 2.7572
-0.3541 0.4730 0.6546 0.9063 1.0792 1.2743 1.8545 2.0555 2.3083 2.5404
-0.3121 0.4016 0.7137 0.8835 1.0736 1.5907 1.8624 2.0857 2.5075 2.6668
-0.2232 0.3631 0.5273 0.7438 1.0492 1.2235 1.5449 2.2198 2.5160 2.6852
-0.2557 0.3528 0.5051 0.6528 0.8351 1.5688 1.8838 2.1056 2.4401 2.6111
-0.4342 0.5318 0.9234 1.1146 1.3015 1.5198 1.8211 2.0340 2.3694 2.5506
-0.4310 0.5269 0.7431 0.9018 1.0734 1.5196 1.8267 2.0244 2.4508 2.6177
-0.2150 0.3249 0.4966 0.9434 1.1627 1.3497 1.8003 2.0045 2.3567 2.5909
-0.2798 0.4111 0.5786 0.7971 1.0414 1.2142 1.6947 2.0866 2.3351 2.5545
-0.1688 0.2693 0.4004 0.6337 1.3058 1.5064 1.7535 1.9689 2.5542 2.7424
-0.4419 0.6209 1.0127 1.2135 1.4104 1.6111 1.8820 2.1005 2.4238 2.5966
-0.3645 0.5120 0.8977 1.2209 1.5286 1.7204 1.9787 2.1779 2.4390 2.6114
-0.2897 0.4136 0.5504 0.8515 1.2641 1.4334 1.8079 2.0656 2.3509 2.7593
-0.1611 0.4723 0.7420 1.0071 1.2571 1.5891 1.9224 2.2345 2.5647 2.7991
-0.2528 0.4178 0.8909 1.3117 1.6622 1.8641 2.1017 2.2974 2.5299 2.6982
-0.1749 0.2700 0.4116 0.6036 1.1430 1.7776 2.0394 2.2220 2.4667 2.6598
-0.3451 0.4325 0.6194 0.7406 0.9176 1.5540 1.8426 2.0479 2.4401 2.5965
-0.3672 0.5164 0.6558 0.8441 1.2332 1.4114 1.6955 2.0875 2.3674 2.5471
-0.2194 0.3467 0.7384 1.1079 1.5398 1.8437 2.1212 2.3296 2.5800 2.7403
-0.1525 0.2343 0.3915 0.6843 1.0517 1.5020 1.7905 1.9667 2.2027 2.6725
-0.3531 0.5908 0.7462 0.9441 1.2774 1.4743 1.8268 2.1059 2.4478 2.6484
-0.3611 0.4981 0.7598 0.9676 1.4024 1.6330 1.9094 2.1433 2.4408 2.6130
-0.2153 0.3366 0.4974 0.6693 1.1944 1.6791 1.9002 2.1105 2.4100 2.5922
-0.2421 0.3392 0.5123 0.9818 1.5411 1.7092 1.9989 2.1981 2.5659 2.7656
-0.2116 0.3250 0.4845 0.8021 1.0088 1.2158 1.8038 2.0223 2.2975 2.5810
-0.1902 0.2942 0.8003 1.1086 1.3606 1.6008 1.8956 2.1328 2.4481 2.6405
-0.2772 0.3914 0.5826 0.7654 0.9495 1.1240 1.3949 2.0411 2.3891 2.5959
-0.2678 0.5220 0.7630 1.1000 1.3747 1.6432 1.9391 2.2237 2.5511 2.7893
-0.3200 0.4245 0.6174 0.9904 1.1662 1.3882 1.7601 1.9524 2.3998 2.5819
-0.1702 0.4871 0.8370 1.0989 1.3593 1.5830 1.8750 2.1277 2.4666 2.6885
-0.2280 0.3748 0.6554 0.9113 1.2081 1.4619 1.8181 2.0541 2.3791 2.5701
-0.1752 0.4363 0.6454 0.8798 1.1079 1.5367 1.8667 2.1716 2.4804 2.7249
-0.3804 0.4700 0.8224 1.0099 1.1892 1.5906 1.8879 2.0907 2.4544 2.6238
-0.1808 0.2910 0.4683 0.7059 0.8980 1.4031 1.7063 1.9444 2.4658 2.6776
-0.2418 0.3803 0.5443 0.7589 1.1496 1.3185 1.5451 1.7433 2.1310 2.6523
-0.2698 0.3690 0.5362 1.0732 1.2921 1.4696 1.7440 1.9470 2.5051 2.6841
-0.4099 0.5102 0.6983 1.0468 1.2459 1.4185 1.8851 2.0815 2.3464 2.5605
-0.0669 0.1354 0.3764 0.8433 1.1719 1.4834 1.8181 2.1312 2.4626 2.8044
-0.1614 0.2372 0.3878 0.5708 1.2759 1.4950 1.8052 2.0807 2.3485 2.6293
-0.1688 0.2875 0.4301 0.9059 1.2361 1.4054 1.8057 1.9924 2.5589 2.7495
-0.2864 0.3783 0.7032 1.0817 1.2382 1.5741 1.8619 2.0656 2.5139 2.6848
-0.3829 0.4781 0.6766 0.8340 1.0056 1.4147 1.6650 1.8840 2.3922 2.5619
-0.3259 0.4187 0.6139 0.7338 1.1831 1.6497 1.9000 2.1278 2.4322 2.5930
-0.2569 0.3790 0.5426 0.8390 0.9871 1.4850 1.8652 2.0732 2.4314 2.6005
-0.1408 0.2283 0.4024 0.8784 1.1485 1.4003 1.7004 1.9205 2.3723 2.6522
-0.2971 0.5039 0.8005 1.1212 1.4232 1.7801 2.1255 2.3907 2.6795 2.8487
-0.1515 0.2344 0.4684 0.8040 1.0401 1.3774 1.8329 2.1235 2.5555 2.7770
-0.5778 0.7157 0.8910 1.0966 1.4235 1.6482 1.9551 2.1831 2.4572 2.6234
-0.3017 0.4161 0.8088 0.9971 1.2000 1.4419 1.7867 2.0224 2.3473 2.5400
-0.1208 0.2814 0.6564 0.9448 1.2377 1.5663 1.9084 2.2112 2.5583 2.8155
-0.2127 0.3127 0.4635 0.6416 0.8449 1.6652 2.0577 2.2656 2.5811 2.7434
-0.1942 0.3011 0.4212 0.6901 1.5369 1.7639 1.9608 2.1766 2.4435 2.6663
-0.3510 0.4345 0.7146 0.9086 1.0678 1.2579 1.4425 2.0265 2.4574 2.6252
-0.3225 0.4323 0.6168 0.8580 1.5388 1.7910 1.9927 2.2013 2.4494 2.6160
-0.2271 0.4488 0.6287 0.7857 1.2086 1.3830 1.6194 2.1955 2.5236 2.6945
-0.2568 0.3510 0.5613 1.0500 1.2521 1.4359 1.6995 1.9187 2.2148 2.4275
-0.2933 0.3941 0.6128 0.8899 1.0720 1.2862 1.5331 1.8301 2.1553 2.3865
-0.3480 0.4626 0.6009 0.7630 0.9044 1.1225 1.8539 2.1845 2.5035 2.7091
-0.1337 0.4722 0.8099 1.1273 1.4252 1.6990 2.0188 2.2922 2.6018 2.8168
-0.1138 0.3263 0.8059 1.0473 1.3262 1.6202 1.9439 2.2007 2.5347 2.7702
-0.1979 0.3130 0.4635 0.8504 1.1143 1.3221 2.0371 2.2421 2.5406 2.7491
-0.3321 0.4194 0.8239 1.0458 1.1981 1.3733 1.5661 1.9985 2.3747 2.5416
-0.3729 0.5958 0.9551 1.2650 1.5484 1.9255 2.2256 2.4809 2.7276 2.8935
-0.1664 0.2516 0.5347 0.7545 1.1971 1.4089 1.7400 2.0871 2.4098 2.6795
-0.2370 0.3178 0.6123 1.3315 1.5470 1.7257 2.0063 2.1977 2.5449 2.7252
-0.2030 0.3328 0.4766 0.7357 1.2780 1.4439 1.7229 1.9405 2.2278 2.6816
-0.1702 0.2919 0.4598 0.7123 0.9077 1.1450 1.8632 2.0806 2.4990 2.7100
-0.2421 0.3578 0.5400 0.7217 0.8971 1.4898 1.8518 2.1205 2.6077 2.7894
-0.3030 0.3935 0.5812 0.7404 0.9425 1.8342 2.0887 2.2811 2.5596 2.7118
-0.1322 0.1997 0.3466 0.6981 1.1811 1.4849 1.8594 2.1114 2.4708 2.7804
-0.2317 0.3069 0.6860 1.4306 1.7121 1.8671 2.1249 2.2995 2.5705 2.7456
-0.3778 0.4863 0.6639 0.9163 1.1560 1.3186 1.5389 1.7169 2.1603 2.5797
-0.2118 0.3499 0.5259 0.7200 1.1348 1.3140 1.5657 2.0241 2.2873 2.5184
-0.2902 0.4368 0.6331 0.8971 1.3102 1.5219 1.8674 2.1512 2.4708 2.6809
-0.1418 0.3988 0.6251 0.8544 1.1268 1.3964 1.7585 2.0322 2.3964 2.6928
-0.2314 0.3462 0.7282 0.9211 1.1766 1.4941 1.7368 1.9546 2.5170 2.7066
-0.2076 0.3251 0.7423 0.9590 1.1936 1.5329 1.8887 2.1588 2.4667 2.6709
-0.2058 0.4139 0.5745 0.7832 0.9595 1.1688 1.7561 1.9562 2.4840 2.7001
-0.1834 0.2971 0.4643 0.6625 0.8802 1.1137 1.5183 1.8417 2.3842 2.7042
-0.1688 0.4218 0.7070 1.0465 1.4496 1.6953 1.9560 2.2174 2.5172 2.7404
-0.2323 0.3981 0.5489 0.7227 1.2886 1.5221 1.7158 2.1184 2.4066 2.5898
-0.3470 0.5265 0.8140 1.0152 1.3206 1.5411 1.8490 2.0588 2.3556 2.5393
-0.1707 0.2595 0.6762 0.9037 1.2781 1.4903 1.7946 2.0610 2.3741 2.5771
-0.1457 0.2318 0.6039 1.0078 1.3461 1.5908 1.8818 2.1248 2.4432 2.6714
-0.6574 0.8086 1.0243 1.2183 1.4837 1.7129 2.0197 2.2464 2.5059 2.6716
-0.2546 0.4983 0.8674 1.2536 1.6704 1.9529 2.2134 2.4319 2.6532 2.8109
-0.2455 0.3379 0.4632 0.8635 1.5286 1.8047 1.9909 2.1806 2.4031 2.5729
-0.4772 0.6742 1.0000 1.2474 1.5288 1.7415 2.0102 2.2168 2.4770 2.6449
-0.3357 0.4382 0.6033 1.1317 1.3681 1.5576 1.9251 2.1119 2.5548 2.7395
-0.2588 0.7015 0.8953 1.0830 1.2828 1.5160 1.8965 2.1921 2.5150 2.7258
-0.2466 0.3512 0.5047 0.6646 0.8161 1.2577 1.8046 2.0214 2.4447 2.6491
-0.1631 0.2283 0.4070 0.5955 1.1126 1.3894 1.8978 2.1849 2.5384 2.7382
-0.3424 0.4748 0.6222 0.8020 0.9706 1.1568 1.7044 1.9297 2.2127 2.5627
-0.2088 0.5143 0.7400 0.9277 1.1032 1.3561 1.8841 2.2004 2.5882 2.7993
-0.2016 0.3488 0.5894 0.7419 1.1488 1.3626 1.5566 1.9694 2.5488 2.7209
-0.2558 0.3914 0.5360 0.7521 1.4330 1.6955 1.8886 2.1428 2.4190 2.5966
-0.4021 0.5034 0.6653 0.8123 0.9586 1.2825 1.9184 2.1120 2.4090 2.5970
-0.2343 0.4800 0.6934 0.8523 1.2786 1.4763 1.7235 2.0400 2.3602 2.5562
-0.2460 0.3687 0.5325 0.7044 1.1488 1.3608 1.8112 2.0757 2.4183 2.6630
-0.1616 0.3644 0.5725 0.9166 1.2481 1.4938 1.8388 2.1175 2.4712 2.7464
-0.3760 0.4841 0.6350 1.0082 1.2110 1.4003 1.8127 2.0018 2.5199 2.7238
-0.1988 0.2824 0.6553 1.0337 1.5413 1.7369 1.9751 2.1751 2.4372 2.6265
-0.2728 0.4094 0.7498 1.0645 1.3516 1.5946 1.9910 2.2172 2.4830 2.6614
-0.1657 0.5327 0.7281 0.9966 1.2385 1.4629 1.8119 2.0973 2.4469 2.6979
-0.1413 0.2098 0.3540 0.5492 0.8486 1.1288 1.6320 1.9056 2.2805 2.5438
-0.2856 0.3666 0.6259 1.1424 1.6605 1.8197 2.0147 2.1986 2.4121 2.5919
-0.2725 0.4829 0.7650 1.0119 1.2977 1.5488 1.8755 2.1155 2.4383 2.6377
-0.2736 0.3804 0.5537 1.0258 1.2269 1.4186 1.9718 2.1468 2.5665 2.7689
-0.2341 0.5953 1.1030 1.4549 1.7361 1.9758 2.2126 2.4213 2.6405 2.8181
-0.2273 0.4638 0.6228 0.8500 1.1016 1.2823 1.7094 1.9523 2.2669 2.7029
-0.2438 0.3798 0.7299 0.9600 1.3765 1.6104 1.8644 2.1161 2.5073 2.7137
-0.1551 0.4869 0.8676 1.2274 1.5069 1.8857 2.1868 2.4411 2.7106 2.8767
-0.2746 0.5454 0.7589 0.9458 1.1597 1.3349 1.6653 2.1142 2.4356 2.6239
-0.1793 0.2646 0.4344 0.7482 1.1502 1.3733 1.8558 2.0817 2.3248 2.5171
-0.2698 0.4202 0.5765 0.8301 1.0073 1.2101 1.9714 2.2051 2.5138 2.7395
-0.1929 0.3091 0.4460 0.6266 1.1805 1.3672 1.5990 2.1514 2.4729 2.6468
-0.1901 0.3047 0.4607 1.1019 1.3168 1.5343 1.9234 2.1365 2.5924 2.7807
-0.3139 0.5009 0.6700 0.8268 1.0117 1.1810 1.6539 2.1984 2.4828 2.6576
-0.1403 0.2173 0.4117 0.7302 1.0038 1.2732 1.7392 2.0337 2.3809 2.7386
-0.4166 0.5101 0.7449 1.1663 1.3492 1.5543 1.9000 2.0941 2.4588 2.6365
-0.3342 0.4335 0.6160 0.8559 1.0112 1.2097 1.4029 1.6361 2.4129 2.6324
-0.4543 0.6159 0.7932 0.9843 1.2562 1.4308 1.7116 1.9919 2.2671 2.4631
-0.2153 0.3609 0.5302 0.7089 0.8756 1.0376 1.6496 2.2826 2.5680 2.7441
-0.4380 0.6439 0.8282 1.0651 1.3650 1.5829 1.8838 2.1005 2.4006 2.5771
-0.2523 0.3636 0.5879 1.1628 1.3542 1.6756 2.0488 2.2543 2.6093 2.7953
-0.4179 0.5426 0.7065 0.8996 1.0684 1.3146 1.9705 2.2021 2.5051 2.7061
-0.1659 0.2860 0.6693 0.9229 1.3959 1.6544 1.9709 2.2257 2.5236 2.7460
-0.2540 0.4356 0.5946 0.7627 1.2274 1.4222 1.6573 1.9601 2.2514 2.4711
-0.1633 0.2337 0.3698 0.5421 1.1757 1.5916 2.1561 2.3371 2.5534 2.7737
-0.1953 0.2730 0.4521 1.2005 1.7062 1.8627 2.1313 2.3266 2.5906 2.7667
-0.3053 0.4054 0.5651 0.7470 0.8910 1.1720 1.8864 2.1074 2.3705 2.5744
-0.1761 0.3033 0.6501 0.8268 1.0369 1.2687 1.8534 2.1889 2.5074 2.7339
-0.2265 0.3990 1.1359 1.4137 1.6839 1.8912 2.0948 2.3042 2.5489 2.7234
-0.3326 0.5400 0.8711 1.0948 1.3752 1.6155 1.9360 2.1537 2.4451 2.6133
-0.2162 0.3522 0.5309 0.7470 0.9677 1.1747 1.5056 1.7942 2.1615 2.4800
-0.1872 0.2761 0.4053 0.7469 1.5858 1.8945 2.1198 2.3197 2.5819 2.7758
-0.5381 0.8651 1.2695 1.4918 1.7774 1.9696 2.1865 2.3687 2.5739 2.7158
-0.2663 0.3422 0.6098 1.2120 1.4516 1.6092 1.8506 2.0376 2.2929 2.5088
-0.1904 0.3051 0.5663 0.7391 1.1589 1.5705 1.8756 2.1653 2.5518 2.7693
-0.1543 0.3519 0.6976 1.0664 1.3696 1.7817 2.1308 2.4259 2.7070 2.8753
-0.3304 0.4283 0.5942 0.7425 0.8906 1.4067 2.0676 2.2460 2.5394 2.7006
-0.2080 0.3215 0.6278 0.7882 1.3123 1.5592 1.8048 2.0831 2.4303 2.6266
-0.1188 0.2481 0.8270 1.2420 1.5824 1.8976 2.1816 2.4248 2.6645 2.8459
-0.0635 0.1528 0.5973 0.9377 1.2653 1.5465 1.8818 2.1681 2.5089 2.7924
-0.3249 0.5179 0.9143 1.2973 1.4966 1.7550 2.0715 2.3166 2.6500 2.8305
-0.1918 0.3107 0.4506 0.6994 1.3463 1.5348 1.8447 2.1903 2.4480 2.6877
-0.3405 0.4644 0.7232 0.9199 1.2611 1.5175 1.8446 2.0652 2.3915 2.5781
-0.3289 0.5152 0.6602 1.0213 1.1886 1.5496 1.9553 2.1883 2.5394 2.7362
-0.3000 0.4097 0.8372 1.0793 1.3095 1.5684 1.8746 2.0783 2.3643 2.5490
-0.2421 0.3280 0.5288 0.9261 1.6911 1.8959 2.1013 2.2823 2.5238 2.6960
-0.1070 0.3131 0.6226 0.8881 1.1808 1.4867 1.8146 2.1088 2.4594 2.7186
-0.4400 0.5533 0.7025 0.9206 1.4089 1.5820 1.8080 2.0832 2.3577 2.5300
-0.2250 0.3434 0.4808 0.6721 0.8198 1.1446 2.0201 2.2625 2.5520 2.7604
-0.1671 0.2551 0.4603 0.6777 0.9661 1.5579 1.8659 2.1196 2.4425 2.6551
-0.3910 0.5877 1.0287 1.3547 1.6899 1.9166 2.1451 2.3337 2.5519 2.7071
-0.1435 0.2165 0.3968 0.8376 1.2572 1.5298 1.8791 2.1352 2.4636 2.7011
-0.1756 0.2799 0.4120 0.5808 0.7573 1.3340 1.8235 2.1200 2.4993 2.7365
-0.1332 0.2174 0.4716 0.9483 1.2723 1.6028 1.9272 2.2190 2.5588 2.7990
-0.2122 0.3143 0.7042 0.8849 1.1312 1.3711 1.6832 1.9633 2.2685 2.5156
-0.2089 0.3339 0.4817 0.8526 1.0657 1.2741 1.5747 1.8000 2.4860 2.6843
-0.1636 0.2617 0.4400 0.7357 1.0355 1.2638 1.5672 1.8504 2.1904 2.6588
-0.1945 0.2934 0.4869 0.8567 1.1262 1.3604 1.6898 1.9143 2.1475 2.3503
-0.1606 0.2442 0.3931 0.9237 1.5811 1.7529 2.0133 2.2272 2.5250 2.7265
-0.4866 0.7045 1.0593 1.2795 1.5326 1.8221 2.1461 2.3665 2.6041 2.7599
-0.4012 0.4911 0.7103 0.8585 1.0495 1.7244 2.0116 2.2041 2.5189 2.6643
-0.4365 0.6694 0.8644 1.1330 1.4510 1.7627 2.1032 2.3690 2.6280 2.8306
-0.2072 0.4018 0.6227 0.8913 1.3038 1.6056 1.9704 2.2816 2.6135 2.8182
-0.3302 0.4968 0.8713 1.0761 1.2576 1.4654 1.8152 2.1400 2.5404 2.7493
-0.1385 0.2292 0.3530 0.6006 1.4699 1.6571 1.9438 2.1663 2.5027 2.7308
-0.1894 0.2915 0.4345 0.6341 1.0024 1.1896 1.6896 2.0966 2.4086 2.6768
-0.3841 0.5197 0.8889 1.1480 1.4383 1.6285 1.8642 2.0669 2.3466 2.5325
-0.2008 0.3097 0.4664 0.6638 1.2798 1.4940 1.7270 2.0264 2.2915 2.4750
-0.1864 0.2857 0.4481 1.1025 1.3096 1.5035 1.7614 1.9891 2.4255 2.6031
-0.4081 0.6134 0.9514 1.1818 1.3943 1.6361 1.9891 2.2395 2.5547 2.7287
-0.2964 0.3876 0.9450 1.2247 1.3906 1.5882 1.8241 2.0589 2.4188 2.5871
-0.3127 0.4038 0.6168 1.0810 1.3067 1.4759 1.8817 2.0781 2.3394 2.5539
-0.2066 0.3059 0.4989 0.7132 0.9066 1.4460 1.7584 1.9755 2.2210 2.4741
-0.2634 0.3956 0.5667 0.8777 1.0517 1.6029 2.0590 2.2607 2.6064 2.7647
-0.4331 0.5315 0.7764 1.0444 1.2269 1.4311 1.7093 1.9187 2.4337 2.6149
-0.2161 0.4429 0.6851 0.8336 1.1037 1.2966 1.5283 2.0299 2.3407 2.5384
-0.2814 0.3637 0.5416 0.9475 1.5137 1.6945 1.8892 2.1017 2.3190 2.5007
-0.4454 0.6883 1.1402 1.4098 1.7435 2.0014 2.2521 2.4457 2.6495 2.7985
-0.1641 0.4083 0.6426 1.0592 1.3258 1.5754 1.8666 2.1381 2.4572 2.7177
-0.3391 0.4607 0.6072 0.8463 1.4207 1.6062 1.8303 2.0887 2.3615 2.5348
-0.2414 0.3396 0.5100 0.7470 1.3329 1.8618 2.0751 2.2564 2.5147 2.6874
-0.1694 0.2535 0.4156 0.8302 1.2853 1.5838 2.0907 2.3085 2.5929 2.7951
-0.2047 0.3652 0.6500 0.8068 1.0178 1.1865 1.4889 2.0671 2.5966 2.7634
-0.2425 0.3247 0.6020 1.2226 1.4272 1.5996 1.8377 2.0413 2.5333 2.7021
-0.3842 0.5030 0.6541 0.8771 1.0576 1.2612 1.6744 1.8735 2.4781 2.6803
-0.2042 0.3280 0.7283 0.8985 1.1444 1.3299 1.6032 2.1539 2.4739 2.6547
-0.1268 0.1924 0.3208 0.5153 1.1304 1.4443 1.8047 2.0552 2.4385 2.7572
-0.2713 0.3659 0.5395 1.0705 1.4228 1.5836 1.9763 2.1641 2.4459 2.6301
-0.3047 0.4043 0.5727 0.7368 0.8997 1.3242 1.6473 1.8879 2.4330 2.6295
-0.1224 0.3948 0.6903 0.9199 1.2852 1.5516 1.8645 2.1231 2.4657 2.7044
-0.2157 0.3281 0.5036 0.9272 1.0975 1.5285 1.8080 2.0569 2.5448 2.7221
-0.1670 0.2490 0.3696 0.5921 1.3019 1.8398 2.2165 2.3725 2.6142 2.8338
-0.3899 0.5573 0.8100 1.0732 1.3966 1.6598 2.0001 2.2517 2.5548 2.7403
-0.4905 0.6064 0.8222 0.9966 1.1912 1.5714 1.9628 2.1727 2.5300 2.7055
-0.1309 0.2342 0.6232 0.8795 1.1283 1.3655 1.7371 2.0251 2.3992 2.6885
-0.1805 0.2672 0.4297 1.2440 1.4967 1.6796 1.9592 2.1784 2.5439 2.7289
-0.2280 0.5429 0.6967 0.8732 1.4074 1.6074 1.9516 2.2124 2.5486 2.7722
-0.2339 0.3379 0.4924 0.9061 1.3074 1.4719 1.8884 2.1110 2.3618 2.5545
-0.1384 0.2291 0.5127 1.0450 1.4017 1.7884 2.1134 2.3664 2.6588 2.8435
-0.2196 0.6359 0.9100 1.2007 1.4589 1.7053 2.0128 2.2722 2.5520 2.7643
-0.1698 0.2615 0.3810 0.5706 1.4297 1.8686 2.0728 2.2559 2.4860 2.6701
-0.1445 0.2158 0.3658 0.5451 0.9389 1.3669 1.7900 2.0846 2.3924 2.7161
-0.2789 0.3816 0.5277 0.8487 1.3751 1.5461 1.7832 2.0264 2.2695 2.4665
-0.1733 0.3023 0.9216 1.2368 1.4776 1.7229 1.9952 2.2471 2.5390 2.7265
-0.3374 0.5033 1.0951 1.3262 1.5284 1.7336 1.9733 2.2009 2.4992 2.6751
-0.1293 0.2743 0.7533 1.0166 1.2416 1.4444 1.7962 2.0851 2.4770 2.7204
-0.3106 0.4176 0.6358 0.9434 1.1419 1.3458 1.9638 2.1678 2.4390 2.6235
-0.4533 0.5760 0.7392 0.9136 1.0829 1.2759 1.7903 2.0360 2.3124 2.5325
-0.3702 0.5218 0.6977 0.8776 1.1096 1.2855 1.5612 1.9480 2.2170 2.4361
-0.1637 0.2647 0.4185 0.6666 1.1584 1.3270 1.7829 1.9821 2.4361 2.7094
-0.1769 0.2767 0.3942 0.5746 1.3595 1.7110 1.9176 2.1405 2.3722 2.5705
-0.2712 0.3820 0.6524 0.8317 1.0341 1.3972 1.7312 1.9918 2.3854 2.5886
-0.1003 0.2046 0.7261 1.1004 1.4057 1.6697 1.9903 2.2603 2.5813 2.8009
-0.2534 0.3752 0.7192 0.9323 1.3698 1.5955 1.8653 2.0656 2.3368 2.5340
-0.3589 0.4508 0.6631 1.0521 1.5065 1.6697 1.8929 2.1074 2.3466 2.5242
-0.1955 0.2862 0.6111 0.8053 1.0501 1.5218 1.7996 2.0303 2.3788 2.5973
-0.2982 0.4033 0.5660 0.8924 1.1933 1.3465 1.7895 2.0173 2.2606 2.5069
-0.3356 0.4711 0.6310 0.8491 1.0049 1.4364 1.8176 2.0292 2.5710 2.7525
-0.2016 0.2912 0.4363 0.9800 1.4897 1.6494 1.8862 2.0819 2.3636 2.6091
-0.4549 0.6491 0.8450 1.0209 1.1747 1.3745 1.8824 2.1130 2.3760 2.5768
-0.2510 0.3524 0.5171 0.8931 1.4094 1.5710 1.8536 2.0478 2.4766 2.7320
-0.1576 0.2547 0.3891 0.8551 1.4282 1.5880 1.8583 2.0521 2.5359 2.7340
-0.3481 0.4382 0.7720 1.1289 1.3203 1.5019 1.7665 1.9570 2.2231 2.4465
-0.3116 0.4068 0.6991 0.8894 1.0912 1.5356 1.8084 2.0006 2.2323 2.4367
-0.2706 0.4033 0.8272 1.0851 1.4820 1.6927 1.9292 2.1267 2.4049 2.5857
-0.2745 0.3550 0.8663 1.3742 1.5545 1.7324 1.9664 2.1538 2.4581 2.6245
-0.1736 0.2553 0.5357 0.9009 1.1888 1.5132 1.8579 2.1181 2.4273 2.6847
-0.3026 0.4148 0.9044 1.1695 1.3657 1.7036 1.9891 2.2226 2.5441 2.7085
-0.3998 0.5108 0.7205 0.9848 1.1828 1.3716 1.7154 1.9191 2.1875 2.4257
-0.2141 0.3095 0.7428 1.0426 1.2851 1.5571 1.7901 1.9804 2.2462 2.5265
-0.1574 0.2290 0.3869 0.5735 1.0925 1.3383 1.6598 1.9364 2.2095 2.4195
+++ /dev/null
-10 128
-0.0120 0.0022 0.0068 -0.0112 -0.0508 -0.0490 0.2249 0.1476 0.0133 -0.0379
-0.0598 0.0477 0.0380 0.0660 0.0517 0.0150 0.0617 0.0081 -0.0768 -0.1007
--0.0087 -0.0440 0.0873 0.0882 0.0391 -0.0060 0.1100 0.0569 -0.0241 -0.0468
-0.0146 -0.0005 0.0322 -0.0650 -0.0778 -0.0780 -0.0255 -0.0527 -0.0301 -0.0401
--0.0240 -0.0560 -0.0374 0.0274 0.0484 -0.0227 0.0328 0.1135 0.0117 -0.0300
--0.0324 -0.0574 0.0302 0.0137 -0.0603 -0.1194 -0.0105 -0.0513 0.0698 0.0538
-0.0635 0.0382 0.0531 0.0897 0.0495 0.0039 -0.0421 -0.0919 0.0407 0.0167
-0.0954 0.0854 0.0360 -0.0025 -0.0252 -0.0528 -0.0435 -0.0561 -0.0405 -0.0432
-0.0110 -0.0010 -0.0433 -0.0167 0.1402 0.0738 0.0423 -0.0024 -0.0920 -0.1099
-0.0179 0.0184 -0.0041 -0.0640 0.1004 0.0608 -0.0023 -0.0357 0.1509 0.1262
--0.0145 -0.0240 -0.0595 -0.1063 0.0597 -0.0040 -0.0886 0.1184 0.0380 0.0126
--0.0072 0.0172 0.0076 0.0288 0.0810 0.0278 0.0709 0.0051 0.0214 -0.0301
-0.0127 -0.0126 -0.0434 0.1610 0.1178 0.0704 0.0257 -0.0073 -0.0425 -0.0610
--0.0165 -0.0369 -0.0785 0.1007 0.0309 -0.0651 0.0142 -0.0614 0.0426 0.0289
--0.0374 -0.0712 0.0049 -0.0382 0.0472 0.0095 -0.0268 -0.0747 -0.0457 -0.0758
--0.0211 -0.0432 -0.0547 -0.0446 -0.1078 0.0090 -0.0565 -0.1298 0.0721 0.0351
--0.0014 -0.0072 -0.0283 -0.0324 -0.0208 -0.0703 0.0979 0.0865 -0.0007 0.1881
--0.0077 -0.0302 0.1231 0.0905 0.0786 0.0432 -0.0286 -0.0661 -0.0055 -0.0275
-0.0010 0.0043 0.0044 0.0380 -0.1201 -0.0098 -0.0166 0.0105 0.0153 0.0134
-0.0843 0.0636 0.0416 -0.0004 -0.0570 -0.0592 0.1158 0.0590 0.0126 0.0034
-0.0346 0.0290 -0.0037 -0.0026 -0.0457 0.1824 0.1469 0.0870 0.0291 -0.0074
-0.0066 0.0682 -0.0148 0.0287 0.0095 -0.0563 0.1296 0.0426 0.1215 0.0886
--0.0132 -0.0399 0.0960 0.0474 0.0140 0.0306 -0.0192 -0.0703 -0.1559 -0.1556
--0.0600 0.0482 0.1257 0.0521 0.0229 -0.0031 0.0817 0.0571 -0.0138 -0.0277
-0.0013 -0.0103 -0.0470 -0.0687 -0.1444 0.0181 0.1350 0.0559 -0.0177 -0.0598
--0.0215 -0.0318 -0.0689 -0.0268 0.0917 0.0307 0.0135 -0.0184 -0.0857 0.1231
-0.0137 -0.0152 0.0199 -0.0291 -0.0685 0.0438 -0.1137 0.0231 -0.0632 -0.0802
--0.0011 0.0314 0.0535 -0.0135 -0.0291 -0.0579 -0.1049 0.0288 -0.0628 0.1355
--0.0901 0.0041 -0.0170 0.0351 0.0144 -0.0505 0.0396 0.0638 -0.0145 0.0141
--0.0400 -0.0603 -0.0714 0.0329 -0.0049 -0.0529 -0.1251 0.0022 -0.0449 -0.0778
-0.0247 0.0296 0.0239 0.0122 -0.0348 -0.1224 -0.0033 0.1237 -0.0016 -0.0436
-0.0246 0.0050 0.0322 0.0818 0.0203 0.0846 0.0022 0.0876 0.0149 -0.0184
--0.0204 -0.0228 0.0365 -0.0164 0.1087 0.0374 -0.0550 0.0330 -0.0582 -0.0736
--0.0305 -0.0485 -0.0572 0.0275 -0.0271 -0.0436 0.1217 0.0700 0.1253 0.0990
--0.0079 -0.0204 -0.0325 0.0491 0.0158 -0.0365 -0.1309 -0.1812 0.1428 0.1148
-0.0680 0.0547 0.0309 0.0079 -0.0332 0.0391 -0.0287 0.1258 0.1123 0.1016
--0.0264 -0.0409 -0.0538 -0.0192 -0.0393 -0.0713 -0.0618 -0.1078 -0.1850 0.0532
-0.0081 -0.0115 -0.0090 0.1201 -0.0413 -0.0995 0.0445 -0.0032 -0.0286 -0.0497
--0.0023 -0.0184 -0.0358 0.1279 0.0847 0.0530 0.0230 -0.0212 0.1245 0.0965
-0.0111 0.1038 0.0597 0.0413 0.0533 0.0011 0.0031 0.0705 0.0242 0.0198
-0.0020 -0.0071 -0.0262 -0.0496 -0.0750 -0.1273 -0.1785 0.0606 -0.0223 -0.0583
--0.0202 0.0669 0.0081 0.0335 -0.0218 -0.1073 -0.0146 -0.0673 0.0490 0.0210
--0.0108 -0.0230 -0.0614 -0.0986 0.0629 0.0006 0.1496 0.1099 0.0316 0.0098
--0.0368 -0.0685 0.0138 -0.0213 -0.0009 0.0344 -0.0249 0.0311 0.0803 0.0759
-0.0038 -0.0158 0.0142 0.0254 0.0970 0.0021 -0.1029 0.0006 0.0576 0.0261
--0.0083 0.0698 0.0406 -0.0348 0.0200 0.0833 0.0186 -0.0145 -0.0725 -0.0872
--0.0506 -0.0673 0.0776 -0.0172 -0.0444 -0.0531 -0.0799 0.0005 -0.0359 -0.0446
-0.0368 0.0376 -0.0407 -0.0190 0.0987 0.0212 -0.0349 -0.0951 -0.0084 -0.0342
--0.0309 -0.0561 0.0950 -0.0125 -0.1028 -0.0133 0.0920 0.0965 0.0668 0.0409
--0.0898 0.0036 -0.0353 -0.0024 -0.0365 -0.0259 -0.0485 -0.0843 -0.0063 -0.0167
--0.0255 -0.0407 -0.0456 -0.0931 -0.0892 -0.0293 -0.0510 0.0183 -0.0104 0.0472
--0.0172 -0.0399 -0.0731 0.0546 0.0320 -0.0283 0.0415 -0.0107 -0.1237 -0.1102
-0.0210 0.0294 -0.0038 -0.0090 -0.0551 -0.0922 0.0261 -0.0334 -0.1181 -0.1536
-0.0092 0.0032 -0.0162 0.0398 0.0205 0.1266 -0.0107 -0.0858 0.0392 0.0032
--0.0038 -0.0269 -0.0737 0.1138 0.0263 -0.0031 -0.1188 0.1621 0.0831 0.0526
-0.0023 -0.0149 -0.0497 0.0898 0.0456 -0.0145 -0.0928 -0.1507 -0.0611 -0.0938
-0.0120 0.0124 -0.0286 -0.1319 0.0219 0.0311 -0.0398 -0.0465 -0.0008 -0.0375
-0.0138 0.0023 0.0024 0.1072 0.0531 0.0006 0.0292 -0.0115 -0.0620 0.1650
-0.0070 -0.0251 0.0715 0.0380 -0.0404 0.1230 0.0629 0.0096 0.0973 0.0641
--0.0586 0.0772 0.0128 0.1060 0.0715 0.0374 -0.0074 -0.0365 -0.0543 -0.0489
--0.0392 0.0871 -0.0069 -0.1084 0.0264 -0.0495 0.0396 0.0005 -0.0293 -0.0240
--0.0327 0.0605 0.0662 0.0100 -0.0007 -0.0525 -0.0812 -0.0686 -0.0873 -0.0830
-0.0119 0.0058 0.0030 -0.0307 0.0650 0.0175 -0.0741 -0.1500 -0.1947 0.0881
-0.0572 0.0411 0.0152 -0.0127 -0.0589 -0.0510 -0.0212 -0.0834 0.1434 0.1318
-0.0518 0.0417 -0.0430 0.0963 -0.0014 0.0173 0.0234 -0.0273 0.0359 -0.0118
-0.0652 0.0587 0.0013 -0.0700 0.1262 0.0975 0.0680 0.0598 0.0048 -0.0305
--0.0185 -0.0440 0.1178 0.0656 0.0052 -0.0534 -0.1151 0.1116 0.0659 0.0344
-0.0788 0.0577 0.0452 0.0283 -0.0278 0.0911 0.0280 -0.0254 0.0029 -0.0361
--0.0165 -0.0322 -0.0526 -0.1057 0.0927 0.0293 -0.1026 -0.1671 0.0470 0.0355
-0.0100 0.0001 -0.0221 -0.0775 -0.1109 -0.1416 0.0884 0.0441 0.0632 0.0409
-0.0204 0.0432 0.0141 -0.0296 0.1073 0.0580 0.0383 0.0270 -0.0857 0.1246
-0.0488 0.0231 0.0648 -0.0179 0.0747 0.0156 -0.0384 -0.0733 -0.0732 -0.0970
-0.0005 -0.0199 -0.0260 -0.0511 -0.1110 0.0670 -0.0413 0.1571 0.0498 0.0191
-0.0037 -0.0085 -0.0796 0.0086 -0.0852 0.0850 0.0115 -0.0065 0.1161 0.0727
-0.0023 0.0483 0.0285 -0.0642 -0.0477 0.0175 0.0346 0.0452 0.0655 0.0284
--0.0986 0.0463 0.0326 -0.0055 0.0702 0.0194 -0.0423 -0.0107 0.0338 0.0619
-0.0126 -0.0138 -0.1115 0.0159 -0.0331 0.0217 -0.0376 -0.0407 -0.0222 -0.0503
-0.0222 0.0071 -0.0490 0.1017 0.0551 -0.0164 0.1578 0.1059 0.0025 -0.0107
-0.0124 -0.0090 0.0322 0.0930 0.0281 -0.0403 -0.0781 0.0125 -0.0670 -0.1058
-0.0363 0.0077 0.1052 0.0039 0.0676 0.0891 0.0433 0.0252 0.0224 -0.0043
--0.0045 -0.0194 -0.0193 -0.0480 -0.0640 -0.0695 -0.1597 -0.0030 0.1728 0.1231
-0.0297 0.0025 0.0619 -0.0347 -0.1171 0.1043 0.0868 0.0191 -0.0739 -0.1075
-0.0073 0.0914 0.0367 -0.0236 0.0232 0.0304 -0.0787 -0.1099 0.0460 0.0082
-0.0296 0.0297 -0.0444 0.0184 0.0602 -0.0295 -0.0934 0.0636 -0.0347 -0.0722
--0.0290 -0.0629 0.0598 0.0013 0.0064 0.1431 0.0920 0.0468 -0.0311 -0.0614
--0.0152 -0.0311 -0.0500 -0.0672 -0.1257 -0.0134 -0.0220 -0.0612 -0.1131 -0.1417
-0.0371 0.0153 -0.0817 -0.0007 0.0837 0.0481 0.0460 0.0678 0.0524 0.0432
-0.0126 -0.0069 -0.0092 -0.0693 -0.0250 0.1510 0.0098 -0.0683 -0.0566 -0.0769
--0.0199 -0.0423 0.0806 0.0562 0.0009 -0.0563 -0.1358 -0.1578 -0.0456 0.0032
-0.0091 0.0101 -0.0090 -0.0279 -0.0489 -0.1038 -0.0815 0.2184 0.1172 0.0902
--0.0024 -0.0135 0.0392 0.0028 0.0792 0.0404 0.0867 0.1610 0.0954 0.0846
--0.0004 -0.0220 -0.0282 -0.1022 -0.0799 0.1278 0.0765 0.0402 0.0850 0.0611
-0.0443 0.0320 -0.0384 -0.0964 0.0030 -0.0398 -0.0730 -0.0052 -0.0267 0.1209
--0.0706 0.1151 0.0722 -0.0175 -0.0927 -0.0559 0.0316 0.0186 0.0105 0.0314
--0.0145 -0.0263 -0.0564 0.0248 -0.0181 -0.0817 -0.0938 0.0366 -0.0315 0.1253
-0.0307 0.0039 0.1290 0.0402 -0.0439 -0.0384 0.0044 -0.0177 -0.0172 -0.0310
-0.0447 0.0298 0.0287 0.0273 -0.0350 -0.0708 -0.1829 -0.0317 0.0643 0.0057
--0.0820 -0.0326 0.0209 -0.0711 0.0084 0.0111 0.0426 0.0262 -0.0061 0.0005
-0.0545 0.0377 -0.0417 -0.0625 0.0114 -0.0405 0.0573 0.0191 -0.0263 -0.0472
--0.0053 -0.0049 -0.0255 -0.0578 -0.0237 -0.0721 -0.1487 -0.1636 0.0046 -0.0355
-0.0309 0.0107 0.0163 0.0132 -0.0536 -0.0009 -0.0706 -0.1350 -0.0514 -0.0960
-0.0306 0.0003 0.0494 0.0701 0.0027 -0.0458 0.0780 0.0327 0.0937 0.0605
--0.0017 -0.0275 0.0797 -0.0268 -0.1014 0.0593 -0.0528 -0.1103 0.0682 0.0322
--0.0507 -0.0806 -0.0646 -0.0052 -0.0576 0.0451 0.0489 0.0150 0.0029 -0.0189
-0.0270 0.0143 -0.0375 -0.0071 -0.0607 -0.1157 -0.0345 -0.1115 0.0201 -0.0104
--0.0807 -0.1088 0.0845 0.0720 0.0441 0.0301 0.0043 0.0052 0.0016 0.0201
--0.0290 -0.0532 0.0036 -0.0201 -0.0723 -0.1321 0.0867 0.0479 -0.0556 -0.0850
--0.0271 0.0126 0.1283 0.0533 -0.0030 -0.0352 -0.0326 -0.0553 0.1402 0.1121
--0.0358 -0.0518 -0.1080 0.0134 0.0950 0.0384 -0.0040 -0.0254 0.0026 -0.0217
--0.0152 -0.0375 -0.0827 0.0916 0.0188 0.1306 0.0983 0.0606 0.0381 0.0080
--0.0107 -0.0269 -0.0573 -0.1189 0.0258 0.1009 0.0565 0.0270 -0.0557 -0.0778
--0.0193 -0.0242 -0.0784 -0.0816 0.0287 -0.0484 0.0292 -0.0414 0.1124 0.0767
-0.0177 -0.0148 0.0472 -0.0808 0.0623 -0.0636 0.0750 -0.0107 0.0673 0.0425
--0.0220 0.0577 -0.0769 -0.0247 -0.0321 0.0341 -0.0108 0.0109 -0.0142 0.0122
-0.0194 0.0248 -0.0096 -0.0205 -0.0460 -0.1160 0.0492 -0.0188 -0.1535 0.0816
-0.0301 -0.0286 -0.0077 -0.0117 -0.0036 -0.0026 0.0133 -0.0032 0.0007 -0.0160
-0.0115 -0.0111 0.0246 -0.0639 0.0325 -0.0313 0.0808 0.0435 -0.0777 -0.1108
--0.0079 -0.0334 -0.0144 -0.0539 0.1564 0.1175 0.0549 0.0340 0.0319 0.0027
--0.0155 -0.0275 -0.0739 -0.0932 0.0108 -0.0698 0.0036 -0.0213 -0.0486 -0.0670
--0.0234 -0.0567 0.0020 0.0908 -0.0151 0.0460 -0.0175 -0.0523 0.0098 -0.0237
-0.0057 -0.0066 -0.0418 0.0418 -0.0449 0.1069 0.0629 -0.0016 -0.1068 -0.1492
--0.0791 0.0403 -0.0009 0.0285 -0.0065 0.0963 0.0550 0.0634 0.0693 0.0694
--0.0068 -0.0197 -0.0919 0.0071 -0.0551 -0.1173 0.0926 0.0413 0.0127 -0.0158
-0.0540 0.0389 -0.0195 -0.0800 -0.1383 0.0440 -0.0139 -0.0405 0.0147 -0.0183
-0.0380 0.0248 0.0520 -0.0609 0.0339 -0.0070 -0.0974 0.1182 0.0221 -0.0310
-0.0043 0.0046 -0.0274 -0.0502 0.0326 -0.0143 -0.0586 -0.0866 -0.1673 -0.1624
-0.0428 0.0385 -0.0228 0.0704 0.0069 -0.0145 -0.0623 -0.0639 -0.1479 0.0212
--0.0078 -0.0297 0.0025 -0.0239 -0.0793 0.0896 0.0315 -0.0546 -0.1309 0.1080
+++ /dev/null
-10 64
--0.0291 0.0272 -0.0364 -0.0313 -0.0487 -0.0205 0.0501 0.0225 0.0178 0.0080
--0.0406 -0.0383 0.0013 -0.0155 -0.0261 -0.0598 0.0003 -0.0242 0.0151 -0.0140
--0.0445 0.0356 0.0180 -0.0272 -0.0018 -0.0177 -0.0703 0.0471 0.0128 -0.0068
--0.0033 -0.0285 -0.0560 -0.0186 -0.0499 -0.0070 0.0068 -0.0126 0.0388 -0.0097
--0.0071 -0.0114 -0.0308 -0.0094 -0.0541 -0.0272 -0.0756 0.0477 -0.0234 0.0678
-0.0048 0.0307 -0.0174 -0.0593 0.0097 -0.0134 0.0034 -0.0212 -0.0418 0.0869
--0.0189 0.0165 -0.0269 0.0744 0.0344 -0.0177 -0.0603 0.0212 -0.0104 0.0345
--0.0130 -0.0352 -0.0086 -0.0257 -0.0286 0.0409 0.0656 0.0106 -0.0598 0.0252
-0.0041 0.0097 -0.0032 -0.0154 -0.0405 0.0670 -0.0164 0.0451 0.0774 0.0504
-0.0010 -0.0091 -0.0345 0.0511 0.0016 0.0011 0.0684 0.0167 0.0601 0.0512
-0.0204 -0.0038 -0.0426 0.0185 -0.0191 -0.0630 0.0295 -0.0153 -0.0559 0.0560
--0.0461 -0.0041 0.0515 0.0219 0.0322 0.0093 0.0044 0.0106 -0.0329 -0.0521
-0.0304 0.0017 0.0209 -0.0002 0.0689 0.0136 0.0216 -0.0268 -0.0682 0.0333
--0.0175 -0.0425 0.0153 -0.0050 -0.0113 0.0297 -0.0659 -0.0344 0.0302 -0.0272
--0.0217 -0.0362 0.0426 0.0233 -0.0393 0.0052 0.0138 0.0657 0.0427 0.0220
--0.0039 -0.0011 -0.0002 -0.0453 -0.0835 0.0144 -0.0268 -0.0589 -0.0185 0.0133
-0.0081 -0.0032 0.0638 0.0032 0.0060 0.0002 -0.0303 -0.0823 0.0124 -0.0308
-0.0108 0.0011 0.0059 0.0396 0.0392 0.0351 -0.0045 -0.0323 -0.0512 -0.0975
--0.0144 -0.0306 -0.0302 -0.0070 0.0123 -0.0042 -0.0083 -0.0514 0.0120 0.1116
--0.0046 -0.0131 0.0472 0.0144 -0.0296 -0.0518 0.0337 -0.0145 -0.0733 0.0793
--0.0064 -0.0162 -0.0327 -0.0711 0.0108 -0.0131 0.0025 -0.0254 -0.0277 -0.0680
--0.0306 0.0055 0.0272 -0.0189 -0.0173 0.0221 0.0773 0.0043 0.0458 -0.0169
--0.0006 0.0299 0.0259 0.0227 -0.0530 -0.0596 -0.0271 -0.0091 0.0181 -0.0233
--0.0116 -0.0398 0.0089 0.0708 -0.0028 -0.0084 -0.0206 -0.0354 -0.0275 -0.0037
-0.0259 -0.0064 -0.0380 0.0572 0.0083 0.0286 -0.0565 0.0158 0.0396 -0.0123
-0.0552 0.0331 -0.0052 -0.0346 -0.0180 -0.0194 -0.0237 0.0184 0.0056 -0.0199
-0.0143 0.0131 -0.0166 0.0196 0.0154 0.0310 -0.0048 0.0901 -0.0333 0.0761
-0.0118 -0.0107 0.0099 0.0078 0.0002 -0.0716 -0.0233 0.0793 0.0516 0.0300
-0.0204 0.0243 0.0192 0.0181 0.0001 -0.0243 -0.0764 -0.0622 -0.0324 0.0640
-0.0132 0.0016 -0.0187 -0.0425 0.0627 0.0094 -0.0786 0.0304 0.0294 -0.0146
--0.0221 -0.0154 0.0285 -0.0709 0.0406 0.0114 0.0073 -0.0199 0.0081 0.0268
-0.0227 0.0055 0.0163 -0.0447 0.0246 0.0795 0.0239 0.0211 -0.0145 -0.0576
--0.0119 0.0637 0.0278 0.0202 -0.0086 0.0389 0.0320 -0.0049 -0.0272 -0.0274
-0.0040 -0.0211 0.0426 0.0480 0.0415 0.0659 0.0408 0.0198 0.0327 0.0029
-0.0430 0.0311 0.0083 0.0353 0.0250 0.0143 0.0106 -0.0305 0.0633 0.0227
--0.0277 0.0302 0.0337 0.0176 0.0191 -0.0156 0.0231 0.0118 0.0465 0.0875
-0.0221 0.0146 0.0147 -0.0211 -0.0317 -0.0179 -0.0049 -0.0297 -0.1078 -0.0413
--0.0531 0.0180 -0.0066 0.0365 -0.0033 0.0090 -0.0158 -0.0698 0.0315 -0.0048
-0.0289 0.0053 0.0082 0.0077 -0.0664 0.0474 0.0407 -0.0096 0.0028 -0.0526
--0.0106 -0.0129 -0.0315 0.0335 -0.0217 -0.0427 0.0582 0.0193 -0.0288 -0.0777
--0.0003 -0.0141 -0.0102 0.0007 -0.0077 -0.0517 -0.0909 0.0128 -0.0349 -0.0769
--0.0227 -0.0159 -0.0327 0.0011 0.0312 0.0100 -0.0180 -0.0537 -0.0997 0.0122
-0.0190 -0.0139 0.0341 -0.0131 -0.0368 -0.0138 -0.0074 -0.0415 0.0791 0.0503
-0.0182 0.0027 0.0032 -0.0325 -0.0309 -0.0898 0.0509 -0.0170 0.0301 -0.0137
-0.0233 0.0100 0.0231 0.0730 0.0212 -0.0299 0.0440 0.0041 -0.0101 -0.0251
-0.0074 -0.0033 -0.0285 -0.0350 0.0101 0.0735 0.0036 -0.0659 0.0429 -0.0052
-0.0148 -0.0035 -0.0233 0.0079 -0.0142 -0.0402 -0.0358 -0.0985 -0.0080 -0.0549
-0.0203 0.0057 -0.0604 0.0098 0.0402 0.0151 0.0500 0.0058 -0.0086 -0.0401
-0.0056 -0.0381 0.0420 -0.0125 0.0157 -0.0268 0.0433 0.0123 -0.0176 -0.0685
-0.0030 0.0502 0.0067 -0.0222 0.0405 -0.0226 0.0020 -0.0401 -0.0026 -0.0521
-0.0317 0.0089 0.0620 0.0251 0.0066 0.0089 -0.0565 0.0414 0.0005 -0.0365
--0.0058 0.0086 -0.0291 -0.0164 -0.0134 -0.0490 -0.0427 -0.0451 0.0869 0.0334
-0.0024 0.0328 -0.0415 0.0003 -0.0287 0.0193 -0.0547 -0.0222 -0.0196 -0.0571
--0.0271 -0.0397 -0.0431 -0.0043 0.0332 0.0093 0.0082 0.0585 0.0282 0.0004
--0.0251 -0.0167 -0.0289 0.0196 -0.0363 0.0850 0.0028 0.0319 -0.0202 -0.0512
-0.0389 0.0226 0.0401 -0.0091 -0.0152 0.0001 0.0738 0.0402 0.0097 0.0310
--0.0126 0.0130 -0.0046 -0.0216 0.0298 -0.0344 0.0713 0.0547 -0.0470 -0.0294
-0.0125 0.0044 -0.0028 0.0209 -0.0200 0.0854 0.0018 -0.0386 -0.0703 0.0778
--0.0036 -0.0347 0.0309 -0.0184 0.0290 -0.0025 -0.0644 0.0347 -0.0523 0.0644
-0.0064 0.0295 -0.0017 0.0282 0.0176 0.0027 0.0246 0.0967 0.0401 -0.0231
-0.0054 -0.0109 0.0055 -0.0479 -0.0490 -0.0136 -0.0245 0.0839 0.0026 -0.0493
-0.0128 -0.0050 -0.0219 -0.0621 0.0313 0.0019 0.0696 0.0459 0.0574 0.0299
--0.0091 -0.0290 -0.0068 0.0276 0.0645 -0.0150 0.0015 -0.0374 0.0415 -0.0124
--0.0171 0.0177 -0.0138 0.0034 0.0840 0.0584 0.0233 0.0100 0.0122 0.0047
+++ /dev/null
-10 64
-0.0221 -0.0035 -0.0032 -0.0177 -0.0327 0.0518 -0.0110 -0.0150 -0.0136 -0.0327
-0.0099 -0.0059 0.0031 -0.0174 0.0464 -0.0240 0.0251 -0.0270 0.0454 -0.0082
--0.0029 0.0025 -0.0267 -0.0318 -0.0157 0.0173 0.0253 0.0063 -0.0481 0.0419
--0.0332 -0.0179 -0.0042 0.0241 0.0044 -0.0098 -0.0081 0.0024 -0.0414 0.0339
--0.0060 0.0182 -0.0051 -0.0479 0.0016 -0.0179 0.0316 0.0222 -0.0029 -0.0351
-0.0074 0.0015 0.0337 -0.0082 -0.0008 0.0129 0.0001 0.0650 0.0175 0.0309
--0.0212 -0.0261 0.0196 -0.0309 0.0093 -0.0272 0.0260 0.0169 0.0132 0.0116
--0.0010 0.0202 0.0228 -0.0227 -0.0141 0.0192 -0.0423 -0.0097 -0.0342 0.0338
--0.0149 -0.0110 -0.0156 0.0290 0.0028 0.0123 -0.0350 -0.0501 0.0272 -0.0245
--0.0005 -0.0194 0.0460 -0.0001 -0.0280 0.0216 -0.0028 -0.0162 0.0177 -0.0254
--0.0109 -0.0026 0.0038 -0.0150 -0.0421 -0.0422 0.0164 -0.0436 0.0054 -0.0098
-0.0061 -0.0106 0.0062 0.0207 -0.0329 0.0177 -0.0578 0.0408 0.0077 -0.0260
-0.0001 -0.0098 0.0106 -0.0003 -0.0292 0.0032 0.0560 0.0311 -0.0282 -0.0445
-0.0033 0.0345 -0.0022 -0.0029 -0.0228 0.0242 0.0197 -0.0286 0.0194 -0.0328
-0.0094 -0.0010 0.0121 0.0229 0.0161 0.0363 -0.0124 0.0179 -0.0626 0.0020
--0.0070 -0.0272 -0.0171 -0.0249 -0.0039 0.0254 0.0317 -0.0324 0.0276 -0.0090
--0.0002 0.0057 -0.0204 0.0512 -0.0170 0.0113 0.0157 0.0427 -0.0024 0.0162
--0.0064 -0.0144 0.0216 0.0053 -0.0361 0.0287 0.0230 -0.0161 -0.0189 0.0589
-0.0091 -0.0059 -0.0308 0.0171 -0.0137 -0.0033 -0.0505 -0.0155 -0.0527 0.0133
--0.0121 -0.0051 0.0219 0.0136 0.0476 -0.0090 -0.0460 0.0208 0.0072 -0.0076
-0.0098 -0.0328 -0.0211 0.0054 -0.0146 -0.0263 0.0248 0.0045 -0.0183 0.0301
-0.0101 0.0139 -0.0073 0.0234 0.0083 -0.0194 -0.0365 0.0307 0.0580 0.0153
--0.0111 0.0019 0.0265 -0.0150 0.0311 0.0362 0.0244 -0.0213 -0.0224 -0.0299
-0.0061 0.0082 -0.0181 0.0081 -0.0344 0.0133 -0.0095 -0.0411 0.0462 0.0371
-0.0089 -0.0157 0.0179 -0.0256 -0.0118 -0.0302 -0.0329 0.0212 -0.0463 -0.0162
--0.0313 0.0096 -0.0040 0.0186 0.0248 -0.0126 0.0472 -0.0079 0.0115 -0.0270
-0.0055 0.0044 0.0172 0.0079 -0.0089 -0.0202 -0.0233 -0.0397 -0.0305 -0.0620
--0.0282 -0.0104 -0.0071 -0.0242 -0.0255 0.0204 -0.0187 -0.0103 -0.0227 -0.0424
--0.0056 0.0065 0.0151 -0.0376 0.0039 0.0009 -0.0507 -0.0040 0.0393 -0.0201
-0.0128 -0.0228 0.0115 -0.0446 0.0316 0.0266 -0.0036 0.0117 -0.0009 0.0048
--0.0088 0.0226 0.0125 0.0090 0.0008 -0.0341 0.0243 -0.0178 -0.0589 0.0278
-0.0151 0.0021 -0.0349 -0.0365 -0.0098 -0.0179 -0.0212 -0.0313 0.0109 -0.0164
--0.0211 -0.0112 -0.0446 0.0014 -0.0034 -0.0179 0.0110 0.0176 0.0286 0.0045
-0.0034 -0.0151 0.0380 0.0331 -0.0034 -0.0439 0.0145 0.0120 0.0036 0.0017
--0.0348 0.0192 0.0167 0.0069 -0.0266 -0.0085 -0.0076 0.0260 0.0234 0.0075
--0.0237 0.0150 -0.0094 -0.0201 0.0234 -0.0041 -0.0160 -0.0549 -0.0021 0.0239
--0.0019 0.0173 0.0295 0.0443 0.0081 0.0181 -0.0039 -0.0270 0.0155 0.0107
-0.0065 -0.0055 -0.0368 0.0232 0.0370 0.0367 0.0046 -0.0167 0.0047 0.0173
-0.0116 0.0053 -0.0229 0.0382 0.0160 -0.0453 0.0057 -0.0267 0.0020 -0.0051
--0.0140 0.0302 -0.0208 0.0106 0.0101 -0.0049 -0.0319 0.0227 -0.0206 -0.0371
--0.0007 -0.0109 -0.0053 0.0078 0.0410 -0.0001 0.0543 0.0328 -0.0196 0.0332
--0.0043 -0.0028 -0.0246 0.0285 -0.0248 0.0153 0.0303 -0.0310 -0.0335 -0.0315
--0.0417 0.1029 0.0377 0.0069 0.0012 0.0065 0.0007 -0.0144 -0.0083 0.0004
-0.0295 0.0099 -0.0144 -0.0145 0.0141 -0.0013 0.0362 -0.0142 -0.0428 -0.0161
--0.0095 -0.0206 0.0116 0.0132 0.0164 0.0158 0.0012 -0.0024 0.0640 0.0364
-0.0005 -0.0022 -0.0165 -0.0057 0.0263 0.0339 0.0014 0.0541 0.0164 -0.0411
-0.0039 -0.0143 -0.0107 0.0032 -0.0160 -0.0502 0.0010 0.0272 0.0161 -0.0500
-0.0083 0.0292 -0.0076 -0.0201 0.0313 0.0213 0.0120 0.0087 0.0285 0.0332
-0.0170 0.0018 0.0001 0.0205 0.0106 -0.0064 -0.0082 -0.0083 -0.0082 0.0886
-0.0075 -0.0078 -0.0038 -0.0337 -0.0491 0.0048 0.0069 0.0300 0.0369 0.0088
--0.0091 -0.0327 0.0041 0.0376 0.0170 0.0154 0.0126 0.0153 -0.0024 -0.0353
-0.0289 -0.0080 0.0063 0.0274 -0.0061 0.0208 0.0390 -0.0060 0.0294 -0.0088
--0.0037 -0.0195 0.0058 0.0023 -0.0149 -0.0360 -0.0587 -0.0248 0.0288 0.0203
--0.0031 0.0081 -0.0112 -0.0221 0.0067 -0.0505 -0.0233 0.0353 -0.0131 0.0417
-0.0243 0.0231 -0.0013 0.0049 -0.0423 -0.0245 -0.0029 0.0184 -0.0162 -0.0010
-0.0045 0.0101 -0.0042 0.0014 -0.0133 -0.0321 0.0642 0.0153 0.0377 0.0277
-0.0275 0.0083 0.0286 -0.0243 -0.0084 -0.0236 0.0027 -0.0289 0.0201 0.0235
-0.0281 0.0078 0.0038 0.0069 0.0302 0.0170 -0.0423 -0.0340 0.0104 -0.0181
-0.0334 -0.0034 -0.0257 -0.0061 0.0140 -0.0099 -0.0195 0.0529 0.0019 0.0010
--0.0114 0.0012 -0.0038 -0.0016 -0.0140 0.0697 0.0372 0.0243 0.0172 0.0066
-0.0192 0.0149 0.0285 0.0077 0.0246 -0.0135 0.0145 0.0317 -0.0074 -0.0438
--0.0034 -0.0175 -0.0245 -0.0153 0.0357 -0.0102 -0.0062 -0.0053 -0.0308 -0.0499
-0.0025 -0.0253 0.0148 0.0031 0.0189 -0.0023 -0.0085 -0.0596 -0.0337 0.0175
--0.0091 -0.0171 -0.0217 -0.0189 0.0056 0.0249 -0.0499 0.0236 0.0042 0.0449
+++ /dev/null
-10 2048
-0.408892 0.649827 0.954657 1.095560 1.374775 1.695544 2.186975 2.404129 2.599671 2.716599
-0.206312 0.393044 0.534358 0.831490 0.964061 1.315881 1.711009 1.884982 2.656064 2.789476
-0.294007 0.430921 0.584720 0.972610 1.346504 1.446720 1.672880 1.854151 2.292980 2.574467
-0.130573 0.192259 0.568997 1.014611 1.204902 1.371336 1.696595 2.109828 2.488139 2.749404
-0.119174 0.172048 0.555350 1.041664 1.294588 1.603976 1.924941 2.215881 2.537337 2.763865
-0.264060 0.351222 0.551394 0.836209 0.955359 1.467373 1.883071 2.011362 2.370015 2.500936
-0.206715 0.433527 0.682328 0.833734 1.164725 1.476463 1.775427 2.152234 2.639949 2.796348
-0.211225 0.320307 0.437323 0.659797 1.492016 1.699378 1.859517 2.131810 2.328455 2.499706
-0.480644 0.630950 0.822352 1.123960 1.461020 1.594792 1.889414 2.166284 2.404039 2.536132
-0.233285 0.324869 0.445867 0.683777 0.826101 0.975483 1.764219 2.154061 2.334729 2.602314
-0.315909 0.537121 0.711160 0.941341 1.178015 1.302627 1.643751 2.058463 2.464410 2.591263
-0.245173 0.382524 0.532006 0.708503 1.236528 1.448436 1.777993 2.124256 2.306038 2.625603
-0.245615 0.291619 0.819764 1.444781 1.578166 1.731349 2.095787 2.242522 2.603987 2.720052
-0.173862 0.229815 0.418896 0.695378 0.931595 1.188532 1.820958 2.120767 2.330289 2.464753
-0.303527 0.372419 0.740620 1.167964 1.327370 1.494681 1.784226 1.898711 2.311465 2.642713
-0.259744 0.401730 0.575188 0.834348 1.431968 1.604358 1.798482 2.185462 2.402074 2.554969
-0.337109 0.570466 1.175085 1.451610 1.761333 1.975735 2.126135 2.293190 2.536691 2.706431
-0.367145 0.452099 0.647409 0.817255 0.902956 1.238037 1.825344 1.922997 2.436059 2.609846
-0.378662 0.531818 0.674407 0.919671 1.409610 1.559852 1.771428 2.027114 2.253246 2.408198
-0.163411 0.267202 0.378752 0.982090 1.260325 1.393847 1.801359 1.943528 2.730199 2.854737
-0.315416 0.366274 0.657622 1.193970 1.448486 1.554740 1.791291 1.913099 2.285878 2.665674
-0.182284 0.250810 0.478825 0.774649 1.250927 1.657871 1.857476 1.999098 2.286088 2.777030
-0.280912 0.330939 0.631688 0.754025 0.941971 1.616999 1.814228 2.013341 2.634148 2.720386
-0.197110 0.280354 0.442898 0.794104 1.537225 1.674591 1.953914 2.155343 2.626079 2.817453
-0.324055 0.494234 0.849184 1.111214 1.388737 1.737885 1.975967 2.381772 2.611796 2.753205
-0.249643 0.364552 0.527912 0.900747 1.026842 1.398842 1.869778 2.015830 2.450740 2.598903
-0.210241 0.311192 0.495868 0.687507 1.152048 1.296946 1.520174 2.255285 2.440410 2.686456
-0.159037 0.244226 0.385934 0.687847 1.072342 1.386804 1.785080 1.924100 2.533529 2.669124
-0.234363 0.441050 0.678179 0.862648 1.224287 1.720752 1.949118 2.386935 2.642309 2.768447
-0.177323 0.256095 0.417949 0.816232 1.042933 1.254927 1.618581 1.928664 2.118610 2.463463
-0.247362 0.335496 0.753623 1.051947 1.239658 1.426773 1.621176 2.053494 2.480950 2.615165
-0.156480 0.216035 0.368476 0.588087 1.238670 1.459124 1.827783 1.975080 2.316953 2.770680
-0.198050 0.342316 0.883251 1.421788 1.645484 1.905948 2.140263 2.301866 2.620508 2.774812
-0.257995 0.358680 0.537441 0.694512 0.824406 1.362975 1.764952 1.925331 2.486171 2.617074
-0.252496 0.330798 0.493815 0.973920 1.306189 1.439735 1.920226 2.087274 2.257323 2.398019
-0.165073 0.249466 0.371194 1.033936 1.278111 1.449107 2.046790 2.168316 2.497102 2.729474
-0.351523 0.566840 0.885298 1.113196 1.285310 1.425799 1.728030 2.101425 2.514797 2.765585
-0.247070 0.331460 0.517797 1.035640 1.189321 1.389341 1.740344 1.976250 2.202072 2.430856
-0.250272 0.471488 0.632229 0.874364 1.003062 1.214226 1.782201 1.915722 2.618775 2.804373
-0.178042 0.247938 0.413307 0.724804 1.348933 1.537515 2.114127 2.301885 2.636884 2.826241
-0.321648 0.521672 0.933498 1.194774 1.582506 1.752098 1.962687 2.185410 2.511609 2.710750
-0.189405 0.281558 0.405270 0.624133 0.831682 0.979077 1.773124 2.022636 2.231772 2.709233
-0.338988 0.556585 0.722942 0.903725 1.137734 1.260460 1.698745 2.141650 2.342421 2.527244
-0.283960 0.422437 0.547151 0.805702 1.347223 1.507695 1.702228 2.041553 2.221081 2.575186
-0.116988 0.373808 0.677058 1.246354 1.579914 1.860096 2.174202 2.426485 2.666464 2.778514
-0.172660 0.279061 0.420803 0.776647 1.027097 1.182553 1.880931 2.023781 2.400028 2.816622
-0.244703 0.354981 0.775126 1.007264 1.208883 1.571339 1.920167 2.128560 2.418384 2.673311
-0.277862 0.345899 0.491009 1.000182 1.668493 1.893737 2.024216 2.203943 2.418550 2.555188
-0.200787 0.681282 1.126094 1.309507 1.738042 2.023257 2.342799 2.463428 2.602179 2.702804
-0.223979 0.466963 0.728850 0.888776 1.090618 1.234456 1.705574 2.241550 2.510834 2.751795
-0.264860 0.389642 0.536973 0.871669 1.323290 1.441181 1.682582 1.973355 2.163007 2.401176
-0.254211 0.390772 0.549594 0.748576 1.280532 1.474290 1.636048 2.013508 2.479875 2.650004
-0.191314 0.280703 0.420214 1.117728 1.347340 1.558388 1.722577 2.094362 2.606691 2.753977
-0.152313 0.198389 0.337122 0.490241 1.023739 1.222176 1.581978 1.852165 2.361974 2.553970
-0.343523 0.473063 0.661058 0.896926 1.009881 1.426789 2.003978 2.115197 2.358072 2.676757
-0.225495 0.299263 0.443642 0.793508 1.407173 1.798104 2.159374 2.284811 2.501925 2.644715
-0.220837 0.608771 0.967248 1.237940 1.450245 1.693405 2.002186 2.239767 2.534945 2.707207
-0.290250 0.359912 0.599268 0.771394 0.922184 1.257421 2.137963 2.330228 2.526054 2.700371
-0.269144 0.463439 0.625052 0.842594 1.239627 1.353331 1.687365 2.092062 2.284863 2.634475
-0.170231 0.237346 0.408666 0.698347 1.146923 1.313417 1.753705 1.891356 2.401344 2.558038
-0.171963 0.247483 0.388808 0.980638 1.502962 1.644121 1.955137 2.148787 2.393447 2.630021
-0.209519 0.325681 0.464669 0.682705 1.111676 1.225834 1.824262 2.151181 2.384320 2.739424
-0.210672 0.533806 0.825201 0.990473 1.145813 1.393566 1.999486 2.222956 2.524156 2.776040
-0.261962 0.340226 0.472952 0.863674 1.443518 1.829669 1.994398 2.132878 2.355090 2.469655
-0.340277 0.460050 0.748860 1.054174 1.614903 1.804636 1.993799 2.247318 2.473443 2.602200
-0.239159 0.394343 0.578732 0.754990 0.941899 1.128161 1.620559 2.020968 2.585087 2.783718
-0.269667 0.342100 0.485464 1.053892 1.413864 1.534461 1.740671 1.909701 2.286779 2.538869
-0.076962 0.097269 0.408343 0.942043 1.237899 1.573872 1.883029 2.186618 2.520305 2.790522
-0.170175 0.223705 0.651279 1.003661 1.370350 1.628746 1.941629 2.172624 2.450895 2.649955
-0.219608 0.300784 0.472750 0.871097 1.064995 1.283347 1.869030 2.047338 2.234764 2.423176
-0.283455 0.337982 0.663326 0.792275 0.925513 1.457560 1.740494 1.857127 2.583274 2.700391
-0.199190 0.263142 0.443787 0.684379 1.185091 1.879212 2.080132 2.224038 2.427704 2.576557
-0.219374 0.680594 0.965335 1.102093 1.296977 1.590756 2.074636 2.334754 2.586458 2.754939
-0.198099 0.308630 0.432817 0.619556 0.754862 0.931998 1.549410 1.846704 2.294094 2.636366
-0.338876 0.446352 0.640399 0.996449 1.224095 1.344627 1.695974 1.883015 2.104946 2.489100
-0.166453 0.240154 0.399798 0.829295 1.305386 1.443374 1.723531 1.880577 2.379309 2.500316
-0.244810 0.287547 0.565833 1.376218 1.610718 1.731021 2.128375 2.264382 2.552460 2.697921
-0.203376 0.353110 0.454768 0.707277 0.892936 1.038801 1.609843 1.809379 2.065993 2.304645
-0.392222 0.453261 0.813874 1.205541 1.320471 1.599816 1.858220 2.029353 2.491522 2.638332
-0.269519 0.326891 0.470180 1.053385 1.538230 1.686468 1.865876 2.081763 2.229408 2.441901
-0.463250 0.707535 1.093317 1.316217 1.598936 1.783637 1.982618 2.134436 2.396915 2.574501
-0.234043 0.348930 0.473804 0.709797 1.030257 1.152835 1.749074 2.178802 2.334442 2.638112
-0.356771 0.553522 0.702444 0.911763 1.372687 1.512426 1.716079 1.969296 2.175300 2.356841
-0.215283 0.314571 0.448084 0.938241 1.488615 1.610559 1.858891 2.014800 2.487515 2.656114
-0.255059 0.324128 0.591637 1.140724 1.280033 1.626440 1.845765 2.008493 2.607807 2.732065
-0.190953 0.284283 0.446537 0.903721 1.083755 1.521604 1.865214 2.039362 2.398102 2.603527
-0.218632 0.323425 0.485128 0.801138 0.934826 1.550687 1.950327 2.141484 2.437725 2.588421
-0.240697 0.351397 0.469534 0.775124 1.406794 1.725183 1.871364 2.156495 2.381976 2.555115
-0.355558 0.461716 0.684575 1.091512 1.719266 1.926216 2.051391 2.237427 2.507442 2.610706
-0.160350 0.190000 0.366405 0.494497 0.868240 1.345426 1.566707 2.068702 2.335099 2.641913
-0.219362 0.326275 0.619951 0.801217 1.176182 1.324616 1.567767 1.852718 2.393752 2.544625
-0.242295 0.361032 0.536827 0.699045 1.264826 1.578333 1.777090 2.115510 2.587465 2.731970
-0.185629 0.225499 0.394464 1.072663 1.725553 1.814897 2.037215 2.318703 2.570456 2.700776
-0.199282 0.271847 0.427336 0.691175 0.936688 1.307560 1.755173 1.941991 2.180527 2.289541
-0.440652 0.657600 0.846249 1.115177 1.383954 1.526095 1.839294 2.054337 2.261747 2.486134
-0.254743 0.370981 0.519721 0.892661 1.365537 1.512546 1.867709 2.025821 2.338400 2.608154
-0.374541 0.564001 1.042547 1.268517 1.427251 1.737400 2.240345 2.527386 2.748712 2.871518
-0.163240 0.229374 0.631209 0.821347 1.079198 1.312352 1.847665 2.085082 2.462129 2.646514
-0.257702 0.368235 0.785115 0.964453 1.130321 1.417415 1.830826 2.058137 2.393471 2.589613
-0.195822 0.280922 0.414972 0.646213 1.237085 1.398279 1.830678 2.337509 2.561924 2.750149
-0.302754 0.361163 0.751614 0.974525 1.131739 1.643605 1.825553 2.044086 2.641030 2.739994
-0.235437 0.315967 0.652539 0.816752 1.083366 1.622892 1.852217 2.030423 2.192530 2.575813
-0.291611 0.410807 0.602501 0.962264 1.083617 1.420033 1.771443 1.907873 2.445734 2.652716
-0.189868 0.257547 0.397682 0.669228 1.309264 1.797630 1.994844 2.138696 2.608657 2.757821
-0.479797 0.701925 0.989967 1.226383 1.556286 1.735962 2.055139 2.286164 2.529859 2.666528
-0.215045 0.313827 0.431033 0.651895 0.829909 1.000831 1.815727 2.226013 2.392474 2.760351
-0.306301 0.398661 0.653631 1.025764 1.189362 1.401036 1.898166 2.051914 2.236996 2.422421
-0.167970 0.224219 0.368107 0.623431 1.201568 1.381682 1.762247 1.920037 2.113047 2.522470
-0.185718 0.243656 0.376917 1.209258 1.581544 1.690223 2.033223 2.376102 2.591085 2.756869
-0.147871 0.206576 0.362439 0.637580 0.940549 1.343574 1.621941 1.733152 1.946250 2.723886
-0.324080 0.457905 0.793499 1.005600 1.260387 1.583156 1.886643 2.096396 2.372896 2.578810
-0.226219 0.308328 0.636626 0.866278 1.534446 1.701010 1.887737 2.161067 2.358914 2.503200
-0.606744 0.955507 1.338156 1.567438 1.821726 2.055362 2.279753 2.416922 2.604378 2.699013
-0.246984 0.386718 0.502785 0.760434 1.042124 1.263722 1.435097 2.414889 2.724612 2.819326
-0.292410 0.502940 0.672216 0.892183 1.209496 1.339252 1.760220 1.968766 2.362511 2.623487
-0.143375 0.199091 0.483698 0.992064 1.214869 1.614010 1.832079 1.978488 2.281935 2.713930
-0.266561 0.304298 0.533705 1.305138 1.580937 1.665891 1.884884 2.014163 2.228380 2.568778
-0.178658 0.231896 0.383912 0.540251 1.225283 1.458102 1.922772 2.083421 2.250593 2.408925
-0.289292 0.350422 0.695339 0.839824 1.012699 1.582703 1.751493 2.110402 2.491079 2.602625
-0.191978 0.275525 0.396619 0.582467 1.263497 1.658220 1.987982 2.164226 2.491219 2.655634
-0.271271 0.427594 0.784469 1.094218 1.535344 1.895921 2.111855 2.328610 2.716413 2.835820
-0.197072 0.315577 0.461034 0.771499 0.895098 1.249097 1.937811 2.117715 2.428590 2.608183
-0.211338 0.407351 0.538840 0.766827 1.152593 1.246498 1.679320 1.905728 2.120349 2.677619
-0.135615 0.163159 0.283783 0.431117 0.953107 1.462377 1.809595 2.130270 2.442565 2.743798
-0.166707 0.238759 0.367497 0.902142 1.508106 1.650293 1.825543 1.979014 2.655324 2.825020
-0.349277 0.540928 0.693205 0.826151 1.104738 1.259800 1.507300 2.094618 2.320842 2.523635
-0.325055 0.432779 0.621749 1.070682 1.304776 1.457668 1.900591 2.027150 2.460400 2.683254
-0.232534 0.355259 0.543295 0.744519 1.329342 1.648497 1.789282 2.116619 2.343387 2.501568
-0.465485 0.876578 1.205981 1.371947 1.745534 1.938156 2.176847 2.328487 2.521049 2.656868
-0.246604 0.364927 0.536848 0.850639 1.033582 1.224962 1.555694 1.725857 2.343766 2.568854
-0.345140 0.476535 0.650548 0.994609 1.167264 1.343813 1.779614 1.923453 2.324548 2.609157
-0.140607 0.199293 0.674213 0.958553 1.263430 1.520789 1.808626 2.055790 2.415260 2.705252
-0.125913 0.381885 0.618365 0.994294 1.317324 1.547930 1.818095 2.158588 2.494214 2.751068
-0.214195 0.320569 0.719851 0.846412 1.134388 1.428969 1.611410 2.041914 2.282243 2.508041
-0.250098 0.404670 0.540333 0.911835 1.060249 1.279821 1.619963 1.771663 2.496606 2.697909
-0.163090 0.213459 0.360500 0.504711 1.040089 1.576896 1.979044 2.125480 2.339164 2.609713
-0.356943 0.533785 0.924836 1.108094 1.324907 1.563986 2.016874 2.233505 2.510859 2.677439
-0.226046 0.346550 0.669965 0.775492 0.992753 1.149356 1.460794 2.260130 2.505825 2.717261
-0.322304 0.403181 0.776459 0.964458 1.099992 1.312705 1.399455 1.890224 2.369477 2.448458
-0.181583 0.245567 0.398747 0.597666 1.249798 1.421203 1.606076 2.062186 2.473743 2.644347
-0.254588 0.326744 1.005093 1.262125 1.386127 1.779710 1.955644 2.320802 2.571383 2.678189
-0.216441 0.331207 0.529500 0.654360 0.976477 1.361296 1.647430 2.064996 2.284304 2.569981
-0.327013 0.391820 0.720865 1.097162 1.210384 1.510465 1.765619 1.895802 2.508466 2.678337
-0.252152 0.343407 0.663772 1.085064 1.474659 1.659743 1.910625 2.070943 2.565518 2.717751
-0.349806 0.488123 1.077976 1.292638 1.515886 1.846355 2.084915 2.406884 2.610810 2.736561
-0.182819 0.308233 0.418992 0.708488 0.808059 1.045333 1.698019 1.837574 2.442304 2.609622
-0.277323 0.408804 0.571028 0.828924 1.404815 1.598729 1.759862 1.985935 2.333424 2.455915
-0.229839 0.342341 0.470342 1.002275 1.285925 1.399377 1.816619 1.930907 2.470705 2.802064
-0.244913 0.299585 0.779774 1.322881 1.429162 1.587382 1.738489 2.162786 2.520459 2.623668
-0.161891 0.228443 0.419656 0.733282 0.922895 1.405447 1.884393 2.078046 2.269896 2.589494
-0.270447 0.452251 0.634105 0.780705 0.965021 1.351395 1.825782 2.214939 2.632158 2.796098
-0.171118 0.234980 0.395507 0.838430 1.544455 1.699044 2.124182 2.287668 2.660613 2.849673
-0.213781 0.293496 0.663454 0.993393 1.412625 1.646492 2.074110 2.290676 2.508346 2.653511
-0.199402 0.316802 0.426338 0.630931 0.735249 1.132121 1.883614 2.046046 2.416976 2.580155
-0.210048 0.294088 0.590707 0.762351 1.146848 1.352924 1.637070 2.017207 2.305862 2.432462
-0.154676 0.232848 0.373861 0.948260 1.342786 1.514201 1.755766 1.926693 2.555124 2.717005
-0.137148 0.221322 0.381753 0.919373 1.152152 1.376375 1.826205 2.189540 2.648671 2.813516
-0.245209 0.338241 0.486220 0.814091 0.944966 1.134755 1.358289 1.523556 2.149645 2.315495
-0.392124 0.549332 0.727700 0.905451 1.202400 1.375569 1.534258 1.840057 2.422734 2.556400
-0.148684 0.204787 0.552934 0.803123 1.372462 1.550381 1.754747 2.118492 2.372977 2.711653
-0.267280 0.397322 0.846103 1.172950 1.465464 1.857475 2.153775 2.381172 2.591304 2.723190
-0.194992 0.314743 0.526878 0.796319 1.177375 1.299335 1.525584 1.682646 2.452032 2.795741
-0.301179 0.371796 0.577128 1.081605 1.303060 1.419674 1.898891 2.054902 2.252552 2.600649
-0.252900 0.355818 0.549064 0.965795 1.162628 1.585047 1.928827 2.119789 2.498842 2.665173
-0.256762 0.436508 0.715681 1.130116 1.316991 1.587569 1.850331 2.197839 2.605877 2.796521
-0.235855 0.314907 0.609574 0.859658 1.266780 1.499482 1.790537 1.910982 2.039772 2.187359
-0.200486 0.336241 0.495825 0.891310 1.133452 1.285295 1.612858 1.828238 2.394734 2.809663
-0.179969 0.232629 0.363081 0.500578 1.184534 1.700401 2.059216 2.168101 2.610554 2.836451
-0.348768 0.492321 1.055246 1.314914 1.471270 1.645210 1.876419 2.100446 2.525029 2.694314
-0.171135 0.273412 0.378187 0.581850 0.726115 0.908194 1.708076 1.905747 2.542437 2.797354
-0.315194 0.475887 0.658397 0.849734 1.017156 1.173887 1.755577 2.042149 2.216786 2.521016
-0.229599 0.378223 0.495710 0.879870 1.173185 1.276381 1.777400 1.935276 2.173970 2.748099
-0.197210 0.253422 0.651252 1.311542 1.636493 1.706783 2.105431 2.346619 2.641613 2.771729
-0.232136 0.443332 0.579669 0.760076 0.955242 1.094270 1.726616 1.914262 2.122649 2.700118
-0.186271 0.267327 0.840223 1.116294 1.440220 1.650886 1.944246 2.192076 2.483403 2.643816
-0.268607 0.318357 0.512736 1.129834 1.613930 1.740081 1.917514 2.123735 2.299945 2.557182
-0.479249 0.689878 1.088007 1.470716 1.716709 1.922473 2.158730 2.305877 2.511790 2.656073
-0.307991 0.431011 0.578118 0.877244 1.205302 1.312688 1.629259 2.238238 2.462001 2.580776
-0.293918 0.452236 0.659902 0.921329 1.309254 1.422508 1.668206 2.064588 2.322038 2.461436
-0.131440 0.209617 0.702675 1.016897 1.223185 1.385724 1.670724 1.961691 2.376852 2.732092
-0.193489 0.279816 0.428516 1.256267 1.395720 1.633455 1.873432 2.214886 2.671449 2.786280
-0.182323 0.240522 0.451705 0.799605 1.223096 1.445970 1.647433 1.971485 2.217583 2.336581
-0.384106 0.488198 0.644947 0.897630 1.047334 1.468272 1.839224 1.937923 2.262459 2.408476
-0.260306 0.326571 0.615384 1.084790 1.376745 1.778446 1.998233 2.171540 2.424597 2.575747
-0.340699 0.545965 0.865284 1.131340 1.458730 1.711046 2.089316 2.336073 2.684077 2.841771
-0.290674 0.372204 0.609647 0.779269 0.906420 1.332695 1.973245 2.155443 2.354880 2.655993
-0.308041 0.460783 0.632808 0.911363 1.081813 1.231896 1.747306 1.927967 2.170864 2.605727
-0.180523 0.263276 0.388872 0.565969 0.970599 1.149292 1.871610 2.207290 2.458204 2.667791
-0.143978 0.222658 0.400384 1.086970 1.323702 1.528106 1.995792 2.231147 2.688186 2.836361
-0.209150 0.326190 0.485707 0.681360 1.195456 1.385054 1.544410 2.045718 2.276514 2.434761
-0.297725 0.399777 0.588061 0.894914 1.022395 1.243834 2.009751 2.182970 2.413135 2.638027
-0.228593 0.289986 0.631198 0.791618 1.403101 1.777890 1.926222 2.136335 2.313587 2.489963
-0.343174 0.500760 1.039265 1.351369 1.721522 1.925940 2.190967 2.354142 2.532626 2.657845
-0.149735 0.297295 0.440372 0.642471 0.732234 1.200738 1.414606 1.770276 2.778155 2.883980
-0.223698 0.281114 0.635545 1.061406 1.252740 1.613423 1.836402 1.963828 2.140470 2.593562
-0.168168 0.232950 0.408892 0.653722 1.031457 1.548556 1.766449 2.230830 2.626126 2.797381
-0.222326 0.345655 0.786775 1.107909 1.305189 1.588197 1.993469 2.213238 2.511325 2.685326
-0.224020 0.317494 0.598436 0.845315 1.197927 1.319317 1.767399 2.160174 2.338471 2.525570
-0.198682 0.295026 0.450891 0.867753 0.988755 1.401296 1.687600 1.894339 2.559558 2.696080
-0.206679 0.295846 0.477897 0.699492 1.273871 1.789097 1.959682 2.171515 2.399523 2.555694
-0.353705 0.509579 0.861689 1.094569 1.427975 1.625819 1.845189 2.034662 2.339261 2.562173
-0.176626 0.248928 0.429179 0.658231 0.856663 1.071207 1.601595 1.968639 2.470776 2.718292
-0.314175 0.392578 0.678288 0.944677 1.081793 1.304708 1.492952 1.733627 2.167258 2.307337
-0.202661 0.269438 0.509570 0.817339 1.376869 1.513847 1.874609 2.094859 2.323847 2.480180
-0.234414 0.278975 0.540035 1.347889 1.582923 1.720967 1.986105 2.114372 2.567473 2.703603
-0.146798 0.210418 0.385776 0.649932 0.920041 1.248588 1.573579 1.711404 2.232087 2.791487
-0.382058 0.469618 0.713606 1.069660 1.176016 1.497437 1.813598 1.950404 2.598859 2.726089
-0.334215 0.396922 0.687976 1.087820 1.575500 1.754574 1.906641 2.123504 2.311875 2.443046
-0.264352 0.802524 1.285656 1.486584 1.714037 1.865311 2.035536 2.281585 2.562390 2.750718
-0.270580 0.372011 0.562949 0.825388 0.994299 1.169245 1.870741 2.135215 2.301336 2.518290
-0.449329 0.649113 0.811339 0.973882 1.234030 1.349977 1.692316 1.971266 2.154687 2.357538
-0.180117 0.263580 0.408830 1.127021 1.317638 1.497965 1.895425 2.031294 2.672116 2.818667
-0.331179 0.404977 0.766611 1.259419 1.431059 1.581972 1.939935 2.087575 2.416872 2.639616
-0.194102 0.279875 0.549239 0.704386 1.177109 1.529852 1.691669 2.044312 2.359273 2.560290
-0.217844 0.305871 0.442547 0.616270 0.791798 1.713038 1.956014 2.134547 2.520649 2.795859
-0.162088 0.245953 0.365670 0.638902 1.457619 1.641568 1.838031 2.013303 2.320106 2.729780
-0.236749 0.306797 0.734177 1.072402 1.551912 1.853315 2.104151 2.256363 2.475312 2.617668
-0.176733 0.238829 0.485876 0.687779 0.927283 1.403874 1.830537 2.195431 2.429970 2.626018
-0.268020 0.478288 0.731817 0.871173 1.083963 1.253101 1.535103 2.185826 2.455996 2.622463
-0.166174 0.232448 0.362076 0.591660 1.356885 1.632572 1.826301 1.987791 2.467764 2.659140
-0.236315 0.287802 0.548409 0.987167 1.721933 1.836472 2.152486 2.384523 2.592315 2.741028
-0.148319 0.185444 0.292576 0.511994 0.653403 1.371832 1.527681 1.776139 2.182163 2.227991
-0.401535 0.564293 0.893142 1.022987 1.156707 1.327441 1.701821 1.993285 2.370534 2.578619
-0.165638 0.255975 0.370284 0.802811 1.426084 1.572731 1.787459 1.915582 2.413753 2.802844
-0.317083 0.519809 0.936968 1.293236 1.686332 1.984336 2.186929 2.353187 2.746765 2.860986
-0.189287 0.380990 0.546039 0.784587 1.003621 1.162395 1.874419 2.057907 2.555748 2.785834
-0.200570 0.284860 0.609927 0.826229 1.198949 1.436548 1.809361 2.033038 2.401620 2.587587
-0.168913 0.291597 0.445205 0.722025 1.163607 1.283554 1.763882 1.943265 2.445617 2.817539
-0.360050 0.443567 0.853632 0.987093 1.191562 1.562912 1.869792 2.232417 2.543480 2.645225
-0.231905 0.297890 0.611365 0.830346 1.094545 1.582087 1.848979 2.056068 2.241982 2.394253
-0.331013 0.427540 0.641785 0.946294 1.070136 1.373613 1.859665 1.965907 2.332441 2.584977
-0.186393 0.242540 0.372099 0.728034 1.467825 1.880137 2.042177 2.272992 2.633925 2.779591
-0.446483 0.648214 0.993351 1.205829 1.476224 1.661697 1.899206 2.087562 2.408776 2.592556
-0.208614 0.297946 0.427983 0.600065 0.709456 1.284278 2.044367 2.179822 2.682450 2.818833
-0.306024 0.468602 0.638450 0.827416 1.302277 1.427429 1.811154 2.176106 2.372543 2.496738
-0.152872 0.217872 0.355627 0.713701 1.075149 1.446741 1.848785 1.978762 2.159635 2.712916
-0.234973 0.319771 0.478090 1.080036 1.447440 1.571699 1.982304 2.127281 2.559717 2.736762
-0.162524 0.250245 0.389070 0.646952 0.872934 1.222022 1.856534 2.002922 2.205745 2.599505
-0.323202 0.432855 0.814249 1.180773 1.335093 1.521419 1.901656 2.092343 2.350187 2.560064
-0.273240 0.329948 0.562890 1.003483 1.538259 1.875392 2.025443 2.170349 2.380148 2.499017
-0.500444 0.796365 1.318632 1.529307 1.785448 1.972761 2.147764 2.310849 2.519566 2.650408
-0.263728 0.375983 0.556014 0.707339 1.188811 1.339543 1.652143 2.209513 2.616263 2.738796
-0.266858 0.438409 0.640135 0.862517 1.340556 1.500100 1.686339 2.153946 2.448590 2.598137
-0.190447 0.295300 0.432651 0.884499 1.072087 1.256294 1.823661 1.957091 2.345386 2.577329
-0.243926 0.297921 0.524525 1.251205 1.478145 1.594774 1.967380 2.076378 2.370787 2.732472
-0.167306 0.212866 0.358147 0.499128 0.984267 1.284647 1.814420 2.033044 2.314127 2.439818
-0.254879 0.320323 0.682137 0.944750 1.083508 1.662985 2.084039 2.246726 2.582054 2.713386
-0.212215 0.297268 0.418087 0.743693 1.609250 1.923321 2.079152 2.242169 2.464816 2.591376
-0.117901 0.208978 0.750040 1.145517 1.437720 1.744291 2.143051 2.439937 2.749809 2.873675
-0.193258 0.299329 0.443516 0.797326 0.939062 1.148247 2.018657 2.143420 2.638335 2.829836
-0.213782 0.353502 0.481322 0.711845 1.170764 1.302711 1.535835 1.703291 2.279212 2.748103
-0.115171 0.144705 0.242103 0.453456 1.202245 1.525989 1.893854 2.179999 2.517564 2.798073
-0.238570 0.307781 0.447781 0.957056 1.599743 1.771585 1.940690 2.245051 2.435372 2.633593
-0.194447 0.266589 0.445674 0.635231 0.910266 1.074602 1.340239 1.919744 2.377594 2.630265
-0.297496 0.544047 0.851256 1.025765 1.203569 1.446499 1.981579 2.194582 2.414346 2.605178
-0.203460 0.275006 0.515591 0.732576 1.407979 1.561138 1.760709 2.030957 2.312387 2.431093
-0.498532 0.697751 1.045964 1.328280 1.488249 1.717432 2.051335 2.268465 2.588202 2.722759
-0.194097 0.345960 0.482722 0.874859 1.052521 1.250837 1.534492 1.720853 2.636782 2.816708
-0.266101 0.394737 0.545547 0.974166 1.278319 1.387120 1.790143 1.967144 2.177889 2.702878
-0.102867 0.171081 0.576060 0.818748 1.189242 1.510470 1.778003 2.103994 2.520545 2.748259
-0.119052 0.208027 0.744711 1.011939 1.289820 1.547449 1.904002 2.157777 2.533138 2.773751
-0.210113 0.291141 0.487281 0.790277 0.954605 1.401661 1.701442 1.897619 2.210404 2.382596
-0.266446 0.411500 0.593156 0.920817 1.042570 1.321476 1.890868 2.015685 2.574753 2.734992
-0.195053 0.286814 0.458352 0.639707 1.284634 1.645299 1.800882 2.168396 2.390218 2.562172
-0.341567 0.526183 0.892818 1.084248 1.334447 1.590215 1.889298 2.135833 2.519801 2.745352
-0.323599 0.420247 0.572363 0.757221 0.889572 1.036953 1.623345 2.196313 2.409765 2.540575
-0.410364 0.592459 0.763563 0.927955 1.176077 1.308890 1.569276 2.059039 2.380497 2.499273
-0.194371 0.276796 0.581419 0.722859 1.264729 1.505348 1.711903 2.189092 2.444234 2.629075
-0.252525 0.297192 0.844332 1.381854 1.514803 1.693308 1.854404 2.129548 2.591287 2.684159
-0.170004 0.214112 0.394084 0.539179 0.822416 1.250980 1.752323 2.086240 2.289006 2.448613
-0.289267 0.343412 0.775795 1.191573 1.303367 1.539691 1.782253 1.905366 2.579603 2.729614
-0.234791 0.321602 0.704594 0.949738 1.420244 1.594285 1.774127 2.194285 2.467211 2.589613
-0.340968 0.561082 1.199771 1.415378 1.689161 1.838640 2.014730 2.162685 2.430697 2.592350
-0.345276 0.499518 0.706277 0.861164 0.999501 1.150174 1.572106 1.964424 2.390120 2.588870
-0.357406 0.496053 0.646703 0.939578 1.460352 1.676567 1.834109 2.014842 2.385901 2.507758
-0.176473 0.238482 0.404112 0.892358 1.136652 1.536592 1.716827 1.872719 2.552209 2.759174
-0.222384 0.324129 0.833161 1.246603 1.460920 1.650632 1.876566 2.087675 2.354362 2.547825
-0.167777 0.229073 0.433058 0.810575 1.128669 1.556495 1.799821 1.915429 2.106489 2.677788
-0.306967 0.371498 0.623689 0.749815 0.934500 1.649015 1.792619 2.190421 2.536272 2.643777
-0.148383 0.236235 0.322878 0.555588 1.594153 1.725789 1.992119 2.178572 2.540447 2.774265
-0.377895 0.546230 0.852056 1.067292 1.455797 1.652672 2.018925 2.238220 2.468715 2.644735
-0.300062 0.399164 0.567524 0.740898 0.849393 1.425476 1.948578 2.050102 2.416440 2.546289
-0.218019 0.356752 0.584786 0.769374 1.165925 1.291779 1.688308 2.175240 2.369045 2.711417
-0.143884 0.210234 0.342148 0.566261 1.198668 1.437368 1.683504 1.842729 2.638129 2.833574
-0.115081 0.173169 0.584021 1.134381 1.407360 1.689153 2.034286 2.294650 2.638147 2.814312
-0.190721 0.252429 0.584147 0.836602 1.015264 1.254879 1.571659 2.007112 2.245095 2.426652
-0.309544 0.480824 0.812592 1.075038 1.325338 1.457449 1.679174 1.976619 2.381620 2.705381
-0.164599 0.274956 0.399399 0.735839 1.360979 1.482765 1.859273 2.011226 2.288457 2.792980
-0.187333 0.353999 1.222795 1.502985 1.770143 1.982262 2.203271 2.378492 2.606563 2.729390
-0.158025 0.248611 0.551584 0.735140 0.915073 1.281500 1.744031 1.922872 2.435679 2.716805
-0.273434 0.367213 0.642574 1.050887 1.345202 1.494431 1.909997 2.107095 2.336366 2.534901
-0.264699 0.416517 0.576907 0.947351 1.178990 1.385352 1.951926 2.132530 2.549979 2.786944
-0.142221 0.546287 0.805410 1.079219 1.288179 1.492189 1.774180 2.114597 2.427330 2.681890
-0.230540 0.326500 0.461675 0.964559 1.255458 1.369392 1.856593 2.039532 2.207278 2.539486
-0.137659 0.377399 0.593860 0.793016 1.115754 1.281644 1.840901 1.971659 2.472814 2.713504
-0.144356 0.222505 0.346683 0.782224 1.201084 1.371745 2.123343 2.366887 2.623919 2.803847
-0.362575 0.509680 1.001234 1.230119 1.473004 1.608864 1.802561 2.021551 2.326705 2.519219
-0.240803 0.361576 0.516660 0.727416 0.914394 1.051113 1.716835 2.160538 2.328331 2.706675
-0.351054 0.517992 0.725905 0.915622 1.055525 1.339295 1.898183 2.100270 2.307558 2.559254
-0.200168 0.322989 0.505425 0.676330 1.190121 1.354931 1.731948 1.999324 2.249015 2.624332
-0.219896 0.269490 0.521875 1.237665 1.710417 1.793651 2.115240 2.279260 2.536737 2.689478
-0.215336 0.396644 0.543160 0.728604 1.109190 1.229364 1.727973 1.963312 2.325039 2.797789
-0.264892 0.352500 0.883446 1.155268 1.338153 1.628498 1.841805 2.014230 2.264319 2.462976
-0.239779 0.301722 0.529044 1.147546 1.636525 1.760760 1.966137 2.262281 2.456574 2.621762
-0.320203 0.679639 1.229787 1.529834 1.826892 2.060858 2.286789 2.422168 2.716167 2.843881
-0.353658 0.547800 0.796651 0.899078 1.041245 1.321838 1.822982 2.161422 2.619096 2.820678
-0.261908 0.345021 0.472318 0.918792 1.423161 1.564348 1.733377 2.067856 2.262877 2.396698
-0.124156 0.193894 0.636158 0.840841 1.110258 1.289251 1.683161 1.869014 2.398865 2.731114
-0.165710 0.239716 0.465502 1.228637 1.420469 1.692829 1.888377 2.147997 2.486300 2.699831
-0.160684 0.209986 0.367031 0.503201 1.015826 1.200739 1.524190 2.011867 2.222744 2.475835
-0.277916 0.405640 0.619792 0.770716 1.136524 1.426314 1.822220 2.135166 2.485194 2.647977
-0.231394 0.352162 0.469144 0.682116 1.481669 1.842849 2.029794 2.179907 2.469833 2.589806
-0.380604 0.561972 0.896403 1.133414 1.391582 1.626403 1.961716 2.211112 2.588392 2.787673
-0.322688 0.406580 0.586076 0.731518 0.852667 1.152831 1.995073 2.295481 2.441596 2.617794
-0.197630 0.400738 0.603098 0.838719 1.177968 1.302320 1.559507 1.871355 2.200186 2.796317
-0.159189 0.198711 0.364347 0.509370 1.127246 1.399692 1.623432 2.046094 2.279806 2.705935
-0.233578 0.298035 0.460794 1.139533 1.415576 1.616317 2.117648 2.254774 2.452874 2.595232
-0.177717 0.242239 0.394824 0.650020 0.987501 1.104089 1.611392 2.177724 2.393809 2.694514
-0.299562 0.409957 0.723642 1.062891 1.216972 1.411830 2.051394 2.240860 2.503777 2.709591
-0.201879 0.287289 0.406508 0.659566 1.400321 1.792888 1.936179 2.099785 2.279253 2.454742
-0.359188 0.531719 0.904543 1.142371 1.572219 1.782800 2.067174 2.342915 2.583586 2.731217
-0.245193 0.363406 0.508075 0.721046 0.817318 1.141324 1.787709 1.937075 2.532146 2.678676
-0.280203 0.342294 0.579285 1.021875 1.451807 1.612518 1.803002 2.013050 2.189908 2.367656
-0.124640 0.167543 0.484641 0.896195 1.324263 1.701101 1.908392 2.091365 2.427391 2.766624
-0.152261 0.248563 0.705878 1.026619 1.492524 1.688058 2.019960 2.241100 2.465374 2.733867
-0.169524 0.275607 0.440772 0.719798 1.121602 1.261028 1.809404 2.005583 2.240287 2.716912
-0.329978 0.420004 0.718053 0.936318 1.070988 1.489233 1.858025 1.988096 2.520192 2.667419
-0.229078 0.298586 0.511977 0.723831 1.144803 1.763599 2.164905 2.282990 2.512775 2.671092
-0.456055 0.680179 0.929388 1.076639 1.233955 1.484650 1.903702 2.126601 2.527098 2.727819
-0.168979 0.211126 0.352636 0.486868 0.828354 1.056116 1.439894 2.019355 2.482102 2.794744
-0.388525 0.560294 0.717429 0.985928 1.184401 1.320169 1.814889 2.045192 2.224054 2.519281
-0.207864 0.278390 0.577744 0.755061 1.180647 1.365438 1.765814 1.933058 2.355569 2.495779
-0.273703 0.316766 0.687833 1.373372 1.573215 1.679562 2.017370 2.150752 2.443206 2.666143
-0.139043 0.179618 0.315633 0.517664 0.768733 1.079636 1.390644 1.825048 2.101118 2.739679
-0.443325 0.508374 0.821570 1.141790 1.252203 1.580452 1.827461 1.983767 2.580866 2.715534
-0.272418 0.343583 0.526010 1.076654 1.474251 1.582828 1.851400 2.162984 2.327319 2.521128
-0.372015 0.542684 0.990447 1.414552 1.716538 1.844518 2.067134 2.276470 2.459989 2.623009
-0.296347 0.473546 0.629389 0.879809 1.022187 1.210411 1.881605 2.064735 2.306350 2.615239
-0.421613 0.570707 0.726241 1.011174 1.451250 1.595500 1.814127 2.086968 2.350981 2.485098
-0.138010 0.208811 0.371352 1.058801 1.360740 1.563789 1.835310 2.106508 2.488086 2.685686
-0.304388 0.366691 0.637332 1.163418 1.322554 1.489449 1.820316 1.937237 2.490676 2.695981
-0.160998 0.233003 0.393385 0.742550 1.040177 1.581795 1.846434 2.020562 2.454386 2.656034
-0.293730 0.353143 0.554522 0.676232 0.826408 1.581608 2.144029 2.268817 2.602846 2.715369
-0.174487 0.251975 0.375041 0.584283 1.427390 1.560251 1.883505 2.266902 2.453791 2.739291
-0.236065 0.282833 0.692209 1.097292 1.694874 1.966224 2.123394 2.280655 2.544753 2.658369
-0.129365 0.165960 0.285820 0.488714 0.981342 1.175696 1.724506 2.087889 2.501287 2.735548
-0.226211 0.351015 0.619709 0.857773 1.132574 1.308463 1.487032 1.965719 2.504712 2.670516
-0.203957 0.285955 0.462644 0.620843 1.230135 1.668195 1.835692 2.036399 2.639041 2.775792
-0.159885 0.225639 0.351326 0.882800 1.592195 1.709989 2.060725 2.305297 2.531165 2.753869
-0.182663 0.255048 0.437572 0.758568 0.996367 1.382381 1.651134 1.839516 2.008732 2.215961
-0.418150 0.556126 0.728385 1.007878 1.270088 1.366376 1.715316 2.066928 2.257578 2.389769
-0.207212 0.291325 0.416536 0.913294 1.492822 1.637098 1.825777 1.978284 2.214137 2.552111
-0.241341 0.427255 0.990332 1.209018 1.403013 1.731713 2.115958 2.363302 2.608966 2.742739
-0.188611 0.290583 0.686340 0.839849 1.094731 1.279717 1.560751 2.134527 2.353362 2.641874
-0.303141 0.383534 0.612718 0.971405 1.141894 1.558084 1.937162 2.069641 2.316813 2.480680
-0.179032 0.247590 0.375840 0.575450 1.367486 1.543422 2.101856 2.277817 2.513453 2.724165
-0.279200 0.350633 0.674006 1.015821 1.154154 1.656796 1.871235 2.061172 2.539189 2.655336
-0.220829 0.293262 0.666921 0.930888 1.307454 1.585242 1.798660 1.919831 2.100904 2.490486
-0.407626 0.528205 0.695580 0.942289 1.068323 1.248001 1.834686 1.955840 2.367277 2.684681
-0.187917 0.238836 0.392030 0.586354 1.220852 1.713253 2.205448 2.317138 2.607952 2.772751
-0.406035 0.678205 1.009915 1.169891 1.361883 1.567949 1.969141 2.218271 2.484866 2.653946
-0.263469 0.379446 0.574642 0.739690 0.891674 1.015764 1.634497 2.310050 2.531555 2.722555
-0.276896 0.353172 0.495976 0.992936 1.248222 1.349871 1.691833 2.151044 2.363150 2.534333
-0.165915 0.220580 0.380706 0.597420 1.137653 1.320387 1.576770 1.939725 2.122544 2.647358
-0.215129 0.283229 0.414568 1.356845 1.527108 1.679575 1.891014 2.130176 2.602350 2.741207
-0.206573 0.274549 0.539970 0.803271 1.064961 1.486193 1.704709 1.828604 1.978928 2.462439
-0.245410 0.534217 0.840240 1.054925 1.298942 1.439072 1.805223 2.039652 2.261595 2.482457
-0.236976 0.308980 0.585923 0.783026 1.498617 1.930204 2.097800 2.251258 2.476303 2.596959
-0.571463 1.021016 1.359450 1.510990 1.761279 1.913272 2.106845 2.286831 2.543023 2.660054
-0.187494 0.265400 0.418588 0.927645 1.377800 1.582098 1.740975 2.237651 2.615481 2.802350
-0.308598 0.491606 0.632564 0.923419 1.411973 1.578570 1.730433 1.976996 2.433166 2.558710
-0.147715 0.217707 0.377800 0.910933 1.185758 1.366725 1.612211 2.013767 2.403550 2.696412
-0.255983 0.321186 0.503024 1.109229 1.544228 1.645679 1.931499 2.060262 2.490962 2.677649
-0.175450 0.230655 0.407361 0.720246 1.062295 1.330697 1.797198 2.019193 2.315150 2.443569
-0.223790 0.338008 0.719854 0.950722 1.144176 1.597163 1.855352 2.263747 2.561723 2.704014
-0.192133 0.289847 0.398779 0.556338 1.501770 1.755759 1.934139 2.206912 2.388353 2.645486
-0.297639 0.450015 0.788874 1.101418 1.627516 1.880937 2.155204 2.413078 2.599468 2.743886
-0.217417 0.333895 0.462399 0.822556 1.071185 1.203256 1.990668 2.195575 2.436009 2.784665
-0.163563 0.239093 0.376533 0.839654 1.058152 1.266142 1.728781 1.907170 2.096879 2.659086
-0.137806 0.181530 0.328192 0.516935 1.031832 1.525160 1.768896 1.915914 2.359545 2.727805
-0.164104 0.236815 0.332559 0.910079 1.609754 1.696913 2.000392 2.161661 2.560691 2.703739
-0.228917 0.407594 0.638844 0.801544 1.054407 1.197528 1.396765 1.854050 2.203784 2.611161
-0.391989 0.486610 0.771960 1.116329 1.248980 1.474917 1.949979 2.088145 2.481910 2.691692
-0.279187 0.400947 0.576848 0.718895 1.254179 1.650864 1.823958 1.934813 2.498090 2.611019
-0.458469 0.714872 1.061410 1.262159 1.583256 1.935302 2.258053 2.430476 2.654284 2.756814
-0.222188 0.326247 0.447894 0.840363 1.072654 1.191396 1.417342 1.567507 2.404790 2.696868
-0.346704 0.402748 0.714703 1.139511 1.315770 1.444510 1.797498 1.920454 2.155272 2.559128
-0.155723 0.214701 0.494437 0.875267 1.172389 1.405229 1.797171 2.092950 2.373162 2.664794
-0.143642 0.390291 0.851279 1.039361 1.187534 1.415631 1.895439 2.190895 2.617165 2.792304
-0.266078 0.370570 0.662415 0.836415 0.988458 1.316618 1.567592 1.858948 2.257531 2.426635
-0.336056 0.469998 0.781562 0.918047 1.031306 1.219377 1.737468 2.050577 2.458442 2.720080
-0.165799 0.215460 0.363262 0.498067 1.217803 1.622985 1.903435 2.072821 2.251153 2.522123
-0.418176 0.619702 0.947421 1.146388 1.456489 1.664370 1.965827 2.179934 2.466824 2.629682
-0.265129 0.360058 0.519333 0.815729 0.992554 1.155878 1.718766 2.222951 2.442701 2.585525
-0.308187 0.464955 0.631733 0.775884 1.197138 1.454372 1.618186 2.005378 2.298683 2.443207
-0.178219 0.251645 0.407157 0.725307 1.323507 1.464894 1.694747 2.102622 2.283774 2.589151
-0.206659 0.311706 0.925646 1.192852 1.568069 1.802078 2.008324 2.197021 2.461939 2.657140
-0.174956 0.236808 0.392320 0.654967 0.934857 1.152108 1.595741 1.864532 2.214108 2.354775
-0.230434 0.344630 0.704520 0.910666 1.348070 1.567822 1.811907 1.939844 2.509990 2.701550
-0.180253 0.232955 0.624261 0.923991 1.421690 1.599589 1.814005 2.073839 2.413260 2.570514
-0.398056 0.571576 1.027057 1.401582 1.532635 1.743391 2.038501 2.173100 2.635865 2.756941
-0.244124 0.349847 0.599577 0.750991 0.891408 1.153522 1.605551 1.899047 2.317997 2.500479
-0.324856 0.539756 0.695489 0.870499 1.378985 1.583978 1.787428 2.079347 2.366844 2.502610
-0.250886 0.480663 0.608352 0.931539 1.092319 1.383530 1.692940 1.863607 2.650750 2.806650
-0.338327 0.396903 0.699669 1.241511 1.414878 1.559671 1.867401 2.000074 2.583166 2.742075
-0.164041 0.233302 0.383240 0.540410 0.806255 1.495618 1.938839 2.063074 2.286859 2.677635
-0.218870 0.316692 0.450414 0.721514 1.234846 1.762116 1.921161 2.415204 2.642001 2.782596
-0.163667 0.235743 0.354094 0.797110 1.437154 1.554340 2.096932 2.265233 2.481373 2.661373
-0.141630 0.198248 0.557013 1.138173 1.485146 1.786655 1.990698 2.185739 2.443261 2.719231
-0.217999 0.366741 0.519705 0.781024 0.899903 1.248543 1.852721 1.986039 2.401777 2.555847
-0.205878 0.302603 0.472303 0.693773 1.275278 1.505045 1.651223 2.075256 2.330750 2.459809
-0.205336 0.309242 0.483400 0.841555 1.362515 1.548353 1.760082 1.993603 2.496424 2.633078
-0.173174 0.251866 0.410487 1.098827 1.251313 1.651838 1.903428 2.405674 2.698209 2.817074
-0.274582 0.463838 0.620569 0.820587 0.988556 1.155062 1.637870 1.835193 2.071934 2.529835
-0.364198 0.472940 0.697706 1.016409 1.151822 1.373913 1.673193 1.811034 2.432956 2.643088
-0.210609 0.316509 0.475251 0.668420 1.418526 1.631402 1.796155 2.141848 2.319077 2.697236
-0.294479 0.519397 0.846472 1.213453 1.709661 1.916717 2.258070 2.456443 2.600351 2.786559
-0.170463 0.255944 0.401983 0.820520 1.094719 1.322743 1.646553 1.784940 2.486157 2.613248
-0.237336 0.356516 0.490576 0.924631 1.184187 1.304165 1.910651 2.102207 2.302776 2.641078
-0.237089 0.334322 0.503100 0.942044 1.087499 1.511162 1.952715 2.075663 2.564695 2.734500
-0.270484 0.426158 0.787084 1.011450 1.420404 1.627576 1.856282 2.112823 2.548329 2.769664
-0.212376 0.278943 0.617049 0.887684 1.142337 1.356367 1.727600 1.935068 2.149199 2.293257
-0.219581 0.437941 0.549582 0.824175 1.110224 1.217621 1.723719 1.891729 2.537107 2.790704
-0.180332 0.207980 0.422463 0.642179 1.028384 1.607980 2.250525 2.381973 2.608993 2.774395
-0.363639 0.523626 1.148877 1.352576 1.562465 1.724307 1.921396 2.120662 2.445004 2.610164
-0.150266 0.222691 0.365816 0.555803 0.688872 1.162897 1.782593 2.040683 2.522491 2.769536
-0.322510 0.444036 0.616943 0.895765 1.056214 1.275784 1.751504 1.895911 2.132909 2.370408
-0.228790 0.394631 0.548588 0.772733 1.227890 1.335766 1.788390 2.041514 2.278792 2.744098
-0.234366 0.288401 0.669909 1.295698 1.461082 1.731631 2.183204 2.296645 2.539291 2.656637
-0.255688 0.474634 0.639397 0.858887 1.097668 1.228104 1.592196 1.812078 2.070709 2.717623
-0.214002 0.365378 0.921340 1.120628 1.379265 1.601621 1.931336 2.141337 2.414577 2.593476
-0.220925 0.307330 0.407573 0.868421 1.663240 1.844525 1.994660 2.189618 2.371374 2.516151
-0.362773 0.569567 1.005505 1.504530 1.678917 1.910360 2.158978 2.297543 2.659978 2.788995
-0.296160 0.426108 0.649527 0.859492 1.056490 1.213501 1.697291 2.135737 2.364297 2.514164
-0.281900 0.432754 0.589102 0.914308 1.277709 1.401926 1.774347 1.972103 2.235129 2.544435
-0.277240 0.357036 0.828830 1.002473 1.178011 1.446057 1.715661 1.918548 2.237210 2.572122
-0.235923 0.330705 0.623139 1.275081 1.398365 1.615244 1.800110 2.151779 2.592066 2.735797
-0.179223 0.246208 0.400152 0.708696 1.129890 1.318110 1.696185 1.907985 2.203754 2.331059
-0.316183 0.382213 0.679593 0.814474 0.986274 1.762901 1.990617 2.149795 2.433563 2.555738
-0.218193 0.282095 0.586606 0.865818 1.378763 1.742711 1.918177 2.243443 2.595193 2.752713
-0.309792 0.481840 0.827993 1.213125 1.606995 1.730492 2.141679 2.280307 2.608238 2.849348
-0.270780 0.352881 0.501183 0.906847 1.086388 1.325169 1.838184 2.204039 2.421528 2.566162
-0.226107 0.390361 0.555807 0.749815 1.088830 1.205930 1.680764 2.021480 2.201488 2.659122
-0.123441 0.173507 0.307303 0.690407 1.173938 1.333877 1.786765 2.000793 2.425213 2.751118
-0.158591 0.214573 0.427561 0.902581 1.277688 1.674870 2.126902 2.421840 2.701440 2.836990
-0.189303 0.283266 0.464375 0.672875 1.104817 1.250272 1.526572 2.083813 2.270321 2.510880
-0.287382 0.434077 0.583769 0.905506 1.053249 1.483726 1.993792 2.165572 2.575308 2.698217
-0.263500 0.370045 0.536776 0.782922 1.324389 1.844905 2.005965 2.156203 2.458755 2.583419
-0.384009 0.584098 0.936199 1.287834 1.635325 1.761083 2.169160 2.324023 2.535401 2.749390
-0.146402 0.213762 0.398489 0.690149 0.996244 1.435892 1.670170 1.813953 2.445981 2.787485
-0.301226 0.367882 0.654854 1.094027 1.229960 1.592088 1.885201 2.005608 2.274408 2.444608
-0.149947 0.216185 0.391920 0.830502 1.253633 1.431601 1.785490 2.103484 2.525214 2.755484
-0.097894 0.173875 0.729312 1.016482 1.304096 1.606405 1.935582 2.257805 2.640341 2.840475
-0.169855 0.242145 0.571777 0.803659 1.022243 1.354604 1.782360 1.980234 2.368909 2.535598
-0.254591 0.378801 0.672668 0.807056 1.056720 1.493018 1.655380 1.979812 2.449241 2.599697
-0.193304 0.260487 0.459964 0.670291 1.308012 1.768287 1.946244 2.212251 2.405579 2.728625
-0.366883 0.536817 0.908218 1.110776 1.354740 1.500190 1.704032 1.943640 2.329476 2.560555
-0.211004 0.305715 0.399667 0.516282 0.691520 0.849824 1.396564 2.291427 2.546197 2.699794
-0.235007 0.315896 0.593374 0.857317 1.094567 1.500585 1.840100 1.974535 2.128181 2.274238
-0.183909 0.226449 0.400954 0.544120 1.348797 1.515812 1.765685 1.973782 2.256647 2.370030
-0.237680 0.317979 0.661098 1.253198 1.394092 1.734084 1.949126 2.131970 2.641034 2.757610
-0.166212 0.241240 0.371751 0.557281 0.767198 1.134161 1.620608 1.834400 2.454323 2.635245
-0.330393 0.391091 0.780047 1.022404 1.134626 1.502694 1.702935 1.890801 2.580707 2.691910
-0.408812 0.495670 0.687407 1.108832 1.546181 1.696379 1.885325 2.139028 2.368060 2.517184
-0.376422 0.555069 1.161646 1.386418 1.622733 1.845580 2.017094 2.201137 2.552466 2.708053
-0.274146 0.380469 0.549878 0.799730 0.939402 1.117940 1.645452 2.052539 2.350689 2.490049
-0.329001 0.575380 0.735296 0.911471 1.268064 1.391747 1.781411 2.007253 2.202059 2.466893
-0.212169 0.311180 0.439692 1.078259 1.267527 1.468391 1.726469 1.906190 2.628147 2.786434
-0.297463 0.361038 0.824509 1.239302 1.339377 1.569785 1.940696 2.077375 2.519418 2.696863
-0.207701 0.292358 0.552629 0.711964 1.172305 1.651429 1.844960 2.071458 2.419231 2.553707
-0.209832 0.301136 0.449094 0.647610 0.777779 1.480469 1.932068 2.131542 2.710060 2.812704
-0.172423 0.255437 0.369220 0.543108 1.401559 1.717608 1.933428 2.154827 2.367862 2.787661
-0.255748 0.347504 0.796616 1.027751 1.504250 1.760784 1.937354 2.112544 2.469490 2.637341
-0.169424 0.278442 0.444446 0.687556 0.797962 1.369199 1.630793 2.131758 2.696521 2.814286
-0.263582 0.429254 0.626198 0.790299 0.996064 1.131137 1.510958 2.083907 2.354499 2.747674
-0.160669 0.249969 0.366613 0.619384 1.335750 1.509419 1.938079 2.107770 2.598329 2.796645
-0.244289 0.315310 0.439736 0.746805 1.478790 1.975786 2.164362 2.279744 2.549736 2.677409
-0.158860 0.216940 0.349617 0.495945 1.053452 1.187951 1.643661 1.872490 2.121853 2.234733
-0.364934 0.547895 0.703548 1.046696 1.327165 1.444813 1.638612 1.994689 2.369195 2.515047
-0.199825 0.282570 0.423937 1.052805 1.331805 1.455952 1.892213 2.048648 2.272970 2.743986
-0.205916 0.528758 1.069123 1.303179 1.547206 1.887462 2.261478 2.525666 2.727548 2.836565
-0.211344 0.325615 0.470129 0.876822 1.036692 1.388499 2.004071 2.168361 2.641575 2.788384
-0.165214 0.237113 0.652635 0.853498 1.274603 1.418260 1.750475 2.188010 2.392225 2.656697
-0.171345 0.265931 0.404296 0.777656 1.251339 1.381106 1.876187 2.028307 2.321131 2.646341
-0.243930 0.315918 0.797490 1.189416 1.348551 1.850071 2.061191 2.229853 2.567528 2.706220
-0.194777 0.274153 0.522750 0.716292 0.872211 1.616112 1.890034 2.023297 2.194462 2.435800
-0.244945 0.443755 0.592420 0.889336 1.105448 1.259185 1.758350 1.914694 2.352504 2.581197
-0.179880 0.257145 0.369148 0.581368 1.406373 1.820128 2.061537 2.213705 2.526442 2.674115
-0.545317 0.839577 1.093857 1.262533 1.530824 1.739612 2.017505 2.229486 2.511345 2.662061
-0.188061 0.301651 0.405278 0.612153 0.779478 1.037845 2.004224 2.211267 2.475847 2.697676
-0.314335 0.465910 0.634660 0.880106 1.266325 1.367294 1.763992 2.104409 2.276097 2.443435
-0.141443 0.203354 0.372102 0.773557 1.052380 1.521452 1.774251 1.900827 2.384498 2.726988
-0.183016 0.267487 0.382582 1.062637 1.528110 1.626188 1.861114 2.019971 2.608976 2.763674
-0.143357 0.192604 0.323821 0.497856 0.905440 1.343367 1.820946 2.001139 2.153210 2.609622
-0.354165 0.489743 0.667126 1.118630 1.392866 1.492788 1.780757 2.073223 2.328160 2.560997
-0.282856 0.383914 0.485830 0.850543 1.506444 1.797613 1.937969 2.146059 2.427443 2.548079
-0.487767 0.866830 1.364561 1.521265 1.733207 1.945262 2.238743 2.399018 2.632115 2.744288
-0.280530 0.416807 0.597088 0.899084 1.119331 1.255621 1.616253 2.134732 2.562029 2.692235
-0.284821 0.494631 0.684501 0.838586 1.258096 1.395495 1.638054 2.162929 2.354037 2.540591
-0.205140 0.295529 0.494620 0.956357 1.129557 1.430489 1.736194 1.883778 2.442628 2.597296
-0.304833 0.379519 0.691807 1.147815 1.310207 1.513791 2.008217 2.142574 2.387944 2.637546
-0.181676 0.219451 0.383940 0.516016 1.044498 1.517177 1.777135 1.964014 2.218885 2.363256
-0.294578 0.352761 0.665993 0.810615 0.975505 1.763777 1.954836 2.159643 2.626241 2.718025
-0.172769 0.247043 0.367453 0.702216 1.520013 1.752683 1.974569 2.256458 2.462168 2.651882
-0.133992 0.301438 0.794542 1.081390 1.502045 1.696404 2.061943 2.278505 2.623520 2.822598
-0.250639 0.391712 0.550858 0.794112 0.913038 1.085745 2.034282 2.313366 2.505665 2.787062
-0.323242 0.434081 0.555684 0.961893 1.357180 1.456826 1.643504 1.784048 2.015616 2.515904
-0.143041 0.186235 0.352826 0.680065 1.264865 1.599306 1.944390 2.254806 2.597410 2.807813
-0.203141 0.289063 0.395881 0.800946 1.463891 1.689942 1.835029 2.061175 2.225528 2.642274
-0.222797 0.394599 0.573255 0.715466 1.025538 1.188023 1.564145 2.025279 2.191600 2.532423
-0.405610 0.492208 0.769597 0.896548 1.095745 1.667540 1.851755 2.090613 2.499090 2.611378
-0.238982 0.324219 0.447220 0.884037 1.482394 1.649975 1.799871 2.147158 2.341317 2.496853
-0.453661 0.658367 0.977870 1.248116 1.512727 1.831479 2.096748 2.293691 2.622778 2.735454
-0.171442 0.338885 0.499399 0.793308 1.060572 1.203862 1.664796 1.804188 2.519133 2.756339
-0.278022 0.338379 0.636156 1.044803 1.186358 1.516967 1.701121 1.872073 2.394724 2.502070
-0.121438 0.167486 0.411911 0.917381 1.165927 1.533981 1.818319 2.060997 2.450329 2.746320
-0.162532 0.224824 0.658346 0.916673 1.391225 1.595859 1.857208 2.217273 2.498430 2.753849
-0.275986 0.349156 0.568548 0.683453 1.016150 1.598731 1.764733 1.935888 2.342502 2.451659
-0.253773 0.480249 0.604419 0.965946 1.273556 1.519695 1.780207 2.006359 2.680279 2.811275
-0.187376 0.271558 0.385829 0.556450 1.380619 1.664090 1.814039 2.064114 2.245361 2.453707
-0.294725 0.466563 0.736292 1.055050 1.550984 1.693651 1.897743 2.212842 2.491391 2.698543
-0.239923 0.334060 0.461488 0.662636 0.791453 1.005699 1.600227 2.170741 2.458382 2.619019
-0.327525 0.492740 0.643437 0.903326 1.245421 1.348861 1.592207 1.937940 2.512050 2.644548
-0.221363 0.338816 0.483946 0.687648 1.284665 1.551620 1.720135 2.073904 2.254226 2.544134
-0.258618 0.300723 0.704898 1.390679 1.579033 1.718703 1.937423 2.081021 2.591851 2.718075
-0.204543 0.311448 0.448600 0.699217 1.072306 1.225857 1.749871 2.025585 2.206864 2.441320
-0.407224 0.493488 0.735697 1.167395 1.335468 1.468164 1.704353 1.844157 2.418454 2.658505
-0.177985 0.233336 0.506489 0.863799 1.426574 1.604693 1.864455 2.179274 2.402289 2.599311
-0.201307 0.580059 1.233073 1.407900 1.670628 1.818287 2.017446 2.256081 2.551962 2.742129
-0.322757 0.406373 0.612482 0.787838 0.909320 1.345224 1.671798 1.785817 2.404421 2.543501
-0.331870 0.431884 0.597156 0.927729 1.457447 1.672300 1.841455 2.039567 2.250965 2.417211
-0.202946 0.328964 0.442956 0.945971 1.181249 1.322011 1.766214 1.899811 2.569787 2.777471
-0.274929 0.335270 0.613025 1.214599 1.385772 1.557449 1.956849 2.066650 2.288912 2.459016
-0.146768 0.210059 0.360823 0.630784 1.072395 1.512445 1.766060 1.876355 2.226609 2.774121
-0.278686 0.371483 0.567509 0.728655 0.855673 1.555589 1.958603 2.076551 2.544275 2.713690
-0.143219 0.224816 0.347059 0.649970 1.564613 1.685486 1.917021 2.072654 2.453763 2.655050
-0.294541 0.443278 0.726594 0.985933 1.415734 1.765955 2.073442 2.328283 2.592514 2.745548
-0.243739 0.365134 0.572466 0.827675 0.939711 1.401796 1.826498 1.947840 2.429538 2.736311
-0.213082 0.349340 0.619784 0.765201 1.188628 1.358763 1.534192 2.128318 2.415976 2.591807
-0.161799 0.248667 0.354739 0.716246 1.327356 1.505974 1.706364 1.848519 2.455553 2.645897
-0.228516 0.375004 0.745896 1.050532 1.367740 1.799352 2.151717 2.418669 2.673185 2.797596
-0.234744 0.320318 0.466401 1.013481 1.184613 1.343346 1.535391 1.904405 2.318092 2.457794
-0.296936 0.385747 0.828858 1.091916 1.213084 1.370156 1.504418 2.008638 2.299958 2.422080
-0.189955 0.288894 0.417900 0.584179 1.286507 1.481483 1.710061 2.088780 2.259900 2.658597
-0.170659 0.301463 1.070828 1.400247 1.605036 1.820055 2.012834 2.274844 2.579681 2.738437
-0.194796 0.277316 0.434438 0.646763 0.772268 1.506173 1.740645 1.962370 2.464322 2.657388
-0.222257 0.294563 0.463770 1.144565 1.329294 1.506915 1.848439 2.035803 2.320447 2.526842
-0.188443 0.314239 0.448752 0.852815 1.354102 1.446757 1.902520 2.034088 2.526616 2.815041
-0.226181 0.693860 0.965201 1.130620 1.285879 1.475154 1.863626 2.238763 2.603071 2.788862
-0.105661 0.160079 0.370939 0.956425 1.151620 1.531460 1.723426 1.913560 2.122164 2.492465
-0.298984 0.431063 0.586646 0.778394 0.883075 1.252332 1.854971 2.007147 2.580641 2.710519
-0.197240 0.272225 0.520497 0.915877 1.306265 1.547858 2.092985 2.299254 2.524173 2.690593
-0.413504 0.577521 0.882547 1.151243 1.588968 1.757858 1.954145 2.157780 2.423490 2.567497
-0.182013 0.280163 0.398250 0.608531 0.819691 0.969023 1.853980 2.067111 2.358004 2.831492
-0.376103 0.585036 0.744512 0.923312 1.183525 1.290764 1.692231 2.073489 2.270157 2.435995
-0.206648 0.328267 0.465432 0.752470 1.311956 1.450538 1.719681 2.019809 2.237402 2.712715
-0.146386 0.213798 0.495001 1.215327 1.552462 1.867870 2.131376 2.312738 2.674961 2.807719
-0.204301 0.298214 0.439837 0.759917 0.957505 1.118467 1.710802 2.037862 2.222732 2.676717
-0.208889 0.314961 0.807094 0.979256 1.326634 1.615428 1.855738 2.074151 2.481053 2.662164
-0.252094 0.321219 0.425486 1.124218 1.685315 1.954485 2.094831 2.253423 2.478229 2.605367
-0.454303 0.738006 1.152178 1.340103 1.644779 1.957406 2.329060 2.526950 2.700749 2.789332
-0.260026 0.460186 0.631124 0.860895 1.160270 1.274078 1.873660 2.167213 2.365849 2.770340
-0.188841 0.259372 0.483027 0.884169 1.354974 1.505271 1.787912 1.916914 2.217944 2.371433
-0.171267 0.239784 0.594776 0.748624 1.254712 1.402634 1.627575 2.102077 2.361702 2.545685
-0.261290 0.332761 0.480740 1.272870 1.411888 1.585755 1.891613 2.059093 2.603683 2.753852
-0.174471 0.227361 0.395376 0.589674 1.098988 1.351413 1.527512 1.875704 2.288035 2.491253
-0.392523 0.493384 0.723718 0.863221 0.994939 1.404446 1.868453 2.008324 2.440145 2.622287
-0.229001 0.293967 0.482060 0.752040 1.321587 1.964756 2.143632 2.272231 2.511299 2.652857
-0.129576 0.441380 0.809457 1.253754 1.449504 1.695975 2.014264 2.282645 2.615841 2.803547
-0.291794 0.444574 0.567987 0.774856 0.900327 1.365457 2.004858 2.128537 2.620438 2.820651
-0.262097 0.516409 0.687606 0.926622 1.163526 1.292705 1.715555 1.937306 2.227923 2.777260
-0.148606 0.204513 0.361193 0.693710 1.055532 1.278718 1.693525 1.980097 2.352859 2.672283
-0.253802 0.336651 0.526195 0.891801 1.442978 1.584849 1.979819 2.247623 2.476136 2.660081
-0.228789 0.338363 0.500714 0.793809 1.196272 1.305413 1.731081 2.259108 2.442615 2.652754
-0.378062 0.473823 0.693080 1.009192 1.183244 1.328164 1.919726 2.260450 2.429886 2.572302
-0.247090 0.357491 0.583930 0.824533 1.624951 1.779841 1.978982 2.185311 2.378227 2.583823
-0.349863 0.525291 0.898639 1.154449 1.653664 1.882655 2.181526 2.353823 2.532309 2.660763
-0.190910 0.256714 0.576278 0.756016 0.919967 1.182918 1.663565 2.144466 2.501734 2.728244
-0.298865 0.359843 0.568492 1.131552 1.379757 1.490406 1.824274 1.945718 2.238708 2.644005
-0.075640 0.092838 0.245669 0.863294 1.223916 1.524202 1.857987 2.167767 2.516095 2.793204
-0.232965 0.332699 0.723652 1.036910 1.459468 1.595582 1.952510 2.172737 2.392688 2.562895
-0.247766 0.389477 0.616596 0.808130 0.997595 1.253872 1.724465 1.938385 2.286441 2.479069
-0.316879 0.442442 0.602552 0.812843 0.919668 1.524096 1.727104 1.959085 2.648008 2.744204
-0.180121 0.250848 0.377588 0.514084 1.112861 1.845482 2.013326 2.213933 2.474673 2.663237
-0.510891 0.729294 0.918315 1.009382 1.258580 1.685479 2.036454 2.223282 2.546829 2.685952
-0.204819 0.306851 0.495622 0.688481 0.939049 1.054525 1.550902 2.063497 2.267332 2.744891
-0.327442 0.389656 0.773076 1.023761 1.144959 1.391107 1.629777 1.826936 2.044965 2.488423
-0.163318 0.224949 0.377732 0.697324 1.243068 1.379089 1.633682 1.887173 2.332645 2.483657
-0.240171 0.293151 0.543472 1.269350 1.631535 1.739995 1.933642 2.084522 2.414170 2.650266
-0.179979 0.246939 0.396342 0.589909 0.919210 1.070722 1.642599 2.043006 2.217357 2.503273
-0.302811 0.355529 0.811588 1.166553 1.271468 1.626247 1.848829 1.997826 2.540939 2.669384
-0.283439 0.349236 0.510446 0.919208 1.451466 1.719296 1.870795 2.075959 2.292387 2.415026
-0.351847 0.508411 1.045930 1.254317 1.551190 1.805638 2.048595 2.229665 2.467316 2.616962
-0.266736 0.408066 0.559013 0.768550 0.973174 1.096776 1.669225 2.079118 2.239808 2.647906
-0.299839 0.538608 0.750887 0.937387 1.361442 1.507727 1.723958 2.019542 2.288365 2.433554
-0.184692 0.270218 0.419274 1.047374 1.395536 1.529142 1.783612 1.919322 2.399668 2.739026
-0.282417 0.355135 0.625619 1.193013 1.365194 1.548352 1.961542 2.076835 2.555666 2.736510
-0.148276 0.201484 0.357526 0.691839 1.109393 1.590808 1.929494 2.052123 2.288831 2.674265
-0.239872 0.340799 0.510028 0.754201 1.021805 1.444270 2.086249 2.268881 2.498859 2.644372
-0.229200 0.356617 0.469799 0.697079 1.459153 1.736841 1.888964 2.204606 2.435847 2.594633
-0.235297 0.299631 0.756788 1.069754 1.591291 1.782731 1.990029 2.186477 2.404269 2.551371
-0.153218 0.216649 0.366074 0.591966 0.786672 1.337023 1.751677 1.932515 2.401392 2.607477
-0.264340 0.436803 0.595010 0.767010 1.179494 1.352438 1.528478 1.996792 2.441404 2.572631
-0.204113 0.325813 0.640860 0.803282 1.276398 1.511437 1.769275 2.073412 2.562526 2.723891
-0.183616 0.242809 0.370321 0.932837 1.683840 1.816525 2.211177 2.406486 2.636015 2.765906
-0.196637 0.265829 0.439050 0.770452 1.054669 1.487115 1.916956 2.043030 2.176612 2.349845
-0.540575 0.704261 0.884898 1.106375 1.273439 1.431611 1.908872 2.163885 2.347449 2.530928
-0.258740 0.346556 0.466932 0.905095 1.485463 1.645285 1.873902 2.133924 2.308179 2.675230
-0.347296 0.582875 0.945844 1.279162 1.499633 1.852636 2.184304 2.463318 2.760760 2.870853
-0.150936 0.266396 0.672274 0.842540 1.058933 1.395955 1.763874 2.053646 2.603603 2.795989
-0.248334 0.323639 0.796411 0.974630 1.217472 1.616989 1.786496 1.995745 2.426072 2.572132
-0.171528 0.226268 0.387197 0.596052 1.219235 1.373257 1.802693 2.162095 2.401149 2.694122
-0.309880 0.375034 0.782497 0.936541 1.130945 1.571152 1.743522 2.158706 2.484175 2.596635
-0.211833 0.283751 0.471901 0.833897 1.238193 1.611788 1.813797 2.021568 2.299015 2.453586
-0.325164 0.495780 0.668458 0.977772 1.204875 1.377736 1.792224 1.981132 2.470212 2.687064
-0.181910 0.238625 0.380080 0.551818 1.284137 1.815502 2.100874 2.224073 2.678894 2.832381
-0.432484 0.602036 0.967559 1.355422 1.539906 1.638130 2.062617 2.274317 2.408629 2.586735
-0.223933 0.320440 0.455471 0.635789 0.775870 0.919569 1.655549 2.258604 2.454533 2.743063
-0.366581 0.460393 0.676450 1.035749 1.222446 1.344767 1.892128 2.136552 2.294736 2.535285
-0.163193 0.228589 0.372272 0.655743 1.215923 1.357562 1.812178 2.049878 2.219187 2.622506
-0.199107 0.255898 0.383597 1.460200 1.573471 1.769089 1.990458 2.299624 2.582669 2.742646
-0.171634 0.266479 0.432062 0.687765 0.835208 1.354791 1.779760 1.939277 2.152823 2.654474
-0.322744 0.454468 0.896616 1.075278 1.276965 1.525868 1.809606 2.045119 2.396969 2.600609
-0.185456 0.225713 0.593805 0.777028 1.383381 1.756301 1.909552 2.182404 2.428047 2.628560
-0.523864 0.996370 1.345344 1.500637 1.856758 1.976312 2.235904 2.414483 2.560231 2.666268
-0.224472 0.316210 0.461082 1.069924 1.226634 1.409037 1.539144 2.110751 2.541082 2.731841
-0.282572 0.449304 0.655998 0.827960 1.292714 1.495327 1.771585 2.007810 2.430764 2.621645
-0.129294 0.178584 0.451465 1.015109 1.245704 1.462743 1.785107 2.042319 2.339740 2.626045
-0.266450 0.311925 0.672071 1.272373 1.586471 1.680518 1.967287 2.126302 2.331703 2.606765
-0.155912 0.210793 0.359734 0.582139 0.993095 1.506017 1.938903 2.072031 2.211582 2.514161
-0.366487 0.454941 0.765153 0.933105 1.077517 1.457225 1.642714 2.050965 2.548495 2.660408
-0.183421 0.269815 0.375652 0.582732 1.364229 1.857303 2.030324 2.188264 2.389621 2.554337
-0.157986 0.433220 0.872229 1.187796 1.412974 1.724479 2.144349 2.464695 2.761508 2.877055
-0.198383 0.350654 0.577264 0.787611 0.933392 1.119024 1.806604 2.076373 2.430526 2.603043
-0.184568 0.290732 0.456474 0.730730 1.167452 1.298890 1.669065 1.850198 2.187295 2.556672
-0.119787 0.157206 0.296086 0.580699 1.039340 1.448681 1.791765 2.115501 2.493729 2.765061
-0.197875 0.296866 0.460866 0.906361 1.504895 1.622424 1.923913 2.064370 2.528505 2.799113
-0.215006 0.360632 0.624855 0.788786 1.122529 1.271335 1.469548 2.029397 2.292842 2.469529
-0.312967 0.420596 0.594715 1.013895 1.177345 1.350956 1.928177 2.047807 2.512550 2.690404
-0.306441 0.447709 0.635622 0.837489 1.339889 1.684905 1.878731 2.050783 2.442345 2.559302
-0.512714 0.732554 1.090397 1.458930 1.653272 1.872563 2.243616 2.386971 2.644360 2.753299
-0.338380 0.388353 0.687865 0.937576 1.022955 1.198008 1.345071 1.507334 2.539150 2.676481
-0.404547 0.489770 0.787746 1.025925 1.160826 1.496135 1.873747 1.995764 2.348409 2.558815
-0.185178 0.273616 0.662107 0.944310 1.146715 1.437855 1.860110 2.088161 2.488532 2.701156
-0.297691 0.433807 0.689073 0.914516 1.224645 1.524468 1.882477 2.108378 2.460989 2.729694
-0.246421 0.329313 0.740815 0.903181 1.072400 1.285931 1.740684 2.032245 2.270116 2.425587
-0.349571 0.509003 0.727457 0.878169 1.005363 1.205249 1.651188 1.987842 2.609611 2.723475
-0.174962 0.249723 0.401862 0.559808 1.151652 1.704681 1.872495 2.239764 2.430897 2.686106
-0.360336 0.530604 0.935905 1.180560 1.399529 1.740890 1.999598 2.182066 2.486093 2.641677
-0.220231 0.312545 0.449608 0.705056 1.007679 1.135090 1.633644 2.306528 2.622813 2.773890
-0.343635 0.564980 0.719160 0.856829 1.120400 1.237963 1.472239 1.924690 2.221264 2.357713
-0.181932 0.261428 0.385382 0.529871 1.326078 1.525795 1.689465 2.161317 2.354960 2.559655
-0.190215 0.341309 1.145487 1.357611 1.520525 1.690701 1.910605 2.192963 2.496750 2.684620
-0.231256 0.323986 0.509297 0.695026 0.811246 1.205058 1.698676 1.952659 2.225356 2.436417
-0.232855 0.310052 0.551612 0.995822 1.160276 1.555029 1.794030 1.930657 2.512921 2.691535
-0.224518 0.299721 0.651543 0.885427 1.520642 1.679516 1.886989 2.041276 2.532253 2.699897
-0.204419 0.557694 1.100186 1.347777 1.507922 1.794663 2.079200 2.312468 2.590685 2.744668
-0.206125 0.397544 0.556512 0.740671 0.860709 1.076989 1.713565 1.825995 2.561599 2.767561
-0.271126 0.422296 0.596820 0.801216 1.362100 1.508235 1.854835 2.090662 2.270770 2.457032
-0.217883 0.344596 0.493190 0.984719 1.284852 1.446608 1.855635 2.014247 2.506491 2.663445
-0.286136 0.348718 0.879652 1.116298 1.280497 1.611569 1.788213 2.223036 2.485667 2.605528
-0.206618 0.325875 0.503268 0.690657 0.816866 1.603798 1.931282 2.048093 2.300900 2.746683
-0.239837 0.367432 0.586673 0.749249 1.029445 1.541977 1.837717 2.152675 2.628130 2.775655
-0.154164 0.222772 0.333818 0.562653 1.465627 1.728492 1.959659 2.326185 2.619462 2.821726
-0.231365 0.366985 0.807033 1.157258 1.520494 1.640269 2.028108 2.269663 2.456856 2.630277
-0.242567 0.331771 0.487513 0.644276 0.800853 1.242217 1.739018 2.099717 2.426228 2.596782
-0.221262 0.374389 0.569573 0.704902 1.187721 1.414042 1.633903 2.049607 2.225608 2.522881
-0.182959 0.295198 0.401501 0.779683 1.428548 1.551019 1.766917 1.908320 2.610886 2.770247
-0.139632 0.228108 0.540279 0.898292 1.161261 1.527413 1.913196 2.221342 2.669902 2.842594
-0.199568 0.297036 0.423971 0.782421 1.094574 1.237964 1.458722 1.683022 2.217064 2.401823
-0.345577 0.539506 0.728116 0.928242 1.109271 1.252921 1.616753 1.872570 2.294941 2.593196
-0.232502 0.366195 0.532625 0.762469 1.377487 1.543949 1.839468 2.094305 2.306962 2.746485
-0.140704 0.240287 0.914003 1.159689 1.490769 1.781986 2.113189 2.322630 2.553898 2.735752
-0.182050 0.274243 0.384886 0.753150 1.226502 1.367895 1.578386 1.756614 2.368689 2.613973
-0.296233 0.395081 0.622990 1.050299 1.209800 1.377648 1.850837 1.965328 2.357424 2.667891
-0.210632 0.289301 0.558974 0.972835 1.230379 1.669485 1.879551 2.047374 2.584468 2.764860
-0.238075 0.443727 0.795624 1.008735 1.264607 1.681476 1.949029 2.204123 2.681059 2.831198
-0.209107 0.318887 0.502202 0.936331 1.215090 1.364179 1.664829 1.835085 2.029832 2.237236
-0.210399 0.360507 0.466140 0.793696 1.167290 1.269402 1.717457 1.883978 2.332357 2.642576
-0.182774 0.238064 0.406254 0.553908 1.089357 1.921943 2.114739 2.269998 2.553977 2.719355
-0.328207 0.496148 0.997544 1.217533 1.381558 1.589977 1.895773 2.171180 2.563942 2.756785
-0.146726 0.209578 0.327902 0.527454 0.750165 0.964221 1.730110 1.909856 2.277000 2.794161
-0.355489 0.509819 0.674351 0.852118 1.030963 1.155918 1.581384 2.041691 2.263390 2.416994
-0.220775 0.394332 0.538938 0.857502 1.090722 1.239600 1.901251 2.063868 2.417954 2.814398
-0.227931 0.269928 0.659119 1.441707 1.726640 1.837599 2.172077 2.323353 2.607646 2.741321
-0.204294 0.338820 0.480507 0.748377 0.971841 1.112524 1.682403 1.842741 2.204016 2.598799
-0.134004 0.253595 0.893064 1.145993 1.324870 1.551540 1.870979 2.144984 2.515124 2.768074
-0.257317 0.324072 0.436271 0.992642 1.573175 1.838976 1.971813 2.132071 2.317177 2.463177
-0.440270 0.694478 1.072028 1.389390 1.760193 1.976248 2.246033 2.390948 2.572760 2.701541
-0.271868 0.367973 0.618954 0.990978 1.193710 1.400934 1.753507 2.089331 2.441172 2.596397
-0.327621 0.496909 0.684291 0.830070 1.230609 1.553632 1.769123 2.021449 2.321602 2.475665
-0.150834 0.225465 0.584436 0.830787 1.228446 1.381420 1.677267 1.961417 2.348329 2.682122
-0.210368 0.286671 0.430934 1.168493 1.348054 1.560861 1.788186 2.334928 2.567985 2.774704
-0.192791 0.272915 0.432199 0.684073 1.250160 1.396822 1.637113 1.872041 2.138995 2.291744
-0.317041 0.383173 0.714443 0.880122 1.046184 1.601600 1.793056 1.983005 2.334210 2.481632
-0.262491 0.384516 0.723463 0.898594 1.235333 1.679346 2.063633 2.230677 2.438434 2.609821
-0.329714 0.503133 0.986474 1.242112 1.421780 1.772248 2.016548 2.418708 2.735517 2.841414
-0.234483 0.366854 0.685189 0.837277 1.107168 1.323527 1.924146 2.188176 2.392339 2.576791
-0.367554 0.480477 0.685257 0.863574 0.967484 1.324325 1.780913 1.895223 2.217908 2.565386
-0.170831 0.247070 0.413674 0.735129 1.097256 1.244501 1.863046 2.116005 2.354145 2.593904
-0.191987 0.265143 0.522063 1.001132 1.477027 1.634641 2.128571 2.320908 2.626696 2.814549
-0.173820 0.236201 0.389631 0.565594 1.191995 1.339140 1.563074 2.078967 2.273323 2.569148
-0.376887 0.472762 0.685713 0.842626 0.950694 1.348880 2.073181 2.248666 2.464908 2.680293
-0.200511 0.267485 0.473655 0.709045 1.237600 1.615428 2.015635 2.177003 2.363079 2.525359
-0.179632 0.571501 0.993053 1.356696 1.697465 1.978072 2.161225 2.343876 2.605905 2.752543
-0.171679 0.323767 0.479066 0.737860 0.967236 1.119767 1.534022 1.686592 2.597041 2.826056
-0.230844 0.314638 0.827482 1.044417 1.246762 1.604017 1.888847 2.034619 2.240069 2.646086
-0.137641 0.194410 0.446076 0.749008 1.056291 1.455419 1.852539 2.123128 2.508952 2.766009
-0.096036 0.420947 0.665747 1.146516 1.463996 1.612743 1.861963 2.227963 2.503650 2.739358
-0.245487 0.384590 0.558312 0.811909 1.198414 1.349136 1.841320 2.025572 2.208162 2.405870
-0.208252 0.316837 0.487011 0.938933 1.139581 1.396565 1.746724 2.105258 2.522568 2.681942
-0.283283 0.395565 0.569206 0.705427 1.140133 1.660691 1.900167 2.146532 2.523653 2.667587
-0.399059 0.602519 0.918365 1.124094 1.352400 1.574194 1.915640 2.120676 2.392517 2.583609
-0.212592 0.313545 0.489908 0.651935 0.827527 1.014819 1.629779 2.107560 2.651570 2.794154
-0.334733 0.413938 0.656403 1.035599 1.230100 1.372371 1.752515 1.932544 2.116066 2.340962
-0.195470 0.268391 0.431096 0.744590 1.272458 1.434994 1.887256 2.055124 2.216059 2.355652
-0.233843 0.277098 0.577590 1.353544 1.573248 1.679793 1.831093 1.982748 2.575813 2.732432
-0.140410 0.214833 0.361115 0.707069 1.082237 1.227591 1.633210 1.818367 2.466253 2.766104
-0.433646 0.517163 0.808168 1.061617 1.182393 1.497547 1.723696 1.907866 2.509297 2.679398
-0.251461 0.331356 0.713430 0.993326 1.485426 1.665910 1.856843 2.073870 2.333905 2.470116
-0.362946 0.782976 1.168741 1.324526 1.627412 1.779530 1.994819 2.203297 2.514465 2.683132
-0.283937 0.367927 0.590168 0.763650 0.889158 1.242000 1.768049 2.150831 2.361695 2.526931
-0.401929 0.576820 0.737804 0.921682 1.116842 1.229133 1.694656 2.010744 2.155271 2.356219
-0.212653 0.310679 0.420635 1.110694 1.371611 1.510937 1.878595 2.017471 2.541126 2.696793
-0.319899 0.406846 0.688156 1.227145 1.532072 1.647604 1.959419 2.112752 2.468573 2.688910
-0.213311 0.302778 0.513141 0.665182 1.070601 1.519880 1.688862 2.155925 2.405361 2.641935
-0.203445 0.273890 0.446788 0.621718 0.821718 1.552774 1.970174 2.157338 2.529885 2.666726
-0.179248 0.265048 0.386747 0.570219 1.370731 1.523935 1.867101 2.136819 2.309819 2.738000
-0.192568 0.286600 0.737250 1.129156 1.630027 1.793060 2.137459 2.357517 2.543832 2.752975
-0.159062 0.222492 0.441749 0.706956 0.873673 1.273730 1.807800 2.085052 2.433983 2.738811
-0.267122 0.464503 0.667094 0.815715 1.028866 1.162422 1.617585 2.164095 2.329764 2.612700
-0.144708 0.223957 0.317997 0.564825 1.508828 1.655161 1.857741 2.024989 2.639153 2.820953
-0.194645 0.249640 0.406742 0.707511 1.660221 1.859905 2.085456 2.405218 2.607363 2.746061
-0.429960 0.592124 0.787877 0.890595 1.103239 1.404765 1.789301 2.072362 2.432455 2.617254
-0.184536 0.285665 0.429789 0.950068 1.412318 1.523812 1.954708 2.141451 2.414013 2.765321
-0.369916 0.560855 0.927769 1.354226 1.560397 1.733808 2.189951 2.345823 2.725694 2.866959
-0.142852 0.219159 0.368392 0.659778 0.999846 1.194353 1.856812 2.065831 2.665677 2.850916
-0.209110 0.305167 0.683734 0.914276 1.379246 1.526394 1.790110 2.064232 2.299981 2.459264
-0.184899 0.316366 0.506466 0.728745 1.218050 1.378981 1.814293 1.999655 2.544039 2.730706
-0.286474 0.355126 0.718899 1.089400 1.225976 1.695737 1.936410 2.121418 2.444195 2.568086
-0.260728 0.353369 0.604610 0.768238 1.072125 1.608746 1.805375 1.949798 2.105786 2.406476
-0.330885 0.561445 0.724292 0.940383 1.093573 1.263066 1.930153 2.163533 2.408371 2.762449
-0.190585 0.245026 0.388935 0.531269 1.613901 1.940446 2.068138 2.295339 2.525519 2.695115
-0.659517 0.793695 0.983316 1.214573 1.426393 1.621779 1.948650 2.120559 2.402013 2.570449
-0.220748 0.332069 0.424610 0.602935 0.734265 0.935558 2.055617 2.265657 2.530681 2.854902
-0.290477 0.440845 0.612873 0.839848 1.327423 1.456572 1.939179 2.167778 2.371320 2.570765
-0.179431 0.280105 0.432734 0.918191 1.192829 1.320190 1.811052 1.955192 2.340353 2.782529
-0.202912 0.265690 0.431272 1.238667 1.481469 1.610194 1.975157 2.101548 2.630962 2.798935
-0.162106 0.210383 0.366556 0.543819 1.054714 1.205759 1.641024 2.015868 2.178793 2.627151
-0.317316 0.385969 0.673513 1.190904 1.357921 1.500892 1.894288 2.020919 2.379283 2.662802
-0.327266 0.429724 0.606313 0.900788 1.464235 1.816681 2.002694 2.138059 2.452853 2.554712
-0.416374 0.642735 1.300859 1.518625 1.707945 1.956089 2.222013 2.390921 2.684341 2.784854
-0.186066 0.250175 0.562512 0.738528 1.208585 1.362690 1.606043 2.109182 2.501183 2.707198
-0.236912 0.461787 0.686242 0.881092 1.300577 1.424620 1.725187 2.169489 2.361758 2.662324
-0.208063 0.337571 0.482777 0.926508 1.161683 1.311006 1.776451 1.933103 2.448810 2.646540
-0.256479 0.328343 0.499814 1.097457 1.386665 1.496809 1.952745 2.087139 2.342994 2.654825
-0.161661 0.224177 0.383379 0.607758 0.991555 1.381589 1.804283 1.998147 2.415608 2.619198
-0.386111 0.495518 0.750917 0.937387 1.069306 1.592878 2.091954 2.230429 2.574083 2.695163
-0.236835 0.303063 0.548777 0.748487 1.602860 1.790903 1.980987 2.173544 2.482285 2.674930
-0.115857 0.253229 0.839446 1.182318 1.604808 1.930292 2.262789 2.477033 2.731091 2.843896
-0.213435 0.341074 0.506347 0.714649 0.813915 1.154546 1.865334 2.056297 2.656061 2.833781
-0.152341 0.225866 0.394818 0.830840 1.039343 1.299776 1.515314 1.701937 2.172593 2.703933
-0.150002 0.193206 0.361814 0.541289 1.168971 1.515576 1.875006 2.181631 2.473830 2.750294
-0.175983 0.238402 0.392935 0.834832 1.568038 1.753001 1.950436 2.176878 2.408077 2.761430
-0.213829 0.318859 0.535586 0.713597 1.015672 1.174333 1.408597 2.083136 2.354086 2.563569
-0.417612 0.500513 0.811466 1.027816 1.139572 1.532510 1.959824 2.084676 2.544668 2.694259
-0.279259 0.446390 0.589074 0.796267 1.496946 1.723595 1.869786 2.100336 2.331076 2.456141
-0.444430 0.638237 1.041068 1.445315 1.605692 1.733619 2.167615 2.326214 2.602181 2.745455
-0.210087 0.362661 0.515500 0.840169 1.033119 1.239618 1.373615 1.803901 2.716235 2.848165
-0.225160 0.350738 0.501850 0.896968 1.297884 1.414194 1.669332 1.835349 2.075666 2.672832
-0.039211 0.113866 0.622349 0.907025 1.252791 1.535875 1.876167 2.163786 2.540348 2.789312
-0.126350 0.194309 0.675134 1.116698 1.365415 1.576318 1.849118 2.102016 2.438531 2.737802
-0.251266 0.342779 0.622143 0.793543 1.004128 1.433428 1.828192 2.011292 2.214652 2.441068
-0.287491 0.392893 0.575294 0.916666 1.023814 1.482149 1.829139 1.953760 2.589735 2.724978
-0.198423 0.295697 0.439598 0.609605 1.262768 1.619956 1.747689 2.005913 2.368608 2.490906
-0.358531 0.483574 0.802846 1.004510 1.351513 1.645034 1.955330 2.161545 2.477437 2.639225
-0.252099 0.385070 0.557560 0.740943 0.911070 1.013935 1.524718 2.136124 2.396009 2.750794
-0.277335 0.507312 0.745418 0.921396 1.189730 1.321635 1.630275 2.000574 2.318359 2.450355
-0.251729 0.359609 0.480792 0.813240 1.317908 1.441397 1.655896 2.171984 2.476511 2.611973
-0.267463 0.311514 0.756574 1.332619 1.482384 1.635505 1.872999 2.053016 2.640422 2.756993
-0.175657 0.240482 0.383528 0.598077 0.916809 1.091066 1.760568 1.946970 2.313700 2.484722
-0.308726 0.352539 0.822652 1.208001 1.295254 1.507386 1.644261 1.995003 2.594656 2.684930
-0.292332 0.442077 0.718688 0.941531 1.395212 1.630615 1.847265 2.270351 2.514492 2.713146
-0.215044 0.379718 1.248947 1.429713 1.705990 1.881505 2.089432 2.306464 2.505316 2.662383
-0.243250 0.359897 0.521676 0.699893 1.005116 1.271071 1.694794 2.008687 2.440679 2.593828
-0.300924 0.394176 0.559419 0.899409 1.454448 1.708566 1.869825 2.116095 2.376539 2.493592
-0.153405 0.251763 0.392574 0.866089 1.104658 1.286553 1.780043 1.916997 2.532174 2.688015
-0.279453 0.326159 0.753633 1.333374 1.499514 1.626480 1.898852 2.038525 2.500726 2.702071
-0.170059 0.229176 0.395854 0.705543 1.082349 1.588065 1.821443 1.949022 2.120108 2.537716
-0.202145 0.274872 0.419107 0.608489 0.758495 1.603432 1.748277 2.189578 2.559336 2.730653
-0.177888 0.251468 0.365661 0.658086 1.634785 1.816726 1.997979 2.183875 2.456958 2.811253
-0.317970 0.468942 0.803601 1.078125 1.370511 1.630999 1.971111 2.226246 2.543508 2.768268
-0.234066 0.324515 0.462757 0.683101 0.779120 1.399880 1.995585 2.098113 2.538242 2.655334
-0.226221 0.390737 0.587891 0.741564 1.148309 1.290898 1.572982 2.116901 2.296227 2.676682
-0.152380 0.275031 0.397732 0.652751 1.329373 1.439312 1.794813 1.940569 2.520664 2.797824
-0.166696 0.251629 0.512274 1.144842 1.315763 1.710247 2.178415 2.460971 2.703738 2.827969
-0.216867 0.347530 0.531282 0.706161 1.126385 1.301329 1.475176 1.901629 2.242013 2.431677
-0.300362 0.482595 0.791226 1.005231 1.156964 1.313455 1.691239 2.006858 2.373111 2.733635
-0.169474 0.255383 0.406046 0.734985 1.442352 1.579575 1.789148 1.957193 2.399133 2.566651
-0.130440 0.237458 1.032166 1.386551 1.711848 1.993258 2.268221 2.439261 2.683283 2.812111
-0.173867 0.278057 0.388656 0.749215 0.960862 1.146135 1.799140 1.979764 2.471783 2.619305
-0.242130 0.340749 0.474654 0.828524 1.328466 1.445245 1.802538 2.204747 2.373101 2.551440
-0.232537 0.347402 0.580048 1.030748 1.297867 1.477044 1.985462 2.164878 2.627119 2.813421
-0.187113 0.520796 0.877184 1.139100 1.389082 1.622317 1.923715 2.144320 2.454348 2.655504
-0.198782 0.276683 0.501229 0.913907 1.081324 1.395372 1.775624 1.940434 2.159949 2.585288
-0.219192 0.432472 0.587263 0.912549 1.202466 1.322625 1.811369 1.992180 2.458299 2.760505
-0.191165 0.276813 0.416963 0.651161 1.167971 1.294155 2.003249 2.230928 2.506110 2.774812
-0.363801 0.518796 0.957361 1.225911 1.566650 1.757756 1.962407 2.115286 2.359997 2.543054
-0.227701 0.362569 0.499430 0.731314 0.922719 1.040854 1.838698 2.164784 2.383067 2.810807
-0.465091 0.619804 0.778037 0.935635 1.093218 1.259037 1.829035 2.206537 2.404214 2.547685
-0.219345 0.331580 0.468701 0.864163 1.221425 1.316478 1.768475 2.078164 2.234895 2.666223
-0.202678 0.257891 0.463059 1.225499 1.595549 1.714423 2.230601 2.403829 2.599305 2.731507
-0.191295 0.292649 0.453931 0.663743 1.147168 1.275622 1.648493 2.119111 2.300099 2.725340
-0.202700 0.296043 0.842652 1.096103 1.432375 1.634580 1.849789 2.019083 2.373823 2.644180
-0.223698 0.286308 0.535549 0.951336 1.583619 1.712827 2.069074 2.228672 2.508621 2.712105
-0.393154 0.609187 1.147735 1.476125 1.660227 2.028129 2.280391 2.450954 2.687946 2.792306
-0.330421 0.541443 0.735477 0.935290 1.088544 1.300043 1.758898 2.291508 2.520235 2.677690
-0.228002 0.342730 0.476697 0.849764 1.368387 1.487565 1.712396 1.973744 2.334383 2.559863
-0.104462 0.175301 0.563572 0.921064 1.173139 1.367029 1.770789 1.951766 2.518901 2.747920
-0.195798 0.262376 0.397584 1.297059 1.483849 1.624630 1.820421 2.042136 2.481635 2.604228
-0.173538 0.223847 0.382154 0.562642 0.874661 1.340042 1.617180 1.932579 2.238320 2.383936
-0.257237 0.371721 0.696634 0.866614 1.045455 1.380460 1.752496 2.066892 2.504906 2.650308
-0.218997 0.321077 0.437617 0.666034 1.306150 1.849231 2.027564 2.199883 2.494261 2.649249
-0.320867 0.453548 0.918076 1.266491 1.422317 1.759869 1.998420 2.173922 2.635097 2.760926
-0.288066 0.410534 0.547460 0.760858 0.863292 1.068351 1.939410 2.167961 2.348114 2.767507
-0.218835 0.407925 0.654818 0.800374 1.153682 1.307829 1.657331 1.988984 2.263141 2.720996
-0.153945 0.202790 0.346143 0.519640 1.071723 1.237072 1.712069 1.893855 2.509996 2.744059
-0.248060 0.319372 0.459918 0.983442 1.443498 1.755178 2.100888 2.226747 2.447411 2.563325
-0.174462 0.227225 0.392742 0.571792 1.079416 1.257366 1.551460 2.042776 2.429302 2.629154
-0.274891 0.362315 0.660508 0.970740 1.151818 1.492509 2.072636 2.222125 2.494909 2.686200
-0.220299 0.317099 0.435591 0.793260 1.562295 1.723726 1.912306 2.110472 2.315517 2.618587
-0.350079 0.511699 0.888658 1.136538 1.502800 1.698163 2.138112 2.327492 2.505197 2.660921
-0.173175 0.286482 0.419571 0.629953 0.747452 1.073798 1.745440 1.887288 2.728362 2.862994
-0.302893 0.357795 0.579776 1.154149 1.373560 1.502096 1.831774 1.992189 2.178385 2.421943
-0.140345 0.186167 0.360424 0.858043 1.324588 1.624322 1.866334 2.036366 2.402471 2.617804
-0.207490 0.275386 0.532026 0.903652 1.559244 1.774707 1.962334 2.362983 2.596218 2.738415
-0.218842 0.320129 0.541623 0.875722 1.067991 1.362399 1.856837 2.024142 2.291054 2.645666
-0.341898 0.421854 0.677264 0.873738 1.018393 1.630494 1.868485 2.019716 2.616580 2.717499
-0.211631 0.278329 0.446819 0.679617 0.882530 1.848991 2.102209 2.280260 2.586273 2.750039
-0.400922 0.636971 0.853016 1.019114 1.364375 1.550804 1.850055 2.119999 2.453786 2.623222
-0.182154 0.242330 0.378923 0.509876 0.716576 1.076135 1.587035 2.069399 2.351207 2.660390
-0.400616 0.546715 0.729647 0.920762 1.100075 1.250132 1.664408 1.856723 2.067945 2.443519
-0.209711 0.304779 0.494008 0.698197 1.296713 1.461577 1.655811 1.885168 2.324920 2.489386
-0.248365 0.299675 0.641181 1.260844 1.683313 1.795634 2.022337 2.219236 2.445410 2.655259
-0.167092 0.244845 0.404157 0.672069 1.004556 1.174641 1.578514 1.897154 2.103236 2.709969
-0.429420 0.514025 0.817076 1.048094 1.187821 1.561651 1.826573 2.032100 2.492575 2.641130
-0.264974 0.350531 0.483895 0.953322 1.415379 1.541498 1.741521 2.171851 2.402443 2.527925
-0.416115 0.686348 1.016333 1.284030 1.627945 1.880349 2.143431 2.282669 2.504877 2.648617
-0.231020 0.416620 0.567188 0.760726 0.955087 1.089751 1.781039 1.967816 2.404279 2.797135
-0.416422 0.567520 0.709693 0.879615 1.302011 1.438085 1.678611 2.054536 2.326361 2.457927
-0.247904 0.324051 0.545383 1.111006 1.266454 1.612279 1.870112 2.027173 2.425991 2.655109
-0.279983 0.344606 0.621600 1.161229 1.307142 1.554450 1.784019 1.936785 2.444710 2.544691
-0.161547 0.223962 0.393255 0.741174 1.202310 1.599192 1.822694 1.937889 2.442478 2.729139
-0.340992 0.431955 0.678217 0.820520 0.999612 1.548630 2.164553 2.310748 2.585979 2.711488
-0.200183 0.279651 0.467745 0.730753 1.426170 1.607139 1.815853 2.220677 2.506455 2.727126
-0.274123 0.333601 0.517799 0.968069 1.665916 2.015026 2.169211 2.290528 2.535899 2.658723
-0.128641 0.167761 0.298260 0.447464 0.821352 1.285100 1.591690 1.879933 2.400984 2.764683
-0.198225 0.285988 0.697225 0.945530 1.135179 1.304018 1.590254 1.943114 2.370953 2.581323
-0.201444 0.271446 0.576127 0.726304 1.159527 1.677334 1.872822 2.127341 2.665189 2.807544
-0.198540 0.257454 0.402737 0.846677 1.689490 1.872412 2.034308 2.301368 2.545100 2.729540
-0.200348 0.278019 0.471514 0.752728 1.057356 1.291805 1.777614 1.916008 2.050356 2.172844
-0.466866 0.645308 0.804067 0.998786 1.191235 1.303931 1.785280 2.063043 2.218678 2.420840
-0.217955 0.321210 0.422194 0.865351 1.405153 1.526771 1.791058 2.088900 2.251039 2.667199
-0.168989 0.497826 1.018345 1.283132 1.493512 1.888380 2.226737 2.418452 2.616832 2.749197
-0.147852 0.218473 0.622343 0.825646 1.034661 1.220457 1.704813 2.051368 2.264302 2.712720
-0.202129 0.285808 0.640153 0.871843 1.173967 1.564865 1.834400 2.062497 2.412487 2.645130
-0.183772 0.259996 0.404816 0.684417 1.383605 1.536056 1.977056 2.169199 2.372324 2.556503
-0.306590 0.365918 0.723737 1.056338 1.191585 1.709401 1.978183 2.126256 2.594741 2.707129
-0.219620 0.295360 0.600693 0.751928 1.012492 1.554688 1.777591 1.936858 2.168459 2.637471
-0.484146 0.588901 0.779655 0.974444 1.078335 1.362035 1.861448 1.968026 2.308413 2.629418
-0.228810 0.270297 0.510434 0.721201 1.241319 1.730974 2.096849 2.211832 2.642499 2.808686
-0.400197 0.579628 1.063821 1.257463 1.434952 1.645068 2.017358 2.268483 2.625254 2.773542
-0.232047 0.335877 0.450404 0.618767 0.762409 0.943602 1.844169 2.391140 2.569963 2.779299
-0.315037 0.423610 0.597448 0.972112 1.370369 1.476900 1.783359 2.042461 2.209021 2.480610
-0.194589 0.300944 0.526012 0.730548 1.193408 1.383086 1.609867 1.882051 2.100633 2.703077
-0.215641 0.294490 0.558585 1.391554 1.487145 1.740600 1.911148 2.277087 2.578133 2.742082
-0.160391 0.226326 0.368755 0.670545 0.912912 1.286570 1.631159 1.807727 1.987079 2.498593
-0.313582 0.634117 0.786900 0.944061 1.309221 1.432287 1.720247 2.096637 2.283214 2.589845
-0.214437 0.264378 0.625288 0.975877 1.451393 1.848655 2.094494 2.248063 2.542408 2.690286
-0.532950 0.968164 1.239348 1.422500 1.673683 1.785201 2.010288 2.200155 2.489732 2.638101
-0.190399 0.270657 0.393327 0.864241 1.117361 1.553286 1.679497 2.236221 2.526322 2.700079
-0.287724 0.467671 0.675841 0.856838 1.284704 1.460878 1.649715 1.913527 2.422638 2.548168
-0.215869 0.300450 0.454163 1.082174 1.280570 1.465769 1.679659 1.869841 2.473902 2.623546
-0.274887 0.330100 0.521274 1.123699 1.527645 1.625993 1.931695 2.090005 2.295751 2.645233
-0.177139 0.223177 0.433328 0.774459 1.097689 1.467517 1.918942 2.134341 2.337195 2.540463
-0.346166 0.429209 0.673089 0.781966 1.198349 1.775370 1.954363 2.186438 2.523312 2.625185
-0.197636 0.296745 0.398712 0.631500 1.583954 1.843578 1.994071 2.173016 2.361743 2.519793
-0.356767 0.538545 0.898397 1.140796 1.519279 1.870556 2.168497 2.427459 2.643928 2.759816
-0.235015 0.349662 0.469548 0.816642 0.998816 1.146467 1.889133 2.097584 2.284986 2.765528
-0.167083 0.224131 0.448491 0.771954 0.948871 1.283667 1.621698 1.998899 2.223248 2.603115
-0.159315 0.217018 0.374226 0.590601 1.105826 1.536441 1.809766 1.960128 2.582005 2.795394
-0.168849 0.234032 0.344667 1.029831 1.622442 1.708285 2.016025 2.179960 2.644139 2.784632
-0.251075 0.442282 0.599669 0.763346 1.115735 1.253234 1.496825 1.992708 2.184264 2.666670
-0.388258 0.473926 0.719990 1.058667 1.198870 1.374618 1.864229 2.002653 2.271742 2.608038
-0.293347 0.422867 0.533090 0.863648 1.464010 1.686465 1.842829 2.008624 2.424518 2.579258
-0.422335 0.661725 1.188673 1.343060 1.557186 1.860452 2.239896 2.431450 2.631923 2.747718
-0.210220 0.335092 0.511807 0.760320 0.952999 1.125991 1.476685 1.647025 2.137411 2.688168
-0.373319 0.450044 0.685548 1.063488 1.214342 1.368881 1.749950 1.871124 2.228036 2.638333
-0.175282 0.247596 0.583289 0.800597 1.137160 1.494047 1.790222 1.974957 2.343536 2.783786
-0.154093 0.244641 0.765316 0.879236 1.262433 1.388927 1.719208 2.139465 2.523177 2.692366
-0.222311 0.296370 0.669831 0.821863 1.017560 1.348925 1.641603 1.852235 2.386204 2.585103
-0.372785 0.531082 0.729578 0.873202 1.002102 1.194509 1.654182 2.163378 2.555067 2.658778
-0.180452 0.250281 0.391345 0.554433 1.111079 1.737542 1.910605 2.127866 2.347054 2.534033
-0.447990 0.697721 0.913809 1.073923 1.398658 1.670558 1.960290 2.195050 2.584428 2.733637
-0.253764 0.410608 0.631333 0.803642 0.949880 1.072389 1.769476 2.303179 2.473513 2.749295
-0.249292 0.446941 0.652687 0.818128 1.175583 1.321675 1.534828 1.927620 2.151897 2.401118
-0.201342 0.301055 0.433733 0.667341 1.394399 1.542142 1.766411 2.222136 2.392138 2.617167
-0.263299 0.393237 0.913686 1.357749 1.580030 1.698507 1.930164 2.135083 2.415503 2.650696
-0.189848 0.308713 0.459867 0.797899 0.949965 1.168427 1.746219 1.919236 2.340878 2.529939
-0.236533 0.300777 0.705293 0.910173 1.158168 1.522892 1.727631 1.847056 2.544899 2.698351
-0.219264 0.293220 0.734905 0.969140 1.364696 1.628075 1.824426 1.921247 2.283403 2.660295
-0.231171 0.417787 0.828086 1.301747 1.563040 1.823547 2.038748 2.195446 2.600171 2.776056
-0.280635 0.391503 0.560168 0.699729 0.849390 1.139817 1.609055 2.003493 2.496847 2.631252
-0.329050 0.484505 0.654854 0.957533 1.414924 1.532367 1.798653 2.132845 2.332577 2.503880
-0.227219 0.317562 0.601344 0.991967 1.260680 1.430395 1.612725 1.766840 2.496056 2.645255
-0.270493 0.315583 0.641937 1.235995 1.409340 1.574822 1.760130 1.902696 2.598899 2.735147
-0.235474 0.326468 0.507399 0.696822 0.844939 1.633632 1.871816 2.063592 2.368254 2.525576
-0.233853 0.361484 0.482226 0.641979 0.992245 1.767823 1.952577 2.472579 2.742913 2.825489
-0.168433 0.243379 0.376538 0.823302 1.489064 1.619584 1.949821 2.203288 2.468309 2.771787
-0.206625 0.282620 0.554762 1.077945 1.286219 1.787257 2.045355 2.207994 2.522847 2.710409
-0.281540 0.359214 0.508755 0.689167 0.780776 1.277647 1.987095 2.102406 2.452824 2.573050
-0.240331 0.408023 0.587761 0.766784 1.268990 1.450068 1.614701 2.027579 2.386559 2.524671
-0.213600 0.378897 0.482559 0.820665 1.293224 1.395614 1.715777 1.852078 2.466446 2.706440
-0.192448 0.262539 0.378679 1.019763 1.468722 1.663670 1.910800 2.391601 2.621746 2.796560
-0.220322 0.364745 0.565226 0.783488 1.013662 1.175116 1.402286 1.885036 2.103704 2.324743
-0.322267 0.390833 0.713492 1.031629 1.156838 1.350887 1.515558 1.694139 2.382654 2.516728
-0.192624 0.294262 0.426181 0.741678 1.498008 1.633347 1.893062 2.059462 2.393665 2.782635
-0.237455 0.354262 0.864239 1.246075 1.666553 1.844678 2.174333 2.351099 2.520290 2.655921
-0.185359 0.302261 0.428703 0.781405 0.947101 1.141955 1.617902 1.761286 2.464616 2.634452
-0.271859 0.354517 0.569485 1.079860 1.240128 1.441296 1.944968 2.053805 2.406507 2.736827
-0.214936 0.298540 0.472345 0.913665 1.080008 1.684282 1.985267 2.173551 2.601519 2.749361
-0.318521 0.444000 0.739244 0.971075 1.303751 1.557191 1.918998 2.197692 2.552225 2.778091
-0.187184 0.266393 0.414559 0.873123 1.122008 1.345856 1.781616 1.932051 2.123625 2.364411
-0.212033 0.437364 0.587744 0.807841 1.008570 1.156068 1.667422 1.813734 2.388649 2.769182
-0.177749 0.231877 0.394438 0.587873 1.018115 1.532170 2.031818 2.176571 2.587458 2.778604
-0.397403 0.572539 1.117765 1.287841 1.469835 1.676483 1.995880 2.232196 2.496431 2.667425
-0.173937 0.259671 0.371889 0.555593 0.908572 1.118222 1.943858 2.087012 2.545553 2.816900
-0.296434 0.458071 0.635222 0.864989 1.198523 1.305471 1.672912 2.015023 2.193002 2.377815
-0.205052 0.312572 0.468685 0.774972 1.212302 1.316262 1.821237 2.193552 2.380352 2.766685
-0.240642 0.281687 0.717545 1.351376 1.501114 1.640455 2.046214 2.216028 2.588688 2.729942
-0.230445 0.421175 0.558602 0.846662 1.051701 1.197214 1.704701 1.838398 2.267565 2.697618
-0.276287 0.327977 0.824738 1.266737 1.373629 1.712792 1.891497 2.121117 2.537629 2.629970
-0.236249 0.310208 0.402132 0.954290 1.542483 1.886318 2.043856 2.203899 2.435931 2.547918
-0.323080 0.525410 0.940102 1.419025 1.732419 1.904886 2.278288 2.399903 2.613800 2.842137
-0.259462 0.384806 0.559454 0.827377 1.079010 1.194629 1.553023 2.150915 2.369416 2.537197
-0.309877 0.458904 0.634515 0.905896 1.340319 1.484136 1.732179 2.044813 2.234578 2.374887
-0.200760 0.267223 0.619798 0.880150 1.341984 1.566789 1.724877 1.834378 2.408354 2.666757
-0.232160 0.325786 0.611845 1.111911 1.277003 1.508409 1.711967 2.103218 2.470657 2.665982
-0.160381 0.206959 0.356984 0.510509 1.122026 1.271899 1.727695 1.943129 2.251421 2.380751
-0.339821 0.413428 0.663411 0.796136 0.920303 1.589702 1.879891 1.995622 2.491309 2.584399
-0.225236 0.289017 0.531590 0.689709 1.348190 1.761804 1.902696 2.175207 2.654910 2.781414
-0.283922 0.449613 0.777624 1.129523 1.487473 1.706799 2.164061 2.402885 2.691872 2.844990
-0.328301 0.439249 0.648655 0.897495 1.049452 1.222028 1.849808 2.229574 2.423163 2.565623
-0.236478 0.488322 0.656819 0.862950 1.144127 1.252241 1.694351 2.068901 2.226797 2.679600
-0.169945 0.258037 0.384767 0.609183 1.121274 1.266086 1.906028 2.054377 2.436068 2.795471
-0.177152 0.233124 0.534434 0.970496 1.404070 1.867414 2.171355 2.381133 2.619262 2.753148
-0.225245 0.323943 0.535205 0.711545 1.030041 1.268317 1.543910 1.921579 2.352057 2.531897
-0.380284 0.516944 0.727113 0.869680 1.061908 1.484627 1.847885 2.176267 2.550710 2.682243
-0.227653 0.311146 0.407614 0.830722 1.390383 1.796577 1.984514 2.172202 2.442702 2.597183
-0.395180 0.597222 0.988635 1.248608 1.649366 1.943305 2.114992 2.281535 2.610845 2.728627
-0.159527 0.253807 0.427177 0.703855 0.920030 1.359209 1.618673 1.774181 2.658938 2.839174
-0.232953 0.317175 0.734127 1.080631 1.332652 1.674943 1.899956 2.046773 2.307884 2.543358
-0.125436 0.171676 0.329679 0.770190 1.288629 1.482675 1.769818 2.055328 2.430854 2.715479
-0.108098 0.175220 0.776302 1.221645 1.460683 1.686249 1.929306 2.193619 2.536986 2.758891
-0.152357 0.202480 0.472758 0.861767 1.159578 1.340969 1.681897 2.048109 2.275054 2.477467
-0.216694 0.273656 0.664155 0.850536 1.153027 1.561670 1.759318 1.901416 2.353101 2.500133
-0.234504 0.329541 0.449717 0.797883 1.290186 1.691782 1.880443 2.100171 2.454967 2.611905
-0.423938 0.621841 0.996723 1.214793 1.409002 1.563377 1.783564 2.010297 2.490150 2.698586
-0.224661 0.325658 0.459910 0.625802 0.808594 0.895832 1.274078 2.111179 2.326505 2.585806
-0.276916 0.361107 0.729423 0.920236 1.053283 1.413110 1.741880 1.962097 2.139800 2.429514
-0.174802 0.232198 0.385912 0.540434 1.262000 1.441657 1.595105 1.943274 2.269839 2.417795
-0.265949 0.330919 0.614312 1.257075 1.438174 1.628356 1.917882 2.077892 2.425421 2.567960
-0.184742 0.272816 0.441616 0.641718 0.815915 1.210558 1.722330 1.942876 2.319698 2.747254
-0.390404 0.468994 0.743751 0.956882 1.081791 1.532303 1.750715 1.909157 2.466230 2.592626
-0.278150 0.353755 0.588139 1.120329 1.521033 1.629736 1.993707 2.192040 2.399567 2.620496
-0.431717 0.694505 1.256024 1.445196 1.671784 1.844456 2.028769 2.200956 2.506360 2.653075
-0.208110 0.276044 0.538093 0.719555 0.900539 1.075355 1.745222 2.086474 2.298600 2.556630
-0.352056 0.531509 0.676701 0.887365 1.282885 1.426632 1.614434 1.945858 2.270688 2.425511
-0.247241 0.356899 0.502519 1.065178 1.284311 1.437490 1.855456 1.992377 2.597541 2.776219
-0.396219 0.473793 0.715289 1.202273 1.346298 1.549130 1.940574 2.082739 2.514755 2.713815
-0.202378 0.285773 0.510159 0.640990 1.020854 1.686414 1.864702 2.133482 2.472249 2.625491
-0.136813 0.196375 0.389204 0.606996 0.826010 1.435725 1.829944 2.110031 2.522891 2.760011
-0.178586 0.265329 0.368903 0.594584 1.563859 1.743534 1.910893 2.088980 2.290832 2.753782
-0.326016 0.474212 0.821872 1.109710 1.491269 1.780679 1.990347 2.151819 2.439284 2.687522
-0.198877 0.303609 0.451495 0.660899 0.772185 1.284705 1.783160 1.923118 2.602735 2.756655
-0.279250 0.410975 0.617113 0.801949 0.990885 1.139677 1.438000 1.937681 2.530952 2.667930
-0.182348 0.288676 0.418208 0.638943 1.372299 1.531009 1.853629 2.058568 2.425537 2.822046
-0.235124 0.297027 0.512992 0.982242 1.579055 1.930478 2.096962 2.225930 2.572915 2.699703
-0.162278 0.215431 0.355780 0.485908 0.932607 1.181318 1.754127 1.988386 2.205810 2.337559
-0.508788 0.685414 0.844731 0.983038 1.244131 1.360404 1.646047 2.084834 2.375165 2.496801
-0.221912 0.310104 0.433571 0.978939 1.478709 1.587503 1.870190 2.010717 2.307807 2.780012
-0.359050 0.649694 1.005623 1.392268 1.637149 1.994024 2.239355 2.474016 2.727591 2.831065
-0.174907 0.277141 0.433141 0.954995 1.167887 1.336923 1.902421 2.052616 2.483944 2.686652
-0.193342 0.297566 0.824802 1.002859 1.285763 1.465909 1.800134 2.073494 2.392133 2.587289
-0.209852 0.288483 0.458682 0.843162 1.202473 1.352796 2.014405 2.202275 2.423702 2.568228
-0.276031 0.338955 0.858149 1.217747 1.357220 1.691136 1.841368 2.176457 2.647222 2.735745
-0.223125 0.303040 0.542560 0.703413 1.109469 1.691790 1.909510 2.043240 2.184955 2.383039
-0.338660 0.434962 0.644715 0.989980 1.142041 1.308641 1.862318 1.996732 2.219202 2.585521
-0.169788 0.227570 0.355680 0.476462 1.249736 1.884793 2.054427 2.245569 2.516757 2.692583
-0.510617 0.730414 1.008300 1.210250 1.460951 1.677387 1.984236 2.201040 2.503259 2.654324
-0.224817 0.351828 0.465847 0.709341 0.827775 0.992719 1.978367 2.142995 2.475303 2.800083
-0.308599 0.506317 0.673098 0.860582 1.161218 1.306099 1.811163 2.021896 2.233070 2.490125
-0.180388 0.242667 0.458646 0.739129 1.098421 1.521511 1.707512 1.853458 2.375659 2.563893
-0.191139 0.259717 0.375119 1.195018 1.535308 1.637017 1.945089 2.126276 2.528158 2.662854
-0.144026 0.195867 0.353543 0.581701 1.048420 1.377425 1.815657 1.969736 2.339863 2.778177
-0.384542 0.545846 0.742643 1.036203 1.274580 1.406237 1.737850 2.169732 2.446560 2.578757
-0.313042 0.444130 0.599720 0.924365 1.567785 1.748672 1.900293 2.194593 2.410541 2.573262
-0.492225 0.752280 1.124936 1.471295 1.758189 2.030974 2.238788 2.397439 2.680130 2.783434
-0.204117 0.347099 0.699998 0.845266 1.234413 1.419863 1.647535 2.080443 2.553390 2.707330
-0.257069 0.400082 0.558347 0.805346 1.259790 1.380823 1.608549 2.124230 2.308452 2.486914
-0.187028 0.318194 0.445217 0.923741 1.268789 1.390301 1.796420 1.931293 2.418538 2.603222
-0.243477 0.326319 0.635481 1.172112 1.360926 1.526662 2.109593 2.260517 2.545032 2.720529
-0.166613 0.243290 0.400708 0.657757 0.842275 1.476511 1.791837 1.950760 2.119370 2.472850
-0.311146 0.353401 0.824181 1.012251 1.149117 1.842349 2.055130 2.218062 2.570268 2.661992
-0.208668 0.283611 0.411201 0.809929 1.517017 1.823008 1.957049 2.229403 2.412596 2.626293
-0.154448 0.334483 0.779457 1.197447 1.370217 1.692002 1.980004 2.409686 2.713983 2.827926
-0.234171 0.317688 0.451503 0.830950 0.995999 1.149839 1.803812 2.310181 2.531615 2.732000
-0.268413 0.427669 0.559871 0.864380 1.275062 1.362920 1.581797 1.689453 2.226263 2.624807
-0.107565 0.142648 0.266262 0.674471 1.151548 1.464128 1.861043 2.141020 2.509385 2.783297
-0.182059 0.241841 0.379523 1.073956 1.618846 1.718260 1.915296 2.047758 2.360928 2.720733
-0.235150 0.374352 0.545815 0.714492 0.870405 1.000816 1.559351 1.984193 2.158182 2.596142
-0.434816 0.514709 0.756010 0.899497 1.037358 1.585142 1.834527 2.000422 2.564235 2.674345
-0.220087 0.341090 0.451896 0.734427 1.391206 1.582675 1.725710 2.141788 2.371107 2.511862
-0.482146 0.706990 1.033285 1.248170 1.467412 1.657558 2.147999 2.343164 2.600856 2.731213
-0.213401 0.322062 0.647358 0.791444 0.977300 1.281320 1.599647 1.939047 2.672620 2.797626
-0.266041 0.338577 0.634659 1.127429 1.295917 1.449033 1.658080 1.796624 2.285728 2.541842
-0.119705 0.174258 0.480098 1.063251 1.273831 1.476888 1.794829 2.119252 2.513047 2.762255
-0.132629 0.207248 0.566178 1.085083 1.427584 1.613863 1.889768 2.150853 2.557229 2.784690
-0.243227 0.327780 0.614668 0.761155 0.956760 1.516306 1.811880 2.030177 2.440252 2.582195
-0.276721 0.454860 0.642970 0.784038 1.148980 1.495704 1.703559 2.045787 2.591550 2.733608
-0.189778 0.287373 0.392353 0.645856 1.447021 1.617951 1.816249 2.137973 2.286683 2.572288
-0.400084 0.558491 0.869949 1.062095 1.467794 1.653306 1.899420 2.128461 2.442747 2.604032
-0.199764 0.300259 0.426072 0.645425 0.897550 1.048949 1.748510 2.273694 2.495239 2.649109
-0.296976 0.548524 0.761769 0.955832 1.233251 1.360741 1.693122 2.106225 2.391505 2.525275
-0.248971 0.399490 0.565645 0.720524 1.301434 1.542758 1.716234 2.124059 2.351786 2.681231
-0.230842 0.287955 0.878785 1.471322 1.627007 1.798878 2.005181 2.197775 2.563907 2.690549
-0.176416 0.248403 0.402172 0.733179 0.912580 1.227444 1.694562 2.088653 2.427226 2.563010
-0.330895 0.394275 0.774692 1.201779 1.321842 1.534733 1.782019 1.938050 2.422893 2.563017
-0.227080 0.299503 0.577295 0.756890 1.417382 1.624050 1.795338 2.177707 2.440812 2.572784
-0.411173 0.652311 1.207281 1.442451 1.795401 2.003085 2.140804 2.292980 2.639630 2.785365
-0.332277 0.425121 0.639151 0.821829 0.917909 1.367536 1.826675 1.939314 2.535595 2.654182
-0.345400 0.534948 0.689404 0.928224 1.433841 1.640941 1.825449 2.051581 2.274575 2.418295
-0.141590 0.233113 0.380526 0.868351 1.172524 1.363081 1.874782 2.001448 2.669736 2.855042
-0.309644 0.355571 0.694245 1.252006 1.460701 1.577178 1.853145 1.978370 2.227714 2.570337
-0.181796 0.242419 0.465928 0.715655 1.132014 1.662718 1.850134 1.972773 2.184021 2.722527
-0.270338 0.338307 0.544290 0.711724 0.871287 1.703598 1.918408 2.093313 2.668494 2.765585
-0.150135 0.233584 0.336008 0.740881 1.603784 1.723020 1.936836 2.077330 2.611782 2.783379
-0.294465 0.456340 0.870538 1.062801 1.291659 1.616175 2.070689 2.369390 2.648605 2.779945
-0.220578 0.311705 0.491111 0.847979 1.008368 1.532076 1.849702 2.005101 2.512156 2.669189
-0.229638 0.339951 0.513064 0.716308 1.121176 1.256758 1.479075 2.121337 2.503285 2.662824
-0.160524 0.210553 0.362234 0.595417 1.110208 1.477620 1.653645 1.883754 2.439740 2.625662
-0.236615 0.430340 0.682470 0.856444 1.159709 1.515913 1.944281 2.332831 2.633186 2.783526
-0.208672 0.301280 0.471802 0.926610 1.098592 1.288875 1.519452 1.800256 2.105532 2.428804
-0.243004 0.379283 0.831427 0.991746 1.231060 1.393310 1.679725 2.091152 2.354981 2.528458
-0.149934 0.192836 0.336118 0.489287 1.278027 1.443086 1.737711 1.939793 2.258510 2.725935
-0.162158 0.237674 0.813115 1.431297 1.690841 1.974269 2.228385 2.387649 2.645607 2.800036
-0.196527 0.310980 0.462098 0.736718 0.837132 1.268534 1.708387 1.848473 2.433059 2.576944
-0.217349 0.293339 0.438216 0.968725 1.350504 1.532480 1.911129 2.082089 2.268517 2.522732
-0.172105 0.253481 0.450363 0.927945 1.249256 1.437596 1.922782 2.218348 2.523926 2.733317
-0.289228 0.446047 0.832892 1.123024 1.277186 1.474382 1.792564 2.096649 2.561362 2.797590
-0.214142 0.283470 0.516137 1.061346 1.260972 1.417097 1.665641 1.862087 2.187452 2.353608
-0.235527 0.492936 0.614052 0.859127 0.993761 1.190535 1.848411 1.973235 2.500443 2.746547
-0.143271 0.207291 0.331889 0.827028 1.406412 1.555136 2.045910 2.231114 2.689514 2.839109
-0.343742 0.496860 0.865166 1.285087 1.588995 1.756794 2.022431 2.211289 2.468649 2.662665
-0.213309 0.328675 0.455568 0.723514 0.874048 1.082530 1.853818 2.038906 2.260788 2.778839
-0.356471 0.536984 0.755721 0.903361 1.038099 1.226007 1.687762 2.156339 2.420844 2.542644
-0.281664 0.451610 0.591581 0.828915 1.326665 1.477284 1.708022 2.017509 2.266128 2.700127
-0.135742 0.202004 0.583681 1.273102 1.602365 1.942380 2.228707 2.450342 2.728373 2.845988
-0.176935 0.288677 0.440469 0.786770 1.012958 1.172754 1.752038 1.913637 2.366577 2.766438
-0.207276 0.322804 0.788604 1.062222 1.294802 1.485775 1.944748 2.180022 2.397073 2.598545
-0.258418 0.319098 0.442127 1.133408 1.649338 1.854417 1.994251 2.185084 2.363409 2.534653
-0.230448 0.768093 1.180265 1.433576 1.687255 1.978844 2.259606 2.452430 2.659127 2.786279
-0.211701 0.332064 0.697403 0.880507 1.102252 1.277927 1.808607 2.273983 2.531209 2.736845
-0.245378 0.367568 0.512696 0.766674 1.343265 1.519747 1.697079 2.028107 2.215378 2.381457
-0.221209 0.324945 0.580820 0.748228 1.178564 1.431153 1.585928 1.927918 2.511054 2.643255
-0.201716 0.269175 0.401778 1.244589 1.471872 1.604627 1.805637 1.992744 2.610885 2.752593
-0.160780 0.247690 0.362958 0.624009 1.013756 1.182001 1.581983 1.735927 2.415792 2.646241
-0.320217 0.438376 0.710346 0.878476 1.032132 1.508649 1.972158 2.150849 2.428882 2.559870
-0.229810 0.276051 0.623852 0.830087 1.321297 1.854677 2.155401 2.284792 2.546209 2.690175
-0.172343 0.516169 0.866716 1.177175 1.468063 1.699344 1.986666 2.212830 2.511703 2.739129
-0.301807 0.360652 0.549602 0.672645 0.818574 1.362279 2.098253 2.278909 2.509794 2.695143
-0.294974 0.528192 0.672468 0.856772 1.265640 1.393603 1.638102 2.013275 2.218602 2.565642
-0.169196 0.238150 0.410484 0.644996 1.213738 1.372823 1.800122 1.969874 2.449498 2.615088
-0.184333 0.260633 0.376102 1.023515 1.545709 1.640728 2.037188 2.208164 2.488002 2.744323
-0.205806 0.304865 0.436462 0.616734 1.126032 1.261522 1.725527 2.275740 2.464199 2.702123
-0.184070 0.318390 0.717474 0.865476 1.106500 1.361536 2.038210 2.231225 2.554333 2.779851
-0.246294 0.360790 0.538254 0.736709 1.529013 1.795377 1.952814 2.142384 2.364128 2.495169
-0.353866 0.494646 0.877256 1.112783 1.566844 1.730636 2.025508 2.291163 2.453412 2.592313
-0.266813 0.432427 0.627311 0.754824 0.905537 1.197394 1.729117 2.123791 2.612331 2.827337
-0.273873 0.325959 0.540600 1.115405 1.498701 1.606801 1.814584 1.961539 2.188053 2.581605
-0.080925 0.099600 0.276658 0.947658 1.291923 1.611810 1.910613 2.219380 2.537903 2.797293
-0.168058 0.226944 0.705184 1.118312 1.428461 1.627351 1.878361 2.102812 2.397762 2.613552
-0.257821 0.370068 0.510355 0.878371 1.064949 1.223791 1.796480 2.039854 2.276323 2.505472
-0.243671 0.302629 0.595985 0.730818 1.062394 1.558183 1.727802 1.887397 2.590876 2.710615
-0.211122 0.278412 0.520693 0.699430 1.097533 1.812529 1.983523 2.189366 2.429825 2.610746
-0.256155 0.564923 0.839859 0.987034 1.191276 1.647157 2.021784 2.266855 2.558850 2.704555
-0.202989 0.292278 0.435910 0.640810 0.806537 0.924136 1.535334 2.086372 2.299823 2.572501
-0.261418 0.340324 0.627433 1.013276 1.180897 1.361209 1.731180 1.903731 2.106233 2.555098
-0.183272 0.269138 0.450407 0.909918 1.188568 1.381279 1.745735 1.872820 2.365239 2.484744
-0.230426 0.280037 0.644137 1.434869 1.666206 1.796575 2.015246 2.157224 2.561916 2.707798
-0.227013 0.347868 0.525371 0.707399 0.880208 1.091634 1.654713 1.951332 2.177455 2.319267
-0.380861 0.446326 0.749128 1.201643 1.336943 1.503446 1.800630 1.947582 2.527910 2.700466
-0.315223 0.375610 0.564441 1.017919 1.552234 1.710374 1.873741 2.122288 2.299878 2.473435
-0.446116 0.664203 0.984542 1.279400 1.574979 1.727934 1.978897 2.175567 2.469185 2.631008
-0.221571 0.330656 0.499929 0.777432 1.028387 1.180617 1.640596 2.168791 2.367015 2.714387
-0.421994 0.632233 0.778145 1.001218 1.346201 1.466628 1.720295 1.964067 2.152128 2.372888
-0.163687 0.242822 0.347278 0.971370 1.516739 1.620115 1.816941 1.949014 2.443334 2.638176
-0.284949 0.352677 0.685252 1.135143 1.255140 1.560889 1.905396 2.035214 2.547256 2.683043
-0.177362 0.243130 0.452833 0.824266 1.135565 1.520115 1.813864 1.958746 2.294091 2.563724
-0.178458 0.242386 0.592702 0.788280 1.051353 1.502905 1.934975 2.183628 2.477003 2.654310
-0.259519 0.407690 0.538212 0.728451 1.390298 1.713874 1.876895 2.109781 2.420753 2.577065
-0.255216 0.310327 0.589176 1.157266 1.687747 1.925407 2.045142 2.222504 2.425083 2.548028
-0.164446 0.206868 0.378009 0.525559 0.944579 1.419792 1.613300 1.889685 2.292641 2.565572
-0.240619 0.406939 0.588886 0.735213 1.146793 1.389773 1.537737 1.878402 2.297976 2.552226
-0.289310 0.418786 0.620314 0.764899 1.239942 1.612628 1.827524 2.107944 2.485462 2.639007
-0.198771 0.253637 0.405678 1.048168 1.663883 1.766039 2.128211 2.283365 2.560190 2.709800
-0.165963 0.230669 0.375008 0.692069 0.959835 1.378579 1.760825 1.948801 2.081418 2.369799
-0.523510 0.686129 0.825335 1.033919 1.330937 1.444794 1.739869 2.062844 2.315205 2.450730
-0.293681 0.417926 0.595503 0.957896 1.404495 1.522162 1.884014 2.096933 2.301269 2.621891
-0.359283 0.604669 1.076288 1.248249 1.451793 1.744413 2.125184 2.431489 2.687730 2.799316
-0.156185 0.235581 0.552175 0.813130 1.154557 1.326329 1.861696 2.153380 2.503796 2.787362
-0.290411 0.440558 0.736912 0.889007 1.171361 1.470366 1.794734 2.061516 2.373978 2.626041
-0.224936 0.320946 0.527542 0.738900 1.255619 1.428610 1.871090 2.256589 2.480524 2.694434
-0.288975 0.352962 0.777218 0.955880 1.109873 1.594800 1.813598 1.955710 2.589302 2.714964
-0.213548 0.285746 0.635954 0.830113 1.233322 1.591243 1.839168 1.977797 2.191863 2.623667
-0.336902 0.465806 0.655656 0.935793 1.068579 1.275847 1.761107 1.886493 2.444770 2.653299
-0.178879 0.258874 0.377390 0.527403 1.357599 1.761048 1.949090 2.163795 2.596422 2.759195
-0.430143 0.622963 0.955719 1.182584 1.497132 1.720157 2.044968 2.255285 2.544050 2.680998
-0.213810 0.308853 0.412187 0.569347 0.698344 0.951238 1.880619 2.207829 2.428571 2.828730
-0.230078 0.350112 0.747969 0.974442 1.265182 1.407146 1.813877 2.069124 2.247230 2.451871
-0.161458 0.227385 0.387324 0.640232 1.277813 1.478011 1.725217 1.915041 2.125833 2.645182
-0.200302 0.251181 0.381966 1.303694 1.547137 1.662388 2.120598 2.270182 2.603139 2.775037
-0.143149 0.204983 0.349581 0.667355 1.054734 1.399807 1.727708 1.850109 2.047799 2.715549
-0.337070 0.484021 0.803330 0.985730 1.331585 1.542266 1.830512 2.086973 2.445274 2.632911
-0.215583 0.269471 0.606879 0.945487 1.515635 1.750218 1.939935 2.174549 2.408151 2.576074
-0.534065 0.863487 1.372366 1.575333 1.866659 2.070622 2.218716 2.368585 2.634956 2.716254
-0.237658 0.350270 0.489196 0.956466 1.150453 1.341383 1.448597 2.345953 2.655585 2.785735
-0.233020 0.367323 0.713299 0.877999 1.226884 1.412189 1.743848 1.959402 2.416964 2.595603
-0.134934 0.190506 0.457228 0.942655 1.200550 1.509494 1.748249 1.912543 2.326213 2.742656
-0.297757 0.342592 0.625651 1.192568 1.540655 1.652384 1.875775 2.074460 2.224137 2.465967
-0.177286 0.234207 0.389716 0.517516 1.264974 1.424653 1.878090 2.150100 2.343577 2.537476
-0.281819 0.367413 0.659188 0.765361 1.004368 1.501384 1.726113 2.194951 2.534788 2.645854
-0.180979 0.252107 0.389029 0.570917 1.209940 1.699305 2.111361 2.224160 2.447867 2.620250
-0.256330 0.426903 0.826318 1.152683 1.487139 1.915114 2.246737 2.487453 2.705023 2.815420
-0.195539 0.316745 0.452617 0.833168 0.960504 1.269064 1.879314 2.025539 2.474377 2.680723
-0.203505 0.369568 0.536367 0.778820 1.088933 1.243750 1.588708 1.823497 2.020053 2.594631
-0.156418 0.198956 0.346275 0.496071 1.022702 1.572819 1.753592 2.143215 2.439211 2.674470
-0.160863 0.247666 0.345815 0.841020 1.523112 1.638256 1.887324 2.031339 2.509810 2.718796
-0.258214 0.480809 0.650419 0.801775 1.142337 1.283943 1.504959 2.054206 2.225835 2.474616
-0.303681 0.412740 0.649849 1.086617 1.266890 1.447470 1.896224 2.075119 2.565787 2.741747
-0.271067 0.413984 0.597954 0.768944 1.247881 1.606107 1.786404 2.085376 2.326363 2.529854
-0.521626 0.811390 1.129336 1.284608 1.629969 1.909728 2.228029 2.368756 2.570103 2.697107
-0.303633 0.421526 0.573677 0.925024 1.125497 1.258550 1.501212 1.610013 2.249352 2.608832
-0.411522 0.503523 0.746692 1.046522 1.172005 1.384521 1.797259 1.900603 2.387578 2.660719
-0.175711 0.239782 0.620582 0.952051 1.278311 1.501826 1.917072 2.130700 2.368785 2.608122
-0.164631 0.422501 0.724319 0.950544 1.214644 1.491261 1.799734 2.067799 2.473726 2.757283
-0.193259 0.281162 0.690376 0.855405 1.232753 1.402146 1.689327 1.991274 2.228334 2.435353
-0.301425 0.429993 0.650401 0.873662 1.008503 1.369274 1.690750 1.825918 2.520079 2.683664
-0.155700 0.201237 0.338696 0.505340 1.147916 1.472901 1.941300 2.074514 2.326431 2.663368
-0.350326 0.535475 0.827403 1.201270 1.427031 1.581852 1.963067 2.220906 2.472991 2.668217
-0.279035 0.416052 0.604816 0.794888 0.990688 1.105072 1.420018 2.166296 2.539337 2.676318
-0.278246 0.394509 0.777126 0.921607 1.080479 1.281224 1.433634 2.046850 2.283781 2.454104
-0.158340 0.199119 0.354050 0.555065 1.177314 1.442096 1.685385 2.144139 2.396032 2.716012
-0.247102 0.317737 0.855614 1.333153 1.454453 1.787157 1.970697 2.269614 2.586000 2.679846
-0.202515 0.257270 0.542126 0.724324 0.933997 1.317188 1.717435 2.091303 2.303481 2.469447
-0.295032 0.375581 0.775220 1.057728 1.185439 1.521116 1.807145 1.955630 2.459124 2.631564
-0.266524 0.353178 0.553809 1.043318 1.444903 1.560508 1.829729 1.962933 2.504864 2.699633
-0.392075 0.574661 1.110281 1.317280 1.473545 1.883432 2.051877 2.263410 2.613387 2.737894
-0.168326 0.277952 0.453865 0.702950 0.855434 1.035959 1.678564 1.811649 2.430121 2.811216
-0.301453 0.416493 0.552087 0.857890 1.446563 1.610970 1.775934 2.104633 2.298771 2.438580
-0.296445 0.422883 0.572322 1.053033 1.294027 1.427183 1.752752 1.892326 2.450076 2.720985
-0.291284 0.337800 0.787813 1.245129 1.350343 1.575395 1.771522 2.054749 2.520469 2.632047
-0.138710 0.200016 0.384208 0.667517 0.930105 1.493340 1.923603 2.079511 2.389298 2.733779
-0.280864 0.419489 0.614429 0.763022 1.011923 1.456038 1.644559 2.246694 2.668232 2.789516
-0.145213 0.217524 0.328786 0.706480 1.529301 1.661988 2.106773 2.330515 2.581680 2.792686
-0.265809 0.345868 0.597082 1.070990 1.497116 1.633533 2.139627 2.280686 2.512817 2.668144
-0.208788 0.353537 0.448428 0.744542 0.832763 1.081624 1.871188 2.032083 2.429608 2.599530
-0.238916 0.386378 0.542985 0.766669 1.174876 1.281048 1.635077 2.080947 2.247664 2.488499
-0.203556 0.321547 0.427750 0.977606 1.419067 1.509630 1.819297 1.946189 2.580163 2.776386
-0.139996 0.214290 0.381653 0.921888 1.276433 1.581217 1.904101 2.138537 2.662439 2.833853
-0.212852 0.314107 0.462617 0.919913 1.063259 1.256340 1.466783 1.677489 2.033592 2.181966
-0.466600 0.630996 0.782487 0.940455 1.238899 1.391865 1.580807 1.885579 2.314316 2.461513
-0.227025 0.350571 0.564570 0.792724 1.354349 1.541346 1.801883 2.207919 2.410212 2.682787
-0.249981 0.396397 0.985691 1.264822 1.534123 1.871221 2.123754 2.286134 2.517526 2.674066
-0.177530 0.299649 0.406845 0.735920 1.226985 1.334179 1.570608 1.724780 2.559215 2.784411
-0.331581 0.410000 0.675272 1.110025 1.255576 1.427242 1.924905 2.045160 2.303923 2.638796
-0.210022 0.302618 0.477941 0.890428 1.097541 1.628245 1.909906 2.220072 2.508520 2.652118
-0.243446 0.420405 0.781875 1.124911 1.345163 1.548171 1.986124 2.256316 2.655998 2.839208
-0.200937 0.269954 0.466285 0.792334 1.180229 1.434359 1.791176 1.944075 2.077160 2.197213
-0.251311 0.446771 0.586446 0.941160 1.156270 1.303306 1.672045 1.830703 2.385130 2.761692
-0.176967 0.213758 0.376271 0.498915 1.047907 1.738519 2.144585 2.257100 2.630427 2.811560
-0.352772 0.503472 0.939563 1.201270 1.506542 1.660120 1.860724 2.068816 2.441126 2.640996
-0.178023 0.303052 0.386553 0.624462 0.745438 0.945475 1.851506 1.982051 2.478715 2.678062
-0.364266 0.492788 0.670783 0.846141 0.981327 1.137049 1.747901 2.123325 2.278768 2.451425
-0.194628 0.412302 0.576670 0.847302 1.093833 1.250221 1.832799 1.978334 2.268735 2.705748
-0.210126 0.261821 0.730491 1.414850 1.596688 1.714047 2.240294 2.394580 2.609061 2.726773
-0.269651 0.402612 0.565711 0.760525 0.889819 1.107327 1.796638 1.997957 2.232105 2.568438
-0.133808 0.231770 0.964886 1.241597 1.484042 1.687250 1.909900 2.150489 2.488549 2.709142
-0.306823 0.378775 0.528651 1.056677 1.597646 1.784457 1.922205 2.165550 2.402629 2.533249
-0.406081 0.580663 1.171379 1.458297 1.720903 1.880717 2.213995 2.369466 2.530713 2.666970
-0.228294 0.391754 0.668996 0.852912 1.156334 1.293279 1.648848 2.231024 2.414612 2.628285
-0.302709 0.472535 0.626855 0.843574 1.352641 1.488643 1.688728 2.088022 2.315798 2.484648
-0.174773 0.243410 0.746413 0.964816 1.191099 1.363990 1.763375 2.002057 2.265912 2.600431
-0.208518 0.277532 0.471186 1.268798 1.353448 1.735767 1.868117 2.374184 2.641977 2.776723
-0.181223 0.240142 0.433185 0.698630 1.302639 1.456283 1.718530 1.991528 2.237981 2.340398
-0.351292 0.440375 0.723077 0.926148 1.074170 1.439999 1.696850 1.901716 2.300430 2.453901
-0.226417 0.295615 0.571000 0.984080 1.315950 1.698856 1.941891 2.121713 2.342505 2.579999
-0.380156 0.575056 0.932765 1.215036 1.441177 1.764868 2.084529 2.309314 2.649989 2.795048
-0.327618 0.406456 0.591362 0.776642 0.880344 1.202380 1.954155 2.143987 2.351308 2.562503
-0.349506 0.502746 0.667403 0.858540 1.006257 1.182652 1.744117 1.942048 2.263027 2.631113
-0.177120 0.223929 0.376392 0.517683 0.980327 1.245272 1.809519 2.111620 2.342282 2.674853
-0.123205 0.175349 0.396680 1.076230 1.369038 1.673956 1.959621 2.213420 2.585626 2.780840
-0.199931 0.299170 0.450172 0.705023 1.188319 1.349840 1.579504 2.154568 2.351041 2.525566
-0.302167 0.465527 0.626305 0.861772 0.982600 1.308182 1.952424 2.093800 2.477514 2.675986
-0.242409 0.306396 0.609503 0.781681 1.304327 1.721020 1.925053 2.059600 2.219491 2.531271
-0.355459 0.562814 1.005674 1.276256 1.699547 1.938826 2.256737 2.427235 2.599155 2.727721
-0.151530 0.250374 0.398298 0.598018 0.779517 1.173799 1.570201 1.708674 2.564516 2.838232
-0.220397 0.279236 0.757790 1.106570 1.277089 1.577301 1.822237 1.978751 2.121441 2.474720
-0.153326 0.218116 0.394366 0.701525 1.051329 1.626441 1.887066 2.073879 2.602080 2.787764
-0.234610 0.396895 0.841428 1.067362 1.368124 1.669319 1.979920 2.264168 2.548149 2.700534
-0.210859 0.310938 0.499147 0.721086 1.174085 1.319358 1.795112 2.119739 2.328704 2.523434
-0.205900 0.309942 0.473488 0.788729 0.910899 1.492677 1.711470 1.896973 2.451938 2.620192
-0.228664 0.320277 0.483685 0.662193 1.183931 1.743195 1.934444 2.129302 2.472394 2.610315
-0.308768 0.504829 0.834602 1.135142 1.422684 1.603830 1.804246 2.039329 2.434630 2.712164
-0.195372 0.307825 0.510685 0.705293 0.862776 0.987472 1.561941 1.940733 2.431850 2.813875
-0.306758 0.363734 0.676055 1.018763 1.123399 1.370232 1.612188 1.792290 2.051896 2.212304
-0.175686 0.229897 0.430909 0.821342 1.267737 1.439041 1.813710 2.050941 2.367020 2.513483
-0.270387 0.314704 0.625717 1.328248 1.485768 1.648429 1.945037 2.074570 2.558789 2.681083
-0.150545 0.249063 0.484485 0.650722 0.926307 1.336973 1.578609 1.727988 2.372974 2.800106
-0.451543 0.550287 0.774083 1.017766 1.117810 1.452119 1.851289 1.956638 2.541998 2.714928
-0.303976 0.365108 0.645290 1.163674 1.649225 1.816629 1.956898 2.167435 2.334752 2.499609
-0.258346 0.804804 1.233083 1.450024 1.793938 1.975438 2.178153 2.350853 2.545268 2.695382
-0.305873 0.411332 0.559751 0.770260 0.870638 1.070601 1.844362 2.171189 2.331380 2.561172
-0.328067 0.572423 0.818346 0.977873 1.251504 1.396022 1.679055 2.003477 2.202890 2.376892
-0.233685 0.324374 0.505263 1.162727 1.383328 1.533712 1.921509 2.038933 2.644680 2.830387
-0.368811 0.446580 0.830711 1.314440 1.454376 1.633636 1.932315 2.093222 2.523433 2.696884
-0.225386 0.331700 0.499419 0.651259 1.081776 1.536183 1.684810 2.115502 2.326023 2.493957
-0.223044 0.298517 0.436019 0.582229 0.785616 1.768538 2.059742 2.207026 2.494017 2.696171
-0.180285 0.258337 0.369821 0.519766 1.426414 1.652781 1.844922 2.044342 2.221032 2.715648
-0.283330 0.386958 0.793201 1.012390 1.401661 1.814923 2.032214 2.252691 2.478442 2.623605
-0.192303 0.289501 0.500660 0.766599 0.927796 1.379237 1.761645 2.133602 2.524890 2.706929
-0.240366 0.425376 0.713195 0.854560 1.062811 1.239666 1.453114 2.086242 2.409526 2.579680
-0.137084 0.190186 0.315294 0.519061 1.348977 1.578096 1.776272 1.932718 2.478330 2.764053
-0.256575 0.299517 0.557847 0.772199 1.734591 1.838024 2.175501 2.380904 2.586733 2.722357
-0.152502 0.184110 0.342575 0.500794 0.869142 1.091892 1.283627 1.913051 2.078861 2.216081
-0.422116 0.624411 0.936013 1.075293 1.214093 1.394857 1.793604 2.068743 2.420462 2.621433
-0.172110 0.265160 0.376968 0.872523 1.415505 1.522936 1.876576 2.026326 2.412597 2.784541
-0.206316 0.484509 0.867999 1.264771 1.619155 1.941304 2.179857 2.450350 2.746320 2.859252
-0.183287 0.327870 0.479087 0.793937 1.054850 1.228053 1.799851 2.057544 2.605366 2.808018
-0.199645 0.251567 0.651339 0.845163 1.224263 1.400865 1.849917 2.073362 2.320314 2.465281
-0.172950 0.268061 0.408629 0.749321 1.232382 1.363027 1.833510 1.995806 2.311255 2.818028
-0.383755 0.436949 0.854750 1.093429 1.211736 1.678565 1.897539 2.135411 2.547959 2.639036
-0.206666 0.277792 0.525267 0.971550 1.150633 1.543543 1.818711 1.982032 2.192940 2.418823
-0.297704 0.438877 0.602705 0.935349 1.126380 1.302724 1.887231 2.030156 2.370716 2.648705
-0.225939 0.261133 0.511885 0.708833 1.424678 1.892147 2.104001 2.250163 2.605088 2.746840
-0.452216 0.679332 1.031388 1.239650 1.444390 1.576987 1.800188 2.037662 2.347747 2.559010
-0.246537 0.319428 0.434869 0.567303 0.678662 1.145054 2.156111 2.318698 2.695808 2.850677
-0.323068 0.487001 0.653349 0.909650 1.315899 1.427550 1.843764 2.091482 2.277958 2.521041
-0.151653 0.209991 0.374931 0.854455 1.064290 1.434370 1.854148 1.976154 2.226004 2.750320
-0.254129 0.318082 0.553509 1.223731 1.483086 1.618808 1.995613 2.126498 2.542503 2.704703
-0.159794 0.237065 0.373617 0.681392 0.916230 1.100174 1.782317 1.960086 2.120694 2.618079
-0.395727 0.506034 0.756406 1.188386 1.370570 1.507131 1.860951 2.052892 2.386064 2.617425
-0.235512 0.301393 0.657521 0.969184 1.638320 1.830168 1.984994 2.183324 2.395359 2.538524
-0.451916 0.818196 1.310860 1.494170 1.734505 1.944228 2.085155 2.271405 2.604215 2.715654
-0.229547 0.331804 0.499374 0.698992 1.265974 1.467138 1.658356 2.268601 2.583952 2.762021
-0.258732 0.443700 0.582380 0.800795 1.354913 1.537609 1.724000 2.113993 2.369337 2.558869
-0.156813 0.299295 0.462045 0.796077 1.096063 1.269277 1.836371 1.991867 2.448318 2.597971
-0.246591 0.304473 0.529300 1.215091 1.451169 1.571384 1.868982 1.972518 2.391725 2.695616
-0.169559 0.209107 0.367228 0.505130 1.079358 1.293153 1.736205 2.042985 2.323978 2.564293
-0.329533 0.392210 0.720874 0.936253 1.067646 1.644185 1.991320 2.118407 2.596262 2.701052
-0.201406 0.291786 0.394755 0.617862 1.695417 1.914199 2.049472 2.237494 2.441266 2.568384
-0.115269 0.195387 0.738170 1.042436 1.524313 1.807507 2.173634 2.393265 2.651838 2.824917
-0.173769 0.282805 0.419446 0.776536 0.928220 1.160391 1.958931 2.101699 2.541381 2.732928
-0.209696 0.340593 0.516203 0.794250 1.153989 1.275003 1.570690 1.733317 2.086323 2.795392
-0.110476 0.145162 0.248644 0.465410 1.205115 1.426951 1.838992 2.085791 2.488927 2.779657
-0.223681 0.283712 0.440694 1.041879 1.657659 1.762280 2.000478 2.153137 2.435135 2.637721
-0.178995 0.282691 0.473035 0.740633 0.911089 1.104519 1.288366 1.821180 2.201221 2.508461
-0.443099 0.561309 0.804443 1.033650 1.140498 1.408557 1.973383 2.105087 2.432294 2.654409
-0.222370 0.320892 0.431815 0.774539 1.450421 1.638383 1.817605 2.055496 2.231523 2.414745
-0.488759 0.722119 1.075268 1.294956 1.551912 1.839530 2.130626 2.354921 2.626536 2.737698
-0.209201 0.325492 0.450619 1.020698 1.213389 1.358613 1.538589 1.759768 2.620164 2.791411
-0.254420 0.409271 0.532950 0.933560 1.248401 1.350851 1.728513 1.887503 2.311205 2.707429
-0.039082 0.123291 0.563195 0.857519 1.261207 1.529819 1.850039 2.144420 2.476829 2.755410
-0.127556 0.217058 0.807380 1.043662 1.378203 1.631976 1.940815 2.207962 2.528274 2.764303
-0.214258 0.299923 0.606169 0.768797 1.015893 1.349821 1.669065 1.924581 2.111348 2.418396
-0.364885 0.502482 0.675283 0.930660 1.036461 1.354434 1.834770 1.950661 2.559472 2.726950
-0.221471 0.330609 0.456653 0.686616 1.285861 1.685279 1.842952 2.117269 2.300993 2.591367
-0.347069 0.500335 0.788322 1.022915 1.371254 1.585460 1.855588 2.176902 2.477587 2.720481
-0.281028 0.414603 0.602236 0.792786 0.907330 1.090040 1.687453 2.129718 2.489785 2.634419
-0.363245 0.571116 0.705668 0.861203 1.204113 1.333048 1.544624 2.016192 2.258768 2.434454
-0.215734 0.321274 0.465393 0.666555 1.274668 1.427396 1.670511 2.228318 2.394993 2.624012
-0.270727 0.332361 0.883612 1.283495 1.433436 1.649610 1.838125 2.021889 2.560021 2.698378
-0.175763 0.213621 0.391730 0.566755 0.955973 1.388956 1.878982 2.137460 2.349368 2.478188
-0.257598 0.316184 0.657817 1.118064 1.272143 1.501175 1.689925 1.857456 2.616979 2.735442
-0.227270 0.307771 0.544263 1.030949 1.478367 1.606785 1.851814 2.266798 2.452714 2.629357
-0.255179 0.376313 1.164078 1.383762 1.652706 1.817476 2.014659 2.160928 2.460094 2.623430
-0.274618 0.450301 0.650957 0.842032 1.042329 1.233369 1.641038 1.987714 2.446952 2.597194
-0.337780 0.514835 0.668892 0.911283 1.476046 1.714011 1.887574 2.115985 2.373951 2.499093
-0.172594 0.270224 0.434372 0.864398 1.037663 1.485795 1.748590 2.020761 2.643028 2.800341
-0.270150 0.317310 0.733644 1.342780 1.517768 1.641210 1.845979 1.981779 2.361540 2.595899
-0.160609 0.230103 0.452778 0.853418 1.061340 1.458644 1.711466 1.875295 2.205269 2.709841
-0.302065 0.354507 0.587391 0.684546 0.931120 1.757948 1.902878 2.288464 2.550897 2.656497
-0.142376 0.211224 0.315730 0.534420 1.587988 1.751880 2.118162 2.354064 2.604623 2.786794
-0.386559 0.540492 0.884711 1.083540 1.507785 1.692150 1.931330 2.198611 2.531354 2.678491
-0.323902 0.389328 0.540529 0.671309 0.782921 1.525984 2.046871 2.140001 2.472270 2.566702
-0.227988 0.399979 0.639588 0.791383 1.185694 1.369429 1.655774 2.094051 2.385252 2.754008
-0.140257 0.228630 0.342001 0.596028 1.326401 1.465391 1.823254 1.961877 2.671876 2.831534
-0.121381 0.186129 0.623448 1.000592 1.306405 1.641012 2.056458 2.375989 2.709278 2.848728
-0.247607 0.350532 0.510244 0.883136 1.094021 1.210853 1.639562 2.030725 2.223639 2.416473
-0.357005 0.520431 0.875831 1.062576 1.221746 1.345463 1.623626 2.038524 2.477051 2.698891
-0.179634 0.278991 0.394920 0.736511 1.402026 1.576761 1.774624 1.972434 2.183128 2.757177
-0.203160 0.430851 1.114653 1.371969 1.757116 1.992375 2.261491 2.431952 2.637357 2.752659
-0.138600 0.200975 0.519401 0.724917 1.034246 1.394176 1.722948 1.946633 2.443593 2.716691
-0.298095 0.365805 0.582351 1.086692 1.326009 1.425975 1.844288 2.197476 2.361003 2.521646
-0.224031 0.332426 0.469990 1.001054 1.197837 1.340048 1.959629 2.074407 2.586538 2.799850
-0.217865 0.623928 0.846007 1.056459 1.270022 1.514463 1.916564 2.173644 2.481877 2.731790
-0.216744 0.285870 0.554706 0.993990 1.223763 1.481385 1.841075 2.001157 2.202645 2.554494
-0.183332 0.408012 0.595713 0.854496 1.037244 1.240493 1.858004 2.051789 2.454286 2.641640
-0.185879 0.262800 0.433401 0.963144 1.221951 1.453093 2.083738 2.338219 2.637954 2.802979
-0.376619 0.531366 0.924956 1.260648 1.459226 1.589579 1.913753 2.153929 2.384625 2.568935
-0.276908 0.401698 0.535406 0.725282 0.853962 0.993671 1.784685 2.264235 2.415421 2.743011
-0.392628 0.530015 0.694728 0.898255 1.037465 1.203267 1.847972 2.130377 2.294167 2.519263
-0.221585 0.348013 0.498036 0.715769 1.244234 1.381107 1.612806 2.098989 2.271383 2.656074
-0.181011 0.243672 0.520565 1.273809 1.635579 1.924649 2.152884 2.325189 2.545337 2.704856
-0.212747 0.338170 0.512165 0.698820 1.069232 1.195663 1.594938 1.997384 2.252972 2.771008
-0.239602 0.319299 0.856477 1.177220 1.318502 1.493392 1.741957 2.006496 2.283856 2.495161
-0.228476 0.280840 0.476230 1.203494 1.625636 1.719185 2.032736 2.169601 2.510422 2.699013
-0.286987 0.578563 1.175416 1.489497 1.807057 2.031448 2.224193 2.402210 2.620582 2.786223
-0.284803 0.530975 0.821128 0.972435 1.146598 1.402202 1.828804 2.094299 2.506084 2.720046
-0.245331 0.345077 0.478580 0.845525 1.322977 1.438811 1.722802 2.097265 2.261936 2.441149
-0.170708 0.247004 0.608618 0.775849 1.065513 1.283496 1.723268 1.892396 2.539816 2.717299
-0.208332 0.300056 0.505156 1.253926 1.377427 1.594647 1.754029 2.171773 2.487478 2.685632
-0.171329 0.225179 0.378514 0.577821 1.098665 1.311943 1.526522 1.967713 2.172531 2.346440
-0.239282 0.344225 0.528808 0.666274 1.042444 1.388419 1.857559 2.094835 2.473543 2.649229
-0.198580 0.259051 0.438298 0.705347 1.431453 1.897639 2.046829 2.207600 2.449656 2.599716
-0.337069 0.528000 0.951780 1.180918 1.376423 1.654985 1.971529 2.266927 2.704743 2.847367
-0.284813 0.367338 0.523627 0.691416 0.797885 1.120421 1.819243 2.265148 2.456517 2.588448
-0.269159 0.476818 0.659344 0.899456 1.209541 1.335886 1.627523 1.903299 2.132623 2.655472
-0.119224 0.156658 0.271903 0.418321 1.065297 1.360087 1.644993 1.982627 2.382784 2.755980
-0.282273 0.349303 0.537097 1.066089 1.307982 1.458937 2.037910 2.256912 2.434757 2.578973
-0.201474 0.291056 0.422152 0.616067 1.022184 1.152574 1.449965 2.197085 2.439911 2.635280
-0.324130 0.396121 0.713192 1.073384 1.173029 1.526515 2.037201 2.137280 2.569318 2.702445
-0.199269 0.284170 0.404247 0.697358 1.446027 1.807057 1.954743 2.169169 2.379241 2.545732
-0.348456 0.529109 0.879319 1.101024 1.475230 1.807439 2.081272 2.280127 2.549592 2.702863
-0.184393 0.309059 0.446883 0.786980 0.939533 1.169098 1.804458 1.930933 2.599357 2.810854
-0.372412 0.451942 0.679847 1.075185 1.453546 1.572935 1.797280 2.060904 2.239656 2.413231
-0.162340 0.215690 0.397026 0.885715 1.351665 1.692524 1.923001 2.162159 2.529446 2.710698
-0.174845 0.244687 0.722017 1.058880 1.584480 1.712948 1.914989 2.272779 2.514853 2.721138
-0.180603 0.263970 0.439556 0.797992 1.025300 1.271742 1.843790 2.013992 2.183901 2.609028
-0.275445 0.331708 0.686947 0.880832 1.019790 1.601662 1.815444 1.960055 2.524843 2.635159
-0.246743 0.338623 0.507004 0.744344 0.978588 1.719875 2.149981 2.270511 2.455050 2.609715
-0.511182 0.731278 1.001870 1.154541 1.304543 1.479350 1.855646 2.159073 2.465297 2.619985
-0.159919 0.196942 0.359631 0.506645 0.910908 1.079437 1.605706 2.020672 2.336267 2.675469
-0.400414 0.532831 0.732331 1.013768 1.194337 1.337622 1.760440 1.913653 2.137670 2.495860
-0.198432 0.265271 0.463330 0.715843 1.124005 1.473936 1.785103 1.947760 2.284523 2.402467
-0.251071 0.299335 0.761114 1.358836 1.477322 1.755740 1.974355 2.155204 2.509334 2.610900
-0.168430 0.240238 0.385248 0.642207 0.818665 1.079971 1.497030 1.739210 2.014670 2.480512
-0.403618 0.476427 0.760625 1.119521 1.225260 1.585741 1.910637 2.082695 2.602596 2.728042
-0.270110 0.353552 0.507117 0.982357 1.452637 1.561604 1.831119 2.097015 2.260480 2.506040
-0.409239 0.594796 0.975401 1.298743 1.696566 1.869597 2.021276 2.210722 2.513551 2.654084
-0.264683 0.461411 0.644817 0.860983 1.044619 1.166400 1.802711 2.091425 2.295669 2.754119
-0.469686 0.613125 0.780126 0.980941 1.398148 1.536063 1.747415 2.051727 2.394884 2.516178
-0.186791 0.269819 0.399921 1.138197 1.381467 1.573894 1.960790 2.110781 2.483798 2.628204
-0.258801 0.327749 0.504295 1.197030 1.358461 1.528535 1.792614 1.927747 2.524317 2.681583
-0.161459 0.233374 0.511026 0.740697 0.973203 1.529858 1.845698 2.024509 2.388404 2.769333
-0.338109 0.399145 0.642671 0.750976 0.940491 1.777467 2.157523 2.269354 2.634732 2.724164
-0.180623 0.259965 0.390546 0.612711 1.433871 1.678265 1.843034 2.228297 2.443281 2.647327
-0.247299 0.293271 0.692143 0.919932 1.644451 1.918105 2.097755 2.258082 2.510431 2.625830
-0.149020 0.205904 0.356032 0.602403 0.987977 1.147484 1.771885 1.955289 2.387841 2.798390
-0.232598 0.414291 0.675328 0.818194 1.101627 1.308523 1.519246 1.952980 2.347393 2.695458
-0.176302 0.240703 0.418040 0.744771 1.241784 1.631902 1.803676 1.965041 2.614696 2.812026
-0.147792 0.225066 0.327162 0.749127 1.639390 1.742663 2.031072 2.226257 2.554880 2.737390
-0.153870 0.209078 0.349325 0.617112 0.939783 1.262086 1.603026 1.759135 1.968177 2.111699
-0.401254 0.531884 0.716519 1.042091 1.338740 1.442853 1.814274 2.094864 2.275463 2.451094
-0.257481 0.354612 0.474799 0.889648 1.418879 1.545760 1.780610 2.002306 2.180143 2.532227
-0.145143 0.398917 0.981552 1.314723 1.480195 1.798420 2.069724 2.386944 2.668464 2.802905
-0.178493 0.240401 0.691115 0.837764 1.073179 1.297529 1.642950 2.040266 2.463959 2.622440
-0.283570 0.372001 0.585235 0.956144 1.106750 1.584081 1.860096 2.009870 2.399586 2.562348
-0.173740 0.229082 0.361309 0.554292 1.445623 1.608360 2.083231 2.257294 2.420588 2.616658
-0.324415 0.415954 0.746050 1.011384 1.143615 1.556506 1.921430 2.048417 2.544327 2.700584
-0.214462 0.286094 0.581008 0.805945 1.275261 1.610434 1.794665 1.905601 2.100985 2.530385
-0.406606 0.540199 0.741703 0.841294 1.020646 1.288940 1.697760 1.988139 2.374821 2.589349
-0.202273 0.235653 0.484403 0.754406 1.274678 1.821075 2.241890 2.368887 2.620778 2.800892
-0.270698 0.780374 1.036092 1.204303 1.426576 1.652095 1.944935 2.222209 2.496745 2.678321
-0.229051 0.330732 0.459692 0.687040 0.867860 0.971515 1.553263 2.327103 2.599324 2.733993
-0.260962 0.343168 0.545250 1.036179 1.306217 1.422412 1.660351 2.041101 2.335761 2.495897
-0.171216 0.239743 0.394965 0.588008 1.144698 1.289132 1.673831 1.940258 2.235772 2.782337
-0.195902 0.254449 0.377534 1.406314 1.521423 1.673084 1.866963 2.261663 2.535496 2.688582
-0.150694 0.213444 0.372155 0.787173 1.035226 1.454281 1.699328 1.829446 2.003441 2.525940
-0.232566 0.460472 0.787265 0.996419 1.396693 1.523961 1.855686 2.119370 2.346354 2.515401
-0.233393 0.307066 0.580252 0.812411 1.638408 1.916323 2.050381 2.201478 2.398327 2.532500
-0.654665 1.113987 1.347221 1.518794 1.813315 1.953845 2.210362 2.381661 2.551979 2.660202
-0.223873 0.325731 0.467395 0.921251 1.270288 1.397723 1.734370 2.414313 2.638346 2.800382
-0.310637 0.477608 0.685272 0.996817 1.355825 1.484000 1.704038 2.061930 2.448624 2.565929
-0.148930 0.226761 0.370757 1.019241 1.219213 1.396110 1.661688 1.901830 2.408793 2.697915
-0.229342 0.295527 0.586649 1.059472 1.597702 1.716890 1.937422 2.109084 2.436811 2.674887
-0.192819 0.263035 0.434697 0.673121 1.119753 1.338824 1.909548 2.076183 2.261830 2.387228
-0.320147 0.380189 0.741994 0.844995 1.074712 1.639187 1.762953 2.266267 2.646178 2.721096
-0.174567 0.253745 0.360203 0.504953 1.488396 1.814662 1.955756 2.149395 2.323488 2.584030
-0.263126 0.470251 0.798026 1.161280 1.606556 1.808008 2.130398 2.302959 2.489210 2.752479
-0.231279 0.366009 0.530320 0.804291 0.943863 1.141251 1.962507 2.101760 2.449591 2.815548
-0.172028 0.250238 0.449914 0.861171 1.080449 1.240891 1.585537 1.918091 2.217571 2.722636
-0.131319 0.183681 0.316018 0.523172 0.890644 1.486126 1.758535 1.891187 2.487652 2.765559
-0.165174 0.243169 0.350507 1.016712 1.534247 1.638560 1.932592 2.084107 2.538300 2.689502
-0.262744 0.474699 0.655053 0.795707 1.068818 1.252172 1.418647 1.961010 2.309455 2.536506
-0.359054 0.435831 0.725138 1.118933 1.229842 1.514926 1.879370 2.001037 2.462089 2.652002
-0.218540 0.299734 0.601107 0.823625 1.269799 1.620287 1.839893 1.976756 2.375450 2.640668
-0.487484 0.730967 1.052266 1.258969 1.526405 1.802696 2.229099 2.451538 2.684818 2.774190
-0.235780 0.364477 0.520691 0.749469 0.950595 1.159410 1.423255 1.544612 2.361393 2.766014
-0.366160 0.476136 0.652510 1.062481 1.309788 1.418863 1.784871 1.987495 2.189248 2.558080
-0.184696 0.253223 0.471758 0.830299 1.272428 1.483910 1.761955 2.136740 2.416390 2.620731
-0.128256 0.217552 0.752532 1.013345 1.185988 1.415101 1.811830 2.211505 2.607414 2.789321
-0.247330 0.328294 0.701060 0.927525 1.109801 1.291869 1.638584 1.875516 2.227907 2.417348
-0.261841 0.503729 0.732366 0.870192 1.033798 1.299712 1.693809 2.023705 2.463903 2.789299
-0.165555 0.219912 0.358917 0.505900 1.230885 1.663232 1.852393 2.028502 2.286248 2.725340
-0.426544 0.643468 0.917679 1.196829 1.471597 1.648363 1.933059 2.151933 2.533829 2.705743
-0.308359 0.416322 0.591830 0.808745 0.946905 1.230266 1.815498 2.281895 2.520403 2.631259
-0.269965 0.447323 0.574488 0.763324 1.256417 1.405168 1.571648 1.980676 2.220782 2.442545
-0.188326 0.280970 0.408039 0.646742 1.320810 1.446061 1.615924 2.148422 2.351742 2.514250
-0.241655 0.365356 0.810170 1.309700 1.669576 1.812447 2.014631 2.236122 2.442170 2.609315
-0.191747 0.289189 0.450664 0.748517 0.915409 1.168139 1.584199 1.750548 2.260120 2.447778
-0.215480 0.278055 0.768309 1.041609 1.391676 1.605855 1.766698 1.876725 2.528928 2.706006
-0.216771 0.298936 0.710997 0.862001 1.342336 1.590245 1.886295 2.097920 2.415093 2.592546
-0.359220 0.566823 0.939326 1.372126 1.545352 1.699671 2.041310 2.205011 2.518317 2.710314
-0.305907 0.442295 0.613007 0.776603 0.914320 1.099675 1.615712 1.826869 2.359635 2.622631
-0.323177 0.497481 0.632094 0.852217 1.431198 1.600546 1.791940 2.143530 2.380021 2.560286
-0.276909 0.420019 0.563912 1.000971 1.135252 1.388079 1.711802 1.918572 2.573328 2.752989
-0.353490 0.388981 0.807777 1.276863 1.382826 1.606736 1.810843 1.979129 2.631848 2.733152
-0.211471 0.306166 0.424434 0.581123 0.710913 1.547934 2.010370 2.138366 2.380508 2.503481
-0.225924 0.333197 0.488381 0.801446 1.090937 1.638206 1.799647 2.390310 2.652313 2.790138
-0.171504 0.249271 0.358286 0.870885 1.550123 1.667881 2.054589 2.231743 2.439091 2.602023
-0.165599 0.227318 0.460922 1.107714 1.477735 1.814994 2.062885 2.255887 2.546566 2.715347
-0.204992 0.345256 0.473494 0.712728 0.805809 1.312492 1.893635 2.009686 2.341092 2.479636
-0.241898 0.390228 0.537134 0.715035 1.312338 1.499876 1.662491 2.135780 2.352112 2.532228
-0.163569 0.301194 0.427433 0.764441 1.375596 1.484079 1.850824 1.989487 2.494381 2.667698
-0.185986 0.271128 0.421812 1.063503 1.222027 1.628289 1.811308 2.167184 2.682964 2.795197
-0.202601 0.379588 0.533353 0.730653 1.060008 1.189413 1.598490 1.835597 2.061862 2.426341
-0.381195 0.485776 0.727063 1.085074 1.215649 1.412868 1.615482 1.828196 2.539184 2.686523
-0.196130 0.286997 0.409907 0.696364 1.424577 1.699356 1.891753 2.153448 2.327269 2.685103
-0.217874 0.396132 0.938681 1.246697 1.661963 1.931349 2.246916 2.421796 2.619892 2.750931
-0.145642 0.216508 0.413198 0.862759 1.057682 1.322682 1.673351 1.828806 2.347789 2.651186
-0.252166 0.353210 0.523268 0.998504 1.176163 1.345135 1.984750 2.128958 2.373533 2.721309
-0.207926 0.318108 0.470343 0.848345 0.989299 1.405273 1.967910 2.101386 2.512180 2.676499
-0.305162 0.559986 0.771585 0.960172 1.334408 1.717417 1.924182 2.084417 2.601968 2.796124
-0.215239 0.293295 0.505385 0.962671 1.240775 1.392460 1.797329 1.965379 2.131247 2.276248
-0.252164 0.460717 0.585238 0.895100 1.077276 1.245603 1.770113 1.919629 2.388482 2.774345
-0.171691 0.214222 0.361048 0.500619 0.905993 1.365660 2.191797 2.291635 2.536887 2.788810
-0.210536 0.585917 1.067844 1.305357 1.534407 1.728603 1.950964 2.160461 2.474553 2.655915
-0.169262 0.231674 0.372121 0.532093 0.775314 1.210871 1.829565 2.081870 2.370289 2.704223
-0.343950 0.448128 0.628833 0.913957 1.088899 1.224316 1.766842 2.099926 2.246679 2.400841
-0.241643 0.386851 0.578033 0.893447 1.284732 1.404909 1.839518 2.125416 2.327160 2.739690
-0.241059 0.287428 0.601200 1.273580 1.460278 1.653802 2.095665 2.226476 2.507632 2.651598
-0.212479 0.430242 0.578263 0.750884 0.984798 1.103297 1.564720 1.845357 2.044045 2.707564
-0.267240 0.357278 0.901382 1.173429 1.387845 1.739763 1.960853 2.173315 2.408387 2.570937
-0.216978 0.306711 0.423920 0.791397 1.547660 1.881522 2.025421 2.184747 2.389726 2.510855
-0.309853 0.505477 1.137673 1.452808 1.660808 1.914525 2.084337 2.308435 2.638463 2.772736
-0.301921 0.420539 0.593933 0.887576 1.158301 1.268991 1.788041 2.156468 2.316421 2.507218
-0.293230 0.474574 0.623415 0.798513 1.266075 1.425523 1.764734 1.994016 2.181652 2.456787
-0.267189 0.365075 0.696711 0.927891 1.096450 1.472164 1.765266 1.937224 2.223753 2.655092
-0.238720 0.370663 0.617866 1.246955 1.365777 1.650640 1.856445 2.306366 2.616822 2.765237
-0.175180 0.233649 0.388873 0.625509 1.137464 1.364059 1.780788 1.978889 2.142278 2.269743
-0.363510 0.421032 0.668364 0.762955 0.998948 1.715897 1.877803 2.064237 2.529901 2.608567
-0.207131 0.288224 0.537847 0.889921 1.241448 1.796637 1.982317 2.231362 2.514249 2.666169
-0.311071 0.486542 0.911402 1.324355 1.500183 1.670614 2.142536 2.330931 2.596184 2.778564
-0.286136 0.386970 0.584375 0.911705 1.134588 1.317656 1.852739 2.283740 2.498365 2.622864
-0.253233 0.419082 0.572357 0.778424 1.126703 1.277532 1.807391 2.017696 2.220121 2.576306
-0.119841 0.163781 0.296364 0.661342 1.063342 1.241590 1.856804 2.104475 2.497328 2.762449
-0.134955 0.201314 0.403983 0.934711 1.360477 1.718449 2.065183 2.278684 2.574632 2.753186
-0.187681 0.272074 0.453358 0.682207 1.079560 1.206376 1.499740 2.043148 2.242754 2.665815
-0.313258 0.412019 0.658075 0.828689 0.973583 1.514446 1.981071 2.102741 2.535037 2.681357
-0.255030 0.322348 0.627488 0.839253 1.410591 1.810002 2.038784 2.181294 2.416832 2.562402
-0.419919 0.625767 0.997973 1.218385 1.544616 1.788193 2.193417 2.384323 2.580200 2.698287
-0.144698 0.204991 0.382026 0.623303 0.874762 1.289145 1.707320 1.863261 2.458684 2.750055
-0.348116 0.419496 0.704420 1.093503 1.227121 1.494841 1.778803 1.913492 2.247296 2.428664
-0.150045 0.246799 0.376978 0.783403 1.269598 1.422794 1.903455 2.035588 2.514973 2.759883
-0.105122 0.206614 0.753484 1.038977 1.400140 1.658373 2.030750 2.283051 2.654021 2.837336
-0.192365 0.288692 0.447554 0.818792 0.961011 1.398186 1.770980 1.943311 2.350650 2.500051
-0.262128 0.381361 0.574890 0.709707 1.071672 1.453038 1.732793 1.979241 2.422853 2.645439
-0.182137 0.236372 0.375437 0.738739 1.319942 1.813603 1.942481 2.136125 2.304536 2.660541
-0.388048 0.531674 0.948328 1.154568 1.307573 1.434685 1.768235 2.048136 2.364776 2.585037
-0.213588 0.288434 0.462998 0.598306 0.773371 0.915658 1.452520 2.086025 2.523003 2.722037
-0.255467 0.334344 0.621250 0.810402 0.995432 1.466371 1.709488 1.890365 2.052513 2.247982
-0.202649 0.282992 0.450372 0.652595 1.271305 1.607863 1.769708 1.985229 2.230577 2.380831
-0.255806 0.325628 0.668776 1.230304 1.373533 1.702388 1.962730 2.144556 2.518005 2.640112
-0.164126 0.217024 0.367572 0.604779 0.787116 1.194139 1.683264 1.826517 2.301871 2.524861
-0.374711 0.458954 0.726536 0.920865 1.045916 1.511231 1.712666 1.895532 2.601724 2.708894
-0.321014 0.460345 0.639594 1.017667 1.508099 1.631146 1.864246 2.140150 2.327445 2.508909
-0.451810 0.719234 1.150765 1.385625 1.620547 1.892342 2.068707 2.263104 2.625298 2.740266
-0.317844 0.411108 0.550802 0.761160 0.870205 1.038480 1.695720 2.112903 2.292249 2.451544
-0.321858 0.548379 0.720393 0.955644 1.233322 1.359795 1.685327 1.923628 2.307181 2.544584
-0.211797 0.292996 0.437036 1.171159 1.397378 1.525798 1.701395 1.861517 2.572521 2.757919
-0.334603 0.405956 0.767677 1.215768 1.335601 1.658739 1.989520 2.108465 2.602700 2.719250
-0.236812 0.348424 0.519218 0.665697 1.102403 1.611533 1.819999 2.115185 2.332044 2.604171
-0.212181 0.308266 0.480795 0.705382 0.828843 1.420354 1.886330 2.032387 2.621328 2.767098
-0.156168 0.242178 0.348609 0.550072 1.486404 1.641030 1.904334 2.091753 2.439156 2.809664
-0.232081 0.327237 0.817249 1.194162 1.571594 1.731682 1.910994 2.090434 2.488066 2.694976
-0.166025 0.252998 0.441946 0.686509 0.905928 1.524321 1.747034 1.950457 2.619697 2.805258
-0.196816 0.324035 0.613887 0.796124 1.033469 1.198765 1.570531 2.015231 2.414398 2.745220
-0.152873 0.238362 0.348769 0.790622 1.413327 1.522987 1.899666 2.041945 2.648276 2.825752
-0.238929 0.311579 0.412073 0.915401 1.512444 1.940985 2.178055 2.302141 2.517257 2.635463
-0.160234 0.194261 0.347515 0.460654 0.859252 1.041440 1.658005 1.765106 2.252543 2.312052
-0.391446 0.575762 0.767956 0.913604 1.304424 1.440779 1.667960 1.962669 2.446664 2.573637
-0.213295 0.338515 0.465366 0.911020 1.312069 1.413848 1.864947 2.045811 2.354224 2.763667
-0.170870 0.556857 1.036355 1.381019 1.682662 1.999979 2.319783 2.526350 2.739001 2.850764
-0.208142 0.323528 0.474225 0.911543 1.048694 1.258201 1.966595 2.078676 2.553969 2.814829
-0.162972 0.229629 0.731192 0.902973 1.246076 1.372954 1.693139 2.110582 2.362875 2.555643
-0.197223 0.291057 0.436718 0.707631 1.251503 1.421382 1.926786 2.108784 2.413585 2.596412
-0.188400 0.289822 0.797989 1.142133 1.323120 1.715797 2.074975 2.335066 2.566622 2.712846
-0.176052 0.240463 0.486022 0.736587 0.983507 1.654478 1.892603 2.036521 2.205899 2.540522
-0.285807 0.420951 0.578219 0.937462 1.172738 1.315248 1.698845 1.846953 2.333613 2.500319
-0.191178 0.264476 0.384535 0.632084 1.446016 1.916538 2.114759 2.257365 2.532359 2.669854
-0.585958 0.712547 0.995175 1.345358 1.519221 1.715374 1.913837 2.069254 2.514199 2.672046
-0.232352 0.335589 0.447674 0.661655 0.840293 1.102372 2.111319 2.297768 2.505132 2.794479
-0.293351 0.391184 0.614053 0.997235 1.204180 1.322845 1.746085 2.070938 2.259359 2.492199
-0.128784 0.193380 0.374338 0.847941 1.107813 1.396176 1.796836 1.928700 2.389952 2.702928
-0.187671 0.251167 0.419138 1.154089 1.596401 1.689187 1.941996 2.092773 2.621931 2.795923
-0.148570 0.200662 0.344258 0.538968 0.866249 1.341751 1.759051 1.890255 2.225276 2.769903
-0.345597 0.416970 0.657718 1.108569 1.439934 1.549124 1.811931 2.165143 2.359862 2.480281
-0.260394 0.347444 0.453068 0.867942 1.515797 1.830215 1.974617 2.135238 2.518564 2.622302
-0.467387 0.718460 1.257405 1.516226 1.785886 1.982028 2.277442 2.407989 2.575877 2.697560
-0.254025 0.396915 0.711272 0.826708 1.079490 1.303882 1.532614 2.101023 2.580896 2.726410
-0.251349 0.458227 0.691728 0.853294 1.181701 1.324576 1.553722 2.121741 2.324860 2.537399
-0.193070 0.295330 0.434005 1.028433 1.180760 1.492311 1.774884 1.958905 2.378250 2.514336
-0.328295 0.438707 0.672483 1.098796 1.409689 1.525062 1.957988 2.202692 2.417235 2.626557
-0.171589 0.215360 0.396416 0.549523 1.010817 1.564392 1.776805 2.010598 2.334140 2.489964
-0.318782 0.372964 0.715257 0.808908 1.049817 1.858174 2.008814 2.244447 2.552397 2.638023
-0.201432 0.265508 0.443842 0.655062 1.463954 1.780676 1.989105 2.317647 2.504044 2.729015
-0.089299 0.221502 0.866390 1.161581 1.386624 1.681219 2.037751 2.306655 2.683398 2.842046
-0.212127 0.340083 0.489712 0.702958 0.879220 1.069546 1.931755 2.304789 2.539222 2.833730
-0.328502 0.460793 0.574149 0.923510 1.262431 1.349319 1.540115 1.646239 1.968666 2.558808
-0.151688 0.205453 0.364147 0.726598 1.290329 1.608244 1.900602 2.132843 2.473238 2.714681
-0.185087 0.268618 0.380471 0.858380 1.535920 1.659732 1.871001 2.060741 2.281531 2.743722
-0.257576 0.375609 0.522074 0.806014 0.988781 1.118512 1.619900 2.008108 2.189450 2.503981
-0.400530 0.492365 0.729967 0.986855 1.095728 1.599909 1.935703 2.057853 2.435587 2.582604
-0.223967 0.308358 0.436977 0.810278 1.375371 1.715667 1.876660 2.086799 2.333392 2.482046
-0.356889 0.697785 1.003210 1.181500 1.520050 1.769174 2.060990 2.297507 2.609041 2.761196
-0.157986 0.286402 0.432170 0.759718 1.081482 1.206946 1.688203 1.857653 2.667619 2.834603
-0.196232 0.271155 0.616200 0.987195 1.265761 1.503484 1.745037 1.946600 2.389443 2.562468
-0.150612 0.207932 0.531767 0.924718 1.224167 1.532206 1.868861 2.129974 2.479660 2.745102
-0.159516 0.244552 0.677711 0.957418 1.266300 1.638493 1.929433 2.212544 2.525881 2.712593
-0.311860 0.375573 0.609251 0.741478 0.874235 1.502532 1.759234 1.910133 2.346160 2.464214
-0.272687 0.495052 0.602981 0.936595 1.218033 1.659652 1.783798 2.226628 2.673580 2.789721
-0.182994 0.269489 0.387738 0.559582 1.343891 1.727891 1.917480 2.131703 2.353147 2.525604
-0.308577 0.475904 0.797573 1.025973 1.477364 1.632200 1.868066 2.187647 2.448313 2.609309
-0.206491 0.281366 0.496579 0.711998 0.842942 1.042724 1.626715 2.075674 2.411838 2.577868
-0.326421 0.517351 0.715080 0.911851 1.128611 1.259596 1.539759 1.960615 2.508231 2.630330
-0.225691 0.354477 0.473958 0.715802 1.385094 1.590187 1.774163 2.045280 2.231611 2.620722
-0.243650 0.282149 0.801163 1.454069 1.614695 1.739741 1.936677 2.098900 2.621205 2.730598
-0.175768 0.236613 0.389409 0.747034 0.946387 1.205905 1.739280 1.989798 2.245012 2.388323
-0.387506 0.464495 0.740570 1.128342 1.279681 1.451771 1.809069 1.941649 2.324383 2.652406
-0.231774 0.321631 0.420712 0.846725 1.477615 1.662880 1.835880 2.220722 2.418706 2.624548
-0.339377 0.589871 1.313110 1.506577 1.748224 1.947324 2.102041 2.254806 2.543830 2.680043
-0.341587 0.433858 0.661863 0.821397 0.950863 1.418003 1.784815 1.903400 2.385908 2.575412
-0.345179 0.447774 0.612195 0.945135 1.419677 1.592743 1.773414 2.040871 2.324811 2.437686
-0.181279 0.307819 0.435997 0.934515 1.100027 1.302288 1.693949 1.895047 2.700574 2.825382
-0.310037 0.368350 0.622802 1.178640 1.411438 1.526484 1.919150 2.065079 2.254912 2.589937
-0.150978 0.212352 0.348668 0.573651 1.039486 1.590007 1.846476 1.963984 2.148357 2.662487
-0.277951 0.349703 0.550843 0.708320 0.838864 1.573740 1.810453 1.992371 2.532412 2.642545
-0.153422 0.252689 0.342559 0.686894 1.497196 1.638310 1.961921 2.130271 2.557903 2.742772
-0.279249 0.447383 0.763867 1.059905 1.545382 1.724231 2.031986 2.292812 2.552588 2.796233
-0.230577 0.389164 0.539408 0.761297 0.908015 1.337558 1.872590 2.004078 2.333966 2.727901
-0.232875 0.346443 0.540354 0.678135 1.101040 1.382052 1.587740 2.186049 2.411254 2.607361
-0.178843 0.269153 0.416180 0.638286 1.259337 1.389112 1.680672 1.869557 2.418798 2.781921
-0.238712 0.372837 0.675624 1.027319 1.339343 1.669807 2.074360 2.351022 2.663150 2.815245
-0.215603 0.308405 0.496032 0.940314 1.090508 1.308705 1.583747 1.902325 2.209688 2.576931
-0.291384 0.348946 0.780234 1.202297 1.290327 1.444813 1.575215 1.952612 2.399593 2.483613
-0.198791 0.307267 0.456507 0.669854 1.275490 1.409566 1.731928 2.093564 2.326604 2.772666
-0.166723 0.274518 1.057461 1.415490 1.716962 1.941408 2.139410 2.271877 2.554685 2.755174
-0.179844 0.282631 0.449297 0.722971 0.854062 1.439226 1.833271 2.030343 2.411399 2.580818
-0.194891 0.247057 0.501829 1.004986 1.304934 1.451918 1.799457 2.025853 2.311832 2.422165
-0.192373 0.297404 0.420858 0.940309 1.303418 1.426055 1.949700 2.077238 2.623849 2.795647
-0.284285 0.555560 0.869980 1.055893 1.232747 1.442851 1.823935 2.260258 2.608541 2.799256
-0.182395 0.248334 0.473858 1.064734 1.236328 1.480815 1.718550 1.883271 2.073356 2.512622
-0.293574 0.445666 0.581331 0.774876 0.860972 1.080798 1.894962 2.036530 2.546161 2.753034
-0.164780 0.231139 0.397045 0.799136 1.184762 1.560887 2.082481 2.246203 2.538883 2.722312
-0.427982 0.603539 0.920429 1.129159 1.650391 1.805433 1.997586 2.263608 2.512703 2.626448
-0.168043 0.256064 0.384473 0.655220 0.888834 1.046199 1.879431 2.027056 2.416638 2.713319
-0.426266 0.599810 0.770098 0.938960 1.085997 1.239035 1.780899 2.098691 2.240555 2.451170
-0.206361 0.331236 0.460417 0.809533 1.319919 1.432077 1.699325 1.907851 2.185584 2.791362
-0.172066 0.257009 0.693635 1.290430 1.502260 1.882174 2.058034 2.285835 2.654385 2.780637
-0.170469 0.242710 0.420771 0.673196 1.013631 1.168518 1.734302 2.076408 2.284278 2.777254
-0.231524 0.384268 0.762288 1.075716 1.340044 1.570221 1.844109 2.087904 2.435480 2.609095
-0.234196 0.299491 0.501062 1.074183 1.591896 1.874452 2.075105 2.288231 2.499325 2.625494
-0.469375 0.772069 1.143891 1.321644 1.809933 2.060553 2.352686 2.509836 2.660967 2.746296
-0.267541 0.509192 0.697162 0.881682 1.154246 1.287919 1.732950 2.170277 2.373112 2.701116
-0.225002 0.296925 0.521071 0.868722 1.247262 1.605607 1.862301 1.995077 2.132673 2.303312
-0.182154 0.268818 0.650902 0.829595 1.340290 1.518522 1.678145 2.062000 2.476058 2.618836
-0.262094 0.315377 0.554545 1.249325 1.471511 1.602479 1.859154 1.986339 2.555494 2.716803
-0.159937 0.221544 0.379613 0.703404 1.009260 1.336589 1.634712 1.832112 2.318601 2.492376
-0.317307 0.445696 0.644479 0.865391 1.006145 1.475121 1.860039 1.994490 2.375194 2.696675
-0.243257 0.313667 0.455515 0.804455 1.138675 1.990813 2.199166 2.317604 2.528196 2.655319
-0.149876 0.523035 0.850884 1.130052 1.422386 1.709616 2.052423 2.309997 2.639482 2.816247
-0.295517 0.381331 0.579620 0.758901 0.871645 1.328267 1.986843 2.119635 2.549100 2.680632
-0.291632 0.485587 0.631619 0.928421 1.214008 1.324041 1.814157 2.030748 2.252379 2.749354
-0.139746 0.195222 0.343435 0.703664 1.118059 1.352517 1.752608 1.877596 2.297202 2.717509
-0.243712 0.353375 0.585060 0.914994 1.377929 1.519246 1.980348 2.132954 2.489440 2.702636
-0.176444 0.255300 0.420605 0.747448 1.153758 1.299601 1.683980 2.102983 2.463231 2.667324
-0.252495 0.390591 0.697066 0.966926 1.231424 1.414479 1.867378 2.243706 2.495192 2.656606
-0.272420 0.381655 0.551517 0.888825 1.590308 1.808189 1.943240 2.138959 2.358917 2.487502
-0.336178 0.471630 0.935669 1.201733 1.678329 1.870851 2.098930 2.268758 2.467556 2.613989
-0.201767 0.332879 0.530137 0.745363 1.051345 1.174747 1.706266 2.049544 2.461842 2.799073
-0.224306 0.303901 0.510428 1.086097 1.267920 1.446573 1.785392 1.911767 2.289610 2.700286
-0.131135 0.171778 0.323877 0.821611 1.226519 1.537322 1.889645 2.169879 2.520932 2.772178
-0.212962 0.347455 0.744136 0.964332 1.426998 1.636084 1.937573 2.189447 2.476377 2.657238
-0.221564 0.298344 0.590780 0.774362 1.002528 1.237108 1.762739 1.946722 2.225939 2.371709
-0.300082 0.409111 0.600009 0.784231 0.905421 1.449797 1.878545 2.002657 2.618940 2.779774
-0.177168 0.244397 0.382973 0.547832 0.958732 1.796741 2.037031 2.198241 2.416774 2.606982
-0.445089 0.691608 0.911651 1.027834 1.215634 1.498612 2.011028 2.296914 2.571657 2.730890
-0.218890 0.332216 0.485543 0.669862 0.827655 0.946060 1.655213 2.081780 2.297490 2.781759
-0.264561 0.330768 0.698979 0.882675 1.036048 1.373216 1.608206 1.801189 2.021468 2.470223
-0.198417 0.232211 0.502648 0.724700 1.196144 1.304503 1.692944 1.862228 2.327527 2.429571
-0.240112 0.278797 0.513980 1.374924 1.647698 1.742378 1.988501 2.137277 2.329969 2.585200
-0.216630 0.297516 0.454364 0.700613 0.893785 1.036923 1.565511 2.032201 2.301512 2.463679
-0.308267 0.357421 0.811138 1.127420 1.244275 1.651427 1.813657 2.045151 2.637104 2.726842
-0.242030 0.328382 0.452907 0.861731 1.555327 1.743950 1.896242 2.084827 2.255121 2.454955
-0.405487 0.653274 1.000615 1.215980 1.553100 1.809940 2.090490 2.237915 2.442893 2.589896
-0.258975 0.421106 0.596341 0.793521 1.016877 1.148382 1.710733 2.132131 2.329411 2.755008
-0.383770 0.618549 0.792683 0.970281 1.353980 1.492209 1.740595 2.034232 2.262266 2.418759
-0.182576 0.276855 0.395058 1.006542 1.378696 1.494813 1.790120 1.929259 2.427587 2.564728
-0.262944 0.336362 0.560480 1.134456 1.298593 1.499501 1.953395 2.050099 2.524027 2.712280
-0.128134 0.176378 0.373760 0.758708 1.132934 1.485273 1.930693 2.068716 2.343529 2.773154
-0.209614 0.299558 0.469136 0.796651 0.955701 1.572224 2.012335 2.290736 2.580444 2.723601
-0.205230 0.307160 0.423168 0.638468 1.376104 1.735940 1.925713 2.112538 2.470319 2.600522
-0.249605 0.312259 0.801138 1.134882 1.687789 1.883222 2.049696 2.223042 2.454133 2.577341
-0.150236 0.180308 0.350515 0.500915 0.804675 1.506103 1.712024 2.023875 2.343152 2.636887
-0.294328 0.430367 0.587290 0.910719 1.184482 1.304216 1.581107 2.004270 2.395137 2.534772
-0.185620 0.281137 0.544021 0.818067 1.320581 1.540046 1.863117 2.127465 2.523995 2.737758
-0.154431 0.208321 0.340239 1.022588 1.552229 1.696583 2.198386 2.394862 2.607880 2.801047
-0.172397 0.232300 0.478592 0.699642 0.957173 1.484486 1.847798 1.985936 2.145557 2.327115
-0.511765 0.721492 0.860517 1.030820 1.340681 1.459390 1.823745 2.108810 2.406735 2.558400
-0.281714 0.392430 0.578702 0.891995 1.494831 1.661309 1.877927 2.097376 2.291857 2.619590
-0.326495 0.586450 0.954506 1.197200 1.519600 1.893887 2.319365 2.533775 2.736139 2.847582
-0.106638 0.178766 0.680283 0.829053 0.990716 1.241479 1.789242 2.154750 2.597141 2.799901
-0.294220 0.377984 0.793384 0.971352 1.172200 1.572398 1.804897 2.028760 2.264042 2.492483
-0.171726 0.263446 0.395475 0.621988 1.267402 1.408927 1.898373 2.102150 2.426709 2.776510
-0.303342 0.364222 0.792880 1.046061 1.184958 1.568551 1.760719 2.139470 2.565548 2.655674
-0.192848 0.257653 0.414826 0.791829 1.260674 1.636533 1.874636 2.009896 2.202175 2.572052
-0.341824 0.417968 0.655810 1.026514 1.158607 1.346654 1.798696 1.911077 2.526891 2.702043
-0.176931 0.234845 0.363167 0.522327 1.394457 1.894472 2.109195 2.282625 2.684080 2.823357
-0.433185 0.607432 0.929790 1.250808 1.472755 1.627281 2.014445 2.256366 2.466320 2.630010
-0.211267 0.313559 0.402576 0.554601 0.723386 0.871912 1.614736 2.390825 2.565792 2.757341
-0.307409 0.394557 0.612848 0.987028 1.191241 1.356915 1.954914 2.160787 2.345073 2.569786
-0.184320 0.254786 0.425592 0.782972 1.223405 1.413726 1.796288 1.997325 2.163509 2.505424
-0.183175 0.235186 0.358817 1.447766 1.601221 1.798948 2.134861 2.384961 2.598175 2.763819
-0.168505 0.236625 0.392319 0.651410 0.887019 1.463266 1.720871 1.858740 2.054516 2.697266
-0.250944 0.424982 0.901118 1.085636 1.247720 1.422572 1.835136 2.141276 2.468994 2.643082
-0.238593 0.326384 0.595703 0.813678 1.506809 1.745897 1.890343 2.252317 2.461518 2.634033
-0.519767 0.866690 1.252206 1.413883 1.854974 2.027801 2.281339 2.431268 2.597701 2.697588
-0.246522 0.333214 0.509160 1.154104 1.290713 1.443135 1.588080 2.324589 2.609196 2.797383
-0.275391 0.402140 0.584019 0.959905 1.333760 1.460912 1.827046 2.003725 2.436316 2.639286
-0.150522 0.212041 0.531410 1.050416 1.371279 1.580851 1.792845 1.995166 2.294940 2.614257
-0.278576 0.329548 0.667074 1.214075 1.560713 1.652347 1.873746 2.021113 2.338907 2.664300
-0.167863 0.226536 0.396757 0.597846 1.051873 1.627164 1.958256 2.062767 2.191380 2.432992
-0.348666 0.407399 0.764654 0.897788 1.054142 1.537316 1.689159 2.089782 2.640438 2.728359
-0.171013 0.243044 0.356522 0.490258 1.359997 1.815025 1.981484 2.206887 2.431276 2.636843
-0.153522 0.396506 0.847453 1.284564 1.488783 1.804268 2.273812 2.522892 2.761823 2.876763
-0.171880 0.287093 0.496257 0.755483 0.937035 1.107577 1.897834 2.108945 2.413154 2.660532
-0.227201 0.370270 0.530492 0.844519 1.174595 1.296373 1.718215 1.907170 2.166590 2.484352
-0.149331 0.183437 0.326162 0.488638 1.002939 1.377342 1.867235 2.108546 2.503408 2.786207
-0.173193 0.266920 0.374287 0.945263 1.452229 1.556781 1.952554 2.099249 2.609846 2.766646
-0.239351 0.413047 0.605130 0.721419 1.069987 1.322991 1.500901 2.100747 2.338950 2.541476
-0.314543 0.427272 0.646059 0.977969 1.105555 1.443778 1.949196 2.065960 2.472020 2.663676
-0.306321 0.430910 0.620780 0.848250 1.324991 1.683308 1.879595 2.069502 2.344394 2.454817
-0.575586 0.847570 1.152532 1.423138 1.684099 1.969479 2.240224 2.428206 2.665523 2.760463
-0.350078 0.450964 0.688480 0.893082 1.035498 1.299152 1.508386 1.683054 2.499108 2.655705
-0.471148 0.571022 0.813000 1.058092 1.196537 1.491163 1.831861 1.956586 2.408824 2.619234
-0.171564 0.273430 0.738762 0.920791 1.183470 1.349450 1.890642 2.110332 2.341546 2.722247
-0.304218 0.440526 0.720869 0.956392 1.296296 1.536912 1.798491 2.129943 2.470933 2.711029
-0.208585 0.283203 0.713164 0.859752 1.075018 1.320232 1.749308 2.009905 2.348887 2.539152
-0.264896 0.431760 0.680060 0.840630 1.005182 1.200071 1.639044 1.877513 2.579690 2.697610
-0.171107 0.229447 0.393985 0.553918 1.187522 1.583641 1.829031 2.101558 2.437468 2.610652
-0.301877 0.445169 0.968634 1.180258 1.415638 1.646629 1.953737 2.185760 2.483000 2.660034
-0.267959 0.387016 0.557674 0.755435 1.057021 1.189525 1.629581 2.283668 2.558077 2.683573
-0.295624 0.500278 0.696740 0.866240 1.099396 1.243691 1.449224 1.818732 2.156886 2.467455
-0.170796 0.218503 0.382819 0.541542 1.174040 1.482773 1.670539 2.124357 2.342810 2.501870
-0.218617 0.408868 1.012231 1.352073 1.571864 1.753294 1.946988 2.192205 2.547198 2.762737
-0.210391 0.288701 0.475984 0.690054 0.862131 1.282021 1.715676 1.959037 2.326017 2.522621
-0.325276 0.411256 0.607216 1.024267 1.146043 1.558528 1.827982 1.956178 2.547484 2.688731
-0.238733 0.302603 0.642540 0.860406 1.382580 1.700239 1.853297 2.013606 2.539089 2.671372
-0.251458 0.654734 1.143938 1.335095 1.596794 1.905380 2.171292 2.352561 2.549262 2.709208
-0.223912 0.427965 0.590260 0.805826 0.965451 1.148957 1.600066 1.767416 2.589376 2.776857
-0.231425 0.413483 0.638906 0.882586 1.449203 1.579707 1.859705 2.112105 2.296389 2.474881
-0.175747 0.273698 0.397808 1.029989 1.240179 1.441564 1.858169 1.988257 2.524452 2.677832
-0.252558 0.363162 0.974161 1.201176 1.356803 1.559352 1.792123 2.089122 2.459025 2.636551
-0.173802 0.246852 0.480971 0.700611 0.891748 1.561958 1.823062 1.996221 2.202269 2.680874
-0.156459 0.259855 0.526047 0.742605 0.958340 1.426445 1.896392 2.280343 2.683239 2.835947
-0.142921 0.202788 0.307634 0.548822 1.431571 1.572303 1.984312 2.212223 2.639484 2.831017
-0.229329 0.366711 0.836992 1.135952 1.499118 1.677865 2.047730 2.243207 2.553663 2.706012
-0.263443 0.342499 0.477117 0.660406 0.787355 1.288964 1.851275 2.320384 2.518393 2.638003
-0.212725 0.343388 0.492706 0.738769 1.226813 1.353718 1.598551 1.965475 2.110981 2.504476
-0.160187 0.263690 0.362021 0.839661 1.356922 1.457150 1.769821 1.888317 2.678737 2.835838
-0.133248 0.196263 0.549077 0.905288 1.338934 1.580432 1.965798 2.247794 2.613434 2.821093
-0.239176 0.349470 0.587777 0.780748 0.980439 1.200381 1.437420 1.725392 2.240059 2.450024
-0.360450 0.512584 0.678578 0.889177 1.014277 1.240800 1.650560 1.806004 2.370762 2.627783
-0.207946 0.300178 0.419389 0.758257 1.373065 1.509366 1.798146 2.166289 2.334602 2.736094
-0.113082 0.204024 0.875013 1.243194 1.622958 1.886831 2.142636 2.338959 2.579123 2.767029
-0.204623 0.309091 0.441874 0.966890 1.231677 1.366805 1.580086 1.745147 2.374530 2.638283
-0.306051 0.414526 0.628201 1.074722 1.259864 1.439108 1.821360 1.964678 2.394043 2.575006
-0.222328 0.323754 0.568002 0.970977 1.120920 1.580969 1.759222 2.139577 2.608362 2.763997
-0.183300 0.372397 0.683079 1.022379 1.330137 1.624137 1.951990 2.252475 2.602804 2.814906
-0.178777 0.259371 0.411261 0.873219 1.178107 1.319602 1.632433 1.885996 2.112106 2.286708
-0.195172 0.346190 0.497154 0.755965 1.230183 1.347062 1.685780 1.867553 2.329508 2.752389
-0.195738 0.263473 0.396445 0.598238 1.275429 1.903330 2.156978 2.286654 2.571493 2.728101
-0.369955 0.545605 1.042124 1.189996 1.350332 1.546670 1.867983 2.111160 2.467785 2.643118
-0.120478 0.160718 0.275169 0.491413 0.821334 1.099250 1.777446 1.936945 2.424408 2.722251
-0.312690 0.451099 0.623388 0.828741 0.993468 1.136473 1.649831 1.980283 2.173337 2.352824
-0.243020 0.364104 0.491726 0.944543 1.131493 1.302149 1.857127 1.973690 2.400218 2.803623
-0.193524 0.259253 0.688441 1.340521 1.671654 1.914554 2.135144 2.313920 2.516303 2.683437
-0.232326 0.387947 0.503848 0.715456 0.874078 1.042221 1.733322 1.898809 2.239800 2.752745
-0.127511 0.344390 0.935547 1.175974 1.388543 1.630551 1.946941 2.245394 2.574897 2.775392
-0.250995 0.323646 0.441648 0.957645 1.547323 1.747938 1.902388 2.157859 2.364221 2.510959
-0.452291 0.693622 1.167859 1.318220 1.723133 1.940224 2.173724 2.424464 2.649258 2.755778
-0.302326 0.431401 0.690302 0.950763 1.203250 1.329801 1.782387 2.179065 2.423352 2.542775
-0.355954 0.504290 0.646021 0.864339 1.352328 1.533661 1.709471 1.960437 2.313335 2.451721
-0.104149 0.152699 0.587242 0.903889 1.183253 1.432120 1.706576 1.956497 2.205742 2.655087
-0.214047 0.281655 0.457781 1.318444 1.423722 1.610884 1.738687 2.315997 2.544975 2.780560
-0.182527 0.232898 0.390991 0.554764 1.219695 1.416974 1.668180 1.883510 2.094564 2.216562
-0.338387 0.409542 0.641629 0.767246 1.002251 1.650238 1.882942 2.041315 2.327004 2.467281
-0.231453 0.309431 0.647883 0.827408 1.212245 1.724138 1.934800 2.138651 2.400716 2.581201
-0.251173 0.509839 0.868347 1.305335 1.478259 1.819818 2.046666 2.383549 2.753204 2.859247
-0.285117 0.362320 0.652022 0.913386 1.044703 1.289808 1.899468 2.119379 2.316214 2.520072
-0.308945 0.404194 0.607700 0.785461 0.897492 1.263812 1.840947 1.995191 2.217981 2.533953
-0.172631 0.233496 0.395828 0.637121 1.094870 1.305225 1.975991 2.149162 2.425342 2.614303
-0.156972 0.227094 0.399128 1.055061 1.517113 1.669668 2.078208 2.233434 2.697606 2.846463
-0.173100 0.226252 0.408500 0.582801 1.098220 1.450523 1.627000 2.016222 2.249189 2.498326
-0.315638 0.497823 0.661879 0.886266 0.997659 1.195049 2.020156 2.258426 2.523904 2.750360
-0.271575 0.365793 0.531980 0.808835 1.273952 1.739663 1.983593 2.133546 2.348498 2.473697
-0.309045 0.513620 0.898951 1.324674 1.639949 1.904400 2.137826 2.348142 2.582366 2.748999
-0.173271 0.315218 0.477788 0.757177 0.875942 1.105511 1.237776 1.628886 2.684859 2.842014
-0.214839 0.273034 0.819191 1.102040 1.352164 1.657619 1.843619 1.972455 2.148374 2.639406
-0.116215 0.162407 0.342715 0.825790 1.042936 1.381631 1.804365 2.083780 2.487045 2.753736
-0.114070 0.425427 0.799793 1.070942 1.370278 1.618583 1.941131 2.202718 2.530097 2.788603
-0.243867 0.378883 0.547723 0.808932 1.239737 1.400240 1.860324 2.069002 2.263329 2.534065
-0.240195 0.333936 0.487895 0.915142 1.015549 1.511986 1.689823 2.078568 2.520731 2.673842
-0.243495 0.327973 0.505429 0.651882 1.068591 1.611267 2.012066 2.161812 2.523348 2.687469
-0.450190 0.521168 0.921017 1.146167 1.266402 1.657642 1.864716 2.036294 2.463023 2.557702
-0.168729 0.270636 0.453713 0.701140 0.915560 1.098438 1.604334 1.960600 2.637718 2.809070
-0.285452 0.345925 0.683009 1.127133 1.267180 1.493486 1.729244 1.897942 2.101957 2.279775
-0.197911 0.283257 0.436315 0.680443 1.328944 1.456235 1.789607 2.073798 2.297794 2.442548
-0.240843 0.293460 0.653007 1.222875 1.575683 1.682154 1.863647 2.019866 2.562349 2.730154
-0.175191 0.254744 0.507483 0.660774 1.010367 1.200881 1.595444 1.912422 2.384227 2.758183
-0.433781 0.510463 0.720856 1.101334 1.226464 1.443652 1.812748 1.957333 2.487847 2.673719
-0.221585 0.287234 0.682977 1.068491 1.562962 1.716402 1.897843 2.129521 2.335900 2.524987
-0.432705 0.840501 1.285672 1.439193 1.607667 1.795398 2.063813 2.311674 2.563015 2.711062
-0.354576 0.466602 0.650767 0.813566 0.938340 1.128342 1.805345 2.218869 2.395036 2.543280
-0.353822 0.544418 0.717185 0.903075 1.193814 1.302618 1.592775 1.928464 2.123197 2.300791
-0.232127 0.335542 0.466150 1.038780 1.385075 1.474844 1.919673 2.031739 2.495480 2.805573
-0.324665 0.377060 0.695910 1.283924 1.443588 1.596523 2.037150 2.169899 2.487425 2.691252
-0.178303 0.236258 0.409957 0.644793 0.991558 1.439340 1.644055 2.056081 2.477767 2.606365
-0.284645 0.347903 0.527540 0.667977 0.816156 1.687403 1.948029 2.113140 2.519425 2.617605
-0.169782 0.245851 0.359543 0.504529 1.401427 1.633494 1.805664 2.181529 2.362061 2.647147
-0.210292 0.309966 0.666265 1.086214 1.491332 1.862248 2.127350 2.359368 2.574699 2.710415
-0.176920 0.247329 0.439418 0.634764 0.868848 1.346770 1.668256 2.024234 2.456935 2.792061
-0.291292 0.461927 0.673858 0.827395 1.001436 1.123471 1.600221 2.273412 2.437555 2.642259
-0.164460 0.272259 0.374336 0.675110 1.490030 1.612152 1.836475 1.984289 2.535905 2.742055
-0.207858 0.272302 0.418159 0.745538 1.629583 1.981417 2.127840 2.293577 2.578197 2.705476
--0.062228 -0.323076 -0.332711 -0.101708 -0.034218 -0.067730 -0.032006 -0.034055 -0.063661 -0.112308
-0.471805 0.655978 0.860725 0.972051 1.153458 1.409133 1.784627 2.073639 2.494294 2.661139
-0.180954 0.273084 0.389972 0.849113 1.392936 1.510894 1.921378 2.096123 2.378596 2.651504
-0.225545 0.488038 0.863470 1.410418 1.596034 1.771648 2.216348 2.386984 2.715102 2.839389
-0.144776 0.247942 0.381281 0.699264 1.145490 1.295150 1.800737 2.008105 2.629862 2.826194
-0.184806 0.248115 0.690786 0.828582 1.321220 1.503651 1.718611 2.087128 2.314827 2.538325
-0.177133 0.339599 0.481545 0.790062 1.227237 1.348197 1.883037 2.021486 2.441350 2.699083
-0.311370 0.368740 0.858970 1.014739 1.208416 1.746055 1.924647 2.151463 2.415915 2.560580
-0.199710 0.264710 0.470506 0.794534 1.118412 1.570882 1.812521 1.939545 2.110880 2.373289
-0.350635 0.482066 0.710421 0.960792 1.103058 1.325978 1.913082 2.069461 2.404068 2.662115
-0.186366 0.241536 0.381062 0.517738 1.497745 1.924116 2.070412 2.234108 2.608905 2.750199
-0.509032 0.734852 0.927875 1.145398 1.394132 1.611867 1.956418 2.176366 2.420236 2.596717
-0.201922 0.299074 0.414361 0.597667 0.721234 0.975702 1.929938 2.144210 2.650822 2.846817
-0.249810 0.373368 0.691262 0.918023 1.296625 1.472578 1.881052 2.160262 2.404070 2.576539
-0.136751 0.198997 0.351968 0.839701 1.241879 1.397675 1.739341 1.946552 2.247675 2.676990
-0.215765 0.277228 0.527200 1.277413 1.507933 1.677635 2.048299 2.207947 2.614490 2.774622
-0.146093 0.199242 0.331057 0.518068 0.983944 1.184948 1.769667 1.933330 2.116265 2.713820
-0.311505 0.400669 0.630844 1.132601 1.442876 1.558170 1.906709 2.045975 2.419754 2.659979
-0.328470 0.401583 0.615037 0.993895 1.574441 1.869936 2.011558 2.184989 2.467408 2.581751
-0.463865 0.687911 1.294672 1.536811 1.700885 1.872005 2.174049 2.341841 2.576782 2.729884
-0.225601 0.311949 0.558510 0.720660 1.176452 1.364036 1.558010 2.010565 2.645874 2.801078
-0.300116 0.554320 0.704246 0.926026 1.318277 1.422364 1.788571 2.123745 2.298732 2.683560
-0.217312 0.342834 0.505628 0.885611 1.036468 1.281361 1.711880 1.931222 2.475950 2.632713
-0.235789 0.329023 0.515572 1.047927 1.413696 1.546519 1.893021 2.099995 2.430834 2.628838
-0.170354 0.225158 0.395611 0.654515 1.106878 1.458362 1.794475 2.012486 2.334320 2.553665
-0.420377 0.492906 0.763825 0.888793 1.057272 1.729447 1.982471 2.145245 2.614874 2.700457
-0.227828 0.299193 0.480966 0.855216 1.663391 1.817425 2.035090 2.237723 2.436081 2.645378
-0.104919 0.220297 0.922747 1.248851 1.468985 1.845122 2.172923 2.471447 2.702677 2.827250
-0.245660 0.363951 0.496495 0.718395 0.792531 1.188290 2.028262 2.148021 2.601079 2.767886
-0.204949 0.323637 0.501508 0.803477 1.101494 1.228773 1.446609 1.596114 1.975723 2.669065
-0.162963 0.221990 0.366143 0.569144 1.300415 1.508941 1.736879 2.176494 2.560640 2.781882
-0.226216 0.303208 0.451507 0.942554 1.584997 1.708649 1.937744 2.125981 2.374113 2.806697
-0.279313 0.434425 0.600140 0.761924 0.967326 1.085339 1.400649 2.085299 2.311823 2.531842
-0.496970 0.611003 0.813504 1.003786 1.112345 1.561294 2.006644 2.127810 2.538433 2.707483
-0.263598 0.399612 0.523023 0.751894 1.468733 1.634563 1.854672 2.093993 2.288808 2.486320
-0.447064 0.669729 1.231144 1.393911 1.519359 1.740011 2.130839 2.331661 2.622426 2.742410
-0.217113 0.344226 0.479443 0.953089 1.113345 1.292028 1.405063 2.035854 2.706084 2.818154
-0.215666 0.346628 0.459806 0.841338 1.330315 1.450787 1.693170 1.963290 2.133067 2.598851
-0.032462 0.108906 0.641839 0.918247 1.274605 1.548613 1.860118 2.149524 2.473967 2.745703
-0.126290 0.220180 0.749275 1.069688 1.256552 1.502364 1.780350 2.049865 2.514790 2.760101
-0.201396 0.256212 0.604955 0.839430 1.037016 1.425915 1.784411 2.082149 2.278545 2.520697
-0.250554 0.361913 0.538203 1.009347 1.125631 1.467374 1.842276 1.982168 2.659098 2.812528
-0.173329 0.232821 0.397105 0.674759 1.272214 1.578849 1.859567 2.046929 2.368178 2.523695
-0.361106 0.495511 0.860190 1.082212 1.386309 1.580348 1.935833 2.155852 2.453898 2.622802
-0.232936 0.346360 0.515455 0.716889 0.946937 1.062494 1.542360 2.240413 2.402681 2.639495
-0.329138 0.483393 0.640612 0.860349 1.191888 1.297933 1.656172 2.079184 2.298135 2.457837
-0.238706 0.397136 0.560834 0.799404 1.288560 1.405264 1.678272 2.182520 2.375152 2.668620
-0.304175 0.364112 0.779173 1.338909 1.476173 1.664278 1.993154 2.118992 2.593337 2.731349
-0.164802 0.217347 0.366682 0.565116 0.753855 1.009701 1.744416 2.023924 2.268955 2.433440
-0.296797 0.356308 0.759995 1.197140 1.309824 1.482490 1.667647 1.840314 2.517650 2.648945
-0.273443 0.411365 0.594999 0.894650 1.424021 1.586944 1.842399 2.215251 2.447173 2.729450
-0.236751 0.360177 1.030195 1.434197 1.683780 1.888286 2.114605 2.264435 2.477029 2.630414
-0.273289 0.394610 0.610213 0.759723 0.937713 1.239572 1.713796 1.995028 2.367774 2.635783
-0.334115 0.411443 0.610825 0.955868 1.502521 1.785262 1.937709 2.105790 2.350122 2.470200
-0.159072 0.242631 0.393231 0.844130 1.217685 1.419823 1.733096 1.891617 2.514256 2.659089
-0.309184 0.361119 0.759243 1.263501 1.440575 1.570597 1.821846 1.944982 2.440271 2.684484
-0.161993 0.224640 0.401324 0.753906 1.032749 1.440682 1.809558 1.978594 2.149676 2.538575
-0.247815 0.331789 0.491727 0.713759 0.865824 1.618286 1.768016 2.244205 2.532077 2.684242
-0.170605 0.248525 0.354505 0.495374 1.569514 1.828195 1.990227 2.213056 2.400769 2.760431
-0.331931 0.515143 0.809566 1.042681 1.451957 1.638579 1.956390 2.262500 2.598192 2.813680
-0.209020 0.349585 0.505601 0.704594 0.814790 1.362447 1.939075 2.048582 2.423957 2.756261
-0.281207 0.453713 0.595485 0.765529 1.220000 1.391996 1.561764 2.022289 2.265860 2.679768
-0.150346 0.251592 0.409505 0.770775 1.236125 1.384343 1.745495 1.893299 2.588497 2.822991
-0.161090 0.246862 0.484826 1.245783 1.397859 1.714145 2.040802 2.468857 2.706233 2.837580
-0.213765 0.374235 0.536566 0.733390 1.126324 1.249567 1.538484 1.976391 2.151928 2.359273
-0.272518 0.457655 0.808972 1.019104 1.150011 1.326035 1.711513 2.051136 2.549677 2.799790
-0.179767 0.262954 0.395346 0.660835 1.345694 1.502264 1.819384 1.963548 2.273263 2.618778
-0.175488 0.306329 1.103215 1.306099 1.574389 1.897560 2.214935 2.416432 2.605393 2.738739
-0.154666 0.239592 0.415828 0.780679 0.945224 1.233384 1.696039 1.940742 2.514563 2.679770
-0.269177 0.354740 0.557021 0.969509 1.345317 1.463570 1.798387 2.241221 2.456339 2.610210
-0.239145 0.326264 0.494465 1.071214 1.209459 1.537726 1.952743 2.113220 2.610725 2.747535
-0.218208 0.598959 0.871276 1.110151 1.386993 1.648655 1.918609 2.193362 2.546880 2.756671
-0.176681 0.262087 0.424568 0.933283 1.208095 1.334188 1.755633 1.926341 2.187131 2.556577
-0.213062 0.385248 0.514741 0.876978 1.165897 1.307493 1.825031 2.012224 2.554948 2.737931
-0.151222 0.247007 0.382114 0.751657 1.215610 1.342363 1.975904 2.137584 2.617134 2.820105
-0.299224 0.473356 0.825171 1.146594 1.528401 1.694234 1.952214 2.144722 2.373789 2.555562
-0.207137 0.319897 0.501670 0.711149 0.853927 1.057889 1.770494 2.071726 2.492216 2.811033
-0.465560 0.618831 0.782398 1.010037 1.195984 1.322540 1.855998 2.160517 2.324801 2.507033
-0.201076 0.301843 0.444311 0.822638 1.176021 1.272371 1.646433 2.064560 2.227727 2.623829
-0.210505 0.247037 0.495092 1.302518 1.760886 1.827284 2.217044 2.446377 2.623543 2.741148
-0.195999 0.279369 0.481573 0.654787 1.080842 1.412382 1.716490 2.052322 2.290101 2.738165
-0.236926 0.310814 0.896361 1.162180 1.328092 1.558913 1.774564 1.905228 2.402246 2.665023
-0.244472 0.327963 0.646896 1.095894 1.620412 1.772324 2.045520 2.193957 2.547128 2.722609
-0.346731 0.581380 1.070375 1.522205 1.740223 1.980572 2.266647 2.404418 2.746561 2.871000
-0.430698 0.619190 0.836877 1.015020 1.167909 1.332640 1.815328 2.234722 2.476070 2.638178
-0.221367 0.307079 0.458329 0.850712 1.289560 1.423009 1.621570 1.985342 2.331434 2.467832
-0.116322 0.217253 0.728326 0.940859 1.188330 1.378722 1.687841 1.910693 2.604869 2.797202
-0.187928 0.267923 0.389066 1.155944 1.483571 1.593699 1.818241 1.963936 2.473096 2.607548
-0.168954 0.211406 0.372427 0.529448 0.973588 1.431171 1.621558 1.856431 2.189298 2.343881
-0.273371 0.413963 0.664359 0.794553 1.017733 1.399395 1.724746 2.089838 2.367948 2.555808
-0.212416 0.270112 0.509967 0.759092 1.293781 1.781086 2.091445 2.219374 2.499069 2.630826
-0.300696 0.481937 0.835784 1.276211 1.461493 1.644316 1.971697 2.234847 2.641035 2.829278
-0.285091 0.416886 0.605330 0.808172 0.944872 1.129570 1.919248 2.157389 2.400226 2.673656
-0.225704 0.384656 0.630586 0.788196 1.224861 1.419420 1.681321 1.970805 2.212616 2.617121
-0.132447 0.177755 0.301537 0.471768 1.155148 1.332095 1.708466 2.024543 2.495585 2.788666
-0.252038 0.329800 0.481080 0.954609 1.422083 1.620359 2.006123 2.168392 2.355165 2.505083
-0.183435 0.241389 0.417674 0.598794 1.014975 1.205139 1.701958 1.977784 2.374336 2.586101
-0.302192 0.384974 0.608153 0.938510 1.084287 1.329203 2.069641 2.319152 2.494203 2.675684
-0.198808 0.281220 0.391748 0.777377 1.553382 1.790825 1.925301 2.135471 2.304278 2.485154
-0.370469 0.548730 0.880131 1.168541 1.456674 1.645880 2.049941 2.288441 2.557653 2.759821
-0.156583 0.250724 0.394960 0.691089 0.837322 1.066297 1.836287 1.972838 2.591097 2.786561
-0.322824 0.379018 0.593081 1.086011 1.406693 1.490406 1.734998 1.912817 2.081717 2.475586
-0.158775 0.218842 0.457222 0.869711 1.219773 1.629722 1.953462 2.134004 2.392326 2.640093
-0.217524 0.325911 0.628615 0.997991 1.504329 1.668932 1.958103 2.245372 2.630371 2.808323
-0.170343 0.254286 0.510717 0.814297 1.028209 1.355930 1.726583 2.047676 2.381522 2.692279
-0.297689 0.343194 0.742306 0.882638 1.038877 1.713935 1.880819 2.088189 2.556386 2.634265
-0.215251 0.296748 0.454072 0.676499 1.007705 1.797713 2.004948 2.206914 2.548819 2.725676
-0.412021 0.642343 0.828334 0.951784 1.236305 1.495649 1.898175 2.129486 2.438961 2.666301
-0.179065 0.252377 0.372814 0.530815 0.713797 0.927597 1.666069 2.104770 2.392383 2.734423
-0.433130 0.566964 0.740476 0.961675 1.107074 1.288034 1.772074 1.904854 2.174689 2.570674
-0.223409 0.295735 0.606368 0.786946 1.326960 1.538874 1.755901 1.939986 2.371080 2.488210
-0.224170 0.294402 0.684662 1.251045 1.593460 1.708681 2.018073 2.187551 2.515208 2.721384
-0.166379 0.238226 0.406222 0.623445 0.883761 1.076979 1.603102 1.916054 2.202559 2.699771
-0.489484 0.578385 0.832748 1.115430 1.216650 1.575882 1.929300 2.049396 2.522680 2.658393
-0.291742 0.359710 0.491711 1.071820 1.458792 1.603219 1.747893 2.124226 2.418190 2.528558
-0.438848 0.678792 1.139964 1.311051 1.673038 1.878533 2.126488 2.288717 2.493483 2.631731
-0.271300 0.466760 0.592041 0.808897 0.942888 1.124238 1.820005 1.976080 2.249710 2.775433
-0.389199 0.559773 0.703683 0.900063 1.345064 1.462662 1.769904 2.128433 2.365683 2.501187
-0.190440 0.280423 0.447001 1.039189 1.218375 1.614861 1.844728 2.111340 2.460942 2.613396
-0.241700 0.302019 0.613366 1.249946 1.410607 1.580256 1.768325 1.986861 2.430632 2.581026
-0.206516 0.286418 0.537788 0.707728 1.197196 1.572380 1.755394 1.933391 2.472918 2.645023
-0.318502 0.396523 0.647544 0.775364 0.936563 1.581584 2.058082 2.195477 2.618710 2.743108
-0.191584 0.269771 0.414492 0.786131 1.376273 1.613474 1.799398 2.344394 2.536806 2.749566
-0.237976 0.316356 0.446480 0.893873 1.679975 1.965388 2.096434 2.252618 2.468845 2.587829
-0.123845 0.159072 0.284123 0.467782 0.818151 1.307335 1.754936 2.066298 2.476057 2.758144
-0.261052 0.393384 0.760978 0.918516 1.100980 1.327690 1.632686 2.033602 2.384945 2.554088
-0.264436 0.350588 0.609731 0.749716 1.157992 1.660102 1.868180 2.004961 2.591971 2.739458
-0.164585 0.215089 0.375970 0.959153 1.727354 1.859913 1.991898 2.220550 2.431018 2.769731
-0.204030 0.290606 0.483834 0.827022 1.016831 1.223453 1.699260 1.910125 2.140620 2.267503
-0.526138 0.709922 0.836725 1.069406 1.269462 1.405044 1.834798 2.034524 2.212188 2.459999
-0.225247 0.340174 0.449473 0.914306 1.380619 1.486761 1.795410 1.983939 2.206215 2.713630
-0.200753 0.622848 0.941841 1.226624 1.507543 1.821962 2.134104 2.366417 2.634739 2.771988
-0.174703 0.282776 0.702258 0.898342 1.084446 1.266724 1.757851 2.083739 2.401420 2.756275
-0.249131 0.323445 0.720321 0.878509 1.110362 1.576682 1.865315 2.114744 2.387200 2.528666
-0.192991 0.271656 0.400815 0.639719 1.281970 1.423380 2.050229 2.264541 2.462010 2.662504
-0.266874 0.325220 0.675228 1.126545 1.267438 1.706113 1.920856 2.125988 2.574605 2.678193
-0.223081 0.286041 0.655976 0.816840 1.060069 1.561164 1.748293 1.911129 2.075313 2.503462
-0.407716 0.515541 0.739241 0.941291 1.059746 1.404674 1.781339 1.892197 2.404849 2.648290
-0.240599 0.312213 0.510661 0.666324 1.224803 1.866233 2.050438 2.204639 2.619539 2.768546
-0.384825 0.587577 1.021218 1.214225 1.437340 1.728676 1.998469 2.183120 2.571593 2.747573
-0.245764 0.343500 0.509527 0.727872 0.876936 1.024899 1.769731 2.415709 2.632816 2.787619
-0.290619 0.390761 0.566531 0.941586 1.353924 1.461037 1.795546 2.132642 2.313283 2.486608
-0.172727 0.258217 0.438312 0.716613 1.170907 1.311367 1.733515 1.899224 2.138675 2.739799
-0.222657 0.287215 0.449779 1.369666 1.490501 1.701894 1.880425 2.393512 2.600773 2.787142
-0.154428 0.222305 0.357310 0.630820 1.037882 1.342771 1.730454 1.920364 2.046990 2.549536
-0.299554 0.623129 0.825895 1.063948 1.332600 1.466624 1.854370 2.128982 2.327186 2.521370
-0.218073 0.257913 0.681337 0.900215 1.517137 1.843444 2.006541 2.205575 2.505616 2.633109
-0.686321 1.027088 1.182402 1.346554 1.590920 1.854772 2.111571 2.250916 2.482490 2.625270
-0.220174 0.305579 0.452469 1.009178 1.208905 1.586079 1.726183 2.308495 2.539415 2.745570
-0.341504 0.508703 0.663379 0.854389 1.270406 1.419250 1.624925 2.064447 2.426578 2.552193
-0.199767 0.277559 0.419200 1.151687 1.302355 1.531961 1.720872 2.013206 2.476765 2.595851
-0.243094 0.314600 0.435247 1.051642 1.528616 1.656151 1.884292 2.065968 2.307851 2.563448
-0.224054 0.300322 0.546545 0.706978 1.059557 1.412749 1.925773 2.119205 2.355100 2.490204
-0.342948 0.395972 0.713508 0.788514 1.092279 1.685316 1.836105 2.270695 2.521777 2.625975
-0.183089 0.263605 0.369340 0.558240 1.511750 1.902656 2.045224 2.218195 2.445586 2.611569
-0.332871 0.558850 0.877672 1.147342 1.590679 1.823730 2.184823 2.407743 2.721120 2.860996
-0.228040 0.355308 0.498081 0.818616 1.098234 1.212951 1.802644 2.085736 2.290465 2.748208
-0.189112 0.289591 0.530362 0.768658 0.944224 1.325806 1.678253 1.884531 2.251127 2.682120
-0.144799 0.199748 0.350015 0.546248 1.106050 1.629785 1.884696 2.005826 2.432189 2.780747
-0.172297 0.243074 0.380863 0.968654 1.645970 1.743664 1.952788 2.092464 2.574491 2.809210
-0.220791 0.397930 0.676300 0.814804 1.085618 1.265955 1.557093 1.974461 2.157493 2.568431
-0.351036 0.481040 0.684693 1.046142 1.219179 1.404440 1.909685 2.051432 2.405205 2.669908
-0.255837 0.394071 0.518620 0.767306 1.393237 1.618907 1.766511 2.022002 2.425935 2.559548
-0.418747 0.617245 1.109151 1.299581 1.560582 1.912698 2.151587 2.420609 2.666448 2.766110
-0.194318 0.321980 0.488422 0.733153 0.927489 1.091432 1.537804 1.709529 2.300954 2.777973
-0.441506 0.552407 0.771304 1.070023 1.253431 1.402955 1.774359 1.917186 2.236828 2.573015
-0.096364 0.161493 0.604211 0.841192 1.084960 1.469012 1.765762 2.035652 2.415550 2.679394
-0.164758 0.273531 0.786362 0.944165 1.314729 1.443079 1.820614 2.232970 2.474360 2.689648
-0.214880 0.277389 0.624783 0.819250 1.049581 1.383136 1.664426 1.809937 2.247050 2.531672
-0.339450 0.490710 0.650894 0.802164 0.968459 1.286294 1.736119 2.108232 2.488573 2.676959
-0.173316 0.243343 0.367127 0.508577 1.224968 1.826439 1.981666 2.158278 2.351480 2.588130
-0.452858 0.676518 0.916839 1.095033 1.353796 1.666215 1.906615 2.097253 2.478402 2.671285
-0.255572 0.430173 0.627154 0.845685 1.029142 1.165075 1.851297 2.238290 2.425106 2.786559
-0.292973 0.495593 0.670882 0.825200 1.176688 1.345844 1.524943 1.905429 2.293155 2.481585
-0.190065 0.270578 0.429350 0.650608 1.338108 1.544596 1.723081 2.100587 2.455792 2.616187
-0.270146 0.357004 1.012493 1.334770 1.484494 1.749118 1.948371 2.163260 2.479187 2.615849
-0.190746 0.284342 0.459935 0.840326 1.058271 1.247416 1.686518 1.858042 2.349852 2.474999
-0.261440 0.355783 0.788131 0.963975 1.170960 1.426067 1.663365 1.845513 2.450110 2.615423
-0.223477 0.289406 0.644196 0.841108 1.449672 1.680461 1.864688 1.970082 2.320400 2.678113
-0.307863 0.471864 0.951274 1.401941 1.598874 1.839736 2.064310 2.222939 2.646039 2.793416
-0.215456 0.324380 0.542457 0.738120 0.904477 1.125488 1.593790 1.942637 2.403731 2.625335
-0.327978 0.431326 0.649146 0.980387 1.452639 1.595021 1.827042 2.174676 2.430383 2.562971
-0.221416 0.405136 0.534878 0.941825 1.275052 1.387146 1.678769 1.816890 2.607600 2.805074
-0.261063 0.296006 0.765065 1.323946 1.455938 1.597320 1.755333 1.939918 2.595321 2.725885
-0.196465 0.266597 0.478088 0.673695 0.918173 1.783876 1.968005 2.144556 2.340807 2.571099
-0.222072 0.329556 0.457488 0.632821 0.926941 1.737060 1.925589 2.280188 2.742106 2.840767
-0.177587 0.262768 0.386637 0.661755 1.507334 1.651771 2.016609 2.209898 2.436253 2.794750
-0.237412 0.318760 0.572489 1.126672 1.262629 1.705670 1.962639 2.240223 2.640836 2.760043
-0.164018 0.263560 0.389157 0.576607 0.699517 1.304965 1.938275 2.108181 2.361245 2.481099
-0.312927 0.453499 0.595937 0.720801 1.155128 1.421222 1.654805 2.125481 2.342733 2.559528
-0.187311 0.340553 0.479298 0.800541 1.324137 1.434292 1.773373 1.966276 2.442163 2.794439
-0.240145 0.361802 0.529355 1.032511 1.333136 1.613724 1.902121 2.393189 2.610681 2.798432
-0.256618 0.369979 0.571037 0.805889 0.931870 1.242267 1.556114 1.777808 2.100100 2.279277
-0.315460 0.387429 0.763439 1.135994 1.225008 1.383314 1.479969 1.857272 2.506217 2.572444
-0.231972 0.332687 0.498409 0.763292 1.482840 1.675304 1.917342 2.171163 2.373797 2.762604
-0.241092 0.374768 0.886119 1.278350 1.760790 1.986414 2.153341 2.321588 2.561671 2.682561
-0.181333 0.265570 0.457041 0.832421 0.997777 1.194519 1.519027 1.911348 2.372249 2.624795
-0.217281 0.313910 0.490988 1.021293 1.238563 1.420272 1.905572 2.077699 2.389621 2.611841
-0.241907 0.344617 0.495322 0.833050 0.943750 1.625368 1.957947 2.118287 2.573169 2.706253
-0.260933 0.421768 0.714877 1.045217 1.348286 1.557267 1.920459 2.142565 2.463638 2.761801
-0.191170 0.260573 0.482902 0.852619 1.182296 1.355163 1.734327 2.038425 2.220238 2.348315
-0.235960 0.420321 0.558300 0.822306 0.959709 1.163020 1.746196 1.872763 2.463190 2.656887
-0.182801 0.229509 0.384936 0.525996 1.144440 1.505356 2.087714 2.235691 2.603441 2.821072
-0.433326 0.648975 1.152821 1.324354 1.499568 1.680615 1.927155 2.144623 2.501930 2.672369
-0.185230 0.282855 0.433567 0.613008 0.800249 1.189297 1.815486 2.216184 2.611609 2.819742
-0.305950 0.512379 0.682631 0.866346 1.140903 1.267093 1.689424 1.993235 2.167743 2.491215
-0.214384 0.330677 0.465107 0.799324 1.249335 1.354711 1.961836 2.155521 2.365402 2.768664
-0.252228 0.294891 0.721925 1.385448 1.627786 1.728361 2.094373 2.246017 2.542430 2.725817
-0.247355 0.467492 0.616684 0.821505 1.051679 1.163064 1.676721 1.903589 2.192444 2.770439
-0.267056 0.322353 0.878273 1.273551 1.387890 1.656880 1.838486 2.256932 2.489329 2.617788
-0.276548 0.347431 0.510036 0.916479 1.503298 1.902076 2.081537 2.205346 2.459159 2.574602
-0.420124 0.634373 0.972031 1.349147 1.660814 1.863940 2.209039 2.359323 2.665996 2.774761
-0.245603 0.346643 0.484960 0.852273 1.113317 1.246194 1.675673 2.134010 2.397448 2.567438
-0.278909 0.453205 0.609401 0.817334 1.386351 1.540485 1.784357 2.027199 2.208866 2.416858
-0.216689 0.291968 0.633303 0.821476 1.230792 1.517474 1.740384 1.839894 2.264549 2.645633
-0.250583 0.356352 0.706187 1.159764 1.340429 1.531877 1.805133 2.212588 2.494217 2.645859
-0.173603 0.221482 0.407668 0.602668 1.173887 1.363948 1.714837 2.069366 2.246713 2.384843
-0.351700 0.426939 0.676212 0.785470 1.018054 1.600174 1.760596 1.981016 2.523457 2.622580
-0.247404 0.347843 0.537821 0.715383 1.334742 1.730445 1.932738 2.116362 2.550868 2.719251
-0.267640 0.435192 0.734410 1.154981 1.439281 1.665625 2.036115 2.238505 2.694509 2.857159
-0.377315 0.500802 0.678295 0.852176 0.986722 1.234297 1.946465 2.216296 2.369690 2.568046
-0.282474 0.484623 0.647346 0.838126 1.116069 1.236355 1.605158 2.068283 2.241476 2.594701
-0.179830 0.276699 0.393477 0.618077 1.005536 1.171683 1.936124 2.147218 2.344016 2.802089
-0.150385 0.222615 0.453699 1.059570 1.514904 1.869262 2.170323 2.385821 2.713541 2.834759
-0.190104 0.279191 0.487233 0.679289 1.139586 1.367418 1.532297 1.968753 2.379302 2.609276
-0.383123 0.512258 0.719040 0.900857 1.026096 1.446135 1.985069 2.104295 2.577580 2.725283
-0.233385 0.311008 0.468900 0.822874 1.358548 1.845397 2.088437 2.201482 2.419016 2.524441
-0.448047 0.666107 0.986682 1.233646 1.707798 1.882326 2.175233 2.389889 2.561257 2.672922
-0.190653 0.315609 0.490994 0.746849 0.882522 1.292447 1.594598 1.771911 2.563910 2.770587
-0.215760 0.268515 0.648673 1.130954 1.282429 1.603348 1.802088 2.039412 2.361344 2.489232
-0.146123 0.204228 0.382306 0.718573 1.152464 1.523749 1.750535 2.085976 2.456666 2.706774
-0.097438 0.189231 0.726839 1.130330 1.394979 1.591658 1.959512 2.188961 2.611863 2.823535
-0.153693 0.220100 0.418171 0.907592 1.098588 1.409276 1.661682 2.052898 2.357440 2.534558
-0.249007 0.320795 0.581631 0.894597 1.056178 1.470144 1.725025 1.888314 2.380417 2.512561
-0.215043 0.307452 0.489967 0.675625 1.212878 1.644852 1.813460 2.219287 2.421185 2.711916
-0.454182 0.656019 0.980383 1.162424 1.342999 1.469780 1.737221 2.016043 2.396287 2.589121
-0.248859 0.363988 0.568562 0.710472 0.879383 0.969136 1.321791 2.203573 2.459572 2.685742
-0.275498 0.346347 0.720990 0.962739 1.142409 1.548421 1.756807 1.939827 2.107470 2.346331
-0.168346 0.213677 0.371061 0.533405 1.281879 1.420915 1.743873 1.929374 2.354611 2.516531
-0.269357 0.323555 0.660417 1.246119 1.389881 1.620112 1.880792 2.024803 2.535747 2.641379
-0.143544 0.211826 0.349106 0.686750 0.852997 1.123379 1.740477 1.910903 2.395457 2.675160
-0.391096 0.461323 0.706811 0.863080 0.973392 1.482338 1.771634 1.885759 2.506445 2.623396
-0.306784 0.371767 0.612809 1.165417 1.539601 1.649444 1.847967 2.215674 2.421224 2.551842
-0.412446 0.658776 1.248823 1.445679 1.591378 1.718751 1.944947 2.241242 2.542474 2.718017
-0.219635 0.320449 0.459092 0.733764 0.861516 1.087584 1.877017 2.055926 2.267583 2.421807
-0.353269 0.558306 0.705301 0.895998 1.276299 1.401657 1.682423 1.948663 2.130723 2.378531
-0.266056 0.406507 0.542960 1.171871 1.333369 1.503282 1.781150 1.967881 2.639831 2.805456
-0.366997 0.435212 0.708835 1.184565 1.338341 1.578537 2.031195 2.174915 2.531932 2.718652
-0.180016 0.244121 0.466532 0.637822 0.933798 1.613163 1.758726 2.141582 2.383844 2.570767
-0.183031 0.268217 0.410149 0.583275 0.768297 1.302461 1.927508 2.184191 2.515648 2.724226
-0.198728 0.279758 0.393674 0.687093 1.521403 1.831985 1.964413 2.182576 2.354737 2.718166
-0.266621 0.428987 0.748177 1.052044 1.416922 1.709958 1.975394 2.163065 2.390250 2.722350
-0.187580 0.301657 0.428103 0.623084 0.722948 1.407722 1.664241 1.898839 2.663491 2.802190
-0.207840 0.306975 0.483853 0.724360 1.022497 1.221432 1.415162 1.956839 2.527680 2.734643
-0.188611 0.284294 0.408262 0.721431 1.384715 1.505269 1.966087 2.173208 2.428517 2.770771
-0.222823 0.272639 0.503764 0.859246 1.498403 1.885767 2.099957 2.235388 2.567829 2.691284
-0.152758 0.219680 0.338675 0.597863 0.978697 1.200801 1.746909 1.957261 2.074441 2.404458
-0.429246 0.630671 0.792842 0.964490 1.262744 1.388795 1.721613 2.091229 2.345298 2.490896
-0.256329 0.380734 0.539915 1.009152 1.400960 1.509524 1.869215 2.029196 2.348803 2.776082
-0.272403 0.672458 0.977874 1.334181 1.683066 1.922996 2.291748 2.486116 2.709534 2.862231
-0.158762 0.287189 0.410234 0.812307 1.117621 1.262447 1.898049 2.047016 2.529228 2.738030
-0.179810 0.233529 0.707400 1.047569 1.289640 1.489108 1.847319 2.074331 2.343157 2.539680
-0.215347 0.304896 0.440699 0.897509 1.322585 1.472844 1.996310 2.165007 2.384550 2.574797
-0.286874 0.339813 0.883878 1.115931 1.272467 1.744249 1.885743 2.158576 2.589603 2.672644
-0.210579 0.284270 0.517041 0.796519 1.129021 1.668905 1.939439 2.065525 2.221131 2.479044
-0.261094 0.357573 0.576680 0.963769 1.112459 1.279265 1.822867 1.981048 2.197737 2.571008
-0.181278 0.244687 0.379354 0.499565 1.371147 1.939687 2.081545 2.257664 2.473413 2.679019
-0.491809 0.793403 1.095573 1.248586 1.433776 1.611914 1.888047 2.132035 2.457073 2.627391
-0.251235 0.353668 0.466231 0.673754 0.761327 1.114781 2.007224 2.123861 2.465832 2.639406
-0.345158 0.523258 0.679274 0.860119 1.194849 1.326006 1.848632 2.132397 2.326670 2.510966
-0.160104 0.220957 0.395991 0.698411 0.969721 1.448772 1.710923 1.833738 2.255148 2.614909
-0.154242 0.218964 0.347268 1.230461 1.592574 1.733703 2.002980 2.182922 2.555376 2.704150
-0.147752 0.202050 0.328105 0.531857 1.097229 1.287887 1.880144 2.033520 2.241027 2.732837
-0.394173 0.497084 0.712849 1.053505 1.351267 1.458228 1.861207 2.181794 2.392320 2.533753
-0.302335 0.380917 0.549353 0.985252 1.517171 1.702307 1.859140 2.148560 2.460271 2.579449
-0.489225 0.748632 1.289304 1.544824 1.780201 2.071873 2.310551 2.443509 2.704605 2.789720
-0.237235 0.383617 0.738218 0.908733 1.218091 1.378373 1.607258 2.196781 2.508687 2.662952
-0.287297 0.414596 0.576260 0.837481 1.292636 1.398051 1.699746 2.155291 2.397760 2.512719
-0.226644 0.373291 0.522981 0.950126 1.196878 1.352198 1.832943 1.977466 2.370185 2.574990
-0.202424 0.294204 0.576457 1.079769 1.296360 1.513369 1.942298 2.239055 2.513119 2.684820
-0.205672 0.262350 0.438217 0.606959 0.798794 1.451892 1.730536 1.885799 2.292567 2.433348
-0.304096 0.348725 0.817557 0.973213 1.149195 1.769516 1.914392 2.234704 2.592687 2.674729
-0.206504 0.281307 0.376040 0.779557 1.499555 1.886752 2.032034 2.220961 2.528659 2.666047
-0.130572 0.255765 0.794488 1.301534 1.504711 1.681929 2.069095 2.309137 2.695781 2.848379
-0.214845 0.339856 0.490758 0.723584 1.026000 1.188343 1.937657 2.288473 2.513405 2.753320
-0.359564 0.482479 0.670546 1.042777 1.240083 1.360140 1.592377 1.718141 2.214001 2.639319
-0.106171 0.136363 0.239866 0.666826 1.262252 1.543841 1.886197 2.162484 2.518336 2.782589
-0.188744 0.251920 0.360219 0.913075 1.618822 1.785177 1.927723 2.115808 2.320559 2.642776
-0.225904 0.378515 0.558007 0.728218 0.996381 1.117859 1.477832 1.960983 2.185323 2.667571
-0.436819 0.511780 0.811933 1.004760 1.128440 1.604755 1.813182 1.987683 2.595291 2.709021
-0.249083 0.362078 0.480846 0.813722 1.404123 1.566622 1.741757 2.142883 2.302238 2.567856
-0.249083 0.362078 0.480846 0.813722 1.404123 1.566622 1.741757 2.142883 2.302238 2.567856
+++ /dev/null
-5 2048
--0.002077 -0.038247 -0.036477 -0.003710 0.058915
--0.035874 -0.128709 0.029183 -0.019849 0.049800
--0.007389 -0.040358 0.044426 0.047695 -0.043474
-0.075558 0.066718 -0.000350 -0.002910 0.009981
--0.009790 0.076568 -0.100581 0.021504 -0.026649
--0.026362 -0.100884 -0.003799 0.061469 0.001711
--0.034198 -0.008936 0.039170 -0.055448 -0.078447
-0.028441 -0.038152 0.015590 0.036567 -0.041377
-0.049588 -0.091695 0.004580 -0.055922 -0.041638
--0.025374 -0.037246 -0.002046 0.002822 -0.108640
--0.050719 0.152889 0.036331 0.025204 -0.017701
-0.035302 0.120953 0.037832 -0.092915 0.065586
--0.048191 -0.092276 -0.077588 -0.043380 0.071115
-0.011347 -0.004383 0.064201 0.091266 -0.037474
-0.019023 0.014911 -0.012935 0.038099 0.015753
-0.005340 -0.046005 0.048595 0.061014 0.075044
-0.083994 -0.042736 0.000191 -0.120346 0.059455
--0.040009 -0.085618 -0.022013 0.016604 -0.021977
--0.041351 0.055057 0.041498 -0.057724 -0.004755
-0.046951 0.098620 0.036630 -0.034510 0.026358
-0.034831 -0.018107 -0.038210 -0.024564 -0.076584
--0.038199 -0.082180 -0.087172 0.100873 -0.013934
-0.007410 0.052748 -0.012468 -0.086356 -0.004344
--0.008693 0.023248 0.088995 0.063277 -0.010981
--0.014865 -0.008322 -0.026526 0.001412 -0.009086
--0.041663 -0.082625 0.022751 -0.040388 -0.157427
-0.000052 0.047105 0.090012 0.049647 -0.052600
-0.043776 0.044112 -0.006996 0.035467 0.033674
-0.038165 0.009940 -0.005274 -0.025234 0.012284
-0.059331 0.033687 -0.030071 0.038173 -0.045016
-0.026068 0.158444 0.048818 -0.057637 0.009770
--0.040754 -0.099489 -0.027782 -0.004839 0.170178
-0.018211 -0.024125 -0.001981 -0.056519 0.022604
-0.043672 -0.084946 0.014191 0.071154 -0.005074
--0.088121 -0.013992 -0.039939 0.008830 -0.019720
--0.014986 0.009192 -0.018737 -0.054735 -0.013960
--0.001601 0.002582 -0.065304 0.007212 -0.013857
--0.007417 -0.077118 -0.033128 0.041117 0.100625
-0.000688 -0.014708 -0.011064 -0.123109 -0.008590
-0.038570 -0.013241 0.026994 -0.007213 -0.000633
-0.001257 -0.072096 0.057499 0.003234 0.041459
--0.084929 -0.010858 0.034929 0.018375 -0.101168
--0.009436 0.035974 -0.047298 0.107772 -0.014572
--0.033241 0.076725 -0.052278 -0.044989 0.064574
--0.034320 -0.080934 -0.062584 -0.052365 -0.007583
-0.043332 -0.039973 0.001890 0.081092 0.032425
-0.072661 0.019296 -0.009173 -0.013795 -0.048534
-0.003494 -0.036829 0.029480 0.062652 0.019438
-0.003633 -0.011968 -0.096593 -0.102286 0.064289
--0.051416 -0.052157 -0.106111 0.005858 -0.031779
-0.001473 0.071136 -0.017587 0.041119 -0.084642
--0.019285 0.061407 0.024265 -0.082217 0.101714
--0.021349 -0.011424 -0.157899 -0.011584 0.086331
--0.079601 0.013742 -0.095978 0.093032 0.011498
--0.108846 -0.042340 -0.021774 -0.091363 -0.082840
--0.068721 -0.023200 0.069062 0.025331 -0.063542
--0.002176 -0.044709 -0.011586 -0.035579 -0.061392
-0.002329 -0.055782 0.087560 -0.009142 -0.031210
-0.087176 0.029363 0.048300 0.030101 0.003028
--0.006744 0.110741 0.047285 0.042711 0.114962
--0.014983 0.067022 -0.034867 0.007693 0.108661
-0.072716 0.001158 -0.020279 0.097118 -0.049090
-0.018332 0.073348 0.048479 0.038012 -0.075550
-0.024128 -0.002290 0.027979 -0.007476 0.128642
-0.063321 -0.016130 -0.010724 -0.033216 0.012203
-0.004603 -0.069020 0.019149 0.023442 -0.041990
-0.001559 -0.054141 -0.017873 0.001051 0.009669
-0.007371 0.043631 0.032348 -0.066689 -0.007712
-0.075542 0.039341 -0.074389 0.089409 -0.067587
-0.013297 -0.123535 -0.034031 0.013429 0.024826
-0.017265 0.052105 0.067939 -0.101957 -0.053347
-0.046413 0.004984 0.062332 0.030324 0.060242
--0.025911 -0.060816 0.054284 -0.056832 0.016850
-0.007933 -0.018569 -0.000549 0.026701 -0.090331
--0.006708 0.055666 0.016664 0.060888 -0.010839
--0.037232 0.056511 -0.020495 -0.017025 0.030780
--0.059804 -0.054145 -0.035811 -0.030383 -0.022947
--0.038436 -0.017628 -0.001154 0.071736 0.013679
-0.089806 0.109393 0.002158 0.022933 -0.009429
--0.081438 -0.020658 0.036259 0.054585 0.017455
-0.037820 0.018769 -0.052528 -0.146355 0.121991
--0.018012 -0.054744 0.003927 0.003980 -0.068627
--0.025582 0.068240 0.012886 -0.118982 -0.025012
--0.060768 0.074453 0.039306 0.043620 -0.021238
-0.008481 -0.086583 -0.067953 0.013657 -0.016164
-0.052682 0.037754 -0.034526 0.147500 -0.038053
--0.000554 0.038997 -0.033353 -0.103730 -0.024374
-0.063047 0.007908 0.052749 -0.060232 0.105523
--0.018157 -0.023187 0.050942 -0.044718 0.023590
--0.031973 -0.076362 0.073925 0.002114 -0.024398
--0.058682 0.080042 0.018073 0.170306 0.034023
-0.049977 -0.005101 0.005590 0.044243 0.045804
--0.002783 0.065756 -0.036121 -0.026414 -0.032356
-0.022865 0.009608 0.014138 0.076862 -0.045138
-0.060759 0.119694 0.029403 -0.106477 -0.030301
-0.005873 -0.044463 0.032373 0.018732 0.030235
-0.054996 0.014096 -0.056245 -0.108233 0.076912
--0.003553 -0.057174 0.014594 -0.044747 -0.000811
--0.070712 0.032588 0.016264 0.000303 0.049043
-0.009463 0.074638 0.018082 0.009662 0.016092
-0.002476 0.044398 -0.087719 -0.019282 -0.061589
-0.060302 -0.067478 -0.040506 0.023576 0.052937
--0.072603 -0.012619 0.001381 -0.072008 -0.029615
-0.037036 -0.024612 0.072062 -0.042065 0.019378
--0.040438 -0.119783 -0.006434 -0.060809 0.085511
--0.008272 0.020380 0.022744 0.066027 -0.063608
-0.000489 0.072277 0.001453 0.008278 0.040882
-0.032724 0.159938 -0.041156 0.022564 0.038648
-0.014324 -0.095703 -0.056763 -0.088713 0.020001
--0.023825 0.027423 -0.018492 0.065606 0.000365
-0.039845 0.018820 -0.038350 -0.078718 -0.033629
--0.001663 0.009565 0.108200 0.058847 0.065809
--0.049633 -0.045554 0.020137 -0.086381 0.091892
--0.002517 -0.024076 -0.000222 0.049573 -0.129418
--0.045283 0.051515 -0.006173 0.029917 -0.010061
-0.006979 0.078079 0.067161 -0.006824 0.036737
-0.001946 0.029299 -0.146673 0.005204 -0.049944
--0.003573 -0.022387 -0.192735 0.086714 0.000681
-0.023023 0.025278 0.032334 -0.092047 -0.097106
-0.009314 -0.026795 0.048717 -0.014619 0.009445
--0.034367 0.013246 0.033975 0.027681 -0.048279
--0.034841 -0.011498 0.129486 0.012413 -0.099857
--0.009759 0.017468 0.030971 0.054610 0.058014
--0.053387 0.017293 0.044926 0.081337 0.056077
--0.014173 0.033715 -0.080168 -0.039195 0.057433
--0.008063 -0.024017 -0.029873 0.059315 -0.016884
-0.037413 0.102710 0.039066 -0.000322 -0.007096
-0.001081 0.004899 0.064913 -0.009724 0.052938
-0.080878 -0.088833 0.017234 -0.064402 0.068572
--0.037607 -0.071831 0.000857 0.017839 -0.001686
-0.014565 0.002904 0.000522 -0.003298 0.002213
-0.095679 0.012244 0.036755 -0.099818 0.011289
--0.028433 0.070577 -0.043776 -0.022561 -0.076359
--0.030471 -0.127211 -0.047570 0.077242 -0.002030
-0.022748 -0.045608 0.087172 -0.006712 -0.112507
-0.048520 -0.049787 0.033883 0.026952 0.022558
-0.062996 0.012765 0.026950 -0.066289 -0.068448
-0.054918 0.003780 0.040104 -0.005777 -0.085504
-0.064809 0.077196 0.014756 0.043405 0.023787
-0.031364 0.128719 -0.042317 -0.004864 0.087827
--0.029815 -0.093621 -0.008519 -0.023955 0.051611
--0.014788 -0.068189 0.037225 0.179376 -0.029766
-0.060538 0.006306 0.012777 0.019308 0.009494
--0.008692 -0.017852 0.038436 0.046522 0.130088
--0.012523 -0.023608 0.032478 -0.090472 0.044247
--0.044404 -0.030180 -0.040445 0.035083 -0.032830
--0.072877 0.049263 0.081485 -0.069301 0.014635
--0.057655 0.197364 -0.000351 -0.022115 0.039887
-0.042215 -0.009109 -0.086347 -0.104682 -0.049640
--0.047970 -0.025332 -0.040848 0.083051 -0.021243
--0.028802 0.015424 0.001733 -0.128243 -0.060411
-0.055727 0.057515 0.146167 -0.056022 0.024345
-0.002416 -0.015298 0.002236 -0.020925 -0.036973
--0.029182 -0.058852 0.072372 -0.069443 -0.038400
--0.056167 0.006957 0.068247 0.059373 -0.048485
-0.034235 0.048623 -0.036035 0.085210 0.110573
--0.015337 0.046972 -0.043542 0.006351 0.031155
-0.088626 0.069233 0.008134 0.019241 -0.060153
-0.041371 0.089979 -0.041853 0.023626 0.016064
--0.053828 -0.049329 -0.016176 -0.013092 0.057257
-0.069686 -0.046114 -0.045261 -0.039290 0.020585
-0.061314 -0.027727 -0.001927 0.022808 -0.015832
--0.075912 -0.014836 0.002965 0.081369 -0.022597
-0.005534 0.065315 0.044334 -0.043319 -0.041186
--0.013693 0.026330 -0.020694 0.032579 -0.067664
--0.035584 -0.076274 -0.115553 0.029283 0.115779
-0.013526 -0.034741 0.010015 -0.130855 -0.047597
-0.080984 0.031915 0.048376 -0.028547 -0.023234
--0.052917 -0.103074 0.071678 -0.043019 -0.020299
--0.045608 0.007487 -0.028223 0.036499 -0.089053
--0.034453 0.074651 -0.025209 0.077487 -0.013263
-0.004921 0.072189 -0.050852 0.059399 0.035439
-0.002935 -0.054894 -0.031357 -0.070326 -0.036947
--0.026730 0.036590 -0.025250 0.113258 0.121094
-0.080910 0.042350 -0.092512 -0.043499 -0.025455
-0.034745 -0.070282 0.032647 0.111722 -0.019157
-0.020761 0.013997 -0.061982 -0.060954 0.055112
-0.036288 -0.080176 -0.027267 0.012212 -0.093795
--0.041882 0.097155 0.087384 -0.031435 -0.082801
-0.009464 0.032459 0.077828 -0.112376 0.108840
-0.019555 0.014775 -0.073011 -0.043973 0.011444
--0.048044 0.056260 -0.038387 0.043656 0.008263
--0.014005 -0.016142 -0.038569 -0.064552 -0.057510
--0.078202 -0.059032 0.084016 -0.010298 0.012574
--0.020059 -0.064059 -0.059392 -0.046799 -0.054238
-0.022026 -0.006059 0.084724 0.041685 -0.029012
-0.026514 0.032033 0.022922 0.031857 0.030105
--0.035650 0.031377 -0.030435 0.061662 0.079732
--0.025495 0.041751 -0.112711 -0.015737 0.015504
-0.121804 -0.030913 -0.016931 0.056284 -0.031211
--0.038259 -0.005525 0.074063 -0.019980 -0.074225
--0.043126 -0.008346 0.052048 -0.010386 0.102477
-0.020457 -0.053151 0.037134 -0.048166 0.025535
--0.004324 -0.102005 0.042549 0.062684 -0.011027
--0.041502 -0.022180 -0.001040 0.012690 0.058495
-0.039481 0.061425 0.036436 -0.094401 0.024691
--0.002509 -0.024231 -0.105831 0.050352 -0.105564
-0.036061 -0.093016 -0.042697 0.049621 -0.014022
-0.037095 0.014433 0.054764 -0.096569 -0.011104
-0.004844 0.011453 0.022667 -0.022798 0.002655
-0.021742 -0.079613 0.045351 -0.079863 0.014770
-0.050245 -0.026754 -0.023870 0.015727 -0.098730
-0.042398 0.154448 -0.009362 0.081429 -0.020656
--0.072560 0.133852 0.025744 -0.109001 0.075747
--0.059454 -0.002469 -0.103847 -0.008798 0.031741
--0.020032 -0.011426 -0.002985 0.061967 -0.058554
-0.096033 0.053995 -0.071745 0.012181 0.016611
--0.051161 -0.042525 0.015651 0.078963 0.054139
--0.007119 0.014112 0.000797 -0.147306 0.012158
--0.048199 -0.042152 -0.060602 0.035608 -0.095526
--0.044437 0.079277 -0.036361 -0.085666 0.005652
--0.035263 0.081781 0.098388 -0.015160 0.032423
-0.048597 -0.010937 -0.045141 -0.016016 -0.045851
-0.017285 0.029554 -0.068669 0.090490 -0.069378
--0.015215 0.065693 -0.080376 -0.098850 -0.001785
--0.000808 0.001812 0.047789 -0.059522 0.029808
--0.040358 -0.013967 -0.035444 -0.057752 0.011251
-0.027783 -0.009928 0.081566 -0.060520 -0.032563
--0.018103 0.008202 0.020263 0.036779 0.028019
-0.034566 0.020755 0.010139 0.022813 0.071878
--0.033001 0.012734 -0.101437 -0.069713 0.016386
-0.040255 0.034849 0.017738 0.082952 0.030522
-0.011027 0.101822 0.000381 -0.044621 -0.048575
--0.018043 -0.104642 0.042318 0.024433 0.071077
-0.028556 0.050381 -0.035783 -0.004765 0.019134
-0.004109 -0.114088 -0.030007 -0.003475 -0.033302
--0.132027 -0.012463 -0.036186 0.000562 -0.054043
--0.003544 0.052264 0.043304 0.012117 0.016872
--0.034524 0.066372 -0.065579 -0.033370 0.014889
-0.004579 -0.049747 -0.050504 0.049331 0.040066
--0.125392 -0.097291 0.050421 -0.071309 -0.051625
-0.065285 0.022484 0.062435 0.017569 -0.040502
--0.004470 -0.054208 0.010625 -0.094016 0.022508
-0.033725 0.032426 -0.015455 0.036159 -0.115369
--0.103817 0.142767 -0.000238 -0.019162 0.008959
-0.030765 0.075502 -0.088049 0.017398 0.024749
--0.021910 -0.075993 -0.149318 -0.174722 0.102620
-0.008195 -0.009007 0.007189 0.076657 0.014460
-0.034428 0.027255 -0.013869 -0.050491 -0.048691
-0.037759 -0.098562 0.085631 0.021691 -0.000794
--0.029941 0.026585 -0.033603 -0.014074 0.066789
-0.005141 -0.012246 -0.067551 0.100708 -0.040232
--0.002751 0.049901 0.016959 0.021812 -0.059523
--0.022331 0.030079 0.058567 -0.029002 0.104237
--0.013602 -0.035019 -0.155316 0.016558 -0.013881
-0.004136 -0.001657 -0.097220 0.019060 0.052990
-0.004200 0.054365 -0.016768 -0.045191 -0.105984
--0.052803 -0.016935 0.092437 -0.013893 -0.033606
--0.023246 -0.039305 0.036068 -0.020164 -0.060244
-0.045916 -0.014132 0.044463 0.046890 -0.118975
-0.074037 0.010976 0.090692 0.090068 0.023711
--0.044310 0.007556 -0.037900 0.026798 0.084256
-0.002559 0.013715 0.004015 0.008334 0.101711
-0.022258 0.030790 -0.065656 0.019198 -0.035505
-0.026328 0.028683 0.115303 -0.028803 -0.086521
--0.004355 -0.046031 0.011248 -0.040795 0.121216
-0.000425 -0.056590 0.011373 -0.070856 0.064965
--0.043302 -0.095015 0.013747 0.048043 0.047157
--0.046839 -0.005878 -0.013815 0.028948 -0.001373
-0.115513 0.049750 0.038856 0.002747 0.068706
--0.059471 0.083940 -0.035785 0.026815 -0.027017
-0.004618 -0.093707 -0.031970 0.104710 -0.008533
--0.008056 -0.017611 0.038062 -0.073507 -0.036477
-0.022407 -0.059049 0.022840 0.012451 -0.010174
-0.057217 -0.050858 -0.053612 -0.064090 -0.097360
-0.041668 -0.011445 -0.075167 0.006584 -0.122856
--0.011272 0.137465 -0.067901 0.011357 -0.050853
-0.020753 0.070596 0.004302 -0.066991 0.055696
--0.043828 -0.042721 -0.096928 -0.047589 0.046254
--0.027538 -0.005234 0.030541 0.077571 -0.039512
-0.032372 -0.022397 0.002903 0.014010 0.028365
-0.007460 0.011506 0.019889 0.062747 0.095319
-0.052300 0.007374 0.036028 -0.116833 0.049517
-0.004313 -0.039924 -0.005692 0.035446 -0.006279
--0.092093 0.025645 0.053023 -0.015761 -0.045887
--0.018082 0.081602 0.046870 0.015485 0.067284
-0.055890 0.008159 -0.036149 -0.067704 -0.096800
-0.015948 -0.036949 -0.083131 0.080618 0.031677
-0.025776 0.047673 -0.012634 -0.098220 0.039341
-0.018630 0.024685 0.068760 -0.009148 -0.006932
-0.000131 -0.009954 -0.075954 -0.020703 0.000996
--0.040731 -0.082876 0.075619 0.017000 -0.130026
-0.003839 0.083757 0.085935 0.058477 -0.018794
-0.019268 0.053820 -0.025907 -0.016484 0.048963
-0.017315 0.011801 -0.016617 -0.016373 0.052079
-0.016567 0.064592 -0.011714 0.047244 -0.029583
--0.010269 0.112646 -0.025079 -0.018015 -0.021550
--0.019521 -0.111462 -0.047937 -0.002779 0.083724
-0.004416 0.004607 -0.006974 -0.101561 0.027376
-0.083440 -0.109869 -0.002361 -0.011364 -0.079707
--0.138325 -0.095825 0.034339 0.024551 -0.012431
--0.000401 0.007608 0.013950 -0.060441 0.010061
-0.012546 -0.000065 -0.023529 0.015494 -0.012896
--0.014981 -0.019040 -0.043634 0.076437 0.059672
-0.014985 -0.037394 0.020033 -0.082023 -0.016717
-0.029711 -0.006237 0.055347 0.024365 0.002094
-0.019464 -0.038260 0.127306 -0.051862 0.049168
--0.074259 -0.022269 0.023182 0.071183 -0.065354
--0.055933 0.064170 -0.055712 0.107983 0.054978
-0.015294 0.093224 -0.052328 0.000761 -0.020823
-0.023903 -0.063241 -0.093322 -0.054658 -0.006845
-0.048141 -0.023201 -0.047564 0.106605 0.000059
-0.146340 0.030121 -0.040556 -0.020381 -0.050294
-0.016659 -0.021563 0.027855 0.069633 -0.009148
-0.027112 0.056646 -0.023372 -0.211107 0.014012
--0.019924 -0.122201 -0.040118 0.003571 -0.146470
-0.017162 0.075261 0.002383 -0.006374 -0.081174
-0.043906 -0.005278 -0.027448 -0.046459 0.140484
-0.008671 0.019853 -0.128017 -0.022950 0.048609
--0.019167 -0.010958 -0.061823 0.072910 0.001440
--0.023976 -0.030275 0.027463 -0.138470 -0.139145
--0.028088 -0.013451 0.113264 0.081011 -0.012685
-0.006025 -0.055737 0.022779 -0.019951 -0.046793
--0.015091 -0.017958 0.063092 0.032101 -0.004007
-0.052309 0.070815 0.012148 0.095984 0.074330
-0.006032 0.083156 -0.045278 0.013825 0.066658
--0.000966 0.053253 -0.095660 -0.022943 0.108130
-0.092983 -0.012055 0.008111 0.064988 0.010427
-0.042345 0.042586 0.077502 0.053009 -0.031546
--0.004484 -0.019859 0.027061 0.016614 0.085821
-0.089250 0.014975 -0.022722 -0.045228 0.047095
--0.028190 -0.124509 -0.029014 0.024231 -0.016564
--0.025209 -0.031288 -0.023742 0.040341 0.030385
--0.022564 0.023760 0.018611 -0.077310 0.051696
-0.028200 0.005454 -0.045487 0.027221 -0.074627
--0.040934 -0.110565 -0.103536 0.033125 0.041451
--0.017540 0.013737 0.131164 -0.103202 -0.000294
-0.030605 -0.030002 0.058861 0.024425 0.055122
-0.021447 -0.043394 0.039465 -0.020523 -0.012530
--0.003317 -0.002650 -0.020200 -0.002414 -0.060515
-0.003135 0.115504 0.005075 0.072669 0.057819
--0.075310 0.064527 0.025999 -0.067556 0.046351
--0.124098 -0.049305 -0.009230 -0.084801 0.068375
--0.026781 -0.066657 0.010588 0.093986 0.017406
-0.047141 0.053480 -0.019255 0.069267 0.010659
--0.068511 0.015815 -0.011687 0.047685 0.033658
-0.064260 0.062994 0.018822 -0.143452 0.092703
--0.029884 -0.006035 -0.016152 -0.021618 -0.045339
--0.049252 0.041988 -0.021510 -0.039175 -0.031350
--0.101541 0.005832 0.055761 0.009961 0.086386
-0.007597 -0.052775 -0.079976 0.023111 0.004302
--0.020123 0.039264 -0.062497 0.078009 0.004409
--0.063787 0.038329 -0.055050 -0.086972 -0.084417
-0.025733 -0.011156 0.104895 0.026765 0.037827
--0.013149 0.009709 0.004095 -0.039085 0.041414
--0.018153 -0.088525 0.078011 -0.022509 -0.080366
--0.047630 0.036346 0.013702 0.071239 0.024081
-0.114305 -0.072565 0.004642 0.035947 0.040623
--0.017954 0.045965 -0.007375 -0.030016 -0.004483
-0.040170 0.083716 0.012267 0.096863 -0.028263
-0.000694 0.069353 0.024960 -0.069792 -0.070096
--0.028321 -0.072324 0.018256 0.000091 0.049255
-0.038695 0.041521 -0.035000 -0.034223 0.090426
--0.004319 -0.060041 0.030034 -0.014687 0.016165
--0.139996 0.013811 0.037782 -0.083214 0.054142
-0.024863 0.017964 0.045207 0.006294 0.058657
--0.071515 0.093447 -0.050680 -0.014853 -0.071657
-0.007823 -0.010828 -0.096918 0.050508 0.136819
--0.042282 -0.060920 -0.006691 -0.054808 -0.055435
-0.076309 -0.048186 0.105925 -0.031527 -0.030737
--0.043870 -0.102846 0.054550 -0.095983 0.065369
--0.027944 0.014204 0.008256 0.035180 -0.105002
--0.011778 0.036941 -0.007284 0.034566 0.002672
--0.011867 0.094032 -0.081505 -0.042171 -0.012357
-0.025234 -0.142099 -0.011399 -0.092199 0.016061
--0.007420 0.024527 0.010787 0.089568 0.009287
-0.040383 0.043550 0.036649 -0.055816 -0.039815
-0.029883 -0.031089 0.087022 0.064863 0.035410
--0.010187 0.023054 -0.018519 -0.057105 0.026218
--0.007645 -0.026641 -0.033134 0.044367 -0.059939
--0.047569 0.091489 0.022502 0.013205 -0.056318
-0.041414 0.022193 0.081274 -0.006608 0.035220
--0.012493 0.024440 -0.105974 -0.058317 -0.038994
-0.042143 0.057826 -0.117349 0.047843 0.089338
-0.065029 0.029927 -0.014494 -0.010548 -0.129518
--0.033996 -0.030825 0.032254 -0.021848 -0.021345
--0.065200 0.012770 0.020636 -0.034493 -0.080268
--0.015033 -0.018599 0.076611 0.034283 -0.084435
-0.051904 0.063942 0.046362 0.039561 0.096234
--0.030658 0.054240 0.027612 0.022042 0.112035
--0.045512 -0.048431 -0.084263 -0.015994 0.103483
-0.045903 -0.004115 -0.021572 0.057589 0.016494
-0.013949 0.101635 0.127534 0.014985 -0.006815
--0.053449 -0.000707 0.052773 -0.047290 0.071075
-0.041771 -0.079418 -0.026505 -0.082019 0.091756
--0.088458 -0.055800 0.015266 0.048373 -0.028842
-0.004456 0.001112 0.005363 0.012172 -0.036807
-0.063688 0.114491 -0.034186 -0.082173 0.044547
-0.010385 0.061010 -0.075589 0.038888 -0.057732
--0.068354 -0.091781 -0.001533 0.042343 0.007713
--0.003066 -0.016490 0.097581 -0.008705 -0.169889
-0.041901 -0.029045 0.088606 0.028236 -0.005092
-0.087986 -0.005514 -0.001520 -0.067407 -0.036923
-0.018378 -0.001874 0.029761 -0.028224 -0.114769
-0.024657 0.082316 0.020235 0.034884 -0.039374
-0.106617 0.085265 -0.014306 -0.039880 0.059967
--0.020866 -0.045287 -0.013407 -0.029010 0.025480
-0.020099 -0.053760 0.035241 0.067883 -0.069313
-0.022318 0.001659 -0.045385 -0.001930 0.007348
-0.027072 -0.051692 0.069337 0.012098 0.107819
--0.026942 -0.039741 0.043295 -0.135918 0.031043
--0.040145 -0.021705 -0.052514 0.001132 -0.030098
--0.040748 0.046793 0.149894 -0.021036 -0.023530
--0.040778 0.085491 0.068161 0.033268 0.032992
--0.008355 0.008600 -0.125074 -0.034204 -0.082832
-0.030318 0.000442 -0.007943 0.113836 -0.044022
-0.015079 0.065357 -0.018956 -0.092656 -0.056274
--0.017481 -0.004857 0.117201 -0.005233 0.069151
-0.011030 -0.024316 -0.015695 -0.011308 -0.005062
--0.010876 -0.038919 0.032578 -0.054136 -0.121302
--0.046807 0.041175 0.059588 0.031040 -0.027127
-0.021551 0.000830 -0.013766 0.046306 0.081467
-0.014301 -0.010731 -0.051227 -0.018797 0.043587
-0.050317 0.086115 -0.027629 0.046202 -0.084445
-0.021044 0.041527 0.005458 0.006677 0.002404
--0.037453 -0.035957 -0.039078 -0.063247 0.088516
-0.079477 0.004030 -0.063421 -0.074051 -0.039753
-0.062917 -0.119760 -0.002471 0.000423 0.007336
--0.124273 0.001094 -0.026391 0.070714 -0.035166
-0.037072 0.018118 0.017500 -0.050692 -0.015928
--0.003390 -0.002367 -0.040046 0.013349 -0.041478
--0.034407 -0.009890 -0.095593 0.109253 0.041509
--0.062990 -0.041682 0.001528 -0.124601 -0.030128
-0.086076 0.003516 0.073015 0.024339 -0.069858
--0.022435 -0.042554 0.107497 -0.132302 0.035124
--0.105430 0.042327 -0.064964 0.057304 -0.092634
--0.058398 0.052083 0.018947 0.087990 -0.026444
-0.023373 0.037085 -0.083589 0.015247 0.016566
--0.026782 -0.070361 -0.019757 -0.109826 -0.040199
--0.009688 -0.005408 -0.003769 0.111444 0.029897
-0.070686 0.021466 -0.052076 0.015609 -0.023854
-0.008088 -0.022084 0.052542 0.122824 -0.018174
--0.009808 0.107602 -0.059166 -0.100824 0.082456
--0.004737 -0.023536 -0.095212 -0.007114 -0.098814
--0.061778 0.049247 0.025130 0.010909 -0.091691
-0.034764 -0.014047 0.002819 -0.050330 0.085399
-0.057257 -0.052435 -0.067151 -0.012311 0.040602
--0.118166 0.053141 -0.119211 0.024274 0.027075
--0.022345 -0.060443 -0.046916 -0.099227 -0.115958
--0.071020 0.015499 0.055810 -0.012697 0.010803
--0.051685 -0.097540 0.013970 -0.096689 -0.060525
-0.010422 0.018434 0.151855 0.015230 -0.080804
-0.040130 0.043946 0.022887 0.043819 -0.027371
-0.037213 0.059423 -0.040656 0.141843 0.065180
--0.083238 0.057208 -0.113200 -0.056009 0.030056
-0.060522 -0.054570 0.006137 0.062833 -0.081547
-0.002753 0.037357 0.055441 0.049180 -0.017699
--0.006225 0.029216 0.040657 0.016328 0.041969
-0.058998 -0.067000 0.002571 -0.008178 0.027776
--0.026103 -0.049399 0.093279 0.052313 -0.029958
--0.070689 -0.054589 0.027325 -0.010464 -0.000604
-0.009479 0.125126 0.086072 -0.052874 0.065774
-0.003009 0.013855 -0.088166 0.018907 -0.064212
-0.023827 -0.024022 -0.121652 0.032035 0.015278
-0.023427 -0.027194 0.066092 -0.100117 -0.048548
-0.013755 0.005344 0.038451 -0.000513 0.018468
-0.065931 -0.062001 0.035615 -0.067561 -0.013315
-0.045441 -0.016064 0.010535 0.035953 -0.068093
-0.035872 0.097935 -0.025516 0.061435 0.028137
--0.042656 0.110708 -0.022981 -0.052860 -0.009583
--0.084678 -0.040172 -0.092364 0.061778 0.003794
--0.002964 -0.047375 -0.029968 0.090529 -0.045382
-0.103144 0.034998 -0.012760 0.013885 0.048887
--0.049886 -0.034647 0.061193 0.058574 0.084107
--0.022304 -0.008817 0.036857 -0.119972 0.000619
--0.079467 -0.031710 -0.108927 -0.033843 -0.034845
--0.125290 0.079806 -0.011673 -0.070719 -0.063897
--0.051524 0.042071 0.082303 -0.016684 0.053366
-0.024657 -0.062913 -0.040533 -0.032117 -0.013188
-0.036519 0.055734 -0.134481 0.055949 -0.050480
-0.002035 0.010998 -0.064264 -0.078569 -0.026404
--0.017580 0.005453 0.068795 -0.031274 0.024178
--0.038245 -0.037973 -0.013256 -0.072256 0.057358
--0.004941 -0.047850 0.119977 -0.015040 -0.079231
--0.013449 -0.005542 0.028890 0.032536 -0.020619
-0.083769 -0.028624 0.049040 0.021538 0.104107
--0.072475 0.019284 -0.044425 -0.058775 0.061172
-0.025682 0.004208 0.041846 0.095369 0.007892
-0.030701 0.062103 -0.086288 -0.068866 -0.110743
-0.052685 -0.069032 0.010339 0.044804 0.106157
-0.105575 0.017263 -0.110890 -0.040735 0.061412
-0.021037 -0.102095 0.039008 0.010335 0.005686
--0.108307 0.057569 -0.004539 -0.019864 0.033710
--0.031254 0.013482 0.035051 0.014893 -0.001676
--0.053780 0.014329 -0.037130 0.010087 -0.043959
-0.031302 -0.006715 -0.065618 0.066261 0.071102
--0.085133 -0.020753 0.050721 -0.042021 0.006613
-0.038123 0.041345 0.095993 -0.028353 -0.008509
--0.039544 -0.069281 0.047585 -0.020085 0.000819
-0.000478 0.017818 0.008015 0.068812 -0.184380
--0.073606 0.120550 -0.032173 0.058092 0.024132
--0.016705 0.130871 -0.094852 0.044256 0.003919
--0.002119 -0.026963 -0.003553 -0.110166 0.083113
--0.008545 -0.026785 0.025936 0.069075 0.054271
-0.029418 0.039817 0.040088 -0.036680 -0.073300
--0.003368 -0.074471 0.111772 0.030913 -0.018960
--0.040689 0.058799 -0.017810 -0.064269 0.071408
--0.022927 -0.077256 -0.075665 0.100717 -0.099471
-0.004792 0.063353 -0.017202 -0.012465 -0.052031
-0.015659 0.049801 0.020300 0.001231 0.061694
--0.002196 -0.039936 -0.095913 -0.006760 -0.036261
--0.004827 -0.023039 -0.062452 0.023724 0.043337
-0.002849 -0.004311 -0.067199 -0.039365 -0.082845
--0.036454 -0.014788 0.059651 -0.039192 -0.021445
--0.003667 -0.011645 0.021036 -0.006220 -0.025338
-0.010705 -0.002077 0.043196 0.035112 -0.036895
-0.017671 0.003759 0.106991 0.040822 0.011089
--0.048837 0.025240 -0.002343 0.015983 0.080230
--0.005045 -0.000454 -0.055852 -0.004494 0.084580
-0.044207 -0.018164 -0.035672 0.024802 -0.028216
-0.026617 0.021648 0.082157 0.012675 -0.049856
-0.001020 -0.118363 0.069854 -0.038161 0.096174
-0.032049 -0.035139 -0.015943 -0.028306 0.055425
--0.092742 -0.074326 0.010130 -0.020646 0.043131
--0.014246 -0.037891 0.006922 0.059464 -0.023168
-0.059938 0.021652 -0.004602 -0.005103 0.062343
-0.000410 0.032704 -0.087978 0.042098 -0.008283
-0.000714 -0.078595 0.004443 0.036763 0.004995
--0.050964 0.045909 0.038942 -0.052841 -0.054318
-0.033939 -0.020268 0.019574 0.029805 -0.002001
-0.068470 -0.056316 0.007236 -0.031313 -0.066063
--0.003425 0.022247 -0.018479 -0.008040 -0.105011
--0.109717 0.132884 0.056892 0.052155 -0.073444
-0.051067 0.107179 0.014594 -0.036657 0.110846
--0.009896 -0.042527 -0.082220 -0.007607 0.057007
--0.034754 0.003213 0.041643 0.142016 -0.007658
-0.012781 0.014366 -0.021935 0.010511 0.028021
-0.002082 -0.027023 0.055247 0.097082 0.111840
-0.040151 -0.019830 -0.007033 -0.097207 0.026595
--0.069875 -0.070451 -0.049743 0.053253 -0.019762
--0.078475 0.043019 0.022103 -0.033625 -0.008627
-0.058858 0.080427 0.060029 0.002771 0.041250
-0.030257 -0.044059 -0.001226 -0.060544 -0.126844
--0.029407 -0.021079 -0.108126 0.070012 -0.006653
-0.013084 0.090992 -0.002726 -0.070041 -0.006757
--0.017571 0.027459 0.103937 0.003012 0.038213
--0.007808 -0.011937 -0.015457 -0.033181 0.012816
-0.010199 -0.056227 0.006057 -0.017569 -0.098687
-0.006000 0.076819 0.022272 0.082508 -0.058508
-0.031808 0.054009 0.007871 0.055301 0.070296
-0.023941 0.025656 -0.005875 -0.068203 0.027482
-0.036615 0.026218 -0.011406 0.026235 -0.022002
--0.011161 0.120568 0.023165 -0.010473 0.002080
--0.033028 -0.043255 -0.030454 0.009261 0.113350
-0.023271 -0.015934 -0.037492 -0.032890 0.016928
-0.020967 -0.090717 -0.016510 0.070725 -0.063975
--0.097203 0.017597 0.016946 0.027298 -0.016049
--0.019287 -0.005319 0.019000 -0.037327 -0.040993
--0.003975 0.027897 -0.095076 -0.010053 -0.014610
-0.005584 -0.024009 0.000599 0.082121 0.098790
-0.005987 -0.036027 -0.067221 -0.128015 -0.052111
-0.056606 -0.020029 0.012172 -0.018025 -0.028588
--0.015169 -0.087101 0.044526 -0.022464 0.054835
--0.084369 -0.058286 -0.039363 -0.003339 -0.116729
--0.051506 0.079944 -0.023815 0.113004 -0.052120
--0.012383 0.075636 -0.024387 -0.039200 0.032050
--0.031568 -0.140199 -0.082589 -0.060485 -0.013115
-0.092001 -0.002684 -0.027087 0.111635 0.050016
-0.077055 -0.010441 -0.006942 -0.026898 -0.083879
--0.008401 -0.026725 0.049993 0.043707 0.027966
--0.019866 -0.057701 -0.086619 -0.114361 -0.008921
--0.039708 -0.122519 -0.074209 0.014381 -0.065102
--0.023419 0.118673 -0.000005 0.071661 -0.127659
--0.009184 0.020308 0.019151 -0.054484 0.096378
-0.016102 -0.060605 -0.128655 -0.004225 0.079251
--0.021895 0.024065 -0.097479 0.045279 -0.036151
--0.045806 0.005106 0.000093 -0.074415 -0.071654
--0.067599 -0.017537 0.050178 0.015860 -0.018919
--0.015382 -0.057989 0.032437 -0.039627 -0.030285
-0.015438 -0.005533 0.110416 -0.004137 -0.030336
-0.085365 0.089779 0.061676 0.017178 -0.016279
-0.028526 0.055656 0.008566 0.000706 0.124966
--0.018124 0.040023 -0.067773 0.028532 0.098381
-0.062832 -0.038523 0.003865 0.065698 -0.026661
-0.076081 0.062167 0.112325 0.052139 -0.040826
-0.003747 -0.052113 0.013442 0.002756 0.102858
-0.040603 -0.012693 0.031245 -0.046645 -0.003625
--0.024647 -0.062463 0.000476 0.024807 -0.036286
--0.003083 -0.015952 -0.016156 0.002976 0.016598
--0.015092 0.058522 0.011542 -0.046504 0.009174
-0.097896 0.056220 -0.055387 0.022356 -0.126788
-0.024795 -0.092333 -0.084406 -0.010051 0.060835
-0.013338 -0.010735 0.052739 -0.119952 -0.093185
-0.010522 -0.001505 0.056134 0.038675 0.016542
-0.005217 -0.061424 0.071990 -0.028908 0.011826
--0.009221 -0.010760 0.023849 0.034664 -0.066108
-0.018587 0.070818 0.013554 0.106469 0.035530
--0.060716 0.072344 0.010625 -0.017888 0.006548
--0.122347 -0.080419 -0.039979 -0.045658 -0.046576
--0.040526 -0.039641 -0.048709 0.067016 0.023042
-0.064800 0.099396 -0.064314 0.005665 -0.025960
--0.094387 -0.056820 0.015466 0.086382 0.024902
--0.019486 0.021888 0.000550 -0.168957 0.071388
--0.019935 -0.042118 -0.040820 -0.012013 -0.072063
--0.004249 0.039160 0.010084 -0.080610 -0.043915
--0.101425 0.074442 0.035350 0.051348 0.051160
--0.031631 -0.053381 -0.062261 -0.020441 -0.031251
-0.050923 0.000358 -0.074646 0.076663 -0.042498
--0.033718 0.037025 -0.017087 -0.091951 0.017983
-0.015622 0.007807 0.087203 -0.061047 0.077306
--0.049822 0.015499 0.035918 -0.044388 0.034786
--0.003435 -0.072680 0.042506 -0.004200 -0.024834
--0.034415 0.065814 0.079911 0.117115 0.013096
-0.065811 0.001560 0.054427 0.085716 0.083343
--0.034994 0.035815 -0.034661 -0.032421 0.000133
-0.021908 0.041958 -0.008418 0.091804 -0.023169
-0.019306 0.087287 0.064984 -0.052908 -0.010301
--0.022717 -0.062698 0.029605 0.020970 0.011270
-0.049229 -0.033794 -0.040198 -0.068419 0.063147
--0.023097 -0.079045 -0.010748 -0.064320 -0.011785
--0.108984 0.015970 -0.038308 0.017991 0.062400
--0.000719 0.044392 0.034008 -0.020969 0.006446
--0.044457 0.044495 -0.084323 -0.014046 -0.057116
-0.037862 -0.024751 -0.045926 0.007665 0.082611
--0.081497 -0.013395 -0.026864 -0.040485 -0.031100
-0.095144 0.005947 0.063254 0.009423 0.031198
-0.008443 -0.078212 -0.002275 -0.025354 0.048808
-0.003982 0.011608 -0.005923 0.061556 -0.091653
--0.028425 0.056332 0.005018 0.007136 0.010607
-0.039647 0.145962 0.007951 -0.017526 -0.039745
-0.023022 -0.066844 -0.047384 -0.044307 0.041848
--0.056589 0.034263 -0.033277 0.073824 -0.030747
-0.009451 0.005157 -0.048186 -0.045749 -0.054258
--0.003301 0.004995 0.071505 0.029585 0.050033
--0.064837 0.012928 0.002785 -0.117405 0.045317
--0.026899 -0.051475 -0.054625 0.064955 -0.136139
--0.083576 0.066985 0.000964 0.024630 -0.036989
-0.049229 0.047537 0.090953 0.036197 0.054765
-0.062892 0.045061 -0.097460 0.009938 -0.027736
--0.008479 0.053538 -0.125219 0.036747 0.027556
--0.017214 0.036754 0.009736 -0.087187 -0.089725
--0.002417 -0.039070 0.076625 0.018126 0.032402
--0.035537 -0.003939 -0.001806 0.018436 -0.060172
--0.024517 0.048085 0.052646 0.044561 -0.126681
--0.005381 0.059991 0.064924 0.047878 0.043526
--0.079817 0.034296 -0.009242 0.037169 0.115281
--0.015147 -0.019430 -0.077776 -0.033431 0.076276
-0.023914 0.014924 -0.049231 0.048491 -0.012740
-0.023873 0.121027 0.067832 -0.009223 -0.039188
--0.018355 -0.042663 0.070587 -0.003855 0.077791
-0.036307 -0.069362 -0.035976 -0.011638 0.103907
--0.055984 -0.110967 -0.002537 -0.016356 -0.022701
--0.018211 0.017831 -0.009534 0.011128 -0.026445
-0.071893 0.028948 0.017993 -0.055001 0.032913
-0.013143 0.141940 -0.030668 -0.010630 -0.075402
--0.008241 -0.097950 -0.070541 0.086461 0.063873
-0.010107 -0.006389 0.086778 -0.017779 -0.056644
-0.040699 -0.054122 0.073702 -0.008815 0.011806
-0.020978 -0.004901 0.046808 -0.038708 -0.048713
-0.065026 -0.042069 0.030306 -0.003984 -0.125105
-0.020044 0.154911 0.060110 0.041504 0.013796
-0.003360 0.144327 -0.056583 -0.031643 0.021938
--0.082644 -0.117123 -0.032869 -0.004149 0.019806
-0.007405 -0.051019 -0.020896 0.133232 -0.028058
-0.050897 0.015399 -0.022377 0.012018 0.002474
--0.031801 -0.041942 0.020380 0.018326 0.106183
-0.038954 -0.045696 0.017961 -0.080241 0.038198
--0.031449 -0.026191 -0.079952 0.035385 -0.053671
--0.055347 0.103293 0.049459 -0.008219 0.010257
--0.061794 0.124358 0.049411 0.069306 0.034282
--0.013114 -0.040074 -0.071968 -0.195520 -0.088871
--0.030547 -0.024227 -0.047665 0.132613 0.012253
-0.036726 0.018979 -0.021295 -0.120084 -0.050532
--0.020265 0.013963 0.136035 -0.067105 0.051832
-0.013865 -0.036402 0.005526 -0.042230 -0.022246
--0.030844 -0.014871 0.097708 -0.055950 -0.060091
--0.107193 -0.000749 0.094279 0.066459 0.015231
-0.068358 0.042724 -0.020943 0.012438 0.110596
--0.022189 0.026125 -0.011649 0.004604 0.037204
-0.039096 0.065797 0.045162 -0.003834 -0.056679
-0.017104 0.070007 -0.005419 -0.016435 -0.000214
--0.097253 -0.033412 -0.004272 0.021730 0.092887
-0.039513 -0.027819 -0.045420 -0.062670 -0.013033
-0.033957 -0.040429 -0.018152 0.020048 0.015966
--0.083740 0.050010 0.032999 0.053057 -0.072973
-0.000797 0.028222 0.063769 -0.045254 -0.001401
--0.008530 0.000350 -0.050423 0.016321 -0.077400
--0.017818 -0.062015 -0.039769 0.103694 0.123584
-0.004844 -0.068111 -0.008528 -0.128884 -0.003312
-0.098749 0.025292 0.013547 0.007157 -0.032589
--0.024049 -0.074941 0.062923 -0.112079 -0.008534
--0.046211 0.028223 -0.041903 -0.001378 -0.077507
--0.015178 0.093495 -0.033668 0.043904 -0.026096
-0.008741 0.024695 -0.042365 0.063246 0.013544
--0.021438 -0.018498 -0.060824 -0.093599 -0.003304
-0.013206 0.019776 0.011491 0.115257 0.066627
-0.042660 0.045968 -0.044189 -0.056683 0.002399
-0.025400 -0.031109 0.037612 0.112170 0.041814
-0.005019 -0.013887 -0.051704 -0.065646 0.030095
--0.006617 -0.067206 -0.053773 0.020368 -0.060694
--0.042554 0.031959 0.034480 -0.016413 -0.056939
-0.026266 0.003617 0.032682 -0.066017 0.064464
-0.025224 -0.014523 -0.107735 -0.028243 0.015327
--0.027555 0.013037 -0.049117 0.015929 -0.001301
--0.010874 -0.018588 -0.021124 -0.055630 -0.102228
--0.048525 -0.057257 0.083344 0.005472 0.060981
--0.022083 -0.107351 -0.002309 -0.015487 -0.065168
-0.011812 -0.029764 0.117191 0.062742 -0.062476
-0.020253 0.014273 0.020564 0.047570 -0.021837
-0.006995 0.009213 -0.047359 0.072944 0.095512
-0.010178 0.039050 -0.077791 -0.020722 0.021947
-0.090992 -0.061050 -0.090772 0.081786 -0.045653
--0.012634 0.036482 0.058533 -0.002696 -0.033458
--0.040412 0.012196 0.010799 -0.011791 0.110559
-0.009821 -0.036074 0.066220 -0.015518 0.056690
--0.027127 -0.071116 0.031944 0.079010 -0.022395
--0.039431 -0.000384 -0.014285 0.016850 0.033711
-0.008705 0.100114 0.041438 -0.100989 0.011356
--0.046625 -0.040932 -0.139483 0.054309 -0.063813
--0.012343 -0.055168 -0.096047 0.031057 -0.034404
-0.061917 0.022545 0.077964 -0.061018 -0.028539
--0.002541 -0.030177 0.006468 -0.005315 0.042803
-0.027882 -0.101187 0.073519 -0.048492 -0.034044
-0.063858 -0.051841 -0.034119 0.025079 -0.055338
-0.022337 0.072417 -0.039178 0.093515 0.010215
--0.063332 0.136724 -0.034306 -0.068709 0.036614
--0.060321 0.003109 -0.064068 -0.001911 0.026497
--0.043444 0.005220 -0.028260 0.089346 -0.073713
-0.082013 0.000948 -0.079297 0.077331 0.007199
-0.013959 -0.089135 -0.001973 0.083595 0.061678
--0.027937 0.074507 0.052481 -0.156418 -0.008126
--0.077649 -0.025098 -0.028822 0.031584 -0.062854
--0.037974 0.052900 -0.008246 -0.058382 0.007371
--0.059698 0.005125 0.103990 0.035731 0.076498
-0.045455 -0.034656 -0.089189 0.010512 -0.022809
-0.023399 0.080456 -0.046407 0.119537 -0.046816
-0.011054 0.024797 -0.075119 -0.091853 0.017319
-0.022797 0.030783 0.051211 -0.054302 0.035466
--0.053426 0.002530 0.020784 -0.089056 0.007237
-0.031757 -0.019566 0.082209 -0.018737 -0.006975
--0.032879 0.000924 0.069241 0.009323 0.017753
-0.041898 0.020597 0.000749 0.046727 0.117703
--0.020501 0.027483 -0.056525 -0.059522 0.018749
-0.025171 0.033068 0.005911 0.134204 0.011451
-0.038296 0.086523 -0.027888 -0.033250 -0.035178
-0.043617 -0.108778 0.024102 0.016641 0.092810
-0.073643 0.030016 -0.066742 -0.010738 0.064668
-0.039526 -0.112082 -0.032794 -0.037218 0.027811
--0.128246 0.003025 -0.070009 -0.076832 -0.013242
--0.030105 0.038807 0.066675 0.013770 0.023016
--0.094473 0.028346 -0.050126 -0.043963 -0.011618
-0.017048 -0.083869 -0.023363 0.030985 0.027338
--0.080760 -0.055583 0.032162 -0.032668 -0.036833
-0.058238 0.020173 0.050309 -0.009187 0.009272
--0.051130 -0.060180 0.014297 -0.085720 0.033908
--0.002635 0.061924 -0.014460 0.025310 -0.143366
--0.086237 0.079075 -0.057641 0.027727 0.053345
-0.030701 0.128530 -0.096663 0.028249 -0.038583
--0.041418 -0.078768 -0.009950 -0.139435 0.050946
--0.001476 -0.004529 -0.005454 0.042876 0.012496
-0.037365 0.037258 -0.009785 -0.014137 -0.075187
--0.015646 -0.084672 0.066850 0.049159 0.022652
--0.100018 0.030626 -0.031693 -0.026283 0.098183
-0.037095 -0.031902 -0.082082 0.064108 -0.081413
--0.016931 0.069276 0.025553 0.019033 -0.009843
-0.021095 0.006896 0.091735 -0.006895 0.125729
--0.038132 -0.025017 -0.094419 0.023870 0.012859
--0.032674 0.010226 -0.092226 -0.004873 0.064962
--0.006137 0.026959 -0.019304 -0.064646 -0.056343
--0.049825 -0.021361 0.067875 -0.021989 0.008580
--0.036917 -0.006108 0.023764 -0.015728 -0.098608
-0.056344 -0.043710 0.075790 0.016095 -0.079516
-0.016637 0.054791 0.091656 0.119050 -0.037915
-0.002929 -0.026705 -0.038725 0.031207 0.092135
--0.016211 0.014904 -0.012804 -0.003882 0.145488
-0.013740 -0.018092 -0.113500 0.052133 -0.037974
-0.032356 0.065081 0.054718 -0.006753 -0.115419
--0.041122 -0.070389 0.024012 -0.033000 0.078595
-0.002090 -0.003576 0.025975 -0.029200 0.073729
--0.067545 -0.099515 0.068346 0.036494 -0.010089
--0.040395 -0.024474 0.000906 0.004180 -0.011648
-0.077079 0.062025 0.048336 -0.047553 0.020667
--0.034650 0.102764 -0.088833 0.063548 -0.063948
-0.004926 -0.075665 -0.010204 0.077117 0.008604
-0.016964 -0.006119 0.015651 -0.060279 -0.084239
-0.021175 -0.041494 0.062789 0.023042 -0.049413
-0.030400 -0.088557 -0.027424 -0.038734 -0.047767
--0.039267 -0.007115 -0.095571 0.040131 -0.172339
--0.015514 0.125809 0.002775 0.011847 -0.039818
-0.003508 0.088794 -0.016537 -0.041801 0.077773
--0.025099 -0.015829 -0.087113 -0.031825 0.018394
--0.033412 -0.037361 0.054089 0.082347 -0.078775
-0.044163 -0.001941 -0.036779 0.006281 0.033103
--0.019683 0.013567 0.044802 0.035896 0.099997
-0.048928 0.024331 0.024339 -0.119730 -0.020516
-0.003938 -0.049114 -0.020101 0.025056 -0.039189
--0.111669 0.015432 0.107806 0.009106 -0.041783
-0.004427 0.114069 0.035561 0.004165 0.048624
-0.065296 -0.020221 -0.112241 -0.024621 -0.104499
-0.040792 -0.042481 -0.126163 0.113850 0.052426
-0.045897 0.073140 -0.038559 -0.101637 -0.010880
-0.014157 0.016488 0.118415 -0.003117 0.015104
-0.005410 -0.047124 -0.034323 -0.038341 0.011107
--0.021536 -0.087493 0.030662 0.003416 -0.087892
--0.019840 0.053393 0.053193 0.082340 -0.013319
-0.013522 0.032147 -0.036372 0.021664 0.058868
-0.001821 0.053133 0.015237 -0.029422 0.049671
-0.032518 0.054852 -0.061126 0.052882 0.005097
--0.000200 0.077584 0.023798 -0.015922 -0.043740
--0.019244 -0.065261 -0.001356 0.041977 0.064243
-0.006831 0.025573 -0.039113 -0.067333 0.007728
-0.061532 -0.086024 0.037808 0.024787 -0.036093
--0.148755 -0.014995 0.025827 -0.017793 -0.025363
-0.010676 -0.014283 0.038621 -0.041757 -0.018561
--0.004984 0.048476 -0.027007 0.007045 -0.010409
-0.017155 -0.042986 -0.059561 0.084763 0.072516
--0.014595 -0.020495 -0.009080 -0.061622 -0.023300
-0.018242 0.008783 0.036423 -0.001710 -0.025459
--0.030263 -0.038355 0.112339 -0.013108 0.030839
--0.050166 -0.045350 -0.006927 0.057254 -0.090539
--0.052734 0.030495 -0.028123 0.095772 0.021287
-0.004939 0.065006 -0.066334 0.009532 0.009978
-0.000692 -0.079650 -0.130620 -0.025115 -0.037193
-0.028545 -0.011885 -0.018329 0.101976 0.056169
-0.074905 -0.039652 -0.019531 -0.031025 -0.031945
--0.004999 -0.024155 0.051113 0.063966 -0.016577
--0.028105 0.007520 -0.098547 -0.151585 0.016061
--0.011144 -0.064311 -0.071227 -0.012819 -0.089185
--0.011034 0.126948 0.065626 0.030017 -0.077054
--0.016170 -0.011244 -0.030183 -0.068083 0.115571
-0.004514 -0.032999 -0.119452 -0.052594 0.048244
-0.006761 0.001824 -0.082055 0.063269 0.016468
--0.015038 0.008738 -0.042234 -0.087201 -0.135683
--0.058265 -0.010563 0.099495 0.035913 0.016120
-0.022021 -0.060263 0.058709 -0.025272 -0.069868
--0.012474 -0.023791 0.072270 0.012475 -0.047178
-0.065743 0.022110 0.027334 0.039002 0.034057
-0.056588 0.090825 -0.083277 0.062553 0.045167
-0.016230 0.042246 -0.055865 -0.029814 0.063583
-0.101556 -0.041974 0.065108 0.059385 -0.023394
-0.067253 0.003519 0.053386 0.071879 -0.052816
--0.014833 -0.034839 0.008862 0.040661 0.076481
-0.113195 -0.022318 0.022988 -0.047563 0.021223
--0.031776 -0.097003 0.010273 0.070963 -0.088181
--0.014952 -0.044557 -0.040211 0.027326 0.055263
--0.027993 0.036839 0.059553 -0.085166 0.023284
-0.081938 0.013347 -0.056030 0.032386 -0.078191
--0.012334 -0.065844 -0.082412 0.021620 0.049765
-0.021974 0.064777 0.116942 -0.066893 -0.029098
-0.063773 -0.015678 0.036050 -0.001531 0.050204
--0.007431 -0.053256 0.019949 -0.084515 -0.052331
-0.003628 -0.002831 0.028651 -0.022563 -0.068663
--0.046864 0.085680 0.035073 0.090355 0.076019
--0.033539 0.078709 0.049120 -0.058380 0.063174
--0.067044 -0.040988 -0.024670 -0.076422 0.022349
--0.059226 -0.063296 -0.024667 0.109900 -0.039214
-0.081493 0.061838 -0.018769 0.054117 0.049416
--0.039105 -0.000888 -0.008740 0.069660 0.056013
--0.013119 0.088704 0.005989 -0.118940 0.055085
--0.021830 -0.027348 -0.037636 -0.044645 -0.013684
--0.033348 0.066928 -0.026840 -0.074085 -0.052255
--0.095346 0.073214 0.052368 0.000793 0.036896
-0.029109 -0.040256 -0.063044 -0.008606 -0.000437
-0.037406 0.035413 -0.064896 0.100694 -0.002451
--0.062127 -0.005213 -0.045513 -0.099165 -0.029096
-0.046180 -0.038707 0.091676 -0.027947 0.081059
--0.051970 0.036875 -0.002862 -0.034628 0.032122
--0.042473 -0.133086 0.097766 0.014513 -0.057376
--0.026905 0.025345 0.058654 0.088520 0.021655
-0.068829 -0.068890 0.073760 0.037294 0.067743
-0.004270 0.030315 -0.017342 -0.022912 0.021230
-0.027415 0.010279 0.033049 0.105463 -0.080985
--0.024846 0.118625 0.017407 -0.060377 -0.071617
--0.034814 -0.031741 0.033114 -0.008946 0.044965
-0.026382 0.068195 -0.053337 -0.079506 0.089886
-0.019186 -0.075490 -0.002131 -0.014334 0.010145
--0.102313 0.044049 0.024515 -0.079086 0.105318
-0.030157 0.019277 0.009149 -0.002192 0.035223
--0.093034 0.037988 -0.056189 0.005485 -0.070967
-0.093206 -0.017940 -0.068121 0.025189 0.098473
--0.047072 -0.057202 0.027986 -0.068841 -0.023193
-0.059350 -0.020968 0.125734 -0.015897 0.013012
--0.018615 -0.122453 -0.008474 -0.064049 0.013910
-0.021902 0.037915 0.039737 0.028260 -0.089535
--0.052408 0.036171 0.024766 0.038944 0.043725
-0.068495 0.097351 -0.051536 -0.026994 0.009734
-0.022521 -0.085412 -0.004269 -0.068523 0.026057
--0.003617 0.002555 -0.024622 0.075742 0.024453
-0.043622 0.048992 -0.003958 -0.051371 -0.010372
--0.009291 -0.026649 0.112796 0.034440 0.000480
-0.000993 0.012835 -0.024524 -0.086702 0.076990
--0.012872 -0.012272 -0.049239 0.045637 -0.100430
--0.080402 0.098860 -0.001607 -0.027740 -0.028447
-0.010187 0.049316 0.064463 -0.032244 0.096351
-0.042173 -0.014830 -0.130350 -0.065157 -0.020131
-0.011826 0.043958 -0.096975 0.094420 0.065360
-0.008046 0.034625 0.022699 -0.011948 -0.162034
--0.028577 -0.049031 0.062518 0.027121 0.011773
--0.062840 -0.028274 0.019513 0.004294 -0.058221
-0.015044 0.032322 0.078632 0.074899 -0.089319
-0.012740 0.036679 0.061490 0.073955 0.074210
--0.042945 0.081229 0.003752 -0.027289 0.107675
-0.028637 -0.027527 -0.094485 -0.014081 0.106655
-0.037034 -0.046495 -0.057983 0.047583 0.007322
--0.000480 0.084590 0.058447 0.010057 -0.044796
--0.035563 -0.017414 0.104652 -0.101773 0.088697
-0.008873 -0.059058 -0.074754 -0.068039 0.080127
--0.042104 -0.067599 0.033969 0.019253 -0.038611
-0.007952 0.028316 -0.003028 0.025731 -0.031708
-0.103465 0.087113 0.002288 -0.034732 0.000345
-0.011011 0.084188 -0.047564 0.007324 -0.100708
--0.031667 -0.084195 -0.045309 0.035772 0.029785
--0.003803 0.041355 0.070690 -0.006148 -0.101234
-0.036078 -0.057998 0.086587 0.069468 -0.017787
-0.043517 -0.032858 -0.018033 -0.080238 -0.054284
-0.011916 -0.027168 0.032061 0.004608 -0.164665
-0.024300 0.127777 -0.001633 0.037157 -0.077063
-0.079112 0.092827 -0.045527 0.012537 0.048156
--0.028838 -0.088344 -0.058200 -0.001037 0.009927
-0.005766 -0.051805 0.035975 0.103039 -0.118515
-0.040739 0.028846 -0.010371 -0.011677 -0.017552
--0.012737 -0.062534 0.096752 0.040808 0.067058
--0.016128 -0.050826 0.049568 -0.159884 0.104117
--0.060870 -0.026777 -0.040150 0.003038 0.011219
--0.047457 0.044509 0.104699 -0.061694 -0.048700
--0.028345 0.058571 0.115771 0.060865 0.049165
--0.017126 -0.029090 -0.087904 -0.040448 -0.053762
--0.009906 0.012529 -0.107155 0.136828 -0.025232
-0.019743 0.120518 -0.033402 -0.147125 -0.096492
--0.011562 -0.010821 0.143581 -0.029410 0.012515
--0.007255 -0.051247 -0.015950 -0.001080 -0.021038
-0.033604 -0.082138 0.032578 -0.050610 -0.097139
--0.058199 0.107657 0.105983 0.027511 -0.023155
-0.031791 0.024300 -0.017968 0.063148 0.049343
--0.007836 -0.006517 -0.013473 -0.004970 0.056535
-0.020974 0.047090 0.009318 0.062741 -0.066064
-0.049383 0.062600 -0.007244 0.025406 -0.011447
--0.019044 -0.033373 -0.012008 -0.020777 0.089488
-0.069039 -0.039904 -0.061004 -0.104096 0.011128
-0.072522 -0.048600 -0.051581 0.021177 0.001740
--0.135630 0.074921 0.010935 0.054793 -0.041526
-0.024169 0.044285 0.017189 -0.023435 -0.022755
--0.018169 0.007995 -0.068248 -0.015644 -0.055355
--0.008988 0.013394 -0.130934 0.055860 0.075055
--0.024869 -0.072987 0.105486 -0.141599 -0.052593
-0.104369 -0.026032 0.010393 0.003048 -0.077763
-0.020642 -0.054726 0.098890 -0.062038 -0.008284
--0.030920 0.041949 -0.052596 0.055867 -0.059301
--0.027785 0.067366 -0.015217 0.061893 -0.058155
-0.044323 0.038825 -0.048558 0.026668 0.056475
--0.042396 -0.044360 -0.073532 -0.092982 -0.055163
--0.002151 -0.047433 0.007696 0.110986 0.055177
-0.038644 0.059219 -0.050130 -0.016829 -0.018164
--0.003120 -0.055675 0.097769 0.119773 0.017092
--0.022682 0.021229 -0.029792 -0.117466 0.066111
-0.065948 -0.074617 -0.074175 0.016698 -0.071365
--0.047641 0.063671 0.005349 -0.039942 -0.093589
-0.065751 0.017235 0.035630 -0.031694 0.061852
-0.053612 -0.016144 -0.071008 -0.029225 0.066491
--0.040345 0.042471 -0.075360 0.066743 0.050696
--0.014316 -0.034336 0.016703 -0.103271 -0.081002
--0.052827 0.007353 0.046627 0.008461 0.049725
--0.003406 -0.093149 0.006210 -0.055973 -0.057089
--0.020200 0.012346 0.141207 0.045917 -0.012261
-0.039647 0.050373 0.056749 0.072718 0.002752
-0.004009 0.038716 -0.039473 0.082663 0.054674
--0.004500 0.042366 -0.110686 -0.077697 0.039758
-0.051345 0.003071 -0.019544 0.063662 -0.082557
-0.025358 0.016659 0.029266 0.011585 -0.055014
--0.026965 0.026974 0.018085 -0.022347 0.075107
-0.063294 -0.046595 0.032484 -0.030675 0.062036
--0.033627 -0.064331 0.081940 0.081033 -0.050699
--0.046257 -0.013797 -0.008749 -0.013019 0.018478
--0.008139 0.075257 0.092736 -0.053166 0.014791
--0.013803 0.044603 -0.116267 0.032848 -0.092134
-0.020647 -0.052370 -0.128516 0.004475 -0.043562
-0.036375 -0.002867 0.103214 -0.109219 0.008372
--0.017374 -0.021978 0.020315 0.012816 0.005703
-0.099649 -0.047777 0.054769 -0.025362 -0.003862
-0.036146 -0.000369 -0.000853 0.012461 -0.032338
-0.013247 0.073478 -0.020868 0.034203 0.002982
--0.016316 0.149713 0.002631 -0.081349 -0.020016
--0.155943 -0.058299 -0.046014 0.027098 0.028942
--0.011857 -0.022016 0.017303 0.105805 -0.012430
-0.086002 -0.009549 -0.071369 -0.005224 0.013152
--0.032159 -0.053343 0.027646 0.043468 0.037717
--0.009747 0.013014 0.058424 -0.101661 -0.010004
--0.053787 -0.020784 -0.072472 -0.041184 -0.087878
--0.077459 0.062841 0.011552 -0.085703 -0.035239
--0.018818 0.030430 0.040444 -0.042755 0.041121
-0.003887 -0.025745 -0.049363 -0.025894 -0.054378
-0.070007 -0.019364 -0.141059 0.039915 -0.045332
-0.024336 0.030320 -0.082784 -0.048936 -0.027234
-0.020447 0.007182 0.084824 -0.045970 0.027752
--0.009759 -0.023702 -0.008379 -0.071048 0.015064
-0.009395 -0.052442 0.130155 -0.011644 -0.014787
--0.021138 0.024468 0.045928 0.043163 -0.030898
-0.065143 -0.014501 -0.008479 -0.017099 0.098271
--0.038323 0.004035 -0.061317 -0.041506 0.038436
-0.055127 0.060303 0.044674 0.128814 0.038762
-0.086495 0.069068 -0.070150 -0.089410 -0.054372
-0.033209 -0.096623 0.034209 0.050531 0.038502
-0.059019 0.043258 -0.045121 -0.063876 0.049971
-0.014954 -0.153720 0.031755 -0.021388 0.014803
--0.125385 0.063700 -0.019166 -0.095829 0.022129
--0.035969 0.041896 0.030461 -0.015321 -0.015067
--0.040013 0.024331 -0.015398 -0.008113 -0.019773
-0.027804 -0.039993 -0.074170 0.033667 0.046367
--0.086691 -0.034684 0.054798 -0.087551 -0.014591
-0.044687 0.057457 0.118611 0.010895 0.011308
--0.066320 -0.063774 0.057919 -0.051338 0.049145
-0.006265 0.048016 -0.010350 0.089136 -0.100672
--0.040908 0.090819 -0.084327 0.065891 0.025763
--0.030480 0.103529 -0.144803 -0.036912 0.017161
--0.020671 -0.059993 -0.030123 -0.104598 0.039178
-0.018764 0.001037 0.014109 0.056332 0.050717
--0.004747 0.035822 0.019209 -0.010162 -0.044650
--0.039307 -0.111424 0.122778 0.090067 0.014313
--0.047117 0.042269 -0.052396 -0.023384 0.123438
--0.016756 -0.092801 -0.058478 0.080712 -0.052288
--0.031113 0.064436 -0.005451 -0.018327 -0.053156
--0.022903 0.031275 0.042126 0.009823 0.074549
-0.002952 -0.010186 -0.114717 -0.029095 -0.026125
-0.003889 -0.003003 -0.060079 0.034566 0.010262
--0.029593 0.012239 -0.052124 -0.028219 -0.110036
--0.015073 0.005623 0.053202 -0.029201 -0.038548
--0.025617 -0.000150 0.022644 0.000550 -0.049223
-0.018036 -0.010954 0.045453 0.019204 -0.075695
-0.027728 0.012573 0.072358 0.082283 0.037531
--0.003946 0.003139 0.000013 0.021161 0.067238
-0.019852 -0.022422 -0.032314 -0.024316 0.106260
--0.001499 -0.028984 -0.045186 0.019666 -0.000966
-0.047073 0.075944 0.081739 -0.029633 -0.060673
--0.013207 -0.057523 0.057259 -0.055200 0.078923
-0.013582 -0.060645 -0.029418 0.013853 0.056976
--0.061172 -0.146801 0.049472 0.016436 0.045997
--0.031589 -0.031052 0.031418 0.026113 -0.038676
-0.064035 0.045482 0.020622 0.005875 0.029585
--0.005284 0.054275 -0.076784 -0.000845 -0.023097
-0.009660 -0.128422 0.002992 0.055651 -0.005932
--0.027123 0.022215 0.057779 -0.080469 -0.076867
-0.008909 -0.030195 0.004706 0.060938 -0.038886
-0.050785 -0.063214 0.004370 -0.033455 -0.013089
--0.009154 -0.030641 -0.030220 0.005174 -0.132262
--0.021476 0.105410 0.027719 0.051123 -0.017271
--0.000185 0.117864 0.035809 -0.071891 0.116329
--0.009954 -0.102737 -0.053397 -0.057653 0.058746
-0.009878 0.024776 0.043190 0.082400 -0.020615
-0.032439 0.035539 -0.018820 0.017822 0.016504
-0.008745 -0.008596 0.054707 0.063681 0.056656
-0.032254 -0.023608 -0.002017 -0.146378 0.047072
--0.016978 -0.066403 -0.042616 0.019845 -0.016902
--0.036058 0.030091 0.057405 -0.035798 0.002185
-0.033655 0.062726 0.038185 -0.024604 0.038026
-0.013655 -0.050063 -0.040289 -0.034587 -0.089238
--0.021893 -0.072730 -0.145619 0.108409 0.003979
-0.003043 0.058544 -0.005494 -0.058294 -0.023242
--0.027050 0.048686 0.105867 0.037255 -0.005019
--0.017867 0.007807 -0.016470 -0.017352 -0.004222
--0.051778 -0.082651 0.031128 -0.051302 -0.094105
--0.007583 0.048196 0.056035 0.076579 -0.049990
-0.037184 0.064354 -0.004853 0.019012 0.052243
-0.041607 0.017800 -0.018867 -0.048040 0.036929
-0.071847 0.012078 -0.003492 0.052903 -0.041736
--0.008196 0.113020 0.034731 -0.051940 0.022987
--0.022300 -0.033261 0.020486 -0.029803 0.179316
-0.014762 -0.006096 -0.022377 -0.053417 0.045007
-0.047412 -0.078434 0.007164 0.048187 -0.032463
--0.106666 -0.022577 -0.007054 0.017166 -0.007364
-0.007677 0.013536 0.004985 -0.052519 -0.019141
-0.018399 0.004096 -0.066275 -0.014342 -0.023287
-0.017068 -0.061082 -0.021342 0.049768 0.072011
-0.006385 -0.035801 -0.027304 -0.099812 0.001797
-0.065304 -0.033306 0.042256 -0.008741 -0.006929
-0.010954 -0.080864 0.095856 -0.012888 0.050346
--0.058343 -0.042527 0.010740 0.027268 -0.131655
--0.022159 0.048331 -0.019242 0.139544 -0.009212
-0.008528 0.095408 -0.072588 -0.026269 0.046686
--0.057569 -0.103939 -0.092932 -0.053006 0.017352
-0.065774 -0.067465 -0.035608 0.077533 0.035754
-0.076737 0.042552 -0.018386 -0.040285 -0.060055
-0.002954 -0.063347 0.023485 0.069391 0.030181
-0.015083 -0.035587 -0.073150 -0.108303 0.033116
--0.051149 -0.070534 -0.072103 0.010046 -0.008050
--0.038552 0.065148 -0.005398 0.029138 -0.091804
--0.032927 0.026057 0.044995 -0.067493 0.140590
--0.010770 -0.051205 -0.134801 0.039771 0.047000
--0.040774 0.024562 -0.118058 0.061721 0.010046
--0.084855 -0.002180 -0.028081 -0.040929 -0.091046
--0.074457 -0.063377 0.065429 0.036303 -0.058948
--0.009780 -0.035398 0.010274 -0.054774 -0.052228
-0.000477 -0.035468 0.059891 -0.011652 -0.043705
-0.130993 0.029418 0.024997 0.014118 -0.000473
-0.012220 0.094825 0.003360 0.050743 0.112621
--0.036424 0.119286 -0.062500 0.028140 0.113267
-0.092232 -0.028352 0.015304 0.118553 -0.037245
-0.047917 0.068301 0.034398 0.054323 -0.111406
-0.016223 -0.016616 0.048104 -0.012621 0.095559
-0.040486 -0.036481 0.006675 -0.029498 0.019722
--0.005174 -0.090840 0.040097 0.031192 -0.056686
--0.015354 -0.037239 -0.040451 0.001148 0.016519
-0.027984 0.063613 0.029013 -0.053331 0.009462
-0.094796 0.073376 -0.035437 0.079788 -0.072969
-0.005683 -0.141562 -0.028240 0.056569 0.053462
-0.024141 0.020688 0.105325 -0.088920 -0.074876
-0.044548 0.015221 0.063364 0.044219 0.028301
--0.011412 -0.033571 0.034361 -0.067847 0.000284
-0.012742 -0.045973 -0.009839 0.044280 -0.077401
-0.013255 0.065280 0.018179 0.074351 0.004383
--0.054040 0.072674 -0.012623 -0.023532 0.057154
--0.077067 -0.071007 -0.013831 -0.015362 -0.004755
--0.051874 -0.046591 -0.008108 0.051772 0.006314
-0.106169 0.066165 -0.024173 0.034211 -0.015378
--0.085769 -0.015752 -0.008456 0.051049 0.015420
--0.005850 -0.015631 -0.060787 -0.151510 0.080912
--0.029476 -0.034162 -0.023308 0.021727 -0.069572
--0.002926 0.066532 0.034835 -0.091864 -0.014468
--0.077637 0.085530 0.058931 0.087803 -0.024233
-0.027189 -0.084814 -0.064844 -0.010260 -0.038228
-0.079925 0.040571 -0.027455 0.112376 0.008327
--0.015541 0.020299 -0.039833 -0.122069 -0.008265
-0.048969 -0.037595 0.073512 -0.070833 0.106844
--0.031463 -0.019591 0.029763 -0.022865 0.013933
--0.014056 -0.092923 0.075324 0.002550 0.006051
--0.074776 0.035465 0.027474 0.120921 0.027105
-0.061516 -0.026568 0.024123 0.047036 0.024385
-0.003344 0.059906 -0.051191 -0.053047 -0.027729
--0.001564 0.005823 0.010087 0.083294 -0.024265
-0.042741 0.094994 0.021393 -0.083504 -0.083151
-0.011291 -0.058920 0.012861 0.030070 0.042736
-0.022911 -0.008546 -0.057609 -0.069900 0.088492
--0.002894 -0.066828 -0.009727 -0.047981 0.019844
--0.085641 0.000042 0.003014 -0.007295 0.035791
-0.036123 0.067002 0.026630 -0.001636 0.009073
--0.016053 0.084871 -0.100683 -0.050020 -0.071874
-0.072365 -0.036757 -0.017701 0.038197 0.053099
--0.056378 -0.028855 0.012463 -0.045723 -0.005667
-0.064256 -0.028177 0.057826 -0.055872 0.030883
--0.002914 -0.097445 0.018108 -0.065132 0.064327
--0.036809 0.022530 0.032579 0.083859 -0.088729
--0.009218 0.070687 -0.027232 0.016749 0.037592
-0.061102 0.155046 -0.004610 -0.031402 0.008374
--0.011437 -0.059360 -0.064021 -0.069056 0.022916
--0.003860 0.044792 -0.030508 0.057430 -0.013125
-0.027304 -0.003144 -0.007603 -0.074523 -0.036823
-0.004066 -0.035482 0.142619 0.062765 0.083342
--0.023363 -0.016003 0.016507 -0.060403 0.074455
--0.020249 -0.025938 -0.007470 0.084381 -0.106173
--0.060300 0.087411 0.014814 0.028437 0.010883
-0.012873 0.103973 0.089761 0.027096 0.064947
-0.033057 0.028486 -0.133571 -0.002210 -0.014149
-0.005981 0.010927 -0.143115 0.070712 0.006923
-0.044569 0.004846 -0.008362 -0.109156 -0.120284
--0.007157 -0.027002 0.075999 0.001357 -0.006077
--0.035577 0.042029 0.018068 0.017700 -0.038593
--0.058375 0.013590 0.094255 0.021156 -0.080328
--0.006126 0.058842 0.032376 0.051314 0.064136
--0.063765 0.028090 0.032284 0.078521 0.108677
-0.012656 0.007400 -0.092093 -0.036734 0.056851
-0.000116 -0.002036 -0.026805 0.084821 -0.011989
-0.023502 0.064916 0.050640 -0.002411 -0.015045
--0.026830 -0.004301 0.065835 -0.025416 0.056093
-0.090627 -0.051534 -0.023105 -0.029171 0.064099
--0.030773 -0.085191 0.015343 -0.005415 0.005626
-0.013041 0.010729 0.018058 0.018453 -0.002180
-0.089388 0.064815 0.021466 -0.092663 -0.019224
--0.008842 0.103392 -0.036092 -0.034972 -0.070552
--0.077454 -0.124438 -0.056352 0.069482 0.030672
--0.003203 -0.020694 0.070840 -0.004376 -0.102179
-0.064995 -0.059481 0.049343 0.024210 -0.003858
-0.056350 -0.015583 0.065190 -0.059043 -0.090407
-0.042894 0.012225 0.074108 0.009773 -0.093983
-0.048272 0.093970 0.039985 0.070722 0.010834
-0.011975 0.135085 -0.000165 -0.021759 0.065164
--0.040893 -0.089985 -0.024270 -0.003863 0.030587
-0.000069 -0.021155 0.028518 0.153614 -0.071797
-0.070676 0.025584 0.005300 0.043065 -0.000089
--0.003734 -0.036750 0.018132 0.036268 0.168510
-0.019026 -0.021440 0.042884 -0.095824 0.021242
--0.026137 -0.034052 -0.063076 0.031835 -0.012727
--0.084292 0.114347 0.068154 -0.074997 0.009182
--0.056381 0.161792 0.065873 -0.004008 0.052013
-0.005326 0.018022 -0.114663 -0.107213 -0.079062
--0.037042 0.007951 -0.066766 0.089297 -0.035405
-0.006611 0.013565 0.029000 -0.122667 -0.037773
-0.030080 0.039640 0.112965 -0.038791 0.051681
-0.018950 -0.002870 0.004002 -0.035366 -0.046099
--0.006632 -0.046456 0.064561 -0.045986 -0.052509
--0.045507 0.034342 0.094059 0.085895 -0.059965
-0.047107 0.045776 -0.051041 0.069720 0.062871
--0.004318 0.016990 -0.053383 -0.000405 0.042032
-0.061772 0.087463 0.018593 0.001180 -0.105041
-0.036585 0.091364 -0.010729 0.002978 0.015583
--0.077926 -0.029862 -0.037549 -0.014135 0.056743
-0.082538 -0.079858 -0.038190 -0.052196 -0.005951
-0.095037 -0.039714 0.003105 0.009675 -0.006472
--0.098367 0.004226 0.018157 0.116425 -0.033752
--0.009903 0.043421 0.067382 -0.058642 -0.037966
--0.004321 0.046370 -0.039951 0.033751 -0.045280
--0.005703 -0.055692 -0.075669 0.043537 0.088421
--0.000079 -0.053451 0.015580 -0.177514 -0.037255
-0.081872 -0.006931 0.040197 -0.040382 -0.030544
--0.032474 -0.073683 0.111389 -0.043286 -0.012181
--0.070486 0.021008 -0.006453 0.059025 -0.084346
--0.045844 0.134617 -0.026041 0.078112 -0.027141
--0.001031 0.044353 -0.065608 0.036661 0.045948
-0.004303 -0.038662 -0.062062 -0.073388 -0.026033
--0.002636 -0.014067 -0.022648 0.128905 0.104651
-0.091629 0.045550 -0.039856 -0.036999 -0.014194
-0.058828 -0.095390 0.054826 0.108067 0.017921
-0.007401 0.037480 -0.051214 -0.080561 0.050245
-0.005451 -0.084552 -0.014427 0.003994 -0.067761
--0.042687 0.064428 0.056058 -0.024265 -0.093157
-0.011618 0.006660 0.071511 -0.116214 0.061118
-0.046247 0.008564 -0.083904 -0.015807 0.002628
--0.075241 0.045928 -0.025621 0.024239 0.024757
--0.010838 -0.006020 -0.007541 -0.087714 -0.046745
--0.086472 -0.058225 0.054459 0.025327 0.052933
--0.014453 -0.076697 -0.033271 -0.024850 -0.042314
-0.006569 0.008881 0.074045 0.050097 -0.053039
-0.019414 0.021988 0.024896 0.056649 0.014029
--0.029525 0.048784 -0.029431 0.042442 0.049334
--0.026698 0.072277 -0.101799 -0.008341 0.047314
-0.082658 -0.016114 -0.042442 0.043527 -0.030064
--0.011416 0.013182 0.060549 0.002644 -0.070164
--0.045732 -0.022494 0.019693 -0.016130 0.079647
-0.000137 -0.038661 0.034959 -0.041633 0.047926
-0.003937 -0.073487 0.058946 0.065316 -0.021139
--0.029658 -0.005529 0.019340 0.005718 0.041614
-0.046584 0.048974 0.064738 -0.076893 0.055570
--0.008793 -0.001555 -0.108121 0.080904 -0.073317
-0.004653 -0.088656 -0.069282 0.058314 0.010922
-0.012637 0.026970 0.078839 -0.078606 -0.003575
-0.010350 0.012762 0.009724 -0.032223 0.025429
-0.028469 -0.112814 0.072108 -0.066038 0.028088
-0.021121 -0.042380 -0.040489 0.029521 -0.098778
-0.078694 0.118164 -0.017958 0.087002 0.013197
--0.023191 0.159205 0.002982 -0.142188 0.019509
--0.062408 -0.050584 -0.091242 0.004705 0.040898
--0.034214 -0.000165 -0.013000 0.062856 -0.025148
-0.102892 0.026243 -0.114277 0.061707 0.020581
--0.052551 -0.075429 0.028865 0.098236 0.087934
-0.003941 0.037129 0.029683 -0.128548 0.026698
--0.036967 -0.019454 -0.078159 0.008871 -0.086884
--0.058585 0.059095 -0.041884 -0.137966 -0.017325
--0.057685 0.085566 0.119159 -0.011731 0.076164
-0.059270 -0.000533 -0.073970 -0.001937 -0.048985
-0.021162 0.035663 -0.047899 0.054477 -0.072253
-0.030344 0.099352 -0.101163 -0.104366 -0.004390
-0.017480 -0.006506 0.031974 -0.043831 0.028735
--0.033380 -0.037286 -0.025470 -0.075025 -0.009320
--0.001852 -0.019244 0.082659 -0.052343 -0.013826
--0.006310 0.016400 0.043020 0.054048 0.019322
-0.025350 0.000037 0.019873 -0.001509 0.073472
--0.050388 0.028730 -0.071807 -0.078877 -0.006660
-0.042649 0.008729 -0.001538 0.090951 0.006897
-0.044002 0.096566 0.016693 -0.023445 -0.061755
-0.017879 -0.081886 0.054302 0.025875 0.073506
-0.045439 0.035703 -0.050539 -0.024113 0.030719
-0.003684 -0.089257 -0.009652 0.004777 -0.019300
--0.184163 0.032927 -0.044636 -0.031259 -0.075344
--0.014780 0.063123 0.067839 0.012301 -0.009528
--0.061510 0.097677 -0.067039 -0.006689 -0.004137
-0.016930 -0.038502 -0.023013 0.052181 0.034074
--0.090822 -0.097151 0.030070 -0.043927 0.004506
-0.049853 0.013260 0.049217 0.011345 -0.015640
--0.017375 -0.084889 0.027637 -0.083011 0.017271
-0.011964 0.013770 -0.041388 0.021785 -0.113317
--0.104729 0.128840 -0.005522 0.005470 0.070867
-0.034456 0.113067 -0.120802 0.015723 0.032177
--0.026534 -0.052353 -0.069474 -0.100515 0.121550
-0.014104 -0.026758 -0.017051 0.063176 0.010188
-0.007059 0.032242 0.002999 -0.038362 -0.058729
-0.021051 -0.069408 0.065496 0.036434 0.024457
--0.051978 0.045735 -0.057632 -0.009011 0.056847
-0.033616 -0.045577 -0.087817 0.102137 -0.027964
--0.002581 0.069852 0.041033 0.041021 -0.038913
--0.025533 0.043910 0.093674 0.006518 0.140256
--0.022931 0.003222 -0.164511 -0.012575 0.008372
-0.023221 -0.013081 -0.086070 0.000152 0.053139
-0.005914 0.050660 -0.044071 -0.047270 -0.079699
--0.047341 -0.038511 0.125150 0.012254 -0.032029
--0.013659 -0.058072 0.035218 -0.033783 -0.083119
-0.046233 -0.049628 0.079349 0.065395 -0.090450
-0.044946 0.046353 0.131024 0.076594 0.042978
--0.047922 0.002985 -0.056522 0.056443 0.112147
-0.010900 0.000489 -0.020178 0.036351 0.129699
-0.037153 0.027557 -0.079114 0.043216 -0.032491
-0.071191 0.026446 0.111274 -0.011111 -0.062724
--0.000122 -0.019280 0.038617 -0.059199 0.111019
-0.020501 -0.045138 -0.015061 -0.064807 0.065959
--0.054589 -0.087659 0.038646 0.014381 0.034881
--0.048543 -0.006280 -0.009214 0.027865 -0.032303
-0.071681 0.064881 0.009542 -0.005854 0.079711
--0.030565 0.072960 -0.051732 0.009082 -0.047330
-0.051060 -0.086171 -0.053292 0.117917 0.007520
-0.006614 0.011574 0.052013 -0.067455 -0.037879
-0.006855 -0.046269 0.030860 0.034071 -0.002125
-0.048522 -0.066340 -0.050068 -0.091857 -0.039875
-0.042169 -0.025418 -0.046173 0.047008 -0.159002
--0.047329 0.169123 -0.038203 -0.005754 -0.037022
-0.040981 0.059210 -0.002242 -0.042617 0.044265
--0.059317 -0.044882 -0.074775 -0.083442 0.028007
--0.041098 -0.031959 0.043096 0.061795 -0.028197
-0.040470 -0.018708 -0.008600 0.002891 0.053975
--0.024208 0.023791 0.009775 0.081813 0.089801
-0.033188 0.016547 0.021751 -0.087759 0.023122
--0.022831 -0.039574 -0.020474 0.037836 -0.007783
--0.094861 0.073247 0.069161 -0.023846 -0.041333
--0.025772 0.087748 0.025988 -0.012948 0.064875
-0.010587 0.013649 -0.041432 -0.081306 -0.084813
--0.006181 -0.038833 -0.069003 0.107345 0.007611
-0.016453 0.041605 -0.043538 -0.126253 0.035968
--0.003914 0.021006 0.086272 -0.015117 0.004273
--0.017316 -0.011375 -0.050330 -0.020760 0.009092
--0.018200 -0.056900 0.062502 0.046639 -0.106123
-0.033584 0.108129 0.061245 0.069683 -0.038308
--0.006263 0.062187 -0.026140 -0.006177 0.072540
-0.026465 0.025257 0.000306 -0.033152 0.070377
-0.032552 0.067946 -0.041184 0.068817 -0.042517
--0.023665 0.089426 -0.009517 -0.031905 -0.028876
--0.047198 -0.101750 -0.021643 0.030076 0.103800
-0.003349 0.017493 0.002512 -0.094201 -0.005963
-0.089063 -0.095130 0.050351 -0.004288 -0.067613
--0.131572 -0.051380 0.008583 0.005412 0.028560
--0.017345 0.004478 0.031108 -0.057891 -0.007459
--0.009374 0.004726 -0.032662 0.036793 -0.009074
--0.023603 -0.039928 -0.021853 0.074091 0.084789
-0.020853 -0.007579 0.017575 -0.082903 -0.016044
-0.033216 -0.023150 0.052294 0.018359 -0.025699
--0.035371 -0.079831 0.144398 -0.041178 0.060835
--0.045799 -0.044320 0.000953 0.061485 -0.045374
--0.093964 0.068302 -0.076466 0.119176 -0.014095
--0.009224 0.091475 -0.038545 0.004967 0.001667
-0.028758 -0.091372 -0.095792 -0.025909 0.005482
-0.031234 -0.025637 -0.021291 0.135677 0.020946
-0.107580 0.013372 -0.085671 0.020971 -0.038560
-0.038570 -0.017209 0.045906 0.060269 0.001966
-0.032650 -0.006186 -0.072219 -0.189856 -0.007205
--0.015639 -0.055057 -0.065552 -0.053151 -0.128235
--0.012954 0.084159 0.026617 0.003305 -0.085995
-0.047267 -0.020931 0.007625 -0.078957 0.121974
-0.045764 0.005225 -0.141436 0.003027 0.051391
--0.036784 -0.001419 -0.053342 0.051094 0.015725
--0.019096 -0.002840 0.026380 -0.069790 -0.184245
--0.051566 -0.028396 0.071692 0.098005 -0.020301
-0.016438 -0.046403 0.001404 -0.000052 -0.054688
--0.022357 0.007259 0.085506 0.017935 -0.014656
-0.098405 0.054979 0.035010 0.075368 0.047790
-0.037848 0.078374 -0.058610 0.016057 0.084829
-0.041381 0.045231 -0.121185 -0.048619 0.095037
-0.078616 0.022570 0.039332 0.081333 -0.008814
-0.036266 0.020667 0.051651 0.048340 -0.014173
-0.001842 -0.015009 0.034124 0.017931 0.056477
-0.124333 0.001687 -0.029607 -0.069722 0.024592
--0.008487 -0.136955 -0.020417 0.039039 -0.063902
--0.051767 -0.039427 -0.040545 0.032784 0.056740
--0.001091 0.036666 0.028260 -0.081961 0.033769
-0.027067 0.018663 -0.038013 0.000810 -0.051724
--0.017021 -0.083432 -0.113410 0.025947 0.004457
--0.019510 -0.003952 0.096457 -0.087833 -0.033332
-0.032633 -0.028593 0.053980 0.004859 0.027062
-0.027726 -0.054113 0.046789 -0.047480 -0.022139
-0.006309 0.013074 0.001745 0.000719 -0.068648
--0.039339 0.124991 -0.017031 0.104387 0.075424
--0.064776 0.049930 0.021317 -0.031441 0.064129
--0.081324 -0.071417 -0.036637 -0.054516 0.069005
--0.034336 -0.097799 0.042552 0.103137 0.014131
-0.086508 0.031131 -0.032366 0.059489 -0.003838
--0.064570 -0.002930 0.012624 0.042919 0.062446
-0.044061 0.055589 0.003834 -0.094630 0.085990
--0.053889 -0.024564 -0.026389 -0.016842 -0.060025
--0.074654 0.030141 -0.008240 -0.045068 -0.051917
--0.152218 0.035234 0.028967 0.032527 0.062252
-0.000908 -0.036356 -0.081610 -0.001575 0.014623
--0.004478 0.064008 -0.087800 0.081273 -0.017113
--0.018705 0.033443 -0.058350 -0.122667 -0.057365
-0.033540 -0.050441 0.124594 0.013386 0.053846
--0.043376 -0.002266 -0.008195 -0.033995 0.053108
--0.040370 -0.064239 0.077268 -0.002621 -0.059563
--0.046177 0.004964 0.033231 0.064375 0.001192
-0.114583 -0.058848 0.061280 0.006693 0.036098
-0.009875 0.035834 -0.018310 -0.036184 -0.014992
-0.069939 0.059780 0.016602 0.073982 -0.035990
--0.015685 0.078068 0.050322 -0.088097 -0.105328
--0.025670 -0.057722 -0.013893 0.006662 0.048590
-0.078264 0.016992 -0.038464 -0.047615 0.099275
-0.010093 -0.039867 0.011067 -0.011289 0.010908
--0.115702 0.003261 0.019257 -0.044432 0.040269
-0.018630 0.024500 0.039527 -0.019008 0.039507
--0.072659 0.078072 -0.050083 -0.037195 -0.134288
-0.019462 0.000276 -0.077134 0.027231 0.091209
--0.050042 -0.033161 0.001557 -0.033891 -0.049683
-0.056345 -0.048181 0.069910 -0.020048 -0.046249
--0.039646 -0.128983 0.089155 -0.075828 0.037947
-0.004400 0.018311 0.016766 0.013464 -0.103994
--0.006838 0.049909 0.006876 0.039950 0.026768
-0.027940 0.106751 -0.086738 -0.030655 -0.023916
-0.054319 -0.087527 -0.016511 -0.107128 0.027059
--0.002389 0.030765 0.000550 0.071481 0.033998
-0.036687 0.048116 0.010056 -0.080424 -0.053276
--0.000327 -0.054330 0.094151 0.063155 0.020931
--0.026860 0.016310 -0.024435 -0.073159 0.050455
-0.022409 -0.008454 -0.035545 0.054995 -0.048738
--0.044119 0.073997 0.039168 -0.014561 -0.032013
-0.028242 0.039841 0.075847 -0.017028 0.060085
--0.021478 0.038475 -0.145149 -0.060014 -0.014315
-0.056108 0.032615 -0.097225 0.033835 0.051055
-0.042640 0.045231 0.000360 -0.041305 -0.108117
--0.023348 -0.045772 0.038096 0.000486 -0.013393
--0.093532 0.016559 0.001345 -0.008241 -0.068229
-0.010724 0.006837 0.077785 0.024403 -0.089797
-0.019810 0.041552 0.064900 0.067216 0.122533
--0.033019 0.073688 0.001023 0.040220 0.079306
--0.033084 -0.028731 -0.066533 0.015167 0.078774
-0.036633 -0.011276 -0.029348 0.033478 0.000076
--0.011424 0.089071 0.107503 -0.027201 -0.024133
--0.086237 -0.015807 0.067867 -0.026911 0.055025
-0.003279 -0.076609 -0.022878 -0.065051 0.117459
--0.064757 -0.048837 -0.006132 0.015775 -0.025174
--0.012054 -0.017396 -0.008215 0.026521 -0.033990
-0.045441 0.100425 0.005545 -0.063862 0.021216
-0.038286 0.073333 -0.080698 0.015085 -0.070552
--0.073377 -0.065780 -0.028242 0.031930 0.034800
-0.014232 0.011229 0.097374 -0.050100 -0.132752
-0.011148 -0.042578 0.076114 0.024497 -0.012283
-0.120806 -0.036672 0.010487 -0.089491 -0.070409
--0.010691 -0.003941 0.028773 0.005044 -0.130679
-0.045320 0.101038 0.007190 0.023122 -0.032858
-0.071021 0.085183 -0.064280 -0.039826 0.069093
--0.045199 -0.056327 -0.038230 -0.030074 0.020018
-0.043187 -0.037153 0.053548 0.081616 -0.046930
-0.041026 -0.013232 -0.029798 -0.007515 -0.009780
--0.014618 -0.049999 0.086479 -0.000441 0.122169
-0.000547 -0.072517 0.024520 -0.173329 0.033337
--0.032822 -0.039451 -0.029459 -0.010553 -0.014511
--0.042816 0.043535 0.098090 -0.011974 -0.009803
--0.011320 0.103835 0.068587 0.016565 0.009926
--0.038017 -0.036161 -0.141386 -0.056138 -0.087531
-0.012520 0.001341 -0.028710 0.134825 -0.022612
-0.025072 0.059725 -0.059548 -0.077144 -0.055577
-0.008583 0.014431 0.160366 -0.000317 0.069355
-0.021539 -0.030848 -0.001411 0.003884 -0.021168
--0.002315 -0.031485 0.058421 -0.069080 -0.089460
--0.074381 0.044224 0.078251 0.015334 -0.018453
-0.024757 -0.006325 -0.030304 0.041022 0.051034
--0.000912 0.014462 -0.042230 -0.034329 0.049998
-0.042384 0.055463 -0.026732 0.016663 -0.070257
-0.027628 0.032582 0.025606 0.007339 -0.016995
--0.014641 -0.013348 -0.035777 -0.048054 0.072409
-0.073357 0.019992 -0.053669 -0.099428 0.009662
-0.053875 -0.084206 -0.028164 0.001825 -0.007384
--0.118351 0.036128 -0.052874 0.044796 -0.008440
-0.034462 0.021959 0.038695 -0.029505 -0.010005
-0.006580 -0.019193 -0.033304 -0.006948 -0.032920
--0.035370 -0.048525 -0.089756 0.086975 0.071726
--0.061466 -0.022927 0.037104 -0.115937 -0.074302
-0.095124 0.034074 0.041596 -0.019002 -0.078886
--0.046289 -0.026431 0.075125 -0.085653 0.030848
--0.087457 -0.013738 -0.079060 0.085171 -0.076996
--0.026743 0.040359 0.001789 0.092574 -0.022293
-0.036215 0.020128 -0.057905 0.020242 0.017234
--0.015028 -0.102072 -0.050335 -0.106620 -0.024631
--0.035796 -0.019773 0.029319 0.102570 0.030958
-0.052784 0.035726 -0.058017 -0.006419 -0.004020
--0.014277 -0.047373 0.048700 0.111928 0.002486
-0.008505 0.051728 -0.097055 -0.122271 0.071235
-0.003188 -0.039588 -0.076039 0.021148 -0.078617
--0.065872 0.029089 -0.000290 0.000898 -0.140194
-0.058506 -0.007075 0.002829 -0.061576 0.057297
-0.022539 -0.043176 -0.078264 -0.026623 0.050164
--0.067814 0.043950 -0.089140 0.025451 0.015987
--0.021710 -0.023764 -0.037703 -0.092210 -0.086925
--0.088289 0.020833 0.085474 0.007660 0.032167
--0.047200 -0.148647 -0.011014 -0.056924 -0.066650
-0.000222 0.031116 0.120665 0.017924 -0.052237
-0.024475 0.057260 0.023098 0.039613 0.002833
-0.015113 0.005702 -0.065102 0.150484 0.040642
--0.062865 0.018220 -0.104305 -0.058038 0.078032
-0.062938 -0.043059 -0.041551 0.090274 -0.090255
-0.003055 0.024771 0.053662 0.023982 -0.007128
--0.022873 0.016118 0.029948 -0.005441 0.027042
-0.035737 -0.062768 0.026554 -0.001648 0.046026
--0.015209 -0.061640 0.080279 0.035525 -0.062174
--0.071438 -0.038252 0.017523 0.005805 0.027560
-0.022277 0.116677 0.082862 -0.023075 0.020718
-0.028369 -0.000644 -0.106525 -0.000025 -0.058375
-0.061774 -0.034461 -0.117604 0.015663 0.025243
-0.050739 -0.035373 0.050164 -0.097896 -0.016953
--0.005625 -0.011887 0.038968 0.009589 0.020354
-0.073417 -0.037194 0.001085 -0.082529 -0.002741
-0.018895 0.000683 -0.005260 0.037680 -0.057914
-0.012065 0.095507 -0.006422 0.038327 0.053359
--0.034912 0.104532 -0.034267 -0.091475 -0.037716
--0.084581 -0.011088 -0.054143 0.048128 0.015983
-0.020394 -0.028289 -0.010829 0.083357 -0.051892
-0.095076 0.000131 -0.014931 0.032836 0.067972
--0.033453 -0.011655 0.043489 0.044985 0.063936
--0.002184 -0.038102 0.055724 -0.108760 -0.005538
--0.065997 0.004333 -0.074726 -0.015630 -0.015614
--0.126012 0.028542 0.044984 -0.082637 -0.073741
--0.053097 0.043995 0.064370 -0.042989 0.078666
-0.032226 -0.050840 -0.030220 -0.007436 -0.034516
-0.018953 0.031855 -0.118774 0.087949 -0.022126
--0.018807 0.026136 -0.060837 -0.058430 -0.043270
--0.023841 -0.001635 0.100076 -0.051546 0.008906
--0.018942 -0.046607 -0.031680 -0.056224 0.042606
-0.027052 -0.054425 0.104195 -0.058465 -0.062190
--0.009973 0.010150 0.018185 0.049565 -0.005886
-0.094118 0.002006 0.034862 -0.013054 0.093378
--0.068149 0.010758 -0.011233 -0.061272 0.036668
-0.049859 -0.008436 0.036689 0.126919 -0.002194
-0.048726 0.081941 -0.048791 -0.035094 -0.075793
-0.038586 -0.043391 0.024660 0.042400 0.074817
-0.074537 0.022976 -0.091022 -0.044301 0.025592
-0.019796 -0.129796 0.029916 0.017043 -0.041798
--0.122413 0.049991 0.006262 -0.014011 -0.015763
--0.024958 0.007419 0.020053 -0.006102 -0.004461
--0.047792 0.040663 -0.058097 0.018616 -0.023217
-0.001382 0.001452 -0.062222 0.051898 0.052539
--0.068723 -0.000916 0.071418 -0.060541 -0.020258
-0.063725 0.074490 0.080845 -0.023018 -0.006902
--0.045143 -0.078702 0.018868 -0.044159 0.011980
-0.025938 0.021655 0.025290 0.063764 -0.132708
--0.035846 0.091140 -0.021667 0.037332 0.035687
--0.056994 0.140855 -0.102945 -0.006009 0.023620
-0.000204 -0.022699 -0.019046 -0.095351 0.050022
--0.004054 -0.019058 -0.006429 0.068069 0.054649
-0.022500 0.029309 0.030159 -0.011081 -0.085224
--0.029775 -0.097594 0.132106 0.026943 0.016069
--0.012230 0.046209 -0.034177 -0.048993 0.094154
--0.006547 -0.043268 -0.100110 0.130569 -0.083928
-0.008317 0.041995 -0.020555 0.004803 -0.056359
-0.023566 0.050093 0.044221 0.017323 0.073761
-0.000300 -0.034851 -0.062557 0.003592 -0.037316
--0.023709 -0.011929 -0.063727 0.008558 0.029238
-0.012654 0.027199 -0.057145 -0.011774 -0.078417
--0.053560 -0.003741 0.037455 -0.039273 -0.042025
--0.002715 -0.030644 0.024806 0.010899 -0.041167
-0.026322 -0.013442 0.040313 0.057461 -0.057587
-0.046460 0.004776 0.094893 0.063931 -0.013181
--0.024787 0.046427 0.000830 0.004541 0.070036
-0.012732 0.022279 -0.046965 -0.012615 0.106753
-0.032489 -0.016696 -0.061242 0.021789 -0.044774
-0.022712 0.030946 0.067933 -0.021075 -0.043324
--0.010231 -0.077078 0.089327 -0.073913 0.129378
-0.001532 -0.043316 -0.016732 -0.026599 0.046714
--0.088765 -0.101898 -0.000950 -0.012357 0.078311
--0.025387 -0.053598 0.022292 0.050494 -0.007031
-0.067206 0.032304 -0.012170 -0.015225 0.029593
--0.011657 0.043622 -0.062834 0.042909 0.003119
--0.005148 -0.106709 0.013981 0.016710 0.024731
--0.050424 0.039756 0.053237 -0.088869 -0.030557
-0.019223 -0.011248 0.001772 0.041389 -0.019693
-0.032684 -0.038816 -0.003782 -0.038112 -0.064818
--0.036779 0.002321 -0.011310 -0.005428 -0.097258
--0.068507 0.117705 0.010296 0.057410 -0.042191
-0.060044 0.076100 0.070634 -0.052272 0.109450
--0.024491 -0.060570 -0.062604 -0.023828 0.043683
--0.008675 0.020641 0.026445 0.122122 -0.030590
-0.007406 -0.006945 -0.038838 0.022271 0.036487
--0.008083 -0.015591 0.089045 0.103083 0.080265
-0.048011 0.008577 -0.024779 -0.098878 0.047757
--0.034944 -0.071262 -0.029632 0.058633 -0.031833
--0.086670 0.020910 0.017850 -0.060040 -0.000118
-0.072375 0.123805 0.028335 0.006174 0.050778
-0.022055 -0.013090 -0.021358 -0.030207 -0.129857
--0.009686 -0.036702 -0.094352 0.083990 -0.027328
-0.022973 0.088840 -0.029830 -0.041108 0.007991
-0.010351 0.043580 0.088045 0.019792 0.034260
--0.018485 -0.026954 0.001393 -0.028881 -0.009226
--0.007746 -0.080511 -0.012092 -0.026729 -0.115592
--0.019491 0.098337 0.046778 0.072298 -0.078237
-0.005173 0.056223 -0.004141 0.066867 0.056189
-0.017966 0.044171 0.000676 -0.045110 0.018200
-0.032009 0.030245 -0.024198 0.053369 -0.032949
-0.005817 0.101192 0.004770 -0.022792 0.027114
-0.010600 -0.037525 -0.040021 0.003401 0.139637
-0.013348 -0.003801 -0.031619 -0.055232 -0.000905
-0.059632 -0.125609 -0.015414 0.054802 -0.053951
--0.064755 0.024768 0.023636 0.018903 -0.000431
--0.029042 0.021020 0.004843 -0.036543 -0.029041
--0.023141 0.025949 -0.071411 -0.019207 0.007088
-0.038696 -0.038765 -0.019290 0.071608 0.100669
-0.002161 -0.019148 -0.033723 -0.110313 -0.048374
-0.036294 -0.011707 0.027523 -0.005146 -0.049367
--0.011778 -0.100402 0.063310 -0.031106 0.021885
--0.095761 -0.080098 0.004308 0.033965 -0.080439
--0.023927 0.055660 0.007395 0.124410 -0.073291
-0.004189 0.060944 -0.045152 -0.060831 0.024748
-0.002404 -0.137119 -0.070340 -0.011515 -0.026093
-0.074911 -0.008646 -0.046756 0.070610 0.043733
-0.056208 -0.004307 -0.017910 -0.044341 -0.049322
--0.031960 -0.031297 0.041787 0.064553 0.010380
--0.009674 -0.056380 -0.131194 -0.102372 0.013069
--0.040055 -0.101666 -0.095641 0.031396 -0.040243
--0.044960 0.107223 -0.038146 0.043004 -0.091273
-0.008832 0.035095 0.018303 -0.033024 0.111336
--0.012516 -0.088527 -0.138520 -0.042476 0.043839
--0.066586 0.012378 -0.100214 0.030453 -0.045537
--0.058136 -0.024370 0.006936 -0.057720 -0.111712
--0.062832 -0.049461 0.055617 0.032267 -0.008208
--0.024939 -0.062605 0.007490 -0.019889 -0.032406
--0.002685 -0.018727 0.104523 0.024688 -0.046299
-0.058710 0.060194 0.045739 0.021202 -0.014056
-0.012044 0.058266 -0.001396 0.021628 0.093785
--0.015184 0.056542 -0.100357 0.020669 0.075524
-0.037202 -0.028476 -0.004358 0.088662 -0.013431
-0.058653 0.069303 0.068988 0.033660 -0.062939
-0.018950 -0.056021 0.021534 -0.016087 0.075798
-0.048597 -0.010444 0.007248 -0.063630 0.010521
--0.014106 -0.074996 -0.000773 0.053311 -0.048215
--0.002735 -0.017992 -0.002647 0.020040 0.029636
--0.022757 0.078272 0.023803 -0.057204 0.024134
-0.064828 0.052842 -0.109740 -0.016306 -0.097522
-0.035253 -0.097609 -0.069816 0.027249 0.039346
--0.007883 0.014192 0.087185 -0.137182 -0.071137
-0.013525 0.010840 0.070855 0.012224 0.018564
--0.008135 -0.046474 0.058225 -0.040550 -0.011424
--0.027632 -0.035317 0.023198 0.038554 -0.081506
--0.012968 0.096501 0.027391 0.100326 0.005492
--0.058045 0.112112 0.002180 -0.025343 0.025626
--0.099536 -0.061595 -0.061651 -0.027489 -0.010581
--0.017782 -0.053973 -0.034355 0.078629 0.008211
-0.072702 0.071223 -0.044680 0.012444 -0.044745
--0.139050 0.003441 0.000913 0.094752 0.048346
--0.007363 0.025892 0.010184 -0.176655 0.133261
-0.001621 -0.024628 -0.030137 -0.007947 -0.085652
--0.029719 0.022053 0.013686 -0.080132 -0.026124
--0.070528 0.051163 0.066954 0.055796 0.025845
--0.010124 -0.065017 -0.069344 -0.022724 -0.000369
-0.053467 0.016636 -0.040196 0.075376 -0.016667
--0.029877 0.004811 -0.023632 -0.097696 0.009076
-0.002224 -0.010353 0.064867 -0.044772 0.077105
--0.055734 -0.018593 0.032803 -0.059184 0.036008
--0.007975 -0.100334 0.044830 -0.020643 -0.039421
--0.010042 0.007773 0.099620 0.108164 0.029716
-0.078106 -0.011285 0.030783 0.081425 0.047785
--0.040324 0.065464 -0.037268 -0.020200 -0.013981
-0.005168 0.027259 -0.021859 0.088221 -0.057304
-0.044425 0.092606 0.044230 -0.055754 -0.033767
--0.019787 -0.048782 0.003298 0.018153 0.021226
-0.068475 -0.047841 -0.084262 -0.076417 0.054885
--0.017738 -0.064677 -0.017373 -0.033227 -0.010808
--0.146013 0.005243 -0.037539 -0.015601 0.022925
--0.011193 0.044758 0.012972 -0.010808 0.024612
--0.056295 0.056909 -0.080235 -0.047137 -0.029242
-0.056368 -0.002198 -0.035936 0.027306 0.075325
--0.064563 0.000437 -0.011783 -0.026348 -0.005163
-0.082637 0.004076 0.084051 -0.032954 0.031309
--0.006451 -0.094091 0.012843 -0.029321 0.020598
-0.015005 -0.014363 0.013016 0.075182 -0.086563
--0.024242 0.085406 -0.009668 0.002995 0.003827
-0.027577 0.119405 -0.019147 0.005101 -0.010265
-0.032537 -0.051797 -0.040632 -0.068586 0.019971
--0.056266 0.018425 -0.035550 0.044019 -0.018450
-0.013988 -0.007499 -0.030389 -0.047227 -0.036402
--0.019853 -0.021715 0.089123 0.033422 0.051031
--0.043643 0.004053 0.039026 -0.092898 0.069717
-0.002242 -0.073405 -0.022716 0.065550 -0.109492
--0.065737 0.051307 -0.007900 -0.001899 -0.038721
-0.061064 0.068115 0.108020 -0.005186 0.091419
-0.038141 0.068502 -0.119719 -0.032776 -0.034200
-0.022829 0.022600 -0.114802 0.021444 0.011983
--0.010708 0.025008 0.016734 -0.058795 -0.121062
--0.020649 -0.036630 0.056523 -0.002163 0.027921
--0.063293 0.012239 0.014511 0.034178 -0.056068
--0.063080 0.014943 0.080895 0.063737 -0.133859
-0.016385 0.042840 0.046425 0.058005 0.035977
--0.084512 0.057576 -0.010982 0.060681 0.072678
--0.008045 0.001068 -0.085375 -0.058554 0.098160
-0.011639 0.009086 -0.053064 0.074379 -0.027243
--0.013015 0.121189 0.047177 -0.009998 -0.034644
--0.007092 -0.012841 0.075861 0.011568 0.086842
-0.045432 -0.079240 -0.025773 -0.009674 0.064448
--0.018079 -0.118996 0.009565 -0.016846 -0.011029
--0.006024 0.033095 0.005964 -0.000340 -0.012580
-0.081590 0.052148 -0.008312 -0.076947 0.027736
-0.018812 0.136957 -0.054412 -0.040884 -0.124297
--0.047994 -0.081925 -0.033440 0.118449 0.044842
-0.004569 -0.006306 0.075165 -0.038914 -0.081500
-0.038445 -0.078834 0.047793 -0.013885 0.006954
-0.039465 -0.031245 0.038253 -0.039471 -0.057441
-0.034043 -0.029460 0.017171 0.000194 -0.094801
-0.013428 0.116396 0.026097 0.041725 0.007773
--0.017706 0.115162 -0.031613 -0.010630 0.042917
--0.039768 -0.139730 -0.048469 -0.000045 0.028945
--0.004139 -0.081954 0.003386 0.115256 -0.049927
-0.077924 0.020540 -0.017751 0.003371 -0.011666
--0.022988 -0.072458 0.027132 0.049961 0.112610
-0.047083 -0.041033 0.043690 -0.084367 0.071528
--0.011307 -0.010002 -0.059736 0.049793 -0.043057
--0.038207 0.109289 0.066216 -0.043249 -0.011953
--0.042904 0.111380 0.021751 0.023150 0.051803
--0.041532 -0.082754 -0.165799 -0.145192 -0.159015
--0.036957 -0.008840 -0.028641 0.105964 0.006864
-0.029247 0.059193 0.009831 -0.144329 -0.047501
--0.014033 0.041089 0.095670 -0.051674 0.049619
-0.031086 -0.026835 -0.015872 -0.041019 -0.016594
--0.047321 -0.050941 0.108942 -0.059399 -0.094262
--0.082008 0.021291 0.061910 0.073377 -0.015244
-0.057463 0.023209 -0.065966 0.034032 0.111775
--0.021516 0.014300 -0.031041 -0.012892 0.024486
-0.045971 0.041949 0.025017 -0.003197 -0.044689
-0.046157 0.053074 -0.010276 -0.022357 0.014208
--0.059017 -0.049325 0.007655 0.034365 0.071554
-0.043755 -0.026127 -0.068545 -0.041093 -0.027706
-0.042534 -0.059878 -0.006088 0.036135 -0.000512
--0.141426 0.019792 0.031442 0.038225 -0.087692
--0.006095 0.062862 0.064053 -0.026935 -0.004107
--0.015518 0.018237 -0.054342 0.025962 -0.043604
--0.041405 -0.044407 -0.066543 0.052842 0.123468
-0.018775 -0.097456 0.021557 -0.111244 -0.022276
-0.087995 0.020846 0.009786 -0.024442 -0.000924
--0.021387 -0.115466 0.059505 -0.084840 -0.018622
--0.039091 0.041857 -0.059951 0.027552 -0.106180
--0.013005 0.077819 -0.057001 0.037112 -0.006017
-0.017069 0.035373 -0.036667 0.041547 0.030229
--0.017543 -0.020408 -0.084738 -0.062925 -0.014286
--0.003367 -0.001926 0.040560 0.163635 0.057733
-0.052600 0.014935 -0.041074 -0.038673 -0.009607
-0.035704 -0.049327 0.051517 0.079677 0.024194
--0.021034 -0.014069 -0.062355 -0.078356 0.049042
--0.028768 -0.088463 -0.035194 0.027880 -0.078732
--0.051166 0.029644 0.064622 -0.002258 -0.067584
-0.014417 0.014299 0.025278 -0.095873 0.081486
-0.018230 -0.014653 -0.093112 -0.067755 0.006200
--0.038621 0.033831 -0.065313 0.022443 0.016583
--0.013554 -0.003383 -0.003813 -0.038565 -0.079906
--0.054026 -0.097241 0.089312 -0.012968 0.081033
--0.047581 -0.080574 -0.024559 -0.018898 -0.082106
-0.008601 -0.028523 0.100338 0.112593 -0.048526
-0.027421 0.024654 -0.000988 0.060571 -0.007538
-0.008276 0.041800 -0.035683 0.044325 0.088914
-0.019003 0.052585 -0.106627 -0.043862 0.018154
-0.061095 -0.055270 -0.060593 0.071565 -0.023743
--0.010098 0.052293 0.067864 0.013882 -0.062200
--0.017320 0.007520 -0.015594 -0.023894 0.092727
-0.029631 -0.013572 0.043058 -0.024937 0.054426
--0.006383 -0.060407 0.031096 0.077251 -0.051193
--0.028054 0.013443 -0.006446 0.025674 0.011140
-0.025108 0.078829 0.096347 -0.120869 0.009600
--0.016833 -0.041386 -0.147598 0.012379 -0.080149
--0.001507 -0.061584 -0.069511 0.053464 -0.028698
-0.050460 0.034750 0.053162 -0.062058 -0.000099
-0.013018 -0.014428 0.008787 -0.021213 0.031728
-0.032305 -0.106213 0.027220 -0.042487 -0.013001
-0.042839 -0.025383 -0.014866 0.006080 -0.055914
--0.004772 0.111496 -0.048142 0.101228 -0.000113
--0.007065 0.108619 -0.026644 -0.081066 0.026279
--0.049199 0.003818 -0.043697 0.009844 0.051099
--0.021007 -0.012906 -0.013888 0.109787 -0.054136
-0.054741 0.002659 -0.080186 0.041342 -0.004960
--0.009585 -0.090940 0.035445 0.084784 0.071802
-0.004212 0.000051 0.061246 -0.179092 0.004524
--0.066032 -0.062309 -0.052999 0.003717 -0.054731
--0.063044 0.065802 0.005675 -0.083010 0.009338
--0.050599 0.044865 0.069794 0.035892 0.069365
-0.077322 -0.037515 -0.101389 -0.032958 -0.023327
-0.004893 0.076975 -0.094625 0.108672 -0.084543
-0.029133 0.033581 -0.097391 -0.099645 -0.008470
-0.047506 0.014070 0.037599 -0.039370 0.027529
--0.037487 -0.030513 0.001358 -0.109004 0.006393
-0.046480 -0.005807 0.072837 -0.015338 -0.034187
--0.036067 0.007979 0.057660 0.043930 0.022410
-0.054219 -0.000956 0.022423 0.048054 0.091746
--0.006642 0.030166 -0.048592 -0.040789 -0.005702
-0.007988 0.043955 -0.019103 0.106518 0.024012
-0.042589 0.059798 -0.006033 -0.026617 -0.048288
-0.015792 -0.114984 0.000601 -0.000354 0.067489
-0.038969 0.014313 -0.064460 -0.002179 0.051347
--0.002092 -0.105852 -0.031092 -0.032437 -0.000174
--0.128927 -0.008284 -0.009141 -0.076672 -0.015283
--0.049413 0.056280 0.045565 -0.006905 0.022082
--0.085801 0.050952 -0.050910 -0.017483 0.005888
--0.006170 -0.061465 -0.030951 0.035802 0.015739
--0.083792 -0.044795 0.060723 -0.030343 -0.069566
-0.030676 0.038387 0.050804 0.004892 0.017579
--0.044803 -0.090476 -0.017970 -0.069598 0.035520
-0.006056 0.044354 -0.061744 0.058806 -0.130744
--0.057101 0.099578 -0.045874 -0.002499 0.046826
-0.049723 0.098173 -0.082881 0.073610 -0.011594
--0.009669 -0.094859 -0.037445 -0.119323 0.065051
--0.015284 -0.026778 0.005845 0.048246 0.025717
-0.028300 0.003404 -0.007273 -0.021871 -0.079752
--0.013062 -0.126858 0.059483 0.049526 0.036093
--0.056998 -0.003159 -0.043116 -0.016197 0.089723
-0.016100 -0.051512 -0.060459 0.061427 -0.060520
--0.010836 0.070291 -0.004533 0.015834 -0.031588
-0.046681 0.024603 0.057986 -0.000132 0.098934
--0.017240 0.002476 -0.113392 0.016989 0.001335
--0.009243 0.021430 -0.088867 0.016496 0.036539
--0.024722 0.027988 -0.025209 -0.037811 -0.070416
--0.027312 -0.042762 0.085979 -0.017748 0.001795
--0.038652 -0.032652 0.049244 -0.003571 -0.092866
-0.021843 -0.080697 0.081009 0.019897 -0.063178
-0.025596 0.016382 0.119656 0.092436 -0.016244
--0.023622 -0.006095 -0.013438 0.039393 0.098847
-0.026872 0.057469 -0.033557 -0.019961 0.171557
-0.009244 -0.003066 -0.087323 0.039711 -0.024124
-0.027198 0.088494 0.108382 0.011044 -0.127500
--0.035575 -0.083203 0.035144 -0.032137 0.120334
-0.002031 -0.020743 0.003890 -0.046130 0.060318
--0.032118 -0.093914 0.036450 0.036482 -0.003628
--0.045976 -0.020514 0.020744 0.028721 0.002437
-0.114939 0.051708 0.055899 -0.024311 0.024351
--0.064421 0.084144 -0.108787 0.030475 -0.042867
-0.008077 -0.063222 -0.026071 0.061247 -0.016598
-0.011100 0.007787 0.023799 -0.068735 -0.056142
-0.025938 -0.060156 0.050084 0.037444 -0.022008
-0.010303 -0.098972 -0.052827 -0.061667 -0.068986
--0.011902 -0.042759 -0.084042 -0.002067 -0.151469
--0.017637 0.134014 -0.026226 0.026110 0.007490
-0.021463 0.079145 0.014098 -0.019123 0.079837
--0.010640 -0.040407 -0.116967 -0.015889 0.022180
--0.005119 -0.014871 0.057013 0.068658 -0.079078
-0.058641 -0.006509 -0.034086 -0.022005 0.041557
-0.016029 -0.003335 0.062705 0.037826 0.092035
-0.047014 0.007296 -0.014070 -0.130533 -0.001078
-0.025557 -0.063677 -0.037435 0.030993 -0.040663
--0.133077 0.001203 0.087675 -0.028956 0.005954
-0.030377 0.094103 0.031530 0.029501 0.058250
-0.043750 0.005780 -0.081652 -0.046912 -0.071344
-0.049909 -0.017203 -0.105850 0.077672 0.063239
-0.015203 0.080354 -0.019175 -0.126004 0.012938
-0.004638 -0.013389 0.087621 -0.010466 0.023940
--0.002703 -0.035427 -0.059936 -0.035946 0.018749
-0.025763 -0.100231 0.035256 0.021093 -0.102097
--0.023912 0.065319 0.051327 0.052308 0.008324
-0.018600 0.027370 -0.019629 0.003753 0.074711
--0.009465 0.042899 -0.007945 -0.044091 0.057014
-0.043860 0.063015 -0.053778 0.033882 -0.018588
--0.007623 0.070289 0.017506 -0.028443 -0.016436
--0.016131 -0.087520 -0.000211 0.013207 0.081102
-0.026870 0.010280 -0.039354 -0.085402 0.005385
-0.045387 -0.075274 0.005158 0.013437 -0.061107
--0.123832 -0.006790 0.046660 0.021633 0.005414
--0.004335 -0.011498 0.029755 -0.025547 -0.002465
-0.008431 0.032361 -0.039776 0.018846 -0.007647
--0.002531 -0.054317 -0.034538 0.095049 0.040090
--0.016239 -0.046115 0.006000 -0.083863 -0.018887
-0.001956 -0.005777 0.053960 0.003049 -0.028290
--0.017755 -0.044904 0.084936 -0.038020 0.048751
--0.036897 -0.069299 0.003508 0.029780 -0.079610
--0.085660 0.060685 -0.006321 0.078501 0.006878
--0.000940 0.062341 -0.042279 -0.015673 0.013762
--0.029805 -0.051092 -0.117256 -0.046978 -0.012383
-0.024326 -0.000611 -0.046838 0.087711 0.032932
-0.089398 -0.013201 -0.035642 -0.013591 -0.019974
-0.002673 -0.016622 0.070976 0.074861 0.005584
-0.013705 0.013057 -0.070513 -0.132482 0.011905
--0.021242 -0.092172 -0.098335 -0.045995 -0.077946
--0.013171 0.148310 0.023267 -0.011841 -0.094360
--0.008329 0.001195 -0.000926 -0.099253 0.141073
-0.039201 0.001784 -0.135018 -0.082677 0.044641
--0.005949 -0.030037 -0.085312 0.049127 0.014847
--0.013469 -0.002593 -0.056090 -0.045962 -0.191274
--0.041064 -0.030590 0.082413 0.061704 0.022132
-0.035533 -0.066234 0.034454 -0.009588 -0.050467
--0.029761 -0.016491 0.067872 0.038969 -0.039014
-0.057543 0.047087 0.043850 0.039443 0.054508
-0.058856 0.109195 -0.043374 0.070615 0.089501
-0.024405 0.045632 -0.080334 -0.004657 0.067992
-0.068464 -0.013325 0.052791 0.040606 -0.016031
-0.043482 0.025913 0.030708 0.051020 -0.058413
-0.012923 -0.031961 -0.001425 0.025659 0.065492
-0.081425 -0.018210 0.009682 -0.008238 0.027227
--0.047221 -0.123710 0.027984 0.046569 -0.051906
--0.013099 -0.010653 -0.030766 0.027285 0.060770
--0.039564 0.053122 0.066810 -0.114075 0.054466
-0.054259 0.024216 -0.045685 -0.001518 -0.082578
--0.026337 -0.055608 -0.075956 0.054064 0.026871
-0.015694 0.016757 0.129806 -0.052800 -0.016678
-0.048569 -0.001337 0.027199 0.004454 0.027064
-0.019218 -0.065149 0.034752 -0.071056 -0.047284
--0.001601 -0.021741 0.012135 -0.006775 -0.080880
--0.033474 0.068299 0.002424 0.082260 0.038960
--0.030455 0.105682 0.013086 -0.054492 0.067646
--0.084988 -0.031769 -0.005191 -0.045479 0.025036
--0.054564 -0.097375 0.013290 0.107239 -0.037042
-0.136211 0.054048 -0.044849 0.071688 0.021370
--0.065162 -0.020715 -0.035790 0.090635 0.057812
--0.008215 0.061018 -0.000019 -0.085259 0.052848
--0.027541 -0.005643 -0.052940 -0.038511 -0.027902
--0.041703 0.075862 0.013165 -0.059187 -0.036318
--0.141024 0.082443 0.069711 -0.013203 0.014406
-0.030125 -0.045500 -0.041806 0.002497 0.025155
-0.017453 0.003895 -0.083765 0.104400 0.011102
--0.048345 0.018909 -0.030988 -0.072003 -0.023689
-0.039778 -0.011208 0.089401 -0.003381 0.064581
--0.037057 0.017900 0.009406 -0.035557 0.007209
--0.003241 -0.108553 0.107998 -0.002787 -0.041577
--0.001725 0.010872 0.036545 0.091885 0.044958
-0.069362 -0.032205 0.088568 0.031341 0.039043
-0.010331 0.015777 -0.034748 -0.023237 0.005678
-0.045804 0.043555 0.039834 0.109120 -0.055790
--0.015894 0.100543 0.050280 -0.072103 -0.045188
--0.011023 -0.045609 0.030003 -0.010336 0.063708
-0.019876 0.039063 -0.034557 -0.076987 0.129728
-0.030980 -0.069793 0.006613 -0.009915 -0.020373
--0.069965 0.002061 0.000541 -0.052867 0.092944
-0.006017 0.032142 0.001437 0.012183 0.032717
--0.116354 0.039141 -0.103482 -0.032555 -0.058604
-0.051576 -0.057991 -0.087256 0.032997 0.087854
--0.040337 -0.024261 0.038911 -0.077252 -0.039797
-0.081800 0.001805 0.100735 0.013940 0.003214
--0.061214 -0.144295 0.008308 -0.079288 0.011819
--0.009353 0.021735 0.041214 0.036036 -0.075607
--0.035037 0.053300 0.014234 0.024169 0.037498
-0.041347 0.073833 -0.068231 -0.042470 0.014760
-0.033778 -0.058964 -0.006533 -0.067729 -0.003610
--0.018476 0.009825 -0.029418 0.050496 0.036382
-0.060848 0.025206 -0.004172 -0.075537 -0.012303
--0.004545 -0.052962 0.118191 0.014623 0.029139
-0.011171 0.016876 -0.013963 -0.059052 0.080971
-0.002827 -0.003879 -0.049140 0.078897 -0.085060
--0.088602 0.131228 0.004221 -0.011391 -0.071427
-0.017718 0.070627 0.054229 -0.044273 0.070835
-0.025214 0.000275 -0.196338 -0.055537 -0.009349
-0.028434 0.030911 -0.087382 0.065504 0.032241
-0.011778 0.089297 0.008448 -0.051996 -0.159620
--0.008923 -0.062831 0.056001 0.025205 -0.012758
--0.071953 -0.005149 0.018063 -0.014935 -0.030631
-0.013403 0.008570 0.080274 0.062037 -0.129636
-0.011472 0.077844 0.062828 0.098467 0.066360
--0.086768 0.078864 0.029290 -0.000317 0.128502
-0.004070 -0.025683 -0.096323 -0.046173 0.149402
-0.030056 -0.030776 -0.044512 0.070740 -0.008688
-0.014318 0.073530 0.097921 0.001865 -0.050654
--0.033176 -0.025587 0.089396 -0.054027 0.105766
-0.000104 -0.058115 -0.051152 -0.028157 0.079932
--0.060212 -0.086791 0.029739 -0.006208 -0.054993
--0.004691 0.017634 -0.011116 0.051677 -0.039065
-0.062654 0.079876 0.012684 -0.029185 -0.019667
-0.012281 0.089665 -0.044542 0.013976 -0.055887
--0.029754 -0.078267 -0.023077 0.060156 0.047758
--0.017389 0.027009 0.061441 -0.041074 -0.115783
-0.058611 -0.060866 0.113852 0.028394 -0.032204
-0.051306 -0.045035 0.012411 -0.104662 -0.067768
-0.005348 -0.053385 0.029868 0.023673 -0.127300
-0.010816 0.112224 -0.017053 0.061578 -0.040140
-0.049130 0.081442 -0.020925 -0.013124 0.049795
-0.000088 -0.080273 -0.041920 -0.006154 0.026384
--0.017665 -0.029077 0.028767 0.109973 -0.064974
-0.016728 0.012762 -0.017789 -0.018455 -0.027535
--0.026842 -0.082729 0.081654 0.058251 0.101281
-0.008607 -0.074243 0.030006 -0.114336 0.077834
--0.042818 -0.047540 -0.040810 0.016980 0.009716
--0.019924 0.025318 0.094241 -0.026210 -0.040988
-0.003781 0.101619 0.098932 0.076552 0.025069
-0.010124 -0.042034 -0.095420 -0.072274 -0.061223
--0.025071 -0.016132 -0.047999 0.172624 -0.036838
-0.011581 0.054710 -0.035830 -0.120277 -0.100100
--0.057028 0.006910 0.118464 -0.022154 0.025012
--0.017797 -0.033263 -0.008283 -0.003727 -0.043563
--0.003699 -0.095741 0.060120 -0.083925 -0.090614
--0.052209 0.069252 0.084102 0.031573 -0.065150
-0.048194 0.013857 -0.000901 0.082968 0.075239
--0.023543 -0.017918 -0.034752 -0.020715 0.045946
-0.025948 0.035884 -0.001330 0.030377 -0.069708
-0.037228 0.064584 -0.011534 0.004775 -0.031321
--0.023894 -0.066680 -0.017407 -0.031766 0.082944
-0.029780 -0.020334 -0.059467 -0.105484 -0.011107
-0.107375 -0.081264 -0.085535 0.015847 0.011785
--0.147292 0.091983 -0.035194 0.018371 -0.019603
-0.000643 0.026524 0.033881 -0.031605 -0.026151
--0.015905 0.025076 -0.040237 -0.015447 -0.036770
--0.023092 -0.008956 -0.094738 0.052213 0.066411
--0.014003 -0.038628 0.067782 -0.113461 -0.048569
-0.077947 -0.029368 0.029847 0.032522 -0.053873
--0.009694 -0.066035 0.097838 -0.080553 0.014786
--0.041721 0.042424 -0.067096 0.086017 -0.083068
--0.031687 0.049261 0.011088 0.055956 -0.042553
-0.064152 0.032740 -0.042521 0.032623 0.026468
--0.060446 -0.061420 -0.040101 -0.072435 -0.035127
--0.015938 -0.056502 -0.012235 0.159594 0.036828
-0.014961 0.039926 -0.052046 -0.008302 -0.025221
--0.019677 -0.050264 0.064556 0.090868 0.045306
--0.056054 0.027715 -0.051663 -0.105423 0.043022
-0.028868 -0.059945 -0.078316 -0.022563 -0.067438
--0.015459 0.051782 0.012461 -0.017353 -0.111666
-0.047354 0.038969 0.018721 -0.042239 0.086618
-0.047663 -0.009423 -0.062622 -0.054796 0.027821
--0.055863 0.015206 -0.063846 0.042120 0.051280
-0.000880 -0.064353 -0.006378 -0.079885 -0.085024
--0.060682 -0.023010 0.052677 0.020476 0.036878
--0.022570 -0.097679 0.024609 -0.051637 -0.023871
-0.018994 -0.008905 0.163821 0.035607 -0.004083
-0.029753 0.070722 0.065015 0.036317 0.015253
--0.018487 0.021981 -0.052297 0.101195 0.046329
--0.018899 0.076923 -0.090549 -0.069408 0.052880
-0.072613 0.016603 0.009898 0.038810 -0.097531
-0.011528 0.033681 0.044555 0.022445 -0.040337
--0.006570 0.016912 0.017289 -0.010643 0.054567
-0.039843 -0.082038 0.051662 -0.036190 0.056489
--0.013943 -0.108354 0.074006 0.095726 -0.069664
--0.034176 -0.043247 0.007026 -0.014616 0.018185
-0.005567 0.064569 0.062030 -0.061575 0.033160
-0.003638 0.043355 -0.092562 -0.001359 -0.118802
-0.034657 -0.080892 -0.115509 0.051575 -0.016477
-0.073726 -0.028197 0.101744 -0.091687 -0.002308
-0.003490 -0.025382 0.023563 0.013144 -0.007840
-0.098021 -0.089215 0.043236 -0.056307 0.013368
-0.056472 0.016004 0.007337 0.008555 -0.046066
--0.000940 0.088476 -0.003382 0.056229 0.011333
-0.025841 0.126240 -0.050253 -0.071801 -0.036593
--0.113256 -0.027423 -0.077799 -0.003365 0.042368
--0.007708 -0.040673 -0.002409 0.091194 -0.002389
-0.089456 -0.007822 -0.034486 0.016810 0.021491
--0.021203 -0.054528 0.050001 0.028679 0.059435
--0.034908 0.003863 0.053342 -0.072845 0.001339
--0.054033 0.012885 -0.065048 -0.045609 -0.058860
--0.076548 0.032086 0.025364 -0.136995 -0.019692
--0.014073 0.049843 0.053275 -0.021054 0.051495
-0.005986 -0.032989 -0.055326 -0.031727 -0.023301
-0.052516 0.011953 -0.114987 0.050477 -0.086649
-0.029069 0.034181 -0.055159 -0.036203 -0.045128
-0.001147 -0.008622 0.073690 -0.077472 0.037649
--0.023539 -0.019114 0.007866 -0.053950 0.029809
-0.002350 -0.026481 0.147821 -0.047601 -0.036813
--0.037253 0.033533 0.027495 0.047206 -0.008682
-0.052569 -0.038196 0.009663 -0.000160 0.096707
--0.058192 0.000390 -0.047017 -0.034486 0.014275
-0.016853 0.040124 0.061386 0.115421 0.015532
-0.083606 0.081646 -0.014130 -0.065768 -0.049301
-0.046979 -0.074307 -0.000569 0.043637 0.041337
-0.036121 0.073310 -0.066751 -0.075889 0.042658
--0.033533 -0.145897 0.036198 0.008869 -0.000721
--0.096931 0.083547 -0.053221 -0.059850 0.044181
--0.047437 0.017891 0.054674 -0.007182 -0.021841
--0.057955 0.025656 -0.022698 0.003117 0.006525
-0.054665 -0.016601 -0.070885 0.038416 0.036323
--0.106994 -0.070705 0.076054 -0.096182 0.017493
-0.019099 0.040334 0.095834 0.024157 -0.012504
--0.036345 -0.054321 0.024473 -0.042893 0.045064
-0.020362 0.013309 -0.022876 0.136195 -0.126968
--0.008470 0.104812 -0.060638 0.042024 0.051826
--0.046516 0.068780 -0.166211 0.010537 -0.020067
--0.016696 -0.031551 -0.045680 -0.140254 0.023460
-0.019033 -0.007193 0.020098 0.033574 0.032849
--0.009729 0.029711 0.035164 -0.031548 -0.069463
--0.068795 -0.076409 0.084793 0.058786 0.033407
--0.055633 0.057879 -0.064890 -0.085820 0.141134
--0.032456 -0.044056 -0.052030 0.080704 -0.065311
--0.029210 0.031372 -0.005285 0.001060 -0.066081
--0.002741 0.043095 0.081838 0.016630 0.083339
--0.027374 -0.002893 -0.096649 -0.007570 -0.027971
-0.023363 -0.012161 -0.079953 0.015753 0.010524
-0.011885 0.035772 -0.053325 -0.031173 -0.135173
--0.008628 -0.004336 0.065589 -0.022764 -0.012130
--0.022211 -0.014175 0.049009 -0.008368 -0.051407
-0.003391 -0.045775 0.040152 0.019404 -0.076654
--0.003267 0.015085 0.089489 0.060779 0.030779
--0.008577 0.025139 -0.005374 0.038636 0.058301
-0.018353 -0.010357 -0.012618 -0.013865 0.082768
-0.012199 -0.031424 -0.049425 0.036742 -0.023385
-0.016261 0.046336 0.082459 -0.046018 -0.072305
-0.007065 -0.052342 0.072695 -0.082325 0.056070
+++ /dev/null
-5 2048
--0.136198 0.024151 -0.063695 0.003294 0.028292
-0.058532 0.000407 0.081822 0.109613 0.092702
-0.002289 -0.004336 -0.001953 0.032305 -0.008448
--0.035198 -0.023077 -0.052002 -0.025974 -0.085171
-0.004385 -0.026216 -0.018253 -0.018256 0.012774
-0.006358 0.026024 -0.087778 0.011771 -0.078083
-0.007874 0.003175 -0.052089 0.064003 -0.042512
-0.014535 0.006232 -0.033255 -0.045854 -0.107260
-0.004491 0.019560 0.061050 0.029138 0.036281
--0.078731 -0.044440 -0.048337 -0.025092 0.081402
--0.007244 -0.049045 0.058090 0.066585 0.018635
--0.075770 0.063007 -0.000503 -0.135694 -0.037603
--0.054068 -0.104063 0.005153 0.006977 0.008814
--0.020893 -0.019060 -0.070042 0.004665 0.090232
--0.015010 0.032240 0.000378 -0.002297 0.004771
--0.040127 -0.041383 0.105462 -0.015007 -0.029958
-0.009637 0.050721 -0.064000 0.070794 -0.027916
-0.001217 -0.095625 0.095422 -0.058274 0.030180
-0.047937 -0.040794 -0.018864 0.036107 -0.038520
--0.035711 -0.046199 -0.031081 -0.090591 -0.073785
-0.068495 -0.021466 0.055625 0.027533 -0.056869
-0.059775 -0.041632 -0.096969 -0.057469 -0.082582
-0.076556 -0.075055 0.014253 -0.024721 -0.110025
-0.039510 0.002922 0.001583 -0.081297 -0.054432
-0.036638 0.106348 -0.029202 0.053259 0.060782
--0.053679 0.039323 0.097200 0.001035 0.086560
--0.023819 -0.121783 -0.029909 0.046493 -0.020142
-0.049289 0.084407 0.081999 -0.002632 -0.023474
--0.049136 -0.022296 0.090649 0.036711 -0.056647
-0.006248 0.061232 0.007889 -0.075399 0.015312
-0.057416 0.103818 -0.016070 0.040505 -0.001189
-0.114331 -0.090671 0.090784 0.004698 -0.078036
--0.096890 0.084786 0.041716 0.042491 -0.057462
--0.014909 -0.032684 0.071338 -0.025083 0.051331
-0.050537 -0.069533 -0.037126 0.032846 0.025729
--0.047775 0.055988 -0.018972 -0.025690 -0.027975
--0.017970 0.023020 0.098593 0.004612 0.013157
-0.044770 0.015091 -0.069310 -0.062427 -0.021413
--0.022487 0.105120 0.052485 0.089068 -0.015127
--0.069327 -0.005520 -0.039356 -0.065169 -0.081883
-0.077729 0.024051 0.008893 0.135290 0.036535
--0.016512 -0.061216 -0.051545 0.019876 0.044939
--0.119244 -0.030603 -0.021134 0.038262 0.002980
--0.079101 0.080099 0.036993 -0.067815 -0.008885
--0.054560 -0.014317 0.093316 0.100385 -0.001690
-0.052346 -0.004258 -0.013592 -0.042301 0.049842
-0.092826 0.061851 0.027621 -0.024069 -0.059213
-0.031617 -0.009108 0.022338 -0.063250 -0.097158
--0.008177 -0.030577 -0.107136 0.017774 0.059538
--0.053438 0.008281 -0.008953 -0.207584 0.041500
-0.006693 -0.093889 -0.039108 0.040752 0.020200
-0.005813 -0.021241 -0.046317 -0.019980 -0.037740
-0.134550 0.018885 -0.020492 0.033445 -0.004411
-0.000456 -0.030901 -0.058047 -0.081834 -0.007611
-0.006314 0.008851 0.070179 0.003036 -0.035749
-0.067106 -0.087172 0.047680 -0.058147 -0.011858
--0.043608 -0.020841 0.038136 -0.031081 0.185361
--0.054055 -0.067146 0.097240 -0.082580 0.051439
-0.003624 -0.133423 0.011530 0.119056 -0.043475
--0.001737 0.110875 0.038530 -0.027030 0.053434
-0.000648 -0.029320 0.121211 0.029589 -0.039707
--0.068850 0.000408 -0.032227 -0.003072 0.052231
-0.034923 0.080837 -0.037156 -0.094754 0.014542
--0.005315 -0.054038 0.012812 -0.027090 -0.001601
--0.083437 0.019212 -0.016505 0.046104 0.038554
-0.072309 -0.011739 0.059850 -0.056206 0.073386
-0.135263 0.000286 -0.060518 0.036391 -0.060506
--0.027527 -0.000692 0.036739 -0.066074 -0.088864
-0.005166 -0.054854 -0.003007 -0.010121 0.027824
--0.036967 -0.100932 -0.182594 -0.013910 0.014657
-0.023979 0.055629 -0.054566 0.106056 -0.079044
--0.037983 -0.044929 0.043735 -0.085774 -0.009132
--0.024985 -0.071464 0.051902 0.102450 0.054042
--0.016588 -0.074683 -0.064110 0.056690 0.110680
--0.064499 -0.033720 0.024264 0.088022 0.031179
--0.015453 0.035079 0.044771 -0.043409 -0.047855
-0.078062 -0.091048 0.052298 0.018898 0.005019
--0.054365 0.080023 -0.065458 -0.065704 0.014520
--0.003386 0.001319 -0.046118 -0.010700 0.008233
--0.030496 -0.072516 0.051522 -0.020414 -0.101831
-0.017761 0.038077 -0.114244 0.041726 0.083964
--0.016531 -0.129688 -0.014288 -0.122167 0.063062
-0.116380 -0.065367 -0.038604 0.095723 -0.036360
--0.066306 0.014726 -0.011596 -0.005770 -0.048796
-0.090592 -0.004417 0.009466 0.098691 -0.066093
-0.001754 -0.005848 -0.043066 -0.037892 0.031807
--0.022616 -0.021159 0.045873 0.028421 -0.085595
-0.049794 -0.001914 0.008752 -0.077905 0.029994
-0.044235 0.064398 0.005282 -0.003674 0.086059
--0.032460 0.015037 -0.007206 -0.036713 0.011909
--0.017113 -0.061523 -0.001698 0.001480 -0.052389
--0.005496 0.081887 0.018394 0.005492 -0.048520
--0.036485 0.006979 0.121328 0.069020 -0.093697
--0.035414 0.025382 0.033335 -0.042742 0.078618
-0.022150 0.100313 -0.081797 -0.006077 -0.036600
-0.043498 -0.047693 0.080861 -0.041208 -0.074855
--0.034519 0.006730 0.150509 0.059429 -0.003976
--0.059532 -0.022218 0.071419 -0.051453 0.008904
-0.063565 -0.107466 -0.026643 -0.009845 0.097906
--0.094940 0.057756 -0.085002 0.019603 -0.098395
-0.015610 0.000806 0.058999 -0.025760 0.036316
-0.071066 0.030579 -0.066243 -0.023751 -0.060747
-0.067731 0.090313 0.041003 0.076536 -0.012685
-0.069395 0.035647 -0.112161 -0.075184 0.003099
--0.017065 0.018376 0.017104 0.109557 0.049888
--0.047698 -0.041877 -0.000537 0.051347 -0.003682
--0.016370 -0.001696 -0.010154 0.067477 -0.036583
--0.020092 0.048256 0.084878 -0.100501 -0.035380
-0.008671 -0.122585 0.038716 -0.002197 -0.101482
-0.037247 -0.032842 -0.068559 -0.021387 0.014449
-0.027927 0.060964 -0.048375 0.028367 0.038134
--0.014885 -0.092447 -0.081616 -0.015822 -0.134913
--0.021274 0.013697 -0.035055 0.055911 0.033111
--0.034970 -0.015798 -0.007119 -0.076467 0.028984
--0.014502 -0.124275 0.021441 0.078607 0.002858
--0.042356 -0.003098 0.045995 0.031341 -0.016968
-0.041560 0.019148 0.004700 0.005637 0.093016
-0.063490 -0.048735 -0.069068 -0.034088 -0.028215
-0.045350 0.075594 0.037776 0.024450 -0.071678
-0.087072 0.009286 -0.023885 0.019862 -0.012771
--0.029248 -0.016036 -0.089092 0.074240 0.169069
--0.033409 0.026100 -0.024626 -0.043863 0.098736
-0.012158 -0.077333 -0.083731 0.013768 -0.080944
--0.060470 0.037407 -0.013690 0.007337 -0.001188
-0.005453 0.026261 0.119036 0.043940 0.046011
--0.035860 0.008540 -0.113766 -0.097502 0.024057
-0.024457 0.118827 -0.001543 -0.064711 -0.007631
-0.049637 -0.101928 -0.002462 0.054230 -0.044736
--0.067470 0.078729 -0.034003 0.014536 -0.022247
-0.161762 -0.041209 0.037097 -0.052532 -0.031344
-0.061129 0.020176 -0.066030 0.038964 0.022928
--0.014012 -0.030939 -0.092443 0.002874 -0.114395
--0.010621 -0.005537 0.018042 -0.045648 0.044588
-0.007453 0.095088 -0.128336 0.107088 -0.032186
--0.047594 0.046694 0.039679 0.083442 -0.088060
-0.060757 0.082896 0.037419 -0.092975 -0.054674
-0.022723 -0.030652 0.025581 0.033843 0.085935
--0.020876 -0.055952 -0.103915 -0.073020 0.045301
-0.020552 0.047020 0.047981 0.150138 -0.041783
--0.081206 0.015811 0.025886 -0.105666 0.097623
--0.026606 -0.109640 0.031300 -0.029835 0.007132
--0.004757 0.036673 -0.113804 -0.044055 0.015492
-0.016617 0.050138 -0.020709 0.070749 0.016487
--0.041772 -0.059857 0.040483 0.002005 -0.030924
-0.045135 0.114146 -0.077004 0.040268 0.014157
--0.007526 -0.029177 0.064663 -0.093478 0.103127
-0.041264 -0.004835 0.013205 0.110399 -0.026498
--0.107188 -0.024533 -0.071115 -0.052007 -0.006395
-0.030684 -0.035133 0.019891 0.033587 -0.028437
--0.019472 -0.016122 -0.099020 -0.052317 -0.029623
-0.023893 -0.019150 0.042703 -0.007384 -0.135429
--0.008658 0.020311 0.016085 -0.113980 -0.001115
--0.036113 0.054423 0.008653 -0.007789 0.077924
--0.129044 -0.005070 0.011282 0.013904 0.077014
--0.025623 -0.031789 -0.073370 0.010481 -0.041819
-0.008182 0.065192 0.027333 -0.034730 -0.026375
--0.073571 -0.019647 0.040694 -0.003020 -0.065061
--0.014276 0.079966 0.003562 -0.144068 0.054787
--0.022846 0.071080 -0.036877 -0.012692 -0.082166
--0.006918 -0.096688 0.095501 0.064056 0.007213
--0.036690 0.026213 0.059957 0.047896 0.003414
-0.000914 0.015446 0.098563 -0.056379 0.137143
-0.018164 -0.076211 -0.070196 0.001563 0.047637
--0.049087 0.114850 -0.090803 -0.012260 -0.036278
-0.029559 0.002293 0.037244 0.047064 0.038113
-0.070849 0.065524 -0.021498 0.000989 -0.091111
--0.036143 0.076107 0.016355 0.059505 -0.023400
--0.048163 0.004599 0.025481 -0.093492 -0.022306
-0.020409 0.023572 -0.001520 0.059761 0.064734
--0.032331 -0.014971 -0.032497 -0.010585 0.008900
--0.085173 -0.038940 0.017863 0.073312 -0.032050
--0.026419 0.012730 0.067669 -0.005028 -0.054256
--0.019721 -0.049805 0.080959 0.050680 0.057457
--0.006579 -0.003248 -0.080847 -0.103158 0.064238
-0.082133 0.070334 -0.026602 -0.064571 0.042901
-0.017513 -0.081866 -0.016501 -0.088344 0.022655
-0.009335 -0.047461 -0.005181 0.060236 0.032349
--0.056626 -0.022179 -0.044705 -0.131625 -0.028104
--0.026924 -0.045874 0.036424 0.026185 0.023864
--0.028118 -0.018505 0.018550 0.000643 -0.055726
-0.101839 -0.037958 0.031116 0.110118 0.009110
-0.112021 -0.038578 -0.104082 -0.042272 0.040893
-0.028742 -0.028607 0.080643 0.003287 -0.063413
-0.099046 -0.029956 0.002892 -0.067344 -0.016823
-0.008602 0.017513 -0.014264 -0.041185 0.124856
--0.054844 -0.072185 0.033952 -0.096401 0.046007
--0.020749 -0.046471 0.003558 0.082125 -0.096910
-0.025411 0.127329 0.076666 0.068718 0.005743
-0.043603 -0.056968 0.086610 0.010153 -0.036367
--0.068722 0.024772 -0.000639 -0.052051 0.074796
-0.019967 0.077602 -0.034771 -0.009789 -0.023551
-0.047117 -0.066717 -0.066348 -0.063558 0.008220
--0.027567 0.036273 -0.067110 0.028847 0.089473
-0.083247 0.004591 0.077405 -0.082932 -0.013968
-0.079836 -0.052437 -0.080184 0.015535 0.000867
--0.020465 0.038101 0.029256 0.027121 -0.094745
-0.022846 0.000927 0.004314 -0.039488 0.016252
--0.016129 -0.000925 -0.125901 0.037569 -0.012151
-0.050660 0.036394 -0.018283 0.058805 -0.009276
-0.002687 -0.029775 -0.002892 -0.018790 -0.068265
--0.026723 -0.038695 0.067644 0.027095 0.104267
--0.033127 -0.092325 -0.101391 0.051657 0.047692
--0.039487 0.017442 -0.007204 0.106333 -0.026736
--0.026984 0.048252 0.041384 -0.002131 0.042443
-0.019367 -0.077827 0.019452 -0.004992 0.095049
--0.020183 0.054128 -0.089501 -0.106767 0.133742
-0.003715 0.065993 -0.010120 0.002578 0.010632
--0.104027 -0.092526 0.051102 -0.064092 0.007341
-0.037981 0.005348 -0.098388 0.082010 0.023682
-0.101454 -0.074181 0.022470 -0.047488 0.034728
-0.054519 -0.059484 -0.055491 0.133582 0.009556
--0.120963 -0.043837 0.028549 0.025534 0.028904
-0.108670 -0.032038 0.012596 0.038519 -0.012244
-0.003888 0.019393 -0.076558 -0.013031 -0.019858
--0.006786 -0.020230 0.044975 0.034040 -0.032445
-0.099970 -0.025120 -0.012044 -0.058520 0.081664
--0.018743 0.028691 0.017459 0.030523 0.121595
--0.045728 -0.044359 0.002157 0.025037 0.043565
--0.027940 -0.112422 0.019525 0.012089 -0.036526
-0.012809 0.102396 0.061700 0.009053 -0.006318
--0.073644 0.052544 0.093009 0.002094 -0.048500
--0.067838 0.044219 0.004622 -0.021517 0.144798
-0.000396 0.028552 -0.047957 0.022072 -0.044059
-0.022301 -0.046990 0.069399 -0.022723 0.001209
--0.061132 0.035083 0.054456 -0.053667 0.023348
--0.021700 0.035612 0.078641 -0.067377 0.046902
-0.103671 -0.042167 -0.039490 0.027663 0.018158
--0.034924 0.044647 -0.017309 0.013019 -0.075672
-0.016417 0.018863 -0.005962 -0.054108 -0.028444
-0.033930 -0.024540 -0.021060 0.018088 -0.079446
-0.004808 0.042524 0.042005 0.062594 -0.020936
-0.045898 -0.007873 -0.067501 -0.079291 -0.053730
--0.044782 0.007470 -0.003636 0.041779 0.032024
--0.055764 -0.025299 -0.042428 0.043255 0.061536
--0.028270 0.031312 -0.055603 0.078003 -0.007771
--0.035400 0.019441 0.101450 -0.047446 -0.021123
--0.003012 -0.065746 0.021167 0.028415 -0.039012
-0.078986 0.041230 -0.109603 -0.053586 0.081713
-0.069524 0.086261 0.032415 0.020301 0.008172
--0.050007 -0.043252 0.032538 -0.040149 -0.060186
--0.036647 0.074839 -0.067704 0.105038 0.016407
--0.017166 -0.040157 -0.034379 -0.045783 0.036121
-0.006989 -0.053621 -0.014310 0.130029 0.014339
-0.010984 -0.049323 0.011801 0.024418 -0.061108
-0.048945 0.020936 -0.016709 0.036678 0.056799
--0.032054 -0.081596 -0.020000 -0.014900 -0.016931
-0.025720 0.030371 0.054373 0.041972 -0.103673
-0.072505 -0.008653 -0.038498 -0.082343 -0.011659
-0.008214 -0.051158 -0.011619 0.011396 0.073440
--0.028140 -0.085370 -0.083429 -0.059579 0.093532
-0.017281 -0.029324 -0.063027 0.036276 -0.035917
--0.062731 0.083485 0.034826 -0.016723 0.041119
-0.006462 0.063240 0.106462 0.005405 0.014198
--0.107371 0.016648 -0.039299 -0.060254 0.066074
-0.010798 0.104663 -0.026071 -0.092536 -0.049821
-0.052302 -0.111521 -0.028997 -0.044881 -0.058612
--0.066180 0.063782 -0.087613 0.131044 0.079319
-0.051549 -0.031150 0.050463 0.014022 0.072812
-0.040951 -0.008242 -0.035076 -0.012706 -0.007732
--0.087407 -0.043003 -0.051495 -0.005909 -0.078253
-0.024556 -0.000301 -0.002836 0.000471 0.036449
--0.033227 0.013122 -0.041830 0.053473 -0.062823
-0.001698 0.056414 -0.009009 0.074868 -0.031437
-0.061142 0.034153 0.037913 -0.016467 -0.112529
--0.042555 0.004865 0.068299 0.039970 0.035002
--0.032275 -0.054429 -0.110647 -0.004981 0.106602
--0.009971 -0.070226 0.011717 0.078195 -0.004486
--0.053666 0.032253 0.019880 -0.063381 -0.011499
--0.021161 -0.147358 0.022501 0.026856 0.014878
-0.071720 -0.018691 -0.078472 0.006781 0.128504
-0.009349 0.032300 0.024117 0.093683 -0.001689
--0.038787 -0.022119 0.025894 -0.051130 -0.029077
--0.003509 0.056923 -0.043564 0.047755 0.029228
-0.094577 -0.059873 0.105327 -0.045681 0.020128
-0.019571 -0.053714 -0.026005 0.082821 0.010883
--0.090635 -0.046160 0.015147 -0.060630 -0.025114
-0.065345 -0.062635 0.033608 -0.000239 -0.055078
-0.028179 0.007232 -0.132300 -0.058511 -0.027521
-0.009924 -0.057576 0.037098 -0.048222 -0.067691
-0.025807 0.005481 0.053364 -0.071026 0.002704
--0.019833 0.056496 -0.012323 0.054975 0.053260
--0.058168 -0.002745 0.051808 0.007857 0.072213
--0.028508 -0.100966 -0.066436 0.094923 -0.032702
-0.016386 0.144962 0.060276 -0.060885 0.045013
--0.008694 -0.035070 0.077187 0.011427 -0.039974
-0.041845 0.095921 -0.012129 -0.069502 0.058053
-0.016498 0.068097 -0.063723 0.058607 -0.084662
-0.051080 -0.084087 0.061664 -0.014378 -0.020357
--0.101420 0.018380 0.026201 0.021273 0.001716
-0.018280 -0.048955 0.114013 0.007403 0.073650
--0.007198 -0.073071 -0.043345 -0.025399 0.062280
--0.057043 0.007375 -0.057945 0.001682 -0.068288
--0.004458 0.057944 0.019870 0.030319 0.023300
-0.023258 0.038816 -0.075939 0.024401 -0.008493
--0.088976 0.084875 -0.004901 0.107413 0.036685
--0.017576 0.049893 -0.017089 -0.076959 -0.047043
-0.012304 0.096589 0.020081 0.055371 0.026179
--0.031262 -0.023054 -0.062863 0.022469 0.026254
--0.081002 0.001604 -0.067115 0.089364 -0.044846
--0.104635 0.022051 0.024153 -0.050297 -0.090473
--0.111208 -0.014747 0.065056 0.064524 0.014978
--0.018009 -0.045181 -0.036814 -0.049839 0.101556
-0.123355 0.029904 0.046059 0.075873 0.023800
-0.018950 -0.069598 -0.023833 -0.044717 -0.059289
-0.005309 -0.050755 -0.129767 0.090909 0.049327
-0.034593 -0.024217 -0.013090 -0.120429 0.018611
-0.035730 -0.069972 -0.020352 0.040567 -0.008846
--0.035745 -0.012086 -0.029290 -0.031875 -0.022851
-0.126885 0.093804 -0.041337 0.064417 0.012827
--0.006103 -0.064712 -0.034377 -0.072895 -0.024513
-0.024964 0.025126 0.053845 -0.032844 -0.040164
-0.057226 -0.047268 0.002180 -0.030810 -0.046649
--0.011612 -0.016914 0.019534 -0.045647 0.103552
--0.019784 -0.059284 0.034278 -0.052666 0.063638
--0.030288 -0.052341 -0.018891 0.060842 -0.038845
-0.029390 0.061982 0.049711 -0.034509 0.014359
--0.001671 -0.096474 0.111850 -0.008201 -0.039744
--0.018012 -0.003881 -0.008624 -0.032458 0.060460
-0.046820 0.050558 -0.004330 -0.043328 0.024076
-0.020855 -0.064731 0.003784 -0.011162 -0.039018
--0.064459 0.004758 -0.065784 0.046246 0.009026
-0.061065 0.051008 0.060159 -0.028994 0.058623
-0.065914 -0.082042 -0.137623 0.009165 -0.028321
-0.013924 0.038290 0.064550 -0.076981 -0.104556
-0.057766 -0.047215 -0.025831 -0.014589 0.040468
--0.018660 -0.044675 -0.134278 -0.019992 0.000064
--0.007643 0.019573 -0.005029 0.139097 -0.058444
-0.015872 -0.061714 0.054845 -0.093905 -0.023694
--0.069868 -0.051634 0.093449 0.116722 0.041075
--0.031597 -0.064630 -0.001604 -0.011889 0.114102
--0.038392 -0.043996 0.036345 0.159256 0.042733
--0.014768 0.023374 0.091565 -0.062174 0.008748
-0.027552 -0.065067 0.043484 0.029833 0.068407
-0.062921 0.100413 -0.044081 -0.047093 0.012867
--0.021198 0.053674 -0.074601 0.009988 -0.000368
-0.004615 -0.031012 0.126258 -0.044950 -0.053716
-0.068829 0.028389 -0.081499 0.096576 0.111555
-0.032580 -0.091888 0.004783 -0.058619 0.103336
-0.023528 -0.067561 -0.052227 0.060540 -0.008415
--0.134399 -0.003137 -0.005498 0.000696 -0.064610
-0.103028 -0.016839 0.054380 0.058673 -0.018968
--0.030411 0.004030 -0.022930 -0.074504 -0.005768
--0.040922 -0.056206 0.026643 0.091472 -0.046289
-0.024551 0.006847 -0.043098 -0.076632 0.023143
--0.027690 0.058150 -0.033455 -0.000947 0.108861
--0.053902 -0.004117 -0.000733 -0.004552 0.018160
--0.015632 -0.075342 -0.057899 0.043216 -0.030867
--0.025610 0.087151 0.015012 -0.058812 -0.077554
--0.057877 0.030875 0.088541 0.068489 -0.037517
--0.013136 0.003726 0.026354 -0.076145 0.081871
-0.009685 0.049282 -0.053126 -0.041669 -0.055971
-0.070689 -0.000302 0.030654 -0.059458 -0.032358
--0.073479 0.014645 0.057040 0.060111 0.026122
--0.021404 -0.035383 0.105578 -0.064143 0.009201
-0.067302 -0.018682 -0.018425 0.053502 0.095608
--0.089642 0.061823 -0.049713 0.118868 -0.071061
-0.033484 0.020846 0.017472 0.009132 0.017367
-0.095422 0.015719 -0.042701 -0.059963 -0.093737
-0.065153 0.040501 0.070592 0.084313 0.023778
-0.011293 0.022143 -0.078417 -0.072724 0.022472
--0.047887 0.042426 0.002790 0.080670 0.045298
--0.124868 -0.052373 -0.036868 0.080892 0.053132
--0.029773 -0.038766 -0.021131 0.028890 -0.019483
--0.031257 0.013785 0.114016 -0.019299 -0.095540
--0.081494 -0.108033 0.072808 0.034714 -0.046113
-0.018918 0.025646 -0.012081 -0.029184 0.035413
-0.062215 0.094361 -0.038357 0.004033 0.061858
--0.040066 -0.073778 -0.039352 -0.026946 -0.078584
--0.027017 -0.016385 -0.070475 0.068096 0.031208
-0.024912 -0.031301 0.028130 -0.092740 0.010887
-0.080067 -0.086228 -0.002645 0.062014 0.039789
--0.000913 -0.002893 0.021215 0.025308 -0.079170
-0.021198 0.011411 -0.029445 0.021288 0.028934
--0.012482 -0.093791 -0.086795 -0.065003 -0.091575
-0.042822 0.048190 0.027573 0.016672 -0.031582
-0.084478 -0.026855 0.002037 -0.003986 -0.032282
--0.037516 0.024939 0.006645 0.069559 0.096001
--0.009324 -0.020647 0.016115 -0.002890 0.099816
-0.035798 -0.055626 -0.082205 0.061510 -0.137040
--0.003237 0.086092 -0.015616 0.038825 0.025940
--0.009435 -0.039900 0.130411 0.041684 0.029411
--0.053212 0.035136 -0.038974 -0.068479 -0.014046
--0.052464 0.114330 0.014803 -0.043086 -0.031898
-0.114055 -0.094015 0.000194 0.005274 -0.032729
--0.061821 0.146682 -0.033636 0.052702 -0.025910
-0.076647 0.000572 0.089946 0.018515 -0.012439
-0.057567 -0.023096 -0.066766 0.029717 -0.021521
--0.048165 0.037444 -0.026950 -0.054050 -0.122571
-0.003033 -0.021280 0.058783 -0.065330 0.032047
-0.016007 0.003629 -0.102811 0.075806 -0.028556
--0.051245 0.032001 0.006924 0.046225 -0.066944
-0.026360 0.071868 0.000989 -0.051417 -0.082284
-0.007536 -0.005941 0.054340 0.097832 0.059470
-0.005201 -0.029254 -0.063891 -0.032060 0.063113
-0.005567 -0.038440 0.079032 0.117269 -0.027965
--0.018444 0.021519 0.056596 -0.077845 -0.001929
-0.018144 -0.117195 0.021022 -0.078031 0.060201
-0.068169 0.033446 -0.116183 0.024450 0.054125
-0.043263 0.043637 -0.024388 0.028606 -0.043272
--0.076651 -0.044322 0.043529 -0.032600 -0.022496
--0.028618 0.105767 -0.131078 0.022952 0.032809
-0.014704 -0.078921 0.053414 -0.130561 0.025975
--0.006145 -0.020377 0.002576 0.111120 -0.027416
--0.056800 -0.034249 -0.102732 -0.077605 -0.054125
-0.013938 -0.018912 0.031272 0.045116 0.009640
--0.000666 -0.010171 -0.101812 -0.086048 -0.079481
-0.012556 -0.025093 -0.037932 0.018846 -0.121557
-0.019521 0.077648 0.062764 -0.080462 -0.006901
--0.022906 0.106898 -0.001186 -0.033179 0.083120
--0.108465 0.004729 -0.004907 -0.051941 0.019890
--0.052798 -0.048321 -0.039992 0.011392 0.022231
-0.052123 0.053230 0.008893 -0.021235 -0.021543
--0.052336 -0.002642 0.014048 0.021729 -0.071873
-0.008583 0.063055 -0.005700 -0.130218 -0.004615
-0.001933 0.068978 0.002830 0.041471 -0.075840
-0.058590 -0.105352 0.109710 -0.008703 0.046126
--0.058564 0.044743 0.028326 -0.017021 -0.043831
--0.006378 0.002489 0.083015 -0.017479 0.032458
-0.075359 -0.070133 -0.094634 0.004253 0.050570
--0.084605 0.081302 0.020066 -0.026905 -0.070421
-0.027450 0.006091 0.038101 0.058759 -0.022035
-0.075718 0.034255 -0.003008 0.013391 -0.039205
--0.027185 0.117021 0.026809 0.017619 -0.048835
-0.013076 -0.001288 -0.041201 -0.077396 -0.060871
-0.003384 0.082249 0.080509 0.073375 0.032946
--0.020732 -0.036562 -0.005218 0.006654 0.017449
--0.070219 -0.067294 -0.000185 0.046725 -0.032632
--0.114281 0.007061 0.027082 -0.042412 -0.035359
--0.017030 -0.081911 0.091617 -0.001734 0.040171
-0.029232 0.022946 -0.023063 -0.099398 0.088196
-0.134224 0.037312 -0.010897 0.015441 0.048401
-0.036710 -0.079633 0.068283 -0.095899 -0.076950
-0.031388 -0.049701 -0.078358 0.071239 0.093230
--0.047640 -0.059715 -0.006775 -0.091115 -0.004787
-0.029706 -0.062712 0.001230 0.035511 0.012170
--0.035826 -0.020972 -0.004566 -0.054826 -0.080743
-0.043183 -0.019993 -0.009134 0.093461 0.062293
-0.055956 -0.052129 -0.076380 -0.112243 0.065413
-0.075567 0.019848 0.094121 0.021786 -0.068644
-0.060691 -0.037556 0.053416 -0.063583 -0.009116
-0.059647 0.033059 0.008383 -0.057678 0.106669
--0.086182 -0.028844 0.069038 -0.050651 0.045613
--0.022872 -0.050951 0.020221 0.009049 -0.129767
--0.034033 0.103312 0.070048 -0.008972 0.021930
--0.019606 -0.031561 0.065822 0.016592 -0.009995
--0.028203 0.056913 -0.043993 -0.020496 0.028610
-0.050871 0.070498 -0.045548 -0.038539 -0.050789
-0.065005 -0.048246 0.011105 -0.026236 0.004123
--0.069629 0.029918 -0.108123 -0.018902 0.020385
-0.012121 0.000873 0.079758 -0.028851 -0.001646
-0.048281 -0.044204 -0.025910 -0.031220 0.006049
--0.039981 0.031852 -0.007419 -0.008198 -0.105351
-0.021943 -0.009020 0.041415 -0.051481 0.064758
--0.066937 0.070473 -0.128350 0.059786 -0.012980
-0.046171 -0.005175 -0.054847 0.066448 -0.057361
-0.015253 -0.020476 0.048261 -0.069168 -0.074295
--0.072588 -0.042977 0.018592 0.070496 0.114648
-0.010817 -0.128853 -0.097246 0.020464 0.031236
--0.024940 0.041108 0.011415 0.087818 -0.043080
-0.025168 0.025134 0.027778 -0.030419 -0.017191
--0.010787 -0.089466 0.006383 0.016841 0.083765
-0.008103 0.031762 -0.065297 -0.043194 0.060151
--0.031870 0.035064 -0.027919 0.019804 0.031581
-0.015682 -0.090393 0.054461 -0.051669 -0.020003
--0.006273 0.029554 -0.052349 0.122862 0.052590
-0.053436 -0.092575 -0.038422 -0.014132 0.025596
--0.007446 -0.068838 -0.100706 0.110571 -0.074217
--0.124216 -0.046391 -0.001952 -0.035192 0.056849
-0.049815 -0.000716 0.078561 0.103458 -0.031106
-0.004277 0.053141 -0.013453 -0.014118 -0.043585
-0.037082 -0.072984 0.085005 0.059632 -0.092468
-0.070536 0.024296 0.032733 -0.064865 0.050807
-0.048457 0.051588 0.064615 0.014068 0.107732
--0.036905 -0.023656 0.039094 -0.021163 0.016683
--0.033733 -0.099111 -0.053957 0.004493 -0.052760
--0.012367 0.103975 0.055514 -0.018205 -0.077832
--0.018229 0.099840 0.043099 0.026033 -0.127892
-0.005209 0.115289 0.030702 -0.090228 0.102291
--0.036231 0.059027 -0.073456 0.025828 -0.058846
-0.023155 -0.021831 0.050419 -0.052958 -0.025641
--0.057417 -0.038855 0.069655 0.009463 -0.011469
--0.001709 0.032146 0.133188 -0.084494 0.022112
-0.105454 -0.037301 -0.006059 -0.002167 0.033760
--0.067749 0.052323 -0.002914 0.042408 -0.038078
-0.080983 0.032390 -0.013515 -0.017162 -0.001944
-0.018212 -0.057337 -0.024336 0.003385 -0.053031
-0.007656 0.093900 0.019898 0.057621 -0.016597
-0.028536 0.010449 -0.048939 -0.132260 -0.015093
--0.032383 0.042496 0.006198 0.022980 0.050028
--0.091286 0.046546 -0.012873 0.053569 0.100661
-0.001121 0.033644 -0.044783 0.040892 -0.007458
-0.015227 0.057715 0.135154 -0.011532 -0.048523
--0.020718 -0.100767 0.060073 0.082344 -0.067297
-0.052855 0.019105 -0.072241 -0.034480 0.046910
-0.028509 0.105159 -0.005862 -0.006672 0.031437
--0.044146 -0.049556 0.015169 -0.001790 -0.082293
--0.043861 0.020628 -0.082354 0.150955 -0.022192
--0.053152 -0.023628 -0.040518 -0.032409 0.040596
--0.072007 -0.085815 0.034433 0.062865 0.051963
-0.007741 -0.008439 0.034908 -0.009552 -0.032946
-0.043386 0.024843 0.020463 0.077839 0.109446
--0.033733 -0.111561 -0.077032 -0.028750 -0.004143
-0.027687 -0.006467 0.011063 0.043189 -0.123963
-0.091285 0.045529 -0.007055 -0.051180 -0.054342
-0.012612 -0.032042 0.014321 0.047055 0.140528
--0.069055 -0.048973 -0.035481 -0.091096 0.061054
--0.017211 -0.042891 -0.047427 0.050343 -0.010907
--0.031955 0.062361 0.017419 -0.036013 -0.002721
-0.041131 0.024163 0.089626 0.022372 0.009373
--0.095530 0.047262 -0.031783 -0.036250 -0.009977
--0.021451 0.082581 -0.051394 -0.022879 -0.034885
-0.076878 -0.111199 -0.010824 0.015104 0.028609
--0.085213 0.147576 -0.065340 0.019676 0.072754
-0.082529 0.036091 0.076516 0.052432 0.071795
-0.008287 -0.036426 -0.009891 0.029857 0.002193
--0.003334 -0.028181 -0.037997 -0.010828 -0.075271
--0.009274 -0.000105 0.026357 -0.014523 -0.000196
-0.045930 0.012760 -0.088269 0.009968 -0.079905
-0.046175 0.009370 -0.000002 0.029935 -0.042887
-0.023842 0.018746 -0.006990 0.008271 -0.090227
-0.030612 0.016519 0.081049 0.009339 0.055323
--0.044325 0.004172 -0.068893 -0.045980 0.077715
-0.001175 -0.046950 0.036603 0.091690 -0.007926
--0.030905 0.059344 0.015477 -0.098726 -0.013555
--0.055799 -0.077539 -0.011439 -0.004065 0.054785
-0.034376 0.008123 -0.066323 0.015381 0.051534
--0.029072 0.008390 -0.021483 0.034645 -0.015101
--0.032733 -0.053135 0.072680 -0.018542 0.019239
-0.037756 0.062391 -0.075094 0.101033 0.003228
-0.041719 -0.083617 0.062272 -0.023256 0.039273
-0.009314 -0.036930 -0.022348 0.054612 -0.061547
--0.057502 -0.045821 -0.027136 -0.057127 -0.040360
-0.066291 0.009189 0.032460 -0.001094 -0.054085
-0.006575 -0.054172 -0.130758 -0.090713 -0.002316
-0.034393 -0.052381 0.012536 0.038109 -0.081767
-0.085920 0.009447 -0.009120 -0.115802 -0.024373
--0.009739 0.098210 -0.050578 0.009031 0.067793
--0.102503 0.070893 0.048610 0.025783 0.070098
--0.082345 -0.110272 -0.069934 0.039617 -0.015865
-0.093134 0.050931 0.078967 0.014464 0.014646
--0.080307 -0.028843 0.108070 -0.021868 -0.059963
--0.033823 0.075594 0.036621 -0.060586 0.034463
-0.062713 0.100354 -0.048699 0.006569 -0.054387
-0.085716 -0.042197 0.055028 -0.023813 -0.019848
--0.128971 0.064906 -0.014135 0.053208 -0.054020
-0.012192 -0.023224 0.086982 0.002569 0.081299
-0.043572 -0.052176 -0.053337 0.001834 -0.002848
--0.073999 0.045245 -0.072961 0.011777 -0.001025
--0.038850 0.021979 0.082271 0.023871 -0.014373
-0.066920 0.022695 -0.046891 -0.028261 0.005879
--0.066511 0.074096 0.039110 0.046744 -0.001032
--0.028041 0.019515 -0.079802 -0.098550 -0.057732
-0.050261 0.061069 -0.014075 0.084526 0.061622
--0.011750 -0.051429 -0.073887 -0.004920 0.014058
--0.107882 -0.029024 -0.096352 0.047279 -0.040754
--0.069567 0.060745 0.075817 -0.045723 -0.101709
--0.047723 -0.030640 0.056081 0.076466 0.002197
--0.010621 0.007690 -0.030150 -0.067986 0.062739
-0.117024 0.061613 0.012656 0.043682 -0.031102
-0.018671 -0.047947 -0.040784 -0.089523 -0.106392
--0.005815 -0.001616 -0.068421 0.027810 0.057644
--0.008067 -0.006506 0.039180 -0.154508 -0.011541
-0.033405 -0.122890 -0.013528 0.038364 -0.001838
--0.004906 -0.046275 -0.038730 -0.031623 -0.003879
-0.152370 -0.022857 -0.072307 0.029362 0.058441
-0.009357 -0.022712 -0.075829 -0.057416 -0.038179
-0.011980 0.029996 0.082156 0.024194 -0.072075
-0.072125 -0.051638 0.039224 -0.086809 -0.049036
--0.016999 -0.028023 -0.045506 -0.030265 0.170708
--0.044189 -0.166394 0.095599 -0.078305 0.024710
--0.012502 -0.049717 0.030435 0.149411 -0.047396
--0.004166 0.092334 0.002567 0.003784 0.058999
--0.014837 -0.013693 0.116725 -0.016922 -0.014098
--0.026542 0.025453 -0.072587 -0.010040 0.040512
-0.061390 0.063914 -0.059682 -0.091206 -0.018253
--0.019787 -0.066510 0.016750 -0.053649 -0.028817
--0.092221 0.050852 -0.009044 0.047829 -0.002441
-0.018727 0.036731 0.089017 -0.091873 0.088367
-0.109395 0.014861 -0.097044 -0.015050 0.009286
-0.002921 0.027523 0.011728 -0.046926 -0.098498
-0.000836 -0.056539 0.023297 0.018001 0.049131
-0.004675 0.001073 -0.170749 0.014371 0.034021
-0.020092 0.037851 -0.028229 0.102064 -0.048952
--0.025833 -0.026058 0.012805 -0.114410 -0.051993
-0.013397 -0.036918 0.089997 0.157135 0.083396
--0.039602 -0.080711 -0.021277 0.053202 0.071289
--0.109812 0.002914 -0.015096 0.091661 0.031649
-0.001854 0.034905 0.032772 -0.002794 -0.042979
-0.068519 -0.063135 0.013342 -0.006060 0.046252
-0.017425 0.141501 -0.060676 -0.083881 0.048423
--0.023162 0.027077 -0.098028 -0.014739 0.010480
--0.022374 -0.086942 0.100437 -0.075083 -0.115201
-0.007563 0.033322 -0.103828 0.051361 0.024684
--0.004454 -0.055777 -0.046699 -0.082728 0.073797
-0.055443 -0.143092 -0.037825 0.078811 0.036497
--0.077281 -0.008325 0.013544 -0.017594 -0.041641
-0.047789 -0.034492 -0.002379 0.073826 -0.075772
--0.009782 0.050561 -0.019115 -0.056305 -0.001601
--0.034683 0.008058 0.060254 0.034221 -0.132588
-0.051493 -0.015100 -0.031876 -0.051222 0.000989
-0.047049 0.026343 -0.041914 -0.036045 0.095869
--0.062112 -0.018423 0.003773 -0.027867 -0.010398
--0.048280 -0.036537 -0.017897 -0.005851 -0.058694
--0.014345 0.061231 0.015028 -0.034773 -0.062937
--0.000104 0.042883 0.145663 0.087783 -0.037200
-0.016255 0.036518 0.046461 -0.034405 0.079881
-0.035236 0.059227 -0.075679 -0.016770 -0.068794
-0.070744 -0.037727 0.127718 -0.021398 -0.046414
--0.032597 0.063874 0.097691 0.026403 -0.004663
--0.087849 -0.026770 0.144388 -0.048131 0.031670
-0.106295 -0.065269 -0.040652 -0.014211 0.056560
--0.043383 0.070554 -0.010791 0.053436 -0.111118
-0.031068 0.016914 0.052035 0.004705 -0.005330
-0.034760 -0.023902 -0.025479 -0.020657 -0.051098
-0.009155 0.063415 0.088456 0.063249 -0.036212
--0.000009 0.037196 -0.081303 -0.097243 -0.019263
-0.029158 0.050108 0.039763 0.121192 0.042011
--0.067899 -0.051989 -0.021537 0.068444 0.027782
--0.016312 -0.019484 -0.002050 0.053199 0.005392
--0.008887 0.011627 0.044619 -0.090553 -0.063460
-0.004298 -0.096710 0.054118 0.026422 -0.054091
-0.011429 0.013193 -0.050806 -0.014131 0.048069
-0.073934 0.058524 -0.027092 0.000422 0.030744
--0.027127 -0.040621 -0.081295 -0.132942 -0.174424
--0.009461 0.028177 -0.035784 0.088923 0.029507
--0.031399 0.023611 -0.016887 -0.076838 0.033483
-0.030485 -0.089706 0.003531 0.109110 0.014393
--0.057547 -0.003360 0.039022 0.000441 -0.017536
-0.010777 0.032913 0.009826 0.011260 0.063002
-0.039884 -0.084768 -0.091794 -0.019418 0.001947
-0.035580 0.092377 0.044137 -0.039732 -0.073936
-0.074461 -0.026009 -0.018411 0.052151 -0.023017
--0.074733 -0.019706 -0.045403 0.041498 0.114826
--0.062412 -0.015496 -0.008802 0.010005 0.134097
--0.006114 -0.127624 -0.111323 0.020666 -0.044975
--0.039706 0.068792 0.011916 0.016754 -0.000454
--0.010497 0.014889 0.070891 0.116098 0.021857
--0.085198 0.023739 -0.088592 -0.046397 -0.013729
--0.021026 0.161165 0.011340 -0.032323 -0.022466
-0.071886 -0.105818 0.021622 0.083276 -0.011759
--0.053961 0.111353 -0.063359 0.048522 0.020913
-0.155966 -0.097759 0.067338 0.004069 0.048556
-0.039733 0.024807 -0.036450 0.026902 -0.001497
-0.008231 0.007538 -0.082664 -0.024402 -0.130124
-0.001341 0.009836 0.031207 -0.007516 0.063997
-0.013111 0.044756 -0.108910 0.036952 -0.038516
-0.032064 0.054737 0.021054 0.090083 -0.095331
-0.086201 0.072386 0.002048 -0.084090 -0.123429
-0.036048 -0.020936 -0.001486 0.048416 0.057746
--0.007902 -0.025902 -0.039170 -0.090144 0.033093
--0.037429 -0.008878 0.031789 0.108803 -0.001264
--0.067338 0.047247 -0.010053 -0.104491 0.019316
--0.038488 -0.110868 -0.017281 -0.069637 0.003541
-0.034292 0.055001 -0.090837 -0.028732 0.016192
-0.056000 0.072632 -0.022204 0.040858 0.031991
--0.034742 -0.035448 0.019035 -0.013232 -0.014398
--0.006173 0.109096 -0.049988 0.013882 0.005876
--0.010246 -0.017441 0.025300 -0.098996 0.052687
-0.025387 0.000912 -0.009639 0.084043 -0.052007
--0.083781 -0.030439 -0.073927 0.007538 0.012090
-0.066881 -0.025604 0.016332 0.037268 -0.033802
--0.015458 -0.021930 -0.070557 -0.051580 0.012924
--0.009009 -0.017953 0.042537 -0.020288 -0.091337
--0.024530 0.040526 0.056023 -0.110282 0.026677
--0.038359 0.097050 0.014986 0.037195 0.054785
--0.083630 0.055443 -0.035272 0.003855 0.043706
--0.057062 -0.037280 -0.046268 0.022056 -0.034342
-0.003546 0.055713 0.011998 0.006224 -0.025227
--0.088934 -0.028368 0.079334 -0.001505 -0.127990
--0.061598 0.084053 0.025380 -0.096473 0.067390
--0.020260 0.092217 -0.018618 0.027917 -0.048252
-0.031415 -0.091387 0.090810 0.045103 -0.026705
--0.064460 0.002074 0.031180 0.067323 -0.016903
--0.005864 -0.003330 0.069051 -0.033416 0.082203
-0.044956 -0.053755 -0.137252 -0.046061 0.093635
--0.088599 0.097969 -0.032264 -0.086639 -0.091644
-0.033056 0.016076 0.011350 0.037895 0.004198
-0.044101 0.049833 -0.032485 0.037383 -0.129242
--0.042353 0.109453 -0.005173 0.074401 -0.070002
--0.005799 0.052127 0.027453 -0.100450 -0.058706
-0.015240 0.069141 0.015929 0.041277 0.055504
--0.023227 -0.001112 0.002065 0.012704 0.036834
--0.089424 -0.016815 0.074728 0.052480 -0.044368
--0.072117 0.037136 0.079468 -0.038248 -0.057019
-0.003825 -0.069667 0.055439 0.014255 0.032135
--0.036398 0.060844 -0.051464 -0.103545 0.071708
-0.063325 0.075800 0.002963 -0.013314 0.045130
-0.020282 -0.083516 0.014408 -0.071592 -0.027531
--0.010278 -0.013934 -0.042730 0.072202 0.007273
--0.019582 -0.018122 0.004112 -0.129409 0.026095
--0.031100 -0.041493 0.001026 0.068622 0.045611
--0.016275 0.007467 0.007254 0.005397 -0.030822
-0.027449 -0.020425 0.019762 0.122976 0.047420
-0.032987 0.001328 -0.098351 -0.053497 0.013908
-0.029366 0.013866 0.122783 0.041198 -0.068939
-0.102145 -0.006101 0.037359 -0.057573 0.015037
-0.049004 -0.008177 -0.020529 -0.022026 0.125989
--0.072538 -0.037701 0.022874 -0.032248 0.015711
--0.012920 -0.043093 -0.039808 0.025999 -0.059643
--0.020747 0.120412 0.058354 0.038064 0.023366
-0.022306 -0.008795 0.096772 0.019502 -0.021527
--0.031783 0.042640 -0.012099 -0.056425 0.052337
-0.040885 0.076375 -0.024182 -0.007386 0.006375
-0.012472 -0.048071 -0.011689 -0.054259 0.004254
--0.041141 0.023551 -0.047763 0.040648 0.055189
-0.041209 0.026372 0.083642 -0.041189 0.018401
-0.098897 -0.079038 -0.058140 -0.021688 -0.004584
-0.008362 0.050981 0.027989 0.004290 -0.077892
-0.079784 0.022189 -0.000950 -0.028833 0.038684
--0.020911 0.002112 -0.089285 -0.009057 -0.044291
-0.067770 0.023611 -0.010856 0.057004 -0.068496
-0.028960 -0.012273 0.005375 -0.038117 -0.075004
-0.002103 0.002426 0.056212 0.025731 0.113254
--0.069929 -0.080474 -0.089722 -0.019285 0.039492
--0.047136 -0.038086 -0.013093 0.104245 -0.014991
-0.002220 0.028745 -0.014120 -0.003022 0.024545
-0.002795 -0.099925 0.077130 -0.017081 0.101062
--0.062377 0.063615 -0.060597 -0.033619 0.126293
--0.014254 0.057849 -0.017270 0.000255 0.046692
--0.054974 -0.092568 0.028597 -0.061007 -0.049412
-0.026217 -0.012099 -0.046248 0.055666 0.060678
-0.069724 -0.056332 -0.008145 -0.067284 0.012714
-0.050454 -0.036820 -0.038474 0.094104 -0.025727
--0.075576 -0.039175 0.010329 0.008010 0.003823
-0.101716 -0.042132 0.070715 0.035590 0.040456
-0.006306 0.001003 -0.055836 0.007729 -0.026461
--0.015636 -0.027037 0.017196 0.048239 -0.066902
-0.090990 0.022012 -0.017646 -0.098129 0.037112
-0.005951 0.024530 0.021647 -0.014662 0.107048
--0.087049 -0.037337 0.044913 0.024889 0.092117
-0.019813 -0.103273 -0.011622 0.001294 -0.057107
--0.019526 0.055974 0.039931 -0.006568 -0.007790
--0.048103 0.049238 0.061609 0.006077 -0.075369
--0.009412 0.048275 0.009865 -0.081620 0.092182
--0.017333 0.064175 -0.040670 0.004648 -0.022311
-0.003981 -0.066772 0.051258 -0.003877 -0.019203
--0.071235 0.039869 0.084219 -0.012268 0.000880
--0.047928 0.058804 0.087149 -0.026185 0.038879
-0.064338 -0.035073 -0.023367 0.048265 0.050703
--0.021562 0.045307 -0.009582 -0.003124 -0.020818
-0.022634 -0.009844 0.002915 -0.015520 -0.030355
-0.083917 -0.031796 -0.047661 0.008159 -0.040844
-0.028545 0.035008 0.057934 0.053669 -0.054020
-0.035223 0.042440 -0.036255 -0.096245 -0.051155
--0.029984 0.014055 0.019736 0.048158 0.004093
--0.025898 -0.014328 0.002510 0.028365 0.085207
-0.006077 0.002203 -0.027505 0.047570 -0.017349
--0.020587 0.067784 0.099796 -0.026735 -0.024473
--0.025703 -0.094091 0.031649 0.029644 0.003411
-0.058308 0.049034 -0.068172 -0.115474 0.069425
-0.033811 0.118472 0.050946 0.053623 0.078579
--0.019271 -0.065324 0.045402 -0.037870 -0.047215
--0.005675 0.086373 -0.014768 0.145929 0.037386
--0.014700 -0.049202 0.023594 -0.056698 0.023680
--0.033374 -0.061027 -0.059854 0.138963 0.011599
-0.001533 -0.035748 -0.008464 0.032284 -0.039337
-0.081951 -0.006716 -0.010483 0.112224 0.090494
--0.038372 -0.067773 -0.036190 -0.038843 -0.011294
-0.090443 0.048152 0.042218 0.056232 -0.093971
-0.122476 -0.005575 -0.036654 -0.029043 -0.034003
-0.022275 -0.033887 -0.060285 0.004531 0.075150
--0.065225 -0.097285 -0.022983 -0.069686 0.069205
--0.001642 -0.056254 -0.077585 0.025569 -0.054803
--0.100539 0.093912 0.080158 -0.002782 0.010494
--0.006143 0.026757 0.145882 -0.004906 0.028979
--0.109082 0.071364 -0.005886 -0.068041 0.037065
--0.018060 0.065418 -0.041926 -0.102324 -0.083326
-0.011189 -0.087023 -0.052738 -0.029586 -0.017342
--0.039294 0.027361 -0.091183 0.088291 0.045424
-0.057392 -0.021108 0.072939 0.049198 0.122993
-0.038302 -0.020317 -0.005652 0.011269 -0.001771
--0.047838 -0.064151 -0.069358 0.022155 -0.083435
-0.003546 0.019317 0.007896 0.030876 0.029493
--0.015680 0.011502 -0.079687 0.043705 -0.076931
-0.007474 0.001457 0.006085 0.047001 -0.040679
-0.038183 0.030132 -0.015742 -0.043583 -0.066149
--0.013762 -0.006024 0.029832 0.027818 0.040294
--0.027094 -0.024302 -0.105055 -0.022415 0.045939
-0.003325 -0.031412 0.002150 0.091557 0.040350
--0.023031 0.051570 -0.004636 -0.046863 -0.032721
--0.001379 -0.136365 0.030118 -0.015619 0.060966
-0.051409 0.002981 -0.085911 0.034787 0.092612
--0.024351 0.032927 -0.011889 0.047216 0.013262
--0.031903 -0.008671 0.062494 -0.057320 -0.025303
--0.026174 0.061109 -0.031321 0.063430 -0.001627
-0.033534 -0.042932 0.077354 -0.044685 0.038110
-0.029437 -0.011422 -0.026351 0.079037 -0.011110
--0.065906 -0.012694 0.002666 -0.081176 0.007352
-0.047210 -0.022385 0.022590 0.004000 -0.056449
-0.028936 -0.002388 -0.119043 0.000528 -0.022876
-0.000565 -0.041766 0.035570 -0.010223 -0.055419
--0.003717 0.050681 0.042119 -0.073103 -0.034640
--0.019828 0.077821 -0.007847 0.115964 0.095672
--0.057148 -0.022559 0.035308 -0.042327 0.097345
--0.034233 -0.054020 -0.057557 0.089841 0.009229
-0.070683 0.108539 0.046246 -0.050120 -0.008497
--0.056988 -0.048306 0.068906 0.015296 -0.073327
-0.020887 0.044562 -0.007768 -0.071345 0.057720
-0.027704 0.094761 -0.024903 0.058677 -0.054592
-0.045246 -0.128952 0.028581 0.009761 -0.036013
--0.137353 0.034736 0.027748 0.045031 0.020522
--0.032682 -0.010848 0.135840 -0.008210 0.064445
-0.016483 -0.066692 -0.036966 -0.018892 0.037266
--0.055969 -0.000146 -0.070159 -0.043813 -0.035507
-0.007295 0.067471 0.062439 0.031139 0.004051
-0.081763 0.058234 -0.080642 0.039998 -0.014646
--0.020107 0.121620 -0.031533 0.049787 0.048427
--0.027995 0.017340 -0.036722 -0.027766 -0.072522
-0.016754 0.116377 -0.007417 0.117559 -0.023170
--0.036028 -0.013555 -0.057848 -0.006776 0.057208
--0.080437 -0.067988 -0.044028 0.086414 -0.051744
--0.073007 0.043810 0.014807 -0.049665 -0.049222
--0.085317 -0.073906 0.084214 0.028253 0.022565
-0.061129 -0.008498 -0.065248 -0.093368 0.125544
-0.101010 0.030100 0.021030 0.003998 -0.000819
-0.051523 -0.052633 -0.031029 -0.086071 -0.030398
--0.049646 -0.039065 -0.114362 0.111554 -0.013322
-0.060882 -0.037407 -0.007392 -0.128509 0.069699
-0.010662 -0.095924 0.004877 0.022956 -0.003608
--0.040638 0.005864 -0.025032 0.003803 -0.033060
-0.104406 0.009014 -0.070791 0.101107 -0.010706
-0.018493 -0.060775 -0.046556 -0.102536 -0.058762
-0.013012 0.047639 0.074284 -0.021771 -0.071480
-0.121697 -0.062576 -0.061069 -0.084239 -0.030672
--0.053509 -0.072509 0.029717 -0.075666 0.119601
--0.071159 -0.064371 0.049556 -0.006955 0.050790
--0.014936 -0.030424 -0.029046 0.095626 -0.053380
-0.026242 0.084580 0.046043 -0.013774 0.048761
--0.003036 -0.055345 0.130574 0.072416 -0.040259
--0.012252 0.029803 -0.017821 -0.029420 0.057413
-0.036485 0.041237 -0.032473 -0.046230 0.000440
--0.003955 -0.066533 0.009267 0.004057 0.002718
--0.054960 0.012076 -0.051431 -0.001750 0.015747
-0.067251 0.037864 0.116071 -0.012828 0.063945
-0.065686 0.005781 -0.102444 0.050582 -0.006415
--0.022414 0.010021 0.095137 -0.034063 -0.154439
-0.018933 -0.026790 -0.009372 -0.025828 0.058756
-0.008035 -0.025525 -0.090140 -0.012845 -0.008559
-0.017881 -0.039468 -0.051786 0.088240 -0.081061
-0.017134 -0.000603 0.072990 -0.106103 -0.045466
--0.026151 -0.003544 0.108411 0.044002 0.070681
--0.065841 -0.096530 -0.055378 0.015170 0.126129
--0.048244 0.006173 0.013564 0.196118 -0.046276
--0.026911 0.046123 0.060438 -0.042470 -0.007582
-0.086581 -0.077901 0.057108 -0.013982 0.095961
-0.013568 0.081727 -0.063919 -0.008458 0.020099
-0.015455 0.049515 -0.048905 -0.006740 0.017709
--0.023263 -0.011752 0.104977 -0.091749 -0.072352
-0.041545 0.027311 -0.061505 0.073899 0.057681
-0.060911 -0.048034 -0.006742 -0.018161 0.082492
-0.044955 -0.030697 -0.042272 0.060646 0.025253
--0.095552 -0.007674 -0.037376 -0.042828 -0.028071
-0.078704 0.034767 0.003569 0.103759 -0.017217
--0.006459 -0.003174 -0.006884 -0.052177 0.000067
--0.000080 0.002880 0.067251 0.077245 -0.083559
-0.043695 0.037396 0.005392 -0.085654 0.021389
-0.037997 0.095932 -0.028364 -0.033582 0.112597
--0.047949 0.014115 0.027626 0.006558 0.055128
--0.035469 -0.081510 -0.015853 0.031846 -0.003825
--0.019678 0.109423 0.054030 -0.050997 -0.017309
--0.027511 -0.012712 0.078270 0.073890 -0.036127
-0.007627 0.021692 0.029178 -0.076480 0.035985
--0.013671 0.074729 -0.070079 -0.041782 -0.003345
-0.081644 -0.007541 0.018661 -0.069248 -0.082554
--0.066409 0.041793 0.088394 0.023002 0.031839
--0.004239 -0.055445 0.153536 -0.029606 0.011440
-0.120925 -0.031292 0.009491 0.023924 0.097333
--0.064946 0.044945 -0.036368 0.075204 -0.043170
-0.084879 0.044759 0.026172 0.014565 0.045921
-0.045467 -0.017067 -0.028516 -0.030039 -0.097097
-0.033711 0.032445 0.072773 0.052865 -0.002100
-0.007495 0.042950 -0.042792 -0.074042 -0.011530
--0.056728 0.042999 0.092369 0.099547 0.013443
--0.054306 -0.043025 -0.068623 0.095940 0.074227
--0.079501 -0.007941 0.000413 0.032496 -0.031837
--0.016260 0.033024 0.064746 -0.017847 -0.104087
-0.000197 -0.151410 0.074026 -0.001001 -0.031403
-0.046221 0.036460 -0.040808 -0.021449 0.032127
-0.079554 0.080997 -0.076818 -0.019398 0.037202
--0.001902 -0.080469 -0.020903 -0.017046 -0.093414
--0.063198 0.002218 -0.041482 0.114007 -0.001262
-0.004609 -0.045369 -0.012778 -0.106632 -0.009353
-0.046742 -0.093363 -0.020190 0.070943 0.104612
--0.026496 0.030245 0.036531 0.049474 -0.034971
-0.010070 -0.016557 -0.015930 0.036066 0.046365
--0.059709 -0.083439 -0.099145 -0.024957 -0.044832
-0.031623 0.022393 0.012334 -0.009649 -0.050844
-0.126142 0.023320 0.052720 0.016504 -0.047781
-0.002926 0.004861 -0.060239 0.050008 0.098520
--0.050552 -0.025407 -0.003390 -0.014939 0.068650
-0.032517 -0.092568 -0.058102 0.078834 -0.068898
-0.001143 0.108254 0.006322 0.014800 -0.012314
-0.050222 -0.034504 0.174248 0.025459 -0.002951
--0.040868 0.022522 -0.081662 -0.051546 0.029154
--0.001469 0.154137 0.010623 0.000752 0.036767
-0.113304 -0.068389 0.029430 0.054651 -0.072835
--0.063281 0.122269 -0.028825 -0.023612 0.018427
-0.073886 -0.005629 0.074243 -0.013698 0.036158
-0.027137 -0.008779 -0.051317 0.034729 0.011425
--0.005290 0.084381 -0.046825 -0.054925 -0.134575
--0.007420 -0.034384 0.032822 -0.006816 0.016250
-0.013071 0.022288 -0.116225 0.121282 -0.061502
--0.022397 0.009282 0.013596 0.083516 -0.068117
-0.018270 0.070016 -0.019013 -0.055558 -0.038255
-0.048457 -0.023579 0.050451 0.085665 0.035829
-0.005139 -0.053830 -0.068741 -0.045650 0.019271
--0.039606 -0.040208 0.113025 0.137240 -0.039967
--0.050847 0.011254 0.031376 -0.087299 0.036520
-0.012497 -0.096540 -0.005847 -0.023409 0.055187
-0.047393 -0.016958 -0.127368 0.014126 0.013071
-0.042850 0.030065 -0.005283 -0.003391 -0.012498
--0.063424 -0.066634 -0.007857 -0.012463 -0.048025
--0.038726 0.093465 -0.068296 -0.004955 0.020647
-0.064345 -0.025818 0.123250 -0.113614 0.042799
-0.012083 0.019991 -0.011713 0.093276 -0.018115
--0.069842 -0.040684 -0.062936 -0.036833 -0.057289
-0.048571 -0.021162 0.059277 0.027594 0.031567
-0.004623 0.013103 -0.070462 -0.031843 -0.062285
-0.003964 -0.043003 0.001089 0.007283 -0.094012
-0.089866 0.071995 0.101778 -0.112357 0.012040
--0.072256 0.086698 0.032881 -0.033458 0.098016
--0.082535 0.048160 0.026744 -0.027036 0.025903
--0.042452 -0.094755 -0.054770 0.004509 0.015786
-0.053114 0.051959 0.021238 -0.079127 -0.025941
--0.061221 -0.032380 0.000678 0.034720 -0.119877
--0.029004 0.038623 -0.037611 -0.139319 -0.005737
-0.041081 0.129303 -0.021741 0.027442 -0.123106
-0.038200 -0.064672 0.083376 0.032648 0.033742
--0.048851 0.029052 0.025199 0.023531 -0.025856
--0.003336 0.029494 0.075111 -0.010905 0.064079
-0.037642 -0.035068 -0.084707 0.026922 0.022164
--0.068680 0.075838 -0.025633 -0.004398 -0.115237
--0.004548 -0.002381 0.026301 0.068400 -0.006462
-0.121501 0.071558 -0.029120 0.004560 -0.059715
-0.020657 0.160004 -0.003257 0.029479 -0.040264
--0.009405 0.008581 -0.016967 -0.102333 -0.102278
--0.030081 0.075670 0.078504 0.112244 0.066878
--0.024548 -0.067136 -0.004662 -0.026166 0.044337
--0.066652 -0.078118 0.000364 0.038618 -0.076186
--0.089846 -0.017872 0.072022 -0.066259 -0.059455
--0.028736 -0.093805 0.079006 0.023036 -0.015992
--0.045002 -0.004511 -0.021728 -0.091307 0.072076
-0.104573 0.051663 0.037822 0.009659 0.091841
--0.000223 -0.070248 0.002859 -0.085403 -0.067834
--0.010392 -0.032752 -0.036464 0.047626 0.061988
--0.020766 -0.098673 0.010533 -0.120437 -0.028288
--0.010613 -0.086247 -0.006349 0.031765 0.038227
--0.042501 0.012368 0.001644 -0.053936 -0.052854
-0.040412 0.006924 0.010332 0.084276 0.018472
-0.030309 -0.012747 -0.071598 -0.111819 0.023998
-0.087829 0.061878 0.094608 -0.037238 -0.050664
-0.036768 -0.026142 0.028210 -0.019029 -0.007024
-0.056710 -0.012442 0.005440 -0.103556 0.139787
--0.138355 -0.040445 0.025577 -0.107722 0.078150
--0.001450 -0.071658 -0.025306 0.038319 -0.103037
--0.028321 0.098830 0.057603 -0.007905 0.078051
--0.009903 -0.025356 0.086842 0.012796 0.022952
--0.014137 0.064001 -0.027812 -0.039279 0.060983
-0.027092 0.074119 -0.010385 -0.012999 -0.057892
-0.027647 -0.079000 0.021994 -0.032696 -0.014011
--0.042864 0.021318 -0.117190 0.023970 0.036325
-0.057969 0.007604 0.135989 -0.027874 0.036906
-0.067047 -0.008885 -0.080445 -0.027705 0.003494
--0.016421 0.020609 -0.029576 0.029755 -0.109042
-0.078601 -0.014246 0.028812 -0.022730 0.042634
--0.037523 0.028199 -0.083746 0.036775 -0.009971
-0.037147 0.014445 -0.058619 0.061398 -0.011282
--0.015391 0.000460 0.008396 -0.046827 -0.027835
--0.014145 -0.069296 0.027030 0.067044 0.087990
--0.003414 -0.125998 -0.042444 -0.033398 0.047298
--0.084005 0.001739 0.050690 0.114059 -0.044072
-0.002756 0.040246 0.024529 -0.045169 0.010004
--0.037919 -0.092984 0.039383 0.031606 0.079460
-0.010879 0.059048 -0.072431 -0.003405 0.086399
-0.008666 0.031679 -0.042362 0.054428 0.060492
--0.022185 -0.099806 0.129259 -0.080670 -0.043866
-0.012856 0.013568 -0.033243 0.095598 0.093044
-0.062030 -0.075113 -0.037729 -0.060376 0.060004
-0.031119 -0.061372 -0.096201 0.101855 -0.016822
--0.082510 -0.060718 -0.033015 -0.027222 0.007231
-0.062973 -0.041640 0.109215 0.081676 -0.013847
--0.013324 0.027366 -0.033590 -0.046803 -0.039116
-0.061055 -0.037717 0.065252 0.078148 -0.053763
-0.050494 -0.011958 0.033369 -0.107018 0.057087
--0.015111 0.079702 0.078616 0.051406 0.103170
--0.055713 -0.031900 0.039951 0.010658 0.030803
--0.032401 -0.161199 -0.006920 -0.041844 -0.054552
-0.068517 0.125210 0.080621 0.013543 -0.033413
--0.044663 0.074392 0.035932 0.023301 -0.045912
--0.009902 0.066933 0.032801 -0.049038 0.095407
--0.039521 0.112499 -0.074490 0.036163 -0.044197
-0.018696 -0.011558 0.057933 -0.025639 -0.061431
--0.081026 0.005753 0.057683 -0.011585 0.006821
--0.006872 0.098313 0.119539 -0.081953 0.004434
-0.067413 -0.006236 0.002746 0.014715 0.026754
--0.037853 0.034309 -0.028443 0.026642 -0.037707
-0.066061 0.019234 0.029629 -0.015190 -0.012766
-0.027166 -0.042834 -0.056186 -0.009603 -0.083747
-0.050175 0.073412 0.007110 0.043388 -0.043870
-0.042677 0.025735 -0.094635 -0.142996 -0.099443
--0.025460 0.022178 0.045321 0.069113 0.054570
--0.064131 0.000827 0.011239 0.039192 0.080176
--0.032389 -0.013939 -0.064993 0.048795 -0.022851
--0.004958 0.060895 0.123682 -0.068608 -0.074900
--0.019889 -0.062160 0.073126 0.058232 -0.032283
-0.081527 -0.007318 -0.072361 0.003923 0.047891
-0.057147 0.118678 -0.020847 -0.014802 -0.015634
--0.052605 -0.036531 0.034867 -0.078556 -0.111584
--0.003560 0.003142 -0.024669 0.173160 0.032364
--0.053222 -0.023754 -0.040899 -0.047008 -0.003696
--0.033042 -0.093138 -0.004980 0.112166 0.080717
--0.010216 -0.006619 0.021922 0.016601 -0.003126
-0.051343 0.053954 -0.046302 0.038985 0.078694
--0.030092 -0.107599 -0.081002 -0.105924 0.002939
-0.011743 0.034846 0.003716 0.065184 -0.117462
-0.164375 0.073700 -0.033512 -0.050132 0.014156
--0.000174 -0.023948 -0.024012 -0.006934 0.108972
--0.059460 -0.048846 -0.012336 -0.051560 0.072806
--0.018567 -0.058139 -0.097127 0.057960 -0.003780
--0.069194 0.099784 0.014634 0.002396 0.004753
-0.054780 0.066215 0.126638 0.054455 0.006893
--0.141807 0.059586 -0.018459 -0.063126 -0.022803
--0.035254 0.069275 -0.013827 -0.071276 -0.003613
-0.069290 -0.132719 0.008038 -0.042340 0.029226
--0.111912 0.046898 -0.082164 0.046524 0.042479
-0.097773 -0.009098 0.059874 0.073312 0.066974
-0.019922 0.006528 -0.012465 0.012819 -0.009649
--0.002277 -0.027303 -0.050759 -0.050323 -0.080025
--0.003253 -0.006990 -0.002405 -0.013040 -0.007020
-0.025178 0.055844 -0.116797 0.017350 -0.095996
-0.027313 0.001295 -0.036475 0.035209 -0.050719
-0.013403 0.027367 -0.033867 -0.020572 -0.083462
-0.026022 0.029014 0.068306 0.059719 0.045583
--0.102670 -0.014676 -0.070060 -0.007867 0.061628
-0.021102 -0.044131 0.078378 0.066952 0.012162
--0.059452 0.052841 -0.010660 -0.090335 -0.061320
--0.052210 -0.080353 0.003880 -0.025212 0.019020
--0.010473 0.007817 -0.044796 0.000027 0.083904
-0.006729 0.028716 -0.007627 0.008946 -0.012966
--0.049870 -0.073154 0.092609 -0.040256 -0.020294
-0.003554 0.076666 -0.067856 0.042000 -0.009122
-0.044476 -0.118767 0.080698 -0.076039 0.023373
-0.024567 -0.033258 -0.036048 0.044153 -0.019221
--0.018260 -0.035700 -0.029634 -0.065584 -0.049991
-0.042902 -0.000452 0.031084 0.045586 -0.065013
-0.072242 -0.014513 -0.122642 -0.018067 -0.052772
-0.066880 -0.103725 0.037586 0.013011 -0.086527
-0.032019 0.010695 0.027327 -0.089804 -0.030002
-0.010910 0.113012 -0.008852 0.024520 0.099760
--0.077270 0.018171 0.079814 0.035008 0.127627
--0.025609 -0.178637 -0.034357 0.054347 -0.012604
-0.043660 0.062421 0.068757 0.002273 0.000552
--0.055697 0.010254 0.102285 0.024048 -0.044425
--0.004860 0.053366 0.013063 -0.098388 0.046218
-0.043926 0.077559 -0.036943 0.060936 -0.016764
-0.098322 -0.041365 0.092078 0.019431 -0.039793
--0.118098 0.023995 0.053538 0.015639 -0.041697
--0.011851 -0.052177 0.084977 -0.050669 0.070218
-0.030401 -0.076060 -0.020483 0.012783 0.033816
--0.050769 0.057281 -0.040092 -0.021298 -0.002690
--0.001729 0.035744 0.065206 -0.002257 0.015864
-0.044906 0.045612 -0.081326 -0.040729 -0.018151
--0.048153 0.086870 0.077712 0.059363 -0.027251
--0.089240 0.025410 -0.036539 -0.067019 -0.057377
-0.058057 0.070889 -0.015866 0.124536 0.012038
--0.007238 -0.051026 -0.027541 0.019248 0.026927
--0.083553 -0.025718 -0.042635 0.058541 -0.011741
--0.059778 0.065660 0.061292 -0.086725 -0.032482
--0.047209 -0.027933 0.087677 0.047367 0.001582
-0.051308 -0.018242 -0.025264 -0.062026 0.074843
-0.088969 0.059484 0.048905 -0.025787 -0.015960
-0.010270 -0.030210 0.036763 -0.093327 -0.114689
-0.013105 -0.035443 -0.085439 0.043021 0.056988
--0.020390 -0.008308 0.009722 -0.148341 0.081086
-0.010332 -0.101445 -0.021486 0.078663 0.025110
-0.007874 -0.023882 -0.034158 0.002488 -0.015558
-0.158690 -0.025837 -0.011736 0.035542 0.005703
-0.001555 -0.019753 -0.040038 -0.051161 -0.002844
-0.041149 0.021540 0.062971 0.012070 -0.035360
-0.091865 -0.090158 0.020460 -0.046615 -0.038100
-0.002630 -0.055311 0.026706 -0.008623 0.155705
--0.030212 -0.117746 0.084958 -0.087229 0.092780
--0.011810 -0.084822 -0.029035 0.127892 -0.065824
-0.008357 0.089638 0.003467 -0.034364 0.040506
--0.001934 -0.050401 0.105320 0.007386 -0.011020
--0.055669 0.029633 -0.034990 -0.028782 0.050039
-0.059295 0.118394 -0.033924 -0.132036 0.012985
-0.000793 -0.035658 0.031224 -0.040614 -0.014333
--0.054078 0.015577 -0.031608 0.071981 0.019771
-0.079765 -0.007986 0.076487 -0.077172 0.119140
-0.102976 -0.039809 -0.092140 0.032478 -0.070501
--0.026617 -0.016197 0.009189 -0.039295 -0.117914
-0.014457 -0.061592 0.025979 -0.028542 0.042043
--0.029473 -0.031444 -0.158578 -0.003258 0.058182
-0.072344 0.052910 -0.092808 0.085354 -0.079413
--0.044358 -0.041179 0.072986 -0.129686 -0.025728
--0.005197 -0.108115 0.063915 0.073996 0.057224
-0.000050 -0.069751 -0.062690 0.026183 0.084719
--0.052197 -0.011673 0.032435 0.084752 0.060158
--0.031241 0.023120 0.048633 -0.025976 -0.032094
-0.051737 -0.070951 0.034497 0.003743 0.019843
--0.055829 0.115532 -0.098594 -0.066675 0.048946
-0.003976 -0.010224 -0.071617 0.007215 0.017134
--0.023828 -0.066295 0.084251 -0.039425 -0.074279
--0.010390 0.058722 -0.091528 0.073371 0.071531
--0.005671 -0.076154 -0.032125 -0.137305 0.071102
-0.068984 -0.088661 -0.037098 0.081501 -0.013426
--0.093305 0.025622 -0.014982 0.007427 -0.068188
-0.064271 -0.035807 0.026492 0.107054 -0.095956
--0.008699 0.021743 -0.031579 -0.040618 0.022948
--0.006215 -0.028661 0.082129 0.022510 -0.090809
-0.032763 -0.014948 -0.000344 -0.068665 0.009455
-0.064722 0.101146 0.018141 -0.019456 0.082955
--0.033054 0.018056 -0.025308 -0.023021 -0.006592
--0.027499 -0.079456 -0.014152 0.030881 -0.059661
--0.023889 0.075852 0.004376 -0.014776 -0.035516
--0.031784 0.056947 0.125839 0.039811 -0.082984
--0.015402 0.040202 0.031099 -0.040303 0.047701
-0.050471 0.082637 -0.118070 -0.024705 -0.027053
-0.042555 -0.045217 0.043471 -0.044274 -0.055532
--0.050709 0.038372 0.139423 0.034228 0.044240
--0.049598 -0.006876 0.084222 -0.084035 0.029679
-0.024672 -0.099431 -0.061796 0.004907 0.127399
--0.065852 0.032572 -0.083461 0.040649 -0.064464
-0.021261 0.012978 0.043311 -0.006692 0.029174
-0.033834 0.010903 -0.049322 -0.023014 -0.053063
-0.050601 0.079776 0.017751 0.090575 -0.044427
-0.037446 0.038015 -0.114311 -0.116158 0.028262
--0.049840 -0.001403 0.022194 0.134131 0.092987
--0.066064 -0.014258 -0.007936 0.069423 0.006734
--0.036449 -0.006999 0.014668 0.062054 -0.033927
--0.037695 0.031955 0.072185 -0.067258 -0.065412
--0.030677 -0.153131 0.064817 0.020761 -0.114634
-0.046484 -0.012249 -0.045214 -0.032565 0.032724
-0.038377 0.052687 -0.074746 0.015211 0.031545
--0.001416 -0.092829 -0.036780 -0.058636 -0.153621
--0.019035 0.008907 -0.020006 0.073795 0.064152
--0.000207 -0.014885 0.001697 -0.075230 0.026080
-0.012374 -0.089499 0.037475 0.064069 0.017655
--0.032040 -0.028499 0.036399 0.038500 -0.014121
-0.034750 -0.002062 -0.015799 0.000062 0.074059
-0.038031 -0.076502 -0.082402 -0.051544 -0.043409
-0.052959 0.046017 0.047906 -0.000054 -0.062527
-0.077616 -0.011144 -0.036095 0.006758 0.006522
--0.023224 -0.010642 -0.107560 0.051291 0.103622
--0.051956 -0.008535 -0.042995 -0.030987 0.123523
-0.039493 -0.107293 -0.068566 0.006004 -0.077249
--0.049696 0.040608 0.002098 -0.005654 0.027282
--0.009389 0.042181 0.088705 0.055663 0.013492
--0.021941 -0.005352 -0.129536 -0.049372 0.006692
-0.010255 0.107988 0.009301 -0.029104 -0.027292
-0.015083 -0.122624 0.012460 0.056717 -0.065848
--0.097599 0.064951 -0.063651 0.037039 -0.031919
-0.160199 -0.025996 -0.003930 -0.047321 0.027398
-0.043702 0.013525 -0.061810 0.010431 0.014853
-0.001414 -0.021460 -0.143900 -0.026666 -0.116995
--0.024697 -0.005896 0.048756 -0.053298 0.041329
-0.012695 0.052326 -0.133818 0.105903 0.031440
--0.035969 0.050106 0.022116 0.126387 -0.109337
-0.072036 0.100468 -0.005336 -0.056878 -0.046406
-0.015972 -0.014095 -0.004362 0.051363 0.094242
--0.044797 -0.027049 -0.074056 -0.081706 0.012076
--0.021437 0.047597 0.088166 0.121074 -0.053524
--0.101688 0.029406 0.050242 -0.066960 0.062052
--0.035998 -0.084834 0.048189 -0.024642 0.023264
--0.011644 0.041881 -0.143927 -0.036006 0.064384
-0.021606 0.052025 -0.023292 0.037743 0.004852
--0.027128 -0.078095 0.017231 -0.009425 -0.026275
-0.007197 0.096964 -0.068860 0.060880 0.037649
-0.014117 -0.065558 0.047350 -0.098632 0.083283
-0.045025 0.025416 0.038291 0.099379 -0.057242
--0.098262 -0.004438 -0.093149 -0.017525 -0.064476
-0.025479 -0.016529 0.020430 0.012592 -0.009811
--0.015037 0.005498 -0.076398 -0.034881 -0.007594
-0.028415 -0.040315 0.028704 -0.028492 -0.105515
-0.018470 0.042456 0.045301 -0.147209 0.007810
--0.047688 0.032497 -0.008208 0.017988 0.084280
--0.102271 0.004685 -0.018636 -0.003214 0.061342
--0.034608 -0.028335 -0.058715 -0.016027 -0.027108
-0.008836 0.088808 0.038542 -0.020970 0.000400
--0.050920 -0.007459 0.061998 -0.024563 -0.091152
--0.014850 0.115523 0.022779 -0.107846 0.019813
--0.004600 0.099048 -0.029527 -0.031147 -0.061377
-0.023544 -0.134421 0.066807 0.032147 0.021599
--0.043477 0.029615 0.039209 0.024621 0.019526
--0.002071 0.031970 0.101991 -0.003775 0.121976
--0.006993 -0.073412 -0.104010 -0.006442 0.062073
--0.052770 0.070835 -0.091445 -0.041991 -0.068768
-0.059883 0.020621 0.042259 0.038888 0.021605
-0.042693 0.038667 -0.040035 0.004977 -0.076466
--0.022332 0.056801 -0.000212 0.035708 -0.032640
--0.038064 0.006782 -0.009894 -0.100385 -0.033497
-0.025298 0.034269 0.027448 0.077164 0.050701
--0.027548 -0.022455 -0.035381 0.018361 -0.004348
--0.069287 -0.017294 -0.004310 0.071591 -0.054832
--0.053949 -0.001929 0.071395 -0.015681 -0.038443
--0.044016 -0.048662 0.078642 0.014355 0.048150
--0.009957 0.032861 -0.075294 -0.123870 0.026265
-0.093728 0.046174 -0.009184 -0.050917 0.079102
-0.050699 -0.110383 -0.040917 -0.086311 0.012596
-0.001827 -0.059395 -0.048207 0.063786 0.026565
--0.077077 -0.004569 -0.044546 -0.099623 0.006256
--0.016101 -0.027424 0.017338 0.024906 0.015827
--0.027372 -0.017107 0.034566 -0.019851 -0.035154
-0.065204 -0.032861 -0.006305 0.115986 0.005671
-0.060617 -0.019162 -0.098096 -0.042694 0.047107
-0.037104 -0.008058 0.084632 -0.004556 -0.101542
-0.075086 -0.009191 0.004624 -0.043225 -0.002498
-0.032484 0.053384 0.011807 -0.035382 0.158001
--0.043066 -0.071159 0.039828 -0.062471 0.016281
--0.043445 -0.029971 -0.014564 0.054938 -0.076111
-0.022672 0.108672 0.099046 0.018104 0.033550
-0.027144 -0.053217 0.067212 0.035840 -0.020805
--0.064595 0.009953 -0.011147 -0.063721 0.036759
-0.018701 0.102409 -0.031796 0.011001 -0.023883
-0.028968 -0.057157 -0.042508 -0.052145 0.008972
--0.065914 0.070920 -0.087959 0.024752 0.079740
-0.056457 0.008541 0.080771 -0.042955 -0.022030
-0.077296 -0.087393 -0.065077 0.010062 -0.035395
--0.023652 0.009169 0.016281 0.043270 -0.112518
-0.024860 -0.024549 0.016927 -0.028905 0.029316
--0.008912 -0.016575 -0.120884 0.023903 -0.054407
-0.044132 0.038152 0.018656 0.065922 -0.016132
--0.006389 -0.043456 -0.005277 -0.038377 -0.043256
--0.028775 -0.034704 0.041058 0.024792 0.075342
--0.087680 -0.084754 -0.123797 0.069380 0.046858
--0.058807 0.032247 -0.003162 0.075858 -0.011643
--0.015012 0.064356 0.018978 -0.013598 0.027903
--0.019744 -0.072473 0.036145 -0.023830 0.091601
-0.000445 0.030482 -0.087404 -0.045375 0.130636
-0.016918 0.057383 -0.002236 0.019154 0.035447
--0.068637 -0.064903 0.079540 -0.091132 -0.027111
-0.020001 -0.002105 -0.063610 0.085303 0.021592
-0.135112 -0.114788 0.011338 -0.012485 0.059281
-0.089211 -0.036178 -0.066274 0.112956 0.046283
--0.074477 -0.051750 0.031961 0.038617 0.011847
-0.114117 -0.067782 0.028677 0.047877 0.009921
-0.018292 0.016738 -0.056403 -0.038710 -0.010604
-0.020050 -0.022217 0.056833 0.036114 -0.051337
-0.155982 0.012794 -0.028857 -0.120583 0.084902
-0.013151 0.029339 0.004512 0.029269 0.158467
--0.059083 -0.044942 -0.002369 0.025053 0.077484
--0.006987 -0.128357 0.000998 0.000658 -0.008066
-0.002694 0.078402 0.051558 0.026018 -0.035135
--0.051516 0.093206 0.075687 0.007585 -0.030493
--0.042801 0.024643 0.035323 -0.068825 0.138089
--0.012481 0.043826 -0.059032 -0.004079 -0.057181
-0.030592 -0.043929 0.081829 -0.034370 -0.027097
--0.043916 0.028082 0.040159 -0.023825 0.016659
--0.040314 0.027255 0.066119 -0.088450 0.079633
-0.085602 -0.045368 -0.019169 0.063621 0.015908
--0.012968 0.043077 -0.011652 -0.009363 -0.072419
-0.041253 0.015117 -0.000599 -0.038888 -0.015197
-0.070823 -0.013167 -0.026186 0.024055 -0.072483
--0.003924 0.013391 0.055366 0.084999 -0.038449
-0.043468 0.030321 -0.071656 -0.068751 -0.085100
--0.045854 -0.012937 0.001146 0.029160 0.007917
--0.038722 -0.013069 -0.022602 0.017646 0.050031
--0.034069 0.004746 -0.045839 0.088322 -0.033433
--0.049425 0.044323 0.135449 -0.033950 -0.006189
-0.008117 -0.074632 0.033319 0.057707 -0.034315
-0.061949 0.058279 -0.069064 -0.024633 0.083634
-0.044328 0.065502 0.039147 0.045297 0.010853
--0.035928 -0.034367 0.029180 -0.079893 -0.056124
--0.021337 0.069848 -0.042840 0.100637 -0.021594
--0.017056 -0.026458 -0.005396 -0.038921 0.024334
--0.013119 -0.040654 -0.019092 0.122318 0.060562
-0.014946 -0.017839 0.014916 0.007557 -0.055684
-0.085343 0.020079 -0.020189 0.024923 0.038626
--0.008572 -0.098936 -0.015287 -0.036331 -0.030196
-0.029395 0.068464 0.062459 0.007118 -0.121145
-0.090713 0.018611 -0.060202 -0.064626 -0.026447
-0.020572 -0.066985 -0.020928 0.046500 0.071362
--0.032780 -0.113550 -0.035570 -0.046101 0.123381
--0.000637 -0.030887 -0.085549 0.058943 -0.047480
--0.069392 0.133001 0.039940 -0.054277 0.026772
-0.012818 0.061828 0.101149 -0.034239 0.018944
--0.101441 0.071801 -0.065653 -0.058695 0.062080
-0.017518 0.111010 -0.059046 -0.054110 -0.031295
-0.055930 -0.143458 -0.044617 -0.023186 -0.013649
--0.111579 0.040441 -0.065712 0.110422 0.014995
-0.035371 0.001600 0.051063 -0.002833 0.096648
-0.023072 0.007446 -0.027126 -0.021716 0.006914
--0.066680 -0.023776 -0.033004 0.018842 -0.100090
-0.006577 -0.009435 0.014480 0.005289 0.027268
--0.023355 -0.000517 -0.035704 0.018493 -0.073805
-0.007356 0.036041 -0.026668 0.057975 -0.046666
-0.054676 0.021222 0.006590 -0.020075 -0.091969
--0.024459 -0.004411 0.080089 0.014146 0.047996
--0.013099 -0.028560 -0.086210 -0.038070 0.115542
--0.029380 -0.069424 0.000189 0.102273 0.014531
--0.058430 0.045176 -0.004636 -0.048318 0.011492
--0.070572 -0.166966 0.056891 0.042773 0.015200
-0.025472 0.000731 -0.061858 -0.008651 0.108291
-0.012505 0.032344 0.012567 0.062585 0.015632
--0.026488 -0.012319 0.030187 -0.052121 0.002827
--0.017721 0.065865 -0.047380 0.020409 0.023943
-0.079766 -0.046306 0.060273 -0.027458 0.038828
-0.032883 -0.043636 0.000901 0.075220 -0.005792
--0.090456 -0.041894 0.002536 -0.104333 -0.034913
-0.038532 -0.048225 0.033342 -0.011078 -0.035938
-0.000390 0.038012 -0.135572 -0.025786 -0.050179
-0.001333 -0.078764 0.020818 -0.022520 -0.065079
-0.013806 0.009337 0.024640 -0.064068 -0.007668
--0.005821 0.054794 0.006679 0.052490 0.085097
--0.084449 0.026105 0.043027 -0.006820 0.063480
--0.005166 -0.108834 -0.074395 0.066384 0.003385
-0.002689 0.152176 0.074065 -0.025017 0.001996
--0.026355 -0.035760 0.063399 -0.010722 -0.053613
-0.040833 0.083154 0.032094 -0.074978 0.040456
-0.007659 0.060872 -0.050901 0.029009 -0.066327
-0.040735 -0.106153 0.073500 -0.025479 -0.054887
--0.075445 0.009415 0.016203 0.012388 0.014428
-0.000457 -0.036095 0.143621 0.046534 0.106183
--0.039550 -0.060834 -0.058729 -0.030704 0.046588
--0.069071 0.044146 -0.047632 -0.019171 -0.064829
-0.017817 0.047929 0.039073 0.022116 0.021014
-0.033732 0.050846 -0.059942 0.004345 -0.029985
--0.080140 0.129440 0.031031 0.084146 0.016015
--0.036682 0.044772 -0.049258 -0.056682 -0.051988
-0.039973 0.080584 0.002750 0.080571 0.017418
--0.049233 -0.050745 -0.078517 0.041796 0.028714
--0.073271 -0.009924 -0.046737 0.077202 -0.089452
--0.100286 0.026524 0.025935 -0.000519 -0.108153
--0.097136 -0.011694 0.088312 0.041746 0.052188
-0.026268 -0.054000 -0.039524 -0.030580 0.094436
-0.083377 0.058849 0.024027 0.068118 0.022595
-0.041719 -0.067897 0.005738 -0.058511 -0.080953
--0.011827 -0.008352 -0.136686 0.077343 0.036266
-0.035162 -0.013237 -0.040135 -0.166246 0.029329
-0.031590 -0.082787 -0.003165 0.022566 -0.029527
--0.026857 -0.030669 -0.012846 -0.014703 -0.024941
-0.097289 0.062474 -0.023270 0.071516 0.026007
-0.012490 -0.079323 -0.064277 -0.101304 -0.014965
-0.038609 0.050228 0.059018 -0.054583 -0.037042
-0.088943 -0.050793 -0.023046 -0.036841 -0.049866
-0.006089 -0.012353 0.050822 -0.044544 0.133501
--0.044647 -0.060379 0.051279 -0.028470 0.068335
--0.008481 -0.078112 -0.022666 0.077373 -0.024423
-0.000007 0.064437 0.062147 -0.038681 0.032008
--0.017525 -0.067472 0.114370 0.020743 -0.076853
--0.017874 0.001327 -0.014704 -0.014656 0.034577
-0.024361 0.056274 0.006448 -0.028830 0.044899
-0.016576 -0.044087 -0.010917 -0.013797 -0.018111
--0.065385 -0.007719 -0.037632 0.031813 0.021400
-0.049162 0.020931 0.037485 -0.026412 0.056338
-0.036907 -0.042904 -0.132436 0.043098 -0.041228
--0.035680 0.034986 0.047873 -0.072791 -0.131274
-0.044610 -0.023411 -0.025045 0.005907 0.046734
--0.032724 -0.061008 -0.111818 0.015564 -0.002133
--0.015445 -0.011766 -0.048157 0.139974 -0.079607
-0.004936 -0.033105 0.052832 -0.087579 -0.040662
--0.055766 -0.026403 0.102134 0.084616 0.064986
--0.020826 -0.077346 -0.025393 -0.002277 0.084614
--0.053523 -0.091453 0.022927 0.150824 -0.002083
--0.001161 0.030663 0.060472 -0.050918 0.018421
-0.027526 -0.091037 0.070144 0.040963 0.090458
-0.030099 0.071509 -0.062928 -0.052351 0.030143
--0.026417 0.032481 -0.045066 0.000111 -0.004684
--0.002093 -0.014278 0.173191 -0.019552 -0.072985
-0.033124 0.074779 -0.053669 0.106059 0.090086
-0.039197 -0.065054 0.025258 -0.050488 0.068107
-0.037370 -0.074734 -0.072895 0.041719 -0.026666
--0.116776 -0.050593 -0.022049 0.019100 -0.052687
-0.077699 0.002538 0.021642 0.069070 -0.025842
--0.025721 0.004558 -0.051248 -0.059783 -0.021367
--0.043714 -0.040732 0.063823 0.074918 -0.079342
-0.050195 0.021249 -0.028816 -0.061727 0.018248
-0.005884 0.050434 -0.021363 -0.018341 0.100200
--0.041043 -0.005428 0.011984 -0.030931 0.026453
-0.005239 -0.089215 -0.046851 0.018966 -0.029878
--0.019543 0.106899 0.047058 -0.097279 -0.091117
--0.029152 0.017775 0.066229 0.079262 -0.009853
-0.015344 0.002972 0.005261 -0.068619 0.065134
-0.021325 0.052198 -0.040335 -0.031105 -0.022038
-0.046868 -0.008746 0.024060 -0.039353 -0.043527
--0.053729 0.048245 0.078712 0.063353 0.054853
-0.000893 -0.011563 0.116159 -0.043972 0.030272
-0.054786 -0.024768 -0.040403 0.056841 0.146419
--0.034807 0.057094 -0.054852 0.104343 -0.076770
-0.050072 0.052860 0.019579 -0.001424 0.015739
-0.065242 -0.006303 -0.020658 -0.036628 -0.138792
-0.038907 0.049015 0.064288 0.105084 -0.009955
--0.013576 0.042749 -0.058027 -0.060563 0.018986
--0.042694 0.055557 0.029964 0.088314 0.017075
--0.098025 -0.059071 -0.029354 0.030490 0.045049
--0.039481 -0.016714 -0.028323 0.051148 -0.033224
--0.012870 -0.002631 0.095782 -0.018745 -0.067411
--0.067803 -0.096432 0.048605 0.001590 -0.007541
-0.020762 0.011888 -0.020905 -0.048766 0.049192
-0.094934 0.090567 -0.064939 0.021130 0.094459
--0.009557 -0.060711 -0.057713 -0.034265 -0.053583
--0.016969 -0.012648 -0.063332 0.105446 0.016028
--0.006489 -0.023448 0.027450 -0.092041 -0.002328
-0.038286 -0.093578 0.014068 0.045683 0.038064
--0.013579 0.012105 0.031264 0.028629 -0.053522
-0.018638 0.010295 -0.019741 0.051773 0.021102
--0.003833 -0.088492 -0.107650 -0.039638 -0.042960
-0.017232 0.033768 0.024773 0.031441 -0.026193
-0.102995 -0.003033 0.013478 -0.022850 -0.045542
--0.043058 0.040213 -0.037024 0.062912 0.127046
-0.001959 -0.029856 0.021744 -0.024546 0.073822
-0.034590 -0.034810 -0.073281 0.037715 -0.086249
--0.031013 0.094574 -0.014633 0.035329 -0.001586
--0.004488 -0.022600 0.105074 0.068271 0.014684
--0.069910 0.035216 -0.046091 -0.056792 0.016636
--0.031304 0.104876 0.015142 -0.014980 -0.018234
-0.076863 -0.070661 -0.018752 0.021078 -0.015693
--0.082177 0.139823 -0.020936 0.000788 -0.047650
-0.086463 0.003184 0.053978 0.016598 0.005082
-0.037579 -0.007222 -0.068342 0.001780 -0.016838
-0.000034 0.019368 -0.028889 -0.073195 -0.167931
--0.002740 -0.051503 0.060666 -0.048875 0.013166
--0.002367 0.018484 -0.088268 0.058154 -0.005778
--0.019212 0.030488 -0.007580 0.042345 -0.062956
-0.013296 0.040910 0.018849 -0.062445 -0.062359
--0.004222 -0.003121 0.026069 0.075825 0.086917
-0.019144 -0.018779 -0.072348 -0.063072 0.046388
-0.009524 -0.032045 0.075619 0.076314 -0.042349
--0.026193 -0.003729 0.066560 -0.103338 -0.004071
--0.000469 -0.090470 0.033564 -0.067881 0.027775
-0.040936 0.054314 -0.123113 -0.001763 0.032899
-0.028282 0.057689 -0.011369 0.021664 -0.023786
--0.104368 -0.070997 0.059588 -0.014596 -0.042435
-0.003429 0.090193 -0.113362 -0.007873 0.011799
-0.036299 -0.059670 0.054351 -0.084675 0.034819
--0.007507 -0.018723 -0.009649 0.092970 0.008836
--0.028752 -0.044170 -0.070934 -0.103397 -0.030638
-0.048533 -0.032645 0.020691 0.053664 0.011144
--0.021593 0.015401 -0.085379 -0.058031 -0.078320
--0.003648 -0.010436 -0.012911 -0.007136 -0.134525
-0.030251 0.042795 0.087389 -0.092708 -0.026287
--0.039855 0.155791 -0.013492 -0.036665 0.072298
--0.133309 -0.003156 0.013287 -0.012142 0.018020
--0.071518 -0.038880 -0.026195 0.009773 -0.006971
-0.044349 0.079337 0.015294 -0.035758 -0.003607
--0.058092 0.001525 0.042209 0.047862 -0.061178
-0.014357 0.093707 0.022406 -0.118850 -0.034213
-0.019269 0.070424 -0.016998 0.021550 -0.094794
-0.004962 -0.108204 0.128671 0.015466 0.031554
--0.080559 0.041092 0.022039 0.001186 -0.022630
--0.043310 0.005192 0.074769 -0.022963 0.039941
-0.055086 -0.081362 -0.064870 0.040274 0.052633
--0.062993 0.085037 -0.010420 -0.016774 -0.052155
-0.002576 0.013639 0.061713 0.041734 -0.008138
-0.080793 0.024851 -0.042037 0.019932 -0.048494
--0.029059 0.146206 0.042139 0.033378 -0.021081
--0.014080 0.001144 -0.016467 -0.076606 -0.056525
-0.005355 0.079452 0.043451 0.085716 0.029884
--0.042582 -0.055446 0.005137 0.000476 0.001691
--0.041210 -0.077759 0.022581 0.046845 -0.028540
--0.120802 -0.013263 0.072039 -0.031588 -0.006830
--0.040167 -0.125914 0.088795 0.022744 0.055951
-0.003326 0.027383 -0.028722 -0.123214 0.059791
-0.097070 0.030682 -0.019252 0.000330 0.082240
-0.006364 -0.113196 0.035671 -0.063923 -0.075420
-0.017812 -0.046079 -0.059540 0.093696 0.056472
--0.031904 -0.065015 -0.019089 -0.091007 0.031632
-0.018500 -0.054687 0.032704 0.040721 0.012163
--0.041854 -0.010613 -0.017039 -0.028850 -0.061295
-0.029279 0.000022 -0.023031 0.084704 0.032995
-0.000464 -0.042280 -0.122277 -0.133466 0.058700
-0.095073 0.044206 0.068361 0.039925 -0.039455
-0.043618 -0.033785 0.035086 -0.056425 0.019711
-0.049265 0.053168 0.030600 -0.096642 0.090726
--0.078183 -0.002747 0.032400 -0.043278 0.040809
--0.019946 -0.088229 0.027009 0.056114 -0.113044
--0.020901 0.076359 0.059245 0.016714 0.040966
--0.010584 -0.003554 0.056159 0.010151 0.000010
--0.027039 0.073329 -0.015462 -0.016179 0.013943
-0.075066 0.067462 -0.030769 -0.024755 -0.022212
-0.040264 -0.071337 0.009512 -0.045952 0.023049
--0.094656 0.057345 -0.124101 -0.007720 0.037588
-0.036110 -0.011456 0.089645 -0.007765 0.014716
-0.059788 -0.047648 -0.019740 -0.007164 -0.013816
--0.060158 0.013439 0.002759 -0.025340 -0.091571
-0.043341 -0.028869 0.026551 -0.031854 0.060505
--0.049549 0.033978 -0.109503 0.068308 -0.028080
-0.053928 -0.022460 -0.086171 0.086833 -0.045654
-0.000759 -0.010999 0.026013 -0.046809 -0.054160
--0.030739 -0.041475 -0.010348 0.057903 0.106187
--0.031967 -0.136159 -0.056033 0.020976 0.056817
--0.030310 0.060592 0.045537 0.086963 -0.032719
-0.018689 0.033949 0.017964 -0.019455 0.008378
-0.014325 -0.124934 -0.010142 0.033116 0.066121
--0.008592 0.059328 -0.090438 -0.060148 0.065598
--0.010732 0.014210 -0.046081 0.019411 0.040325
--0.012140 -0.084611 0.064608 -0.023209 -0.018978
-0.028244 -0.000390 -0.070852 0.136445 0.055833
-0.034530 -0.106636 -0.049748 -0.043837 0.056670
--0.020391 -0.027277 -0.125403 0.082621 -0.064172
--0.085208 -0.034925 0.000691 -0.016798 0.037357
-0.058365 -0.014015 0.051315 0.078205 0.001672
-0.009538 0.041777 0.001519 -0.031501 -0.027967
-0.008286 -0.051667 0.045953 0.057151 -0.083565
-0.099401 0.052489 0.027972 -0.093449 0.022696
-0.014953 0.056948 0.062741 0.024005 0.076825
--0.029857 -0.002820 0.046866 -0.002247 0.022284
--0.005875 -0.120877 -0.029880 0.030478 -0.074641
-0.026517 0.141968 0.041939 -0.017604 -0.063098
--0.042315 0.108332 0.077079 0.042498 -0.093786
--0.000624 0.109876 0.061671 -0.037131 0.145507
--0.015339 0.059306 -0.094584 0.004561 -0.031261
-0.003112 -0.004144 0.054816 -0.035342 -0.020048
--0.055998 -0.008131 0.096183 0.002903 0.002243
--0.024465 -0.011484 0.122067 -0.117424 0.061629
-0.100785 -0.008995 -0.021311 -0.034915 0.028992
--0.065386 0.062233 0.009424 0.013652 -0.066035
-0.068604 0.015424 -0.016048 -0.028882 -0.021780
-0.034733 -0.052918 -0.046384 0.003918 -0.037747
-0.012883 0.061961 0.011614 0.047979 -0.020950
-0.012662 -0.003597 -0.016134 -0.114584 -0.032846
--0.025773 0.029225 0.029423 0.035929 0.050919
--0.093288 0.024548 0.026469 0.086567 0.069788
--0.015915 0.014888 -0.054796 0.032121 0.010392
-0.010094 0.027316 0.105326 -0.033913 -0.034646
--0.047655 -0.119467 0.014906 0.070898 -0.051722
-0.085920 0.026450 -0.048565 -0.048393 0.040708
-0.013886 0.115144 0.000426 0.025815 0.028617
--0.076183 -0.060818 0.007730 -0.030613 -0.106233
-0.008414 0.008274 -0.071702 0.123060 -0.014131
--0.075611 -0.006558 -0.031029 -0.038394 0.018650
--0.068219 -0.088628 0.017122 0.073322 0.003094
-0.023978 -0.022533 0.052647 0.005485 -0.022853
-0.047387 0.058945 -0.012186 0.049493 0.117395
--0.008681 -0.136174 -0.057438 -0.017543 -0.020215
-0.064213 -0.018764 0.030830 0.026967 -0.104162
-0.097321 0.026515 -0.008192 -0.071056 -0.023457
-0.037214 -0.028805 0.019265 0.010163 0.118572
--0.083174 -0.026261 -0.079021 -0.109716 0.081199
--0.001821 -0.039505 -0.064758 0.022196 -0.008395
--0.056773 0.070319 0.039957 -0.024091 -0.012671
-0.043873 0.034859 0.113349 0.002335 -0.016767
--0.117575 0.038224 -0.016650 -0.007249 -0.028289
--0.020867 0.099598 -0.027205 -0.047643 -0.022079
-0.062869 -0.095742 0.004349 -0.009783 -0.009631
--0.114174 0.101698 -0.020882 0.032183 0.046772
-0.066030 0.023138 0.031676 0.048789 0.064708
-0.016049 -0.022143 -0.026033 0.014811 0.017879
-0.005234 -0.011470 -0.061933 0.012402 -0.073904
--0.008574 0.011810 0.022041 -0.034666 0.015863
-0.032824 0.011302 -0.083572 0.034152 -0.049572
-0.046696 -0.004826 -0.026282 0.006930 -0.036282
-0.018845 0.023008 -0.022702 0.002839 -0.056809
-0.046756 -0.012044 0.093032 0.037759 0.053581
--0.068607 -0.014841 -0.102444 -0.056353 0.054083
-0.022493 -0.027398 0.044342 0.073545 -0.016381
--0.030891 0.080430 0.020741 -0.064660 -0.030998
--0.064001 -0.094590 -0.012708 0.031636 0.033664
-0.017650 -0.020332 -0.049802 0.010802 0.048687
--0.014333 0.032177 -0.003331 0.031214 -0.009314
--0.043033 -0.047137 0.054111 -0.030505 -0.006532
-0.021755 0.050908 -0.056081 0.074478 0.019301
-0.003105 -0.097554 0.054912 -0.016068 0.031570
-0.019298 -0.067236 -0.010230 0.065782 -0.048545
--0.032341 -0.039446 -0.004134 -0.054109 -0.014461
-0.064470 -0.004466 0.064183 -0.013807 -0.040371
-0.012385 -0.043869 -0.179654 -0.075267 -0.058833
-0.027833 -0.078315 0.006233 0.019417 -0.100407
-0.057753 0.000717 0.032416 -0.121474 -0.047213
--0.015720 0.092246 -0.059387 0.040603 0.109440
--0.058153 0.071202 0.030939 0.049569 0.087021
--0.076095 -0.131564 -0.027353 -0.000486 -0.015803
-0.104552 0.088105 0.072307 -0.020686 0.043142
--0.089957 0.000627 0.140513 0.006435 -0.023427
--0.000585 0.090754 0.029188 -0.057282 0.010274
-0.075187 0.111159 -0.057877 0.069809 -0.050756
-0.062932 -0.036407 0.050992 0.009269 -0.006383
--0.106503 0.017063 0.008141 0.064195 -0.045832
-0.011576 -0.041847 0.061264 -0.005204 0.058984
-0.021548 -0.048377 -0.044097 0.010789 0.013451
--0.063551 0.063079 -0.080144 -0.027762 -0.017784
--0.023803 0.027775 0.060824 0.001841 -0.009369
-0.061007 0.032254 -0.064190 -0.006988 -0.010230
--0.038793 0.076776 0.045814 0.049754 0.027771
--0.047904 0.017897 -0.052309 -0.106778 -0.037221
-0.011510 0.060085 -0.009615 0.096725 0.047490
--0.010900 -0.074275 -0.061489 0.016070 0.006262
--0.121827 0.005654 -0.050379 0.042456 -0.027064
--0.068110 0.106922 0.068599 -0.034845 -0.067145
--0.036874 -0.041315 0.035902 0.059175 0.013939
-0.008294 -0.000352 -0.046255 -0.058090 0.089826
-0.091060 0.092701 0.009236 0.013325 -0.019194
-0.039376 -0.018583 -0.016868 -0.096550 -0.086377
--0.016296 0.002608 -0.083265 0.049964 0.042836
--0.011462 -0.046261 0.084247 -0.180528 0.034023
-0.041962 -0.128842 -0.057438 0.031753 -0.013294
--0.008752 -0.054893 -0.036386 -0.004605 -0.020903
-0.113550 0.017158 -0.063971 0.047456 0.033803
-0.026820 -0.033048 -0.057221 -0.039801 -0.029135
-0.004112 0.055166 0.080631 0.011347 -0.039214
-0.069633 -0.057947 0.018314 -0.110810 -0.006258
-0.011057 -0.058755 -0.016184 -0.078348 0.154720
--0.056156 -0.110551 0.114867 -0.031689 0.014677
-0.024109 -0.060048 0.019844 0.109975 -0.045339
-0.002565 0.067118 0.019907 0.004995 0.078815
--0.017892 0.015592 0.118138 0.009682 -0.024624
--0.025684 0.027247 -0.044912 -0.011851 0.057506
-0.106751 0.066538 -0.073230 -0.069470 -0.044869
--0.007738 -0.078232 0.000098 -0.056553 -0.000261
--0.069574 0.025403 -0.032460 0.042204 -0.009414
-0.024336 0.002379 0.084422 -0.062254 0.070007
-0.083297 0.011215 -0.087554 0.008854 -0.031248
--0.019485 0.015117 0.019539 -0.018885 -0.091190
-0.006668 -0.029364 0.010585 0.004194 0.053285
--0.032862 0.007750 -0.181078 0.014752 -0.032591
-0.035286 0.052475 -0.044255 0.152326 -0.034986
-0.001871 -0.048154 0.032533 -0.150372 -0.061009
-0.025623 -0.057468 0.099245 0.098809 0.047259
--0.017644 -0.089718 -0.052981 0.060000 0.050683
--0.093984 -0.012007 0.021790 0.115572 0.011056
--0.005239 0.022166 0.036556 -0.019139 -0.017723
-0.036182 -0.053160 0.008506 0.003654 0.035883
--0.011143 0.126442 -0.042372 -0.049170 0.021566
--0.034390 0.004133 -0.083543 0.003794 0.003199
-0.023898 -0.058139 0.097937 -0.021906 -0.118046
--0.009779 0.053140 -0.086424 0.032891 0.040964
-0.003078 -0.054441 -0.008601 -0.059920 0.074604
-0.120587 -0.102501 -0.066840 0.070391 0.032323
--0.084081 -0.025867 0.003136 -0.037883 -0.064963
-0.077565 -0.011987 -0.030929 0.076324 -0.096244
--0.003417 0.038221 -0.027320 -0.034091 0.001490
--0.007638 -0.034015 0.052893 0.055546 -0.147361
-0.042258 -0.020035 -0.017400 -0.076711 -0.017528
-0.045540 0.051725 -0.024199 -0.035180 0.069090
--0.066211 0.016712 0.012236 -0.023556 -0.008512
--0.043404 -0.040132 0.006223 0.020953 -0.040829
--0.031888 0.063196 0.044618 -0.021241 -0.065557
-0.013691 0.016905 0.113755 0.054933 -0.021644
-0.016741 0.030625 0.010121 -0.037365 0.072566
-0.006060 0.080380 -0.086262 -0.033079 -0.082250
-0.087161 -0.049737 0.100611 -0.073241 -0.060578
--0.018873 0.076177 0.146262 0.031684 -0.014816
--0.074152 0.012492 0.111905 -0.037241 0.036831
-0.091650 -0.058779 -0.035497 0.009717 0.105238
--0.068452 0.050555 -0.035241 0.038942 -0.086304
-0.055772 0.028480 0.055647 -0.013345 0.009719
-0.060855 -0.009449 -0.029466 -0.039618 -0.045775
-0.012008 0.093753 0.059452 0.084398 -0.063094
-0.003659 0.074625 -0.110159 -0.075540 -0.006386
-0.010137 0.032774 0.014827 0.166347 0.079179
--0.032299 -0.047524 -0.033098 0.052546 0.023211
--0.005083 -0.040770 0.010451 0.047465 -0.015315
--0.001296 0.006073 0.070897 -0.060137 -0.051576
--0.032384 -0.082914 0.047391 0.018599 -0.072054
-0.020109 0.006570 -0.072222 -0.028125 0.023991
-0.073458 0.052141 -0.039550 0.020745 -0.004247
--0.027316 -0.026412 -0.050898 -0.048547 -0.135601
--0.022268 0.038434 -0.006989 0.106829 0.013384
-0.000746 0.016253 -0.014804 -0.086222 0.017979
-0.043413 -0.078404 0.050130 0.105998 0.009523
--0.080688 -0.029072 0.043530 0.018815 -0.027097
-0.017270 0.008265 0.029905 0.025756 0.068311
-0.010413 -0.062141 -0.092435 -0.009085 -0.011445
-0.024539 0.076003 0.038136 -0.010407 -0.045941
-0.082228 -0.001579 -0.035917 0.064558 -0.023500
--0.063481 0.003930 -0.067573 0.030233 0.098224
--0.042799 0.003064 0.009816 -0.008225 0.109707
--0.034960 -0.080238 -0.123786 0.048109 -0.059473
--0.055367 0.057060 -0.001238 0.030381 0.025074
-0.006831 0.017900 0.111674 0.097968 0.015896
--0.050238 0.041727 -0.107658 -0.072374 -0.018776
-0.001860 0.159151 -0.015443 -0.046034 -0.062151
-0.065586 -0.066719 0.031320 0.059675 -0.022808
--0.066461 0.086303 -0.026658 0.070774 0.006480
-0.159805 -0.035879 0.058009 0.012928 -0.008505
-0.051041 -0.000692 -0.022889 0.039547 0.001201
--0.030295 0.029145 -0.073169 -0.019964 -0.102560
--0.021646 -0.009084 0.039313 -0.008758 0.059413
-0.019112 0.068432 -0.154269 0.042342 -0.017110
-0.003279 0.087898 0.002044 0.110066 -0.076844
-0.041884 0.035740 -0.001247 -0.094360 -0.090406
-0.040890 -0.028718 0.013704 0.031084 0.040651
--0.028325 -0.027470 -0.060171 -0.069388 0.051373
--0.010018 0.016317 0.030962 0.131065 -0.012443
--0.085994 0.023695 0.036048 -0.123378 0.017394
--0.014188 -0.147008 0.010122 -0.048605 0.011567
-0.011549 0.033481 -0.087698 -0.007977 0.012262
-0.046426 0.046093 -0.000803 0.034084 0.024231
--0.011190 -0.037156 0.022545 0.009116 -0.021868
-0.000176 0.161431 -0.066441 -0.004212 0.008997
--0.027580 -0.039554 0.047688 -0.114080 0.037481
-0.021017 -0.015449 0.023651 0.076890 -0.062376
--0.089367 -0.035901 -0.117304 -0.014988 -0.004232
-0.065798 -0.038753 0.006615 0.027216 0.000892
--0.043842 -0.027915 -0.077769 -0.025289 0.007296
-0.021684 -0.008098 0.034493 0.002195 -0.089680
-0.015447 0.014866 0.063536 -0.107947 0.040356
--0.049353 0.085041 -0.019010 0.017126 0.054466
--0.095573 0.040640 0.005208 0.001846 0.046985
--0.060406 -0.059147 -0.078410 0.032047 -0.027762
-0.023664 0.067476 0.025927 0.004505 -0.005180
--0.107366 -0.052865 0.059971 0.018624 -0.086019
--0.038792 0.082042 -0.009606 -0.082518 0.048899
--0.032272 0.118434 -0.029891 0.014012 -0.078772
-0.071631 -0.124648 0.096824 0.071580 -0.014951
--0.078224 0.028148 0.050459 0.044666 -0.016543
--0.039821 -0.016072 0.087706 -0.056648 0.087416
-0.030016 -0.076113 -0.101181 -0.049336 0.048944
--0.063956 0.087916 -0.036885 -0.059650 -0.044808
-0.054549 0.006956 0.033701 0.030349 -0.017304
-0.057616 0.016137 -0.052723 0.039906 -0.101393
--0.068763 0.099576 0.006264 0.083677 -0.032515
--0.006446 0.031066 0.009386 -0.132131 -0.067080
-0.049843 0.065652 0.020336 0.046760 0.071347
--0.013796 -0.001044 -0.022677 0.019523 0.014154
--0.120083 -0.039608 0.050937 0.066017 -0.034193
--0.069836 0.025969 0.058877 -0.033911 -0.021741
-0.005164 -0.037563 0.051151 0.030827 0.041654
--0.050675 0.032902 -0.056904 -0.083309 0.051372
-0.092971 0.070309 0.017775 -0.033610 0.023024
-0.044912 -0.113795 0.009331 -0.100912 -0.024567
-0.000589 -0.023568 -0.041534 0.046948 0.019053
--0.031982 -0.010104 -0.033008 -0.120085 0.014601
--0.013314 -0.032777 0.022640 0.053925 0.056793
--0.009301 0.011372 0.004027 -0.017398 -0.055177
-0.038121 -0.000187 0.037310 0.135976 0.012337
-0.060620 -0.032842 -0.103898 -0.068672 0.001160
-0.043004 -0.011293 0.085530 0.053401 -0.086065
-0.123377 0.016620 0.045728 -0.034590 -0.014069
-0.081166 0.009573 0.008541 0.007549 0.143099
--0.050664 -0.045174 0.012225 -0.052408 0.008760
--0.016453 -0.030851 -0.052611 0.054134 -0.086747
--0.068170 0.152077 0.049576 0.035454 0.051824
-0.042151 -0.013574 0.070619 0.043677 -0.011524
--0.051292 0.065538 -0.002312 -0.036357 0.061560
-0.011089 0.083280 -0.022801 -0.035830 0.007115
-0.022494 -0.033816 -0.026885 -0.055802 0.037931
--0.067432 0.034696 -0.048668 0.025237 0.063419
-0.052414 0.002888 0.073912 -0.070773 0.030231
-0.098077 -0.052981 -0.038547 -0.044533 0.015899
--0.006684 0.059142 0.015994 -0.010569 -0.114343
-0.049113 0.011781 0.007813 -0.023202 0.027226
--0.048228 0.023363 -0.119744 -0.005880 -0.047102
-0.056647 0.043309 -0.020351 0.078326 -0.050033
-0.004297 -0.004014 -0.008930 -0.041817 -0.061743
--0.031268 0.020567 0.053127 0.035109 0.095886
--0.022695 -0.103689 -0.101536 -0.035350 0.033822
--0.071528 -0.027884 -0.013301 0.135256 -0.057997
--0.006784 0.025162 0.014105 -0.008340 0.036569
--0.047669 -0.071591 0.074153 -0.001441 0.118717
--0.038919 0.054650 -0.101206 -0.019929 0.096971
-0.019005 0.066319 -0.033069 -0.010263 0.057814
--0.038319 -0.115955 0.048866 -0.085605 -0.005601
-0.066517 -0.010474 -0.068925 0.056969 0.055565
-0.068964 -0.047482 -0.006419 -0.087153 0.047383
-0.032670 -0.032209 -0.036239 0.140438 -0.038488
--0.103112 -0.063917 0.016553 0.017109 -0.018945
-0.071205 -0.057507 0.036017 0.043139 0.045741
-0.011471 0.019692 -0.031466 -0.001430 -0.027755
--0.010061 -0.028245 0.031925 0.070075 -0.044640
-0.079725 -0.005444 -0.055716 -0.081872 0.035299
--0.020415 0.060898 0.037726 -0.007902 0.118692
--0.091406 -0.074996 0.014883 -0.011479 0.096472
--0.004637 -0.120365 0.011661 -0.019123 -0.055083
--0.021707 0.080305 0.062197 -0.007888 -0.014681
--0.064206 0.034037 0.066576 0.037499 -0.089224
--0.027816 0.038300 -0.009289 -0.093182 0.126160
-0.000015 0.066641 -0.028392 0.023167 -0.021511
-0.010571 -0.044084 0.057444 0.012462 0.005604
--0.062572 0.054520 0.053554 0.005974 0.010050
--0.037332 0.047516 0.066630 -0.035787 0.074909
-0.066925 -0.030867 -0.053629 0.022622 0.033939
--0.033606 0.038370 0.006718 0.000847 -0.048333
-0.027340 -0.025685 0.007564 -0.047322 -0.016881
-0.054471 -0.017126 -0.063705 0.008150 -0.059374
-0.010814 0.037617 0.025879 0.059782 -0.064248
-0.042565 0.025815 -0.028591 -0.064574 -0.034454
--0.031756 0.000598 0.011630 0.073568 0.026113
--0.014567 0.003799 -0.014072 0.027953 0.071711
--0.011735 0.014001 -0.022183 0.070160 -0.007010
--0.049052 0.104807 0.111959 -0.037082 -0.007329
--0.011153 -0.073166 0.045311 0.040814 -0.001227
-0.040666 0.038813 -0.049173 -0.078035 0.061429
-0.063840 0.120475 0.035684 0.029819 0.046868
--0.017290 -0.035945 0.064987 -0.053189 -0.049460
--0.030434 0.069244 -0.015774 0.136658 -0.012690
-0.005401 -0.045873 0.006291 -0.075787 0.046146
--0.001969 -0.104323 -0.047978 0.150326 0.032908
--0.004080 -0.012965 -0.015875 0.014424 -0.040690
-0.098688 0.025183 -0.017974 0.072128 0.070408
--0.030717 -0.065297 -0.073385 -0.051253 -0.014989
-0.058581 0.033837 0.014225 0.031069 -0.081646
-0.089555 -0.017678 -0.068486 -0.040654 -0.051917
-0.047272 -0.042437 -0.042350 0.019696 0.085122
--0.053413 -0.122905 -0.021426 -0.039696 0.051817
-0.020410 -0.050261 -0.093654 -0.001174 -0.043672
--0.102482 0.084668 0.098393 -0.052216 0.050107
--0.005196 0.034413 0.122643 -0.031565 0.066945
--0.079300 0.072369 -0.011993 -0.035713 0.023269
--0.002546 0.076113 -0.067724 -0.084767 -0.053840
-0.037939 -0.091041 -0.026871 -0.009130 -0.021081
--0.067836 0.022012 -0.052138 0.083855 0.065835
-0.061174 -0.015388 0.100602 -0.009214 0.131331
-0.048374 -0.020733 -0.009385 -0.013658 0.012043
--0.057898 -0.017737 -0.088355 0.024991 -0.079612
-0.000356 0.019063 0.032476 0.022195 0.010063
--0.017095 0.024040 -0.080464 0.063948 -0.114944
-0.012612 0.022171 -0.005737 0.035304 -0.061207
-0.055311 0.033024 0.010681 -0.035592 -0.053947
--0.011004 -0.012254 0.055221 0.045545 0.049084
-0.005046 -0.005400 -0.115901 -0.044796 0.068701
--0.005781 -0.031080 0.037791 0.097212 0.026378
--0.032777 0.026666 0.006559 -0.032347 -0.025736
--0.039802 -0.165807 0.007831 0.003219 0.090520
-0.051658 -0.027677 -0.121531 0.016080 0.074249
--0.017031 0.055987 0.005024 0.056572 0.006367
--0.029525 -0.005725 0.069335 -0.024541 -0.003936
--0.050003 0.053274 -0.052184 0.045028 0.014532
-0.039597 -0.056809 0.094737 -0.048726 0.081476
-0.030138 -0.008376 0.001189 0.059831 -0.018934
--0.069575 0.002414 -0.006677 -0.061422 -0.024261
-0.061177 -0.023449 -0.000323 -0.012054 -0.074484
-0.038383 0.021929 -0.101717 -0.022789 -0.036563
-0.013636 -0.063362 0.053011 0.004735 -0.077306
-0.008396 0.043986 0.028657 -0.067441 -0.008945
--0.037043 0.071514 -0.037839 0.077754 0.066277
--0.065319 -0.001333 0.067596 -0.021862 0.099395
--0.063958 -0.082056 -0.044809 0.063666 0.000060
-0.046881 0.121405 0.030877 -0.008566 0.007738
--0.043809 -0.049349 0.046172 0.040387 -0.045205
-0.007940 0.060687 -0.036544 -0.076121 0.042696
--0.003337 0.102081 -0.040222 0.067540 -0.025542
-0.030041 -0.090029 0.041031 0.020329 -0.012727
--0.089279 0.046642 0.018999 0.055650 0.032822
--0.052350 -0.055869 0.123885 -0.019014 0.088042
-0.001830 -0.080700 -0.023798 -0.021378 0.007657
--0.042996 0.023456 -0.055210 -0.018485 -0.033292
--0.016446 0.052880 0.043571 0.032302 -0.006553
-0.054726 0.057637 -0.079728 0.030525 -0.045654
--0.016583 0.136252 -0.001399 0.088342 0.059925
--0.018644 0.033899 -0.026838 -0.060676 -0.084264
--0.007612 0.086537 -0.000185 0.091345 0.006932
--0.012308 -0.029627 -0.057073 -0.008780 0.039234
--0.044963 -0.042058 -0.067929 0.074154 -0.051802
--0.061304 0.020025 0.026829 -0.086288 -0.076261
--0.069406 -0.050920 0.124796 0.022026 0.010977
-0.038169 -0.027398 -0.073580 -0.056630 0.093880
-0.081911 0.024440 0.008606 0.033419 -0.000580
-0.033675 -0.032327 -0.007767 -0.065309 -0.050057
--0.050072 -0.014708 -0.100502 0.074529 0.005808
-0.016991 -0.022397 -0.012659 -0.102715 0.069860
-0.007505 -0.098626 0.017930 0.000660 0.030909
--0.019108 -0.001078 -0.038606 -0.007684 -0.046485
-0.070639 0.016330 -0.034902 0.085208 0.016702
-0.031560 -0.039036 -0.086796 -0.116810 -0.043757
-0.027858 0.024031 0.045674 -0.036231 -0.081680
-0.085800 -0.045662 -0.023544 -0.087212 -0.075608
--0.015723 -0.040238 0.013265 -0.085104 0.106223
--0.082075 -0.107869 0.056348 -0.031110 0.053637
-0.000135 -0.037700 -0.055809 0.094526 -0.021978
-0.034525 0.054227 0.053019 0.003097 0.040872
--0.039125 -0.085945 0.154564 0.038990 -0.027547
-0.001012 0.012970 -0.012585 -0.008224 0.076006
-0.057344 0.055498 -0.015305 -0.064045 -0.009027
-0.028053 -0.055613 0.019793 0.005156 -0.005730
--0.081848 0.009551 -0.035835 -0.005885 -0.006310
-0.056241 0.074335 0.101385 -0.045124 0.075779
-0.098255 -0.025349 -0.135871 0.068593 0.018442
-0.008761 -0.006857 0.032026 -0.041062 -0.176540
--0.003354 -0.030120 -0.024455 -0.009820 0.053273
--0.013461 -0.013288 -0.112246 0.007427 0.011505
-0.000211 -0.007304 -0.033855 0.097950 -0.118398
-0.030054 0.000253 0.110782 -0.135596 -0.057368
--0.016542 -0.002743 0.078980 0.080403 0.081391
--0.047818 -0.058659 -0.050242 0.012663 0.083037
--0.061626 0.019808 -0.007693 0.160145 0.019543
-0.010731 0.046526 0.068954 -0.024462 -0.015987
-0.057362 -0.091820 0.016953 0.016968 0.076250
-0.018441 0.111365 -0.067091 -0.018485 0.053164
-0.005666 0.035169 -0.035022 -0.006122 -0.002602
--0.047379 -0.023841 0.119826 -0.069174 -0.036278
-0.066394 0.057299 -0.074109 0.057609 0.038296
-0.057444 -0.029816 0.022335 -0.034234 0.104815
-0.048829 -0.043111 -0.072490 0.067468 0.004571
--0.110285 -0.021601 -0.020759 -0.012685 -0.017656
-0.126982 0.016916 -0.004567 0.107105 -0.027552
-0.007144 -0.013052 -0.020950 -0.061707 -0.025117
--0.020557 -0.015960 0.045201 0.121070 -0.089963
-0.035852 0.025505 -0.020181 -0.106140 0.001278
--0.003190 0.085573 -0.040587 -0.057134 0.092945
--0.049909 0.014414 0.010498 -0.020042 0.053348
--0.005743 -0.065367 -0.017619 0.024990 -0.016761
--0.001102 0.081298 0.066867 -0.051868 -0.045101
--0.008798 0.003830 0.082195 0.041312 -0.048878
-0.029855 0.023388 0.029924 -0.050988 0.039197
--0.009097 0.043885 -0.079323 -0.043981 -0.028178
-0.066419 0.012794 0.059244 -0.059898 -0.071819
--0.106012 0.055735 0.110205 0.053225 -0.000572
--0.024268 -0.039276 0.113882 -0.011410 0.026499
-0.086180 -0.011966 0.013046 0.031127 0.066167
--0.027553 0.060671 -0.045735 0.060949 -0.051384
-0.048136 0.029615 0.023552 0.009801 0.050664
-0.065347 -0.026945 -0.067001 -0.022261 -0.108076
-0.060158 0.041960 0.067335 0.052471 -0.029246
-0.005009 0.007741 -0.052254 -0.083086 -0.017223
--0.052633 0.052579 0.067865 0.153710 0.017808
--0.087647 -0.021298 -0.079632 0.070262 0.044472
--0.050379 -0.010528 -0.002296 0.013103 -0.019826
--0.007796 0.016897 0.056191 0.006326 -0.079428
--0.036621 -0.124708 0.063044 -0.022890 -0.045545
-0.041047 0.025474 -0.028608 0.002726 0.048077
-0.099637 0.066892 -0.070620 0.001304 0.013309
--0.014646 -0.054310 -0.000625 -0.041803 -0.102217
--0.045571 -0.015019 -0.026224 0.105191 0.032885
--0.000149 -0.033313 0.006390 -0.078169 -0.030753
-0.041211 -0.066981 0.004327 0.092330 0.071230
--0.029542 0.036311 0.054269 0.022893 -0.046259
--0.001621 -0.003966 0.005826 0.056342 0.042238
--0.028467 -0.044194 -0.112504 -0.019352 -0.056343
-0.025104 0.017498 0.028931 0.016630 -0.061128
-0.115505 0.002142 0.019876 0.014986 -0.066700
-0.002735 0.027334 -0.033263 0.031449 0.112566
--0.025718 -0.017066 -0.019976 -0.036001 0.083541
-0.048068 -0.073969 -0.035121 0.039966 -0.077883
--0.015535 0.089870 0.023998 0.011277 0.010489
-0.033555 -0.012483 0.127157 0.027709 0.014969
--0.033730 0.006080 -0.048319 -0.052745 0.027066
--0.021685 0.115020 0.006318 -0.021548 0.021575
-0.090884 -0.054542 -0.015574 0.030923 -0.068692
--0.095404 0.092367 -0.049371 -0.007959 0.012304
-0.123951 0.014405 0.082998 -0.023011 0.029154
-0.017924 -0.006151 -0.084050 0.033509 -0.002582
-0.024225 0.045534 -0.034178 -0.026409 -0.121581
-0.007469 -0.024266 0.049937 -0.020242 0.021756
--0.020005 0.017806 -0.083185 0.089127 -0.055074
--0.034134 0.018495 -0.014900 0.084470 -0.088049
-0.012587 0.053323 -0.003416 -0.081639 -0.022685
-0.028673 -0.041773 0.034449 0.070890 0.057659
-0.017152 -0.036172 -0.093521 -0.025296 0.035162
-0.029819 -0.039228 0.085181 0.163548 -0.001854
--0.029758 0.022943 0.021209 -0.070771 0.014429
--0.013368 -0.088799 -0.009255 -0.052504 0.041099
-0.025723 0.001161 -0.107366 -0.001012 0.033565
-0.044131 0.035694 -0.021740 0.002649 0.007424
--0.085656 -0.093763 -0.001170 -0.025695 -0.037360
--0.044626 0.064499 -0.071805 -0.003962 0.048891
-0.024092 -0.027384 0.095833 -0.090763 0.002000
-0.023459 0.019764 -0.029245 0.119488 0.005968
--0.096712 -0.071733 -0.047297 -0.074321 -0.062880
-0.035501 -0.027280 0.037144 0.008541 0.020241
-0.018467 -0.015675 -0.095340 -0.027954 -0.069184
--0.012559 -0.010226 -0.008974 0.014176 -0.089107
-0.055689 0.060512 0.073656 -0.081115 0.028454
--0.087380 0.077056 -0.016938 -0.014435 0.091481
--0.117469 0.042015 0.041204 -0.038524 0.004206
--0.062655 -0.068726 -0.052024 -0.002012 -0.016652
-0.058910 0.036081 0.033210 -0.054379 0.003673
--0.091615 -0.001601 0.019547 0.062960 -0.110025
--0.019088 0.071235 -0.039133 -0.103127 0.005287
-0.019768 0.106127 -0.017072 -0.008543 -0.093660
-0.044248 -0.053844 0.097968 0.000346 0.012930
--0.032294 0.027944 0.021196 0.006513 -0.001250
--0.020211 0.039251 0.067859 0.020349 0.058248
-0.024609 -0.074146 -0.100418 0.030150 0.026229
--0.039773 0.099169 0.008735 -0.011164 -0.109708
-0.001230 0.003111 0.054746 0.076006 0.018527
-0.098756 0.017060 -0.025289 -0.006160 -0.078352
-0.002616 0.144579 -0.020766 0.062239 -0.016518
--0.035809 -0.021765 -0.035105 -0.144630 -0.095066
-0.010952 0.046460 0.068649 0.085352 0.087482
--0.033104 -0.048980 -0.018280 -0.014775 0.025770
--0.111625 -0.092460 0.005859 0.075107 -0.062936
--0.085897 0.005900 0.055026 -0.087076 -0.027440
--0.033017 -0.063979 0.066972 0.028398 0.010265
--0.030890 -0.001574 -0.045533 -0.106812 0.113658
-0.104903 0.004971 0.028534 -0.023905 0.074634
--0.025588 -0.100482 -0.029403 -0.070372 -0.062718
--0.020418 -0.021403 -0.043078 0.080410 0.075037
--0.035154 -0.074551 -0.013207 -0.145218 -0.000997
--0.014570 -0.065138 0.008479 0.044833 0.024817
--0.038683 0.006048 0.032395 -0.031666 -0.059782
-0.070540 0.001925 0.005314 0.060966 0.028570
-0.041891 -0.035393 -0.044033 -0.087988 0.022861
-0.054156 0.027545 0.100860 -0.032365 -0.073861
-0.047055 -0.005439 0.042181 -0.028039 0.007216
-0.034289 -0.013035 0.012785 -0.068215 0.102120
--0.090059 -0.035706 0.026737 -0.089429 0.038438
--0.040128 -0.077000 -0.054932 0.048963 -0.127689
--0.020587 0.094010 0.104367 -0.014378 0.068899
-0.007536 -0.012966 0.078066 0.039371 0.013971
--0.019439 0.083877 -0.042991 -0.046952 0.039415
-0.055981 0.076150 -0.000417 -0.001657 -0.048929
-0.046983 -0.072438 -0.012301 -0.047275 -0.023350
--0.059164 -0.003587 -0.100107 0.007189 0.060971
-0.042822 -0.008493 0.134842 -0.044502 -0.010541
-0.089334 -0.016620 -0.048559 -0.027560 -0.005511
--0.032724 0.034262 -0.042951 0.017548 -0.145421
-0.056398 -0.006331 0.030847 0.001640 0.057797
--0.063806 -0.000882 -0.091910 0.016087 -0.019546
-0.061433 0.036856 -0.056495 0.069485 -0.031554
--0.012055 0.017768 0.015448 -0.074610 -0.037352
--0.004122 -0.064702 0.053976 0.074254 0.134606
--0.001169 -0.110572 -0.031859 0.002913 0.016777
--0.083814 0.052146 0.036174 0.103645 -0.024775
--0.005335 0.048662 0.002436 -0.040366 0.023406
--0.028113 -0.087518 0.030981 0.017198 0.042213
-0.009268 0.022638 -0.091913 -0.007325 0.067826
-0.007175 0.039739 -0.030746 0.019636 0.060134
-0.002597 -0.074017 0.092250 -0.059181 -0.016534
--0.011358 -0.017007 -0.017703 0.102970 0.122663
-0.057377 -0.041987 -0.053837 -0.031373 0.063014
-0.006671 -0.090650 -0.138471 0.106533 0.010497
--0.102967 -0.075716 -0.038511 -0.071066 0.017321
-0.093836 -0.006301 0.118555 0.061346 0.013449
--0.000558 0.009959 -0.026395 -0.028150 -0.032041
-0.044864 -0.060691 0.041780 0.046048 -0.051785
-0.062238 0.004872 0.030879 -0.128966 0.012667
-0.023845 0.078065 0.044196 0.046742 0.148868
--0.030628 -0.042491 0.021535 -0.011918 0.043483
--0.047778 -0.117530 -0.005429 -0.008792 -0.098801
-0.020009 0.106857 0.089897 0.024663 -0.061028
--0.015371 0.069471 0.045508 0.046334 -0.069530
-0.010731 0.072915 0.065071 -0.058529 0.071085
--0.012683 0.094842 -0.090176 0.065021 -0.044033
-0.019140 -0.012000 0.092585 -0.034244 -0.040555
--0.084684 -0.011832 0.061629 0.009146 0.027188
--0.026891 0.080725 0.088536 -0.084517 0.044584
-0.093624 -0.016766 0.021101 -0.002887 0.009587
--0.068241 0.007223 -0.040467 0.035718 -0.043998
-0.050133 0.003764 0.010389 -0.000348 -0.020485
-0.049700 -0.066152 -0.041930 -0.021767 -0.077931
-0.035116 0.108204 0.024456 0.032605 -0.043283
-0.024511 0.009921 -0.031396 -0.173419 -0.049078
--0.014906 0.036522 0.041073 0.061298 0.024532
--0.074779 -0.013084 0.018258 0.041618 0.044657
--0.018537 0.007319 -0.066448 0.027570 -0.032981
--0.024516 0.092119 0.129643 -0.016032 -0.072728
--0.044848 -0.084876 0.072567 0.089222 -0.006042
-0.077927 0.001985 -0.041619 -0.009227 0.069988
-0.088912 0.133137 -0.016458 0.008841 0.031287
--0.047102 -0.083683 0.030843 -0.112282 -0.103671
--0.006459 -0.031852 -0.057190 0.207145 -0.002174
--0.047509 -0.051560 -0.034172 -0.058751 0.014904
--0.055125 -0.123573 -0.025949 0.094512 0.035410
-0.003286 0.008369 0.029091 0.023530 -0.021963
-0.056787 0.037285 -0.041070 0.012945 0.109131
--0.012940 -0.088290 -0.060557 -0.064861 0.027757
-0.012384 0.004678 -0.022211 0.059852 -0.089239
-0.120404 0.036099 -0.023853 -0.025676 0.001845
-0.000298 -0.029950 -0.027028 0.027301 0.128816
--0.046314 -0.030039 0.011273 -0.059749 0.055640
-0.001351 -0.032191 -0.091552 0.054641 0.010980
--0.105128 0.083057 0.017517 0.006971 -0.014256
-0.046500 0.060555 0.099997 0.034081 0.044797
--0.117689 0.049576 -0.059663 -0.109523 0.015561
--0.039089 0.097102 -0.015266 -0.057401 0.015861
-0.029363 -0.123492 0.017355 -0.025359 0.005924
+++ /dev/null
-/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
-
-/*
- * This intermediary file and the files that used to create it are under
- * The LGPL. See the file COPYING.
- */
-
-#include "defines.h"
-
- /* ../src/codebook/lspres_centre1.txt */
-static const float codes0[] = {
- 300,
- 350,
- 400,
- 450,
- 500,
- 550,
- 600,
- 650
-};
- /* ../src/codebook/lspres_bw1.txt */
-static const float codes1[] = {
- 35,
- 80,
- 140,
- 250
-};
- /* ../src/codebook/lsp3.txt */
-static const float codes2[] = {
- 500,
- 550,
- 600,
- 650,
- 700,
- 750,
- 800,
- 850,
- 900,
- 950,
- 1000,
- 1050,
- 1100,
- 1150,
- 1200,
- 1250
-};
- /* ../src/codebook/lsp4.txt */
-static const float codes3[] = {
- 700,
- 800,
- 900,
- 1000,
- 1100,
- 1200,
- 1300,
- 1400,
- 1500,
- 1600,
- 1700,
- 1800,
- 1900,
- 2000,
- 2100,
- 2200
-};
-
-const struct lsp_codebook lsp_cbres[] = {
- /* ../src/codebook/lspres_centre1.txt */
- {
- 1,
- 3,
- 8,
- codes0
- },
- /* ../src/codebook/lspres_bw1.txt */
- {
- 1,
- 2,
- 4,
- codes1
- },
- /* ../src/codebook/lsp3.txt */
- {
- 1,
- 4,
- 16,
- codes2
- },
- /* ../src/codebook/lsp4.txt */
- {
- 1,
- 4,
- 16,
- codes3
- },
- { 0, 0, 0, 0 }
-};
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: codec2.c
- AUTHOR......: David Rowe
- DATE CREATED: 21/8/2010
-
- Codec2 fully quantised encoder and decoder functions. If you want use
- codec2, the codec2_xxx functions are for you.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-
-#include "defines.h"
-#include "sine.h"
-#include "nlp.h"
-#include "dump.h"
-#include "lpc.h"
-#include "quantise.h"
-#include "phase.h"
-#include "interp.h"
-#include "postfilter.h"
-#include "codec2.h"
-#include "lsp.h"
-#include "codec2_internal.h"
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION HEADERS
-
-\*---------------------------------------------------------------------------*/
-
-void analyse_one_frame(struct CODEC2 *c2, MODEL *model, short speech[]);
-void synthesise_one_frame(struct CODEC2 *c2, short speech[], MODEL *model,
- float ak[]);
-void codec2_encode_3200(struct CODEC2 *c2, unsigned char * bits, short speech[]);
-void codec2_decode_3200(struct CODEC2 *c2, short speech[], const unsigned char * bits);
-void codec2_encode_2400(struct CODEC2 *c2, unsigned char * bits, short speech[]);
-void codec2_decode_2400(struct CODEC2 *c2, short speech[], const unsigned char * bits);
-void codec2_encode_1400(struct CODEC2 *c2, unsigned char * bits, short speech[]);
-void codec2_decode_1400(struct CODEC2 *c2, short speech[], const unsigned char * bits);
-void codec2_encode_1200(struct CODEC2 *c2, unsigned char * bits, short speech[]);
-void codec2_decode_1200(struct CODEC2 *c2, short speech[], const unsigned char * bits);
-void ear_protection(float in_out[], int n);
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_create
- AUTHOR......: David Rowe
- DATE CREATED: 21/8/2010
-
- Create and initialise an instance of the codec. Returns a pointer
- to the codec states or NULL on failure. One set of states is
- sufficient for a full duuplex codec (i.e. an encoder and decoder).
- You don't need separate states for encoders and decoders. See
- c2enc.c and c2dec.c for examples.
-
-\*---------------------------------------------------------------------------*/
-
-struct CODEC2 * CODEC2_WIN32SUPPORT codec2_create(int mode)
-{
- struct CODEC2 *c2;
- int i,l;
-
- c2 = (struct CODEC2*)malloc(sizeof(struct CODEC2));
- if (c2 == NULL)
- return NULL;
-
- assert(
- (mode == CODEC2_MODE_3200) ||
- (mode == CODEC2_MODE_2400) ||
- (mode == CODEC2_MODE_1400) ||
- (mode == CODEC2_MODE_1200)
- );
- c2->mode = mode;
- for(i=0; i<M; i++)
- c2->Sn[i] = 1.0;
- c2->hpf_states[0] = c2->hpf_states[1] = 0.0;
- for(i=0; i<2*N; i++)
- c2->Sn_[i] = 0;
- c2->fft_fwd_cfg = kiss_fft_alloc(FFT_ENC, 0, NULL, NULL);
- make_analysis_window(c2->fft_fwd_cfg, c2->w,c2->W);
- make_synthesis_window(c2->Pn);
- c2->fft_inv_cfg = kiss_fft_alloc(FFT_DEC, 1, NULL, NULL);
- quantise_init();
- c2->prev_Wo_enc = 0.0;
- c2->bg_est = 0.0;
- c2->ex_phase = 0.0;
-
- for(l=1; l<=MAX_AMP; l++)
- c2->prev_model_dec.A[l] = 0.0;
- c2->prev_model_dec.Wo = TWO_PI/P_MAX;
- c2->prev_model_dec.L = PI/c2->prev_model_dec.Wo;
- c2->prev_model_dec.voiced = 0;
-
- for(i=0; i<LPC_ORD; i++) {
- c2->prev_lsps_dec[i] = i*PI/(LPC_ORD+1);
- }
- c2->prev_e_dec = 1;
-
- c2->nlp = nlp_create();
- if (c2->nlp == NULL) {
- free (c2);
- return NULL;
- }
-
- c2->lpc_pf = 1; c2->bass_boost = 1; c2->beta = LPCPF_BETA; c2->gamma = LPCPF_GAMMA;
-
- c2->xq_enc[0] = c2->xq_enc[1] = 0.0;
- c2->xq_dec[0] = c2->xq_dec[1] = 0.0;
-
- return c2;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_destroy
- AUTHOR......: David Rowe
- DATE CREATED: 21/8/2010
-
- Destroy an instance of the codec.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT codec2_destroy(struct CODEC2 *c2)
-{
- assert(c2 != NULL);
- nlp_destroy(c2->nlp);
- KISS_FFT_FREE(c2->fft_fwd_cfg);
- KISS_FFT_FREE(c2->fft_inv_cfg);
- free(c2);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_bits_per_frame
- AUTHOR......: David Rowe
- DATE CREATED: Nov 14 2011
-
- Returns the number of bits per frame.
-
-\*---------------------------------------------------------------------------*/
-
-int CODEC2_WIN32SUPPORT codec2_bits_per_frame(struct CODEC2 *c2) {
- if (c2->mode == CODEC2_MODE_3200)
- return 64;
- if (c2->mode == CODEC2_MODE_2400)
- return 48;
- if (c2->mode == CODEC2_MODE_1400)
- return 56;
- if (c2->mode == CODEC2_MODE_1200)
- return 48;
-
- return 0; /* shouldn't get here */
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_samples_per_frame
- AUTHOR......: David Rowe
- DATE CREATED: Nov 14 2011
-
- Returns the number of bits per frame.
-
-\*---------------------------------------------------------------------------*/
-
-int CODEC2_WIN32SUPPORT codec2_samples_per_frame(struct CODEC2 *c2) {
- if (c2->mode == CODEC2_MODE_3200)
- return 160;
- if (c2->mode == CODEC2_MODE_2400)
- return 160;
- if (c2->mode == CODEC2_MODE_1400)
- return 320;
- if (c2->mode == CODEC2_MODE_1200)
- return 320;
-
- return 0; /* shouldnt get here */
-}
-
-void CODEC2_WIN32SUPPORT codec2_encode(struct CODEC2 *c2, unsigned char *bits, short speech[])
-{
- assert(c2 != NULL);
- assert(
- (c2->mode == CODEC2_MODE_3200) ||
- (c2->mode == CODEC2_MODE_2400) ||
- (c2->mode == CODEC2_MODE_1400) ||
- (c2->mode == CODEC2_MODE_1200)
- );
-
- if (c2->mode == CODEC2_MODE_3200)
- codec2_encode_3200(c2, bits, speech);
- if (c2->mode == CODEC2_MODE_2400)
- codec2_encode_2400(c2, bits, speech);
- if (c2->mode == CODEC2_MODE_1400)
- codec2_encode_1400(c2, bits, speech);
- if (c2->mode == CODEC2_MODE_1200)
- codec2_encode_1200(c2, bits, speech);
-}
-
-void CODEC2_WIN32SUPPORT codec2_decode(struct CODEC2 *c2, short speech[], const unsigned char *bits)
-{
- assert(c2 != NULL);
- assert(
- (c2->mode == CODEC2_MODE_3200) ||
- (c2->mode == CODEC2_MODE_2400) ||
- (c2->mode == CODEC2_MODE_1400) ||
- (c2->mode == CODEC2_MODE_1200)
- );
-
- if (c2->mode == CODEC2_MODE_3200)
- codec2_decode_3200(c2, speech, bits);
- if (c2->mode == CODEC2_MODE_2400)
- codec2_decode_2400(c2, speech, bits);
- if (c2->mode == CODEC2_MODE_1400)
- codec2_decode_1400(c2, speech, bits);
- if (c2->mode == CODEC2_MODE_1200)
- codec2_decode_1200(c2, speech, bits);
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_encode_3200
- AUTHOR......: David Rowe
- DATE CREATED: 13 Sep 2012
-
- Encodes 160 speech samples (20ms of speech) into 64 bits.
-
- The codec2 algorithm actually operates internally on 10ms (80
- sample) frames, so we run the encoding algorithm twice. On the
- first frame we just send the voicing bits. On the second frame we
- send all model parameters. Compared to 2400 we use a larger number
- of bits for the LSPs and non-VQ pitch and energy.
-
- The bit allocation is:
-
- Parameter bits/frame
- --------------------------------------
- Harmonic magnitudes (LSPs) 50
- Pitch (Wo) 7
- Energy 5
- Voicing (10ms update) 2
- TOTAL 64
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_encode_3200(struct CODEC2 *c2, unsigned char * bits, short speech[])
-{
- MODEL model;
- float ak[LPC_ORD+1];
- float lsps[LPC_ORD];
- float e;
- int Wo_index, e_index;
- int lspd_indexes[LPC_ORD];
- int i;
- unsigned int nbit = 0;
-
- assert(c2 != NULL);
-
- memset(bits, '\0', ((codec2_bits_per_frame(c2) + 7) / 8));
-
- /* first 10ms analysis frame - we just want voicing */
-
- analyse_one_frame(c2, &model, speech);
- pack(bits, &nbit, model.voiced, 1);
-
- /* second 10ms analysis frame */
-
- analyse_one_frame(c2, &model, &speech[N]);
- pack(bits, &nbit, model.voiced, 1);
- Wo_index = encode_Wo(model.Wo);
- pack(bits, &nbit, Wo_index, WO_BITS);
-
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- e_index = encode_energy(e);
- pack(bits, &nbit, e_index, E_BITS);
-
- encode_lspds_scalar(lspd_indexes, lsps, LPC_ORD);
- for(i=0; i<LSPD_SCALAR_INDEXES; i++) {
- pack(bits, &nbit, lspd_indexes[i], lspd_bits(i));
- }
-
- assert(nbit == (unsigned)codec2_bits_per_frame(c2));
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_decode_3200
- AUTHOR......: David Rowe
- DATE CREATED: 13 Sep 2012
-
- Decodes a frame of 64 bits into 160 samples (20ms) of speech.
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_decode_3200(struct CODEC2 *c2, short speech[], const unsigned char * bits)
-{
- MODEL model[2];
- int lspd_indexes[LPC_ORD];
- float lsps[2][LPC_ORD];
- int Wo_index, e_index;
- float e[2];
- float snr;
- float ak[2][LPC_ORD+1];
- int i,j;
- unsigned int nbit = 0;
-
- assert(c2 != NULL);
-
- /* only need to zero these out due to (unused) snr calculation */
-
- for(i=0; i<2; i++)
- for(j=1; j<=MAX_AMP; j++)
- model[i].A[j] = 0.0;
-
- /* unpack bits from channel ------------------------------------*/
-
- /* this will partially fill the model params for the 2 x 10ms
- frames */
-
- model[0].voiced = unpack(bits, &nbit, 1);
- model[1].voiced = unpack(bits, &nbit, 1);
-
- Wo_index = unpack(bits, &nbit, WO_BITS);
- model[1].Wo = decode_Wo(Wo_index);
- model[1].L = PI/model[1].Wo;
-
- e_index = unpack(bits, &nbit, E_BITS);
- e[1] = decode_energy(e_index);
-
- for(i=0; i<LSPD_SCALAR_INDEXES; i++) {
- lspd_indexes[i] = unpack(bits, &nbit, lspd_bits(i));
- }
- decode_lspds_scalar(&lsps[1][0], lspd_indexes, LPC_ORD);
-
- /* interpolate ------------------------------------------------*/
-
- /* Wo and energy are sampled every 20ms, so we interpolate just 1
- 10ms frame between 20ms samples */
-
- interp_Wo(&model[0], &c2->prev_model_dec, &model[1]);
- e[0] = interp_energy(c2->prev_e_dec, e[1]);
-
- /* LSPs are sampled every 20ms so we interpolate the frame in
- between, then recover spectral amplitudes */
-
- interpolate_lsp_ver2(&lsps[0][0], c2->prev_lsps_dec, &lsps[1][0], 0.5);
- for(i=0; i<2; i++) {
- lsp_to_lpc(&lsps[i][0], &ak[i][0], LPC_ORD);
- aks_to_M2(c2->fft_fwd_cfg, &ak[i][0], LPC_ORD, &model[i], e[i], &snr, 0, 0,
- c2->lpc_pf, c2->bass_boost, c2->beta, c2->gamma);
- apply_lpc_correction(&model[i]);
- }
-
- /* synthesise ------------------------------------------------*/
-
- for(i=0; i<2; i++)
- synthesise_one_frame(c2, &speech[N*i], &model[i], &ak[i][0]);
-
- /* update memories for next frame ----------------------------*/
-
- c2->prev_model_dec = model[1];
- c2->prev_e_dec = e[1];
- for(i=0; i<LPC_ORD; i++)
- c2->prev_lsps_dec[i] = lsps[1][i];
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_encode_2400
- AUTHOR......: David Rowe
- DATE CREATED: 21/8/2010
-
- Encodes 160 speech samples (20ms of speech) into 48 bits.
-
- The codec2 algorithm actually operates internally on 10ms (80
- sample) frames, so we run the encoding algorithm twice. On the
- first frame we just send the voicing bit. On the second frame we
- send all model parameters.
-
- The bit allocation is:
-
- Parameter bits/frame
- --------------------------------------
- Harmonic magnitudes (LSPs) 36
- Joint VQ of Energy and Wo 8
- Voicing (10ms update) 2
- Spare 2
- TOTAL 48
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_encode_2400(struct CODEC2 *c2, unsigned char * bits, short speech[])
-{
- MODEL model;
- float ak[LPC_ORD+1];
- float lsps[LPC_ORD];
- float e;
- int WoE_index;
- int lsp_indexes[LPC_ORD];
- int i;
- int spare = 0;
- unsigned int nbit = 0;
-
- assert(c2 != NULL);
-
- memset(bits, '\0', ((codec2_bits_per_frame(c2) + 7) / 8));
-
- /* first 10ms analysis frame - we just want voicing */
-
- analyse_one_frame(c2, &model, speech);
- pack(bits, &nbit, model.voiced, 1);
-
- /* second 10ms analysis frame */
-
- analyse_one_frame(c2, &model, &speech[N]);
- pack(bits, &nbit, model.voiced, 1);
-
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- WoE_index = encode_WoE(&model, e, c2->xq_enc);
- pack(bits, &nbit, WoE_index, WO_E_BITS);
-
- encode_lsps_scalar(lsp_indexes, lsps, LPC_ORD);
- for(i=0; i<LSP_SCALAR_INDEXES; i++) {
- pack(bits, &nbit, lsp_indexes[i], lsp_bits(i));
- }
- pack(bits, &nbit, spare, 2);
-
- assert(nbit == (unsigned)codec2_bits_per_frame(c2));
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_decode_2400
- AUTHOR......: David Rowe
- DATE CREATED: 21/8/2010
-
- Decodes frames of 48 bits into 160 samples (20ms) of speech.
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_decode_2400(struct CODEC2 *c2, short speech[], const unsigned char * bits)
-{
- MODEL model[2];
- int lsp_indexes[LPC_ORD];
- float lsps[2][LPC_ORD];
- int WoE_index;
- float e[2];
- float snr;
- float ak[2][LPC_ORD+1];
- int i,j;
- unsigned int nbit = 0;
-
- assert(c2 != NULL);
-
- /* only need to zero these out due to (unused) snr calculation */
-
- for(i=0; i<2; i++)
- for(j=1; j<=MAX_AMP; j++)
- model[i].A[j] = 0.0;
-
- /* unpack bits from channel ------------------------------------*/
-
- /* this will partially fill the model params for the 2 x 10ms
- frames */
-
- model[0].voiced = unpack(bits, &nbit, 1);
-
- model[1].voiced = unpack(bits, &nbit, 1);
- WoE_index = unpack(bits, &nbit, WO_E_BITS);
- decode_WoE(&model[1], &e[1], c2->xq_dec, WoE_index);
-
- for(i=0; i<LSP_SCALAR_INDEXES; i++) {
- lsp_indexes[i] = unpack(bits, &nbit, lsp_bits(i));
- }
- decode_lsps_scalar(&lsps[1][0], lsp_indexes, LPC_ORD);
- check_lsp_order(&lsps[1][0], LPC_ORD);
- bw_expand_lsps(&lsps[1][0], LPC_ORD);
-
- /* interpolate ------------------------------------------------*/
-
- /* Wo and energy are sampled every 20ms, so we interpolate just 1
- 10ms frame between 20ms samples */
-
- interp_Wo(&model[0], &c2->prev_model_dec, &model[1]);
- e[0] = interp_energy(c2->prev_e_dec, e[1]);
-
- /* LSPs are sampled every 20ms so we interpolate the frame in
- between, then recover spectral amplitudes */
-
- interpolate_lsp_ver2(&lsps[0][0], c2->prev_lsps_dec, &lsps[1][0], 0.5);
- for(i=0; i<2; i++) {
- lsp_to_lpc(&lsps[i][0], &ak[i][0], LPC_ORD);
- aks_to_M2(c2->fft_fwd_cfg, &ak[i][0], LPC_ORD, &model[i], e[i], &snr, 0, 0,
- c2->lpc_pf, c2->bass_boost, c2->beta, c2->gamma);
- apply_lpc_correction(&model[i]);
- }
-
- /* synthesise ------------------------------------------------*/
-
- for(i=0; i<2; i++)
- synthesise_one_frame(c2, &speech[N*i], &model[i], &ak[i][0]);
-
- /* update memories for next frame ----------------------------*/
-
- c2->prev_model_dec = model[1];
- c2->prev_e_dec = e[1];
- for(i=0; i<LPC_ORD; i++)
- c2->prev_lsps_dec[i] = lsps[1][i];
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_encode_1400
- AUTHOR......: David Rowe
- DATE CREATED: May 11 2012
-
- Encodes 320 speech samples (40ms of speech) into 56 bits.
-
- The codec2 algorithm actually operates internally on 10ms (80
- sample) frames, so we run the encoding algorithm 4 times:
-
- frame 0: voicing bit
- frame 1: voicing bit, joint VQ of Wo and E
- frame 2: voicing bit
- frame 3: voicing bit, joint VQ of Wo and E, scalar LSPs
-
- The bit allocation is:
-
- Parameter frame 2 frame 4 Total
- -------------------------------------------------------
- Harmonic magnitudes (LSPs) 0 36 36
- Energy+Wo 8 8 16
- Voicing (10ms update) 2 2 4
- TOTAL 10 46 56
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_encode_1400(struct CODEC2 *c2, unsigned char * bits, short speech[])
-{
- MODEL model;
- float lsps[LPC_ORD];
- float ak[LPC_ORD+1];
- float e;
- int lsp_indexes[LPC_ORD];
- int WoE_index;
- int i;
- unsigned int nbit = 0;
-
- assert(c2 != NULL);
-
- memset(bits, '\0', ((codec2_bits_per_frame(c2) + 7) / 8));
-
- /* frame 1: - voicing ---------------------------------------------*/
-
- analyse_one_frame(c2, &model, speech);
- pack(bits, &nbit, model.voiced, 1);
-
- /* frame 2: - voicing, joint Wo & E -------------------------------*/
-
- analyse_one_frame(c2, &model, &speech[N]);
- pack(bits, &nbit, model.voiced, 1);
-
- /* need to run this just to get LPC energy */
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
-
- WoE_index = encode_WoE(&model, e, c2->xq_enc);
- pack(bits, &nbit, WoE_index, WO_E_BITS);
-
- /* frame 3: - voicing ---------------------------------------------*/
-
- analyse_one_frame(c2, &model, &speech[2*N]);
- pack(bits, &nbit, model.voiced, 1);
-
- /* frame 4: - voicing, joint Wo & E, scalar LSPs ------------------*/
-
- analyse_one_frame(c2, &model, &speech[3*N]);
- pack(bits, &nbit, model.voiced, 1);
-
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- WoE_index = encode_WoE(&model, e, c2->xq_enc);
- pack(bits, &nbit, WoE_index, WO_E_BITS);
-
- encode_lsps_scalar(lsp_indexes, lsps, LPC_ORD);
- for(i=0; i<LSP_SCALAR_INDEXES; i++) {
- pack(bits, &nbit, lsp_indexes[i], lsp_bits(i));
- }
-
- assert(nbit == (unsigned)codec2_bits_per_frame(c2));
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_decode_1400
- AUTHOR......: David Rowe
- DATE CREATED: 11 May 2012
-
- Decodes frames of 56 bits into 320 samples (40ms) of speech.
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_decode_1400(struct CODEC2 *c2, short speech[], const unsigned char * bits)
-{
- MODEL model[4];
- int lsp_indexes[LPC_ORD];
- float lsps[4][LPC_ORD];
- int WoE_index;
- float e[4];
- float snr;
- float ak[4][LPC_ORD+1];
- int i,j;
- unsigned int nbit = 0;
- float weight;
-
- assert(c2 != NULL);
-
- /* only need to zero these out due to (unused) snr calculation */
-
- for(i=0; i<4; i++)
- for(j=1; j<=MAX_AMP; j++)
- model[i].A[j] = 0.0;
-
- /* unpack bits from channel ------------------------------------*/
-
- /* this will partially fill the model params for the 4 x 10ms
- frames */
-
- model[0].voiced = unpack(bits, &nbit, 1);
-
- model[1].voiced = unpack(bits, &nbit, 1);
- WoE_index = unpack(bits, &nbit, WO_E_BITS);
- decode_WoE(&model[1], &e[1], c2->xq_dec, WoE_index);
-
- model[2].voiced = unpack(bits, &nbit, 1);
-
- model[3].voiced = unpack(bits, &nbit, 1);
- WoE_index = unpack(bits, &nbit, WO_E_BITS);
- decode_WoE(&model[3], &e[3], c2->xq_dec, WoE_index);
-
- for(i=0; i<LSP_SCALAR_INDEXES; i++) {
- lsp_indexes[i] = unpack(bits, &nbit, lsp_bits(i));
- }
- decode_lsps_scalar(&lsps[3][0], lsp_indexes, LPC_ORD);
- check_lsp_order(&lsps[3][0], LPC_ORD);
- bw_expand_lsps(&lsps[3][0], LPC_ORD);
-
- /* interpolate ------------------------------------------------*/
-
- /* Wo and energy are sampled every 20ms, so we interpolate just 1
- 10ms frame between 20ms samples */
-
- interp_Wo(&model[0], &c2->prev_model_dec, &model[1]);
- e[0] = interp_energy(c2->prev_e_dec, e[1]);
- interp_Wo(&model[2], &model[1], &model[3]);
- e[2] = interp_energy(e[1], e[3]);
-
- /* LSPs are sampled every 40ms so we interpolate the 3 frames in
- between, then recover spectral amplitudes */
-
- for(i=0, weight=0.25; i<3; i++, weight += 0.25) {
- interpolate_lsp_ver2(&lsps[i][0], c2->prev_lsps_dec, &lsps[3][0], weight);
- }
- for(i=0; i<4; i++) {
- lsp_to_lpc(&lsps[i][0], &ak[i][0], LPC_ORD);
- aks_to_M2(c2->fft_fwd_cfg, &ak[i][0], LPC_ORD, &model[i], e[i], &snr, 0, 0,
- c2->lpc_pf, c2->bass_boost, c2->beta, c2->gamma);
- apply_lpc_correction(&model[i]);
- }
-
- /* synthesise ------------------------------------------------*/
-
- for(i=0; i<4; i++)
- synthesise_one_frame(c2, &speech[N*i], &model[i], &ak[i][0]);
-
- /* update memories for next frame ----------------------------*/
-
- c2->prev_model_dec = model[3];
- c2->prev_e_dec = e[3];
- for(i=0; i<LPC_ORD; i++)
- c2->prev_lsps_dec[i] = lsps[3][i];
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_encode_1200
- AUTHOR......: David Rowe
- DATE CREATED: Nov 14 2011
-
- Encodes 320 speech samples (40ms of speech) into 48 bits.
-
- The codec2 algorithm actually operates internally on 10ms (80
- sample) frames, so we run the encoding algorithm four times:
-
- frame 0: voicing bit
- frame 1: voicing bit, joint VQ of Wo and E
- frame 2: voicing bit
- frame 3: voicing bit, joint VQ of Wo and E, VQ LSPs
-
- The bit allocation is:
-
- Parameter frame 2 frame 4 Total
- -------------------------------------------------------
- Harmonic magnitudes (LSPs) 0 27 27
- Energy+Wo 8 8 16
- Voicing (10ms update) 2 2 4
- Spare 0 1 1
- TOTAL 10 38 48
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_encode_1200(struct CODEC2 *c2, unsigned char * bits, short speech[])
-{
- MODEL model;
- float lsps[LPC_ORD];
- float lsps_[LPC_ORD];
- float ak[LPC_ORD+1];
- float e;
- int lsp_indexes[LPC_ORD];
- int WoE_index;
- int i;
- int spare = 0;
- unsigned int nbit = 0;
-
- assert(c2 != NULL);
-
- memset(bits, '\0', ((codec2_bits_per_frame(c2) + 7) / 8));
-
- /* frame 1: - voicing ---------------------------------------------*/
-
- analyse_one_frame(c2, &model, speech);
- pack(bits, &nbit, model.voiced, 1);
-
- /* frame 2: - voicing, joint Wo & E -------------------------------*/
-
- analyse_one_frame(c2, &model, &speech[N]);
- pack(bits, &nbit, model.voiced, 1);
-
- /* need to run this just to get LPC energy */
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
-
- WoE_index = encode_WoE(&model, e, c2->xq_enc);
- pack(bits, &nbit, WoE_index, WO_E_BITS);
-
- /* frame 3: - voicing ---------------------------------------------*/
-
- analyse_one_frame(c2, &model, &speech[2*N]);
- pack(bits, &nbit, model.voiced, 1);
-
- /* frame 4: - voicing, joint Wo & E, scalar LSPs ------------------*/
-
- analyse_one_frame(c2, &model, &speech[3*N]);
- pack(bits, &nbit, model.voiced, 1);
-
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- WoE_index = encode_WoE(&model, e, c2->xq_enc);
- pack(bits, &nbit, WoE_index, WO_E_BITS);
-
- encode_lsps_vq(lsp_indexes, lsps, lsps_, LPC_ORD);
- for(i=0; i<LSP_PRED_VQ_INDEXES; i++) {
- pack(bits, &nbit, lsp_indexes[i], lsp_pred_vq_bits(i));
- }
- pack(bits, &nbit, spare, 1);
-
- assert(nbit == (unsigned)codec2_bits_per_frame(c2));
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: codec2_decode_1200
- AUTHOR......: David Rowe
- DATE CREATED: 14 Feb 2012
-
- Decodes frames of 48 bits into 320 samples (40ms) of speech.
-
-\*---------------------------------------------------------------------------*/
-
-void codec2_decode_1200(struct CODEC2 *c2, short speech[], const unsigned char * bits)
-{
- MODEL model[4];
- int lsp_indexes[LPC_ORD];
- float lsps[4][LPC_ORD];
- int WoE_index;
- float e[4];
- float snr;
- float ak[4][LPC_ORD+1];
- int i,j;
- unsigned int nbit = 0;
- float weight;
-
- assert(c2 != NULL);
-
- /* only need to zero these out due to (unused) snr calculation */
-
- for(i=0; i<4; i++)
- for(j=1; j<=MAX_AMP; j++)
- model[i].A[j] = 0.0;
-
- /* unpack bits from channel ------------------------------------*/
-
- /* this will partially fill the model params for the 4 x 10ms
- frames */
-
- model[0].voiced = unpack(bits, &nbit, 1);
-
- model[1].voiced = unpack(bits, &nbit, 1);
- WoE_index = unpack(bits, &nbit, WO_E_BITS);
- decode_WoE(&model[1], &e[1], c2->xq_dec, WoE_index);
-
- model[2].voiced = unpack(bits, &nbit, 1);
-
- model[3].voiced = unpack(bits, &nbit, 1);
- WoE_index = unpack(bits, &nbit, WO_E_BITS);
- decode_WoE(&model[3], &e[3], c2->xq_dec, WoE_index);
-
- for(i=0; i<LSP_PRED_VQ_INDEXES; i++) {
- lsp_indexes[i] = unpack(bits, &nbit, lsp_pred_vq_bits(i));
- }
- decode_lsps_vq(lsp_indexes, &lsps[3][0], LPC_ORD);
- check_lsp_order(&lsps[3][0], LPC_ORD);
- bw_expand_lsps(&lsps[3][0], LPC_ORD);
-
- /* interpolate ------------------------------------------------*/
-
- /* Wo and energy are sampled every 20ms, so we interpolate just 1
- 10ms frame between 20ms samples */
-
- interp_Wo(&model[0], &c2->prev_model_dec, &model[1]);
- e[0] = interp_energy(c2->prev_e_dec, e[1]);
- interp_Wo(&model[2], &model[1], &model[3]);
- e[2] = interp_energy(e[1], e[3]);
-
- /* LSPs are sampled every 40ms so we interpolate the 3 frames in
- between, then recover spectral amplitudes */
-
- for(i=0, weight=0.25; i<3; i++, weight += 0.25) {
- interpolate_lsp_ver2(&lsps[i][0], c2->prev_lsps_dec, &lsps[3][0], weight);
- }
- for(i=0; i<4; i++) {
- lsp_to_lpc(&lsps[i][0], &ak[i][0], LPC_ORD);
- aks_to_M2(c2->fft_fwd_cfg, &ak[i][0], LPC_ORD, &model[i], e[i], &snr, 0, 0,
- c2->lpc_pf, c2->bass_boost, c2->beta, c2->gamma);
- apply_lpc_correction(&model[i]);
- }
-
- /* synthesise ------------------------------------------------*/
-
- for(i=0; i<4; i++)
- synthesise_one_frame(c2, &speech[N*i], &model[i], &ak[i][0]);
-
- /* update memories for next frame ----------------------------*/
-
- c2->prev_model_dec = model[3];
- c2->prev_e_dec = e[3];
- for(i=0; i<LPC_ORD; i++)
- c2->prev_lsps_dec[i] = lsps[3][i];
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: synthesise_one_frame()
- AUTHOR......: David Rowe
- DATE CREATED: 23/8/2010
-
- Synthesise 80 speech samples (10ms) from model parameters.
-
-\*---------------------------------------------------------------------------*/
-
-void synthesise_one_frame(struct CODEC2 *c2, short speech[], MODEL *model, float ak[])
-{
- int i;
-
- phase_synth_zero_order(c2->fft_fwd_cfg, model, ak, &c2->ex_phase, LPC_ORD);
- postfilter(model, &c2->bg_est);
- synthesise(c2->fft_inv_cfg, c2->Sn_, model, c2->Pn, 1);
- ear_protection(c2->Sn_, N);
-
- for(i=0; i<N; i++) {
- if (c2->Sn_[i] > 32767.0)
- speech[i] = 32767;
- else if (c2->Sn_[i] < -32767.0)
- speech[i] = -32767;
- else
- speech[i] = c2->Sn_[i];
- }
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: analyse_one_frame()
- AUTHOR......: David Rowe
- DATE CREATED: 23/8/2010
-
- Extract sinusoidal model parameters from 80 speech samples (10ms of
- speech).
-
-\*---------------------------------------------------------------------------*/
-
-void analyse_one_frame(struct CODEC2 *c2, MODEL *model, short speech[])
-{
- COMP Sw[FFT_ENC];
- COMP Sw_[FFT_ENC];
- COMP Ew[FFT_ENC];
- float pitch, snr;
- int i;
-
- /* Read input speech */
-
- for(i=0; i<M-N; i++)
- c2->Sn[i] = c2->Sn[i+N];
- for(i=0; i<N; i++)
- c2->Sn[i+M-N] = speech[i];
-
- dft_speech(c2->fft_fwd_cfg, Sw, c2->Sn, c2->w);
-
- /* Estimate pitch */
-
- nlp(c2->nlp,c2->Sn,N,M,P_MIN,P_MAX,&pitch,Sw, c2->W, &c2->prev_Wo_enc);
- model->Wo = TWO_PI/pitch;
- model->L = PI/model->Wo;
-
- /* estimate model parameters */
-
- two_stage_pitch_refinement(model, Sw);
- estimate_amplitudes(model, Sw, c2->W);
- snr = est_voicing_mbe(model, Sw, c2->W, Sw_, Ew, c2->prev_Wo_enc);
- //fprintf(stderr,"snr %3.2f v: %d Wo: %f prev_Wo: %f\n",
- // snr, model->voiced, model->Wo, c2->prev_Wo_enc);
- c2->prev_Wo_enc = model->Wo;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: ear_protection()
- AUTHOR......: David Rowe
- DATE CREATED: Nov 7 2012
-
- Limits output level to protect ears when there are bit errors or the input
- is overdriven. This doesn't correct or mask bit erros, just reduces the
- worst of their damage.
-
-\*---------------------------------------------------------------------------*/
-
-void ear_protection(float in_out[], int n) {
- float max_sample, over, gain;
- int i;
-
- /* find maximum sample in frame */
-
- max_sample = 0.0;
- for(i=0; i<n; i++)
- if (in_out[i] > max_sample)
- max_sample = in_out[i];
-
- /* determine how far above set point */
-
- over = max_sample/30000.0;
-
- /* If we are x dB over set point we reduce level by 2x dB, this
- attenuates major excursions in amplitude (likely to be caused
- by bit errors) more than smaller ones */
-
- if (over > 1.0) {
- gain = 1.0/(over*over);
- //fprintf(stderr, "gain: %f\n", gain);
- for(i=0; i<n; i++)
- in_out[i] *= gain;
- }
-}
-
-void CODEC2_WIN32SUPPORT codec2_set_lpc_post_filter(struct CODEC2 *c2, int enable, int bass_boost, float beta, float gamma)
-{
- assert((beta >= 0.0) && (beta <= 1.0));
- assert((gamma >= 0.0) && (gamma <= 1.0));
- c2->lpc_pf = enable;
- c2->bass_boost = bass_boost;
- c2->beta = beta;
- c2->gamma = gamma;
-}
-
-/*
- Allows optional stealing of one of the voicing bits for use as a
- spare bit, only 1400 bit/s supported for now. Experimental method
- of sending voice/data frames for FreeDV.
-*/
-
-int CODEC2_WIN32SUPPORT codec2_get_spare_bit_index(struct CODEC2 *c2)
-{
- assert(c2 != NULL);
-
- if (c2->mode != CODEC2_MODE_1400)
- return -1;
-
- return 10; // bit 10 (11th bit) is v2 (third voicing bit)
-}
-
-/*
- Reconstructs the spare voicing bit. Note works on unpacked bits
- for convenience.
-*/
-
-int CODEC2_WIN32SUPPORT codec2_rebuild_spare_bit(struct CODEC2 *c2, int unpacked_bits[])
-{
- int v0,v1,v3;
-
- assert(c2 != NULL);
-
- if (c2->mode != CODEC2_MODE_1400)
- return -1;
-
- v0 = unpacked_bits[0];
- v1 = unpacked_bits[1];
- v3 = unpacked_bits[11];
-
- /* if either adjacent frame is voiced, make this one voiced */
-
- unpacked_bits[10] = (v1 || v3);
-
- return 0;
-}
-
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: codec2.h
- AUTHOR......: David Rowe
- DATE CREATED: 21 August 2010
-
- Codec 2 fully quantised encoder and decoder functions. If you want use
- Codec 2, these are the functions you need to call.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifdef __cplusplus
- extern "C" {
-#endif
-
-#ifndef __CODEC2__
-#define __CODEC2__
-
-/* set up the calling convention for DLL function import/export for
- WIN32 cross compiling */
-
-#ifdef __CODEC2_WIN32__
-#ifdef __CODEC2_BUILDING_DLL__
-#define CODEC2_WIN32SUPPORT __declspec(dllexport) __stdcall
-#else
-#define CODEC2_WIN32SUPPORT __declspec(dllimport) __stdcall
-#endif
-#else
-#define CODEC2_WIN32SUPPORT
-#endif
-
-#define CODEC2_MODE_3200 0
-#define CODEC2_MODE_2400 1
-#define CODEC2_MODE_1400 2
-#define CODEC2_MODE_1200 3
-
-struct CODEC2;
-
-struct CODEC2 * CODEC2_WIN32SUPPORT codec2_create(int mode);
-void CODEC2_WIN32SUPPORT codec2_destroy(struct CODEC2 *codec2_state);
-void CODEC2_WIN32SUPPORT codec2_encode(struct CODEC2 *codec2_state, unsigned char * bits, short speech_in[]);
-void CODEC2_WIN32SUPPORT codec2_decode(struct CODEC2 *codec2_state, short speech_out[], const unsigned char *bits);
-int CODEC2_WIN32SUPPORT codec2_samples_per_frame(struct CODEC2 *codec2_state);
-int CODEC2_WIN32SUPPORT codec2_bits_per_frame(struct CODEC2 *codec2_state);
-
-void CODEC2_WIN32SUPPORT codec2_set_lpc_post_filter(struct CODEC2 *codec2_state, int enable, int bass_boost, float beta, float gamma);
-int CODEC2_WIN32SUPPORT codec2_get_spare_bit_index(struct CODEC2 *codec2_state);
-int CODEC2_WIN32SUPPORT codec2_rebuild_spare_bit(struct CODEC2 *codec2_state, int unpacked_bits[]);
-
-#endif
-
-#ifdef __cplusplus
-}
-#endif
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: codec2_internal.h
- AUTHOR......: David Rowe
- DATE CREATED: April 16 2012
-
- Header file for Codec2 internal states, exposed via this header
- file to assist in testing.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __CODEC2_INTERNAL__
-#define __CODEC2_INTERNAL__
-
-struct CODEC2 {
- int mode;
- kiss_fft_cfg fft_fwd_cfg; /* forward FFT config */
- float w[M]; /* time domain hamming window */
- COMP W[FFT_ENC]; /* DFT of w[] */
- float Pn[2*N]; /* trapezoidal synthesis window */
- float Sn[M]; /* input speech */
- float hpf_states[2]; /* high pass filter states */
- void *nlp; /* pitch predictor states */
-
- kiss_fft_cfg fft_inv_cfg; /* inverse FFT config */
- float Sn_[2*N]; /* synthesised output speech */
- float ex_phase; /* excitation model phase track */
- float bg_est; /* background noise estimate for post filter */
- float prev_Wo_enc; /* previous frame's pitch estimate */
- MODEL prev_model_dec; /* previous frame's model parameters */
- float prev_lsps_dec[LPC_ORD]; /* previous frame's LSPs */
- float prev_e_dec; /* previous frame's LPC energy */
-
- int lpc_pf; /* LPC post filter on */
- int bass_boost; /* LPC post filter bass boost */
- float beta; /* LPC post filter parameters */
- float gamma;
-
- float xq_enc[2]; /* joint pitch and energy VQ states */
- float xq_dec[2];
-};
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: comp.h
- AUTHOR......: David Rowe
- DATE CREATED: 24/08/09
-
- Complex number definition.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __COMP__
-#define __COMP__
-
-/* Complex number */
-
-typedef struct {
- float real;
- float imag;
-} COMP;
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: defines.h
- AUTHOR......: David Rowe
- DATE CREATED: 23/4/93
-
- Defines and structures used throughout the codec.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __DEFINES__
-#define __DEFINES__
-
-/*---------------------------------------------------------------------------*\
-
- DEFINES
-
-\*---------------------------------------------------------------------------*/
-
-/* General defines */
-
-#define N 80 /* number of samples per frame */
-#define MAX_AMP 80 /* maximum number of harmonics */
-#define PI 3.141592654 /* mathematical constant */
-#define TWO_PI 6.283185307 /* mathematical constant */
-#define FS 8000 /* sample rate in Hz */
-#define MAX_STR 256 /* maximum string size */
-
-#define NW 279 /* analysis window size */
-#define FFT_ENC 512 /* size of FFT used for encoder */
-#define FFT_DEC 512 /* size of FFT used in decoder */
-#define TW 40 /* Trapezoidal synthesis window overlap */
-#define V_THRESH 6.0 /* voicing threshold in dB */
-#define LPC_MAX 20 /* maximum LPC order */
-#define LPC_ORD 10 /* phase modelling LPC order */
-
-/* Pitch estimation defines */
-
-#define M 320 /* pitch analysis frame size */
-#define P_MIN 20 /* minimum pitch */
-#define P_MAX 160 /* maximum pitch */
-
-/*---------------------------------------------------------------------------*\
-
- TYPEDEFS
-
-\*---------------------------------------------------------------------------*/
-
-/* Structure to hold model parameters for one frame */
-
-typedef struct {
- float Wo; /* fundamental frequency estimate in radians */
- int L; /* number of harmonics */
- float A[MAX_AMP+1]; /* amplitiude of each harmonic */
- float phi[MAX_AMP+1]; /* phase of each harmonic */
- int voiced; /* non-zero if this frame is voiced */
-} MODEL;
-
-/* describes each codebook */
-
-struct lsp_codebook {
- int k; /* dimension of vector */
- int log2m; /* number of bits in m */
- int m; /* elements in codebook */
- const float * cb; /* The elements */
-};
-
-extern const struct lsp_codebook lsp_cb[];
-extern const struct lsp_codebook lsp_cbd[];
-extern const struct lsp_codebook lsp_cbvq[];
-extern const struct lsp_codebook lsp_cbjnd[];
-extern const struct lsp_codebook lsp_cbdt[];
-extern const struct lsp_codebook lsp_cbjvm[];
-extern const struct lsp_codebook lsp_cbvqanssi[];
-extern const struct lsp_codebook ge_cb[];
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: dump.c
- AUTHOR......: David Rowe
- DATE CREATED: 25/8/09
-
- Routines to dump data to text files for Octave analysis.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "defines.h"
-#include "comp.h"
-#include "dump.h"
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-
-#ifdef DUMP
-static int dumpon = 0;
-
-static FILE *fsn = NULL;
-static FILE *fsw = NULL;
-static FILE *few = NULL;
-static FILE *fsw_ = NULL;
-static FILE *fmodel = NULL;
-static FILE *fqmodel = NULL;
-static FILE *fpwb = NULL;
-static FILE *fpw = NULL;
-static FILE *frw = NULL;
-static FILE *flsp = NULL;
-static FILE *fweights = NULL;
-static FILE *flsp_ = NULL;
-static FILE *fphase = NULL;
-static FILE *fphase_ = NULL;
-static FILE *ffw = NULL;
-static FILE *fe = NULL;
-static FILE *fsq = NULL;
-static FILE *fdec = NULL;
-static FILE *fsnr = NULL;
-static FILE *flpcsnr = NULL;
-static FILE *fak = NULL;
-static FILE *fak_ = NULL;
-static FILE *fbg = NULL;
-static FILE *fE = NULL;
-static FILE *frk = NULL;
-static FILE *fhephase = NULL;
-
-static char prefix[MAX_STR];
-
-void dump_on(char p[]) {
- dumpon = 1;
- strcpy(prefix, p);
-}
-
-void dump_off(){
- if (fsn != NULL)
- fclose(fsn);
- if (fsw != NULL)
- fclose(fsw);
- if (fsw_ != NULL)
- fclose(fsw_);
- if (few != NULL)
- fclose(few);
- if (fmodel != NULL)
- fclose(fmodel);
- if (fqmodel != NULL)
- fclose(fqmodel);
- if (fpwb != NULL)
- fclose(fpwb);
- if (fpw != NULL)
- fclose(fpw);
- if (frw != NULL)
- fclose(frw);
- if (flsp != NULL)
- fclose(flsp);
- if (fweights != NULL)
- fclose(fweights);
- if (flsp_ != NULL)
- fclose(flsp_);
- if (fphase != NULL)
- fclose(fphase);
- if (fphase_ != NULL)
- fclose(fphase_);
- if (ffw != NULL)
- fclose(ffw);
- if (fe != NULL)
- fclose(fe);
- if (fsq != NULL)
- fclose(fsq);
- if (fdec != NULL)
- fclose(fdec);
- if (fsnr != NULL)
- fclose(fsnr);
- if (flpcsnr != NULL)
- fclose(flpcsnr);
- if (fak != NULL)
- fclose(fak);
- if (fak_ != NULL)
- fclose(fak_);
- if (fbg != NULL)
- fclose(fbg);
- if (fE != NULL)
- fclose(fE);
- if (frk != NULL)
- fclose(frk);
- if (fhephase != NULL)
- fclose(fhephase);
-}
-
-void dump_Sn(float Sn[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fsn == NULL) {
- sprintf(s,"%s_sn.txt", prefix);
- fsn = fopen(s, "wt");
- assert(fsn != NULL);
- }
-
- /* split across two lines to avoid max line length problems */
- /* reconstruct in Octave */
-
- for(i=0; i<M/2; i++)
- fprintf(fsn,"%f\t",Sn[i]);
- fprintf(fsn,"\n");
- for(i=M/2; i<M; i++)
- fprintf(fsn,"%f\t",Sn[i]);
- fprintf(fsn,"\n");
-}
-
-void dump_Sw(COMP Sw[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fsw == NULL) {
- sprintf(s,"%s_sw.txt", prefix);
- fsw = fopen(s, "wt");
- assert(fsw != NULL);
- }
-
- for(i=0; i<FFT_ENC/2; i++)
- fprintf(fsw,"%f\t",
- 10.0*log10(Sw[i].real*Sw[i].real + Sw[i].imag*Sw[i].imag));
- fprintf(fsw,"\n");
-}
-
-void dump_Sw_(COMP Sw_[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fsw_ == NULL) {
- sprintf(s,"%s_sw_.txt", prefix);
- fsw_ = fopen(s, "wt");
- assert(fsw_ != NULL);
- }
-
- for(i=0; i<FFT_ENC/2; i++)
- fprintf(fsw_,"%f\t",
- 10.0*log10(Sw_[i].real*Sw_[i].real + Sw_[i].imag*Sw_[i].imag));
- fprintf(fsw_,"\n");
-}
-
-void dump_Ew(COMP Ew[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (few == NULL) {
- sprintf(s,"%s_ew.txt", prefix);
- few = fopen(s, "wt");
- assert(few != NULL);
- }
-
- for(i=0; i<FFT_ENC/2; i++)
- fprintf(few,"%f\t",
- 10.0*log10(Ew[i].real*Ew[i].real + Ew[i].imag*Ew[i].imag));
- fprintf(few,"\n");
-}
-
-void dump_model(MODEL *model) {
- int l;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fmodel == NULL) {
- sprintf(s,"%s_model.txt", prefix);
- fmodel = fopen(s, "wt");
- assert(fmodel != NULL);
- }
-
- fprintf(fmodel,"%f\t%d\t", model->Wo, model->L);
- for(l=1; l<=model->L; l++)
- fprintf(fmodel,"%f\t",model->A[l]);
- for(l=model->L+1; l<MAX_AMP; l++)
- fprintf(fmodel,"0.0\t");
- fprintf(fmodel,"%d\t",model->voiced);
- fprintf(fmodel,"\n");
-}
-
-void dump_quantised_model(MODEL *model) {
- int l;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fqmodel == NULL) {
- sprintf(s,"%s_qmodel.txt", prefix);
- fqmodel = fopen(s, "wt");
- assert(fqmodel != NULL);
- }
-
- fprintf(fqmodel,"%f\t%d\t", model->Wo, model->L);
- for(l=1; l<=model->L; l++)
- fprintf(fqmodel,"%f\t",model->A[l]);
- for(l=model->L+1; l<MAX_AMP; l++)
- fprintf(fqmodel,"0.0\t");
- fprintf(fqmodel,"\n");
-}
-
-void dump_phase(float phase[], int L) {
- int l;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fphase == NULL) {
- sprintf(s,"%s_phase.txt", prefix);
- fphase = fopen(s, "wt");
- assert(fphase != NULL);
- }
-
- for(l=1; l<=L; l++)
- fprintf(fphase,"%f\t",phase[l]);
- for(l=L+1; l<MAX_AMP; l++)
- fprintf(fphase,"%f\t",0.0);
- fprintf(fphase,"\n");
-}
-
-void dump_phase_(float phase_[], int L) {
- int l;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fphase_ == NULL) {
- sprintf(s,"%s_phase_.txt", prefix);
- fphase_ = fopen(s, "wt");
- assert(fphase_ != NULL);
- }
-
- for(l=1; l<=L; l++)
- fprintf(fphase_,"%f\t",phase_[l]);
- for(l=L+1; l<MAX_AMP; l++)
- fprintf(fphase_,"%f\t",0.0);
- fprintf(fphase_,"\n");
-}
-
-
-void dump_hephase(int ind[], int dim) {
- int m;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fhephase == NULL) {
- sprintf(s,"%s_hephase.txt", prefix);
- fhephase = fopen(s, "wt");
- assert(fhephase != NULL);
- }
-
- for(m=0; m<dim; m++)
- fprintf(fhephase,"%d\t",ind[m]);
- fprintf(fhephase,"\n");
-}
-
-
-void dump_snr(float snr) {
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fsnr == NULL) {
- sprintf(s,"%s_snr.txt", prefix);
- fsnr = fopen(s, "wt");
- assert(fsnr != NULL);
- }
-
- fprintf(fsnr,"%f\n",snr);
-}
-
-void dump_lpc_snr(float snr) {
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (flpcsnr == NULL) {
- sprintf(s,"%s_lpc_snr.txt", prefix);
- flpcsnr = fopen(s, "wt");
- assert(flpcsnr != NULL);
- }
-
- fprintf(flpcsnr,"%f\n",snr);
-}
-
-/* Pw "before" post filter so we can plot before and after */
-
-void dump_Pwb(COMP Pwb[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fpwb == NULL) {
- sprintf(s,"%s_pwb.txt", prefix);
- fpwb = fopen(s, "wt");
- assert(fpwb != NULL);
- }
-
- for(i=0; i<FFT_ENC/2; i++)
- fprintf(fpwb,"%f\t",Pwb[i].real);
- fprintf(fpwb,"\n");
-}
-
-void dump_Pw(COMP Pw[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fpw == NULL) {
- sprintf(s,"%s_pw.txt", prefix);
- fpw = fopen(s, "wt");
- assert(fpw != NULL);
- }
-
- for(i=0; i<FFT_ENC/2; i++)
- fprintf(fpw,"%f\t",Pw[i].real);
- fprintf(fpw,"\n");
-}
-
-void dump_Rw(float Rw[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (frw == NULL) {
- sprintf(s,"%s_rw.txt", prefix);
- frw = fopen(s, "wt");
- assert(frw != NULL);
- }
-
- for(i=0; i<FFT_ENC/2; i++)
- fprintf(frw,"%f\t",Rw[i]);
- fprintf(frw,"\n");
-}
-
-void dump_weights(float w[], int order) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fweights == NULL) {
- sprintf(s,"%s_weights.txt", prefix);
- fweights = fopen(s, "wt");
- assert(fweights != NULL);
- }
-
- for(i=0; i<order; i++)
- fprintf(fweights,"%f\t", w[i]);
- fprintf(fweights,"\n");
-}
-
-void dump_lsp(float lsp[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (flsp == NULL) {
- sprintf(s,"%s_lsp.txt", prefix);
- flsp = fopen(s, "wt");
- assert(flsp != NULL);
- }
-
- for(i=0; i<10; i++)
- fprintf(flsp,"%f\t",lsp[i]);
- fprintf(flsp,"\n");
-}
-
-void dump_lsp_(float lsp_[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (flsp_ == NULL) {
- sprintf(s,"%s_lsp_.txt", prefix);
- flsp_ = fopen(s, "wt");
- assert(flsp_ != NULL);
- }
-
- for(i=0; i<10; i++)
- fprintf(flsp_,"%f\t",lsp_[i]);
- fprintf(flsp_,"\n");
-}
-
-void dump_ak(float ak[], int order) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fak == NULL) {
- sprintf(s,"%s_ak.txt", prefix);
- fak = fopen(s, "wt");
- assert(fak != NULL);
- }
-
- for(i=0; i<=order; i++)
- fprintf(fak,"%f\t",ak[i]);
- fprintf(fak,"\n");
-}
-
-void dump_ak_(float ak_[], int order) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fak_ == NULL) {
- sprintf(s,"%s_ak_.txt", prefix);
- fak_ = fopen(s, "wt");
- assert(fak_ != NULL);
- }
-
- for(i=0; i<=order; i++)
- fprintf(fak_,"%f\t",ak_[i]);
- fprintf(fak_,"\n");
-}
-
-void dump_Fw(COMP Fw[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (ffw == NULL) {
- sprintf(s,"%s_fw.txt", prefix);
- ffw = fopen(s, "wt");
- assert(ffw != NULL);
- }
-
- for(i=0; i<256; i++)
- fprintf(ffw,"%f\t",Fw[i].real);
- fprintf(ffw,"\n");
-}
-
-void dump_e(float e_hz[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fe == NULL) {
- sprintf(s,"%s_e.txt", prefix);
- fe = fopen(s, "wt");
- assert(fe != NULL);
- }
-
- for(i=0; i<500/2; i++)
- fprintf(fe,"%f\t",e_hz[i]);
- fprintf(fe,"\n");
- for(i=500/2; i<500; i++)
- fprintf(fe,"%f\t",e_hz[i]);
- fprintf(fe,"\n");
-}
-
-void dump_sq(float sq[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fsq == NULL) {
- sprintf(s,"%s_sq.txt", prefix);
- fsq = fopen(s, "wt");
- assert(fsq != NULL);
- }
-
- for(i=0; i<M/2; i++)
- fprintf(fsq,"%f\t",sq[i]);
- fprintf(fsq,"\n");
- for(i=M/2; i<M; i++)
- fprintf(fsq,"%f\t",sq[i]);
- fprintf(fsq,"\n");
-}
-
-void dump_dec(COMP Fw[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fdec == NULL) {
- sprintf(s,"%s_dec.txt", prefix);
- fdec = fopen(s, "wt");
- assert(fdec != NULL);
- }
-
- for(i=0; i<320/5; i++)
- fprintf(fdec,"%f\t",Fw[i].real);
- fprintf(fdec,"\n");
-}
-
-void dump_bg(float e, float bg_est, float percent_uv) {
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fbg == NULL) {
- sprintf(s,"%s_bg.txt", prefix);
- fbg = fopen(s, "wt");
- assert(fbg != NULL);
- }
-
- fprintf(fbg,"%f\t%f\t%f\n", e, bg_est, percent_uv);
-}
-
-void dump_E(float E) {
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (fE == NULL) {
- sprintf(s,"%s_E.txt", prefix);
- fE = fopen(s, "wt");
- assert(fE != NULL);
- }
-
- fprintf(fE,"%f\n", 10.0*log10(E));
-}
-
-void dump_Rk(float Rk[]) {
- int i;
- char s[MAX_STR];
-
- if (!dumpon) return;
-
- if (frk == NULL) {
- sprintf(s,"%s_rk.txt", prefix);
- frk = fopen(s, "wt");
- assert(frk != NULL);
- }
-
- for(i=0; i<P_MAX; i++)
- fprintf(frk,"%f\t",Rk[i]);
- fprintf(frk,"\n");
-}
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: dump.h
- AUTHOR......: David Rowe
- DATE CREATED: 25/8/09
-
- Routines to dump data to text files for Octave analysis.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __DUMP__
-#define __DUMP__
-
-#include "comp.h"
-
-void dump_on(char filename_prefix[]);
-void dump_off();
-
-void dump_Sn(float Sn[]);
-void dump_Sw(COMP Sw[]);
-void dump_Sw_(COMP Sw_[]);
-void dump_Ew(COMP Ew[]);
-
-/* amplitude modelling */
-
-void dump_model(MODEL *m);
-void dump_quantised_model(MODEL *m);
-void dump_Pwn(COMP Pw[]);
-void dump_Pw(COMP Pw[]);
-void dump_Rw(float Rw[]);
-void dump_lsp(float lsp[]);
-void dump_weights(float w[], int ndim);
-void dump_lsp_(float lsp_[]);
-void dump_ak(float ak[], int order);
-void dump_ak_(float ak[], int order);
-void dump_E(float E);
-void dump_lpc_snr(float snr);
-
-/* phase modelling */
-
-void dump_snr(float snr);
-void dump_phase(float phase[], int L);
-void dump_phase_(float phase[], int L);
-void dump_hephase(int ind[], int dim);
-
-/* NLP states */
-
-void dump_sq(float sq[]);
-void dump_dec(COMP Fw[]);
-void dump_Fw(COMP Fw[]);
-void dump_e(float e_hz[]);
-void dump_Rk(float Rk[]);
-
-/* post filter */
-
-void dump_bg(float e, float bg_est, float percent_uv);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv.c
- AUTHOR......: David Rowe
- DATE CREATED: April 14 2012
-
- Functions that implement the FDMDV modem.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/*---------------------------------------------------------------------------*\
-
- INCLUDES
-
-\*---------------------------------------------------------------------------*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-
-#include "fdmdv_internal.h"
-#include "fdmdv.h"
-#include "rn.h"
-#include "test_bits.h"
-#include "pilot_coeff.h"
-#include "kiss_fft.h"
-#include "hanning.h"
-#include "os.h"
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*---------------------------------------------------------------------------*/
-
-static COMP cneg(COMP a)
-{
- COMP res;
-
- res.real = -a.real;
- res.imag = -a.imag;
-
- return res;
-}
-
-static COMP cconj(COMP a)
-{
- COMP res;
-
- res.real = a.real;
- res.imag = -a.imag;
-
- return res;
-}
-
-static COMP cmult(COMP a, COMP b)
-{
- COMP res;
-
- res.real = a.real*b.real - a.imag*b.imag;
- res.imag = a.real*b.imag + a.imag*b.real;
-
- return res;
-}
-
-static COMP fcmult(float a, COMP b)
-{
- COMP res;
-
- res.real = a*b.real;
- res.imag = a*b.imag;
-
- return res;
-}
-
-static COMP cadd(COMP a, COMP b)
-{
- COMP res;
-
- res.real = a.real + b.real;
- res.imag = a.imag + b.imag;
-
- return res;
-}
-
-static float cabsolute(COMP a)
-{
- return sqrt(pow(a.real, 2.0) + pow(a.imag, 2.0));
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_create
- AUTHOR......: David Rowe
- DATE CREATED: 16/4/2012
-
- Create and initialise an instance of the modem. Returns a pointer
- to the modem states or NULL on failure. One set of states is
- sufficient for a full duplex modem.
-
-\*---------------------------------------------------------------------------*/
-
-struct FDMDV * CODEC2_WIN32SUPPORT fdmdv_create(void)
-{
- struct FDMDV *f;
- int c, i, k;
- float carrier_freq;
-
- assert(FDMDV_BITS_PER_FRAME == NC*NB);
- assert(FDMDV_NOM_SAMPLES_PER_FRAME == M);
- assert(FDMDV_MAX_SAMPLES_PER_FRAME == (M+M/P));
-
- f = (struct FDMDV*)malloc(sizeof(struct FDMDV));
- if (f == NULL)
- return NULL;
-
- f->current_test_bit = 0;
- for(i=0; i<NTEST_BITS; i++)
- f->rx_test_bits_mem[i] = 0;
-
- f->tx_pilot_bit = 0;
-
- for(c=0; c<NC+1; c++) {
- f->prev_tx_symbols[c].real = 1.0;
- f->prev_tx_symbols[c].imag = 0.0;
- f->prev_rx_symbols[c].real = 1.0;
- f->prev_rx_symbols[c].imag = 0.0;
-
- for(k=0; k<NSYM; k++) {
- f->tx_filter_memory[c][k].real = 0.0;
- f->tx_filter_memory[c][k].imag = 0.0;
- }
-
- for(k=0; k<NFILTER; k++) {
- f->rx_filter_memory[c][k].real = 0.0;
- f->rx_filter_memory[c][k].imag = 0.0;
- }
-
- /* Spread initial FDM carrier phase out as far as possible.
- This helped PAPR for a few dB. We don't need to adjust rx
- phase as DQPSK takes care of that. */
-
- f->phase_tx[c].real = cos(2.0*PI*c/(NC+1));
- f->phase_tx[c].imag = sin(2.0*PI*c/(NC+1));
-
- f->phase_rx[c].real = 1.0;
- f->phase_rx[c].imag = 0.0;
-
- for(k=0; k<NT*P; k++) {
- f->rx_filter_mem_timing[c][k].real = 0.0;
- f->rx_filter_mem_timing[c][k].imag = 0.0;
- }
- for(k=0; k<NFILTERTIMING; k++) {
- f->rx_baseband_mem_timing[c][k].real = 0.0;
- f->rx_baseband_mem_timing[c][k].imag = 0.0;
- }
- }
-
- /* Set up frequency of each carrier */
-
- for(c=0; c<NC/2; c++) {
- carrier_freq = (-NC/2 + c)*FSEP + FDMDV_FCENTRE;
- f->freq[c].real = cos(2.0*PI*carrier_freq/FS);
- f->freq[c].imag = sin(2.0*PI*carrier_freq/FS);
- }
-
- for(c=NC/2; c<NC; c++) {
- carrier_freq = (-NC/2 + c + 1)*FSEP + FDMDV_FCENTRE;
- f->freq[c].real = cos(2.0*PI*carrier_freq/FS);
- f->freq[c].imag = sin(2.0*PI*carrier_freq/FS);
- }
-
- f->freq[NC].real = cos(2.0*PI*FDMDV_FCENTRE/FS);
- f->freq[NC].imag = sin(2.0*PI*FDMDV_FCENTRE/FS);
-
- /* Generate DBPSK pilot Look Up Table (LUT) */
-
- generate_pilot_lut(f->pilot_lut, &f->freq[NC]);
-
- /* freq Offset estimation states */
-
- f->fft_pilot_cfg = kiss_fft_alloc (MPILOTFFT, 0, NULL, NULL);
- assert(f->fft_pilot_cfg != NULL);
-
- for(i=0; i<NPILOTBASEBAND; i++) {
- f->pilot_baseband1[i].real = f->pilot_baseband2[i].real = 0.0;
- f->pilot_baseband1[i].imag = f->pilot_baseband2[i].imag = 0.0;
- }
- f->pilot_lut_index = 0;
- f->prev_pilot_lut_index = 3*M;
-
- for(i=0; i<NPILOTLPF; i++) {
- f->pilot_lpf1[i].real = f->pilot_lpf2[i].real = 0.0;
- f->pilot_lpf1[i].imag = f->pilot_lpf2[i].imag = 0.0;
- }
-
- f->foff = 0.0;
- f->foff_rect.real = 1.0;
- f->foff_rect.imag = 0.0;
- f->foff_phase_rect.real = 1.0;
- f->foff_phase_rect.imag = 0.0;
-
- f->fest_state = 0;
- f->coarse_fine = COARSE;
-
- for(c=0; c<NC+1; c++) {
- f->sig_est[c] = 0.0;
- f->noise_est[c] = 0.0;
- }
-
- for(i=0; i<2*FDMDV_NSPEC; i++)
- f->fft_buf[i] = 0.0;
- f->fft_cfg = kiss_fft_alloc (2*FDMDV_NSPEC, 0, NULL, NULL);
- assert(f->fft_cfg != NULL);
-
-
- return f;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_destroy
- AUTHOR......: David Rowe
- DATE CREATED: 16/4/2012
-
- Destroy an instance of the modem.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_destroy(struct FDMDV *fdmdv)
-{
- assert(fdmdv != NULL);
- KISS_FFT_FREE(fdmdv->fft_pilot_cfg);
- KISS_FFT_FREE(fdmdv->fft_cfg);
- free(fdmdv);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_get_test_bits()
- AUTHOR......: David Rowe
- DATE CREATED: 16/4/2012
-
- Generate a frame of bits from a repeating sequence of random data. OK so
- it's not very random if it repeats but it makes syncing at the demod easier
- for test purposes.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_get_test_bits(struct FDMDV *f, int tx_bits[])
-{
- int i;
-
- for(i=0; i<FDMDV_BITS_PER_FRAME; i++) {
- tx_bits[i] = test_bits[f->current_test_bit];
- f->current_test_bit++;
- if (f->current_test_bit > (NTEST_BITS-1))
- f->current_test_bit = 0;
- }
- }
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: bits_to_dqpsk_symbols()
- AUTHOR......: David Rowe
- DATE CREATED: 16/4/2012
-
- Maps bits to parallel DQPSK symbols. Generate Nc+1 QPSK symbols from
- vector of (1,Nc*Nb) input tx_bits. The Nc+1 symbol is the +1 -1 +1
- .... BPSK sync carrier.
-
-\*---------------------------------------------------------------------------*/
-
-void bits_to_dqpsk_symbols(COMP tx_symbols[], COMP prev_tx_symbols[], int tx_bits[], int *pilot_bit)
-{
- int c, msb, lsb;
- COMP j = {0.0,1.0};
-
- /* map tx_bits to to Nc DQPSK symbols */
-
- for(c=0; c<NC; c++) {
- msb = tx_bits[2*c];
- lsb = tx_bits[2*c+1];
- if ((msb == 0) && (lsb == 0))
- tx_symbols[c] = prev_tx_symbols[c];
- if ((msb == 0) && (lsb == 1))
- tx_symbols[c] = cmult(j, prev_tx_symbols[c]);
- if ((msb == 1) && (lsb == 0))
- tx_symbols[c] = cneg(prev_tx_symbols[c]);
- if ((msb == 1) && (lsb == 1))
- tx_symbols[c] = cmult(cneg(j),prev_tx_symbols[c]);
- }
-
- /* +1 -1 +1 -1 BPSK sync carrier, once filtered becomes (roughly)
- two spectral lines at +/- Rs/2 */
-
- if (*pilot_bit)
- tx_symbols[NC] = cneg(prev_tx_symbols[NC]);
- else
- tx_symbols[NC] = prev_tx_symbols[NC];
-
- if (*pilot_bit)
- *pilot_bit = 0;
- else
- *pilot_bit = 1;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: tx_filter()
- AUTHOR......: David Rowe
- DATE CREATED: 17/4/2012
-
- Given NC*NB bits construct M samples (1 symbol) of NC+1 filtered
- symbols streams.
-
-\*---------------------------------------------------------------------------*/
-
-void tx_filter(COMP tx_baseband[NC+1][M], COMP tx_symbols[], COMP tx_filter_memory[NC+1][NSYM])
-{
- int c;
- int i,j,k;
- float acc;
- COMP gain;
-
- gain.real = sqrt(2.0)/2.0;
- gain.imag = 0.0;
-
- /*
- for(c=0; c<NC+1; c++)
- tx_filter_memory[c][NFILTER-1] = cmult(tx_symbols[c], gain);
- */
- for(c=0; c<NC+1; c++)
- tx_filter_memory[c][NSYM-1] = cmult(tx_symbols[c], gain);
-
-
- /*
- tx filter each symbol, generate M filtered output samples for each symbol.
- Efficient polyphase filter techniques used as tx_filter_memory is sparse
- */
-
- for(i=0; i<M; i++) {
- for(c=0; c<NC+1; c++) {
-
- /* filter real sample of symbol for carrier c */
-
- acc = 0.0;
- for(j=0,k=M-i-1; j<NSYM; j++,k+=M)
- acc += M * tx_filter_memory[c][j].real * gt_alpha5_root[k];
- tx_baseband[c][i].real = acc;
-
- /* filter imag sample of symbol for carrier c */
-
- acc = 0.0;
- for(j=0,k=M-i-1; j<NSYM; j++,k+=M)
- acc += M * tx_filter_memory[c][j].imag * gt_alpha5_root[k];
- tx_baseband[c][i].imag = acc;
-
- }
- }
-
- /* shift memory, inserting zeros at end */
-
- for(i=0; i<NSYM-1; i++)
- for(c=0; c<NC+1; c++)
- tx_filter_memory[c][i] = tx_filter_memory[c][i+1];
-
- for(c=0; c<NC+1; c++) {
- tx_filter_memory[c][NSYM-1].real = 0.0;
- tx_filter_memory[c][NSYM-1].imag = 0.0;
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdm_upconvert()
- AUTHOR......: David Rowe
- DATE CREATED: 17/4/2012
-
- Construct FDM signal by frequency shifting each filtered symbol
- stream. Returns complex signal so we can apply frequency offsets
- easily.
-
-\*---------------------------------------------------------------------------*/
-
-void fdm_upconvert(COMP tx_fdm[], COMP tx_baseband[NC+1][M], COMP phase_tx[], COMP freq[])
-{
- int i,c;
- COMP two = {2.0, 0.0};
- COMP pilot;
-
- for(i=0; i<M; i++) {
- tx_fdm[i].real = 0.0;
- tx_fdm[i].imag = 0.0;
- }
-
- /* Nc/2 tones below centre freq */
-
- for (c=0; c<NC/2; c++)
- for (i=0; i<M; i++) {
- phase_tx[c] = cmult(phase_tx[c], freq[c]);
- tx_fdm[i] = cadd(tx_fdm[i], cmult(tx_baseband[c][i], phase_tx[c]));
- }
-
- /* Nc/2 tones above centre freq */
-
- for (c=NC/2; c<NC; c++)
- for (i=0; i<M; i++) {
- phase_tx[c] = cmult(phase_tx[c], freq[c]);
- tx_fdm[i] = cadd(tx_fdm[i], cmult(tx_baseband[c][i], phase_tx[c]));
- }
-
- /* add centre pilot tone */
-
- c = NC;
- for (i=0; i<M; i++) {
- phase_tx[c] = cmult(phase_tx[c], freq[c]);
- pilot = cmult(cmult(two, tx_baseband[c][i]), phase_tx[c]);
- tx_fdm[i] = cadd(tx_fdm[i], pilot);
- }
-
- /*
- Scale such that total Carrier power C of real(tx_fdm) = Nc. This
- excludes the power of the pilot tone.
- We return the complex (single sided) signal to make frequency
- shifting for the purpose of testing easier
- */
-
- for (i=0; i<M; i++)
- tx_fdm[i] = cmult(two, tx_fdm[i]);
-
- /* normalise digital oscilators as the magnitude can drfift over time */
-
- for (c=0; c<NC+1; c++) {
- phase_tx[c].real /= cabsolute(phase_tx[c]);
- phase_tx[c].imag /= cabsolute(phase_tx[c]);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_mod()
- AUTHOR......: David Rowe
- DATE CREATED: 26/4/2012
-
- FDMDV modulator, take a frame of FDMDV_BITS_PER_FRAME bits and
- generates a frame of FDMDV_SAMPLES_PER_FRAME modulated symbols.
- Sync bit is returned to aid alignment of your next frame.
-
- The sync_bit value returned will be used for the _next_ frame.
-
- The output signal is complex to support single sided frequency
- shifting, for example when testing frequency offsets in channel
- simulation.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_mod(struct FDMDV *fdmdv, COMP tx_fdm[],
- int tx_bits[], int *sync_bit)
-{
- COMP tx_symbols[NC+1];
- COMP tx_baseband[NC+1][M];
-
- bits_to_dqpsk_symbols(tx_symbols, fdmdv->prev_tx_symbols, tx_bits, &fdmdv->tx_pilot_bit);
- memcpy(fdmdv->prev_tx_symbols, tx_symbols, sizeof(COMP)*(NC+1));
- tx_filter(tx_baseband, tx_symbols, fdmdv->tx_filter_memory);
- fdm_upconvert(tx_fdm, tx_baseband, fdmdv->phase_tx, fdmdv->freq);
-
- *sync_bit = fdmdv->tx_pilot_bit;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: generate_pilot_fdm()
- AUTHOR......: David Rowe
- DATE CREATED: 19/4/2012
-
- Generate M samples of DBPSK pilot signal for Freq offset estimation.
-
-\*---------------------------------------------------------------------------*/
-
-void generate_pilot_fdm(COMP *pilot_fdm, int *bit, float *symbol,
- float *filter_mem, COMP *phase, COMP *freq)
-{
- int i,j,k;
- float tx_baseband[M];
-
- /* +1 -1 +1 -1 DBPSK sync carrier, once filtered becomes (roughly)
- two spectral lines at +/- RS/2 */
-
- if (*bit)
- *symbol = -*symbol;
- else
- *symbol = *symbol;
- if (*bit)
- *bit = 0;
- else
- *bit = 1;
-
- /* filter DPSK symbol to create M baseband samples */
-
- filter_mem[NFILTER-1] = (sqrt(2)/2) * *symbol;
- for(i=0; i<M; i++) {
- tx_baseband[i] = 0.0;
- for(j=M-1,k=M-i-1; j<NFILTER; j+=M,k+=M)
- tx_baseband[i] += M * filter_mem[j] * gt_alpha5_root[k];
- }
-
- /* shift memory, inserting zeros at end */
-
- for(i=0; i<NFILTER-M; i++)
- filter_mem[i] = filter_mem[i+M];
-
- for(i=NFILTER-M; i<NFILTER; i++)
- filter_mem[i] = 0.0;
-
- /* upconvert */
-
- for(i=0; i<M; i++) {
- *phase = cmult(*phase, *freq);
- pilot_fdm[i].real = sqrt(2)*2*tx_baseband[i] * phase->real;
- pilot_fdm[i].imag = sqrt(2)*2*tx_baseband[i] * phase->imag;
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: generate_pilot_lut()
- AUTHOR......: David Rowe
- DATE CREATED: 19/4/2012
-
- Generate a 4M sample vector of DBPSK pilot signal. As the pilot signal
- is periodic in 4M samples we can then use this vector as a look up table
- for pilot signal generation in the demod.
-
-\*---------------------------------------------------------------------------*/
-
-void generate_pilot_lut(COMP pilot_lut[], COMP *pilot_freq)
-{
- int pilot_rx_bit = 0;
- float pilot_symbol = sqrt(2.0);
- COMP pilot_phase = {1.0, 0.0};
- float pilot_filter_mem[NFILTER];
- COMP pilot[M];
- int i,f;
-
- for(i=0; i<NFILTER; i++)
- pilot_filter_mem[i] = 0.0;
-
- /* discard first 4 symbols as filter memory is filling, just keep
- last four symbols */
-
- for(f=0; f<8; f++) {
- generate_pilot_fdm(pilot, &pilot_rx_bit, &pilot_symbol, pilot_filter_mem, &pilot_phase, pilot_freq);
- if (f >= 4)
- memcpy(&pilot_lut[M*(f-4)], pilot, M*sizeof(COMP));
- }
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: lpf_peak_pick()
- AUTHOR......: David Rowe
- DATE CREATED: 20/4/2012
-
- LPF and peak pick part of freq est, put in a function as we call it twice.
-
-\*---------------------------------------------------------------------------*/
-
-void lpf_peak_pick(float *foff, float *max, COMP pilot_baseband[],
- COMP pilot_lpf[], kiss_fft_cfg fft_pilot_cfg, COMP S[], int nin)
-{
- int i,j,k;
- int mpilot;
- COMP s[MPILOTFFT];
- float mag, imax;
- int ix;
- float r;
-
- /* LPF cutoff 200Hz, so we can handle max +/- 200 Hz freq offset */
-
- for(i=0; i<NPILOTLPF-nin; i++)
- pilot_lpf[i] = pilot_lpf[nin+i];
- for(i=NPILOTLPF-nin, j=0; i<NPILOTLPF; i++,j++) {
- pilot_lpf[i].real = 0.0; pilot_lpf[i].imag = 0.0;
- for(k=0; k<NPILOTCOEFF; k++)
- pilot_lpf[i] = cadd(pilot_lpf[i], fcmult(pilot_coeff[k], pilot_baseband[j+k]));
- }
-
- /* decimate to improve DFT resolution, window and DFT */
-
- mpilot = FS/(2*200); /* calc decimation rate given new sample rate is twice LPF freq */
- for(i=0; i<MPILOTFFT; i++) {
- s[i].real = 0.0; s[i].imag = 0.0;
- }
- for(i=0,j=0; i<NPILOTLPF; i+=mpilot,j++) {
- s[j] = fcmult(hanning[i], pilot_lpf[i]);
- }
-
- kiss_fft(fft_pilot_cfg, (kiss_fft_cpx *)s, (kiss_fft_cpx *)S);
-
- /* peak pick and convert to Hz */
-
- imax = 0.0;
- ix = 0;
- for(i=0; i<MPILOTFFT; i++) {
- mag = S[i].real*S[i].real + S[i].imag*S[i].imag;
- if (mag > imax) {
- imax = mag;
- ix = i;
- }
- }
- r = 2.0*200.0/MPILOTFFT; /* maps FFT bin to frequency in Hz */
-
- if (ix >= MPILOTFFT/2)
- *foff = (ix - MPILOTFFT)*r;
- else
- *foff = (ix)*r;
- *max = imax;
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: rx_est_freq_offset()
- AUTHOR......: David Rowe
- DATE CREATED: 19/4/2012
-
- Estimate frequency offset of FDM signal using BPSK pilot. Note that
- this algorithm is quite sensitive to pilot tone level wrt other
- carriers, so test variations to the pilot amplitude carefully.
-
-\*---------------------------------------------------------------------------*/
-
-float rx_est_freq_offset(struct FDMDV *f, COMP rx_fdm[], int nin)
-{
- int i,j;
- COMP pilot[M+M/P];
- COMP prev_pilot[M+M/P];
- float foff, foff1, foff2;
- float max1, max2;
-
- assert(nin <= M+M/P);
-
- /* get pilot samples used for correlation/down conversion of rx signal */
-
- for (i=0; i<nin; i++) {
- pilot[i] = f->pilot_lut[f->pilot_lut_index];
- f->pilot_lut_index++;
- if (f->pilot_lut_index >= 4*M)
- f->pilot_lut_index = 0;
-
- prev_pilot[i] = f->pilot_lut[f->prev_pilot_lut_index];
- f->prev_pilot_lut_index++;
- if (f->prev_pilot_lut_index >= 4*M)
- f->prev_pilot_lut_index = 0;
- }
-
- /*
- Down convert latest M samples of pilot by multiplying by ideal
- BPSK pilot signal we have generated locally. The peak of the
- resulting signal is sensitive to the time shift between the
- received and local version of the pilot, so we do it twice at
- different time shifts and choose the maximum.
- */
-
- for(i=0; i<NPILOTBASEBAND-nin; i++) {
- f->pilot_baseband1[i] = f->pilot_baseband1[i+nin];
- f->pilot_baseband2[i] = f->pilot_baseband2[i+nin];
- }
-
- for(i=0,j=NPILOTBASEBAND-nin; i<nin; i++,j++) {
- f->pilot_baseband1[j] = cmult(rx_fdm[i], cconj(pilot[i]));
- f->pilot_baseband2[j] = cmult(rx_fdm[i], cconj(prev_pilot[i]));
- }
-
- lpf_peak_pick(&foff1, &max1, f->pilot_baseband1, f->pilot_lpf1, f->fft_pilot_cfg, f->S1, nin);
- lpf_peak_pick(&foff2, &max2, f->pilot_baseband2, f->pilot_lpf2, f->fft_pilot_cfg, f->S2, nin);
-
- if (max1 > max2)
- foff = foff1;
- else
- foff = foff2;
-
- return foff;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_freq_shift()
- AUTHOR......: David Rowe
- DATE CREATED: 26/4/2012
-
- Frequency shift modem signal. The use of complex input and output allows
- single sided frequency shifting (no images).
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_freq_shift(COMP rx_fdm_fcorr[], COMP rx_fdm[], float foff,
- COMP *foff_rect, COMP *foff_phase_rect, int nin)
-{
- int i;
-
- foff_rect->real = cos(2.0*PI*foff/FS);
- foff_rect->imag = sin(2.0*PI*foff/FS);
- for(i=0; i<nin; i++) {
- *foff_phase_rect = cmult(*foff_phase_rect, *foff_rect);
- rx_fdm_fcorr[i] = cmult(rx_fdm[i], *foff_phase_rect);
- }
-
- /* normalise digital oscilator as the magnitude can drfift over time */
-
- foff_phase_rect->real /= cabsolute(*foff_phase_rect);
- foff_phase_rect->imag /= cabsolute(*foff_phase_rect);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdm_downconvert()
- AUTHOR......: David Rowe
- DATE CREATED: 22/4/2012
-
- Frequency shift each modem carrier down to Nc+1 baseband signals.
-
-\*---------------------------------------------------------------------------*/
-
-void fdm_downconvert(COMP rx_baseband[NC+1][M+M/P], COMP rx_fdm[], COMP phase_rx[], COMP freq[], int nin)
-{
- int i,c;
-
- /* maximum number of input samples to demod */
-
- assert(nin <= (M+M/P));
-
- /* Nc/2 tones below centre freq */
-
- for (c=0; c<NC/2; c++)
- for (i=0; i<nin; i++) {
- phase_rx[c] = cmult(phase_rx[c], freq[c]);
- rx_baseband[c][i] = cmult(rx_fdm[i], cconj(phase_rx[c]));
- }
-
- /* Nc/2 tones above centre freq */
-
- for (c=NC/2; c<NC; c++)
- for (i=0; i<nin; i++) {
- phase_rx[c] = cmult(phase_rx[c], freq[c]);
- rx_baseband[c][i] = cmult(rx_fdm[i], cconj(phase_rx[c]));
- }
-
- /* centre pilot tone */
-
- c = NC;
- for (i=0; i<nin; i++) {
- phase_rx[c] = cmult(phase_rx[c], freq[c]);
- rx_baseband[c][i] = cmult(rx_fdm[i], cconj(phase_rx[c]));
- }
-
- /* normalise digital oscilators as the magnitude can drfift over time */
-
- for (c=0; c<NC+1; c++) {
- phase_rx[c].real /= cabsolute(phase_rx[c]);
- phase_rx[c].imag /= cabsolute(phase_rx[c]);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: rx_filter()
- AUTHOR......: David Rowe
- DATE CREATED: 22/4/2012
-
- Receive filter each baseband signal at oversample rate P. Filtering at
- rate P lowers CPU compared to rate M.
-
- Depending on the number of input samples to the demod nin, we
- produce P-1, P (usually), or P+1 filtered samples at rate P. nin is
- occasionally adjusted to compensate for timing slips due to
- different tx and rx sample clocks.
-
-\*---------------------------------------------------------------------------*/
-
-void rx_filter(COMP rx_filt[NC+1][P+1], COMP rx_baseband[NC+1][M+M/P], COMP rx_filter_memory[NC+1][NFILTER], int nin)
-{
- int c, i,j,k,l;
- int n=M/P;
-
- /* rx filter each symbol, generate P filtered output samples for
- each symbol. Note we keep filter memory at rate M, it's just
- the filter output at rate P */
-
- for(i=0, j=0; i<nin; i+=n,j++) {
-
- /* latest input sample */
-
- for(c=0; c<NC+1; c++)
- for(k=NFILTER-n,l=i; k<NFILTER; k++,l++)
- rx_filter_memory[c][k] = rx_baseband[c][l];
-
- /* convolution (filtering) */
-
- for(c=0; c<NC+1; c++) {
- rx_filt[c][j].real = 0.0; rx_filt[c][j].imag = 0.0;
- for(k=0; k<NFILTER; k++)
- rx_filt[c][j] = cadd(rx_filt[c][j], fcmult(gt_alpha5_root[k], rx_filter_memory[c][k]));
- }
-
- /* make room for next input sample */
-
- for(c=0; c<NC+1; c++)
- for(k=0,l=n; k<NFILTER-n; k++,l++)
- rx_filter_memory[c][k] = rx_filter_memory[c][l];
- }
-
- assert(j <= (P+1)); /* check for any over runs */
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: rx_est_timing()
- AUTHOR......: David Rowe
- DATE CREATED: 23/4/2012
-
- Estimate optimum timing offset, re-filter receive symbols at optimum
- timing estimate.
-
-\*---------------------------------------------------------------------------*/
-
-float rx_est_timing(COMP rx_symbols[],
- COMP rx_filt[NC+1][P+1],
- COMP rx_baseband[NC+1][M+M/P],
- COMP rx_filter_mem_timing[NC+1][NT*P],
- float env[],
- COMP rx_baseband_mem_timing[NC+1][NFILTERTIMING],
- int nin)
-{
- int c,i,j,k;
- int adjust, s;
- COMP x, phase, freq;
- float rx_timing;
-
- /*
- nin adjust
- --------------------------------
- 120 -1 (one less rate P sample)
- 160 0 (nominal)
- 200 1 (one more rate P sample)
- */
-
- adjust = P - nin*P/M;
-
- /* update buffer of NT rate P filtered symbols */
-
- for(c=0; c<NC+1; c++)
- for(i=0,j=P-adjust; i<(NT-1)*P+adjust; i++,j++)
- rx_filter_mem_timing[c][i] = rx_filter_mem_timing[c][j];
- for(c=0; c<NC+1; c++)
- for(i=(NT-1)*P+adjust,j=0; i<NT*P; i++,j++)
- rx_filter_mem_timing[c][i] = rx_filt[c][j];
-
- /* sum envelopes of all carriers */
-
- for(i=0; i<NT*P; i++) {
- env[i] = 0.0;
- for(c=0; c<NC+1; c++)
- env[i] += cabsolute(rx_filter_mem_timing[c][i]);
- }
-
- /* The envelope has a frequency component at the symbol rate. The
- phase of this frequency component indicates the timing. So work
- out single DFT at frequency 2*pi/P */
-
- x.real = 0.0; x.imag = 0.0;
- freq.real = cos(2*PI/P);
- freq.imag = sin(2*PI/P);
- phase.real = 1.0;
- phase.imag = 0.0;
-
- for(i=0; i<NT*P; i++) {
- x = cadd(x, fcmult(env[i], phase));
- phase = cmult(phase, freq);
- }
-
- /* Map phase to estimated optimum timing instant at rate M. The
- M/4 part was adjusted by experiment, I know not why.... */
-
- rx_timing = atan2(x.imag, x.real)*M/(2*PI) + M/4;
-
- if (rx_timing > M)
- rx_timing -= M;
- if (rx_timing < -M)
- rx_timing += M;
-
- /* rx_filt_mem_timing contains M + Nfilter + M samples of the
- baseband signal at rate M this enables us to resample the
- filtered rx symbol with M sample precision once we have
- rx_timing */
-
- for(c=0; c<NC+1; c++)
- for(i=0,j=nin; i<NFILTERTIMING-nin; i++,j++)
- rx_baseband_mem_timing[c][i] = rx_baseband_mem_timing[c][j];
- for(c=0; c<NC+1; c++)
- for(i=NFILTERTIMING-nin,j=0; i<NFILTERTIMING; i++,j++)
- rx_baseband_mem_timing[c][i] = rx_baseband[c][j];
-
- /* rx filter to get symbol for each carrier at estimated optimum
- timing instant. We use rate M filter memory to get fine timing
- resolution. */
-
- s = round(rx_timing) + M;
- for(c=0; c<NC+1; c++) {
- rx_symbols[c].real = 0.0;
- rx_symbols[c].imag = 0.0;
- for(k=s,j=0; k<s+NFILTER; k++,j++)
- rx_symbols[c] = cadd(rx_symbols[c], fcmult(gt_alpha5_root[j], rx_baseband_mem_timing[c][k]));
- }
-
- return rx_timing;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: qpsk_to_bits()
- AUTHOR......: David Rowe
- DATE CREATED: 24/4/2012
-
- Convert DQPSK symbols back to an array of bits, extracts sync bit
- from DBPSK pilot, and also uses pilot to estimate fine frequency
- error.
-
-\*---------------------------------------------------------------------------*/
-
-float qpsk_to_bits(int rx_bits[], int *sync_bit, COMP phase_difference[], COMP prev_rx_symbols[], COMP rx_symbols[])
-{
- int c;
- COMP pi_on_4;
- COMP d;
- int msb=0, lsb=0;
- float ferr;
-
- pi_on_4.real = cos(PI/4.0);
- pi_on_4.imag = sin(PI/4.0);
-
- /* Extra 45 degree clockwise lets us use real and imag axis as
- decision boundaries */
-
- for(c=0; c<NC; c++)
- phase_difference[c] = cmult(cmult(rx_symbols[c], cconj(prev_rx_symbols[c])), pi_on_4);
-
- /* map (Nc,1) DQPSK symbols back into an (1,Nc*Nb) array of bits */
-
- for (c=0; c<NC; c++) {
- d = phase_difference[c];
- if ((d.real >= 0) && (d.imag >= 0)) {
- msb = 0; lsb = 0;
- }
- if ((d.real < 0) && (d.imag >= 0)) {
- msb = 0; lsb = 1;
- }
- if ((d.real < 0) && (d.imag < 0)) {
- msb = 1; lsb = 0;
- }
- if ((d.real >= 0) && (d.imag < 0)) {
- msb = 1; lsb = 1;
- }
- rx_bits[2*c] = msb;
- rx_bits[2*c+1] = lsb;
- }
-
- /* Extract DBPSK encoded Sync bit and fine freq offset estimate */
-
- phase_difference[NC] = cmult(rx_symbols[NC], cconj(prev_rx_symbols[NC]));
- if (phase_difference[NC].real < 0) {
- *sync_bit = 1;
- ferr = phase_difference[NC].imag;
- }
- else {
- *sync_bit = 0;
- ferr = -phase_difference[NC].imag;
- }
-
- /* pilot carrier gets an extra pi/4 rotation to make it consistent
- with other carriers, as we need it for snr_update and scatter
- diagram */
-
- phase_difference[NC] = cmult(phase_difference[NC], pi_on_4);
-
- return ferr;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: snr_update()
- AUTHOR......: David Rowe
- DATE CREATED: 17 May 2012
-
- Given phase differences update estimates of signal and noise levels.
-
-\*---------------------------------------------------------------------------*/
-
-void snr_update(float sig_est[], float noise_est[], COMP phase_difference[])
-{
- float s[NC+1];
- COMP refl_symbols[NC+1];
- float n[NC+1];
- COMP pi_on_4;
- int c;
-
- pi_on_4.real = cos(PI/4.0);
- pi_on_4.imag = sin(PI/4.0);
-
- /* mag of each symbol is distance from origin, this gives us a
- vector of mags, one for each carrier. */
-
- for(c=0; c<NC+1; c++)
- s[c] = cabsolute(phase_difference[c]);
-
- /* signal mag estimate for each carrier is a smoothed version of
- instantaneous magntitude, this gives us a vector of smoothed
- mag estimates, one for each carrier. */
-
- for(c=0; c<NC+1; c++)
- sig_est[c] = SNR_COEFF*sig_est[c] + (1.0 - SNR_COEFF)*s[c];
-
- /* noise mag estimate is distance of current symbol from average
- location of that symbol. We reflect all symbols into the first
- quadrant for convenience. */
-
- for(c=0; c<NC+1; c++) {
- refl_symbols[c].real = fabs(phase_difference[c].real);
- refl_symbols[c].imag = fabs(phase_difference[c].imag);
- n[c] = cabsolute(cadd(fcmult(sig_est[c], pi_on_4), cneg(refl_symbols[c])));
- }
-
- /* noise mag estimate for each carrier is a smoothed version of
- instantaneous noise mag, this gives us a vector of smoothed
- noise power estimates, one for each carrier. */
-
- for(c=0; c<NC+1; c++)
- noise_est[c] = SNR_COEFF*noise_est[c] + (1 - SNR_COEFF)*n[c];
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_put_test_bits()
- AUTHOR......: David Rowe
- DATE CREATED: 24/4/2012
-
- Accepts nbits from rx and attempts to sync with test_bits sequence.
- If sync OK measures bit errors.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_put_test_bits(struct FDMDV *f, int *sync,
- int *bit_errors, int *ntest_bits,
- int rx_bits[])
-{
- int i,j;
- float ber;
-
- /* Append to our memory */
-
- for(i=0,j=FDMDV_BITS_PER_FRAME; i<NTEST_BITS-FDMDV_BITS_PER_FRAME; i++,j++)
- f->rx_test_bits_mem[i] = f->rx_test_bits_mem[j];
- for(i=NTEST_BITS-FDMDV_BITS_PER_FRAME,j=0; i<NTEST_BITS; i++,j++)
- f->rx_test_bits_mem[i] = rx_bits[j];
-
- /* see how many bit errors we get when checked against test sequence */
-
- *bit_errors = 0;
- for(i=0; i<NTEST_BITS; i++) {
- *bit_errors += test_bits[i] ^ f->rx_test_bits_mem[i];
- //printf("%d %d %d %d\n", i, test_bits[i], f->rx_test_bits_mem[i], test_bits[i] ^ f->rx_test_bits_mem[i]);
- }
-
- /* if less than a thresh we are aligned and in sync with test sequence */
-
- ber = (float)*bit_errors/NTEST_BITS;
-
- *sync = 0;
- if (ber < 0.2)
- *sync = 1;
-
- *ntest_bits = NTEST_BITS;
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: freq_state(()
- AUTHOR......: David Rowe
- DATE CREATED: 24/4/2012
-
- Freq offset state machine. Moves between coarse and fine states
- based on BPSK pilot sequence. Freq offset estimator occasionally
- makes mistakes when used continuously. So we use it until we have
- acquired the BPSK pilot, then switch to a more robust "fine"
- tracking algorithm. If we lose sync we switch back to coarse mode
- for fast re-acquisition of large frequency offsets.
-
-\*---------------------------------------------------------------------------*/
-
-int freq_state(int sync_bit, int *state)
-{
- int next_state, coarse_fine;
-
- /* acquire state, look for 6 symbol 010101 sequence from sync bit */
-
- next_state = *state;
- switch(*state) {
- case 0:
- if (sync_bit == 0)
- next_state = 1;
- break;
- case 1:
- if (sync_bit == 1)
- next_state = 2;
- else
- next_state = 0;
- break;
- case 2:
- if (sync_bit == 0)
- next_state = 3;
- else
- next_state = 0;
- break;
- case 3:
- if (sync_bit == 1)
- next_state = 4;
- else
- next_state = 0;
- break;
- case 4:
- if (sync_bit == 0)
- next_state = 5;
- else
- next_state = 0;
- break;
- case 5:
- if (sync_bit == 1)
- next_state = 6;
- else
- next_state = 0;
- break;
-
- /* states 6 and above are track mode, make sure we keep
- getting 0101 sync bit sequence */
-
- case 6:
- if (sync_bit == 0)
- next_state = 7;
- else
- next_state = 0;
-
- break;
- case 7:
- if (sync_bit == 1)
- next_state = 6;
- else
- next_state = 0;
- break;
- }
-
- *state = next_state;
- if (*state >= 6)
- coarse_fine = FINE;
- else
- coarse_fine = COARSE;
-
- return coarse_fine;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_demod()
- AUTHOR......: David Rowe
- DATE CREATED: 26/4/2012
-
- FDMDV demodulator, take an array of FDMDV_SAMPLES_PER_FRAME
- modulated samples, returns an array of FDMDV_BITS_PER_FRAME bits,
- plus the sync bit.
-
- The input signal is complex to support single sided frequcny shifting
- before the demod input (e.g. fdmdv2 click to tune feature).
-
- The number of input samples nin will normally be M ==
- FDMDV_SAMPLES_PER_FRAME. However to adjust for differences in
- transmit and receive sample clocks nin will occasionally be M-M/P,
- or M+M/P.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_demod(struct FDMDV *fdmdv, int rx_bits[],
- int *sync_bit, COMP rx_fdm[], int *nin)
-{
- float foff_coarse, foff_fine;
- COMP rx_fdm_fcorr[M+M/P];
- COMP rx_baseband[NC+1][M+M/P];
- COMP rx_filt[NC+1][P+1];
- COMP rx_symbols[NC+1];
- float env[NT*P];
-
- /* freq offset estimation and correction */
-
- foff_coarse = rx_est_freq_offset(fdmdv, rx_fdm, *nin);
-
- if (fdmdv->coarse_fine == COARSE)
- fdmdv->foff = foff_coarse;
- fdmdv_freq_shift(rx_fdm_fcorr, rx_fdm, -fdmdv->foff, &fdmdv->foff_rect, &fdmdv->foff_phase_rect, *nin);
-
- /* baseband processing */
-
- fdm_downconvert(rx_baseband, rx_fdm_fcorr, fdmdv->phase_rx, fdmdv->freq, *nin);
- rx_filter(rx_filt, rx_baseband, fdmdv->rx_filter_memory, *nin);
- fdmdv->rx_timing = rx_est_timing(rx_symbols, rx_filt, rx_baseband, fdmdv->rx_filter_mem_timing, env, fdmdv->rx_baseband_mem_timing, *nin);
-
- /* Adjust number of input samples to keep timing within bounds */
-
- *nin = M;
-
- if (fdmdv->rx_timing > 2*M/P)
- *nin += M/P;
-
- if (fdmdv->rx_timing < 0)
- *nin -= M/P;
-
- foff_fine = qpsk_to_bits(rx_bits, sync_bit, fdmdv->phase_difference, fdmdv->prev_rx_symbols, rx_symbols);
- memcpy(fdmdv->prev_rx_symbols, rx_symbols, sizeof(COMP)*(NC+1));
- snr_update(fdmdv->sig_est, fdmdv->noise_est, fdmdv->phase_difference);
-
- /* freq offset estimation state machine */
-
- fdmdv->coarse_fine = freq_state(*sync_bit, &fdmdv->fest_state);
- fdmdv->foff -= TRACK_COEFF*foff_fine;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: calc_snr()
- AUTHOR......: David Rowe
- DATE CREATED: 17 May 2012
-
- Calculate current SNR estimate (3000Hz noise BW)
-
-\*---------------------------------------------------------------------------*/
-
-float calc_snr(float sig_est[], float noise_est[])
-{
- float S, SdB;
- float mean, N50, N50dB, N3000dB;
- float snr_dB;
- int c;
-
- S = 0.0;
- for(c=0; c<NC+1; c++)
- S += pow(sig_est[c], 2.0);
- SdB = 10.0*log10(S+1E-12);
-
- /* Average noise mag across all carriers and square to get an
- average noise power. This is an estimate of the noise power in
- Rs = 50Hz of BW (note for raised root cosine filters Rs is the
- noise BW of the filter) */
-
- mean = 0.0;
- for(c=0; c<NC+1; c++)
- mean += noise_est[c];
- mean /= (NC+1);
- N50 = pow(mean, 2.0);
- N50dB = 10.0*log10(N50+1E-12);
-
- /* Now multiply by (3000 Hz)/(50 Hz) to find the total noise power
- in 3000 Hz */
-
- N3000dB = N50dB + 10.0*log10(3000.0/RS);
-
- snr_dB = SdB - N3000dB;
-
- return snr_dB;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_get_demod_stats()
- AUTHOR......: David Rowe
- DATE CREATED: 1 May 2012
-
- Fills stats structure with a bunch of demod information.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_get_demod_stats(struct FDMDV *fdmdv,
- struct FDMDV_STATS *fdmdv_stats)
-{
- int c;
-
- fdmdv_stats->snr_est = calc_snr(fdmdv->sig_est, fdmdv->noise_est);
- fdmdv_stats->fest_coarse_fine = fdmdv->coarse_fine;
- fdmdv_stats->foff = fdmdv->foff;
- fdmdv_stats->rx_timing = fdmdv->rx_timing;
- fdmdv_stats->clock_offset = 0.0; /* TODO - implement clock offset estimation */
-
- assert((NC+1) == FDMDV_NSYM);
-
- for(c=0; c<NC+1; c++) {
- fdmdv_stats->rx_symbols[c] = fdmdv->phase_difference[c];
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_8_to_48()
- AUTHOR......: David Rowe
- DATE CREATED: 9 May 2012
-
- Changes the sample rate of a signal from 8 to 48 kHz. Experience
- with PC based modems has shown that PC sound cards have a more
- accurate sample clock when set for 48 kHz than 8 kHz.
-
- n is the number of samples at the 8 kHz rate, there are FDMDV_OS*n samples
- at the 48 kHz rate. A memory of FDMDV_OS_TAPS/FDMDV_OS samples is reqd for
- in8k[] (see t48_8.c unit test as example).
-
- This is a classic polyphase upsampler. We take the 8 kHz samples
- and insert (FDMDV_OS-1) zeroes between each sample, then
- FDMDV_OS_TAPS FIR low pass filter the signal at 4kHz. As most of
- the input samples are zeroes, we only need to multiply non-zero
- input samples by filter coefficients. The zero insertion and
- filtering are combined in the code below and I'm too lazy to explain
- it further right now....
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_8_to_48(float out48k[], float in8k[], int n)
-{
- int i,j,k,l;
-
- /* make sure n is an integer multiple of the oversampling rate, ow
- this function breaks */
-
- assert((n % FDMDV_OS) == 0);
-
- for(i=0; i<n; i++) {
- for(j=0; j<FDMDV_OS; j++) {
- out48k[i*FDMDV_OS+j] = 0.0;
- for(k=0,l=0; k<FDMDV_OS_TAPS; k+=FDMDV_OS,l++)
- out48k[i*FDMDV_OS+j] += fdmdv_os_filter[k+j]*in8k[i-l];
- out48k[i*FDMDV_OS+j] *= FDMDV_OS;
-
- }
- }
-
- /* update filter memory */
-
- for(i=-(FDMDV_OS_TAPS/FDMDV_OS); i<0; i++)
- in8k[i] = in8k[i + n];
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_48_to_8()
- AUTHOR......: David Rowe
- DATE CREATED: 9 May 2012
-
- Changes the sample rate of a signal from 48 to 8 kHz.
-
- n is the number of samples at the 8 kHz rate, there are FDMDV_OS*n
- samples at the 48 kHz rate. As above however a memory of
- FDMDV_OS_TAPS samples is reqd for in48k[] (see t48_8.c unit test as example).
-
- Low pass filter the 48 kHz signal at 4 kHz using the same filter as
- the upsampler, then just output every FDMDV_OS-th filtered sample.
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_48_to_8(float out8k[], float in48k[], int n)
-{
- int i,j;
-
- for(i=0; i<n; i++) {
- out8k[i] = 0.0;
- for(j=0; j<FDMDV_OS_TAPS; j++)
- out8k[i] += fdmdv_os_filter[j]*in48k[i*FDMDV_OS-j];
- }
-
- /* update filter memory */
-
- for(i=-FDMDV_OS_TAPS; i<0; i++)
- in48k[i] = in48k[i + n*FDMDV_OS];
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: fdmdv_get_rx_spectrum()
- AUTHOR......: David Rowe
- DATE CREATED: 9 June 2012
-
- Returns the FDMDV_NSPEC point magnitude spectrum of the rx signal in
- dB. The spectral samples are scaled so that 0dB is the peak, a good
- range for plotting is 0 to -40dB.
-
- Note only the real part of the complex input signal is used at
- present. A complex variable is used for input for compatability
- with the other rx signal procesing.
-
- Successive calls can be used to build up a waterfall or spectrogram
- plot, by mapping the received levels to colours.
-
- The time-frequency resolution of the spectrum can be adjusted by varying
- FDMDV_NSPEC. Note that a 2*FDMDV_NSPEC size FFT is reqd to get
- FDMDV_NSPEC output points. FDMDV_NSPEC must be a power of 2.
-
- See octave/tget_spec.m for a demo real time spectral display using
- Octave. This demo averages the output over time to get a smoother
- display:
-
- av = 0.9*av + 0.1*mag_dB
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_get_rx_spectrum(struct FDMDV *f, float mag_spec_dB[],
- COMP rx_fdm[], int nin)
-{
- int i,j;
- COMP fft_in[2*FDMDV_NSPEC];
- COMP fft_out[2*FDMDV_NSPEC];
- float full_scale_dB;
-
- /* update buffer of input samples */
-
- for(i=0; i<2*FDMDV_NSPEC-nin; i++)
- f->fft_buf[i] = f->fft_buf[i+nin];
- for(j=0; j<nin; j++,i++)
- f->fft_buf[i] = rx_fdm[j].real;
- assert(i == 2*FDMDV_NSPEC);
-
- /* window and FFT */
-
- for(i=0; i<2*FDMDV_NSPEC; i++) {
- fft_in[i].real = f->fft_buf[i] * (0.5 - 0.5*cos((float)i*2.0*PI/(2*FDMDV_NSPEC)));
- fft_in[i].imag = 0.0;
- }
-
- kiss_fft(f->fft_cfg, (kiss_fft_cpx *)fft_in, (kiss_fft_cpx *)fft_out);
-
- /* FFT scales up a signal of level 1 FDMDV_NSPEC */
-
- full_scale_dB = 20*log10(FDMDV_NSPEC);
-
- /* scale and convert to dB */
-
- for(i=0; i<FDMDV_NSPEC; i++) {
- mag_spec_dB[i] = 10.0*log10(fft_out[i].real*fft_out[i].real + fft_out[i].imag*fft_out[i].imag + 1E-12);
- mag_spec_dB[i] -= full_scale_dB;
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- Function used during development to test if magnitude of digital
- oscillators was drifting. It was!
-
-\*---------------------------------------------------------------------------*/
-
-void CODEC2_WIN32SUPPORT fdmdv_dump_osc_mags(struct FDMDV *f)
-{
- int i;
-
- fprintf(stderr, "phase_tx[]:\n");
- for(i=0; i<=NC; i++)
- fprintf(stderr," %1.3f", cabsolute(f->phase_tx[i]));
- fprintf(stderr,"\nfreq[]:\n");
- for(i=0; i<=NC; i++)
- fprintf(stderr," %1.3f", cabsolute(f->freq[i]));
- fprintf(stderr,"\nfoff_rect %1.3f foff_phase_rect: %1.3f", cabsolute(f->foff_rect), cabsolute(f->foff_phase_rect));
- fprintf(stderr,"\nphase_rx[]:\n");
- for(i=0; i<=NC; i++)
- fprintf(stderr," %1.3f", cabsolute(f->phase_rx[i]));
- fprintf(stderr, "\n\n");
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv.h
- AUTHOR......: David Rowe
- DATE CREATED: April 14 2012
-
- A 1400 bit/s Frequency Division Multiplexed Digital Voice (FDMDV)
- modem. Used for digital audio over HF SSB. See README_fdmdv.txt for
- more information, and fdmdv_mod.c and fdmdv_demod.c for example
- usage.
-
- References:
-
- [1] http://n1su.com/fdmdv/FDMDV_Docs_Rel_1_4b.pdf
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __FDMDV__
-#define __FDMDV__
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-/* set up the calling convention for DLL function import/export for
- WIN32 cross compiling */
-
-#ifdef __CODEC2_WIN32__
-#ifdef __CODEC2_BUILDING_DLL__
-#define CODEC2_WIN32SUPPORT __declspec(dllexport) __stdcall
-#else
-#define CODEC2_WIN32SUPPORT __declspec(dllimport) __stdcall
-#endif
-#else
-#define CODEC2_WIN32SUPPORT
-#endif
-
-#include "comp.h"
-
-#define FDMDV_BITS_PER_FRAME 28 /* 20ms frames, 1400 bit/s */
-#define FDMDV_NOM_SAMPLES_PER_FRAME 160 /* modulator output samples/frame and nominal demod samples/frame */
- /* at 8000 Hz sample rate */
-#define FDMDV_MAX_SAMPLES_PER_FRAME 200 /* max demod samples/frame, use this to allocate storage */
-#define FDMDV_SCALE 1000 /* suggested scaling for 16 bit shorts */
-#define FDMDV_NSYM 15
-#define FDMDV_FCENTRE 1500 /* Centre frequency, Nc/2 carriers below this, Nc/2 carriers above (Hz) */
-
-/* 8 to 48 kHz sample rate conversion */
-
-#define FDMDV_OS 6 /* oversampling rate */
-#define FDMDV_OS_TAPS 48 /* number of OS filter taps */
-
-/* FFT points */
-
-#define FDMDV_NSPEC 512
-#define FDMDV_MAX_F_HZ 4000
-
-/* FDMDV states and stats structures */
-
-struct FDMDV;
-
-struct FDMDV_STATS {
- float snr_est; /* estimated SNR of rx signal in dB (3 kHz noise BW) */
- COMP rx_symbols[FDMDV_NSYM]; /* latest received symbols, for scatter plot */
- int fest_coarse_fine; /* freq est state, 0-coarse 1-fine */
- float foff; /* estimated freq offset in Hz */
- float rx_timing; /* estimated optimum timing offset in samples */
- float clock_offset; /* Estimated tx/rx sample clock offset in ppm */
-};
-
-struct FDMDV * CODEC2_WIN32SUPPORT fdmdv_create(void);
-void CODEC2_WIN32SUPPORT fdmdv_destroy(struct FDMDV *fdmdv_state);
-
-void CODEC2_WIN32SUPPORT fdmdv_mod(struct FDMDV *fdmdv_state, COMP tx_fdm[], int tx_bits[], int *sync_bit);
-void CODEC2_WIN32SUPPORT fdmdv_demod(struct FDMDV *fdmdv_state, int rx_bits[], int *sync_bit, COMP rx_fdm[], int *nin);
-
-void CODEC2_WIN32SUPPORT fdmdv_get_test_bits(struct FDMDV *fdmdv_state, int tx_bits[]);
-void CODEC2_WIN32SUPPORT fdmdv_put_test_bits(struct FDMDV *f, int *sync, int *bit_errors, int *ntest_bits, int rx_bits[]);
-
-void CODEC2_WIN32SUPPORT fdmdv_get_demod_stats(struct FDMDV *fdmdv_state, struct FDMDV_STATS *fdmdv_stats);
-void CODEC2_WIN32SUPPORT fdmdv_get_rx_spectrum(struct FDMDV *fdmdv_state, float mag_dB[], COMP rx_fdm[], int nin);
-
-void CODEC2_WIN32SUPPORT fdmdv_8_to_48(float out48k[], float in8k[], int n);
-void CODEC2_WIN32SUPPORT fdmdv_48_to_8(float out8k[], float in48k[], int n);
-
-void CODEC2_WIN32SUPPORT fdmdv_freq_shift(COMP rx_fdm_fcorr[], COMP rx_fdm[], float foff, COMP *foff_rect, COMP *foff_phase_rect, int nin);
-
-/* debug/development function(s) */
-
-void CODEC2_WIN32SUPPORT fdmdv_dump_osc_mags(struct FDMDV *f);
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv_demod.c
- AUTHOR......: David Rowe
- DATE CREATED: April 30 2012
-
- Given an input raw file (8kHz, 16 bit shorts) of FDMDV modem samples
- outputs a file of bits. The output file is assumed to be arranged
- as codec frames of 56 bits (7 bytes) which are received as two 28
- bit modem frames.
-
- Demod states can be optionally logged to an Octave file for display
- using the Octave script fdmdv_demod_c.m. This is useful for
- checking demod performance.
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <errno.h>
-
-#include "fdmdv.h"
-#include "octave.h"
-
-#define BITS_PER_CODEC_FRAME (2*FDMDV_BITS_PER_FRAME)
-#define BYTES_PER_CODEC_FRAME (BITS_PER_CODEC_FRAME/8)
-
-/* lof of information we want to dump to Octave */
-
-#define MAX_FRAMES 50*60 /* 1 minute at 50 symbols/s */
-
-int main(int argc, char *argv[])
-{
- FILE *fin, *fout;
- struct FDMDV *fdmdv;
- char packed_bits[BYTES_PER_CODEC_FRAME];
- int rx_bits[FDMDV_BITS_PER_FRAME];
- int codec_bits[2*FDMDV_BITS_PER_FRAME];
- COMP rx_fdm[FDMDV_MAX_SAMPLES_PER_FRAME];
- short rx_fdm_scaled[FDMDV_MAX_SAMPLES_PER_FRAME];
- int i, bit, byte, c;
- int nin, nin_prev;
- int sync_bit;
- int state, next_state;
- int f;
- FILE *foct = NULL;
- struct FDMDV_STATS stats;
- float *rx_fdm_log;
- int rx_fdm_log_col_index;
- COMP rx_symbols_log[FDMDV_NSYM][MAX_FRAMES];
- int coarse_fine_log[MAX_FRAMES];
- float rx_timing_log[MAX_FRAMES];
- float foff_log[MAX_FRAMES];
- int sync_bit_log[MAX_FRAMES];
- int rx_bits_log[FDMDV_BITS_PER_FRAME*MAX_FRAMES];
- float snr_est_log[MAX_FRAMES];
- float *rx_spec_log;
- int max_frames_reached;
-
- if (argc < 3) {
- printf("usage: %s InputModemRawFile OutputBitFile [OctaveDumpFile]\n", argv[0]);
- printf("e.g %s hts1a_fdmdv.raw hts1a.c2\n", argv[0]);
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input modem sample file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[2],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output bit file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- /* malloc some of the bigger variables to prevent out of stack problems */
-
- rx_fdm_log = (float*)malloc(sizeof(float)*FDMDV_MAX_SAMPLES_PER_FRAME*MAX_FRAMES);
- assert(rx_fdm_log != NULL);
- rx_spec_log = (float*)malloc(sizeof(float)*FDMDV_NSPEC*MAX_FRAMES);
- assert(rx_spec_log != NULL);
-
- fdmdv = fdmdv_create();
- f = 0;
- state = 0;
- nin = FDMDV_NOM_SAMPLES_PER_FRAME;
- rx_fdm_log_col_index = 0;
- max_frames_reached = 0;
-
- while(fread(rx_fdm_scaled, sizeof(short), nin, fin) == nin)
- {
- for(i=0; i<nin; i++) {
- rx_fdm[i].real = (float)rx_fdm_scaled[i]/FDMDV_SCALE;
- rx_fdm[i].imag = 0;
- }
- nin_prev = nin;
- fdmdv_demod(fdmdv, rx_bits, &sync_bit, rx_fdm, &nin);
-
- /* log data for optional Octave dump */
-
- if (f < MAX_FRAMES) {
- fdmdv_get_demod_stats(fdmdv, &stats);
-
- /* log modem states for later dumping to Octave log file */
-
- memcpy(&rx_fdm_log[rx_fdm_log_col_index], rx_fdm, sizeof(float)*nin_prev);
- rx_fdm_log_col_index += nin_prev;
-
- for(c=0; c<FDMDV_NSYM; c++)
- rx_symbols_log[c][f] = stats.rx_symbols[c];
- foff_log[f] = stats.foff;
- rx_timing_log[f] = stats.rx_timing;
- coarse_fine_log[f] = stats.fest_coarse_fine;
- sync_bit_log[f] = sync_bit;
- memcpy(&rx_bits_log[FDMDV_BITS_PER_FRAME*f], rx_bits, sizeof(int)*FDMDV_BITS_PER_FRAME);
- snr_est_log[f] = stats.snr_est;
-
- fdmdv_get_rx_spectrum(fdmdv, &rx_spec_log[f*FDMDV_NSPEC], rx_fdm, nin_prev);
-
- f++;
- }
-
- if ((f == MAX_FRAMES) && !max_frames_reached) {
- fprintf(stderr,"MAX_FRAMES exceed in Octave log, log truncated\n");
- max_frames_reached = 1;
- }
-
- /* state machine to output codec bits only if we have a 0,1
- sync bit sequence */
-
- next_state = state;
- switch (state) {
- case 0:
- if (sync_bit == 0) {
- next_state = 1;
- memcpy(codec_bits, rx_bits, FDMDV_BITS_PER_FRAME*sizeof(int));
- }
- else
- next_state = 0;
- break;
- case 1:
- if (sync_bit == 1) {
- memcpy(&codec_bits[FDMDV_BITS_PER_FRAME], rx_bits, FDMDV_BITS_PER_FRAME*sizeof(int));
-
- /* pack bits, MSB received first */
-
- bit = 7; byte = 0;
- memset(packed_bits, 0, BYTES_PER_CODEC_FRAME);
- for(i=0; i<BITS_PER_CODEC_FRAME; i++) {
- packed_bits[byte] |= (codec_bits[i] << bit);
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == BYTES_PER_CODEC_FRAME);
-
- fwrite(packed_bits, sizeof(char), BYTES_PER_CODEC_FRAME, fout);
- }
- next_state = 0;
- break;
- }
- state = next_state;
-
- /* if this is in a pipeline, we probably don't want the usual
- buffering to occur */
-
- if (fout == stdout) fflush(stdout);
- if (fin == stdin) fflush(stdin);
- }
-
- /* Optional dump to Octave log file */
-
- if (argc == 4) {
-
- /* make sure 3rd arg is not just the pipe command */
-
- if (strcmp(argv[3],"|")) {
- if ((foct = fopen(argv[3],"wt")) == NULL ) {
- fprintf(stderr, "Error opening Octave dump file: %s: %s.\n",
- argv[3], strerror(errno));
- exit(1);
- }
- octave_save_float(foct, "rx_fdm_log_c", rx_fdm_log, 1, rx_fdm_log_col_index, FDMDV_MAX_SAMPLES_PER_FRAME);
- octave_save_complex(foct, "rx_symbols_log_c", (COMP*)rx_symbols_log, FDMDV_NSYM, f, MAX_FRAMES);
- octave_save_float(foct, "foff_log_c", foff_log, 1, f, MAX_FRAMES);
- octave_save_float(foct, "rx_timing_log_c", rx_timing_log, 1, f, MAX_FRAMES);
- octave_save_int(foct, "coarse_fine_log_c", coarse_fine_log, 1, f);
- octave_save_int(foct, "rx_bits_log_c", rx_bits_log, 1, FDMDV_BITS_PER_FRAME*f);
- octave_save_int(foct, "sync_bit_log_c", sync_bit_log, 1, f);
- octave_save_float(foct, "snr_est_log_c", snr_est_log, 1, f, MAX_FRAMES);
- octave_save_float(foct, "rx_spec_log_c", rx_spec_log, f, FDMDV_NSPEC, FDMDV_NSPEC);
- fclose(foct);
- }
- }
-
- //fdmdv_dump_osc_mags(fdmdv);
-
- fclose(fin);
- fclose(fout);
- free(rx_fdm_log);
- free(rx_spec_log);
- fdmdv_destroy(fdmdv);
-
- return 0;
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv_get_test_bits.c
- AUTHOR......: David Rowe
- DATE CREATED: 1 May 2012
-
- Generates a file of packed test bits, useful for input to fdmdv_mod.
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <errno.h>
-
-#include "fdmdv.h"
-
-#define BITS_PER_CODEC_FRAME (2*FDMDV_BITS_PER_FRAME)
-#define BYTES_PER_CODEC_FRAME (BITS_PER_CODEC_FRAME/8)
-
-int main(int argc, char *argv[])
-{
- FILE *fout;
- struct FDMDV *fdmdv;
- char packed_bits[BYTES_PER_CODEC_FRAME];
- int tx_bits[2*FDMDV_BITS_PER_FRAME];
- int n, i, bit, byte;
- int numBits, nCodecFrames;
-
- if (argc < 3) {
- printf("usage: %s OutputBitFile numBits\n", argv[0]);
- printf("e.g %s test.c2 1400\n", argv[0]);
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[1],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output bit file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- numBits = atoi(argv[2]);
- nCodecFrames = numBits/BITS_PER_CODEC_FRAME;
-
- fdmdv = fdmdv_create();
-
- for(n=0; n<nCodecFrames; n++) {
-
- fdmdv_get_test_bits(fdmdv, tx_bits);
- fdmdv_get_test_bits(fdmdv, &tx_bits[FDMDV_BITS_PER_FRAME]);
-
- /* pack bits, MSB received first */
-
- bit = 7; byte = 0;
- memset(packed_bits, 0, BYTES_PER_CODEC_FRAME);
- for(i=0; i<BITS_PER_CODEC_FRAME; i++) {
- packed_bits[byte] |= (tx_bits[i] << bit);
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == BYTES_PER_CODEC_FRAME);
-
- fwrite(packed_bits, sizeof(char), BYTES_PER_CODEC_FRAME, fout);
-
- /* if this is in a pipeline, we probably don't want the usual
- buffering to occur */
-
- if (fout == stdout) fflush(stdout);
- }
-
- fclose(fout);
- fdmdv_destroy(fdmdv);
-
- return 0;
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv_interleave.c
- AUTHOR......: David Rowe
- DATE CREATED: May 27 2012
-
- Given an input file of bits outputs an interleaved or optionally
- de-intervleaved file of bits.
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <errno.h>
-
-#include "fdmdv.h"
-
-#define MAX_INTERLEAVER 1024
-
-int main(int argc, char *argv[])
-{
- FILE *fin, *fout, *finter;
- int interleaver[MAX_INTERLEAVER];
- char *packed_bits;
- int *bits;
- int *interleaved_bits;
- int i, bit, byte, m, mpacked, frames, interleave, src_bit, dest_bit;
-
- if (argc < 4) {
- printf("usage: %s InputBitFile OutputBitFile InterleaverFile [de]\n", argv[0]);
- printf("e.g %s hts1a.c2 hts1a_interleaved.c2 interleaver.txt\n", argv[0]);
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input bit file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[2],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output bit file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- if ((finter = fopen(argv[3],"rt")) == NULL ) {
- fprintf(stderr, "Error opening interleaver file: %s: %s.\n",
- argv[3], strerror(errno));
- exit(1);
- }
-
- if (argc == 5)
- interleave = 1;
- else
- interleave = 0;
-
- /* load interleaver, size determines block size we will process */
-
- src_bit = 0;
- while(fscanf(finter, "%d\n", &dest_bit) == 1) {
- if (interleave)
- interleaver[dest_bit] = src_bit;
- else
- interleaver[src_bit] = dest_bit;
-
- src_bit++;
- if (src_bit == MAX_INTERLEAVER) {
- fprintf(stderr, "Error interleaver too big\n");
- exit(1);
- }
- }
- fclose(finter);
-
- m = src_bit;
- fprintf(stderr, "Interleaver size m = %d interleave = %d\n", m, interleave);
- mpacked = m/8;
-
- packed_bits = (char*)malloc(mpacked*sizeof(char));
- assert(packed_bits != NULL);
- bits = (int*)malloc(m*sizeof(int));
- assert(bits != NULL);
- interleaved_bits = (int*)malloc(m*sizeof(int));
- assert(interleaved_bits != NULL);
-
- frames = 0;
-
- while(fread(packed_bits, sizeof(char), mpacked, fin) == mpacked) {
- frames++;
-
- /* unpack bits, MSB first */
-
- bit = 7; byte = 0;
- for(i=0; i<m; i++) {
- bits[i] = (packed_bits[byte] >> bit) & 0x1;
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == mpacked);
-
- /* (de) interleave */
-
- for(i=0; i<m; i++)
- interleaved_bits[i] = bits[interleaver[i]];
-
- /* pack bits, MSB sent first */
-
- bit = 7; byte = 0;
- memset(packed_bits, 0, mpacked);
- for(i=0; i<m; i++) {
- packed_bits[byte] |= (interleaved_bits[i] << bit);
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == mpacked);
-
- fwrite(packed_bits, sizeof(char), mpacked, fout);
-
- /* if this is in a pipeline, we probably don't want the usual
- buffering to occur */
-
- if (fout == stdout) fflush(stdout);
- if (fin == stdin) fflush(stdin);
- }
-
- free(packed_bits);
- free(bits);
- free(interleaved_bits);
-
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv_internal.h
- AUTHOR......: David Rowe
- DATE CREATED: April 16 2012
-
- Header file for FDMDV internal functions, exposed via this header
- file for testing.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __FDMDV_INTERNAL__
-#define __FDMDV_INTERNAL__
-
-#include "comp.h"
-#include "fdmdv.h"
-#include "kiss_fft.h"
-
-/*---------------------------------------------------------------------------*\
-
- DEFINES
-
-\*---------------------------------------------------------------------------*/
-
-#define PI 3.141592654
-#define FS 8000 /* sample rate in Hz */
-#define T (1.0/FS) /* sample period in seconds */
-#define RS 50 /* symbol rate in Hz */
-#define NC 14 /* number of data carriers (plus one pilot in the centre) */
-#define NB 2 /* Bits/symbol for QPSK modulation */
-#define RB (NC*RS*NB) /* bit rate */
-#define M (FS/RS) /* oversampling factor */
-#define NSYM 6 /* number of symbols to filter over */
-#define NFILTER (NSYM*M) /* size of tx/rx filters at sample rate M */
-
-#define FSEP 75 /* Separation between carriers (Hz) */
-
-#define NT 5 /* number of symbols we estimate timing over */
-#define P 4 /* oversample factor used for initial rx symbol filtering */
-#define NFILTERTIMING (M+NFILTER+M) /* filter memory used for resampling after timing estimation */
-
-#define NTEST_BITS (NC*NB*4) /* length of test bit sequence */
-
-#define NPILOT_LUT (4*M) /* number of pilot look up table samples */
-#define NPILOTCOEFF 30 /* number of FIR filter coeffs in LP filter */
-#define NPILOTBASEBAND (NPILOTCOEFF+M+M/P) /* number of pilot baseband samples reqd for pilot LPF */
-#define NPILOTLPF (4*M) /* number of samples we DFT pilot over, pilot est window */
-#define MPILOTFFT 256
-
-/* freq offset sestimation states */
-
-#define COARSE 0
-#define FINE 1
-
-/* averaging filter coeffs */
-
-#define TRACK_COEFF 0.5
-#define SNR_COEFF 0.9 /* SNR est averaging filter coeff */
-
-/*---------------------------------------------------------------------------*\
-
- STRUCT for States
-
-\*---------------------------------------------------------------------------*/
-
-struct FDMDV {
- /* test data (test frame) states */
-
- int current_test_bit;
- int rx_test_bits_mem[NTEST_BITS];
-
- /* Modulator */
-
- int tx_pilot_bit;
- COMP prev_tx_symbols[NC+1];
- COMP tx_filter_memory[NC+1][NSYM];
- COMP phase_tx[NC+1];
- COMP freq[NC+1];
-
- /* Pilot generation at demodulator */
-
- COMP pilot_lut[NPILOT_LUT];
- int pilot_lut_index;
- int prev_pilot_lut_index;
-
- /* freq offset estimation states */
-
- kiss_fft_cfg fft_pilot_cfg;
- COMP pilot_baseband1[NPILOTBASEBAND];
- COMP pilot_baseband2[NPILOTBASEBAND];
- COMP pilot_lpf1[NPILOTLPF];
- COMP pilot_lpf2[NPILOTLPF];
- COMP S1[MPILOTFFT];
- COMP S2[MPILOTFFT];
-
- /* freq offset correction states */
-
- float foff;
- COMP foff_rect;
- COMP foff_phase_rect;
-
- /* Demodulator */
-
- COMP phase_rx[NC+1];
- COMP rx_filter_memory[NC+1][NFILTER];
- COMP rx_filter_mem_timing[NC+1][NT*P];
- COMP rx_baseband_mem_timing[NC+1][NFILTERTIMING];
- float rx_timing;
- COMP phase_difference[NC+1];
- COMP prev_rx_symbols[NC+1];
-
- /* freq est state machine */
-
- int fest_state;
- int coarse_fine;
-
- /* SNR estimation states */
-
- float sig_est[NC+1];
- float noise_est[NC+1];
-
- /* Buf for FFT/waterfall */
-
- float fft_buf[2*FDMDV_NSPEC];
- kiss_fft_cfg fft_cfg;
- };
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION PROTOTYPES
-
-\*---------------------------------------------------------------------------*/
-
-void bits_to_dqpsk_symbols(COMP tx_symbols[], COMP prev_tx_symbols[], int tx_bits[], int *pilot_bit);
-void tx_filter(COMP tx_baseband[NC+1][M], COMP tx_symbols[], COMP tx_filter_memory[NC+1][NSYM]);
-void fdm_upconvert(COMP tx_fdm[], COMP tx_baseband[NC+1][M], COMP phase_tx[], COMP freq_tx[]);
-void generate_pilot_fdm(COMP *pilot_fdm, int *bit, float *symbol, float *filter_mem, COMP *phase, COMP *freq);
-void generate_pilot_lut(COMP pilot_lut[], COMP *pilot_freq);
-float rx_est_freq_offset(struct FDMDV *f, COMP rx_fdm[], int nin);
-void lpf_peak_pick(float *foff, float *max, COMP pilot_baseband[], COMP pilot_lpf[], kiss_fft_cfg fft_pilot_cfg, COMP S[], int nin);
-void freq_shift(COMP rx_fdm_fcorr[], COMP rx_fdm[], float foff, COMP *foff_rect, COMP *foff_phase_rect, int nin);
-void fdm_downconvert(COMP rx_baseband[NC+1][M+M/P], COMP rx_fdm[], COMP phase_rx[], COMP freq[], int nin);
-void rx_filter(COMP rx_filt[NC+1][P+1], COMP rx_baseband[NC+1][M+M/P], COMP rx_filter_memory[NC+1][NFILTER], int nin);
-float rx_est_timing(COMP rx_symbols[],
- COMP rx_filt[NC+1][P+1],
- COMP rx_baseband[NC+1][M+M/P],
- COMP rx_filter_mem_timing[NC+1][NT*P],
- float env[],
- COMP rx_baseband_mem_timing[NC+1][NFILTERTIMING],
- int nin);
-float qpsk_to_bits(int rx_bits[], int *sync_bit, COMP phase_difference[], COMP prev_rx_symbols[], COMP rx_symbols[]);
-void snr_update(float sig_est[], float noise_est[], COMP phase_difference[]);
-int freq_state(int sync_bit, int *state);
-float calc_snr(float sig_est[], float noise_est[]);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv_mod.c
- AUTHOR......: David Rowe
- DATE CREATED: April 28 2012
-
- Given an input file of bits outputs a raw file (8kHz, 16 bit shorts)
- of FDMDV modem samples ready to send over a HF radio channel. The
- input file is assumed to be arranged as codec frames of 56 bits (7
- bytes) which we send as two 28 bit modem frames.
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <errno.h>
-
-#include "fdmdv.h"
-
-#define BITS_PER_CODEC_FRAME (2*FDMDV_BITS_PER_FRAME)
-#define BYTES_PER_CODEC_FRAME (BITS_PER_CODEC_FRAME/8)
-
-int main(int argc, char *argv[])
-{
- FILE *fin, *fout;
- struct FDMDV *fdmdv;
- char packed_bits[BYTES_PER_CODEC_FRAME];
- int tx_bits[2*FDMDV_BITS_PER_FRAME];
- COMP tx_fdm[2*FDMDV_NOM_SAMPLES_PER_FRAME];
- short tx_fdm_scaled[2*FDMDV_NOM_SAMPLES_PER_FRAME];
- int frames;
- int i, bit, byte;
- int sync_bit;
-
- if (argc < 3) {
- printf("usage: %s InputBitFile OutputModemRawFile\n", argv[0]);
- printf("e.g %s hts1a.c2 hts1a_fdmdv.raw\n", argv[0]);
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input bit file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[2],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output modem sample file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- fdmdv = fdmdv_create();
- frames = 0;
-
- while(fread(packed_bits, sizeof(char), BYTES_PER_CODEC_FRAME, fin) == BYTES_PER_CODEC_FRAME) {
- frames++;
-
- /* unpack bits, MSB first */
-
- bit = 7; byte = 0;
- for(i=0; i<BITS_PER_CODEC_FRAME; i++) {
- tx_bits[i] = (packed_bits[byte] >> bit) & 0x1;
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == BYTES_PER_CODEC_FRAME);
-
- /* modulate even and odd frames */
-
- fdmdv_mod(fdmdv, tx_fdm, tx_bits, &sync_bit);
- assert(sync_bit == 1);
-
- fdmdv_mod(fdmdv, &tx_fdm[FDMDV_NOM_SAMPLES_PER_FRAME], &tx_bits[FDMDV_BITS_PER_FRAME], &sync_bit);
- assert(sync_bit == 0);
-
- /* scale and save to disk as shorts */
-
- for(i=0; i<2*FDMDV_NOM_SAMPLES_PER_FRAME; i++)
- tx_fdm_scaled[i] = FDMDV_SCALE * tx_fdm[i].real;
-
- fwrite(tx_fdm_scaled, sizeof(short), 2*FDMDV_NOM_SAMPLES_PER_FRAME, fout);
-
- /* if this is in a pipeline, we probably don't want the usual
- buffering to occur */
-
- if (fout == stdout) fflush(stdout);
- if (fin == stdin) fflush(stdin);
- }
-
- //fdmdv_dump_osc_mags(fdmdv);
-
- fclose(fin);
- fclose(fout);
- fdmdv_destroy(fdmdv);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fdmdv_put_test_bits.c
- AUTHOR......: David Rowe
- DATE CREATED: 1 May 2012
-
- Using a file of packed test bits as input, determines bit error
- rate. Useful for testing fdmdv_demod.
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <errno.h>
-
-#include "fdmdv.h"
-
-#define BITS_PER_CODEC_FRAME (2*FDMDV_BITS_PER_FRAME)
-#define BYTES_PER_CODEC_FRAME (BITS_PER_CODEC_FRAME/8)
-
-int main(int argc, char *argv[])
-{
- FILE *fin;
- struct FDMDV *fdmdv;
- char packed_bits[BYTES_PER_CODEC_FRAME];
- int rx_bits[2*FDMDV_BITS_PER_FRAME];
- int i, bit, byte;
- int test_frame_sync, bit_errors, total_bit_errors, total_bits, ntest_bits;
-
- if (argc < 2) {
- printf("usage: %s InputBitFile\n", argv[0]);
- printf("e.g %s test.c2\n", argv[0]);
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input bit file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- fdmdv = fdmdv_create();
- total_bit_errors = 0;
- total_bits = 0;
-
- while(fread(packed_bits, sizeof(char), BYTES_PER_CODEC_FRAME, fin) == BYTES_PER_CODEC_FRAME) {
- /* unpack bits, MSB first */
-
- bit = 7; byte = 0;
- for(i=0; i<BITS_PER_CODEC_FRAME; i++) {
- rx_bits[i] = (packed_bits[byte] >> bit) & 0x1;
- //printf("%d 0x%x %d\n", i, packed_bits[byte], rx_bits[i]);
- bit--;
- if (bit < 0) {
- bit = 7;
- byte++;
- }
- }
- assert(byte == BYTES_PER_CODEC_FRAME);
-
- fdmdv_put_test_bits(fdmdv, &test_frame_sync, &bit_errors, &ntest_bits, rx_bits);
- if (test_frame_sync == 1) {
- total_bit_errors += bit_errors;
- total_bits = total_bits + ntest_bits;
- printf("+");
- }
- else
- printf("-");
- fdmdv_put_test_bits(fdmdv, &test_frame_sync, &bit_errors, &ntest_bits, &rx_bits[FDMDV_BITS_PER_FRAME]);
- if (test_frame_sync == 1) {
- total_bit_errors += bit_errors;
- total_bits = total_bits + ntest_bits;
- printf("+");
- }
- else
- printf("-");
-
- /* if this is in a pipeline, we probably don't want the usual
- buffering to occur */
-
- if (fin == stdin) fflush(stdin);
- }
-
- fclose(fin);
- fdmdv_destroy(fdmdv);
-
- printf("\nbits %d errors %d BER %1.4f\n", total_bits, total_bit_errors, (float)total_bit_errors/(1E-6+total_bits) );
- return 0;
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fifo.c
- AUTHOR......: David Rowe
- DATE CREATED: Oct 15 2012
-
- A FIFO design useful in gluing the FDMDV modem and codec together in
- integrated applications. The unittest/tfifo indicates these
- routines are thread safe without the need for syncronisation
- object, e.g. a different thread can read and write to a fifo at the
- same time.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include "fifo.h"
-
-struct FIFO {
- short *buf;
- short *pin;
- short *pout;
- int nshort;
-};
-
-struct FIFO *fifo_create(int nshort) {
- struct FIFO *fifo;
-
- fifo = (struct FIFO *)malloc(sizeof(struct FIFO));
- assert(fifo != NULL);
-
- fifo->buf = (short*)malloc(sizeof(short)*nshort);
- assert(fifo->buf != NULL);
- fifo->pin = fifo->buf;
- fifo->pout = fifo->buf;
- fifo->nshort = nshort;
-
- return fifo;
-}
-
-void fifo_destroy(struct FIFO *fifo) {
- assert(fifo != NULL);
- free(fifo->buf);
- free(fifo);
-}
-
-int fifo_write(struct FIFO *fifo, short data[], int n) {
- int i;
- int fifo_free;
- short *pdata;
- short *pin = fifo->pin;
-
- assert(fifo != NULL);
- assert(data != NULL);
-
- // available storage is one less than nshort as prd == pwr
- // is reserved for empty rather than full
-
- fifo_free = fifo->nshort - fifo_used(fifo) - 1;
-
- if (n > fifo_free) {
- return -1;
- }
- else {
-
- /* This could be made more efficient with block copies
- using memcpy */
-
- pdata = data;
- for(i=0; i<n; i++) {
- *pin++ = *pdata++;
- if (pin == (fifo->buf + fifo->nshort))
- pin = fifo->buf;
- }
- fifo->pin = pin;
- }
-
- return 0;
-}
-
-int fifo_read(struct FIFO *fifo, short data[], int n)
-{
- int i;
- short *pdata;
- short *pin = fifo->pin;
- short *pout = fifo->pout;
-
- assert(fifo != NULL);
- assert(data != NULL);
-
- if (n > fifo_used(fifo)) {
- return -1;
- }
- else {
-
- /* This could be made more efficient with block copies
- using memcpy */
-
- pdata = data;
- for(i=0; i<n; i++) {
- *pdata++ = *pout++;
- if (pout == (fifo->buf + fifo->nshort))
- pout = fifo->buf;
- }
- fifo->pout = pout;
- }
-
- return 0;
-}
-
-int fifo_used(struct FIFO *fifo)
-{
- short *pin = fifo->pin;
- short *pout = fifo->pout;
- unsigned int used;
-
- assert(fifo != NULL);
- if (pin >= pout)
- used = pin - pout;
- else
- used = fifo->nshort + (unsigned int)(pin - pout);
-
- return used;
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: fifo.h
- AUTHOR......: David Rowe
- DATE CREATED: Oct 15 2012
-
- A FIFO design useful in gluing the FDMDV modem and codec together in
- integrated applications.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __FIFO__
-#define __FIFO__
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-struct FIFO;
-
-struct FIFO *fifo_create(int nshort);
-void fifo_destroy(struct FIFO *fifo);
-int fifo_write(struct FIFO *fifo, short data[], int n);
-int fifo_read(struct FIFO *fifo, short data[], int n);
-int fifo_used(struct FIFO *fifo);
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: four1.c
- AUTHOR......: David Rowe
- DATE CREATED: 20/2/95
-
- Numerical Recipies in C FFT function. I have a nasty licence so please
- replace me.
-
-\*---------------------------------------------------------------------------*/
-
-#include <math.h>
-
-#define SWAP(a,b) tempr=(a);(a)=(b);(b)=tempr
-
-void four1(data,nn,isign)
-float data[];
-int nn,isign;
-{
- int n,mmax,m,j,istep,i;
- double wtemp,wr,wpr,wpi,wi,theta;
- float tempr,tempi;
-
- n=nn << 1;
- j=1;
- for (i=1;i<n;i+=2) {
- if (j > i) {
- SWAP(data[j],data[i]);
- SWAP(data[j+1],data[i+1]);
- }
- m=n >> 1;
- while (m >= 2 && j > m) {
- j -= m;
- m >>= 1;
- }
- j += m;
- }
- mmax=2;
- while (n > mmax) {
- istep=2*mmax;
- theta=6.28318530717959/(isign*mmax);
- wtemp=sin(0.5*theta);
- wpr = -2.0*wtemp*wtemp;
- wpi=sin(theta);
- wr=1.0;
- wi=0.0;
- for (m=1;m<mmax;m+=2) {
- for (i=m;i<=n;i+=istep) {
- j=i+mmax;
- tempr=wr*data[j]-wi*data[j+1];
- tempi=wr*data[j+1]+wi*data[j];
- data[j]=data[i]-tempr;
- data[j+1]=data[i+1]-tempi;
- data[i] += tempr;
- data[i+1] += tempi;
- }
- wr=(wtemp=wr)*wpr-wi*wpi+wr;
- wi=wi*wpr+wtemp*wpi+wi;
- }
- mmax=istep;
- }
-}
-
-#undef SWAP
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: four1.h
- AUTHOR......: David Rowe
- DATE CREATED: 20/2/95
-
- Numerical Recipies in C FFT function. I have a nasty licence so please
- replace me.
-
-\*---------------------------------------------------------------------------*/
-
-#ifndef __FOUR1__
-#define __FOUR1__
-
-void four1(float x[], int n, int isign);
-
-#endif /* __FOUR1__ */
-
+++ /dev/null
-#!/bin/sh
-# fq20.shsh
-# David Rowe 27 July 2010
-#
-# Decode a file with fully quantised codec at 20ms frame rate
-
-../src/sinedec ../raw/$1.raw $1.mdl -o $1_phase0_lsp_20_EWo2.raw --phase 0 --lpc 10 --lsp --postfilter --dec
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: generate_codebook.c
- AUTHOR......: Bruce Perens
- DATE CREATED: 29 Sep 2010
-
- Generate header files containing LSP quantisers, runs at compile time.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <ctype.h>
-#include <math.h>
-
-static const char usage[] =
-"Usage: %s filename array_name [filename ...]\n"
-"\tCreate C code for codebook tables.\n";
-
-static const char format[] =
-"The table format must be:\n"
-"\tTwo integers describing the dimensions of the codebook.\n"
-"\tThen, enough numbers to fill the specified dimensions.\n";
-
-static const char header[] =
-"/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */\n\n"
-"/*\n"
-" * This intermediary file and the files that used to create it are under \n"
-" * The LGPL. See the file COPYING.\n"
-" */\n\n"
-"#include \"defines.h\"\n\n";
-
-struct codebook {
- unsigned int k;
- unsigned int log2m;
- unsigned int m;
- float * cb;
-};
-
-static void
-dump_array(const struct codebook * b, int index)
-{
- int limit = b->k * b->m;
- int i;
-
- printf("static const float codes%d[] = {\n", index);
- for ( i = 0; i < limit; i++ ) {
- printf(" %g", b->cb[i]);
- if ( i < limit - 1 )
- printf(",");
-
- /* organise VQs by rows, looks prettier */
- if ( ((i+1) % b->k) == 0 )
- printf("\n");
- }
- printf("};\n");
-}
-
-static void
-dump_structure(const struct codebook * b, int index)
-{
- printf(" {\n");
- printf(" %d,\n", b->k);
- printf(" %g,\n", log(b->m) / log(2));
- printf(" %d,\n", b->m);
- printf(" codes%d\n", index);
- printf(" }");
-}
-
-float
-get_float(FILE * in, const char * name, char * * cursor, char * buffer,
- int size)
-{
- for ( ; ; ) {
- char * s = *cursor;
- char c;
-
- while ( (c = *s) != '\0' && !isdigit(c) && c != '-' && c != '.' )
- s++;
-
- /* Comments start with "#" and continue to the end of the line. */
- if ( c != '\0' && c != '#' ) {
- char * end = 0;
- float f = 0;
-
- f = strtod(s, &end);
-
- if ( end != s )
- *cursor = end;
- return f;
- }
-
- if ( fgets(buffer, size, in) == NULL ) {
- fprintf(stderr, "%s: Format error. %s\n", name, format);
- exit(1);
- }
- *cursor = buffer;
- }
-}
-
-static struct codebook *
-load(FILE * file, const char * name)
-{
- char line[1024];
- char * cursor = line;
- struct codebook * b = malloc(sizeof(struct codebook));
- int i;
- int size;
-
- *cursor = '\0';
-
- b->k = (int)get_float(file, name, &cursor, line, sizeof(line));
- b->m = (int)get_float(file, name ,&cursor, line, sizeof(line));
- size = b->k * b->m;
-
- b->cb = (float *)malloc(size * sizeof(float));
-
- for ( i = 0; i < size; i++ )
- b->cb[i] = get_float(file, name, &cursor, line, sizeof(line));
-
- return b;
-}
-
-int
-main(int argc, char * * argv)
-{
- struct codebook * * cb = malloc(argc * sizeof(struct codebook *));
- int i;
-
- if ( argc < 2 ) {
- fprintf(stderr, usage, argv[0]);
- fprintf(stderr, format);
- exit(1);
- }
-
- for ( i = 0; i < argc - 2; i++ ) {
- FILE * in = fopen(argv[i + 2], "r");
-
- if ( in == NULL ) {
- perror(argv[i + 2]);
- exit(1);
- }
-
- cb[i] = load(in, argv[i + 2]);
-
- fclose(in);
- }
-
- printf(header);
- for ( i = 0; i < argc - 2; i++ ) {
- printf(" /* %s */\n", argv[i + 2]);
- dump_array(cb[i], i);
- }
- printf("\nconst struct lsp_codebook %s[] = {\n", argv[1]);
- for ( i = 0; i < argc - 2; i++ ) {
- printf(" /* %s */\n", argv[i + 2]);
- dump_structure(cb[i], i);
- printf(",\n");
- }
- printf(" { 0, 0, 0, 0 }\n");
- printf("};\n");
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: genlspdtcb.c
- AUTHOR......: David Rowe
- DATE CREATED: 2 Nov 2011
-
- Generates codebooks (quantisation tables) for LSP delta-T VQ.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-
-*/
-
-#define MAX_ROWS 10
-
-float lsp1to4[] = {
- -25,0,25,
- -25,0,25,
- -50,0,50,
- -50,0,50
-};
-
-float lsp5to10[] = {
- -50,0,50,
- -50,0,50,
- -50,0,50,
- -50,0,50,
- -50,0,50,
- -50,0,50
-};
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-
-void create_codebook_text_file(char filename[], float lsp[],
- int rows, int cols);
-
-int main(void) {
- create_codebook_text_file("codebook/lspdt1-4.txt", lsp1to4, 4, 3);
- create_codebook_text_file("codebook/lspdt5-10.txt", lsp5to10, 6, 3);
- return 0;
-}
-
-void create_codebook_text_file(char filename[], float lsp[],
- int rows, int cols)
-{
- FILE *f;
- int i, digits[MAX_ROWS];
-
- f = fopen(filename, "wt");
- if (f == NULL) {
- printf("Can't open codebook text file %s\n", filename);
- exit(0);
- }
-
- for(i=0; i<rows; i++)
- digits[i] = 0;
-
- fprintf(f, "%d %d\n", rows, (int)pow(cols, rows));
-
- do {
- for(i=0; i<rows; i++)
- fprintf(f, "%4.0f ", lsp[cols*i + digits[i]]);
- fprintf(f, "\n");
- digits[0]++;
- for(i=0; i<rows-1; i++)
- if (digits[i]== cols) {
- digits[i] = 0;
- digits[i+1]++;
- }
- } while (digits[rows-1] != cols);
-
- fclose(f);
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: globals.c
- AUTHOR......: David Rowe
- DATE CREATED: 11/5/94
-
- Globals for sinusoidal speech coder.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "sine.h" /* global defines for coder */
-
-/* Globals used in encoder and decoder */
-
-int frames; /* number of frames processed so far */
-float Sn[M]; /* float input speech samples */
-MODEL model; /* model parameters for the current frame */
-int Nw; /* number of samples in analysis window */
-float sig; /* energy of current frame */
-
-/* Globals used in encoder */
-
-float w[M]; /* time domain hamming window */
-COMP W[FFT_ENC]; /* DFT of w[] */
-COMP Sw[FFT_ENC]; /* DFT of current frame */
-
-/* Globals used in decoder */
-
-COMP Sw_[FFT_ENC]; /* DFT of all voiced synthesised signal */
-float Sn_[AW_DEC]; /* synthesised speech */
-float Pn[AW_DEC]; /* time domain Parzen (trapezoidal) window */
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: globals.h
- AUTHOR......: David Rowe
- DATE CREATED: 1/11/94
-
- Globals for sinusoidal speech coder.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/* Globals used in encoder and decoder */
-
-extern int frames; /* number of frames processed so far */
-extern float Sn[]; /* float input speech samples */
-extern MODEL model; /* model parameters for the current frame */
-extern int Nw; /* number of samples in analysis window */
-extern float sig; /* energy of current frame */
-
-/* Globals used in encoder */
-
-extern float w[]; /* time domain hamming window */
-extern COMP W[]; /* frequency domain hamming window */
-extern COMP Sw[]; /* DFT of current frame */
-extern COMP Sw_[]; /* DFT of all voiced synthesised signal */
-
-/* Globals used in decoder */
-
-extern float Sn_[]; /* output synthesised speech samples */
-extern float Pn[]; /* time domain Parzen (trapezoidal) window */
-
+++ /dev/null
-const float glottal[]={
- 0.000000,
- -0.057687,
- -0.115338,
- -0.172917,
- -0.230385,
- -0.287707,
- -0.344845,
- -0.401762,
- -0.458419,
- -0.514781,
- -0.570809,
- -0.626467,
- -0.681721,
- -0.736537,
- -0.790884,
- -0.844733,
- -0.898057,
- -0.950834,
- -1.003044,
- -1.054670,
- -1.105700,
- -1.156124,
- -1.205936,
- -1.255132,
- -1.303711,
- -1.351675,
- -1.399026,
- -1.445769,
- -1.491908,
- -1.537448,
- -1.582393,
- -1.626747,
- -1.670514,
- -1.713693,
- -1.756285,
- -1.798288,
- -1.839697,
- -1.880507,
- -1.920712,
- -1.960302,
- -1.999269,
- -2.037603,
- -2.075295,
- -2.112335,
- -2.148716,
- -2.184430,
- -2.219472,
- -2.253839,
- -2.287531,
- -2.320550,
- -2.352900,
- -2.384588,
- -2.415623,
- -2.446019,
- -2.475788,
- -2.504946,
- -2.533512,
- -2.561501,
- -2.588934,
- -2.615827,
- -2.642198,
- -2.668064,
- -2.693439,
- -2.718337,
- -2.742767,
- -2.766738,
- -2.790256,
- -2.813322,
- -2.835936,
- -2.858094,
- -2.879790,
- -2.901016,
- -2.921759,
- -2.942008,
- -2.961747,
- -2.980961,
- -2.999632,
- -3.017745,
- -3.035282,
- -3.052228,
- -3.068567,
- -3.084285,
- -3.099371,
- -3.113813,
- -3.127605,
- -3.140738,
- 3.129975,
- 3.118167,
- 3.107022,
- 3.096537,
- 3.086709,
- 3.077531,
- 3.068996,
- 3.061096,
- 3.053821,
- 3.047159,
- 3.041102,
- 3.035636,
- 3.030753,
- 3.026441,
- 3.022690,
- 3.019491,
- 3.016836,
- 3.014718,
- 3.013132,
- 3.012072,
- 3.011535,
- 3.011521,
- 3.012028,
- 3.013057,
- 3.014612,
- 3.016695,
- 3.019310,
- 3.022463,
- 3.026160,
- 3.030407,
- 3.035212,
- 3.040580,
- 3.046520,
- 3.053038,
- 3.060141,
- 3.067836,
- 3.076128,
- 3.085023,
- 3.094525,
- 3.104639,
- 3.115367,
- 3.126712,
- 3.138674,
- -3.131930,
- -3.118731,
- -3.104915,
- -3.090485,
- -3.075444,
- -3.059795,
- -3.043543,
- -3.026695,
- -3.009254,
- -2.991229,
- -2.972625,
- -2.953449,
- -2.933710,
- -2.913414,
- -2.892567,
- -2.871176,
- -2.849248,
- -2.826787,
- -2.803798,
- -2.780284,
- -2.756247,
- -2.731689,
- -2.706609,
- -2.681005,
- -2.654875,
- -2.628213,
- -2.601015,
- -2.573272,
- -2.544977,
- -2.516121,
- -2.486694,
- -2.456686,
- -2.426084,
- -2.394879,
- -2.363060,
- -2.330616,
- -2.297538,
- -2.263816,
- -2.229444,
- -2.194416,
- -2.158727,
- -2.122375,
- -2.085359,
- -2.047682,
- -2.009347,
- -1.970361,
- -1.930732,
- -1.890470,
- -1.849587,
- -1.808098,
- -1.766017,
- -1.723360,
- -1.680145,
- -1.636388,
- -1.592105,
- -1.547313,
- -1.502025,
- -1.456256,
- -1.410016,
- -1.363314,
- -1.316157,
- -1.268547,
- -1.220486,
- -1.171971,
- -1.122997,
- -1.073555,
- -1.023636,
- -0.973227,
- -0.922312,
- -0.870875,
- -0.818899,
- -0.766366,
- -0.713257,
- -0.659554,
- -0.605242,
- -0.550303,
- -0.494723,
- -0.438492,
- -0.381598,
- -0.324036,
- -0.265800,
- -0.206889,
- -0.147303,
- -0.087046,
- -0.026121,
- 0.035463,
- 0.097698,
- 0.160576,
- 0.224087,
- 0.288221,
- 0.352969,
- 0.418323,
- 0.484276,
- 0.550822,
- 0.617958,
- 0.685681,
- 0.753991,
- 0.822889,
- 0.892378,
- 0.962462,
- 1.033144,
- 1.104430,
- 1.176325,
- 1.248833,
- 1.321956,
- 1.395696,
- 1.470051,
- 1.545019,
- 1.620593,
- 1.696763,
- 1.773516,
- 1.850837,
- 1.928705,
- 2.007097,
- 2.085987,
- 2.165347,
- 2.245145,
- 2.325347,
- 2.405919,
- 2.486824,
- 2.568025,
- 2.649485,
- 2.731167,
- 2.813033,
- 2.895045,
- 2.977167,
- 3.059362};
+++ /dev/null
-/* Generated by hanning_file() Octave function */
-
-const float hanning[]={
- 0,
- 2.4171e-05,
- 9.66816e-05,
- 0.000217525,
- 0.000386689,
- 0.000604158,
- 0.00086991,
- 0.00118392,
- 0.00154616,
- 0.00195659,
- 0.00241517,
- 0.00292186,
- 0.00347661,
- 0.00407937,
- 0.00473008,
- 0.00542867,
- 0.00617507,
- 0.00696922,
- 0.00781104,
- 0.00870045,
- 0.00963736,
- 0.0106217,
- 0.0116533,
- 0.0127322,
- 0.0138581,
- 0.0150311,
- 0.0162509,
- 0.0175175,
- 0.0188308,
- 0.0201906,
- 0.0215968,
- 0.0230492,
- 0.0245478,
- 0.0260923,
- 0.0276826,
- 0.0293186,
- 0.0310001,
- 0.032727,
- 0.034499,
- 0.036316,
- 0.0381779,
- 0.0400844,
- 0.0420354,
- 0.0440307,
- 0.04607,
- 0.0481533,
- 0.0502802,
- 0.0524506,
- 0.0546643,
- 0.056921,
- 0.0592206,
- 0.0615627,
- 0.0639473,
- 0.0663741,
- 0.0688427,
- 0.0713531,
- 0.0739048,
- 0.0764978,
- 0.0791318,
- 0.0818064,
- 0.0845214,
- 0.0872767,
- 0.0900718,
- 0.0929066,
- 0.0957807,
- 0.0986939,
- 0.101646,
- 0.104636,
- 0.107665,
- 0.110732,
- 0.113836,
- 0.116978,
- 0.120156,
- 0.123372,
- 0.126624,
- 0.129912,
- 0.133235,
- 0.136594,
- 0.139989,
- 0.143418,
- 0.146881,
- 0.150379,
- 0.153911,
- 0.157476,
- 0.161074,
- 0.164705,
- 0.168368,
- 0.172063,
- 0.17579,
- 0.179549,
- 0.183338,
- 0.187158,
- 0.191008,
- 0.194888,
- 0.198798,
- 0.202737,
- 0.206704,
- 0.2107,
- 0.214724,
- 0.218775,
- 0.222854,
- 0.226959,
- 0.231091,
- 0.235249,
- 0.239432,
- 0.243641,
- 0.247874,
- 0.252132,
- 0.256414,
- 0.260719,
- 0.265047,
- 0.269398,
- 0.273772,
- 0.278167,
- 0.282584,
- 0.287021,
- 0.29148,
- 0.295958,
- 0.300456,
- 0.304974,
- 0.30951,
- 0.314065,
- 0.318638,
- 0.323228,
- 0.327835,
- 0.332459,
- 0.3371,
- 0.341756,
- 0.346427,
- 0.351113,
- 0.355814,
- 0.360528,
- 0.365256,
- 0.369997,
- 0.374751,
- 0.379516,
- 0.384293,
- 0.389082,
- 0.393881,
- 0.398691,
- 0.40351,
- 0.408338,
- 0.413176,
- 0.418022,
- 0.422876,
- 0.427737,
- 0.432605,
- 0.43748,
- 0.44236,
- 0.447247,
- 0.452138,
- 0.457034,
- 0.461935,
- 0.466839,
- 0.471746,
- 0.476655,
- 0.481568,
- 0.486481,
- 0.491397,
- 0.496313,
- 0.501229,
- 0.506145,
- 0.511061,
- 0.515976,
- 0.520889,
- 0.5258,
- 0.530708,
- 0.535614,
- 0.540516,
- 0.545414,
- 0.550308,
- 0.555197,
- 0.560081,
- 0.564958,
- 0.56983,
- 0.574695,
- 0.579552,
- 0.584402,
- 0.589244,
- 0.594077,
- 0.598901,
- 0.603715,
- 0.60852,
- 0.613314,
- 0.618097,
- 0.622868,
- 0.627628,
- 0.632375,
- 0.63711,
- 0.641831,
- 0.646538,
- 0.651232,
- 0.655911,
- 0.660574,
- 0.665222,
- 0.669855,
- 0.67447,
- 0.679069,
- 0.683651,
- 0.688215,
- 0.69276,
- 0.697287,
- 0.701795,
- 0.706284,
- 0.710752,
- 0.7152,
- 0.719627,
- 0.724033,
- 0.728418,
- 0.73278,
- 0.73712,
- 0.741437,
- 0.74573,
- 0.75,
- 0.754246,
- 0.758467,
- 0.762663,
- 0.766833,
- 0.770978,
- 0.775097,
- 0.779189,
- 0.783254,
- 0.787291,
- 0.791301,
- 0.795283,
- 0.799236,
- 0.80316,
- 0.807055,
- 0.810921,
- 0.814756,
- 0.81856,
- 0.822334,
- 0.826077,
- 0.829788,
- 0.833468,
- 0.837115,
- 0.840729,
- 0.844311,
- 0.847859,
- 0.851374,
- 0.854855,
- 0.858301,
- 0.861713,
- 0.86509,
- 0.868431,
- 0.871737,
- 0.875007,
- 0.87824,
- 0.881437,
- 0.884598,
- 0.887721,
- 0.890806,
- 0.893854,
- 0.896864,
- 0.899835,
- 0.902768,
- 0.905661,
- 0.908516,
- 0.911331,
- 0.914106,
- 0.916841,
- 0.919536,
- 0.92219,
- 0.924804,
- 0.927376,
- 0.929907,
- 0.932397,
- 0.934845,
- 0.93725,
- 0.939614,
- 0.941935,
- 0.944213,
- 0.946448,
- 0.94864,
- 0.950789,
- 0.952894,
- 0.954955,
- 0.956972,
- 0.958946,
- 0.960874,
- 0.962759,
- 0.964598,
- 0.966393,
- 0.968142,
- 0.969846,
- 0.971505,
- 0.973118,
- 0.974686,
- 0.976207,
- 0.977683,
- 0.979112,
- 0.980495,
- 0.981832,
- 0.983122,
- 0.984365,
- 0.985561,
- 0.986711,
- 0.987813,
- 0.988868,
- 0.989876,
- 0.990837,
- 0.99175,
- 0.992616,
- 0.993434,
- 0.994204,
- 0.994927,
- 0.995601,
- 0.996228,
- 0.996807,
- 0.997337,
- 0.99782,
- 0.998255,
- 0.998641,
- 0.998979,
- 0.999269,
- 0.999511,
- 0.999704,
- 0.999849,
- 0.999946,
- 0.999994,
- 0.999994,
- 0.999946,
- 0.999849,
- 0.999704,
- 0.999511,
- 0.999269,
- 0.998979,
- 0.998641,
- 0.998255,
- 0.99782,
- 0.997337,
- 0.996807,
- 0.996228,
- 0.995601,
- 0.994927,
- 0.994204,
- 0.993434,
- 0.992616,
- 0.99175,
- 0.990837,
- 0.989876,
- 0.988868,
- 0.987813,
- 0.986711,
- 0.985561,
- 0.984365,
- 0.983122,
- 0.981832,
- 0.980495,
- 0.979112,
- 0.977683,
- 0.976207,
- 0.974686,
- 0.973118,
- 0.971505,
- 0.969846,
- 0.968142,
- 0.966393,
- 0.964598,
- 0.962759,
- 0.960874,
- 0.958946,
- 0.956972,
- 0.954955,
- 0.952894,
- 0.950789,
- 0.94864,
- 0.946448,
- 0.944213,
- 0.941935,
- 0.939614,
- 0.93725,
- 0.934845,
- 0.932397,
- 0.929907,
- 0.927376,
- 0.924804,
- 0.92219,
- 0.919536,
- 0.916841,
- 0.914106,
- 0.911331,
- 0.908516,
- 0.905661,
- 0.902768,
- 0.899835,
- 0.896864,
- 0.893854,
- 0.890806,
- 0.887721,
- 0.884598,
- 0.881437,
- 0.87824,
- 0.875007,
- 0.871737,
- 0.868431,
- 0.86509,
- 0.861713,
- 0.858301,
- 0.854855,
- 0.851374,
- 0.847859,
- 0.844311,
- 0.840729,
- 0.837115,
- 0.833468,
- 0.829788,
- 0.826077,
- 0.822334,
- 0.81856,
- 0.814756,
- 0.810921,
- 0.807055,
- 0.80316,
- 0.799236,
- 0.795283,
- 0.791301,
- 0.787291,
- 0.783254,
- 0.779189,
- 0.775097,
- 0.770978,
- 0.766833,
- 0.762663,
- 0.758467,
- 0.754246,
- 0.75,
- 0.74573,
- 0.741437,
- 0.73712,
- 0.73278,
- 0.728418,
- 0.724033,
- 0.719627,
- 0.7152,
- 0.710752,
- 0.706284,
- 0.701795,
- 0.697287,
- 0.69276,
- 0.688215,
- 0.683651,
- 0.679069,
- 0.67447,
- 0.669855,
- 0.665222,
- 0.660574,
- 0.655911,
- 0.651232,
- 0.646538,
- 0.641831,
- 0.63711,
- 0.632375,
- 0.627628,
- 0.622868,
- 0.618097,
- 0.613314,
- 0.60852,
- 0.603715,
- 0.598901,
- 0.594077,
- 0.589244,
- 0.584402,
- 0.579552,
- 0.574695,
- 0.56983,
- 0.564958,
- 0.560081,
- 0.555197,
- 0.550308,
- 0.545414,
- 0.540516,
- 0.535614,
- 0.530708,
- 0.5258,
- 0.520889,
- 0.515976,
- 0.511061,
- 0.506145,
- 0.501229,
- 0.496313,
- 0.491397,
- 0.486481,
- 0.481568,
- 0.476655,
- 0.471746,
- 0.466839,
- 0.461935,
- 0.457034,
- 0.452138,
- 0.447247,
- 0.44236,
- 0.43748,
- 0.432605,
- 0.427737,
- 0.422876,
- 0.418022,
- 0.413176,
- 0.408338,
- 0.40351,
- 0.398691,
- 0.393881,
- 0.389082,
- 0.384293,
- 0.379516,
- 0.374751,
- 0.369997,
- 0.365256,
- 0.360528,
- 0.355814,
- 0.351113,
- 0.346427,
- 0.341756,
- 0.3371,
- 0.332459,
- 0.327835,
- 0.323228,
- 0.318638,
- 0.314065,
- 0.30951,
- 0.304974,
- 0.300456,
- 0.295958,
- 0.29148,
- 0.287021,
- 0.282584,
- 0.278167,
- 0.273772,
- 0.269398,
- 0.265047,
- 0.260719,
- 0.256414,
- 0.252132,
- 0.247874,
- 0.243641,
- 0.239432,
- 0.235249,
- 0.231091,
- 0.226959,
- 0.222854,
- 0.218775,
- 0.214724,
- 0.2107,
- 0.206704,
- 0.202737,
- 0.198798,
- 0.194888,
- 0.191008,
- 0.187158,
- 0.183338,
- 0.179549,
- 0.17579,
- 0.172063,
- 0.168368,
- 0.164705,
- 0.161074,
- 0.157476,
- 0.153911,
- 0.150379,
- 0.146881,
- 0.143418,
- 0.139989,
- 0.136594,
- 0.133235,
- 0.129912,
- 0.126624,
- 0.123372,
- 0.120156,
- 0.116978,
- 0.113836,
- 0.110732,
- 0.107665,
- 0.104636,
- 0.101646,
- 0.0986939,
- 0.0957807,
- 0.0929066,
- 0.0900718,
- 0.0872767,
- 0.0845214,
- 0.0818064,
- 0.0791318,
- 0.0764978,
- 0.0739048,
- 0.0713531,
- 0.0688427,
- 0.0663741,
- 0.0639473,
- 0.0615627,
- 0.0592206,
- 0.056921,
- 0.0546643,
- 0.0524506,
- 0.0502802,
- 0.0481533,
- 0.04607,
- 0.0440307,
- 0.0420354,
- 0.0400844,
- 0.0381779,
- 0.036316,
- 0.034499,
- 0.032727,
- 0.0310001,
- 0.0293186,
- 0.0276826,
- 0.0260923,
- 0.0245478,
- 0.0230492,
- 0.0215968,
- 0.0201906,
- 0.0188308,
- 0.0175175,
- 0.0162509,
- 0.0150311,
- 0.0138581,
- 0.0127322,
- 0.0116533,
- 0.0106217,
- 0.00963736,
- 0.00870045,
- 0.00781104,
- 0.00696922,
- 0.00617507,
- 0.00542867,
- 0.00473008,
- 0.00407937,
- 0.00347661,
- 0.00292186,
- 0.00241517,
- 0.00195659,
- 0.00154616,
- 0.00118392,
- 0.00086991,
- 0.000604158,
- 0.000386689,
- 0.000217525,
- 9.66816e-05,
- 2.4171e-05,
- 0
-};
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: interp.c
- AUTHOR......: David Rowe
- DATE CREATED: 9/10/09
-
- Interpolation of 20ms frames to 10ms frames.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <math.h>
-#include <string.h>
-#include <stdio.h>
-
-#include "defines.h"
-#include "interp.h"
-#include "lsp.h"
-#include "quantise.h"
-
-float sample_log_amp(MODEL *model, float w);
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: interp()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/10
-
- Given two frames decribed by model parameters 20ms apart, determines
- the model parameters of the 10ms frame between them. Assumes
- voicing is available for middle (interpolated) frame. Outputs are
- amplitudes and Wo for the interpolated frame.
-
- This version can interpolate the amplitudes between two frames of
- different Wo and L.
-
- This version works by log linear interpolation, but listening tests
- showed it creates problems in background noise, e.g. hts2a and mmt1.
- When this function is used (--dec mode) bg noise appears to be
- amplitude modulated, and gets louder. The interp_lsp() function
- below seems to do a better job.
-
-\*---------------------------------------------------------------------------*/
-
-void interpolate(
- MODEL *interp, /* interpolated model params */
- MODEL *prev, /* previous frames model params */
- MODEL *next /* next frames model params */
-)
-{
- int l;
- float w,log_amp;
-
- /* Wo depends on voicing of this and adjacent frames */
-
- if (interp->voiced) {
- if (prev->voiced && next->voiced)
- interp->Wo = (prev->Wo + next->Wo)/2.0;
- if (!prev->voiced && next->voiced)
- interp->Wo = next->Wo;
- if (prev->voiced && !next->voiced)
- interp->Wo = prev->Wo;
- }
- else {
- interp->Wo = TWO_PI/P_MAX;
- }
- interp->L = PI/interp->Wo;
-
- /* Interpolate amplitudes using linear interpolation in log domain */
-
- for(l=1; l<=interp->L; l++) {
- w = l*interp->Wo;
- log_amp = (sample_log_amp(prev, w) + sample_log_amp(next, w))/2.0;
- interp->A[l] = pow(10.0, log_amp);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: sample_log_amp()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/10
-
- Samples the amplitude envelope at an arbitrary frequency w. Uses
- linear interpolation in the log domain to sample between harmonic
- amplitudes.
-
-\*---------------------------------------------------------------------------*/
-
-float sample_log_amp(MODEL *model, float w)
-{
- int m;
- float f, log_amp;
-
- assert(w > 0.0); assert (w <= PI);
-
- m = floor(w/model->Wo + 0.5);
- f = (w - m*model->Wo)/w;
- assert(f <= 1.0);
-
- if (m < 1) {
- log_amp = f*log10(model->A[1] + 1E-6);
- }
- else if ((m+1) > model->L) {
- log_amp = (1.0-f)*log10(model->A[model->L] + 1E-6);
- }
- else {
- log_amp = (1.0-f)*log10(model->A[m] + 1E-6) +
- f*log10(model->A[m+1] + 1E-6);
- }
-
- return log_amp;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: interp_lsp()
- AUTHOR......: David Rowe
- DATE CREATED: 10 Nov 2010
-
- Given two frames decribed by model parameters 20ms apart, determines
- the model parameters of the 10ms frame between them. Assumes
- voicing is available for middle (interpolated) frame. Outputs are
- amplitudes and Wo for the interpolated frame.
-
- This version uses interpolation of LSPs, seems to do a better job
- with bg noise.
-
-\*---------------------------------------------------------------------------*/
-
-void interpolate_lsp(
- kiss_fft_cfg fft_fwd_cfg,
- MODEL *interp, /* interpolated model params */
- MODEL *prev, /* previous frames model params */
- MODEL *next, /* next frames model params */
- float *prev_lsps, /* previous frames LSPs */
- float prev_e, /* previous frames LPC energy */
- float *next_lsps, /* next frames LSPs */
- float next_e, /* next frames LPC energy */
- float *ak_interp, /* interpolated aks for this frame */
- float *lsps_interp/* interpolated lsps for this frame */
-)
-{
- int i;
- float e;
- float snr;
-
- /* trap corner case where V est is probably wrong */
-
- if (interp->voiced && !prev->voiced && !next->voiced) {
- interp->voiced = 0;
- }
-
- /* Wo depends on voicing of this and adjacent frames */
-
- if (interp->voiced) {
- if (prev->voiced && next->voiced)
- interp->Wo = (prev->Wo + next->Wo)/2.0;
- if (!prev->voiced && next->voiced)
- interp->Wo = next->Wo;
- if (prev->voiced && !next->voiced)
- interp->Wo = prev->Wo;
- }
- else {
- interp->Wo = TWO_PI/P_MAX;
- }
- interp->L = PI/interp->Wo;
-
- //printf(" interp: prev_v: %d next_v: %d prev_Wo: %f next_Wo: %f\n",
- // prev->voiced, next->voiced, prev->Wo, next->Wo);
- //printf(" interp: Wo: %1.5f L: %d\n", interp->Wo, interp->L);
-
- /* interpolate LSPs */
-
- for(i=0; i<LPC_ORD; i++) {
- lsps_interp[i] = (prev_lsps[i] + next_lsps[i])/2.0;
- }
-
- /* Interpolate LPC energy in log domain */
-
- e = pow(10.0, (log10(prev_e) + log10(next_e))/2.0);
- //printf(" interp: e: %f\n", e);
-
- /* convert back to amplitudes */
-
- lsp_to_lpc(lsps_interp, ak_interp, LPC_ORD);
- aks_to_M2(fft_fwd_cfg, ak_interp, LPC_ORD, interp, e, &snr, 0, 0, 1, 1, LPCPF_BETA, LPCPF_GAMMA);
- //printf(" interp: ak[1]: %f A[1] %f\n", ak_interp[1], interp->A[1]);
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: interp_Wo()
- AUTHOR......: David Rowe
- DATE CREATED: 22 May 2012
-
- Interpolates centre 10ms sample of Wo and L samples given two
- samples 20ms apart. Assumes voicing is available for centre
- (interpolated) frame.
-
-\*---------------------------------------------------------------------------*/
-
-void interp_Wo(
- MODEL *interp, /* interpolated model params */
- MODEL *prev, /* previous frames model params */
- MODEL *next /* next frames model params */
- )
-{
- /* trap corner case where voicing est is probably wrong */
-
- if (interp->voiced && !prev->voiced && !next->voiced) {
- interp->voiced = 0;
- }
-
- /* Wo depends on voicing of this and adjacent frames */
-
- if (interp->voiced) {
- if (prev->voiced && next->voiced)
- interp->Wo = (prev->Wo + next->Wo)/2.0;
- if (!prev->voiced && next->voiced)
- interp->Wo = next->Wo;
- if (prev->voiced && !next->voiced)
- interp->Wo = prev->Wo;
- }
- else {
- interp->Wo = TWO_PI/P_MAX;
- }
- interp->L = PI/interp->Wo;
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: interp_energy()
- AUTHOR......: David Rowe
- DATE CREATED: 22 May 2012
-
- Interpolates centre 10ms sample of energy given two samples 20ms
- apart.
-
-\*---------------------------------------------------------------------------*/
-
-float interp_energy(float prev_e, float next_e)
-{
- return pow(10.0, (log10(prev_e) + log10(next_e))/2.0);
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: interpolate_lsp_ver2()
- AUTHOR......: David Rowe
- DATE CREATED: 22 May 2012
-
- Weighted interpolation of LSPs.
-
-\*---------------------------------------------------------------------------*/
-
-void interpolate_lsp_ver2(float interp[], float prev[], float next[], float weight)
-{
- int i;
-
- for(i=0; i<LPC_ORD; i++)
- interp[i] = (1.0 - weight)*prev[i] + weight*next[i];
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: interp.h
- AUTHOR......: David Rowe
- DATE CREATED: 9/10/09
-
- Interpolation of 20ms frames to 10ms frames.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __INTERP__
-#define __INTERP__
-
-#include "kiss_fft.h"
-
-void interpolate(MODEL *interp, MODEL *prev, MODEL *next);
-void interpolate_lsp(kiss_fft_cfg fft_dec_cfg,
- MODEL *interp, MODEL *prev, MODEL *next,
- float *prev_lsps, float prev_e,
- float *next_lsps, float next_e,
- float *ak_interp, float *lsps_interp);
-void interp_Wo(MODEL *interp, MODEL *prev, MODEL *next);
-float interp_energy(float prev, float next);
-void interpolate_lsp_ver2(float interp[], float prev[], float next[], float weight);
-
-#endif
+++ /dev/null
-/*
-Copyright (c) 2003-2010, Mark Borgerding
-
-All rights reserved.
-
-Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
- * Neither the author nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-*/
-
-
-#include "_kiss_fft_guts.h"
-/* The guts header contains all the multiplication and addition macros that are defined for
- fixed or floating point complex numbers. It also delares the kf_ internal functions.
- */
-
-static void kf_bfly2(
- kiss_fft_cpx * Fout,
- const size_t fstride,
- const kiss_fft_cfg st,
- int m
- )
-{
- kiss_fft_cpx * Fout2;
- kiss_fft_cpx * tw1 = st->twiddles;
- kiss_fft_cpx t;
- Fout2 = Fout + m;
- do{
- C_FIXDIV(*Fout,2); C_FIXDIV(*Fout2,2);
-
- C_MUL (t, *Fout2 , *tw1);
- tw1 += fstride;
- C_SUB( *Fout2 , *Fout , t );
- C_ADDTO( *Fout , t );
- ++Fout2;
- ++Fout;
- }while (--m);
-}
-
-static void kf_bfly4(
- kiss_fft_cpx * Fout,
- const size_t fstride,
- const kiss_fft_cfg st,
- const size_t m
- )
-{
- kiss_fft_cpx *tw1,*tw2,*tw3;
- kiss_fft_cpx scratch[6];
- size_t k=m;
- const size_t m2=2*m;
- const size_t m3=3*m;
-
-
- tw3 = tw2 = tw1 = st->twiddles;
-
- do {
- C_FIXDIV(*Fout,4); C_FIXDIV(Fout[m],4); C_FIXDIV(Fout[m2],4); C_FIXDIV(Fout[m3],4);
-
- C_MUL(scratch[0],Fout[m] , *tw1 );
- C_MUL(scratch[1],Fout[m2] , *tw2 );
- C_MUL(scratch[2],Fout[m3] , *tw3 );
-
- C_SUB( scratch[5] , *Fout, scratch[1] );
- C_ADDTO(*Fout, scratch[1]);
- C_ADD( scratch[3] , scratch[0] , scratch[2] );
- C_SUB( scratch[4] , scratch[0] , scratch[2] );
- C_SUB( Fout[m2], *Fout, scratch[3] );
- tw1 += fstride;
- tw2 += fstride*2;
- tw3 += fstride*3;
- C_ADDTO( *Fout , scratch[3] );
-
- if(st->inverse) {
- Fout[m].r = scratch[5].r - scratch[4].i;
- Fout[m].i = scratch[5].i + scratch[4].r;
- Fout[m3].r = scratch[5].r + scratch[4].i;
- Fout[m3].i = scratch[5].i - scratch[4].r;
- }else{
- Fout[m].r = scratch[5].r + scratch[4].i;
- Fout[m].i = scratch[5].i - scratch[4].r;
- Fout[m3].r = scratch[5].r - scratch[4].i;
- Fout[m3].i = scratch[5].i + scratch[4].r;
- }
- ++Fout;
- }while(--k);
-}
-
-static void kf_bfly3(
- kiss_fft_cpx * Fout,
- const size_t fstride,
- const kiss_fft_cfg st,
- size_t m
- )
-{
- size_t k=m;
- const size_t m2 = 2*m;
- kiss_fft_cpx *tw1,*tw2;
- kiss_fft_cpx scratch[5];
- kiss_fft_cpx epi3;
- epi3 = st->twiddles[fstride*m];
-
- tw1=tw2=st->twiddles;
-
- do{
- C_FIXDIV(*Fout,3); C_FIXDIV(Fout[m],3); C_FIXDIV(Fout[m2],3);
-
- C_MUL(scratch[1],Fout[m] , *tw1);
- C_MUL(scratch[2],Fout[m2] , *tw2);
-
- C_ADD(scratch[3],scratch[1],scratch[2]);
- C_SUB(scratch[0],scratch[1],scratch[2]);
- tw1 += fstride;
- tw2 += fstride*2;
-
- Fout[m].r = Fout->r - HALF_OF(scratch[3].r);
- Fout[m].i = Fout->i - HALF_OF(scratch[3].i);
-
- C_MULBYSCALAR( scratch[0] , epi3.i );
-
- C_ADDTO(*Fout,scratch[3]);
-
- Fout[m2].r = Fout[m].r + scratch[0].i;
- Fout[m2].i = Fout[m].i - scratch[0].r;
-
- Fout[m].r -= scratch[0].i;
- Fout[m].i += scratch[0].r;
-
- ++Fout;
- }while(--k);
-}
-
-static void kf_bfly5(
- kiss_fft_cpx * Fout,
- const size_t fstride,
- const kiss_fft_cfg st,
- int m
- )
-{
- kiss_fft_cpx *Fout0,*Fout1,*Fout2,*Fout3,*Fout4;
- int u;
- kiss_fft_cpx scratch[13];
- kiss_fft_cpx * twiddles = st->twiddles;
- kiss_fft_cpx *tw;
- kiss_fft_cpx ya,yb;
- ya = twiddles[fstride*m];
- yb = twiddles[fstride*2*m];
-
- Fout0=Fout;
- Fout1=Fout0+m;
- Fout2=Fout0+2*m;
- Fout3=Fout0+3*m;
- Fout4=Fout0+4*m;
-
- tw=st->twiddles;
- for ( u=0; u<m; ++u ) {
- C_FIXDIV( *Fout0,5); C_FIXDIV( *Fout1,5); C_FIXDIV( *Fout2,5); C_FIXDIV( *Fout3,5); C_FIXDIV( *Fout4,5);
- scratch[0] = *Fout0;
-
- C_MUL(scratch[1] ,*Fout1, tw[u*fstride]);
- C_MUL(scratch[2] ,*Fout2, tw[2*u*fstride]);
- C_MUL(scratch[3] ,*Fout3, tw[3*u*fstride]);
- C_MUL(scratch[4] ,*Fout4, tw[4*u*fstride]);
-
- C_ADD( scratch[7],scratch[1],scratch[4]);
- C_SUB( scratch[10],scratch[1],scratch[4]);
- C_ADD( scratch[8],scratch[2],scratch[3]);
- C_SUB( scratch[9],scratch[2],scratch[3]);
-
- Fout0->r += scratch[7].r + scratch[8].r;
- Fout0->i += scratch[7].i + scratch[8].i;
-
- scratch[5].r = scratch[0].r + S_MUL(scratch[7].r,ya.r) + S_MUL(scratch[8].r,yb.r);
- scratch[5].i = scratch[0].i + S_MUL(scratch[7].i,ya.r) + S_MUL(scratch[8].i,yb.r);
-
- scratch[6].r = S_MUL(scratch[10].i,ya.i) + S_MUL(scratch[9].i,yb.i);
- scratch[6].i = -S_MUL(scratch[10].r,ya.i) - S_MUL(scratch[9].r,yb.i);
-
- C_SUB(*Fout1,scratch[5],scratch[6]);
- C_ADD(*Fout4,scratch[5],scratch[6]);
-
- scratch[11].r = scratch[0].r + S_MUL(scratch[7].r,yb.r) + S_MUL(scratch[8].r,ya.r);
- scratch[11].i = scratch[0].i + S_MUL(scratch[7].i,yb.r) + S_MUL(scratch[8].i,ya.r);
- scratch[12].r = - S_MUL(scratch[10].i,yb.i) + S_MUL(scratch[9].i,ya.i);
- scratch[12].i = S_MUL(scratch[10].r,yb.i) - S_MUL(scratch[9].r,ya.i);
-
- C_ADD(*Fout2,scratch[11],scratch[12]);
- C_SUB(*Fout3,scratch[11],scratch[12]);
-
- ++Fout0;++Fout1;++Fout2;++Fout3;++Fout4;
- }
-}
-
-/* perform the butterfly for one stage of a mixed radix FFT */
-static void kf_bfly_generic(
- kiss_fft_cpx * Fout,
- const size_t fstride,
- const kiss_fft_cfg st,
- int m,
- int p
- )
-{
- int u,k,q1,q;
- kiss_fft_cpx * twiddles = st->twiddles;
- kiss_fft_cpx t;
- int Norig = st->nfft;
-
- kiss_fft_cpx * scratch = (kiss_fft_cpx*)KISS_FFT_TMP_ALLOC(sizeof(kiss_fft_cpx)*p);
-
- for ( u=0; u<m; ++u ) {
- k=u;
- for ( q1=0 ; q1<p ; ++q1 ) {
- scratch[q1] = Fout[ k ];
- C_FIXDIV(scratch[q1],p);
- k += m;
- }
-
- k=u;
- for ( q1=0 ; q1<p ; ++q1 ) {
- int twidx=0;
- Fout[ k ] = scratch[0];
- for (q=1;q<p;++q ) {
- twidx += fstride * k;
- if (twidx>=Norig) twidx-=Norig;
- C_MUL(t,scratch[q] , twiddles[twidx] );
- C_ADDTO( Fout[ k ] ,t);
- }
- k += m;
- }
- }
- KISS_FFT_TMP_FREE(scratch);
-}
-
-static
-void kf_work(
- kiss_fft_cpx * Fout,
- const kiss_fft_cpx * f,
- const size_t fstride,
- int in_stride,
- int * factors,
- const kiss_fft_cfg st
- )
-{
- kiss_fft_cpx * Fout_beg=Fout;
- const int p=*factors++; /* the radix */
- const int m=*factors++; /* stage's fft length/p */
- const kiss_fft_cpx * Fout_end = Fout + p*m;
-
-#ifdef _OPENMP
- // use openmp extensions at the
- // top-level (not recursive)
- if (fstride==1 && p<=5)
- {
- int k;
-
- // execute the p different work units in different threads
-# pragma omp parallel for
- for (k=0;k<p;++k)
- kf_work( Fout +k*m, f+ fstride*in_stride*k,fstride*p,in_stride,factors,st);
- // all threads have joined by this point
-
- switch (p) {
- case 2: kf_bfly2(Fout,fstride,st,m); break;
- case 3: kf_bfly3(Fout,fstride,st,m); break;
- case 4: kf_bfly4(Fout,fstride,st,m); break;
- case 5: kf_bfly5(Fout,fstride,st,m); break;
- default: kf_bfly_generic(Fout,fstride,st,m,p); break;
- }
- return;
- }
-#endif
-
- if (m==1) {
- do{
- *Fout = *f;
- f += fstride*in_stride;
- }while(++Fout != Fout_end );
- }else{
- do{
- // recursive call:
- // DFT of size m*p performed by doing
- // p instances of smaller DFTs of size m,
- // each one takes a decimated version of the input
- kf_work( Fout , f, fstride*p, in_stride, factors,st);
- f += fstride*in_stride;
- }while( (Fout += m) != Fout_end );
- }
-
- Fout=Fout_beg;
-
- // recombine the p smaller DFTs
- switch (p) {
- case 2: kf_bfly2(Fout,fstride,st,m); break;
- case 3: kf_bfly3(Fout,fstride,st,m); break;
- case 4: kf_bfly4(Fout,fstride,st,m); break;
- case 5: kf_bfly5(Fout,fstride,st,m); break;
- default: kf_bfly_generic(Fout,fstride,st,m,p); break;
- }
-}
-
-/* facbuf is populated by p1,m1,p2,m2, ...
- where
- p[i] * m[i] = m[i-1]
- m0 = n */
-static
-void kf_factor(int n,int * facbuf)
-{
- int p=4;
- double floor_sqrt;
- floor_sqrt = floor( sqrt((double)n) );
-
- /*factor out powers of 4, powers of 2, then any remaining primes */
- do {
- while (n % p) {
- switch (p) {
- case 4: p = 2; break;
- case 2: p = 3; break;
- default: p += 2; break;
- }
- if (p > floor_sqrt)
- p = n; /* no more factors, skip to end */
- }
- n /= p;
- *facbuf++ = p;
- *facbuf++ = n;
- } while (n > 1);
-}
-
-/*
- *
- * User-callable function to allocate all necessary storage space for the fft.
- *
- * The return value is a contiguous block of memory, allocated with malloc. As such,
- * It can be freed with free(), rather than a kiss_fft-specific function.
- * */
-kiss_fft_cfg kiss_fft_alloc(int nfft,int inverse_fft,void * mem,size_t * lenmem )
-{
- kiss_fft_cfg st=NULL;
- size_t memneeded = sizeof(struct kiss_fft_state)
- + sizeof(kiss_fft_cpx)*(nfft-1); /* twiddle factors*/
-
- if ( lenmem==NULL ) {
- st = ( kiss_fft_cfg)KISS_FFT_MALLOC( memneeded );
- }else{
- if (mem != NULL && *lenmem >= memneeded)
- st = (kiss_fft_cfg)mem;
- *lenmem = memneeded;
- }
- if (st) {
- int i;
- st->nfft=nfft;
- st->inverse = inverse_fft;
-
- for (i=0;i<nfft;++i) {
- const double pi=3.141592653589793238462643383279502884197169399375105820974944;
- double phase = -2*pi*i / nfft;
- if (st->inverse)
- phase *= -1;
- kf_cexp(st->twiddles+i, phase );
- }
-
- kf_factor(nfft,st->factors);
- }
- return st;
-}
-
-
-void kiss_fft_stride(kiss_fft_cfg st,const kiss_fft_cpx *fin,kiss_fft_cpx *fout,int in_stride)
-{
- if (fin == fout) {
- //NOTE: this is not really an in-place FFT algorithm.
- //It just performs an out-of-place FFT into a temp buffer
- kiss_fft_cpx * tmpbuf = (kiss_fft_cpx*)KISS_FFT_TMP_ALLOC( sizeof(kiss_fft_cpx)*st->nfft);
- kf_work(tmpbuf,fin,1,in_stride, st->factors,st);
- memcpy(fout,tmpbuf,sizeof(kiss_fft_cpx)*st->nfft);
- KISS_FFT_TMP_FREE(tmpbuf);
- }else{
- kf_work( fout, fin, 1,in_stride, st->factors,st );
- }
-}
-
-void kiss_fft(kiss_fft_cfg cfg,const kiss_fft_cpx *fin,kiss_fft_cpx *fout)
-{
- kiss_fft_stride(cfg,fin,fout,1);
-}
-
-
-void kiss_fft_cleanup(void)
-{
- // nothing needed any more
-}
-
-int kiss_fft_next_fast_size(int n)
-{
- while(1) {
- int m=n;
- while ( (m%2) == 0 ) m/=2;
- while ( (m%3) == 0 ) m/=3;
- while ( (m%5) == 0 ) m/=5;
- if (m<=1)
- break; /* n is completely factorable by twos, threes, and fives */
- n++;
- }
- return n;
-}
+++ /dev/null
-#ifndef KISS_FFT_H
-#define KISS_FFT_H
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <math.h>
-#include <string.h>
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-/*
- ATTENTION!
- If you would like a :
- -- a utility that will handle the caching of fft objects
- -- real-only (no imaginary time component ) FFT
- -- a multi-dimensional FFT
- -- a command-line utility to perform ffts
- -- a command-line utility to perform fast-convolution filtering
-
- Then see kfc.h kiss_fftr.h kiss_fftnd.h fftutil.c kiss_fastfir.c
- in the tools/ directory.
-*/
-
-#ifdef USE_SIMD
-# include <xmmintrin.h>
-# define kiss_fft_scalar __m128
-#define KISS_FFT_MALLOC(nbytes) _mm_malloc(nbytes,16)
-#define KISS_FFT_FREE _mm_free
-#else
-#define KISS_FFT_MALLOC malloc
-#define KISS_FFT_FREE free
-#endif
-
-
-#ifdef FIXED_POINT
-#include <sys/types.h>
-# if (FIXED_POINT == 32)
-# define kiss_fft_scalar int32_t
-# else
-# define kiss_fft_scalar int16_t
-# endif
-#else
-# ifndef kiss_fft_scalar
-/* default is float */
-# define kiss_fft_scalar float
-# endif
-#endif
-
-typedef struct {
- kiss_fft_scalar r;
- kiss_fft_scalar i;
-}kiss_fft_cpx;
-
-typedef struct kiss_fft_state* kiss_fft_cfg;
-
-/*
- * kiss_fft_alloc
- *
- * Initialize a FFT (or IFFT) algorithm's cfg/state buffer.
- *
- * typical usage: kiss_fft_cfg mycfg=kiss_fft_alloc(1024,0,NULL,NULL);
- *
- * The return value from fft_alloc is a cfg buffer used internally
- * by the fft routine or NULL.
- *
- * If lenmem is NULL, then kiss_fft_alloc will allocate a cfg buffer using malloc.
- * The returned value should be free()d when done to avoid memory leaks.
- *
- * The state can be placed in a user supplied buffer 'mem':
- * If lenmem is not NULL and mem is not NULL and *lenmem is large enough,
- * then the function places the cfg in mem and the size used in *lenmem
- * and returns mem.
- *
- * If lenmem is not NULL and ( mem is NULL or *lenmem is not large enough),
- * then the function returns NULL and places the minimum cfg
- * buffer size in *lenmem.
- * */
-
-kiss_fft_cfg kiss_fft_alloc(int nfft,int inverse_fft,void * mem,size_t * lenmem);
-
-/*
- * kiss_fft(cfg,in_out_buf)
- *
- * Perform an FFT on a complex input buffer.
- * for a forward FFT,
- * fin should be f[0] , f[1] , ... ,f[nfft-1]
- * fout will be F[0] , F[1] , ... ,F[nfft-1]
- * Note that each element is complex and can be accessed like
- f[k].r and f[k].i
- * */
-void kiss_fft(kiss_fft_cfg cfg,const kiss_fft_cpx *fin,kiss_fft_cpx *fout);
-
-/*
- A more generic version of the above function. It reads its input from every Nth sample.
- * */
-void kiss_fft_stride(kiss_fft_cfg cfg,const kiss_fft_cpx *fin,kiss_fft_cpx *fout,int fin_stride);
-
-/* If kiss_fft_alloc allocated a buffer, it is one contiguous
- buffer and can be simply free()d when no longer needed*/
-#define kiss_fft_free free
-
-/*
- Cleans up some memory that gets managed internally. Not necessary to call, but it might clean up
- your compiler output to call this before you exit.
-*/
-void kiss_fft_cleanup(void);
-
-
-/*
- * Returns the smallest integer k, such that k>=n and k has only "fast" factors (2,3,5)
- */
-int kiss_fft_next_fast_size(int n);
-
-/* for real ffts, we need an even size */
-#define kiss_fftr_next_fast_size_real(n) \
- (kiss_fft_next_fast_size( ((n)+1)>>1)<<1)
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif
+++ /dev/null
-#!/bin/sh
-# listensim.sh
-# David Rowe 10 Sep 2009
-#
-# Listen to files processed with sim.sh
-
-../script/menu.sh ../raw/$1.raw $1_uq.raw $1_phase0.raw $1_lpc10.raw $1_lsp.raw $1_phase0_lpc10.raw $1_phase0_lsp.raw $1_phase0_lsp.raw $2 $3
-
-
+++ /dev/null
-#!/bin/sh
-# listen1.sh
-# David Rowe 10 Sep 2009
-#
-# Run menu with common sample file options, headphone version
-
-#../script/menu.sh ../raw/$1.raw $1_uq.raw $1_phase0.raw $1_lpc10.raw $1_lsp.raw $1_phase0_lpc10.raw $1_phase0_lsp.raw ../raw/$1_g729a.raw $2 $3 -d /dev/dsp1
-
-# compare to other codecs
-
-#../script/menu.sh ../raw/$1.raw $1_phase0_lsp.raw $1_phase0_lsp_20.raw ../raw/$1_g729a.raw ../raw/$1_gsm13k.raw ../raw/$1_speex_8k.raw $2 $3 -d /dev/dsp1
-
-../script/menu.sh ../raw/$1.raw $1_uq.raw $1_phase0.raw $1_test.raw ../raw/$1_g729a.raw $2 $3 -d /dev/dsp1
-
-
+++ /dev/null
-#!/bin/sh
-# listensim.sh
-# David Rowe 10 Sep 2009
-#
-# Listen to files processed with sim.sh
-
-../script/menu.sh $1_uq.raw $1_lpc10.raw $1_lpcpf.raw $1_phase0.raw $1_phase0_lpcpf.raw $2 $3 $4 $5
-
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: lpc.c
- AUTHOR......: David Rowe
- DATE CREATED: 30 Sep 1990 (!)
-
- Linear Prediction functions written in C.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009-2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#define LPC_MAX_N 512 /* maximum no. of samples in frame */
-#define PI 3.141592654 /* mathematical constant */
-
-#define ALPHA 1.0
-#define BETA 0.94
-
-#include <assert.h>
-#include <math.h>
-#include "defines.h"
-#include "lpc.h"
-
-/*---------------------------------------------------------------------------*\
-
- pre_emp()
-
- Pre-emphasise (high pass filter with zero close to 0 Hz) a frame of
- speech samples. Helps reduce dynamic range of LPC spectrum, giving
- greater weight and hensea better match to low energy formants.
-
- Should be balanced by de-emphasis of the output speech.
-
-\*---------------------------------------------------------------------------*/
-
-void pre_emp(
- float Sn_pre[], /* output frame of speech samples */
- float Sn[], /* input frame of speech samples */
- float *mem, /* Sn[-1]single sample memory */
- int Nsam /* number of speech samples to use */
-)
-{
- int i;
-
- for(i=0; i<Nsam; i++) {
- Sn_pre[i] = Sn[i] - ALPHA * mem[0];
- mem[0] = Sn[i];
- }
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- de_emp()
-
- De-emphasis filter (low pass filter with polse close to 0 Hz).
-
-\*---------------------------------------------------------------------------*/
-
-void de_emp(
- float Sn_de[], /* output frame of speech samples */
- float Sn[], /* input frame of speech samples */
- float *mem, /* Sn[-1]single sample memory */
- int Nsam /* number of speech samples to use */
-)
-{
- int i;
-
- for(i=0; i<Nsam; i++) {
- Sn_de[i] = Sn[i] + BETA * mem[0];
- mem[0] = Sn_de[i];
- }
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- hanning_window()
-
- Hanning windows a frame of speech samples.
-
-\*---------------------------------------------------------------------------*/
-
-void hanning_window(
- float Sn[], /* input frame of speech samples */
- float Wn[], /* output frame of windowed samples */
- int Nsam /* number of samples */
-)
-{
- int i; /* loop variable */
-
- for(i=0; i<Nsam; i++)
- Wn[i] = Sn[i]*(0.5 - 0.5*cos(2*PI*(float)i/(Nsam-1)));
-}
-
-/*---------------------------------------------------------------------------*\
-
- autocorrelate()
-
- Finds the first P autocorrelation values of an array of windowed speech
- samples Sn[].
-
-\*---------------------------------------------------------------------------*/
-
-void autocorrelate(
- float Sn[], /* frame of Nsam windowed speech samples */
- float Rn[], /* array of P+1 autocorrelation coefficients */
- int Nsam, /* number of windowed samples to use */
- int order /* order of LPC analysis */
-)
-{
- int i,j; /* loop variables */
-
- for(j=0; j<order+1; j++) {
- Rn[j] = 0.0;
- for(i=0; i<Nsam-j; i++)
- Rn[j] += Sn[i]*Sn[i+j];
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- levinson_durbin()
-
- Given P+1 autocorrelation coefficients, finds P Linear Prediction Coeff.
- (LPCs) where P is the order of the LPC all-pole model. The Levinson-Durbin
- algorithm is used, and is described in:
-
- J. Makhoul
- "Linear prediction, a tutorial review"
- Proceedings of the IEEE
- Vol-63, No. 4, April 1975
-
-\*---------------------------------------------------------------------------*/
-
-void levinson_durbin(
- float R[], /* order+1 autocorrelation coeff */
- float lpcs[], /* order+1 LPC's */
- int order /* order of the LPC analysis */
-)
-{
- float E[LPC_MAX+1];
- float k[LPC_MAX+1];
- float a[LPC_MAX+1][LPC_MAX+1];
- float sum;
- int i,j; /* loop variables */
-
- E[0] = R[0]; /* Equation 38a, Makhoul */
-
- for(i=1; i<=order; i++) {
- sum = 0.0;
- for(j=1; j<=i-1; j++)
- sum += a[i-1][j]*R[i-j];
- k[i] = -1.0*(R[i] + sum)/E[i-1]; /* Equation 38b, Makhoul */
- if (fabs(k[i]) > 1.0)
- k[i] = 0.0;
-
- a[i][i] = k[i];
-
- for(j=1; j<=i-1; j++)
- a[i][j] = a[i-1][j] + k[i]*a[i-1][i-j]; /* Equation 38c, Makhoul */
-
- E[i] = (1-k[i]*k[i])*E[i-1]; /* Equation 38d, Makhoul */
- }
-
- for(i=1; i<=order; i++)
- lpcs[i] = a[order][i];
- lpcs[0] = 1.0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- inverse_filter()
-
- Inverse Filter, A(z). Produces an array of residual samples from an array
- of input samples and linear prediction coefficients.
-
- The filter memory is stored in the first order samples of the input array.
-
-\*---------------------------------------------------------------------------*/
-
-void inverse_filter(
- float Sn[], /* Nsam input samples */
- float a[], /* LPCs for this frame of samples */
- int Nsam, /* number of samples */
- float res[], /* Nsam residual samples */
- int order /* order of LPC */
-)
-{
- int i,j; /* loop variables */
-
- for(i=0; i<Nsam; i++) {
- res[i] = 0.0;
- for(j=0; j<=order; j++)
- res[i] += Sn[i-j]*a[j];
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- synthesis_filter()
-
- C version of the Speech Synthesis Filter, 1/A(z). Given an array of
- residual or excitation samples, and the the LP filter coefficients, this
- function will produce an array of speech samples. This filter structure is
- IIR.
-
- The synthesis filter has memory as well, this is treated in the same way
- as the memory for the inverse filter (see inverse_filter() notes above).
- The difference is that the memory for the synthesis filter is stored in
- the output array, wheras the memory of the inverse filter is stored in the
- input array.
-
- Note: the calling function must update the filter memory.
-
-\*---------------------------------------------------------------------------*/
-
-void synthesis_filter(
- float res[], /* Nsam input residual (excitation) samples */
- float a[], /* LPCs for this frame of speech samples */
- int Nsam, /* number of speech samples */
- int order, /* LPC order */
- float Sn_[] /* Nsam output synthesised speech samples */
-)
-{
- int i,j; /* loop variables */
-
- /* Filter Nsam samples */
-
- for(i=0; i<Nsam; i++) {
- Sn_[i] = res[i]*a[0];
- for(j=1; j<=order; j++)
- Sn_[i] -= Sn_[i-j]*a[j];
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- find_aks()
-
- This function takes a frame of samples, and determines the linear
- prediction coefficients for that frame of samples.
-
-\*---------------------------------------------------------------------------*/
-
-void find_aks(
- float Sn[], /* Nsam samples with order sample memory */
- float a[], /* order+1 LPCs with first coeff 1.0 */
- int Nsam, /* number of input speech samples */
- int order, /* order of the LPC analysis */
- float *E /* residual energy */
-)
-{
- float Wn[LPC_MAX_N]; /* windowed frame of Nsam speech samples */
- float R[LPC_MAX+1]; /* order+1 autocorrelation values of Sn[] */
- int i;
-
- assert(order < LPC_MAX);
- assert(Nsam < LPC_MAX_N);
-
- hanning_window(Sn,Wn,Nsam);
- autocorrelate(Wn,R,Nsam,order);
- levinson_durbin(R,a,order);
-
- *E = 0.0;
- for(i=0; i<=order; i++)
- *E += a[i]*R[i];
- if (*E < 0.0)
- *E = 1E-12;
-}
-
-/*---------------------------------------------------------------------------*\
-
- weight()
-
- Weights a vector of LPCs.
-
-\*---------------------------------------------------------------------------*/
-
-void weight(
- float ak[], /* vector of order+1 LPCs */
- float gamma, /* weighting factor */
- int order, /* num LPCs (excluding leading 1.0) */
- float akw[] /* weighted vector of order+1 LPCs */
-)
-{
- int i;
-
- for(i=1; i<=order; i++)
- akw[i] = ak[i]*pow(gamma,(float)i);
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: lpc.h
- AUTHOR......: David Rowe
- DATE CREATED: 24/8/09
-
- Linear Prediction functions written in C.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009-2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __LPC__
-#define __LPC__
-
-#define LPC_MAX_ORDER 20
-
-void pre_emp(float Sn_pre[], float Sn[], float *mem, int Nsam);
-void de_emp(float Sn_se[], float Sn[], float *mem, int Nsam);
-void hanning_window(float Sn[], float Wn[], int Nsam);
-void autocorrelate(float Sn[], float Rn[], int Nsam, int order);
-void levinson_durbin(float R[], float lpcs[], int order);
-void inverse_filter(float Sn[], float a[], int Nsam, float res[], int order);
-void synthesis_filter(float res[], float a[], int Nsam, int order, float Sn_[]);
-void find_aks(float Sn[], float a[], int Nsam, int order, float *E);
-void weight(float ak[], float gamma, int order, float akw[]);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: lsp.c
- AUTHOR......: David Rowe
- DATE CREATED: 24/2/93
-
-
- This file contains functions for LPC to LSP conversion and LSP to
- LPC conversion. Note that the LSP coefficients are not in radians
- format but in the x domain of the unit circle.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "defines.h"
-#include "lsp.h"
-#include <math.h>
-#include <stdio.h>
-#include <stdlib.h>
-
-/* Only 10 gets used, so far. */
-#define LSP_MAX_ORDER 20
-
-/*---------------------------------------------------------------------------*\
-
- Introduction to Line Spectrum Pairs (LSPs)
- ------------------------------------------
-
- LSPs are used to encode the LPC filter coefficients {ak} for
- transmission over the channel. LSPs have several properties (like
- less sensitivity to quantisation noise) that make them superior to
- direct quantisation of {ak}.
-
- A(z) is a polynomial of order lpcrdr with {ak} as the coefficients.
-
- A(z) is transformed to P(z) and Q(z) (using a substitution and some
- algebra), to obtain something like:
-
- A(z) = 0.5[P(z)(z+z^-1) + Q(z)(z-z^-1)] (1)
-
- As you can imagine A(z) has complex zeros all over the z-plane. P(z)
- and Q(z) have the very neat property of only having zeros _on_ the
- unit circle. So to find them we take a test point z=exp(jw) and
- evaluate P (exp(jw)) and Q(exp(jw)) using a grid of points between 0
- and pi.
-
- The zeros (roots) of P(z) also happen to alternate, which is why we
- swap coefficients as we find roots. So the process of finding the
- LSP frequencies is basically finding the roots of 5th order
- polynomials.
-
- The root so P(z) and Q(z) occur in symmetrical pairs at +/-w, hence
- the name Line Spectrum Pairs (LSPs).
-
- To convert back to ak we just evaluate (1), "clocking" an impulse
- thru it lpcrdr times gives us the impulse response of A(z) which is
- {ak}.
-
-\*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: cheb_poly_eva()
- AUTHOR......: David Rowe
- DATE CREATED: 24/2/93
-
- This function evalutes a series of chebyshev polynomials
-
- FIXME: performing memory allocation at run time is very inefficient,
- replace with stack variables of MAX_P size.
-
-\*---------------------------------------------------------------------------*/
-
-
-static float
-cheb_poly_eva(float *coef,float x,int m)
-/* float coef[] coefficients of the polynomial to be evaluated */
-/* float x the point where polynomial is to be evaluated */
-/* int m order of the polynomial */
-{
- int i;
- float *t,*u,*v,sum;
- float T[(LSP_MAX_ORDER / 2) + 1];
-
- /* Initialise pointers */
-
- t = T; /* T[i-2] */
- *t++ = 1.0;
- u = t--; /* T[i-1] */
- *u++ = x;
- v = u--; /* T[i] */
-
- /* Evaluate chebyshev series formulation using iterative approach */
-
- for(i=2;i<=m/2;i++)
- *v++ = (2*x)*(*u++) - *t++; /* T[i] = 2*x*T[i-1] - T[i-2] */
-
- sum=0.0; /* initialise sum to zero */
- t = T; /* reset pointer */
-
- /* Evaluate polynomial and return value also free memory space */
-
- for(i=0;i<=m/2;i++)
- sum+=coef[(m/2)-i]**t++;
-
- return sum;
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: lpc_to_lsp()
- AUTHOR......: David Rowe
- DATE CREATED: 24/2/93
-
- This function converts LPC coefficients to LSP coefficients.
-
-\*---------------------------------------------------------------------------*/
-
-int lpc_to_lsp (float *a, int lpcrdr, float *freq, int nb, float delta)
-/* float *a lpc coefficients */
-/* int lpcrdr order of LPC coefficients (10) */
-/* float *freq LSP frequencies in radians */
-/* int nb number of sub-intervals (4) */
-/* float delta grid spacing interval (0.02) */
-{
- float psuml,psumr,psumm,temp_xr,xl,xr,xm = 0;
- float temp_psumr;
- int i,j,m,flag,k;
- float *px; /* ptrs of respective P'(z) & Q'(z) */
- float *qx;
- float *p;
- float *q;
- float *pt; /* ptr used for cheb_poly_eval()
- whether P' or Q' */
- int roots=0; /* number of roots found */
- float Q[LSP_MAX_ORDER + 1];
- float P[LSP_MAX_ORDER + 1];
-
- flag = 1;
- m = lpcrdr/2; /* order of P'(z) & Q'(z) polynimials */
-
- /* Allocate memory space for polynomials */
-
- /* determine P'(z)'s and Q'(z)'s coefficients where
- P'(z) = P(z)/(1 + z^(-1)) and Q'(z) = Q(z)/(1-z^(-1)) */
-
- px = P; /* initilaise ptrs */
- qx = Q;
- p = px;
- q = qx;
- *px++ = 1.0;
- *qx++ = 1.0;
- for(i=1;i<=m;i++){
- *px++ = a[i]+a[lpcrdr+1-i]-*p++;
- *qx++ = a[i]-a[lpcrdr+1-i]+*q++;
- }
- px = P;
- qx = Q;
- for(i=0;i<m;i++){
- *px = 2**px;
- *qx = 2**qx;
- px++;
- qx++;
- }
- px = P; /* re-initialise ptrs */
- qx = Q;
-
- /* Search for a zero in P'(z) polynomial first and then alternate to Q'(z).
- Keep alternating between the two polynomials as each zero is found */
-
- xr = 0; /* initialise xr to zero */
- xl = 1.0; /* start at point xl = 1 */
-
-
- for(j=0;j<lpcrdr;j++){
- if(j%2) /* determines whether P' or Q' is eval. */
- pt = qx;
- else
- pt = px;
-
- psuml = cheb_poly_eva(pt,xl,lpcrdr); /* evals poly. at xl */
- flag = 1;
- while(flag && (xr >= -1.0)){
- xr = xl - delta ; /* interval spacing */
- psumr = cheb_poly_eva(pt,xr,lpcrdr);/* poly(xl-delta_x) */
- temp_psumr = psumr;
- temp_xr = xr;
-
- /* if no sign change increment xr and re-evaluate
- poly(xr). Repeat til sign change. if a sign change has
- occurred the interval is bisected and then checked again
- for a sign change which determines in which interval the
- zero lies in. If there is no sign change between poly(xm)
- and poly(xl) set interval between xm and xr else set
- interval between xl and xr and repeat till root is located
- within the specified limits */
-
- if((psumr*psuml)<0.0){
- roots++;
-
- psumm=psuml;
- for(k=0;k<=nb;k++){
- xm = (xl+xr)/2; /* bisect the interval */
- psumm=cheb_poly_eva(pt,xm,lpcrdr);
- if(psumm*psuml>0.){
- psuml=psumm;
- xl=xm;
- }
- else{
- psumr=psumm;
- xr=xm;
- }
- }
-
- /* once zero is found, reset initial interval to xr */
- freq[j] = (xm);
- xl = xm;
- flag = 0; /* reset flag for next search */
- }
- else{
- psuml=temp_psumr;
- xl=temp_xr;
- }
- }
- }
-
- /* convert from x domain to radians */
-
- for(i=0; i<lpcrdr; i++) {
- freq[i] = acos(freq[i]);
- }
-
- return(roots);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: lsp_to_lpc()
- AUTHOR......: David Rowe
- DATE CREATED: 24/2/93
-
- This function converts LSP coefficients to LPC coefficients. In the
- Speex code we worked out a way to simplify this significantly.
-
-\*---------------------------------------------------------------------------*/
-
-void lsp_to_lpc(float *lsp, float *ak, int lpcrdr)
-/* float *freq array of LSP frequencies in radians */
-/* float *ak array of LPC coefficients */
-/* int lpcrdr order of LPC coefficients */
-
-
-{
- int i,j;
- float xout1,xout2,xin1,xin2;
- float *pw,*n1,*n2,*n3,*n4 = 0;
- int m = lpcrdr/2;
- float freq[LSP_MAX_ORDER];
- float Wp[(LSP_MAX_ORDER * 4) + 2];
-
- /* convert from radians to the x=cos(w) domain */
-
- for(i=0; i<lpcrdr; i++)
- freq[i] = cos(lsp[i]);
-
- pw = Wp;
-
- /* initialise contents of array */
-
- for(i=0;i<=4*m+1;i++){ /* set contents of buffer to 0 */
- *pw++ = 0.0;
- }
-
- /* Set pointers up */
-
- pw = Wp;
- xin1 = 1.0;
- xin2 = 1.0;
-
- /* reconstruct P(z) and Q(z) by cascading second order polynomials
- in form 1 - 2xz(-1) +z(-2), where x is the LSP coefficient */
-
- for(j=0;j<=lpcrdr;j++){
- for(i=0;i<m;i++){
- n1 = pw+(i*4);
- n2 = n1 + 1;
- n3 = n2 + 1;
- n4 = n3 + 1;
- xout1 = xin1 - 2*(freq[2*i]) * *n1 + *n2;
- xout2 = xin2 - 2*(freq[2*i+1]) * *n3 + *n4;
- *n2 = *n1;
- *n4 = *n3;
- *n1 = xin1;
- *n3 = xin2;
- xin1 = xout1;
- xin2 = xout2;
- }
- xout1 = xin1 + *(n4+1);
- xout2 = xin2 - *(n4+2);
- ak[j] = (xout1 + xout2)*0.5;
- *(n4+1) = xin1;
- *(n4+2) = xin2;
-
- xin1 = 0.0;
- xin2 = 0.0;
- }
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: lsp.c
- AUTHOR......: David Rowe
- DATE CREATED: 24/2/93
-
-
- This file contains functions for LPC to LSP conversion and LSP to
- LPC conversion. Note that the LSP coefficients are not in radians
- format but in the x domain of the unit circle.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __LSP__
-#define __LSP__
-
-int lpc_to_lsp (float *a, int lpcrdr, float *freq, int nb, float delta);
-void lsp_to_lpc(float *freq, float *ak, int lpcrdr);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: nlp.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/3/93
-
- Non Linear Pitch (NLP) estimation functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "defines.h"
-#include "nlp.h"
-#include "dump.h"
-#include "kiss_fft.h"
-
-#include <assert.h>
-#include <math.h>
-#include <stdlib.h>
-
-/*---------------------------------------------------------------------------*\
-
- DEFINES
-
-\*---------------------------------------------------------------------------*/
-
-#define PMAX_M 600 /* maximum NLP analysis window size */
-#define COEFF 0.95 /* notch filter parameter */
-#define PE_FFT_SIZE 512 /* DFT size for pitch estimation */
-#define DEC 5 /* decimation factor */
-#define SAMPLE_RATE 8000
-#define PI 3.141592654 /* mathematical constant */
-#define T 0.1 /* threshold for local minima candidate */
-#define F0_MAX 500
-#define CNLP 0.3 /* post processor constant */
-#define NLP_NTAP 48 /* Decimation LPF order */
-
-/*---------------------------------------------------------------------------*\
-
- GLOBALS
-
-\*---------------------------------------------------------------------------*/
-
-/* 48 tap 600Hz low pass FIR filter coefficients */
-
-const float nlp_fir[] = {
- -1.0818124e-03,
- -1.1008344e-03,
- -9.2768838e-04,
- -4.2289438e-04,
- 5.5034190e-04,
- 2.0029849e-03,
- 3.7058509e-03,
- 5.1449415e-03,
- 5.5924666e-03,
- 4.3036754e-03,
- 8.0284511e-04,
- -4.8204610e-03,
- -1.1705810e-02,
- -1.8199275e-02,
- -2.2065282e-02,
- -2.0920610e-02,
- -1.2808831e-02,
- 3.2204775e-03,
- 2.6683811e-02,
- 5.5520624e-02,
- 8.6305944e-02,
- 1.1480192e-01,
- 1.3674206e-01,
- 1.4867556e-01,
- 1.4867556e-01,
- 1.3674206e-01,
- 1.1480192e-01,
- 8.6305944e-02,
- 5.5520624e-02,
- 2.6683811e-02,
- 3.2204775e-03,
- -1.2808831e-02,
- -2.0920610e-02,
- -2.2065282e-02,
- -1.8199275e-02,
- -1.1705810e-02,
- -4.8204610e-03,
- 8.0284511e-04,
- 4.3036754e-03,
- 5.5924666e-03,
- 5.1449415e-03,
- 3.7058509e-03,
- 2.0029849e-03,
- 5.5034190e-04,
- -4.2289438e-04,
- -9.2768838e-04,
- -1.1008344e-03,
- -1.0818124e-03
-};
-
-typedef struct {
- float sq[PMAX_M]; /* squared speech samples */
- float mem_x,mem_y; /* memory for notch filter */
- float mem_fir[NLP_NTAP]; /* decimation FIR filter memory */
- kiss_fft_cfg fft_cfg; /* kiss FFT config */
-} NLP;
-
-float test_candidate_mbe(COMP Sw[], COMP W[], float f0);
-float post_process_mbe(COMP Fw[], int pmin, int pmax, float gmax, COMP Sw[], COMP W[], float *prev_Wo);
-float post_process_sub_multiples(COMP Fw[],
- int pmin, int pmax, float gmax, int gmax_bin,
- float *prev_Wo);
-
-/*---------------------------------------------------------------------------*\
-
- nlp_create()
-
- Initialisation function for NLP pitch estimator.
-
-\*---------------------------------------------------------------------------*/
-
-void *nlp_create()
-{
- NLP *nlp;
- int i;
-
- nlp = (NLP*)malloc(sizeof(NLP));
- if (nlp == NULL)
- return NULL;
-
- for(i=0; i<PMAX_M; i++)
- nlp->sq[i] = 0.0;
- nlp->mem_x = 0.0;
- nlp->mem_y = 0.0;
- for(i=0; i<NLP_NTAP; i++)
- nlp->mem_fir[i] = 0.0;
-
- nlp->fft_cfg = kiss_fft_alloc (PE_FFT_SIZE, 0, NULL, NULL);
- assert(nlp->fft_cfg != NULL);
-
- return (void*)nlp;
-}
-
-/*---------------------------------------------------------------------------*\
-
- nlp_destroy()
-
- Shut down function for NLP pitch estimator.
-
-\*---------------------------------------------------------------------------*/
-
-void nlp_destroy(void *nlp_state)
-{
- NLP *nlp;
- assert(nlp_state != NULL);
- nlp = (NLP*)nlp_state;
-
- KISS_FFT_FREE(nlp->fft_cfg);
- free(nlp_state);
-}
-
-/*---------------------------------------------------------------------------*\
-
- nlp()
-
- Determines the pitch in samples using the Non Linear Pitch (NLP)
- algorithm [1]. Returns the fundamental in Hz. Note that the actual
- pitch estimate is for the centre of the M sample Sn[] vector, not
- the current N sample input vector. This is (I think) a delay of 2.5
- frames with N=80 samples. You should align further analysis using
- this pitch estimate to be centred on the middle of Sn[].
-
- Two post processors have been tried, the MBE version (as discussed
- in [1]), and a post processor that checks sub-multiples. Both
- suffer occasional gross pitch errors (i.e. neither are perfect). In
- the presence of background noise the sub-multiple algorithm tends
- towards low F0 which leads to better sounding background noise than
- the MBE post processor.
-
- A good way to test and develop the NLP pitch estimator is using the
- tnlp (codec2/unittest) and the codec2/octave/plnlp.m Octave script.
-
- A pitch tracker searching a few frames forward and backward in time
- would be a useful addition.
-
- References:
-
- [1] http://www.itr.unisa.edu.au/~steven/thesis/dgr.pdf Chapter 4
-
-\*---------------------------------------------------------------------------*/
-
-float nlp(
- void *nlp_state,
- float Sn[], /* input speech vector */
- int n, /* frames shift (no. new samples in Sn[]) */
- int m, /* analysis window size */
- int pmin, /* minimum pitch value */
- int pmax, /* maximum pitch value */
- float *pitch, /* estimated pitch period in samples */
- COMP Sw[], /* Freq domain version of Sn[] */
- COMP W[], /* Freq domain window */
- float *prev_Wo
-)
-{
- NLP *nlp;
- float notch; /* current notch filter output */
- COMP fw[PE_FFT_SIZE]; /* DFT of squared signal (input) */
- COMP Fw[PE_FFT_SIZE]; /* DFT of squared signal (output) */
- float gmax;
- int gmax_bin;
- int i,j;
- float best_f0;
-
- assert(nlp_state != NULL);
- assert(m <= PMAX_M);
- nlp = (NLP*)nlp_state;
-
- /* Square, notch filter at DC, and LP filter vector */
-
- for(i=m-n; i<m; i++) /* square latest speech samples */
- nlp->sq[i] = Sn[i]*Sn[i];
-
- for(i=m-n; i<m; i++) { /* notch filter at DC */
- notch = nlp->sq[i] - nlp->mem_x;
- notch += COEFF*nlp->mem_y;
- nlp->mem_x = nlp->sq[i];
- nlp->mem_y = notch;
- nlp->sq[i] = notch + 1.0; /* With 0 input vectors to codec,
- kiss_fft() would take a long
- time to execute when running in
- real time. Problem was traced
- to kiss_fft function call in
- this function. Adding this small
- constant fixed problem. Not
- exactly sure why. */
- }
-
- for(i=m-n; i<m; i++) { /* FIR filter vector */
-
- for(j=0; j<NLP_NTAP-1; j++)
- nlp->mem_fir[j] = nlp->mem_fir[j+1];
- nlp->mem_fir[NLP_NTAP-1] = nlp->sq[i];
-
- nlp->sq[i] = 0.0;
- for(j=0; j<NLP_NTAP; j++)
- nlp->sq[i] += nlp->mem_fir[j]*nlp_fir[j];
- }
-
- /* Decimate and DFT */
-
- for(i=0; i<PE_FFT_SIZE; i++) {
- fw[i].real = 0.0;
- fw[i].imag = 0.0;
- }
- for(i=0; i<m/DEC; i++) {
- fw[i].real = nlp->sq[i*DEC]*(0.5 - 0.5*cos(2*PI*i/(m/DEC-1)));
- }
- #ifdef DUMP
- dump_dec(Fw);
- #endif
-
- kiss_fft(nlp->fft_cfg, (kiss_fft_cpx *)fw, (kiss_fft_cpx *)Fw);
- for(i=0; i<PE_FFT_SIZE; i++)
- Fw[i].real = Fw[i].real*Fw[i].real + Fw[i].imag*Fw[i].imag;
-
- #ifdef DUMP
- dump_sq(nlp->sq);
- dump_Fw(Fw);
- #endif
-
- /* find global peak */
-
- gmax = 0.0;
- gmax_bin = PE_FFT_SIZE*DEC/pmax;
- for(i=PE_FFT_SIZE*DEC/pmax; i<=PE_FFT_SIZE*DEC/pmin; i++) {
- if (Fw[i].real > gmax) {
- gmax = Fw[i].real;
- gmax_bin = i;
- }
- }
-
- //#define POST_PROCESS_MBE
- #ifdef POST_PROCESS_MBE
- best_f0 = post_process_mbe(Fw, pmin, pmax, gmax, Sw, W, prev_Wo);
- #else
- best_f0 = post_process_sub_multiples(Fw, pmin, pmax, gmax, gmax_bin, prev_Wo);
- #endif
-
- /* Shift samples in buffer to make room for new samples */
-
- for(i=0; i<m-n; i++)
- nlp->sq[i] = nlp->sq[i+n];
-
- /* return pitch and F0 estimate */
-
- *pitch = (float)SAMPLE_RATE/best_f0;
- return(best_f0);
-}
-
-/*---------------------------------------------------------------------------*\
-
- post_process_sub_multiples()
-
- Given the global maximma of Fw[] we search integer submultiples for
- local maxima. If local maxima exist and they are above an
- experimentally derived threshold (OK a magic number I pulled out of
- the air) we choose the submultiple as the F0 estimate.
-
- The rational for this is that the lowest frequency peak of Fw[]
- should be F0, as Fw[] can be considered the autocorrelation function
- of Sw[] (the speech spectrum). However sometimes due to phase
- effects the lowest frequency maxima may not be the global maxima.
-
- This works OK in practice and favours low F0 values in the presence
- of background noise which means the sinusoidal codec does an OK job
- of synthesising the background noise. High F0 in background noise
- tends to sound more periodic introducing annoying artifacts.
-
-\*---------------------------------------------------------------------------*/
-
-float post_process_sub_multiples(COMP Fw[],
- int pmin, int pmax, float gmax, int gmax_bin,
- float *prev_Wo)
-{
- int min_bin, cmax_bin;
- int mult;
- float thresh, best_f0;
- int b, bmin, bmax, lmax_bin;
- float lmax, cmax;
- int prev_f0_bin;
-
- /* post process estimate by searching submultiples */
-
- mult = 2;
- min_bin = PE_FFT_SIZE*DEC/pmax;
- cmax_bin = gmax_bin;
- prev_f0_bin = *prev_Wo*(4000.0/PI)*(PE_FFT_SIZE*DEC)/SAMPLE_RATE;
-
- while(gmax_bin/mult >= min_bin) {
-
- b = gmax_bin/mult; /* determine search interval */
- bmin = 0.8*b;
- bmax = 1.2*b;
- if (bmin < min_bin)
- bmin = min_bin;
-
- /* lower threshold to favour previous frames pitch estimate,
- this is a form of pitch tracking */
-
- if ((prev_f0_bin > bmin) && (prev_f0_bin < bmax))
- thresh = CNLP*0.5*gmax;
- else
- thresh = CNLP*gmax;
-
- lmax = 0;
- lmax_bin = bmin;
- for (b=bmin; b<=bmax; b++) /* look for maximum in interval */
- if (Fw[b].real > lmax) {
- lmax = Fw[b].real;
- lmax_bin = b;
- }
-
- if (lmax > thresh)
- if ((lmax > Fw[lmax_bin-1].real) && (lmax > Fw[lmax_bin+1].real)) {
- cmax = lmax;
- cmax_bin = lmax_bin;
- }
-
- mult++;
- }
-
- best_f0 = (float)cmax_bin*SAMPLE_RATE/(PE_FFT_SIZE*DEC);
-
- return best_f0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- post_process_mbe()
-
- Use the MBE pitch estimation algorithm to evaluate pitch candidates. This
- works OK but the accuracy at low F0 is affected by NW, the analysis window
- size used for the DFT of the input speech Sw[]. Also favours high F0 in
- the presence of background noise which causes periodic artifacts in the
- synthesised speech.
-
-\*---------------------------------------------------------------------------*/
-
-float post_process_mbe(COMP Fw[], int pmin, int pmax, float gmax, COMP Sw[], COMP W[], float *prev_Wo)
-{
- float candidate_f0;
- float f0,best_f0; /* fundamental frequency */
- float e,e_min; /* MBE cost function */
- int i;
- float e_hz[F0_MAX];
- int bin;
- float f0_min, f0_max;
- float f0_start, f0_end;
-
- f0_min = (float)SAMPLE_RATE/pmax;
- f0_max = (float)SAMPLE_RATE/pmin;
-
- /* Now look for local maxima. Each local maxima is a candidate
- that we test using the MBE pitch estimation algotithm */
-
- for(i=0; i<F0_MAX; i++)
- e_hz[i] = -1;
- e_min = 1E32;
- best_f0 = 50;
- for(i=PE_FFT_SIZE*DEC/pmax; i<=PE_FFT_SIZE*DEC/pmin; i++) {
- if ((Fw[i].real > Fw[i-1].real) && (Fw[i].real > Fw[i+1].real)) {
-
- /* local maxima found, lets test if it's big enough */
-
- if (Fw[i].real > T*gmax) {
-
- /* OK, sample MBE cost function over +/- 10Hz range in 2.5Hz steps */
-
- candidate_f0 = (float)i*SAMPLE_RATE/(PE_FFT_SIZE*DEC);
- f0_start = candidate_f0-20;
- f0_end = candidate_f0+20;
- if (f0_start < f0_min) f0_start = f0_min;
- if (f0_end > f0_max) f0_end = f0_max;
-
- for(f0=f0_start; f0<=f0_end; f0+= 2.5) {
- e = test_candidate_mbe(Sw, W, f0);
- bin = floor(f0); assert((bin > 0) && (bin < F0_MAX));
- e_hz[bin] = e;
- if (e < e_min) {
- e_min = e;
- best_f0 = f0;
- }
- }
-
- }
- }
- }
-
- /* finally sample MBE cost function around previous pitch estimate
- (form of pitch tracking) */
-
- candidate_f0 = *prev_Wo * SAMPLE_RATE/TWO_PI;
- f0_start = candidate_f0-20;
- f0_end = candidate_f0+20;
- if (f0_start < f0_min) f0_start = f0_min;
- if (f0_end > f0_max) f0_end = f0_max;
-
- for(f0=f0_start; f0<=f0_end; f0+= 2.5) {
- e = test_candidate_mbe(Sw, W, f0);
- bin = floor(f0); assert((bin > 0) && (bin < F0_MAX));
- e_hz[bin] = e;
- if (e < e_min) {
- e_min = e;
- best_f0 = f0;
- }
- }
-
- #ifdef DUMP
- dump_e(e_hz);
- #endif
-
- return best_f0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- test_candidate_mbe()
-
- Returns the error of the MBE cost function for the input f0.
-
- Note: I think a lot of the operations below can be simplified as
- W[].imag = 0 and has been normalised such that den always equals 1.
-
-\*---------------------------------------------------------------------------*/
-
-float test_candidate_mbe(
- COMP Sw[],
- COMP W[],
- float f0
-)
-{
- COMP Sw_[FFT_ENC]; /* DFT of all voiced synthesised signal */
- int l,al,bl,m; /* loop variables */
- COMP Am; /* amplitude sample for this band */
- int offset; /* centers Hw[] about current harmonic */
- float den; /* denominator of Am expression */
- float error; /* accumulated error between originl and synthesised */
- float Wo; /* current "test" fundamental freq. */
- int L;
-
- L = floor((SAMPLE_RATE/2.0)/f0);
- Wo = f0*(2*PI/SAMPLE_RATE);
-
- error = 0.0;
-
- /* Just test across the harmonics in the first 1000 Hz (L/4) */
-
- for(l=1; l<L/4; l++) {
- Am.real = 0.0;
- Am.imag = 0.0;
- den = 0.0;
- al = ceil((l - 0.5)*Wo*FFT_ENC/TWO_PI);
- bl = ceil((l + 0.5)*Wo*FFT_ENC/TWO_PI);
-
- /* Estimate amplitude of harmonic assuming harmonic is totally voiced */
-
- for(m=al; m<bl; m++) {
- offset = FFT_ENC/2 + m - l*Wo*FFT_ENC/TWO_PI + 0.5;
- Am.real += Sw[m].real*W[offset].real + Sw[m].imag*W[offset].imag;
- Am.imag += Sw[m].imag*W[offset].real - Sw[m].real*W[offset].imag;
- den += W[offset].real*W[offset].real + W[offset].imag*W[offset].imag;
- }
-
- Am.real = Am.real/den;
- Am.imag = Am.imag/den;
-
- /* Determine error between estimated harmonic and original */
-
- for(m=al; m<bl; m++) {
- offset = FFT_ENC/2 + m - l*Wo*FFT_ENC/TWO_PI + 0.5;
- Sw_[m].real = Am.real*W[offset].real - Am.imag*W[offset].imag;
- Sw_[m].imag = Am.real*W[offset].imag + Am.imag*W[offset].real;
- error += (Sw[m].real - Sw_[m].real)*(Sw[m].real - Sw_[m].real);
- error += (Sw[m].imag - Sw_[m].imag)*(Sw[m].imag - Sw_[m].imag);
- }
- }
-
- return error;
-}
-
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: nlp.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/3/93
-
- Non Linear Pitch (NLP) estimation functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __NLP__
-#define __NLP__
-
-#include "comp.h"
-
-void *nlp_create();
-void nlp_destroy(void *nlp_state);
-float nlp(void *nlp_state, float Sn[], int n, int m, int pmin, int pmax,
- float *pitch, COMP Sw[], COMP W[], float *prev_Wo);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: octave.c
- AUTHOR......: David Rowe
- DATE CREATED: April 28 2012
-
- Functions to save C arrays in GNU Octave matrix format. The output text
- file can be directly read into Octave using "load filename".
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <stdio.h>
-#include "octave.h"
-
-void octave_save_int(FILE *f, char name[], int data[], int rows, int cols)
-{
- int r,c;
-
- fprintf(f, "# name: %s\n", name);
- fprintf(f, "# type: matrix\n");
- fprintf(f, "# rows: %d\n", rows);
- fprintf(f, "# columns: %d\n", cols);
-
- for(r=0; r<rows; r++) {
- for(c=0; c<cols; c++)
- fprintf(f, " %d", data[r*cols+c]);
- fprintf(f, "\n");
- }
-
- fprintf(f, "\n\n");
-}
-
-void octave_save_float(FILE *f, char name[], float data[], int rows, int cols, int col_len)
-{
- int r,c;
-
- fprintf(f, "# name: %s\n", name);
- fprintf(f, "# type: matrix\n");
- fprintf(f, "# rows: %d\n", rows);
- fprintf(f, "# columns: %d\n", cols);
-
- for(r=0; r<rows; r++) {
- for(c=0; c<cols; c++)
- fprintf(f, " %f", data[r*col_len+c]);
- fprintf(f, "\n");
- }
-
- fprintf(f, "\n\n");
-}
-
-void octave_save_complex(FILE *f, char name[], COMP data[], int rows, int cols, int col_len)
-{
- int r,c;
-
- fprintf(f, "# name: %s\n", name);
- fprintf(f, "# type: complex matrix\n");
- fprintf(f, "# rows: %d\n", rows);
- fprintf(f, "# columns: %d\n", cols);
-
- for(r=0; r<rows; r++) {
- for(c=0; c<cols; c++)
- fprintf(f, " (%f,%f)", data[r*col_len+c].real, data[r*col_len+c].imag);
- fprintf(f, "\n");
- }
-
- fprintf(f, "\n\n");
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: octave.h
- AUTHOR......: David Rowe
- DATE CREATED: April 28 2012
-
- Functions to save C arrays in Octave matrix format. the output text
- file can be directly read into octave using "load filename".
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __OCTAVE__
-#define __OCTAVE__
-
-#include "comp.h"
-
-void octave_save_int(FILE *f, char name[], int data[], int rows, int cols);
-void octave_save_float(FILE *f, char name[], float data[], int rows, int cols, int col_len);
-void octave_save_complex(FILE *f, char name[], COMP data[], int rows, int cols, int col_len);
-
-#endif
+++ /dev/null
-/* Generate using fir1(47,1/6) in Octave */
-
-const float fdmdv_os_filter[]= {
- -3.55606818e-04,
- -8.98615286e-04,
- -1.40119781e-03,
- -1.71713852e-03,
- -1.56471179e-03,
- -6.28128960e-04,
- 1.24522223e-03,
- 3.83138676e-03,
- 6.41309478e-03,
- 7.85893186e-03,
- 6.93514929e-03,
- 2.79361991e-03,
- -4.51051400e-03,
- -1.36671853e-02,
- -2.21034939e-02,
- -2.64084653e-02,
- -2.31425052e-02,
- -9.84218694e-03,
- 1.40648474e-02,
- 4.67316298e-02,
- 8.39615986e-02,
- 1.19925275e-01,
- 1.48381174e-01,
- 1.64097819e-01,
- 1.64097819e-01,
- 1.48381174e-01,
- 1.19925275e-01,
- 8.39615986e-02,
- 4.67316298e-02,
- 1.40648474e-02,
- -9.84218694e-03,
- -2.31425052e-02,
- -2.64084653e-02,
- -2.21034939e-02,
- -1.36671853e-02,
- -4.51051400e-03,
- 2.79361991e-03,
- 6.93514929e-03,
- 7.85893186e-03,
- 6.41309478e-03,
- 3.83138676e-03,
- 1.24522223e-03,
- -6.28128960e-04,
- -1.56471179e-03,
- -1.71713852e-03,
- -1.40119781e-03,
- -8.98615286e-04,
- -3.55606818e-04
-};
-
+++ /dev/null
-/*
- Copyright (C) 2010 Perens LLC <bruce@perens.com>
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include "defines.h"
-#include "quantise.h"
-#include <stdio.h>
-
-/* Compile-time constants */
-/* Size of unsigned char in bits. Assumes 8 bits-per-char. */
-static const unsigned int WordSize = 8;
-
-/* Mask to pick the bit component out of bitIndex. */
-static const unsigned int IndexMask = 0x7;
-
-/* Used to pick the word component out of bitIndex. */
-static const unsigned int ShiftRight = 3;
-
-/** Pack a bit field into a bit string, encoding the field in Gray code.
- *
- * The output is an array of unsigned char data. The fields are efficiently
- * packed into the bit string. The Gray coding is a naive attempt to reduce
- * the effect of single-bit errors, we expect to do a better job as the
- * codec develops.
- *
- * This code would be simpler if it just set one bit at a time in the string,
- * but would hit the same cache line more often. I'm not sure the complexity
- * gains us anything here.
- *
- * Although field is currently of int type rather than unsigned for
- * compatibility with the rest of the code, indices are always expected to
- * be >= 0.
- */
-void
-pack(
- unsigned char * bitArray, /* The output bit string. */
- unsigned int * bitIndex, /* Index into the string in BITS, not bytes.*/
- int field, /* The bit field to be packed. */
- unsigned int fieldWidth/* Width of the field in BITS, not bytes. */
- )
-{
- /* Convert the field to Gray code */
- field = (field >> 1) ^ field;
-
- do {
- unsigned int bI = *bitIndex;
- unsigned int bitsLeft = WordSize - (bI & IndexMask);
- unsigned int sliceWidth =
- bitsLeft < fieldWidth ? bitsLeft : fieldWidth;
- unsigned int wordIndex = bI >> ShiftRight;
-
- bitArray[wordIndex] |=
- ((unsigned char)((field >> (fieldWidth - sliceWidth))
- << (bitsLeft - sliceWidth)));
-
- *bitIndex = bI + sliceWidth;
- fieldWidth -= sliceWidth;
- } while ( fieldWidth != 0 );
-}
-
-/** Unpack a field from a bit string, converting from Gray code to binary.
- *
- */
-int
-unpack(
- const unsigned char * bitArray, /* The input bit string. */
- unsigned int * bitIndex, /* Index into the string in BITS, not bytes.*/
- unsigned int fieldWidth/* Width of the field in BITS, not bytes. */
- )
-{
- unsigned int field = 0;
- unsigned int t;
-
- do {
- unsigned int bI = *bitIndex;
- unsigned int bitsLeft = WordSize - (bI & IndexMask);
- unsigned int sliceWidth =
- bitsLeft < fieldWidth ? bitsLeft : fieldWidth;
-
- field |= (((bitArray[bI >> ShiftRight] >> (bitsLeft - sliceWidth)) & ((1 << sliceWidth) - 1)) << (fieldWidth - sliceWidth));
-
- *bitIndex = bI + sliceWidth;
- fieldWidth -= sliceWidth;
- } while ( fieldWidth != 0 );
-
- /* Convert from Gray code to binary. Works for maximum 8-bit fields. */
- t = field ^ (field >> 8);
- t ^= (t >> 4);
- t ^= (t >> 2);
- t ^= (t >> 1);
- return t;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: phase.c
- AUTHOR......: David Rowe
- DATE CREATED: 1/2/09
-
- Functions for modelling and synthesising phase.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not,see <http://www.gnu.org/licenses/>.
-*/
-
-#include "defines.h"
-#include "phase.h"
-#include "kiss_fft.h"
-#include "comp.h"
-#include "glottal.c"
-
-#include <assert.h>
-#include <ctype.h>
-#include <math.h>
-#include <string.h>
-#include <stdlib.h>
-
-#define GLOTTAL_FFT_SIZE 512
-
-/*---------------------------------------------------------------------------*\
-
- aks_to_H()
-
- Samples the complex LPC synthesis filter spectrum at the harmonic
- frequencies.
-
-\*---------------------------------------------------------------------------*/
-
-void aks_to_H(
- kiss_fft_cfg fft_fwd_cfg,
- MODEL *model, /* model parameters */
- float aks[], /* LPC's */
- float G, /* energy term */
- COMP H[], /* complex LPC spectral samples */
- int order
-)
-{
- COMP pw[FFT_ENC]; /* power spectrum (input) */
- COMP Pw[FFT_ENC]; /* power spectrum (output) */
- int i,m; /* loop variables */
- int am,bm; /* limits of current band */
- float r; /* no. rads/bin */
- float Em; /* energy in band */
- float Am; /* spectral amplitude sample */
- int b; /* centre bin of harmonic */
- float phi_; /* phase of LPC spectra */
-
- r = TWO_PI/(FFT_ENC);
-
- /* Determine DFT of A(exp(jw)) ------------------------------------------*/
-
- for(i=0; i<FFT_ENC; i++) {
- pw[i].real = 0.0;
- pw[i].imag = 0.0;
- }
-
- for(i=0; i<=order; i++)
- pw[i].real = aks[i];
-
- kiss_fft(fft_fwd_cfg, (kiss_fft_cpx *)pw, (kiss_fft_cpx *)Pw);
-
- /* Sample magnitude and phase at harmonics */
-
- for(m=1; m<=model->L; m++) {
- am = floor((m - 0.5)*model->Wo/r + 0.5);
- bm = floor((m + 0.5)*model->Wo/r + 0.5);
- b = floor(m*model->Wo/r + 0.5);
-
- Em = 0.0;
- for(i=am; i<bm; i++)
- Em += G/(Pw[i].real*Pw[i].real + Pw[i].imag*Pw[i].imag);
- Am = sqrt(fabs(Em/(bm-am)));
-
- phi_ = -atan2(Pw[b].imag,Pw[b].real);
- H[m].real = Am*cos(phi_);
- H[m].imag = Am*sin(phi_);
- }
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- phase_synth_zero_order()
-
- Synthesises phases based on SNR and a rule based approach. No phase
- parameters are required apart from the SNR (which can be reduced to a
- 1 bit V/UV decision per frame).
-
- The phase of each harmonic is modelled as the phase of a LPC
- synthesis filter excited by an impulse. Unlike the first order
- model the position of the impulse is not transmitted, so we create
- an excitation pulse train using a rule based approach.
-
- Consider a pulse train with a pulse starting time n=0, with pulses
- repeated at a rate of Wo, the fundamental frequency. A pulse train
- in the time domain is equivalent to harmonics in the frequency
- domain. We can make an excitation pulse train using a sum of
- sinsusoids:
-
- for(m=1; m<=L; m++)
- ex[n] = cos(m*Wo*n)
-
- Note: the Octave script ../octave/phase.m is an example of this if
- you would like to try making a pulse train.
-
- The phase of each excitation harmonic is:
-
- arg(E[m]) = mWo
-
- where E[m] are the complex excitation (freq domain) samples,
- arg(x), just returns the phase of a complex sample x.
-
- As we don't transmit the pulse position for this model, we need to
- synthesise it. Now the excitation pulses occur at a rate of Wo.
- This means the phase of the first harmonic advances by N samples
- over a synthesis frame of N samples. For example if Wo is pi/20
- (200 Hz), then over a 10ms frame (N=80 samples), the phase of the
- first harmonic would advance (pi/20)*80 = 4*pi or two complete
- cycles.
-
- We generate the excitation phase of the fundamental (first
- harmonic):
-
- arg[E[1]] = Wo*N;
-
- We then relate the phase of the m-th excitation harmonic to the
- phase of the fundamental as:
-
- arg(E[m]) = m*arg(E[1])
-
- This E[m] then gets passed through the LPC synthesis filter to
- determine the final harmonic phase.
-
- Comparing to speech synthesised using original phases:
-
- - Through headphones speech synthesised with this model is not as
- good. Through a loudspeaker it is very close to original phases.
-
- - If there are voicing errors, the speech can sound clicky or
- staticy. If V speech is mistakenly declared UV, this model tends to
- synthesise impulses or clicks, as there is usually very little shift or
- dispersion through the LPC filter.
-
- - When combined with LPC amplitude modelling there is an additional
- drop in quality. I am not sure why, theory is interformant energy
- is raised making any phase errors more obvious.
-
- NOTES:
-
- 1/ This synthesis model is effectively the same as a simple LPC-10
- vocoders, and yet sounds much better. Why? Conventional wisdom
- (AMBE, MELP) says mixed voicing is required for high quality
- speech.
-
- 2/ I am pretty sure the Lincoln Lab sinusoidal coding guys (like xMBE
- also from MIT) first described this zero phase model, I need to look
- up the paper.
-
- 3/ Note that this approach could cause some discontinuities in
- the phase at the edge of synthesis frames, as no attempt is made
- to make sure that the phase tracks are continuous (the excitation
- phases are continuous, but not the final phases after filtering
- by the LPC spectra). Technically this is a bad thing. However
- this may actually be a good thing, disturbing the phase tracks a
- bit. More research needed, e.g. test a synthesis model that adds
- a small delta-W to make phase tracks line up for voiced
- harmonics.
-
-\*---------------------------------------------------------------------------*/
-
-void phase_synth_zero_order(
- kiss_fft_cfg fft_fwd_cfg,
- MODEL *model,
- float aks[],
- float *ex_phase, /* excitation phase of fundamental */
- int order
-)
-{
- int m;
- float new_phi;
- COMP Ex[MAX_AMP+1]; /* excitation samples */
- COMP A_[MAX_AMP+1]; /* synthesised harmonic samples */
- COMP H[MAX_AMP+1]; /* LPC freq domain samples */
- float G;
- float jitter = 0.0;
- float r;
- int b;
-
- G = 1.0;
- aks_to_H(fft_fwd_cfg, model, aks, G, H, order);
-
- /*
- Update excitation fundamental phase track, this sets the position
- of each pitch pulse during voiced speech. After much experiment
- I found that using just this frame's Wo improved quality for UV
- sounds compared to interpolating two frames Wo like this:
-
- ex_phase[0] += (*prev_Wo+model->Wo)*N/2;
- */
-
- ex_phase[0] += (model->Wo)*N;
- ex_phase[0] -= TWO_PI*floor(ex_phase[0]/TWO_PI + 0.5);
- r = TWO_PI/GLOTTAL_FFT_SIZE;
-
- for(m=1; m<=model->L; m++) {
-
- /* generate excitation */
-
- if (model->voiced) {
- //float rnd;
-
- b = floor(m*model->Wo/r + 0.5);
- if (b > ((GLOTTAL_FFT_SIZE/2)-1)) {
- b = (GLOTTAL_FFT_SIZE/2)-1;
- }
-
- /* I think adding a little jitter helps improve low pitch
- males like hts1a. This moves the onset of each harmonic
- over +/- 0.25 of a sample.
- */
- //jitter = 0.25*(1.0 - 2.0*rand()/RAND_MAX);
- jitter = 0;
-
- //rnd = (PI/8)*(1.0 - 2.0*rand()/RAND_MAX);
- Ex[m].real = cos(ex_phase[0]*m/* - jitter*model->Wo*m + glottal[b]*/);
- Ex[m].imag = sin(ex_phase[0]*m/* - jitter*model->Wo*m + glottal[b]*/);
- }
- else {
-
- /* When a few samples were tested I found that LPC filter
- phase is not needed in the unvoiced case, but no harm in
- keeping it.
- */
- float phi = TWO_PI*(float)rand()/RAND_MAX;
- Ex[m].real = cos(phi);
- Ex[m].imag = sin(phi);
- }
-
- /* filter using LPC filter */
-
- A_[m].real = H[m].real*Ex[m].real - H[m].imag*Ex[m].imag;
- A_[m].imag = H[m].imag*Ex[m].real + H[m].real*Ex[m].imag;
-
- /* modify sinusoidal phase */
-
- new_phi = atan2(A_[m].imag, A_[m].real+1E-12);
- model->phi[m] = new_phi;
- }
-
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: phase.h
- AUTHOR......: David Rowe
- DATE CREATED: 1/2/09
-
- Functions for modelling phase.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __PHASE__
-#define __PHASE__
-
-#include "kiss_fft.h"
-
-void phase_synth_zero_order(kiss_fft_cfg fft_dec_cfg,
- MODEL *model,
- float aks[],
- float *ex_phase,
- int order);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: phaseexp.c
- AUTHOR......: David Rowe
- DATE CREATED: June 2012
-
- Experimental functions for quantising, modelling and synthesising phase.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not,see <http://www.gnu.org/licenses/>.
-*/
-
-#include "defines.h"
-#include "phase.h"
-#include "kiss_fft.h"
-#include "comp.h"
-
-#include <assert.h>
-#include <ctype.h>
-#include <math.h>
-#include <string.h>
-#include <stdlib.h>
-
-/* Bruce Perens' funcs to load codebook files */
-
-struct codebook {
- unsigned int k;
- unsigned int log2m;
- unsigned int m;
- COMP *cb;
- unsigned int offset;
-};
-
-static const char format[] =
-"The table format must be:\n"
-"\tTwo integers describing the dimensions of the codebook.\n"
-"\tThen, enough numbers to fill the specified dimensions.\n";
-
-float get_float(FILE * in, const char * name, char * * cursor, char * buffer, int size)
-{
- for ( ; ; ) {
- char * s = *cursor;
- char c;
-
- while ( (c = *s) != '\0' && !isdigit(c) && c != '-' && c != '.' )
- s++;
-
- /* Comments start with "#" and continue to the end of the line. */
- if ( c != '\0' && c != '#' ) {
- char * end = 0;
- float f = 0;
-
- f = strtod(s, &end);
-
- if ( end != s )
- *cursor = end;
- return f;
- }
-
- if ( fgets(buffer, size, in) == NULL ) {
- fprintf(stderr, "%s: Format error. %s\n", name, format);
- exit(1);
- }
- *cursor = buffer;
- }
-}
-
-static struct codebook *load(const char * name)
-{
- FILE *file;
- char line[2048];
- char *cursor = line;
- struct codebook *b = malloc(sizeof(struct codebook));
- int i;
- int size;
- float angle;
-
- file = fopen(name, "rt");
- assert(file != NULL);
-
- *cursor = '\0';
-
- b->k = (int)get_float(file, name, &cursor, line, sizeof(line));
- b->m = (int)get_float(file, name ,&cursor, line, sizeof(line));
- size = b->k * b->m;
-
- b->cb = (COMP *)malloc(size * sizeof(COMP));
-
- for ( i = 0; i < size; i++ ) {
- angle = get_float(file, name, &cursor, line, sizeof(line));
- b->cb[i].real = cos(angle);
- b->cb[i].imag = sin(angle);
- }
-
- fclose(file);
-
- return b;
-}
-
-
-/* states for phase experiments */
-
-struct PEXP {
- float phi1;
- float phi_prev[MAX_AMP];
- float Wo_prev;
- int frames;
- float snr;
- float var;
- int var_n;
- struct codebook *vq1,*vq2,*vq3,*vq4,*vq5;
- float vq_var;
- int vq_var_n;
- MODEL prev_model;
- int state;
-};
-
-
-/*---------------------------------------------------------------------------* \
-
- phase_experiment_create()
-
- Inits states for phase quantisation experiments.
-
-\*---------------------------------------------------------------------------*/
-
-struct PEXP * phase_experiment_create() {
- struct PEXP *pexp;
- int i;
-
- pexp = (struct PEXP *)malloc(sizeof(struct PEXP));
- assert (pexp != NULL);
-
- pexp->phi1 = 0;
- for(i=0; i<MAX_AMP; i++)
- pexp->phi_prev[i] = 0.0;
- pexp->Wo_prev = 0.0;
- pexp->frames = 0;
- pexp->snr = 0.0;
- pexp->var = 0.0;
- pexp->var_n = 0;
-
- /* smoothed 10th order for 1st 1 khz */
- //pexp->vq1 = load("../unittest/ph1_10_1024.txt");
- //pexp->vq1->offset = 0;
-
- /* load experimental phase VQ */
-
- //pexp->vq1 = load("../unittest/testn1_20_1024.txt");
- pexp->vq1 = load("../unittest/test.txt");
- //pexp->vq2 = load("../unittest/testn21_40_1024.txt");
- pexp->vq2 = load("../unittest/test11_20_1024.txt");
- pexp->vq3 = load("../unittest/test21_30_1024.txt");
- pexp->vq4 = load("../unittest/test31_40_1024.txt");
- pexp->vq5 = load("../unittest/test41_60_1024.txt");
- pexp->vq1->offset = 0;
- pexp->vq2->offset = 10;
- pexp->vq3->offset = 20;
- pexp->vq4->offset = 30;
- pexp->vq5->offset = 40;
-
- pexp->vq_var = 0.0;
- pexp->vq_var_n = 0;
-
- pexp->state = 0;
-
- return pexp;
-}
-
-
-/*---------------------------------------------------------------------------* \
-
- phase_experiment_destroy()
-
-\*---------------------------------------------------------------------------*/
-
-void phase_experiment_destroy(struct PEXP *pexp) {
- assert(pexp != NULL);
- if (pexp->snr != 0.0)
- printf("snr: %4.2f dB\n", pexp->snr/pexp->frames);
- if (pexp->var != 0.0)
- printf("var...: %4.3f std dev...: %4.3f (%d non zero phases)\n",
- pexp->var/pexp->var_n, sqrt(pexp->var/pexp->var_n), pexp->var_n);
- if (pexp->vq_var != 0.0)
- printf("vq var: %4.3f vq std dev: %4.3f (%d non zero phases)\n",
- pexp->vq_var/pexp->vq_var_n, sqrt(pexp->vq_var/pexp->vq_var_n), pexp->vq_var_n);
- free(pexp);
-}
-
-
-/*---------------------------------------------------------------------------* \
-
- Various test and experimental functions ................
-
-\*---------------------------------------------------------------------------*/
-
-/* Bubblesort to find highest amplitude harmonics */
-
-struct AMPINDEX {
- float amp;
- int index;
-};
-
-static void bubbleSort(struct AMPINDEX numbers[], int array_size)
-{
- int i, j;
- struct AMPINDEX temp;
-
- for (i = (array_size - 1); i > 0; i--)
- {
- for (j = 1; j <= i; j++)
- {
- //printf("i %d j %d %f %f \n", i, j, numbers[j-1].amp, numbers[j].amp);
- if (numbers[j-1].amp < numbers[j].amp)
- {
- temp = numbers[j-1];
- numbers[j-1] = numbers[j];
- numbers[j] = temp;
- }
- }
- }
-}
-
-
-static void print_pred_error(struct PEXP *pexp, MODEL *model, int start, int end, float mag_thresh) {
- int i;
- float mag;
-
- mag = 0.0;
- for(i=start; i<=end; i++)
- mag += model->A[i]*model->A[i];
- mag = 10*log10(mag/(end-start));
-
- if (mag > mag_thresh) {
- for(i=start; i<=end; i++) {
- float pred = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0;
- float err = pred - model->phi[i];
- err = atan2(sin(err),cos(err));
- printf("%f\n",err);
- }
- //printf("\n");
- }
-
-}
-
-
-static void predict_phases(struct PEXP *pexp, MODEL *model, int start, int end) {
- int i;
-
- for(i=start; i<=end; i++) {
- model->phi[i] = pexp->phi_prev[i] + N*i*model->Wo;
- }
-
-}
-static float refine_Wo(struct PEXP *pexp,
- MODEL *model,
- int start,
- int end);
-
-/* Fancy state based phase prediction. Actually works OK on most utterances,
- but could use some tuning. Breaks down a bit on mmt1. */
-
-static void predict_phases_state(struct PEXP *pexp, MODEL *model, int start, int end) {
- int i, next_state;
- float best_Wo, dWo;
-
- //best_Wo = refine_Wo(pexp, model, start, end);
- //best_Wo = (model->Wo + pexp->Wo_prev)/2.0;
- best_Wo = model->Wo;
-
- dWo = fabs(model->Wo - pexp->Wo_prev)/model->Wo;
- next_state = pexp->state;
- switch(pexp->state) {
- case 0:
- if (dWo < 0.1) {
- /* UV -> V transition, so start with phases in lock. They will
- drift a bit over voiced track which is kinda what we want, so
- we don't get clicky speech.
- */
- next_state = 1;
- for(i=start; i<=end; i++)
- pexp->phi_prev[i] = i*pexp->phi1;
- }
-
- break;
- case 1:
- if (dWo > 0.1)
- next_state = 0;
- break;
- }
- pexp->state = next_state;
-
- if (pexp->state == 0)
- for(i=start; i<=end; i++) {
- model->phi[i] = PI*(1.0 - 2.0*rand()/RAND_MAX);
- }
- else
- for(i=start; i<=end; i++) {
- model->phi[i] = pexp->phi_prev[i] + N*i*best_Wo;
- }
- printf("state %d\n", pexp->state);
-}
-
-static void struct_phases(struct PEXP *pexp, MODEL *model, int start, int end) {
- int i;
-
- for(i=start; i<=end; i++)
- model->phi[i] = pexp->phi1*i;
-
-}
-
-
-static void predict_phases2(struct PEXP *pexp, MODEL *model, int start, int end) {
- int i;
- float pred, str, diff;
-
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*model->Wo;
- str = pexp->phi1*i;
- diff = str - pred;
- diff = atan2(sin(diff), cos(diff));
- if (diff > 0)
- pred += PI/16;
- else
- pred -= PI/16;
- model->phi[i] = pred;
- }
-
-}
-
-static void skip_phases(struct PEXP *pexp, MODEL *model, int start, int end) {
- int i;
-
- for(i=start; i<=end; i+=2)
- model->phi[i] = model->phi[i-1] - model->phi[i-2];
-
-}
-
-static void rand_phases(MODEL *model, int start, int end) {
- int i;
-
- for(i=start; i<=end; i++)
- model->phi[i] = PI*(1.0 - 2.0*(float)rand()/RAND_MAX);
-
-}
-
-static void quant_phase(float *phase, float min, float max, int bits) {
- int levels = 1 << bits;
- int index;
- float norm, step;
-
- norm = (*phase - min)/(max - min);
- index = floor(levels*norm);
-
- //printf("phase %f norm %f index %d ", *phase, norm, index);
- if (index < 0 ) index = 0;
- if (index > (levels-1)) index = levels-1;
- //printf("index %d ", index);
- step = (max - min)/levels;
- *phase = min + step*index + 0.5*step;
- //printf("step %f phase %f\n", step, *phase);
-}
-
-static void quant_phases(MODEL *model, int start, int end, int bits) {
- int i;
-
- for(i=start; i<=end; i++) {
- quant_phase(&model->phi[i], -PI, PI, bits);
- }
-}
-
-static void fixed_bits_per_frame(struct PEXP *pexp, MODEL *model, int m, int budget) {
- int res, finished;
-
- res = 3;
- finished = 0;
-
- while(!finished) {
- if (m > model->L/2)
- res = 2;
- if (((budget - res) < 0) || (m > model->L))
- finished = 1;
- else {
- quant_phase(&model->phi[m], -PI, PI, res);
- budget -= res;
- m++;
- }
- }
- printf("m: %d L: %d budget: %d\n", m, model->L, budget);
- predict_phases(pexp, model, m, model->L);
- //rand_phases(model, m, model->L);
-}
-
-/* used to plot histogram of quantisation error, for 3 bits, 8 levels,
- should be uniform between +/- PI/8 */
-
-static void check_phase_quant(MODEL *model, float tol)
-{
- int m;
- float phi_before[MAX_AMP];
-
- for(m=1; m<=model->L; m++)
- phi_before[m] = model->phi[m];
-
- quant_phases(model, 1, model->L, 3);
-
- for(m=1; m<=model->L; m++) {
- float err = phi_before[m] - model->phi[m];
- printf("%f\n", err);
- if (fabs(err) > tol)
- exit(0);
- }
-}
-
-
-static float est_phi1(MODEL *model, int start, int end)
-{
- int m;
- float delta, s, c, phi1_est;
-
- if (end > model->L)
- end = model->L;
-
- s = c = 0.0;
- for(m=start; m<end; m++) {
- delta = model->phi[m+1] - model->phi[m];
- s += sin(delta);
- c += cos(delta);
- }
-
- phi1_est = atan2(s,c);
-
- return phi1_est;
-}
-
-static void print_phi1_pred_error(MODEL *model, int start, int end)
-{
- int m;
- float phi1_est;
-
- phi1_est = est_phi1(model, start, end);
-
- for(m=start; m<end; m++) {
- float err = model->phi[m+1] - model->phi[m] - phi1_est;
- err = atan2(sin(err),cos(err));
- printf("%f\n", err);
- }
-}
-
-
-static void first_order_band(MODEL *model, int start, int end, float phi1_est)
-{
- int m;
- float pred_err, av_pred_err;
- float c,s;
-
- s = c = 0.0;
- for(m=start; m<end; m++) {
- pred_err = model->phi[m] - phi1_est*m;
- s += sin(pred_err);
- c += cos(pred_err);
- }
-
- av_pred_err = atan2(s,c);
- for(m=start; m<end; m++) {
- model->phi[m] = av_pred_err + phi1_est*m;
- model->phi[m] = atan2(sin(model->phi[m]), cos(model->phi[m]));
- }
-
-}
-
-
-static void sub_linear(MODEL *model, int start, int end, float phi1_est)
-{
- int m;
-
- for(m=start; m<end; m++) {
- model->phi[m] = m*phi1_est;
- }
-}
-
-
-static void top_amp(struct PEXP *pexp, MODEL *model, int start, int end, int n_harm, int pred)
-{
- int removed = 0, not_removed = 0;
- int top, i, j;
- struct AMPINDEX sorted[MAX_AMP];
-
- /* sort into ascending order of amplitude */
-
- printf("\n");
- for(i=start,j=0; i<end; i++,j++) {
- sorted[j].amp = model->A[i];
- sorted[j].index = i;
- printf("%f ", model->A[i]);
- }
- bubbleSort(sorted, end-start);
-
- printf("\n");
- for(j=0; j<n_harm; j++)
- printf("%d %f\n", j, sorted[j].amp);
-
- /* keep phase of top n_harm, predict others */
-
- for(i=start; i<end; i++) {
- top = 0;
- for(j=0; j<n_harm; j++) {
- if (model->A[i] == sorted[j].amp) {
- top = 1;
- assert(i == sorted[j].index);
- }
- }
-
- #define ALTTOP
- #ifdef ALTTOP
- model->phi[i] = 0.0; /* make sure */
- if (top) {
- model->phi[i] = i*pexp->phi1;
- removed++;
- }
- else {
- model->phi[i] = PI*(1.0 - 2.0*(float)rand()/RAND_MAX); // note: try rand for higher harms
- removed++;
- }
- #else
- if (!top) {
- model->phi[i] = 0.0; /* make sure */
- if (pred) {
- //model->phi[i] = pexp->phi_prev[i] + i*N*(model->Wo + pexp->Wo_prev)/2.0;
- model->phi[i] = i*model->phi[1];
- }
- else
- model->phi[i] = PI*(1.0 - 2.0*(float)rand()/RAND_MAX); // note: try rand for higher harms
- removed++;
- }
- else {
- /* need to make this work thru budget of bits */
- quant_phase(&model->phi[i], -PI, PI, 3);
- not_removed++;
- }
- #endif
- }
- printf("dim: %d rem %d not_rem %d\n", end-start, removed, not_removed);
-
-}
-
-
-static void limit_prediction_error(struct PEXP *pexp, MODEL *model, int start, int end, float limit)
-{
- int i;
- float pred, pred_error, error;
-
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0;
- pred_error = pred - model->phi[i];
- pred_error -= TWO_PI*floor((pred_error+PI)/TWO_PI);
- quant_phase(&pred_error, -limit, limit, 2);
-
- error = pred - pred_error - model->phi[i];
- error -= TWO_PI*floor((error+PI)/TWO_PI);
- printf("%f\n", pred_error);
- model->phi[i] = pred - pred_error;
- }
-}
-
-
-static void quant_prediction_error(struct PEXP *pexp, MODEL *model, int start, int end, float limit)
-{
- int i;
- float pred, pred_error;
-
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0;
- pred_error = pred - model->phi[i];
- pred_error -= TWO_PI*floor((pred_error+PI)/TWO_PI);
-
- printf("%f\n", pred_error);
- model->phi[i] = pred - pred_error;
- }
-}
-
-
-static void print_sparse_pred_error(struct PEXP *pexp, MODEL *model, int start, int end, float mag_thresh)
-{
- int i, index;
- float mag, pred, error;
- float sparse_pe[MAX_AMP];
-
- mag = 0.0;
- for(i=start; i<=end; i++)
- mag += model->A[i]*model->A[i];
- mag = 10*log10(mag/(end-start));
-
- if (mag > mag_thresh) {
- for(i=0; i<MAX_AMP; i++) {
- sparse_pe[i] = 0.0;
- }
-
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0;
- error = pred - model->phi[i];
- error = atan2(sin(error),cos(error));
-
- index = MAX_AMP*i*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe[index] = error;
- }
-
- /* dump spare phase vector in polar format */
-
- for(i=0; i<MAX_AMP; i++)
- printf("%f ", sparse_pe[i]);
- printf("\n");
- }
-}
-
-
-static void update_snr_calc(struct PEXP *pexp, MODEL *model, float before[])
-{
- int m;
- float signal, noise, diff;
-
- signal = 0.0; noise = 0.0;
- for(m=1; m<=model->L; m++) {
- signal += model->A[m]*model->A[m];
- diff = cos(model->phi[m]) - cos(before[m]);
- noise += pow(model->A[m]*diff, 2.0);
- diff = sin(model->phi[m]) - sin(before[m]);
- noise += pow(model->A[m]*diff, 2.0);
- //printf("%f %f\n", before[m], model->phi[m]);
- }
- //printf("%f %f snr = %f\n", signal, noise, 10.0*log10(signal/noise));
- pexp->snr += 10.0*log10(signal/noise);
-}
-
-
-static void update_variance_calc(struct PEXP *pexp, MODEL *model, float before[])
-{
- int m;
- float diff;
-
- for(m=1; m<model->L; m++) {
- diff = model->phi[m] - before[m];
- diff = atan2(sin(diff), cos(diff));
- pexp->var += diff*diff;
- }
- pexp->var_n += model->L;
-}
-
-void print_vec(COMP cb[], int d, int e)
-{
- int i,j;
-
- for(j=0; j<e; j++) {
- for(i=0; i<d; i++)
- printf("%f %f ", cb[j*d+i].real, cb[j*d+i].imag);
- printf("\n");
- }
-}
-
-static COMP cconj(COMP a)
-{
- COMP res;
-
- res.real = a.real;
- res.imag = -a.imag;
-
- return res;
-}
-
-static COMP cadd(COMP a, COMP b)
-{
- COMP res;
-
- res.real = a.real + b.real;
- res.imag = a.imag + b.imag;
-
- return res;
-}
-
-static COMP cmult(COMP a, COMP b)
-{
- COMP res;
-
- res.real = a.real*b.real - a.imag*b.imag;
- res.imag = a.real*b.imag + a.imag*b.real;
-
- return res;
-}
-
-static int vq_phase(COMP cb[], COMP vec[], float weights[], int d, int e, float *se)
-{
- float error; /* current error */
- int besti; /* best index so far */
- float best_error; /* best error so far */
- int i,j;
- int ignore;
- COMP diffr;
- float diffp, metric, best_metric;
-
- besti = 0;
- best_metric = best_error = 1E32;
- for(j=0; j<e; j++) {
- error = 0.0;
- metric = 0.0;
- for(i=0; i<d; i++) {
- ignore = (vec[i].real == 0.0) && (vec[i].imag == 0.0);
- if (!ignore) {
- diffr = cmult(cb[j*d+i], cconj(vec[i]));
- diffp = atan2(diffr.imag, diffr.real);
- error += diffp*diffp;
- metric += weights[i]*weights[i]*diffp*diffp;
- //metric += weights[i]*diffp*diffp;
- //metric = log10(weights[i]*fabs(diffp));
- //printf("diffp %f metric %f\n", diffp, metric);
- //if (metric < log10(PI/(8.0*sqrt(3.0))))
- // metric = log10(PI/(8.0*sqrt(3.0)));
- }
- }
- if (metric < best_metric) {
- best_metric = metric;
- best_error = error;
- besti = j;
- }
- }
-
- *se += best_error;
-
- return(besti);
-}
-
-
-static float refine_Wo(struct PEXP *pexp,
- MODEL *model,
- int start,
- int end)
-
-{
- int i;
- float Wo_est, best_var, Wo, var, pred, error, best_Wo;
-
- /* test variance over a range of Wo values */
-
- Wo_est = (model->Wo + pexp->Wo_prev)/2.0;
- best_var = 1E32;
- for(Wo=0.97*Wo_est; Wo<=1.03*Wo_est; Wo+=0.001*Wo_est) {
-
- /* predict phase and sum differences between harmonics */
-
- var = 0.0;
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*Wo;
- error = pred - model->phi[i];
- error = atan2(sin(error),cos(error));
- var += error*error;
- }
-
- if (var < best_var) {
- best_var = var;
- best_Wo = Wo;
- }
- }
-
- return best_Wo;
-}
-
-
-static void split_vq(COMP sparse_pe_out[], struct PEXP *pexp, struct codebook *vq, float weights[], COMP sparse_pe_in[])
-{
- int i, j, non_zero, vq_ind;
-
- //printf("\n offset %d k %d m %d j: ", vq->offset, vq->k, vq->m);
- vq_ind = vq_phase(vq->cb, &sparse_pe_in[vq->offset], &weights[vq->offset], vq->k, vq->m, &pexp->vq_var);
-
- non_zero = 0;
- for(i=0, j=vq->offset; i<vq->k; i++,j++) {
- //printf("%f ", atan2(sparse_pe[i].imag, sparse_pe[i].real));
- if ((sparse_pe_in[j].real != 0.0) && (sparse_pe_in[j].imag != 0.0)) {
- //printf("%d ", j);
- sparse_pe_out[j] = vq->cb[vq->k * vq_ind + i];
- non_zero++;
- }
- }
- pexp->vq_var_n += non_zero;
-}
-
-
-static void sparse_vq_pred_error(struct PEXP *pexp,
- MODEL *model
-)
-{
- int i, index;
- float pred, error, error_q_angle, best_Wo;
- COMP sparse_pe_in[MAX_AMP], sparse_pe_out[MAX_AMP];
- float weights[MAX_AMP];
- COMP error_q_rect;
-
- best_Wo = refine_Wo(pexp, model, 1, model->L);
- //best_Wo = (model->Wo + pexp->Wo_prev)/2.0;
-
- /* transform to sparse pred error vector */
-
- for(i=0; i<MAX_AMP; i++) {
- sparse_pe_in[i].real = 0.0;
- sparse_pe_in[i].imag = 0.0;
- sparse_pe_out[i].real = 0.0;
- sparse_pe_out[i].imag = 0.0;
- }
-
- //printf("\n");
- for(i=1; i<=model->L; i++) {
- pred = pexp->phi_prev[i] + N*i*best_Wo;
- error = pred - model->phi[i];
-
- index = MAX_AMP*i*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_in[index].real = cos(error);
- sparse_pe_in[index].imag = sin(error);
- sparse_pe_out[index] = sparse_pe_in[index];
- weights[index] = model->A[i];
- //printf("%d ", index);
- }
-
- /* vector quantise */
-
- split_vq(sparse_pe_out, pexp, pexp->vq1, weights, sparse_pe_in);
- split_vq(sparse_pe_out, pexp, pexp->vq2, weights, sparse_pe_in);
- split_vq(sparse_pe_out, pexp, pexp->vq3, weights, sparse_pe_in);
- split_vq(sparse_pe_out, pexp, pexp->vq4, weights, sparse_pe_in);
- split_vq(sparse_pe_out, pexp, pexp->vq5, weights, sparse_pe_in);
-
- /* transform quantised phases back */
-
- for(i=1; i<=model->L; i++) {
- pred = pexp->phi_prev[i] + N*i*best_Wo;
-
- index = MAX_AMP*i*model->Wo/PI;
- assert(index < MAX_AMP);
- error_q_rect = sparse_pe_out[index];
- error_q_angle = atan2(error_q_rect.imag, error_q_rect.real);
- model->phi[i] = pred - error_q_angle;
- model->phi[i] = atan2(sin(model->phi[i]), cos(model->phi[i]));
- }
-}
-
-
-/*
- est delta (in Wo)
- see if this gives us a better (smaller variance) prediction error
-*/
-
-static void print_pred_error_sparse_wo_correction(struct PEXP *pexp,
- MODEL *model,
- int start, int end,
- float mag_thresh)
-{
- int i, index;
- float mag, pred, error[MAX_AMP], diff, c, s, delta, err;
- float sparse_pe[MAX_AMP];
-
- mag = 0.0;
- for(i=start; i<=end; i++)
- mag += model->A[i]*model->A[i];
- mag = 10*log10(mag/(end-start));
-
- if (mag > mag_thresh) {
- for(i=0; i<MAX_AMP; i++) {
- sparse_pe[i] = 0.0;
- }
-
- /* predict phase and sum differences between harmonics */
-
- for(i=start; i<=end; i++) {
- //model->phi[i] = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0 + 0.01*N*i;
- pred = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0;
- error[i] = pred - model->phi[i];
- }
-
- /* estimate delta Wo */
-
- c = s = 0.0;
- for(i=start+1; i<=end; i++) {
- diff = error[i] - error[i-1];
- c += log(model->A[i])*cos(diff);
- s += log(model->A[i])*sin(diff);
- }
- delta = atan2(s,c)/N;
- //printf("delta %f\n",delta);
- delta = 0;
- /* now predict phases using corrected Wo */
-
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*(model->Wo + pexp->Wo_prev)/2.0 - N*i*delta;
- err = pred - model->phi[i];
- err = atan2(sin(err),cos(err));
-
- index = MAX_AMP*i*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe[index] = err;
- }
-
- /* dump spare phase vector in polar format */
-
- for(i=0; i<MAX_AMP; i++)
- printf("%f ", sparse_pe[i]);
- printf("\n");
-
- }
-
-}
-
-
-static void print_pred_error_sparse_wo_correction1(struct PEXP *pexp,
- MODEL *model,
- int start, int end,
- float mag_thresh)
-{
- int i, index;
- float mag, pred, best_Wo, err;
- float sparse_pe[MAX_AMP];
-
- mag = 0.0;
- for(i=start; i<=end; i++)
- mag += model->A[i]*model->A[i];
- mag = 10*log10(mag/(end-start));
-
- if (mag > mag_thresh) {
-
- best_Wo = refine_Wo(pexp, model, start, end);
-
- /* now predict phases using corrected Wo */
-
- for(i=0; i<MAX_AMP; i++) {
- sparse_pe[i] = 0.0;
- }
-
- for(i=start; i<=end; i++) {
- pred = pexp->phi_prev[i] + N*i*best_Wo;
- err = pred - model->phi[i];
- err = atan2(sin(err),cos(err));
-
- index = MAX_AMP*i*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe[index] = err;
- }
-
- /* dump spare phase vector in polar format */
-
- for(i=0; i<MAX_AMP; i++)
- printf("%f ", sparse_pe[i]);
- printf("\n");
-
- }
-
-}
-
-
-static void predict_phases1(struct PEXP *pexp, MODEL *model, int start, int end) {
- int i;
- float best_Wo;
-
- best_Wo = refine_Wo(pexp, model, 1, model->L);
-
- for(i=start; i<=end; i++) {
- model->phi[i] = pexp->phi_prev[i] + N*i*best_Wo;
- }
-}
-
-
-/*
- This functions tests theory that some bands can be combined together
- due to less frequency resolution at higher frequencies. This will
- reduce the amount of information we need to encode.
-*/
-
-void smooth_phase(struct PEXP *pexp, MODEL *model, int mode)
-{
- int m, i, j, index, step, v, en, nav, st;
- COMP sparse_pe_in[MAX_AMP], av;
- COMP sparse_pe_out[MAX_AMP];
- COMP smoothed[MAX_AMP];
- float best_Wo, pred, err;
- float weights[MAX_AMP];
- float avw, smoothed_weights[MAX_AMP];
- COMP smoothed_in[MAX_AMP], smoothed_out[MAX_AMP];
-
- best_Wo = refine_Wo(pexp, model, 1, model->L);
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe_in[m].real = sparse_pe_in[m].imag = 0.0;
- sparse_pe_out[m].real = sparse_pe_out[m].imag = 0.0;
- }
-
- /* set up sparse array */
-
- for(m=1; m<=model->L; m++) {
- pred = pexp->phi_prev[m] + N*m*best_Wo;
- err = model->phi[m] - pred;
- err = atan2(sin(err),cos(err));
-
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe_in[index].real = model->A[m]*cos(err);
- sparse_pe_in[index].imag = model->A[m]*sin(err);
- sparse_pe_out[index] = sparse_pe_in[index];
- weights[index] = model->A[m];
- }
-
- /* now combine samples at high frequencies to reduce dimension */
-
- step = 2;
- st = 0;
- for(i=st,v=0; i<MAX_AMP; i+=step,v++) {
-
- /* average over one band */
-
- av.real = 0.0; av.imag = 0.0; avw = 0.0; nav = 0;
- en = i+step;
- if (en > (MAX_AMP-1))
- en = MAX_AMP-1;
- for(j=i; j<en; j++) {
- if ((sparse_pe_in[j].real != 0.0) &&(sparse_pe_in[j].imag != 0.0) ) {
- av = cadd(av, sparse_pe_in[j]);
- avw += weights[j];
- nav++;
- }
- }
- if (nav) {
- smoothed[v] = av;
- smoothed_weights[v] = avw/nav;
- }
- else
- smoothed[v].real = smoothed[v].imag = 0.0;
- }
-
- if (mode == 2) {
- for(i=0; i<MAX_AMP; i++) {
- smoothed_in[i] = smoothed[i];
- smoothed_out[i] = smoothed_in[i];
- }
- split_vq(smoothed_out, pexp, pexp->vq1, smoothed_weights, smoothed_in);
- for(i=0; i<MAX_AMP; i++)
- smoothed[i] = smoothed_out[i];
- }
-
- /* set all samples to smoothed average */
-
- for(i=st,v=0; i<MAX_AMP; i+=step,v++) {
- en = i+step;
- if (en > (MAX_AMP-1))
- en = MAX_AMP-1;
- for(j=i; j<en; j++)
- sparse_pe_out[j] = smoothed[v];
- if (mode == 1)
- printf("%f ", atan2(smoothed[v].imag, smoothed[v].real));
- }
- if (mode == 1)
- printf("\n");
-
- /* convert back to Am */
-
- for(m=1; m<=model->L; m++) {
- index = MAX_AMP*m*model->Wo/PI;
- assert(index < MAX_AMP);
- pred = pexp->phi_prev[m] + N*m*best_Wo;
- err = atan2(sparse_pe_out[index].imag, sparse_pe_out[index].real);
- model->phi[m] = pred + err;
- }
-
-}
-
-/*
- Another version of a functions that tests the theory that some bands
- can be combined together due to less frequency resolution at higher
- frequencies. This will reduce the amount of information we need to
- encode.
-*/
-
-void smooth_phase2(struct PEXP *pexp, MODEL *model) {
- float m;
- float step;
- int a,b,h,i;
- float best_Wo, pred, err, s,c, phi1_;
-
- best_Wo = refine_Wo(pexp, model, 1, model->L);
-
- step = (float)model->L/30;
- printf("\nL: %d step: %3.2f am,bm: ", model->L, step);
- for(m=(float)model->L/4; m<=model->L; m+=step) {
- a = floor(m);
- b = floor(m+step);
- if (b > model->L) b = model->L;
- h = b-a;
-
- printf("%d,%d,(%d) ", a, b, h);
- c = s = 0.0;
- if (h>1) {
- for(i=a; i<b; i++) {
- pred = pexp->phi_prev[i] + N*i*best_Wo;
- err = model->phi[i] - pred;
- c += cos(err); s += sin(err);
- }
- phi1_ = atan2(s,c);
- for(i=a; i<b; i++) {
- pred = pexp->phi_prev[i] + N*i*best_Wo;
- printf("%d: %4.3f -> ", i, model->phi[i]);
- model->phi[i] = pred + phi1_;
- model->phi[i] = atan2(sin(model->phi[i]),cos(model->phi[i]));
- printf("%4.3f ", model->phi[i]);
- }
- }
- }
-}
-
-
-#define MAX_BINS 40
-//static float bins[] = {2600.0, 2800.0, 3000.0, 3200.0, 3400.0, 3600.0, 3800.0, 4000.0};
-static float bins[] = {/*
-
- 1000.0, 1100.0, 1200.0, 1300.0, 1400.0,
- 1500.0, 1600.0, 1700.0, 1800.0, 1900.0,*/
-
- 2000.0, 2400.0, 2800.0,
- 3000.0, 3400.0, 3600.0, 4000.0};
-
-void smooth_phase3(struct PEXP *pexp, MODEL *model) {
- int m, i;
- int nbins;
- int b;
- float f, best_Wo, pred, err;
- COMP av[MAX_BINS];
-
- nbins = sizeof(bins)/sizeof(float);
- best_Wo = refine_Wo(pexp, model, 1, model->L);
-
- /* clear all bins */
-
- for(i=0; i<MAX_BINS; i++) {
- av[i].real = 0.0;
- av[i].imag = 0.0;
- }
-
- /* add phases into each bin */
-
- for(m=1; m<=model->L; m++) {
- f = m*model->Wo*FS/TWO_PI;
- if (f > bins[0]) {
-
- /* find bin */
-
- for(i=0; i<nbins; i++)
- if ((f > bins[i]) && (f <= bins[i+1]))
- b = i;
- assert(b < MAX_BINS);
-
- /* est predicted phase from average */
-
- pred = pexp->phi_prev[m] + N*m*best_Wo;
- err = model->phi[m] - pred;
- av[b].real += cos(err); av[b].imag += sin(err);
- }
-
- }
-
- /* use averages to est phases */
-
- for(m=1; m<=model->L; m++) {
- f = m*model->Wo*FS/TWO_PI;
- if (f > bins[0]) {
-
- /* find bin */
-
- for(i=0; i<nbins; i++)
- if ((f > bins[i]) && (f <= bins[i+1]))
- b = i;
- assert(b < MAX_BINS);
-
- /* add predicted phase error to this bin */
-
- printf("L %d m %d f %4.f b %d\n", model->L, m, f, b);
-
- pred = pexp->phi_prev[m] + N*m*best_Wo;
- err = atan2(av[b].imag, av[b].real);
- printf(" %d: %4.3f -> ", m, model->phi[m]);
- model->phi[m] = pred + err;
- model->phi[m] = atan2(sin(model->phi[m]),cos(model->phi[m]));
- printf("%4.3f\n", model->phi[m]);
- }
- }
- printf("\n");
-}
-
-
-/*
- Try to code the phase of the largest amplitude in each band. Randomise the
- phase of the other harmonics. The theory is that only the largest harmonic
- will be audible.
-*/
-
-void cb_phase1(struct PEXP *pexp, MODEL *model) {
- int m, i;
- int nbins;
- int b;
- float f, best_Wo;
- float max_val[MAX_BINS];
- int max_ind[MAX_BINS];
-
- nbins = sizeof(bins)/sizeof(float);
- best_Wo = refine_Wo(pexp, model, 1, model->L);
-
- for(i=0; i<nbins; i++)
- max_val[i] = 0.0;
-
- /* determine max amplitude for each bin */
-
- for(m=1; m<=model->L; m++) {
- f = m*model->Wo*FS/TWO_PI;
- if (f > bins[0]) {
-
- /* find bin */
-
- for(i=0; i<nbins; i++)
- if ((f > bins[i]) && (f <= bins[i+1]))
- b = i;
- assert(b < MAX_BINS);
-
- if (model->A[m] > max_val[b]) {
- max_val[b] = model->A[m];
- max_ind[b] = m;
- }
- }
-
- }
-
- /* randomise phase of other harmonics */
-
- for(m=1; m<=model->L; m++) {
- f = m*model->Wo*FS/TWO_PI;
- if (f > bins[0]) {
-
- /* find bin */
-
- for(i=0; i<nbins; i++)
- if ((f > bins[i]) && (f <= bins[i+1]))
- b = i;
- assert(b < MAX_BINS);
-
- if (m != max_ind[b])
- model->phi[m] = pexp->phi_prev[m] + N*m*best_Wo;
- }
- }
-}
-
-
-/*
- Theory is only the phase of the envelope of signal matters within a
- Critical Band. So we estimate the position of an impulse that
- approximates the envelope of the signal.
-*/
-
-void cb_phase2(struct PEXP *pexp, MODEL *model) {
- int st, m, i, a, b, step;
- float diff,w,c,s,phi1_;
- float A[MAX_AMP];
-
- for(m=1; m<=model->L; m++) {
- A[m] = model->A[m];
- model->A[m] = 0;
- }
-
- st = 2*model->L/4;
- step = 3;
- model->phi[1] = pexp->phi_prev[1] + (pexp->Wo_prev+model->Wo)*N/2.0;
-
- printf("L=%d ", model->L);
- for(m=st; m<st+step*2; m+=step) {
- a = m; b=a+step;
- if (b > model->L)
- b = model->L;
-
- c = s = 0;
- for(i=a; i<b-1; i++) {
- printf("diff %d,%d ", i, i+1);
- diff = model->phi[i+1] - model->phi[i];
- //w = (model->A[i+1] + model->A[i])/2;
- w = 1.0;
- c += w*cos(diff); s += w*sin(diff);
- }
- phi1_ = atan2(s,c);
- printf("replacing: ");
- for(i=a; i<b; i++) {
- //model->phi[i] = i*phi1_;
- //model->phi[i] = i*model->phi[1];
- //model->phi[i] = m*(pexp->Wo_prev+model->Wo)*N/2.0;
- model->A[m] = A[m];
- printf("%d ", i);
- }
- printf(" . ");
- }
- printf("\n");
-}
-
-
-static void smooth_phase4(MODEL *model) {
- int m;
- float phi_m, phi_m_1;
-
- if (model->L > 25) {
- printf("\nL %d\n", model->L);
- for(m=model->L/2; m<=model->L; m+=2) {
- if ((m+1) <= model->L) {
- phi_m = (model->phi[m] - model->phi[m+1])/2.0;
- phi_m_1 = (model->phi[m+1] - model->phi[m])/2.0;
- model->phi[m] = phi_m;
- model->phi[m+1] = phi_m_1;
- printf("%d %4.3f %4.3f ", m, phi_m, phi_m_1);
- }
- }
- }
-
-}
-
-/* try repeating last frame, just advance phases to account for time shift */
-
-static void repeat_phases(struct PEXP *pexp, MODEL *model) {
- int m;
-
- *model = pexp->prev_model;
- for(m=1; m<=model->L; m++)
- model->phi[m] += N*m*model->Wo;
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- phase_experiment()
-
- Phase quantisation experiments.
-
-\*---------------------------------------------------------------------------*/
-
-void phase_experiment(struct PEXP *pexp, MODEL *model, char *arg) {
- int m;
- float before[MAX_AMP], best_Wo;
-
- assert(pexp != NULL);
- memcpy(before, &model->phi[0], sizeof(float)*MAX_AMP);
-
- if (strcmp(arg,"q3") == 0) {
- quant_phases(model, 1, model->L, 3);
- update_snr_calc(pexp, model, before);
- update_variance_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"dec2") == 0) {
- if ((pexp->frames % 2) != 0) {
- predict_phases(pexp, model, 1, model->L);
- update_snr_calc(pexp, model, before);
- update_variance_calc(pexp, model, before);
- }
- }
-
- if (strcmp(arg,"repeat") == 0) {
- if ((pexp->frames % 2) != 0) {
- repeat_phases(pexp, model);
- update_snr_calc(pexp, model, before);
- update_variance_calc(pexp, model, before);
- }
- }
-
- if (strcmp(arg,"vq") == 0) {
- sparse_vq_pred_error(pexp, model);
- update_snr_calc(pexp, model, before);
- update_variance_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"pred") == 0)
- predict_phases_state(pexp, model, 1, model->L);
-
- if (strcmp(arg,"pred1k") == 0)
- predict_phases(pexp, model, 1, model->L/4);
-
- if (strcmp(arg,"smooth") == 0) {
- smooth_phase(pexp, model,0);
- update_snr_calc(pexp, model, before);
- }
- if (strcmp(arg,"smoothtrain") == 0)
- smooth_phase(pexp, model,1);
- if (strcmp(arg,"smoothvq") == 0) {
- smooth_phase(pexp, model,2);
- update_snr_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"smooth2") == 0)
- smooth_phase2(pexp, model);
- if (strcmp(arg,"smooth3") == 0)
- smooth_phase3(pexp, model);
- if (strcmp(arg,"smooth4") == 0)
- smooth_phase4(model);
- if (strcmp(arg,"vqsmooth3") == 0) {
- sparse_vq_pred_error(pexp, model);
- smooth_phase3(pexp, model);
- }
-
- if (strcmp(arg,"cb1") == 0) {
- cb_phase1(pexp, model);
- update_snr_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"top") == 0) {
- //top_amp(pexp, model, 1, model->L/4, 4, 1);
- //top_amp(pexp, model, model->L/4, model->L/3, 4, 1);
- //top_amp(pexp, model, model->L/3+1, model->L/2, 4, 1);
- //top_amp(pexp, model, model->L/2, model->L, 6, 1);
- //rand_phases(model, model->L/2, 3*model->L/4);
- //struct_phases(pexp, model, model->L/2, 3*model->L/4);
- //update_snr_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"pred23") == 0) {
- predict_phases2(pexp, model, model->L/2, model->L);
- update_snr_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"struct23") == 0) {
- struct_phases(pexp, model, model->L/2, 3*model->L/4 );
- update_snr_calc(pexp, model, before);
- }
-
- if (strcmp(arg,"addnoise") == 0) {
- int m;
- float max;
-
- max = 0;
- for(m=1; m<=model->L; m++)
- if (model->A[m] > max)
- max = model->A[m];
- max = 20.0*log10(max);
- for(m=1; m<=model->L; m++)
- if (20.0*log10(model->A[m]) < (max-20)) {
- model->phi[m] += (PI/4)*(1.0 -2.0*rand()/RAND_MAX);
- //printf("m %d\n", m);
- }
- }
-
- /* normalise phases */
-
- for(m=1; m<=model->L; m++)
- model->phi[m] = atan2(sin(model->phi[m]), cos(model->phi[m]));
-
- /* update states */
-
- //best_Wo = refine_Wo(pexp, model, model->L/2, model->L);
- pexp->phi1 += N*model->Wo;
-
- for(m=1; m<=model->L; m++)
- pexp->phi_prev[m] = model->phi[m];
- pexp->Wo_prev = model->Wo;
- pexp->frames++;
- pexp->prev_model = *model;
-}
-
-#ifdef OLD_STUFF
- //quant_phases(model, 1, model->L, 3);
- //update_variance_calc(pexp, model, before);
- //print_sparse_pred_error(pexp, model, 1, model->L, 40.0);
-
- //sparse_vq_pred_error(pexp, model);
-
- //quant_phases(model, model->L/4+1, model->L, 3);
-
- //predict_phases1(pexp, model, 1, model->L/4);
- //quant_phases(model, model->L/4+1, model->L, 3);
-
- //quant_phases(model, 1, model->L/8, 3);
-
- //update_snr_calc(pexp, model, before);
- //update_variance_calc(pexp, model, before);
-
- //fixed_bits_per_frame(pexp, model, 40);
- //struct_phases(pexp, model, 1, model->L/4);
- //rand_phases(model, 10, model->L);
- //for(m=1; m<=model->L; m++)
- // model->A[m] = 0.0;
- //model->A[model->L/2] = 1000;
- //repeat_phases(model, 20);
- //predict_phases(pexp, model, 1, model->L/4);
- //quant_phases(model, 1, 10, 3);
- //quant_phases(model, 10, 20, 2);
- //repeat_phases(model, 20);
- //rand_phases(model, 3*model->L/4, model->L);
- // print_phi1_pred_error(model, 1, model->L);
- //predict_phases(pexp, model, 1, model->L/4);
- //first_order_band(model, model->L/4, model->L/2);
- //first_order_band(model, model->L/2, 3*model->L/4);
- //if (fabs(model->Wo - pexp->Wo_prev)< 0.1*model->Wo)
-
- //print_pred_error(pexp, model, 1, model->L, 40.0);
- //print_sparse_pred_error(pexp, model, 1, model->L, 40.0);
-
- //phi1_est = est_phi1(model, 1, model->L/4);
- //print_phi1_pred_error(model, 1, model->L/4);
-
- //first_order_band(model, 1, model->L/4, phi1_est);
- //sub_linear(model, 1, model->L/4, phi1_est);
-
- //top_amp(pexp, model, 1, model->L/4, 4);
- //top_amp(pexp, model, model->L/4, model->L/2, 4);
-
- //first_order_band(model, 1, model->L/4, phi1_est);
- //first_order_band(model, model->L/4, model->L/2, phi1_est);
-
- //if (fabs(model->Wo - pexp->Wo_prev) > 0.2*model->Wo)
- // rand_phases(model, model->L/2, model->L);
-
- //top_amp(pexp, model, 1, model->L/4, 4);
- //top_amp(pexp, model, model->L/4, model->L/2, 8);
- //top_amp(pexp, model, model->L/4+1, model->L/2, 10, 1);
- //top_amp(pexp, model, 1, model->L/4, 10, 1);
- //top_amp(pexp, model, model->L/4+1, 3*model->L/4, 10, 1);
- //top_amp(pexp, model, 1, 3*model->L/4, 20, 1);
-
- #ifdef REAS_CAND1
- predict_phases(pexp, model, 1, model->L/4);
- top_amp(pexp, model, model->L/4+1, 3*model->L/4, 10, 1);
- rand_phases(model, 3*model->L/4+1, model->L);
- #endif
-
- #ifdef REAS_CAND2
- if ((pexp->frames % 2) == 0) {
- //printf("quant\n");
- predict_phases(pexp, model, 1, model->L/4);
- //top_amp(pexp, model, model->L/4+1, 3*model->L/4, 20, 1);
- top_amp(pexp, model, model->L/4+1, 7*model->L/8, 20, 1);
- rand_phases(model, 7*model->L/8+1, model->L);
- }
- else {
- //printf("predict\n");
- predict_phases(pexp, model, 1, model->L);
- }
- #endif
-
- //#define REAS_CAND3
- #ifdef REAS_CAND3
- if ((pexp->frames % 3) != 0) {
- printf("pred\n");
- predict_phases(pexp, model, 1, model->L);
- }
- else {
- predict_phases(pexp, model, 1, model->L/4);
- fixed_bits_per_frame(pexp, model, model->L/4+1, 60);
- }
- #endif
- //predict_phases(pexp, model, model->L/4, model->L);
-
-
- //print_pred_error(pexp, model, 1, model->L);
- //limit_prediction_error(pexp, model, model->L/2, model->L, PI/2);
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: phaseexp.h
- AUTHOR......: David Rowe
- DATE CREATED: June 2012
-
- Experimental functions for quantising, modelling and synthesising phase.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __PHASEEXP__
-#define __PHASEEXP__
-
-#include "kiss_fft.h"
-
-struct PEXP;
-
-struct PEXP * phase_experiment_create();
-void phase_experiment_destroy(struct PEXP *pexp);
-void phase_experiment(struct PEXP *pexp, MODEL *model, char *arg);
-
-#endif
+++ /dev/null
-/* Generated by pilot_coeff_file() Octave function */
-
-const float pilot_coeff[]={
- 0.00204705,
- 0.00276339,
- 0.00432595,
- 0.00697042,
- 0.0108452,
- 0.0159865,
- 0.0223035,
- 0.029577,
- 0.0374709,
- 0.045557,
- 0.0533491,
- 0.0603458,
- 0.0660751,
- 0.070138,
- 0.0722452,
- 0.0722452,
- 0.070138,
- 0.0660751,
- 0.0603458,
- 0.0533491,
- 0.045557,
- 0.0374709,
- 0.029577,
- 0.0223035,
- 0.0159865,
- 0.0108452,
- 0.00697042,
- 0.00432595,
- 0.00276339,
- 0.00204705
-};
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: postfilter.c
- AUTHOR......: David Rowe
- DATE CREATED: 13/09/09
-
- Postfilter to improve sound quality for speech with high levels of
- background noise. Unlike mixed-excitation models requires no bits
- to be transmitted to handle background noise.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <math.h>
-
-#include "defines.h"
-#include "comp.h"
-#include "dump.h"
-#include "postfilter.h"
-
-/*---------------------------------------------------------------------------*\
-
- DEFINES
-
-\*---------------------------------------------------------------------------*/
-
-#define BG_THRESH 40.0 /* only consider low levels signals for bg_est */
-#define BG_BETA 0.1 /* averaging filter constant */
-#define BG_MARGIN 6.0 /* harmonics this far above BG noise are
- randomised. Helped make bg noise less
- spikey (impulsive) for mmt1, but speech was
- perhaps a little rougher.
- */
-
-/*---------------------------------------------------------------------------*\
-
- postfilter()
-
- The post filter is designed to help with speech corrupted by
- background noise. The zero phase model tends to make speech with
- background noise sound "clicky". With high levels of background
- noise the low level inter-formant parts of the spectrum will contain
- noise rather than speech harmonics, so modelling them as voiced
- (i.e. a continuous, non-random phase track) is inaccurate.
-
- Some codecs (like MBE) have a mixed voicing model that breaks the
- spectrum into voiced and unvoiced regions. Several bits/frame
- (5-12) are required to transmit the frequency selective voicing
- information. Mixed excitation also requires accurate voicing
- estimation (parameter estimators always break occasionally under
- exceptional conditions).
-
- In our case we use a post filter approach which requires no
- additional bits to be transmitted. The decoder measures the average
- level of the background noise during unvoiced frames. If a harmonic
- is less than this level it is made unvoiced by randomising it's
- phases.
-
- This idea is rather experimental. Some potential problems that may
- happen:
-
- 1/ If someone says "aaaaaaaahhhhhhhhh" will background estimator track
- up to speech level? This would be a bad thing.
-
- 2/ If background noise suddenly dissapears from the source speech does
- estimate drop quickly? What is noise suddenly re-appears?
-
- 3/ Background noise with a non-flat sepctrum. Current algorithm just
- comsiders scpetrum as a whole, but this could be broken up into
- bands, each with their own estimator.
-
- 4/ Males and females with the same level of background noise. Check
- performance the same. Changing Wo affects width of each band, may
- affect bg energy estimates.
-
- 5/ Not sure what happens during long periods of voiced speech
- e.g. "sshhhhhhh"
-
-\*---------------------------------------------------------------------------*/
-
-void postfilter(
- MODEL *model,
- float *bg_est
-)
-{
- int m, uv;
- float e;
-
- /* determine average energy across spectrum */
-
- e = 0.0;
- for(m=1; m<=model->L; m++)
- e += model->A[m]*model->A[m];
-
- assert(e > 0.0);
- e = 10.0*log10(e/model->L);
-
- /* If beneath threhold, update bg estimate. The idea
- of the threshold is to prevent updating during high level
- speech. */
-
- if ((e < BG_THRESH) && !model->voiced)
- *bg_est = *bg_est*(1.0 - BG_BETA) + e*BG_BETA;
-
- /* now mess with phases during voiced frames to make any harmonics
- less then our background estimate unvoiced.
- */
-
- uv = 0;
- if (model->voiced)
- for(m=1; m<=model->L; m++)
- if (20.0*log10(model->A[m]) < (*bg_est + BG_MARGIN)) {
- model->phi[m] = TWO_PI*(float)rand()/RAND_MAX;
- uv++;
- }
-
-#ifdef DUMP
- dump_bg(e, *bg_est, 100.0*uv/model->L);
-#endif
-
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: postfilter.h
- AUTHOR......: David Rowe
- DATE CREATED: 13/09/09
-
- Postfilter header file.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __POSTFILTER__
-#define __POSTFILTER__
-
-void postfilter(MODEL *model, float *bg_est);
-
-#endif
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: quantise.c
- AUTHOR......: David Rowe
- DATE CREATED: 31/5/92
-
- Quantisation functions for the sinusoidal coder.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-
-*/
-
-#include <assert.h>
-#include <ctype.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-
-#include "defines.h"
-#include "dump.h"
-#include "quantise.h"
-#include "lpc.h"
-#include "lsp.h"
-#include "kiss_fft.h"
-
-#define LSP_DELTA1 0.01 /* grid spacing for LSP root searches */
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION HEADERS
-
-\*---------------------------------------------------------------------------*/
-
-float speech_to_uq_lsps(float lsp[], float ak[], float Sn[], float w[],
- int order);
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*---------------------------------------------------------------------------*/
-
-int lsp_bits(int i) {
- return lsp_cb[i].log2m;
-}
-
-int lspd_bits(int i) {
- return lsp_cbd[i].log2m;
-}
-
-int lspdt_bits(int i) {
- return lsp_cbdt[i].log2m;
-}
-
-int lsp_pred_vq_bits(int i) {
- return lsp_cbjvm[i].log2m;
-}
-
-/*---------------------------------------------------------------------------*\
-
- quantise_init
-
- Loads the entire LSP quantiser comprised of several vector quantisers
- (codebooks).
-
-\*---------------------------------------------------------------------------*/
-
-void quantise_init()
-{
-}
-
-/*---------------------------------------------------------------------------*\
-
- quantise
-
- Quantises vec by choosing the nearest vector in codebook cb, and
- returns the vector index. The squared error of the quantised vector
- is added to se.
-
-\*---------------------------------------------------------------------------*/
-
-long quantise(const float * cb, float vec[], float w[], int k, int m, float *se)
-/* float cb[][K]; current VQ codebook */
-/* float vec[]; vector to quantise */
-/* float w[]; weighting vector */
-/* int k; dimension of vectors */
-/* int m; size of codebook */
-/* float *se; accumulated squared error */
-{
- float e; /* current error */
- long besti; /* best index so far */
- float beste; /* best error so far */
- long j;
- int i;
- float diff;
-
- besti = 0;
- beste = 1E32;
- for(j=0; j<m; j++) {
- e = 0.0;
- for(i=0; i<k; i++) {
- diff = cb[j*k+i]-vec[i];
- e += pow(diff*w[i],2.0);
- }
- if (e < beste) {
- beste = e;
- besti = j;
- }
- }
-
- *se += beste;
-
- return(besti);
-}
-
-/*---------------------------------------------------------------------------*\
-
- encode_lspds_scalar()
-
- Scalar/VQ LSP difference quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-void encode_lspds_scalar(
- int indexes[],
- float lsp[],
- int order
-)
-{
- int i,k,m;
- float lsp_hz[LPC_MAX];
- float lsp__hz[LPC_MAX];
- float dlsp[LPC_MAX];
- float dlsp_[LPC_MAX];
- float wt[LPC_MAX];
- const float *cb;
- float se;
-
- assert(order == LPC_ORD);
-
- for(i=0; i<order; i++) {
- wt[i] = 1.0;
- }
-
- /* convert from radians to Hz so we can use human readable
- frequencies */
-
- for(i=0; i<order; i++)
- lsp_hz[i] = (4000.0/PI)*lsp[i];
-
- //printf("\n");
-
- wt[0] = 1.0;
- for(i=0; i<order; i++) {
-
- /* find difference from previous qunatised lsp */
-
- if (i)
- dlsp[i] = lsp_hz[i] - lsp__hz[i-1];
- else
- dlsp[0] = lsp_hz[0];
-
- k = lsp_cbd[i].k;
- m = lsp_cbd[i].m;
- cb = lsp_cbd[i].cb;
- indexes[i] = quantise(cb, &dlsp[i], wt, k, m, &se);
- dlsp_[i] = cb[indexes[i]*k];
-
-
- if (i)
- lsp__hz[i] = lsp__hz[i-1] + dlsp_[i];
- else
- lsp__hz[0] = dlsp_[0];
-
- //printf("%d lsp %3.2f dlsp %3.2f dlsp_ %3.2f lsp_ %3.2f\n", i, lsp_hz[i], dlsp[i], dlsp_[i], lsp__hz[i]);
- }
-
-}
-
-void decode_lspds_scalar(
- float lsp_[],
- int indexes[],
- int order
-)
-{
- int i,k;
- float lsp__hz[LPC_MAX];
- float dlsp_[LPC_MAX];
- const float *cb;
-
- assert(order == LPC_ORD);
-
- for(i=0; i<order; i++) {
-
- k = lsp_cbd[i].k;
- cb = lsp_cbd[i].cb;
- dlsp_[i] = cb[indexes[i]*k];
-
- if (i)
- lsp__hz[i] = lsp__hz[i-1] + dlsp_[i];
- else
- lsp__hz[0] = dlsp_[0];
-
- lsp_[i] = (PI/4000.0)*lsp__hz[i];
-
- //printf("%d dlsp_ %3.2f lsp_ %3.2f\n", i, dlsp_[i], lsp__hz[i]);
- }
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- lspvq_quantise
-
- Vector LSP quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-void lspvq_quantise(
- float lsp[],
- float lsp_[],
- int order
-)
-{
- int i,k,m,ncb, nlsp;
- float wt[LPC_ORD], lsp_hz[LPC_ORD];
- const float *cb;
- float se;
- int index;
-
- for(i=0; i<LPC_ORD; i++) {
- wt[i] = 1.0;
- lsp_hz[i] = 4000.0*lsp[i]/PI;
- }
-
- /* scalar quantise LSPs 1,2,3,4 */
-
- /* simple uniform scalar quantisers */
-
- for(i=0; i<4; i++) {
- k = lsp_cb[i].k;
- m = lsp_cb[i].m;
- cb = lsp_cb[i].cb;
- index = quantise(cb, &lsp_hz[i], wt, k, m, &se);
- lsp_[i] = cb[index*k]*PI/4000.0;
- }
-
- //#define WGHT
-#ifdef WGHT
- for(i=4; i<9; i++) {
- wt[i] = 1.0/(lsp[i]-lsp[i-1]) + 1.0/(lsp[i+1]-lsp[i]);
- //printf("wt[%d] = %f\n", i, wt[i]);
- }
- wt[9] = 1.0/(lsp[i]-lsp[i-1]);
-#endif
-
- /* VQ LSPs 5,6,7,8,9,10 */
-
- ncb = 4;
- nlsp = 4;
- k = lsp_cbjnd[ncb].k;
- m = lsp_cbjnd[ncb].m;
- cb = lsp_cbjnd[ncb].cb;
- index = quantise(cb, &lsp_hz[nlsp], &wt[nlsp], k, m, &se);
- for(i=4; i<LPC_ORD; i++) {
- lsp_[i] = cb[index*k+i-4]*(PI/4000.0);
- //printf("%4.f (%4.f) ", lsp_hz[i], cb[index*k+i-4]);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- lspjnd_quantise
-
- Experimental JND LSP quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-void lspjnd_quantise(float lsps[], float lsps_[], int order)
-{
- int i,k,m;
- float wt[LPC_ORD], lsps_hz[LPC_ORD];
- const float *cb;
- float se = 0.0;
- int index;
-
- for(i=0; i<LPC_ORD; i++) {
- wt[i] = 1.0;
- }
-
- /* convert to Hz */
-
- for(i=0; i<LPC_ORD; i++) {
- lsps_hz[i] = lsps[i]*(4000.0/PI);
- lsps_[i] = lsps[i];
- }
-
- /* simple uniform scalar quantisers */
-
- for(i=0; i<4; i++) {
- k = lsp_cbjnd[i].k;
- m = lsp_cbjnd[i].m;
- cb = lsp_cbjnd[i].cb;
- index = quantise(cb, &lsps_hz[i], wt, k, m, &se);
- lsps_[i] = cb[index*k]*(PI/4000.0);
- }
-
- /* VQ LSPs 5,6,7,8,9,10 */
-
- k = lsp_cbjnd[4].k;
- m = lsp_cbjnd[4].m;
- cb = lsp_cbjnd[4].cb;
- index = quantise(cb, &lsps_hz[4], &wt[4], k, m, &se);
- //printf("k = %d m = %d c[0] %f cb[k] %f\n", k,m,cb[0],cb[k]);
- //printf("index = %4d: ", index);
- for(i=4; i<LPC_ORD; i++) {
- lsps_[i] = cb[index*k+i-4]*(PI/4000.0);
- //printf("%4.f (%4.f) ", lsps_hz[i], cb[index*k+i-4]);
- }
- //printf("\n");
-}
-
-void compute_weights(const float *x, float *w, int ndim);
-
-/*---------------------------------------------------------------------------*\
-
- lspdt_quantise
-
- LSP difference in time quantiser. Split VQ, encoding LSPs 1-4 with
- one VQ, and LSPs 5-10 with a second. Update of previous lsp memory
- is done outside of this function to handle dT between 10 or 20ms
- frames.
-
- mode action
- ------------------
-
- LSPDT_ALL VQ LSPs 1-4 and 5-10
- LSPDT_LOW Just VQ LSPs 1-4, for LSPs 5-10 just copy previous
- LSPDT_HIGH Just VQ LSPs 5-10, for LSPs 1-4 just copy previous
-
-\*---------------------------------------------------------------------------*/
-
-void lspdt_quantise(float lsps[], float lsps_[], float lsps__prev[], int mode)
-{
- int i;
- float wt[LPC_ORD];
- float lsps_dt[LPC_ORD];
-#ifdef TRY_LSPDT_VQ
- int k,m;
- int index;
- const float *cb;
- float se = 0.0;
-#endif // TRY_LSPDT_VQ
-
- //compute_weights(lsps, wt, LPC_ORD);
- for(i=0; i<LPC_ORD; i++) {
- wt[i] = 1.0;
- }
-
- //compute_weights(lsps, wt, LPC_ORD );
-
- for(i=0; i<LPC_ORD; i++) {
- lsps_dt[i] = lsps[i] - lsps__prev[i];
- lsps_[i] = lsps__prev[i];
- }
-
- //#define TRY_LSPDT_VQ
-#ifdef TRY_LSPDT_VQ
- /* this actually improves speech a bit, but 40ms updates works surprsingly well.... */
- k = lsp_cbdt[0].k;
- m = lsp_cbdt[0].m;
- cb = lsp_cbdt[0].cb;
- index = quantise(cb, lsps_dt, wt, k, m, &se);
- for(i=0; i<LPC_ORD; i++) {
- lsps_[i] += cb[index*k + i];
- }
-#endif
-
-}
-
-#define MIN(a,b) ((a)<(b)?(a):(b))
-#define MAX_ENTRIES 16384
-
-void compute_weights(const float *x, float *w, int ndim)
-{
- int i;
- w[0] = MIN(x[0], x[1]-x[0]);
- for (i=1;i<ndim-1;i++)
- w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
- w[ndim-1] = MIN(x[ndim-1]-x[ndim-2], PI-x[ndim-1]);
-
- for (i=0;i<ndim;i++)
- w[i] = 1./(.01+w[i]);
- //w[0]*=3;
- //w[1]*=2;
-}
-
-/* LSP weight calculation ported from m-file function kindly submitted
- by Anssi, OH3GDD */
-
-void compute_weights_anssi_mode2(const float *x, float *w, int ndim)
-{
- int i;
- float d[LPC_ORD];
-
- assert(ndim == LPC_ORD);
-
- for(i=0; i<LPC_ORD; i++)
- d[i] = 1.0;
-
- d[0] = x[1];
- for (i=1; i<LPC_ORD-1; i++)
- d[i] = x[i+1] - x[i-1];
- d[LPC_ORD-1] = PI - x[8];
- for (i=0; i<LPC_ORD; i++) {
- if (x[i]<((400.0/4000.0)*PI))
- w[i]=5.0/(0.01+d[i]);
- else if (x[i]<((700.0/4000.0)*PI))
- w[i]=4.0/(0.01+d[i]);
- else if (x[i]<((1200.0/4000.0)*PI))
- w[i]=3.0/(0.01+d[i]);
- else if (x[i]<((2000.0/4000.0)*PI))
- w[i]=2.0/(0.01+d[i]);
- else
- w[i]=1.0/(0.01+d[i]);
-
- w[i]=pow(w[i]+0.3, 0.66);
- }
-}
-
-int find_nearest(const float *codebook, int nb_entries, float *x, int ndim)
-{
- int i, j;
- float min_dist = 1e15;
- int nearest = 0;
-
- for (i=0;i<nb_entries;i++)
- {
- float dist=0;
- for (j=0;j<ndim;j++)
- dist += (x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
- if (dist<min_dist)
- {
- min_dist = dist;
- nearest = i;
- }
- }
- return nearest;
-}
-
-int find_nearest_weighted(const float *codebook, int nb_entries, float *x, const float *w, int ndim)
-{
- int i, j;
- float min_dist = 1e15;
- int nearest = 0;
-
- for (i=0;i<nb_entries;i++)
- {
- float dist=0;
- for (j=0;j<ndim;j++)
- dist += w[j]*(x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
- if (dist<min_dist)
- {
- min_dist = dist;
- nearest = i;
- }
- }
- return nearest;
-}
-
-void lspjvm_quantise(float *x, float *xq, int ndim)
-{
- int i, n1, n2, n3;
- float err[LPC_ORD], err2[LPC_ORD], err3[LPC_ORD];
- float w[LPC_ORD], w2[LPC_ORD], w3[LPC_ORD];
- const float *codebook1 = lsp_cbjvm[0].cb;
- const float *codebook2 = lsp_cbjvm[1].cb;
- const float *codebook3 = lsp_cbjvm[2].cb;
-
- w[0] = MIN(x[0], x[1]-x[0]);
- for (i=1;i<ndim-1;i++)
- w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
- w[ndim-1] = MIN(x[ndim-1]-x[ndim-2], PI-x[ndim-1]);
-
- compute_weights(x, w, ndim);
-
- n1 = find_nearest(codebook1, lsp_cbjvm[0].m, x, ndim);
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = codebook1[ndim*n1+i];
- err[i] = x[i] - xq[i];
- }
- for (i=0;i<ndim/2;i++)
- {
- err2[i] = err[2*i];
- err3[i] = err[2*i+1];
- w2[i] = w[2*i];
- w3[i] = w[2*i+1];
- }
- n2 = find_nearest_weighted(codebook2, lsp_cbjvm[1].m, err2, w2, ndim/2);
- n3 = find_nearest_weighted(codebook3, lsp_cbjvm[2].m, err3, w3, ndim/2);
-
- for (i=0;i<ndim/2;i++)
- {
- xq[2*i] += codebook2[ndim*n2/2+i];
- xq[2*i+1] += codebook3[ndim*n3/2+i];
- }
-}
-
-#define MBEST_STAGES 4
-
-struct MBEST_LIST {
- int index[MBEST_STAGES]; /* index of each stage that lead us to this error */
- float error;
-};
-
-struct MBEST {
- int entries; /* number of entries in mbest list */
- struct MBEST_LIST *list;
-};
-
-
-static struct MBEST *mbest_create(int entries) {
- int i,j;
- struct MBEST *mbest;
-
- assert(entries > 0);
- mbest = (struct MBEST *)malloc(sizeof(struct MBEST));
- assert(mbest != NULL);
-
- mbest->entries = entries;
- mbest->list = (struct MBEST_LIST *)malloc(entries*sizeof(struct MBEST_LIST));
- assert(mbest->list != NULL);
-
- for(i=0; i<mbest->entries; i++) {
- for(j=0; j<MBEST_STAGES; j++)
- mbest->list[i].index[j] = 0;
- mbest->list[i].error = 1E32;
- }
-
- return mbest;
-}
-
-
-static void mbest_destroy(struct MBEST *mbest) {
- assert(mbest != NULL);
- free(mbest->list);
- free(mbest);
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- mbest_insert
-
- Insert the results of a vector to codebook entry comparison. The
- list is ordered in order or error, so those entries with the
- smallest error will be first on the list.
-
-\*---------------------------------------------------------------------------*/
-
-static void mbest_insert(struct MBEST *mbest, int index[], float error) {
- int i, j, found;
- struct MBEST_LIST *list = mbest->list;
- int entries = mbest->entries;
-
- found = 0;
- for(i=0; i<entries && !found; i++)
- if (error < list[i].error) {
- found = 1;
- for(j=entries-1; j>i; j--)
- list[j] = list[j-1];
- for(j=0; j<MBEST_STAGES; j++)
- list[i].index[j] = index[j];
- list[i].error = error;
- }
-}
-
-
-static void mbest_print(char title[], struct MBEST *mbest) {
- int i,j;
-
- printf("%s\n", title);
- for(i=0; i<mbest->entries; i++) {
- for(j=0; j<MBEST_STAGES; j++)
- printf(" %4d ", mbest->list[i].index[j]);
- printf(" %f\n", mbest->list[i].error);
- }
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- mbest_search
-
- Searches vec[] to a codebbook of vectors, and maintains a list of the mbest
- closest matches.
-
-\*---------------------------------------------------------------------------*/
-
-static void mbest_search(
- const float *cb, /* VQ codebook to search */
- float vec[], /* target vector */
- float w[], /* weighting vector */
- int k, /* dimension of vector */
- int m, /* number on entries in codebook */
- struct MBEST *mbest, /* list of closest matches */
- int index[] /* indexes that lead us here */
-)
-{
- float e;
- int i,j;
- float diff;
-
- for(j=0; j<m; j++) {
- e = 0.0;
- for(i=0; i<k; i++) {
- diff = cb[j*k+i]-vec[i];
- e += pow(diff*w[i],2.0);
- }
- index[0] = j;
- mbest_insert(mbest, index, e);
- }
-}
-
-
-/* 3 stage VQ LSP quantiser. Design and guidance kindly submitted by Anssi, OH3GDD */
-
-void lspanssi_quantise(float *x, float *xq, int ndim, int mbest_entries)
-{
- int i, j, n1, n2, n3, n4;
- float w[LPC_ORD];
- const float *codebook1 = lsp_cbvqanssi[0].cb;
- const float *codebook2 = lsp_cbvqanssi[1].cb;
- const float *codebook3 = lsp_cbvqanssi[2].cb;
- const float *codebook4 = lsp_cbvqanssi[3].cb;
- struct MBEST *mbest_stage1, *mbest_stage2, *mbest_stage3, *mbest_stage4;
- float target[LPC_ORD];
- int index[MBEST_STAGES];
-
- mbest_stage1 = mbest_create(mbest_entries);
- mbest_stage2 = mbest_create(mbest_entries);
- mbest_stage3 = mbest_create(mbest_entries);
- mbest_stage4 = mbest_create(mbest_entries);
- for(i=0; i<MBEST_STAGES; i++)
- index[i] = 0;
-
- compute_weights_anssi_mode2(x, w, ndim);
-
- #ifdef DUMP
- dump_weights(w, ndim);
- #endif
-
- /* Stage 1 */
-
- mbest_search(codebook1, x, w, ndim, lsp_cbvqanssi[0].m, mbest_stage1, index);
- mbest_print("Stage 1:", mbest_stage1);
-
- /* Stage 2 */
-
- for (j=0; j<mbest_entries; j++) {
- index[1] = n1 = mbest_stage1->list[j].index[0];
- for(i=0; i<ndim; i++)
- target[i] = x[i] - codebook1[ndim*n1+i];
- mbest_search(codebook2, target, w, ndim, lsp_cbvqanssi[1].m, mbest_stage2, index);
- }
- mbest_print("Stage 2:", mbest_stage2);
-
- /* Stage 3 */
-
- for (j=0; j<mbest_entries; j++) {
- index[2] = n1 = mbest_stage2->list[j].index[1];
- index[1] = n2 = mbest_stage2->list[j].index[0];
- for(i=0; i<ndim; i++)
- target[i] = x[i] - codebook1[ndim*n1+i] - codebook2[ndim*n2+i];
- mbest_search(codebook3, target, w, ndim, lsp_cbvqanssi[2].m, mbest_stage3, index);
- }
- mbest_print("Stage 3:", mbest_stage3);
-
- /* Stage 4 */
-
- for (j=0; j<mbest_entries; j++) {
- index[3] = n1 = mbest_stage3->list[j].index[2];
- index[2] = n2 = mbest_stage3->list[j].index[1];
- index[1] = n3 = mbest_stage3->list[j].index[0];
- for(i=0; i<ndim; i++)
- target[i] = x[i] - codebook1[ndim*n1+i] - codebook2[ndim*n2+i] - codebook3[ndim*n3+i];
- mbest_search(codebook4, target, w, ndim, lsp_cbvqanssi[3].m, mbest_stage4, index);
- }
- mbest_print("Stage 4:", mbest_stage4);
-
- n1 = mbest_stage4->list[0].index[3];
- n2 = mbest_stage4->list[0].index[2];
- n3 = mbest_stage4->list[0].index[1];
- n4 = mbest_stage4->list[0].index[0];
- for (i=0;i<ndim;i++)
- xq[i] = codebook1[ndim*n1+i] + codebook2[ndim*n2+i] + codebook3[ndim*n3+i] + codebook4[ndim*n4+i];
-
- mbest_destroy(mbest_stage1);
- mbest_destroy(mbest_stage2);
- mbest_destroy(mbest_stage3);
- mbest_destroy(mbest_stage4);
-}
-
-int check_lsp_order(float lsp[], int lpc_order)
-{
- int i;
- float tmp;
- int swaps = 0;
-
- for(i=1; i<lpc_order; i++)
- if (lsp[i] < lsp[i-1]) {
- //printf("swap %d\n",i);
- swaps++;
- tmp = lsp[i-1];
- lsp[i-1] = lsp[i]-0.05;
- lsp[i] = tmp+0.05;
- }
-
- return swaps;
-}
-
-void force_min_lsp_dist(float lsp[], int lpc_order)
-{
- int i;
-
- for(i=1; i<lpc_order; i++)
- if ((lsp[i]-lsp[i-1]) < 0.01) {
- lsp[i] += 0.01;
- }
-}
-
-#ifdef NOT_USED
-/*---------------------------------------------------------------------------*\
-
- lpc_model_amplitudes
-
- Derive a LPC model for amplitude samples then estimate amplitude samples
- from this model with optional LSP quantisation.
-
- Returns the spectral distortion for this frame.
-
-\*---------------------------------------------------------------------------*/
-
-float lpc_model_amplitudes(
- float Sn[], /* Input frame of speech samples */
- float w[],
- MODEL *model, /* sinusoidal model parameters */
- int order, /* LPC model order */
- int lsp_quant, /* optional LSP quantisation if non-zero */
- float ak[] /* output aks */
-)
-{
- float Wn[M];
- float R[LPC_MAX+1];
- float E;
- int i,j;
- float snr;
- float lsp[LPC_MAX];
- float lsp_hz[LPC_MAX];
- float lsp_[LPC_MAX];
- int roots; /* number of LSP roots found */
- float wt[LPC_MAX];
-
- for(i=0; i<M; i++)
- Wn[i] = Sn[i]*w[i];
- autocorrelate(Wn,R,M,order);
- levinson_durbin(R,ak,order);
-
- E = 0.0;
- for(i=0; i<=order; i++)
- E += ak[i]*R[i];
-
- for(i=0; i<order; i++)
- wt[i] = 1.0;
-
- if (lsp_quant) {
- roots = lpc_to_lsp(ak, order, lsp, 5, LSP_DELTA1);
- if (roots != order)
- printf("LSP roots not found\n");
-
- /* convert from radians to Hz to make quantisers more
- human readable */
-
- for(i=0; i<order; i++)
- lsp_hz[i] = (4000.0/PI)*lsp[i];
-
-#ifdef NOT_NOW
- /* simple uniform scalar quantisers */
-
- for(i=0; i<10; i++) {
- k = lsp_cb[i].k;
- m = lsp_cb[i].m;
- cb = lsp_cb[i].cb;
- index = quantise(cb, &lsp_hz[i], wt, k, m, &se);
- lsp_hz[i] = cb[index*k];
- }
-#endif
-
- /* experiment: simulating uniform quantisation error
- for(i=0; i<order; i++)
- lsp[i] += PI*(12.5/4000.0)*(1.0 - 2.0*(float)rand()/RAND_MAX);
- */
-
- for(i=0; i<order; i++)
- lsp[i] = (PI/4000.0)*lsp_hz[i];
-
- /* Bandwidth Expansion (BW). Prevents any two LSPs getting too
- close together after quantisation. We know from experiment
- that LSP quantisation errors < 12.5Hz (25Hz step size) are
- inaudible so we use that as the minimum LSP separation.
- */
-
- for(i=1; i<5; i++) {
- if (lsp[i] - lsp[i-1] < PI*(12.5/4000.0))
- lsp[i] = lsp[i-1] + PI*(12.5/4000.0);
- }
-
- /* as quantiser gaps increased, larger BW expansion was required
- to prevent twinkly noises */
-
- for(i=5; i<8; i++) {
- if (lsp[i] - lsp[i-1] < PI*(25.0/4000.0))
- lsp[i] = lsp[i-1] + PI*(25.0/4000.0);
- }
- for(i=8; i<order; i++) {
- if (lsp[i] - lsp[i-1] < PI*(75.0/4000.0))
- lsp[i] = lsp[i-1] + PI*(75.0/4000.0);
- }
-
- for(j=0; j<order; j++)
- lsp_[j] = lsp[j];
-
- lsp_to_lpc(lsp_, ak, order);
-#ifdef DUMP
- dump_lsp(lsp);
-#endif
- }
-
-#ifdef DUMP
- dump_E(E);
-#endif
- #ifdef SIM_QUANT
- /* simulated LPC energy quantisation */
- {
- float e = 10.0*log10(E);
- e += 2.0*(1.0 - 2.0*(float)rand()/RAND_MAX);
- E = pow(10.0,e/10.0);
- }
- #endif
-
- aks_to_M2(ak,order,model,E,&snr, 1, 0, 1); /* {ak} -> {Am} LPC decode */
-
- return snr;
-}
-#endif
-
-/*---------------------------------------------------------------------------*\
-
- lpc_post_filter()
-
- Applies a post filter to the LPC synthesis filter power spectrum
- Pw, which supresses the inter-formant energy.
-
- The algorithm is from p267 (Section 8.6) of "Digital Speech",
- edited by A.M. Kondoz, 1994 published by Wiley and Sons. Chapter 8
- of this text is on the MBE vocoder, and this is a freq domain
- adaptation of post filtering commonly used in CELP.
-
- I used the Octave simulation lpcpf.m to get an understaing of the
- algorithm.
-
- Requires two more FFTs which is significantly more MIPs. However
- it should be possible to implement this more efficiently in the
- time domain. Just not sure how to handle relative time delays
- between the synthesis stage and updating these coeffs. A smaller
- FFT size might also be accetable to save CPU.
-
- TODO:
- [ ] sync var names between Octave and C version
- [ ] doc gain normalisation
- [ ] I think the first FFT is not rqd as we do the same
- thing in aks_to_M2().
-
-\*---------------------------------------------------------------------------*/
-
-void lpc_post_filter(kiss_fft_cfg fft_fwd_cfg, MODEL *model, COMP Pw[], float ak[],
- int order, int dump, float beta, float gamma, int bass_boost)
-{
- int i;
- COMP x[FFT_ENC]; /* input to FFTs */
- COMP Aw[FFT_ENC]; /* LPC analysis filter spectrum */
- COMP Ww[FFT_ENC]; /* weighting spectrum */
- float Rw[FFT_ENC]; /* R = WA */
- float e_before, e_after, gain;
- float Pfw[FFT_ENC]; /* Post filter mag spectrum */
- float max_Rw, min_Rw;
- float range, thresh, r, w;
- int m, bin;
-
- /* Determine LPC inverse filter spectrum 1/A(exp(jw)) -----------*/
-
- /* we actually want the synthesis filter A(exp(jw)) but the
- inverse (analysis) filter is easier to find as it's FIR, we
- just use the inverse of 1/A to get the synthesis filter
- A(exp(jw)) */
-
- for(i=0; i<FFT_ENC; i++) {
- x[i].real = 0.0;
- x[i].imag = 0.0;
- }
-
- for(i=0; i<=order; i++)
- x[i].real = ak[i];
- kiss_fft(fft_fwd_cfg, (kiss_fft_cpx *)x, (kiss_fft_cpx *)Aw);
-
- for(i=0; i<FFT_ENC/2; i++) {
- Aw[i].real = 1.0/sqrt(Aw[i].real*Aw[i].real + Aw[i].imag*Aw[i].imag);
- }
-
- /* Determine weighting filter spectrum W(exp(jw)) ---------------*/
-
- for(i=0; i<FFT_ENC; i++) {
- x[i].real = 0.0;
- x[i].imag = 0.0;
- }
-
- for(i=0; i<=order; i++)
- x[i].real = ak[i] * pow(gamma, (float)i);
- kiss_fft(fft_fwd_cfg, (kiss_fft_cpx *)x, (kiss_fft_cpx *)Ww);
-
- for(i=0; i<FFT_ENC/2; i++) {
- Ww[i].real = sqrt(Ww[i].real*Ww[i].real + Ww[i].imag*Ww[i].imag);
- }
-
- /* Determined combined filter R = WA ---------------------------*/
-
- max_Rw = 0.0; min_Rw = 1E32;
- for(i=0; i<FFT_ENC/2; i++) {
- Rw[i] = Ww[i].real * Aw[i].real;
- if (Rw[i] > max_Rw)
- max_Rw = Rw[i];
- if (Rw[i] < min_Rw)
- min_Rw = Rw[i];
-
- }
- #ifdef DUMP
- if (dump)
- dump_Rw(Rw);
- #endif
-
- /* create post filter mag spectrum and apply ------------------*/
-
- /* measure energy before post filtering */
-
- e_before = 1E-4;
- for(i=0; i<FFT_ENC/2; i++)
- e_before += Pw[i].real;
-
- /* apply post filter and measure energy */
-
- #ifdef DUMP
- if (dump)
- dump_Pwb(Pw);
- #endif
-
- e_after = 1E-4;
- for(i=0; i<FFT_ENC/2; i++) {
- Pfw[i] = pow(Rw[i], beta);
- Pw[i].real *= Pfw[i] * Pfw[i];
- e_after += Pw[i].real;
- }
- gain = e_before/e_after;
-
- /* apply gain factor to normalise energy */
-
- for(i=0; i<FFT_ENC/2; i++) {
- Pw[i].real *= gain;
- }
-
- if (bass_boost) {
- /* add 3dB to first 1 kHz to account for LP effect of PF */
-
- for(i=0; i<FFT_ENC/8; i++) {
- Pw[i].real *= 1.4*1.4;
- }
- }
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- aks_to_M2()
-
- Transforms the linear prediction coefficients to spectral amplitude
- samples. This function determines A(m) from the average energy per
- band using an FFT.
-
-\*---------------------------------------------------------------------------*/
-
-void aks_to_M2(
- kiss_fft_cfg fft_fwd_cfg,
- float ak[], /* LPC's */
- int order,
- MODEL *model, /* sinusoidal model parameters for this frame */
- float E, /* energy term */
- float *snr, /* signal to noise ratio for this frame in dB */
- int dump, /* true to dump sample to dump file */
- int sim_pf, /* true to simulate a post filter */
- int pf, /* true to LPC post filter */
- int bass_boost, /* enable LPC filter 0-1khz 3dB boost */
- float beta,
- float gamma /* LPC post filter parameters */
-)
-{
- COMP pw[FFT_ENC]; /* input to FFT for power spectrum */
- COMP Pw[FFT_ENC]; /* output power spectrum */
- int i,m; /* loop variables */
- int am,bm; /* limits of current band */
- float r; /* no. rads/bin */
- float Em; /* energy in band */
- float Am; /* spectral amplitude sample */
- float signal, noise;
-
- r = TWO_PI/(FFT_ENC);
-
- /* Determine DFT of A(exp(jw)) --------------------------------------------*/
-
- for(i=0; i<FFT_ENC; i++) {
- pw[i].real = 0.0;
- pw[i].imag = 0.0;
- }
-
- for(i=0; i<=order; i++)
- pw[i].real = ak[i];
- kiss_fft(fft_fwd_cfg, (kiss_fft_cpx *)pw, (kiss_fft_cpx *)Pw);
-
- /* Determine power spectrum P(w) = E/(A(exp(jw))^2 ------------------------*/
-
- for(i=0; i<FFT_ENC/2; i++)
- Pw[i].real = E/(Pw[i].real*Pw[i].real + Pw[i].imag*Pw[i].imag);
-
- if (pf)
- lpc_post_filter(fft_fwd_cfg, model, Pw, ak, order, dump, beta, gamma, bass_boost);
-
- #ifdef DUMP
- if (dump)
- dump_Pw(Pw);
- #endif
-
- /* Determine magnitudes from P(w) ----------------------------------------*/
-
- /* when used just by decoder {A} might be all zeroes so init signal
- and noise to prevent log(0) errors */
-
- signal = 1E-30; noise = 1E-32;
-
- for(m=1; m<=model->L; m++) {
- am = floor((m - 0.5)*model->Wo/r + 0.5);
- bm = floor((m + 0.5)*model->Wo/r + 0.5);
- Em = 0.0;
-
- for(i=am; i<bm; i++)
- Em += Pw[i].real;
- Am = sqrt(Em);
-
- signal += pow(model->A[m],2.0);
- noise += pow(model->A[m] - Am,2.0);
-
- /* This code significantly improves perf of LPC model, in
- particular when combined with phase0. The LPC spectrum tends
- to track just under the peaks of the spectral envelope, and
- just above nulls. This algorithm does the reverse to
- compensate - raising the amplitudes of spectral peaks, while
- attenuating the null. This enhances the formants, and
- supresses the energy between formants. */
-
- if (sim_pf) {
- if (Am > model->A[m])
- Am *= 0.7;
- if (Am < model->A[m])
- Am *= 1.4;
- }
-
- model->A[m] = Am;
- }
- *snr = 10.0*log10(signal/noise);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_Wo()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Encodes Wo using a WO_LEVELS quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-int encode_Wo(float Wo)
-{
- int index;
- float Wo_min = TWO_PI/P_MAX;
- float Wo_max = TWO_PI/P_MIN;
- float norm;
-
- norm = (Wo - Wo_min)/(Wo_max - Wo_min);
- index = floor(WO_LEVELS * norm + 0.5);
- if (index < 0 ) index = 0;
- if (index > (WO_LEVELS-1)) index = WO_LEVELS-1;
-
- return index;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_Wo()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Decodes Wo using a WO_LEVELS quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-float decode_Wo(int index)
-{
- float Wo_min = TWO_PI/P_MAX;
- float Wo_max = TWO_PI/P_MIN;
- float step;
- float Wo;
-
- step = (Wo_max - Wo_min)/WO_LEVELS;
- Wo = Wo_min + step*(index);
-
- return Wo;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_Wo_dt()
- AUTHOR......: David Rowe
- DATE CREATED: 6 Nov 2011
-
- Encodes Wo difference from last frame.
-
-\*---------------------------------------------------------------------------*/
-
-int encode_Wo_dt(float Wo, float prev_Wo)
-{
- int index, mask, max_index, min_index;
- float Wo_min = TWO_PI/P_MAX;
- float Wo_max = TWO_PI/P_MIN;
- float norm;
-
- norm = (Wo - prev_Wo)/(Wo_max - Wo_min);
- index = floor(WO_LEVELS * norm + 0.5);
- //printf("ENC index: %d ", index);
-
- /* hard limit */
-
- max_index = (1 << (WO_DT_BITS-1)) - 1;
- min_index = - (max_index+1);
- if (index > max_index) index = max_index;
- if (index < min_index) index = min_index;
- //printf("max_index: %d min_index: %d hard index: %d ",
- // max_index, min_index, index);
-
- /* mask so that only LSB WO_DT_BITS remain, bit WO_DT_BITS is the sign bit */
-
- mask = ((1 << WO_DT_BITS) - 1);
- index &= mask;
- //printf("mask: 0x%x index: 0x%x\n", mask, index);
-
- return index;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_Wo_dt()
- AUTHOR......: David Rowe
- DATE CREATED: 6 Nov 2011
-
- Decodes Wo using WO_DT_BITS difference from last frame.
-
-\*---------------------------------------------------------------------------*/
-
-float decode_Wo_dt(int index, float prev_Wo)
-{
- float Wo_min = TWO_PI/P_MAX;
- float Wo_max = TWO_PI/P_MIN;
- float step;
- float Wo;
- int mask;
-
- /* sign extend index */
-
- //printf("DEC index: %d ");
- if (index & (1 << (WO_DT_BITS-1))) {
- mask = ~((1 << WO_DT_BITS) - 1);
- index |= mask;
- }
- //printf("DEC mask: 0x%x index: %d \n", mask, index);
-
- step = (Wo_max - Wo_min)/WO_LEVELS;
- Wo = prev_Wo + step*(index);
-
- /* bit errors can make us go out of range leading to all sorts of
- probs like seg faults */
-
- if (Wo > Wo_max) Wo = Wo_max;
- if (Wo < Wo_min) Wo = Wo_min;
-
- return Wo;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: speech_to_uq_lsps()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Analyse a windowed frame of time domain speech to determine LPCs
- which are the converted to LSPs for quantisation and transmission
- over the channel.
-
-\*---------------------------------------------------------------------------*/
-
-float speech_to_uq_lsps(float lsp[],
- float ak[],
- float Sn[],
- float w[],
- int order
-)
-{
- int i, roots;
- float Wn[M];
- float R[LPC_MAX+1];
- float e, E;
-
- e = 0.0;
- for(i=0; i<M; i++) {
- Wn[i] = Sn[i]*w[i];
- e += Wn[i]*Wn[i];
- }
-
- /* trap 0 energy case as LPC analysis will fail */
-
- if (e == 0.0) {
- for(i=0; i<order; i++)
- lsp[i] = (PI/order)*(float)i;
- return 0.0;
- }
-
- autocorrelate(Wn, R, M, order);
- levinson_durbin(R, ak, order);
-
- E = 0.0;
- for(i=0; i<=order; i++)
- E += ak[i]*R[i];
-
- /* 15 Hz BW expansion as I can't hear the difference and it may help
- help occasional fails in the LSP root finding. Important to do this
- after energy calculation to avoid -ve energy values.
- */
-
- for(i=0; i<=order; i++)
- ak[i] *= pow(0.994,(float)i);
-
- roots = lpc_to_lsp(ak, order, lsp, 5, LSP_DELTA1);
- if (roots != order) {
- /* if root finding fails use some benign LSP values instead */
- for(i=0; i<order; i++)
- lsp[i] = (PI/order)*(float)i;
- }
-
- return E;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_lsps_scalar()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Thirty-six bit sclar LSP quantiser. From a vector of unquantised
- (floating point) LSPs finds the quantised LSP indexes.
-
-\*---------------------------------------------------------------------------*/
-
-void encode_lsps_scalar(int indexes[], float lsp[], int order)
-{
- int i,k,m;
- float wt[1];
- float lsp_hz[LPC_MAX];
- const float * cb;
- float se;
-
- /* convert from radians to Hz so we can use human readable
- frequencies */
-
- for(i=0; i<order; i++)
- lsp_hz[i] = (4000.0/PI)*lsp[i];
-
- /* scalar quantisers */
-
- wt[0] = 1.0;
- for(i=0; i<order; i++) {
- k = lsp_cb[i].k;
- m = lsp_cb[i].m;
- cb = lsp_cb[i].cb;
- indexes[i] = quantise(cb, &lsp_hz[i], wt, k, m, &se);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_lsps_scalar()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- From a vector of quantised LSP indexes, returns the quantised
- (floating point) LSPs.
-
-\*---------------------------------------------------------------------------*/
-
-void decode_lsps_scalar(float lsp[], int indexes[], int order)
-{
- int i,k;
- float lsp_hz[LPC_MAX];
- const float * cb;
-
- for(i=0; i<order; i++) {
- k = lsp_cb[i].k;
- cb = lsp_cb[i].cb;
- lsp_hz[i] = cb[indexes[i]*k];
- }
-
- /* convert back to radians */
-
- for(i=0; i<order; i++)
- lsp[i] = (PI/4000.0)*lsp_hz[i];
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_lsps_diff_freq_vq()
- AUTHOR......: David Rowe
- DATE CREATED: 15 November 2011
-
- Twenty-five bit LSP quantiser. LSPs 1-4 are quantised with scalar
- LSP differences (in frequency, i.e difference from the previous
- LSP). LSPs 5-10 are quantised with a VQ trained generated using
- vqtrainjnd.c
-
-\*---------------------------------------------------------------------------*/
-
-void encode_lsps_diff_freq_vq(int indexes[], float lsp[], int order)
-{
- int i,k,m;
- float lsp_hz[LPC_MAX];
- float lsp__hz[LPC_MAX];
- float dlsp[LPC_MAX];
- float dlsp_[LPC_MAX];
- float wt[LPC_MAX];
- const float * cb;
- float se;
-
- for(i=0; i<LPC_ORD; i++) {
- wt[i] = 1.0;
- }
-
- /* convert from radians to Hz so we can use human readable
- frequencies */
-
- for(i=0; i<order; i++)
- lsp_hz[i] = (4000.0/PI)*lsp[i];
-
- /* scalar quantisers for LSP differences 1..4 */
-
- wt[0] = 1.0;
- for(i=0; i<4; i++) {
- if (i)
- dlsp[i] = lsp_hz[i] - lsp__hz[i-1];
- else
- dlsp[0] = lsp_hz[0];
-
- k = lsp_cbd[i].k;
- m = lsp_cbd[i].m;
- cb = lsp_cbd[i].cb;
- indexes[i] = quantise(cb, &dlsp[i], wt, k, m, &se);
- dlsp_[i] = cb[indexes[i]*k];
-
- if (i)
- lsp__hz[i] = lsp__hz[i-1] + dlsp_[i];
- else
- lsp__hz[0] = dlsp_[0];
- }
-
- /* VQ LSPs 5,6,7,8,9,10 */
-
- k = lsp_cbjnd[4].k;
- m = lsp_cbjnd[4].m;
- cb = lsp_cbjnd[4].cb;
- indexes[4] = quantise(cb, &lsp_hz[4], &wt[4], k, m, &se);
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_lsps_diff_freq_vq()
- AUTHOR......: David Rowe
- DATE CREATED: 15 Nov 2011
-
- From a vector of quantised LSP indexes, returns the quantised
- (floating point) LSPs.
-
-\*---------------------------------------------------------------------------*/
-
-void decode_lsps_diff_freq_vq(float lsp_[], int indexes[], int order)
-{
- int i,k,m;
- float dlsp_[LPC_MAX];
- float lsp__hz[LPC_MAX];
- const float * cb;
-
- /* scalar LSP differences */
-
- for(i=0; i<4; i++) {
- cb = lsp_cbd[i].cb;
- dlsp_[i] = cb[indexes[i]];
- if (i)
- lsp__hz[i] = lsp__hz[i-1] + dlsp_[i];
- else
- lsp__hz[0] = dlsp_[0];
- }
-
- /* VQ */
-
- k = lsp_cbjnd[4].k;
- m = lsp_cbjnd[4].m;
- cb = lsp_cbjnd[4].cb;
- for(i=4; i<order; i++)
- lsp__hz[i] = cb[indexes[4]*k+i-4];
-
- /* convert back to radians */
-
- for(i=0; i<order; i++)
- lsp_[i] = (PI/4000.0)*lsp__hz[i];
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_lsps_diff_time()
- AUTHOR......: David Rowe
- DATE CREATED: 12 Sep 2012
-
- Encode difference from preious frames's LSPs using
- 3,3,2,2,2,2,1,1,1,1 scalar quantisers (18 bits total).
-
-\*---------------------------------------------------------------------------*/
-
-void encode_lsps_diff_time(int indexes[],
- float lsps[],
- float lsps__prev[],
- int order)
-{
- int i,k,m;
- float lsps_dt[LPC_ORD];
- float wt[LPC_MAX];
- const float * cb;
- float se;
-
- /* Determine difference in time and convert from radians to Hz so
- we can use human readable frequencies */
-
- for(i=0; i<LPC_ORD; i++) {
- lsps_dt[i] = (4000/PI)*(lsps[i] - lsps__prev[i]);
- }
-
- /* scalar quantisers */
-
- wt[0] = 1.0;
- for(i=0; i<order; i++) {
- k = lsp_cbdt[i].k;
- m = lsp_cbdt[i].m;
- cb = lsp_cbdt[i].cb;
- indexes[i] = quantise(cb, &lsps_dt[i], wt, k, m, &se);
- }
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_lsps_diff_time()
- AUTHOR......: David Rowe
- DATE CREATED: 15 Nov 2011
-
- From a quantised LSP indexes, returns the quantised
- (floating point) LSPs.
-
-\*---------------------------------------------------------------------------*/
-
-void decode_lsps_diff_time(
- float lsps_[],
- int indexes[],
- float lsps__prev[],
- int order)
-{
- int i,k,m;
- const float * cb;
-
- for(i=0; i<order; i++)
- lsps_[i] = lsps__prev[i];
-
- for(i=0; i<order; i++) {
- k = lsp_cbdt[i].k;
- cb = lsp_cbdt[i].cb;
- lsps_[i] += (PI/4000.0)*cb[indexes[i]*k];
- }
-
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_lsps_vq()
- AUTHOR......: David Rowe
- DATE CREATED: 15 Feb 2012
-
- Multi-stage VQ LSP quantiser developed by Jean-Marc Valin.
-
-\*---------------------------------------------------------------------------*/
-
-void encode_lsps_vq(int *indexes, float *x, float *xq, int ndim)
-{
- int i, n1, n2, n3;
- float err[LPC_ORD], err2[LPC_ORD], err3[LPC_ORD];
- float w[LPC_ORD], w2[LPC_ORD], w3[LPC_ORD];
- const float *codebook1 = lsp_cbjvm[0].cb;
- const float *codebook2 = lsp_cbjvm[1].cb;
- const float *codebook3 = lsp_cbjvm[2].cb;
-
- assert(ndim <= LPC_ORD);
-
- w[0] = MIN(x[0], x[1]-x[0]);
- for (i=1;i<ndim-1;i++)
- w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
- w[ndim-1] = MIN(x[ndim-1]-x[ndim-2], PI-x[ndim-1]);
-
- compute_weights(x, w, ndim);
-
- n1 = find_nearest(codebook1, lsp_cbjvm[0].m, x, ndim);
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = codebook1[ndim*n1+i];
- err[i] = x[i] - xq[i];
- }
- for (i=0;i<ndim/2;i++)
- {
- err2[i] = err[2*i];
- err3[i] = err[2*i+1];
- w2[i] = w[2*i];
- w3[i] = w[2*i+1];
- }
- n2 = find_nearest_weighted(codebook2, lsp_cbjvm[1].m, err2, w2, ndim/2);
- n3 = find_nearest_weighted(codebook3, lsp_cbjvm[2].m, err3, w3, ndim/2);
-
- indexes[0] = n1;
- indexes[1] = n2;
- indexes[2] = n3;
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_lsps_vq()
- AUTHOR......: David Rowe
- DATE CREATED: 15 Feb 2012
-
-\*---------------------------------------------------------------------------*/
-
-void decode_lsps_vq(int *indexes, float *xq, int ndim)
-{
- int i, n1, n2, n3;
- const float *codebook1 = lsp_cbjvm[0].cb;
- const float *codebook2 = lsp_cbjvm[1].cb;
- const float *codebook3 = lsp_cbjvm[2].cb;
-
- n1 = indexes[0];
- n2 = indexes[1];
- n3 = indexes[2];
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = codebook1[ndim*n1+i];
- }
- for (i=0;i<ndim/2;i++)
- {
- xq[2*i] += codebook2[ndim*n2/2+i];
- xq[2*i+1] += codebook3[ndim*n3/2+i];
- }
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: bw_expand_lsps()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Applies Bandwidth Expansion (BW) to a vector of LSPs. Prevents any
- two LSPs getting too close together after quantisation. We know
- from experiment that LSP quantisation errors < 12.5Hz (25Hz step
- size) are inaudible so we use that as the minimum LSP separation.
-
-\*---------------------------------------------------------------------------*/
-
-void bw_expand_lsps(float lsp[],
- int order
-)
-{
- int i;
-
- for(i=1; i<4; i++) {
-
- if ((lsp[i] - lsp[i-1]) < 50*(PI/4000.0))
- lsp[i] = lsp[i-1] + 50.0*(PI/4000.0);
-
- }
-
- /* As quantiser gaps increased, larger BW expansion was required
- to prevent twinkly noises. This may need more experiment for
- different quanstisers.
- */
-
- for(i=4; i<order; i++) {
- if (lsp[i] - lsp[i-1] < PI*(100.0/4000.0))
- lsp[i] = lsp[i-1] + PI*(100.0/4000.0);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: locate_lsps_jnd_steps()
- AUTHOR......: David Rowe
- DATE CREATED: 27/10/2011
-
- Applies a form of Bandwidth Expansion (BW) to a vector of LSPs.
- Listening tests have determined that "quantising" the position of
- each LSP to the non-linear steps below introduces a "just noticable
- difference" in the synthesised speech.
-
- This operation can be used before quantisation to limit the input
- data to the quantiser to a number of discrete steps.
-
- This operation can also be used during quantisation as a form of
- hysteresis in the calculation of quantiser error. For example if
- the quantiser target of lsp1 is 500 Hz, candidate vectors with lsp1
- of 515 and 495 Hz sound effectively the same.
-
-\*---------------------------------------------------------------------------*/
-
-void locate_lsps_jnd_steps(float lsps[], int order)
-{
- int i;
- float lsp_hz, step;
-
- assert(order == 10);
-
- /* quantise to 25Hz steps */
-
- step = 25;
- for(i=0; i<2; i++) {
- lsp_hz = lsps[i]*4000.0/PI;
- lsp_hz = floor(lsp_hz/step + 0.5)*step;
- lsps[i] = lsp_hz*PI/4000.0;
- if (i) {
- if (lsps[i] == lsps[i-1])
- lsps[i] += step*PI/4000.0;
-
- }
- }
-
- /* quantise to 50Hz steps */
-
- step = 50;
- for(i=2; i<4; i++) {
- lsp_hz = lsps[i]*4000.0/PI;
- lsp_hz = floor(lsp_hz/step + 0.5)*step;
- lsps[i] = lsp_hz*PI/4000.0;
- if (i) {
- if (lsps[i] == lsps[i-1])
- lsps[i] += step*PI/4000.0;
-
- }
- }
-
- /* quantise to 100Hz steps */
-
- step = 100;
- for(i=4; i<10; i++) {
- lsp_hz = lsps[i]*4000.0/PI;
- lsp_hz = floor(lsp_hz/step + 0.5)*step;
- lsps[i] = lsp_hz*PI/4000.0;
- if (i) {
- if (lsps[i] == lsps[i-1])
- lsps[i] += step*PI/4000.0;
-
- }
- }
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: apply_lpc_correction()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Apply first harmonic LPC correction at decoder. This helps improve
- low pitch males after LPC modelling, like hts1a and morig.
-
-\*---------------------------------------------------------------------------*/
-
-void apply_lpc_correction(MODEL *model)
-{
- if (model->Wo < (PI*150.0/4000)) {
- model->A[1] *= 0.032;
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_energy()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Encodes LPC energy using an E_LEVELS quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-int encode_energy(float e)
-{
- int index;
- float e_min = E_MIN_DB;
- float e_max = E_MAX_DB;
- float norm;
-
- e = 10.0*log10(e);
- norm = (e - e_min)/(e_max - e_min);
- index = floor(E_LEVELS * norm + 0.5);
- if (index < 0 ) index = 0;
- if (index > (E_LEVELS-1)) index = E_LEVELS-1;
-
- return index;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_energy()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Decodes energy using a E_LEVELS quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-float decode_energy(int index)
-{
- float e_min = E_MIN_DB;
- float e_max = E_MAX_DB;
- float step;
- float e;
-
- step = (e_max - e_min)/E_LEVELS;
- e = e_min + step*(index);
- e = pow(10.0,e/10.0);
-
- return e;
-}
-
-#ifdef NOT_USED
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_amplitudes()
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/2010
-
- Given the amplitude quantiser indexes recovers the harmonic
- amplitudes.
-
-\*---------------------------------------------------------------------------*/
-
-float decode_amplitudes(kiss_fft_cfg fft_fwd_cfg,
- MODEL *model,
- float ak[],
- int lsp_indexes[],
- int energy_index,
- float lsps[],
- float *e
-)
-{
- float snr;
-
- decode_lsps_scalar(lsps, lsp_indexes, LPC_ORD);
- bw_expand_lsps(lsps, LPC_ORD);
- lsp_to_lpc(lsps, ak, LPC_ORD);
- *e = decode_energy(energy_index);
- aks_to_M2(ak, LPC_ORD, model, *e, &snr, 1, 0, 0, 1);
- apply_lpc_correction(model);
-
- return snr;
-}
-#endif
-
-static float ge_coeff[2] = {0.8, 0.9};
-
-void compute_weights2(const float *x, const float *xp, float *w, int ndim)
-{
- w[0] = 30;
- w[1] = 1;
- if (x[1]<0)
- {
- w[0] *= .6;
- w[1] *= .3;
- }
- if (x[1]<-10)
- {
- w[0] *= .3;
- w[1] *= .3;
- }
- /* Higher weight if pitch is stable */
- if (fabs(x[0]-xp[0])<.2)
- {
- w[0] *= 2;
- w[1] *= 1.5;
- } else if (fabs(x[0]-xp[0])>.5) /* Lower if not stable */
- {
- w[0] *= .5;
- }
-
- /* Lower weight for low energy */
- if (x[1] < xp[1]-10)
- {
- w[1] *= .5;
- }
- if (x[1] < xp[1]-20)
- {
- w[1] *= .5;
- }
-
- //w[0] = 30;
- //w[1] = 1;
-
- /* Square the weights because it's applied on the squared error */
- w[0] *= w[0];
- w[1] *= w[1];
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: quantise_WoE()
- AUTHOR......: Jean-Marc Valin & David Rowe
- DATE CREATED: 29 Feb 2012
-
- Experimental joint Wo and LPC energy vector quantiser developed by
- Jean-Marc Valin. Exploits correlations between the difference in
- the log pitch and log energy from frame to frame. For example
- both the pitch and energy tend to only change by small amounts
- during voiced speech, however it is important that these changes be
- coded carefully. During unvoiced speech they both change a lot but
- the ear is less sensitve to errors so coarser quantisation is OK.
-
- The ear is sensitive to log energy and loq pitch so we quantise in
- these domains. That way the error measure used to quantise the
- values is close to way the ear senses errors.
-
- See http://jmspeex.livejournal.com/10446.html
-
-\*---------------------------------------------------------------------------*/
-
-void quantise_WoE(MODEL *model, float *e, float xq[])
-{
- int i, n1;
- float x[2];
- float err[2];
- float w[2];
- const float *codebook1 = ge_cb[0].cb;
- int nb_entries = ge_cb[0].m;
- int ndim = ge_cb[0].k;
- float Wo_min = TWO_PI/P_MAX;
- float Wo_max = TWO_PI/P_MIN;
-
- x[0] = log10((model->Wo/PI)*4000.0/50.0)/log10(2);
- x[1] = 10.0*log10(1e-4 + *e);
-
- compute_weights2(x, xq, w, ndim);
- for (i=0;i<ndim;i++)
- err[i] = x[i]-ge_coeff[i]*xq[i];
- n1 = find_nearest_weighted(codebook1, nb_entries, err, w, ndim);
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = ge_coeff[i]*xq[i] + codebook1[ndim*n1+i];
- err[i] -= codebook1[ndim*n1+i];
- }
-
- /*
- x = log2(4000*Wo/(PI*50));
- 2^x = 4000*Wo/(PI*50)
- Wo = (2^x)*(PI*50)/4000;
- */
-
- model->Wo = pow(2.0, xq[0])*(PI*50.0)/4000.0;
-
- /* bit errors can make us go out of range leading to all sorts of
- probs like seg faults */
-
- if (model->Wo > Wo_max) model->Wo = Wo_max;
- if (model->Wo < Wo_min) model->Wo = Wo_min;
-
- model->L = PI/model->Wo; /* if we quantise Wo re-compute L */
-
- *e = pow(10.0, xq[1]/10.0);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: encode_WoE()
- AUTHOR......: Jean-Marc Valin & David Rowe
- DATE CREATED: 11 May 2012
-
- Joint Wo and LPC energy vector quantiser developed my Jean-Marc
- Valin. Returns index, and updated states xq[].
-
-\*---------------------------------------------------------------------------*/
-
-int encode_WoE(MODEL *model, float e, float xq[])
-{
- int i, n1;
- float x[2];
- float err[2];
- float w[2];
- const float *codebook1 = ge_cb[0].cb;
- int nb_entries = ge_cb[0].m;
- int ndim = ge_cb[0].k;
-
- assert((1<<WO_E_BITS) == nb_entries);
-
- if (e < 0.0) e = 0; /* occasional small negative energies due LPC round off I guess */
-
- x[0] = log10((model->Wo/PI)*4000.0/50.0)/log10(2);
- x[1] = 10.0*log10(1e-4 + e);
-
- compute_weights2(x, xq, w, ndim);
- for (i=0;i<ndim;i++)
- err[i] = x[i]-ge_coeff[i]*xq[i];
- n1 = find_nearest_weighted(codebook1, nb_entries, err, w, ndim);
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = ge_coeff[i]*xq[i] + codebook1[ndim*n1+i];
- err[i] -= codebook1[ndim*n1+i];
- }
-
- //printf("enc: %f %f (%f)(%f) \n", xq[0], xq[1], e, 10.0*log10(1e-4 + e));
- return n1;
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: decode_WoE()
- AUTHOR......: Jean-Marc Valin & David Rowe
- DATE CREATED: 11 May 2012
-
- Joint Wo and LPC energy vector quantiser developed my Jean-Marc
- Valin. Given index and states xq[], returns Wo & E, and updates
- states xq[].
-
-\*---------------------------------------------------------------------------*/
-
-void decode_WoE(MODEL *model, float *e, float xq[], int n1)
-{
- int i;
- float err[2];
- const float *codebook1 = ge_cb[0].cb;
- int ndim = ge_cb[0].k;
- float Wo_min = TWO_PI/P_MAX;
- float Wo_max = TWO_PI/P_MIN;
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = ge_coeff[i]*xq[i] + codebook1[ndim*n1+i];
- err[i] -= codebook1[ndim*n1+i];
- }
-
- //printf("dec: %f %f\n", xq[0], xq[1]);
- model->Wo = pow(2.0, xq[0])*(PI*50.0)/4000.0;
-
- /* bit errors can make us go out of range leading to all sorts of
- probs like seg faults */
-
- if (model->Wo > Wo_max) model->Wo = Wo_max;
- if (model->Wo < Wo_min) model->Wo = Wo_min;
-
- model->L = PI/model->Wo; /* if we quantise Wo re-compute L */
-
- *e = pow(10.0, xq[1]/10.0);
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: quantise.h
- AUTHOR......: David Rowe
- DATE CREATED: 31/5/92
-
- Quantisation functions for the sinusoidal coder.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __QUANTISE__
-#define __QUANTISE__
-
-#include "kiss_fft.h"
-
-#define WO_BITS 7
-#define WO_LEVELS (1<<WO_BITS)
-#define WO_DT_BITS 3
-
-#define E_BITS 5
-#define E_LEVELS (1<<E_BITS)
-#define E_MIN_DB -10.0
-#define E_MAX_DB 40.0
-
-#define LSP_SCALAR_INDEXES 10
-#define LSPD_SCALAR_INDEXES 10
-#define LSP_PRED_VQ_INDEXES 3
-#define LSP_DIFF_FREQ_INDEXES 5
-#define LSP_DIFF_TIME_BITS 7
-
-#define LSPDT_ALL 0
-#define LSPDT_LOW 1
-#define LSPDT_HIGH 2
-
-#define WO_E_BITS 8
-
-#define LPCPF_GAMMA 0.5
-#define LPCPF_BETA 0.2
-
-void quantise_init();
-float lpc_model_amplitudes(float Sn[], float w[], MODEL *model, int order,
- int lsp,float ak[]);
-void aks_to_M2(kiss_fft_cfg fft_fwd_cfg, float ak[], int order, MODEL *model,
- float E, float *snr, int dump, int sim_pf,
- int pf, int bass_boost, float beta, float gamma);
-
-int encode_Wo(float Wo);
-float decode_Wo(int index);
-int encode_Wo_dt(float Wo, float prev_Wo);
-float decode_Wo_dt(int index, float prev_Wo);
-void encode_lsps_scalar(int indexes[], float lsp[], int order);
-void decode_lsps_scalar(float lsp[], int indexes[], int order);
-void encode_lspds_scalar(int indexes[], float lsp[], int order);
-void decode_lspds_scalar(float lsp[], int indexes[], int order);
-void encode_lsps_diff_freq_vq(int indexes[], float lsp[], int order);
-void decode_lsps_diff_freq_vq(float lsp_[], int indexes[], int order);
-void encode_lsps_diff_time(int indexes[],
- float lsp[],
- float lsp__prev[],
- int order);
-void decode_lsps_diff_time(float lsp_[],
- int indexes[],
- float lsp__prev[],
- int order);
-
-void encode_lsps_vq(int *indexes, float *x, float *xq, int ndim);
-void decode_lsps_vq(int *indexes, float *xq, int ndim);
-
-long quantise(const float * cb, float vec[], float w[], int k, int m, float *se);
-void lspvq_quantise(float lsp[], float lsp_[], int order);
-void lspjnd_quantise(float lsp[], float lsp_[], int order);
-void lspdt_quantise(float lsps[], float lsps_[], float lsps__prev[], int mode);
-void lspjvm_quantise(float lsps[], float lsps_[], int order);
-void lspanssi_quantise(float lsps[], float lsps_[], int order, int mbest_entries);
-
-void quantise_WoE(MODEL *model, float *e, float xq[]);
-int encode_WoE(MODEL *model, float e, float xq[]);
-void decode_WoE(MODEL *model, float *e, float xq[], int n1);
-
-int encode_energy(float e);
-float decode_energy(int index);
-
-void pack(unsigned char * bits, unsigned int *nbit, int index, unsigned int index_bits);
-int unpack(const unsigned char * bits, unsigned int *nbit, unsigned int index_bits);
-
-int lsp_bits(int i);
-int lspd_bits(int i);
-int lspdt_bits(int i);
-int lsp_pred_vq_bits(int i);
-
-void apply_lpc_correction(MODEL *model);
-float speech_to_uq_lsps(float lsp[],
- float ak[],
- float Sn[],
- float w[],
- int order
- );
-int check_lsp_order(float lsp[], int lpc_order);
-void bw_expand_lsps(float lsp[], int order);
-void locate_lsps_jnd_steps(float lsp[], int order);
-float decode_amplitudes(MODEL *model,
- float ak[],
- int lsp_indexes[],
- int energy_index,
- float lsps[],
- float *e);
-
-#endif
+++ /dev/null
-/* Generated by rn_file() Octave function */
-
-const float gt_alpha5_root[]={
- 2.86997e-05,
- 2.2286e-05,
- 1.82863e-05,
- 1.42303e-05,
- 1.04905e-05,
- 6.70859e-06,
- 3.05918e-06,
- -6.22187e-07,
- -4.22748e-06,
- -7.85603e-06,
- -1.14317e-05,
- -1.50227e-05,
- -1.85712e-05,
- -2.21275e-05,
- -2.56455e-05,
- -2.91642e-05,
- -3.26453e-05,
- -3.61199e-05,
- -3.95556e-05,
- -4.29778e-05,
- -4.63581e-05,
- -4.97179e-05,
- -5.3032e-05,
- -5.63184e-05,
- -5.95548e-05,
- -6.27565e-05,
- -6.59032e-05,
- -6.90085e-05,
- -7.20538e-05,
- -7.50509e-05,
- -7.7983e-05,
- -8.08605e-05,
- -8.36678e-05,
- -8.64141e-05,
- -8.9085e-05,
- -9.16888e-05,
- -9.42119e-05,
- -9.66619e-05,
- -9.9026e-05,
- -0.000101311,
- -0.000103505,
- -0.000105614,
- -0.000107627,
- -0.00010955,
- -0.000111372,
- -0.000113099,
- -0.00011472,
- -0.000116241,
- -0.000117652,
- -0.000118959,
- -0.000120152,
- -0.000121235,
- -0.000122201,
- -0.000123053,
- -0.000123784,
- -0.000124397,
- -0.000124884,
- -0.00012525,
- -0.000125487,
- -0.000125598,
- -0.000125578,
- -0.000125428,
- -0.000125145,
- -0.000124729,
- -0.000124185,
- -0.000123518,
- -0.000122709,
- -0.000121766,
- -0.000120685,
- -0.000119471,
- -0.000118119,
- -0.000116633,
- -0.000115009,
- -0.000113251,
- -0.000111356,
- -0.000109326,
- -0.00010716,
- -0.00010486,
- -0.000102424,
- -9.98553e-05,
- -9.71528e-05,
- -9.43199e-05,
- -9.13551e-05,
- -8.82623e-05,
- -8.50404e-05,
- -8.16936e-05,
- -7.82211e-05,
- -7.46271e-05,
- -7.09109e-05,
- -6.70773e-05,
- -6.31256e-05,
- -5.90607e-05,
- -5.48823e-05,
- -5.05954e-05,
- -4.62001e-05,
- -4.17016e-05,
- -3.71002e-05,
- -3.24015e-05,
- -2.7606e-05,
- -2.27195e-05,
- -1.77428e-05,
- -1.2682e-05,
- -7.53795e-06,
- -2.31702e-06,
- 2.97965e-06,
- 8.34567e-06,
- 1.37796e-05,
- 1.9275e-05,
- 2.483e-05,
- 3.04382e-05,
- 3.60975e-05,
- 4.18011e-05,
- 4.75467e-05,
- 5.33273e-05,
- 5.91403e-05,
- 6.49787e-05,
- 7.08393e-05,
- 7.67152e-05,
- 8.26029e-05,
- 8.84957e-05,
- 9.43895e-05,
- 0.000100278,
- 0.000106157,
- 0.00011202,
- 0.000117864,
- 0.000123681,
- 0.000129468,
- 0.000135218,
- 0.000140929,
- 0.000146583,
- 0.000152183,
- 0.000157725,
- 0.000163202,
- 0.000168608,
- 0.000173938,
- 0.000179183,
- 0.00018434,
- 0.0001894,
- 0.00019436,
- 0.000199211,
- 0.000203949,
- 0.000208568,
- 0.000213063,
- 0.000217426,
- 0.000221654,
- 0.00022574,
- 0.000229678,
- 0.000233463,
- 0.000237089,
- 0.000240551,
- 0.000243843,
- 0.000246959,
- 0.000249895,
- 0.000252644,
- 0.000255202,
- 0.000257562,
- 0.000259721,
- 0.000261672,
- 0.000263411,
- 0.000264933,
- 0.000266234,
- 0.000267308,
- 0.000268152,
- 0.00026876,
- 0.000269128,
- 0.000269253,
- 0.000269129,
- 0.000268754,
- 0.000268123,
- 0.000267232,
- 0.000266079,
- 0.000264658,
- 0.000262968,
- 0.000261006,
- 0.000258767,
- 0.000256251,
- 0.000253453,
- 0.000250373,
- 0.000247007,
- 0.000243354,
- 0.000239412,
- 0.00023518,
- 0.000230655,
- 0.000225837,
- 0.000220723,
- 0.000215314,
- 0.000209608,
- 0.000203605,
- 0.000197304,
- 0.000190706,
- 0.000183812,
- 0.000176621,
- 0.000169145,
- 0.000161363,
- 0.000153275,
- 0.000144895,
- 0.000136224,
- 0.000127266,
- 0.00011802,
- 0.000108491,
- 9.8679e-05,
- 8.85877e-05,
- 7.82196e-05,
- 6.7577e-05,
- 5.66636e-05,
- 4.54822e-05,
- 3.40369e-05,
- 2.23311e-05,
- 1.03695e-05,
- -1.844e-06,
- -1.43041e-05,
- -2.70061e-05,
- -3.99444e-05,
- -5.31139e-05,
- -6.65082e-05,
- -8.01218e-05,
- -9.39481e-05,
- -0.000107981,
- -0.000122213,
- -0.000136638,
- -0.000151248,
- -0.000166036,
- -0.000180995,
- -0.000196115,
- -0.00021139,
- -0.000226811,
- -0.000242369,
- -0.000258056,
- -0.000273861,
- -0.000289776,
- -0.000305792,
- -0.000321898,
- -0.000338084,
- -0.000354342,
- -0.00037066,
- -0.000387027,
- -0.000403434,
- -0.00041987,
- -0.000436324,
- -0.000452784,
- -0.00046924,
- -0.00048568,
- -0.000502091,
- -0.000518464,
- -0.000534785,
- -0.000551043,
- -0.000567225,
- -0.000583319,
- -0.000599314,
- -0.000615196,
- -0.000630955,
- -0.000646575,
- -0.000662049,
- -0.000677361,
- -0.000692506,
- -0.000707464,
- -0.00072229,
- -0.000736922,
- -0.000751266,
- -0.000765372,
- -0.000779217,
- -0.000792798,
- -0.000806094,
- -0.000819098,
- -0.000831793,
- -0.000844168,
- -0.000856207,
- -0.000867898,
- -0.000879227,
- -0.00089018,
- -0.000900744,
- -0.000910906,
- -0.000920652,
- -0.00092997,
- -0.000938844,
- -0.000947263,
- -0.000955214,
- -0.000962682,
- -0.000969654,
- -0.000976119,
- -0.000982062,
- -0.00098747,
- -0.000992332,
- -0.000996634,
- -0.00100036,
- -0.00100351,
- -0.00100606,
- -0.001008,
- -0.00100932,
- -0.00101,
- -0.00101005,
- -0.00100943,
- -0.00100816,
- -0.0010062,
- -0.00100356,
- -0.00100021,
- -0.000996162,
- -0.000991392,
- -0.000985892,
- -0.000979654,
- -0.000972668,
- -0.000964925,
- -0.000956415,
- -0.000947131,
- -0.000937065,
- -0.000926208,
- -0.000914552,
- -0.00090209,
- -0.000888816,
- -0.000874721,
- -0.0008598,
- -0.000844046,
- -0.000827453,
- -0.000810015,
- -0.000791726,
- -0.000772581,
- -0.000752576,
- -0.000731704,
- -0.000709965,
- -0.00068735,
- -0.000663865,
- -0.000639509,
- -0.000614269,
- -0.000588146,
- -0.000561139,
- -0.000533246,
- -0.000504468,
- -0.000474802,
- -0.000444251,
- -0.000412813,
- -0.00038049,
- -0.000347281,
- -0.000313189,
- -0.000278215,
- -0.000242361,
- -0.000205629,
- -0.000168024,
- -0.000129546,
- -9.02024e-05,
- -4.99954e-05,
- -8.93026e-06,
- 3.2988e-05,
- 7.57537e-05,
- 0.000119361,
- 0.000163804,
- 0.000209075,
- 0.000255167,
- 0.000302074,
- 0.000349786,
- 0.000398297,
- 0.000447596,
- 0.000497676,
- 0.000548526,
- 0.000600136,
- 0.000652497,
- 0.000705598,
- 0.000759427,
- 0.000813972,
- 0.000869223,
- 0.000925166,
- 0.000981789,
- 0.00103908,
- 0.00109702,
- 0.00115561,
- 0.00121482,
- 0.00127464,
- 0.00133505,
- 0.00139605,
- 0.00145762,
- 0.00151973,
- 0.00158238,
- 0.00164555,
- 0.00170922,
- 0.00177337,
- 0.00183799,
- 0.00190305,
- 0.00196854,
- 0.00203445,
- 0.00210075,
- 0.00216742,
- 0.00223445,
- 0.00230181,
- 0.00236949,
- 0.00243747,
- 0.00250572,
- 0.00257423,
- 0.00264296,
- 0.00271192,
- 0.00278107,
- 0.00285039,
- 0.00291986,
- 0.00298947,
- 0.00305918,
- 0.00312898,
- 0.00319884,
- 0.00326874,
- 0.00333866,
- 0.00340857,
- 0.00347846,
- 0.00354831,
- 0.00361808,
- 0.00368775,
- 0.00375731,
- 0.00382673,
- 0.00389599,
- 0.00396506,
- 0.00403393,
- 0.00410256,
- 0.00417094,
- 0.00423904,
- 0.00430684,
- 0.00437431,
- 0.00444144,
- 0.0045082,
- 0.00457457,
- 0.00464052,
- 0.00470603,
- 0.00477108,
- 0.00483565,
- 0.00489972,
- 0.00496325,
- 0.00502623,
- 0.00508865,
- 0.00515046,
- 0.00521166,
- 0.00527223,
- 0.00533213,
- 0.00539135,
- 0.00544987,
- 0.00550766,
- 0.00556472,
- 0.005621,
- 0.00567651,
- 0.00573121,
- 0.00578508,
- 0.00583811,
- 0.00589028,
- 0.00594157,
- 0.00599196,
- 0.00604143,
- 0.00608996,
- 0.00613754,
- 0.00618415,
- 0.00622977,
- 0.00627439,
- 0.00631798,
- 0.00636054,
- 0.00640204,
- 0.0064425,
- 0.00648186,
- 0.00652009,
- 0.00655722,
- 0.00659322,
- 0.00662808,
- 0.00666179,
- 0.00669433,
- 0.00672571,
- 0.00675589,
- 0.00678488,
- 0.00681266,
- 0.00683921,
- 0.00686454,
- 0.00688863,
- 0.00691147,
- 0.00693305,
- 0.00695336,
- 0.0069724,
- 0.00699016,
- 0.00700663,
- 0.00702181,
- 0.00703569,
- 0.00704826,
- 0.00705952,
- 0.00706947,
- 0.00707809,
- 0.0070854,
- 0.00709138,
- 0.00709604,
- 0.00709937,
- 0.00710136,
- 0.00710203,
- 0.00710136,
- 0.00709937,
- 0.00709604,
- 0.00709138,
- 0.0070854,
- 0.00707809,
- 0.00706947,
- 0.00705952,
- 0.00704826,
- 0.00703569,
- 0.00702181,
- 0.00700663,
- 0.00699016,
- 0.0069724,
- 0.00695336,
- 0.00693305,
- 0.00691147,
- 0.00688863,
- 0.00686454,
- 0.00683921,
- 0.00681266,
- 0.00678488,
- 0.00675589,
- 0.00672571,
- 0.00669433,
- 0.00666179,
- 0.00662808,
- 0.00659322,
- 0.00655722,
- 0.00652009,
- 0.00648186,
- 0.0064425,
- 0.00640204,
- 0.00636054,
- 0.00631798,
- 0.00627439,
- 0.00622977,
- 0.00618415,
- 0.00613754,
- 0.00608996,
- 0.00604143,
- 0.00599196,
- 0.00594157,
- 0.00589028,
- 0.00583811,
- 0.00578508,
- 0.00573121,
- 0.00567651,
- 0.005621,
- 0.00556472,
- 0.00550766,
- 0.00544987,
- 0.00539135,
- 0.00533213,
- 0.00527223,
- 0.00521166,
- 0.00515046,
- 0.00508865,
- 0.00502623,
- 0.00496325,
- 0.00489972,
- 0.00483565,
- 0.00477108,
- 0.00470603,
- 0.00464052,
- 0.00457457,
- 0.0045082,
- 0.00444144,
- 0.00437431,
- 0.00430684,
- 0.00423904,
- 0.00417094,
- 0.00410256,
- 0.00403393,
- 0.00396506,
- 0.00389599,
- 0.00382673,
- 0.00375731,
- 0.00368775,
- 0.00361808,
- 0.00354831,
- 0.00347846,
- 0.00340857,
- 0.00333866,
- 0.00326874,
- 0.00319884,
- 0.00312898,
- 0.00305918,
- 0.00298947,
- 0.00291986,
- 0.00285039,
- 0.00278107,
- 0.00271192,
- 0.00264296,
- 0.00257423,
- 0.00250572,
- 0.00243747,
- 0.00236949,
- 0.00230181,
- 0.00223445,
- 0.00216742,
- 0.00210075,
- 0.00203445,
- 0.00196854,
- 0.00190305,
- 0.00183799,
- 0.00177337,
- 0.00170922,
- 0.00164555,
- 0.00158238,
- 0.00151973,
- 0.00145762,
- 0.00139605,
- 0.00133505,
- 0.00127464,
- 0.00121482,
- 0.00115561,
- 0.00109702,
- 0.00103908,
- 0.000981789,
- 0.000925166,
- 0.000869223,
- 0.000813972,
- 0.000759427,
- 0.000705598,
- 0.000652497,
- 0.000600136,
- 0.000548526,
- 0.000497676,
- 0.000447596,
- 0.000398297,
- 0.000349786,
- 0.000302074,
- 0.000255167,
- 0.000209075,
- 0.000163804,
- 0.000119361,
- 7.57537e-05,
- 3.2988e-05,
- -8.93026e-06,
- -4.99954e-05,
- -9.02024e-05,
- -0.000129546,
- -0.000168024,
- -0.000205629,
- -0.000242361,
- -0.000278215,
- -0.000313189,
- -0.000347281,
- -0.00038049,
- -0.000412813,
- -0.000444251,
- -0.000474802,
- -0.000504468,
- -0.000533246,
- -0.000561139,
- -0.000588146,
- -0.000614269,
- -0.000639509,
- -0.000663865,
- -0.00068735,
- -0.000709965,
- -0.000731704,
- -0.000752576,
- -0.000772581,
- -0.000791726,
- -0.000810015,
- -0.000827453,
- -0.000844046,
- -0.0008598,
- -0.000874721,
- -0.000888816,
- -0.00090209,
- -0.000914552,
- -0.000926208,
- -0.000937065,
- -0.000947131,
- -0.000956415,
- -0.000964925,
- -0.000972668,
- -0.000979654,
- -0.000985892,
- -0.000991392,
- -0.000996162,
- -0.00100021,
- -0.00100356,
- -0.0010062,
- -0.00100816,
- -0.00100943,
- -0.00101005,
- -0.00101,
- -0.00100932,
- -0.001008,
- -0.00100606,
- -0.00100351,
- -0.00100036,
- -0.000996634,
- -0.000992332,
- -0.00098747,
- -0.000982062,
- -0.000976119,
- -0.000969654,
- -0.000962682,
- -0.000955214,
- -0.000947263,
- -0.000938844,
- -0.00092997,
- -0.000920652,
- -0.000910906,
- -0.000900744,
- -0.00089018,
- -0.000879227,
- -0.000867898,
- -0.000856207,
- -0.000844168,
- -0.000831793,
- -0.000819098,
- -0.000806094,
- -0.000792798,
- -0.000779217,
- -0.000765372,
- -0.000751266,
- -0.000736922,
- -0.00072229,
- -0.000707464,
- -0.000692506,
- -0.000677361,
- -0.000662049,
- -0.000646575,
- -0.000630955,
- -0.000615196,
- -0.000599314,
- -0.000583319,
- -0.000567225,
- -0.000551043,
- -0.000534785,
- -0.000518464,
- -0.000502091,
- -0.00048568,
- -0.00046924,
- -0.000452784,
- -0.000436324,
- -0.00041987,
- -0.000403434,
- -0.000387027,
- -0.00037066,
- -0.000354342,
- -0.000338084,
- -0.000321898,
- -0.000305792,
- -0.000289776,
- -0.000273861,
- -0.000258056,
- -0.000242369,
- -0.000226811,
- -0.00021139,
- -0.000196115,
- -0.000180995,
- -0.000166036,
- -0.000151248,
- -0.000136638,
- -0.000122213,
- -0.000107981,
- -9.39481e-05,
- -8.01218e-05,
- -6.65082e-05,
- -5.31139e-05,
- -3.99444e-05,
- -2.70061e-05,
- -1.43041e-05,
- -1.844e-06,
- 1.03695e-05,
- 2.23311e-05,
- 3.40369e-05,
- 4.54822e-05,
- 5.66636e-05,
- 6.7577e-05,
- 7.82196e-05,
- 8.85877e-05,
- 9.8679e-05,
- 0.000108491,
- 0.00011802,
- 0.000127266,
- 0.000136224,
- 0.000144895,
- 0.000153275,
- 0.000161363,
- 0.000169145,
- 0.000176621,
- 0.000183812,
- 0.000190706,
- 0.000197304,
- 0.000203605,
- 0.000209608,
- 0.000215314,
- 0.000220723,
- 0.000225837,
- 0.000230655,
- 0.00023518,
- 0.000239412,
- 0.000243354,
- 0.000247007,
- 0.000250373,
- 0.000253453,
- 0.000256251,
- 0.000258767,
- 0.000261006,
- 0.000262968,
- 0.000264658,
- 0.000266079,
- 0.000267232,
- 0.000268123,
- 0.000268754,
- 0.000269129,
- 0.000269253,
- 0.000269128,
- 0.00026876,
- 0.000268152,
- 0.000267308,
- 0.000266234,
- 0.000264933,
- 0.000263411,
- 0.000261672,
- 0.000259721,
- 0.000257562,
- 0.000255202,
- 0.000252644,
- 0.000249895,
- 0.000246959,
- 0.000243843,
- 0.000240551,
- 0.000237089,
- 0.000233463,
- 0.000229678,
- 0.00022574,
- 0.000221654,
- 0.000217426,
- 0.000213063,
- 0.000208568,
- 0.000203949,
- 0.000199211,
- 0.00019436,
- 0.0001894,
- 0.00018434,
- 0.000179183,
- 0.000173938,
- 0.000168608,
- 0.000163202,
- 0.000157725,
- 0.000152183,
- 0.000146583,
- 0.000140929,
- 0.000135218,
- 0.000129468,
- 0.000123681,
- 0.000117864,
- 0.00011202,
- 0.000106157,
- 0.000100278,
- 9.43895e-05,
- 8.84957e-05,
- 8.26029e-05,
- 7.67152e-05,
- 7.08393e-05,
- 6.49787e-05,
- 5.91403e-05,
- 5.33273e-05,
- 4.75467e-05,
- 4.18011e-05,
- 3.60975e-05,
- 3.04382e-05,
- 2.483e-05,
- 1.9275e-05,
- 1.37796e-05,
- 8.34567e-06,
- 2.97965e-06,
- -2.31702e-06,
- -7.53795e-06,
- -1.2682e-05,
- -1.77428e-05,
- -2.27195e-05,
- -2.7606e-05,
- -3.24015e-05,
- -3.71002e-05,
- -4.17016e-05,
- -4.62001e-05,
- -5.05954e-05,
- -5.48823e-05,
- -5.90607e-05,
- -6.31256e-05,
- -6.70773e-05,
- -7.09109e-05,
- -7.46271e-05,
- -7.82211e-05,
- -8.16936e-05,
- -8.50404e-05,
- -8.82623e-05,
- -9.13551e-05,
- -9.43199e-05,
- -9.71528e-05,
- -9.98553e-05,
- -0.000102424,
- -0.00010486,
- -0.00010716,
- -0.000109326,
- -0.000111356,
- -0.000113251,
- -0.000115009,
- -0.000116633,
- -0.000118119,
- -0.000119471,
- -0.000120685,
- -0.000121766,
- -0.000122709,
- -0.000123518,
- -0.000124185,
- -0.000124729,
- -0.000125145,
- -0.000125428,
- -0.000125578,
- -0.000125598,
- -0.000125487,
- -0.00012525,
- -0.000124884,
- -0.000124397,
- -0.000123784,
- -0.000123053,
- -0.000122201,
- -0.000121235,
- -0.000120152,
- -0.000118959,
- -0.000117652,
- -0.000116241,
- -0.00011472,
- -0.000113099,
- -0.000111372,
- -0.00010955,
- -0.000107627,
- -0.000105614,
- -0.000103505,
- -0.000101311,
- -9.9026e-05,
- -9.66619e-05,
- -9.42119e-05,
- -9.16888e-05,
- -8.9085e-05,
- -8.64141e-05,
- -8.36678e-05,
- -8.08605e-05,
- -7.7983e-05,
- -7.50509e-05,
- -7.20538e-05,
- -6.90085e-05,
- -6.59032e-05,
- -6.27565e-05,
- -5.95548e-05,
- -5.63184e-05,
- -5.3032e-05,
- -4.97179e-05,
- -4.63581e-05,
- -4.29778e-05,
- -3.95556e-05,
- -3.61199e-05,
- -3.26453e-05,
- -2.91642e-05,
- -2.56455e-05,
- -2.21275e-05,
- -1.85712e-05,
- -1.50227e-05,
- -1.14317e-05,
- -7.85603e-06,
- -4.22748e-06,
- -6.22187e-07,
- 3.05918e-06,
- 6.70859e-06,
- 1.04905e-05,
- 1.42303e-05,
- 1.82863e-05,
- 2.2286e-05
-};
+++ /dev/null
-#!/bin/sh
-# sim.sh
-# David Rowe 10 Sep 2009
-
-# Process a source file using the codec 2 simulation. An output
-# speech file is generated for each major processing step, from the
-# unquantised siusoidal model to fully quantised. This way we can
-# listen to the effect of each processing step. Use listensim.sh to
-# test the output files.
-
-../src/c2sim ../raw/$1.raw -o $1_uq.raw
-../src/c2sim ../raw/$1.raw --phase0 -o $1_phase0.raw --postfilter
-../src/c2sim ../raw/$1.raw --lpc 10 -o $1_lpc10.raw --postfilter
-../src/c2sim ../raw/$1.raw --phase0 --lpc 10 -o $1_phase0_lpc10.raw --postfilter
-../src/c2sim ../raw/$1.raw --phase0 --lpc 10 --dec -o $1_phase0_lpc10_dec.raw --postfilter
-../src/c2sim ../raw/$1.raw --phase0 --lpc 10 --lsp --dec -o $1_phase0_lsp_dec.raw --postfilter
-
-#../src/c2sim ../raw/$1.raw --lpc 10 --lsp -o $1_lsp.raw
-#../src/c2sim ../raw/$1.raw --phase0 --lpc 10 -o $1_phase0_lpc10.raw --postfilter
-#../src/c2sim ../raw/$1.raw --phase0 --lpc 10 --lsp -o $1_phase0_lsp.raw --postfilter
-#../src/c2sim ../raw/$1.raw --phase0 --lpc 10 --lsp -o $1_phase0_lsp_dec.raw --postfilter --dec
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: sine.c
- AUTHOR......: David Rowe
- DATE CREATED: 19/8/2010
-
- Sinusoidal analysis and synthesis functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 1990-2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/*---------------------------------------------------------------------------*\
-
- INCLUDES
-
-\*---------------------------------------------------------------------------*/
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <math.h>
-
-#include "defines.h"
-#include "sine.h"
-#include "kiss_fft.h"
-
-#define HPF_BETA 0.125
-
-/*---------------------------------------------------------------------------*\
-
- HEADERS
-
-\*---------------------------------------------------------------------------*/
-
-void hs_pitch_refinement(MODEL *model, COMP Sw[], float pmin, float pmax,
- float pstep);
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*---------------------------------------------------------------------------*/
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: make_analysis_window
- AUTHOR......: David Rowe
- DATE CREATED: 11/5/94
-
- Init function that generates the time domain analysis window and it's DFT.
-
-\*---------------------------------------------------------------------------*/
-
-void make_analysis_window(kiss_fft_cfg fft_fwd_cfg, float w[], COMP W[])
-{
- float m;
- COMP wshift[FFT_ENC];
- COMP temp;
- int i,j;
-
- /*
- Generate Hamming window centered on M-sample pitch analysis window
-
- 0 M/2 M-1
- |-------------|-------------|
- |-------|-------|
- NW samples
-
- All our analysis/synthsis is centred on the M/2 sample.
- */
-
- m = 0.0;
- for(i=0; i<M/2-NW/2; i++)
- w[i] = 0.0;
- for(i=M/2-NW/2,j=0; i<M/2+NW/2; i++,j++) {
- w[i] = 0.5 - 0.5*cos(TWO_PI*j/(NW-1));
- m += w[i]*w[i];
- }
- for(i=M/2+NW/2; i<M; i++)
- w[i] = 0.0;
-
- /* Normalise - makes freq domain amplitude estimation straight
- forward */
-
- m = 1.0/sqrt(m*FFT_ENC);
- for(i=0; i<M; i++) {
- w[i] *= m;
- }
-
- /*
- Generate DFT of analysis window, used for later processing. Note
- we modulo FFT_ENC shift the time domain window w[], this makes the
- imaginary part of the DFT W[] equal to zero as the shifted w[] is
- even about the n=0 time axis if NW is odd. Having the imag part
- of the DFT W[] makes computation easier.
-
- 0 FFT_ENC-1
- |-------------------------|
-
- ----\ /----
- \ /
- \ / <- shifted version of window w[n]
- \ /
- \ /
- -------
-
- |---------| |---------|
- NW/2 NW/2
- */
-
- for(i=0; i<FFT_ENC; i++) {
- wshift[i].real = 0.0;
- wshift[i].imag = 0.0;
- }
- for(i=0; i<NW/2; i++)
- wshift[i].real = w[i+M/2];
- for(i=FFT_ENC-NW/2,j=M/2-NW/2; i<FFT_ENC; i++,j++)
- wshift[i].real = w[j];
-
- kiss_fft(fft_fwd_cfg, (kiss_fft_cpx *)wshift, (kiss_fft_cpx *)W);
-
- /*
- Re-arrange W[] to be symmetrical about FFT_ENC/2. Makes later
- analysis convenient.
-
- Before:
-
-
- 0 FFT_ENC-1
- |----------|---------|
- __ _
- \ /
- \_______________/
-
- After:
-
- 0 FFT_ENC-1
- |----------|---------|
- ___
- / \
- ________/ \_______
-
- */
-
-
- for(i=0; i<FFT_ENC/2; i++) {
- temp.real = W[i].real;
- temp.imag = W[i].imag;
- W[i].real = W[i+FFT_ENC/2].real;
- W[i].imag = W[i+FFT_ENC/2].imag;
- W[i+FFT_ENC/2].real = temp.real;
- W[i+FFT_ENC/2].imag = temp.imag;
- }
-
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: hpf
- AUTHOR......: David Rowe
- DATE CREATED: 16 Nov 2010
-
- High pass filter with a -3dB point of about 160Hz.
-
- y(n) = -HPF_BETA*y(n-1) + x(n) - x(n-1)
-
-\*---------------------------------------------------------------------------*/
-
-float hpf(float x, float states[])
-{
- states[0] += -HPF_BETA*states[0] + x - states[1];
- states[1] = x;
-
- return states[0];
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: dft_speech
- AUTHOR......: David Rowe
- DATE CREATED: 27/5/94
-
- Finds the DFT of the current speech input speech frame.
-
-\*---------------------------------------------------------------------------*/
-
-void dft_speech(kiss_fft_cfg fft_fwd_cfg, COMP Sw[], float Sn[], float w[])
-{
- int i;
- COMP sw[FFT_ENC];
-
- for(i=0; i<FFT_ENC; i++) {
- sw[i].real = 0.0;
- sw[i].imag = 0.0;
- }
-
- /* Centre analysis window on time axis, we need to arrange input
- to FFT this way to make FFT phases correct */
-
- /* move 2nd half to start of FFT input vector */
-
- for(i=0; i<NW/2; i++)
- sw[i].real = Sn[i+M/2]*w[i+M/2];
-
- /* move 1st half to end of FFT input vector */
-
- for(i=0; i<NW/2; i++)
- sw[FFT_ENC-NW/2+i].real = Sn[i+M/2-NW/2]*w[i+M/2-NW/2];
-
- kiss_fft(fft_fwd_cfg, (kiss_fft_cpx *)sw, (kiss_fft_cpx *)Sw);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: two_stage_pitch_refinement
- AUTHOR......: David Rowe
- DATE CREATED: 27/5/94
-
- Refines the current pitch estimate using the harmonic sum pitch
- estimation technique.
-
-\*---------------------------------------------------------------------------*/
-
-void two_stage_pitch_refinement(MODEL *model, COMP Sw[])
-{
- float pmin,pmax,pstep; /* pitch refinment minimum, maximum and step */
-
- /* Coarse refinement */
-
- pmax = TWO_PI/model->Wo + 5;
- pmin = TWO_PI/model->Wo - 5;
- pstep = 1.0;
- hs_pitch_refinement(model,Sw,pmin,pmax,pstep);
-
- /* Fine refinement */
-
- pmax = TWO_PI/model->Wo + 1;
- pmin = TWO_PI/model->Wo - 1;
- pstep = 0.25;
- hs_pitch_refinement(model,Sw,pmin,pmax,pstep);
-
- /* Limit range */
-
- if (model->Wo < TWO_PI/P_MAX)
- model->Wo = TWO_PI/P_MAX;
- if (model->Wo > TWO_PI/P_MIN)
- model->Wo = TWO_PI/P_MIN;
-
- model->L = floor(PI/model->Wo);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: hs_pitch_refinement
- AUTHOR......: David Rowe
- DATE CREATED: 27/5/94
-
- Harmonic sum pitch refinement function.
-
- pmin pitch search range minimum
- pmax pitch search range maximum
- step pitch search step size
- model current pitch estimate in model.Wo
-
- model refined pitch estimate in model.Wo
-
-\*---------------------------------------------------------------------------*/
-
-void hs_pitch_refinement(MODEL *model, COMP Sw[], float pmin, float pmax, float pstep)
-{
- int m; /* loop variable */
- int b; /* bin for current harmonic centre */
- float E; /* energy for current pitch*/
- float Wo; /* current "test" fundamental freq. */
- float Wom; /* Wo that maximises E */
- float Em; /* mamimum energy */
- float r; /* number of rads/bin */
- float p; /* current pitch */
-
- /* Initialisation */
-
- model->L = PI/model->Wo; /* use initial pitch est. for L */
- Wom = model->Wo;
- Em = 0.0;
- r = TWO_PI/FFT_ENC;
-
- /* Determine harmonic sum for a range of Wo values */
-
- for(p=pmin; p<=pmax; p+=pstep) {
- E = 0.0;
- Wo = TWO_PI/p;
-
- /* Sum harmonic magnitudes */
-
- for(m=1; m<=model->L; m++) {
- b = floor(m*Wo/r + 0.5);
- E += Sw[b].real*Sw[b].real + Sw[b].imag*Sw[b].imag;
- }
-
- /* Compare to see if this is a maximum */
-
- if (E > Em) {
- Em = E;
- Wom = Wo;
- }
- }
-
- model->Wo = Wom;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: estimate_amplitudes
- AUTHOR......: David Rowe
- DATE CREATED: 27/5/94
-
- Estimates the complex amplitudes of the harmonics.
-
-\*---------------------------------------------------------------------------*/
-
-void estimate_amplitudes(MODEL *model, COMP Sw[], COMP W[])
-{
- int i,m; /* loop variables */
- int am,bm; /* bounds of current harmonic */
- int b; /* DFT bin of centre of current harmonic */
- float den; /* denominator of amplitude expression */
- float r; /* number of rads/bin */
- int offset;
- COMP Am;
-
- r = TWO_PI/FFT_ENC;
-
- for(m=1; m<=model->L; m++) {
- den = 0.0;
- am = floor((m - 0.5)*model->Wo/r + 0.5);
- bm = floor((m + 0.5)*model->Wo/r + 0.5);
- b = floor(m*model->Wo/r + 0.5);
-
- /* Estimate ampltude of harmonic */
-
- den = 0.0;
- Am.real = Am.imag = 0.0;
- for(i=am; i<bm; i++) {
- den += Sw[i].real*Sw[i].real + Sw[i].imag*Sw[i].imag;
- offset = i + FFT_ENC/2 - floor(m*model->Wo/r + 0.5);
- Am.real += Sw[i].real*W[offset].real;
- Am.imag += Sw[i].imag*W[offset].real;
- }
-
- model->A[m] = sqrt(den);
-
- /* Estimate phase of harmonic */
-
- model->phi[m] = atan2(Sw[b].imag,Sw[b].real);
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- est_voicing_mbe()
-
- Returns the error of the MBE cost function for a fiven F0.
-
- Note: I think a lot of the operations below can be simplified as
- W[].imag = 0 and has been normalised such that den always equals 1.
-
-\*---------------------------------------------------------------------------*/
-
-float est_voicing_mbe(
- MODEL *model,
- COMP Sw[],
- COMP W[],
- COMP Sw_[], /* DFT of all voiced synthesised signal */
- /* useful for debugging/dump file */
- COMP Ew[], /* DFT of error */
- float prev_Wo)
-{
- int i,l,al,bl,m; /* loop variables */
- COMP Am; /* amplitude sample for this band */
- int offset; /* centers Hw[] about current harmonic */
- float den; /* denominator of Am expression */
- float error; /* accumulated error between original and synthesised */
- float Wo;
- float sig, snr;
- float elow, ehigh, eratio;
- float dF0, sixty;
-
- sig = 1E-4;
- for(l=1; l<=model->L/4; l++) {
- sig += model->A[l]*model->A[l];
- }
- for(i=0; i<FFT_ENC; i++) {
- Sw_[i].real = 0.0;
- Sw_[i].imag = 0.0;
- Ew[i].real = 0.0;
- Ew[i].imag = 0.0;
- }
-
- Wo = model->Wo;
- error = 1E-4;
-
- /* Just test across the harmonics in the first 1000 Hz (L/4) */
-
- for(l=1; l<=model->L/4; l++) {
- Am.real = 0.0;
- Am.imag = 0.0;
- den = 0.0;
- al = ceil((l - 0.5)*Wo*FFT_ENC/TWO_PI);
- bl = ceil((l + 0.5)*Wo*FFT_ENC/TWO_PI);
-
- /* Estimate amplitude of harmonic assuming harmonic is totally voiced */
-
- for(m=al; m<bl; m++) {
- offset = FFT_ENC/2 + m - l*Wo*FFT_ENC/TWO_PI + 0.5;
- Am.real += Sw[m].real*W[offset].real + Sw[m].imag*W[offset].imag;
- Am.imag += Sw[m].imag*W[offset].real - Sw[m].real*W[offset].imag;
- den += W[offset].real*W[offset].real + W[offset].imag*W[offset].imag;
- }
-
- Am.real = Am.real/den;
- Am.imag = Am.imag/den;
-
- /* Determine error between estimated harmonic and original */
-
- for(m=al; m<bl; m++) {
- offset = FFT_ENC/2 + m - l*Wo*FFT_ENC/TWO_PI + 0.5;
- Sw_[m].real = Am.real*W[offset].real - Am.imag*W[offset].imag;
- Sw_[m].imag = Am.real*W[offset].imag + Am.imag*W[offset].real;
- Ew[m].real = Sw[m].real - Sw_[m].real;
- Ew[m].imag = Sw[m].imag - Sw_[m].imag;
- error += Ew[m].real*Ew[m].real;
- error += Ew[m].imag*Ew[m].imag;
- }
- }
-
- snr = 10.0*log10(sig/error);
- if (snr > V_THRESH)
- model->voiced = 1;
- else
- model->voiced = 0;
-
- /* post processing, helps clean up some voicing errors ------------------*/
-
- /*
- Determine the ratio of low freqency to high frequency energy,
- voiced speech tends to be dominated by low frequency energy,
- unvoiced by high frequency. This measure can be used to
- determine if we have made any gross errors.
- */
-
- elow = ehigh = 1E-4;
- for(l=1; l<=model->L/2; l++) {
- elow += model->A[l]*model->A[l];
- }
- for(l=model->L/2; l<=model->L; l++) {
- ehigh += model->A[l]*model->A[l];
- }
- eratio = 10.0*log10(elow/ehigh);
- dF0 = 0.0;
-
- /* Look for Type 1 errors, strongly V speech that has been
- accidentally declared UV */
-
- if (model->voiced == 0)
- if (eratio > 10.0)
- model->voiced = 1;
-
- /* Look for Type 2 errors, strongly UV speech that has been
- accidentally declared V */
-
- if (model->voiced == 1) {
- if (eratio < -10.0)
- model->voiced = 0;
-
- /* If pitch is jumping about it's likely this is UV */
-
- /* 13 Feb 2012 - this seems to add some V errors so comment out for now. Maybe
- double check on bg noise files
-
- dF0 = (model->Wo - prev_Wo)*FS/TWO_PI;
- if (fabs(dF0) > 15.0)
- model->voiced = 0;
- */
-
- /* A common source of Type 2 errors is the pitch estimator
- gives a low (50Hz) estimate for UV speech, which gives a
- good match with noise due to the close harmoonic spacing.
- These errors are much more common than people with 50Hz3
- pitch, so we have just a small eratio threshold. */
-
- sixty = 60.0*TWO_PI/FS;
- if ((eratio < -4.0) && (model->Wo <= sixty))
- model->voiced = 0;
- }
- //printf(" v: %d snr: %f eratio: %3.2f %f\n",model->voiced,snr,eratio,dF0);
-
- return snr;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: make_synthesis_window
- AUTHOR......: David Rowe
- DATE CREATED: 11/5/94
-
- Init function that generates the trapezoidal (Parzen) sythesis window.
-
-\*---------------------------------------------------------------------------*/
-
-void make_synthesis_window(float Pn[])
-{
- int i;
- float win;
-
- /* Generate Parzen window in time domain */
-
- win = 0.0;
- for(i=0; i<N/2-TW; i++)
- Pn[i] = 0.0;
- win = 0.0;
- for(i=N/2-TW; i<N/2+TW; win+=1.0/(2*TW), i++ )
- Pn[i] = win;
- for(i=N/2+TW; i<3*N/2-TW; i++)
- Pn[i] = 1.0;
- win = 1.0;
- for(i=3*N/2-TW; i<3*N/2+TW; win-=1.0/(2*TW), i++)
- Pn[i] = win;
- for(i=3*N/2+TW; i<2*N; i++)
- Pn[i] = 0.0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: synthesise
- AUTHOR......: David Rowe
- DATE CREATED: 20/2/95
-
- Synthesise a speech signal in the frequency domain from the
- sinusodal model parameters. Uses overlap-add with a trapezoidal
- window to smoothly interpolate betwen frames.
-
-\*---------------------------------------------------------------------------*/
-
-void synthesise(
- kiss_fft_cfg fft_inv_cfg,
- float Sn_[], /* time domain synthesised signal */
- MODEL *model, /* ptr to model parameters for this frame */
- float Pn[], /* time domain Parzen window */
- int shift /* flag used to handle transition frames */
-)
-{
- int i,l,j,b; /* loop variables */
- COMP Sw_[FFT_DEC]; /* DFT of synthesised signal */
- COMP sw_[FFT_DEC]; /* synthesised signal */
-
- if (shift) {
- /* Update memories */
-
- for(i=0; i<N-1; i++) {
- Sn_[i] = Sn_[i+N];
- }
- Sn_[N-1] = 0.0;
- }
-
- for(i=0; i<FFT_DEC; i++) {
- Sw_[i].real = 0.0;
- Sw_[i].imag = 0.0;
- }
-
- /*
- Nov 2010 - found that synthesis using time domain cos() functions
- gives better results for synthesis frames greater than 10ms. Inverse
- FFT synthesis using a 512 pt FFT works well for 10ms window. I think
- (but am not sure) that the problem is related to the quantisation of
- the harmonic frequencies to the FFT bin size, e.g. there is a
- 8000/512 Hz step between FFT bins. For some reason this makes
- the speech from longer frame > 10ms sound poor. The effect can also
- be seen when synthesising test signals like single sine waves, some
- sort of amplitude modulation at the frame rate.
-
- Another possibility is using a larger FFT size (1024 or 2048).
- */
-
-#define FFT_SYNTHESIS
-#ifdef FFT_SYNTHESIS
- /* Now set up frequency domain synthesised speech */
- for(l=1; l<=model->L; l++) {
- //for(l=model->L/2; l<=model->L; l++) {
- //for(l=1; l<=model->L/4; l++) {
- b = floor(l*model->Wo*FFT_DEC/TWO_PI + 0.5);
- if (b > ((FFT_DEC/2)-1)) {
- b = (FFT_DEC/2)-1;
- }
- Sw_[b].real = model->A[l]*cos(model->phi[l]);
- Sw_[b].imag = model->A[l]*sin(model->phi[l]);
- Sw_[FFT_DEC-b].real = Sw_[b].real;
- Sw_[FFT_DEC-b].imag = -Sw_[b].imag;
- }
-
- /* Perform inverse DFT */
-
- kiss_fft(fft_inv_cfg, (kiss_fft_cpx *)Sw_, (kiss_fft_cpx *)sw_);
-#else
- /*
- Direct time domain synthesis using the cos() function. Works
- well at 10ms and 20ms frames rates. Note synthesis window is
- still used to handle overlap-add between adjacent frames. This
- could be simplified as we don't need to synthesise where Pn[]
- is zero.
- */
- for(l=1; l<=model->L; l++) {
- for(i=0,j=-N+1; i<N-1; i++,j++) {
- Sw_[FFT_DEC-N+1+i].real += 2.0*model->A[l]*cos(j*model->Wo*l + model->phi[l]);
- }
- for(i=N-1,j=0; i<2*N; i++,j++)
- Sw_[j].real += 2.0*model->A[l]*cos(j*model->Wo*l + model->phi[l]);
- }
-#endif
-
- /* Overlap add to previous samples */
-
- for(i=0; i<N-1; i++) {
- Sn_[i] += sw_[FFT_DEC-N+1+i].real*Pn[i];
- }
-
- if (shift)
- for(i=N-1,j=0; i<2*N; i++,j++)
- Sn_[i] = sw_[j].real*Pn[i];
- else
- for(i=N-1,j=0; i<2*N; i++,j++)
- Sn_[i] += sw_[j].real*Pn[i];
-}
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: sine.h
- AUTHOR......: David Rowe
- DATE CREATED: 1/11/94
-
- Header file for sinusoidal analysis and synthesis functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __SINE__
-#define __SINE__
-
-#include "defines.h"
-#include "comp.h"
-#include "kiss_fft.h"
-
-void make_analysis_window(kiss_fft_cfg fft_fwd_cfg, float w[], COMP W[]);
-float hpf(float x, float states[]);
-void dft_speech(kiss_fft_cfg fft_fwd_cfg, COMP Sw[], float Sn[], float w[]);
-void two_stage_pitch_refinement(MODEL *model, COMP Sw[]);
-void estimate_amplitudes(MODEL *model, COMP Sw[], COMP W[]);
-float est_voicing_mbe(MODEL *model, COMP Sw[], COMP W[], COMP Sw_[],COMP Ew[],
- float prev_Wo);
-void make_synthesis_window(float Pn[]);
-void synthesise(kiss_fft_cfg fft_inv_cfg, float Sn_[], MODEL *model, float Pn[], int shift);
-
-#endif
+++ /dev/null
-/* Generated by test_bits_file() Octave function */
-
-const int test_bits[]={
- 0,
- 1,
- 1,
- 0,
- 0,
- 0,
- 1,
- 1,
- 0,
- 0,
- 1,
- 0,
- 1,
- 0,
- 0,
- 1,
- 0,
- 1,
- 1,
- 0,
- 0,
- 1,
- 1,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 0,
- 1,
- 1,
- 1,
- 0,
- 1,
- 1,
- 0,
- 0,
- 1,
- 1,
- 1,
- 0,
- 1,
- 1,
- 0,
- 1,
- 1,
- 1,
- 1,
- 1,
- 0,
- 0,
- 1,
- 0,
- 0,
- 1,
- 1,
- 1,
- 0,
- 0,
- 1,
- 1,
- 1,
- 0,
- 0,
- 0,
- 0,
- 1,
- 1,
- 1,
- 0,
- 0,
- 1,
- 1,
- 1,
- 1,
- 1,
- 0,
- 1,
- 1,
- 1,
- 0,
- 0,
- 1,
- 1,
- 0,
- 1,
- 1,
- 1,
- 1,
- 1,
- 1,
- 1,
- 0,
- 0,
- 1,
- 1,
- 0,
- 1,
- 0,
- 0,
- 0,
- 1,
- 1,
- 1,
- 0
-};
+++ /dev/null
-AM_CFLAGS = -I../src -I$(abs_srcdir)/../src -fPIC -g -DFLOATING_POINT -DVAR_ARRAYS -O2 -Wall
-AUTOMAKE_OPTIONS = gnu
-NAME = libcodec2
-AM_CPPFLAGS = $(AM_CFLAGS)
-
-noinst_PROGRAMS = genres genlsp extract vqtrain vqtrainjnd tnlp tinterp tquant vq_train_jvm scalarlsptest tfdmdv t48_8 lspsync create_interleaver tlspsens vqtrainph genphdata genampdata polar2rect vqtrainsp tprede pre de tfifo
-
-genres_SOURCES = genres.c ../src/lpc.c
-genres_LDADD = $(lib_LTLIBRARIES)
-genres_LDFLAGS = $(LIBS)
-
-genlsp_SOURCES = genlsp.c ../src/lpc.c ../src/lsp.c
-genlsp_LDADD = $(lib_LTLIBRARIES)
-genlsp_LDFLAGS = $(LIBS)
-
-extract_SOURCES = extract.c
-extract_LDADD = $(lib_LTLIBRARIES)
-extract_LDFLAGS = $(LIBS)
-
-vqtrain_SOURCES = vqtrain.c
-vqtrain_LDADD = $(lib_LTLIBRARIES)
-vqtrain_LDFLAGS = $(LIBS)
-
-vqtrainjnd_SOURCES = vqtrainjnd.c
-vqtrainjnd_LDADD = $(lib_LTLIBRARIES)
-vqtrainjnd_LDFLAGS = $(LIBS)
-
-vqtrainph_SOURCES = vqtrainph.c
-vqtrainph_LDADD = $(lib_LTLIBRARIES)
-vqtrainph_LDFLAGS = $(LIBS)
-
-vqtrainsp_SOURCES = vqtrainsp.c
-vqtrainsp_LDADD = $(lib_LTLIBRARIES)
-vqtrainsp_LDFLAGS = $(LIBS)
-
-genphdata_SOURCES = genphdata.c
-genphdata_LDADD = $(lib_LTLIBRARIES)
-genphdata_LDFLAGS = $(LIBS)
-
-genampdata_SOURCES = genampdata.c
-genampdata_LDADD = $(lib_LTLIBRARIES)
-genampdata_LDFLAGS = $(LIBS)
-
-polar2rect_SOURCES = polar2rect.c
-polar2rect_LDADD = $(lib_LTLIBRARIES)
-polar2rect_LDFLAGS = $(LIBS)
-
-vq_train_jvm_SOURCES = vq_train_jvm.c
-vq_train_jvm_LDADD = $(lib_LTLIBRARIES)
-vq_train_jvm_LDFLAGS = $(LIBS)
-
-CODEBOOKS = ../src/codebook.c ../src/codebookd.c ../src/codebookvq.c ../src/codebookjnd.c ../src/codebookdt.c ../src/codebookjvm.c ../src/codebookvqanssi.c ../src/codebookge.c
-
-tnlp_SOURCES = tnlp.c ../src/sine.c ../src/nlp.c ../src/kiss_fft.c ../src/dump.c
-tnlp_LDADD = $(lib_LTLIBRARIES)
-tnlp_LDFLAGS = $(LIBS)
-
-tinterp_SOURCES = tinterp.c ../src/sine.c ../src/kiss_fft.c ../src/interp.c ../src/lpc.c ../src/lsp.c ../src/quantise.c $(CODEBOOKS) ../src/dump.c
-tinterp_LDADD = $(lib_LTLIBRARIES)
-tinterp_LDFLAGS = $(LIBS)
-
-tquant_SOURCES = tquant.c ../src/quantise.c ../src/lpc.c ../src/lsp.c ../src/dump.c ../src/kiss_fft.c $(CODEBOOKS)
-tquant_LDADD = $(lib_LTLIBRARIES)
-tquant_LDFLAGS = $(LIBS)
-
-scalarlsptest_SOURCES = scalarlsptest.c ../src/quantise.c ../src/lpc.c ../src/lsp.c ../src/dump.c ../src/kiss_fft.c $(CODEBOOKS)
-scalarlsptest_LDADD = $(lib_LTLIBRARIES)
-scalarlsptest_LDFLAGS = $(LIBS)
-
-tfdmdv_SOURCES = tfdmdv.c ../src/fdmdv.c ../src/kiss_fft.c ../src/octave.c
-tfdmdv_LDADD = $(lib_LTLIBRARIES)
-tfdmdv_LDFLAGS = $(LIBS)
-
-t48_8_SOURCES = t48_8.c ../src/fdmdv.c ../src/kiss_fft.c
-t48_8_LDADD = $(lib_LTLIBRARIES)
-t48_8_LDFLAGS = $(LIBS)
-
-lspsync_SOURCES = lspsync.c ../src/quantise.c ../src/lpc.c ../src/lsp.c ../src/dump.c ../src/kiss_fft.c \
-../src/codec2.c ../src/sine.c ../src/nlp.c ../src/postfilter.c ../src/phase.c ../src/interp.c ../src/pack.c $(CODEBOOKS)
-lspsync_LDADD = $(lib_LTLIBRARIES)
-lspsync_LDFLAGS = $(LIBS)
-
-create_interleaver_SOURCES = create_interleaver.c
-create_interleaver_LDADD = $(lib_LTLIBRARIES)
-create_interleaver_LDFLAGS = $(LIBS)
-
-tlspsens_SOURCES = tlspsens.c ../src/quantise.c ../src/lpc.c ../src/lsp.c ../src/dump.c ../src/kiss_fft.c ../src/codec2.c ../src/sine.c ../src/nlp.c ../src/pack.c ../src/interp.c ../src/postfilter.c ../src/phase.c $(CODEBOOKS)
-tlspsens_LDADD = $(lib_LTLIBRARIES)
-tlspsens_LDFLAGS = $(LIBS)
-
-tprede_SOURCES = tprede.c ../src/lpc.c
-tprede_LDADD = $(lib_LTLIBRARIES)
-tprede_LDFLAGS = $(LIBS)
-
-pre_SOURCES = pre.c ../src/lpc.c
-pre_LDADD = $(lib_LTLIBRARIES)
-pre_LDFLAGS = $(LIBS)
-
-de_SOURCES = de.c ../src/lpc.c
-de_LDADD = $(lib_LTLIBRARIES)
-de_LDFLAGS = $(LIBS)
-
-tfifo_SOURCES = tfifo.c ../src/fifo.c
-tfifo_LDADD = $(lib_LTLIBRARIES) -lpthread
-tfifo_LDFLAGS = $(LIBS)
+++ /dev/null
-README
-for codec2/unittest
-Created David Rowe 31 July 2012
-
-Training (experimental) sparse phase VQs:
-
-1/ In ../src/phase.c phase_experiment() enable:
-
- print_sparse_pred_error()
-
- and 'make' c2sim (in src)
-
-2/ Run over a training database:
-
- $ ./c2sim /xhome1/codec2/samples/train.spc --phaseexp > train_phtrain.txt
-
- a) check stats in Octave:
- octave> load ../src/train_phtrain.txt
- octave> std(nonzeros(train_phtrain(:,1:20)))
- octave> hist(nonzeros(train_phtrain(:,1:20)),20)
-3/ Extract and convert to floats vector you wish to train for example
- first 20 (out of MAX_AMP == 80):
-
- $ ./extract ../src/train_phtrain.txt train_phtrain.flt 1 20
-
-4/ Convert to rectangular:
-
- $ ./polar2rect train_phtrain.flt train_phtrainr.flt
-
-5/ Run this program:
-
- $ ./vqtrainph train_phtrainr.flt 20 1024 vq.txt
-
- Ouput is vq.txt
-
-Tests
------
-
-+ build up insmallest possible stesp
-+ impl errors v alg errors
-+ use actual phase data as codebook
-+ test vq with rand phases first or known data
-
+++ /dev/null
-/*
- create_interleaver.c
- David Rowe
- May 27 2012
-
- Creates an interleaver for Codec 2.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-
-int main(int argc, char * argv[]) {
- int m,i, src_bit, dest_bit;
- FILE *f;
- int *interleaver;
-
- if (argc != 3) {
- printf("usage: %s InterleaverBits InterleaverFile\n", argv[0]);
- exit(1);
- }
-
- m = atoi(argv[1]);
- f = fopen(argv[2],"wt");
- assert(f != NULL);
-
-
- interleaver = (int*)malloc(m*sizeof(int));
- assert(interleaver != NULL);
- for(i=0; i<m; i++)
- interleaver[i] = -1;
-
- src_bit = 0;
- while(src_bit != m) {
- dest_bit = ((float)rand()/RAND_MAX)*m;
- if (interleaver[dest_bit] == -1) {
- interleaver[dest_bit] = src_bit;
- src_bit++;
- }
- }
-
- for(i=0; i<m; i++) {
- fprintf(f, "%d\n", interleaver[i]);
- }
-
- fclose(f);
- return 0;
-}
+++ /dev/null
-/*
- de.c
- David Rowe
- Sep 26 2012
-
- Takes audio from a file, de-emphasises, and sends to output file.
-*/
-
-#include <assert.h>
-#include <errno.h>
-#include <math.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include "lpc.h"
-
-#define N 80
-
-int main(int argc, char *argv[]) {
- FILE *fin, *fout;
- short buf[N];
- float Sn[N], Sn_de[N];
- float de_mem = 0.0;
- int i;
-
- if (argc != 3) {
- printf("usage: de InputRawSpeechFile OutputRawSpeechFile\n");
- printf("e.g de input.raw output.raw");
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input speech file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[2],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output speech file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- while(fread(buf, sizeof(short), N, fin) == N) {
- for(i=0; i<N; i++)
- Sn[i] = buf[i];
- de_emp(Sn_de, Sn, &de_mem, N);
- for(i=0; i<N; i++)
- buf[i] = Sn_de[i];
- fwrite(buf, sizeof(short), N, fout);
- }
-
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: dvdongle2.c
- AUTHOR......: David Rowe
- DATE CREATED: 28 Oct 2010
-
- Program to encode and decode raw speech samples using the AMBE codec
- implemented on a DV Dongle.
-
- The DV Dongle connects to a USB port and provides encoding and
- decoding of compressed audio using the DVSI AMBE2000 full duplex
- vocoder DSP chip.
-
- Refs:
-
- [1] http://www.dvdongle.com/
- [2] http://www.moetronix.com/files/dvdongletechref100.pdf
- [3] http://www.dvsinc.com/manuals/AMBE-2000_manual.pdf
- [4] http://www.moetronix.com/files/ambetest103.zip
-
- Serial code based on ser.c sample from http://www.captain.at
-
- Compile with:
-
- gcc dvdongle2.c -o dvdongle2 -Wall -g -O2
-
- Note: This program is not very stable, it sometimes stops part way
- through processing an utterance. I made it just good enough to work
- most of the time, as my purpose was just to process a few sample
- files.
-
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 1990-2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2.1, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <unistd.h>
-#include <fcntl.h>
-#include <errno.h>
-#include <termios.h>
-
-#define MAX_STR 1024
-#define LEN_TARGET_NAME_RESPONSE 14
-#define N 160
-
-/* message parsing state machine states */
-
-#define MSGSTATE_HDR1 0
-#define MSGSTATE_HDR2 1
-#define MSGSTATE_DATA 2
-
-#define LENGTH_MASK 0x1FFF /* mask for message length */
-#define TYPE_MASK 0xE0 /* mask for upper byte of header */
-#define TYPE_C 0x20 /* compressed speech from target */
-#define TYPE_UC 0x40 /* uncompressed speech from target */
-
-#define MAX_MSG_LEN 8192
-
-/* Control items sent to DV Dongle */
-
-char target_name[] = {0x04, 0x20, 0x01, 0x00};
-
-/* note [2] appears to be in error, specifies run as 0x02, stop as 0x01 */
-
-char run_state_stop[] = {0x05, 0x00, 0x18, 0x00, 0x00};
-char run_state_run[] = {0x05, 0x00, 0x18, 0x00, 0x01};
-
-/* Control item codes from DV Dongle */
-
-char data_item_0[] = {0x42, 0x81};
-char data_item_1[] = {0x32, 0xa0};
-char run_state[] = {0x05, 0x00};
-char idle[] = {0x00, 0x00};
-
-typedef struct {
- short header;
- char power;
- char control1;
- short rate[5];
- short unused[3];
- short dtmf;
- short control2;
- short channel_data[12];
-} COMPRESSED;
-
-COMPRESSED c_in;
-COMPRESSED c_out;
-FILE *fin, *fout, *f;
-int fd, c_msg, uc_msg;
-
-int initport(int fd) {
- struct termios options;
-
- // Set the options for the port...
-
- cfmakeraw(&options);
- cfsetispeed(&options, B230400);
- cfsetospeed(&options, B230400);
- options.c_cflag |= (CLOCAL | CREAD);
- tcsetattr(fd, TCSANOW, &options);
-
- return 1;
-}
-
-int getbaud(int fd) {
- struct termios termAttr;
- int inputSpeed = -1;
- speed_t baudRate;
-
- tcgetattr(fd, &termAttr);
-
- /* Get the input speed */
-
- baudRate = cfgetispeed(&termAttr);
- switch (baudRate) {
- case B0: inputSpeed = 0; break;
- case B50: inputSpeed = 50; break;
- case B110: inputSpeed = 110; break;
- case B134: inputSpeed = 134; break;
- case B150: inputSpeed = 150; break;
- case B200: inputSpeed = 200; break;
- case B300: inputSpeed = 300; break;
- case B600: inputSpeed = 600; break;
- case B1200: inputSpeed = 1200; break;
- case B1800: inputSpeed = 1800; break;
- case B2400: inputSpeed = 2400; break;
- case B4800: inputSpeed = 4800; break;
- case B9600: inputSpeed = 9600; break;
- case B19200: inputSpeed = 19200; break;
- case B38400: inputSpeed = 38400; break;
- case B57600: inputSpeed = 38400; break;
- case B115200: inputSpeed = 38400; break;
- case B230400: inputSpeed = 230400; break;
- }
-
- return inputSpeed;
-}
-
-void write_dongle(int fd, char *data, int len) {
- int n;
- //printf(" writing %d bytes\n", len);
- n = write(fd, data, len);
- if (n < 0) {
- perror("write failed");
- exit(1);
- }
-}
-
-void read_dongle(int fd, char *data, int len) {
- int n;
- //printf(" reading %d bytes \n", len);
-
- n = read(fd, data, len);
- if (n < 0) {
- perror("read failed");
- exit(1);
- }
- //printf(" read %d bytes\n", len);
-}
-
-void parse_message(int msg_type, int msg_len, char msg_data[]) {
- short buf[N];
- COMPRESSED *c_out;
-
- //printf("msg_type: 0x%02x msg_len: %d\n", msg_type, msg_len);
-
- /* echo compressed speech frames back to target */
-
- if (msg_type == TYPE_C) {
- c_out = (COMPRESSED*)msg_data;
-#ifdef TMP
- printf("control1 0x%04x\n", c_out->control1 & 0xff);
- printf("rate[0] 0x%04x\n", c_out->rate[0]);
- printf("rate[1] 0x%04x\n", c_out->rate[1]);
- printf("rate[2] 0x%04x\n", c_out->rate[2]);
- printf("rate[3] 0x%04x\n", c_out->rate[3]);
- printf("rate[4] 0x%04x\n", c_out->rate[4]);
- printf("control2 0x%04x\n", c_out->control2 & 0xffff);
- printf("cd[0] 0x%04x\n", c_out->channel_data[0] & 0xffff);
- printf("cd[1] 0x%04x\n", c_out->channel_data[1] & 0xffff);
- printf("cd[2] 0x%04x\n", c_out->channel_data[2] & 0xffff);
- printf("cd[3] 0x%04x\n", c_out->channel_data[3] & 0xffff);
- printf("cd[4] 0x%04x\n", c_out->channel_data[4] & 0xffff);
- printf("cd[5] 0x%04x\n", c_out->channel_data[5] & 0xffff);
- printf("cd[6] 0x%04x\n", c_out->channel_data[6] & 0xffff);
- printf("uc_msg %d\n", uc_msg);
-#endif
- printf("bit errors %d\n", c_out->unused[2]);
- memcpy(&c_in.channel_data,
- &c_out->channel_data,
- sizeof(c_in.channel_data));
-
- write_dongle(fd, data_item_1, sizeof(data_item_1));
- write_dongle(fd, (char*)&c_in, sizeof(c_in));
-
- c_msg++;
- }
-
- /* write speech buffers to disk */
-
- if (msg_type == TYPE_UC) {
-
- if (fout != NULL) {
- fwrite(msg_data, sizeof(char), msg_len-2, fout);
- printf("msg_len %d\n", msg_len);
- }
-
- if (fin != NULL)
- fread(buf, sizeof(short), N, fin);
- else
- memset(buf, 0, sizeof(buf));
-
- write_dongle(fd, data_item_0, sizeof(data_item_0));
- write_dongle(fd, (char*)buf, sizeof(buf));
-
- uc_msg++;
- }
-}
-
-int main(int argc, char **argv) {
- char response[MAX_STR];
- int i;
- int state, next_state;
- short header;
- int msg_type, msg_length;
- char msg_data[MAX_MSG_LEN];
- int n, length;
- int r;
-
- char data;
-
- f = fopen("/tmp/log.txt", "wt");
- assert(f != NULL);
-
- /* open and configure serial port */
-
- fd = open("/dev/ttyUSB0", O_RDWR | O_NOCTTY | O_NDELAY);
- if (fd == -1) {
- perror("open_port: Unable to open /dev/ttyS0 - ");
- exit(1);
- } else {
- fcntl(fd, F_SETFL, 0);
- }
-
- initport(fd);
-
- fin = NULL;
- if (argc >= 2) {
- fin = fopen(argv[1],"rb");
- assert(fin != NULL);
- }
- fout = NULL;
- if (argc == 3) {
- fout = fopen(argv[2],"wb");
- assert(fout != NULL);
- }
-
- /* check DV Dongle is alive */
-
- write_dongle(fd, target_name, sizeof(target_name));
- read_dongle(fd, response, LEN_TARGET_NAME_RESPONSE);
- if (strcmp(&response[4],"DV Dongle") != 0) {
- printf("DV Dongle not responding\n");
- exit(1);
- }
- printf("Found DV Dongle....\n");
-
- c_in.header = 0x13ec;
- c_in.power = 0x0;
- c_in.control1 = 0x0;
-
-#define RATE2000
-#ifdef RATE2000
- c_in.rate[0] = 0x0028; /* 2000 bit/s, no FEC */
- c_in.rate[1] = 0x0000;
- c_in.rate[2] = 0x0000;
- c_in.rate[3] = 0x0000;
- c_in.rate[4] = 0x6248;
-#endif
-
-#ifdef RATE3600_1200
- c_in.rate[0] = 0x5048; /* 3600 bit/s, 1200 bit/s FEC */
- c_in.rate[1] = 0x0001;
- c_in.rate[2] = 0x0000;
- c_in.rate[3] = 0x2412;
- c_in.rate[4] = 0x6860;
-#endif
-
- c_in.unused[0] = 0x0;
- c_in.unused[1] = 0x0;
- c_in.unused[2] = 0x0;
- c_in.dtmf = 0x00ff;
- c_in.control2 = 0x8000;
-
- /* put codec in run mode */
-
- write_dongle(fd, run_state_run, sizeof(run_state_run));
- //write_dongle(fd, data_item_1, sizeof(data_item_1));
- //write_dongle(fd, (char*)&c_in, sizeof(c_in));
-
- state = MSGSTATE_HDR1;
- header = msg_type = msg_length = n = length = 0;
- c_msg = uc_msg = 0;
-
- for(i=0; i<100000; i++) {
- /*
- We can only reliably read one byte at a time. Until I
- realised this there was "much wailing and gnashing of
- teeth". Trying to read() n bytes read() returns n but may
- actually reads some number between 1 and n. So it may only
- read 1 byte int data[] but return n.
- */
- r = read(fd, &data, 1);
- assert(r == 1);
-
- /* used state machine design from ambetest103.zip, SerialPort.cpp */
-
- next_state = state;
- switch(state) {
- case MSGSTATE_HDR1:
- header = data;
- next_state = MSGSTATE_HDR2;
- break;
- case MSGSTATE_HDR2:
- header |= data<<8;
- msg_length = header & LENGTH_MASK;
- msg_type = header & TYPE_MASK;
- //printf("%0x %d\n", msg_type, msg_length);
- if (length == 2) {
- parse_message(msg_type, msg_length, msg_data);
- next_state = MSGSTATE_HDR1;
- }
- else {
- if (msg_length == 0x0)
- length = 8192;
- else
- length = msg_length - 2;
- n = 0;
- next_state = MSGSTATE_DATA;
- }
- break;
- case MSGSTATE_DATA:
- msg_data[n++] = data;
- length--;
- if (length == 0) {
- parse_message(msg_type, msg_length, msg_data);
- next_state = MSGSTATE_HDR1;
- }
- break;
- }
- state = next_state;
- }
-
- printf("finished, c_msg = %d uc_msg = %d\n", c_msg, uc_msg);
-
- write_dongle(fd, run_state_stop, sizeof(run_state_stop));
-
- close(fd);
- if (fin != NULL)
- fclose(fin);
- if (fout != NULL)
- fclose(fout);
- fclose(f);
-
- return 0;
-}
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: extract.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- This program extracts a float file of vectors from a text file
- of vectors. The float files are easier to process quickly
- during VQ training. A subset of the text file VQ may be
- extracted to faciltate split VQ of scaler VQ design.
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#define MAX_STR 2048 /* maximum string length */
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <ctype.h>
-#include <assert.h>
-
-void scan_line(FILE *fp, float f[], int n);
-
-int main(int argc, char *argv[]) {
- FILE *ftext; /* text file of vectors */
- FILE *ffloat; /* float file of vectors */
- int st,en; /* start and end values of vector to copy */
- float *buf; /* ptr to vector read from ftext */
- long lines; /* lines read so far */
-
- if (argc != 5) {
- printf("usage: %s TextFile FloatFile start(1 .. 10) end(1 .. 10)\n", argv[0]);
- exit(1);
- }
-
- /* read command line arguments and open files */
-
- ftext = fopen(argv[1],"rt");
- if (ftext == NULL) {
- printf("Error opening text file: %s\n",argv[1]);
- exit(1);
- }
-
- ffloat = fopen(argv[2],"wb");
- if (ffloat == NULL) {
- printf("Error opening float file: %s\n",argv[2]);
- exit(1);
- }
-
- st = atoi(argv[3]);
- en = atoi(argv[4]);
-
- buf = (float*)malloc(en*sizeof(float));
- if (buf == NULL) {
- printf("Error in malloc()\n");
- exit(1);
- }
-
- lines = 0;
- while(!feof(ftext)) {
- scan_line(ftext, buf, en);
- if (!feof(ftext)) {
- fwrite(&buf[st-1], sizeof(float), en-st+1, ffloat);
- printf("\r%ld lines",++lines);
- }
- }
- printf("\n");
-
- /* clean up and exit */
-
- free(buf);
- fclose(ftext);
- fclose(ffloat);
-
- return 0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: scan_line()
-
- AUTHOR......: David Rowe
- DATE CREATED: 20/2/95
-
- This function reads a vector of floats from a line in a text file.
-
-\*---------------------------------------------------------------------------*/
-
-void scan_line(FILE *fp, float f[], int n)
-/* FILE *fp; file ptr to text file */
-/* float f[]; array of floats to return */
-/* int n; number of floats in line */
-{
- char s[MAX_STR];
- char *ps,*pe;
- int i;
-
- memset(s, 0, MAX_STR);
- ps = pe = fgets(s,MAX_STR,fp);
- if (ps == NULL)
- return;
- for(i=0; i<n; i++) {
- while( isspace(*pe)) pe++;
- while( !isspace(*pe)) pe++;
- sscanf(ps,"%f",&f[i]);
- ps = pe;
- }
-}
-
+++ /dev/null
-/*
- ge_train.c
- Jean Marc Valin Feb 2012
-
- Joint pitch and energy VQ training program
-
- usage:
-
- cat GE | ./ge_train 2 1000000 8 > quantized
-
- The first column is the log2 of the pitch compared to the lowest freq,
- so log2(wo/pi*4000/50) where wo is the frequency your patch outputs. The
- second column is the energy in dB, so 10*log10(1e-4+E)
-*/
-
-/*
- Copyright (C) 2012 Jean-Marc Valin
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <valgrind/memcheck.h>
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <math.h>
-
-#define MIN(a,b) ((a)<(b)?(a):(b))
-//#define COEF 0.0
-
-static float COEF[2] = {0.8, 0.9};
-//static float COEF[2] = {0.0, 0.};
-
-#define MAX_ENTRIES 16384
-
-void compute_weights2(const float *x, const float *xp, float *w, int ndim)
-{
- w[0] = 30;
- w[1] = 1;
- if (x[1]<0)
- {
- w[0] *= .6;
- w[1] *= .3;
- }
- if (x[1]<-10)
- {
- w[0] *= .3;
- w[1] *= .3;
- }
- /* Higher weight if pitch is stable */
- if (fabs(x[0]-xp[0])<.2)
- {
- w[0] *= 2;
- w[1] *= 1.5;
- } else if (fabs(x[0]-xp[0])>.5) /* Lower if not stable */
- {
- w[0] *= .5;
- }
-
- /* Lower weight for low energy */
- if (x[1] < xp[1]-10)
- {
- w[1] *= .5;
- }
- if (x[1] < xp[1]-20)
- {
- w[1] *= .5;
- }
-
- //w[0] = 30;
- //w[1] = 1;
-
- /* Square the weights because it's applied on the squared error */
- w[0] *= w[0];
- w[1] *= w[1];
-
-}
-
-int find_nearest_weighted(const float *codebook, int nb_entries, float *x, const float *w, int ndim)
-{
- int i, j;
- float min_dist = 1e15;
- int nearest = 0;
-
- for (i=0;i<nb_entries;i++)
- {
- float dist=0;
- for (j=0;j<ndim;j++)
- dist += w[j]*(x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
- if (dist<min_dist)
- {
- min_dist = dist;
- nearest = i;
- }
- }
- return nearest;
-}
-
-int quantize_ge(const float *x, const float *codebook1, int nb_entries, float *xq, int ndim)
-{
- int i, n1;
- float err[ndim];
- float w[ndim];
-
- compute_weights2(x, xq, w, ndim);
-
- for (i=0;i<ndim;i++)
- err[i] = x[i]-COEF[i]*xq[i];
- n1 = find_nearest_weighted(codebook1, nb_entries, err, w, ndim);
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = COEF[i]*xq[i] + codebook1[ndim*n1+i];
- err[i] -= codebook1[ndim*n1+i];
- }
- return 0;
-}
-
-void split(float *codebook, int nb_entries, int ndim)
-{
- int i,j;
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- {
- float delta = .01*(rand()/(float)RAND_MAX-.5);
- codebook[i*ndim+j] += delta;
- codebook[(i+nb_entries)*ndim+j] = codebook[i*ndim+j] - delta;
- }
- }
-}
-
-
-void update_weighted(float *data, float *weight, int nb_vectors, float *codebook, int nb_entries, int ndim)
-{
- int i,j;
- float count[MAX_ENTRIES][ndim];
- int nearest[nb_vectors];
-
- //fprintf(stderr, "weighted: %d %d\n", nb_entries, ndim);
- for (i=0;i<nb_entries;i++)
- for (j=0;j<ndim;j++)
- count[i][j] = 0;
-
- for (i=0;i<nb_vectors;i++)
- {
- nearest[i] = find_nearest_weighted(codebook, nb_entries, data+i*ndim, weight+i*ndim, ndim);
- }
- for (i=0;i<nb_entries*ndim;i++)
- codebook[i] = 0;
-
- for (i=0;i<nb_vectors;i++)
- {
- int n = nearest[i];
- for (j=0;j<ndim;j++)
- {
- float w = sqrt(weight[i*ndim+j]);
- count[n][j]+=w;
- codebook[n*ndim+j] += w*data[i*ndim+j];
- }
- }
-
- //float w2=0;
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- codebook[i*ndim+j] *= (1./count[i][j]);
- //w2 += (count[i]/(float)nb_vectors)*(count[i]/(float)nb_vectors);
- }
- //fprintf(stderr, "%f / %d\n", 1./w2, nb_entries);
-}
-
-void vq_train_weighted(float *data, float *weight, int nb_vectors, float *codebook, int nb_entries, int ndim)
-{
- int i, j, e;
- e = 1;
- for (j=0;j<ndim;j++)
- codebook[j] = 0;
- for (i=0;i<nb_vectors;i++)
- for (j=0;j<ndim;j++)
- codebook[j] += data[i*ndim+j];
- for (j=0;j<ndim;j++)
- codebook[j] *= (1./nb_vectors);
-
-
- while (e< nb_entries)
- {
-#if 1
- split(codebook, e, ndim);
- e<<=1;
-#else
- split1(codebook, e, data, nb_vectors, ndim);
- e++;
-#endif
- fprintf(stderr, "%d\n", e);
- for (j=0;j<10;j++)
- update_weighted(data, weight, nb_vectors, codebook, e, ndim);
- }
-}
-
-
-int main(int argc, char **argv)
-{
- int i,j;
- int nb_vectors, nb_entries, ndim;
- float *data, *pred, *codebook, *codebook2, *codebook3;
- float *weight, *weight2, *weight3;
- float *delta;
- double err[2] = {0, 0};
- double werr[2] = {0, 0};
- double wsum[2] = {0, 0};
-
- ndim = atoi(argv[1]);
- nb_vectors = atoi(argv[2]);
- nb_entries = 1<<atoi(argv[3]);
-
- data = malloc(nb_vectors*ndim*sizeof(*data));
- weight = malloc(nb_vectors*ndim*sizeof(*weight));
- weight2 = malloc(nb_vectors*ndim*sizeof(*weight2));
- weight3 = malloc(nb_vectors*ndim*sizeof(*weight3));
- pred = malloc(nb_vectors*ndim*sizeof(*pred));
- codebook = malloc(nb_entries*ndim*sizeof(*codebook));
- codebook2 = malloc(nb_entries*ndim*sizeof(*codebook2));
- codebook3 = malloc(nb_entries*ndim*sizeof(*codebook3));
-
- for (i=0;i<nb_vectors;i++)
- {
- if (feof(stdin))
- break;
- for (j=0;j<ndim;j++)
- {
- scanf("%f ", &data[i*ndim+j]);
- }
- }
- nb_vectors = i;
- VALGRIND_CHECK_MEM_IS_DEFINED(data, nb_entries*ndim);
-
- for (i=0;i<nb_vectors;i++)
- {
- if (i==0)
- compute_weights2(data+i*ndim, data+i*ndim, weight+i*ndim, ndim);
- else
- compute_weights2(data+i*ndim, data+(i-1)*ndim, weight+i*ndim, ndim);
- }
- for (i=0;i<ndim;i++)
- pred[i] = data[i];
- for (i=1;i<nb_vectors;i++)
- {
- for (j=0;j<ndim;j++)
- pred[i*ndim+j] = data[i*ndim+j] - COEF[j]*data[(i-1)*ndim+j];
- }
-
- VALGRIND_CHECK_MEM_IS_DEFINED(pred, nb_entries*ndim);
- vq_train_weighted(pred, weight, nb_vectors, codebook, nb_entries, ndim);
- printf("%d %d\n", ndim, nb_entries);
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- {
- printf("%f ", codebook[i*ndim+j]);
- }
- printf("\n");
- }
-
- delta = malloc(nb_vectors*ndim*sizeof(*data));
- float xq[2] = {0,0};
- for (i=0;i<nb_vectors;i++)
- {
- //int nearest = find_nearest_weighted(codebook, nb_entries, &pred[i*ndim], &weight[i*ndim], ndim);
- quantize_ge(&data[i*ndim], codebook, nb_entries, xq, ndim);
- //printf("%f %f\n", xq[0], xq[1]);
- for (j=0;j<ndim;j++)
- {
- delta[i*ndim+j] = xq[j]-data[i*ndim+j];
- err[j] += (delta[i*ndim+j])*(delta[i*ndim+j]);
- werr[j] += weight[i*ndim+j]*(delta[i*ndim+j])*(delta[i*ndim+j]);
- wsum[j] += weight[i*ndim+j];
- //delta[i*ndim+j] = pred[i*ndim+j] - codebook[nearest*ndim+j];
- //printf("%f ", delta[i*ndim+j]);
- //err[j] += (delta[i*ndim+j])*(delta[i*ndim+j]);
- }
- //printf("\n");
- }
- fprintf(stderr, "GE RMS error: %f %f\n", sqrt(err[0]/nb_vectors), sqrt(err[1]/nb_vectors));
- fprintf(stderr, "Weighted GE error: %f %f\n", sqrt(werr[0]/wsum[0]), sqrt(werr[1]/wsum[1]));
-
- return 0;
-}
+++ /dev/null
-/*
- genampdata.c
-
- Generates test sparse amplitude data for vqtrainsp testing.
-*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-#include <assert.h>
-#include "../src/defines.h"
-
-typedef struct {
- float real;
- float imag;
-} COMP;
-
-#define NVEC 200000
-#define D 2
-#define E 8
-
-int main(void) {
- FILE *f=fopen("testamp.flt", "wb");
- int i, j, m, L, index;
- float amp, noisey_amp, pitch, Wo;
- float sparse_pe[MAX_AMP];
-
- #ifdef TEST1
- /* D fixed amplitude vectors of E elements long,
- with D=2, E=8:
-
- $ ./vqtrainsp testamp.flt 2 8 test.txt
-
- test.txt should be same as training data.
- */
- for(i=0; i<E; i++) {
- amp = i+1;
- for(j=0; j<D; j++)
- fwrite(&, sizeof(float), 1, f);
- }
- #endif
-
- #ifdef TEST2
- /*
- Bunch of amps uniformly distributed between -1 and 1. With e
- entry "codebook" (1 dimensional vector or scalar):
-
- $ ./vqtrainsp testamp.flt 1 e test.txt
-
-
- should get std dev of 1/(e*sqrt(3))
- */
-
- for(i=0; i<NVEC; i++) {
- amp = 1.0 - 2.0*rand()/RAND_MAX;
- fwrite(&, sizeof(float), 1, f);
- }
- #endif
-
- #define TEST3
- #ifdef TEST3
- /*
- Data for testing training of spare amplitudes. Similar to TEST1, each
- sparse vector is set to the same amplitude.
-
- /vqtrainsp testamp.flt 20 8 test.txt
-
- */
-
- for(i=0; i<NVEC; i++) {
- for(amp=1.0; amp<=8.0; amp++) {
- pitch = P_MIN + (P_MAX-P_MIN)*((float)rand()/RAND_MAX);
- Wo = TWO_PI/pitch;
- L = floor(PI/Wo);
- //printf("pitch %f Wo %f L %d\n", pitch, Wo, L);
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe[m] = 0.0;
- }
-
- for(m=1; m<=L; m++) {
- index = MAX_AMP*m*Wo/PI;
- assert(index < MAX_AMP);
- noisey_amp = amp + 0.2*(1.0 - 2.0*rand()/RAND_MAX);
- sparse_pe[index] = noisey_amp;
- #ifdef DBG
- if (m < MAX_AMP/8)
- printf(" %4.3f ", noisey_amp);
- #endif
- }
- #ifdef DBG
- printf("\n");
- #endif
-
- fwrite(sparse_pe, sizeof(float), MAX_AMP/8, f);
- }
- }
-
- #endif
-
- return 0;
-}
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: genlsp.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- This program genrates a text file of LSP vectors from an input
- speech file.
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#define P 12 /* LP order */
-#define LSP_DELTA1 0.01 /* grid spacing for LSP root searches */
-#define NW 279 /* frame size in samples */
-#define N 80 /* frame to frame shift */
-#define THRESH 40.0 /* threshold energy/sample for frame inclusion */
-#define PI 3.141592654 /* mathematical constant */
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include "lpc.h" /* LPC analysis functions */
-#include "lsp.h" /* LSP encode/decode functions */
-
-int switch_present(sw,argc,argv)
- char sw[]; /* switch in string form */
- int argc; /* number of command line arguments */
- char *argv[]; /* array of command line arguments in string form */
-{
- int i; /* loop variable */
-
- for(i=1; i<argc; i++)
- if (!strcmp(sw,argv[i]))
- return(i);
-
- return 0;
-}
-
-int main(int argc, char *argv[]) {
- FILE *fspc; /* input file ptr for test database */
- FILE *flsp; /* output text file of LSPs */
- short buf[N]; /* input frame of speech samples */
- float Sn[NW]; /* float input speech samples */
- float ak[P+1]; /* LPCs for current frame */
- float lsp[P]; /* LSPs for current frame */
- float lsp_prev[P]; /* LSPs for previous frame */
- float E; /* frame energy */
- long f; /* number of frames */
- long af; /* number frames with "active" speech */
- float Eres; /* LPC residual energy */
- int i;
- int roots;
- int unstables;
- int lspd, log, lspdt;
- float diff;
-
- /* Initialise ------------------------------------------------------*/
-
- if (argc < 3) {
- printf("usage: %s RawFile LSPTextFile [--lspd] [--log] [--lspdt] \n", argv[0]);
- exit(1);
- }
-
- /* Open files */
-
- fspc = fopen(argv[1],"rb");
- if (fspc == NULL) {
- printf("Error opening input SPC file: %s",argv[1]);
- exit(1);
- }
-
- flsp = fopen(argv[2],"wt");
- if (flsp == NULL) {
- printf("Error opening output LSP file: %s",argv[2]);
- exit(1);
- }
-
- lspd = switch_present("--lspd", argc, argv);
- log = switch_present("--log", argc, argv);
- lspdt = switch_present("--lspdt", argc, argv);
-
- for(i=0; i<NW; i++)
- Sn[i] = 0.0;
-
- /* Read SPC file, and determine aks[] for each frame ------------------*/
-
- f = af = 0;
- unstables = 0;
- while(fread(buf,sizeof(short),N,fspc) == N) {
-
- for(i=0; i<NW-N; i++)
- Sn[i] = Sn[i+N];
- E = 0.0;
- for(i=0; i<N; i++) {
- Sn[i+NW-N] = buf[i];
- E += Sn[i]*Sn[i];
- }
-
- E = 0.0;
- for(i=0; i<NW; i++) {
- E += Sn[i]*Sn[i];
- }
- E = 10.0*log10(E/NW);
-
- /* If energy high enough, include this frame */
-
- f++;
- if (E > THRESH) {
- af++;
- printf("Active Frame: %ld unstables: %d\n",af, unstables);
-
- find_aks(Sn, ak, NW, P, &Eres);
- roots = lpc_to_lsp(ak, P , lsp, 5, LSP_DELTA1);
- if (roots == P) {
- if (lspd) {
- if (log) {
- fprintf(flsp,"%f ",log10(lsp[0]));
- for(i=1; i<P; i++) {
- diff = lsp[i]-lsp[i-1];
- if (diff < (PI/4000.0)*25.0) diff = (PI/4000.0)*25.0;
- fprintf(flsp,"%f ",log10(diff));
- }
- }
- else {
- fprintf(flsp,"%f ",lsp[0]);
- for(i=1; i<P; i++)
- fprintf(flsp,"%f ",lsp[i]-lsp[i-1]);
- }
-
- fprintf(flsp,"\n");
-
- }
- else if (lspdt) {
- for(i=0; i<P; i++)
- fprintf(flsp,"%f ",lsp[i]-lsp_prev[i]);
- fprintf(flsp,"\n");
-
- }
- else {
- if (log) {
- for(i=0; i<P; i++)
- fprintf(flsp,"%f ",log10(lsp[i]));
- fprintf(flsp,"\n");
- }
- else {
- for(i=0; i<P; i++)
- fprintf(flsp,"%f ",lsp[i]);
- fprintf(flsp,"\n");
- }
-
- }
- memcpy(lsp_prev, lsp, sizeof(lsp));
- }
- else
- unstables++;
- }
- }
-
- printf("%3.2f %% active frames\n", 100.0*(float)af/f);
- fclose(fspc);
- fclose(flsp);
-
- return 0;
-}
-
+++ /dev/null
-/*
- genphdata.c
-
- Generates test phase data for vqtrainph testing.
-*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-#include <assert.h>
-#include "../src/defines.h"
-
-typedef struct {
- float real;
- float imag;
-} COMP;
-
-#define NVEC 100000
-#define D 2
-#define E 8
-
-int main(void) {
- FILE *f=fopen("testph.flt", "wb");
- int i, m, L, index;
- float angle, noisey_angle, pitch, Wo;
- COMP c;
- COMP sparse_pe[MAX_AMP];
-
- #ifdef TEST1
- for(i=0; i<D*E; i++) {
- c.real = cos(i*TWO_PI/(M*D));
- c.imag = sin(i*TWO_PI/(M*D));
- fwrite(&c, sizeof(COMP), 1, f);
- }
- #endif
-
- #ifdef TEST2
- /*
- Bunch of random phases, should get std dev per element of
- pi/(sqrt(3)*pow(2,b/D)), or 0.321 for (b=5, D=2):
-
- ./vqtrainph testph.flt 2 32 test.txt
- */
-
- for(i=0; i<NVEC; i++) {
- angle = PI*(1.0 - 2.0*rand()/RAND_MAX);
- c.real = cos(angle);
- c.imag = sin(angle);
- fwrite(&c, sizeof(COMP), 1, f);
- }
- #endif
-
- #define TEST3
- #ifdef TEST3
- /*
- Data for testing training in sparse phases. No correlation, so
- should be same performance as TEST2. Attempting to train a
- MAX_AMP/4 = 20 (first 1 kHz) phase quantiser.
-
- */
-
- angle = 0;
- for(i=0; i<NVEC; i++) {
- pitch = P_MIN + (P_MAX-P_MIN)*((float)rand()/RAND_MAX);
- //pitch = 40;
- Wo = TWO_PI/pitch;
- L = floor(PI/Wo);
- //printf("pitch %f Wo %f L %d\n", pitch, Wo, L);
-
- for(m=0; m<MAX_AMP; m++) {
- sparse_pe[m].real = 0.0;
- sparse_pe[m].imag = 0.0;
- }
-
- angle += PI/8;
- for(m=1; m<=L; m++) {
- noisey_angle = angle + (PI/16)*(1.0 - 2.0*rand()/RAND_MAX);
- //angle = (PI/16)*(1.0 - 2.0*rand()/RAND_MAX);
- index = MAX_AMP*m*Wo/PI;
- assert(index < MAX_AMP);
- sparse_pe[index].real = cos(noisey_angle);
- sparse_pe[index].imag = sin(noisey_angle);
- }
-
- fwrite(&sparse_pe, sizeof(COMP), MAX_AMP/4, f);
- }
-
- #endif
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: genres.c
- AUTHOR......: David Rowe
- DATE CREATED: 24/8/09
-
- Generates a file of LPC residual samples from original speech.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <lpc.h>
-
-#define N 160
-#define P 10
-
-int main(int argc, char *argv[])
-{
- FILE *fin,*fres; /* input and output files */
- short buf[N]; /* buffer of 16 bit speech samples */
- float Sn[P+N]; /* input speech samples */
- float res[N]; /* residual after LPC filtering */
- float E;
- float ak[P+1]; /* LP coeffs */
-
- int frames; /* frames processed so far */
- int i; /* loop variables */
-
- if (argc < 3) {
- printf("usage: %s InputFile ResidualFile\n", argv[0]);
- exit(1);
- }
-
- /* Open files */
-
- if ((fin = fopen(argv[1],"rb")) == NULL) {
- printf("Error opening input file: %s\n",argv[1]);
- exit(0);
- }
-
- if ((fres = fopen(argv[2],"wb")) == NULL) {
- printf("Error opening output residual file: %s\n",argv[2]);
- exit(0);
- }
-
- /* Initialise */
-
- frames = 0;
- for(i=0; i<P; i++) {
- Sn[i] = 0.0;
- }
-
- /* Main loop */
-
- while( (fread(buf,sizeof(short),N,fin)) == N) {
- frames++;
- for(i=0; i<N; i++)
- Sn[P+i] = (float)buf[i];
-
- /* Determine {ak} and filter to find residual */
-
- find_aks(&Sn[P], ak, N, P, &E);
- inverse_filter(&Sn[P], ak, N, res, P);
- for(i=0; i<N; i++)
- buf[i] = (short)res[i];
- fwrite(buf,sizeof(short),N,fres);
- }
-
- fclose(fin);
- fclose(fres);
-
- return 0;
-}
+++ /dev/null
-225
-250
-275
-300
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
+++ /dev/null
-2900
-3100
-3300
-3500
-
+++ /dev/null
-325
-350
-375
-400
-425
-450
-475
-500
-525
-550
-575
-600
-625
-650
-675
-700
+++ /dev/null
-500
-550
-600
-650
-700
-750
-800
-850
-900
-950
-1000
-1050
-1100
-1150
-1200
-1250
+++ /dev/null
-700
-800
-900
-1000
-1100
-1200
-1300
-1400
-1500
-1600
-1700
-1800
-1900
-2000
-2100
-2200
+++ /dev/null
-6 4096
-1.081234 1.578844 1.855572 1.937313 2.532441 2.649806
-1.062804 1.450009 1.839560 1.956503 2.488847 2.653463
-1.101587 1.361019 1.833584 1.932414 2.505176 2.629812
-1.079058 1.376855 1.872688 1.955078 2.541337 2.633780
-1.095536 1.631036 1.866273 2.066987 2.506661 2.570431
-1.093059 1.561358 1.772473 2.123863 2.547475 2.618258
-1.093649 1.500206 1.786047 2.077115 2.483767 2.572542
-1.035022 1.485983 1.678652 2.079363 2.402344 2.513315
-1.231720 1.630566 1.849906 2.023447 2.467212 2.571610
-1.206362 1.478193 1.855647 2.009197 2.437429 2.552382
-1.204249 1.495756 1.846404 2.039977 2.500628 2.592437
-1.272025 1.438353 1.854503 2.038713 2.518717 2.620094
-1.298912 1.483356 1.838869 1.983659 2.488374 2.597006
-1.385591 1.500184 1.819431 1.981705 2.505537 2.612529
-1.413670 1.566546 1.767180 1.994490 2.569613 2.625244
-1.469053 1.626083 1.751768 2.041187 2.608951 2.658775
-1.489505 1.617638 1.689177 2.053852 2.662243 2.705533
-1.431122 1.535578 1.647319 1.810924 2.575767 2.692196
-1.411673 1.606174 1.730361 1.969368 2.628110 2.691849
-1.341020 1.639970 2.197392 2.281319 2.449714 2.625998
-1.319877 1.674826 2.101177 2.281732 2.499782 2.611482
-1.274620 1.610124 1.901436 2.235657 2.518178 2.628876
-1.172210 1.365637 1.784703 1.904448 2.538076 2.646190
-1.096161 1.350109 1.754990 1.869673 2.486568 2.605496
-1.036538 1.326195 1.729890 1.862116 2.461192 2.575454
-1.016529 1.277247 1.688801 1.808376 2.462981 2.576244
-0.968031 1.329007 1.716412 1.821357 2.481150 2.561950
-0.940641 1.283342 1.767876 1.860537 2.503139 2.594903
-0.926995 1.243331 1.738909 1.901001 2.449501 2.557636
-0.839883 1.237117 1.702150 1.812616 2.421388 2.492978
-0.924474 1.188075 1.757524 1.824899 2.455944 2.611065
-0.964230 1.207274 1.666224 1.876812 2.507149 2.580412
-0.989772 1.189729 1.693447 1.807142 2.445712 2.561953
-0.919183 1.203118 1.673832 1.772614 2.385797 2.511668
-0.978552 1.175420 1.613855 1.726871 2.328959 2.516699
-1.014543 1.254251 1.587284 1.756626 2.403061 2.510828
-1.096718 1.231168 1.557405 1.843944 2.463584 2.555458
-1.168771 1.351177 1.613931 1.831029 2.476269 2.581218
-1.176515 1.264150 1.564916 1.760486 2.483522 2.581045
-1.017969 1.249828 1.424493 1.593545 2.458340 2.525030
-1.053988 1.216029 1.517421 1.851941 2.342751 2.502327
-0.908986 1.250795 1.593917 1.887100 2.373089 2.530129
-0.993871 1.164018 1.616620 1.775732 2.569459 2.658570
-1.102483 1.386153 1.573681 1.785642 2.317931 2.508557
-1.207240 1.390831 1.551049 1.850614 2.335983 2.494330
-0.905032 1.416478 1.580046 1.841825 2.503807 2.601603
-0.795890 1.107933 1.597705 2.015496 2.402148 2.534611
-0.732401 1.158610 1.557468 1.938003 2.626415 2.705430
-0.859670 1.129062 1.671859 1.953992 2.514790 2.615870
-0.921647 1.245355 1.683753 1.894457 2.599645 2.716564
-0.845409 1.194759 1.767314 1.844514 2.589767 2.716944
-0.977678 1.141401 1.667109 1.923833 2.632008 2.689070
-0.951137 1.122551 1.714183 1.885895 2.535763 2.672112
-1.029949 1.159554 1.739443 1.928325 2.488185 2.623518
-0.925634 1.225929 1.751801 1.970749 2.532895 2.621066
-1.012300 1.211427 1.793946 1.885857 2.467267 2.572492
-0.993978 1.137467 1.743472 1.840886 2.390082 2.566385
-0.989822 1.173068 1.687559 1.948929 2.325527 2.473423
-0.955854 1.237231 1.807406 2.116766 2.391031 2.502779
-1.103361 1.357985 1.852236 2.097091 2.392749 2.553242
-1.128873 1.440897 1.927907 2.176697 2.407985 2.544276
-1.316127 1.575436 1.964565 2.158944 2.485840 2.576132
-1.469605 1.772101 1.954837 2.164070 2.399616 2.481917
-1.506520 1.754882 2.018413 2.249491 2.486272 2.607615
-1.524190 1.776451 2.054579 2.275694 2.584977 2.669083
-1.518000 1.850281 2.026435 2.301875 2.577528 2.669180
-1.422050 1.788979 1.967476 2.184773 2.596851 2.699678
-1.208408 1.434703 1.923623 2.003769 2.602930 2.685007
-1.221170 1.436565 1.879969 2.033402 2.498146 2.695421
-1.217714 1.375982 1.908609 1.973031 2.480559 2.645396
-1.200348 1.412239 1.863276 2.054536 2.409232 2.646327
-1.439453 1.675933 2.064707 2.273226 2.606450 2.696215
-1.547568 1.956021 2.083785 2.387077 2.634316 2.711216
-1.745365 1.995260 2.176270 2.409488 2.632251 2.707416
-1.819289 1.982164 2.210166 2.452194 2.603770 2.664517
-1.669555 1.940179 2.100875 2.386942 2.530819 2.630866
-1.597684 1.945913 2.072836 2.338891 2.544245 2.608247
-1.656152 1.888690 1.984550 2.301133 2.510775 2.586360
-1.618800 1.898863 2.024738 2.291312 2.440530 2.560289
-1.481284 1.826210 1.971921 2.192909 2.417020 2.530293
-1.318733 1.581540 1.845445 2.163997 2.389227 2.505418
-1.341326 1.565852 1.802875 2.218482 2.430769 2.545834
-1.318506 1.412657 1.677620 2.182351 2.372753 2.476532
-1.243720 1.456674 1.665712 2.126711 2.332874 2.438449
-1.152502 1.458855 1.582937 2.037521 2.342102 2.428296
-1.025383 1.407599 1.551528 1.846789 2.282863 2.385436
-0.876560 1.384326 1.582900 1.741935 2.239923 2.338453
-0.953781 1.441879 1.592404 1.764174 2.294091 2.474201
-0.899968 1.454031 1.634363 1.724312 2.353403 2.597502
-0.784159 1.423933 1.737258 1.855960 2.390032 2.614540
-0.802442 1.397066 1.658548 1.816788 2.429390 2.500099
-0.863071 1.318492 1.646022 1.812971 2.398098 2.503855
-0.896870 1.306239 1.671592 1.902175 2.466526 2.601523
-0.999503 1.304292 1.708420 1.899036 2.512342 2.655191
-1.045277 1.266302 1.669631 1.846323 2.517066 2.637484
-1.038456 1.158529 1.643778 1.865279 2.583201 2.658938
-1.026317 1.219306 1.768348 1.840920 2.538168 2.673329
-1.080965 1.215431 1.730192 1.836927 2.236858 2.608870
-1.101801 1.431508 1.752078 1.918964 2.091244 2.538958
-1.178729 1.297314 1.724099 1.850753 2.310291 2.621525
-1.151182 1.239683 1.754792 1.850524 2.539101 2.705992
-1.202697 1.300604 1.763340 1.867428 2.470717 2.664655
-1.261122 1.368681 1.753282 1.846646 2.461515 2.652599
-1.263075 1.364289 1.797670 1.876939 2.543725 2.660224
-1.320149 1.415925 1.809830 1.903217 2.515554 2.648236
-1.339872 1.459354 1.806677 1.924576 2.491477 2.587047
-1.355170 1.451772 1.763405 1.944161 2.472633 2.561167
-1.327925 1.428910 1.704448 1.914816 2.397366 2.503472
-1.307600 1.415352 1.616295 1.840793 2.322166 2.470994
-1.248247 1.349207 1.617615 1.772735 2.250680 2.486533
-1.096572 1.355681 1.626115 1.941988 2.313846 2.498213
-1.012526 1.342839 1.647854 1.907164 2.435934 2.533191
-0.944393 1.399280 1.642998 1.931993 2.331977 2.489908
-0.883306 1.402338 1.706359 2.025366 2.373713 2.543710
-0.829559 1.235771 1.712746 2.184853 2.386736 2.544183
-0.923799 1.513109 1.703086 2.105291 2.476476 2.555162
-0.772688 1.443301 1.656120 2.053011 2.450442 2.532517
-0.776285 1.403196 1.734016 1.935257 2.464085 2.566799
-0.782396 1.418811 1.758875 1.973225 2.548330 2.610298
-0.789572 1.411082 1.771533 2.060410 2.540262 2.631254
-0.774326 1.288019 1.837269 1.960951 2.512420 2.581626
-0.811751 1.274027 1.810006 1.885738 2.565463 2.639219
-0.844982 1.320831 1.873915 1.944600 2.561048 2.661720
-0.881256 1.695357 1.906981 2.078886 2.618546 2.678654
-1.099890 1.727818 1.971319 2.153135 2.509688 2.602947
-1.173850 1.685437 1.917457 2.147432 2.383055 2.567035
-1.101548 1.543219 1.820605 2.055324 2.338724 2.585028
-0.975012 1.379716 1.776625 2.033293 2.194151 2.518224
-0.967054 1.082459 1.618973 2.077928 2.206837 2.370886
-1.009607 1.120613 1.534181 2.088528 2.282936 2.420584
-0.899159 1.208523 1.423691 1.970324 2.287269 2.498904
-0.879682 1.314480 1.479489 1.689360 2.209743 2.285765
-1.033473 1.243843 1.473137 1.667992 2.159422 2.255044
-1.048412 1.255890 1.536997 1.820047 2.142252 2.313751
-1.048246 1.189264 1.705109 1.835993 2.105450 2.372062
-1.034320 1.138878 1.514616 1.829657 2.170447 2.425608
-1.103878 1.217645 1.622150 1.805848 2.027526 2.376811
-1.087235 1.195012 1.559018 1.895036 2.250122 2.379205
-1.130013 1.293868 1.692397 1.858880 2.197201 2.349063
-1.162892 1.304601 1.691021 1.969323 2.268614 2.430288
-1.151808 1.257932 1.673832 1.902017 2.189155 2.458708
-1.168445 1.271828 1.557328 2.084152 2.308031 2.420367
-1.235095 1.340187 1.656794 2.095155 2.283187 2.409638
-1.252394 1.355363 1.609848 2.085193 2.332714 2.488870
-1.226314 1.343994 1.673049 2.215533 2.459996 2.546921
-1.408182 1.566449 1.701931 2.155097 2.540243 2.588591
-1.303998 1.548995 1.653578 2.128738 2.589470 2.633320
-1.312529 1.488936 1.690548 1.982880 2.558390 2.622521
-1.303590 1.485664 1.772996 1.991417 2.555629 2.650059
-1.257202 1.528917 1.880489 2.045674 2.400087 2.567493
-1.294719 1.634324 1.911539 2.046657 2.438083 2.611133
-1.328444 1.716065 1.850301 2.021260 2.507052 2.612864
-1.138077 1.269039 1.792588 1.898148 2.530410 2.653563
-1.024794 1.145542 1.688222 1.812928 2.425037 2.650928
-1.056656 1.178042 1.590336 1.747349 2.368449 2.618711
-0.994299 1.110839 1.632651 1.730538 2.337688 2.550296
-0.960030 1.103482 1.632800 1.745079 2.197252 2.530535
-0.952099 1.078914 1.704160 1.837306 2.319065 2.544307
-0.901034 1.074801 1.653662 1.788590 2.393831 2.533117
-0.970595 1.130054 1.568353 1.820966 2.445105 2.563373
-0.883200 1.029140 1.480583 1.884365 2.321620 2.470715
-0.817959 0.941844 1.410138 1.540709 2.174043 2.482774
-0.772028 0.888033 1.490117 1.717092 2.324349 2.560462
-0.874200 1.020101 1.571479 1.746811 2.437393 2.561332
-0.827282 1.010026 1.605382 1.750680 2.261846 2.481604
-0.790605 1.149000 1.653820 1.781055 2.358642 2.491606
-0.746581 0.961080 1.604908 1.879005 2.319270 2.551585
-0.845418 0.969530 1.696169 1.890927 2.301880 2.621489
-0.826083 1.016050 1.658604 1.852554 2.435884 2.572744
-0.804260 0.948999 1.684490 2.103337 2.475054 2.575853
-0.837016 1.029999 1.676991 1.796645 2.498023 2.631032
-0.779629 0.917041 1.607073 1.868904 2.459568 2.628902
-0.802981 0.922379 1.556141 1.967845 2.595450 2.692512
-0.821239 0.952349 1.585249 2.095797 2.593711 2.655934
-0.819528 1.109552 1.526845 1.767514 2.637798 2.710511
-0.846222 1.055717 1.707281 1.838626 2.113999 2.501403
-0.956553 1.439848 1.724902 1.939820 2.145194 2.431913
-1.334292 1.551594 1.721399 2.019173 2.178003 2.329439
-1.247359 1.571459 1.834521 2.114156 2.268206 2.489811
-1.223145 1.573420 1.846247 2.016089 2.219280 2.457849
-1.239932 1.537791 1.822800 2.046476 2.444455 2.578055
-1.299681 1.557742 1.798304 2.080692 2.393370 2.575201
-1.273117 1.474131 1.814869 2.014907 2.405011 2.602918
-1.229029 1.448502 1.757153 2.050565 2.417160 2.594614
-1.206296 1.515099 1.788958 2.042150 2.368561 2.585804
-1.158903 1.544803 1.861448 2.066653 2.405246 2.590991
-1.203257 1.479859 1.833516 2.070616 2.431802 2.585701
-1.170767 1.555780 1.826674 2.077078 2.467476 2.619408
-1.116279 1.593527 1.824249 2.160817 2.427806 2.600491
-1.250314 1.617299 1.962648 2.152242 2.531239 2.631433
-1.352996 1.645245 2.070194 2.180379 2.612026 2.688774
-1.460334 1.917189 2.086815 2.314592 2.641184 2.723059
-1.557095 1.916613 2.056898 2.263201 2.640329 2.702797
-1.410674 1.903388 2.077833 2.222944 2.615402 2.694117
-1.340491 1.804040 2.040016 2.149565 2.607705 2.678152
-1.090681 1.321064 1.862736 1.983775 2.475855 2.592436
-1.002459 1.265507 1.813017 1.904336 2.499258 2.626541
-1.051386 1.161286 1.832534 1.955080 2.502338 2.624753
-0.942516 1.064243 1.669560 1.977253 2.464181 2.598328
-0.869608 0.984141 1.454614 1.956177 2.507893 2.617868
-0.972489 1.135467 1.529146 1.729979 2.411574 2.571077
-1.051275 1.149410 1.547524 1.827149 2.511333 2.617618
-1.079744 1.191206 1.539363 1.944728 2.545236 2.632156
-1.182063 1.260030 1.596098 2.084659 2.511859 2.579406
-1.172004 1.352761 1.462749 2.015059 2.625356 2.679374
-1.200545 1.322975 1.515601 1.769202 2.523140 2.666825
-1.228092 1.307135 1.734031 1.914746 2.244815 2.562025
-1.176188 1.321661 1.782310 1.882580 2.271364 2.521450
-1.150025 1.486223 1.774146 1.970935 2.385075 2.612636
-1.103163 1.455003 1.720622 1.899593 2.356715 2.591383
-1.070467 1.386313 1.746928 1.891984 2.367512 2.543572
-0.953610 1.176163 1.643545 1.919980 2.372057 2.572461
-1.052319 1.405171 1.688954 1.831668 2.542879 2.632479
-0.996802 1.441427 1.684462 1.821948 2.595992 2.658845
-1.026550 1.334938 1.740944 1.840382 2.571653 2.678967
-1.108319 1.200840 1.706127 1.999085 2.514665 2.648206
-1.133324 1.219468 1.747774 2.013077 2.406643 2.640363
-1.142143 1.218723 1.814638 1.951061 2.430067 2.666180
-1.081563 1.207089 1.846455 1.946284 2.339144 2.612659
-1.146374 1.238625 1.874251 1.968098 2.427377 2.595630
-1.069408 1.393128 1.859759 1.941816 2.374471 2.538181
-1.060221 1.402928 1.784643 1.909954 2.080852 2.375424
-0.893759 1.225333 1.741426 1.895488 2.062213 2.441777
-0.911307 1.301394 1.651487 1.798169 1.996879 2.208655
-1.102905 1.503307 1.707775 1.808533 1.958631 2.311679
-1.149446 1.328058 1.738279 1.904609 2.061868 2.257965
-1.121345 1.230563 1.748776 1.950661 2.086466 2.389286
-0.948970 1.101893 1.676635 1.875393 2.016817 2.296681
-1.035082 1.162231 1.641377 1.952709 2.100948 2.358717
-0.994183 1.114307 1.547601 1.773728 1.966081 2.336299
-1.025110 1.139705 1.585236 1.912371 2.102465 2.482426
-0.955352 1.062216 1.659060 1.848407 2.043281 2.487426
-1.049103 1.120549 1.446982 1.949018 2.026898 2.560590
-1.012432 1.138276 1.367936 2.008468 2.189441 2.422416
-1.082028 1.234911 1.351755 1.827170 2.173158 2.300241
-1.094359 1.235138 1.416416 1.922593 2.128232 2.419413
-1.034512 1.151307 1.492358 1.980846 2.149036 2.365312
-1.013088 1.154539 1.459958 1.943044 2.281758 2.397269
-0.987103 1.274347 1.561873 1.917460 2.334292 2.495651
-0.989791 1.289172 1.623138 1.982329 2.345033 2.548052
-1.042013 1.225970 1.610016 1.974800 2.406311 2.537036
-1.019690 1.323725 1.679076 1.983690 2.443023 2.561932
-1.030978 1.249914 1.753285 1.970302 2.442750 2.577102
-1.078647 1.281367 1.821676 2.046994 2.512487 2.614303
-1.042503 1.318276 1.817538 1.977740 2.538774 2.643473
-1.033751 1.323431 1.885960 1.993635 2.587127 2.648293
-1.084158 1.434121 1.899660 1.974483 2.661669 2.717102
-1.095790 1.481301 1.916550 1.970409 2.671232 2.730973
-1.147960 1.553068 1.884541 1.960664 2.501839 2.667876
-1.137776 1.498910 1.962620 2.047239 2.537310 2.642351
-1.108862 1.435492 1.955490 2.195866 2.514284 2.601530
-1.191071 1.557850 1.984542 2.270790 2.541878 2.642064
-1.110737 1.553081 1.978127 2.211052 2.613375 2.706641
-1.114093 1.728016 1.975042 2.124483 2.602927 2.681942
-1.148485 1.627087 1.968135 2.073898 2.607358 2.686667
-1.109004 1.450655 1.961102 2.058609 2.611646 2.694610
-1.095904 1.318763 1.866640 2.096294 2.574677 2.658840
-1.116558 1.367968 1.922533 2.016505 2.549444 2.646230
-1.129468 1.529113 1.942204 2.003339 2.527872 2.699919
-1.139050 1.679536 1.945866 2.032922 2.537427 2.642172
-1.219207 1.599421 1.929600 2.011091 2.539104 2.705280
-1.233969 1.556201 1.930999 2.084786 2.578580 2.675834
-1.234430 1.653741 2.033213 2.256759 2.637546 2.699663
-1.255288 1.475044 2.022543 2.289234 2.587690 2.703947
-1.253389 1.472198 1.956397 2.211186 2.574243 2.676099
-1.126854 1.587210 1.950824 2.031487 2.416846 2.614459
-1.007062 1.608304 1.896229 1.986335 2.223017 2.524028
-1.067280 1.729449 1.931889 2.045329 2.164850 2.400910
-0.946660 1.699777 1.870624 1.981832 2.135670 2.447688
-1.002686 1.728563 1.939905 2.072520 2.274792 2.467485
-1.148787 1.600550 2.003063 2.128026 2.409105 2.506525
-1.191365 1.359514 1.908437 2.116985 2.369079 2.529393
-1.229740 1.316359 1.901465 2.001169 2.368350 2.575701
-1.167453 1.284078 1.851548 2.056283 2.446292 2.573763
-1.177049 1.282978 1.796076 2.014566 2.409896 2.524428
-1.166550 1.281729 1.804132 1.938592 2.383050 2.543803
-1.144710 1.266197 1.755782 1.865513 2.354119 2.575142
-1.168465 1.283561 1.695054 1.817537 2.302788 2.529561
-1.093474 1.316111 1.625831 1.791050 2.303314 2.408563
-1.072994 1.218877 1.586912 1.725308 2.219203 2.343524
-0.946241 1.172838 1.426290 1.551682 2.192575 2.321727
-1.001802 1.174980 1.507444 1.697862 2.240802 2.478241
-0.992564 1.257780 1.429092 1.819825 2.234153 2.434915
-0.933586 1.255559 1.372464 1.686266 2.265977 2.349467
-0.987914 1.162881 1.404420 1.563483 2.227668 2.485371
-1.058576 1.185833 1.325383 1.445585 2.164512 2.455141
-1.042271 1.149610 1.389036 1.473828 1.906671 2.390132
-0.966952 1.075537 1.288155 1.405105 2.061861 2.451990
-0.901530 1.194476 1.354732 1.705750 2.325032 2.434812
-1.038418 1.292428 1.527305 1.909844 2.230333 2.465135
-1.336010 1.441693 1.849134 2.208029 2.414400 2.532513
-1.436224 1.645653 2.008636 2.198160 2.502278 2.601413
-1.424341 1.684427 1.929812 2.122504 2.512280 2.604860
-1.452203 1.722988 1.962207 2.156659 2.484102 2.584594
-1.481999 1.735238 1.971190 2.222801 2.512305 2.623621
-1.392556 1.721267 1.940304 2.174966 2.488944 2.601854
-1.243347 1.558461 1.809822 1.990890 2.381971 2.537485
-1.199294 1.421504 1.763108 1.990880 2.358918 2.489556
-1.217773 1.348784 1.714665 1.916837 2.379728 2.456961
-1.219523 1.326854 1.719656 1.838075 2.299329 2.435406
-1.263073 1.353656 1.787228 1.918973 2.320389 2.448246
-1.270962 1.373799 1.718185 1.857935 2.366922 2.481748
-1.284351 1.368069 1.793907 1.895081 2.356790 2.524604
-1.244789 1.353657 1.782947 1.928688 2.225716 2.379949
-1.269283 1.368726 1.719184 1.909677 2.267163 2.491540
-1.249305 1.338194 1.799918 1.917097 2.274691 2.533224
-1.179498 1.259046 1.802972 1.927327 2.228930 2.503637
-1.140961 1.245902 1.708660 1.923794 2.243465 2.557345
-1.063955 1.209030 1.737289 1.945349 2.338697 2.573092
-1.003475 1.109161 1.745131 1.902188 2.308443 2.601614
-0.937618 1.077537 1.747804 1.869648 2.205055 2.570449
-0.885099 1.192451 1.790545 1.876157 2.360305 2.598108
-0.803485 0.966415 1.768458 1.928742 2.196723 2.530460
-0.797205 1.120717 1.776585 1.878573 2.370357 2.614341
-0.831514 1.059080 1.808800 1.905483 2.448208 2.573050
-0.806597 0.967446 1.829385 1.963682 2.358632 2.653242
-0.699378 0.851831 1.739446 1.933943 2.516377 2.655249
-0.739203 1.033985 1.902113 2.010327 2.494149 2.629822
-0.945605 1.079706 1.796352 2.039543 2.581863 2.699784
-0.843512 1.304861 1.835452 2.036832 2.600217 2.677826
-0.970152 1.414374 1.854051 1.957787 2.596045 2.665425
-1.067282 1.438542 1.888429 2.067094 2.531016 2.643177
-1.117619 1.563112 1.886324 2.218866 2.530223 2.624080
-1.209656 1.626913 1.943700 2.187427 2.555090 2.658675
-1.338891 1.812879 2.030890 2.305204 2.569275 2.661165
-1.303367 1.840104 2.035985 2.286745 2.614227 2.713359
-1.193428 1.727354 1.926203 2.184400 2.574784 2.631812
-1.063515 1.717188 1.903657 2.119051 2.444811 2.497667
-1.062175 1.188948 1.810480 2.044978 2.322378 2.578780
-1.073201 1.177557 1.654731 2.023264 2.200369 2.442874
-1.027815 1.165415 1.669466 1.859614 2.202142 2.462466
-1.035584 1.148236 1.604900 1.872549 2.257851 2.551682
-1.007205 1.131087 1.579146 1.969788 2.331637 2.507912
-0.908594 1.005601 1.463269 2.072372 2.304356 2.407363
-0.981614 1.126428 1.280565 1.886853 2.101922 2.487836
-1.006764 1.132557 1.253088 1.718315 2.189249 2.436605
-0.899830 1.156538 1.260748 1.696712 2.116655 2.228297
-0.896996 1.246551 1.436874 1.645194 2.073642 2.149130
-0.965481 1.069671 1.446489 1.949492 2.091582 2.298331
-0.898113 1.058765 1.617556 1.941551 2.113568 2.374743
-0.769481 1.159379 1.597415 1.959851 2.283842 2.418197
-0.908091 1.305340 1.473570 1.862549 2.164147 2.331091
-0.924282 1.334689 1.563201 2.043541 2.406015 2.515756
-0.972939 1.381971 1.549985 2.021238 2.268488 2.419332
-1.032229 1.484031 1.620031 1.952234 2.267322 2.486440
-1.005234 1.354692 1.620203 1.777917 2.223067 2.497574
-1.072742 1.245035 1.661666 1.819389 2.260496 2.468700
-1.134470 1.250480 1.737034 1.868971 2.303204 2.466426
-1.145935 1.293264 1.728505 1.950979 2.350982 2.504021
-1.226356 1.329795 1.750777 1.982144 2.347843 2.553027
-1.234801 1.328107 1.696728 2.060564 2.437310 2.535600
-1.247128 1.360496 1.742955 1.961348 2.474080 2.668447
-1.234736 1.329837 1.688634 1.913331 2.442940 2.627695
-1.230430 1.326635 1.697588 1.806044 2.381473 2.618535
-1.188567 1.273079 1.708983 1.969001 2.340683 2.588959
-1.204284 1.331218 1.835523 2.141256 2.463226 2.583492
-1.202374 1.397220 1.863749 2.155165 2.599733 2.681191
-1.217581 1.333297 1.763898 1.994983 2.601835 2.684817
-1.272368 1.364451 1.776352 1.952098 2.563424 2.676170
-1.330173 1.434654 1.825090 1.938032 2.579405 2.666102
-1.383550 1.514770 1.774712 2.134998 2.528583 2.614711
-1.488234 1.631245 1.795942 2.180588 2.497787 2.585930
-1.497854 1.598429 1.760395 1.985719 2.538066 2.622220
-1.446514 1.555686 1.675484 1.899620 2.547070 2.637129
-1.420188 1.651758 1.888119 2.201558 2.498716 2.624372
-1.524851 1.748918 1.939479 2.132594 2.426619 2.604303
-1.588214 1.786968 1.965710 2.123251 2.417433 2.579888
-1.603052 1.805249 1.932723 2.088062 2.490882 2.628467
-1.521714 1.853040 1.968163 2.198421 2.530921 2.597229
-1.496309 1.785807 2.001979 2.206169 2.574155 2.645280
-1.405201 1.500557 1.908673 2.179223 2.543732 2.645774
-1.369555 1.501308 1.848796 2.089859 2.551118 2.643621
-1.395377 1.488644 1.872404 2.028116 2.530256 2.599192
-1.354582 1.508972 1.848875 1.976677 2.504926 2.579355
-1.325752 1.411326 1.837129 1.970792 2.502717 2.584831
-1.264497 1.390436 1.764758 2.087338 2.519279 2.625037
-1.280904 1.355652 1.790288 1.995707 2.502567 2.587359
-1.267443 1.360843 1.858033 2.035632 2.509375 2.584870
-1.238902 1.487541 1.786660 2.080354 2.480913 2.582137
-1.228708 1.441140 1.715963 1.893335 2.507070 2.565131
-1.167347 1.397307 1.672051 1.923535 2.438392 2.523520
-1.169232 1.356809 1.567433 1.950379 2.378945 2.468006
-1.240244 1.470896 1.629735 2.024684 2.376716 2.454875
-1.370859 1.665288 1.831505 2.176433 2.486403 2.586565
-1.513368 1.657039 1.965014 2.298013 2.532148 2.623007
-1.446940 1.612676 1.929087 2.232303 2.466210 2.565149
-1.430659 1.664527 1.882163 2.234579 2.421664 2.527294
-1.511551 1.658934 1.944043 2.198499 2.451946 2.588348
-1.539441 1.741360 2.111062 2.229922 2.438935 2.615056
-1.510948 1.846893 2.061790 2.202452 2.484110 2.572628
-1.366393 1.611652 2.079365 2.260070 2.467062 2.588032
-1.383579 1.641339 1.997349 2.226153 2.491435 2.611630
-1.381458 1.706898 1.963061 2.125553 2.596797 2.681115
-1.360033 1.558255 1.949661 2.054826 2.599573 2.714554
-1.379339 1.491775 1.925897 2.046337 2.539371 2.696047
-1.313275 1.469403 1.863111 2.141749 2.553959 2.668104
-1.201520 1.563000 1.925029 2.093014 2.476606 2.614413
-0.965563 1.662126 1.836100 2.071866 2.530046 2.578446
-0.976435 1.635119 1.844726 2.005117 2.553083 2.614153
-1.098159 1.549476 1.826426 1.907908 2.490671 2.625630
-0.971599 1.431927 1.818186 1.923193 2.493841 2.568117
-0.881008 1.272866 1.901429 1.959221 2.513674 2.596017
-0.915929 1.478770 1.955701 2.082549 2.494350 2.585776
-1.008177 1.579393 1.898198 2.139172 2.477629 2.551209
-0.937399 1.507567 1.803910 1.922590 2.546047 2.637297
-0.848413 1.358228 1.783925 1.906229 2.477012 2.588525
-0.863404 1.488629 1.835502 1.930032 2.465498 2.545317
-0.844376 1.622282 1.826798 2.048364 2.490552 2.545809
-0.869731 1.705034 1.854703 2.111605 2.517014 2.593453
-0.862235 1.623015 1.899372 2.028710 2.527844 2.574800
-0.931658 1.576339 1.853614 1.975118 2.542237 2.614786
-0.848799 1.588406 1.847097 1.955899 2.534073 2.584561
-0.737814 1.457219 1.829993 1.966203 2.501271 2.579455
-0.786199 1.100080 1.860369 1.964282 2.419364 2.566134
-0.728962 1.040841 1.773818 1.963733 2.356948 2.578866
-0.733093 1.147783 1.789774 1.909293 2.349819 2.481103
-0.785959 1.280236 1.730487 1.926696 2.346913 2.422480
-0.784924 1.446821 1.669690 1.935370 2.368317 2.459601
-0.758523 1.466915 1.805902 1.946588 2.352213 2.426335
-0.767907 1.544295 1.768171 2.003937 2.239037 2.386192
-0.896374 1.562074 1.716926 1.903301 2.308243 2.430582
-0.834530 1.504812 1.737424 1.917731 2.409279 2.493291
-0.896027 1.406949 1.730026 1.903326 2.431247 2.539722
-1.039666 1.364116 1.806278 1.948174 2.440690 2.557972
-1.093454 1.412357 1.833723 1.940104 2.489654 2.564450
-1.190180 1.386167 1.848700 1.956202 2.481553 2.580885
-1.243158 1.350416 1.811797 1.893593 2.467576 2.613520
-1.221986 1.308711 1.815913 1.911989 2.417533 2.600995
-1.228372 1.343619 1.763163 1.872602 2.394885 2.582719
-1.278387 1.389710 1.738500 1.870267 2.420854 2.532852
-1.211636 1.401793 1.710146 1.811019 2.363826 2.482240
-1.161497 1.400684 1.766674 1.891745 2.392605 2.495922
-1.114937 1.405487 1.718336 1.927418 2.356818 2.468335
-1.074680 1.452959 1.668715 1.898094 2.336526 2.443457
-1.006705 1.356254 1.629477 1.848470 2.313894 2.426320
-0.966452 1.457923 1.654693 1.906386 2.320056 2.418339
-0.939007 1.519988 1.667014 1.989416 2.390669 2.488951
-0.946840 1.483985 1.701087 2.105572 2.391444 2.490066
-0.909129 1.501060 1.665371 2.004939 2.256700 2.389841
-0.958919 1.390613 1.680082 2.107156 2.297251 2.440839
-1.462160 1.588562 1.808539 2.109890 2.264826 2.417467
-1.301642 1.673806 1.892518 2.168109 2.477558 2.561621
-1.152769 1.529326 1.783781 2.014354 2.446614 2.560929
-1.128698 1.493018 1.748156 1.930275 2.530674 2.621591
-1.164356 1.496855 1.767664 1.871136 2.607250 2.684794
-1.122714 1.380513 1.762236 1.875604 2.441522 2.732814
-1.173906 1.545927 1.843801 1.933791 2.123448 2.629011
-1.155439 1.465806 1.793876 1.928550 2.168553 2.609610
-1.147812 1.484543 1.816424 1.908762 2.262620 2.704081
-1.185870 1.393524 1.811853 1.881115 2.544291 2.735905
-1.153304 1.451135 1.855404 1.888619 2.603314 2.738077
-1.208854 1.582363 1.784858 1.880089 2.596481 2.727884
-1.194841 1.542896 1.919056 2.023145 2.551891 2.634186
-1.230327 1.492063 1.937225 2.133605 2.615726 2.690226
-1.258764 1.581307 1.980070 2.138762 2.599037 2.691033
-1.220691 1.572961 1.917212 2.177536 2.599585 2.702012
-1.258143 1.556630 1.871736 2.132633 2.585514 2.673307
-1.233770 1.598238 1.849957 2.013674 2.542859 2.634481
-1.269759 1.560794 1.865225 2.076328 2.521082 2.617443
-1.116561 1.680882 1.781694 1.920497 2.592211 2.675845
-1.048209 1.662996 1.817400 1.915170 2.484585 2.623077
-0.954241 1.619674 1.813457 1.881694 2.550667 2.631971
-0.964363 1.579747 1.728712 1.862126 2.567566 2.636332
-1.296922 1.646884 1.889259 2.069271 2.320227 2.481389
-1.232775 1.619596 1.955470 2.066559 2.335277 2.456514
-1.238971 1.351788 1.877566 2.166413 2.317967 2.474389
-1.180292 1.388353 1.607451 1.950835 2.210855 2.477718
-1.124001 1.423538 1.617323 1.826801 2.206068 2.444078
-1.147794 1.487048 1.627974 1.926015 2.278418 2.486526
-1.092654 1.499725 1.623041 1.880156 2.411660 2.648649
-1.115294 1.468690 1.607626 1.814459 2.356904 2.576088
-1.176045 1.424631 1.614229 1.966337 2.352676 2.570354
-1.211051 1.467429 1.617777 1.851487 2.389770 2.591860
-1.287681 1.464858 1.633790 1.856231 2.349748 2.565320
-1.298585 1.495223 1.639003 1.942642 2.415390 2.518116
-1.309890 1.431142 1.757192 1.977209 2.414871 2.520878
-1.392241 1.477414 1.811303 1.909687 2.440417 2.573891
-1.414942 1.515382 1.858997 2.127937 2.490674 2.635418
-1.490435 1.565967 1.952412 2.049065 2.499936 2.600180
-1.485068 1.734116 1.997368 2.089376 2.524766 2.608159
-1.507131 1.787198 2.048100 2.128356 2.533629 2.624653
-1.485217 1.772591 2.048100 2.144373 2.595743 2.679785
-1.560042 1.744521 2.076144 2.156837 2.615057 2.698771
-1.506276 1.855445 2.064190 2.144534 2.585665 2.687788
-1.592877 1.903451 2.084530 2.163395 2.496904 2.633589
-1.609454 1.870860 2.119821 2.186594 2.599505 2.697819
-1.594779 1.855348 2.025620 2.142545 2.572299 2.637841
-1.527194 1.714086 2.076267 2.185169 2.526549 2.631137
-1.518012 1.628010 2.039263 2.134528 2.453843 2.576361
-1.531312 1.678082 2.035179 2.146889 2.504859 2.584171
-1.508627 1.632606 1.965140 2.148678 2.496640 2.592746
-1.499896 1.599423 1.913687 2.036860 2.450192 2.538166
-1.481158 1.583812 1.884461 2.013870 2.359497 2.481100
-1.475736 1.569698 1.799993 1.916182 2.329218 2.535901
-1.498641 1.623604 1.792824 1.945217 2.358627 2.490727
-1.431128 1.574627 1.743263 2.006116 2.347765 2.508896
-1.427064 1.536583 1.790690 1.943028 2.344465 2.452652
-1.436838 1.542023 1.758917 1.925622 2.242913 2.416844
-1.419788 1.509038 1.863320 1.995399 2.275792 2.424732
-1.424396 1.510477 1.882887 2.179017 2.304708 2.455667
-1.366051 1.461194 1.935323 2.147551 2.263420 2.465785
-1.407395 1.564972 1.981125 2.103440 2.445291 2.565104
-1.597013 1.877015 2.068503 2.270312 2.499356 2.604888
-1.484981 1.818125 2.149815 2.337593 2.504753 2.589439
-1.487878 1.937181 2.118271 2.308368 2.511781 2.604626
-1.682297 1.977033 2.192290 2.373676 2.522931 2.611282
-1.749459 1.905682 2.218271 2.352013 2.574227 2.681484
-1.676221 1.936512 2.237179 2.343782 2.535908 2.661271
-1.723362 1.989915 2.271236 2.413144 2.550828 2.649366
-1.756006 1.996913 2.312656 2.461484 2.625420 2.708736
-1.499770 1.763295 2.158871 2.346879 2.592716 2.682851
-1.747521 1.927133 2.248936 2.410841 2.604121 2.690881
-1.670354 1.938258 2.247669 2.447135 2.657540 2.730040
-1.669237 1.959610 2.179318 2.440527 2.588429 2.640800
-1.780231 2.015138 2.164810 2.399021 2.581913 2.646942
-1.739561 1.967219 2.065694 2.364479 2.589977 2.649441
-1.605008 1.875105 2.018901 2.227404 2.541181 2.603541
-1.511246 1.892601 2.027827 2.148110 2.520001 2.608199
-1.363362 1.568768 1.910845 2.057695 2.463506 2.558819
-1.338497 1.483825 1.883695 2.067074 2.448950 2.577904
-1.369193 1.437863 1.845222 2.078464 2.428504 2.615891
-1.377698 1.498294 1.867666 2.164965 2.492547 2.570908
-1.408098 1.487760 1.872414 2.097948 2.447272 2.551716
-1.402363 1.531952 1.897693 2.126667 2.419162 2.551442
-1.456496 1.554631 1.841067 2.095807 2.421290 2.561761
-1.434931 1.529146 1.795336 2.163704 2.446465 2.530309
-1.391108 1.495499 1.869679 2.161228 2.381406 2.532017
-1.388934 1.534466 1.797003 2.102941 2.398508 2.521270
-1.358571 1.471303 1.760049 2.100883 2.350197 2.546548
-1.276599 1.519215 1.779419 2.095819 2.442938 2.665941
-1.206661 1.457865 1.760464 2.244280 2.495881 2.644848
-1.214611 1.460274 1.979019 2.239454 2.398324 2.634473
-1.275473 1.473470 1.878570 2.203117 2.475028 2.687851
-1.291712 1.399288 1.813807 2.194118 2.502758 2.614888
-1.260058 1.397998 1.924890 2.186721 2.511667 2.644548
-1.210634 1.326713 1.897594 2.107441 2.460079 2.711722
-1.202657 1.319235 1.892634 2.079859 2.379418 2.679891
-0.967019 1.105970 1.761322 2.107426 2.328428 2.593155
-0.947746 1.035797 1.393730 2.061233 2.300744 2.668280
-0.996167 1.215029 1.378995 1.861982 2.329665 2.605022
-1.008823 1.198481 1.313837 1.693525 2.360746 2.604824
-1.054057 1.218510 1.368106 1.738006 2.174906 2.546071
-1.021568 1.133991 1.369174 1.935639 2.267798 2.544415
-1.033742 1.227769 1.451289 2.005917 2.412620 2.595031
-1.065155 1.168636 1.530185 2.061499 2.410743 2.485478
-1.121227 1.281283 1.432233 1.909928 2.202734 2.509308
-1.170032 1.306041 1.494945 1.981910 2.202815 2.351735
-1.152630 1.266186 1.620999 2.057673 2.214453 2.381642
-1.228128 1.313272 1.751468 2.118469 2.263417 2.453888
-1.307832 1.398650 1.799753 2.125735 2.260615 2.451800
-1.360104 1.477444 1.835740 2.121870 2.291563 2.499791
-1.398477 1.492966 1.806519 2.107140 2.241410 2.434146
-1.351212 1.462506 1.726393 2.122387 2.285789 2.421844
-1.297203 1.498868 1.766246 2.157839 2.376714 2.497158
-1.377349 1.518971 1.803789 2.191150 2.356374 2.478897
-1.289165 1.553241 1.674591 2.112634 2.403345 2.473877
-1.188972 1.700336 1.834324 2.055585 2.599531 2.700414
-1.077038 1.667666 1.902189 2.045693 2.602910 2.700056
-1.072057 1.272462 1.843743 1.901183 2.586254 2.720558
-1.084385 1.392072 1.823558 1.901299 2.589426 2.680029
-1.106319 1.441363 1.766145 1.853724 2.549356 2.627414
-1.094566 1.550024 1.771922 1.870952 2.559682 2.628051
-1.041899 1.598552 1.813702 1.928485 2.545630 2.671501
-1.090204 1.610510 1.812559 2.019257 2.556321 2.608793
-1.016528 1.626657 1.742411 2.041925 2.541538 2.602247
-1.075570 1.647752 1.870667 2.073970 2.574597 2.628798
-1.126656 1.586213 1.792572 1.982408 2.629180 2.725561
-1.027776 1.542665 1.831396 1.956878 2.603010 2.668523
-1.111897 1.543416 1.861469 1.942917 2.621957 2.672864
-1.080512 1.583194 1.857304 1.958456 2.633597 2.695142
-1.132239 1.449156 1.884949 1.977000 2.607850 2.709420
-1.232769 1.612605 1.960435 2.071693 2.644678 2.727118
-1.325014 1.779901 1.967304 2.113871 2.547837 2.668723
-1.404585 1.644448 2.058088 2.257112 2.519116 2.634613
-1.413485 1.609401 2.002521 2.184102 2.587532 2.696153
-1.354020 1.593877 2.014439 2.122204 2.617254 2.721812
-1.373822 1.656758 1.992185 2.189875 2.548725 2.702514
-1.421181 1.611084 1.958071 2.123616 2.569835 2.648136
-1.379179 1.620195 1.922636 2.093948 2.550690 2.641857
-1.367726 1.656675 1.838447 1.992123 2.596226 2.654039
-1.394553 1.750623 1.872269 2.038430 2.553215 2.623595
-1.464021 1.741591 1.912988 2.150261 2.565594 2.648823
-1.461132 1.809059 1.954612 2.209898 2.570276 2.642519
-1.434520 1.770834 1.904022 2.217315 2.631183 2.686995
-1.375527 1.631662 1.885996 2.086587 2.600503 2.671257
-1.339213 1.568724 1.817375 2.085568 2.591336 2.666455
-1.504403 1.779590 2.057141 2.272445 2.534600 2.634655
-1.474504 1.746318 2.044711 2.137376 2.474545 2.630529
-1.557045 1.755017 2.039661 2.080935 2.661339 2.741743
-1.573452 1.715361 2.056726 2.098368 2.691640 2.743685
-1.511431 1.831887 1.991585 2.156042 2.624346 2.709519
-1.501907 1.714027 2.012931 2.079434 2.554662 2.690409
-1.547183 1.671908 1.977966 2.104057 2.507158 2.614807
-1.563264 1.635971 1.990128 2.123718 2.563823 2.633190
-1.587772 1.697791 2.007538 2.127360 2.588839 2.656541
-1.618303 1.722230 2.008488 2.131284 2.618167 2.687641
-1.580078 1.684932 2.000646 2.087829 2.613984 2.687671
-1.572775 1.736323 1.961536 2.144351 2.641248 2.687943
-1.538985 1.652845 1.952108 2.156038 2.639302 2.685734
-1.537130 1.622797 1.963527 2.075940 2.612204 2.679327
-1.537449 1.633250 1.986524 2.075675 2.542791 2.643796
-1.543228 1.772021 2.053914 2.142473 2.536411 2.690489
-1.621800 1.829997 2.052741 2.210858 2.583215 2.665837
-1.609565 1.935324 2.146682 2.393315 2.597212 2.670556
-1.560818 1.935543 2.191435 2.444376 2.609921 2.692602
-1.704277 1.874585 2.010256 2.380095 2.528658 2.604802
-1.624784 1.837785 1.925361 2.193011 2.497168 2.569432
-1.556125 1.832653 1.986935 2.189317 2.453204 2.531630
-1.347428 1.669666 1.943932 2.108052 2.506631 2.608423
-1.278409 1.497251 1.838413 2.073920 2.454553 2.592324
-1.271049 1.415120 1.758107 2.232460 2.422770 2.554672
-1.260337 1.356714 1.913167 2.225895 2.380602 2.557250
-1.223099 1.307974 1.784088 2.207517 2.362875 2.487786
-1.249454 1.538164 1.716600 1.998319 2.362110 2.465531
-1.208014 1.503064 1.761303 1.917077 2.448048 2.525133
-1.151848 1.461146 1.783945 1.946886 2.452561 2.556307
-1.165555 1.347773 1.799946 1.920752 2.437876 2.546954
-1.109788 1.310449 1.815889 1.923381 2.427304 2.602804
-1.091990 1.233639 1.789609 1.925036 2.467804 2.611170
-1.052323 1.194748 1.809895 1.914231 2.390180 2.556318
-1.032267 1.189488 1.775623 1.889690 2.393248 2.640830
-0.992854 1.169627 1.814159 1.912252 2.320268 2.634324
-1.054415 1.177746 1.762755 1.907196 2.266178 2.516301
-1.029545 1.167365 1.780060 1.973540 2.227843 2.613887
-1.067777 1.184807 1.741322 1.919129 2.121959 2.500789
-1.167843 1.263051 1.778629 1.900717 2.150811 2.568660
-1.247027 1.323672 1.811046 1.934590 2.184022 2.674617
-1.331781 1.426137 1.785144 1.966030 2.114558 2.541825
-1.360900 1.444142 1.862535 1.949748 2.426744 2.646105
-1.408538 1.451788 1.866918 2.014230 2.478842 2.705911
-1.405554 1.483551 1.874980 1.960293 2.502764 2.662540
-1.442367 1.544656 1.883354 1.987590 2.562980 2.647761
-1.480719 1.536202 1.881818 2.018874 2.582349 2.661791
-1.513078 1.583246 1.895764 1.987154 2.586166 2.676009
-1.497760 1.602088 1.831006 1.985404 2.564090 2.643635
-1.497065 1.564915 1.844643 1.957697 2.539930 2.677163
-1.468106 1.523747 1.865842 1.940079 2.607970 2.684862
-1.468104 1.564389 1.858916 1.982405 2.606481 2.709686
-1.422735 1.519196 1.806791 1.891590 2.614823 2.703893
-1.396871 1.476698 1.776404 2.013253 2.607847 2.665988
-1.391532 1.504565 1.830535 2.081544 2.611020 2.720808
-1.372885 1.645062 1.833360 2.015761 2.631341 2.701342
-1.331289 1.747404 1.897953 2.146510 2.586685 2.658273
-1.503178 1.734690 1.914996 2.282089 2.598389 2.679187
-1.465242 1.711762 2.025166 2.284078 2.653659 2.717393
-1.423402 1.768761 2.084406 2.277880 2.636443 2.711524
-1.423821 1.724472 2.032594 2.300309 2.603340 2.686111
-1.433184 1.818868 2.053883 2.409241 2.628605 2.699461
-1.509846 1.793493 2.052637 2.357768 2.644126 2.718058
-1.575730 1.851530 2.032958 2.374899 2.583530 2.662235
-1.501264 1.780829 1.998554 2.329265 2.505605 2.606743
-1.460060 1.763209 1.912334 2.214416 2.494328 2.577616
-1.444041 1.657674 1.895357 2.148549 2.478458 2.595455
-1.454287 1.619858 1.935887 2.189754 2.478831 2.594880
-1.377243 1.642180 1.919668 2.142842 2.421514 2.541038
-1.051059 1.421021 1.830399 2.021216 2.373690 2.548829
-0.964571 1.071641 1.394899 2.151202 2.371776 2.464951
-0.966306 1.181025 1.302213 2.014819 2.375093 2.435135
-0.895560 1.207845 1.335308 1.823923 2.239924 2.363100
-1.006776 1.203093 1.317821 1.873977 2.336638 2.408782
-1.054129 1.225595 1.379006 2.024687 2.333311 2.421550
-1.090202 1.224770 1.409674 2.013195 2.245364 2.353229
-1.076475 1.203972 1.563890 2.033954 2.203362 2.369101
-1.127967 1.249133 1.664693 2.080426 2.256625 2.469541
-1.202013 1.429684 1.793680 2.080715 2.339984 2.460053
-1.517223 1.673904 1.927925 2.203642 2.386760 2.520143
-1.586618 1.786240 2.041674 2.198999 2.416371 2.581194
-1.593300 1.808548 2.148779 2.250278 2.372090 2.532412
-1.657294 1.783458 2.150393 2.258130 2.453915 2.616209
-1.571489 1.792659 2.117652 2.350385 2.577192 2.666949
-1.301994 1.729750 1.974424 2.093250 2.593899 2.663024
-1.100218 1.563399 1.919910 2.059220 2.562974 2.637757
-1.025074 1.540738 1.811898 2.057911 2.491877 2.603248
-1.015309 1.473504 1.802588 2.013084 2.436758 2.605319
-1.022065 1.158479 1.689786 2.183529 2.383778 2.492374
-1.212476 1.453108 1.823947 2.061442 2.396186 2.536578
-1.126243 1.452934 1.809587 2.071074 2.408943 2.549557
-0.880332 1.324785 1.621337 1.967251 2.313156 2.426927
-0.749583 1.358409 1.575073 1.870590 2.279227 2.377431
-0.901917 1.290215 1.674425 1.954410 2.233361 2.391524
-0.850971 1.252102 1.657646 1.816460 2.183885 2.328806
-0.881480 1.284101 1.698159 1.844661 2.341820 2.440909
-0.874499 1.182682 1.709489 1.917452 2.365966 2.499649
-0.833751 1.231132 1.803319 1.918020 2.459092 2.546881
-0.850970 1.127086 1.772073 1.855222 2.487580 2.582865
-0.881650 1.114802 1.820703 1.959079 2.521753 2.598731
-0.803558 1.150285 1.798477 1.952675 2.538917 2.634898
-0.867833 0.990496 1.832275 1.929767 2.547660 2.681084
-0.865057 1.067437 1.773263 1.860188 2.558331 2.702216
-0.832529 0.985960 1.756367 1.862925 2.438281 2.623782
-0.850804 1.060553 1.892217 1.984007 2.483774 2.661123
-0.873803 1.041984 1.746198 1.932438 2.338221 2.554585
-0.958594 1.103471 1.836438 1.936783 2.393758 2.573200
-1.014831 1.140873 1.825933 2.013713 2.401490 2.609423
-1.075369 1.457644 1.900463 2.033493 2.314190 2.490949
-1.201715 1.736170 1.914076 2.066503 2.386907 2.476963
-1.215217 1.873613 2.065903 2.182990 2.374981 2.489555
-1.620207 1.851261 2.111542 2.342798 2.527494 2.633887
-1.683879 1.860372 2.126009 2.404344 2.562983 2.636158
-1.703817 1.934383 2.133673 2.393214 2.601932 2.682469
-1.526877 1.900128 2.151100 2.361638 2.575171 2.658979
-1.587253 1.881390 2.129945 2.267860 2.577863 2.657840
-1.539163 1.871344 2.190283 2.360385 2.624615 2.705636
-1.625747 1.862181 2.120094 2.339463 2.592159 2.682142
-1.679527 1.920689 2.161166 2.317106 2.648896 2.712106
-1.635199 1.922826 2.174839 2.407399 2.630046 2.709271
-1.454186 1.975699 2.151850 2.371342 2.609179 2.685790
-1.672439 2.011404 2.183017 2.463917 2.652956 2.711525
-1.612105 1.987481 2.102582 2.293346 2.616125 2.670264
-1.528075 1.895073 2.053582 2.232503 2.544912 2.624122
-1.420355 1.683500 1.963431 2.159418 2.536725 2.620131
-1.456320 1.693132 1.969234 2.164744 2.587162 2.677588
-1.481106 1.637541 1.992642 2.178479 2.548138 2.632755
-1.488517 1.591174 2.016501 2.123324 2.528663 2.614918
-1.477429 1.651519 1.962894 2.102183 2.543300 2.618840
-1.473856 1.622302 1.992230 2.080352 2.572688 2.644430
-1.478216 1.633404 1.931202 2.064133 2.552282 2.629338
-1.452477 1.676763 1.945911 2.084750 2.600973 2.668889
-1.411560 1.706182 1.890249 2.169616 2.567319 2.650155
-1.383398 1.664625 1.803260 2.108612 2.595771 2.646221
-1.434597 1.645007 1.871751 2.115488 2.528958 2.660256
-1.444542 1.581834 1.898636 2.094074 2.528453 2.631504
-1.465558 1.562000 1.841423 2.051601 2.559944 2.632318
-1.499287 1.581053 1.857454 2.098994 2.511597 2.604341
-1.528680 1.651347 1.871308 2.071232 2.562548 2.622460
-1.514467 1.633477 1.778604 2.123502 2.606102 2.662390
-1.301476 1.683914 1.796063 2.170750 2.644952 2.691777
-1.154424 1.626935 1.749221 1.996410 2.579238 2.652899
-1.117912 1.569269 1.795380 1.885300 2.376717 2.739725
-1.251786 1.625672 1.839263 1.991314 2.350120 2.655047
-1.412131 1.694235 1.839362 1.998399 2.445222 2.739684
-1.370157 1.687258 1.879731 2.006454 2.329014 2.632962
-1.174780 1.729049 1.887372 2.013905 2.259388 2.557737
-1.317917 1.737041 1.878083 1.979313 2.175363 2.634863
-1.140130 1.586450 1.932219 2.027711 2.236840 2.484950
-1.100136 1.600099 1.851286 1.972375 2.604826 2.649449
-1.111969 1.525982 1.842706 2.011491 2.601600 2.669393
-1.080825 1.492576 1.810233 1.965312 2.556725 2.645171
-1.129345 1.635898 1.785176 2.137400 2.498003 2.572522
-1.003594 1.603010 1.722697 2.139397 2.431587 2.510996
-1.120169 1.425151 1.675683 2.050774 2.343247 2.460676
-1.328607 1.599151 1.873581 2.170450 2.470538 2.613529
-1.382087 1.595341 1.923462 2.082111 2.349552 2.510754
-1.466192 1.572864 1.870467 2.179996 2.346338 2.471868
-1.379765 1.633014 1.808273 2.166294 2.398723 2.492469
-1.305921 1.610021 1.856406 2.001543 2.390671 2.533908
-1.383086 1.586806 1.757224 1.934804 2.433540 2.587951
-1.307509 1.450943 1.675332 2.033940 2.244229 2.418123
-1.191501 1.484072 1.750272 2.096644 2.249380 2.504983
-1.241378 1.491790 1.776884 2.071735 2.367933 2.508071
-1.265701 1.459923 1.781754 2.009900 2.348578 2.516037
-1.279508 1.414652 1.795096 2.055938 2.395700 2.530542
-1.337338 1.445932 1.853009 2.075183 2.385984 2.535489
-1.288973 1.424709 1.797989 2.026295 2.299802 2.423713
-1.365284 1.471788 1.801705 1.937695 2.345304 2.466696
-1.353791 1.447746 1.736211 1.868886 2.274358 2.475584
-1.360863 1.449607 1.680466 1.802646 2.395536 2.513256
-1.388330 1.526246 1.673331 1.909867 2.385020 2.535430
-1.424428 1.544219 1.720205 1.936245 2.307968 2.491418
-1.448943 1.552009 1.797935 1.937520 2.406873 2.546121
-1.432034 1.521621 1.799322 2.021435 2.477329 2.571754
-1.463087 1.546282 1.834418 2.063488 2.489800 2.595267
-1.425467 1.556435 1.904716 2.110821 2.466374 2.587563
-1.384837 1.569415 1.925581 2.072374 2.561291 2.640537
-1.418492 1.539421 1.937535 2.014318 2.609201 2.676764
-1.397006 1.483285 1.936731 1.977746 2.595606 2.735850
-1.335615 1.441868 1.884738 1.994960 2.589628 2.695748
-1.357490 1.518997 1.871603 1.980199 2.629016 2.700305
-1.353558 1.524318 1.891083 1.963707 2.595814 2.679332
-1.295102 1.639282 1.907387 2.103139 2.583356 2.679778
-1.455545 1.667590 1.953202 2.240488 2.570672 2.673617
-1.460281 1.786653 1.997747 2.285131 2.582928 2.677618
-1.543121 1.729391 2.155674 2.280274 2.655577 2.744248
-1.434440 1.748782 2.042199 2.201295 2.606501 2.695862
-1.436079 1.747337 2.067838 2.253257 2.575944 2.679075
-1.470866 1.698245 2.083133 2.257574 2.565342 2.666191
-1.417419 1.693439 2.053193 2.243538 2.544836 2.632800
-1.412107 1.681588 2.081799 2.326098 2.472446 2.570581
-1.397226 1.764739 2.031556 2.297123 2.471645 2.575881
-1.466497 1.694305 2.005924 2.206325 2.534515 2.635757
-1.437113 1.746568 1.923838 2.127846 2.356631 2.464479
-1.324023 1.597918 1.757776 2.124352 2.347986 2.440470
-1.375387 1.626387 1.778068 2.068399 2.258938 2.397532
-1.379576 1.621789 1.857961 1.994277 2.306086 2.477213
-1.416412 1.648893 1.869117 2.098359 2.345397 2.475125
-1.426241 1.639197 1.925396 2.072677 2.448945 2.532546
-1.459052 1.615870 1.911170 2.125459 2.483704 2.592087
-1.459433 1.690704 1.852418 2.136068 2.529395 2.597199
-1.485144 1.578047 1.810569 2.150621 2.559043 2.618237
-1.529055 1.594664 1.738903 2.261216 2.595771 2.651620
-1.532488 1.585333 1.820935 2.229621 2.623157 2.658477
-1.374401 1.528078 1.848019 2.042459 2.458230 2.591088
-1.399870 1.597467 1.853082 2.096076 2.431604 2.556847
-1.457434 1.609510 1.930756 2.186100 2.392287 2.525064
-1.440508 1.607587 1.869980 2.158283 2.424280 2.555526
-1.376758 1.474791 1.750562 2.190623 2.406180 2.547123
-1.327713 1.454236 1.644635 2.110356 2.352447 2.455926
-1.302805 1.418954 1.609785 2.093121 2.263489 2.393252
-1.207712 1.379869 1.536412 2.059932 2.317302 2.455399
-1.154213 1.302966 1.499207 2.070378 2.322203 2.630828
-1.111474 1.224424 1.625635 2.176079 2.342546 2.606190
-0.945723 1.083298 1.625408 2.214532 2.389898 2.510077
-0.992344 1.116986 1.451917 2.008420 2.313589 2.437855
-1.117309 1.392988 1.713458 2.132315 2.276818 2.497613
-1.332868 1.580932 1.895512 2.129003 2.425104 2.576946
-1.322037 1.497740 1.819219 2.128645 2.443614 2.567952
-1.361937 1.547377 1.790968 2.062941 2.465318 2.546093
-1.252677 1.483878 1.758631 2.033450 2.416283 2.539220
-1.099384 1.344747 1.686531 2.016752 2.355863 2.530839
-1.126109 1.263617 1.649938 1.991544 2.309088 2.514895
-1.190621 1.289655 1.692709 2.009481 2.160091 2.417069
-1.174976 1.414314 1.797856 1.987597 2.278818 2.492762
-1.205354 1.482053 1.850760 2.025549 2.342281 2.523425
-1.248034 1.561185 1.852759 2.096445 2.428364 2.551865
-1.260728 1.601832 1.901052 2.131984 2.409850 2.565546
-1.265037 1.693841 2.000531 2.200039 2.503508 2.617708
-1.278843 1.738264 2.062020 2.289983 2.604440 2.678111
-1.339428 1.735918 2.050123 2.352408 2.597394 2.688219
-1.301064 1.708745 1.965976 2.286214 2.546707 2.653175
-1.278604 1.746157 1.950065 2.214767 2.605793 2.687616
-1.183771 1.523062 1.879119 2.004908 2.600314 2.690485
-1.186222 1.342133 1.817831 1.940077 2.504905 2.659254
-1.179389 1.243680 1.894260 1.979753 2.558019 2.721819
-1.175622 1.357037 1.853192 1.940810 2.646805 2.705660
-1.211124 1.369645 1.825254 1.913289 2.634717 2.712259
-1.169472 1.345149 1.764944 1.883669 2.591077 2.714522
-1.222090 1.389480 1.800177 1.935903 2.573766 2.702922
-1.287266 1.375911 1.878738 1.986045 2.625999 2.708468
-1.299711 1.389598 1.873905 1.942723 2.533485 2.691472
-1.271356 1.424203 1.849847 1.953565 2.555561 2.652372
-1.253571 1.448512 1.829531 1.919100 2.487837 2.630761
-1.223923 1.323017 1.841258 1.932730 2.226845 2.570717
-1.226170 1.321389 1.771794 1.948065 2.137880 2.563052
-1.316238 1.399466 1.789328 1.965570 2.132039 2.424710
-1.264391 1.363953 1.735531 2.005600 2.155844 2.418921
-1.214027 1.319779 1.662017 1.902948 2.064631 2.424833
-1.242602 1.342314 1.624757 1.929420 2.083549 2.318443
-1.241605 1.439119 1.646334 1.817919 1.997763 2.196632
-1.239348 1.336917 1.777062 2.028009 2.155853 2.328702
-1.178416 1.266326 1.802039 1.959820 2.145703 2.469513
-1.247702 1.328626 1.812686 1.992792 2.200638 2.499445
-1.270078 1.370907 1.882273 1.997225 2.254284 2.526050
-1.295553 1.376421 1.860437 2.076734 2.248998 2.567118
-1.304838 1.386085 1.832762 2.061619 2.219399 2.486348
-1.314313 1.381482 1.912831 2.017535 2.287746 2.576424
-1.275078 1.353772 1.858468 2.037031 2.362055 2.615420
-1.287115 1.366797 1.835524 1.961094 2.291985 2.562975
-1.256666 1.341161 1.798806 1.921264 2.333647 2.596913
-1.229284 1.337507 1.753982 1.942388 2.403549 2.602171
-1.224871 1.322981 1.792609 1.918908 2.363314 2.520583
-1.218452 1.321589 1.651493 1.884157 2.366537 2.521284
-1.193218 1.359120 1.632401 1.857625 2.322851 2.452708
-1.205474 1.368035 1.608030 1.815042 2.341851 2.574505
-1.061251 1.318432 1.545024 1.888740 2.401884 2.617020
-1.072522 1.365786 1.514127 1.893675 2.369617 2.474232
-1.111644 1.436790 1.606098 1.842456 2.382418 2.474111
-1.012061 1.316202 1.471593 1.799057 2.349432 2.455130
-1.089471 1.248571 1.572785 1.953061 2.298439 2.461784
-1.068360 1.195813 1.624024 2.111295 2.311476 2.419253
-1.147513 1.525224 1.724810 1.957167 2.387532 2.471314
-1.334336 1.568150 1.749039 1.962569 2.390633 2.484647
-1.298140 1.467881 1.814397 1.941570 2.384226 2.522176
-1.295007 1.418486 1.859466 1.962329 2.376315 2.521757
-1.335831 1.436636 1.858260 1.966332 2.446579 2.563483
-1.346492 1.477982 1.905644 1.998091 2.490052 2.584468
-1.407183 1.540763 1.879296 1.992980 2.487939 2.564009
-1.447665 1.628575 1.828196 2.053651 2.534046 2.605859
-1.524705 1.620051 1.837880 2.017915 2.592167 2.653373
-1.564584 1.647141 1.761178 2.024150 2.615248 2.656575
-1.529370 1.593981 1.683157 1.979831 2.601640 2.654391
-1.585075 1.652835 1.786770 2.031845 2.518000 2.620980
-1.588906 1.644232 1.813812 2.041481 2.610723 2.666049
-1.601362 1.686074 1.862952 2.127114 2.608859 2.655021
-1.640245 1.750920 1.921102 2.164412 2.547516 2.617193
-1.548602 1.638196 1.917398 2.092646 2.563829 2.615836
-1.515875 1.616955 1.844164 2.007026 2.528173 2.601071
-1.465872 1.572195 1.740969 2.011290 2.493415 2.581928
-1.411908 1.534275 1.669392 2.025507 2.419065 2.534991
-1.339405 1.524896 1.674545 2.018990 2.344004 2.443795
-1.300672 1.527060 1.673067 2.036189 2.269516 2.383792
-1.193083 1.476495 1.664464 1.933230 2.291004 2.414954
-1.192791 1.485591 1.649261 1.844048 2.295088 2.502001
-1.197824 1.364864 1.703691 1.827209 2.262766 2.499801
-1.138273 1.379249 1.658127 1.912486 2.389082 2.583381
-1.166597 1.357942 1.688915 1.942734 2.491527 2.589252
-1.170615 1.391547 1.721925 1.889510 2.506116 2.616390
-1.210959 1.452702 1.755617 1.844973 2.490062 2.624729
-1.212139 1.519716 1.785919 1.889270 2.551264 2.629492
-1.276001 1.664615 1.957757 2.249343 2.602286 2.677701
-1.400862 1.816183 1.994456 2.325956 2.651785 2.717305
-1.466054 1.834563 2.118572 2.372427 2.625377 2.704685
-1.578859 1.790938 2.136097 2.392831 2.638547 2.714022
-1.480700 1.816555 2.206450 2.432389 2.575887 2.645111
-1.617288 1.807665 2.241721 2.440067 2.567226 2.631745
-1.570100 1.785068 2.178210 2.348135 2.467045 2.556638
-1.579682 1.701535 2.005186 2.288766 2.434155 2.548589
-1.578691 1.674213 1.965474 2.199446 2.334867 2.479803
-1.640546 1.726915 1.991606 2.240338 2.400971 2.523628
-1.588532 1.709671 1.874418 2.160822 2.381523 2.517230
-1.447497 1.665484 1.900942 2.103382 2.397872 2.535571
-1.203022 1.599213 1.884283 2.032257 2.369015 2.504738
-1.146521 1.513193 1.880497 1.985787 2.407380 2.522482
-1.131266 1.435001 1.834092 2.111348 2.306550 2.531154
-1.176712 1.640343 1.870115 2.064938 2.313000 2.439124
-1.254490 1.590614 1.958487 2.200173 2.344272 2.479816
-1.243959 1.684492 2.016502 2.192945 2.451075 2.547334
-1.537310 1.763854 2.188639 2.371726 2.539927 2.648079
-1.646538 1.887574 2.280949 2.443446 2.593067 2.680775
-1.567456 1.876170 2.108713 2.427826 2.611726 2.691363
-1.341056 1.874127 2.114216 2.396197 2.621228 2.702770
-1.449196 1.837843 2.058401 2.307470 2.616907 2.689695
-1.313491 1.794349 1.961057 2.237499 2.597739 2.685191
-1.202175 1.706913 1.905104 2.139148 2.612890 2.693658
-1.080344 1.590487 1.846519 2.059279 2.631365 2.697376
-1.043219 1.601906 1.900346 2.141041 2.588352 2.662523
-0.984957 1.556146 1.841481 2.148769 2.577337 2.662952
-0.979403 1.553838 1.844172 2.052598 2.577754 2.641114
-0.947313 1.453890 1.836463 1.998780 2.566547 2.637546
-0.959460 1.441678 1.832870 2.106499 2.553643 2.630882
-0.951016 1.397882 1.793743 2.053066 2.492635 2.622573
-0.870727 1.369217 1.817794 2.107476 2.524230 2.627945
-0.902872 1.385159 1.754800 2.013432 2.536990 2.654823
-0.891101 1.362395 1.753579 1.878041 2.559805 2.662468
-0.835616 1.259326 1.757169 1.832338 2.486345 2.635682
-0.787419 1.132035 1.693975 1.776933 2.533180 2.616312
-0.791106 1.068132 1.697743 1.851598 2.571958 2.669553
-0.759951 1.112356 1.562357 1.855199 2.490682 2.601972
-0.792061 1.139999 1.724823 1.954458 2.608864 2.689684
-0.823952 1.270934 1.741090 2.077662 2.613199 2.669386
-0.736534 1.124969 1.743684 2.093250 2.579787 2.661721
-0.797043 1.051944 1.780229 2.240357 2.583476 2.662315
-0.923582 1.503155 1.776882 2.018470 2.613910 2.703042
-1.421538 1.735030 2.006889 2.210344 2.574319 2.670736
-1.350174 1.606122 1.963013 2.084969 2.478192 2.589945
-1.361799 1.656583 1.974082 2.173881 2.479634 2.612008
-1.319939 1.764454 2.027445 2.249293 2.529644 2.635744
-1.394028 1.664199 2.006309 2.246188 2.558094 2.671320
-1.385394 1.755426 2.080024 2.329874 2.630895 2.722673
-1.333690 1.669430 2.021492 2.250607 2.600265 2.689100
-1.341532 1.698164 1.975002 2.237112 2.560850 2.684376
-1.388610 1.785046 1.956888 2.281386 2.563576 2.643708
-1.345894 1.706236 1.842983 2.264164 2.606222 2.694785
-1.320329 1.694191 1.923363 2.218151 2.645478 2.750259
-1.332386 1.748388 2.014721 2.221780 2.602628 2.697461
-1.397603 1.715354 1.949721 2.236000 2.577802 2.661479
-1.618810 1.795968 2.016419 2.205191 2.506636 2.636829
-1.659811 1.735333 2.021086 2.175840 2.443378 2.641454
-1.539528 1.652064 1.946773 2.095081 2.446637 2.636547
-1.532272 1.592873 1.977822 2.053408 2.551491 2.674907
-1.509350 1.581109 2.004243 2.059379 2.524603 2.702937
-1.432533 1.504626 1.930707 2.042330 2.440661 2.690850
-1.194640 1.677037 2.023104 2.078391 2.446911 2.745852
-1.210373 1.824825 2.021515 2.139089 2.539931 2.659640
-1.276624 1.715436 1.952490 2.083815 2.473462 2.664346
-1.235656 1.548445 2.067341 2.118624 2.427438 2.727540
-1.283474 1.374296 1.963417 2.098418 2.474393 2.702856
-1.305021 1.394700 2.068003 2.139040 2.520168 2.706208
-1.284823 1.494312 2.055208 2.140334 2.602120 2.698828
-1.296593 1.587724 2.087205 2.156563 2.618559 2.718633
-1.252465 1.583350 2.108883 2.173872 2.600502 2.685035
-1.177439 1.612038 2.093884 2.155173 2.581066 2.695123
-1.132957 1.572991 2.135458 2.220598 2.615734 2.710569
-1.060318 1.542980 2.165747 2.230410 2.609442 2.697786
-0.993306 1.542205 2.170751 2.247209 2.631170 2.706892
-0.783750 1.568542 2.323323 2.398878 2.594196 2.690603
-0.866024 1.454427 2.113290 2.187039 2.662007 2.719943
-0.793002 1.437700 2.125666 2.225555 2.588880 2.664786
-0.863183 1.439828 2.031948 2.203948 2.586483 2.646886
-0.817301 1.443077 2.078742 2.356665 2.572146 2.635324
-0.840200 1.268198 1.973956 2.380693 2.546743 2.624124
-0.905910 1.472855 2.000805 2.420178 2.606009 2.662539
-0.885218 1.599132 2.063964 2.335379 2.688751 2.736255
-0.812099 1.480973 2.103159 2.193629 2.621360 2.702113
-0.727009 1.481278 2.088167 2.170556 2.575583 2.660557
-0.783755 1.482083 2.210773 2.281994 2.564635 2.658081
-0.810890 1.318001 2.156661 2.250146 2.565371 2.666169
-0.775372 1.352710 2.277457 2.371730 2.587244 2.655489
-0.765239 1.280609 2.227449 2.304899 2.577531 2.696870
-0.860727 1.309962 2.239215 2.358255 2.523746 2.681832
-0.828001 1.157509 2.157199 2.279201 2.554510 2.655379
-0.776568 1.131001 2.110470 2.282369 2.502240 2.634533
-0.662804 1.210648 2.214487 2.275268 2.480153 2.598167
-0.752595 1.172127 2.270252 2.354795 2.534373 2.613431
-0.769014 1.037539 2.239849 2.320190 2.523883 2.637275
-0.747299 1.036519 2.059875 2.380316 2.507719 2.677768
-0.818428 1.110448 2.132574 2.306792 2.442669 2.597844
-0.838124 1.256032 2.152521 2.304078 2.501081 2.591854
-0.842740 1.147341 2.045086 2.317073 2.459293 2.588472
-0.950977 1.150930 2.097644 2.290004 2.497415 2.643449
-0.932262 1.159756 1.945175 2.233748 2.538888 2.635754
-0.872640 1.294667 1.881084 2.112185 2.488729 2.612697
-0.953242 1.398337 1.906758 2.024454 2.396667 2.616332
-1.019160 1.447236 1.917323 2.023333 2.213019 2.528896
-0.980910 1.420444 1.857618 1.943436 2.294481 2.596120
-1.007917 1.474723 1.827586 1.921475 2.567362 2.643752
-1.057674 1.583820 1.862216 1.988312 2.507590 2.602780
-1.089480 1.610937 1.894205 2.067983 2.401427 2.589250
-1.155642 1.601524 1.853784 2.109924 2.266420 2.654880
-1.190394 1.403206 1.850320 2.129434 2.355479 2.599651
-1.165667 1.266234 1.847925 2.191760 2.352164 2.576809
-1.112543 1.237226 1.755553 2.196412 2.378413 2.515897
-1.093202 1.229320 1.630970 2.198491 2.394327 2.490062
-1.030916 1.160090 1.536996 2.150269 2.345755 2.526171
-1.090134 1.227459 1.470303 2.121663 2.325691 2.414263
-1.084185 1.353427 1.495774 2.165409 2.396637 2.501534
-1.128688 1.380138 1.551457 2.110309 2.296856 2.418999
-1.087172 1.454259 1.658795 2.020385 2.196298 2.381465
-1.039395 1.582193 1.728098 2.070179 2.301852 2.489432
-1.019025 1.646872 1.828918 2.125767 2.542468 2.624929
-1.017909 1.675444 2.009386 2.200627 2.432273 2.532754
-0.975365 1.568456 2.099629 2.243759 2.469669 2.558656
-1.045139 1.750545 2.091194 2.277034 2.473998 2.559636
-1.003490 1.670000 2.149872 2.216814 2.544142 2.591015
-0.972271 1.669349 2.066914 2.253461 2.528115 2.626794
-1.001400 1.910537 2.208899 2.322095 2.475052 2.594146
-1.106236 1.762398 2.170214 2.368326 2.532382 2.636954
-0.937567 1.570796 2.208314 2.312080 2.547601 2.604149
-0.984015 1.531648 2.154446 2.260403 2.519554 2.621365
-1.058045 1.589683 2.130473 2.238788 2.559220 2.636001
-1.126293 1.674296 2.142380 2.304378 2.581987 2.659797
-1.092169 1.547245 2.138847 2.246962 2.570924 2.653740
-1.164152 1.513575 2.120596 2.203037 2.555931 2.629117
-1.154436 1.451664 2.109876 2.193787 2.569383 2.668688
-1.171007 1.297549 2.105789 2.224294 2.529719 2.663245
-1.139370 1.343339 2.024942 2.161273 2.570054 2.662064
-1.214975 1.759488 2.013624 2.126711 2.350657 2.508933
-1.410441 1.787361 1.940449 2.082004 2.255781 2.406359
-1.192527 1.698280 1.956892 2.084836 2.235743 2.490643
-1.173627 1.448751 2.011122 2.145246 2.280142 2.534706
-1.172797 1.327177 1.938868 2.095910 2.247560 2.526844
-1.129709 1.376142 1.891533 1.985327 2.196351 2.582653
-1.195218 1.292910 1.887213 2.025135 2.200698 2.525594
-1.246281 1.338967 1.851654 2.072793 2.209074 2.457441
-1.244715 1.395538 1.916844 2.097048 2.296495 2.526646
-1.346432 1.453272 2.128410 2.313839 2.566271 2.666215
-1.392181 1.506569 2.060420 2.183828 2.523643 2.656421
-1.397671 1.478362 2.037869 2.140024 2.522879 2.634883
-1.405078 1.437969 2.064698 2.121678 2.484341 2.664086
-1.527970 1.731644 2.001400 2.182281 2.477459 2.609679
-1.602215 1.694049 2.065008 2.176143 2.567575 2.650751
-1.549243 1.668152 2.061940 2.136053 2.575954 2.678540
-1.590489 1.693208 1.921586 2.193585 2.522338 2.657822
-1.593120 1.715596 2.057856 2.172814 2.502009 2.607762
-1.508461 1.713948 2.053457 2.146855 2.383043 2.628673
-1.500942 1.577870 1.978516 2.080955 2.517866 2.640817
-1.503819 1.559203 1.933282 2.030596 2.516193 2.657495
-1.430951 1.506436 1.856364 2.014512 2.406913 2.583800
-1.394417 1.471155 1.914772 2.015327 2.414514 2.568928
-1.376718 1.476739 1.841743 1.961573 2.459621 2.552505
-1.304829 1.509257 1.807862 1.899025 2.532604 2.616563
-1.486241 1.646868 1.928992 2.176641 2.503384 2.645535
-1.477068 1.576408 1.937301 2.094449 2.468734 2.643633
-1.431493 1.551268 1.935807 2.027994 2.468760 2.605588
-1.427171 1.670820 1.944981 2.109944 2.482745 2.652433
-1.393190 1.649564 1.991075 2.070334 2.586450 2.667337
-1.406966 1.518528 1.967049 2.067755 2.501722 2.624107
-1.399129 1.487381 1.880327 1.972568 2.359193 2.604810
-1.419452 1.541906 1.920889 2.015257 2.416437 2.547537
-1.447736 1.626647 1.911603 2.037838 2.508304 2.609091
-1.507943 1.649223 1.954490 2.063843 2.515779 2.591471
-1.512511 1.697882 1.919266 2.077175 2.545774 2.631085
-1.577487 1.652922 1.969378 2.057105 2.533497 2.610477
-1.604710 1.687839 1.943635 2.030700 2.552461 2.659467
-1.634825 1.710086 1.943508 2.035741 2.553037 2.650522
-1.629110 1.721048 1.907265 2.020140 2.570097 2.652611
-1.653862 1.731013 1.917069 2.016503 2.551305 2.678978
-1.675623 1.740253 1.923108 1.995468 2.543890 2.693466
-1.704324 1.761003 1.892088 1.958603 2.520344 2.709583
-1.631746 1.698022 1.879765 1.974816 2.475043 2.688708
-1.563394 1.662351 1.863499 1.961656 2.492069 2.692141
-1.535271 1.621802 1.864516 2.016880 2.457202 2.701452
-1.463627 1.689995 1.942593 2.019493 2.516076 2.684085
-1.427161 1.545730 1.922601 1.983390 2.549083 2.724037
-1.387863 1.469421 1.874287 2.047091 2.486568 2.643007
-1.364743 1.462745 1.908513 2.076519 2.468769 2.627416
-1.421611 1.616670 2.074387 2.243630 2.604811 2.697119
-1.443567 1.802480 2.145890 2.311026 2.615127 2.704969
-1.402806 1.864810 2.209376 2.377972 2.654288 2.731440
-1.472673 1.860803 2.162882 2.447267 2.648421 2.719024
-1.518497 1.794725 2.075011 2.339205 2.552102 2.655931
-1.503597 1.758472 2.111549 2.304480 2.551002 2.643546
-1.466759 1.587712 2.046144 2.276602 2.546510 2.649906
-1.414608 1.499164 2.000686 2.080851 2.549084 2.654414
-1.324617 1.597419 1.961703 2.075259 2.518788 2.638260
-1.262448 1.666067 1.961546 2.098269 2.549101 2.630367
-1.220869 1.632115 1.947651 2.054954 2.515971 2.607563
-1.136650 1.569138 1.923253 2.011403 2.513979 2.612924
-1.058570 1.570577 1.921267 2.037973 2.484487 2.569497
-1.039823 1.492368 1.862383 2.113321 2.462634 2.586287
-1.291651 1.546687 1.888427 2.160338 2.444567 2.573682
-1.154151 1.629832 1.978719 2.114524 2.505413 2.616168
-1.018988 1.844229 2.003497 2.145640 2.430051 2.549664
-1.003639 1.900247 2.103968 2.200810 2.555267 2.678873
-1.007182 1.652528 2.033376 2.117896 2.534356 2.593837
-1.014065 1.625311 2.073565 2.163998 2.546138 2.611829
-1.009846 1.729007 2.001610 2.190071 2.554550 2.635426
-1.019489 1.599817 2.062920 2.180981 2.585351 2.651906
-1.042282 1.559849 2.061719 2.184907 2.608829 2.711272
-1.093985 1.606698 2.067049 2.179456 2.578115 2.647082
-1.117524 1.554503 2.010457 2.171257 2.524192 2.604614
-1.189148 1.687116 2.026818 2.220744 2.584656 2.673603
-1.184285 1.592927 2.011407 2.140558 2.575633 2.652764
-1.243271 1.544342 1.991354 2.103724 2.547726 2.633837
-1.249802 1.530059 1.930460 2.044509 2.489498 2.611045
-1.317227 1.550858 1.927474 2.019107 2.563575 2.632413
-1.300146 1.571198 1.817213 1.967321 2.572012 2.659755
-1.304786 1.459074 1.804350 1.873800 2.572345 2.677847
-1.272113 1.387927 1.710588 1.798443 2.519124 2.630967
-1.168824 1.271438 1.680467 1.847635 2.472587 2.636108
-1.127715 1.380423 1.702693 1.948341 2.254799 2.516590
-1.037344 1.362071 1.698870 1.943363 2.319984 2.576108
-0.912701 1.215239 1.774758 2.057933 2.407301 2.609739
-0.884045 1.283341 1.740086 2.012038 2.332329 2.530152
-0.859928 1.361393 1.787767 2.032428 2.439162 2.572497
-0.933575 1.497313 1.860114 2.007764 2.460777 2.636583
-0.980843 1.376674 1.808267 1.899302 2.551384 2.660680
-0.888314 1.390836 1.819063 1.938604 2.611726 2.713704
-0.839112 1.455052 1.864246 1.932569 2.561260 2.649480
-0.851738 1.633441 1.854938 2.065105 2.591532 2.637966
-0.927993 1.739190 1.882023 2.133201 2.585017 2.640778
-0.938681 1.795656 1.962111 2.138930 2.565233 2.627897
-0.939389 1.842127 2.021817 2.196345 2.611519 2.658322
-0.876668 1.922758 2.066598 2.238607 2.657831 2.709139
-0.928890 1.831807 2.053719 2.203623 2.653635 2.695408
-0.843177 1.785949 2.180039 2.258075 2.596807 2.669868
-0.904710 1.738574 2.045482 2.171335 2.659082 2.701770
-0.870576 1.672854 2.046684 2.160295 2.663395 2.706284
-0.863208 1.611276 2.039577 2.131986 2.662744 2.710206
-0.911587 1.521477 1.972249 2.117701 2.671514 2.736290
-0.857624 1.506231 1.927459 2.092066 2.599004 2.671353
-0.876724 1.386211 1.930102 2.020125 2.640246 2.715714
-0.822485 1.363083 1.951099 2.012089 2.546285 2.704224
-0.896312 1.299233 1.946153 2.039999 2.427568 2.660429
-0.993275 1.379765 2.001120 2.083441 2.476481 2.621083
-1.111974 1.369262 1.980570 2.050077 2.518420 2.654724
-1.168214 1.421156 1.929649 2.013732 2.513895 2.659462
-1.185532 1.477308 1.941700 2.021792 2.545835 2.636829
-1.134677 1.498395 1.996860 2.077054 2.487095 2.605961
-1.411729 1.500808 1.930565 2.251695 2.391409 2.514752
-1.387101 1.551631 1.939267 2.134432 2.390647 2.538102
-1.436468 1.601632 1.856306 2.001721 2.498428 2.579682
-1.490762 1.673865 1.865367 2.015258 2.490944 2.589599
-1.532290 1.665821 1.854110 1.987787 2.544314 2.634547
-1.563136 1.683249 1.819205 1.981344 2.592402 2.655991
-1.532691 1.642869 1.795089 1.955952 2.595574 2.688667
-1.506939 1.596868 1.724719 1.902522 2.497152 2.646767
-1.385229 1.553302 1.733776 1.993489 2.385677 2.620193
-1.191373 1.508094 1.914117 2.177183 2.460347 2.600638
-0.990202 1.268417 1.760300 1.988487 2.516663 2.661016
-1.004888 1.273030 1.919583 1.976961 2.621532 2.711155
-1.013289 1.479166 1.983769 2.021110 2.561293 2.681392
-1.094384 1.424205 1.985002 2.164791 2.592137 2.670975
-1.057765 1.377512 1.866113 2.165416 2.490671 2.623341
-1.001768 1.321304 1.902289 2.133880 2.499889 2.659347
-0.896048 1.414778 1.927546 2.127605 2.570653 2.658502
-0.862503 1.586972 1.946548 2.153624 2.615123 2.677873
-0.837783 1.700010 1.932982 2.209447 2.588567 2.687532
-0.901209 1.639772 1.999974 2.070577 2.515297 2.763152
-0.955829 1.601245 2.008965 2.112233 2.503888 2.592844
-0.939285 1.704094 2.027412 2.125922 2.430007 2.538916
-0.948268 1.700873 2.002768 2.088348 2.563468 2.622110
-0.959154 1.624274 2.005824 2.077760 2.577716 2.658733
-0.932538 1.593435 1.952831 2.044660 2.567978 2.644497
-0.933107 1.590563 1.945695 2.111900 2.534278 2.608873
-0.943808 1.649088 1.897019 2.104647 2.578170 2.689758
-1.003034 1.619161 1.930228 2.216721 2.582337 2.637890
-0.936810 1.692346 1.965525 2.118648 2.628517 2.684797
-0.973578 1.737821 1.975673 2.106344 2.658295 2.722445
-0.955324 1.750194 1.961437 2.075373 2.655612 2.731757
-0.994013 1.727390 1.946779 2.062413 2.643379 2.738490
-1.005363 1.693919 1.929868 2.100177 2.618754 2.684861
-0.967862 1.640078 1.930261 2.021548 2.639890 2.726662
-0.928258 1.579359 1.864413 1.973012 2.638908 2.717888
-1.058334 1.410591 1.870850 2.066023 2.451575 2.633697
-1.123046 1.486876 1.862969 2.086078 2.412975 2.591738
-1.177472 1.431539 1.849290 2.099756 2.423335 2.566135
-1.187028 1.443506 1.882075 1.983318 2.550673 2.639389
-1.267969 1.628389 1.932608 2.043278 2.552232 2.641727
-1.355546 1.701559 1.924241 2.034556 2.590180 2.660965
-1.472056 1.739983 1.914264 2.052330 2.573889 2.644926
-1.461490 1.790656 1.911310 2.057871 2.525599 2.587235
-1.542347 1.742399 1.901654 2.063063 2.499169 2.580661
-1.550813 1.642896 1.877392 1.995154 2.474361 2.561166
-1.625354 1.724756 1.899115 2.052586 2.447095 2.556852
-1.636703 1.742201 1.904488 2.155317 2.470314 2.569291
-1.608688 1.701026 1.957110 2.085583 2.465316 2.552203
-1.517569 1.685169 1.923050 2.028968 2.382899 2.503932
-1.215848 1.648126 1.842885 2.049966 2.393827 2.484346
-1.158500 1.452995 1.752665 1.859020 2.467269 2.575520
-1.128274 1.384146 1.801504 1.899178 2.472451 2.609988
-1.080623 1.414338 1.812493 1.916642 2.422686 2.620118
-1.104866 1.492913 1.854038 1.971940 2.444002 2.583583
-1.235805 1.437823 1.919484 2.042792 2.483999 2.617147
-1.167412 1.407601 1.774394 2.073573 2.390599 2.543323
-1.096565 1.317231 1.782210 2.013544 2.394372 2.571806
-1.104307 1.206800 1.718582 2.001006 2.351339 2.505639
-1.047321 1.316889 1.824322 2.050773 2.417158 2.531028
-1.087184 1.408401 1.843144 2.031666 2.440481 2.544264
-1.108521 1.394200 1.760026 2.005728 2.435035 2.552154
-1.121767 1.340590 1.749504 1.963633 2.493819 2.609645
-1.122415 1.452714 1.793131 2.030414 2.502133 2.593239
-1.026877 1.468099 1.745342 1.860466 2.483684 2.579747
-0.971670 1.244091 1.752977 1.837331 2.384716 2.625316
-0.917302 1.104410 1.674928 1.792426 2.336189 2.629469
-0.961560 1.088356 1.555776 1.663706 2.282322 2.579748
-0.919563 1.063279 1.573205 1.711100 2.422693 2.675976
-0.875889 1.022614 1.380839 1.829163 2.584656 2.667378
-0.763749 1.018806 1.506319 1.707976 2.471526 2.595865
-0.886944 1.031388 1.425057 1.710023 2.427922 2.576385
-0.890351 1.037652 1.443986 1.587883 2.520205 2.695833
-0.906256 1.035046 1.405613 1.523743 2.536532 2.596081
-0.929418 1.061071 1.157090 1.566597 2.528260 2.694068
-0.917396 1.106117 1.253042 1.389506 2.551566 2.709098
-0.910230 1.042070 1.162527 1.362129 2.393076 2.605349
-0.804288 1.059586 1.418081 1.530362 2.410566 2.663442
-0.907675 1.046288 1.392541 1.508232 2.495351 2.692340
-0.835212 1.126874 1.350498 1.463210 2.567735 2.694674
-0.770295 1.150701 1.428259 1.601173 2.610228 2.683669
-0.924536 1.075405 1.468526 1.669865 2.543683 2.693196
-0.972382 1.191757 1.544758 1.638670 2.535321 2.642972
-0.903877 1.101926 1.510782 1.602659 2.487038 2.638272
-0.881279 1.096901 1.554249 1.644297 2.424659 2.557575
-0.866115 1.118877 1.603042 1.702467 2.543898 2.649301
-0.906645 1.160248 1.672021 1.747258 2.517909 2.650863
-0.861085 1.205864 1.660991 1.847091 2.462741 2.632034
-0.837175 1.187776 1.806042 1.889495 2.508608 2.684557
-0.797709 1.178516 1.903177 2.021653 2.546180 2.690072
-0.802875 1.262753 1.923936 2.000576 2.568440 2.670106
-0.766638 1.320827 1.961021 2.058945 2.582312 2.646725
-0.811579 1.455194 2.011480 2.084784 2.548418 2.639933
-0.829770 1.484961 2.052714 2.127227 2.530640 2.608181
-0.799011 1.567454 2.155632 2.265108 2.573173 2.668504
-0.730379 1.358614 2.125791 2.194588 2.518703 2.605426
-0.720667 1.277836 2.042808 2.111923 2.592800 2.675300
-0.777663 1.163703 2.066790 2.179199 2.570004 2.675513
-0.839969 1.373176 2.185884 2.304679 2.509358 2.602576
-0.815752 1.915221 2.233635 2.288481 2.569983 2.628428
-1.191882 1.945689 2.175132 2.299053 2.523524 2.632041
-1.036281 1.742208 2.072713 2.141555 2.573194 2.641551
-1.042507 1.303046 2.012892 2.154612 2.530678 2.649182
-1.109942 1.204237 1.928687 2.058228 2.384097 2.639570
-1.187387 1.287703 1.954253 2.071260 2.382559 2.641811
-1.239189 1.327757 1.930550 2.015277 2.361685 2.627501
-1.292084 1.351985 1.938008 2.017320 2.411502 2.663432
-1.306236 1.382401 1.918450 2.038312 2.339392 2.637738
-1.330235 1.401641 1.873760 1.990443 2.185496 2.510909
-1.356391 1.459759 1.883388 1.980460 2.264547 2.541810
-1.347396 1.438637 1.891675 2.018006 2.302572 2.643809
-1.300877 1.390171 1.889271 1.972933 2.337515 2.605637
-1.318667 1.410121 1.895352 1.990366 2.384682 2.654040
-1.309274 1.425501 1.966145 2.021896 2.501117 2.698509
-1.293853 1.370923 1.908443 1.999149 2.465481 2.673998
-1.277395 1.382844 2.002299 2.066843 2.496853 2.664070
-1.245384 1.422441 2.002908 2.070718 2.556839 2.666388
-1.272587 1.491087 2.012301 2.129241 2.562307 2.657432
-1.265182 1.533940 2.020942 2.093088 2.498380 2.630954
-1.265700 1.477033 2.103009 2.196534 2.455284 2.619887
-1.288505 1.642454 2.093854 2.247833 2.561691 2.658788
-1.410258 1.828971 2.171872 2.374134 2.564587 2.653381
-1.353887 1.710043 2.209331 2.426043 2.629318 2.702189
-1.413615 1.766928 2.137724 2.434853 2.632060 2.702909
-1.459054 1.706939 2.135084 2.377030 2.626415 2.708945
-1.498018 1.687923 2.094822 2.342946 2.558778 2.665699
-1.413908 1.588267 2.086727 2.293084 2.513587 2.642131
-1.399998 1.553342 1.938772 2.183871 2.458665 2.610409
-1.373521 1.449791 1.880601 2.079841 2.298236 2.559768
-1.367538 1.440752 1.973770 2.086070 2.339106 2.621913
-1.368842 1.460821 2.006053 2.129789 2.391520 2.650517
-1.375993 1.496235 2.050052 2.130850 2.453915 2.698625
-1.340575 1.484156 2.084130 2.140940 2.549924 2.685428
-1.389975 1.553009 2.063781 2.147982 2.592260 2.703825
-1.247451 1.503376 2.044299 2.136485 2.344491 2.599169
-1.315110 1.540850 2.028329 2.116330 2.272535 2.431545
-1.298833 1.587487 2.071926 2.185875 2.335690 2.500779
-1.293658 1.562430 2.031101 2.149606 2.408168 2.517292
-1.357545 1.513305 1.998085 2.153047 2.450464 2.583804
-1.314414 1.517423 2.079463 2.179438 2.522288 2.616203
-1.237750 1.513563 2.052227 2.181066 2.539042 2.628158
-1.208558 1.486041 2.046503 2.194666 2.489982 2.636673
-1.196570 1.462494 2.073139 2.230856 2.547633 2.700603
-1.080935 1.459427 2.110500 2.217708 2.538133 2.678354
-1.094483 1.378608 2.167880 2.246181 2.567935 2.691322
-0.942435 1.463343 2.253533 2.330775 2.538479 2.626769
-0.828468 1.390170 2.152319 2.218028 2.545274 2.621490
-0.883311 1.334196 2.094816 2.191259 2.475576 2.573464
-0.863185 1.418682 2.080489 2.166381 2.556104 2.714086
-0.848520 1.391080 2.049319 2.134194 2.702541 2.780818
-0.826225 1.373582 2.037386 2.120576 2.736093 2.782594
-0.823246 1.343853 2.033890 2.111803 2.740872 2.787067
-0.833848 1.336791 2.045450 2.118012 2.699609 2.796181
-0.811654 1.321345 2.094991 2.178116 2.494230 2.649899
-0.947528 1.361146 2.127848 2.219008 2.511382 2.668194
-0.875759 1.251606 2.133422 2.241748 2.473825 2.662930
-0.933534 1.448444 2.139134 2.244510 2.486761 2.606936
-0.945109 1.280801 2.208944 2.335059 2.511318 2.614528
-0.956935 1.371241 2.107196 2.194521 2.403252 2.573030
-0.981000 1.251932 2.147964 2.266597 2.440418 2.624374
-1.061610 1.231691 2.076021 2.233401 2.438599 2.636988
-1.018874 1.354035 1.998033 2.260078 2.443139 2.554775
-1.080301 1.301891 2.034629 2.145600 2.415056 2.591218
-1.133867 1.359760 2.063950 2.164629 2.439392 2.628661
-1.125038 1.414128 1.997540 2.103717 2.392421 2.599578
-1.167273 1.393564 1.998177 2.076478 2.441776 2.643288
-1.198696 1.421193 1.967983 2.057020 2.432820 2.645067
-1.256230 1.378074 1.941853 2.019326 2.444584 2.608853
-1.295565 1.412154 1.932411 2.008349 2.430053 2.649016
-1.281347 1.464522 1.888236 2.006518 2.425280 2.635204
-1.270582 1.406704 1.901187 1.969293 2.470983 2.647901
-1.266697 1.372887 1.871811 1.957591 2.414971 2.648622
-1.194388 1.351744 1.888250 1.978092 2.400857 2.662660
-1.198872 1.299839 1.864283 1.963651 2.362794 2.619509
-1.126580 1.240104 1.902544 1.997646 2.331426 2.608634
-1.104618 1.214183 1.879788 2.014306 2.251659 2.573373
-1.024288 1.193207 1.868916 2.127876 2.376009 2.623451
-1.000362 1.230212 1.960304 2.075244 2.329353 2.584128
-0.977548 1.321985 1.988755 2.104256 2.381026 2.607919
-0.927608 1.447916 2.027888 2.123013 2.478479 2.585880
-0.887733 1.516534 2.046895 2.153890 2.480515 2.582006
-0.898681 1.564754 2.091528 2.179653 2.573940 2.676783
-0.974718 1.500859 2.081966 2.177780 2.532281 2.634995
-1.023818 1.390635 2.060590 2.142028 2.469386 2.636908
-1.106581 1.431053 1.977134 2.097146 2.471693 2.659120
-1.201259 1.485663 1.944652 2.112542 2.500250 2.665927
-1.285694 1.520657 1.911058 2.044248 2.487710 2.665801
-1.362495 1.534785 1.910552 1.990936 2.505705 2.661527
-1.434594 1.514838 1.934187 2.017407 2.501527 2.693875
-1.420840 1.519491 1.909348 1.986650 2.460403 2.688194
-1.404412 1.469806 1.964287 2.054233 2.366794 2.655269
-1.388287 1.466909 1.964052 2.058950 2.286531 2.604935
-1.367998 1.434810 1.857703 2.007116 2.196577 2.604187
-1.300836 1.380544 1.740254 2.046889 2.235228 2.521906
-1.231299 1.321604 1.867230 2.147627 2.354630 2.579138
-1.154924 1.255903 1.932323 2.164374 2.392832 2.605994
-1.098663 1.202218 1.948275 2.150159 2.492596 2.625742
-1.057458 1.221852 1.869129 2.268825 2.456540 2.580362
-1.033078 1.150105 1.708873 2.264876 2.476044 2.563612
-0.988998 1.159268 1.962027 2.302711 2.448723 2.560725
-1.028425 1.228689 2.025910 2.260366 2.561850 2.661757
-0.934860 1.348208 2.053889 2.214742 2.525301 2.647713
-0.919150 1.264565 2.068138 2.183398 2.534979 2.644315
-0.975247 1.362233 2.052147 2.231420 2.582800 2.724482
-0.954336 1.311177 1.977372 2.238157 2.478111 2.617046
-0.941853 1.335982 1.976422 2.219013 2.579491 2.714299
-0.928694 1.366450 1.884879 2.183146 2.580560 2.657594
-0.986067 1.338370 1.954317 2.187863 2.566522 2.638835
-0.912646 1.284402 1.814142 2.175069 2.553933 2.638518
-0.968965 1.310497 1.839690 2.078084 2.590335 2.660573
-0.977192 1.304629 1.880951 2.127022 2.598044 2.712114
-1.023839 1.299619 1.944708 2.103778 2.625919 2.730897
-1.110208 1.286313 1.959383 2.053969 2.564587 2.676132
-1.028136 1.324243 1.976740 2.094942 2.586202 2.754727
-1.129799 1.269907 2.011874 2.109219 2.588902 2.696539
-1.056967 1.340484 2.016171 2.105554 2.557611 2.747157
-1.037500 1.255766 2.029385 2.136193 2.511776 2.709627
-1.006157 1.417167 2.071949 2.132612 2.543898 2.701957
-1.136962 1.416211 2.050339 2.112042 2.449673 2.695205
-1.135319 1.436267 2.083850 2.194924 2.386385 2.656934
-1.094073 1.385456 2.015160 2.113333 2.320097 2.641531
-1.025929 1.360649 1.878300 1.981456 2.128037 2.458938
-1.142747 1.416162 1.901013 2.054884 2.170210 2.459052
-1.093211 1.488385 1.801376 2.073578 2.203432 2.494834
-1.161243 1.263262 1.784814 2.071204 2.194577 2.436217
-1.010788 1.141181 1.728171 2.118721 2.251271 2.426326
-1.083805 1.275984 1.888426 2.068392 2.227464 2.511105
-1.093824 1.303401 1.924085 2.183963 2.348527 2.531702
-1.409867 1.540059 1.722330 2.049905 2.235685 2.389249
-1.466595 1.617030 1.819393 2.035808 2.439730 2.543324
-1.526883 1.811727 1.926153 2.129197 2.481471 2.556058
-1.420465 1.731610 1.925362 2.081119 2.474447 2.570275
-1.248374 1.462520 1.699273 1.907107 2.355354 2.484796
-1.183224 1.558159 1.646615 1.999807 2.374069 2.461600
-1.143841 1.513288 1.675690 1.906750 2.428362 2.518793
-1.066986 1.500051 1.667526 1.961464 2.445898 2.521565
-1.046648 1.520761 1.705160 1.878376 2.459759 2.532729
-1.013709 1.559530 1.737535 1.955854 2.437820 2.515857
-1.021952 1.586883 1.737034 1.929179 2.523644 2.577879
-0.942307 1.579146 1.776104 2.060265 2.437220 2.517653
-0.914226 1.642076 1.812801 2.001091 2.508510 2.570062
-0.952017 1.688066 1.935018 2.016153 2.446793 2.563584
-0.856280 1.697514 1.902727 2.012686 2.522414 2.584398
-0.891878 1.553150 1.935497 2.046974 2.532664 2.594967
-0.845424 1.602286 1.937720 2.027521 2.583016 2.649168
-0.876501 1.716624 1.939566 2.067536 2.588264 2.625363
-0.901014 1.864369 1.978925 2.075191 2.462666 2.609798
-0.911677 1.767853 1.947788 2.072575 2.595744 2.634946
-0.937394 1.708734 1.927739 2.054606 2.574109 2.647431
-1.003647 1.614615 1.942062 2.035984 2.592009 2.664724
-1.089415 1.563712 1.910690 1.974956 2.590910 2.681816
-1.180196 1.457231 1.840836 1.921595 2.573409 2.659354
-1.239380 1.444276 1.818908 1.893870 2.559595 2.657419
-1.377315 1.528992 1.744904 1.862220 2.591155 2.669066
-1.504904 1.589455 1.777756 1.887229 2.506207 2.617754
-1.628411 1.697438 1.830602 1.957574 2.495413 2.652982
-1.655345 1.726761 1.914454 2.042947 2.589709 2.658972
-1.698171 1.754006 1.967189 2.090429 2.602705 2.677128
-1.676303 1.767709 2.042847 2.156668 2.628324 2.690687
-1.724974 1.789927 2.022254 2.138454 2.576232 2.671774
-1.748186 1.802674 2.037781 2.180248 2.542513 2.638948
-1.727494 1.820586 1.984490 2.159068 2.525266 2.641113
-1.681162 1.820947 1.975700 2.157376 2.485796 2.590414
-1.695585 1.807190 1.993679 2.180888 2.380331 2.560860
-1.706934 1.810695 2.008115 2.133097 2.420753 2.641751
-1.654579 1.765733 2.024758 2.124029 2.493478 2.660848
-1.482280 1.849534 2.039337 2.240485 2.457215 2.547774
-1.603912 1.832539 2.051601 2.251630 2.461138 2.560412
-1.611914 1.787316 2.134457 2.250322 2.620939 2.678279
-1.702258 1.857664 2.093573 2.245781 2.633559 2.687798
-1.692364 1.776254 2.026193 2.275357 2.580552 2.683245
-1.587105 1.750297 1.997944 2.242069 2.586538 2.691453
-1.535548 1.765338 2.053611 2.233619 2.646730 2.717875
-1.189624 1.336795 1.763750 2.001818 2.436073 2.594289
-1.190961 1.322629 1.662495 2.028538 2.347408 2.530977
-1.170930 1.394685 1.727435 2.022812 2.382661 2.552602
-1.082797 1.383312 1.623231 1.825654 2.463128 2.574492
-1.058861 1.316419 1.617844 1.734402 2.496675 2.607354
-1.031745 1.332707 1.534727 1.707419 2.433275 2.544209
-1.096632 1.405927 1.540583 1.719915 2.509655 2.573209
-1.088142 1.381934 1.507222 1.618554 2.484112 2.618437
-1.128355 1.341806 1.494171 1.715551 2.495969 2.579865
-1.175042 1.360111 1.572899 1.757164 2.481162 2.588909
-1.251837 1.388286 1.580411 1.744290 2.530232 2.614281
-1.310739 1.444267 1.657251 1.823494 2.515110 2.614602
-1.329594 1.483659 1.703926 1.871461 2.532374 2.621921
-1.364647 1.503101 1.755842 1.919028 2.547482 2.624406
-1.400143 1.516781 1.808646 1.943813 2.572341 2.655551
-1.403936 1.536778 1.854571 1.961169 2.527770 2.650144
-1.441635 1.534902 1.873629 1.970753 2.528116 2.670832
-1.448614 1.528669 1.860977 1.951947 2.473243 2.657815
-1.451619 1.547843 1.824154 2.019980 2.462454 2.654097
-1.474914 1.548478 1.890892 1.995469 2.484609 2.659992
-1.432352 1.541523 1.888921 2.060202 2.407091 2.630443
-1.443739 1.529785 1.892698 1.996592 2.373799 2.620977
-1.379224 1.489730 1.897357 2.016742 2.416784 2.627496
-1.377069 1.463119 1.911655 2.022620 2.355389 2.608649
-1.331805 1.431037 1.929174 2.046904 2.374045 2.605001
-1.261392 1.448545 1.975458 2.082519 2.366860 2.620796
-1.222534 1.418974 1.979786 2.116310 2.439587 2.664630
-1.142938 1.304442 1.984504 2.071356 2.473077 2.672948
-1.163073 1.268521 1.930445 2.046302 2.305097 2.594448
-1.102508 1.246087 1.951734 2.103272 2.299777 2.571979
-1.010568 1.147332 1.902536 2.046240 2.288021 2.566997
-1.010466 1.307000 1.827652 2.076872 2.333263 2.555967
-1.246338 1.534633 1.859079 2.187994 2.388066 2.541619
-1.200493 1.578943 1.899233 2.165025 2.448881 2.583181
-0.969958 1.321171 1.879198 2.166270 2.417955 2.602455
-0.883738 1.359575 2.004523 2.100728 2.516977 2.633388
-0.844286 1.405546 2.057051 2.140524 2.516435 2.660060
-0.862435 1.502332 2.107411 2.205164 2.558187 2.660491
-0.940459 1.428240 2.139821 2.233319 2.564481 2.673761
-0.930987 1.583981 2.021904 2.152394 2.404035 2.506344
-1.046556 1.798258 1.988424 2.129290 2.357578 2.453538
-1.053483 1.593749 2.104331 2.232679 2.372807 2.498150
-1.137645 1.642783 2.089155 2.231807 2.383165 2.575567
-1.180782 1.899843 2.114705 2.223340 2.453147 2.554915
-1.144768 1.795798 2.058166 2.194105 2.452139 2.558749
-1.132549 1.688302 1.980246 2.107445 2.321949 2.446573
-1.155835 1.527004 1.951246 2.101869 2.265669 2.423260
-1.218988 1.551877 1.978933 2.129503 2.365239 2.547894
-1.269955 1.592834 1.957403 2.059254 2.477360 2.620075
-1.304775 1.597146 1.974266 2.084408 2.414413 2.613437
-1.304611 1.645522 1.976796 2.100584 2.364468 2.510600
-1.357449 1.721619 2.013975 2.141789 2.385178 2.512136
-1.335725 1.833907 2.001270 2.155846 2.401439 2.496098
-1.311398 1.558292 1.938760 2.063279 2.307274 2.526616
-1.360360 1.440763 1.893578 2.075310 2.237527 2.504599
-1.331599 1.468494 1.928903 2.060963 2.318029 2.567821
-1.318611 1.537603 1.924470 2.015195 2.358808 2.593307
-1.214364 1.546191 1.882099 1.995250 2.377928 2.652939
-1.296335 1.566534 1.875140 2.003277 2.476321 2.631527
-1.397784 1.586154 1.861480 2.030113 2.587065 2.654646
-1.475237 1.644203 1.915883 2.047027 2.653267 2.714423
-1.524741 1.716019 1.957822 2.067654 2.623703 2.690243
-1.578686 1.677809 1.940919 2.066782 2.613829 2.704583
-1.558659 1.702533 1.930114 2.028274 2.615049 2.686527
-1.500895 1.699904 1.908920 1.998738 2.620634 2.691280
-1.442946 1.702672 1.900985 1.975333 2.624730 2.699244
-1.372883 1.638290 1.917707 2.028286 2.626184 2.697452
-1.284224 1.656214 1.897845 1.992564 2.644425 2.707381
-1.204035 1.651822 1.889771 1.992564 2.638494 2.709577
-1.149198 1.622068 1.884510 1.979246 2.632691 2.699244
-1.133732 1.618626 1.895041 1.977544 2.625046 2.694884
-1.157568 1.662329 1.889784 1.978395 2.626035 2.684544
-1.218943 1.667105 1.879063 2.005165 2.602271 2.658132
-1.224226 1.626864 1.791981 1.894650 2.517637 2.647870
-1.354348 1.558760 1.843077 1.930892 2.571225 2.630861
-1.339527 1.595092 1.762248 1.979267 2.546017 2.613198
-1.389217 1.592419 1.859636 1.962120 2.550950 2.637714
-1.441267 1.590433 1.879393 1.987047 2.582006 2.666738
-1.431033 1.609808 1.890274 2.037874 2.525040 2.672056
-1.468384 1.575421 1.945848 2.029866 2.551470 2.705315
-1.450092 1.601430 1.954103 2.062799 2.534132 2.666966
-1.482171 1.565438 1.973588 2.124154 2.520208 2.656022
-1.429418 1.560169 1.984368 2.078415 2.510933 2.668346
-1.440913 1.587927 1.976090 2.097963 2.464144 2.621669
-1.432466 1.582610 1.973345 2.159930 2.500511 2.668329
-1.429101 1.593924 1.974811 2.070207 2.527049 2.683794
-1.377247 1.571046 1.937033 2.094336 2.488609 2.653189
-1.485270 1.572718 1.935520 2.015863 2.471891 2.687018
-1.473606 1.569260 1.872618 1.962880 2.412797 2.654369
-1.486059 1.580245 1.866252 1.975544 2.318749 2.586712
-1.465213 1.581118 1.784993 1.913021 2.172477 2.555915
-1.433656 1.566339 1.728508 1.853259 2.061966 2.413952
-1.367612 1.543842 1.700068 1.854972 2.034622 2.282022
-1.503264 1.657179 1.809362 1.937669 2.143191 2.435605
-1.340742 1.593266 1.833843 2.129408 2.468938 2.572839
-1.336721 1.481696 1.944774 2.230613 2.480290 2.580121
-1.321318 1.603141 1.968333 2.203371 2.515102 2.650047
-1.341931 1.668341 1.988838 2.185252 2.564141 2.653216
-1.315554 1.648897 1.959899 2.147638 2.516885 2.612616
-1.277314 1.620218 2.001858 2.229409 2.531549 2.621818
-1.305168 1.578599 2.038627 2.295512 2.565341 2.654838
-1.330511 1.609911 1.991543 2.262708 2.563339 2.665956
-1.374004 1.683930 1.980067 2.338575 2.595603 2.682727
-1.268703 1.389752 1.885378 2.110404 2.488114 2.638645
-1.216813 1.310045 1.854691 2.036714 2.277594 2.566534
-1.234945 1.337806 1.949427 2.059361 2.295326 2.566468
-1.188939 1.302387 1.996200 2.107442 2.349193 2.585236
-1.268977 1.440154 2.024771 2.136855 2.444005 2.664042
-1.274373 1.383125 2.066734 2.151173 2.407560 2.654201
-1.264553 1.356123 2.001656 2.118864 2.287784 2.569535
-1.234337 1.329784 2.063392 2.150768 2.367188 2.598596
-1.155210 1.257442 2.082496 2.211439 2.390593 2.620100
-1.199455 1.265557 1.934979 2.226691 2.540894 2.664195
-1.304701 1.526851 1.954550 2.174656 2.477694 2.621713
-1.638067 1.896263 2.077081 2.361007 2.646027 2.718839
-1.643821 1.943109 2.131987 2.329624 2.578717 2.645464
-1.640898 1.989224 2.161468 2.269205 2.586475 2.655395
-1.723007 1.910073 2.070189 2.259565 2.564392 2.640342
-1.652067 1.998733 2.135937 2.352824 2.652512 2.717475
-1.680722 2.074091 2.269666 2.453470 2.699939 2.763041
-1.695085 2.058973 2.193637 2.313571 2.639345 2.699445
-1.782955 2.014033 2.224899 2.332287 2.645355 2.724401
-1.705960 1.974745 2.180829 2.256084 2.575177 2.716938
-1.662556 1.988643 2.115183 2.205279 2.548376 2.657655
-1.562053 1.843896 2.173269 2.265891 2.477950 2.695966
-1.685920 1.795837 2.078330 2.180138 2.465369 2.667314
-1.680613 1.738555 1.994736 2.131193 2.473191 2.649544
-1.659289 1.833639 2.000087 2.140167 2.564913 2.692724
-1.714890 1.784823 1.974907 2.085230 2.566670 2.701036
-1.729112 1.826059 1.895041 2.053724 2.603924 2.699244
-1.696294 1.791079 1.916038 2.017742 2.583106 2.704200
-1.626844 1.720989 1.890443 2.014482 2.589192 2.689135
-1.574181 1.677998 1.880801 1.982799 2.574984 2.664083
-1.432597 1.676378 1.834673 1.964658 2.535300 2.638654
-1.318535 1.535375 1.836957 1.932882 2.478408 2.578350
-1.226292 1.492951 1.836423 1.946067 2.430171 2.582074
-1.098912 1.499048 1.896293 2.028872 2.540535 2.618603
-1.034465 1.533372 1.964842 2.070966 2.578583 2.651519
-0.979835 1.480912 1.975960 2.089319 2.534240 2.632634
-0.916592 1.481293 1.967506 2.053292 2.558345 2.642742
-0.937338 1.474374 2.023762 2.110460 2.585438 2.665463
-0.873055 1.560533 2.028802 2.086416 2.575020 2.684778
-0.901938 1.628414 2.031806 2.102850 2.610158 2.685650
-0.862562 1.556144 1.997573 2.081742 2.533196 2.615757
-0.906140 1.665744 2.019373 2.133337 2.581928 2.661153
-0.872836 1.638660 2.038436 2.097283 2.645014 2.697786
-0.829264 1.441895 2.039191 2.111142 2.611659 2.688610
-0.825197 1.304534 2.056354 2.143792 2.590309 2.657819
-0.793520 1.521024 1.979438 2.058424 2.596225 2.668581
-0.849751 1.485532 1.986103 2.055458 2.624269 2.701899
-0.849936 1.385589 2.007518 2.060577 2.567229 2.678449
-0.829655 1.230975 1.988404 2.101475 2.530728 2.677331
-0.940677 1.264510 1.946316 2.046724 2.499806 2.677984
-1.038884 1.297487 1.958215 2.035997 2.406970 2.650323
-1.157909 1.247311 1.892511 1.984329 2.396990 2.663399
-1.237064 1.318827 1.843309 1.954773 2.420851 2.693910
-1.328871 1.403948 1.808685 1.946118 2.400888 2.683397
-1.393193 1.460812 1.822128 1.939601 2.242548 2.723232
-1.370957 1.526137 1.785367 1.963164 2.136749 2.644805
-1.501135 1.606768 1.841831 2.009462 2.198461 2.614649
-1.467944 1.551473 1.849852 1.982829 2.208604 2.514793
-1.405944 1.480977 1.855980 1.997060 2.178717 2.490007
-1.448170 1.520957 1.868813 1.975365 2.241031 2.616351
-1.380808 1.612670 1.869962 2.026788 2.443477 2.639977
-1.483716 1.596112 1.969733 2.100913 2.577431 2.688144
-1.467685 1.578222 1.986564 2.194709 2.570945 2.671094
-1.496302 1.614196 2.032020 2.218322 2.553463 2.681813
-1.596958 1.722731 2.144525 2.319980 2.604392 2.703958
-1.563283 1.830072 2.213128 2.432926 2.641108 2.721000
-1.591103 1.948477 2.288414 2.486581 2.666837 2.743573
-1.475707 1.718658 2.050982 2.217962 2.487280 2.571804
-1.558930 1.772302 2.094474 2.234464 2.518928 2.597737
-1.567586 1.822091 2.100593 2.286654 2.533948 2.648113
-1.750029 1.936668 2.135601 2.347638 2.546896 2.638316
-1.756882 1.998584 2.116800 2.223412 2.556559 2.647062
-1.700043 1.922262 2.075348 2.184374 2.556081 2.639062
-1.598667 1.709712 1.994558 2.098788 2.521397 2.628442
-1.609782 1.719799 1.937528 2.091978 2.547584 2.621070
-1.580745 1.686692 1.927934 2.059508 2.580331 2.643528
-1.541164 1.684662 1.944797 2.038248 2.568516 2.637104
-1.474497 1.633889 1.881331 1.988847 2.554704 2.623589
-1.427685 1.616808 1.898469 1.994121 2.545908 2.635844
-1.366974 1.583736 1.860760 2.018090 2.526247 2.594032
-1.257899 1.562399 1.870764 1.961750 2.512050 2.589589
-1.183313 1.571246 1.867445 1.988791 2.543767 2.607786
-1.137720 1.607193 1.879149 2.008769 2.536804 2.607481
-1.053818 1.511423 1.904439 2.002387 2.584849 2.657089
-1.029306 1.560669 1.913466 1.984439 2.613420 2.670916
-0.990299 1.520302 1.919708 2.005988 2.615870 2.705960
-0.927002 1.486845 1.900099 1.977768 2.614622 2.695757
-0.924166 1.500302 1.837270 1.915819 2.601787 2.702827
-0.901854 1.422756 1.898010 1.950141 2.572992 2.759299
-0.910623 1.286484 1.801282 1.925793 2.438152 2.671294
-0.904293 1.226137 1.873337 1.946907 2.485265 2.645532
-0.872654 1.122664 1.912497 2.047619 2.468062 2.645490
-1.136081 1.248013 1.725399 2.180627 2.493778 2.579400
-1.161500 1.346974 1.804044 2.157021 2.550312 2.633164
-1.287295 1.663717 2.044188 2.321923 2.599284 2.687129
-1.456799 1.758274 2.055266 2.310654 2.549315 2.660074
-1.416948 1.741370 2.104189 2.357764 2.591761 2.679543
-1.379535 1.752525 2.173415 2.361073 2.617497 2.699322
-1.361005 1.762025 2.115710 2.330663 2.562002 2.650389
-1.340777 1.685357 2.024889 2.281946 2.547415 2.639463
-1.278174 1.686145 1.961407 2.165468 2.554171 2.647873
-1.294524 1.547620 1.981967 2.183432 2.547510 2.637235
-1.201621 1.343641 2.007859 2.089427 2.535679 2.660742
-1.201995 1.332111 1.949153 2.051811 2.553202 2.665468
-1.180355 1.354250 1.890523 2.069912 2.515229 2.620120
-1.128725 1.419757 1.854779 2.056632 2.480702 2.583539
-1.133191 1.402342 1.822656 2.013606 2.539914 2.639438
-1.149266 1.376927 1.821187 1.914934 2.562423 2.664037
-1.080871 1.408443 1.788020 1.879929 2.517515 2.656681
-1.152439 1.509600 1.822338 1.939812 2.528944 2.619151
-1.227262 1.543782 1.935413 2.017678 2.575512 2.665626
-1.253647 1.485940 1.945543 1.987370 2.539186 2.715089
-1.224504 1.521337 1.982156 2.044940 2.522684 2.687446
-1.258716 1.476124 1.981858 2.073104 2.536174 2.634089
-1.255580 1.471131 1.983938 2.052555 2.541040 2.708650
-1.221419 1.556731 2.013319 2.089772 2.538596 2.706495
-1.178484 1.474650 2.007635 2.122088 2.560256 2.629434
-1.136643 1.459288 2.033733 2.100427 2.544702 2.689126
-1.035202 1.462561 2.024973 2.194093 2.530601 2.662208
-1.090875 1.522421 2.038442 2.129424 2.587618 2.687392
-1.054541 1.538340 2.000589 2.084015 2.516505 2.644331
-1.069567 1.471150 1.977006 2.102657 2.548224 2.645658
-1.084637 1.235068 1.999027 2.091007 2.405191 2.622410
-1.073907 1.180490 1.961383 2.101877 2.255303 2.531797
-1.185536 1.320277 2.006751 2.098846 2.443082 2.582972
-1.256811 1.419989 1.983529 2.130962 2.470417 2.558689
-1.290736 1.391916 1.995379 2.106560 2.351663 2.485168
-1.428569 1.748298 2.044813 2.277573 2.513087 2.625248
-1.495766 1.686660 2.135657 2.292230 2.499007 2.616505
-1.482459 1.632012 2.083877 2.297241 2.488552 2.605327
-1.538843 1.630868 2.111745 2.223107 2.576837 2.693238
-1.551627 1.628553 2.040601 2.158000 2.590177 2.713514
-1.570014 1.637722 1.958103 2.124258 2.570176 2.692788
-1.534589 1.607992 1.801643 2.087274 2.392697 2.600933
-1.502776 1.607625 1.843802 2.082344 2.323284 2.522392
-1.515698 1.613442 1.837842 2.027239 2.402910 2.602242
-1.510034 1.607577 1.826422 1.955465 2.340570 2.679619
-1.445827 1.566639 1.756421 1.869709 2.296147 2.601653
-1.410709 1.488515 1.820022 1.910438 2.358230 2.614654
-1.301575 1.428283 1.812427 1.902581 2.293360 2.725276
-1.106808 1.351509 1.888725 1.956330 2.320442 2.646886
-1.056263 1.366917 1.866615 1.968949 2.421463 2.653524
-1.148746 1.368055 1.809637 2.064105 2.437788 2.604096
-0.990270 1.453159 1.887277 2.035172 2.296937 2.600298
-0.943695 1.204266 1.748001 1.886445 2.181614 2.509804
-1.057049 1.221402 1.835972 1.972438 2.154951 2.492969
-0.936404 1.225524 1.895053 1.998065 2.539531 2.644930
-0.941516 1.224493 1.966408 2.055267 2.515087 2.609082
-1.000240 1.314972 1.942001 2.051921 2.535877 2.634783
-1.031394 1.407401 1.953467 2.045443 2.550815 2.634369
-1.118870 1.441951 1.952517 2.061995 2.494339 2.608036
-1.197103 1.553158 1.887646 2.009186 2.472098 2.550658
-1.293802 1.588339 1.868376 2.045916 2.481096 2.566107
-1.353770 1.610646 1.897619 2.083477 2.408292 2.543397
-1.403681 1.521997 1.891672 2.054144 2.357288 2.512253
-1.370402 1.446254 1.871326 1.998144 2.336676 2.570693
-1.499387 1.755248 2.090328 2.282953 2.484033 2.574394
-1.567708 1.842611 2.136623 2.278726 2.477117 2.576067
-1.591554 1.767544 2.169415 2.302935 2.525126 2.637496
-1.458272 1.799744 2.227216 2.397500 2.616529 2.705570
-1.496705 1.846042 2.279896 2.437186 2.649673 2.726623
-1.502759 1.731322 2.268727 2.464213 2.623623 2.706745
-1.497299 1.617932 2.156580 2.386255 2.579030 2.664716
-1.379977 1.538687 1.850634 2.109517 2.410662 2.586146
-1.405875 1.497926 1.741705 1.932278 2.337183 2.563846
-1.346170 1.431041 1.657425 1.884420 2.373948 2.587354
-1.307909 1.406366 1.734141 1.875825 2.460720 2.602094
-1.273940 1.571154 1.771276 1.912248 2.536452 2.595610
-1.200061 1.575178 1.770854 1.877630 2.508016 2.579146
-1.125813 1.539421 1.722626 1.859971 2.511653 2.574626
-1.064900 1.484512 1.690862 1.832750 2.519579 2.589278
-1.042869 1.483231 1.627118 1.867084 2.495867 2.550264
-0.950910 1.474823 1.576110 1.830086 2.519438 2.569906
-1.004516 1.423026 1.550120 1.835220 2.473605 2.544366
-1.026409 1.365688 1.510656 1.879110 2.467179 2.543867
-0.978321 1.338491 1.528018 1.913878 2.465066 2.524725
-0.922555 1.409585 1.520258 1.932657 2.404714 2.472216
-1.009019 1.345028 1.518729 1.999531 2.463064 2.544939
-0.989351 1.433164 1.573872 2.015438 2.401202 2.490979
-1.035325 1.556325 1.677312 2.086779 2.481518 2.567949
-1.004119 1.575292 1.796393 2.075521 2.402912 2.574238
-1.037355 1.681818 1.943106 2.065425 2.478887 2.598899
-1.005855 1.684746 1.972392 2.109307 2.565052 2.623513
-0.954873 1.719791 2.006188 2.112346 2.598630 2.682782
-0.937994 1.728321 1.993763 2.105254 2.632050 2.700706
-0.889626 1.709530 2.001291 2.090092 2.620540 2.709802
-0.912128 1.657624 1.966778 2.058636 2.626429 2.702918
-0.972006 1.569116 1.985953 2.130241 2.569149 2.677258
-1.038791 1.651170 2.008290 2.118109 2.599188 2.701292
-1.102203 1.624993 1.998759 2.125031 2.569760 2.646643
-1.187738 1.639367 2.059243 2.147304 2.475862 2.634964
-1.274099 1.590670 2.016754 2.099633 2.548725 2.668989
-1.373403 1.630011 1.981494 2.070929 2.505950 2.689328
-1.511208 1.602606 1.911343 2.022899 2.475945 2.645751
-1.553078 1.639398 1.870403 1.975613 2.473431 2.626572
-1.633420 1.773325 1.875127 1.959482 2.413151 2.625912
-1.596719 1.747314 1.878046 2.049018 2.587489 2.669276
-1.664674 1.933354 2.156044 2.280025 2.462736 2.571555
-1.551190 1.695801 2.047099 2.236977 2.447592 2.570843
-1.648304 1.728067 2.060789 2.273739 2.475137 2.631203
-1.633548 1.757572 2.089279 2.240980 2.436119 2.556847
-1.608644 1.684711 2.123747 2.256566 2.486503 2.598234
-1.653176 1.714541 2.105354 2.203230 2.509317 2.641781
-1.541046 1.679960 2.104266 2.247262 2.540379 2.626724
-1.559664 1.659637 2.101376 2.213674 2.473238 2.562999
-1.608810 1.671776 2.071434 2.184829 2.493283 2.639463
-1.538876 1.610189 2.083083 2.171544 2.554389 2.650993
-1.511021 1.595459 2.031637 2.130089 2.587598 2.660399
-1.340693 1.587842 1.931002 2.117119 2.599860 2.676574
-1.484682 1.533251 2.024488 2.113154 2.548321 2.659954
-1.534337 1.608310 2.031541 2.136001 2.537102 2.617716
-1.571577 1.618314 2.056726 2.139748 2.525414 2.622206
-1.564471 1.631266 2.060592 2.166039 2.469995 2.635657
-1.533650 1.663515 2.093962 2.190787 2.406743 2.622754
-1.570124 1.631042 2.049374 2.165169 2.393566 2.588498
-1.552473 1.634522 2.008478 2.098878 2.509195 2.669322
-1.498536 1.602806 2.008880 2.099726 2.525137 2.659175
-1.450925 1.660536 1.991759 2.103304 2.544073 2.696474
-1.447598 1.569099 1.993051 2.079756 2.587712 2.676395
-1.394567 1.544697 2.006663 2.078973 2.579015 2.721882
-1.347921 1.507746 1.993785 2.077331 2.510234 2.682685
-1.265189 1.355385 1.877848 2.063826 2.425800 2.657797
-1.266300 1.376932 2.008877 2.275008 2.479039 2.636159
-1.414729 1.680622 2.057398 2.332754 2.549975 2.652454
-1.499883 1.708789 2.054742 2.313580 2.521026 2.613915
-1.445680 1.741768 2.126388 2.338809 2.495118 2.597970
-1.459203 1.792340 2.113493 2.346074 2.563702 2.664973
-1.416845 1.644394 2.131474 2.322905 2.578800 2.677164
-1.447967 1.708221 2.144894 2.272584 2.593212 2.700869
-1.474608 1.742978 2.066944 2.341635 2.601749 2.685249
-1.346721 1.653940 1.999147 2.218537 2.633365 2.723602
-1.375208 1.551414 2.052682 2.232013 2.586844 2.697029
-1.260950 1.501751 1.925196 2.033937 2.546694 2.652031
-1.259339 1.500189 1.909647 1.982913 2.545881 2.638673
-1.252838 1.563842 1.910593 1.973683 2.579307 2.664280
-1.263002 1.546326 1.878080 2.031152 2.583468 2.653793
-1.265196 1.521273 1.905708 1.967385 2.581430 2.658715
-1.307704 1.547718 1.881421 1.962040 2.573475 2.658828
-1.291340 1.575015 1.915239 1.985560 2.602082 2.697699
-1.295431 1.626460 1.923299 2.023724 2.591291 2.680142
-1.301210 1.624080 1.878934 1.998083 2.560098 2.634506
-1.305813 1.620922 1.888028 1.989036 2.606227 2.669425
-1.308088 1.642328 1.885958 2.013573 2.611911 2.696648
-1.312101 1.627858 1.861841 1.974096 2.602616 2.658487
-1.292897 1.605725 1.877131 1.973395 2.599643 2.682844
-1.273139 1.591736 1.870416 1.947454 2.602328 2.674146
-1.283582 1.620817 1.847273 1.928033 2.590051 2.636876
-1.246205 1.560066 1.851625 1.954533 2.587535 2.673542
-1.260393 1.539639 1.831617 1.928432 2.552288 2.629629
-1.261220 1.505229 1.857309 1.933908 2.569004 2.696314
-1.283108 1.719865 1.823903 1.976026 2.565436 2.628748
-1.314387 1.617735 1.804065 1.960535 2.596814 2.686738
-1.338699 1.637284 1.896932 2.009128 2.523466 2.637375
-1.336475 1.577029 1.850025 1.943237 2.521339 2.596832
-1.398912 1.549275 1.724463 1.861933 2.166791 2.466332
-1.406894 1.497435 1.805042 1.909122 2.284281 2.542582
-1.474849 1.579373 1.970765 2.079699 2.371434 2.542616
-1.452309 1.539401 2.076665 2.137999 2.442972 2.649515
-1.450617 1.506612 2.036385 2.131452 2.484829 2.674720
-1.434796 1.583083 2.027674 2.136807 2.429113 2.578344
-1.087572 1.367208 1.786303 2.025035 2.298079 2.515673
-0.992092 1.436432 1.725512 1.965111 2.425717 2.549021
-0.969474 1.497321 1.730092 2.016045 2.414373 2.633316
-0.936277 1.413012 1.683609 2.029768 2.443096 2.552830
-1.176352 1.559638 1.748772 2.061891 2.311483 2.434690
-1.067106 1.406642 1.643885 1.978806 2.374725 2.547845
-0.989262 1.333111 1.475085 1.728650 2.492018 2.553467
-0.957471 1.308545 1.424561 1.823472 2.490215 2.552316
-1.035765 1.254486 1.352081 1.786247 2.539488 2.585779
-1.023678 1.232418 1.398476 1.875768 2.451677 2.540251
-1.037249 1.247286 1.387422 2.008554 2.419268 2.496115
-1.045924 1.231687 1.361952 1.887611 2.384450 2.471500
-1.000981 1.250837 1.376662 1.767666 2.398053 2.484439
-1.061773 1.214611 1.410756 1.728252 2.423979 2.514269
-1.168228 1.291194 1.597509 1.900015 2.415419 2.555014
-1.150788 1.412860 1.825953 1.953264 2.400052 2.535324
-1.166923 1.517635 1.943529 2.034246 2.373359 2.521470
-1.183183 1.523161 1.995315 2.119892 2.433461 2.591155
-1.159482 1.521728 2.072369 2.176962 2.514904 2.660759
-1.260320 1.722656 2.116773 2.249048 2.534123 2.645628
-1.450433 1.717713 2.048790 2.212752 2.499485 2.636128
-1.449227 1.653123 2.023641 2.196888 2.453054 2.612516
-1.388122 1.597569 1.968649 2.163453 2.425431 2.578033
-1.347603 1.449808 1.894138 2.168973 2.446471 2.602268
-1.398006 1.471755 1.922063 2.120957 2.396434 2.600718
-1.428663 1.541308 2.046052 2.132513 2.397088 2.643104
-1.492673 1.585159 2.059339 2.158303 2.480824 2.648749
-1.558991 1.648786 2.037511 2.153321 2.512380 2.647660
-1.587505 1.659085 2.020500 2.139692 2.537458 2.616564
-1.634348 1.739360 2.044485 2.218194 2.530130 2.622735
-1.650152 1.736774 2.049269 2.148919 2.551868 2.651288
-1.640705 1.707347 1.991329 2.119563 2.587595 2.642835
-1.655822 1.709750 1.941946 2.090791 2.570081 2.630366
-1.606441 1.695623 1.852762 2.047845 2.554897 2.628090
-1.484591 1.657033 1.822979 2.008956 2.584027 2.653723
-1.348381 1.627797 1.779073 1.897327 2.521867 2.646403
-1.155644 1.464872 1.763798 1.943553 2.555854 2.642088
-1.339453 1.676328 1.971041 2.186803 2.438887 2.571072
-1.297378 1.615525 1.946759 2.151180 2.429841 2.558129
-1.136457 1.519887 1.867226 2.107387 2.452727 2.553710
-0.943433 1.350976 1.714327 1.830884 2.380038 2.573606
-0.933950 1.078579 1.553087 1.662344 2.027950 2.453145
-0.896937 1.246931 1.586629 1.684078 2.397137 2.611707
-0.892078 1.350059 1.560075 1.689846 2.506278 2.607560
-0.772181 1.313675 1.525659 1.650282 2.468977 2.636413
-0.863603 1.328577 1.481135 1.768890 2.496778 2.546566
-0.908312 1.258415 1.382771 1.699751 2.448589 2.547326
-0.863083 1.273798 1.422414 1.575877 2.509924 2.567103
-0.798143 1.233378 1.328045 1.718547 2.545479 2.654885
-0.937997 1.297209 1.447389 1.659450 2.539430 2.664368
-1.015311 1.282646 1.449652 1.656931 2.519587 2.597241
-1.012603 1.308086 1.428756 1.742642 2.581377 2.654752
-1.075222 1.359942 1.466363 1.790456 2.582927 2.654917
-1.174719 1.354592 1.470683 1.808114 2.611814 2.690601
-1.304671 1.380565 1.486415 1.863253 2.499088 2.646637
-1.329253 1.458935 1.599739 1.985102 2.412241 2.489601
-1.326849 1.466962 1.650712 1.972882 2.173652 2.363777
-1.440729 1.597862 1.756923 1.942121 2.134420 2.330899
-1.490912 1.615283 1.799725 1.989183 2.307191 2.535959
-1.523001 1.676436 1.841390 2.084493 2.490067 2.619504
-1.536446 1.672927 1.834339 2.067942 2.594848 2.655730
-1.585206 1.673419 1.879347 2.026137 2.609162 2.691334
-1.576452 1.662112 1.868110 1.987273 2.629831 2.702492
-1.561137 1.629084 1.910414 2.005430 2.633437 2.726135
-1.531209 1.615548 1.873644 1.966279 2.522587 2.706064
-1.473294 1.591222 1.908945 1.973407 2.535042 2.733124
-1.412536 1.473645 1.871722 1.957323 2.341205 2.740704
-1.379808 1.473241 1.923919 1.986068 2.447172 2.657583
-1.333691 1.500115 1.933534 2.138032 2.501795 2.615830
-1.405765 1.570091 2.028114 2.332669 2.573681 2.664117
-1.386052 1.546746 2.101843 2.380119 2.607300 2.712463
-1.420552 1.664080 2.096840 2.287671 2.545433 2.645671
-1.429919 1.632895 2.056448 2.245342 2.469727 2.594625
-1.450338 1.542326 1.936139 2.160089 2.389658 2.594948
-1.458650 1.545840 1.973946 2.132840 2.280546 2.519107
-1.499624 1.621854 1.924363 2.086584 2.253820 2.393464
-1.480124 1.596614 1.822901 2.030079 2.212455 2.440593
-1.385572 1.515794 1.763525 2.007562 2.207014 2.505163
-1.363477 1.483710 1.745394 2.020826 2.177380 2.428417
-1.422412 1.526361 1.802470 2.041367 2.267629 2.509983
-1.451781 1.539504 1.888618 2.079745 2.258528 2.500819
-1.462745 1.548876 1.925748 2.065292 2.320100 2.591877
-1.459612 1.526791 1.937299 2.029745 2.425999 2.618215
-1.426774 1.495962 1.934803 2.028683 2.474317 2.639936
-1.395478 1.494605 1.923542 2.006865 2.508795 2.651596
-1.315323 1.475877 1.925867 2.012444 2.562544 2.642674
-1.216208 1.542312 1.867609 1.962911 2.578507 2.638914
-1.188119 1.592111 1.826165 1.956758 2.592728 2.659305
-1.157283 1.519027 1.841285 1.936129 2.596722 2.669387
-1.042732 1.334857 1.852810 1.927812 2.509256 2.721390
-1.076921 1.512728 1.892211 1.976017 2.370736 2.635640
-1.328644 1.555209 1.826957 2.080018 2.447934 2.607755
-1.271225 1.383527 1.740551 2.048721 2.356257 2.567108
-1.288765 1.385478 1.793872 1.977849 2.390396 2.604554
-1.328655 1.422241 1.805644 2.002822 2.289156 2.544301
-1.377945 1.493655 1.793682 2.031868 2.353733 2.518906
-1.384430 1.453654 1.838071 2.001840 2.390785 2.635123
-1.289457 1.403427 1.871018 1.986122 2.479981 2.723796
-1.207888 1.388220 1.865052 2.031661 2.450066 2.591415
-1.218628 1.309314 1.909852 2.003782 2.499425 2.604984
-1.178831 1.273297 1.832814 2.025041 2.508629 2.650229
-1.147475 1.259195 1.930161 2.027735 2.522075 2.634075
-1.100906 1.268026 1.857908 1.951898 2.508895 2.660387
-1.069825 1.225671 1.888950 1.974341 2.492132 2.592105
-1.042255 1.182210 1.891740 2.039958 2.559652 2.679327
-0.956414 1.180966 1.881463 1.994332 2.316474 2.617691
-1.061791 1.571696 1.926569 2.107177 2.404155 2.525452
-1.374312 1.475896 1.678426 1.972424 2.364289 2.516531
-1.363442 1.455771 1.763156 1.970798 2.368334 2.586977
-1.423043 1.591891 1.798197 2.012780 2.388112 2.602184
-1.527265 1.605781 1.909513 2.033429 2.406683 2.593463
-1.585135 1.664508 1.918013 2.026537 2.425727 2.600924
-1.611888 1.728561 1.907667 2.034036 2.395680 2.641770
-1.463013 1.624657 1.872286 1.998243 2.487821 2.662465
-1.507075 1.597912 1.893748 1.997011 2.535979 2.672459
-1.502401 1.618027 1.888560 2.024162 2.581852 2.656536
-1.553117 1.639479 1.918920 2.034284 2.576859 2.655677
-1.577358 1.648261 1.958093 2.053413 2.567886 2.656516
-1.595375 1.654628 1.997767 2.099746 2.531642 2.675206
-1.621639 1.704007 1.957750 2.074637 2.584314 2.660506
-1.618433 1.711386 1.954786 2.067454 2.533767 2.695229
-1.617851 1.716314 1.949677 2.103360 2.635944 2.686892
-1.649322 1.746309 1.901606 2.064352 2.606774 2.690238
-1.635059 1.769603 1.904617 2.019099 2.607597 2.713325
-1.645565 1.779500 1.868948 1.965332 2.592154 2.714895
-1.686573 1.757504 1.858066 1.922036 2.505271 2.698890
-1.612716 1.703234 1.831053 1.925901 2.373806 2.613684
-1.244351 1.409563 1.713462 1.967702 2.351463 2.537356
-1.269988 1.387301 1.640967 1.991832 2.324911 2.501768
-1.305349 1.455772 1.788777 2.091229 2.487237 2.614726
-1.413862 1.518807 1.888520 2.252275 2.448086 2.594722
-1.409418 1.591460 1.944717 2.196924 2.518393 2.638233
-1.399142 1.703314 1.966146 2.224863 2.616908 2.734082
-1.375311 1.636377 2.061764 2.292420 2.586624 2.705744
-1.394667 1.733415 2.073598 2.297154 2.573824 2.672888
-1.366082 1.738611 2.016634 2.285662 2.605490 2.693517
-1.360620 1.601685 1.967966 2.194839 2.564848 2.657918
-1.354700 1.471541 1.990171 2.165439 2.569000 2.679116
-1.319372 1.403922 2.030220 2.115007 2.452702 2.635911
-1.303257 1.374731 1.975040 2.111171 2.369818 2.660606
-1.325790 1.431051 2.036171 2.113943 2.475995 2.685073
-1.307478 1.510363 2.117703 2.179166 2.554579 2.695776
-1.311427 1.548305 2.128351 2.279725 2.551702 2.645499
-1.293775 1.442228 2.115561 2.289555 2.415905 2.531210
-1.278672 1.697114 2.092498 2.199540 2.368518 2.561138
-1.292641 1.867932 2.128826 2.206329 2.450839 2.551778
-1.234857 1.631071 2.143705 2.304460 2.491014 2.565728
-1.219953 1.367565 2.149802 2.218488 2.495215 2.635299
-1.208902 1.484837 2.180300 2.276690 2.526332 2.626732
-1.165264 1.458241 2.155590 2.227283 2.490182 2.596799
-1.116188 1.492178 2.177271 2.241905 2.532331 2.620529
-1.096897 1.524925 2.093489 2.345253 2.480356 2.611159
-1.043785 1.369028 2.229277 2.306648 2.527431 2.613026
-1.080719 1.336126 2.135541 2.240613 2.463443 2.634282
-1.126263 1.502538 2.065329 2.274832 2.512833 2.588250
-1.199125 1.448000 2.040575 2.216856 2.449127 2.544297
-1.244303 1.540831 2.036533 2.174834 2.470267 2.580345
-1.277190 1.574057 2.066371 2.150365 2.508540 2.611728
-1.341754 1.576876 2.031475 2.120651 2.496164 2.575343
-1.335444 1.541598 1.994337 2.108804 2.518844 2.622948
-1.351719 1.543708 2.003315 2.075354 2.579158 2.656631
-1.359299 1.470533 1.968461 2.042323 2.565151 2.664841
-1.368199 1.433218 1.983774 2.044947 2.438603 2.670598
-1.351177 1.426131 1.991290 2.087726 2.430748 2.616370
-1.349866 1.483300 2.000270 2.242826 2.535909 2.629047
-1.322061 1.596777 2.113123 2.408146 2.548980 2.625263
-1.381288 1.648758 2.192458 2.378361 2.579516 2.654496
-1.372134 1.542663 2.062546 2.307310 2.475587 2.580621
-1.363570 1.463481 1.864764 2.288459 2.467800 2.571685
-1.335793 1.536300 1.886159 2.221871 2.543381 2.670529
-1.259757 1.393352 1.604761 1.934288 2.430512 2.509599
-1.224722 1.349648 1.481936 1.836832 2.384963 2.463134
-1.253661 1.369206 1.505507 1.994342 2.366061 2.454562
-1.250448 1.372217 1.563439 2.133283 2.391531 2.461107
-1.298984 1.412532 1.560005 2.162846 2.475577 2.551467
-1.308701 1.487231 1.616571 2.140891 2.422519 2.527844
-1.362265 1.509740 1.691137 2.151850 2.425060 2.504008
-1.415186 1.573817 1.726343 2.145690 2.423615 2.518947
-1.468304 1.624569 1.768003 2.107079 2.433687 2.501879
-1.474213 1.645172 1.829377 2.150471 2.330539 2.454132
-1.488731 1.662220 1.853177 2.160434 2.390722 2.507469
-1.515371 1.685102 1.820897 2.090815 2.477135 2.541320
-1.533941 1.681022 1.911151 2.101052 2.431211 2.507421
-1.547022 1.762747 1.905315 2.057302 2.369967 2.496458
-1.524747 1.707503 1.880853 2.145136 2.331290 2.443298
-1.532670 1.689464 1.838440 2.066707 2.352074 2.487585
-1.449082 1.639914 1.786524 2.047043 2.328788 2.426218
-1.393415 1.607003 1.752128 2.065963 2.381000 2.473775
-1.234921 1.620384 1.751709 2.079353 2.400969 2.471820
-1.128649 1.589193 1.725978 2.097814 2.421776 2.507176
-1.205122 1.491109 1.707033 2.143134 2.407676 2.489596
-1.105985 1.524092 1.740260 2.142524 2.422755 2.532710
-1.146867 1.428089 1.698792 2.100330 2.423332 2.545496
-1.116015 1.351902 1.754307 2.146023 2.411698 2.527537
-1.178509 1.306840 1.824109 2.272040 2.452886 2.546314
-1.386046 1.686532 2.010818 2.148686 2.439205 2.570934
-1.334381 1.674050 1.962490 2.108725 2.403922 2.587496
-1.309542 1.519433 2.030598 2.119732 2.436082 2.620801
-1.199624 1.425192 2.037889 2.161327 2.493314 2.639529
-0.913804 1.251727 2.055079 2.176873 2.416854 2.644928
-0.822137 1.067331 2.019119 2.216592 2.395557 2.658189
-0.859923 0.985874 1.904285 2.160589 2.433708 2.639822
-0.906761 1.140617 2.010505 2.146239 2.469640 2.644134
-0.950845 1.253958 2.039526 2.095898 2.600275 2.711094
-0.953879 1.245319 1.985465 2.133152 2.543655 2.613003
-1.031672 1.286594 1.974619 2.037126 2.541018 2.690276
-1.051598 1.373163 1.905246 2.009638 2.495552 2.674053
-1.088262 1.297396 1.898694 2.018578 2.508840 2.690510
-1.146698 1.282269 1.930714 2.010155 2.439408 2.647009
-1.157205 1.343846 1.930823 2.029125 2.368152 2.598000
-1.247348 1.432742 1.942594 2.067451 2.392833 2.554304
-1.297617 1.516021 1.993391 2.079273 2.439458 2.548273
-1.386254 1.483598 1.965854 2.071612 2.444793 2.594366
-1.429692 1.499865 1.880633 2.074107 2.346203 2.604251
-1.569133 1.644482 1.942763 2.045196 2.370694 2.589367
-1.696361 1.745617 1.980943 2.093662 2.433481 2.583667
-1.694840 1.801151 1.961027 2.068322 2.452636 2.638290
-1.619793 1.785586 1.919626 2.055816 2.238163 2.498763
-1.223689 1.621225 1.791717 1.898693 2.161669 2.499947
-1.144413 1.452915 1.780893 1.866745 2.214208 2.494268
-1.135538 1.495124 1.820776 1.894356 2.115005 2.441578
-1.131378 1.535817 1.737318 1.842419 2.021638 2.425946
-1.212645 1.312165 1.752907 1.889323 2.108905 2.469701
-1.253951 1.352407 1.652652 1.960954 2.394436 2.568676
-1.362676 1.580790 1.913319 2.212617 2.381597 2.528987
-1.417331 1.582049 1.977630 2.237995 2.413078 2.580292
-1.383161 1.603552 2.016139 2.210126 2.449048 2.587234
-1.442111 1.544212 1.938946 2.141876 2.494998 2.590164
-1.381730 1.579156 1.982000 2.138775 2.485780 2.620572
-1.361593 1.597812 1.964935 2.138121 2.542610 2.622470
-1.360664 1.614689 2.010781 2.161500 2.460448 2.583897
-1.390092 1.628646 1.963826 2.130557 2.477732 2.613382
-1.346169 1.648499 2.082367 2.321708 2.555952 2.649424
-1.440422 1.742439 2.007648 2.208244 2.450993 2.577906
-1.444825 1.695062 2.026868 2.210477 2.414028 2.532766
-1.345541 1.589166 1.955423 2.129306 2.409889 2.543165
-1.400043 1.481922 1.947067 2.110259 2.313164 2.531167
-1.384776 1.484787 1.983872 2.107142 2.360088 2.585480
-1.429185 1.514936 2.019660 2.137662 2.329551 2.585292
-1.450546 1.518321 2.010034 2.102797 2.401692 2.603278
-1.441363 1.525406 1.964971 2.076719 2.376014 2.594808
-1.464787 1.521553 1.968987 2.077867 2.444963 2.621082
-1.486696 1.573684 2.001845 2.108515 2.433771 2.626158
-1.471032 1.543603 1.991659 2.111714 2.473307 2.645459
-1.415271 1.524488 2.012703 2.095751 2.458820 2.642016
-1.407514 1.501486 2.050311 2.156204 2.480187 2.623271
-1.376118 1.459583 2.009938 2.169415 2.480196 2.642689
-1.345946 1.472883 2.073124 2.184863 2.486126 2.610362
-1.306365 1.438379 2.090496 2.213143 2.554203 2.683954
-1.219262 1.423037 2.090917 2.170494 2.559623 2.668211
-1.180469 1.408080 1.935170 2.088177 2.548134 2.639438
-1.209541 1.528929 1.887266 1.961882 2.483440 2.649342
-1.219923 1.521384 1.939175 1.988023 2.460034 2.673476
-1.198754 1.474098 1.859112 1.981042 2.395346 2.719202
-1.118408 1.504845 1.897944 2.002376 2.242870 2.598523
-1.018525 1.459894 1.746590 2.051954 2.324856 2.458848
-0.866990 1.387782 1.654105 1.799741 2.325792 2.407380
-0.862252 1.365828 1.705762 1.802245 2.416352 2.493849
-0.928394 1.546454 1.716680 1.877069 2.379724 2.524594
-1.083354 1.487338 1.801149 2.005692 2.321736 2.558733
-1.057425 1.339797 1.834422 1.934601 2.279625 2.530701
-0.954787 1.140996 1.792870 1.891796 2.342908 2.492038
-0.996853 1.130036 1.792153 1.895409 2.236238 2.403350
-0.920268 1.069492 1.874858 2.072086 2.335228 2.486570
-0.954214 1.081065 1.827324 2.079149 2.238820 2.508120
-0.894487 1.013841 1.716536 2.018446 2.175347 2.482241
-0.842005 0.979634 1.644526 1.945897 2.271025 2.438632
-0.955710 1.090003 1.754054 1.967070 2.127836 2.448885
-0.954385 1.094473 1.727553 2.005579 2.266567 2.514397
-1.025620 1.137605 1.787527 2.002076 2.336896 2.511839
-1.013813 1.175105 1.881936 2.016643 2.345862 2.445716
-1.082667 1.227297 1.923243 2.022783 2.402376 2.520967
-1.118115 1.224136 1.824448 1.961745 2.245832 2.515829
-1.146448 1.298991 1.872929 1.995465 2.371727 2.526896
-1.188552 1.310653 1.902213 1.996780 2.290374 2.520538
-1.309924 1.416529 1.878448 2.050089 2.224176 2.387793
-1.394764 1.506270 1.934888 2.056817 2.271193 2.453341
-1.377933 1.572642 1.990697 2.083570 2.381595 2.606523
-1.444019 1.689297 1.997464 2.153207 2.361127 2.507701
-1.515035 1.642770 1.929088 2.159339 2.335507 2.497838
-1.540079 1.708314 1.883825 2.094981 2.398624 2.570098
-1.600911 1.698511 1.881481 2.085171 2.451013 2.653738
-1.502633 1.756061 2.040722 2.163397 2.376168 2.548669
-1.532107 1.855341 1.993840 2.139554 2.302488 2.430987
-1.484859 1.822055 1.964302 2.135961 2.337023 2.472337
-1.536688 1.766917 1.951249 2.090524 2.324175 2.529206
-1.582282 1.723852 1.912068 2.069366 2.302944 2.473896
-1.499712 1.593288 1.912697 2.034098 2.366553 2.553790
-1.434200 1.540709 1.867569 1.989167 2.323715 2.539399
-1.189101 1.500824 1.763417 1.976198 2.137279 2.441179
-1.165922 1.470178 1.772997 1.927098 2.088007 2.304301
-1.250154 1.600421 1.818068 1.922113 2.080252 2.241814
-1.122694 1.628796 1.814409 1.932949 2.099304 2.418672
-1.019615 1.510656 1.850726 1.995621 2.130205 2.457063
-0.958176 1.639680 1.840433 1.956534 2.104283 2.279028
-1.010543 1.537512 1.772221 1.930517 2.101622 2.248506
-0.904371 1.505016 1.664330 1.827875 2.278031 2.348418
-1.067733 1.454537 1.686858 1.803459 2.384372 2.499789
-1.262873 1.516004 1.882748 1.975559 2.353571 2.519731
-1.560637 1.698959 1.921539 2.000060 2.540292 2.605234
-1.665625 1.744091 1.995924 2.104003 2.538942 2.620162
-1.615168 1.748503 2.024112 2.126056 2.408165 2.614133
-1.678025 1.752954 2.027903 2.146564 2.382374 2.568508
-1.580352 1.680273 1.997415 2.122458 2.459846 2.587827
-1.590082 1.692050 1.934784 2.095757 2.552980 2.625876
-1.539000 1.620243 1.920765 2.031604 2.481670 2.592695
-1.408796 1.511786 1.744250 1.896588 2.412019 2.515579
-1.320558 1.487993 1.754964 1.896907 2.437159 2.563184
-1.174869 1.524851 1.708181 1.962955 2.513779 2.581010
-1.287639 1.559567 1.903084 2.105175 2.450979 2.599458
-1.224033 1.507999 1.922793 2.076370 2.372907 2.581210
-1.163218 1.444961 1.734673 2.020179 2.322152 2.541566
-1.212255 1.448003 1.638494 2.031919 2.229345 2.399467
-1.108889 1.283327 1.481151 1.907068 2.100013 2.293484
-1.155218 1.290372 1.476717 1.688065 2.089220 2.181765
-1.171472 1.290390 1.556515 1.825992 2.018143 2.243494
-1.149886 1.282652 1.601900 1.745296 2.110780 2.409060
-1.223914 1.360718 1.650069 1.792936 2.265100 2.370934
-1.254374 1.404539 1.706674 1.854649 2.276473 2.394690
-1.225833 1.442107 1.766130 1.924123 2.292396 2.394677
-1.211141 1.461886 1.804549 1.927018 2.361986 2.453285
-1.218638 1.405782 1.809530 1.914204 2.318449 2.520048
-1.222942 1.394674 1.840107 1.932398 2.391674 2.503193
-1.206898 1.372866 1.842954 1.943799 2.424465 2.578763
-1.246306 1.423826 1.866209 1.962415 2.436055 2.595659
-1.270919 1.455901 1.888055 1.976335 2.469281 2.582811
-1.198265 1.323940 1.880236 1.949408 2.471659 2.644805
-1.174323 1.293200 1.765612 2.019282 2.282243 2.576238
-1.141730 1.383190 1.882826 2.126532 2.453044 2.611191
-1.483342 1.650728 2.043593 2.193798 2.517271 2.622915
-1.446069 1.621898 1.999609 2.103532 2.493478 2.581923
-1.414671 1.630237 1.945678 2.061773 2.500655 2.588950
-1.438432 1.615586 1.903350 2.013028 2.426105 2.613642
-1.556674 1.623119 1.875461 1.972308 2.366695 2.629218
-1.466504 1.638319 1.796576 1.959267 2.457617 2.603231
-1.308284 1.481394 1.730539 1.979266 2.332265 2.538090
-1.301646 1.413738 1.674441 1.933375 2.143487 2.508142
-1.318907 1.416559 1.751644 1.913438 2.294089 2.555125
-1.324509 1.425623 1.844923 1.947411 2.375384 2.597366
-1.266998 1.359728 1.849155 1.950839 2.370723 2.579301
-1.162697 1.344305 1.906935 1.986568 2.470580 2.583422
-1.115998 1.365829 1.948029 2.040077 2.461135 2.583597
-1.061798 1.350291 2.006280 2.080459 2.451632 2.526961
-1.024331 1.233571 1.989411 2.085049 2.387181 2.495816
-0.962287 1.219238 1.967000 2.089191 2.424659 2.599861
-0.881533 1.356828 2.047429 2.155394 2.409074 2.508754
-0.856010 1.217716 2.008528 2.111528 2.424806 2.537738
-0.774065 0.965055 1.874139 2.035878 2.251024 2.527966
-0.820344 0.990331 1.960958 2.242123 2.349553 2.535465
-0.846158 1.062894 1.972506 2.169152 2.353165 2.556086
-0.748812 1.063441 1.949952 2.066846 2.364509 2.602003
-0.855725 1.158383 2.008420 2.144140 2.328495 2.600481
-0.862076 1.188230 1.906456 2.191351 2.368506 2.542645
-0.814218 1.194007 2.086397 2.156864 2.482953 2.574777
-0.811087 1.320952 2.038259 2.112835 2.508878 2.598939
-0.967874 1.191718 2.049318 2.146525 2.422668 2.566778
-1.008026 1.234198 2.040908 2.121036 2.480150 2.609085
-1.118175 1.312265 1.961423 2.071245 2.409323 2.600531
-1.189338 1.302425 1.961961 2.063211 2.432115 2.545303
-1.253885 1.371226 1.931879 2.030140 2.387565 2.558949
-1.307301 1.398036 1.910989 2.006938 2.409438 2.577142
-1.330085 1.468465 1.908521 2.012222 2.418015 2.537683
-1.367992 1.492291 1.942021 2.036750 2.498866 2.581003
-1.368367 1.443433 1.947482 2.013180 2.486344 2.585241
-1.418284 1.496850 1.933442 2.024630 2.473682 2.594036
-1.443886 1.551220 1.904909 2.018103 2.456717 2.542868
-1.473689 1.587097 1.899829 2.079006 2.421501 2.584477
-1.424674 1.611334 1.974517 2.142720 2.402882 2.620760
-1.431487 1.622660 1.940232 2.125436 2.429652 2.581851
-1.484538 1.690581 1.921860 2.109101 2.474401 2.607828
-1.498136 1.751579 1.925730 2.039135 2.440519 2.616180
-1.505248 1.789182 1.994666 2.114126 2.408417 2.599889
-1.609869 1.793035 1.986226 2.160600 2.519572 2.593245
-1.562825 1.739913 1.974184 2.143221 2.539588 2.620088
-1.650259 1.723964 2.002949 2.150399 2.532100 2.600746
-1.584628 1.665482 1.833853 1.979658 2.511168 2.576182
-1.547562 1.665631 1.805111 1.930451 2.428670 2.548606
-1.499078 1.595123 1.700269 1.824190 2.376924 2.575480
-1.300837 1.552954 1.664576 1.791707 2.488304 2.561078
-1.168605 1.311953 1.668583 1.872905 2.413570 2.493285
-1.047458 1.249963 1.699886 1.914183 2.417032 2.496381
-0.948776 1.275594 1.738944 1.998684 2.312154 2.462020
-0.921081 1.311946 1.775244 1.895491 2.382160 2.528440
-0.811311 1.125217 1.745194 2.094737 2.326109 2.511883
-0.796518 1.060230 1.740129 2.060503 2.179506 2.385501
-0.868836 1.153353 1.792833 1.945638 2.125498 2.248001
-0.915536 1.218160 1.818910 2.068347 2.243402 2.348648
-0.966595 1.301606 1.895255 2.111957 2.248646 2.389247
-0.995849 1.442084 1.952071 2.066120 2.240125 2.338587
-1.056392 1.372214 1.984171 2.119327 2.271702 2.372743
-1.098400 1.324164 1.781533 2.082856 2.218804 2.344318
-1.039157 1.356474 1.820178 2.114625 2.346728 2.450389
-0.988689 1.293884 1.916348 2.088201 2.362497 2.481270
-1.104406 1.230679 1.939434 2.122401 2.254811 2.377705
-1.086105 1.174481 1.826346 2.111318 2.237689 2.471667
-1.069802 1.206486 1.845381 2.118634 2.471087 2.575405
-1.074963 1.342794 1.955309 2.147713 2.511467 2.589270
-1.149198 1.418813 1.887043 1.966968 2.472616 2.587246
-1.455749 1.669829 1.964104 2.175182 2.469990 2.605009
-1.418548 1.603566 1.964426 2.175678 2.466765 2.583333
-1.389392 1.601163 1.925746 2.131857 2.442025 2.574229
-1.415333 1.507338 1.911262 2.087139 2.535199 2.629580
-1.382483 1.453710 1.872292 1.955406 2.554343 2.658507
-1.392944 1.482296 1.838526 1.928577 2.473732 2.633718
-1.390456 1.463044 1.839906 1.922012 2.514942 2.698788
-1.339376 1.470118 1.858751 1.959522 2.539427 2.686382
-1.353776 1.541029 1.822546 2.022164 2.542215 2.677200
-1.350868 1.631877 1.918792 2.183528 2.501087 2.617310
-1.407644 1.669128 2.000740 2.224226 2.522804 2.634897
-1.433780 1.586913 1.999627 2.192922 2.535981 2.626121
-1.413876 1.639426 1.952196 2.170695 2.501106 2.610591
-1.505388 1.613685 1.991590 2.214459 2.487873 2.612841
-1.409245 1.563694 2.048043 2.154145 2.483727 2.642180
-1.411023 1.646699 1.983177 2.152550 2.568807 2.661248
-1.384745 1.603808 1.934487 2.141949 2.507642 2.630050
-1.366120 1.551337 1.999561 2.177467 2.489112 2.596761
-1.355542 1.635015 2.008420 2.162675 2.465273 2.661406
-1.453972 1.673697 2.037857 2.180201 2.615971 2.709278
-1.369538 1.696466 1.999789 2.084847 2.482775 2.666286
-1.349740 1.462313 1.966717 2.051722 2.472616 2.652615
-1.327312 1.437762 1.928517 2.006392 2.505810 2.658921
-1.341350 1.419153 1.921202 1.991463 2.530825 2.613585
-1.342697 1.505329 1.946926 2.029431 2.538224 2.635583
-1.392743 1.535099 1.936104 2.024567 2.527279 2.614258
-1.432564 1.543790 1.951854 2.049855 2.546244 2.623711
-1.452940 1.569432 1.932369 2.037247 2.558693 2.638096
-1.467999 1.597453 1.920306 2.018574 2.536219 2.622824
-1.486806 1.569654 1.875855 1.966065 2.536740 2.631905
-1.454618 1.578126 1.811620 1.974659 2.537513 2.606334
-1.418040 1.507665 1.783572 1.893001 2.551797 2.628991
-1.264140 1.474380 1.770586 1.898927 2.524762 2.594073
-1.118340 1.456671 1.734720 1.996589 2.412285 2.519146
-1.096432 1.603123 1.808391 2.012238 2.409620 2.544361
-0.976303 1.473740 1.759171 1.855828 2.412929 2.483947
-0.990184 1.390703 1.710711 1.831672 2.377092 2.454935
-1.056900 1.387366 1.783109 1.873514 2.401419 2.486425
-0.989786 1.452622 1.851566 1.945924 2.403454 2.482939
-1.112084 1.364820 1.770002 1.921998 2.290405 2.437297
-1.096250 1.336388 1.741855 1.968572 2.211613 2.362493
-1.000030 1.346185 1.704531 1.966852 2.277389 2.389374
-1.027901 1.174070 1.793005 2.026854 2.178200 2.387232
-1.056882 1.167504 1.861000 2.204421 2.351246 2.485631
-1.075972 1.226420 1.997644 2.196176 2.330099 2.494137
-1.147221 1.258128 1.958667 2.258550 2.387749 2.552119
-1.162811 1.290567 2.052795 2.201829 2.424621 2.560484
-1.147890 1.265733 2.025675 2.130794 2.496878 2.620259
-1.239563 1.315734 2.018377 2.123513 2.463946 2.569207
-1.181131 1.358942 1.942155 2.159833 2.458701 2.593961
-1.247455 1.386435 1.898250 1.999009 2.446020 2.542764
-1.227695 1.504889 1.817998 1.908019 2.213334 2.552228
-1.201972 1.577872 1.771276 1.873354 2.061263 2.535817
-1.306230 1.516310 1.819234 1.923423 2.382025 2.582568
-1.505719 1.585654 1.949330 2.046203 2.448307 2.615962
-1.623749 1.698728 2.009543 2.108007 2.461522 2.647903
-1.690861 1.764294 2.036097 2.175502 2.515253 2.616822
-1.715336 1.828294 2.078551 2.252209 2.483666 2.607649
-1.659970 1.807170 1.975009 2.255594 2.481341 2.589617
-1.734824 1.850216 2.012044 2.276744 2.519359 2.608181
-1.635768 1.862548 1.956456 2.328743 2.568869 2.632471
-1.616355 1.825398 1.949523 2.281216 2.560861 2.641804
-1.592472 1.804360 1.927158 2.167339 2.577510 2.646873
-1.606484 1.895095 1.983153 2.112452 2.477608 2.576959
-1.708493 1.835068 1.966711 2.127238 2.427571 2.543077
-1.691093 1.889580 1.986069 2.206774 2.522399 2.601798
-1.702442 1.902120 2.076380 2.216219 2.484843 2.603543
-1.329491 1.542588 1.875436 2.105532 2.385234 2.536630
-1.321384 1.474161 1.932268 2.152505 2.374420 2.506710
-1.277750 1.458580 1.963094 2.182377 2.417003 2.558654
-1.208016 1.418710 2.009739 2.138531 2.396782 2.554506
-1.198910 1.299925 1.983625 2.150128 2.296124 2.505944
-1.250344 1.361156 2.010558 2.195944 2.340984 2.500873
-1.308664 1.585162 2.106341 2.214164 2.402673 2.635894
-1.330165 1.494630 2.141901 2.235810 2.459582 2.649465
-1.296306 1.434105 2.098086 2.204131 2.355208 2.600113
-1.309619 1.402978 1.892542 2.184955 2.333605 2.513160
-1.269067 1.491839 1.958963 2.174572 2.324689 2.543667
-1.434975 1.628849 1.981273 2.247282 2.476397 2.593980
-1.459644 1.650080 2.024368 2.267723 2.546314 2.675203
-1.381486 1.703195 2.138905 2.295559 2.545762 2.642527
-1.441842 1.700585 2.197906 2.276293 2.468211 2.694954
-1.539669 1.999668 2.206532 2.351484 2.651231 2.734825
-1.589576 1.926407 2.173457 2.256196 2.633242 2.707677
-1.434262 1.859373 2.141950 2.211447 2.511783 2.628376
-1.326814 1.596573 2.024769 2.115813 2.426136 2.609340
-1.229072 1.325550 1.838698 2.013045 2.471300 2.639281
-1.230813 1.329059 1.872619 1.964510 2.444752 2.594694
-1.193705 1.426297 1.898594 2.039364 2.502714 2.581046
-1.175637 1.473287 1.912423 2.002740 2.476222 2.606851
-1.099269 1.443896 1.892457 1.997567 2.522081 2.611086
-1.113739 1.439098 1.912268 2.000476 2.462769 2.559343
-1.085510 1.469634 1.914465 2.064613 2.427917 2.512412
-1.052481 1.501205 1.918797 1.999794 2.493684 2.571708
-1.043597 1.331616 1.927947 1.989186 2.445730 2.578082
-1.051981 1.200390 1.938627 2.026811 2.446750 2.629884
-0.978672 1.083042 1.868777 2.133583 2.430141 2.580267
-0.904772 1.105214 1.960566 2.064948 2.362564 2.604875
-0.859439 1.084629 1.901705 2.033000 2.276166 2.574716
-0.948943 1.043554 1.855644 2.050857 2.444431 2.661478
-0.974338 1.126459 1.927321 2.020910 2.455487 2.559782
-0.995629 1.175887 1.937743 2.013680 2.378974 2.617290
-1.001312 1.224390 1.901702 1.976467 2.425878 2.574844
-0.985969 1.282601 1.886614 2.032451 2.455957 2.599528
-0.927590 1.320448 1.924006 2.012174 2.498308 2.599681
-1.007942 1.383963 1.921628 2.007624 2.507570 2.607500
-0.972512 1.446775 1.920365 2.013492 2.490207 2.576492
-0.951123 1.452036 1.889861 1.987269 2.421483 2.562217
-0.924342 1.369953 1.851744 1.942740 2.475661 2.544282
-0.882605 1.301666 1.850813 2.032498 2.364632 2.541824
-0.933888 1.368996 1.943109 2.023849 2.405442 2.530330
-0.927916 1.112379 1.847430 1.979093 2.255596 2.563992
-1.031936 1.249132 1.833165 1.925221 2.310315 2.520141
-0.934046 1.239886 1.909603 2.008149 2.372869 2.548965
-0.984297 1.220031 1.823788 1.947602 2.264359 2.478653
-0.933366 1.278980 1.860469 1.942999 2.289801 2.465670
-0.983115 1.227707 1.842104 2.047699 2.272651 2.531979
-0.953311 1.245822 1.849685 1.945142 2.289569 2.572282
-0.994609 1.303464 1.868144 1.971560 2.372435 2.585257
-0.986061 1.364094 1.852132 1.917821 2.435113 2.633873
-0.975486 1.248848 1.848797 1.934434 2.402023 2.574203
-1.008388 1.304679 1.804310 1.888508 2.369473 2.598230
-0.999393 1.329937 1.901438 1.994378 2.397503 2.504548
-0.922186 1.321538 1.851082 1.962056 2.382159 2.472985
-0.897224 1.382187 1.780842 1.921734 2.359590 2.448091
-0.859516 1.447371 1.732311 1.881193 2.295231 2.380849
-0.986347 1.601641 1.752386 1.966362 2.314384 2.459101
-1.265264 1.616535 1.811273 2.097139 2.371242 2.550361
-1.318958 1.600426 1.755641 2.029814 2.329188 2.493144
-1.209901 1.470135 1.670187 1.970732 2.416208 2.523420
-1.122232 1.308395 1.457114 1.720231 2.384259 2.470421
-1.077675 1.245511 1.366478 1.664281 2.327344 2.419196
-1.075445 1.228131 1.365376 1.558947 2.238585 2.324563
-1.044502 1.215785 1.325993 1.645187 2.148642 2.225749
-0.955863 1.150609 1.283133 1.492306 2.177576 2.266677
-0.909204 1.045108 1.166160 1.320593 2.215965 2.352846
-0.960368 1.103540 1.278352 1.467726 2.260152 2.460237
-1.010220 1.186777 1.290055 1.578425 2.388733 2.500317
-1.020144 1.135718 1.239343 1.388838 2.438182 2.563922
-1.082493 1.206954 1.347455 1.490039 2.404819 2.494617
-1.144114 1.278638 1.434725 1.567887 2.322768 2.424800
-1.274296 1.348789 1.515602 1.632221 2.360105 2.552789
-1.301328 1.390629 1.638492 1.764907 2.347961 2.576115
-1.358515 1.444452 1.724492 1.843715 2.478143 2.574552
-1.399712 1.513306 1.791713 1.902169 2.495815 2.581592
-1.448866 1.534750 1.821506 1.931492 2.517823 2.622859
-1.438398 1.530057 1.831437 1.999329 2.531929 2.623280
-1.511918 1.581087 1.927484 2.041399 2.573287 2.663469
-1.535380 1.608310 1.924231 2.048796 2.546746 2.681650
-1.544368 1.620413 1.980425 2.068130 2.477398 2.626652
-1.558461 1.643007 2.024613 2.121014 2.451868 2.639494
-1.524202 1.613947 2.005898 2.115477 2.429090 2.663085
-1.504519 1.590381 1.966356 2.072628 2.376901 2.621094
-1.439395 1.512336 1.950354 2.058564 2.276407 2.573036
-1.315215 1.400050 1.854752 1.957633 2.246197 2.576501
-1.288117 1.488904 1.945571 2.024839 2.439848 2.605685
-1.436278 1.667254 2.056847 2.146443 2.548238 2.661743
-1.417389 1.819841 2.083572 2.220278 2.606693 2.690863
-1.373599 1.963014 2.144565 2.274057 2.547389 2.638900
-1.320367 1.918635 2.063208 2.237723 2.415847 2.517654
-1.223778 1.619753 1.890594 2.107915 2.520999 2.629701
-1.018748 1.427668 1.917566 2.001782 2.435507 2.564351
-1.026252 1.377048 1.949170 2.039209 2.393769 2.530053
-1.009988 1.472847 1.998049 2.079876 2.484961 2.553950
-1.053267 1.468372 2.016120 2.129309 2.456623 2.564128
-1.101072 1.355268 2.010441 2.107467 2.395605 2.537748
-1.132796 1.391658 2.016574 2.114099 2.497623 2.585099
-1.173305 1.443009 1.970633 2.104863 2.447883 2.535937
-1.209478 1.384097 1.972240 2.069587 2.457494 2.573686
-1.242419 1.453561 1.983731 2.068419 2.471041 2.593609
-1.320388 1.463651 1.997825 2.082334 2.472034 2.605892
-1.389516 1.477732 1.978692 2.094038 2.480170 2.644445
-1.413743 1.526085 1.963751 2.113919 2.403846 2.654427
-1.519419 1.592852 1.919458 2.024494 2.301172 2.668892
-1.513663 1.600129 1.922007 2.105104 2.278322 2.523416
-1.481852 1.659944 1.913552 2.049439 2.272255 2.493787
-1.567545 1.659167 1.930647 2.071517 2.312595 2.564270
-1.550890 1.677657 1.863928 2.010128 2.223475 2.520007
-1.572772 1.683020 1.863047 2.002198 2.320378 2.560791
-1.621943 1.734050 1.920642 2.062932 2.335107 2.576252
-1.631487 1.697136 1.952883 2.056578 2.459627 2.652858
-1.594706 1.671490 1.936091 2.013301 2.430776 2.669632
-1.601444 1.668704 1.945495 2.037168 2.503369 2.682121
-1.587570 1.664898 1.944621 2.032989 2.569757 2.703408
-1.556417 1.631245 1.930707 2.040513 2.453873 2.665177
-1.487851 1.565634 1.892869 2.011729 2.393945 2.647118
-1.406012 1.520184 1.791646 1.987880 2.289334 2.602762
-1.358221 1.436040 1.818480 1.957084 2.309801 2.605784
-1.309339 1.405329 1.835697 2.076369 2.340807 2.613062
-1.303792 1.415614 1.985149 2.129488 2.469355 2.643119
-1.358952 1.437733 1.988826 2.127374 2.537981 2.656471
-1.333866 1.480460 1.950069 2.122437 2.431168 2.587133
-1.384528 1.539708 1.964093 2.130549 2.510449 2.652805
-1.412625 1.544436 1.947280 2.173185 2.593018 2.716637
-1.433269 1.539892 2.004125 2.201951 2.515051 2.635244
-1.447580 1.554019 2.128269 2.240167 2.470753 2.657077
-1.480647 1.609898 2.097964 2.167566 2.473701 2.700702
-1.607823 1.675959 2.023409 2.146384 2.426913 2.636247
-1.643303 1.717783 2.060655 2.197557 2.415413 2.614329
-1.737392 1.816967 2.039362 2.219707 2.422999 2.623531
-1.694258 1.799366 2.042600 2.280098 2.418626 2.583273
-1.556188 1.831866 1.985355 2.207899 2.471677 2.630819
-1.421150 1.803896 1.984581 2.123513 2.438200 2.522496
-1.327444 1.668870 1.888433 2.029945 2.224455 2.461746
-1.109824 1.562199 1.862663 1.977860 2.139552 2.328644
-1.233875 1.580797 1.854187 2.021788 2.193504 2.355917
-1.207537 1.568638 1.872908 1.986671 2.137938 2.487653
-1.179978 1.625946 1.900003 2.008135 2.231660 2.594349
-1.469842 1.717204 1.875670 2.024433 2.325463 2.488422
-1.641097 1.809779 1.926763 2.062053 2.414037 2.542900
-1.648803 1.734123 1.966905 2.086726 2.354475 2.498840
-1.605468 1.689394 2.010048 2.114211 2.407628 2.527066
-1.520887 1.628733 1.977005 2.086771 2.340162 2.489336
-1.503816 1.600587 2.039010 2.130377 2.396482 2.513742
-1.437817 1.545316 2.043931 2.188366 2.356821 2.521449
-1.445398 1.549208 1.982213 2.096659 2.328629 2.462126
-1.416417 1.504357 1.973772 2.080427 2.393479 2.543532
-1.425822 1.528083 1.995729 2.162530 2.440693 2.562510
-1.394274 1.473952 2.043537 2.149086 2.432979 2.549080
-1.373755 1.476048 2.043903 2.160251 2.345351 2.501882
-1.370183 1.443588 2.092872 2.178103 2.413056 2.590595
-1.320393 1.466374 2.036782 2.137812 2.435621 2.578912
-1.286926 1.393325 2.060733 2.200945 2.500015 2.582353
-1.323391 1.421794 2.058500 2.153930 2.495548 2.638088
-1.295313 1.393216 2.004420 2.138189 2.526374 2.641535
-1.230979 1.355132 2.047369 2.156418 2.522379 2.664129
-1.233755 1.308524 1.939495 2.097348 2.487349 2.649836
-1.227589 1.355101 1.875835 1.977538 2.319288 2.575191
-1.227369 1.507108 1.853515 2.022894 2.212431 2.576493
-1.152896 1.470513 1.830430 1.954309 2.331452 2.533253
-1.336656 1.650185 1.779214 2.043424 2.444821 2.539640
-1.455824 1.582937 2.022254 2.176680 2.481340 2.592664
-1.437625 1.556245 2.081454 2.174959 2.482445 2.614573
-1.416470 1.620886 2.033007 2.157073 2.462925 2.601588
-1.376304 1.551493 2.117213 2.198338 2.416190 2.605635
-1.442804 1.657855 2.127088 2.206301 2.344857 2.578113
-1.368110 1.538734 2.060199 2.198045 2.366884 2.622242
-1.346445 1.428338 1.980453 2.126605 2.283275 2.530611
-1.304592 1.373259 1.923523 2.096362 2.239964 2.508433
-1.298027 1.371594 1.954971 2.107512 2.349707 2.545570
-1.307177 1.416169 1.980337 2.064455 2.389102 2.588444
-1.279296 1.390782 1.959784 2.090687 2.436145 2.612606
-1.317020 1.415866 1.921874 2.071794 2.463821 2.616221
-1.294309 1.412297 1.916195 2.019201 2.484708 2.611341
-1.310051 1.407774 1.853169 2.009907 2.466493 2.645013
-1.341298 1.422330 1.885156 1.967813 2.483863 2.626324
-1.428263 1.526125 1.885115 1.978529 2.499386 2.603389
-1.501165 1.580511 1.847282 2.000494 2.465952 2.608868
-1.538510 1.625396 1.813916 1.950057 2.522899 2.620472
-1.566628 1.639602 1.771792 1.878749 2.541764 2.663693
-1.543435 1.647821 1.748616 1.822597 2.434677 2.631280
-1.623389 1.680917 1.759152 1.844539 2.521467 2.653611
-1.574857 1.663719 1.767780 1.869740 2.453335 2.658218
-1.558309 1.661251 1.793844 1.895130 2.261873 2.572330
-1.543680 1.627756 1.817671 1.921282 2.432997 2.653342
-1.493536 1.575657 1.805687 1.939448 2.470642 2.665081
-1.440050 1.513838 1.832212 1.937802 2.530248 2.702867
-1.319101 1.506232 1.823485 1.931612 2.539554 2.676703
-1.307271 1.563371 1.847930 1.951724 2.251818 2.453220
-1.336405 1.661596 1.828825 1.988331 2.189506 2.354248
-1.342922 1.598751 1.784739 1.915122 2.109991 2.450644
-1.336704 1.646363 1.800742 1.891215 2.235913 2.558506
-1.311763 1.500014 1.830220 1.945042 2.430387 2.644578
-1.266113 1.431962 1.858757 2.059148 2.590485 2.674762
-1.317779 1.419948 1.916462 2.124820 2.574729 2.668476
-1.341519 1.436167 1.968421 2.097444 2.572787 2.685098
-1.305930 1.438859 1.933746 2.036080 2.569070 2.656417
-1.279130 1.406473 1.943094 2.031719 2.530080 2.630882
-1.286005 1.410029 1.969688 2.040243 2.448573 2.651374
-1.257538 1.391063 1.966565 2.039208 2.402422 2.646794
-1.224386 1.352129 1.931370 2.006343 2.456203 2.696151
-1.296292 1.488099 1.996948 2.068189 2.594535 2.695842
-1.334566 1.607716 1.922141 2.163161 2.545921 2.679970
-1.381781 1.646772 2.037640 2.204087 2.545791 2.639326
-1.416818 1.628929 2.045931 2.209348 2.523853 2.675794
-1.431463 1.694802 1.998932 2.159531 2.522928 2.664749
-1.384236 1.622936 2.036943 2.115706 2.528893 2.633929
-1.403832 1.558362 2.027347 2.138015 2.562774 2.659379
-1.390591 1.671936 2.017942 2.164595 2.592820 2.683609
-1.357527 1.553759 2.023137 2.212306 2.420463 2.558257
-1.301715 1.465816 2.052932 2.215957 2.420685 2.548524
-1.339331 1.597053 2.035156 2.145819 2.509602 2.644137
-1.346088 1.633870 2.006920 2.114724 2.570026 2.688879
-1.358438 1.501669 1.949578 2.027633 2.479635 2.637460
-1.427991 1.533690 1.853629 1.960806 2.437544 2.588461
-1.507003 1.585812 1.864642 1.950265 2.478769 2.624546
-1.535154 1.619477 1.784602 1.926332 2.537152 2.665799
-1.499658 1.574823 1.685832 1.822553 2.533986 2.705306
-1.585485 1.642424 1.721846 1.846735 2.524494 2.710346
-1.167359 1.627213 1.768394 1.853039 2.265556 2.540517
-1.110320 1.506953 1.805632 1.881807 2.361271 2.589961
-1.066434 1.539420 1.746305 1.936119 2.127988 2.461181
-1.110995 1.565351 1.852078 1.960462 2.214924 2.497897
-1.116118 1.590687 1.879184 1.969081 2.323294 2.532966
-1.148401 1.557455 1.819964 1.963793 2.380344 2.484532
-1.092558 1.569815 1.784004 1.959241 2.324259 2.468490
-1.212996 1.578928 1.751637 1.901569 2.271773 2.386093
-1.123979 1.626268 1.758062 1.983762 2.291127 2.408000
-1.075785 1.534831 1.784777 2.041940 2.236695 2.368112
-1.118783 1.415693 1.971932 2.122755 2.330245 2.440458
-1.016087 1.334517 1.899204 2.121574 2.425143 2.543872
-1.066196 1.289419 1.948157 2.081946 2.471493 2.593822
-1.064989 1.255756 1.935973 2.036951 2.493176 2.612753
-1.049670 1.228450 1.829530 2.025060 2.431071 2.670840
-1.019627 1.313583 1.880313 1.953952 2.491693 2.642660
-1.153477 1.551900 1.909752 2.133530 2.540066 2.626465
-1.293030 1.600480 2.035687 2.166885 2.572967 2.658261
-1.409308 1.624144 1.993621 2.268493 2.527057 2.651858
-1.426397 1.681509 2.039405 2.215283 2.559060 2.681401
-1.422045 1.752644 2.027991 2.231432 2.546485 2.631238
-1.403067 1.735547 2.007077 2.202109 2.635543 2.718353
-1.364124 1.687363 2.011927 2.293629 2.640697 2.705256
-1.328058 1.608269 1.989851 2.364958 2.590564 2.689451
-1.333592 1.644867 2.130503 2.308577 2.644140 2.732807
-1.405236 1.665965 2.123365 2.315861 2.656941 2.732874
-1.435372 1.679544 2.019100 2.254404 2.596082 2.674056
-1.041025 1.476515 1.923322 2.290557 2.592337 2.673623
-0.818396 1.189747 2.051367 2.233382 2.417100 2.622567
-0.745703 1.240251 2.139256 2.224179 2.476418 2.558791
-0.786217 1.296744 2.004359 2.245816 2.548718 2.631400
-0.781573 1.122340 1.875748 2.277284 2.459421 2.557207
-0.697586 1.327149 2.097985 2.173556 2.574671 2.693605
-0.773107 1.393007 1.971171 2.270220 2.591495 2.651543
-0.799951 1.252666 1.928383 2.211233 2.577718 2.683817
-0.737528 1.237907 1.827160 2.110526 2.476303 2.627671
-0.896067 1.421355 1.841161 2.104821 2.432869 2.585719
-0.920446 1.418578 1.943416 2.252701 2.491235 2.623110
-0.905094 1.284731 1.843688 2.269109 2.479541 2.595905
-1.049549 1.447497 1.841173 2.160358 2.575747 2.655700
-1.282800 1.445416 1.901230 2.290173 2.581640 2.678726
-1.174710 1.517021 1.867926 2.176617 2.547483 2.640154
-1.241259 1.518496 1.936773 2.208770 2.521322 2.619833
-1.321929 1.540199 1.998528 2.205769 2.605663 2.707912
-1.303802 1.622926 1.880392 2.189485 2.588909 2.669966
-1.360827 1.658553 1.903323 2.178010 2.554280 2.634772
-1.385461 1.623312 1.959095 2.257739 2.605390 2.694616
-1.467954 1.628168 2.003097 2.348920 2.596096 2.674558
-1.411837 1.691393 1.947010 2.259218 2.526145 2.615112
-1.415256 1.697464 2.003104 2.284290 2.526236 2.643365
-1.365343 1.610187 2.022103 2.171703 2.557595 2.642236
-1.343948 1.630769 2.040836 2.261714 2.477921 2.647359
-1.333580 1.630378 2.031205 2.210871 2.504057 2.623327
-1.344121 1.704685 2.065813 2.192571 2.541365 2.658520
-1.439884 1.666588 2.082726 2.206006 2.636341 2.699174
-1.344355 1.655936 2.026852 2.227832 2.565868 2.661265
-1.299677 1.585295 1.961552 2.231139 2.599559 2.677599
-1.184434 1.441654 1.888542 2.255409 2.554664 2.625508
-1.446570 1.792548 2.022664 2.179214 2.497160 2.591115
-1.464682 1.809276 2.060194 2.205446 2.545963 2.641910
-1.481290 1.729523 2.025686 2.250012 2.537459 2.667746
-1.476458 1.657788 2.008062 2.249201 2.503220 2.613116
-1.386264 1.589548 2.031702 2.218301 2.509210 2.619100
-1.386263 1.662864 2.052585 2.208677 2.488387 2.623049
-1.438117 1.646070 1.967818 2.212439 2.508718 2.629395
-1.437599 1.590230 2.089082 2.184453 2.566546 2.677847
-1.367022 1.652527 2.084373 2.169492 2.483600 2.655744
-1.403779 1.701337 2.062797 2.148537 2.443186 2.657250
-1.399193 1.706047 2.062427 2.144585 2.531224 2.635014
-1.409664 1.750569 2.005073 2.087238 2.602834 2.694068
-1.430153 1.760399 2.048802 2.118059 2.569383 2.657275
-1.418847 1.858926 2.018666 2.141412 2.597867 2.671139
-1.515040 1.815611 1.942165 2.089059 2.554645 2.634597
-1.420031 1.740119 1.953746 2.196133 2.502692 2.639749
-1.384099 1.723309 1.901165 2.160196 2.426618 2.522583
-1.341050 1.737372 1.894752 2.110869 2.407505 2.502838
-1.375756 1.553983 1.784274 1.981423 2.504116 2.571526
-1.414589 1.520552 1.715365 2.013015 2.511199 2.608636
-1.384971 1.519108 1.696689 1.939377 2.575701 2.644752
-1.377861 1.611683 1.751236 2.044564 2.493605 2.567974
-1.360853 1.553679 1.693976 2.036113 2.535885 2.588469
-1.391629 1.489335 1.631480 1.853083 2.529546 2.631825
-1.364077 1.476053 1.629040 1.949019 2.525741 2.587922
-1.243896 1.398594 1.539687 2.066323 2.528653 2.592221
-1.255509 1.429357 1.548843 1.950985 2.519984 2.574845
-1.213331 1.388798 1.505976 1.886640 2.486118 2.545361
-1.125797 1.286903 1.534946 1.982051 2.490209 2.570684
-1.132522 1.296198 1.460831 1.925246 2.355670 2.444037
-1.146734 1.365341 1.496067 2.020613 2.448334 2.510650
-1.192778 1.378937 1.491161 1.959258 2.459140 2.519716
-1.271605 1.383883 1.525856 1.953206 2.473140 2.526275
-1.199948 1.366094 1.519729 1.926772 2.562989 2.623739
-1.236017 1.383510 1.510394 1.793300 2.585490 2.677079
-1.277218 1.416561 1.539447 1.923790 2.599080 2.667723
-1.195957 1.408063 1.568713 2.090793 2.622180 2.668897
-1.174436 1.300805 1.706567 2.070327 2.332828 2.490999
-1.120253 1.252790 1.562102 2.057117 2.357857 2.488099
-1.176325 1.291966 1.760265 2.093355 2.395545 2.591528
-1.197722 1.415532 1.801926 2.033180 2.459620 2.592560
-1.170462 1.491249 1.888044 2.082479 2.392285 2.528149
-1.083509 1.491779 1.949458 2.046197 2.422471 2.591609
-1.059936 1.417978 1.954816 2.073246 2.480964 2.599125
-0.939633 1.348507 2.005684 2.094229 2.474051 2.580294
-0.849679 1.293534 1.998123 2.105266 2.410101 2.615907
-0.886534 1.432349 1.990451 2.089797 2.379083 2.539500
-0.973462 1.473622 1.944390 2.051837 2.393100 2.468610
-1.041989 1.576432 1.952733 2.062536 2.326319 2.437768
-1.048696 1.543946 1.799024 2.015259 2.415911 2.487382
-1.060745 1.463281 1.792003 1.940494 2.417438 2.517618
-1.086879 1.350511 1.715443 1.804481 2.481994 2.577240
-1.237763 1.487227 1.724896 1.808323 2.528530 2.614554
-1.398461 1.499585 1.705939 1.817865 2.537422 2.611149
-1.461839 1.549278 1.719489 1.835184 2.480052 2.656622
-1.411934 1.594838 1.722617 1.840214 2.536598 2.618705
-1.527085 1.609472 1.704839 1.832817 2.512769 2.605081
-1.549304 1.649714 1.747183 1.838847 2.593282 2.681523
-1.408650 1.622130 1.797760 1.950766 2.238972 2.463941
-1.463558 1.647961 1.790731 1.921407 2.348044 2.572625
-1.531892 1.700373 1.834041 2.005597 2.413477 2.570542
-1.595204 1.681563 1.857023 2.020177 2.475381 2.620261
-1.578383 1.651863 1.912263 2.011994 2.512496 2.625607
-1.551105 1.644360 1.936207 2.041608 2.527321 2.617243
-1.531973 1.623150 1.927602 2.007454 2.528038 2.634563
-1.492463 1.579493 1.908682 1.998228 2.490609 2.583094
-1.445430 1.548758 1.913697 2.002797 2.519245 2.610948
-1.397285 1.482251 1.891220 1.983837 2.474487 2.607776
-1.358299 1.562942 1.902050 2.003614 2.425639 2.585407
-1.313352 1.518886 1.923066 2.011942 2.496939 2.583703
-1.321679 1.506830 1.903064 1.990064 2.510610 2.619736
-1.272893 1.513437 1.897901 2.039656 2.536517 2.604144
-1.255738 1.431150 1.896619 1.960886 2.526746 2.624236
-1.253559 1.392826 1.893788 1.975079 2.520685 2.596673
-1.212336 1.375220 1.860311 1.964962 2.531189 2.598668
-1.177442 1.324186 1.806632 1.885288 2.487316 2.595463
-1.184996 1.383080 1.783224 1.863469 2.466568 2.570648
-1.162268 1.444731 1.797884 1.960244 2.515838 2.594432
-1.293132 1.612625 1.912866 2.113069 2.467202 2.592647
-1.354402 1.698025 1.960114 2.149465 2.532985 2.652695
-1.412069 1.729124 2.034085 2.172945 2.538810 2.643693
-1.391792 1.801757 1.944790 2.194546 2.467300 2.547714
-1.476077 1.743192 1.982548 2.141155 2.559049 2.642891
-1.423680 1.857196 1.998407 2.146989 2.499501 2.583857
-1.420678 1.878169 2.012321 2.298282 2.578266 2.665489
-1.455663 1.910540 2.069836 2.393055 2.593493 2.679808
-1.525575 1.925713 2.186470 2.400715 2.660126 2.743114
-1.376147 1.633438 1.934297 2.250493 2.494057 2.618970
-1.354498 1.560950 1.931259 2.207320 2.500701 2.611053
-1.308071 1.569512 1.967243 2.245460 2.461123 2.595512
-1.347009 1.654983 1.980907 2.251887 2.510089 2.634977
-1.478008 1.588438 2.038202 2.224140 2.499366 2.646631
-1.451530 1.630286 2.114101 2.249734 2.416504 2.651801
-1.412137 1.655832 2.128349 2.224639 2.525056 2.681740
-1.374504 1.848893 2.140832 2.291897 2.602827 2.691005
-1.378568 1.744853 2.106673 2.201221 2.626831 2.711996
-1.082739 1.603117 2.070774 2.129571 2.504286 2.657551
-1.013288 1.467910 1.960032 2.091788 2.362049 2.561554
-0.994100 1.328068 1.791699 1.902549 2.410628 2.501324
-0.999159 1.325245 1.722310 1.871377 2.281177 2.502088
-1.035282 1.338082 1.653023 1.759760 2.441464 2.540672
-1.077126 1.293589 1.565666 1.711796 2.330341 2.436256
-1.058117 1.243026 1.488328 1.623677 2.330121 2.429536
-1.150659 1.296201 1.574724 1.701839 2.390475 2.507354
-1.167918 1.382035 1.573815 1.795297 2.440653 2.490361
-1.221368 1.405075 1.535783 1.728642 2.412290 2.519375
-1.248273 1.383975 1.572280 1.826858 2.425352 2.494218
-1.274149 1.386267 1.557821 1.734106 2.378306 2.477968
-1.343890 1.456032 1.668535 1.815600 2.248744 2.419705
-1.356022 1.559300 1.731279 1.853333 2.343968 2.514760
-1.433214 1.575906 1.673186 1.781463 2.292800 2.491264
-1.354708 1.637604 1.875368 2.162870 2.408490 2.566375
-1.464664 1.591442 2.071219 2.235462 2.398887 2.563489
-1.424812 1.622646 2.020332 2.161315 2.328264 2.468190
-1.364274 1.516152 2.011760 2.109608 2.395705 2.554722
-1.342677 1.460516 2.038898 2.122976 2.506655 2.643449
-1.338308 1.519884 2.030044 2.100145 2.533338 2.674767
-1.321127 1.545574 1.977232 2.122268 2.557592 2.680218
-1.315091 1.467109 1.972429 2.068538 2.526845 2.645634
-1.304457 1.400689 1.954545 2.053140 2.562504 2.685886
-1.267182 1.376660 1.888057 2.029893 2.545417 2.669311
-1.225012 1.339338 1.887320 1.965236 2.543506 2.672285
-1.226210 1.403527 1.797664 1.959693 2.540988 2.627346
-1.347025 1.607942 1.966769 2.184515 2.477879 2.608821
-1.332099 1.755961 1.948416 2.176713 2.513390 2.601370
-1.349288 1.781404 1.922794 2.109230 2.462878 2.559863
-1.362379 1.693594 1.884339 2.088053 2.522473 2.613966
-1.320290 1.510299 1.857749 2.065435 2.494726 2.605564
-1.282991 1.459743 1.744910 1.961419 2.439941 2.623746
-1.251365 1.381919 1.673542 1.772697 2.323540 2.661592
-1.204256 1.435153 1.654230 1.737800 2.305057 2.581558
-1.181960 1.465280 1.670027 1.861303 2.444123 2.546129
-1.347122 1.628258 1.931339 2.123429 2.466851 2.598918
-1.170479 1.284934 1.552741 1.832546 2.299787 2.519811
-1.190040 1.284015 1.646086 1.969170 2.496917 2.620449
-1.255411 1.381474 1.781732 2.094994 2.431362 2.593520
-1.231880 1.334167 1.796249 2.040002 2.387081 2.554655
-1.180520 1.308571 1.818239 1.976323 2.293501 2.451796
-1.102564 1.266319 1.844247 1.961761 2.324841 2.514083
-1.004636 1.144874 1.835019 1.997102 2.182380 2.522076
-0.956994 1.212915 1.940923 2.060449 2.312226 2.441670
-0.795434 1.444280 1.932418 2.047161 2.365680 2.450523
-0.942462 1.606038 2.025121 2.119735 2.299947 2.431814
-0.812186 1.469389 2.078323 2.173021 2.391967 2.474051
-0.831008 1.620609 2.092943 2.167732 2.334863 2.416721
-0.917049 1.800997 2.121233 2.199383 2.347284 2.440519
-0.857286 1.679152 2.112428 2.203072 2.444738 2.529211
-0.809582 1.542552 2.182369 2.239437 2.461979 2.543366
-0.912283 1.779198 2.166321 2.251092 2.461682 2.576876
-0.774827 1.770199 2.179196 2.239611 2.487323 2.560225
-1.222989 1.574575 2.081078 2.223587 2.501523 2.661302
-1.394216 1.696320 2.036647 2.273328 2.570400 2.684130
-1.370771 1.698913 2.082660 2.245671 2.598794 2.695446
-1.372406 1.647175 2.142373 2.272905 2.608093 2.686558
-1.342788 1.694536 2.123284 2.256762 2.575277 2.690952
-1.380553 1.750680 2.123405 2.199744 2.488043 2.610243
-1.395056 1.883317 2.088702 2.189488 2.458258 2.548140
-1.413151 1.872836 2.020835 2.161956 2.396167 2.487013
-1.403097 1.764242 1.911249 2.055851 2.391006 2.484601
-1.250592 1.606846 1.834805 1.914414 2.344090 2.549461
-1.171007 1.406438 1.699124 1.858102 2.354073 2.471053
-1.132691 1.251867 1.521350 1.638290 2.355284 2.470608
-1.011681 1.287897 1.450262 1.663822 2.285463 2.371452
-1.030244 1.208417 1.366673 1.550352 2.337520 2.421401
-0.964915 1.171185 1.288162 1.588419 2.327292 2.388297
-0.953674 1.102888 1.263755 1.835591 2.316855 2.424820
-0.886544 1.074635 1.242245 1.964445 2.296815 2.412946
-0.853009 1.077083 1.184534 1.752324 2.283038 2.389217
-0.840278 1.033222 1.152546 1.520954 2.333984 2.454533
-0.910770 1.083873 1.223537 1.668076 2.346235 2.511845
-0.967915 1.121818 1.220258 1.806588 2.421129 2.498176
-0.992265 1.169069 1.260049 1.679990 2.398939 2.459143
-1.065276 1.230957 1.322385 1.753477 2.314399 2.415925
-1.081305 1.271782 1.458008 1.729400 2.332304 2.405121
-1.017815 1.349087 1.515836 1.721892 2.292963 2.398991
-1.097652 1.332937 1.570030 1.776462 2.377274 2.465894
-1.147644 1.302495 1.640156 1.797044 2.363880 2.474795
-1.127168 1.322009 1.684884 1.796463 2.407050 2.578659
-1.159532 1.266652 1.709552 1.830584 2.438156 2.572425
-1.137105 1.331512 1.749399 1.846000 2.414391 2.511488
-1.121271 1.351105 1.728223 1.846664 2.449211 2.564158
-1.118680 1.261543 1.794458 1.885767 2.429009 2.552772
-1.076991 1.212163 1.727637 1.861263 2.432992 2.564041
-1.082093 1.261697 1.760917 1.858031 2.315851 2.573591
-1.086353 1.279061 1.763123 1.864186 2.380786 2.485297
-0.988401 1.262393 1.737901 1.836710 2.375780 2.492390
-1.074712 1.196202 1.677279 1.806309 2.341401 2.560642
-1.067864 1.265290 1.689350 1.802993 2.401947 2.524062
-1.010475 1.289540 1.652721 1.778727 2.362305 2.466551
-0.977570 1.261308 1.576271 1.741327 2.297622 2.404091
-1.097180 1.464421 1.606664 1.717614 2.330709 2.412068
-1.383838 1.652270 1.898203 2.096608 2.476719 2.574183
-1.279735 1.700611 1.894987 2.029873 2.468395 2.584491
-1.236668 1.683312 1.791059 1.953368 2.533100 2.587084
-1.185052 1.599131 1.853897 1.944925 2.499951 2.572896
-1.163573 1.307316 1.872443 1.953987 2.544667 2.623228
-1.190969 1.449255 1.863288 1.937666 2.525272 2.599969
-1.118547 1.513105 1.856666 1.968822 2.497385 2.575529
-1.156521 1.630926 1.845452 2.051106 2.443167 2.534052
-1.410042 1.541981 2.135508 2.235609 2.575406 2.680553
-1.392791 1.720666 2.034946 2.192456 2.487154 2.653398
-1.581248 1.837838 2.109761 2.187484 2.497898 2.660089
-1.663078 1.901302 2.151665 2.248289 2.534789 2.639793
-1.623160 1.843067 2.177770 2.255312 2.543601 2.681190
-1.539709 1.846069 2.119080 2.315024 2.605425 2.695012
-1.532691 1.805362 2.166180 2.276515 2.582080 2.695324
-1.517203 1.864729 2.111840 2.241033 2.602399 2.678593
-1.481004 1.879771 2.183398 2.258504 2.624580 2.714706
-1.480064 1.947829 2.126591 2.239313 2.602703 2.689760
-1.615747 2.025678 2.188405 2.291472 2.673701 2.723276
-1.546688 2.023668 2.137583 2.233880 2.563573 2.627361
-1.517274 1.902434 2.132410 2.189277 2.548379 2.643352
-1.498762 1.602359 2.159933 2.275665 2.540579 2.682962
-1.573572 1.655201 2.071740 2.214602 2.523447 2.642142
-1.601993 1.680362 2.130147 2.247308 2.567706 2.670568
-1.632928 1.733671 2.134699 2.255127 2.559994 2.682076
-1.707428 1.752059 2.139704 2.252060 2.567637 2.647910
-1.680790 1.812582 2.189235 2.287297 2.578245 2.644737
-1.746130 1.778548 2.119511 2.283392 2.596379 2.686826
-1.680242 1.774944 2.097848 2.213994 2.558507 2.656276
-1.698158 1.777690 2.096918 2.211009 2.512421 2.625627
-1.757218 1.828197 2.092183 2.218630 2.459897 2.653906
-1.768299 1.815758 2.044601 2.174404 2.469800 2.674385
-1.740913 1.830010 2.044499 2.168426 2.442501 2.587668
-1.728988 1.801586 2.036902 2.135694 2.483000 2.647346
-1.740200 1.780349 2.039841 2.116482 2.460078 2.666408
-1.679167 1.810585 1.976200 2.085150 2.330970 2.574697
-1.675383 1.741676 1.986605 2.086988 2.444839 2.648385
-1.605366 1.684640 1.977146 2.084309 2.401376 2.626669
-1.593589 1.667011 1.993079 2.095793 2.477055 2.660517
-1.495436 1.677492 1.915438 2.107516 2.504100 2.687519
-1.371193 1.581007 1.812088 2.159971 2.540808 2.654514
-1.308897 1.652762 1.877696 2.100223 2.498357 2.635266
-1.257546 1.701192 1.908659 2.063978 2.330876 2.588480
-1.260641 1.733829 1.901311 2.046022 2.230421 2.379709
-1.192017 1.695443 1.866332 1.969861 2.131279 2.367813
-1.331300 1.727619 1.875686 1.967226 2.115488 2.461652
-1.221851 1.644785 1.861070 1.957289 2.263788 2.509227
-1.297010 1.684814 1.825106 1.981266 2.388696 2.497940
-1.292992 1.621691 1.795497 1.891584 2.430941 2.597238
-1.293338 1.412441 1.678427 2.013436 2.406265 2.575295
-1.355250 1.470521 1.748288 2.044830 2.411070 2.590823
-1.352085 1.474384 1.811950 2.028535 2.445376 2.597977
-1.380432 1.472981 1.836191 1.957768 2.390372 2.571170
-1.417568 1.514975 1.839991 1.974610 2.382486 2.510706
-1.396329 1.511621 1.743909 2.009524 2.414088 2.533502
-1.355999 1.511197 1.775041 1.973539 2.445398 2.568851
-1.357482 1.533305 1.820633 1.998326 2.395457 2.573696
-1.244544 1.446552 1.726849 1.935995 2.428985 2.555947
-1.206555 1.365874 1.510017 1.809039 2.464853 2.520241
-1.204707 1.340270 1.477154 1.731800 2.461076 2.525822
-1.152135 1.294762 1.429873 1.669780 2.436091 2.504828
-1.122329 1.284669 1.445441 1.811897 2.444467 2.535691
-1.167102 1.311995 1.430682 1.931216 2.579180 2.626367
-1.140963 1.255562 1.416924 1.913114 2.462643 2.552650
-1.175380 1.325094 1.434137 1.826282 2.534111 2.599692
-1.152952 1.311344 1.428753 1.733281 2.499163 2.555417
-1.208942 1.318147 1.450855 1.631131 2.484793 2.560756
-1.214984 1.312305 1.496973 1.602685 2.441060 2.513740
-1.154899 1.274352 1.497828 1.611080 2.493972 2.628464
-1.221737 1.324479 1.529355 1.668502 2.496342 2.572455
-1.265483 1.360436 1.574447 1.698291 2.465872 2.529454
-1.299969 1.411470 1.634331 1.790167 2.464188 2.546209
-1.296816 1.461296 1.674047 1.867297 2.472828 2.546532
-1.319231 1.493029 1.702922 1.867177 2.417583 2.503853
-1.307703 1.511731 1.795464 1.988697 2.415827 2.502063
-1.341439 1.567295 1.849636 2.054411 2.368545 2.484938
-1.346092 1.709857 1.847822 2.089875 2.320388 2.426929
-1.351207 1.582397 1.853947 2.087781 2.269740 2.406134
-1.403409 1.681258 1.930634 2.064741 2.317595 2.445510
-1.303563 1.800429 1.946546 2.064780 2.347899 2.575654
-1.401968 1.795117 2.043851 2.149158 2.337423 2.475421
-1.486349 1.896915 2.033679 2.164583 2.427213 2.516709
-1.581223 1.920360 2.032925 2.186636 2.458825 2.534175
-1.623672 1.949219 2.056949 2.220873 2.544733 2.612737
-1.720081 1.916335 2.069658 2.310061 2.503085 2.592652
-1.652066 1.993905 2.122170 2.282322 2.533728 2.604129
-1.696384 1.990268 2.088659 2.317899 2.562346 2.630795
-1.688613 1.976549 2.085500 2.354425 2.483404 2.567677
-1.791891 1.956617 2.084765 2.344129 2.473213 2.578020
-1.770146 1.955967 2.075143 2.263105 2.508576 2.594808
-1.688172 1.958387 2.097165 2.237127 2.443133 2.558386
-1.614095 1.858106 1.996129 2.151245 2.327315 2.485345
-1.517662 1.729778 1.975388 2.118726 2.390828 2.523423
-1.576388 1.764916 1.937347 2.159436 2.354537 2.476553
-1.596523 1.796717 1.930679 2.173774 2.415264 2.515193
-1.598274 1.758907 1.941525 2.242941 2.461919 2.548378
-1.564588 1.667806 1.910211 2.207508 2.432969 2.562295
-1.502258 1.598757 1.701036 1.993517 2.431658 2.568611
-1.261165 1.379257 1.669436 1.864259 2.424394 2.560278
-1.183142 1.291685 1.496242 1.775091 2.415349 2.571850
-1.176858 1.280643 1.397295 1.556275 2.482609 2.556911
-1.151406 1.269090 1.402613 1.529417 2.547298 2.660723
-1.138350 1.270088 1.386698 1.656508 2.516680 2.570828
-1.167637 1.288387 1.379397 1.815954 2.488744 2.544025
-1.191129 1.318584 1.433056 1.898734 2.440995 2.505523
-1.231547 1.339710 1.505832 1.865461 2.401919 2.567552
-1.249001 1.342543 1.526521 1.644629 2.260060 2.528113
-1.292116 1.385043 1.567293 1.928018 2.343597 2.526727
-1.553055 1.731196 1.875584 2.037623 2.189580 2.433617
-1.556332 1.807351 2.009873 2.134758 2.395110 2.517757
-1.700800 1.862996 2.016062 2.212872 2.465828 2.576608
-1.744516 1.892300 2.042875 2.203697 2.393022 2.529386
-1.614682 1.867043 2.024132 2.172368 2.402152 2.567866
-1.662548 1.926469 2.016222 2.153675 2.544682 2.636605
-1.607737 1.840632 2.036507 2.148869 2.475726 2.623423
-1.542603 1.789412 1.988210 2.133702 2.500071 2.623838
-1.520491 1.854019 1.966284 2.100229 2.465497 2.590987
-1.429100 1.726203 1.958566 2.068736 2.397125 2.578275
-1.230963 1.483915 1.909424 2.037168 2.278162 2.442677
-1.165473 1.402475 1.877668 1.985029 2.337001 2.482301
-1.060649 1.341795 1.891591 1.997803 2.342252 2.473851
-1.045982 1.264410 1.892878 2.028108 2.265711 2.418342
-0.872467 1.318607 1.941288 2.054895 2.265976 2.523000
-0.878165 1.208778 1.863524 2.074171 2.319885 2.460496
-0.871380 1.050930 1.866310 2.044293 2.184267 2.469225
-0.814866 1.206234 1.936241 2.046364 2.243986 2.391005
-0.791495 1.154802 1.950862 2.062225 2.270188 2.497120
-0.734873 1.117496 2.013891 2.146348 2.252079 2.340218
-0.717596 1.113315 2.145116 2.214288 2.350660 2.437091
-0.747897 1.181886 1.982640 2.073387 2.391063 2.461216
-0.814210 1.593704 1.930814 2.051889 2.279916 2.450975
-1.007998 1.635254 1.848698 1.998294 2.264960 2.399367
-1.058125 1.548258 1.725115 1.885874 2.174154 2.386746
-1.065325 1.446828 1.763113 2.061160 2.393931 2.533355
-1.245436 1.513106 1.699869 1.885972 2.163732 2.412556
-1.402218 1.550167 1.679097 2.104476 2.314265 2.464617
-1.439688 1.565541 1.746159 2.175756 2.353179 2.445969
-1.282789 1.467574 1.689789 2.057017 2.299566 2.506538
-1.157513 1.360077 1.531522 1.931682 2.277828 2.387362
-1.127719 1.287186 1.421085 1.844362 2.281074 2.385221
-1.172511 1.317506 1.497831 1.768329 2.327099 2.453399
-1.215615 1.351452 1.554622 1.706859 2.280267 2.410315
-1.162714 1.318505 1.568816 1.757107 2.225559 2.321236
-1.221146 1.364069 1.728202 1.867240 2.149636 2.323430
-1.274525 1.455876 1.651807 1.929882 2.119518 2.245371
-1.324827 1.466657 1.837727 1.982753 2.167839 2.294890
-1.207408 1.463737 1.907228 2.010942 2.187613 2.315377
-1.197505 1.325369 1.903945 2.104257 2.264375 2.406017
-0.964658 1.421326 1.800591 2.075541 2.249667 2.391422
-0.900184 1.419486 1.860531 2.052169 2.204670 2.414730
-0.976462 1.444988 1.837158 1.997086 2.133567 2.303194
-0.943062 1.543803 1.914625 1.993134 2.184650 2.344182
-0.896780 1.426973 1.923545 2.039994 2.257922 2.504524
-0.957615 1.553177 1.862682 2.044650 2.192655 2.484166
-1.024381 1.626871 1.891283 2.041787 2.304775 2.613132
-1.260699 1.570977 1.796922 1.938909 2.457980 2.543689
-1.433872 1.676893 2.020354 2.249287 2.488434 2.619226
-1.427791 1.605308 1.999841 2.197618 2.472581 2.628257
-1.344936 1.547750 2.019906 2.153463 2.482519 2.664904
-1.394553 1.830863 2.075753 2.146704 2.529848 2.662938
-1.393531 1.579984 2.005267 2.068322 2.595828 2.677955
-1.371670 1.501665 2.012362 2.069292 2.605716 2.701205
-1.365970 1.443760 1.893696 2.063362 2.540864 2.635754
-1.392813 1.470933 1.920415 1.985276 2.612047 2.670626
-1.393576 1.502340 1.926492 2.019514 2.571540 2.645701
-1.331438 1.470056 1.844344 1.945539 2.527331 2.620827
-1.280394 1.379998 1.822792 1.927676 2.470720 2.614037
-1.230446 1.394851 1.772237 1.910697 2.494879 2.569172
-1.103766 1.420997 1.742156 1.901028 2.458527 2.544960
-1.070834 1.438456 1.754789 1.827791 2.323725 2.484121
-1.023924 1.522342 1.713716 1.834742 2.289596 2.496846
-1.123843 1.539945 1.766275 1.866623 2.349980 2.441218
-1.046667 1.496581 1.791535 1.859477 2.400747 2.468296
-1.031227 1.504904 1.714267 1.944348 2.365219 2.459437
-1.201184 1.370120 1.882630 2.011333 2.411295 2.510294
-1.249461 1.324457 1.907616 2.059001 2.448619 2.551408
-1.308584 1.403015 1.961155 2.048592 2.475709 2.562469
-1.354357 1.476040 2.008730 2.111323 2.513237 2.591557
-1.415309 1.559632 2.020191 2.107847 2.505348 2.596462
-1.452150 1.536961 2.033461 2.120472 2.473458 2.600239
-1.476159 1.570668 1.981439 2.089874 2.441733 2.574939
-1.532138 1.607322 1.996255 2.099111 2.448993 2.575083
-1.578251 1.670901 1.946452 2.067931 2.484573 2.596033
-1.645992 1.719829 1.908426 2.034805 2.521504 2.630135
-1.675204 1.739089 1.858009 1.951150 2.549621 2.668138
-1.698801 1.740674 1.816221 1.872214 2.552990 2.675039
-1.589313 1.665941 1.751972 1.834254 2.495821 2.663916
-1.443571 1.535057 1.685496 1.788025 2.391781 2.644852
-1.389394 1.597558 1.884291 2.161052 2.453631 2.577281
-1.344693 1.573396 1.949051 2.033207 2.436483 2.650227
-1.340679 1.442192 1.904082 1.992387 2.427510 2.604339
-1.301569 1.363519 1.870210 1.953388 2.445808 2.609366
-1.265637 1.365516 1.838660 1.922174 2.431739 2.552480
-1.291868 1.451067 1.770742 1.900677 2.380488 2.474590
-1.319797 1.502062 1.686208 1.922008 2.291200 2.392613
-1.253224 1.445797 1.591748 1.893558 2.295028 2.381503
-1.171375 1.370630 1.523209 1.825821 2.336350 2.399182
-1.238986 1.365086 1.486833 1.790131 2.302513 2.384222
-1.186490 1.327527 1.463687 1.680778 2.322037 2.402246
-1.160765 1.294904 1.467635 1.613241 2.219663 2.329651
-1.167970 1.312269 1.458793 1.725469 2.182513 2.270653
-1.160491 1.371381 1.546645 1.859914 2.151480 2.267109
-1.060643 1.447736 1.589363 1.762026 2.187949 2.312538
-1.096873 1.449372 1.669939 1.880786 2.205157 2.322919
-0.965471 1.394985 1.664859 1.869740 2.130135 2.272101
-0.992815 1.276232 1.736324 1.883127 2.198488 2.291947
-0.989087 1.348989 1.869284 1.945029 2.217100 2.329616
-0.905850 1.296468 1.839413 1.984491 2.131357 2.261643
-0.913468 1.347104 1.974941 2.056808 2.233065 2.312403
-0.891335 1.518146 1.956057 2.017051 2.234247 2.369537
-0.838007 1.490697 2.017641 2.097784 2.331456 2.417972
-0.918242 1.411219 2.047094 2.157938 2.312207 2.414304
-0.737470 1.475335 2.131705 2.195099 2.336065 2.410088
-0.804454 1.247009 2.183193 2.253103 2.376866 2.457474
-0.910989 1.120584 2.031279 2.134740 2.301672 2.401323
-0.823657 1.023714 1.899299 2.153486 2.278157 2.468898
-0.820197 0.968457 1.655670 2.137310 2.320413 2.442552
-0.901009 1.047635 1.785794 2.126322 2.248142 2.419219
-0.908944 1.151536 1.941268 2.153759 2.287775 2.477861
-1.022921 1.329810 1.973526 2.121196 2.269160 2.496929
-1.008035 1.176565 1.832554 2.130737 2.263094 2.484071
-1.148404 1.261617 1.868165 2.138339 2.287914 2.475774
-1.131641 1.245536 1.746902 2.127206 2.273644 2.439518
-1.105449 1.230686 1.759865 2.023222 2.225896 2.485020
-1.232277 1.363476 1.914876 2.021647 2.314039 2.455927
-1.287966 1.377464 1.853658 2.039634 2.348077 2.502708
-1.285144 1.520789 1.951021 2.053636 2.366537 2.486110
-1.276358 1.656613 1.882329 2.084625 2.430619 2.524004
-1.305701 1.532539 1.861534 2.029161 2.435632 2.519577
-1.295725 1.474840 1.838375 2.045012 2.413018 2.545296
-1.232802 1.307215 1.786758 1.911450 2.533633 2.625793
-1.106012 1.252432 1.737311 1.827401 2.395470 2.658026
-1.080321 1.249736 1.763810 1.842229 2.488083 2.637970
-1.084809 1.302696 1.791104 1.915712 2.532753 2.626979
-1.024077 1.398495 1.758154 1.947685 2.536753 2.647797
-1.052552 1.486524 1.835972 2.013128 2.526539 2.621519
-0.980943 1.528894 1.887706 1.990429 2.559226 2.631730
-0.954706 1.355188 1.890849 1.968743 2.538301 2.645803
-0.894853 1.316420 1.931923 2.000630 2.617822 2.706960
-0.859848 1.166660 1.851854 2.011085 2.629872 2.731061
-0.817565 1.169139 1.975684 2.117069 2.593136 2.683713
-0.776768 0.999874 1.951669 2.126997 2.578530 2.719218
-0.750075 1.105669 2.015241 2.099156 2.469178 2.637879
-0.878438 1.039620 2.078822 2.189100 2.453168 2.610618
-0.915136 1.114879 2.017689 2.236527 2.370275 2.538277
-0.826110 1.208983 2.069074 2.156825 2.331864 2.463067
-0.869876 1.289563 2.061703 2.143050 2.313737 2.395809
-0.790056 1.421058 1.945728 2.025231 2.254924 2.384106
-0.782642 1.678142 1.928308 1.980152 2.169702 2.290020
-0.795940 1.409661 1.767797 1.894756 2.191648 2.280190
-0.832117 1.169093 1.828013 1.911028 2.228646 2.366162
-0.862231 1.189399 1.754948 1.924129 2.312126 2.412551
-1.034774 1.290469 1.783502 1.996158 2.343760 2.462730
-1.135806 1.358791 1.789192 1.980630 2.376359 2.495841
-1.303901 1.414996 1.787505 1.918440 2.435463 2.547746
-1.489246 1.592963 1.850578 1.950051 2.428039 2.571337
-1.631472 1.742640 1.887885 1.994933 2.493769 2.619665
-1.683853 1.800379 1.926611 2.064050 2.509149 2.592626
-1.745313 1.854259 1.988545 2.117137 2.504306 2.611340
-1.764270 1.890575 2.037993 2.174299 2.507724 2.600610
-1.680174 1.817366 1.937110 2.228976 2.550139 2.623314
-1.552625 1.819462 1.957322 2.263495 2.517281 2.580506
-1.558425 1.784912 2.021491 2.239374 2.543712 2.637456
-1.240665 1.739293 1.889814 2.105082 2.532436 2.618228
-0.928972 1.440269 1.769258 1.853352 2.400406 2.636877
-1.055767 1.488842 1.756065 1.832574 2.209682 2.650309
-1.013301 1.381032 1.704087 1.772713 2.155486 2.585135
-1.009186 1.333235 1.741382 1.846496 2.158765 2.517761
-1.006381 1.519900 1.813751 1.916290 2.407674 2.581853
-1.357730 1.530547 1.883639 2.141513 2.463268 2.614627
-1.426823 1.560875 1.882518 2.175206 2.488354 2.628703
-1.315984 1.579838 1.859556 2.083481 2.419884 2.564645
-1.213050 1.538899 1.800250 1.882067 2.341570 2.574606
-1.275056 1.543507 1.917099 2.127451 2.388939 2.542721
-1.438943 1.698143 1.856610 2.075189 2.266712 2.437372
-1.454331 1.663763 1.869820 2.011414 2.366272 2.533385
-1.382166 1.672920 1.827442 1.942032 2.453906 2.559856
-1.400656 1.585453 1.841334 2.002744 2.426997 2.517756
-1.382144 1.688087 1.819756 2.063153 2.417793 2.492551
-1.255095 1.603378 1.753915 2.047569 2.455562 2.569585
-1.134783 1.409147 1.705283 1.802106 2.488030 2.647140
-1.111876 1.260129 1.676050 1.778495 2.501588 2.627003
-1.060347 1.208811 1.660354 1.776864 2.488758 2.604456
-0.947120 1.164647 1.642037 1.723789 2.475156 2.567411
-0.902077 1.251204 1.664026 1.769008 2.499003 2.576704
-0.920170 1.243894 1.709681 1.794989 2.534352 2.623833
-0.938770 1.267684 1.725861 1.870157 2.549512 2.628197
-0.914357 1.254315 1.712915 1.784742 2.590431 2.707485
-0.930246 1.281241 1.802793 1.878861 2.560218 2.687216
-0.955350 1.148671 1.814732 1.902586 2.557821 2.684594
-0.968330 1.098589 1.813440 1.911875 2.463136 2.646490
-0.990311 1.185444 1.864673 1.941589 2.488112 2.664465
-1.186903 1.590929 1.954158 2.033697 2.597861 2.662179
-1.302643 1.694423 1.997444 2.169046 2.617414 2.693079
-1.379258 1.718278 1.993219 2.212202 2.543730 2.640859
-1.405165 1.780534 1.997893 2.151147 2.555776 2.632215
-1.297766 1.878255 2.020268 2.190566 2.546467 2.617338
-1.442158 1.856645 2.101038 2.299709 2.561481 2.644123
-1.370167 1.781207 2.114991 2.251821 2.446751 2.549845
-1.403451 1.703568 2.079302 2.221399 2.448766 2.593978
-1.413349 1.649169 2.009976 2.159164 2.518675 2.615138
-1.326655 1.719941 1.950443 2.025468 2.521068 2.635953
-1.385954 1.552749 1.856784 1.937506 2.496646 2.580159
-1.345409 1.488014 1.885538 2.017189 2.546874 2.625597
-1.335716 1.420210 1.787067 1.976842 2.501334 2.643553
-1.303803 1.408266 1.801454 1.901471 2.375048 2.575946
-1.312907 1.408086 1.837981 1.950093 2.318536 2.475897
-1.193613 1.293642 1.819061 1.974492 2.468077 2.585285
-1.191527 1.311470 1.711629 1.854585 2.395044 2.554024
-1.103176 1.332165 1.717922 1.857994 2.340287 2.445217
-0.996011 1.234172 1.751022 1.868274 2.285877 2.406723
-1.055311 1.378240 1.712116 1.841673 2.206702 2.440537
-1.078611 1.465910 1.787009 1.948977 2.231741 2.478981
-0.984520 1.420593 1.815304 1.925218 2.263433 2.430940
-0.984574 1.495178 1.774189 1.964126 2.221656 2.346849
-1.154842 1.507200 1.812101 1.949371 2.281741 2.426097
-1.170058 1.429376 1.745091 1.937927 2.235016 2.374769
-1.206485 1.487526 1.767298 2.009836 2.207048 2.339471
-1.073656 1.377733 1.828679 1.993004 2.130615 2.256776
-1.088454 1.495385 1.907767 1.996871 2.213903 2.390489
-1.122976 1.422213 1.865827 2.037113 2.253747 2.418388
-1.134166 1.382636 1.804236 1.963200 2.161170 2.473602
-1.245397 1.552607 1.960811 2.134690 2.453597 2.577539
-1.118704 1.567208 1.952615 2.176519 2.446630 2.578556
-1.141708 1.643603 2.013339 2.277434 2.557381 2.634785
-1.392514 1.807925 2.039343 2.237922 2.578023 2.668286
-1.433212 1.833712 2.020620 2.252182 2.518635 2.600857
-1.379262 1.712226 2.024999 2.242965 2.515533 2.602479
-1.366984 1.675637 1.976590 2.199474 2.516967 2.598815
-1.352760 1.801872 2.033607 2.181935 2.491382 2.589883
-1.323663 1.743572 2.009640 2.122701 2.474517 2.566379
-1.190092 1.540538 1.933066 2.088076 2.506726 2.570608
-1.519832 1.766187 1.906004 2.076747 2.261416 2.407680
-1.534691 1.714074 2.016476 2.130902 2.323259 2.457608
-1.522050 1.794760 2.050945 2.218278 2.408013 2.537728
-1.665365 1.906867 2.025658 2.232383 2.430131 2.550641
-1.666299 1.834650 1.998042 2.220240 2.401507 2.502391
-1.523608 1.730092 1.862962 2.164599 2.466262 2.549229
-1.216124 1.503465 1.760462 1.967473 2.381720 2.564350
-1.171128 1.429428 1.616628 1.917782 2.387933 2.477271
-1.091303 1.351374 1.568657 1.796196 2.437587 2.514874
-1.001277 1.386906 1.539603 1.775045 2.413270 2.482152
-0.952227 1.397307 1.527926 1.722524 2.442747 2.492370
-0.824979 1.388886 1.568976 1.735264 2.408751 2.471180
-0.794444 1.433059 1.588848 1.749579 2.489366 2.576364
-0.899067 1.521851 1.681397 1.780293 2.441748 2.508286
-0.922249 1.464613 1.592525 1.828442 2.418162 2.477264
-0.871556 1.444421 1.538321 1.889009 2.353691 2.412544
-0.857823 1.270248 1.501265 1.760257 2.355761 2.407297
-0.846263 1.176606 1.481984 1.614166 2.369933 2.485687
-0.882414 1.176092 1.377969 1.497390 2.380010 2.516508
-0.938718 1.100648 1.489109 1.576205 2.325566 2.543468
-0.932462 1.105586 1.294346 1.470956 2.400120 2.554718
-0.945253 1.161000 1.303877 1.580262 2.466680 2.584612
-1.018317 1.214740 1.330580 1.683749 2.482961 2.557157
-1.048240 1.175481 1.258095 1.599087 2.521448 2.642499
-1.073739 1.203513 1.298705 1.688758 2.555683 2.614473
-1.096788 1.260856 1.368595 1.755340 2.493034 2.606453
-1.105643 1.227026 1.404391 1.849702 2.523314 2.601568
-1.143864 1.269393 1.387340 1.829083 2.395167 2.496463
-1.099246 1.228614 1.344408 1.664420 2.440626 2.518066
-1.116181 1.228322 1.332947 1.667312 2.331673 2.512262
-1.201517 1.299388 1.478475 1.577915 2.003307 2.451583
-1.167995 1.292729 1.470730 1.814621 2.140965 2.436146
-1.280521 1.424881 1.595211 1.803880 2.205832 2.315376
-1.230157 1.364939 1.610435 2.002513 2.172872 2.355721
-1.302555 1.400606 1.734329 2.074003 2.208548 2.389274
-1.512686 1.818227 2.144783 2.266917 2.447736 2.569392
-1.507528 1.760422 2.164228 2.276872 2.479494 2.624837
-1.446511 1.760436 2.114696 2.256700 2.572570 2.661468
-1.468868 1.812355 2.114567 2.193023 2.617745 2.713842
-1.449647 1.776448 2.080604 2.210155 2.540909 2.713991
-1.441252 1.719517 2.114612 2.218690 2.511304 2.660049
-1.477657 1.619839 2.112699 2.198704 2.520599 2.655696
-1.532866 1.718145 2.132629 2.222301 2.551440 2.665729
-1.341030 1.814584 2.125039 2.245863 2.547976 2.649591
-1.361910 1.698086 2.076920 2.255113 2.524884 2.647043
-1.315333 1.592772 2.109776 2.210194 2.517745 2.666968
-1.382801 1.571593 2.106842 2.204058 2.495197 2.661417
-1.453626 1.641746 2.100313 2.199368 2.462404 2.608881
-1.376104 1.646574 1.987188 2.218409 2.413618 2.526810
-1.372839 1.632461 2.056237 2.163721 2.376186 2.586874
-1.432614 1.624632 2.074174 2.119889 2.480656 2.669026
-1.410683 1.662804 2.069219 2.130369 2.581373 2.714005
-1.174126 1.524516 2.032046 2.105255 2.502385 2.653307
-1.150832 1.249780 2.004788 2.158226 2.317980 2.588167
-1.057643 1.199724 2.043666 2.165479 2.371022 2.608171
-1.070330 1.169192 2.051065 2.187195 2.476449 2.671328
-0.989962 1.100883 1.959715 2.107656 2.451860 2.659328
-0.995945 1.125081 1.967729 2.171051 2.352755 2.586378
-0.951054 1.073408 1.768679 2.213097 2.362509 2.504270
-0.912647 1.063629 1.874306 2.209354 2.347793 2.515052
-0.880146 1.057702 1.939506 2.298197 2.447874 2.559719
-0.808391 0.999903 1.789456 2.221085 2.383243 2.512098
-0.872797 1.051306 1.907981 2.345885 2.551438 2.620384
-0.736864 0.925226 2.101552 2.273865 2.392948 2.568863
-0.704727 1.026198 2.094726 2.212489 2.474164 2.656197
-0.793545 1.029482 1.901019 2.333682 2.650248 2.721424
-0.890709 1.270067 2.139854 2.238320 2.544384 2.711324
-0.971655 1.317691 2.245472 2.351092 2.631963 2.711259
-1.080789 1.555771 2.010618 2.245992 2.528408 2.644890
-1.409512 1.769321 2.106696 2.284262 2.512254 2.638336
-1.248437 1.661986 2.035140 2.283241 2.534287 2.647326
-0.952460 1.123797 2.103484 2.258075 2.394744 2.604571
-0.989645 1.181656 2.023429 2.237371 2.369517 2.522527
-0.926042 1.348117 1.949341 2.062080 2.346962 2.449077
-0.919696 1.405301 1.834047 2.099696 2.376206 2.493394
-1.000811 1.371649 1.836653 2.224095 2.410108 2.539296
-1.200088 1.436788 1.839151 2.179281 2.398849 2.498430
-1.223520 1.486412 1.943988 2.252258 2.407325 2.540679
-1.113671 1.477208 1.844163 2.218008 2.381333 2.486877
-1.138107 1.498752 1.980951 2.297474 2.457848 2.560767
-1.146154 1.614539 1.898903 2.232476 2.416572 2.510958
-1.119673 1.589916 1.824415 2.111914 2.354760 2.453276
-1.032037 1.589416 1.852847 2.142988 2.324001 2.472943
-0.989427 1.528982 1.914645 2.179193 2.376737 2.494371
-1.095755 1.494564 1.866122 2.136805 2.283713 2.464058
-0.834557 1.463722 1.882565 2.150927 2.378636 2.463091
-0.835589 1.296069 1.771371 2.098776 2.286243 2.426378
-0.806577 1.403328 1.685216 2.040945 2.235736 2.356401
-0.800011 1.383092 1.814158 1.959934 2.309583 2.386791
-0.804745 1.318210 1.821360 1.908703 2.235131 2.427141
-0.895849 1.367225 1.864812 1.979670 2.324237 2.420788
-0.827390 1.425085 1.767158 2.058185 2.376232 2.469430
-0.917915 1.497920 1.855338 1.987207 2.315382 2.451640
-0.940855 1.409563 1.789190 1.988531 2.336666 2.534686
-0.972711 1.291697 1.786937 1.914881 2.323264 2.405491
-0.993281 1.368817 1.807237 1.958622 2.357274 2.459276
-1.074694 1.349312 1.840844 1.954844 2.269081 2.384056
-1.100597 1.218573 1.756134 1.900188 2.277874 2.406215
-1.165622 1.313695 1.843695 1.962222 2.157100 2.342911
-1.157768 1.372357 1.879963 1.991928 2.258080 2.390865
-1.286092 1.780986 1.959702 2.118874 2.324541 2.437595
-1.455169 1.738149 2.098885 2.235010 2.428464 2.539714
-1.500252 1.684257 2.161002 2.272591 2.399078 2.510334
-1.485672 1.846402 2.195717 2.305655 2.546282 2.650594
-1.727818 2.013707 2.167283 2.304214 2.586608 2.652160
-1.676773 1.960528 2.217006 2.368813 2.598284 2.681624
-1.631959 1.915752 2.227040 2.335178 2.603101 2.710218
-1.663857 1.973017 2.124709 2.222354 2.660483 2.724322
-1.542011 1.929582 2.075601 2.170628 2.628551 2.707745
-1.509689 1.706046 2.056908 2.197674 2.578326 2.653903
-1.482072 1.673728 2.131047 2.194868 2.586319 2.690293
-1.423447 1.643267 2.092317 2.178941 2.527205 2.636748
-1.355154 1.565169 2.023932 2.236487 2.538323 2.655495
-1.328421 1.553976 2.081558 2.161922 2.472742 2.656928
-1.330758 1.419042 2.026707 2.129051 2.367999 2.571017
-1.270648 1.377593 2.025948 2.140131 2.389237 2.575945
-1.236825 1.345428 2.022395 2.109848 2.478126 2.633911
-1.222076 1.320425 1.939670 2.021742 2.436807 2.628532
-1.252172 1.358274 1.972621 2.079346 2.371453 2.598928
-1.266234 1.470203 1.930446 2.145813 2.471858 2.618153
-1.332281 1.546411 2.025723 2.219524 2.464616 2.645111
-1.418604 1.649476 2.008305 2.128114 2.489878 2.676868
-1.455677 1.684682 1.988976 2.152647 2.470396 2.651526
-1.447490 1.600650 1.935900 2.271764 2.512990 2.631833
-1.444770 1.556361 2.020377 2.282318 2.475768 2.612336
-1.387476 1.487406 2.024679 2.244659 2.445046 2.582829
-1.353922 1.443279 1.957555 2.171307 2.336106 2.560084
-1.369786 1.447714 2.006181 2.191416 2.404713 2.604727
-1.425956 1.504279 2.072312 2.178177 2.417663 2.603411
-1.440235 1.540501 2.082397 2.211979 2.377070 2.637315
-1.497010 1.582681 2.056522 2.172175 2.389278 2.593845
-1.504963 1.584564 1.984094 2.149333 2.367563 2.559723
-1.519045 1.603989 1.993800 2.109929 2.327255 2.599694
-1.569559 1.651048 1.988942 2.116726 2.345772 2.569917
-1.569894 1.683682 1.980575 2.182917 2.357234 2.587282
-1.607074 1.712704 1.951468 2.125681 2.307168 2.547246
-1.645231 1.736599 1.952360 2.131487 2.376223 2.606463
-1.669612 1.763984 1.979653 2.173233 2.332349 2.516667
-1.632436 1.758871 1.980800 2.124271 2.285899 2.443828
-1.557406 1.667695 1.902055 2.106931 2.260859 2.483917
-1.470421 1.688945 1.846379 2.032834 2.185130 2.375868
-1.421944 1.531479 1.825667 2.026592 2.180382 2.360115
-1.385644 1.606158 1.846365 2.071388 2.488500 2.607454
-1.359715 1.577664 1.897105 2.111958 2.471108 2.603005
-1.339447 1.542640 1.933966 2.133741 2.454906 2.583194
-1.325808 1.691761 2.080233 2.164213 2.474164 2.605215
-1.347146 1.624704 2.074108 2.214395 2.430593 2.562946
-1.314857 1.541837 1.967631 2.164145 2.372693 2.606516
-1.312898 1.534081 1.917285 2.089949 2.411610 2.570672
-1.283019 1.557401 1.937879 2.103338 2.520615 2.623700
-1.138825 1.337472 1.871092 1.972746 2.433484 2.647653
-1.155936 1.281125 1.831346 1.919243 2.266602 2.600943
-1.166841 1.273824 1.843198 1.946026 2.318377 2.578792
-1.172291 1.275007 1.832581 2.025917 2.353813 2.624686
-1.082157 1.265436 1.892357 1.989008 2.383161 2.601421
-1.091903 1.208823 1.835009 2.034461 2.394722 2.562904
-1.098835 1.199487 1.757650 2.065888 2.390403 2.578893
-1.132798 1.244386 1.876625 2.071549 2.339183 2.537916
-1.180603 1.259469 1.823163 2.095055 2.256898 2.542724
-1.186987 1.312908 1.800793 2.105036 2.366989 2.496082
-1.266390 1.377139 1.810434 2.113272 2.329619 2.533152
-1.323586 1.404515 1.904242 2.145928 2.386113 2.580936
-1.352171 1.451401 1.949824 2.077051 2.390820 2.538573
-1.343859 1.452231 1.889889 2.026744 2.317477 2.482486
-1.244808 1.378854 1.792557 1.986745 2.422571 2.536950
-1.124619 1.253596 1.703825 1.951315 2.439640 2.545147
-0.995104 1.411750 1.728505 1.861639 2.456605 2.544957
-1.001072 1.409106 1.797727 1.897572 2.409482 2.555324
-1.033981 1.428160 1.786944 1.880286 2.326359 2.503159
-0.970169 1.320721 1.716642 1.841569 2.220200 2.388916
-0.930477 1.373382 1.798398 1.904734 2.305786 2.525304
-0.939935 1.418455 1.772704 1.878087 2.367491 2.461526
-0.949116 1.527114 1.765903 1.840735 2.164926 2.474337
-0.993353 1.629343 1.813445 1.910215 2.100772 2.492902
-1.013830 1.549621 1.796834 1.891936 2.239760 2.556346
-0.970121 1.509802 1.834006 1.938978 2.338575 2.504346
-0.947238 1.361377 1.783553 1.984713 2.423900 2.547178
-0.980991 1.388783 1.783307 2.131708 2.454635 2.558692
-1.002668 1.402339 1.807195 2.024461 2.464418 2.554280
-1.010697 1.404186 1.872558 2.079362 2.479332 2.569625
-0.972976 1.375802 1.843367 1.980698 2.513609 2.578272
-0.932062 1.277676 1.851126 1.985878 2.466286 2.566260
-0.938577 1.181150 1.833964 1.965034 2.458011 2.550532
-0.940095 1.145447 1.796688 2.078273 2.482897 2.610630
-0.909789 1.074084 1.717403 2.139110 2.462525 2.572261
-0.882446 1.066652 1.729556 2.284662 2.478899 2.555022
-0.938178 1.121504 1.828485 2.234041 2.474778 2.557100
-0.917165 1.283072 1.779497 2.100290 2.475831 2.590182
-1.062938 1.349043 1.762759 2.118297 2.504806 2.606788
-1.186965 1.461900 1.889039 2.112738 2.481323 2.621310
-1.480720 1.619232 1.979483 2.177103 2.436476 2.578983
-1.448723 1.566337 1.880134 2.138534 2.339676 2.554594
-1.407995 1.613546 1.828927 2.052703 2.344501 2.538078
-1.616019 1.691006 1.856347 1.980078 2.548246 2.637759
-1.628171 1.684163 1.886153 2.012867 2.563772 2.621577
-1.595743 1.688011 1.935400 2.025813 2.483630 2.616820
-1.641560 1.708656 1.955460 2.046989 2.519834 2.645741
-1.673668 1.752213 1.951288 2.080918 2.487394 2.640725
-1.656417 1.736239 1.991365 2.098321 2.571908 2.676827
-1.659820 1.732449 1.951246 2.077020 2.581642 2.693515
-1.654803 1.716207 1.966639 2.044230 2.563251 2.680200
-1.602729 1.682614 1.917410 1.994825 2.531087 2.673289
-1.582550 1.639535 1.926100 1.992074 2.532073 2.697110
-1.462370 1.585004 1.818300 1.897553 2.557132 2.706256
-1.453199 1.550734 1.815192 1.916461 2.399968 2.667684
-1.419387 1.557717 1.784441 1.909176 2.511382 2.669980
-1.395165 1.539820 1.847477 1.930837 2.583961 2.703625
-1.348853 1.610875 1.958146 2.043068 2.586086 2.664353
-1.372390 1.658144 1.958657 2.189437 2.450481 2.650316
-1.352586 1.528092 1.923141 2.194837 2.427729 2.562143
-1.380925 1.612272 1.993385 2.176111 2.508934 2.635056
-1.429580 1.686586 2.017126 2.172565 2.486420 2.609268
-1.392123 1.641039 1.952077 2.065066 2.421215 2.574909
-1.399593 1.788262 1.952093 2.098580 2.489935 2.629393
-1.383756 1.662435 1.983097 2.112236 2.532805 2.631814
-1.372732 1.673625 1.912122 2.134246 2.432996 2.612276
-1.396034 1.642619 1.962634 2.197392 2.521323 2.660686
-1.379360 1.623989 2.069404 2.243124 2.562033 2.668437
-1.338665 1.618629 2.042041 2.195119 2.570159 2.699099
-1.294124 1.712084 2.050162 2.120133 2.607839 2.681695
-1.293254 1.596252 1.993414 2.060041 2.583077 2.664144
-1.209917 1.362665 1.955116 2.028347 2.512957 2.625803
-1.381701 1.706617 2.003167 2.146470 2.500026 2.613009
-1.204671 1.734562 1.928802 2.109687 2.476898 2.549090
-1.114491 1.696319 1.888819 2.043672 2.539268 2.637168
-1.119312 1.601460 1.846733 2.085664 2.577543 2.645353
-1.128747 1.531175 1.858280 2.146770 2.596351 2.688725
-1.130254 1.674654 1.830664 2.172114 2.562554 2.672831
-1.100767 1.644406 1.833225 2.040605 2.599334 2.652288
-1.066968 1.530596 1.768634 2.003323 2.617323 2.678055
-1.063119 1.469356 1.797817 1.881851 2.568187 2.679145
-1.177293 1.703277 1.865510 2.061041 2.481068 2.581444
-1.404135 1.657504 1.927058 2.181851 2.457409 2.580431
-1.428360 1.663538 1.984994 2.183449 2.458664 2.569489
-1.403204 1.667154 1.955094 2.146449 2.462636 2.562658
-1.234126 1.597848 1.917754 2.034440 2.407548 2.560257
-1.224528 1.368625 1.848065 1.924719 2.494949 2.670207
-1.214772 1.588344 1.765811 2.003861 2.526784 2.635964
-1.264884 1.636472 1.825225 2.077058 2.563495 2.679292
-1.269611 1.588977 1.782182 2.095015 2.620415 2.691789
-1.296409 1.504336 1.802915 2.013382 2.605687 2.681621
-1.334375 1.520771 1.796606 1.963884 2.600418 2.703744
-1.397570 1.600583 1.845972 1.940123 2.616223 2.696111
-1.430879 1.559075 1.799241 1.994052 2.598948 2.674700
-1.482115 1.583037 1.807507 1.981426 2.575382 2.684729
-1.464344 1.565621 1.776029 1.917627 2.575000 2.659270
-1.455399 1.538232 1.730658 1.882074 2.563750 2.660443
-1.499577 1.584423 1.688069 1.892068 2.587098 2.688675
-1.479760 1.573703 1.695194 2.024437 2.558177 2.639037
-1.452267 1.547118 1.750567 2.072025 2.537014 2.673786
-1.447379 1.563037 1.794376 2.141633 2.353387 2.502548
-1.351721 1.450714 1.730230 1.991889 2.298349 2.463553
-1.318760 1.414624 1.641985 1.948338 2.326246 2.474291
-1.212051 1.346227 1.685099 1.959885 2.322238 2.512951
-1.209021 1.302946 1.634616 1.930848 2.282912 2.507545
-1.188947 1.292823 1.665660 2.177853 2.373563 2.474293
-1.257542 1.451148 1.836011 2.161476 2.447295 2.596642
-1.253420 1.370197 1.833717 2.244743 2.479769 2.576022
-1.179954 1.302011 1.592154 2.151577 2.455959 2.518120
-1.114477 1.257653 1.411579 2.042361 2.548294 2.620409
-1.099986 1.307070 1.407174 2.159418 2.585914 2.649358
-1.131151 1.246857 1.401279 2.116604 2.483756 2.546663
-1.173775 1.340865 1.449901 2.093705 2.561030 2.626482
-1.189575 1.346203 1.465586 2.003540 2.517749 2.575697
-1.217965 1.302991 1.569488 2.028970 2.455729 2.550140
-1.231915 1.393228 1.520464 1.955734 2.476226 2.642241
-1.277177 1.451138 1.591018 1.925992 2.458091 2.566561
-1.216236 1.483117 1.688680 1.988972 2.454628 2.599617
-1.184293 1.553039 1.838890 2.100265 2.385006 2.550049
-1.239174 1.792822 1.959073 2.182600 2.445294 2.529569
-1.624571 1.860854 2.120332 2.219916 2.429410 2.594102
-1.753243 1.889331 2.136521 2.254574 2.436331 2.562459
-1.757269 1.956924 2.242335 2.360108 2.493739 2.587626
-1.806843 1.985195 2.197761 2.338682 2.496335 2.600682
-1.859905 2.030422 2.282537 2.396000 2.548595 2.632629
-1.771104 1.896134 2.306763 2.421261 2.538338 2.625956
-1.505646 1.893235 2.019328 2.325790 2.487965 2.585530
-1.189137 1.771099 1.915068 2.254873 2.534430 2.612783
-1.103999 1.649346 1.834993 1.935938 2.534134 2.651998
-1.079006 1.522445 1.767276 1.934965 2.523135 2.596389
-1.106210 1.608040 1.751444 2.008392 2.491731 2.577152
-1.225135 1.597265 1.857833 2.103611 2.465420 2.593047
-1.375366 1.618359 1.930516 2.214454 2.445564 2.576198
-1.429991 1.698975 1.982144 2.233337 2.490443 2.605353
-1.482797 1.679463 1.997759 2.222400 2.464577 2.586822
-1.407997 1.676636 1.970849 2.221085 2.440364 2.592428
-1.279905 1.618797 1.920986 2.161088 2.438805 2.627424
-0.936959 1.310295 1.663367 2.010101 2.515991 2.597781
-1.014662 1.401511 1.590078 2.080875 2.556905 2.622152
-1.043648 1.384572 1.571501 1.988231 2.568660 2.647893
-1.107266 1.413973 1.562057 1.877144 2.554722 2.637289
-1.179476 1.467385 1.605003 1.839003 2.523485 2.640499
-1.218315 1.412023 1.591634 1.796526 2.519799 2.660570
-1.305370 1.427385 1.614577 1.763694 2.497267 2.657791
-1.338542 1.456340 1.642200 1.862353 2.448789 2.631625
-1.328675 1.442223 1.575230 1.858910 2.470665 2.570433
-1.351215 1.466285 1.601432 1.863743 2.425253 2.500336
-1.360914 1.476484 1.624624 1.832107 2.486273 2.563333
-1.401730 1.499881 1.613403 1.749733 2.423219 2.591408
-1.261551 1.402991 1.523781 1.802043 2.499740 2.605532
-1.160005 1.467049 1.605598 1.787691 2.508050 2.557362
-1.279521 1.535093 1.620574 1.758619 2.409621 2.676419
-1.161358 1.505461 1.626199 1.733096 2.398831 2.617482
-1.184633 1.528528 1.614286 1.698210 2.350337 2.667102
-1.117350 1.538074 1.658450 1.759625 2.281261 2.580678
-1.109838 1.492830 1.701966 1.789832 2.151236 2.489725
-1.010233 1.467118 1.631090 1.886421 2.420021 2.522779
-0.950861 1.336887 1.617005 1.789550 2.449618 2.528894
-1.028468 1.348095 1.571888 1.880393 2.543912 2.608014
-1.110746 1.415658 1.690546 2.005512 2.558177 2.650097
-1.110147 1.432665 1.669404 1.901594 2.516926 2.602743
-1.067829 1.543381 1.719440 1.979004 2.543666 2.617575
-1.422545 1.701061 1.940427 2.327061 2.557612 2.642956
-1.386122 1.781934 2.040679 2.383895 2.573951 2.633463
-1.512775 1.696332 2.184500 2.295985 2.578995 2.677261
-1.571845 1.705242 2.225227 2.319189 2.542604 2.676163
-1.514913 1.844285 2.247341 2.361592 2.529071 2.653297
-1.603580 1.948417 2.271813 2.429600 2.528208 2.617731
-1.620409 2.024184 2.379020 2.477983 2.622963 2.670765
-1.578823 1.906347 2.238314 2.378843 2.556955 2.647118
-1.611136 1.900666 2.185777 2.317384 2.517010 2.610141
-1.554611 1.941431 2.133055 2.249862 2.491762 2.571608
-1.469621 1.918901 2.094184 2.225177 2.490350 2.564343
-1.335366 1.697214 2.017085 2.232317 2.474337 2.571016
-1.221936 1.519055 1.814063 2.129404 2.458290 2.560125
-1.193348 1.426044 1.731637 2.009086 2.485687 2.566097
-1.140861 1.304138 1.724072 1.962123 2.456816 2.673582
-1.171988 1.316998 1.756942 2.050812 2.520621 2.679355
-1.135139 1.410213 1.715289 2.092595 2.499448 2.617713
-1.114534 1.487214 1.595404 2.013785 2.531961 2.628395
-1.185163 1.399888 1.582655 2.195793 2.518380 2.582468
-1.104552 1.423680 1.656289 2.262530 2.593187 2.664012
-1.164305 1.596992 1.717746 2.207846 2.563155 2.621398
-1.022593 1.596460 1.831763 2.287975 2.519037 2.580420
-0.920067 1.656499 1.829222 2.207172 2.535598 2.582536
-0.940069 1.577439 1.960575 2.189248 2.482820 2.549330
-0.824619 1.708493 1.932229 2.188611 2.551880 2.605484
-0.819752 1.688971 1.950607 2.083451 2.463192 2.515870
-0.820934 1.718478 2.021631 2.158415 2.521119 2.576288
-0.860984 1.615689 2.046857 2.146219 2.469888 2.571061
-0.722400 1.647372 1.973155 2.066104 2.438838 2.609071
-0.853506 1.577947 1.949855 2.082839 2.448741 2.512425
-0.745605 1.464510 1.993321 2.077513 2.469178 2.532474
-0.710718 1.533693 1.890047 2.013877 2.425598 2.516390
-0.877569 1.511979 1.831605 2.031903 2.441617 2.517441
-1.259618 1.519519 1.879696 2.138828 2.450290 2.614072
-1.326658 1.670099 1.919340 2.148365 2.362928 2.464453
-1.437714 1.671637 1.955052 2.166713 2.405950 2.557523
-1.603868 1.740291 1.989945 2.198778 2.467525 2.585653
-1.638499 1.743252 2.051089 2.149707 2.462625 2.569332
-1.631833 1.721768 2.002918 2.131145 2.438931 2.569221
-1.603157 1.763192 2.082194 2.174769 2.376719 2.502259
-1.630977 1.703944 2.009215 2.149268 2.369179 2.580570
-1.576599 1.658687 1.922940 2.124950 2.448734 2.578273
-1.516265 1.630706 1.860803 2.127036 2.444402 2.582277
-1.458879 1.547626 1.796080 2.046972 2.378056 2.535592
-1.376657 1.512511 1.733562 2.098209 2.361768 2.452137
-1.134749 1.320184 1.582547 2.052886 2.449062 2.527062
-1.079447 1.164059 1.573367 2.220764 2.500300 2.560928
-1.060468 1.186417 1.456658 2.155790 2.437004 2.526903
-0.974645 1.132811 1.563530 2.089864 2.504612 2.571780
-0.925733 1.049035 1.555693 2.095444 2.541677 2.614171
-1.012861 1.154680 1.283807 2.126165 2.558786 2.595811
-0.970704 1.088894 1.398803 1.969666 2.517460 2.621486
-0.996670 1.155602 1.284230 1.967741 2.478048 2.536750
-1.061875 1.172759 1.296847 1.890131 2.465313 2.550488
-0.971133 1.146895 1.425088 1.823656 2.310199 2.513193
-1.122316 1.246948 1.573931 1.945863 2.350666 2.546107
-1.130444 1.281802 1.711748 2.052845 2.471168 2.568969
-1.285794 1.425185 1.874398 2.085225 2.426111 2.576993
-1.273537 1.490213 1.878772 2.106249 2.402449 2.544368
-1.224244 1.462476 1.904611 2.128189 2.416565 2.570019
-1.252061 1.449849 1.802510 2.119875 2.418885 2.518798
-1.327124 1.417585 1.789962 2.174930 2.340651 2.468715
-1.346777 1.435555 1.734308 2.036035 2.356552 2.531051
-1.235820 1.315959 1.597124 1.897870 2.284217 2.575948
-0.955415 1.303770 1.560187 1.730070 2.449775 2.648120
-0.909089 1.471674 1.624478 1.890973 2.389653 2.627950
-0.919631 1.366873 1.506021 1.842587 2.342002 2.554492
-0.855197 1.279671 1.539553 1.688524 2.386911 2.502065
-0.807057 1.135620 1.541600 1.681299 2.243913 2.510869
-0.849115 1.190235 1.449935 1.541388 2.302579 2.655596
-0.832569 1.273363 1.592481 1.792808 2.284175 2.498482
-0.835449 1.168916 1.544629 1.718930 2.423889 2.632619
-0.826578 1.276188 1.407857 1.660287 2.378044 2.474526
-0.873632 1.360315 1.502868 1.758332 2.570802 2.712262
-0.828320 1.284633 1.462407 1.624198 2.575860 2.705612
-0.866930 1.133312 1.254056 1.429890 2.499289 2.562307
-0.807119 1.218080 1.346012 1.540621 2.487606 2.633103
-0.983680 1.146576 1.336648 1.479310 2.327156 2.614361
-0.991742 1.170728 1.296168 1.485606 2.543050 2.663819
-0.857243 1.172195 1.298593 1.623901 2.581253 2.675646
-1.024459 1.245164 1.335833 1.923956 2.623488 2.689817
-1.035260 1.293064 1.419811 1.882694 2.474976 2.673673
-0.981160 1.239841 1.334553 1.628448 2.544049 2.681735
-0.948338 1.227389 1.360095 1.572061 2.447980 2.668611
-1.097120 1.256099 1.362188 1.632542 2.507787 2.656424
-1.060738 1.283998 1.527933 1.676274 2.540944 2.638141
-0.999111 1.230695 1.531258 1.643979 2.373065 2.634336
-0.900037 1.357157 1.519901 1.691155 2.333453 2.605899
-0.906535 1.200477 1.615255 1.715962 2.288870 2.609565
-0.841267 1.337701 1.721187 1.799125 2.176356 2.627236
-0.950819 1.507117 1.718816 1.826725 2.050526 2.489892
-0.922437 1.447590 1.832061 1.920513 2.148990 2.509573
-0.797637 1.120473 1.756266 1.946112 2.209112 2.535941
-0.821846 1.168739 1.837911 1.977726 2.361612 2.642410
-0.802821 1.394640 1.945588 2.031517 2.337491 2.589953
-0.808599 1.214285 1.878529 2.002325 2.280219 2.577779
-0.825133 1.329296 1.896620 1.979559 2.455746 2.573104
-0.847939 1.235948 1.897295 2.016610 2.422214 2.651151
-0.793266 1.311794 1.885265 1.974869 2.493916 2.699921
-0.835729 1.418115 1.839725 1.903232 2.507962 2.645131
-0.849380 1.476197 1.836815 1.977378 2.321338 2.561101
-0.774570 1.284607 1.758190 1.864424 2.367732 2.561205
-0.896154 1.466437 1.770222 1.871354 2.586553 2.688477
-1.097803 1.576496 1.742325 1.910224 2.160666 2.658455
-0.950720 1.452865 1.760158 1.934774 2.196277 2.624191
-0.947778 1.334777 1.745609 1.830510 2.256113 2.667856
-0.970291 1.214911 1.745935 1.840709 2.268780 2.555177
-1.027483 1.193053 1.655411 1.770558 2.115990 2.502962
-1.108625 1.224039 1.556423 1.705900 2.019067 2.463824
-1.137334 1.248642 1.659896 1.835999 2.087298 2.494018
-1.192784 1.290313 1.652861 1.878632 2.086082 2.615960
-1.231829 1.343294 1.528206 1.646125 1.912160 2.354407
-1.043149 1.380698 1.679143 1.830121 2.008367 2.414010
-1.102887 1.243057 1.747479 1.861385 2.203092 2.504381
-1.049734 1.354368 1.735882 1.819000 2.248805 2.557794
-1.105977 1.571421 1.764806 1.953547 2.428854 2.560105
-1.290846 1.550164 1.837562 2.126596 2.488831 2.600779
-1.194236 1.426699 1.837665 1.914014 2.443207 2.635517
-1.165504 1.260088 1.790938 1.893312 2.400453 2.646643
-1.224955 1.308139 1.825926 1.919493 2.321356 2.695079
-1.248486 1.345382 1.775451 1.876708 2.353719 2.654140
-1.271138 1.399667 1.811535 1.897580 2.403493 2.653922
-1.309100 1.407658 1.806843 1.897827 2.339222 2.632347
-1.291018 1.383330 1.802439 1.887187 2.247718 2.662452
-1.261355 1.370512 1.755969 1.871246 2.101895 2.593588
-1.282645 1.376536 1.775534 1.904499 2.192341 2.507429
-1.361360 1.450864 1.791066 1.906164 2.221501 2.543343
-1.334993 1.431384 1.716268 1.905493 2.089197 2.378260
-1.385673 1.470423 1.765397 1.909217 2.173842 2.456572
-1.364318 1.455064 1.754884 1.871473 2.365039 2.572279
-1.387777 1.486887 1.712089 1.847504 2.243563 2.570692
-1.312448 1.425290 1.622893 1.756780 1.978470 2.367512
-1.347202 1.454345 1.683431 1.825472 2.087917 2.462563
-1.326447 1.405443 1.727641 1.835551 2.328868 2.614333
-1.333108 1.429712 1.796075 1.900347 2.445062 2.652912
-1.322803 1.421588 1.736939 1.843495 2.532120 2.646639
-1.344685 1.431856 1.766206 1.924579 2.550076 2.689857
-1.388277 1.485813 1.711960 1.826211 2.496137 2.658495
-1.411133 1.495610 1.776872 1.876674 2.492586 2.651345
-1.417795 1.491577 1.801693 1.890405 2.442446 2.706992
-1.406122 1.515595 1.757336 1.896968 2.382045 2.633633
-1.425860 1.514813 1.773260 1.901744 2.447546 2.634715
-1.476029 1.555032 1.745731 1.861617 2.398766 2.614978
-1.459852 1.561528 1.786445 1.911235 2.476542 2.591787
-1.403056 1.514189 1.720761 1.900939 2.489890 2.577333
-1.428127 1.523512 1.689756 1.835214 2.458899 2.565972
-1.328956 1.434709 1.604068 1.734252 2.466296 2.566835
-1.241317 1.343249 1.457997 1.696624 2.527818 2.645659
-1.136623 1.311125 1.429957 1.695364 2.542525 2.660410
-1.153111 1.344144 1.690808 1.985929 2.420013 2.553782
-1.231755 1.373918 1.668818 2.117444 2.401907 2.488883
-0.978581 1.115592 1.517126 2.000531 2.449025 2.526020
-0.951081 1.107962 1.208612 1.737223 2.474298 2.611849
-0.981806 1.127841 1.220590 1.720985 2.586528 2.698889
-0.977554 1.224067 1.337758 1.713271 2.593374 2.675408
-0.986078 1.260397 1.407440 1.571486 2.569420 2.631754
-1.068774 1.209396 1.464430 1.557978 2.551351 2.669751
-1.034191 1.174307 1.467256 1.555295 2.460490 2.642259
-1.056632 1.178692 1.509897 1.621544 2.153033 2.540535
-1.108939 1.240242 1.651384 1.778538 2.227605 2.571951
-1.040854 1.397785 1.709633 1.830019 2.398698 2.618954
-1.063080 1.564032 1.695538 1.794688 2.419017 2.577353
-1.156653 1.579890 1.742991 1.888966 2.419007 2.626873
-1.282148 1.604674 1.769820 1.984806 2.290529 2.408545
-1.414961 1.752587 1.937904 2.076787 2.287689 2.502281
-1.561586 1.882695 2.087185 2.199871 2.398595 2.509058
-1.741771 1.963051 2.161078 2.262211 2.516056 2.626131
-1.579553 1.916299 2.201667 2.301679 2.458486 2.648337
-1.656200 1.849299 2.101697 2.302170 2.487760 2.573832
-1.761707 1.935887 2.167102 2.423095 2.531309 2.619774
-1.747342 1.946460 2.129719 2.452120 2.591709 2.681100
-1.664774 1.950714 2.064839 2.452925 2.653282 2.719977
-1.182120 1.806988 2.031810 2.240448 2.589338 2.666952
-0.911793 1.444427 1.938199 2.009542 2.518849 2.662424
-0.906235 1.353950 1.860144 1.948940 2.570343 2.653728
-0.915756 1.182444 1.779374 1.918355 2.495182 2.685238
-0.923262 1.168083 1.705447 2.007985 2.401242 2.584424
-0.915338 1.196101 1.641183 1.957797 2.235160 2.502509
-1.116935 1.269153 1.597465 1.950801 2.129101 2.392503
-1.227147 1.344231 1.809259 1.999158 2.320768 2.545770
-1.307876 1.517973 1.832338 2.042156 2.347761 2.543408
-1.142909 1.427477 1.831520 2.022295 2.356478 2.589639
-1.020209 1.202712 1.780168 2.070788 2.565827 2.661648
-1.087846 1.265956 1.653284 2.093962 2.625661 2.709244
-1.146593 1.234170 1.666291 2.022252 2.605716 2.676253
-1.089057 1.311412 1.647149 1.833847 2.666682 2.722762
-1.188386 1.319963 1.725677 1.806948 2.571193 2.664171
-1.209565 1.358036 1.697429 1.794200 2.470455 2.640229
-1.246047 1.338292 1.695538 1.782003 2.565757 2.666941
-1.261251 1.384481 1.619675 1.779584 2.591799 2.712426
-1.337507 1.450232 1.646992 1.774207 2.578969 2.703367
-1.387688 1.478096 1.618920 1.747276 2.531990 2.665704
-1.301779 1.392643 1.541867 1.665649 2.484537 2.655063
-1.257012 1.398833 1.527358 1.734139 2.619531 2.689676
-1.211161 1.324264 1.664338 1.911508 2.589343 2.685254
-1.113028 1.325407 1.697702 1.940185 2.591124 2.679629
-1.000343 1.352231 1.719494 2.024790 2.577661 2.639096
-0.952537 1.564659 1.914580 2.021105 2.481262 2.553572
-0.941380 1.573371 1.898482 1.990822 2.388399 2.527824
-0.835656 1.426857 1.914902 2.006303 2.455843 2.544426
-0.762518 1.617975 1.848163 1.952719 2.511683 2.576889
-0.760103 1.720246 1.884039 1.972497 2.526184 2.668968
-0.788105 1.515939 1.760885 1.953721 2.498661 2.553903
-0.842390 1.235086 1.687435 2.011114 2.391471 2.529546
-0.970555 1.304880 1.689915 2.060096 2.386014 2.524270
-1.078507 1.220815 1.630394 2.103928 2.411414 2.518300
-1.035130 1.374294 1.739516 2.015391 2.383541 2.542893
-1.232775 1.466122 1.942876 2.112602 2.359872 2.476841
-1.032139 1.460157 1.843607 2.111319 2.405612 2.545609
-0.863004 1.575367 1.754339 2.026425 2.484055 2.545871
-0.781880 1.621135 1.876114 2.131620 2.591150 2.665213
-0.689257 1.567671 1.951319 2.246727 2.507788 2.649956
-0.762920 1.454508 2.052137 2.239950 2.408909 2.570384
-0.735313 1.369541 2.141121 2.226737 2.404256 2.515847
-0.692794 1.213217 2.021728 2.170012 2.409789 2.632609
-0.749191 1.327407 1.876305 2.159813 2.396372 2.543556
-0.723514 1.311926 1.779121 2.000990 2.333064 2.521625
-0.800844 1.399334 1.702525 1.886771 2.183805 2.391837
-0.935365 1.532399 1.746103 1.843273 2.027876 2.366925
-0.879717 1.390978 1.696694 1.873227 2.273388 2.532951
-1.115628 1.395380 1.552486 2.062541 2.379745 2.485662
-1.253460 1.379822 1.726521 2.164899 2.386851 2.507812
-1.288652 1.548609 1.769224 2.106137 2.428838 2.517503
-1.369653 1.611147 1.793668 1.970474 2.367649 2.558036
-1.399028 1.694930 1.865624 2.036762 2.409162 2.586430
-1.433335 1.745725 1.930732 2.159385 2.426554 2.579037
-1.267585 1.665867 1.971379 2.103318 2.444523 2.567741
-1.226120 1.497218 1.888612 2.083592 2.547854 2.623475
-1.217864 1.502320 1.850155 1.973913 2.506017 2.625566
-1.213794 1.595369 1.875039 1.979415 2.427150 2.606463
-1.239752 1.513874 1.766680 1.947926 2.281624 2.492074
-1.247634 1.585626 1.729740 1.894696 2.381964 2.522121
-1.201153 1.474465 1.746568 1.834238 2.289729 2.525183
-1.181465 1.555321 1.703604 1.823083 2.315827 2.443888
-1.196327 1.573762 1.735225 1.808031 2.403501 2.557243
-1.149081 1.631606 1.769163 1.925569 2.368122 2.542814
-1.071093 1.633545 1.761338 1.872468 2.408464 2.573521
-1.065230 1.551738 1.713412 1.880487 2.387426 2.512159
-0.987564 1.635727 1.785940 1.956709 2.413400 2.548618
-0.931677 1.526457 1.773013 1.896960 2.437956 2.513898
-0.900322 1.645882 1.787979 2.041039 2.334273 2.434592
-0.867303 1.714715 1.901607 2.099190 2.387096 2.475894
-0.868278 1.693735 1.917301 2.013076 2.274597 2.382531
-0.848816 1.567192 1.829012 1.929834 2.339398 2.425619
-0.789452 1.369290 1.826862 1.917268 2.414283 2.502071
-0.737031 1.173300 1.873028 1.972833 2.455130 2.541243
-0.759015 1.250729 1.781114 1.994631 2.420436 2.554945
-0.749485 1.363939 1.896372 1.993571 2.442257 2.509848
-0.749379 1.214662 1.940660 2.034076 2.450716 2.568302
-0.801242 1.269156 1.870897 1.955986 2.405162 2.473861
-0.823290 1.258951 1.879861 2.069704 2.411773 2.510105
-0.836531 1.273927 1.957305 2.047469 2.490158 2.582295
-0.834116 1.183883 1.886457 1.969193 2.499483 2.604335
-0.876413 1.171153 1.946619 2.030903 2.431350 2.553010
-0.839364 1.056108 1.853641 2.100590 2.392613 2.554339
-0.864173 1.164684 1.835487 1.968845 2.376306 2.516103
-0.932804 1.294569 1.830951 1.901036 2.445265 2.552572
-0.963048 1.356861 1.768829 1.893219 2.479918 2.614673
-1.037066 1.359723 1.820807 1.891047 2.519312 2.605020
-1.060607 1.462340 1.797954 1.939293 2.521868 2.591879
-1.079923 1.504167 1.802208 1.930535 2.465137 2.543195
-1.140112 1.339064 1.813350 1.905307 2.370068 2.530420
-1.151868 1.356167 1.772359 1.883710 2.370014 2.610806
-1.288085 1.638629 1.751055 2.279923 2.555394 2.623279
-1.451442 1.739489 1.916401 2.388700 2.636146 2.702827
-1.591253 1.851544 2.218282 2.385490 2.593754 2.679427
-1.592264 2.016137 2.233799 2.333758 2.544823 2.665169
-1.654199 1.941575 2.250965 2.372366 2.458905 2.599827
-1.703247 2.025498 2.229596 2.337095 2.468575 2.617655
-1.638815 2.005565 2.201946 2.268461 2.499537 2.618409
-1.924675 2.135325 2.458180 2.504168 2.593838 2.625401
-1.803809 2.062572 2.199354 2.289456 2.550039 2.643916
-1.773011 1.976616 2.107571 2.220874 2.444977 2.543841
-1.764952 2.001727 2.214453 2.254705 2.475610 2.579746
-1.678332 1.863913 2.244638 2.343674 2.471126 2.636086
-1.755810 1.860246 2.223719 2.353060 2.498302 2.586676
-1.693433 1.869241 2.283303 2.395805 2.519741 2.583673
-1.704396 1.791207 2.147185 2.336447 2.479029 2.590894
-1.683258 1.862251 2.163335 2.351843 2.520908 2.616034
-1.623219 1.804206 2.222072 2.360296 2.619900 2.699507
-1.657240 1.825612 2.258489 2.347345 2.545732 2.694714
-1.660069 1.860341 2.253569 2.364116 2.564093 2.630731
-1.596899 1.839512 2.218930 2.385793 2.546468 2.625886
-1.622317 1.851201 1.996215 2.377397 2.522071 2.595493
-1.029466 1.254529 1.748991 2.053525 2.445882 2.576112
-0.856689 0.993818 1.569607 2.213756 2.461855 2.547082
-1.016581 1.191900 1.293465 1.778141 2.455802 2.551646
-1.010542 1.228148 1.311431 1.820284 2.531515 2.656752
-0.908278 1.189582 1.285536 1.858600 2.525918 2.619924
-0.871987 1.171922 1.317490 1.826516 2.400744 2.518087
-1.033124 1.188852 1.439697 2.039008 2.572425 2.656103
-0.970197 1.295635 1.402442 2.035038 2.488178 2.549888
-1.088196 1.220650 1.553062 2.133376 2.535702 2.595055
-1.009947 1.389803 1.517057 2.115221 2.474188 2.550693
-0.993372 1.427374 1.539173 1.972396 2.525839 2.583860
-1.048290 1.482084 1.637176 2.161075 2.523169 2.614712
-1.024326 1.562855 1.692237 2.295162 2.594836 2.648573
-0.907692 1.612559 1.746134 2.162536 2.575745 2.616258
-0.890482 1.611128 1.773927 1.970733 2.577746 2.659601
-0.808392 1.597802 1.785959 2.006399 2.565042 2.638957
-0.766474 1.584421 1.835838 1.929741 2.581539 2.641074
-0.769957 1.626769 1.869258 2.029447 2.602778 2.660482
-0.798945 1.531859 1.834894 1.946531 2.628257 2.692621
-0.720628 1.380228 1.817598 1.895348 2.547755 2.607196
-0.717991 1.301269 1.753273 1.880568 2.501113 2.570677
-0.757538 1.197506 1.719315 1.863401 2.467197 2.580754
-0.753702 1.292466 1.691851 1.775796 2.472592 2.583782
-0.814552 1.234200 1.583851 1.688282 2.546255 2.601382
-0.892573 1.259415 1.548665 1.628711 2.465185 2.557477
-0.949846 1.260567 1.429248 1.620283 2.396748 2.457397
-1.035299 1.244100 1.498240 1.643920 2.381366 2.524331
-1.108074 1.337571 1.538192 1.800588 2.513582 2.617693
-1.182535 1.370472 1.561886 1.844157 2.545726 2.614455
-1.215270 1.374402 1.595386 1.940797 2.512277 2.594163
-1.232828 1.356701 1.648355 2.040665 2.518326 2.606889
-1.295532 1.441002 1.626009 2.063594 2.535454 2.607196
-1.317455 1.484169 1.666626 2.107203 2.509460 2.569563
-1.288135 1.404836 1.708442 2.142397 2.478263 2.558149
-1.301178 1.490634 1.688663 2.209739 2.516570 2.582597
-1.388908 1.488602 1.753074 2.249110 2.468447 2.532735
-1.432358 1.501949 1.756043 2.227378 2.540315 2.633816
-1.270629 1.444250 1.697177 2.167736 2.574168 2.667078
-1.377953 1.511825 1.619242 2.070588 2.580573 2.655449
-1.319093 1.437635 1.575159 1.826257 2.568503 2.646941
-1.273340 1.439378 1.614682 1.977816 2.589179 2.642268
-1.364811 1.491437 1.654641 1.914895 2.277580 2.491707
-1.381399 1.482330 1.625703 1.767453 2.292816 2.535410
-1.316122 1.410804 1.574518 1.696495 2.241547 2.544142
-1.249213 1.448411 1.651606 1.812013 2.166941 2.528826
-1.329985 1.430104 1.637785 1.753696 2.144268 2.491734
-1.212008 1.460184 1.663715 1.723968 2.452735 2.654868
-1.154672 1.427992 1.639839 1.703824 2.524782 2.647191
-1.132193 1.276380 1.638189 1.750734 2.360136 2.630237
-1.106796 1.292196 1.563991 1.737151 2.276384 2.673484
-1.009469 1.409199 1.605253 1.755880 2.549809 2.666897
-0.849242 1.424760 1.607336 1.770467 2.593061 2.697570
-0.884126 1.418674 1.690537 1.910365 2.648893 2.753562
-0.835786 1.505326 1.650834 1.839830 2.667508 2.731820
-0.830887 1.418426 1.698221 1.812786 2.546614 2.605179
-0.770144 1.456185 1.735350 1.839787 2.485317 2.539411
-0.741204 1.461201 1.720258 2.039661 2.613149 2.656617
-0.746126 1.436058 1.674916 1.868865 2.616457 2.659599
-0.785082 1.343492 1.675451 1.756554 2.550054 2.611912
-0.745773 1.354824 1.630019 1.938987 2.453600 2.549079
-0.845780 1.469252 1.629079 1.974969 2.499282 2.549783
-0.949421 1.462768 1.572994 2.286043 2.549581 2.602929
-1.025145 1.385363 1.648388 2.192934 2.440628 2.531024
-1.033724 1.436166 1.744094 2.132259 2.544044 2.618903
-1.082839 1.455838 1.597987 2.003093 2.628262 2.736133
-1.021616 1.380799 1.537805 2.007919 2.656179 2.725478
-0.934605 1.338311 1.721281 2.021380 2.452658 2.635942
-0.974987 1.280603 1.740482 1.988643 2.383388 2.588543
-0.963572 1.358626 1.775093 2.077077 2.374408 2.552547
-1.339392 1.606067 1.941038 2.159799 2.446540 2.587306
-1.268637 1.604063 1.940062 2.178915 2.487660 2.597501
-1.129807 1.522621 1.872974 2.075068 2.479707 2.633172
-1.135346 1.422302 1.865991 1.945310 2.523357 2.686142
-1.135540 1.562266 1.768152 1.922013 2.506054 2.736130
-1.173335 1.637622 1.845405 1.974533 2.379511 2.627590
-1.223094 1.477161 1.799506 1.945290 2.603703 2.697773
-1.285652 1.781420 1.972532 2.335252 2.649620 2.719252
-1.516066 1.862470 2.084987 2.386138 2.563370 2.650523
-1.622511 1.800884 2.074682 2.371099 2.494100 2.608952
-1.644218 1.730914 2.235251 2.344625 2.460604 2.621775
-1.646495 1.743836 2.118671 2.334538 2.487649 2.597304
-1.574474 1.666941 2.165682 2.294626 2.463016 2.642929
-1.568529 1.662679 2.068377 2.240071 2.374784 2.534291
-1.501088 1.675567 2.019200 2.253935 2.403957 2.560212
-1.333222 1.481857 1.810385 2.032438 2.235271 2.464023
-1.184189 1.376469 1.743067 2.077177 2.247370 2.436639
-0.860298 1.017970 1.399466 2.031356 2.445832 2.512045
-0.987543 1.187216 1.324668 2.086564 2.440265 2.507859
-0.987539 1.057392 1.400508 2.291033 2.462013 2.534542
-1.072567 1.168456 1.335425 2.281555 2.595283 2.641991
-1.042424 1.219473 1.328751 2.104394 2.481407 2.544847
-1.075840 1.204873 1.370286 2.206558 2.509524 2.557197
-1.075906 1.188083 1.414337 2.320102 2.530914 2.589422
-1.076149 1.267397 1.411982 2.218421 2.452294 2.540946
-1.154549 1.314810 1.500389 2.300970 2.505189 2.569795
-1.170382 1.300375 1.477782 2.201078 2.418226 2.511009
-1.164826 1.290783 1.436432 2.042173 2.434597 2.517154
-1.193857 1.293191 1.527594 2.008805 2.370813 2.473257
-1.263542 1.385669 1.596130 2.048764 2.427787 2.504082
-1.305187 1.421012 1.658876 2.095853 2.429425 2.518576
-1.378304 1.494361 1.710276 2.078040 2.477964 2.559482
-1.333727 1.475263 1.674044 2.039635 2.446712 2.527050
-1.346152 1.468526 1.673673 1.961087 2.462599 2.567158
-1.324261 1.466904 1.747093 2.009440 2.480558 2.571278
-1.306921 1.411049 1.740784 2.032398 2.466338 2.575794
-1.277304 1.408311 1.715677 1.956928 2.505971 2.597300
-1.239174 1.409858 1.635688 1.843138 2.511337 2.592493
-1.262271 1.377900 1.665878 1.785276 2.414923 2.519101
-1.223772 1.378608 1.706935 1.812010 2.472106 2.553503
-1.248275 1.560969 1.688454 2.024421 2.464682 2.532083
-1.551147 1.674831 1.863917 2.242605 2.425666 2.512306
-1.613538 1.736360 1.915832 2.284340 2.505100 2.575495
-1.675654 1.764549 2.013262 2.308596 2.479308 2.570877
-1.676790 1.732192 2.216913 2.350744 2.516807 2.584938
-1.672091 1.768085 2.170300 2.277530 2.411164 2.492525
-1.645851 1.881233 2.216349 2.320633 2.460809 2.564931
-1.714095 1.933206 2.220117 2.327698 2.453033 2.557432
-1.864162 1.965600 2.211890 2.354075 2.451546 2.543697
-1.840509 1.980901 2.141357 2.275924 2.487833 2.607026
-1.281628 1.508538 1.878088 2.153311 2.510390 2.597723
-1.285937 1.558518 1.895925 2.154502 2.510047 2.628884
-1.179704 1.457966 1.805824 2.088695 2.536834 2.648347
-1.213178 1.474144 1.796481 1.886388 2.426441 2.597142
-1.175759 1.566628 1.786803 1.959634 2.443976 2.621808
-1.241280 1.495544 1.772941 1.959431 2.513639 2.611886
-1.252864 1.547349 1.741300 1.873671 2.447277 2.674639
-1.234254 1.437033 1.742154 1.835750 2.372173 2.581494
-1.262397 1.351279 1.710277 1.833486 2.308910 2.583598
-1.330861 1.424104 1.673893 1.802977 2.271847 2.556762
-1.374920 1.473192 1.703358 1.804519 2.374494 2.625833
-1.350424 1.477644 1.741927 1.869579 2.468162 2.637851
-1.299448 1.409270 1.707326 1.828822 2.412618 2.660075
-1.283675 1.413183 1.694008 1.913840 2.235005 2.663358
-1.131349 1.545449 1.738197 1.927132 2.242548 2.529539
-1.310395 1.445321 1.800815 1.941760 2.224181 2.430698
-1.207823 1.407710 1.792289 1.897833 2.278582 2.588793
-1.172078 1.380374 1.769606 1.870709 2.420713 2.665411
-1.050374 1.292916 1.708676 1.815571 2.398301 2.647835
-1.012196 1.352840 1.710467 1.798435 2.501052 2.622110
-0.949688 1.511315 1.802233 2.051775 2.386590 2.543931
-1.239527 1.523312 1.992644 2.175922 2.535838 2.663321
-1.170409 1.423959 1.918088 2.072957 2.371327 2.600694
-1.153282 1.631638 1.943662 2.041389 2.426287 2.527936
-1.130992 1.687340 1.913097 1.982416 2.366644 2.592156
-0.876015 1.539120 1.952815 2.040387 2.354192 2.592474
-0.741027 1.330783 2.010264 2.088976 2.406380 2.512408
-0.692068 1.220984 1.966843 2.053168 2.527609 2.625367
-0.697907 1.406778 2.016010 2.085819 2.573177 2.652342
-0.747161 1.542479 1.982188 2.091091 2.573313 2.614600
-0.759939 1.518111 1.938220 2.162963 2.534355 2.639085
-0.752015 1.445930 2.097743 2.150626 2.479886 2.587138
-0.804190 1.428522 2.012448 2.195806 2.470749 2.577263
-0.757784 1.356544 1.878177 2.232246 2.530996 2.630296
-0.782189 1.251703 1.766911 2.206553 2.564453 2.617695
-0.692136 1.308291 1.593024 1.842927 2.504334 2.652647
-0.779817 1.264995 1.689687 1.803686 2.530498 2.669456
-0.774734 1.199620 1.649586 1.726576 2.437097 2.591528
-0.885025 1.311938 1.646470 1.739192 2.578721 2.671994
-0.949387 1.387109 1.641927 1.762570 2.528769 2.585787
-1.012043 1.455355 1.666729 1.752575 2.434270 2.553516
-1.104075 1.529375 1.682092 1.973044 2.345511 2.511577
-1.423997 1.619409 1.995513 2.298913 2.430779 2.521288
-1.582461 1.832072 2.275101 2.383131 2.482800 2.539316
-1.706366 2.001667 2.300029 2.394812 2.486966 2.586945
-1.532256 1.933761 2.284009 2.422313 2.622936 2.706043
-1.678938 1.889060 2.338973 2.512967 2.632369 2.679498
-1.634405 1.783714 2.124182 2.462997 2.610348 2.691361
-1.618353 1.751021 2.026128 2.418017 2.609402 2.678953
-1.565199 1.794303 1.902067 2.405664 2.629332 2.696870
-1.282138 1.591250 1.852032 2.314230 2.617777 2.722940
-1.220365 1.421679 1.694336 1.881742 2.556796 2.653179
-1.139402 1.299007 1.622371 1.770432 2.543866 2.640704
-1.214491 1.467423 1.628034 1.794008 2.563409 2.691705
-1.059626 1.521805 1.631948 1.865161 2.601036 2.683659
-1.180200 1.536587 1.671861 2.137961 2.587647 2.638393
-1.213651 1.582110 1.709505 2.157513 2.476799 2.574007
-1.248459 1.553050 1.645298 1.897537 2.577761 2.681279
-1.340584 1.601427 1.679985 1.889143 2.647088 2.755132
-1.194554 1.575563 1.697528 1.801365 2.596516 2.752368
-1.152988 1.531378 1.716414 1.812718 2.417149 2.696455
-1.175284 1.565269 1.657415 1.734779 2.517977 2.671209
-1.315878 1.515976 1.775170 2.058078 2.307304 2.449295
-1.247131 1.381271 1.568357 1.857012 2.157278 2.435014
-1.240254 1.383648 1.580575 1.991473 2.303569 2.411055
-1.286797 1.385847 1.730704 2.067540 2.326906 2.473042
-1.204107 1.337886 1.665492 2.038754 2.231416 2.543395
-1.182343 1.312111 1.522260 1.971028 2.237772 2.483629
-1.095429 1.319910 1.465710 2.032595 2.279936 2.523638
-1.152497 1.294508 1.458307 2.032534 2.306031 2.406760
-0.991441 1.274662 1.428222 1.940576 2.399100 2.509374
-0.850157 1.274723 1.453729 1.893527 2.382294 2.477664
-0.936060 1.313211 1.426739 1.888973 2.551745 2.604392
-0.972592 1.328333 1.432833 2.011050 2.573671 2.613672
-0.909400 1.422756 1.494628 2.073945 2.620634 2.662685
-0.828475 1.431701 1.569493 2.054254 2.622115 2.669741
-0.779249 1.375673 1.476635 1.949187 2.558998 2.622137
-0.815710 1.472687 1.650494 2.000905 2.565206 2.611683
-0.822357 1.333508 1.551653 1.864184 2.595847 2.706122
-0.736497 1.259887 1.490815 1.882220 2.494405 2.619982
-0.902240 1.431002 1.520505 1.910794 2.605395 2.678585
-0.900488 1.363048 1.461814 2.009771 2.665876 2.717180
-1.015394 1.361530 1.474854 1.920438 2.637482 2.702570
-0.950918 1.335184 1.440876 1.874351 2.678915 2.746244
-0.965674 1.306906 1.412895 1.727184 2.656317 2.739472
-1.121335 1.291332 1.412980 1.731394 2.624577 2.735999
-1.135486 1.299970 1.448634 1.635793 2.616713 2.687744
-1.120410 1.248201 1.383680 1.579760 2.397167 2.585237
-1.113415 1.294499 1.482373 1.602789 2.394835 2.634809
-1.241746 1.318174 1.473167 1.577503 2.426003 2.649775
-1.184376 1.272893 1.497747 1.608053 2.144455 2.537267
-1.283135 1.377322 1.543041 1.645177 2.105790 2.490904
-1.138008 1.380756 1.560480 1.640979 2.271006 2.625523
-1.243884 1.351538 1.603070 1.739791 2.038080 2.447512
-1.267258 1.509957 1.641649 1.831984 2.331327 2.472826
-1.276365 1.476401 1.625021 1.930342 2.319377 2.524369
-1.222679 1.559407 1.669982 1.805473 2.326911 2.580278
-1.265218 1.503892 1.830979 2.091536 2.396722 2.569088
-1.256047 1.528877 1.853033 2.106171 2.365139 2.503280
-1.236501 1.479118 1.728297 2.041463 2.528558 2.612900
-1.220644 1.605193 1.713770 1.950925 2.597639 2.649495
-1.255546 1.591871 1.706750 2.062713 2.561381 2.626901
-1.307080 1.580016 1.653547 1.941293 2.552727 2.643706
-1.310968 1.512803 1.656527 1.839190 2.592097 2.677706
-1.188596 1.316082 1.579370 1.690772 2.438500 2.641881
-1.114671 1.235994 1.591973 1.749192 2.359438 2.545213
-1.080067 1.277132 1.727997 2.041411 2.337068 2.549786
-1.032222 1.250210 1.680999 1.998340 2.318533 2.502200
-1.064719 1.159182 1.666731 2.019294 2.256570 2.573467
-1.026313 1.146367 1.672929 2.054063 2.433228 2.615716
-0.942929 1.092789 1.613522 2.077784 2.365142 2.499737
-0.980250 1.254777 1.492003 1.801193 2.445325 2.575711
-0.957395 1.251868 1.378337 1.744574 2.502966 2.665866
-0.840336 1.267995 1.397728 1.827984 2.555867 2.651285
-1.009902 1.175808 1.277770 2.048361 2.637904 2.700904
-0.883840 1.026780 1.146692 1.893681 2.518692 2.610564
-0.997171 1.138289 1.246408 1.837527 2.549820 2.642693
-0.992125 1.178874 1.282272 1.974399 2.559112 2.612968
-1.067589 1.255803 1.359021 1.963939 2.541420 2.596308
-1.086327 1.329068 1.432326 1.928840 2.528332 2.598239
-1.100351 1.345579 1.469529 1.942358 2.469723 2.561680
-1.101019 1.374382 1.561144 1.942560 2.484288 2.552996
-1.177497 1.455165 1.571485 1.943496 2.500309 2.550902
-1.260768 1.477903 1.601611 2.024022 2.487425 2.554237
-1.216439 1.470082 1.639601 1.957212 2.523832 2.588189
-1.257980 1.407199 1.651434 1.910722 2.464200 2.620868
-1.162091 1.436543 1.682166 1.896924 2.447302 2.677069
-1.250215 1.484632 1.653870 1.930473 2.493894 2.633436
-1.237977 1.513389 1.648781 1.880344 2.504094 2.581491
-1.223199 1.412456 1.634083 1.797183 2.451210 2.620618
-1.258745 1.358397 1.627717 1.726099 2.428287 2.621329
-1.234919 1.345606 1.552151 1.708675 2.385742 2.606052
-1.186417 1.341808 1.636911 1.754679 2.429716 2.544394
-1.216260 1.305888 1.632777 1.755770 2.320806 2.583785
-1.165343 1.284152 1.560527 1.682036 2.243217 2.494673
-1.085859 1.215111 1.590602 1.715333 2.231633 2.527227
-1.091652 1.384156 1.655159 1.716563 2.302785 2.535552
-1.060328 1.239077 1.627213 1.737571 2.420162 2.599147
-1.090079 1.394777 1.682485 1.799904 2.331813 2.532862
-1.169038 1.568116 1.785725 2.031553 2.372207 2.497865
-1.241903 1.662080 1.822491 2.169543 2.424542 2.525186
-1.040287 1.690414 1.853098 2.038593 2.472015 2.535969
-0.974879 1.689063 1.850137 2.151312 2.507415 2.562538
-0.879683 1.743838 1.968060 2.161147 2.463916 2.545849
-0.790116 1.794412 2.037297 2.159739 2.508403 2.564883
-0.793374 1.796169 2.060524 2.331075 2.591299 2.648578
-0.859332 1.800464 2.025451 2.200641 2.534316 2.611320
-0.825206 1.895126 2.063579 2.264528 2.514030 2.610797
-0.974068 1.904781 2.002639 2.315848 2.539666 2.595157
-0.961311 1.821283 2.015215 2.274545 2.600786 2.653365
-0.971040 1.737011 1.914953 2.243896 2.572362 2.612602
-0.999552 1.817902 1.953097 2.178591 2.574331 2.626275
-0.977300 1.756036 1.929137 2.135346 2.424209 2.556085
-1.065543 1.747638 1.899169 2.309745 2.587388 2.630589
-1.077057 1.655717 1.868334 2.238603 2.508913 2.571841
-1.077829 1.716423 1.791462 2.266223 2.615485 2.654046
-1.276021 1.713383 1.788825 2.101442 2.625616 2.679590
-1.263173 1.699086 1.776931 2.035107 2.610346 2.653421
-1.297137 1.667668 1.744010 2.030119 2.608062 2.678066
-1.262373 1.626459 1.781159 2.026178 2.636261 2.699179
-1.318031 1.657767 1.763578 1.939043 2.575450 2.705613
-0.980669 1.555891 1.722977 1.978553 2.568958 2.638420
-0.840013 1.463397 1.772781 2.164864 2.566894 2.666228
-0.832158 1.505750 1.937891 2.233974 2.630131 2.694884
-0.745541 1.530097 2.060727 2.162996 2.619130 2.692130
-0.832050 1.597985 2.127678 2.196662 2.528870 2.619304
-0.820544 1.616482 2.044842 2.133557 2.587661 2.668155
-0.789348 1.638569 1.996032 2.212800 2.572934 2.615430
-0.806795 1.742530 2.043915 2.183841 2.603407 2.660269
-0.843597 1.761377 1.998823 2.132969 2.596500 2.673163
-0.927714 1.759399 1.987169 2.201990 2.591677 2.650810
-1.070504 1.767115 1.978295 2.227191 2.642696 2.686380
-1.022852 1.856828 1.989822 2.217218 2.480936 2.574687
-0.886409 1.742690 1.863071 2.054904 2.542328 2.627054
-0.996501 1.553639 1.808061 1.948514 2.516726 2.605745
-1.218221 1.525015 1.878023 2.107205 2.423952 2.578894
-1.274705 1.491779 1.906237 2.101242 2.455724 2.563566
-1.319477 1.587082 1.879825 2.240443 2.439462 2.547992
-1.474513 1.699004 1.929257 2.228217 2.451873 2.563132
-1.545274 1.722709 1.892103 2.169162 2.520241 2.602958
-1.546160 1.668894 1.961486 2.212079 2.505999 2.621266
-1.535625 1.699287 2.016356 2.250824 2.550093 2.645619
-1.583411 1.687746 2.051949 2.332633 2.491721 2.598036
-1.500933 1.594052 1.929231 2.259850 2.422622 2.547761
-1.464918 1.614783 1.881701 2.216729 2.528952 2.623217
-1.406726 1.605026 1.805977 2.222725 2.509009 2.587841
-1.106418 1.527781 1.730182 2.045916 2.549464 2.637497
-1.008151 1.439718 1.665472 1.941372 2.652442 2.751095
-0.971347 1.402084 1.708896 1.953274 2.613325 2.684989
-0.946352 1.501044 1.672151 1.975870 2.527905 2.585573
-0.909229 1.453576 1.713898 2.065638 2.529315 2.613161
-0.975079 1.523288 1.839559 2.138553 2.498690 2.583725
-0.899524 1.552407 1.831637 2.068567 2.544880 2.611180
-0.805175 1.462327 1.860536 2.101344 2.570440 2.654850
-0.859011 1.514531 1.892400 2.012520 2.579679 2.648521
-0.763528 1.522433 1.902539 2.018517 2.556446 2.609582
-0.814387 1.494849 1.941715 2.077981 2.540329 2.612839
-0.853805 1.401871 1.942985 2.088086 2.488394 2.578614
-0.782036 1.348553 1.935300 2.025076 2.516816 2.598046
-0.754386 1.384949 1.900243 1.999656 2.600374 2.663763
-0.746921 1.421143 1.934567 2.038908 2.553273 2.612298
-0.731911 1.450761 1.924508 2.032744 2.497904 2.556491
-0.706741 1.543731 1.876596 1.992525 2.510176 2.565960
-0.852548 1.549952 1.899169 2.226497 2.522787 2.583939
-0.885718 1.656999 1.865791 2.162889 2.467388 2.553769
-0.951271 1.641721 1.813995 2.153059 2.427099 2.499612
-0.928485 1.502784 1.809440 2.224767 2.472400 2.553921
-0.816616 1.391098 1.665580 2.176141 2.510722 2.582819
-0.915934 1.390936 1.767514 2.169548 2.471665 2.652526
-1.115341 1.362311 1.722592 2.033033 2.406363 2.601875
-1.138664 1.252976 1.684517 1.937366 2.384311 2.623900
-1.084318 1.211953 1.633639 1.889936 2.413095 2.626228
-1.126224 1.344921 1.648605 2.071123 2.484189 2.605656
-1.123905 1.461556 1.845099 2.172457 2.462662 2.605139
-1.132557 1.468636 1.740223 2.184934 2.467938 2.580103
-1.148248 1.506173 1.676602 2.049290 2.446774 2.565419
-0.999544 1.404698 1.641769 1.863324 2.523843 2.592114
-0.932167 1.395984 1.709428 1.845739 2.524792 2.599616
-0.870085 1.476327 1.721511 1.897091 2.490256 2.593759
-0.891107 1.429106 1.789728 1.958425 2.519104 2.604987
-0.855550 1.421268 1.900935 2.011013 2.546617 2.609760
-0.895038 1.482579 1.873572 1.974828 2.519429 2.584450
-0.809092 1.486499 1.902272 2.000876 2.518374 2.597261
-0.808211 1.460169 1.881579 1.961398 2.468386 2.616332
-0.774237 1.471857 1.901217 2.013761 2.564870 2.665691
-0.800018 1.576948 1.938176 2.043718 2.494383 2.630097
-0.804705 1.570759 1.889356 1.975489 2.447653 2.555191
-0.840709 1.603377 1.827077 2.026318 2.442892 2.492424
-0.887288 1.536144 1.781616 1.952198 2.500811 2.576512
-0.847527 1.504701 1.792948 1.891589 2.578888 2.637316
-0.959025 1.533821 1.821486 1.979739 2.463750 2.544302
-1.036319 1.640786 1.886024 1.962887 2.358662 2.577756
-0.981142 1.486738 1.733096 1.878277 2.537973 2.610473
-1.046486 1.438515 1.740840 1.850012 2.590883 2.684137
-1.103404 1.489782 1.738241 1.817496 2.588368 2.701052
-1.176925 1.473684 1.732853 1.823270 2.524527 2.733540
-1.173320 1.438383 1.696555 1.792536 2.580785 2.665770
-1.134955 1.421862 1.604070 1.756135 2.617948 2.706644
-1.136007 1.384178 1.699100 1.855319 2.591013 2.683215
-1.201710 1.421935 1.737864 2.011199 2.540959 2.681093
-1.227450 1.624461 2.125226 2.340556 2.593435 2.671453
-1.265133 1.765689 2.131338 2.391774 2.613959 2.699849
-1.342282 1.581411 1.979244 2.297759 2.520391 2.602258
-1.449013 1.725546 2.176279 2.354739 2.538758 2.627319
-1.418726 1.898681 2.206330 2.275600 2.488746 2.586794
-1.555706 1.837600 2.165743 2.346188 2.530178 2.628757
-1.444437 1.790050 1.911014 2.301915 2.468862 2.540557
-1.378052 1.668499 1.845265 2.324889 2.537708 2.601471
-1.394741 1.682710 1.817346 2.075533 2.512120 2.566889
-1.297199 1.655884 1.825405 2.062105 2.513307 2.577371
-1.280659 1.669901 1.824567 2.168209 2.528166 2.601986
-1.306896 1.600808 1.767971 2.095291 2.509869 2.606002
-1.257678 1.559755 1.787804 2.076895 2.540388 2.627179
-1.196849 1.597550 1.817421 2.152662 2.580796 2.651246
-1.235935 1.676643 1.942307 2.326482 2.561542 2.645593
-1.189058 1.818895 2.081496 2.366454 2.608018 2.672086
-1.427589 1.885421 2.264907 2.424220 2.571371 2.651155
-1.714473 1.937868 2.390009 2.457149 2.552016 2.601930
-1.874136 2.073506 2.370468 2.511263 2.709177 2.749495
-1.647818 1.987798 2.281909 2.412099 2.604693 2.674821
-1.596366 1.881529 2.193995 2.380524 2.511918 2.584564
-1.555508 1.775218 2.064094 2.325699 2.512934 2.599262
-1.330054 1.712961 1.917624 2.285900 2.466591 2.579279
-0.990071 1.410874 1.632331 1.965889 2.466882 2.580417
-0.925150 1.299025 1.551401 1.897486 2.498481 2.645212
-0.968080 1.367127 1.520360 1.988159 2.313473 2.546943
-0.974374 1.283811 1.474810 2.078302 2.331089 2.455153
-1.000624 1.299150 1.415675 1.955760 2.261550 2.354258
-0.964045 1.136490 1.305931 1.936406 2.197537 2.299418
-1.013087 1.201143 1.372664 1.820179 2.063576 2.210659
-1.086478 1.216705 1.476655 1.604039 1.855963 2.324503
-1.090160 1.201207 1.460778 1.562225 2.016093 2.458980
-1.133754 1.257469 1.407186 1.787681 2.289532 2.530854
-1.134831 1.341221 1.636293 1.813775 2.219453 2.584652
-0.952747 1.300930 1.616891 1.751014 2.352113 2.547879
-1.078704 1.490043 1.571579 1.800532 2.468175 2.650436
-1.239045 1.333032 1.551379 1.707824 2.242922 2.604251
-1.176517 1.299114 1.588881 1.714081 2.128856 2.533523
-1.135831 1.253056 1.538412 1.634480 2.258093 2.593874
-1.092382 1.253236 1.541772 1.679875 2.423197 2.617584
-1.142663 1.256402 1.528284 1.629676 2.391580 2.589689
-1.172793 1.281248 1.479204 1.608878 2.335938 2.593681
-1.146782 1.251953 1.432916 1.553285 2.238941 2.534180
-1.109946 1.231415 1.412105 1.516055 2.308569 2.599903
-1.120273 1.235535 1.425736 1.509519 2.435529 2.643814
-1.085869 1.189296 1.392718 1.494347 2.129342 2.508989
-1.020500 1.173144 1.440965 1.574421 2.335855 2.524051
-1.040551 1.174338 1.525717 1.693110 2.493748 2.632352
-1.034516 1.205262 1.365087 1.513000 2.471788 2.578008
-1.079383 1.204002 1.332428 1.456604 2.502131 2.665633
-1.088863 1.236949 1.357003 1.564945 2.602020 2.707576
-1.106792 1.262402 1.367273 1.823952 2.598579 2.676300
-1.085013 1.233527 1.311463 1.730333 2.560087 2.690320
-1.069205 1.180224 1.343020 1.474834 2.268046 2.544311
-1.039392 1.375617 1.721445 2.038018 2.463998 2.600812
-1.267853 1.384109 1.659902 1.934021 2.207761 2.424577
-1.225276 1.316621 1.678147 1.819230 2.165345 2.498548
-1.114141 1.283029 1.655518 1.879671 2.352472 2.553537
-1.094762 1.370017 1.799126 2.082377 2.469494 2.578819
-1.041250 1.472757 1.748735 2.047588 2.511699 2.589828
-1.071665 1.456546 1.700524 1.927317 2.441484 2.607003
-0.929006 1.487241 1.669550 1.885619 2.544274 2.628318
-0.844366 1.339712 1.812456 2.300208 2.566012 2.631255
-0.761441 1.279951 1.670446 2.006350 2.526824 2.607557
-0.716643 1.374843 1.843436 2.126958 2.552993 2.613146
-0.749967 1.598458 1.883266 2.050443 2.579184 2.614111
-0.759376 1.596383 1.929103 1.984550 2.566734 2.654207
-0.724977 1.682905 1.888292 2.034796 2.503861 2.565502
-0.812327 1.669865 1.961771 2.102146 2.538781 2.598559
-0.767334 1.594629 1.984319 2.133419 2.501689 2.557813
-0.760230 1.650647 1.928366 2.094047 2.565241 2.596082
-0.766762 1.648062 1.858552 2.078593 2.587079 2.608213
-0.860938 1.629253 1.824855 2.067350 2.563373 2.603209
-0.960953 1.583632 1.752206 2.078444 2.555531 2.628507
-1.007927 1.548004 1.734955 2.185660 2.489350 2.551445
-1.040401 1.471117 1.643519 2.051558 2.508524 2.579168
-1.096025 1.457427 1.604009 1.926200 2.482033 2.552204
-1.130428 1.431534 1.592806 2.014740 2.510652 2.567779
-1.197898 1.465481 1.622929 2.075950 2.507052 2.582750
-1.258831 1.504797 1.659109 1.970653 2.595750 2.685651
-1.315451 1.467446 1.705718 1.898634 2.602572 2.704978
-1.272475 1.431894 1.712848 1.940258 2.650379 2.717166
-1.278865 1.528652 1.796202 1.995202 2.501761 2.587606
-1.458616 1.693943 2.067903 2.264838 2.506857 2.623939
-1.718797 1.909611 2.147601 2.354174 2.485581 2.591269
-1.813873 1.875483 2.097637 2.329683 2.497798 2.596247
-1.744286 1.859449 2.043169 2.284589 2.430897 2.538572
-1.514180 1.808296 1.933791 2.234651 2.462232 2.546237
-1.489264 1.781194 1.908004 2.144484 2.418589 2.513858
-1.434785 1.679793 1.817348 2.105365 2.431372 2.528241
-1.469581 1.589507 1.813510 2.213129 2.440502 2.520511
-1.496287 1.640049 1.893865 2.298621 2.484705 2.576207
-1.333417 1.584728 1.893019 2.121814 2.525345 2.632617
-1.518722 1.735840 1.956529 2.176426 2.465338 2.572342
-1.520953 1.742556 2.010582 2.133578 2.447458 2.566704
-1.458119 1.692227 2.001920 2.120543 2.431042 2.565112
-1.526915 1.662389 2.025135 2.125056 2.537873 2.626810
-1.498303 1.644212 1.960732 2.103288 2.440309 2.572412
-1.415476 1.548286 1.770800 2.099931 2.450265 2.599463
-1.367188 1.460632 1.739482 2.074030 2.551953 2.639997
+++ /dev/null
- 950
-1050
-1150
-1250
-1350
-1450
-1550
-1650
-1750
-1850
-1950
-2050
-2150
-2250
-2350
-2450
-
-
+++ /dev/null
-1100
-1200
-1300
-1400
-1500
-1600
-1700
-1800
-1900
-2000
-2100
-2200
-2300
-2400
-2500
-2600
-
-
+++ /dev/null
-1500
-1600
-1700
-1800
-1900
-2000
-2100
-2200
-2300
-2400
-2500
-2600
-2700
-2800
-2900
-3000
-
-
+++ /dev/null
-2300
-2400
-2500
-2600
-2700
-2800
-2900
-3000
-
-
+++ /dev/null
-2500
-2600
-2700
-2800
-2900
-3000
-3100
-3200
-
-
+++ /dev/null
-0.263308 0.108769 0.321376
-0.258448 0.055984 0.230859
-0.266067 0.060719 0.217388
-0.280055 0.057994 0.244228
-0.266912 0.064695 0.265145
-0.271651 0.079610 0.259575
-0.226822 0.156621 0.158998
-0.156949 0.052659 0.212653
-0.166041 0.209329 0.265886
-0.308633 0.053423 0.276948
-0.332112 0.035457 0.286972
-0.339533 0.040123 0.272290
-0.330792 0.023602 0.274813
-0.316456 0.037932 0.249650
-0.287286 0.046071 0.242200
-0.261514 0.049979 0.284344
-0.214376 0.103675 0.338804
-0.188651 0.116868 0.328440
-0.177177 0.072134 0.154176
-0.199766 0.183234 0.706565
-0.350628 0.229826 0.529061
-0.297560 0.045946 0.288017
-0.314602 0.041640 0.200681
-0.348282 0.038714 0.240448
-0.381632 0.043026 0.229469
-0.401854 0.029415 0.202430
-0.408573 0.044563 0.177371
-0.424312 0.067150 0.184192
-0.428423 0.056620 0.165082
-0.443482 0.038789 0.168832
-0.432034 0.046019 0.195869
-0.472514 0.052971 0.175566
-0.445147 0.060539 0.186875
-0.447305 0.043459 0.217896
-0.418837 0.064057 0.224309
-0.394427 0.072473 0.216686
-0.372086 0.031878 0.245392
-0.335537 0.047914 0.232315
-0.307720 0.076985 0.263440
-0.212588 0.199799 0.241274
-0.177978 0.061936 0.419219
-0.184726 0.071514 0.295235
-0.179928 0.120561 0.197113
-0.194093 0.091120 0.307566
-0.238704 0.088264 0.256089
-0.256704 0.056376 0.272029
-0.245826 0.056285 0.221666
-0.252157 0.069875 0.209436
-0.293844 0.058822 0.205688
-0.333145 0.032022 0.198412
-0.374122 0.058501 0.198354
-0.388622 0.055018 0.174356
-0.402915 0.069231 0.171417
-0.409007 0.055048 0.195699
-0.393180 0.068521 0.192734
-0.378148 0.042573 0.211319
-0.364531 0.032711 0.200555
-0.346684 0.053755 0.199507
-0.303076 0.088318 0.231307
-0.308105 0.120302 0.271168
-0.275060 0.183236 0.280609
-0.191607 0.254478 0.333707
-0.415869 0.157513 0.330550
-0.466958 0.126641 0.345873
-0.393315 0.137590 0.278630
-0.367297 0.215695 0.295962
-0.209423 0.343791 0.353190
-0.239247 0.069127 0.351070
-0.219601 0.067725 0.316134
-0.183085 0.108910 0.288046
-0.141405 0.106410 0.374917
-0.340773 0.180383 0.280306
-0.324313 0.206337 0.392025
-0.377497 0.310052 0.251511
-0.369942 0.206976 0.403513
-0.391822 0.165248 0.458238
-0.402392 0.132235 0.391573
-0.363609 0.109018 0.385179
-0.393092 0.150649 0.690282
-0.248424 0.072260 0.403322
-0.258842 0.062838 0.331583
-0.277543 0.023397 0.334487
-0.259767 0.019332 0.283729
-0.277333 0.022787 0.286736
-0.278562 0.034487 0.253401
-0.294439 0.029548 0.223983
-0.306420 0.021466 0.246669
-0.311799 0.029621 0.232167
-0.314573 0.026307 0.211228
-0.322046 0.036979 0.185969
-0.340920 0.051908 0.181885
-0.378651 0.100615 0.150541
-0.362534 0.107177 0.127000
-0.366188 0.118540 0.096115
-0.335906 0.123585 0.100436
-0.289660 0.136844 0.121618
-0.234449 0.115458 0.142944
-0.234687 0.112186 0.213379
-0.218786 0.097113 0.246862
-0.230751 0.090415 0.225856
-0.249914 0.071568 0.228974
-0.239316 0.089091 0.205158
-0.235823 0.092666 0.179934
-0.260464 0.077785 0.193877
-0.245534 0.073180 0.169632
-0.285464 0.081401 0.206102
-0.272122 0.072806 0.177335
-0.256928 0.066768 0.151148
-0.259615 0.074334 0.119038
-0.285004 0.089415 0.117455
-0.326626 0.085390 0.097219
-0.322959 0.072295 0.114366
-0.342931 0.060610 0.112868
-0.349890 0.057216 0.138586
-0.347363 0.058881 0.164623
-0.358032 0.064472 0.175272
-0.357807 0.072462 0.156002
-0.336895 0.066119 0.134206
-0.337276 0.073707 0.151129
-0.326144 0.057722 0.152109
-0.287242 0.055461 0.172280
-0.233531 0.070892 0.220511
-0.247128 0.049358 0.274502
-0.224586 0.046013 0.357086
-0.229675 0.045704 0.405370
-0.272311 0.072851 0.349441
-0.262378 0.048277 0.301490
-0.272410 0.052304 0.234698
-0.296903 0.047644 0.225221
-0.308756 0.052127 0.222936
-0.336122 0.044504 0.193011
-0.365030 0.064659 0.137103
-0.372444 0.036236 0.135129
-0.379957 0.052989 0.104509
-0.395033 0.063805 0.099117
-0.395331 0.016167 0.079401
-0.361374 0.077860 0.067214
-0.366584 0.051942 0.030922
-0.417962 0.076156 0.084209
-0.376593 0.111196 0.068356
-0.321411 0.091882 0.063007
-0.335365 0.070341 0.082301
-0.348707 0.075437 0.099469
-0.292758 0.061200 0.121062
-0.277998 0.061337 0.145208
-0.272000 0.072048 0.230783
-0.206511 0.121757 0.280188
-0.162259 0.031322 0.393199
-0.200906 0.088613 0.124277
-0.184134 0.084894 0.197393
-0.290246 0.077754 0.223919
-0.263962 0.059362 0.091101
-0.317773 0.055238 0.129435
-0.356413 0.042508 0.107483
-0.365057 0.023078 0.085620
-0.411914 0.048078 0.093016
-0.419049 0.030016 0.101357
-0.436160 0.024666 0.066348
-0.436704 0.046967 0.092223
-0.494088 0.068777 0.102742
-0.470076 0.075909 0.074128
-0.451110 0.088014 0.089431
-0.487849 0.092611 0.051933
-0.533716 0.041322 0.035398
-0.457297 0.061196 0.094392
-0.434718 0.062690 0.099115
-0.432830 0.099336 0.064658
-0.445522 0.032508 0.029007
-0.435059 0.064532 0.071763
-0.400424 0.095239 0.052280
-0.394880 0.061922 0.073728
-0.341705 0.050045 0.060238
-0.382169 0.078170 0.085591
-0.375733 0.095367 0.086298
-0.367753 0.093088 0.107387
-0.355679 0.126981 0.119866
-0.183195 0.178369 0.154227
-0.215939 0.281661 0.137611
-0.255382 0.232429 0.090575
-0.294261 0.198828 0.092855
-0.358379 0.158423 0.138468
-0.380219 0.176473 0.110948
-0.305047 0.161007 0.139954
-0.262435 0.236041 0.144567
-0.354204 0.222414 0.107065
-0.345190 0.184018 0.124352
-0.338177 0.204525 0.067254
-0.305092 0.238787 0.094788
-0.351980 0.224928 0.156944
-0.345016 0.185595 0.192659
-0.337844 0.184025 0.160326
-0.359544 0.217341 0.327157
-0.357648 0.230240 0.366907
-0.395642 0.165926 0.261342
-0.343546 0.156618 0.223511
-0.361635 0.096729 0.184236
-0.415440 0.076743 0.154942
-0.431066 0.076513 0.121105
-0.451174 0.082936 0.112437
-0.495682 0.125322 0.083250
-0.457920 0.105206 0.069372
-0.428288 0.096431 0.099719
-0.402112 0.089533 0.102279
-0.374406 0.069315 0.151993
-0.341303 0.072495 0.181235
-0.288181 0.130601 0.149994
-0.437823 0.194847 0.236998
-0.517891 0.162410 0.219232
-0.458004 0.239400 0.097958
-0.500390 0.177654 0.095729
-0.362675 0.278449 0.190598
-0.273868 0.085220 0.143261
-0.337997 0.064583 0.239703
-0.368143 0.045688 0.271347
-0.379949 0.029454 0.196794
-0.353352 0.028491 0.129485
-0.352112 0.017867 0.185794
-0.346936 0.025652 0.201147
-0.313751 0.022409 0.193629
-0.310985 0.028334 0.172877
-0.224772 0.055169 0.272269
-0.241855 0.030040 0.280276
-0.228564 0.021920 0.257200
-0.227718 0.054195 0.234162
-0.238926 0.054818 0.264076
-0.237314 0.075502 0.320709
-0.270880 0.085558 0.331728
-0.256455 0.080580 0.308559
-0.287309 0.097558 0.267753
-0.290763 0.080224 0.284406
-0.283022 0.068509 0.295506
-0.275270 0.069930 0.316990
-0.303843 0.092797 0.344720
-0.295250 0.075062 0.317300
-0.304161 0.067487 0.286738
-0.324174 0.057767 0.264031
-0.327890 0.076403 0.220917
-0.357965 0.072263 0.193322
-0.369869 0.059126 0.176957
-0.380683 0.051077 0.189741
-0.377526 0.045779 0.169338
-0.362044 0.051634 0.203021
-0.349094 0.041532 0.208466
-0.350344 0.021300 0.239499
-0.325966 0.026791 0.230178
-0.322013 0.042984 0.214929
-0.290199 0.049255 0.255248
-0.268860 0.057260 0.292111
-0.254110 0.065897 0.262323
-0.240555 0.081414 0.242131
-0.214107 0.099448 0.291511
-0.227603 0.116971 0.293158
-0.242687 0.099576 0.273347
-0.212057 0.080928 0.206493
-0.216818 0.054102 0.208481
-0.244560 0.059543 0.241185
-0.244893 0.055478 0.253047
-0.252424 0.044367 0.250846
-0.232805 0.046411 0.221492
-0.259503 0.030997 0.257981
-0.258163 0.036285 0.290086
-0.255400 0.060582 0.318764
-0.231850 0.078839 0.288307
-0.236986 0.070470 0.304299
-0.213303 0.073593 0.296093
-0.205272 0.040867 0.334217
-0.186676 0.036373 0.251392
-0.217783 0.043270 0.241924
-0.214511 0.052788 0.255946
-0.208572 0.053861 0.286926
-0.242888 0.106360 0.347276
-0.288960 0.124946 0.201239
-0.342775 0.093960 0.144984
-0.377197 0.085376 0.129922
-0.412166 0.088434 0.132108
-0.390249 0.076679 0.114031
-0.383989 0.062449 0.122055
-0.387523 0.079554 0.156435
-0.379580 0.077513 0.179594
-0.314430 0.087760 0.175421
-0.294579 0.101436 0.212711
-0.307017 0.089327 0.197301
-0.305232 0.075488 0.208874
-0.313937 0.065084 0.223413
-0.318828 0.066585 0.241867
-0.319064 0.044985 0.234334
-0.327293 0.054936 0.224270
-0.313956 0.059037 0.208250
-0.320067 0.067497 0.178744
-0.325844 0.051785 0.249839
-0.291419 0.140846 0.176356
-0.304736 0.257499 0.321206
-0.412538 0.193653 0.527310
-0.464326 0.177155 0.484639
-0.388370 0.247578 0.270502
-0.309708 0.243245 0.219685
-0.267637 0.120670 0.182524
-0.333329 0.064619 0.195862
-0.337853 0.035063 0.182235
-0.363054 0.041039 0.161560
-0.346506 0.045356 0.166242
-0.343175 0.032640 0.168740
-0.329834 0.040738 0.160952
-0.327688 0.025263 0.170543
-0.337286 0.032068 0.148672
-0.352876 0.027518 0.154928
-0.355731 0.040489 0.143599
-0.360021 0.052552 0.125346
-0.379432 0.019637 0.116855
-0.389556 0.033257 0.172091
-0.388615 0.005982 0.167184
-0.380871 0.031560 0.161735
-0.370428 0.034266 0.174805
-0.364127 0.028565 0.187409
-0.354946 0.032953 0.173018
-0.355197 0.019611 0.169606
-0.317361 0.028988 0.147085
-0.272330 0.043511 0.120042
-0.266965 0.057786 0.178702
-0.218195 0.094896 0.158774
-0.210802 0.102337 0.189513
-0.233979 0.076536 0.270353
-0.202083 0.169732 0.380558
-0.239441 0.172991 0.265931
-0.276190 0.226470 0.297090
-0.261790 0.365551 0.166357
-0.291971 0.099794 0.304947
-0.299131 0.063916 0.222310
-0.286582 0.041561 0.230600
-0.291056 0.054960 0.304060
-0.275948 0.057784 0.330696
-0.309766 0.028970 0.340314
-0.294102 0.043690 0.317927
-0.309171 0.030830 0.307374
-0.307411 0.020232 0.279361
-0.330913 0.034844 0.243337
-0.332192 0.027616 0.212354
-0.350338 0.039211 0.192995
-0.354502 0.055994 0.189121
-0.341296 0.073283 0.165587
-0.313181 0.094281 0.118029
-0.258194 0.134394 0.161487
-0.211766 0.110672 0.388399
-0.180619 0.089602 0.393854
-0.207652 0.057423 0.402186
-0.248737 0.121119 0.265945
-0.257647 0.145656 0.128647
-0.273116 0.146530 0.091939
-0.258193 0.186626 0.065391
-0.306617 0.177781 0.064168
-0.347651 0.163069 0.074409
-0.357362 0.133103 0.066344
-0.284876 0.117297 0.059904
-0.329676 0.124514 0.067178
-0.347508 0.100037 0.082550
-0.223342 0.163723 0.106806
-0.242615 0.106352 0.107873
-0.278081 0.104596 0.093439
-0.308805 0.106582 0.092192
-0.299730 0.076828 0.096766
-0.240110 0.112476 0.067117
-0.231410 0.073181 0.088404
-0.187246 0.100727 0.078664
-0.193716 0.126844 0.159078
-0.094366 0.454024 0.291647
-0.440203 0.228612 0.310365
-0.456753 0.186484 0.299839
-0.308520 0.205526 0.313406
-0.228109 0.069024 0.190235
-0.251018 0.045216 0.163280
-0.273421 0.051226 0.164458
-0.293630 0.030524 0.175355
-0.298281 0.027483 0.155763
-0.301235 0.032609 0.127618
-0.295114 0.036459 0.089043
-0.321284 0.052688 0.103598
-0.323611 0.031672 0.118877
-0.338816 0.045778 0.089024
-0.310812 0.060414 0.075229
-0.277050 0.068429 0.061631
-0.331845 0.057911 0.166403
-0.357599 0.078369 0.229133
-0.267510 0.109542 0.134427
-0.288685 0.206571 0.249532
-0.359999 0.229179 0.199289
-0.400078 0.178102 0.233727
-0.416741 0.100494 0.304150
-0.427570 0.154323 0.369992
-0.256414 0.275755 0.244236
-0.175186 0.345607 0.170933
-0.324895 0.207437 0.260709
-0.314928 0.217055 0.179225
-0.375454 0.184067 0.158251
-0.461676 0.155360 0.119282
-0.421915 0.134009 0.232978
-0.373661 0.177682 0.207681
-0.135194 0.242891 0.321398
-0.321335 0.077009 0.197895
-0.338990 0.031707 0.225496
-0.324230 0.087363 0.236806
-0.270364 0.162874 0.154703
-0.241859 0.198105 0.177328
-0.257345 0.254782 0.195962
-0.199872 0.236295 0.186694
-0.245869 0.190731 0.141457
-0.335308 0.137010 0.136606
-0.408226 0.106606 0.149159
-0.428609 0.091994 0.166467
-0.472127 0.089046 0.165746
-0.498132 0.086762 0.208918
-0.481551 0.029402 0.264176
-0.482803 0.039294 0.214899
-0.446093 0.026027 0.128251
-0.407029 0.046922 0.066767
-0.365305 0.060238 0.090360
-0.383768 0.048819 0.140115
-0.370504 0.054257 0.143952
-0.358656 0.050846 0.152415
-0.343721 0.051667 0.150554
-0.352689 0.037849 0.181895
-0.387896 0.023860 0.226017
-0.385152 0.026671 0.273998
-0.389716 0.042722 0.253226
-0.390426 0.060857 0.236081
-0.391309 0.070621 0.271022
-0.365299 0.052628 0.227580
-0.349302 0.056899 0.217929
-0.334019 0.044267 0.204909
-0.322675 0.052532 0.195847
-0.331578 0.059559 0.211188
-0.337346 0.044211 0.217457
-0.349988 0.042267 0.223684
-0.349544 0.052704 0.234279
-0.362448 0.055041 0.249180
-0.361727 0.044749 0.216369
-0.348153 0.069352 0.209682
-0.337217 0.045887 0.252731
-0.331050 0.046309 0.303014
-0.315984 0.081682 0.302052
-0.284402 0.070739 0.237853
-0.160928 0.095527 0.301120
-0.243864 0.253123 0.323982
-0.277572 0.092148 0.227598
-0.287300 0.089141 0.248731
-0.266347 0.080300 0.293693
-0.251289 0.087932 0.356317
-0.229821 0.046012 0.383514
-0.211823 0.052236 0.376683
-0.227721 0.066729 0.381682
-0.211191 0.099568 0.361644
-0.250163 0.058192 0.302916
-0.238782 0.062404 0.276585
-0.226470 0.067801 0.245403
-0.201436 0.085254 0.282160
-0.219802 0.088189 0.275429
-0.195729 0.096373 0.259539
-0.239596 0.069924 0.258877
-0.252931 0.058961 0.285795
-0.198265 0.083733 0.337224
-0.154613 0.036968 0.351381
-0.177337 0.021450 0.364380
-0.179088 0.025299 0.334012
-0.159295 0.027232 0.308317
-0.188645 0.046948 0.354951
-0.239592 0.093448 0.325226
-0.260247 0.055024 0.254124
-0.271796 0.061114 0.279167
-0.277210 0.043283 0.292067
-0.285919 0.056460 0.283294
-0.294039 0.048722 0.271710
-0.284689 0.041537 0.264456
-0.295141 0.036382 0.263883
-0.297060 0.034184 0.245546
-0.293229 0.029850 0.279750
-0.281186 0.022593 0.265907
-0.277293 0.025365 0.243586
-0.258324 0.031845 0.190247
-0.259675 0.040360 0.270911
-0.247039 0.037888 0.299431
-0.208028 0.109870 0.417382
-0.143955 0.352665 0.276035
-0.219494 0.404511 0.278305
-0.352442 0.182051 0.309356
-0.405915 0.135088 0.307030
-0.369146 0.162615 0.410960
-0.433703 0.099514 0.369783
-0.285682 0.219583 0.351837
-0.205221 0.076512 0.429524
-0.209111 0.064178 0.357358
-0.213614 0.027846 0.368032
-0.211762 0.020177 0.348034
-0.239715 0.025079 0.308549
-0.181970 0.021514 0.274842
-0.207709 0.021261 0.265212
-0.224222 0.023951 0.292046
-0.205208 0.035452 0.292259
-0.228577 0.040117 0.304294
-0.185628 0.027511 0.302807
-0.208356 0.024577 0.316996
-0.164632 0.053682 0.299398
-0.154684 0.059791 0.276709
-0.163141 0.113219 0.252962
-0.145021 0.179019 0.408733
-0.214761 0.213412 0.297524
-0.308714 0.266575 0.390462
-0.419920 0.278106 0.288387
-0.436034 0.199545 0.357313
-0.451619 0.349524 0.419884
-0.351454 0.399809 0.460027
-0.360729 0.263047 0.612763
-0.418659 0.158631 0.284739
-0.456406 0.261108 0.373714
-0.424203 0.185874 0.316636
-0.400414 0.220266 0.453220
-0.368427 0.288074 0.412510
-0.343373 0.311195 0.490064
-0.395724 0.120734 0.436366
-0.344054 0.121619 0.347531
-0.272067 0.060489 0.198795
-0.301511 0.071935 0.185958
-0.309917 0.058524 0.190423
-0.300737 0.068082 0.171283
-0.295951 0.070752 0.150988
-0.296628 0.093980 0.139509
-0.302790 0.088637 0.162273
-0.289209 0.107492 0.167687
-0.257493 0.099688 0.159880
-0.265074 0.094624 0.181755
-0.266152 0.102270 0.207499
-0.269178 0.081363 0.277388
-0.234937 0.089620 0.382405
-0.183980 0.071956 0.466773
-0.219287 0.038089 0.431341
-0.202243 0.025685 0.466386
-0.158633 0.040859 0.449110
-0.165286 0.038598 0.497265
-0.170922 0.081097 0.523174
-0.255371 0.073482 0.249855
-0.294450 0.061848 0.264223
-0.304183 0.048479 0.179739
-0.310850 0.055590 0.165979
-0.311457 0.049670 0.147335
-0.330971 0.043725 0.142906
-0.338014 0.047764 0.127744
-0.367458 0.069305 0.112055
-0.365012 0.080855 0.169084
-0.360471 0.123986 0.145022
-0.219106 0.213898 0.129019
-0.206939 0.158987 0.242265
-0.246130 0.209339 0.215908
-0.281650 0.212707 0.204391
-0.368421 0.137607 0.310718
-0.416555 0.186663 0.125862
-0.490086 0.115875 0.145587
-0.582071 0.084161 0.206439
-0.516409 0.100131 0.260412
-0.209178 0.109586 0.221433
-0.269122 0.077905 0.211916
-0.300134 0.057524 0.238951
-0.303992 0.045603 0.260036
-0.322399 0.041910 0.267995
-0.316911 0.039992 0.287154
-0.327515 0.024597 0.301819
-0.326525 0.038109 0.322430
-0.341705 0.034554 0.344489
-0.315359 0.057607 0.326479
-0.311192 0.052833 0.302654
-0.297687 0.053640 0.333832
-0.310295 0.070962 0.376051
-0.287143 0.033181 0.414809
-0.248935 0.044304 0.319914
-0.246203 0.096450 0.292594
-0.203226 0.299903 0.287677
-0.450787 0.226937 0.192194
-0.429364 0.129302 0.269024
-0.457446 0.111038 0.290750
-0.498339 0.083336 0.319890
-0.424246 0.121867 0.333939
-0.180169 0.212830 0.368602
-0.241118 0.059711 0.365439
-0.224747 0.101688 0.488165
-0.246281 0.034903 0.465119
-0.214101 0.041638 0.545771
-0.172272 0.040285 0.598901
-0.204244 0.073643 0.382078
-0.146978 0.063294 0.389213
-0.382561 0.211691 0.242082
-0.362189 0.175671 0.247243
-0.318033 0.195181 0.218764
-0.318069 0.292363 0.228042
-0.255232 0.340570 0.247263
-0.224048 0.079338 0.358775
-0.236448 0.054617 0.310908
-0.239437 0.046635 0.344813
-0.243703 0.031212 0.389996
-0.226767 0.019507 0.406603
-0.238177 0.018267 0.376086
-0.218586 0.029858 0.389601
-0.197366 0.025585 0.402150
-0.181994 0.030716 0.427478
-0.190316 0.080557 0.359194
-0.190657 0.107271 0.458600
-0.155050 0.289997 0.417618
-0.187166 0.466579 0.426216
-0.327820 0.426769 0.326883
-0.298164 0.333603 0.351558
-0.222925 0.307747 0.580913
-0.198007 0.195365 0.578080
-0.210838 0.132715 0.542845
-0.231681 0.145101 0.436671
-0.232264 0.139358 0.387084
-0.255424 0.134975 0.350235
-0.269033 0.107837 0.261451
-0.321432 0.091599 0.275752
-0.380638 0.048055 0.299763
-0.405177 0.039883 0.236148
-0.423159 0.034218 0.181764
-0.453693 0.035502 0.198420
-0.464601 0.056361 0.119659
-0.481653 0.094843 0.109332
-0.543887 0.077760 0.119617
-0.510174 0.067882 0.146075
-0.506307 0.045510 0.174226
-0.488336 0.037550 0.110817
-0.414503 0.071944 0.106334
-0.383441 0.044148 0.118702
-0.368264 0.023699 0.150335
-0.307715 0.072824 0.135304
-0.294683 0.031017 0.196791
-0.275515 0.032364 0.181864
-0.235271 0.050178 0.178346
-0.215182 0.042335 0.185990
-0.209160 0.034271 0.223795
-0.228156 0.042936 0.260040
-0.223438 0.035509 0.277441
-0.180634 0.048455 0.281545
-0.197426 0.043630 0.273470
-0.205039 0.042828 0.313134
-0.223919 0.042287 0.320436
-0.223789 0.049071 0.285841
-0.214087 0.074972 0.257980
-0.221706 0.055601 0.498696
-0.248886 0.066833 0.445954
-0.213931 0.250226 0.256738
-0.405740 0.215131 0.170840
-0.328009 0.225653 0.293796
-0.402298 0.209079 0.214184
-0.399981 0.190690 0.264499
-0.363176 0.143635 0.492934
-0.411671 0.175359 0.406973
-0.483187 0.170802 0.394002
-0.431046 0.230553 0.250015
-0.389736 0.164181 0.297007
-0.397937 0.264402 0.341441
-0.395597 0.192289 0.302742
-0.343285 0.064916 0.354126
-0.350910 0.048799 0.290592
-0.347107 0.053302 0.266173
-0.361248 0.035141 0.231596
-0.353263 0.036751 0.257156
-0.332918 0.021247 0.255062
-0.360739 0.026445 0.281881
-0.367061 0.033022 0.325980
-0.350245 0.030285 0.303678
-0.327460 0.062073 0.283904
-0.264953 0.154809 0.315348
-0.324552 0.162784 0.438341
-0.429845 0.118138 0.486718
-0.437485 0.201399 0.415841
-0.427985 0.188146 0.278007
-0.298482 0.166884 0.350707
-0.267071 0.100408 0.291668
-0.274139 0.048797 0.268746
-0.281772 0.064356 0.267733
-0.214424 0.106076 0.312509
-0.331917 0.145161 0.280800
-0.354727 0.078392 0.279286
-0.371871 0.063102 0.214163
-0.396773 0.045559 0.209831
-0.421855 0.036944 0.214993
-0.420483 0.038557 0.160983
-0.436158 0.046191 0.146786
-0.453173 0.052302 0.137395
-0.481122 0.055096 0.145895
-0.465610 0.080732 0.136565
-0.449280 0.063650 0.159070
-0.438899 0.073552 0.140745
-0.432289 0.052628 0.119653
-0.420075 0.055923 0.142166
-0.415632 0.042002 0.128100
-0.412222 0.024997 0.139031
-0.391770 0.036632 0.146635
-0.393909 0.035907 0.188207
-0.368782 0.042784 0.188583
-0.363114 0.026468 0.218028
-0.375379 0.033356 0.364183
-0.345201 0.072563 0.316474
-0.306150 0.169779 0.294978
-0.484261 0.214170 0.267057
-0.406809 0.237896 0.384323
-0.392655 0.344627 0.332547
-0.326695 0.369933 0.207731
-0.407366 0.219126 0.278777
-0.398951 0.222770 0.323388
-0.464580 0.171047 0.338723
-0.397575 0.158165 0.591424
-0.420764 0.281705 0.506598
-0.473997 0.277563 0.218714
-0.336638 0.220260 0.461195
-0.342381 0.160051 0.377158
-0.246975 0.040158 0.263418
-0.239553 0.054919 0.205493
-0.252654 0.036861 0.224388
-0.253305 0.022395 0.239997
-0.271057 0.036266 0.237408
-0.273993 0.028386 0.214558
-0.242393 0.034220 0.204126
-0.236256 0.038163 0.247591
-0.209356 0.079325 0.234462
-0.194870 0.063640 0.214830
-0.244111 0.043255 0.236907
-0.264016 0.045660 0.223915
-0.260253 0.048634 0.207679
-0.251574 0.057245 0.189983
-0.263437 0.063508 0.241134
-0.271436 0.069219 0.251311
-0.261483 0.087406 0.246475
-0.250589 0.076269 0.277050
-0.244799 0.069765 0.292298
-0.232217 0.055247 0.331780
-0.216197 0.056278 0.342299
-0.176402 0.053897 0.380149
-0.224991 0.078406 0.337659
-0.231780 0.062395 0.422354
-0.189766 0.154959 0.437237
-0.204459 0.136309 0.307237
-0.260264 0.045977 0.240046
-0.269789 0.046212 0.252599
-0.274164 0.035012 0.302447
-0.230060 0.090744 0.305382
-0.166096 0.140832 0.294885
-0.154169 0.268532 0.226818
-0.349563 0.262265 0.343630
-0.354489 0.268911 0.296625
-0.375822 0.171148 0.332545
-0.476794 0.136744 0.259507
-0.399929 0.118339 0.259498
-0.271716 0.130588 0.469224
-0.305172 0.032898 0.454218
-0.308690 0.042473 0.417566
-0.288698 0.024952 0.300569
-0.290810 0.015293 0.221283
-0.268986 0.033267 0.147285
-0.237334 0.048825 0.120734
-0.228777 0.055634 0.150103
-0.204334 0.073034 0.174915
-0.208027 0.057339 0.236310
-0.198897 0.066784 0.271433
-0.202506 0.057603 0.300680
-0.222788 0.058041 0.300819
-0.233042 0.055613 0.290225
-0.246512 0.042508 0.284706
-0.260946 0.032017 0.314281
-0.280743 0.031362 0.358053
-0.305375 0.031854 0.387510
-0.269256 0.025479 0.381275
-0.245952 0.040037 0.364854
-0.268189 0.040204 0.323075
-0.275163 0.050477 0.311422
-0.265688 0.064899 0.301225
-0.239306 0.268505 0.378907
-0.312398 0.266259 0.164624
-0.480542 0.174554 0.171654
-0.552172 0.158933 0.144993
-0.458784 0.141655 0.212248
-0.428648 0.163482 0.164911
-0.350278 0.208056 0.235462
-0.359219 0.250780 0.234338
-0.336572 0.248935 0.259563
-0.293959 0.257267 0.267935
-0.238555 0.202335 0.370163
-0.245646 0.069245 0.336645
-0.261452 0.055228 0.352020
-0.268939 0.054326 0.369767
-0.286819 0.048101 0.382083
-0.271280 0.052949 0.401336
-0.248193 0.051118 0.385676
-0.239973 0.026597 0.429200
-0.214644 0.060995 0.454583
-0.220676 0.083808 0.406302
-0.250805 0.126260 0.297366
-0.334644 0.192200 0.346535
-0.381125 0.159560 0.367527
-0.340438 0.157087 0.328361
-0.277244 0.160062 0.390717
-0.292870 0.052195 0.355769
-0.345623 0.035855 0.396258
-0.374273 0.031225 0.447159
-0.276809 0.033552 0.581647
-0.224359 0.099923 0.647568
-0.333303 0.049949 0.516785
-0.312970 0.123739 0.396509
-0.238621 0.146067 0.231297
-0.165305 0.049204 0.329040
-0.278324 0.199829 0.426235
-0.253210 0.337113 0.436856
-0.206203 0.578084 0.277516
-0.309249 0.169748 0.538897
-0.332333 0.091215 0.435451
-0.279107 0.030067 0.502383
-0.259234 0.086196 0.546189
-0.267603 0.068953 0.484586
-0.265845 0.064849 0.423640
-0.281793 0.086538 0.401598
-0.264889 0.079521 0.377251
-0.266400 0.115068 0.375961
-0.205215 0.130153 0.360079
-0.229061 0.160330 0.306438
-0.189984 0.185082 0.324728
-0.229945 0.128947 0.326026
-0.253837 0.089731 0.266618
-0.255704 0.088487 0.224765
-0.286792 0.092177 0.188518
-0.320841 0.097300 0.214002
-0.333689 0.106637 0.185748
-0.333838 0.086680 0.174199
-0.319590 0.093878 0.148540
-0.340092 0.115413 0.159425
-0.351543 0.092448 0.163319
-0.342527 0.091358 0.203951
-0.331816 0.119469 0.305761
-0.280244 0.128802 0.290044
-0.304101 0.105074 0.248131
-0.338603 0.080077 0.255476
-0.309197 0.057247 0.254671
-0.300156 0.070286 0.244369
-0.286353 0.065888 0.254045
-0.258600 0.108479 0.234651
-0.224997 0.109225 0.266261
-0.195413 0.126245 0.250545
-0.281750 0.062811 0.213758
-0.303917 0.051829 0.203332
-0.317902 0.072075 0.155470
-0.327787 0.081576 0.130690
-0.355867 0.073091 0.127604
-0.358901 0.085628 0.142860
-0.347105 0.087525 0.122878
-0.333158 0.110155 0.130534
-0.305063 0.115625 0.125246
-0.311381 0.117013 0.156404
-0.308163 0.112438 0.188106
-0.269326 0.130721 0.245640
-0.216982 0.085835 0.320106
-0.212607 0.057787 0.321804
-0.198387 0.073638 0.315780
-0.186044 0.054189 0.321956
-0.163325 0.054977 0.246522
-0.182868 0.034089 0.225316
-0.180488 0.047224 0.190814
-0.157011 0.029435 0.267719
-0.233375 0.081439 0.132706
-0.274801 0.044742 0.195953
-0.306673 0.028692 0.261583
-0.305705 0.037574 0.221126
-0.303135 0.045524 0.239984
-0.282405 0.040832 0.282276
-0.283758 0.040311 0.339897
-0.234144 0.030246 0.331245
-0.216669 0.066311 0.278480
-0.190170 0.097245 0.230782
-0.168054 0.072931 0.353984
-0.179260 0.077851 0.328143
-0.174966 0.076302 0.231521
-0.175667 0.078095 0.272008
-0.189384 0.067503 0.247983
-0.214139 0.046101 0.272932
-0.233914 0.045467 0.277783
-0.244588 0.049198 0.296792
-0.256730 0.043153 0.334920
-0.257759 0.032742 0.347498
-0.285465 0.026853 0.316266
-0.271270 0.033933 0.272250
-0.276680 0.045231 0.220594
-0.288564 0.042172 0.209508
-0.292675 0.047892 0.190494
-0.308407 0.037952 0.274706
-0.318522 0.038643 0.364714
-0.247803 0.111933 0.190722
-0.233404 0.144416 0.275805
-0.249166 0.193532 0.320038
-0.310797 0.319086 0.285728
-0.360867 0.217696 0.267229
-0.373286 0.186187 0.279616
-0.387949 0.127631 0.343667
-0.415183 0.073517 0.405553
-0.454532 0.127629 0.417735
-0.448768 0.149562 0.299421
-0.512886 0.163940 0.302645
-0.392881 0.193813 0.357648
-0.261675 0.259539 0.466201
-0.234490 0.096500 0.443213
-0.258238 0.062531 0.385246
-0.260465 0.035885 0.401811
-0.261667 0.036601 0.432964
-0.281564 0.058277 0.447718
-0.247830 0.105619 0.413321
-0.195343 0.165737 0.277588
-0.216014 0.219408 0.421047
-0.169087 0.221263 0.482537
-0.227429 0.183042 0.484872
-0.260935 0.291958 0.298961
-0.224112 0.158830 0.343758
-0.284726 0.056334 0.226615
-0.294599 0.051973 0.149180
-0.325047 0.051628 0.179937
-0.356402 0.049165 0.175911
-0.376165 0.058355 0.163522
-0.397813 0.057225 0.144147
-0.393141 0.044994 0.129534
-0.402884 0.044005 0.110816
-0.407746 0.063560 0.121868
-0.403282 0.071499 0.138498
-0.406901 0.052769 0.156323
-0.400491 0.038429 0.161151
-0.391847 0.058654 0.157748
-0.385015 0.067309 0.137188
-0.377336 0.045050 0.152108
-0.362722 0.055345 0.162513
-0.315826 0.042890 0.168139
-0.283083 0.080878 0.165981
-0.285489 0.067464 0.191727
-0.145248 0.070726 0.324069
-0.399799 0.255914 0.214022
-0.429920 0.159068 0.250011
-0.439445 0.183575 0.202417
-0.398499 0.258210 0.143533
-0.465245 0.169443 0.256422
-0.422318 0.358987 0.185421
-0.253220 0.222325 0.265472
-0.210594 0.307630 0.214541
-0.175040 0.446152 0.193737
-0.226217 0.379009 0.100408
-0.340833 0.306077 0.113355
-0.265242 0.294847 0.105075
-0.276714 0.304171 0.186038
-0.390551 0.100132 0.539154
-0.297133 0.125853 0.333330
-0.196927 0.178243 0.197378
-0.257580 0.128441 0.214041
-0.229792 0.130115 0.182553
-0.170106 0.162513 0.231148
-0.164595 0.106934 0.342563
-0.175852 0.127587 0.392165
-0.157779 0.134743 0.489792
-0.152201 0.097943 0.432539
-0.162413 0.153705 0.347737
-0.277299 0.150900 0.266126
-0.266806 0.172668 0.234574
-0.318579 0.167283 0.249262
-0.347916 0.107363 0.231007
-0.372857 0.090140 0.210306
-0.384342 0.113638 0.196678
-0.404131 0.095394 0.183804
-0.384612 0.121810 0.167672
-0.322944 0.132564 0.210257
-0.290364 0.146204 0.223432
-0.264192 0.157656 0.193948
-0.233485 0.163743 0.200412
-0.207187 0.138320 0.212342
-0.225556 0.124901 0.244775
-0.239106 0.105732 0.239571
-0.287733 0.114294 0.228538
-0.340176 0.100254 0.107080
-0.389066 0.103998 0.122846
-0.444975 0.102241 0.133970
-0.415860 0.114565 0.114926
-0.453877 0.120214 0.107920
-0.403927 0.096306 0.080457
-0.421740 0.122693 0.079588
-0.450640 0.144936 0.071884
-0.393762 0.136866 0.060204
-0.381369 0.180962 0.064094
-0.417859 0.160286 0.072990
-0.381221 0.146156 0.087738
-0.393977 0.119086 0.094996
-0.414356 0.146006 0.109031
-0.435031 0.134052 0.138616
-0.396483 0.123711 0.134754
-0.382302 0.141141 0.123735
-0.353663 0.145826 0.104587
-0.332036 0.171052 0.104051
-0.311513 0.199338 0.131723
-0.285181 0.190876 0.163180
-0.274455 0.184371 0.123920
-0.301600 0.169794 0.109397
-0.311406 0.141832 0.086234
-0.321738 0.140580 0.119486
-0.327427 0.145551 0.158359
-0.310737 0.168048 0.174012
-0.297873 0.175289 0.197738
-0.319909 0.123865 0.237833
-0.344952 0.122697 0.263042
-0.371611 0.111286 0.281178
-0.378247 0.099648 0.307710
-0.394570 0.079100 0.338162
-0.416351 0.038242 0.333196
-0.417830 0.042111 0.293185
-0.430829 0.039852 0.251519
-0.427375 0.079094 0.261696
-0.452757 0.101221 0.232921
-0.431060 0.088368 0.204739
-0.384616 0.086474 0.244279
-0.416919 0.124304 0.189584
-0.448928 0.116694 0.166079
-0.402548 0.157029 0.204021
-0.405248 0.099612 0.223420
-0.394667 0.126257 0.226234
-0.393587 0.155514 0.157489
-0.388278 0.150483 0.241885
-0.363290 0.151279 0.275569
-0.369461 0.131040 0.246673
-0.365592 0.135952 0.213237
-0.355959 0.141295 0.179707
-0.320616 0.134892 0.181918
+++ /dev/null
-0.347624 0.090959 0.454834
-0.446215 0.124000 0.370817
-0.409839 0.143155 0.295004
-0.440759 0.090281 0.296885
-0.465214 0.048451 0.542712
-0.471598 0.086037 0.483358
-0.372213 0.179217 0.438123
-0.592442 0.166741 0.433982
-0.399563 0.151320 0.400160
-0.479513 0.108517 0.258405
-0.485953 0.066923 0.193914
-0.548002 0.077271 0.152336
-0.565599 0.143205 0.140294
-0.558550 0.201462 0.109620
-0.607051 0.211633 0.152670
-0.670273 0.190261 0.139432
-0.430187 0.478301 0.135903
-0.148336 0.680821 0.114594
-0.185120 0.925628 0.147625
-0.249453 0.196637 0.241588
-0.179636 0.162617 0.313756
-0.586115 0.159387 0.307418
-0.472213 0.142351 0.245426
-0.384650 0.125831 0.240183
-0.332192 0.095235 0.255403
-0.300937 0.083633 0.239104
-0.282901 0.084036 0.324663
-0.264823 0.053630 0.355336
-0.262817 0.057144 0.308867
-0.235162 0.063366 0.290788
-0.225952 0.074491 0.259080
-0.250763 0.056393 0.263298
-0.261983 0.035121 0.221390
-0.232025 0.071049 0.211475
-0.251247 0.084420 0.177652
-0.317549 0.092361 0.194930
-0.376276 0.108869 0.213490
-0.407707 0.134249 0.200956
-0.324354 0.161579 0.180522
-0.155666 0.212650 0.191861
-0.276764 0.149348 0.164832
-0.232067 0.140034 0.296200
-0.202557 0.227413 0.232181
-0.213631 0.254317 0.286816
-0.230290 0.348972 0.223799
-0.073922 0.234044 0.444311
-0.165732 0.157286 0.377940
-0.143741 0.116266 0.367517
-0.170743 0.108278 0.335489
-0.204941 0.105478 0.323687
-0.232372 0.096166 0.294273
-0.249692 0.106680 0.233431
-0.247681 0.098716 0.205549
-0.285627 0.093674 0.181026
-0.273729 0.071657 0.199517
-0.324046 0.078751 0.174477
-0.320316 0.099534 0.141530
-0.305721 0.138944 0.194222
-0.307697 0.112445 0.306832
-0.263996 0.168409 0.279904
-0.209440 0.206560 0.352981
-0.207167 0.322235 0.237881
-0.248742 0.300747 0.244987
-0.244240 0.372015 0.250098
-0.311161 0.424673 0.225040
-0.297068 0.321411 0.313296
-0.379598 0.254957 0.371188
-0.432562 0.150907 0.250569
-0.490914 0.159011 0.203063
-0.459581 0.210629 0.184517
-0.365981 0.161992 0.242609
-0.273934 0.337911 0.234642
-0.303721 0.505646 0.388642
-0.245707 0.638533 0.280329
-0.225268 0.652879 0.192438
-0.258619 0.514447 0.279012
-0.316225 0.442602 0.335354
-0.376736 0.486777 0.308274
-0.327223 0.324066 0.242576
-0.485431 0.280997 0.355045
-0.572007 0.122510 0.240640
-0.616966 0.130938 0.227853
-0.513791 0.196874 0.180058
-0.466626 0.182542 0.223111
-0.402779 0.115602 0.343902
-0.375184 0.115227 0.402459
-0.273038 0.096940 0.441549
-0.286064 0.098337 0.549602
-0.246440 0.074548 0.556880
-0.236129 0.064941 0.588188
-0.209837 0.057975 0.532197
-0.259255 0.105430 0.407552
-0.302610 0.088086 0.382011
-0.330261 0.083490 0.318869
-0.339807 0.116430 0.207260
-0.296092 0.172928 0.144366
-0.253885 0.186664 0.166529
-0.277668 0.172442 0.196902
-0.314677 0.169787 0.285051
-0.278732 0.261731 0.151343
-0.192094 0.380939 0.072290
-0.164268 0.445241 0.088517
-0.213885 0.495691 0.078607
-0.244315 0.538432 0.099402
-0.213845 0.607105 0.091577
-0.286835 0.597563 0.087259
-0.318522 0.532846 0.080556
-0.284601 0.472920 0.105552
-0.326441 0.404994 0.109082
-0.361786 0.342944 0.134275
-0.405219 0.182087 0.266692
-0.339703 0.133107 0.349810
-0.318105 0.105264 0.418487
-0.268618 0.127749 0.519300
-0.210097 0.094867 0.551063
-0.184708 0.182810 0.698480
-0.158544 0.111449 0.634672
-0.170413 0.071464 0.657281
-0.171397 0.082903 0.699070
-0.201223 0.064064 0.627255
-0.180269 0.136502 0.501476
-0.221574 0.070933 0.434092
-0.211382 0.073149 0.481703
-0.114169 0.100113 0.915283
-0.146052 0.246456 0.633652
-0.275922 0.245082 0.498471
-0.266161 0.247382 0.434042
-0.302721 0.126115 0.373389
-0.300980 0.138225 0.249755
-0.290909 0.136927 0.286352
-0.350897 0.109421 0.304023
-0.386165 0.088656 0.245381
-0.382333 0.105625 0.151256
-0.421477 0.091637 0.128128
-0.404884 0.121558 0.102941
-0.322205 0.220312 0.077762
-0.283695 0.260465 0.065194
-0.383440 0.199544 0.094240
-0.480839 0.209932 0.141564
-0.441391 0.230279 0.141240
-0.362251 0.290803 0.099062
-0.301174 0.368993 0.092277
-0.377409 0.363282 0.091280
-0.337772 0.461506 0.076775
-0.373032 0.519469 0.124106
-0.314757 0.552002 0.139769
-0.250607 0.492442 0.145557
-0.335493 0.328724 0.166487
-0.534645 0.644574 0.182718
-0.488781 0.353657 0.328925
-0.554548 0.233808 0.376737
-0.492450 0.553839 0.367700
-0.394815 0.210972 0.142784
-0.238589 0.303384 0.080013
-0.224147 0.255123 0.068313
-0.256497 0.235171 0.099373
-0.297511 0.154648 0.113728
-0.305673 0.117198 0.107972
-0.290657 0.090218 0.126335
-0.258861 0.096775 0.145361
-0.259983 0.099517 0.110715
-0.118646 0.148765 0.076387
-0.145023 0.105727 0.109695
-0.181102 0.134847 0.077805
-0.211445 0.088585 0.101849
-0.198248 0.105956 0.172142
-0.180296 0.129252 0.141319
-0.221042 0.083049 0.144665
-0.212791 0.063744 0.179816
-0.167506 0.115897 0.208529
-0.205822 0.062715 0.241237
-0.172651 0.083940 0.183620
-0.124447 0.084470 0.196419
-0.186739 0.063095 0.269351
-0.160093 0.104677 0.295459
-0.143447 0.142741 0.276552
-0.123263 0.196627 0.476282
-0.108325 0.605694 0.334137
-0.285290 0.315781 0.362135
-0.353244 0.270895 0.333924
-0.263653 0.300345 0.291813
-0.208575 0.465618 0.269759
-0.220467 0.418879 0.223504
-0.146022 0.320151 0.302772
-0.183727 0.325046 0.366600
-0.171236 0.313334 0.429997
-0.247905 0.276696 0.319839
-0.127071 0.396634 0.387451
-0.073374 0.373431 0.434696
-0.210963 0.363358 0.326782
-0.268129 0.366304 0.302607
-0.276157 0.386117 0.406186
-0.340781 0.360413 0.321075
-0.431904 0.276036 0.404829
-0.495040 0.225348 0.450453
-0.262250 0.219954 0.192843
-0.261002 0.142204 0.241314
-0.278943 0.115884 0.204352
-0.260726 0.138775 0.101751
-0.183464 0.210049 0.109076
-0.162266 0.261270 0.088046
-0.236604 0.196725 0.126686
-0.316678 0.196107 0.179685
-0.243299 0.306025 0.151947
-0.400615 0.162590 0.232750
-0.372639 0.216589 0.209970
-0.140820 0.222509 0.129726
-0.097670 0.184209 0.193834
-0.193869 0.127067 0.282177
-0.208523 0.142275 0.352114
-0.126584 0.151378 0.342813
-0.235628 0.172984 0.215508
-0.249437 0.175207 0.390557
-0.255433 0.127918 0.372391
-0.359147 0.151917 0.290168
-0.351722 0.205430 0.115799
-0.267453 0.279897 0.108704
-0.350766 0.239207 0.087893
-0.318117 0.273230 0.085462
-0.381113 0.237724 0.065900
-0.219080 0.256349 0.369571
-0.196609 0.194954 0.411062
-0.213051 0.139071 0.398959
-0.244873 0.146332 0.435157
-0.235630 0.181860 0.511397
-0.292860 0.209424 0.147620
-0.331811 0.148006 0.093985
-0.293049 0.144326 0.069176
-0.281985 0.195922 0.077879
-0.228381 0.205538 0.080972
-0.235938 0.163446 0.071037
-0.168487 0.195102 0.072566
-0.199465 0.163509 0.108306
-0.255681 0.174779 0.108553
-0.302851 0.083047 0.155297
-0.321466 0.113845 0.176969
-0.338191 0.096339 0.224480
-0.360544 0.065938 0.241459
-0.378601 0.057338 0.276674
-0.368373 0.076055 0.310651
-0.344437 0.070848 0.286673
-0.376329 0.104163 0.278687
-0.355476 0.110470 0.243634
-0.362002 0.085143 0.260003
-0.411330 0.051881 0.247678
-0.414240 0.068326 0.276653
-0.410484 0.082208 0.354845
-0.418149 0.061438 0.388696
-0.433860 0.142628 0.438577
-0.495950 0.091923 0.413338
-0.434164 0.131070 0.325030
-0.347126 0.153569 0.402577
-0.458076 0.093458 0.443701
-0.495375 0.120909 0.562539
-0.589514 0.080183 0.512524
-0.531194 0.063220 0.328711
-0.499017 0.059249 0.243179
-0.530991 0.079568 0.259341
-0.585658 0.077791 0.416801
-0.536002 0.122366 0.473100
-0.511945 0.062231 0.459896
-0.486451 0.116847 0.370233
-0.481843 0.144265 0.420622
-0.407554 0.241229 0.282167
-0.320925 0.282038 0.252246
-0.225131 0.374849 0.479590
-0.228011 0.237458 0.622277
-0.261961 0.179596 0.806264
-0.076218 0.139692 1.043456
-0.151340 0.328626 0.887716
-0.337210 0.198192 0.379580
-0.460842 0.167548 0.160717
-0.477628 0.229247 0.072684
-0.451350 0.203095 0.091994
-0.420022 0.110903 0.058632
-0.449733 0.161924 0.093239
-0.411145 0.163560 0.078750
-0.435222 0.142044 0.126205
-0.420083 0.099757 0.203874
-0.370276 0.131184 0.131964
-0.354905 0.098162 0.185357
-0.354880 0.098109 0.151202
-0.355875 0.081150 0.202714
-0.329850 0.070604 0.206228
-0.326647 0.063899 0.235204
-0.330171 0.045901 0.207938
-0.329941 0.047031 0.176438
-0.337293 0.074879 0.140863
-0.368014 0.066698 0.168744
-0.300423 0.104975 0.266224
-0.156403 0.547850 0.093121
-0.288125 0.304080 0.176781
-0.210923 0.180445 0.267334
-0.236880 0.217374 0.275212
-0.213759 0.376162 0.184946
-0.372297 0.209676 0.309731
-0.445389 0.226789 0.291673
-0.519740 0.112223 0.265429
-0.472434 0.174961 0.115646
-0.417682 0.274453 0.070003
-0.458596 0.258372 0.047548
-0.455272 0.274496 0.086373
-0.444215 0.318398 0.074804
-0.427749 0.360899 0.081827
-0.369149 0.335197 0.063361
-0.408385 0.324949 0.072860
-0.384052 0.298347 0.060899
-0.373725 0.264760 0.080748
-0.352145 0.176148 0.080707
-0.310910 0.188712 0.108730
-0.250319 0.151051 0.140139
-0.238071 0.144852 0.173219
-0.228573 0.106294 0.172491
-0.217371 0.097639 0.248280
-0.253003 0.069144 0.233568
-0.256968 0.055968 0.160406
-0.235219 0.115044 0.075964
-0.336525 0.077151 0.097771
-0.295976 0.059336 0.123351
-0.324309 0.059429 0.397350
-0.348266 0.106120 0.501358
-0.340380 0.127511 0.440305
-0.275937 0.136374 0.468843
-0.266087 0.282816 0.379226
-0.228482 0.306643 0.416738
-0.246227 0.200955 0.450023
-0.318533 0.209335 0.569205
-0.413909 0.089360 0.618461
-0.382377 0.110800 0.185218
-0.298919 0.076922 0.206253
-0.295486 0.062198 0.170334
-0.220572 0.123944 0.132661
-0.199126 0.138104 0.199012
-0.150799 0.164435 0.128584
-0.141718 0.112651 0.157620
-0.218667 0.109546 0.215544
-0.255989 0.086240 0.259903
-0.300656 0.046011 0.269817
-0.291157 0.059173 0.236624
-0.310810 0.077525 0.293206
-0.314641 0.049528 0.310313
-0.279240 0.086840 0.353600
-0.165264 0.103047 0.417338
-0.208135 0.117070 0.429435
-0.232791 0.103415 0.462895
-0.271864 0.129281 0.319815
-0.366981 0.141852 0.212178
-0.373262 0.242359 0.117112
-0.422067 0.278600 0.123501
-0.338944 0.345572 0.098531
-0.308216 0.428668 0.066433
-0.271454 0.398601 0.070491
-0.278913 0.492798 0.060932
-0.247776 0.441372 0.071561
-0.343570 0.386117 0.081017
-0.461654 0.239819 0.108222
-0.430485 0.272031 0.176591
-0.408685 0.297320 0.097183
-0.485213 0.284632 0.069179
-0.461397 0.373449 0.100410
-0.671420 0.378029 0.088090
-0.808405 0.276010 0.102934
-0.704869 0.430068 0.070162
-0.554941 0.507594 0.125272
-0.359919 0.301913 0.230542
-0.251847 0.314817 0.199777
-0.293156 0.307596 0.224547
-0.356977 0.402190 0.240191
-0.290117 0.743767 0.395678
-0.392248 0.703453 0.280630
-0.476220 0.520924 0.129796
-0.527212 0.411812 0.063633
-0.542919 0.358453 0.095274
-0.556482 0.315834 0.117993
-0.482078 0.326051 0.096336
-0.420379 0.426709 0.088736
-0.369052 0.415845 0.093306
-0.437630 0.334794 0.118496
-0.466644 0.293770 0.233791
-0.508918 0.228596 0.222776
-0.484639 0.121415 0.212331
-0.443499 0.096268 0.231387
-0.511197 0.174015 0.270205
-0.352556 0.283611 0.272015
-0.293392 0.425947 0.162990
-0.332821 0.275494 0.174376
-0.298858 0.241340 0.192968
-0.305188 0.294785 0.139588
-0.375530 0.449251 0.144064
-0.292345 0.781183 0.254538
-0.358461 0.243978 0.182222
-0.415777 0.244409 0.238222
-0.467064 0.146980 0.298146
-0.416339 0.232371 0.189786
-0.191873 0.319957 0.083328
-0.203436 0.360141 0.135797
-0.374532 0.135837 0.364913
-0.268287 0.102231 0.714801
-0.254501 0.146265 0.649860
-0.218848 0.270739 0.467287
-0.188426 0.170744 0.462937
-0.245247 0.107864 0.332378
-0.122418 0.152546 0.533111
-0.079016 0.314882 0.596442
-0.126964 0.240808 0.550476
-0.075791 0.140645 0.502026
-0.093230 0.113111 0.626546
-0.172159 0.080636 0.831021
-0.068199 0.206815 0.906033
-0.062132 0.233971 0.778223
-0.074593 0.142563 0.751383
-0.109526 0.088462 0.775006
-0.124547 0.075148 0.714916
-0.219269 0.045432 0.388959
-0.127591 0.145316 0.230824
-0.075140 0.099358 0.462657
-0.064338 0.123266 0.563272
-0.078238 0.117014 0.688975
-0.084643 0.135331 0.834358
-0.139739 0.180181 0.788226
-0.146212 0.130036 0.742469
-0.142021 0.071166 0.618520
-0.264581 0.062830 0.446908
-0.320084 0.063118 0.350973
-0.396868 0.104191 0.308665
-0.464396 0.100744 0.190844
-0.474587 0.135638 0.122223
-0.505265 0.164031 0.083774
-0.508671 0.149050 0.116783
-0.494586 0.165303 0.148019
-0.472521 0.133399 0.178996
-0.472105 0.087004 0.224228
-0.446638 0.121806 0.273503
-0.367261 0.095789 0.337281
-0.359383 0.069161 0.376118
-0.283834 0.061745 0.401507
-0.233699 0.158991 0.567659
-0.131424 0.169028 0.614621
-0.073539 0.165230 0.608024
-0.084229 0.293229 0.506663
-0.148758 0.720830 0.237339
-0.256384 0.243042 0.348749
-0.395262 0.183863 0.343968
-0.381026 0.153580 0.322679
-0.344857 0.169307 0.357051
-0.180931 0.274934 0.267210
-0.133417 0.315317 0.364657
-0.184162 0.267604 0.330168
-0.220026 0.283042 0.231767
-0.259555 0.237606 0.232106
-0.276933 0.249820 0.287878
-0.349980 0.282625 0.421991
-0.481016 0.212218 0.325727
-0.458797 0.184528 0.274070
-0.484482 0.148105 0.341873
-0.526047 0.155385 0.400111
-0.526136 0.175193 0.328794
-0.556038 0.116326 0.373700
-0.437912 0.183108 0.320129
-0.154855 0.684819 0.527786
-0.142128 0.492151 0.711010
-0.062256 0.311531 0.691655
-0.180612 0.307234 0.730728
-0.152739 0.786052 0.357275
-0.421748 0.155971 0.355152
-0.513427 0.140653 0.180397
-0.503293 0.090152 0.226204
-0.470923 0.079454 0.290961
-0.458356 0.094363 0.377705
-0.447899 0.062986 0.355100
-0.490749 0.048144 0.340535
-0.490854 0.079767 0.368968
-0.568302 0.078153 0.271815
-0.574387 0.098205 0.200963
-0.644881 0.089413 0.208920
-0.636596 0.088651 0.058559
-0.553118 0.323894 0.063352
-0.583298 0.295978 0.091612
-0.606749 0.318066 0.058865
-0.487005 0.454915 0.177572
-0.329222 0.315592 0.285150
-0.299399 0.277718 0.282728
-0.302006 0.358174 0.148859
-0.334243 0.327319 0.350426
-0.291480 0.333984 0.274831
-0.383078 0.333489 0.255643
-0.406396 0.413215 0.258302
-0.479588 0.360631 0.169112
-0.594135 0.255844 0.137076
-0.847445 0.093619 0.248967
-0.810961 0.161433 0.181118
-0.732094 0.308294 0.140083
-0.623878 0.379968 0.070210
-0.567617 0.374818 0.060450
-0.664229 0.294886 0.104059
-0.645906 0.246204 0.135086
-0.673058 0.227775 0.100138
-0.659455 0.250925 0.067423
-0.627904 0.283712 0.067938
-0.581249 0.267066 0.063458
-0.617716 0.219403 0.068390
-0.599018 0.303403 0.166919
-0.450459 0.568624 0.270030
-0.497221 0.226918 0.270466
-0.411324 0.232483 0.331049
-0.320406 0.443850 0.269652
-0.187291 0.561422 0.165638
-0.294572 0.343681 0.200707
-0.326397 0.258546 0.286441
-0.279400 0.306226 0.260735
-0.193123 0.385992 0.258247
-0.342327 0.381838 0.147491
-0.433089 0.378484 0.207774
-0.362956 0.347448 0.222551
-0.361638 0.480201 0.226996
-0.384522 0.377667 0.186341
-0.427881 0.296866 0.282612
-0.563327 0.229524 0.304696
-0.567170 0.247155 0.202733
-0.585411 0.220038 0.115594
-0.519250 0.229429 0.071582
-0.466406 0.348495 0.062605
-0.474052 0.430997 0.059085
-0.456952 0.434321 0.092489
-0.443242 0.479322 0.066114
-0.424170 0.532398 0.074007
-0.394911 0.475416 0.086889
-0.452632 0.411710 0.140813
-0.403571 0.307690 0.141199
-0.330609 0.309675 0.202639
-0.162152 0.333000 0.246273
-0.104212 0.372786 0.256919
-0.136824 0.521324 0.228461
-0.104865 0.608493 0.187863
-0.112234 0.499159 0.140580
-0.103176 0.394350 0.106114
-0.097342 0.431118 0.194462
-0.199846 0.166342 0.150206
-0.257308 0.138618 0.204462
-0.377777 0.076428 0.214777
-0.396461 0.078672 0.186686
-0.412491 0.083042 0.157354
-0.409492 0.113963 0.166822
-0.402656 0.132414 0.136860
-0.384318 0.169269 0.141277
-0.379760 0.142363 0.169790
-0.434051 0.125795 0.180081
-0.291493 0.229394 0.111634
-0.413319 0.193400 0.112837
-0.413655 0.226896 0.114264
-0.433596 0.176677 0.130118
-0.324845 0.251559 0.120351
-0.359504 0.214180 0.154811
-0.415838 0.197748 0.221624
-0.330767 0.232694 0.237892
-0.283703 0.199163 0.276558
-0.402389 0.264705 0.562024
-0.405915 0.068161 0.722076
-0.408789 0.081683 0.224705
-0.412949 0.070850 0.318290
-0.383543 0.088037 0.376585
-0.413842 0.087764 0.457480
-0.394697 0.085379 0.526908
-0.326022 0.124012 0.545103
-0.360363 0.103599 0.573651
-0.374875 0.071392 0.577138
-0.426542 0.064067 0.485994
-0.414344 0.062295 0.436129
-0.357597 0.053368 0.442984
-0.352690 0.061527 0.481466
-0.435965 0.091560 0.330005
-0.452104 0.173696 0.389629
-0.240811 0.227686 0.399164
-0.387054 0.212876 0.250823
-0.348481 0.199112 0.239045
-0.406692 0.124037 0.262865
-0.364589 0.130457 0.265840
-0.418494 0.152965 0.158070
-0.525395 0.176045 0.224438
-0.649496 0.162294 0.265624
-0.577476 0.087708 0.311571
-0.635120 0.080693 0.336377
-0.695460 0.066421 0.421660
-0.621358 0.149936 0.353147
-0.567838 0.187842 0.239684
-0.610053 0.188465 0.189601
-0.290729 0.370305 0.245506
-0.474752 0.256582 0.192554
-0.523264 0.281951 0.174076
-0.487445 0.266791 0.140722
-0.418187 0.308871 0.224831
-0.542461 0.339261 0.179909
-0.660046 0.325237 0.064232
-0.699190 0.263381 0.081222
-0.771760 0.141829 0.114068
-0.849307 0.167518 0.110492
-0.768620 0.215479 0.101016
-0.943168 0.112917 0.126022
-0.700213 0.207371 0.114043
-0.520214 0.355040 0.056977
-0.501121 0.416740 0.097933
-0.413408 0.446710 0.207348
-0.316233 0.501402 0.172782
-0.422015 0.299620 0.334807
-0.467201 0.278473 0.294606
-0.449356 0.314132 0.169959
-0.383191 0.318048 0.185054
-0.263466 0.409830 0.258522
-0.344203 0.180472 0.319223
-0.362266 0.169616 0.180383
-0.341699 0.182702 0.146822
-0.335987 0.174976 0.210809
-0.395083 0.165288 0.194206
-0.465646 0.099187 0.323536
-0.462006 0.053739 0.310921
-0.455068 0.081078 0.262737
-0.418012 0.119395 0.233351
-0.345448 0.135789 0.188425
-0.351492 0.162596 0.117706
-0.344759 0.149410 0.147248
-0.314307 0.134967 0.151339
-0.286415 0.116093 0.164754
-0.277756 0.126139 0.130984
-0.361188 0.110945 0.070191
-0.361209 0.201107 0.056536
-0.284536 0.314088 0.069545
-0.432086 0.300442 0.045010
-0.395858 0.449191 0.053920
-0.358265 0.503243 0.063399
-0.373607 0.577103 0.071048
-0.277978 0.673759 0.088057
-0.361589 0.613722 0.123032
-0.384724 0.684712 0.091070
-0.459571 0.724691 0.081391
-0.440636 0.611416 0.071085
-0.491405 0.544525 0.066202
-0.495390 0.482599 0.069217
-0.585200 0.253363 0.096585
-0.538917 0.276943 0.073936
-0.500464 0.315306 0.054544
-0.664338 0.150817 0.196704
-0.500195 0.080074 0.282262
-0.530558 0.067443 0.375424
-0.440087 0.352641 0.277248
-0.390681 0.267263 0.209143
-0.359333 0.241690 0.261267
-0.370447 0.247920 0.308405
-0.336215 0.226039 0.305830
-0.195785 0.339497 0.283349
-0.151348 0.445352 0.258280
-0.266713 0.219848 0.307969
-0.218114 0.294964 0.285277
-0.174107 0.381064 0.212437
-0.155914 0.377087 0.116389
-0.134386 0.253742 0.304443
-0.151029 0.213087 0.353221
-0.217483 0.140058 0.241820
-0.242753 0.116518 0.270671
-0.285332 0.068762 0.270927
-0.317498 0.078582 0.264060
-0.277862 0.110739 0.250417
-0.308456 0.109889 0.221582
-0.276315 0.089684 0.226545
-0.333980 0.135929 0.231792
-0.334591 0.166897 0.259283
-0.397876 0.537888 0.188209
-0.290878 0.394567 0.198465
-0.163752 0.435990 0.173066
-0.191115 0.481622 0.133956
-0.260636 0.377095 0.197277
-0.338080 0.235880 0.426527
-0.378463 0.127767 0.454089
-0.385046 0.056905 0.498118
-0.374068 0.049953 0.405294
-0.271022 0.098818 0.289459
-0.182680 0.217988 0.292618
-0.225435 0.235809 0.318205
-0.177229 0.103515 0.463042
-0.175834 0.055640 0.486987
-0.183210 0.062875 0.440837
-0.226003 0.097193 0.366732
-0.251396 0.070201 0.393377
-0.234201 0.074576 0.326442
-0.223004 0.066314 0.353857
-0.186211 0.106789 0.245913
-0.151535 0.094840 0.253435
-0.195080 0.089425 0.287492
-0.162720 0.067083 0.227111
-0.196415 0.076298 0.212223
-0.180505 0.083889 0.141164
-0.246234 0.066099 0.131760
-0.282666 0.087223 0.081269
-0.340580 0.122366 0.117784
-0.376555 0.091363 0.111974
-0.393102 0.087543 0.417517
-0.297217 0.163487 0.549749
-0.362450 0.174227 0.634258
-0.323933 0.627863 0.231764
-0.327261 0.458545 0.128228
-0.345717 0.429564 0.187171
-0.260069 0.337062 0.335170
-0.306881 0.385334 0.293359
-0.271898 0.457259 0.215823
-0.259289 0.441347 0.303200
-0.363305 0.398019 0.291679
-0.291795 0.279053 0.324220
-0.294547 0.262771 0.399943
-0.371243 0.306137 0.366069
-0.382008 0.339743 0.307443
-0.438316 0.228950 0.367986
-0.537463 0.298231 0.257224
-0.645494 0.307091 0.289935
-0.669328 0.320508 0.177252
-0.616771 0.434999 0.131058
-0.565925 0.511230 0.217275
-0.568203 0.409220 0.089091
-0.577548 0.394258 0.217345
-0.648943 0.237348 0.200174
-0.599721 0.237036 0.256373
-0.754878 0.197561 0.266084
-0.714487 0.175657 0.200087
-0.710745 0.237411 0.165014
-0.720827 0.339743 0.072832
-0.545081 0.459358 0.071144
-0.346804 0.807739 0.104644
-0.216743 0.762837 0.120249
-0.197697 0.658146 0.387627
-0.165912 0.499878 0.549502
-0.241754 0.317091 0.529186
-0.169200 0.553212 0.416930
-0.320751 0.621112 0.366138
-0.337485 0.556049 0.269330
-0.250664 0.574848 0.514561
-0.140209 0.430307 0.459246
-0.162363 0.246323 0.477493
-0.381402 0.092797 0.469234
-0.459381 0.155970 0.481903
-0.442539 0.088546 0.414977
-0.408686 0.121373 0.498045
-0.329248 0.153610 0.482630
-0.331997 0.142511 0.315883
-0.221799 0.396419 0.292101
-0.176966 0.273274 0.211951
-0.203478 0.286430 0.129390
-0.216827 0.258314 0.184043
-0.234488 0.175930 0.313819
-0.311501 0.270429 0.211948
-0.294432 0.162487 0.229611
-0.329328 0.117112 0.277223
-0.416641 0.099298 0.274074
-0.554873 0.155235 0.201501
-0.569426 0.189358 0.155950
-0.539367 0.241198 0.105444
-0.501517 0.357700 0.084370
-0.545573 0.281564 0.125541
-0.514425 0.301811 0.096910
-0.460345 0.293995 0.114532
-0.487409 0.345311 0.229900
-0.412521 0.355808 0.145545
-0.509374 0.347915 0.128813
-0.629454 0.215821 0.104369
-0.658561 0.176420 0.084630
-0.700668 0.136656 0.112851
-0.667071 0.122890 0.157514
-0.612182 0.148628 0.155034
-0.539605 0.176739 0.090625
-0.590039 0.124542 0.106912
-0.629817 0.100757 0.139713
-0.604716 0.105384 0.173581
-0.720555 0.111138 0.330763
-0.245112 0.336634 0.265337
-0.226689 0.424271 0.348303
-0.329654 0.359100 0.261678
-0.379459 0.286999 0.299860
-0.342863 0.299943 0.318446
-0.330710 0.371149 0.198420
-0.285053 0.275836 0.238793
-0.361749 0.196487 0.281140
-0.406042 0.191956 0.297341
-0.445690 0.223770 0.237164
-0.393133 0.274606 0.262027
-0.544286 0.142320 0.276324
-0.619365 0.107015 0.281186
-0.607150 0.081004 0.243243
-0.678787 0.091345 0.263915
-0.734877 0.105834 0.242728
-0.694254 0.100473 0.181406
-0.758976 0.109087 0.167450
-0.565683 0.217978 0.071529
-0.445274 0.395501 0.058069
-0.484692 0.379794 0.062350
-0.214619 0.245836 0.117895
-0.246969 0.229441 0.150311
-0.385481 0.258270 0.151377
-0.353085 0.290950 0.141139
-0.535642 0.170306 0.146284
-0.446113 0.090546 0.161019
-0.348613 0.118759 0.163942
-0.256859 0.116937 0.175945
-0.095533 0.124223 0.128081
-0.104333 0.215306 0.075249
-0.100294 0.187881 0.135738
-0.148622 0.275139 0.167339
-0.078452 0.360587 0.329967
-0.127610 0.289917 0.238589
-0.148272 0.316966 0.121487
-0.085461 0.330668 0.163259
-0.142401 0.216090 0.250904
-0.175731 0.166076 0.233510
-0.152278 0.156198 0.181459
-0.193328 0.210638 0.148227
-0.207811 0.191064 0.188672
-0.296438 0.161485 0.325233
-0.306068 0.199688 0.322695
-0.342566 0.219355 0.346721
-0.291750 0.188465 0.494566
-0.352065 0.234211 0.491138
-0.383860 0.596099 0.458394
-0.386344 0.202868 0.380113
-0.399359 0.282461 0.474285
-0.322622 0.279134 0.358938
-0.347701 0.262331 0.223429
-0.424998 0.191838 0.164353
-0.451151 0.131623 0.217203
-0.456273 0.120859 0.149404
-0.490554 0.108928 0.157243
-0.517816 0.130242 0.142810
-0.500090 0.217505 0.103504
-0.514504 0.191274 0.118656
-0.554806 0.122508 0.163126
-0.442524 0.162708 0.199911
-0.388949 0.157852 0.109288
-0.504477 0.095186 0.125173
-0.477591 0.066576 0.138585
-0.452216 0.100773 0.107700
-0.485286 0.127587 0.074852
-0.488827 0.194629 0.066040
-0.426576 0.237428 0.067677
-0.340727 0.291206 0.061076
-0.243435 0.361855 0.071906
-0.382323 0.324483 0.098684
-0.414425 0.354228 0.048282
-0.401390 0.400107 0.040249
-0.403756 0.393196 0.073045
-0.357685 0.422727 0.054290
-0.376221 0.373641 0.056815
-0.334172 0.375680 0.054225
-0.296174 0.361326 0.050408
-0.326273 0.330339 0.064557
-0.420692 0.255904 0.094806
-0.421944 0.199537 0.068849
-0.326830 0.232006 0.153704
-0.301454 0.201485 0.233060
-0.258842 0.191789 0.343414
-0.294282 0.195861 0.362979
-0.286399 0.234317 0.360778
-0.319442 0.214047 0.274131
-0.333404 0.220264 0.204146
-0.386995 0.195077 0.182131
-0.404880 0.215968 0.423836
-0.477146 0.435211 0.260239
-0.532189 0.227684 0.146512
-0.568278 0.159946 0.110703
-0.605267 0.174809 0.088477
-0.624009 0.142924 0.112772
-0.652905 0.148818 0.139204
-0.714256 0.157313 0.148093
-0.720760 0.199261 0.080657
-0.741518 0.278514 0.083257
-0.566298 0.527298 0.062699
-0.445052 0.597589 0.130277
-0.526449 0.626948 0.074424
-0.801938 0.367141 0.075543
-0.916524 0.255963 0.112835
-0.645568 0.521635 0.064144
-0.608913 0.448818 0.064142
-0.629099 0.328544 0.099333
-0.620582 0.182449 0.132128
-0.590707 0.148356 0.186809
-0.543143 0.102875 0.300062
-0.527847 0.116107 0.336959
-0.499887 0.117763 0.297680
-0.508919 0.134512 0.236929
-0.531706 0.109558 0.239043
-0.541620 0.120673 0.208110
-0.517661 0.098274 0.183512
-0.449983 0.054085 0.247178
-0.575793 0.062186 0.355346
-0.489231 0.203337 0.380285
-0.340551 0.340643 0.414281
-0.210167 0.526078 0.337705
-0.284920 0.525512 0.222620
-0.208797 0.499630 0.207868
-0.267127 0.583546 0.176083
-0.228186 0.428672 0.171167
-0.258450 0.355455 0.160617
-0.273653 0.409657 0.120028
-0.264098 0.344696 0.111979
-0.222486 0.415597 0.112772
-0.199350 0.325482 0.185961
-0.294632 0.157878 0.367064
-0.346967 0.102272 0.381014
-0.324707 0.101328 0.346674
-0.300669 0.154767 0.427674
-0.297977 0.190730 0.402531
-0.322781 0.242743 0.378056
-0.419505 0.654624 0.200084
-0.318601 0.692538 0.162850
-0.178499 0.579044 0.270280
-0.195204 0.388057 0.398083
-0.241827 0.349617 0.379452
-0.315199 0.303795 0.489292
-0.380392 0.178450 0.504430
-0.414296 0.143625 0.555054
-0.339645 0.110851 0.633101
-0.315159 0.082478 0.583218
-0.337965 0.059219 0.531018
-0.321096 0.080831 0.498225
-0.307444 0.107476 0.461283
-0.278693 0.093535 0.490594
-0.252057 0.083619 0.514079
-0.224412 0.111350 0.505414
-0.169223 0.083911 0.512845
-0.208880 0.083504 0.402948
-0.187837 0.073111 0.335010
-0.206755 0.055269 0.311264
-0.156291 0.062835 0.298062
-0.156028 0.064082 0.415247
-0.129754 0.074279 0.474540
-0.183725 0.101044 0.375452
-0.181248 0.060180 0.378248
-0.178353 0.183494 0.547763
-0.303398 0.241676 0.322364
-0.263082 0.269825 0.205102
-0.295290 0.241493 0.251070
-0.310143 0.206645 0.446008
-0.249752 0.262630 0.261739
-0.225039 0.305225 0.344815
-0.153658 0.404495 0.314509
-0.142025 0.474338 0.358307
-0.228656 0.455858 0.431304
-0.360261 0.434834 0.461602
-0.432447 0.356868 0.399441
-0.405888 0.423867 0.341787
-0.307752 0.379122 0.354664
-0.495951 0.255588 0.098194
-0.590320 0.364141 0.130834
-0.523157 0.411325 0.142398
-0.622815 0.267082 0.098576
-0.586226 0.337718 0.086861
-0.396476 0.396958 0.127666
-0.278385 0.309875 0.439028
-0.210412 0.240403 0.530267
-0.142154 0.341782 0.515974
-0.236712 0.330636 0.302147
-0.313995 0.313085 0.102247
-0.536878 0.123790 0.095432
-0.546579 0.066696 0.222251
-0.528723 0.046496 0.288028
-0.490438 0.079978 0.328045
-0.416715 0.108530 0.389254
-0.350888 0.083964 0.417653
-0.307331 0.062124 0.473629
-0.274119 0.115537 0.597408
-0.226906 0.099518 0.609696
-0.147094 0.067376 0.550921
-0.178994 0.061997 0.585308
-0.132607 0.110425 0.587137
-0.110327 0.099682 0.549983
-0.068912 0.202205 0.534312
-0.065072 0.231313 0.620174
-0.080325 0.190639 0.689245
-0.127351 0.125355 0.674554
-0.110891 0.072596 0.663783
-0.097157 0.070549 0.589126
-0.106411 0.082418 0.509171
-0.125632 0.088198 0.439270
-0.126006 0.083980 0.396385
-0.144132 0.069483 0.352444
-0.105337 0.088013 0.358993
-0.119785 0.099438 0.312550
-0.070842 0.142954 0.331889
-0.071861 0.089577 0.402256
-0.108923 0.084005 0.258422
-0.092866 0.123378 0.193507
-0.088292 0.071041 0.315009
-0.063561 0.165270 0.420738
-0.074840 0.133173 0.262739
-0.089400 0.194231 0.262021
-0.079851 0.205849 0.344821
-0.157143 0.146865 0.421765
-0.125245 0.208011 0.414350
-0.174337 0.251983 0.396703
-0.084886 0.272191 0.354568
-0.110693 0.292372 0.436834
-0.211165 0.375835 0.619400
-0.062966 0.412899 0.552075
-0.081388 0.529721 0.443287
-0.081245 0.483334 0.304728
-0.138084 0.348639 0.182624
-0.103443 0.309738 0.080859
-0.104109 0.260851 0.123996
-0.091414 0.251910 0.196193
-0.076304 0.263206 0.278157
-0.134332 0.188036 0.301992
-0.107220 0.138757 0.409882
-0.128381 0.129478 0.471249
-0.160195 0.115412 0.544945
-0.191115 0.149126 0.609196
-0.184568 0.103795 0.587575
-0.248953 0.058854 0.636286
-0.192984 0.081624 0.751367
-0.220001 0.099182 0.668267
-0.223085 0.059316 0.689244
-0.276099 0.046871 0.774911
-0.314266 0.073942 0.676716
-0.296234 0.076044 0.626027
-0.279541 0.049108 0.565247
-0.285398 0.057887 0.519502
-0.243492 0.048975 0.483027
-0.309314 0.059143 0.435497
-0.387586 0.051625 0.354348
-0.397104 0.047268 0.326093
-0.434850 0.059475 0.193227
+++ /dev/null
-5 1024
-0.490574 0.255810 0.097016 0.668209 0.076176
-0.319657 0.377243 0.111246 0.519778 0.213532
-0.364308 0.499601 0.080493 0.524374 0.178250
-0.309691 0.486066 0.086872 0.593653 0.081516
-0.511878 0.227659 0.205762 0.464504 0.072641
-0.415877 0.221666 0.335610 0.566378 0.068611
-0.432793 0.262579 0.300716 0.456684 0.072810
-0.449945 0.126438 0.410080 0.461448 0.063356
-0.395672 0.238704 0.113056 0.471384 0.175583
-0.271033 0.349694 0.122549 0.405050 0.094055
-0.256025 0.401662 0.153103 0.446633 0.101411
-0.196597 0.467529 0.166464 0.498735 0.097213
-0.180138 0.381420 0.152389 0.514638 0.089537
-0.132744 0.304911 0.152650 0.583153 0.097649
-0.111190 0.161269 0.163283 0.673181 0.079189
-0.123015 0.112572 0.323074 0.592470 0.066637
-0.161118 0.095718 0.455233 0.767700 0.071090
-0.152146 0.098727 0.256718 0.969609 0.130922
-0.237523 0.116394 0.260363 0.787369 0.066436
-0.281553 0.534802 0.112685 0.153703 0.108972
-0.312479 0.447863 0.170904 0.228491 0.097052
-0.296432 0.346142 0.293149 0.331820 0.110852
-0.262549 0.297210 0.087733 0.729481 0.079176
-0.212710 0.412005 0.145571 0.599877 0.097017
-0.235745 0.381859 0.105728 0.701574 0.097767
-0.254355 0.439673 0.075854 0.633815 0.087595
-0.329609 0.416567 0.112711 0.634041 0.079475
-0.403396 0.432572 0.162376 0.571168 0.158567
-0.287614 0.474969 0.161406 0.563635 0.139393
-0.283025 0.497138 0.077927 0.607423 0.163092
-0.273090 0.543705 0.098977 0.570197 0.241298
-0.256126 0.457031 0.162645 0.688488 0.083656
-0.244353 0.541124 0.107308 0.612757 0.091303
-0.133591 0.529436 0.155266 0.589826 0.109966
-0.169031 0.424115 0.159383 0.621843 0.161686
-0.197216 0.289787 0.167090 0.636383 0.182529
-0.220826 0.159524 0.216292 0.685372 0.175210
-0.163352 0.133163 0.258336 0.707076 0.069078
-0.139154 0.127062 0.188384 0.887034 0.076588
-0.149980 0.129949 0.139695 1.099261 0.119098
-0.116969 0.248652 0.346785 0.563640 0.149677
-0.288434 0.390172 0.230976 0.523980 0.142045
-0.204095 0.265235 0.247311 0.729439 0.074811
-0.223184 0.193652 0.102042 0.585987 0.270676
-0.208143 0.120077 0.185902 0.646853 0.088698
-0.355403 0.111468 0.373144 0.782590 0.084255
-0.467759 0.441272 0.454529 0.331431 0.068101
-0.287421 0.457040 0.408663 0.482212 0.061728
-0.357332 0.423457 0.207750 0.647728 0.065810
-0.278780 0.374907 0.213186 0.898049 0.086156
-0.254920 0.512858 0.068783 0.832756 0.092460
-0.155053 0.504579 0.227236 0.724872 0.074763
-0.224304 0.592281 0.154800 0.708373 0.084213
-0.134061 0.649051 0.265649 0.518767 0.136752
-0.159119 0.597636 0.132300 0.544301 0.080443
-0.165326 0.584118 0.065722 0.501958 0.113312
-0.168393 0.605334 0.170032 0.442580 0.111346
-0.222994 0.617265 0.187848 0.353529 0.108058
-0.341928 0.566020 0.267172 0.250143 0.094590
-0.259273 0.480338 0.214658 0.296496 0.096477
-0.376071 0.427466 0.264839 0.212427 0.086437
-0.255428 0.467896 0.110450 0.239556 0.176526
-0.246442 0.283461 0.119163 0.266608 0.102263
-0.244230 0.220479 0.202744 0.193491 0.182223
-0.237905 0.265321 0.225608 0.313174 0.087490
-0.319376 0.102135 0.327013 0.263502 0.075298
-0.390918 0.172754 0.184723 0.394890 0.146035
-0.273313 0.346658 0.092567 0.641158 0.151283
-0.284128 0.499354 0.081163 0.466535 0.297221
-0.178627 0.505374 0.097332 0.391523 0.244837
-0.242389 0.479312 0.181425 0.323507 0.276699
-0.227955 0.434010 0.184932 0.350457 0.167121
-0.326553 0.127161 0.261385 0.230075 0.165213
-0.247641 0.152672 0.221240 0.220448 0.083136
-0.138131 0.168731 0.293988 0.150390 0.154272
-0.236984 0.179876 0.290894 0.126578 0.101180
-0.322888 0.120611 0.456483 0.246062 0.067720
-0.255233 0.111619 0.355633 0.185287 0.091429
-0.265851 0.149737 0.318600 0.149243 0.216703
-0.451118 0.128440 0.361694 0.171150 0.106107
-0.211707 0.286172 0.315759 0.241198 0.150374
-0.193664 0.323335 0.464691 0.210845 0.137824
-0.099896 0.302611 0.444419 0.202631 0.098263
-0.206293 0.199056 0.454382 0.228845 0.085913
-0.343607 0.108340 0.521050 0.409023 0.064294
-0.493453 0.123961 0.247355 0.447710 0.124726
-0.434770 0.143238 0.183864 0.561544 0.086875
-0.529629 0.148537 0.149009 0.473557 0.136178
-0.379057 0.132645 0.109105 0.638162 0.277237
-0.633604 0.264938 0.162909 0.497149 0.179863
-0.500831 0.188804 0.188785 0.614856 0.179411
-0.409058 0.293672 0.183466 0.539013 0.180347
-0.340943 0.260960 0.231356 0.682368 0.162876
-0.243558 0.350532 0.230302 0.638438 0.126011
-0.168147 0.405395 0.147416 0.723426 0.111308
-0.144733 0.493639 0.084317 0.806213 0.114733
-0.209375 0.447862 0.072831 0.678780 0.187683
-0.116793 0.292883 0.094540 0.405312 0.470496
-0.339386 0.369706 0.107212 0.183574 0.399445
-0.142545 0.519655 0.092104 0.423208 0.366382
-0.093719 0.480688 0.072510 0.700939 0.168728
-0.096498 0.393584 0.070223 0.528217 0.428409
-0.106946 0.213115 0.090222 0.645586 0.382829
-0.131374 0.284012 0.100010 0.696767 0.283433
-0.084860 0.378946 0.098026 0.591087 0.224287
-0.076065 0.390799 0.089447 0.556643 0.130491
-0.085384 0.299699 0.167066 0.530650 0.136243
-0.101110 0.275481 0.324362 0.407650 0.214664
-0.094439 0.210386 0.210643 0.534842 0.192886
-0.094551 0.323082 0.149016 0.523689 0.226975
-0.220485 0.335486 0.256500 0.409588 0.150207
-0.366839 0.298863 0.309801 0.490853 0.152025
-0.411901 0.248761 0.230634 0.405806 0.220158
-0.562388 0.230272 0.289954 0.326961 0.180335
-0.433963 0.388442 0.510615 0.183758 0.128993
-0.741497 0.175849 0.278972 0.290774 0.093210
-0.636737 0.297657 0.365424 0.301362 0.087897
-0.642858 0.381201 0.076680 0.397305 0.211904
-0.666816 0.294012 0.134119 0.575608 0.066802
-0.673901 0.374634 0.175412 0.431165 0.076339
-0.511508 0.520820 0.139574 0.514646 0.069956
-0.520418 0.676457 0.064624 0.566333 0.064221
-0.598325 0.523644 0.074044 0.596331 0.066797
-0.933498 0.193401 0.143854 0.384238 0.081501
-0.632041 0.309843 0.244221 0.175740 0.134154
-0.568536 0.196273 0.123632 0.141162 0.214852
-0.500738 0.214997 0.179596 0.229019 0.227366
-0.333126 0.392124 0.318250 0.149137 0.265740
-0.251055 0.458955 0.593244 0.208910 0.121161
-0.298473 0.125524 0.614986 0.207582 0.101533
-0.352024 0.191840 0.514194 0.250891 0.147019
-0.263760 0.133327 0.326719 0.550786 0.063452
-0.149142 0.305892 0.218217 0.537478 0.088693
-0.201858 0.412388 0.241794 0.422920 0.114007
-0.142398 0.414950 0.222849 0.474207 0.085970
-0.094251 0.497997 0.240920 0.516622 0.097808
-0.111682 0.520946 0.148676 0.474755 0.091833
-0.117734 0.589300 0.215125 0.270818 0.107284
-0.201989 0.494555 0.179351 0.388040 0.114157
-0.174398 0.484392 0.260266 0.320839 0.096003
-0.085306 0.348476 0.249229 0.368376 0.199297
-0.124532 0.461494 0.527860 0.212430 0.093418
-0.113723 0.376335 0.368746 0.324531 0.177288
-0.101162 0.363061 0.490114 0.290204 0.085286
-0.108277 0.250270 0.530634 0.258356 0.079511
-0.145081 0.134926 0.501157 0.371551 0.069207
-0.231306 0.116734 0.501041 0.513138 0.077657
-0.176259 0.097578 0.459134 0.613445 0.063998
-0.164468 0.189593 0.257897 0.610588 0.064585
-0.233804 0.306454 0.185793 0.265924 0.304463
-0.343128 0.231821 0.135908 0.350415 0.244677
-0.344263 0.124095 0.110467 0.582485 0.146492
-0.148671 0.504915 0.094415 0.664071 0.066676
-0.095715 0.618261 0.179292 0.545763 0.242356
-0.103474 0.514563 0.090244 0.614314 0.211560
-0.113099 0.514409 0.084701 0.508874 0.291824
-0.088297 0.564236 0.080256 0.490382 0.213520
-0.122914 0.581662 0.068764 0.592567 0.118286
-0.070668 0.514562 0.081542 0.627909 0.102380
-0.188592 0.486562 0.077089 0.549411 0.233297
-0.140458 0.532554 0.174729 0.513439 0.183895
-0.118377 0.435228 0.123578 0.665560 0.298307
-0.087854 0.611600 0.097721 0.686778 0.177549
-0.154595 0.699793 0.082366 0.692338 0.115191
-0.130325 0.640376 0.080435 0.569886 0.205270
-0.203456 0.576083 0.073822 0.525491 0.194465
-0.111898 0.687564 0.102749 0.541060 0.099285
-0.254521 0.662003 0.071248 0.479177 0.251266
-0.207296 0.627004 0.082830 0.633571 0.157024
-0.103953 0.665250 0.420705 0.548528 0.067388
-0.353493 0.620117 0.092475 0.520480 0.209522
-0.297252 0.650446 0.069155 0.659795 0.109539
-0.224459 0.631257 0.066952 0.780605 0.106404
-0.120831 0.603720 0.539876 0.453029 0.060154
-0.139273 0.198121 0.102822 0.995897 0.098301
-0.237263 0.579293 0.092012 0.327905 0.315070
-0.486273 0.391733 0.242175 0.149691 0.214426
-0.300339 0.132790 0.151137 0.165343 0.263675
-0.470234 0.207154 0.257271 0.118630 0.377311
-0.231404 0.184568 0.123060 0.224821 0.395590
-0.294403 0.259511 0.187609 0.423169 0.134765
-0.213429 0.150682 0.223072 0.282966 0.256916
-0.188239 0.250539 0.140391 0.362037 0.288466
-0.297488 0.272163 0.285020 0.322549 0.263203
-0.339489 0.234995 0.229447 0.188811 0.306166
-0.471108 0.316005 0.226394 0.317645 0.222039
-0.357586 0.365287 0.315209 0.372770 0.185823
-0.388093 0.277880 0.357906 0.315369 0.171751
-0.441160 0.240648 0.283512 0.163176 0.214520
-0.299201 0.396604 0.182789 0.317222 0.153875
-0.285743 0.424218 0.144479 0.364270 0.098407
-0.505903 0.165614 0.127044 0.254585 0.089779
-0.331316 0.102213 0.146285 0.374807 0.075771
-0.447060 0.119162 0.132109 0.378569 0.075195
-0.480053 0.196352 0.101594 0.402987 0.078775
-0.221052 0.566668 0.091514 0.406351 0.113527
-0.267701 0.491109 0.088210 0.449996 0.079021
-0.173590 0.667613 0.073920 0.479611 0.145941
-0.161590 0.750841 0.279513 0.400302 0.100640
-0.123252 0.448395 0.474747 0.539272 0.089969
-0.103201 0.404376 0.184240 0.701070 0.205018
-0.120487 0.369051 0.450877 0.702917 0.091539
-0.120387 0.210856 0.422533 0.626951 0.069784
-0.133489 0.337866 0.586816 0.462600 0.061741
-0.155228 0.099643 0.613974 0.677822 0.065653
-0.238915 0.114730 0.285524 0.886174 0.107992
-0.097758 0.288300 0.175006 0.323226 0.380635
-0.193016 0.396803 0.125995 0.371597 0.302987
-0.328241 0.351932 0.169485 0.365731 0.247671
-0.359390 0.296631 0.073742 0.434952 0.226132
-0.345670 0.369745 0.178296 0.422139 0.159520
-0.271279 0.469466 0.244005 0.447820 0.207990
-0.361580 0.120094 0.215775 0.878268 0.160090
-0.277345 0.128469 0.186375 0.989875 0.070807
-0.298700 0.442492 0.085352 0.812309 0.072085
-0.141086 0.576619 0.235677 0.648656 0.116102
-0.092415 0.551379 0.171369 0.413082 0.246634
-0.112362 0.648358 0.192381 0.371821 0.209130
-0.085349 0.673175 0.083715 0.356861 0.212484
-0.109528 0.672834 0.079353 0.454863 0.227345
-0.314176 0.472511 0.109010 0.378621 0.221648
-0.473822 0.407882 0.096108 0.180136 0.258137
-0.339014 0.658837 0.128012 0.208939 0.304361
-0.404801 0.486071 0.173029 0.140185 0.331012
-0.522218 0.309443 0.134996 0.162711 0.355239
-0.239218 0.564177 0.134663 0.133921 0.234046
-0.132066 0.791260 0.218037 0.140401 0.260218
-0.121835 0.666346 0.256077 0.131259 0.288536
-0.101989 0.541072 0.298054 0.124917 0.349203
-0.088976 0.393531 0.316070 0.143252 0.341282
-0.101393 0.320009 0.436810 0.118405 0.346214
-0.115633 0.286281 0.212116 0.159512 0.497827
-0.286947 0.279577 0.227044 0.122089 0.428814
-0.086166 0.333882 0.763682 0.106719 0.492366
-0.112629 0.187606 0.582205 0.157566 0.435087
-0.129445 0.192272 0.407708 0.144958 0.241631
-0.384213 0.153504 0.435697 0.181808 0.317005
-0.211711 0.272203 0.553356 0.303220 0.107653
-0.278393 0.274678 0.378365 0.392714 0.164314
-0.249986 0.217448 0.464347 0.456336 0.080569
-0.344974 0.497950 0.330937 0.337593 0.148443
-0.222730 0.448762 0.331648 0.395038 0.111948
-0.278511 0.448111 0.197387 0.487487 0.068759
-0.284545 0.587071 0.190442 0.450325 0.120815
-0.242897 0.540770 0.089529 0.528286 0.099731
-0.311484 0.576470 0.068708 0.572142 0.102919
-0.356067 0.502825 0.078341 0.695153 0.078752
-0.394819 0.429408 0.088022 0.731616 0.077904
-0.401981 0.374078 0.083607 0.460834 0.178060
-0.342091 0.485245 0.075656 0.425769 0.148694
-0.301302 0.522671 0.160822 0.379160 0.087694
-0.394884 0.535562 0.385186 0.169599 0.171204
-0.467932 0.533984 0.233680 0.290672 0.197333
-0.567897 0.202538 0.121919 0.562827 0.077447
-0.498173 0.336008 0.085433 0.608275 0.067929
-0.402247 0.498935 0.083195 0.569731 0.083813
-0.228445 0.525870 0.229214 0.550628 0.084302
-0.269995 0.522327 0.080030 0.468787 0.181821
-0.494799 0.454542 0.075562 0.510643 0.220302
-0.536191 0.294448 0.089924 0.469042 0.180989
-0.433882 0.313513 0.088848 0.567754 0.161336
-0.400192 0.334434 0.148995 0.538420 0.081007
-0.419312 0.469218 0.252292 0.325453 0.093272
-0.309433 0.619520 0.206890 0.291754 0.215947
-0.312741 0.555786 0.245782 0.366817 0.173692
-0.500191 0.370349 0.087660 0.386210 0.176883
-0.696041 0.382472 0.085830 0.228362 0.231409
-0.704156 0.170202 0.121273 0.150301 0.291043
-0.602824 0.191671 0.096937 0.161816 0.434180
-0.903506 0.230343 0.082074 0.187722 0.125128
-0.384170 0.375233 0.115102 0.222496 0.118075
-0.128983 0.707425 0.176360 0.164154 0.159361
-0.084548 0.571038 0.097687 0.305940 0.187860
-0.128042 0.606879 0.092465 0.348941 0.137691
-0.095473 0.678141 0.122052 0.341624 0.111983
-0.090864 0.562484 0.088849 0.394831 0.185360
-0.123849 0.507637 0.079890 0.464565 0.178220
-0.122564 0.410094 0.102049 0.484462 0.294573
-0.229321 0.286865 0.188570 0.513885 0.106524
-0.147548 0.389244 0.179789 0.595543 0.054525
-0.181343 0.199067 0.143642 0.709901 0.067120
-0.133527 0.236448 0.220785 0.640310 0.205873
-0.146697 0.228089 0.427444 0.399805 0.142999
-0.135772 0.124591 0.354606 0.626347 0.194995
-0.174970 0.096177 0.360896 0.773055 0.151537
-0.129752 0.123873 0.231596 0.762722 0.226311
-0.094786 0.206587 0.093236 0.497512 0.446528
-0.110523 0.170676 0.101314 0.773611 0.319170
-0.112312 0.176026 0.473699 0.522928 0.170826
-0.257136 0.158335 0.510015 0.385679 0.194140
-0.103087 0.529797 0.416572 0.184552 0.117677
-0.169263 0.371936 0.191937 0.292095 0.125469
-0.297466 0.238101 0.136424 0.387694 0.074518
-0.237761 0.211913 0.172642 0.307723 0.149041
-0.201199 0.252732 0.258414 0.281538 0.155626
-0.347975 0.190591 0.195409 0.286847 0.181540
-0.274058 0.298589 0.091129 0.426866 0.191629
-0.246536 0.278837 0.188331 0.411223 0.079774
-0.113327 0.424052 0.099892 0.495951 0.078924
-0.083116 0.564109 0.181962 0.428562 0.120069
-0.083834 0.498604 0.109611 0.332854 0.102921
-0.080710 0.451451 0.161543 0.440414 0.171509
-0.074355 0.465288 0.122748 0.363411 0.173461
-0.092007 0.488316 0.112396 0.280348 0.179377
-0.084620 0.407361 0.122379 0.357813 0.245605
-0.089475 0.498801 0.099468 0.365981 0.248221
-0.078040 0.536380 0.132965 0.250027 0.261269
-0.108924 0.502718 0.178496 0.323830 0.329518
-0.088507 0.572954 0.225507 0.304754 0.224929
-0.124548 0.590063 0.104624 0.315887 0.265646
-0.104299 0.717161 0.203711 0.278911 0.212791
-0.181081 0.726864 0.076367 0.381984 0.224228
-0.232249 0.709155 0.127219 0.291505 0.249139
-0.319579 0.712186 0.082794 0.380234 0.227925
-0.266859 0.759329 0.077150 0.503108 0.110534
-0.250604 0.853961 0.094041 0.316646 0.218562
-0.158680 0.868187 0.085373 0.580488 0.108664
-0.203564 0.899781 0.104219 0.435037 0.158907
-0.180082 0.736011 0.170314 0.446979 0.114729
-0.442348 0.574640 0.061388 0.635575 0.080820
-0.485214 0.465943 0.072348 0.674169 0.104751
-0.452473 0.474026 0.090702 0.423456 0.124520
-0.536765 0.407861 0.214815 0.315424 0.114424
-0.387891 0.385258 0.234788 0.322837 0.159279
-0.424436 0.245501 0.234072 0.260119 0.112615
-0.433081 0.234628 0.164498 0.349419 0.092404
-0.589196 0.169146 0.182072 0.288234 0.094524
-0.642431 0.145496 0.163391 0.402251 0.167644
-0.241206 0.720484 0.268696 0.302572 0.105894
-0.227208 0.516362 0.297669 0.263151 0.217841
-0.157823 0.505412 0.209992 0.327272 0.208331
-0.188918 0.567152 0.287327 0.404316 0.221471
-0.117589 0.482686 0.417164 0.306122 0.096026
-0.096426 0.452399 0.451314 0.293387 0.256610
-0.224454 0.127500 0.532287 0.238199 0.324602
-0.135876 0.144824 0.324903 0.322635 0.438443
-0.260561 0.170798 0.211409 0.355245 0.375861
-0.241357 0.129124 0.400639 0.276088 0.218756
-0.199518 0.259911 0.381201 0.324165 0.197395
-0.251235 0.377989 0.344902 0.270364 0.211865
-0.291296 0.384935 0.422781 0.294449 0.090980
-0.395823 0.365064 0.344755 0.415986 0.084583
-0.386477 0.248849 0.455442 0.365781 0.088672
-0.458033 0.155479 0.426783 0.280998 0.145175
-0.531981 0.141346 0.329938 0.252887 0.250131
-0.374946 0.268161 0.075505 0.510520 0.332301
-0.184531 0.374438 0.194028 0.517563 0.214417
-0.147560 0.465804 0.195189 0.428052 0.176505
-0.148334 0.523244 0.128330 0.361610 0.151203
-0.077690 0.465213 0.245172 0.390288 0.240527
-0.086426 0.430840 0.330699 0.420341 0.124550
-0.112022 0.345300 0.269904 0.488879 0.216281
-0.124982 0.372020 0.199492 0.426906 0.295323
-0.090183 0.350995 0.106602 0.430935 0.379114
-0.082426 0.406537 0.203467 0.310012 0.281593
-0.097489 0.660568 0.359241 0.290708 0.157249
-0.225098 0.605767 0.361924 0.359285 0.082358
-0.132418 0.382778 0.252320 0.761284 0.075589
-0.094659 0.441486 0.188296 0.651609 0.091024
-0.105780 0.329945 0.175481 0.666592 0.136558
-0.089106 0.324847 0.402205 0.426529 0.076884
-0.104303 0.249418 0.358039 0.353634 0.090345
-0.097984 0.107847 0.191108 0.634878 0.146858
-0.108646 0.138888 0.147686 0.762312 0.116913
-0.212705 0.171260 0.283930 0.262645 0.181071
-0.163478 0.208128 0.156460 0.271129 0.174478
-0.139789 0.152510 0.124415 0.248322 0.322683
-0.135948 0.126114 0.118662 0.442261 0.258146
-0.269052 0.117807 0.240510 0.315434 0.077056
-0.272173 0.190742 0.228064 0.380147 0.091157
-0.093206 0.405534 0.219163 0.416979 0.109899
-0.079579 0.352146 0.301267 0.545994 0.090767
-0.084397 0.359349 0.118580 0.517250 0.074602
-0.142924 0.375509 0.104248 0.557536 0.080598
-0.078233 0.435400 0.149153 0.515426 0.089637
-0.110687 0.467759 0.349990 0.600145 0.085545
-0.100132 0.551704 0.325140 0.370687 0.141516
-0.181971 0.519689 0.286529 0.452168 0.096892
-0.159153 0.383139 0.297630 0.360105 0.077438
-0.183481 0.283365 0.129323 0.656147 0.069784
-0.220018 0.182682 0.385213 0.555811 0.084366
-0.231995 0.281431 0.313643 0.520252 0.082302
-0.240791 0.233989 0.320275 0.403334 0.084817
-0.171626 0.210184 0.395140 0.301540 0.074726
-0.123974 0.217388 0.372344 0.199194 0.098678
-0.094207 0.340277 0.342699 0.229163 0.094361
-0.185288 0.230262 0.262745 0.200532 0.102872
-0.095962 0.264991 0.227913 0.202329 0.177991
-0.080476 0.352796 0.139512 0.208977 0.227863
-0.275940 0.222441 0.111305 0.254747 0.156578
-0.165298 0.474978 0.192185 0.235092 0.135086
-0.233131 0.392950 0.157143 0.269425 0.156572
-0.298527 0.302925 0.133842 0.506002 0.132732
-0.241454 0.398460 0.084375 0.494325 0.234749
-0.159631 0.421398 0.092589 0.413926 0.179796
-0.158224 0.418616 0.283534 0.367067 0.205082
-0.412365 0.395342 0.111344 0.328391 0.244173
-0.731001 0.188693 0.218000 0.439587 0.059263
-0.745998 0.200881 0.187697 0.535200 0.060072
-0.469681 0.181024 0.087472 0.556582 0.163565
-0.441174 0.437510 0.095320 0.502861 0.077980
-0.322936 0.728585 0.177880 0.361976 0.127210
-0.548711 0.485972 0.114597 0.398005 0.088237
-0.610200 0.296764 0.238908 0.322896 0.084667
-0.592628 0.345184 0.098471 0.562811 0.087139
-0.560240 0.449189 0.083091 0.579717 0.093314
-0.663473 0.368021 0.076482 0.477615 0.079947
-0.840453 0.162820 0.244379 0.383785 0.063482
-0.912157 0.172957 0.256442 0.240074 0.091406
-0.834827 0.322582 0.132713 0.399434 0.066227
-0.874296 0.227941 0.130581 0.534307 0.055764
-0.781475 0.321342 0.090938 0.519094 0.079899
-0.710368 0.431864 0.099467 0.532623 0.068002
-0.383525 0.718920 0.099055 0.461407 0.121495
-0.321455 0.825089 0.079595 0.427568 0.108507
-0.462084 0.596965 0.071969 0.517949 0.100383
-0.621282 0.471919 0.098704 0.478693 0.075515
-0.776229 0.441476 0.101458 0.413008 0.071570
-1.055603 0.281500 0.098804 0.330063 0.056286
-0.771298 0.184425 0.130775 0.291681 0.117787
-0.665328 0.260827 0.103040 0.287881 0.123419
-0.664697 0.240922 0.136388 0.447161 0.065891
-0.414409 0.353609 0.145744 0.442868 0.087314
-0.340256 0.437220 0.091053 0.510486 0.092269
-0.288764 0.365145 0.080428 0.571963 0.079355
-0.256452 0.463354 0.070186 0.524028 0.128702
-0.171512 0.504065 0.086462 0.532869 0.092264
-0.090054 0.543273 0.088797 0.502580 0.106631
-0.114850 0.462977 0.076917 0.569930 0.177260
-0.151671 0.397556 0.095758 0.505144 0.181704
-0.192648 0.353679 0.095802 0.575344 0.156084
-0.235208 0.332379 0.146583 0.514241 0.063492
-0.297139 0.344976 0.192100 0.465214 0.077665
-0.344994 0.271830 0.170591 0.477851 0.069874
-0.378705 0.252593 0.253455 0.525208 0.074234
-0.422686 0.223283 0.163494 0.463124 0.074401
-0.536741 0.207841 0.375674 0.335239 0.080770
-0.576205 0.121946 0.482428 0.189663 0.122584
-0.676912 0.137942 0.410135 0.303729 0.052162
-0.500812 0.275746 0.395759 0.178866 0.106177
-0.185855 0.153489 0.402933 0.141660 0.119752
-0.347855 0.262387 0.216402 0.262314 0.088094
-0.394245 0.275682 0.213007 0.425591 0.126433
-0.280260 0.257848 0.091658 0.697149 0.196117
-0.285112 0.250968 0.090577 0.843502 0.109028
-0.319921 0.257047 0.092162 0.768396 0.316052
-0.355869 0.267076 0.091597 0.198027 0.510532
-0.307895 0.345189 0.078152 0.344043 0.358648
-0.221846 0.299984 0.112351 0.523762 0.364610
-0.291795 0.410895 0.105575 0.603179 0.258227
-0.283089 0.424032 0.071178 0.791398 0.180963
-0.404844 0.302286 0.101039 0.708910 0.163041
-0.358318 0.318550 0.090435 0.516159 0.065090
-0.298166 0.435765 0.229621 0.406055 0.118523
-0.368986 0.384758 0.217436 0.396128 0.086725
-0.411213 0.354891 0.234282 0.497014 0.084281
-0.307657 0.332725 0.287959 0.434842 0.080152
-0.337856 0.231898 0.120082 0.591233 0.069187
-0.346355 0.263461 0.225771 0.624157 0.064656
-0.418261 0.188590 0.138241 0.691730 0.068140
-0.618168 0.133250 0.084086 0.594058 0.182457
-0.715131 0.240256 0.105083 0.675577 0.056648
-0.591409 0.161581 0.158443 0.842515 0.108974
-0.350607 0.231988 0.112984 0.202511 0.203101
-0.300281 0.425813 0.103862 0.158493 0.225605
-0.104868 0.621079 0.312459 0.141264 0.161945
-0.192814 0.214042 0.244105 0.366775 0.176633
-0.270326 0.120168 0.205289 0.345302 0.166367
-0.339007 0.134562 0.326535 0.353717 0.199303
-0.427795 0.117156 0.172565 0.516587 0.227170
-0.303780 0.139461 0.275676 0.533802 0.207780
-0.394670 0.130774 0.425867 0.442357 0.201882
-0.216763 0.191531 0.366565 0.479326 0.214174
-0.097217 0.120156 0.107590 0.582121 0.222583
-0.167975 0.157098 0.292665 0.513619 0.084077
-0.163339 0.318464 0.335679 0.453557 0.139234
-0.081592 0.386785 0.081896 0.495806 0.213491
-0.088051 0.370484 0.160735 0.432777 0.204573
-0.074725 0.459123 0.090166 0.429763 0.124912
-0.188613 0.370441 0.104341 0.400017 0.082281
-0.347630 0.196574 0.073723 0.441321 0.077130
-0.329961 0.342811 0.083976 0.423968 0.090995
-0.217172 0.345686 0.084780 0.488087 0.101164
-0.406673 0.272249 0.098395 0.420694 0.091348
-0.385704 0.257156 0.070908 0.324285 0.105747
-0.274677 0.268878 0.080441 0.343145 0.135384
-0.250038 0.175672 0.106202 0.368802 0.097441
-0.163520 0.411919 0.100421 0.243085 0.147996
-0.074293 0.397642 0.107317 0.290996 0.193865
-0.161399 0.337870 0.098872 0.320589 0.165900
-0.086900 0.354661 0.109703 0.286976 0.095093
-0.090251 0.377230 0.113555 0.402994 0.083618
-0.076344 0.263634 0.109835 0.339987 0.222795
-0.084522 0.203422 0.107145 0.507916 0.209607
-0.112317 0.197961 0.147767 0.392846 0.191935
-0.160377 0.138381 0.146411 0.382843 0.119865
-0.096779 0.236364 0.158125 0.406405 0.074097
-0.071278 0.230916 0.124923 0.333671 0.128043
-0.076867 0.314226 0.120144 0.280011 0.169668
-0.084828 0.426814 0.229878 0.183948 0.187964
-0.091915 0.578979 0.157955 0.193695 0.165487
-0.147362 0.515345 0.097774 0.255679 0.120270
-0.216319 0.147567 0.200703 0.134818 0.226775
-0.345195 0.373533 0.190523 0.148016 0.092224
-0.403999 0.182963 0.122107 0.207890 0.107122
-0.249797 0.156173 0.137234 0.199544 0.131932
-0.097153 0.250759 0.139250 0.232362 0.211991
-0.190336 0.293021 0.114678 0.197947 0.120045
-0.289001 0.303379 0.111096 0.135843 0.150785
-0.299836 0.298154 0.133264 0.198659 0.093498
-0.267982 0.369040 0.186695 0.239136 0.091856
-0.225610 0.405658 0.103119 0.157298 0.093425
-0.210233 0.359038 0.183413 0.172165 0.094590
-0.232533 0.285959 0.226716 0.138425 0.102607
-0.251807 0.114231 0.225196 0.169145 0.130262
-0.196681 0.131629 0.290550 0.249612 0.088731
-0.243067 0.127312 0.146654 0.308179 0.085049
-0.338559 0.140278 0.100978 0.301595 0.106500
-0.219595 0.467497 0.081582 0.359391 0.125808
-0.147560 0.414328 0.163898 0.351622 0.173962
-0.097265 0.497791 0.227591 0.352834 0.128111
-0.103010 0.462785 0.310935 0.245591 0.122244
-0.082383 0.388077 0.185504 0.343316 0.137526
-0.088990 0.438568 0.203709 0.270278 0.109601
-0.099761 0.329199 0.149830 0.304031 0.249088
-0.091143 0.326604 0.291538 0.334291 0.120320
-0.091393 0.351780 0.234918 0.254151 0.169727
-0.088636 0.262717 0.274724 0.281853 0.219807
-0.110626 0.219733 0.372703 0.291122 0.240271
-0.147262 0.193514 0.282718 0.166328 0.348140
-0.215753 0.283606 0.338510 0.204902 0.290646
-0.249265 0.660090 0.308265 0.154668 0.214312
-0.184237 0.457150 0.358988 0.155031 0.226845
-0.085928 0.461941 0.313838 0.233675 0.235701
-0.152277 0.546282 0.244499 0.213061 0.206098
-0.127947 0.626109 0.242087 0.241094 0.281851
-0.185087 0.648682 0.147192 0.192190 0.316338
-0.126523 0.730039 0.358042 0.122395 0.193527
-0.099402 0.293812 0.455058 0.219881 0.194990
-0.140126 0.121216 0.447204 0.462855 0.285712
-0.130693 0.092146 0.402485 0.902334 0.103806
-0.186313 0.103913 0.515406 0.626164 0.194363
-0.130862 0.133525 0.578230 0.495540 0.065482
-0.133112 0.171137 0.648298 0.374117 0.238776
-0.117563 0.253110 0.632193 0.195934 0.100484
-0.123787 0.147417 0.506314 0.292581 0.258762
-0.191351 0.125634 0.488336 0.276781 0.084991
-0.095634 0.433137 0.500180 0.133656 0.153654
-0.113082 0.343094 0.432986 0.128759 0.218562
-0.082603 0.429341 0.351512 0.117175 0.223189
-0.088047 0.371923 0.239395 0.216084 0.264315
-0.093190 0.278617 0.297918 0.134469 0.258214
-0.104852 0.260763 0.390849 0.137838 0.152196
-0.220196 0.210581 0.386651 0.207171 0.180526
-0.185770 0.244580 0.310431 0.129160 0.205549
-0.352853 0.158613 0.396338 0.160413 0.161804
-0.623161 0.135729 0.281111 0.641385 0.060850
-0.601179 0.235528 0.147420 0.676282 0.075378
-0.237210 0.512938 0.081247 0.719764 0.100476
-0.313619 0.398199 0.084859 0.727021 0.072137
-0.415154 0.318599 0.086411 0.844552 0.074841
-0.414193 0.186697 0.133621 1.003991 0.090317
-0.525046 0.126708 0.158060 0.656220 0.071292
-0.506539 0.199293 0.222064 0.594940 0.056127
-0.588419 0.116726 0.374361 0.494496 0.062444
-0.587909 0.161096 0.247685 0.508021 0.074031
-0.427260 0.175283 0.161764 0.797938 0.081903
-0.365955 0.293527 0.113142 0.712024 0.075121
-0.516236 0.390842 0.077007 0.770221 0.074317
-0.629270 0.381192 0.082654 0.659143 0.069191
-0.364438 0.389905 0.093220 0.651788 0.157496
-0.367133 0.364451 0.097770 0.526551 0.125794
-0.459416 0.189986 0.121752 0.328420 0.198173
-0.234904 0.434831 0.196421 0.214213 0.123432
-0.245564 0.355295 0.178844 0.420738 0.184541
-0.263115 0.415513 0.093895 0.437966 0.145018
-0.264263 0.395578 0.086908 0.349500 0.200286
-0.200094 0.352862 0.173362 0.435563 0.108616
-0.258514 0.266984 0.097829 0.451154 0.078365
-0.289789 0.173100 0.193328 0.613342 0.066761
-0.384511 0.117381 0.144745 0.493977 0.060918
-0.321287 0.136297 0.206007 0.449189 0.084129
-0.371064 0.120061 0.244529 0.348665 0.075581
-0.383605 0.111685 0.372188 0.378829 0.087538
-0.174528 0.200500 0.203880 0.536189 0.097704
-0.226423 0.256017 0.201538 0.593869 0.082507
-0.275188 0.339960 0.203946 0.219877 0.162736
-0.239492 0.288304 0.090042 0.261673 0.213821
-0.152091 0.224078 0.126405 0.603417 0.175553
-0.176378 0.304695 0.087618 0.592353 0.084284
-0.261868 0.265799 0.100472 0.563239 0.093167
-0.181788 0.305669 0.102111 0.450140 0.211949
-0.076788 0.312046 0.114906 0.383016 0.181321
-0.072498 0.327165 0.105074 0.455708 0.110841
-0.083842 0.251487 0.120489 0.439817 0.158393
-0.086221 0.273512 0.110497 0.497088 0.076061
-0.076690 0.290120 0.088018 0.513515 0.185343
-0.091149 0.246724 0.119248 0.584019 0.114931
-0.085559 0.311584 0.084386 0.550846 0.106859
-0.080454 0.396575 0.093437 0.473853 0.136830
-0.089353 0.382071 0.099052 0.396226 0.157854
-0.210887 0.219290 0.116425 0.362522 0.187150
-0.176967 0.255448 0.117574 0.310020 0.105187
-0.392418 0.212007 0.286555 0.188339 0.092884
-0.344965 0.265505 0.225226 0.147488 0.106140
-0.148182 0.138167 0.388457 0.241265 0.112270
-0.197373 0.131937 0.283996 0.356406 0.073471
-0.246375 0.146284 0.127800 0.282946 0.226409
-0.358012 0.189491 0.156340 0.352246 0.069082
-0.214274 0.363392 0.245513 0.331406 0.119490
-0.093232 0.409989 0.395607 0.166468 0.122107
-0.122065 0.552656 0.460436 0.115372 0.181968
-0.119270 0.602676 0.580138 0.247072 0.071915
-0.334314 0.212124 0.245339 0.411184 0.082342
-0.344198 0.199682 0.197387 0.518104 0.126800
-0.298611 0.364076 0.155972 0.575893 0.099503
-0.249879 0.405878 0.103603 0.526826 0.095430
-0.182662 0.493723 0.079858 0.462683 0.135075
-0.088535 0.619266 0.100563 0.470730 0.132925
-0.179689 0.598357 0.088681 0.428125 0.225276
-0.212633 0.682527 0.086947 0.395939 0.110870
-0.205101 0.610063 0.096655 0.347915 0.205010
-0.141822 0.680363 0.091759 0.366814 0.325419
-0.183195 0.776576 0.114337 0.241439 0.329250
-0.103939 0.739682 0.143415 0.164819 0.345811
-0.137855 0.630401 0.110674 0.287816 0.446019
-0.098682 0.470697 0.132827 0.178435 0.516442
-0.074890 0.379911 0.133316 0.243811 0.351980
-0.091414 0.591116 0.077867 0.401649 0.277337
-0.063991 0.510720 0.066415 0.526174 0.171061
-0.091198 0.309140 0.103600 0.535669 0.316638
-0.093317 0.258841 0.100346 0.744677 0.085006
-0.080710 0.302136 0.098014 0.638831 0.098723
-0.099287 0.309662 0.104631 0.597698 0.172054
-0.100144 0.233660 0.127926 0.674948 0.122933
-0.083106 0.258737 0.105127 0.603675 0.247173
-0.124688 0.224305 0.100198 0.797080 0.214990
-0.109656 0.200220 0.109010 0.854398 0.092044
-0.131654 0.161230 0.126313 0.923489 0.222156
-0.108983 0.212933 0.237962 0.732235 0.084731
-0.124876 0.316481 0.280211 0.621265 0.084670
-0.291151 0.156039 0.169693 0.788326 0.062107
-0.363626 0.144241 0.273635 0.576773 0.063353
-0.246209 0.111402 0.411881 0.431162 0.073653
-0.187427 0.214392 0.248322 0.426410 0.096999
-0.259263 0.391515 0.214924 0.345257 0.090006
-0.265809 0.325254 0.241771 0.283388 0.095075
-0.360417 0.278085 0.304761 0.236391 0.060111
-0.244583 0.277639 0.307198 0.298215 0.100785
-0.190750 0.300193 0.350348 0.158056 0.096414
-0.314417 0.242688 0.380630 0.164618 0.096062
-0.243765 0.206741 0.354691 0.248322 0.088520
-0.177022 0.234262 0.293393 0.331888 0.093099
-0.161817 0.331698 0.255844 0.286339 0.110281
-0.278399 0.284033 0.185269 0.305259 0.184203
-0.385992 0.480594 0.173432 0.378859 0.153632
-0.184090 0.115317 0.748681 0.378734 0.060556
-0.151586 0.107061 0.742021 0.535618 0.051151
-0.332921 0.095413 0.513180 0.645978 0.059463
-0.258027 0.096049 0.611288 0.535843 0.059083
-0.247584 0.121388 0.614788 0.370232 0.077324
-0.169111 0.140849 0.604788 0.239980 0.095216
-0.111607 0.322529 0.542365 0.168161 0.109291
-0.241876 0.305289 0.439888 0.120248 0.200225
-0.284239 0.394417 0.251394 0.244455 0.193399
-0.147939 0.165823 0.154594 0.167245 0.301729
-0.181518 0.161729 0.146628 0.202260 0.206488
-0.212973 0.328934 0.129941 0.155031 0.247663
-0.102294 0.362696 0.130871 0.170694 0.124880
-0.213580 0.332469 0.270053 0.226216 0.097265
-0.452215 0.241818 0.093796 0.538977 0.071308
-0.489047 0.360411 0.090544 0.488290 0.081715
-0.552862 0.219107 0.213786 0.398709 0.155961
-0.437694 0.412404 0.209319 0.437276 0.195087
-0.199286 0.644714 0.440653 0.212028 0.096342
-0.287744 0.341997 0.207514 0.385949 0.117592
-0.263774 0.439511 0.269147 0.341149 0.172563
-0.454161 0.381508 0.331847 0.268151 0.152272
-0.498290 0.289594 0.304899 0.362633 0.106732
-0.481679 0.328798 0.222406 0.397769 0.104606
-0.346873 0.440248 0.129990 0.443019 0.087516
-0.380155 0.530965 0.097578 0.409382 0.082665
-0.321254 0.579714 0.089049 0.390589 0.201519
-0.362547 0.576427 0.085672 0.491626 0.104850
-0.276854 0.642201 0.083025 0.467384 0.121062
-0.273630 0.663476 0.158964 0.548773 0.087067
-0.373979 0.679628 0.060478 0.566170 0.089921
-0.231054 0.689868 0.075141 0.554939 0.121992
-0.131352 0.746985 0.224259 0.632082 0.114206
-0.122786 0.768200 0.082348 0.539275 0.195919
-0.109772 0.815210 0.139772 0.362727 0.266362
-0.104772 0.856439 0.113332 0.232571 0.246206
-0.120584 0.754666 0.080447 0.429169 0.118502
-0.129558 0.791075 0.105915 0.315074 0.120715
-0.471551 0.424768 0.106094 0.298460 0.095269
-0.554926 0.269653 0.080730 0.240918 0.109021
-0.715432 0.175592 0.151435 0.182408 0.123486
-0.137564 0.237719 0.187711 0.139854 0.135833
-0.094527 0.273567 0.286247 0.168053 0.115917
-0.167637 0.157429 0.212566 0.193778 0.120081
-0.336811 0.142407 0.179532 0.175920 0.143067
-0.359984 0.220774 0.139955 0.276172 0.088412
-0.229300 0.314626 0.202672 0.266918 0.121818
-0.254903 0.239660 0.205666 0.231586 0.089226
-0.167122 0.146638 0.180676 0.284930 0.110311
-0.343078 0.188097 0.234475 0.241020 0.085210
-0.453742 0.129229 0.238583 0.231887 0.093298
-0.339970 0.125720 0.278618 0.183409 0.087075
-0.340525 0.112000 0.203560 0.267435 0.074552
-0.421266 0.136001 0.163313 0.278632 0.077810
-0.231080 0.342813 0.163037 0.331660 0.151451
-0.219435 0.349874 0.194108 0.374829 0.093483
-0.192275 0.378257 0.132811 0.343050 0.103414
-0.110721 0.427391 0.100405 0.325509 0.111209
-0.146685 0.286203 0.121744 0.415444 0.104287
-0.140158 0.355739 0.095810 0.450215 0.085634
-0.169104 0.279898 0.130179 0.506051 0.078620
-0.182052 0.216413 0.119325 0.576246 0.074259
-0.225160 0.129927 0.259427 0.435333 0.063882
-0.269429 0.222859 0.221923 0.506932 0.072807
-0.178884 0.213869 0.166680 0.458615 0.073113
-0.173590 0.299930 0.242906 0.454873 0.075763
-0.100242 0.268104 0.176813 0.481588 0.072095
-0.090237 0.243244 0.251971 0.381230 0.134740
-0.115219 0.162206 0.219459 0.448797 0.139604
-0.153424 0.114968 0.426394 0.484294 0.069918
-0.340250 0.102354 0.415558 0.530027 0.067470
-0.463554 0.114390 0.258182 0.708843 0.077525
-0.490093 0.173433 0.090040 0.421955 0.279956
-0.382461 0.193817 0.087070 0.298236 0.364436
-0.318849 0.150566 0.097605 0.414953 0.299328
-0.113221 0.190688 0.097473 0.317986 0.524035
-0.487612 0.157990 0.137684 0.207485 0.328511
-0.415390 0.156206 0.110413 0.173488 0.449581
-0.392854 0.243412 0.095319 0.158735 0.352930
-0.554126 0.279294 0.084682 0.789521 0.053595
-0.426016 0.255484 0.163308 0.615069 0.071484
-0.431377 0.338700 0.141517 0.673050 0.060005
-0.566932 0.141427 0.223486 0.375608 0.070605
-0.493511 0.233734 0.315571 0.238950 0.087048
-0.297922 0.264510 0.411237 0.278766 0.092207
-0.282302 0.280217 0.244330 0.279897 0.142264
-0.177097 0.323486 0.184695 0.254221 0.183230
-0.184257 0.328819 0.268892 0.187933 0.187193
-0.122061 0.220291 0.321286 0.201051 0.198515
-0.326682 0.185267 0.112300 0.407868 0.149352
-0.193578 0.190639 0.125066 0.491527 0.159276
-0.122828 0.230083 0.225742 0.246379 0.289540
-0.208084 0.292604 0.243207 0.126616 0.272821
-0.288296 0.286988 0.273500 0.223556 0.187415
-0.202485 0.337359 0.222418 0.324829 0.208113
-0.149017 0.419979 0.241372 0.290285 0.175273
-0.085329 0.455188 0.179868 0.274085 0.218022
-0.149409 0.414893 0.200622 0.357569 0.102277
-0.087805 0.312668 0.140154 0.367296 0.098465
-0.089148 0.241602 0.116991 0.435363 0.284444
-0.102707 0.161375 0.122429 0.703344 0.226518
-0.194637 0.121701 0.250432 0.461063 0.167048
-0.127617 0.158234 0.229630 0.325473 0.201565
-0.095300 0.179652 0.103247 0.535340 0.340825
-0.087410 0.265488 0.197557 0.377987 0.253206
-0.086397 0.306960 0.231208 0.441333 0.106770
-0.121230 0.358556 0.167666 0.464476 0.115565
-0.141336 0.323618 0.111516 0.503399 0.110768
-0.105150 0.362605 0.111172 0.614013 0.078718
-0.141384 0.450586 0.064529 0.592426 0.068985
-0.098662 0.400708 0.085985 0.636453 0.149305
-0.152546 0.320095 0.087644 0.691881 0.122628
-0.205102 0.370324 0.096574 0.622388 0.082397
-0.311191 0.243388 0.111673 0.558532 0.190249
-0.260012 0.292469 0.255853 0.373923 0.095727
-0.324122 0.216718 0.325816 0.332369 0.076832
-0.213938 0.301380 0.215070 0.323471 0.134882
-0.310035 0.327218 0.144910 0.349521 0.137458
-0.328729 0.313940 0.162626 0.287671 0.091596
-0.188131 0.449382 0.149802 0.305148 0.110859
-0.226128 0.397555 0.219231 0.283246 0.128045
-0.268488 0.383741 0.267036 0.140066 0.113841
-0.300194 0.307947 0.234061 0.213999 0.085346
-0.249251 0.359982 0.175305 0.303210 0.089854
-0.305787 0.174719 0.170370 0.267549 0.093204
-0.277988 0.215844 0.288148 0.208727 0.119363
-0.251537 0.194177 0.264074 0.293404 0.095994
-0.198388 0.217117 0.190170 0.358153 0.091230
-0.259438 0.298203 0.180977 0.340391 0.098331
-0.213229 0.282142 0.168016 0.412408 0.145436
-0.155758 0.305559 0.214118 0.355955 0.096258
-0.160386 0.184590 0.361414 0.413724 0.083817
-0.112845 0.220949 0.421627 0.486660 0.061043
-0.112629 0.190622 0.638070 0.341215 0.082163
-0.116782 0.255025 0.491926 0.370337 0.065029
-0.154064 0.331035 0.181792 0.381628 0.163855
-0.109744 0.273913 0.213751 0.316332 0.168076
-0.174637 0.393942 0.248357 0.229476 0.127964
-0.132432 0.261070 0.323617 0.263662 0.118229
-0.107105 0.214560 0.444968 0.282514 0.117291
-0.119399 0.169338 0.506733 0.185210 0.138955
-0.221036 0.132225 0.518560 0.171333 0.187982
-0.199032 0.152181 0.654897 0.144632 0.237100
-0.120866 0.235536 0.584756 0.165567 0.242740
-0.109058 0.386849 0.680956 0.275759 0.068830
-0.105995 0.368329 0.606941 0.161897 0.237895
-0.143761 0.179830 0.780855 0.202850 0.097554
-0.268849 0.443371 0.378456 0.183844 0.111634
-0.228760 0.335152 0.265416 0.280008 0.156587
-0.179733 0.367035 0.353314 0.263542 0.108968
-0.167471 0.309785 0.282987 0.352425 0.164452
-0.296403 0.267574 0.263134 0.372176 0.161801
-0.226712 0.354418 0.317933 0.355062 0.151163
-0.103298 0.357472 0.310082 0.291660 0.309223
-0.101618 0.343584 0.340646 0.212203 0.202494
-0.195241 0.408380 0.177813 0.242224 0.242440
-0.313510 0.358992 0.112963 0.263010 0.210174
-0.309341 0.249017 0.208548 0.340886 0.113637
-0.372923 0.300790 0.189317 0.246020 0.170098
-0.511267 0.252399 0.215894 0.218157 0.085380
-0.460722 0.326954 0.181351 0.303566 0.087593
-0.427875 0.335350 0.285155 0.176962 0.082338
-0.362400 0.286238 0.329083 0.230290 0.137244
-0.480916 0.194219 0.211225 0.327812 0.074704
-0.352388 0.305558 0.103426 0.617043 0.070092
-0.211613 0.490287 0.136608 0.466294 0.185644
-0.179765 0.528888 0.066660 0.646064 0.127519
-0.184515 0.296351 0.122412 0.800505 0.095897
-0.139991 0.352790 0.102051 0.933430 0.160030
-0.130957 0.352874 0.086439 0.751460 0.187693
-0.097718 0.377684 0.084285 0.794735 0.086198
-0.113793 0.433105 0.077788 0.698458 0.088428
-0.110614 0.442982 0.121026 0.588836 0.093086
-0.194030 0.442051 0.073890 0.583050 0.121409
-0.168129 0.371113 0.099215 0.602795 0.239593
-0.131199 0.468405 0.097038 0.327861 0.436528
-0.105739 0.344430 0.114523 0.270244 0.474281
-0.172534 0.406580 0.145497 0.222626 0.382126
-0.087707 0.315868 0.208793 0.169532 0.349797
-0.111903 0.195832 0.150730 0.204733 0.423196
-0.085304 0.388147 0.240388 0.122330 0.256361
-0.082961 0.517760 0.233624 0.130478 0.240802
-0.082212 0.582552 0.147653 0.157918 0.277928
-0.103393 0.589256 0.170611 0.155752 0.395248
-0.085466 0.464226 0.135038 0.188922 0.198734
-0.072725 0.439998 0.165898 0.173695 0.298867
-0.104679 0.499326 0.228596 0.218945 0.325428
-0.080427 0.446632 0.200732 0.147028 0.409762
-0.075389 0.517600 0.114506 0.227527 0.363530
-0.084986 0.523083 0.086758 0.315701 0.315594
-0.088441 0.430377 0.106263 0.270315 0.279921
-0.081395 0.467028 0.133672 0.464790 0.242030
-0.090952 0.453212 0.149743 0.547528 0.175694
-0.099379 0.481611 0.071887 0.534029 0.100287
-0.083062 0.386335 0.220161 0.532010 0.173719
-0.144972 0.263844 0.201580 0.469277 0.177389
-0.142121 0.147515 0.211734 0.584132 0.310712
-0.353816 0.133526 0.405674 0.623611 0.160589
-0.324226 0.184162 0.342782 0.466907 0.096072
-0.310467 0.115672 0.285285 0.672622 0.074180
-0.263143 0.201205 0.336584 0.648774 0.075784
-0.180648 0.357954 0.426869 0.380501 0.111876
-0.119271 0.457551 0.527575 0.382157 0.062359
-0.430820 0.165178 0.255443 0.435750 0.074534
-0.237698 0.131779 0.153751 0.487195 0.075951
-0.180891 0.425850 0.088458 0.492405 0.095550
-0.127499 0.456765 0.097912 0.496377 0.139623
-0.113342 0.558562 0.083514 0.413433 0.105192
-0.154586 0.452843 0.117083 0.405856 0.095318
-0.110357 0.322982 0.108231 0.465112 0.168830
-0.106166 0.234890 0.174721 0.581859 0.064417
-0.121238 0.142086 0.198109 0.545828 0.068485
-0.126792 0.116153 0.295495 0.813626 0.074704
-0.181164 0.105619 0.372673 0.692702 0.063916
-0.112864 0.183776 0.258872 0.434172 0.231634
-0.084876 0.160535 0.242597 0.602670 0.081827
-0.099892 0.230109 0.283019 0.473404 0.089380
-0.117540 0.181325 0.242558 0.352096 0.084823
-0.096557 0.204351 0.129500 0.505436 0.090511
-0.093064 0.150856 0.121938 0.580397 0.124525
-0.097239 0.137281 0.323145 0.480001 0.089031
-0.102517 0.153194 0.359697 0.381040 0.170476
-0.156408 0.147906 0.342562 0.312323 0.095657
-0.260029 0.136204 0.390788 0.332696 0.084106
-0.299114 0.136351 0.309438 0.400320 0.068766
-0.267323 0.186838 0.183452 0.438919 0.217618
-0.107227 0.170604 0.112600 0.371471 0.390769
-0.255438 0.269699 0.266564 0.497348 0.174202
-0.190164 0.374471 0.261554 0.538124 0.113444
-0.271933 0.286121 0.157487 0.651620 0.081535
-0.196314 0.203974 0.165772 0.797090 0.105362
-0.309812 0.186345 0.098772 0.675252 0.086908
-0.383614 0.333117 0.281250 0.299235 0.085667
-0.421148 0.216396 0.359232 0.371396 0.072937
-0.318360 0.264567 0.262105 0.319453 0.073952
-0.262536 0.409518 0.292890 0.263326 0.086857
-0.231399 0.536373 0.240170 0.174999 0.098506
-0.114050 0.465195 0.301214 0.145552 0.138694
-0.099833 0.344497 0.224309 0.143338 0.129083
-0.085813 0.345800 0.327581 0.131012 0.164973
-0.127262 0.186996 0.218444 0.163716 0.232902
-0.088498 0.290046 0.185292 0.165045 0.250641
-0.110534 0.184782 0.269122 0.249893 0.115434
-0.148053 0.265736 0.193619 0.250175 0.091308
-0.379875 0.285987 0.161507 0.361349 0.144975
-0.390482 0.367610 0.105617 0.347003 0.103944
-0.334816 0.476018 0.210396 0.274579 0.200321
-0.421665 0.151238 0.177117 0.144761 0.197904
-0.454088 0.285435 0.115227 0.152621 0.139846
-0.358198 0.468506 0.200348 0.123930 0.174367
-0.185748 0.449898 0.199187 0.134662 0.194569
-0.103349 0.471913 0.152270 0.151000 0.085548
-0.282837 0.308619 0.317962 0.215435 0.105821
-0.402882 0.326504 0.197948 0.232861 0.086919
-0.390806 0.213090 0.234939 0.324037 0.084063
-0.492621 0.111084 0.319478 0.341779 0.086320
-0.482136 0.118733 0.296374 0.546299 0.071209
-0.605538 0.245134 0.181933 0.544933 0.059700
-0.618492 0.293192 0.233297 0.475559 0.067750
-0.601265 0.269593 0.342096 0.447819 0.079243
-0.514350 0.298209 0.161298 0.541413 0.079463
-0.447130 0.363282 0.181394 0.588958 0.068802
-0.438142 0.456465 0.207360 0.438283 0.087927
-0.538469 0.407440 0.181607 0.443458 0.109596
-0.521273 0.426539 0.292112 0.408676 0.079726
-0.541366 0.408530 0.221462 0.553654 0.063429
-0.541684 0.325679 0.121371 0.669718 0.149155
-0.392702 0.525994 0.076333 0.633049 0.173987
-0.333941 0.576747 0.075341 0.717406 0.129229
-0.300007 0.469533 0.314894 0.583532 0.079827
-0.359423 0.582027 0.197819 0.626980 0.071930
-0.375155 0.526411 0.181059 0.497522 0.076711
-0.440203 0.345132 0.347966 0.737184 0.090692
-0.415601 0.609245 0.350830 0.418593 0.061022
-0.200119 0.796816 0.429073 0.283859 0.065924
-0.534968 0.295700 0.290228 0.575688 0.098730
-0.332613 0.308798 0.174258 0.388578 0.074034
-0.186081 0.473443 0.092342 0.303737 0.205637
-0.286049 0.395487 0.102551 0.283964 0.109250
-0.447677 0.281928 0.093508 0.270614 0.101271
-0.275778 0.337680 0.223162 0.318782 0.151265
-0.328181 0.353926 0.241536 0.255548 0.115068
-0.344691 0.399851 0.187118 0.309705 0.081445
-0.328331 0.319898 0.212749 0.327657 0.107502
-0.403608 0.157937 0.333564 0.272334 0.085989
-0.447611 0.159044 0.250646 0.339178 0.168145
-0.367334 0.294287 0.252652 0.317527 0.166986
-0.405963 0.275243 0.245541 0.366684 0.093630
-0.305351 0.216470 0.287889 0.294907 0.143758
-0.114953 0.171443 0.123606 0.319322 0.255373
-0.090433 0.253035 0.122365 0.240238 0.333953
-0.081823 0.308896 0.093993 0.340615 0.329296
-0.082674 0.341047 0.098594 0.414837 0.255269
-0.087470 0.446794 0.079606 0.431651 0.220610
-0.089093 0.426871 0.106092 0.365100 0.328627
-0.459583 0.347569 0.081792 0.356045 0.394248
-0.593081 0.220081 0.080151 0.293147 0.332040
-0.426883 0.291573 0.100010 0.251732 0.287532
-0.167967 0.514537 0.108654 0.210527 0.270166
-0.090191 0.658566 0.116349 0.252329 0.294360
-0.101347 0.661212 0.091714 0.248497 0.188598
-0.193061 0.583990 0.132395 0.265251 0.184525
-0.236665 0.553438 0.101675 0.301357 0.108440
-0.336569 0.509293 0.104890 0.302262 0.131419
-0.321735 0.630549 0.087409 0.374096 0.112967
-0.467603 0.615493 0.085577 0.419123 0.122689
-0.453593 0.708086 0.085382 0.338539 0.118159
-0.562007 0.607979 0.086375 0.367191 0.089294
-0.670852 0.547460 0.085965 0.387358 0.091762
-0.569530 0.585864 0.070041 0.487567 0.090297
-0.517535 0.747142 0.082653 0.439445 0.085448
-0.550921 0.642960 0.210149 0.312601 0.077560
-0.434674 0.758326 0.259834 0.201585 0.120645
-0.397124 0.654162 0.458831 0.180345 0.085122
-0.593045 0.502594 0.302433 0.281234 0.088978
-0.719975 0.402121 0.203694 0.280016 0.073221
-0.715201 0.570861 0.067241 0.478463 0.065605
-0.683625 0.689241 0.060655 0.334940 0.098963
-0.556302 0.776554 0.069081 0.306893 0.086083
-0.426715 0.813035 0.104246 0.242797 0.204849
-0.378576 0.825199 0.098678 0.322154 0.096380
-0.373181 0.938991 0.074899 0.329906 0.115048
-0.531337 0.890418 0.086286 0.195433 0.102164
-0.331830 0.938828 0.132144 0.187716 0.129650
-0.263502 0.782498 0.313909 0.148704 0.136379
-0.169978 0.983636 0.087887 0.271870 0.160723
-0.421034 1.050926 0.080973 0.173235 0.091496
-0.226638 1.162236 0.131864 0.171522 0.148265
-0.153397 0.976301 0.178361 0.136460 0.233506
-0.256414 0.918775 0.249344 0.145875 0.168910
-0.296611 0.848865 0.155931 0.162775 0.271815
-0.124515 0.874587 0.289086 0.122107 0.167854
-0.126736 0.855896 0.245568 0.281517 0.123689
-0.161475 0.828095 0.407515 0.150156 0.104949
-0.405729 0.596624 0.213151 0.386929 0.116147
-0.420695 0.635707 0.107173 0.355082 0.250151
-0.391488 0.492272 0.088173 0.260076 0.229852
-0.292133 0.511892 0.094559 0.227255 0.374600
-0.446199 0.398980 0.100935 0.615509 0.072066
-0.559358 0.292218 0.134613 0.381863 0.081697
-0.531829 0.297407 0.114050 0.322506 0.239551
-0.365141 0.332372 0.155150 0.138239 0.261754
-0.246994 0.456676 0.214320 0.142386 0.333454
-0.101428 0.541105 0.347628 0.137940 0.237903
-0.111916 0.688920 0.518607 0.141385 0.130675
-0.097677 0.516438 0.680891 0.148460 0.119448
-0.074679 0.311782 0.864591 0.195630 0.074962
-0.128848 0.146236 0.877752 0.345093 0.040314
-0.250258 0.116181 0.750184 0.265212 0.071996
-0.436550 0.113508 0.609363 0.315415 0.088130
-0.563791 0.115646 0.469339 0.333534 0.061239
-0.588540 0.139056 0.251609 0.186147 0.125557
-0.654957 0.156575 0.300506 0.405071 0.075981
-0.526240 0.414692 0.183810 0.186420 0.097223
-0.597026 0.511405 0.108666 0.171816 0.130111
-0.762306 0.336982 0.108317 0.193431 0.116628
-0.631676 0.454942 0.114949 0.315528 0.083995
-0.813025 0.522594 0.067380 0.196985 0.090847
-0.931959 0.388760 0.069329 0.236506 0.086399
-0.703619 0.564281 0.098629 0.276405 0.098209
-0.669720 0.698228 0.087051 0.183111 0.087664
-0.527639 0.662217 0.125666 0.194637 0.220262
-0.435453 0.529825 0.119419 0.176498 0.096993
-0.569041 0.527193 0.094926 0.298364 0.241613
-0.454893 0.563825 0.102980 0.332162 0.090583
-0.376914 0.679534 0.106861 0.199343 0.123625
-0.256805 0.727460 0.087715 0.290642 0.122030
-0.225371 0.814127 0.136481 0.212414 0.191651
+++ /dev/null
-0.281245 0.072824
-0.339645 0.060014
-0.409277 0.064576
-0.523095 0.061305
-0.230096 0.211887
-0.207683 0.332701
-0.284308 0.308783
-0.140378 0.711570
-0.174527 0.127827
-0.352952 0.235323
-0.370502 0.190103
-0.402932 0.159641
-0.347927 0.146360
-0.296583 0.131013
-0.223266 0.153607
-0.197020 0.420964
-0.116898 0.516163
-0.119488 0.109699
-0.111778 0.278792
-0.578302 0.202919
-0.414620 0.214613
-0.305886 0.397131
-0.332819 0.101995
-0.378387 0.086890
-0.382898 0.121331
-0.453255 0.063910
-0.426851 0.114357
-0.460512 0.099039
-0.479185 0.134529
-0.496434 0.084061
-0.573538 0.071989
-0.531672 0.120071
-0.591529 0.134458
-0.511033 0.180023
-0.448004 0.171478
-0.322286 0.187786
-0.297869 0.238597
-0.242424 0.263223
-0.175075 0.260064
-0.201034 0.074025
-0.268571 0.522305
-0.344104 0.296771
-0.409613 0.271732
-0.173676 0.190087
-0.115603 0.193700
-0.115269 0.373202
-0.407643 0.637929
-0.439428 0.478964
-0.567749 0.389060
-0.551502 0.271892
-0.639284 0.075639
-0.665511 0.286926
-0.720983 0.084070
-0.795786 0.214436
-0.832583 0.095102
-0.671796 0.164706
-0.983554 0.136778
-0.812831 0.368808
-0.644281 0.515306
-0.480389 0.316998
-0.403689 0.360441
-0.476736 0.232898
-0.248084 0.111421
-0.273953 0.180184
+++ /dev/null
-0.678062 0.043120
-0.472775 0.257353
-0.522878 0.127961
-0.628034 0.038788
-0.480545 0.057725
-0.437201 0.064479
-0.327854 0.073645
-0.308168 0.135691
-0.390919 0.172150
-0.362940 0.121889
-0.384688 0.065511
-0.419078 0.117947
-0.468913 0.116759
-0.507838 0.089601
-0.555567 0.052196
-0.521040 0.052787
-0.589645 0.043616
-0.985285 0.088227
-0.724020 0.177911
-0.129928 0.130564
-0.120671 0.249971
-0.266520 0.077658
-0.685157 0.083387
-0.673088 0.130951
-0.726463 0.107217
-0.779587 0.130439
-0.652097 0.060232
-0.616365 0.062903
-0.614893 0.095188
-0.671203 0.264629
-0.657805 0.188243
-0.647995 0.095077
-0.581225 0.110398
-0.573894 0.254912
-0.531176 0.201073
-0.544230 0.353796
-0.621094 0.138556
-0.717028 0.053894
-0.890269 0.071236
-1.100420 0.115118
-0.492946 0.167302
-0.387836 0.249419
-0.929411 0.210459
-0.389735 0.351413
-0.273341 0.443161
-0.453321 0.457227
-0.303206 0.300360
-0.563261 0.148813
-0.789479 0.244432
-0.817080 0.062843
-0.852058 0.150352
-0.760492 0.059787
-0.711233 0.355546
-0.598869 0.189758
-0.583624 0.073653
-0.548949 0.089569
-0.445394 0.183962
-0.333115 0.197087
-0.246232 0.142290
-0.263973 0.216087
-0.185969 0.192135
-0.205425 0.302232
-0.195923 0.088343
-0.148277 0.406699
+++ /dev/null
-6 3369
-1400.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1400.0 1900.0 2400.0 2500.0 3200.0 3400.0
-1400.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1400.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1400.0 1900.0 2300.0 2600.0 3200.0 3300.0
-1400.0 1900.0 2100.0 2600.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1600.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1800.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1800.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1900.0 2000.0 2200.0 2600.0 3300.0 3400.0
-1700.0 2000.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2600.0 2900.0 3200.0 3300.0
-1600.0 2000.0 2500.0 2800.0 3200.0 3400.0
-1500.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1400.0 1700.0 2200.0 2400.0 3200.0 3300.0
-1300.0 1700.0 2200.0 2300.0 3200.0 3300.0
-1300.0 1600.0 2200.0 2300.0 3200.0 3300.0
-1200.0 1600.0 2200.0 2400.0 3200.0 3300.0
-1200.0 1600.0 2200.0 2300.0 3200.0 3300.0
-1200.0 1500.0 2200.0 2300.0 3100.0 3300.0
-1200.0 1500.0 2200.0 2300.0 3200.0 3300.0
-1300.0 1500.0 2100.0 2300.0 3000.0 3200.0
-1300.0 1600.0 2000.0 2200.0 3000.0 3200.0
-1400.0 1700.0 2000.0 2300.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2300.0 3200.0 3300.0
-1300.0 1600.0 1900.0 2100.0 3100.0 3200.0
-1200.0 1500.0 2100.0 2300.0 3200.0 3300.0
-1500.0 1800.0 2000.0 2300.0 3000.0 3200.0
-1200.0 1500.0 2200.0 2400.0 3300.0 3400.0
-1200.0 1500.0 2200.0 2400.0 3200.0 3400.0
-1200.0 1500.0 2200.0 2400.0 3200.0 3300.0
-1300.0 1500.0 2300.0 2400.0 3200.0 3300.0
-1300.0 1500.0 2200.0 2500.0 3000.0 3200.0
-1300.0 1600.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1800.0 2400.0 2600.0 3100.0 3200.0
-1700.0 2000.0 2500.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2600.0 2700.0 3100.0 3200.0
-1900.0 2300.0 2600.0 2900.0 3200.0 3300.0
-2000.0 2300.0 2600.0 2900.0 3300.0 3400.0
-1900.0 2300.0 2500.0 2900.0 3300.0 3400.0
-1800.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2500.0 3200.0 3400.0
-1500.0 1800.0 2400.0 2600.0 3100.0 3400.0
-1800.0 2100.0 2600.0 2900.0 3300.0 3500.0
-2000.0 2500.0 2700.0 3000.0 3400.0 3500.0
-2200.0 2500.0 2700.0 3100.0 3300.0 3400.0
-2300.0 2500.0 2700.0 3100.0 3300.0 3400.0
-2100.0 2500.0 2600.0 3000.0 3200.0 3300.0
-2100.0 2400.0 2500.0 3000.0 3200.0 3300.0
-1700.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1700.0 2000.0 2300.0 2800.0 3100.0 3300.0
-1600.0 1900.0 2200.0 2800.0 3000.0 3200.0
-1500.0 1900.0 2100.0 2700.0 3000.0 3200.0
-1400.0 1900.0 2000.0 2600.0 3000.0 3100.0
-1200.0 1600.0 2100.0 2400.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2400.0 3200.0 3400.0
-1600.0 1700.0 2200.0 2400.0 3100.0 3400.0
-1600.0 1700.0 2200.0 2400.0 3200.0 3400.0
-1700.0 1800.0 2300.0 2400.0 3200.0 3400.0
-1700.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2400.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2100.0 2400.0 3000.0 3100.0
-1500.0 1700.0 2100.0 2300.0 3000.0 3100.0
-1400.0 1700.0 2100.0 2500.0 3000.0 3200.0
-1000.0 1700.0 2300.0 2500.0 3200.0 3300.0
-1100.0 1700.0 2400.0 2500.0 3300.0 3400.0
-1500.0 2000.0 2300.0 2600.0 3000.0 3300.0
-1300.0 1600.0 1800.0 2600.0 2900.0 3100.0
-1300.0 1600.0 1900.0 2200.0 2900.0 3000.0
-1500.0 1700.0 2200.0 2500.0 2900.0 3000.0
-1500.0 1600.0 2100.0 2400.0 2900.0 3100.0
-1500.0 1600.0 2000.0 2600.0 3000.0 3100.0
-1600.0 1700.0 2100.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2500.0 3300.0 3400.0
-1700.0 1900.0 2200.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2400.0 2600.0 3000.0 3300.0
-1700.0 2100.0 2400.0 2600.0 3100.0 3300.0
-1700.0 2100.0 2400.0 2600.0 3200.0 3400.0
-1400.0 1600.0 2300.0 2400.0 3300.0 3400.0
-1300.0 1400.0 2100.0 2200.0 2900.0 3200.0
-1000.0 1300.0 2200.0 2300.0 3200.0 3400.0
-1600.0 2000.0 2300.0 2600.0 2800.0 3100.0
-1600.0 2000.0 2300.0 2600.0 2900.0 3200.0
-1600.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1700.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1600.0 1900.0 2300.0 2500.0 3100.0 3400.0
-1500.0 1900.0 2300.0 2600.0 3000.0 3300.0
-1500.0 1900.0 2300.0 2600.0 3100.0 3300.0
-1500.0 2000.0 2300.0 2700.0 3100.0 3300.0
-2000.0 2500.0 2700.0 2900.0 3300.0 3400.0
-2000.0 2400.0 2600.0 2800.0 3300.0 3400.0
-1700.0 2300.0 2600.0 2800.0 3300.0 3400.0
-1400.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1300.0 1600.0 2300.0 2500.0 3200.0 3300.0
-1300.0 1500.0 2000.0 2300.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2400.0 2900.0 3300.0
-1500.0 1700.0 2200.0 2400.0 3000.0 3200.0
-1400.0 1800.0 2200.0 2400.0 3000.0 3300.0
-1400.0 1800.0 2200.0 2400.0 3000.0 3200.0
-1200.0 1500.0 2100.0 2400.0 3100.0 3300.0
-1300.0 1800.0 2200.0 2300.0 3300.0 3400.0
-1300.0 1700.0 2200.0 2400.0 3300.0 3400.0
-1400.0 1500.0 2300.0 2500.0 3100.0 3400.0
-1500.0 1600.0 2300.0 2500.0 3100.0 3300.0
-1500.0 1600.0 2400.0 2500.0 3100.0 3300.0
-1400.0 1800.0 2400.0 2500.0 3000.0 3300.0
-1300.0 1700.0 2100.0 2500.0 3000.0 3200.0
-1300.0 1600.0 2100.0 2500.0 3100.0 3200.0
-1300.0 1700.0 2200.0 2500.0 3100.0 3200.0
-1300.0 1600.0 2200.0 2500.0 3100.0 3300.0
-1300.0 1700.0 2300.0 2600.0 3200.0 3300.0
-1300.0 1700.0 2400.0 2500.0 3200.0 3400.0
-1500.0 1900.0 2500.0 2600.0 3200.0 3400.0
-1500.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1600.0 2100.0 2600.0 2900.0 3400.0 3500.0
-1600.0 1900.0 2500.0 2800.0 3300.0 3400.0
-1500.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1600.0 2000.0 2500.0 2700.0 3100.0 3200.0
-1500.0 1700.0 2400.0 2700.0 3100.0 3200.0
-1500.0 1600.0 2400.0 2600.0 3100.0 3300.0
-1500.0 1600.0 2200.0 2400.0 3000.0 3200.0
-1500.0 1600.0 2200.0 2300.0 3000.0 3200.0
-1400.0 1700.0 2100.0 2300.0 3000.0 3100.0
-1700.0 1800.0 2300.0 2800.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2800.0 3200.0 3300.0
-1800.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1800.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1600.0 2000.0 2300.0 2500.0 3000.0 3200.0
-1500.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1500.0 1700.0 2200.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2400.0 3000.0 3100.0
-1600.0 1700.0 2300.0 2400.0 3000.0 3100.0
-1600.0 1700.0 2300.0 2400.0 3000.0 3200.0
-1600.0 1700.0 2300.0 2400.0 2900.0 3100.0
-1600.0 1700.0 2300.0 2400.0 2900.0 3200.0
-1600.0 1700.0 2300.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2300.0 2500.0 2900.0 3300.0
-1400.0 1500.0 2200.0 2500.0 3000.0 3300.0
-1200.0 1400.0 2300.0 2400.0 3000.0 3300.0
-1100.0 1400.0 2300.0 2400.0 3100.0 3300.0
-1200.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1400.0 2000.0 2400.0 2700.0 3300.0 3400.0
-1600.0 2100.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2300.0 2600.0 2900.0 3300.0 3400.0
-1400.0 2100.0 2400.0 2600.0 3100.0 3200.0
-1300.0 1600.0 2300.0 2500.0 3000.0 3200.0
-1200.0 1500.0 2100.0 2500.0 3000.0 3200.0
-1300.0 1700.0 2100.0 2300.0 2900.0 3200.0
-1500.0 1600.0 2200.0 2400.0 3000.0 3100.0
-1500.0 1600.0 2200.0 2500.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2500.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2500.0 3100.0 3300.0
-1600.0 1700.0 2200.0 2400.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2500.0 3300.0 3400.0
-1700.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1800.0 2000.0 2300.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2700.0 3300.0 3400.0
-1900.0 2000.0 2100.0 2400.0 3300.0 3400.0
-1800.0 2100.0 2400.0 2800.0 3200.0 3400.0
-2000.0 2200.0 2500.0 2700.0 3100.0 3300.0
-2000.0 2300.0 2500.0 2700.0 3100.0 3300.0
-2000.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1900.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1800.0 1900.0 2300.0 2600.0 3300.0 3400.0
-1800.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2600.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2300.0 2600.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1500.0 1800.0 2100.0 2500.0 3100.0 3200.0
-1700.0 2100.0 2400.0 2800.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2900.0 3200.0 3300.0
-1900.0 2100.0 2400.0 2900.0 3200.0 3300.0
-1800.0 2100.0 2400.0 2800.0 3100.0 3200.0
-2000.0 2200.0 2500.0 2800.0 3100.0 3300.0
-2000.0 2200.0 2700.0 2800.0 3100.0 3300.0
-2000.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2000.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2100.0 2600.0 2800.0 3200.0 3400.0
-1800.0 2200.0 2500.0 2700.0 3300.0 3400.0
-1700.0 1900.0 2500.0 2600.0 3200.0 3400.0
-1700.0 1900.0 2400.0 2700.0 3200.0 3400.0
-1500.0 1900.0 2500.0 2600.0 3100.0 3300.0
-1200.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1300.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1200.0 1600.0 2400.0 2600.0 3200.0 3300.0
-1200.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1300.0 2000.0 2400.0 2700.0 3200.0 3300.0
-1200.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1100.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1100.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1000.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1000.0 1500.0 2400.0 2500.0 3100.0 3200.0
-1000.0 1500.0 2300.0 2400.0 3100.0 3200.0
-1000.0 1900.0 2300.0 2500.0 3000.0 3100.0
-1100.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1200.0 1800.0 2300.0 2400.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2400.0 3100.0 3200.0
-1400.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2400.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2400.0 3100.0 3200.0
-1500.0 1800.0 2200.0 2400.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2400.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1800.0 2000.0 2300.0 2800.0 2900.0 3100.0
-1500.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1500.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1500.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1600.0 2000.0 2400.0 2700.0 3300.0 3400.0
-1600.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1700.0 2100.0 2400.0 2600.0 2900.0 3200.0
-1600.0 2000.0 2500.0 2700.0 2900.0 3200.0
-1500.0 1800.0 2400.0 2800.0 3000.0 3200.0
-1500.0 1800.0 2100.0 2400.0 2900.0 3100.0
-1600.0 1900.0 2100.0 2400.0 3100.0 3300.0
-1600.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1800.0 1900.0 2300.0 2400.0 3100.0 3300.0
-1900.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1900.0 2200.0 2600.0 2700.0 3300.0 3400.0
-1900.0 2300.0 2600.0 2700.0 3300.0 3400.0
-1900.0 2300.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2200.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2400.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2300.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2400.0 2600.0 2700.0 3300.0 3400.0
-2000.0 2200.0 2600.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3100.0 3200.0
-1900.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1800.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1800.0 1900.0 2300.0 2500.0 3000.0 3100.0
-1800.0 1900.0 2400.0 2700.0 3000.0 3200.0
-1800.0 1900.0 2500.0 2700.0 3000.0 3200.0
-1800.0 2000.0 2500.0 2700.0 3100.0 3200.0
-2000.0 2300.0 2600.0 2900.0 3100.0 3300.0
-1900.0 2300.0 2700.0 3000.0 3200.0 3300.0
-2000.0 2400.0 2700.0 3000.0 3200.0 3300.0
-2100.0 2500.0 2800.0 3000.0 3200.0 3300.0
-2200.0 2400.0 2800.0 3000.0 3300.0 3400.0
-1900.0 2200.0 2700.0 2900.0 3300.0 3400.0
-2200.0 2400.0 2900.0 3100.0 3300.0 3400.0
-2100.0 2400.0 2800.0 3100.0 3300.0 3400.0
-2200.0 2500.0 2800.0 3100.0 3300.0 3400.0
-2100.0 2400.0 2600.0 2800.0 3300.0 3400.0
-2000.0 2400.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1800.0 1900.0 2400.0 2700.0 3100.0 3200.0
-1800.0 1900.0 2400.0 2700.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2700.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2700.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2700.0 2900.0 3200.0
-1700.0 1900.0 2300.0 2700.0 2900.0 3200.0
-1700.0 1900.0 2200.0 2700.0 3000.0 3200.0
-1700.0 2000.0 2300.0 2800.0 3000.0 3200.0
-1400.0 1700.0 2300.0 2400.0 3300.0 3400.0
-1400.0 1800.0 2300.0 2400.0 3300.0 3400.0
-1400.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1400.0 2100.0 2300.0 2500.0 3300.0 3400.0
-1400.0 2100.0 2300.0 2600.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2700.0 3200.0 3400.0
-1800.0 2100.0 2600.0 2900.0 3200.0 3400.0
-1800.0 2100.0 2600.0 2800.0 3300.0 3400.0
-1800.0 2100.0 2600.0 2700.0 3300.0 3400.0
-1800.0 2000.0 2500.0 2700.0 3300.0 3400.0
-1800.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1800.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1800.0 2200.0 2400.0 2600.0 3300.0 3400.0
-1800.0 2200.0 2400.0 2700.0 3300.0 3400.0
-1900.0 2300.0 2600.0 2900.0 3200.0 3400.0
-1900.0 2200.0 2600.0 2700.0 3200.0 3400.0
-1900.0 2100.0 2600.0 2700.0 3300.0 3400.0
-2000.0 2100.0 2500.0 2700.0 3200.0 3300.0
-2000.0 2100.0 2500.0 2700.0 3300.0 3400.0
-2000.0 2200.0 2500.0 2700.0 3300.0 3400.0
-2000.0 2100.0 2600.0 2700.0 3300.0 3400.0
-2000.0 2100.0 2500.0 2700.0 3400.0 3500.0
-1900.0 2100.0 2500.0 2600.0 3200.0 3400.0
-2000.0 2200.0 2600.0 2700.0 3200.0 3400.0
-2100.0 2300.0 2600.0 2800.0 3300.0 3400.0
-2100.0 2500.0 2700.0 3100.0 3300.0 3400.0
-2100.0 2500.0 2800.0 3100.0 3300.0 3400.0
-2100.0 2300.0 2400.0 2700.0 3200.0 3300.0
-2000.0 2300.0 2500.0 2800.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1600.0 1900.0 2300.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2800.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2400.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2400.0 3100.0 3300.0
-1400.0 1700.0 2300.0 2400.0 3100.0 3300.0
-1400.0 1500.0 2300.0 2400.0 3100.0 3300.0
-1300.0 1500.0 2300.0 2400.0 3100.0 3300.0
-1300.0 1500.0 2400.0 2500.0 3100.0 3300.0
-1300.0 1500.0 2400.0 2500.0 3000.0 3300.0
-1300.0 1500.0 2300.0 2400.0 2900.0 3300.0
-1400.0 1500.0 2400.0 2500.0 2900.0 3300.0
-1500.0 1600.0 2300.0 2500.0 2800.0 3300.0
-1600.0 1700.0 2300.0 2500.0 2800.0 3400.0
-1700.0 1800.0 2300.0 2500.0 2800.0 3300.0
-1800.0 1900.0 2400.0 2500.0 3100.0 3400.0
-1800.0 1900.0 2400.0 2500.0 3200.0 3400.0
-1900.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1900.0 2200.0 2600.0 2900.0 3400.0 3500.0
-1800.0 2200.0 2600.0 2900.0 3300.0 3400.0
-1900.0 2300.0 2600.0 3000.0 3400.0 3500.0
-2000.0 2300.0 2600.0 3000.0 3300.0 3400.0
-1800.0 2200.0 2500.0 2900.0 3200.0 3300.0
-1800.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2800.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2700.0 3100.0 3300.0
-1400.0 1800.0 2300.0 2600.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2400.0 3000.0 3100.0
-1500.0 1800.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2200.0 2500.0 2800.0 3000.0 3300.0
-2000.0 2300.0 2600.0 2800.0 3100.0 3300.0
-2000.0 2300.0 2700.0 2900.0 3100.0 3300.0
-2100.0 2300.0 2700.0 2900.0 3100.0 3300.0
-2000.0 2300.0 2700.0 3000.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2600.0 3300.0 3400.0
-1400.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1300.0 1900.0 2300.0 2600.0 3100.0 3300.0
-1200.0 1600.0 2200.0 2400.0 3000.0 3100.0
-1100.0 1500.0 2200.0 2400.0 3100.0 3200.0
-1100.0 1400.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1500.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1500.0 2300.0 2400.0 3300.0 3400.0
-1300.0 1400.0 2400.0 2500.0 3100.0 3300.0
-1500.0 2200.0 2500.0 2600.0 3100.0 3200.0
-2100.0 2400.0 2700.0 3000.0 3200.0 3300.0
-2200.0 2400.0 2700.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2700.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2700.0 2900.0 3300.0 3400.0
-2000.0 2300.0 2700.0 3000.0 3400.0 3500.0
-2100.0 2400.0 2700.0 3000.0 3400.0 3500.0
-2100.0 2500.0 2700.0 3100.0 3400.0 3500.0
-1900.0 2400.0 2600.0 2800.0 3300.0 3400.0
-1900.0 2100.0 2600.0 2800.0 3300.0 3400.0
-1900.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1900.0 2100.0 2500.0 2600.0 3300.0 3400.0
-1800.0 2200.0 2400.0 2800.0 3300.0 3400.0
-1800.0 2000.0 2400.0 2700.0 3300.0 3400.0
-1900.0 2000.0 2400.0 2700.0 3200.0 3300.0
-2000.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1500.0 2100.0 2200.0 2500.0 3300.0 3400.0
-1400.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1400.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2200.0 2600.0 3100.0 3200.0
-1700.0 2100.0 2400.0 2700.0 3100.0 3300.0
-1800.0 2000.0 2400.0 2700.0 3000.0 3200.0
-1600.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1700.0 2000.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2200.0 2600.0 2900.0 3200.0
-1600.0 1900.0 2300.0 2600.0 2900.0 3200.0
-1600.0 1900.0 2300.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2500.0 3000.0 3200.0
-1600.0 1800.0 2300.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2400.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2500.0 3000.0 3100.0
-1700.0 1800.0 2300.0 2500.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2400.0 3000.0 3200.0
-1700.0 1800.0 2100.0 2300.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2400.0 3000.0 3200.0
-1800.0 2000.0 2200.0 2400.0 3000.0 3200.0
-1800.0 2000.0 2300.0 2500.0 3100.0 3300.0
-1800.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1800.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1700.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1700.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1800.0 2100.0 2500.0 2900.0 3300.0 3400.0
-1800.0 2200.0 2600.0 2800.0 3300.0 3500.0
-1800.0 2100.0 2600.0 2900.0 3300.0 3400.0
-1800.0 2100.0 2600.0 3000.0 3200.0 3300.0
-1800.0 2200.0 2600.0 2900.0 3200.0 3300.0
-1800.0 2100.0 2600.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2400.0 2700.0 3100.0 3200.0
-1700.0 2000.0 2300.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2100.0 2400.0 2600.0 3100.0 3200.0
-1800.0 2100.0 2400.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1800.0 2000.0 2400.0 2700.0 3100.0 3300.0
-1700.0 2000.0 2400.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2300.0 2700.0 3100.0 3300.0
-1700.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2500.0 3000.0 3200.0
-1500.0 1700.0 2100.0 2500.0 2900.0 3100.0
-1500.0 1800.0 2300.0 2600.0 2900.0 3200.0
-1500.0 1900.0 2400.0 2600.0 3000.0 3200.0
-1600.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2400.0 2700.0 3100.0 3300.0
-1600.0 2200.0 2600.0 2900.0 3300.0 3400.0
-1700.0 2200.0 2600.0 3000.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2900.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2900.0 3300.0 3400.0
-1500.0 1800.0 2400.0 2500.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2500.0 3300.0 3400.0
-1500.0 1700.0 2300.0 2400.0 3300.0 3400.0
-1600.0 1800.0 2300.0 2400.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1600.0 1700.0 2400.0 2500.0 2800.0 3300.0
-1600.0 1800.0 2300.0 2500.0 2700.0 3200.0
-1600.0 1700.0 2300.0 2500.0 2700.0 3200.0
-1600.0 1700.0 2200.0 2500.0 2700.0 3100.0
-1600.0 1700.0 2200.0 2500.0 2600.0 3000.0
-1600.0 1700.0 2400.0 2500.0 2700.0 3200.0
-1600.0 1700.0 2400.0 2500.0 2800.0 3200.0
-1700.0 1800.0 2400.0 2600.0 2900.0 3300.0
-1700.0 1800.0 2300.0 2600.0 2800.0 3300.0
-1700.0 1800.0 2400.0 2600.0 3000.0 3400.0
-1700.0 1800.0 2300.0 2500.0 2900.0 3300.0
-1600.0 1700.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1800.0 2000.0 2400.0 3000.0 3200.0
-1400.0 1700.0 2000.0 2300.0 3000.0 3200.0
-1700.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1700.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1800.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2600.0 3300.0 3400.0
-2000.0 2100.0 2200.0 2600.0 3300.0 3400.0
-2000.0 2100.0 2300.0 2600.0 3300.0 3400.0
-2100.0 2200.0 2500.0 2800.0 3300.0 3400.0
-2000.0 2100.0 2300.0 2500.0 3200.0 3300.0
-1900.0 2000.0 2200.0 2600.0 3200.0 3300.0
-1800.0 1900.0 2100.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2100.0 2300.0 3000.0 3200.0
-1500.0 1800.0 2100.0 2400.0 3100.0 3300.0
-1500.0 1700.0 2200.0 2500.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1500.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1800.0 2300.0 2600.0 3000.0 3400.0 3500.0
-1900.0 2300.0 2700.0 3000.0 3400.0 3500.0
-2000.0 2300.0 2800.0 3100.0 3300.0 3400.0
-2100.0 2300.0 2800.0 3100.0 3300.0 3400.0
-2000.0 2300.0 2700.0 3000.0 3200.0 3300.0
-2000.0 2200.0 2600.0 2900.0 3100.0 3300.0
-2000.0 2200.0 2500.0 2800.0 3000.0 3200.0
-2000.0 2200.0 2400.0 2800.0 3100.0 3200.0
-1600.0 2000.0 2400.0 2600.0 3100.0 3200.0
-1400.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1400.0 1900.0 2300.0 2600.0 3000.0 3200.0
-1500.0 2000.0 2400.0 2700.0 2900.0 3200.0
-2000.0 2300.0 2800.0 3000.0 3200.0 3400.0
-2100.0 2300.0 2900.0 3100.0 3300.0 3400.0
-1800.0 2300.0 2600.0 2900.0 3400.0 3500.0
-1700.0 2300.0 2500.0 2900.0 3300.0 3400.0
-1300.0 2000.0 2400.0 2700.0 3300.0 3400.0
-1200.0 1900.0 2300.0 2600.0 3300.0 3400.0
-1200.0 1800.0 2300.0 2600.0 3300.0 3400.0
-1100.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1800.0 2200.0 2600.0 2800.0 3300.0 3400.0
-1800.0 2000.0 2500.0 2700.0 3200.0 3400.0
-1700.0 2100.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2200.0 2600.0 2800.0 3300.0 3400.0
-1800.0 2200.0 2600.0 3000.0 3300.0 3500.0
-1700.0 2100.0 2600.0 2800.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2800.0 3300.0 3500.0
-1800.0 2200.0 2500.0 2900.0 3300.0 3400.0
-2100.0 2200.0 2600.0 2700.0 3100.0 3400.0
-1900.0 2100.0 2500.0 2600.0 3100.0 3400.0
-1900.0 2000.0 2500.0 2600.0 3200.0 3400.0
-1900.0 2000.0 2600.0 2700.0 3200.0 3400.0
-1800.0 1900.0 2500.0 2600.0 3100.0 3400.0
-1600.0 2000.0 2700.0 2800.0 3300.0 3400.0
-1400.0 2000.0 2700.0 2800.0 3300.0 3400.0
-1000.0 1900.0 2700.0 2800.0 3300.0 3400.0
-1000.0 1400.0 2700.0 2900.0 3200.0 3400.0
-1100.0 1500.0 2700.0 2900.0 3200.0 3300.0
-1200.0 1700.0 2400.0 2500.0 3100.0 3300.0
-1300.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1300.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1400.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1500.0 2000.0 2400.0 2700.0 3000.0 3300.0
-1300.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2700.0 2800.0 3300.0 3400.0
-1500.0 1900.0 2700.0 2800.0 3300.0 3400.0
-1400.0 1800.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2300.0 2600.0 2700.0 2900.0 3200.0
-1500.0 1700.0 2400.0 2600.0 2800.0 3300.0
-1600.0 1700.0 2500.0 2700.0 2900.0 3300.0
-1800.0 1900.0 2600.0 2700.0 3200.0 3400.0
-1800.0 1900.0 2600.0 2700.0 3200.0 3300.0
-2000.0 2200.0 2600.0 2800.0 3200.0 3300.0
-2000.0 2100.0 2600.0 2700.0 3200.0 3400.0
-2000.0 2100.0 2500.0 2800.0 3200.0 3400.0
-2000.0 2100.0 2600.0 2700.0 3100.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2600.0 3100.0 3200.0
-1700.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2700.0 3200.0 3400.0
-1900.0 2000.0 2500.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1800.0 2100.0 2500.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2600.0 3200.0 3400.0
-1800.0 1900.0 2400.0 2500.0 3000.0 3300.0
-1800.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1900.0 2100.0 2500.0 2600.0 3200.0 3300.0
-2000.0 2100.0 2500.0 2600.0 3300.0 3400.0
-2000.0 2200.0 2500.0 2600.0 3300.0 3400.0
-2100.0 2200.0 2500.0 2600.0 3300.0 3400.0
-2100.0 2200.0 2500.0 2600.0 3200.0 3400.0
-2100.0 2200.0 2400.0 2500.0 3200.0 3400.0
-2000.0 2100.0 2400.0 2500.0 3200.0 3400.0
-1800.0 1900.0 2400.0 2600.0 3200.0 3400.0
-1800.0 1900.0 2500.0 2600.0 3200.0 3400.0
-1800.0 2300.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2400.0 2800.0 3000.0 3300.0 3500.0
-1900.0 2300.0 2800.0 3100.0 3300.0 3400.0
-2000.0 2300.0 2700.0 2900.0 3200.0 3400.0
-1800.0 2000.0 2600.0 2900.0 3300.0 3400.0
-1700.0 2000.0 2500.0 2600.0 3200.0 3400.0
-1600.0 2100.0 2500.0 2600.0 3300.0 3400.0
-1500.0 2100.0 2500.0 2600.0 3300.0 3400.0
-1500.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1400.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1300.0 2000.0 2600.0 2800.0 3300.0 3400.0
-1500.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1600.0 2000.0 2500.0 2700.0 3200.0 3400.0
-1600.0 2000.0 2500.0 2600.0 3200.0 3400.0
-1600.0 2000.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1600.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1500.0 1700.0 2200.0 2400.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2500.0 2900.0 3200.0
-1300.0 1700.0 2200.0 2500.0 3000.0 3300.0
-1200.0 1700.0 2200.0 2600.0 3000.0 3200.0
-1100.0 1700.0 2300.0 2600.0 3100.0 3300.0
-1200.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1100.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1200.0 2200.0 2400.0 2700.0 3300.0 3400.0
-1200.0 2300.0 2500.0 2700.0 3300.0 3400.0
-1200.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1200.0 2300.0 2600.0 2800.0 3300.0 3400.0
-1100.0 1800.0 2500.0 2600.0 3400.0 3500.0
-1300.0 1700.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1800.0 2500.0 2600.0 3200.0 3400.0
-1500.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1500.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1800.0 1900.0 2500.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2400.0 2500.0 3200.0 3300.0
-2000.0 2100.0 2300.0 2500.0 3300.0 3400.0
-1500.0 1900.0 2400.0 2800.0 3100.0 3300.0
-1200.0 1700.0 2500.0 2600.0 3300.0 3400.0
-1300.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1400.0 1800.0 2500.0 2700.0 3300.0 3400.0
-1300.0 1700.0 2400.0 2700.0 3200.0 3400.0
-1100.0 2100.0 2600.0 2700.0 3300.0 3400.0
-1200.0 2100.0 2600.0 2700.0 3300.0 3400.0
-1200.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1200.0 2100.0 2500.0 2600.0 3300.0 3400.0
-1200.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1200.0 2200.0 2500.0 2700.0 3400.0 3500.0
-1400.0 1800.0 2400.0 2600.0 3100.0 3400.0
-1400.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1500.0 1800.0 2400.0 2700.0 3100.0 3300.0
-1500.0 1900.0 2400.0 2600.0 3200.0 3400.0
-1600.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1900.0 2200.0 2400.0 2600.0 3300.0 3400.0
-2000.0 2200.0 2400.0 2600.0 3200.0 3300.0
-2000.0 2100.0 2400.0 2500.0 3200.0 3300.0
-2100.0 2200.0 2500.0 2600.0 3200.0 3300.0
-2100.0 2200.0 2500.0 2700.0 3200.0 3300.0
-2000.0 2100.0 2400.0 2600.0 3100.0 3200.0
-1500.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1500.0 1900.0 2300.0 2400.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2400.0 3100.0 3300.0
-1400.0 1800.0 2300.0 2400.0 3100.0 3300.0
-1400.0 1900.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1700.0 2200.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2200.0 2500.0 3000.0 3200.0
-1300.0 1700.0 2400.0 2600.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2500.0 3200.0 3300.0
-1400.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1100.0 1500.0 2300.0 2400.0 3200.0 3400.0
-1000.0 1600.0 2500.0 2600.0 3300.0 3400.0
-1000.0 1700.0 2500.0 2600.0 3300.0 3400.0
-1000.0 1800.0 2600.0 2700.0 3300.0 3400.0
-1000.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1000.0 1800.0 2800.0 2900.0 3300.0 3400.0
-1400.0 1600.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1700.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1700.0 2500.0 2600.0 3000.0 3400.0
-1700.0 1800.0 2500.0 2600.0 3000.0 3400.0
-1700.0 1800.0 2400.0 2600.0 2800.0 3300.0
-1700.0 1800.0 2400.0 2600.0 2900.0 3400.0
-1700.0 1800.0 2500.0 2600.0 3200.0 3400.0
-1700.0 1800.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1800.0 2500.0 2600.0 3200.0 3400.0
-1600.0 1800.0 2600.0 2700.0 3200.0 3400.0
-1600.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1600.0 2000.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2300.0 2800.0 3000.0 3300.0 3400.0
-1800.0 2100.0 2800.0 3100.0 3300.0 3400.0
-1900.0 2100.0 2700.0 2900.0 3300.0 3400.0
-1800.0 2000.0 2600.0 2800.0 3200.0 3400.0
-1700.0 1900.0 2500.0 2800.0 3100.0 3300.0
-1700.0 1800.0 2400.0 2600.0 3000.0 3300.0
-1700.0 1800.0 2500.0 2700.0 3000.0 3400.0
-1700.0 1900.0 2600.0 2700.0 3100.0 3400.0
-1600.0 1900.0 2600.0 2700.0 3000.0 3300.0
-1700.0 2000.0 2600.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1700.0 1900.0 2600.0 2800.0 3200.0 3300.0
-1600.0 1900.0 2600.0 2800.0 3200.0 3400.0
-1200.0 1800.0 2700.0 2800.0 3200.0 3400.0
-1100.0 1700.0 2700.0 2800.0 3200.0 3300.0
-1500.0 1800.0 2600.0 2700.0 3100.0 3400.0
-1500.0 1800.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1800.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1800.0 2400.0 2500.0 3100.0 3400.0
-1500.0 1700.0 2400.0 2500.0 3000.0 3400.0
-1400.0 1600.0 2400.0 2500.0 3000.0 3400.0
-1400.0 1600.0 2400.0 2600.0 2900.0 3300.0
-1200.0 1700.0 2600.0 2700.0 3100.0 3300.0
-1200.0 1800.0 2600.0 2700.0 3200.0 3400.0
-1100.0 1900.0 2600.0 2700.0 3200.0 3400.0
-1400.0 1800.0 2500.0 2700.0 3200.0 3400.0
-1700.0 1900.0 2500.0 2600.0 2900.0 3300.0
-1600.0 1700.0 2500.0 2700.0 3000.0 3400.0
-1400.0 1500.0 2500.0 2700.0 3200.0 3400.0
-1400.0 1700.0 2500.0 2700.0 3000.0 3300.0
-1800.0 2000.0 2200.0 2600.0 2900.0 3200.0
-1900.0 2100.0 2400.0 2600.0 3100.0 3300.0
-1900.0 2300.0 2400.0 2700.0 3200.0 3300.0
-1800.0 2200.0 2400.0 2700.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2400.0 3000.0 3200.0
-1500.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1500.0 1900.0 2100.0 2400.0 3100.0 3200.0
-1400.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1300.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1200.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1200.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1100.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1200.0 2200.0 2500.0 2600.0 3300.0 3400.0
-1500.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1800.0 1900.0 2300.0 2400.0 3300.0 3400.0
-2100.0 2200.0 2400.0 2600.0 3300.0 3400.0
-2200.0 2300.0 2600.0 2700.0 3300.0 3400.0
-2200.0 2300.0 2600.0 2800.0 3300.0 3400.0
-2100.0 2300.0 2500.0 2800.0 3100.0 3300.0
-2200.0 2300.0 2600.0 2700.0 3100.0 3400.0
-2100.0 2200.0 2600.0 2700.0 3200.0 3400.0
-1900.0 2300.0 2600.0 2900.0 3100.0 3300.0
-2000.0 2300.0 2600.0 2900.0 3200.0 3300.0
-2200.0 2300.0 2700.0 2900.0 3300.0 3400.0
-2000.0 2300.0 2500.0 2900.0 3300.0 3400.0
-1500.0 1700.0 2200.0 2600.0 3100.0 3300.0
-1500.0 1700.0 2200.0 2600.0 3000.0 3300.0
-1500.0 1800.0 2200.0 2600.0 3100.0 3300.0
-1500.0 1800.0 2000.0 2300.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2300.0 3200.0 3300.0
-1600.0 1900.0 2100.0 2300.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1800.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1800.0 2000.0 2400.0 2500.0 3200.0 3400.0
-1800.0 2000.0 2400.0 2600.0 3100.0 3400.0
-1800.0 1900.0 2400.0 2600.0 3100.0 3400.0
-1400.0 1600.0 2500.0 2600.0 2900.0 3300.0
-1300.0 1500.0 2500.0 2600.0 2900.0 3300.0
-1300.0 1700.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1900.0 2400.0 2800.0 3100.0 3200.0
-1500.0 2000.0 2400.0 2800.0 3100.0 3300.0
-1100.0 1700.0 2600.0 2700.0 3200.0 3400.0
-1100.0 1800.0 2600.0 2700.0 3300.0 3400.0
-1100.0 1800.0 2700.0 2800.0 3300.0 3400.0
-1700.0 2000.0 2600.0 2700.0 3100.0 3400.0
-1700.0 2100.0 2500.0 2600.0 3000.0 3200.0
-1700.0 2200.0 2600.0 2700.0 3100.0 3200.0
-1700.0 2000.0 2500.0 2600.0 3000.0 3200.0
-1700.0 1900.0 2500.0 2600.0 3000.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3000.0 3300.0
-2000.0 2200.0 2400.0 2600.0 3300.0 3400.0
-1800.0 2100.0 2400.0 2500.0 3300.0 3400.0
-1700.0 2100.0 2400.0 2500.0 3300.0 3400.0
-1500.0 2100.0 2400.0 2500.0 3300.0 3400.0
-1600.0 2100.0 2400.0 2500.0 3300.0 3400.0
-1700.0 2000.0 2300.0 2400.0 3300.0 3400.0
-1700.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1800.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1900.0 2000.0 2400.0 2500.0 3100.0 3400.0
-1900.0 2000.0 2400.0 2500.0 3000.0 3400.0
-1900.0 2000.0 2300.0 2400.0 2800.0 3300.0
-1800.0 2000.0 2200.0 2400.0 2600.0 3200.0
-1900.0 2000.0 2300.0 2500.0 2800.0 3200.0
-1700.0 2000.0 2300.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2800.0 3200.0 3300.0
-1700.0 2000.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2000.0 2600.0 2900.0 3300.0 3400.0
-1700.0 1800.0 2500.0 2700.0 3200.0 3400.0
-1600.0 1700.0 2400.0 2600.0 2900.0 3300.0
-1600.0 1700.0 2500.0 2600.0 2900.0 3300.0
-1600.0 1800.0 2600.0 2700.0 3100.0 3400.0
-1600.0 1700.0 2600.0 2700.0 3000.0 3300.0
-1600.0 1700.0 2600.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2800.0 3200.0 3400.0
-2100.0 2500.0 2700.0 3000.0 3300.0 3400.0
-2100.0 2400.0 2700.0 2900.0 3300.0 3400.0
-2200.0 2500.0 2700.0 3000.0 3300.0 3400.0
-2200.0 2500.0 2800.0 2900.0 3400.0 3500.0
-2200.0 2500.0 2800.0 2900.0 3300.0 3500.0
-2100.0 2500.0 2700.0 2800.0 3300.0 3400.0
-2100.0 2400.0 2700.0 2900.0 3200.0 3400.0
-2100.0 2300.0 2600.0 2800.0 3100.0 3400.0
-2100.0 2200.0 2500.0 2700.0 3100.0 3400.0
-2200.0 2300.0 2500.0 2700.0 3200.0 3400.0
-1900.0 2100.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1900.0 2400.0 2500.0 3100.0 3300.0
-1400.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1200.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1100.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1100.0 1700.0 2600.0 2700.0 3300.0 3400.0
-1300.0 1600.0 2500.0 2600.0 3100.0 3400.0
-1500.0 1600.0 2400.0 2500.0 3000.0 3400.0
-1600.0 1700.0 2400.0 2500.0 3100.0 3400.0
-1900.0 2000.0 2300.0 2500.0 2900.0 3400.0
-1900.0 2000.0 2400.0 2500.0 2800.0 3300.0
-1900.0 2000.0 2500.0 2700.0 3300.0 3400.0
-1900.0 2000.0 2500.0 2800.0 3300.0 3400.0
-2000.0 2200.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2200.0 2700.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2700.0 2900.0 3200.0 3300.0
-2000.0 2300.0 2700.0 2900.0 3200.0 3300.0
-2200.0 2600.0 2700.0 2900.0 3300.0 3400.0
-2100.0 2400.0 2700.0 2800.0 3300.0 3400.0
-2100.0 2200.0 2500.0 2700.0 3300.0 3400.0
-1900.0 2100.0 2400.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1500.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1200.0 1900.0 2400.0 2500.0 3300.0 3500.0
-1200.0 1600.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2100.0 2600.0 2900.0 3300.0 3400.0
-1800.0 2200.0 2700.0 3000.0 3300.0 3400.0
-1800.0 2200.0 2800.0 3000.0 3300.0 3400.0
-1700.0 2100.0 2600.0 2900.0 3200.0 3400.0
-1700.0 2000.0 2600.0 2800.0 3200.0 3400.0
-1600.0 1800.0 2500.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2500.0 2600.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2600.0 3200.0 3300.0
-1500.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2500.0 3200.0 3400.0
-1400.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1400.0 1800.0 2300.0 2400.0 3200.0 3400.0
-1600.0 1900.0 2500.0 2600.0 3200.0 3400.0
-1500.0 1900.0 2600.0 2700.0 3200.0 3400.0
-1500.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1400.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1400.0 1900.0 2600.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2600.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2600.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2700.0 2900.0 3200.0 3300.0
-2000.0 2100.0 2500.0 2700.0 3200.0 3400.0
-2000.0 2100.0 2400.0 2600.0 3100.0 3400.0
-2000.0 2100.0 2300.0 2600.0 3000.0 3300.0
-1900.0 2000.0 2300.0 2500.0 3000.0 3400.0
-1800.0 1900.0 2300.0 2400.0 3000.0 3400.0
-1600.0 1800.0 2300.0 2400.0 3000.0 3400.0
-1400.0 1700.0 2400.0 2500.0 2900.0 3400.0
-1300.0 1700.0 2400.0 2500.0 3100.0 3400.0
-1400.0 1700.0 2300.0 2600.0 3100.0 3300.0
-1200.0 1600.0 2400.0 2500.0 3200.0 3300.0
-1200.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2400.0 2600.0 3000.0 3300.0
-2000.0 2300.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2300.0 2900.0 3100.0 3400.0 3500.0
-1900.0 2100.0 2700.0 3000.0 3300.0 3400.0
-1800.0 1900.0 2300.0 2700.0 3100.0 3300.0
-1800.0 1900.0 2200.0 2500.0 3100.0 3300.0
-1700.0 1800.0 2100.0 2400.0 3000.0 3300.0
-1700.0 1800.0 2200.0 2400.0 3100.0 3300.0
-1400.0 1900.0 2100.0 2300.0 3200.0 3300.0
-1300.0 1800.0 2000.0 2300.0 3200.0 3300.0
-1300.0 1800.0 1900.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2100.0 2600.0 3200.0 3300.0
-2000.0 2100.0 2400.0 2500.0 3100.0 3400.0
-2100.0 2200.0 2400.0 2500.0 3100.0 3400.0
-2100.0 2400.0 2800.0 2900.0 3100.0 3300.0
-2000.0 2200.0 2600.0 2900.0 3200.0 3300.0
-2100.0 2200.0 2700.0 2800.0 3200.0 3300.0
-2000.0 2100.0 2700.0 2800.0 3200.0 3300.0
-2000.0 2100.0 2600.0 2800.0 3200.0 3400.0
-1900.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1800.0 1900.0 2500.0 2700.0 3300.0 3400.0
-2000.0 2100.0 2600.0 2700.0 3200.0 3300.0
-2000.0 2100.0 2600.0 2700.0 3100.0 3400.0
-1900.0 2100.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1800.0 2000.0 2600.0 2700.0 3300.0 3500.0
-1700.0 1900.0 2500.0 2700.0 3200.0 3400.0
-1800.0 2100.0 2700.0 2900.0 3200.0 3400.0
-1900.0 2200.0 2600.0 2900.0 3200.0 3300.0
-1900.0 2200.0 2700.0 2900.0 3200.0 3400.0
-1800.0 2200.0 2700.0 3000.0 3200.0 3400.0
-1800.0 2100.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2200.0 2600.0 2900.0 3300.0 3500.0
-1700.0 2100.0 2500.0 2800.0 3400.0 3500.0
-1600.0 1900.0 2400.0 2600.0 3200.0 3400.0
-1600.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1700.0 2000.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1700.0 2000.0 2300.0 2400.0 2900.0 3200.0
-1900.0 2000.0 2600.0 2700.0 3100.0 3200.0
-1900.0 2000.0 2600.0 2700.0 3100.0 3400.0
-1800.0 2000.0 2600.0 2700.0 3100.0 3300.0
-1400.0 1800.0 2300.0 2600.0 3000.0 3200.0
-1300.0 1800.0 2200.0 2500.0 3100.0 3300.0
-1300.0 1900.0 2200.0 2600.0 3100.0 3300.0
-1400.0 1800.0 2100.0 2500.0 3000.0 3200.0
-1300.0 1600.0 1700.0 2500.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2400.0 3100.0 3200.0
-1300.0 1600.0 1800.0 2300.0 3100.0 3200.0
-1500.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1500.0 1900.0 2500.0 2600.0 3000.0 3200.0
-1800.0 2200.0 2600.0 2800.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2400.0 2700.0 3100.0 3300.0
-1800.0 1900.0 2500.0 2700.0 3100.0 3300.0
-1800.0 1900.0 2600.0 2700.0 3000.0 3300.0
-2100.0 2200.0 2600.0 2700.0 3200.0 3300.0
-2100.0 2200.0 2600.0 2700.0 3300.0 3400.0
-1900.0 2100.0 2300.0 2500.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2800.0 3100.0 3300.0
-1600.0 2100.0 2500.0 2700.0 3100.0 3300.0
-1500.0 1900.0 2400.0 2700.0 3100.0 3300.0
-1200.0 1700.0 1800.0 2100.0 3200.0 3400.0
-1400.0 1700.0 1800.0 2200.0 3300.0 3400.0
-1600.0 1800.0 1900.0 2400.0 3200.0 3300.0
-1700.0 1900.0 2000.0 2500.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2400.0 2900.0 3100.0
-1800.0 2000.0 2200.0 2400.0 2800.0 3200.0
-1900.0 2100.0 2300.0 2600.0 2900.0 3300.0
-1900.0 2100.0 2300.0 2600.0 3200.0 3400.0
-2000.0 2100.0 2400.0 2500.0 3300.0 3400.0
-1800.0 1900.0 2400.0 2500.0 3200.0 3500.0
-1700.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1800.0 2000.0 2600.0 3000.0 3300.0 3400.0
-1900.0 2000.0 2500.0 2700.0 2900.0 3200.0
-1900.0 2000.0 2500.0 2700.0 2900.0 3100.0
-1900.0 2000.0 2400.0 2600.0 2900.0 3200.0
-1700.0 2000.0 2300.0 2600.0 2900.0 3200.0
-1800.0 2000.0 2300.0 2600.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2600.0 2900.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3000.0 3300.0
-1900.0 2000.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1800.0 2200.0 2600.0 3000.0 3300.0
-1600.0 1800.0 2200.0 2500.0 3000.0 3300.0
-1700.0 1900.0 2300.0 2600.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2600.0 3000.0 3200.0
-1800.0 1900.0 2400.0 2500.0 3000.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3200.0 3400.0
-1600.0 1700.0 2400.0 2600.0 3100.0 3300.0
-1600.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1600.0 2400.0 2500.0 3200.0 3400.0
-1400.0 1600.0 2400.0 2500.0 3200.0 3400.0
-1300.0 1600.0 2400.0 2500.0 3200.0 3300.0
-1400.0 2000.0 2500.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2200.0 2500.0 3000.0 3300.0
-1700.0 1900.0 2300.0 2500.0 3100.0 3300.0
-2000.0 2100.0 2400.0 2600.0 3100.0 3300.0
-2000.0 2200.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2000.0 2400.0 2500.0 3200.0 3400.0
-2100.0 2200.0 2300.0 2400.0 3200.0 3400.0
-2000.0 2100.0 2300.0 2500.0 3000.0 3400.0
-1600.0 1800.0 2100.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2200.0 2700.0 3200.0 3300.0
-1800.0 1900.0 2400.0 2800.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2800.0 3200.0 3400.0
-1700.0 2100.0 2600.0 2900.0 3300.0 3500.0
-1800.0 2200.0 2600.0 2900.0 3300.0 3500.0
-1700.0 2200.0 2600.0 2900.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2800.0 3200.0 3400.0
-1700.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1700.0 1800.0 2600.0 2700.0 3100.0 3400.0
-1700.0 1800.0 2600.0 2700.0 3200.0 3400.0
-1700.0 1900.0 2700.0 2800.0 3200.0 3400.0
-1600.0 1900.0 2700.0 2800.0 3200.0 3300.0
-1400.0 1900.0 2800.0 2900.0 3200.0 3300.0
-1600.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2600.0 2700.0 3200.0 3400.0
-1700.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1700.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1700.0 1800.0 2500.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2000.0 2400.0 2800.0 3300.0 3400.0
-1600.0 1800.0 2100.0 2400.0 3100.0 3200.0
-1700.0 1800.0 2000.0 2700.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2700.0 3100.0 3200.0
-1800.0 2000.0 2200.0 2700.0 3100.0 3200.0
-1900.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2300.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2400.0 2700.0 3100.0 3200.0
-2000.0 2100.0 2400.0 2700.0 3100.0 3200.0
-2000.0 2200.0 2400.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1800.0 2100.0 2200.0 2600.0 3100.0 3200.0
-1600.0 2000.0 2200.0 2600.0 3100.0 3200.0
-1500.0 2000.0 2200.0 2700.0 3100.0 3200.0
-1500.0 1900.0 2200.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2200.0 2600.0 3100.0 3200.0
-1800.0 2100.0 2600.0 2700.0 3100.0 3300.0
-1700.0 2100.0 2600.0 2700.0 3100.0 3300.0
-1500.0 1800.0 2600.0 2700.0 3200.0 3400.0
-1200.0 1400.0 2500.0 2700.0 3200.0 3400.0
-1400.0 1700.0 2400.0 2600.0 3200.0 3400.0
-1400.0 1600.0 2400.0 2600.0 3100.0 3400.0
-1500.0 1700.0 2500.0 2600.0 3000.0 3300.0
-1600.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2600.0 3000.0 3400.0
-2000.0 2100.0 2500.0 2600.0 3000.0 3300.0
-2100.0 2200.0 2500.0 2600.0 3100.0 3400.0
-2200.0 2300.0 2500.0 2600.0 3100.0 3400.0
-1400.0 1900.0 2300.0 2400.0 2800.0 3200.0
-1400.0 1900.0 2300.0 2400.0 2700.0 3100.0
-1500.0 1700.0 2300.0 2400.0 2800.0 3200.0
-1600.0 1700.0 2100.0 2500.0 3000.0 3300.0
-1700.0 2000.0 2400.0 2800.0 3000.0 3300.0
-1800.0 2000.0 2600.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1800.0 2000.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1800.0 2200.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2100.0 2600.0 2800.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2700.0 3000.0 3300.0
-1800.0 1900.0 2500.0 2700.0 3000.0 3300.0
-1900.0 2000.0 2500.0 2700.0 3100.0 3300.0
-1900.0 2000.0 2500.0 2700.0 3100.0 3400.0
-1700.0 1900.0 2600.0 2800.0 3200.0 3400.0
-1600.0 1900.0 2600.0 2800.0 3300.0 3400.0
-1500.0 1800.0 2500.0 2700.0 3300.0 3400.0
-1500.0 1900.0 2400.0 2500.0 3200.0 3400.0
-1200.0 1800.0 2200.0 2300.0 3100.0 3200.0
-1400.0 1900.0 2300.0 2600.0 3000.0 3300.0
-1300.0 1400.0 2300.0 2400.0 2800.0 3100.0
-1300.0 1400.0 2300.0 2500.0 3000.0 3200.0
-1300.0 1600.0 2400.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2400.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2400.0 2600.0 3000.0 3200.0
-1500.0 1700.0 2400.0 2600.0 2900.0 3200.0
-1600.0 1800.0 2400.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2500.0 2700.0 3000.0 3300.0
-1900.0 2100.0 2600.0 2700.0 3000.0 3300.0
-1900.0 2100.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2100.0 2400.0 2700.0 3100.0 3300.0
-2000.0 2200.0 2400.0 2700.0 3100.0 3300.0
-1900.0 2300.0 2600.0 2700.0 3000.0 3200.0
-2000.0 2200.0 2500.0 2600.0 3000.0 3200.0
-1900.0 2000.0 2500.0 2600.0 3000.0 3300.0
-1800.0 2000.0 2400.0 2600.0 3000.0 3300.0
-1500.0 1900.0 2300.0 2500.0 2700.0 3000.0
-1500.0 2000.0 2400.0 2500.0 2700.0 3100.0
-1200.0 1900.0 2300.0 2500.0 2800.0 3000.0
-1300.0 1800.0 2200.0 2300.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2500.0 3100.0 3200.0
-2100.0 2200.0 2600.0 2700.0 3100.0 3300.0
-2100.0 2200.0 2600.0 2700.0 3000.0 3300.0
-2000.0 2200.0 2600.0 2700.0 3100.0 3300.0
-2000.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2300.0 2400.0 3100.0 3300.0
-1500.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1600.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2100.0 2600.0 2900.0 3100.0
-1400.0 1700.0 1900.0 2300.0 2800.0 3000.0
-1500.0 1700.0 1900.0 2200.0 2800.0 2900.0
-1500.0 1700.0 2000.0 2200.0 2900.0 3000.0
-1500.0 1700.0 2100.0 2300.0 2900.0 3000.0
-1500.0 1800.0 2200.0 2300.0 3000.0 3100.0
-1500.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1600.0 1800.0 2300.0 2400.0 3100.0 3200.0
-1600.0 1800.0 2300.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1600.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1700.0 2300.0 2500.0 2900.0 3300.0
-1800.0 2100.0 2500.0 2600.0 3200.0 3300.0
-1900.0 2100.0 2400.0 2500.0 3100.0 3400.0
-1900.0 2100.0 2200.0 2500.0 3100.0 3300.0
-1700.0 1800.0 2200.0 2500.0 2900.0 3300.0
-1700.0 1800.0 2400.0 2500.0 3000.0 3300.0
-1600.0 1700.0 2400.0 2500.0 3100.0 3300.0
-1500.0 1700.0 2400.0 2500.0 3100.0 3300.0
-1400.0 1700.0 2500.0 2600.0 3100.0 3200.0
-1300.0 1600.0 2500.0 2600.0 3100.0 3200.0
-1200.0 1600.0 2500.0 2600.0 3100.0 3200.0
-1100.0 1700.0 2600.0 2700.0 3100.0 3200.0
-1100.0 1500.0 2600.0 2700.0 3100.0 3200.0
-1100.0 1500.0 2600.0 2700.0 3100.0 3300.0
-1100.0 1500.0 2500.0 2700.0 3000.0 3300.0
-1000.0 1600.0 2600.0 2700.0 3100.0 3300.0
-1300.0 1600.0 2600.0 2700.0 3100.0 3300.0
-1300.0 1600.0 2600.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2500.0 2600.0 3100.0 3300.0
-1700.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1800.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2500.0 2700.0 3100.0 3400.0
-1800.0 2100.0 2500.0 2700.0 3100.0 3300.0
-1900.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2200.0 2400.0 2600.0 3100.0 3300.0
-1900.0 2300.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2000.0 2200.0 2400.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2300.0 3200.0 3300.0
-1400.0 1600.0 2200.0 2400.0 3100.0 3200.0
-1100.0 1500.0 2300.0 2500.0 3000.0 3100.0
-1400.0 1700.0 2500.0 2700.0 3200.0 3300.0
-1500.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1800.0 2100.0 2500.0 2800.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2500.0 3200.0 3400.0
-1700.0 1900.0 2300.0 2500.0 3200.0 3400.0
-1800.0 2100.0 2500.0 2800.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2800.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2800.0 3100.0 3400.0
-1700.0 2100.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2100.0 2600.0 2700.0 3300.0 3500.0
-1900.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1600.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1400.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2400.0 3000.0 3100.0
-1300.0 1700.0 2300.0 2500.0 3000.0 3100.0
-1600.0 1700.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2300.0 2400.0 3100.0 3300.0
-2200.0 2300.0 2600.0 2800.0 3200.0 3400.0
-2100.0 2300.0 2500.0 2900.0 3200.0 3300.0
-2200.0 2300.0 2500.0 2900.0 3200.0 3300.0
-2000.0 2300.0 2500.0 2700.0 3200.0 3300.0
-2200.0 2400.0 2500.0 2700.0 3200.0 3300.0
-2200.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2500.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2600.0 2700.0 3100.0 3300.0
-1500.0 1800.0 2600.0 2700.0 3100.0 3300.0
-1600.0 1700.0 2600.0 2700.0 2900.0 3300.0
-1600.0 1700.0 2600.0 2800.0 3000.0 3300.0
-1700.0 2000.0 2700.0 2800.0 3100.0 3400.0
-1600.0 1900.0 2500.0 2700.0 3000.0 3300.0
-1800.0 2200.0 2800.0 2900.0 3300.0 3400.0
-2000.0 2500.0 2800.0 2900.0 3400.0 3500.0
-2000.0 2400.0 2800.0 2900.0 3400.0 3500.0
-2000.0 2300.0 2700.0 2800.0 3200.0 3400.0
-1600.0 1700.0 2400.0 2600.0 3200.0 3300.0
-1500.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1400.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1400.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1700.0 2500.0 2600.0 3100.0 3300.0
-1300.0 1500.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1400.0 2400.0 2500.0 3100.0 3300.0
-1200.0 1500.0 2400.0 2500.0 3100.0 3300.0
-1200.0 1600.0 2400.0 2500.0 3100.0 3300.0
-1200.0 1700.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1200.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1200.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1200.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1200.0 1700.0 2400.0 2500.0 3100.0 3200.0
-1200.0 1600.0 2400.0 2500.0 3000.0 3200.0
-1200.0 1600.0 2400.0 2500.0 2900.0 3100.0
-1200.0 1700.0 2400.0 2500.0 3000.0 3300.0
-1300.0 1700.0 2400.0 2500.0 3100.0 3300.0
-1200.0 1700.0 2400.0 2500.0 3000.0 3100.0
-1200.0 1700.0 2300.0 2400.0 3000.0 3100.0
-1600.0 2000.0 2300.0 2600.0 3000.0 3300.0
-1400.0 1600.0 1900.0 2200.0 3000.0 3100.0
-1400.0 1600.0 1800.0 2100.0 3000.0 3100.0
-1300.0 1500.0 1600.0 2000.0 3100.0 3200.0
-1300.0 1500.0 1700.0 1900.0 3100.0 3200.0
-1400.0 1600.0 1700.0 1900.0 3100.0 3200.0
-1600.0 1700.0 2000.0 2100.0 3100.0 3200.0
-1600.0 1800.0 2100.0 2200.0 3100.0 3200.0
-1800.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2700.0 3100.0 3400.0
-1900.0 2000.0 2500.0 2600.0 3000.0 3400.0
-1800.0 2100.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2300.0 2600.0 2800.0 3300.0 3500.0
-1600.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2500.0 2600.0 3100.0 3300.0
-1300.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1400.0 1800.0 2600.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2500.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1900.0 2000.0 2500.0 2700.0 2900.0 3300.0
-2000.0 2100.0 2400.0 2600.0 2900.0 3200.0
-2000.0 2100.0 2400.0 2600.0 3000.0 3300.0
-2100.0 2200.0 2400.0 2600.0 3000.0 3300.0
-2000.0 2100.0 2500.0 2600.0 3100.0 3400.0
-1900.0 2000.0 2400.0 2600.0 3000.0 3400.0
-1800.0 1900.0 2300.0 2500.0 2900.0 3400.0
-1700.0 1800.0 2500.0 2700.0 3100.0 3400.0
-1700.0 1900.0 2500.0 2700.0 3100.0 3400.0
-1800.0 1900.0 2700.0 2800.0 3200.0 3400.0
-2100.0 2200.0 2600.0 2800.0 3100.0 3400.0
-2200.0 2300.0 2600.0 2800.0 3100.0 3400.0
-1800.0 2300.0 2500.0 2700.0 3100.0 3300.0
-1500.0 2000.0 2400.0 2500.0 2800.0 3100.0
-1600.0 2000.0 2400.0 2500.0 2800.0 3100.0
-1600.0 2000.0 2400.0 2500.0 2800.0 3200.0
-1600.0 2000.0 2400.0 2500.0 2900.0 3300.0
-1800.0 2200.0 2500.0 2600.0 3000.0 3300.0
-2100.0 2300.0 2500.0 2600.0 3100.0 3300.0
-2100.0 2200.0 2600.0 2700.0 3100.0 3200.0
-1800.0 1900.0 2600.0 2700.0 3100.0 3200.0
-1800.0 1900.0 2600.0 2700.0 3100.0 3300.0
-1700.0 1800.0 2600.0 2700.0 3100.0 3300.0
-1700.0 1800.0 2600.0 2700.0 3200.0 3300.0
-1600.0 1700.0 2600.0 2700.0 3200.0 3400.0
-1600.0 1700.0 2500.0 2700.0 3200.0 3300.0
-1500.0 1800.0 2400.0 2500.0 3000.0 3300.0
-1500.0 1900.0 2300.0 2500.0 3000.0 3200.0
-1700.0 2100.0 2300.0 2600.0 3100.0 3300.0
-1800.0 2000.0 2700.0 2800.0 3100.0 3300.0
-1700.0 1800.0 2500.0 2700.0 2900.0 3300.0
-1600.0 1800.0 2500.0 2700.0 3000.0 3300.0
-1700.0 1800.0 2400.0 2600.0 3100.0 3300.0
-1700.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1800.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2500.0 3200.0 3300.0
-2000.0 2100.0 2300.0 2500.0 3200.0 3400.0
-2000.0 2100.0 2200.0 2400.0 3200.0 3400.0
-2000.0 2100.0 2300.0 2400.0 3100.0 3400.0
-1700.0 1900.0 2400.0 2500.0 3200.0 3400.0
-1700.0 1900.0 2400.0 2500.0 3100.0 3400.0
-1700.0 1800.0 2400.0 2600.0 3300.0 3400.0
-1700.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1600.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1700.0 1900.0 2600.0 2800.0 3100.0 3300.0
-1700.0 2100.0 2600.0 2700.0 3300.0 3400.0
-1800.0 2000.0 2400.0 2500.0 3100.0 3300.0
-2000.0 2100.0 2300.0 2400.0 3200.0 3400.0
-1400.0 1900.0 2300.0 2400.0 3000.0 3300.0
-1400.0 2000.0 2300.0 2500.0 3000.0 3100.0
-1400.0 1700.0 2500.0 2600.0 3100.0 3300.0
-1300.0 1600.0 2400.0 2600.0 3100.0 3300.0
-1300.0 1600.0 2400.0 2500.0 3200.0 3400.0
-1500.0 2000.0 2500.0 2700.0 3200.0 3400.0
-1800.0 2100.0 2500.0 2900.0 3200.0 3400.0
-1800.0 2200.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2000.0 2500.0 2900.0 3300.0 3400.0
-1700.0 2100.0 2600.0 2900.0 3400.0 3500.0
-1500.0 1900.0 2400.0 2800.0 3300.0 3400.0
-1800.0 2100.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2000.0 2600.0 2800.0 3300.0 3400.0
-1700.0 2100.0 2600.0 2800.0 3200.0 3400.0
-1900.0 2200.0 2600.0 2800.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2100.0 2700.0 2800.0 3300.0 3400.0
-1700.0 2100.0 2700.0 2800.0 3200.0 3400.0
-1800.0 2200.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2200.0 2600.0 2700.0 3300.0 3400.0
-1800.0 2300.0 2600.0 2700.0 3300.0 3400.0
-1900.0 2300.0 2500.0 2700.0 3300.0 3400.0
-1800.0 2200.0 2500.0 2800.0 3200.0 3400.0
-1800.0 2200.0 2500.0 2700.0 3100.0 3300.0
-1700.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1800.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1800.0 2000.0 2200.0 2500.0 3300.0 3400.0
-1800.0 2000.0 2200.0 2600.0 3300.0 3400.0
-1500.0 1800.0 1900.0 2400.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2500.0 3200.0 3300.0
-1500.0 1800.0 1900.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2400.0 3300.0 3400.0
-1500.0 1700.0 2200.0 2600.0 3000.0 3200.0
-1400.0 1700.0 2000.0 2600.0 3000.0 3200.0
-1500.0 1900.0 2400.0 2600.0 3100.0 3200.0
-1400.0 1900.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1600.0 2500.0 2700.0 3100.0 3300.0
-1200.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1800.0 2300.0 2400.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2300.0 3200.0 3300.0
-1800.0 1900.0 2200.0 2300.0 3300.0 3400.0
-1800.0 2100.0 2300.0 2400.0 2900.0 3200.0
-1900.0 2100.0 2300.0 2500.0 3000.0 3300.0
-1900.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1600.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1700.0 2300.0 2400.0 3200.0 3300.0
-1500.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1600.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2200.0 2500.0 2700.0 3300.0 3400.0
-1800.0 2300.0 2500.0 2700.0 3300.0 3400.0
-1800.0 2400.0 2500.0 2900.0 3300.0 3400.0
-1900.0 2400.0 2600.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2700.0 3000.0 3400.0 3500.0
-1800.0 2100.0 2500.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2900.0 3200.0 3400.0
-1800.0 2100.0 2600.0 2800.0 3100.0 3400.0
-1800.0 2200.0 2700.0 2800.0 3200.0 3400.0
-1800.0 2300.0 2700.0 2900.0 3300.0 3500.0
-1400.0 2000.0 2600.0 2700.0 3200.0 3400.0
-1300.0 1800.0 2200.0 2300.0 3000.0 3100.0
-1300.0 1700.0 2100.0 2200.0 3100.0 3200.0
-1400.0 1700.0 2000.0 2200.0 3000.0 3100.0
-1400.0 1600.0 2000.0 2100.0 3000.0 3100.0
-1500.0 1800.0 2000.0 2300.0 3100.0 3200.0
-1600.0 1800.0 2000.0 2300.0 3100.0 3200.0
-1600.0 1800.0 2000.0 2200.0 3100.0 3200.0
-1700.0 2000.0 2200.0 2300.0 3000.0 3200.0
-1700.0 2100.0 2400.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2600.0 2800.0 3000.0 3200.0
-1700.0 1900.0 2600.0 2700.0 3200.0 3400.0
-1600.0 1700.0 2400.0 2600.0 3200.0 3400.0
-1600.0 1700.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2100.0 2500.0 2800.0 3200.0 3300.0
-1700.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1700.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2500.0 3100.0 3300.0
-1500.0 1900.0 2100.0 2400.0 3100.0 3300.0
-1500.0 1600.0 2000.0 2300.0 3000.0 3200.0
-1500.0 1700.0 2100.0 2500.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2700.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2600.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2500.0 3000.0 3200.0
-1400.0 1700.0 2400.0 2500.0 3000.0 3200.0
-1200.0 1500.0 2500.0 2600.0 3000.0 3100.0
-1100.0 1900.0 2600.0 2700.0 3000.0 3100.0
-1500.0 2000.0 2700.0 2800.0 3200.0 3400.0
-1700.0 2100.0 2700.0 2800.0 3300.0 3400.0
-1800.0 2200.0 2700.0 2800.0 3300.0 3400.0
-1800.0 2400.0 2700.0 2800.0 3200.0 3300.0
-1800.0 2300.0 2500.0 2600.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2400.0 3000.0 3200.0
-1400.0 1600.0 1800.0 2200.0 3000.0 3100.0
-1300.0 1600.0 1700.0 2100.0 3000.0 3100.0
-1200.0 1400.0 1600.0 2400.0 3000.0 3100.0
-1300.0 1500.0 1600.0 2100.0 3000.0 3100.0
-1400.0 1600.0 1700.0 2100.0 3000.0 3100.0
-1400.0 1700.0 2100.0 2300.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2300.0 3100.0 3200.0
-1400.0 1600.0 2200.0 2300.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2400.0 3100.0 3200.0
-1400.0 1700.0 2300.0 2400.0 3100.0 3200.0
-1400.0 1600.0 2300.0 2400.0 3100.0 3200.0
-1400.0 1600.0 2200.0 2300.0 3000.0 3200.0
-1500.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1700.0 2000.0 2700.0 2800.0 3200.0 3400.0
-2100.0 2400.0 2800.0 2900.0 3200.0 3400.0
-2000.0 2500.0 2700.0 2800.0 3400.0 3500.0
-2100.0 2600.0 2800.0 2900.0 3400.0 3500.0
-2000.0 2500.0 2700.0 2800.0 3300.0 3400.0
-1900.0 2100.0 2700.0 2800.0 3200.0 3400.0
-2100.0 2200.0 2700.0 2800.0 3200.0 3400.0
-2100.0 2200.0 2700.0 2900.0 3300.0 3400.0
-2200.0 2300.0 2700.0 2800.0 3200.0 3400.0
-1700.0 2100.0 2400.0 2700.0 3200.0 3400.0
-1600.0 2100.0 2400.0 2600.0 2900.0 3200.0
-1500.0 2100.0 2400.0 2500.0 2800.0 3100.0
-1600.0 2100.0 2400.0 2500.0 2800.0 3200.0
-1600.0 2100.0 2400.0 2500.0 2900.0 3200.0
-1600.0 2100.0 2400.0 2500.0 3000.0 3200.0
-1600.0 2100.0 2300.0 2500.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2600.0 3100.0 3300.0
-1700.0 1900.0 2300.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2500.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2200.0 2500.0 3100.0 3300.0
-1500.0 1700.0 1900.0 2200.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2100.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2300.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2400.0 3200.0 3300.0
-1500.0 1700.0 1800.0 2400.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2200.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2100.0 3200.0 3300.0
-1500.0 1600.0 1900.0 2000.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2100.0 3200.0 3300.0
-1600.0 1700.0 2000.0 2100.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2300.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1700.0 2000.0 2400.0 2600.0 3000.0 3100.0
-1700.0 2100.0 2400.0 2600.0 3000.0 3100.0
-1600.0 2000.0 2400.0 2600.0 2900.0 3100.0
-1800.0 2200.0 2600.0 2800.0 3000.0 3200.0
-2000.0 2400.0 2500.0 2800.0 3100.0 3200.0
-2100.0 2500.0 2600.0 2800.0 3200.0 3300.0
-2200.0 2500.0 2700.0 3000.0 3200.0 3300.0
-2100.0 2500.0 2700.0 3000.0 3200.0 3300.0
-2200.0 2500.0 2600.0 3000.0 3200.0 3300.0
-2200.0 2500.0 2600.0 2900.0 3200.0 3300.0
-2200.0 2400.0 2600.0 2800.0 3100.0 3300.0
-2000.0 2300.0 2500.0 2700.0 3100.0 3200.0
-2000.0 2200.0 2500.0 2700.0 3100.0 3200.0
-2000.0 2300.0 2500.0 2800.0 3100.0 3200.0
-2000.0 2300.0 2400.0 2800.0 3100.0 3200.0
-2100.0 2200.0 2500.0 2800.0 3100.0 3200.0
-2000.0 2100.0 2500.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2400.0 3100.0 3300.0
-1500.0 1600.0 1800.0 2100.0 3200.0 3300.0
-1500.0 1700.0 1800.0 2100.0 3200.0 3300.0
-1500.0 1700.0 1800.0 2300.0 3200.0 3300.0
-2000.0 2200.0 2400.0 2600.0 3000.0 3200.0
-2000.0 2400.0 2600.0 2800.0 3100.0 3300.0
-2000.0 2400.0 2500.0 2700.0 3100.0 3300.0
-1800.0 2200.0 2500.0 2600.0 3100.0 3300.0
-1600.0 1800.0 2400.0 2500.0 3000.0 3200.0
-1500.0 1800.0 2400.0 2500.0 3000.0 3100.0
-1800.0 2000.0 2200.0 2700.0 3000.0 3300.0
-1600.0 1900.0 2100.0 2600.0 3000.0 3200.0
-1500.0 1700.0 1900.0 2300.0 3000.0 3100.0
-1500.0 1700.0 1900.0 2200.0 3000.0 3100.0
-1600.0 1700.0 2200.0 2400.0 2900.0 3000.0
-1600.0 1800.0 2200.0 2400.0 2900.0 3000.0
-1800.0 2300.0 2600.0 2700.0 3200.0 3400.0
-1800.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1800.0 1900.0 2400.0 2600.0 3300.0 3400.0
-1700.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1600.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2400.0 2600.0 3100.0 3200.0
-2000.0 2100.0 2500.0 2600.0 3200.0 3300.0
-2100.0 2200.0 2400.0 2600.0 3200.0 3400.0
-1700.0 2000.0 2400.0 2600.0 3100.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1600.0 1900.0 2200.0 2500.0 3000.0 3100.0
-1500.0 1800.0 2000.0 2300.0 3000.0 3100.0
-1500.0 1700.0 1900.0 2100.0 2900.0 3000.0
-1400.0 1600.0 2400.0 2700.0 2900.0 3100.0
-1400.0 1600.0 2300.0 2600.0 3000.0 3100.0
-1500.0 1600.0 2300.0 2500.0 2900.0 3100.0
-1600.0 1700.0 2400.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2400.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2600.0 3100.0 3200.0
-1700.0 2100.0 2400.0 2600.0 3100.0 3200.0
-1600.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2200.0 2300.0 3100.0 3300.0
-1400.0 1600.0 2200.0 2300.0 3200.0 3300.0
-1300.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1200.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1200.0 1700.0 2400.0 2500.0 3300.0 3400.0
-1500.0 1700.0 2300.0 2500.0 3100.0 3200.0
-1900.0 2000.0 2300.0 2400.0 3200.0 3300.0
-2200.0 2300.0 2500.0 2700.0 3200.0 3300.0
-2100.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1300.0 1900.0 2300.0 2400.0 3100.0 3300.0
-1800.0 2000.0 2400.0 2700.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2400.0 3000.0 3300.0
-1600.0 2000.0 2400.0 2700.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2600.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2600.0 3000.0 3300.0
-1800.0 2100.0 2400.0 2500.0 3100.0 3300.0
-1700.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1600.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2300.0 3200.0 3400.0
-1400.0 1600.0 2200.0 2300.0 3200.0 3400.0
-1300.0 1500.0 2200.0 2300.0 3200.0 3300.0
-1200.0 1600.0 2300.0 2400.0 3300.0 3400.0
-1200.0 1500.0 2300.0 2400.0 3200.0 3400.0
-1200.0 1400.0 2300.0 2400.0 3100.0 3400.0
-1300.0 1500.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2300.0 2600.0 2700.0 3300.0 3400.0
-1800.0 2400.0 2700.0 3000.0 3300.0 3400.0
-1800.0 2300.0 2700.0 2800.0 3200.0 3300.0
-1800.0 2200.0 2500.0 2600.0 3300.0 3400.0
-1700.0 1900.0 2400.0 2600.0 3200.0 3400.0
-1700.0 1800.0 2200.0 2500.0 3200.0 3400.0
-1500.0 1700.0 2300.0 2500.0 3100.0 3300.0
-1400.0 1700.0 2200.0 2400.0 3000.0 3200.0
-1300.0 1600.0 2200.0 2300.0 3000.0 3100.0
-1300.0 1900.0 2200.0 2400.0 2900.0 3100.0
-1400.0 1900.0 2300.0 2400.0 3000.0 3100.0
-1400.0 1900.0 2300.0 2500.0 2900.0 3100.0
-1400.0 1800.0 2400.0 2600.0 2800.0 3100.0
-1600.0 2000.0 2500.0 2700.0 3100.0 3300.0
-1500.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1500.0 2100.0 2600.0 2900.0 3300.0 3400.0
-1800.0 2300.0 2600.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2600.0 2700.0 3300.0 3400.0
-2000.0 2200.0 2500.0 2700.0 3000.0 3100.0
-2000.0 2300.0 2600.0 2800.0 3100.0 3200.0
-2100.0 2400.0 2500.0 2900.0 3200.0 3300.0
-2100.0 2300.0 2500.0 2800.0 3100.0 3200.0
-1900.0 2200.0 2300.0 2700.0 3100.0 3200.0
-1200.0 1900.0 2000.0 2300.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2100.0 3200.0 3300.0
-1400.0 1600.0 1700.0 2100.0 3200.0 3300.0
-1400.0 1600.0 1700.0 2200.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2600.0 2900.0 3100.0
-1900.0 2300.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2700.0 2900.0 3200.0 3400.0
-1800.0 2100.0 2700.0 2800.0 3100.0 3400.0
-1800.0 2100.0 2600.0 2800.0 3000.0 3200.0
-1800.0 2100.0 2700.0 2800.0 3200.0 3400.0
-1400.0 1600.0 2600.0 2700.0 3000.0 3300.0
-1400.0 1500.0 2600.0 2700.0 3000.0 3400.0
-1300.0 1400.0 2400.0 2800.0 3000.0 3300.0
-1800.0 2200.0 2600.0 2900.0 3200.0 3400.0
-1600.0 2100.0 2600.0 2900.0 3200.0 3400.0
-1200.0 1700.0 2500.0 2600.0 3000.0 3100.0
-1200.0 1800.0 2300.0 2600.0 3000.0 3100.0
-1200.0 1800.0 2300.0 2500.0 3000.0 3100.0
-1300.0 1700.0 2400.0 2500.0 3000.0 3100.0
-1500.0 1800.0 2400.0 2500.0 2900.0 3000.0
-1600.0 2300.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2200.0 2700.0 2900.0 3100.0 3200.0
-1900.0 2200.0 2800.0 2900.0 3100.0 3200.0
-1900.0 2300.0 2800.0 2900.0 3200.0 3300.0
-2200.0 2500.0 2800.0 3000.0 3300.0 3400.0
-2100.0 2500.0 2800.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2700.0 2800.0 3300.0 3500.0
-1900.0 2200.0 2600.0 2800.0 3300.0 3400.0
-1900.0 2100.0 2700.0 2800.0 3300.0 3400.0
-1700.0 1900.0 2600.0 2700.0 3000.0 3300.0
-1600.0 1700.0 2500.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2600.0 2800.0 3100.0 3300.0
-1800.0 1900.0 2500.0 2800.0 3000.0 3300.0
-1900.0 2000.0 2600.0 2800.0 3100.0 3400.0
-2000.0 2100.0 2500.0 2700.0 3000.0 3300.0
-2100.0 2200.0 2500.0 2700.0 3000.0 3300.0
-2100.0 2200.0 2500.0 2800.0 3000.0 3300.0
-2000.0 2100.0 2400.0 2700.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2600.0 2800.0 3100.0
-1700.0 2000.0 2500.0 2700.0 3100.0 3300.0
-1700.0 2100.0 2700.0 2800.0 3100.0 3300.0
-1500.0 1700.0 2400.0 2600.0 3100.0 3400.0
-1500.0 1600.0 2400.0 2500.0 3000.0 3300.0
-1400.0 1600.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1500.0 2300.0 2600.0 3100.0 3300.0
-1500.0 1600.0 2400.0 2600.0 2900.0 3200.0
-1600.0 1700.0 2300.0 2600.0 3000.0 3200.0
-1600.0 1700.0 2300.0 2700.0 3000.0 3200.0
-1700.0 1800.0 2400.0 2600.0 3000.0 3200.0
-1600.0 1700.0 2300.0 2500.0 3100.0 3200.0
-1500.0 1600.0 2200.0 2400.0 3100.0 3200.0
-1300.0 1800.0 2200.0 2400.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2400.0 3000.0 3200.0
-1200.0 1700.0 2300.0 2400.0 2900.0 3100.0
-1200.0 1800.0 2400.0 2500.0 2900.0 3200.0
-1200.0 1800.0 2300.0 2500.0 3100.0 3200.0
-1300.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1300.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1200.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1200.0 1500.0 2400.0 2500.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2400.0 2700.0 3000.0 3300.0
-1800.0 2000.0 2300.0 2600.0 3000.0 3300.0
-1900.0 2000.0 2300.0 2400.0 3200.0 3500.0
-1900.0 2000.0 2300.0 2400.0 3100.0 3400.0
-1800.0 2000.0 2300.0 2500.0 3200.0 3400.0
-1700.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1800.0 2100.0 2500.0 2800.0 3100.0 3400.0
-1800.0 2000.0 2500.0 2800.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2600.0 3100.0 3300.0
-1700.0 2100.0 2500.0 2700.0 3100.0 3400.0
-1600.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1500.0 2200.0 2400.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2300.0 2700.0 3300.0 3400.0
-1400.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1600.0 2000.0 2300.0 2600.0 3300.0 3400.0
-1600.0 2100.0 2300.0 2600.0 3300.0 3400.0
-1700.0 1900.0 2300.0 2600.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2400.0 3300.0 3400.0
-1900.0 2000.0 2200.0 2400.0 3300.0 3400.0
-1700.0 1800.0 2200.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2100.0 2500.0 3000.0 3200.0
-1500.0 1700.0 2100.0 2500.0 3000.0 3200.0
-1500.0 1600.0 2100.0 2500.0 3000.0 3200.0
-1500.0 1700.0 2200.0 2700.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1700.0 1800.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2100.0 2500.0 3100.0 3300.0
-2000.0 2300.0 2700.0 2800.0 3100.0 3300.0
-2200.0 2500.0 2900.0 3000.0 3200.0 3300.0
-2300.0 2500.0 2900.0 3000.0 3200.0 3300.0
-1400.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1600.0 2000.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1900.0 2000.0 2400.0 3200.0 3300.0
-1300.0 1800.0 2000.0 2400.0 3300.0 3400.0
-1400.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1800.0 2200.0 2600.0 3000.0 3300.0 3400.0
-1900.0 2200.0 2800.0 2900.0 3300.0 3400.0
-2000.0 2500.0 2900.0 3100.0 3200.0 3300.0
-2000.0 2400.0 2900.0 3000.0 3300.0 3400.0
-2100.0 2400.0 2800.0 3000.0 3200.0 3300.0
-2000.0 2400.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2600.0 2800.0 3200.0 3300.0
-1500.0 1900.0 2300.0 2700.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2600.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2500.0 3200.0 3400.0
-1100.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1000.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1000.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1000.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1100.0 1900.0 2400.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2700.0 3100.0 3400.0
-1700.0 2100.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2200.0 2600.0 2800.0 3100.0 3300.0
-2100.0 2200.0 2600.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2400.0 2700.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2600.0 3100.0 3200.0
-1400.0 1500.0 1800.0 2800.0 3200.0 3300.0
-1300.0 1500.0 1700.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2400.0 2700.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2300.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2200.0 2600.0 3000.0 3200.0
-1200.0 1600.0 1800.0 2000.0 3100.0 3400.0
-1100.0 1600.0 2400.0 2500.0 3000.0 3300.0
-1400.0 1700.0 2300.0 2400.0 2900.0 3200.0
-1700.0 2000.0 2300.0 2700.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2400.0 3000.0 3400.0
-1700.0 1800.0 2300.0 2400.0 2900.0 3400.0
-1700.0 1800.0 2300.0 2400.0 2800.0 3300.0
-1800.0 1900.0 2300.0 2400.0 2800.0 3200.0
-1800.0 1900.0 2300.0 2400.0 3000.0 3300.0
-1800.0 1900.0 2300.0 2400.0 2900.0 3300.0
-1700.0 1800.0 2200.0 2300.0 2600.0 3200.0
-1700.0 1800.0 2200.0 2300.0 2700.0 3200.0
-1700.0 1800.0 2300.0 2400.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2400.0 3100.0 3400.0
-1700.0 1800.0 2200.0 2400.0 3200.0 3400.0
-1700.0 1900.0 2200.0 2400.0 3300.0 3400.0
-1800.0 1900.0 2200.0 2400.0 3200.0 3400.0
-1800.0 1900.0 2300.0 2400.0 3200.0 3400.0
-1800.0 1900.0 2300.0 2400.0 3100.0 3400.0
-1800.0 2000.0 2200.0 2400.0 3200.0 3300.0
-1800.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1700.0 1800.0 2000.0 2200.0 3200.0 3300.0
-1400.0 1700.0 1800.0 2200.0 3200.0 3300.0
-1400.0 1800.0 2100.0 2500.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2300.0 2500.0 2900.0 3200.0
-1800.0 2200.0 2500.0 2700.0 3000.0 3300.0
-2000.0 2400.0 2700.0 2800.0 3100.0 3300.0
-2200.0 2500.0 2800.0 2900.0 3200.0 3300.0
-1500.0 2300.0 2500.0 2900.0 3300.0 3400.0
-1500.0 1700.0 2300.0 2600.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2600.0 3000.0 3300.0
-1600.0 1700.0 2200.0 2300.0 3200.0 3400.0
-1600.0 1700.0 2200.0 2300.0 3300.0 3400.0
-1200.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1000.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1000.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1300.0 1700.0 2200.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2500.0 2700.0 3000.0 3200.0
-1300.0 1900.0 2400.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2700.0 3100.0 3200.0
-1700.0 2100.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2400.0 2500.0 3200.0 3400.0
-1600.0 2000.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2300.0 2400.0 3000.0 3200.0
-1500.0 1900.0 2200.0 2300.0 3000.0 3200.0
-1500.0 2000.0 2200.0 2400.0 3100.0 3200.0
-1400.0 2000.0 2200.0 2400.0 3100.0 3200.0
-1300.0 2000.0 2200.0 2500.0 3100.0 3200.0
-1100.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1000.0 2000.0 2400.0 2500.0 3100.0 3200.0
-1000.0 1700.0 2400.0 2500.0 3100.0 3200.0
-1000.0 1600.0 2400.0 2500.0 3100.0 3200.0
-1100.0 1600.0 2400.0 2500.0 3100.0 3200.0
-1100.0 1600.0 2400.0 2600.0 3100.0 3200.0
-1100.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1100.0 1500.0 2500.0 2600.0 3200.0 3300.0
-1100.0 1500.0 2500.0 2600.0 3100.0 3200.0
-1200.0 1400.0 2400.0 2600.0 3100.0 3200.0
-1300.0 1700.0 2300.0 2400.0 3200.0 3300.0
-1300.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1400.0 1900.0 2300.0 2400.0 3100.0 3300.0
-1500.0 1700.0 2300.0 2400.0 3000.0 3200.0
-1500.0 1700.0 2300.0 2400.0 3000.0 3300.0
-2100.0 2300.0 2800.0 3000.0 3300.0 3400.0
-2200.0 2400.0 2900.0 3000.0 3200.0 3300.0
-2100.0 2300.0 2900.0 3000.0 3300.0 3400.0
-2000.0 2300.0 2600.0 3000.0 3200.0 3300.0
-1300.0 1600.0 2200.0 2600.0 3100.0 3300.0
-1000.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1000.0 2100.0 2400.0 2600.0 3300.0 3400.0
-1300.0 1700.0 1900.0 2100.0 3100.0 3200.0
-1500.0 1800.0 2000.0 2400.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2100.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2500.0 3300.0 3400.0
-1700.0 1900.0 2100.0 2500.0 2900.0 3200.0
-1600.0 1900.0 2100.0 2300.0 2800.0 3200.0
-1200.0 1700.0 2200.0 2600.0 3000.0 3300.0
-1200.0 1700.0 2300.0 2600.0 3100.0 3300.0
-1600.0 2100.0 2400.0 2700.0 3100.0 3300.0
-1500.0 2000.0 2400.0 2600.0 3100.0 3400.0
-2100.0 2200.0 2700.0 3000.0 3200.0 3300.0
-2100.0 2200.0 2700.0 2900.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2600.0 2900.0 3200.0
-1400.0 1600.0 1800.0 2900.0 3200.0 3300.0
-1600.0 1700.0 1900.0 2500.0 3100.0 3200.0
-1700.0 1800.0 2000.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2300.0 3100.0 3200.0
-2300.0 2500.0 2800.0 2900.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2800.0 3200.0 3300.0
-1500.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2400.0 3100.0 3300.0
-1600.0 1800.0 2200.0 2300.0 3000.0 3300.0
-1700.0 1800.0 2200.0 2300.0 3000.0 3300.0
-1700.0 1900.0 2200.0 2400.0 3100.0 3300.0
-1700.0 1900.0 2200.0 2400.0 3100.0 3400.0
-1700.0 1800.0 2200.0 2400.0 3100.0 3400.0
-1500.0 1800.0 2300.0 2400.0 2900.0 3300.0
-1500.0 1700.0 2200.0 2400.0 3100.0 3400.0
-1400.0 1700.0 2200.0 2300.0 3100.0 3400.0
-1600.0 1900.0 2500.0 2700.0 3200.0 3400.0
-1500.0 1800.0 2400.0 2600.0 3000.0 3300.0
-1400.0 2100.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1800.0 2100.0 2300.0 3200.0 3300.0
-1800.0 2100.0 2600.0 2900.0 3100.0 3200.0
-2000.0 2400.0 2900.0 3100.0 3300.0 3400.0
-1500.0 1800.0 2200.0 2400.0 3300.0 3400.0
-1500.0 2000.0 2100.0 2700.0 3300.0 3400.0
-1600.0 1800.0 2000.0 2400.0 2900.0 3100.0
-1600.0 1800.0 2200.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2100.0 2600.0 3000.0 3200.0
-1600.0 1900.0 2100.0 2400.0 3000.0 3300.0
-1600.0 2000.0 2200.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2100.0 2400.0 3300.0 3400.0
-1400.0 1700.0 2200.0 2600.0 3000.0 3200.0
-1300.0 1600.0 2200.0 2500.0 3000.0 3200.0
-1300.0 1500.0 2100.0 2500.0 3000.0 3300.0
-1200.0 1600.0 1700.0 2400.0 3300.0 3400.0
-1300.0 1600.0 1700.0 2500.0 3300.0 3400.0
-1300.0 1600.0 1700.0 2500.0 3200.0 3300.0
-1400.0 1700.0 1800.0 2500.0 3200.0 3300.0
-1500.0 1800.0 2000.0 2500.0 3200.0 3300.0
-1500.0 1900.0 2000.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2400.0 3200.0 3300.0
-1600.0 1900.0 2100.0 2400.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2200.0 3000.0 3300.0
-1400.0 1600.0 2100.0 2200.0 3000.0 3200.0
-1400.0 1800.0 2100.0 2300.0 3000.0 3200.0
-1600.0 2100.0 2300.0 2700.0 3100.0 3300.0
-1200.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1600.0 2100.0 2200.0 2600.0 3300.0 3400.0
-1300.0 2000.0 2200.0 2500.0 3300.0 3400.0
-1300.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1300.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2800.0 3100.0 3300.0
-1900.0 2200.0 2500.0 2900.0 3100.0 3300.0
-2000.0 2100.0 2600.0 2800.0 3200.0 3300.0
-2000.0 2100.0 2700.0 2900.0 3200.0 3300.0
-1000.0 1900.0 2400.0 2600.0 3300.0 3400.0
-1000.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1000.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1000.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1000.0 1800.0 2400.0 2600.0 3300.0 3400.0
-1000.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1400.0 1700.0 2200.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2500.0 3000.0 3300.0
-1300.0 1800.0 2100.0 2400.0 3200.0 3300.0
-1100.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1100.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1100.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1100.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1100.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1200.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2400.0 3300.0 3400.0
-1500.0 1800.0 2200.0 2300.0 3300.0 3400.0
-1700.0 2200.0 2700.0 3000.0 3300.0 3400.0
-1900.0 2200.0 2800.0 3000.0 3200.0 3300.0
-1900.0 2200.0 2500.0 3000.0 3200.0 3300.0
-1600.0 2100.0 2300.0 2700.0 3300.0 3400.0
-1600.0 2000.0 2300.0 2700.0 3300.0 3400.0
-1600.0 2100.0 2500.0 3000.0 3300.0 3400.0
-1600.0 2200.0 2600.0 3000.0 3300.0 3400.0
-1900.0 2400.0 2900.0 3100.0 3300.0 3400.0
-2100.0 2500.0 2900.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2900.0 3000.0 3200.0 3300.0
-1700.0 2200.0 2400.0 2900.0 3200.0 3300.0
-1300.0 1800.0 2100.0 2500.0 3200.0 3300.0
-1500.0 1600.0 1800.0 2300.0 3000.0 3200.0
-1500.0 1600.0 1900.0 2000.0 3000.0 3300.0
-1400.0 1800.0 2200.0 2600.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2400.0 2900.0 3100.0
-1500.0 1700.0 2100.0 2400.0 2900.0 3100.0
-1400.0 1700.0 2100.0 2400.0 3000.0 3200.0
-1400.0 1700.0 2300.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2600.0 3200.0 3300.0
-1000.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1400.0 1900.0 2000.0 2500.0 3200.0 3300.0
-1600.0 1900.0 2100.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2300.0 2500.0 3200.0 3300.0
-2200.0 2400.0 2800.0 3000.0 3200.0 3300.0
-1900.0 2300.0 2400.0 2700.0 3100.0 3200.0
-1900.0 2200.0 2300.0 2600.0 3100.0 3200.0
-1900.0 2100.0 2300.0 2800.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2700.0 3200.0 3300.0
-1900.0 2200.0 2500.0 2700.0 3100.0 3300.0
-1700.0 1800.0 2200.0 2500.0 3300.0 3400.0
-1700.0 1900.0 2200.0 2700.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2700.0 3300.0 3400.0
-1800.0 2000.0 2400.0 2800.0 3300.0 3400.0
-1800.0 2000.0 2300.0 2600.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1900.0 2100.0 2400.0 2600.0 3200.0 3300.0
-2000.0 2200.0 2400.0 2700.0 3200.0 3300.0
-2100.0 2200.0 2500.0 2900.0 3200.0 3300.0
-2200.0 2300.0 2600.0 2900.0 3200.0 3300.0
-2200.0 2300.0 2700.0 2900.0 3100.0 3300.0
-2100.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2600.0 2800.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2700.0 3000.0 3200.0
-1800.0 2000.0 2400.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2200.0 2500.0 3100.0 3200.0
-1300.0 1900.0 2100.0 2300.0 3100.0 3300.0
-1200.0 1600.0 2100.0 2200.0 3200.0 3400.0
-1100.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1400.0 1700.0 2100.0 2300.0 3100.0 3300.0
-1400.0 1900.0 2200.0 2500.0 3300.0 3400.0
-1300.0 1800.0 2200.0 2700.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2600.0 3200.0 3300.0
-1400.0 2000.0 2200.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2200.0 2600.0 3300.0 3400.0
-1400.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1400.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1400.0 1800.0 2200.0 2300.0 3000.0 3300.0
-1400.0 1800.0 2200.0 2300.0 3100.0 3300.0
-1400.0 1800.0 2100.0 2300.0 3200.0 3400.0
-1500.0 2000.0 2400.0 2700.0 3300.0 3400.0
-1700.0 2100.0 2500.0 3000.0 3300.0 3400.0
-1400.0 1900.0 2300.0 2800.0 3200.0 3300.0
-1400.0 2000.0 2200.0 2400.0 3200.0 3300.0
-1200.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1200.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1200.0 2000.0 2200.0 2500.0 3300.0 3400.0
-1700.0 2100.0 2300.0 2400.0 3200.0 3400.0
-1400.0 1600.0 1800.0 2500.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2200.0 2500.0 3100.0 3300.0
-2000.0 2100.0 2500.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2200.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2300.0 3200.0 3400.0
-1600.0 1800.0 2000.0 2300.0 3200.0 3400.0
-1600.0 1800.0 2100.0 2300.0 3200.0 3400.0
-1500.0 1800.0 2000.0 2300.0 3300.0 3400.0
-1500.0 1700.0 1900.0 2400.0 3300.0 3400.0
-1600.0 1900.0 2000.0 2700.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2600.0 3100.0 3300.0
-1700.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1700.0 2000.0 2400.0 2700.0 3100.0 3200.0
-2300.0 2400.0 2700.0 3000.0 3200.0 3300.0
-2200.0 2400.0 2600.0 2900.0 3200.0 3300.0
-2200.0 2400.0 2500.0 2800.0 3200.0 3300.0
-2100.0 2400.0 2500.0 2800.0 3200.0 3300.0
-2000.0 2400.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2300.0 2400.0 2800.0 3200.0 3300.0
-1900.0 2300.0 2600.0 2700.0 3100.0 3300.0
-2000.0 2400.0 2800.0 2900.0 3200.0 3300.0
-1700.0 2200.0 2500.0 2800.0 3200.0 3400.0
-1500.0 2100.0 2400.0 2600.0 3100.0 3300.0
-1500.0 1900.0 2300.0 2500.0 3200.0 3400.0
-1400.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1700.0 2400.0 2600.0 3200.0 3300.0
-1100.0 1700.0 2400.0 2600.0 3300.0 3400.0
-1100.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1100.0 1800.0 2400.0 2500.0 3200.0 3300.0
-1100.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1100.0 2100.0 2500.0 2600.0 3200.0 3300.0
-1100.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1000.0 2200.0 2600.0 2700.0 3200.0 3300.0
-1100.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1100.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2500.0 2900.0 3200.0
-1600.0 1700.0 2200.0 2600.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2600.0 2800.0 3000.0
-1500.0 1700.0 2100.0 2500.0 2800.0 3000.0
-1500.0 1600.0 2200.0 2500.0 2800.0 3100.0
-1500.0 1600.0 2300.0 2600.0 2800.0 3100.0
-1400.0 1500.0 2300.0 2700.0 2900.0 3100.0
-1400.0 1500.0 2200.0 2700.0 2800.0 3100.0
-1400.0 1600.0 2000.0 2700.0 2900.0 3100.0
-1500.0 1700.0 2200.0 2700.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2700.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2700.0 3000.0 3300.0
-1700.0 1800.0 2200.0 2700.0 2900.0 3200.0
-1800.0 1900.0 2200.0 2700.0 2900.0 3100.0
-1700.0 1900.0 2200.0 2600.0 2900.0 3000.0
-1800.0 2000.0 2300.0 2700.0 2900.0 3100.0
-1800.0 2000.0 2300.0 2800.0 3000.0 3200.0
-1800.0 2000.0 2400.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2800.0 3000.0 3200.0
-1500.0 1700.0 2200.0 2500.0 3000.0 3100.0
-1700.0 2100.0 2400.0 2800.0 3100.0 3200.0
-1800.0 2200.0 2700.0 2900.0 3400.0 3500.0
-1900.0 2400.0 2700.0 2900.0 3400.0 3500.0
-2000.0 2400.0 2600.0 2900.0 3300.0 3400.0
-1900.0 2400.0 2500.0 2800.0 3200.0 3300.0
-1900.0 2300.0 2500.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1600.0 1700.0 2300.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2400.0 2600.0 2900.0 3100.0
-1600.0 2100.0 2600.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2700.0 3000.0 3200.0 3300.0
-1700.0 2300.0 2800.0 2900.0 3200.0 3300.0
-1700.0 2300.0 2700.0 3000.0 3200.0 3300.0
-1600.0 2100.0 2700.0 2900.0 3300.0 3400.0
-1200.0 1600.0 2400.0 2600.0 3000.0 3300.0
-1100.0 1400.0 2400.0 2700.0 2900.0 3100.0
-1200.0 1800.0 2200.0 2500.0 3100.0 3300.0
-1200.0 1700.0 2200.0 2500.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2500.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2500.0 2800.0 3100.0
-2000.0 2200.0 2400.0 2500.0 2800.0 3100.0
-2000.0 2200.0 2400.0 2600.0 2800.0 3200.0
-2000.0 2100.0 2500.0 2700.0 3100.0 3400.0
-1900.0 2000.0 2600.0 2700.0 3100.0 3300.0
-1900.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1900.0 2400.0 2700.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2800.0 2900.0 3200.0 3400.0
-1900.0 2000.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2100.0 2400.0 2700.0 3000.0 3200.0
-1900.0 2100.0 2400.0 2800.0 3100.0 3200.0
-1900.0 2100.0 2400.0 2800.0 3300.0 3400.0
-1500.0 1800.0 2100.0 2600.0 3100.0 3300.0
-1600.0 1800.0 2100.0 2200.0 3000.0 3300.0
-1800.0 2100.0 2300.0 2500.0 3000.0 3200.0
-2000.0 2100.0 2300.0 2500.0 3000.0 3300.0
-2000.0 2100.0 2300.0 2500.0 2900.0 3300.0
-2000.0 2100.0 2300.0 2400.0 2900.0 3300.0
-1600.0 1800.0 2300.0 2500.0 2900.0 3200.0
-1700.0 1900.0 2400.0 2700.0 3000.0 3200.0
-1700.0 2000.0 2400.0 2600.0 3000.0 3300.0
-1600.0 2000.0 2300.0 2700.0 3000.0 3200.0
-1500.0 1800.0 2300.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2400.0 2800.0 3000.0
-1800.0 2000.0 2400.0 2500.0 2900.0 3200.0
-1800.0 2000.0 2400.0 2600.0 3000.0 3200.0
-1900.0 2000.0 2400.0 2500.0 3000.0 3200.0
-1900.0 2000.0 2300.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2400.0 2900.0 3200.0
-1800.0 1900.0 2200.0 2300.0 2900.0 3200.0
-1600.0 1800.0 2200.0 2400.0 3100.0 3300.0
-1600.0 2000.0 2400.0 2700.0 3100.0 3200.0
-1800.0 2100.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2200.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2300.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2300.0 2400.0 2700.0 3000.0 3200.0
-2100.0 2200.0 2400.0 2500.0 3000.0 3300.0
-1900.0 2000.0 2300.0 2600.0 2800.0 3300.0
-1900.0 2000.0 2400.0 2700.0 3100.0 3300.0
-1500.0 2000.0 2400.0 2700.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2800.0 3000.0 3300.0
-1900.0 2000.0 2400.0 2700.0 2900.0 3200.0
-2000.0 2200.0 2400.0 2700.0 2900.0 3200.0
-2100.0 2200.0 2400.0 2700.0 2900.0 3200.0
-2100.0 2300.0 2400.0 2600.0 2800.0 3200.0
-1300.0 2000.0 2300.0 2500.0 2700.0 3100.0
-1800.0 1900.0 2100.0 2400.0 2900.0 3100.0
-1700.0 1900.0 2100.0 2500.0 2900.0 3100.0
-1800.0 1900.0 2300.0 2600.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2600.0 2800.0 3200.0
-1700.0 1800.0 2300.0 2600.0 2800.0 3100.0
-1700.0 1800.0 2300.0 2700.0 2800.0 3200.0
-1500.0 1700.0 2300.0 2600.0 3000.0 3300.0
-1400.0 1700.0 2200.0 2500.0 3000.0 3300.0
-1400.0 1600.0 2200.0 2300.0 3000.0 3300.0
-1400.0 1600.0 2200.0 2400.0 2800.0 3300.0
-1500.0 1600.0 2200.0 2400.0 2900.0 3300.0
-1500.0 1600.0 2200.0 2400.0 2800.0 3300.0
-1500.0 1700.0 2200.0 2500.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2400.0 2700.0 3000.0 3200.0
-1600.0 2000.0 2500.0 2800.0 3000.0 3300.0
-2000.0 2200.0 2500.0 2600.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1500.0 1700.0 1800.0 2300.0 3300.0 3400.0
-1400.0 1600.0 1800.0 2000.0 3200.0 3400.0
-1400.0 1600.0 1800.0 1900.0 3100.0 3400.0
-1400.0 1600.0 1900.0 2000.0 2900.0 3300.0
-1400.0 1500.0 1900.0 2000.0 2900.0 3200.0
-1900.0 2200.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2200.0 2500.0 2700.0 3000.0 3200.0
-1800.0 2200.0 2600.0 2700.0 3100.0 3200.0
-2000.0 2300.0 2700.0 2800.0 3200.0 3300.0
-2100.0 2200.0 2600.0 2800.0 3000.0 3300.0
-2100.0 2200.0 2500.0 2700.0 3100.0 3300.0
-1700.0 1800.0 2000.0 2100.0 2800.0 3200.0
-1600.0 1700.0 1900.0 2000.0 2800.0 3200.0
-1400.0 1500.0 1800.0 1900.0 2800.0 3200.0
-1400.0 1800.0 2100.0 2400.0 3000.0 3200.0
-1600.0 1900.0 2300.0 2600.0 3000.0 3300.0
-1600.0 1900.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2400.0 2700.0 3000.0 3200.0
-1600.0 1900.0 2400.0 2700.0 3000.0 3300.0
-1500.0 1900.0 2400.0 2700.0 3000.0 3300.0
-1100.0 1400.0 2500.0 2800.0 3000.0 3300.0
-1100.0 1300.0 2300.0 2800.0 3000.0 3200.0
-1400.0 1500.0 2100.0 2700.0 2900.0 3100.0
-1500.0 1600.0 2100.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2600.0 2800.0 3100.0
-1800.0 2000.0 2300.0 2600.0 2800.0 3000.0
-1900.0 2100.0 2300.0 2600.0 2800.0 3100.0
-2000.0 2100.0 2300.0 2600.0 2800.0 3100.0
-2000.0 2100.0 2400.0 2500.0 2800.0 3200.0
-1900.0 2100.0 2300.0 2500.0 2800.0 3200.0
-1800.0 1900.0 2300.0 2500.0 2800.0 3300.0
-1700.0 1800.0 2300.0 2500.0 3000.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3000.0 3200.0
-1500.0 1900.0 2200.0 2600.0 3100.0 3300.0
-1300.0 1500.0 1800.0 1900.0 2900.0 3200.0
-1300.0 1500.0 1800.0 1900.0 2900.0 3300.0
-1300.0 1500.0 1800.0 1900.0 2800.0 3200.0
-1400.0 1500.0 1700.0 1900.0 2800.0 3200.0
-1400.0 1500.0 1700.0 1800.0 2800.0 3200.0
-1700.0 2000.0 2400.0 2500.0 3100.0 3300.0
-2100.0 2400.0 2700.0 2800.0 3300.0 3500.0
-1800.0 2300.0 2700.0 2900.0 3200.0 3400.0
-1700.0 2300.0 2700.0 2900.0 3300.0 3400.0
-1700.0 2100.0 2700.0 2900.0 3300.0 3400.0
-1800.0 2400.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2500.0 2800.0 3000.0 3300.0 3400.0
-2000.0 2500.0 2800.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2700.0 3000.0 3200.0 3400.0
-1900.0 2300.0 2700.0 3000.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2700.0 2900.0 3200.0
-1800.0 2000.0 2400.0 2700.0 2900.0 3100.0
-1900.0 2000.0 2300.0 2700.0 2900.0 3000.0
-1900.0 2000.0 2400.0 2700.0 2900.0 3100.0
-1800.0 1900.0 2400.0 2700.0 2900.0 3100.0
-1800.0 1900.0 2300.0 2700.0 2800.0 3100.0
-1800.0 1900.0 2300.0 2600.0 2800.0 3100.0
-1500.0 1800.0 2400.0 2700.0 3200.0 3400.0
-1600.0 1800.0 2500.0 2700.0 3100.0 3400.0
-1500.0 1700.0 2400.0 2700.0 3000.0 3300.0
-1400.0 1500.0 2400.0 2700.0 2900.0 3200.0
-1300.0 1500.0 2300.0 2700.0 2900.0 3100.0
-1400.0 1600.0 2100.0 2600.0 2800.0 3000.0
-1500.0 1600.0 2100.0 2600.0 2800.0 3000.0
-1400.0 1600.0 2200.0 2400.0 3000.0 3200.0
-1300.0 1600.0 2200.0 2500.0 2900.0 3200.0
-1300.0 1700.0 2200.0 2600.0 3000.0 3300.0
-1300.0 1700.0 2200.0 2700.0 3100.0 3200.0
-1200.0 1400.0 2200.0 2700.0 2900.0 3100.0
-1100.0 1400.0 2300.0 2700.0 2900.0 3100.0
-1100.0 1300.0 2400.0 2800.0 3000.0 3200.0
-1200.0 1600.0 2300.0 2600.0 3100.0 3200.0
-1500.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1800.0 2100.0 2400.0 2800.0 3200.0 3300.0
-1600.0 2100.0 2400.0 2800.0 3200.0 3300.0
-1600.0 2000.0 2500.0 2900.0 3200.0 3300.0
-1800.0 2000.0 2500.0 2900.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2800.0 3100.0 3300.0
-1600.0 1800.0 2400.0 2700.0 3100.0 3300.0
-1500.0 1600.0 2200.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2200.0 2500.0 2800.0 3200.0
-1400.0 1600.0 2100.0 2500.0 2800.0 3100.0
-1200.0 1400.0 2200.0 2500.0 2700.0 3100.0
-1100.0 1400.0 2400.0 2800.0 2900.0 3100.0
-1400.0 1700.0 2300.0 2600.0 2900.0 3200.0
-1500.0 1800.0 2300.0 2500.0 2900.0 3300.0
-1500.0 1700.0 2000.0 2100.0 3000.0 3300.0
-1500.0 1700.0 2000.0 2200.0 3100.0 3300.0
-1500.0 1700.0 2100.0 2300.0 3100.0 3200.0
-1600.0 1900.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2300.0 2800.0 3100.0 3300.0 3400.0
-1800.0 2200.0 2700.0 2900.0 3200.0 3400.0
-1700.0 2200.0 2700.0 2800.0 3200.0 3400.0
-1500.0 1800.0 2600.0 2700.0 3000.0 3200.0
-1500.0 1700.0 2300.0 2700.0 2800.0 3100.0
-1400.0 1500.0 2100.0 2200.0 2700.0 3200.0
-1400.0 1500.0 2000.0 2100.0 2600.0 3100.0
-1300.0 1500.0 1900.0 2000.0 2500.0 3100.0
-1400.0 1500.0 1800.0 1900.0 2700.0 3200.0
-1500.0 1600.0 2000.0 2100.0 2600.0 3100.0
-1700.0 1800.0 2000.0 2200.0 2600.0 3100.0
-1700.0 1800.0 2100.0 2200.0 2700.0 3100.0
-1600.0 2000.0 2400.0 2500.0 3000.0 3200.0
-2000.0 2200.0 2500.0 2900.0 3100.0 3300.0
-1900.0 2200.0 2400.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2200.0 2400.0 2700.0 3300.0
-1700.0 1800.0 2300.0 2400.0 2800.0 3200.0
-1800.0 1900.0 2300.0 2500.0 2800.0 3200.0
-1900.0 2100.0 2400.0 2500.0 3000.0 3300.0
-2100.0 2200.0 2500.0 2600.0 3000.0 3300.0
-2000.0 2100.0 2500.0 2700.0 2900.0 3200.0
-1700.0 1900.0 2200.0 2700.0 2800.0 3100.0
-1800.0 1900.0 2400.0 2700.0 2800.0 3200.0
-1800.0 1900.0 2400.0 2700.0 2900.0 3200.0
-1700.0 1800.0 2200.0 2700.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2700.0 3000.0 3200.0
-1900.0 2100.0 2500.0 2900.0 3100.0 3300.0
-1700.0 2000.0 2500.0 2700.0 3200.0 3400.0
-1900.0 2200.0 2700.0 3000.0 3300.0 3400.0
-2000.0 2400.0 2800.0 3100.0 3400.0 3500.0
-2100.0 2400.0 2600.0 2900.0 3200.0 3300.0
-2100.0 2400.0 2500.0 2700.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1700.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1500.0 1600.0 1800.0 1900.0 2600.0 3100.0
-1500.0 1600.0 1900.0 2000.0 2500.0 3100.0
-1600.0 1700.0 2000.0 2100.0 2500.0 3100.0
-1800.0 2100.0 2300.0 2500.0 2800.0 3200.0
-1900.0 2100.0 2300.0 2500.0 2700.0 3200.0
-2000.0 2200.0 2400.0 2600.0 2900.0 3300.0
-2000.0 2200.0 2400.0 2600.0 2900.0 3200.0
-2000.0 2100.0 2400.0 2500.0 2900.0 3300.0
-1800.0 2200.0 2500.0 2900.0 3400.0 3500.0
-1800.0 2300.0 2500.0 2900.0 3300.0 3400.0
-2000.0 2300.0 2500.0 2800.0 3000.0 3300.0
-1800.0 2000.0 2400.0 2500.0 2800.0 3300.0
-1100.0 1400.0 2600.0 2800.0 3000.0 3200.0
-1300.0 1500.0 2200.0 2700.0 2900.0 3200.0
-1400.0 1600.0 2200.0 2700.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2600.0 3100.0 3200.0
-1500.0 1800.0 2200.0 2400.0 3100.0 3300.0
-1700.0 1800.0 2200.0 2500.0 3000.0 3300.0
-1700.0 1800.0 2200.0 2600.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2600.0 3000.0 3200.0
-1700.0 1800.0 2400.0 2700.0 3000.0 3100.0
-1600.0 1700.0 2500.0 2800.0 3000.0 3200.0
-1400.0 1500.0 2200.0 2700.0 2900.0 3100.0
-1300.0 1400.0 2100.0 2700.0 2900.0 3200.0
-1500.0 1900.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2500.0 2700.0 3100.0
-1600.0 1700.0 2200.0 2500.0 2800.0 3200.0
-1600.0 1800.0 2100.0 2500.0 2900.0 3200.0
-1600.0 1800.0 2100.0 2600.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2800.0 3100.0 3300.0
-1800.0 2100.0 2400.0 2700.0 3000.0 3300.0
-2000.0 2100.0 2500.0 2800.0 3000.0 3200.0
-1800.0 2000.0 2500.0 2700.0 3000.0 3200.0
-1600.0 1900.0 2300.0 2700.0 2900.0 3200.0
-1600.0 1900.0 2100.0 2500.0 2800.0 3100.0
-1700.0 1900.0 2100.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2100.0 2600.0 2800.0 3000.0
-1600.0 1700.0 2000.0 2600.0 2800.0 3000.0
-1400.0 1700.0 2200.0 2700.0 3000.0 3200.0
-1500.0 1800.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2300.0 2600.0 3000.0 3300.0
-1600.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1600.0 1900.0 2300.0 2600.0 3100.0 3300.0
-1200.0 1300.0 2100.0 2700.0 3000.0 3100.0
-1300.0 1400.0 2100.0 2700.0 2900.0 3100.0
-1300.0 1400.0 2200.0 2700.0 2900.0 3100.0
-1300.0 1400.0 2100.0 2600.0 2800.0 3100.0
-1300.0 1500.0 2100.0 2600.0 2800.0 3100.0
-1500.0 1600.0 1900.0 2500.0 2900.0 3100.0
-1500.0 1700.0 2100.0 2700.0 2900.0 3200.0
-1600.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2800.0 3200.0 3400.0
-1700.0 2000.0 2400.0 2800.0 3200.0 3400.0
-1600.0 1700.0 2200.0 2400.0 2800.0 3300.0
-1500.0 1600.0 2200.0 2400.0 3000.0 3300.0
-1500.0 1700.0 2300.0 2700.0 3100.0 3300.0
-1400.0 1500.0 2000.0 2600.0 2900.0 3100.0
-1400.0 1500.0 2100.0 2500.0 2800.0 3100.0
-1400.0 1700.0 2200.0 2600.0 3000.0 3300.0
-1000.0 1500.0 2600.0 2800.0 3100.0 3400.0
-1300.0 1500.0 2500.0 2700.0 2900.0 3300.0
-1500.0 1600.0 2200.0 2600.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2400.0 2700.0 3200.0
-1700.0 1800.0 2100.0 2400.0 2600.0 3100.0
-1600.0 1700.0 2100.0 2400.0 2700.0 3200.0
-1600.0 1900.0 2300.0 2700.0 3000.0 3300.0
-1500.0 1600.0 2000.0 2400.0 3000.0 3300.0
-1600.0 1800.0 2300.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2400.0 2600.0 3200.0 3400.0
-1600.0 1800.0 2400.0 2600.0 3200.0 3400.0
-1700.0 1800.0 2300.0 2600.0 3000.0 3300.0
-1700.0 1800.0 2100.0 2500.0 2900.0 3200.0
-1800.0 1900.0 2100.0 2600.0 2800.0 3000.0
-1800.0 1900.0 2200.0 2600.0 2800.0 3000.0
-1800.0 1900.0 2200.0 2600.0 2900.0 3100.0
-1700.0 1800.0 2100.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2100.0 2700.0 2900.0 3100.0
-1400.0 1600.0 2100.0 2700.0 2900.0 3200.0
-1200.0 1600.0 2200.0 2400.0 3000.0 3300.0
-1600.0 1900.0 2300.0 2700.0 3100.0 3400.0
-1200.0 1800.0 2300.0 2700.0 3100.0 3300.0
-1600.0 2000.0 2400.0 2800.0 3100.0 3300.0
-1700.0 1900.0 2100.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2600.0 3100.0 3400.0
-1900.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1900.0 2100.0 2300.0 2700.0 3100.0 3300.0
-1200.0 1400.0 2200.0 2800.0 3000.0 3100.0
-1800.0 2100.0 2400.0 2700.0 3200.0 3400.0
-1600.0 2100.0 2500.0 2800.0 3100.0 3300.0
-1600.0 2000.0 2500.0 2800.0 3200.0 3300.0
-1700.0 2000.0 2500.0 2800.0 3200.0 3400.0
-1700.0 1900.0 2700.0 2800.0 3100.0 3400.0
-1600.0 1800.0 2400.0 2600.0 3100.0 3400.0
-1600.0 1800.0 2300.0 2500.0 3100.0 3400.0
-1600.0 1800.0 2200.0 2500.0 3100.0 3400.0
-1600.0 1800.0 2100.0 2300.0 3100.0 3400.0
-1500.0 1700.0 2000.0 2200.0 3000.0 3300.0
-1500.0 1600.0 1900.0 2000.0 3000.0 3200.0
-1300.0 1500.0 1700.0 1900.0 2800.0 3200.0
-1800.0 2000.0 2300.0 2600.0 3000.0 3200.0
-1700.0 2000.0 2200.0 2600.0 3000.0 3200.0
-1600.0 1900.0 2400.0 2600.0 3000.0 3300.0
-1300.0 1700.0 2100.0 2400.0 2900.0 3200.0
-1600.0 1800.0 2400.0 2600.0 3000.0 3300.0
-1300.0 1600.0 2200.0 2300.0 2900.0 3200.0
-1300.0 1400.0 2100.0 2200.0 3000.0 3200.0
-1300.0 1500.0 1800.0 2000.0 3000.0 3200.0
-1300.0 1400.0 1800.0 1900.0 2800.0 3200.0
-1300.0 1700.0 2200.0 2500.0 3000.0 3200.0
-1200.0 1800.0 2300.0 2600.0 3200.0 3300.0
-1400.0 1900.0 2300.0 2700.0 3100.0 3300.0
-1500.0 2000.0 2400.0 2600.0 3000.0 3300.0
-1600.0 2000.0 2500.0 2600.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2700.0 3100.0 3300.0
-1600.0 2000.0 2500.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2300.0 2600.0 2800.0 3200.0
-1300.0 1500.0 2000.0 2600.0 2700.0 3000.0
-1300.0 1500.0 2200.0 2600.0 2800.0 3100.0
-1400.0 1500.0 2100.0 2600.0 2800.0 3100.0
-1400.0 1500.0 2100.0 2600.0 2800.0 3000.0
-1500.0 1600.0 2000.0 2500.0 2700.0 3000.0
-1500.0 1700.0 2000.0 2500.0 2700.0 3000.0
-1600.0 1700.0 2000.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2100.0 2500.0 2900.0 3100.0
-1700.0 1900.0 2100.0 2500.0 2900.0 3000.0
-1800.0 2000.0 2200.0 2600.0 2800.0 3000.0
-1800.0 2100.0 2300.0 2600.0 2800.0 3100.0
-1800.0 2100.0 2300.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2200.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2300.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2300.0 2600.0 2800.0 3100.0
-1700.0 1900.0 2200.0 2600.0 2800.0 3000.0
-1700.0 1800.0 2100.0 2500.0 2700.0 3000.0
-1500.0 1700.0 2200.0 2400.0 2800.0 3300.0
-1500.0 1900.0 2300.0 2500.0 3100.0 3300.0
-1700.0 1800.0 2200.0 2800.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2700.0 3000.0 3200.0
-1900.0 2100.0 2400.0 2600.0 3000.0 3200.0
-2000.0 2200.0 2400.0 2700.0 3000.0 3200.0
-1900.0 2300.0 2400.0 2700.0 3100.0 3300.0
-1500.0 1600.0 1800.0 2000.0 3100.0 3300.0
-1200.0 1400.0 1900.0 2500.0 2900.0 3100.0
-1600.0 1700.0 2000.0 2100.0 2900.0 3300.0
-1700.0 1800.0 2100.0 2200.0 2900.0 3300.0
-1800.0 1900.0 2200.0 2300.0 3000.0 3300.0
-1900.0 2000.0 2200.0 2300.0 3100.0 3300.0
-2000.0 2100.0 2300.0 2500.0 3100.0 3400.0
-1900.0 2100.0 2300.0 2500.0 3000.0 3200.0
-1800.0 2000.0 2300.0 2400.0 2900.0 3200.0
-1900.0 2200.0 2600.0 2800.0 3100.0 3300.0
-2000.0 2400.0 2600.0 2700.0 3200.0 3400.0
-1800.0 2200.0 2600.0 2700.0 3100.0 3300.0
-1600.0 2100.0 2600.0 2700.0 3100.0 3300.0
-1600.0 2100.0 2500.0 2800.0 3200.0 3400.0
-1900.0 2200.0 2500.0 2800.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2800.0 3300.0 3400.0
-1700.0 1900.0 2600.0 2800.0 3100.0 3400.0
-1600.0 1700.0 2400.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2200.0 2500.0 2800.0 3200.0
-1400.0 1600.0 2300.0 2500.0 2900.0 3200.0
-1400.0 1500.0 2300.0 2600.0 2900.0 3200.0
-1300.0 1500.0 2400.0 2600.0 3000.0 3300.0
-1200.0 1400.0 2400.0 2600.0 2900.0 3300.0
-1200.0 1300.0 2300.0 2600.0 2800.0 3200.0
-1200.0 1300.0 2300.0 2600.0 2800.0 3100.0
-1200.0 1400.0 2300.0 2600.0 2800.0 3200.0
-1200.0 1400.0 2300.0 2500.0 2800.0 3200.0
-1200.0 1400.0 2300.0 2500.0 2700.0 3200.0
-1300.0 1400.0 2300.0 2500.0 2700.0 3200.0
-1300.0 1400.0 2300.0 2400.0 2900.0 3200.0
-1300.0 1600.0 2300.0 2400.0 2900.0 3200.0
-1600.0 1700.0 2200.0 2500.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2500.0 2900.0 3200.0
-1600.0 1800.0 2300.0 2400.0 2900.0 3200.0
-1600.0 1800.0 2200.0 2400.0 2900.0 3200.0
-1700.0 1900.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2300.0 2600.0 2900.0 3200.0
-1600.0 1800.0 2500.0 2700.0 2900.0 3200.0
-1600.0 1900.0 2500.0 2800.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2800.0 3000.0 3200.0
-1400.0 1700.0 2400.0 2700.0 2900.0 3200.0
-1400.0 1500.0 2200.0 2600.0 2800.0 3100.0
-1300.0 1500.0 2300.0 2600.0 2800.0 3100.0
-1200.0 1400.0 2300.0 2500.0 2700.0 3100.0
-1300.0 1600.0 2200.0 2600.0 3000.0 3300.0
-1200.0 1600.0 2500.0 2700.0 3100.0 3400.0
-1300.0 1800.0 2400.0 2700.0 3200.0 3400.0
-1300.0 1700.0 2300.0 2700.0 3100.0 3300.0
-1300.0 1700.0 2200.0 2500.0 3100.0 3300.0
-1300.0 1600.0 2200.0 2600.0 2900.0 3200.0
-1400.0 1600.0 2200.0 2700.0 2800.0 3100.0
-1600.0 1700.0 2200.0 2700.0 3100.0 3200.0
-1800.0 2000.0 2400.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2400.0 2800.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2300.0 2700.0 3000.0 3300.0
-1800.0 1900.0 2600.0 2800.0 3300.0 3400.0
-1900.0 2100.0 2300.0 2600.0 2900.0 3100.0
-1900.0 2200.0 2400.0 2700.0 3000.0 3100.0
-1800.0 2300.0 2400.0 2700.0 3000.0 3100.0
-1800.0 2300.0 2400.0 2600.0 3100.0 3200.0
-2000.0 2300.0 2400.0 2700.0 3100.0 3200.0
-2100.0 2300.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2100.0 2500.0 2700.0 3000.0 3200.0
-1900.0 2000.0 2300.0 2700.0 2900.0 3100.0
-1600.0 1800.0 2200.0 2500.0 2700.0 3000.0
-1500.0 1800.0 2300.0 2500.0 2700.0 3000.0
-1500.0 1800.0 2200.0 2500.0 2700.0 3000.0
-1600.0 1800.0 2300.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2400.0 2700.0 3000.0 3200.0
-1700.0 1800.0 2500.0 2700.0 3000.0 3200.0
-1700.0 1800.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1700.0 2400.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2400.0 2600.0 2800.0 3200.0
-1500.0 1700.0 2400.0 2500.0 2800.0 3200.0
-1400.0 1600.0 2400.0 2500.0 3000.0 3300.0
-1500.0 1700.0 2300.0 2400.0 2900.0 3200.0
-1500.0 1800.0 2200.0 2400.0 2800.0 3000.0
-1600.0 1900.0 2200.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2300.0 2600.0 2900.0 3000.0
-1600.0 2000.0 2300.0 2500.0 2900.0 3100.0
-1600.0 1800.0 2100.0 2300.0 2900.0 3100.0
-1300.0 1500.0 2200.0 2400.0 3000.0 3200.0
-1300.0 1500.0 2200.0 2400.0 2900.0 3200.0
-1300.0 1500.0 2200.0 2500.0 2900.0 3200.0
-1400.0 1500.0 2300.0 2500.0 2900.0 3200.0
-1600.0 1700.0 2100.0 2500.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2600.0 2800.0 3100.0
-1700.0 1800.0 2100.0 2500.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2600.0 2900.0 3100.0
-1700.0 1900.0 2300.0 2600.0 2900.0 3200.0
-1800.0 2100.0 2300.0 2600.0 2900.0 3200.0
-1800.0 2100.0 2300.0 2700.0 2900.0 3200.0
-1900.0 2200.0 2400.0 2700.0 2900.0 3200.0
-1900.0 2100.0 2300.0 2700.0 2900.0 3100.0
-1900.0 2000.0 2300.0 2600.0 2800.0 3100.0
-1900.0 2200.0 2500.0 2800.0 3100.0 3300.0
-1900.0 2200.0 2400.0 2800.0 3000.0 3200.0
-1900.0 2200.0 2400.0 2700.0 2900.0 3100.0
-1900.0 2300.0 2400.0 2800.0 3100.0 3200.0
-2000.0 2300.0 2500.0 2800.0 3100.0 3300.0
-1900.0 2400.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2000.0 2200.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2100.0 2400.0 2900.0 3200.0
-1500.0 1600.0 2200.0 2400.0 2700.0 3200.0
-1300.0 1400.0 2200.0 2500.0 2700.0 3200.0
-1200.0 1500.0 2500.0 2700.0 3000.0 3300.0
-1300.0 1600.0 2400.0 2600.0 3000.0 3300.0
-2000.0 2200.0 2600.0 2700.0 3000.0 3300.0
-2100.0 2300.0 2500.0 2700.0 3000.0 3300.0
-2100.0 2300.0 2600.0 2700.0 3000.0 3300.0
-2000.0 2200.0 2600.0 2700.0 3000.0 3200.0
-1800.0 2300.0 2500.0 2600.0 2900.0 3200.0
-1800.0 2300.0 2500.0 2700.0 2900.0 3100.0
-1800.0 2200.0 2400.0 2600.0 2900.0 3200.0
-1800.0 2200.0 2400.0 2600.0 2800.0 3100.0
-1800.0 2200.0 2300.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2200.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2800.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2800.0 3000.0 3300.0
-1600.0 1800.0 2300.0 2800.0 3000.0 3300.0
-1400.0 1700.0 2200.0 2500.0 2800.0 2900.0
-1400.0 1700.0 2100.0 2500.0 2900.0 3200.0
-1700.0 2000.0 2200.0 2800.0 3200.0 3300.0
-1800.0 1900.0 2200.0 2700.0 2900.0 3200.0
-1800.0 2000.0 2200.0 2700.0 2900.0 3100.0
-1800.0 2000.0 2200.0 2700.0 2800.0 3000.0
-1800.0 2000.0 2200.0 2700.0 2800.0 3100.0
-1600.0 1900.0 2100.0 2600.0 2900.0 3200.0
-2000.0 2100.0 2600.0 2900.0 3000.0 3200.0
-2000.0 2200.0 2700.0 2900.0 3100.0 3300.0
-2000.0 2200.0 2400.0 2800.0 3000.0 3200.0
-2000.0 2200.0 2300.0 2700.0 3000.0 3200.0
-1700.0 2200.0 2400.0 2600.0 2900.0 3100.0
-1800.0 2200.0 2400.0 2700.0 3000.0 3200.0
-1900.0 2300.0 2500.0 2700.0 3000.0 3200.0
-1900.0 2300.0 2500.0 2700.0 2900.0 3100.0
-1900.0 2300.0 2500.0 2800.0 3000.0 3200.0
-1900.0 2300.0 2500.0 2700.0 2900.0 3200.0
-1800.0 2200.0 2400.0 2700.0 2900.0 3100.0
-1800.0 2000.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1700.0 2100.0 2800.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2500.0 3000.0 3100.0
-1400.0 1800.0 2300.0 2500.0 3000.0 3100.0
-1400.0 1800.0 2300.0 2500.0 2900.0 3100.0
-1600.0 1800.0 2500.0 2800.0 3100.0 3200.0
-1700.0 2000.0 2400.0 2700.0 3200.0 3400.0
-1700.0 2000.0 2500.0 2800.0 3100.0 3400.0
-1500.0 1700.0 2300.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2200.0 2600.0 2800.0 3200.0
-1500.0 1700.0 2200.0 2600.0 2900.0 3300.0
-1400.0 1700.0 2200.0 2600.0 2900.0 3300.0
-1200.0 1500.0 2200.0 2300.0 3100.0 3400.0
-1200.0 1600.0 2300.0 2400.0 3200.0 3300.0
-1200.0 1700.0 2300.0 2400.0 3100.0 3300.0
-1100.0 1700.0 2400.0 2500.0 3100.0 3300.0
-1100.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1100.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1000.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1000.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1100.0 1600.0 2400.0 2500.0 3200.0 3300.0
-1100.0 1600.0 2300.0 2400.0 3200.0 3300.0
-1300.0 1600.0 2300.0 2500.0 3100.0 3300.0
-1400.0 1700.0 2300.0 2500.0 3100.0 3300.0
-2000.0 2100.0 2500.0 2600.0 3200.0 3400.0
-1700.0 2100.0 2600.0 2800.0 3100.0 3200.0
-1800.0 2200.0 2700.0 2900.0 3100.0 3300.0
-2100.0 2400.0 2700.0 2900.0 3200.0 3300.0
-2100.0 2500.0 2700.0 2900.0 3300.0 3400.0
-2100.0 2400.0 2600.0 2800.0 3200.0 3400.0
-1700.0 1900.0 2400.0 2600.0 2900.0 3000.0
-1600.0 1900.0 2400.0 2500.0 2800.0 2900.0
-1300.0 2000.0 2400.0 2500.0 2900.0 3200.0
-1500.0 2000.0 2400.0 2500.0 2900.0 3100.0
-1600.0 2000.0 2400.0 2600.0 3000.0 3100.0
-1700.0 1900.0 2500.0 2600.0 3100.0 3200.0
-1600.0 1800.0 2600.0 2700.0 3300.0 3400.0
-1500.0 1600.0 2600.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2600.0 2700.0 3200.0 3400.0
-1500.0 2100.0 2600.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2700.0 2900.0 3300.0 3400.0
-1700.0 2300.0 2700.0 2800.0 3300.0 3400.0
-1800.0 2300.0 2700.0 2800.0 3300.0 3400.0
-1400.0 1700.0 2500.0 2600.0 3000.0 3300.0
-1400.0 1800.0 2500.0 2600.0 3000.0 3300.0
-1800.0 2200.0 2700.0 2900.0 3300.0 3400.0
-1800.0 2300.0 2600.0 2900.0 3300.0 3400.0
-1400.0 1900.0 2500.0 2600.0 3200.0 3400.0
-1400.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1400.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1200.0 2000.0 2400.0 2700.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2500.0 3100.0 3200.0
-1200.0 1700.0 2300.0 2500.0 3000.0 3100.0
-1200.0 1800.0 2400.0 2500.0 3000.0 3100.0
-1100.0 2100.0 2300.0 2600.0 3000.0 3100.0
-1400.0 1800.0 2200.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2400.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2400.0 2600.0 3300.0 3400.0
-1600.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1600.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1500.0 2400.0 2700.0 2800.0 3100.0 3300.0
-1300.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1400.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1600.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1600.0 2100.0 2300.0 2500.0 3000.0 3100.0
-1800.0 2100.0 2400.0 2700.0 2900.0 3200.0
-1500.0 1700.0 2000.0 2600.0 3200.0 3300.0
-1400.0 1700.0 2000.0 2400.0 3200.0 3300.0
-1400.0 1900.0 2200.0 2500.0 3100.0 3300.0
-1500.0 1900.0 2200.0 2500.0 3100.0 3300.0
-1200.0 1900.0 2500.0 2600.0 3100.0 3300.0
-1000.0 1700.0 2600.0 2800.0 3300.0 3400.0
-1200.0 1500.0 2400.0 2700.0 2900.0 3200.0
-1700.0 2100.0 2400.0 2800.0 3200.0 3400.0
-1700.0 2000.0 2600.0 2800.0 3100.0 3400.0
-1700.0 2000.0 2600.0 2700.0 3000.0 3300.0
-1500.0 1700.0 2500.0 2700.0 3000.0 3300.0
-1600.0 2000.0 2600.0 2800.0 3100.0 3300.0
-1500.0 2000.0 2500.0 2800.0 3200.0 3400.0
-1400.0 1800.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2600.0 2900.0 3200.0 3400.0
-1700.0 2200.0 2600.0 2800.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1500.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1400.0 1800.0 2500.0 2700.0 3000.0 3300.0
-1300.0 1600.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1700.0 2500.0 2600.0 3300.0 3400.0
-1500.0 1700.0 2400.0 2500.0 3200.0 3400.0
-1900.0 2000.0 2300.0 2500.0 3200.0 3400.0
-1600.0 1900.0 2100.0 2500.0 3000.0 3200.0
-1600.0 2100.0 2500.0 2800.0 3200.0 3300.0
-1400.0 2000.0 2400.0 2700.0 3200.0 3300.0
-900.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1100.0 1600.0 2700.0 2800.0 3200.0 3400.0
-1200.0 1600.0 2600.0 2800.0 3200.0 3400.0
-1300.0 1700.0 2500.0 2700.0 3100.0 3300.0
-1400.0 1700.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1800.0 2300.0 2500.0 3100.0 3200.0
-1400.0 2100.0 2400.0 2600.0 2900.0 3100.0
-1300.0 2000.0 2400.0 2600.0 3100.0 3200.0
-1200.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2500.0 3100.0 3300.0
-1600.0 2000.0 2400.0 2600.0 3200.0 3400.0
-1800.0 2000.0 2300.0 2500.0 3100.0 3400.0
-1700.0 1900.0 2300.0 2400.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2400.0 2900.0 3300.0
-1600.0 1800.0 2300.0 2400.0 3000.0 3300.0
-1600.0 1700.0 2300.0 2400.0 3000.0 3300.0
-1600.0 1700.0 2300.0 2400.0 2800.0 3200.0
-1600.0 1700.0 2300.0 2400.0 2900.0 3300.0
-1500.0 1700.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1600.0 2500.0 2700.0 3100.0 3300.0
-1300.0 1500.0 2500.0 2700.0 3100.0 3300.0
-1300.0 1600.0 2400.0 2700.0 3000.0 3400.0
-1800.0 2300.0 2600.0 2800.0 3100.0 3300.0
-1800.0 2200.0 2500.0 2800.0 3100.0 3300.0
-1700.0 2100.0 2500.0 2700.0 3000.0 3300.0
-1600.0 1900.0 2500.0 2700.0 2900.0 3200.0
-1700.0 2000.0 2500.0 2700.0 3000.0 3200.0
-1700.0 2300.0 2600.0 2700.0 3200.0 3400.0
-1400.0 1700.0 1900.0 2200.0 3200.0 3300.0
-1200.0 1900.0 2100.0 2600.0 3100.0 3200.0
-1200.0 1900.0 2200.0 2700.0 3100.0 3200.0
-1200.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1100.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1200.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1200.0 1800.0 2300.0 2600.0 3200.0 3400.0
-1200.0 1600.0 2400.0 2700.0 3200.0 3400.0
-1200.0 1500.0 2400.0 2600.0 3000.0 3200.0
-1300.0 1500.0 2100.0 2500.0 2700.0 3000.0
-1200.0 1800.0 2400.0 2600.0 3100.0 3200.0
-1200.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1700.0 2400.0 2700.0 3100.0 3300.0 3400.0
-2000.0 2500.0 2700.0 3100.0 3400.0 3500.0
-1900.0 2400.0 2700.0 3100.0 3400.0 3500.0
-1900.0 2200.0 2700.0 3100.0 3300.0 3400.0
-1800.0 2200.0 2700.0 3100.0 3300.0 3400.0
-1500.0 1700.0 2100.0 2500.0 3200.0 3300.0
-1400.0 1800.0 2100.0 2600.0 3200.0 3300.0
-1200.0 1700.0 2000.0 2300.0 3300.0 3400.0
-1300.0 1500.0 1600.0 2300.0 3100.0 3200.0
-1500.0 1900.0 2400.0 2600.0 3000.0 3300.0
-1500.0 2000.0 2400.0 2500.0 2800.0 3200.0
-1400.0 2000.0 2400.0 2500.0 2900.0 3200.0
-1300.0 1600.0 1700.0 2300.0 3300.0 3400.0
-1300.0 1600.0 1700.0 2100.0 3200.0 3400.0
-2000.0 2200.0 2500.0 2900.0 3300.0 3400.0
-2100.0 2300.0 2500.0 2700.0 3300.0 3400.0
-1900.0 2200.0 2400.0 2700.0 3300.0 3400.0
-1500.0 1900.0 2200.0 2400.0 3000.0 3300.0
-1500.0 1900.0 2400.0 2700.0 3300.0 3400.0
-1500.0 1700.0 2500.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2500.0 2600.0 3100.0 3400.0
-1600.0 2000.0 2400.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2600.0 3000.0 3100.0
-1500.0 1800.0 2200.0 2600.0 3000.0 3100.0
-1500.0 1900.0 2400.0 2500.0 3000.0 3200.0
-1200.0 1500.0 2400.0 2600.0 3200.0 3300.0
-1500.0 2000.0 2500.0 2700.0 3100.0 3300.0
-1700.0 2100.0 2500.0 2900.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1400.0 2000.0 2300.0 2500.0 3200.0 3400.0
-1200.0 1900.0 2200.0 2400.0 3300.0 3400.0
-1200.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1200.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1200.0 1700.0 2300.0 2400.0 3300.0 3400.0
-1200.0 1600.0 2200.0 2300.0 3300.0 3400.0
-1200.0 1600.0 2200.0 2400.0 3300.0 3400.0
-1300.0 1600.0 2100.0 2400.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2600.0 2900.0 3200.0
-2100.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1600.0 1800.0 2300.0 2500.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2500.0 3100.0 3300.0
-1400.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1800.0 2400.0 2600.0 3100.0 3300.0
-1300.0 1800.0 2400.0 2700.0 3200.0 3300.0
-1100.0 1800.0 2400.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2500.0 2600.0 2900.0 3200.0
-1500.0 2100.0 2500.0 2600.0 2900.0 3200.0
-1500.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1300.0 1900.0 2400.0 2800.0 3100.0 3300.0
-1300.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1300.0 1800.0 2600.0 2700.0 3100.0 3400.0
-1300.0 1700.0 2600.0 2700.0 3100.0 3300.0
-1300.0 1700.0 2600.0 2700.0 3100.0 3400.0
-1400.0 1900.0 2400.0 2600.0 2900.0 3100.0
-1500.0 1800.0 2300.0 2600.0 2900.0 3100.0
-1600.0 1900.0 2400.0 2600.0 3000.0 3200.0
-1700.0 2000.0 2600.0 2900.0 3100.0 3300.0
-1800.0 2300.0 2500.0 2800.0 3200.0 3400.0
-1900.0 2300.0 2600.0 2900.0 3300.0 3400.0
-1600.0 1900.0 2500.0 2600.0 3000.0 3100.0
-1600.0 1900.0 2500.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2200.0 2500.0 3200.0 3300.0
-1500.0 1900.0 2200.0 2500.0 3300.0 3400.0
-1500.0 1800.0 2200.0 2400.0 3200.0 3400.0
-1500.0 1800.0 2100.0 2400.0 3200.0 3400.0
-1600.0 1800.0 2100.0 2200.0 3200.0 3400.0
-1700.0 1800.0 2100.0 2400.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2400.0 2700.0 3100.0
-1600.0 1900.0 2400.0 2500.0 3000.0 3300.0
-1600.0 2100.0 2500.0 2600.0 3200.0 3400.0
-1200.0 2000.0 2400.0 2500.0 3400.0 3500.0
-1200.0 1600.0 2300.0 2400.0 3200.0 3400.0
-1400.0 1900.0 2400.0 2500.0 3000.0 3200.0
-1300.0 1800.0 2100.0 2500.0 3100.0 3300.0
-1300.0 1700.0 2300.0 2500.0 3100.0 3300.0
-1300.0 1700.0 2200.0 2400.0 3200.0 3300.0
-1300.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1700.0 1900.0 2400.0 2600.0 3300.0 3400.0
-1700.0 1900.0 2500.0 2700.0 3000.0 3100.0
-1700.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2500.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2400.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2400.0 2600.0 3100.0 3300.0
-1500.0 1700.0 2400.0 2600.0 3100.0 3300.0
-1300.0 1700.0 2400.0 2600.0 3100.0 3300.0
-1300.0 1700.0 2400.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2300.0 2600.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2600.0 3300.0 3400.0
-1500.0 1800.0 2300.0 2500.0 3300.0 3400.0
-1500.0 1700.0 2200.0 2400.0 3300.0 3400.0
-1800.0 2200.0 2400.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2600.0 3200.0 3300.0
-1900.0 2000.0 2200.0 2500.0 3300.0 3400.0
-1900.0 2100.0 2300.0 2600.0 3300.0 3400.0
-1800.0 1900.0 2200.0 2600.0 3100.0 3300.0
-1100.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1000.0 1700.0 2700.0 2800.0 3200.0 3300.0
-1000.0 1800.0 2600.0 2700.0 3000.0 3100.0
-1200.0 2000.0 2600.0 2800.0 3200.0 3300.0
-1200.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1200.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1200.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1300.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1300.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1400.0 1900.0 2300.0 2600.0 3300.0 3400.0
-2200.0 2400.0 2500.0 2900.0 3200.0 3300.0
-2100.0 2200.0 2400.0 2800.0 3200.0 3300.0
-2000.0 2200.0 2400.0 2800.0 3200.0 3300.0
-1900.0 2100.0 2400.0 2800.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2400.0 2800.0 3000.0
-1600.0 1900.0 2300.0 2400.0 2900.0 3300.0
-1800.0 2100.0 2400.0 2500.0 3100.0 3200.0
-1800.0 2300.0 2500.0 2700.0 3200.0 3300.0
-1800.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1500.0 1900.0 2100.0 2700.0 3000.0 3100.0
-1500.0 1700.0 1800.0 2600.0 3300.0 3400.0
-1500.0 1700.0 1800.0 2500.0 3300.0 3400.0
-1300.0 1500.0 1600.0 2500.0 3200.0 3300.0
-1300.0 1500.0 1700.0 2400.0 3000.0 3100.0
-1600.0 2000.0 2500.0 2700.0 3300.0 3400.0
-2000.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1800.0 2000.0 2200.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2100.0 2600.0 3200.0 3300.0
-1700.0 2000.0 2100.0 2700.0 3200.0 3300.0
-1700.0 2100.0 2200.0 2700.0 3200.0 3300.0
-1700.0 2200.0 2400.0 2700.0 3200.0 3300.0
-1700.0 2200.0 2400.0 2600.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2600.0 3200.0 3300.0
-1800.0 2400.0 2600.0 3000.0 3300.0 3400.0
-1800.0 2400.0 2800.0 3100.0 3300.0 3400.0
-1900.0 2400.0 2800.0 3100.0 3300.0 3500.0
-1900.0 2300.0 2800.0 3000.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2600.0 3000.0 3100.0
-1500.0 1700.0 1900.0 2500.0 3300.0 3400.0
-1200.0 1700.0 2200.0 2300.0 3100.0 3300.0
-1100.0 1500.0 2300.0 2400.0 3000.0 3300.0
-1200.0 1600.0 2300.0 2400.0 3100.0 3300.0
-1200.0 1600.0 2300.0 2400.0 3100.0 3400.0
-1300.0 1600.0 2200.0 2400.0 3200.0 3300.0
-1500.0 1600.0 2100.0 2400.0 3000.0 3300.0
-1600.0 1700.0 2100.0 2400.0 3100.0 3300.0
-1500.0 1600.0 2100.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2200.0 2600.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2200.0 2500.0 2900.0 3200.0
-1300.0 1600.0 2200.0 2600.0 3000.0 3200.0
-1700.0 2000.0 2400.0 2800.0 3000.0 3100.0
-1700.0 2100.0 2400.0 2700.0 3000.0 3100.0
-1800.0 2200.0 2500.0 2800.0 3000.0 3200.0
-1700.0 2100.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2200.0 2500.0 2700.0 3200.0 3400.0
-1600.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2400.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2300.0 3300.0 3400.0
-1400.0 1600.0 1800.0 2200.0 3300.0 3400.0
-1500.0 1600.0 1900.0 2600.0 3000.0 3200.0
-1500.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1200.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1900.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1800.0 2100.0 2300.0 2600.0 3300.0 3400.0
-1700.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1600.0 2100.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1500.0 2100.0 2500.0 2600.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2500.0 2900.0 3100.0
-1800.0 2000.0 2500.0 2800.0 3000.0 3200.0
-1400.0 1600.0 2100.0 2600.0 3000.0 3300.0
-1700.0 2000.0 2400.0 2700.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1700.0 2100.0 2600.0 2700.0 3000.0 3300.0
-1800.0 2100.0 2500.0 2700.0 3100.0 3200.0
-2200.0 2300.0 2500.0 2800.0 3200.0 3300.0
-2100.0 2300.0 2500.0 2800.0 3200.0 3300.0
-2000.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2400.0 2700.0 3100.0 3400.0
-1300.0 1800.0 2100.0 2500.0 3100.0 3200.0
-1300.0 1800.0 2200.0 2800.0 3100.0 3200.0
-1300.0 2000.0 2200.0 2600.0 3200.0 3300.0
-1900.0 2100.0 2400.0 2500.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1500.0 1900.0 2400.0 2600.0 3300.0 3400.0
-1500.0 1800.0 2400.0 2600.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2600.0 3200.0 3400.0
-1400.0 1700.0 2400.0 2600.0 3100.0 3300.0
-1400.0 1900.0 2500.0 2600.0 2900.0 3200.0
-1400.0 1900.0 2400.0 2700.0 3000.0 3200.0
-1400.0 1900.0 2400.0 2600.0 3000.0 3100.0
-1400.0 1900.0 2300.0 2500.0 2700.0 3000.0
-1300.0 1800.0 2200.0 2500.0 3300.0 3400.0
-1300.0 1800.0 2200.0 2400.0 3300.0 3400.0
-1300.0 1700.0 2100.0 2400.0 3200.0 3400.0
-1400.0 1900.0 2300.0 2600.0 3100.0 3300.0
-1900.0 2200.0 2400.0 2800.0 3100.0 3200.0
-1600.0 2200.0 2400.0 2700.0 3300.0 3400.0
-1600.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1700.0 2000.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2300.0 2500.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2400.0 3200.0 3300.0
-1800.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1900.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2500.0 2600.0 3100.0 3300.0
-1400.0 1900.0 2300.0 2500.0 2800.0 3200.0
-1400.0 1900.0 2300.0 2500.0 2900.0 3300.0
-1400.0 1600.0 2300.0 2500.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2500.0 3100.0 3200.0
-2000.0 2200.0 2500.0 2700.0 3000.0 3300.0
-1600.0 2100.0 2600.0 2900.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2500.0 3100.0 3200.0
-1200.0 2100.0 2600.0 2700.0 3200.0 3300.0
-1100.0 2100.0 2600.0 2800.0 3200.0 3300.0
-1000.0 2000.0 2800.0 2900.0 3100.0 3200.0
-1600.0 1900.0 2100.0 2500.0 3000.0 3100.0
-1700.0 1900.0 2200.0 2500.0 3000.0 3100.0
-1700.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1400.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1300.0 2000.0 2200.0 2400.0 3100.0 3200.0
-1200.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1200.0 1800.0 2300.0 2600.0 3100.0 3200.0
-1300.0 1600.0 2300.0 2700.0 3100.0 3200.0
-1300.0 1700.0 2300.0 2700.0 3100.0 3200.0
-1100.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1300.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1800.0 2100.0 2600.0 3300.0 3400.0
-1500.0 1900.0 2100.0 2500.0 2800.0 3000.0
-1500.0 2000.0 2200.0 2500.0 3000.0 3100.0
-1500.0 2000.0 2200.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1600.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2600.0 2900.0 3100.0
-1900.0 2300.0 2600.0 2800.0 3100.0 3200.0
-2000.0 2400.0 2700.0 2800.0 3100.0 3200.0
-1300.0 1800.0 2000.0 2400.0 3100.0 3200.0
-1100.0 1700.0 2100.0 2400.0 3100.0 3200.0
-1300.0 1600.0 2100.0 2500.0 3000.0 3100.0
-1200.0 1700.0 2200.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2100.0 2300.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2200.0 3200.0 3300.0
-1700.0 1900.0 2100.0 2300.0 3200.0 3300.0
-1800.0 1900.0 2400.0 2800.0 3100.0 3200.0
-2000.0 2300.0 2800.0 3000.0 3100.0 3300.0
-2100.0 2300.0 2700.0 3000.0 3200.0 3300.0
-2100.0 2300.0 2600.0 2900.0 3200.0 3300.0
-2200.0 2400.0 2700.0 2800.0 3200.0 3300.0
-1700.0 2000.0 2300.0 2500.0 3000.0 3100.0
-1600.0 2000.0 2300.0 2400.0 2800.0 3200.0
-1700.0 2100.0 2300.0 2400.0 2900.0 3200.0
-1400.0 1800.0 2300.0 2600.0 3000.0 3300.0
-1500.0 2200.0 2400.0 2700.0 3100.0 3200.0
-1500.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1600.0 2400.0 2500.0 3100.0 3400.0
-1600.0 2200.0 2500.0 2800.0 3300.0 3400.0
-1600.0 2000.0 2500.0 2800.0 3300.0 3400.0
-1400.0 1700.0 2400.0 2500.0 3200.0 3400.0
-1400.0 1600.0 2400.0 2600.0 3200.0 3300.0
-1400.0 1700.0 2300.0 2500.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2400.0 2800.0 3200.0
-1500.0 2000.0 2300.0 2400.0 2700.0 3200.0
-1400.0 1900.0 2300.0 2500.0 3000.0 3300.0
-1200.0 1400.0 2300.0 2600.0 2900.0 3100.0
-1500.0 2000.0 2300.0 2500.0 3000.0 3200.0
-1800.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1500.0 1800.0 2400.0 2600.0 3000.0 3200.0
-1200.0 1500.0 2200.0 2400.0 3000.0 3100.0
-1500.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1700.0 2000.0 2600.0 2800.0 3200.0 3300.0
-1500.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1700.0 1800.0 2000.0 2300.0 3000.0 3100.0
-1600.0 1900.0 2300.0 2500.0 2800.0 3100.0
-1600.0 1800.0 2300.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1700.0 2200.0 2400.0 3000.0 3300.0
-1500.0 1700.0 2300.0 2500.0 3200.0 3400.0
-1500.0 1700.0 2300.0 2400.0 2800.0 3300.0
-1600.0 1700.0 2200.0 2400.0 2600.0 3200.0
-1700.0 1800.0 2200.0 2400.0 2900.0 3300.0
-1900.0 2100.0 2400.0 2500.0 3100.0 3300.0
-1900.0 2000.0 2400.0 2500.0 3100.0 3300.0
-1900.0 2300.0 2500.0 2900.0 3200.0 3300.0
-2200.0 2400.0 2700.0 3100.0 3300.0 3400.0
-2200.0 2400.0 2800.0 3100.0 3300.0 3400.0
-1500.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2300.0 3100.0 3300.0
-1700.0 2000.0 2600.0 2900.0 3200.0 3400.0
-1500.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1300.0 1600.0 2000.0 2500.0 3000.0 3200.0
-1800.0 2000.0 2200.0 2500.0 3000.0 3100.0
-1200.0 1800.0 2200.0 2400.0 3100.0 3200.0
-1300.0 1500.0 2100.0 2200.0 3100.0 3200.0
-1400.0 1900.0 2200.0 2300.0 3200.0 3300.0
-1900.0 2300.0 2600.0 3000.0 3200.0 3400.0
-1900.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2600.0 2900.0 3100.0 3300.0
-1200.0 1500.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1900.0 2300.0 2400.0 2600.0 3100.0
-1500.0 1600.0 2100.0 2400.0 2900.0 3200.0
-1400.0 1600.0 2200.0 2600.0 2900.0 3200.0
-1700.0 1800.0 2100.0 2300.0 3000.0 3100.0
-1700.0 1900.0 2100.0 2300.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2300.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2300.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2300.0 3100.0 3300.0
-1700.0 2100.0 2400.0 2900.0 3300.0 3400.0
-1600.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1500.0 2000.0 2400.0 2600.0 3100.0 3200.0
-1600.0 2000.0 2300.0 2500.0 2800.0 3000.0
-1500.0 1700.0 1800.0 2200.0 2800.0 2900.0
-1500.0 1700.0 1900.0 2100.0 2700.0 2800.0
-1600.0 2000.0 2300.0 2500.0 3000.0 3300.0
-1900.0 2300.0 2500.0 2800.0 3100.0 3200.0
-2200.0 2400.0 2600.0 3000.0 3200.0 3300.0
-2300.0 2500.0 2800.0 3100.0 3300.0 3400.0
-1900.0 2400.0 2700.0 3000.0 3400.0 3500.0
-1900.0 2400.0 2600.0 3000.0 3400.0 3500.0
-1800.0 2300.0 2700.0 3100.0 3400.0 3500.0
-1800.0 2300.0 2700.0 3000.0 3300.0 3400.0
-1400.0 1700.0 2200.0 2500.0 3200.0 3400.0
-1600.0 1900.0 2500.0 2600.0 3100.0 3300.0
-2000.0 2300.0 2600.0 2800.0 3300.0 3400.0
-1900.0 2200.0 2500.0 2800.0 3300.0 3400.0
-1700.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1600.0 1700.0 2300.0 2500.0 3200.0 3400.0
-1600.0 1700.0 2300.0 2400.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2600.0 3300.0 3400.0
-1500.0 1700.0 2300.0 2700.0 3300.0 3400.0
-1400.0 1800.0 2300.0 2400.0 3100.0 3400.0
-1500.0 2000.0 2300.0 2400.0 2900.0 3200.0
-1500.0 1900.0 2300.0 2400.0 2800.0 3200.0
-1300.0 1800.0 2200.0 2500.0 3000.0 3100.0
-1200.0 1700.0 2200.0 2300.0 3200.0 3300.0
-1200.0 1700.0 2200.0 2400.0 3200.0 3300.0
-1100.0 1700.0 2200.0 2400.0 3200.0 3300.0
-1100.0 1700.0 2300.0 2500.0 3100.0 3200.0
-1100.0 1700.0 2300.0 2600.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2600.0 3000.0 3200.0
-1300.0 1900.0 2300.0 2600.0 3000.0 3300.0
-1300.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1400.0 2000.0 2500.0 2800.0 3200.0 3300.0
-1200.0 1600.0 2400.0 2700.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2500.0 3100.0 3200.0
-1500.0 1600.0 2200.0 2600.0 3000.0 3200.0
-1500.0 1600.0 2200.0 2500.0 3000.0 3300.0
-1200.0 1600.0 2400.0 2600.0 3200.0 3400.0
-1000.0 2300.0 2800.0 2900.0 3100.0 3200.0
-900.0 1700.0 2700.0 2800.0 3200.0 3300.0
-1500.0 1700.0 2400.0 2500.0 3100.0 3200.0
-1500.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1400.0 1900.0 2400.0 2500.0 2900.0 3100.0
-1600.0 2100.0 2400.0 2600.0 3000.0 3100.0
-1700.0 1900.0 2300.0 2500.0 3000.0 3100.0
-2100.0 2400.0 2600.0 2900.0 3100.0 3300.0
-2200.0 2400.0 2700.0 2900.0 3200.0 3300.0
-2100.0 2200.0 2700.0 2800.0 3100.0 3300.0
-2000.0 2100.0 2300.0 2600.0 3100.0 3300.0
-1800.0 2000.0 2100.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2500.0 2900.0 3000.0
-1800.0 1900.0 2300.0 2400.0 3000.0 3100.0
-1800.0 1900.0 2200.0 2400.0 3000.0 3100.0
-1800.0 2000.0 2200.0 2500.0 3100.0 3200.0
-1800.0 2000.0 2300.0 2800.0 3100.0 3200.0
-1800.0 2000.0 2400.0 2800.0 3100.0 3200.0
-1800.0 2000.0 2400.0 2800.0 3000.0 3100.0
-1700.0 1900.0 2300.0 2700.0 2900.0 3100.0
-1700.0 1900.0 2200.0 2700.0 2900.0 3100.0
-1600.0 1800.0 2000.0 2600.0 2800.0 3000.0
-1500.0 1700.0 2000.0 2500.0 2900.0 3100.0
-1700.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2400.0 3100.0 3300.0
-1800.0 2000.0 2300.0 2500.0 3000.0 3100.0
-1800.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1400.0 1600.0 2100.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2000.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2000.0 2400.0 3200.0 3300.0
-1200.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1100.0 1700.0 2100.0 2300.0 3000.0 3100.0
-1300.0 1500.0 1700.0 2000.0 2900.0 3100.0
-1600.0 1900.0 2200.0 2400.0 2900.0 3100.0
-1700.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1700.0 1800.0 2100.0 2500.0 3100.0 3300.0
-2000.0 2300.0 2500.0 2700.0 3100.0 3400.0
-1900.0 2200.0 2500.0 2600.0 3000.0 3300.0
-1900.0 2000.0 2300.0 2400.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2400.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2400.0 3000.0 3100.0
-1500.0 1600.0 2500.0 2600.0 2900.0 3300.0
-1500.0 1700.0 2500.0 2600.0 3100.0 3200.0
-1900.0 2300.0 2500.0 2800.0 3200.0 3300.0
-1400.0 1600.0 2000.0 2600.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2600.0 3000.0 3100.0
-1800.0 1900.0 2400.0 2900.0 3100.0 3300.0
-1800.0 1900.0 2500.0 2900.0 3100.0 3300.0
-1600.0 1800.0 2100.0 2700.0 3000.0 3200.0
-1700.0 2000.0 2300.0 2700.0 2900.0 3200.0
-1600.0 2000.0 2400.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2300.0 2500.0 3300.0 3400.0
-1400.0 1600.0 2200.0 2400.0 3100.0 3300.0
-1500.0 1600.0 2200.0 2500.0 3200.0 3400.0
-1600.0 1700.0 2300.0 2400.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2500.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2500.0 3200.0 3300.0
-1700.0 2100.0 2300.0 2400.0 3100.0 3300.0
-1600.0 2000.0 2400.0 2500.0 3000.0 3300.0
-1500.0 1800.0 2300.0 2400.0 2900.0 3200.0
-1600.0 2000.0 2400.0 2800.0 3200.0 3400.0
-1900.0 2200.0 2600.0 2800.0 3200.0 3400.0
-1900.0 2200.0 2500.0 2800.0 3100.0 3400.0
-1300.0 1800.0 2400.0 2600.0 3100.0 3400.0
-1300.0 1500.0 2400.0 2500.0 2900.0 3300.0
-1300.0 1700.0 2500.0 2600.0 3100.0 3200.0
-1300.0 1700.0 2600.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1700.0 1900.0 2100.0 2600.0 3200.0 3300.0
-1700.0 2000.0 2100.0 2300.0 3200.0 3300.0
-2000.0 2100.0 2400.0 2600.0 3200.0 3400.0
-2100.0 2200.0 2500.0 2700.0 3200.0 3400.0
-1800.0 1900.0 2500.0 2700.0 3200.0 3400.0
-1700.0 2000.0 2500.0 2700.0 3300.0 3400.0
-1400.0 1900.0 2500.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1600.0 2000.0 2300.0 2600.0 3000.0 3200.0
-1600.0 1900.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2100.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2200.0 2500.0 2700.0 3100.0
-1400.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1300.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1300.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1800.0 2100.0 2500.0 2700.0 3000.0 3300.0
-1800.0 2100.0 2400.0 2700.0 3100.0 3300.0
-1900.0 2100.0 2500.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2400.0 3200.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1900.0 2000.0 2700.0 2800.0 3200.0 3400.0
-1900.0 2000.0 2600.0 2900.0 3100.0 3300.0
-2000.0 2200.0 2800.0 2900.0 3300.0 3400.0
-2000.0 2100.0 2700.0 2800.0 3300.0 3400.0
-1900.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1600.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1400.0 1900.0 2100.0 2400.0 3200.0 3300.0
-1200.0 1900.0 2100.0 2400.0 3100.0 3200.0
-1200.0 1800.0 2100.0 2500.0 2900.0 3200.0
-1300.0 1700.0 1900.0 2400.0 2800.0 2900.0
-1900.0 2300.0 2600.0 3000.0 3200.0 3300.0
-1800.0 2300.0 2600.0 3000.0 3300.0 3400.0
-1800.0 2200.0 2500.0 2800.0 3300.0 3500.0
-1700.0 1900.0 2300.0 2400.0 3200.0 3400.0
-1800.0 1900.0 2400.0 2500.0 3100.0 3300.0
-2100.0 2200.0 2400.0 2500.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2800.0 3100.0 3200.0
-2000.0 2300.0 2600.0 2700.0 3100.0 3300.0
-2100.0 2200.0 2500.0 2600.0 3100.0 3300.0
-2000.0 2200.0 2300.0 2500.0 3100.0 3300.0
-1800.0 1900.0 2100.0 2300.0 3200.0 3300.0
-1800.0 1900.0 2100.0 2400.0 3300.0 3400.0
-1700.0 1800.0 2200.0 2300.0 3300.0 3400.0
-1700.0 1800.0 2200.0 2300.0 3200.0 3400.0
-1600.0 1700.0 2200.0 2300.0 2900.0 3400.0
-1400.0 1600.0 2500.0 2600.0 3100.0 3200.0
-1300.0 1400.0 2400.0 2600.0 3000.0 3100.0
-1300.0 1500.0 2400.0 2500.0 3000.0 3200.0
-1300.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1300.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2400.0 3300.0 3400.0
-1000.0 1500.0 2500.0 2600.0 3200.0 3400.0
-1000.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1700.0 2200.0 2600.0 3000.0 3200.0
-900.0 1800.0 2400.0 2600.0 3300.0 3400.0
-900.0 1800.0 2300.0 2400.0 3300.0 3400.0
-1000.0 1600.0 2300.0 2400.0 3300.0 3400.0
-1400.0 1900.0 2200.0 2600.0 3300.0 3400.0
-1500.0 1900.0 2300.0 2600.0 3300.0 3400.0
-1300.0 2000.0 2200.0 2500.0 3000.0 3200.0
-1100.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1100.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1100.0 1900.0 2400.0 2700.0 3200.0 3300.0
-1300.0 2000.0 2200.0 2400.0 3200.0 3300.0
-1800.0 2100.0 2400.0 2800.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2700.0 3300.0 3400.0
-1700.0 2000.0 2300.0 2700.0 3200.0 3400.0
-1200.0 1600.0 2500.0 2600.0 3200.0 3400.0
-1100.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1500.0 1600.0 2400.0 2700.0 2900.0 3200.0
-1500.0 1800.0 2500.0 2700.0 3100.0 3400.0
-1600.0 1900.0 2600.0 2800.0 3100.0 3300.0
-1700.0 1800.0 2600.0 2700.0 3000.0 3300.0
-1700.0 1800.0 2500.0 2600.0 2900.0 3200.0
-1700.0 1800.0 2500.0 2600.0 3000.0 3300.0
-1600.0 1700.0 2500.0 2600.0 3000.0 3300.0
-1700.0 2000.0 2400.0 2700.0 3100.0 3400.0
-1700.0 1800.0 2400.0 2600.0 2900.0 3200.0
-1800.0 1900.0 2500.0 2600.0 2900.0 3200.0
-1700.0 1800.0 2200.0 2500.0 2700.0 3200.0
-1700.0 1800.0 2300.0 2500.0 2800.0 3200.0
-1500.0 1600.0 2000.0 2400.0 2600.0 2900.0
-1200.0 1300.0 2100.0 2400.0 2600.0 3200.0
-1700.0 2200.0 2500.0 2900.0 3200.0 3400.0
-1700.0 2200.0 2600.0 2900.0 3400.0 3500.0
-1700.0 2100.0 2700.0 2900.0 3400.0 3500.0
-1500.0 1800.0 2400.0 2600.0 3100.0 3300.0
-1100.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1700.0 2600.0 2700.0 3200.0 3400.0
-1400.0 1900.0 2600.0 2800.0 3200.0 3300.0
-1600.0 2000.0 2500.0 2900.0 3300.0 3400.0
-1500.0 1700.0 2500.0 2700.0 3100.0 3300.0
-1800.0 2000.0 2500.0 2700.0 2900.0 3300.0
-1900.0 2000.0 2600.0 2700.0 2900.0 3300.0
-1900.0 2100.0 2400.0 2700.0 2900.0 3200.0
-1900.0 2000.0 2500.0 2700.0 3000.0 3300.0
-1900.0 2000.0 2400.0 2700.0 3000.0 3300.0
-1700.0 1900.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1900.0 2500.0 2600.0 3200.0 3500.0
-1900.0 2100.0 2600.0 2900.0 3200.0 3400.0
-2100.0 2300.0 2700.0 2900.0 3200.0 3300.0
-1600.0 2000.0 2200.0 2400.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2400.0 2900.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2800.0 3200.0
-1900.0 2200.0 2500.0 2700.0 3000.0 3200.0
-1900.0 2300.0 2600.0 2700.0 3100.0 3200.0
-1800.0 2400.0 2600.0 2900.0 3200.0 3300.0
-1800.0 2300.0 2500.0 2900.0 3200.0 3300.0
-1600.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1500.0 1700.0 2200.0 2400.0 2900.0 3200.0
-1500.0 1600.0 2200.0 2300.0 2800.0 3200.0
-1400.0 1500.0 2100.0 2200.0 2800.0 3200.0
-1400.0 1500.0 2100.0 2300.0 2800.0 3200.0
-1400.0 1500.0 2200.0 2400.0 2700.0 3100.0
-1700.0 1900.0 2400.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2400.0 2700.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2700.0 2900.0 3300.0
-2000.0 2100.0 2400.0 2700.0 3000.0 3300.0
-1400.0 1600.0 2500.0 2700.0 3100.0 3400.0
-1000.0 1600.0 2300.0 2400.0 3100.0 3200.0
-1100.0 1700.0 2400.0 2500.0 3200.0 3300.0
-1200.0 1700.0 2300.0 2400.0 3100.0 3200.0
-2000.0 2100.0 2400.0 2500.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1400.0 1600.0 2300.0 2400.0 3100.0 3300.0
-1300.0 1500.0 2300.0 2500.0 3000.0 3300.0
-1300.0 1500.0 2300.0 2500.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2400.0 2500.0 3000.0 3200.0
-1900.0 2400.0 2600.0 3000.0 3200.0 3300.0
-1400.0 1500.0 2400.0 2600.0 2900.0 3300.0
-1400.0 1500.0 2200.0 2600.0 2800.0 3300.0
-1400.0 1500.0 2200.0 2500.0 2800.0 3200.0
-1400.0 1500.0 2300.0 2500.0 3000.0 3300.0
-1600.0 2000.0 2400.0 2700.0 3200.0 3400.0
-1700.0 2200.0 2600.0 2800.0 3100.0 3300.0
-1800.0 2100.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2300.0 3000.0 3300.0
-1600.0 1700.0 2200.0 2500.0 3200.0 3400.0
-1600.0 1800.0 2300.0 2400.0 3100.0 3300.0
-1700.0 1800.0 2200.0 2400.0 3000.0 3300.0
-1700.0 1800.0 2200.0 2300.0 3000.0 3200.0
-1700.0 1800.0 2200.0 2300.0 3100.0 3300.0
-1700.0 2000.0 2200.0 2600.0 3200.0 3300.0
-1800.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1600.0 1700.0 2100.0 2400.0 2900.0 3200.0
-1500.0 1800.0 2300.0 2700.0 3000.0 3300.0
-1500.0 1800.0 2200.0 2600.0 3000.0 3300.0
-1700.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2600.0 2800.0 3200.0 3400.0
-1800.0 1900.0 2500.0 2800.0 3100.0 3300.0
-1600.0 1800.0 2500.0 2600.0 3000.0 3300.0
-1200.0 1500.0 2500.0 2700.0 3100.0 3200.0
-1100.0 1900.0 2500.0 2600.0 3100.0 3200.0
-1200.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1500.0 1700.0 2100.0 2200.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2200.0 3300.0 3400.0
-1500.0 1600.0 1800.0 2000.0 3300.0 3400.0
-1400.0 1600.0 1800.0 1900.0 3300.0 3400.0
-1400.0 1600.0 2400.0 2600.0 3000.0 3400.0
-1400.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1500.0 1700.0 2400.0 2700.0 3100.0 3300.0
-1500.0 1800.0 2500.0 2700.0 3000.0 3300.0
-1400.0 1500.0 2400.0 2600.0 3000.0 3300.0
-1200.0 1400.0 2300.0 2400.0 3000.0 3200.0
-1200.0 1600.0 2300.0 2400.0 3100.0 3200.0
-1400.0 2000.0 2400.0 2700.0 3100.0 3300.0
-1600.0 1900.0 2300.0 2700.0 3100.0 3200.0
-1500.0 1900.0 2300.0 2700.0 3100.0 3200.0
-1200.0 1400.0 2300.0 2500.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2600.0 3000.0 3100.0
-1800.0 1900.0 2500.0 2600.0 2900.0 3100.0
-1600.0 2000.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1900.0 2400.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2400.0 2500.0 2900.0 3300.0
-1700.0 1800.0 2300.0 2500.0 2900.0 3200.0
-1700.0 1800.0 2400.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1700.0 2000.0 2300.0 2500.0 3000.0 3200.0
-1800.0 2000.0 2300.0 2500.0 3000.0 3200.0
-1900.0 2100.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2100.0 2400.0 2600.0 3000.0 3300.0
-2000.0 2100.0 2300.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1700.0 2100.0 2500.0 2700.0 3200.0 3400.0
-1700.0 1900.0 2300.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2400.0 2900.0 3300.0
-1800.0 1900.0 2300.0 2500.0 3000.0 3300.0
-1800.0 2000.0 2200.0 2500.0 2900.0 3200.0
-1900.0 2200.0 2400.0 2600.0 2900.0 3200.0
-1700.0 2100.0 2600.0 2800.0 3100.0 3300.0
-1800.0 2300.0 2700.0 2900.0 3200.0 3300.0
-2000.0 2300.0 2800.0 2900.0 3100.0 3300.0
-2100.0 2200.0 2600.0 2800.0 3200.0 3300.0
-1800.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1800.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1600.0 1800.0 2000.0 3100.0 3300.0
-1300.0 1700.0 2300.0 2400.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2300.0 2500.0 2900.0 3100.0
-1500.0 1700.0 2300.0 2500.0 2900.0 3100.0
-1500.0 1700.0 2300.0 2500.0 2800.0 3000.0
-1500.0 1600.0 2300.0 2500.0 2800.0 3200.0
-1400.0 1500.0 2300.0 2600.0 3000.0 3200.0
-1200.0 1600.0 2400.0 2500.0 3000.0 3300.0
-1400.0 1600.0 2200.0 2500.0 2900.0 3200.0
-1500.0 1900.0 2300.0 2600.0 2900.0 3200.0
-1400.0 1800.0 2400.0 2700.0 3200.0 3400.0
-1500.0 1900.0 2400.0 2700.0 3200.0 3400.0
-1700.0 2100.0 2400.0 2800.0 3000.0 3300.0
-1700.0 2000.0 2500.0 2700.0 3100.0 3400.0
-1800.0 1900.0 2400.0 2800.0 3200.0 3300.0
-1800.0 1900.0 2300.0 2900.0 3200.0 3300.0
-1800.0 1900.0 2500.0 2800.0 3200.0 3300.0
-1700.0 1800.0 2400.0 2800.0 3200.0 3300.0
-1700.0 1800.0 2400.0 2700.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2600.0 3000.0 3300.0
-1600.0 1700.0 2200.0 2500.0 2900.0 3300.0
-1500.0 1600.0 2300.0 2500.0 3000.0 3300.0
-1500.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1500.0 2000.0 2400.0 2800.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2400.0 2700.0 3200.0 3400.0
-1300.0 1700.0 2300.0 2500.0 3200.0 3400.0
-1100.0 1700.0 2300.0 2400.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2200.0 3300.0 3400.0
-1900.0 2300.0 2600.0 2800.0 3200.0 3400.0
-1900.0 2400.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2300.0 2700.0 2900.0 3400.0 3500.0
-1900.0 2300.0 2700.0 2900.0 3400.0 3500.0
-1900.0 2100.0 2800.0 2900.0 3300.0 3400.0
-1700.0 1800.0 2700.0 2800.0 3100.0 3300.0
-1500.0 1700.0 2700.0 2800.0 3200.0 3300.0
-1500.0 1600.0 2600.0 2700.0 3000.0 3300.0
-1400.0 1600.0 2600.0 2800.0 3000.0 3200.0
-1200.0 1400.0 2600.0 2700.0 3000.0 3200.0
-1000.0 1500.0 2600.0 2800.0 3200.0 3400.0
-1100.0 1300.0 2500.0 2800.0 3000.0 3200.0
-1500.0 1600.0 2500.0 2600.0 3000.0 3300.0
-1400.0 1500.0 2300.0 2600.0 2800.0 3200.0
-1400.0 1600.0 2200.0 2600.0 2800.0 3100.0
-1500.0 1600.0 2300.0 2700.0 2900.0 3200.0
-1400.0 1500.0 2500.0 2600.0 3100.0 3400.0
-1400.0 1500.0 2400.0 2600.0 2800.0 3300.0
-1400.0 1600.0 2400.0 2600.0 2800.0 3200.0
-1300.0 1600.0 2300.0 2600.0 2900.0 3300.0
-1700.0 2200.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2300.0 2600.0 2700.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3100.0 3200.0
-1800.0 2300.0 2500.0 2600.0 3200.0 3300.0
-1900.0 2400.0 2500.0 2800.0 3300.0 3400.0
-1800.0 2000.0 2600.0 2800.0 3300.0 3400.0
-1600.0 1900.0 2400.0 2800.0 3200.0 3300.0
-1700.0 1800.0 2600.0 2800.0 3000.0 3300.0
-1900.0 2000.0 2600.0 2800.0 3200.0 3300.0
-2000.0 2100.0 2700.0 2800.0 3200.0 3400.0
-2000.0 2100.0 2600.0 2800.0 3300.0 3400.0
-1600.0 1700.0 2300.0 2600.0 2900.0 3300.0
-1400.0 1600.0 2400.0 2500.0 2800.0 3200.0
-1800.0 1900.0 2500.0 2700.0 3000.0 3400.0
-1900.0 2000.0 2600.0 2700.0 3000.0 3300.0
-1700.0 2000.0 2400.0 2600.0 2900.0 3200.0
-1500.0 1600.0 2300.0 2600.0 3000.0 3300.0
-1500.0 1600.0 2400.0 2600.0 2900.0 3300.0
-1400.0 1500.0 2300.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2500.0 2600.0 2900.0 3200.0
-2000.0 2100.0 2400.0 2600.0 3000.0 3200.0
-1800.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1600.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1500.0 1800.0 2400.0 2700.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2400.0 3000.0 3200.0
-2000.0 2200.0 2400.0 2500.0 3200.0 3300.0
-2200.0 2300.0 2600.0 2700.0 3200.0 3300.0
-2100.0 2200.0 2400.0 2700.0 3000.0 3200.0
-2100.0 2200.0 2500.0 2700.0 3000.0 3200.0
-2200.0 2300.0 2600.0 2800.0 3000.0 3300.0
-1900.0 2200.0 2600.0 2700.0 3000.0 3300.0
-1700.0 1800.0 2500.0 2700.0 2800.0 3200.0
-1700.0 1800.0 2600.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2500.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2700.0 3300.0 3400.0
-1800.0 2000.0 2400.0 2600.0 3100.0 3200.0
-1700.0 2200.0 2300.0 2500.0 3200.0 3300.0
-1700.0 2200.0 2300.0 2600.0 3100.0 3200.0
-1600.0 1700.0 2400.0 2600.0 3300.0 3400.0
-1600.0 1700.0 2400.0 2500.0 3300.0 3400.0
-1900.0 2100.0 2500.0 2800.0 3000.0 3100.0
-1800.0 2100.0 2500.0 2800.0 3000.0 3100.0
-1800.0 2100.0 2600.0 2800.0 3100.0 3200.0
-1800.0 2000.0 2500.0 2800.0 3100.0 3200.0
-1900.0 2100.0 2500.0 2600.0 3000.0 3200.0
-1800.0 1900.0 2600.0 2800.0 3200.0 3400.0
-1500.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1100.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1100.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1300.0 1500.0 2200.0 2400.0 2900.0 3300.0
-1600.0 1700.0 2300.0 2500.0 2900.0 3300.0
-1600.0 1700.0 2400.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2000.0 2500.0 2700.0 3100.0 3200.0
-2100.0 2200.0 2400.0 2600.0 3100.0 3400.0
-2100.0 2200.0 2500.0 2600.0 3000.0 3400.0
-1900.0 2100.0 2400.0 2700.0 3000.0 3100.0
-1600.0 1800.0 2200.0 2400.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2300.0 2900.0 3300.0
-1600.0 1700.0 2100.0 2300.0 2800.0 3100.0
-2200.0 2300.0 2600.0 2800.0 3100.0 3300.0
-2200.0 2300.0 2700.0 2800.0 3100.0 3400.0
-2000.0 2100.0 2600.0 2800.0 3100.0 3400.0
-1700.0 1800.0 2400.0 2700.0 2900.0 3200.0
-1600.0 1800.0 2400.0 2700.0 3100.0 3200.0
-1600.0 1800.0 2300.0 2400.0 3000.0 3200.0
-1800.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2600.0 2900.0 3200.0
-1900.0 2100.0 2300.0 2700.0 2800.0 3000.0
-1800.0 2000.0 2600.0 2700.0 3000.0 3300.0
-1800.0 1900.0 2400.0 2600.0 2900.0 3300.0
-1700.0 1800.0 2300.0 2400.0 2900.0 3300.0
-1600.0 1700.0 2100.0 2500.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2600.0 3100.0 3200.0
-1500.0 1700.0 2200.0 2500.0 2900.0 3300.0
-1500.0 1600.0 2300.0 2400.0 2800.0 3300.0
-1400.0 1600.0 2300.0 2400.0 3000.0 3300.0
-1500.0 2000.0 2500.0 2800.0 3200.0 3300.0
-1300.0 1500.0 2600.0 2700.0 3100.0 3300.0
-1200.0 1400.0 1700.0 1900.0 3100.0 3300.0
-1200.0 1700.0 1900.0 2300.0 3200.0 3300.0
-1200.0 1900.0 2000.0 2300.0 3200.0 3300.0
-1200.0 2000.0 2100.0 2500.0 3300.0 3400.0
-1200.0 2000.0 2200.0 2600.0 3300.0 3400.0
-1200.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1000.0 1900.0 2300.0 2500.0 3200.0 3300.0
-1200.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1400.0 1600.0 2300.0 2500.0 3200.0 3300.0
-1500.0 1600.0 2500.0 2700.0 2900.0 3200.0
-1600.0 1900.0 2400.0 2800.0 3100.0 3300.0
-1700.0 1800.0 2400.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2500.0 2800.0 3100.0 3200.0
-1500.0 1800.0 2400.0 2500.0 2900.0 3100.0
-1500.0 1600.0 2400.0 2500.0 2900.0 3200.0
-1300.0 1500.0 2200.0 2500.0 2800.0 3100.0
-1300.0 1400.0 2000.0 2400.0 2600.0 2900.0
-1400.0 1500.0 2100.0 2500.0 2700.0 3100.0
-1500.0 2000.0 2300.0 2600.0 3000.0 3200.0
-1700.0 2100.0 2400.0 2600.0 2900.0 3100.0
-1400.0 1500.0 2300.0 2600.0 3000.0 3300.0
-1500.0 1700.0 2200.0 2300.0 3200.0 3300.0
-1400.0 1600.0 2000.0 2400.0 3100.0 3300.0
-1500.0 1700.0 2000.0 2100.0 3100.0 3300.0
-1600.0 1900.0 2200.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2200.0 2400.0 2800.0 3200.0
-1500.0 1600.0 2100.0 2500.0 3000.0 3300.0
-1500.0 1600.0 2000.0 2500.0 2900.0 3300.0
-1500.0 1600.0 2100.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2200.0 2700.0 2800.0 3100.0
-1300.0 1400.0 2200.0 2600.0 3000.0 3200.0
-1400.0 1900.0 2400.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2500.0 2600.0 3000.0 3200.0
-1500.0 1700.0 2300.0 2500.0 2800.0 3200.0
-1700.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2300.0 3000.0 3300.0
-1600.0 1700.0 2000.0 2400.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2600.0 2900.0 3200.0
-1500.0 2000.0 2300.0 2600.0 3100.0 3400.0
-1400.0 1900.0 2500.0 2700.0 3100.0 3300.0
-1400.0 1700.0 2600.0 2700.0 3100.0 3300.0
-1500.0 1600.0 2300.0 2600.0 2800.0 3200.0
-1700.0 1800.0 2300.0 2500.0 3100.0 3400.0
-1500.0 1600.0 2200.0 2300.0 3100.0 3300.0
-1400.0 1500.0 2200.0 2400.0 3100.0 3200.0
-1400.0 1600.0 2200.0 2400.0 3000.0 3100.0
-1700.0 2100.0 2300.0 2700.0 3100.0 3200.0
-1900.0 2300.0 2500.0 2700.0 3100.0 3200.0
-1900.0 2300.0 2600.0 2800.0 3100.0 3300.0
-1900.0 2400.0 2600.0 2900.0 3200.0 3300.0
-1900.0 2300.0 2600.0 2800.0 3300.0 3400.0
-1800.0 2400.0 2600.0 2800.0 3300.0 3400.0
-1600.0 1800.0 2600.0 2700.0 3000.0 3300.0
-1600.0 1700.0 2600.0 2700.0 2900.0 3200.0
-1500.0 1600.0 2500.0 2700.0 3000.0 3300.0
-1300.0 1400.0 2400.0 2700.0 2900.0 3300.0
-1300.0 1400.0 2300.0 2700.0 2800.0 3100.0
-1300.0 1400.0 2500.0 2800.0 3000.0 3300.0
-1500.0 1700.0 2400.0 2500.0 2800.0 3300.0
-1900.0 2000.0 2500.0 2600.0 3000.0 3200.0
-1800.0 2000.0 2400.0 2500.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2300.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2400.0 2800.0 3200.0
-1600.0 1700.0 2200.0 2400.0 2800.0 3200.0
-1500.0 1600.0 2200.0 2400.0 2700.0 3300.0
-1400.0 1500.0 2200.0 2400.0 2900.0 3200.0
-1600.0 1700.0 2300.0 2500.0 2700.0 3000.0
-1600.0 1700.0 2200.0 2500.0 2700.0 3000.0
-1700.0 1900.0 2200.0 2500.0 2800.0 3100.0
-1900.0 2000.0 2300.0 2500.0 2900.0 3100.0
-1900.0 2100.0 2300.0 2500.0 2900.0 3200.0
-1900.0 2100.0 2300.0 2500.0 3100.0 3300.0
-2000.0 2200.0 2600.0 2800.0 3000.0 3200.0
-1900.0 2200.0 2500.0 2700.0 2900.0 3200.0
-2100.0 2300.0 2600.0 2800.0 3100.0 3300.0
-2100.0 2300.0 2600.0 2700.0 3000.0 3200.0
-2100.0 2200.0 2500.0 2600.0 3000.0 3200.0
-1500.0 1600.0 2300.0 2400.0 2900.0 3200.0
-1400.0 1500.0 2100.0 2400.0 2800.0 3100.0
-1300.0 1600.0 2100.0 2400.0 3100.0 3200.0
-1300.0 1400.0 2300.0 2600.0 2800.0 3200.0
-1400.0 1500.0 2200.0 2500.0 2700.0 3200.0
-1400.0 1500.0 2300.0 2500.0 2700.0 3200.0
-1500.0 1600.0 2400.0 2500.0 2800.0 3200.0
-1600.0 1700.0 2400.0 2500.0 2900.0 3200.0
-1700.0 1800.0 2400.0 2500.0 2900.0 3100.0
-1800.0 1900.0 2400.0 2600.0 3000.0 3200.0
-2100.0 2200.0 2700.0 2900.0 3200.0 3300.0
-1800.0 2100.0 2500.0 2900.0 3100.0 3300.0
-1700.0 1800.0 2500.0 2800.0 2900.0 3300.0
-1200.0 1600.0 2100.0 2400.0 3000.0 3200.0
-1600.0 1700.0 2100.0 2600.0 2900.0 3000.0
-1600.0 1700.0 2200.0 2700.0 2900.0 3000.0
-1600.0 1800.0 2200.0 2500.0 2900.0 3000.0
-1700.0 1800.0 2300.0 2500.0 2900.0 3100.0
-1700.0 1900.0 2300.0 2600.0 2900.0 3100.0
-1500.0 1700.0 2000.0 2600.0 2900.0 3100.0
-1400.0 1600.0 1800.0 2600.0 3000.0 3100.0
-1300.0 1500.0 1700.0 2700.0 3100.0 3200.0
-1300.0 1700.0 2400.0 2700.0 3100.0 3300.0
-1200.0 1600.0 2400.0 2600.0 2900.0 3200.0
-1300.0 1400.0 2000.0 2700.0 2800.0 3000.0
-1400.0 1500.0 2000.0 2600.0 2800.0 3000.0
-1500.0 1700.0 2100.0 2600.0 2800.0 3000.0
-1600.0 1800.0 2200.0 2700.0 2800.0 3000.0
-1600.0 1800.0 2100.0 2700.0 2900.0 3100.0
-1500.0 1900.0 2300.0 2700.0 3000.0 3100.0
-1500.0 1900.0 2300.0 2700.0 3000.0 3200.0
-1500.0 2000.0 2300.0 2700.0 3000.0 3200.0
-1800.0 2100.0 2300.0 2700.0 3100.0 3300.0
-1500.0 2000.0 2300.0 2600.0 3000.0 3100.0
-1500.0 2100.0 2300.0 2700.0 3100.0 3200.0
-1600.0 2100.0 2200.0 2700.0 3100.0 3200.0
-1500.0 2100.0 2200.0 2600.0 3100.0 3200.0
-1400.0 2300.0 2500.0 2700.0 3100.0 3200.0
-1700.0 2100.0 2300.0 2700.0 2900.0 3100.0
-1500.0 1800.0 2300.0 2700.0 3000.0 3100.0
-1500.0 1700.0 2300.0 2700.0 3000.0 3100.0
-1500.0 1600.0 2100.0 2700.0 3000.0 3100.0
-1400.0 1500.0 1900.0 2600.0 3100.0 3200.0
-1200.0 1300.0 1900.0 2600.0 2900.0 3100.0
-1100.0 1200.0 1800.0 2700.0 3000.0 3100.0
-1200.0 1300.0 1800.0 2700.0 3000.0 3100.0
-1200.0 1400.0 1900.0 2700.0 3000.0 3100.0
-1300.0 1500.0 1800.0 2600.0 3000.0 3100.0
-1200.0 1400.0 2300.0 2700.0 2900.0 3100.0
-1300.0 1400.0 2200.0 2700.0 2800.0 3100.0
-1300.0 1500.0 2000.0 2600.0 2900.0 3100.0
-1300.0 1500.0 2100.0 2700.0 2900.0 3100.0
-1400.0 1800.0 2100.0 2600.0 2800.0 3000.0
-1400.0 1800.0 2100.0 2500.0 2900.0 3100.0
-1700.0 2000.0 2500.0 2800.0 3000.0 3200.0
-1900.0 2000.0 2700.0 2800.0 3100.0 3400.0
-1900.0 2100.0 2600.0 2800.0 3100.0 3300.0
-1600.0 2100.0 2400.0 2700.0 3200.0 3400.0
-1700.0 2000.0 2300.0 2500.0 2800.0 3200.0
-1500.0 1700.0 2100.0 2300.0 3000.0 3200.0
-1400.0 1900.0 2200.0 2500.0 2900.0 3200.0
-1400.0 1900.0 2300.0 2500.0 2700.0 3100.0
-1300.0 1500.0 2100.0 2700.0 2800.0 3100.0
-1300.0 1500.0 2000.0 2600.0 2800.0 3100.0
-1300.0 1400.0 2100.0 2600.0 2800.0 3000.0
-1300.0 1400.0 2000.0 2600.0 2800.0 3000.0
-1200.0 1300.0 2000.0 2700.0 2800.0 3000.0
-1200.0 1400.0 2300.0 2600.0 2900.0 3200.0
-1300.0 1600.0 2300.0 2700.0 2900.0 3200.0
-1600.0 1900.0 2300.0 2800.0 3100.0 3200.0
-1700.0 1900.0 2300.0 2800.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2600.0 2900.0 3000.0
-1700.0 1900.0 2400.0 2600.0 2800.0 3100.0
-1700.0 2100.0 2400.0 2500.0 2800.0 3100.0
-1700.0 2000.0 2400.0 2500.0 2900.0 3100.0
-1900.0 2200.0 2400.0 2600.0 3000.0 3200.0
-1700.0 2000.0 2400.0 2700.0 3000.0 3100.0
-1500.0 1900.0 2300.0 2600.0 3000.0 3100.0
-1500.0 1600.0 2100.0 2600.0 2900.0 3200.0
-1400.0 1600.0 1800.0 2300.0 2800.0 2900.0
-1400.0 1600.0 1700.0 2500.0 3200.0 3300.0
-1400.0 1600.0 1800.0 2400.0 3200.0 3300.0
-1400.0 1700.0 1900.0 2200.0 3100.0 3200.0
-1300.0 1700.0 1900.0 2300.0 3100.0 3200.0
-1100.0 1600.0 2000.0 2300.0 3000.0 3100.0
-1500.0 1900.0 2500.0 2800.0 3200.0 3300.0
-1800.0 2000.0 2300.0 2800.0 3000.0 3100.0
-1800.0 1900.0 2300.0 2700.0 2900.0 3200.0
-1700.0 1900.0 2300.0 2600.0 2800.0 3100.0
-1700.0 1900.0 2100.0 2500.0 2700.0 3000.0
-1700.0 1900.0 2100.0 2600.0 2800.0 3000.0
-1700.0 1900.0 2100.0 2700.0 2900.0 3100.0
-1700.0 1900.0 2500.0 2800.0 3000.0 3300.0
-1400.0 1600.0 1900.0 2600.0 2900.0 3000.0
-1500.0 1600.0 2000.0 2200.0 3200.0 3300.0
-1300.0 1500.0 1700.0 2600.0 3100.0 3200.0
-1300.0 1500.0 1700.0 2700.0 3000.0 3100.0
-1500.0 1700.0 2300.0 2700.0 3000.0 3200.0
-1700.0 2000.0 2500.0 2800.0 3100.0 3200.0
-1200.0 1300.0 1800.0 2600.0 3000.0 3100.0
-1300.0 1600.0 2000.0 2400.0 3000.0 3200.0
-1500.0 1600.0 2000.0 2600.0 3200.0 3300.0
-1600.0 1700.0 2100.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2700.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2700.0 3200.0 3300.0
-1600.0 1900.0 2100.0 2700.0 3200.0 3300.0
-1100.0 1800.0 2200.0 2400.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2800.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2700.0 3000.0 3100.0
-1500.0 1800.0 2200.0 2800.0 3100.0 3200.0
-1600.0 1900.0 2200.0 2800.0 3100.0 3200.0
-1600.0 1900.0 2100.0 2700.0 3100.0 3200.0
-1500.0 1900.0 2100.0 2600.0 3100.0 3200.0
-1700.0 2100.0 2400.0 2700.0 3000.0 3300.0
-1900.0 2400.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2200.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2200.0 2600.0 2900.0 3200.0 3300.0
-1800.0 2400.0 2600.0 2800.0 3100.0 3200.0
-1800.0 2400.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2300.0 2400.0 2700.0 3100.0 3200.0
-1600.0 2300.0 2500.0 2700.0 3100.0 3200.0
-1500.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1600.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1500.0 2200.0 2500.0 2700.0 3100.0 3200.0
-1500.0 2200.0 2400.0 2600.0 3000.0 3100.0
-1600.0 2200.0 2400.0 2700.0 3000.0 3100.0
-1500.0 2100.0 2400.0 2700.0 3000.0 3100.0
-1400.0 1800.0 2100.0 2400.0 3200.0 3300.0
-1200.0 1300.0 2100.0 2800.0 3000.0 3200.0
-1300.0 1400.0 2100.0 2700.0 3000.0 3200.0
-1500.0 1700.0 2200.0 2800.0 3000.0 3100.0
-1800.0 2200.0 2400.0 2600.0 3000.0 3200.0
-1700.0 1900.0 2400.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2500.0 2800.0 3000.0 3200.0
-1600.0 1800.0 2500.0 2700.0 3000.0 3200.0
-1600.0 1700.0 2300.0 2700.0 2900.0 3100.0
-1500.0 1700.0 2100.0 2700.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2600.0 2900.0 3000.0
-1500.0 1600.0 1900.0 2600.0 3000.0 3100.0
-1500.0 1700.0 2000.0 2500.0 3000.0 3100.0
-1500.0 1700.0 2000.0 2500.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2600.0 3000.0 3100.0
-1500.0 1800.0 2000.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2500.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2600.0 2900.0 3200.0 3300.0
-1800.0 2000.0 2500.0 2900.0 3100.0 3300.0
-1400.0 1600.0 1900.0 2600.0 3000.0 3100.0
-1400.0 1600.0 1900.0 2700.0 3000.0 3100.0
-1500.0 1700.0 2300.0 2800.0 3000.0 3200.0
-1700.0 2000.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2100.0 2600.0 3000.0 3300.0 3400.0
-1800.0 2100.0 2600.0 3000.0 3200.0 3400.0
-1600.0 1800.0 2300.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2600.0 3100.0 3200.0
-1100.0 1400.0 2100.0 2800.0 3100.0 3200.0
-1200.0 1700.0 2200.0 2400.0 3000.0 3200.0
-1500.0 2100.0 2500.0 2800.0 3200.0 3400.0
-1500.0 2000.0 2200.0 2400.0 3100.0 3300.0
-1400.0 1900.0 2200.0 2300.0 3000.0 3200.0
-1500.0 1800.0 2200.0 2400.0 3000.0 3200.0
-1200.0 1600.0 2300.0 2500.0 3100.0 3200.0
-1300.0 1900.0 2200.0 2700.0 3200.0 3300.0
-1100.0 1300.0 2000.0 2700.0 3100.0 3200.0
-1400.0 1500.0 2400.0 2700.0 2900.0 3300.0
-1500.0 1800.0 2500.0 2700.0 3000.0 3100.0
-1500.0 1700.0 2500.0 2800.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2400.0 2700.0 3200.0
-1300.0 1400.0 2000.0 2400.0 2600.0 3000.0
-1200.0 1300.0 2100.0 2500.0 2700.0 3100.0
-1800.0 2100.0 2400.0 2600.0 2800.0 3100.0
-1800.0 2100.0 2400.0 2600.0 2800.0 3000.0
-1900.0 2200.0 2500.0 2700.0 2900.0 3100.0
-1900.0 2300.0 2500.0 2800.0 3000.0 3100.0
-1900.0 2400.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2400.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2400.0 2600.0 2700.0 3100.0 3200.0
-1800.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1900.0 2400.0 2600.0 2800.0 3100.0 3300.0
-1900.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1700.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1700.0 2200.0 2600.0 2800.0 3200.0 3300.0
-2000.0 2200.0 2800.0 3000.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2700.0 3100.0 3300.0
-1900.0 2100.0 2400.0 2800.0 3000.0 3200.0
-1900.0 2100.0 2300.0 2800.0 3000.0 3200.0
-1800.0 2100.0 2300.0 2700.0 3000.0 3200.0
-1600.0 2000.0 2200.0 2700.0 3000.0 3100.0
-1600.0 2000.0 2200.0 2500.0 3000.0 3100.0
-1700.0 2000.0 2200.0 2700.0 3000.0 3200.0
-1700.0 2000.0 2200.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2200.0 2700.0 3100.0 3200.0
-1500.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2800.0 3000.0 3100.0
-1600.0 1900.0 2200.0 2700.0 3000.0 3100.0
-1600.0 1900.0 2300.0 2700.0 3000.0 3100.0
-1600.0 2000.0 2400.0 2800.0 3100.0 3200.0
-1700.0 2000.0 2200.0 2700.0 3100.0 3200.0
-1800.0 2000.0 2200.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2100.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2700.0 3000.0 3100.0 3300.0
-1800.0 2100.0 2700.0 3000.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2900.0 3100.0 3200.0
-1900.0 2100.0 2500.0 3000.0 3100.0 3200.0
-1700.0 2000.0 2500.0 2900.0 3100.0 3200.0
-1800.0 2100.0 2600.0 2900.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2900.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2900.0 3100.0 3200.0
-1600.0 2000.0 2300.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2100.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2200.0 2700.0 3000.0 3200.0
-2000.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1800.0 2100.0 2300.0 2700.0 3200.0 3300.0
-1700.0 2100.0 2300.0 2700.0 3000.0 3200.0
-1600.0 2200.0 2400.0 2800.0 3200.0 3300.0
-1600.0 1700.0 2000.0 2300.0 2700.0 3100.0
-1800.0 2000.0 2200.0 2400.0 2700.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2700.0 3000.0
-1500.0 1600.0 2200.0 2500.0 2800.0 3300.0
-1500.0 1600.0 2100.0 2500.0 2700.0 3000.0
-1500.0 2000.0 2300.0 2500.0 2700.0 2900.0
-1700.0 2100.0 2300.0 2600.0 2800.0 3000.0
-1700.0 2200.0 2400.0 2700.0 3000.0 3100.0
-1500.0 2200.0 2400.0 2600.0 3000.0 3200.0
-1500.0 2100.0 2400.0 2600.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2600.0 3000.0 3200.0
-1500.0 2100.0 2300.0 2600.0 3000.0 3100.0
-1600.0 2000.0 2300.0 2700.0 3000.0 3100.0
-1600.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1500.0 1800.0 2000.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2000.0 2500.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2300.0 3000.0 3100.0
-1400.0 1800.0 2100.0 2400.0 2900.0 3100.0
-1600.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1600.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2800.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2100.0 2600.0 2900.0 3100.0
-1600.0 1900.0 2100.0 2500.0 2900.0 3100.0
-1600.0 1900.0 2100.0 2600.0 2900.0 3100.0
-1600.0 1900.0 2100.0 2600.0 2800.0 3100.0
-1600.0 1800.0 2200.0 2600.0 2800.0 3000.0
-1600.0 1900.0 2200.0 2700.0 2900.0 3100.0
-1600.0 1900.0 2200.0 2600.0 2900.0 3000.0
-1900.0 2000.0 2200.0 2800.0 3000.0 3100.0
-1400.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1400.0 1900.0 2100.0 2400.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2400.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2300.0 3100.0 3300.0
-1400.0 1700.0 2100.0 2300.0 3200.0 3300.0
-1400.0 1600.0 2100.0 2300.0 3200.0 3300.0
-1300.0 1600.0 2100.0 2300.0 3200.0 3300.0
-1300.0 1600.0 2100.0 2300.0 3100.0 3300.0
-1200.0 1400.0 2000.0 2200.0 3100.0 3300.0
-1200.0 1400.0 2000.0 2600.0 3100.0 3200.0
-1200.0 1400.0 2000.0 2800.0 3100.0 3200.0
-1200.0 1400.0 2100.0 2800.0 3100.0 3200.0
-1400.0 1500.0 2200.0 2700.0 3000.0 3100.0
-1700.0 1900.0 2200.0 2500.0 2900.0 3200.0
-1400.0 1600.0 2200.0 2700.0 2900.0 3100.0
-1500.0 1600.0 1900.0 2700.0 2900.0 3000.0
-1500.0 1600.0 1900.0 2700.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2700.0 3000.0 3100.0
-1400.0 1600.0 2000.0 2600.0 2900.0 3100.0
-1300.0 1500.0 2400.0 2700.0 2900.0 3200.0
-1600.0 1800.0 2300.0 2700.0 3100.0 3400.0
-1600.0 2100.0 2400.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2700.0 3000.0 3100.0
-1600.0 1900.0 2100.0 2700.0 3000.0 3100.0
-1600.0 1800.0 2100.0 2700.0 3000.0 3100.0
-1700.0 1800.0 2300.0 2800.0 3100.0 3200.0
-1800.0 1900.0 2400.0 2900.0 3100.0 3200.0
-1500.0 1700.0 1800.0 2600.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2800.0 3000.0 3200.0
-1800.0 2100.0 2600.0 2900.0 3100.0 3300.0
-1700.0 2300.0 2500.0 2700.0 3100.0 3200.0
-2000.0 2400.0 2500.0 2700.0 3100.0 3200.0
-1900.0 2500.0 2600.0 2800.0 3100.0 3200.0
-1800.0 2400.0 2700.0 2900.0 3200.0 3300.0
-1900.0 2400.0 2600.0 2800.0 3100.0 3200.0
-1700.0 2200.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2200.0 2300.0 2600.0 3100.0 3200.0
-1800.0 2200.0 2300.0 2700.0 3100.0 3200.0
-1800.0 2200.0 2400.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2500.0 2900.0 3300.0 3400.0
-1900.0 2100.0 2400.0 2900.0 3100.0 3200.0
-1900.0 2200.0 2400.0 2800.0 3000.0 3100.0
-1800.0 2200.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2300.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2300.0 2400.0 2800.0 3100.0 3200.0
-1800.0 2100.0 2300.0 2700.0 2900.0 3100.0
-1700.0 2000.0 2500.0 2800.0 3000.0 3300.0
-1100.0 1300.0 2300.0 2600.0 2800.0 3200.0
-1400.0 1600.0 2200.0 2500.0 2800.0 3100.0
-1400.0 1600.0 2000.0 2500.0 2700.0 3000.0
-1400.0 1500.0 1900.0 2500.0 2800.0 2900.0
-1400.0 1500.0 1900.0 2600.0 2900.0 3000.0
-1400.0 1600.0 1900.0 2700.0 2900.0 3000.0
-1500.0 1600.0 2000.0 2700.0 2900.0 3100.0
-1500.0 1600.0 2000.0 2700.0 2900.0 3000.0
-1500.0 1600.0 2100.0 2800.0 3000.0 3100.0
-1600.0 1700.0 2100.0 2800.0 3000.0 3100.0
-1900.0 2200.0 2600.0 2900.0 3300.0 3400.0
-2000.0 2200.0 2600.0 3000.0 3300.0 3400.0
-2000.0 2200.0 2600.0 3000.0 3200.0 3300.0
-1800.0 2100.0 2700.0 3000.0 3400.0 3500.0
-1300.0 1600.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1700.0 2400.0 2500.0 2800.0 2900.0
-1400.0 1700.0 2400.0 2500.0 2800.0 3000.0
-1500.0 2000.0 2400.0 2500.0 3100.0 3200.0
-1400.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1400.0 1500.0 2400.0 2500.0 3100.0 3300.0
-1900.0 2200.0 2600.0 2900.0 3200.0 3400.0
-1600.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1800.0 2200.0 2800.0 3100.0 3400.0 3500.0
-1900.0 2200.0 2700.0 3000.0 3400.0 3500.0
-1900.0 2400.0 2800.0 3000.0 3200.0 3400.0
-1300.0 1900.0 2100.0 2400.0 2800.0 3000.0
-1800.0 2100.0 2300.0 2500.0 2800.0 3100.0
-1800.0 2100.0 2400.0 2600.0 2900.0 3100.0
-1600.0 1800.0 2500.0 2600.0 2900.0 3000.0
-1700.0 1900.0 2200.0 2400.0 2900.0 3200.0
-1600.0 1800.0 2000.0 2300.0 3000.0 3200.0
-1600.0 1700.0 1900.0 2300.0 3100.0 3300.0
-1400.0 1600.0 1800.0 2200.0 3200.0 3300.0
-1400.0 1600.0 1800.0 2300.0 3100.0 3200.0
-1400.0 1600.0 1800.0 2300.0 3000.0 3200.0
-1100.0 2200.0 2500.0 2600.0 2700.0 2900.0
-1200.0 1900.0 2500.0 2600.0 2800.0 3000.0
-1200.0 1800.0 2500.0 2600.0 2800.0 2900.0
-1300.0 1900.0 2500.0 2600.0 2800.0 3100.0
-1500.0 2100.0 2400.0 2500.0 2900.0 3200.0
-1400.0 2100.0 2400.0 2500.0 3000.0 3200.0
-1400.0 2000.0 2400.0 2500.0 3000.0 3300.0
-1300.0 1700.0 2300.0 2400.0 3200.0 3400.0
-1700.0 1900.0 2400.0 2500.0 3000.0 3300.0
-1900.0 2000.0 2500.0 2600.0 2900.0 3200.0
-1900.0 2100.0 2500.0 2700.0 2900.0 3200.0
-2000.0 2100.0 2600.0 2700.0 3000.0 3200.0
-2000.0 2100.0 2600.0 2700.0 3000.0 3300.0
-1900.0 2100.0 2500.0 2600.0 2900.0 3200.0
-1800.0 1900.0 2500.0 2700.0 3100.0 3400.0
-1600.0 2100.0 2400.0 2600.0 3100.0 3300.0
-1700.0 1800.0 2500.0 2600.0 2900.0 3300.0
-1500.0 1900.0 2400.0 2500.0 2800.0 3200.0
-1500.0 2000.0 2400.0 2500.0 2700.0 3000.0
-2100.0 2400.0 2700.0 3000.0 3300.0 3400.0
-1900.0 2200.0 2600.0 2800.0 3100.0 3400.0
-1800.0 2100.0 2600.0 2700.0 3100.0 3400.0
-1800.0 2000.0 2300.0 2500.0 2800.0 3200.0
-1700.0 2100.0 2200.0 2600.0 2900.0 3100.0
-1400.0 2100.0 2200.0 2600.0 2900.0 3100.0
-1500.0 1700.0 2100.0 2400.0 2800.0 3000.0
-1500.0 2000.0 2400.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2400.0 2500.0 3000.0 3200.0
-1500.0 1700.0 2400.0 2500.0 3000.0 3300.0
-1700.0 2100.0 2500.0 2600.0 3200.0 3400.0
-1800.0 2300.0 2500.0 2800.0 3200.0 3300.0
-1800.0 2300.0 2600.0 2900.0 3200.0 3300.0
-1900.0 2300.0 2600.0 3000.0 3300.0 3400.0
-1800.0 1900.0 2300.0 2400.0 2700.0 3100.0
-1600.0 1800.0 2200.0 2500.0 2900.0 3200.0
-1700.0 1900.0 2400.0 2700.0 3100.0 3400.0
-1800.0 2200.0 2400.0 2800.0 3200.0 3400.0
-1900.0 2200.0 2800.0 3000.0 3300.0 3400.0
-2300.0 2600.0 2700.0 2900.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2600.0 3100.0 3300.0
-1700.0 1900.0 2400.0 2500.0 2900.0 3100.0
-1900.0 2100.0 2400.0 2500.0 2900.0 3200.0
-2000.0 2100.0 2400.0 2500.0 2900.0 3200.0
-2000.0 2100.0 2500.0 2600.0 3000.0 3200.0
-2000.0 2200.0 2500.0 2600.0 3000.0 3300.0
-2000.0 2200.0 2600.0 2700.0 2900.0 3100.0
-1700.0 2000.0 2600.0 2700.0 3000.0 3100.0
-1900.0 2200.0 2700.0 2800.0 3100.0 3200.0
-1900.0 2400.0 2700.0 2800.0 3200.0 3300.0
-2100.0 2400.0 2600.0 2800.0 3100.0 3300.0
-2200.0 2500.0 2700.0 2900.0 3200.0 3300.0
-2000.0 2400.0 2800.0 3000.0 3300.0 3400.0
-1300.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1400.0 1800.0 2200.0 2500.0 3000.0 3200.0
-1300.0 1600.0 2100.0 2500.0 2900.0 3200.0
-1300.0 1500.0 2100.0 2400.0 2900.0 3200.0
-1500.0 1700.0 1800.0 2200.0 2600.0 3200.0
-1500.0 1900.0 2200.0 2400.0 2800.0 3100.0
-1300.0 1600.0 2200.0 2300.0 3200.0 3400.0
-1300.0 1700.0 2200.0 2400.0 3100.0 3300.0
-1500.0 2100.0 2300.0 2700.0 3200.0 3400.0
-2000.0 2300.0 2800.0 3000.0 3300.0 3400.0
-1800.0 2300.0 2800.0 3000.0 3400.0 3500.0
-1800.0 2300.0 2700.0 3000.0 3300.0 3500.0
-2000.0 2500.0 2800.0 3100.0 3400.0 3500.0
-2000.0 2500.0 2800.0 3100.0 3300.0 3400.0
-2000.0 2400.0 2800.0 3100.0 3300.0 3400.0
-2100.0 2500.0 2800.0 2900.0 3300.0 3400.0
-2000.0 2300.0 2800.0 2900.0 3200.0 3300.0
-2000.0 2300.0 2700.0 2800.0 3100.0 3200.0
-1900.0 2200.0 2500.0 2700.0 3100.0 3200.0
-1600.0 2200.0 2400.0 2600.0 2900.0 3100.0
-1500.0 2200.0 2400.0 2600.0 2900.0 3200.0
-1400.0 1900.0 2200.0 2400.0 2700.0 3000.0
-1400.0 1900.0 2300.0 2500.0 2800.0 3100.0
-1600.0 1900.0 2400.0 2500.0 2800.0 3000.0
-1600.0 1800.0 2400.0 2600.0 2900.0 3000.0
-1600.0 1900.0 2500.0 2600.0 2900.0 3100.0
-1600.0 1900.0 2400.0 2500.0 3000.0 3100.0
-1600.0 2000.0 2400.0 2600.0 3000.0 3200.0
-1400.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1900.0 2200.0 2500.0 3000.0 3100.0
-1400.0 1800.0 2000.0 2400.0 3000.0 3100.0
-1400.0 1700.0 1900.0 2400.0 2800.0 2900.0
-1700.0 2100.0 2400.0 2600.0 3000.0 3300.0
-1900.0 2100.0 2500.0 2600.0 3000.0 3300.0
-1900.0 2100.0 2400.0 2500.0 2800.0 3200.0
-1800.0 2000.0 2300.0 2400.0 2900.0 3300.0
-1600.0 1800.0 2000.0 2300.0 2700.0 3200.0
-1300.0 1500.0 2100.0 2500.0 3000.0 3200.0
-1400.0 2000.0 2200.0 2400.0 2900.0 3200.0
-1800.0 1900.0 2300.0 2600.0 3000.0 3300.0
-1900.0 2000.0 2300.0 2500.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2400.0 2800.0 3100.0
-1700.0 2000.0 2400.0 2500.0 2800.0 3000.0
-1600.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1900.0 2200.0 2400.0 2700.0 3000.0 3200.0
-1900.0 2100.0 2300.0 2500.0 2800.0 3000.0
-1700.0 2000.0 2300.0 2500.0 2900.0 3100.0
-1700.0 2100.0 2300.0 2500.0 2900.0 3100.0
-1500.0 1700.0 1900.0 2500.0 2800.0 3100.0
-1600.0 1800.0 2000.0 2500.0 2700.0 3000.0
-1700.0 1800.0 2100.0 2500.0 2700.0 2900.0
-2000.0 2300.0 2700.0 2900.0 3100.0 3200.0
-2000.0 2300.0 2600.0 2900.0 3100.0 3200.0
-1600.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2500.0 2800.0 3000.0
-1400.0 2000.0 2400.0 2500.0 2900.0 3100.0
-1500.0 2000.0 2400.0 2500.0 3100.0 3300.0
-1700.0 2100.0 2500.0 2800.0 3300.0 3500.0
-1500.0 1600.0 2300.0 2500.0 2800.0 3100.0
-1500.0 1800.0 2300.0 2500.0 2700.0 2900.0
-1400.0 2000.0 2300.0 2400.0 2700.0 3100.0
-1400.0 2100.0 2400.0 2500.0 2800.0 3200.0
-1400.0 2100.0 2400.0 2500.0 2900.0 3200.0
-1800.0 2000.0 2300.0 2400.0 3000.0 3300.0
-1900.0 2200.0 2500.0 2600.0 2900.0 3100.0
-1800.0 2200.0 2600.0 2900.0 3100.0 3200.0
-2100.0 2500.0 2700.0 2800.0 3200.0 3300.0
-1900.0 2400.0 2600.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2700.0 3100.0 3200.0
-1800.0 2000.0 2500.0 2600.0 2900.0 3100.0
-1800.0 2100.0 2500.0 2600.0 2900.0 3100.0
-1900.0 2100.0 2500.0 2600.0 2900.0 3100.0
-1900.0 2100.0 2400.0 2500.0 2900.0 3100.0
-1900.0 2200.0 2300.0 2500.0 2900.0 3200.0
-1800.0 2200.0 2400.0 2600.0 3000.0 3100.0
-1800.0 2200.0 2400.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2300.0 2800.0 3200.0 3400.0
-1600.0 2100.0 2300.0 2700.0 3200.0 3400.0
-1800.0 2200.0 2600.0 2700.0 3000.0 3200.0
-1900.0 2200.0 2600.0 3000.0 3200.0 3400.0
-2000.0 2400.0 2900.0 3000.0 3300.0 3500.0
-2100.0 2500.0 2800.0 2900.0 3400.0 3500.0
-2100.0 2600.0 2800.0 3000.0 3300.0 3400.0
-2300.0 2600.0 2800.0 3000.0 3200.0 3300.0
-2200.0 2500.0 2600.0 2800.0 3200.0 3300.0
-2200.0 2400.0 2600.0 2700.0 3200.0 3300.0
-2100.0 2300.0 2500.0 2700.0 3100.0 3300.0
-2100.0 2300.0 2500.0 2800.0 3000.0 3200.0
-1900.0 2100.0 2200.0 2500.0 3000.0 3200.0
-1700.0 2000.0 2400.0 2600.0 3000.0 3200.0
-1900.0 2200.0 2700.0 3000.0 3200.0 3300.0
-2000.0 2300.0 2900.0 3000.0 3300.0 3400.0
-2100.0 2400.0 2800.0 3000.0 3300.0 3400.0
-2000.0 2500.0 2800.0 2900.0 3300.0 3400.0
-2100.0 2600.0 2800.0 2900.0 3300.0 3400.0
-1800.0 2100.0 2700.0 2900.0 3200.0 3300.0
-1800.0 2200.0 2600.0 2800.0 3100.0 3300.0
-1700.0 2000.0 2400.0 2500.0 2700.0 2900.0
-1500.0 1800.0 2400.0 2600.0 2900.0 3200.0
-1500.0 2000.0 2400.0 2500.0 2800.0 3000.0
-1500.0 1900.0 2400.0 2500.0 2700.0 3000.0
-1500.0 2000.0 2400.0 2600.0 2800.0 3100.0
-1500.0 1800.0 2500.0 2600.0 3000.0 3300.0
-1500.0 2100.0 2400.0 2500.0 3000.0 3300.0
-1600.0 2100.0 2400.0 2600.0 3000.0 3300.0
-1600.0 2000.0 2400.0 2600.0 2800.0 3100.0
-1900.0 2300.0 2700.0 2900.0 3300.0 3400.0
-1800.0 2300.0 2700.0 3100.0 3300.0 3400.0
-2000.0 2100.0 2300.0 2700.0 3000.0 3300.0
-2100.0 2300.0 2600.0 2700.0 3100.0 3300.0
-2100.0 2300.0 2500.0 2700.0 3200.0 3300.0
-2100.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1600.0 2100.0 2400.0 2600.0 3100.0 3200.0
-1500.0 2100.0 2500.0 2600.0 3000.0 3100.0
-1600.0 2100.0 2300.0 2600.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2600.0 3000.0 3300.0
-1600.0 1800.0 2500.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2500.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2400.0 2600.0 2900.0 3100.0
-1700.0 2100.0 2500.0 2800.0 3000.0 3200.0
-1600.0 1800.0 2300.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2200.0 2700.0 3100.0 3300.0
-1600.0 1700.0 2100.0 2700.0 3100.0 3200.0
-1600.0 1700.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2200.0 2500.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2300.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2300.0 3200.0 3400.0
-1300.0 1600.0 2100.0 2200.0 3200.0 3300.0
-1300.0 1700.0 2200.0 2400.0 3200.0 3400.0
-1300.0 1600.0 2200.0 2300.0 3100.0 3400.0
-1400.0 1600.0 2200.0 2300.0 2900.0 3300.0
-1400.0 1600.0 2200.0 2400.0 2900.0 3300.0
-1300.0 1500.0 2200.0 2400.0 3000.0 3300.0
-1300.0 1500.0 2200.0 2400.0 3100.0 3300.0
-1200.0 1500.0 2200.0 2400.0 3100.0 3300.0
-1200.0 1700.0 2300.0 2500.0 3200.0 3300.0
-1800.0 2000.0 2300.0 2400.0 3200.0 3400.0
-2000.0 2100.0 2400.0 2500.0 3000.0 3400.0
-2000.0 2200.0 2500.0 2700.0 3200.0 3400.0
-2000.0 2500.0 2700.0 2900.0 3400.0 3500.0
-1700.0 2000.0 2500.0 2600.0 3000.0 3300.0
-1600.0 1700.0 2100.0 2400.0 2800.0 3200.0
-1400.0 1600.0 2200.0 2300.0 3000.0 3400.0
-1300.0 1500.0 2200.0 2300.0 2800.0 3200.0
-1500.0 1700.0 2400.0 2500.0 3000.0 3200.0
-1600.0 1700.0 2400.0 2500.0 3000.0 3300.0
-1700.0 1800.0 2400.0 2500.0 2900.0 3200.0
-1800.0 1900.0 2400.0 2500.0 2900.0 3100.0
-1700.0 1900.0 2400.0 2500.0 2900.0 3200.0
-1500.0 1700.0 2300.0 2400.0 3100.0 3400.0
-1400.0 1600.0 2200.0 2400.0 2800.0 3100.0
-1400.0 1600.0 2200.0 2400.0 2800.0 3200.0
-1400.0 1600.0 2100.0 2300.0 2800.0 3200.0
-1500.0 1600.0 2100.0 2400.0 2700.0 3100.0
-1600.0 1700.0 2200.0 2400.0 2800.0 3100.0
-1600.0 2200.0 2500.0 2700.0 3300.0 3400.0
-1500.0 2000.0 2500.0 2900.0 3300.0 3400.0
-1400.0 2000.0 2400.0 2800.0 3200.0 3400.0
-1400.0 1700.0 2300.0 2600.0 3000.0 3200.0
-1300.0 1600.0 2300.0 2400.0 3100.0 3200.0
-1300.0 1600.0 2300.0 2400.0 3000.0 3200.0
-1200.0 1500.0 2200.0 2300.0 3000.0 3300.0
-1300.0 1700.0 2300.0 2400.0 3100.0 3300.0
-1300.0 1600.0 2300.0 2400.0 3000.0 3300.0
-1300.0 1700.0 2300.0 2400.0 3000.0 3300.0
-1300.0 1600.0 2200.0 2300.0 3000.0 3300.0
-1300.0 1600.0 2200.0 2300.0 3100.0 3300.0
-1300.0 1400.0 2200.0 2300.0 3000.0 3300.0
-1300.0 1600.0 2200.0 2400.0 3100.0 3300.0
-1400.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1400.0 1600.0 2300.0 2400.0 3200.0 3400.0
-1400.0 1600.0 2300.0 2400.0 3100.0 3400.0
-1400.0 1600.0 2300.0 2400.0 3000.0 3400.0
-1400.0 1500.0 2400.0 2500.0 3000.0 3300.0
-1400.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2300.0 3200.0 3400.0
-1400.0 1600.0 2100.0 2400.0 3100.0 3400.0
-1600.0 1900.0 2200.0 2500.0 2800.0 3100.0
-1500.0 1800.0 2200.0 2300.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2400.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2400.0 2900.0 3200.0
-1800.0 1900.0 2400.0 2500.0 2800.0 3100.0
-2000.0 2100.0 2500.0 2600.0 3100.0 3300.0
-2000.0 2100.0 2400.0 2500.0 3000.0 3300.0
-1800.0 2100.0 2400.0 2600.0 3200.0 3400.0
-1600.0 1900.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1700.0 2200.0 2300.0 3000.0 3300.0
-1400.0 1700.0 2100.0 2200.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2300.0 3100.0 3200.0
-1900.0 2200.0 2400.0 2500.0 2900.0 3100.0
-1400.0 1600.0 2200.0 2600.0 3100.0 3300.0
-1400.0 1700.0 2300.0 2700.0 3100.0 3300.0
-1500.0 1900.0 2300.0 2600.0 3200.0 3400.0
-1200.0 1600.0 2400.0 2500.0 3100.0 3200.0
-1200.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1700.0 1800.0 2100.0 2300.0 2900.0 3000.0
-1800.0 1900.0 2200.0 2300.0 2900.0 3000.0
-1900.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2300.0 2600.0 3200.0 3300.0
-1800.0 2100.0 2500.0 2600.0 3300.0 3400.0
-1700.0 2300.0 2500.0 2900.0 3200.0 3300.0
-1900.0 2400.0 2800.0 3000.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2500.0 3000.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3100.0 3400.0
-1600.0 2000.0 2200.0 2600.0 3200.0 3300.0
-1500.0 2100.0 2500.0 2800.0 3200.0 3300.0
-1500.0 2000.0 2500.0 2800.0 3300.0 3400.0
-1800.0 2000.0 2500.0 2900.0 3300.0 3400.0
-1500.0 2100.0 2400.0 2800.0 3300.0 3400.0
-1300.0 2000.0 2400.0 2500.0 3300.0 3400.0
-1600.0 1700.0 2200.0 2400.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2300.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2400.0 2900.0 3300.0
-1500.0 1700.0 2300.0 2400.0 2900.0 3100.0
-1400.0 1800.0 2500.0 2600.0 3000.0 3200.0
-1300.0 1600.0 2400.0 2500.0 3100.0 3300.0
-1300.0 1500.0 2400.0 2500.0 3000.0 3400.0
-1300.0 1500.0 2500.0 2600.0 3000.0 3300.0
-1300.0 1500.0 2400.0 2500.0 2800.0 3300.0
-1400.0 1500.0 2500.0 2600.0 2900.0 3300.0
-1800.0 2200.0 2700.0 2900.0 3200.0 3300.0
-1600.0 1700.0 2400.0 2500.0 2900.0 3300.0
-1600.0 1700.0 2300.0 2500.0 2800.0 3300.0
-1700.0 1800.0 2200.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2300.0 3100.0 3200.0
-1600.0 1800.0 2200.0 2400.0 3100.0 3200.0
-1500.0 1800.0 2100.0 2300.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2400.0 2900.0 3200.0
-1500.0 2000.0 2200.0 2400.0 2700.0 3200.0
-1600.0 1900.0 2200.0 2400.0 2800.0 3200.0
-1700.0 1800.0 2400.0 2500.0 3300.0 3500.0
-1500.0 1800.0 2300.0 2600.0 3200.0 3400.0
-1300.0 1600.0 2200.0 2400.0 3200.0 3400.0
-1200.0 1600.0 2200.0 2400.0 3100.0 3300.0
-1100.0 1500.0 2100.0 2300.0 3100.0 3200.0
-1400.0 1700.0 2100.0 2400.0 3100.0 3200.0
-1500.0 1600.0 2100.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2100.0 2300.0 2900.0 3000.0
-1600.0 1700.0 2100.0 2400.0 2900.0 3100.0
-1600.0 1700.0 2100.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2100.0 2300.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2300.0 3200.0 3300.0
-1700.0 1900.0 2100.0 2300.0 3200.0 3400.0
-1800.0 1900.0 2100.0 2300.0 3200.0 3400.0
-1700.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2300.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2300.0 2700.0 3100.0
-1600.0 1700.0 2100.0 2300.0 2500.0 3000.0
-1500.0 1800.0 2300.0 2500.0 2900.0 3100.0
-1500.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1500.0 2000.0 2500.0 2900.0 3200.0 3300.0
-1700.0 2400.0 2900.0 3100.0 3300.0 3400.0
-1700.0 2100.0 2400.0 2800.0 3300.0 3400.0
-1800.0 2400.0 2600.0 2800.0 3100.0 3300.0
-1200.0 1600.0 2400.0 2500.0 3100.0 3400.0
-1300.0 1500.0 2400.0 2500.0 3100.0 3400.0
-1400.0 1500.0 2400.0 2500.0 3000.0 3200.0
-1400.0 1600.0 2400.0 2500.0 3000.0 3200.0
-1800.0 2100.0 2500.0 2600.0 3000.0 3200.0
-1700.0 2200.0 2500.0 2800.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2500.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2500.0 3000.0 3200.0
-1400.0 2000.0 2400.0 2500.0 3200.0 3400.0
-1800.0 2100.0 2400.0 2500.0 3200.0 3400.0
-1800.0 1900.0 2200.0 2400.0 3100.0 3300.0
-1700.0 2000.0 2400.0 2600.0 3200.0 3400.0
-1600.0 1700.0 2300.0 2400.0 3100.0 3400.0
-1600.0 1700.0 2300.0 2400.0 3200.0 3400.0
-1200.0 1700.0 2400.0 2500.0 3200.0 3400.0
-1700.0 2200.0 2800.0 3100.0 3400.0 3500.0
-1600.0 2000.0 2400.0 2800.0 3300.0 3400.0
-1300.0 1600.0 2100.0 2300.0 3100.0 3200.0
-1300.0 1600.0 2100.0 2200.0 3100.0 3200.0
-1300.0 1500.0 1800.0 2000.0 3000.0 3100.0
-1300.0 1500.0 1800.0 1900.0 3100.0 3200.0
-1400.0 1500.0 1700.0 1800.0 3100.0 3200.0
-1400.0 1600.0 1700.0 2000.0 2800.0 2900.0
-1500.0 1700.0 2200.0 2400.0 2800.0 3200.0
-1500.0 1700.0 2200.0 2300.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2200.0 3100.0 3200.0
-1300.0 1500.0 1800.0 2200.0 3100.0 3200.0
-1400.0 1800.0 2300.0 2500.0 2900.0 3200.0
-1400.0 1800.0 2300.0 2400.0 2700.0 3200.0
-1500.0 1600.0 2000.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2000.0 2400.0 3100.0 3300.0
-1500.0 1700.0 2200.0 2500.0 2800.0 3200.0
-1700.0 1800.0 2200.0 2500.0 2800.0 3100.0
-1600.0 1700.0 2200.0 2500.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2500.0 2900.0 3100.0
-1900.0 2000.0 2400.0 2600.0 3000.0 3200.0
-1500.0 1700.0 2200.0 2500.0 3000.0 3300.0
-1300.0 1500.0 2200.0 2400.0 3000.0 3400.0
-1200.0 1400.0 2200.0 2500.0 3200.0 3400.0
-1300.0 1600.0 2000.0 2200.0 3100.0 3200.0
-1400.0 1600.0 1900.0 2000.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2400.0 2900.0 3100.0
-1500.0 1600.0 2200.0 2300.0 2800.0 3100.0
-1400.0 1600.0 2200.0 2300.0 2800.0 3100.0
-1300.0 1600.0 2300.0 2400.0 2900.0 3300.0
-1700.0 2200.0 2800.0 3100.0 3300.0 3400.0
-1700.0 2200.0 2600.0 3000.0 3300.0 3500.0
-1100.0 1500.0 2400.0 2500.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2500.0 2700.0 3100.0
-1900.0 2100.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2400.0 3000.0 3300.0
-1500.0 2100.0 2500.0 2800.0 3300.0 3400.0
-1600.0 2100.0 2500.0 2900.0 3300.0 3400.0
-1200.0 1600.0 2400.0 2500.0 2900.0 3400.0
-1300.0 1500.0 2300.0 2500.0 2700.0 3200.0
-1400.0 1600.0 2500.0 2600.0 3000.0 3300.0
-1300.0 1600.0 2400.0 2500.0 3100.0 3400.0
-1300.0 1800.0 2300.0 2500.0 3100.0 3300.0
-1300.0 1600.0 2300.0 2400.0 3100.0 3300.0
-1200.0 1600.0 2300.0 2400.0 3000.0 3300.0
-1100.0 1700.0 2200.0 2500.0 3100.0 3300.0
-1500.0 1600.0 2200.0 2600.0 3000.0 3300.0
-1500.0 1600.0 2200.0 2600.0 2900.0 3300.0
-1500.0 1700.0 2400.0 2600.0 2900.0 3300.0
-1500.0 1600.0 2300.0 2500.0 2900.0 3200.0
-1700.0 2100.0 2600.0 3000.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2500.0 3100.0 3500.0
-1500.0 1600.0 2400.0 2500.0 3100.0 3400.0
-1500.0 1600.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1500.0 1600.0 2000.0 3200.0 3400.0
-1900.0 2000.0 2300.0 2500.0 2900.0 3200.0
-2000.0 2500.0 2700.0 2800.0 3200.0 3300.0
-2000.0 2200.0 2500.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2400.0 2800.0 2900.0 3100.0
-1700.0 1800.0 2400.0 2800.0 3000.0 3100.0
-1700.0 1800.0 2300.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2800.0 3100.0 3200.0
-1400.0 1900.0 2200.0 2400.0 3000.0 3200.0
-2100.0 2300.0 2800.0 3000.0 3200.0 3300.0
-2100.0 2400.0 2900.0 3000.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2600.0 3000.0 3100.0
-1700.0 1800.0 2300.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2100.0 2600.0 2900.0 3100.0
-1700.0 1800.0 2100.0 2700.0 2900.0 3100.0
-1800.0 1900.0 2200.0 2700.0 3000.0 3100.0
-1900.0 2100.0 2300.0 2800.0 3100.0 3200.0
-2000.0 2400.0 2600.0 2900.0 3200.0 3300.0
-1300.0 1700.0 2400.0 2700.0 3100.0 3200.0
-1200.0 1500.0 2300.0 2400.0 3000.0 3200.0
-1100.0 1500.0 2300.0 2500.0 3100.0 3200.0
-2000.0 2300.0 2800.0 3000.0 3200.0 3300.0
-2100.0 2400.0 2900.0 3000.0 3300.0 3400.0
-2200.0 2500.0 2900.0 3100.0 3300.0 3400.0
-2300.0 2500.0 2900.0 3100.0 3300.0 3400.0
-2200.0 2500.0 2900.0 3100.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3200.0 3400.0
-1500.0 1800.0 2000.0 2300.0 3200.0 3400.0
-1700.0 1800.0 2000.0 2100.0 3200.0 3400.0
-1800.0 1900.0 2200.0 2300.0 3200.0 3400.0
-1900.0 2000.0 2500.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2400.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2500.0 2800.0 3200.0 3400.0
-1800.0 2300.0 2600.0 2800.0 3200.0 3400.0
-1500.0 1900.0 2600.0 2800.0 3100.0 3300.0
-1400.0 1500.0 2400.0 2700.0 2800.0 3100.0
-1400.0 1500.0 2300.0 2700.0 2800.0 3100.0
-1400.0 1500.0 2400.0 2800.0 2900.0 3100.0
-1300.0 1500.0 2300.0 2900.0 3100.0 3200.0
-1300.0 1500.0 2200.0 2900.0 3100.0 3300.0
-1500.0 1600.0 2000.0 2700.0 3200.0 3300.0
-1500.0 1600.0 2000.0 2400.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2400.0 2900.0 3200.0
-1700.0 1900.0 2100.0 2400.0 2900.0 3200.0
-2000.0 2400.0 2700.0 2900.0 3100.0 3200.0
-1900.0 2000.0 2400.0 2800.0 3100.0 3200.0
-1700.0 1900.0 2500.0 2800.0 3000.0 3200.0
-1100.0 1400.0 2500.0 2900.0 3100.0 3200.0
-2200.0 2500.0 2900.0 3000.0 3200.0 3400.0
-2100.0 2500.0 2900.0 3000.0 3200.0 3400.0
-1900.0 2100.0 2500.0 2900.0 3000.0 3200.0
-1900.0 2000.0 2400.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2800.0 3000.0 3100.0
-1700.0 1900.0 2200.0 2800.0 3000.0 3100.0
-1600.0 1900.0 2000.0 2500.0 2800.0 3000.0
-1300.0 1900.0 2100.0 2500.0 2900.0 3100.0
-1500.0 1900.0 2100.0 2600.0 2900.0 3100.0
-1100.0 1400.0 2500.0 2700.0 3000.0 3300.0
-1300.0 1600.0 2500.0 2700.0 2900.0 3300.0
-1500.0 1700.0 2500.0 2700.0 2900.0 3200.0
-1700.0 1900.0 2600.0 2700.0 3000.0 3200.0
-1800.0 1900.0 2500.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2500.0 2800.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2800.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2800.0 3000.0 3100.0
-1900.0 2100.0 2500.0 2900.0 3100.0 3200.0
-1800.0 2100.0 2500.0 2800.0 3000.0 3200.0
-1500.0 1700.0 2100.0 2600.0 2900.0 3100.0
-1500.0 1700.0 2400.0 2800.0 3000.0 3200.0
-1500.0 1700.0 2400.0 2900.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2600.0 3000.0 3300.0
-1200.0 1700.0 2500.0 2700.0 3000.0 3300.0
-1200.0 1500.0 2600.0 2700.0 3000.0 3300.0
-1300.0 1600.0 2600.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2400.0 2600.0 2900.0 3200.0
-1700.0 1800.0 2500.0 2600.0 2800.0 3200.0
-1900.0 2000.0 2400.0 2700.0 2800.0 3100.0
-2000.0 2100.0 2500.0 2700.0 2800.0 3100.0
-1800.0 1900.0 2400.0 2700.0 2800.0 3100.0
-1700.0 1800.0 2400.0 2700.0 2800.0 3100.0
-1600.0 1700.0 2400.0 2700.0 2800.0 3100.0
-1500.0 1600.0 2400.0 2700.0 2800.0 3200.0
-1400.0 1600.0 2300.0 2600.0 2900.0 3200.0
-1300.0 1500.0 2400.0 2600.0 2800.0 3200.0
-1200.0 1400.0 2500.0 2600.0 2900.0 3200.0
-1300.0 1400.0 2200.0 2600.0 2800.0 3100.0
-1900.0 2100.0 2600.0 2800.0 3200.0 3400.0
-1900.0 2000.0 2500.0 2800.0 3200.0 3300.0
-1800.0 2100.0 2500.0 2700.0 2900.0 3100.0
-1600.0 2000.0 2400.0 2800.0 3000.0 3200.0
-1600.0 1900.0 2400.0 2800.0 3000.0 3300.0
-1800.0 1900.0 2300.0 2700.0 3000.0 3100.0
-1800.0 1900.0 2300.0 2700.0 2900.0 3000.0
-1700.0 1900.0 2200.0 2500.0 2900.0 3000.0
-1400.0 1900.0 2200.0 2500.0 2900.0 3100.0
-1500.0 1800.0 2200.0 2400.0 2900.0 3100.0
-1600.0 1900.0 2300.0 2500.0 3000.0 3200.0
-1800.0 2100.0 2300.0 2700.0 3100.0 3200.0
-1900.0 2300.0 2600.0 2800.0 3000.0 3200.0
-1500.0 1700.0 2300.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2300.0 2800.0 3000.0 3100.0
-2000.0 2100.0 2400.0 2800.0 3100.0 3200.0
-2100.0 2400.0 2500.0 2800.0 3100.0 3200.0
-1900.0 2100.0 2500.0 2800.0 3000.0 3200.0
-1700.0 1800.0 2400.0 2800.0 3000.0 3200.0
-1300.0 1500.0 2200.0 2800.0 3100.0 3200.0
-1400.0 1500.0 2400.0 2800.0 2900.0 3200.0
-1400.0 1600.0 2500.0 2700.0 3000.0 3200.0
-1500.0 1600.0 2400.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2400.0 2700.0 2900.0 3200.0
-1400.0 1600.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1600.0 2600.0 2700.0 3100.0 3300.0
-1000.0 1800.0 2700.0 2800.0 3200.0 3400.0
-1100.0 1700.0 2400.0 2500.0 3200.0 3400.0
-1600.0 1800.0 2000.0 2200.0 3200.0 3400.0
-1800.0 1900.0 2200.0 2400.0 3000.0 3300.0
-1800.0 1900.0 2200.0 2600.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2700.0 3000.0 3200.0
-1300.0 1500.0 2500.0 2800.0 3000.0 3300.0
-1700.0 2000.0 2500.0 2700.0 2900.0 3200.0
-2000.0 2200.0 2500.0 2700.0 2900.0 3200.0
-2200.0 2600.0 2700.0 2800.0 3100.0 3300.0
-2100.0 2600.0 2700.0 2900.0 3300.0 3400.0
-2200.0 2300.0 2600.0 2800.0 3000.0 3200.0
-1600.0 2200.0 2500.0 2700.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2700.0 3100.0 3200.0
-1800.0 2000.0 2500.0 2900.0 3100.0 3200.0
-2200.0 2400.0 2600.0 2900.0 3100.0 3200.0
-2200.0 2500.0 2600.0 2800.0 3100.0 3200.0
-2300.0 2500.0 2600.0 2800.0 3200.0 3300.0
-2200.0 2500.0 2700.0 2800.0 3200.0 3300.0
-2200.0 2500.0 2700.0 2800.0 3100.0 3200.0
-2200.0 2400.0 2600.0 2800.0 3100.0 3200.0
-2000.0 2200.0 2400.0 2800.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2800.0 3000.0 3200.0
-1700.0 2100.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2200.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2000.0 2200.0 2600.0 3000.0 3100.0
-1600.0 1900.0 2300.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2300.0 2500.0 2800.0 2900.0
-1700.0 2100.0 2400.0 2700.0 3100.0 3200.0
-1400.0 1600.0 1700.0 2100.0 3200.0 3400.0
-1500.0 1800.0 2200.0 2300.0 3200.0 3500.0
-1300.0 1700.0 2300.0 2500.0 2900.0 3200.0
-1300.0 1500.0 2100.0 2500.0 2900.0 3200.0
-1700.0 2000.0 2200.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2500.0 2700.0 2900.0 3200.0
-1700.0 1900.0 2400.0 2700.0 2900.0 3200.0
-1600.0 1700.0 2300.0 2600.0 2900.0 3200.0
-1400.0 1600.0 2300.0 2400.0 2800.0 3300.0
-1600.0 1700.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1800.0 2400.0 2700.0 2900.0 3300.0
-1600.0 1800.0 2400.0 2800.0 3000.0 3200.0
-1600.0 1700.0 2100.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2200.0 2500.0 2700.0 3200.0
-1700.0 2000.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1700.0 2400.0 2700.0 3000.0 3200.0
-1500.0 1600.0 2300.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2300.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2200.0 2800.0 3100.0 3200.0
-1500.0 1600.0 2200.0 2800.0 3100.0 3200.0
-1500.0 1600.0 2100.0 2800.0 3100.0 3200.0
-1500.0 1600.0 2000.0 2600.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2800.0 3100.0 3200.0
-1700.0 1900.0 2500.0 2900.0 3100.0 3300.0
-2300.0 2400.0 2600.0 2900.0 3200.0 3300.0
-2200.0 2300.0 2500.0 2800.0 3100.0 3300.0
-2000.0 2200.0 2400.0 2600.0 3000.0 3300.0
-1300.0 1800.0 2200.0 2400.0 3000.0 3300.0
-1500.0 1800.0 2300.0 2400.0 3100.0 3400.0
-1800.0 2100.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2100.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1900.0 2500.0 2600.0 3000.0 3300.0
-1600.0 1800.0 2500.0 2600.0 3000.0 3400.0
-1600.0 1900.0 2400.0 2500.0 3100.0 3400.0
-1600.0 1800.0 2300.0 2400.0 3100.0 3400.0
-1600.0 1800.0 2200.0 2300.0 3100.0 3400.0
-1600.0 1800.0 2000.0 2200.0 3100.0 3400.0
-1700.0 1800.0 2300.0 2600.0 3100.0 3200.0
-2200.0 2300.0 2500.0 2800.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2500.0 3000.0 3200.0
-1300.0 1700.0 2300.0 2400.0 3000.0 3200.0
-1400.0 1800.0 2300.0 2400.0 3000.0 3100.0
-1200.0 1500.0 2600.0 2800.0 3000.0 3300.0
-2200.0 2400.0 2600.0 2800.0 3000.0 3200.0
-2000.0 2500.0 2600.0 2800.0 3100.0 3200.0
-1900.0 2400.0 2600.0 2700.0 3100.0 3200.0
-2000.0 2300.0 2400.0 2600.0 3000.0 3200.0
-1900.0 2200.0 2400.0 2800.0 3100.0 3300.0
-1800.0 2100.0 2300.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2400.0 2600.0 3100.0 3200.0
-2000.0 2300.0 2500.0 2600.0 2900.0 3200.0
-1600.0 2100.0 2400.0 2600.0 2900.0 3300.0
-1400.0 1700.0 2400.0 2800.0 3000.0 3200.0
-1100.0 1700.0 2900.0 3000.0 3200.0 3400.0
-1100.0 1700.0 2300.0 2900.0 3300.0 3400.0
-1100.0 1500.0 2300.0 2400.0 3300.0 3500.0
-1400.0 1700.0 2200.0 2400.0 3000.0 3300.0
-1600.0 1800.0 2300.0 2600.0 2900.0 3300.0
-2000.0 2100.0 2400.0 2800.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2700.0 3000.0 3100.0
-1600.0 1900.0 2100.0 2600.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2600.0 3000.0 3300.0
-1500.0 1700.0 1900.0 2200.0 3200.0 3400.0
-1400.0 1600.0 1800.0 2100.0 3200.0 3400.0
-1300.0 1500.0 1600.0 2200.0 3300.0 3400.0
-1800.0 2000.0 2200.0 2400.0 3000.0 3300.0
-2100.0 2500.0 2700.0 2800.0 3100.0 3200.0
-2100.0 2400.0 2600.0 2800.0 3100.0 3200.0
-1300.0 1800.0 2200.0 2600.0 3000.0 3200.0
-1800.0 2200.0 2400.0 2800.0 3200.0 3300.0
-1700.0 2100.0 2300.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2200.0 3000.0 3300.0
-1500.0 1700.0 2100.0 2200.0 3100.0 3400.0
-1500.0 1700.0 2000.0 2200.0 3100.0 3400.0
-1700.0 1800.0 2100.0 2300.0 3100.0 3400.0
-1900.0 2000.0 2400.0 2600.0 3000.0 3100.0
-2100.0 2500.0 2800.0 2900.0 3200.0 3300.0
-1800.0 2200.0 2400.0 2700.0 3100.0 3200.0
-1700.0 2100.0 2300.0 2600.0 3000.0 3100.0
-1900.0 2100.0 2300.0 2700.0 3000.0 3100.0
-2000.0 2200.0 2500.0 2700.0 2900.0 3100.0
-1400.0 1700.0 2000.0 2600.0 3200.0 3300.0
-1400.0 1700.0 2200.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2900.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2600.0 3000.0 3100.0
-1600.0 1900.0 2200.0 2500.0 2900.0 3000.0
-1600.0 1800.0 2000.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2300.0 2700.0 2900.0 3100.0
-1500.0 1900.0 2200.0 2500.0 2600.0 3200.0
-1800.0 1900.0 2400.0 2800.0 2900.0 3200.0
-2000.0 2100.0 2400.0 2800.0 3000.0 3200.0
-2000.0 2300.0 2400.0 2700.0 3200.0 3300.0
-1900.0 2200.0 2400.0 2800.0 3200.0 3300.0
-1300.0 1800.0 2200.0 2600.0 3100.0 3300.0
-2000.0 2400.0 2800.0 3000.0 3200.0 3400.0
-2200.0 2300.0 2800.0 3000.0 3200.0 3300.0
-2100.0 2300.0 2600.0 3000.0 3200.0 3300.0
-2100.0 2200.0 2600.0 2900.0 3100.0 3200.0
-2100.0 2200.0 2500.0 2900.0 3100.0 3200.0
-1800.0 2100.0 2300.0 2800.0 3100.0 3200.0
-1800.0 2000.0 2200.0 2600.0 3100.0 3200.0
-2000.0 2100.0 2400.0 2900.0 3100.0 3200.0
-2200.0 2500.0 2800.0 3000.0 3200.0 3300.0
-2100.0 2400.0 2800.0 3000.0 3200.0 3400.0
-2000.0 2100.0 2500.0 2800.0 3100.0 3200.0
-2000.0 2100.0 2500.0 2900.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2800.0 2900.0 3100.0
-1600.0 1900.0 2100.0 2500.0 2800.0 3000.0
-1700.0 1900.0 2200.0 2500.0 2800.0 3000.0
-2100.0 2400.0 2700.0 3000.0 3200.0 3400.0
-1700.0 1800.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1700.0 2300.0 2800.0 3000.0 3200.0
-1600.0 1900.0 2300.0 2800.0 3100.0 3300.0
-1400.0 1600.0 1700.0 2100.0 3300.0 3400.0
-1600.0 1700.0 2000.0 2300.0 3200.0 3400.0
-1600.0 1800.0 2300.0 2700.0 2900.0 3200.0
-1600.0 1700.0 2300.0 2800.0 2900.0 3200.0
-1600.0 1800.0 2300.0 2800.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2800.0 3000.0 3100.0
-1800.0 1900.0 2300.0 2600.0 2900.0 3300.0
-1700.0 1800.0 2300.0 2500.0 3000.0 3400.0
-1600.0 1700.0 2200.0 2400.0 3000.0 3400.0
-1600.0 1700.0 2200.0 2300.0 3000.0 3400.0
-2000.0 2100.0 2300.0 2400.0 3000.0 3300.0
-2200.0 2500.0 2700.0 2900.0 3200.0 3400.0
-2000.0 2500.0 2600.0 2800.0 3200.0 3300.0
-2100.0 2500.0 2600.0 2900.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2700.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2800.0 3000.0 3100.0
-1700.0 2000.0 2300.0 2700.0 3000.0 3200.0
-2000.0 2100.0 2500.0 2800.0 3000.0 3100.0
-1400.0 1600.0 1800.0 2100.0 3300.0 3400.0
-1500.0 1800.0 2100.0 2300.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2500.0 3000.0 3300.0
-1600.0 1700.0 2200.0 2600.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2700.0 3000.0 3200.0
-1700.0 1800.0 2200.0 2700.0 3000.0 3100.0
-1800.0 2000.0 2200.0 2800.0 3000.0 3100.0
-1300.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1300.0 2000.0 2200.0 2600.0 3100.0 3200.0
-2100.0 2500.0 2800.0 2900.0 3200.0 3400.0
-2200.0 2600.0 2800.0 3000.0 3300.0 3400.0
-1600.0 1900.0 2500.0 2600.0 3100.0 3400.0
-1400.0 1800.0 2500.0 2600.0 3100.0 3400.0
-1100.0 1800.0 2600.0 2700.0 3200.0 3400.0
-1000.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1200.0 1500.0 1700.0 1900.0 3000.0 3400.0
-1700.0 2100.0 2300.0 2700.0 3200.0 3300.0
-2000.0 2100.0 2600.0 2800.0 3100.0 3300.0
-2000.0 2100.0 2500.0 2900.0 3100.0 3200.0
-1700.0 2000.0 2300.0 2800.0 3100.0 3200.0
-1600.0 2000.0 2100.0 2700.0 3000.0 3100.0
-1600.0 2000.0 2100.0 2700.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2500.0 2900.0 3100.0
-1700.0 2000.0 2200.0 2500.0 2900.0 3100.0
-1500.0 2000.0 2200.0 2400.0 2900.0 3100.0
-1600.0 1900.0 2200.0 2600.0 3000.0 3100.0
-1600.0 1900.0 2300.0 2700.0 2900.0 3100.0
-1700.0 2000.0 2200.0 2700.0 2900.0 3000.0
-1700.0 2000.0 2300.0 2700.0 2900.0 3100.0
-1700.0 2000.0 2300.0 2600.0 2900.0 3100.0
-1700.0 1900.0 2400.0 2600.0 2800.0 3000.0
-1700.0 1800.0 2300.0 2600.0 2800.0 3000.0
-1700.0 1900.0 2400.0 2600.0 2900.0 3100.0
-1700.0 1900.0 2300.0 2500.0 2800.0 3100.0
-1700.0 2100.0 2400.0 2600.0 2800.0 3100.0
-2000.0 2200.0 2500.0 2700.0 2800.0 3100.0
-1900.0 2200.0 2400.0 2700.0 2900.0 3000.0
-1800.0 2000.0 2300.0 2700.0 2900.0 3000.0
-1800.0 2300.0 2500.0 2700.0 3000.0 3100.0
-2000.0 2400.0 2600.0 2800.0 3100.0 3200.0
-1900.0 2300.0 2700.0 2800.0 3200.0 3300.0
-1800.0 2400.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1700.0 2000.0 2300.0 2500.0 2900.0 3000.0
-1700.0 1800.0 2100.0 2500.0 2900.0 3000.0
-1600.0 1700.0 2000.0 2400.0 2900.0 3100.0
-1600.0 1700.0 2100.0 2400.0 2700.0 2900.0
-1500.0 1600.0 2000.0 2600.0 2800.0 3100.0
-1400.0 1500.0 2000.0 2700.0 3200.0 3300.0
-1500.0 1600.0 2100.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2100.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2800.0 3100.0 3300.0
-2000.0 2200.0 2800.0 2900.0 3200.0 3400.0
-2000.0 2200.0 2800.0 2900.0 3100.0 3400.0
-2000.0 2100.0 2700.0 2900.0 3100.0 3400.0
-1800.0 2200.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2200.0 2600.0 2800.0 3100.0 3200.0
-1900.0 2200.0 2500.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2500.0 2900.0 3100.0
-1800.0 1900.0 2200.0 2500.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2500.0 2800.0 3000.0
-1500.0 1700.0 2100.0 2400.0 2700.0 3100.0
-1400.0 1500.0 1900.0 2400.0 3000.0 3100.0
-1400.0 1600.0 2000.0 2400.0 3100.0 3200.0
-1500.0 1700.0 2100.0 2400.0 3000.0 3200.0
-1600.0 1800.0 2100.0 2400.0 2900.0 3100.0
-1600.0 1800.0 2100.0 2300.0 3000.0 3200.0
-1600.0 1800.0 2100.0 2300.0 3100.0 3300.0
-1600.0 1700.0 2000.0 2200.0 3200.0 3300.0
-1600.0 1700.0 1900.0 2100.0 3000.0 3300.0
-1700.0 1800.0 2100.0 2400.0 3100.0 3200.0
-2000.0 2300.0 2500.0 2700.0 2900.0 3100.0
-2000.0 2300.0 2600.0 2700.0 3000.0 3200.0
-1900.0 2100.0 2400.0 2600.0 2900.0 3200.0
-1700.0 1900.0 2200.0 2600.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2600.0 2700.0 3100.0
-1600.0 1700.0 2200.0 2600.0 2800.0 3000.0
-1500.0 1600.0 2100.0 2700.0 2800.0 3000.0
-1300.0 1500.0 2000.0 2700.0 3000.0 3200.0
-1200.0 1500.0 2100.0 2800.0 3000.0 3200.0
-1300.0 1500.0 2100.0 2800.0 3000.0 3100.0
-1600.0 1900.0 2100.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1500.0 1900.0 2400.0 2500.0 2900.0 3200.0
-1600.0 1700.0 2200.0 2500.0 2900.0 3100.0
-1600.0 1700.0 2200.0 2700.0 2800.0 3000.0
-1600.0 1700.0 2200.0 2700.0 2900.0 3100.0
-1500.0 1700.0 2400.0 2700.0 2900.0 3100.0
-1500.0 1800.0 2400.0 2700.0 2900.0 3200.0
-1700.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1700.0 2100.0 2500.0 2600.0 2900.0 3100.0
-1900.0 2300.0 2600.0 2700.0 3000.0 3100.0
-1800.0 2200.0 2600.0 2700.0 3000.0 3100.0
-1900.0 2200.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2100.0 2400.0 2800.0 3000.0 3100.0
-1800.0 2000.0 2300.0 2500.0 3000.0 3300.0
-1600.0 2000.0 2200.0 2600.0 2800.0 3000.0
-1700.0 1800.0 2100.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2100.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2100.0 2400.0 2900.0 3200.0
-1400.0 1600.0 2100.0 2300.0 3000.0 3200.0
-1400.0 1800.0 2100.0 2500.0 3100.0 3200.0
-1700.0 1900.0 2300.0 2500.0 2700.0 3100.0
-1800.0 1900.0 2200.0 2500.0 2800.0 3200.0
-1700.0 1900.0 2100.0 2500.0 2800.0 3100.0
-1700.0 1900.0 2200.0 2500.0 2800.0 3200.0
-1600.0 1800.0 2100.0 2600.0 2800.0 3100.0
-1600.0 1800.0 2200.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2200.0 2600.0 2800.0 3100.0
-1400.0 1600.0 2200.0 2600.0 2900.0 3100.0
-1400.0 1600.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2700.0 2900.0 3200.0
-1500.0 1700.0 2100.0 2600.0 3000.0 3100.0
-1600.0 1700.0 2100.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2300.0 2500.0 2900.0 3100.0
-1700.0 1900.0 2300.0 2500.0 2900.0 3100.0
-1600.0 1800.0 2300.0 2500.0 2900.0 3000.0
-1500.0 1700.0 2000.0 2700.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2600.0 2900.0 3100.0
-1500.0 1600.0 1900.0 2500.0 2900.0 3000.0
-1500.0 1600.0 1900.0 2600.0 2900.0 3100.0
-1700.0 1900.0 2500.0 2700.0 3100.0 3200.0
-1600.0 1700.0 2300.0 2700.0 2900.0 3200.0
-1600.0 1700.0 2200.0 2700.0 2800.0 3100.0
-1600.0 1700.0 2300.0 2700.0 2800.0 3100.0
-1500.0 1600.0 2200.0 2700.0 2900.0 3200.0
-1500.0 1600.0 2100.0 2700.0 3000.0 3200.0
-1400.0 1500.0 2100.0 2700.0 3000.0 3100.0
-1600.0 1800.0 2200.0 2500.0 3200.0 3300.0
-1900.0 2200.0 2400.0 2700.0 3100.0 3300.0
-1900.0 2100.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2100.0 2400.0 2800.0 3000.0 3200.0
-1600.0 1800.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2400.0 3000.0 3300.0
-1700.0 1900.0 2100.0 2500.0 3100.0 3300.0
-1600.0 1800.0 2200.0 2500.0 3200.0 3400.0
-1700.0 1900.0 2200.0 2500.0 3200.0 3400.0
-1600.0 1800.0 2200.0 2600.0 3200.0 3300.0
-1900.0 2100.0 2500.0 2700.0 2900.0 3100.0
-1900.0 2200.0 2400.0 2600.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2500.0 2700.0 3000.0
-1600.0 1700.0 2100.0 2500.0 2600.0 3000.0
-1600.0 1700.0 2200.0 2400.0 2700.0 2900.0
-1700.0 1800.0 2300.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2300.0 2500.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2400.0 2800.0 3100.0
-1700.0 1900.0 2200.0 2400.0 2800.0 3100.0
-1500.0 2000.0 2300.0 2700.0 2900.0 3100.0
-1500.0 1900.0 2300.0 2500.0 3000.0 3300.0
-1700.0 2000.0 2400.0 2900.0 3200.0 3300.0
-2000.0 2100.0 2400.0 2700.0 3000.0 3100.0
-1900.0 2200.0 2400.0 2600.0 2900.0 3000.0
-1700.0 2100.0 2300.0 2700.0 2900.0 3000.0
-1600.0 2000.0 2200.0 2600.0 3000.0 3100.0
-1600.0 2100.0 2200.0 2600.0 3000.0 3100.0
-1600.0 2100.0 2300.0 2600.0 3000.0 3100.0
-1700.0 2100.0 2300.0 2600.0 2900.0 3100.0
-1800.0 2300.0 2400.0 2700.0 3000.0 3200.0
-1900.0 2300.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2400.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2400.0 2600.0 2800.0 3000.0 3200.0
-1800.0 2400.0 2600.0 2800.0 3000.0 3200.0
-1800.0 2300.0 2600.0 2700.0 3000.0 3100.0
-1600.0 1800.0 2300.0 2500.0 2800.0 3100.0
-1500.0 1800.0 2200.0 2500.0 2800.0 3000.0
-1500.0 1800.0 2300.0 2500.0 2800.0 3100.0
-1400.0 1900.0 2300.0 2500.0 2800.0 3000.0
-2000.0 2100.0 2500.0 2700.0 3100.0 3200.0
-2000.0 2100.0 2600.0 2800.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2700.0 2900.0 3100.0
-1800.0 2100.0 2400.0 2600.0 2900.0 3200.0
-1800.0 2000.0 2400.0 2600.0 2900.0 3200.0
-1700.0 1900.0 2400.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2100.0 2500.0 2900.0 3200.0
-1200.0 1700.0 2200.0 2400.0 2900.0 3200.0
-1500.0 1600.0 1900.0 2500.0 2800.0 3000.0
-1500.0 1600.0 2000.0 2500.0 2800.0 3000.0
-1600.0 1700.0 2100.0 2500.0 2800.0 3200.0
-1700.0 1800.0 2100.0 2400.0 2800.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2900.0 3100.0
-1700.0 1800.0 2300.0 2700.0 3100.0 3300.0
-1300.0 1700.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1800.0 2300.0 2700.0 3100.0 3300.0
-1500.0 1600.0 1900.0 2100.0 2800.0 3300.0
-1600.0 1700.0 2000.0 2100.0 2700.0 3300.0
-1800.0 2200.0 2400.0 2500.0 3000.0 3300.0
-1700.0 2300.0 2400.0 2600.0 3100.0 3200.0
-1700.0 2200.0 2400.0 2600.0 3000.0 3100.0
-1800.0 2000.0 2300.0 2500.0 2800.0 3100.0
-1800.0 2000.0 2200.0 2500.0 2900.0 3100.0
-1800.0 2100.0 2200.0 2700.0 3000.0 3100.0
-1800.0 2000.0 2200.0 2600.0 2900.0 3000.0
-1700.0 2000.0 2100.0 2600.0 3000.0 3100.0
-1700.0 2000.0 2100.0 2500.0 3000.0 3100.0
-1700.0 1900.0 2300.0 2500.0 2800.0 3200.0
-1600.0 1900.0 2300.0 2500.0 2900.0 3200.0
-1500.0 1800.0 2200.0 2500.0 3100.0 3300.0
-1600.0 1700.0 2300.0 2700.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2600.0 2900.0 3000.0
-1400.0 1600.0 2000.0 2600.0 2900.0 3200.0
-1500.0 1600.0 2000.0 2600.0 2900.0 3200.0
-1600.0 1700.0 2100.0 2500.0 2900.0 3200.0
-1500.0 1900.0 2300.0 2400.0 3000.0 3300.0
-1600.0 1800.0 2300.0 2500.0 3000.0 3300.0
-1800.0 2200.0 2500.0 2700.0 2900.0 3100.0
-1500.0 1900.0 2200.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2700.0 2900.0 3100.0
-1400.0 1600.0 2000.0 2700.0 2800.0 3000.0
-1400.0 1600.0 1900.0 2600.0 2800.0 3000.0
-1400.0 1600.0 2100.0 2600.0 2900.0 3200.0
-1500.0 1600.0 2100.0 2600.0 3000.0 3200.0
-1500.0 1600.0 2100.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2000.0 2600.0 2900.0 3000.0
-1700.0 1900.0 2100.0 2600.0 2800.0 3100.0
-1800.0 2000.0 2400.0 2700.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2700.0 3000.0 3200.0
-1800.0 2200.0 2600.0 2900.0 3100.0 3300.0
-1800.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1800.0 1900.0 2100.0 2400.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2500.0 3000.0 3200.0
-1600.0 1700.0 2300.0 2500.0 2800.0 3200.0
-1600.0 1700.0 2200.0 2600.0 2800.0 3200.0
-1600.0 1700.0 2100.0 2600.0 2800.0 3200.0
-1600.0 1700.0 2000.0 2600.0 2800.0 3100.0
-1400.0 1700.0 2000.0 2600.0 2900.0 3100.0
-1800.0 2200.0 2500.0 2900.0 3100.0 3300.0
-1700.0 2100.0 2500.0 2900.0 3100.0 3200.0
-1500.0 1700.0 2400.0 2700.0 2900.0 3200.0
-1400.0 1500.0 2300.0 2500.0 2800.0 3100.0
-1300.0 1500.0 2300.0 2500.0 2800.0 3100.0
-1300.0 1500.0 2200.0 2600.0 2700.0 3100.0
-1200.0 1600.0 2400.0 2600.0 3000.0 3200.0
-1600.0 2000.0 2500.0 2700.0 3000.0 3300.0
-1500.0 1700.0 2500.0 2700.0 3000.0 3200.0
-1400.0 1500.0 2000.0 2700.0 3000.0 3100.0
-1400.0 1500.0 1900.0 2600.0 3000.0 3100.0
-2000.0 2300.0 2800.0 2900.0 3200.0 3400.0
-2100.0 2500.0 2700.0 2800.0 3200.0 3400.0
-1900.0 2300.0 2500.0 2700.0 3100.0 3400.0
-1800.0 1900.0 2200.0 2500.0 3000.0 3300.0
-1900.0 2200.0 2500.0 2600.0 2900.0 3200.0
-1900.0 2100.0 2300.0 2700.0 2800.0 3100.0
-1900.0 2000.0 2200.0 2600.0 3000.0 3200.0
-1900.0 2000.0 2500.0 2800.0 3100.0 3300.0
-1800.0 1900.0 2200.0 2700.0 2800.0 3100.0
-1700.0 1800.0 2400.0 2600.0 2800.0 3200.0
-1700.0 1900.0 2400.0 2500.0 2900.0 3300.0
-1400.0 1700.0 2300.0 2400.0 2600.0 3000.0
-1600.0 1700.0 2000.0 2200.0 2900.0 3200.0
-1600.0 1700.0 2000.0 2300.0 2900.0 3200.0
-1800.0 1900.0 2100.0 2600.0 2800.0 3100.0
-1800.0 1900.0 2300.0 2600.0 2900.0 3100.0
-1100.0 1800.0 2200.0 2400.0 2900.0 3200.0
-1200.0 1700.0 2300.0 2500.0 3000.0 3200.0
-1500.0 1600.0 2200.0 2600.0 2700.0 3100.0
-1700.0 1800.0 2100.0 2500.0 3000.0 3100.0
-1300.0 1700.0 2000.0 2400.0 3000.0 3200.0
-1300.0 1600.0 2000.0 2300.0 3100.0 3200.0
-1300.0 1600.0 1900.0 2300.0 3100.0 3200.0
-1400.0 1600.0 1900.0 2300.0 3100.0 3200.0
-1400.0 1600.0 1900.0 2400.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2400.0 3100.0 3200.0
-1800.0 2100.0 2200.0 2700.0 3100.0 3200.0
-1700.0 2100.0 2200.0 2700.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2600.0 3200.0 3400.0
-1900.0 2200.0 2600.0 3000.0 3300.0 3400.0
-1400.0 1800.0 2200.0 2600.0 3000.0 3300.0
-1000.0 1400.0 2400.0 2600.0 2900.0 3200.0
-1200.0 1500.0 2500.0 2600.0 3000.0 3300.0
-1200.0 1500.0 2400.0 2600.0 3000.0 3300.0
-1200.0 1500.0 2400.0 2600.0 2900.0 3300.0
-1200.0 1500.0 2400.0 2500.0 2900.0 3300.0
-1200.0 1500.0 2300.0 2500.0 3000.0 3300.0
-1200.0 1500.0 2300.0 2400.0 3000.0 3300.0
-1300.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2500.0 2800.0 3200.0
-1800.0 1900.0 2300.0 2500.0 2700.0 3200.0
-1800.0 1900.0 2300.0 2600.0 2700.0 3100.0
-1800.0 1900.0 2400.0 2600.0 2800.0 3200.0
-1900.0 2000.0 2700.0 2800.0 3100.0 3300.0
-1900.0 2000.0 2600.0 2800.0 3000.0 3300.0
-1900.0 2000.0 2500.0 2800.0 3000.0 3300.0
-1900.0 2100.0 2700.0 2800.0 3100.0 3300.0
-1900.0 2000.0 2700.0 2800.0 3000.0 3300.0
-1900.0 2000.0 2600.0 2800.0 3000.0 3200.0
-1200.0 1500.0 2200.0 2500.0 3100.0 3300.0
-1600.0 1900.0 2200.0 2600.0 3000.0 3200.0
-1300.0 1700.0 2300.0 2500.0 3100.0 3200.0
-1400.0 1500.0 2100.0 2400.0 2600.0 3100.0
-1500.0 1600.0 2000.0 2400.0 2700.0 3100.0
-1600.0 1700.0 2000.0 2500.0 2700.0 3100.0
-1900.0 2100.0 2300.0 2600.0 2900.0 3200.0
-1900.0 2100.0 2400.0 2600.0 2900.0 3100.0
-1700.0 2000.0 2200.0 2700.0 2900.0 3100.0
-1800.0 2000.0 2100.0 2700.0 3000.0 3100.0
-1800.0 1900.0 2100.0 2700.0 3000.0 3200.0
-1900.0 2100.0 2700.0 2800.0 3000.0 3300.0
-1900.0 2300.0 2700.0 2800.0 3100.0 3300.0
-2000.0 2400.0 2700.0 2800.0 3200.0 3400.0
-1600.0 2000.0 2300.0 2600.0 3000.0 3100.0
-1000.0 1400.0 2200.0 2400.0 3100.0 3300.0
-1400.0 1500.0 2000.0 2100.0 2900.0 3300.0
-1800.0 1900.0 2100.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2700.0 3000.0 3300.0
-1800.0 2000.0 2300.0 2700.0 3100.0 3300.0
-1800.0 2100.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2200.0 2800.0 2900.0 3200.0 3300.0
-2000.0 2200.0 2500.0 2900.0 3200.0 3300.0
-1800.0 2000.0 2300.0 2400.0 3100.0 3200.0
-1800.0 2000.0 2300.0 2400.0 3000.0 3200.0
-1800.0 1900.0 2200.0 2400.0 3000.0 3200.0
-1600.0 1800.0 2100.0 2600.0 2800.0 3000.0
-1500.0 1600.0 2200.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2000.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2000.0 2500.0 3100.0 3200.0
-1600.0 1900.0 2000.0 2500.0 3000.0 3100.0
-1900.0 2300.0 2800.0 2900.0 3200.0 3400.0
-2000.0 2200.0 2700.0 3000.0 3200.0 3300.0
-1900.0 2400.0 2800.0 2900.0 3200.0 3300.0
-2000.0 2400.0 2700.0 2900.0 3100.0 3300.0
-1800.0 2200.0 2400.0 2800.0 3000.0 3200.0
-1900.0 2200.0 2700.0 3000.0 3200.0 3400.0
-1900.0 2200.0 2600.0 2800.0 3000.0 3300.0
-1600.0 1700.0 2400.0 2600.0 2800.0 3200.0
-1600.0 1700.0 2300.0 2700.0 2800.0 3200.0
-1600.0 1700.0 2200.0 2700.0 2800.0 3200.0
-1600.0 1700.0 2000.0 2400.0 2900.0 3200.0
-1600.0 1900.0 2200.0 2500.0 2800.0 3000.0
-1600.0 2000.0 2400.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2000.0 2700.0 3000.0 3100.0
-1400.0 1600.0 2100.0 2700.0 2900.0 3100.0
-1900.0 2200.0 2800.0 3000.0 3300.0 3500.0
-1700.0 2000.0 2700.0 2800.0 3100.0 3300.0
-1600.0 1800.0 2200.0 2500.0 2800.0 3100.0
-1600.0 1800.0 2100.0 2400.0 2800.0 3000.0
-1600.0 2000.0 2300.0 2600.0 2800.0 3000.0
-1600.0 1900.0 2300.0 2600.0 2800.0 3000.0
-1800.0 2200.0 2500.0 2900.0 3200.0 3400.0
-1700.0 1900.0 2200.0 2800.0 3100.0 3200.0
-1600.0 2000.0 2300.0 2700.0 3000.0 3300.0
-1600.0 2000.0 2200.0 2600.0 3000.0 3200.0
-1800.0 2100.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1900.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2400.0 2600.0 2900.0 3200.0
-1300.0 2000.0 2300.0 2400.0 2800.0 3300.0
-1800.0 2000.0 2400.0 2600.0 2900.0 3300.0
-1900.0 2200.0 2300.0 2700.0 3000.0 3100.0
-1900.0 2200.0 2300.0 2700.0 3000.0 3200.0
-1800.0 2200.0 2400.0 2800.0 3100.0 3200.0
-1600.0 2100.0 2200.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2300.0 2500.0 2900.0 3200.0
-1800.0 2200.0 2400.0 2700.0 3100.0 3300.0
-1200.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1000.0 1600.0 2700.0 2900.0 3200.0 3300.0
-1000.0 1500.0 2700.0 2900.0 3200.0 3300.0
-1500.0 1700.0 2600.0 2800.0 3100.0 3300.0
-1500.0 1700.0 2600.0 2800.0 3000.0 3300.0
-1600.0 1700.0 2500.0 2800.0 3000.0 3300.0
-1600.0 1700.0 2400.0 2800.0 3000.0 3300.0
-1700.0 1800.0 2000.0 2400.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2500.0 3000.0 3100.0
-1700.0 1900.0 2200.0 2500.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2400.0 2600.0 2800.0 3100.0
-1200.0 1600.0 2200.0 2400.0 2900.0 3100.0
-1300.0 1800.0 2400.0 2600.0 2900.0 3200.0
-1300.0 1500.0 2000.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2400.0 2700.0 3100.0 3200.0
-1800.0 2100.0 2400.0 2700.0 3100.0 3400.0
-1500.0 1600.0 2000.0 2200.0 3000.0 3300.0
-1600.0 1700.0 2100.0 2200.0 3000.0 3300.0
-1700.0 1800.0 2100.0 2300.0 3100.0 3300.0
-1800.0 1900.0 2200.0 2400.0 2900.0 3100.0
-1800.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1500.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1500.0 2100.0 2300.0 2500.0 3100.0 3300.0
-1700.0 1900.0 2400.0 2700.0 2900.0 3100.0
-1400.0 1800.0 2200.0 2300.0 3100.0 3400.0
-1300.0 1800.0 2300.0 2400.0 3000.0 3300.0
-1800.0 2200.0 2400.0 2600.0 3100.0 3300.0
-1800.0 2100.0 2300.0 2500.0 3100.0 3200.0
-1100.0 1700.0 2200.0 2300.0 3000.0 3200.0
-1100.0 1600.0 2200.0 2400.0 3100.0 3200.0
-1200.0 2000.0 2300.0 2500.0 3000.0 3100.0
-1700.0 2300.0 2500.0 2800.0 3200.0 3300.0
-1500.0 1900.0 2200.0 2400.0 2900.0 3100.0
-1400.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1400.0 2000.0 2200.0 2600.0 3100.0 3200.0
-1700.0 2000.0 2300.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2500.0 2800.0 2900.0 3200.0
-1700.0 1800.0 2500.0 2700.0 2900.0 3200.0
-1600.0 1800.0 2400.0 2600.0 2800.0 3200.0
-1400.0 1700.0 2100.0 2500.0 3000.0 3300.0
-1400.0 1600.0 1900.0 2000.0 3100.0 3300.0
-1400.0 1600.0 2000.0 2100.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2400.0 2900.0 3300.0
-2100.0 2300.0 2600.0 2900.0 3100.0 3300.0
-1200.0 1800.0 2200.0 2400.0 3000.0 3200.0
-1700.0 2000.0 2300.0 2600.0 3000.0 3300.0
-1900.0 2400.0 2700.0 2900.0 3300.0 3400.0
-1400.0 1600.0 2100.0 2500.0 3100.0 3200.0
-1400.0 1700.0 2300.0 2500.0 3200.0 3400.0
-1400.0 1600.0 2300.0 2500.0 3200.0 3400.0
-1400.0 1600.0 2300.0 2500.0 3100.0 3400.0
-1500.0 1700.0 2200.0 2800.0 3100.0 3200.0
-1500.0 1600.0 2300.0 2800.0 3000.0 3200.0
-1400.0 1600.0 2300.0 2800.0 3000.0 3200.0
-1200.0 1400.0 2400.0 2900.0 3100.0 3200.0
-1200.0 1400.0 2400.0 2900.0 3200.0 3300.0
-1100.0 1400.0 2400.0 2900.0 3200.0 3300.0
-1600.0 1800.0 2400.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2400.0 2800.0 3000.0 3200.0
-1900.0 2300.0 2700.0 3000.0 3300.0 3400.0
-1800.0 2300.0 2800.0 3000.0 3200.0 3400.0
-1800.0 1900.0 2400.0 2800.0 3100.0 3300.0
-1700.0 1800.0 2100.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2700.0 3100.0 3200.0
-1600.0 1700.0 2000.0 2500.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2700.0 3100.0 3200.0
-1900.0 2200.0 2500.0 2800.0 3000.0 3100.0
-2000.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2800.0 2900.0 3200.0
-1700.0 1800.0 2400.0 2800.0 2900.0 3200.0
-1600.0 1800.0 2600.0 2800.0 3000.0 3300.0
-2100.0 2300.0 2500.0 2800.0 3000.0 3300.0
-2100.0 2200.0 2500.0 2600.0 2900.0 3200.0
-1900.0 2100.0 2400.0 2600.0 2800.0 3200.0
-1800.0 2000.0 2700.0 2800.0 3000.0 3300.0
-1700.0 2100.0 2400.0 2600.0 3000.0 3200.0
-1800.0 2000.0 2400.0 2500.0 3100.0 3400.0
-1900.0 2200.0 2500.0 2600.0 3100.0 3200.0
-1900.0 2200.0 2500.0 2600.0 3000.0 3200.0
-1800.0 2200.0 2500.0 2600.0 3000.0 3100.0
-2000.0 2200.0 2600.0 2700.0 3100.0 3200.0
-2000.0 2300.0 2600.0 2700.0 3100.0 3200.0
-1800.0 2100.0 2300.0 2500.0 2900.0 3100.0
-1800.0 2100.0 2700.0 3000.0 3300.0 3400.0
-1800.0 2000.0 2700.0 2900.0 3200.0 3300.0
-1900.0 2100.0 2400.0 2700.0 3000.0 3300.0
-1900.0 2100.0 2400.0 2700.0 2900.0 3100.0
-2000.0 2200.0 2400.0 2700.0 2900.0 3100.0
-2000.0 2400.0 2600.0 2700.0 2900.0 3100.0
-1500.0 1700.0 2200.0 2300.0 3100.0 3300.0
-1400.0 1600.0 2300.0 2600.0 2900.0 3300.0
-1600.0 1700.0 2500.0 2700.0 2900.0 3200.0
-1600.0 1700.0 2500.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2300.0 2400.0 3000.0 3400.0
-1500.0 1700.0 2100.0 2300.0 2900.0 3300.0
-1600.0 1700.0 2100.0 2300.0 3000.0 3300.0
-1500.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1500.0 2100.0 2500.0 2600.0 3000.0 3200.0
-1500.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1600.0 1700.0 2000.0 2500.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2600.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2500.0 3000.0 3100.0
-1800.0 1900.0 2200.0 2600.0 3000.0 3100.0
-1700.0 2100.0 2600.0 2900.0 3100.0 3400.0
-1700.0 2000.0 2600.0 2900.0 3200.0 3300.0
-1800.0 1900.0 2300.0 2800.0 2900.0 3100.0
-1800.0 1900.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2000.0 2500.0 2900.0 3200.0 3400.0
-1800.0 2400.0 2800.0 2900.0 3300.0 3400.0
-1500.0 1800.0 2300.0 2700.0 3200.0 3300.0
-1600.0 1700.0 2400.0 2800.0 3000.0 3200.0
-1200.0 1600.0 2200.0 2600.0 2900.0 3200.0
-1400.0 1800.0 2400.0 2800.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2800.0 3100.0 3300.0
-1300.0 1700.0 2300.0 2600.0 3000.0 3200.0
-1500.0 1600.0 2400.0 2600.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2000.0 2600.0 2900.0 3200.0 3400.0
-1900.0 2000.0 2700.0 2900.0 3200.0 3400.0
-1200.0 1800.0 2400.0 2500.0 3000.0 3300.0
-1300.0 1900.0 2400.0 2500.0 3100.0 3300.0
-1700.0 2000.0 2500.0 2900.0 3200.0 3300.0
-1100.0 1400.0 2400.0 2900.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2700.0 3100.0 3200.0
-2000.0 2200.0 2400.0 2600.0 3000.0 3100.0
-1900.0 2100.0 2300.0 2600.0 3000.0 3100.0
-1700.0 1900.0 2500.0 2800.0 3100.0 3200.0
-1400.0 1600.0 2400.0 2800.0 3000.0 3200.0
-1200.0 1500.0 2200.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2700.0 3100.0 3200.0
-1500.0 1700.0 2200.0 2400.0 2900.0 3100.0
-1500.0 1800.0 2200.0 2300.0 2800.0 2900.0
-1500.0 1800.0 2200.0 2500.0 2900.0 3100.0
-1600.0 1800.0 2200.0 2500.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2700.0 2900.0 3000.0
-1600.0 1800.0 2100.0 2800.0 3000.0 3100.0
-1800.0 1900.0 2300.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2400.0 2800.0 3200.0 3400.0
-1900.0 2000.0 2500.0 2800.0 3200.0 3400.0
-1900.0 2000.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1700.0 2200.0 2500.0 3100.0 3300.0
-1900.0 2300.0 2500.0 2800.0 3100.0 3300.0
-1300.0 2000.0 2200.0 2400.0 2800.0 3100.0
-1400.0 1700.0 2300.0 2600.0 3000.0 3300.0
-1500.0 1600.0 2300.0 2700.0 2800.0 3100.0
-1600.0 1800.0 2300.0 2600.0 2800.0 3100.0
-1900.0 2000.0 2400.0 2600.0 2900.0 3100.0
-2000.0 2500.0 2600.0 2700.0 3200.0 3300.0
-2200.0 2500.0 2600.0 2900.0 3100.0 3300.0
-2100.0 2400.0 2600.0 2700.0 3200.0 3300.0
-2100.0 2400.0 2600.0 2700.0 3200.0 3400.0
-1700.0 1900.0 2500.0 2700.0 2900.0 3100.0
-1900.0 2300.0 2400.0 2700.0 3000.0 3200.0
-2000.0 2300.0 2500.0 2700.0 3000.0 3100.0
-2000.0 2400.0 2500.0 2800.0 3200.0 3300.0
-2000.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2200.0 2400.0 3000.0 3300.0
-1400.0 1600.0 2100.0 2400.0 2900.0 3200.0
-1600.0 1700.0 2200.0 2300.0 2700.0 3200.0
-1700.0 1800.0 2100.0 2300.0 2800.0 3300.0
-1700.0 1800.0 2200.0 2400.0 2800.0 3300.0
-1900.0 2000.0 2200.0 2500.0 3000.0 3200.0
-1300.0 2000.0 2300.0 2400.0 2900.0 3200.0
-1900.0 2200.0 2400.0 2500.0 2900.0 3200.0
-1600.0 1800.0 2200.0 2500.0 2700.0 3100.0
-1600.0 1700.0 2300.0 2500.0 3000.0 3400.0
-1900.0 2000.0 2400.0 2700.0 2900.0 3300.0
-1800.0 2200.0 2400.0 2600.0 2900.0 3100.0
-1700.0 2000.0 2300.0 2600.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2600.0 2800.0 3000.0
-1600.0 1700.0 2100.0 2700.0 2900.0 3000.0
-1400.0 1600.0 2000.0 2200.0 2800.0 3200.0
-1200.0 1600.0 2000.0 2400.0 3000.0 3200.0
-1200.0 1700.0 2200.0 2500.0 3000.0 3100.0
-1600.0 1900.0 2600.0 2800.0 3000.0 3200.0
-1500.0 1900.0 2300.0 2700.0 2900.0 3200.0
-1200.0 1900.0 2300.0 2400.0 3000.0 3300.0
-1400.0 1600.0 2300.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2500.0 3000.0 3200.0
-1500.0 1600.0 2100.0 2400.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2300.0 3000.0 3300.0
-1600.0 1700.0 2100.0 2200.0 2900.0 3300.0
-1500.0 1600.0 2000.0 2100.0 2800.0 3200.0
-1500.0 1600.0 2000.0 2200.0 2800.0 3200.0
-1500.0 1600.0 2000.0 2200.0 2900.0 3200.0
-1500.0 1800.0 2100.0 2200.0 2900.0 3300.0
-2100.0 2300.0 2500.0 2700.0 2900.0 3100.0
-2000.0 2200.0 2400.0 2600.0 2800.0 3100.0
-1800.0 2100.0 2300.0 2600.0 2800.0 3000.0
-1600.0 1800.0 2400.0 2600.0 2800.0 3000.0
-1200.0 1300.0 2100.0 2700.0 2800.0 3000.0
-1100.0 1300.0 2300.0 2700.0 2900.0 3100.0
-1100.0 1300.0 2300.0 2700.0 2800.0 3100.0
-1100.0 1300.0 2300.0 2800.0 2900.0 3100.0
-1500.0 1800.0 2300.0 2700.0 3100.0 3200.0
-1200.0 1800.0 2300.0 2600.0 3000.0 3200.0
-1700.0 1800.0 2300.0 2600.0 2800.0 3200.0
-1900.0 2000.0 2400.0 2600.0 2800.0 3200.0
-2100.0 2200.0 2400.0 2600.0 3100.0 3300.0
-2000.0 2200.0 2400.0 2600.0 3100.0 3300.0
-2300.0 2500.0 2800.0 3000.0 3200.0 3300.0
-1900.0 2200.0 2700.0 2800.0 3100.0 3300.0
-1600.0 1700.0 2200.0 2600.0 3000.0 3300.0
-1500.0 1700.0 2100.0 2400.0 3100.0 3300.0
-1300.0 1600.0 2100.0 2400.0 3200.0 3400.0
-1400.0 2000.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1600.0 2300.0 2400.0 2800.0 3200.0
-1400.0 1600.0 2300.0 2500.0 2800.0 3200.0
-1400.0 1500.0 2300.0 2500.0 2800.0 3200.0
-1400.0 1500.0 2200.0 2600.0 3000.0 3300.0
-1500.0 1600.0 2000.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2200.0 2700.0 3000.0 3200.0
-1500.0 1600.0 2300.0 2700.0 3000.0 3200.0
-1800.0 2000.0 2500.0 2800.0 2900.0 3200.0
-1700.0 1900.0 2500.0 2700.0 2900.0 3200.0
-1900.0 2200.0 2600.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2200.0 2700.0 3100.0 3200.0
-1300.0 1500.0 2100.0 2800.0 3100.0 3200.0
-1500.0 1600.0 2400.0 2800.0 3000.0 3300.0
-1400.0 1500.0 2500.0 2600.0 2900.0 3200.0
-1500.0 1600.0 2400.0 2600.0 2800.0 3300.0
-1600.0 1700.0 2400.0 2600.0 2800.0 3300.0
-1800.0 2000.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2000.0 2300.0 2700.0 3000.0 3100.0
-1900.0 2100.0 2400.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2400.0 2800.0 3000.0 3300.0
-1800.0 1900.0 2300.0 2700.0 2900.0 3100.0
-1800.0 2100.0 2300.0 2700.0 3000.0 3100.0
-1900.0 2100.0 2300.0 2800.0 3000.0 3100.0
-1400.0 2000.0 2200.0 2500.0 3000.0 3200.0
-1900.0 2200.0 2600.0 3000.0 3200.0 3300.0
-1800.0 2200.0 2600.0 3000.0 3200.0 3300.0
-1500.0 1600.0 2400.0 2600.0 2800.0 3200.0
-1400.0 1600.0 2500.0 2700.0 2900.0 3200.0
-1500.0 1600.0 2400.0 2700.0 2900.0 3100.0
-1500.0 2100.0 2400.0 2700.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2600.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2600.0 2900.0 3100.0
-1700.0 2000.0 2200.0 2600.0 2900.0 3100.0
-1700.0 2200.0 2400.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2500.0 2600.0 2900.0 3100.0
-1500.0 1700.0 2500.0 2600.0 2900.0 3100.0
-1400.0 1600.0 2300.0 2600.0 2900.0 3100.0
-1200.0 1400.0 2200.0 2600.0 2900.0 3200.0
-1600.0 1700.0 2200.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2500.0 3100.0 3200.0
-1600.0 1900.0 2200.0 2700.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2800.0 3100.0 3200.0
-1900.0 2100.0 2500.0 2700.0 3100.0 3400.0
-2100.0 2300.0 2600.0 2800.0 3000.0 3200.0
-2000.0 2300.0 2600.0 2800.0 3000.0 3200.0
-2100.0 2400.0 2700.0 2800.0 3000.0 3200.0
-1600.0 2300.0 2600.0 2800.0 3000.0 3100.0
-1700.0 2300.0 2600.0 2800.0 3000.0 3100.0
-1600.0 1700.0 2400.0 2600.0 3000.0 3300.0
-1500.0 1700.0 2400.0 2500.0 2900.0 3300.0
-1600.0 1900.0 2300.0 2600.0 2700.0 3300.0
-1600.0 1900.0 2300.0 2500.0 3300.0 3400.0
-1600.0 1800.0 2300.0 2500.0 3200.0 3400.0
-1800.0 2200.0 2700.0 2900.0 3300.0 3500.0
-1700.0 2000.0 2400.0 2600.0 3300.0 3400.0
-1800.0 2200.0 2800.0 3000.0 3200.0 3300.0
-2100.0 2400.0 2800.0 3100.0 3400.0 3500.0
-2100.0 2500.0 2800.0 3100.0 3400.0 3500.0
-1900.0 2300.0 2900.0 3000.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2400.0 3200.0 3400.0
-1400.0 1700.0 2000.0 2300.0 3000.0 3100.0
-1400.0 1600.0 1900.0 2100.0 3000.0 3100.0
-1400.0 1600.0 1800.0 2100.0 3100.0 3200.0
-1400.0 1600.0 1800.0 2000.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2300.0 2900.0 3300.0
-1600.0 1800.0 2400.0 2500.0 2900.0 3300.0
-1900.0 2000.0 2200.0 2400.0 3100.0 3300.0
-1900.0 2000.0 2200.0 2400.0 3200.0 3400.0
-1300.0 1500.0 2000.0 2500.0 3000.0 3200.0
-1300.0 1600.0 2100.0 2500.0 3000.0 3200.0
-1300.0 1600.0 2300.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2200.0 2600.0 3200.0 3400.0
-1600.0 1800.0 2100.0 2400.0 3300.0 3400.0
-1700.0 1900.0 2200.0 2400.0 3200.0 3400.0
-1800.0 2000.0 2400.0 2700.0 3200.0 3400.0
-1900.0 2200.0 2600.0 2700.0 3000.0 3200.0
-1800.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2400.0 3100.0 3200.0
-1400.0 1600.0 1800.0 2000.0 3000.0 3100.0
-1400.0 1600.0 1800.0 2000.0 2900.0 3000.0
-1400.0 1600.0 1800.0 2100.0 2800.0 3000.0
-1500.0 1700.0 2100.0 2400.0 3000.0 3300.0
-1400.0 1600.0 2200.0 2500.0 3200.0 3300.0
-1100.0 1700.0 2400.0 2600.0 3100.0 3300.0
-1200.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2800.0 3300.0 3400.0
-1600.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1800.0 2200.0 2700.0 3100.0 3400.0 3500.0
-1800.0 2200.0 2800.0 3000.0 3400.0 3500.0
-1900.0 2300.0 2800.0 3100.0 3400.0 3500.0
-1900.0 2400.0 2800.0 3100.0 3300.0 3400.0
-1800.0 2200.0 2600.0 2900.0 3400.0 3500.0
-1600.0 1800.0 2400.0 2800.0 3200.0 3300.0
-2000.0 2500.0 2600.0 2900.0 3200.0 3300.0
-2100.0 2400.0 2600.0 3000.0 3200.0 3300.0
-2200.0 2500.0 2700.0 3100.0 3200.0 3300.0
-2100.0 2500.0 2600.0 2800.0 3300.0 3400.0
-2000.0 2100.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2500.0 3100.0 3400.0
-1700.0 1900.0 2300.0 2400.0 3100.0 3400.0
-1600.0 1900.0 2300.0 2500.0 3200.0 3400.0
-1600.0 2200.0 2700.0 3000.0 3300.0 3400.0
-1800.0 2300.0 2700.0 3000.0 3400.0 3500.0
-1700.0 2300.0 2500.0 2800.0 3300.0 3400.0
-1500.0 1900.0 2500.0 2700.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2800.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2500.0 3200.0 3300.0
-1100.0 2000.0 2400.0 2500.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2700.0 3100.0 3300.0
-1500.0 1900.0 2500.0 2700.0 3100.0 3300.0
-1500.0 1900.0 2300.0 2500.0 2700.0 2900.0
-1400.0 1800.0 2200.0 2500.0 2700.0 2900.0
-1400.0 1800.0 2400.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2400.0 2600.0 3000.0 3300.0
-1500.0 1900.0 2100.0 2300.0 3200.0 3300.0
-1400.0 1800.0 2300.0 2400.0 3000.0 3300.0
-2000.0 2300.0 2800.0 3000.0 3400.0 3500.0
-1600.0 1900.0 2200.0 2300.0 3100.0 3400.0
-1600.0 1800.0 2000.0 2500.0 3000.0 3100.0
-1500.0 1700.0 1800.0 2400.0 3100.0 3200.0
-1500.0 1600.0 1800.0 2400.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2300.0 2500.0 2900.0 3300.0
-1900.0 2300.0 2700.0 2900.0 3100.0 3300.0
-1400.0 1700.0 2300.0 2500.0 3100.0 3200.0
-1200.0 1700.0 2300.0 2500.0 3100.0 3200.0
-1300.0 2200.0 2600.0 2800.0 3100.0 3300.0
-1100.0 1700.0 2500.0 2600.0 3200.0 3400.0
-1300.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1400.0 1500.0 2500.0 2600.0 3100.0 3300.0
-1700.0 1800.0 2300.0 2500.0 2700.0 3300.0
-1800.0 2000.0 2500.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2500.0 2900.0 3200.0
-1800.0 1900.0 2400.0 2500.0 2800.0 3200.0
-1900.0 2000.0 2300.0 2500.0 2800.0 3300.0
-1800.0 2000.0 2200.0 2500.0 2800.0 3300.0
-1900.0 2300.0 2700.0 3000.0 3300.0 3500.0
-2100.0 2300.0 2900.0 3000.0 3200.0 3300.0
-1900.0 2100.0 2800.0 2900.0 3100.0 3300.0
-1700.0 2000.0 2600.0 2700.0 2900.0 3100.0
-1700.0 2100.0 2600.0 2800.0 3000.0 3200.0
-1700.0 2100.0 2600.0 2900.0 3100.0 3300.0
-1400.0 1500.0 1700.0 2900.0 3300.0 3400.0
-1400.0 1700.0 1800.0 2600.0 3300.0 3400.0
-1400.0 1700.0 2000.0 2700.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2300.0 2900.0 3000.0
-1400.0 1700.0 1800.0 2200.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2100.0 3000.0 3200.0
-1300.0 1600.0 1800.0 2000.0 3000.0 3100.0
-1300.0 1600.0 1800.0 2000.0 3100.0 3200.0
-1300.0 1500.0 1700.0 2200.0 3200.0 3300.0
-1300.0 1600.0 1700.0 2200.0 3200.0 3300.0
-1300.0 1500.0 1600.0 2100.0 3200.0 3300.0
-1600.0 1700.0 2100.0 2300.0 3100.0 3300.0
-1500.0 1600.0 2300.0 2400.0 3100.0 3400.0
-1900.0 2400.0 2800.0 3100.0 3400.0 3500.0
-2000.0 2400.0 2800.0 3000.0 3400.0 3500.0
-1600.0 1800.0 2200.0 2600.0 2900.0 3100.0
-1300.0 1600.0 1800.0 2400.0 3100.0 3200.0
-1200.0 1600.0 1800.0 2100.0 3000.0 3100.0
-1400.0 1900.0 2100.0 2400.0 3000.0 3100.0
-1300.0 1900.0 2100.0 2300.0 3000.0 3200.0
-1300.0 1800.0 2100.0 2300.0 3000.0 3200.0
-1400.0 1800.0 2500.0 2700.0 3100.0 3400.0
-1100.0 1800.0 2200.0 2300.0 3100.0 3200.0
-1100.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1200.0 1700.0 2300.0 2400.0 3200.0 3300.0
-1400.0 1700.0 2300.0 2400.0 3000.0 3300.0
-1400.0 1700.0 2400.0 2500.0 3000.0 3300.0
-1900.0 2200.0 2400.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2400.0 3200.0 3400.0
-1300.0 1700.0 2200.0 2400.0 2900.0 3100.0
-1100.0 1600.0 1800.0 2100.0 2900.0 3000.0
-1500.0 1700.0 1900.0 2100.0 3000.0 3100.0
-1600.0 1700.0 1900.0 2100.0 3000.0 3100.0
-1700.0 1900.0 2300.0 2500.0 2900.0 3200.0
-1400.0 1800.0 2200.0 2300.0 3300.0 3400.0
-2100.0 2400.0 2800.0 2900.0 3200.0 3300.0
-2200.0 2500.0 2700.0 2900.0 3100.0 3300.0
-2300.0 2500.0 2700.0 3000.0 3100.0 3300.0
-1700.0 2200.0 2400.0 2800.0 3300.0 3400.0
-1800.0 2300.0 2800.0 3100.0 3400.0 3500.0
-1800.0 2300.0 2600.0 3100.0 3400.0 3500.0
-1800.0 2300.0 2600.0 3100.0 3300.0 3400.0
-1500.0 1700.0 2400.0 2600.0 3000.0 3300.0
-1400.0 1600.0 2400.0 2500.0 2900.0 3300.0
-1200.0 1700.0 2200.0 2400.0 3100.0 3200.0
-1500.0 2000.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2300.0 2700.0 3000.0 3200.0
-1300.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1600.0 1900.0 2400.0 2500.0 3000.0 3200.0
-2000.0 2300.0 2600.0 2700.0 3000.0 3100.0
-1800.0 2000.0 2500.0 2800.0 3000.0 3300.0
-2000.0 2400.0 2600.0 2700.0 3100.0 3200.0
-1700.0 2400.0 2600.0 2800.0 3100.0 3200.0
-1200.0 1800.0 2200.0 2300.0 3300.0 3400.0
-1100.0 1600.0 2200.0 2400.0 3200.0 3300.0
-1100.0 1800.0 1900.0 2500.0 3000.0 3100.0
-1200.0 1700.0 1900.0 2500.0 3100.0 3200.0
-1400.0 1800.0 2300.0 2500.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2500.0 3100.0 3400.0
-1500.0 1700.0 2300.0 2400.0 2900.0 3300.0
-1500.0 1900.0 2200.0 2600.0 3000.0 3100.0
-1300.0 1600.0 2100.0 2300.0 3000.0 3100.0
-1400.0 1700.0 2200.0 2300.0 3000.0 3100.0
-1400.0 1700.0 2200.0 2400.0 3000.0 3100.0
-1400.0 1600.0 2200.0 2300.0 3000.0 3100.0
-1500.0 1700.0 2200.0 2400.0 3100.0 3300.0
-1500.0 1700.0 2100.0 2300.0 3200.0 3300.0
-1400.0 1700.0 2000.0 2300.0 3200.0 3300.0
-1300.0 1700.0 2100.0 2500.0 3100.0 3200.0
-1500.0 1800.0 2200.0 2700.0 3000.0 3200.0
-1500.0 1700.0 2300.0 2400.0 3200.0 3400.0
-1500.0 1600.0 2200.0 2400.0 3100.0 3400.0
-1400.0 1600.0 2200.0 2400.0 3100.0 3400.0
-1100.0 1700.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1900.0 2300.0 2500.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2600.0 3100.0 3400.0
-1500.0 1700.0 2300.0 2500.0 3000.0 3400.0
-1500.0 1900.0 2200.0 2600.0 2800.0 3000.0
-1500.0 1800.0 2200.0 2500.0 2900.0 3000.0
-1500.0 1700.0 2200.0 2500.0 3100.0 3400.0
-1300.0 1800.0 2100.0 2300.0 3300.0 3400.0
-1100.0 1600.0 2200.0 2500.0 3000.0 3300.0
-1400.0 1600.0 2100.0 2500.0 2900.0 3200.0
-1500.0 1800.0 2400.0 2600.0 3300.0 3400.0
-1500.0 1900.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2000.0 2100.0 2600.0 3000.0 3200.0
-1500.0 1700.0 2100.0 2600.0 3100.0 3300.0
-1500.0 1600.0 1800.0 2200.0 3200.0 3300.0
-1600.0 1800.0 1900.0 2300.0 3300.0 3400.0
-1500.0 1800.0 2100.0 2200.0 3200.0 3400.0
-1500.0 2000.0 2200.0 2600.0 3200.0 3300.0
-1300.0 1700.0 2100.0 2300.0 3100.0 3300.0
-1400.0 1500.0 2100.0 2300.0 3000.0 3300.0
-1500.0 1600.0 2100.0 2300.0 3000.0 3300.0
-1500.0 1600.0 2200.0 2300.0 3000.0 3300.0
-1400.0 1900.0 2100.0 2200.0 3000.0 3100.0
-1400.0 1800.0 2100.0 2400.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2600.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2300.0 3200.0 3400.0
-1500.0 1900.0 2200.0 2400.0 2600.0 3300.0
-1500.0 1900.0 2300.0 2400.0 2800.0 3300.0
-1400.0 1600.0 2400.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2400.0 2500.0 3100.0 3300.0
-1500.0 1600.0 2400.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2100.0 2300.0 2800.0 3300.0
-1800.0 2100.0 2600.0 3000.0 3400.0 3500.0
-2100.0 2500.0 2900.0 3100.0 3400.0 3500.0
-1700.0 2100.0 2600.0 2700.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2400.0 3200.0 3400.0
-1500.0 1800.0 2400.0 2500.0 3100.0 3400.0
-1600.0 2300.0 2700.0 3000.0 3300.0 3400.0
-1400.0 1600.0 1700.0 2100.0 3100.0 3200.0
-1400.0 1600.0 1700.0 2000.0 3100.0 3200.0
-1600.0 1700.0 1900.0 2200.0 3100.0 3300.0
-1800.0 1900.0 2500.0 2600.0 3000.0 3300.0
-1800.0 2100.0 2600.0 2900.0 3400.0 3500.0
-1800.0 2000.0 2300.0 2900.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2400.0 2900.0 3100.0
-1100.0 1600.0 2500.0 2700.0 3100.0 3400.0
-1200.0 1700.0 2600.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2600.0 2900.0 3300.0 3400.0
-1800.0 2200.0 2700.0 3000.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2600.0 3100.0 3300.0
-1300.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1800.0 2100.0 2800.0 2900.0 3300.0 3400.0
-1700.0 1800.0 2000.0 2400.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2500.0 3100.0 3300.0
-1800.0 2100.0 2300.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2600.0 2700.0 3000.0 3200.0
-1800.0 2000.0 2600.0 2700.0 3000.0 3200.0
-1900.0 2000.0 2500.0 2700.0 3000.0 3200.0
-2000.0 2100.0 2500.0 2600.0 2900.0 3200.0
-1800.0 1900.0 2500.0 2700.0 2900.0 3300.0
-1700.0 1800.0 2500.0 2700.0 3000.0 3300.0
-1800.0 2200.0 2700.0 2800.0 3200.0 3300.0
-1400.0 1600.0 2400.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2300.0 2700.0 2900.0 3100.0
-1400.0 1600.0 2400.0 2700.0 2900.0 3200.0
-1700.0 2300.0 2700.0 3000.0 3300.0 3400.0
-1400.0 1700.0 2400.0 2700.0 3100.0 3300.0
-1400.0 1700.0 2400.0 2700.0 3000.0 3300.0
-1400.0 1700.0 1800.0 2500.0 3000.0 3100.0
-1300.0 1700.0 1900.0 2300.0 3000.0 3100.0
-1400.0 1800.0 1900.0 2400.0 3000.0 3100.0
-1900.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1200.0 1700.0 2200.0 2300.0 2900.0 3100.0
-1300.0 1700.0 2200.0 2400.0 2800.0 3100.0
-1400.0 1700.0 2200.0 2300.0 2800.0 3100.0
-1500.0 1700.0 2200.0 2300.0 2900.0 3200.0
-1500.0 1700.0 2100.0 2300.0 2900.0 3200.0
-1500.0 1700.0 2000.0 2200.0 2900.0 3100.0
-1500.0 1700.0 1900.0 2200.0 3000.0 3200.0
-1500.0 1700.0 1900.0 2300.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2300.0 3100.0 3200.0
-1600.0 1800.0 2300.0 2600.0 3000.0 3100.0
-2000.0 2500.0 2700.0 2900.0 3200.0 3300.0
-2300.0 2500.0 2800.0 3100.0 3200.0 3300.0
-2300.0 2500.0 2600.0 2900.0 3200.0 3300.0
-1500.0 1700.0 2000.0 2400.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2200.0 3100.0 3300.0
-1600.0 1700.0 1800.0 2100.0 3200.0 3300.0
-1300.0 1600.0 2300.0 2500.0 3000.0 3100.0
-1200.0 1800.0 2300.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2300.0 2400.0 2800.0 3200.0
-1400.0 1700.0 2300.0 2400.0 2900.0 3300.0
-1500.0 2000.0 2500.0 2600.0 2800.0 3100.0
-1800.0 2000.0 2200.0 2600.0 3000.0 3200.0
-1400.0 1700.0 1900.0 2100.0 3000.0 3100.0
-1300.0 1600.0 2300.0 2400.0 2900.0 3100.0
-1400.0 1700.0 2300.0 2500.0 3000.0 3200.0
-1500.0 1700.0 2300.0 2600.0 3100.0 3200.0
-1500.0 1800.0 2400.0 2600.0 3100.0 3200.0
-1600.0 1800.0 2000.0 2600.0 2900.0 3100.0
-1500.0 1700.0 1900.0 2600.0 2900.0 3100.0
-1400.0 1600.0 1700.0 2200.0 3100.0 3200.0
-1300.0 1500.0 1700.0 2100.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2700.0 3100.0 3300.0
-1400.0 1700.0 1900.0 2200.0 3000.0 3100.0
-1400.0 1800.0 2000.0 2200.0 3000.0 3100.0
-2100.0 2300.0 2500.0 2700.0 3100.0 3200.0
-1500.0 1900.0 2300.0 2500.0 3000.0 3100.0
-1500.0 1900.0 2200.0 2500.0 2900.0 3100.0
-1500.0 1800.0 2100.0 2500.0 2900.0 3100.0
-1500.0 1700.0 2300.0 2600.0 2800.0 3200.0
-1500.0 1700.0 2300.0 2500.0 3000.0 3100.0
-1400.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1200.0 1500.0 2600.0 2700.0 2900.0 3000.0
-1300.0 1600.0 2500.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2500.0 2600.0 3000.0 3200.0
-1400.0 1700.0 2500.0 2600.0 3000.0 3200.0
-1500.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2400.0 2600.0 2900.0 3200.0
-1400.0 1600.0 2400.0 2700.0 3000.0 3300.0
-1400.0 1500.0 2200.0 2600.0 2900.0 3200.0
-1300.0 1700.0 2400.0 2600.0 3000.0 3300.0
-1800.0 2000.0 2500.0 2600.0 3100.0 3400.0
-1100.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1100.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1100.0 1800.0 2400.0 2600.0 3100.0 3300.0
-1000.0 1800.0 2500.0 2700.0 3200.0 3300.0
-1100.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2500.0 2900.0 3300.0
-1700.0 1900.0 2300.0 2500.0 3000.0 3300.0
-1300.0 1700.0 2100.0 2300.0 3000.0 3200.0
-1300.0 1600.0 2000.0 2200.0 3000.0 3100.0
-1300.0 1600.0 1900.0 2100.0 3000.0 3100.0
-1500.0 1700.0 2400.0 2600.0 2900.0 3100.0
-1500.0 1900.0 2600.0 2700.0 3100.0 3200.0
-2100.0 2400.0 2900.0 3100.0 3300.0 3400.0
-2000.0 2500.0 2900.0 3100.0 3400.0 3500.0
-2000.0 2500.0 2700.0 3000.0 3300.0 3400.0
-1600.0 1900.0 2600.0 2700.0 3100.0 3300.0
-1600.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1100.0 1500.0 1600.0 2200.0 2900.0 3000.0
-1200.0 1500.0 1600.0 2100.0 3000.0 3100.0
-2300.0 2500.0 2900.0 3100.0 3400.0 3500.0
-1500.0 1900.0 2300.0 2400.0 2900.0 3200.0
-1500.0 2000.0 2500.0 2600.0 3100.0 3300.0
-1500.0 1900.0 2400.0 2800.0 3200.0 3300.0
-1100.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1200.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1300.0 1700.0 2400.0 2500.0 3100.0 3200.0
-1600.0 2100.0 2300.0 2600.0 3100.0 3200.0
-1300.0 1800.0 2100.0 2300.0 3200.0 3300.0
-1200.0 1800.0 2100.0 2300.0 3100.0 3200.0
-2100.0 2200.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2300.0 2600.0 2900.0 3200.0 3400.0
-2100.0 2400.0 2700.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2600.0 2700.0 3100.0 3300.0
-2100.0 2400.0 2600.0 3000.0 3300.0 3400.0
-1400.0 1800.0 2300.0 2400.0 3000.0 3200.0
-1500.0 1700.0 1900.0 2400.0 2900.0 3000.0
-1500.0 1600.0 1800.0 2300.0 3100.0 3200.0
-1500.0 1700.0 1800.0 2300.0 3100.0 3200.0
-2100.0 2500.0 2700.0 3000.0 3400.0 3500.0
-2000.0 2400.0 2700.0 2900.0 3400.0 3500.0
-1400.0 1800.0 1900.0 2600.0 3100.0 3200.0
-1400.0 1800.0 2100.0 2300.0 3200.0 3300.0
-1600.0 1800.0 2300.0 2500.0 3000.0 3100.0
-1400.0 2000.0 2400.0 2700.0 3100.0 3200.0
-1400.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1700.0 1800.0 2500.0 2800.0 3100.0 3300.0
-1400.0 1800.0 2400.0 2500.0 2900.0 3300.0
-1400.0 2000.0 2400.0 2500.0 3100.0 3300.0
-1300.0 1600.0 2400.0 2600.0 3200.0 3300.0
-1900.0 2400.0 2900.0 3100.0 3400.0 3500.0
-2000.0 2400.0 2900.0 3100.0 3400.0 3500.0
-900.0 1800.0 2500.0 2600.0 3200.0 3300.0
-900.0 1800.0 2600.0 2700.0 3200.0 3300.0
-1000.0 1700.0 2800.0 2900.0 3200.0 3300.0
-1500.0 1600.0 2200.0 2600.0 2900.0 3200.0
-1600.0 1800.0 2100.0 2500.0 2800.0 3000.0
-1800.0 1900.0 2400.0 2600.0 2900.0 3100.0
-1900.0 2100.0 2600.0 2900.0 3100.0 3300.0
-1800.0 1900.0 2600.0 2800.0 3000.0 3200.0
-1900.0 2100.0 2500.0 2900.0 3200.0 3400.0
-1300.0 1500.0 2400.0 2700.0 2900.0 3100.0
-1300.0 1600.0 2500.0 2600.0 2900.0 3100.0
-1400.0 1600.0 2400.0 2600.0 2900.0 3100.0
-1600.0 1700.0 2500.0 2800.0 2900.0 3200.0
-1700.0 2000.0 2600.0 3000.0 3300.0 3400.0
-1900.0 2200.0 2700.0 2800.0 3200.0 3400.0
-2000.0 2100.0 2700.0 2800.0 3100.0 3300.0
-2000.0 2100.0 2600.0 2800.0 3100.0 3200.0
-1700.0 2000.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2100.0 2300.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2500.0 3200.0 3400.0
-1300.0 1800.0 2300.0 2400.0 3200.0 3400.0
-1300.0 1900.0 2300.0 2500.0 3200.0 3300.0
-2000.0 2300.0 2600.0 2700.0 3000.0 3300.0
-1800.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1800.0 2500.0 2700.0 3100.0 3300.0
-1200.0 1500.0 2500.0 2900.0 3100.0 3200.0
-1400.0 1600.0 2500.0 2700.0 2900.0 3100.0
-2100.0 2400.0 2700.0 2800.0 3100.0 3300.0
-1600.0 2100.0 2400.0 2800.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2600.0 3100.0 3200.0
-1300.0 1500.0 2300.0 2600.0 3100.0 3300.0
-2000.0 2200.0 2700.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2700.0 2800.0 3300.0 3400.0
-1800.0 2400.0 2700.0 3000.0 3400.0 3500.0
-1900.0 2400.0 2800.0 3000.0 3400.0 3500.0
-2000.0 2100.0 2600.0 2800.0 3000.0 3300.0
-2100.0 2200.0 2700.0 2800.0 3000.0 3300.0
-1500.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1300.0 2000.0 2200.0 2500.0 3000.0 3100.0
-1800.0 2100.0 2300.0 2500.0 3100.0 3300.0
-1500.0 1800.0 2500.0 2800.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2600.0 3200.0 3400.0
-1400.0 1700.0 2300.0 2400.0 3200.0 3400.0
-1100.0 1800.0 2300.0 2400.0 3300.0 3400.0
-1000.0 1900.0 2400.0 2500.0 3100.0 3400.0
-1600.0 1800.0 2200.0 2300.0 3100.0 3300.0
-1500.0 1600.0 2300.0 2400.0 3100.0 3300.0
-1500.0 1600.0 2200.0 2300.0 3200.0 3400.0
-1400.0 1800.0 2300.0 2700.0 3000.0 3300.0
-1400.0 1800.0 2100.0 2300.0 2800.0 3200.0
-1400.0 1800.0 2100.0 2500.0 2900.0 3200.0
-1200.0 1600.0 1700.0 2100.0 3000.0 3100.0
-1200.0 1600.0 1900.0 2400.0 3000.0 3200.0
-1100.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1100.0 2000.0 2400.0 2700.0 3100.0 3200.0
-1200.0 1400.0 2400.0 2600.0 2900.0 3200.0
-1300.0 1400.0 2300.0 2400.0 2800.0 3300.0
-1300.0 1500.0 2300.0 2400.0 2900.0 3200.0
-1300.0 1600.0 2400.0 2500.0 2800.0 3200.0
-1300.0 1600.0 2300.0 2500.0 2900.0 3200.0
-1300.0 1500.0 1600.0 2100.0 2800.0 2900.0
-1500.0 1800.0 2500.0 2700.0 3200.0 3400.0
-1400.0 1700.0 2300.0 2500.0 2900.0 3100.0
-1300.0 1700.0 2400.0 2500.0 3000.0 3200.0
-1200.0 1600.0 2500.0 2600.0 3100.0 3400.0
-1100.0 1700.0 2500.0 2600.0 3100.0 3400.0
-1400.0 1800.0 2200.0 2300.0 2600.0 3000.0
-1300.0 1800.0 2200.0 2300.0 2500.0 3000.0
-1400.0 1800.0 2300.0 2700.0 3000.0 3200.0
-1300.0 1500.0 2300.0 2400.0 2900.0 3100.0
-1300.0 1600.0 2400.0 2500.0 3000.0 3200.0
-1200.0 1600.0 2400.0 2600.0 3100.0 3300.0
-1200.0 1500.0 2600.0 2700.0 3100.0 3300.0
-1200.0 1500.0 2500.0 2700.0 2900.0 3200.0
-1400.0 1600.0 2300.0 2500.0 3100.0 3300.0
-1400.0 1600.0 2000.0 2200.0 2900.0 3000.0
-1300.0 1500.0 1800.0 1900.0 2800.0 2900.0
-1200.0 1600.0 1700.0 2200.0 2900.0 3000.0
-1300.0 1700.0 1800.0 2100.0 2900.0 3000.0
-1500.0 1700.0 2100.0 2400.0 2600.0 3100.0
-1500.0 2000.0 2500.0 2600.0 3000.0 3200.0
-1700.0 2000.0 2200.0 2600.0 2900.0 3200.0
-1700.0 2200.0 2600.0 2700.0 3100.0 3300.0
-1600.0 1700.0 2400.0 2500.0 3000.0 3400.0
-1900.0 2000.0 2100.0 2300.0 3300.0 3400.0
-1700.0 1900.0 2400.0 2500.0 3100.0 3300.0
-1500.0 1800.0 2200.0 2300.0 3100.0 3400.0
-1900.0 2300.0 2500.0 3000.0 3300.0 3400.0
-1500.0 1700.0 2100.0 2300.0 3000.0 3300.0
-1700.0 1900.0 2200.0 2400.0 2700.0 3200.0
-1800.0 1900.0 2200.0 2300.0 2700.0 3100.0
-1700.0 1900.0 2100.0 2300.0 2700.0 3100.0
-1700.0 2000.0 2600.0 2800.0 3100.0 3300.0
-1200.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1300.0 1900.0 2200.0 2500.0 3000.0 3100.0
-1500.0 1600.0 2300.0 2500.0 3000.0 3200.0
-1400.0 1500.0 2300.0 2500.0 3000.0 3200.0
-1300.0 1700.0 2100.0 2400.0 3100.0 3200.0
-1500.0 1600.0 2200.0 2500.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2300.0 3100.0 3400.0
-1400.0 1600.0 2100.0 2300.0 2900.0 3000.0
-1400.0 1600.0 2000.0 2200.0 2800.0 2900.0
-1400.0 1800.0 2200.0 2500.0 3100.0 3300.0
-1400.0 1800.0 2100.0 2400.0 3100.0 3300.0
-1400.0 1700.0 2000.0 2400.0 3000.0 3200.0
-1900.0 2100.0 2300.0 2500.0 2800.0 3100.0
-1900.0 2100.0 2300.0 2500.0 2900.0 3100.0
-1400.0 1600.0 2100.0 2400.0 3000.0 3200.0
-1400.0 1600.0 2000.0 2300.0 3000.0 3200.0
-1600.0 2000.0 2200.0 2600.0 2900.0 3200.0
-1600.0 2000.0 2200.0 2600.0 3000.0 3300.0
-1300.0 1900.0 2200.0 2400.0 3000.0 3200.0
-1700.0 2000.0 2300.0 2700.0 3000.0 3300.0
-1000.0 1600.0 2600.0 2700.0 3200.0 3300.0
-1100.0 1700.0 2600.0 2700.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2400.0 3300.0 3400.0
-1900.0 2100.0 2300.0 2500.0 3100.0 3200.0
-1400.0 1700.0 2200.0 2500.0 3300.0 3400.0
-1400.0 1900.0 2200.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2700.0 3000.0 3200.0
-1600.0 1800.0 2100.0 2400.0 3000.0 3200.0
-1700.0 1800.0 2100.0 2400.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2500.0 2900.0 3300.0
-1800.0 1900.0 2200.0 2500.0 2900.0 3300.0
-1800.0 1900.0 2200.0 2500.0 2900.0 3200.0
-1700.0 1900.0 2200.0 2400.0 3000.0 3300.0
-1700.0 1900.0 2200.0 2400.0 2600.0 3000.0
-1500.0 1800.0 2500.0 2600.0 3200.0 3300.0
-1600.0 1700.0 2500.0 2600.0 3000.0 3200.0
-1600.0 1700.0 2400.0 2500.0 3100.0 3200.0
-1600.0 1700.0 2500.0 2600.0 3100.0 3200.0
-1600.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1800.0 1900.0 2500.0 2600.0 3000.0 3200.0
-1900.0 2400.0 2700.0 3000.0 3300.0 3500.0
-1900.0 2400.0 2700.0 3100.0 3300.0 3400.0
-2000.0 2400.0 2600.0 3000.0 3300.0 3400.0
-1800.0 2500.0 2700.0 2900.0 3300.0 3400.0
-1800.0 2400.0 2700.0 2900.0 3400.0 3500.0
-1900.0 2400.0 2700.0 3000.0 3200.0 3300.0
-1600.0 1800.0 2400.0 2500.0 3000.0 3300.0
-1700.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1300.0 1800.0 2000.0 2500.0 3100.0 3200.0
-1500.0 1800.0 2300.0 2400.0 3000.0 3100.0
-2100.0 2500.0 2700.0 2900.0 3100.0 3300.0
-1800.0 2000.0 2200.0 2500.0 2800.0 3100.0
-1400.0 1700.0 1900.0 2300.0 2800.0 2900.0
-1800.0 2000.0 2300.0 2700.0 3000.0 3300.0
-1800.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1700.0 1800.0 2400.0 2800.0 3100.0 3300.0
-1500.0 1700.0 2500.0 2600.0 2900.0 3300.0
-1400.0 1500.0 2300.0 2500.0 2900.0 3300.0
-1500.0 1700.0 2200.0 2500.0 2900.0 3200.0
-1700.0 1900.0 2100.0 2300.0 3100.0 3300.0
-1400.0 1800.0 2200.0 2400.0 2700.0 3100.0
-1300.0 1500.0 1700.0 1900.0 2800.0 3000.0
-1300.0 1500.0 1700.0 1900.0 2900.0 3000.0
-1100.0 1600.0 2300.0 2500.0 3100.0 3200.0
-1000.0 1600.0 2300.0 2500.0 3200.0 3300.0
-1000.0 1700.0 2300.0 2400.0 3200.0 3300.0
-900.0 1700.0 2300.0 2400.0 3200.0 3300.0
-900.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1200.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1200.0 1700.0 2200.0 2300.0 3100.0 3200.0
-1300.0 1700.0 2200.0 2300.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2300.0 3100.0 3200.0
-1500.0 1700.0 2200.0 2300.0 3000.0 3200.0
-1500.0 1600.0 2200.0 2300.0 2900.0 3200.0
-1600.0 2000.0 2300.0 2400.0 3100.0 3300.0
-1600.0 2100.0 2300.0 2400.0 2700.0 3300.0
-1600.0 1800.0 2100.0 2300.0 2900.0 3000.0
-1400.0 1600.0 1700.0 2300.0 2900.0 3000.0
-1600.0 1800.0 2100.0 2300.0 3000.0 3100.0
-1600.0 1700.0 2000.0 2200.0 3000.0 3100.0
-1500.0 1600.0 2300.0 2400.0 2900.0 3100.0
-1500.0 1600.0 2400.0 2500.0 3000.0 3200.0
-1800.0 2100.0 2600.0 2700.0 3100.0 3200.0
-1500.0 1600.0 1900.0 2300.0 2900.0 3100.0
-1500.0 1700.0 2300.0 2700.0 3100.0 3200.0
-1500.0 2100.0 2500.0 2700.0 3100.0 3300.0
-1000.0 1500.0 2400.0 2500.0 3100.0 3300.0
-1200.0 1400.0 2400.0 2500.0 2900.0 3300.0
-1300.0 1700.0 2200.0 2400.0 2900.0 3000.0
-1200.0 2000.0 2400.0 2500.0 3000.0 3200.0
-1200.0 1900.0 2400.0 2500.0 3100.0 3300.0
-1300.0 1800.0 2400.0 2500.0 3100.0 3400.0
-1500.0 1800.0 2300.0 2400.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2400.0 3000.0 3200.0
-1600.0 1900.0 2100.0 2400.0 2900.0 3200.0
-1400.0 1600.0 2200.0 2400.0 2900.0 3100.0
-1500.0 1700.0 2200.0 2400.0 3000.0 3100.0
-1400.0 1600.0 2300.0 2400.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2300.0 2900.0 3200.0
-1600.0 1700.0 2000.0 2200.0 3000.0 3200.0
-1600.0 1800.0 2100.0 2400.0 2900.0 3200.0
-1600.0 1700.0 2100.0 2300.0 2900.0 3200.0
-1400.0 1600.0 2100.0 2400.0 3200.0 3300.0
-1200.0 1600.0 2100.0 2300.0 3100.0 3200.0
-1600.0 2100.0 2300.0 2500.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2300.0 2400.0 2900.0 3200.0
-1400.0 1500.0 2100.0 2400.0 2700.0 3100.0
-1200.0 1400.0 2100.0 2200.0 3000.0 3300.0
-1300.0 1800.0 2200.0 2300.0 2800.0 3200.0
-1300.0 1700.0 2200.0 2300.0 2800.0 3300.0
-1400.0 1800.0 2200.0 2300.0 2800.0 3200.0
-1800.0 2100.0 2500.0 3000.0 3200.0 3400.0
-1700.0 1900.0 2200.0 2500.0 3100.0 3300.0
-1800.0 1900.0 2100.0 2400.0 3200.0 3300.0
-1500.0 1600.0 2200.0 2300.0 3200.0 3300.0
-1400.0 1700.0 2200.0 2300.0 3100.0 3300.0
-1400.0 1900.0 2200.0 2600.0 3100.0 3300.0
-1600.0 1900.0 2500.0 2900.0 3200.0 3300.0
-1400.0 1900.0 2400.0 2700.0 3100.0 3200.0
-1400.0 1600.0 2200.0 2300.0 2900.0 3100.0
-1600.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1800.0 2000.0 2400.0 2900.0 3100.0 3200.0
-1900.0 2000.0 2500.0 2900.0 3100.0 3300.0
-1500.0 1600.0 2100.0 2200.0 3000.0 3300.0
-1500.0 1600.0 2100.0 2300.0 2900.0 3200.0
-1300.0 1500.0 2200.0 2300.0 2800.0 3100.0
-1100.0 1900.0 2500.0 2700.0 3100.0 3200.0
-1300.0 1800.0 2300.0 2700.0 3100.0 3200.0
-1100.0 1700.0 2200.0 2600.0 3000.0 3200.0
-1300.0 1600.0 1900.0 2100.0 3000.0 3200.0
-1300.0 1500.0 1800.0 1900.0 3000.0 3100.0
-1100.0 1400.0 2500.0 2600.0 3000.0 3300.0
-1300.0 1500.0 2400.0 2600.0 2900.0 3300.0
-1700.0 1900.0 2300.0 2400.0 3000.0 3300.0
-1600.0 1800.0 2100.0 2400.0 2800.0 3100.0
-1500.0 1700.0 2000.0 2500.0 2800.0 3000.0
-1400.0 1700.0 2200.0 2500.0 2900.0 3100.0
-1300.0 1500.0 2300.0 2600.0 3000.0 3300.0
-1000.0 1600.0 2200.0 2500.0 3000.0 3100.0
-1000.0 1500.0 2500.0 2600.0 3100.0 3300.0
-1000.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1000.0 1700.0 2600.0 2700.0 3200.0 3300.0
-2000.0 2400.0 2800.0 3000.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2700.0 3100.0 3200.0
-1800.0 1900.0 2400.0 2700.0 3000.0 3300.0
-1700.0 2100.0 2300.0 2500.0 3000.0 3200.0
-1200.0 1400.0 1500.0 2100.0 3100.0 3200.0
-1400.0 1600.0 1700.0 2200.0 3000.0 3200.0
-1600.0 1800.0 1900.0 2200.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2300.0 3000.0 3200.0
-1900.0 2000.0 2400.0 2500.0 3000.0 3300.0
-1800.0 1900.0 2400.0 2500.0 2900.0 3300.0
-1800.0 1900.0 2300.0 2500.0 3100.0 3400.0
-1800.0 2000.0 2400.0 2600.0 3200.0 3400.0
-1400.0 1600.0 2100.0 2200.0 3100.0 3400.0
-1500.0 1700.0 1900.0 2500.0 3000.0 3200.0
-1300.0 1400.0 2200.0 2500.0 2900.0 3200.0
-1300.0 1700.0 2100.0 2600.0 3100.0 3300.0
-1900.0 2100.0 2400.0 2700.0 3200.0 3400.0
-1700.0 2000.0 2300.0 2500.0 3000.0 3300.0
-1600.0 1700.0 2100.0 2600.0 3000.0 3200.0
-1400.0 1600.0 1700.0 2000.0 3000.0 3100.0
-1300.0 1500.0 1600.0 2000.0 3000.0 3100.0
-1400.0 1600.0 2100.0 2200.0 2700.0 3200.0
-1300.0 1600.0 1700.0 2300.0 3100.0 3300.0
-1500.0 1700.0 2200.0 2500.0 3100.0 3200.0
-2100.0 2200.0 2600.0 2900.0 3200.0 3400.0
-2100.0 2300.0 2700.0 3000.0 3300.0 3400.0
-1900.0 2300.0 2800.0 3100.0 3300.0 3500.0
-1900.0 2300.0 2700.0 3100.0 3400.0 3500.0
-1900.0 2300.0 2700.0 3100.0 3300.0 3400.0
-1400.0 1800.0 2200.0 2300.0 2900.0 3200.0
-1400.0 1600.0 2100.0 2300.0 2800.0 3300.0
-1300.0 1700.0 2200.0 2300.0 2800.0 3200.0
-1300.0 1600.0 2200.0 2300.0 2900.0 3300.0
-1400.0 1800.0 2200.0 2600.0 3100.0 3300.0
-1700.0 2100.0 2400.0 2700.0 3000.0 3200.0
-1300.0 1800.0 2200.0 2500.0 3000.0 3300.0
-1900.0 2000.0 2500.0 2600.0 2900.0 3300.0
-2100.0 2200.0 2400.0 2600.0 2900.0 3200.0
-2100.0 2200.0 2400.0 2600.0 3000.0 3200.0
-2000.0 2100.0 2400.0 2500.0 3000.0 3200.0
-1800.0 2000.0 2200.0 2400.0 3100.0 3200.0
-1400.0 2000.0 2300.0 2400.0 3000.0 3100.0
-1300.0 1600.0 2100.0 2300.0 2700.0 3200.0
-1200.0 1800.0 2200.0 2400.0 3200.0 3400.0
-1200.0 1800.0 2300.0 2400.0 3200.0 3400.0
-1200.0 1900.0 2300.0 2400.0 3100.0 3400.0
-1700.0 1800.0 2100.0 2300.0 2800.0 3200.0
-1500.0 1600.0 2200.0 2300.0 2900.0 3300.0
-1500.0 1600.0 2100.0 2300.0 2800.0 3200.0
-1500.0 1600.0 2000.0 2200.0 2700.0 3200.0
-1400.0 1900.0 2200.0 2600.0 3200.0 3300.0
-1400.0 1600.0 2100.0 2200.0 2800.0 3200.0
-1900.0 2100.0 2300.0 2600.0 3100.0 3300.0
-2000.0 2300.0 2600.0 2800.0 3200.0 3400.0
-1700.0 1800.0 2300.0 2500.0 2700.0 3200.0
-1700.0 1800.0 2300.0 2500.0 2700.0 3100.0
-1800.0 1900.0 2400.0 2500.0 2700.0 3100.0
-1700.0 1800.0 2400.0 2500.0 2800.0 3200.0
-1600.0 1800.0 2500.0 2600.0 2900.0 3100.0
-1500.0 1800.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1500.0 2100.0 2300.0 2900.0 3300.0
-1400.0 1600.0 2100.0 2300.0 3000.0 3300.0
-1600.0 1700.0 2200.0 2500.0 3100.0 3400.0
-1600.0 2000.0 2200.0 2400.0 2900.0 3100.0
-2000.0 2200.0 2600.0 2900.0 3200.0 3400.0
-1200.0 1400.0 2200.0 2300.0 3100.0 3300.0
-1300.0 1500.0 2200.0 2300.0 3100.0 3300.0
-1700.0 1800.0 2200.0 2300.0 3100.0 3400.0
-1800.0 1900.0 2200.0 2300.0 2900.0 3300.0
-1800.0 2000.0 2400.0 2700.0 3100.0 3400.0
-1600.0 1700.0 2000.0 2100.0 2700.0 3100.0
-1700.0 1900.0 2200.0 2300.0 2900.0 3200.0
-2200.0 2500.0 2700.0 2800.0 3100.0 3300.0
-1600.0 1700.0 2200.0 2300.0 2900.0 3100.0
-1400.0 1500.0 1600.0 2000.0 3000.0 3200.0
-1500.0 1700.0 1900.0 2400.0 3000.0 3200.0
-1900.0 2200.0 2500.0 2900.0 3200.0 3300.0
-1900.0 2400.0 2600.0 2900.0 3300.0 3400.0
-1800.0 2100.0 2200.0 2400.0 3000.0 3300.0
-1400.0 1600.0 1700.0 2300.0 3200.0 3300.0
-1400.0 1600.0 1900.0 2500.0 3200.0 3300.0
-1700.0 2100.0 2700.0 3000.0 3300.0 3400.0
-1400.0 1800.0 2300.0 2700.0 3100.0 3200.0
-1400.0 1600.0 2300.0 2700.0 3000.0 3200.0
-1400.0 2000.0 2200.0 2500.0 3100.0 3300.0
-1600.0 2100.0 2400.0 2900.0 3200.0 3400.0
-1400.0 1600.0 1800.0 2600.0 3300.0 3400.0
-1400.0 1500.0 1700.0 2200.0 3200.0 3300.0
-1400.0 1500.0 1700.0 2100.0 3100.0 3200.0
-1300.0 1500.0 2200.0 2400.0 2800.0 3100.0
-1300.0 1600.0 1800.0 2400.0 3000.0 3100.0
-1400.0 1600.0 2000.0 2200.0 3000.0 3300.0
-1500.0 1600.0 2100.0 2400.0 3100.0 3300.0
-1500.0 1700.0 2100.0 2300.0 2700.0 3100.0
-1500.0 1600.0 2000.0 2200.0 2600.0 3100.0
-1400.0 1500.0 2000.0 2300.0 3100.0 3300.0
-1400.0 1500.0 2000.0 2200.0 3100.0 3300.0
-1600.0 1800.0 2200.0 2300.0 3000.0 3200.0
-1400.0 1700.0 2100.0 2500.0 2900.0 3100.0
-1400.0 1800.0 2200.0 2400.0 2900.0 3000.0
-1500.0 1800.0 2300.0 2500.0 3000.0 3200.0
-2000.0 2300.0 2800.0 3100.0 3400.0 3500.0
-2000.0 2500.0 2800.0 2900.0 3200.0 3300.0
-1400.0 2000.0 2300.0 2600.0 3000.0 3300.0
-1600.0 1900.0 2300.0 2700.0 3200.0 3400.0
-2000.0 2400.0 2800.0 2900.0 3300.0 3400.0
-1200.0 1400.0 2000.0 2200.0 3200.0 3400.0
-1200.0 1600.0 2400.0 2500.0 2900.0 3200.0
-1500.0 1600.0 2300.0 2400.0 2800.0 3200.0
-1100.0 1600.0 2200.0 2300.0 3300.0 3400.0
-1300.0 1600.0 2200.0 2400.0 3000.0 3300.0
-1300.0 1600.0 2200.0 2400.0 2700.0 3200.0
-1400.0 1700.0 2300.0 2500.0 2700.0 3100.0
-1500.0 1700.0 2400.0 2500.0 2800.0 3100.0
-1800.0 2000.0 2200.0 2300.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2400.0 2900.0 3200.0
-1700.0 1900.0 2200.0 2400.0 2900.0 3300.0
-1300.0 1700.0 2200.0 2300.0 3200.0 3400.0
-1500.0 1600.0 2300.0 2400.0 3000.0 3400.0
-1600.0 1900.0 2400.0 2800.0 3200.0 3400.0
-1500.0 1600.0 2300.0 2400.0 2900.0 3300.0
-1600.0 1700.0 2300.0 2400.0 2800.0 3300.0
-1800.0 2000.0 2200.0 2500.0 3000.0 3300.0
-1900.0 2000.0 2300.0 2500.0 2800.0 3100.0
-1600.0 1700.0 2400.0 2600.0 3100.0 3400.0
-1600.0 1800.0 2400.0 2700.0 3200.0 3300.0
-1600.0 1900.0 2400.0 2700.0 3200.0 3400.0
-1500.0 1800.0 2200.0 2500.0 3200.0 3400.0
-1200.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1900.0 2000.0 2400.0 2600.0 3100.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3000.0 3400.0
-1400.0 2000.0 2300.0 2400.0 2600.0 3100.0
-1800.0 1900.0 2100.0 2200.0 3300.0 3400.0
-1400.0 1600.0 1700.0 2300.0 3300.0 3400.0
-1400.0 1600.0 1700.0 2200.0 3300.0 3400.0
-1400.0 1600.0 1700.0 2300.0 3200.0 3400.0
-1600.0 1800.0 2000.0 2300.0 2900.0 3100.0
-1700.0 1800.0 2000.0 2300.0 2900.0 3100.0
-1600.0 1800.0 2100.0 2300.0 2800.0 3100.0
-1500.0 1700.0 2100.0 2300.0 2800.0 3100.0
-1500.0 1600.0 2100.0 2300.0 2700.0 3100.0
-1500.0 1600.0 2100.0 2200.0 2700.0 3100.0
-1400.0 1800.0 2300.0 2400.0 2800.0 3100.0
-1400.0 1600.0 2300.0 2400.0 2900.0 3300.0
-1200.0 1700.0 2200.0 2300.0 2900.0 3200.0
-1400.0 1500.0 2100.0 2400.0 3200.0 3400.0
-1700.0 2100.0 2400.0 2500.0 2900.0 3100.0
-1500.0 1700.0 2000.0 2400.0 3000.0 3200.0
-1400.0 1900.0 2200.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2700.0 3000.0 3100.0
-1600.0 1800.0 2100.0 2500.0 2800.0 3100.0
-2000.0 2300.0 2500.0 2800.0 3000.0 3100.0
-1900.0 2400.0 2700.0 2800.0 3100.0 3200.0
-1800.0 2300.0 2700.0 2800.0 3100.0 3200.0
-1700.0 2400.0 2700.0 2800.0 3200.0 3300.0
-1700.0 2400.0 2700.0 2800.0 3100.0 3200.0
-1600.0 2400.0 2700.0 2800.0 3100.0 3200.0
-1600.0 2000.0 2200.0 2700.0 3100.0 3200.0
-1800.0 2200.0 2600.0 2800.0 3100.0 3400.0
-1800.0 2200.0 2600.0 3000.0 3200.0 3400.0
-1800.0 2200.0 2300.0 2700.0 3200.0 3300.0
-1600.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2200.0 2500.0 2800.0 3000.0
-2000.0 2400.0 2800.0 3100.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2000.0 2600.0 3100.0
-1400.0 1600.0 1900.0 2000.0 2500.0 3100.0
-1400.0 1600.0 1800.0 2000.0 2500.0 3100.0
-1400.0 1500.0 1800.0 1900.0 2500.0 3100.0
-1400.0 1500.0 1800.0 1900.0 2600.0 3200.0
-1400.0 1500.0 1700.0 2000.0 2900.0 3200.0
-1300.0 1700.0 2100.0 2600.0 3100.0 3200.0
-1200.0 1700.0 2200.0 2500.0 3100.0 3200.0
-1800.0 2000.0 2500.0 2600.0 3000.0 3200.0
-1700.0 1900.0 2200.0 2700.0 2900.0 3200.0
-1500.0 1700.0 2100.0 2600.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2400.0 2700.0 3100.0
-1600.0 1900.0 2200.0 2600.0 2800.0 3100.0
-1600.0 1800.0 2100.0 2500.0 3000.0 3100.0
-1600.0 1800.0 2000.0 2200.0 2600.0 3100.0
-1200.0 1400.0 2300.0 2700.0 2800.0 3100.0
-1300.0 1600.0 2100.0 2600.0 3100.0 3300.0
-1400.0 1600.0 2100.0 2500.0 2700.0 3000.0
-1300.0 1600.0 2300.0 2600.0 3000.0 3300.0
-1300.0 1700.0 2300.0 2700.0 3000.0 3300.0
-1400.0 1600.0 2000.0 2500.0 2800.0 3000.0
-1800.0 2000.0 2200.0 2600.0 2800.0 3100.0
-1800.0 1900.0 2400.0 2600.0 2800.0 3100.0
-1500.0 1700.0 2200.0 2700.0 2900.0 3100.0
-1400.0 1700.0 2300.0 2700.0 3000.0 3100.0
-1700.0 2200.0 2500.0 2900.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2700.0 3000.0 3200.0
-1700.0 2000.0 2600.0 2700.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2500.0 3100.0 3200.0
-1500.0 2000.0 2200.0 2600.0 3000.0 3100.0
-1500.0 1800.0 2000.0 2800.0 3200.0 3300.0
-1700.0 1900.0 2500.0 2600.0 2900.0 3200.0
-1800.0 2000.0 2400.0 2600.0 3000.0 3100.0
-1400.0 1700.0 2100.0 2500.0 2700.0 3000.0
-1500.0 1900.0 2200.0 2400.0 2800.0 3200.0
-1300.0 1500.0 2100.0 2400.0 3100.0 3300.0
-1200.0 1600.0 2200.0 2500.0 3200.0 3300.0
-1300.0 1800.0 2300.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1300.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1500.0 1700.0 2100.0 2700.0 3100.0 3200.0
-1500.0 1700.0 2100.0 2800.0 3100.0 3200.0
-1700.0 2000.0 2200.0 2500.0 3100.0 3200.0
-1800.0 1900.0 2100.0 2300.0 2600.0 3100.0
-1500.0 1600.0 1800.0 2000.0 2500.0 3100.0
-1700.0 2000.0 2200.0 2400.0 3100.0 3300.0
-1600.0 1800.0 2000.0 2400.0 2900.0 3200.0
-1400.0 1500.0 1700.0 1900.0 3000.0 3200.0
-1600.0 1700.0 2000.0 2600.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1700.0 2200.0 2600.0 2800.0 3100.0 3200.0
-1600.0 2200.0 2500.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2200.0 2500.0 3000.0 3100.0
-1600.0 2000.0 2500.0 2800.0 3100.0 3300.0
-1700.0 2100.0 2400.0 2900.0 3200.0 3300.0
-1800.0 2000.0 2400.0 2700.0 3000.0 3100.0
-1800.0 2000.0 2500.0 2700.0 3000.0 3100.0
-1600.0 1900.0 2300.0 2600.0 3000.0 3100.0
-1500.0 1900.0 2100.0 2500.0 3000.0 3200.0
-1900.0 2300.0 2500.0 2600.0 2900.0 3100.0
-2000.0 2200.0 2500.0 2800.0 3300.0 3400.0
-2100.0 2300.0 2600.0 2800.0 3200.0 3400.0
-2200.0 2400.0 2800.0 2900.0 3200.0 3300.0
-2100.0 2500.0 2700.0 2900.0 3200.0 3300.0
-1800.0 2300.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2300.0 2500.0 2700.0 3000.0 3200.0
-1400.0 1800.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1600.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1700.0 2200.0 2700.0 3100.0 3300.0
-1500.0 1700.0 2200.0 2700.0 3000.0 3200.0
-1500.0 1700.0 2100.0 2700.0 2900.0 3100.0
-1800.0 2300.0 2600.0 2700.0 3200.0 3300.0
-1800.0 2400.0 2700.0 2800.0 3300.0 3400.0
-1800.0 2500.0 2700.0 2900.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2400.0 2800.0 3000.0
-1600.0 1800.0 2200.0 2400.0 2800.0 3100.0
-1900.0 2000.0 2200.0 2700.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2700.0 3100.0 3300.0
-2000.0 2200.0 2500.0 2600.0 2900.0 3100.0
-1400.0 1900.0 2400.0 2700.0 3000.0 3300.0
-1500.0 1900.0 2300.0 2700.0 3000.0 3300.0
-1300.0 1800.0 2100.0 2400.0 3100.0 3200.0
-1500.0 1800.0 2200.0 2500.0 2700.0 3100.0
-1600.0 2000.0 2200.0 2600.0 2900.0 3100.0
-1700.0 2100.0 2700.0 3000.0 3200.0 3300.0
-1600.0 1800.0 2600.0 2800.0 3200.0 3300.0
-1200.0 1600.0 2200.0 2600.0 3000.0 3300.0
-1800.0 2300.0 2600.0 2800.0 3100.0 3200.0
-1800.0 2400.0 2700.0 2800.0 3100.0 3200.0
-1700.0 2300.0 2700.0 2800.0 3100.0 3200.0
-1900.0 2200.0 2700.0 2900.0 3100.0 3300.0
-1600.0 2200.0 2500.0 2700.0 3000.0 3200.0
-1600.0 2000.0 2500.0 2700.0 3000.0 3100.0
-1800.0 2200.0 2500.0 2600.0 3100.0 3200.0
-1800.0 2500.0 2700.0 2800.0 3200.0 3300.0
-1700.0 2300.0 2600.0 2700.0 3100.0 3200.0
-1400.0 1600.0 2000.0 2500.0 2900.0 3100.0
-1700.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1200.0 1400.0 1700.0 1800.0 2700.0 3200.0
-1500.0 1700.0 2000.0 2400.0 2700.0 3000.0
-1600.0 1800.0 2300.0 2400.0 2800.0 3100.0
-1800.0 2000.0 2400.0 2500.0 2900.0 3100.0
-1700.0 2000.0 2400.0 2600.0 2900.0 3000.0
-1500.0 1900.0 2300.0 2600.0 2900.0 3100.0
-1500.0 1900.0 2200.0 2600.0 2900.0 3100.0
-1500.0 1900.0 2100.0 2400.0 2900.0 3100.0
-1700.0 2300.0 2500.0 2800.0 3100.0 3200.0
-1600.0 2400.0 2700.0 2800.0 3200.0 3300.0
-1500.0 2400.0 2800.0 2900.0 3200.0 3300.0
-1200.0 1700.0 2300.0 2400.0 3000.0 3200.0
-1300.0 1900.0 2400.0 2600.0 3200.0 3300.0
-1500.0 2100.0 2300.0 2700.0 3100.0 3300.0
-1700.0 2200.0 2500.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2000.0 2500.0 3000.0 3300.0
-1600.0 2000.0 2400.0 2500.0 3100.0 3300.0
-1400.0 1900.0 2300.0 2500.0 3200.0 3400.0
-1100.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1100.0 2200.0 2400.0 2700.0 3200.0 3300.0
-1200.0 2000.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2500.0 2900.0 3000.0
-1500.0 1900.0 2200.0 2400.0 2600.0 3100.0
-1800.0 2000.0 2500.0 2600.0 2900.0 3200.0
-2000.0 2100.0 2500.0 2700.0 3100.0 3300.0
-1800.0 2100.0 2400.0 2600.0 3000.0 3400.0
-1600.0 1800.0 2200.0 2400.0 3300.0 3400.0
-1400.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1600.0 1900.0 2200.0 2700.0 3200.0 3300.0
-1500.0 1900.0 2300.0 2400.0 3000.0 3200.0
-1500.0 1900.0 2300.0 2500.0 2900.0 3200.0
-2200.0 2500.0 2900.0 3000.0 3300.0 3400.0
-1500.0 1800.0 2400.0 2700.0 3300.0 3400.0
-1400.0 1800.0 2100.0 2700.0 3100.0 3200.0
-1400.0 1600.0 2000.0 2700.0 3100.0 3200.0
-1900.0 2000.0 2300.0 2800.0 3100.0 3200.0
-2100.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2500.0 2900.0 3100.0
-1800.0 1900.0 2200.0 2700.0 3200.0 3300.0
-1800.0 2200.0 2800.0 3000.0 3300.0 3500.0
-1800.0 2300.0 2600.0 2900.0 3300.0 3500.0
-2100.0 2400.0 2700.0 3000.0 3300.0 3500.0
-1600.0 1800.0 2200.0 2400.0 2900.0 3300.0
-1500.0 1900.0 2500.0 2600.0 2900.0 3100.0
-1600.0 2100.0 2400.0 2600.0 2800.0 3100.0
-1500.0 1600.0 2100.0 2400.0 2900.0 3300.0
-1500.0 1700.0 2200.0 2400.0 2900.0 3300.0
-1400.0 1500.0 2300.0 2500.0 3200.0 3300.0
-1400.0 1700.0 2400.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2400.0 2500.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2400.0 2900.0 3200.0
-1700.0 2400.0 2600.0 2900.0 3300.0 3400.0
-1600.0 1700.0 2100.0 2300.0 2700.0 3200.0
-1800.0 2300.0 2600.0 2900.0 3100.0 3300.0
-1800.0 2400.0 2600.0 2900.0 3300.0 3400.0
-1900.0 2300.0 2700.0 2900.0 3200.0 3400.0
-1400.0 1800.0 2200.0 2500.0 3300.0 3400.0
-1300.0 1900.0 2300.0 2700.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2400.0 2500.0 3000.0 3300.0
-1900.0 2300.0 2600.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2700.0 2900.0 3100.0 3300.0
-1600.0 1800.0 2000.0 2500.0 2900.0 3000.0
-1800.0 2100.0 2400.0 2500.0 2900.0 3100.0
-1500.0 1700.0 2400.0 2500.0 2700.0 3000.0
-1400.0 1600.0 2200.0 2500.0 2600.0 3000.0
-1300.0 2100.0 2300.0 2800.0 3100.0 3200.0
-1300.0 2100.0 2200.0 2700.0 3100.0 3200.0
-1500.0 2000.0 2300.0 2500.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2400.0 2800.0 3200.0
-1900.0 2000.0 2300.0 2500.0 2900.0 3300.0
-1600.0 1900.0 2500.0 2800.0 3100.0 3200.0
-1400.0 2000.0 2400.0 2600.0 3000.0 3100.0
-1200.0 1900.0 2000.0 2400.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2000.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2600.0 2900.0 3000.0
-1700.0 1900.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2200.0 2800.0 3000.0 3200.0 3400.0
-2000.0 2300.0 2900.0 3100.0 3300.0 3400.0
-1500.0 2000.0 2300.0 2700.0 3300.0 3400.0
-1200.0 1700.0 2300.0 2500.0 3100.0 3300.0
-1300.0 1800.0 2200.0 2600.0 3200.0 3300.0
-1200.0 2000.0 2200.0 2600.0 3100.0 3200.0
-2000.0 2300.0 2500.0 2900.0 3200.0 3300.0
-2200.0 2300.0 2700.0 3000.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2500.0 2800.0 3000.0
-1200.0 1800.0 2300.0 2400.0 3200.0 3300.0
-1200.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1200.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1600.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1500.0 1700.0 1900.0 2400.0 2800.0 3000.0
-1500.0 1700.0 1900.0 2500.0 2800.0 3000.0
-1500.0 1800.0 2100.0 2700.0 3000.0 3200.0
-2000.0 2200.0 2700.0 3000.0 3300.0 3400.0
-2100.0 2400.0 2800.0 3000.0 3400.0 3500.0
-2000.0 2200.0 2700.0 2900.0 3200.0 3300.0
-2100.0 2500.0 2800.0 3000.0 3400.0 3500.0
-2000.0 2300.0 2600.0 2700.0 3200.0 3300.0
-1900.0 2300.0 2600.0 2700.0 3200.0 3400.0
-1500.0 1800.0 2300.0 2600.0 3000.0 3300.0
-1400.0 1900.0 2400.0 2500.0 2700.0 3000.0
-2200.0 2300.0 2700.0 2900.0 3200.0 3300.0
-2100.0 2300.0 2700.0 2800.0 3200.0 3300.0
-2000.0 2300.0 2500.0 2700.0 3300.0 3400.0
-2300.0 2500.0 2800.0 3100.0 3400.0 3500.0
-2200.0 2600.0 2800.0 3100.0 3300.0 3400.0
-2200.0 2600.0 2700.0 3000.0 3300.0 3400.0
-1900.0 2200.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2400.0 2600.0 2900.0 3100.0
-1700.0 1800.0 2300.0 2500.0 2700.0 3000.0
-1500.0 1800.0 2200.0 2400.0 2800.0 3200.0
-1300.0 2100.0 2400.0 2700.0 3300.0 3400.0
-1200.0 1900.0 2400.0 2600.0 3100.0 3300.0
-1200.0 1500.0 2400.0 2500.0 3100.0 3400.0
-1400.0 1500.0 2400.0 2600.0 3000.0 3400.0
-1500.0 1600.0 2500.0 2600.0 3100.0 3400.0
-1600.0 2100.0 2400.0 2500.0 3100.0 3300.0
-1600.0 2200.0 2400.0 2600.0 3100.0 3300.0
-1800.0 2300.0 2600.0 2900.0 3200.0 3400.0
-2100.0 2200.0 2500.0 2700.0 2900.0 3200.0
-1700.0 2000.0 2300.0 2400.0 2700.0 3000.0
-2000.0 2200.0 2400.0 2700.0 3300.0 3400.0
-1500.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1200.0 1700.0 2200.0 2400.0 3300.0 3400.0
-1400.0 1900.0 2000.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2200.0 2600.0 3200.0 3300.0
-1200.0 2100.0 2300.0 2600.0 3300.0 3400.0
-1100.0 2100.0 2300.0 2600.0 3300.0 3400.0
-1900.0 2100.0 2600.0 2700.0 3100.0 3300.0
-1200.0 1600.0 2100.0 2400.0 3000.0 3300.0
-1200.0 1700.0 2100.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2100.0 2300.0 2600.0 3000.0
-1900.0 2200.0 2300.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2500.0 2900.0 3200.0
-1500.0 1900.0 2100.0 2500.0 2900.0 3100.0
-1300.0 1900.0 2100.0 2400.0 3000.0 3100.0
-1800.0 2400.0 2800.0 3000.0 3400.0 3500.0
-1600.0 2000.0 2300.0 2800.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2400.0 3000.0 3300.0
-1400.0 2100.0 2300.0 2500.0 3200.0 3400.0
-1700.0 2000.0 2500.0 2700.0 3000.0 3300.0
-1800.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1700.0 1900.0 2800.0 3100.0 3200.0
-1300.0 1600.0 1800.0 2600.0 3100.0 3200.0
-1300.0 1500.0 1600.0 2400.0 3100.0 3200.0
-1400.0 1600.0 1700.0 2200.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2500.0 2900.0 3200.0
-1500.0 1900.0 2100.0 2400.0 3200.0 3300.0
-1800.0 2000.0 2100.0 2500.0 3200.0 3300.0
-1400.0 2000.0 2400.0 2500.0 3100.0 3200.0
-1200.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1100.0 1800.0 2300.0 2600.0 3100.0 3300.0
-1400.0 1700.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2300.0 2600.0 3100.0 3200.0
-1500.0 1800.0 2500.0 2700.0 3100.0 3300.0
-1500.0 1900.0 2500.0 2700.0 3000.0 3200.0
-1600.0 1900.0 2500.0 2800.0 3200.0 3400.0
-1600.0 1700.0 2400.0 2700.0 2900.0 3200.0
-1500.0 1600.0 2100.0 2600.0 2800.0 3100.0
-1300.0 1500.0 1700.0 1900.0 3000.0 3100.0
-1400.0 1500.0 2200.0 2400.0 3100.0 3300.0
-1100.0 1400.0 2200.0 2500.0 3200.0 3300.0
-1200.0 1500.0 1700.0 1900.0 3200.0 3300.0
-1500.0 1700.0 2300.0 2700.0 3000.0 3300.0
-1900.0 2200.0 2700.0 2800.0 3100.0 3400.0
-1900.0 2200.0 2700.0 2900.0 3300.0 3500.0
-1400.0 1900.0 2300.0 2400.0 3000.0 3200.0
-1500.0 1600.0 2300.0 2600.0 2900.0 3200.0
-1800.0 2100.0 2700.0 2800.0 3200.0 3300.0
-1500.0 1700.0 2400.0 2800.0 3100.0 3300.0
-1700.0 1900.0 2700.0 2800.0 3300.0 3400.0
-1700.0 2100.0 2600.0 2800.0 3100.0 3400.0
-1700.0 2200.0 2700.0 2900.0 3200.0 3400.0
-1900.0 2100.0 2400.0 2800.0 3200.0 3400.0
-1800.0 2100.0 2300.0 2600.0 3000.0 3300.0
-1800.0 2000.0 2200.0 2500.0 3100.0 3300.0
-1400.0 1600.0 2300.0 2400.0 3200.0 3300.0
-1600.0 1800.0 2300.0 2400.0 2900.0 3100.0
-1800.0 2200.0 2700.0 2800.0 3100.0 3300.0
-1800.0 2100.0 2700.0 2800.0 3000.0 3300.0
-1800.0 2100.0 2700.0 2800.0 3100.0 3300.0
-1500.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1200.0 1800.0 2200.0 2400.0 3100.0 3300.0
-1000.0 1400.0 2300.0 2400.0 3200.0 3300.0
-1100.0 1500.0 2200.0 2400.0 3200.0 3300.0
-1200.0 1500.0 2100.0 2200.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2600.0 3200.0 3400.0
-1100.0 1500.0 2100.0 2200.0 3200.0 3300.0
-1500.0 2000.0 2600.0 2800.0 3200.0 3400.0
-1400.0 1600.0 2500.0 2800.0 3000.0 3300.0
-1500.0 1600.0 2500.0 2700.0 3100.0 3300.0
-1400.0 1700.0 2600.0 2800.0 3000.0 3300.0
-1100.0 1900.0 2200.0 2400.0 3100.0 3300.0
-1000.0 1800.0 2200.0 2400.0 3200.0 3300.0
-1000.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1300.0 1600.0 1800.0 2000.0 3200.0 3300.0
-1300.0 1500.0 1800.0 1900.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2500.0 3000.0 3300.0
-1700.0 1800.0 2400.0 2600.0 3100.0 3400.0
-1500.0 1600.0 2100.0 2600.0 2800.0 3200.0
-1500.0 1600.0 2200.0 2600.0 2800.0 3000.0
-1600.0 1700.0 2100.0 2500.0 2900.0 3100.0
-1500.0 1600.0 2100.0 2500.0 2800.0 3200.0
-1500.0 1600.0 2100.0 2500.0 2700.0 3100.0
-1500.0 1600.0 2100.0 2400.0 2800.0 3100.0
-1500.0 1700.0 2200.0 2400.0 2800.0 3100.0
-2000.0 2300.0 2600.0 2700.0 3200.0 3400.0
-1600.0 1800.0 2100.0 2600.0 3100.0 3300.0
-1600.0 1700.0 2200.0 2700.0 3100.0 3300.0
-1300.0 1800.0 2400.0 2600.0 3100.0 3300.0
-1300.0 1500.0 2400.0 2700.0 3000.0 3300.0
-1500.0 1600.0 1900.0 2600.0 2900.0 3000.0
-1800.0 1900.0 2200.0 2700.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2700.0 3000.0 3300.0
-1800.0 1900.0 2400.0 2700.0 2900.0 3300.0
-1900.0 2000.0 2600.0 2700.0 3000.0 3200.0
-1900.0 2200.0 2700.0 2800.0 3000.0 3200.0
-1500.0 1600.0 2100.0 2500.0 2800.0 3100.0
-1100.0 1300.0 2400.0 2600.0 2800.0 3200.0
-1200.0 1500.0 2300.0 2600.0 3100.0 3300.0
-1200.0 1600.0 1800.0 2000.0 3200.0 3300.0
-1400.0 1600.0 1900.0 2000.0 3200.0 3300.0
-1300.0 1500.0 1700.0 1900.0 3200.0 3300.0
-2000.0 2200.0 2700.0 2800.0 3200.0 3400.0
-1500.0 1600.0 2400.0 2500.0 2900.0 3300.0
-1100.0 1700.0 2100.0 2300.0 3100.0 3200.0
-1500.0 1600.0 2100.0 2700.0 2900.0 3000.0
-1500.0 1900.0 2300.0 2600.0 2900.0 3000.0
-1600.0 2000.0 2200.0 2600.0 3100.0 3300.0
-1400.0 1600.0 1800.0 2000.0 3100.0 3200.0
-1900.0 2000.0 2300.0 2500.0 3000.0 3300.0
-1900.0 2100.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2400.0 2700.0 2800.0 3200.0 3400.0
-1900.0 2500.0 2700.0 2800.0 3300.0 3400.0
-2000.0 2500.0 2800.0 2900.0 3300.0 3500.0
-2100.0 2600.0 2800.0 3000.0 3400.0 3500.0
-1500.0 1600.0 2300.0 2600.0 2900.0 3300.0
-1600.0 2100.0 2600.0 2800.0 3200.0 3300.0
-1300.0 1500.0 2300.0 2700.0 3000.0 3300.0
-1400.0 1800.0 2300.0 2500.0 2700.0 3100.0
-1400.0 1600.0 2400.0 2700.0 3200.0 3300.0
-1400.0 1500.0 2300.0 2600.0 3200.0 3300.0
-1400.0 1600.0 2200.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2100.0 2300.0 3200.0 3400.0
-2100.0 2400.0 2700.0 2800.0 3100.0 3400.0
-2100.0 2400.0 2700.0 2800.0 3200.0 3400.0
-1600.0 1800.0 2600.0 2700.0 3000.0 3400.0
-1500.0 1700.0 2600.0 2700.0 2900.0 3300.0
-1600.0 1800.0 2600.0 2700.0 3000.0 3200.0
-1900.0 2500.0 2700.0 3000.0 3400.0 3500.0
-2000.0 2500.0 2600.0 3100.0 3300.0 3400.0
-2100.0 2300.0 2700.0 3000.0 3200.0 3400.0
-1600.0 1700.0 2100.0 2500.0 3100.0 3300.0
-1600.0 1700.0 2000.0 2400.0 3200.0 3300.0
-1600.0 1700.0 2000.0 2500.0 3200.0 3300.0
-2200.0 2500.0 2700.0 2900.0 3300.0 3400.0
-1200.0 1400.0 2100.0 2500.0 3000.0 3100.0
-1400.0 1700.0 2200.0 2400.0 3100.0 3300.0
-1300.0 1700.0 2000.0 2200.0 3100.0 3200.0
-1200.0 1600.0 1700.0 2100.0 3100.0 3200.0
-1800.0 2100.0 2700.0 2900.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2800.0 2900.0 3100.0
-1900.0 2000.0 2300.0 2700.0 2900.0 3200.0
-2000.0 2100.0 2400.0 2700.0 3000.0 3200.0
-1800.0 1900.0 2400.0 2700.0 3100.0 3400.0
-1700.0 1800.0 2500.0 2800.0 3000.0 3300.0
-2200.0 2600.0 2800.0 2900.0 3300.0 3400.0
-1500.0 1700.0 2200.0 2500.0 3200.0 3300.0
-1300.0 1600.0 2200.0 2500.0 3100.0 3200.0
-1700.0 1900.0 2300.0 2700.0 3100.0 3200.0
-1700.0 1900.0 2400.0 2800.0 3000.0 3200.0
-1300.0 1800.0 2200.0 2600.0 3000.0 3300.0
-1200.0 1500.0 2300.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2400.0 3100.0 3400.0
-1300.0 1700.0 2200.0 2300.0 3100.0 3300.0
-1500.0 1700.0 2300.0 2500.0 3200.0 3300.0
-1500.0 1600.0 2400.0 2600.0 3200.0 3300.0
-1600.0 1700.0 2400.0 2700.0 3100.0 3400.0
-1600.0 1700.0 2300.0 2800.0 3000.0 3300.0
-1300.0 1700.0 2300.0 2600.0 2700.0 2900.0
-1500.0 1600.0 2200.0 2600.0 2800.0 3200.0
-1300.0 1700.0 2200.0 2400.0 3000.0 3200.0
-1400.0 1900.0 2300.0 2600.0 2900.0 3300.0
-1200.0 1400.0 2500.0 2600.0 3100.0 3400.0
-1500.0 1600.0 2200.0 2500.0 2700.0 3200.0
-1600.0 1700.0 2300.0 2500.0 2700.0 3300.0
-1100.0 1300.0 2200.0 2700.0 3000.0 3200.0
-1200.0 1300.0 2000.0 2700.0 2900.0 3100.0
-1800.0 2000.0 2700.0 2900.0 3100.0 3300.0
-1800.0 1900.0 2400.0 2800.0 3000.0 3300.0
-1900.0 2000.0 2400.0 2800.0 3000.0 3300.0
-2000.0 2100.0 2400.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2300.0 2600.0 2700.0 3100.0
-1500.0 1700.0 2100.0 2500.0 2700.0 2900.0
-1400.0 1800.0 2400.0 2600.0 2800.0 3200.0
-2000.0 2100.0 2500.0 2900.0 3100.0 3300.0
-2000.0 2100.0 2600.0 2900.0 3100.0 3300.0
-2100.0 2200.0 2500.0 2800.0 3100.0 3300.0
-1900.0 2000.0 2500.0 2600.0 2900.0 3100.0
-1800.0 1900.0 2500.0 2700.0 2800.0 3100.0
-1900.0 2300.0 2800.0 2900.0 3300.0 3400.0
-1700.0 1800.0 2100.0 2200.0 3100.0 3200.0
-1800.0 1900.0 2200.0 2300.0 3100.0 3200.0
-1200.0 1700.0 2100.0 2300.0 3200.0 3300.0
-1400.0 1600.0 2000.0 2200.0 3000.0 3100.0
-1500.0 1600.0 2200.0 2500.0 2900.0 3100.0
-1900.0 2200.0 2400.0 2600.0 2800.0 3000.0
-1900.0 2100.0 2400.0 2700.0 2800.0 3000.0
-1900.0 2100.0 2300.0 2700.0 2900.0 3000.0
-1800.0 2000.0 2400.0 2900.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2800.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2500.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2200.0 2700.0 3100.0
-1600.0 1700.0 2100.0 2200.0 2600.0 3100.0
-1900.0 2200.0 2400.0 2900.0 3300.0 3400.0
-1600.0 1800.0 2400.0 2500.0 2900.0 3200.0
-2000.0 2200.0 2400.0 2500.0 2800.0 3200.0
-2000.0 2400.0 2500.0 2700.0 2900.0 3100.0
-1900.0 2000.0 2200.0 2300.0 3100.0 3400.0
-2000.0 2100.0 2300.0 2600.0 3000.0 3200.0
-2000.0 2100.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2600.0 2900.0 3000.0
-1300.0 1500.0 2300.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2100.0 2600.0 2900.0 3000.0
-1700.0 1800.0 2200.0 2500.0 2700.0 3100.0
-1900.0 2400.0 2600.0 2700.0 3000.0 3100.0
-2000.0 2400.0 2500.0 2900.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2600.0 2800.0 3100.0
-1900.0 2100.0 2600.0 3000.0 3200.0 3300.0
-1800.0 2300.0 2400.0 2600.0 3200.0 3300.0
-1900.0 2200.0 2300.0 2600.0 3200.0 3300.0
-1900.0 2400.0 2800.0 2900.0 3200.0 3400.0
-1800.0 2400.0 2700.0 2800.0 3200.0 3400.0
-1700.0 2100.0 2200.0 2600.0 3000.0 3100.0
-1900.0 2200.0 2500.0 2900.0 3200.0 3400.0
-1800.0 2400.0 2600.0 2700.0 3300.0 3400.0
-1900.0 2500.0 2700.0 2900.0 3300.0 3400.0
-1900.0 2400.0 2800.0 2900.0 3300.0 3400.0
-1800.0 2400.0 2800.0 2900.0 3200.0 3400.0
-1200.0 1300.0 2400.0 2800.0 2900.0 3100.0
-1600.0 1800.0 2000.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2300.0 2700.0 3200.0 3300.0
-1800.0 2100.0 2300.0 2800.0 3200.0 3300.0
-1500.0 1600.0 2100.0 2200.0 2800.0 3100.0
-1500.0 1600.0 2000.0 2200.0 2500.0 3100.0
-1400.0 1500.0 2200.0 2500.0 2700.0 3000.0
-1200.0 1400.0 2300.0 2600.0 2800.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2800.0 3000.0
-1700.0 2100.0 2200.0 2600.0 2800.0 2900.0
-2000.0 2200.0 2400.0 2700.0 3000.0 3100.0
-1500.0 2100.0 2500.0 2600.0 3100.0 3200.0
-1800.0 2400.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2400.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2300.0 2400.0 2600.0 3200.0 3300.0
-1900.0 2000.0 2400.0 2700.0 3000.0 3100.0
-2000.0 2200.0 2700.0 2900.0 3100.0 3200.0
-1800.0 1900.0 2300.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2200.0 2700.0 3200.0 3300.0
-1900.0 2100.0 2200.0 2700.0 3200.0 3300.0
-1600.0 2000.0 2200.0 2700.0 3200.0 3300.0
-1800.0 2000.0 2300.0 2800.0 3200.0 3300.0
-2000.0 2200.0 2500.0 2800.0 3200.0 3400.0
-1800.0 2100.0 2400.0 2900.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2700.0 3000.0 3100.0
-1500.0 1700.0 2100.0 2300.0 2600.0 3100.0
-1400.0 1500.0 1800.0 1900.0 2400.0 3000.0
-1400.0 1500.0 1800.0 1900.0 2300.0 3000.0
-1400.0 1600.0 1900.0 2000.0 2600.0 3200.0
-1700.0 1800.0 2200.0 2300.0 2700.0 3100.0
-1500.0 1600.0 2100.0 2700.0 3100.0 3200.0
-1400.0 1500.0 2100.0 2700.0 3100.0 3200.0
-1700.0 1800.0 2200.0 2600.0 2900.0 3000.0
-1800.0 1900.0 2200.0 2600.0 2900.0 3000.0
-1400.0 1600.0 2100.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2000.0 2500.0 2900.0 3100.0
-1600.0 1800.0 2400.0 2800.0 3100.0 3200.0
-1400.0 1900.0 2300.0 2700.0 3100.0 3200.0
-1900.0 2200.0 2500.0 2900.0 3300.0 3400.0
-1500.0 1600.0 2100.0 2800.0 3200.0 3300.0
-1400.0 1500.0 1700.0 1900.0 2800.0 3100.0
-1400.0 1600.0 2100.0 2600.0 2800.0 3100.0
-1500.0 1700.0 2300.0 2600.0 2800.0 3000.0
-1600.0 1700.0 2500.0 2700.0 3100.0 3200.0
-1600.0 1900.0 2400.0 2800.0 3000.0 3200.0
-1800.0 2300.0 2600.0 2700.0 3100.0 3300.0
-1900.0 2300.0 2500.0 2700.0 3100.0 3300.0
-1700.0 2000.0 2200.0 2600.0 3000.0 3100.0
-1600.0 1900.0 2100.0 2700.0 2900.0 3100.0
-1600.0 2200.0 2400.0 2700.0 3200.0 3300.0
-1700.0 2300.0 2500.0 2700.0 3200.0 3300.0
-1600.0 2100.0 2300.0 2500.0 3100.0 3200.0
-1700.0 2100.0 2300.0 2500.0 3100.0 3200.0
-1800.0 2200.0 2300.0 2600.0 3200.0 3300.0
-1700.0 2200.0 2400.0 2600.0 3300.0 3400.0
-1700.0 2200.0 2300.0 2600.0 3200.0 3300.0
-1800.0 1900.0 2300.0 2600.0 2900.0 3200.0
-1700.0 1800.0 2200.0 2400.0 2700.0 3000.0
-1800.0 1900.0 2200.0 2500.0 2700.0 3100.0
-1700.0 1900.0 2100.0 2600.0 3100.0 3200.0
-1900.0 2000.0 2300.0 2800.0 3200.0 3300.0
-1800.0 2000.0 2200.0 2700.0 3200.0 3300.0
-1700.0 1800.0 2100.0 2400.0 3200.0 3300.0
-1200.0 1500.0 2400.0 2700.0 2900.0 3000.0
-1700.0 1800.0 2100.0 2200.0 2500.0 3000.0
-1700.0 1800.0 2100.0 2200.0 2400.0 3000.0
-1600.0 1700.0 2000.0 2100.0 2400.0 3000.0
-1600.0 1700.0 1900.0 2000.0 2500.0 3000.0
-1700.0 1900.0 2100.0 2400.0 2600.0 2900.0
-1800.0 2000.0 2200.0 2400.0 2600.0 3000.0
-1600.0 1900.0 2400.0 2500.0 2900.0 3200.0
-1900.0 2100.0 2300.0 2700.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2700.0 2800.0 3000.0
-1900.0 2000.0 2300.0 2700.0 2800.0 3100.0
-1500.0 1600.0 2300.0 2700.0 2900.0 3100.0
-1700.0 2200.0 2700.0 2800.0 3100.0 3300.0
-1600.0 2000.0 2600.0 2800.0 3200.0 3300.0
-1800.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1600.0 2200.0 2600.0 2700.0 3000.0 3100.0
-2000.0 2200.0 2400.0 2600.0 2900.0 3100.0
-1400.0 1600.0 2000.0 2600.0 2800.0 3000.0
-1500.0 1600.0 2500.0 2700.0 3000.0 3100.0
-1300.0 1500.0 2200.0 2600.0 3100.0 3300.0
-1100.0 1600.0 2200.0 2500.0 3000.0 3200.0
-1200.0 1400.0 2200.0 2700.0 2800.0 3000.0
-1200.0 1400.0 2300.0 2600.0 2700.0 3000.0
-1600.0 1700.0 2000.0 2100.0 2600.0 3100.0
-1800.0 2300.0 2400.0 2600.0 2800.0 3100.0
-1700.0 2300.0 2700.0 2800.0 3200.0 3300.0
-1300.0 1600.0 2300.0 2700.0 2900.0 3000.0
-1500.0 1600.0 2200.0 2700.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2700.0 3000.0 3100.0
-1900.0 2000.0 2300.0 2600.0 2800.0 3000.0
-1900.0 2100.0 2300.0 2600.0 2800.0 3000.0
-1500.0 1900.0 2500.0 2700.0 3000.0 3100.0
-1900.0 2400.0 2700.0 2900.0 3100.0 3300.0
-1300.0 1600.0 1800.0 2100.0 2900.0 3200.0
-1700.0 1800.0 2000.0 2200.0 3100.0 3200.0
-2000.0 2300.0 2700.0 3100.0 3300.0 3400.0
-1900.0 2200.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2300.0 2800.0 3000.0 3200.0 3300.0
-2100.0 2300.0 2800.0 2900.0 3200.0 3300.0
-2000.0 2200.0 2800.0 2900.0 3200.0 3300.0
-1700.0 1900.0 2400.0 2800.0 3200.0 3300.0
-1500.0 1600.0 2200.0 2800.0 3200.0 3300.0
-1400.0 1500.0 2200.0 2500.0 2900.0 3200.0
-1300.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1200.0 1800.0 2300.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2500.0 2700.0 3200.0 3300.0
-1900.0 2300.0 2400.0 2700.0 2900.0 3100.0
-1900.0 2200.0 2400.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2100.0 2800.0 3100.0 3200.0
-1800.0 2400.0 2600.0 2700.0 3000.0 3100.0
-1600.0 1700.0 1900.0 2000.0 2500.0 3100.0
-1800.0 1900.0 2100.0 2300.0 2900.0 3300.0
-1300.0 1700.0 2400.0 2700.0 3200.0 3300.0
-1500.0 2000.0 2500.0 2800.0 3100.0 3300.0
-1900.0 2300.0 2400.0 2600.0 3300.0 3400.0
-1900.0 2300.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1600.0 2100.0 2800.0 3100.0 3200.0
-1500.0 1600.0 2100.0 2200.0 2700.0 3200.0
-1500.0 1600.0 1900.0 2000.0 2600.0 3100.0
-1400.0 1500.0 1900.0 2000.0 2600.0 3100.0
-1400.0 1600.0 1900.0 2000.0 2700.0 3200.0
-1700.0 1900.0 2100.0 2400.0 3000.0 3100.0
-1800.0 2000.0 2200.0 2400.0 2900.0 3200.0
-1700.0 2000.0 2200.0 2400.0 2800.0 3100.0
-1800.0 2000.0 2300.0 2700.0 2900.0 3200.0
-1700.0 2000.0 2200.0 2400.0 3000.0 3200.0
-1600.0 1900.0 2100.0 2300.0 3000.0 3200.0
-1700.0 1900.0 2100.0 2300.0 3000.0 3200.0
-1600.0 1900.0 2100.0 2400.0 3000.0 3200.0
-1700.0 1900.0 2200.0 2600.0 2900.0 3100.0
-1500.0 1800.0 1900.0 2400.0 2800.0 3000.0
-1700.0 2000.0 2400.0 2900.0 3100.0 3300.0
-1800.0 2000.0 2700.0 2900.0 3200.0 3400.0
-2000.0 2200.0 2600.0 2900.0 3100.0 3200.0
-1600.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1800.0 2000.0 2200.0 2400.0 2600.0 3100.0
-1700.0 1800.0 2000.0 2100.0 2600.0 3100.0
-1600.0 1700.0 1900.0 2000.0 2700.0 3200.0
-1700.0 1900.0 2100.0 2300.0 2600.0 3100.0
-2000.0 2300.0 2500.0 2600.0 3200.0 3300.0
-1500.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1500.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1600.0 2200.0 2500.0 2800.0 3100.0 3200.0
-1500.0 2100.0 2400.0 2700.0 3100.0 3200.0
-1600.0 2100.0 2400.0 2700.0 3000.0 3100.0
-1800.0 2100.0 2400.0 2700.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2600.0 3000.0 3200.0
-1400.0 1900.0 2400.0 2600.0 3000.0 3300.0
-1400.0 1500.0 2100.0 2600.0 3000.0 3100.0
-1300.0 1500.0 2300.0 2600.0 2800.0 3200.0
-1400.0 1600.0 2200.0 2600.0 3000.0 3200.0
-1700.0 1800.0 2200.0 2600.0 2900.0 3200.0
-1700.0 1800.0 2000.0 2600.0 2900.0 3100.0
-1600.0 1800.0 2000.0 2500.0 3000.0 3200.0
-1300.0 1500.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2300.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2400.0 3000.0 3200.0
-1700.0 1900.0 2200.0 2600.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2600.0 2800.0 2900.0
-1600.0 1700.0 2000.0 2300.0 3100.0 3200.0
-1600.0 1700.0 2100.0 2400.0 3000.0 3200.0
-2000.0 2100.0 2400.0 2800.0 3100.0 3300.0
-1700.0 2200.0 2300.0 2700.0 3000.0 3100.0
-1700.0 2200.0 2400.0 2600.0 3000.0 3200.0
-1900.0 2300.0 2400.0 2600.0 3000.0 3200.0
-2100.0 2200.0 2600.0 2800.0 3200.0 3400.0
-2100.0 2200.0 2700.0 2900.0 3200.0 3400.0
-2000.0 2200.0 2800.0 3000.0 3200.0 3400.0
-2000.0 2200.0 2700.0 3000.0 3200.0 3400.0
-2000.0 2200.0 2700.0 2900.0 3200.0 3400.0
-1700.0 2100.0 2400.0 2900.0 3100.0 3200.0
-1500.0 1800.0 1900.0 2500.0 3000.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2900.0 3300.0
-1800.0 2000.0 2300.0 2400.0 2700.0 3100.0
-1800.0 2100.0 2300.0 2800.0 3000.0 3200.0
-1600.0 2300.0 2500.0 2800.0 3100.0 3200.0
-1600.0 2100.0 2500.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2100.0 2800.0 3000.0 3100.0
-1800.0 2300.0 2600.0 2700.0 3100.0 3200.0
-2000.0 2200.0 2800.0 3000.0 3300.0 3400.0
-2000.0 2200.0 2600.0 2800.0 3200.0 3400.0
-1700.0 1800.0 2200.0 2600.0 2800.0 3200.0
-1600.0 1800.0 2200.0 2500.0 2800.0 3200.0
-1600.0 1700.0 1900.0 2000.0 2600.0 3100.0
-1600.0 1700.0 2200.0 2800.0 3000.0 3200.0
-1700.0 1800.0 2400.0 2900.0 3100.0 3300.0
-1900.0 2200.0 2700.0 2900.0 3400.0 3500.0
-1700.0 1800.0 2000.0 2200.0 2900.0 3200.0
-1700.0 1900.0 2100.0 2300.0 2900.0 3200.0
-1200.0 1400.0 2200.0 2900.0 3100.0 3200.0
-1800.0 1900.0 2300.0 2600.0 2800.0 3200.0
-1600.0 1700.0 2000.0 2200.0 2700.0 3200.0
-1600.0 1700.0 2000.0 2200.0 2800.0 3200.0
-1600.0 1700.0 2000.0 2100.0 2800.0 3200.0
-1600.0 1800.0 2000.0 2100.0 2800.0 3200.0
-1700.0 1800.0 2000.0 2300.0 2900.0 3200.0
-1800.0 1900.0 2200.0 2600.0 3200.0 3300.0
-1800.0 2000.0 2200.0 2500.0 3200.0 3300.0
-1300.0 1500.0 1900.0 2600.0 3100.0 3200.0
-1300.0 1400.0 2000.0 2600.0 3200.0 3300.0
-1600.0 1700.0 2100.0 2700.0 3000.0 3200.0
-1400.0 1500.0 2000.0 2600.0 3100.0 3200.0
-1400.0 1500.0 2000.0 2700.0 3100.0 3200.0
-1500.0 1800.0 2400.0 2700.0 3000.0 3300.0
-1500.0 1600.0 2200.0 2300.0 2700.0 3300.0
-1400.0 1500.0 2200.0 2400.0 2700.0 3200.0
-1300.0 1500.0 2300.0 2600.0 2900.0 3200.0
-1400.0 1700.0 2400.0 2600.0 3000.0 3200.0
-1300.0 1600.0 2400.0 2500.0 2900.0 3200.0
-1400.0 1500.0 2200.0 2400.0 2900.0 3300.0
-1400.0 1600.0 2100.0 2200.0 3200.0 3300.0
-1400.0 1800.0 2200.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1500.0 1700.0 1900.0 2600.0 3200.0 3300.0
-1500.0 1600.0 1800.0 2000.0 2800.0 3200.0
-1500.0 1600.0 1900.0 2000.0 2700.0 3200.0
-1500.0 1600.0 1900.0 2000.0 2800.0 3200.0
-1600.0 1700.0 2000.0 2500.0 3000.0 3200.0
-1600.0 1700.0 2200.0 2700.0 2900.0 3200.0
-1300.0 1500.0 2300.0 2700.0 2900.0 3200.0
-1600.0 1700.0 2600.0 2800.0 2900.0 3200.0
-1300.0 1500.0 2300.0 2500.0 2800.0 3200.0
-1300.0 1400.0 2300.0 2500.0 2800.0 3200.0
-1500.0 1700.0 2200.0 2600.0 2700.0 3100.0
-1500.0 1700.0 2200.0 2600.0 2800.0 3000.0
-1500.0 1700.0 2000.0 2600.0 2700.0 3000.0
-1100.0 1300.0 2300.0 2800.0 3100.0 3200.0
-1600.0 1700.0 2100.0 2500.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2300.0 2700.0 2900.0 3200.0
-1800.0 2000.0 2500.0 2800.0 3100.0 3400.0
-1900.0 2000.0 2800.0 2900.0 3300.0 3400.0
-1800.0 2000.0 2700.0 2800.0 3300.0 3400.0
-1700.0 1800.0 2100.0 2200.0 2600.0 3100.0
-1500.0 1600.0 1800.0 1900.0 2600.0 3200.0
-1600.0 1700.0 1900.0 2000.0 2600.0 3200.0
-1600.0 1700.0 2000.0 2100.0 2600.0 3200.0
-1700.0 1800.0 2000.0 2100.0 2800.0 3300.0
-1600.0 1900.0 2100.0 2400.0 3000.0 3100.0
-1600.0 1800.0 2300.0 2600.0 2900.0 3000.0
-1400.0 1500.0 2100.0 2600.0 2900.0 3100.0
-1400.0 1500.0 2200.0 2600.0 2900.0 3100.0
-1000.0 1200.0 2300.0 2900.0 3100.0 3200.0
-1300.0 1700.0 2400.0 2600.0 3000.0 3200.0
-1100.0 1600.0 2300.0 2600.0 3200.0 3300.0
-1200.0 1600.0 2300.0 2600.0 3100.0 3300.0
-1100.0 1600.0 2200.0 2600.0 3100.0 3300.0
-1600.0 2200.0 2400.0 2700.0 3100.0 3200.0
-1700.0 1800.0 2300.0 2700.0 2800.0 3000.0
-1400.0 1700.0 1900.0 2500.0 3200.0 3300.0
-1700.0 1900.0 2200.0 2400.0 2800.0 3000.0
-1400.0 1600.0 2100.0 2200.0 2700.0 3000.0
-1500.0 1700.0 2200.0 2400.0 2700.0 3100.0
-1500.0 1600.0 2200.0 2400.0 2800.0 3100.0
-1000.0 1900.0 2200.0 2500.0 3200.0 3300.0
-1200.0 1700.0 2100.0 2400.0 3200.0 3300.0
-1700.0 2000.0 2500.0 2600.0 3100.0 3400.0
-1600.0 2200.0 2400.0 2600.0 3200.0 3300.0
-2000.0 2500.0 2600.0 3000.0 3300.0 3400.0
-1400.0 1500.0 2100.0 2300.0 3200.0 3300.0
-1500.0 1700.0 2100.0 2400.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2300.0 3300.0 3400.0
-1800.0 2200.0 2500.0 2700.0 3100.0 3400.0
-1500.0 1900.0 2300.0 2600.0 3200.0 3300.0
-2100.0 2200.0 2600.0 2900.0 3100.0 3300.0
-1500.0 1600.0 1800.0 2600.0 3200.0 3300.0
-1300.0 1500.0 1600.0 2200.0 3100.0 3200.0
-1200.0 1800.0 2300.0 2400.0 3000.0 3200.0
-1100.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1400.0 1700.0 2200.0 2500.0 3100.0 3200.0
-1900.0 2100.0 2300.0 2600.0 3000.0 3300.0
-1900.0 2100.0 2500.0 2800.0 3300.0 3400.0
-1700.0 1900.0 2300.0 2500.0 3100.0 3400.0
-1500.0 1900.0 2200.0 2500.0 2900.0 3200.0
-1200.0 2000.0 2300.0 2400.0 2500.0 3100.0
-1200.0 2000.0 2300.0 2400.0 2600.0 3100.0
-1900.0 2200.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2200.0 2500.0 2700.0 3200.0 3400.0
-1800.0 2100.0 2400.0 2500.0 3200.0 3300.0
-1800.0 2100.0 2300.0 2500.0 3300.0 3400.0
-1500.0 1700.0 1800.0 2500.0 3200.0 3300.0
-1400.0 1600.0 1800.0 2300.0 3200.0 3300.0
-1300.0 1600.0 2300.0 2400.0 3200.0 3400.0
-1200.0 1500.0 1700.0 2100.0 3100.0 3200.0
-2100.0 2300.0 2400.0 2800.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2400.0 3100.0 3300.0
-1400.0 1600.0 2000.0 2100.0 3000.0 3300.0
-1900.0 2000.0 2200.0 2400.0 3000.0 3300.0
-1500.0 1800.0 2200.0 2300.0 3000.0 3300.0
-1300.0 1500.0 2100.0 2200.0 2800.0 3300.0
-1500.0 1800.0 2200.0 2400.0 3000.0 3300.0
-1600.0 1900.0 2300.0 2600.0 3200.0 3400.0
-1300.0 1800.0 2200.0 2500.0 3000.0 3200.0
-1100.0 1600.0 2200.0 2300.0 3100.0 3200.0
-1300.0 1500.0 2000.0 2200.0 3100.0 3300.0
-2300.0 2500.0 2900.0 3100.0 3200.0 3300.0
-2300.0 2400.0 2700.0 2800.0 3100.0 3300.0
-2000.0 2100.0 2400.0 2700.0 3200.0 3300.0
-1600.0 1700.0 1900.0 2100.0 3200.0 3300.0
-1600.0 1800.0 1900.0 2300.0 3200.0 3300.0
-1500.0 1600.0 1900.0 2600.0 3100.0 3200.0
-1300.0 1500.0 1900.0 2300.0 3000.0 3100.0
-1200.0 1600.0 2000.0 2100.0 3200.0 3300.0
-1300.0 2000.0 2200.0 2400.0 2700.0 3100.0
-1100.0 1900.0 2300.0 2400.0 3000.0 3100.0
-1200.0 1500.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1600.0 1900.0 2500.0 3000.0 3100.0
-1300.0 1500.0 1600.0 2300.0 3200.0 3300.0
-1500.0 1800.0 2100.0 2400.0 3100.0 3200.0
-1900.0 2200.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1500.0 2100.0 2300.0 2900.0 3200.0
-1100.0 1600.0 2100.0 2300.0 3100.0 3200.0
-1100.0 1600.0 2100.0 2300.0 3200.0 3300.0
-1000.0 1600.0 2200.0 2300.0 3100.0 3300.0
-1100.0 1600.0 2100.0 2300.0 3000.0 3100.0
-1100.0 1400.0 2300.0 2500.0 3200.0 3300.0
-1700.0 2100.0 2500.0 2800.0 3100.0 3400.0
-1300.0 1600.0 2300.0 2400.0 3200.0 3300.0
-1400.0 1700.0 2300.0 2400.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2400.0 3000.0 3300.0
-1700.0 1900.0 2500.0 2600.0 3000.0 3200.0
-1100.0 1500.0 2400.0 2500.0 3100.0 3200.0
-1700.0 1900.0 2100.0 2400.0 3100.0 3300.0
-1300.0 1700.0 2200.0 2600.0 3100.0 3300.0
-1600.0 1700.0 2000.0 2200.0 3100.0 3300.0
-1800.0 2000.0 2200.0 2400.0 3200.0 3400.0
-1900.0 2100.0 2600.0 2800.0 3000.0 3200.0
-1900.0 2100.0 2600.0 2800.0 3100.0 3200.0
-1400.0 1900.0 2400.0 2500.0 3100.0 3300.0
-1100.0 2100.0 2300.0 2700.0 3100.0 3200.0
-1100.0 1800.0 2200.0 2500.0 3000.0 3100.0
-1100.0 1800.0 2200.0 2400.0 3000.0 3100.0
-1500.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1500.0 2000.0 2400.0 2500.0 3200.0 3400.0
-1800.0 2000.0 2500.0 2600.0 3000.0 3300.0
-1900.0 2400.0 2600.0 2900.0 3200.0 3400.0
-1500.0 2100.0 2500.0 2700.0 3200.0 3300.0
-1400.0 2100.0 2400.0 2700.0 3100.0 3200.0
-1500.0 2100.0 2500.0 2700.0 3000.0 3200.0
-1600.0 2100.0 2500.0 2600.0 3100.0 3300.0
-1500.0 1800.0 2100.0 2700.0 3100.0 3300.0
-1300.0 1600.0 1800.0 2500.0 3200.0 3300.0
-1300.0 1500.0 1600.0 2800.0 3300.0 3400.0
-1300.0 1400.0 2200.0 2300.0 3100.0 3300.0
-1300.0 1600.0 2400.0 2500.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2500.0 3200.0 3400.0
-1400.0 2000.0 2100.0 2400.0 3000.0 3100.0
-1300.0 1900.0 2100.0 2400.0 3100.0 3200.0
-1600.0 1700.0 2200.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2300.0 2400.0 2900.0 3200.0
-1300.0 1600.0 2200.0 2400.0 3000.0 3200.0
-1200.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1500.0 1600.0 2200.0 2400.0 3100.0 3300.0
-1000.0 1600.0 2500.0 2600.0 3100.0 3200.0
-900.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1400.0 1700.0 2500.0 2700.0 3100.0 3300.0
-1300.0 1900.0 2500.0 2700.0 3200.0 3300.0
-1600.0 2000.0 2400.0 2500.0 2900.0 3100.0
-1400.0 1600.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1600.0 2600.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2600.0 2700.0 3100.0 3400.0
-1600.0 2100.0 2600.0 2900.0 3300.0 3400.0
-1800.0 2100.0 2800.0 3000.0 3300.0 3400.0
-1800.0 2300.0 2700.0 2900.0 3400.0 3500.0
-1800.0 2400.0 2900.0 3100.0 3300.0 3400.0
-1200.0 1800.0 2300.0 2400.0 3000.0 3100.0
-1300.0 1600.0 2400.0 2500.0 3100.0 3200.0
-1400.0 1800.0 2400.0 2500.0 3200.0 3400.0
-2000.0 2500.0 2700.0 3100.0 3300.0 3400.0
-1900.0 2000.0 2400.0 2800.0 3100.0 3300.0
-1500.0 1800.0 1900.0 2500.0 3100.0 3200.0
-1600.0 1800.0 2000.0 2600.0 3100.0 3200.0
-1700.0 2000.0 2200.0 2700.0 3000.0 3100.0
-1700.0 2000.0 2300.0 2600.0 2900.0 3000.0
-2300.0 2400.0 2700.0 2900.0 3200.0 3300.0
-1200.0 1600.0 2200.0 2300.0 3000.0 3100.0
-1400.0 2000.0 2300.0 2500.0 3100.0 3200.0
-1500.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1300.0 1700.0 1800.0 2400.0 2900.0 3000.0
-1300.0 1500.0 1600.0 2200.0 2800.0 2900.0
-1900.0 2100.0 2500.0 2700.0 3000.0 3300.0
-1500.0 1900.0 2400.0 2600.0 2900.0 3300.0
-1400.0 1800.0 2300.0 2500.0 3100.0 3300.0
-1300.0 1800.0 2500.0 2700.0 3100.0 3300.0
-1300.0 1800.0 2400.0 2600.0 3100.0 3200.0
-1200.0 1700.0 2400.0 2500.0 2900.0 3100.0
-1100.0 1800.0 2000.0 2200.0 3000.0 3100.0
-1300.0 1600.0 1700.0 2600.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2400.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2400.0 3000.0 3100.0
-1800.0 1900.0 2400.0 2500.0 3000.0 3100.0
-1500.0 2200.0 2500.0 2700.0 3300.0 3400.0
-1900.0 2500.0 2700.0 3000.0 3300.0 3400.0
-1400.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1400.0 1800.0 2100.0 2500.0 3000.0 3100.0
-1200.0 1500.0 1600.0 2600.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2300.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2200.0 3100.0 3200.0
-1200.0 1500.0 1600.0 2200.0 3100.0 3200.0
-1200.0 1500.0 1600.0 2300.0 3000.0 3100.0
-1300.0 1800.0 2400.0 2600.0 3000.0 3200.0
-1300.0 1800.0 2200.0 2400.0 3100.0 3300.0
-1400.0 1800.0 2200.0 2400.0 3100.0 3300.0
-1600.0 1700.0 2100.0 2300.0 2700.0 3100.0
-1700.0 1800.0 2100.0 2300.0 2700.0 3200.0
-1700.0 1800.0 2200.0 2300.0 2800.0 3200.0
-1700.0 2200.0 2400.0 2800.0 3100.0 3200.0
-1100.0 2000.0 2200.0 2400.0 3000.0 3100.0
-1100.0 1900.0 2000.0 2400.0 3000.0 3100.0
-1300.0 1500.0 1600.0 2700.0 3200.0 3300.0
-1300.0 1500.0 1600.0 2600.0 3300.0 3400.0
-1600.0 1700.0 2000.0 2600.0 3100.0 3200.0
-1700.0 2200.0 2500.0 2700.0 2900.0 3200.0
-1100.0 1700.0 2200.0 2300.0 3100.0 3200.0
-1100.0 1800.0 2100.0 2200.0 3100.0 3200.0
-1100.0 1600.0 2000.0 2100.0 3100.0 3200.0
-1100.0 1600.0 1900.0 2100.0 3100.0 3200.0
-1200.0 1600.0 1800.0 2000.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2000.0 3100.0 3200.0
-1300.0 1600.0 1700.0 2000.0 3000.0 3100.0
-1200.0 1500.0 1600.0 2000.0 3000.0 3100.0
-1500.0 1700.0 1900.0 2400.0 2800.0 2900.0
-1600.0 2000.0 2300.0 2600.0 2900.0 3100.0
-2200.0 2400.0 2700.0 2800.0 3100.0 3300.0
-1700.0 2100.0 2300.0 2400.0 2800.0 3200.0
-1600.0 1800.0 2300.0 2400.0 2800.0 3200.0
-1000.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1000.0 1900.0 2800.0 2900.0 3300.0 3400.0
-1400.0 1600.0 1800.0 2400.0 2700.0 3000.0
-1800.0 2000.0 2300.0 2500.0 2900.0 3100.0
-1200.0 1800.0 2600.0 2700.0 3200.0 3300.0
-1300.0 1800.0 2400.0 2500.0 3000.0 3300.0
-1500.0 1900.0 2500.0 2700.0 3200.0 3400.0
-1400.0 1800.0 2500.0 2600.0 3100.0 3300.0
-1600.0 1800.0 2200.0 2300.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2400.0 2700.0 3100.0
-1700.0 1900.0 2200.0 2500.0 2700.0 3100.0
-1300.0 1400.0 2200.0 2800.0 3100.0 3200.0
-1700.0 2100.0 2300.0 2500.0 2800.0 3100.0
-1500.0 1600.0 2200.0 2700.0 2900.0 3100.0
-1200.0 1400.0 2200.0 2800.0 3000.0 3200.0
-1200.0 1400.0 2300.0 2800.0 3100.0 3200.0
-1900.0 2000.0 2600.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2500.0 2800.0 3000.0 3300.0
-2100.0 2300.0 2500.0 2700.0 2900.0 3200.0
-1900.0 2000.0 2700.0 2900.0 3100.0 3400.0
-1900.0 2000.0 2600.0 2900.0 3200.0 3300.0
-1900.0 2000.0 2600.0 2900.0 3200.0 3400.0
-900.0 1500.0 2500.0 2600.0 3200.0 3400.0
-1800.0 1900.0 2400.0 2800.0 2900.0 3100.0
-1600.0 1900.0 2300.0 2600.0 2900.0 3100.0
-1400.0 1500.0 2000.0 2400.0 2900.0 3100.0
-1500.0 1800.0 2200.0 2400.0 2600.0 2800.0
-2000.0 2400.0 2800.0 2900.0 3100.0 3400.0
-1900.0 2300.0 2800.0 2900.0 3100.0 3300.0
-1200.0 1400.0 1900.0 2600.0 3100.0 3200.0
-2100.0 2300.0 2800.0 2900.0 3100.0 3200.0
-2000.0 2400.0 2600.0 2700.0 3100.0 3300.0
-2000.0 2400.0 2600.0 2700.0 3000.0 3200.0
-2000.0 2300.0 2600.0 2700.0 2900.0 3200.0
-1800.0 1900.0 2300.0 2600.0 2800.0 3000.0
-2000.0 2300.0 2500.0 2800.0 3000.0 3200.0
-1700.0 2000.0 2200.0 2600.0 2800.0 3000.0
-1900.0 2000.0 2400.0 2800.0 2900.0 3100.0
-2200.0 2600.0 2800.0 2900.0 3200.0 3400.0
-1600.0 1700.0 2200.0 2400.0 2700.0 3200.0
-1500.0 1600.0 2300.0 2400.0 2700.0 3200.0
-1300.0 1500.0 2200.0 2500.0 2700.0 3100.0
-1700.0 1800.0 2100.0 2200.0 2700.0 3200.0
-1900.0 2000.0 2600.0 2900.0 3000.0 3200.0
-1800.0 2100.0 2400.0 2500.0 2800.0 3100.0
-1400.0 1500.0 2200.0 2500.0 2700.0 3100.0
-1500.0 1600.0 2200.0 2400.0 2700.0 3100.0
-1700.0 1800.0 2300.0 2400.0 2700.0 3100.0
-1900.0 2000.0 2300.0 2500.0 2700.0 3100.0
-1900.0 2200.0 2400.0 2700.0 2800.0 3100.0
-1600.0 1700.0 2200.0 2600.0 2700.0 3100.0
-2100.0 2400.0 2600.0 2800.0 3000.0 3200.0
-2100.0 2300.0 2700.0 2800.0 3200.0 3400.0
-1800.0 2300.0 2600.0 2800.0 3000.0 3200.0
-2000.0 2200.0 2400.0 2700.0 3000.0 3300.0
-1900.0 2200.0 2400.0 2600.0 3000.0 3300.0
-1700.0 2000.0 2300.0 2600.0 2800.0 3000.0
-1600.0 1800.0 2100.0 2500.0 2700.0 3000.0
-1600.0 1700.0 2300.0 2600.0 2800.0 3000.0
-1600.0 1700.0 2400.0 2600.0 2800.0 3000.0
-2000.0 2300.0 2600.0 2700.0 3300.0 3400.0
-1700.0 1800.0 2100.0 2500.0 3000.0 3300.0
-1300.0 1500.0 2300.0 2400.0 3000.0 3300.0
-1500.0 1600.0 1900.0 2100.0 3000.0 3100.0
-1900.0 2000.0 2500.0 2800.0 3100.0 3200.0
-2000.0 2400.0 2900.0 3000.0 3200.0 3400.0
-1700.0 1800.0 2100.0 2500.0 2700.0 3100.0
-1500.0 2000.0 2400.0 2500.0 3000.0 3300.0
-1500.0 1600.0 2300.0 2400.0 2700.0 3100.0
-1600.0 1700.0 2300.0 2400.0 2700.0 3200.0
-1700.0 1800.0 2200.0 2500.0 2600.0 3000.0
-1800.0 1900.0 2200.0 2500.0 2700.0 3000.0
-1800.0 1900.0 2200.0 2600.0 2700.0 3000.0
-1800.0 2200.0 2500.0 2700.0 2900.0 3200.0
-1200.0 1600.0 2500.0 2600.0 3000.0 3300.0
-1000.0 1300.0 2400.0 2900.0 3100.0 3200.0
-1300.0 1600.0 2500.0 2800.0 3000.0 3200.0
-1800.0 2100.0 2600.0 2800.0 3000.0 3300.0
-1300.0 1600.0 2500.0 2800.0 2900.0 3200.0
-1200.0 1500.0 2300.0 2700.0 2900.0 3200.0
-1200.0 1400.0 2300.0 2700.0 2900.0 3200.0
-1400.0 1600.0 2100.0 2500.0 3100.0 3300.0
-1700.0 2300.0 2600.0 2800.0 3100.0 3200.0
-2000.0 2200.0 2400.0 2700.0 2800.0 3100.0
-1400.0 1500.0 2300.0 2800.0 3000.0 3100.0
-1500.0 1600.0 2300.0 2800.0 2900.0 3100.0
-1500.0 1600.0 2400.0 2800.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2700.0 2800.0 3000.0
-1800.0 1900.0 2600.0 2700.0 2900.0 3200.0
-1800.0 2000.0 2700.0 2800.0 3200.0 3400.0
-1800.0 2000.0 2600.0 2800.0 3000.0 3300.0
-1700.0 1800.0 2400.0 2600.0 2900.0 3100.0
-2000.0 2200.0 2500.0 2600.0 3000.0 3100.0
-2000.0 2100.0 2500.0 2900.0 3200.0 3300.0
-1800.0 2000.0 2600.0 2900.0 3100.0 3300.0
-1700.0 1900.0 2200.0 2700.0 2800.0 3000.0
-1700.0 2000.0 2500.0 2600.0 3200.0 3300.0
-1400.0 1600.0 2300.0 2500.0 2700.0 3100.0
-1900.0 2300.0 2800.0 3000.0 3400.0 3500.0
-1600.0 1800.0 2300.0 2400.0 2800.0 3300.0
-1600.0 1700.0 2200.0 2400.0 2800.0 3000.0
-1600.0 1700.0 2300.0 2600.0 3000.0 3100.0
-1800.0 2100.0 2700.0 2900.0 3300.0 3500.0
-1600.0 1700.0 2300.0 2800.0 2900.0 3100.0
-1300.0 1500.0 2200.0 2700.0 2900.0 3100.0
-1200.0 1400.0 2500.0 2900.0 3000.0 3200.0
-1900.0 2200.0 2400.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2600.0 2900.0 3100.0 3400.0
-1600.0 1700.0 2100.0 2600.0 2700.0 3100.0
-1500.0 1600.0 2300.0 2500.0 2700.0 3100.0
-1500.0 1600.0 2200.0 2800.0 3100.0 3300.0
-1300.0 1500.0 2000.0 2700.0 3100.0 3200.0
-1300.0 1500.0 1900.0 2600.0 3200.0 3300.0
-1300.0 1400.0 2000.0 2400.0 3200.0 3300.0
-1300.0 1400.0 2000.0 2300.0 3100.0 3300.0
-1300.0 1500.0 2000.0 2300.0 3100.0 3200.0
-1800.0 2000.0 2200.0 2400.0 3100.0 3300.0
-1700.0 1900.0 2300.0 2400.0 2800.0 3300.0
-1200.0 2200.0 2500.0 2700.0 3200.0 3300.0
-1300.0 2100.0 2300.0 2700.0 3200.0 3300.0
-1400.0 2200.0 2400.0 2900.0 3300.0 3400.0
-1500.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1200.0 1900.0 2400.0 2500.0 3000.0 3200.0
-1200.0 2000.0 2400.0 2600.0 3000.0 3200.0
-1200.0 1900.0 2400.0 2500.0 3200.0 3300.0
-2000.0 2300.0 2700.0 3000.0 3200.0 3400.0
-1900.0 2100.0 2600.0 3000.0 3300.0 3400.0
-1500.0 1900.0 2200.0 2600.0 3000.0 3300.0
-1400.0 1800.0 2200.0 2500.0 3000.0 3300.0
-1800.0 2000.0 2300.0 2400.0 3300.0 3400.0
-1600.0 2100.0 2300.0 2400.0 3100.0 3300.0
-1900.0 2300.0 2800.0 3000.0 3200.0 3400.0
-1700.0 2100.0 2400.0 2700.0 3100.0 3400.0
-1400.0 1800.0 2300.0 2600.0 3200.0 3400.0
-1700.0 2000.0 2200.0 2400.0 3100.0 3200.0
-1500.0 1800.0 2200.0 2500.0 3000.0 3300.0
-1700.0 1900.0 2200.0 2600.0 2900.0 3200.0
-1400.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1500.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1600.0 2100.0 2300.0 2700.0 3100.0 3200.0
-1600.0 1700.0 1900.0 2800.0 3000.0 3100.0
-1500.0 1700.0 1900.0 2600.0 3000.0 3100.0
-1500.0 1600.0 2100.0 2600.0 3200.0 3300.0
-2200.0 2300.0 2600.0 2900.0 3100.0 3300.0
-1900.0 2200.0 2400.0 2700.0 3000.0 3300.0
-1400.0 1700.0 2300.0 2400.0 3000.0 3100.0
-1900.0 2000.0 2400.0 2500.0 3100.0 3200.0
-2000.0 2500.0 2600.0 2800.0 3300.0 3400.0
-2000.0 2400.0 2600.0 3000.0 3200.0 3300.0
-1500.0 1800.0 2300.0 2500.0 2900.0 3200.0
-1300.0 1900.0 2200.0 2300.0 3000.0 3200.0
-1600.0 1700.0 2500.0 2800.0 3200.0 3400.0
-1500.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1900.0 2200.0 2500.0 2700.0 3000.0 3300.0
-1300.0 1600.0 1800.0 2100.0 3000.0 3100.0
-1000.0 1900.0 2200.0 2500.0 3100.0 3200.0
-1200.0 2000.0 2300.0 2600.0 3300.0 3400.0
-1400.0 1600.0 1800.0 2600.0 2900.0 3100.0
-1400.0 1700.0 2000.0 2600.0 3100.0 3200.0
-1300.0 1800.0 2000.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2300.0 2400.0 2700.0 3100.0
-1700.0 1800.0 2000.0 2400.0 3100.0 3200.0
-1800.0 1900.0 2100.0 2500.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2500.0 2800.0 3100.0
-1600.0 1800.0 2100.0 2400.0 2700.0 2800.0
-1300.0 1700.0 2100.0 2200.0 3100.0 3300.0
-1300.0 1700.0 2100.0 2200.0 3000.0 3200.0
-1500.0 1800.0 2200.0 2400.0 2700.0 3200.0
-1600.0 1800.0 2200.0 2300.0 2900.0 3200.0
-1500.0 1800.0 2100.0 2400.0 2900.0 3200.0
-1400.0 1700.0 1900.0 2200.0 2800.0 2900.0
-1500.0 1800.0 2100.0 2500.0 3000.0 3100.0
-1500.0 1900.0 2100.0 2500.0 3000.0 3100.0
-1500.0 2000.0 2200.0 2700.0 3200.0 3300.0
-1400.0 1800.0 2200.0 2500.0 3200.0 3300.0
-1500.0 2000.0 2200.0 2400.0 2900.0 3200.0
-1800.0 2000.0 2700.0 2900.0 3300.0 3400.0
-1500.0 1800.0 2100.0 2500.0 3200.0 3300.0
-1400.0 1700.0 1800.0 2200.0 3100.0 3200.0
-1400.0 1600.0 1700.0 2300.0 3000.0 3100.0
-1300.0 2000.0 2100.0 2700.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2500.0 3100.0 3200.0
-1400.0 1700.0 1800.0 2300.0 3000.0 3100.0
-1600.0 1700.0 1900.0 2600.0 3000.0 3100.0
-1800.0 2100.0 2300.0 2700.0 3300.0 3400.0
-1700.0 2100.0 2300.0 2700.0 3300.0 3400.0
-1800.0 2100.0 2300.0 2400.0 2700.0 3100.0
-1500.0 1700.0 1900.0 2600.0 3100.0 3200.0
-1300.0 2000.0 2200.0 2800.0 3200.0 3300.0
-1700.0 1900.0 2600.0 2900.0 3200.0 3400.0
-1200.0 1800.0 2600.0 2700.0 3100.0 3200.0
-1900.0 2000.0 2200.0 2500.0 3200.0 3400.0
-1300.0 1700.0 2300.0 2400.0 2900.0 3200.0
-1200.0 1600.0 2200.0 2400.0 2800.0 3100.0
-1200.0 1800.0 2200.0 2600.0 3200.0 3300.0
-1300.0 1800.0 2300.0 2700.0 3300.0 3400.0
-1700.0 2000.0 2400.0 2500.0 3000.0 3200.0
-1600.0 1900.0 2200.0 2300.0 2900.0 3100.0
-1400.0 1700.0 1900.0 2400.0 3000.0 3100.0
-1600.0 1900.0 2400.0 2700.0 3300.0 3400.0
-1800.0 2300.0 2700.0 3000.0 3200.0 3400.0
-1300.0 1700.0 2300.0 2600.0 3000.0 3300.0
-1200.0 1800.0 2200.0 2600.0 3100.0 3300.0
-1700.0 2000.0 2400.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2400.0 2600.0 3000.0
-1600.0 1700.0 2100.0 2400.0 2600.0 3000.0
-1700.0 1900.0 2200.0 2400.0 2800.0 3200.0
-1700.0 2100.0 2300.0 2700.0 2800.0 3000.0
-1600.0 1900.0 2100.0 2600.0 2900.0 3000.0
-1800.0 2000.0 2700.0 2800.0 3100.0 3400.0
-1500.0 1600.0 2200.0 2800.0 3000.0 3100.0
-1300.0 1500.0 2100.0 2700.0 3000.0 3100.0
-1500.0 1800.0 2300.0 2600.0 3000.0 3100.0
-1600.0 1700.0 2300.0 2700.0 2900.0 3000.0
-1600.0 1800.0 2200.0 2600.0 2800.0 3100.0
-1500.0 1600.0 2300.0 2600.0 2900.0 3100.0
-1600.0 1800.0 2200.0 2700.0 3000.0 3300.0
-2100.0 2200.0 2600.0 2700.0 2900.0 3100.0
-1800.0 1900.0 2300.0 2700.0 2800.0 3000.0
-1800.0 1900.0 2200.0 2700.0 2800.0 3000.0
-1500.0 1800.0 2000.0 2600.0 3000.0 3100.0
-1500.0 1700.0 2100.0 2500.0 2700.0 3000.0
-1500.0 1600.0 1900.0 2000.0 2400.0 3100.0
-1200.0 1500.0 2100.0 2200.0 2700.0 3200.0
-1300.0 1700.0 2400.0 2700.0 3000.0 3200.0
-1600.0 1700.0 2400.0 2800.0 2900.0 3200.0
-1500.0 1800.0 2000.0 2500.0 2900.0 3200.0
-1800.0 2000.0 2200.0 2500.0 2700.0 3000.0
-1800.0 1900.0 2300.0 2600.0 2700.0 3200.0
-1500.0 1700.0 2200.0 2700.0 2900.0 3200.0
-1300.0 1400.0 2100.0 2600.0 3000.0 3200.0
-1400.0 1500.0 2100.0 2700.0 3000.0 3200.0
-1500.0 1600.0 2300.0 2800.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2600.0 2900.0 3300.0
-1600.0 1700.0 2100.0 2400.0 2900.0 3300.0
-1500.0 1600.0 1900.0 2100.0 2500.0 3100.0
-1700.0 1900.0 2100.0 2400.0 2700.0 3100.0
-1400.0 1500.0 2100.0 2800.0 3100.0 3200.0
-1400.0 1600.0 2100.0 2800.0 3000.0 3200.0
-1700.0 1800.0 2100.0 2700.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2600.0 2700.0 3000.0
-1500.0 1600.0 2100.0 2600.0 2700.0 3100.0
-1600.0 1700.0 2000.0 2500.0 2900.0 3200.0
-1900.0 2000.0 2300.0 2400.0 2700.0 3100.0
-1900.0 2100.0 2300.0 2500.0 2700.0 3100.0
-1900.0 2100.0 2400.0 2600.0 2800.0 3100.0
-1700.0 2200.0 2400.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2600.0 2900.0 3200.0 3300.0
-2000.0 2100.0 2300.0 2500.0 2800.0 3100.0
-1800.0 1900.0 2200.0 2400.0 2800.0 3200.0
-1900.0 2100.0 2700.0 2900.0 3200.0 3400.0
-1800.0 2100.0 2300.0 2800.0 2900.0 3100.0
-1800.0 2000.0 2200.0 2700.0 2900.0 3000.0
-1800.0 1900.0 2200.0 2700.0 2900.0 3000.0
-2100.0 2200.0 2600.0 2800.0 3000.0 3200.0
-1600.0 1700.0 2100.0 2400.0 2700.0 3100.0
-1800.0 2000.0 2200.0 2300.0 2600.0 3100.0
-1700.0 1900.0 2300.0 2600.0 2700.0 3000.0
-1800.0 2000.0 2300.0 2500.0 2900.0 3200.0
-1200.0 1400.0 2300.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2800.0 3000.0 3200.0
-1600.0 1800.0 2300.0 2700.0 3000.0 3100.0
-1700.0 1800.0 2300.0 2700.0 2900.0 3000.0
-1400.0 1500.0 2000.0 2200.0 2900.0 3200.0
-2000.0 2300.0 2400.0 2700.0 2900.0 3100.0
-1400.0 2100.0 2400.0 2800.0 3100.0 3200.0
-1500.0 1600.0 1900.0 2100.0 2900.0 3200.0
-1500.0 1700.0 2400.0 2600.0 3000.0 3200.0
-1300.0 1500.0 2300.0 2700.0 3100.0 3300.0
-1600.0 2100.0 2300.0 2600.0 3000.0 3200.0
-1900.0 2300.0 2400.0 2700.0 3000.0 3100.0
-1700.0 2300.0 2600.0 2900.0 3200.0 3300.0
-1700.0 2000.0 2200.0 2600.0 2800.0 3100.0
-1800.0 1900.0 2200.0 2600.0 2800.0 3100.0
-2000.0 2100.0 2500.0 2800.0 3000.0 3300.0
-2000.0 2100.0 2700.0 2900.0 3100.0 3300.0
-2100.0 2300.0 2800.0 2900.0 3100.0 3300.0
-1800.0 1900.0 2100.0 2500.0 2800.0 3200.0
-1700.0 1800.0 2200.0 2500.0 2700.0 3000.0
-1500.0 1700.0 2100.0 2500.0 2800.0 3100.0
-1800.0 2100.0 2400.0 2900.0 3200.0 3300.0
-1800.0 2100.0 2700.0 2900.0 3100.0 3300.0
-1700.0 2000.0 2200.0 2500.0 2800.0 3100.0
-1300.0 1900.0 2200.0 2600.0 2800.0 3000.0
-1400.0 1900.0 2300.0 2700.0 2900.0 3200.0
-1800.0 2200.0 2500.0 2800.0 3000.0 3100.0
-1800.0 2300.0 2600.0 2700.0 3000.0 3200.0
-1500.0 1700.0 2200.0 2500.0 2800.0 3100.0
-1500.0 1700.0 2100.0 2600.0 2800.0 3100.0
-1400.0 1500.0 1900.0 2700.0 3100.0 3200.0
-2000.0 2500.0 2900.0 3100.0 3300.0 3400.0
-1200.0 1800.0 2400.0 2700.0 3100.0 3300.0
-1700.0 1900.0 2100.0 2500.0 2700.0 3100.0
-1500.0 2300.0 2500.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2600.0 2700.0 3000.0
-1800.0 1900.0 2300.0 2500.0 2700.0 3100.0
-1900.0 2000.0 2300.0 2600.0 3000.0 3300.0
-1400.0 1600.0 2200.0 2600.0 2800.0 3200.0
-1400.0 1700.0 2300.0 2600.0 3000.0 3100.0
-1500.0 1700.0 2100.0 2500.0 2800.0 3200.0
-2200.0 2600.0 2900.0 3100.0 3400.0 3500.0
-2200.0 2500.0 2900.0 3100.0 3300.0 3500.0
-1800.0 2100.0 2400.0 2900.0 3100.0 3300.0
-1600.0 1800.0 2300.0 2600.0 2900.0 3100.0
-1200.0 1400.0 2200.0 2400.0 3000.0 3200.0
-1300.0 1700.0 2100.0 2400.0 2900.0 3100.0
-1600.0 1700.0 2100.0 2200.0 3000.0 3200.0
-1500.0 1600.0 2500.0 2800.0 3100.0 3300.0
-1400.0 1600.0 2300.0 2700.0 3000.0 3300.0
-1400.0 1600.0 2200.0 2500.0 2900.0 3100.0
-1300.0 1600.0 2300.0 2600.0 3100.0 3300.0
-1600.0 1700.0 2200.0 2400.0 2900.0 3200.0
-1700.0 1800.0 2100.0 2300.0 3000.0 3300.0
-1300.0 1400.0 2300.0 2600.0 2900.0 3200.0
-1300.0 1500.0 2300.0 2500.0 2900.0 3200.0
-1800.0 1900.0 2200.0 2400.0 2700.0 3100.0
-1800.0 1900.0 2200.0 2400.0 2800.0 3100.0
-1600.0 1700.0 2200.0 2400.0 2700.0 3100.0
-1400.0 1600.0 2200.0 2500.0 3000.0 3300.0
-1500.0 1700.0 2200.0 2400.0 3000.0 3400.0
-1600.0 1700.0 2200.0 2500.0 2700.0 3200.0
-1700.0 1800.0 2100.0 2200.0 2800.0 3200.0
-1600.0 1700.0 2100.0 2200.0 3100.0 3300.0
-1500.0 1600.0 2100.0 2200.0 3100.0 3300.0
-1000.0 1800.0 2200.0 2500.0 3100.0 3300.0
-1100.0 1700.0 2200.0 2500.0 3000.0 3200.0
-1400.0 1800.0 2100.0 2400.0 2800.0 3000.0
-1500.0 1800.0 2500.0 2700.0 3000.0 3200.0
-1900.0 2500.0 2800.0 3000.0 3400.0 3500.0
-2000.0 2500.0 2900.0 3200.0 3400.0 3500.0
-1400.0 1700.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1900.0 2300.0 2500.0 3000.0 3200.0
-1400.0 2000.0 2300.0 2600.0 2900.0 3100.0
-1400.0 1900.0 2200.0 2500.0 2700.0 3100.0
-1600.0 1800.0 2000.0 2400.0 3000.0 3200.0
-1300.0 1800.0 2400.0 2700.0 3100.0 3300.0
-1400.0 1600.0 2400.0 2600.0 3100.0 3200.0
-1400.0 1500.0 1600.0 2400.0 3200.0 3300.0
-1900.0 2300.0 2600.0 2900.0 3100.0 3200.0
-1100.0 1700.0 2500.0 2600.0 3100.0 3300.0
-1300.0 1700.0 2400.0 2500.0 3000.0 3300.0
-1400.0 1700.0 2400.0 2500.0 3000.0 3400.0
-1400.0 1600.0 2400.0 2500.0 2900.0 3400.0
-1400.0 1700.0 2400.0 2500.0 3100.0 3400.0
-1500.0 1600.0 2300.0 2600.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2400.0 3000.0 3200.0
-1600.0 1800.0 2200.0 2300.0 3000.0 3100.0
-1500.0 1900.0 2400.0 2700.0 3000.0 3200.0
-1300.0 1800.0 2400.0 2700.0 3300.0 3400.0
-1400.0 1700.0 2200.0 2500.0 2900.0 3200.0
-1800.0 2100.0 2500.0 2700.0 3100.0 3400.0
-1000.0 1500.0 1800.0 2200.0 3000.0 3100.0
-2100.0 2600.0 2900.0 3100.0 3300.0 3400.0
-1900.0 2000.0 2200.0 2500.0 3100.0 3300.0
-1700.0 1900.0 2300.0 2600.0 2900.0 3300.0
-1600.0 1800.0 2000.0 2200.0 3100.0 3300.0
-1300.0 1700.0 2300.0 2600.0 3100.0 3200.0
-1400.0 2100.0 2400.0 2700.0 3100.0 3300.0
-1200.0 1500.0 2200.0 2600.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2500.0 3000.0 3100.0
-1600.0 1900.0 2300.0 2500.0 3000.0 3100.0
-1500.0 1800.0 2600.0 2800.0 3200.0 3400.0
-1600.0 1700.0 2300.0 2500.0 3100.0 3400.0
-1500.0 1600.0 2300.0 2600.0 3100.0 3400.0
-1200.0 1500.0 2500.0 2600.0 3100.0 3400.0
-1200.0 1500.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1600.0 2500.0 2600.0 3100.0 3300.0
-1900.0 2300.0 2600.0 2900.0 3400.0 3500.0
-900.0 1500.0 2600.0 2700.0 3100.0 3200.0
-2100.0 2500.0 2900.0 3100.0 3300.0 3400.0
-1400.0 2100.0 2300.0 2500.0 3000.0 3300.0
-1200.0 1600.0 1700.0 2300.0 3100.0 3200.0
-1100.0 1800.0 2200.0 2600.0 3000.0 3200.0
-1500.0 2000.0 2400.0 2700.0 3100.0 3200.0
-2000.0 2100.0 2400.0 2600.0 2900.0 3300.0
-1400.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1200.0 1600.0 2300.0 2500.0 3000.0 3200.0
-1500.0 1600.0 2300.0 2500.0 3100.0 3200.0
-2300.0 2500.0 2700.0 2800.0 3100.0 3300.0
-2200.0 2300.0 2500.0 2700.0 3100.0 3200.0
-1300.0 1900.0 2300.0 2500.0 2800.0 3000.0
-1200.0 1800.0 2300.0 2500.0 3000.0 3300.0
-1400.0 1600.0 2400.0 2600.0 3200.0 3400.0
-1500.0 1600.0 2300.0 2500.0 3100.0 3400.0
-1400.0 1900.0 2400.0 2500.0 2700.0 3100.0
-1200.0 1600.0 2200.0 2600.0 3100.0 3300.0
-1300.0 1600.0 2300.0 2600.0 3100.0 3400.0
-1500.0 1600.0 2200.0 2500.0 3100.0 3400.0
-1600.0 2000.0 2500.0 2700.0 3000.0 3200.0
-1600.0 1700.0 2000.0 2300.0 3000.0 3200.0
-1400.0 1700.0 1800.0 2300.0 3100.0 3200.0
-2100.0 2200.0 2400.0 2600.0 3200.0 3300.0
-1600.0 1900.0 2400.0 2500.0 2700.0 3200.0
-2200.0 2300.0 2500.0 2700.0 3100.0 3300.0
-2200.0 2300.0 2600.0 2700.0 3100.0 3300.0
-1400.0 1800.0 2300.0 2500.0 2800.0 3200.0
-1600.0 1800.0 2300.0 2500.0 2700.0 3100.0
-1400.0 1600.0 1800.0 2500.0 2900.0 3000.0
-1400.0 1600.0 1900.0 2600.0 3000.0 3200.0
-1500.0 1700.0 2000.0 2600.0 3000.0 3200.0
-1400.0 1700.0 2400.0 2500.0 3100.0 3300.0
-2300.0 2400.0 2700.0 3000.0 3200.0 3400.0
-1300.0 1700.0 2100.0 2300.0 3100.0 3200.0
-1300.0 1700.0 2100.0 2300.0 3000.0 3100.0
-1300.0 1700.0 2000.0 2200.0 3000.0 3100.0
-1400.0 1700.0 1900.0 2300.0 3000.0 3100.0
-1400.0 1600.0 1800.0 2300.0 2900.0 3000.0
-1300.0 1800.0 2400.0 2600.0 3000.0 3300.0
-2200.0 2300.0 2500.0 2800.0 3000.0 3200.0
-1900.0 2200.0 2400.0 2600.0 2900.0 3300.0
-1900.0 2100.0 2400.0 2600.0 3200.0 3400.0
-1900.0 2400.0 2600.0 2800.0 3200.0 3400.0
-1800.0 2100.0 2500.0 2600.0 3200.0 3400.0
-1500.0 1900.0 2400.0 2600.0 2900.0 3100.0
-1200.0 1600.0 2300.0 2500.0 3200.0 3300.0
-1100.0 1400.0 2300.0 2400.0 3000.0 3300.0
-1000.0 1800.0 2400.0 2500.0 3300.0 3400.0
-1000.0 1700.0 2400.0 2500.0 3300.0 3400.0
-2000.0 2400.0 2800.0 3000.0 3300.0 3500.0
-1400.0 2100.0 2500.0 2700.0 3300.0 3400.0
-1200.0 1900.0 2500.0 2600.0 3200.0 3300.0
-1400.0 2000.0 2500.0 2600.0 3100.0 3300.0
-1800.0 2200.0 2700.0 3000.0 3300.0 3500.0
-1700.0 2200.0 2400.0 2700.0 3100.0 3300.0
-1000.0 2000.0 2300.0 2400.0 3300.0 3400.0
-1400.0 1900.0 2400.0 2600.0 3300.0 3400.0
-1300.0 1800.0 2400.0 2500.0 3100.0 3300.0
-1600.0 2000.0 2500.0 2600.0 3200.0 3300.0
-2100.0 2500.0 2700.0 3000.0 3200.0 3400.0
-1600.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1400.0 1700.0 1900.0 2100.0 3300.0 3400.0
-1500.0 1700.0 2000.0 2200.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2300.0 2600.0 2900.0
-1600.0 1700.0 2300.0 2500.0 2800.0 3000.0
-1600.0 1700.0 2200.0 2300.0 2900.0 3200.0
-1300.0 1500.0 2300.0 2400.0 2800.0 3200.0
-1400.0 1700.0 2300.0 2400.0 3000.0 3200.0
-1600.0 1700.0 2100.0 2300.0 2900.0 3300.0
-1500.0 2100.0 2300.0 2600.0 3100.0 3300.0
-1100.0 1500.0 2200.0 2300.0 3100.0 3300.0
-1000.0 1800.0 2300.0 2400.0 3100.0 3200.0
-900.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1000.0 1800.0 2400.0 2500.0 3100.0 3200.0
-1700.0 2200.0 2500.0 2900.0 3400.0 3500.0
-1300.0 1900.0 2300.0 2400.0 3300.0 3400.0
-1100.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1200.0 1700.0 2300.0 2400.0 3200.0 3400.0
-1300.0 1700.0 2300.0 2500.0 3200.0 3300.0
-1200.0 1500.0 2200.0 2300.0 3000.0 3200.0
-1200.0 1800.0 2200.0 2300.0 3000.0 3200.0
-1000.0 1800.0 2400.0 2500.0 3100.0 3300.0
-900.0 1800.0 2600.0 2700.0 3300.0 3400.0
-900.0 1900.0 2700.0 2800.0 3300.0 3400.0
-1800.0 2400.0 2700.0 3100.0 3400.0 3500.0
-1400.0 1600.0 2200.0 2400.0 2900.0 3200.0
-1700.0 2300.0 2500.0 2700.0 3300.0 3400.0
-1400.0 1900.0 2400.0 2600.0 3200.0 3400.0
-1300.0 1500.0 2200.0 2400.0 2700.0 3100.0
-1500.0 1600.0 2000.0 2200.0 2900.0 3100.0
-1500.0 1600.0 1800.0 1900.0 2800.0 3300.0
-1700.0 1800.0 2000.0 2300.0 3000.0 3300.0
-2200.0 2400.0 2600.0 2700.0 3300.0 3400.0
-1700.0 1900.0 2300.0 2400.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2400.0 2700.0 3100.0
-1700.0 2300.0 2600.0 3000.0 3300.0 3400.0
-2200.0 2300.0 2500.0 2700.0 3100.0 3400.0
-1600.0 1800.0 2000.0 2200.0 3200.0 3300.0
-2100.0 2500.0 2700.0 2900.0 3400.0 3500.0
-2100.0 2400.0 2600.0 2700.0 3100.0 3300.0
-2100.0 2400.0 2700.0 3100.0 3300.0 3400.0
-1400.0 1700.0 2200.0 2600.0 2900.0 3200.0
-1000.0 1900.0 2200.0 2400.0 3100.0 3200.0
-1100.0 1600.0 2500.0 2600.0 3100.0 3300.0
-1300.0 1600.0 2200.0 2300.0 2800.0 3300.0
-1000.0 2000.0 2500.0 2600.0 3300.0 3400.0
-1700.0 2200.0 2400.0 2700.0 3200.0 3400.0
-1200.0 2000.0 2400.0 2500.0 3100.0 3200.0
-1100.0 1700.0 2100.0 2200.0 3000.0 3200.0
-1100.0 1600.0 2100.0 2200.0 3100.0 3300.0
-1100.0 1600.0 2200.0 2300.0 3200.0 3300.0
-1300.0 1700.0 2300.0 2400.0 3300.0 3400.0
-1300.0 1800.0 2300.0 2400.0 3300.0 3400.0
-1000.0 1800.0 2300.0 2400.0 3100.0 3300.0
-1400.0 2000.0 2300.0 2500.0 2900.0 3200.0
-1100.0 1900.0 2400.0 2500.0 3100.0 3200.0
-1000.0 2000.0 2600.0 2700.0 3300.0 3400.0
-1200.0 1600.0 2200.0 2300.0 3100.0 3300.0
-1300.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1000.0 1700.0 2400.0 2600.0 3300.0 3400.0
-1000.0 1700.0 2400.0 2600.0 3200.0 3300.0
-2000.0 2400.0 2700.0 3100.0 3300.0 3400.0
-1500.0 1900.0 2200.0 2400.0 3200.0 3300.0
-1400.0 1700.0 2100.0 2200.0 3100.0 3300.0
-2200.0 2400.0 2600.0 2900.0 3300.0 3400.0
-1300.0 1900.0 2100.0 2500.0 3000.0 3200.0
-1900.0 2100.0 2300.0 2400.0 3000.0 3300.0
-1100.0 2200.0 2600.0 2700.0 3300.0 3400.0
-1700.0 1900.0 2400.0 2500.0 3000.0 3400.0
-1800.0 2100.0 2600.0 2900.0 3100.0 3400.0
-1900.0 2300.0 2900.0 3100.0 3300.0 3400.0
-1900.0 2400.0 2600.0 3000.0 3300.0 3500.0
-1400.0 2100.0 2400.0 2500.0 2700.0 3000.0
-1300.0 1600.0 1900.0 2100.0 2900.0 3000.0
-1900.0 2000.0 2200.0 2300.0 3000.0 3300.0
-1300.0 1600.0 2200.0 2500.0 3000.0 3300.0
-1100.0 1800.0 2300.0 2500.0 3100.0 3300.0
-1100.0 1700.0 2300.0 2500.0 3000.0 3200.0
-1200.0 1600.0 2300.0 2400.0 3000.0 3200.0
-1300.0 1600.0 2200.0 2400.0 2900.0 3200.0
-1800.0 2300.0 2600.0 3000.0 3300.0 3500.0
-1500.0 2000.0 2400.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2200.0 2500.0 2800.0 3000.0
-1800.0 2100.0 2300.0 2400.0 2700.0 3000.0
-1800.0 2100.0 2300.0 2500.0 2900.0 3200.0
-1700.0 1900.0 2100.0 2700.0 2900.0 3200.0
-1800.0 2100.0 2300.0 2600.0 2900.0 3000.0
-1600.0 1800.0 2100.0 2400.0 2600.0 2900.0
-1800.0 1900.0 2400.0 2800.0 3000.0 3100.0
-2000.0 2400.0 2700.0 2900.0 3200.0 3400.0
-1900.0 2100.0 2800.0 2900.0 3200.0 3400.0
-2000.0 2100.0 2500.0 2800.0 2900.0 3100.0
-1800.0 1900.0 2500.0 2600.0 2900.0 3300.0
-1600.0 1700.0 2000.0 2100.0 3000.0 3200.0
-1600.0 1700.0 2000.0 2100.0 2900.0 3200.0
-2000.0 2200.0 2400.0 2800.0 3100.0 3300.0
-2100.0 2300.0 2800.0 2900.0 3300.0 3400.0
-1900.0 2000.0 2300.0 2400.0 2900.0 3100.0
-1500.0 1800.0 2300.0 2500.0 3000.0 3300.0
-1200.0 1800.0 2500.0 2600.0 2900.0 3000.0
-1400.0 1700.0 2200.0 2600.0 2900.0 3000.0
-1500.0 1700.0 2200.0 2600.0 3000.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2900.0 3200.0
-1800.0 1900.0 2200.0 2600.0 2900.0 3200.0
-1800.0 2000.0 2200.0 2400.0 2800.0 3100.0
-1400.0 1600.0 1900.0 2100.0 2700.0 3200.0
-1500.0 2000.0 2200.0 2500.0 3000.0 3200.0
-1700.0 1800.0 2000.0 2200.0 3100.0 3300.0
-1800.0 1900.0 2100.0 2400.0 3000.0 3100.0
-1800.0 2100.0 2400.0 2600.0 3000.0 3100.0
-2000.0 2300.0 2600.0 2800.0 3000.0 3300.0
-2100.0 2300.0 2800.0 2900.0 3200.0 3400.0
-1800.0 1900.0 2500.0 2800.0 3100.0 3200.0
-1800.0 2000.0 2200.0 2500.0 2900.0 3000.0
-1700.0 1800.0 2100.0 2700.0 2900.0 3000.0
-1700.0 1800.0 2600.0 2800.0 3100.0 3300.0
-1600.0 2000.0 2300.0 2800.0 3100.0 3300.0
-1500.0 1600.0 1900.0 2000.0 2900.0 3200.0
-2100.0 2300.0 2700.0 2800.0 3000.0 3200.0
-2000.0 2200.0 2400.0 2600.0 3100.0 3200.0
-1800.0 2100.0 2400.0 2500.0 3000.0 3200.0
-1800.0 2100.0 2500.0 2600.0 2900.0 3200.0
-2100.0 2400.0 2800.0 2900.0 3300.0 3400.0
-1800.0 2000.0 2300.0 2600.0 3100.0 3400.0
-1700.0 2000.0 2300.0 2600.0 2900.0 3300.0
-1800.0 1900.0 2300.0 2500.0 2800.0 3000.0
-1400.0 1600.0 2200.0 2500.0 2900.0 3300.0
-1600.0 1700.0 2100.0 2300.0 2600.0 3100.0
-1700.0 1800.0 2100.0 2500.0 2800.0 3200.0
-1500.0 1600.0 2200.0 2700.0 2800.0 3200.0
-2100.0 2300.0 2700.0 2800.0 3100.0 3300.0
-1600.0 1700.0 2000.0 2400.0 3000.0 3300.0
-1500.0 1600.0 2600.0 2800.0 3100.0 3300.0
-1800.0 2000.0 2400.0 2600.0 2900.0 3100.0
-1700.0 1800.0 2300.0 2500.0 2600.0 3100.0
-1500.0 1800.0 2100.0 2500.0 2900.0 3300.0
-1600.0 1800.0 2100.0 2500.0 3000.0 3300.0
-1700.0 1800.0 2300.0 2400.0 2800.0 3100.0
-1600.0 1700.0 2000.0 2300.0 2800.0 3100.0
-1700.0 1800.0 2200.0 2400.0 2700.0 3100.0
-2000.0 2500.0 2800.0 3000.0 3400.0 3500.0
-1900.0 2400.0 2800.0 2900.0 3400.0 3500.0
-1600.0 1700.0 2400.0 2700.0 2900.0 3100.0
-1600.0 1700.0 2500.0 2600.0 2900.0 3100.0
-1500.0 1700.0 2200.0 2600.0 2900.0 3100.0
-1700.0 2000.0 2200.0 2500.0 2900.0 3200.0
-1500.0 1700.0 2200.0 2700.0 3200.0 3300.0
-1400.0 1500.0 2100.0 2500.0 3000.0 3200.0
-1200.0 1500.0 2200.0 2400.0 2800.0 3200.0
-1500.0 1600.0 2000.0 2100.0 2900.0 3200.0
-1800.0 1900.0 2100.0 2500.0 2900.0 3200.0
-1500.0 1800.0 2300.0 2500.0 2800.0 3200.0
-1500.0 1800.0 2500.0 2800.0 3100.0 3300.0
-1300.0 1800.0 2500.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2300.0 2700.0 2900.0 3000.0
-1500.0 1600.0 2200.0 2400.0 2600.0 3100.0
-1600.0 2000.0 2500.0 2600.0 3000.0 3300.0
-1500.0 1600.0 2000.0 2600.0 2800.0 3000.0
-1500.0 1600.0 2200.0 2600.0 2700.0 3000.0
-1200.0 1600.0 2200.0 2400.0 3000.0 3200.0
-1800.0 2300.0 2500.0 2800.0 3000.0 3100.0
-1500.0 1600.0 2500.0 2800.0 2900.0 3200.0
-1300.0 1500.0 2300.0 2800.0 3100.0 3200.0
-1700.0 1800.0 2100.0 2500.0 2800.0 3000.0
-1400.0 1800.0 2200.0 2600.0 3000.0 3200.0
-1500.0 1700.0 2000.0 2700.0 3100.0 3200.0
-1400.0 1600.0 2300.0 2600.0 3000.0 3300.0
-1700.0 2100.0 2700.0 2900.0 3300.0 3500.0
-1700.0 1800.0 2300.0 2700.0 2800.0 3100.0
-1600.0 1800.0 2200.0 2600.0 2700.0 3000.0
-1900.0 2300.0 2400.0 2600.0 2800.0 3100.0
-1300.0 1600.0 2100.0 2200.0 3100.0 3300.0
-1500.0 1800.0 2400.0 2700.0 3000.0 3100.0
-1600.0 1800.0 2000.0 2600.0 2900.0 3000.0
-1600.0 1800.0 2100.0 2700.0 2900.0 3000.0
-1600.0 1700.0 2300.0 2700.0 3000.0 3100.0
-1700.0 1800.0 2400.0 2700.0 2900.0 3100.0
-1800.0 1900.0 2500.0 2600.0 3000.0 3100.0
-1700.0 1800.0 2100.0 2400.0 2700.0 3200.0
-1700.0 2000.0 2200.0 2500.0 2800.0 3000.0
-2000.0 2400.0 2500.0 2700.0 3000.0 3100.0
-1800.0 2000.0 2600.0 2700.0 3100.0 3200.0
-2200.0 2400.0 2700.0 2900.0 3100.0 3300.0
-2300.0 2500.0 2700.0 2900.0 3100.0 3300.0
-1800.0 2200.0 2300.0 2600.0 3000.0 3100.0
-1700.0 2100.0 2300.0 2800.0 3100.0 3200.0
-2000.0 2400.0 2600.0 2800.0 3000.0 3200.0
-1500.0 2000.0 2200.0 2600.0 3100.0 3300.0
-1100.0 1600.0 2200.0 2600.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2500.0 2700.0 3000.0
-1900.0 2300.0 2400.0 2600.0 2800.0 3000.0
-1700.0 2100.0 2300.0 2600.0 2900.0 3000.0
-1600.0 1700.0 2000.0 2200.0 2600.0 3100.0
-1600.0 1900.0 2200.0 2400.0 3000.0 3100.0
-1300.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1600.0 2100.0 2300.0 2600.0 2900.0 3000.0
-1700.0 2100.0 2300.0 2500.0 2800.0 3000.0
-1600.0 2100.0 2300.0 2500.0 2800.0 3000.0
-1500.0 1800.0 2000.0 2300.0 2800.0 2900.0
-1300.0 1600.0 2300.0 2600.0 2900.0 3200.0
-1200.0 1700.0 2100.0 2600.0 3100.0 3300.0
-1800.0 2200.0 2600.0 2700.0 3200.0 3300.0
-1600.0 1700.0 1900.0 2100.0 3100.0 3200.0
-1500.0 2000.0 2300.0 2500.0 3000.0 3300.0
-1600.0 1700.0 2000.0 2500.0 2700.0 2900.0
-1600.0 1800.0 2100.0 2500.0 2900.0 3000.0
-1600.0 1700.0 2100.0 2500.0 2700.0 2900.0
-1600.0 1700.0 2200.0 2500.0 2700.0 2900.0
-1500.0 1700.0 2000.0 2600.0 2800.0 3000.0
-1200.0 1600.0 2200.0 2400.0 2800.0 3000.0
-1800.0 2200.0 2400.0 2600.0 2800.0 3000.0
-1700.0 2000.0 2200.0 2500.0 2700.0 3100.0
-1700.0 2000.0 2200.0 2500.0 2700.0 3000.0
-1600.0 1900.0 2300.0 2600.0 2800.0 3200.0
-1200.0 1400.0 2000.0 2600.0 2800.0 3000.0
-1400.0 1600.0 2200.0 2600.0 3000.0 3300.0
-1500.0 1700.0 2200.0 2400.0 2700.0 2900.0
-1600.0 1700.0 2200.0 2500.0 2800.0 3000.0
-1600.0 1700.0 2100.0 2400.0 2700.0 3000.0
-1900.0 2100.0 2400.0 2600.0 3000.0 3100.0
-1900.0 2500.0 2700.0 2800.0 3100.0 3200.0
-1800.0 2200.0 2500.0 2600.0 3000.0 3200.0
-1900.0 2200.0 2400.0 2500.0 2800.0 3100.0
-1800.0 2100.0 2300.0 2500.0 2700.0 3000.0
-2000.0 2300.0 2400.0 2600.0 2900.0 3100.0
-1400.0 1600.0 1800.0 1900.0 2700.0 3200.0
-1400.0 1600.0 1700.0 1900.0 2800.0 3100.0
-2100.0 2200.0 2600.0 3000.0 3200.0 3300.0
-1700.0 2000.0 2200.0 2400.0 2700.0 2900.0
-1500.0 1600.0 1900.0 2400.0 2600.0 2700.0
-1600.0 1700.0 2000.0 2400.0 2600.0 2800.0
-1900.0 2000.0 2500.0 2800.0 2900.0 3200.0
-1500.0 1600.0 1900.0 2100.0 2700.0 3200.0
-1500.0 1700.0 2000.0 2200.0 2900.0 3300.0
-1800.0 2000.0 2700.0 2800.0 3200.0 3300.0
-1700.0 1800.0 2400.0 2700.0 3300.0 3400.0
-1600.0 1900.0 2500.0 2700.0 3300.0 3400.0
-1200.0 1800.0 2100.0 2400.0 3100.0 3200.0
-1200.0 1800.0 2100.0 2500.0 3200.0 3300.0
-1600.0 1700.0 2200.0 2600.0 2900.0 3200.0
-1800.0 2200.0 2500.0 2600.0 3200.0 3400.0
-1000.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1100.0 2000.0 2600.0 2700.0 3200.0 3300.0
-1300.0 1800.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1700.0 1800.0 2400.0 3000.0 3100.0
-1500.0 1800.0 2000.0 2400.0 3100.0 3200.0
-1200.0 1400.0 1500.0 2300.0 3100.0 3200.0
-2100.0 2200.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2100.0 2400.0 2900.0 3100.0
-1400.0 1500.0 2100.0 2400.0 2800.0 3200.0
-1100.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1200.0 2000.0 2300.0 2700.0 3100.0 3200.0
-1300.0 1700.0 2200.0 2500.0 2900.0 3000.0
-1400.0 1700.0 1900.0 2600.0 2900.0 3100.0
-1200.0 2000.0 2300.0 2700.0 3200.0 3300.0
-1500.0 2200.0 2400.0 2600.0 3200.0 3300.0
-1400.0 1800.0 2000.0 2500.0 3000.0 3100.0
-1400.0 2000.0 2300.0 2500.0 3200.0 3300.0
-1900.0 2400.0 2600.0 2700.0 3100.0 3300.0
-1300.0 1600.0 1700.0 2200.0 3000.0 3100.0
-1300.0 1600.0 2500.0 2600.0 3100.0 3300.0
-1500.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1600.0 2400.0 2600.0 3200.0 3400.0
-1400.0 2000.0 2300.0 2500.0 2700.0 3000.0
-1500.0 1900.0 2300.0 2500.0 2700.0 3100.0
-1500.0 1600.0 1800.0 2500.0 2800.0 3000.0
-1300.0 1800.0 2200.0 2600.0 3100.0 3200.0
-1300.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1300.0 1700.0 2100.0 2400.0 3100.0 3300.0
-1300.0 1900.0 2300.0 2600.0 3000.0 3200.0
-1200.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1700.0 2200.0 2500.0 2600.0 3200.0 3400.0
-1600.0 2000.0 2200.0 2300.0 3100.0 3200.0
-1800.0 1900.0 2300.0 2600.0 3200.0 3300.0
-1800.0 1900.0 2100.0 2500.0 3200.0 3300.0
-1900.0 2000.0 2100.0 2500.0 3300.0 3400.0
-1700.0 2100.0 2600.0 2800.0 3300.0 3500.0
-1600.0 1800.0 2200.0 2700.0 3200.0 3300.0
-1400.0 2000.0 2300.0 2400.0 2600.0 3000.0
-1400.0 1600.0 2100.0 2300.0 3100.0 3200.0
-1100.0 1900.0 2500.0 2600.0 3300.0 3400.0
-1200.0 1600.0 2300.0 2600.0 3100.0 3400.0
-1400.0 1600.0 2100.0 2400.0 3000.0 3300.0
-1400.0 1700.0 2100.0 2500.0 3100.0 3300.0
-1200.0 2000.0 2700.0 2800.0 3300.0 3400.0
-1700.0 1800.0 2000.0 2300.0 3300.0 3400.0
-1300.0 1600.0 1800.0 2100.0 3100.0 3200.0
-1800.0 1900.0 2100.0 2200.0 3200.0 3400.0
-1800.0 1900.0 2100.0 2300.0 3300.0 3400.0
-1800.0 1900.0 2200.0 2300.0 3100.0 3300.0
-1800.0 2300.0 2800.0 2900.0 3200.0 3300.0
-1900.0 2200.0 2500.0 2600.0 3200.0 3300.0
-1300.0 1600.0 2300.0 2500.0 2900.0 3300.0
-1400.0 1600.0 2300.0 2500.0 2900.0 3300.0
-1400.0 1700.0 2400.0 2500.0 2900.0 3200.0
-1500.0 1700.0 2100.0 2200.0 3100.0 3200.0
-1500.0 1700.0 2100.0 2200.0 3100.0 3300.0
-1500.0 1600.0 2100.0 2300.0 2900.0 3300.0
-1300.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1200.0 1900.0 2200.0 2500.0 3000.0 3200.0
-1000.0 1300.0 2100.0 2200.0 2900.0 3200.0
-1400.0 1600.0 1700.0 2000.0 3300.0 3400.0
-1300.0 1500.0 1600.0 2000.0 3300.0 3400.0
-1300.0 1500.0 1700.0 1900.0 3300.0 3400.0
-1500.0 1600.0 2100.0 2300.0 3100.0 3400.0
-1500.0 1600.0 2300.0 2500.0 2700.0 3200.0
-1400.0 2000.0 2300.0 2400.0 2700.0 3200.0
-1200.0 1500.0 2400.0 2600.0 2900.0 3200.0
-1500.0 1600.0 2300.0 2400.0 2700.0 3300.0
-1500.0 1700.0 2200.0 2400.0 2600.0 3100.0
-1500.0 1700.0 2300.0 2500.0 3100.0 3400.0
-1600.0 1700.0 2400.0 2600.0 3000.0 3400.0
-1600.0 1700.0 2500.0 2700.0 3100.0 3400.0
-1400.0 1500.0 2300.0 2400.0 3000.0 3300.0
-1500.0 1600.0 2100.0 2300.0 3000.0 3200.0
-1500.0 1600.0 2200.0 2400.0 2900.0 3200.0
-1500.0 1700.0 2400.0 2500.0 2900.0 3200.0
-1400.0 1900.0 2200.0 2300.0 2800.0 3200.0
-1500.0 1800.0 2100.0 2200.0 3000.0 3300.0
-2000.0 2100.0 2500.0 2600.0 3000.0 3400.0
-1000.0 1600.0 2200.0 2300.0 3200.0 3400.0
-1300.0 1500.0 2300.0 2600.0 2900.0 3300.0
-1400.0 1600.0 2500.0 2600.0 2900.0 3200.0
-1400.0 1600.0 2100.0 2400.0 3100.0 3300.0
-1500.0 2000.0 2300.0 2500.0 3100.0 3300.0
-1000.0 1700.0 2100.0 2200.0 3200.0 3300.0
-1500.0 1700.0 2200.0 2400.0 3200.0 3400.0
-1600.0 1800.0 2300.0 2400.0 3000.0 3100.0
-1300.0 1500.0 2100.0 2200.0 3000.0 3300.0
-1200.0 1400.0 2200.0 2300.0 3000.0 3300.0
-1600.0 1700.0 1900.0 2200.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2300.0 3000.0 3400.0
-1400.0 1500.0 2200.0 2500.0 2800.0 3100.0
-1800.0 1900.0 2300.0 2500.0 3000.0 3400.0
-1500.0 1700.0 2100.0 2500.0 2700.0 3100.0
-1600.0 1900.0 2400.0 2700.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2500.0 2700.0 3300.0
-1800.0 1900.0 2400.0 2500.0 2800.0 3300.0
-1300.0 1600.0 2100.0 2300.0 3000.0 3300.0
-1300.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1100.0 1500.0 2500.0 2600.0 3100.0 3400.0
-1600.0 1700.0 2200.0 2500.0 2600.0 3100.0
-1500.0 1600.0 2200.0 2500.0 2600.0 3100.0
-1600.0 2200.0 2600.0 2800.0 3100.0 3300.0
-2000.0 2200.0 2600.0 2700.0 3300.0 3400.0
-1500.0 2000.0 2200.0 2400.0 2600.0 2900.0
-1500.0 1800.0 2200.0 2400.0 3100.0 3400.0
-1800.0 2200.0 2600.0 2800.0 3400.0 3500.0
-1600.0 1700.0 2200.0 2600.0 3200.0 3400.0
-1800.0 2000.0 2300.0 2600.0 3200.0 3400.0
-1600.0 1800.0 2200.0 2600.0 3200.0 3400.0
-1500.0 1600.0 2100.0 2400.0 2800.0 3200.0
-1500.0 1800.0 2000.0 2600.0 3200.0 3300.0
-1200.0 1800.0 1900.0 2200.0 3100.0 3200.0
-1500.0 1600.0 2200.0 2400.0 3200.0 3300.0
-1800.0 1900.0 2600.0 2800.0 3000.0 3300.0
-1300.0 1600.0 2300.0 2400.0 3000.0 3100.0
-2000.0 2100.0 2400.0 2600.0 3000.0 3100.0
-2000.0 2100.0 2500.0 2600.0 2900.0 3100.0
-1800.0 2000.0 2500.0 2600.0 3000.0 3100.0
-1800.0 2300.0 2700.0 2800.0 3400.0 3500.0
-1200.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1600.0 2000.0 2500.0 2700.0 3100.0 3400.0
-1900.0 2100.0 2600.0 2700.0 3000.0 3200.0
-1500.0 1900.0 2600.0 2800.0 3200.0 3300.0
-1600.0 1800.0 2200.0 2700.0 3200.0 3400.0
-1400.0 1800.0 2400.0 2600.0 2900.0 3200.0
-1500.0 1700.0 2500.0 2600.0 3000.0 3200.0
-1800.0 2100.0 2600.0 2800.0 3400.0 3500.0
-1700.0 2000.0 2600.0 2800.0 3000.0 3300.0
-1800.0 2100.0 2700.0 2900.0 3400.0 3500.0
-1600.0 1700.0 2600.0 2700.0 3100.0 3400.0
-1800.0 1900.0 2400.0 2600.0 2800.0 3000.0
-1600.0 2000.0 2500.0 2600.0 2900.0 3200.0
-1400.0 1800.0 2400.0 2500.0 2900.0 3100.0
-1500.0 1800.0 2400.0 2500.0 2900.0 3200.0
-1200.0 1400.0 2300.0 2500.0 2900.0 3200.0
-1400.0 1600.0 2500.0 2700.0 3000.0 3300.0
-1500.0 1900.0 2500.0 2700.0 3000.0 3300.0
-1000.0 1400.0 2600.0 2700.0 3100.0 3300.0
-1400.0 1700.0 2100.0 2300.0 2900.0 3000.0
-1700.0 1800.0 2400.0 2600.0 2800.0 3000.0
-1500.0 2000.0 2100.0 2500.0 3000.0 3100.0
-2000.0 2100.0 2300.0 2400.0 3100.0 3300.0
-2100.0 2200.0 2600.0 2800.0 3100.0 3200.0
-2100.0 2200.0 2600.0 2700.0 3000.0 3200.0
-1800.0 2000.0 2600.0 2800.0 3100.0 3400.0
-1700.0 2000.0 2500.0 2900.0 3100.0 3300.0
-1700.0 2000.0 2500.0 2900.0 3100.0 3400.0
-1600.0 1800.0 2500.0 2800.0 3000.0 3200.0
-1500.0 1800.0 2200.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2300.0 2600.0 3200.0 3300.0
-1500.0 1600.0 2400.0 2600.0 2800.0 3100.0
-1200.0 1600.0 2200.0 2600.0 3000.0 3200.0
-1500.0 1600.0 2000.0 2300.0 2900.0 3200.0
-1900.0 2000.0 2400.0 2700.0 3200.0 3400.0
-1900.0 2000.0 2400.0 2700.0 2800.0 3200.0
-1500.0 1700.0 2300.0 2600.0 3200.0 3400.0
-1700.0 1800.0 2400.0 2500.0 2800.0 3100.0
-1500.0 1600.0 2200.0 2400.0 2900.0 3100.0
-1500.0 1600.0 2200.0 2500.0 3100.0 3300.0
-1600.0 2000.0 2200.0 2400.0 2700.0 3100.0
-1500.0 1700.0 2300.0 2600.0 2900.0 3300.0
-1700.0 1800.0 2100.0 2300.0 2900.0 3100.0
-1400.0 1500.0 2000.0 2500.0 2700.0 3000.0
-1800.0 1900.0 2300.0 2400.0 2800.0 3100.0
-1300.0 1800.0 2200.0 2500.0 2900.0 3100.0
-1300.0 1900.0 2300.0 2700.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2500.0 2700.0 3100.0
-1600.0 1700.0 2200.0 2600.0 3100.0 3300.0
-1400.0 1500.0 2300.0 2500.0 2800.0 3000.0
-1300.0 1700.0 2100.0 2500.0 3000.0 3300.0
-1600.0 1800.0 2200.0 2400.0 2800.0 3200.0
-1400.0 1500.0 2200.0 2500.0 3200.0 3300.0
-1800.0 1900.0 2200.0 2500.0 3000.0 3100.0
-1300.0 1500.0 2200.0 2400.0 2900.0 3100.0
-1300.0 1500.0 2300.0 2500.0 3100.0 3300.0
-1100.0 1500.0 2400.0 2500.0 3000.0 3200.0
-1600.0 1700.0 2400.0 2600.0 2800.0 3100.0
-1500.0 1600.0 2400.0 2500.0 2800.0 3100.0
-1500.0 1600.0 2000.0 2500.0 2800.0 3100.0
-1200.0 1700.0 2400.0 2600.0 3200.0 3300.0
-1100.0 1600.0 2400.0 2500.0 3200.0 3400.0
-1100.0 1500.0 2400.0 2500.0 3000.0 3400.0
-1100.0 1600.0 2400.0 2500.0 3100.0 3300.0
-1900.0 2000.0 2400.0 2500.0 2900.0 3100.0
-1300.0 1500.0 2200.0 2300.0 2700.0 3100.0
-1600.0 1900.0 2500.0 2800.0 3200.0 3300.0
-1900.0 2100.0 2600.0 2900.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2600.0 3000.0 3300.0
-1800.0 1900.0 2400.0 2500.0 2900.0 3000.0
-1300.0 1500.0 2300.0 2400.0 2900.0 3000.0
-1200.0 1700.0 1800.0 2300.0 2900.0 3000.0
-1200.0 1600.0 1800.0 2200.0 2900.0 3000.0
-1200.0 1700.0 2100.0 2300.0 3100.0 3200.0
-1400.0 1900.0 2100.0 2400.0 3000.0 3200.0
-1100.0 1500.0 2500.0 2600.0 3000.0 3300.0
-1300.0 1400.0 2400.0 2500.0 2800.0 3300.0
-1300.0 1500.0 2300.0 2500.0 3200.0 3400.0
-1300.0 1900.0 2300.0 2700.0 3100.0 3200.0
-1700.0 1900.0 2200.0 2400.0 2700.0 3100.0
-1400.0 1500.0 2000.0 2500.0 2600.0 3000.0
-1500.0 1600.0 2000.0 2400.0 2600.0 3000.0
-1400.0 1700.0 2400.0 2600.0 3000.0 3300.0
-2000.0 2100.0 2300.0 2500.0 2900.0 3100.0
-1900.0 2000.0 2400.0 2500.0 2800.0 3000.0
-1800.0 1900.0 2200.0 2400.0 2700.0 3000.0
-1400.0 1600.0 1900.0 2300.0 2600.0 3000.0
-1600.0 2000.0 2600.0 2800.0 3300.0 3400.0
-1200.0 1600.0 1800.0 2100.0 3200.0 3300.0
-1900.0 2300.0 2700.0 2800.0 3400.0 3500.0
-1500.0 1600.0 2200.0 2500.0 2700.0 3100.0
-1700.0 2100.0 2300.0 2500.0 2900.0 3200.0
-1300.0 1500.0 2200.0 2500.0 3000.0 3300.0
-1400.0 1500.0 2100.0 2500.0 2600.0 2900.0
-1500.0 1600.0 2200.0 2300.0 2800.0 3300.0
-1500.0 1600.0 1800.0 2100.0 2800.0 2900.0
-1700.0 1800.0 2200.0 2400.0 2600.0 3100.0
-1600.0 1900.0 2600.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2600.0 3000.0 3400.0
-1200.0 1500.0 2300.0 2400.0 2900.0 3300.0
-1600.0 2100.0 2500.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2300.0 2500.0 2600.0 2900.0
-1500.0 1600.0 2400.0 2600.0 3000.0 3100.0
-1600.0 1800.0 2600.0 2800.0 3000.0 3200.0
-1400.0 1700.0 2200.0 2500.0 3100.0 3400.0
-1600.0 1700.0 2300.0 2600.0 2700.0 3100.0
-1600.0 1700.0 2100.0 2500.0 2700.0 3100.0
-2000.0 2200.0 2500.0 2700.0 3100.0 3400.0
-1900.0 2100.0 2400.0 2600.0 3000.0 3400.0
-1400.0 1800.0 2100.0 2600.0 2900.0 3100.0
-1000.0 1800.0 2100.0 2300.0 3100.0 3200.0
-1400.0 1500.0 2200.0 2400.0 3000.0 3300.0
-1300.0 1800.0 2200.0 2300.0 3000.0 3200.0
-1100.0 1500.0 2300.0 2400.0 3000.0 3200.0
-1400.0 1500.0 2300.0 2400.0 2900.0 3300.0
-1400.0 1500.0 2200.0 2400.0 2800.0 3300.0
-1200.0 1600.0 2100.0 2200.0 3200.0 3300.0
-1600.0 1800.0 2100.0 2300.0 2500.0 3100.0
-1500.0 1600.0 2400.0 2600.0 3000.0 3400.0
-1500.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1900.0 2500.0 2600.0 2900.0 3200.0 3300.0
-1300.0 1500.0 2100.0 2500.0 2700.0 3100.0
-1200.0 1400.0 2400.0 2500.0 2800.0 3200.0
-1600.0 1700.0 2300.0 2400.0 2900.0 3400.0
-1100.0 1800.0 2200.0 2300.0 3300.0 3400.0
-1800.0 2200.0 2500.0 2800.0 3100.0 3400.0
-1200.0 1700.0 2100.0 2700.0 3100.0 3200.0
-1300.0 1600.0 2100.0 2600.0 3000.0 3200.0
-2000.0 2200.0 2300.0 2400.0 3100.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3100.0 3400.0
-1300.0 1700.0 2000.0 2600.0 3200.0 3300.0
-1100.0 1700.0 2300.0 2400.0 3200.0 3400.0
-1100.0 1600.0 2300.0 2400.0 3200.0 3400.0
-1700.0 2300.0 2800.0 3000.0 3300.0 3400.0
-1700.0 2000.0 2300.0 2800.0 3200.0 3300.0
-1800.0 1900.0 2100.0 2600.0 3000.0 3200.0
-1300.0 2000.0 2200.0 2600.0 3000.0 3200.0
-1300.0 1500.0 2300.0 2400.0 3000.0 3400.0
-1600.0 1700.0 2100.0 2300.0 2800.0 3200.0
-1700.0 1800.0 2400.0 2700.0 2800.0 3200.0
-1800.0 1900.0 2500.0 2700.0 2800.0 3200.0
-1700.0 1800.0 2100.0 2300.0 2900.0 3300.0
-1500.0 1700.0 2300.0 2400.0 2700.0 3200.0
-1600.0 2100.0 2500.0 2800.0 3100.0 3200.0
-1400.0 1700.0 2300.0 2700.0 3000.0 3300.0
-900.0 1400.0 2300.0 2500.0 3100.0 3300.0
-1700.0 1800.0 2300.0 2400.0 3000.0 3400.0
-2000.0 2100.0 2400.0 2600.0 2900.0 3100.0
-1900.0 2500.0 2600.0 2800.0 3300.0 3400.0
-1400.0 1500.0 2200.0 2300.0 2900.0 3300.0
-1600.0 1700.0 2000.0 2500.0 2600.0 3100.0
-1700.0 1800.0 2200.0 2300.0 2900.0 3200.0
-2100.0 2500.0 2800.0 3100.0 3300.0 3500.0
-1900.0 2400.0 2600.0 2700.0 3300.0 3400.0
-1700.0 2100.0 2500.0 2600.0 3300.0 3400.0
-1100.0 1500.0 2300.0 2400.0 3100.0 3400.0
-1200.0 1500.0 2300.0 2400.0 3300.0 3400.0
-1200.0 1800.0 2200.0 2400.0 3300.0 3400.0
-1500.0 1900.0 2200.0 2300.0 3100.0 3300.0
-1300.0 1600.0 1800.0 2100.0 3200.0 3300.0
-1600.0 1800.0 2400.0 2600.0 2900.0 3300.0
-1700.0 1900.0 2400.0 2600.0 3000.0 3400.0
-1300.0 1800.0 2200.0 2300.0 2900.0 3200.0
-1400.0 1700.0 2200.0 2300.0 3200.0 3400.0
-1400.0 1600.0 2200.0 2400.0 3200.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3200.0 3500.0
-1600.0 1700.0 2500.0 2600.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2500.0 2900.0 3400.0
-1700.0 1800.0 2300.0 2400.0 2900.0 3500.0
-1700.0 1800.0 2300.0 2400.0 3000.0 3500.0
-1600.0 1700.0 2300.0 2500.0 2700.0 3400.0
-1800.0 1900.0 2400.0 2500.0 3000.0 3500.0
-1300.0 1600.0 1800.0 2500.0 3100.0 3300.0
-1200.0 1700.0 2000.0 2200.0 3200.0 3300.0
-1200.0 1600.0 2200.0 2300.0 3200.0 3400.0
-1200.0 1600.0 2200.0 2400.0 3200.0 3400.0
-1600.0 2300.0 2600.0 2900.0 3300.0 3400.0
-1300.0 1600.0 2200.0 2300.0 3000.0 3400.0
-1900.0 2100.0 2400.0 2500.0 2800.0 3100.0
-1400.0 2000.0 2500.0 2700.0 3100.0 3200.0
-1700.0 1800.0 2400.0 2500.0 2800.0 3300.0
-1900.0 2000.0 2400.0 2600.0 2800.0 3400.0
-1600.0 2200.0 2500.0 2800.0 3200.0 3300.0
-1200.0 1700.0 2300.0 2400.0 3000.0 3300.0
-1200.0 1400.0 2200.0 2300.0 2900.0 3200.0
-1600.0 1800.0 2400.0 2700.0 3200.0 3400.0
-1600.0 1900.0 2400.0 2600.0 3100.0 3400.0
-1500.0 1800.0 2400.0 2600.0 3000.0 3400.0
-1600.0 1700.0 2400.0 2500.0 3100.0 3500.0
-1500.0 1600.0 2100.0 2300.0 2700.0 3200.0
-1500.0 1600.0 2100.0 2200.0 2600.0 3100.0
-1700.0 1900.0 2400.0 2700.0 3300.0 3400.0
-1200.0 1500.0 2200.0 2300.0 3300.0 3400.0
-1300.0 1600.0 2100.0 2200.0 3300.0 3400.0
-1400.0 1500.0 2100.0 2200.0 3200.0 3400.0
-1800.0 1900.0 2300.0 2400.0 2800.0 3300.0
-1900.0 2000.0 2400.0 2500.0 2800.0 3200.0
-2000.0 2100.0 2400.0 2600.0 2800.0 3200.0
-1500.0 2100.0 2300.0 2500.0 2800.0 3200.0
-1500.0 1800.0 2300.0 2400.0 3000.0 3200.0
-1700.0 1800.0 2600.0 2800.0 3000.0 3200.0
-1900.0 2500.0 2800.0 2900.0 3200.0 3300.0
-1100.0 1400.0 2500.0 2800.0 3000.0 3200.0
-1200.0 1400.0 2700.0 2900.0 3100.0 3300.0
-1200.0 1400.0 2600.0 2900.0 3000.0 3300.0
-1200.0 1400.0 2700.0 2900.0 3000.0 3400.0
-1200.0 1600.0 2600.0 2800.0 3100.0 3400.0
-1300.0 1800.0 2400.0 2500.0 2900.0 3200.0
-1400.0 1700.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1900.0 2300.0 2400.0 2900.0 3300.0
-1800.0 1900.0 2600.0 2700.0 3100.0 3400.0
-1800.0 2000.0 2600.0 2700.0 3100.0 3400.0
-1800.0 1900.0 2600.0 2700.0 3000.0 3400.0
-1400.0 1800.0 2300.0 2500.0 2700.0 3000.0
-1600.0 1700.0 2500.0 2700.0 3200.0 3400.0
-1500.0 1700.0 2400.0 2700.0 3000.0 3200.0
-1500.0 1900.0 2400.0 2700.0 3100.0 3200.0
-1900.0 2100.0 2700.0 2800.0 3200.0 3300.0
-1600.0 2000.0 2300.0 2400.0 3200.0 3400.0
-1500.0 1700.0 2500.0 2700.0 3200.0 3300.0
-1700.0 1800.0 2500.0 2700.0 3200.0 3300.0
-1800.0 1900.0 2600.0 2800.0 3100.0 3400.0
-1700.0 1800.0 2500.0 2800.0 2900.0 3200.0
-1600.0 1700.0 2500.0 2700.0 3000.0 3300.0
-1200.0 1700.0 2700.0 2800.0 3100.0 3300.0
-1200.0 1500.0 2700.0 2900.0 3100.0 3300.0
-1500.0 1800.0 2400.0 2700.0 3100.0 3400.0
-1400.0 1600.0 2600.0 2800.0 3000.0 3300.0
-1600.0 1800.0 2500.0 2700.0 3000.0 3400.0
-1500.0 1800.0 2300.0 2600.0 3100.0 3400.0
-1500.0 1700.0 2300.0 2500.0 2700.0 3300.0
-2000.0 2100.0 2500.0 2700.0 2900.0 3300.0
-2200.0 2300.0 2600.0 2700.0 3200.0 3400.0
-1400.0 1800.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2600.0 2700.0 3100.0 3400.0
-1300.0 1700.0 2100.0 2500.0 3100.0 3300.0
-2100.0 2200.0 2600.0 2800.0 3300.0 3400.0
-2100.0 2300.0 2700.0 2800.0 3300.0 3400.0
-1600.0 1700.0 2500.0 2700.0 3100.0 3300.0
-1400.0 1700.0 2600.0 2700.0 3200.0 3400.0
-1200.0 1500.0 2600.0 2800.0 3100.0 3300.0
-1800.0 1900.0 2500.0 2600.0 3000.0 3400.0
-1700.0 1800.0 2400.0 2600.0 2900.0 3000.0
-1200.0 1600.0 2800.0 3000.0 3200.0 3300.0
-1600.0 1700.0 2300.0 2600.0 3200.0 3400.0
-1700.0 1800.0 2200.0 2500.0 2800.0 3300.0
-1700.0 1800.0 2600.0 2700.0 3000.0 3400.0
-1500.0 1600.0 2600.0 2800.0 3000.0 3300.0
-1100.0 1300.0 2400.0 2900.0 3000.0 3200.0
-1100.0 1500.0 2700.0 2800.0 3100.0 3300.0
-1600.0 1800.0 2000.0 2300.0 3300.0 3400.0
-1800.0 2000.0 2100.0 2400.0 3300.0 3400.0
-1800.0 2000.0 2500.0 2600.0 2900.0 3300.0
-1600.0 1700.0 2400.0 2700.0 2900.0 3300.0
-1600.0 1700.0 2600.0 2800.0 3100.0 3300.0
-1500.0 1700.0 1900.0 2100.0 3000.0 3300.0
-1900.0 2000.0 2100.0 2300.0 3200.0 3400.0
-2100.0 2200.0 2500.0 2600.0 2900.0 3300.0
-1800.0 2000.0 2200.0 2400.0 3300.0 3400.0
-1700.0 1800.0 2100.0 2300.0 3300.0 3400.0
-2000.0 2200.0 2500.0 2600.0 3200.0 3400.0
-1700.0 1900.0 2100.0 2800.0 3100.0 3200.0
-1800.0 1900.0 2500.0 2900.0 3100.0 3200.0
-1800.0 1900.0 2500.0 2900.0 3000.0 3200.0
-1300.0 1500.0 1800.0 1900.0 2700.0 3200.0
-1000.0 1300.0 2400.0 3000.0 3300.0 3400.0
-1400.0 1600.0 1800.0 1900.0 2900.0 3300.0
-1500.0 1700.0 1900.0 2000.0 2800.0 3200.0
-1800.0 2000.0 2300.0 2500.0 2700.0 3100.0
-1800.0 1900.0 2200.0 2300.0 2800.0 3200.0
-1200.0 1900.0 2500.0 2600.0 2900.0 3000.0
-1200.0 1900.0 2400.0 2600.0 2900.0 3000.0
-1800.0 2000.0 2100.0 2400.0 3000.0 3200.0
-1900.0 2200.0 2600.0 2900.0 3100.0 3200.0
-1600.0 1700.0 2000.0 2100.0 2700.0 3200.0
-1600.0 1800.0 2300.0 2800.0 3100.0 3200.0
-1700.0 1900.0 2400.0 2700.0 2900.0 3300.0
-1900.0 2000.0 2400.0 2800.0 3200.0 3300.0
-1400.0 1600.0 2300.0 2500.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2200.0 2700.0 3200.0
-2000.0 2100.0 2600.0 2900.0 3300.0 3400.0
-1200.0 1500.0 2300.0 2500.0 2900.0 3200.0
-1200.0 1400.0 2200.0 2400.0 2900.0 3200.0
-1600.0 2200.0 2400.0 2600.0 3200.0 3400.0
-1700.0 1800.0 2400.0 2500.0 3000.0 3100.0
-1700.0 1800.0 2200.0 2600.0 3100.0 3200.0
-1200.0 1900.0 2300.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2000.0 2800.0 3200.0 3300.0
-1500.0 1700.0 2400.0 2500.0 3000.0 3100.0
-1400.0 2000.0 2400.0 2600.0 3000.0 3300.0
-1200.0 1400.0 2400.0 2800.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2100.0 2900.0 3300.0
-1500.0 1600.0 2000.0 2200.0 2800.0 3300.0
-1200.0 1500.0 2100.0 2200.0 3000.0 3300.0
-1400.0 2000.0 2300.0 2700.0 3100.0 3300.0
-1600.0 1700.0 2000.0 2700.0 3200.0 3300.0
-1700.0 1900.0 2300.0 2600.0 2800.0 3200.0
-2100.0 2300.0 2600.0 2800.0 3100.0 3200.0
-1400.0 1800.0 2400.0 2500.0 3000.0 3200.0
-1500.0 2100.0 2400.0 2700.0 3000.0 3300.0
-1600.0 1700.0 2100.0 2700.0 3000.0 3100.0
-1500.0 1800.0 2200.0 2700.0 3100.0 3300.0
-1300.0 1500.0 2400.0 2500.0 2900.0 3200.0
-1200.0 1500.0 2500.0 2600.0 3000.0 3200.0
-1100.0 1500.0 2400.0 2500.0 2900.0 3300.0
-1800.0 1900.0 2400.0 2500.0 2800.0 3000.0
-1700.0 1800.0 2100.0 2800.0 3100.0 3200.0
-1900.0 2200.0 2400.0 2900.0 3100.0 3200.0
-1500.0 1700.0 2300.0 2600.0 2800.0 3100.0
-1300.0 1500.0 1900.0 2500.0 3000.0 3100.0
-1700.0 1800.0 2400.0 2700.0 3100.0 3200.0
-1900.0 2500.0 2900.0 3100.0 3300.0 3400.0
-1500.0 1800.0 2000.0 2600.0 2900.0 3100.0
-1900.0 2300.0 2500.0 2800.0 3200.0 3400.0
-1500.0 2100.0 2500.0 2700.0 3200.0 3400.0
-1500.0 2100.0 2500.0 2700.0 2900.0 3200.0
-1800.0 2300.0 2800.0 2900.0 3300.0 3400.0
-1600.0 1900.0 2200.0 2600.0 3000.0 3300.0
-1400.0 1900.0 2400.0 2600.0 2800.0 3100.0
-1300.0 1700.0 2500.0 2600.0 3000.0 3200.0
-1400.0 1800.0 2100.0 2500.0 2800.0 3100.0
-1700.0 2400.0 2600.0 3000.0 3300.0 3400.0
-2200.0 2400.0 2700.0 3000.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2700.0 3000.0 3200.0
-1300.0 1700.0 2300.0 2600.0 2900.0 3200.0
-1400.0 1900.0 2200.0 2500.0 2700.0 3000.0
-1500.0 1900.0 2200.0 2800.0 3100.0 3300.0
-1400.0 1600.0 1800.0 2200.0 3200.0 3400.0
-1700.0 2000.0 2200.0 2700.0 3200.0 3300.0
-1400.0 1900.0 2500.0 2700.0 3300.0 3400.0
-1500.0 2100.0 2300.0 2500.0 2800.0 3100.0
-1500.0 2000.0 2300.0 2500.0 2800.0 3100.0
-1500.0 1600.0 2400.0 2800.0 3000.0 3200.0
-1400.0 1600.0 2200.0 2700.0 3000.0 3100.0
-1200.0 1800.0 2000.0 2300.0 2900.0 3100.0
-1300.0 1900.0 2400.0 2700.0 3200.0 3300.0
-2200.0 2500.0 2800.0 3100.0 3400.0 3500.0
-2100.0 2400.0 2900.0 3000.0 3100.0 3300.0
-1200.0 1500.0 1700.0 2300.0 2900.0 3000.0
-1600.0 2200.0 2600.0 2800.0 3200.0 3300.0
-1700.0 2300.0 2500.0 2800.0 3100.0 3300.0
-1400.0 1900.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1700.0 2500.0 2600.0 3100.0 3400.0
-1300.0 1700.0 2500.0 2600.0 3100.0 3400.0
-1400.0 2100.0 2300.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1100.0 1900.0 2100.0 2500.0 3100.0 3200.0
-1300.0 1400.0 2500.0 2600.0 3000.0 3300.0
-1300.0 2000.0 2400.0 2600.0 3100.0 3300.0
-1500.0 2000.0 2300.0 2600.0 3200.0 3400.0
-1400.0 1900.0 2200.0 2700.0 3000.0 3200.0
-1600.0 2100.0 2500.0 2600.0 3000.0 3200.0
-1600.0 2100.0 2500.0 2700.0 3000.0 3200.0
-1500.0 2000.0 2500.0 2700.0 3000.0 3200.0
-1900.0 2400.0 2600.0 2900.0 3400.0 3500.0
-1400.0 1700.0 2300.0 2700.0 3000.0 3200.0
-1800.0 2300.0 2900.0 3100.0 3400.0 3500.0
-1700.0 2100.0 2300.0 2500.0 3000.0 3100.0
-1900.0 2100.0 2500.0 3000.0 3300.0 3400.0
-1300.0 1500.0 1800.0 2500.0 2800.0 3000.0
-1300.0 1400.0 2000.0 2400.0 2800.0 3200.0
-1300.0 2100.0 2400.0 2600.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2600.0 3000.0 3200.0
-1400.0 1900.0 2400.0 2600.0 3100.0 3200.0
-1300.0 1800.0 2500.0 2600.0 3100.0 3200.0
-1500.0 2100.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1700.0 2000.0 2700.0 2900.0 3100.0
-1400.0 2000.0 2200.0 2400.0 2700.0 3100.0
-1200.0 1400.0 2600.0 2700.0 2900.0 3100.0
-1500.0 2100.0 2300.0 2500.0 2700.0 3100.0
-1800.0 2100.0 2500.0 2600.0 3100.0 3200.0
-1200.0 1700.0 2100.0 2500.0 3200.0 3300.0
-1400.0 2100.0 2300.0 2700.0 3200.0 3300.0
-1700.0 2000.0 2600.0 2800.0 3100.0 3200.0
-1400.0 1700.0 2300.0 2700.0 3200.0 3300.0
-1300.0 1600.0 2200.0 2400.0 3100.0 3200.0
-1400.0 1500.0 2200.0 2500.0 3000.0 3200.0
-1400.0 1700.0 2300.0 2500.0 2800.0 3100.0
-1500.0 1700.0 2200.0 2500.0 2700.0 3100.0
-1500.0 1700.0 2200.0 2500.0 2900.0 3100.0
-1800.0 2000.0 2700.0 2900.0 3100.0 3400.0
-1300.0 1700.0 2100.0 2200.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2700.0 2900.0 3300.0
-1500.0 1600.0 2700.0 2800.0 3000.0 3300.0
-1400.0 1500.0 2500.0 2700.0 2900.0 3200.0
-1100.0 1600.0 2400.0 2600.0 3000.0 3200.0
-1600.0 2000.0 2700.0 2900.0 3300.0 3400.0
-1400.0 1500.0 2600.0 2800.0 3000.0 3300.0
-1400.0 1500.0 2600.0 2700.0 3000.0 3300.0
-1400.0 1500.0 2500.0 2700.0 2900.0 3300.0
-1700.0 1900.0 2600.0 2900.0 3100.0 3300.0
-1500.0 1600.0 2300.0 2700.0 3100.0 3200.0
-1200.0 1700.0 2300.0 2700.0 3000.0 3200.0
-1500.0 1600.0 2500.0 2800.0 3000.0 3300.0
-1500.0 1600.0 1700.0 1800.0 3100.0 3400.0
-1500.0 1600.0 2300.0 2700.0 3000.0 3300.0
-1300.0 1500.0 2600.0 2700.0 3200.0 3300.0
-2100.0 2200.0 2500.0 2700.0 3100.0 3200.0
-2100.0 2200.0 2800.0 3000.0 3200.0 3300.0
-1500.0 1700.0 2400.0 2600.0 2800.0 3100.0
-1500.0 1800.0 2400.0 2700.0 3000.0 3200.0
-1400.0 1700.0 2400.0 2700.0 3100.0 3200.0
-900.0 1500.0 2800.0 2900.0 3100.0 3300.0
-1400.0 1700.0 2500.0 2700.0 3100.0 3400.0
-1800.0 2000.0 2300.0 2800.0 3100.0 3300.0
-1200.0 1600.0 2300.0 2400.0 2900.0 3200.0
-1800.0 1900.0 2300.0 2600.0 3000.0 3100.0
-1300.0 1600.0 1900.0 2400.0 2900.0 3200.0
-1400.0 1600.0 2500.0 2700.0 2900.0 3300.0
-900.0 1600.0 2200.0 2300.0 3200.0 3300.0
-1300.0 1900.0 2200.0 2300.0 3100.0 3300.0
-1700.0 1900.0 2500.0 2900.0 3200.0 3300.0
-1400.0 1900.0 2500.0 2700.0 3200.0 3400.0
-1700.0 2000.0 2200.0 2500.0 2900.0 3000.0
-1200.0 1500.0 2600.0 2800.0 3100.0 3400.0
-1400.0 1700.0 2100.0 2600.0 3000.0 3300.0
-1400.0 1700.0 2500.0 2800.0 3200.0 3300.0
-1800.0 2400.0 2600.0 2900.0 3400.0 3500.0
-1900.0 2100.0 2500.0 2600.0 3100.0 3200.0
-2200.0 2500.0 2800.0 3000.0 3400.0 3500.0
-1600.0 1800.0 1900.0 2500.0 3100.0 3200.0
-1100.0 1600.0 2500.0 2600.0 3200.0 3400.0
-1700.0 2200.0 2500.0 2700.0 3100.0 3400.0
-1000.0 1700.0 2200.0 2300.0 3200.0 3300.0
-1100.0 1700.0 2200.0 2600.0 3100.0 3300.0
-1100.0 1700.0 2300.0 2700.0 3200.0 3300.0
-1500.0 1800.0 2100.0 2600.0 3200.0 3300.0
-1300.0 2100.0 2400.0 2600.0 2800.0 3200.0
-1800.0 1900.0 2200.0 2600.0 2800.0 3200.0
-1800.0 1900.0 2500.0 2600.0 3100.0 3200.0
-1400.0 2100.0 2300.0 2500.0 2700.0 3100.0
-1300.0 2000.0 2400.0 2500.0 2800.0 3200.0
-1600.0 2100.0 2600.0 2800.0 3200.0 3400.0
-1400.0 1800.0 2200.0 2400.0 3300.0 3400.0
-1300.0 1700.0 2200.0 2300.0 3300.0 3400.0
-1300.0 1600.0 2200.0 2300.0 3300.0 3400.0
-1300.0 1600.0 2300.0 2400.0 3300.0 3400.0
-1100.0 1700.0 2200.0 2300.0 3300.0 3400.0
-1500.0 1900.0 2200.0 2500.0 2700.0 3100.0
-1300.0 1700.0 1900.0 2200.0 3000.0 3100.0
-1400.0 1600.0 2500.0 2600.0 3300.0 3400.0
-1500.0 1600.0 2500.0 2600.0 3200.0 3400.0
-1000.0 1700.0 2600.0 2700.0 3300.0 3400.0
-1000.0 1600.0 2600.0 2700.0 3300.0 3400.0
-1400.0 1700.0 2500.0 2600.0 3000.0 3400.0
-1400.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1500.0 1600.0 2400.0 2600.0 3200.0 3400.0
-1600.0 2200.0 2500.0 2600.0 3200.0 3300.0
-1000.0 1900.0 2400.0 2500.0 3300.0 3400.0
-1200.0 1700.0 2200.0 2400.0 3200.0 3400.0
-2000.0 2200.0 2600.0 2900.0 3300.0 3400.0
-2200.0 2300.0 2700.0 2800.0 3300.0 3400.0
-2200.0 2300.0 2700.0 2800.0 3200.0 3300.0
-2000.0 2300.0 2400.0 2700.0 3100.0 3300.0
-2200.0 2300.0 2600.0 2800.0 3200.0 3300.0
-1500.0 2000.0 2300.0 2400.0 3200.0 3300.0
-1500.0 1600.0 1800.0 2500.0 3200.0 3300.0
-1100.0 1900.0 2200.0 2400.0 3000.0 3300.0
-1500.0 2100.0 2600.0 2700.0 3200.0 3400.0
-1400.0 1900.0 2400.0 2600.0 3000.0 3200.0
-1200.0 1800.0 2400.0 2600.0 3200.0 3300.0
-1200.0 1700.0 2700.0 2800.0 3200.0 3300.0
-1200.0 1600.0 2600.0 2700.0 3200.0 3300.0
-1300.0 1600.0 2500.0 2600.0 3000.0 3300.0
-1500.0 1600.0 2500.0 2700.0 2900.0 3300.0
-1500.0 1700.0 1800.0 2500.0 3100.0 3200.0
-1400.0 1700.0 1900.0 2600.0 3100.0 3200.0
-1300.0 1700.0 2500.0 2600.0 3200.0 3300.0
-1100.0 1400.0 2600.0 3000.0 3200.0 3300.0
-1100.0 1400.0 2600.0 2900.0 3100.0 3300.0
-1600.0 1800.0 1900.0 2600.0 3200.0 3300.0
-2000.0 2100.0 2600.0 2700.0 3100.0 3200.0
-1300.0 1700.0 2100.0 2300.0 3200.0 3300.0
-1100.0 1700.0 2800.0 2900.0 3200.0 3300.0
-1500.0 1700.0 2500.0 2600.0 2900.0 3200.0
-1400.0 1800.0 2600.0 2700.0 3200.0 3300.0
-1600.0 1700.0 2100.0 2400.0 3000.0 3300.0
-1300.0 1500.0 1600.0 2200.0 3000.0 3100.0
-1300.0 2000.0 2500.0 2700.0 3100.0 3200.0
-1800.0 2200.0 2500.0 2600.0 3200.0 3300.0
-1700.0 2200.0 2400.0 2600.0 2800.0 3100.0
-2000.0 2200.0 2600.0 2800.0 3000.0 3300.0
-1300.0 1400.0 2400.0 2700.0 3100.0 3300.0
-1500.0 1600.0 1900.0 2000.0 2900.0 3300.0
-1000.0 1200.0 2400.0 2500.0 3100.0 3400.0
-1800.0 1900.0 2200.0 2400.0 2600.0 3000.0
-1900.0 2000.0 2200.0 2600.0 2800.0 3000.0
-1300.0 1800.0 2200.0 2400.0 2900.0 3200.0
-1800.0 2100.0 2300.0 2500.0 2800.0 3000.0
-1500.0 2000.0 2300.0 2600.0 2800.0 3100.0
-1000.0 1400.0 2400.0 2500.0 3100.0 3300.0
-1300.0 1900.0 2700.0 2800.0 3200.0 3300.0
-1900.0 2200.0 2300.0 2500.0 2800.0 3100.0
-1900.0 2000.0 2200.0 2600.0 2800.0 3100.0
-1600.0 1700.0 2100.0 2200.0 2900.0 3200.0
-1500.0 1900.0 2200.0 2500.0 3000.0 3300.0
-1400.0 1900.0 2400.0 2800.0 3100.0 3300.0
-1900.0 2000.0 2300.0 2600.0 2800.0 3200.0
-1900.0 2100.0 2300.0 2600.0 2800.0 3200.0
-1600.0 1700.0 2300.0 2700.0 3100.0 3300.0
-1600.0 1800.0 2100.0 2300.0 2600.0 3000.0
-1600.0 1800.0 2100.0 2400.0 2600.0 3000.0
-1700.0 2000.0 2200.0 2500.0 3100.0 3300.0
-1600.0 1700.0 2000.0 2400.0 2600.0 3000.0
-1300.0 1500.0 2200.0 2400.0 2800.0 3200.0
-1300.0 1700.0 2200.0 2400.0 2900.0 3200.0
-1700.0 1900.0 2100.0 2300.0 2800.0 3100.0
-1200.0 1400.0 2300.0 2400.0 2900.0 3300.0
-1400.0 1500.0 2000.0 2200.0 2700.0 3000.0
-1200.0 1900.0 2400.0 2600.0 3000.0 3300.0
-1700.0 1800.0 2100.0 2300.0 2600.0 3100.0
-1900.0 2000.0 2200.0 2400.0 2700.0 3000.0
-1900.0 2100.0 2300.0 2400.0 2700.0 3000.0
-1400.0 1800.0 2200.0 2400.0 2700.0 3200.0
-1700.0 1800.0 2200.0 2300.0 2900.0 3300.0
-1700.0 2000.0 2500.0 2800.0 3400.0 3500.0
-1300.0 1500.0 2200.0 2300.0 3100.0 3200.0
-1400.0 1800.0 2100.0 2600.0 3000.0 3200.0
-1300.0 1900.0 2200.0 2500.0 3100.0 3300.0
-1500.0 2100.0 2600.0 2700.0 3200.0 3300.0
-1300.0 1800.0 2600.0 2700.0 3200.0 3300.0
-1000.0 1500.0 2700.0 2800.0 3100.0 3300.0
-2200.0 2300.0 2500.0 2900.0 3200.0 3400.0
-2100.0 2200.0 2500.0 2900.0 3100.0 3300.0
-1500.0 1600.0 2400.0 2700.0 3000.0 3300.0
-1300.0 1500.0 1600.0 2000.0 3200.0 3400.0
-1400.0 1600.0 1700.0 2000.0 3200.0 3400.0
-1700.0 1900.0 2700.0 2800.0 3200.0 3300.0
-1700.0 1900.0 2700.0 2800.0 3100.0 3300.0
-1500.0 1600.0 2300.0 2700.0 2800.0 3200.0
-1500.0 1600.0 2200.0 2500.0 2900.0 3300.0
-1200.0 1500.0 2100.0 2600.0 3000.0 3300.0
-1800.0 2300.0 2700.0 2800.0 3200.0 3400.0
-1000.0 1400.0 2400.0 2500.0 2900.0 3300.0
-1000.0 1500.0 2500.0 2600.0 2900.0 3200.0
-1900.0 2400.0 2700.0 3000.0 3200.0 3400.0
-1700.0 1900.0 2300.0 2400.0 3000.0 3400.0
-1300.0 1600.0 1700.0 2200.0 3100.0 3300.0
-1800.0 1900.0 2600.0 2900.0 3100.0 3300.0
-2300.0 2600.0 2800.0 2900.0 3300.0 3400.0
-1000.0 1500.0 2400.0 2500.0 3200.0 3300.0
-1400.0 1600.0 2100.0 2300.0 2900.0 3200.0
-1500.0 2000.0 2400.0 2600.0 2800.0 3000.0
-1400.0 1900.0 2300.0 2600.0 2800.0 3100.0
-1600.0 1700.0 2500.0 2600.0 2800.0 3200.0
-2000.0 2200.0 2800.0 3000.0 3300.0 3500.0
-2000.0 2400.0 2700.0 2800.0 3200.0 3300.0
-1400.0 1600.0 1700.0 1900.0 3200.0 3400.0
-2100.0 2200.0 2400.0 2700.0 3000.0 3300.0
-2100.0 2400.0 2800.0 3000.0 3100.0 3300.0
-1800.0 2000.0 2300.0 2400.0 3100.0 3400.0
-1400.0 1700.0 2600.0 2700.0 3000.0 3300.0
-1300.0 1700.0 2200.0 2500.0 3200.0 3400.0
-1500.0 1900.0 2300.0 2600.0 2800.0 3100.0
-2200.0 2500.0 2700.0 2800.0 3200.0 3400.0
-2100.0 2200.0 2500.0 2800.0 3000.0 3200.0
-1700.0 1900.0 2300.0 2600.0 2800.0 3000.0
-1800.0 2000.0 2400.0 2700.0 2900.0 3300.0
-1500.0 1800.0 2000.0 2400.0 3000.0 3100.0
-1500.0 1700.0 1800.0 2600.0 3100.0 3200.0
-1200.0 1700.0 2300.0 2600.0 3000.0 3200.0
-1400.0 1500.0 1900.0 2700.0 3000.0 3100.0
-1600.0 2100.0 2300.0 2700.0 3000.0 3100.0
-1700.0 2300.0 2400.0 2700.0 3100.0 3200.0
-1800.0 2300.0 2400.0 2700.0 2900.0 3100.0
-1400.0 1500.0 1900.0 2500.0 2800.0 3000.0
-1300.0 1500.0 1900.0 2600.0 3000.0 3100.0
-1500.0 1600.0 2000.0 2500.0 2900.0 3100.0
-1500.0 1900.0 2300.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2500.0 2700.0 3000.0 3100.0
-1400.0 1500.0 2000.0 2500.0 2800.0 3000.0
-1400.0 1500.0 2000.0 2600.0 3000.0 3100.0
-1700.0 2000.0 2200.0 2600.0 2700.0 3000.0
-1400.0 1700.0 2000.0 2500.0 3100.0 3200.0
-1700.0 1900.0 2400.0 2700.0 2800.0 3100.0
-1700.0 2000.0 2300.0 2500.0 2800.0 3100.0
-1400.0 1600.0 1900.0 2400.0 2700.0 3000.0
-1500.0 1700.0 1900.0 2400.0 2700.0 3000.0
-1400.0 1500.0 1900.0 2800.0 3100.0 3200.0
-1400.0 1900.0 2200.0 2600.0 3100.0 3200.0
-1200.0 1600.0 2200.0 2500.0 3000.0 3100.0
-1500.0 1800.0 2500.0 2800.0 3000.0 3200.0
-1200.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1700.0 2100.0 2300.0 2500.0 2700.0 3200.0
-1300.0 1600.0 2100.0 2300.0 2800.0 3200.0
-1800.0 2000.0 2200.0 2800.0 3100.0 3200.0
-2100.0 2400.0 2900.0 3000.0 3300.0 3500.0
-1700.0 1900.0 2600.0 2900.0 3200.0 3300.0
-2100.0 2500.0 2900.0 3000.0 3200.0 3300.0
-2000.0 2300.0 2800.0 2900.0 3100.0 3400.0
-1300.0 1500.0 2100.0 2400.0 2800.0 3200.0
-1600.0 1700.0 2000.0 2700.0 3000.0 3100.0
-1500.0 1800.0 2000.0 2500.0 3000.0 3100.0
-1500.0 1800.0 2200.0 2700.0 2900.0 3100.0
-1600.0 1700.0 2100.0 2400.0 2600.0 3100.0
-1500.0 1900.0 2300.0 2400.0 2900.0 3300.0
-1300.0 2000.0 2400.0 2700.0 3100.0 3200.0
-1300.0 2000.0 2300.0 2700.0 3300.0 3400.0
-1700.0 2200.0 2400.0 2800.0 3200.0 3300.0
-1400.0 1900.0 2600.0 2900.0 3200.0 3300.0
-1400.0 1700.0 2000.0 2400.0 3100.0 3200.0
-1400.0 1600.0 2300.0 2500.0 2700.0 3000.0
-1500.0 1600.0 2300.0 2600.0 3100.0 3200.0
-1500.0 1900.0 2200.0 2400.0 3300.0 3400.0
-1200.0 1900.0 2100.0 2400.0 2900.0 3100.0
-1000.0 2300.0 2600.0 2800.0 3200.0 3300.0
-2200.0 2300.0 2600.0 2900.0 3300.0 3400.0
-1400.0 1600.0 2600.0 2700.0 3200.0 3300.0
-1300.0 2100.0 2500.0 2700.0 3100.0 3200.0
-1400.0 1600.0 2500.0 2600.0 3000.0 3400.0
-1200.0 1800.0 2700.0 2800.0 3000.0 3100.0
-1100.0 2000.0 2600.0 2700.0 3100.0 3200.0
-1000.0 1900.0 2700.0 2800.0 3100.0 3200.0
-1100.0 1900.0 2700.0 2800.0 3200.0 3300.0
-1200.0 1800.0 2500.0 2600.0 3000.0 3200.0
-2000.0 2100.0 2500.0 2600.0 3100.0 3200.0
-1400.0 2000.0 2500.0 2700.0 3200.0 3300.0
-2300.0 2400.0 2900.0 3100.0 3300.0 3400.0
-1600.0 1900.0 2300.0 2500.0 2900.0 3100.0
-1300.0 2200.0 2400.0 2900.0 3300.0 3400.0
-1300.0 2100.0 2200.0 2500.0 3200.0 3300.0
-1300.0 1900.0 2500.0 2600.0 3000.0 3100.0
-1300.0 1900.0 2500.0 2600.0 3100.0 3200.0
-1300.0 2000.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1700.0 1800.0 2300.0 2600.0 3000.0 3400.0
-1600.0 1800.0 2300.0 2700.0 3200.0 3400.0
-1300.0 1500.0 1600.0 2600.0 3200.0 3300.0
-1300.0 1500.0 1600.0 2500.0 3300.0 3400.0
-1300.0 1500.0 1600.0 2700.0 3300.0 3400.0
-2100.0 2500.0 3000.0 3100.0 3300.0 3400.0
-1400.0 1900.0 2300.0 2400.0 3100.0 3200.0
-1600.0 2200.0 2300.0 2600.0 3300.0 3400.0
-1300.0 1600.0 1700.0 2700.0 3100.0 3200.0
-1800.0 2300.0 2500.0 2800.0 3100.0 3300.0
-1500.0 1600.0 2400.0 2600.0 3100.0 3400.0
-1200.0 1900.0 2200.0 2400.0 3000.0 3100.0
-1400.0 1900.0 2200.0 2700.0 3100.0 3200.0
-1300.0 1700.0 2300.0 2600.0 2900.0 3100.0
-1300.0 2000.0 2300.0 2600.0 3200.0 3300.0
-1800.0 1900.0 2400.0 2600.0 3200.0 3500.0
-1700.0 1800.0 2400.0 2700.0 2900.0 3300.0
-1400.0 2000.0 2400.0 2500.0 2700.0 2900.0
-1400.0 2100.0 2400.0 2500.0 2700.0 3100.0
-1500.0 1700.0 2300.0 2700.0 2900.0 3200.0
-1200.0 1300.0 2300.0 2800.0 3000.0 3200.0
-1200.0 1400.0 2100.0 2600.0 3000.0 3300.0
-1600.0 1700.0 2500.0 2700.0 2800.0 3200.0
-1700.0 2100.0 2200.0 2700.0 3000.0 3100.0
-1400.0 1500.0 2100.0 2400.0 2900.0 3200.0
-1700.0 2100.0 2200.0 2600.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2500.0 2900.0 3000.0
-1300.0 1500.0 2000.0 2600.0 2900.0 3000.0
-1800.0 1900.0 2100.0 2300.0 3000.0 3200.0
-1100.0 1500.0 2500.0 2800.0 3000.0 3200.0
-1900.0 2000.0 2200.0 2400.0 2800.0 3200.0
-1800.0 1900.0 2700.0 2800.0 3100.0 3300.0
-1200.0 1400.0 2000.0 2700.0 3000.0 3100.0
-1300.0 1400.0 1900.0 2000.0 2600.0 3200.0
-1000.0 1300.0 2400.0 2600.0 2800.0 3200.0
-1700.0 1800.0 2200.0 2400.0 2600.0 3000.0
-2000.0 2300.0 2400.0 2700.0 2900.0 3000.0
-1600.0 1700.0 2000.0 2200.0 2500.0 3100.0
-1700.0 2300.0 2700.0 2800.0 3200.0 3400.0
-1600.0 1700.0 2300.0 2600.0 2700.0 3000.0
-1400.0 1500.0 2000.0 2700.0 2900.0 3100.0
-1100.0 1400.0 2200.0 2600.0 2800.0 3000.0
-1700.0 2100.0 2300.0 2600.0 3000.0 3300.0
-1400.0 1500.0 1700.0 1800.0 2700.0 3200.0
-1500.0 1600.0 1900.0 2000.0 2600.0 3200.0
-1000.0 1300.0 2400.0 2600.0 2900.0 3300.0
-1300.0 1500.0 1900.0 2500.0 2700.0 3000.0
-1800.0 1900.0 2200.0 2600.0 2900.0 3300.0
-1300.0 1400.0 1700.0 1800.0 2700.0 3200.0
-1700.0 1800.0 2000.0 2500.0 2700.0 2900.0
-1800.0 2000.0 2300.0 2700.0 2800.0 3100.0
-1600.0 1700.0 2200.0 2800.0 2900.0 3100.0
-1800.0 2100.0 2800.0 2900.0 3200.0 3400.0
-1700.0 2100.0 2800.0 2900.0 3100.0 3400.0
-1900.0 2400.0 2700.0 2800.0 3400.0 3500.0
-1600.0 1700.0 2400.0 2700.0 2800.0 3200.0
-1600.0 1900.0 2200.0 2500.0 3000.0 3300.0
-1400.0 1500.0 2000.0 2500.0 2800.0 3100.0
-1200.0 1300.0 2100.0 2500.0 2700.0 3000.0
-1900.0 2200.0 2600.0 2800.0 3400.0 3500.0
-1500.0 1900.0 2600.0 2700.0 2900.0 3300.0
-1400.0 1500.0 2000.0 2100.0 2700.0 3100.0
-1600.0 1700.0 2100.0 2200.0 2600.0 3200.0
-1700.0 2200.0 2500.0 2700.0 3000.0 3100.0
-1800.0 2300.0 2500.0 2600.0 2900.0 3100.0
-1100.0 1300.0 2500.0 2700.0 2900.0 3200.0
-1400.0 1500.0 1900.0 2000.0 2600.0 3200.0
-1600.0 1700.0 2000.0 2100.0 2800.0 3300.0
-1300.0 1900.0 2300.0 2600.0 2700.0 3000.0
-1800.0 1900.0 2500.0 2700.0 2900.0 3100.0
-2100.0 2200.0 2700.0 3000.0 3100.0 3300.0
-2000.0 2100.0 2700.0 2900.0 3200.0 3400.0
-1500.0 1700.0 1800.0 2200.0 3200.0 3300.0
-1500.0 1800.0 2000.0 2700.0 3200.0 3300.0
-1800.0 1900.0 2100.0 2400.0 3100.0 3200.0
-1500.0 1600.0 2400.0 2500.0 3200.0 3300.0
-1400.0 1800.0 2400.0 2600.0 3300.0 3400.0
-1400.0 1800.0 2400.0 2600.0 3200.0 3400.0
-2300.0 2600.0 2800.0 3100.0 3300.0 3400.0
-2000.0 2100.0 2800.0 2900.0 3300.0 3400.0
-1400.0 1700.0 2600.0 2700.0 3200.0 3300.0
-1300.0 1700.0 2500.0 2700.0 3200.0 3300.0
-1500.0 1800.0 2200.0 2700.0 3000.0 3300.0
-1800.0 2000.0 2300.0 2500.0 2900.0 3300.0
-1300.0 1800.0 2400.0 2500.0 3200.0 3400.0
-1500.0 1900.0 2500.0 2600.0 3000.0 3300.0
-1700.0 1800.0 2700.0 2800.0 3200.0 3400.0
-1500.0 1800.0 2700.0 2800.0 3200.0 3400.0
-1500.0 1800.0 2700.0 2800.0 3300.0 3400.0
-1400.0 1600.0 2400.0 2500.0 3200.0 3300.0
-1600.0 1800.0 2400.0 2800.0 3100.0 3300.0
-1500.0 2100.0 2500.0 2600.0 3100.0 3300.0
-1500.0 1600.0 2500.0 2600.0 3000.0 3400.0
-1200.0 1900.0 2300.0 2500.0 3100.0 3300.0
-1500.0 1600.0 2300.0 2500.0 3200.0 3300.0
-1600.0 2300.0 2600.0 2800.0 3300.0 3400.0
-2100.0 2400.0 2500.0 2700.0 3200.0 3300.0
-1100.0 1800.0 2500.0 2600.0 2900.0 3200.0
-1400.0 1700.0 2100.0 2600.0 3000.0 3200.0
-1700.0 2000.0 2500.0 2600.0 3000.0 3100.0
-1100.0 1500.0 2500.0 2600.0 3100.0 3300.0
-1500.0 1600.0 2200.0 2400.0 2600.0 3200.0
-1600.0 1800.0 2300.0 2500.0 2900.0 3300.0
-1600.0 1700.0 2100.0 2300.0 3000.0 3200.0
-2000.0 2200.0 2600.0 2800.0 3300.0 3400.0
-1600.0 1700.0 1900.0 2400.0 3100.0 3300.0
-1200.0 1700.0 2300.0 2500.0 3100.0 3400.0
-1100.0 1600.0 1900.0 2200.0 3000.0 3100.0
-1400.0 1900.0 2300.0 2600.0 2900.0 3000.0
-1900.0 2200.0 2800.0 3000.0 3200.0 3400.0
-1400.0 1500.0 2200.0 2300.0 2700.0 3100.0
-1800.0 1900.0 2200.0 2600.0 3000.0 3300.0
-1700.0 1900.0 2200.0 2500.0 2700.0 3000.0
-1600.0 1800.0 2000.0 2400.0 2700.0 2800.0
-1900.0 2300.0 2700.0 2900.0 3100.0 3200.0
-1400.0 1500.0 2000.0 2400.0 2900.0 3000.0
-1800.0 2100.0 2200.0 2500.0 2700.0 3000.0
-1200.0 1300.0 1900.0 2500.0 3000.0 3100.0
-1100.0 1200.0 2500.0 2900.0 3000.0 3200.0
-1400.0 1500.0 1900.0 2000.0 2500.0 3100.0
-1400.0 1600.0 2000.0 2200.0 2500.0 3100.0
-1200.0 1700.0 2300.0 2700.0 3100.0 3300.0
-1900.0 2200.0 2300.0 2500.0 2700.0 3100.0
-1500.0 1600.0 2000.0 2100.0 2800.0 3300.0
-1500.0 1800.0 2000.0 2300.0 2600.0 2900.0
-2100.0 2200.0 2600.0 2700.0 3000.0 3100.0
-2100.0 2300.0 2700.0 2900.0 3200.0 3400.0
-1600.0 1700.0 1900.0 2000.0 2700.0 3100.0
-1300.0 1500.0 1800.0 1900.0 2500.0 3100.0
-1900.0 2500.0 2700.0 2900.0 3200.0 3300.0
-1200.0 1400.0 2000.0 2700.0 3200.0 3300.0
-1900.0 2500.0 2700.0 2800.0 3200.0 3300.0
-1200.0 1600.0 2200.0 2400.0 2900.0 3200.0
-2000.0 2200.0 2600.0 2700.0 3100.0 3400.0
-1500.0 1700.0 2000.0 2300.0 2600.0 3000.0
-1700.0 2100.0 2500.0 2700.0 3000.0 3100.0
-1800.0 2200.0 2500.0 2700.0 3000.0 3100.0
-2000.0 2400.0 2600.0 2900.0 3100.0 3200.0
-1700.0 2400.0 2500.0 2700.0 3100.0 3200.0
-1600.0 2000.0 2100.0 2600.0 3000.0 3100.0
-1500.0 2100.0 2400.0 2600.0 3000.0 3200.0
-1400.0 1600.0 2000.0 2600.0 3100.0 3200.0
-1500.0 1700.0 2000.0 2800.0 3100.0 3200.0
-1600.0 1700.0 2000.0 2700.0 3100.0 3200.0
-1400.0 2000.0 2300.0 2500.0 3000.0 3200.0
-1600.0 1800.0 2000.0 2300.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2700.0 2900.0 3200.0
-1100.0 1400.0 2200.0 2300.0 3200.0 3300.0
-1800.0 2400.0 2800.0 2900.0 3200.0 3300.0
-1700.0 2400.0 2800.0 2900.0 3200.0 3300.0
-2000.0 2200.0 2800.0 3000.0 3400.0 3500.0
-1300.0 1400.0 2200.0 2900.0 3100.0 3200.0
-1200.0 1400.0 2300.0 2900.0 3100.0 3200.0
-1600.0 1900.0 2300.0 2600.0 2900.0 3300.0
-1700.0 2200.0 2300.0 2700.0 3100.0 3200.0
-1200.0 1700.0 2400.0 2700.0 3000.0 3300.0
-1500.0 1700.0 1900.0 2500.0 2900.0 3100.0
-1700.0 1800.0 2200.0 2600.0 2900.0 3300.0
-1300.0 1400.0 1900.0 2600.0 3000.0 3100.0
-1200.0 1400.0 2200.0 2500.0 2900.0 3300.0
-1500.0 1800.0 2000.0 2500.0 2900.0 3000.0
-1300.0 1400.0 2300.0 2500.0 2900.0 3300.0
-1700.0 2100.0 2300.0 2700.0 3000.0 3100.0
-1700.0 2100.0 2300.0 2800.0 3000.0 3100.0
-1200.0 1300.0 2100.0 2800.0 3200.0 3300.0
-1300.0 1600.0 2100.0 2600.0 2900.0 3100.0
-1300.0 1400.0 1800.0 2500.0 2800.0 3000.0
-1500.0 1700.0 2400.0 2600.0 2900.0 3000.0
-2100.0 2200.0 2500.0 2600.0 3000.0 3100.0
-2200.0 2300.0 2500.0 2700.0 3000.0 3200.0
-1400.0 1800.0 2000.0 2300.0 3200.0 3300.0
-1600.0 1700.0 2400.0 2700.0 3100.0 3200.0
-1600.0 1700.0 2500.0 2700.0 3000.0 3200.0
-1900.0 2500.0 2600.0 2800.0 3200.0 3300.0
-1200.0 1400.0 2600.0 2800.0 3000.0 3300.0
-1800.0 2300.0 2500.0 3000.0 3300.0 3400.0
-1200.0 1400.0 2200.0 2700.0 3200.0 3300.0
-1100.0 1400.0 2400.0 2500.0 3100.0 3400.0
-1100.0 1300.0 2400.0 2500.0 3200.0 3400.0
-1000.0 1400.0 2400.0 2500.0 3000.0 3300.0
-1800.0 1900.0 2400.0 2700.0 3200.0 3400.0
-1600.0 1700.0 2200.0 2500.0 2800.0 3300.0
-2000.0 2200.0 2400.0 2800.0 2900.0 3100.0
-1300.0 1800.0 2700.0 2800.0 3200.0 3400.0
-1800.0 2200.0 2700.0 3000.0 3400.0 3500.0
-1800.0 1900.0 2300.0 2600.0 2700.0 3000.0
-1900.0 2000.0 2400.0 2600.0 2900.0 3400.0
-1600.0 1700.0 2300.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2500.0 2700.0 3200.0 3300.0
-2100.0 2500.0 2800.0 3000.0 3200.0 3400.0
-1800.0 2000.0 2300.0 2400.0 3000.0 3100.0
-2300.0 2400.0 2600.0 2900.0 3100.0 3300.0
-1600.0 1800.0 2400.0 2500.0 3000.0 3100.0
-2100.0 2500.0 2900.0 3100.0 3200.0 3300.0
-1600.0 1900.0 2500.0 2900.0 3100.0 3300.0
-1500.0 1800.0 2300.0 2400.0 3200.0 3400.0
-1300.0 1500.0 2700.0 2800.0 3100.0 3300.0
-1200.0 1500.0 2600.0 2700.0 3200.0 3300.0
-1000.0 1500.0 2700.0 2800.0 3200.0 3300.0
-1100.0 1600.0 2600.0 2700.0 3200.0 3300.0
-1500.0 1700.0 2600.0 2700.0 3000.0 3300.0
-1100.0 1700.0 2800.0 2900.0 3200.0 3400.0
-1300.0 1700.0 2300.0 2500.0 3300.0 3400.0
-1700.0 2100.0 2400.0 2500.0 3200.0 3300.0
-1500.0 1800.0 2100.0 2400.0 3300.0 3400.0
-2000.0 2100.0 2400.0 2600.0 2800.0 3100.0
-1600.0 1700.0 2300.0 2800.0 3100.0 3300.0
-1900.0 2100.0 2800.0 3000.0 3300.0 3400.0
-2000.0 2100.0 2300.0 2600.0 2900.0 3200.0
-1100.0 1500.0 2500.0 2700.0 2900.0 3300.0
-1600.0 1800.0 2200.0 2500.0 2700.0 2800.0
-2000.0 2200.0 2500.0 2600.0 3100.0 3200.0
-1400.0 1600.0 2100.0 2900.0 3100.0 3200.0
-1900.0 2400.0 2800.0 3000.0 3200.0 3300.0
-2000.0 2300.0 2500.0 2700.0 2900.0 3200.0
-1700.0 2100.0 2300.0 2800.0 3200.0 3300.0
-1400.0 2000.0 2300.0 2500.0 3100.0 3300.0
-2000.0 2500.0 2600.0 3000.0 3200.0 3300.0
-1500.0 1700.0 2500.0 2600.0 3000.0 3400.0
-1100.0 2000.0 2500.0 2700.0 3200.0 3300.0
-1400.0 1600.0 2600.0 2900.0 3100.0 3400.0
-1800.0 2300.0 2800.0 3000.0 3200.0 3300.0
-1700.0 2000.0 2100.0 2300.0 3300.0 3400.0
-1400.0 1700.0 1800.0 2300.0 3300.0 3400.0
-1400.0 1500.0 2300.0 2500.0 3000.0 3400.0
-1400.0 1700.0 2600.0 2700.0 3100.0 3200.0
-1500.0 1700.0 2600.0 2700.0 3200.0 3300.0
-1600.0 1800.0 2600.0 2700.0 3100.0 3300.0
-1200.0 1400.0 1500.0 2200.0 3100.0 3200.0
-1500.0 1600.0 2100.0 2400.0 2700.0 3200.0
-1000.0 1500.0 2600.0 2700.0 3000.0 3300.0
-1200.0 1500.0 1600.0 2100.0 3100.0 3200.0
-1800.0 2200.0 2600.0 3000.0 3400.0 3500.0
-1000.0 2300.0 2600.0 2700.0 3200.0 3300.0
-1400.0 1600.0 2100.0 2500.0 2800.0 3200.0
-1300.0 1900.0 2300.0 2500.0 2900.0 3300.0
-1500.0 1600.0 2400.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2500.0 2800.0 3100.0 3200.0
-1000.0 2100.0 2500.0 2600.0 3100.0 3400.0
-1700.0 1800.0 2100.0 2400.0 3000.0 3100.0
-2200.0 2300.0 2600.0 2700.0 3000.0 3300.0
-1900.0 2000.0 2700.0 2800.0 3300.0 3400.0
-1500.0 1700.0 2400.0 2500.0 2900.0 3100.0
-1100.0 1600.0 2800.0 2900.0 3200.0 3300.0
-2000.0 2600.0 2800.0 3000.0 3400.0 3500.0
-1900.0 2500.0 2800.0 3100.0 3400.0 3500.0
-1200.0 1700.0 2700.0 2800.0 3200.0 3400.0
-1300.0 1600.0 2700.0 2800.0 3100.0 3400.0
-1500.0 1700.0 2700.0 2800.0 3100.0 3400.0
-1300.0 1400.0 2500.0 2800.0 3200.0 3400.0
-1700.0 2000.0 2700.0 2800.0 3300.0 3400.0
-1800.0 1900.0 2600.0 2700.0 3300.0 3400.0
-1100.0 1800.0 2700.0 2800.0 3200.0 3300.0
-2100.0 2600.0 2700.0 3000.0 3300.0 3400.0
-1300.0 1600.0 1800.0 2100.0 2900.0 3000.0
-1300.0 1500.0 2200.0 2400.0 3100.0 3400.0
-1200.0 1500.0 1700.0 2000.0 3000.0 3100.0
-1200.0 1500.0 1700.0 2100.0 3000.0 3100.0
-1300.0 2000.0 2200.0 2400.0 2700.0 3000.0
-1500.0 1800.0 2100.0 2300.0 3300.0 3400.0
-1100.0 1600.0 1800.0 2200.0 3000.0 3100.0
-1000.0 1800.0 2100.0 2400.0 3000.0 3100.0
-1500.0 1600.0 2300.0 2400.0 2900.0 3400.0
-1400.0 1600.0 1800.0 2100.0 2900.0 3000.0
-1100.0 1500.0 2100.0 2200.0 3100.0 3200.0
-1300.0 1700.0 1800.0 2200.0 3000.0 3100.0
-1500.0 1700.0 2100.0 2300.0 2700.0 2900.0
-1100.0 1700.0 1900.0 2100.0 2900.0 3000.0
-1400.0 1700.0 2100.0 2400.0 2900.0 3200.0
-1300.0 1600.0 1800.0 2300.0 3000.0 3100.0
-1200.0 1500.0 1700.0 2300.0 3000.0 3100.0
-1600.0 1800.0 1900.0 2300.0 3000.0 3100.0
-1700.0 2200.0 2600.0 2900.0 3100.0 3300.0
-1900.0 2400.0 2500.0 2700.0 2900.0 3100.0
-1800.0 2000.0 2100.0 2400.0 3100.0 3200.0
-1700.0 2400.0 2700.0 2800.0 3000.0 3200.0
-1800.0 1900.0 2300.0 2600.0 2800.0 3300.0
-1300.0 1900.0 2500.0 2600.0 3200.0 3400.0
-1400.0 1600.0 2300.0 2400.0 2800.0 3100.0
-1900.0 2000.0 2300.0 2700.0 3000.0 3300.0
-1700.0 1800.0 2400.0 2700.0 3200.0 3400.0
-1800.0 2000.0 2300.0 2600.0 2900.0 3300.0
-2100.0 2300.0 2600.0 2700.0 3300.0 3400.0
-1400.0 1600.0 2200.0 2400.0 3200.0 3300.0
-1300.0 1600.0 1800.0 2200.0 2800.0 2900.0
-1500.0 1700.0 1900.0 2600.0 2800.0 3000.0
-1700.0 2200.0 2500.0 2600.0 3100.0 3300.0
-1200.0 1700.0 1800.0 2100.0 3000.0 3100.0
-1100.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1100.0 1900.0 2100.0 2300.0 2900.0 3000.0
-1200.0 1700.0 2400.0 2600.0 3100.0 3400.0
-1100.0 1700.0 2600.0 2700.0 3000.0 3300.0
-1000.0 1700.0 2700.0 2800.0 3200.0 3400.0
-1100.0 1900.0 2200.0 2300.0 3200.0 3300.0
-1300.0 1900.0 2300.0 2500.0 3000.0 3300.0
-1200.0 1600.0 2600.0 2700.0 3100.0 3400.0
-1300.0 1600.0 1800.0 2400.0 3000.0 3200.0
-1400.0 1700.0 1800.0 2100.0 3200.0 3400.0
-1000.0 1500.0 2300.0 2400.0 3200.0 3400.0
-900.0 1700.0 2600.0 2700.0 3300.0 3400.0
-1100.0 1400.0 2500.0 2700.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2500.0 2800.0 2900.0
-2100.0 2300.0 2700.0 2900.0 3400.0 3500.0
-2100.0 2200.0 2300.0 2400.0 3000.0 3300.0
-1800.0 2000.0 2400.0 2500.0 2800.0 3000.0
-1700.0 1900.0 2300.0 2500.0 2700.0 3000.0
-1300.0 1400.0 2300.0 2900.0 3100.0 3200.0
-2100.0 2300.0 2600.0 2900.0 3100.0 3200.0
-1400.0 1800.0 2200.0 2300.0 3200.0 3400.0
-2100.0 2500.0 2900.0 3200.0 3400.0 3500.0
-1700.0 1900.0 2100.0 2400.0 3200.0 3400.0
-1600.0 1700.0 2300.0 2600.0 2800.0 2900.0
-1800.0 2000.0 2300.0 2700.0 2800.0 3000.0
-1900.0 2300.0 2600.0 2800.0 3000.0 3100.0
-1300.0 1600.0 2200.0 2600.0 3100.0 3200.0
-1500.0 1600.0 2400.0 2500.0 2900.0 3400.0
-1600.0 1800.0 2000.0 2700.0 3100.0 3200.0
-1000.0 1800.0 2600.0 2700.0 3200.0 3400.0
-900.0 1800.0 2500.0 2600.0 3300.0 3400.0
-1300.0 2200.0 2300.0 2700.0 3200.0 3300.0
-1200.0 2000.0 2300.0 2500.0 3300.0 3400.0
-1100.0 1500.0 2400.0 2500.0 3100.0 3400.0
-1300.0 1700.0 1900.0 2100.0 3000.0 3100.0
-2000.0 2100.0 2500.0 2600.0 3300.0 3500.0
-1500.0 1800.0 2000.0 2500.0 3300.0 3400.0
-2000.0 2100.0 2800.0 2900.0 3100.0 3300.0
-2300.0 2400.0 2600.0 2800.0 3200.0 3300.0
-1400.0 1900.0 2200.0 2300.0 3100.0 3200.0
-1500.0 1900.0 2600.0 2700.0 3200.0 3300.0
-1500.0 1600.0 2200.0 2600.0 3100.0 3400.0
-1700.0 1800.0 2500.0 2700.0 3300.0 3400.0
-1100.0 1600.0 2400.0 2500.0 3300.0 3400.0
-900.0 1600.0 2600.0 2700.0 3300.0 3400.0
-1400.0 1500.0 2200.0 2600.0 3200.0 3400.0
-1200.0 2000.0 2400.0 2500.0 2700.0 3200.0
-1300.0 1500.0 2500.0 2600.0 3200.0 3300.0
-1500.0 1600.0 2300.0 2600.0 3200.0 3400.0
-1300.0 2000.0 2300.0 2800.0 3000.0 3200.0
-2000.0 2100.0 2600.0 2700.0 3000.0 3100.0
-2000.0 2200.0 2600.0 2700.0 3000.0 3100.0
-2100.0 2200.0 2800.0 2900.0 3100.0 3200.0
-1900.0 2100.0 2500.0 2600.0 3000.0 3100.0
-1900.0 2100.0 2300.0 2500.0 2800.0 2900.0
-1800.0 2000.0 2600.0 2700.0 3000.0 3400.0
-1400.0 1700.0 1800.0 2500.0 2800.0 3200.0
-1300.0 1800.0 2200.0 2300.0 3200.0 3400.0
-1400.0 1600.0 1700.0 2200.0 3200.0 3400.0
-1400.0 1500.0 1600.0 2100.0 3200.0 3400.0
-1700.0 2100.0 2300.0 2500.0 3300.0 3400.0
-1600.0 2000.0 2600.0 2800.0 3200.0 3400.0
-1400.0 1600.0 2700.0 2800.0 3000.0 3300.0
-1400.0 1500.0 1600.0 2200.0 3300.0 3400.0
-1600.0 1700.0 2500.0 2600.0 3300.0 3400.0
-1000.0 1500.0 2300.0 2400.0 3000.0 3100.0
-1400.0 1500.0 1700.0 1800.0 3200.0 3300.0
-1600.0 2000.0 2300.0 2500.0 2800.0 3100.0
-1900.0 2500.0 2600.0 2900.0 3400.0 3500.0
-1800.0 1900.0 2500.0 2600.0 3300.0 3500.0
-1500.0 1900.0 2200.0 2300.0 3200.0 3300.0
-1900.0 2200.0 2500.0 2600.0 3300.0 3400.0
-1400.0 2000.0 2300.0 2600.0 3100.0 3300.0
-1800.0 1900.0 2300.0 2400.0 3200.0 3500.0
-1100.0 1900.0 2500.0 2600.0 2900.0 3000.0
-1600.0 1700.0 2300.0 2400.0 2900.0 3000.0
-1700.0 2300.0 2500.0 2700.0 3000.0 3100.0
-2100.0 2200.0 2700.0 2900.0 3100.0 3400.0
-1400.0 1900.0 2300.0 2600.0 2800.0 2900.0
-1800.0 2000.0 2200.0 2400.0 2600.0 2900.0
-1400.0 2100.0 2500.0 2600.0 2900.0 3100.0
-1700.0 1900.0 2400.0 2800.0 3200.0 3400.0
-1000.0 1500.0 2300.0 2400.0 3000.0 3300.0
-1500.0 2000.0 2300.0 2800.0 3200.0 3300.0
-1900.0 2000.0 2300.0 2600.0 3100.0 3400.0
-1300.0 1500.0 2400.0 2600.0 3300.0 3400.0
-2100.0 2500.0 2900.0 3100.0 3200.0 3400.0
-1400.0 1700.0 1800.0 2400.0 3200.0 3300.0
-1400.0 1500.0 2300.0 2600.0 3100.0 3400.0
-1000.0 1900.0 2600.0 2700.0 3000.0 3100.0
-1100.0 1800.0 2500.0 2700.0 3200.0 3300.0
-1700.0 1800.0 2200.0 2700.0 2800.0 3200.0
-2000.0 2200.0 2700.0 2800.0 3100.0 3200.0
-1300.0 2100.0 2400.0 2500.0 2900.0 3100.0
-1300.0 2000.0 2400.0 2500.0 2800.0 3000.0
-1500.0 2100.0 2500.0 2600.0 2900.0 3100.0
-1700.0 2200.0 2500.0 2700.0 3000.0 3200.0
-1600.0 2100.0 2500.0 2600.0 3000.0 3100.0
-1700.0 2200.0 2500.0 2600.0 3000.0 3200.0
-1800.0 2200.0 2300.0 2600.0 3000.0 3200.0
-1300.0 1500.0 1700.0 2100.0 3300.0 3400.0
-1300.0 1500.0 1700.0 2000.0 3300.0 3400.0
-1300.0 1900.0 2700.0 2800.0 3200.0 3400.0
-1700.0 2500.0 2700.0 2900.0 3300.0 3400.0
-1100.0 1700.0 2100.0 2200.0 3300.0 3400.0
-1000.0 1800.0 2700.0 2900.0 3300.0 3400.0
-1500.0 1600.0 2500.0 2600.0 3200.0 3300.0
-1100.0 1900.0 2600.0 2800.0 3000.0 3100.0
-1300.0 1500.0 2400.0 2500.0 3200.0 3300.0
-1700.0 2100.0 2300.0 2400.0 2800.0 3300.0
-1300.0 1500.0 1700.0 1800.0 3200.0 3400.0
-2000.0 2100.0 2400.0 2700.0 2900.0 3300.0
-1400.0 1500.0 2500.0 2600.0 3000.0 3200.0
-1400.0 1500.0 2000.0 2900.0 3300.0 3400.0
-1300.0 1500.0 2600.0 2700.0 3100.0 3200.0
-1100.0 1300.0 2700.0 2800.0 3200.0 3300.0
-1100.0 1300.0 2500.0 2600.0 2900.0 3100.0
-1900.0 2300.0 2400.0 2600.0 2700.0 3100.0
-1300.0 2100.0 2200.0 2600.0 3200.0 3300.0
-1100.0 1800.0 2400.0 2500.0 2900.0 3100.0
-1000.0 1800.0 2200.0 2300.0 3200.0 3300.0
-1500.0 1700.0 1800.0 2600.0 3200.0 3400.0
-1500.0 2000.0 2400.0 2600.0 2700.0 3100.0
-2000.0 2100.0 2300.0 2500.0 2700.0 3300.0
-1000.0 1500.0 2700.0 2800.0 3300.0 3400.0
+++ /dev/null
-/*
- lspsync.c
- David Rowe 24 May 2012
-
- Attempt at using LSP information to provide frame sync. If we have
- correct frame alignment, LSPs will not need sorting.
-
- However this method as tested appears unreliable, often several
- sync positions per frame are found, even with a F=10 memory. For
- F=6, about 87% relaible. This might be useful if combined with a
- another sync method, for example a single alternating sync bit per
- frame.
-
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include "codec2.h"
-#include "defines.h"
-#include "quantise.h"
-
-#define F 6 /* look at LSP ordering in F-1 frames */
-#define CORRECT_OFFSET 10 /* LSPs start 10 bits int frame qt 2400 bit/s */
-
-
-static int check_candidate(char bits[], int offset)
-{
- int i;
- int lsp_indexes[LPC_ORD];
- float lsps[LPC_ORD];
- unsigned int nbit = offset;
- int swaps;
-
- for(i=0; i<LSP_SCALAR_INDEXES; i++) {
- lsp_indexes[i] = unpack(bits, &nbit, lsp_bits(i));
- }
- decode_lsps_scalar(lsps, lsp_indexes, LPC_ORD);
- swaps = check_lsp_order(lsps, LPC_ORD);
-
- return swaps;
-}
-
-int main(int argc, char *argv[]) {
- struct CODEC2 *c2;
- int i,offset, nsamples, nbits, nbytes, frames;
- short *speech;
- char *bits;
- FILE *fin;
- int swaps, pass, fail, match;
-
- c2 = codec2_create(CODEC2_MODE_2400);
- nsamples = codec2_samples_per_frame(c2);
- nbits = codec2_bits_per_frame(c2);
- nbytes = nbits/8;
- speech = (short*)malloc(nsamples*sizeof(short));
-
- /* keep FRAMES frame memory of bit stream */
-
- bits = (char*)malloc(F*nbytes*sizeof(char));
- for(i=0; i<F*nbytes; i++)
- bits[i] = 0;
-
- fin = fopen("../raw/hts1a.raw", "rb");
- assert(fin != NULL);
- match = pass = fail = frames = 0;
-
- /* prime memeory with first frame to ensure we don't start
- checking until we have two frames of coded bits */
-
- fread(speech, sizeof(short), nsamples, fin);
- frames++;
- codec2_encode(c2, &bits[(F-2)*nbytes], speech);
-
- /* OK start looking for correct frame offset */
-
- while(fread(speech, sizeof(short), nsamples, fin) == nsamples) {
- frames++;
- codec2_encode(c2, &bits[(F-1)*nbytes], speech);
-
- for(offset=0; offset<nbits; offset++) {
- swaps = check_candidate(bits, offset);
- if (swaps == 0) {
-
- /* OK found a candidate .. lets check a F-1 frames in total */
-
- for(i=0; i<(F-1); i++)
- swaps += check_candidate(bits, offset + nbits*i);
-
- if (swaps == 0) {
- printf("frame %d offset: %d swaps: %d\n", frames, offset, swaps);
- match++;
- if (offset == CORRECT_OFFSET)
- pass++;
- else
- fail++;
- }
- }
- }
-
- /* update F frame memory of bits */
-
- for(i=0; i<nbytes*(F-1); i++)
- bits[i] = bits[i+nbytes];
- }
-
- fclose(fin);
- free(speech);
- free(bits);
- codec2_destroy(c2);
-
- printf("passed %f %%\n", (float)pass*100.0/match);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: lsptest.c
- AUTHOR......: David Rowe
- DATE CREATED: 24/8/09
-
- Test Speech LPC to LSP conversion and quantisation.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, write to the Free Software
- Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <lpc.h>
-#include <lsp.h>
-#include <sd.h>
-
-#define N 160
-#define P 10
-
-#define LPC_FLOOR 0.0002 /* autocorrelation floor */
-#define LSP_DELTA1 0.2 /* grid spacing for LSP root searches */
-#define NDFT 256 /* DFT size for SD calculation */
-
-/* Speex lag window */
-
-const float lag_window[11] = {
- 1.00000, 0.99716, 0.98869, 0.97474, 0.95554, 0.93140, 0.90273, 0.86998,
- 0.83367, 0.79434, 0.75258
-};
-
-/*---------------------------------------------------------------------------*\
-
- find_aks_for_lsp()
-
- This function takes a frame of samples, and determines the linear
- prediction coefficients for that frame of samples. Modified version of
- find_aks from lpc.c to include autocorrelation noise floor and lag window
- to match Speex processing steps prior to LSP conversion.
-
-\*---------------------------------------------------------------------------*/
-
-void find_aks_for_lsp(
- float Sn[], /* Nsam samples with order sample memory */
- float a[], /* order+1 LPCs with first coeff 1.0 */
- int Nsam, /* number of input speech samples */
- int order, /* order of the LPC analysis */
- float *E /* residual energy */
-)
-{
- float Wn[N]; /* windowed frame of Nsam speech samples */
- float R[P+1]; /* order+1 autocorrelation values of Sn[] */
- int i;
-
- hanning_window(Sn,Wn,Nsam);
-
- autocorrelate(Wn,R,Nsam,order);
- R[0] += LPC_FLOOR;
- assert(order == 10); /* lag window only defined for order == 10 */
- for(i=0; i<=order; i++)
- R[i] *= lag_window[i];
- levinson_durbin(R,a,order);
-
- *E = 0.0;
- for(i=0; i<=order; i++)
- *E += a[i]*R[i];
- if (*E < 0.0)
- *E = 1E-12;
-}
-
-/*---------------------------------------------------------------------------*\
-
- MAIN
-
-\*---------------------------------------------------------------------------*/
-
-int main(int argc, char *argv[])
-{
- FILE *fin; /* input speech files */
- short buf[N]; /* buffer of 16 bit speech samples */
- float Sn[P+N]; /* input speech samples */
- float E;
- float ak[P+1]; /* LP coeffs */
- float ak_[P+1]; /* quantised LP coeffs */
- float lsp[P];
- float lsp_[P]; /* quantised LSPs */
- int roots; /* number of LSP roots found */
- int frames; /* frames processed so far */
- int i; /* loop variables */
-
- SpeexBits bits;
-
- float sd; /* SD for this frame */
- float totsd; /* accumulated SD so far */
- int gt2,gt4; /* number of frames > 2 and 4 dB SD */
- int unstables; /* number of unstable LSP frames */
-
- if (argc < 2) {
- printf("usage: %s InputFile\n", argv[0]);
- exit(0);
- }
-
- /* Open files */
-
- if ((fin = fopen(argv[1],"rb")) == NULL) {
- printf("Error opening input file: %s\n",argv[1]);
- exit(0);
- }
-
- /* Initialise */
-
- frames = 0;
- for(i=0; i<P; i++) {
- Sn[i] = 0.0;
- }
- ak_[0] = 1.0;
-
- speex_bits_init(&bits);
-
- totsd = 0.0;
- unstables = 0;
- gt2 = 0; gt4 = 0;
-
- /* Main loop */
-
- while( (fread(buf,sizeof(short),N,fin)) == N) {
- frames++;
- for(i=0; i<N; i++)
- Sn[P+i] = (float)buf[i];
-
- /* convert to LSP domain and back */
-
- find_aks(&Sn[P], ak, N, P, &E);
- roots = lpc_to_lsp(&ak[1], P , lsp, 10, LSP_DELTA1, NULL);
- if (roots == P) {
-
- speex_bits_reset(&bits);
- lsp_quant_lbr(lsp, lsp_, P, &bits);
- lsp_to_lpc(lsp_, &ak_[1], P, NULL);
-
- /* measure spectral distortion */
- sd = spectral_dist(ak, ak_, P, NDFT);
- if (sd > 2.0) gt2++;
- if (sd > 4.0) gt4++;
- totsd += sd;
- }
- else
- unstables++;
- }
-
- fclose(fin);
-
- printf("frames = %d Av sd = %3.2f dB", frames, totsd/frames);
- printf(" >2 dB %3.2f%% >4 dB %3.2f%% unstables: %d\n",gt2*100.0/frames,
- gt4*100.0/frames, unstables);
-
- return 0;
-}
-
+++ /dev/null
-/*
- mksine.c
- David Rowe
- 10 Nov 2010
-
- Creates a file of sine wave samples.
-*/
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <math.h>
-
-#define TWO_PI 6.283185307
-#define N 8000
-#define FS 8000.0
-#define AMP 1000.0
-
-int main(int argc, char *argv[]) {
- FILE *f;
- int i;
- float freq;
- short buf[N];
-
- if (argc != 3) {
- printf("usage: %s outputFile frequencyHz\n", argv[0]);
- exit(1);
- }
-
- f = fopen(argv[1] ,"wb");
- freq = atof(argv[2]);
-
- for(i=0; i<N; i++)
- buf[i] = AMP*cos(freq*i*(TWO_PI/FS));
-
- fwrite(buf, sizeof(short), N, f);
-
- return 0;
-}
+++ /dev/null
-/*
- polar2rect.c
- David Rowe 28 July 2013
-
- Convert a file of sparse phases in polar (angle) format to a file in rect
- format.
-*/
-
-#include <assert.h>
-#include <math.h>
-#include <stdlib.h>
-#include <stdio.h>
-
-typedef struct {
- float real;
- float imag;
-} COMP;
-
-int main(int argc, char *argv[]) {
- FILE *fpolar;
- FILE *frect;
- float polar;
- COMP rect;
-
- if (argc != 3) {
- printf("usage: %s polarFile rectFile\n", argv[0]);
- exit(0);
- }
-
- fpolar = fopen(argv[1], "rb");
- assert(fpolar != NULL);
- frect = fopen(argv[2], "wb");
- assert(frect != NULL);
-
- while (fread(&polar, sizeof(float), 1, fpolar) != 0) {
- if (polar == 0.0) {
- /* this values indicates the VQ training should ignore
- this vector element. It's not a valid phase as it
- doesn't have mangitude of 1.0 */
- rect.real = 0.0;
- rect.imag = 0.0;
- }
- else {
- rect.real = cos(polar);
- rect.imag = sin(polar);
- }
- fwrite(&rect, sizeof(COMP), 1, frect);
- }
-
- fclose(fpolar);
- fclose(frect);
-
- return 0;
-}
+++ /dev/null
-/*
- pre.c
- David Rowe
- Sep 26 2012
-
- Takes audio from a file, pre-emphasises, and sends to output file.
-*/
-
-#include <assert.h>
-#include <math.h>
-#include <errno.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include "lpc.h"
-
-#define N 80
-
-int main(int argc, char*argv[]) {
- FILE *fin, *fout;
- short buf[N];
- float Sn[N], Sn_pre[N];
- float pre_mem = 0.0;
- int i;
-
- if (argc != 3) {
- printf("usage: pre InputRawSpeechFile OutputRawSpeechFile\n");
- printf("e.g pre input.raw output.raw");
- exit(1);
- }
-
- if (strcmp(argv[1], "-") == 0) fin = stdin;
- else if ( (fin = fopen(argv[1],"rb")) == NULL ) {
- fprintf(stderr, "Error opening input speech file: %s: %s.\n",
- argv[1], strerror(errno));
- exit(1);
- }
-
- if (strcmp(argv[2], "-") == 0) fout = stdout;
- else if ( (fout = fopen(argv[2],"wb")) == NULL ) {
- fprintf(stderr, "Error opening output speech file: %s: %s.\n",
- argv[2], strerror(errno));
- exit(1);
- }
-
- while(fread(buf, sizeof(short), N, fin) == N) {
- for(i=0; i<N; i++)
- Sn[i] = buf[i];
- pre_emp(Sn_pre, Sn, &pre_mem, N);
- for(i=0; i<N; i++)
- buf[i] = Sn_pre[i];
- fwrite(buf, sizeof(short), N, fout);
- }
-
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
+++ /dev/null
-#!/bin/bash
-
-# verbose, skittish
-set -ex
-
-# run valgrind?
-VG="valgrind --error-exitcode=149 --leak-check=full --show-reachable=yes"
-
-# make sure we're up-to-date
-make
-
-
-# runs, not certaion wht it does yet
-${VG} ./tcodec2
-${VG} ./tinterp
-${VG} ./tquant
-
-# these fail, missing arguments
-${VG} ./extract
-${VG} ./genlsp
-${VG} ./genres
-${VG} ./scalarlsptest
-${VG} ./tnlp
-${VG} ./vq_train_jvm
-${VG} ./vqtrain
-${VG} ./vqtrainjnd
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: scalarlsptest.c
- AUTHOR......: David Rowe
- DATE CREATED: 8/2/12
-
- Test Scalar LSP quantiser, output variance of quantisation error.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-
-#include "defines.h"
-#include "quantise.h"
-
-/*---------------------------------------------------------------------------*\
-
- MAIN
-
-\*---------------------------------------------------------------------------*/
-
-int main(int argc, char *argv[])
-{
- FILE *ftrain; /* LSP training data text file */
- float lsp[LPC_ORD]; /* LSP input vector in rads */
- float lsp_hz[LPC_ORD]; /* LSP input vector in Hz */
- int vectors; /* number LSP vectors processed */
- int k,m; /* LSP vector order and codebook size */
- int index;
- float wt[1]; /* weighting (not used here for scalars) */
- const float *cb; /* LSP quantiser codebook */
- int i, ret;
- float total_se;
-
- if (argc < 2) {
- printf("usage: %s InputFile\n", argv[0]);
- exit(1);
- }
-
- if ((ftrain = fopen(argv[1],"rt")) == NULL) {
- printf("Error opening input file: %s\n",argv[1]);
- exit(0);
- }
-
- total_se = 0.0;
- vectors = 0;
- wt[0] = 1.0;
-
- /* Main loop */
-
- while(!feof(ftrain)) {
-
- /* Read LSP input vector speech */
-
- for (i=0; i<LPC_ORD; i++) {
- ret = fscanf(ftrain, "%f ", &lsp[i]);
- }
- vectors++;
- if ((vectors % 1000) == 0)
- printf("\r%d vectors", vectors);
-
- /* convert from radians to Hz so we can use human readable
- frequencies */
-
- for(i=0; i<LPC_ORD; i++)
- lsp_hz[i] = (4000.0/PI)*lsp[i];
-
- /* simple uniform scalar quantisers */
-
- for(i=0; i<LPC_ORD; i++) {
- k = lsp_cb[i].k;
- m = lsp_cb[i].m;
- cb = lsp_cb[i].cb;
- index = quantise(cb, &lsp_hz[i], wt, k, m, &total_se);
- //printf("k %d m %d lsp[%d] %f %f se %f\n", k,m,i,lsp_hz[i], cb[index],se);
- }
- //printf("total se %f\n", total_se);
- //exit(0);
- }
-
- fclose(ftrain);
-
- printf("\n variance = %f\n", ((PI*PI)/(4000.0*4000.0))*total_se/vectors);
-
- return 0;
-}
-
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: sd.c
- AUTHOR......: David Rowe
- DATE CREATED: 20/7/93
-
- Function to determine spectral distortion between two sets of LPCs.
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#define MAX_N 2048 /* maximum DFT size */
-
-#include <math.h>
-#include "four1.h"
-#include "comp.h"
-#include "sd.h"
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: spectral_dist()
-
- AUTHOR......: David Rowe
- DATE CREATED: 20/7/93
-
- This function returns the soectral distoertion between two
- sets of LPCs.
-
-\*---------------------------------------------------------------------------*/
-
-float spectral_dist(float ak1[], float ak2[], int p, int n)
-/* float ak1[]; unquantised set of p+1 LPCs */
-/* float ak2[]; quantised set of p+1 LPCs */
-/* int p; LP order */
-/* int n; DFT size to use for SD calculations (power of 2) */
-{
- COMP A1[MAX_N]; /* DFT of ak1[] */
- COMP A2[MAX_N]; /* DFT of ak2[] */
- float P1,P2; /* power of current bin */
- float sd;
- int i;
-
- for(i=0; i<n; i++) {
- A1[i].real = 0.0;
- A1[i].imag = 0.0;
- A2[i].real = 0.0;
- A2[i].imag = 0.0;
- }
-
- for(i=0; i<p+1; i++) {
- A1[i].real = ak1[i];
- A2[i].real = ak2[i];
- }
-
- four1(&A1[-1].imag,n,-1);
- four1(&A2[-1].imag,n,-1);
-
- sd = 0.0;
- for(i=0; i<n; i++) {
- P1 = A1[i].real*A1[i].real + A1[i].imag*A1[i].imag;
- P2 = A2[i].real*A2[i].real + A2[i].imag*A2[i].imag;
- sd += pow(log10(P2/P1),2.0);
- }
- sd = 10.0*sqrt(sd/n); /* sd in dB */
-
- return(sd);
-}
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: sd.h
- AUTHOR......: David Rowe
- DATE CREATED: 22/7/93
-
- Function to determine spectral distortion between two sets of LPCs.
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#ifndef __SD__
-#define __SD__
-
-float spectral_dist(float ak1[], float ak2[], int p, int n);
-
-#endif /* __SD__ */
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: speexlsptest.c
- AUTHOR......: David Rowe
- DATE CREATED: 24/8/09
-
- Test LPC to LSP conversion and quantisation using Speex LSP quantiser.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <lpc.h>
-#include <lsp.h>
-#include <sd.h>
-
-#define N 160
-#define P 10
-
-#define LPC_FLOOR 0.0002 /* autocorrelation floor */
-#define LSP_DELTA1 0.2 /* grid spacing for LSP root searches */
-#define NDFT 256 /* DFT size for SD calculation */
-
-/* Speex lag window */
-
-const float lag_window[11] = {
- 1.00000, 0.99716, 0.98869, 0.97474, 0.95554, 0.93140, 0.90273, 0.86998,
- 0.83367, 0.79434, 0.75258
-};
-
-/*---------------------------------------------------------------------------*\
-
- find_aks_for_lsp()
-
- This function takes a frame of samples, and determines the linear
- prediction coefficients for that frame of samples. Modified version of
- find_aks from lpc.c to include autocorrelation noise floor and lag window
- to match Speex processing steps prior to LSP conversion.
-
-\*---------------------------------------------------------------------------*/
-
-void find_aks_for_lsp(
- float Sn[], /* Nsam samples with order sample memory */
- float a[], /* order+1 LPCs with first coeff 1.0 */
- int Nsam, /* number of input speech samples */
- int order, /* order of the LPC analysis */
- float *E /* residual energy */
-)
-{
- float Wn[N]; /* windowed frame of Nsam speech samples */
- float R[P+1]; /* order+1 autocorrelation values of Sn[] */
- int i;
-
- hanning_window(Sn,Wn,Nsam);
-
- autocorrelate(Wn,R,Nsam,order);
- R[0] += LPC_FLOOR;
- assert(order == 10); /* lag window only defined for order == 10 */
- for(i=0; i<=order; i++)
- R[i] *= lag_window[i];
- levinson_durbin(R,a,order);
-
- *E = 0.0;
- for(i=0; i<=order; i++)
- *E += a[i]*R[i];
- if (*E < 0.0)
- *E = 1E-12;
-}
-
-/*---------------------------------------------------------------------------*\
-
- MAIN
-
-\*---------------------------------------------------------------------------*/
-
-int main(int argc, char *argv[])
-{
- FILE *fin; /* input speech files */
- short buf[N]; /* buffer of 16 bit speech samples */
- float Sn[P+N]; /* input speech samples */
- float E;
- float ak[P+1]; /* LP coeffs */
- float ak_[P+1]; /* quantised LP coeffs */
- float lsp[P];
- float lsp_[P]; /* quantised LSPs */
- int roots; /* number of LSP roots found */
- int frames; /* frames processed so far */
- int i; /* loop variables */
-
- SpeexBits bits;
-
- float sd; /* SD for this frame */
- float totsd; /* accumulated SD so far */
- int gt2,gt4; /* number of frames > 2 and 4 dB SD */
- int unstables; /* number of unstable LSP frames */
-
- if (argc < 2) {
- printf("usage: %s InputFile\n", argv[0]);
- exit(0);
- }
-
- /* Open files */
-
- if ((fin = fopen(argv[1],"rb")) == NULL) {
- printf("Error opening input file: %s\n",argv[1]);
- exit(0);
- }
-
- /* Initialise */
-
- frames = 0;
- for(i=0; i<P; i++) {
- Sn[i] = 0.0;
- }
- ak_[0] = 1.0;
-
- speex_bits_init(&bits);
-
- totsd = 0.0;
- unstables = 0;
- gt2 = 0; gt4 = 0;
-
- /* Main loop */
-
- while( (fread(buf,sizeof(short),N,fin)) == N) {
- frames++;
- for(i=0; i<N; i++)
- Sn[P+i] = (float)buf[i];
-
- /* convert to LSP domain and back */
-
- find_aks(&Sn[P], ak, N, P, &E);
- roots = lpc_to_lsp(&ak[1], P , lsp, 10, LSP_DELTA1, NULL);
- if (roots == P) {
-
- speex_bits_reset(&bits);
- lsp_quant_lbr(lsp, lsp_, P, &bits);
- lsp_to_lpc(lsp_, &ak_[1], P, NULL);
-
- /* measure spectral distortion */
- sd = spectral_dist(ak, ak_, P, NDFT);
- if (sd > 2.0) gt2++;
- if (sd > 4.0) gt4++;
- totsd += sd;
- }
- else
- unstables++;
- }
-
- fclose(fin);
-
- printf("frames = %d Av sd = %3.2f dB", frames, totsd/frames);
- printf(" >2 dB %3.2f%% >4 dB %3.2f%% unstables: %d\n",gt2*100.0/frames,
- gt4*100.0/frames, unstables);
-
- return 0;
-}
-
+++ /dev/null
-/*
- t48_8.c
- David Rowe
- May 10 2012
-
- Unit test for 48 to 8 kHz sample rate conversion functions. I
- evaluated output by plotting using Octave and looking for jaggies:
-
- pl("../unittest/out48.raw",1,3000)
- pl("../unittest/out8.raw",1,3000)
-
- Listening to it also shows up anything nasty:
-
- $ play -s -2 -r 48000 out48.raw
- $ play -s -2 -r 8000 out8.raw
-
- */
-
-#include <assert.h>
-#include <math.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include "fdmdv.h"
-
-#define N8 160 /* procssing buffer size at 8 kHz */
-#define N48 (N8*FDMDV_OS)
-#define MEM8 (FDMDV_OS_TAPS/FDMDV_OS)
-#define FRAMES 50
-#define TWO_PI 6.283185307
-#define FS 8000
-
-#define SINE
-
-int main() {
- float in8k[MEM8 + N8];
- float out48k[N48];
- short out48k_short[N48];
- FILE *f48;
-
- float in48k[FDMDV_OS_TAPS + N48];
- float out8k[N48];
- short out8k_short[N8];
- FILE *f8;
-
- int i,f,t,t1;
- float freq = 800.0;
-
- f48 = fopen("out48.raw", "wb");
- assert(f48 != NULL);
- f8 = fopen("out8.raw", "wb");
- assert(f8 != NULL);
-
- /* clear filter memories */
-
- for(i=0; i<MEM8; i++)
- in8k[i] = 0.0;
- for(i=0; i<FDMDV_OS_TAPS; i++)
- in48k[i] = 0.0;
-
- t = t1 = 0;
- for(f=0; f<FRAMES; f++) {
-
-#ifdef DC
- for(i=0; i<N8; i++)
- in8k[MEM8+i] = 16000.0;
-#endif
-#ifdef SINE
- for(i=0; i<N8; i++,t++)
- in8k[MEM8+i] = 16000.0*cos(TWO_PI*t*freq/FS);
-#endif
-
- /* upsample */
-
- fdmdv_8_to_48(out48k, &in8k[MEM8], N8);
- /*
- for(i=0; i<MEM8; i++)
- in8k[i] = in8k[i+N8];
- */
-
- /* save 48k to disk for plotting and check out */
-
- for(i=0; i<N48; i++)
- out48k_short[i] = (short)out48k[i];
- fwrite(out48k_short, sizeof(short), N48, f48);
-
- /* add a 10 kHz spurious signal for fun, we want down sampler to
- knock this out */
-
- for(i=0; i<N48; i++,t1++)
- in48k[i+FDMDV_OS_TAPS] = out48k[i] + 16000.0*cos(TWO_PI*t1*1E4/FS);
-
- /* downsample */
-
- fdmdv_48_to_8(out8k, &in48k[FDMDV_OS_TAPS], N8);
- /*
- for(i=0; i<FDMDV_OS_TAPS; i++)
- in48k[i] = in48k[i+N48];
- */
-
- /* save 8k to disk for plotting and check out */
-
- for(i=0; i<N8; i++)
- out8k_short[i] = (short)out8k[i];
- fwrite(out8k_short, sizeof(short), N8, f8);
-
- }
-
- fclose(f48);
- fclose(f8);
- return 0;
-
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tcodec2.c
- AUTHOR......: David Rowe
- DATE CREATED: 24/8/10
-
- Test program for codec2.c functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-#include "defines.h"
-#include "comp.h"
-#include "codec2.h"
-#include "quantise.h"
-#include "interp.h"
-
-/* CODEC2 struct copies from codec2.c to help with testing */
-
-struct CODEC2 {
- int mode;
- float w[M]; /* time domain hamming window */
- COMP W[FFT_ENC]; /* DFT of w[] */
- float Pn[2*N]; /* trapezoidal synthesis window */
- float Sn[M]; /* input speech */
- float hpf_states[2]; /* high pass filter states */
- void *nlp; /* pitch predictor states */
- float Sn_[2*N]; /* synthesised output speech */
- float ex_phase; /* excitation model phase track */
- float bg_est; /* background noise estimate for post filter */
- float prev_Wo; /* previous frame's pitch estimate */
- MODEL prev_model; /* previous frame's model parameters */
- float prev_lsps_[LPC_ORD]; /* previous frame's LSPs */
- float prev_energy; /* previous frame's LPC energy */
-};
-
-void analyse_one_frame(struct CODEC2 *c2, MODEL *model, short speech[]);
-void synthesise_one_frame(struct CODEC2 *c2, short speech[], MODEL *model, float ak[]);
-
-int test1()
-{
- FILE *fin, *fout;
- short buf[N];
- struct CODEC2 *c2;
- MODEL model;
- float ak[LPC_ORD+1];
- float lsps[LPC_ORD];
-
- c2 = codec2_create(CODEC2_MODE_2400);
-
- fin = fopen("../raw/hts1a.raw", "rb");
- assert(fin != NULL);
- fout = fopen("hts1a_test.raw", "wb");
- assert(fout != NULL);
-
- while(fread(buf, sizeof(short), N, fin) == N) {
- analyse_one_frame(c2, &model, buf);
- speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- synthesise_one_frame(c2, buf, &model, ak);
- fwrite(buf, sizeof(short), N, fout);
- }
-
- codec2_destroy(c2);
-
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
-
-int test2()
-{
- FILE *fin, *fout;
- short buf[2*N];
- struct CODEC2 *c2;
- MODEL model, model_interp;
- float ak[LPC_ORD+1];
- int voiced1, voiced2;
- int lsp_indexes[LPC_ORD];
- int energy_index;
- int Wo_index;
- char *bits;
- int nbit;
- int i;
- float lsps[LPC_ORD];
- float e;
-
- c2 = codec2_create(CODEC2_MODE_2400);
- bits = (char*)malloc(codec2_bits_per_frame(c2));
- assert(bits != NULL);
- fin = fopen("../raw/hts1a.raw", "rb");
- assert(fin != NULL);
- fout = fopen("hts1a_test.raw", "wb");
- assert(fout != NULL);
-
- while(fread(buf, sizeof(short), 2*N, fin) == 2*N) {
- /* first 10ms analysis frame - we just want voicing */
-
- analyse_one_frame(c2, &model, buf);
- voiced1 = model.voiced;
-
- /* second 10ms analysis frame */
-
- analyse_one_frame(c2, &model, &buf[N]);
- voiced2 = model.voiced;
-
- Wo_index = encode_Wo(model.Wo);
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- encode_lsps_scalar(lsp_indexes, lsps, LPC_ORD);
- energy_index = encode_energy(e);
- nbit = 0;
- pack((unsigned char*)bits, (unsigned *)&nbit, Wo_index, WO_BITS);
- for(i=0; i<LPC_ORD; i++) {
- pack((unsigned char*)bits, (unsigned *)&nbit, lsp_indexes[i], lsp_bits(i));
- }
- pack((unsigned char*)bits, (unsigned *)&nbit, energy_index, E_BITS);
- pack((unsigned char*)bits, (unsigned *)&nbit, voiced1, 1);
- pack((unsigned char*)bits, (unsigned *)&nbit, voiced2, 1);
-
- nbit = 0;
- Wo_index = unpack((unsigned char*)bits, (unsigned *)&nbit, WO_BITS);
- for(i=0; i<LPC_ORD; i++) {
- lsp_indexes[i] = unpack((unsigned char*)bits, (unsigned *)&nbit, lsp_bits(i));
- }
- energy_index = unpack((unsigned char*)bits, (unsigned *)&nbit, E_BITS);
- voiced1 = unpack((unsigned char*)bits, (unsigned *)&nbit, 1);
- voiced2 = unpack((unsigned char*)bits, (unsigned *)&nbit, 1);
-
- model.Wo = decode_Wo(Wo_index);
- model.L = PI/model.Wo;
- decode_amplitudes(&model,
- ak,
- lsp_indexes,
- energy_index,
- lsps,
- &e);
-
- model.voiced = voiced2;
- model_interp.voiced = voiced1;
- interpolate(&model_interp, &c2->prev_model, &model);
-
- synthesise_one_frame(c2, buf, &model_interp, ak);
- synthesise_one_frame(c2, &buf[N], &model, ak);
-
- memcpy(&c2->prev_model, &model, sizeof(MODEL));
- fwrite(buf, sizeof(short), 2*N, fout);
- }
-
- free(bits);
- codec2_destroy(c2);
-
- fclose(fin);
- fclose(fout);
-
- return 0;
-}
-
-int test3()
-{
- FILE *fin, *fout, *fbits;
- short buf1[2*N];
- short buf2[2*N];
- char *bits;
- struct CODEC2 *c2;
-
- c2 = codec2_create(CODEC2_MODE_2400);
- int numBits = codec2_bits_per_frame(c2);
- int numBytes = (numBits+7)>>3;
-
- bits = (char*)malloc(numBytes);
-
- fin = fopen("../raw/hts1a.raw", "rb");
- assert(fin != NULL);
- fout = fopen("hts1a_test.raw", "wb");
- assert(fout != NULL);
- fbits = fopen("hts1a_test3.bit", "wb");
- assert(fout != NULL);
-
- while(fread(buf1, sizeof(short), 2*N, fin) == 2*N) {
- codec2_encode(c2, (void*)bits, buf1);
- fwrite(bits, sizeof(char), numBytes, fbits);
- codec2_decode(c2, buf2, (void*)bits);
- fwrite(buf2, sizeof(short), numBytes, fout);
- }
-
- free(bits);
- codec2_destroy(c2);
-
- fclose(fin);
- fclose(fout);
- fclose(fbits);
-
- return 0;
-}
-
-int main() {
- test3();
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tcontphase.c
- AUTHOR......: David Rowe
- DATE CREATED: 11/9/09
-
- Test program for developing continuous phase track synthesis algorithm.
- However while developing this it was discovered that synthesis_mixed()
- worked just as well.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#define N 80 /* frame size */
-#define F 160 /* frames to synthesis */
-#define P 10 /* LPC order */
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-#include "sine.h"
-#include "dump.h"
-#include "synth.h"
-#include "phase.h"
-
-int frames;
-
-float ak[] = {
- 1.000000,
--1.455836,
- 1.361841,
--0.879267,
- 0.915985,
--1.002202,
- 0.944103,
--0.743094,
- 1.053356,
--0.817491,
- 0.431222
-};
-
-
-/*---------------------------------------------------------------------------*\
-
- switch_present()
-
- Searches the command line arguments for a "switch". If the switch is
- found, returns the command line argument where it ws found, else returns
- NULL.
-
-\*---------------------------------------------------------------------------*/
-
-int switch_present(sw,argc,argv)
- char sw[]; /* switch in string form */
- int argc; /* number of command line arguments */
- char *argv[]; /* array of command line arguments in string form */
-{
- int i; /* loop variable */
-
- for(i=1; i<argc; i++)
- if (!strcmp(sw,argv[i]))
- return(i);
-
- return 0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- MAIN
-
-\*---------------------------------------------------------------------------*/
-
-int main(argc,argv)
-int argc;
-char *argv[];
-{
- FILE *fout;
- short buf[N];
- int i,j;
- int dump;
- float phi_prev[MAX_AMP];
- float Wo_prev, ex_phase, G;
- //float ak[P+1];
- COMP H[MAX_AMP];
- float f0;
-
- if (argc < 3) {
- printf("\nusage: %s OutputRawSpeechFile F0\n", argv[0]);
- exit(1);
- }
-
- /* Output file */
-
- if ((fout = fopen(argv[1],"wb")) == NULL) {
- printf("Error opening output speech file: %s\n",argv[1]);
- exit(1);
- }
-
- f0 = atof(argv[2]);
-
- dump = switch_present("--dump",argc,argv);
- if (dump)
- dump_on(argv[dump+1]);
-
- init_decoder();
-
- for(i=0; i<MAX_AMP; i++)
- phi_prev[i] = 0.0;
- Wo_prev = 0.0;
-
- model.Wo = PI*(f0/4000.0);
- G = 1000.0;
- model.L = floor(PI/model.Wo);
-
- //aks_to_H(&model, ak, G , H, P);
- //for(i=1; i<=model.L; i++)
- model.A[i] = sqrt(H[i].real*H[i].real + H[i].imag*H[i].imag);
- //printf("L = %d\n", model.L);
- //model.L = 10;
- for(i=1; i<=model.L; i++) {
- model.A[i] = 1000/model.L;
- model.phi[i] = 0;
- H[i].real = 1.0; H[i].imag = 0.0;
- }
-
- //ak[0] = 1.0;
- //for(i=1; i<=P; i++)
- // ak[i] = 0.0;
-
- frames = 0;
- for(j=0; j<F; j++) {
- frames++;
-
- #ifdef SWAP
- /* lets make phases bounce around from frame to frame. This
- could happen if H[m] is varying, for example due to frame
- to frame Wo variations, or non-stationary speech.
- Continous model generally results in smooth phase track
- under these circumstances. */
- if (j%2){
- H[1].real = 1.0; H[1].imag = 0.0;
- model.phi[1] = 0.0;
- }
- else {
- H[1].real = 0.0; H[1].imag = 1.0;
- model.phi[1] = PI/2;
- }
- #endif
-
- //#define CONT
- #ifdef CONT
- synthesise_continuous_phase(Pn, &model, Sn_, 1, &Wo_prev, phi_prev);
- #else
- phase_synth_zero_order(5.0, H, &Wo_prev, &ex_phase);
- synthesise_mixed(Pn,&model,Sn_,1);
- #endif
-
- for(i=0; i<N; i++)
- buf[i] = Sn_[i];
- fwrite(buf,sizeof(short),N,fout);
- }
-
- fclose(fout);
- if (dump) dump_off();
-
- return 0;
-}
-
-
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tfdmdv.c
- AUTHOR......: David Rowe
- DATE CREATED: April 16 2012
-
- Tests for the C version of the FDMDV modem. This program outputs a
- file of Octave vectors that are loaded and automatically tested
- against the Octave version of the modem by the Octave script
- tfmddv.m
-
-\*---------------------------------------------------------------------------*/
-
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-
-#include "fdmdv_internal.h"
-#include "fdmdv.h"
-#include "octave.h"
-
-#define FRAMES 25
-#define CHANNEL_BUF_SIZE (10*M)
-
-int main(int argc, char *argv[])
-{
- struct FDMDV *fdmdv;
- int tx_bits[FDMDV_BITS_PER_FRAME];
- COMP tx_symbols[NC+1];
- COMP tx_baseband[NC+1][M];
- COMP tx_fdm[M];
- float channel[CHANNEL_BUF_SIZE];
- int channel_count;
- COMP rx_fdm[M+M/P];
- float foff_coarse;
- int nin, next_nin;
- COMP rx_fdm_fcorr[M+M/P];
- COMP rx_baseband[NC+1][M+M/P];
- COMP rx_filt[NC+1][P+1];
- float rx_timing;
- float env[NT*P];
- COMP rx_symbols[NC+1];
- int rx_bits[FDMDV_BITS_PER_FRAME];
- float foff_fine;
- int sync_bit;
- int fest_state;
-
- int tx_bits_log[FDMDV_BITS_PER_FRAME*FRAMES];
- COMP tx_symbols_log[(NC+1)*FRAMES];
- COMP tx_baseband_log[(NC+1)][M*FRAMES];
- COMP tx_fdm_log[M*FRAMES];
- COMP pilot_baseband1_log[NPILOTBASEBAND*FRAMES];
- COMP pilot_baseband2_log[NPILOTBASEBAND*FRAMES];
- COMP pilot_lpf1_log[NPILOTLPF*FRAMES];
- COMP pilot_lpf2_log[NPILOTLPF*FRAMES];
- COMP S1_log[MPILOTFFT*FRAMES];
- COMP S2_log[MPILOTFFT*FRAMES];
- float foff_coarse_log[FRAMES];
- float foff_log[FRAMES];
- COMP rx_baseband_log[(NC+1)][(M+M/P)*FRAMES];
- int rx_baseband_log_col_index;
- COMP rx_filt_log[NC+1][(P+1)*FRAMES];
- int rx_filt_log_col_index;
- float env_log[NT*P*FRAMES];
- float rx_timing_log[FRAMES];
- COMP rx_symbols_log[NC+1][FRAMES];
- float sig_est_log[NC+1][FRAMES];
- float noise_est_log[NC+1][FRAMES];
- int rx_bits_log[FDMDV_BITS_PER_FRAME*FRAMES];
- float foff_fine_log[FRAMES];
- int sync_bit_log[FRAMES];
- int coarse_fine_log[FRAMES];
- int nin_log[FRAMES];
-
- FILE *fout;
- int f,c,i,j;
-
- fdmdv = fdmdv_create();
- next_nin = M;
- channel_count = 0;
-
- rx_baseband_log_col_index = 0;
- rx_filt_log_col_index = 0;
-
- printf("sizeof FDMDV states: %d bytes\n", sizeof(struct FDMDV));
-
- for(f=0; f<FRAMES; f++) {
-
- /* --------------------------------------------------------*\
- Modulator
- \*---------------------------------------------------------*/
-
- fdmdv_get_test_bits(fdmdv, tx_bits);
- bits_to_dqpsk_symbols(tx_symbols, fdmdv->prev_tx_symbols, tx_bits, &fdmdv->tx_pilot_bit);
- memcpy(fdmdv->prev_tx_symbols, tx_symbols, sizeof(COMP)*(NC+1));
- tx_filter(tx_baseband, tx_symbols, fdmdv->tx_filter_memory);
- fdm_upconvert(tx_fdm, tx_baseband, fdmdv->phase_tx, fdmdv->freq);
-
- /* --------------------------------------------------------*\
- Channel
- \*---------------------------------------------------------*/
-
- nin = next_nin;
- /*
- if (f == 2)
- nin = 120;
- if (f == 3)
- nin = 200;
- if ((f !=2) && (f != 3))
- nin = M;
- */
- /* add M tx samples to end of buffer */
-
- assert((channel_count + M) < CHANNEL_BUF_SIZE);
- for(i=0; i<M; i++)
- channel[channel_count+i] = tx_fdm[i].real;
- channel_count += M;
-
- /* take nin samples from start of buffer */
-
- for(i=0; i<nin; i++) {
- rx_fdm[i].real = channel[i];
- rx_fdm[i].imag = 0;
- }
-
- /* shift buffer back */
-
- for(i=0,j=nin; j<channel_count; i++,j++)
- channel[i] = channel[j];
- channel_count -= nin;
-
- /* --------------------------------------------------------*\
- Demodulator
- \*---------------------------------------------------------*/
-
- /* freq offset estimation and correction */
-
- foff_coarse = rx_est_freq_offset(fdmdv, rx_fdm, nin);
- if (fdmdv->coarse_fine == COARSE)
- fdmdv->foff = foff_coarse;
- fdmdv_freq_shift(rx_fdm_fcorr, rx_fdm, fdmdv->foff, &fdmdv->foff_rect, &fdmdv->foff_phase_rect, nin);
-
- /* baseband processing */
-
- fdm_downconvert(rx_baseband, rx_fdm_fcorr, fdmdv->phase_rx, fdmdv->freq, nin);
- rx_filter(rx_filt, rx_baseband, fdmdv->rx_filter_memory, nin);
- rx_timing = rx_est_timing(rx_symbols, rx_filt, rx_baseband, fdmdv->rx_filter_mem_timing, env, fdmdv->rx_baseband_mem_timing, nin);
- foff_fine = qpsk_to_bits(rx_bits, &sync_bit, fdmdv->phase_difference, fdmdv->prev_rx_symbols, rx_symbols);
- snr_update(fdmdv->sig_est, fdmdv->noise_est, fdmdv->phase_difference);
- memcpy(fdmdv->prev_rx_symbols, rx_symbols, sizeof(COMP)*(NC+1));
-
- next_nin = M;
-
- if (rx_timing > 2*M/P)
- next_nin += M/P;
-
- if (rx_timing < 0)
- next_nin -= M/P;
-
- fdmdv->coarse_fine = freq_state(sync_bit, &fdmdv->fest_state);
- fdmdv->foff -= TRACK_COEFF*foff_fine;
-
- /* --------------------------------------------------------*\
- Log each vector
- \*---------------------------------------------------------*/
-
- memcpy(&tx_bits_log[FDMDV_BITS_PER_FRAME*f], tx_bits, sizeof(int)*FDMDV_BITS_PER_FRAME);
- memcpy(&tx_symbols_log[(NC+1)*f], tx_symbols, sizeof(COMP)*(NC+1));
- for(c=0; c<NC+1; c++)
- for(i=0; i<M; i++)
- tx_baseband_log[c][f*M+i] = tx_baseband[c][i];
- memcpy(&tx_fdm_log[M*f], tx_fdm, sizeof(COMP)*M);
-
- /* freq offset estimation */
-
- memcpy(&pilot_baseband1_log[f*NPILOTBASEBAND], fdmdv->pilot_baseband1, sizeof(COMP)*NPILOTBASEBAND);
- memcpy(&pilot_baseband2_log[f*NPILOTBASEBAND], fdmdv->pilot_baseband2, sizeof(COMP)*NPILOTBASEBAND);
- memcpy(&pilot_lpf1_log[f*NPILOTLPF], fdmdv->pilot_lpf1, sizeof(COMP)*NPILOTLPF);
- memcpy(&pilot_lpf2_log[f*NPILOTLPF], fdmdv->pilot_lpf2, sizeof(COMP)*NPILOTLPF);
- memcpy(&S1_log[f*MPILOTFFT], fdmdv->S1, sizeof(COMP)*MPILOTFFT);
- memcpy(&S2_log[f*MPILOTFFT], fdmdv->S2, sizeof(COMP)*MPILOTFFT);
- foff_coarse_log[f] = foff_coarse;
- foff_log[f] = fdmdv->foff;
-
- /* rx down conversion */
-
- for(c=0; c<NC+1; c++) {
- for(i=0; i<nin; i++)
- rx_baseband_log[c][rx_baseband_log_col_index + i] = rx_baseband[c][i];
- }
- rx_baseband_log_col_index += nin;
-
- /* rx filtering */
-
- for(c=0; c<NC+1; c++) {
- for(i=0; i<(P*nin)/M; i++)
- rx_filt_log[c][rx_filt_log_col_index + i] = rx_filt[c][i];
- }
- rx_filt_log_col_index += (P*nin)/M;
-
- /* timing estimation */
-
- memcpy(&env_log[NT*P*f], env, sizeof(float)*NT*P);
- rx_timing_log[f] = rx_timing;
- nin_log[f] = nin;
- for(c=0; c<NC+1; c++)
- rx_symbols_log[c][f] = rx_symbols[c];
-
- /* qpsk_to_bits() */
-
- memcpy(&rx_bits_log[FDMDV_BITS_PER_FRAME*f], rx_bits, sizeof(int)*FDMDV_BITS_PER_FRAME);
- for(c=0; c<NC+1; c++) {
- sig_est_log[c][f] = fdmdv->sig_est[c];
- noise_est_log[c][f] = fdmdv->noise_est[c];
- }
- foff_fine_log[f] = foff_fine;
- sync_bit_log[f] = sync_bit;
-
- coarse_fine_log[f] = fdmdv->coarse_fine;
- }
-
-
- /*---------------------------------------------------------*\
- Dump logs to Octave file for evaluation
- by tfdmdv.m Octave script
- \*---------------------------------------------------------*/
-
- fout = fopen("tfdmdv_out.txt","wt");
- assert(fout != NULL);
- fprintf(fout, "# Created by tfdmdv.c\n");
- octave_save_int(fout, "tx_bits_log_c", tx_bits_log, 1, FDMDV_BITS_PER_FRAME*FRAMES);
- octave_save_complex(fout, "tx_symbols_log_c", tx_symbols_log, 1, (NC+1)*FRAMES, (NC+1)*FRAMES);
- octave_save_complex(fout, "tx_baseband_log_c", (COMP*)tx_baseband_log, (NC+1), M*FRAMES, M*FRAMES);
- octave_save_complex(fout, "tx_fdm_log_c", (COMP*)tx_fdm_log, 1, M*FRAMES, M*FRAMES);
- octave_save_complex(fout, "pilot_lut_c", (COMP*)fdmdv->pilot_lut, 1, NPILOT_LUT, NPILOT_LUT);
- octave_save_complex(fout, "pilot_baseband1_log_c", pilot_baseband1_log, 1, NPILOTBASEBAND*FRAMES, NPILOTBASEBAND*FRAMES);
- octave_save_complex(fout, "pilot_baseband2_log_c", pilot_baseband2_log, 1, NPILOTBASEBAND*FRAMES, NPILOTBASEBAND*FRAMES);
- octave_save_complex(fout, "pilot_lpf1_log_c", pilot_lpf1_log, 1, NPILOTLPF*FRAMES, NPILOTLPF*FRAMES);
- octave_save_complex(fout, "pilot_lpf2_log_c", pilot_lpf2_log, 1, NPILOTLPF*FRAMES, NPILOTLPF*FRAMES);
- octave_save_complex(fout, "S1_log_c", S1_log, 1, MPILOTFFT*FRAMES, MPILOTFFT*FRAMES);
- octave_save_complex(fout, "S2_log_c", S2_log, 1, MPILOTFFT*FRAMES, MPILOTFFT*FRAMES);
- octave_save_float(fout, "foff_log_c", foff_log, 1, FRAMES, FRAMES);
- octave_save_float(fout, "foff_coarse_log_c", foff_coarse_log, 1, FRAMES, FRAMES);
- octave_save_complex(fout, "rx_baseband_log_c", (COMP*)rx_baseband_log, (NC+1), rx_baseband_log_col_index, (M+M/P)*FRAMES);
- octave_save_complex(fout, "rx_filt_log_c", (COMP*)rx_filt_log, (NC+1), rx_filt_log_col_index, (P+1)*FRAMES);
- octave_save_float(fout, "env_log_c", env_log, 1, NT*P*FRAMES, NT*P*FRAMES);
- octave_save_float(fout, "rx_timing_log_c", rx_timing_log, 1, FRAMES, FRAMES);
- octave_save_complex(fout, "rx_symbols_log_c", (COMP*)rx_symbols_log, (NC+1), FRAMES, FRAMES);
- octave_save_float(fout, "sig_est_log_c", (float*)sig_est_log, (NC+1), FRAMES, FRAMES);
- octave_save_float(fout, "noise_est_log_c", (float*)noise_est_log, (NC+1), FRAMES, FRAMES);
- octave_save_int(fout, "rx_bits_log_c", rx_bits_log, 1, FDMDV_BITS_PER_FRAME*FRAMES);
- octave_save_float(fout, "foff_fine_log_c", foff_fine_log, 1, FRAMES, FRAMES);
- octave_save_int(fout, "sync_bit_log_c", sync_bit_log, 1, FRAMES);
- octave_save_int(fout, "coarse_fine_log_c", coarse_fine_log, 1, FRAMES);
- octave_save_int(fout, "nin_log_c", nin_log, 1, FRAMES);
- fclose(fout);
-
- fdmdv_destroy(fdmdv);
-
- return 0;
-}
-
+++ /dev/null
-/*
- tfifo.c
- David Rowe
- Nov 19 2012
-
- Takes FIFOs, in particular thread safety.
-*/
-
-#include <assert.h>
-#include <stdio.h>
-#include <pthread.h>
-#include "fifo.h"
-
-#define FIFO_SZ 1024
-#define WRITE_SZ 10
-#define READ_SZ 8
-#define N_MAX 100
-#define LOOPS 1000000
-
-int run_thread = 1;
-struct FIFO *f;
-
-void writer(void);
-void *writer_thread(void *data);
-pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER;
-
-#define USE_THREADS
-//#define USE_MUTEX
-
-int main() {
- pthread_t awriter_thread;
- int i,j;
- short read_buf[READ_SZ];
- int n_out = 0;
- int sucess;
-
- f = fifo_create(FIFO_SZ);
- #ifdef USE_THREADS
- pthread_create(&awriter_thread, NULL, writer_thread, NULL);
- #endif
-
- for(i=0; i<LOOPS; ) {
- #ifndef USE_THREADS
- writer();
- #endif
-
- #ifdef USE_MUTEX
- pthread_mutex_lock(&mutex);
- #endif
- sucess = (fifo_read(f, read_buf, READ_SZ) == 0);
- #ifdef USE_MUTEX
- pthread_mutex_unlock(&mutex);
- #endif
-
- if (sucess) {
- for(j=0; j<READ_SZ; j++) {
- if (read_buf[j] != n_out)
- printf("error: %d %d\n", read_buf[j], n_out);
- n_out++;
- if (n_out == N_MAX)
- n_out = 0;
- }
- i++;
- }
-
- }
-
- #ifdef USE_THREADS
- run_thread = 0;
- pthread_join(awriter_thread,NULL);
- #endif
-
- return 0;
-}
-
-int n_in = 0;
-
-void writer(void) {
- short write_buf[WRITE_SZ];
- int i;
-
- if ((FIFO_SZ - fifo_used(f)) > WRITE_SZ) {
- for(i=0; i<WRITE_SZ; i++) {
- write_buf[i] = n_in++;
- if (n_in == N_MAX)
- n_in = 0;
- }
- #ifdef USE_MUTEX
- pthread_mutex_lock(&mutex);
- #endif
- fifo_write(f, write_buf, WRITE_SZ);
- pthread_mutex_unlock(&mutex);
- }
-}
-
-void *writer_thread(void *data) {
-
- while(run_thread) {
- writer();
- }
-
- return NULL;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tinterp.c
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/10
-
- Tests interpolation functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-#include <sys/types.h>
-#include <sys/stat.h>
-#include <unistd.h>
-
-#include "defines.h"
-#include "sine.h"
-#include "interp.h"
-
-void make_amp(MODEL *model, float f0, float cdB, float mdBHz)
-{
- int i;
- float mdBrad = mdBHz*FS/TWO_PI;
-
- model->Wo = f0*TWO_PI/FS;
- model->L = PI/model->Wo;
- for(i=0; i<=model->L; i++)
- model->A[i] = pow(10.0,(cdB + (float)i*model->Wo*mdBrad)/20.0);
- model->voiced = 1;
-}
-
-void write_amp(char file[], MODEL *model)
-{
- FILE *f;
- int i;
-
- f = fopen(file,"wt");
- for(i=1; i<=model->L; i++)
- fprintf(f, "%f\t%f\n", model->Wo*i, model->A[i]);
- fclose(f);
-}
-
-const char *get_next_float(const char *s, float *num)
-{
- const char *p = s;
- char tmp[MAX_STR];
-
- while(*p && !isspace(*p))
- p++;
- assert((p-s) < (int)(sizeof(tmp)-1));
- memcpy(tmp, s, p-s);
- tmp[p-s] = 0;
- *num = atof(tmp);
-
- return p+1;
-}
-
-const char *get_next_int(const char *s, int *num)
-{
- const char *p = s;
- char tmp[MAX_STR];
-
- while(*p && !isspace(*p))
- p++;
- assert((p-s) < (int)(sizeof(tmp)-1));
- memcpy(tmp, s, p-s);
- tmp[p-s] = 0;
- *num = atoi(tmp);
-
- return p+1;
-}
-
-void load_amp(MODEL *model, const char * file, int frame)
-{
- FILE *f;
- int i;
- char s[1024];
- const char *ps;
-
- f = fopen(file,"rt");
- assert(f);
-
- for(i=0; i<frame; i++)
- ps = fgets(s, 1023, f);
-
- /// can frame ever be 0? what if fgets fails?
- ps = s;
- ps = get_next_float(ps, &model->Wo);
- ps = get_next_int(ps, &model->L);
- for(i=1; i<=model->L; i++)
- ps = get_next_float(ps, &model->A[i]);
-
- fclose(f);
-}
-
-void load_or_make_amp(MODEL *model,
- const char * filename, int frame,
- float f0, float cdB, float mdBHz)
-{
- struct stat buf;
- int rc = stat(filename, &buf);
- if (rc || !S_ISREG(buf.st_mode) || ((buf.st_mode & S_IRUSR) != S_IRUSR))
- {
- make_amp(model, f0, cdB, mdBHz);
- }
- else
- {
- load_amp(model, filename, frame);
- }
-}
-int main() {
- MODEL prev, next, interp;
-
- load_or_make_amp(&prev,
- "../src/hts1a_model.txt", 32,
- 50.0, 60.0, 6E-3);
- load_or_make_amp(&next,
- "../src/hts1a_model.txt", 34,
- 50.0, 40.0, 6E-3);
-
- interp.voiced = 1;
- interpolate(&interp, &prev, &next);
-
- write_amp("tinterp_prev.txt", &prev);
- write_amp("tinterp_interp.txt", &interp);
- write_amp("tinterp_next.txt", &next);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tlspsens.c
- AUTHOR......: David Rowe
- DATE CREATED: 31 May 2012
-
- Testing bit error sensitivity of LSP bits, first step in devising an unequal
- error protection scheme.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-#include "defines.h"
-#include "comp.h"
-#include "codec2.h"
-#include "quantise.h"
-#include "interp.h"
-#include "codec2_internal.h"
-
-float run_a_test(char raw_file_name[], int bit_to_corrupt)
-{
- FILE *fin;
- short buf[N];
- struct CODEC2 *c2;
- kiss_fft_cfg fft_fwd_cfg;
- MODEL model;
- float ak[LPC_ORD+1];
- float lsps[LPC_ORD], e;
- int lsp_indexes[LPC_ORD], found_bit;
- float snr, snr_sum;
- int frames, i, mask, index;
-
- c2 = codec2_create(CODEC2_MODE_2400);
- fft_fwd_cfg = kiss_fft_alloc(FFT_ENC, 0, NULL, NULL);
-
- fin = fopen(raw_file_name, "rb");
- assert(fin != NULL);
-
- /* find bit we are corrupting */
-
- found_bit = 0;
- for(i=0; i<LSP_SCALAR_INDEXES; i++) {
- if (!found_bit) {
- if (bit_to_corrupt > lsp_bits(i))
- bit_to_corrupt -= lsp_bits(i);
- else {
- index = i;
- mask = (1 << bit_to_corrupt);
- printf(" index: %d bit: %d mask: 0x%x ", index, bit_to_corrupt, mask);
- found_bit = 1;
- }
- }
- }
- assert(found_bit == 1);
-
- /* OK test a sample file, flipping bit */
-
- snr_sum = 0.0;
- frames = 0;
- while(fread(buf, sizeof(short), N, fin) == N) {
- analyse_one_frame(c2, &model, buf);
- e = speech_to_uq_lsps(lsps, ak, c2->Sn, c2->w, LPC_ORD);
- encode_lsps_scalar(lsp_indexes, lsps, LPC_ORD);
-
- /* find and flip bit we are testing */
-
- lsp_indexes[index] ^= mask;
-
- /* decode LSPs and measure SNR */
-
- decode_lsps_scalar(lsps, lsp_indexes, LPC_ORD);
- check_lsp_order(lsps, LPC_ORD);
- bw_expand_lsps(lsps, LPC_ORD);
- lsp_to_lpc(lsps, ak, LPC_ORD);
- aks_to_M2(fft_fwd_cfg, ak, LPC_ORD, &model, e, &snr, 0, 0, 1, 1, LPCPF_BETA, LPCPF_GAMMA);
- snr_sum += snr;
- frames++;
- }
-
- codec2_destroy(c2);
-
- fclose(fin);
-
- return snr_sum/frames;
-}
-
-int main(int argc, char *argv[]) {
- int i;
- int total_lsp_bits = 0;
- float snr;
-
- if (argc != 2) {
- printf("usage: %s RawFile\n", argv[0]);
- exit(1);
- }
-
- for(i=0; i<LPC_ORD; i++)
- total_lsp_bits += lsp_bits(i);
-
- for(i=0; i<total_lsp_bits; i++) {
- snr = run_a_test(argv[1], i);
- printf("%d %5.2f\n", i, snr);
- }
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tnlp.c
- AUTHOR......: David Rowe
- DATE CREATED: 23/3/93
-
- Test program for non linear pitch estimation functions.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#define N 80 /* frame size */
-#define M 320 /* pitch analysis window size */
-#define PITCH_MIN 20
-#define PITCH_MAX 160
-#define TNLP
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-
-#include "defines.h"
-#include "dump.h"
-#include "sine.h"
-#include "nlp.h"
-#include "kiss_fft.h"
-
-int frames;
-
-/*---------------------------------------------------------------------------*\
-
- switch_present()
-
- Searches the command line arguments for a "switch". If the switch is
- found, returns the command line argument where it ws found, else returns
- NULL.
-
-\*---------------------------------------------------------------------------*/
-
-int switch_present(sw,argc,argv)
- char sw[]; /* switch in string form */
- int argc; /* number of command line arguments */
- char *argv[]; /* array of command line arguments in string form */
-{
- int i; /* loop variable */
-
- for(i=1; i<argc; i++)
- if (!strcmp(sw,argv[i]))
- return(i);
-
- return 0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- MAIN
-
-\*---------------------------------------------------------------------------*/
-
-int main(argc,argv)
-int argc;
-char *argv[];
-{
- FILE *fin,*fout;
- short buf[N];
- float Sn[M]; /* float input speech samples */
- kiss_fft_cfg fft_fwd_cfg;
- COMP Sw[FFT_ENC]; /* DFT of Sn[] */
- float w[M]; /* time domain hamming window */
- COMP W[FFT_ENC]; /* DFT of w[] */
- float pitch;
- int i;
- float prev_Wo;
- void *nlp_states;
-#ifdef DUMP
- int dump;
-#endif
-
- if (argc < 3) {
- printf("\nusage: tnlp InputRawSpeechFile OutputPitchTextFile "
- "[--dump DumpFile]\n");
- exit(1);
- }
-
- /* Input file */
-
- if ((fin = fopen(argv[1],"rb")) == NULL) {
- printf("Error opening input speech file: %s\n",argv[1]);
- exit(1);
- }
-
- /* Output file */
-
- if ((fout = fopen(argv[2],"wt")) == NULL) {
- printf("Error opening output text file: %s\n",argv[2]);
- exit(1);
- }
-
-#ifdef DUMP
- dump = switch_present("--dump",argc,argv);
- if (dump)
- dump_on(argv[dump+1]);
-#else
-/// TODO
-/// #warning "Compile with -DDUMP if you expect to dump anything."
-#endif
-
- nlp_states = nlp_create();
- fft_fwd_cfg = kiss_fft_alloc(FFT_ENC, 0, NULL, NULL);
- make_analysis_window(fft_fwd_cfg, w, W);
-
- frames = 0;
- prev_Wo = 0;
- while(fread(buf,sizeof(short),N,fin)) {
- printf("%d\n", frames++);
-
- /* Update input speech buffers */
-
- for(i=0; i<M-N; i++)
- Sn[i] = Sn[i+N];
- for(i=0; i<N; i++)
- Sn[i+M-N] = buf[i];
- dft_speech(fft_fwd_cfg, Sw, Sn, w);
-#ifdef DUMP
- dump_Sn(Sn); dump_Sw(Sw);
-#endif
-
- nlp(nlp_states,Sn,N,M,PITCH_MIN,PITCH_MAX,&pitch,Sw,W, &prev_Wo);
- prev_Wo = TWO_PI/pitch;
-
- fprintf(fout,"%f\n",pitch);
- }
-
- fclose(fin);
- fclose(fout);
-#ifdef DUMP
- if (dump) dump_off();
-#endif
- nlp_destroy(nlp_states);
-
- return 0;
-}
-
-
+++ /dev/null
-/*
- tpre_de.c
- David Rowe
- Sep 24 2012
-
- Unit test to generate the combined impulse response of pre & de-emphasis filters.
-
- pl("../unittest/out48.raw",1,3000)
- pl("../unittest/out8.raw",1,3000)
-
- Listening to it also shows up anything nasty:
-
- $ play -s -2 -r 48000 out48.raw
- $ play -s -2 -r 8000 out8.raw
-
- */
-
-#include <assert.h>
-#include <math.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include "lpc.h"
-
-#define N 10
-#define F 10
-
-int main() {
- FILE *fprede;
- float Sn[N], Sn_pre[N], Sn_de[N];
- float pre_mem = 0.0, de_mem = 0.0;
- int i, f;
-
- fprede = fopen("prede.txt", "wt");
- assert(fprede != NULL);
-
- for(i=0; i<N; i++)
- Sn[i] = 0.0;
-
- Sn[0]= 1.0;
-
- for(f=0; f<F; f++) {
- pre_emp(Sn_pre, Sn, &pre_mem, N);
- de_emp(Sn_de, Sn_pre, &de_mem, N);
- for(i=0; i<N; i++) {
- fprintf(fprede, "%f\n", Sn_de[i]);
- }
- Sn[0] = 0.0;
- }
-
- fclose(fprede);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: tquant.c
- AUTHOR......: David Rowe
- DATE CREATED: 22/8/10
-
- Generates quantisation curves for plotting on Octave.
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2010 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-#include <math.h>
-
-#include "defines.h"
-#include "dump.h"
-#include "quantise.h"
-
-int test_Wo_quant();
-int test_lsp_quant();
-int test_lsp(int lsp_number, int levels, float max_error_hz);
-int test_energy_quant(int levels, float max_error_dB);
-
-int main() {
- quantise_init();
- test_Wo_quant();
- test_lsp_quant();
- test_energy_quant(E_LEVELS, 0.5*(E_MAX_DB - E_MIN_DB)/E_LEVELS);
-
- return 0;
-}
-
-int test_lsp_quant() {
- test_lsp( 1, 16, 12.5);
- test_lsp( 2, 16, 12.5);
- test_lsp( 3, 16, 25);
- test_lsp( 4, 16, 50);
- test_lsp( 5, 16, 50);
- test_lsp( 6, 16, 50);
- test_lsp( 7, 16, 50);
- test_lsp( 8, 8, 50);
- test_lsp( 9, 8, 50);
- test_lsp(10, 4, 100);
-
- return 0;
-}
-
-int test_energy_quant(int levels, float max_error_dB) {
- FILE *fe;
- float e,e_dec, error, low_e, high_e;
- int index, index_in, index_out, i;
-
- /* check 1:1 match between input and output levels */
-
- for(i=0; i<levels; i++) {
- index_in = i;
- e = decode_energy(index_in);
- index_out = encode_energy(e);
- if (index_in != index_out) {
- printf("edB: %f index_in: %d index_out: %d\n",
- 10.0*log10(e), index_in, index_out);
- exit(0);
- }
- }
-
- /* check error over range of quantiser */
-
- low_e = decode_energy(0);
- high_e = decode_energy(levels-1);
- fe = fopen("energy_err.txt", "wt");
-
- for(e=low_e; e<high_e; e +=(high_e-low_e)/1000.0) {
- index = encode_energy(e);
- e_dec = decode_energy(index);
- error = 10.0*log10(e) - 10.0*log10(e_dec);
- fprintf(fe, "%f\n", error);
- if (fabs(error) > max_error_dB) {
- printf("error: %f %f\n", error, max_error_dB);
- exit(0);
- }
- }
-
- fclose(fe);
- return 0;
-}
-
-int test_lsp(int lsp_number, int levels, float max_error_hz) {
- float lsp[LPC_ORD];
- int indexes_in[LPC_ORD];
- int indexes_out[LPC_ORD];
- int indexes[LPC_ORD];
- int i;
- float lowf, highf, f, error;
- char s[MAX_STR];
- FILE *flsp;
- float max_error_rads;
-
- lsp_number--;
- max_error_rads = max_error_hz*TWO_PI/FS;
-
- for(i=0; i<LPC_ORD; i++)
- indexes_in[i] = 0;
-
- for(i=0; i<levels; i++) {
- indexes_in[lsp_number] = i;
- decode_lsps_scalar(lsp, indexes_in, LPC_ORD);
- encode_lsps_scalar(indexes_out, lsp,LPC_ORD);
- if (indexes_in[lsp_number] != indexes_out[lsp_number]) {
- printf("freq: %f index_in: %d index_out: %d\n",
- lsp[lsp_number]+1, indexes_in[lsp_number],
- indexes_out[lsp_number]);
- exit(0);
- }
- }
-
- for(i=0; i<LPC_ORD; i++)
- indexes[i] = 0;
- indexes[lsp_number] = 0;
- decode_lsps_scalar(lsp, indexes, LPC_ORD);
- lowf = lsp[lsp_number];
- indexes[lsp_number] = levels - 1;
- decode_lsps_scalar(lsp, indexes, LPC_ORD);
- highf = lsp[lsp_number];
- sprintf(s,"lsp%d_err.txt", lsp_number+1);
- flsp = fopen(s, "wt");
-
- for(f=lowf; f<highf; f +=(highf-lowf)/1000.0) {
- lsp[lsp_number] = f;
- encode_lsps_scalar(indexes, lsp, LPC_ORD);
- decode_lsps_scalar(lsp, indexes, LPC_ORD);
- error = f - lsp[lsp_number];
- fprintf(flsp, "%f\n", error);
- if (fabs(error) > max_error_rads) {
- printf("%d error: %f %f\n", lsp_number+1, error, max_error_rads);
- exit(0);
- }
- }
-
- fclose(flsp);
-
- printf("OK\n");
-
- return 0;
-}
-
-int test_Wo_quant() {
- int c;
- FILE *f;
- float Wo,Wo_dec, error, step_size;
- int index, index_in, index_out;
-
- /* output Wo quant curve for plotting */
-
- f = fopen("quant_pitch.txt","wt");
-
- for(Wo=0.9*(TWO_PI/P_MAX); Wo<=1.1*(TWO_PI/P_MIN); Wo += 0.001) {
- index = encode_Wo(Wo);
- fprintf(f, "%f %d\n", Wo, index);
- }
-
- fclose(f);
-
- /* check for all Wo codes we get 1:1 match between encoder
- and decoder Wo levels */
-
- for(c=0; c<WO_LEVELS; c++) {
- index_in = c;
- Wo = decode_Wo(index_in);
- index_out = encode_Wo(Wo);
- if (index_in != index_out)
- printf(" Wo %f index_in %d index_out %d\n", Wo,
- index_in, index_out);
- }
-
- /* measure quantisation error stats and compare to expected. Also
- plot histogram of error file to check. */
-
- f = fopen("quant_pitch_err.txt","wt");
- step_size = ((TWO_PI/P_MIN) - (TWO_PI/P_MAX))/WO_LEVELS;
-
- for(Wo=TWO_PI/P_MAX; Wo<0.99*TWO_PI/P_MIN; Wo += 0.0001) {
- index = encode_Wo(Wo);
- Wo_dec = decode_Wo(index);
- error = Wo - Wo_dec;
- if (fabs(error) > (step_size/2.0)) {
- printf("error: %f step_size/2: %f\n", error, step_size/2.0);
- exit(0);
- }
- fprintf(f,"%f\n",error);
- }
- printf("OK\n");
-
- fclose(f);
- return 0;
-}
+++ /dev/null
-/*
- tsrc.c
- David Rowe
- Sat Nov 3 2012
-
- Unit test for libresample code.
-
- */
-
-#include <assert.h>
-#include <math.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <samplerate.h>
-
-#define N8 160 /* processing buffer size at 8 kHz */
-#define N48 ((int)N8*(48000/8000)) /* buf size assuming 48k max sample rate */
-
-int main(int argc, char *argv[]) {
- FILE *f8k, *fout;
- short in8k_short[N8];
- float in8k[N8];
- float out[N48];
- short out_short[N48];
- SRC_STATE *src;
- SRC_DATA data;
- int error;
-
- if (argc != 4) {
- printf("usage %s inputRawFile OutputRawFile OutputSamplerate\n", argv[0]);
- exit(0);
- }
-
- f8k = fopen(argv[1], "rb");
- assert(f8k != NULL);
-
- fout = fopen(argv[2], "wb");
- assert(fout != NULL);
-
- src = src_new(SRC_SINC_FASTEST, 1, &error);
- assert(src != NULL);
-
- data.data_in = in8k;
- data.data_out = out;
- data.input_frames = N8;
- data.output_frames = N48;
- data.end_of_input = 0;
- data.src_ratio = atof(argv[3])/8000;
- printf("%f\n", data.src_ratio);
-
- while(fread(in8k_short, sizeof(short), N8, f8k) == N8) {
- src_short_to_float_array(in8k_short, in8k, N8);
- src_process(src, &data);
- printf("%d %d\n", (int)data.output_frames , (int)data.output_frames_gen);
- assert(data.output_frames_gen <= N48);
- src_float_to_short_array(out, out_short, data.output_frames_gen);
- fwrite(out_short, sizeof(short), data.output_frames_gen, fout);
- }
-
- fclose(fout);
- fclose(f8k);
-
- return 0;
-}
+++ /dev/null
-/*---------------------------------------------------------------------------*\
-
- FILE........: vq_train_jvm.c
- AUTHOR......: Jean-Marc Valin
- DATE CREATED: 21 Jan 2012
-
- Multi-stage Vector Quantoser training program developed by Jean-Marc at
- linux.conf.au 2012. Minor mods by David Rowe
-
-\*---------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 Jean-Marc Valin
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-
-#ifdef VALGRIND
-#include <valgrind/memcheck.h>
-#endif
-
-#include <assert.h>
-#include <stdlib.h>
-#include <stdio.h>
-#include <math.h>
-
-#define MIN(a,b) ((a)<(b)?(a):(b))
-#define COEF 0.0f
-#define MAX_ENTRIES 16384
-
-void compute_weights(const float *x, float *w, int ndim)
-{
- int i;
- w[0] = MIN(x[0], x[1]-x[0]);
- for (i=1;i<ndim-1;i++)
- w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
- w[ndim-1] = MIN(x[ndim-1]-x[ndim-2], M_PI-x[ndim-1]);
-
- for (i=0;i<ndim;i++)
- w[i] = 1./(.01+w[i]);
- w[0]*=3;
- w[1]*=2;
-}
-
-int find_nearest(const float *codebook, int nb_entries, float *x, int ndim, float *min_dist)
-{
- int i, j;
- int nearest = 0;
-
- *min_dist = 1E15;
-
- for (i=0;i<nb_entries;i++)
- {
- float dist=0;
- for (j=0;j<ndim;j++)
- dist += (x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
- if (dist<*min_dist)
- {
- *min_dist = dist;
- nearest = i;
- }
- }
- return nearest;
-}
-
-int find_nearest_weighted(const float *codebook, int nb_entries, float *x, const float *w, int ndim)
-{
- int i, j;
- float min_dist = 1e15;
- int nearest = 0;
-
- for (i=0;i<nb_entries;i++)
- {
- float dist=0;
- for (j=0;j<ndim;j++)
- dist += w[j]*(x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
- if (dist<min_dist)
- {
- min_dist = dist;
- nearest = i;
- }
- }
- return nearest;
-}
-
-int quantize_lsp(const float *x, const float *codebook1, const float *codebook2,
- const float *codebook3, int nb_entries, float *xq, int ndim)
-{
- int i, n1, n2, n3;
- float err[ndim], err2[ndim], err3[ndim];
- float w[ndim], w2[ndim], w3[ndim], min_dist;
-
- w[0] = MIN(x[0], x[1]-x[0]);
- for (i=1;i<ndim-1;i++)
- w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
- w[ndim-1] = MIN(x[ndim-1]-x[ndim-2], M_PI-x[ndim-1]);
-
- /*
- for (i=0;i<ndim;i++)
- w[i] = 1./(.003+w[i]);
- w[0]*=3;
- w[1]*=2;*/
- compute_weights(x, w, ndim);
-
- for (i=0;i<ndim;i++)
- err[i] = x[i]-COEF*xq[i];
- n1 = find_nearest(codebook1, nb_entries, err, ndim, &min_dist);
-
- for (i=0;i<ndim;i++)
- {
- xq[i] = COEF*xq[i] + codebook1[ndim*n1+i];
- err[i] -= codebook1[ndim*n1+i];
- }
- for (i=0;i<ndim/2;i++)
- {
- err2[i] = err[2*i];
- err3[i] = err[2*i+1];
- w2[i] = w[2*i];
- w3[i] = w[2*i+1];
- }
- n2 = find_nearest_weighted(codebook2, nb_entries, err2, w2, ndim/2);
- n3 = find_nearest_weighted(codebook3, nb_entries, err3, w3, ndim/2);
-
- for (i=0;i<ndim/2;i++)
- {
- xq[2*i] += codebook2[ndim*n2/2+i];
- xq[2*i+1] += codebook3[ndim*n3/2+i];
- }
- return 0;
-}
-
-void split(float *codebook, int nb_entries, int ndim)
-{
- int i,j;
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- {
- float delta = .01*(rand()/(float)RAND_MAX-.5);
- codebook[i*ndim+j] += delta;
- codebook[(i+nb_entries)*ndim+j] = codebook[i*ndim+j] - delta;
- }
- }
-}
-
-void update(float *data, int nb_vectors, float *codebook, int nb_entries, int ndim)
-{
- int i,j;
- int count[nb_entries];
- int nearest[nb_vectors];
- float min_dist;
- float total_min_dist = 0;
-
- for (i=0;i<nb_entries;i++)
- count[i] = 0;
-
- for (i=0;i<nb_vectors;i++)
- {
- nearest[i] = find_nearest(codebook, nb_entries, data+i*ndim, ndim, &min_dist);
- total_min_dist += min_dist;
- }
- for (i=0;i<nb_entries*ndim;i++)
- codebook[i] = 0;
-
- for (i=0;i<nb_vectors;i++)
- {
- int n = nearest[i];
- count[n]++;
- for (j=0;j<ndim;j++)
- codebook[n*ndim+j] += data[i*ndim+j];
- }
-
- float w2=0;
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- codebook[i*ndim+j] *= (1./count[i]);
- w2 += (count[i]/(float)nb_vectors)*(count[i]/(float)nb_vectors);
- }
- fprintf(stderr, "%f / %d var = %f\n", 1./w2, nb_entries, total_min_dist/nb_vectors );
-}
-
-void update_weighted(float *data, float *weight, int nb_vectors, float *codebook, int nb_entries, int ndim)
-{
- int i,j;
- float count[MAX_ENTRIES][ndim];
- int nearest[nb_vectors];
-
- for (i=0;i<nb_entries;i++)
- for (j=0;j<ndim;j++)
- count[i][j] = 0;
-
- for (i=0;i<nb_vectors;i++)
- {
- nearest[i] = find_nearest_weighted(codebook, nb_entries, data+i*ndim, weight+i*ndim, ndim);
- }
- for (i=0;i<nb_entries*ndim;i++)
- codebook[i] = 0;
-
- for (i=0;i<nb_vectors;i++)
- {
- int n = nearest[i];
- for (j=0;j<ndim;j++)
- {
- float w = sqrt(weight[i*ndim+j]);
- count[n][j]+=w;
- codebook[n*ndim+j] += w*data[i*ndim+j];
- }
- }
-
- //float w2=0;
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- codebook[i*ndim+j] *= (1./count[i][j]);
- //w2 += (count[i]/(float)nb_vectors)*(count[i]/(float)nb_vectors);
- }
- //fprintf(stderr, "%f / %d\n", 1./w2, nb_entries);
-}
-
-void vq_train(float *data, int nb_vectors, float *codebook, int nb_entries, int ndim)
-{
- int i, j, e;
- e = 1;
-
- for (j=0;j<ndim;j++)
- codebook[j] = 0;
- for (i=0;i<nb_vectors;i++)
- for (j=0;j<ndim;j++)
- codebook[j] += data[i*ndim+j];
- for (j=0;j<ndim;j++)
- codebook[j] *= (1./nb_vectors);
-
- while (e< nb_entries)
- {
- split(codebook, e, ndim);
- fprintf(stderr, "%d\n", e);
- e<<=1;
- for (j=0;j<ndim;j++)
- update(data, nb_vectors, codebook, e, ndim);
- }
-}
-
-void vq_train_weighted(float *data, float *weight, int nb_vectors, float *codebook, int nb_entries, int ndim)
-{
- int i, j, e;
- e = 1;
- for (j=0;j<ndim;j++)
- codebook[j] = 0;
- for (i=0;i<nb_vectors;i++)
- for (j=0;j<ndim;j++)
- codebook[j] += data[i*ndim+j];
- for (j=0;j<ndim;j++)
- codebook[j] *= (1./nb_vectors);
-
- while (e<nb_entries)
- {
- split(codebook, e, ndim);
- fprintf(stderr, "%d\n", e);
- e<<=1;
- for (j=0;j<ndim;j++)
- update_weighted(data, weight, nb_vectors, codebook, e, ndim);
- }
-}
-
-
-int main(int argc, char **argv)
-{
- int i,j;
- FILE *ftrain;
- int nb_vectors, nb_entries, ndim;
- float *data, *pred, *codebook, *codebook2, *codebook3;
- float *weight, *weight2, *weight3;
- float *delta, *delta2;
- float tmp, err, min_dist, total_min_dist;
- int ret;
- char filename[256];
- FILE *fcb;
-
- printf("Jean-Marc Valin's Split VQ training program....\n");
-
- if (argc != 5) {
- printf("usage: %s TrainTextFile K(dimension) M(codebook size) VQFilesPrefix\n", argv[0]);
- exit(1);
- }
-
- ndim = atoi(argv[2]);
- nb_vectors = atoi(argv[3]);
- nb_entries = atoi(argv[3]);
-
- /* determine size of training file */
-
- ftrain = fopen(argv[1],"rt"); assert(ftrain != NULL);
- nb_vectors = 0;
- while (1) {
- if (feof(ftrain))
- break;
- for (j=0;j<ndim;j++)
- {
- ret = fscanf(ftrain, "%f ", &tmp);
- }
- nb_vectors++;
- if ((nb_vectors % 1000) == 0)
- printf("\r%d lines",nb_vectors);
- }
-
- rewind(ftrain);
-
- printf("\nndim %d nb_vectors %d nb_entries %d\n", ndim, nb_vectors, nb_entries);
-
- data = malloc(nb_vectors*ndim*sizeof(*data));
- weight = malloc(nb_vectors*ndim*sizeof(*weight));
- weight2 = malloc(nb_vectors*ndim*sizeof(*weight2));
- weight3 = malloc(nb_vectors*ndim*sizeof(*weight3));
- pred = malloc(nb_vectors*ndim*sizeof(*pred));
- codebook = malloc(nb_entries*ndim*sizeof(*codebook));
- codebook2 = malloc(nb_entries*ndim*sizeof(*codebook2));
- codebook3 = malloc(nb_entries*ndim*sizeof(*codebook3));
-
- for (i=0;i<nb_vectors;i++)
- {
- if (feof(ftrain))
- break;
- for (j=0;j<ndim;j++)
- {
- ret = fscanf(ftrain, "%f ", &data[i*ndim+j]);
- }
- }
- nb_vectors = i;
-
-#ifdef VALGRIND
- VALGRIND_CHECK_MEM_IS_DEFINED(data, nb_entries*ndim);
-#endif
-
- /* determine weights for each training vector */
-
- for (i=0;i<nb_vectors;i++)
- {
- compute_weights(data+i*ndim, weight+i*ndim, ndim);
- for (j=0;j<ndim/2;j++)
- {
- weight2[i*ndim/2+j] = weight[i*ndim+2*j];
- weight3[i*ndim/2+j] = weight[i*ndim+2*j+1];
- }
- }
-
- /* 20ms (two frame gaps) initial predictor state */
-
- for (i=0;i<ndim;i++) {
- pred[i+ndim] = pred[i] = data[i] - M_PI*(i+1)/(ndim+1);
- }
-
- /* generate predicted data for training */
-
- for (i=2;i<nb_vectors;i++)
- {
- for (j=0;j<ndim;j++)
- pred[i*ndim+j] = data[i*ndim+j] - COEF*data[(i-2)*ndim+j];
- }
-
-#ifdef VALGRIND
- VALGRIND_CHECK_MEM_IS_DEFINED(pred, nb_entries*ndim);
-#endif
-
- /* train first stage */
-
- vq_train(pred, nb_vectors, codebook, nb_entries, ndim);
-
- delta = malloc(nb_vectors*ndim*sizeof(*data));
- err = 0;
- total_min_dist = 0;
- for (i=0;i<nb_vectors;i++)
- {
- int nearest = find_nearest(codebook, nb_entries, &pred[i*ndim], ndim, &min_dist);
- total_min_dist += min_dist;
- for (j=0;j<ndim;j++)
- {
- //delta[i*ndim+j] = data[i*ndim+j] - codebook[nearest*ndim+j];
- //printf("%f ", delta[i*ndim+j]);
- //err += (delta[i*ndim+j])*(delta[i*ndim+j]);
- delta[i*ndim/2+j/2+(j&1)*nb_vectors*ndim/2] = pred[i*ndim+j] - codebook[nearest*ndim+j];
- //printf("%f ", delta[i*ndim/2+j/2+(j&1)*nb_vectors*ndim/2]);
- err += (delta[i*ndim/2+j/2+(j&1)*nb_vectors*ndim/2])*(delta[i*ndim/2+j/2+(j&1)*nb_vectors*ndim/2]);
- }
- //printf("\n");
- }
- fprintf(stderr, "Stage 1 LSP RMS error: %f\n", sqrt(err/nb_vectors/ndim));
- fprintf(stderr, "Stage 1 LSP variance.: %f\n", total_min_dist/nb_vectors);
-
-#if 1
- vq_train(delta, nb_vectors, codebook2, nb_entries, ndim/2);
- vq_train(delta+ndim*nb_vectors/2, nb_vectors, codebook3, nb_entries, ndim/2);
-#else
- vq_train_weighted(delta, weight2, nb_vectors, codebook2, nb_entries, ndim/2);
- vq_train_weighted(delta+ndim*nb_vectors/2, weight3, nb_vectors, codebook3, nb_entries, ndim/2);
-#endif
-
- err = 0;
- total_min_dist = 0;
-
- delta2 = delta + nb_vectors*ndim/2;
-
- for (i=0;i<nb_vectors;i++)
- {
- int n1, n2;
- n1 = find_nearest(codebook2, nb_entries, &delta[i*ndim/2], ndim/2, &min_dist);
- for (j=0;j<ndim/2;j++)
- {
- delta[i*ndim/2+j] = delta[i*ndim/2+j] - codebook2[n1*ndim/2+j];
- err += (delta[i*ndim/2+j])*(delta[i*ndim/2+j]);
- }
- total_min_dist += min_dist;
-
- n2 = find_nearest(codebook3, nb_entries, &delta2[i*ndim/2], ndim/2, &min_dist);
- for (j=0;j<ndim/2;j++)
- {
- delta[i*ndim/2+j] = delta[i*ndim/2+j] - codebook2[n2*ndim/2+j];
- err += (delta2[i*ndim/2+j])*(delta2[i*ndim/2+j]);
- }
- total_min_dist += min_dist;
- }
- fprintf(stderr, "Stage 2 LSP RMS error: %f\n", sqrt(err/nb_vectors/ndim));
- fprintf(stderr, "Stage 2 LSP Variance.: %f\n", total_min_dist/nb_vectors);
-
- float xq[ndim];
- for (i=0;i<ndim;i++)
- xq[i] = M_PI*(i+1)/(ndim+1);
-
- for (i=0;i<nb_vectors;i++)
- {
- quantize_lsp(data+i*ndim, codebook, codebook2,
- codebook3, nb_entries, xq, ndim);
- /*for (j=0;j<ndim;j++)
- printf("%f ", xq[j]);
- printf("\n");*/
- }
-
- /* save output tables to text files */
-
- sprintf(filename, "%s1.txt", argv[4]);
- fcb = fopen(filename, "wt"); assert(fcb != NULL);
- fprintf(fcb, "%d %d\n", ndim, nb_entries);
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim;j++)
- fprintf(fcb, "%f ", codebook[i*ndim+j]);
- fprintf(fcb, "\n");
- }
- fclose(fcb);
-
- sprintf(filename, "%s2.txt", argv[4]);
- fcb = fopen(filename, "wt"); assert(fcb != NULL);
- fprintf(fcb, "%d %d\n", ndim/2, nb_entries);
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim/2;j++)
- fprintf(fcb, "%f ", codebook2[i*ndim/2+j]);
- fprintf(fcb, "\n");
- }
- fclose(fcb);
-
- sprintf(filename, "%s3.txt", argv[4]);
- fcb = fopen(filename, "wt"); assert(fcb != NULL);
- fprintf(fcb, "%d %d\n", ndim/2, nb_entries);
- for (i=0;i<nb_entries;i++)
- {
- for (j=0;j<ndim/2;j++)
- fprintf(fcb, "%f ", codebook3[i*ndim/2+j]);
- fprintf(fcb, "\n");
- }
- fclose(fcb);
-
- return 0;
-}
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: VQTRAIN.C
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- This program trains vector quantisers using K dimensional Lloyd-Max
- method.
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2009 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/*-----------------------------------------------------------------------*\
-
- INCLUDES
-
-\*-----------------------------------------------------------------------*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-#include <assert.h>
-
-/*-----------------------------------------------------------------------*\
-
- DEFINES
-
-\*-----------------------------------------------------------------------*/
-
-#define DELTAQ 0.01 /* quiting distortion */
-#define MAX_STR 80 /* maximum string length */
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTION PROTOTYPES
-
-\*-----------------------------------------------------------------------*/
-
-void zero(float v[], int k);
-void acc(float v1[], float v2[], int k);
-void norm(float v[], int k, long n);
-long quantise(float cb[], float vec[], int k, int m, float *se);
-
-/*-----------------------------------------------------------------------* \
-
- MAIN
-
-\*-----------------------------------------------------------------------*/
-
-int main(int argc, char *argv[]) {
- long k,m; /* dimension and codebook size */
- float *vec; /* current vector */
- float *cb; /* vector codebook */
- float *cent; /* centroids for each codebook entry */
- long *n; /* number of vectors in this interval */
- long J; /* number of vectors in training set */
- long i,j;
- long ind; /* index of current vector */
- float se; /* squared error for this iteration */
- float Dn,Dn_1; /* current and previous iterations distortion */
- float delta; /* improvement in distortion */
- FILE *ftrain; /* file containing training set */
- FILE *fvq; /* file containing vector quantiser */
- int ret;
-
- /* Interpret command line arguments */
-
- if (argc != 5) {
- printf("usage: %s TrainFile K(dimension) M(codebook size) VQFile\n", argv[0]);
- exit(1);
- }
-
- /* Open training file */
-
- ftrain = fopen(argv[1],"rb");
- if (ftrain == NULL) {
- printf("Error opening training database file: %s\n",argv[1]);
- exit(1);
- }
-
- /* determine k and m, and allocate arrays */
-
- k = atol(argv[2]);
- m = atol(argv[3]);
- printf("dimension K=%ld number of entries M=%ld\n", k, m);
- vec = (float*)malloc(sizeof(float)*k);
- cb = (float*)malloc(sizeof(float)*k*m);
- cent = (float*)malloc(sizeof(float)*k*m);
- n = (long*)malloc(sizeof(long)*m);
- if (cb == NULL || cb == NULL || cent == NULL || vec == NULL) {
- printf("Error in malloc.\n");
- exit(1);
- }
-
- /* determine size of training set */
-
- J = 0;
- while(fread(vec, sizeof(float), k, ftrain) == (size_t)k)
- J++;
- printf("J=%ld entries in training set\n", J);
-
- /* set up initial codebook state from samples of training set */
-
- rewind(ftrain);
- ret = fread(cb, sizeof(float), k*m, ftrain);
-
- /* main loop */
-
- Dn = 1E32;
- j = 1;
- do {
- Dn_1 = Dn;
-
- /* zero centroids */
-
- for(i=0; i<m; i++) {
- zero(¢[i*k], k);
- n[i] = 0;
- }
-
- /* quantise training set */
-
- se = 0.0;
- rewind(ftrain);
- for(i=0; i<J; i++) {
- ret = fread(vec, sizeof(float), k, ftrain);
- ind = quantise(cb, vec, k, m, &se);
- n[ind]++;
- acc(¢[ind*k], vec, k);
- }
- Dn = se/J;
- delta = (Dn_1-Dn)/Dn;
-
- printf("\r Iteration %ld, Dn = %f, Delta = %e\n", j, Dn, delta);
- j++;
-
- /* determine new codebook from centroids */
-
- if (delta > DELTAQ)
- for(i=0; i<m; i++) {
- if (n[i] != 0) {
- norm(¢[i*k], k, n[i]);
- memcpy(&cb[i*k], ¢[i*k], k*sizeof(float));
- }
- }
-
- } while (delta > DELTAQ);
-
- /* save codebook to disk */
-
- fvq = fopen(argv[4],"wt");
- if (fvq == NULL) {
- printf("Error opening VQ file: %s\n",argv[4]);
- exit(1);
- }
-
- fprintf(fvq,"%ld %ld\n",k,m);
- for(j=0; j<m; j++) {
- for(i=0; i<k; i++)
- fprintf(fvq,"%f ",cb[j*k+i]);
- fprintf(fvq,"\n");
- }
- fclose(fvq);
-
- return 0;
-}
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*-----------------------------------------------------------------------*/
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: zero()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Zeros a vector of length k.
-
-\*---------------------------------------------------------------------------*/
-
-void zero(float v[], int k)
-/* float v[]; ptr to start of vector */
-/* int k; lngth of vector */
-{
- int i;
-
- for(i=0; i<k; i++)
- v[i] = 0.0;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: acc()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Adds k dimensional vectors v1 to v2 and stores the result back in v1.
-
-\*---------------------------------------------------------------------------*/
-
-void acc(float v1[], float v2[], int k)
-/* float v1[]; ptr to start of vector to accumulate */
-/* float v2[]; ptr to start of vector to add */
-/* int k; dimension of vectors */
-{
- int i;
-
- for(i=0; i<k; i++)
- v1[i] += v2[i];
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: norm()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Divides each element in k dimensional vector v by n.
-
-\*---------------------------------------------------------------------------*/
-
-void norm(float v[], int k, long n)
-/* float v[]; ptr to start of vector */
-/* int k; dimension of vectors */
-/* int n; normalising factor */
-{
- int i;
-
- for(i=0; i<k; i++)
- v[i] /= n;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: quantise()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Quantises vec by choosing the nearest vector in codebook cb, and
- returns the vector index. The squared error of the quantised vector
- is added to se.
-
-\*---------------------------------------------------------------------------*/
-
-long quantise(float cb[], float vec[], int k, int m, float *se)
-/* float cb[][K]; current VQ codebook */
-/* float vec[]; vector to quantise */
-/* int k; dimension of vectors */
-/* int m; size of codebook */
-/* float *se; accumulated squared error */
-{
- float e; /* current error */
- long besti; /* best index so far */
- float beste; /* best error so far */
- long j;
- int i;
- float diff;
-
- besti = 0;
- beste = 1E32;
- for(j=0; j<m; j++) {
- e = 0.0;
- for(i=0; i<k; i++) {
- diff = cb[j*k+i]-vec[i];
- e += pow(diff,2.0);
- }
- if (e < beste) {
- beste = e;
- besti = j;
- }
- }
-
- *se += beste;
-
- return(besti);
-}
-
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: vqtrainjnd.c
- AUTHOR......: David Rowe
- DATE CREATED: 10 Nov 2011
-
- This program trains vector quantisers for LSPs using an
- experimental, but very simple Just Noticable Difference (JND)
- algorithm:
-
- - we quantise each training vector to JND steps (say 100Hz for LSPs
- 5-10)
- - we then use the most popular training vectors as our VQ codebook
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2011 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/*-----------------------------------------------------------------------*\
-
- INCLUDES
-
-\*-----------------------------------------------------------------------*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-
-/*-----------------------------------------------------------------------*\
-
- DEFINES
-
-\*-----------------------------------------------------------------------*/
-
-#define PI 3.141592654 /* mathematical constant */
-#define MAX_POP 10
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTION PROTOTYPES
-
-\*-----------------------------------------------------------------------*/
-
-void zero(float v[], int k);
-void acc(float v1[], float v2[], int k);
-void norm(float v[], int k, long n);
-void locate_lsps_jnd_steps(float lsps[], float step, int k);
-
-/*-----------------------------------------------------------------------* \
-
- MAIN
-
-\*-----------------------------------------------------------------------*/
-
-int main(int argc, char *argv[]) {
- int k; /* dimension and codebook size */
- float *vec; /* current vector */
- int *n; /* number of vectors in this interval */
- int J; /* number of vectors in training set */
- int i,j;
- FILE *ftrain; /* file containing training set */
- float *train; /* training database */
- //float *pend_train; /* last entry */
- float *pt;
- int ntrain, match, vec_exists, vec_index=0, entry;
- int popular[MAX_POP], pop_thresh;
- FILE *fvq;
- float jnd;
-
- /* Interpret command line arguments */
-
- if (argc != 6) {
- printf("usage: %s TrainFile K(dimension) JND popThresh VQFile\n",
- argv[0]);
- exit(1);
- }
-
- /* Open training file */
-
- ftrain = fopen(argv[1],"rb");
- if (ftrain == NULL) {
- printf("Error opening training database file: %s\n",argv[1]);
- exit(1);
- }
-
- /* determine k and m, and allocate arrays */
-
- k = atol(argv[2]);
- jnd = atof(argv[3]);
- pop_thresh = atol(argv[4]);
- printf("dimension K=%d popThresh=%d JND=%3.1f Hz\n",
- k, pop_thresh, jnd);
- vec = (float*)malloc(sizeof(float)*k);
- if (vec == NULL) {
- printf("Error in malloc.\n");
- exit(1);
- }
-
- /* determine size of training set */
-
- J = 0;
- while(fread(vec, sizeof(float), k, ftrain) == (size_t)k)
- J++;
- printf("J=%d entries in training set\n", J);
- train = (float*)malloc(sizeof(float)*k*J);
- if (train == NULL) {
- printf("Error in malloc.\n");
- exit(1);
- }
- printf("training array is %d bytes\n", sizeof(float)*k*J);
-
- n = (int*)malloc(sizeof(int)*J);
- if (n == NULL) {
- printf("Error in malloc.\n");
- exit(1);
- }
- for(i=0; i<J; i++)
- n[i] = 0;
-
- /* now load up train data base and quantise */
-
- rewind(ftrain);
- ntrain = 0;
- entry = 0;
- while(fread(vec, sizeof(float), k, ftrain) == (size_t)k) {
-
- /* convert to Hz */
-
- for(j=0; j<k; j++)
- vec[j] *= 4000.0/PI;
-
- /* quantise to JND steps */
-
- locate_lsps_jnd_steps(vec, jnd, k);
-
- /* see if a match already exists in database */
-
- pt = train;
- vec_exists = 0;
- for(i=0; i<ntrain; i++) {
- match = 1;
- for(j=0; j<k; j++)
- if (vec[j] != pt[j])
- match = 0;
- if (match) {
- vec_exists = 1;
- vec_index = i;
- }
- pt += k;
- }
-
- if (vec_exists)
- n[vec_index]++;
- else {
- /* add to database */
-
- for(j=0; j<k; j++) {
- train[ntrain*k + j] = vec[j];
- }
- ntrain++;
-
- }
- entry++;
- if ((entry % 100) == 0)
- printf("\rtrain input vectors: %d unique vectors: %d",
- entry, ntrain);
- }
- printf("\n");
-
- for(i=0; i<MAX_POP; i++)
- popular[i] = 0;
- for(i=0; i<ntrain; i++) {
- if (n[i] < MAX_POP)
- popular[n[i]]++;
- }
-
- for(i=0; i<MAX_POP; i++)
- printf("popular[%d] = %d\n", i, popular[i]);
-
- /* dump result */
-
- fvq = fopen(argv[5],"wt");
- if (fvq == NULL) {
- printf("Error opening VQ file: %s\n",argv[4]);
- exit(1);
- }
-
- fprintf(fvq,"%d %d\n", k, popular[pop_thresh]);
- for(i=0; i<ntrain; i++) {
- if (n[i] > pop_thresh) {
- for(j=0; j<k; j++)
- fprintf(fvq, "%4.1f ",train[i*k+j]);
- fprintf(fvq,"\n");
- }
- }
- fclose(fvq);
-
- return 0;
-}
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*-----------------------------------------------------------------------*/
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: locate_lsps_jnd_steps()
- AUTHOR......: David Rowe
- DATE CREATED: 27/10/2011
-
- Applies a form of Bandwidth Expansion (BW) to a vector of LSPs.
- Listening tests have determined that "quantising" the position of
- each LSP (say to 100Hz steps for LSPs 5..10) introduces a "just
- noticable difference" in the synthesised speech.
-
- This operation can be used before quantisation to limit the input
- data to the quantiser to a number of discrete steps.
-
-\*---------------------------------------------------------------------------*/
-
-void locate_lsps_jnd_steps(float lsps[], float step, int k)
-{
- int i;
-
- for(i=0; i<k; i++) {
- lsps[i] = floor(lsps[i]/step + 0.5)*step;
- if (i) {
- if (lsps[i] == lsps[i-1])
- lsps[i] += step;
-
- }
- }
-
-}
-
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: vqtrainph.c
- AUTHOR......: David Rowe
- DATE CREATED: 27 July 2012
-
- This program trains phase vector quantisers. Modified from
- vqtrain.c
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/*-----------------------------------------------------------------------*\
-
- INCLUDES
-
-\*-----------------------------------------------------------------------*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-#include <assert.h>
-
-typedef struct {
- float real;
- float imag;
-} COMP;
-
-/*-----------------------------------------------------------------------* \
-
- DEFINES
-
-\*-----------------------------------------------------------------------*/
-
-#define DELTAQ 0.01 /* quiting distortion */
-#define MAX_STR 80 /* maximum string length */
-#define PI 3.141592654
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTION PROTOTYPES
-
-\*-----------------------------------------------------------------------*/
-
-void zero(COMP v[], int d);
-void acc(COMP v1[], COMP v2[], int d);
-void norm(COMP v[], int k);
-int quantise(COMP cb[], COMP vec[], int d, int e, float *se);
-void print_vec(COMP cb[], int d, int e);
-
-/*-----------------------------------------------------------------------* \
-
- MAIN
-
-\*-----------------------------------------------------------------------*/
-
-int main(int argc, char *argv[]) {
- int d,e; /* dimension and codebook size */
- COMP *vec; /* current vector */
- COMP *cb; /* vector codebook */
- COMP *cent; /* centroids for each codebook entry */
- int *n; /* number of vectors in this interval */
- int J; /* number of vectors in training set */
- int ind; /* index of current vector */
- float se; /* total squared error for this iteration */
- float var; /* variance */
- float var_1; /* previous variance */
- float delta; /* improvement in distortion */
- FILE *ftrain; /* file containing training set */
- FILE *fvq; /* file containing vector quantiser */
- int ret;
- int i,j, finished, iterations;
- float b; /* equivalent number of bits */
- float improvement;
- float sd_vec, sd_element, sd_theory, bits_theory;
- int var_n;
-
- /* Interpret command line arguments */
-
- if (argc != 5) {
- printf("usage: %s TrainFile D(dimension) E(number of entries) VQFile\n", argv[0]);
- exit(1);
- }
-
- /* Open training file */
-
- ftrain = fopen(argv[1],"rb");
- if (ftrain == NULL) {
- printf("Error opening training database file: %s\n",argv[1]);
- exit(1);
- }
-
- /* determine k and m, and allocate arrays */
-
- d = atoi(argv[2]);
- e = atoi(argv[3]);
- printf("\n");
- printf("dimension D=%d number of entries E=%d\n", d, e);
- vec = (COMP*)malloc(sizeof(COMP)*d);
- cb = (COMP*)malloc(sizeof(COMP)*d*e);
- cent = (COMP*)malloc(sizeof(COMP)*d*e);
- n = (int*)malloc(sizeof(int)*e);
- if (cb == NULL || cb == NULL || cent == NULL || vec == NULL) {
- printf("Error in malloc.\n");
- exit(1);
- }
-
- /* determine size of training set */
-
- J = 0;
- var_n = 0;
- while(fread(vec, sizeof(COMP), d, ftrain) == (size_t)d) {
- for(j=0; j<d; j++)
- if ((vec[j].real != 0.0) && (vec[j].imag != 0.0))
- var_n++;
- J++;
- }
- printf("J=%d sparse vectors in training set, %d non-zero phases\n", J, var_n);
-
- /* set up initial codebook state from samples of training set */
-
- rewind(ftrain);
- ret = fread(cb, sizeof(COMP), d*e, ftrain);
-
- /* codebook can't have any zero phase angle entries, these need to be set to
- zero angle so cmult used to find phase angle differences works */
-
- for(i=0; i<d*e; i++)
- if ((cb[i].real == 0.0) && (cb[i].imag == 0.0)) {
- cb[i].real = 1.0;
- cb[i].imag = 0.0;
- }
-
- //print_vec(cb, d, 1);
-
- /* main loop */
-
- printf("\n");
- printf("Iteration delta var std dev\n");
- printf("--------------------------------\n");
-
- b = log10((float)e)/log10(2.0);
- sd_theory = (PI/sqrt(3.0))*pow(2.0, -b/(float)d);
-
- iterations = 0;
- finished = 0;
- delta = 0;
- var_1 = 0.0;
-
- do {
- /* zero centroids */
-
- for(i=0; i<e; i++) {
- zero(¢[i*d], d);
- n[i] = 0;
- }
-
- /* quantise training set */
-
- se = 0.0;
- rewind(ftrain);
- for(i=0; i<J; i++) {
- ret = fread(vec, sizeof(COMP), d, ftrain);
- ind = quantise(cb, vec, d, e, &se);
- //printf("%d ", ind);
- n[ind]++;
- acc(¢[ind*d], vec, d);
- }
-
- /* work out stats */
-
- var = se/var_n;
- sd_vec = sqrt(var);
-
- /* we need to know dimension of cb (which varies from vector to vector)
- to calc bits_theory. Maybe measure and use average dimension....
- */
- //bits_theory = d*log10(PI/(sd_element*sqrt(3.0)))/log10(2.0);
- //improvement = bits_theory - b;
-
- //print_vec(cent, d, 1);
-
- //print_vec(cb, d, 1);
-
- iterations++;
- if (iterations > 1) {
- if (var > 0.0) {
- delta = (var_1 - var)/var;
- }
- else
- delta = 0;
- if (delta < DELTAQ)
- finished = 1;
- }
-
- if (!finished) {
- /* determine new codebook from centroids */
-
- for(i=0; i<e; i++) {
- norm(¢[i*d], d);
- memcpy(&cb[i*d], ¢[i*d], d*sizeof(COMP));
- }
- }
-
- printf("%2d %4.3f %4.3f %4.3f \n",iterations, delta, var, sd_vec);
-
- var_1 = var;
- } while (!finished);
-
-
- //print_vec(cb, d, 1);
-
- /* save codebook to disk */
-
- fvq = fopen(argv[4],"wt");
- if (fvq == NULL) {
- printf("Error opening VQ file: %s\n",argv[4]);
- exit(1);
- }
-
- fprintf(fvq,"%d %d\n",d,e);
- for(j=0; j<e; j++) {
- for(i=0; i<d; i++)
- fprintf(fvq,"% 4.3f ", atan2(cb[j*d+i].imag, cb[j*d+i].real));
- fprintf(fvq,"\n");
- }
- fclose(fvq);
-
- return 0;
-}
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*-----------------------------------------------------------------------*/
-
-void print_vec(COMP cb[], int d, int e)
-{
- int i,j;
-
- for(j=0; j<e; j++) {
- for(i=0; i<d; i++)
- printf("%f %f ", cb[j*d+i].real, cb[j*d+i].imag);
- printf("\n");
- }
-}
-
-
-static COMP cconj(COMP a)
-{
- COMP res;
-
- res.real = a.real;
- res.imag = -a.imag;
-
- return res;
-}
-
-static COMP cmult(COMP a, COMP b)
-{
- COMP res;
-
- res.real = a.real*b.real - a.imag*b.imag;
- res.imag = a.real*b.imag + a.imag*b.real;
-
- return res;
-}
-
-static COMP cadd(COMP a, COMP b)
-{
- COMP res;
-
- res.real = a.real + b.real;
- res.imag = a.imag + b.imag;
-
- return res;
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: zero()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Zeros a vector of length d.
-
-\*---------------------------------------------------------------------------*/
-
-void zero(COMP v[], int d)
-{
- int i;
-
- for(i=0; i<d; i++) {
- v[i].real = 0.0;
- v[i].imag = 0.0;
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: acc()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Adds d dimensional vectors v1 to v2 and stores the result back
- in v1. We add them like vectors on the complex plane, summing
- the real and imag terms.
-
- An unused entry in a sparse vector has both the real and imag
- parts set to zero so won't affect the accumulation process.
-
-\*---------------------------------------------------------------------------*/
-
-void acc(COMP v1[], COMP v2[], int d)
-{
- int i;
-
- for(i=0; i<d; i++)
- v1[i] = cadd(v1[i], v2[i]);
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: norm()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Normalises each element in d dimensional vector.
-
-\*---------------------------------------------------------------------------*/
-
-void norm(COMP v[], int d)
-{
- int i;
- float mag;
-
- for(i=0; i<d; i++) {
- mag = sqrt(v[i].real*v[i].real + v[i].imag*v[i].imag);
- if (mag == 0.0) {
- /* can't have zero cb entries as cmult will break in quantise().
- We effectively set sparese phases to an angle of 0. */
- v[i].real = 1.0;
- v[i].imag = 0.0;
- }
- else {
- v[i].real /= mag;
- v[i].imag /= mag;
- }
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: quantise()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Quantises vec by choosing the nearest vector in codebook cb, and
- returns the vector index. The squared error of the quantised vector
- is added to se.
-
- Unused entries in sparse vectors are ignored.
-
-\*---------------------------------------------------------------------------*/
-
-int quantise(COMP cb[], COMP vec[], int d, int e, float *se)
-{
- float error; /* current error */
- int besti; /* best index so far */
- float best_error; /* best error so far */
- int i,j;
- int ignore;
- COMP diff;
-
- besti = 0;
- best_error = 1E32;
- for(j=0; j<e; j++) {
- error = 0.0;
- for(i=0; i<d; i++) {
- ignore = (vec[i].real == 0.0) && (vec[i].imag == 0.0);
- if (!ignore) {
- diff = cmult(cb[j*d+i], cconj(vec[i]));
- error += pow(atan2(diff.imag, diff.real), 2.0);
- }
- }
- if (error < best_error) {
- best_error = error;
- besti = j;
- }
- }
-
- *se += best_error;
-
- return(besti);
-}
-
+++ /dev/null
-/*--------------------------------------------------------------------------*\
-
- FILE........: vqtrainsp.c
- AUTHOR......: David Rowe
- DATE CREATED: 7 August 2012
-
- This program trains sparse amplitude vector quantisers.
- Modified from vqtrainph.c
-
-\*--------------------------------------------------------------------------*/
-
-/*
- Copyright (C) 2012 David Rowe
-
- All rights reserved.
-
- This program is free software; you can redistribute it and/or modify
- it under the terms of the GNU Lesser General Public License version 2, as
- published by the Free Software Foundation. This program is
- distributed in the hope that it will be useful, but WITHOUT ANY
- WARRANTY; without even the implied warranty of MERCHANTABILITY or
- FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
- License for more details.
-
- You should have received a copy of the GNU Lesser General Public License
- along with this program; if not, see <http://www.gnu.org/licenses/>.
-*/
-
-/*-----------------------------------------------------------------------*\
-
- INCLUDES
-
-\*-----------------------------------------------------------------------*/
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <string.h>
-#include <math.h>
-#include <ctype.h>
-#include <assert.h>
-
-typedef struct {
- float real;
- float imag;
-} COMP;
-
-/*-----------------------------------------------------------------------* \
-
- DEFINES
-
-\*-----------------------------------------------------------------------*/
-
-#define DELTAQ 0.01 /* quiting distortion */
-#define MAX_STR 80 /* maximum string length */
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTION PROTOTYPES
-
-\*-----------------------------------------------------------------------*/
-
-void zero(float v[], int d);
-void acc(float v1[], float v2[], int d);
-void norm(float v[], int k, int n[]);
-int quantise(float cb[], float vec[], int d, int e, float *se);
-void print_vec(float cb[], int d, int e);
-void split(float cb[], int d, int b);
-int gain_shape_quantise(float cb[], float vec[], int d, int e, float *se, float *best_gain);
-
-/*-----------------------------------------------------------------------* \
-
- MAIN
-
-\*-----------------------------------------------------------------------*/
-
-int main(int argc, char *argv[]) {
- int d,e; /* dimension and codebook size */
- float *vec; /* current vector */
- float *cb; /* vector codebook */
- float *cent; /* centroids for each codebook entry */
- int *n; /* number of vectors in this interval */
- int J; /* number of vectors in training set */
- int ind; /* index of current vector */
- float se; /* total squared error for this iteration */
- float var; /* variance */
- float var_1; /* previous variance */
- float delta; /* improvement in distortion */
- FILE *ftrain; /* file containing training set */
- FILE *fvq; /* file containing vector quantiser */
- int ret;
- int i,j, finished, iterations;
- float sd;
- int var_n, bits, b, levels;
-
- /* Interpret command line arguments */
-
- if (argc < 5) {
- printf("usage: %s TrainFile D(dimension) B(number of bits) VQFile [error.txt file]\n", argv[0]);
- exit(1);
- }
-
- /* Open training file */
-
- ftrain = fopen(argv[1],"rb");
- if (ftrain == NULL) {
- printf("Error opening training database file: %s\n",argv[1]);
- exit(1);
- }
-
- /* determine k and m, and allocate arrays */
-
- d = atoi(argv[2]);
- bits = atoi(argv[3]);
- e = 1<<bits;
- printf("\n");
- printf("dimension D=%d number of bits B=%d entries E=%d\n", d, bits, e);
- vec = (float*)malloc(sizeof(float)*d);
- cb = (float*)malloc(sizeof(float)*d*e);
- cent = (float*)malloc(sizeof(float)*d*e);
- n = (int*)malloc(sizeof(int)*d*e);
- if (cb == NULL || cb == NULL || cent == NULL || vec == NULL) {
- printf("Error in malloc.\n");
- exit(1);
- }
-
- /* determine size of training set */
-
- J = 0;
- var_n = 0;
- while(fread(vec, sizeof(float), d, ftrain) == (size_t)d) {
- for(j=0; j<d; j++)
- if (vec[j] != 0.0)
- var_n++;
- J++;
- }
- printf("J=%d sparse vectors in training set, %d non-zero values\n", J, var_n);
-
- /* set up initial codebook from centroid of training set */
-
- //#define DBG
-
- zero(cent, d);
- for(j=0; j<d; j++)
- n[j] = 0;
- rewind(ftrain);
- #ifdef DBG
- printf("initial codebook...\n");
- #endif
- for(i=0; i<J; i++) {
- ret = fread(vec, sizeof(float), d, ftrain);
- #ifdef DBG
- print_vec(vec, d, 1);
- #endif
- acc(cent, vec, d);
- for(j=0; j<d; j++)
- if (vec[j] != 0.0)
- n[j]++;
- }
- norm(cent, d, n);
- memcpy(cb, cent, d*sizeof(float));
- #ifdef DBG
- printf("\n");
- print_vec(cb, d, 1);
- #endif
-
- /* main loop */
-
- printf("\n");
- printf("bits Iteration delta var std dev\n");
- printf("---------------------------------------\n");
-
- for(b=1; b<=bits; b++) {
- levels = 1<<b;
- iterations = 0;
- finished = 0;
- delta = 0;
- var_1 = 0.0;
-
- split(cb, d, levels/2);
- //print_vec(cb, d, levels);
-
- do {
- /* zero centroids */
-
- for(i=0; i<levels; i++) {
- zero(¢[i*d], d);
- for(j=0; j<d; j++)
- n[i*d+j] = 0;
- }
-
- //#define DBG
- #ifdef DBG
- printf("cb...\n");
- print_vec(cb, d, levels);
- printf("\n\nquantise...\n");
- #endif
-
- /* quantise training set */
-
- se = 0.0;
- rewind(ftrain);
- for(i=0; i<J; i++) {
- ret = fread(vec, sizeof(float), d, ftrain);
- ind = quantise(cb, vec, d, levels, &se);
- //ind = gain_shape_quantise(cb, vec, d, levels, &se, &best_gain);
- //for(j=0; j<d; j++)
- // if (vec[j] != 0.0)
- // vec[j] += best_gain;
- #ifdef DBG
- print_vec(vec, d, 1);
- printf(" ind %d se: %f\n", ind, se);
- #endif
- acc(¢[ind*d], vec, d);
- for(j=0; j<d; j++)
- if (vec[j] != 0.0)
- n[ind*d+j]++;
- }
-
- #ifdef DBG
- printf("cent...\n");
- print_vec(cent, d, e);
- printf("\n");
- #endif
-
- /* work out stats */
-
- var = se/var_n;
- sd = sqrt(var);
-
- iterations++;
- if (iterations > 1) {
- if (var > 0.0) {
- delta = (var_1 - var)/var;
- }
- else
- delta = 0;
- if (delta < DELTAQ)
- finished = 1;
- }
-
- if (!finished) {
- /* determine new codebook from centroids */
-
- for(i=0; i<levels; i++) {
- norm(¢[i*d], d, &n[i*d]);
- memcpy(&cb[i*d], ¢[i*d], d*sizeof(float));
- }
- }
-
- #ifdef DBG
- printf("new cb ...\n");
- print_vec(cent, d, e);
- printf("\n");
- #endif
-
- printf("%2d %2d %4.3f %6.3f %4.3f\r",b,iterations, delta, var, sd);
- fflush(stdout);
-
- var_1 = var;
- } while (!finished);
- printf("\n");
- }
-
-
- //print_vec(cb, d, 1);
-
- /* save codebook to disk */
-
- fvq = fopen(argv[4],"wt");
- if (fvq == NULL) {
- printf("Error opening VQ file: %s\n",argv[4]);
- exit(1);
- }
-
- fprintf(fvq,"%d %d\n",d,e);
- for(j=0; j<e; j++) {
- for(i=0; i<d; i++)
- fprintf(fvq,"% 7.3f ", cb[j*d+i]);
- fprintf(fvq,"\n");
- }
- fclose(fvq);
-
- /* optionally dump error file for multi-stage work */
-
- if (argc == 6) {
- FILE *ferr = fopen(argv[5],"wt");
- assert(ferr != NULL);
- rewind(ftrain);
- for(i=0; i<J; i++) {
- ret = fread(vec, sizeof(float), d, ftrain);
- ind = quantise(cb, vec, d, levels, &se);
- for(j=0; j<d; j++) {
- if (vec[j] != 0.0)
- vec[j] -= cb[ind*d+j];
- fprintf(ferr, "%f ", vec[j]);
- }
- fprintf(ferr, "\n");
- }
- }
-
- return 0;
-}
-
-/*-----------------------------------------------------------------------*\
-
- FUNCTIONS
-
-\*-----------------------------------------------------------------------*/
-
-void print_vec(float cb[], int d, int e)
-{
- int i,j;
-
- for(j=0; j<e; j++) {
- printf(" ");
- for(i=0; i<d; i++)
- printf("% 7.3f ", cb[j*d+i]);
- printf("\n");
- }
-}
-
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: zero()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Zeros a vector of length d.
-
-\*---------------------------------------------------------------------------*/
-
-void zero(float v[], int d)
-{
- int i;
-
- for(i=0; i<d; i++) {
- v[i] = 0.0;
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: acc()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Adds d dimensional vectors v1 to v2 and stores the result back
- in v1.
-
- An unused entry in a sparse vector is set to zero so won't
- affect the accumulation process.
-
-\*---------------------------------------------------------------------------*/
-
-void acc(float v1[], float v2[], int d)
-{
- int i;
-
- for(i=0; i<d; i++)
- v1[i] += v2[i];
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: norm()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Normalises each element in d dimensional vector.
-
-\*---------------------------------------------------------------------------*/
-
-void norm(float v[], int d, int n[])
-{
- int i;
-
- for(i=0; i<d; i++) {
- if (n[i] != 0)
- v[i] /= n[i];
- }
-}
-
-/*---------------------------------------------------------------------------*\
-
- FUNCTION....: quantise()
-
- AUTHOR......: David Rowe
- DATE CREATED: 23/2/95
-
- Quantises vec by choosing the nearest vector in codebook cb, and
- returns the vector index. The squared error of the quantised vector
- is added to se.
-
- Unused entries in sparse vectors are ignored.
-
-\*---------------------------------------------------------------------------*/
-
-int quantise(float cb[], float vec[], int d, int e, float *se)
-{
- float error; /* current error */
- int besti; /* best index so far */
- float best_error; /* best error so far */
- int i,j;
- float diff;
-
- besti = 0;
- best_error = 1E32;
- for(j=0; j<e; j++) {
- error = 0.0;
- for(i=0; i<d; i++) {
- if (vec[i] != 0.0) {
- diff = cb[j*d+i] - vec[i];
- error += diff*diff;
- }
- }
- if (error < best_error) {
- best_error = error;
- besti = j;
- }
- }
-
- *se += best_error;
-
- return(besti);
-}
-
-int gain_shape_quantise(float cb[], float vec[], int d, int e, float *se, float *best_gain)
-{
- float error; /* current error */
- int besti; /* best index so far */
- float best_error; /* best error so far */
- int i,j,m;
- float diff, metric, best_metric, gain, sumAm, sumCb;
-
- besti = 0;
- best_metric = best_error = 1E32;
- for(j=0; j<e; j++) {
-
- /* compute optimum gain */
-
- sumAm = sumCb = 0.0;
- m = 0;
- for(i=0; i<d; i++) {
- if (vec[i] != 0.0) {
- m++;
- sumAm += vec[i];
- sumCb += cb[j*d+i];
- }
- }
- gain = (sumAm - sumCb)/m;
-
- /* compute error */
-
- metric = error = 0.0;
- for(i=0; i<d; i++) {
- if (vec[i] != 0.0) {
- diff = vec[i] - cb[j*d+i] - gain;
- error += diff*diff;
- metric += diff*diff;
- }
- }
- if (metric < best_metric) {
- best_error = error;
- best_metric = metric;
- *best_gain = gain;
- besti = j;
- }
- }
-
- *se += best_error;
-
- return(besti);
-}
-
-void split(float cb[], int d, int levels)
-{
- int i,j;
-
- for (i=0;i<levels;i++) {
- for (j=0;j<d;j++) {
- float delta = .01*(rand()/(float)RAND_MAX-.5);
- cb[i*d+j] += delta;
- cb[(i+levels)*d+j] = cb[i*d+j] - delta;
- }
- }
-}
-
+++ /dev/null
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
+++ /dev/null
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
+++ /dev/null
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
+++ /dev/null
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-1
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
-0
--- /dev/null
+<?xml version="1.0" encoding="utf-8"?>
+<Project DefaultTargets="Build" ToolsVersion="14.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+ <ItemGroup Label="ProjectConfigurations">
+ <ProjectConfiguration Include="Debug|Win32">
+ <Configuration>Debug</Configuration>
+ <Platform>Win32</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Release|Win32">
+ <Configuration>Release</Configuration>
+ <Platform>Win32</Platform>
+ </ProjectConfiguration>
+ </ItemGroup>
+ <PropertyGroup Label="Globals">
+ <ProjectName>Download libcodec2</ProjectName>
+ <RootNamespace>Download libcodec2</RootNamespace>
+ <Keyword>Win32Proj</Keyword>
+ <ProjectGuid>{9CFA562C-C611-48A7-90A2-BB031B47FE6D}</ProjectGuid>
+ </PropertyGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
+ <ConfigurationType>Utility</ConfigurationType>
+ <CharacterSet>MultiByte</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
+ <ConfigurationType>Utility</ConfigurationType>
+ <CharacterSet>MultiByte</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
+ <Import Project="$(SolutionDir)\w32\extdll.props" />
+ <ImportGroup Label="ExtensionSettings">
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="..\..\w32\libcodec2.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="..\..\w32\libcodec2.props" />
+ </ImportGroup>
+ <PropertyGroup Label="UserMacros" />
+ <PropertyGroup>
+ <_ProjectFileVersion>10.0.30319.1</_ProjectFileVersion>
+ <IntDir Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">$(PlatformName)\libcodec2\$(Configuration)\</IntDir>
+ <IntDir Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">$(PlatformName)\libcodec2\$(Configuration)\</IntDir>
+ </PropertyGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+ <BuildLog>
+ <Path>$(IntDir)BuildLog $(ProjectName).htm</Path>
+ </BuildLog>
+ <PreBuildEvent>
+ <Command>
+ </Command>
+ </PreBuildEvent>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+ <BuildLog>
+ <Path>$(IntDir)BuildLog $(ProjectName).htm</Path>
+ </BuildLog>
+ <PreBuildEvent>
+ <Command>
+ </Command>
+ </PreBuildEvent>
+ </ItemDefinitionGroup>
+ <ItemGroup>
+ <CustomBuild Include="cleancount">
+ <FileType>Document</FileType>
+ <Message Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">Downloading libcodec2.</Message>
+ <Command Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">if not exist "$(libcodec2LibDir)" cscript /nologo "$(ProjectDir)util.vbs" GetUnzip http://files.freeswitch.org/downloads/libs/libcodec2-$(libcodec2_Version).tar.gz "$(ProjectDir).."
+</Command>
+ <Outputs Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">$(libcodec2LibDir);%(Outputs)</Outputs>
+ <Message Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">Downloading libcodec2.</Message>
+ <Command Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">if not exist "$(libcodec2LibDir)" cscript /nologo "$(ProjectDir)util.vbs" GetUnzip http://files.freeswitch.org/downloads/libs/libcodec2-$(libcodec2_Version).tar.gz "$(ProjectDir).."
+</Command>
+ <Outputs Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">$(libcodec2LibDir);%(Outputs)</Outputs>
+ </CustomBuild>
+ </ItemGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
+ <ImportGroup Label="ExtensionTargets">
+ </ImportGroup>
+</Project>
\ No newline at end of file
--- /dev/null
+REM
+REM In order to regenerate headers
+REM execute this generate.bat from the "VS2015 x86 Native Tools Command Prompt"
+REM
+
+cd ../../libcodec2-2.59/src
+cl /EHsc generate_codebook.c
+generate_codebook.exe lsp_cb codebook/lsp1.txt codebook/lsp2.txt codebook/lsp3.txt codebook/lsp4.txt codebook/lsp5.txt codebook/lsp6.txt codebook/lsp7.txt codebook/lsp8.txt codebook/lsp9.txt codebook/lsp10.txt > codebook.c
+generate_codebook.exe lsp_cbd codebook/dlsp1.txt codebook/dlsp2.txt codebook/dlsp3.txt codebook/dlsp4.txt codebook/dlsp5.txt codebook/dlsp6.txt codebook/dlsp7.txt codebook/dlsp8.txt codebook/dlsp9.txt codebook/dlsp10.txt > codebookd.c
+generate_codebook.exe lsp_cbdt codebook/lspdt1.txt codebook/lspdt2.txt codebook/lspdt3.txt codebook/lspdt4.txt codebook/lspdt5.txt codebook/lspdt6.txt codebook/lspdt7.txt codebook/lspdt8.txt codebook/lspdt9.txt codebook/lspdt10.txt > codebookdt.c
+generate_codebook.exe lsp_cbvq codebook/lsp1.txt codebook/lsp2.txt codebook/lsp3.txt codebook/lsp4.txt ../unittest/lsp45678910.txt > codebookvq.c
+generate_codebook.exe lsp_cbjnd codebook/lsp1.txt codebook/lsp2.txt codebook/lsp3.txt codebook/lsp4.txt ../unittest/lspjnd5-10.txt > codebookjnd.c
+generate_codebook.exe lsp_cbjvm codebook/lspjvm1.txt codebook/lspjvm2.txt codebook/lspjvm3.txt > codebookjvm.c
+generate_codebook.exe lsp_cbvqanssi codebook/lspvqanssi1.txt codebook/lspvqanssi2.txt codebook/lspvqanssi3.txt codebook/lspvqanssi4.txt > codebookvqanssi.c
+generate_codebook.exe ge_cb codebook/gecb.txt > codebookge.c
\ No newline at end of file
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/lsp1.txt */
+static const float codes0[] = {
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600
+};
+ /* codebook/lsp2.txt */
+static const float codes1[] = {
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700
+};
+ /* codebook/lsp3.txt */
+static const float codes2[] = {
+ 500,
+ 550,
+ 600,
+ 650,
+ 700,
+ 750,
+ 800,
+ 850,
+ 900,
+ 950,
+ 1000,
+ 1050,
+ 1100,
+ 1150,
+ 1200,
+ 1250
+};
+ /* codebook/lsp4.txt */
+static const float codes3[] = {
+ 700,
+ 800,
+ 900,
+ 1000,
+ 1100,
+ 1200,
+ 1300,
+ 1400,
+ 1500,
+ 1600,
+ 1700,
+ 1800,
+ 1900,
+ 2000,
+ 2100,
+ 2200
+};
+ /* codebook/lsp5.txt */
+static const float codes4[] = {
+ 950,
+ 1050,
+ 1150,
+ 1250,
+ 1350,
+ 1450,
+ 1550,
+ 1650,
+ 1750,
+ 1850,
+ 1950,
+ 2050,
+ 2150,
+ 2250,
+ 2350,
+ 2450
+};
+ /* codebook/lsp6.txt */
+static const float codes5[] = {
+ 1100,
+ 1200,
+ 1300,
+ 1400,
+ 1500,
+ 1600,
+ 1700,
+ 1800,
+ 1900,
+ 2000,
+ 2100,
+ 2200,
+ 2300,
+ 2400,
+ 2500,
+ 2600
+};
+ /* codebook/lsp7.txt */
+static const float codes6[] = {
+ 1500,
+ 1600,
+ 1700,
+ 1800,
+ 1900,
+ 2000,
+ 2100,
+ 2200,
+ 2300,
+ 2400,
+ 2500,
+ 2600,
+ 2700,
+ 2800,
+ 2900,
+ 3000
+};
+ /* codebook/lsp8.txt */
+static const float codes7[] = {
+ 2300,
+ 2400,
+ 2500,
+ 2600,
+ 2700,
+ 2800,
+ 2900,
+ 3000
+};
+ /* codebook/lsp9.txt */
+static const float codes8[] = {
+ 2500,
+ 2600,
+ 2700,
+ 2800,
+ 2900,
+ 3000,
+ 3100,
+ 3200
+};
+ /* codebook/lsp10.txt */
+static const float codes9[] = {
+ 2900,
+ 3100,
+ 3300,
+ 3500
+};
+
+const struct lsp_codebook lsp_cb[] = {
+ /* codebook/lsp1.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes0
+ },
+ /* codebook/lsp2.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes1
+ },
+ /* codebook/lsp3.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes2
+ },
+ /* codebook/lsp4.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes3
+ },
+ /* codebook/lsp5.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes4
+ },
+ /* codebook/lsp6.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes5
+ },
+ /* codebook/lsp7.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes6
+ },
+ /* codebook/lsp8.txt */
+ {
+ 1,
+ 3,
+ 8,
+ codes7
+ },
+ /* codebook/lsp9.txt */
+ {
+ 1,
+ 3,
+ 8,
+ codes8
+ },
+ /* codebook/lsp10.txt */
+ {
+ 1,
+ 2,
+ 4,
+ codes9
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/dlsp1.txt */
+static const float codes0[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+ /* codebook/dlsp2.txt */
+static const float codes1[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+ /* codebook/dlsp3.txt */
+static const float codes2[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+ /* codebook/dlsp4.txt */
+static const float codes3[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 250,
+ 300,
+ 350,
+ 400,
+ 450,
+ 500,
+ 550,
+ 600,
+ 650,
+ 700,
+ 750,
+ 800,
+ 850,
+ 900,
+ 950,
+ 1000,
+ 1050,
+ 1100,
+ 1150,
+ 1200,
+ 1250,
+ 1300,
+ 1350,
+ 1400
+};
+ /* codebook/dlsp5.txt */
+static const float codes4[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 250,
+ 300,
+ 350,
+ 400,
+ 450,
+ 500,
+ 550,
+ 600,
+ 650,
+ 700,
+ 750,
+ 800,
+ 850,
+ 900,
+ 950,
+ 1000,
+ 1050,
+ 1100,
+ 1150,
+ 1200,
+ 1250,
+ 1300,
+ 1350,
+ 1400
+};
+ /* codebook/dlsp6.txt */
+static const float codes5[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 250,
+ 300,
+ 350,
+ 400,
+ 450,
+ 500,
+ 550,
+ 600,
+ 650,
+ 700,
+ 750,
+ 800,
+ 850,
+ 900,
+ 950,
+ 1000,
+ 1050,
+ 1100,
+ 1150,
+ 1200,
+ 1250,
+ 1300,
+ 1350,
+ 1400
+};
+ /* codebook/dlsp7.txt */
+static const float codes6[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+ /* codebook/dlsp8.txt */
+static const float codes7[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+ /* codebook/dlsp9.txt */
+static const float codes8[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+ /* codebook/dlsp10.txt */
+static const float codes9[] = {
+ 25,
+ 50,
+ 75,
+ 100,
+ 125,
+ 150,
+ 175,
+ 200,
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700,
+ 725,
+ 750,
+ 775,
+ 800
+};
+
+const struct lsp_codebook lsp_cbd[] = {
+ /* codebook/dlsp1.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes0
+ },
+ /* codebook/dlsp2.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes1
+ },
+ /* codebook/dlsp3.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes2
+ },
+ /* codebook/dlsp4.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes3
+ },
+ /* codebook/dlsp5.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes4
+ },
+ /* codebook/dlsp6.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes5
+ },
+ /* codebook/dlsp7.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes6
+ },
+ /* codebook/dlsp8.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes7
+ },
+ /* codebook/dlsp9.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes8
+ },
+ /* codebook/dlsp10.txt */
+ {
+ 1,
+ 5,
+ 32,
+ codes9
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/lspdt1.txt */
+static const float codes0[] = {
+ -75,
+ -50,
+ -25,
+ 0,
+ 25,
+ 50,
+ 75,
+ 100
+};
+ /* codebook/lspdt2.txt */
+static const float codes1[] = {
+ -75,
+ -50,
+ -25,
+ 0,
+ 25,
+ 50,
+ 75,
+ 100
+};
+ /* codebook/lspdt3.txt */
+static const float codes2[] = {
+ -50,
+ 0,
+ 50,
+ 100
+};
+ /* codebook/lspdt4.txt */
+static const float codes3[] = {
+ -50,
+ 0,
+ 50,
+ 100
+};
+ /* codebook/lspdt5.txt */
+static const float codes4[] = {
+ -50,
+ 0,
+ 50,
+ 100
+};
+ /* codebook/lspdt6.txt */
+static const float codes5[] = {
+ -50,
+ 0,
+ 50,
+ 100
+};
+ /* codebook/lspdt7.txt */
+static const float codes6[] = {
+ -50,
+ 50
+};
+ /* codebook/lspdt8.txt */
+static const float codes7[] = {
+ -50,
+ 50
+};
+ /* codebook/lspdt9.txt */
+static const float codes8[] = {
+ -50,
+ 50
+};
+ /* codebook/lspdt10.txt */
+static const float codes9[] = {
+ -50,
+ 50
+};
+
+const struct lsp_codebook lsp_cbdt[] = {
+ /* codebook/lspdt1.txt */
+ {
+ 1,
+ 3,
+ 8,
+ codes0
+ },
+ /* codebook/lspdt2.txt */
+ {
+ 1,
+ 3,
+ 8,
+ codes1
+ },
+ /* codebook/lspdt3.txt */
+ {
+ 1,
+ 2,
+ 4,
+ codes2
+ },
+ /* codebook/lspdt4.txt */
+ {
+ 1,
+ 2,
+ 4,
+ codes3
+ },
+ /* codebook/lspdt5.txt */
+ {
+ 1,
+ 2,
+ 4,
+ codes4
+ },
+ /* codebook/lspdt6.txt */
+ {
+ 1,
+ 2,
+ 4,
+ codes5
+ },
+ /* codebook/lspdt7.txt */
+ {
+ 1,
+ 1,
+ 2,
+ codes6
+ },
+ /* codebook/lspdt8.txt */
+ {
+ 1,
+ 1,
+ 2,
+ codes7
+ },
+ /* codebook/lspdt9.txt */
+ {
+ 1,
+ 1,
+ 2,
+ codes8
+ },
+ /* codebook/lspdt10.txt */
+ {
+ 1,
+ 1,
+ 2,
+ codes9
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/gecb.txt */
+static const float codes0[] = {
+ 2.71, 12.0184,
+ 0.04675, -2.73881,
+ 0.120993, 8.38895,
+ -1.58028, -0.892307,
+ 1.19307, -1.91561,
+ 0.187101, -3.27679,
+ 0.332251, -7.66455,
+ -1.47944, 31.2461,
+ 1.52761, 27.7095,
+ -0.524379, 5.25012,
+ 0.55333, 7.4388,
+ -0.843451, -1.95299,
+ 2.26389, 8.61029,
+ 0.143143, 2.36549,
+ 0.616506, 1.28427,
+ -1.71133, 22.0967,
+ 1.00813, 17.3965,
+ -0.106718, 1.41891,
+ -0.136246, 14.2736,
+ -1.70909, -20.5319,
+ 1.65787, -3.39107,
+ 0.138049, -4.95785,
+ 0.536729, -1.94375,
+ 0.196307, 36.8519,
+ 1.27248, 22.5565,
+ -0.670219, -1.90604,
+ 0.382092, 6.40113,
+ -0.756911, -4.90102,
+ 1.82931, 4.6138,
+ 0.318794, 0.73683,
+ 0.612815, -2.07505,
+ -0.410151, 24.7871,
+ 1.77602, 13.1909,
+ 0.106457, -0.104492,
+ 0.192206, 10.1838,
+ -1.82442, -7.71565,
+ 0.931346, 4.34835,
+ 0.308813, -4.086,
+ 0.397143, -11.8089,
+ -0.048715, 41.2273,
+ 0.877342, 35.8503,
+ -0.759794, 0.476634,
+ 0.978593, 7.67467,
+ -1.19506, 3.03883,
+ 2.63989, -3.41106,
+ 0.191127, 3.60351,
+ 0.402932, 1.0843,
+ -2.15202, 18.1076,
+ 1.5468, 8.32271,
+ -0.143089, -4.07592,
+ -0.150142, 5.86674,
+ -1.40844, -3.2507,
+ 1.56615, -10.4132,
+ 0.178171, -10.2267,
+ 0.362164, -0.028556,
+ -0.070125, 24.3907,
+ 0.594752, 17.4828,
+ -0.28698, -6.90407,
+ 0.464818, 10.2055,
+ -1.00684, -14.3572,
+ 2.32957, -3.69161,
+ 0.335745, 2.40714,
+ 1.01966, -3.15565,
+ -1.25945, 7.9919,
+ 2.38369, 19.6806,
+ -0.094947, -2.41374,
+ 0.20933, 6.66477,
+ -2.22103, 1.37986,
+ 1.29239, 2.04633,
+ 0.243626, -0.890741,
+ 0.428773, -7.19366,
+ -1.11374, 41.3414,
+ 2.6098, 31.1405,
+ -0.446468, 2.53419,
+ 0.490104, 4.62757,
+ -1.11723, -3.24174,
+ 1.79156, 8.41493,
+ 0.156012, 0.183336,
+ 0.532447, 3.15455,
+ -0.764484, 18.514,
+ 0.952395, 11.7713,
+ -0.332567, 0.346987,
+ 0.202165, 14.7168,
+ -2.12924, -15.559,
+ 1.35358, -1.92679,
+ -0.010963, -16.3364,
+ 0.399053, -2.79057,
+ 0.750657, 31.1483,
+ 0.655743, 24.4819,
+ -0.45321, -0.735879,
+ 0.2869, 6.5467,
+ -0.715673, -12.3578,
+ 1.54849, 3.87217,
+ 0.271874, 0.802339,
+ 0.502073, -4.85485,
+ -0.497037, 17.7619,
+ 1.19116, 13.9544,
+ 0.01563, 1.33157,
+ 0.341867, 8.93537,
+ -2.31601, -5.39506,
+ 0.75861, 1.9645,
+ 0.24132, -3.23769,
+ 0.267151, -11.2344,
+ -0.273126, 32.6248,
+ 1.75352, 40.432,
+ -0.784011, 3.04576,
+ 0.705987, 5.66118,
+ -1.3864, 1.35356,
+ 2.37646, 1.67485,
+ 0.242973, 4.73218,
+ 0.491227, 0.354061,
+ -1.60676, 8.65895,
+ 1.16711, 5.9871,
+ -0.137601, -12.0417,
+ -0.251375, 10.3972,
+ -1.43151, -8.90411,
+ 0.98828, -13.209,
+ 0.261484, -6.35497,
+ 0.395932, -0.702529,
+ 0.283704, 26.8996,
+ 0.420959, 15.4418,
+ -0.355804, -13.7278,
+ 0.527372, 12.3985,
+ -1.16956, -15.9985,
+ 1.90669, -5.81605,
+ 0.354492, 3.85157,
+ 0.82576, -4.16264,
+ -0.49019, 13.0572,
+ 2.25577, 13.5264,
+ -0.004956, -3.23713,
+ 0.026709, 7.86645,
+ -1.81037, -0.451183,
+ 1.08383, -0.18362,
+ 0.135836, -2.26658,
+ 0.375812, -5.51225,
+ -1.96644, 38.6829,
+ 1.97799, 24.5655,
+ -0.704656, 6.35881,
+ 0.480786, 7.05175,
+ -0.976417, -2.42273,
+ 2.50215, 6.75935,
+ 0.083588, 3.2588,
+ 0.543629, 0.910013,
+ -1.23196, 23.0915,
+ 0.785492, 14.807,
+ -0.213554, 1.688,
+ 0.004748, 18.1718,
+ -1.54719, -16.1168,
+ 1.50104, -3.28114,
+ 0.080133, -4.63472,
+ 0.476592, -2.18093,
+ 0.44247, 40.304,
+ 1.07277, 27.592,
+ -0.594738, -4.16681,
+ 0.42248, 7.61609,
+ -0.927521, -7.27441,
+ 1.99162, 1.29636,
+ 0.291307, 2.39878,
+ 0.721081, -1.95062,
+ -0.804256, 24.9295,
+ 1.64839, 19.1197,
+ 0.060852, -0.590639,
+ 0.266085, 9.10325,
+ -1.9574, -2.88461,
+ 1.11693, 2.6724,
+ 0.35458, -2.74854,
+ 0.330733, -14.1561,
+ -0.527851, 39.5756,
+ 0.991152, 43.195,
+ -0.589619, 1.26919,
+ 0.787401, 8.73071,
+ -1.0138, 1.02507,
+ 2.8254, 1.89538,
+ 0.24089, 2.74557,
+ 0.427195, 2.54446,
+ -1.95311, 12.244,
+ 1.44862, 12.0607,
+ -0.210492, -3.37906,
+ -0.056713, 10.204,
+ -1.65237, -5.10274,
+ 1.29475, -12.2708,
+ 0.111608, -8.67592,
+ 0.326634, -1.16763,
+ 0.021781, 31.1258,
+ 0.455335, 21.4684,
+ -0.37544, -3.37121,
+ 0.39362, 11.302,
+ -0.851456, -19.4149,
+ 2.10703, -2.22886,
+ 0.373233, 1.92406,
+ 0.884438, -1.72058,
+ -0.975127, 9.84013,
+ 2.0033, 17.3954,
+ -0.036915, -1.11137,
+ 0.148456, 5.39997,
+ -1.91441, 4.77382,
+ 1.44791, 0.537122,
+ 0.194979, -1.03818,
+ 0.495771, -9.95502,
+ -1.05899, 32.9471,
+ 2.01122, 32.4544,
+ -0.30965, 4.71911,
+ 0.436082, 4.63552,
+ -1.23711, -1.25428,
+ 2.02274, 9.42834,
+ 0.190342, 1.46077,
+ 0.479017, 2.48479,
+ -1.07848, 16.2217,
+ 1.20764, 9.65421,
+ -0.258087, -1.67236,
+ 0.071852, 13.416,
+ -1.87723, -16.072,
+ 1.28957, -4.87118,
+ 0.067713, -13.4427,
+ 0.435551, -4.1655,
+ 0.46614, 30.5895,
+ 0.904895, 21.598,
+ -0.518369, -2.53205,
+ 0.337363, 5.63726,
+ -0.554975, -17.4005,
+ 1.69188, 1.14574,
+ 0.227934, 0.889297,
+ 0.587303, -5.72973,
+ -0.262133, 18.6666,
+ 1.39505, 17.0029,
+ -0.01909, 4.30838,
+ 0.304235, 12.6699,
+ -2.07406, -6.46084,
+ 0.920546, 1.21296,
+ 0.284927, -1.78547,
+ 0.209724, -16.024,
+ -0.636067, 31.5768,
+ 1.34989, 34.6775,
+ -0.971625, 5.30086,
+ 0.590249, 4.44971,
+ -1.56787, 3.60239,
+ 2.1455, 4.51666,
+ 0.296022, 4.12017,
+ 0.445299, 0.868772,
+ -1.44193, 14.1284,
+ 1.35575, 6.0074,
+ -0.012814, -7.49657,
+ -0.43, 8.50012,
+ -1.20469, -7.11326,
+ 1.10102, -6.83682,
+ 0.196463, -6.234,
+ 0.436747, -1.12979,
+ 0.141052, 22.8549,
+ 0.290821, 18.8114,
+ -0.529536, -7.73251,
+ 0.63428, 10.7898,
+ -1.33472, -20.3258,
+ 1.81564, -1.90332,
+ 0.394778, 3.79758,
+ 0.732682, -8.18382,
+ -0.741244, 11.7683
+};
+
+const struct lsp_codebook ge_cb[] = {
+ /* codebook/gecb.txt */
+ {
+ 2,
+ 8,
+ 256,
+ codes0
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/lsp1.txt */
+static const float codes0[] = {
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600
+};
+ /* codebook/lsp2.txt */
+static const float codes1[] = {
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700
+};
+ /* codebook/lsp3.txt */
+static const float codes2[] = {
+ 500,
+ 550,
+ 600,
+ 650,
+ 700,
+ 750,
+ 800,
+ 850,
+ 900,
+ 950,
+ 1000,
+ 1050,
+ 1100,
+ 1150,
+ 1200,
+ 1250
+};
+ /* codebook/lsp4.txt */
+static const float codes3[] = {
+ 700,
+ 800,
+ 900,
+ 1000,
+ 1100,
+ 1200,
+ 1300,
+ 1400,
+ 1500,
+ 1600,
+ 1700,
+ 1800,
+ 1900,
+ 2000,
+ 2100,
+ 2200
+};
+ /* ../unittest/lspjnd5-10.txt */
+static const float codes4[] = {
+ 1400, 2000, 2400, 2500, 3300, 3400,
+ 1400, 1900, 2400, 2500, 3200, 3400,
+ 1400, 1800, 2400, 2500, 3200, 3300,
+ 1400, 1800, 2400, 2500, 3300, 3400,
+ 1400, 2100, 2400, 2600, 3300, 3400,
+ 1400, 1900, 2300, 2600, 3200, 3300,
+ 1400, 1900, 2100, 2600, 3100, 3200,
+ 1600, 2100, 2400, 2500, 3200, 3300,
+ 1500, 1900, 2300, 2600, 3100, 3200,
+ 1600, 1800, 2400, 2600, 3200, 3300,
+ 1700, 1900, 2300, 2500, 3200, 3300,
+ 1800, 1900, 2300, 2500, 3200, 3300,
+ 1800, 2000, 2300, 2500, 3300, 3400,
+ 1900, 2000, 2200, 2600, 3300, 3400,
+ 1700, 2000, 2700, 2900, 3200, 3300,
+ 1700, 2100, 2600, 2900, 3200, 3300,
+ 1600, 2000, 2500, 2800, 3200, 3400,
+ 1500, 1800, 2300, 2400, 3200, 3300,
+ 1400, 1700, 2200, 2400, 3200, 3300,
+ 1300, 1700, 2200, 2300, 3200, 3300,
+ 1300, 1600, 2200, 2300, 3200, 3300,
+ 1200, 1600, 2200, 2400, 3200, 3300,
+ 1200, 1600, 2200, 2300, 3200, 3300,
+ 1200, 1500, 2200, 2300, 3100, 3300,
+ 1200, 1500, 2200, 2300, 3200, 3300,
+ 1300, 1500, 2100, 2300, 3000, 3200,
+ 1300, 1600, 2000, 2200, 3000, 3200,
+ 1400, 1700, 2000, 2300, 3100, 3200,
+ 1500, 1700, 2000, 2300, 3200, 3300,
+ 1300, 1600, 1900, 2100, 3100, 3200,
+ 1200, 1500, 2100, 2300, 3200, 3300,
+ 1500, 1800, 2000, 2300, 3000, 3200,
+ 1200, 1500, 2200, 2400, 3300, 3400,
+ 1200, 1500, 2200, 2400, 3200, 3400,
+ 1200, 1500, 2200, 2400, 3200, 3300,
+ 1300, 1500, 2300, 2400, 3200, 3300,
+ 1300, 1500, 2200, 2500, 3000, 3200,
+ 1300, 1600, 2300, 2600, 3000, 3200,
+ 1400, 1800, 2400, 2600, 3100, 3200,
+ 1700, 2000, 2500, 2800, 3200, 3300,
+ 1900, 2200, 2600, 2700, 3100, 3200,
+ 1900, 2300, 2600, 2900, 3200, 3300,
+ 2000, 2300, 2600, 2900, 3300, 3400,
+ 1900, 2300, 2500, 2900, 3300, 3400,
+ 1800, 2300, 2500, 2800, 3300, 3400,
+ 1600, 1800, 2400, 2500, 3200, 3400,
+ 1500, 1800, 2400, 2600, 3100, 3400,
+ 1800, 2100, 2600, 2900, 3300, 3500,
+ 2000, 2500, 2700, 3000, 3400, 3500,
+ 2200, 2500, 2700, 3100, 3300, 3400,
+ 2300, 2500, 2700, 3100, 3300, 3400,
+ 2100, 2500, 2600, 3000, 3200, 3300,
+ 2100, 2400, 2500, 3000, 3200, 3300,
+ 1700, 2000, 2300, 2700, 3100, 3200,
+ 1700, 2000, 2300, 2800, 3100, 3300,
+ 1600, 1900, 2200, 2800, 3000, 3200,
+ 1500, 1900, 2100, 2700, 3000, 3200,
+ 1400, 1900, 2000, 2600, 3000, 3100,
+ 1200, 1600, 2100, 2400, 3200, 3300,
+ 1500, 1600, 2300, 2400, 3200, 3400,
+ 1600, 1700, 2200, 2400, 3100, 3400,
+ 1600, 1700, 2200, 2400, 3200, 3400,
+ 1700, 1800, 2300, 2400, 3200, 3400,
+ 1700, 1800, 2300, 2400, 3200, 3300,
+ 1700, 1800, 2300, 2400, 3100, 3200,
+ 1700, 1800, 2200, 2500, 3100, 3200,
+ 1600, 1800, 2100, 2400, 3000, 3100,
+ 1500, 1700, 2100, 2300, 3000, 3100,
+ 1400, 1700, 2100, 2500, 3000, 3200,
+ 1000, 1700, 2300, 2500, 3200, 3300,
+ 1100, 1700, 2400, 2500, 3300, 3400,
+ 1500, 2000, 2300, 2600, 3000, 3300,
+ 1300, 1600, 1800, 2600, 2900, 3100,
+ 1300, 1600, 1900, 2200, 2900, 3000,
+ 1500, 1700, 2200, 2500, 2900, 3000,
+ 1500, 1600, 2100, 2400, 2900, 3100,
+ 1500, 1600, 2000, 2600, 3000, 3100,
+ 1600, 1700, 2100, 2600, 3100, 3200,
+ 1700, 1900, 2100, 2500, 3300, 3400,
+ 1700, 1900, 2200, 2500, 3300, 3400,
+ 1600, 2000, 2400, 2600, 3000, 3300,
+ 1700, 2100, 2400, 2600, 3100, 3300,
+ 1700, 2100, 2400, 2600, 3200, 3400,
+ 1400, 1600, 2300, 2400, 3300, 3400,
+ 1300, 1400, 2100, 2200, 2900, 3200,
+ 1000, 1300, 2200, 2300, 3200, 3400,
+ 1600, 2000, 2300, 2600, 2800, 3100,
+ 1600, 2000, 2300, 2600, 2900, 3200,
+ 1600, 2000, 2300, 2600, 3100, 3300,
+ 1700, 2000, 2300, 2600, 3100, 3300,
+ 1600, 1900, 2300, 2500, 3100, 3400,
+ 1500, 1900, 2300, 2600, 3000, 3300,
+ 1500, 1900, 2300, 2600, 3100, 3300,
+ 1500, 2000, 2300, 2700, 3100, 3300,
+ 2000, 2500, 2700, 2900, 3300, 3400,
+ 2000, 2400, 2600, 2800, 3300, 3400,
+ 1700, 2300, 2600, 2800, 3300, 3400,
+ 1400, 1700, 2400, 2500, 3200, 3300,
+ 1300, 1600, 2300, 2500, 3200, 3300,
+ 1300, 1500, 2000, 2300, 3200, 3300,
+ 1500, 1800, 2200, 2400, 2900, 3300,
+ 1500, 1700, 2200, 2400, 3000, 3200,
+ 1400, 1800, 2200, 2400, 3000, 3300,
+ 1400, 1800, 2200, 2400, 3000, 3200,
+ 1200, 1500, 2100, 2400, 3100, 3300,
+ 1300, 1800, 2200, 2300, 3300, 3400,
+ 1300, 1700, 2200, 2400, 3300, 3400,
+ 1400, 1500, 2300, 2500, 3100, 3400,
+ 1500, 1600, 2300, 2500, 3100, 3300,
+ 1500, 1600, 2400, 2500, 3100, 3300,
+ 1400, 1800, 2400, 2500, 3000, 3300,
+ 1300, 1700, 2100, 2500, 3000, 3200,
+ 1300, 1600, 2100, 2500, 3100, 3200,
+ 1300, 1700, 2200, 2500, 3100, 3200,
+ 1300, 1600, 2200, 2500, 3100, 3300,
+ 1300, 1700, 2300, 2600, 3200, 3300,
+ 1300, 1700, 2400, 2500, 3200, 3400,
+ 1500, 1900, 2500, 2600, 3200, 3400,
+ 1500, 2000, 2500, 2600, 3300, 3400,
+ 1600, 2100, 2600, 2900, 3400, 3500,
+ 1600, 1900, 2500, 2800, 3300, 3400,
+ 1500, 2000, 2500, 2600, 3200, 3300,
+ 1600, 2000, 2500, 2700, 3100, 3200,
+ 1500, 1700, 2400, 2700, 3100, 3200,
+ 1500, 1600, 2400, 2600, 3100, 3300,
+ 1500, 1600, 2200, 2400, 3000, 3200,
+ 1500, 1600, 2200, 2300, 3000, 3200,
+ 1400, 1700, 2100, 2300, 3000, 3100,
+ 1700, 1800, 2300, 2800, 3100, 3300,
+ 1800, 2100, 2500, 2800, 3200, 3300,
+ 1800, 2200, 2500, 2700, 3200, 3300,
+ 1900, 2200, 2500, 2800, 3200, 3300,
+ 1800, 2200, 2500, 2800, 3200, 3300,
+ 1600, 2000, 2300, 2500, 3000, 3200,
+ 1500, 1900, 2200, 2500, 3100, 3200,
+ 1500, 1700, 2200, 2400, 3100, 3200,
+ 1600, 1700, 2200, 2400, 3000, 3100,
+ 1600, 1700, 2300, 2400, 3000, 3100,
+ 1600, 1700, 2300, 2400, 3000, 3200,
+ 1600, 1700, 2300, 2400, 2900, 3100,
+ 1600, 1700, 2300, 2400, 2900, 3200,
+ 1600, 1700, 2300, 2500, 2900, 3200,
+ 1500, 1600, 2300, 2500, 2900, 3300,
+ 1400, 1500, 2200, 2500, 3000, 3300,
+ 1200, 1400, 2300, 2400, 3000, 3300,
+ 1100, 1400, 2300, 2400, 3100, 3300,
+ 1200, 1800, 2400, 2500, 3300, 3400,
+ 1400, 2000, 2400, 2700, 3300, 3400,
+ 1600, 2100, 2500, 2800, 3300, 3400,
+ 1700, 2300, 2600, 2900, 3300, 3400,
+ 1400, 2100, 2400, 2600, 3100, 3200,
+ 1300, 1600, 2300, 2500, 3000, 3200,
+ 1200, 1500, 2100, 2500, 3000, 3200,
+ 1300, 1700, 2100, 2300, 2900, 3200,
+ 1500, 1600, 2200, 2400, 3000, 3100,
+ 1500, 1600, 2200, 2500, 3000, 3200,
+ 1600, 1700, 2200, 2500, 3100, 3200,
+ 1600, 1700, 2200, 2500, 3100, 3300,
+ 1600, 1700, 2200, 2400, 3100, 3300,
+ 1600, 1700, 2300, 2500, 3300, 3400,
+ 1700, 1800, 2300, 2500, 3300, 3400,
+ 1800, 2000, 2300, 2700, 3200, 3300,
+ 1900, 2000, 2300, 2700, 3300, 3400,
+ 1900, 2000, 2100, 2400, 3300, 3400,
+ 1800, 2100, 2400, 2800, 3200, 3400,
+ 2000, 2200, 2500, 2700, 3100, 3300,
+ 2000, 2300, 2500, 2700, 3100, 3300,
+ 2000, 2300, 2500, 2800, 3300, 3400,
+ 1900, 2300, 2500, 2800, 3300, 3400,
+ 1800, 1900, 2300, 2600, 3300, 3400,
+ 1800, 1900, 2400, 2600, 3200, 3300,
+ 1700, 1900, 2400, 2500, 3200, 3300,
+ 1700, 1800, 2300, 2600, 3200, 3300,
+ 1600, 1700, 2300, 2600, 3200, 3300,
+ 1600, 1900, 2300, 2600, 3200, 3300,
+ 1500, 1800, 2200, 2400, 3200, 3300,
+ 1500, 1800, 2100, 2500, 3100, 3200,
+ 1700, 2100, 2400, 2800, 3200, 3300,
+ 1900, 2100, 2500, 2900, 3200, 3300,
+ 1900, 2100, 2400, 2900, 3200, 3300,
+ 1800, 2100, 2400, 2800, 3100, 3200,
+ 2000, 2200, 2500, 2800, 3100, 3300,
+ 2000, 2200, 2700, 2800, 3100, 3300,
+ 2000, 2300, 2600, 2800, 3200, 3300,
+ 1800, 2000, 2600, 2800, 3200, 3300,
+ 1800, 2100, 2600, 2800, 3200, 3400,
+ 1800, 2200, 2500, 2700, 3300, 3400,
+ 1700, 1900, 2500, 2600, 3200, 3400,
+ 1700, 1900, 2400, 2700, 3200, 3400,
+ 1500, 1900, 2500, 2600, 3100, 3300,
+ 1200, 2100, 2400, 2600, 3200, 3300,
+ 1300, 1800, 2400, 2500, 3200, 3300,
+ 1200, 1600, 2400, 2600, 3200, 3300,
+ 1200, 1900, 2500, 2700, 3200, 3300,
+ 1300, 2000, 2400, 2700, 3200, 3300,
+ 1200, 1900, 2300, 2500, 3200, 3300,
+ 1100, 1800, 2300, 2400, 3200, 3300,
+ 1100, 1900, 2300, 2500, 3200, 3300,
+ 1100, 2100, 2400, 2600, 3200, 3300,
+ 1000, 1900, 2400, 2500, 3200, 3300,
+ 1000, 1500, 2400, 2500, 3100, 3200,
+ 1000, 1500, 2300, 2400, 3100, 3200,
+ 1000, 1900, 2300, 2500, 3000, 3100,
+ 1100, 1900, 2300, 2400, 3100, 3200,
+ 1200, 1800, 2300, 2400, 3100, 3200,
+ 1300, 1800, 2300, 2400, 3100, 3200,
+ 1400, 1800, 2300, 2400, 3200, 3300,
+ 1600, 1700, 2300, 2400, 3100, 3300,
+ 1600, 1700, 2300, 2400, 3100, 3200,
+ 1600, 1700, 2200, 2400, 3100, 3200,
+ 1500, 1800, 2200, 2400, 3100, 3200,
+ 1400, 1800, 2200, 2400, 3100, 3200,
+ 1400, 1800, 2200, 2400, 3000, 3100,
+ 1800, 2000, 2300, 2800, 2900, 3100,
+ 1500, 1900, 2300, 2500, 3100, 3200,
+ 1500, 1900, 2300, 2400, 3300, 3400,
+ 1500, 2000, 2400, 2600, 3300, 3400,
+ 1600, 2000, 2400, 2700, 3300, 3400,
+ 1600, 2000, 2400, 2500, 3300, 3400,
+ 1600, 2000, 2400, 2600, 3300, 3400,
+ 1700, 2100, 2400, 2600, 2900, 3200,
+ 1600, 2000, 2500, 2700, 2900, 3200,
+ 1500, 1800, 2400, 2800, 3000, 3200,
+ 1500, 1800, 2100, 2400, 2900, 3100,
+ 1600, 1900, 2100, 2400, 3100, 3300,
+ 1600, 1900, 2100, 2500, 3100, 3200,
+ 1800, 1900, 2300, 2400, 3100, 3300,
+ 1900, 2000, 2500, 2600, 3200, 3300,
+ 1900, 2200, 2600, 2700, 3300, 3400,
+ 1900, 2300, 2600, 2700, 3300, 3400,
+ 1900, 2300, 2700, 2800, 3300, 3400,
+ 2000, 2200, 2700, 2800, 3300, 3400,
+ 2000, 2400, 2700, 2800, 3300, 3400,
+ 2000, 2300, 2700, 2800, 3300, 3400,
+ 2000, 2400, 2600, 2700, 3300, 3400,
+ 2000, 2200, 2600, 2700, 3200, 3300,
+ 1900, 2100, 2600, 2700, 3200, 3300,
+ 1900, 2100, 2500, 2700, 3200, 3300,
+ 1900, 2000, 2400, 2600, 3200, 3300,
+ 1900, 2000, 2400, 2600, 3100, 3200,
+ 1900, 2000, 2300, 2500, 3100, 3200,
+ 1800, 2000, 2300, 2500, 3100, 3200,
+ 1800, 1900, 2300, 2500, 3000, 3100,
+ 1800, 1900, 2400, 2700, 3000, 3200,
+ 1800, 1900, 2500, 2700, 3000, 3200,
+ 1800, 2000, 2500, 2700, 3100, 3200,
+ 2000, 2300, 2600, 2900, 3100, 3300,
+ 1900, 2300, 2700, 3000, 3200, 3300,
+ 2000, 2400, 2700, 3000, 3200, 3300,
+ 2100, 2500, 2800, 3000, 3200, 3300,
+ 2200, 2400, 2800, 3000, 3300, 3400,
+ 1900, 2200, 2700, 2900, 3300, 3400,
+ 2200, 2400, 2900, 3100, 3300, 3400,
+ 2100, 2400, 2800, 3100, 3300, 3400,
+ 2200, 2500, 2800, 3100, 3300, 3400,
+ 2100, 2400, 2600, 2800, 3300, 3400,
+ 2000, 2400, 2600, 2700, 3200, 3300,
+ 1700, 2000, 2400, 2600, 3200, 3300,
+ 1700, 1900, 2400, 2600, 3100, 3300,
+ 1800, 1900, 2400, 2700, 3200, 3300,
+ 1800, 1900, 2400, 2700, 3100, 3200,
+ 1800, 1900, 2400, 2700, 3100, 3300,
+ 1800, 1900, 2300, 2700, 3100, 3200,
+ 1700, 1900, 2200, 2700, 3000, 3300,
+ 1700, 1800, 2300, 2700, 2900, 3200,
+ 1700, 1900, 2300, 2700, 2900, 3200,
+ 1700, 1900, 2200, 2700, 3000, 3200,
+ 1700, 2000, 2300, 2800, 3000, 3200,
+ 1400, 1700, 2300, 2400, 3300, 3400,
+ 1400, 1800, 2300, 2400, 3300, 3400,
+ 1400, 1900, 2300, 2400, 3300, 3400,
+ 1400, 2100, 2300, 2500, 3300, 3400,
+ 1400, 2100, 2300, 2600, 3300, 3400,
+ 1700, 2200, 2500, 2700, 3200, 3400,
+ 1800, 2100, 2600, 2900, 3200, 3400,
+ 1800, 2100, 2600, 2800, 3300, 3400,
+ 1800, 2100, 2600, 2700, 3300, 3400,
+ 1800, 2000, 2500, 2700, 3300, 3400,
+ 1800, 2100, 2400, 2700, 3300, 3400,
+ 1800, 2100, 2400, 2600, 3300, 3400,
+ 1800, 2200, 2400, 2600, 3300, 3400,
+ 1800, 2200, 2400, 2700, 3300, 3400,
+ 1900, 2300, 2600, 2900, 3200, 3400,
+ 1900, 2200, 2600, 2700, 3200, 3400,
+ 1900, 2100, 2600, 2700, 3300, 3400,
+ 2000, 2100, 2500, 2700, 3200, 3300,
+ 2000, 2100, 2500, 2700, 3300, 3400,
+ 2000, 2200, 2500, 2700, 3300, 3400,
+ 2000, 2100, 2600, 2700, 3300, 3400,
+ 2000, 2100, 2500, 2700, 3400, 3500,
+ 1900, 2100, 2500, 2600, 3200, 3400,
+ 2000, 2200, 2600, 2700, 3200, 3400,
+ 2100, 2300, 2600, 2800, 3300, 3400,
+ 2100, 2500, 2700, 3100, 3300, 3400,
+ 2100, 2500, 2800, 3100, 3300, 3400,
+ 2100, 2300, 2400, 2700, 3200, 3300,
+ 2000, 2300, 2500, 2800, 3200, 3300,
+ 1700, 2100, 2500, 2700, 3200, 3300,
+ 1600, 1900, 2300, 2700, 3100, 3300,
+ 1600, 1800, 2300, 2800, 3100, 3300,
+ 1500, 1800, 2300, 2400, 3100, 3200,
+ 1500, 1700, 2300, 2400, 3100, 3300,
+ 1400, 1700, 2300, 2400, 3100, 3300,
+ 1400, 1500, 2300, 2400, 3100, 3300,
+ 1300, 1500, 2300, 2400, 3100, 3300,
+ 1300, 1500, 2400, 2500, 3100, 3300,
+ 1300, 1500, 2400, 2500, 3000, 3300,
+ 1300, 1500, 2300, 2400, 2900, 3300,
+ 1400, 1500, 2400, 2500, 2900, 3300,
+ 1500, 1600, 2300, 2500, 2800, 3300,
+ 1600, 1700, 2300, 2500, 2800, 3400,
+ 1700, 1800, 2300, 2500, 2800, 3300,
+ 1800, 1900, 2400, 2500, 3100, 3400,
+ 1800, 1900, 2400, 2500, 3200, 3400,
+ 1900, 2000, 2400, 2500, 3300, 3400,
+ 1900, 2000, 2300, 2500, 3300, 3400,
+ 1900, 2200, 2600, 2900, 3400, 3500,
+ 1800, 2200, 2600, 2900, 3300, 3400,
+ 1900, 2300, 2600, 3000, 3400, 3500,
+ 2000, 2300, 2600, 3000, 3300, 3400,
+ 1800, 2200, 2500, 2900, 3200, 3300,
+ 1800, 2100, 2400, 2700, 3200, 3300,
+ 1900, 2100, 2500, 2800, 3200, 3300,
+ 1700, 2100, 2500, 2700, 3100, 3300,
+ 1400, 1800, 2300, 2600, 3100, 3200,
+ 1300, 1600, 1700, 2400, 3000, 3100,
+ 1500, 1800, 2300, 2600, 3000, 3200,
+ 1900, 2200, 2500, 2800, 3000, 3300,
+ 2000, 2300, 2600, 2800, 3100, 3300,
+ 2000, 2300, 2700, 2900, 3100, 3300,
+ 2100, 2300, 2700, 2900, 3100, 3300,
+ 2000, 2300, 2700, 3000, 3300, 3400,
+ 1700, 2200, 2500, 2600, 3300, 3400,
+ 1400, 2000, 2400, 2600, 3300, 3400,
+ 1300, 1900, 2300, 2600, 3100, 3300,
+ 1200, 1600, 2200, 2400, 3000, 3100,
+ 1100, 1500, 2200, 2400, 3100, 3200,
+ 1100, 1400, 2300, 2400, 3200, 3300,
+ 1100, 1500, 2300, 2400, 3200, 3300,
+ 1100, 1500, 2300, 2400, 3300, 3400,
+ 1300, 1400, 2400, 2500, 3100, 3300,
+ 1500, 2200, 2500, 2600, 3100, 3200,
+ 2100, 2400, 2700, 3000, 3200, 3300,
+ 2200, 2400, 2700, 3000, 3300, 3400,
+ 2000, 2400, 2700, 3000, 3300, 3400,
+ 2000, 2400, 2700, 2900, 3300, 3400,
+ 2000, 2300, 2700, 3000, 3400, 3500,
+ 2100, 2400, 2700, 3000, 3400, 3500,
+ 2100, 2500, 2700, 3100, 3400, 3500,
+ 1900, 2400, 2600, 2800, 3300, 3400,
+ 1900, 2100, 2600, 2800, 3300, 3400,
+ 1900, 2100, 2500, 2700, 3300, 3400,
+ 1900, 2100, 2500, 2600, 3300, 3400,
+ 1800, 2200, 2400, 2800, 3300, 3400,
+ 1800, 2000, 2400, 2700, 3300, 3400,
+ 1900, 2000, 2400, 2700, 3200, 3300,
+ 2000, 2100, 2400, 2600, 3300, 3400,
+ 1500, 2100, 2200, 2500, 3300, 3400,
+ 1400, 1900, 2300, 2500, 3300, 3400,
+ 1400, 2000, 2300, 2600, 3200, 3300,
+ 1400, 1800, 2200, 2600, 3100, 3200,
+ 1700, 2100, 2400, 2700, 3100, 3300,
+ 1800, 2000, 2400, 2700, 3000, 3200,
+ 1600, 2000, 2300, 2500, 3100, 3200,
+ 1700, 2000, 2300, 2500, 3100, 3300,
+ 1600, 1900, 2200, 2600, 2900, 3200,
+ 1600, 1900, 2300, 2600, 2900, 3200,
+ 1600, 1900, 2300, 2600, 3000, 3200,
+ 1600, 1800, 2200, 2500, 3000, 3200,
+ 1600, 1800, 2300, 2600, 3100, 3200,
+ 1700, 1800, 2400, 2600, 3100, 3200,
+ 1700, 1800, 2300, 2500, 3000, 3100,
+ 1700, 1800, 2300, 2500, 3100, 3200,
+ 1700, 1800, 2200, 2400, 3000, 3200,
+ 1700, 1800, 2100, 2300, 3100, 3200,
+ 1700, 1900, 2100, 2400, 3000, 3200,
+ 1800, 2000, 2200, 2400, 3000, 3200,
+ 1800, 2000, 2300, 2500, 3100, 3300,
+ 1800, 2000, 2300, 2600, 3200, 3300,
+ 1800, 2000, 2400, 2600, 3200, 3300,
+ 1800, 2000, 2400, 2600, 3300, 3400,
+ 1800, 1900, 2400, 2500, 3300, 3400,
+ 1700, 1900, 2400, 2500, 3300, 3400,
+ 1700, 2100, 2400, 2600, 3300, 3400,
+ 1800, 2100, 2500, 2900, 3300, 3400,
+ 1800, 2200, 2600, 2800, 3300, 3500,
+ 1800, 2100, 2600, 2900, 3300, 3400,
+ 1800, 2100, 2600, 3000, 3200, 3300,
+ 1800, 2200, 2600, 2900, 3200, 3300,
+ 1800, 2100, 2600, 2800, 3200, 3300,
+ 1900, 2200, 2400, 2700, 3100, 3200,
+ 1700, 2000, 2300, 2700, 3000, 3100,
+ 1700, 2000, 2300, 2600, 3000, 3100,
+ 1800, 2100, 2400, 2600, 3100, 3200,
+ 1800, 2100, 2400, 2700, 3100, 3200,
+ 1900, 2100, 2400, 2700, 3200, 3300,
+ 1800, 2000, 2400, 2700, 3100, 3300,
+ 1700, 2000, 2400, 2700, 3100, 3300,
+ 1700, 1900, 2300, 2700, 3100, 3300,
+ 1700, 2000, 2300, 2600, 3100, 3200,
+ 1600, 1900, 2300, 2600, 3100, 3200,
+ 1400, 1700, 2200, 2500, 3000, 3200,
+ 1500, 1700, 2100, 2500, 2900, 3100,
+ 1500, 1800, 2300, 2600, 2900, 3200,
+ 1500, 1900, 2400, 2600, 3000, 3200,
+ 1600, 2000, 2300, 2700, 3100, 3200,
+ 1600, 2000, 2400, 2700, 3100, 3300,
+ 1600, 2200, 2600, 2900, 3300, 3400,
+ 1700, 2200, 2600, 3000, 3300, 3400,
+ 1700, 2100, 2500, 2900, 3300, 3400,
+ 1700, 2200, 2500, 2900, 3300, 3400,
+ 1500, 1800, 2400, 2500, 3200, 3400,
+ 1500, 1700, 2400, 2500, 3300, 3400,
+ 1500, 1700, 2300, 2400, 3300, 3400,
+ 1600, 1800, 2300, 2400, 3300, 3400,
+ 1600, 1800, 2400, 2500, 3300, 3400,
+ 1600, 1700, 2400, 2500, 2800, 3300,
+ 1600, 1800, 2300, 2500, 2700, 3200,
+ 1600, 1700, 2300, 2500, 2700, 3200,
+ 1600, 1700, 2200, 2500, 2700, 3100,
+ 1600, 1700, 2200, 2500, 2600, 3000,
+ 1600, 1700, 2400, 2500, 2700, 3200,
+ 1600, 1700, 2400, 2500, 2800, 3200,
+ 1700, 1800, 2400, 2600, 2900, 3300,
+ 1700, 1800, 2300, 2600, 2800, 3300,
+ 1700, 1800, 2400, 2600, 3000, 3400,
+ 1700, 1800, 2300, 2500, 2900, 3300,
+ 1600, 1700, 2300, 2500, 3000, 3300,
+ 1400, 1800, 2000, 2400, 3000, 3200,
+ 1400, 1700, 2000, 2300, 3000, 3200,
+ 1700, 2000, 2300, 2500, 3100, 3200,
+ 1700, 1800, 2400, 2500, 3100, 3200,
+ 1800, 2000, 2400, 2500, 3200, 3300,
+ 1900, 2000, 2400, 2600, 3300, 3400,
+ 1900, 2000, 2300, 2600, 3300, 3400,
+ 2000, 2100, 2200, 2600, 3300, 3400,
+ 2000, 2100, 2300, 2600, 3300, 3400,
+ 2100, 2200, 2500, 2800, 3300, 3400,
+ 2000, 2100, 2300, 2500, 3200, 3300,
+ 1900, 2000, 2200, 2600, 3200, 3300,
+ 1800, 1900, 2100, 2600, 3100, 3200,
+ 1700, 1900, 2100, 2600, 3000, 3200,
+ 1500, 1800, 2100, 2300, 3000, 3200,
+ 1500, 1800, 2100, 2400, 3100, 3300,
+ 1500, 1700, 2200, 2500, 3100, 3300,
+ 1500, 1800, 2200, 2300, 3200, 3300,
+ 1500, 1900, 2300, 2500, 3300, 3400,
+ 1800, 2300, 2600, 3000, 3400, 3500,
+ 1900, 2300, 2700, 3000, 3400, 3500,
+ 2000, 2300, 2800, 3100, 3300, 3400,
+ 2100, 2300, 2800, 3100, 3300, 3400,
+ 2000, 2300, 2700, 3000, 3200, 3300,
+ 2000, 2200, 2600, 2900, 3100, 3300,
+ 2000, 2200, 2500, 2800, 3000, 3200,
+ 2000, 2200, 2400, 2800, 3100, 3200,
+ 1600, 2000, 2400, 2600, 3100, 3200,
+ 1400, 1900, 2400, 2500, 3100, 3200,
+ 1400, 1900, 2300, 2600, 3000, 3200,
+ 1500, 2000, 2400, 2700, 2900, 3200,
+ 2000, 2300, 2800, 3000, 3200, 3400,
+ 2100, 2300, 2900, 3100, 3300, 3400,
+ 1800, 2300, 2600, 2900, 3400, 3500,
+ 1700, 2300, 2500, 2900, 3300, 3400,
+ 1300, 2000, 2400, 2700, 3300, 3400,
+ 1200, 1900, 2300, 2600, 3300, 3400,
+ 1200, 1800, 2300, 2600, 3300, 3400,
+ 1100, 1800, 2300, 2500, 3300, 3400,
+ 1800, 2200, 2600, 2800, 3300, 3400,
+ 1800, 2000, 2500, 2700, 3200, 3400,
+ 1700, 2100, 2600, 2700, 3200, 3300,
+ 1700, 2200, 2600, 2800, 3300, 3400,
+ 1800, 2200, 2600, 3000, 3300, 3500,
+ 1700, 2100, 2600, 2800, 3300, 3400,
+ 1700, 2100, 2500, 2800, 3300, 3400,
+ 1700, 2200, 2500, 2800, 3300, 3400,
+ 1700, 2200, 2500, 2800, 3300, 3500,
+ 1800, 2200, 2500, 2900, 3300, 3400,
+ 2100, 2200, 2600, 2700, 3100, 3400,
+ 1900, 2100, 2500, 2600, 3100, 3400,
+ 1900, 2000, 2500, 2600, 3200, 3400,
+ 1900, 2000, 2600, 2700, 3200, 3400,
+ 1800, 1900, 2500, 2600, 3100, 3400,
+ 1600, 2000, 2700, 2800, 3300, 3400,
+ 1400, 2000, 2700, 2800, 3300, 3400,
+ 1000, 1900, 2700, 2800, 3300, 3400,
+ 1000, 1400, 2700, 2900, 3200, 3400,
+ 1100, 1500, 2700, 2900, 3200, 3300,
+ 1200, 1700, 2400, 2500, 3100, 3300,
+ 1300, 1900, 2400, 2500, 3300, 3400,
+ 1300, 2000, 2400, 2600, 3200, 3300,
+ 1400, 2000, 2400, 2600, 3100, 3300,
+ 1500, 2000, 2400, 2700, 3000, 3300,
+ 1300, 2100, 2400, 2700, 3200, 3300,
+ 1400, 1900, 2700, 2800, 3300, 3400,
+ 1500, 1900, 2700, 2800, 3300, 3400,
+ 1400, 1800, 2600, 2700, 3200, 3400,
+ 1800, 2300, 2600, 2700, 2900, 3200,
+ 1500, 1700, 2400, 2600, 2800, 3300,
+ 1600, 1700, 2500, 2700, 2900, 3300,
+ 1800, 1900, 2600, 2700, 3200, 3400,
+ 1800, 1900, 2600, 2700, 3200, 3300,
+ 2000, 2200, 2600, 2800, 3200, 3300,
+ 2000, 2100, 2600, 2700, 3200, 3400,
+ 2000, 2100, 2500, 2800, 3200, 3400,
+ 2000, 2100, 2600, 2700, 3100, 3300,
+ 1900, 2000, 2400, 2600, 3100, 3300,
+ 1800, 1900, 2400, 2600, 3100, 3200,
+ 1700, 2000, 2300, 2400, 3200, 3300,
+ 1900, 2100, 2500, 2700, 3200, 3400,
+ 1900, 2000, 2500, 2700, 3200, 3400,
+ 1800, 2000, 2500, 2600, 3200, 3300,
+ 1800, 2100, 2500, 2700, 3200, 3400,
+ 1800, 2000, 2500, 2600, 3200, 3400,
+ 1800, 1900, 2400, 2500, 3000, 3300,
+ 1800, 2000, 2400, 2600, 3100, 3300,
+ 1900, 2100, 2500, 2600, 3200, 3300,
+ 2000, 2100, 2500, 2600, 3300, 3400,
+ 2000, 2200, 2500, 2600, 3300, 3400,
+ 2100, 2200, 2500, 2600, 3300, 3400,
+ 2100, 2200, 2500, 2600, 3200, 3400,
+ 2100, 2200, 2400, 2500, 3200, 3400,
+ 2000, 2100, 2400, 2500, 3200, 3400,
+ 1800, 1900, 2400, 2600, 3200, 3400,
+ 1800, 1900, 2500, 2600, 3200, 3400,
+ 1800, 2300, 2700, 2900, 3300, 3400,
+ 1900, 2400, 2800, 3000, 3300, 3500,
+ 1900, 2300, 2800, 3100, 3300, 3400,
+ 2000, 2300, 2700, 2900, 3200, 3400,
+ 1800, 2000, 2600, 2900, 3300, 3400,
+ 1700, 2000, 2500, 2600, 3200, 3400,
+ 1600, 2100, 2500, 2600, 3300, 3400,
+ 1500, 2100, 2500, 2600, 3300, 3400,
+ 1500, 2000, 2400, 2500, 3200, 3300,
+ 1400, 2000, 2400, 2600, 3200, 3300,
+ 1300, 1900, 2400, 2600, 3100, 3300,
+ 1300, 2000, 2600, 2800, 3300, 3400,
+ 1500, 2000, 2600, 2700, 3300, 3400,
+ 1600, 2000, 2500, 2700, 3200, 3400,
+ 1600, 2000, 2500, 2600, 3200, 3400,
+ 1600, 2000, 2400, 2500, 3200, 3400,
+ 1700, 2000, 2300, 2500, 3300, 3400,
+ 1600, 1900, 2300, 2400, 3300, 3400,
+ 1500, 1700, 2200, 2400, 3200, 3300,
+ 1500, 1800, 2200, 2500, 2900, 3200,
+ 1300, 1700, 2200, 2500, 3000, 3300,
+ 1200, 1700, 2200, 2600, 3000, 3200,
+ 1100, 1700, 2300, 2600, 3100, 3300,
+ 1200, 1800, 2300, 2500, 3300, 3400,
+ 1100, 2100, 2400, 2600, 3300, 3400,
+ 1200, 2200, 2400, 2700, 3300, 3400,
+ 1200, 2300, 2500, 2700, 3300, 3400,
+ 1200, 2300, 2500, 2800, 3300, 3400,
+ 1200, 2300, 2600, 2800, 3300, 3400,
+ 1100, 1800, 2500, 2600, 3400, 3500,
+ 1300, 1700, 2500, 2600, 3200, 3400,
+ 1400, 1800, 2500, 2600, 3200, 3400,
+ 1500, 1900, 2500, 2600, 3200, 3300,
+ 1500, 1900, 2500, 2700, 3200, 3300,
+ 1800, 1900, 2500, 2700, 3100, 3200,
+ 1900, 2100, 2400, 2500, 3200, 3300,
+ 2000, 2100, 2300, 2500, 3300, 3400,
+ 1500, 1900, 2400, 2800, 3100, 3300,
+ 1200, 1700, 2500, 2600, 3300, 3400,
+ 1300, 1900, 2500, 2600, 3300, 3400,
+ 1400, 1800, 2500, 2700, 3300, 3400,
+ 1300, 1700, 2400, 2700, 3200, 3400,
+ 1100, 2100, 2600, 2700, 3300, 3400,
+ 1200, 2100, 2600, 2700, 3300, 3400,
+ 1200, 2100, 2500, 2700, 3300, 3400,
+ 1200, 2100, 2500, 2600, 3300, 3400,
+ 1200, 2000, 2500, 2600, 3300, 3400,
+ 1200, 2200, 2500, 2700, 3400, 3500,
+ 1400, 1800, 2400, 2600, 3100, 3400,
+ 1400, 1900, 2400, 2600, 3100, 3300,
+ 1500, 1800, 2400, 2700, 3100, 3300,
+ 1500, 1900, 2400, 2600, 3200, 3400,
+ 1600, 2100, 2400, 2600, 3300, 3400,
+ 1900, 2200, 2400, 2600, 3300, 3400,
+ 2000, 2200, 2400, 2600, 3200, 3300,
+ 2000, 2100, 2400, 2500, 3200, 3300,
+ 2100, 2200, 2500, 2600, 3200, 3300,
+ 2100, 2200, 2500, 2700, 3200, 3300,
+ 2000, 2100, 2400, 2600, 3100, 3200,
+ 1500, 2100, 2300, 2600, 3100, 3200,
+ 1500, 1900, 2300, 2400, 3100, 3300,
+ 1500, 1800, 2300, 2400, 3100, 3300,
+ 1400, 1800, 2300, 2400, 3100, 3300,
+ 1400, 1900, 2300, 2500, 3100, 3300,
+ 1600, 1900, 2500, 2600, 3200, 3300,
+ 1500, 1800, 2300, 2600, 3100, 3300,
+ 1400, 1700, 2200, 2600, 3100, 3200,
+ 1400, 1600, 2200, 2500, 3000, 3200,
+ 1300, 1700, 2400, 2600, 3100, 3200,
+ 1400, 1700, 2200, 2500, 3200, 3300,
+ 1400, 1800, 2300, 2500, 3200, 3300,
+ 1300, 1900, 2200, 2400, 3200, 3300,
+ 1100, 1500, 2300, 2400, 3200, 3400,
+ 1000, 1600, 2500, 2600, 3300, 3400,
+ 1000, 1700, 2500, 2600, 3300, 3400,
+ 1000, 1800, 2600, 2700, 3300, 3400,
+ 1000, 1900, 2600, 2700, 3300, 3400,
+ 1000, 1800, 2800, 2900, 3300, 3400,
+ 1400, 1600, 2500, 2600, 3100, 3400,
+ 1600, 1700, 2500, 2600, 3100, 3400,
+ 1600, 1700, 2500, 2600, 3000, 3400,
+ 1700, 1800, 2500, 2600, 3000, 3400,
+ 1700, 1800, 2400, 2600, 2800, 3300,
+ 1700, 1800, 2400, 2600, 2900, 3400,
+ 1700, 1800, 2500, 2600, 3200, 3400,
+ 1700, 1800, 2500, 2600, 3100, 3400,
+ 1600, 1800, 2500, 2600, 3200, 3400,
+ 1600, 1800, 2600, 2700, 3200, 3400,
+ 1600, 1900, 2600, 2700, 3300, 3400,
+ 1600, 2000, 2600, 2700, 3200, 3400,
+ 1800, 2300, 2800, 3000, 3300, 3400,
+ 1800, 2100, 2800, 3100, 3300, 3400,
+ 1900, 2100, 2700, 2900, 3300, 3400,
+ 1800, 2000, 2600, 2800, 3200, 3400,
+ 1700, 1900, 2500, 2800, 3100, 3300,
+ 1700, 1800, 2400, 2600, 3000, 3300,
+ 1700, 1800, 2500, 2700, 3000, 3400,
+ 1700, 1900, 2600, 2700, 3100, 3400,
+ 1600, 1900, 2600, 2700, 3000, 3300,
+ 1700, 2000, 2600, 2700, 3100, 3300,
+ 1700, 1900, 2600, 2700, 3200, 3300,
+ 1700, 1900, 2600, 2800, 3200, 3300,
+ 1600, 1900, 2600, 2800, 3200, 3400,
+ 1200, 1800, 2700, 2800, 3200, 3400,
+ 1100, 1700, 2700, 2800, 3200, 3300,
+ 1500, 1800, 2600, 2700, 3100, 3400,
+ 1500, 1800, 2500, 2600, 3100, 3400,
+ 1600, 1800, 2500, 2600, 3100, 3400,
+ 1600, 1800, 2400, 2500, 3100, 3400,
+ 1500, 1700, 2400, 2500, 3000, 3400,
+ 1400, 1600, 2400, 2500, 3000, 3400,
+ 1400, 1600, 2400, 2600, 2900, 3300,
+ 1200, 1700, 2600, 2700, 3100, 3300,
+ 1200, 1800, 2600, 2700, 3200, 3400,
+ 1100, 1900, 2600, 2700, 3200, 3400,
+ 1400, 1800, 2500, 2700, 3200, 3400,
+ 1700, 1900, 2500, 2600, 2900, 3300,
+ 1600, 1700, 2500, 2700, 3000, 3400,
+ 1400, 1500, 2500, 2700, 3200, 3400,
+ 1400, 1700, 2500, 2700, 3000, 3300,
+ 1800, 2000, 2200, 2600, 2900, 3200,
+ 1900, 2100, 2400, 2600, 3100, 3300,
+ 1900, 2300, 2400, 2700, 3200, 3300,
+ 1800, 2200, 2400, 2700, 3200, 3300,
+ 1600, 1900, 2200, 2400, 3000, 3200,
+ 1500, 1900, 2100, 2500, 3100, 3200,
+ 1500, 1900, 2100, 2400, 3100, 3200,
+ 1400, 1900, 2100, 2500, 3200, 3300,
+ 1300, 2000, 2200, 2500, 3200, 3300,
+ 1200, 2000, 2200, 2500, 3200, 3300,
+ 1200, 2100, 2300, 2600, 3200, 3300,
+ 1100, 2000, 2500, 2600, 3300, 3400,
+ 1200, 2200, 2500, 2600, 3300, 3400,
+ 1500, 1800, 2400, 2500, 3300, 3400,
+ 1800, 1900, 2300, 2400, 3300, 3400,
+ 2100, 2200, 2400, 2600, 3300, 3400,
+ 2200, 2300, 2600, 2700, 3300, 3400,
+ 2200, 2300, 2600, 2800, 3300, 3400,
+ 2100, 2300, 2500, 2800, 3100, 3300,
+ 2200, 2300, 2600, 2700, 3100, 3400,
+ 2100, 2200, 2600, 2700, 3200, 3400,
+ 1900, 2300, 2600, 2900, 3100, 3300,
+ 2000, 2300, 2600, 2900, 3200, 3300,
+ 2200, 2300, 2700, 2900, 3300, 3400,
+ 2000, 2300, 2500, 2900, 3300, 3400,
+ 1500, 1700, 2200, 2600, 3100, 3300,
+ 1500, 1700, 2200, 2600, 3000, 3300,
+ 1500, 1800, 2200, 2600, 3100, 3300,
+ 1500, 1800, 2000, 2300, 3200, 3300,
+ 1600, 1800, 2000, 2300, 3200, 3300,
+ 1600, 1900, 2100, 2300, 3200, 3300,
+ 1700, 1900, 2200, 2400, 3200, 3300,
+ 1700, 1900, 2300, 2400, 3300, 3400,
+ 1800, 1900, 2300, 2500, 3300, 3400,
+ 1800, 2000, 2400, 2500, 3200, 3400,
+ 1800, 2000, 2400, 2600, 3100, 3400,
+ 1800, 1900, 2400, 2600, 3100, 3400,
+ 1400, 1600, 2500, 2600, 2900, 3300,
+ 1300, 1500, 2500, 2600, 2900, 3300,
+ 1300, 1700, 2300, 2700, 3000, 3200,
+ 1600, 1900, 2400, 2800, 3100, 3200,
+ 1500, 2000, 2400, 2800, 3100, 3300,
+ 1100, 1700, 2600, 2700, 3200, 3400,
+ 1100, 1800, 2600, 2700, 3300, 3400,
+ 1100, 1800, 2700, 2800, 3300, 3400,
+ 1700, 2000, 2600, 2700, 3100, 3400,
+ 1700, 2100, 2500, 2600, 3000, 3200,
+ 1700, 2200, 2600, 2700, 3100, 3200,
+ 1700, 2000, 2500, 2600, 3000, 3200,
+ 1700, 1900, 2500, 2600, 3000, 3300,
+ 1700, 1900, 2400, 2600, 3000, 3300,
+ 2000, 2200, 2400, 2600, 3300, 3400,
+ 1800, 2100, 2400, 2500, 3300, 3400,
+ 1700, 2100, 2400, 2500, 3300, 3400,
+ 1500, 2100, 2400, 2500, 3300, 3400,
+ 1600, 2100, 2400, 2500, 3300, 3400,
+ 1700, 2000, 2300, 2400, 3300, 3400,
+ 1700, 2000, 2400, 2500, 3300, 3400,
+ 1800, 2000, 2400, 2500, 3300, 3400,
+ 1900, 2000, 2400, 2500, 3100, 3400,
+ 1900, 2000, 2400, 2500, 3000, 3400,
+ 1900, 2000, 2300, 2400, 2800, 3300,
+ 1800, 2000, 2200, 2400, 2600, 3200,
+ 1900, 2000, 2300, 2500, 2800, 3200,
+ 1700, 2000, 2300, 2700, 3100, 3300,
+ 1700, 1900, 2500, 2800, 3200, 3300,
+ 1700, 2000, 2500, 2800, 3300, 3400,
+ 1700, 2000, 2600, 2900, 3300, 3400,
+ 1700, 1800, 2500, 2700, 3200, 3400,
+ 1600, 1700, 2400, 2600, 2900, 3300,
+ 1600, 1700, 2500, 2600, 2900, 3300,
+ 1600, 1800, 2600, 2700, 3100, 3400,
+ 1600, 1700, 2600, 2700, 3000, 3300,
+ 1600, 1700, 2600, 2700, 3100, 3300,
+ 1700, 1900, 2500, 2800, 3200, 3400,
+ 2100, 2500, 2700, 3000, 3300, 3400,
+ 2100, 2400, 2700, 2900, 3300, 3400,
+ 2200, 2500, 2700, 3000, 3300, 3400,
+ 2200, 2500, 2800, 2900, 3400, 3500,
+ 2200, 2500, 2800, 2900, 3300, 3500,
+ 2100, 2500, 2700, 2800, 3300, 3400,
+ 2100, 2400, 2700, 2900, 3200, 3400,
+ 2100, 2300, 2600, 2800, 3100, 3400,
+ 2100, 2200, 2500, 2700, 3100, 3400,
+ 2200, 2300, 2500, 2700, 3200, 3400,
+ 1900, 2100, 2400, 2500, 3200, 3400,
+ 1700, 2000, 2400, 2500, 3200, 3300,
+ 1500, 1900, 2400, 2500, 3100, 3300,
+ 1400, 1900, 2500, 2600, 3300, 3400,
+ 1200, 1900, 2600, 2700, 3300, 3400,
+ 1100, 2000, 2600, 2700, 3300, 3400,
+ 1100, 1700, 2600, 2700, 3300, 3400,
+ 1300, 1600, 2500, 2600, 3100, 3400,
+ 1500, 1600, 2400, 2500, 3000, 3400,
+ 1600, 1700, 2400, 2500, 3100, 3400,
+ 1900, 2000, 2300, 2500, 2900, 3400,
+ 1900, 2000, 2400, 2500, 2800, 3300,
+ 1900, 2000, 2500, 2700, 3300, 3400,
+ 1900, 2000, 2500, 2800, 3300, 3400,
+ 2000, 2200, 2700, 2900, 3300, 3400,
+ 1900, 2200, 2700, 2800, 3200, 3300,
+ 1900, 2200, 2700, 2900, 3200, 3300,
+ 2000, 2300, 2700, 2900, 3200, 3300,
+ 2200, 2600, 2700, 2900, 3300, 3400,
+ 2100, 2400, 2700, 2800, 3300, 3400,
+ 2100, 2200, 2500, 2700, 3300, 3400,
+ 1900, 2100, 2400, 2500, 3300, 3400,
+ 1600, 2000, 2400, 2500, 3200, 3300,
+ 1500, 2000, 2400, 2500, 3300, 3400,
+ 1200, 1900, 2400, 2500, 3300, 3500,
+ 1200, 1600, 2400, 2500, 3200, 3400,
+ 1700, 2100, 2600, 2900, 3300, 3400,
+ 1800, 2200, 2700, 3000, 3300, 3400,
+ 1800, 2200, 2800, 3000, 3300, 3400,
+ 1700, 2100, 2600, 2900, 3200, 3400,
+ 1700, 2000, 2600, 2800, 3200, 3400,
+ 1600, 1800, 2500, 2700, 3200, 3400,
+ 1500, 1700, 2500, 2600, 3200, 3400,
+ 1500, 1700, 2400, 2600, 3200, 3300,
+ 1500, 1800, 2400, 2600, 3200, 3300,
+ 1500, 1800, 2300, 2500, 3200, 3400,
+ 1400, 1800, 2300, 2500, 3300, 3400,
+ 1400, 1800, 2300, 2400, 3200, 3400,
+ 1600, 1900, 2500, 2600, 3200, 3400,
+ 1500, 1900, 2600, 2700, 3200, 3400,
+ 1500, 1900, 2600, 2700, 3300, 3400,
+ 1400, 1900, 2600, 2700, 3300, 3400,
+ 1400, 1900, 2600, 2700, 3200, 3400,
+ 1500, 1700, 2600, 2700, 3100, 3300,
+ 1600, 1800, 2600, 2700, 3100, 3200,
+ 1900, 2100, 2700, 2900, 3200, 3300,
+ 2000, 2100, 2500, 2700, 3200, 3400,
+ 2000, 2100, 2400, 2600, 3100, 3400,
+ 2000, 2100, 2300, 2600, 3000, 3300,
+ 1900, 2000, 2300, 2500, 3000, 3400,
+ 1800, 1900, 2300, 2400, 3000, 3400,
+ 1600, 1800, 2300, 2400, 3000, 3400,
+ 1400, 1700, 2400, 2500, 2900, 3400,
+ 1300, 1700, 2400, 2500, 3100, 3400,
+ 1400, 1700, 2300, 2600, 3100, 3300,
+ 1200, 1600, 2400, 2500, 3200, 3300,
+ 1200, 1600, 2500, 2600, 3200, 3300,
+ 1300, 1800, 2500, 2600, 3200, 3300,
+ 1400, 1800, 2500, 2600, 3200, 3300,
+ 1700, 2000, 2400, 2600, 3100, 3200,
+ 1800, 1900, 2400, 2600, 3000, 3300,
+ 2000, 2300, 2700, 2900, 3300, 3400,
+ 1900, 2300, 2900, 3100, 3400, 3500,
+ 1900, 2100, 2700, 3000, 3300, 3400,
+ 1800, 1900, 2300, 2700, 3100, 3300,
+ 1800, 1900, 2200, 2500, 3100, 3300,
+ 1700, 1800, 2100, 2400, 3000, 3300,
+ 1700, 1800, 2200, 2400, 3100, 3300,
+ 1400, 1900, 2100, 2300, 3200, 3300,
+ 1300, 1800, 2000, 2300, 3200, 3300,
+ 1300, 1800, 1900, 2500, 3200, 3300,
+ 1300, 1900, 2100, 2600, 3200, 3300,
+ 2000, 2100, 2400, 2500, 3100, 3400,
+ 2100, 2200, 2400, 2500, 3100, 3400,
+ 2100, 2400, 2800, 2900, 3100, 3300,
+ 2000, 2200, 2600, 2900, 3200, 3300,
+ 2100, 2200, 2700, 2800, 3200, 3300,
+ 2000, 2100, 2700, 2800, 3200, 3300,
+ 2000, 2100, 2600, 2800, 3200, 3400,
+ 1900, 2000, 2600, 2700, 3300, 3400,
+ 1800, 1900, 2500, 2700, 3300, 3400,
+ 2000, 2100, 2600, 2700, 3200, 3300,
+ 2000, 2100, 2600, 2700, 3100, 3400,
+ 1900, 2100, 2600, 2700, 3200, 3400,
+ 1800, 2000, 2600, 2700, 3300, 3400,
+ 1800, 2000, 2600, 2700, 3300, 3500,
+ 1700, 1900, 2500, 2700, 3200, 3400,
+ 1800, 2100, 2700, 2900, 3200, 3400,
+ 1900, 2200, 2600, 2900, 3200, 3300,
+ 1900, 2200, 2700, 2900, 3200, 3400,
+ 1800, 2200, 2700, 3000, 3200, 3400,
+ 1800, 2100, 2700, 2900, 3300, 3400,
+ 1900, 2200, 2600, 2900, 3300, 3500,
+ 1700, 2100, 2500, 2800, 3400, 3500,
+ 1600, 1900, 2400, 2600, 3200, 3400,
+ 1600, 1900, 2400, 2500, 3300, 3400,
+ 1700, 2000, 2400, 2500, 3200, 3400,
+ 1700, 2000, 2300, 2500, 3200, 3300,
+ 1700, 2000, 2300, 2400, 2900, 3200,
+ 1900, 2000, 2600, 2700, 3100, 3200,
+ 1900, 2000, 2600, 2700, 3100, 3400,
+ 1800, 2000, 2600, 2700, 3100, 3300,
+ 1400, 1800, 2300, 2600, 3000, 3200,
+ 1300, 1800, 2200, 2500, 3100, 3300,
+ 1300, 1900, 2200, 2600, 3100, 3300,
+ 1400, 1800, 2100, 2500, 3000, 3200,
+ 1300, 1600, 1700, 2500, 3100, 3200,
+ 1300, 1600, 1700, 2400, 3100, 3200,
+ 1300, 1600, 1800, 2300, 3100, 3200,
+ 1500, 1800, 2400, 2500, 3100, 3200,
+ 1500, 1900, 2500, 2600, 3000, 3200,
+ 1800, 2200, 2600, 2800, 3200, 3400,
+ 1800, 2000, 2500, 2700, 3100, 3300,
+ 1700, 1900, 2400, 2700, 3100, 3300,
+ 1800, 1900, 2500, 2700, 3100, 3300,
+ 1800, 1900, 2600, 2700, 3000, 3300,
+ 2100, 2200, 2600, 2700, 3200, 3300,
+ 2100, 2200, 2600, 2700, 3300, 3400,
+ 1900, 2100, 2300, 2500, 3300, 3400,
+ 1700, 2100, 2500, 2800, 3100, 3300,
+ 1600, 2100, 2500, 2700, 3100, 3300,
+ 1500, 1900, 2400, 2700, 3100, 3300,
+ 1200, 1700, 1800, 2100, 3200, 3400,
+ 1400, 1700, 1800, 2200, 3300, 3400,
+ 1600, 1800, 1900, 2400, 3200, 3300,
+ 1700, 1900, 2000, 2500, 3100, 3200,
+ 1700, 1900, 2100, 2400, 2900, 3100,
+ 1800, 2000, 2200, 2400, 2800, 3200,
+ 1900, 2100, 2300, 2600, 2900, 3300,
+ 1900, 2100, 2300, 2600, 3200, 3400,
+ 2000, 2100, 2400, 2500, 3300, 3400,
+ 1800, 1900, 2400, 2500, 3200, 3500,
+ 1700, 1900, 2500, 2700, 3200, 3300,
+ 1800, 2000, 2600, 3000, 3300, 3400,
+ 1900, 2000, 2500, 2700, 2900, 3200,
+ 1900, 2000, 2500, 2700, 2900, 3100,
+ 1900, 2000, 2400, 2600, 2900, 3200,
+ 1700, 2000, 2300, 2600, 2900, 3200,
+ 1800, 2000, 2300, 2600, 2900, 3200,
+ 1900, 2000, 2400, 2600, 2900, 3300,
+ 1900, 2000, 2400, 2600, 3000, 3300,
+ 1900, 2000, 2500, 2600, 3100, 3400,
+ 1600, 1800, 2200, 2600, 3000, 3300,
+ 1600, 1800, 2200, 2500, 3000, 3300,
+ 1700, 1900, 2300, 2600, 3000, 3200,
+ 1800, 1900, 2300, 2600, 3000, 3200,
+ 1800, 1900, 2400, 2500, 3000, 3400,
+ 1700, 1800, 2400, 2500, 3200, 3400,
+ 1600, 1700, 2400, 2600, 3100, 3300,
+ 1600, 1700, 2400, 2500, 3200, 3300,
+ 1500, 1600, 2400, 2500, 3200, 3400,
+ 1400, 1600, 2400, 2500, 3200, 3400,
+ 1300, 1600, 2400, 2500, 3200, 3300,
+ 1400, 2000, 2500, 2700, 3100, 3300,
+ 1700, 1900, 2200, 2500, 3000, 3300,
+ 1700, 1900, 2300, 2500, 3100, 3300,
+ 2000, 2100, 2400, 2600, 3100, 3300,
+ 2000, 2200, 2500, 2600, 3100, 3300,
+ 1900, 2000, 2400, 2500, 3200, 3400,
+ 2100, 2200, 2300, 2400, 3200, 3400,
+ 2000, 2100, 2300, 2500, 3000, 3400,
+ 1600, 1800, 2100, 2500, 3000, 3200,
+ 1700, 1800, 2200, 2700, 3200, 3300,
+ 1800, 1900, 2400, 2800, 3200, 3400,
+ 1800, 2000, 2500, 2800, 3200, 3400,
+ 1700, 2100, 2600, 2900, 3300, 3500,
+ 1800, 2200, 2600, 2900, 3300, 3500,
+ 1700, 2200, 2600, 2900, 3300, 3400,
+ 1700, 2100, 2500, 2800, 3200, 3400,
+ 1700, 1900, 2600, 2700, 3300, 3400,
+ 1700, 1800, 2600, 2700, 3100, 3400,
+ 1700, 1800, 2600, 2700, 3200, 3400,
+ 1700, 1900, 2700, 2800, 3200, 3400,
+ 1600, 1900, 2700, 2800, 3200, 3300,
+ 1400, 1900, 2800, 2900, 3200, 3300,
+ 1600, 2000, 2600, 2700, 3200, 3300,
+ 1700, 2000, 2600, 2700, 3200, 3300,
+ 1700, 2000, 2600, 2700, 3200, 3400,
+ 1700, 2000, 2600, 2700, 3300, 3400,
+ 1700, 1900, 2500, 2600, 3300, 3400,
+ 1700, 1800, 2500, 2700, 3100, 3300,
+ 1700, 1900, 2500, 2800, 3300, 3400,
+ 1700, 2000, 2400, 2800, 3300, 3400,
+ 1600, 1800, 2100, 2400, 3100, 3200,
+ 1700, 1800, 2000, 2700, 3100, 3200,
+ 1700, 1900, 2100, 2700, 3100, 3200,
+ 1800, 2000, 2200, 2700, 3100, 3200,
+ 1900, 2000, 2300, 2700, 3100, 3200,
+ 1900, 2100, 2300, 2700, 3100, 3200,
+ 1900, 2100, 2400, 2700, 3100, 3200,
+ 2000, 2100, 2400, 2700, 3100, 3200,
+ 2000, 2200, 2400, 2700, 3100, 3200,
+ 1900, 2100, 2300, 2600, 3100, 3200,
+ 1800, 2100, 2200, 2600, 3100, 3200,
+ 1600, 2000, 2200, 2600, 3100, 3200,
+ 1500, 2000, 2200, 2700, 3100, 3200,
+ 1500, 1900, 2200, 2700, 3100, 3200,
+ 1500, 1800, 2200, 2600, 3100, 3200,
+ 1800, 2100, 2600, 2700, 3100, 3300,
+ 1700, 2100, 2600, 2700, 3100, 3300,
+ 1500, 1800, 2600, 2700, 3200, 3400,
+ 1200, 1400, 2500, 2700, 3200, 3400,
+ 1400, 1700, 2400, 2600, 3200, 3400,
+ 1400, 1600, 2400, 2600, 3100, 3400,
+ 1500, 1700, 2500, 2600, 3000, 3300,
+ 1600, 1800, 2500, 2600, 3100, 3300,
+ 1700, 1900, 2500, 2600, 3100, 3300,
+ 1800, 1900, 2400, 2600, 3000, 3400,
+ 2000, 2100, 2500, 2600, 3000, 3300,
+ 2100, 2200, 2500, 2600, 3100, 3400,
+ 2200, 2300, 2500, 2600, 3100, 3400,
+ 1400, 1900, 2300, 2400, 2800, 3200,
+ 1400, 1900, 2300, 2400, 2700, 3100,
+ 1500, 1700, 2300, 2400, 2800, 3200,
+ 1600, 1700, 2100, 2500, 3000, 3300,
+ 1700, 2000, 2400, 2800, 3000, 3300,
+ 1800, 2000, 2600, 2800, 3100, 3300,
+ 1800, 2000, 2500, 2700, 3200, 3300,
+ 1800, 2000, 2600, 2700, 3200, 3400,
+ 1800, 2000, 2600, 2700, 3200, 3300,
+ 1800, 2200, 2600, 2800, 3200, 3300,
+ 1800, 2100, 2600, 2800, 3100, 3300,
+ 1700, 1900, 2500, 2700, 3000, 3300,
+ 1800, 1900, 2500, 2700, 3000, 3300,
+ 1900, 2000, 2500, 2700, 3100, 3300,
+ 1900, 2000, 2500, 2700, 3100, 3400,
+ 1700, 1900, 2600, 2800, 3200, 3400,
+ 1600, 1900, 2600, 2800, 3300, 3400,
+ 1500, 1800, 2500, 2700, 3300, 3400,
+ 1500, 1900, 2400, 2500, 3200, 3400,
+ 1200, 1800, 2200, 2300, 3100, 3200,
+ 1400, 1900, 2300, 2600, 3000, 3300,
+ 1300, 1400, 2300, 2400, 2800, 3100,
+ 1300, 1400, 2300, 2500, 3000, 3200,
+ 1300, 1600, 2400, 2600, 3000, 3200,
+ 1400, 1600, 2400, 2500, 2900, 3200,
+ 1500, 1600, 2400, 2600, 3000, 3200,
+ 1500, 1700, 2400, 2600, 2900, 3200,
+ 1600, 1800, 2400, 2600, 2900, 3100,
+ 1800, 2000, 2500, 2700, 3000, 3300,
+ 1900, 2100, 2600, 2700, 3000, 3300,
+ 1900, 2100, 2500, 2700, 3000, 3200,
+ 2000, 2100, 2400, 2700, 3100, 3300,
+ 2000, 2200, 2400, 2700, 3100, 3300,
+ 1900, 2300, 2600, 2700, 3000, 3200,
+ 2000, 2200, 2500, 2600, 3000, 3200,
+ 1900, 2000, 2500, 2600, 3000, 3300,
+ 1800, 2000, 2400, 2600, 3000, 3300,
+ 1500, 1900, 2300, 2500, 2700, 3000,
+ 1500, 2000, 2400, 2500, 2700, 3100,
+ 1200, 1900, 2300, 2500, 2800, 3000,
+ 1300, 1800, 2200, 2300, 3100, 3200,
+ 1600, 1900, 2400, 2500, 3100, 3200,
+ 2100, 2200, 2600, 2700, 3100, 3300,
+ 2100, 2200, 2600, 2700, 3000, 3300,
+ 2000, 2200, 2600, 2700, 3100, 3300,
+ 2000, 2100, 2400, 2600, 3200, 3300,
+ 1800, 2000, 2300, 2400, 3100, 3300,
+ 1500, 2000, 2200, 2500, 3200, 3300,
+ 1600, 1900, 2400, 2600, 3100, 3300,
+ 1500, 1800, 2200, 2600, 3000, 3200,
+ 1500, 1800, 2100, 2600, 2900, 3100,
+ 1400, 1700, 1900, 2300, 2800, 3000,
+ 1500, 1700, 1900, 2200, 2800, 2900,
+ 1500, 1700, 2000, 2200, 2900, 3000,
+ 1500, 1700, 2100, 2300, 2900, 3000,
+ 1500, 1800, 2200, 2300, 3000, 3100,
+ 1500, 1800, 2200, 2400, 3000, 3100,
+ 1600, 1800, 2300, 2400, 3100, 3200,
+ 1600, 1800, 2300, 2500, 3100, 3200,
+ 1600, 1800, 2400, 2500, 3100, 3200,
+ 1600, 1800, 2400, 2500, 3100, 3300,
+ 1600, 1800, 2400, 2500, 3200, 3300,
+ 1500, 1700, 2400, 2500, 3200, 3300,
+ 1500, 1700, 2300, 2500, 2900, 3300,
+ 1800, 2100, 2500, 2600, 3200, 3300,
+ 1900, 2100, 2400, 2500, 3100, 3400,
+ 1900, 2100, 2200, 2500, 3100, 3300,
+ 1700, 1800, 2200, 2500, 2900, 3300,
+ 1700, 1800, 2400, 2500, 3000, 3300,
+ 1600, 1700, 2400, 2500, 3100, 3300,
+ 1500, 1700, 2400, 2500, 3100, 3300,
+ 1400, 1700, 2500, 2600, 3100, 3200,
+ 1300, 1600, 2500, 2600, 3100, 3200,
+ 1200, 1600, 2500, 2600, 3100, 3200,
+ 1100, 1700, 2600, 2700, 3100, 3200,
+ 1100, 1500, 2600, 2700, 3100, 3200,
+ 1100, 1500, 2600, 2700, 3100, 3300,
+ 1100, 1500, 2500, 2700, 3000, 3300,
+ 1000, 1600, 2600, 2700, 3100, 3300,
+ 1300, 1600, 2600, 2700, 3100, 3300,
+ 1300, 1600, 2600, 2700, 3200, 3300,
+ 1500, 1700, 2500, 2600, 3100, 3300,
+ 1700, 1800, 2500, 2600, 3100, 3300,
+ 1700, 1900, 2500, 2600, 3200, 3300,
+ 1800, 1900, 2500, 2600, 3200, 3300,
+ 1800, 2000, 2500, 2700, 3100, 3400,
+ 1800, 2100, 2500, 2700, 3100, 3300,
+ 1900, 2200, 2500, 2700, 3200, 3300,
+ 1900, 2200, 2400, 2600, 3100, 3300,
+ 1900, 2300, 2500, 2600, 3100, 3300,
+ 1900, 2000, 2200, 2400, 3200, 3300,
+ 1600, 1900, 2200, 2300, 3200, 3300,
+ 1400, 1600, 2200, 2400, 3100, 3200,
+ 1100, 1500, 2300, 2500, 3000, 3100,
+ 1400, 1700, 2500, 2700, 3200, 3300,
+ 1500, 1800, 2400, 2500, 3200, 3300,
+ 1800, 2100, 2500, 2800, 3100, 3300,
+ 1800, 1900, 2300, 2500, 3200, 3400,
+ 1700, 1900, 2300, 2500, 3200, 3400,
+ 1800, 2100, 2500, 2800, 3200, 3400,
+ 1800, 2000, 2500, 2800, 3200, 3300,
+ 1900, 2100, 2600, 2800, 3100, 3400,
+ 1700, 2100, 2600, 2700, 3200, 3400,
+ 1800, 2100, 2600, 2700, 3300, 3500,
+ 1900, 2000, 2500, 2600, 3300, 3400,
+ 1600, 1900, 2200, 2400, 3200, 3300,
+ 1400, 2000, 2300, 2600, 3100, 3200,
+ 1300, 1800, 2300, 2400, 3000, 3100,
+ 1300, 1700, 2300, 2500, 3000, 3100,
+ 1600, 1700, 2600, 2700, 3200, 3300,
+ 1700, 2000, 2300, 2400, 3100, 3300,
+ 2200, 2300, 2600, 2800, 3200, 3400,
+ 2100, 2300, 2500, 2900, 3200, 3300,
+ 2200, 2300, 2500, 2900, 3200, 3300,
+ 2000, 2300, 2500, 2700, 3200, 3300,
+ 2200, 2400, 2500, 2700, 3200, 3300,
+ 2200, 2400, 2600, 2800, 3200, 3300,
+ 1700, 2000, 2400, 2700, 3000, 3200,
+ 1700, 1900, 2500, 2700, 3000, 3200,
+ 1700, 1900, 2600, 2700, 3100, 3300,
+ 1500, 1800, 2600, 2700, 3100, 3300,
+ 1600, 1700, 2600, 2700, 2900, 3300,
+ 1600, 1700, 2600, 2800, 3000, 3300,
+ 1700, 2000, 2700, 2800, 3100, 3400,
+ 1600, 1900, 2500, 2700, 3000, 3300,
+ 1800, 2200, 2800, 2900, 3300, 3400,
+ 2000, 2500, 2800, 2900, 3400, 3500,
+ 2000, 2400, 2800, 2900, 3400, 3500,
+ 2000, 2300, 2700, 2800, 3200, 3400,
+ 1600, 1700, 2400, 2600, 3200, 3300,
+ 1500, 1900, 2400, 2500, 3200, 3300,
+ 1400, 1900, 2400, 2500, 3200, 3300,
+ 1400, 1900, 2500, 2600, 3200, 3300,
+ 1300, 1900, 2500, 2600, 3200, 3300,
+ 1300, 1700, 2500, 2600, 3100, 3300,
+ 1300, 1500, 2500, 2600, 3100, 3300,
+ 1200, 1400, 2400, 2500, 3100, 3300,
+ 1200, 1500, 2400, 2500, 3100, 3300,
+ 1200, 1600, 2400, 2500, 3100, 3300,
+ 1200, 1700, 2500, 2600, 3100, 3300,
+ 1200, 1700, 2500, 2600, 3200, 3300,
+ 1200, 1800, 2500, 2600, 3200, 3300,
+ 1200, 1800, 2400, 2500, 3200, 3300,
+ 1200, 1800, 2400, 2500, 3100, 3300,
+ 1200, 1700, 2400, 2500, 3100, 3200,
+ 1200, 1600, 2400, 2500, 3000, 3200,
+ 1200, 1600, 2400, 2500, 2900, 3100,
+ 1200, 1700, 2400, 2500, 3000, 3300,
+ 1300, 1700, 2400, 2500, 3100, 3300,
+ 1200, 1700, 2400, 2500, 3000, 3100,
+ 1200, 1700, 2300, 2400, 3000, 3100,
+ 1600, 2000, 2300, 2600, 3000, 3300,
+ 1400, 1600, 1900, 2200, 3000, 3100,
+ 1400, 1600, 1800, 2100, 3000, 3100,
+ 1300, 1500, 1600, 2000, 3100, 3200,
+ 1300, 1500, 1700, 1900, 3100, 3200,
+ 1400, 1600, 1700, 1900, 3100, 3200,
+ 1600, 1700, 2000, 2100, 3100, 3200,
+ 1600, 1800, 2100, 2200, 3100, 3200,
+ 1800, 1900, 2300, 2400, 3200, 3300,
+ 1900, 2100, 2600, 2700, 3100, 3400,
+ 1900, 2000, 2500, 2600, 3000, 3400,
+ 1800, 2100, 2600, 2700, 3200, 3400,
+ 1800, 2300, 2600, 2800, 3300, 3500,
+ 1600, 2100, 2400, 2600, 3200, 3300,
+ 1300, 1900, 2500, 2600, 3100, 3300,
+ 1300, 1800, 2500, 2600, 3100, 3300,
+ 1400, 1800, 2600, 2700, 3100, 3300,
+ 1600, 1800, 2500, 2700, 3100, 3300,
+ 1600, 1800, 2500, 2600, 3200, 3300,
+ 1700, 1800, 2500, 2600, 3200, 3300,
+ 1900, 2000, 2500, 2700, 2900, 3300,
+ 2000, 2100, 2400, 2600, 2900, 3200,
+ 2000, 2100, 2400, 2600, 3000, 3300,
+ 2100, 2200, 2400, 2600, 3000, 3300,
+ 2000, 2100, 2500, 2600, 3100, 3400,
+ 1900, 2000, 2400, 2600, 3000, 3400,
+ 1800, 1900, 2300, 2500, 2900, 3400,
+ 1700, 1800, 2500, 2700, 3100, 3400,
+ 1700, 1900, 2500, 2700, 3100, 3400,
+ 1800, 1900, 2700, 2800, 3200, 3400,
+ 2100, 2200, 2600, 2800, 3100, 3400,
+ 2200, 2300, 2600, 2800, 3100, 3400,
+ 1800, 2300, 2500, 2700, 3100, 3300,
+ 1500, 2000, 2400, 2500, 2800, 3100,
+ 1600, 2000, 2400, 2500, 2800, 3100,
+ 1600, 2000, 2400, 2500, 2800, 3200,
+ 1600, 2000, 2400, 2500, 2900, 3300,
+ 1800, 2200, 2500, 2600, 3000, 3300,
+ 2100, 2300, 2500, 2600, 3100, 3300,
+ 2100, 2200, 2600, 2700, 3100, 3200,
+ 1800, 1900, 2600, 2700, 3100, 3200,
+ 1800, 1900, 2600, 2700, 3100, 3300,
+ 1700, 1800, 2600, 2700, 3100, 3300,
+ 1700, 1800, 2600, 2700, 3200, 3300,
+ 1600, 1700, 2600, 2700, 3200, 3400,
+ 1600, 1700, 2500, 2700, 3200, 3300,
+ 1500, 1800, 2400, 2500, 3000, 3300,
+ 1500, 1900, 2300, 2500, 3000, 3200,
+ 1700, 2100, 2300, 2600, 3100, 3300,
+ 1800, 2000, 2700, 2800, 3100, 3300,
+ 1700, 1800, 2500, 2700, 2900, 3300,
+ 1600, 1800, 2500, 2700, 3000, 3300,
+ 1700, 1800, 2400, 2600, 3100, 3300,
+ 1700, 1800, 2400, 2500, 3200, 3300,
+ 1800, 1900, 2400, 2500, 3200, 3300,
+ 1900, 2000, 2400, 2500, 3200, 3300,
+ 2000, 2100, 2300, 2500, 3200, 3400,
+ 2000, 2100, 2200, 2400, 3200, 3400,
+ 2000, 2100, 2300, 2400, 3100, 3400,
+ 1700, 1900, 2400, 2500, 3200, 3400,
+ 1700, 1900, 2400, 2500, 3100, 3400,
+ 1700, 1800, 2400, 2600, 3300, 3400,
+ 1700, 1800, 2500, 2600, 3300, 3400,
+ 1600, 1900, 2500, 2600, 3300, 3400,
+ 1700, 1900, 2600, 2800, 3100, 3300,
+ 1700, 2100, 2600, 2700, 3300, 3400,
+ 1800, 2000, 2400, 2500, 3100, 3300,
+ 2000, 2100, 2300, 2400, 3200, 3400,
+ 1400, 1900, 2300, 2400, 3000, 3300,
+ 1400, 2000, 2300, 2500, 3000, 3100,
+ 1400, 1700, 2500, 2600, 3100, 3300,
+ 1300, 1600, 2400, 2600, 3100, 3300,
+ 1300, 1600, 2400, 2500, 3200, 3400,
+ 1500, 2000, 2500, 2700, 3200, 3400,
+ 1800, 2100, 2500, 2900, 3200, 3400,
+ 1800, 2200, 2500, 2800, 3300, 3400,
+ 1700, 2000, 2500, 2900, 3300, 3400,
+ 1700, 2100, 2600, 2900, 3400, 3500,
+ 1500, 1900, 2400, 2800, 3300, 3400,
+ 1800, 2100, 2500, 2800, 3300, 3400,
+ 1700, 2000, 2600, 2800, 3300, 3400,
+ 1700, 2100, 2600, 2800, 3200, 3400,
+ 1900, 2200, 2600, 2800, 3200, 3300,
+ 1900, 2100, 2600, 2800, 3200, 3300,
+ 1800, 2100, 2700, 2800, 3300, 3400,
+ 1700, 2100, 2700, 2800, 3200, 3400,
+ 1800, 2200, 2600, 2700, 3200, 3400,
+ 1800, 2200, 2600, 2700, 3300, 3400,
+ 1800, 2300, 2600, 2700, 3300, 3400,
+ 1900, 2300, 2500, 2700, 3300, 3400,
+ 1800, 2200, 2500, 2800, 3200, 3400,
+ 1800, 2200, 2500, 2700, 3100, 3300,
+ 1700, 2200, 2400, 2600, 3100, 3200,
+ 1800, 2000, 2300, 2500, 3200, 3300,
+ 1800, 2000, 2200, 2500, 3300, 3400,
+ 1800, 2000, 2200, 2600, 3300, 3400,
+ 1500, 1800, 1900, 2400, 3200, 3300,
+ 1500, 1700, 1900, 2500, 3200, 3300,
+ 1500, 1800, 1900, 2500, 3200, 3300,
+ 1600, 1800, 2000, 2400, 3300, 3400,
+ 1500, 1700, 2200, 2600, 3000, 3200,
+ 1400, 1700, 2000, 2600, 3000, 3200,
+ 1500, 1900, 2400, 2600, 3100, 3200,
+ 1400, 1900, 2500, 2600, 3100, 3300,
+ 1200, 1600, 2500, 2700, 3100, 3300,
+ 1200, 1800, 2500, 2600, 3100, 3200,
+ 1400, 1800, 2300, 2400, 3100, 3200,
+ 1400, 1700, 2200, 2300, 3200, 3300,
+ 1800, 1900, 2200, 2300, 3300, 3400,
+ 1800, 2100, 2300, 2400, 2900, 3200,
+ 1900, 2100, 2300, 2500, 3000, 3300,
+ 1900, 2100, 2400, 2600, 3300, 3400,
+ 1600, 1900, 2400, 2500, 3200, 3300,
+ 1500, 1700, 2300, 2400, 3200, 3300,
+ 1500, 1900, 2300, 2500, 3200, 3300,
+ 1600, 2000, 2500, 2700, 3200, 3300,
+ 1900, 2200, 2500, 2700, 3300, 3400,
+ 1800, 2300, 2500, 2700, 3300, 3400,
+ 1800, 2400, 2500, 2900, 3300, 3400,
+ 1900, 2400, 2600, 3000, 3300, 3400,
+ 2000, 2400, 2700, 3000, 3400, 3500,
+ 1800, 2100, 2500, 2900, 3200, 3300,
+ 1700, 2100, 2500, 2900, 3200, 3400,
+ 1800, 2100, 2600, 2800, 3100, 3400,
+ 1800, 2200, 2700, 2800, 3200, 3400,
+ 1800, 2300, 2700, 2900, 3300, 3500,
+ 1400, 2000, 2600, 2700, 3200, 3400,
+ 1300, 1800, 2200, 2300, 3000, 3100,
+ 1300, 1700, 2100, 2200, 3100, 3200,
+ 1400, 1700, 2000, 2200, 3000, 3100,
+ 1400, 1600, 2000, 2100, 3000, 3100,
+ 1500, 1800, 2000, 2300, 3100, 3200,
+ 1600, 1800, 2000, 2300, 3100, 3200,
+ 1600, 1800, 2000, 2200, 3100, 3200,
+ 1700, 2000, 2200, 2300, 3000, 3200,
+ 1700, 2100, 2400, 2800, 3100, 3300,
+ 1800, 2000, 2600, 2800, 3000, 3200,
+ 1700, 1900, 2600, 2700, 3200, 3400,
+ 1600, 1700, 2400, 2600, 3200, 3400,
+ 1600, 1700, 2400, 2500, 3200, 3400,
+ 1700, 2100, 2500, 2800, 3200, 3300,
+ 1700, 2200, 2500, 2800, 3200, 3300,
+ 1700, 2100, 2400, 2600, 3200, 3300,
+ 1700, 1900, 2400, 2600, 3200, 3300,
+ 1600, 1900, 2200, 2500, 3100, 3300,
+ 1500, 1900, 2100, 2400, 3100, 3300,
+ 1500, 1600, 2000, 2300, 3000, 3200,
+ 1500, 1700, 2100, 2500, 3100, 3300,
+ 1600, 1800, 2300, 2700, 3100, 3300,
+ 1600, 1700, 2300, 2600, 3100, 3200,
+ 1500, 1700, 2300, 2500, 3000, 3200,
+ 1400, 1700, 2400, 2500, 3000, 3200,
+ 1200, 1500, 2500, 2600, 3000, 3100,
+ 1100, 1900, 2600, 2700, 3000, 3100,
+ 1500, 2000, 2700, 2800, 3200, 3400,
+ 1700, 2100, 2700, 2800, 3300, 3400,
+ 1800, 2200, 2700, 2800, 3300, 3400,
+ 1800, 2400, 2700, 2800, 3200, 3300,
+ 1800, 2300, 2500, 2600, 3100, 3200,
+ 1500, 1800, 2100, 2400, 3000, 3200,
+ 1400, 1600, 1800, 2200, 3000, 3100,
+ 1300, 1600, 1700, 2100, 3000, 3100,
+ 1200, 1400, 1600, 2400, 3000, 3100,
+ 1300, 1500, 1600, 2100, 3000, 3100,
+ 1400, 1600, 1700, 2100, 3000, 3100,
+ 1400, 1700, 2100, 2300, 3100, 3200,
+ 1400, 1700, 2200, 2300, 3100, 3200,
+ 1400, 1600, 2200, 2300, 3100, 3200,
+ 1400, 1700, 2200, 2400, 3100, 3200,
+ 1400, 1700, 2300, 2400, 3100, 3200,
+ 1400, 1600, 2300, 2400, 3100, 3200,
+ 1400, 1600, 2200, 2300, 3000, 3200,
+ 1500, 2000, 2400, 2600, 3200, 3300,
+ 1700, 2000, 2700, 2800, 3200, 3400,
+ 2100, 2400, 2800, 2900, 3200, 3400,
+ 2000, 2500, 2700, 2800, 3400, 3500,
+ 2100, 2600, 2800, 2900, 3400, 3500,
+ 2000, 2500, 2700, 2800, 3300, 3400,
+ 1900, 2100, 2700, 2800, 3200, 3400,
+ 2100, 2200, 2700, 2800, 3200, 3400,
+ 2100, 2200, 2700, 2900, 3300, 3400,
+ 2200, 2300, 2700, 2800, 3200, 3400,
+ 1700, 2100, 2400, 2700, 3200, 3400,
+ 1600, 2100, 2400, 2600, 2900, 3200,
+ 1500, 2100, 2400, 2500, 2800, 3100,
+ 1600, 2100, 2400, 2500, 2800, 3200,
+ 1600, 2100, 2400, 2500, 2900, 3200,
+ 1600, 2100, 2400, 2500, 3000, 3200,
+ 1600, 2100, 2300, 2500, 3200, 3300,
+ 1700, 1800, 2200, 2600, 3100, 3300,
+ 1700, 1900, 2300, 2600, 3100, 3300,
+ 1800, 1900, 2300, 2500, 3100, 3300,
+ 1800, 1900, 2400, 2500, 3100, 3200,
+ 1600, 1800, 2200, 2500, 3100, 3300,
+ 1500, 1700, 1900, 2200, 3100, 3200,
+ 1500, 1700, 1900, 2100, 3100, 3200,
+ 1500, 1700, 1900, 2300, 3200, 3300,
+ 1500, 1700, 1900, 2400, 3200, 3300,
+ 1500, 1700, 1800, 2400, 3200, 3300,
+ 1500, 1700, 1900, 2200, 3200, 3300,
+ 1500, 1700, 1900, 2100, 3200, 3300,
+ 1500, 1600, 1900, 2000, 3100, 3200,
+ 1500, 1700, 2000, 2100, 3200, 3300,
+ 1600, 1700, 2000, 2100, 3200, 3300,
+ 1600, 1800, 2100, 2300, 3200, 3300,
+ 1700, 1900, 2300, 2500, 3100, 3200,
+ 1700, 2000, 2400, 2600, 3000, 3100,
+ 1700, 2100, 2400, 2600, 3000, 3100,
+ 1600, 2000, 2400, 2600, 2900, 3100,
+ 1800, 2200, 2600, 2800, 3000, 3200,
+ 2000, 2400, 2500, 2800, 3100, 3200,
+ 2100, 2500, 2600, 2800, 3200, 3300,
+ 2200, 2500, 2700, 3000, 3200, 3300,
+ 2100, 2500, 2700, 3000, 3200, 3300,
+ 2200, 2500, 2600, 3000, 3200, 3300,
+ 2200, 2500, 2600, 2900, 3200, 3300,
+ 2200, 2400, 2600, 2800, 3100, 3300,
+ 2000, 2300, 2500, 2700, 3100, 3200,
+ 2000, 2200, 2500, 2700, 3100, 3200,
+ 2000, 2300, 2500, 2800, 3100, 3200,
+ 2000, 2300, 2400, 2800, 3100, 3200,
+ 2100, 2200, 2500, 2800, 3100, 3200,
+ 2000, 2100, 2500, 2800, 3200, 3300,
+ 1900, 2000, 2200, 2500, 3200, 3300,
+ 1600, 1800, 2100, 2400, 3100, 3300,
+ 1500, 1600, 1800, 2100, 3200, 3300,
+ 1500, 1700, 1800, 2100, 3200, 3300,
+ 1500, 1700, 1800, 2300, 3200, 3300,
+ 2000, 2200, 2400, 2600, 3000, 3200,
+ 2000, 2400, 2600, 2800, 3100, 3300,
+ 2000, 2400, 2500, 2700, 3100, 3300,
+ 1800, 2200, 2500, 2600, 3100, 3300,
+ 1600, 1800, 2400, 2500, 3000, 3200,
+ 1500, 1800, 2400, 2500, 3000, 3100,
+ 1800, 2000, 2200, 2700, 3000, 3300,
+ 1600, 1900, 2100, 2600, 3000, 3200,
+ 1500, 1700, 1900, 2300, 3000, 3100,
+ 1500, 1700, 1900, 2200, 3000, 3100,
+ 1600, 1700, 2200, 2400, 2900, 3000,
+ 1600, 1800, 2200, 2400, 2900, 3000,
+ 1800, 2300, 2600, 2700, 3200, 3400,
+ 1800, 1900, 2500, 2600, 3300, 3400,
+ 1800, 1900, 2400, 2600, 3300, 3400,
+ 1700, 1900, 2300, 2500, 3300, 3400,
+ 1600, 1800, 2300, 2400, 3200, 3300,
+ 1300, 1900, 2300, 2400, 3100, 3200,
+ 1600, 1700, 2400, 2600, 3100, 3200,
+ 2000, 2100, 2500, 2600, 3200, 3300,
+ 2100, 2200, 2400, 2600, 3200, 3400,
+ 1700, 2000, 2400, 2600, 3100, 3400,
+ 1700, 1800, 2400, 2500, 3100, 3300,
+ 1600, 1900, 2300, 2400, 3100, 3200,
+ 1600, 1900, 2200, 2500, 3000, 3100,
+ 1500, 1800, 2000, 2300, 3000, 3100,
+ 1500, 1700, 1900, 2100, 2900, 3000,
+ 1400, 1600, 2400, 2700, 2900, 3100,
+ 1400, 1600, 2300, 2600, 3000, 3100,
+ 1500, 1600, 2300, 2500, 2900, 3100,
+ 1600, 1700, 2400, 2600, 3000, 3200,
+ 1600, 1800, 2400, 2600, 3100, 3200,
+ 1600, 1900, 2400, 2600, 3100, 3200,
+ 1700, 2100, 2400, 2600, 3100, 3200,
+ 1600, 2000, 2300, 2600, 3100, 3200,
+ 1400, 1600, 2200, 2300, 3100, 3300,
+ 1400, 1600, 2200, 2300, 3200, 3300,
+ 1300, 1800, 2300, 2500, 3300, 3400,
+ 1200, 1900, 2400, 2500, 3300, 3400,
+ 1200, 1700, 2400, 2500, 3300, 3400,
+ 1500, 1700, 2300, 2500, 3100, 3200,
+ 1900, 2000, 2300, 2400, 3200, 3300,
+ 2200, 2300, 2500, 2700, 3200, 3300,
+ 2100, 2300, 2500, 2800, 3300, 3400,
+ 1300, 1900, 2300, 2400, 3100, 3300,
+ 1800, 2000, 2400, 2700, 3200, 3300,
+ 1500, 2000, 2300, 2400, 3000, 3300,
+ 1600, 2000, 2400, 2700, 3000, 3200,
+ 1800, 2100, 2400, 2600, 3000, 3200,
+ 1800, 2100, 2400, 2600, 3000, 3300,
+ 1800, 2100, 2400, 2500, 3100, 3300,
+ 1700, 2100, 2300, 2600, 3100, 3200,
+ 1600, 2000, 2200, 2500, 3200, 3300,
+ 1500, 1800, 2200, 2300, 3200, 3400,
+ 1400, 1600, 2200, 2300, 3200, 3400,
+ 1300, 1500, 2200, 2300, 3200, 3300,
+ 1200, 1600, 2300, 2400, 3300, 3400,
+ 1200, 1500, 2300, 2400, 3200, 3400,
+ 1200, 1400, 2300, 2400, 3100, 3400,
+ 1300, 1500, 2400, 2500, 3200, 3400,
+ 1700, 2300, 2600, 2700, 3300, 3400,
+ 1800, 2400, 2700, 3000, 3300, 3400,
+ 1800, 2300, 2700, 2800, 3200, 3300,
+ 1800, 2200, 2500, 2600, 3300, 3400,
+ 1700, 1900, 2400, 2600, 3200, 3400,
+ 1700, 1800, 2200, 2500, 3200, 3400,
+ 1500, 1700, 2300, 2500, 3100, 3300,
+ 1400, 1700, 2200, 2400, 3000, 3200,
+ 1300, 1600, 2200, 2300, 3000, 3100,
+ 1300, 1900, 2200, 2400, 2900, 3100,
+ 1400, 1900, 2300, 2400, 3000, 3100,
+ 1400, 1900, 2300, 2500, 2900, 3100,
+ 1400, 1800, 2400, 2600, 2800, 3100,
+ 1600, 2000, 2500, 2700, 3100, 3300,
+ 1500, 2000, 2500, 2700, 3200, 3300,
+ 1500, 2100, 2600, 2900, 3300, 3400,
+ 1800, 2300, 2600, 2800, 3300, 3400,
+ 1700, 2200, 2600, 2700, 3300, 3400,
+ 2000, 2200, 2500, 2700, 3000, 3100,
+ 2000, 2300, 2600, 2800, 3100, 3200,
+ 2100, 2400, 2500, 2900, 3200, 3300,
+ 2100, 2300, 2500, 2800, 3100, 3200,
+ 1900, 2200, 2300, 2700, 3100, 3200,
+ 1200, 1900, 2000, 2300, 3100, 3200,
+ 1300, 1600, 1700, 2100, 3200, 3300,
+ 1400, 1600, 1700, 2100, 3200, 3300,
+ 1400, 1600, 1700, 2200, 3200, 3300,
+ 1600, 1700, 2200, 2600, 2900, 3100,
+ 1900, 2300, 2700, 2900, 3200, 3300,
+ 1700, 2100, 2700, 2900, 3200, 3400,
+ 1800, 2100, 2700, 2800, 3100, 3400,
+ 1800, 2100, 2600, 2800, 3000, 3200,
+ 1800, 2100, 2700, 2800, 3200, 3400,
+ 1400, 1600, 2600, 2700, 3000, 3300,
+ 1400, 1500, 2600, 2700, 3000, 3400,
+ 1300, 1400, 2400, 2800, 3000, 3300,
+ 1800, 2200, 2600, 2900, 3200, 3400,
+ 1600, 2100, 2600, 2900, 3200, 3400,
+ 1200, 1700, 2500, 2600, 3000, 3100,
+ 1200, 1800, 2300, 2600, 3000, 3100,
+ 1200, 1800, 2300, 2500, 3000, 3100,
+ 1300, 1700, 2400, 2500, 3000, 3100,
+ 1500, 1800, 2400, 2500, 2900, 3000,
+ 1600, 2300, 2500, 2700, 3000, 3100,
+ 1900, 2200, 2700, 2900, 3100, 3200,
+ 1900, 2200, 2800, 2900, 3100, 3200,
+ 1900, 2300, 2800, 2900, 3200, 3300,
+ 2200, 2500, 2800, 3000, 3300, 3400,
+ 2100, 2500, 2800, 3000, 3300, 3400,
+ 2000, 2400, 2700, 2800, 3300, 3500,
+ 1900, 2200, 2600, 2800, 3300, 3400,
+ 1900, 2100, 2700, 2800, 3300, 3400,
+ 1700, 1900, 2600, 2700, 3000, 3300,
+ 1600, 1700, 2500, 2600, 3100, 3300,
+ 1800, 1900, 2600, 2800, 3100, 3300,
+ 1800, 1900, 2500, 2800, 3000, 3300,
+ 1900, 2000, 2600, 2800, 3100, 3400,
+ 2000, 2100, 2500, 2700, 3000, 3300,
+ 2100, 2200, 2500, 2700, 3000, 3300,
+ 2100, 2200, 2500, 2800, 3000, 3300,
+ 2000, 2100, 2400, 2700, 2900, 3200,
+ 1900, 2000, 2400, 2600, 2800, 3100,
+ 1700, 2000, 2500, 2700, 3100, 3300,
+ 1700, 2100, 2700, 2800, 3100, 3300,
+ 1500, 1700, 2400, 2600, 3100, 3400,
+ 1500, 1600, 2400, 2500, 3000, 3300,
+ 1400, 1600, 2300, 2600, 3100, 3300,
+ 1400, 1500, 2300, 2600, 3100, 3300,
+ 1500, 1600, 2400, 2600, 2900, 3200,
+ 1600, 1700, 2300, 2600, 3000, 3200,
+ 1600, 1700, 2300, 2700, 3000, 3200,
+ 1700, 1800, 2400, 2600, 3000, 3200,
+ 1600, 1700, 2300, 2500, 3100, 3200,
+ 1500, 1600, 2200, 2400, 3100, 3200,
+ 1300, 1800, 2200, 2400, 3100, 3200,
+ 1300, 1800, 2300, 2400, 3000, 3200,
+ 1200, 1700, 2300, 2400, 2900, 3100,
+ 1200, 1800, 2400, 2500, 2900, 3200,
+ 1200, 1800, 2300, 2500, 3100, 3200,
+ 1300, 1800, 2400, 2600, 3200, 3300,
+ 1300, 1700, 2400, 2500, 3200, 3300,
+ 1200, 1700, 2400, 2500, 3200, 3300,
+ 1200, 1500, 2400, 2500, 3200, 3300,
+ 1900, 2100, 2500, 2800, 3100, 3300,
+ 1800, 2000, 2400, 2700, 3000, 3300,
+ 1800, 2000, 2300, 2600, 3000, 3300,
+ 1900, 2000, 2300, 2400, 3200, 3500,
+ 1900, 2000, 2300, 2400, 3100, 3400,
+ 1800, 2000, 2300, 2500, 3200, 3400,
+ 1700, 2000, 2500, 2600, 3300, 3400,
+ 1800, 2100, 2500, 2800, 3100, 3400,
+ 1800, 2000, 2500, 2800, 3100, 3300,
+ 1800, 2100, 2500, 2600, 3100, 3300,
+ 1700, 2100, 2500, 2700, 3100, 3400,
+ 1600, 1700, 2500, 2600, 3200, 3300,
+ 1500, 2200, 2400, 2700, 3200, 3300,
+ 1400, 2000, 2300, 2700, 3300, 3400,
+ 1400, 2000, 2300, 2500, 3300, 3400,
+ 1600, 2000, 2400, 2600, 3100, 3300,
+ 1600, 2000, 2300, 2600, 3300, 3400,
+ 1600, 2100, 2300, 2600, 3300, 3400,
+ 1700, 1900, 2300, 2600, 3300, 3400,
+ 1900, 2000, 2300, 2400, 3300, 3400,
+ 1900, 2000, 2200, 2400, 3300, 3400,
+ 1700, 1800, 2200, 2500, 3000, 3200,
+ 1700, 1800, 2100, 2500, 3000, 3200,
+ 1500, 1700, 2100, 2500, 3000, 3200,
+ 1500, 1600, 2100, 2500, 3000, 3200,
+ 1500, 1700, 2200, 2700, 3100, 3200,
+ 1600, 1900, 2300, 2700, 3200, 3300,
+ 1500, 1700, 1800, 2600, 3200, 3300,
+ 1600, 1900, 2100, 2500, 3100, 3300,
+ 2000, 2300, 2700, 2800, 3100, 3300,
+ 2200, 2500, 2900, 3000, 3200, 3300,
+ 2300, 2500, 2900, 3000, 3200, 3300,
+ 1400, 1900, 2300, 2500, 3200, 3300,
+ 1600, 2000, 2300, 2700, 3200, 3300,
+ 1500, 1900, 2000, 2400, 3200, 3300,
+ 1300, 1800, 2000, 2400, 3300, 3400,
+ 1400, 1900, 2200, 2500, 3200, 3300,
+ 1800, 2200, 2600, 3000, 3300, 3400,
+ 1900, 2200, 2800, 2900, 3300, 3400,
+ 2000, 2500, 2900, 3100, 3200, 3300,
+ 2000, 2400, 2900, 3000, 3300, 3400,
+ 2100, 2400, 2800, 3000, 3200, 3300,
+ 2000, 2400, 2700, 2900, 3200, 3300,
+ 1700, 2100, 2600, 2800, 3200, 3300,
+ 1500, 1900, 2300, 2700, 3100, 3300,
+ 1500, 1800, 2200, 2600, 3200, 3300,
+ 1500, 1700, 2200, 2500, 3200, 3400,
+ 1100, 2200, 2500, 2800, 3200, 3300,
+ 1000, 2100, 2500, 2700, 3200, 3300,
+ 1000, 2000, 2500, 2700, 3200, 3300,
+ 1000, 2000, 2400, 2600, 3200, 3300,
+ 1100, 1900, 2400, 2600, 3100, 3200,
+ 1600, 1900, 2400, 2700, 3100, 3400,
+ 1700, 2100, 2500, 2700, 3000, 3200,
+ 2000, 2200, 2600, 2800, 3100, 3300,
+ 2100, 2200, 2600, 2800, 3100, 3300,
+ 1900, 2100, 2400, 2700, 3100, 3300,
+ 1900, 2000, 2300, 2600, 3100, 3200,
+ 1800, 1900, 2200, 2600, 3100, 3200,
+ 1500, 1700, 2000, 2600, 3100, 3200,
+ 1400, 1500, 1800, 2800, 3200, 3300,
+ 1300, 1500, 1700, 2600, 3200, 3300,
+ 1600, 1900, 2400, 2700, 3100, 3200,
+ 1600, 1900, 2400, 2700, 3100, 3300,
+ 1700, 1900, 2300, 2700, 3000, 3200,
+ 1700, 1900, 2200, 2600, 3000, 3200,
+ 1200, 1600, 1800, 2000, 3100, 3400,
+ 1100, 1600, 2400, 2500, 3000, 3300,
+ 1400, 1700, 2300, 2400, 2900, 3200,
+ 1700, 2000, 2300, 2700, 3200, 3300,
+ 1600, 1700, 2300, 2400, 3000, 3400,
+ 1700, 1800, 2300, 2400, 2900, 3400,
+ 1700, 1800, 2300, 2400, 2800, 3300,
+ 1800, 1900, 2300, 2400, 2800, 3200,
+ 1800, 1900, 2300, 2400, 3000, 3300,
+ 1800, 1900, 2300, 2400, 2900, 3300,
+ 1700, 1800, 2200, 2300, 2600, 3200,
+ 1700, 1800, 2200, 2300, 2700, 3200,
+ 1700, 1800, 2300, 2400, 3000, 3300,
+ 1700, 1800, 2300, 2400, 3100, 3400,
+ 1700, 1800, 2200, 2400, 3200, 3400,
+ 1700, 1900, 2200, 2400, 3300, 3400,
+ 1800, 1900, 2200, 2400, 3200, 3400,
+ 1800, 1900, 2300, 2400, 3200, 3400,
+ 1800, 1900, 2300, 2400, 3100, 3400,
+ 1800, 2000, 2200, 2400, 3200, 3300,
+ 1800, 1900, 2200, 2400, 3200, 3300,
+ 1700, 1800, 2000, 2200, 3200, 3300,
+ 1400, 1700, 1800, 2200, 3200, 3300,
+ 1400, 1800, 2100, 2500, 3100, 3300,
+ 1500, 1800, 2200, 2700, 3100, 3200,
+ 1600, 2000, 2300, 2500, 2900, 3200,
+ 1800, 2200, 2500, 2700, 3000, 3300,
+ 2000, 2400, 2700, 2800, 3100, 3300,
+ 2200, 2500, 2800, 2900, 3200, 3300,
+ 1500, 2300, 2500, 2900, 3300, 3400,
+ 1500, 1700, 2300, 2600, 3000, 3200,
+ 1700, 1900, 2300, 2600, 3000, 3300,
+ 1600, 1700, 2200, 2300, 3200, 3400,
+ 1600, 1700, 2200, 2300, 3300, 3400,
+ 1200, 2000, 2400, 2600, 3200, 3300,
+ 1000, 1800, 2400, 2500, 3200, 3300,
+ 1000, 2000, 2300, 2500, 3200, 3300,
+ 1300, 1700, 2200, 2600, 3100, 3200,
+ 1600, 1900, 2500, 2700, 3000, 3200,
+ 1300, 1900, 2400, 2700, 3000, 3200,
+ 1600, 1800, 2200, 2700, 3100, 3200,
+ 1700, 2100, 2300, 2500, 3100, 3300,
+ 1600, 1900, 2400, 2500, 3200, 3400,
+ 1600, 2000, 2300, 2500, 3100, 3300,
+ 1600, 1900, 2300, 2400, 3000, 3200,
+ 1500, 1900, 2200, 2300, 3000, 3200,
+ 1500, 2000, 2200, 2400, 3100, 3200,
+ 1400, 2000, 2200, 2400, 3100, 3200,
+ 1300, 2000, 2200, 2500, 3100, 3200,
+ 1100, 2100, 2300, 2600, 3100, 3200,
+ 1000, 2000, 2400, 2500, 3100, 3200,
+ 1000, 1700, 2400, 2500, 3100, 3200,
+ 1000, 1600, 2400, 2500, 3100, 3200,
+ 1100, 1600, 2400, 2500, 3100, 3200,
+ 1100, 1600, 2400, 2600, 3100, 3200,
+ 1100, 1600, 2500, 2600, 3200, 3300,
+ 1100, 1500, 2500, 2600, 3200, 3300,
+ 1100, 1500, 2500, 2600, 3100, 3200,
+ 1200, 1400, 2400, 2600, 3100, 3200,
+ 1300, 1700, 2300, 2400, 3200, 3300,
+ 1300, 1800, 2300, 2400, 3200, 3300,
+ 1300, 1900, 2300, 2400, 3200, 3300,
+ 1400, 1900, 2300, 2400, 3100, 3300,
+ 1500, 1700, 2300, 2400, 3000, 3200,
+ 1500, 1700, 2300, 2400, 3000, 3300,
+ 2100, 2300, 2800, 3000, 3300, 3400,
+ 2200, 2400, 2900, 3000, 3200, 3300,
+ 2100, 2300, 2900, 3000, 3300, 3400,
+ 2000, 2300, 2600, 3000, 3200, 3300,
+ 1300, 1600, 2200, 2600, 3100, 3300,
+ 1000, 2000, 2300, 2500, 3300, 3400,
+ 1000, 2100, 2400, 2600, 3300, 3400,
+ 1300, 1700, 1900, 2100, 3100, 3200,
+ 1500, 1800, 2000, 2400, 3200, 3300,
+ 1600, 1800, 2000, 2500, 3200, 3300,
+ 1600, 1800, 2100, 2600, 3200, 3300,
+ 1700, 1900, 2100, 2700, 3200, 3300,
+ 1600, 1800, 2100, 2500, 3300, 3400,
+ 1700, 1900, 2100, 2500, 2900, 3200,
+ 1600, 1900, 2100, 2300, 2800, 3200,
+ 1200, 1700, 2200, 2600, 3000, 3300,
+ 1200, 1700, 2300, 2600, 3100, 3300,
+ 1600, 2100, 2400, 2700, 3100, 3300,
+ 1500, 2000, 2400, 2600, 3100, 3400,
+ 2100, 2200, 2700, 3000, 3200, 3300,
+ 2100, 2200, 2700, 2900, 3100, 3300,
+ 1500, 1800, 2200, 2600, 2900, 3200,
+ 1400, 1600, 1800, 2900, 3200, 3300,
+ 1600, 1700, 1900, 2500, 3100, 3200,
+ 1700, 1800, 2000, 2600, 3100, 3200,
+ 1700, 1800, 2100, 2600, 3200, 3300,
+ 1700, 1900, 2200, 2600, 3200, 3300,
+ 1700, 1900, 2200, 2600, 3100, 3200,
+ 1700, 1900, 2200, 2500, 3100, 3200,
+ 1700, 1800, 2200, 2600, 3200, 3300,
+ 1700, 1800, 2200, 2500, 3200, 3300,
+ 1600, 1800, 2100, 2300, 3100, 3200,
+ 2300, 2500, 2800, 2900, 3200, 3300,
+ 1700, 1900, 2400, 2700, 3200, 3300,
+ 1700, 2000, 2400, 2800, 3200, 3300,
+ 1500, 1900, 2300, 2700, 3200, 3300,
+ 1500, 2000, 2300, 2500, 3200, 3300,
+ 1600, 1900, 2200, 2500, 3200, 3300,
+ 1600, 1900, 2200, 2400, 3100, 3300,
+ 1600, 1800, 2200, 2300, 3000, 3300,
+ 1700, 1800, 2200, 2300, 3000, 3300,
+ 1700, 1900, 2200, 2400, 3100, 3300,
+ 1700, 1900, 2200, 2400, 3100, 3400,
+ 1700, 1800, 2200, 2400, 3100, 3400,
+ 1500, 1800, 2300, 2400, 2900, 3300,
+ 1500, 1700, 2200, 2400, 3100, 3400,
+ 1400, 1700, 2200, 2300, 3100, 3400,
+ 1600, 1900, 2500, 2700, 3200, 3400,
+ 1500, 1800, 2400, 2600, 3000, 3300,
+ 1400, 2100, 2500, 2600, 3100, 3300,
+ 1200, 1800, 2100, 2300, 3200, 3300,
+ 1800, 2100, 2600, 2900, 3100, 3200,
+ 2000, 2400, 2900, 3100, 3300, 3400,
+ 1500, 1800, 2200, 2400, 3300, 3400,
+ 1500, 2000, 2100, 2700, 3300, 3400,
+ 1600, 1800, 2000, 2400, 2900, 3100,
+ 1600, 1800, 2200, 2600, 3000, 3200,
+ 1500, 1800, 2100, 2600, 3000, 3200,
+ 1600, 1900, 2100, 2400, 3000, 3300,
+ 1600, 2000, 2200, 2500, 3300, 3400,
+ 1600, 2000, 2100, 2400, 3300, 3400,
+ 1400, 1700, 2200, 2600, 3000, 3200,
+ 1300, 1600, 2200, 2500, 3000, 3200,
+ 1300, 1500, 2100, 2500, 3000, 3300,
+ 1200, 1600, 1700, 2400, 3300, 3400,
+ 1300, 1600, 1700, 2500, 3300, 3400,
+ 1300, 1600, 1700, 2500, 3200, 3300,
+ 1400, 1700, 1800, 2500, 3200, 3300,
+ 1500, 1800, 2000, 2500, 3200, 3300,
+ 1500, 1900, 2000, 2500, 3200, 3300,
+ 1600, 1800, 2100, 2400, 3200, 3300,
+ 1600, 1900, 2100, 2400, 3200, 3300,
+ 1500, 1700, 2100, 2200, 3000, 3300,
+ 1400, 1600, 2100, 2200, 3000, 3200,
+ 1400, 1800, 2100, 2300, 3000, 3200,
+ 1600, 2100, 2300, 2700, 3100, 3300,
+ 1200, 2100, 2400, 2700, 3300, 3400,
+ 1600, 2100, 2200, 2600, 3300, 3400,
+ 1300, 2000, 2200, 2500, 3300, 3400,
+ 1300, 2300, 2500, 2800, 3300, 3400,
+ 1300, 2000, 2300, 2500, 3200, 3300,
+ 1700, 2000, 2400, 2800, 3100, 3300,
+ 1900, 2200, 2500, 2900, 3100, 3300,
+ 2000, 2100, 2600, 2800, 3200, 3300,
+ 2000, 2100, 2700, 2900, 3200, 3300,
+ 1000, 1900, 2400, 2600, 3300, 3400,
+ 1000, 1900, 2500, 2600, 3200, 3300,
+ 1000, 1900, 2500, 2600, 3300, 3400,
+ 1000, 1800, 2400, 2600, 3200, 3300,
+ 1000, 1800, 2400, 2600, 3300, 3400,
+ 1000, 1900, 2400, 2600, 3200, 3300,
+ 1400, 1700, 2200, 2600, 3100, 3300,
+ 1400, 1600, 2100, 2500, 3000, 3300,
+ 1300, 1800, 2100, 2400, 3200, 3300,
+ 1100, 1900, 2200, 2400, 3200, 3300,
+ 1100, 1900, 2300, 2500, 3300, 3400,
+ 1100, 1900, 2400, 2500, 3200, 3300,
+ 1100, 1900, 2400, 2600, 3200, 3300,
+ 1100, 1900, 2300, 2400, 3300, 3400,
+ 1200, 2000, 2300, 2500, 3200, 3300,
+ 1300, 1900, 2200, 2400, 3300, 3400,
+ 1500, 1800, 2200, 2300, 3300, 3400,
+ 1700, 2200, 2700, 3000, 3300, 3400,
+ 1900, 2200, 2800, 3000, 3200, 3300,
+ 1900, 2200, 2500, 3000, 3200, 3300,
+ 1600, 2100, 2300, 2700, 3300, 3400,
+ 1600, 2000, 2300, 2700, 3300, 3400,
+ 1600, 2100, 2500, 3000, 3300, 3400,
+ 1600, 2200, 2600, 3000, 3300, 3400,
+ 1900, 2400, 2900, 3100, 3300, 3400,
+ 2100, 2500, 2900, 3000, 3300, 3400,
+ 2000, 2400, 2900, 3000, 3200, 3300,
+ 1700, 2200, 2400, 2900, 3200, 3300,
+ 1300, 1800, 2100, 2500, 3200, 3300,
+ 1500, 1600, 1800, 2300, 3000, 3200,
+ 1500, 1600, 1900, 2000, 3000, 3300,
+ 1400, 1800, 2200, 2600, 3200, 3300,
+ 1600, 1800, 2200, 2400, 2900, 3100,
+ 1500, 1700, 2100, 2400, 2900, 3100,
+ 1400, 1700, 2100, 2400, 3000, 3200,
+ 1400, 1700, 2300, 2600, 3200, 3300,
+ 1300, 1900, 2300, 2600, 3200, 3300,
+ 1000, 2100, 2500, 2700, 3300, 3400,
+ 1400, 1900, 2000, 2500, 3200, 3300,
+ 1600, 1900, 2100, 2500, 3300, 3400,
+ 1600, 2000, 2300, 2500, 3200, 3300,
+ 2200, 2400, 2800, 3000, 3200, 3300,
+ 1900, 2300, 2400, 2700, 3100, 3200,
+ 1900, 2200, 2300, 2600, 3100, 3200,
+ 1900, 2100, 2300, 2800, 3200, 3300,
+ 1700, 2000, 2400, 2700, 3200, 3300,
+ 1900, 2200, 2500, 2700, 3100, 3300,
+ 1700, 1800, 2200, 2500, 3300, 3400,
+ 1700, 1900, 2200, 2700, 3200, 3300,
+ 1700, 1900, 2300, 2700, 3300, 3400,
+ 1800, 2000, 2400, 2800, 3300, 3400,
+ 1800, 2000, 2300, 2600, 3300, 3400,
+ 1900, 2000, 2300, 2500, 3200, 3300,
+ 1900, 2100, 2400, 2600, 3200, 3300,
+ 2000, 2200, 2400, 2700, 3200, 3300,
+ 2100, 2200, 2500, 2900, 3200, 3300,
+ 2200, 2300, 2600, 2900, 3200, 3300,
+ 2200, 2300, 2700, 2900, 3100, 3300,
+ 2100, 2400, 2600, 2800, 3200, 3300,
+ 1900, 2200, 2600, 2800, 3000, 3200,
+ 1800, 2100, 2400, 2700, 3000, 3200,
+ 1800, 2000, 2400, 2700, 3100, 3200,
+ 1600, 2000, 2200, 2500, 3100, 3200,
+ 1300, 1900, 2100, 2300, 3100, 3300,
+ 1200, 1600, 2100, 2200, 3200, 3400,
+ 1100, 2000, 2400, 2600, 3200, 3300,
+ 1400, 1700, 2100, 2300, 3100, 3300,
+ 1400, 1900, 2200, 2500, 3300, 3400,
+ 1300, 1800, 2200, 2700, 3200, 3300,
+ 1300, 1900, 2200, 2600, 3200, 3300,
+ 1400, 2000, 2200, 2700, 3200, 3300,
+ 1400, 2000, 2200, 2600, 3300, 3400,
+ 1400, 2000, 2200, 2500, 3200, 3300,
+ 1400, 1900, 2200, 2400, 3200, 3300,
+ 1400, 1800, 2200, 2300, 3000, 3300,
+ 1400, 1800, 2200, 2300, 3100, 3300,
+ 1400, 1800, 2100, 2300, 3200, 3400,
+ 1500, 2000, 2400, 2700, 3300, 3400,
+ 1700, 2100, 2500, 3000, 3300, 3400,
+ 1400, 1900, 2300, 2800, 3200, 3300,
+ 1400, 2000, 2200, 2400, 3200, 3300,
+ 1200, 1900, 2200, 2400, 3200, 3300,
+ 1200, 1900, 2200, 2500, 3200, 3300,
+ 1200, 2000, 2200, 2500, 3300, 3400,
+ 1700, 2100, 2300, 2400, 3200, 3400,
+ 1400, 1600, 1800, 2500, 3100, 3200,
+ 1500, 1800, 2100, 2500, 3000, 3200,
+ 1700, 1800, 2200, 2500, 3100, 3300,
+ 2000, 2100, 2500, 2800, 3100, 3300,
+ 1900, 2100, 2200, 2700, 3100, 3200,
+ 1500, 1800, 2100, 2300, 3200, 3400,
+ 1600, 1800, 2000, 2300, 3200, 3400,
+ 1600, 1800, 2100, 2300, 3200, 3400,
+ 1500, 1800, 2000, 2300, 3300, 3400,
+ 1500, 1700, 1900, 2400, 3300, 3400,
+ 1600, 1900, 2000, 2700, 3100, 3200,
+ 1700, 1900, 2200, 2600, 3100, 3300,
+ 1700, 1900, 2200, 2500, 3200, 3300,
+ 1700, 2000, 2400, 2600, 3100, 3300,
+ 1700, 2000, 2400, 2700, 3100, 3200,
+ 2300, 2400, 2700, 3000, 3200, 3300,
+ 2200, 2400, 2600, 2900, 3200, 3300,
+ 2200, 2400, 2500, 2800, 3200, 3300,
+ 2100, 2400, 2500, 2800, 3200, 3300,
+ 2000, 2400, 2500, 2700, 3200, 3300,
+ 1900, 2300, 2400, 2800, 3200, 3300,
+ 1900, 2300, 2600, 2700, 3100, 3300,
+ 2000, 2400, 2800, 2900, 3200, 3300,
+ 1700, 2200, 2500, 2800, 3200, 3400,
+ 1500, 2100, 2400, 2600, 3100, 3300,
+ 1500, 1900, 2300, 2500, 3200, 3400,
+ 1400, 1900, 2300, 2400, 3200, 3300,
+ 1100, 1700, 2400, 2600, 3200, 3300,
+ 1100, 1700, 2400, 2600, 3300, 3400,
+ 1100, 1800, 2400, 2500, 3300, 3400,
+ 1100, 1800, 2400, 2500, 3200, 3300,
+ 1100, 2000, 2500, 2600, 3200, 3300,
+ 1100, 2100, 2500, 2600, 3200, 3300,
+ 1100, 2100, 2500, 2700, 3200, 3300,
+ 1000, 2200, 2600, 2700, 3200, 3300,
+ 1100, 2300, 2600, 2800, 3200, 3300,
+ 1100, 2100, 2500, 2700, 3100, 3200,
+ 1500, 1700, 2300, 2500, 2900, 3200,
+ 1600, 1700, 2200, 2600, 2800, 3100,
+ 1600, 1700, 2100, 2600, 2800, 3000,
+ 1500, 1700, 2100, 2500, 2800, 3000,
+ 1500, 1600, 2200, 2500, 2800, 3100,
+ 1500, 1600, 2300, 2600, 2800, 3100,
+ 1400, 1500, 2300, 2700, 2900, 3100,
+ 1400, 1500, 2200, 2700, 2800, 3100,
+ 1400, 1600, 2000, 2700, 2900, 3100,
+ 1500, 1700, 2200, 2700, 3100, 3300,
+ 1500, 1800, 2300, 2700, 3100, 3300,
+ 1600, 1700, 2300, 2700, 3000, 3300,
+ 1700, 1800, 2200, 2700, 2900, 3200,
+ 1800, 1900, 2200, 2700, 2900, 3100,
+ 1700, 1900, 2200, 2600, 2900, 3000,
+ 1800, 2000, 2300, 2700, 2900, 3100,
+ 1800, 2000, 2300, 2800, 3000, 3200,
+ 1800, 2000, 2400, 2800, 3000, 3200,
+ 1800, 1900, 2300, 2800, 3000, 3200,
+ 1500, 1700, 2200, 2500, 3000, 3100,
+ 1700, 2100, 2400, 2800, 3100, 3200,
+ 1800, 2200, 2700, 2900, 3400, 3500,
+ 1900, 2400, 2700, 2900, 3400, 3500,
+ 2000, 2400, 2600, 2900, 3300, 3400,
+ 1900, 2400, 2500, 2800, 3200, 3300,
+ 1900, 2300, 2500, 2600, 3200, 3300,
+ 1700, 1900, 2400, 2500, 3100, 3200,
+ 1600, 1700, 2300, 2600, 2900, 3100,
+ 1600, 1700, 2400, 2600, 2900, 3100,
+ 1600, 2100, 2600, 2800, 3300, 3400,
+ 1700, 2200, 2700, 3000, 3200, 3300,
+ 1700, 2300, 2800, 2900, 3200, 3300,
+ 1700, 2300, 2700, 3000, 3200, 3300,
+ 1600, 2100, 2700, 2900, 3300, 3400,
+ 1200, 1600, 2400, 2600, 3000, 3300,
+ 1100, 1400, 2400, 2700, 2900, 3100,
+ 1200, 1800, 2200, 2500, 3100, 3300,
+ 1200, 1700, 2200, 2500, 3100, 3300,
+ 1800, 1900, 2300, 2500, 2900, 3200,
+ 1900, 2000, 2400, 2500, 2800, 3100,
+ 2000, 2200, 2400, 2500, 2800, 3100,
+ 2000, 2200, 2400, 2600, 2800, 3200,
+ 2000, 2100, 2500, 2700, 3100, 3400,
+ 1900, 2000, 2600, 2700, 3100, 3300,
+ 1900, 2000, 2600, 2700, 3200, 3300,
+ 1900, 2400, 2700, 3000, 3300, 3400,
+ 2000, 2400, 2800, 2900, 3200, 3400,
+ 1900, 2000, 2300, 2600, 3000, 3200,
+ 1900, 2100, 2400, 2700, 3000, 3200,
+ 1900, 2100, 2400, 2800, 3100, 3200,
+ 1900, 2100, 2400, 2800, 3300, 3400,
+ 1500, 1800, 2100, 2600, 3100, 3300,
+ 1600, 1800, 2100, 2200, 3000, 3300,
+ 1800, 2100, 2300, 2500, 3000, 3200,
+ 2000, 2100, 2300, 2500, 3000, 3300,
+ 2000, 2100, 2300, 2500, 2900, 3300,
+ 2000, 2100, 2300, 2400, 2900, 3300,
+ 1600, 1800, 2300, 2500, 2900, 3200,
+ 1700, 1900, 2400, 2700, 3000, 3200,
+ 1700, 2000, 2400, 2600, 3000, 3300,
+ 1600, 2000, 2300, 2700, 3000, 3200,
+ 1500, 1800, 2300, 2600, 3100, 3200,
+ 1700, 1800, 2300, 2400, 2800, 3000,
+ 1800, 2000, 2400, 2500, 2900, 3200,
+ 1800, 2000, 2400, 2600, 3000, 3200,
+ 1900, 2000, 2400, 2500, 3000, 3200,
+ 1900, 2000, 2300, 2500, 3000, 3200,
+ 1800, 1900, 2200, 2400, 2900, 3200,
+ 1800, 1900, 2200, 2300, 2900, 3200,
+ 1600, 1800, 2200, 2400, 3100, 3300,
+ 1600, 2000, 2400, 2700, 3100, 3200,
+ 1800, 2100, 2500, 2700, 3000, 3200,
+ 2000, 2200, 2500, 2700, 3000, 3200,
+ 2000, 2300, 2500, 2700, 3000, 3200,
+ 2000, 2300, 2400, 2700, 3000, 3200,
+ 2100, 2200, 2400, 2500, 3000, 3300,
+ 1900, 2000, 2300, 2600, 2800, 3300,
+ 1900, 2000, 2400, 2700, 3100, 3300,
+ 1500, 2000, 2400, 2700, 3100, 3300,
+ 1600, 1900, 2500, 2800, 3000, 3300,
+ 1900, 2000, 2400, 2700, 2900, 3200,
+ 2000, 2200, 2400, 2700, 2900, 3200,
+ 2100, 2200, 2400, 2700, 2900, 3200,
+ 2100, 2300, 2400, 2600, 2800, 3200,
+ 1300, 2000, 2300, 2500, 2700, 3100,
+ 1800, 1900, 2100, 2400, 2900, 3100,
+ 1700, 1900, 2100, 2500, 2900, 3100,
+ 1800, 1900, 2300, 2600, 3100, 3300,
+ 1600, 1700, 2300, 2600, 2800, 3200,
+ 1700, 1800, 2300, 2600, 2800, 3100,
+ 1700, 1800, 2300, 2700, 2800, 3200,
+ 1500, 1700, 2300, 2600, 3000, 3300,
+ 1400, 1700, 2200, 2500, 3000, 3300,
+ 1400, 1600, 2200, 2300, 3000, 3300,
+ 1400, 1600, 2200, 2400, 2800, 3300,
+ 1500, 1600, 2200, 2400, 2900, 3300,
+ 1500, 1600, 2200, 2400, 2800, 3300,
+ 1500, 1700, 2200, 2500, 3000, 3200,
+ 1700, 1900, 2300, 2700, 3000, 3300,
+ 1600, 1800, 2400, 2700, 3000, 3200,
+ 1600, 2000, 2500, 2800, 3000, 3300,
+ 2000, 2200, 2500, 2600, 3200, 3300,
+ 1600, 1800, 2200, 2500, 3100, 3200,
+ 1500, 1700, 1800, 2300, 3300, 3400,
+ 1400, 1600, 1800, 2000, 3200, 3400,
+ 1400, 1600, 1800, 1900, 3100, 3400,
+ 1400, 1600, 1900, 2000, 2900, 3300,
+ 1400, 1500, 1900, 2000, 2900, 3200,
+ 1900, 2200, 2500, 2800, 3100, 3200,
+ 1800, 2200, 2500, 2700, 3000, 3200,
+ 1800, 2200, 2600, 2700, 3100, 3200,
+ 2000, 2300, 2700, 2800, 3200, 3300,
+ 2100, 2200, 2600, 2800, 3000, 3300,
+ 2100, 2200, 2500, 2700, 3100, 3300,
+ 1700, 1800, 2000, 2100, 2800, 3200,
+ 1600, 1700, 1900, 2000, 2800, 3200,
+ 1400, 1500, 1800, 1900, 2800, 3200,
+ 1400, 1800, 2100, 2400, 3000, 3200,
+ 1600, 1900, 2300, 2600, 3000, 3300,
+ 1600, 1900, 2300, 2500, 3100, 3300,
+ 1600, 1900, 2400, 2700, 3000, 3200,
+ 1600, 1900, 2400, 2700, 3000, 3300,
+ 1500, 1900, 2400, 2700, 3000, 3300,
+ 1100, 1400, 2500, 2800, 3000, 3300,
+ 1100, 1300, 2300, 2800, 3000, 3200,
+ 1400, 1500, 2100, 2700, 2900, 3100,
+ 1500, 1600, 2100, 2700, 2900, 3100,
+ 1700, 1800, 2200, 2600, 2800, 3100,
+ 1800, 2000, 2300, 2600, 2800, 3000,
+ 1900, 2100, 2300, 2600, 2800, 3100,
+ 2000, 2100, 2300, 2600, 2800, 3100,
+ 2000, 2100, 2400, 2500, 2800, 3200,
+ 1900, 2100, 2300, 2500, 2800, 3200,
+ 1800, 1900, 2300, 2500, 2800, 3300,
+ 1700, 1800, 2300, 2500, 3000, 3300,
+ 1700, 1900, 2400, 2600, 3000, 3200,
+ 1500, 1900, 2200, 2600, 3100, 3300,
+ 1300, 1500, 1800, 1900, 2900, 3200,
+ 1300, 1500, 1800, 1900, 2900, 3300,
+ 1300, 1500, 1800, 1900, 2800, 3200,
+ 1400, 1500, 1700, 1900, 2800, 3200,
+ 1400, 1500, 1700, 1800, 2800, 3200,
+ 1700, 2000, 2400, 2500, 3100, 3300,
+ 2100, 2400, 2700, 2800, 3300, 3500,
+ 1800, 2300, 2700, 2900, 3200, 3400,
+ 1700, 2300, 2700, 2900, 3300, 3400,
+ 1700, 2100, 2700, 2900, 3300, 3400,
+ 1800, 2400, 2700, 2900, 3300, 3400,
+ 1900, 2500, 2800, 3000, 3300, 3400,
+ 2000, 2500, 2800, 3000, 3300, 3400,
+ 2000, 2400, 2700, 3000, 3200, 3400,
+ 1900, 2300, 2700, 3000, 3200, 3400,
+ 1800, 2000, 2500, 2700, 2900, 3200,
+ 1800, 2000, 2400, 2700, 2900, 3100,
+ 1900, 2000, 2300, 2700, 2900, 3000,
+ 1900, 2000, 2400, 2700, 2900, 3100,
+ 1800, 1900, 2400, 2700, 2900, 3100,
+ 1800, 1900, 2300, 2700, 2800, 3100,
+ 1800, 1900, 2300, 2600, 2800, 3100,
+ 1500, 1800, 2400, 2700, 3200, 3400,
+ 1600, 1800, 2500, 2700, 3100, 3400,
+ 1500, 1700, 2400, 2700, 3000, 3300,
+ 1400, 1500, 2400, 2700, 2900, 3200,
+ 1300, 1500, 2300, 2700, 2900, 3100,
+ 1400, 1600, 2100, 2600, 2800, 3000,
+ 1500, 1600, 2100, 2600, 2800, 3000,
+ 1400, 1600, 2200, 2400, 3000, 3200,
+ 1300, 1600, 2200, 2500, 2900, 3200,
+ 1300, 1700, 2200, 2600, 3000, 3300,
+ 1300, 1700, 2200, 2700, 3100, 3200,
+ 1200, 1400, 2200, 2700, 2900, 3100,
+ 1100, 1400, 2300, 2700, 2900, 3100,
+ 1100, 1300, 2400, 2800, 3000, 3200,
+ 1200, 1600, 2300, 2600, 3100, 3200,
+ 1500, 2100, 2400, 2700, 3200, 3300,
+ 1800, 2100, 2400, 2800, 3200, 3300,
+ 1600, 2100, 2400, 2800, 3200, 3300,
+ 1600, 2000, 2500, 2900, 3200, 3300,
+ 1800, 2000, 2500, 2900, 3200, 3300,
+ 1700, 1900, 2400, 2800, 3100, 3300,
+ 1600, 1800, 2400, 2700, 3100, 3300,
+ 1500, 1600, 2200, 2500, 2900, 3200,
+ 1500, 1600, 2200, 2500, 2800, 3200,
+ 1400, 1600, 2100, 2500, 2800, 3100,
+ 1200, 1400, 2200, 2500, 2700, 3100,
+ 1100, 1400, 2400, 2800, 2900, 3100,
+ 1400, 1700, 2300, 2600, 2900, 3200,
+ 1500, 1800, 2300, 2500, 2900, 3300,
+ 1500, 1700, 2000, 2100, 3000, 3300,
+ 1500, 1700, 2000, 2200, 3100, 3300,
+ 1500, 1700, 2100, 2300, 3100, 3200,
+ 1600, 1900, 2500, 2700, 3100, 3200,
+ 1800, 2300, 2800, 3100, 3300, 3400,
+ 1800, 2200, 2700, 2900, 3200, 3400,
+ 1700, 2200, 2700, 2800, 3200, 3400,
+ 1500, 1800, 2600, 2700, 3000, 3200,
+ 1500, 1700, 2300, 2700, 2800, 3100,
+ 1400, 1500, 2100, 2200, 2700, 3200,
+ 1400, 1500, 2000, 2100, 2600, 3100,
+ 1300, 1500, 1900, 2000, 2500, 3100,
+ 1400, 1500, 1800, 1900, 2700, 3200,
+ 1500, 1600, 2000, 2100, 2600, 3100,
+ 1700, 1800, 2000, 2200, 2600, 3100,
+ 1700, 1800, 2100, 2200, 2700, 3100,
+ 1600, 2000, 2400, 2500, 3000, 3200,
+ 2000, 2200, 2500, 2900, 3100, 3300,
+ 1900, 2200, 2400, 2600, 2900, 3100,
+ 1600, 1700, 2200, 2400, 2700, 3300,
+ 1700, 1800, 2300, 2400, 2800, 3200,
+ 1800, 1900, 2300, 2500, 2800, 3200,
+ 1900, 2100, 2400, 2500, 3000, 3300,
+ 2100, 2200, 2500, 2600, 3000, 3300,
+ 2000, 2100, 2500, 2700, 2900, 3200,
+ 1700, 1900, 2200, 2700, 2800, 3100,
+ 1800, 1900, 2400, 2700, 2800, 3200,
+ 1800, 1900, 2400, 2700, 2900, 3200,
+ 1700, 1800, 2200, 2700, 2800, 3100,
+ 1700, 1800, 2200, 2700, 3000, 3200,
+ 1900, 2100, 2500, 2900, 3100, 3300,
+ 1700, 2000, 2500, 2700, 3200, 3400,
+ 1900, 2200, 2700, 3000, 3300, 3400,
+ 2000, 2400, 2800, 3100, 3400, 3500,
+ 2100, 2400, 2600, 2900, 3200, 3300,
+ 2100, 2400, 2500, 2700, 3100, 3300,
+ 1800, 2100, 2500, 2700, 3200, 3300,
+ 1700, 2100, 2400, 2700, 3200, 3300,
+ 1500, 1600, 1800, 1900, 2600, 3100,
+ 1500, 1600, 1900, 2000, 2500, 3100,
+ 1600, 1700, 2000, 2100, 2500, 3100,
+ 1800, 2100, 2300, 2500, 2800, 3200,
+ 1900, 2100, 2300, 2500, 2700, 3200,
+ 2000, 2200, 2400, 2600, 2900, 3300,
+ 2000, 2200, 2400, 2600, 2900, 3200,
+ 2000, 2100, 2400, 2500, 2900, 3300,
+ 1800, 2200, 2500, 2900, 3400, 3500,
+ 1800, 2300, 2500, 2900, 3300, 3400,
+ 2000, 2300, 2500, 2800, 3000, 3300,
+ 1800, 2000, 2400, 2500, 2800, 3300,
+ 1100, 1400, 2600, 2800, 3000, 3200,
+ 1300, 1500, 2200, 2700, 2900, 3200,
+ 1400, 1600, 2200, 2700, 3000, 3200,
+ 1400, 1600, 2200, 2600, 3100, 3200,
+ 1500, 1800, 2200, 2400, 3100, 3300,
+ 1700, 1800, 2200, 2500, 3000, 3300,
+ 1700, 1800, 2200, 2600, 3000, 3200,
+ 1700, 1800, 2300, 2600, 3000, 3200,
+ 1700, 1800, 2400, 2700, 3000, 3100,
+ 1600, 1700, 2500, 2800, 3000, 3200,
+ 1400, 1500, 2200, 2700, 2900, 3100,
+ 1300, 1400, 2100, 2700, 2900, 3200,
+ 1500, 1900, 2300, 2600, 3000, 3200,
+ 1400, 1600, 2200, 2500, 2700, 3100,
+ 1600, 1700, 2200, 2500, 2800, 3200,
+ 1600, 1800, 2100, 2500, 2900, 3200,
+ 1600, 1800, 2100, 2600, 3000, 3200,
+ 1800, 2100, 2400, 2800, 3100, 3300,
+ 1800, 2100, 2400, 2700, 3000, 3300,
+ 2000, 2100, 2500, 2800, 3000, 3200,
+ 1800, 2000, 2500, 2700, 3000, 3200,
+ 1600, 1900, 2300, 2700, 2900, 3200,
+ 1600, 1900, 2100, 2500, 2800, 3100,
+ 1700, 1900, 2100, 2500, 2800, 3000,
+ 1700, 1800, 2100, 2600, 2800, 3000,
+ 1600, 1700, 2000, 2600, 2800, 3000,
+ 1400, 1700, 2200, 2700, 3000, 3200,
+ 1500, 1800, 2300, 2700, 3000, 3200,
+ 1600, 1800, 2300, 2600, 3000, 3300,
+ 1600, 1800, 2300, 2600, 3100, 3300,
+ 1600, 1900, 2300, 2600, 3100, 3300,
+ 1200, 1300, 2100, 2700, 3000, 3100,
+ 1300, 1400, 2100, 2700, 2900, 3100,
+ 1300, 1400, 2200, 2700, 2900, 3100,
+ 1300, 1400, 2100, 2600, 2800, 3100,
+ 1300, 1500, 2100, 2600, 2800, 3100,
+ 1500, 1600, 1900, 2500, 2900, 3100,
+ 1500, 1700, 2100, 2700, 2900, 3200,
+ 1600, 1900, 2400, 2700, 3200, 3300,
+ 1900, 2100, 2500, 2800, 3200, 3400,
+ 1700, 2000, 2400, 2800, 3200, 3400,
+ 1600, 1700, 2200, 2400, 2800, 3300,
+ 1500, 1600, 2200, 2400, 3000, 3300,
+ 1500, 1700, 2300, 2700, 3100, 3300,
+ 1400, 1500, 2000, 2600, 2900, 3100,
+ 1400, 1500, 2100, 2500, 2800, 3100,
+ 1400, 1700, 2200, 2600, 3000, 3300,
+ 1000, 1500, 2600, 2800, 3100, 3400,
+ 1300, 1500, 2500, 2700, 2900, 3300,
+ 1500, 1600, 2200, 2600, 2800, 3100,
+ 1700, 1800, 2200, 2400, 2700, 3200,
+ 1700, 1800, 2100, 2400, 2600, 3100,
+ 1600, 1700, 2100, 2400, 2700, 3200,
+ 1600, 1900, 2300, 2700, 3000, 3300,
+ 1500, 1600, 2000, 2400, 3000, 3300,
+ 1600, 1800, 2300, 2600, 3200, 3300,
+ 1700, 1800, 2400, 2600, 3200, 3400,
+ 1600, 1800, 2400, 2600, 3200, 3400,
+ 1700, 1800, 2300, 2600, 3000, 3300,
+ 1700, 1800, 2100, 2500, 2900, 3200,
+ 1800, 1900, 2100, 2600, 2800, 3000,
+ 1800, 1900, 2200, 2600, 2800, 3000,
+ 1800, 1900, 2200, 2600, 2900, 3100,
+ 1700, 1800, 2100, 2600, 2900, 3100,
+ 1600, 1700, 2100, 2700, 2900, 3100,
+ 1400, 1600, 2100, 2700, 2900, 3200,
+ 1200, 1600, 2200, 2400, 3000, 3300,
+ 1600, 1900, 2300, 2700, 3100, 3400,
+ 1200, 1800, 2300, 2700, 3100, 3300,
+ 1600, 2000, 2400, 2800, 3100, 3300,
+ 1700, 1900, 2100, 2600, 3100, 3300,
+ 1800, 1900, 2300, 2600, 3100, 3400,
+ 1900, 2000, 2300, 2600, 3200, 3300,
+ 1900, 2000, 2300, 2600, 3100, 3300,
+ 1900, 2100, 2300, 2700, 3100, 3300,
+ 1200, 1400, 2200, 2800, 3000, 3100,
+ 1800, 2100, 2400, 2700, 3200, 3400,
+ 1600, 2100, 2500, 2800, 3100, 3300,
+ 1600, 2000, 2500, 2800, 3200, 3300,
+ 1700, 2000, 2500, 2800, 3200, 3400,
+ 1700, 1900, 2700, 2800, 3100, 3400,
+ 1600, 1800, 2400, 2600, 3100, 3400,
+ 1600, 1800, 2300, 2500, 3100, 3400,
+ 1600, 1800, 2200, 2500, 3100, 3400,
+ 1600, 1800, 2100, 2300, 3100, 3400,
+ 1500, 1700, 2000, 2200, 3000, 3300,
+ 1500, 1600, 1900, 2000, 3000, 3200,
+ 1300, 1500, 1700, 1900, 2800, 3200,
+ 1800, 2000, 2300, 2600, 3000, 3200,
+ 1700, 2000, 2200, 2600, 3000, 3200,
+ 1600, 1900, 2400, 2600, 3000, 3300,
+ 1300, 1700, 2100, 2400, 2900, 3200,
+ 1600, 1800, 2400, 2600, 3000, 3300,
+ 1300, 1600, 2200, 2300, 2900, 3200,
+ 1300, 1400, 2100, 2200, 3000, 3200,
+ 1300, 1500, 1800, 2000, 3000, 3200,
+ 1300, 1400, 1800, 1900, 2800, 3200,
+ 1300, 1700, 2200, 2500, 3000, 3200,
+ 1200, 1800, 2300, 2600, 3200, 3300,
+ 1400, 1900, 2300, 2700, 3100, 3300,
+ 1500, 2000, 2400, 2600, 3000, 3300,
+ 1600, 2000, 2500, 2600, 3100, 3300,
+ 1600, 1900, 2500, 2700, 3100, 3300,
+ 1600, 2000, 2500, 2600, 3000, 3200,
+ 1400, 1600, 2300, 2600, 2800, 3200,
+ 1300, 1500, 2000, 2600, 2700, 3000,
+ 1300, 1500, 2200, 2600, 2800, 3100,
+ 1400, 1500, 2100, 2600, 2800, 3100,
+ 1400, 1500, 2100, 2600, 2800, 3000,
+ 1500, 1600, 2000, 2500, 2700, 3000,
+ 1500, 1700, 2000, 2500, 2700, 3000,
+ 1600, 1700, 2000, 2500, 2800, 3000,
+ 1700, 1800, 2100, 2500, 2900, 3100,
+ 1700, 1900, 2100, 2500, 2900, 3000,
+ 1800, 2000, 2200, 2600, 2800, 3000,
+ 1800, 2100, 2300, 2600, 2800, 3100,
+ 1800, 2100, 2300, 2600, 2900, 3100,
+ 1800, 2000, 2200, 2600, 2900, 3100,
+ 1800, 2000, 2300, 2600, 2900, 3100,
+ 1800, 2000, 2300, 2600, 2800, 3100,
+ 1700, 1900, 2200, 2600, 2800, 3000,
+ 1700, 1800, 2100, 2500, 2700, 3000,
+ 1500, 1700, 2200, 2400, 2800, 3300,
+ 1500, 1900, 2300, 2500, 3100, 3300,
+ 1700, 1800, 2200, 2800, 3100, 3200,
+ 1700, 1900, 2100, 2700, 3000, 3200,
+ 1900, 2100, 2400, 2600, 3000, 3200,
+ 2000, 2200, 2400, 2700, 3000, 3200,
+ 1900, 2300, 2400, 2700, 3100, 3300,
+ 1500, 1600, 1800, 2000, 3100, 3300,
+ 1200, 1400, 1900, 2500, 2900, 3100,
+ 1600, 1700, 2000, 2100, 2900, 3300,
+ 1700, 1800, 2100, 2200, 2900, 3300,
+ 1800, 1900, 2200, 2300, 3000, 3300,
+ 1900, 2000, 2200, 2300, 3100, 3300,
+ 2000, 2100, 2300, 2500, 3100, 3400,
+ 1900, 2100, 2300, 2500, 3000, 3200,
+ 1800, 2000, 2300, 2400, 2900, 3200,
+ 1900, 2200, 2600, 2800, 3100, 3300,
+ 2000, 2400, 2600, 2700, 3200, 3400,
+ 1800, 2200, 2600, 2700, 3100, 3300,
+ 1600, 2100, 2600, 2700, 3100, 3300,
+ 1600, 2100, 2500, 2800, 3200, 3400,
+ 1900, 2200, 2500, 2800, 3200, 3400,
+ 1800, 2000, 2500, 2800, 3300, 3400,
+ 1700, 1900, 2600, 2800, 3100, 3400,
+ 1600, 1700, 2400, 2700, 3100, 3300,
+ 1400, 1600, 2200, 2500, 2800, 3200,
+ 1400, 1600, 2300, 2500, 2900, 3200,
+ 1400, 1500, 2300, 2600, 2900, 3200,
+ 1300, 1500, 2400, 2600, 3000, 3300,
+ 1200, 1400, 2400, 2600, 2900, 3300,
+ 1200, 1300, 2300, 2600, 2800, 3200,
+ 1200, 1300, 2300, 2600, 2800, 3100,
+ 1200, 1400, 2300, 2600, 2800, 3200,
+ 1200, 1400, 2300, 2500, 2800, 3200,
+ 1200, 1400, 2300, 2500, 2700, 3200,
+ 1300, 1400, 2300, 2500, 2700, 3200,
+ 1300, 1400, 2300, 2400, 2900, 3200,
+ 1300, 1600, 2300, 2400, 2900, 3200,
+ 1600, 1700, 2200, 2500, 3000, 3200,
+ 1600, 1700, 2200, 2500, 2900, 3200,
+ 1600, 1800, 2300, 2400, 2900, 3200,
+ 1600, 1800, 2200, 2400, 2900, 3200,
+ 1700, 1900, 2400, 2700, 3000, 3300,
+ 1600, 1800, 2400, 2700, 3000, 3300,
+ 1600, 1800, 2300, 2600, 2900, 3200,
+ 1600, 1800, 2500, 2700, 2900, 3200,
+ 1600, 1900, 2500, 2800, 3100, 3300,
+ 1600, 1900, 2500, 2800, 3000, 3200,
+ 1400, 1700, 2400, 2700, 2900, 3200,
+ 1400, 1500, 2200, 2600, 2800, 3100,
+ 1300, 1500, 2300, 2600, 2800, 3100,
+ 1200, 1400, 2300, 2500, 2700, 3100,
+ 1300, 1600, 2200, 2600, 3000, 3300,
+ 1200, 1600, 2500, 2700, 3100, 3400,
+ 1300, 1800, 2400, 2700, 3200, 3400,
+ 1300, 1700, 2300, 2700, 3100, 3300,
+ 1300, 1700, 2200, 2500, 3100, 3300,
+ 1300, 1600, 2200, 2600, 2900, 3200,
+ 1400, 1600, 2200, 2700, 2800, 3100,
+ 1600, 1700, 2200, 2700, 3100, 3200,
+ 1800, 2000, 2400, 2800, 3100, 3300,
+ 1800, 2000, 2400, 2800, 3200, 3300,
+ 1700, 1800, 2200, 2700, 2900, 3100,
+ 1700, 1800, 2300, 2700, 3000, 3300,
+ 1800, 1900, 2600, 2800, 3300, 3400,
+ 1900, 2100, 2300, 2600, 2900, 3100,
+ 1900, 2200, 2400, 2700, 3000, 3100,
+ 1800, 2300, 2400, 2700, 3000, 3100,
+ 1800, 2300, 2400, 2600, 3100, 3200,
+ 2000, 2300, 2400, 2700, 3100, 3200,
+ 2100, 2300, 2500, 2700, 3000, 3200,
+ 2000, 2100, 2500, 2700, 3000, 3200,
+ 1900, 2000, 2300, 2700, 2900, 3100,
+ 1600, 1800, 2200, 2500, 2700, 3000,
+ 1500, 1800, 2300, 2500, 2700, 3000,
+ 1500, 1800, 2200, 2500, 2700, 3000,
+ 1600, 1800, 2300, 2500, 2800, 3000,
+ 1700, 1800, 2400, 2700, 3000, 3200,
+ 1700, 1800, 2500, 2700, 3000, 3200,
+ 1700, 1800, 2400, 2700, 3000, 3300,
+ 1600, 1700, 2400, 2600, 2900, 3200,
+ 1500, 1700, 2400, 2600, 2800, 3200,
+ 1500, 1700, 2400, 2500, 2800, 3200,
+ 1400, 1600, 2400, 2500, 3000, 3300,
+ 1500, 1700, 2300, 2400, 2900, 3200,
+ 1500, 1800, 2200, 2400, 2800, 3000,
+ 1600, 1900, 2200, 2600, 2900, 3100,
+ 1800, 2000, 2300, 2600, 2900, 3000,
+ 1600, 2000, 2300, 2500, 2900, 3100,
+ 1600, 1800, 2100, 2300, 2900, 3100,
+ 1300, 1500, 2200, 2400, 3000, 3200,
+ 1300, 1500, 2200, 2400, 2900, 3200,
+ 1300, 1500, 2200, 2500, 2900, 3200,
+ 1400, 1500, 2300, 2500, 2900, 3200,
+ 1600, 1700, 2100, 2500, 2800, 3100,
+ 1600, 1700, 2100, 2600, 2800, 3100,
+ 1700, 1800, 2100, 2500, 2800, 3100,
+ 1700, 1800, 2200, 2600, 2900, 3100,
+ 1700, 1900, 2300, 2600, 2900, 3200,
+ 1800, 2100, 2300, 2600, 2900, 3200,
+ 1800, 2100, 2300, 2700, 2900, 3200,
+ 1900, 2200, 2400, 2700, 2900, 3200,
+ 1900, 2100, 2300, 2700, 2900, 3100,
+ 1900, 2000, 2300, 2600, 2800, 3100,
+ 1900, 2200, 2500, 2800, 3100, 3300,
+ 1900, 2200, 2400, 2800, 3000, 3200,
+ 1900, 2200, 2400, 2700, 2900, 3100,
+ 1900, 2300, 2400, 2800, 3100, 3200,
+ 2000, 2300, 2500, 2800, 3100, 3300,
+ 1900, 2400, 2500, 2800, 3100, 3200,
+ 1800, 2000, 2200, 2500, 3000, 3200,
+ 1800, 1900, 2100, 2400, 2900, 3200,
+ 1500, 1600, 2200, 2400, 2700, 3200,
+ 1300, 1400, 2200, 2500, 2700, 3200,
+ 1200, 1500, 2500, 2700, 3000, 3300,
+ 1300, 1600, 2400, 2600, 3000, 3300,
+ 2000, 2200, 2600, 2700, 3000, 3300,
+ 2100, 2300, 2500, 2700, 3000, 3300,
+ 2100, 2300, 2600, 2700, 3000, 3300,
+ 2000, 2200, 2600, 2700, 3000, 3200,
+ 1800, 2300, 2500, 2600, 2900, 3200,
+ 1800, 2300, 2500, 2700, 2900, 3100,
+ 1800, 2200, 2400, 2600, 2900, 3200,
+ 1800, 2200, 2400, 2600, 2800, 3100,
+ 1800, 2200, 2300, 2600, 2900, 3100,
+ 1800, 2000, 2200, 2800, 3000, 3200,
+ 1800, 1900, 2200, 2800, 3000, 3200,
+ 1700, 1900, 2300, 2800, 3000, 3300,
+ 1600, 1800, 2300, 2800, 3000, 3300,
+ 1400, 1700, 2200, 2500, 2800, 2900,
+ 1400, 1700, 2100, 2500, 2900, 3200,
+ 1700, 2000, 2200, 2800, 3200, 3300,
+ 1800, 1900, 2200, 2700, 2900, 3200,
+ 1800, 2000, 2200, 2700, 2900, 3100,
+ 1800, 2000, 2200, 2700, 2800, 3000,
+ 1800, 2000, 2200, 2700, 2800, 3100,
+ 1600, 1900, 2100, 2600, 2900, 3200,
+ 2000, 2100, 2600, 2900, 3000, 3200,
+ 2000, 2200, 2700, 2900, 3100, 3300,
+ 2000, 2200, 2400, 2800, 3000, 3200,
+ 2000, 2200, 2300, 2700, 3000, 3200,
+ 1700, 2200, 2400, 2600, 2900, 3100,
+ 1800, 2200, 2400, 2700, 3000, 3200,
+ 1900, 2300, 2500, 2700, 3000, 3200,
+ 1900, 2300, 2500, 2700, 2900, 3100,
+ 1900, 2300, 2500, 2800, 3000, 3200,
+ 1900, 2300, 2500, 2700, 2900, 3200,
+ 1800, 2200, 2400, 2700, 2900, 3100,
+ 1800, 2000, 2300, 2700, 3000, 3200,
+ 1600, 1700, 2100, 2800, 3100, 3200,
+ 1400, 1800, 2200, 2500, 3000, 3100,
+ 1400, 1800, 2300, 2500, 3000, 3100,
+ 1400, 1800, 2300, 2500, 2900, 3100,
+ 1600, 1800, 2500, 2800, 3100, 3200,
+ 1700, 2000, 2400, 2700, 3200, 3400,
+ 1700, 2000, 2500, 2800, 3100, 3400,
+ 1500, 1700, 2300, 2600, 2900, 3200,
+ 1500, 1700, 2200, 2600, 2800, 3200,
+ 1500, 1700, 2200, 2600, 2900, 3300,
+ 1400, 1700, 2200, 2600, 2900, 3300,
+ 1200, 1500, 2200, 2300, 3100, 3400,
+ 1200, 1600, 2300, 2400, 3200, 3300,
+ 1200, 1700, 2300, 2400, 3100, 3300,
+ 1100, 1700, 2400, 2500, 3100, 3300,
+ 1100, 1800, 2500, 2600, 3100, 3300,
+ 1100, 1800, 2500, 2600, 3200, 3300,
+ 1000, 1800, 2500, 2600, 3200, 3300,
+ 1000, 1700, 2400, 2500, 3200, 3300,
+ 1100, 1600, 2400, 2500, 3200, 3300,
+ 1100, 1600, 2300, 2400, 3200, 3300,
+ 1300, 1600, 2300, 2500, 3100, 3300,
+ 1400, 1700, 2300, 2500, 3100, 3300,
+ 2000, 2100, 2500, 2600, 3200, 3400,
+ 1700, 2100, 2600, 2800, 3100, 3200,
+ 1800, 2200, 2700, 2900, 3100, 3300,
+ 2100, 2400, 2700, 2900, 3200, 3300,
+ 2100, 2500, 2700, 2900, 3300, 3400,
+ 2100, 2400, 2600, 2800, 3200, 3400,
+ 1700, 1900, 2400, 2600, 2900, 3000,
+ 1600, 1900, 2400, 2500, 2800, 2900,
+ 1300, 2000, 2400, 2500, 2900, 3200,
+ 1500, 2000, 2400, 2500, 2900, 3100,
+ 1600, 2000, 2400, 2600, 3000, 3100,
+ 1700, 1900, 2500, 2600, 3100, 3200,
+ 1600, 1800, 2600, 2700, 3300, 3400,
+ 1500, 1600, 2600, 2700, 3200, 3400,
+ 1500, 1700, 2600, 2700, 3200, 3400,
+ 1500, 2100, 2600, 2800, 3300, 3400,
+ 1700, 2200, 2700, 2900, 3300, 3400,
+ 1700, 2300, 2700, 2800, 3300, 3400,
+ 1800, 2300, 2700, 2800, 3300, 3400,
+ 1400, 1700, 2500, 2600, 3000, 3300,
+ 1400, 1800, 2500, 2600, 3000, 3300,
+ 1800, 2200, 2700, 2900, 3300, 3400,
+ 1800, 2300, 2600, 2900, 3300, 3400,
+ 1400, 1900, 2500, 2600, 3200, 3400,
+ 1400, 2000, 2400, 2500, 3200, 3300,
+ 1400, 2100, 2400, 2600, 3200, 3300,
+ 1200, 2000, 2400, 2700, 3200, 3300,
+ 1300, 1900, 2300, 2600, 3100, 3200,
+ 1300, 1800, 2300, 2500, 3100, 3200,
+ 1200, 1700, 2300, 2500, 3000, 3100,
+ 1200, 1800, 2400, 2500, 3000, 3100,
+ 1100, 2100, 2300, 2600, 3000, 3100,
+ 1400, 1800, 2200, 2700, 3100, 3200,
+ 1600, 2000, 2400, 2600, 3200, 3300,
+ 1600, 1900, 2400, 2600, 3300, 3400,
+ 1600, 2000, 2500, 2600, 3300, 3400,
+ 1600, 2000, 2300, 2500, 3300, 3400,
+ 1500, 2400, 2700, 2800, 3100, 3300,
+ 1300, 2000, 2500, 2600, 3200, 3300,
+ 1400, 2000, 2500, 2600, 3200, 3300,
+ 1600, 1900, 2400, 2600, 3200, 3300,
+ 1600, 2000, 2300, 2600, 3200, 3300,
+ 1600, 2100, 2300, 2500, 3000, 3100,
+ 1800, 2100, 2400, 2700, 2900, 3200,
+ 1500, 1700, 2000, 2600, 3200, 3300,
+ 1400, 1700, 2000, 2400, 3200, 3300,
+ 1400, 1900, 2200, 2500, 3100, 3300,
+ 1500, 1900, 2200, 2500, 3100, 3300,
+ 1200, 1900, 2500, 2600, 3100, 3300,
+ 1000, 1700, 2600, 2800, 3300, 3400,
+ 1200, 1500, 2400, 2700, 2900, 3200,
+ 1700, 2100, 2400, 2800, 3200, 3400,
+ 1700, 2000, 2600, 2800, 3100, 3400,
+ 1700, 2000, 2600, 2700, 3000, 3300,
+ 1500, 1700, 2500, 2700, 3000, 3300,
+ 1600, 2000, 2600, 2800, 3100, 3300,
+ 1500, 2000, 2500, 2800, 3200, 3400,
+ 1400, 1800, 2500, 2800, 3300, 3400,
+ 1700, 2200, 2600, 2900, 3200, 3400,
+ 1700, 2200, 2600, 2800, 3200, 3400,
+ 1800, 2000, 2500, 2600, 3300, 3400,
+ 1500, 1800, 2200, 2500, 3100, 3200,
+ 1600, 2100, 2400, 2700, 3300, 3400,
+ 1400, 1800, 2500, 2700, 3000, 3300,
+ 1300, 1600, 2500, 2600, 3200, 3400,
+ 1400, 1700, 2500, 2600, 3300, 3400,
+ 1500, 1700, 2400, 2500, 3200, 3400,
+ 1900, 2000, 2300, 2500, 3200, 3400,
+ 1600, 1900, 2100, 2500, 3000, 3200,
+ 1600, 2100, 2500, 2800, 3200, 3300,
+ 1400, 2000, 2400, 2700, 3200, 3300,
+ 900, 1800, 2400, 2600, 3200, 3300,
+ 1100, 1600, 2700, 2800, 3200, 3400,
+ 1200, 1600, 2600, 2800, 3200, 3400,
+ 1300, 1700, 2500, 2700, 3100, 3300,
+ 1400, 1700, 2400, 2700, 3200, 3300,
+ 1400, 1800, 2300, 2500, 3100, 3200,
+ 1400, 2100, 2400, 2600, 2900, 3100,
+ 1300, 2000, 2400, 2600, 3100, 3200,
+ 1200, 1800, 2300, 2500, 3200, 3300,
+ 1300, 1900, 2300, 2500, 3100, 3300,
+ 1600, 2000, 2400, 2600, 3200, 3400,
+ 1800, 2000, 2300, 2500, 3100, 3400,
+ 1700, 1900, 2300, 2400, 3100, 3300,
+ 1600, 1800, 2300, 2400, 2900, 3300,
+ 1600, 1800, 2300, 2400, 3000, 3300,
+ 1600, 1700, 2300, 2400, 3000, 3300,
+ 1600, 1700, 2300, 2400, 2800, 3200,
+ 1600, 1700, 2300, 2400, 2900, 3300,
+ 1500, 1700, 2300, 2500, 3000, 3300,
+ 1400, 1700, 2500, 2600, 3200, 3300,
+ 1300, 1600, 2500, 2700, 3100, 3300,
+ 1300, 1500, 2500, 2700, 3100, 3300,
+ 1300, 1600, 2400, 2700, 3000, 3400,
+ 1800, 2300, 2600, 2800, 3100, 3300,
+ 1800, 2200, 2500, 2800, 3100, 3300,
+ 1700, 2100, 2500, 2700, 3000, 3300,
+ 1600, 1900, 2500, 2700, 2900, 3200,
+ 1700, 2000, 2500, 2700, 3000, 3200,
+ 1700, 2300, 2600, 2700, 3200, 3400,
+ 1400, 1700, 1900, 2200, 3200, 3300,
+ 1200, 1900, 2100, 2600, 3100, 3200,
+ 1200, 1900, 2200, 2700, 3100, 3200,
+ 1200, 1900, 2300, 2700, 3200, 3300,
+ 1100, 2000, 2300, 2600, 3200, 3300,
+ 1200, 1900, 2400, 2700, 3200, 3300,
+ 1200, 1800, 2300, 2600, 3200, 3400,
+ 1200, 1600, 2400, 2700, 3200, 3400,
+ 1200, 1500, 2400, 2600, 3000, 3200,
+ 1300, 1500, 2100, 2500, 2700, 3000,
+ 1200, 1800, 2400, 2600, 3100, 3200,
+ 1200, 2000, 2400, 2500, 3200, 3300,
+ 1700, 2400, 2700, 3100, 3300, 3400,
+ 2000, 2500, 2700, 3100, 3400, 3500,
+ 1900, 2400, 2700, 3100, 3400, 3500,
+ 1900, 2200, 2700, 3100, 3300, 3400,
+ 1800, 2200, 2700, 3100, 3300, 3400,
+ 1500, 1700, 2100, 2500, 3200, 3300,
+ 1400, 1800, 2100, 2600, 3200, 3300,
+ 1200, 1700, 2000, 2300, 3300, 3400,
+ 1300, 1500, 1600, 2300, 3100, 3200,
+ 1500, 1900, 2400, 2600, 3000, 3300,
+ 1500, 2000, 2400, 2500, 2800, 3200,
+ 1400, 2000, 2400, 2500, 2900, 3200,
+ 1300, 1600, 1700, 2300, 3300, 3400,
+ 1300, 1600, 1700, 2100, 3200, 3400,
+ 2000, 2200, 2500, 2900, 3300, 3400,
+ 2100, 2300, 2500, 2700, 3300, 3400,
+ 1900, 2200, 2400, 2700, 3300, 3400,
+ 1500, 1900, 2200, 2400, 3000, 3300,
+ 1500, 1900, 2400, 2700, 3300, 3400,
+ 1500, 1700, 2500, 2700, 3200, 3400,
+ 1500, 1700, 2500, 2600, 3100, 3400,
+ 1600, 2000, 2400, 2700, 3200, 3300,
+ 1600, 1800, 2200, 2600, 3000, 3100,
+ 1500, 1800, 2200, 2600, 3000, 3100,
+ 1500, 1900, 2400, 2500, 3000, 3200,
+ 1200, 1500, 2400, 2600, 3200, 3300,
+ 1500, 2000, 2500, 2700, 3100, 3300,
+ 1700, 2100, 2500, 2900, 3200, 3300,
+ 1400, 1800, 2400, 2500, 3100, 3300,
+ 1400, 2000, 2300, 2500, 3200, 3400,
+ 1200, 1900, 2200, 2400, 3300, 3400,
+ 1200, 1900, 2300, 2500, 3300, 3400,
+ 1200, 1900, 2300, 2400, 3300, 3400,
+ 1200, 1700, 2300, 2400, 3300, 3400,
+ 1200, 1600, 2200, 2300, 3300, 3400,
+ 1200, 1600, 2200, 2400, 3300, 3400,
+ 1300, 1600, 2100, 2400, 3200, 3300,
+ 1500, 1700, 2200, 2600, 2900, 3200,
+ 2100, 2200, 2500, 2800, 3200, 3300,
+ 1600, 1800, 2300, 2500, 3100, 3300,
+ 1500, 1800, 2300, 2500, 3100, 3300,
+ 1400, 1800, 2300, 2600, 3100, 3300,
+ 1400, 1800, 2400, 2600, 3100, 3300,
+ 1300, 1800, 2400, 2700, 3200, 3300,
+ 1100, 1800, 2400, 2700, 3200, 3300,
+ 1400, 2000, 2500, 2600, 2900, 3200,
+ 1500, 2100, 2500, 2600, 2900, 3200,
+ 1500, 1900, 2400, 2600, 3100, 3300,
+ 1300, 1900, 2400, 2800, 3100, 3300,
+ 1300, 2000, 2500, 2700, 3200, 3300,
+ 1300, 1800, 2600, 2700, 3100, 3400,
+ 1300, 1700, 2600, 2700, 3100, 3300,
+ 1300, 1700, 2600, 2700, 3100, 3400,
+ 1400, 1900, 2400, 2600, 2900, 3100,
+ 1500, 1800, 2300, 2600, 2900, 3100,
+ 1600, 1900, 2400, 2600, 3000, 3200,
+ 1700, 2000, 2600, 2900, 3100, 3300,
+ 1800, 2300, 2500, 2800, 3200, 3400,
+ 1900, 2300, 2600, 2900, 3300, 3400,
+ 1600, 1900, 2500, 2600, 3000, 3100,
+ 1600, 1900, 2500, 2600, 3000, 3200,
+ 1500, 1800, 2200, 2500, 3200, 3300,
+ 1500, 1900, 2200, 2500, 3300, 3400,
+ 1500, 1800, 2200, 2400, 3200, 3400,
+ 1500, 1800, 2100, 2400, 3200, 3400,
+ 1600, 1800, 2100, 2200, 3200, 3400,
+ 1700, 1800, 2100, 2400, 3100, 3300,
+ 1600, 1700, 2300, 2400, 2700, 3100,
+ 1600, 1900, 2400, 2500, 3000, 3300,
+ 1600, 2100, 2500, 2600, 3200, 3400,
+ 1200, 2000, 2400, 2500, 3400, 3500,
+ 1200, 1600, 2300, 2400, 3200, 3400,
+ 1400, 1900, 2400, 2500, 3000, 3200,
+ 1300, 1800, 2100, 2500, 3100, 3300,
+ 1300, 1700, 2300, 2500, 3100, 3300,
+ 1300, 1700, 2200, 2400, 3200, 3300,
+ 1300, 1800, 2200, 2400, 3200, 3300,
+ 1500, 1800, 2300, 2500, 3200, 3300,
+ 1600, 1800, 2300, 2500, 3300, 3400,
+ 1700, 1900, 2400, 2600, 3300, 3400,
+ 1700, 1900, 2500, 2700, 3000, 3100,
+ 1700, 1800, 2500, 2600, 3100, 3200,
+ 1700, 1800, 2500, 2600, 3000, 3200,
+ 1600, 1800, 2400, 2600, 3000, 3200,
+ 1600, 1800, 2400, 2600, 3100, 3300,
+ 1500, 1700, 2400, 2600, 3100, 3300,
+ 1300, 1700, 2400, 2600, 3100, 3300,
+ 1300, 1700, 2400, 2600, 3200, 3300,
+ 1400, 1800, 2400, 2600, 3200, 3300,
+ 1400, 1800, 2300, 2600, 3200, 3300,
+ 1500, 1800, 2300, 2600, 3300, 3400,
+ 1500, 1800, 2300, 2500, 3300, 3400,
+ 1500, 1700, 2200, 2400, 3300, 3400,
+ 1800, 2200, 2400, 2600, 3200, 3300,
+ 1700, 1900, 2300, 2700, 3200, 3300,
+ 1600, 1800, 2000, 2600, 3200, 3300,
+ 1900, 2000, 2200, 2500, 3300, 3400,
+ 1900, 2100, 2300, 2600, 3300, 3400,
+ 1800, 1900, 2200, 2600, 3100, 3300,
+ 1100, 1900, 2600, 2700, 3200, 3300,
+ 1000, 1700, 2700, 2800, 3200, 3300,
+ 1000, 1800, 2600, 2700, 3000, 3100,
+ 1200, 2000, 2600, 2800, 3200, 3300,
+ 1200, 2000, 2500, 2700, 3200, 3300,
+ 1200, 2000, 2500, 2600, 3200, 3300,
+ 1200, 2000, 2400, 2500, 3300, 3400,
+ 1300, 2000, 2300, 2500, 3300, 3400,
+ 1300, 1900, 2300, 2500, 3300, 3400,
+ 1400, 1900, 2300, 2600, 3300, 3400,
+ 2200, 2400, 2500, 2900, 3200, 3300,
+ 2100, 2200, 2400, 2800, 3200, 3300,
+ 2000, 2200, 2400, 2800, 3200, 3300,
+ 1900, 2100, 2400, 2800, 3200, 3300,
+ 1600, 1800, 2000, 2400, 2800, 3000,
+ 1600, 1900, 2300, 2400, 2900, 3300,
+ 1800, 2100, 2400, 2500, 3100, 3200,
+ 1800, 2300, 2500, 2700, 3200, 3300,
+ 1800, 2100, 2500, 2700, 3300, 3400,
+ 1500, 1900, 2100, 2700, 3000, 3100,
+ 1500, 1700, 1800, 2600, 3300, 3400,
+ 1500, 1700, 1800, 2500, 3300, 3400,
+ 1300, 1500, 1600, 2500, 3200, 3300,
+ 1300, 1500, 1700, 2400, 3000, 3100,
+ 1600, 2000, 2500, 2700, 3300, 3400,
+ 2000, 2100, 2400, 2700, 3300, 3400,
+ 1800, 2000, 2200, 2600, 3100, 3300,
+ 1800, 1900, 2100, 2600, 3200, 3300,
+ 1700, 2000, 2100, 2700, 3200, 3300,
+ 1700, 2100, 2200, 2700, 3200, 3300,
+ 1700, 2200, 2400, 2700, 3200, 3300,
+ 1700, 2200, 2400, 2600, 3200, 3300,
+ 1700, 2100, 2500, 2600, 3200, 3300,
+ 1800, 2400, 2600, 3000, 3300, 3400,
+ 1800, 2400, 2800, 3100, 3300, 3400,
+ 1900, 2400, 2800, 3100, 3300, 3500,
+ 1900, 2300, 2800, 3000, 3300, 3400,
+ 1600, 1800, 2400, 2600, 3000, 3100,
+ 1500, 1700, 1900, 2500, 3300, 3400,
+ 1200, 1700, 2200, 2300, 3100, 3300,
+ 1100, 1500, 2300, 2400, 3000, 3300,
+ 1200, 1600, 2300, 2400, 3100, 3300,
+ 1200, 1600, 2300, 2400, 3100, 3400,
+ 1300, 1600, 2200, 2400, 3200, 3300,
+ 1500, 1600, 2100, 2400, 3000, 3300,
+ 1600, 1700, 2100, 2400, 3100, 3300,
+ 1500, 1600, 2100, 2500, 3100, 3300,
+ 1600, 1900, 2200, 2600, 3100, 3300,
+ 1500, 1800, 2200, 2500, 3000, 3200,
+ 1400, 1800, 2200, 2500, 2900, 3200,
+ 1300, 1600, 2200, 2600, 3000, 3200,
+ 1700, 2000, 2400, 2800, 3000, 3100,
+ 1700, 2100, 2400, 2700, 3000, 3100,
+ 1800, 2200, 2500, 2800, 3000, 3200,
+ 1700, 2100, 2500, 2800, 3100, 3200,
+ 1800, 2200, 2500, 2700, 3200, 3400,
+ 1600, 1900, 2300, 2500, 3200, 3300,
+ 1600, 1800, 2100, 2500, 3200, 3300,
+ 1600, 1800, 2000, 2400, 3200, 3300,
+ 1500, 1700, 1900, 2300, 3300, 3400,
+ 1400, 1600, 1800, 2200, 3300, 3400,
+ 1500, 1600, 1900, 2600, 3000, 3200,
+ 1500, 2000, 2300, 2600, 3200, 3300,
+ 1200, 1900, 2100, 2500, 3200, 3300,
+ 1900, 2100, 2300, 2600, 3200, 3300,
+ 1800, 2100, 2300, 2600, 3300, 3400,
+ 1700, 2100, 2300, 2600, 3200, 3300,
+ 1600, 2100, 2300, 2700, 3200, 3300,
+ 1500, 1900, 2400, 2700, 3200, 3300,
+ 1400, 1900, 2400, 2700, 3200, 3300,
+ 1400, 1900, 2400, 2600, 3200, 3300,
+ 1500, 2100, 2500, 2600, 3200, 3300,
+ 1600, 1800, 2100, 2500, 2900, 3100,
+ 1800, 2000, 2500, 2800, 3000, 3200,
+ 1400, 1600, 2100, 2600, 3000, 3300,
+ 1700, 2000, 2400, 2700, 3300, 3400,
+ 1700, 2100, 2500, 2700, 3300, 3400,
+ 1700, 2100, 2600, 2700, 3000, 3300,
+ 1800, 2100, 2500, 2700, 3100, 3200,
+ 2200, 2300, 2500, 2800, 3200, 3300,
+ 2100, 2300, 2500, 2800, 3200, 3300,
+ 2000, 2200, 2500, 2800, 3200, 3300,
+ 1900, 2000, 2400, 2700, 3100, 3200,
+ 1600, 2000, 2400, 2700, 3100, 3400,
+ 1300, 1800, 2100, 2500, 3100, 3200,
+ 1300, 1800, 2200, 2800, 3100, 3200,
+ 1300, 2000, 2200, 2600, 3200, 3300,
+ 1900, 2100, 2400, 2500, 3000, 3200,
+ 1800, 2100, 2400, 2600, 3200, 3300,
+ 1500, 1900, 2400, 2600, 3300, 3400,
+ 1500, 1800, 2400, 2600, 3200, 3400,
+ 1500, 1700, 2400, 2600, 3200, 3400,
+ 1400, 1700, 2400, 2600, 3100, 3300,
+ 1400, 1900, 2500, 2600, 2900, 3200,
+ 1400, 1900, 2400, 2700, 3000, 3200,
+ 1400, 1900, 2400, 2600, 3000, 3100,
+ 1400, 1900, 2300, 2500, 2700, 3000,
+ 1300, 1800, 2200, 2500, 3300, 3400,
+ 1300, 1800, 2200, 2400, 3300, 3400,
+ 1300, 1700, 2100, 2400, 3200, 3400,
+ 1400, 1900, 2300, 2600, 3100, 3300,
+ 1900, 2200, 2400, 2800, 3100, 3200,
+ 1600, 2200, 2400, 2700, 3300, 3400,
+ 1600, 2100, 2400, 2700, 3200, 3300,
+ 1400, 1700, 2000, 2500, 3000, 3200,
+ 1400, 1800, 2300, 2500, 3000, 3200,
+ 1700, 1900, 2100, 2400, 3200, 3300,
+ 1800, 1900, 2200, 2500, 3200, 3300,
+ 1900, 2000, 2500, 2700, 3200, 3300,
+ 1900, 2000, 2500, 2600, 3100, 3300,
+ 1400, 1900, 2300, 2500, 2800, 3200,
+ 1400, 1900, 2300, 2500, 2900, 3300,
+ 1400, 1600, 2300, 2500, 3000, 3200,
+ 1400, 1600, 2200, 2500, 3100, 3200,
+ 2000, 2200, 2500, 2700, 3000, 3300,
+ 1600, 2100, 2600, 2900, 3200, 3300,
+ 1500, 1700, 2100, 2500, 3100, 3200,
+ 1200, 2100, 2600, 2700, 3200, 3300,
+ 1100, 2100, 2600, 2800, 3200, 3300,
+ 1000, 2000, 2800, 2900, 3100, 3200,
+ 1600, 1900, 2100, 2500, 3000, 3100,
+ 1700, 1900, 2200, 2500, 3000, 3100,
+ 1700, 1900, 2300, 2400, 3100, 3200,
+ 1400, 2000, 2300, 2400, 3200, 3300,
+ 1300, 2000, 2200, 2400, 3100, 3200,
+ 1200, 2000, 2300, 2500, 3100, 3200,
+ 1200, 1800, 2300, 2600, 3100, 3200,
+ 1300, 1600, 2300, 2700, 3100, 3200,
+ 1300, 1700, 2300, 2700, 3100, 3200,
+ 1100, 2000, 2300, 2600, 3100, 3200,
+ 1300, 2000, 2400, 2500, 3200, 3300,
+ 1300, 1900, 2400, 2500, 3200, 3300,
+ 1500, 1800, 2100, 2600, 3300, 3400,
+ 1500, 1900, 2100, 2500, 2800, 3000,
+ 1500, 2000, 2200, 2500, 3000, 3100,
+ 1500, 2000, 2200, 2600, 3100, 3200,
+ 1600, 1900, 2300, 2500, 3100, 3200,
+ 1600, 1900, 2200, 2400, 3100, 3200,
+ 1600, 1900, 2400, 2600, 2900, 3100,
+ 1900, 2300, 2600, 2800, 3100, 3200,
+ 2000, 2400, 2700, 2800, 3100, 3200,
+ 1300, 1800, 2000, 2400, 3100, 3200,
+ 1100, 1700, 2100, 2400, 3100, 3200,
+ 1300, 1600, 2100, 2500, 3000, 3100,
+ 1200, 1700, 2200, 2500, 3000, 3200,
+ 1400, 1800, 2100, 2300, 3100, 3200,
+ 1700, 1800, 2100, 2200, 3200, 3300,
+ 1700, 1900, 2100, 2300, 3200, 3300,
+ 1800, 1900, 2400, 2800, 3100, 3200,
+ 2000, 2300, 2800, 3000, 3100, 3300,
+ 2100, 2300, 2700, 3000, 3200, 3300,
+ 2100, 2300, 2600, 2900, 3200, 3300,
+ 2200, 2400, 2700, 2800, 3200, 3300,
+ 1700, 2000, 2300, 2500, 3000, 3100,
+ 1600, 2000, 2300, 2400, 2800, 3200,
+ 1700, 2100, 2300, 2400, 2900, 3200,
+ 1400, 1800, 2300, 2600, 3000, 3300,
+ 1500, 2200, 2400, 2700, 3100, 3200,
+ 1500, 2200, 2500, 2700, 3200, 3300,
+ 1400, 1600, 2400, 2500, 3100, 3400,
+ 1600, 2200, 2500, 2800, 3300, 3400,
+ 1600, 2000, 2500, 2800, 3300, 3400,
+ 1400, 1700, 2400, 2500, 3200, 3400,
+ 1400, 1600, 2400, 2600, 3200, 3300,
+ 1400, 1700, 2300, 2500, 3200, 3300,
+ 1500, 2000, 2300, 2400, 2800, 3200,
+ 1500, 2000, 2300, 2400, 2700, 3200,
+ 1400, 1900, 2300, 2500, 3000, 3300,
+ 1200, 1400, 2300, 2600, 2900, 3100,
+ 1500, 2000, 2300, 2500, 3000, 3200,
+ 1800, 2000, 2500, 2600, 3100, 3200,
+ 1500, 1800, 2400, 2600, 3000, 3200,
+ 1200, 1500, 2200, 2400, 3000, 3100,
+ 1500, 1900, 2400, 2600, 3200, 3300,
+ 1700, 2000, 2600, 2800, 3200, 3300,
+ 1500, 1900, 2100, 2500, 3200, 3300,
+ 1700, 1800, 2000, 2300, 3000, 3100,
+ 1600, 1900, 2300, 2500, 2800, 3100,
+ 1600, 1800, 2300, 2500, 3000, 3200,
+ 1700, 1800, 2300, 2500, 3200, 3300,
+ 1700, 1800, 2300, 2500, 3100, 3300,
+ 1600, 1700, 2200, 2400, 3000, 3300,
+ 1500, 1700, 2300, 2500, 3200, 3400,
+ 1500, 1700, 2300, 2400, 2800, 3300,
+ 1600, 1700, 2200, 2400, 2600, 3200,
+ 1700, 1800, 2200, 2400, 2900, 3300,
+ 1900, 2100, 2400, 2500, 3100, 3300,
+ 1900, 2000, 2400, 2500, 3100, 3300,
+ 1900, 2300, 2500, 2900, 3200, 3300,
+ 2200, 2400, 2700, 3100, 3300, 3400,
+ 2200, 2400, 2800, 3100, 3300, 3400,
+ 1500, 1900, 2300, 2400, 3200, 3300,
+ 1500, 1800, 2200, 2300, 3100, 3300,
+ 1700, 2000, 2600, 2900, 3200, 3400,
+ 1500, 2000, 2300, 2500, 3100, 3200,
+ 1300, 1600, 2000, 2500, 3000, 3200,
+ 1800, 2000, 2200, 2500, 3000, 3100,
+ 1200, 1800, 2200, 2400, 3100, 3200,
+ 1300, 1500, 2100, 2200, 3100, 3200,
+ 1400, 1900, 2200, 2300, 3200, 3300,
+ 1900, 2300, 2600, 3000, 3200, 3400,
+ 1900, 2300, 2600, 2800, 3200, 3300,
+ 1900, 2200, 2600, 2900, 3100, 3300,
+ 1200, 1500, 2500, 2600, 3100, 3200,
+ 1400, 1900, 2300, 2400, 2600, 3100,
+ 1500, 1600, 2100, 2400, 2900, 3200,
+ 1400, 1600, 2200, 2600, 2900, 3200,
+ 1700, 1800, 2100, 2300, 3000, 3100,
+ 1700, 1900, 2100, 2300, 3100, 3200,
+ 1800, 1900, 2200, 2300, 3200, 3300,
+ 1700, 1900, 2200, 2300, 3200, 3300,
+ 1700, 1800, 2200, 2300, 3200, 3300,
+ 1600, 1700, 2200, 2300, 3100, 3300,
+ 1700, 2100, 2400, 2900, 3300, 3400,
+ 1600, 2100, 2500, 2700, 3300, 3400,
+ 1500, 2000, 2400, 2600, 3100, 3200,
+ 1600, 2000, 2300, 2500, 2800, 3000,
+ 1500, 1700, 1800, 2200, 2800, 2900,
+ 1500, 1700, 1900, 2100, 2700, 2800,
+ 1600, 2000, 2300, 2500, 3000, 3300,
+ 1900, 2300, 2500, 2800, 3100, 3200,
+ 2200, 2400, 2600, 3000, 3200, 3300,
+ 2300, 2500, 2800, 3100, 3300, 3400,
+ 1900, 2400, 2700, 3000, 3400, 3500,
+ 1900, 2400, 2600, 3000, 3400, 3500,
+ 1800, 2300, 2700, 3100, 3400, 3500,
+ 1800, 2300, 2700, 3000, 3300, 3400,
+ 1400, 1700, 2200, 2500, 3200, 3400,
+ 1600, 1900, 2500, 2600, 3100, 3300,
+ 2000, 2300, 2600, 2800, 3300, 3400,
+ 1900, 2200, 2500, 2800, 3300, 3400,
+ 1700, 2100, 2400, 2700, 3300, 3400,
+ 1600, 1700, 2300, 2500, 3200, 3400,
+ 1600, 1700, 2300, 2400, 3300, 3400,
+ 1600, 1800, 2400, 2600, 3300, 3400,
+ 1500, 1700, 2300, 2700, 3300, 3400,
+ 1400, 1800, 2300, 2400, 3100, 3400,
+ 1500, 2000, 2300, 2400, 2900, 3200,
+ 1500, 1900, 2300, 2400, 2800, 3200,
+ 1300, 1800, 2200, 2500, 3000, 3100,
+ 1200, 1700, 2200, 2300, 3200, 3300,
+ 1200, 1700, 2200, 2400, 3200, 3300,
+ 1100, 1700, 2200, 2400, 3200, 3300,
+ 1100, 1700, 2300, 2500, 3100, 3200,
+ 1100, 1700, 2300, 2600, 3100, 3200,
+ 1300, 1800, 2300, 2600, 3000, 3200,
+ 1300, 1900, 2300, 2600, 3000, 3300,
+ 1300, 1800, 2300, 2600, 3100, 3300,
+ 1400, 2000, 2500, 2800, 3200, 3300,
+ 1200, 1600, 2400, 2700, 3200, 3300,
+ 1500, 1800, 2300, 2500, 3100, 3200,
+ 1500, 1600, 2200, 2600, 3000, 3200,
+ 1500, 1600, 2200, 2500, 3000, 3300,
+ 1200, 1600, 2400, 2600, 3200, 3400,
+ 1000, 2300, 2800, 2900, 3100, 3200,
+ 900, 1700, 2700, 2800, 3200, 3300,
+ 1500, 1700, 2400, 2500, 3100, 3200,
+ 1500, 1900, 2400, 2500, 3100, 3200,
+ 1400, 1900, 2400, 2500, 2900, 3100,
+ 1600, 2100, 2400, 2600, 3000, 3100,
+ 1700, 1900, 2300, 2500, 3000, 3100,
+ 2100, 2400, 2600, 2900, 3100, 3300,
+ 2200, 2400, 2700, 2900, 3200, 3300,
+ 2100, 2200, 2700, 2800, 3100, 3300,
+ 2000, 2100, 2300, 2600, 3100, 3300,
+ 1800, 2000, 2100, 2600, 3100, 3200,
+ 1800, 1900, 2200, 2500, 2900, 3000,
+ 1800, 1900, 2300, 2400, 3000, 3100,
+ 1800, 1900, 2200, 2400, 3000, 3100,
+ 1800, 2000, 2200, 2500, 3100, 3200,
+ 1800, 2000, 2300, 2800, 3100, 3200,
+ 1800, 2000, 2400, 2800, 3100, 3200,
+ 1800, 2000, 2400, 2800, 3000, 3100,
+ 1700, 1900, 2300, 2700, 2900, 3100,
+ 1700, 1900, 2200, 2700, 2900, 3100,
+ 1600, 1800, 2000, 2600, 2800, 3000,
+ 1500, 1700, 2000, 2500, 2900, 3100,
+ 1700, 1900, 2200, 2500, 3000, 3200,
+ 1700, 1800, 2300, 2400, 3100, 3300,
+ 1800, 2000, 2300, 2500, 3000, 3100,
+ 1800, 1900, 2200, 2400, 3100, 3200,
+ 1400, 1600, 2100, 2600, 3000, 3200,
+ 1400, 1600, 2000, 2500, 3000, 3200,
+ 1400, 1800, 2000, 2400, 3200, 3300,
+ 1200, 1900, 2100, 2500, 3100, 3200,
+ 1100, 1700, 2100, 2300, 3000, 3100,
+ 1300, 1500, 1700, 2000, 2900, 3100,
+ 1600, 1900, 2200, 2400, 2900, 3100,
+ 1700, 2000, 2200, 2500, 3200, 3300,
+ 1700, 1800, 2100, 2500, 3100, 3300,
+ 2000, 2300, 2500, 2700, 3100, 3400,
+ 1900, 2200, 2500, 2600, 3000, 3300,
+ 1900, 2000, 2300, 2400, 3100, 3300,
+ 1800, 1900, 2300, 2400, 3000, 3200,
+ 1800, 1900, 2300, 2500, 3100, 3200,
+ 1700, 1800, 2300, 2400, 3000, 3100,
+ 1500, 1600, 2500, 2600, 2900, 3300,
+ 1500, 1700, 2500, 2600, 3100, 3200,
+ 1900, 2300, 2500, 2800, 3200, 3300,
+ 1400, 1600, 2000, 2600, 3000, 3200,
+ 1700, 1900, 2100, 2600, 3000, 3100,
+ 1800, 1900, 2400, 2900, 3100, 3300,
+ 1800, 1900, 2500, 2900, 3100, 3300,
+ 1600, 1800, 2100, 2700, 3000, 3200,
+ 1700, 2000, 2300, 2700, 2900, 3200,
+ 1600, 2000, 2400, 2600, 2900, 3200,
+ 1500, 1700, 2300, 2500, 3300, 3400,
+ 1400, 1600, 2200, 2400, 3100, 3300,
+ 1500, 1600, 2200, 2500, 3200, 3400,
+ 1600, 1700, 2300, 2400, 3200, 3300,
+ 1600, 1700, 2300, 2500, 3200, 3300,
+ 1600, 1700, 2200, 2500, 3200, 3300,
+ 1700, 2100, 2300, 2400, 3100, 3300,
+ 1600, 2000, 2400, 2500, 3000, 3300,
+ 1500, 1800, 2300, 2400, 2900, 3200,
+ 1600, 2000, 2400, 2800, 3200, 3400,
+ 1900, 2200, 2600, 2800, 3200, 3400,
+ 1900, 2200, 2500, 2800, 3100, 3400,
+ 1300, 1800, 2400, 2600, 3100, 3400,
+ 1300, 1500, 2400, 2500, 2900, 3300,
+ 1300, 1700, 2500, 2600, 3100, 3200,
+ 1300, 1700, 2600, 2700, 3200, 3300,
+ 1400, 1900, 2600, 2700, 3200, 3300,
+ 1400, 2000, 2600, 2700, 3200, 3300,
+ 1700, 1900, 2100, 2600, 3200, 3300,
+ 1700, 2000, 2100, 2300, 3200, 3300,
+ 2000, 2100, 2400, 2600, 3200, 3400,
+ 2100, 2200, 2500, 2700, 3200, 3400,
+ 1800, 1900, 2500, 2700, 3200, 3400,
+ 1700, 2000, 2500, 2700, 3300, 3400,
+ 1400, 1900, 2500, 2700, 3100, 3200,
+ 1500, 1800, 2500, 2600, 3100, 3300,
+ 1600, 2000, 2300, 2600, 3000, 3200,
+ 1600, 1900, 2300, 2700, 3000, 3200,
+ 1600, 1800, 2300, 2600, 3000, 3200,
+ 1400, 1600, 2100, 2500, 3000, 3200,
+ 1400, 1800, 2200, 2500, 2700, 3100,
+ 1400, 1900, 2300, 2500, 3100, 3200,
+ 1300, 2000, 2300, 2500, 3100, 3200,
+ 1300, 1900, 2300, 2500, 3100, 3200,
+ 1800, 2100, 2500, 2700, 3000, 3300,
+ 1800, 2100, 2400, 2700, 3100, 3300,
+ 1900, 2100, 2500, 2700, 3100, 3300,
+ 1600, 1800, 2300, 2400, 3200, 3400,
+ 1700, 1800, 2400, 2500, 3300, 3400,
+ 1900, 2000, 2700, 2800, 3200, 3400,
+ 1900, 2000, 2600, 2900, 3100, 3300,
+ 2000, 2200, 2800, 2900, 3300, 3400,
+ 2000, 2100, 2700, 2800, 3300, 3400,
+ 1900, 2100, 2400, 2700, 3300, 3400,
+ 1600, 1900, 2100, 2500, 3200, 3300,
+ 1400, 1900, 2100, 2400, 3200, 3300,
+ 1200, 1900, 2100, 2400, 3100, 3200,
+ 1200, 1800, 2100, 2500, 2900, 3200,
+ 1300, 1700, 1900, 2400, 2800, 2900,
+ 1900, 2300, 2600, 3000, 3200, 3300,
+ 1800, 2300, 2600, 3000, 3300, 3400,
+ 1800, 2200, 2500, 2800, 3300, 3500,
+ 1700, 1900, 2300, 2400, 3200, 3400,
+ 1800, 1900, 2400, 2500, 3100, 3300,
+ 2100, 2200, 2400, 2500, 3100, 3300,
+ 1800, 2100, 2500, 2800, 3100, 3200,
+ 2000, 2300, 2600, 2700, 3100, 3300,
+ 2100, 2200, 2500, 2600, 3100, 3300,
+ 2000, 2200, 2300, 2500, 3100, 3300,
+ 1800, 1900, 2100, 2300, 3200, 3300,
+ 1800, 1900, 2100, 2400, 3300, 3400,
+ 1700, 1800, 2200, 2300, 3300, 3400,
+ 1700, 1800, 2200, 2300, 3200, 3400,
+ 1600, 1700, 2200, 2300, 2900, 3400,
+ 1400, 1600, 2500, 2600, 3100, 3200,
+ 1300, 1400, 2400, 2600, 3000, 3100,
+ 1300, 1500, 2400, 2500, 3000, 3200,
+ 1300, 1800, 2400, 2500, 3100, 3200,
+ 1300, 1900, 2400, 2500, 3100, 3200,
+ 1800, 1900, 2200, 2400, 3300, 3400,
+ 1000, 1500, 2500, 2600, 3200, 3400,
+ 1000, 1700, 2500, 2600, 3200, 3300,
+ 1300, 1700, 2200, 2600, 3000, 3200,
+ 900, 1800, 2400, 2600, 3300, 3400,
+ 900, 1800, 2300, 2400, 3300, 3400,
+ 1000, 1600, 2300, 2400, 3300, 3400,
+ 1400, 1900, 2200, 2600, 3300, 3400,
+ 1500, 1900, 2300, 2600, 3300, 3400,
+ 1300, 2000, 2200, 2500, 3000, 3200,
+ 1100, 1800, 2300, 2500, 3200, 3300,
+ 1100, 1800, 2400, 2600, 3200, 3300,
+ 1100, 1900, 2400, 2700, 3200, 3300,
+ 1300, 2000, 2200, 2400, 3200, 3300,
+ 1800, 2100, 2400, 2800, 3300, 3400,
+ 1700, 2200, 2500, 2700, 3300, 3400,
+ 1700, 2000, 2300, 2700, 3200, 3400,
+ 1200, 1600, 2500, 2600, 3200, 3400,
+ 1100, 1900, 2500, 2600, 3200, 3300,
+ 1500, 1600, 2400, 2700, 2900, 3200,
+ 1500, 1800, 2500, 2700, 3100, 3400,
+ 1600, 1900, 2600, 2800, 3100, 3300,
+ 1700, 1800, 2600, 2700, 3000, 3300,
+ 1700, 1800, 2500, 2600, 2900, 3200,
+ 1700, 1800, 2500, 2600, 3000, 3300,
+ 1600, 1700, 2500, 2600, 3000, 3300,
+ 1700, 2000, 2400, 2700, 3100, 3400,
+ 1700, 1800, 2400, 2600, 2900, 3200,
+ 1800, 1900, 2500, 2600, 2900, 3200,
+ 1700, 1800, 2200, 2500, 2700, 3200,
+ 1700, 1800, 2300, 2500, 2800, 3200,
+ 1500, 1600, 2000, 2400, 2600, 2900,
+ 1200, 1300, 2100, 2400, 2600, 3200,
+ 1700, 2200, 2500, 2900, 3200, 3400,
+ 1700, 2200, 2600, 2900, 3400, 3500,
+ 1700, 2100, 2700, 2900, 3400, 3500,
+ 1500, 1800, 2400, 2600, 3100, 3300,
+ 1100, 1700, 2500, 2600, 3200, 3300,
+ 1300, 1700, 2600, 2700, 3200, 3400,
+ 1400, 1900, 2600, 2800, 3200, 3300,
+ 1600, 2000, 2500, 2900, 3300, 3400,
+ 1500, 1700, 2500, 2700, 3100, 3300,
+ 1800, 2000, 2500, 2700, 2900, 3300,
+ 1900, 2000, 2600, 2700, 2900, 3300,
+ 1900, 2100, 2400, 2700, 2900, 3200,
+ 1900, 2000, 2500, 2700, 3000, 3300,
+ 1900, 2000, 2400, 2700, 3000, 3300,
+ 1700, 1900, 2500, 2600, 3100, 3400,
+ 1600, 1900, 2500, 2600, 3200, 3500,
+ 1900, 2100, 2600, 2900, 3200, 3400,
+ 2100, 2300, 2700, 2900, 3200, 3300,
+ 1600, 2000, 2200, 2400, 3100, 3200,
+ 1700, 1900, 2200, 2400, 2900, 3100,
+ 1700, 1800, 2100, 2400, 2800, 3200,
+ 1900, 2200, 2500, 2700, 3000, 3200,
+ 1900, 2300, 2600, 2700, 3100, 3200,
+ 1800, 2400, 2600, 2900, 3200, 3300,
+ 1800, 2300, 2500, 2900, 3200, 3300,
+ 1600, 1800, 2500, 2600, 3300, 3400,
+ 1500, 1700, 2200, 2400, 2900, 3200,
+ 1500, 1600, 2200, 2300, 2800, 3200,
+ 1400, 1500, 2100, 2200, 2800, 3200,
+ 1400, 1500, 2100, 2300, 2800, 3200,
+ 1400, 1500, 2200, 2400, 2700, 3100,
+ 1700, 1900, 2400, 2800, 3100, 3200,
+ 1700, 1800, 2400, 2700, 3100, 3300,
+ 1800, 1900, 2300, 2700, 2900, 3300,
+ 2000, 2100, 2400, 2700, 3000, 3300,
+ 1400, 1600, 2500, 2700, 3100, 3400,
+ 1000, 1600, 2300, 2400, 3100, 3200,
+ 1100, 1700, 2400, 2500, 3200, 3300,
+ 1200, 1700, 2300, 2400, 3100, 3200,
+ 2000, 2100, 2400, 2500, 3100, 3300,
+ 1900, 2000, 2300, 2500, 3100, 3300,
+ 1600, 1800, 2300, 2500, 3200, 3300,
+ 1400, 1600, 2300, 2400, 3100, 3300,
+ 1300, 1500, 2300, 2500, 3000, 3300,
+ 1300, 1500, 2300, 2500, 3100, 3200,
+ 1300, 1800, 2300, 2600, 3100, 3200,
+ 1800, 1900, 2400, 2500, 3000, 3200,
+ 1900, 2400, 2600, 3000, 3200, 3300,
+ 1400, 1500, 2400, 2600, 2900, 3300,
+ 1400, 1500, 2200, 2600, 2800, 3300,
+ 1400, 1500, 2200, 2500, 2800, 3200,
+ 1400, 1500, 2300, 2500, 3000, 3300,
+ 1600, 2000, 2400, 2700, 3200, 3400,
+ 1700, 2200, 2600, 2800, 3100, 3300,
+ 1800, 2100, 2600, 2700, 3200, 3300,
+ 1700, 2200, 2500, 2700, 3200, 3300,
+ 1500, 1700, 2200, 2300, 3000, 3300,
+ 1600, 1700, 2200, 2500, 3200, 3400,
+ 1600, 1800, 2300, 2400, 3100, 3300,
+ 1700, 1800, 2200, 2400, 3000, 3300,
+ 1700, 1800, 2200, 2300, 3000, 3200,
+ 1700, 1800, 2200, 2300, 3100, 3300,
+ 1700, 2000, 2200, 2600, 3200, 3300,
+ 1800, 1900, 2200, 2500, 3100, 3200,
+ 1600, 1700, 2100, 2400, 2900, 3200,
+ 1500, 1800, 2300, 2700, 3000, 3300,
+ 1500, 1800, 2200, 2600, 3000, 3300,
+ 1700, 2000, 2500, 2700, 3200, 3300,
+ 1900, 2000, 2600, 2800, 3200, 3400,
+ 1800, 1900, 2500, 2800, 3100, 3300,
+ 1600, 1800, 2500, 2600, 3000, 3300,
+ 1200, 1500, 2500, 2700, 3100, 3200,
+ 1100, 1900, 2500, 2600, 3100, 3200,
+ 1200, 1900, 2400, 2500, 3100, 3200,
+ 1500, 1700, 2100, 2200, 3200, 3300,
+ 1600, 1800, 2000, 2200, 3300, 3400,
+ 1500, 1600, 1800, 2000, 3300, 3400,
+ 1400, 1600, 1800, 1900, 3300, 3400,
+ 1400, 1600, 2400, 2600, 3000, 3400,
+ 1400, 1800, 2500, 2600, 3100, 3200,
+ 1500, 1700, 2400, 2700, 3100, 3300,
+ 1500, 1800, 2500, 2700, 3000, 3300,
+ 1400, 1500, 2400, 2600, 3000, 3300,
+ 1200, 1400, 2300, 2400, 3000, 3200,
+ 1200, 1600, 2300, 2400, 3100, 3200,
+ 1400, 2000, 2400, 2700, 3100, 3300,
+ 1600, 1900, 2300, 2700, 3100, 3200,
+ 1500, 1900, 2300, 2700, 3100, 3200,
+ 1200, 1400, 2300, 2500, 3100, 3300,
+ 1800, 1900, 2400, 2600, 3000, 3100,
+ 1800, 1900, 2500, 2600, 2900, 3100,
+ 1600, 2000, 2400, 2700, 3000, 3300,
+ 1600, 1900, 2400, 2500, 3100, 3300,
+ 1600, 1900, 2500, 2600, 3100, 3200,
+ 1700, 1800, 2400, 2500, 2900, 3300,
+ 1700, 1800, 2300, 2500, 2900, 3200,
+ 1700, 1800, 2400, 2500, 3000, 3200,
+ 1800, 1900, 2200, 2500, 3000, 3200,
+ 1700, 2000, 2300, 2500, 3000, 3200,
+ 1800, 2000, 2300, 2500, 3000, 3200,
+ 1900, 2100, 2300, 2600, 3000, 3200,
+ 1900, 2100, 2400, 2600, 3000, 3300,
+ 2000, 2100, 2300, 2500, 3000, 3200,
+ 1700, 1800, 2300, 2600, 3100, 3300,
+ 1700, 2100, 2500, 2700, 3200, 3400,
+ 1700, 1900, 2300, 2500, 3000, 3200,
+ 1800, 1900, 2200, 2400, 2900, 3300,
+ 1800, 1900, 2300, 2500, 3000, 3300,
+ 1800, 2000, 2200, 2500, 2900, 3200,
+ 1900, 2200, 2400, 2600, 2900, 3200,
+ 1700, 2100, 2600, 2800, 3100, 3300,
+ 1800, 2300, 2700, 2900, 3200, 3300,
+ 2000, 2300, 2800, 2900, 3100, 3300,
+ 2100, 2200, 2600, 2800, 3200, 3300,
+ 1800, 1900, 2300, 2400, 3100, 3200,
+ 1700, 1800, 2300, 2500, 3000, 3200,
+ 1800, 1900, 2300, 2500, 3000, 3200,
+ 1800, 1900, 2300, 2600, 3100, 3200,
+ 1800, 2000, 2300, 2600, 3100, 3200,
+ 1400, 1600, 1800, 2000, 3100, 3300,
+ 1300, 1700, 2300, 2400, 3100, 3200,
+ 1500, 1700, 2300, 2400, 3100, 3200,
+ 1600, 1700, 2300, 2500, 2900, 3100,
+ 1500, 1700, 2300, 2500, 2900, 3100,
+ 1500, 1700, 2300, 2500, 2800, 3000,
+ 1500, 1600, 2300, 2500, 2800, 3200,
+ 1400, 1500, 2300, 2600, 3000, 3200,
+ 1200, 1600, 2400, 2500, 3000, 3300,
+ 1400, 1600, 2200, 2500, 2900, 3200,
+ 1500, 1900, 2300, 2600, 2900, 3200,
+ 1400, 1800, 2400, 2700, 3200, 3400,
+ 1500, 1900, 2400, 2700, 3200, 3400,
+ 1700, 2100, 2400, 2800, 3000, 3300,
+ 1700, 2000, 2500, 2700, 3100, 3400,
+ 1800, 1900, 2400, 2800, 3200, 3300,
+ 1800, 1900, 2300, 2900, 3200, 3300,
+ 1800, 1900, 2500, 2800, 3200, 3300,
+ 1700, 1800, 2400, 2800, 3200, 3300,
+ 1700, 1800, 2400, 2700, 3200, 3300,
+ 1600, 1700, 2300, 2600, 3000, 3300,
+ 1600, 1700, 2200, 2500, 2900, 3300,
+ 1500, 1600, 2300, 2500, 3000, 3300,
+ 1500, 1900, 2400, 2500, 3300, 3400,
+ 1500, 2000, 2400, 2800, 3200, 3300,
+ 1400, 1800, 2400, 2700, 3200, 3300,
+ 1400, 1900, 2400, 2700, 3200, 3400,
+ 1300, 1700, 2300, 2500, 3200, 3400,
+ 1100, 1700, 2300, 2400, 3100, 3200,
+ 1500, 1700, 1900, 2200, 3300, 3400,
+ 1900, 2300, 2600, 2800, 3200, 3400,
+ 1900, 2400, 2700, 2800, 3300, 3400,
+ 2000, 2300, 2700, 2900, 3400, 3500,
+ 1900, 2300, 2700, 2900, 3400, 3500,
+ 1900, 2100, 2800, 2900, 3300, 3400,
+ 1700, 1800, 2700, 2800, 3100, 3300,
+ 1500, 1700, 2700, 2800, 3200, 3300,
+ 1500, 1600, 2600, 2700, 3000, 3300,
+ 1400, 1600, 2600, 2800, 3000, 3200,
+ 1200, 1400, 2600, 2700, 3000, 3200,
+ 1000, 1500, 2600, 2800, 3200, 3400,
+ 1100, 1300, 2500, 2800, 3000, 3200,
+ 1500, 1600, 2500, 2600, 3000, 3300,
+ 1400, 1500, 2300, 2600, 2800, 3200,
+ 1400, 1600, 2200, 2600, 2800, 3100,
+ 1500, 1600, 2300, 2700, 2900, 3200,
+ 1400, 1500, 2500, 2600, 3100, 3400,
+ 1400, 1500, 2400, 2600, 2800, 3300,
+ 1400, 1600, 2400, 2600, 2800, 3200,
+ 1300, 1600, 2300, 2600, 2900, 3300,
+ 1700, 2200, 2600, 2700, 3200, 3300,
+ 1700, 2300, 2600, 2700, 3200, 3300,
+ 1700, 1900, 2400, 2600, 3100, 3200,
+ 1800, 2300, 2500, 2600, 3200, 3300,
+ 1900, 2400, 2500, 2800, 3300, 3400,
+ 1800, 2000, 2600, 2800, 3300, 3400,
+ 1600, 1900, 2400, 2800, 3200, 3300,
+ 1700, 1800, 2600, 2800, 3000, 3300,
+ 1900, 2000, 2600, 2800, 3200, 3300,
+ 2000, 2100, 2700, 2800, 3200, 3400,
+ 2000, 2100, 2600, 2800, 3300, 3400,
+ 1600, 1700, 2300, 2600, 2900, 3300,
+ 1400, 1600, 2400, 2500, 2800, 3200,
+ 1800, 1900, 2500, 2700, 3000, 3400,
+ 1900, 2000, 2600, 2700, 3000, 3300,
+ 1700, 2000, 2400, 2600, 2900, 3200,
+ 1500, 1600, 2300, 2600, 3000, 3300,
+ 1500, 1600, 2400, 2600, 2900, 3300,
+ 1400, 1500, 2300, 2700, 3000, 3300,
+ 1600, 1800, 2500, 2600, 2900, 3200,
+ 2000, 2100, 2400, 2600, 3000, 3200,
+ 1800, 2000, 2300, 2400, 3200, 3300,
+ 1600, 1900, 2300, 2400, 3200, 3300,
+ 1500, 1800, 2400, 2700, 3200, 3300,
+ 1700, 1900, 2300, 2400, 3000, 3200,
+ 2000, 2200, 2400, 2500, 3200, 3300,
+ 2200, 2300, 2600, 2700, 3200, 3300,
+ 2100, 2200, 2400, 2700, 3000, 3200,
+ 2100, 2200, 2500, 2700, 3000, 3200,
+ 2200, 2300, 2600, 2800, 3000, 3300,
+ 1900, 2200, 2600, 2700, 3000, 3300,
+ 1700, 1800, 2500, 2700, 2800, 3200,
+ 1700, 1800, 2600, 2700, 3000, 3200,
+ 1700, 1900, 2500, 2700, 3100, 3300,
+ 1700, 1900, 2500, 2700, 3300, 3400,
+ 1800, 2000, 2400, 2600, 3100, 3200,
+ 1700, 2200, 2300, 2500, 3200, 3300,
+ 1700, 2200, 2300, 2600, 3100, 3200,
+ 1600, 1700, 2400, 2600, 3300, 3400,
+ 1600, 1700, 2400, 2500, 3300, 3400,
+ 1900, 2100, 2500, 2800, 3000, 3100,
+ 1800, 2100, 2500, 2800, 3000, 3100,
+ 1800, 2100, 2600, 2800, 3100, 3200,
+ 1800, 2000, 2500, 2800, 3100, 3200,
+ 1900, 2100, 2500, 2600, 3000, 3200,
+ 1800, 1900, 2600, 2800, 3200, 3400,
+ 1500, 2100, 2500, 2700, 3300, 3400,
+ 1100, 2000, 2400, 2600, 3300, 3400,
+ 1100, 1900, 2400, 2500, 3300, 3400,
+ 1300, 1500, 2200, 2400, 2900, 3300,
+ 1600, 1700, 2300, 2500, 2900, 3300,
+ 1600, 1700, 2400, 2500, 3000, 3200,
+ 1800, 1900, 2500, 2600, 3100, 3300,
+ 1900, 2000, 2500, 2700, 3100, 3200,
+ 2100, 2200, 2400, 2600, 3100, 3400,
+ 2100, 2200, 2500, 2600, 3000, 3400,
+ 1900, 2100, 2400, 2700, 3000, 3100,
+ 1600, 1800, 2200, 2400, 3000, 3200,
+ 1600, 1700, 2200, 2300, 2900, 3300,
+ 1600, 1700, 2100, 2300, 2800, 3100,
+ 2200, 2300, 2600, 2800, 3100, 3300,
+ 2200, 2300, 2700, 2800, 3100, 3400,
+ 2000, 2100, 2600, 2800, 3100, 3400,
+ 1700, 1800, 2400, 2700, 2900, 3200,
+ 1600, 1800, 2400, 2700, 3100, 3200,
+ 1600, 1800, 2300, 2400, 3000, 3200,
+ 1800, 1900, 2400, 2600, 3100, 3300,
+ 1900, 2000, 2300, 2600, 2900, 3200,
+ 1900, 2100, 2300, 2700, 2800, 3000,
+ 1800, 2000, 2600, 2700, 3000, 3300,
+ 1800, 1900, 2400, 2600, 2900, 3300,
+ 1700, 1800, 2300, 2400, 2900, 3300,
+ 1600, 1700, 2100, 2500, 3000, 3200,
+ 1600, 1800, 2200, 2600, 3100, 3200,
+ 1500, 1700, 2200, 2500, 2900, 3300,
+ 1500, 1600, 2300, 2400, 2800, 3300,
+ 1400, 1600, 2300, 2400, 3000, 3300,
+ 1500, 2000, 2500, 2800, 3200, 3300,
+ 1300, 1500, 2600, 2700, 3100, 3300,
+ 1200, 1400, 1700, 1900, 3100, 3300,
+ 1200, 1700, 1900, 2300, 3200, 3300,
+ 1200, 1900, 2000, 2300, 3200, 3300,
+ 1200, 2000, 2100, 2500, 3300, 3400,
+ 1200, 2000, 2200, 2600, 3300, 3400,
+ 1200, 2000, 2300, 2400, 3200, 3300,
+ 1000, 1900, 2300, 2500, 3200, 3300,
+ 1200, 1800, 2200, 2500, 3100, 3200,
+ 1400, 1600, 2300, 2500, 3200, 3300,
+ 1500, 1600, 2500, 2700, 2900, 3200,
+ 1600, 1900, 2400, 2800, 3100, 3300,
+ 1700, 1800, 2400, 2800, 3100, 3200,
+ 1700, 1800, 2500, 2800, 3100, 3200,
+ 1500, 1800, 2400, 2500, 2900, 3100,
+ 1500, 1600, 2400, 2500, 2900, 3200,
+ 1300, 1500, 2200, 2500, 2800, 3100,
+ 1300, 1400, 2000, 2400, 2600, 2900,
+ 1400, 1500, 2100, 2500, 2700, 3100,
+ 1500, 2000, 2300, 2600, 3000, 3200,
+ 1700, 2100, 2400, 2600, 2900, 3100,
+ 1400, 1500, 2300, 2600, 3000, 3300,
+ 1500, 1700, 2200, 2300, 3200, 3300,
+ 1400, 1600, 2000, 2400, 3100, 3300,
+ 1500, 1700, 2000, 2100, 3100, 3300,
+ 1600, 1900, 2200, 2500, 2900, 3200,
+ 1500, 1600, 2200, 2400, 2800, 3200,
+ 1500, 1600, 2100, 2500, 3000, 3300,
+ 1500, 1600, 2000, 2500, 2900, 3300,
+ 1500, 1600, 2100, 2500, 2900, 3200,
+ 1500, 1600, 2200, 2700, 2800, 3100,
+ 1300, 1400, 2200, 2600, 3000, 3200,
+ 1400, 1900, 2400, 2700, 3100, 3300,
+ 1600, 1800, 2500, 2600, 3000, 3200,
+ 1500, 1700, 2300, 2500, 2800, 3200,
+ 1700, 1800, 2200, 2400, 3200, 3300,
+ 1700, 1900, 2200, 2300, 3000, 3300,
+ 1600, 1700, 2000, 2400, 3000, 3200,
+ 1700, 1800, 2300, 2600, 2900, 3200,
+ 1500, 2000, 2300, 2600, 3100, 3400,
+ 1400, 1900, 2500, 2700, 3100, 3300,
+ 1400, 1700, 2600, 2700, 3100, 3300,
+ 1500, 1600, 2300, 2600, 2800, 3200,
+ 1700, 1800, 2300, 2500, 3100, 3400,
+ 1500, 1600, 2200, 2300, 3100, 3300,
+ 1400, 1500, 2200, 2400, 3100, 3200,
+ 1400, 1600, 2200, 2400, 3000, 3100,
+ 1700, 2100, 2300, 2700, 3100, 3200,
+ 1900, 2300, 2500, 2700, 3100, 3200,
+ 1900, 2300, 2600, 2800, 3100, 3300,
+ 1900, 2400, 2600, 2900, 3200, 3300,
+ 1900, 2300, 2600, 2800, 3300, 3400,
+ 1800, 2400, 2600, 2800, 3300, 3400,
+ 1600, 1800, 2600, 2700, 3000, 3300,
+ 1600, 1700, 2600, 2700, 2900, 3200,
+ 1500, 1600, 2500, 2700, 3000, 3300,
+ 1300, 1400, 2400, 2700, 2900, 3300,
+ 1300, 1400, 2300, 2700, 2800, 3100,
+ 1300, 1400, 2500, 2800, 3000, 3300,
+ 1500, 1700, 2400, 2500, 2800, 3300,
+ 1900, 2000, 2500, 2600, 3000, 3200,
+ 1800, 2000, 2400, 2500, 3100, 3200,
+ 1700, 1800, 2100, 2300, 2800, 3100,
+ 1700, 1800, 2200, 2400, 2800, 3200,
+ 1600, 1700, 2200, 2400, 2800, 3200,
+ 1500, 1600, 2200, 2400, 2700, 3300,
+ 1400, 1500, 2200, 2400, 2900, 3200,
+ 1600, 1700, 2300, 2500, 2700, 3000,
+ 1600, 1700, 2200, 2500, 2700, 3000,
+ 1700, 1900, 2200, 2500, 2800, 3100,
+ 1900, 2000, 2300, 2500, 2900, 3100,
+ 1900, 2100, 2300, 2500, 2900, 3200,
+ 1900, 2100, 2300, 2500, 3100, 3300,
+ 2000, 2200, 2600, 2800, 3000, 3200,
+ 1900, 2200, 2500, 2700, 2900, 3200,
+ 2100, 2300, 2600, 2800, 3100, 3300,
+ 2100, 2300, 2600, 2700, 3000, 3200,
+ 2100, 2200, 2500, 2600, 3000, 3200,
+ 1500, 1600, 2300, 2400, 2900, 3200,
+ 1400, 1500, 2100, 2400, 2800, 3100,
+ 1300, 1600, 2100, 2400, 3100, 3200,
+ 1300, 1400, 2300, 2600, 2800, 3200,
+ 1400, 1500, 2200, 2500, 2700, 3200,
+ 1400, 1500, 2300, 2500, 2700, 3200,
+ 1500, 1600, 2400, 2500, 2800, 3200,
+ 1600, 1700, 2400, 2500, 2900, 3200,
+ 1700, 1800, 2400, 2500, 2900, 3100,
+ 1800, 1900, 2400, 2600, 3000, 3200,
+ 2100, 2200, 2700, 2900, 3200, 3300,
+ 1800, 2100, 2500, 2900, 3100, 3300,
+ 1700, 1800, 2500, 2800, 2900, 3300,
+ 1200, 1600, 2100, 2400, 3000, 3200,
+ 1600, 1700, 2100, 2600, 2900, 3000,
+ 1600, 1700, 2200, 2700, 2900, 3000,
+ 1600, 1800, 2200, 2500, 2900, 3000,
+ 1700, 1800, 2300, 2500, 2900, 3100,
+ 1700, 1900, 2300, 2600, 2900, 3100,
+ 1500, 1700, 2000, 2600, 2900, 3100,
+ 1400, 1600, 1800, 2600, 3000, 3100,
+ 1300, 1500, 1700, 2700, 3100, 3200,
+ 1300, 1700, 2400, 2700, 3100, 3300,
+ 1200, 1600, 2400, 2600, 2900, 3200,
+ 1300, 1400, 2000, 2700, 2800, 3000,
+ 1400, 1500, 2000, 2600, 2800, 3000,
+ 1500, 1700, 2100, 2600, 2800, 3000,
+ 1600, 1800, 2200, 2700, 2800, 3000,
+ 1600, 1800, 2100, 2700, 2900, 3100,
+ 1500, 1900, 2300, 2700, 3000, 3100,
+ 1500, 1900, 2300, 2700, 3000, 3200,
+ 1500, 2000, 2300, 2700, 3000, 3200,
+ 1800, 2100, 2300, 2700, 3100, 3300,
+ 1500, 2000, 2300, 2600, 3000, 3100,
+ 1500, 2100, 2300, 2700, 3100, 3200,
+ 1600, 2100, 2200, 2700, 3100, 3200,
+ 1500, 2100, 2200, 2600, 3100, 3200,
+ 1400, 2300, 2500, 2700, 3100, 3200,
+ 1700, 2100, 2300, 2700, 2900, 3100,
+ 1500, 1800, 2300, 2700, 3000, 3100,
+ 1500, 1700, 2300, 2700, 3000, 3100,
+ 1500, 1600, 2100, 2700, 3000, 3100,
+ 1400, 1500, 1900, 2600, 3100, 3200,
+ 1200, 1300, 1900, 2600, 2900, 3100,
+ 1100, 1200, 1800, 2700, 3000, 3100,
+ 1200, 1300, 1800, 2700, 3000, 3100,
+ 1200, 1400, 1900, 2700, 3000, 3100,
+ 1300, 1500, 1800, 2600, 3000, 3100,
+ 1200, 1400, 2300, 2700, 2900, 3100,
+ 1300, 1400, 2200, 2700, 2800, 3100,
+ 1300, 1500, 2000, 2600, 2900, 3100,
+ 1300, 1500, 2100, 2700, 2900, 3100,
+ 1400, 1800, 2100, 2600, 2800, 3000,
+ 1400, 1800, 2100, 2500, 2900, 3100,
+ 1700, 2000, 2500, 2800, 3000, 3200,
+ 1900, 2000, 2700, 2800, 3100, 3400,
+ 1900, 2100, 2600, 2800, 3100, 3300,
+ 1600, 2100, 2400, 2700, 3200, 3400,
+ 1700, 2000, 2300, 2500, 2800, 3200,
+ 1500, 1700, 2100, 2300, 3000, 3200,
+ 1400, 1900, 2200, 2500, 2900, 3200,
+ 1400, 1900, 2300, 2500, 2700, 3100,
+ 1300, 1500, 2100, 2700, 2800, 3100,
+ 1300, 1500, 2000, 2600, 2800, 3100,
+ 1300, 1400, 2100, 2600, 2800, 3000,
+ 1300, 1400, 2000, 2600, 2800, 3000,
+ 1200, 1300, 2000, 2700, 2800, 3000,
+ 1200, 1400, 2300, 2600, 2900, 3200,
+ 1300, 1600, 2300, 2700, 2900, 3200,
+ 1600, 1900, 2300, 2800, 3100, 3200,
+ 1700, 1900, 2300, 2800, 3000, 3200,
+ 1700, 1900, 2100, 2600, 2900, 3000,
+ 1700, 1900, 2400, 2600, 2800, 3100,
+ 1700, 2100, 2400, 2500, 2800, 3100,
+ 1700, 2000, 2400, 2500, 2900, 3100,
+ 1900, 2200, 2400, 2600, 3000, 3200,
+ 1700, 2000, 2400, 2700, 3000, 3100,
+ 1500, 1900, 2300, 2600, 3000, 3100,
+ 1500, 1600, 2100, 2600, 2900, 3200,
+ 1400, 1600, 1800, 2300, 2800, 2900,
+ 1400, 1600, 1700, 2500, 3200, 3300,
+ 1400, 1600, 1800, 2400, 3200, 3300,
+ 1400, 1700, 1900, 2200, 3100, 3200,
+ 1300, 1700, 1900, 2300, 3100, 3200,
+ 1100, 1600, 2000, 2300, 3000, 3100,
+ 1500, 1900, 2500, 2800, 3200, 3300,
+ 1800, 2000, 2300, 2800, 3000, 3100,
+ 1800, 1900, 2300, 2700, 2900, 3200,
+ 1700, 1900, 2300, 2600, 2800, 3100,
+ 1700, 1900, 2100, 2500, 2700, 3000,
+ 1700, 1900, 2100, 2600, 2800, 3000,
+ 1700, 1900, 2100, 2700, 2900, 3100,
+ 1700, 1900, 2500, 2800, 3000, 3300
+};
+
+const struct lsp_codebook lsp_cbjnd[] = {
+ /* codebook/lsp1.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes0
+ },
+ /* codebook/lsp2.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes1
+ },
+ /* codebook/lsp3.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes2
+ },
+ /* codebook/lsp4.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes3
+ },
+ /* ../unittest/lspjnd5-10.txt */
+ {
+ 6,
+ 11.7181,
+ 3369,
+ codes4
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/lspjvm1.txt */
+static const float codes0[] = {
+ 0.435217, 0.668864, 1.0103, 1.22042, 1.50398, 1.78468, 2.13546, 2.35747, 2.61891, 2.73804,
+ 0.179285, 0.33316, 0.500638, 0.79695, 1.03999, 1.23497, 1.6523, 1.84823, 2.62556, 2.80497,
+ 0.268785, 0.356576, 0.595753, 1.04434, 1.24938, 1.42868, 1.68699, 1.86469, 2.33991, 2.5138,
+ 0.12007, 0.165585, 0.484694, 0.95916, 1.23753, 1.52915, 1.83751, 2.10773, 2.48749, 2.76685,
+ 0.150214, 0.229487, 0.62824, 0.961255, 1.33706, 1.59831, 1.91974, 2.21786, 2.53732, 2.75956,
+ 0.268624, 0.34598, 0.569637, 0.754737, 0.916538, 1.50854, 1.78635, 1.95442, 2.36953, 2.50182,
+ 0.246064, 0.468874, 0.662711, 0.890015, 1.14715, 1.51043, 1.78106, 2.09594, 2.65539, 2.80037,
+ 0.191631, 0.280628, 0.393229, 0.611761, 1.42017, 1.70774, 1.87303, 2.10155, 2.28035, 2.49949,
+ 0.361668, 0.507047, 0.789974, 1.04599, 1.50238, 1.67703, 1.90534, 2.16255, 2.43226, 2.59087,
+ 0.20816, 0.294285, 0.448634, 0.694229, 0.872517, 1.07032, 1.70335, 2.16874, 2.42619, 2.60366,
+ 0.316939, 0.513618, 0.705487, 0.917036, 1.17599, 1.31114, 1.6186, 2.03784, 2.45052, 2.5794,
+ 0.241068, 0.377728, 0.521595, 0.717203, 1.31041, 1.53999, 1.73643, 2.09893, 2.29792, 2.58735,
+ 0.234937, 0.281875, 0.780422, 1.44073, 1.60943, 1.75643, 1.97721, 2.14861, 2.60203, 2.7225,
+ 0.178679, 0.242672, 0.416988, 0.708348, 0.95562, 1.17667, 1.7818, 2.05449, 2.28159, 2.44811,
+ 0.345036, 0.42108, 0.740887, 1.16544, 1.32494, 1.4888, 1.76346, 1.90617, 2.39505, 2.64916,
+ 0.249586, 0.357494, 0.520747, 0.847195, 1.42841, 1.59778, 1.77819, 2.1785, 2.41344, 2.56466,
+ 0.295235, 0.574231, 1.2491, 1.4641, 1.72756, 1.92679, 2.09536, 2.28483, 2.56707, 2.72248,
+ 0.34193, 0.427307, 0.634001, 0.804212, 0.905629, 1.33337, 1.79033, 1.89276, 2.44582, 2.60283,
+ 0.363948, 0.508985, 0.667357, 0.946354, 1.43756, 1.62654, 1.81114, 2.03909, 2.29188, 2.43549,
+ 0.163514, 0.277407, 0.409207, 0.902065, 1.18907, 1.33964, 1.80241, 1.96077, 2.65293, 2.81899,
+ 0.302643, 0.359753, 0.651207, 1.20802, 1.4237, 1.54815, 1.88213, 2.01559, 2.26054, 2.5789,
+ 0.155928, 0.216908, 0.381812, 0.654803, 1.11237, 1.58993, 1.84756, 1.97672, 2.22408, 2.72534,
+ 0.274981, 0.347675, 0.572, 0.736046, 0.894248, 1.63237, 1.89139, 2.05689, 2.6029, 2.72178,
+ 0.154496, 0.243461, 0.348174, 0.689505, 1.57381, 1.70031, 1.94318, 2.10158, 2.56466, 2.77317,
+ 0.292612, 0.466612, 0.795936, 1.04747, 1.41369, 1.75085, 2.06289, 2.34007, 2.61361, 2.76949,
+ 0.242896, 0.3615, 0.555859, 0.793597, 0.932291, 1.40947, 1.86386, 2.00953, 2.4645, 2.67749,
+ 0.221646, 0.344724, 0.554564, 0.729403, 1.13657, 1.30177, 1.52918, 2.16359, 2.39582, 2.61081,
+ 0.160969, 0.224467, 0.371545, 0.626879, 1.16095, 1.44423, 1.67597, 1.87978, 2.47859, 2.67202,
+ 0.214172, 0.341585, 0.676575, 0.977397, 1.32543, 1.7201, 2.07259, 2.36954, 2.63528, 2.77879,
+ 0.203311, 0.289438, 0.458739, 0.914153, 1.12288, 1.30292, 1.58384, 1.88683, 2.18787, 2.42704,
+ 0.280383, 0.3716, 0.824827, 1.10025, 1.23623, 1.39892, 1.57804, 2.016, 2.36897, 2.50673,
+ 0.170627, 0.251778, 0.393686, 0.608347, 1.2876, 1.44667, 1.79328, 2.03655, 2.31015, 2.75244,
+ 0.18058, 0.288746, 0.987854, 1.43171, 1.67722, 1.91566, 2.12494, 2.28945, 2.58961, 2.75426,
+ 0.176335, 0.266263, 0.445421, 0.706403, 0.875402, 1.42292, 1.75867, 1.96091, 2.41068, 2.60175,
+ 0.216173, 0.287404, 0.480696, 1.00977, 1.2913, 1.47664, 1.89558, 2.06429, 2.28406, 2.48311,
+ 0.176523, 0.273934, 0.403407, 0.966139, 1.30472, 1.43661, 1.94473, 2.08484, 2.54446, 2.76242,
+ 0.311836, 0.550501, 0.879591, 1.09623, 1.27666, 1.47786, 1.81771, 2.15434, 2.56047, 2.77984,
+ 0.179765, 0.25056, 0.455939, 1.02389, 1.22513, 1.47566, 1.73462, 1.91871, 2.14734, 2.43824,
+ 0.271033, 0.457235, 0.599622, 0.821049, 0.940125, 1.20094, 1.84972, 1.98666, 2.54817, 2.75158,
+ 0.179326, 0.248002, 0.426405, 0.81706, 1.28589, 1.56502, 2.11736, 2.29871, 2.5724, 2.7527,
+ 0.374409, 0.535936, 0.897009, 1.18507, 1.59157, 1.7572, 1.96794, 2.17999, 2.45739, 2.62264,
+ 0.185472, 0.282752, 0.409439, 0.657499, 0.856446, 1.0294, 1.87993, 2.06932, 2.34474, 2.7531,
+ 0.375964, 0.578457, 0.758945, 0.929339, 1.12748, 1.25944, 1.70411, 2.12297, 2.33603, 2.4983,
+ 0.225641, 0.36103, 0.501679, 0.783379, 1.31485, 1.45262, 1.71415, 1.98716, 2.2257, 2.72436,
+ 0.144996, 0.252919, 0.632145, 1.22604, 1.57534, 1.90155, 2.17148, 2.39055, 2.68229, 2.80983,
+ 0.172022, 0.263338, 0.448634, 0.729435, 0.984007, 1.1716, 1.75705, 1.99023, 2.32131, 2.77121,
+ 0.235731, 0.351117, 0.796871, 1.05571, 1.30022, 1.59182, 1.89587, 2.12292, 2.41789, 2.59982,
+ 0.254053, 0.319371, 0.455623, 1.08614, 1.66467, 1.91588, 2.05908, 2.23342, 2.45204, 2.58679,
+ 0.375538, 0.742993, 1.13991, 1.33776, 1.73556, 2.01391, 2.31501, 2.48343, 2.65158, 2.75521,
+ 0.247245, 0.481131, 0.710366, 0.897602, 1.12109, 1.27171, 1.78735, 2.1995, 2.42966, 2.74067,
+ 0.226103, 0.311441, 0.501648, 0.844424, 1.36282, 1.53134, 1.77747, 1.98993, 2.18749, 2.3585,
+ 0.195862, 0.296224, 0.609554, 0.783241, 1.24347, 1.44548, 1.63703, 2.02264, 2.48356, 2.64614,
+ 0.233302, 0.299441, 0.472792, 1.24946, 1.45788, 1.60186, 1.83143, 1.99372, 2.59719, 2.75543,
+ 0.168096, 0.224183, 0.3827, 0.596214, 1.06059, 1.29442, 1.60576, 1.84849, 2.3577, 2.56919,
+ 0.33005, 0.445912, 0.661713, 0.874446, 1.00079, 1.45297, 1.94399, 2.07692, 2.42388, 2.61236,
+ 0.226382, 0.287303, 0.517631, 0.806229, 1.30901, 1.88528, 2.16051, 2.28641, 2.52638, 2.66082,
+ 0.20317, 0.499314, 0.887358, 1.23507, 1.46292, 1.69826, 1.99932, 2.22922, 2.57161, 2.76669,
+ 0.307531, 0.378353, 0.573606, 0.712218, 0.850169, 1.309, 2.05909, 2.26382, 2.49794, 2.67682,
+ 0.276203, 0.51025, 0.6868, 0.902844, 1.2052, 1.32798, 1.71889, 2.03895, 2.25639, 2.69715,
+ 0.161948, 0.229115, 0.393619, 0.683613, 1.13781, 1.32269, 1.78372, 1.96158, 2.38907, 2.63608,
+ 0.201334, 0.276773, 0.468994, 0.967017, 1.47597, 1.63242, 1.96577, 2.19728, 2.48059, 2.70155,
+ 0.214587, 0.315421, 0.469498, 0.733397, 1.146, 1.27791, 1.72784, 2.22713, 2.44026, 2.68112,
+ 0.255602, 0.394609, 0.743393, 0.977796, 1.19908, 1.40597, 1.91834, 2.22483, 2.47919, 2.66339,
+ 0.245989, 0.352625, 0.517055, 0.80283, 1.55871, 1.79565, 1.94405, 2.13364, 2.33327, 2.47998,
+ 0.337423, 0.480433, 0.869036, 1.13957, 1.63076, 1.82296, 2.07484, 2.29261, 2.47913, 2.62532,
+ 0.220974, 0.35885, 0.57164, 0.752791, 0.937013, 1.15172, 1.6744, 2.06247, 2.55872, 2.78484,
+ 0.267518, 0.331708, 0.541111, 1.11655, 1.41112, 1.53287, 1.79295, 1.93352, 2.24894, 2.62864,
+ 0.084613, 0.105083, 0.297424, 0.916949, 1.2563, 1.56703, 1.88539, 2.18987, 2.52279, 2.7921,
+ 0.205328, 0.287223, 0.724462, 1.0324, 1.45771, 1.64217, 1.92563, 2.17552, 2.42964, 2.60549,
+ 0.232554, 0.338724, 0.502115, 0.859975, 1.04409, 1.24565, 1.80656, 1.99964, 2.26116, 2.45998,
+ 0.291638, 0.379172, 0.626072, 0.792796, 0.959124, 1.50489, 1.73447, 1.91961, 2.61436, 2.72271,
+ 0.191554, 0.263114, 0.426797, 0.610628, 1.07741, 1.82954, 2.02195, 2.21057, 2.42765, 2.61383,
+ 0.389151, 0.679476, 0.915414, 1.03664, 1.25085, 1.58661, 2.04097, 2.2815, 2.56794, 2.71882,
+ 0.2032, 0.30128, 0.470357, 0.668716, 0.851737, 0.980327, 1.57086, 2.03762, 2.28907, 2.69388,
+ 0.304064, 0.405934, 0.710274, 0.962705, 1.12882, 1.34167, 1.63505, 1.84538, 2.07992, 2.50751,
+ 0.171777, 0.240705, 0.409371, 0.786432, 1.2232, 1.37569, 1.69176, 1.86608, 2.35041, 2.49394,
+ 0.231251, 0.277994, 0.557867, 1.32582, 1.66035, 1.77948, 2.00714, 2.17232, 2.44046, 2.65231,
+ 0.188101, 0.259494, 0.412543, 0.624843, 0.839549, 1.0337, 1.63413, 1.93194, 2.24608, 2.42577,
+ 0.361304, 0.419465, 0.795676, 1.18461, 1.2968, 1.57845, 1.84175, 1.99736, 2.54054, 2.68714,
+ 0.274372, 0.338938, 0.492443, 0.963516, 1.50951, 1.70638, 1.86988, 2.07717, 2.26128, 2.44418,
+ 0.41599, 0.652103, 1.03129, 1.26955, 1.57275, 1.77297, 2.00466, 2.17527, 2.43061, 2.59655,
+ 0.242045, 0.370942, 0.534392, 0.763529, 1.00117, 1.12976, 1.68219, 2.14464, 2.32448, 2.7157,
+ 0.377438, 0.588168, 0.765394, 0.976873, 1.35665, 1.49009, 1.73797, 2.00677, 2.21369, 2.38997,
+ 0.191625, 0.284123, 0.405342, 1.01678, 1.43273, 1.54759, 1.81393, 1.95832, 2.47077, 2.64926,
+ 0.272672, 0.349555, 0.633911, 1.15223, 1.30394, 1.54764, 1.9195, 2.0477, 2.56278, 2.73058,
+ 0.168423, 0.23633, 0.421468, 0.831345, 1.08354, 1.55345, 1.88073, 2.0647, 2.37086, 2.63295,
+ 0.219318, 0.301481, 0.513617, 0.765086, 1.02602, 1.51465, 2.0482, 2.24857, 2.49981, 2.65707,
+ 0.232695, 0.347947, 0.495203, 0.71883, 1.42301, 1.72249, 1.87958, 2.16504, 2.42025, 2.58966,
+ 0.270284, 0.336865, 0.684929, 1.15579, 1.69042, 1.87674, 2.02736, 2.22618, 2.44675, 2.582,
+ 0.149701, 0.193747, 0.352019, 0.520123, 0.823974, 1.43475, 1.68659, 1.96115, 2.37091, 2.69307,
+ 0.254818, 0.412303, 0.601514, 0.771438, 1.17545, 1.37657, 1.53903, 1.93704, 2.40858, 2.56362,
+ 0.233713, 0.355886, 0.593725, 0.76288, 1.27148, 1.5639, 1.79752, 2.09469, 2.53863, 2.71173,
+ 0.179028, 0.237103, 0.396818, 1.04202, 1.63354, 1.76268, 2.12393, 2.32239, 2.58819, 2.75134,
+ 0.182027, 0.251039, 0.434581, 0.714302, 0.950997, 1.4379, 1.81357, 1.9691, 2.14588, 2.35397,
+ 0.501538, 0.692148, 0.84886, 1.07131, 1.35054, 1.48948, 1.84164, 2.10428, 2.34154, 2.51529,
+ 0.27453, 0.38147, 0.526682, 0.922143, 1.44495, 1.5736, 1.85877, 2.06675, 2.2848, 2.62682,
+ 0.360617, 0.583131, 0.979491, 1.25408, 1.48835, 1.79756, 2.21952, 2.48218, 2.74237, 2.86203,
+ 0.140913, 0.220301, 0.619552, 0.818307, 1.05243, 1.33997, 1.83073, 2.13395, 2.53638, 2.75113,
+ 0.293514, 0.391691, 0.79008, 0.96274, 1.16032, 1.5266, 1.80549, 2.04146, 2.36162, 2.56496,
+ 0.199542, 0.290571, 0.452891, 0.689515, 1.25853, 1.40988, 1.88624, 2.22813, 2.46568, 2.72665,
+ 0.29692, 0.356356, 0.784287, 0.99654, 1.14618, 1.62387, 1.8155, 2.0383, 2.60063, 2.7057,
+ 0.206451, 0.276025, 0.537547, 0.802572, 1.22041, 1.64206, 1.86363, 2.00198, 2.21534, 2.58538,
+ 0.33365, 0.464751, 0.653772, 0.966306, 1.10387, 1.3402, 1.7847, 1.91459, 2.47017, 2.68692,
+ 0.181861, 0.24487, 0.376456, 0.554383, 1.3299, 1.81044, 2.04784, 2.20232, 2.66086, 2.81706,
+ 0.450565, 0.647291, 0.951172, 1.22943, 1.51964, 1.68681, 2.04911, 2.26717, 2.50128, 2.6506,
+ 0.219996, 0.320591, 0.427747, 0.601183, 0.753448, 0.929578, 1.74198, 2.28579, 2.47263, 2.74957,
+ 0.333848, 0.423373, 0.658791, 1.0313, 1.22263, 1.36577, 1.90189, 2.1211, 2.29031, 2.53118,
+ 0.166064, 0.233902, 0.383355, 0.661806, 1.22657, 1.39968, 1.77127, 1.97454, 2.17349, 2.56634,
+ 0.189286, 0.243602, 0.390584, 1.38793, 1.58872, 1.76324, 2.09112, 2.31631, 2.59353, 2.75508,
+ 0.158404, 0.224878, 0.385, 0.668463, 0.942954, 1.41197, 1.70031, 1.82807, 2.0594, 2.69255,
+ 0.325989, 0.461263, 0.851471, 1.04571, 1.28403, 1.5162, 1.79734, 2.08839, 2.43767, 2.62721,
+ 0.223709, 0.28919, 0.632812, 0.858738, 1.5419, 1.74677, 1.93574, 2.18482, 2.40433, 2.58301,
+ 0.545842, 0.95242, 1.34082, 1.51684, 1.83888, 2.01289, 2.24497, 2.40317, 2.59228, 2.69112,
+ 0.238526, 0.349079, 0.494582, 0.987665, 1.17075, 1.34823, 1.46864, 2.29696, 2.64416, 2.78738,
+ 0.270857, 0.442003, 0.655998, 0.881913, 1.25925, 1.42836, 1.76987, 1.99853, 2.39559, 2.65284,
+ 0.154384, 0.211806, 0.489481, 0.997257, 1.24982, 1.54123, 1.77886, 1.9494, 2.31914, 2.62339,
+ 0.268258, 0.312888, 0.589114, 1.25863, 1.57271, 1.67543, 1.91278, 2.07046, 2.27993, 2.56423,
+ 0.170715, 0.224965, 0.374011, 0.540197, 1.16189, 1.49907, 1.92587, 2.08257, 2.24662, 2.46972,
+ 0.324358, 0.391989, 0.706816, 0.833614, 1.01573, 1.56899, 1.73598, 2.12707, 2.55841, 2.65387,
+ 0.178059, 0.258575, 0.374125, 0.536831, 1.33483, 1.79863, 1.98698, 2.18925, 2.43227, 2.6267,
+ 0.198857, 0.420955, 0.817664, 1.17836, 1.46674, 1.8213, 2.20733, 2.47441, 2.73828, 2.85119,
+ 0.188344, 0.324302, 0.470468, 0.790033, 0.934101, 1.18872, 1.88717, 2.05283, 2.44832, 2.63024,
+ 0.201295, 0.365646, 0.526513, 0.758388, 1.1401, 1.26733, 1.65017, 1.87934, 2.10289, 2.60029,
+ 0.135058, 0.169428, 0.307348, 0.50316, 1.01808, 1.44795, 1.81098, 2.134, 2.48028, 2.75985,
+ 0.178006, 0.26661, 0.390327, 0.928681, 1.50161, 1.62133, 1.87136, 2.02586, 2.58044, 2.7708,
+ 0.246182, 0.42429, 0.644023, 0.801168, 1.11488, 1.27776, 1.50332, 2.07489, 2.2957, 2.50138,
+ 0.322996, 0.430355, 0.6316, 1.0477, 1.22184, 1.42673, 1.90308, 2.03222, 2.51673, 2.70845,
+ 0.292994, 0.430599, 0.619178, 0.794567, 1.28303, 1.65282, 1.84084, 2.06995, 2.38538, 2.52825,
+ 0.525494, 0.787797, 1.12182, 1.38748, 1.67457, 1.93622, 2.22404, 2.39062, 2.63428, 2.74323,
+ 0.299504, 0.409196, 0.602235, 0.892336, 1.05643, 1.25377, 1.48914, 1.63988, 2.42748, 2.65037,
+ 0.423758, 0.52048, 0.758987, 1.04126, 1.17366, 1.42368, 1.81824, 1.93641, 2.363, 2.62664,
+ 0.155042, 0.247496, 0.641445, 0.954509, 1.22497, 1.46585, 1.83784, 2.09046, 2.4515, 2.71616,
+ 0.251949, 0.421094, 0.706797, 0.975659, 1.25991, 1.52007, 1.81631, 2.12202, 2.47491, 2.71667,
+ 0.21522, 0.302248, 0.730598, 0.896343, 1.14557, 1.37019, 1.70069, 2.02256, 2.28327, 2.48922,
+ 0.28523, 0.453559, 0.66367, 0.861526, 1.0116, 1.24742, 1.65598, 1.86129, 2.57894, 2.73133,
+ 0.162067, 0.219409, 0.373433, 0.544669, 1.1033, 1.59718, 1.92104, 2.1434, 2.4065, 2.66048,
+ 0.342367, 0.511499, 0.93135, 1.16322, 1.39365, 1.61115, 1.97277, 2.19442, 2.47077, 2.64926,
+ 0.25101, 0.364125, 0.560956, 0.746545, 1.01984, 1.17072, 1.53295, 2.28867, 2.57709, 2.72307,
+ 0.315001, 0.489412, 0.720682, 0.877607, 1.09047, 1.25385, 1.44822, 1.92295, 2.25589, 2.40863,
+ 0.174666, 0.235793, 0.387644, 0.554402, 1.23109, 1.45614, 1.68803, 2.12745, 2.36703, 2.59727,
+ 0.215113, 0.341915, 1.04372, 1.32275, 1.49541, 1.74189, 1.96116, 2.23982, 2.5449, 2.70394,
+ 0.219852, 0.30177, 0.513912, 0.705474, 0.87754, 1.2959, 1.699, 1.98706, 2.28797, 2.49697,
+ 0.290638, 0.366442, 0.655155, 1.04499, 1.17215, 1.53254, 1.80079, 1.94893, 2.50968, 2.66005,
+ 0.232252, 0.31377, 0.658552, 0.941977, 1.46317, 1.66549, 1.86246, 2.02784, 2.53402, 2.70124,
+ 0.326539, 0.552681, 1.12173, 1.33138, 1.52007, 1.86708, 2.08286, 2.33247, 2.60604, 2.73709,
+ 0.190254, 0.340428, 0.492777, 0.739738, 0.895461, 1.07937, 1.64316, 1.79529, 2.49182, 2.72938,
+ 0.283586, 0.41844, 0.587306, 0.870866, 1.41855, 1.57703, 1.7995, 2.0694, 2.27448, 2.4381,
+ 0.235752, 0.35765, 0.502891, 1.01243, 1.25885, 1.40779, 1.82006, 1.95583, 2.5059, 2.73433,
+ 0.278412, 0.343137, 0.849977, 1.2329, 1.3505, 1.59063, 1.78752, 2.09158, 2.54136, 2.66386,
+ 0.162966, 0.243159, 0.439238, 0.684821, 0.887783, 1.4629, 1.88174, 2.04425, 2.28939, 2.705,
+ 0.235063, 0.371799, 0.57821, 0.752199, 1.00855, 1.47628, 1.80491, 2.2714, 2.65504, 2.78965,
+ 0.154939, 0.223696, 0.344718, 0.667555, 1.49566, 1.66944, 2.06988, 2.30721, 2.62769, 2.81134,
+ 0.239702, 0.335917, 0.716616, 1.1318, 1.45251, 1.63913, 2.10552, 2.27982, 2.50203, 2.66922,
+ 0.226818, 0.331261, 0.472705, 0.651974, 0.781639, 1.2198, 1.8229, 2.08273, 2.43933, 2.6109,
+ 0.223413, 0.359594, 0.534704, 0.741518, 1.22589, 1.38987, 1.61819, 2.00991, 2.207, 2.45984,
+ 0.171308, 0.268378, 0.383799, 0.858926, 1.37629, 1.51917, 1.7806, 1.92291, 2.62309, 2.8024,
+ 0.140134, 0.21232, 0.443224, 0.967457, 1.26424, 1.56215, 1.92915, 2.21739, 2.66834, 2.83075,
+ 0.221323, 0.322124, 0.485563, 0.818589, 1.01184, 1.19898, 1.42362, 1.6694, 2.15752, 2.36319,
+ 0.369687, 0.525655, 0.719213, 0.939654, 1.13763, 1.31222, 1.59994, 1.82681, 2.35522, 2.58068,
+ 0.211975, 0.314411, 0.489148, 0.739213, 1.3778, 1.5545, 1.82437, 2.15887, 2.35299, 2.72262,
+ 0.170698, 0.296368, 0.934285, 1.24313, 1.5559, 1.86654, 2.15994, 2.36344, 2.58503, 2.73853,
+ 0.189263, 0.305887, 0.439912, 0.78461, 1.22726, 1.34251, 1.58765, 1.75491, 2.43989, 2.72131,
+ 0.296339, 0.385169, 0.612012, 1.08132, 1.27636, 1.43718, 1.87147, 2.00172, 2.33909, 2.64022,
+ 0.229588, 0.320544, 0.517278, 0.969137, 1.14256, 1.62609, 1.87792, 2.11546, 2.54674, 2.70802,
+ 0.248869, 0.420193, 0.732388, 1.04902, 1.30341, 1.60146, 1.94921, 2.23946, 2.64822, 2.82261,
+ 0.2076, 0.29232, 0.496539, 0.857149, 1.18229, 1.39985, 1.71416, 1.86824, 2.02794, 2.20074,
+ 0.225558, 0.396897, 0.541783, 0.873366, 1.17897, 1.29958, 1.67719, 1.8496, 2.33048, 2.75272,
+ 0.176821, 0.231377, 0.372767, 0.508565, 1.15282, 1.80805, 2.11268, 2.25007, 2.57134, 2.74855,
+ 0.352149, 0.515765, 1.02324, 1.26022, 1.44357, 1.62207, 1.8728, 2.10018, 2.48928, 2.67104,
+ 0.166138, 0.263444, 0.370151, 0.590066, 0.754819, 0.940533, 1.76187, 1.94661, 2.44501, 2.75819,
+ 0.342082, 0.476411, 0.656223, 0.851774, 1.00399, 1.15337, 1.6944, 2.06562, 2.25564, 2.44015,
+ 0.227237, 0.376514, 0.514329, 0.894887, 1.14167, 1.28305, 1.83138, 1.9859, 2.33447, 2.78488,
+ 0.215891, 0.269548, 0.684111, 1.40566, 1.67481, 1.80093, 2.17209, 2.3394, 2.59157, 2.7301,
+ 0.23624, 0.400377, 0.533684, 0.750343, 0.910405, 1.08911, 1.73773, 1.91281, 2.19252, 2.68873,
+ 0.169242, 0.284879, 0.916252, 1.16977, 1.43368, 1.64438, 1.91912, 2.16162, 2.48266, 2.68259,
+ 0.270731, 0.336506, 0.477594, 1.04271, 1.60584, 1.79686, 1.94591, 2.16004, 2.35491, 2.52095,
+ 0.420586, 0.652563, 1.11716, 1.40601, 1.74754, 1.94742, 2.20309, 2.35997, 2.5479, 2.68217,
+ 0.281552, 0.395037, 0.640181, 0.944531, 1.19396, 1.33049, 1.71866, 2.18839, 2.44459, 2.57867,
+ 0.311824, 0.476892, 0.633431, 0.845825, 1.33252, 1.49166, 1.69361, 2.04108, 2.28932, 2.4394,
+ 0.133945, 0.20079, 0.647237, 0.927687, 1.18888, 1.36966, 1.69956, 1.97278, 2.29526, 2.67818,
+ 0.204796, 0.278215, 0.443465, 1.27048, 1.40521, 1.64092, 1.82425, 2.32709, 2.59964, 2.77253,
+ 0.18397, 0.244116, 0.410594, 0.639103, 1.22159, 1.40487, 1.62836, 1.90244, 2.16863, 2.3068,
+ 0.343622, 0.434735, 0.666599, 0.868069, 1.04894, 1.53278, 1.81983, 1.97188, 2.2887, 2.44875,
+ 0.238017, 0.320361, 0.657255, 0.917611, 1.30331, 1.72736, 1.98891, 2.18145, 2.44297, 2.61332,
+ 0.323613, 0.545056, 0.930173, 1.22606, 1.44018, 1.7723, 2.05689, 2.34781, 2.68938, 2.82062,
+ 0.28893, 0.401387, 0.617124, 0.836453, 0.990306, 1.26123, 1.91328, 2.11005, 2.32458, 2.55716,
+ 0.33267, 0.480804, 0.656147, 0.880536, 1.02957, 1.23049, 1.76906, 1.9323, 2.20037, 2.58521,
+ 0.185551, 0.265352, 0.409432, 0.608847, 1.0347, 1.22282, 1.87697, 2.17165, 2.4035, 2.66644,
+ 0.155026, 0.223348, 0.401684, 1.07914, 1.41579, 1.62002, 2.04552, 2.25851, 2.63162, 2.80229,
+ 0.183461, 0.263081, 0.425694, 0.635685, 1.18866, 1.35756, 1.57499, 2.08598, 2.28872, 2.51111,
+ 0.314738, 0.463011, 0.648733, 0.877651, 1.00289, 1.26581, 2.00541, 2.1981, 2.48153, 2.71418,
+ 0.244411, 0.318444, 0.546578, 0.793615, 1.32615, 1.73548, 1.9456, 2.11466, 2.31535, 2.47853,
+ 0.326237, 0.54354, 0.987361, 1.30441, 1.68493, 1.90215, 2.20717, 2.37427, 2.55753, 2.71622,
+ 0.157795, 0.283302, 0.430398, 0.660379, 0.81106, 1.14254, 1.4793, 1.71871, 2.67026, 2.84756,
+ 0.220856, 0.283872, 0.779935, 1.07494, 1.31221, 1.62633, 1.83761, 1.96888, 2.15599, 2.60238,
+ 0.140763, 0.205719, 0.406561, 0.762459, 1.04127, 1.48699, 1.83831, 2.11461, 2.55281, 2.77228,
+ 0.140451, 0.39592, 0.79211, 1.108, 1.40264, 1.62308, 1.94315, 2.22795, 2.54616, 2.774,
+ 0.229862, 0.336462, 0.54659, 0.81015, 1.20191, 1.34679, 1.82532, 2.09293, 2.28573, 2.47336,
+ 0.224913, 0.328246, 0.517269, 0.874793, 1.01259, 1.45218, 1.69578, 2.01493, 2.51145, 2.67257,
+ 0.247745, 0.335741, 0.546558, 0.710177, 1.17056, 1.72779, 1.97068, 2.15853, 2.48282, 2.62891,
+ 0.398252, 0.555087, 0.890367, 1.1212, 1.38153, 1.60123, 1.86665, 2.06661, 2.40516, 2.58802,
+ 0.198563, 0.288867, 0.478054, 0.658477, 0.851841, 1.0271, 1.53974, 2.02111, 2.57946, 2.78418,
+ 0.304271, 0.371642, 0.66159, 1.06898, 1.22425, 1.41193, 1.68052, 1.86977, 2.10007, 2.30855,
+ 0.188223, 0.257939, 0.432402, 0.73505, 1.31804, 1.48553, 1.82811, 2.04644, 2.30702, 2.45724,
+ 0.246723, 0.297276, 0.604475, 1.3109, 1.57044, 1.68885, 1.91366, 2.05133, 2.55601, 2.71497,
+ 0.158309, 0.234509, 0.435792, 0.6679, 0.957567, 1.23592, 1.59294, 1.81816, 2.30739, 2.76897,
+ 0.419843, 0.501412, 0.766892, 1.07317, 1.18937, 1.48022, 1.7666, 1.92215, 2.53794, 2.69477,
+ 0.27514, 0.335563, 0.678421, 1.08152, 1.59238, 1.77263, 1.93124, 2.1407, 2.3338, 2.49086,
+ 0.372056, 0.856814, 1.23954, 1.40999, 1.6903, 1.86302, 2.0727, 2.27355, 2.53266, 2.69052,
+ 0.321254, 0.422981, 0.604856, 0.793437, 0.912112, 1.12845, 1.79598, 2.17323, 2.36015, 2.53614,
+ 0.395214, 0.598779, 0.771997, 0.946713, 1.21378, 1.33043, 1.66033, 1.97715, 2.16506, 2.34402,
+ 0.225286, 0.317828, 0.464801, 1.11233, 1.36951, 1.512, 1.92195, 2.05341, 2.59352, 2.77729,
+ 0.330612, 0.407807, 0.730129, 1.25973, 1.45981, 1.60567, 1.98131, 2.13701, 2.46597, 2.67972,
+ 0.213145, 0.305305, 0.507016, 0.662299, 1.05685, 1.47986, 1.6719, 2.10271, 2.36987, 2.58199,
+ 0.219658, 0.296096, 0.443507, 0.610973, 0.799691, 1.67658, 1.96549, 2.15323, 2.50223, 2.693,
+ 0.174947, 0.257739, 0.373547, 0.552567, 1.40532, 1.61425, 1.84892, 2.11779, 2.31788, 2.7119,
+ 0.209667, 0.297529, 0.756195, 1.0953, 1.5642, 1.84477, 2.1037, 2.29266, 2.52005, 2.67949,
+ 0.170138, 0.24031, 0.452247, 0.684414, 0.880102, 1.36692, 1.74165, 2.13129, 2.50573, 2.73261,
+ 0.278164, 0.468635, 0.707518, 0.853693, 1.05478, 1.21046, 1.54094, 2.17456, 2.41066, 2.61214,
+ 0.155738, 0.23889, 0.352836, 0.621012, 1.44144, 1.6197, 1.82517, 1.97533, 2.52537, 2.74857,
+ 0.223776, 0.274424, 0.479048, 0.797871, 1.69419, 1.87813, 2.13528, 2.37373, 2.59542, 2.72979,
+ 0.151088, 0.198286, 0.326558, 0.536276, 0.845893, 1.14165, 1.46056, 1.76287, 2.02585, 2.1773,
+ 0.434445, 0.614208, 0.887657, 1.02845, 1.19136, 1.3922, 1.78689, 2.06248, 2.4234, 2.61936,
+ 0.180755, 0.275311, 0.397787, 0.859366, 1.40976, 1.52332, 1.90885, 2.08232, 2.38972, 2.74389,
+ 0.275975, 0.508416, 0.889894, 1.31893, 1.63331, 1.90473, 2.16901, 2.37466, 2.72697, 2.84767,
+ 0.156239, 0.262624, 0.406657, 0.739074, 1.04449, 1.20123, 1.81089, 2.0056, 2.5817, 2.80489,
+ 0.195391, 0.258771, 0.654924, 0.824371, 1.31526, 1.50073, 1.76594, 2.06399, 2.34118, 2.51366,
+ 0.178034, 0.301047, 0.46302, 0.716172, 1.19887, 1.34045, 1.83456, 2.02213, 2.40075, 2.77629,
+ 0.340368, 0.404236, 0.843747, 1.03924, 1.20211, 1.70805, 1.91495, 2.16951, 2.52152, 2.62335,
+ 0.218465, 0.289694, 0.528045, 0.817051, 1.13234, 1.58046, 1.83889, 1.98339, 2.14749, 2.34813,
+ 0.322509, 0.458058, 0.654679, 0.958976, 1.11821, 1.32157, 1.90139, 2.04641, 2.36093, 2.66422,
+ 0.191821, 0.252321, 0.389176, 0.581111, 1.52967, 1.93169, 2.08361, 2.27046, 2.56685, 2.71388,
+ 0.493961, 0.710827, 0.98226, 1.19627, 1.41933, 1.62091, 1.92801, 2.14565, 2.42977, 2.60197,
+ 0.213148, 0.311589, 0.424636, 0.602664, 0.736895, 1.02216, 1.99228, 2.21853, 2.61163, 2.85032,
+ 0.288129, 0.434441, 0.629313, 0.856153, 1.28967, 1.42452, 1.8758, 2.15024, 2.35181, 2.53684,
+ 0.160031, 0.230716, 0.406654, 0.870424, 1.15652, 1.39232, 1.8041, 1.95144, 2.21048, 2.73516,
+ 0.22934, 0.293962, 0.503222, 1.2421, 1.47582, 1.62465, 1.99868, 2.1445, 2.57855, 2.75327,
+ 0.15877, 0.220035, 0.363386, 0.577761, 0.96309, 1.17494, 1.73817, 1.9792, 2.16244, 2.66192,
+ 0.346062, 0.444816, 0.716985, 1.18072, 1.37058, 1.523, 1.89217, 2.06668, 2.3958, 2.62766,
+ 0.307495, 0.38933, 0.612607, 0.969283, 1.55771, 1.83994, 1.99674, 2.17238, 2.42063, 2.5392,
+ 0.437804, 0.726957, 1.29117, 1.5033, 1.76543, 1.96212, 2.16365, 2.33623, 2.57962, 2.70852,
+ 0.232184, 0.333678, 0.528368, 0.706749, 1.20328, 1.37902, 1.61116, 2.15468, 2.5929, 2.75032,
+ 0.272652, 0.46171, 0.625777, 0.839609, 1.34202, 1.49673, 1.71538, 2.13757, 2.37004, 2.59739,
+ 0.184908, 0.302324, 0.454883, 0.880307, 1.10438, 1.29253, 1.7772, 1.94336, 2.44417, 2.62273,
+ 0.265644, 0.341261, 0.553228, 1.13947, 1.42715, 1.56044, 1.93394, 2.08413, 2.39331, 2.65413,
+ 0.16792, 0.207301, 0.370331, 0.525538, 1.03089, 1.36816, 1.78247, 2.0624, 2.33276, 2.5263,
+ 0.343172, 0.433912, 0.717501, 0.889734, 1.05206, 1.69528, 2.05316, 2.20846, 2.60887, 2.71832,
+ 0.216527, 0.305247, 0.44589, 0.729271, 1.63974, 1.90328, 2.05335, 2.22125, 2.43225, 2.56802,
+ 0.110545, 0.209955, 0.844788, 1.1742, 1.4922, 1.81024, 2.17727, 2.4405, 2.69729, 2.83523,
+ 0.217384, 0.337412, 0.488999, 0.761842, 0.879715, 1.20953, 1.97075, 2.1208, 2.61165, 2.79176,
+ 0.190459, 0.296484, 0.469967, 0.800649, 1.10556, 1.27853, 1.51694, 1.69307, 2.11442, 2.71674,
+ 0.134814, 0.175978, 0.300425, 0.496817, 1.2443, 1.48531, 1.86172, 2.13123, 2.48505, 2.77388,
+ 0.210174, 0.278266, 0.435508, 0.927538, 1.60691, 1.7539, 1.95755, 2.16628, 2.39852, 2.74961,
+ 0.213766, 0.3153, 0.509924, 0.70993, 0.964724, 1.10678, 1.38261, 2.00107, 2.32321, 2.56531,
+ 0.400615, 0.524954, 0.798552, 1.01285, 1.13549, 1.47485, 1.98903, 2.13091, 2.50797, 2.67946,
+ 0.2494, 0.377023, 0.519635, 0.754227, 1.45956, 1.64276, 1.82896, 2.07788, 2.29823, 2.46753,
+ 0.473365, 0.683973, 1.05234, 1.37583, 1.54811, 1.74759, 2.1393, 2.31877, 2.60998, 2.73925,
+ 0.203877, 0.341791, 0.48518, 0.884069, 1.09759, 1.26953, 1.47992, 1.75788, 2.6484, 2.82239,
+ 0.273046, 0.404254, 0.555403, 0.954547, 1.29123, 1.39902, 1.72289, 1.90344, 2.17198, 2.64531,
+ 0.040369, 0.117266, 0.617136, 0.892043, 1.26033, 1.54165, 1.85938, 2.1531, 2.49823, 2.76189,
+ 0.132414, 0.211358, 0.742445, 1.06686, 1.33108, 1.57079, 1.86746, 2.13253, 2.47962, 2.73108,
+ 0.237329, 0.326529, 0.612538, 0.790663, 0.990133, 1.41374, 1.73823, 1.93691, 2.16773, 2.45163,
+ 0.27396, 0.405794, 0.57253, 0.933672, 1.05782, 1.39795, 1.85653, 1.99755, 2.59949, 2.76004,
+ 0.199334, 0.29838, 0.442931, 0.628638, 1.30321, 1.64014, 1.80402, 2.11302, 2.37545, 2.54895,
+ 0.350188, 0.50201, 0.821298, 1.03864, 1.36929, 1.5924, 1.91082, 2.15649, 2.46051, 2.65326,
+ 0.281558, 0.399892, 0.573105, 0.753299, 0.900613, 1.05457, 1.58199, 2.17844, 2.43035, 2.61604,
+ 0.344653, 0.543532, 0.703715, 0.862285, 1.19822, 1.33821, 1.57908, 2.06077, 2.30675, 2.48575,
+ 0.220701, 0.326795, 0.520618, 0.755133, 1.29555, 1.45189, 1.6905, 2.20005, 2.41427, 2.61591,
+ 0.279478, 0.332193, 0.801527, 1.34597, 1.48748, 1.6785, 1.9222, 2.10002, 2.58557, 2.71339,
+ 0.163502, 0.212169, 0.365096, 0.525464, 0.869846, 1.20881, 1.79399, 2.04031, 2.29718, 2.4698,
+ 0.285531, 0.341488, 0.754059, 1.17002, 1.30084, 1.5137, 1.69986, 1.88992, 2.58146, 2.70687,
+ 0.249595, 0.366997, 0.626427, 0.945219, 1.40704, 1.56056, 1.83166, 2.23115, 2.46635, 2.65452,
+ 0.271671, 0.443136, 1.15641, 1.40646, 1.67652, 1.85648, 2.06322, 2.2305, 2.47584, 2.63958,
+ 0.28662, 0.427806, 0.63732, 0.803409, 0.996161, 1.26638, 1.68175, 2.00397, 2.39465, 2.58855,
+ 0.314906, 0.440519, 0.612129, 0.896126, 1.47241, 1.71769, 1.88135, 2.09944, 2.36917, 2.49547,
+ 0.170277, 0.25127, 0.405477, 0.915641, 1.12689, 1.43663, 1.71477, 1.8932, 2.55299, 2.73852,
+ 0.27941, 0.337137, 0.734563, 1.28105, 1.4806, 1.61188, 1.85321, 1.99488, 2.41605, 2.65483,
+ 0.165776, 0.226083, 0.417544, 0.744574, 1.04447, 1.53489, 1.80849, 1.94495, 2.13849, 2.60179,
+ 0.264579, 0.336652, 0.542033, 0.71019, 0.913338, 1.65575, 1.81776, 2.23196, 2.52444, 2.65852,
+ 0.158194, 0.235588, 0.338347, 0.541657, 1.58338, 1.76629, 2.00914, 2.24334, 2.50394, 2.77516,
+ 0.332612, 0.50962, 0.822935, 1.07588, 1.45429, 1.65079, 1.97445, 2.25128, 2.53734, 2.74512,
+ 0.262817, 0.359709, 0.520893, 0.707667, 0.818364, 1.43885, 1.97125, 2.08767, 2.49701, 2.64644,
+ 0.2332, 0.399599, 0.612456, 0.775547, 1.19919, 1.35576, 1.6469, 2.13625, 2.34249, 2.69574,
+ 0.149687, 0.238538, 0.372248, 0.63452, 1.25581, 1.43379, 1.77004, 1.92875, 2.61191, 2.82493,
+ 0.137016, 0.210297, 0.591489, 1.12545, 1.37565, 1.6853, 2.08961, 2.39089, 2.70446, 2.84443,
+ 0.21349, 0.341024, 0.541716, 0.750061, 1.0882, 1.24458, 1.55534, 1.96557, 2.1879, 2.38371,
+ 0.300159, 0.489291, 0.825022, 1.0371, 1.19409, 1.34738, 1.68475, 2.02494, 2.46561, 2.74097,
+ 0.170029, 0.255033, 0.392758, 0.727117, 1.38207, 1.57968, 1.80091, 1.95907, 2.28234, 2.7288,
+ 0.175883, 0.365509, 1.11217, 1.38587, 1.72039, 1.97781, 2.2453, 2.42161, 2.62957, 2.754,
+ 0.16259, 0.248164, 0.45463, 0.763209, 0.966031, 1.28234, 1.73074, 1.93805, 2.47938, 2.66756,
+ 0.258043, 0.345866, 0.55652, 0.981312, 1.36153, 1.48238, 1.87224, 2.15823, 2.36227, 2.55503,
+ 0.234139, 0.348843, 0.528234, 0.987884, 1.19522, 1.42215, 1.96003, 2.12737, 2.60332, 2.793,
+ 0.179699, 0.559209, 0.867682, 1.08884, 1.31689, 1.5715, 1.9222, 2.19739, 2.50112, 2.72868,
+ 0.216784, 0.310791, 0.487492, 0.932903, 1.20195, 1.36655, 1.8004, 1.9775, 2.17426, 2.53707,
+ 0.186878, 0.400655, 0.580952, 0.846287, 1.10387, 1.26678, 1.84277, 2.01959, 2.488, 2.71722,
+ 0.164641, 0.248712, 0.389358, 0.772822, 1.21256, 1.36992, 2.02587, 2.27762, 2.61752, 2.80953,
+ 0.351899, 0.520326, 0.926597, 1.21965, 1.50984, 1.67684, 1.92174, 2.11125, 2.35638, 2.54593,
+ 0.242182, 0.365285, 0.506156, 0.71602, 0.865221, 1.01169, 1.78692, 2.12298, 2.35088, 2.76773,
+ 0.413776, 0.559566, 0.7358, 0.928997, 1.07912, 1.26718, 1.88007, 2.15249, 2.32483, 2.53986,
+ 0.210597, 0.329568, 0.469735, 0.78859, 1.21549, 1.31981, 1.71146, 2.05899, 2.24544, 2.65373,
+ 0.197937, 0.254148, 0.477985, 1.22709, 1.62992, 1.76743, 2.18698, 2.3851, 2.59487, 2.72554,
+ 0.205489, 0.333855, 0.523915, 0.706275, 1.10215, 1.24661, 1.6489, 2.02683, 2.28169, 2.75931,
+ 0.230328, 0.322431, 0.861834, 1.14561, 1.34721, 1.57611, 1.80728, 2.00482, 2.35437, 2.57225,
+ 0.224898, 0.282022, 0.506636, 1.1523, 1.62656, 1.75209, 2.02818, 2.21882, 2.48896, 2.67046,
+ 0.313732, 0.625469, 1.16447, 1.49908, 1.74961, 2.01853, 2.26223, 2.4296, 2.69216, 2.8225,
+ 0.375623, 0.575307, 0.7912, 0.93577, 1.09694, 1.34339, 1.80799, 2.18731, 2.51972, 2.6948,
+ 0.236981, 0.332412, 0.47927, 0.844461, 1.34764, 1.49073, 1.68394, 2.03914, 2.29762, 2.45843,
+ 0.129047, 0.20625, 0.636751, 0.865101, 1.13689, 1.35661, 1.7048, 1.91668, 2.51836, 2.75632,
+ 0.195171, 0.266517, 0.414793, 1.23956, 1.45291, 1.60836, 1.83305, 2.0478, 2.47352, 2.62199,
+ 0.165853, 0.21272, 0.372757, 0.536136, 1.01394, 1.33963, 1.55512, 1.94574, 2.23628, 2.44095,
+ 0.256981, 0.368868, 0.635878, 0.802543, 1.08476, 1.43912, 1.81473, 2.12052, 2.45815, 2.62146,
+ 0.214382, 0.297135, 0.445091, 0.70205, 1.3651, 1.85126, 2.06703, 2.2073, 2.47073, 2.61243,
+ 0.34071, 0.532103, 0.935278, 1.17102, 1.37789, 1.6386, 1.96527, 2.24616, 2.63127, 2.80634,
+ 0.310524, 0.412051, 0.582478, 0.768755, 0.871594, 1.11985, 1.92635, 2.20751, 2.40709, 2.63663,
+ 0.249349, 0.443517, 0.631532, 0.810096, 1.20513, 1.35721, 1.6074, 1.98416, 2.20802, 2.64511,
+ 0.14309, 0.185312, 0.325214, 0.504, 1.13447, 1.32791, 1.67365, 2.0069, 2.38928, 2.74609,
+ 0.226575, 0.298946, 0.453938, 0.998061, 1.3946, 1.59728, 2.06418, 2.22325, 2.42547, 2.56946,
+ 0.183924, 0.255181, 0.415834, 0.624247, 1.04234, 1.20308, 1.55524, 2.12531, 2.40035, 2.66192,
+ 0.27561, 0.365968, 0.654909, 0.990108, 1.1708, 1.45533, 2.07756, 2.25267, 2.50232, 2.68595,
+ 0.204334, 0.287844, 0.39481, 0.761295, 1.5012, 1.78471, 1.93557, 2.15283, 2.34926, 2.54564,
+ 0.342976, 0.527539, 0.917466, 1.16059, 1.49953, 1.76183, 2.09527, 2.30187, 2.54057, 2.69469,
+ 0.202374, 0.333367, 0.480179, 0.708677, 0.819505, 1.10529, 1.80664, 1.95335, 2.61084, 2.7975,
+ 0.307033, 0.368471, 0.602486, 1.10861, 1.41335, 1.52864, 1.79852, 1.98614, 2.16905, 2.43726,
+ 0.144073, 0.196932, 0.386988, 0.819061, 1.28977, 1.62507, 1.90192, 2.13611, 2.48302, 2.70797,
+ 0.17676, 0.268627, 0.662082, 1.05687, 1.54797, 1.71139, 1.97294, 2.24991, 2.54447, 2.76109,
+ 0.191409, 0.292985, 0.492193, 0.800526, 1.04184, 1.27855, 1.83663, 2.02868, 2.24939, 2.62778,
+ 0.324102, 0.399146, 0.687435, 0.868704, 1.02296, 1.58208, 1.85385, 1.98188, 2.55491, 2.67706,
+ 0.229172, 0.302836, 0.481418, 0.704363, 0.967567, 1.82827, 2.0973, 2.25847, 2.54911, 2.70465,
+ 0.467124, 0.696788, 0.9395, 1.09499, 1.27754, 1.4885, 1.89628, 2.15847, 2.47418, 2.65999,
+ 0.175418, 0.234039, 0.367674, 0.513586, 0.747619, 1.0084, 1.58316, 2.05311, 2.36329, 2.68115,
+ 0.410273, 0.561949, 0.736215, 0.956685, 1.13569, 1.28842, 1.75061, 1.93771, 2.15132, 2.48934,
+ 0.204541, 0.277613, 0.529607, 0.722971, 1.19998, 1.44734, 1.71563, 1.92105, 2.35778, 2.50749,
+ 0.253116, 0.311907, 0.696982, 1.32008, 1.57542, 1.70532, 2.00507, 2.16867, 2.46188, 2.66505,
+ 0.163657, 0.237902, 0.393374, 0.60949, 0.854272, 1.08998, 1.52639, 1.84234, 2.12625, 2.67905,
+ 0.448627, 0.530664, 0.812719, 1.0952, 1.20764, 1.57541, 1.88421, 2.0343, 2.55301, 2.68835,
+ 0.262717, 0.338748, 0.512685, 1.00354, 1.48018, 1.62208, 1.82852, 2.14242, 2.35646, 2.51153,
+ 0.417111, 0.636688, 1.03657, 1.31988, 1.67992, 1.87339, 2.07372, 2.2494, 2.50773, 2.65105,
+ 0.263698, 0.461151, 0.618737, 0.830471, 1.00404, 1.15887, 1.80157, 2.02022, 2.30656, 2.74304,
+ 0.387779, 0.575108, 0.729791, 0.932981, 1.36116, 1.50516, 1.75118, 2.06847, 2.33826, 2.48764,
+ 0.18151, 0.265666, 0.454631, 1.08238, 1.2873, 1.5792, 1.85118, 2.09696, 2.46724, 2.64693,
+ 0.277668, 0.345119, 0.602341, 1.1792, 1.37899, 1.54562, 1.81386, 1.96259, 2.4918, 2.66445,
+ 0.17932, 0.24808, 0.456925, 0.722589, 1.12693, 1.57945, 1.7994, 1.95067, 2.48412, 2.70724,
+ 0.314322, 0.381145, 0.608651, 0.727613, 0.890472, 1.61028, 2.13617, 2.25836, 2.59638, 2.70978,
+ 0.189539, 0.266068, 0.419729, 0.651693, 1.41016, 1.64311, 1.85481, 2.27558, 2.49205, 2.72201,
+ 0.254466, 0.313038, 0.594149, 1.01254, 1.68881, 1.93546, 2.11918, 2.28787, 2.53554, 2.66793,
+ 0.134691, 0.171906, 0.30274, 0.492936, 0.899551, 1.22919, 1.73394, 2.01288, 2.44634, 2.74276,
+ 0.231556, 0.365068, 0.680761, 0.889142, 1.11134, 1.2959, 1.54264, 1.97178, 2.42756, 2.63191,
+ 0.222525, 0.305606, 0.527193, 0.687519, 1.18138, 1.67176, 1.86368, 2.07202, 2.63452, 2.77927,
+ 0.17877, 0.237415, 0.37516, 0.856692, 1.67368, 1.81374, 2.01679, 2.27242, 2.5226, 2.73596,
+ 0.193532, 0.268731, 0.451328, 0.753471, 0.984854, 1.28535, 1.68565, 1.88412, 2.09168, 2.24342,
+ 0.476037, 0.65161, 0.801054, 1.01016, 1.24137, 1.35584, 1.77598, 2.08615, 2.27291, 2.45435,
+ 0.211657, 0.308331, 0.421366, 0.865966, 1.41877, 1.55674, 1.78615, 2.02033, 2.19859, 2.63198,
+ 0.203789, 0.490794, 1.01014, 1.27501, 1.47221, 1.81014, 2.17064, 2.43766, 2.66212, 2.78806,
+ 0.174355, 0.252095, 0.674715, 0.842194, 1.05509, 1.278, 1.69868, 2.07056, 2.39938, 2.65743,
+ 0.245109, 0.324049, 0.628822, 0.92791, 1.1236, 1.58007, 1.87864, 2.0546, 2.35872, 2.54684,
+ 0.182644, 0.253804, 0.386248, 0.614056, 1.36482, 1.54588, 2.04017, 2.21883, 2.41901, 2.62461,
+ 0.295605, 0.367794, 0.690701, 1.05516, 1.1866, 1.64445, 1.94415, 2.10144, 2.56212, 2.69127,
+ 0.220878, 0.289573, 0.640307, 0.822072, 1.14406, 1.5678, 1.76641, 1.90811, 2.10346, 2.56049,
+ 0.403453, 0.526298, 0.732204, 0.90115, 1.03587, 1.33938, 1.78399, 1.94196, 2.37103, 2.62665,
+ 0.212825, 0.25857, 0.471588, 0.685549, 1.26374, 1.82105, 2.16382, 2.2884, 2.62806, 2.78816,
+ 0.401181, 0.642053, 1.03247, 1.23611, 1.44445, 1.68668, 2.00672, 2.22851, 2.57211, 2.72396,
+ 0.239433, 0.341091, 0.492629, 0.70763, 0.881426, 1.03082, 1.71925, 2.34406, 2.57906, 2.75694,
+ 0.294093, 0.38277, 0.577412, 1.00928, 1.31304, 1.4193, 1.74467, 2.09423, 2.28904, 2.47584,
+ 0.169805, 0.236922, 0.403314, 0.638995, 1.17645, 1.35214, 1.66557, 1.90976, 2.15012, 2.71624,
+ 0.210447, 0.277913, 0.452474, 1.40269, 1.51343, 1.72094, 1.90394, 2.2785, 2.58376, 2.74318,
+ 0.159574, 0.225382, 0.374008, 0.714137, 1.01125, 1.37171, 1.69916, 1.87159, 2.02706, 2.49119,
+ 0.258602, 0.557253, 0.81972, 1.03886, 1.30147, 1.44536, 1.83061, 2.09817, 2.32081, 2.54107,
+ 0.232756, 0.282242, 0.631974, 0.898694, 1.53744, 1.86922, 2.06397, 2.23446, 2.49823, 2.63352,
+ 0.580133, 0.997946, 1.32096, 1.48187, 1.73161, 1.89858, 2.12071, 2.29013, 2.53009, 2.65166,
+ 0.21184, 0.307093, 0.45336, 0.945579, 1.25082, 1.49029, 1.72414, 2.2811, 2.5627, 2.7526,
+ 0.314276, 0.493555, 0.667782, 0.8965, 1.32301, 1.48262, 1.66749, 1.97441, 2.42735, 2.55568,
+ 0.182455, 0.261592, 0.418011, 1.05093, 1.26139, 1.44337, 1.66547, 1.93903, 2.44469, 2.63845,
+ 0.24157, 0.306934, 0.491293, 1.10595, 1.55483, 1.66652, 1.92392, 2.08765, 2.3676, 2.65489,
+ 0.190084, 0.25485, 0.454062, 0.724519, 1.08336, 1.39389, 1.89234, 2.08886, 2.32176, 2.4843,
+ 0.306497, 0.389831, 0.721793, 0.839714, 1.12475, 1.6524, 1.82292, 2.27331, 2.5692, 2.6696,
+ 0.1862, 0.27346, 0.383201, 0.564758, 1.51107, 1.84502, 1.99828, 2.1941, 2.38869, 2.58792,
+ 0.300722, 0.478218, 0.823364, 1.12749, 1.59114, 1.87135, 2.17472, 2.40318, 2.62478, 2.7824,
+ 0.228884, 0.358342, 0.504622, 0.795874, 1.00562, 1.15261, 1.90805, 2.12479, 2.37247, 2.79758,
+ 0.171885, 0.248234, 0.432842, 0.833143, 1.04089, 1.26929, 1.66164, 1.91863, 2.15896, 2.6534,
+ 0.140943, 0.193684, 0.343025, 0.562303, 1.06955, 1.54333, 1.82447, 1.96164, 2.46351, 2.77054,
+ 0.173053, 0.245656, 0.360656, 0.960618, 1.58953, 1.68991, 1.98414, 2.143, 2.58839, 2.7594,
+ 0.24018, 0.429951, 0.63744, 0.786596, 1.06915, 1.22657, 1.47088, 1.95205, 2.19506, 2.61597,
+ 0.367862, 0.471897, 0.730834, 1.08232, 1.22629, 1.46293, 1.92817, 2.05247, 2.40674, 2.66246,
+ 0.247175, 0.358209, 0.535946, 0.781876, 1.3637, 1.63524, 1.80723, 1.99378, 2.45277, 2.60104,
+ 0.445578, 0.687898, 1.11411, 1.30103, 1.5774, 1.88604, 2.2249, 2.43653, 2.65969, 2.76103,
+ 0.214389, 0.336025, 0.487794, 0.759534, 0.970518, 1.1411, 1.45733, 1.62464, 2.30692, 2.71527,
+ 0.3773, 0.466775, 0.716121, 1.08378, 1.25654, 1.41124, 1.78943, 1.93637, 2.20557, 2.56236,
+ 0.148362, 0.214593, 0.545023, 0.840437, 1.19333, 1.48066, 1.79187, 2.08342, 2.41054, 2.67613,
+ 0.150403, 0.278398, 0.792676, 0.97668, 1.21885, 1.40524, 1.77506, 2.16246, 2.54786, 2.74638,
+ 0.236301, 0.328633, 0.630867, 0.839915, 1.04235, 1.29887, 1.62775, 1.83949, 2.29893, 2.49396,
+ 0.337889, 0.49792, 0.711277, 0.85042, 0.992027, 1.24688, 1.71075, 2.08668, 2.52716, 2.70716,
+ 0.172215, 0.23654, 0.372897, 0.525146, 1.18258, 1.73573, 1.92703, 2.11462, 2.31917, 2.54278,
+ 0.415304, 0.624807, 0.906616, 1.11784, 1.44615, 1.66942, 1.94841, 2.17282, 2.50453, 2.67075,
+ 0.265417, 0.407241, 0.613894, 0.816534, 0.980063, 1.15606, 1.75675, 2.27485, 2.49719, 2.71224,
+ 0.27644, 0.468209, 0.649518, 0.816686, 1.19517, 1.35552, 1.54923, 1.93527, 2.21787, 2.42698,
+ 0.188925, 0.277012, 0.412665, 0.672627, 1.35481, 1.51452, 1.69999, 2.14455, 2.38219, 2.58608,
+ 0.24263, 0.352485, 0.912974, 1.34378, 1.60443, 1.80187, 2.01479, 2.19307, 2.46081, 2.632,
+ 0.190903, 0.285841, 0.44907, 0.760328, 0.954285, 1.18294, 1.69264, 1.87816, 2.27684, 2.46596,
+ 0.220659, 0.300374, 0.721694, 0.947306, 1.29833, 1.56298, 1.76062, 1.88825, 2.50644, 2.68968,
+ 0.213168, 0.290928, 0.695227, 0.918179, 1.37819, 1.63199, 1.84789, 2.00307, 2.35836, 2.61935,
+ 0.328586, 0.517244, 0.93732, 1.37624, 1.57484, 1.76435, 2.05863, 2.22433, 2.58444, 2.75665,
+ 0.248486, 0.367007, 0.562147, 0.750632, 0.902785, 1.14756, 1.63742, 1.91206, 2.41399, 2.6057,
+ 0.310691, 0.477895, 0.670796, 0.940507, 1.41829, 1.5635, 1.80514, 2.11408, 2.37636, 2.53516,
+ 0.256555, 0.41421, 0.559427, 0.981289, 1.19165, 1.37831, 1.6784, 1.84931, 2.5767, 2.75663,
+ 0.291424, 0.335003, 0.750149, 1.28965, 1.43721, 1.59999, 1.80318, 1.96741, 2.60175, 2.73376,
+ 0.195254, 0.279513, 0.451755, 0.649111, 0.828694, 1.60951, 1.91491, 2.09122, 2.31959, 2.5349,
+ 0.222304, 0.332624, 0.475678, 0.685205, 1.03033, 1.73722, 1.92098, 2.37829, 2.70672, 2.81773,
+ 0.164833, 0.240093, 0.359862, 0.801929, 1.51368, 1.64171, 2.04052, 2.24884, 2.48866, 2.71403,
+ 0.214777, 0.287322, 0.572644, 1.14507, 1.36711, 1.75269, 2.04242, 2.22207, 2.54305, 2.69789,
+ 0.226099, 0.330382, 0.474439, 0.687757, 0.799187, 1.31984, 1.94457, 2.0781, 2.3678, 2.50846,
+ 0.24454, 0.392163, 0.553692, 0.729765, 1.24786, 1.44838, 1.61759, 2.07464, 2.34005, 2.51806,
+ 0.175381, 0.314231, 0.446023, 0.797404, 1.32846, 1.43973, 1.79335, 1.93957, 2.4688, 2.72165,
+ 0.205808, 0.29367, 0.452447, 1.07427, 1.28823, 1.65563, 1.8575, 2.36469, 2.63981, 2.79814,
+ 0.253926, 0.392653, 0.587584, 0.800134, 0.97631, 1.18559, 1.57069, 1.82141, 2.09089, 2.34902,
+ 0.322461, 0.410912, 0.723569, 1.06064, 1.20152, 1.40036, 1.57919, 1.78876, 2.46024, 2.6166,
+ 0.211266, 0.304981, 0.436011, 0.771978, 1.49062, 1.67775, 1.88623, 2.1135, 2.32635, 2.72726,
+ 0.235012, 0.406911, 0.864785, 1.29148, 1.70829, 1.93855, 2.1799, 2.3524, 2.56379, 2.71145,
+ 0.176814, 0.26862, 0.445837, 0.823113, 1.02978, 1.27157, 1.62339, 1.81122, 2.40214, 2.61417,
+ 0.241865, 0.339268, 0.507509, 1.00368, 1.20435, 1.37256, 1.94079, 2.10137, 2.38561, 2.66998,
+ 0.230878, 0.334743, 0.50037, 0.879929, 1.02189, 1.53377, 1.97079, 2.12897, 2.56726, 2.71729,
+ 0.297505, 0.451574, 0.748848, 0.988527, 1.36624, 1.60667, 1.89466, 2.17448, 2.52143, 2.75917,
+ 0.199265, 0.271145, 0.49816, 0.854679, 1.1721, 1.36415, 1.76208, 1.96909, 2.17354, 2.31163,
+ 0.222173, 0.424864, 0.564942, 0.829809, 1.03817, 1.19405, 1.7206, 1.85809, 2.43176, 2.74146,
+ 0.181961, 0.226819, 0.390513, 0.556339, 1.0566, 1.55306, 2.12835, 2.25802, 2.6025, 2.80212,
+ 0.3576, 0.565047, 1.15301, 1.35031, 1.53358, 1.71854, 1.95789, 2.17535, 2.50565, 2.67849,
+ 0.162257, 0.236808, 0.374039, 0.570569, 0.748034, 1.17226, 1.82339, 2.05303, 2.51377, 2.77207,
+ 0.305794, 0.46587, 0.645121, 0.88265, 1.14129, 1.26686, 1.70158, 2.00288, 2.18412, 2.41125,
+ 0.231652, 0.380738, 0.549642, 0.83741, 1.22527, 1.33297, 1.85158, 2.11937, 2.31508, 2.73211,
+ 0.235449, 0.286771, 0.684809, 1.34666, 1.52663, 1.70348, 2.10149, 2.25455, 2.57718, 2.71899,
+ 0.23387, 0.446515, 0.60508, 0.814654, 1.05496, 1.1788, 1.63316, 1.84974, 2.13938, 2.73277,
+ 0.271706, 0.335152, 0.857227, 1.25374, 1.38719, 1.70217, 1.89677, 2.19111, 2.48, 2.60136,
+ 0.237386, 0.314549, 0.438339, 0.912164, 1.57776, 1.87779, 2.03279, 2.19704, 2.41232, 2.53648,
+ 0.361168, 0.574093, 1.02384, 1.46852, 1.69056, 1.91737, 2.18737, 2.33403, 2.6691, 2.80629,
+ 0.27848, 0.398742, 0.573342, 0.839212, 1.07389, 1.22209, 1.69168, 2.16526, 2.37741, 2.53688,
+ 0.286018, 0.447947, 0.61506, 0.849446, 1.31947, 1.46358, 1.76995, 2.00103, 2.18943, 2.45038,
+ 0.21944, 0.301601, 0.668534, 0.861094, 1.21, 1.49867, 1.74512, 1.87777, 2.31438, 2.6196,
+ 0.223591, 0.352153, 0.598841, 1.21789, 1.35908, 1.59174, 1.77109, 2.21386, 2.56154, 2.73542,
+ 0.176857, 0.236601, 0.395107, 0.634632, 1.13349, 1.33512, 1.77037, 1.98131, 2.20656, 2.33972,
+ 0.334735, 0.402265, 0.659168, 0.781639, 0.975228, 1.665, 1.87207, 2.04753, 2.47696, 2.57398,
+ 0.215968, 0.284755, 0.524241, 0.78146, 1.33481, 1.77238, 1.95388, 2.19421, 2.57825, 2.74194,
+ 0.298193, 0.489879, 0.812985, 1.18369, 1.49642, 1.67998, 2.10879, 2.31656, 2.67378, 2.85161,
+ 0.312989, 0.415446, 0.618011, 0.899096, 1.08368, 1.26338, 1.8874, 2.24306, 2.41945, 2.57048,
+ 0.244471, 0.431115, 0.601512, 0.813139, 1.10216, 1.22106, 1.69244, 2.03316, 2.2218, 2.61984,
+ 0.150949, 0.21906, 0.349217, 0.611327, 1.07711, 1.25055, 1.91552, 2.08398, 2.45, 2.79254,
+ 0.161611, 0.218964, 0.445377, 0.927863, 1.45115, 1.76846, 2.13001, 2.36672, 2.666, 2.81405,
+ 0.196, 0.297256, 0.497266, 0.6919, 1.08988, 1.27368, 1.51372, 2.00647, 2.27378, 2.57222,
+ 0.335268, 0.460795, 0.685187, 0.867664, 1.01381, 1.47955, 2.01199, 2.16848, 2.57264, 2.71756,
+ 0.257604, 0.340872, 0.499757, 0.843052, 1.39655, 1.83169, 2.03423, 2.17033, 2.42262, 2.5405,
+ 0.417663, 0.631718, 0.955424, 1.19732, 1.6598, 1.87988, 2.1688, 2.35905, 2.57809, 2.69825,
+ 0.162052, 0.251583, 0.4399, 0.660911, 0.903902, 1.3203, 1.62476, 1.77858, 2.53053, 2.79971,
+ 0.256861, 0.322803, 0.68537, 1.08644, 1.26328, 1.56988, 1.85165, 2.01495, 2.26471, 2.44701,
+ 0.125192, 0.176171, 0.336135, 0.7816, 1.20022, 1.43997, 1.80542, 2.07752, 2.46247, 2.73819,
+ 0.102286, 0.191322, 0.774556, 1.07615, 1.36946, 1.62715, 1.97301, 2.236, 2.60937, 2.81298,
+ 0.173442, 0.232622, 0.491622, 0.844157, 1.09524, 1.3708, 1.69697, 2.05141, 2.31606, 2.50205,
+ 0.257531, 0.343598, 0.654071, 0.838985, 1.0481, 1.48747, 1.72538, 1.89742, 2.43051, 2.586,
+ 0.1979, 0.276312, 0.440283, 0.705103, 1.26734, 1.7403, 1.93448, 2.15401, 2.4002, 2.62414,
+ 0.40959, 0.596785, 0.983751, 1.18177, 1.37115, 1.50238, 1.75828, 2.01857, 2.38005, 2.59215,
+ 0.231819, 0.33289, 0.483514, 0.644585, 0.816808, 0.926308, 1.4033, 2.23301, 2.46786, 2.67846,
+ 0.25861, 0.340064, 0.670485, 0.908467, 1.10761, 1.45624, 1.75958, 1.93218, 2.11312, 2.31013,
+ 0.184377, 0.249203, 0.410806, 0.587907, 1.3025, 1.51032, 1.72443, 1.98189, 2.2829, 2.42213,
+ 0.25411, 0.313328, 0.659859, 1.26582, 1.41295, 1.66593, 1.92715, 2.10198, 2.55145, 2.67303,
+ 0.161592, 0.23748, 0.376535, 0.637094, 0.823028, 1.13761, 1.69642, 1.87577, 2.40363, 2.63962,
+ 0.384501, 0.466812, 0.740791, 0.938093, 1.06235, 1.50928, 1.74914, 1.9178, 2.54816, 2.67151,
+ 0.333872, 0.419367, 0.638994, 1.09262, 1.52055, 1.64945, 1.86662, 2.14894, 2.34672, 2.50614,
+ 0.426216, 0.686997, 1.23588, 1.42885, 1.61159, 1.79286, 2.01759, 2.23372, 2.54777, 2.69661,
+ 0.262949, 0.367509, 0.530429, 0.741867, 0.872474, 1.0696, 1.74557, 2.06119, 2.28384, 2.49418,
+ 0.335782, 0.547236, 0.716211, 0.919077, 1.27569, 1.40844, 1.68512, 1.96739, 2.21764, 2.44668,
+ 0.227629, 0.330991, 0.486068, 1.11757, 1.30498, 1.51013, 1.75726, 1.94697, 2.62556, 2.7826,
+ 0.35985, 0.436633, 0.750634, 1.20151, 1.33757, 1.59484, 1.97027, 2.11384, 2.57381, 2.72996,
+ 0.211871, 0.304028, 0.512758, 0.663762, 1.08635, 1.63333, 1.81802, 2.12958, 2.39108, 2.60077,
+ 0.196092, 0.279726, 0.434488, 0.624802, 0.772358, 1.40438, 1.94878, 2.16092, 2.63, 2.77518,
+ 0.176304, 0.262521, 0.373719, 0.581101, 1.52011, 1.73617, 1.93323, 2.14017, 2.35813, 2.75352,
+ 0.254932, 0.381411, 0.806187, 1.10229, 1.53452, 1.75028, 1.9709, 2.15987, 2.45592, 2.65841,
+ 0.190385, 0.288656, 0.449066, 0.678174, 0.812376, 1.44933, 1.72866, 1.96632, 2.63881, 2.78955,
+ 0.251178, 0.386509, 0.609363, 0.797102, 1.02416, 1.18173, 1.45466, 2.01263, 2.49309, 2.69893,
+ 0.166654, 0.266226, 0.385171, 0.71199, 1.3979, 1.53235, 1.91597, 2.088, 2.56527, 2.78953,
+ 0.238453, 0.306036, 0.449309, 0.876277, 1.52144, 1.93398, 2.13442, 2.26799, 2.5376, 2.65825,
+ 0.161634, 0.219919, 0.353206, 0.524346, 0.961806, 1.20771, 1.68792, 1.91694, 2.16187, 2.32066,
+ 0.413612, 0.597095, 0.793763, 0.98629, 1.28179, 1.41266, 1.65246, 2.01609, 2.38416, 2.52858,
+ 0.228655, 0.341562, 0.480989, 0.988605, 1.371, 1.47742, 1.86103, 2.01585, 2.33975, 2.77315,
+ 0.259092, 0.597012, 0.985224, 1.32174, 1.64335, 1.95737, 2.28868, 2.49747, 2.71649, 2.84447,
+ 0.185652, 0.304664, 0.446232, 0.864434, 1.09179, 1.27377, 1.94257, 2.09554, 2.52465, 2.76824,
+ 0.176687, 0.256678, 0.745652, 0.934909, 1.28376, 1.44006, 1.76524, 2.12209, 2.3881, 2.59055,
+ 0.189805, 0.275637, 0.440995, 0.821356, 1.25602, 1.41098, 1.92978, 2.12014, 2.39603, 2.60464,
+ 0.266823, 0.337688, 0.819408, 1.13475, 1.2892, 1.77703, 1.98289, 2.22175, 2.59029, 2.6981,
+ 0.205348, 0.276512, 0.527305, 0.727412, 1.02465, 1.65398, 1.90418, 2.04661, 2.21792, 2.45566,
+ 0.293498, 0.424494, 0.613795, 0.95613, 1.13398, 1.3248, 1.80903, 1.95392, 2.29385, 2.57588,
+ 0.18312, 0.24965, 0.376204, 0.543914, 1.35083, 1.90722, 2.09255, 2.25571, 2.51439, 2.6879,
+ 0.541205, 0.789796, 1.05895, 1.26942, 1.5039, 1.70219, 1.97018, 2.17544, 2.49681, 2.65224,
+ 0.229326, 0.339475, 0.451881, 0.66121, 0.795832, 1.0738, 2.0271, 2.20637, 2.4789, 2.72678,
+ 0.330006, 0.506868, 0.673076, 0.887406, 1.22877, 1.34923, 1.78129, 2.08658, 2.27776, 2.48003,
+ 0.138389, 0.200001, 0.396259, 0.811975, 1.09071, 1.46041, 1.74549, 1.90427, 2.34825, 2.69989,
+ 0.176584, 0.242161, 0.37827, 1.17785, 1.56472, 1.67817, 1.95162, 2.12141, 2.58011, 2.73713,
+ 0.145852, 0.198423, 0.335644, 0.550505, 1.01973, 1.37119, 1.79763, 1.94383, 2.20749, 2.74647,
+ 0.385078, 0.503696, 0.703239, 1.06999, 1.36574, 1.47205, 1.82583, 2.15964, 2.37128, 2.52097,
+ 0.28495, 0.38805, 0.507352, 0.879125, 1.52353, 1.77624, 1.9296, 2.15756, 2.44799, 2.5864,
+ 0.491116, 0.756155, 1.2552, 1.52246, 1.77658, 2.02812, 2.28606, 2.42977, 2.67911, 2.77616,
+ 0.252477, 0.396081, 0.713022, 0.861502, 1.15222, 1.3708, 1.61401, 2.1448, 2.57407, 2.71253,
+ 0.282756, 0.438437, 0.613566, 0.847746, 1.26077, 1.37906, 1.6422, 2.13754, 2.36837, 2.52216,
+ 0.203971, 0.322195, 0.479842, 0.953133, 1.21128, 1.39763, 1.80081, 1.95452, 2.40348, 2.57371,
+ 0.264533, 0.358424, 0.628768, 1.11124, 1.34025, 1.50648, 1.99959, 2.19411, 2.46141, 2.66736,
+ 0.17773, 0.22368, 0.394553, 0.556177, 0.947415, 1.50064, 1.73353, 1.92605, 2.26147, 2.43605,
+ 0.314223, 0.363636, 0.727886, 0.85188, 1.05384, 1.79813, 1.97435, 2.1826, 2.538, 2.62968,
+ 0.201778, 0.2755, 0.404891, 0.747466, 1.50005, 1.84118, 1.99884, 2.22681, 2.48199, 2.66951,
+ 0.132164, 0.314955, 0.821473, 1.19604, 1.42659, 1.69993, 2.03686, 2.3235, 2.68547, 2.82896,
+ 0.223374, 0.347335, 0.50773, 0.773547, 0.967916, 1.13413, 1.9914, 2.30657, 2.52136, 2.78875,
+ 0.312742, 0.449784, 0.583287, 0.934234, 1.26857, 1.36506, 1.5693, 1.68705, 2.0773, 2.59502,
+ 0.124286, 0.162126, 0.29073, 0.654031, 1.23166, 1.53846, 1.89307, 2.18478, 2.56264, 2.79822,
+ 0.177049, 0.251654, 0.367891, 0.912504, 1.55758, 1.69305, 1.89899, 2.07214, 2.35016, 2.64604,
+ 0.240517, 0.378333, 0.547809, 0.754272, 0.973321, 1.10367, 1.57442, 2.02805, 2.21113, 2.56271,
+ 0.427795, 0.519003, 0.771284, 0.93724, 1.08662, 1.60988, 1.87875, 2.05279, 2.53412, 2.65715,
+ 0.22437, 0.317969, 0.439666, 0.812931, 1.3985, 1.62663, 1.79418, 2.114, 2.30916, 2.49684
+};
+ /* codebook/lspjvm2.txt */
+static const float codes1[] = {
+ 0.005167, -0.03731, -0.002159, 0.016849, 0.130396,
+ 0.039445, 0.03168, -0.074412, -0.031499, 0.060536,
+ 0.019479, -0.030564, -0.048137, -0.056279, -0.027829,
+ 0.020585, -0.01127, 0.023913, -0.005706, 0.011407,
+ -0.023217, 0.107455, -0.037777, 0.00407, -0.017279,
+ -0.090444, 0.007641, 0.099001, -0.047913, -0.017199,
+ 0.0227, -0.063865, 0.047213, 0.043843, -0.036225,
+ 0.001312, -0.123861, -0.038988, 0.058666, 0.074541,
+ 0.039508, 0.1103, 0.013954, -0.119228, -0.035807,
+ -0.047392, 0.027035, -0.004412, -0.03265, -0.03715,
+ 0.002491, -0.045447, 0.15826, 0.022828, -0.030124,
+ -0.047856, 0.088744, -0.009678, 0.106688, 0.08769,
+ -0.027941, 0.044084, -0.0285, 0.018736, -0.069969,
+ -0.035358, -0.051568, -0.030459, -0.017899, 0.027632,
+ -0.018607, -0.123557, 0.019228, 0.057485, -0.028907,
+ 0.019057, 0.038151, -0.08022, 0.034222, 0.023081,
+ 0.021312, 0.041905, 0.112903, 0.024092, 0.093974,
+ -0.116679, 0.015344, -0.066059, -0.096437, 0.004041,
+ -0.022464, -0.11626, 0.047819, -0.003921, -0.073504,
+ 0.001975, -0.025869, 0.0282, 0.12269, 0.010627,
+ -0.035672, 0.078963, -0.009686, 0.000743, -0.147582,
+ 0.016932, -0.020291, -0.096896, -0.237875, -0.029121,
+ 0.017376, -0.04013, -0.053865, 0.15406, -0.013215,
+ 0.015215, -0.019023, -0.070604, 0.032265, 0.04034,
+ 0.102365, -0.022746, 0.019895, 0.05057, 0.008845,
+ -0.034134, 0.044441, -0.049387, -0.140481, 0.07257,
+ 0.013023, -0.006079, 0.037574, 0.004937, -0.081501,
+ 0.003696, 0.049908, 0.007355, 0.000403, 0.026006,
+ -0.008466, 0.08068, 0.061382, -0.108985, -0.08806,
+ -0.012275, -0.081061, 0.020333, -0.079001, 0.068724,
+ -0.014081, -0.042609, 0.093365, 0.04412, 0.000303,
+ 0.063391, 0.096574, -0.105424, 0.039041, 0.010412,
+ -0.054031, -0.084948, 0.080406, -0.035883, 0.137428,
+ 0.063037, 0.050562, 0.02469, -0.031394, 0.13032,
+ -0.015501, -0.078884, -0.076886, -0.013864, -0.073587,
+ 0.048778, 0.003814, -0.031125, 0.046897, 0.028304,
+ 0.048692, 0.132795, 0.06545, 0.059487, -0.042396,
+ -0.176999, 0.056943, -0.004135, -0.049378, -0.041083,
+ -0.039445, -0.016292, -0.00455, 0.06201, -0.079613,
+ -0.054566, -0.008476, -0.01671, 0.049202, 0.025758,
+ -0.078723, 0.092091, 0.096536, -0.065079, 0.021161,
+ 0.076657, 0.009203, -0.036866, -0.016559, 0.012823,
+ 0.008225, -0.003006, 0.108033, 0.04312, -0.06087,
+ -0.019346, 0.02279, -0.001728, 0.062304, -0.016965,
+ -0.001302, -0.01449, -0.041803, -0.034058, -0.197066,
+ -0.033655, -0.127217, -0.108681, -0.010571, -0.004705,
+ -0.015553, -0.086069, 0.034109, -0.101379, 0.002068,
+ -0.004003, -0.044637, -0.068617, 0.052228, -0.047812,
+ -0.043307, 0.035681, 0.042207, -0.055946, 0.055944,
+ -0.026792, -0.012601, -0.05671, -0.021094, 0.105842,
+ -0.025598, -0.078858, -0.013487, 0.030728, -0.031956,
+ 0.031444, 0.022763, 0.025364, 0.121366, 0.070736,
+ -0.084556, 0.098118, -0.024301, -0.058655, -0.043194,
+ -0.011752, -0.043781, 0.091051, -0.071201, -0.02098,
+ 0.082904, -0.031657, -0.088247, 0.066709, -0.079182,
+ -0.012151, 0.011796, -0.010589, 0.100656, 0.094539,
+ 0.035967, 0.025338, 0.071826, 0.009741, -0.040209,
+ 0.006866, -0.015095, -0.168469, -0.056133, 0.060145,
+ 0.04583, -0.068969, 0.034551, 0.015842, -0.092809,
+ 0.054699, 0.138744, 0.001726, 0.006927, 0.005167,
+ 0.016978, 0.046384, -0.060183, -0.040742, -0.072692,
+ -0.022489, -0.029728, -0.065018, -0.124741, 0.044927,
+ -0.029057, -0.037154, 0.031068, 0.060086, 0.009984,
+ 0.009311, -0.006957, -0.105508, 0.059637, -0.019564,
+ -0.068154, -0.066443, 0.000799, 0.028579, 0.097063,
+ 0.096936, 0.03023, -0.034623, -0.088918, 0.040334,
+ 0.019439, -0.050707, -0.003294, -0.028505, -0.053599,
+ 0.06246, -0.070688, -0.016465, -0.03568, 0.017378,
+ 0.009363, 0.048761, 0.043374, 0.039587, -0.023232,
+ -0.067033, 0.042663, 0.05407, -0.042797, -0.089391,
+ -0.030497, -0.050249, 0.059528, 0.089089, -0.029633,
+ 0.064125, -0.086614, -0.002005, 0.08062, 0.000502,
+ -0.00349, 0.097336, 0.099565, 0.015648, 0.006691,
+ 0.077668, 0.016572, 0.035404, -0.046026, 0.017237,
+ -0.048631, 0.009314, 0.141479, 0.017079, 0.043796,
+ -0.106474, 0.145951, 0.05774, 0.01125, -0.059443,
+ 0.027572, 0.02665, 0.008527, 0.002949, -0.03768,
+ -0.077991, -0.090617, 0.00342, -0.04601, 0.007354,
+ 0.019056, -0.128651, 0.016464, 0.004584, -0.030883,
+ -0.092069, 0.038976, -0.08184, 0.066695, -0.04734,
+ 0.003513, 0.040613, 0.046815, -0.023406, 0.062389,
+ 0.021759, 0.024928, -0.018922, -0.048006, 0.0638,
+ -0.014416, -0.050333, 0.042628, -0.114934, -0.10145,
+ 0.062139, 0.029295, -0.065908, 0.111463, 0.050781,
+ -0.022707, 0.135414, 0.003548, 0.134535, -0.048259,
+ -0.092344, -0.027727, 0.016343, -0.060786, -0.081502,
+ -0.005412, -0.026229, -0.143331, 0.052404, -0.077298,
+ -0.035919, -0.041968, -0.106108, -0.004369, 0.065028,
+ 0.09637, -0.053299, 0.043317, -0.049735, 0.049815,
+ 0.032324, 0.051309, -0.009607, -0.205917, 0.005023,
+ -0.054316, -0.022895, 0.099327, -0.006927, -0.076574,
+ -0.111024, 0.111026, 0.038381, -0.060368, 0.064238,
+ -0.034316, 0.026846, 0.02574, -0.076162, -0.163904,
+ 0.055955, -0.056885, 0.014831, -0.120715, 0.090938,
+ 0.035289, -0.036439, 0.060012, 0.080302, 0.036215,
+ 0.06525, 0.08303, -0.058784, 0.104826, -0.051805,
+ -0.011099, -0.00642, 0.053042, 0.024127, 0.092534,
+ 0.058569, -0.033442, 0.025186, -0.018222, 0.117744,
+ 0.044345, -0.042456, -0.043767, -0.021378, -0.121965,
+ 0.027371, 0.052731, -0.020316, 0.036912, 0.115357,
+ 0.03115, 0.041547, 0.059267, -0.039672, -0.086918,
+ -0.162369, 0.024801, 0.031725, 0.0834, -0.034463,
+ 0.000272, -0.008147, -0.002016, 0.131953, -0.092911,
+ -0.091944, -0.062864, -0.005221, 0.063647, -0.012658,
+ 0.042685, 0.067952, 0.038644, -0.153221, 0.096841,
+ 0.108299, 0.089446, -0.047164, 0.004196, -0.043268,
+ -0.035456, 0.050838, 0.070444, 0.084465, -0.07998,
+ -0.048916, 0.057726, 0.023894, 0.027653, 0.017775,
+ 0.015461, -0.030287, -0.022245, 0.052081, -0.150947,
+ -0.002682, -0.056774, -0.123366, -0.091754, 0.006536,
+ 0.006473, -0.143025, 0.05469, -0.043189, 0.03297,
+ 0.027446, 0.033127, -0.132722, -0.010417, -0.080097,
+ -0.018187, 0.001858, 0.11129, -0.090749, 0.059434,
+ -0.068738, 0.090679, -0.14507, -0.065277, 0.063514,
+ -0.003982, -0.056382, -0.003673, 0.015845, -0.073396,
+ 0.043688, 0.002836, 0.069211, 0.124852, -0.053313,
+ -0.040946, 0.07044, -0.107024, -0.019199, -0.033672,
+ -0.00144, 0.02168, 0.110595, -0.053452, -0.052426,
+ 0.035461, -0.028179, -0.049041, 0.02258, -0.010989,
+ -0.002913, -0.051691, -0.075881, 0.037241, 0.076377,
+ 0.034735, -0.031556, 0.073516, -0.001427, 0.016296,
+ -0.017537, 0.003346, -0.099774, -0.067624, -0.044257,
+ -0.018202, 0.030622, 0.012773, 0.046475, -0.121785,
+ -0.057265, 0.116179, -0.079916, 0.066396, 0.050104,
+ -0.013177, 0.057766, -0.047879, -0.109526, -0.146491,
+ 0.032675, -0.049318, -0.057045, -0.080068, 0.089621,
+ -0.046564, -0.029992, 0.040828, 0.029281, -0.037369,
+ -0.009731, -0.082145, -0.117622, 0.117077, 0.037369,
+ 0.00082, -0.106634, -0.007967, 0.000812, 0.140637,
+ 0.03653, 0.062121, -0.065504, -0.09493, 0.121336,
+ 0.01753, -0.01733, -0.040402, -0.018255, 0.010992,
+ 0.019746, -0.027564, 0.033588, 0.042466, -0.003143,
+ 0.013767, 0.084179, 0.033753, -0.017279, -0.009676,
+ -0.006452, 0.032645, 0.031852, -0.030975, -0.043384,
+ -0.005433, -0.015258, 0.053273, 0.054748, -0.064736,
+ 0.008959, -0.141223, -0.032957, -0.015079, 0.018198,
+ -0.001681, 0.143079, 0.076, 0.001037, -0.048744,
+ 0.022062, 0.02603, -0.008263, -0.050353, -0.023037,
+ -0.036477, -0.051733, 0.137823, -0.034438, -0.007573,
+ -0.004256, 0.064218, 0.075183, 0.095106, 0.026497,
+ 0.02636, 0.009791, -0.058039, 0.053315, -0.077817,
+ -0.033283, -0.081151, -0.05522, 0.004268, 0.017539,
+ -0.007329, -0.1172, 0.09322, 0.037359, 0.002718,
+ 0.010749, 0.018281, -0.0758, -0.024889, 0.00572,
+ 0.022129, 0.035613, 0.036187, 0.032246, 0.105439,
+ -0.073766, 0.016887, -0.059934, -0.049471, 0.07352,
+ -0.024041, -0.104642, 0.023557, -0.059746, -0.043871,
+ 0.022311, -0.00025, -0.074027, 0.198593, 0.102732,
+ 0.024478, 0.077658, -0.060042, -0.018229, -0.149648,
+ -0.009871, -0.105822, 0.007585, -0.161459, -0.041121,
+ -0.02146, 0.00902, -0.065018, 0.111801, -0.024953,
+ 0.074594, -0.026041, -0.062859, 0.009199, 0.069609,
+ 0.078672, -0.033414, 0.054128, 0.005408, -0.016273,
+ 0.052076, 0.10761, -0.067518, -0.0964, 0.033703,
+ -0.01435, -0.024676, 0.056254, -0.04377, -0.060847,
+ -0.004185, 0.07355, -0.05783, -0.016644, 0.029096,
+ 0.005755, 0.026472, 0.040449, -0.09195, -0.048538,
+ -0.034439, -0.107938, 0.090712, -0.117001, 0.04317,
+ -0.006505, -0.035277, 0.117316, 0.127002, 0.047906,
+ -0.001441, 0.118379, -0.132165, 0.00738, 0.023823,
+ -0.02012, -0.083725, 0.047284, 0.023795, 0.074123,
+ -0.013439, 0.024994, 0.060254, -0.06912, 0.166373,
+ -0.024228, -0.06315, -0.046506, -0.077202, -0.054592,
+ -0.006571, 0.010335, -0.006568, 0.003982, 0.075837,
+ 0.008643, 0.136339, -0.005502, 0.03391, -0.066379,
+ -0.127371, -0.006954, 0.03977, -0.070123, 0.060925,
+ -0.046386, -0.02642, -0.00528, 0.103509, -0.02231,
+ -0.00374, -0.014999, -0.03777, 0.080005, 0.025231,
+ -0.054995, 0.071017, 0.009442, -0.075737, 0.013441,
+ 0.051947, 0.027097, -0.070351, -0.055705, -0.021115,
+ 0.021387, 0.029232, 0.163331, -0.03238, 0.010008,
+ -0.011987, -0.028631, 0.002665, 0.01477, -0.009558,
+ -0.034325, 0.01583, -0.091253, -0.012677, -0.107378,
+ -0.034624, -0.047725, -0.10233, 0.042525, -0.006869,
+ 0.014048, -0.043127, 0.052384, -0.047473, 0.055102,
+ 0.009744, -0.033646, -0.081755, -0.001464, -0.016223,
+ -0.036697, -0.002279, 0.023279, -0.036221, 0.101478,
+ -0.058454, 0.065074, 0.003524, 0.00501, 0.097182,
+ -0.038171, -0.037943, -0.009994, -0.033355, -0.044552,
+ 0.041318, 0.065041, 9.2e-05, 0.100816, 0.029007,
+ -0.031803, 0.183537, -0.009617, -0.010544, -0.028465,
+ 0.0069, -0.014988, 0.09049, -0.174817, 0.027464,
+ 0.063314, -0.049281, -0.001567, 0.091421, -0.078603,
+ -0.004869, -0.063266, -0.001922, 0.069338, 0.081771,
+ 0.058737, 0.073195, 0.081676, -0.047808, -0.025797,
+ -0.004185, 0.033203, -0.125472, -0.108148, 0.031258,
+ 0.035192, 0.029957, 0.046675, 0.047238, -0.088197,
+ 0.033315, 0.114919, -0.04918, 0.025707, 0.053843,
+ 0.035182, 0.140206, -0.05866, -0.025978, -0.019658,
+ -0.014847, -0.021051, -0.034385, -0.121789, 0.173406,
+ -0.112251, -0.022333, 0.071206, 0.028998, 0.046468,
+ 0.067704, -0.026159, -0.158316, 0.014936, 0.040216,
+ -0.010137, -0.053492, 0.004935, -0.011277, 0.073852,
+ 0.091261, 0.114794, -0.01406, -0.051545, 0.077316,
+ 0.101258, -0.046137, 0.022994, -0.066767, -0.065537,
+ 0.049952, -0.043582, 0.012823, 0.009313, 0.036343,
+ 0.054885, 0.037796, 0.02194, 0.013211, 0.006019,
+ -0.099578, 0.058596, -0.045463, -0.015632, -0.087141,
+ -0.019273, -0.03314, 0.043796, 0.119057, -0.081813,
+ -0.021538, -0.070453, -0.052551, 0.077213, 9.4e-05,
+ 0.050268, 0.092271, 0.051688, -0.025224, 0.075437,
+ 0.027983, 0.069205, 0.031787, -0.099975, 0.004387,
+ -0.002747, -0.056567, 0.161394, 0.000164, 0.084189,
+ -0.124844, 0.050329, 0.009844, 0.055877, 0.055701,
+ 0.030479, 0.028843, -0.001076, -0.017173, -0.10277,
+ -0.038426, -0.133841, -0.03584, -0.072046, 0.020206,
+ 0.016438, -0.097885, 0.041857, 0.034601, 0.030422,
+ -0.089192, -0.014112, -0.052276, 0.012005, -0.029335,
+ -0.011331, 0.101833, 0.063827, 0.044288, 0.101597,
+ -0.034689, -0.027434, -0.017801, -0.079224, 0.067103,
+ -0.027456, -0.098034, 0.009448, -0.038986, -0.156729,
+ 0.085023, 0.033136, -0.021343, 0.110701, -0.011901,
+ -0.006484, 0.082023, -0.027094, 0.091208, -0.013163,
+ -0.012223, 0.005933, 0.010653, -0.098119, -0.005304,
+ -0.021061, -0.058077, -0.073035, 0.097856, -0.102847,
+ -0.035329, -0.092754, -0.101463, -0.048671, 0.055015,
+ 0.102145, 0.062017, 0.016002, 0.036489, 0.059,
+ 0.042861, 0.025447, -0.019735, -0.107841, -0.033752,
+ -0.043982, -0.067059, 0.051092, 0.025235, -0.147107,
+ -0.016269, 0.123009, 0.035894, -0.020453, 0.040013,
+ 0.015557, 0.015825, 0.080712, -0.06963, -0.149739,
+ 0.022006, -0.008848, 0.040169, -0.095688, 0.059575,
+ -0.030641, -0.061353, 0.046302, 0.104489, 0.043372,
+ -0.001579, 0.059737, -0.104073, 0.042342, -0.048611,
+ -0.013811, -0.056255, 0.107179, 0.057433, 0.084815,
+ 0.030217, 0.02236, -0.040342, -0.028775, 0.120588,
+ 0.04127, -0.045775, -0.030195, -0.106859, -0.104349,
+ 0.072418, -0.003603, -0.013072, 0.040728, 0.086869,
+ 0.091943, 0.066517, 0.024442, -0.030929, -0.03292,
+ -0.160336, -0.010347, -0.068458, 0.017458, 0.044823,
+ 0.050694, 0.067625, 0.040303, 0.113164, -0.038747,
+ -0.065558, -0.106357, -0.028352, 0.121488, 0.026548,
+ -0.00782, 0.054872, 0.094674, -0.099533, 0.005231,
+ 0.118132, 0.04278, -0.065079, 0.03144, 0.043229,
+ -0.050024, 0.015943, 0.073917, 0.034049, 0.010548,
+ -0.024979, 0.022639, 0.027795, 0.049491, 0.048762,
+ -0.002738, -0.010783, -0.027637, -0.006986, -0.104141,
+ -0.066719, -0.061742, -0.067028, -0.053057, -0.003478,
+ -0.050948, -0.122196, 0.022082, 0.002595, 0.015094,
+ 0.006014, 0.005784, -0.184537, -0.034872, -0.036104,
+ 0.055412, 0.006886, 0.103488, -0.063001, 0.096665,
+ -0.035533, 0.009847, -0.095114, 0.008588, 0.023736,
+ -0.034278, -0.11197, -0.041172, 0.03973, -0.102952,
+ 0.063775, 0.039273, 0.109863, 0.0918, 0.030306,
+ -0.082206, 0.089449, -0.058478, -0.029341, 0.038389,
+ 0.061057, -0.024711, 0.111044, -0.035079, -0.027985,
+ 0.01457, 0.002046, -0.031545, 0.058848, -0.0195,
+ -0.002475, -0.025589, -0.144358, 0.063478, 0.124927,
+ -0.014094, -0.01097, 0.031621, -0.040043, 0.004389,
+ 0.025003, 0.052397, -0.054526, -0.073469, 0.026795,
+ -0.024697, 0.024739, 0.118299, 0.014948, -0.132109,
+ 0.020192, 0.037815, -0.09027, 0.049313, 0.082764,
+ -0.022642, -0.006053, -0.038073, -0.057363, -0.107347,
+ 0.033166, -0.027556, -0.019765, -0.111958, 0.027773,
+ -0.063001, -0.052998, 0.019353, -0.009646, -0.01127,
+ 0.011872, -0.006508, -0.122226, 0.059824, 0.041779,
+ 0.016445, -0.03189, -0.03631, 0.013085, 0.091631,
+ 0.062866, 0.054501, -0.117523, -0.010907, 0.087026,
+ -0.014974, -0.03592, -0.048565, -0.019246, -0.043405,
+ -0.006959, 0.006211, 0.04237, 0.014603, -0.006435,
+ 0.019149, 0.078038, -0.020556, 0.018114, -0.036521,
+ -0.054036, 0.007325, 0.056349, -0.033497, -0.02596,
+ 0.050184, -0.066536, 0.091501, 0.071356, -0.049044,
+ -0.032263, -0.095268, -0.008784, 0.049033, 0.036929,
+ 0.020357, 0.152151, 0.040814, -0.063159, -0.024324,
+ -0.017084, 0.011876, -0.015442, -0.019811, -0.000366,
+ -0.0027, -0.072981, 0.109288, 0.007473, -0.049442,
+ -0.05404, 0.051947, 0.019359, 0.12916, 0.021981,
+ 0.002248, 0.035262, -0.023141, 0.064666, -0.078273,
+ -0.031663, -0.031343, -0.006058, -0.045421, 0.017466,
+ -0.067122, -0.130784, 0.067057, 0.05246, -0.041165,
+ -0.004411, 0.046453, -0.055461, 0.048162, -0.009687,
+ 0.02153, 0.007211, 0.104764, 0.079849, 0.086248,
+ -0.072791, 0.001112, -0.027964, -0.071233, -0.013339,
+ 0.007979, -0.118231, 0.076826, -0.060762, -0.084358,
+ -0.011447, 0.009765, 0.014163, 0.164784, -0.015892,
+ -0.020756, 0.152509, -0.014014, -0.041853, -0.117008,
+ -0.011755, -0.005766, -0.086896, -0.13965, -0.032342,
+ 0.025651, -0.007843, -0.039073, 0.103397, -0.042591,
+ -0.005971, -0.001324, -0.053945, -0.000716, 0.048977,
+ 0.130185, 0.028226, 0.061179, 0.024489, -0.021939,
+ -0.007019, 0.054336, -0.01004, -0.095411, 0.082406,
+ -0.03213, -0.015054, 0.033059, 0.002802, -0.080159,
+ -0.022452, 0.077426, -0.015314, 0.033583, 0.028479,
+ 0.023293, 0.035078, 0.006442, -0.110541, -0.106244,
+ -0.034737, -0.10414, -0.03457, -0.114316, 0.079382,
+ 0.006009, 0.003901, 0.080081, 0.055082, 0.012896,
+ 0.064981, 0.057219, -0.112986, 0.003906, -0.028414,
+ -0.012383, -0.054541, 0.077483, 0.004267, 0.123567,
+ 0.007369, 0.099856, 0.023273, -0.028194, 0.12203,
+ -0.036635, -0.126589, -0.034567, -0.028288, -0.06504,
+ 0.01428, 0.011435, -0.004867, 0.043901, 0.035395,
+ 0.028599, 0.075858, 0.11846, 0.070581, -0.051903,
+ -0.170905, 0.050352, 0.053514, -0.017139, 0.021748,
+ -0.09661, 0.008904, -0.001049, 0.078787, -0.101201,
+ -0.026229, -0.019757, -0.035771, 0.054142, 0.068041,
+ -0.020328, 0.099979, 0.096623, -0.046957, -0.001733,
+ 0.049586, 0.052458, -0.031724, -0.028332, -0.005418,
+ 0.04671, 0.014238, 0.133125, -0.005428, -0.080055,
+ -0.033226, 0.034007, 0.025272, 0.033924, -0.044662,
+ -0.03469, -0.079173, -0.160689, -0.153893, -0.228771,
+ -0.00245, -0.083966, -0.168294, 0.010694, -0.012167,
+ 4e-06, -0.044377, 0.023373, -0.077437, 0.012178,
+ -0.015899, -0.010828, -0.062847, 0.029927, -0.074557,
+ -0.053306, 0.049688, 0.057017, -0.022571, 0.015337,
+ -0.046545, 0.018895, -0.024848, -0.004424, 0.165442,
+ -0.060201, -0.098629, -0.06519, 0.036582, -0.038566,
+ 0.051453, 0.093478, 0.039619, 0.117535, 0.090386,
+ -0.029366, 0.108075, -0.016568, -0.093576, -0.048799,
+ -0.045599, -0.023619, 0.070072, -0.109294, 0.001548,
+ 0.076285, -0.091274, -0.068829, 0.000215, -0.046519,
+ -0.022512, -0.027067, 0.014905, 0.079017, 0.140699,
+ 0.061141, 0.009178, 0.097811, 0.033468, -0.006666,
+ 0.007163, -0.007578, -0.124238, -0.025271, 0.017581,
+ 0.042405, -0.034252, 0.06489, 0.0025, -0.139083,
+ 0.009733, 0.158179, 0.014474, 0.038913, 0.05629,
+ -0.004998, 0.075401, -0.030557, -0.038595, -0.04907,
+ -0.01468, -0.076306, -0.132365, -0.177693, 0.09176,
+ -0.057238, -0.072379, 0.050877, 0.051489, 0.028125,
+ 0.004991, 0.032621, -0.167359, 0.041002, -0.007072,
+ -0.086405, -0.042263, -0.019757, -0.011524, 0.066004,
+ 0.08567, 0.008071, -0.013614, -0.062142, 0.08328,
+ 0.000887, -0.07582, 0.008295, -0.020136, -0.016886,
+ 0.089657, -0.10626, -0.051491, -0.012687, 0.054778,
+ 0.011535, 0.086613, 0.053803, 0.027164, -0.023825,
+ -0.040009, 0.080987, 0.026309, -0.000334, -0.085288,
+ -0.024208, -0.08504, 0.096077, 0.120527, -0.044181,
+ 0.003034, -0.091142, 0.006471, 0.115971, -0.026358,
+ 0.003489, 0.083633, 0.109975, -0.029425, 0.061726,
+ 0.056115, -0.006711, 0.013158, -0.062917, -0.015029,
+ 0.003354, 0.031574, 0.119045, 0.022859, 0.023777,
+ -0.068292, 0.115604, 0.031617, 0.008953, 0.006943,
+ 0.01442, 0.008569, -0.031547, -0.006857, -0.05169,
+ -0.086683, -0.108339, 0.005093, -0.108646, -0.03472,
+ 0.054273, -0.096753, 0.050806, -0.021115, -0.025278,
+ -0.079997, 0.027008, -0.034211, 0.090949, 0.005678,
+ 0.019288, 0.042083, 0.062119, 0.019301, 0.040859,
+ -0.009113, 0.022427, -0.004019, -0.06089, 0.032884,
+ -0.012373, -0.037976, 0.017625, -0.079369, -0.050788,
+ 0.07972, -0.039347, -0.085324, 0.091044, 0.026653,
+ -0.063122, 0.099371, -0.024736, 0.084631, -0.100421,
+ -0.073313, 0.014317, 0.022555, -0.116051, -0.063966,
+ -0.009688, -0.063666, -0.131709, 0.016744, -0.135028,
+ -0.003708, -0.043685, -0.121631, -0.03693, 0.125776,
+ 0.084333, 0.010114, 0.071231, -0.010395, 0.059391,
+ 0.01776, 0.033034, -0.018996, -0.13054, 0.025758,
+ -0.018261, -0.060044, 0.127025, -0.032724, -0.107299,
+ -0.064538, 0.090073, -0.010186, -0.066127, 0.107025,
+ -0.01094, 0.003083, 0.01903, -0.023935, -0.140176,
+ 0.003549, -0.042402, -0.010695, -0.185915, 0.060835,
+ 0.005405, -0.013822, 0.029205, 0.079338, 0.068155,
+ 0.071485, 0.030282, -0.087207, 0.07348, -0.02794,
+ 0.004896, -0.033246, 0.072637, 0.018017, 0.054712,
+ 0.026184, -0.005287, 0.034456, -0.036753, 0.079232,
+ 0.072707, 0.004506, -0.039353, -0.01556, -0.071466,
+ 0.010257, 0.067446, -0.006598, 0.047396, 0.072218,
+ 0.023405, 0.082663, 0.015319, -0.035436, -0.075461,
+ -0.124036, -0.032046, 0.060837, 0.010231, -0.053024,
+ 0.0228, 0.042891, -0.041549, 0.132395, -0.09533,
+ -0.077091, -0.058554, -0.070632, 0.04757, 0.031856,
+ 0.000127, 0.114996, 0.05866, -0.092472, 0.064503,
+ 0.09645, 0.0662, -0.001059, 0.039487, -0.032859,
+ -0.065721, 0.001601, 0.088037, 0.059828, -0.047411,
+ -0.077714, 0.010275, 0.013629, 0.003304, 0.005407,
+ 0.000665, 0.012927, -0.077525, 0.069202, -0.157417,
+ 0.014547, -0.095965, -0.087546, -0.067375, -0.027867,
+ 0.005458, -0.095839, 0.105294, -0.044892, 0.045151,
+ -0.001349, 0.038356, -0.127152, -0.080503, -0.105423,
+ -0.018484, 0.008439, 0.104398, -0.027959, 0.082086,
+ -0.020605, 0.042785, -0.109139, -0.025958, 0.079733,
+ 0.036289, -0.083773, -0.033819, 0.032566, -0.065556,
+ 0.006659, 0.00209, 0.097027, 0.115715, -0.013271,
+ -0.067514, 0.128365, -0.089129, 0.02616, -0.040584,
+ -0.002443, -0.017254, 0.129204, -0.110078, -0.064943,
+ 0.089215, -0.022299, -0.034959, 0.022446, -0.019254,
+ -0.0389, -0.069862, -0.07054, 0.069949, 0.111993,
+ -0.006311, -0.009057, 0.094278, -0.014932, 0.003657,
+ -0.019323, 0.026145, -0.062611, -0.073753, -0.007182,
+ 0.014101, 0.015776, 0.052537, 0.064728, -0.160187,
+ -0.005122, 0.076356, -0.104763, 0.091493, 0.020225,
+ -0.000433, 0.062698, -0.060457, -0.14754, -0.066168,
+ 0.007195, -0.061498, -0.037801, -0.039763, 0.059551,
+ -0.02841, -0.07451, 0.057667, 0.020584, -0.04251,
+ -0.025311, -0.037825, -0.18801, 0.077423, 0.030749,
+ -0.025465, -0.067541, 0.003073, -0.049778, 0.127789,
+ 0.002786, 0.120009, -0.067812, -0.026565, 0.111272,
+ 0.023219, -0.024403, -0.014507, -0.048624, 0.022163,
+ 0.014596, -0.052136, 0.00158, 0.064595, 0.017963,
+ 0.02133, 0.098862, -0.009253, -0.041062, 0.008903,
+ -0.013829, 0.031967, 0.076571, -0.005348, -0.04401,
+ 0.031252, 0.000369, 0.036818, 0.072854, -0.038569,
+ 0.004161, -0.128017, -0.053152, 0.050896, -0.015212,
+ -0.036159, 0.097995, 0.068397, -0.048472, -0.056131,
+ -0.01192, 0.059188, 0.010215, -0.061152, -0.011717,
+ -0.035949, -0.057039, 0.090859, -0.029682, 0.041466,
+ -0.025106, 0.131191, 0.059327, 0.085383, 0.021699,
+ 0.04923, 0.03663, -0.077086, 0.017806, -0.08879,
+ 0.00404, -0.069533, -0.026785, 0.009666, 0.014017,
+ -0.055897, -0.096299, 0.120693, 0.029995, 0.032602,
+ -0.001365, 0.034015, -0.053512, 0.001573, -0.01917,
+ 0.003956, 0.006452, 0.067313, 0.028301, 0.160615,
+ -0.053111, 0.01399, -0.02706, -0.013638, 0.039376,
+ -0.054462, -0.096553, 0.079994, -0.043791, -0.025051,
+ -0.003222, 0.019418, -0.049525, 0.151136, 0.034123,
+ 0.055117, 0.058918, -0.017393, 0.026169, -0.12638,
+ -0.019008, -0.028939, -0.014027, -0.173373, -0.032841,
+ -0.00337, 0.03968, -0.118311, 0.114094, -0.041869,
+ 0.041121, -0.038391, -0.096074, -0.032479, 0.060222,
+ 0.063968, -0.024528, 0.018158, -0.009892, -0.043882,
+ -0.005004, 0.1298, -0.025438, -0.121186, 0.04986,
+ 0.010448, -0.040388, 0.061853, -0.017304, -0.035088,
+ -0.008678, 0.061476, -0.039493, -0.005055, 0.079169,
+ 0.046134, 0.00977, 0.068294, -0.078965, -0.043792,
+ -0.030529, -0.053845, 0.053853, -0.140682, 0.111461,
+ 0.003549, -0.014939, 0.148955, 0.072861, 0.004332,
+ 0.015386, 0.062006, -0.122325, -0.032529, 0.010241,
+ -0.047982, -0.12644, 0.05584, 0.067128, 0.101189,
+ -0.00263, 0.031969, 0.046076, -0.080194, 0.10474,
+ -0.033486, -0.077818, -0.058697, -0.095258, -0.111074,
+ 0.037236, 0.011711, 0.001113, -0.005664, 0.048588,
+ 0.041131, 0.098257, 0.033126, 0.029317, -0.095311,
+ -0.071555, -0.039999, 0.026678, -0.072182, 0.035031,
+ -0.007997, -0.048174, -0.006796, 0.075959, -0.05206,
+ -0.007645, 0.037076, -0.035574, 0.085576, 0.034126,
+ -0.050676, 0.05143, 0.031999, -0.134308, -0.001489,
+ 0.084564, -0.018394, -0.09741, -0.042931, -0.025608,
+ -0.025489, 0.041919, 0.142482, 0.004617, -0.041085,
+ -0.028816, -0.015527, -0.031005, 0.028405, -0.02224,
+ -0.067737, -0.025241, -0.052578, 0.012322, -0.120556,
+ 0.016278, -0.081744, -0.09916, 0.025144, 0.025441,
+ 0.003176, -0.073871, 0.031718, -0.028622, 0.029031,
+ 0.01791, -0.030693, -0.104215, -0.015422, -0.065738,
+ -0.048346, -0.012847, 0.046849, -0.008621, 0.058771,
+ -0.054495, 0.031597, -0.038844, 0.043138, 0.092588,
+ -0.071371, -0.059093, -0.001197, 0.001766, -0.074762,
+ 0.02947, 0.089616, 0.005009, 0.052977, 0.015899,
+ -0.045424, 0.158466, -0.038717, -0.032506, 0.028687,
+ 0.011435, -0.006772, 0.047605, -0.144659, -0.031229,
+ 0.073577, 0.01153, -0.008172, 0.058883, -0.088412,
+ 0.033615, -0.03412, -0.030701, 0.101215, 0.096645,
+ 0.027368, 0.041249, 0.081502, -0.02544, 0.007592,
+ 0.059893, 0.012106, -0.112009, -0.114692, 0.016397,
+ 0.087068, 0.016199, 0.051263, 0.011915, -0.085364,
+ 0.026046, 0.145258, -0.047521, 0.077134, -0.000345,
+ 0.034532, 0.099801, -0.087591, -0.059719, -0.058671,
+ 0.022737, -0.001887, -0.107049, -0.116757, 0.134115,
+ -0.055403, 0.005157, 0.067618, 0.081074, 0.071787,
+ 0.063802, -0.00343, -0.106491, 0.017543, 0.002214,
+ -0.013785, -0.032962, 0.010084, 0.024325, 0.045963,
+ 0.059883, 0.072282, -0.008608, -0.015127, 0.048225,
+ 0.041752, -0.068845, 0.012227, -0.090748, -0.035309,
+ 0.045353, -0.078624, -0.019489, 0.035531, 0.058571,
+ 0.045414, 0.039032, -0.011106, 0.048787, -0.025336,
+ -0.084893, 0.031896, 0.01085, 0.012526, -0.053205,
+ 0.016952, -0.044041, 0.068766, 0.097328, -0.122229,
+ 0.027016, -0.051759, -0.057246, 0.074566, 0.006201,
+ 0.069904, 0.100068, 0.076124, 0.004278, 0.029466,
+ 0.045229, 0.055683, 0.01879, -0.067806, 0.039373,
+ 0.029179, -0.036787, 0.129921, -0.028993, 0.037711,
+ -0.105011, 0.138747, -0.00437, 0.05208, 0.050835,
+ 0.025511, -0.002962, 0.007852, -0.055234, -0.075055,
+ 0.00046, -0.089231, -0.030467, -0.080347, 0.007488,
+ 0.06746, -0.076368, 0.084991, 0.039544, 0.033391,
+ -0.044318, 0.00639, -0.079387, -0.002909, -0.029708,
+ -0.047882, 0.06304, 0.065719, 0.021811, 0.070945,
+ -0.007571, -0.001302, -0.064119, -0.068005, 0.05104,
+ -0.017747, -0.063938, 0.018673, -0.038391, -0.099966,
+ 0.057475, -0.007669, 0.009384, 0.109283, 0.012248,
+ -0.048858, 0.092498, 0.011967, 0.061525, -0.028819,
+ -0.015131, -0.02416, -0.03322, -0.101648, -0.01798,
+ -0.003342, -0.049829, -0.125096, 0.128241, -0.047377,
+ -0.028943, -0.109072, -0.066133, -0.015454, 0.098334,
+ 0.053371, 0.011324, 0.042781, 0.044313, 0.06251,
+ 0.098408, 0.06541, -0.040693, -0.116351, -0.032327,
+ -0.013634, -0.058591, 0.081507, 0.042019, -0.09977,
+ -0.018275, 0.084624, -0.007512, -0.041113, 0.054203,
+ 0.017879, -0.029747, 0.059865, -0.048281, -0.111513,
+ -0.022478, 0.002059, 0.022383, -0.12536, 0.058216,
+ 0.002386, -0.0816, 0.049288, 0.157428, 0.057724,
+ 0.005046, 0.102125, -0.083473, 0.044059, -0.094864,
+ 0.03912, -0.063306, 0.057341, 0.060519, 0.107383,
+ 0.007076, -0.009373, -0.012555, -0.06663, 0.117121,
+ 0.025254, -0.008796, -0.062102, -0.083164, -0.079007,
+ 0.084839, 0.042308, -0.055353, 0.036386, 0.132641,
+ 0.084464, 0.056288, -0.011636, -0.059554, -0.087748,
+ -0.147377, -0.052414, -0.010203, -0.009159, -0.018829,
+ 0.009621, 0.061633, 0.015716, 0.086332, -0.061465,
+ -0.011833, -0.062998, -0.021168, 0.125194, 0.045025,
+ 0.052316, 0.02572, 0.095155, -0.093252, 0.02872,
+ 0.056113, 0.063321, -0.045315, 0.025199, 0.023591,
+ -0.070481, 0.07235, 0.092458, 0.047973, -0.025439,
+ -0.001281, 0.021028, 0.034576, 0.084779, 0.006867,
+ -0.010323, -0.04633, -0.009172, 0.030485, -0.117679,
+ -0.021782, -0.034737, -0.086292, -0.045885, 0.009655,
+ -0.037167, -0.123331, 0.017291, -0.028319, 0.071447,
+ -0.05718, -0.032912, -0.139418, -0.025966, -0.039305,
+ 0.009411, -0.054017, 0.076307, -0.060252, 0.110087,
+ -0.061366, 0.038897, -0.098107, 0.046119, 0.043021,
+ -0.02913, -0.096885, 0.007623, 0.090513, -0.097416,
+ 0.053264, 0.058296, 0.054372, 0.060769, 0.015586,
+ -0.067956, 0.059996, -0.03785, 0.005986, 0.000778,
+ 0.045873, -0.065546, 0.0779, -0.085638, 0.000698,
+ 0.027694, -0.021241, -0.002777, 0.034509, -0.048173,
+ 0.009988, 0.001008, -0.077434, 0.026002, 0.13949,
+ 0.00891, 0.007791, 0.059292, -0.057047, 0.014127,
+ -0.022959, 0.08571, -0.068087, -0.081561, 0.005935,
+ 0.007577, 0.061544, 0.076542, 0.00166, -0.113279,
+ 0.024973, 0.08675, -0.061674, 0.095059, 0.089352,
+ -0.024436, 0.024181, -0.016117, -0.073634, -0.067986,
+ 0.074701, -0.046868, -0.054634, -0.092485, 0.006662,
+ -0.033256, -0.053774, 0.049001, -0.002339, 0.013545,
+ -0.006432, -0.012089, -0.086842, 0.104105, 0.061991
+};
+ /* codebook/lspjvm3.txt */
+static const float codes2[] = {
+ 0.007066, 0.075781, -0.070082, -0.092014, -0.066477,
+ 0.09051, 0.106622, 0.025911, -0.01676, 0.003724,
+ -0.024628, 0.058332, 0.012876, 0.059557, -0.002092,
+ -0.065092, -0.096975, -0.041837, -0.002432, 0.058918,
+ 0.014358, 0.080049, -0.008803, -0.002091, -0.097584,
+ 0.085323, -0.026053, -0.086585, -0.009541, 0.130555,
+ 0.045391, 0.037557, 0.074726, -0.050453, 0.033517,
+ -0.035576, -0.084211, -0.08643, 0.00891, -0.072674,
+ -0.098699, -0.02454, -0.048972, -0.066975, -0.048791,
+ 0.032184, 0.070992, -0.014416, 0.141892, -0.044249,
+ -0.108921, -0.02045, 0.115988, 0.011287, -0.026273,
+ 0.024341, 0.138519, -0.036467, 0.020684, 0.074258,
+ -0.053563, 0.077463, 0.072166, 0.032112, -0.079303,
+ -0.025039, 0.079675, 0.094211, -0.115754, 0.038892,
+ 0.050897, -0.024639, 0.057826, -0.110429, 0.071184,
+ 0.015309, -0.034027, -0.055726, 0.043179, -0.063089,
+ 0.043359, -0.011698, 0.006637, 0.002751, 0.03011,
+ -0.001261, 0.11147, 0.043277, -0.004205, -0.021599,
+ -0.005698, 0.058842, 0.168422, 0.059313, -0.007971,
+ -0.087599, 0.073891, -0.083238, 0.099279, -0.017364,
+ -0.018429, 0.01404, -0.014864, -0.111512, 0.08945,
+ -0.028498, -0.087983, -0.07732, -0.062602, 0.000328,
+ -0.027152, -0.093796, 0.111381, -0.018603, 0.092394,
+ -0.007256, 0.025391, 0.011454, 0.012802, -0.04168,
+ 0.008078, 0.020905, -0.105401, -0.083265, 0.027756,
+ -0.04963, -0.044085, -0.051424, 0.104125, -0.000779,
+ -0.063079, -0.130699, 0.0705, 0.033468, -0.019802,
+ -0.061011, 0.094839, -0.040122, 0.118409, 0.05695,
+ 0.086391, -0.006615, 0.045337, -0.04419, -0.106474,
+ -0.081912, 0.067557, -0.031649, -0.014437, 0.057585,
+ -0.121755, -0.049113, 0.057109, -0.049872, 0.044104,
+ 0.064705, -0.091589, 0.037286, -0.048606, -0.045398,
+ 0.003456, 0.05723, 0.006262, -0.055206, -0.063871,
+ -0.005249, 0.081783, 0.134969, -0.002331, 0.052643,
+ -0.093346, 0.072093, 0.116025, -0.031453, -0.006012,
+ -0.038574, -0.030841, 0.010288, 0.02442, 0.051657,
+ -0.086584, 0.046381, 0.00541, 0.052622, -0.072741,
+ 0.079023, 0.078099, -0.093912, 0.005477, -0.006721,
+ 0.100232, -0.017587, 0.044819, 0.036655, 0.02158,
+ -0.006829, -0.050076, -0.00302, 0.088246, 0.01356,
+ -0.01569, 0.012477, -0.052595, -0.048861, -0.033688,
+ 0.055615, 0.092298, -0.066194, 0.016416, -0.066059,
+ 0.046976, 0.003023, 0.104646, 0.109136, 0.018293,
+ -0.016507, -0.006859, 0.004326, 0.070843, 0.14075,
+ 0.025774, 0.03473, -0.07959, 0.050054, -0.10795,
+ 0.002378, 0.097498, 0.027111, -0.122953, -0.002423,
+ -0.020539, -0.063263, -0.095493, -0.157361, -0.039183,
+ 0.025721, 0.026897, -0.0012, 0.033997, -0.001749,
+ 0.061593, -0.013053, -0.106317, -0.06819, 0.046352,
+ -0.05606, 0.157084, -0.049365, 0.053959, -0.051065,
+ -0.047672, 0.08157, 0.064342, -0.030705, -0.070806,
+ -0.076503, -0.059471, 0.012419, 0.073968, -0.026179,
+ -0.038473, 0.059013, -0.035783, -0.030057, -0.036346,
+ -0.052692, -0.015346, -0.022687, -0.035279, 0.013314,
+ 0.068397, -0.046609, -0.009593, -0.040796, 0.157438,
+ -0.07536, -0.110464, 0.031839, -0.029035, -0.015222,
+ 0.041013, -0.099212, -0.10892, -0.008627, 0.012095,
+ 0.020855, 0.009935, -0.086917, 0.058827, -0.006536,
+ 0.022104, -0.005013, 0.003496, 0.046663, -0.051061,
+ -0.036803, -0.067317, -0.007075, 0.18087, -0.027434,
+ -0.025056, -0.039341, -0.073918, -0.00318, -0.11093,
+ -0.042711, 0.005519, -0.035005, -0.088419, 0.170942,
+ 0.001503, -0.121485, 0.066383, -0.067346, 0.005643,
+ 0.080088, -0.042562, -0.006668, -0.036538, 0.020683,
+ 0.042848, 0.027852, -0.029088, -0.156468, 0.006503,
+ 0.037716, 0.032082, 0.038416, 0.021835, -0.106963,
+ -0.043017, 0.018166, 0.070409, -0.005426, -0.035585,
+ -0.111071, -0.039986, 0.05043, 0.035157, 0.066902,
+ -0.040684, 0.060527, 0.036225, 0.002527, -0.015087,
+ 0.059243, 0.021268, -0.010682, -0.018434, 0.059128,
+ 0.111314, -0.05407, 0.105744, -0.051476, -0.01297,
+ -0.000358, -0.099249, -0.077385, 0.069924, -0.039101,
+ -0.072139, -0.049069, -0.088018, 0.006144, 0.000712,
+ 0.08103, 0.021987, -0.046031, 0.058087, -0.00132,
+ -0.046851, -0.011062, 0.108321, -0.001146, -0.071193,
+ 0.044973, -0.002915, -0.003323, 0.041735, 0.094566,
+ 0.05353, 0.035927, 0.100282, 0.059082, -0.054059,
+ -0.012158, -0.035417, 0.020412, -0.073193, 0.059296,
+ -0.040489, -0.09525, -0.003821, -0.084904, 0.053925,
+ 0.109183, -0.005862, -0.036538, 0.080962, -0.040647,
+ 0.02007, 0.057778, -0.020197, -0.079626, -0.003186,
+ -0.050855, 0.128185, 0.034731, 0.05746, -0.035236,
+ -0.057096, -0.001238, 0.122018, -0.071204, -0.047253,
+ -0.051767, 0.048301, -0.052678, 0.02599, -0.017481,
+ -0.029379, 0.030738, 0.047207, -0.047864, -0.033561,
+ 0.029884, -0.091175, -0.085446, -0.02614, 0.092628,
+ 0.067706, -0.085617, 0.081433, 0.047305, 0.031945,
+ -0.048728, -0.040387, 0.046206, 0.010578, -0.037639,
+ 0.011328, -0.042458, -0.149597, 0.033882, -0.061869,
+ 0.0088, 0.057754, -0.095876, 0.03823, 0.096876,
+ -0.033487, -0.141669, -0.014172, 0.028439, -0.092764,
+ -0.053714, 0.086926, 0.034786, 0.136053, -0.005569,
+ 0.028753, 0.00963, 0.044114, -0.050365, -0.066224,
+ 0.006017, 0.014348, 0.024471, 0.000489, 0.067234,
+ -0.021678, -0.11876, 0.036349, -0.040295, 0.076358,
+ -0.008444, -0.086082, -0.044018, -0.025804, 0.028971,
+ -0.009233, 0.053026, -0.035341, -0.182193, -0.102515,
+ 0.08921, 0.066812, 0.032417, 0.046882, -0.034815,
+ -0.052293, 0.022814, 0.129622, 0.128232, -0.012105,
+ -0.087084, 0.004762, 0.086538, 0.046566, 0.098359,
+ -0.018713, 0.039204, -0.021707, -0.06011, -0.117527,
+ -0.005459, 0.060994, -0.057718, -0.021783, 0.035154,
+ 0.100557, -0.01547, -0.025818, 0.00845, 0.051535,
+ -0.001388, -0.11461, -0.057903, 0.041862, 0.061778,
+ 0.045701, -0.078563, -0.070166, -0.04845, -0.08853,
+ 0.021375, -0.004598, -0.09071, -0.009399, -0.073952,
+ -0.035575, -0.05028, 0.11478, 0.137866, 0.065234,
+ 0.003594, -0.066802, -0.144989, 0.166201, 0.039564,
+ -0.022457, -0.03009, 0.016187, 0.115443, -0.097331,
+ -0.019139, 0.09944, 0.002198, -0.030953, 0.021099,
+ -0.045399, -0.046871, 0.022533, -0.064657, 0.005776,
+ 0.049063, -0.028478, 0.019268, 0.054265, 0.028042,
+ 0.045559, -0.005541, -0.01441, -0.024165, -0.054976,
+ -0.073258, 0.084205, 0.036077, -0.068683, 0.004708,
+ -0.085228, 0.001234, 0.046261, -0.050496, -0.028227,
+ -0.086828, -0.001218, 0.021865, 0.003791, -0.000568,
+ -0.088733, -0.040041, -0.035891, -0.054915, 0.073463,
+ -0.132031, -0.012844, -0.068544, 0.013052, 0.087335,
+ 0.038603, -0.115382, -0.010433, -0.007113, 0.095126,
+ -0.047378, -0.081353, 0.018021, -0.021156, -0.120774,
+ 0.040038, 0.007633, -0.088728, -0.009928, 0.020142,
+ 0.052024, -0.021063, -0.118121, 0.102739, -0.055837,
+ 0.005253, -0.061924, 0.06368, -0.014512, -0.020259,
+ 0.029493, -0.013435, -0.020638, 0.089342, 0.001092,
+ -0.046491, -0.145634, -0.083159, -0.158142, -0.279281,
+ 0.003611, 0.055863, -0.064655, -0.088773, 0.089283,
+ -0.029619, -0.089949, 0.017197, -0.066633, -0.052347,
+ 0.090828, -0.087551, 0.000338, 0.085238, -0.005313,
+ 0.096211, 0.071381, -0.076546, -0.077927, -0.040864,
+ 0.062936, 0.041559, 0.016235, -0.017513, 0.014773,
+ -0.025734, 0.028586, 0.070292, 0.055794, -0.026131,
+ -0.076954, -0.082228, 0.043947, -0.035921, 0.152668,
+ -0.04951, 0.023159, 0.008506, -0.044773, -0.160358,
+ 0.024984, -0.025587, -0.071627, -0.038376, 0.088478,
+ 0.120568, 0.046723, 0.086731, 0.000695, -0.015751,
+ -0.027837, -0.160937, -0.095031, 0.036271, -0.009061,
+ -0.015078, -0.036281, -0.103665, -0.058258, -0.049573,
+ 0.022021, 0.108296, -0.002586, 0.065655, -0.018584,
+ -0.046441, -0.031018, 0.06735, 0.014328, 0.00886,
+ -0.000245, 0.0634, -0.00181, 0.043515, 0.090344,
+ -0.063845, 0.020485, 0.079401, 0.070558, -0.116428,
+ 0.032628, 0.068949, 0.052238, -0.04453, 0.096813,
+ 0.029911, -0.008814, 0.044352, -0.168172, 0.009604,
+ 0.055828, -0.100739, -0.026013, 0.021193, -0.051425,
+ 0.035891, -0.004085, 0.030216, -0.060801, 0.037202,
+ 0.007262, 0.120686, 0.026846, 0.058464, -0.100792,
+ -0.009176, 0.027589, 0.123957, -0.011283, -0.025744,
+ -0.105081, 0.118244, -0.042122, -0.025404, 0.000873,
+ -0.012703, 0.084159, -0.067539, -0.140536, 0.041637,
+ -0.014485, -0.043382, -0.048004, -0.075416, 0.054401,
+ -0.018651, -0.032908, 0.164231, -0.053236, 0.033946,
+ -0.021681, -0.012655, -0.037049, -0.001613, -0.053393,
+ -0.014635, 0.017954, -0.116115, -0.027232, 0.034005,
+ -0.035376, 0.026492, -0.03725, 0.070733, 0.074835,
+ -0.021378, -0.14298, 0.123195, 0.003699, 0.025398,
+ 0.015629, 0.07737, 0.032623, 0.12158, 0.0971,
+ 0.000946, -0.056355, 0.042065, 0.008184, -0.081824,
+ -0.101937, 0.065473, 0.00336, 0.069241, 0.073002,
+ -0.053844, -0.044301, 0.080351, -0.091833, 0.044288,
+ 0.007447, -0.120723, -0.013806, -0.023636, -0.064616,
+ 0.030556, 0.07263, 0.074428, -0.087759, -0.02644,
+ 0.06484, 0.049162, 0.091053, 0.023891, 0.033811,
+ -0.027746, 0.116392, 0.106126, -0.056644, -0.014781,
+ 0.036137, -0.002632, 0.055512, 0.070077, 0.067819,
+ -0.030625, 0.053772, -0.078457, -0.021351, -0.113011,
+ 0.052797, 0.044875, -0.077269, -0.009867, 0.101493,
+ 0.073477, -0.024103, 0.049145, -0.004706, -0.025211,
+ -0.053731, -0.049009, -0.035786, 0.05443, 0.046515,
+ 0.025154, -0.043569, -0.034789, -0.05861, 0.006931,
+ 0.012049, 0.046809, -0.129441, 0.025541, -0.030933,
+ 0.000297, -0.054058, 0.179837, 0.081515, 0.004932,
+ -0.028445, -0.073753, 0.010629, 0.080042, 0.09871,
+ -0.014017, 0.057597, 0.00101, 0.071658, -0.06757,
+ 0.074384, 0.110366, -0.018121, -0.108754, 0.037793,
+ 0.028041, -0.047508, -0.031359, -0.098913, -0.036486,
+ -0.017311, -0.001279, -0.013694, 0.051968, 0.036512,
+ 0.088201, 0.031155, -0.043442, -0.065045, 0.023486,
+ 0.027, 0.104768, -0.015176, -0.038754, -0.004178,
+ 0.003732, 0.062166, 0.085438, -0.077368, -0.101645,
+ -0.118347, 0.007589, -0.056489, 0.082268, 0.020253,
+ -0.035623, 0.034235, -0.099354, -0.061237, -0.024285,
+ 0.005441, -0.039694, -0.025957, -0.004411, 0.049903,
+ 0.00304, 0.036243, 0.023552, -0.007334, 0.128963,
+ -0.077727, -0.059175, -0.019437, -0.024872, 0.004339,
+ 0.084006, -0.076605, -0.102261, 0.036714, -0.035205,
+ -0.007642, -0.005125, -0.030525, 0.09639, -0.053138,
+ -0.002192, -0.024851, 0.050645, 0.04149, -0.043183,
+ 0.046796, -0.050894, 0.055023, 0.133834, -0.024013,
+ 0.000872, -0.057072, -0.00063, 0.04207, -0.129339,
+ -0.064283, 0.037836, -0.066393, 0.004438, 0.125379,
+ -0.062213, -0.067468, 0.090177, -0.046094, -0.025725,
+ 0.079101, -0.074909, -0.04373, -0.073483, 0.069672,
+ -0.020413, -7.9e-05, -0.049725, -0.120751, -0.04698,
+ 0.039894, 0.072305, 0.009798, 0.005613, -0.045217,
+ 0.006862, 0.036285, 0.074819, -0.006747, 0.015144,
+ -0.071562, 0.012324, -0.001082, 0.014835, 0.07996,
+ -0.027804, 0.103358, -0.017203, 0.014914, -0.056687,
+ 0.030827, 0.028076, 0.003395, -0.073255, 0.11031,
+ 0.056498, -0.044893, 0.110122, -0.109058, -0.052302,
+ -0.001604, -0.089977, -0.060548, 0.107808, 0.025463,
+ -0.070203, -0.000513, -0.123913, 0.046247, -0.085392,
+ 0.096343, 0.09589, -0.06495, 0.070363, 0.034272,
+ 0.037773, -0.07695, 0.124858, -0.009008, -0.010115,
+ 0.083868, 0.051242, 0.039149, 0.015185, 0.083375,
+ 0.029773, -0.045961, 0.100395, 0.003743, -0.138294,
+ -0.041755, 0.010806, 0.057797, -0.147374, 0.095858,
+ -0.009929, -0.103347, -0.03231, -0.11056, 0.121377,
+ 0.145244, 0.017079, -0.080587, 0.020516, -0.044939,
+ -0.010477, 0.038347, -0.003466, -0.001618, 0.0196,
+ -0.021762, 0.125482, 0.011074, 0.065815, 0.040298,
+ 0.009202, -0.051686, 0.129684, -0.131135, 0.044536,
+ 0.009313, 0.102518, -0.075351, 0.054338, 0.020273,
+ -0.045753, 0.031345, 0.000407, -0.097294, -0.000416,
+ -0.007466, -0.044972, -0.078744, 0.042414, 0.066624,
+ 0.030318, -0.067852, 0.061416, -0.028992, 0.056606,
+ 0.004038, -0.036253, -0.014279, 0.023123, -0.007832,
+ -0.000137, -0.027684, -0.127648, -0.007713, -0.008746,
+ -0.0265, 0.049032, -0.183319, 0.059107, 0.0665,
+ 0.016902, -0.093331, 0.090129, 0.016648, -0.083492,
+ -0.023669, -0.010473, 0.027614, 0.145068, 0.000681,
+ 0.044133, -0.035809, 0.005668, -0.090461, -0.090732,
+ -0.033927, 0.042997, 0.0217, -0.046955, 0.044487,
+ -0.026444, -0.061011, 0.01011, -0.023804, 0.030427,
+ -0.015195, -0.155603, -0.016584, 0.021461, -0.003528,
+ -0.059784, 0.032214, 0.000847, -0.098859, -0.07898,
+ 0.043188, 0.066433, 0.062309, 0.144507, 0.006865,
+ -0.068953, 0.046698, 0.099369, 0.043354, -0.014309,
+ -0.033202, -0.00295, 0.040734, 0.083454, 0.039319,
+ 0.051358, 0.006074, -0.073465, -0.090554, -0.120787,
+ -0.040676, 0.092412, -0.085151, -0.021699, 0.005813,
+ 0.103135, 0.024964, 0.025832, -0.075982, 0.035699,
+ -0.02731, -0.153007, 0.03642, 0.0576, 0.08163,
+ 0.001605, -0.054191, -0.033043, -0.01439, -0.071383,
+ 0.03618, 0.03586, -0.04698, 0.038541, -0.044757,
+ -0.078032, -0.029878, 0.078183, 0.082251, 0.010549,
+ 0.053317, -0.038231, -0.06561, 0.055798, 0.037504,
+ 0.076317, -0.027605, 0.010349, 0.095361, -0.088636,
+ 0.049089, 0.113316, 0.051084, 0.038589, 0.03433,
+ -0.055948, -0.037217, -0.015418, -0.139976, 0.036306,
+ 0.039306, -0.009889, -0.04491, 0.016559, -5e-05,
+ 0.106073, 0.01528, -0.002563, -0.109085, -0.048475,
+ -0.035319, 0.16386, 0.032981, -0.044932, 0.003227,
+ -0.123233, -0.010638, 0.055479, -0.003666, -0.072249,
+ -0.111158, 0.065365, 0.010691, 0.039119, -0.001837,
+ -0.118729, 0.06147, -0.002077, -0.033335, -0.060165,
+ -0.026081, -0.001806, -0.079616, -7.5e-05, 0.080598,
+ 0.032908, -0.03514, -0.003136, -0.029024, 0.094622,
+ -0.075773, -0.022898, -0.014817, 0.058393, -0.111505,
+ 0.036794, -0.01576, -0.112602, 0.030323, 0.085897,
+ -0.020834, 0.056079, -0.103762, 0.117671, -0.041205,
+ 0.041684, -0.084336, 0.034186, 0.011973, -0.006313,
+ 0.040836, -0.035709, 0.03417, 0.122672, 0.090973,
+ -0.053182, -0.059371, 0.091017, -0.090998, -0.116986,
+ 0.001405, 0.138364, 0.017107, -0.064076, 0.103486,
+ -0.031142, -0.030068, 0.046547, -0.133471, -0.042055,
+ 0.140418, -0.125084, 0.035218, -0.001162, -0.02113,
+ -0.012034, 0.097413, -0.079006, -0.03903, -0.054011,
+ 0.143887, 0.078835, -0.000601, -0.021173, -0.039895,
+ -0.02505, 0.075865, 0.039221, 0.032458, 0.038206,
+ -0.038873, -0.085003, -0.032736, -0.026956, 0.113525,
+ -0.023933, 0.120794, -0.003862, -0.026459, -0.138724,
+ 0.089559, 0.029002, -0.052098, -0.085692, 0.115174,
+ 0.083497, 0.024179, 0.119021, -0.067541, 0.019047,
+ -0.02772, -0.086083, -0.055329, 0.020087, -0.027086,
+ -0.047858, -0.051975, -0.035205, -0.059342, -0.068582,
+ 0.058936, 0.044141, -0.080315, 0.119744, -0.046518,
+ -0.064588, -0.027212, 0.147823, 0.032404, 0.01669,
+ 0.024302, 0.08556, -0.001525, 0.016469, 0.038891,
+ -0.020146, 0.019943, 0.045067, 0.03807, -0.086274,
+ -0.025769, 0.044192, 0.102141, -0.064765, 0.055849,
+ 0.048803, -0.030066, -0.00922, -0.116655, 0.068295,
+ 0.04758, -0.076138, -0.070307, 0.047582, -0.111342,
+ 0.004656, -0.004452, 0.029703, -0.004259, 0.01113,
+ 0.014446, 0.166086, 0.059565, 0.000985, -0.052607,
+ 0.013251, 0.094476, 0.106216, 0.016715, -0.025581,
+ -0.101244, 0.072897, -0.114526, 0.024681, 0.010784,
+ -0.051759, 0.032389, -0.050202, -0.083316, 0.052334,
+ -0.0351, -0.116721, -0.110336, -0.053391, 0.065541,
+ -0.02979, -0.020457, 0.135285, -0.004142, 0.111508,
+ -0.030936, 0.018549, -0.016034, 0.018572, -0.084336,
+ -0.048615, -0.018739, -0.096815, -0.090162, 0.01941,
+ -0.040821, -0.009925, -0.097427, 0.091891, 0.031793,
+ -0.024598, -0.132848, 0.078353, 0.089339, -0.068562,
+ -0.020779, 0.040974, -0.055675, 0.169131, 0.029649,
+ 0.078165, -0.050679, -0.005881, -0.004983, -0.104324,
+ -0.069096, 0.12796, 0.011392, -0.000769, 0.062168,
+ -0.079842, 0.001606, 0.089284, -0.035465, 0.031075,
+ 0.029519, -0.102956, -0.010902, -0.06403, -0.019669,
+ 0.057492, 0.075802, -0.008904, -0.060743, -0.053144,
+ 0.005126, 0.06298, 0.085674, 0.019895, 0.104448,
+ -0.086473, 0.056906, 0.056795, -0.01294, 0.036606,
+ -0.008604, -0.04045, 0.042062, 0.04181, 0.02768,
+ -0.092256, 0.091237, -0.0395, 0.024761, -0.088978,
+ 0.068585, 0.088295, -0.048033, -0.017808, 0.04537,
+ 0.1246, -0.03532, 0.056751, 0.092751, 0.054025,
+ -0.015725, -0.061938, 0.036806, 0.078768, -0.016065,
+ 0.002444, -0.023887, -0.072177, -0.02979, -0.00586,
+ 0.015478, 0.129142, -0.091024, 0.071482, -0.065445,
+ 0.005867, -0.006051, 0.098646, 0.054089, 0.018713,
+ 0.033837, -0.008355, -0.051959, 0.05744, 0.160305,
+ -0.001863, 0.016738, -0.033705, 0.062233, -0.140759,
+ 0.027342, 0.060074, 0.030362, -0.117875, 0.06102,
+ -0.028026, -0.088238, -0.003782, -0.146288, -0.080395,
+ 0.050048, 0.036136, 0.0195, 0.066902, 0.020355,
+ 0.024817, -0.056254, -0.140918, -0.085803, 0.02054,
+ -0.00373, 0.161411, -0.049408, 0.000219, -0.002348,
+ -0.055021, 0.06782, 0.126483, -0.031063, -0.119299,
+ -0.102834, 0.001133, 0.010172, 0.107707, -0.029106,
+ -0.059813, 0.036698, -0.02172, -0.043189, -0.00227,
+ -0.031694, 0.009605, -0.022459, -0.036417, 0.053675,
+ 0.061561, -0.012723, 0.05004, -0.02945, 0.131044,
+ -0.124516, -0.107579, -0.012171, 0.011761, 0.002599,
+ 0.016327, -0.060854, -0.08091, 0.030875, -0.002997,
+ -0.02097, -0.01188, -0.086096, 0.037912, 0.012421,
+ 0.055253, -0.00725, 0.04174, 0.055596, -0.02442,
+ -0.017564, -0.079202, 0.008897, 0.180091, 0.05449,
+ 0.001772, -0.022151, -0.082048, -0.010559, -0.163377,
+ -0.02066, -0.017827, -0.0308, -0.045856, 0.122405,
+ -0.052946, -0.13049, 0.097383, -0.116737, 0.039855,
+ 0.056504, -0.059549, -0.059931, -0.018658, 0.034898,
+ 0.054889, 0.005373, -0.066796, -0.12736, 0.04796,
+ 0.071746, 0.02741, -0.006212, 0.024132, -0.094062,
+ 0.005369, -0.008926, 0.073085, -0.014265, -0.029204,
+ -0.100025, -0.072076, 0.014651, 0.069368, 0.048275,
+ -0.066823, 0.086074, 0.014921, -0.015395, -0.045138,
+ 0.026224, 0.000902, -0.038208, -0.035221, 0.057397,
+ 0.097606, -0.073195, 0.051626, -0.033488, 0.027813,
+ 0.00207, -0.09751, -0.057877, 0.12668, -0.082194,
+ -0.072597, 0.006014, -0.093185, -0.016853, -0.02279,
+ 0.138461, 0.005394, -0.056485, 0.102778, 0.028918,
+ -0.045604, -0.060041, 0.121251, 0.02926, -0.101404,
+ 0.061194, 0.033039, -0.016798, 0.064263, 0.065144,
+ 0.010925, 0.023151, 0.107623, 0.027977, -0.090356,
+ -0.024863, -0.00644, 0.04787, -0.047486, 0.088211,
+ -0.012139, -0.116121, -0.000525, -0.140961, 0.016604,
+ 0.06349, -0.022732, -0.046944, 0.06697, -0.068838,
+ 0.016143, 0.026202, -0.043344, -0.064881, 0.024877,
+ -0.072845, 0.120531, 0.077901, 0.047272, 0.011713,
+ -0.044646, 0.040932, 0.076164, -0.101233, -0.029615,
+ -0.065118, 0.050966, -0.023273, 0.053517, 0.02371,
+ -0.007489, 0.035822, 0.023439, -0.055528, -0.004033,
+ -0.007662, -0.096546, -0.081662, 0.037141, 0.137562,
+ 0.075526, -0.097496, 0.12399, 0.013996, 0.087005,
+ -0.019788, -0.082043, 0.020524, 0.007027, -0.021537,
+ -0.036264, -0.090952, -0.177722, -0.009306, -0.031473,
+ -0.009287, 0.047557, -0.090241, 0.089347, 0.056375,
+ -0.005506, -0.112128, 0.004356, 0.064421, -0.038478,
+ -0.035674, 0.040616, 0.007731, 0.160236, -0.054199,
+ -0.007537, 0.012434, 0.022001, -0.021567, -0.075163,
+ -0.026053, 0.015909, 0.041015, 0.021832, 0.034152,
+ -0.048539, -0.086655, 0.047465, 0.000682, 0.04264,
+ 0.023697, -0.095971, -0.022874, -0.000369, 0.003413,
+ 0.046005, 0.064807, 0.010131, -0.129517, -0.092254,
+ 0.116469, 0.053796, 0.03811, 0.09447, 0.018435,
+ -0.034803, 0.073591, 0.108348, 0.104096, 0.049884,
+ -0.021274, 0.022097, 0.065347, 0.065555, 0.089319,
+ 0.000474, -0.004186, -0.040493, -0.065543, -0.083167,
+ -0.017425, 0.049177, -0.044248, 0.008399, 0.06818,
+ 0.154778, 0.027549, -0.008012, 0.01495, 0.043254,
+ 0.039599, -0.136415, -0.018716, 0.0619, 0.031263,
+ 0.058118, -0.0372, -0.114692, -0.080876, -0.053238,
+ 0.077436, 0.015015, -0.092517, 0.005804, -0.065541,
+ -0.005653, -0.073184, 0.095594, 0.08247, 0.060989,
+ -0.000262, -0.035766, -0.083441, 0.122634, 0.088429,
+ -0.014397, -0.055434, -0.005659, 0.069697, -0.064892,
+ 0.008824, 0.082498, 0.051866, -0.03607, 0.033403,
+ -0.082855, -0.087376, 0.002714, -0.097121, -0.01917,
+ 0.027179, -0.06987, -0.009316, 0.04745, 0.040657,
+ 0.060527, 0.00462, -0.040264, -0.051228, -0.029023,
+ -0.071384, 0.101421, 0.009538, -0.099185, 0.0601,
+ -0.048395, -0.024677, 0.025125, -0.056043, -0.058045,
+ -0.054059, 0.008107, 0.021078, 0.04529, -0.018459,
+ -0.113359, 0.014009, -0.006826, -0.052747, 0.046922,
+ -0.075976, 0.008538, -0.084411, -0.004369, 0.045801,
+ 0.075392, -0.06734, 0.014454, 0.032407, 0.092478,
+ -0.061859, -0.083458, 0.051442, 0.031695, -0.080233,
+ 0.054028, 0.027, -0.073549, 0.0323, 0.036501,
+ -0.011384, -0.02078, -0.124142, 0.093905, -0.028332,
+ 0.039139, -0.030944, 0.079952, -0.001717, 0.013976,
+ 0.038005, -0.001751, -0.044097, 0.129827, 0.014385,
+ -0.001682, -0.063458, -0.002511, -0.07815, -0.141236,
+ 0.021955, 0.104851, -0.093246, -0.060019, 0.069998,
+ 0.004399, -0.096408, 0.059327, -0.062268, -0.074327,
+ 0.108063, -0.090534, -0.045654, 0.048119, 0.049187,
+ 0.042105, 0.043964, -0.091516, -0.047999, -0.028881,
+ 0.070471, 0.055401, -0.025605, 0.011176, 0.008475,
+ 0.022254, 0.038266, 0.048106, 0.047176, -0.017967,
+ -0.010978, -0.088762, 0.034806, 0.019311, 0.126815,
+ -0.010571, 0.053073, 0.032162, -0.00078, -0.1522,
+ -0.014253, -0.021954, -0.13104, -0.061376, 0.113838,
+ 0.060725, 0.020201, 0.102533, -0.011392, -0.052046,
+ -0.069625, -0.091011, -0.097954, 0.067847, 0.017856,
+ -0.053461, -0.040679, -0.121664, -0.077208, -0.106919,
+ 0.057996, 0.069756, -0.012433, 0.069569, -0.055159,
+ -0.024801, -0.060448, 0.1017, 0.014619, 0.03658,
+ -0.004526, 0.093977, -0.028211, 0.045261, 0.149736,
+ -0.014691, -0.007959, 0.097708, 0.107128, -0.079723,
+ 0.029157, 0.020116, 0.104828, -0.064208, 0.119172,
+ 0.039583, -0.029446, 0.006628, -0.110398, 0.004062,
+ 0.048132, -0.060601, 0.009448, 0.051777, -0.053127,
+ 0.050551, -0.001924, 0.028079, -0.050618, -0.013698,
+ 0.00192, 0.088162, 0.073078, 0.085795, -0.066788,
+ 0.014025, 0.042699, 0.176241, -0.046674, -0.034822,
+ -0.051433, 0.121729, -0.057076, 0.023901, 0.045075,
+ -0.057182, 0.05478, -0.01728, -0.146674, 0.00209,
+ -0.016223, -0.044841, -0.084524, -0.152479, 0.072688,
+ -0.006962, 0.008711, 0.127455, -0.003876, 0.053162,
+ -0.013682, -0.025386, -0.000427, -0.024811, -0.024474,
+ -0.056267, 0.062116, -0.121311, -0.053011, 0.065651,
+ -0.075385, -0.00868, -0.063033, 0.083039, 0.110577,
+ -0.000152, -0.127017, 0.055904, 0.013659, 0.005664,
+ -0.002852, 0.047248, 0.001128, 0.100773, 0.037274,
+ 0.026368, -0.042205, 0.021887, -0.020247, -0.056678,
+ -0.077475, 0.089799, 0.058003, 0.039741, 0.106663,
+ -0.016853, -0.015972, 0.075741, -0.048829, 0.015374,
+ -0.032657, -0.125677, -0.06206, -0.057409, -0.061287,
+ 0.073151, 0.050357, 0.053547, -0.059886, -0.051298,
+ 0.057954, -0.003817, 0.076028, 0.006757, 0.061109,
+ -0.03803, 0.143209, 0.092207, -0.018493, 0.062291,
+ 0.005751, -0.036449, 0.067582, 0.031449, 0.101894,
+ -0.080754, 0.011515, -0.049485, -0.016137, -0.087818,
+ 0.108851, 0.038222, -0.099315, -0.003117, 0.052278,
+ 0.107517, -0.036233, 0.06537, 0.040409, -0.057029,
+ -0.033167, -0.081758, -0.019502, 0.033438, 0.013365,
+ -0.01776, -0.025906, -0.020244, -0.078722, -0.011697,
+ -0.028246, 0.068647, -0.106417, 0.026956, -0.064914,
+ 0.062711, -0.017857, 0.151539, 0.044613, -0.01782,
+ 0.009085, -0.032785, -0.025795, 0.07579, 0.075667,
+ -0.040398, 0.058556, -0.042634, 0.093973, -0.099529,
+ 0.057103, 0.073562, 0.01264, -0.066141, 0.029558,
+ 0.060219, -0.083699, -0.054799, -0.120442, -0.000374,
+ 0.006521, 0.034512, -0.039558, 0.042191, 0.033865,
+ 0.103992, -0.014977, -0.077384, -0.05134, 0.001873,
+ 0.047451, 0.140612, -0.024885, -0.02142, -0.046604,
+ 0.030606, 0.10066, 0.076356, -0.019288, -0.09857,
+ -0.114463, -0.010855, -0.034657, 0.025618, -0.003356,
+ -0.087913, 0.064346, -0.07554, -0.091569, -0.024965,
+ -0.021232, -0.017255, -0.056931, -0.003104, 0.030219,
+ -0.020112, -0.012334, 0.035298, 0.001405, 0.161753,
+ -0.064618, -0.064401, -0.007218, -0.00012, -0.047208,
+ 0.116105, -0.056464, -0.069645, -0.007032, -0.01209,
+ -0.023237, 0.016, -0.039802, 0.074319, -0.012604,
+ 0.014863, -0.058081, 0.093219, 0.062253, -0.040302,
+ 0.027405, -0.128683, 0.039923, 0.116808, -0.011706,
+ 0.012483, -0.017698, 0.003645, -0.007588, -0.120662,
+ -0.032868, 0.066217, -0.031343, -0.034166, 0.146334,
+ -0.031228, -0.125921, 0.117756, -0.042686, -0.062094,
+ 0.049375, -0.112262, 0.010166, -0.073599, 0.04869,
+ 0.028292, 0.020076, -0.062865, -0.106114, -0.0253,
+ 0.066916, 0.029279, 0.028191, -0.003599, -0.040614,
+ 0.020491, 0.060238, 0.052747, -0.01039, -0.022389,
+ -0.063358, -0.028707, 0.035907, -0.011898, 0.079703,
+ -0.003758, 0.078051, -0.017869, 0.009045, -0.018982,
+ 0.034974, 0.069405, -0.018909, -0.038613, 0.083909,
+ 0.033935, -0.036607, 0.088891, -0.052599, -0.059839,
+ 0.052758, -0.068308, -0.063615, 0.126093, -0.00946,
+ -0.042175, -0.011113, -0.073071, 0.052086, -0.052619,
+ 0.049226, 0.066898, -0.045666, 0.117923, 0.053656,
+ -0.010739, -0.043962, 0.141903, 0.001792, -0.035469,
+ 0.090671, 0.043993, -0.013655, 0.018989, 0.127223,
+ 0.00103, -0.001154, 0.081839, -0.024979, -0.103704,
+ -0.07792, 0.036083, 0.06822, -0.06221, 0.11373,
+ -0.010501, -0.065801, 0.050885, -0.104304, 0.121937,
+ 0.11185, 0.00968, -0.011791, 0.001677, -0.035029,
+ 0.010677, 0.024572, -0.01286, -0.030323, -0.010466,
+ 0.011279, 0.167752, 0.003136, 0.109709, 0.007292,
+ 0.000987, 0.004572, 0.108706, -0.113192, -0.012431,
+ -0.015225, 0.073653, -0.051275, 0.077928, -0.012752,
+ -0.011708, 0.014172, 0.025162, -0.095378, 0.026382,
+ -0.028889, -0.058569, -0.129329, 0.011087, 0.061452,
+ 0.056893, -0.058004, 0.103586, -0.060752, 0.081824,
+ -0.042805, -0.015991, -0.024444, 0.028952, -0.013528,
+ 0.042851, 0.019988, -0.165741, -0.031012, -0.014713,
+ -0.026059, 0.031698, -0.134343, 0.03209, 0.020828,
+ 0.051674, -0.128006, 0.050856, 0.02222, -0.073513,
+ -0.00934, 0.013756, 0.036163, 0.098407, -0.023495,
+ 0.023858, 0.008121, 0.02222, -0.103489, -0.046663,
+ -0.033, 0.063565, 0.029224, -0.012693, 0.084202,
+ 0.012187, -0.051, 0.026126, -0.043293, 0.008675,
+ -0.019812, -0.16507, -0.014555, -0.047431, 0.01799,
+ -0.040073, 0.107192, 0.022228, -0.089023, -0.066885,
+ 0.01463, 0.073186, 0.069902, 0.072634, 0.019593,
+ -0.041539, 0.031788, 0.09231, 0.027223, 0.034027,
+ -0.051855, 0.000391, 0.007869, 0.13191, 0.069384,
+ 0.046276, 0.04044, -0.037093, -0.031393, -0.112828,
+ 0.015709, 0.096749, -0.103205, -0.021284, 0.011405,
+ 0.158287, -0.021028, 0.042219, -0.050759, 0.069715,
+ -0.042907, -0.11698, 0.014224, 0.094648, 0.028395,
+ 0.041535, -0.057033, -0.047607, -0.024419, -0.034905,
+ 0.010125, 0.036728, -0.052503, -0.001839, -0.033477,
+ -0.053414, -0.070394, 0.092895, 0.1006, -0.026352,
+ 0.080574, -0.028763, -0.059548, 0.094571, 0.091787,
+ 0.041437, 0.014312, 0.045792, 0.108269, -0.081586,
+ 0.056288, 0.137447, 0.054718, -0.032474, 0.054502,
+ -0.100144, -0.00646, 0.024739, -0.117043, -0.008919,
+ 0.070299, -0.036862, -0.014543, 0.0245, -0.015222,
+ 0.114975, -0.043705, 0.000421, -0.061872, -0.035148,
+ -0.022797, 0.128575, -0.031798, -0.086718, -0.007172,
+ -0.071706, -0.006833, 0.028645, -0.007011, -0.096745,
+ -0.142269, 0.027996, 0.06521, 0.061381, 0.000741,
+ -0.140531, 0.01748, -0.014986, -0.040893, -0.012718,
+ -0.012494, -0.021869, -0.032923, 0.016456, 0.104475,
+ 0.010792, -0.066178, 0.019097, -0.001893, 0.067513,
+ -0.092673, -0.059851, -0.045936, 0.052642, -0.0625,
+ 0.065013, -0.025659, -0.149301, 0.051705, 0.035692,
+ -0.04579, -0.007482, -0.069141, 0.149365, -0.042039,
+ 0.018492, -0.081315, 0.05588, 0.058158, 0.019669,
+ 0.063836, -0.012391, 0.007057, 0.155454, 0.033854,
+ -0.016532, -0.007661, 0.043113, -0.080283, -0.10867,
+ -0.029344, 0.093781, -0.01584, -0.068134, 0.091804,
+ 0.004148, -0.058507, 0.059633, -0.095883, -0.004939,
+ 0.086151, -0.113571, -0.019466, -0.009167, 0.003662
+};
+
+const struct lsp_codebook lsp_cbjvm[] = {
+ /* codebook/lspjvm1.txt */
+ {
+ 10,
+ 9,
+ 512,
+ codes0
+ },
+ /* codebook/lspjvm2.txt */
+ {
+ 5,
+ 9,
+ 512,
+ codes1
+ },
+ /* codebook/lspjvm3.txt */
+ {
+ 5,
+ 9,
+ 512,
+ codes2
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/lsp1.txt */
+static const float codes0[] = {
+ 225,
+ 250,
+ 275,
+ 300,
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600
+};
+ /* codebook/lsp2.txt */
+static const float codes1[] = {
+ 325,
+ 350,
+ 375,
+ 400,
+ 425,
+ 450,
+ 475,
+ 500,
+ 525,
+ 550,
+ 575,
+ 600,
+ 625,
+ 650,
+ 675,
+ 700
+};
+ /* codebook/lsp3.txt */
+static const float codes2[] = {
+ 500,
+ 550,
+ 600,
+ 650,
+ 700,
+ 750,
+ 800,
+ 850,
+ 900,
+ 950,
+ 1000,
+ 1050,
+ 1100,
+ 1150,
+ 1200,
+ 1250
+};
+ /* codebook/lsp4.txt */
+static const float codes3[] = {
+ 700,
+ 800,
+ 900,
+ 1000,
+ 1100,
+ 1200,
+ 1300,
+ 1400,
+ 1500,
+ 1600,
+ 1700,
+ 1800,
+ 1900,
+ 2000,
+ 2100,
+ 2200
+};
+ /* ../unittest/lsp45678910.txt */
+static const float codes4[] = {
+ 1.08123, 1.57884, 1.85557, 1.93731, 2.53244, 2.64981,
+ 1.0628, 1.45001, 1.83956, 1.9565, 2.48885, 2.65346,
+ 1.10159, 1.36102, 1.83358, 1.93241, 2.50518, 2.62981,
+ 1.07906, 1.37686, 1.87269, 1.95508, 2.54134, 2.63378,
+ 1.09554, 1.63104, 1.86627, 2.06699, 2.50666, 2.57043,
+ 1.09306, 1.56136, 1.77247, 2.12386, 2.54748, 2.61826,
+ 1.09365, 1.50021, 1.78605, 2.07712, 2.48377, 2.57254,
+ 1.03502, 1.48598, 1.67865, 2.07936, 2.40234, 2.51331,
+ 1.23172, 1.63057, 1.84991, 2.02345, 2.46721, 2.57161,
+ 1.20636, 1.47819, 1.85565, 2.0092, 2.43743, 2.55238,
+ 1.20425, 1.49576, 1.8464, 2.03998, 2.50063, 2.59244,
+ 1.27202, 1.43835, 1.8545, 2.03871, 2.51872, 2.62009,
+ 1.29891, 1.48336, 1.83887, 1.98366, 2.48837, 2.59701,
+ 1.38559, 1.50018, 1.81943, 1.9817, 2.50554, 2.61253,
+ 1.41367, 1.56655, 1.76718, 1.99449, 2.56961, 2.62524,
+ 1.46905, 1.62608, 1.75177, 2.04119, 2.60895, 2.65878,
+ 1.48951, 1.61764, 1.68918, 2.05385, 2.66224, 2.70553,
+ 1.43112, 1.53558, 1.64732, 1.81092, 2.57577, 2.6922,
+ 1.41167, 1.60617, 1.73036, 1.96937, 2.62811, 2.69185,
+ 1.34102, 1.63997, 2.19739, 2.28132, 2.44971, 2.626,
+ 1.31988, 1.67483, 2.10118, 2.28173, 2.49978, 2.61148,
+ 1.27462, 1.61012, 1.90144, 2.23566, 2.51818, 2.62888,
+ 1.17221, 1.36564, 1.7847, 1.90445, 2.53808, 2.64619,
+ 1.09616, 1.35011, 1.75499, 1.86967, 2.48657, 2.6055,
+ 1.03654, 1.3262, 1.72989, 1.86212, 2.46119, 2.57545,
+ 1.01653, 1.27725, 1.6888, 1.80838, 2.46298, 2.57624,
+ 0.968031, 1.32901, 1.71641, 1.82136, 2.48115, 2.56195,
+ 0.940641, 1.28334, 1.76788, 1.86054, 2.50314, 2.5949,
+ 0.926995, 1.24333, 1.73891, 1.901, 2.4495, 2.55764,
+ 0.839883, 1.23712, 1.70215, 1.81262, 2.42139, 2.49298,
+ 0.924474, 1.18807, 1.75752, 1.8249, 2.45594, 2.61106,
+ 0.96423, 1.20727, 1.66622, 1.87681, 2.50715, 2.58041,
+ 0.989772, 1.18973, 1.69345, 1.80714, 2.44571, 2.56195,
+ 0.919183, 1.20312, 1.67383, 1.77261, 2.3858, 2.51167,
+ 0.978552, 1.17542, 1.61386, 1.72687, 2.32896, 2.5167,
+ 1.01454, 1.25425, 1.58728, 1.75663, 2.40306, 2.51083,
+ 1.09672, 1.23117, 1.5574, 1.84394, 2.46358, 2.55546,
+ 1.16877, 1.35118, 1.61393, 1.83103, 2.47627, 2.58122,
+ 1.17651, 1.26415, 1.56492, 1.76049, 2.48352, 2.58104,
+ 1.01797, 1.24983, 1.42449, 1.59354, 2.45834, 2.52503,
+ 1.05399, 1.21603, 1.51742, 1.85194, 2.34275, 2.50233,
+ 0.908986, 1.2508, 1.59392, 1.8871, 2.37309, 2.53013,
+ 0.993871, 1.16402, 1.61662, 1.77573, 2.56946, 2.65857,
+ 1.10248, 1.38615, 1.57368, 1.78564, 2.31793, 2.50856,
+ 1.20724, 1.39083, 1.55105, 1.85061, 2.33598, 2.49433,
+ 0.905032, 1.41648, 1.58005, 1.84183, 2.50381, 2.6016,
+ 0.79589, 1.10793, 1.59771, 2.0155, 2.40215, 2.53461,
+ 0.732401, 1.15861, 1.55747, 1.938, 2.62642, 2.70543,
+ 0.85967, 1.12906, 1.67186, 1.95399, 2.51479, 2.61587,
+ 0.921647, 1.24536, 1.68375, 1.89446, 2.59964, 2.71656,
+ 0.845409, 1.19476, 1.76731, 1.84451, 2.58977, 2.71694,
+ 0.977678, 1.1414, 1.66711, 1.92383, 2.63201, 2.68907,
+ 0.951137, 1.12255, 1.71418, 1.8859, 2.53576, 2.67211,
+ 1.02995, 1.15955, 1.73944, 1.92833, 2.48818, 2.62352,
+ 0.925634, 1.22593, 1.7518, 1.97075, 2.5329, 2.62107,
+ 1.0123, 1.21143, 1.79395, 1.88586, 2.46727, 2.57249,
+ 0.993978, 1.13747, 1.74347, 1.84089, 2.39008, 2.56639,
+ 0.989822, 1.17307, 1.68756, 1.94893, 2.32553, 2.47342,
+ 0.955854, 1.23723, 1.80741, 2.11677, 2.39103, 2.50278,
+ 1.10336, 1.35799, 1.85224, 2.09709, 2.39275, 2.55324,
+ 1.12887, 1.4409, 1.92791, 2.1767, 2.40798, 2.54428,
+ 1.31613, 1.57544, 1.96457, 2.15894, 2.48584, 2.57613,
+ 1.4696, 1.7721, 1.95484, 2.16407, 2.39962, 2.48192,
+ 1.50652, 1.75488, 2.01841, 2.24949, 2.48627, 2.60761,
+ 1.52419, 1.77645, 2.05458, 2.27569, 2.58498, 2.66908,
+ 1.518, 1.85028, 2.02643, 2.30188, 2.57753, 2.66918,
+ 1.42205, 1.78898, 1.96748, 2.18477, 2.59685, 2.69968,
+ 1.20841, 1.4347, 1.92362, 2.00377, 2.60293, 2.68501,
+ 1.22117, 1.43657, 1.87997, 2.0334, 2.49815, 2.69542,
+ 1.21771, 1.37598, 1.90861, 1.97303, 2.48056, 2.6454,
+ 1.20035, 1.41224, 1.86328, 2.05454, 2.40923, 2.64633,
+ 1.43945, 1.67593, 2.06471, 2.27323, 2.60645, 2.69621,
+ 1.54757, 1.95602, 2.08379, 2.38708, 2.63432, 2.71122,
+ 1.74537, 1.99526, 2.17627, 2.40949, 2.63225, 2.70742,
+ 1.81929, 1.98216, 2.21017, 2.45219, 2.60377, 2.66452,
+ 1.66955, 1.94018, 2.10087, 2.38694, 2.53082, 2.63087,
+ 1.59768, 1.94591, 2.07284, 2.33889, 2.54425, 2.60825,
+ 1.65615, 1.88869, 1.98455, 2.30113, 2.51078, 2.58636,
+ 1.6188, 1.89886, 2.02474, 2.29131, 2.44053, 2.56029,
+ 1.48128, 1.82621, 1.97192, 2.19291, 2.41702, 2.53029,
+ 1.31873, 1.58154, 1.84545, 2.164, 2.38923, 2.50542,
+ 1.34133, 1.56585, 1.80288, 2.21848, 2.43077, 2.54583,
+ 1.31851, 1.41266, 1.67762, 2.18235, 2.37275, 2.47653,
+ 1.24372, 1.45667, 1.66571, 2.12671, 2.33287, 2.43845,
+ 1.1525, 1.45886, 1.58294, 2.03752, 2.3421, 2.4283,
+ 1.02538, 1.4076, 1.55153, 1.84679, 2.28286, 2.38544,
+ 0.87656, 1.38433, 1.5829, 1.74194, 2.23992, 2.33845,
+ 0.953781, 1.44188, 1.5924, 1.76417, 2.29409, 2.4742,
+ 0.899968, 1.45403, 1.63436, 1.72431, 2.3534, 2.5975,
+ 0.784159, 1.42393, 1.73726, 1.85596, 2.39003, 2.61454,
+ 0.802442, 1.39707, 1.65855, 1.81679, 2.42939, 2.5001,
+ 0.863071, 1.31849, 1.64602, 1.81297, 2.3981, 2.50385,
+ 0.89687, 1.30624, 1.67159, 1.90217, 2.46653, 2.60152,
+ 0.999503, 1.30429, 1.70842, 1.89904, 2.51234, 2.65519,
+ 1.04528, 1.2663, 1.66963, 1.84632, 2.51707, 2.63748,
+ 1.03846, 1.15853, 1.64378, 1.86528, 2.5832, 2.65894,
+ 1.02632, 1.21931, 1.76835, 1.84092, 2.53817, 2.67333,
+ 1.08097, 1.21543, 1.73019, 1.83693, 2.23686, 2.60887,
+ 1.1018, 1.43151, 1.75208, 1.91896, 2.09124, 2.53896,
+ 1.17873, 1.29731, 1.7241, 1.85075, 2.31029, 2.62153,
+ 1.15118, 1.23968, 1.75479, 1.85052, 2.5391, 2.70599,
+ 1.2027, 1.3006, 1.76334, 1.86743, 2.47072, 2.66465,
+ 1.26112, 1.36868, 1.75328, 1.84665, 2.46151, 2.6526,
+ 1.26307, 1.36429, 1.79767, 1.87694, 2.54373, 2.66022,
+ 1.32015, 1.41593, 1.80983, 1.90322, 2.51555, 2.64824,
+ 1.33987, 1.45935, 1.80668, 1.92458, 2.49148, 2.58705,
+ 1.35517, 1.45177, 1.7634, 1.94416, 2.47263, 2.56117,
+ 1.32792, 1.42891, 1.70445, 1.91482, 2.39737, 2.50347,
+ 1.3076, 1.41535, 1.61629, 1.84079, 2.32217, 2.47099,
+ 1.24825, 1.34921, 1.61761, 1.77273, 2.25068, 2.48653,
+ 1.09657, 1.35568, 1.62611, 1.94199, 2.31385, 2.49821,
+ 1.01253, 1.34284, 1.64785, 1.90716, 2.43593, 2.53319,
+ 0.944393, 1.39928, 1.643, 1.93199, 2.33198, 2.48991,
+ 0.883306, 1.40234, 1.70636, 2.02537, 2.37371, 2.54371,
+ 0.829559, 1.23577, 1.71275, 2.18485, 2.38674, 2.54418,
+ 0.923799, 1.51311, 1.70309, 2.10529, 2.47648, 2.55516,
+ 0.772688, 1.4433, 1.65612, 2.05301, 2.45044, 2.53252,
+ 0.776285, 1.4032, 1.73402, 1.93526, 2.46409, 2.5668,
+ 0.782396, 1.41881, 1.75888, 1.97322, 2.54833, 2.6103,
+ 0.789572, 1.41108, 1.77153, 2.06041, 2.54026, 2.63125,
+ 0.774326, 1.28802, 1.83727, 1.96095, 2.51242, 2.58163,
+ 0.811751, 1.27403, 1.81001, 1.88574, 2.56546, 2.63922,
+ 0.844982, 1.32083, 1.87391, 1.9446, 2.56105, 2.66172,
+ 0.881256, 1.69536, 1.90698, 2.07889, 2.61855, 2.67865,
+ 1.09989, 1.72782, 1.97132, 2.15314, 2.50969, 2.60295,
+ 1.17385, 1.68544, 1.91746, 2.14743, 2.38305, 2.56703,
+ 1.10155, 1.54322, 1.82061, 2.05532, 2.33872, 2.58503,
+ 0.975012, 1.37972, 1.77663, 2.03329, 2.19415, 2.51822,
+ 0.967054, 1.08246, 1.61897, 2.07793, 2.20684, 2.37089,
+ 1.00961, 1.12061, 1.53418, 2.08853, 2.28294, 2.42058,
+ 0.899159, 1.20852, 1.42369, 1.97032, 2.28727, 2.4989,
+ 0.879682, 1.31448, 1.47949, 1.68936, 2.20974, 2.28576,
+ 1.03347, 1.24384, 1.47314, 1.66799, 2.15942, 2.25504,
+ 1.04841, 1.25589, 1.537, 1.82005, 2.14225, 2.31375,
+ 1.04825, 1.18926, 1.70511, 1.83599, 2.10545, 2.37206,
+ 1.03432, 1.13888, 1.51462, 1.82966, 2.17045, 2.42561,
+ 1.10388, 1.21765, 1.62215, 1.80585, 2.02753, 2.37681,
+ 1.08723, 1.19501, 1.55902, 1.89504, 2.25012, 2.3792,
+ 1.13001, 1.29387, 1.6924, 1.85888, 2.1972, 2.34906,
+ 1.16289, 1.3046, 1.69102, 1.96932, 2.26861, 2.43029,
+ 1.15181, 1.25793, 1.67383, 1.90202, 2.18916, 2.45871,
+ 1.16844, 1.27183, 1.55733, 2.08415, 2.30803, 2.42037,
+ 1.2351, 1.34019, 1.65679, 2.09516, 2.28319, 2.40964,
+ 1.25239, 1.35536, 1.60985, 2.08519, 2.33271, 2.48887,
+ 1.22631, 1.34399, 1.67305, 2.21553, 2.46, 2.54692,
+ 1.40818, 1.56645, 1.70193, 2.1551, 2.54024, 2.58859,
+ 1.304, 1.549, 1.65358, 2.12874, 2.58947, 2.63332,
+ 1.31253, 1.48894, 1.69055, 1.98288, 2.55839, 2.62252,
+ 1.30359, 1.48566, 1.773, 1.99142, 2.55563, 2.65006,
+ 1.2572, 1.52892, 1.88049, 2.04567, 2.40009, 2.56749,
+ 1.29472, 1.63432, 1.91154, 2.04666, 2.43808, 2.61113,
+ 1.32844, 1.71607, 1.8503, 2.02126, 2.50705, 2.61286,
+ 1.13808, 1.26904, 1.79259, 1.89815, 2.53041, 2.65356,
+ 1.02479, 1.14554, 1.68822, 1.81293, 2.42504, 2.65093,
+ 1.05666, 1.17804, 1.59034, 1.74735, 2.36845, 2.61871,
+ 0.994299, 1.11084, 1.63265, 1.73054, 2.33769, 2.5503,
+ 0.96003, 1.10348, 1.6328, 1.74508, 2.19725, 2.53053,
+ 0.952099, 1.07891, 1.70416, 1.83731, 2.31907, 2.54431,
+ 0.901034, 1.0748, 1.65366, 1.78859, 2.39383, 2.53312,
+ 0.970595, 1.13005, 1.56835, 1.82097, 2.44511, 2.56337,
+ 0.8832, 1.02914, 1.48058, 1.88436, 2.32162, 2.47072,
+ 0.817959, 0.941844, 1.41014, 1.54071, 2.17404, 2.48277,
+ 0.772028, 0.888033, 1.49012, 1.71709, 2.32435, 2.56046,
+ 0.8742, 1.0201, 1.57148, 1.74681, 2.43739, 2.56133,
+ 0.827282, 1.01003, 1.60538, 1.75068, 2.26185, 2.4816,
+ 0.790605, 1.149, 1.65382, 1.78105, 2.35864, 2.49161,
+ 0.746581, 0.96108, 1.60491, 1.879, 2.31927, 2.55158,
+ 0.845418, 0.96953, 1.69617, 1.89093, 2.30188, 2.62149,
+ 0.826083, 1.01605, 1.6586, 1.85255, 2.43588, 2.57274,
+ 0.80426, 0.948999, 1.68449, 2.10334, 2.47505, 2.57585,
+ 0.837016, 1.03, 1.67699, 1.79665, 2.49802, 2.63103,
+ 0.779629, 0.917041, 1.60707, 1.8689, 2.45957, 2.6289,
+ 0.802981, 0.922379, 1.55614, 1.96784, 2.59545, 2.69251,
+ 0.821239, 0.952349, 1.58525, 2.0958, 2.59371, 2.65593,
+ 0.819528, 1.10955, 1.52684, 1.76751, 2.6378, 2.71051,
+ 0.846222, 1.05572, 1.70728, 1.83863, 2.114, 2.5014,
+ 0.956553, 1.43985, 1.7249, 1.93982, 2.14519, 2.43191,
+ 1.33429, 1.55159, 1.7214, 2.01917, 2.178, 2.32944,
+ 1.24736, 1.57146, 1.83452, 2.11416, 2.26821, 2.48981,
+ 1.22315, 1.57342, 1.84625, 2.01609, 2.21928, 2.45785,
+ 1.23993, 1.53779, 1.8228, 2.04648, 2.44445, 2.57805,
+ 1.29968, 1.55774, 1.7983, 2.08069, 2.39337, 2.5752,
+ 1.27312, 1.47413, 1.81487, 2.01491, 2.40501, 2.60292,
+ 1.22903, 1.4485, 1.75715, 2.05057, 2.41716, 2.59461,
+ 1.2063, 1.5151, 1.78896, 2.04215, 2.36856, 2.5858,
+ 1.1589, 1.5448, 1.86145, 2.06665, 2.40525, 2.59099,
+ 1.20326, 1.47986, 1.83352, 2.07062, 2.4318, 2.5857,
+ 1.17077, 1.55578, 1.82667, 2.07708, 2.46748, 2.61941,
+ 1.11628, 1.59353, 1.82425, 2.16082, 2.42781, 2.60049,
+ 1.25031, 1.6173, 1.96265, 2.15224, 2.53124, 2.63143,
+ 1.353, 1.64524, 2.07019, 2.18038, 2.61203, 2.68877,
+ 1.46033, 1.91719, 2.08682, 2.31459, 2.64118, 2.72306,
+ 1.5571, 1.91661, 2.0569, 2.2632, 2.64033, 2.7028,
+ 1.41067, 1.90339, 2.07783, 2.22294, 2.6154, 2.69412,
+ 1.34049, 1.80404, 2.04002, 2.14956, 2.60771, 2.67815,
+ 1.09068, 1.32106, 1.86274, 1.98378, 2.47586, 2.59244,
+ 1.00246, 1.26551, 1.81302, 1.90434, 2.49926, 2.62654,
+ 1.05139, 1.16129, 1.83253, 1.95508, 2.50234, 2.62475,
+ 0.942516, 1.06424, 1.66956, 1.97725, 2.46418, 2.59833,
+ 0.869608, 0.984141, 1.45461, 1.95618, 2.50789, 2.61787,
+ 0.972489, 1.13547, 1.52915, 1.72998, 2.41157, 2.57108,
+ 1.05128, 1.14941, 1.54752, 1.82715, 2.51133, 2.61762,
+ 1.07974, 1.19121, 1.53936, 1.94473, 2.54524, 2.63216,
+ 1.18206, 1.26003, 1.5961, 2.08466, 2.51186, 2.57941,
+ 1.172, 1.35276, 1.46275, 2.01506, 2.62536, 2.67937,
+ 1.20054, 1.32298, 1.5156, 1.7692, 2.52314, 2.66683,
+ 1.22809, 1.30713, 1.73403, 1.91475, 2.24482, 2.56203,
+ 1.17619, 1.32166, 1.78231, 1.88258, 2.27136, 2.52145,
+ 1.15003, 1.48622, 1.77415, 1.97093, 2.38508, 2.61264,
+ 1.10316, 1.455, 1.72062, 1.89959, 2.35671, 2.59138,
+ 1.07047, 1.38631, 1.74693, 1.89198, 2.36751, 2.54357,
+ 0.95361, 1.17616, 1.64355, 1.91998, 2.37206, 2.57246,
+ 1.05232, 1.40517, 1.68895, 1.83167, 2.54288, 2.63248,
+ 0.996802, 1.44143, 1.68446, 1.82195, 2.59599, 2.65884,
+ 1.02655, 1.33494, 1.74094, 1.84038, 2.57165, 2.67897,
+ 1.10832, 1.20084, 1.70613, 1.99908, 2.51466, 2.64821,
+ 1.13332, 1.21947, 1.74777, 2.01308, 2.40664, 2.64036,
+ 1.14214, 1.21872, 1.81464, 1.95106, 2.43007, 2.66618,
+ 1.08156, 1.20709, 1.84645, 1.94628, 2.33914, 2.61266,
+ 1.14637, 1.23863, 1.87425, 1.9681, 2.42738, 2.59563,
+ 1.06941, 1.39313, 1.85976, 1.94182, 2.37447, 2.53818,
+ 1.06022, 1.40293, 1.78464, 1.90995, 2.08085, 2.37542,
+ 0.893759, 1.22533, 1.74143, 1.89549, 2.06221, 2.44178,
+ 0.911307, 1.30139, 1.65149, 1.79817, 1.99688, 2.20866,
+ 1.10291, 1.50331, 1.70777, 1.80853, 1.95863, 2.31168,
+ 1.14945, 1.32806, 1.73828, 1.90461, 2.06187, 2.25797,
+ 1.12135, 1.23056, 1.74878, 1.95066, 2.08647, 2.38929,
+ 0.94897, 1.10189, 1.67664, 1.87539, 2.01682, 2.29668,
+ 1.03508, 1.16223, 1.64138, 1.95271, 2.10095, 2.35872,
+ 0.994183, 1.11431, 1.5476, 1.77373, 1.96608, 2.3363,
+ 1.02511, 1.1397, 1.58524, 1.91237, 2.10246, 2.48243,
+ 0.955352, 1.06222, 1.65906, 1.84841, 2.04328, 2.48743,
+ 1.0491, 1.12055, 1.44698, 1.94902, 2.0269, 2.56059,
+ 1.01243, 1.13828, 1.36794, 2.00847, 2.18944, 2.42242,
+ 1.08203, 1.23491, 1.35176, 1.82717, 2.17316, 2.30024,
+ 1.09436, 1.23514, 1.41642, 1.92259, 2.12823, 2.41941,
+ 1.03451, 1.15131, 1.49236, 1.98085, 2.14904, 2.36531,
+ 1.01309, 1.15454, 1.45996, 1.94304, 2.28176, 2.39727,
+ 0.987103, 1.27435, 1.56187, 1.91746, 2.33429, 2.49565,
+ 0.989791, 1.28917, 1.62314, 1.98233, 2.34503, 2.54805,
+ 1.04201, 1.22597, 1.61002, 1.9748, 2.40631, 2.53704,
+ 1.01969, 1.32372, 1.67908, 1.98369, 2.44302, 2.56193,
+ 1.03098, 1.24991, 1.75329, 1.9703, 2.44275, 2.5771,
+ 1.07865, 1.28137, 1.82168, 2.04699, 2.51249, 2.6143,
+ 1.0425, 1.31828, 1.81754, 1.97774, 2.53877, 2.64347,
+ 1.03375, 1.32343, 1.88596, 1.99364, 2.58713, 2.64829,
+ 1.08416, 1.43412, 1.89966, 1.97448, 2.66167, 2.7171,
+ 1.09579, 1.4813, 1.91655, 1.97041, 2.67123, 2.73097,
+ 1.14796, 1.55307, 1.88454, 1.96066, 2.50184, 2.66788,
+ 1.13778, 1.49891, 1.96262, 2.04724, 2.53731, 2.64235,
+ 1.10886, 1.43549, 1.95549, 2.19587, 2.51428, 2.60153,
+ 1.19107, 1.55785, 1.98454, 2.27079, 2.54188, 2.64206,
+ 1.11074, 1.55308, 1.97813, 2.21105, 2.61337, 2.70664,
+ 1.11409, 1.72802, 1.97504, 2.12448, 2.60293, 2.68194,
+ 1.14848, 1.62709, 1.96813, 2.0739, 2.60736, 2.68667,
+ 1.109, 1.45065, 1.9611, 2.05861, 2.61165, 2.69461,
+ 1.0959, 1.31876, 1.86664, 2.09629, 2.57468, 2.65884,
+ 1.11656, 1.36797, 1.92253, 2.01651, 2.54944, 2.64623,
+ 1.12947, 1.52911, 1.9422, 2.00334, 2.52787, 2.69992,
+ 1.13905, 1.67954, 1.94587, 2.03292, 2.53743, 2.64217,
+ 1.21921, 1.59942, 1.9296, 2.01109, 2.5391, 2.70528,
+ 1.23397, 1.5562, 1.931, 2.08479, 2.57858, 2.67583,
+ 1.23443, 1.65374, 2.03321, 2.25676, 2.63755, 2.69966,
+ 1.25529, 1.47504, 2.02254, 2.28923, 2.58769, 2.70395,
+ 1.25339, 1.4722, 1.9564, 2.21119, 2.57424, 2.6761,
+ 1.12685, 1.58721, 1.95082, 2.03149, 2.41685, 2.61446,
+ 1.00706, 1.6083, 1.89623, 1.98634, 2.22302, 2.52403,
+ 1.06728, 1.72945, 1.93189, 2.04533, 2.16485, 2.40091,
+ 0.94666, 1.69978, 1.87062, 1.98183, 2.13567, 2.44769,
+ 1.00269, 1.72856, 1.93991, 2.07252, 2.27479, 2.46748,
+ 1.14879, 1.60055, 2.00306, 2.12803, 2.40911, 2.50653,
+ 1.19137, 1.35951, 1.90844, 2.11699, 2.36908, 2.52939,
+ 1.22974, 1.31636, 1.90147, 2.00117, 2.36835, 2.5757,
+ 1.16745, 1.28408, 1.85155, 2.05628, 2.44629, 2.57376,
+ 1.17705, 1.28298, 1.79608, 2.01457, 2.4099, 2.52443,
+ 1.16655, 1.28173, 1.80413, 1.93859, 2.38305, 2.5438,
+ 1.14471, 1.2662, 1.75578, 1.86551, 2.35412, 2.57514,
+ 1.16847, 1.28356, 1.69505, 1.81754, 2.30279, 2.52956,
+ 1.09347, 1.31611, 1.62583, 1.79105, 2.30331, 2.40856,
+ 1.07299, 1.21888, 1.58691, 1.72531, 2.2192, 2.34352,
+ 0.946241, 1.17284, 1.42629, 1.55168, 2.19257, 2.32173,
+ 1.0018, 1.17498, 1.50744, 1.69786, 2.2408, 2.47824,
+ 0.992564, 1.25778, 1.42909, 1.81983, 2.23415, 2.43492,
+ 0.933586, 1.25556, 1.37246, 1.68627, 2.26598, 2.34947,
+ 0.987914, 1.16288, 1.40442, 1.56348, 2.22767, 2.48537,
+ 1.05858, 1.18583, 1.32538, 1.44559, 2.16451, 2.45514,
+ 1.04227, 1.14961, 1.38904, 1.47383, 1.90667, 2.39013,
+ 0.966952, 1.07554, 1.28815, 1.4051, 2.06186, 2.45199,
+ 0.90153, 1.19448, 1.35473, 1.70575, 2.32503, 2.43481,
+ 1.03842, 1.29243, 1.52731, 1.90984, 2.23033, 2.46514,
+ 1.33601, 1.44169, 1.84913, 2.20803, 2.4144, 2.53251,
+ 1.43622, 1.64565, 2.00864, 2.19816, 2.50228, 2.60141,
+ 1.42434, 1.68443, 1.92981, 2.1225, 2.51228, 2.60486,
+ 1.4522, 1.72299, 1.96221, 2.15666, 2.4841, 2.58459,
+ 1.482, 1.73524, 1.97119, 2.2228, 2.51231, 2.62362,
+ 1.39256, 1.72127, 1.9403, 2.17497, 2.48894, 2.60185,
+ 1.24335, 1.55846, 1.80982, 1.99089, 2.38197, 2.53748,
+ 1.19929, 1.4215, 1.76311, 1.99088, 2.35892, 2.48956,
+ 1.21777, 1.34878, 1.71467, 1.91684, 2.37973, 2.45696,
+ 1.21952, 1.32685, 1.71966, 1.83808, 2.29933, 2.43541,
+ 1.26307, 1.35366, 1.78723, 1.91897, 2.32039, 2.44825,
+ 1.27096, 1.3738, 1.71818, 1.85793, 2.36692, 2.48175,
+ 1.28435, 1.36807, 1.79391, 1.89508, 2.35679, 2.5246,
+ 1.24479, 1.35366, 1.78295, 1.92869, 2.22572, 2.37995,
+ 1.26928, 1.36873, 1.71918, 1.90968, 2.26716, 2.49154,
+ 1.24931, 1.33819, 1.79992, 1.9171, 2.27469, 2.53322,
+ 1.1795, 1.25905, 1.80297, 1.92733, 2.22893, 2.50364,
+ 1.14096, 1.2459, 1.70866, 1.92379, 2.24346, 2.55734,
+ 1.06395, 1.20903, 1.73729, 1.94535, 2.3387, 2.57309,
+ 1.00347, 1.10916, 1.74513, 1.90219, 2.30844, 2.60161,
+ 0.937618, 1.07754, 1.7478, 1.86965, 2.20505, 2.57045,
+ 0.885099, 1.19245, 1.79054, 1.87616, 2.36031, 2.59811,
+ 0.803485, 0.966415, 1.76846, 1.92874, 2.19672, 2.53046,
+ 0.797205, 1.12072, 1.77658, 1.87857, 2.37036, 2.61434,
+ 0.831514, 1.05908, 1.8088, 1.90548, 2.44821, 2.57305,
+ 0.806597, 0.967446, 1.82939, 1.96368, 2.35863, 2.65324,
+ 0.699378, 0.851831, 1.73945, 1.93394, 2.51638, 2.65525,
+ 0.739203, 1.03399, 1.90211, 2.01033, 2.49415, 2.62982,
+ 0.945605, 1.07971, 1.79635, 2.03954, 2.58186, 2.69978,
+ 0.843512, 1.30486, 1.83545, 2.03683, 2.60022, 2.67783,
+ 0.970152, 1.41437, 1.85405, 1.95779, 2.59605, 2.66543,
+ 1.06728, 1.43854, 1.88843, 2.06709, 2.53102, 2.64318,
+ 1.11762, 1.56311, 1.88632, 2.21887, 2.53022, 2.62408,
+ 1.20966, 1.62691, 1.9437, 2.18743, 2.55509, 2.65867,
+ 1.33889, 1.81288, 2.03089, 2.3052, 2.56927, 2.66116,
+ 1.30337, 1.8401, 2.03598, 2.28675, 2.61423, 2.71336,
+ 1.19343, 1.72735, 1.9262, 2.1844, 2.57478, 2.63181,
+ 1.06351, 1.71719, 1.90366, 2.11905, 2.44481, 2.49767,
+ 1.06218, 1.18895, 1.81048, 2.04498, 2.32238, 2.57878,
+ 1.0732, 1.17756, 1.65473, 2.02326, 2.20037, 2.44287,
+ 1.02781, 1.16542, 1.66947, 1.85961, 2.20214, 2.46247,
+ 1.03558, 1.14824, 1.6049, 1.87255, 2.25785, 2.55168,
+ 1.00721, 1.13109, 1.57915, 1.96979, 2.33164, 2.50791,
+ 0.908594, 1.0056, 1.46327, 2.07237, 2.30436, 2.40736,
+ 0.981614, 1.12643, 1.28057, 1.88685, 2.10192, 2.48784,
+ 1.00676, 1.13256, 1.25309, 1.71832, 2.18925, 2.4366,
+ 0.89983, 1.15654, 1.26075, 1.69671, 2.11666, 2.2283,
+ 0.896996, 1.24655, 1.43687, 1.64519, 2.07364, 2.14913,
+ 0.965481, 1.06967, 1.44649, 1.94949, 2.09158, 2.29833,
+ 0.898113, 1.05877, 1.61756, 1.94155, 2.11357, 2.37474,
+ 0.769481, 1.15938, 1.59741, 1.95985, 2.28384, 2.4182,
+ 0.908091, 1.30534, 1.47357, 1.86255, 2.16415, 2.33109,
+ 0.924282, 1.33469, 1.5632, 2.04354, 2.40601, 2.51576,
+ 0.972939, 1.38197, 1.54999, 2.02124, 2.26849, 2.41933,
+ 1.03223, 1.48403, 1.62003, 1.95223, 2.26732, 2.48644,
+ 1.00523, 1.35469, 1.6202, 1.77792, 2.22307, 2.49757,
+ 1.07274, 1.24504, 1.66167, 1.81939, 2.2605, 2.4687,
+ 1.13447, 1.25048, 1.73703, 1.86897, 2.3032, 2.46643,
+ 1.14594, 1.29326, 1.72851, 1.95098, 2.35098, 2.50402,
+ 1.22636, 1.3298, 1.75078, 1.98214, 2.34784, 2.55303,
+ 1.2348, 1.32811, 1.69673, 2.06056, 2.43731, 2.5356,
+ 1.24713, 1.3605, 1.74295, 1.96135, 2.47408, 2.66845,
+ 1.23474, 1.32984, 1.68863, 1.91333, 2.44294, 2.6277,
+ 1.23043, 1.32664, 1.69759, 1.80604, 2.38147, 2.61854,
+ 1.18857, 1.27308, 1.70898, 1.969, 2.34068, 2.58896,
+ 1.20428, 1.33122, 1.83552, 2.14126, 2.46323, 2.58349,
+ 1.20237, 1.39722, 1.86375, 2.15516, 2.59973, 2.68119,
+ 1.21758, 1.3333, 1.7639, 1.99498, 2.60184, 2.68482,
+ 1.27237, 1.36445, 1.77635, 1.9521, 2.56342, 2.67617,
+ 1.33017, 1.43465, 1.82509, 1.93803, 2.57941, 2.6661,
+ 1.38355, 1.51477, 1.77471, 2.135, 2.52858, 2.61471,
+ 1.48823, 1.63125, 1.79594, 2.18059, 2.49779, 2.58593,
+ 1.49785, 1.59843, 1.7604, 1.98572, 2.53807, 2.62222,
+ 1.44651, 1.55569, 1.67548, 1.89962, 2.54707, 2.63713,
+ 1.42019, 1.65176, 1.88812, 2.20156, 2.49872, 2.62437,
+ 1.52485, 1.74892, 1.93948, 2.13259, 2.42662, 2.6043,
+ 1.58821, 1.78697, 1.96571, 2.12325, 2.41743, 2.57989,
+ 1.60305, 1.80525, 1.93272, 2.08806, 2.49088, 2.62847,
+ 1.52171, 1.85304, 1.96816, 2.19842, 2.53092, 2.59723,
+ 1.49631, 1.78581, 2.00198, 2.20617, 2.57416, 2.64528,
+ 1.4052, 1.50056, 1.90867, 2.17922, 2.54373, 2.64577,
+ 1.36955, 1.50131, 1.8488, 2.08986, 2.55112, 2.64362,
+ 1.39538, 1.48864, 1.8724, 2.02812, 2.53026, 2.59919,
+ 1.35458, 1.50897, 1.84888, 1.97668, 2.50493, 2.57936,
+ 1.32575, 1.41133, 1.83713, 1.97079, 2.50272, 2.58483,
+ 1.2645, 1.39044, 1.76476, 2.08734, 2.51928, 2.62504,
+ 1.2809, 1.35565, 1.79029, 1.99571, 2.50257, 2.58736,
+ 1.26744, 1.36084, 1.85803, 2.03563, 2.50938, 2.58487,
+ 1.2389, 1.48754, 1.78666, 2.08035, 2.48091, 2.58214,
+ 1.22871, 1.44114, 1.71596, 1.89333, 2.50707, 2.56513,
+ 1.16735, 1.39731, 1.67205, 1.92353, 2.43839, 2.52352,
+ 1.16923, 1.35681, 1.56743, 1.95038, 2.37895, 2.46801,
+ 1.24024, 1.4709, 1.62973, 2.02468, 2.37672, 2.45487,
+ 1.37086, 1.66529, 1.8315, 2.17643, 2.4864, 2.58657,
+ 1.51337, 1.65704, 1.96501, 2.29801, 2.53215, 2.62301,
+ 1.44694, 1.61268, 1.92909, 2.2323, 2.46621, 2.56515,
+ 1.43066, 1.66453, 1.88216, 2.23458, 2.42166, 2.52729,
+ 1.51155, 1.65893, 1.94404, 2.1985, 2.45195, 2.58835,
+ 1.53944, 1.74136, 2.11106, 2.22992, 2.43894, 2.61506,
+ 1.51095, 1.84689, 2.06179, 2.20245, 2.48411, 2.57263,
+ 1.36639, 1.61165, 2.07937, 2.26007, 2.46706, 2.58803,
+ 1.38358, 1.64134, 1.99735, 2.22615, 2.49144, 2.61163,
+ 1.38146, 1.7069, 1.96306, 2.12555, 2.5968, 2.68111,
+ 1.36003, 1.55825, 1.94966, 2.05483, 2.59957, 2.71455,
+ 1.37934, 1.49178, 1.9259, 2.04634, 2.53937, 2.69605,
+ 1.31327, 1.4694, 1.86311, 2.14175, 2.55396, 2.6681,
+ 1.20152, 1.563, 1.92503, 2.09301, 2.47661, 2.61441,
+ 0.965563, 1.66213, 1.8361, 2.07187, 2.53005, 2.57845,
+ 0.976435, 1.63512, 1.84473, 2.00512, 2.55308, 2.61415,
+ 1.09816, 1.54948, 1.82643, 1.90791, 2.49067, 2.62563,
+ 0.971599, 1.43193, 1.81819, 1.92319, 2.49384, 2.56812,
+ 0.881008, 1.27287, 1.90143, 1.95922, 2.51367, 2.59602,
+ 0.915929, 1.47877, 1.9557, 2.08255, 2.49435, 2.58578,
+ 1.00818, 1.57939, 1.8982, 2.13917, 2.47763, 2.55121,
+ 0.937399, 1.50757, 1.80391, 1.92259, 2.54605, 2.6373,
+ 0.848413, 1.35823, 1.78393, 1.90623, 2.47701, 2.58853,
+ 0.863404, 1.48863, 1.8355, 1.93003, 2.4655, 2.54532,
+ 0.844376, 1.62228, 1.8268, 2.04836, 2.49055, 2.54581,
+ 0.869731, 1.70503, 1.8547, 2.1116, 2.51701, 2.59345,
+ 0.862235, 1.62302, 1.89937, 2.02871, 2.52784, 2.5748,
+ 0.931658, 1.57634, 1.85361, 1.97512, 2.54224, 2.61479,
+ 0.848799, 1.58841, 1.8471, 1.9559, 2.53407, 2.58456,
+ 0.737814, 1.45722, 1.82999, 1.9662, 2.50127, 2.57945,
+ 0.786199, 1.10008, 1.86037, 1.96428, 2.41936, 2.56613,
+ 0.728962, 1.04084, 1.77382, 1.96373, 2.35695, 2.57887,
+ 0.733093, 1.14778, 1.78977, 1.90929, 2.34982, 2.4811,
+ 0.785959, 1.28024, 1.73049, 1.9267, 2.34691, 2.42248,
+ 0.784924, 1.44682, 1.66969, 1.93537, 2.36832, 2.4596,
+ 0.758523, 1.46692, 1.8059, 1.94659, 2.35221, 2.42634,
+ 0.767907, 1.54429, 1.76817, 2.00394, 2.23904, 2.38619,
+ 0.896374, 1.56207, 1.71693, 1.9033, 2.30824, 2.43058,
+ 0.83453, 1.50481, 1.73742, 1.91773, 2.40928, 2.49329,
+ 0.896027, 1.40695, 1.73003, 1.90333, 2.43125, 2.53972,
+ 1.03967, 1.36412, 1.80628, 1.94817, 2.44069, 2.55797,
+ 1.09345, 1.41236, 1.83372, 1.9401, 2.48965, 2.56445,
+ 1.19018, 1.38617, 1.8487, 1.9562, 2.48155, 2.58088,
+ 1.24316, 1.35042, 1.8118, 1.89359, 2.46758, 2.61352,
+ 1.22199, 1.30871, 1.81591, 1.91199, 2.41753, 2.601,
+ 1.22837, 1.34362, 1.76316, 1.8726, 2.39489, 2.58272,
+ 1.27839, 1.38971, 1.7385, 1.87027, 2.42085, 2.53285,
+ 1.21164, 1.40179, 1.71015, 1.81102, 2.36383, 2.48224,
+ 1.1615, 1.40068, 1.76667, 1.89174, 2.39261, 2.49592,
+ 1.11494, 1.40549, 1.71834, 1.92742, 2.35682, 2.46833,
+ 1.07468, 1.45296, 1.66872, 1.89809, 2.33653, 2.44346,
+ 1.00671, 1.35625, 1.62948, 1.84847, 2.31389, 2.42632,
+ 0.966452, 1.45792, 1.65469, 1.90639, 2.32006, 2.41834,
+ 0.939007, 1.51999, 1.66701, 1.98942, 2.39067, 2.48895,
+ 0.94684, 1.48398, 1.70109, 2.10557, 2.39144, 2.49007,
+ 0.909129, 1.50106, 1.66537, 2.00494, 2.2567, 2.38984,
+ 0.958919, 1.39061, 1.68008, 2.10716, 2.29725, 2.44084,
+ 1.46216, 1.58856, 1.80854, 2.10989, 2.26483, 2.41747,
+ 1.30164, 1.67381, 1.89252, 2.16811, 2.47756, 2.56162,
+ 1.15277, 1.52933, 1.78378, 2.01435, 2.44661, 2.56093,
+ 1.1287, 1.49302, 1.74816, 1.93027, 2.53067, 2.62159,
+ 1.16436, 1.49686, 1.76766, 1.87114, 2.60725, 2.68479,
+ 1.12271, 1.38051, 1.76224, 1.8756, 2.44152, 2.73281,
+ 1.17391, 1.54593, 1.8438, 1.93379, 2.12345, 2.62901,
+ 1.15544, 1.46581, 1.79388, 1.92855, 2.16855, 2.60961,
+ 1.14781, 1.48454, 1.81642, 1.90876, 2.26262, 2.70408,
+ 1.18587, 1.39352, 1.81185, 1.88111, 2.54429, 2.7359,
+ 1.1533, 1.45114, 1.8554, 1.88862, 2.60331, 2.73808,
+ 1.20885, 1.58236, 1.78486, 1.88009, 2.59648, 2.72788,
+ 1.19484, 1.5429, 1.91906, 2.02314, 2.55189, 2.63419,
+ 1.23033, 1.49206, 1.93722, 2.13361, 2.61573, 2.69023,
+ 1.25876, 1.58131, 1.98007, 2.13876, 2.59904, 2.69103,
+ 1.22069, 1.57296, 1.91721, 2.17754, 2.59959, 2.70201,
+ 1.25814, 1.55663, 1.87174, 2.13263, 2.58551, 2.67331,
+ 1.23377, 1.59824, 1.84996, 2.01367, 2.54286, 2.63448,
+ 1.26976, 1.56079, 1.86522, 2.07633, 2.52108, 2.61744,
+ 1.11656, 1.68088, 1.78169, 1.9205, 2.59221, 2.67584,
+ 1.04821, 1.663, 1.8174, 1.91517, 2.48459, 2.62308,
+ 0.954241, 1.61967, 1.81346, 1.88169, 2.55067, 2.63197,
+ 0.964363, 1.57975, 1.72871, 1.86213, 2.56757, 2.63633,
+ 1.29692, 1.64688, 1.88926, 2.06927, 2.32023, 2.48139,
+ 1.23277, 1.6196, 1.95547, 2.06656, 2.33528, 2.45651,
+ 1.23897, 1.35179, 1.87757, 2.16641, 2.31797, 2.47439,
+ 1.18029, 1.38835, 1.60745, 1.95083, 2.21086, 2.47772,
+ 1.124, 1.42354, 1.61732, 1.8268, 2.20607, 2.44408,
+ 1.14779, 1.48705, 1.62797, 1.92602, 2.27842, 2.48653,
+ 1.09265, 1.49972, 1.62304, 1.88016, 2.41166, 2.64865,
+ 1.11529, 1.46869, 1.60763, 1.81446, 2.3569, 2.57609,
+ 1.17604, 1.42463, 1.61423, 1.96634, 2.35268, 2.57035,
+ 1.21105, 1.46743, 1.61778, 1.85149, 2.38977, 2.59186,
+ 1.28768, 1.46486, 1.63379, 1.85623, 2.34975, 2.56532,
+ 1.29859, 1.49522, 1.639, 1.94264, 2.41539, 2.51812,
+ 1.30989, 1.43114, 1.75719, 1.97721, 2.41487, 2.52088,
+ 1.39224, 1.47741, 1.8113, 1.90969, 2.44042, 2.57389,
+ 1.41494, 1.51538, 1.859, 2.12794, 2.49067, 2.63542,
+ 1.49044, 1.56597, 1.95241, 2.04907, 2.49994, 2.60018,
+ 1.48507, 1.73412, 1.99737, 2.08938, 2.52477, 2.60816,
+ 1.50713, 1.7872, 2.0481, 2.12836, 2.53363, 2.62465,
+ 1.48522, 1.77259, 2.0481, 2.14437, 2.59574, 2.67979,
+ 1.56004, 1.74452, 2.07614, 2.15684, 2.61506, 2.69877,
+ 1.50628, 1.85545, 2.06419, 2.14453, 2.58566, 2.68779,
+ 1.59288, 1.90345, 2.08453, 2.16339, 2.4969, 2.63359,
+ 1.60945, 1.87086, 2.11982, 2.18659, 2.5995, 2.69782,
+ 1.59478, 1.85535, 2.02562, 2.14254, 2.5723, 2.63784,
+ 1.52719, 1.71409, 2.07627, 2.18517, 2.52655, 2.63114,
+ 1.51801, 1.62801, 2.03926, 2.13453, 2.45384, 2.57636,
+ 1.53131, 1.67808, 2.03518, 2.14689, 2.50486, 2.58417,
+ 1.50863, 1.63261, 1.96514, 2.14868, 2.49664, 2.59275,
+ 1.4999, 1.59942, 1.91369, 2.03686, 2.45019, 2.53817,
+ 1.48116, 1.58381, 1.88446, 2.01387, 2.3595, 2.4811,
+ 1.47574, 1.5697, 1.79999, 1.91618, 2.32922, 2.5359,
+ 1.49864, 1.6236, 1.79282, 1.94522, 2.35863, 2.49073,
+ 1.43113, 1.57463, 1.74326, 2.00612, 2.34776, 2.5089,
+ 1.42706, 1.53658, 1.79069, 1.94303, 2.34447, 2.45265,
+ 1.43684, 1.54202, 1.75892, 1.92562, 2.24291, 2.41684,
+ 1.41979, 1.50904, 1.86332, 1.9954, 2.27579, 2.42473,
+ 1.4244, 1.51048, 1.88289, 2.17902, 2.30471, 2.45567,
+ 1.36605, 1.46119, 1.93532, 2.14755, 2.26342, 2.46579,
+ 1.4074, 1.56497, 1.98112, 2.10344, 2.44529, 2.5651,
+ 1.59701, 1.87701, 2.0685, 2.27031, 2.49936, 2.60489,
+ 1.48498, 1.81813, 2.14982, 2.33759, 2.50475, 2.58944,
+ 1.48788, 1.93718, 2.11827, 2.30837, 2.51178, 2.60463,
+ 1.6823, 1.97703, 2.19229, 2.37368, 2.52293, 2.61128,
+ 1.74946, 1.90568, 2.21827, 2.35201, 2.57423, 2.68148,
+ 1.67622, 1.93651, 2.23718, 2.34378, 2.53591, 2.66127,
+ 1.72336, 1.98992, 2.27124, 2.41314, 2.55083, 2.64937,
+ 1.75601, 1.99691, 2.31266, 2.46148, 2.62542, 2.70874,
+ 1.49977, 1.7633, 2.15887, 2.34688, 2.59272, 2.68285,
+ 1.74752, 1.92713, 2.24894, 2.41084, 2.60412, 2.69088,
+ 1.67035, 1.93826, 2.24767, 2.44713, 2.65754, 2.73004,
+ 1.66924, 1.95961, 2.17932, 2.44053, 2.58843, 2.6408,
+ 1.78023, 2.01514, 2.16481, 2.39902, 2.58191, 2.64694,
+ 1.73956, 1.96722, 2.06569, 2.36448, 2.58998, 2.64944,
+ 1.60501, 1.87511, 2.0189, 2.2274, 2.54118, 2.60354,
+ 1.51125, 1.8926, 2.02783, 2.14811, 2.52, 2.6082,
+ 1.36336, 1.56877, 1.91085, 2.05769, 2.46351, 2.55882,
+ 1.3385, 1.48382, 1.8837, 2.06707, 2.44895, 2.5779,
+ 1.36919, 1.43786, 1.84522, 2.07846, 2.4285, 2.61589,
+ 1.3777, 1.49829, 1.86767, 2.16496, 2.49255, 2.57091,
+ 1.4081, 1.48776, 1.87241, 2.09795, 2.44727, 2.55172,
+ 1.40236, 1.53195, 1.89769, 2.12667, 2.41916, 2.55144,
+ 1.4565, 1.55463, 1.84107, 2.09581, 2.42129, 2.56176,
+ 1.43493, 1.52915, 1.79534, 2.1637, 2.44647, 2.53031,
+ 1.39111, 1.4955, 1.86968, 2.16123, 2.38141, 2.53202,
+ 1.38893, 1.53447, 1.797, 2.10294, 2.39851, 2.52127,
+ 1.35857, 1.4713, 1.76005, 2.10088, 2.3502, 2.54655,
+ 1.2766, 1.51921, 1.77942, 2.09582, 2.44294, 2.66594,
+ 1.20666, 1.45786, 1.76046, 2.24428, 2.49588, 2.64485,
+ 1.21461, 1.46027, 1.97902, 2.23945, 2.39832, 2.63447,
+ 1.27547, 1.47347, 1.87857, 2.20312, 2.47503, 2.68785,
+ 1.29171, 1.39929, 1.81381, 2.19412, 2.50276, 2.61489,
+ 1.26006, 1.398, 1.92489, 2.18672, 2.51167, 2.64455,
+ 1.21063, 1.32671, 1.89759, 2.10744, 2.46008, 2.71172,
+ 1.20266, 1.31923, 1.89263, 2.07986, 2.37942, 2.67989,
+ 0.967019, 1.10597, 1.76132, 2.10743, 2.32843, 2.59315,
+ 0.947746, 1.0358, 1.39373, 2.06123, 2.30074, 2.66828,
+ 0.996167, 1.21503, 1.37899, 1.86198, 2.32966, 2.60502,
+ 1.00882, 1.19848, 1.31384, 1.69352, 2.36075, 2.60482,
+ 1.05406, 1.21851, 1.36811, 1.73801, 2.17491, 2.54607,
+ 1.02157, 1.13399, 1.36917, 1.93564, 2.2678, 2.54441,
+ 1.03374, 1.22777, 1.45129, 2.00592, 2.41262, 2.59503,
+ 1.06516, 1.16864, 1.53018, 2.0615, 2.41074, 2.48548,
+ 1.12123, 1.28128, 1.43223, 1.90993, 2.20273, 2.50931,
+ 1.17003, 1.30604, 1.49495, 1.98191, 2.20282, 2.35174,
+ 1.15263, 1.26619, 1.621, 2.05767, 2.21445, 2.38164,
+ 1.22813, 1.31327, 1.75147, 2.11847, 2.26342, 2.45389,
+ 1.30783, 1.39865, 1.79975, 2.12574, 2.26062, 2.4518,
+ 1.3601, 1.47744, 1.83574, 2.12187, 2.29156, 2.49979,
+ 1.39848, 1.49297, 1.80652, 2.10714, 2.24141, 2.43415,
+ 1.35121, 1.46251, 1.72639, 2.12239, 2.28579, 2.42184,
+ 1.2972, 1.49887, 1.76625, 2.15784, 2.37671, 2.49716,
+ 1.37735, 1.51897, 1.80379, 2.19115, 2.35637, 2.4789,
+ 1.28917, 1.55324, 1.67459, 2.11263, 2.40335, 2.47388,
+ 1.18897, 1.70034, 1.83432, 2.05558, 2.59953, 2.70041,
+ 1.07704, 1.66767, 1.90219, 2.04569, 2.60291, 2.70006,
+ 1.07206, 1.27246, 1.84374, 1.90118, 2.58625, 2.72056,
+ 1.08439, 1.39207, 1.82356, 1.9013, 2.58943, 2.68003,
+ 1.10632, 1.44136, 1.76614, 1.85372, 2.54936, 2.62741,
+ 1.09457, 1.55002, 1.77192, 1.87095, 2.55968, 2.62805,
+ 1.0419, 1.59855, 1.8137, 1.92849, 2.54563, 2.6715,
+ 1.0902, 1.61051, 1.81256, 2.01926, 2.55632, 2.60879,
+ 1.01653, 1.62666, 1.74241, 2.04192, 2.54154, 2.60225,
+ 1.07557, 1.64775, 1.87067, 2.07397, 2.5746, 2.6288,
+ 1.12666, 1.58621, 1.79257, 1.98241, 2.62918, 2.72556,
+ 1.02778, 1.54267, 1.8314, 1.95688, 2.60301, 2.66852,
+ 1.1119, 1.54342, 1.86147, 1.94292, 2.62196, 2.67286,
+ 1.08051, 1.58319, 1.8573, 1.95846, 2.6336, 2.69514,
+ 1.13224, 1.44916, 1.88495, 1.977, 2.60785, 2.70942,
+ 1.23277, 1.6126, 1.96044, 2.07169, 2.64468, 2.72712,
+ 1.32501, 1.7799, 1.9673, 2.11387, 2.54784, 2.66872,
+ 1.40459, 1.64445, 2.05809, 2.25711, 2.51912, 2.63461,
+ 1.41349, 1.6094, 2.00252, 2.1841, 2.58753, 2.69615,
+ 1.35402, 1.59388, 2.01444, 2.1222, 2.61725, 2.72181,
+ 1.37382, 1.65676, 1.99218, 2.18987, 2.54872, 2.70251,
+ 1.42118, 1.61108, 1.95807, 2.12362, 2.56983, 2.64814,
+ 1.37918, 1.6202, 1.92264, 2.09395, 2.55069, 2.64186,
+ 1.36773, 1.65667, 1.83845, 1.99212, 2.59623, 2.65404,
+ 1.39455, 1.75062, 1.87227, 2.03843, 2.55322, 2.62359,
+ 1.46402, 1.74159, 1.91299, 2.15026, 2.56559, 2.64882,
+ 1.46113, 1.80906, 1.95461, 2.2099, 2.57028, 2.64252,
+ 1.43452, 1.77083, 1.90402, 2.21731, 2.63118, 2.687,
+ 1.37553, 1.63166, 1.886, 2.08659, 2.6005, 2.67126,
+ 1.33921, 1.56872, 1.81737, 2.08557, 2.59134, 2.66646,
+ 1.5044, 1.77959, 2.05714, 2.27244, 2.5346, 2.63465,
+ 1.4745, 1.74632, 2.04471, 2.13738, 2.47455, 2.63053,
+ 1.55704, 1.75502, 2.03966, 2.08094, 2.66134, 2.74174,
+ 1.57345, 1.71536, 2.05673, 2.09837, 2.69164, 2.74369,
+ 1.51143, 1.83189, 1.99159, 2.15604, 2.62435, 2.70952,
+ 1.50191, 1.71403, 2.01293, 2.07943, 2.55466, 2.69041,
+ 1.54718, 1.67191, 1.97797, 2.10406, 2.50716, 2.61481,
+ 1.56326, 1.63597, 1.99013, 2.12372, 2.56382, 2.63319,
+ 1.58777, 1.69779, 2.00754, 2.12736, 2.58884, 2.65654,
+ 1.6183, 1.72223, 2.00849, 2.13128, 2.61817, 2.68764,
+ 1.58008, 1.68493, 2.00065, 2.08783, 2.61398, 2.68767,
+ 1.57278, 1.73632, 1.96154, 2.14435, 2.64125, 2.68794,
+ 1.53899, 1.65285, 1.95211, 2.15604, 2.6393, 2.68573,
+ 1.53713, 1.6228, 1.96353, 2.07594, 2.6122, 2.67933,
+ 1.53745, 1.63325, 1.98652, 2.07568, 2.54279, 2.6438,
+ 1.54323, 1.77202, 2.05391, 2.14247, 2.53641, 2.69049,
+ 1.6218, 1.83, 2.05274, 2.21086, 2.58321, 2.66584,
+ 1.60957, 1.93532, 2.14668, 2.39332, 2.59721, 2.67056,
+ 1.56082, 1.93554, 2.19144, 2.44438, 2.60992, 2.6926,
+ 1.70428, 1.87459, 2.01026, 2.3801, 2.52866, 2.6048,
+ 1.62478, 1.83779, 1.92536, 2.19301, 2.49717, 2.56943,
+ 1.55613, 1.83265, 1.98694, 2.18932, 2.4532, 2.53163,
+ 1.34743, 1.66967, 1.94393, 2.10805, 2.50663, 2.60842,
+ 1.27841, 1.49725, 1.83841, 2.07392, 2.45455, 2.59232,
+ 1.27105, 1.41512, 1.75811, 2.23246, 2.42277, 2.55467,
+ 1.26034, 1.35671, 1.91317, 2.22589, 2.3806, 2.55725,
+ 1.2231, 1.30797, 1.78409, 2.20752, 2.36287, 2.48779,
+ 1.24945, 1.53816, 1.7166, 1.99832, 2.36211, 2.46553,
+ 1.20801, 1.50306, 1.7613, 1.91708, 2.44805, 2.52513,
+ 1.15185, 1.46115, 1.78394, 1.94689, 2.45256, 2.55631,
+ 1.16556, 1.34777, 1.79995, 1.92075, 2.43788, 2.54695,
+ 1.10979, 1.31045, 1.81589, 1.92338, 2.4273, 2.6028,
+ 1.09199, 1.23364, 1.78961, 1.92504, 2.4678, 2.61117,
+ 1.05232, 1.19475, 1.8099, 1.91423, 2.39018, 2.55632,
+ 1.03227, 1.18949, 1.77562, 1.88969, 2.39325, 2.64083,
+ 0.992854, 1.16963, 1.81416, 1.91225, 2.32027, 2.63432,
+ 1.05441, 1.17775, 1.76276, 1.9072, 2.26618, 2.5163,
+ 1.02954, 1.16736, 1.78006, 1.97354, 2.22784, 2.61389,
+ 1.06778, 1.18481, 1.74132, 1.91913, 2.12196, 2.50079,
+ 1.16784, 1.26305, 1.77863, 1.90072, 2.15081, 2.56866,
+ 1.24703, 1.32367, 1.81105, 1.93459, 2.18402, 2.67462,
+ 1.33178, 1.42614, 1.78514, 1.96603, 2.11456, 2.54183,
+ 1.3609, 1.44414, 1.86253, 1.94975, 2.42674, 2.64611,
+ 1.40854, 1.45179, 1.86692, 2.01423, 2.47884, 2.70591,
+ 1.40555, 1.48355, 1.87498, 1.96029, 2.50276, 2.66254,
+ 1.44237, 1.54466, 1.88335, 1.98759, 2.56298, 2.64776,
+ 1.48072, 1.5362, 1.88182, 2.01887, 2.58235, 2.66179,
+ 1.51308, 1.58325, 1.89576, 1.98715, 2.58617, 2.67601,
+ 1.49776, 1.60209, 1.83101, 1.9854, 2.56409, 2.64364,
+ 1.49706, 1.56491, 1.84464, 1.9577, 2.53993, 2.67716,
+ 1.46811, 1.52375, 1.86584, 1.94008, 2.60797, 2.68486,
+ 1.4681, 1.56439, 1.85892, 1.9824, 2.60648, 2.70969,
+ 1.42273, 1.5192, 1.80679, 1.89159, 2.61482, 2.70389,
+ 1.39687, 1.4767, 1.7764, 2.01325, 2.60785, 2.66599,
+ 1.39153, 1.50457, 1.83054, 2.08154, 2.61102, 2.72081,
+ 1.37288, 1.64506, 1.83336, 2.01576, 2.63134, 2.70134,
+ 1.33129, 1.7474, 1.89795, 2.14651, 2.58668, 2.65827,
+ 1.50318, 1.73469, 1.915, 2.28209, 2.59839, 2.67919,
+ 1.46524, 1.71176, 2.02517, 2.28408, 2.65366, 2.71739,
+ 1.4234, 1.76876, 2.08441, 2.27788, 2.63644, 2.71152,
+ 1.42382, 1.72447, 2.03259, 2.30031, 2.60334, 2.68611,
+ 1.43318, 1.81887, 2.05388, 2.40924, 2.6286, 2.69946,
+ 1.50985, 1.79349, 2.05264, 2.35777, 2.64413, 2.71806,
+ 1.57573, 1.85153, 2.03296, 2.3749, 2.58353, 2.66224,
+ 1.50126, 1.78083, 1.99855, 2.32927, 2.5056, 2.60674,
+ 1.46006, 1.76321, 1.91233, 2.21442, 2.49433, 2.57762,
+ 1.44404, 1.65767, 1.89536, 2.14855, 2.47846, 2.59545,
+ 1.45429, 1.61986, 1.93589, 2.18975, 2.47883, 2.59488,
+ 1.37724, 1.64218, 1.91967, 2.14284, 2.42151, 2.54104,
+ 1.05106, 1.42102, 1.8304, 2.02122, 2.37369, 2.54883,
+ 0.964571, 1.07164, 1.3949, 2.1512, 2.37178, 2.46495,
+ 0.966306, 1.18103, 1.30221, 2.01482, 2.37509, 2.43513,
+ 0.89556, 1.20784, 1.33531, 1.82392, 2.23992, 2.3631,
+ 1.00678, 1.20309, 1.31782, 1.87398, 2.33664, 2.40878,
+ 1.05413, 1.22559, 1.37901, 2.02469, 2.33331, 2.42155,
+ 1.0902, 1.22477, 1.40967, 2.0132, 2.24536, 2.35323,
+ 1.07648, 1.20397, 1.56389, 2.03395, 2.20336, 2.3691,
+ 1.12797, 1.24913, 1.66469, 2.08043, 2.25662, 2.46954,
+ 1.20201, 1.42968, 1.79368, 2.08071, 2.33998, 2.46005,
+ 1.51722, 1.6739, 1.92792, 2.20364, 2.38676, 2.52014,
+ 1.58662, 1.78624, 2.04167, 2.199, 2.41637, 2.58119,
+ 1.5933, 1.80855, 2.14878, 2.25028, 2.37209, 2.53241,
+ 1.65729, 1.78346, 2.15039, 2.25813, 2.45392, 2.61621,
+ 1.57149, 1.79266, 2.11765, 2.35038, 2.57719, 2.66695,
+ 1.30199, 1.72975, 1.97442, 2.09325, 2.5939, 2.66302,
+ 1.10022, 1.5634, 1.91991, 2.05922, 2.56297, 2.63776,
+ 1.02507, 1.54074, 1.8119, 2.05791, 2.49188, 2.60325,
+ 1.01531, 1.4735, 1.80259, 2.01308, 2.43676, 2.60532,
+ 1.02207, 1.15848, 1.68979, 2.18353, 2.38378, 2.49237,
+ 1.21248, 1.45311, 1.82395, 2.06144, 2.39619, 2.53658,
+ 1.12624, 1.45293, 1.80959, 2.07107, 2.40894, 2.54956,
+ 0.880332, 1.32478, 1.62134, 1.96725, 2.31316, 2.42693,
+ 0.749583, 1.35841, 1.57507, 1.87059, 2.27923, 2.37743,
+ 0.901917, 1.29022, 1.67443, 1.95441, 2.23336, 2.39152,
+ 0.850971, 1.2521, 1.65765, 1.81646, 2.18389, 2.32881,
+ 0.88148, 1.2841, 1.69816, 1.84466, 2.34182, 2.44091,
+ 0.874499, 1.18268, 1.70949, 1.91745, 2.36597, 2.49965,
+ 0.833751, 1.23113, 1.80332, 1.91802, 2.45909, 2.54688,
+ 0.85097, 1.12709, 1.77207, 1.85522, 2.48758, 2.58286,
+ 0.88165, 1.1148, 1.8207, 1.95908, 2.52175, 2.59873,
+ 0.803558, 1.15029, 1.79848, 1.95267, 2.53892, 2.6349,
+ 0.867833, 0.990496, 1.83228, 1.92977, 2.54766, 2.68108,
+ 0.865057, 1.06744, 1.77326, 1.86019, 2.55833, 2.70222,
+ 0.832529, 0.98596, 1.75637, 1.86293, 2.43828, 2.62378,
+ 0.850804, 1.06055, 1.89222, 1.98401, 2.48377, 2.66112,
+ 0.873803, 1.04198, 1.7462, 1.93244, 2.33822, 2.55458,
+ 0.958594, 1.10347, 1.83644, 1.93678, 2.39376, 2.5732,
+ 1.01483, 1.14087, 1.82593, 2.01371, 2.40149, 2.60942,
+ 1.07537, 1.45764, 1.90046, 2.03349, 2.31419, 2.49095,
+ 1.20171, 1.73617, 1.91408, 2.0665, 2.38691, 2.47696,
+ 1.21522, 1.87361, 2.0659, 2.18299, 2.37498, 2.48955,
+ 1.62021, 1.85126, 2.11154, 2.3428, 2.52749, 2.63389,
+ 1.68388, 1.86037, 2.12601, 2.40434, 2.56298, 2.63616,
+ 1.70382, 1.93438, 2.13367, 2.39321, 2.60193, 2.68247,
+ 1.52688, 1.90013, 2.1511, 2.36164, 2.57517, 2.65898,
+ 1.58725, 1.88139, 2.12995, 2.26786, 2.57786, 2.65784,
+ 1.53916, 1.87134, 2.19028, 2.36038, 2.62461, 2.70564,
+ 1.62575, 1.86218, 2.12009, 2.33946, 2.59216, 2.68214,
+ 1.67953, 1.92069, 2.16117, 2.31711, 2.6489, 2.71211,
+ 1.6352, 1.92283, 2.17484, 2.4074, 2.63005, 2.70927,
+ 1.45419, 1.9757, 2.15185, 2.37134, 2.60918, 2.68579,
+ 1.67244, 2.0114, 2.18302, 2.46392, 2.65296, 2.71152,
+ 1.61211, 1.98748, 2.10258, 2.29335, 2.61613, 2.67026,
+ 1.52807, 1.89507, 2.05358, 2.2325, 2.54491, 2.62412,
+ 1.42035, 1.6835, 1.96343, 2.15942, 2.53673, 2.62013,
+ 1.45632, 1.69313, 1.96923, 2.16474, 2.58716, 2.67759,
+ 1.48111, 1.63754, 1.99264, 2.17848, 2.54814, 2.63276,
+ 1.48852, 1.59117, 2.0165, 2.12332, 2.52866, 2.61492,
+ 1.47743, 1.65152, 1.96289, 2.10218, 2.5433, 2.61884,
+ 1.47386, 1.6223, 1.99223, 2.08035, 2.57269, 2.64443,
+ 1.47822, 1.6334, 1.9312, 2.06413, 2.55228, 2.62934,
+ 1.45248, 1.67676, 1.94591, 2.08475, 2.60097, 2.66889,
+ 1.41156, 1.70618, 1.89025, 2.16962, 2.56732, 2.65016,
+ 1.3834, 1.66463, 1.80326, 2.10861, 2.59577, 2.64622,
+ 1.4346, 1.64501, 1.87175, 2.11549, 2.52896, 2.66026,
+ 1.44454, 1.58183, 1.89864, 2.09407, 2.52845, 2.6315,
+ 1.46556, 1.562, 1.84142, 2.0516, 2.55994, 2.63232,
+ 1.49929, 1.58105, 1.85745, 2.09899, 2.5116, 2.60434,
+ 1.52868, 1.65135, 1.87131, 2.07123, 2.56255, 2.62246,
+ 1.51447, 1.63348, 1.7786, 2.1235, 2.6061, 2.66239,
+ 1.30148, 1.68391, 1.79606, 2.17075, 2.64495, 2.69178,
+ 1.15442, 1.62694, 1.74922, 1.99641, 2.57924, 2.6529,
+ 1.11791, 1.56927, 1.79538, 1.8853, 2.37672, 2.73973,
+ 1.25179, 1.62567, 1.83926, 1.99131, 2.35012, 2.65505,
+ 1.41213, 1.69423, 1.83936, 1.9984, 2.44522, 2.73968,
+ 1.37016, 1.68726, 1.87973, 2.00645, 2.32901, 2.63296,
+ 1.17478, 1.72905, 1.88737, 2.01391, 2.25939, 2.55774,
+ 1.31792, 1.73704, 1.87808, 1.97931, 2.17536, 2.63486,
+ 1.14013, 1.58645, 1.93222, 2.02771, 2.23684, 2.48495,
+ 1.10014, 1.6001, 1.85129, 1.97238, 2.60483, 2.64945,
+ 1.11197, 1.52598, 1.84271, 2.01149, 2.6016, 2.66939,
+ 1.08082, 1.49258, 1.81023, 1.96531, 2.55673, 2.64517,
+ 1.12935, 1.6359, 1.78518, 2.1374, 2.498, 2.57252,
+ 1.00359, 1.60301, 1.7227, 2.1394, 2.43159, 2.511,
+ 1.12017, 1.42515, 1.67568, 2.05077, 2.34325, 2.46068,
+ 1.32861, 1.59915, 1.87358, 2.17045, 2.47054, 2.61353,
+ 1.38209, 1.59534, 1.92346, 2.08211, 2.34955, 2.51075,
+ 1.46619, 1.57286, 1.87047, 2.18, 2.34634, 2.47187,
+ 1.37977, 1.63301, 1.80827, 2.16629, 2.39872, 2.49247,
+ 1.30592, 1.61002, 1.85641, 2.00154, 2.39067, 2.53391,
+ 1.38309, 1.58681, 1.75722, 1.9348, 2.43354, 2.58795,
+ 1.30751, 1.45094, 1.67533, 2.03394, 2.24423, 2.41812,
+ 1.1915, 1.48407, 1.75027, 2.09664, 2.24938, 2.50498,
+ 1.24138, 1.49179, 1.77688, 2.07173, 2.36793, 2.50807,
+ 1.2657, 1.45992, 1.78175, 2.0099, 2.34858, 2.51604,
+ 1.27951, 1.41465, 1.7951, 2.05594, 2.3957, 2.53054,
+ 1.33734, 1.44593, 1.85301, 2.07518, 2.38598, 2.53549,
+ 1.28897, 1.42471, 1.79799, 2.02629, 2.2998, 2.42371,
+ 1.36528, 1.47179, 1.80171, 1.9377, 2.3453, 2.4667,
+ 1.35379, 1.44775, 1.73621, 1.86889, 2.27436, 2.47558,
+ 1.36086, 1.44961, 1.68047, 1.80265, 2.39554, 2.51326,
+ 1.38833, 1.52625, 1.67333, 1.90987, 2.38502, 2.53543,
+ 1.42443, 1.54422, 1.7202, 1.93624, 2.30797, 2.49142,
+ 1.44894, 1.55201, 1.79794, 1.93752, 2.40687, 2.54612,
+ 1.43203, 1.52162, 1.79932, 2.02144, 2.47733, 2.57175,
+ 1.46309, 1.54628, 1.83442, 2.06349, 2.4898, 2.59527,
+ 1.42547, 1.55643, 1.90472, 2.11082, 2.46637, 2.58756,
+ 1.38484, 1.56941, 1.92558, 2.07237, 2.56129, 2.64054,
+ 1.41849, 1.53942, 1.93754, 2.01432, 2.6092, 2.67676,
+ 1.39701, 1.48328, 1.93673, 1.97775, 2.59561, 2.73585,
+ 1.33562, 1.44187, 1.88474, 1.99496, 2.58963, 2.69575,
+ 1.35749, 1.519, 1.8716, 1.9802, 2.62902, 2.7003,
+ 1.35356, 1.52432, 1.89108, 1.96371, 2.59581, 2.67933,
+ 1.2951, 1.63928, 1.90739, 2.10314, 2.58336, 2.67978,
+ 1.45554, 1.66759, 1.9532, 2.24049, 2.57067, 2.67362,
+ 1.46028, 1.78665, 1.99775, 2.28513, 2.58293, 2.67762,
+ 1.54312, 1.72939, 2.15567, 2.28027, 2.65558, 2.74425,
+ 1.43444, 1.74878, 2.0422, 2.20129, 2.6065, 2.69586,
+ 1.43608, 1.74734, 2.06784, 2.25326, 2.57594, 2.67908,
+ 1.47087, 1.69825, 2.08313, 2.25757, 2.56534, 2.66619,
+ 1.41742, 1.69344, 2.05319, 2.24354, 2.54484, 2.6328,
+ 1.41211, 1.68159, 2.0818, 2.3261, 2.47245, 2.57058,
+ 1.39723, 1.76474, 2.03156, 2.29712, 2.47165, 2.57588,
+ 1.4665, 1.6943, 2.00592, 2.20633, 2.53451, 2.63576,
+ 1.43711, 1.74657, 1.92384, 2.12785, 2.35663, 2.46448,
+ 1.32402, 1.59792, 1.75778, 2.12435, 2.34799, 2.44047,
+ 1.37539, 1.62639, 1.77807, 2.0684, 2.25894, 2.39753,
+ 1.37958, 1.62179, 1.85796, 1.99428, 2.30609, 2.47721,
+ 1.41641, 1.64889, 1.86912, 2.09836, 2.3454, 2.47513,
+ 1.42624, 1.6392, 1.9254, 2.07268, 2.44895, 2.53255,
+ 1.45905, 1.61587, 1.91117, 2.12546, 2.4837, 2.59209,
+ 1.45943, 1.6907, 1.85242, 2.13607, 2.5294, 2.5972,
+ 1.48514, 1.57805, 1.81057, 2.15062, 2.55904, 2.61824,
+ 1.52905, 1.59466, 1.7389, 2.26122, 2.59577, 2.65162,
+ 1.53249, 1.58533, 1.82094, 2.22962, 2.62316, 2.65848,
+ 1.3744, 1.52808, 1.84802, 2.04246, 2.45823, 2.59109,
+ 1.39987, 1.59747, 1.85308, 2.09608, 2.4316, 2.55685,
+ 1.45743, 1.60951, 1.93076, 2.1861, 2.39229, 2.52506,
+ 1.44051, 1.60759, 1.86998, 2.15828, 2.42428, 2.55553,
+ 1.37676, 1.47479, 1.75056, 2.19062, 2.40618, 2.54712,
+ 1.32771, 1.45424, 1.64463, 2.11036, 2.35245, 2.45593,
+ 1.3028, 1.41895, 1.60978, 2.09312, 2.26349, 2.39325,
+ 1.20771, 1.37987, 1.53641, 2.05993, 2.3173, 2.4554,
+ 1.15421, 1.30297, 1.49921, 2.07038, 2.3222, 2.63083,
+ 1.11147, 1.22442, 1.62564, 2.17608, 2.34255, 2.60619,
+ 0.945723, 1.0833, 1.62541, 2.21453, 2.3899, 2.51008,
+ 0.992344, 1.11699, 1.45192, 2.00842, 2.31359, 2.43786,
+ 1.11731, 1.39299, 1.71346, 2.13231, 2.27682, 2.49761,
+ 1.33287, 1.58093, 1.89551, 2.129, 2.4251, 2.57695,
+ 1.32204, 1.49774, 1.81922, 2.12864, 2.44361, 2.56795,
+ 1.36194, 1.54738, 1.79097, 2.06294, 2.46532, 2.54609,
+ 1.25268, 1.48388, 1.75863, 2.03345, 2.41628, 2.53922,
+ 1.09938, 1.34475, 1.68653, 2.01675, 2.35586, 2.53084,
+ 1.12611, 1.26362, 1.64994, 1.99154, 2.30909, 2.51489,
+ 1.19062, 1.28965, 1.69271, 2.00948, 2.16009, 2.41707,
+ 1.17498, 1.41431, 1.79786, 1.9876, 2.27882, 2.49276,
+ 1.20535, 1.48205, 1.85076, 2.02555, 2.34228, 2.52343,
+ 1.24803, 1.56119, 1.85276, 2.09645, 2.42836, 2.55187,
+ 1.26073, 1.60183, 1.90105, 2.13198, 2.40985, 2.56555,
+ 1.26504, 1.69384, 2.00053, 2.20004, 2.50351, 2.61771,
+ 1.27884, 1.73826, 2.06202, 2.28998, 2.60444, 2.67811,
+ 1.33943, 1.73592, 2.05012, 2.35241, 2.59739, 2.68822,
+ 1.30106, 1.70875, 1.96598, 2.28621, 2.54671, 2.65318,
+ 1.2786, 1.74616, 1.95007, 2.21477, 2.60579, 2.68762,
+ 1.18377, 1.52306, 1.87912, 2.00491, 2.60031, 2.69049,
+ 1.18622, 1.34213, 1.81783, 1.94008, 2.5049, 2.65925,
+ 1.17939, 1.24368, 1.89426, 1.97975, 2.55802, 2.72182,
+ 1.17562, 1.35704, 1.85319, 1.94081, 2.64681, 2.70566,
+ 1.21112, 1.36964, 1.82525, 1.91329, 2.63472, 2.71226,
+ 1.16947, 1.34515, 1.76494, 1.88367, 2.59108, 2.71452,
+ 1.22209, 1.38948, 1.80018, 1.9359, 2.57377, 2.70292,
+ 1.28727, 1.37591, 1.87874, 1.98605, 2.626, 2.70847,
+ 1.29971, 1.3896, 1.8739, 1.94272, 2.53348, 2.69147,
+ 1.27136, 1.4242, 1.84985, 1.95357, 2.55556, 2.65237,
+ 1.25357, 1.44851, 1.82953, 1.9191, 2.48784, 2.63076,
+ 1.22392, 1.32302, 1.84126, 1.93273, 2.22685, 2.57072,
+ 1.22617, 1.32139, 1.77179, 1.94807, 2.13788, 2.56305,
+ 1.31624, 1.39947, 1.78933, 1.96557, 2.13204, 2.42471,
+ 1.26439, 1.36395, 1.73553, 2.0056, 2.15584, 2.41892,
+ 1.21403, 1.31978, 1.66202, 1.90295, 2.06463, 2.42483,
+ 1.2426, 1.34231, 1.62476, 1.92942, 2.08355, 2.31844,
+ 1.24161, 1.43912, 1.64633, 1.81792, 1.99776, 2.19663,
+ 1.23935, 1.33692, 1.77706, 2.02801, 2.15585, 2.3287,
+ 1.17842, 1.26633, 1.80204, 1.95982, 2.1457, 2.46951,
+ 1.2477, 1.32863, 1.81269, 1.99279, 2.20064, 2.49944,
+ 1.27008, 1.37091, 1.88227, 1.99723, 2.25428, 2.52605,
+ 1.29555, 1.37642, 1.86044, 2.07673, 2.249, 2.56712,
+ 1.30484, 1.38609, 1.83276, 2.06162, 2.2194, 2.48635,
+ 1.31431, 1.38148, 1.91283, 2.01753, 2.28775, 2.57642,
+ 1.27508, 1.35377, 1.85847, 2.03703, 2.36206, 2.61542,
+ 1.28711, 1.3668, 1.83552, 1.96109, 2.29199, 2.56297,
+ 1.25667, 1.34116, 1.79881, 1.92126, 2.33365, 2.59691,
+ 1.22928, 1.33751, 1.75398, 1.94239, 2.40355, 2.60217,
+ 1.22487, 1.32298, 1.79261, 1.91891, 2.36331, 2.52058,
+ 1.21845, 1.32159, 1.65149, 1.88416, 2.36654, 2.52128,
+ 1.19322, 1.35912, 1.6324, 1.85763, 2.32285, 2.45271,
+ 1.20547, 1.36803, 1.60803, 1.81504, 2.34185, 2.57451,
+ 1.06125, 1.31843, 1.54502, 1.88874, 2.40188, 2.61702,
+ 1.07252, 1.36579, 1.51413, 1.89367, 2.36962, 2.47423,
+ 1.11164, 1.43679, 1.6061, 1.84246, 2.38242, 2.47411,
+ 1.01206, 1.3162, 1.47159, 1.79906, 2.34943, 2.45513,
+ 1.08947, 1.24857, 1.57279, 1.95306, 2.29844, 2.46178,
+ 1.06836, 1.19581, 1.62402, 2.11129, 2.31148, 2.41925,
+ 1.14751, 1.52522, 1.72481, 1.95717, 2.38753, 2.47131,
+ 1.33434, 1.56815, 1.74904, 1.96257, 2.39063, 2.48465,
+ 1.29814, 1.46788, 1.8144, 1.94157, 2.38423, 2.52218,
+ 1.29501, 1.41849, 1.85947, 1.96233, 2.37632, 2.52176,
+ 1.33583, 1.43664, 1.85826, 1.96633, 2.44658, 2.56348,
+ 1.34649, 1.47798, 1.90564, 1.99809, 2.49005, 2.58447,
+ 1.40718, 1.54076, 1.8793, 1.99298, 2.48794, 2.56401,
+ 1.44766, 1.62857, 1.8282, 2.05365, 2.53405, 2.60586,
+ 1.52471, 1.62005, 1.83788, 2.01792, 2.59217, 2.65337,
+ 1.56458, 1.64714, 1.76118, 2.02415, 2.61525, 2.65657,
+ 1.52937, 1.59398, 1.68316, 1.97983, 2.60164, 2.65439,
+ 1.58508, 1.65284, 1.78677, 2.03185, 2.518, 2.62098,
+ 1.58891, 1.64423, 1.81381, 2.04148, 2.61072, 2.66605,
+ 1.60136, 1.68607, 1.86295, 2.12711, 2.60886, 2.65502,
+ 1.64024, 1.75092, 1.9211, 2.16441, 2.54752, 2.61719,
+ 1.5486, 1.6382, 1.9174, 2.09265, 2.56383, 2.61584,
+ 1.51587, 1.61696, 1.84416, 2.00703, 2.52817, 2.60107,
+ 1.46587, 1.5722, 1.74097, 2.01129, 2.49342, 2.58193,
+ 1.41191, 1.53428, 1.66939, 2.02551, 2.41906, 2.53499,
+ 1.3394, 1.5249, 1.67455, 2.01899, 2.344, 2.44379,
+ 1.30067, 1.52706, 1.67307, 2.03619, 2.26952, 2.38379,
+ 1.19308, 1.4765, 1.66446, 1.93323, 2.291, 2.41495,
+ 1.19279, 1.48559, 1.64926, 1.84405, 2.29509, 2.502,
+ 1.19782, 1.36486, 1.70369, 1.82721, 2.26277, 2.4998,
+ 1.13827, 1.37925, 1.65813, 1.91249, 2.38908, 2.58338,
+ 1.1666, 1.35794, 1.68892, 1.94273, 2.49153, 2.58925,
+ 1.17061, 1.39155, 1.72193, 1.88951, 2.50612, 2.61639,
+ 1.21096, 1.4527, 1.75562, 1.84497, 2.49006, 2.62473,
+ 1.21214, 1.51972, 1.78592, 1.88927, 2.55126, 2.62949,
+ 1.276, 1.66462, 1.95776, 2.24934, 2.60229, 2.6777,
+ 1.40086, 1.81618, 1.99446, 2.32596, 2.65178, 2.7173,
+ 1.46605, 1.83456, 2.11857, 2.37243, 2.62538, 2.70468,
+ 1.57886, 1.79094, 2.1361, 2.39283, 2.63855, 2.71402,
+ 1.4807, 1.81656, 2.20645, 2.43239, 2.57589, 2.64511,
+ 1.61729, 1.80766, 2.24172, 2.44007, 2.56723, 2.63175,
+ 1.5701, 1.78507, 2.17821, 2.34813, 2.46705, 2.55664,
+ 1.57968, 1.70153, 2.00519, 2.28877, 2.43415, 2.54859,
+ 1.57869, 1.67421, 1.96547, 2.19945, 2.33487, 2.4798,
+ 1.64055, 1.72692, 1.99161, 2.24034, 2.40097, 2.52363,
+ 1.58853, 1.70967, 1.87442, 2.16082, 2.38152, 2.51723,
+ 1.4475, 1.66548, 1.90094, 2.10338, 2.39787, 2.53557,
+ 1.20302, 1.59921, 1.88428, 2.03226, 2.36901, 2.50474,
+ 1.14652, 1.51319, 1.8805, 1.98579, 2.40738, 2.52248,
+ 1.13127, 1.435, 1.83409, 2.11135, 2.30655, 2.53115,
+ 1.17671, 1.64034, 1.87012, 2.06494, 2.313, 2.43912,
+ 1.25449, 1.59061, 1.95849, 2.20017, 2.34427, 2.47982,
+ 1.24396, 1.68449, 2.0165, 2.19295, 2.45108, 2.54733,
+ 1.53731, 1.76385, 2.18864, 2.37173, 2.53993, 2.64808,
+ 1.64654, 1.88757, 2.28095, 2.44345, 2.59307, 2.68077,
+ 1.56746, 1.87617, 2.10871, 2.42783, 2.61173, 2.69136,
+ 1.34106, 1.87413, 2.11422, 2.3962, 2.62123, 2.70277,
+ 1.4492, 1.83784, 2.0584, 2.30747, 2.61691, 2.68969,
+ 1.31349, 1.79435, 1.96106, 2.2375, 2.59774, 2.68519,
+ 1.20218, 1.70691, 1.9051, 2.13915, 2.61289, 2.69366,
+ 1.08034, 1.59049, 1.84652, 2.05928, 2.63137, 2.69738,
+ 1.04322, 1.60191, 1.90035, 2.14104, 2.58835, 2.66252,
+ 0.984957, 1.55615, 1.84148, 2.14877, 2.57734, 2.66295,
+ 0.979403, 1.55384, 1.84417, 2.0526, 2.57775, 2.64111,
+ 0.947313, 1.45389, 1.83646, 1.99878, 2.56655, 2.63755,
+ 0.95946, 1.44168, 1.83287, 2.1065, 2.55364, 2.63088,
+ 0.951016, 1.39788, 1.79374, 2.05307, 2.49264, 2.62257,
+ 0.870727, 1.36922, 1.81779, 2.10748, 2.52423, 2.62794,
+ 0.902872, 1.38516, 1.7548, 2.01343, 2.53699, 2.65482,
+ 0.891101, 1.3624, 1.75358, 1.87804, 2.5598, 2.66247,
+ 0.835616, 1.25933, 1.75717, 1.83234, 2.48635, 2.63568,
+ 0.787419, 1.13204, 1.69397, 1.77693, 2.53318, 2.61631,
+ 0.791106, 1.06813, 1.69774, 1.8516, 2.57196, 2.66955,
+ 0.759951, 1.11236, 1.56236, 1.8552, 2.49068, 2.60197,
+ 0.792061, 1.14, 1.72482, 1.95446, 2.60886, 2.68968,
+ 0.823952, 1.27093, 1.74109, 2.07766, 2.6132, 2.66939,
+ 0.736534, 1.12497, 1.74368, 2.09325, 2.57979, 2.66172,
+ 0.797043, 1.05194, 1.78023, 2.24036, 2.58348, 2.66231,
+ 0.923582, 1.50315, 1.77688, 2.01847, 2.61391, 2.70304,
+ 1.42154, 1.73503, 2.00689, 2.21034, 2.57432, 2.67074,
+ 1.35017, 1.60612, 1.96301, 2.08497, 2.47819, 2.58995,
+ 1.3618, 1.65658, 1.97408, 2.17388, 2.47963, 2.61201,
+ 1.31994, 1.76445, 2.02745, 2.24929, 2.52964, 2.63574,
+ 1.39403, 1.6642, 2.00631, 2.24619, 2.55809, 2.67132,
+ 1.38539, 1.75543, 2.08002, 2.32987, 2.63089, 2.72267,
+ 1.33369, 1.66943, 2.02149, 2.25061, 2.60027, 2.6891,
+ 1.34153, 1.69816, 1.975, 2.23711, 2.56085, 2.68438,
+ 1.38861, 1.78505, 1.95689, 2.28139, 2.56358, 2.64371,
+ 1.34589, 1.70624, 1.84298, 2.26416, 2.60622, 2.69479,
+ 1.32033, 1.69419, 1.92336, 2.21815, 2.64548, 2.75026,
+ 1.33239, 1.74839, 2.01472, 2.22178, 2.60263, 2.69746,
+ 1.3976, 1.71535, 1.94972, 2.236, 2.5778, 2.66148,
+ 1.61881, 1.79597, 2.01642, 2.20519, 2.50664, 2.63683,
+ 1.65981, 1.73533, 2.02109, 2.17584, 2.44338, 2.64145,
+ 1.53953, 1.65206, 1.94677, 2.09508, 2.44664, 2.63655,
+ 1.53227, 1.59287, 1.97782, 2.05341, 2.55149, 2.67491,
+ 1.50935, 1.58111, 2.00424, 2.05938, 2.5246, 2.70294,
+ 1.43253, 1.50463, 1.93071, 2.04233, 2.44066, 2.69085,
+ 1.19464, 1.67704, 2.0231, 2.07839, 2.44691, 2.74585,
+ 1.21037, 1.82483, 2.02151, 2.13909, 2.53993, 2.65964,
+ 1.27662, 1.71544, 1.95249, 2.08382, 2.47346, 2.66435,
+ 1.23566, 1.54844, 2.06734, 2.11862, 2.42744, 2.72754,
+ 1.28347, 1.3743, 1.96342, 2.09842, 2.47439, 2.70286,
+ 1.30502, 1.3947, 2.068, 2.13904, 2.52017, 2.70621,
+ 1.28482, 1.49431, 2.05521, 2.14033, 2.60212, 2.69883,
+ 1.29659, 1.58772, 2.0872, 2.15656, 2.61856, 2.71863,
+ 1.25247, 1.58335, 2.10888, 2.17387, 2.6005, 2.68503,
+ 1.17744, 1.61204, 2.09388, 2.15517, 2.58107, 2.69512,
+ 1.13296, 1.57299, 2.13546, 2.2206, 2.61573, 2.71057,
+ 1.06032, 1.54298, 2.16575, 2.23041, 2.60944, 2.69779,
+ 0.993306, 1.5422, 2.17075, 2.24721, 2.63117, 2.70689,
+ 0.78375, 1.56854, 2.32332, 2.39888, 2.5942, 2.6906,
+ 0.866024, 1.45443, 2.11329, 2.18704, 2.66201, 2.71994,
+ 0.793002, 1.4377, 2.12567, 2.22555, 2.58888, 2.66479,
+ 0.863183, 1.43983, 2.03195, 2.20395, 2.58648, 2.64689,
+ 0.817301, 1.44308, 2.07874, 2.35666, 2.57215, 2.63532,
+ 0.8402, 1.2682, 1.97396, 2.38069, 2.54674, 2.62412,
+ 0.90591, 1.47285, 2.0008, 2.42018, 2.60601, 2.66254,
+ 0.885218, 1.59913, 2.06396, 2.33538, 2.68875, 2.73625,
+ 0.812099, 1.48097, 2.10316, 2.19363, 2.62136, 2.70211,
+ 0.727009, 1.48128, 2.08817, 2.17056, 2.57558, 2.66056,
+ 0.783755, 1.48208, 2.21077, 2.28199, 2.56464, 2.65808,
+ 0.81089, 1.318, 2.15666, 2.25015, 2.56537, 2.66617,
+ 0.775372, 1.35271, 2.27746, 2.37173, 2.58724, 2.65549,
+ 0.765239, 1.28061, 2.22745, 2.3049, 2.57753, 2.69687,
+ 0.860727, 1.30996, 2.23921, 2.35825, 2.52375, 2.68183,
+ 0.828001, 1.15751, 2.1572, 2.2792, 2.55451, 2.65538,
+ 0.776568, 1.131, 2.11047, 2.28237, 2.50224, 2.63453,
+ 0.662804, 1.21065, 2.21449, 2.27527, 2.48015, 2.59817,
+ 0.752595, 1.17213, 2.27025, 2.35479, 2.53437, 2.61343,
+ 0.769014, 1.03754, 2.23985, 2.32019, 2.52388, 2.63727,
+ 0.747299, 1.03652, 2.05988, 2.38032, 2.50772, 2.67777,
+ 0.818428, 1.11045, 2.13257, 2.30679, 2.44267, 2.59784,
+ 0.838124, 1.25603, 2.15252, 2.30408, 2.50108, 2.59185,
+ 0.84274, 1.14734, 2.04509, 2.31707, 2.45929, 2.58847,
+ 0.950977, 1.15093, 2.09764, 2.29, 2.49742, 2.64345,
+ 0.932262, 1.15976, 1.94518, 2.23375, 2.53889, 2.63575,
+ 0.87264, 1.29467, 1.88108, 2.11219, 2.48873, 2.6127,
+ 0.953242, 1.39834, 1.90676, 2.02445, 2.39667, 2.61633,
+ 1.01916, 1.44724, 1.91732, 2.02333, 2.21302, 2.5289,
+ 0.98091, 1.42044, 1.85762, 1.94344, 2.29448, 2.59612,
+ 1.00792, 1.47472, 1.82759, 1.92148, 2.56736, 2.64375,
+ 1.05767, 1.58382, 1.86222, 1.98831, 2.50759, 2.60278,
+ 1.08948, 1.61094, 1.8942, 2.06798, 2.40143, 2.58925,
+ 1.15564, 1.60152, 1.85378, 2.10992, 2.26642, 2.65488,
+ 1.19039, 1.40321, 1.85032, 2.12943, 2.35548, 2.59965,
+ 1.16567, 1.26623, 1.84792, 2.19176, 2.35216, 2.57681,
+ 1.11254, 1.23723, 1.75555, 2.19641, 2.37841, 2.5159,
+ 1.0932, 1.22932, 1.63097, 2.19849, 2.39433, 2.49006,
+ 1.03092, 1.16009, 1.537, 2.15027, 2.34576, 2.52617,
+ 1.09013, 1.22746, 1.4703, 2.12166, 2.32569, 2.41426,
+ 1.08419, 1.35343, 1.49577, 2.16541, 2.39664, 2.50153,
+ 1.12869, 1.38014, 1.55146, 2.11031, 2.29686, 2.419,
+ 1.08717, 1.45426, 1.65879, 2.02039, 2.1963, 2.38146,
+ 1.03939, 1.58219, 1.7281, 2.07018, 2.30185, 2.48943,
+ 1.01902, 1.64687, 1.82892, 2.12577, 2.54247, 2.62493,
+ 1.01791, 1.67544, 2.00939, 2.20063, 2.43227, 2.53275,
+ 0.975365, 1.56846, 2.09963, 2.24376, 2.46967, 2.55866,
+ 1.04514, 1.75055, 2.09119, 2.27703, 2.474, 2.55964,
+ 1.00349, 1.67, 2.14987, 2.21681, 2.54414, 2.59102,
+ 0.972271, 1.66935, 2.06691, 2.25346, 2.52812, 2.62679,
+ 1.0014, 1.91054, 2.2089, 2.32209, 2.47505, 2.59415,
+ 1.10624, 1.7624, 2.17021, 2.36833, 2.53238, 2.63695,
+ 0.937567, 1.5708, 2.20831, 2.31208, 2.5476, 2.60415,
+ 0.984015, 1.53165, 2.15445, 2.2604, 2.51955, 2.62137,
+ 1.05805, 1.58968, 2.13047, 2.23879, 2.55922, 2.636,
+ 1.12629, 1.6743, 2.14238, 2.30438, 2.58199, 2.6598,
+ 1.09217, 1.54725, 2.13885, 2.24696, 2.57092, 2.65374,
+ 1.16415, 1.51357, 2.1206, 2.20304, 2.55593, 2.62912,
+ 1.15444, 1.45166, 2.10988, 2.19379, 2.56938, 2.66869,
+ 1.17101, 1.29755, 2.10579, 2.22429, 2.52972, 2.66324,
+ 1.13937, 1.34334, 2.02494, 2.16127, 2.57005, 2.66206,
+ 1.21497, 1.75949, 2.01362, 2.12671, 2.35066, 2.50893,
+ 1.41044, 1.78736, 1.94045, 2.082, 2.25578, 2.40636,
+ 1.19253, 1.69828, 1.95689, 2.08484, 2.23574, 2.49064,
+ 1.17363, 1.44875, 2.01112, 2.14525, 2.28014, 2.53471,
+ 1.1728, 1.32718, 1.93887, 2.09591, 2.24756, 2.52684,
+ 1.12971, 1.37614, 1.89153, 1.98533, 2.19635, 2.58265,
+ 1.19522, 1.29291, 1.88721, 2.02514, 2.2007, 2.52559,
+ 1.24628, 1.33897, 1.85165, 2.07279, 2.20907, 2.45744,
+ 1.24471, 1.39554, 1.91684, 2.09705, 2.29649, 2.52665,
+ 1.34643, 1.45327, 2.12841, 2.31384, 2.56627, 2.66621,
+ 1.39218, 1.50657, 2.06042, 2.18383, 2.52364, 2.65642,
+ 1.39767, 1.47836, 2.03787, 2.14002, 2.52288, 2.63488,
+ 1.40508, 1.43797, 2.0647, 2.12168, 2.48434, 2.66409,
+ 1.52797, 1.73164, 2.0014, 2.18228, 2.47746, 2.60968,
+ 1.60222, 1.69405, 2.06501, 2.17614, 2.56757, 2.65075,
+ 1.54924, 1.66815, 2.06194, 2.13605, 2.57595, 2.67854,
+ 1.59049, 1.69321, 1.92159, 2.19358, 2.52234, 2.65782,
+ 1.59312, 1.7156, 2.05786, 2.17281, 2.50201, 2.60776,
+ 1.50846, 1.71395, 2.05346, 2.14686, 2.38304, 2.62867,
+ 1.50094, 1.57787, 1.97852, 2.08096, 2.51787, 2.64082,
+ 1.50382, 1.5592, 1.93328, 2.0306, 2.51619, 2.6575,
+ 1.43095, 1.50644, 1.85636, 2.01451, 2.40691, 2.5838,
+ 1.39442, 1.47116, 1.91477, 2.01533, 2.41451, 2.56893,
+ 1.37672, 1.47674, 1.84174, 1.96157, 2.45962, 2.55251,
+ 1.30483, 1.50926, 1.80786, 1.89902, 2.5326, 2.61656,
+ 1.48624, 1.64687, 1.92899, 2.17664, 2.50338, 2.64553,
+ 1.47707, 1.57641, 1.9373, 2.09445, 2.46873, 2.64363,
+ 1.43149, 1.55127, 1.93581, 2.02799, 2.46876, 2.60559,
+ 1.42717, 1.67082, 1.94498, 2.10994, 2.48274, 2.65243,
+ 1.39319, 1.64956, 1.99108, 2.07033, 2.58645, 2.66734,
+ 1.40697, 1.51853, 1.96705, 2.06775, 2.50172, 2.62411,
+ 1.39913, 1.48738, 1.88033, 1.97257, 2.35919, 2.60481,
+ 1.41945, 1.54191, 1.92089, 2.01526, 2.41644, 2.54754,
+ 1.44774, 1.62665, 1.9116, 2.03784, 2.5083, 2.60909,
+ 1.50794, 1.64922, 1.95449, 2.06384, 2.51578, 2.59147,
+ 1.51251, 1.69788, 1.91927, 2.07717, 2.54577, 2.63108,
+ 1.57749, 1.65292, 1.96938, 2.05711, 2.5335, 2.61048,
+ 1.60471, 1.68784, 1.94363, 2.0307, 2.55246, 2.65947,
+ 1.63482, 1.71009, 1.94351, 2.03574, 2.55304, 2.65052,
+ 1.62911, 1.72105, 1.90726, 2.02014, 2.5701, 2.65261,
+ 1.65386, 1.73101, 1.91707, 2.0165, 2.55131, 2.67898,
+ 1.67562, 1.74025, 1.92311, 1.99547, 2.54389, 2.69347,
+ 1.70432, 1.761, 1.89209, 1.9586, 2.52034, 2.70958,
+ 1.63175, 1.69802, 1.87977, 1.97482, 2.47504, 2.68871,
+ 1.56339, 1.66235, 1.8635, 1.96166, 2.49207, 2.69214,
+ 1.53527, 1.6218, 1.86452, 2.01688, 2.4572, 2.70145,
+ 1.46363, 1.69, 1.94259, 2.01949, 2.51608, 2.68408,
+ 1.42716, 1.54573, 1.9226, 1.98339, 2.54908, 2.72404,
+ 1.38786, 1.46942, 1.87429, 2.04709, 2.48657, 2.64301,
+ 1.36474, 1.46274, 1.90851, 2.07652, 2.46877, 2.62742,
+ 1.42161, 1.61667, 2.07439, 2.24363, 2.60481, 2.69712,
+ 1.44357, 1.80248, 2.14589, 2.31103, 2.61513, 2.70497,
+ 1.40281, 1.86481, 2.20938, 2.37797, 2.65429, 2.73144,
+ 1.47267, 1.8608, 2.16288, 2.44727, 2.64842, 2.71902,
+ 1.5185, 1.79472, 2.07501, 2.33921, 2.5521, 2.65593,
+ 1.5036, 1.75847, 2.11155, 2.30448, 2.551, 2.64355,
+ 1.46676, 1.58771, 2.04614, 2.2766, 2.54651, 2.64991,
+ 1.41461, 1.49916, 2.00069, 2.08085, 2.54908, 2.65441,
+ 1.32462, 1.59742, 1.9617, 2.07526, 2.51879, 2.63826,
+ 1.26245, 1.66607, 1.96155, 2.09827, 2.5491, 2.63037,
+ 1.22087, 1.63212, 1.94765, 2.05495, 2.51597, 2.60756,
+ 1.13665, 1.56914, 1.92325, 2.0114, 2.51398, 2.61292,
+ 1.05857, 1.57058, 1.92127, 2.03797, 2.48449, 2.5695,
+ 1.03982, 1.49237, 1.86238, 2.11332, 2.46263, 2.58629,
+ 1.29165, 1.54669, 1.88843, 2.16034, 2.44457, 2.57368,
+ 1.15415, 1.62983, 1.97872, 2.11452, 2.50541, 2.61617,
+ 1.01899, 1.84423, 2.0035, 2.14564, 2.43005, 2.54966,
+ 1.00364, 1.90025, 2.10397, 2.20081, 2.55527, 2.67887,
+ 1.00718, 1.65253, 2.03338, 2.1179, 2.53436, 2.59384,
+ 1.01407, 1.62531, 2.07357, 2.164, 2.54614, 2.61183,
+ 1.00985, 1.72901, 2.00161, 2.19007, 2.55455, 2.63543,
+ 1.01949, 1.59982, 2.06292, 2.18098, 2.58535, 2.65191,
+ 1.04228, 1.55985, 2.06172, 2.18491, 2.60883, 2.71127,
+ 1.09398, 1.6067, 2.06705, 2.17946, 2.57811, 2.64708,
+ 1.11752, 1.5545, 2.01046, 2.17126, 2.52419, 2.60461,
+ 1.18915, 1.68712, 2.02682, 2.22074, 2.58466, 2.6736,
+ 1.18429, 1.59293, 2.01141, 2.14056, 2.57563, 2.65276,
+ 1.24327, 1.54434, 1.99135, 2.10372, 2.54773, 2.63384,
+ 1.2498, 1.53006, 1.93046, 2.04451, 2.4895, 2.61104,
+ 1.31723, 1.55086, 1.92747, 2.01911, 2.56358, 2.63241,
+ 1.30015, 1.5712, 1.81721, 1.96732, 2.57201, 2.65975,
+ 1.30479, 1.45907, 1.80435, 1.8738, 2.57235, 2.67785,
+ 1.27211, 1.38793, 1.71059, 1.79844, 2.51912, 2.63097,
+ 1.16882, 1.27144, 1.68047, 1.84764, 2.47259, 2.63611,
+ 1.12771, 1.38042, 1.70269, 1.94834, 2.2548, 2.51659,
+ 1.03734, 1.36207, 1.69887, 1.94336, 2.31998, 2.57611,
+ 0.912701, 1.21524, 1.77476, 2.05793, 2.4073, 2.60974,
+ 0.884045, 1.28334, 1.74009, 2.01204, 2.33233, 2.53015,
+ 0.859928, 1.36139, 1.78777, 2.03243, 2.43916, 2.5725,
+ 0.933575, 1.49731, 1.86011, 2.00776, 2.46078, 2.63658,
+ 0.980843, 1.37667, 1.80827, 1.8993, 2.55138, 2.66068,
+ 0.888314, 1.39084, 1.81906, 1.9386, 2.61173, 2.7137,
+ 0.839112, 1.45505, 1.86425, 1.93257, 2.56126, 2.64948,
+ 0.851738, 1.63344, 1.85494, 2.0651, 2.59153, 2.63797,
+ 0.927993, 1.73919, 1.88202, 2.1332, 2.58502, 2.64078,
+ 0.938681, 1.79566, 1.96211, 2.13893, 2.56523, 2.6279,
+ 0.939389, 1.84213, 2.02182, 2.19635, 2.61152, 2.65832,
+ 0.876668, 1.92276, 2.0666, 2.23861, 2.65783, 2.70914,
+ 0.92889, 1.83181, 2.05372, 2.20362, 2.65364, 2.69541,
+ 0.843177, 1.78595, 2.18004, 2.25807, 2.59681, 2.66987,
+ 0.90471, 1.73857, 2.04548, 2.17133, 2.65908, 2.70177,
+ 0.870576, 1.67285, 2.04668, 2.1603, 2.66339, 2.70628,
+ 0.863208, 1.61128, 2.03958, 2.13199, 2.66274, 2.71021,
+ 0.911587, 1.52148, 1.97225, 2.1177, 2.67151, 2.73629,
+ 0.857624, 1.50623, 1.92746, 2.09207, 2.599, 2.67135,
+ 0.876724, 1.38621, 1.9301, 2.02012, 2.64025, 2.71571,
+ 0.822485, 1.36308, 1.9511, 2.01209, 2.54628, 2.70422,
+ 0.896312, 1.29923, 1.94615, 2.04, 2.42757, 2.66043,
+ 0.993275, 1.37977, 2.00112, 2.08344, 2.47648, 2.62108,
+ 1.11197, 1.36926, 1.98057, 2.05008, 2.51842, 2.65472,
+ 1.16821, 1.42116, 1.92965, 2.01373, 2.5139, 2.65946,
+ 1.18553, 1.47731, 1.9417, 2.02179, 2.54584, 2.63683,
+ 1.13468, 1.49839, 1.99686, 2.07705, 2.4871, 2.60596,
+ 1.41173, 1.50081, 1.93056, 2.25169, 2.39141, 2.51475,
+ 1.3871, 1.55163, 1.93927, 2.13443, 2.39065, 2.5381,
+ 1.43647, 1.60163, 1.85631, 2.00172, 2.49843, 2.57968,
+ 1.49076, 1.67386, 1.86537, 2.01526, 2.49094, 2.5896,
+ 1.53229, 1.66582, 1.85411, 1.98779, 2.54431, 2.63455,
+ 1.56314, 1.68325, 1.81921, 1.98134, 2.5924, 2.65599,
+ 1.53269, 1.64287, 1.79509, 1.95595, 2.59557, 2.68867,
+ 1.50694, 1.59687, 1.72472, 1.90252, 2.49715, 2.64677,
+ 1.38523, 1.5533, 1.73378, 1.99349, 2.38568, 2.62019,
+ 1.19137, 1.50809, 1.91412, 2.17718, 2.46035, 2.60064,
+ 0.990202, 1.26842, 1.7603, 1.98849, 2.51666, 2.66102,
+ 1.00489, 1.27303, 1.91958, 1.97696, 2.62153, 2.71115,
+ 1.01329, 1.47917, 1.98377, 2.02111, 2.56129, 2.68139,
+ 1.09438, 1.4242, 1.985, 2.16479, 2.59214, 2.67097,
+ 1.05777, 1.37751, 1.86611, 2.16542, 2.49067, 2.62334,
+ 1.00177, 1.3213, 1.90229, 2.13388, 2.49989, 2.65935,
+ 0.896048, 1.41478, 1.92755, 2.1276, 2.57065, 2.6585,
+ 0.862503, 1.58697, 1.94655, 2.15362, 2.61512, 2.67787,
+ 0.837783, 1.70001, 1.93298, 2.20945, 2.58857, 2.68753,
+ 0.901209, 1.63977, 1.99997, 2.07058, 2.5153, 2.76315,
+ 0.955829, 1.60125, 2.00897, 2.11223, 2.50389, 2.59284,
+ 0.939285, 1.70409, 2.02741, 2.12592, 2.43001, 2.53892,
+ 0.948268, 1.70087, 2.00277, 2.08835, 2.56347, 2.62211,
+ 0.959154, 1.62427, 2.00582, 2.07776, 2.57772, 2.65873,
+ 0.932538, 1.59344, 1.95283, 2.04466, 2.56798, 2.6445,
+ 0.933107, 1.59056, 1.9457, 2.1119, 2.53428, 2.60887,
+ 0.943808, 1.64909, 1.89702, 2.10465, 2.57817, 2.68976,
+ 1.00303, 1.61916, 1.93023, 2.21672, 2.58234, 2.63789,
+ 0.93681, 1.69235, 1.96553, 2.11865, 2.62852, 2.6848,
+ 0.973578, 1.73782, 1.97567, 2.10634, 2.65829, 2.72245,
+ 0.955324, 1.75019, 1.96144, 2.07537, 2.65561, 2.73176,
+ 0.994013, 1.72739, 1.94678, 2.06241, 2.64338, 2.73849,
+ 1.00536, 1.69392, 1.92987, 2.10018, 2.61875, 2.68486,
+ 0.967862, 1.64008, 1.93026, 2.02155, 2.63989, 2.72666,
+ 0.928258, 1.57936, 1.86441, 1.97301, 2.63891, 2.71789,
+ 1.05833, 1.41059, 1.87085, 2.06602, 2.45158, 2.6337,
+ 1.12305, 1.48688, 1.86297, 2.08608, 2.41298, 2.59174,
+ 1.17747, 1.43154, 1.84929, 2.09976, 2.42334, 2.56613,
+ 1.18703, 1.44351, 1.88207, 1.98332, 2.55067, 2.63939,
+ 1.26797, 1.62839, 1.93261, 2.04328, 2.55223, 2.64173,
+ 1.35555, 1.70156, 1.92424, 2.03456, 2.59018, 2.66096,
+ 1.47206, 1.73998, 1.91426, 2.05233, 2.57389, 2.64493,
+ 1.46149, 1.79066, 1.91131, 2.05787, 2.5256, 2.58723,
+ 1.54235, 1.7424, 1.90165, 2.06306, 2.49917, 2.58066,
+ 1.55081, 1.6429, 1.87739, 1.99515, 2.47436, 2.56117,
+ 1.62535, 1.72476, 1.89911, 2.05259, 2.44709, 2.55685,
+ 1.6367, 1.7422, 1.90449, 2.15532, 2.47031, 2.56929,
+ 1.60869, 1.70103, 1.95711, 2.08558, 2.46532, 2.5522,
+ 1.51757, 1.68517, 1.92305, 2.02897, 2.3829, 2.50393,
+ 1.21585, 1.64813, 1.84289, 2.04997, 2.39383, 2.48435,
+ 1.1585, 1.45299, 1.75267, 1.85902, 2.46727, 2.57552,
+ 1.12827, 1.38415, 1.8015, 1.89918, 2.47245, 2.60999,
+ 1.08062, 1.41434, 1.81249, 1.91664, 2.42269, 2.62012,
+ 1.10487, 1.49291, 1.85404, 1.97194, 2.444, 2.58358,
+ 1.23581, 1.43782, 1.91948, 2.04279, 2.484, 2.61715,
+ 1.16741, 1.4076, 1.77439, 2.07357, 2.3906, 2.54332,
+ 1.09657, 1.31723, 1.78221, 2.01354, 2.39437, 2.57181,
+ 1.10431, 1.2068, 1.71858, 2.00101, 2.35134, 2.50564,
+ 1.04732, 1.31689, 1.82432, 2.05077, 2.41716, 2.53103,
+ 1.08718, 1.4084, 1.84314, 2.03167, 2.44048, 2.54426,
+ 1.10852, 1.3942, 1.76003, 2.00573, 2.43503, 2.55215,
+ 1.12177, 1.34059, 1.7495, 1.96363, 2.49382, 2.60964,
+ 1.12241, 1.45271, 1.79313, 2.03041, 2.50213, 2.59324,
+ 1.02688, 1.4681, 1.74534, 1.86047, 2.48368, 2.57975,
+ 0.97167, 1.24409, 1.75298, 1.83733, 2.38472, 2.62532,
+ 0.917302, 1.10441, 1.67493, 1.79243, 2.33619, 2.62947,
+ 0.96156, 1.08836, 1.55578, 1.66371, 2.28232, 2.57975,
+ 0.919563, 1.06328, 1.5732, 1.7111, 2.42269, 2.67598,
+ 0.875889, 1.02261, 1.38084, 1.82916, 2.58466, 2.66738,
+ 0.763749, 1.01881, 1.50632, 1.70798, 2.47153, 2.59587,
+ 0.886944, 1.03139, 1.42506, 1.71002, 2.42792, 2.57639,
+ 0.890351, 1.03765, 1.44399, 1.58788, 2.52021, 2.69583,
+ 0.906256, 1.03505, 1.40561, 1.52374, 2.53653, 2.59608,
+ 0.929418, 1.06107, 1.15709, 1.5666, 2.52826, 2.69407,
+ 0.917396, 1.10612, 1.25304, 1.38951, 2.55157, 2.7091,
+ 0.91023, 1.04207, 1.16253, 1.36213, 2.39308, 2.60535,
+ 0.804288, 1.05959, 1.41808, 1.53036, 2.41057, 2.66344,
+ 0.907675, 1.04629, 1.39254, 1.50823, 2.49535, 2.69234,
+ 0.835212, 1.12687, 1.3505, 1.46321, 2.56773, 2.69467,
+ 0.770295, 1.1507, 1.42826, 1.60117, 2.61023, 2.68367,
+ 0.924536, 1.07541, 1.46853, 1.66987, 2.54368, 2.6932,
+ 0.972382, 1.19176, 1.54476, 1.63867, 2.53532, 2.64297,
+ 0.903877, 1.10193, 1.51078, 1.60266, 2.48704, 2.63827,
+ 0.881279, 1.0969, 1.55425, 1.6443, 2.42466, 2.55757,
+ 0.866115, 1.11888, 1.60304, 1.70247, 2.5439, 2.6493,
+ 0.906645, 1.16025, 1.67202, 1.74726, 2.51791, 2.65086,
+ 0.861085, 1.20586, 1.66099, 1.84709, 2.46274, 2.63203,
+ 0.837175, 1.18778, 1.80604, 1.8895, 2.50861, 2.68456,
+ 0.797709, 1.17852, 1.90318, 2.02165, 2.54618, 2.69007,
+ 0.802875, 1.26275, 1.92394, 2.00058, 2.56844, 2.67011,
+ 0.766638, 1.32083, 1.96102, 2.05894, 2.58231, 2.64672,
+ 0.811579, 1.45519, 2.01148, 2.08478, 2.54842, 2.63993,
+ 0.82977, 1.48496, 2.05271, 2.12723, 2.53064, 2.60818,
+ 0.799011, 1.56745, 2.15563, 2.26511, 2.57317, 2.6685,
+ 0.730379, 1.35861, 2.12579, 2.19459, 2.5187, 2.60543,
+ 0.720667, 1.27784, 2.04281, 2.11192, 2.5928, 2.6753,
+ 0.777663, 1.1637, 2.06679, 2.1792, 2.57, 2.67551,
+ 0.839969, 1.37318, 2.18588, 2.30468, 2.50936, 2.60258,
+ 0.815752, 1.91522, 2.23363, 2.28848, 2.56998, 2.62843,
+ 1.19188, 1.94569, 2.17513, 2.29905, 2.52352, 2.63204,
+ 1.03628, 1.74221, 2.07271, 2.14156, 2.57319, 2.64155,
+ 1.04251, 1.30305, 2.01289, 2.15461, 2.53068, 2.64918,
+ 1.10994, 1.20424, 1.92869, 2.05823, 2.3841, 2.63957,
+ 1.18739, 1.2877, 1.95425, 2.07126, 2.38256, 2.64181,
+ 1.23919, 1.32776, 1.93055, 2.01528, 2.36169, 2.6275,
+ 1.29208, 1.35198, 1.93801, 2.01732, 2.4115, 2.66343,
+ 1.30624, 1.3824, 1.91845, 2.03831, 2.33939, 2.63774,
+ 1.33024, 1.40164, 1.87376, 1.99044, 2.1855, 2.51091,
+ 1.35639, 1.45976, 1.88339, 1.98046, 2.26455, 2.54181,
+ 1.3474, 1.43864, 1.89167, 2.01801, 2.30257, 2.64381,
+ 1.30088, 1.39017, 1.88927, 1.97293, 2.33752, 2.60564,
+ 1.31867, 1.41012, 1.89535, 1.99037, 2.38468, 2.65404,
+ 1.30927, 1.4255, 1.96615, 2.0219, 2.50112, 2.69851,
+ 1.29385, 1.37092, 1.90844, 1.99915, 2.46548, 2.674,
+ 1.2774, 1.38284, 2.0023, 2.06684, 2.49685, 2.66407,
+ 1.24538, 1.42244, 2.00291, 2.07072, 2.55684, 2.66639,
+ 1.27259, 1.49109, 2.0123, 2.12924, 2.56231, 2.65743,
+ 1.26518, 1.53394, 2.02094, 2.09309, 2.49838, 2.63095,
+ 1.2657, 1.47703, 2.10301, 2.19653, 2.45528, 2.61989,
+ 1.2885, 1.64245, 2.09385, 2.24783, 2.56169, 2.65879,
+ 1.41026, 1.82897, 2.17187, 2.37413, 2.56459, 2.65338,
+ 1.35389, 1.71004, 2.20933, 2.42604, 2.62932, 2.70219,
+ 1.41361, 1.76693, 2.13772, 2.43485, 2.63206, 2.70291,
+ 1.45905, 1.70694, 2.13508, 2.37703, 2.62642, 2.70895,
+ 1.49802, 1.68792, 2.09482, 2.34295, 2.55878, 2.6657,
+ 1.41391, 1.58827, 2.08673, 2.29308, 2.51359, 2.64213,
+ 1.4, 1.55334, 1.93877, 2.18387, 2.45866, 2.61041,
+ 1.37352, 1.44979, 1.8806, 2.07984, 2.29824, 2.55977,
+ 1.36754, 1.44075, 1.97377, 2.08607, 2.33911, 2.62191,
+ 1.36884, 1.46082, 2.00605, 2.12979, 2.39152, 2.65052,
+ 1.37599, 1.49624, 2.05005, 2.13085, 2.45392, 2.69863,
+ 1.34057, 1.48416, 2.08413, 2.14094, 2.54992, 2.68543,
+ 1.38997, 1.55301, 2.06378, 2.14798, 2.59226, 2.70382,
+ 1.24745, 1.50338, 2.0443, 2.13649, 2.34449, 2.59917,
+ 1.31511, 1.54085, 2.02833, 2.11633, 2.27254, 2.43155,
+ 1.29883, 1.58749, 2.07193, 2.18587, 2.33569, 2.50078,
+ 1.29366, 1.56243, 2.0311, 2.14961, 2.40817, 2.51729,
+ 1.35755, 1.5133, 1.99809, 2.15305, 2.45046, 2.5838,
+ 1.31441, 1.51742, 2.07946, 2.17944, 2.52229, 2.6162,
+ 1.23775, 1.51356, 2.05223, 2.18107, 2.53904, 2.62816,
+ 1.20856, 1.48604, 2.0465, 2.19467, 2.48998, 2.63667,
+ 1.19657, 1.46249, 2.07314, 2.23086, 2.54763, 2.7006,
+ 1.08094, 1.45943, 2.1105, 2.21771, 2.53813, 2.67835,
+ 1.09448, 1.37861, 2.16788, 2.24618, 2.56793, 2.69132,
+ 0.942435, 1.46334, 2.25353, 2.33078, 2.53848, 2.62677,
+ 0.828468, 1.39017, 2.15232, 2.21803, 2.54527, 2.62149,
+ 0.883311, 1.3342, 2.09482, 2.19126, 2.47558, 2.57346,
+ 0.863185, 1.41868, 2.08049, 2.16638, 2.5561, 2.71409,
+ 0.84852, 1.39108, 2.04932, 2.13419, 2.70254, 2.78082,
+ 0.826225, 1.37358, 2.03739, 2.12058, 2.73609, 2.78259,
+ 0.823246, 1.34385, 2.03389, 2.1118, 2.74087, 2.78707,
+ 0.833848, 1.33679, 2.04545, 2.11801, 2.69961, 2.79618,
+ 0.811654, 1.32134, 2.09499, 2.17812, 2.49423, 2.6499,
+ 0.947528, 1.36115, 2.12785, 2.21901, 2.51138, 2.66819,
+ 0.875759, 1.25161, 2.13342, 2.24175, 2.47382, 2.66293,
+ 0.933534, 1.44844, 2.13913, 2.24451, 2.48676, 2.60694,
+ 0.945109, 1.2808, 2.20894, 2.33506, 2.51132, 2.61453,
+ 0.956935, 1.37124, 2.1072, 2.19452, 2.40325, 2.57303,
+ 0.981, 1.25193, 2.14796, 2.2666, 2.44042, 2.62437,
+ 1.06161, 1.23169, 2.07602, 2.2334, 2.4386, 2.63699,
+ 1.01887, 1.35404, 1.99803, 2.26008, 2.44314, 2.55477,
+ 1.0803, 1.30189, 2.03463, 2.1456, 2.41506, 2.59122,
+ 1.13387, 1.35976, 2.06395, 2.16463, 2.43939, 2.62866,
+ 1.12504, 1.41413, 1.99754, 2.10372, 2.39242, 2.59958,
+ 1.16727, 1.39356, 1.99818, 2.07648, 2.44178, 2.64329,
+ 1.1987, 1.42119, 1.96798, 2.05702, 2.43282, 2.64507,
+ 1.25623, 1.37807, 1.94185, 2.01933, 2.44458, 2.60885,
+ 1.29557, 1.41215, 1.93241, 2.00835, 2.43005, 2.64902,
+ 1.28135, 1.46452, 1.88824, 2.00652, 2.42528, 2.6352,
+ 1.27058, 1.4067, 1.90119, 1.96929, 2.47098, 2.6479,
+ 1.2667, 1.37289, 1.87181, 1.95759, 2.41497, 2.64862,
+ 1.19439, 1.35174, 1.88825, 1.97809, 2.40086, 2.66266,
+ 1.19887, 1.29984, 1.86428, 1.96365, 2.36279, 2.61951,
+ 1.12658, 1.2401, 1.90254, 1.99765, 2.33143, 2.60863,
+ 1.10462, 1.21418, 1.87979, 2.01431, 2.25166, 2.57337,
+ 1.02429, 1.19321, 1.86892, 2.12788, 2.37601, 2.62345,
+ 1.00036, 1.23021, 1.9603, 2.07524, 2.32935, 2.58413,
+ 0.977548, 1.32199, 1.98875, 2.10426, 2.38103, 2.60792,
+ 0.927608, 1.44792, 2.02789, 2.12301, 2.47848, 2.58588,
+ 0.887733, 1.51653, 2.0469, 2.15389, 2.48052, 2.58201,
+ 0.898681, 1.56475, 2.09153, 2.17965, 2.57394, 2.67678,
+ 0.974718, 1.50086, 2.08197, 2.17778, 2.53228, 2.63499,
+ 1.02382, 1.39064, 2.06059, 2.14203, 2.46939, 2.63691,
+ 1.10658, 1.43105, 1.97713, 2.09715, 2.47169, 2.65912,
+ 1.20126, 1.48566, 1.94465, 2.11254, 2.50025, 2.66593,
+ 1.28569, 1.52066, 1.91106, 2.04425, 2.48771, 2.6658,
+ 1.36249, 1.53479, 1.91055, 1.99094, 2.50571, 2.66153,
+ 1.43459, 1.51484, 1.93419, 2.01741, 2.50153, 2.69388,
+ 1.42084, 1.51949, 1.90935, 1.98665, 2.4604, 2.68819,
+ 1.40441, 1.46981, 1.96429, 2.05423, 2.36679, 2.65527,
+ 1.38829, 1.46691, 1.96405, 2.05895, 2.28653, 2.60493,
+ 1.368, 1.43481, 1.8577, 2.00712, 2.19658, 2.60419,
+ 1.30084, 1.38054, 1.74025, 2.04689, 2.23523, 2.52191,
+ 1.2313, 1.3216, 1.86723, 2.14763, 2.35463, 2.57914,
+ 1.15492, 1.2559, 1.93232, 2.16437, 2.39283, 2.60599,
+ 1.09866, 1.20222, 1.94827, 2.15016, 2.4926, 2.62574,
+ 1.05746, 1.22185, 1.86913, 2.26883, 2.45654, 2.58036,
+ 1.03308, 1.1501, 1.70887, 2.26488, 2.47604, 2.56361,
+ 0.988998, 1.15927, 1.96203, 2.30271, 2.44872, 2.56072,
+ 1.02842, 1.22869, 2.02591, 2.26037, 2.56185, 2.66176,
+ 0.93486, 1.34821, 2.05389, 2.21474, 2.5253, 2.64771,
+ 0.91915, 1.26456, 2.06814, 2.1834, 2.53498, 2.64432,
+ 0.975247, 1.36223, 2.05215, 2.23142, 2.5828, 2.72448,
+ 0.954336, 1.31118, 1.97737, 2.23816, 2.47811, 2.61705,
+ 0.941853, 1.33598, 1.97642, 2.21901, 2.57949, 2.7143,
+ 0.928694, 1.36645, 1.88488, 2.18315, 2.58056, 2.65759,
+ 0.986067, 1.33837, 1.95432, 2.18786, 2.56652, 2.63883,
+ 0.912646, 1.2844, 1.81414, 2.17507, 2.55393, 2.63852,
+ 0.968965, 1.3105, 1.83969, 2.07808, 2.59033, 2.66057,
+ 0.977192, 1.30463, 1.88095, 2.12702, 2.59804, 2.71211,
+ 1.02384, 1.29962, 1.94471, 2.10378, 2.62592, 2.7309,
+ 1.11021, 1.28631, 1.95938, 2.05397, 2.56459, 2.67613,
+ 1.02814, 1.32424, 1.97674, 2.09494, 2.5862, 2.75473,
+ 1.1298, 1.26991, 2.01187, 2.10922, 2.5889, 2.69654,
+ 1.05697, 1.34048, 2.01617, 2.10555, 2.55761, 2.74716,
+ 1.0375, 1.25577, 2.02939, 2.13619, 2.51178, 2.70963,
+ 1.00616, 1.41717, 2.07195, 2.13261, 2.5439, 2.70196,
+ 1.13696, 1.41621, 2.05034, 2.11204, 2.44967, 2.6952,
+ 1.13532, 1.43627, 2.08385, 2.19492, 2.38638, 2.65693,
+ 1.09407, 1.38546, 2.01516, 2.11333, 2.3201, 2.64153,
+ 1.02593, 1.36065, 1.8783, 1.98146, 2.12804, 2.45894,
+ 1.14275, 1.41616, 1.90101, 2.05488, 2.17021, 2.45905,
+ 1.09321, 1.48838, 1.80138, 2.07358, 2.20343, 2.49483,
+ 1.16124, 1.26326, 1.78481, 2.0712, 2.19458, 2.43622,
+ 1.01079, 1.14118, 1.72817, 2.11872, 2.25127, 2.42633,
+ 1.0838, 1.27598, 1.88843, 2.06839, 2.22746, 2.51111,
+ 1.09382, 1.3034, 1.92409, 2.18396, 2.34853, 2.5317,
+ 1.40987, 1.54006, 1.72233, 2.04991, 2.23569, 2.38925,
+ 1.4666, 1.61703, 1.81939, 2.03581, 2.43973, 2.54332,
+ 1.52688, 1.81173, 1.92615, 2.1292, 2.48147, 2.55606,
+ 1.42046, 1.73161, 1.92536, 2.08112, 2.47445, 2.57028,
+ 1.24837, 1.46252, 1.69927, 1.90711, 2.35535, 2.4848,
+ 1.18322, 1.55816, 1.64662, 1.99981, 2.37407, 2.4616,
+ 1.14384, 1.51329, 1.67569, 1.90675, 2.42836, 2.51879,
+ 1.06699, 1.50005, 1.66753, 1.96146, 2.4459, 2.52156,
+ 1.04665, 1.52076, 1.70516, 1.87838, 2.45976, 2.53273,
+ 1.01371, 1.55953, 1.73753, 1.95585, 2.43782, 2.51586,
+ 1.02195, 1.58688, 1.73703, 1.92918, 2.52364, 2.57788,
+ 0.942307, 1.57915, 1.7761, 2.06027, 2.43722, 2.51765,
+ 0.914226, 1.64208, 1.8128, 2.00109, 2.50851, 2.57006,
+ 0.952017, 1.68807, 1.93502, 2.01615, 2.44679, 2.56358,
+ 0.85628, 1.69751, 1.90273, 2.01269, 2.52241, 2.5844,
+ 0.891878, 1.55315, 1.9355, 2.04697, 2.53266, 2.59497,
+ 0.845424, 1.60229, 1.93772, 2.02752, 2.58302, 2.64917,
+ 0.876501, 1.71662, 1.93957, 2.06754, 2.58826, 2.62536,
+ 0.901014, 1.86437, 1.97892, 2.07519, 2.46267, 2.6098,
+ 0.911677, 1.76785, 1.94779, 2.07258, 2.59574, 2.63495,
+ 0.937394, 1.70873, 1.92774, 2.05461, 2.57411, 2.64743,
+ 1.00365, 1.61461, 1.94206, 2.03598, 2.59201, 2.66472,
+ 1.08941, 1.56371, 1.91069, 1.97496, 2.59091, 2.68182,
+ 1.1802, 1.45723, 1.84084, 1.92159, 2.57341, 2.65935,
+ 1.23938, 1.44428, 1.81891, 1.89387, 2.5596, 2.65742,
+ 1.37732, 1.52899, 1.7449, 1.86222, 2.59116, 2.66907,
+ 1.5049, 1.58946, 1.77776, 1.88723, 2.50621, 2.61775,
+ 1.62841, 1.69744, 1.8306, 1.95757, 2.49541, 2.65298,
+ 1.65534, 1.72676, 1.91445, 2.04295, 2.58971, 2.65897,
+ 1.69817, 1.75401, 1.96719, 2.09043, 2.60271, 2.67713,
+ 1.6763, 1.76771, 2.04285, 2.15667, 2.62832, 2.69069,
+ 1.72497, 1.78993, 2.02225, 2.13845, 2.57623, 2.67177,
+ 1.74819, 1.80267, 2.03778, 2.18025, 2.54251, 2.63895,
+ 1.72749, 1.82059, 1.98449, 2.15907, 2.52527, 2.64111,
+ 1.68116, 1.82095, 1.9757, 2.15738, 2.4858, 2.59041,
+ 1.69559, 1.80719, 1.99368, 2.18089, 2.38033, 2.56086,
+ 1.70693, 1.8107, 2.00812, 2.1331, 2.42075, 2.64175,
+ 1.65458, 1.76573, 2.02476, 2.12403, 2.49348, 2.66085,
+ 1.48228, 1.84953, 2.03934, 2.24048, 2.45722, 2.54777,
+ 1.60391, 1.83254, 2.0516, 2.25163, 2.46114, 2.56041,
+ 1.61191, 1.78732, 2.13446, 2.25032, 2.62094, 2.67828,
+ 1.70226, 1.85766, 2.09357, 2.24578, 2.63356, 2.6878,
+ 1.69236, 1.77625, 2.02619, 2.27536, 2.58055, 2.68324,
+ 1.58711, 1.7503, 1.99794, 2.24207, 2.58654, 2.69145,
+ 1.53555, 1.76534, 2.05361, 2.23362, 2.64673, 2.71788,
+ 1.18962, 1.33679, 1.76375, 2.00182, 2.43607, 2.59429,
+ 1.19096, 1.32263, 1.6625, 2.02854, 2.34741, 2.53098,
+ 1.17093, 1.39469, 1.72743, 2.02281, 2.38266, 2.5526,
+ 1.0828, 1.38331, 1.62323, 1.82565, 2.46313, 2.57449,
+ 1.05886, 1.31642, 1.61784, 1.7344, 2.49668, 2.60735,
+ 1.03174, 1.33271, 1.53473, 1.70742, 2.43327, 2.54421,
+ 1.09663, 1.40593, 1.54058, 1.71992, 2.50965, 2.57321,
+ 1.08814, 1.38193, 1.50722, 1.61855, 2.48411, 2.61844,
+ 1.12836, 1.34181, 1.49417, 1.71555, 2.49597, 2.57986,
+ 1.17504, 1.36011, 1.5729, 1.75716, 2.48116, 2.58891,
+ 1.25184, 1.38829, 1.58041, 1.74429, 2.53023, 2.61428,
+ 1.31074, 1.44427, 1.65725, 1.82349, 2.51511, 2.6146,
+ 1.32959, 1.48366, 1.70393, 1.87146, 2.53237, 2.62192,
+ 1.36465, 1.5031, 1.75584, 1.91903, 2.54748, 2.62441,
+ 1.40014, 1.51678, 1.80865, 1.94381, 2.57234, 2.65555,
+ 1.40394, 1.53678, 1.85457, 1.96117, 2.52777, 2.65014,
+ 1.44164, 1.5349, 1.87363, 1.97075, 2.52812, 2.67083,
+ 1.44861, 1.52867, 1.86098, 1.95195, 2.47324, 2.65781,
+ 1.45162, 1.54784, 1.82415, 2.01998, 2.46245, 2.6541,
+ 1.47491, 1.54848, 1.89089, 1.99547, 2.48461, 2.65999,
+ 1.43235, 1.54152, 1.88892, 2.0602, 2.40709, 2.63044,
+ 1.44374, 1.52979, 1.8927, 1.99659, 2.3738, 2.62098,
+ 1.37922, 1.48973, 1.89736, 2.01674, 2.41678, 2.6275,
+ 1.37707, 1.46312, 1.91165, 2.02262, 2.35539, 2.60865,
+ 1.3318, 1.43104, 1.92917, 2.0469, 2.37404, 2.605,
+ 1.26139, 1.44854, 1.97546, 2.08252, 2.36686, 2.6208,
+ 1.22253, 1.41897, 1.97979, 2.11631, 2.43959, 2.66463,
+ 1.14294, 1.30444, 1.9845, 2.07136, 2.47308, 2.67295,
+ 1.16307, 1.26852, 1.93044, 2.0463, 2.3051, 2.59445,
+ 1.10251, 1.24609, 1.95173, 2.10327, 2.29978, 2.57198,
+ 1.01057, 1.14733, 1.90254, 2.04624, 2.28802, 2.567,
+ 1.01047, 1.307, 1.82765, 2.07687, 2.33326, 2.55597,
+ 1.24634, 1.53463, 1.85908, 2.18799, 2.38807, 2.54162,
+ 1.20049, 1.57894, 1.89923, 2.16502, 2.44888, 2.58318,
+ 0.969958, 1.32117, 1.8792, 2.16627, 2.41795, 2.60245,
+ 0.883738, 1.35958, 2.00452, 2.10073, 2.51698, 2.63339,
+ 0.844286, 1.40555, 2.05705, 2.14052, 2.51643, 2.66006,
+ 0.862435, 1.50233, 2.10741, 2.20516, 2.55819, 2.66049,
+ 0.940459, 1.42824, 2.13982, 2.23332, 2.56448, 2.67376,
+ 0.930987, 1.58398, 2.0219, 2.15239, 2.40404, 2.50634,
+ 1.04656, 1.79826, 1.98842, 2.12929, 2.35758, 2.45354,
+ 1.05348, 1.59375, 2.10433, 2.23268, 2.37281, 2.49815,
+ 1.13765, 1.64278, 2.08915, 2.23181, 2.38316, 2.57557,
+ 1.18078, 1.89984, 2.11471, 2.22334, 2.45315, 2.55491,
+ 1.14477, 1.7958, 2.05817, 2.1941, 2.45214, 2.55875,
+ 1.13255, 1.6883, 1.98025, 2.10745, 2.32195, 2.44657,
+ 1.15584, 1.527, 1.95125, 2.10187, 2.26567, 2.42326,
+ 1.21899, 1.55188, 1.97893, 2.1295, 2.36524, 2.54789,
+ 1.26996, 1.59283, 1.9574, 2.05925, 2.47736, 2.62007,
+ 1.30477, 1.59715, 1.97427, 2.08441, 2.41441, 2.61344,
+ 1.30461, 1.64552, 1.9768, 2.10058, 2.36447, 2.5106,
+ 1.35745, 1.72162, 2.01397, 2.14179, 2.38518, 2.51214,
+ 1.33572, 1.83391, 2.00127, 2.15585, 2.40144, 2.4961,
+ 1.3114, 1.55829, 1.93876, 2.06328, 2.30727, 2.52662,
+ 1.36036, 1.44076, 1.89358, 2.07531, 2.23753, 2.5046,
+ 1.3316, 1.46849, 1.9289, 2.06096, 2.31803, 2.56782,
+ 1.31861, 1.5376, 1.92447, 2.01519, 2.35881, 2.59331,
+ 1.21436, 1.54619, 1.8821, 1.99525, 2.37793, 2.65294,
+ 1.29633, 1.56653, 1.87514, 2.00328, 2.47632, 2.63153,
+ 1.39778, 1.58615, 1.86148, 2.03011, 2.58706, 2.65465,
+ 1.47524, 1.6442, 1.91588, 2.04703, 2.65327, 2.71442,
+ 1.52474, 1.71602, 1.95782, 2.06765, 2.6237, 2.69024,
+ 1.57869, 1.67781, 1.94092, 2.06678, 2.61383, 2.70458,
+ 1.55866, 1.70253, 1.93011, 2.02827, 2.61505, 2.68653,
+ 1.5009, 1.6999, 1.90892, 1.99874, 2.62063, 2.69128,
+ 1.44295, 1.70267, 1.90099, 1.97533, 2.62473, 2.69924,
+ 1.37288, 1.63829, 1.91771, 2.02829, 2.62618, 2.69745,
+ 1.28422, 1.65621, 1.89785, 1.99256, 2.64442, 2.70738,
+ 1.20404, 1.65182, 1.88977, 1.99256, 2.63849, 2.70958,
+ 1.1492, 1.62207, 1.88451, 1.97925, 2.63269, 2.69924,
+ 1.13373, 1.61863, 1.89504, 1.97754, 2.62505, 2.69488,
+ 1.15757, 1.66233, 1.88978, 1.97839, 2.62603, 2.68454,
+ 1.21894, 1.6671, 1.87906, 2.00517, 2.60227, 2.65813,
+ 1.22423, 1.62686, 1.79198, 1.89465, 2.51764, 2.64787,
+ 1.35435, 1.55876, 1.84308, 1.93089, 2.57122, 2.63086,
+ 1.33953, 1.59509, 1.76225, 1.97927, 2.54602, 2.6132,
+ 1.38922, 1.59242, 1.85964, 1.96212, 2.55095, 2.63771,
+ 1.44127, 1.59043, 1.87939, 1.98705, 2.58201, 2.66674,
+ 1.43103, 1.60981, 1.89027, 2.03787, 2.52504, 2.67206,
+ 1.46838, 1.57542, 1.94585, 2.02987, 2.55147, 2.70532,
+ 1.45009, 1.60143, 1.9541, 2.0628, 2.53413, 2.66697,
+ 1.48217, 1.56544, 1.97359, 2.12415, 2.52021, 2.65602,
+ 1.42942, 1.56017, 1.98437, 2.07841, 2.51093, 2.66835,
+ 1.44091, 1.58793, 1.97609, 2.09796, 2.46414, 2.62167,
+ 1.43247, 1.58261, 1.97335, 2.15993, 2.50051, 2.66833,
+ 1.4291, 1.59392, 1.97481, 2.07021, 2.52705, 2.68379,
+ 1.37725, 1.57105, 1.93703, 2.09434, 2.48861, 2.65319,
+ 1.48527, 1.57272, 1.93552, 2.01586, 2.47189, 2.68702,
+ 1.47361, 1.56926, 1.87262, 1.96288, 2.4128, 2.65437,
+ 1.48606, 1.58025, 1.86625, 1.97554, 2.31875, 2.58671,
+ 1.46521, 1.58112, 1.78499, 1.91302, 2.17248, 2.55592,
+ 1.43366, 1.56634, 1.72851, 1.85326, 2.06197, 2.41395,
+ 1.36761, 1.54384, 1.70007, 1.85497, 2.03462, 2.28202,
+ 1.50326, 1.65718, 1.80936, 1.93767, 2.14319, 2.43561,
+ 1.34074, 1.59327, 1.83384, 2.12941, 2.46894, 2.57284,
+ 1.33672, 1.4817, 1.94477, 2.23061, 2.48029, 2.58012,
+ 1.32132, 1.60314, 1.96833, 2.20337, 2.5151, 2.65005,
+ 1.34193, 1.66834, 1.98884, 2.18525, 2.56414, 2.65322,
+ 1.31555, 1.6489, 1.9599, 2.14764, 2.51689, 2.61262,
+ 1.27731, 1.62022, 2.00186, 2.22941, 2.53155, 2.62182,
+ 1.30517, 1.5786, 2.03863, 2.29551, 2.56534, 2.65484,
+ 1.33051, 1.60991, 1.99154, 2.26271, 2.56334, 2.66596,
+ 1.374, 1.68393, 1.98007, 2.33857, 2.5956, 2.68273,
+ 1.2687, 1.38975, 1.88538, 2.1104, 2.48811, 2.63864,
+ 1.21681, 1.31005, 1.85469, 2.03671, 2.27759, 2.56653,
+ 1.23495, 1.33781, 1.94943, 2.05936, 2.29533, 2.56647,
+ 1.18894, 1.30239, 1.9962, 2.10744, 2.34919, 2.58524,
+ 1.26898, 1.44015, 2.02477, 2.13685, 2.44401, 2.66404,
+ 1.27437, 1.38312, 2.06673, 2.15117, 2.40756, 2.6542,
+ 1.26455, 1.35612, 2.00166, 2.11886, 2.28778, 2.56954,
+ 1.23434, 1.32978, 2.06339, 2.15077, 2.36719, 2.5986,
+ 1.15521, 1.25744, 2.0825, 2.21144, 2.39059, 2.6201,
+ 1.19946, 1.26556, 1.93498, 2.22669, 2.54089, 2.6642,
+ 1.3047, 1.52685, 1.95455, 2.17466, 2.47769, 2.62171,
+ 1.63807, 1.89626, 2.07708, 2.36101, 2.64603, 2.71884,
+ 1.64382, 1.94311, 2.13199, 2.32962, 2.57872, 2.64546,
+ 1.6409, 1.98922, 2.16147, 2.26921, 2.58647, 2.6554,
+ 1.72301, 1.91007, 2.07019, 2.25957, 2.56439, 2.64034,
+ 1.65207, 1.99873, 2.13594, 2.35282, 2.65251, 2.71747,
+ 1.68072, 2.07409, 2.26967, 2.45347, 2.69994, 2.76304,
+ 1.69509, 2.05897, 2.19364, 2.31357, 2.63934, 2.69945,
+ 1.78296, 2.01403, 2.2249, 2.33229, 2.64535, 2.7244,
+ 1.70596, 1.97475, 2.18083, 2.25608, 2.57518, 2.71694,
+ 1.66256, 1.98864, 2.11518, 2.20528, 2.54838, 2.65766,
+ 1.56205, 1.8439, 2.17327, 2.26589, 2.47795, 2.69597,
+ 1.68592, 1.79584, 2.07833, 2.18014, 2.46537, 2.66731,
+ 1.68061, 1.73855, 1.99474, 2.13119, 2.47319, 2.64954,
+ 1.65929, 1.83364, 2.00009, 2.14017, 2.56491, 2.69272,
+ 1.71489, 1.78482, 1.97491, 2.08523, 2.56667, 2.70104,
+ 1.72911, 1.82606, 1.89504, 2.05372, 2.60392, 2.69924,
+ 1.69629, 1.79108, 1.91604, 2.01774, 2.58311, 2.7042,
+ 1.62684, 1.72099, 1.89044, 2.01448, 2.58919, 2.68914,
+ 1.57418, 1.678, 1.8808, 1.9828, 2.57498, 2.66408,
+ 1.4326, 1.67638, 1.83467, 1.96466, 2.5353, 2.63865,
+ 1.31853, 1.53537, 1.83696, 1.93288, 2.47841, 2.57835,
+ 1.22629, 1.49295, 1.83642, 1.94607, 2.43017, 2.58207,
+ 1.09891, 1.49905, 1.89629, 2.02887, 2.54053, 2.6186,
+ 1.03446, 1.53337, 1.96484, 2.07097, 2.57858, 2.65152,
+ 0.979835, 1.48091, 1.97596, 2.08932, 2.53424, 2.63263,
+ 0.916592, 1.48129, 1.96751, 2.05329, 2.55835, 2.64274,
+ 0.937338, 1.47437, 2.02376, 2.11046, 2.58544, 2.66546,
+ 0.873055, 1.56053, 2.0288, 2.08642, 2.57502, 2.68478,
+ 0.901938, 1.62841, 2.03181, 2.10285, 2.61016, 2.68565,
+ 0.862562, 1.55614, 1.99757, 2.08174, 2.5332, 2.61576,
+ 0.90614, 1.66574, 2.01937, 2.13334, 2.58193, 2.66115,
+ 0.872836, 1.63866, 2.03844, 2.09728, 2.64501, 2.69779,
+ 0.829264, 1.4419, 2.03919, 2.11114, 2.61166, 2.68861,
+ 0.825197, 1.30453, 2.05635, 2.14379, 2.59031, 2.65782,
+ 0.79352, 1.52102, 1.97944, 2.05842, 2.59623, 2.66858,
+ 0.849751, 1.48553, 1.9861, 2.05546, 2.62427, 2.7019,
+ 0.849936, 1.38559, 2.00752, 2.06058, 2.56723, 2.67845,
+ 0.829655, 1.23098, 1.9884, 2.10148, 2.53073, 2.67733,
+ 0.940677, 1.26451, 1.94632, 2.04672, 2.49981, 2.67798,
+ 1.03888, 1.29749, 1.95821, 2.036, 2.40697, 2.65032,
+ 1.15791, 1.24731, 1.89251, 1.98433, 2.39699, 2.6634,
+ 1.23706, 1.31883, 1.84331, 1.95477, 2.42085, 2.69391,
+ 1.32887, 1.40395, 1.80868, 1.94612, 2.40089, 2.6834,
+ 1.39319, 1.46081, 1.82213, 1.9396, 2.24255, 2.72323,
+ 1.37096, 1.52614, 1.78537, 1.96316, 2.13675, 2.6448,
+ 1.50113, 1.60677, 1.84183, 2.00946, 2.19846, 2.61465,
+ 1.46794, 1.55147, 1.84985, 1.98283, 2.2086, 2.51479,
+ 1.40594, 1.48098, 1.85598, 1.99706, 2.17872, 2.49001,
+ 1.44817, 1.52096, 1.86881, 1.97537, 2.24103, 2.61635,
+ 1.38081, 1.61267, 1.86996, 2.02679, 2.44348, 2.63998,
+ 1.48372, 1.59611, 1.96973, 2.10091, 2.57743, 2.68814,
+ 1.46768, 1.57822, 1.98656, 2.19471, 2.57095, 2.67109,
+ 1.4963, 1.6142, 2.03202, 2.21832, 2.55346, 2.68181,
+ 1.59696, 1.72273, 2.14453, 2.31998, 2.60439, 2.70396,
+ 1.56328, 1.83007, 2.21313, 2.43293, 2.64111, 2.721,
+ 1.5911, 1.94848, 2.28841, 2.48658, 2.66684, 2.74357,
+ 1.47571, 1.71866, 2.05098, 2.21796, 2.48728, 2.5718,
+ 1.55893, 1.7723, 2.09447, 2.23446, 2.51893, 2.59774,
+ 1.56759, 1.82209, 2.10059, 2.28665, 2.53395, 2.64811,
+ 1.75003, 1.93667, 2.1356, 2.34764, 2.5469, 2.63832,
+ 1.75688, 1.99858, 2.1168, 2.22341, 2.55656, 2.64706,
+ 1.70004, 1.92226, 2.07535, 2.18437, 2.55608, 2.63906,
+ 1.59867, 1.70971, 1.99456, 2.09879, 2.5214, 2.62844,
+ 1.60978, 1.7198, 1.93753, 2.09198, 2.54758, 2.62107,
+ 1.58074, 1.68669, 1.92793, 2.05951, 2.58033, 2.64353,
+ 1.54116, 1.68466, 1.9448, 2.03825, 2.56852, 2.6371,
+ 1.4745, 1.63389, 1.88133, 1.98885, 2.5547, 2.62359,
+ 1.42769, 1.61681, 1.89847, 1.99412, 2.54591, 2.63584,
+ 1.36697, 1.58374, 1.86076, 2.01809, 2.52625, 2.59403,
+ 1.2579, 1.5624, 1.87076, 1.96175, 2.51205, 2.58959,
+ 1.18331, 1.57125, 1.86744, 1.98879, 2.54377, 2.60779,
+ 1.13772, 1.60719, 1.87915, 2.00877, 2.5368, 2.60748,
+ 1.05382, 1.51142, 1.90444, 2.00239, 2.58485, 2.65709,
+ 1.02931, 1.56067, 1.91347, 1.98444, 2.61342, 2.67092,
+ 0.990299, 1.5203, 1.91971, 2.00599, 2.61587, 2.70596,
+ 0.927002, 1.48685, 1.9001, 1.97777, 2.61462, 2.69576,
+ 0.924166, 1.5003, 1.83727, 1.91582, 2.60179, 2.70283,
+ 0.901854, 1.42276, 1.89801, 1.95014, 2.57299, 2.7593,
+ 0.910623, 1.28648, 1.80128, 1.92579, 2.43815, 2.67129,
+ 0.904293, 1.22614, 1.87334, 1.94691, 2.48527, 2.64553,
+ 0.872654, 1.12266, 1.9125, 2.04762, 2.46806, 2.64549,
+ 1.13608, 1.24801, 1.7254, 2.18063, 2.49378, 2.5794,
+ 1.1615, 1.34697, 1.80404, 2.15702, 2.55031, 2.63316,
+ 1.28729, 1.66372, 2.04419, 2.32192, 2.59928, 2.68713,
+ 1.4568, 1.75827, 2.05527, 2.31065, 2.54931, 2.66007,
+ 1.41695, 1.74137, 2.10419, 2.35776, 2.59176, 2.67954,
+ 1.37953, 1.75252, 2.17341, 2.36107, 2.6175, 2.69932,
+ 1.361, 1.76202, 2.11571, 2.33066, 2.562, 2.65039,
+ 1.34078, 1.68536, 2.02489, 2.28195, 2.54742, 2.63946,
+ 1.27817, 1.68614, 1.96141, 2.16547, 2.55417, 2.64787,
+ 1.29452, 1.54762, 1.98197, 2.18343, 2.54751, 2.63723,
+ 1.20162, 1.34364, 2.00786, 2.08943, 2.53568, 2.66074,
+ 1.202, 1.33211, 1.94915, 2.05181, 2.5532, 2.66547,
+ 1.18035, 1.35425, 1.89052, 2.06991, 2.51523, 2.62012,
+ 1.12873, 1.41976, 1.85478, 2.05663, 2.4807, 2.58354,
+ 1.13319, 1.40234, 1.82266, 2.01361, 2.53991, 2.63944,
+ 1.14927, 1.37693, 1.82119, 1.91493, 2.56242, 2.66404,
+ 1.08087, 1.40844, 1.78802, 1.87993, 2.51751, 2.65668,
+ 1.15244, 1.5096, 1.82234, 1.93981, 2.52894, 2.61915,
+ 1.22726, 1.54378, 1.93541, 2.01768, 2.57551, 2.66563,
+ 1.25365, 1.48594, 1.94554, 1.98737, 2.53919, 2.71509,
+ 1.2245, 1.52134, 1.98216, 2.04494, 2.52268, 2.68745,
+ 1.25872, 1.47612, 1.98186, 2.0731, 2.53617, 2.63409,
+ 1.25558, 1.47113, 1.98394, 2.05256, 2.54104, 2.70865,
+ 1.22142, 1.55673, 2.01332, 2.08977, 2.5386, 2.7065,
+ 1.17848, 1.47465, 2.00764, 2.12209, 2.56026, 2.62943,
+ 1.13664, 1.45929, 2.03373, 2.10043, 2.5447, 2.68913,
+ 1.0352, 1.46256, 2.02497, 2.19409, 2.5306, 2.66221,
+ 1.09088, 1.52242, 2.03844, 2.12942, 2.58762, 2.68739,
+ 1.05454, 1.53834, 2.00059, 2.08401, 2.51651, 2.64433,
+ 1.06957, 1.47115, 1.97701, 2.10266, 2.54822, 2.64566,
+ 1.08464, 1.23507, 1.99903, 2.09101, 2.40519, 2.62241,
+ 1.07391, 1.18049, 1.96138, 2.10188, 2.2553, 2.5318,
+ 1.18554, 1.32028, 2.00675, 2.09885, 2.44308, 2.58297,
+ 1.25681, 1.41999, 1.98353, 2.13096, 2.47042, 2.55869,
+ 1.29074, 1.39192, 1.99538, 2.10656, 2.35166, 2.48517,
+ 1.42857, 1.7483, 2.04481, 2.27757, 2.51309, 2.62525,
+ 1.49577, 1.68666, 2.13566, 2.29223, 2.49901, 2.6165,
+ 1.48246, 1.63201, 2.08388, 2.29724, 2.48855, 2.60533,
+ 1.53884, 1.63087, 2.11175, 2.22311, 2.57684, 2.69324,
+ 1.55163, 1.62855, 2.0406, 2.158, 2.59018, 2.71351,
+ 1.57001, 1.63772, 1.9581, 2.12426, 2.57018, 2.69279,
+ 1.53459, 1.60799, 1.80164, 2.08727, 2.3927, 2.60093,
+ 1.50278, 1.60763, 1.8438, 2.08234, 2.32328, 2.52239,
+ 1.5157, 1.61344, 1.83784, 2.02724, 2.40291, 2.60224,
+ 1.51003, 1.60758, 1.82642, 1.95546, 2.34057, 2.67962,
+ 1.44583, 1.56664, 1.75642, 1.86971, 2.29615, 2.60165,
+ 1.41071, 1.48852, 1.82002, 1.91044, 2.35823, 2.61465,
+ 1.30157, 1.42828, 1.81243, 1.90258, 2.29336, 2.72528,
+ 1.10681, 1.35151, 1.88873, 1.95633, 2.32044, 2.64689,
+ 1.05626, 1.36692, 1.86662, 1.96895, 2.42146, 2.65352,
+ 1.14875, 1.36805, 1.80964, 2.06411, 2.43779, 2.6041,
+ 0.99027, 1.45316, 1.88728, 2.03517, 2.29694, 2.6003,
+ 0.943695, 1.20427, 1.748, 1.88645, 2.18161, 2.5098,
+ 1.05705, 1.2214, 1.83597, 1.97244, 2.15495, 2.49297,
+ 0.936404, 1.22552, 1.89505, 1.99806, 2.53953, 2.64493,
+ 0.941516, 1.22449, 1.96641, 2.05527, 2.51509, 2.60908,
+ 1.00024, 1.31497, 1.942, 2.05192, 2.53588, 2.63478,
+ 1.03139, 1.4074, 1.95347, 2.04544, 2.55082, 2.63437,
+ 1.11887, 1.44195, 1.95252, 2.062, 2.49434, 2.60804,
+ 1.1971, 1.55316, 1.88765, 2.00919, 2.4721, 2.55066,
+ 1.2938, 1.58834, 1.86838, 2.04592, 2.4811, 2.56611,
+ 1.35377, 1.61065, 1.89762, 2.08348, 2.40829, 2.5434,
+ 1.40368, 1.522, 1.89167, 2.05414, 2.35729, 2.51225,
+ 1.3704, 1.44625, 1.87133, 1.99814, 2.33668, 2.57069,
+ 1.49939, 1.75525, 2.09033, 2.28295, 2.48403, 2.57439,
+ 1.56771, 1.84261, 2.13662, 2.27873, 2.47712, 2.57607,
+ 1.59155, 1.76754, 2.16941, 2.30293, 2.52513, 2.6375,
+ 1.45827, 1.79974, 2.22722, 2.3975, 2.61653, 2.70557,
+ 1.49671, 1.84604, 2.2799, 2.43719, 2.64967, 2.72662,
+ 1.50276, 1.73132, 2.26873, 2.46421, 2.62362, 2.70674,
+ 1.4973, 1.61793, 2.15658, 2.38626, 2.57903, 2.66472,
+ 1.37998, 1.53869, 1.85063, 2.10952, 2.41066, 2.58615,
+ 1.40587, 1.49793, 1.7417, 1.93228, 2.33718, 2.56385,
+ 1.34617, 1.43104, 1.65743, 1.88442, 2.37395, 2.58735,
+ 1.30791, 1.40637, 1.73414, 1.87583, 2.46072, 2.60209,
+ 1.27394, 1.57115, 1.77128, 1.91225, 2.53645, 2.59561,
+ 1.20006, 1.57518, 1.77085, 1.87763, 2.50802, 2.57915,
+ 1.12581, 1.53942, 1.72263, 1.85997, 2.51165, 2.57463,
+ 1.0649, 1.48451, 1.69086, 1.83275, 2.51958, 2.58928,
+ 1.04287, 1.48323, 1.62712, 1.86708, 2.49587, 2.55026,
+ 0.95091, 1.47482, 1.57611, 1.83009, 2.51944, 2.56991,
+ 1.00452, 1.42303, 1.55012, 1.83522, 2.4736, 2.54437,
+ 1.02641, 1.36569, 1.51066, 1.87911, 2.46718, 2.54387,
+ 0.978321, 1.33849, 1.52802, 1.91388, 2.46507, 2.52472,
+ 0.922555, 1.40958, 1.52026, 1.93266, 2.40471, 2.47222,
+ 1.00902, 1.34503, 1.51873, 1.99953, 2.46306, 2.54494,
+ 0.989351, 1.43316, 1.57387, 2.01544, 2.4012, 2.49098,
+ 1.03533, 1.55632, 1.67731, 2.08678, 2.48152, 2.56795,
+ 1.00412, 1.57529, 1.79639, 2.07552, 2.40291, 2.57424,
+ 1.03735, 1.68182, 1.94311, 2.06542, 2.47889, 2.5989,
+ 1.00585, 1.68475, 1.97239, 2.10931, 2.56505, 2.62351,
+ 0.954873, 1.71979, 2.00619, 2.11235, 2.59863, 2.68278,
+ 0.937994, 1.72832, 1.99376, 2.10525, 2.63205, 2.70071,
+ 0.889626, 1.70953, 2.00129, 2.09009, 2.62054, 2.7098,
+ 0.912128, 1.65762, 1.96678, 2.05864, 2.62643, 2.70292,
+ 0.972006, 1.56912, 1.98595, 2.13024, 2.56915, 2.67726,
+ 1.03879, 1.65117, 2.00829, 2.11811, 2.59919, 2.70129,
+ 1.1022, 1.62499, 1.99876, 2.12503, 2.56976, 2.64664,
+ 1.18774, 1.63937, 2.05924, 2.1473, 2.47586, 2.63496,
+ 1.2741, 1.59067, 2.01675, 2.09963, 2.54872, 2.66899,
+ 1.3734, 1.63001, 1.98149, 2.07093, 2.50595, 2.68933,
+ 1.51121, 1.60261, 1.91134, 2.0229, 2.47594, 2.64575,
+ 1.55308, 1.6394, 1.8704, 1.97561, 2.47343, 2.62657,
+ 1.63342, 1.77332, 1.87513, 1.95948, 2.41315, 2.62591,
+ 1.59672, 1.74731, 1.87805, 2.04902, 2.58749, 2.66928,
+ 1.66467, 1.93335, 2.15604, 2.28003, 2.46274, 2.57155,
+ 1.55119, 1.6958, 2.0471, 2.23698, 2.44759, 2.57084,
+ 1.6483, 1.72807, 2.06079, 2.27374, 2.47514, 2.6312,
+ 1.63355, 1.75757, 2.08928, 2.24098, 2.43612, 2.55685,
+ 1.60864, 1.68471, 2.12375, 2.25657, 2.4865, 2.59823,
+ 1.65318, 1.71454, 2.10535, 2.20323, 2.50932, 2.64178,
+ 1.54105, 1.67996, 2.10427, 2.24726, 2.54038, 2.62672,
+ 1.55966, 1.65964, 2.10138, 2.21367, 2.47324, 2.563,
+ 1.60881, 1.67178, 2.07143, 2.18483, 2.49328, 2.63946,
+ 1.53888, 1.61019, 2.08308, 2.17154, 2.55439, 2.65099,
+ 1.51102, 1.59546, 2.03164, 2.13009, 2.5876, 2.6604,
+ 1.34069, 1.58784, 1.931, 2.11712, 2.59986, 2.67657,
+ 1.48468, 1.53325, 2.02449, 2.11315, 2.54832, 2.65995,
+ 1.53434, 1.60831, 2.03154, 2.136, 2.5371, 2.61772,
+ 1.57158, 1.61831, 2.05673, 2.13975, 2.52541, 2.62221,
+ 1.56447, 1.63127, 2.06059, 2.16604, 2.47, 2.63566,
+ 1.53365, 1.66351, 2.09396, 2.19079, 2.40674, 2.62275,
+ 1.57012, 1.63104, 2.04937, 2.16517, 2.39357, 2.5885,
+ 1.55247, 1.63452, 2.00848, 2.09888, 2.5092, 2.66932,
+ 1.49854, 1.60281, 2.00888, 2.09973, 2.52514, 2.65917,
+ 1.45092, 1.66054, 1.99176, 2.1033, 2.54407, 2.69647,
+ 1.4476, 1.5691, 1.99305, 2.07976, 2.58771, 2.67639,
+ 1.39457, 1.5447, 2.00666, 2.07897, 2.57902, 2.72188,
+ 1.34792, 1.50775, 1.99379, 2.07733, 2.51023, 2.68268,
+ 1.26519, 1.35538, 1.87785, 2.06383, 2.4258, 2.6578,
+ 1.2663, 1.37693, 2.00888, 2.27501, 2.47904, 2.63616,
+ 1.41473, 1.68062, 2.0574, 2.33275, 2.54997, 2.65245,
+ 1.49988, 1.70879, 2.05474, 2.31358, 2.52103, 2.61391,
+ 1.44568, 1.74177, 2.12639, 2.33881, 2.49512, 2.59797,
+ 1.4592, 1.79234, 2.11349, 2.34607, 2.5637, 2.66497,
+ 1.41684, 1.64439, 2.13147, 2.32291, 2.5788, 2.67716,
+ 1.44797, 1.70822, 2.14489, 2.27258, 2.59321, 2.70087,
+ 1.47461, 1.74298, 2.06694, 2.34163, 2.60175, 2.68525,
+ 1.34672, 1.65394, 1.99915, 2.21854, 2.63336, 2.7236,
+ 1.37521, 1.55141, 2.05268, 2.23201, 2.58684, 2.69703,
+ 1.26095, 1.50175, 1.9252, 2.03394, 2.54669, 2.65203,
+ 1.25934, 1.50019, 1.90965, 1.98291, 2.54588, 2.63867,
+ 1.25284, 1.56384, 1.91059, 1.97368, 2.57931, 2.66428,
+ 1.263, 1.54633, 1.87808, 2.03115, 2.58347, 2.65379,
+ 1.2652, 1.52127, 1.90571, 1.96739, 2.58143, 2.65872,
+ 1.3077, 1.54772, 1.88142, 1.96204, 2.57347, 2.65883,
+ 1.29134, 1.57501, 1.91524, 1.98556, 2.60208, 2.6977,
+ 1.29543, 1.62646, 1.9233, 2.02372, 2.59129, 2.68014,
+ 1.30121, 1.62408, 1.87893, 1.99808, 2.5601, 2.63451,
+ 1.30581, 1.62092, 1.88803, 1.98904, 2.60623, 2.66943,
+ 1.30809, 1.64233, 1.88596, 2.01357, 2.61191, 2.69665,
+ 1.3121, 1.62786, 1.86184, 1.9741, 2.60262, 2.65849,
+ 1.2929, 1.60573, 1.87713, 1.97339, 2.59964, 2.68284,
+ 1.27314, 1.59174, 1.87042, 1.94745, 2.60233, 2.67415,
+ 1.28358, 1.62082, 1.84727, 1.92803, 2.59005, 2.63688,
+ 1.2462, 1.56007, 1.85162, 1.95453, 2.58753, 2.67354,
+ 1.26039, 1.53964, 1.83162, 1.92843, 2.55229, 2.62963,
+ 1.26122, 1.50523, 1.85731, 1.93391, 2.569, 2.69631,
+ 1.28311, 1.71986, 1.8239, 1.97603, 2.56544, 2.62875,
+ 1.31439, 1.61774, 1.80406, 1.96054, 2.59681, 2.68674,
+ 1.3387, 1.63728, 1.89693, 2.00913, 2.52347, 2.63738,
+ 1.33648, 1.57703, 1.85003, 1.94324, 2.52134, 2.59683,
+ 1.39891, 1.54928, 1.72446, 1.86193, 2.16679, 2.46633,
+ 1.40689, 1.49743, 1.80504, 1.90912, 2.28428, 2.54258,
+ 1.47485, 1.57937, 1.97076, 2.0797, 2.37143, 2.54262,
+ 1.45231, 1.5394, 2.07666, 2.138, 2.44297, 2.64951,
+ 1.45062, 1.50661, 2.03639, 2.13145, 2.48483, 2.67472,
+ 1.4348, 1.58308, 2.02767, 2.13681, 2.42911, 2.57834,
+ 1.08757, 1.36721, 1.7863, 2.02503, 2.29808, 2.51567,
+ 0.992092, 1.43643, 1.72551, 1.96511, 2.42572, 2.54902,
+ 0.969474, 1.49732, 1.73009, 2.01605, 2.41437, 2.63332,
+ 0.936277, 1.41301, 1.68361, 2.02977, 2.4431, 2.55283,
+ 1.17635, 1.55964, 1.74877, 2.06189, 2.31148, 2.43469,
+ 1.06711, 1.40664, 1.64389, 1.97881, 2.37473, 2.54784,
+ 0.989262, 1.33311, 1.47509, 1.72865, 2.49202, 2.55347,
+ 0.957471, 1.30854, 1.42456, 1.82347, 2.49022, 2.55232,
+ 1.03577, 1.25449, 1.35208, 1.78625, 2.53949, 2.58578,
+ 1.02368, 1.23242, 1.39848, 1.87577, 2.45168, 2.54025,
+ 1.03725, 1.24729, 1.38742, 2.00855, 2.41927, 2.49611,
+ 1.04592, 1.23169, 1.36195, 1.88761, 2.38445, 2.4715,
+ 1.00098, 1.25084, 1.37666, 1.76767, 2.39805, 2.48444,
+ 1.06177, 1.21461, 1.41076, 1.72825, 2.42398, 2.51427,
+ 1.16823, 1.29119, 1.59751, 1.90001, 2.41542, 2.55501,
+ 1.15079, 1.41286, 1.82595, 1.95326, 2.40005, 2.53532,
+ 1.16692, 1.51763, 1.94353, 2.03425, 2.37336, 2.52147,
+ 1.18318, 1.52316, 1.99531, 2.11989, 2.43346, 2.59116,
+ 1.15948, 1.52173, 2.07237, 2.17696, 2.5149, 2.66076,
+ 1.26032, 1.72266, 2.11677, 2.24905, 2.53412, 2.64563,
+ 1.45043, 1.71771, 2.04879, 2.21275, 2.49949, 2.63613,
+ 1.44923, 1.65312, 2.02364, 2.19689, 2.45305, 2.61252,
+ 1.38812, 1.59757, 1.96865, 2.16345, 2.42543, 2.57803,
+ 1.3476, 1.44981, 1.89414, 2.16897, 2.44647, 2.60227,
+ 1.39801, 1.47176, 1.92206, 2.12096, 2.39643, 2.60072,
+ 1.42866, 1.54131, 2.04605, 2.13251, 2.39709, 2.6431,
+ 1.49267, 1.58516, 2.05934, 2.1583, 2.48082, 2.64875,
+ 1.55899, 1.64879, 2.03751, 2.15332, 2.51238, 2.64766,
+ 1.5875, 1.65909, 2.0205, 2.13969, 2.53746, 2.61656,
+ 1.63435, 1.73936, 2.04449, 2.21819, 2.53013, 2.62274,
+ 1.65015, 1.73677, 2.04927, 2.14892, 2.55187, 2.65129,
+ 1.6407, 1.70735, 1.99133, 2.11956, 2.58759, 2.64283,
+ 1.65582, 1.70975, 1.94195, 2.09079, 2.57008, 2.63037,
+ 1.60644, 1.69562, 1.85276, 2.04784, 2.5549, 2.62809,
+ 1.48459, 1.65703, 1.82298, 2.00896, 2.58403, 2.65372,
+ 1.34838, 1.6278, 1.77907, 1.89733, 2.52187, 2.6464,
+ 1.15564, 1.46487, 1.7638, 1.94355, 2.55585, 2.64209,
+ 1.33945, 1.67633, 1.97104, 2.1868, 2.43889, 2.57107,
+ 1.29738, 1.61553, 1.94676, 2.15118, 2.42984, 2.55813,
+ 1.13646, 1.51989, 1.86723, 2.10739, 2.45273, 2.55371,
+ 0.943433, 1.35098, 1.71433, 1.83088, 2.38004, 2.57361,
+ 0.93395, 1.07858, 1.55309, 1.66234, 2.02795, 2.45315,
+ 0.896937, 1.24693, 1.58663, 1.68408, 2.39714, 2.61171,
+ 0.892078, 1.35006, 1.56008, 1.68985, 2.50628, 2.60756,
+ 0.772181, 1.31368, 1.52566, 1.65028, 2.46898, 2.63641,
+ 0.863603, 1.32858, 1.48114, 1.76889, 2.49678, 2.54657,
+ 0.908312, 1.25841, 1.38277, 1.69975, 2.44859, 2.54733,
+ 0.863083, 1.2738, 1.42241, 1.57588, 2.50992, 2.5671,
+ 0.798143, 1.23338, 1.32805, 1.71855, 2.54548, 2.65489,
+ 0.937997, 1.29721, 1.44739, 1.65945, 2.53943, 2.66437,
+ 1.01531, 1.28265, 1.44965, 1.65693, 2.51959, 2.59724,
+ 1.0126, 1.30809, 1.42876, 1.74264, 2.58138, 2.65475,
+ 1.07522, 1.35994, 1.46636, 1.79046, 2.58293, 2.65492,
+ 1.17472, 1.35459, 1.47068, 1.80811, 2.61181, 2.6906,
+ 1.30467, 1.38057, 1.48642, 1.86325, 2.49909, 2.64664,
+ 1.32925, 1.45894, 1.59974, 1.9851, 2.41224, 2.4896,
+ 1.32685, 1.46696, 1.65071, 1.97288, 2.17365, 2.36378,
+ 1.44073, 1.59786, 1.75692, 1.94212, 2.13442, 2.3309,
+ 1.49091, 1.61528, 1.79973, 1.98918, 2.30719, 2.53596,
+ 1.523, 1.67644, 1.84139, 2.08449, 2.49007, 2.6195,
+ 1.53645, 1.67293, 1.83434, 2.06794, 2.59485, 2.65573,
+ 1.58521, 1.67342, 1.87935, 2.02614, 2.60916, 2.69133,
+ 1.57645, 1.66211, 1.86811, 1.98727, 2.62983, 2.70249,
+ 1.56114, 1.62908, 1.91041, 2.00543, 2.63344, 2.72614,
+ 1.53121, 1.61555, 1.87364, 1.96628, 2.52259, 2.70606,
+ 1.47329, 1.59122, 1.90894, 1.97341, 2.53504, 2.73312,
+ 1.41254, 1.47364, 1.87172, 1.95732, 2.3412, 2.7407,
+ 1.37981, 1.47324, 1.92392, 1.98607, 2.44717, 2.65758,
+ 1.33369, 1.50012, 1.93353, 2.13803, 2.5018, 2.61583,
+ 1.40577, 1.57009, 2.02811, 2.33267, 2.57368, 2.66412,
+ 1.38605, 1.54675, 2.10184, 2.38012, 2.6073, 2.71246,
+ 1.42055, 1.66408, 2.09684, 2.28767, 2.54543, 2.64567,
+ 1.42992, 1.63289, 2.05645, 2.24534, 2.46973, 2.59462,
+ 1.45034, 1.54233, 1.93614, 2.16009, 2.38966, 2.59495,
+ 1.45865, 1.54584, 1.97395, 2.13284, 2.28055, 2.51911,
+ 1.49962, 1.62185, 1.92436, 2.08658, 2.25382, 2.39346,
+ 1.48012, 1.59661, 1.8229, 2.03008, 2.21246, 2.44059,
+ 1.38557, 1.51579, 1.76353, 2.00756, 2.20701, 2.50516,
+ 1.36348, 1.48371, 1.74539, 2.02083, 2.17738, 2.42842,
+ 1.42241, 1.52636, 1.80247, 2.04137, 2.26763, 2.50998,
+ 1.45178, 1.5395, 1.88862, 2.07975, 2.25853, 2.50082,
+ 1.46274, 1.54888, 1.92575, 2.06529, 2.3201, 2.59188,
+ 1.45961, 1.52679, 1.9373, 2.02975, 2.426, 2.61822,
+ 1.42677, 1.49596, 1.9348, 2.02868, 2.47432, 2.63994,
+ 1.39548, 1.4946, 1.92354, 2.00687, 2.5088, 2.6516,
+ 1.31532, 1.47588, 1.92587, 2.01244, 2.56254, 2.64267,
+ 1.21621, 1.54231, 1.86761, 1.96291, 2.57851, 2.63891,
+ 1.18812, 1.59211, 1.82616, 1.95676, 2.59273, 2.65931,
+ 1.15728, 1.51903, 1.84128, 1.93613, 2.59672, 2.66939,
+ 1.04273, 1.33486, 1.85281, 1.92781, 2.50926, 2.72139,
+ 1.07692, 1.51273, 1.89221, 1.97602, 2.37074, 2.63564,
+ 1.32864, 1.55521, 1.82696, 2.08002, 2.44793, 2.60775,
+ 1.27122, 1.38353, 1.74055, 2.04872, 2.35626, 2.56711,
+ 1.28876, 1.38548, 1.79387, 1.97785, 2.3904, 2.60455,
+ 1.32866, 1.42224, 1.80564, 2.00282, 2.28916, 2.5443,
+ 1.37794, 1.49365, 1.79368, 2.03187, 2.35373, 2.51891,
+ 1.38443, 1.45365, 1.83807, 2.00184, 2.39078, 2.63512,
+ 1.28946, 1.40343, 1.87102, 1.98612, 2.47998, 2.7238,
+ 1.20789, 1.38822, 1.86505, 2.03166, 2.45007, 2.59141,
+ 1.21863, 1.30931, 1.90985, 2.00378, 2.49942, 2.60498,
+ 1.17883, 1.2733, 1.83281, 2.02504, 2.50863, 2.65023,
+ 1.14748, 1.25919, 1.93016, 2.02773, 2.52207, 2.63407,
+ 1.10091, 1.26803, 1.85791, 1.9519, 2.50889, 2.66039,
+ 1.06983, 1.22567, 1.88895, 1.97434, 2.49213, 2.5921,
+ 1.04226, 1.18221, 1.89174, 2.03996, 2.55965, 2.67933,
+ 0.956414, 1.18097, 1.88146, 1.99433, 2.31647, 2.61769,
+ 1.06179, 1.5717, 1.92657, 2.10718, 2.40416, 2.52545,
+ 1.37431, 1.4759, 1.67843, 1.97242, 2.36429, 2.51653,
+ 1.36344, 1.45577, 1.76316, 1.9708, 2.36833, 2.58698,
+ 1.42304, 1.59189, 1.7982, 2.01278, 2.38811, 2.60218,
+ 1.52726, 1.60578, 1.90951, 2.03343, 2.40668, 2.59346,
+ 1.58513, 1.66451, 1.91801, 2.02654, 2.42573, 2.60092,
+ 1.61189, 1.72856, 1.90767, 2.03404, 2.39568, 2.64177,
+ 1.46301, 1.62466, 1.87229, 1.99824, 2.48782, 2.66247,
+ 1.50707, 1.59791, 1.89375, 1.99701, 2.53598, 2.67246,
+ 1.5024, 1.61803, 1.88856, 2.02416, 2.58185, 2.65654,
+ 1.55312, 1.63948, 1.91892, 2.03428, 2.57686, 2.65568,
+ 1.57736, 1.64826, 1.95809, 2.05341, 2.56789, 2.65652,
+ 1.59537, 1.65463, 1.99777, 2.09975, 2.53164, 2.67521,
+ 1.62164, 1.70401, 1.95775, 2.07464, 2.58431, 2.66051,
+ 1.61843, 1.71139, 1.95479, 2.06745, 2.53377, 2.69523,
+ 1.61785, 1.71631, 1.94968, 2.10336, 2.63594, 2.68689,
+ 1.64932, 1.74631, 1.90161, 2.06435, 2.60677, 2.69024,
+ 1.63506, 1.7696, 1.90462, 2.0191, 2.6076, 2.71333,
+ 1.64557, 1.7795, 1.86895, 1.96533, 2.59215, 2.7149,
+ 1.68657, 1.7575, 1.85807, 1.92204, 2.50527, 2.69889,
+ 1.61272, 1.70323, 1.83105, 1.9259, 2.37381, 2.61368,
+ 1.24435, 1.40956, 1.71346, 1.9677, 2.35146, 2.53736,
+ 1.26999, 1.3873, 1.64097, 1.99183, 2.32491, 2.50177,
+ 1.30535, 1.45577, 1.78878, 2.09123, 2.48724, 2.61473,
+ 1.41386, 1.51881, 1.88852, 2.25227, 2.44809, 2.59472,
+ 1.40942, 1.59146, 1.94472, 2.19692, 2.51839, 2.63823,
+ 1.39914, 1.70331, 1.96615, 2.22486, 2.61691, 2.73408,
+ 1.37531, 1.63638, 2.06176, 2.29242, 2.58662, 2.70574,
+ 1.39467, 1.73342, 2.0736, 2.29715, 2.57382, 2.67289,
+ 1.36608, 1.73861, 2.01663, 2.28566, 2.60549, 2.69352,
+ 1.36062, 1.60169, 1.96797, 2.19484, 2.56485, 2.65792,
+ 1.3547, 1.47154, 1.99017, 2.16544, 2.569, 2.67912,
+ 1.31937, 1.40392, 2.03022, 2.11501, 2.4527, 2.63591,
+ 1.30326, 1.37473, 1.97504, 2.11117, 2.36982, 2.66061,
+ 1.32579, 1.43105, 2.03617, 2.11394, 2.476, 2.68507,
+ 1.30748, 1.51036, 2.1177, 2.17917, 2.55458, 2.69578,
+ 1.31143, 1.54831, 2.12835, 2.27973, 2.5517, 2.6455,
+ 1.29377, 1.44223, 2.11556, 2.28956, 2.4159, 2.53121,
+ 1.27867, 1.69711, 2.0925, 2.19954, 2.36852, 2.56114,
+ 1.29264, 1.86793, 2.12883, 2.20633, 2.45084, 2.55178,
+ 1.23486, 1.63107, 2.1437, 2.30446, 2.49101, 2.56573,
+ 1.21995, 1.36757, 2.1498, 2.21849, 2.49521, 2.6353,
+ 1.2089, 1.48484, 2.1803, 2.27669, 2.52633, 2.62673,
+ 1.16526, 1.45824, 2.15559, 2.22728, 2.49018, 2.5968,
+ 1.11619, 1.49218, 2.17727, 2.2419, 2.53233, 2.62053,
+ 1.0969, 1.52492, 2.09349, 2.34525, 2.48036, 2.61116,
+ 1.04378, 1.36903, 2.22928, 2.30665, 2.52743, 2.61303,
+ 1.08072, 1.33613, 2.13554, 2.24061, 2.46344, 2.63428,
+ 1.12626, 1.50254, 2.06533, 2.27483, 2.51283, 2.58825,
+ 1.19913, 1.448, 2.04058, 2.21686, 2.44913, 2.5443,
+ 1.2443, 1.54083, 2.03653, 2.17483, 2.47027, 2.58034,
+ 1.27719, 1.57406, 2.06637, 2.15037, 2.50854, 2.61173,
+ 1.34175, 1.57688, 2.03148, 2.12065, 2.49616, 2.57534,
+ 1.33544, 1.5416, 1.99434, 2.1088, 2.51884, 2.62295,
+ 1.35172, 1.54371, 2.00331, 2.07535, 2.57916, 2.65663,
+ 1.3593, 1.47053, 1.96846, 2.04232, 2.56515, 2.66484,
+ 1.3682, 1.43322, 1.98377, 2.04495, 2.4386, 2.6706,
+ 1.35118, 1.42613, 1.99129, 2.08773, 2.43075, 2.61637,
+ 1.34987, 1.4833, 2.00027, 2.24283, 2.53591, 2.62905,
+ 1.32206, 1.59678, 2.11312, 2.40815, 2.54898, 2.62526,
+ 1.38129, 1.64876, 2.19246, 2.37836, 2.57952, 2.6545,
+ 1.37213, 1.54266, 2.06255, 2.30731, 2.47559, 2.58062,
+ 1.36357, 1.46348, 1.86476, 2.28846, 2.4678, 2.57169,
+ 1.33579, 1.5363, 1.88616, 2.22187, 2.54338, 2.67053,
+ 1.25976, 1.39335, 1.60476, 1.93429, 2.43051, 2.5096,
+ 1.22472, 1.34965, 1.48194, 1.83683, 2.38496, 2.46313,
+ 1.25366, 1.36921, 1.50551, 1.99434, 2.36606, 2.45456,
+ 1.25045, 1.37222, 1.56344, 2.13328, 2.39153, 2.46111,
+ 1.29898, 1.41253, 1.56, 2.16285, 2.47558, 2.55147,
+ 1.3087, 1.48723, 1.61657, 2.14089, 2.42252, 2.52784,
+ 1.36226, 1.50974, 1.69114, 2.15185, 2.42506, 2.50401,
+ 1.41519, 1.57382, 1.72634, 2.14569, 2.42361, 2.51895,
+ 1.4683, 1.62457, 1.768, 2.10708, 2.43369, 2.50188,
+ 1.47421, 1.64517, 1.82938, 2.15047, 2.33054, 2.45413,
+ 1.48873, 1.66222, 1.85318, 2.16043, 2.39072, 2.50747,
+ 1.51537, 1.6851, 1.8209, 2.09082, 2.47713, 2.54132,
+ 1.53394, 1.68102, 1.91115, 2.10105, 2.43121, 2.50742,
+ 1.54702, 1.76275, 1.90532, 2.0573, 2.36997, 2.49646,
+ 1.52475, 1.7075, 1.88085, 2.14514, 2.33129, 2.4433,
+ 1.53267, 1.68946, 1.83844, 2.06671, 2.35207, 2.48759,
+ 1.44908, 1.63991, 1.78652, 2.04704, 2.32879, 2.42622,
+ 1.39341, 1.607, 1.75213, 2.06596, 2.381, 2.47377,
+ 1.23492, 1.62038, 1.75171, 2.07935, 2.40097, 2.47182,
+ 1.12865, 1.58919, 1.72598, 2.09781, 2.42178, 2.50718,
+ 1.20512, 1.49111, 1.70703, 2.14313, 2.40768, 2.4896,
+ 1.10599, 1.52409, 1.74026, 2.14252, 2.42276, 2.53271,
+ 1.14687, 1.42809, 1.69879, 2.10033, 2.42333, 2.5455,
+ 1.11601, 1.3519, 1.75431, 2.14602, 2.4117, 2.52754,
+ 1.17851, 1.30684, 1.82411, 2.27204, 2.45289, 2.54631,
+ 1.38605, 1.68653, 2.01082, 2.14869, 2.4392, 2.57093,
+ 1.33438, 1.67405, 1.96249, 2.10873, 2.40392, 2.5875,
+ 1.30954, 1.51943, 2.0306, 2.11973, 2.43608, 2.6208,
+ 1.19962, 1.42519, 2.03789, 2.16133, 2.49331, 2.63953,
+ 0.913804, 1.25173, 2.05508, 2.17687, 2.41685, 2.64493,
+ 0.822137, 1.06733, 2.01912, 2.21659, 2.39556, 2.65819,
+ 0.859923, 0.985874, 1.90428, 2.16059, 2.43371, 2.63982,
+ 0.906761, 1.14062, 2.0105, 2.14624, 2.46964, 2.64413,
+ 0.950845, 1.25396, 2.03953, 2.0959, 2.60028, 2.71109,
+ 0.953879, 1.24532, 1.98547, 2.13315, 2.54365, 2.613,
+ 1.03167, 1.28659, 1.97462, 2.03713, 2.54102, 2.69028,
+ 1.0516, 1.37316, 1.90525, 2.00964, 2.49555, 2.67405,
+ 1.08826, 1.2974, 1.89869, 2.01858, 2.50884, 2.69051,
+ 1.1467, 1.28227, 1.93071, 2.01015, 2.43941, 2.64701,
+ 1.1572, 1.34385, 1.93082, 2.02912, 2.36815, 2.598,
+ 1.24735, 1.43274, 1.94259, 2.06745, 2.39283, 2.5543,
+ 1.29762, 1.51602, 1.99339, 2.07927, 2.43946, 2.54827,
+ 1.38625, 1.4836, 1.96585, 2.07161, 2.44479, 2.59437,
+ 1.42969, 1.49987, 1.88063, 2.07411, 2.3462, 2.60425,
+ 1.56913, 1.64448, 1.94276, 2.0452, 2.37069, 2.58937,
+ 1.69636, 1.74562, 1.98094, 2.09366, 2.43348, 2.58367,
+ 1.69484, 1.80115, 1.96103, 2.06832, 2.45264, 2.63829,
+ 1.61979, 1.78559, 1.91963, 2.05582, 2.23816, 2.49876,
+ 1.22369, 1.62122, 1.79172, 1.89869, 2.16167, 2.49995,
+ 1.14441, 1.45291, 1.78089, 1.86674, 2.21421, 2.49427,
+ 1.13554, 1.49512, 1.82078, 1.89436, 2.11501, 2.44158,
+ 1.13138, 1.53582, 1.73732, 1.84242, 2.02164, 2.42595,
+ 1.21265, 1.31217, 1.75291, 1.88932, 2.10891, 2.4697,
+ 1.25395, 1.35241, 1.65265, 1.96095, 2.39444, 2.56868,
+ 1.36268, 1.58079, 1.91332, 2.21262, 2.3816, 2.52899,
+ 1.41733, 1.58205, 1.97763, 2.23799, 2.41308, 2.58029,
+ 1.38316, 1.60355, 2.01614, 2.21013, 2.44905, 2.58723,
+ 1.44211, 1.54421, 1.93895, 2.14188, 2.495, 2.59016,
+ 1.38173, 1.57916, 1.982, 2.13878, 2.48578, 2.62057,
+ 1.36159, 1.59781, 1.96493, 2.13812, 2.54261, 2.62247,
+ 1.36066, 1.61469, 2.01078, 2.1615, 2.46045, 2.5839,
+ 1.39009, 1.62865, 1.96383, 2.13056, 2.47773, 2.61338,
+ 1.34617, 1.6485, 2.08237, 2.32171, 2.55595, 2.64942,
+ 1.44042, 1.74244, 2.00765, 2.20824, 2.45099, 2.57791,
+ 1.44483, 1.69506, 2.02687, 2.21048, 2.41403, 2.53277,
+ 1.34554, 1.58917, 1.95542, 2.12931, 2.40989, 2.54316,
+ 1.40004, 1.48192, 1.94707, 2.11026, 2.31316, 2.53117,
+ 1.38478, 1.48479, 1.98387, 2.10714, 2.36009, 2.58548,
+ 1.42919, 1.51494, 2.01966, 2.13766, 2.32955, 2.58529,
+ 1.45055, 1.51832, 2.01003, 2.1028, 2.40169, 2.60328,
+ 1.44136, 1.52541, 1.96497, 2.07672, 2.37601, 2.59481,
+ 1.46479, 1.52155, 1.96899, 2.07787, 2.44496, 2.62108,
+ 1.4867, 1.57368, 2.00184, 2.10852, 2.43377, 2.62616,
+ 1.47103, 1.5436, 1.99166, 2.11171, 2.47331, 2.64546,
+ 1.41527, 1.52449, 2.0127, 2.09575, 2.45882, 2.64202,
+ 1.40751, 1.50149, 2.05031, 2.1562, 2.48019, 2.62327,
+ 1.37612, 1.45958, 2.00994, 2.16941, 2.4802, 2.64269,
+ 1.34595, 1.47288, 2.07312, 2.18486, 2.48613, 2.61036,
+ 1.30637, 1.43838, 2.0905, 2.21314, 2.5542, 2.68395,
+ 1.21926, 1.42304, 2.09092, 2.17049, 2.55962, 2.66821,
+ 1.18047, 1.40808, 1.93517, 2.08818, 2.54813, 2.63944,
+ 1.20954, 1.52893, 1.88727, 1.96188, 2.48344, 2.64934,
+ 1.21992, 1.52138, 1.93918, 1.98802, 2.46003, 2.67348,
+ 1.19875, 1.4741, 1.85911, 1.98104, 2.39535, 2.7192,
+ 1.11841, 1.50485, 1.89794, 2.00238, 2.24287, 2.59852,
+ 1.01853, 1.45989, 1.74659, 2.05195, 2.32486, 2.45885,
+ 0.86699, 1.38778, 1.6541, 1.79974, 2.32579, 2.40738,
+ 0.862252, 1.36583, 1.70576, 1.80225, 2.41635, 2.49385,
+ 0.928394, 1.54645, 1.71668, 1.87707, 2.37972, 2.52459,
+ 1.08335, 1.48734, 1.80115, 2.00569, 2.32174, 2.55873,
+ 1.05743, 1.3398, 1.83442, 1.9346, 2.27962, 2.5307,
+ 0.954787, 1.141, 1.79287, 1.8918, 2.34291, 2.49204,
+ 0.996853, 1.13004, 1.79215, 1.89541, 2.23624, 2.40335,
+ 0.920268, 1.06949, 1.87486, 2.07209, 2.33523, 2.48657,
+ 0.954214, 1.08107, 1.82732, 2.07915, 2.23882, 2.50812,
+ 0.894487, 1.01384, 1.71654, 2.01845, 2.17535, 2.48224,
+ 0.842005, 0.979634, 1.64453, 1.9459, 2.27102, 2.43863,
+ 0.95571, 1.09, 1.75405, 1.96707, 2.12784, 2.44888,
+ 0.954385, 1.09447, 1.72755, 2.00558, 2.26657, 2.5144,
+ 1.02562, 1.1376, 1.78753, 2.00208, 2.3369, 2.51184,
+ 1.01381, 1.1751, 1.88194, 2.01664, 2.34586, 2.44572,
+ 1.08267, 1.2273, 1.92324, 2.02278, 2.40238, 2.52097,
+ 1.11811, 1.22414, 1.82445, 1.96175, 2.24583, 2.51583,
+ 1.14645, 1.29899, 1.87293, 1.99547, 2.37173, 2.5269,
+ 1.18855, 1.31065, 1.90221, 1.99678, 2.29037, 2.52054,
+ 1.30992, 1.41653, 1.87845, 2.05009, 2.22418, 2.38779,
+ 1.39476, 1.50627, 1.93489, 2.05682, 2.27119, 2.45334,
+ 1.37793, 1.57264, 1.9907, 2.08357, 2.38159, 2.60652,
+ 1.44402, 1.6893, 1.99746, 2.15321, 2.36113, 2.5077,
+ 1.51504, 1.64277, 1.92909, 2.15934, 2.33551, 2.49784,
+ 1.54008, 1.70831, 1.88382, 2.09498, 2.39862, 2.5701,
+ 1.60091, 1.69851, 1.88148, 2.08517, 2.45101, 2.65374,
+ 1.50263, 1.75606, 2.04072, 2.1634, 2.37617, 2.54867,
+ 1.53211, 1.85534, 1.99384, 2.13955, 2.30249, 2.43099,
+ 1.48486, 1.82205, 1.9643, 2.13596, 2.33702, 2.47234,
+ 1.53669, 1.76692, 1.95125, 2.09052, 2.32417, 2.52921,
+ 1.58228, 1.72385, 1.91207, 2.06937, 2.30294, 2.4739,
+ 1.49971, 1.59329, 1.9127, 2.0341, 2.36655, 2.55379,
+ 1.4342, 1.54071, 1.86757, 1.98917, 2.32371, 2.5394,
+ 1.1891, 1.50082, 1.76342, 1.9762, 2.13728, 2.44118,
+ 1.16592, 1.47018, 1.773, 1.9271, 2.08801, 2.3043,
+ 1.25015, 1.60042, 1.81807, 1.92211, 2.08025, 2.24181,
+ 1.12269, 1.6288, 1.81441, 1.93295, 2.0993, 2.41867,
+ 1.01962, 1.51066, 1.85073, 1.99562, 2.1302, 2.45706,
+ 0.958176, 1.63968, 1.84043, 1.95653, 2.10428, 2.27903,
+ 1.01054, 1.53751, 1.77222, 1.93052, 2.10162, 2.24851,
+ 0.904371, 1.50502, 1.66433, 1.82788, 2.27803, 2.34842,
+ 1.06773, 1.45454, 1.68686, 1.80346, 2.38437, 2.49979,
+ 1.26287, 1.516, 1.88275, 1.97556, 2.35357, 2.51973,
+ 1.56064, 1.69896, 1.92154, 2.00006, 2.54029, 2.60523,
+ 1.66562, 1.74409, 1.99592, 2.104, 2.53894, 2.62016,
+ 1.61517, 1.7485, 2.02411, 2.12606, 2.40816, 2.61413,
+ 1.67803, 1.75295, 2.0279, 2.14656, 2.38237, 2.56851,
+ 1.58035, 1.68027, 1.99741, 2.12246, 2.45985, 2.58783,
+ 1.59008, 1.69205, 1.93478, 2.09576, 2.55298, 2.62588,
+ 1.539, 1.62024, 1.92077, 2.0316, 2.48167, 2.59269,
+ 1.4088, 1.51179, 1.74425, 1.89659, 2.41202, 2.51558,
+ 1.32056, 1.48799, 1.75496, 1.89691, 2.43716, 2.56318,
+ 1.17487, 1.52485, 1.70818, 1.96295, 2.51378, 2.58101,
+ 1.28764, 1.55957, 1.90308, 2.10518, 2.45098, 2.59946,
+ 1.22403, 1.508, 1.92279, 2.07637, 2.37291, 2.58121,
+ 1.16322, 1.44496, 1.73467, 2.02018, 2.32215, 2.54157,
+ 1.21226, 1.448, 1.63849, 2.03192, 2.22935, 2.39947,
+ 1.10889, 1.28333, 1.48115, 1.90707, 2.10001, 2.29348,
+ 1.15522, 1.29037, 1.47672, 1.68807, 2.08922, 2.18177,
+ 1.17147, 1.29039, 1.55651, 1.82599, 2.01814, 2.24349,
+ 1.14989, 1.28265, 1.6019, 1.7453, 2.11078, 2.40906,
+ 1.22391, 1.36072, 1.65007, 1.79294, 2.2651, 2.37093,
+ 1.25437, 1.40454, 1.70667, 1.85465, 2.27647, 2.39469,
+ 1.22583, 1.44211, 1.76613, 1.92412, 2.2924, 2.39468,
+ 1.21114, 1.46189, 1.80455, 1.92702, 2.36199, 2.45328,
+ 1.21864, 1.40578, 1.80953, 1.9142, 2.31845, 2.52005,
+ 1.22294, 1.39467, 1.84011, 1.9324, 2.39167, 2.50319,
+ 1.2069, 1.37287, 1.84295, 1.9438, 2.42446, 2.57876,
+ 1.24631, 1.42383, 1.86621, 1.96241, 2.43605, 2.59566,
+ 1.27092, 1.4559, 1.88805, 1.97634, 2.46928, 2.58281,
+ 1.19826, 1.32394, 1.88024, 1.94941, 2.47166, 2.6448,
+ 1.17432, 1.2932, 1.76561, 2.01928, 2.28224, 2.57624,
+ 1.14173, 1.38319, 1.88283, 2.12653, 2.45304, 2.61119,
+ 1.48334, 1.65073, 2.04359, 2.1938, 2.51727, 2.62292,
+ 1.44607, 1.6219, 1.99961, 2.10353, 2.49348, 2.58192,
+ 1.41467, 1.63024, 1.94568, 2.06177, 2.50065, 2.58895,
+ 1.43843, 1.61559, 1.90335, 2.01303, 2.42611, 2.61364,
+ 1.55667, 1.62312, 1.87546, 1.97231, 2.36669, 2.62922,
+ 1.4665, 1.63832, 1.79658, 1.95927, 2.45762, 2.60323,
+ 1.30828, 1.48139, 1.73054, 1.97927, 2.33226, 2.53809,
+ 1.30165, 1.41374, 1.67444, 1.93338, 2.14349, 2.50814,
+ 1.31891, 1.41656, 1.75164, 1.91344, 2.29409, 2.55512,
+ 1.32451, 1.42562, 1.84492, 1.94741, 2.37538, 2.59737,
+ 1.267, 1.35973, 1.84915, 1.95084, 2.37072, 2.5793,
+ 1.1627, 1.34431, 1.90693, 1.98657, 2.47058, 2.58342,
+ 1.116, 1.36583, 1.94803, 2.04008, 2.46113, 2.5836,
+ 1.0618, 1.35029, 2.00628, 2.08046, 2.45163, 2.52696,
+ 1.02433, 1.23357, 1.98941, 2.08505, 2.38718, 2.49582,
+ 0.962287, 1.21924, 1.967, 2.08919, 2.42466, 2.59986,
+ 0.881533, 1.35683, 2.04743, 2.15539, 2.40907, 2.50875,
+ 0.85601, 1.21772, 2.00853, 2.11153, 2.42481, 2.53774,
+ 0.774065, 0.965055, 1.87414, 2.03588, 2.25102, 2.52797,
+ 0.820344, 0.990331, 1.96096, 2.24212, 2.34955, 2.53547,
+ 0.846158, 1.06289, 1.97251, 2.16915, 2.35316, 2.55609,
+ 0.748812, 1.06344, 1.94995, 2.06685, 2.36451, 2.602,
+ 0.855725, 1.15838, 2.00842, 2.14414, 2.3285, 2.60048,
+ 0.862076, 1.18823, 1.90646, 2.19135, 2.36851, 2.54264,
+ 0.814218, 1.19401, 2.0864, 2.15686, 2.48295, 2.57478,
+ 0.811087, 1.32095, 2.03826, 2.11283, 2.50888, 2.59894,
+ 0.967874, 1.19172, 2.04932, 2.14652, 2.42267, 2.56678,
+ 1.00803, 1.2342, 2.04091, 2.12104, 2.48015, 2.60909,
+ 1.11818, 1.31227, 1.96142, 2.07124, 2.40932, 2.60053,
+ 1.18934, 1.30243, 1.96196, 2.06321, 2.43212, 2.5453,
+ 1.25389, 1.37123, 1.93188, 2.03014, 2.38756, 2.55895,
+ 1.3073, 1.39804, 1.91099, 2.00694, 2.40944, 2.57714,
+ 1.33009, 1.46846, 1.90852, 2.01222, 2.41802, 2.53768,
+ 1.36799, 1.49229, 1.94202, 2.03675, 2.49887, 2.581,
+ 1.36837, 1.44343, 1.94748, 2.01318, 2.48634, 2.58524,
+ 1.41828, 1.49685, 1.93344, 2.02463, 2.47368, 2.59404,
+ 1.44389, 1.55122, 1.90491, 2.0181, 2.45672, 2.54287,
+ 1.47369, 1.5871, 1.89983, 2.07901, 2.4215, 2.58448,
+ 1.42467, 1.61133, 1.97452, 2.14272, 2.40288, 2.62076,
+ 1.43149, 1.62266, 1.94023, 2.12544, 2.42965, 2.58185,
+ 1.48454, 1.69058, 1.92186, 2.1091, 2.4744, 2.60783,
+ 1.49814, 1.75158, 1.92573, 2.03913, 2.44052, 2.61618,
+ 1.50525, 1.78918, 1.99467, 2.11413, 2.40842, 2.59989,
+ 1.60987, 1.79304, 1.98623, 2.1606, 2.51957, 2.59325,
+ 1.56282, 1.73991, 1.97418, 2.14322, 2.53959, 2.62009,
+ 1.65026, 1.72396, 2.00295, 2.1504, 2.5321, 2.60075,
+ 1.58463, 1.66548, 1.83385, 1.97966, 2.51117, 2.57618,
+ 1.54756, 1.66563, 1.80511, 1.93045, 2.42867, 2.54861,
+ 1.49908, 1.59512, 1.70027, 1.82419, 2.37692, 2.57548,
+ 1.30084, 1.55295, 1.66458, 1.79171, 2.4883, 2.56108,
+ 1.1686, 1.31195, 1.66858, 1.87291, 2.41357, 2.49328,
+ 1.04746, 1.24996, 1.69989, 1.91418, 2.41703, 2.49638,
+ 0.948776, 1.27559, 1.73894, 1.99868, 2.31215, 2.46202,
+ 0.921081, 1.31195, 1.77524, 1.89549, 2.38216, 2.52844,
+ 0.811311, 1.12522, 1.74519, 2.09474, 2.32611, 2.51188,
+ 0.796518, 1.06023, 1.74013, 2.0605, 2.17951, 2.3855,
+ 0.868836, 1.15335, 1.79283, 1.94564, 2.1255, 2.248,
+ 0.915536, 1.21816, 1.81891, 2.06835, 2.2434, 2.34865,
+ 0.966595, 1.30161, 1.89525, 2.11196, 2.24865, 2.38925,
+ 0.995849, 1.44208, 1.95207, 2.06612, 2.24012, 2.33859,
+ 1.05639, 1.37221, 1.98417, 2.11933, 2.2717, 2.37274,
+ 1.0984, 1.32416, 1.78153, 2.08286, 2.2188, 2.34432,
+ 1.03916, 1.35647, 1.82018, 2.11462, 2.34673, 2.45039,
+ 0.988689, 1.29388, 1.91635, 2.0882, 2.3625, 2.48127,
+ 1.10441, 1.23068, 1.93943, 2.1224, 2.25481, 2.37771,
+ 1.0861, 1.17448, 1.82635, 2.11132, 2.23769, 2.47167,
+ 1.0698, 1.20649, 1.84538, 2.11863, 2.47109, 2.5754,
+ 1.07496, 1.34279, 1.95531, 2.14771, 2.51147, 2.58927,
+ 1.1492, 1.41881, 1.88704, 1.96697, 2.47262, 2.58725,
+ 1.45575, 1.66983, 1.9641, 2.17518, 2.46999, 2.60501,
+ 1.41855, 1.60357, 1.96443, 2.17568, 2.46676, 2.58333,
+ 1.38939, 1.60116, 1.92575, 2.13186, 2.44202, 2.57423,
+ 1.41533, 1.50734, 1.91126, 2.08714, 2.5352, 2.62958,
+ 1.38248, 1.45371, 1.87229, 1.95541, 2.55434, 2.65851,
+ 1.39294, 1.4823, 1.83853, 1.92858, 2.47373, 2.63372,
+ 1.39046, 1.46304, 1.83991, 1.92201, 2.51494, 2.69879,
+ 1.33938, 1.47012, 1.85875, 1.95952, 2.53943, 2.68638,
+ 1.35378, 1.54103, 1.82255, 2.02216, 2.54222, 2.6772,
+ 1.35087, 1.63188, 1.91879, 2.18353, 2.50109, 2.61731,
+ 1.40764, 1.66913, 2.00074, 2.22423, 2.5228, 2.6349,
+ 1.43378, 1.58691, 1.99963, 2.19292, 2.53598, 2.62612,
+ 1.41388, 1.63943, 1.9522, 2.1707, 2.50111, 2.61059,
+ 1.50539, 1.61369, 1.99159, 2.21446, 2.48787, 2.61284,
+ 1.40925, 1.56369, 2.04804, 2.15415, 2.48373, 2.64218,
+ 1.41102, 1.6467, 1.98318, 2.15255, 2.56881, 2.66125,
+ 1.38475, 1.60381, 1.93449, 2.14195, 2.50764, 2.63005,
+ 1.36612, 1.55134, 1.99956, 2.17747, 2.48911, 2.59676,
+ 1.35554, 1.63502, 2.00842, 2.16267, 2.46527, 2.66141,
+ 1.45397, 1.6737, 2.03786, 2.1802, 2.61597, 2.70928,
+ 1.36954, 1.69647, 1.99979, 2.08485, 2.48277, 2.66629,
+ 1.34974, 1.46231, 1.96672, 2.05172, 2.47262, 2.65262,
+ 1.32731, 1.43776, 1.92852, 2.00639, 2.50581, 2.65892,
+ 1.34135, 1.41915, 1.9212, 1.99146, 2.53082, 2.61358,
+ 1.3427, 1.50533, 1.94693, 2.02943, 2.53822, 2.63558,
+ 1.39274, 1.5351, 1.9361, 2.02457, 2.52728, 2.61426,
+ 1.43256, 1.54379, 1.95185, 2.04985, 2.54624, 2.62371,
+ 1.45294, 1.56943, 1.93237, 2.03725, 2.55869, 2.6381,
+ 1.468, 1.59745, 1.92031, 2.01857, 2.53622, 2.62282,
+ 1.48681, 1.56965, 1.87585, 1.96607, 2.53674, 2.63191,
+ 1.45462, 1.57813, 1.81162, 1.97466, 2.53751, 2.60633,
+ 1.41804, 1.50767, 1.78357, 1.893, 2.5518, 2.62899,
+ 1.26414, 1.47438, 1.77059, 1.89893, 2.52476, 2.59407,
+ 1.11834, 1.45667, 1.73472, 1.99659, 2.41229, 2.51915,
+ 1.09643, 1.60312, 1.80839, 2.01224, 2.40962, 2.54436,
+ 0.976303, 1.47374, 1.75917, 1.85583, 2.41293, 2.48395,
+ 0.990184, 1.3907, 1.71071, 1.83167, 2.37709, 2.45494,
+ 1.0569, 1.38737, 1.78311, 1.87351, 2.40142, 2.48642,
+ 0.989786, 1.45262, 1.85157, 1.94592, 2.40345, 2.48294,
+ 1.11208, 1.36482, 1.77, 1.922, 2.29041, 2.4373,
+ 1.09625, 1.33639, 1.74186, 1.96857, 2.21161, 2.36249,
+ 1.00003, 1.34618, 1.70453, 1.96685, 2.27739, 2.38937,
+ 1.0279, 1.17407, 1.793, 2.02685, 2.1782, 2.38723,
+ 1.05688, 1.1675, 1.861, 2.20442, 2.35125, 2.48563,
+ 1.07597, 1.22642, 1.99764, 2.19618, 2.3301, 2.49414,
+ 1.14722, 1.25813, 1.95867, 2.25855, 2.38775, 2.55212,
+ 1.16281, 1.29057, 2.05279, 2.20183, 2.42462, 2.56048,
+ 1.14789, 1.26573, 2.02568, 2.13079, 2.49688, 2.62026,
+ 1.23956, 1.31573, 2.01838, 2.12351, 2.46395, 2.56921,
+ 1.18113, 1.35894, 1.94216, 2.15983, 2.4587, 2.59396,
+ 1.24746, 1.38644, 1.89825, 1.99901, 2.44602, 2.54276,
+ 1.22769, 1.50489, 1.818, 1.90802, 2.21333, 2.55223,
+ 1.20197, 1.57787, 1.77128, 1.87335, 2.06126, 2.53582,
+ 1.30623, 1.51631, 1.81923, 1.92342, 2.38203, 2.58257,
+ 1.50572, 1.58565, 1.94933, 2.0462, 2.44831, 2.61596,
+ 1.62375, 1.69873, 2.00954, 2.10801, 2.46152, 2.6479,
+ 1.69086, 1.76429, 2.0361, 2.1755, 2.51525, 2.61682,
+ 1.71534, 1.82829, 2.07855, 2.25221, 2.48367, 2.60765,
+ 1.65997, 1.80717, 1.97501, 2.25559, 2.48134, 2.58962,
+ 1.73482, 1.85022, 2.01204, 2.27674, 2.51936, 2.60818,
+ 1.63577, 1.86255, 1.95646, 2.32874, 2.56887, 2.63247,
+ 1.61635, 1.8254, 1.94952, 2.28122, 2.56086, 2.6418,
+ 1.59247, 1.80436, 1.92716, 2.16734, 2.57751, 2.64687,
+ 1.60648, 1.89509, 1.98315, 2.11245, 2.47761, 2.57696,
+ 1.70849, 1.83507, 1.96671, 2.12724, 2.42757, 2.54308,
+ 1.69109, 1.88958, 1.98607, 2.20677, 2.5224, 2.6018,
+ 1.70244, 1.90212, 2.07638, 2.21622, 2.48484, 2.60354,
+ 1.32949, 1.54259, 1.87544, 2.10553, 2.38523, 2.53663,
+ 1.32138, 1.47416, 1.93227, 2.1525, 2.37442, 2.50671,
+ 1.27775, 1.45858, 1.96309, 2.18238, 2.417, 2.55865,
+ 1.20802, 1.41871, 2.00974, 2.13853, 2.39678, 2.55451,
+ 1.19891, 1.29992, 1.98363, 2.15013, 2.29612, 2.50594,
+ 1.25034, 1.36116, 2.01056, 2.19594, 2.34098, 2.50087,
+ 1.30866, 1.58516, 2.10634, 2.21416, 2.40267, 2.63589,
+ 1.33017, 1.49463, 2.1419, 2.23581, 2.45958, 2.64947,
+ 1.29631, 1.43411, 2.09809, 2.20413, 2.35521, 2.60011,
+ 1.30962, 1.40298, 1.89254, 2.18495, 2.33361, 2.51316,
+ 1.26907, 1.49184, 1.95896, 2.17457, 2.32469, 2.54367,
+ 1.43498, 1.62885, 1.98127, 2.24728, 2.4764, 2.59398,
+ 1.45964, 1.65008, 2.02437, 2.26772, 2.54631, 2.6752,
+ 1.38149, 1.70319, 2.13891, 2.29556, 2.54576, 2.64253,
+ 1.44184, 1.70059, 2.19791, 2.27629, 2.46821, 2.69495,
+ 1.53967, 1.99967, 2.20653, 2.35148, 2.65123, 2.73482,
+ 1.58958, 1.92641, 2.17346, 2.2562, 2.63324, 2.70768,
+ 1.43426, 1.85937, 2.14195, 2.21145, 2.51178, 2.62838,
+ 1.32681, 1.59657, 2.02477, 2.11581, 2.42614, 2.60934,
+ 1.22907, 1.32555, 1.8387, 2.01305, 2.4713, 2.63928,
+ 1.23081, 1.32906, 1.87262, 1.96451, 2.44475, 2.59469,
+ 1.1937, 1.4263, 1.89859, 2.03936, 2.50271, 2.58105,
+ 1.17564, 1.47329, 1.91242, 2.00274, 2.47622, 2.60685,
+ 1.09927, 1.4439, 1.89246, 1.99757, 2.52208, 2.61109,
+ 1.11374, 1.4391, 1.91227, 2.00048, 2.46277, 2.55934,
+ 1.08551, 1.46963, 1.91446, 2.06461, 2.42792, 2.51241,
+ 1.05248, 1.5012, 1.9188, 1.99979, 2.49368, 2.57171,
+ 1.0436, 1.33162, 1.92795, 1.98919, 2.44573, 2.57808,
+ 1.05198, 1.20039, 1.93863, 2.02681, 2.44675, 2.62988,
+ 0.978672, 1.08304, 1.86878, 2.13358, 2.43014, 2.58027,
+ 0.904772, 1.10521, 1.96057, 2.06495, 2.36256, 2.60488,
+ 0.859439, 1.08463, 1.90171, 2.033, 2.27617, 2.57472,
+ 0.948943, 1.04355, 1.85564, 2.05086, 2.44443, 2.66148,
+ 0.974338, 1.12646, 1.92732, 2.02091, 2.45549, 2.55978,
+ 0.995629, 1.17589, 1.93774, 2.01368, 2.37897, 2.61729,
+ 1.00131, 1.22439, 1.9017, 1.97647, 2.42588, 2.57484,
+ 0.985969, 1.2826, 1.88661, 2.03245, 2.45596, 2.59953,
+ 0.92759, 1.32045, 1.92401, 2.01217, 2.49831, 2.59968,
+ 1.00794, 1.38396, 1.92163, 2.00762, 2.50757, 2.6075,
+ 0.972512, 1.44677, 1.92036, 2.01349, 2.49021, 2.57649,
+ 0.951123, 1.45204, 1.88986, 1.98727, 2.42148, 2.56222,
+ 0.924342, 1.36995, 1.85174, 1.94274, 2.47566, 2.54428,
+ 0.882605, 1.30167, 1.85081, 2.0325, 2.36463, 2.54182,
+ 0.933888, 1.369, 1.94311, 2.02385, 2.40544, 2.53033,
+ 0.927916, 1.11238, 1.84743, 1.97909, 2.2556, 2.56399,
+ 1.03194, 1.24913, 1.83317, 1.92522, 2.31031, 2.52014,
+ 0.934046, 1.23989, 1.9096, 2.00815, 2.37287, 2.54896,
+ 0.984297, 1.22003, 1.82379, 1.9476, 2.26436, 2.47865,
+ 0.933366, 1.27898, 1.86047, 1.943, 2.2898, 2.46567,
+ 0.983115, 1.22771, 1.8421, 2.0477, 2.27265, 2.53198,
+ 0.953311, 1.24582, 1.84968, 1.94514, 2.28957, 2.57228,
+ 0.994609, 1.30346, 1.86814, 1.97156, 2.37244, 2.58526,
+ 0.986061, 1.36409, 1.85213, 1.91782, 2.43511, 2.63387,
+ 0.975486, 1.24885, 1.8488, 1.93443, 2.40202, 2.5742,
+ 1.00839, 1.30468, 1.80431, 1.88851, 2.36947, 2.59823,
+ 0.999393, 1.32994, 1.90144, 1.99438, 2.3975, 2.50455,
+ 0.922186, 1.32154, 1.85108, 1.96206, 2.38216, 2.47299,
+ 0.897224, 1.38219, 1.78084, 1.92173, 2.35959, 2.44809,
+ 0.859516, 1.44737, 1.73231, 1.88119, 2.29523, 2.38085,
+ 0.986347, 1.60164, 1.75239, 1.96636, 2.31438, 2.4591,
+ 1.26526, 1.61653, 1.81127, 2.09714, 2.37124, 2.55036,
+ 1.31896, 1.60043, 1.75564, 2.02981, 2.32919, 2.49314,
+ 1.2099, 1.47013, 1.67019, 1.97073, 2.41621, 2.52342,
+ 1.12223, 1.3084, 1.45711, 1.72023, 2.38426, 2.47042,
+ 1.07767, 1.24551, 1.36648, 1.66428, 2.32734, 2.4192,
+ 1.07545, 1.22813, 1.36538, 1.55895, 2.23858, 2.32456,
+ 1.0445, 1.21579, 1.32599, 1.64519, 2.14864, 2.22575,
+ 0.955863, 1.15061, 1.28313, 1.49231, 2.17758, 2.26668,
+ 0.909204, 1.04511, 1.16616, 1.32059, 2.21597, 2.35285,
+ 0.960368, 1.10354, 1.27835, 1.46773, 2.26015, 2.46024,
+ 1.01022, 1.18678, 1.29006, 1.57843, 2.38873, 2.50032,
+ 1.02014, 1.13572, 1.23934, 1.38884, 2.43818, 2.56392,
+ 1.08249, 1.20695, 1.34746, 1.49004, 2.40482, 2.49462,
+ 1.14411, 1.27864, 1.43473, 1.56789, 2.32277, 2.4248,
+ 1.2743, 1.34879, 1.5156, 1.63222, 2.36011, 2.55279,
+ 1.30133, 1.39063, 1.63849, 1.76491, 2.34796, 2.57611,
+ 1.35852, 1.44445, 1.72449, 1.84371, 2.47814, 2.57455,
+ 1.39971, 1.51331, 1.79171, 1.90217, 2.49582, 2.58159,
+ 1.44887, 1.53475, 1.82151, 1.93149, 2.51782, 2.62286,
+ 1.4384, 1.53006, 1.83144, 1.99933, 2.53193, 2.62328,
+ 1.51192, 1.58109, 1.92748, 2.0414, 2.57329, 2.66347,
+ 1.53538, 1.60831, 1.92423, 2.0488, 2.54675, 2.68165,
+ 1.54437, 1.62041, 1.98043, 2.06813, 2.4774, 2.62665,
+ 1.55846, 1.64301, 2.02461, 2.12101, 2.45187, 2.63949,
+ 1.5242, 1.61395, 2.0059, 2.11548, 2.42909, 2.66308,
+ 1.50452, 1.59038, 1.96636, 2.07263, 2.3769, 2.62109,
+ 1.43939, 1.51234, 1.95035, 2.05856, 2.27641, 2.57304,
+ 1.31521, 1.40005, 1.85475, 1.95763, 2.2462, 2.5765,
+ 1.28812, 1.4889, 1.94557, 2.02484, 2.43985, 2.60568,
+ 1.43628, 1.66725, 2.05685, 2.14644, 2.54824, 2.66174,
+ 1.41739, 1.81984, 2.08357, 2.22028, 2.60669, 2.69086,
+ 1.3736, 1.96301, 2.14457, 2.27406, 2.54739, 2.6389,
+ 1.32037, 1.91864, 2.06321, 2.23772, 2.41585, 2.51765,
+ 1.22378, 1.61975, 1.89059, 2.10791, 2.521, 2.6297,
+ 1.01875, 1.42767, 1.91757, 2.00178, 2.43551, 2.56435,
+ 1.02625, 1.37705, 1.94917, 2.03921, 2.39377, 2.53005,
+ 1.00999, 1.47285, 1.99805, 2.07988, 2.48496, 2.55395,
+ 1.05327, 1.46837, 2.01612, 2.12931, 2.45662, 2.56413,
+ 1.10107, 1.35527, 2.01044, 2.10747, 2.39561, 2.53775,
+ 1.1328, 1.39166, 2.01657, 2.1141, 2.49762, 2.5851,
+ 1.17331, 1.44301, 1.97063, 2.10486, 2.44788, 2.53594,
+ 1.20948, 1.3841, 1.97224, 2.06959, 2.45749, 2.57369,
+ 1.24242, 1.45356, 1.98373, 2.06842, 2.47104, 2.59361,
+ 1.32039, 1.46365, 1.99783, 2.08233, 2.47203, 2.60589,
+ 1.38952, 1.47773, 1.97869, 2.09404, 2.48017, 2.64444,
+ 1.41374, 1.52609, 1.96375, 2.11392, 2.40385, 2.65443,
+ 1.51942, 1.59285, 1.91946, 2.02449, 2.30117, 2.66889,
+ 1.51366, 1.60013, 1.92201, 2.1051, 2.27832, 2.52342,
+ 1.48185, 1.65994, 1.91355, 2.04944, 2.27225, 2.49379,
+ 1.56755, 1.65917, 1.93065, 2.07152, 2.31259, 2.56427,
+ 1.55089, 1.67766, 1.86393, 2.01013, 2.22347, 2.52001,
+ 1.57277, 1.68302, 1.86305, 2.0022, 2.32038, 2.56079,
+ 1.62194, 1.73405, 1.92064, 2.06293, 2.33511, 2.57625,
+ 1.63149, 1.69714, 1.95288, 2.05658, 2.45963, 2.65286,
+ 1.59471, 1.67149, 1.93609, 2.0133, 2.43078, 2.66963,
+ 1.60144, 1.6687, 1.9455, 2.03717, 2.50337, 2.68212,
+ 1.58757, 1.6649, 1.94462, 2.03299, 2.56976, 2.70341,
+ 1.55642, 1.63125, 1.93071, 2.04051, 2.45387, 2.66518,
+ 1.48785, 1.56563, 1.89287, 2.01173, 2.39394, 2.64712,
+ 1.40601, 1.52018, 1.79165, 1.98788, 2.28933, 2.60276,
+ 1.35822, 1.43604, 1.81848, 1.95708, 2.3098, 2.60578,
+ 1.30934, 1.40533, 1.8357, 2.07637, 2.34081, 2.61306,
+ 1.30379, 1.41561, 1.98515, 2.12949, 2.46936, 2.64312,
+ 1.35895, 1.43773, 1.98883, 2.12737, 2.53798, 2.65647,
+ 1.33387, 1.48046, 1.95007, 2.12244, 2.43117, 2.58713,
+ 1.38453, 1.53971, 1.96409, 2.13055, 2.51045, 2.65281,
+ 1.41262, 1.54444, 1.94728, 2.17319, 2.59302, 2.71664,
+ 1.43327, 1.53989, 2.00413, 2.20195, 2.51505, 2.63524,
+ 1.44758, 1.55402, 2.12827, 2.24017, 2.47075, 2.65708,
+ 1.48065, 1.6099, 2.09796, 2.16757, 2.4737, 2.7007,
+ 1.60782, 1.67596, 2.02341, 2.14638, 2.42691, 2.63625,
+ 1.6433, 1.71778, 2.06066, 2.19756, 2.41541, 2.61433,
+ 1.73739, 1.81697, 2.03936, 2.21971, 2.423, 2.62353,
+ 1.69426, 1.79937, 2.0426, 2.2801, 2.41863, 2.58327,
+ 1.55619, 1.83187, 1.98536, 2.2079, 2.47168, 2.63082,
+ 1.42115, 1.8039, 1.98458, 2.12351, 2.4382, 2.5225,
+ 1.32744, 1.66887, 1.88843, 2.02994, 2.22446, 2.46175,
+ 1.10982, 1.5622, 1.86266, 1.97786, 2.13955, 2.32864,
+ 1.23388, 1.5808, 1.85419, 2.02179, 2.1935, 2.35592,
+ 1.20754, 1.56864, 1.87291, 1.98667, 2.13794, 2.48765,
+ 1.17998, 1.62595, 1.9, 2.00814, 2.23166, 2.59435,
+ 1.46984, 1.7172, 1.87567, 2.02443, 2.32546, 2.48842,
+ 1.6411, 1.80978, 1.92676, 2.06205, 2.41404, 2.5429,
+ 1.6488, 1.73412, 1.9669, 2.08673, 2.35448, 2.49884,
+ 1.60547, 1.68939, 2.01005, 2.11421, 2.40763, 2.52707,
+ 1.52089, 1.62873, 1.97701, 2.08677, 2.34016, 2.48934,
+ 1.50382, 1.60059, 2.03901, 2.13038, 2.39648, 2.51374,
+ 1.43782, 1.54532, 2.04393, 2.18837, 2.35682, 2.52145,
+ 1.4454, 1.54921, 1.98221, 2.09666, 2.32863, 2.46213,
+ 1.41642, 1.50436, 1.97377, 2.08043, 2.39348, 2.54353,
+ 1.42582, 1.52808, 1.99573, 2.16253, 2.44069, 2.56251,
+ 1.39427, 1.47395, 2.04354, 2.14909, 2.43298, 2.54908,
+ 1.37375, 1.47605, 2.0439, 2.16025, 2.34535, 2.50188,
+ 1.37018, 1.44359, 2.09287, 2.1781, 2.41306, 2.5906,
+ 1.32039, 1.46637, 2.03678, 2.13781, 2.43562, 2.57891,
+ 1.28693, 1.39332, 2.06073, 2.20094, 2.50002, 2.58235,
+ 1.32339, 1.42179, 2.0585, 2.15393, 2.49555, 2.63809,
+ 1.29531, 1.39322, 2.00442, 2.13819, 2.52637, 2.64154,
+ 1.23098, 1.35513, 2.04737, 2.15642, 2.52238, 2.66413,
+ 1.23375, 1.30852, 1.93949, 2.09735, 2.48735, 2.64984,
+ 1.22759, 1.3551, 1.87583, 1.97754, 2.31929, 2.57519,
+ 1.22737, 1.50711, 1.85352, 2.02289, 2.21243, 2.57649,
+ 1.1529, 1.47051, 1.83043, 1.95431, 2.33145, 2.53325,
+ 1.33666, 1.65018, 1.77921, 2.04342, 2.44482, 2.53964,
+ 1.45582, 1.58294, 2.02225, 2.17668, 2.48134, 2.59266,
+ 1.43763, 1.55624, 2.08145, 2.17496, 2.48245, 2.61457,
+ 1.41647, 1.62089, 2.03301, 2.15707, 2.46292, 2.60159,
+ 1.3763, 1.55149, 2.11721, 2.19834, 2.41619, 2.60563,
+ 1.4428, 1.65786, 2.12709, 2.2063, 2.34486, 2.57811,
+ 1.36811, 1.53873, 2.0602, 2.19805, 2.36688, 2.62224,
+ 1.34644, 1.42834, 1.98045, 2.12661, 2.28327, 2.53061,
+ 1.30459, 1.37326, 1.92352, 2.09636, 2.23996, 2.50843,
+ 1.29803, 1.37159, 1.95497, 2.10751, 2.34971, 2.54557,
+ 1.30718, 1.41617, 1.98034, 2.06446, 2.3891, 2.58844,
+ 1.2793, 1.39078, 1.95978, 2.09069, 2.43615, 2.61261,
+ 1.31702, 1.41587, 1.92187, 2.07179, 2.46382, 2.61622,
+ 1.29431, 1.4123, 1.9162, 2.0192, 2.48471, 2.61134,
+ 1.31005, 1.40777, 1.85317, 2.00991, 2.46649, 2.64501,
+ 1.3413, 1.42233, 1.88516, 1.96781, 2.48386, 2.62632,
+ 1.42826, 1.52612, 1.88512, 1.97853, 2.49939, 2.60339,
+ 1.50117, 1.58051, 1.84728, 2.00049, 2.46595, 2.60887,
+ 1.53851, 1.6254, 1.81392, 1.95006, 2.5229, 2.62047,
+ 1.56663, 1.6396, 1.77179, 1.87875, 2.54176, 2.66369,
+ 1.54343, 1.64782, 1.74862, 1.8226, 2.43468, 2.63128,
+ 1.62339, 1.68092, 1.75915, 1.84454, 2.52147, 2.65361,
+ 1.57486, 1.66372, 1.76778, 1.86974, 2.45334, 2.65822,
+ 1.55831, 1.66125, 1.79384, 1.89513, 2.26187, 2.57233,
+ 1.54368, 1.62776, 1.81767, 1.92128, 2.433, 2.65334,
+ 1.49354, 1.57566, 1.80569, 1.93945, 2.47064, 2.66508,
+ 1.44005, 1.51384, 1.83221, 1.9378, 2.53025, 2.70287,
+ 1.3191, 1.50623, 1.82349, 1.93161, 2.53955, 2.6767,
+ 1.30727, 1.56337, 1.84793, 1.95172, 2.25182, 2.45322,
+ 1.33641, 1.6616, 1.82882, 1.98833, 2.18951, 2.35425,
+ 1.34292, 1.59875, 1.78474, 1.91512, 2.10999, 2.45064,
+ 1.3367, 1.64636, 1.80074, 1.89121, 2.23591, 2.55851,
+ 1.31176, 1.50001, 1.83022, 1.94504, 2.43039, 2.64458,
+ 1.26611, 1.43196, 1.85876, 2.05915, 2.59049, 2.67476,
+ 1.31778, 1.41995, 1.91646, 2.12482, 2.57473, 2.66848,
+ 1.34152, 1.43617, 1.96842, 2.09744, 2.57279, 2.6851,
+ 1.30593, 1.43886, 1.93375, 2.03608, 2.56907, 2.65642,
+ 1.27913, 1.40647, 1.94309, 2.03172, 2.53008, 2.63088,
+ 1.28601, 1.41003, 1.96969, 2.04024, 2.44857, 2.65137,
+ 1.25754, 1.39106, 1.96657, 2.03921, 2.40242, 2.64679,
+ 1.22439, 1.35213, 1.93137, 2.00634, 2.4562, 2.69615,
+ 1.29629, 1.4881, 1.99695, 2.06819, 2.59454, 2.69584,
+ 1.33457, 1.60772, 1.92214, 2.16316, 2.54592, 2.67997,
+ 1.38178, 1.64677, 2.03764, 2.20409, 2.54579, 2.63933,
+ 1.41682, 1.62893, 2.04593, 2.20935, 2.52385, 2.67579,
+ 1.43146, 1.6948, 1.99893, 2.15953, 2.52293, 2.66475,
+ 1.38424, 1.62294, 2.03694, 2.11571, 2.52889, 2.63393,
+ 1.40383, 1.55836, 2.02735, 2.13802, 2.56277, 2.65938,
+ 1.39059, 1.67194, 2.01794, 2.16459, 2.59282, 2.68361,
+ 1.35753, 1.55376, 2.02314, 2.21231, 2.42046, 2.55826,
+ 1.30172, 1.46582, 2.05293, 2.21596, 2.42069, 2.54852,
+ 1.33933, 1.59705, 2.03516, 2.14582, 2.5096, 2.64414,
+ 1.34609, 1.63387, 2.00692, 2.11472, 2.57003, 2.68888,
+ 1.35844, 1.50167, 1.94958, 2.02763, 2.47964, 2.63746,
+ 1.42799, 1.53369, 1.85363, 1.96081, 2.43754, 2.58846,
+ 1.507, 1.58581, 1.86464, 1.95027, 2.47877, 2.62455,
+ 1.53515, 1.61948, 1.7846, 1.92633, 2.53715, 2.6658,
+ 1.49966, 1.57482, 1.68583, 1.82255, 2.53399, 2.70531,
+ 1.58548, 1.64242, 1.72185, 1.84674, 2.52449, 2.71035,
+ 1.16736, 1.62721, 1.76839, 1.85304, 2.26556, 2.54052,
+ 1.11032, 1.50695, 1.80563, 1.88181, 2.36127, 2.58996,
+ 1.06643, 1.53942, 1.7463, 1.93612, 2.12799, 2.46118,
+ 1.111, 1.56535, 1.85208, 1.96046, 2.21492, 2.4979,
+ 1.11612, 1.59069, 1.87918, 1.96908, 2.32329, 2.53297,
+ 1.1484, 1.55745, 1.81996, 1.96379, 2.38034, 2.48453,
+ 1.09256, 1.56982, 1.784, 1.95924, 2.32426, 2.46849,
+ 1.213, 1.57893, 1.75164, 1.90157, 2.27177, 2.38609,
+ 1.12398, 1.62627, 1.75806, 1.98376, 2.29113, 2.408,
+ 1.07579, 1.53483, 1.78478, 2.04194, 2.2367, 2.36811,
+ 1.11878, 1.41569, 1.97193, 2.12276, 2.33025, 2.44046,
+ 1.01609, 1.33452, 1.8992, 2.12157, 2.42514, 2.54387,
+ 1.0662, 1.28942, 1.94816, 2.08195, 2.47149, 2.59382,
+ 1.06499, 1.25576, 1.93597, 2.03695, 2.49318, 2.61275,
+ 1.04967, 1.22845, 1.82953, 2.02506, 2.43107, 2.67084,
+ 1.01963, 1.31358, 1.88031, 1.95395, 2.49169, 2.64266,
+ 1.15348, 1.5519, 1.90975, 2.13353, 2.54007, 2.62647,
+ 1.29303, 1.60048, 2.03569, 2.16688, 2.57297, 2.65826,
+ 1.40931, 1.62414, 1.99362, 2.26849, 2.52706, 2.65186,
+ 1.4264, 1.68151, 2.03941, 2.21528, 2.55906, 2.6814,
+ 1.42204, 1.75264, 2.02799, 2.23143, 2.54648, 2.63124,
+ 1.40307, 1.73555, 2.00708, 2.20211, 2.63554, 2.71835,
+ 1.36412, 1.68736, 2.01193, 2.29363, 2.6407, 2.70526,
+ 1.32806, 1.60827, 1.98985, 2.36496, 2.59056, 2.68945,
+ 1.33359, 1.64487, 2.1305, 2.30858, 2.64414, 2.73281,
+ 1.40524, 1.66596, 2.12336, 2.31586, 2.65694, 2.73287,
+ 1.43537, 1.67954, 2.0191, 2.2544, 2.59608, 2.67406,
+ 1.04103, 1.47652, 1.92332, 2.29056, 2.59234, 2.67362,
+ 0.818396, 1.18975, 2.05137, 2.23338, 2.4171, 2.62257,
+ 0.745703, 1.24025, 2.13926, 2.22418, 2.47642, 2.55879,
+ 0.786217, 1.29674, 2.00436, 2.24582, 2.54872, 2.6314,
+ 0.781573, 1.12234, 1.87575, 2.27728, 2.45942, 2.55721,
+ 0.697586, 1.32715, 2.09799, 2.17356, 2.57467, 2.6936,
+ 0.773107, 1.39301, 1.97117, 2.27022, 2.5915, 2.65154,
+ 0.799951, 1.25267, 1.92838, 2.21123, 2.57772, 2.68382,
+ 0.737528, 1.23791, 1.82716, 2.11053, 2.4763, 2.62767,
+ 0.896067, 1.42136, 1.84116, 2.10482, 2.43287, 2.58572,
+ 0.920446, 1.41858, 1.94342, 2.2527, 2.49124, 2.62311,
+ 0.905094, 1.28473, 1.84369, 2.26911, 2.47954, 2.59591,
+ 1.04955, 1.4475, 1.84117, 2.16036, 2.57575, 2.6557,
+ 1.2828, 1.44542, 1.90123, 2.29017, 2.58164, 2.67873,
+ 1.17471, 1.51702, 1.86793, 2.17662, 2.54748, 2.64015,
+ 1.24126, 1.5185, 1.93677, 2.20877, 2.52132, 2.61983,
+ 1.32193, 1.5402, 1.99853, 2.20577, 2.60566, 2.70791,
+ 1.3038, 1.62293, 1.88039, 2.18949, 2.58891, 2.66997,
+ 1.36083, 1.65855, 1.90332, 2.17801, 2.55428, 2.63477,
+ 1.38546, 1.62331, 1.9591, 2.25774, 2.60539, 2.69462,
+ 1.46795, 1.62817, 2.0031, 2.34892, 2.5961, 2.67456,
+ 1.41184, 1.69139, 1.94701, 2.25922, 2.52614, 2.61511,
+ 1.41526, 1.69746, 2.0031, 2.28429, 2.52624, 2.64336,
+ 1.36534, 1.61019, 2.0221, 2.1717, 2.5576, 2.64224,
+ 1.34395, 1.63077, 2.04084, 2.26171, 2.47792, 2.64736,
+ 1.33358, 1.63038, 2.0312, 2.21087, 2.50406, 2.62333,
+ 1.34412, 1.70468, 2.06581, 2.19257, 2.54136, 2.65852,
+ 1.43988, 1.66659, 2.08273, 2.20601, 2.63634, 2.69917,
+ 1.34435, 1.65594, 2.02685, 2.22783, 2.56587, 2.66126,
+ 1.29968, 1.58529, 1.96155, 2.23114, 2.59956, 2.6776,
+ 1.18443, 1.44165, 1.88854, 2.25541, 2.55466, 2.62551,
+ 1.44657, 1.79255, 2.02266, 2.17921, 2.49716, 2.59111,
+ 1.46468, 1.80928, 2.06019, 2.20545, 2.54596, 2.64191,
+ 1.48129, 1.72952, 2.02569, 2.25001, 2.53746, 2.66775,
+ 1.47646, 1.65779, 2.00806, 2.2492, 2.50322, 2.61312,
+ 1.38626, 1.58955, 2.0317, 2.2183, 2.50921, 2.6191,
+ 1.38626, 1.66286, 2.05258, 2.20868, 2.48839, 2.62305,
+ 1.43812, 1.64607, 1.96782, 2.21244, 2.50872, 2.6294,
+ 1.4376, 1.59023, 2.08908, 2.18445, 2.56655, 2.67785,
+ 1.36702, 1.65253, 2.08437, 2.16949, 2.4836, 2.65574,
+ 1.40378, 1.70134, 2.0628, 2.14854, 2.44319, 2.65725,
+ 1.39919, 1.70605, 2.06243, 2.14458, 2.53122, 2.63501,
+ 1.40966, 1.75057, 2.00507, 2.08724, 2.60283, 2.69407,
+ 1.43015, 1.7604, 2.0488, 2.11806, 2.56938, 2.65727,
+ 1.41885, 1.85893, 2.01867, 2.14141, 2.59787, 2.67114,
+ 1.51504, 1.81561, 1.94217, 2.08906, 2.55465, 2.6346,
+ 1.42003, 1.74012, 1.95375, 2.19613, 2.50269, 2.63975,
+ 1.3841, 1.72331, 1.90117, 2.1602, 2.42662, 2.52258,
+ 1.34105, 1.73737, 1.89475, 2.11087, 2.40751, 2.50284,
+ 1.37576, 1.55398, 1.78427, 1.98142, 2.50412, 2.57153,
+ 1.41459, 1.52055, 1.71537, 2.01302, 2.5112, 2.60864,
+ 1.38497, 1.51911, 1.69669, 1.93938, 2.5757, 2.64475,
+ 1.37786, 1.61168, 1.75124, 2.04456, 2.4936, 2.56797,
+ 1.36085, 1.55368, 1.69398, 2.03611, 2.53589, 2.58847,
+ 1.39163, 1.48933, 1.63148, 1.85308, 2.52955, 2.63182,
+ 1.36408, 1.47605, 1.62904, 1.94902, 2.52574, 2.58792,
+ 1.2439, 1.39859, 1.53969, 2.06632, 2.52865, 2.59222,
+ 1.25551, 1.42936, 1.54884, 1.95098, 2.51998, 2.57485,
+ 1.21333, 1.3888, 1.50598, 1.88664, 2.48612, 2.54536,
+ 1.1258, 1.2869, 1.53495, 1.98205, 2.49021, 2.57068,
+ 1.13252, 1.2962, 1.46083, 1.92525, 2.35567, 2.44404,
+ 1.14673, 1.36534, 1.49607, 2.02061, 2.44833, 2.51065,
+ 1.19278, 1.37894, 1.49116, 1.95926, 2.45914, 2.51972,
+ 1.27161, 1.38388, 1.52586, 1.95321, 2.47314, 2.52627,
+ 1.19995, 1.36609, 1.51973, 1.92677, 2.56299, 2.62374,
+ 1.23602, 1.38351, 1.51039, 1.7933, 2.58549, 2.67708,
+ 1.27722, 1.41656, 1.53945, 1.92379, 2.59908, 2.66772,
+ 1.19596, 1.40806, 1.56871, 2.09079, 2.62218, 2.6689,
+ 1.17444, 1.3008, 1.70657, 2.07033, 2.33283, 2.491,
+ 1.12025, 1.25279, 1.5621, 2.05712, 2.35786, 2.4881,
+ 1.17632, 1.29197, 1.76026, 2.09335, 2.39555, 2.59153,
+ 1.19772, 1.41553, 1.80193, 2.03318, 2.45962, 2.59256,
+ 1.17046, 1.49125, 1.88804, 2.08248, 2.39229, 2.52815,
+ 1.08351, 1.49178, 1.94946, 2.0462, 2.42247, 2.59161,
+ 1.05994, 1.41798, 1.95482, 2.07325, 2.48096, 2.59912,
+ 0.939633, 1.34851, 2.00568, 2.09423, 2.47405, 2.58029,
+ 0.849679, 1.29353, 1.99812, 2.10527, 2.4101, 2.61591,
+ 0.886534, 1.43235, 1.99045, 2.0898, 2.37908, 2.5395,
+ 0.973462, 1.47362, 1.94439, 2.05184, 2.3931, 2.46861,
+ 1.04199, 1.57643, 1.95273, 2.06254, 2.32632, 2.43777,
+ 1.0487, 1.54395, 1.79902, 2.01526, 2.41591, 2.48738,
+ 1.06075, 1.46328, 1.792, 1.94049, 2.41744, 2.51762,
+ 1.08688, 1.35051, 1.71544, 1.80448, 2.48199, 2.57724,
+ 1.23776, 1.48723, 1.7249, 1.80832, 2.52853, 2.61455,
+ 1.39846, 1.49959, 1.70594, 1.81787, 2.53742, 2.61115,
+ 1.46184, 1.54928, 1.71949, 1.83518, 2.48005, 2.65662,
+ 1.41193, 1.59484, 1.72262, 1.84021, 2.5366, 2.61871,
+ 1.52708, 1.60947, 1.70484, 1.83282, 2.51277, 2.60508,
+ 1.5493, 1.64971, 1.74718, 1.83885, 2.59328, 2.68152,
+ 1.40865, 1.62213, 1.79776, 1.95077, 2.23897, 2.46394,
+ 1.46356, 1.64796, 1.79073, 1.92141, 2.34804, 2.57262,
+ 1.53189, 1.70037, 1.83404, 2.0056, 2.41348, 2.57054,
+ 1.5952, 1.68156, 1.85702, 2.02018, 2.47538, 2.62026,
+ 1.57838, 1.65186, 1.91226, 2.01199, 2.5125, 2.62561,
+ 1.55111, 1.64436, 1.93621, 2.04161, 2.52732, 2.61724,
+ 1.53197, 1.62315, 1.9276, 2.00745, 2.52804, 2.63456,
+ 1.49246, 1.57949, 1.90868, 1.99823, 2.49061, 2.58309,
+ 1.44543, 1.54876, 1.9137, 2.0028, 2.51924, 2.61095,
+ 1.39728, 1.48225, 1.89122, 1.98384, 2.47449, 2.60778,
+ 1.3583, 1.56294, 1.90205, 2.00361, 2.42564, 2.58541,
+ 1.31335, 1.51889, 1.92307, 2.01194, 2.49694, 2.5837,
+ 1.32168, 1.50683, 1.90306, 1.99006, 2.51061, 2.61974,
+ 1.27289, 1.51344, 1.8979, 2.03966, 2.53652, 2.60414,
+ 1.25574, 1.43115, 1.89662, 1.96089, 2.52675, 2.62424,
+ 1.25356, 1.39283, 1.89379, 1.97508, 2.52068, 2.59667,
+ 1.21234, 1.37522, 1.86031, 1.96496, 2.53119, 2.59867,
+ 1.17744, 1.32419, 1.80663, 1.88529, 2.48732, 2.59546,
+ 1.185, 1.38308, 1.78322, 1.86347, 2.46657, 2.57065,
+ 1.16227, 1.44473, 1.79788, 1.96024, 2.51584, 2.59443,
+ 1.29313, 1.61263, 1.91287, 2.11307, 2.4672, 2.59265,
+ 1.3544, 1.69802, 1.96011, 2.14947, 2.53298, 2.65269,
+ 1.41207, 1.72912, 2.03409, 2.17295, 2.53881, 2.64369,
+ 1.39179, 1.80176, 1.94479, 2.19455, 2.4673, 2.54771,
+ 1.47608, 1.74319, 1.98255, 2.14116, 2.55905, 2.64289,
+ 1.42368, 1.8572, 1.99841, 2.14699, 2.4995, 2.58386,
+ 1.42068, 1.87817, 2.01232, 2.29828, 2.57827, 2.66549,
+ 1.45566, 1.91054, 2.06984, 2.39305, 2.59349, 2.67981,
+ 1.52558, 1.92571, 2.18647, 2.40072, 2.66013, 2.74311,
+ 1.37615, 1.63344, 1.9343, 2.25049, 2.49406, 2.61897,
+ 1.3545, 1.56095, 1.93126, 2.20732, 2.5007, 2.61105,
+ 1.30807, 1.56951, 1.96724, 2.24546, 2.46112, 2.59551,
+ 1.34701, 1.65498, 1.98091, 2.25189, 2.51009, 2.63498,
+ 1.47801, 1.58844, 2.0382, 2.22414, 2.49937, 2.64663,
+ 1.45153, 1.63029, 2.1141, 2.24973, 2.4165, 2.6518,
+ 1.41214, 1.65583, 2.12835, 2.22464, 2.52506, 2.68174,
+ 1.3745, 1.84889, 2.14083, 2.2919, 2.60283, 2.691,
+ 1.37857, 1.74485, 2.10667, 2.20122, 2.62683, 2.712,
+ 1.08274, 1.60312, 2.07077, 2.12957, 2.50429, 2.65755,
+ 1.01329, 1.46791, 1.96003, 2.09179, 2.36205, 2.56155,
+ 0.9941, 1.32807, 1.7917, 1.90255, 2.41063, 2.50132,
+ 0.999159, 1.32525, 1.72231, 1.87138, 2.28118, 2.50209,
+ 1.03528, 1.33808, 1.65302, 1.75976, 2.44146, 2.54067,
+ 1.07713, 1.29359, 1.56567, 1.7118, 2.33034, 2.43626,
+ 1.05812, 1.24303, 1.48833, 1.62368, 2.33012, 2.42954,
+ 1.15066, 1.2962, 1.57472, 1.70184, 2.39048, 2.50735,
+ 1.16792, 1.38204, 1.57381, 1.7953, 2.44065, 2.49036,
+ 1.22137, 1.40507, 1.53578, 1.72864, 2.41229, 2.51938,
+ 1.24827, 1.38398, 1.57228, 1.82686, 2.42535, 2.49422,
+ 1.27415, 1.38627, 1.55782, 1.73411, 2.37831, 2.47797,
+ 1.34389, 1.45603, 1.66853, 1.8156, 2.24874, 2.4197,
+ 1.35602, 1.5593, 1.73128, 1.85333, 2.34397, 2.51476,
+ 1.43321, 1.57591, 1.67319, 1.78146, 2.2928, 2.49126,
+ 1.35471, 1.6376, 1.87537, 2.16287, 2.40849, 2.56638,
+ 1.46466, 1.59144, 2.07122, 2.23546, 2.39889, 2.56349,
+ 1.42481, 1.62265, 2.02033, 2.16131, 2.32826, 2.46819,
+ 1.36427, 1.51615, 2.01176, 2.10961, 2.3957, 2.55472,
+ 1.34268, 1.46052, 2.0389, 2.12298, 2.50665, 2.64345,
+ 1.33831, 1.51988, 2.03004, 2.10015, 2.53334, 2.67477,
+ 1.32113, 1.54557, 1.97723, 2.12227, 2.55759, 2.68022,
+ 1.31509, 1.46711, 1.97243, 2.06854, 2.52684, 2.64563,
+ 1.30446, 1.40069, 1.95455, 2.05314, 2.5625, 2.68589,
+ 1.26718, 1.37666, 1.88806, 2.02989, 2.54542, 2.66931,
+ 1.22501, 1.33934, 1.88732, 1.96524, 2.54351, 2.67229,
+ 1.22621, 1.40353, 1.79766, 1.95969, 2.54099, 2.62735,
+ 1.34703, 1.60794, 1.96677, 2.18451, 2.47788, 2.60882,
+ 1.3321, 1.75596, 1.94842, 2.17671, 2.51339, 2.60137,
+ 1.34929, 1.7814, 1.92279, 2.10923, 2.46288, 2.55986,
+ 1.36238, 1.69359, 1.88434, 2.08805, 2.52247, 2.61397,
+ 1.32029, 1.5103, 1.85775, 2.06543, 2.49473, 2.60556,
+ 1.28299, 1.45974, 1.74491, 1.96142, 2.43994, 2.62375,
+ 1.25136, 1.38192, 1.67354, 1.7727, 2.32354, 2.66159,
+ 1.20426, 1.43515, 1.65423, 1.7378, 2.30506, 2.58156,
+ 1.18196, 1.46528, 1.67003, 1.8613, 2.44412, 2.54613,
+ 1.34712, 1.62826, 1.93134, 2.12343, 2.46685, 2.59892,
+ 1.17048, 1.28493, 1.55274, 1.83255, 2.29979, 2.51981,
+ 1.19004, 1.28402, 1.64609, 1.96917, 2.49692, 2.62045,
+ 1.25541, 1.38147, 1.78173, 2.09499, 2.43136, 2.59352,
+ 1.23188, 1.33417, 1.79625, 2.04, 2.38708, 2.55466,
+ 1.18052, 1.30857, 1.81824, 1.97632, 2.2935, 2.4518,
+ 1.10256, 1.26632, 1.84425, 1.96176, 2.32484, 2.51408,
+ 1.00464, 1.14487, 1.83502, 1.9971, 2.18238, 2.52208,
+ 0.956994, 1.21291, 1.94092, 2.06045, 2.31223, 2.44167,
+ 0.795434, 1.44428, 1.93242, 2.04716, 2.36568, 2.45052,
+ 0.942462, 1.60604, 2.02512, 2.11974, 2.29995, 2.43181,
+ 0.812186, 1.46939, 2.07832, 2.17302, 2.39197, 2.47405,
+ 0.831008, 1.62061, 2.09294, 2.16773, 2.33486, 2.41672,
+ 0.917049, 1.801, 2.12123, 2.19938, 2.34728, 2.44052,
+ 0.857286, 1.67915, 2.11243, 2.20307, 2.44474, 2.52921,
+ 0.809582, 1.54255, 2.18237, 2.23944, 2.46198, 2.54337,
+ 0.912283, 1.7792, 2.16632, 2.25109, 2.46168, 2.57688,
+ 0.774827, 1.7702, 2.1792, 2.23961, 2.48732, 2.56023,
+ 1.22299, 1.57457, 2.08108, 2.22359, 2.50152, 2.6613,
+ 1.39422, 1.69632, 2.03665, 2.27333, 2.5704, 2.68413,
+ 1.37077, 1.69891, 2.08266, 2.24567, 2.59879, 2.69545,
+ 1.37241, 1.64717, 2.14237, 2.27291, 2.60809, 2.68656,
+ 1.34279, 1.69454, 2.12328, 2.25676, 2.57528, 2.69095,
+ 1.38055, 1.75068, 2.1234, 2.19974, 2.48804, 2.61024,
+ 1.39506, 1.88332, 2.0887, 2.18949, 2.45826, 2.54814,
+ 1.41315, 1.87284, 2.02083, 2.16196, 2.39617, 2.48701,
+ 1.4031, 1.76424, 1.91125, 2.05585, 2.39101, 2.4846,
+ 1.25059, 1.60685, 1.83481, 1.91441, 2.34409, 2.54946,
+ 1.17101, 1.40644, 1.69912, 1.8581, 2.35407, 2.47105,
+ 1.13269, 1.25187, 1.52135, 1.63829, 2.35528, 2.47061,
+ 1.01168, 1.2879, 1.45026, 1.66382, 2.28546, 2.37145,
+ 1.03024, 1.20842, 1.36667, 1.55035, 2.33752, 2.4214,
+ 0.964915, 1.17119, 1.28816, 1.58842, 2.32729, 2.3883,
+ 0.953674, 1.10289, 1.26375, 1.83559, 2.31685, 2.42482,
+ 0.886544, 1.07464, 1.24224, 1.96444, 2.29681, 2.41295,
+ 0.853009, 1.07708, 1.18453, 1.75232, 2.28304, 2.38922,
+ 0.840278, 1.03322, 1.15255, 1.52095, 2.33398, 2.45453,
+ 0.91077, 1.08387, 1.22354, 1.66808, 2.34624, 2.51185,
+ 0.967915, 1.12182, 1.22026, 1.80659, 2.42113, 2.49818,
+ 0.992265, 1.16907, 1.26005, 1.67999, 2.39894, 2.45914,
+ 1.06528, 1.23096, 1.32238, 1.75348, 2.3144, 2.41593,
+ 1.08131, 1.27178, 1.45801, 1.7294, 2.3323, 2.40512,
+ 1.01781, 1.34909, 1.51584, 1.72189, 2.29296, 2.39899,
+ 1.09765, 1.33294, 1.57003, 1.77646, 2.37727, 2.46589,
+ 1.14764, 1.3025, 1.64016, 1.79704, 2.36388, 2.4748,
+ 1.12717, 1.32201, 1.68488, 1.79646, 2.40705, 2.57866,
+ 1.15953, 1.26665, 1.70955, 1.83058, 2.43816, 2.57242,
+ 1.1371, 1.33151, 1.7494, 1.846, 2.41439, 2.51149,
+ 1.12127, 1.3511, 1.72822, 1.84666, 2.44921, 2.56416,
+ 1.11868, 1.26154, 1.79446, 1.88577, 2.42901, 2.55277,
+ 1.07699, 1.21216, 1.72764, 1.86126, 2.43299, 2.56404,
+ 1.08209, 1.2617, 1.76092, 1.85803, 2.31585, 2.57359,
+ 1.08635, 1.27906, 1.76312, 1.86419, 2.38079, 2.4853,
+ 0.988401, 1.26239, 1.7379, 1.83671, 2.37578, 2.49239,
+ 1.07471, 1.1962, 1.67728, 1.80631, 2.3414, 2.56064,
+ 1.06786, 1.26529, 1.68935, 1.80299, 2.40195, 2.52406,
+ 1.01048, 1.28954, 1.65272, 1.77873, 2.3623, 2.46655,
+ 0.97757, 1.26131, 1.57627, 1.74133, 2.29762, 2.40409,
+ 1.09718, 1.46442, 1.60666, 1.71761, 2.33071, 2.41207,
+ 1.38384, 1.65227, 1.8982, 2.09661, 2.47672, 2.57418,
+ 1.27973, 1.70061, 1.89499, 2.02987, 2.46839, 2.58449,
+ 1.23667, 1.68331, 1.79106, 1.95337, 2.5331, 2.58708,
+ 1.18505, 1.59913, 1.8539, 1.94492, 2.49995, 2.5729,
+ 1.16357, 1.30732, 1.87244, 1.95399, 2.54467, 2.62323,
+ 1.19097, 1.44925, 1.86329, 1.93767, 2.52527, 2.59997,
+ 1.11855, 1.51311, 1.85667, 1.96882, 2.49739, 2.57553,
+ 1.15652, 1.63093, 1.84545, 2.05111, 2.44317, 2.53405,
+ 1.41004, 1.54198, 2.13551, 2.23561, 2.57541, 2.68055,
+ 1.39279, 1.72067, 2.03495, 2.19246, 2.48715, 2.6534,
+ 1.58125, 1.83784, 2.10976, 2.18748, 2.4979, 2.66009,
+ 1.66308, 1.9013, 2.15166, 2.24829, 2.53479, 2.63979,
+ 1.62316, 1.84307, 2.17777, 2.25531, 2.5436, 2.68119,
+ 1.53971, 1.84607, 2.11908, 2.31502, 2.60542, 2.69501,
+ 1.53269, 1.80536, 2.16618, 2.27652, 2.58208, 2.69532,
+ 1.5172, 1.86473, 2.11184, 2.24103, 2.6024, 2.67859,
+ 1.481, 1.87977, 2.1834, 2.2585, 2.62458, 2.71471,
+ 1.48006, 1.94783, 2.12659, 2.23931, 2.6027, 2.68976,
+ 1.61575, 2.02568, 2.18841, 2.29147, 2.6737, 2.72328,
+ 1.54669, 2.02367, 2.13758, 2.23388, 2.56357, 2.62736,
+ 1.51727, 1.90243, 2.13241, 2.18928, 2.54838, 2.64335,
+ 1.49876, 1.60236, 2.15993, 2.27567, 2.54058, 2.68296,
+ 1.57357, 1.6552, 2.07174, 2.2146, 2.52345, 2.64214,
+ 1.60199, 1.68036, 2.13015, 2.24731, 2.56771, 2.67057,
+ 1.63293, 1.73367, 2.1347, 2.25513, 2.55999, 2.68208,
+ 1.70743, 1.75206, 2.1397, 2.25206, 2.56764, 2.64791,
+ 1.68079, 1.81258, 2.18923, 2.2873, 2.57824, 2.64474,
+ 1.74613, 1.77855, 2.11951, 2.28339, 2.59638, 2.68683,
+ 1.68024, 1.77494, 2.09785, 2.21399, 2.55851, 2.65628,
+ 1.69816, 1.77769, 2.09692, 2.21101, 2.51242, 2.62563,
+ 1.75722, 1.8282, 2.09218, 2.21863, 2.4599, 2.65391,
+ 1.7683, 1.81576, 2.0446, 2.1744, 2.4698, 2.67439,
+ 1.74091, 1.83001, 2.0445, 2.16843, 2.4425, 2.58767,
+ 1.72899, 1.80159, 2.0369, 2.13569, 2.483, 2.64735,
+ 1.7402, 1.78035, 2.03984, 2.11648, 2.46008, 2.66641,
+ 1.67917, 1.81059, 1.9762, 2.08515, 2.33097, 2.5747,
+ 1.67538, 1.74168, 1.98661, 2.08699, 2.44484, 2.64839,
+ 1.60537, 1.68464, 1.97715, 2.08431, 2.40138, 2.62667,
+ 1.59359, 1.66701, 1.99308, 2.09579, 2.47706, 2.66052,
+ 1.49544, 1.67749, 1.91544, 2.10752, 2.5041, 2.68752,
+ 1.37119, 1.58101, 1.81209, 2.15997, 2.54081, 2.65451,
+ 1.3089, 1.65276, 1.8777, 2.10022, 2.49836, 2.63527,
+ 1.25755, 1.70119, 1.90866, 2.06398, 2.33088, 2.58848,
+ 1.26064, 1.73383, 1.90131, 2.04602, 2.23042, 2.37971,
+ 1.19202, 1.69544, 1.86633, 1.96986, 2.13128, 2.36781,
+ 1.3313, 1.72762, 1.87569, 1.96723, 2.11549, 2.46165,
+ 1.22185, 1.64479, 1.86107, 1.95729, 2.26379, 2.50923,
+ 1.29701, 1.68481, 1.82511, 1.98127, 2.3887, 2.49794,
+ 1.29299, 1.62169, 1.7955, 1.89158, 2.43094, 2.59724,
+ 1.29334, 1.41244, 1.67843, 2.01344, 2.40627, 2.57529,
+ 1.35525, 1.47052, 1.74829, 2.04483, 2.41107, 2.59082,
+ 1.35208, 1.47438, 1.81195, 2.02853, 2.44538, 2.59798,
+ 1.38043, 1.47298, 1.83619, 1.95777, 2.39037, 2.57117,
+ 1.41757, 1.51497, 1.83999, 1.97461, 2.38249, 2.51071,
+ 1.39633, 1.51162, 1.74391, 2.00952, 2.41409, 2.5335,
+ 1.356, 1.5112, 1.77504, 1.97354, 2.4454, 2.56885,
+ 1.35748, 1.53331, 1.82063, 1.99833, 2.39546, 2.5737,
+ 1.24454, 1.44655, 1.72685, 1.93599, 2.42899, 2.55595,
+ 1.20656, 1.36587, 1.51002, 1.80904, 2.46485, 2.52024,
+ 1.20471, 1.34027, 1.47715, 1.7318, 2.46108, 2.52582,
+ 1.15214, 1.29476, 1.42987, 1.66978, 2.43609, 2.50483,
+ 1.12233, 1.28467, 1.44544, 1.8119, 2.44447, 2.53569,
+ 1.1671, 1.312, 1.43068, 1.93122, 2.57918, 2.62637,
+ 1.14096, 1.25556, 1.41692, 1.91311, 2.46264, 2.55265,
+ 1.17538, 1.32509, 1.43414, 1.82628, 2.53411, 2.59969,
+ 1.15295, 1.31134, 1.42875, 1.73328, 2.49916, 2.55542,
+ 1.20894, 1.31815, 1.45086, 1.63113, 2.48479, 2.56076,
+ 1.21498, 1.3123, 1.49697, 1.60268, 2.44106, 2.51374,
+ 1.1549, 1.27435, 1.49783, 1.61108, 2.49397, 2.62846,
+ 1.22174, 1.32448, 1.52936, 1.6685, 2.49634, 2.57245,
+ 1.26548, 1.36044, 1.57445, 1.69829, 2.46587, 2.52945,
+ 1.29997, 1.41147, 1.63433, 1.79017, 2.46419, 2.54621,
+ 1.29682, 1.4613, 1.67405, 1.8673, 2.47283, 2.54653,
+ 1.31923, 1.49303, 1.70292, 1.86718, 2.41758, 2.50385,
+ 1.3077, 1.51173, 1.79546, 1.9887, 2.41583, 2.50206,
+ 1.34144, 1.56729, 1.84964, 2.05441, 2.36855, 2.48494,
+ 1.34609, 1.70986, 1.84782, 2.08987, 2.32039, 2.42693,
+ 1.35121, 1.5824, 1.85395, 2.08778, 2.26974, 2.40613,
+ 1.40341, 1.68126, 1.93063, 2.06474, 2.3176, 2.44551,
+ 1.30356, 1.80043, 1.94655, 2.06478, 2.3479, 2.57565,
+ 1.40197, 1.79512, 2.04385, 2.14916, 2.33742, 2.47542,
+ 1.48635, 1.89691, 2.03368, 2.16458, 2.42721, 2.51671,
+ 1.58122, 1.92036, 2.03292, 2.18664, 2.45883, 2.53417,
+ 1.62367, 1.94922, 2.05695, 2.22087, 2.54473, 2.61274,
+ 1.72008, 1.91633, 2.06966, 2.31006, 2.50308, 2.59265,
+ 1.65207, 1.9939, 2.12217, 2.28232, 2.53373, 2.60413,
+ 1.69638, 1.99027, 2.08866, 2.3179, 2.56235, 2.6308,
+ 1.68861, 1.97655, 2.0855, 2.35442, 2.4834, 2.56768,
+ 1.79189, 1.95662, 2.08476, 2.34413, 2.47321, 2.57802,
+ 1.77015, 1.95597, 2.07514, 2.2631, 2.50858, 2.59481,
+ 1.68817, 1.95839, 2.09717, 2.23713, 2.44313, 2.55839,
+ 1.61409, 1.85811, 1.99613, 2.15125, 2.32732, 2.48534,
+ 1.51766, 1.72978, 1.97539, 2.11873, 2.39083, 2.52342,
+ 1.57639, 1.76492, 1.93735, 2.15944, 2.35454, 2.47655,
+ 1.59652, 1.79672, 1.93068, 2.17377, 2.41526, 2.51519,
+ 1.59827, 1.75891, 1.94152, 2.24294, 2.46192, 2.54838,
+ 1.56459, 1.66781, 1.91021, 2.20751, 2.43297, 2.56229,
+ 1.50226, 1.59876, 1.70104, 1.99352, 2.43166, 2.56861,
+ 1.26117, 1.37926, 1.66944, 1.86426, 2.42439, 2.56028,
+ 1.18314, 1.29168, 1.49624, 1.77509, 2.41535, 2.57185,
+ 1.17686, 1.28064, 1.39729, 1.55628, 2.48261, 2.55691,
+ 1.15141, 1.26909, 1.40261, 1.52942, 2.5473, 2.66072,
+ 1.13835, 1.27009, 1.3867, 1.65651, 2.51668, 2.57083,
+ 1.16764, 1.28839, 1.3794, 1.81595, 2.48874, 2.54402,
+ 1.19113, 1.31858, 1.43306, 1.89873, 2.44099, 2.50552,
+ 1.23155, 1.33971, 1.50583, 1.86546, 2.40192, 2.56755,
+ 1.249, 1.34254, 1.52652, 1.64463, 2.26006, 2.52811,
+ 1.29212, 1.38504, 1.56729, 1.92802, 2.3436, 2.52673,
+ 1.55306, 1.7312, 1.87558, 2.03762, 2.18958, 2.43362,
+ 1.55633, 1.80735, 2.00987, 2.13476, 2.39511, 2.51776,
+ 1.7008, 1.863, 2.01606, 2.21287, 2.46583, 2.57661,
+ 1.74452, 1.8923, 2.04288, 2.2037, 2.39302, 2.52939,
+ 1.61468, 1.86704, 2.02413, 2.17237, 2.40215, 2.56787,
+ 1.66255, 1.92647, 2.01622, 2.15368, 2.54468, 2.63661,
+ 1.60774, 1.84063, 2.03651, 2.14887, 2.47573, 2.62342,
+ 1.5426, 1.78941, 1.98821, 2.1337, 2.50007, 2.62384,
+ 1.52049, 1.85402, 1.96628, 2.10023, 2.4655, 2.59099,
+ 1.4291, 1.7262, 1.95857, 2.06874, 2.39713, 2.57827,
+ 1.23096, 1.48391, 1.90942, 2.03717, 2.27816, 2.44268,
+ 1.16547, 1.40247, 1.87767, 1.98503, 2.337, 2.4823,
+ 1.06065, 1.34179, 1.89159, 1.9978, 2.34225, 2.47385,
+ 1.04598, 1.26441, 1.89288, 2.02811, 2.26571, 2.41834,
+ 0.872467, 1.31861, 1.94129, 2.05489, 2.26598, 2.523,
+ 0.878165, 1.20878, 1.86352, 2.07417, 2.31989, 2.4605,
+ 0.87138, 1.05093, 1.86631, 2.04429, 2.18427, 2.46922,
+ 0.814866, 1.20623, 1.93624, 2.04636, 2.24399, 2.39101,
+ 0.791495, 1.1548, 1.95086, 2.06223, 2.27019, 2.49712,
+ 0.734873, 1.1175, 2.01389, 2.14635, 2.25208, 2.34022,
+ 0.717596, 1.11331, 2.14512, 2.21429, 2.35066, 2.43709,
+ 0.747897, 1.18189, 1.98264, 2.07339, 2.39106, 2.46122,
+ 0.81421, 1.5937, 1.93081, 2.05189, 2.27992, 2.45097,
+ 1.008, 1.63525, 1.8487, 1.99829, 2.26496, 2.39937,
+ 1.05813, 1.54826, 1.72511, 1.88587, 2.17415, 2.38675,
+ 1.06533, 1.44683, 1.76311, 2.06116, 2.39393, 2.53335,
+ 1.24544, 1.51311, 1.69987, 1.88597, 2.16373, 2.41256,
+ 1.40222, 1.55017, 1.6791, 2.10448, 2.31427, 2.46462,
+ 1.43969, 1.56554, 1.74616, 2.17576, 2.35318, 2.44597,
+ 1.28279, 1.46757, 1.68979, 2.05702, 2.29957, 2.50654,
+ 1.15751, 1.36008, 1.53152, 1.93168, 2.27783, 2.38736,
+ 1.12772, 1.28719, 1.42109, 1.84436, 2.28107, 2.38522,
+ 1.17251, 1.31751, 1.49783, 1.76833, 2.3271, 2.4534,
+ 1.21562, 1.35145, 1.55462, 1.70686, 2.28027, 2.41032,
+ 1.16271, 1.31851, 1.56882, 1.75711, 2.22556, 2.32124,
+ 1.22115, 1.36407, 1.7282, 1.86724, 2.14964, 2.32343,
+ 1.27453, 1.45588, 1.65181, 1.92988, 2.11952, 2.24537,
+ 1.32483, 1.46666, 1.83773, 1.98275, 2.16784, 2.29489,
+ 1.20741, 1.46374, 1.90723, 2.01094, 2.18761, 2.31538,
+ 1.1975, 1.32537, 1.90394, 2.10426, 2.26437, 2.40602,
+ 0.964658, 1.42133, 1.80059, 2.07554, 2.24967, 2.39142,
+ 0.900184, 1.41949, 1.86053, 2.05217, 2.20467, 2.41473,
+ 0.976462, 1.44499, 1.83716, 1.99709, 2.13357, 2.30319,
+ 0.943062, 1.5438, 1.91463, 1.99313, 2.18465, 2.34418,
+ 0.89678, 1.42697, 1.92355, 2.03999, 2.25792, 2.50452,
+ 0.957615, 1.55318, 1.86268, 2.04465, 2.19266, 2.48417,
+ 1.02438, 1.62687, 1.89128, 2.04179, 2.30477, 2.61313,
+ 1.2607, 1.57098, 1.79692, 1.93891, 2.45798, 2.54369,
+ 1.43387, 1.67689, 2.02035, 2.24929, 2.48843, 2.61923,
+ 1.42779, 1.60531, 1.99984, 2.19762, 2.47258, 2.62826,
+ 1.34494, 1.54775, 2.01991, 2.15346, 2.48252, 2.6649,
+ 1.39455, 1.83086, 2.07575, 2.1467, 2.52985, 2.66294,
+ 1.39353, 1.57998, 2.00527, 2.06832, 2.59583, 2.67795,
+ 1.37167, 1.50166, 2.01236, 2.06929, 2.60572, 2.70121,
+ 1.36597, 1.44376, 1.8937, 2.06336, 2.54086, 2.63575,
+ 1.39281, 1.47093, 1.92042, 1.98528, 2.61205, 2.67063,
+ 1.39358, 1.50234, 1.92649, 2.01951, 2.57154, 2.6457,
+ 1.33144, 1.47006, 1.84434, 1.94554, 2.52733, 2.62083,
+ 1.28039, 1.38, 1.82279, 1.92768, 2.47072, 2.61404,
+ 1.23045, 1.39485, 1.77224, 1.9107, 2.49488, 2.56917,
+ 1.10377, 1.421, 1.74216, 1.90103, 2.45853, 2.54496,
+ 1.07083, 1.43846, 1.75479, 1.82779, 2.32372, 2.48412,
+ 1.02392, 1.52234, 1.71372, 1.83474, 2.2896, 2.49685,
+ 1.12384, 1.53995, 1.76628, 1.86662, 2.34998, 2.44122,
+ 1.04667, 1.49658, 1.79154, 1.85948, 2.40075, 2.4683,
+ 1.03123, 1.5049, 1.71427, 1.94435, 2.36522, 2.45944,
+ 1.20118, 1.37012, 1.88263, 2.01133, 2.41129, 2.51029,
+ 1.24946, 1.32446, 1.90762, 2.059, 2.44862, 2.55141,
+ 1.30858, 1.40302, 1.96116, 2.04859, 2.47571, 2.56247,
+ 1.35436, 1.47604, 2.00873, 2.11132, 2.51324, 2.59156,
+ 1.41531, 1.55963, 2.02019, 2.10785, 2.50535, 2.59646,
+ 1.45215, 1.53696, 2.03346, 2.12047, 2.47346, 2.60024,
+ 1.47616, 1.57067, 1.98144, 2.08987, 2.44173, 2.57494,
+ 1.53214, 1.60732, 1.99626, 2.09911, 2.44899, 2.57508,
+ 1.57825, 1.6709, 1.94645, 2.06793, 2.48457, 2.59603,
+ 1.64599, 1.71983, 1.90843, 2.03481, 2.5215, 2.63014,
+ 1.6752, 1.73909, 1.85801, 1.95115, 2.54962, 2.66814,
+ 1.6988, 1.74067, 1.81622, 1.87221, 2.55299, 2.67504,
+ 1.58931, 1.66594, 1.75197, 1.83425, 2.49582, 2.66392,
+ 1.44357, 1.53506, 1.6855, 1.78803, 2.39178, 2.64485,
+ 1.38939, 1.59756, 1.88429, 2.16105, 2.45363, 2.57728,
+ 1.34469, 1.5734, 1.94905, 2.03321, 2.43648, 2.65023,
+ 1.34068, 1.44219, 1.90408, 1.99239, 2.42751, 2.60434,
+ 1.30157, 1.36352, 1.87021, 1.95339, 2.44581, 2.60937,
+ 1.26564, 1.36552, 1.83866, 1.92217, 2.43174, 2.55248,
+ 1.29187, 1.45107, 1.77074, 1.90068, 2.38049, 2.47459,
+ 1.3198, 1.50206, 1.68621, 1.92201, 2.2912, 2.39261,
+ 1.25322, 1.4458, 1.59175, 1.89356, 2.29503, 2.3815,
+ 1.17138, 1.37063, 1.52321, 1.82582, 2.33635, 2.39918,
+ 1.23899, 1.36509, 1.48683, 1.79013, 2.30251, 2.38422,
+ 1.18649, 1.32753, 1.46369, 1.68078, 2.32204, 2.40225,
+ 1.16077, 1.2949, 1.46764, 1.61324, 2.21966, 2.32965,
+ 1.16797, 1.31227, 1.45879, 1.72547, 2.18251, 2.27065,
+ 1.16049, 1.37138, 1.54665, 1.85991, 2.15148, 2.26711,
+ 1.06064, 1.44774, 1.58936, 1.76203, 2.18795, 2.31254,
+ 1.09687, 1.44937, 1.66994, 1.88079, 2.20516, 2.32292,
+ 0.965471, 1.39498, 1.66486, 1.86974, 2.13014, 2.2721,
+ 0.992815, 1.27623, 1.73632, 1.88313, 2.19849, 2.29195,
+ 0.989087, 1.34899, 1.86928, 1.94503, 2.2171, 2.32962,
+ 0.90585, 1.29647, 1.83941, 1.98449, 2.13136, 2.26164,
+ 0.913468, 1.3471, 1.97494, 2.05681, 2.23306, 2.3124,
+ 0.891335, 1.51815, 1.95606, 2.01705, 2.23425, 2.36954,
+ 0.838007, 1.4907, 2.01764, 2.09778, 2.33146, 2.41797,
+ 0.918242, 1.41122, 2.04709, 2.15794, 2.31221, 2.4143,
+ 0.73747, 1.47534, 2.13171, 2.1951, 2.33607, 2.41009,
+ 0.804454, 1.24701, 2.18319, 2.2531, 2.37687, 2.45747,
+ 0.910989, 1.12058, 2.03128, 2.13474, 2.30167, 2.40132,
+ 0.823657, 1.02371, 1.8993, 2.15349, 2.27816, 2.4689,
+ 0.820197, 0.968457, 1.65567, 2.13731, 2.32041, 2.44255,
+ 0.901009, 1.04763, 1.78579, 2.12632, 2.24814, 2.41922,
+ 0.908944, 1.15154, 1.94127, 2.15376, 2.28778, 2.47786,
+ 1.02292, 1.32981, 1.97353, 2.1212, 2.26916, 2.49693,
+ 1.00803, 1.17657, 1.83255, 2.13074, 2.26309, 2.48407,
+ 1.1484, 1.26162, 1.86817, 2.13834, 2.28791, 2.47577,
+ 1.13164, 1.24554, 1.7469, 2.12721, 2.27364, 2.43952,
+ 1.10545, 1.23069, 1.75987, 2.02322, 2.2259, 2.48502,
+ 1.23228, 1.36348, 1.91488, 2.02165, 2.31404, 2.45593,
+ 1.28797, 1.37746, 1.85366, 2.03963, 2.34808, 2.50271,
+ 1.28514, 1.52079, 1.95102, 2.05364, 2.36654, 2.48611,
+ 1.27636, 1.65661, 1.88233, 2.08463, 2.43062, 2.524,
+ 1.3057, 1.53254, 1.86153, 2.02916, 2.43563, 2.51958,
+ 1.29572, 1.47484, 1.83837, 2.04501, 2.41302, 2.5453,
+ 1.2328, 1.30721, 1.78676, 1.91145, 2.53363, 2.62579,
+ 1.10601, 1.25243, 1.73731, 1.8274, 2.39547, 2.65803,
+ 1.08032, 1.24974, 1.76381, 1.84223, 2.48808, 2.63797,
+ 1.08481, 1.3027, 1.7911, 1.91571, 2.53275, 2.62698,
+ 1.02408, 1.39849, 1.75815, 1.94769, 2.53675, 2.6478,
+ 1.05255, 1.48652, 1.83597, 2.01313, 2.52654, 2.62152,
+ 0.980943, 1.52889, 1.88771, 1.99043, 2.55923, 2.63173,
+ 0.954706, 1.35519, 1.89085, 1.96874, 2.5383, 2.6458,
+ 0.894853, 1.31642, 1.93192, 2.00063, 2.61782, 2.70696,
+ 0.859848, 1.16666, 1.85185, 2.01109, 2.62987, 2.73106,
+ 0.817565, 1.16914, 1.97568, 2.11707, 2.59314, 2.68371,
+ 0.776768, 0.999874, 1.95167, 2.127, 2.57853, 2.71922,
+ 0.750075, 1.10567, 2.01524, 2.09916, 2.46918, 2.63788,
+ 0.878438, 1.03962, 2.07882, 2.1891, 2.45317, 2.61062,
+ 0.915136, 1.11488, 2.01769, 2.23653, 2.37028, 2.53828,
+ 0.82611, 1.20898, 2.06907, 2.15683, 2.33186, 2.46307,
+ 0.869876, 1.28956, 2.0617, 2.14305, 2.31374, 2.39581,
+ 0.790056, 1.42106, 1.94573, 2.02523, 2.25492, 2.38411,
+ 0.782642, 1.67814, 1.92831, 1.98015, 2.1697, 2.29002,
+ 0.79594, 1.40966, 1.7678, 1.89476, 2.19165, 2.28019,
+ 0.832117, 1.16909, 1.82801, 1.91103, 2.22865, 2.36616,
+ 0.862231, 1.1894, 1.75495, 1.92413, 2.31213, 2.41255,
+ 1.03477, 1.29047, 1.7835, 1.99616, 2.34376, 2.46273,
+ 1.13581, 1.35879, 1.78919, 1.98063, 2.37636, 2.49584,
+ 1.3039, 1.415, 1.78751, 1.91844, 2.43546, 2.54775,
+ 1.48925, 1.59296, 1.85058, 1.95005, 2.42804, 2.57134,
+ 1.63147, 1.74264, 1.88788, 1.99493, 2.49377, 2.61966,
+ 1.68385, 1.80038, 1.92661, 2.06405, 2.50915, 2.59263,
+ 1.74531, 1.85426, 1.98854, 2.11714, 2.50431, 2.61134,
+ 1.76427, 1.89058, 2.03799, 2.1743, 2.50772, 2.60061,
+ 1.68017, 1.81737, 1.93711, 2.22898, 2.55014, 2.62331,
+ 1.55262, 1.81946, 1.95732, 2.26349, 2.51728, 2.58051,
+ 1.55842, 1.78491, 2.02149, 2.23937, 2.54371, 2.63746,
+ 1.24066, 1.73929, 1.88981, 2.10508, 2.53244, 2.61823,
+ 0.928972, 1.44027, 1.76926, 1.85335, 2.40041, 2.63688,
+ 1.05577, 1.48884, 1.75607, 1.83257, 2.20968, 2.65031,
+ 1.0133, 1.38103, 1.70409, 1.77271, 2.15549, 2.58513,
+ 1.00919, 1.33324, 1.74138, 1.8465, 2.15877, 2.51776,
+ 1.00638, 1.5199, 1.81375, 1.91629, 2.40767, 2.58185,
+ 1.35773, 1.53055, 1.88364, 2.14151, 2.46327, 2.61463,
+ 1.42682, 1.56088, 1.88252, 2.17521, 2.48835, 2.6287,
+ 1.31598, 1.57984, 1.85956, 2.08348, 2.41988, 2.56465,
+ 1.21305, 1.5389, 1.80025, 1.88207, 2.34157, 2.57461,
+ 1.27506, 1.54351, 1.9171, 2.12745, 2.38894, 2.54272,
+ 1.43894, 1.69814, 1.85661, 2.07519, 2.26671, 2.43737,
+ 1.45433, 1.66376, 1.86982, 2.01141, 2.36627, 2.53339,
+ 1.38217, 1.67292, 1.82744, 1.94203, 2.45391, 2.55986,
+ 1.40066, 1.58545, 1.84133, 2.00274, 2.427, 2.51776,
+ 1.38214, 1.68809, 1.81976, 2.06315, 2.41779, 2.49255,
+ 1.2551, 1.60338, 1.75391, 2.04757, 2.45556, 2.56959,
+ 1.13478, 1.40915, 1.70528, 1.80211, 2.48803, 2.64714,
+ 1.11188, 1.26013, 1.67605, 1.77849, 2.50159, 2.627,
+ 1.06035, 1.20881, 1.66035, 1.77686, 2.48876, 2.60446,
+ 0.94712, 1.16465, 1.64204, 1.72379, 2.47516, 2.56741,
+ 0.902077, 1.2512, 1.66403, 1.76901, 2.499, 2.5767,
+ 0.92017, 1.24389, 1.70968, 1.79499, 2.53435, 2.62383,
+ 0.93877, 1.26768, 1.72586, 1.87016, 2.54951, 2.6282,
+ 0.914357, 1.25432, 1.71291, 1.78474, 2.59043, 2.70748,
+ 0.930246, 1.28124, 1.80279, 1.87886, 2.56022, 2.68722,
+ 0.95535, 1.14867, 1.81473, 1.90259, 2.55782, 2.68459,
+ 0.96833, 1.09859, 1.81344, 1.91188, 2.46314, 2.64649,
+ 0.990311, 1.18544, 1.86467, 1.94159, 2.48811, 2.66446,
+ 1.1869, 1.59093, 1.95416, 2.0337, 2.59786, 2.66218,
+ 1.30264, 1.69442, 1.99744, 2.16905, 2.61741, 2.69308,
+ 1.37926, 1.71828, 1.99322, 2.2122, 2.54373, 2.64086,
+ 1.40516, 1.78053, 1.99789, 2.15115, 2.55578, 2.63222,
+ 1.29777, 1.87826, 2.02027, 2.19057, 2.54647, 2.61734,
+ 1.44216, 1.85664, 2.10104, 2.29971, 2.56148, 2.64412,
+ 1.37017, 1.78121, 2.11499, 2.25182, 2.44675, 2.54984,
+ 1.40345, 1.70357, 2.0793, 2.2214, 2.44877, 2.59398,
+ 1.41335, 1.64917, 2.00998, 2.15916, 2.51868, 2.61514,
+ 1.32666, 1.71994, 1.95044, 2.02547, 2.52107, 2.63595,
+ 1.38595, 1.55275, 1.85678, 1.93751, 2.49665, 2.58016,
+ 1.34541, 1.48801, 1.88554, 2.01719, 2.54687, 2.6256,
+ 1.33572, 1.42021, 1.78707, 1.97684, 2.50133, 2.64355,
+ 1.3038, 1.40827, 1.80145, 1.90147, 2.37505, 2.57595,
+ 1.31291, 1.40809, 1.83798, 1.95009, 2.31854, 2.4759,
+ 1.19361, 1.29364, 1.81906, 1.97449, 2.46808, 2.58528,
+ 1.19153, 1.31147, 1.71163, 1.85459, 2.39504, 2.55402,
+ 1.10318, 1.33217, 1.71792, 1.85799, 2.34029, 2.44522,
+ 0.996011, 1.23417, 1.75102, 1.86827, 2.28588, 2.40672,
+ 1.05531, 1.37824, 1.71212, 1.84167, 2.2067, 2.44054,
+ 1.07861, 1.46591, 1.78701, 1.94898, 2.23174, 2.47898,
+ 0.98452, 1.42059, 1.8153, 1.92522, 2.26343, 2.43094,
+ 0.984574, 1.49518, 1.77419, 1.96413, 2.22166, 2.34685,
+ 1.15484, 1.5072, 1.8121, 1.94937, 2.28174, 2.4261,
+ 1.17006, 1.42938, 1.74509, 1.93793, 2.23502, 2.37477,
+ 1.20649, 1.48753, 1.7673, 2.00984, 2.20705, 2.33947,
+ 1.07366, 1.37773, 1.82868, 1.993, 2.13061, 2.25678,
+ 1.08845, 1.49539, 1.90777, 1.99687, 2.2139, 2.39049,
+ 1.12298, 1.42221, 1.86583, 2.03711, 2.25375, 2.41839,
+ 1.13417, 1.38264, 1.80424, 1.9632, 2.16117, 2.4736,
+ 1.2454, 1.55261, 1.96081, 2.13469, 2.4536, 2.57754,
+ 1.1187, 1.56721, 1.95262, 2.17652, 2.44663, 2.57856,
+ 1.14171, 1.6436, 2.01334, 2.27743, 2.55738, 2.63478,
+ 1.39251, 1.80792, 2.03934, 2.23792, 2.57802, 2.66829,
+ 1.43321, 1.83371, 2.02062, 2.25218, 2.51864, 2.60086,
+ 1.37926, 1.71223, 2.025, 2.24296, 2.51553, 2.60248,
+ 1.36698, 1.67564, 1.97659, 2.19947, 2.51697, 2.59881,
+ 1.35276, 1.80187, 2.03361, 2.18194, 2.49138, 2.58988,
+ 1.32366, 1.74357, 2.00964, 2.1227, 2.47452, 2.56638,
+ 1.19009, 1.54054, 1.93307, 2.08808, 2.50673, 2.57061,
+ 1.51983, 1.76619, 1.906, 2.07675, 2.26142, 2.40768,
+ 1.53469, 1.71407, 2.01648, 2.1309, 2.32326, 2.45761,
+ 1.52205, 1.79476, 2.05095, 2.21828, 2.40801, 2.53773,
+ 1.66536, 1.90687, 2.02566, 2.23238, 2.43013, 2.55064,
+ 1.6663, 1.83465, 1.99804, 2.22024, 2.40151, 2.50239,
+ 1.52361, 1.73009, 1.86296, 2.1646, 2.46626, 2.54923,
+ 1.21612, 1.50347, 1.76046, 1.96747, 2.38172, 2.56435,
+ 1.17113, 1.42943, 1.61663, 1.91778, 2.38793, 2.47727,
+ 1.0913, 1.35137, 1.56866, 1.7962, 2.43759, 2.51487,
+ 1.00128, 1.38691, 1.5396, 1.77505, 2.41327, 2.48215,
+ 0.952227, 1.39731, 1.52793, 1.72252, 2.44275, 2.49237,
+ 0.824979, 1.38889, 1.56898, 1.73526, 2.40875, 2.47118,
+ 0.794444, 1.43306, 1.58885, 1.74958, 2.48937, 2.57636,
+ 0.899067, 1.52185, 1.6814, 1.78029, 2.44175, 2.50829,
+ 0.922249, 1.46461, 1.59253, 1.82844, 2.41816, 2.47726,
+ 0.871556, 1.44442, 1.53832, 1.88901, 2.35369, 2.41254,
+ 0.857823, 1.27025, 1.50127, 1.76026, 2.35576, 2.4073,
+ 0.846263, 1.17661, 1.48198, 1.61417, 2.36993, 2.48569,
+ 0.882414, 1.17609, 1.37797, 1.49739, 2.38001, 2.51651,
+ 0.938718, 1.10065, 1.48911, 1.57621, 2.32557, 2.54347,
+ 0.932462, 1.10559, 1.29435, 1.47096, 2.40012, 2.55472,
+ 0.945253, 1.161, 1.30388, 1.58026, 2.46668, 2.58461,
+ 1.01832, 1.21474, 1.33058, 1.68375, 2.48296, 2.55716,
+ 1.04824, 1.17548, 1.2581, 1.59909, 2.52145, 2.6425,
+ 1.07374, 1.20351, 1.2987, 1.68876, 2.55568, 2.61447,
+ 1.09679, 1.26086, 1.3686, 1.75534, 2.49303, 2.60645,
+ 1.10564, 1.22703, 1.40439, 1.8497, 2.52331, 2.60157,
+ 1.14386, 1.26939, 1.38734, 1.82908, 2.39517, 2.49646,
+ 1.09925, 1.22861, 1.34441, 1.66442, 2.44063, 2.51807,
+ 1.11618, 1.22832, 1.33295, 1.66731, 2.33167, 2.51226,
+ 1.20152, 1.29939, 1.47847, 1.57791, 2.00331, 2.45158,
+ 1.16799, 1.29273, 1.47073, 1.81462, 2.14096, 2.43615,
+ 1.28052, 1.42488, 1.59521, 1.80388, 2.20583, 2.31538,
+ 1.23016, 1.36494, 1.61044, 2.00251, 2.17287, 2.35572,
+ 1.30255, 1.40061, 1.73433, 2.074, 2.20855, 2.38927,
+ 1.51269, 1.81823, 2.14478, 2.26692, 2.44774, 2.56939,
+ 1.50753, 1.76042, 2.16423, 2.27687, 2.47949, 2.62484,
+ 1.44651, 1.76044, 2.1147, 2.2567, 2.57257, 2.66147,
+ 1.46887, 1.81236, 2.11457, 2.19302, 2.61774, 2.71384,
+ 1.44965, 1.77645, 2.0806, 2.21016, 2.54091, 2.71399,
+ 1.44125, 1.71952, 2.11461, 2.21869, 2.5113, 2.66005,
+ 1.47766, 1.61984, 2.1127, 2.1987, 2.5206, 2.6557,
+ 1.53287, 1.71815, 2.13263, 2.2223, 2.55144, 2.66573,
+ 1.34103, 1.81458, 2.12504, 2.24586, 2.54798, 2.64959,
+ 1.36191, 1.69809, 2.07692, 2.25511, 2.52488, 2.64704,
+ 1.31533, 1.59277, 2.10978, 2.21019, 2.51775, 2.66697,
+ 1.3828, 1.57159, 2.10684, 2.20406, 2.4952, 2.66142,
+ 1.45363, 1.64175, 2.10031, 2.19937, 2.4624, 2.60888,
+ 1.3761, 1.64657, 1.98719, 2.21841, 2.41362, 2.52681,
+ 1.37284, 1.63246, 2.05624, 2.16372, 2.37619, 2.58687,
+ 1.43261, 1.62463, 2.07417, 2.11989, 2.48066, 2.66903,
+ 1.41068, 1.6628, 2.06922, 2.13037, 2.58137, 2.714,
+ 1.17413, 1.52452, 2.03205, 2.10525, 2.50238, 2.65331,
+ 1.15083, 1.24978, 2.00479, 2.15823, 2.31798, 2.58817,
+ 1.05764, 1.19972, 2.04367, 2.16548, 2.37102, 2.60817,
+ 1.07033, 1.16919, 2.05106, 2.1872, 2.47645, 2.67133,
+ 0.989962, 1.10088, 1.95972, 2.10766, 2.45186, 2.65933,
+ 0.995945, 1.12508, 1.96773, 2.17105, 2.35276, 2.58638,
+ 0.951054, 1.07341, 1.76868, 2.2131, 2.36251, 2.50427,
+ 0.912647, 1.06363, 1.87431, 2.20935, 2.34779, 2.51505,
+ 0.880146, 1.0577, 1.93951, 2.2982, 2.44787, 2.55972,
+ 0.808391, 0.999903, 1.78946, 2.22109, 2.38324, 2.5121,
+ 0.872797, 1.05131, 1.90798, 2.34589, 2.55144, 2.62038,
+ 0.736864, 0.925226, 2.10155, 2.27386, 2.39295, 2.56886,
+ 0.704727, 1.0262, 2.09473, 2.21249, 2.47416, 2.6562,
+ 0.793545, 1.02948, 1.90102, 2.33368, 2.65025, 2.72142,
+ 0.890709, 1.27007, 2.13985, 2.23832, 2.54438, 2.71132,
+ 0.971655, 1.31769, 2.24547, 2.35109, 2.63196, 2.71126,
+ 1.08079, 1.55577, 2.01062, 2.24599, 2.52841, 2.64489,
+ 1.40951, 1.76932, 2.1067, 2.28426, 2.51225, 2.63834,
+ 1.24844, 1.66199, 2.03514, 2.28324, 2.53429, 2.64733,
+ 0.95246, 1.1238, 2.10348, 2.25807, 2.39474, 2.60457,
+ 0.989645, 1.18166, 2.02343, 2.23737, 2.36952, 2.52253,
+ 0.926042, 1.34812, 1.94934, 2.06208, 2.34696, 2.44908,
+ 0.919696, 1.4053, 1.83405, 2.0997, 2.37621, 2.49339,
+ 1.00081, 1.37165, 1.83665, 2.2241, 2.41011, 2.5393,
+ 1.20009, 1.43679, 1.83915, 2.17928, 2.39885, 2.49843,
+ 1.22352, 1.48641, 1.94399, 2.25226, 2.40733, 2.54068,
+ 1.11367, 1.47721, 1.84416, 2.21801, 2.38133, 2.48688,
+ 1.13811, 1.49875, 1.98095, 2.29747, 2.45785, 2.56077,
+ 1.14615, 1.61454, 1.8989, 2.23248, 2.41657, 2.51096,
+ 1.11967, 1.58992, 1.82441, 2.11191, 2.35476, 2.45328,
+ 1.03204, 1.58942, 1.85285, 2.14299, 2.324, 2.47294,
+ 0.989427, 1.52898, 1.91464, 2.17919, 2.37674, 2.49437,
+ 1.09575, 1.49456, 1.86612, 2.13681, 2.28371, 2.46406,
+ 0.834557, 1.46372, 1.88257, 2.15093, 2.37864, 2.46309,
+ 0.835589, 1.29607, 1.77137, 2.09878, 2.28624, 2.42638,
+ 0.806577, 1.40333, 1.68522, 2.04095, 2.23574, 2.3564,
+ 0.800011, 1.38309, 1.81416, 1.95993, 2.30958, 2.38679,
+ 0.804745, 1.31821, 1.82136, 1.9087, 2.23513, 2.42714,
+ 0.895849, 1.36723, 1.86481, 1.97967, 2.32424, 2.42079,
+ 0.82739, 1.42508, 1.76716, 2.05819, 2.37623, 2.46943,
+ 0.917915, 1.49792, 1.85534, 1.98721, 2.31538, 2.45164,
+ 0.940855, 1.40956, 1.78919, 1.98853, 2.33667, 2.53469,
+ 0.972711, 1.2917, 1.78694, 1.91488, 2.32326, 2.40549,
+ 0.993281, 1.36882, 1.80724, 1.95862, 2.35727, 2.45928,
+ 1.07469, 1.34931, 1.84084, 1.95484, 2.26908, 2.38406,
+ 1.1006, 1.21857, 1.75613, 1.90019, 2.27787, 2.40621,
+ 1.16562, 1.31369, 1.8437, 1.96222, 2.1571, 2.34291,
+ 1.15777, 1.37236, 1.87996, 1.99193, 2.25808, 2.39087,
+ 1.28609, 1.78099, 1.9597, 2.11887, 2.32454, 2.43759,
+ 1.45517, 1.73815, 2.09889, 2.23501, 2.42846, 2.53971,
+ 1.50025, 1.68426, 2.161, 2.27259, 2.39908, 2.51033,
+ 1.48567, 1.8464, 2.19572, 2.30566, 2.54628, 2.65059,
+ 1.72782, 2.01371, 2.16728, 2.30421, 2.58661, 2.65216,
+ 1.67677, 1.96053, 2.21701, 2.36881, 2.59828, 2.68162,
+ 1.63196, 1.91575, 2.22704, 2.33518, 2.6031, 2.71022,
+ 1.66386, 1.97302, 2.12471, 2.22235, 2.66048, 2.72432,
+ 1.54201, 1.92958, 2.0756, 2.17063, 2.62855, 2.70775,
+ 1.50969, 1.70605, 2.05691, 2.19767, 2.57833, 2.6539,
+ 1.48207, 1.67373, 2.13105, 2.19487, 2.58632, 2.69029,
+ 1.42345, 1.64327, 2.09232, 2.17894, 2.5272, 2.63675,
+ 1.35515, 1.56517, 2.02393, 2.23649, 2.53832, 2.65549,
+ 1.32842, 1.55398, 2.08156, 2.16192, 2.47274, 2.65693,
+ 1.33076, 1.41904, 2.02671, 2.12905, 2.368, 2.57102,
+ 1.27065, 1.37759, 2.02595, 2.14013, 2.38924, 2.57594,
+ 1.23682, 1.34543, 2.02239, 2.10985, 2.47813, 2.63391,
+ 1.22208, 1.32043, 1.93967, 2.02174, 2.43681, 2.62853,
+ 1.25217, 1.35827, 1.97262, 2.07935, 2.37145, 2.59893,
+ 1.26623, 1.4702, 1.93045, 2.14581, 2.47186, 2.61815,
+ 1.33228, 1.54641, 2.02572, 2.21952, 2.46462, 2.64511,
+ 1.4186, 1.64948, 2.00831, 2.12811, 2.48988, 2.67687,
+ 1.45568, 1.68468, 1.98898, 2.15265, 2.4704, 2.65153,
+ 1.44749, 1.60065, 1.9359, 2.27176, 2.51299, 2.63183,
+ 1.44477, 1.55636, 2.02038, 2.28232, 2.47577, 2.61234,
+ 1.38748, 1.48741, 2.02468, 2.24466, 2.44505, 2.58283,
+ 1.35392, 1.44328, 1.95756, 2.17131, 2.33611, 2.56008,
+ 1.36979, 1.44771, 2.00618, 2.19142, 2.40471, 2.60473,
+ 1.42596, 1.50428, 2.07231, 2.17818, 2.41766, 2.60341,
+ 1.44024, 1.5405, 2.0824, 2.21198, 2.37707, 2.63732,
+ 1.49701, 1.58268, 2.05652, 2.17217, 2.38928, 2.59384,
+ 1.50496, 1.58456, 1.98409, 2.14933, 2.36756, 2.55972,
+ 1.51904, 1.60399, 1.9938, 2.10993, 2.32726, 2.59969,
+ 1.56956, 1.65105, 1.98894, 2.11673, 2.34577, 2.56992,
+ 1.56989, 1.68368, 1.98057, 2.18292, 2.35723, 2.58728,
+ 1.60707, 1.7127, 1.95147, 2.12568, 2.30717, 2.54725,
+ 1.64523, 1.7366, 1.95236, 2.13149, 2.37622, 2.60646,
+ 1.66961, 1.76398, 1.97965, 2.17323, 2.33235, 2.51667,
+ 1.63244, 1.75887, 1.9808, 2.12427, 2.2859, 2.44383,
+ 1.55741, 1.6677, 1.90206, 2.10693, 2.26086, 2.48392,
+ 1.47042, 1.68895, 1.84638, 2.03283, 2.18513, 2.37587,
+ 1.42194, 1.53148, 1.82567, 2.02659, 2.18038, 2.36012,
+ 1.38564, 1.60616, 1.84636, 2.07139, 2.4885, 2.60745,
+ 1.35971, 1.57766, 1.8971, 2.11196, 2.47111, 2.603,
+ 1.33945, 1.54264, 1.93397, 2.13374, 2.45491, 2.58319,
+ 1.32581, 1.69176, 2.08023, 2.16421, 2.47416, 2.60522,
+ 1.34715, 1.6247, 2.07411, 2.2144, 2.43059, 2.56295,
+ 1.31486, 1.54184, 1.96763, 2.16414, 2.37269, 2.60652,
+ 1.3129, 1.53408, 1.91728, 2.08995, 2.41161, 2.57067,
+ 1.28302, 1.5574, 1.93788, 2.10334, 2.52062, 2.6237,
+ 1.13883, 1.33747, 1.87109, 1.97275, 2.43348, 2.64765,
+ 1.15594, 1.28112, 1.83135, 1.91924, 2.2666, 2.60094,
+ 1.16684, 1.27382, 1.8432, 1.94603, 2.31838, 2.57879,
+ 1.17229, 1.27501, 1.83258, 2.02592, 2.35381, 2.62469,
+ 1.08216, 1.26544, 1.89236, 1.98901, 2.38316, 2.60142,
+ 1.0919, 1.20882, 1.83501, 2.03446, 2.39472, 2.5629,
+ 1.09883, 1.19949, 1.75765, 2.06589, 2.3904, 2.57889,
+ 1.1328, 1.24439, 1.87662, 2.07155, 2.33918, 2.53792,
+ 1.1806, 1.25947, 1.82316, 2.09506, 2.2569, 2.54272,
+ 1.18699, 1.31291, 1.80079, 2.10504, 2.36699, 2.49608,
+ 1.26639, 1.37714, 1.81043, 2.11327, 2.32962, 2.53315,
+ 1.32359, 1.40452, 1.90424, 2.14593, 2.38611, 2.58094,
+ 1.35217, 1.4514, 1.94982, 2.07705, 2.39082, 2.53857,
+ 1.34386, 1.45223, 1.88989, 2.02674, 2.31748, 2.48249,
+ 1.24481, 1.37885, 1.79256, 1.98674, 2.42257, 2.53695,
+ 1.12462, 1.2536, 1.70382, 1.95132, 2.43964, 2.54515,
+ 0.995104, 1.41175, 1.72851, 1.86164, 2.4566, 2.54496,
+ 1.00107, 1.40911, 1.79773, 1.89757, 2.40948, 2.55532,
+ 1.03398, 1.42816, 1.78694, 1.88029, 2.32636, 2.50316,
+ 0.970169, 1.32072, 1.71664, 1.84157, 2.2202, 2.38892,
+ 0.930477, 1.37338, 1.7984, 1.90473, 2.30579, 2.5253,
+ 0.939935, 1.41846, 1.7727, 1.87809, 2.36749, 2.46153,
+ 0.949116, 1.52711, 1.7659, 1.84073, 2.16493, 2.47434,
+ 0.993353, 1.62934, 1.81344, 1.91022, 2.10077, 2.4929,
+ 1.01383, 1.54962, 1.79683, 1.89194, 2.23976, 2.55635,
+ 0.970121, 1.5098, 1.83401, 1.93898, 2.33857, 2.50435,
+ 0.947238, 1.36138, 1.78355, 1.98471, 2.4239, 2.54718,
+ 0.980991, 1.38878, 1.78331, 2.13171, 2.45463, 2.55869,
+ 1.00267, 1.40234, 1.80719, 2.02446, 2.46442, 2.55428,
+ 1.0107, 1.40419, 1.87256, 2.07936, 2.47933, 2.56962,
+ 0.972976, 1.3758, 1.84337, 1.9807, 2.51361, 2.57827,
+ 0.932062, 1.27768, 1.85113, 1.98588, 2.46629, 2.56626,
+ 0.938577, 1.18115, 1.83396, 1.96503, 2.45801, 2.55053,
+ 0.940095, 1.14545, 1.79669, 2.07827, 2.4829, 2.61063,
+ 0.909789, 1.07408, 1.7174, 2.13911, 2.46252, 2.57226,
+ 0.882446, 1.06665, 1.72956, 2.28466, 2.4789, 2.55502,
+ 0.938178, 1.1215, 1.82849, 2.23404, 2.47478, 2.5571,
+ 0.917165, 1.28307, 1.7795, 2.10029, 2.47583, 2.59018,
+ 1.06294, 1.34904, 1.76276, 2.1183, 2.50481, 2.60679,
+ 1.18696, 1.4619, 1.88904, 2.11274, 2.48132, 2.62131,
+ 1.48072, 1.61923, 1.97948, 2.1771, 2.43648, 2.57898,
+ 1.44872, 1.56634, 1.88013, 2.13853, 2.33968, 2.55459,
+ 1.40799, 1.61355, 1.82893, 2.0527, 2.3445, 2.53808,
+ 1.61602, 1.69101, 1.85635, 1.98008, 2.54825, 2.63776,
+ 1.62817, 1.68416, 1.88615, 2.01287, 2.56377, 2.62158,
+ 1.59574, 1.68801, 1.9354, 2.02581, 2.48363, 2.61682,
+ 1.64156, 1.70866, 1.95546, 2.04699, 2.51983, 2.64574,
+ 1.67367, 1.75221, 1.95129, 2.08092, 2.48739, 2.64072,
+ 1.65642, 1.73624, 1.99136, 2.09832, 2.57191, 2.67683,
+ 1.65982, 1.73245, 1.95125, 2.07702, 2.58164, 2.69352,
+ 1.6548, 1.71621, 1.96664, 2.04423, 2.56325, 2.6802,
+ 1.60273, 1.68261, 1.91741, 1.99483, 2.53109, 2.67329,
+ 1.58255, 1.63953, 1.9261, 1.99207, 2.53207, 2.69711,
+ 1.46237, 1.585, 1.8183, 1.89755, 2.55713, 2.70626,
+ 1.4532, 1.55073, 1.81519, 1.91646, 2.39997, 2.66768,
+ 1.41939, 1.55772, 1.78444, 1.90918, 2.51138, 2.66998,
+ 1.39516, 1.53982, 1.84748, 1.93084, 2.58396, 2.70362,
+ 1.34885, 1.61088, 1.95815, 2.04307, 2.58609, 2.66435,
+ 1.37239, 1.65814, 1.95866, 2.18944, 2.45048, 2.65032,
+ 1.35259, 1.52809, 1.92314, 2.19484, 2.42773, 2.56214,
+ 1.38093, 1.61227, 1.99338, 2.17611, 2.50893, 2.63506,
+ 1.42958, 1.68659, 2.01713, 2.17256, 2.48642, 2.60927,
+ 1.39212, 1.64104, 1.95208, 2.06507, 2.42122, 2.57491,
+ 1.39959, 1.78826, 1.95209, 2.09858, 2.48993, 2.62939,
+ 1.38376, 1.66244, 1.9831, 2.11224, 2.5328, 2.63181,
+ 1.37273, 1.67362, 1.91212, 2.13425, 2.433, 2.61228,
+ 1.39603, 1.64262, 1.96263, 2.19739, 2.52132, 2.66069,
+ 1.37936, 1.62399, 2.0694, 2.24312, 2.56203, 2.66844,
+ 1.33867, 1.61863, 2.04204, 2.19512, 2.57016, 2.6991,
+ 1.29412, 1.71208, 2.05016, 2.12013, 2.60784, 2.68169,
+ 1.29325, 1.59625, 1.99341, 2.06004, 2.58308, 2.66414,
+ 1.20992, 1.36267, 1.95512, 2.02835, 2.51296, 2.6258,
+ 1.3817, 1.70662, 2.00317, 2.14647, 2.50003, 2.61301,
+ 1.20467, 1.73456, 1.9288, 2.10969, 2.4769, 2.54909,
+ 1.11449, 1.69632, 1.88882, 2.04367, 2.53927, 2.63717,
+ 1.11931, 1.60146, 1.84673, 2.08566, 2.57754, 2.64535,
+ 1.12875, 1.53118, 1.85828, 2.14677, 2.59635, 2.68872,
+ 1.13025, 1.67465, 1.83066, 2.17211, 2.56255, 2.67283,
+ 1.10077, 1.64441, 1.83323, 2.04061, 2.59933, 2.65229,
+ 1.06697, 1.5306, 1.76863, 2.00332, 2.61732, 2.67806,
+ 1.06312, 1.46936, 1.79782, 1.88185, 2.56819, 2.67915,
+ 1.17729, 1.70328, 1.86551, 2.06104, 2.48107, 2.58144,
+ 1.40413, 1.6575, 1.92706, 2.18185, 2.45741, 2.58043,
+ 1.42836, 1.66354, 1.98499, 2.18345, 2.45866, 2.56949,
+ 1.4032, 1.66715, 1.95509, 2.14645, 2.46264, 2.56266,
+ 1.23413, 1.59785, 1.91775, 2.03444, 2.40755, 2.56026,
+ 1.22453, 1.36863, 1.84807, 1.92472, 2.49495, 2.67021,
+ 1.21477, 1.58834, 1.76581, 2.00386, 2.52678, 2.63596,
+ 1.26488, 1.63647, 1.82522, 2.07706, 2.56349, 2.67929,
+ 1.26961, 1.58898, 1.78218, 2.09502, 2.62041, 2.69179,
+ 1.29641, 1.50434, 1.80291, 2.01338, 2.60569, 2.68162,
+ 1.33438, 1.52077, 1.79661, 1.96388, 2.60042, 2.70374,
+ 1.39757, 1.60058, 1.84597, 1.94012, 2.61622, 2.69611,
+ 1.43088, 1.55907, 1.79924, 1.99405, 2.59895, 2.6747,
+ 1.48212, 1.58304, 1.80751, 1.98143, 2.57538, 2.68473,
+ 1.46434, 1.56562, 1.77603, 1.91763, 2.575, 2.65927,
+ 1.4554, 1.53823, 1.73066, 1.88207, 2.56375, 2.66044,
+ 1.49958, 1.58442, 1.68807, 1.89207, 2.5871, 2.68867,
+ 1.47976, 1.5737, 1.69519, 2.02444, 2.55818, 2.63904,
+ 1.45227, 1.54712, 1.75057, 2.07203, 2.53701, 2.67379,
+ 1.44738, 1.56304, 1.79438, 2.14163, 2.35339, 2.50255,
+ 1.35172, 1.45071, 1.73023, 1.99189, 2.29835, 2.46355,
+ 1.31876, 1.41462, 1.64199, 1.94834, 2.32625, 2.47429,
+ 1.21205, 1.34623, 1.6851, 1.95989, 2.32224, 2.51295,
+ 1.20902, 1.30295, 1.63462, 1.93085, 2.28291, 2.50754,
+ 1.18895, 1.29282, 1.66566, 2.17785, 2.37356, 2.47429,
+ 1.25754, 1.45115, 1.83601, 2.16148, 2.44729, 2.59664,
+ 1.25342, 1.3702, 1.83372, 2.24474, 2.47977, 2.57602,
+ 1.17995, 1.30201, 1.59215, 2.15158, 2.45596, 2.51812,
+ 1.11448, 1.25765, 1.41158, 2.04236, 2.54829, 2.62041,
+ 1.09999, 1.30707, 1.40717, 2.15942, 2.58591, 2.64936,
+ 1.13115, 1.24686, 1.40128, 2.1166, 2.48376, 2.54666,
+ 1.17377, 1.34087, 1.4499, 2.0937, 2.56103, 2.62648,
+ 1.18957, 1.3462, 1.46559, 2.00354, 2.51775, 2.5757,
+ 1.21797, 1.30299, 1.56949, 2.02897, 2.45573, 2.55014,
+ 1.23191, 1.39323, 1.52046, 1.95573, 2.47623, 2.64224,
+ 1.27718, 1.45114, 1.59102, 1.92599, 2.45809, 2.56656,
+ 1.21624, 1.48312, 1.68868, 1.98897, 2.45463, 2.59962,
+ 1.18429, 1.55304, 1.83889, 2.10027, 2.38501, 2.55005,
+ 1.23917, 1.79282, 1.95907, 2.1826, 2.44529, 2.52957,
+ 1.62457, 1.86085, 2.12033, 2.21992, 2.42941, 2.5941,
+ 1.75324, 1.88933, 2.13652, 2.25457, 2.43633, 2.56246,
+ 1.75727, 1.95692, 2.24234, 2.36011, 2.49374, 2.58763,
+ 1.80684, 1.9852, 2.19776, 2.33868, 2.49634, 2.60068,
+ 1.85991, 2.03042, 2.28254, 2.396, 2.54859, 2.63263,
+ 1.7711, 1.89613, 2.30676, 2.42126, 2.53834, 2.62596,
+ 1.50565, 1.89323, 2.01933, 2.32579, 2.48797, 2.58553,
+ 1.18914, 1.7711, 1.91507, 2.25487, 2.53443, 2.61278,
+ 1.104, 1.64935, 1.83499, 1.93594, 2.53413, 2.652,
+ 1.07901, 1.52244, 1.76728, 1.93497, 2.52313, 2.59639,
+ 1.10621, 1.60804, 1.75144, 2.00839, 2.49173, 2.57715,
+ 1.22513, 1.59727, 1.85783, 2.10361, 2.46542, 2.59305,
+ 1.37537, 1.61836, 1.93052, 2.21445, 2.44556, 2.5762,
+ 1.42999, 1.69897, 1.98214, 2.23334, 2.49044, 2.60535,
+ 1.4828, 1.67946, 1.99776, 2.2224, 2.46458, 2.58682,
+ 1.408, 1.67664, 1.97085, 2.22109, 2.44036, 2.59243,
+ 1.2799, 1.6188, 1.92099, 2.16109, 2.43881, 2.62742,
+ 0.936959, 1.31029, 1.66337, 2.0101, 2.51599, 2.59778,
+ 1.01466, 1.40151, 1.59008, 2.08087, 2.55691, 2.62215,
+ 1.04365, 1.38457, 1.5715, 1.98823, 2.56866, 2.64789,
+ 1.10727, 1.41397, 1.56206, 1.87714, 2.55472, 2.63729,
+ 1.17948, 1.46739, 1.605, 1.839, 2.52348, 2.6405,
+ 1.21832, 1.41202, 1.59163, 1.79653, 2.5198, 2.66057,
+ 1.30537, 1.42738, 1.61458, 1.76369, 2.49727, 2.65779,
+ 1.33854, 1.45634, 1.6422, 1.86235, 2.44879, 2.63162,
+ 1.32868, 1.44222, 1.57523, 1.85891, 2.47066, 2.57043,
+ 1.35122, 1.46628, 1.60143, 1.86374, 2.42525, 2.50034,
+ 1.36091, 1.47648, 1.62462, 1.83211, 2.48627, 2.56333,
+ 1.40173, 1.49988, 1.6134, 1.74973, 2.42322, 2.59141,
+ 1.26155, 1.40299, 1.52378, 1.80204, 2.49974, 2.60553,
+ 1.16, 1.46705, 1.6056, 1.78769, 2.50805, 2.55736,
+ 1.27952, 1.53509, 1.62057, 1.75862, 2.40962, 2.67642,
+ 1.16136, 1.50546, 1.6262, 1.7331, 2.39883, 2.61748,
+ 1.18463, 1.52853, 1.61429, 1.69821, 2.35034, 2.6671,
+ 1.11735, 1.53807, 1.65845, 1.75962, 2.28126, 2.58068,
+ 1.10984, 1.49283, 1.70197, 1.78983, 2.15124, 2.48973,
+ 1.01023, 1.46712, 1.63109, 1.88642, 2.42002, 2.52278,
+ 0.950861, 1.33689, 1.617, 1.78955, 2.44962, 2.52889,
+ 1.02847, 1.3481, 1.57189, 1.88039, 2.54391, 2.60801,
+ 1.11075, 1.41566, 1.69055, 2.00551, 2.55818, 2.6501,
+ 1.11015, 1.43266, 1.6694, 1.90159, 2.51693, 2.60274,
+ 1.06783, 1.54338, 1.71944, 1.979, 2.54367, 2.61757,
+ 1.42254, 1.70106, 1.94043, 2.32706, 2.55761, 2.64296,
+ 1.38612, 1.78193, 2.04068, 2.38389, 2.57395, 2.63346,
+ 1.51277, 1.69633, 2.1845, 2.29598, 2.57899, 2.67726,
+ 1.57185, 1.70524, 2.22523, 2.31919, 2.5426, 2.67616,
+ 1.51491, 1.84429, 2.24734, 2.36159, 2.52907, 2.6533,
+ 1.60358, 1.94842, 2.27181, 2.4296, 2.52821, 2.61773,
+ 1.62041, 2.02418, 2.37902, 2.47798, 2.62296, 2.67076,
+ 1.57882, 1.90635, 2.23831, 2.37884, 2.55696, 2.64712,
+ 1.61114, 1.90067, 2.18578, 2.31738, 2.51701, 2.61014,
+ 1.55461, 1.94143, 2.13305, 2.24986, 2.49176, 2.57161,
+ 1.46962, 1.9189, 2.09418, 2.22518, 2.49035, 2.56434,
+ 1.33537, 1.69721, 2.01709, 2.23232, 2.47434, 2.57102,
+ 1.22194, 1.51906, 1.81406, 2.1294, 2.45829, 2.56013,
+ 1.19335, 1.42604, 1.73164, 2.00909, 2.48569, 2.5661,
+ 1.14086, 1.30414, 1.72407, 1.96212, 2.45682, 2.67358,
+ 1.17199, 1.317, 1.75694, 2.05081, 2.52062, 2.67935,
+ 1.13514, 1.41021, 1.71529, 2.0926, 2.49945, 2.61771,
+ 1.11453, 1.48721, 1.5954, 2.01378, 2.53196, 2.6284,
+ 1.18516, 1.39989, 1.58265, 2.19579, 2.51838, 2.58247,
+ 1.10455, 1.42368, 1.65629, 2.26253, 2.59319, 2.66401,
+ 1.1643, 1.59699, 1.71775, 2.20785, 2.56315, 2.6214,
+ 1.02259, 1.59646, 1.83176, 2.28798, 2.51904, 2.58042,
+ 0.920067, 1.6565, 1.82922, 2.20717, 2.5356, 2.58254,
+ 0.940069, 1.57744, 1.96057, 2.18925, 2.48282, 2.54933,
+ 0.824619, 1.70849, 1.93223, 2.18861, 2.55188, 2.60548,
+ 0.819752, 1.68897, 1.95061, 2.08345, 2.46319, 2.51587,
+ 0.820934, 1.71848, 2.02163, 2.15842, 2.52112, 2.57629,
+ 0.860984, 1.61569, 2.04686, 2.14622, 2.46989, 2.57106,
+ 0.7224, 1.64737, 1.97316, 2.0661, 2.43884, 2.60907,
+ 0.853506, 1.57795, 1.94985, 2.08284, 2.44874, 2.51242,
+ 0.745605, 1.46451, 1.99332, 2.07751, 2.46918, 2.53247,
+ 0.710718, 1.53369, 1.89005, 2.01388, 2.4256, 2.51639,
+ 0.877569, 1.51198, 1.8316, 2.0319, 2.44162, 2.51744,
+ 1.25962, 1.51952, 1.8797, 2.13883, 2.45029, 2.61407,
+ 1.32666, 1.6701, 1.91934, 2.14837, 2.36293, 2.46445,
+ 1.43771, 1.67164, 1.95505, 2.16671, 2.40595, 2.55752,
+ 1.60387, 1.74029, 1.98995, 2.19878, 2.46753, 2.58565,
+ 1.6385, 1.74325, 2.05109, 2.14971, 2.46263, 2.56933,
+ 1.63183, 1.72177, 2.00292, 2.13115, 2.43893, 2.56922,
+ 1.60316, 1.76319, 2.08219, 2.17477, 2.37672, 2.50226,
+ 1.63098, 1.70394, 2.00922, 2.14927, 2.36918, 2.58057,
+ 1.5766, 1.65869, 1.92294, 2.12495, 2.44873, 2.57827,
+ 1.51627, 1.63071, 1.8608, 2.12704, 2.4444, 2.58228,
+ 1.45888, 1.54763, 1.79608, 2.04697, 2.37806, 2.53559,
+ 1.37666, 1.51251, 1.73356, 2.09821, 2.36177, 2.45214,
+ 1.13475, 1.32018, 1.58255, 2.05289, 2.44906, 2.52706,
+ 1.07945, 1.16406, 1.57337, 2.22076, 2.5003, 2.56093,
+ 1.06047, 1.18642, 1.45666, 2.15579, 2.437, 2.5269,
+ 0.974645, 1.13281, 1.56353, 2.08986, 2.50461, 2.57178,
+ 0.925733, 1.04903, 1.55569, 2.09544, 2.54168, 2.61417,
+ 1.01286, 1.15468, 1.28381, 2.12616, 2.55879, 2.59581,
+ 0.970704, 1.08889, 1.3988, 1.96967, 2.51746, 2.62149,
+ 0.99667, 1.1556, 1.28423, 1.96774, 2.47805, 2.53675,
+ 1.06187, 1.17276, 1.29685, 1.89013, 2.46531, 2.55049,
+ 0.971133, 1.1469, 1.42509, 1.82366, 2.3102, 2.51319,
+ 1.12232, 1.24695, 1.57393, 1.94586, 2.35067, 2.54611,
+ 1.13044, 1.2818, 1.71175, 2.05285, 2.47117, 2.56897,
+ 1.28579, 1.42518, 1.8744, 2.08523, 2.42611, 2.57699,
+ 1.27354, 1.49021, 1.87877, 2.10625, 2.40245, 2.54437,
+ 1.22424, 1.46248, 1.90461, 2.12819, 2.41656, 2.57002,
+ 1.25206, 1.44985, 1.80251, 2.11987, 2.41888, 2.5188,
+ 1.32712, 1.41759, 1.78996, 2.17493, 2.34065, 2.46871,
+ 1.34678, 1.43555, 1.73431, 2.03604, 2.35655, 2.53105,
+ 1.23582, 1.31596, 1.59712, 1.89787, 2.28422, 2.57595,
+ 0.955415, 1.30377, 1.56019, 1.73007, 2.44977, 2.64812,
+ 0.909089, 1.47167, 1.62448, 1.89097, 2.38965, 2.62795,
+ 0.919631, 1.36687, 1.50602, 1.84259, 2.342, 2.55449,
+ 0.855197, 1.27967, 1.53955, 1.68852, 2.38691, 2.50206,
+ 0.807057, 1.13562, 1.5416, 1.6813, 2.24391, 2.51087,
+ 0.849115, 1.19024, 1.44993, 1.54139, 2.30258, 2.6556,
+ 0.832569, 1.27336, 1.59248, 1.79281, 2.28417, 2.49848,
+ 0.835449, 1.16892, 1.54463, 1.71893, 2.42389, 2.63262,
+ 0.826578, 1.27619, 1.40786, 1.66029, 2.37804, 2.47453,
+ 0.873632, 1.36031, 1.50287, 1.75833, 2.5708, 2.71226,
+ 0.82832, 1.28463, 1.46241, 1.6242, 2.57586, 2.70561,
+ 0.86693, 1.13331, 1.25406, 1.42989, 2.49929, 2.56231,
+ 0.807119, 1.21808, 1.34601, 1.54062, 2.48761, 2.6331,
+ 0.98368, 1.14658, 1.33665, 1.47931, 2.32716, 2.61436,
+ 0.991742, 1.17073, 1.29617, 1.48561, 2.54305, 2.66382,
+ 0.857243, 1.17219, 1.29859, 1.6239, 2.58125, 2.67565,
+ 1.02446, 1.24516, 1.33583, 1.92396, 2.62349, 2.68982,
+ 1.03526, 1.29306, 1.41981, 1.88269, 2.47498, 2.67367,
+ 0.98116, 1.23984, 1.33455, 1.62845, 2.54405, 2.68174,
+ 0.948338, 1.22739, 1.3601, 1.57206, 2.44798, 2.66861,
+ 1.09712, 1.2561, 1.36219, 1.63254, 2.50779, 2.65642,
+ 1.06074, 1.284, 1.52793, 1.67627, 2.54094, 2.63814,
+ 0.999111, 1.2307, 1.53126, 1.64398, 2.37306, 2.63434,
+ 0.900037, 1.35716, 1.5199, 1.69115, 2.33345, 2.6059,
+ 0.906535, 1.20048, 1.61525, 1.71596, 2.28887, 2.60957,
+ 0.841267, 1.3377, 1.72119, 1.79912, 2.17636, 2.62724,
+ 0.950819, 1.50712, 1.71882, 1.82673, 2.05053, 2.48989,
+ 0.922437, 1.44759, 1.83206, 1.92051, 2.14899, 2.50957,
+ 0.797637, 1.12047, 1.75627, 1.94611, 2.20911, 2.53594,
+ 0.821846, 1.16874, 1.83791, 1.97773, 2.36161, 2.64241,
+ 0.802821, 1.39464, 1.94559, 2.03152, 2.33749, 2.58995,
+ 0.808599, 1.21429, 1.87853, 2.00233, 2.28022, 2.57778,
+ 0.825133, 1.3293, 1.89662, 1.97956, 2.45575, 2.5731,
+ 0.847939, 1.23595, 1.89729, 2.01661, 2.42221, 2.65115,
+ 0.793266, 1.31179, 1.88526, 1.97487, 2.49392, 2.69992,
+ 0.835729, 1.41812, 1.83973, 1.90323, 2.50796, 2.64513,
+ 0.84938, 1.4762, 1.83681, 1.97738, 2.32134, 2.5611,
+ 0.77457, 1.28461, 1.75819, 1.86442, 2.36773, 2.5612,
+ 0.896154, 1.46644, 1.77022, 1.87135, 2.58655, 2.68848,
+ 1.0978, 1.5765, 1.74232, 1.91022, 2.16067, 2.65845,
+ 0.95072, 1.45287, 1.76016, 1.93477, 2.19628, 2.62419,
+ 0.947778, 1.33478, 1.74561, 1.83051, 2.25611, 2.66786,
+ 0.970291, 1.21491, 1.74593, 1.84071, 2.26878, 2.55518,
+ 1.02748, 1.19305, 1.65541, 1.77056, 2.11599, 2.50296,
+ 1.10863, 1.22404, 1.55642, 1.7059, 2.01907, 2.46382,
+ 1.13733, 1.24864, 1.6599, 1.836, 2.0873, 2.49402,
+ 1.19278, 1.29031, 1.65286, 1.87863, 2.08608, 2.61596,
+ 1.23183, 1.34329, 1.52821, 1.64612, 1.91216, 2.35441,
+ 1.04315, 1.3807, 1.67914, 1.83012, 2.00837, 2.41401,
+ 1.10289, 1.24306, 1.74748, 1.86138, 2.20309, 2.50438,
+ 1.04973, 1.35437, 1.73588, 1.819, 2.24881, 2.55779,
+ 1.10598, 1.57142, 1.76481, 1.95355, 2.42885, 2.56011,
+ 1.29085, 1.55016, 1.83756, 2.1266, 2.48883, 2.60078,
+ 1.19424, 1.4267, 1.83766, 1.91401, 2.44321, 2.63552,
+ 1.1655, 1.26009, 1.79094, 1.89331, 2.40045, 2.64664,
+ 1.22495, 1.30814, 1.82593, 1.91949, 2.32136, 2.69508,
+ 1.24849, 1.34538, 1.77545, 1.87671, 2.35372, 2.65414,
+ 1.27114, 1.39967, 1.81154, 1.89758, 2.40349, 2.65392,
+ 1.3091, 1.40766, 1.80684, 1.89783, 2.33922, 2.63235,
+ 1.29102, 1.38333, 1.80244, 1.88719, 2.24772, 2.66245,
+ 1.26136, 1.37051, 1.75597, 1.87125, 2.1019, 2.59359,
+ 1.28264, 1.37654, 1.77553, 1.9045, 2.19234, 2.50743,
+ 1.36136, 1.45086, 1.79107, 1.90616, 2.2215, 2.54334,
+ 1.33499, 1.43138, 1.71627, 1.90549, 2.0892, 2.37826,
+ 1.38567, 1.47042, 1.7654, 1.90922, 2.17384, 2.45657,
+ 1.36432, 1.45506, 1.75488, 1.87147, 2.36504, 2.57228,
+ 1.38778, 1.48689, 1.71209, 1.8475, 2.24356, 2.57069,
+ 1.31245, 1.42529, 1.62289, 1.75678, 1.97847, 2.36751,
+ 1.3472, 1.45434, 1.68343, 1.82547, 2.08792, 2.46256,
+ 1.32645, 1.40544, 1.72764, 1.83555, 2.32887, 2.61433,
+ 1.33311, 1.42971, 1.79607, 1.90035, 2.44506, 2.65291,
+ 1.3228, 1.42159, 1.73694, 1.8435, 2.53212, 2.64664,
+ 1.34468, 1.43186, 1.76621, 1.92458, 2.55008, 2.68986,
+ 1.38828, 1.48581, 1.71196, 1.82621, 2.49614, 2.65849,
+ 1.41113, 1.49561, 1.77687, 1.87667, 2.49259, 2.65135,
+ 1.41779, 1.49158, 1.80169, 1.89041, 2.44245, 2.70699,
+ 1.40612, 1.51559, 1.75734, 1.89697, 2.38205, 2.63363,
+ 1.42586, 1.51481, 1.77326, 1.90174, 2.44755, 2.63472,
+ 1.47603, 1.55503, 1.74573, 1.86162, 2.39877, 2.61498,
+ 1.45985, 1.56153, 1.78645, 1.91123, 2.47654, 2.59179,
+ 1.40306, 1.51419, 1.72076, 1.90094, 2.48989, 2.57733,
+ 1.42813, 1.52351, 1.68976, 1.83521, 2.4589, 2.56597,
+ 1.32896, 1.43471, 1.60407, 1.73425, 2.4663, 2.56683,
+ 1.24132, 1.34325, 1.458, 1.69662, 2.52782, 2.64566,
+ 1.13662, 1.31113, 1.42996, 1.69536, 2.54253, 2.66041,
+ 1.15311, 1.34414, 1.69081, 1.98593, 2.42001, 2.55378,
+ 1.23176, 1.37392, 1.66882, 2.11744, 2.40191, 2.48888,
+ 0.978581, 1.11559, 1.51713, 2.00053, 2.44902, 2.52602,
+ 0.951081, 1.10796, 1.20861, 1.73722, 2.4743, 2.61185,
+ 0.981806, 1.12784, 1.22059, 1.72099, 2.58653, 2.69889,
+ 0.977554, 1.22407, 1.33776, 1.71327, 2.59337, 2.67541,
+ 0.986078, 1.2604, 1.40744, 1.57149, 2.56942, 2.63175,
+ 1.06877, 1.2094, 1.46443, 1.55798, 2.55135, 2.66975,
+ 1.03419, 1.17431, 1.46726, 1.55529, 2.46049, 2.64226,
+ 1.05663, 1.17869, 1.5099, 1.62154, 2.15303, 2.54053,
+ 1.10894, 1.24024, 1.65138, 1.77854, 2.22761, 2.57195,
+ 1.04085, 1.39778, 1.70963, 1.83002, 2.3987, 2.61895,
+ 1.06308, 1.56403, 1.69554, 1.79469, 2.41902, 2.57735,
+ 1.15665, 1.57989, 1.74299, 1.88897, 2.41901, 2.62687,
+ 1.28215, 1.60467, 1.76982, 1.98481, 2.29053, 2.40855,
+ 1.41496, 1.75259, 1.9379, 2.07679, 2.28769, 2.50228,
+ 1.56159, 1.88269, 2.08718, 2.19987, 2.3986, 2.50906,
+ 1.74177, 1.96305, 2.16108, 2.26221, 2.51606, 2.62613,
+ 1.57955, 1.9163, 2.20167, 2.30168, 2.45849, 2.64834,
+ 1.6562, 1.8493, 2.1017, 2.30217, 2.48776, 2.57383,
+ 1.76171, 1.93589, 2.1671, 2.42309, 2.53131, 2.61977,
+ 1.74734, 1.94646, 2.12972, 2.45212, 2.59171, 2.6811,
+ 1.66477, 1.95071, 2.06484, 2.45292, 2.65328, 2.71998,
+ 1.18212, 1.80699, 2.03181, 2.24045, 2.58934, 2.66695,
+ 0.911793, 1.44443, 1.9382, 2.00954, 2.51885, 2.66242,
+ 0.906235, 1.35395, 1.86014, 1.94894, 2.57034, 2.65373,
+ 0.915756, 1.18244, 1.77937, 1.91835, 2.49518, 2.68524,
+ 0.923262, 1.16808, 1.70545, 2.00799, 2.40124, 2.58442,
+ 0.915338, 1.1961, 1.64118, 1.9578, 2.23516, 2.50251,
+ 1.11694, 1.26915, 1.59747, 1.9508, 2.1291, 2.3925,
+ 1.22715, 1.34423, 1.80926, 1.99916, 2.32077, 2.54577,
+ 1.30788, 1.51797, 1.83234, 2.04216, 2.34776, 2.54341,
+ 1.14291, 1.42748, 1.83152, 2.02229, 2.35648, 2.58964,
+ 1.02021, 1.20271, 1.78017, 2.07079, 2.56583, 2.66165,
+ 1.08785, 1.26596, 1.65328, 2.09396, 2.62566, 2.70924,
+ 1.14659, 1.23417, 1.66629, 2.02225, 2.60572, 2.67625,
+ 1.08906, 1.31141, 1.64715, 1.83385, 2.66668, 2.72276,
+ 1.18839, 1.31996, 1.72568, 1.80695, 2.57119, 2.66417,
+ 1.20957, 1.35804, 1.69743, 1.7942, 2.47045, 2.64023,
+ 1.24605, 1.33829, 1.69554, 1.782, 2.56576, 2.66694,
+ 1.26125, 1.38448, 1.61968, 1.77958, 2.5918, 2.71243,
+ 1.33751, 1.45023, 1.64699, 1.77421, 2.57897, 2.70337,
+ 1.38769, 1.4781, 1.61892, 1.74728, 2.53199, 2.6657,
+ 1.30178, 1.39264, 1.54187, 1.66565, 2.48454, 2.65506,
+ 1.25701, 1.39883, 1.52736, 1.73414, 2.61953, 2.68968,
+ 1.21116, 1.32426, 1.66434, 1.91151, 2.58934, 2.68525,
+ 1.11303, 1.32541, 1.6977, 1.94018, 2.59112, 2.67963,
+ 1.00034, 1.35223, 1.71949, 2.02479, 2.57766, 2.6391,
+ 0.952537, 1.56466, 1.91458, 2.02111, 2.48126, 2.55357,
+ 0.94138, 1.57337, 1.89848, 1.99082, 2.3884, 2.52782,
+ 0.835656, 1.42686, 1.9149, 2.0063, 2.45584, 2.54443,
+ 0.762518, 1.61797, 1.84816, 1.95272, 2.51168, 2.57689,
+ 0.760103, 1.72025, 1.88404, 1.9725, 2.52618, 2.66897,
+ 0.788105, 1.51594, 1.76089, 1.95372, 2.49866, 2.5539,
+ 0.84239, 1.23509, 1.68744, 2.01111, 2.39147, 2.52955,
+ 0.970555, 1.30488, 1.68991, 2.0601, 2.38601, 2.52427,
+ 1.07851, 1.22081, 1.63039, 2.10393, 2.41141, 2.5183,
+ 1.03513, 1.37429, 1.73952, 2.01539, 2.38354, 2.54289,
+ 1.23277, 1.46612, 1.94288, 2.1126, 2.35987, 2.47684,
+ 1.03214, 1.46016, 1.84361, 2.11132, 2.40561, 2.54561,
+ 0.863004, 1.57537, 1.75434, 2.02642, 2.48406, 2.54587,
+ 0.78188, 1.62113, 1.87611, 2.13162, 2.59115, 2.66521,
+ 0.689257, 1.56767, 1.95132, 2.24673, 2.50779, 2.64996,
+ 0.76292, 1.45451, 2.05214, 2.23995, 2.40891, 2.57038,
+ 0.735313, 1.36954, 2.14112, 2.22674, 2.40426, 2.51585,
+ 0.692794, 1.21322, 2.02173, 2.17001, 2.40979, 2.63261,
+ 0.749191, 1.32741, 1.8763, 2.15981, 2.39637, 2.54356,
+ 0.723514, 1.31193, 1.77912, 2.00099, 2.33306, 2.52163,
+ 0.800844, 1.39933, 1.70253, 1.88677, 2.1838, 2.39184,
+ 0.935365, 1.5324, 1.7461, 1.84327, 2.02788, 2.36693,
+ 0.879717, 1.39098, 1.69669, 1.87323, 2.27339, 2.53295,
+ 1.11563, 1.39538, 1.55249, 2.06254, 2.37975, 2.48566,
+ 1.25346, 1.37982, 1.72652, 2.1649, 2.38685, 2.50781,
+ 1.28865, 1.54861, 1.76922, 2.10614, 2.42884, 2.5175,
+ 1.36965, 1.61115, 1.79367, 1.97047, 2.36765, 2.55804,
+ 1.39903, 1.69493, 1.86562, 2.03676, 2.40916, 2.58643,
+ 1.43333, 1.74573, 1.93073, 2.15938, 2.42655, 2.57904,
+ 1.26759, 1.66587, 1.97138, 2.10332, 2.44452, 2.56774,
+ 1.22612, 1.49722, 1.88861, 2.08359, 2.54785, 2.62348,
+ 1.21786, 1.50232, 1.85015, 1.97391, 2.50602, 2.62557,
+ 1.21379, 1.59537, 1.87504, 1.97942, 2.42715, 2.60646,
+ 1.23975, 1.51387, 1.76668, 1.94793, 2.28162, 2.49207,
+ 1.24763, 1.58563, 1.72974, 1.8947, 2.38196, 2.52212,
+ 1.20115, 1.47447, 1.74657, 1.83424, 2.28973, 2.52518,
+ 1.18147, 1.55532, 1.7036, 1.82308, 2.31583, 2.44389,
+ 1.19633, 1.57376, 1.73522, 1.80803, 2.4035, 2.55724,
+ 1.14908, 1.63161, 1.76916, 1.92557, 2.36812, 2.54281,
+ 1.07109, 1.63355, 1.76134, 1.87247, 2.40846, 2.57352,
+ 1.06523, 1.55174, 1.71341, 1.88049, 2.38743, 2.51216,
+ 0.987564, 1.63573, 1.78594, 1.95671, 2.4134, 2.54862,
+ 0.931677, 1.52646, 1.77301, 1.89696, 2.43796, 2.5139,
+ 0.900322, 1.64588, 1.78798, 2.04104, 2.33427, 2.43459,
+ 0.867303, 1.71472, 1.90161, 2.09919, 2.3871, 2.47589,
+ 0.868278, 1.69374, 1.9173, 2.01308, 2.2746, 2.38253,
+ 0.848816, 1.56719, 1.82901, 1.92983, 2.3394, 2.42562,
+ 0.789452, 1.36929, 1.82686, 1.91727, 2.41428, 2.50207,
+ 0.737031, 1.1733, 1.87303, 1.97283, 2.45513, 2.54124,
+ 0.759015, 1.25073, 1.78111, 1.99463, 2.42044, 2.55494,
+ 0.749485, 1.36394, 1.89637, 1.99357, 2.44226, 2.50985,
+ 0.749379, 1.21466, 1.94066, 2.03408, 2.45072, 2.5683,
+ 0.801242, 1.26916, 1.8709, 1.95599, 2.40516, 2.47386,
+ 0.82329, 1.25895, 1.87986, 2.0697, 2.41177, 2.5101,
+ 0.836531, 1.27393, 1.9573, 2.04747, 2.49016, 2.58229,
+ 0.834116, 1.18388, 1.88646, 1.96919, 2.49948, 2.60434,
+ 0.876413, 1.17115, 1.94662, 2.0309, 2.43135, 2.55301,
+ 0.839364, 1.05611, 1.85364, 2.10059, 2.39261, 2.55434,
+ 0.864173, 1.16468, 1.83549, 1.96885, 2.37631, 2.5161,
+ 0.932804, 1.29457, 1.83095, 1.90104, 2.44527, 2.55257,
+ 0.963048, 1.35686, 1.76883, 1.89322, 2.47992, 2.61467,
+ 1.03707, 1.35972, 1.82081, 1.89105, 2.51931, 2.60502,
+ 1.06061, 1.46234, 1.79795, 1.93929, 2.52187, 2.59188,
+ 1.07992, 1.50417, 1.80221, 1.93053, 2.46514, 2.5432,
+ 1.14011, 1.33906, 1.81335, 1.90531, 2.37007, 2.53042,
+ 1.15187, 1.35617, 1.77236, 1.88371, 2.37001, 2.61081,
+ 1.28808, 1.63863, 1.75106, 2.27992, 2.55539, 2.62328,
+ 1.45144, 1.73949, 1.9164, 2.3887, 2.63615, 2.70283,
+ 1.59125, 1.85154, 2.21828, 2.38549, 2.59375, 2.67943,
+ 1.59226, 2.01614, 2.2338, 2.33376, 2.54482, 2.66517,
+ 1.6542, 1.94158, 2.25097, 2.37237, 2.4589, 2.59983,
+ 1.70325, 2.0255, 2.2296, 2.3371, 2.46858, 2.61766,
+ 1.63882, 2.00556, 2.20195, 2.26846, 2.49954, 2.61841,
+ 1.92467, 2.13532, 2.45818, 2.50417, 2.59384, 2.6254,
+ 1.80381, 2.06257, 2.19935, 2.28946, 2.55004, 2.64392,
+ 1.77301, 1.97662, 2.10757, 2.22087, 2.44498, 2.54384,
+ 1.76495, 2.00173, 2.21445, 2.2547, 2.47561, 2.57975,
+ 1.67833, 1.86391, 2.24464, 2.34367, 2.47113, 2.63609,
+ 1.75581, 1.86025, 2.22372, 2.35306, 2.4983, 2.58668,
+ 1.69343, 1.86924, 2.2833, 2.3958, 2.51974, 2.58367,
+ 1.7044, 1.79121, 2.14719, 2.33645, 2.47903, 2.59089,
+ 1.68326, 1.86225, 2.16334, 2.35184, 2.52091, 2.61603,
+ 1.62322, 1.80421, 2.22207, 2.3603, 2.6199, 2.69951,
+ 1.65724, 1.82561, 2.25849, 2.34735, 2.54573, 2.69471,
+ 1.66007, 1.86034, 2.25357, 2.36412, 2.56409, 2.63073,
+ 1.5969, 1.83951, 2.21893, 2.38579, 2.54647, 2.62589,
+ 1.62232, 1.8512, 1.99621, 2.3774, 2.52207, 2.59549,
+ 1.02947, 1.25453, 1.74899, 2.05352, 2.44588, 2.57611,
+ 0.856689, 0.993818, 1.56961, 2.21376, 2.46185, 2.54708,
+ 1.01658, 1.1919, 1.29347, 1.77814, 2.4558, 2.55165,
+ 1.01054, 1.22815, 1.31143, 1.82028, 2.53151, 2.65675,
+ 0.908278, 1.18958, 1.28554, 1.8586, 2.52592, 2.61992,
+ 0.871987, 1.17192, 1.31749, 1.82652, 2.40074, 2.51809,
+ 1.03312, 1.18885, 1.4397, 2.03901, 2.57242, 2.6561,
+ 0.970197, 1.29563, 1.40244, 2.03504, 2.48818, 2.54989,
+ 1.0882, 1.22065, 1.55306, 2.13338, 2.5357, 2.59506,
+ 1.00995, 1.3898, 1.51706, 2.11522, 2.47419, 2.55069,
+ 0.993372, 1.42737, 1.53917, 1.9724, 2.52584, 2.58386,
+ 1.04829, 1.48208, 1.63718, 2.16108, 2.52317, 2.61471,
+ 1.02433, 1.56286, 1.69224, 2.29516, 2.59484, 2.64857,
+ 0.907692, 1.61256, 1.74613, 2.16254, 2.57575, 2.61626,
+ 0.890482, 1.61113, 1.77393, 1.97073, 2.57775, 2.6596,
+ 0.808392, 1.5978, 1.78596, 2.0064, 2.56504, 2.63896,
+ 0.766474, 1.58442, 1.83584, 1.92974, 2.58154, 2.64107,
+ 0.769957, 1.62677, 1.86926, 2.02945, 2.60278, 2.66048,
+ 0.798945, 1.53186, 1.83489, 1.94653, 2.62826, 2.69262,
+ 0.720628, 1.38023, 1.8176, 1.89535, 2.54776, 2.6072,
+ 0.717991, 1.30127, 1.75327, 1.88057, 2.50111, 2.57068,
+ 0.757538, 1.19751, 1.71932, 1.8634, 2.4672, 2.58075,
+ 0.753702, 1.29247, 1.69185, 1.7758, 2.47259, 2.58378,
+ 0.814552, 1.2342, 1.58385, 1.68828, 2.54626, 2.60138,
+ 0.892573, 1.25942, 1.54867, 1.62871, 2.46518, 2.55748,
+ 0.949846, 1.26057, 1.42925, 1.62028, 2.39675, 2.4574,
+ 1.0353, 1.2441, 1.49824, 1.64392, 2.38137, 2.52433,
+ 1.10807, 1.33757, 1.53819, 1.80059, 2.51358, 2.61769,
+ 1.18254, 1.37047, 1.56189, 1.84416, 2.54573, 2.61445,
+ 1.21527, 1.3744, 1.59539, 1.9408, 2.51228, 2.59416,
+ 1.23283, 1.3567, 1.64836, 2.04066, 2.51833, 2.60689,
+ 1.29553, 1.441, 1.62601, 2.06359, 2.53545, 2.6072,
+ 1.31746, 1.48417, 1.66663, 2.1072, 2.50946, 2.56956,
+ 1.28814, 1.40484, 1.70844, 2.1424, 2.47826, 2.55815,
+ 1.30118, 1.49063, 1.68866, 2.20974, 2.51657, 2.5826,
+ 1.38891, 1.4886, 1.75307, 2.24911, 2.46845, 2.53274,
+ 1.43236, 1.50195, 1.75604, 2.22738, 2.54031, 2.63382,
+ 1.27063, 1.44425, 1.69718, 2.16774, 2.57417, 2.66708,
+ 1.37795, 1.51182, 1.61924, 2.07059, 2.58057, 2.65545,
+ 1.31909, 1.43763, 1.57516, 1.82626, 2.5685, 2.64694,
+ 1.27334, 1.43938, 1.61468, 1.97782, 2.58918, 2.64227,
+ 1.36481, 1.49144, 1.65464, 1.9149, 2.27758, 2.49171,
+ 1.3814, 1.48233, 1.6257, 1.76745, 2.29282, 2.53541,
+ 1.31612, 1.4108, 1.57452, 1.6965, 2.24155, 2.54414,
+ 1.24921, 1.44841, 1.65161, 1.81201, 2.16694, 2.52883,
+ 1.32999, 1.4301, 1.63778, 1.7537, 2.14427, 2.49173,
+ 1.21201, 1.46018, 1.66372, 1.72397, 2.45273, 2.65487,
+ 1.15467, 1.42799, 1.63984, 1.70382, 2.52478, 2.64719,
+ 1.13219, 1.27638, 1.63819, 1.75073, 2.36014, 2.63024,
+ 1.1068, 1.2922, 1.56399, 1.73715, 2.27638, 2.67348,
+ 1.00947, 1.4092, 1.60525, 1.75588, 2.54981, 2.6669,
+ 0.849242, 1.42476, 1.60734, 1.77047, 2.59306, 2.69757,
+ 0.884126, 1.41867, 1.69054, 1.91036, 2.64889, 2.75356,
+ 0.835786, 1.50533, 1.65083, 1.83983, 2.66751, 2.73182,
+ 0.830887, 1.41843, 1.69822, 1.81279, 2.54661, 2.60518,
+ 0.770144, 1.45618, 1.73535, 1.83979, 2.48532, 2.53941,
+ 0.741204, 1.4612, 1.72026, 2.03966, 2.61315, 2.65662,
+ 0.746126, 1.43606, 1.67492, 1.86887, 2.61646, 2.6596,
+ 0.785082, 1.34349, 1.67545, 1.75655, 2.55005, 2.61191,
+ 0.745773, 1.35482, 1.63002, 1.93899, 2.4536, 2.54908,
+ 0.84578, 1.46925, 1.62908, 1.97497, 2.49928, 2.54978,
+ 0.949421, 1.46277, 1.57299, 2.28604, 2.54958, 2.60293,
+ 1.02515, 1.38536, 1.64839, 2.19293, 2.44063, 2.53102,
+ 1.03372, 1.43617, 1.74409, 2.13226, 2.54404, 2.6189,
+ 1.08284, 1.45584, 1.59799, 2.00309, 2.62826, 2.73613,
+ 1.02162, 1.3808, 1.5378, 2.00792, 2.65618, 2.72548,
+ 0.934605, 1.33831, 1.72128, 2.02138, 2.45266, 2.63594,
+ 0.974987, 1.2806, 1.74048, 1.98864, 2.38339, 2.58854,
+ 0.963572, 1.35863, 1.77509, 2.07708, 2.37441, 2.55255,
+ 1.33939, 1.60607, 1.94104, 2.1598, 2.44654, 2.58731,
+ 1.26864, 1.60406, 1.94006, 2.17892, 2.48766, 2.5975,
+ 1.12981, 1.52262, 1.87297, 2.07507, 2.47971, 2.63317,
+ 1.13535, 1.4223, 1.86599, 1.94531, 2.52336, 2.68614,
+ 1.13554, 1.56227, 1.76815, 1.92201, 2.50605, 2.73613,
+ 1.17333, 1.63762, 1.8454, 1.97453, 2.37951, 2.62759,
+ 1.22309, 1.47716, 1.79951, 1.94529, 2.6037, 2.69777,
+ 1.28565, 1.78142, 1.97253, 2.33525, 2.64962, 2.71925,
+ 1.51607, 1.86247, 2.08499, 2.38614, 2.56337, 2.65052,
+ 1.62251, 1.80088, 2.07468, 2.3711, 2.4941, 2.60895,
+ 1.64422, 1.73091, 2.23525, 2.34462, 2.4606, 2.62177,
+ 1.64649, 1.74384, 2.11867, 2.33454, 2.48765, 2.5973,
+ 1.57447, 1.66694, 2.16568, 2.29463, 2.46302, 2.64293,
+ 1.56853, 1.66268, 2.06838, 2.24007, 2.37478, 2.53429,
+ 1.50109, 1.67557, 2.0192, 2.25394, 2.40396, 2.56021,
+ 1.33322, 1.48186, 1.81038, 2.03244, 2.23527, 2.46402,
+ 1.18419, 1.37647, 1.74307, 2.07718, 2.24737, 2.43664,
+ 0.860298, 1.01797, 1.39947, 2.03136, 2.44583, 2.51204,
+ 0.987543, 1.18722, 1.32467, 2.08656, 2.44026, 2.50786,
+ 0.987539, 1.05739, 1.40051, 2.29103, 2.46201, 2.53454,
+ 1.07257, 1.16846, 1.33543, 2.28155, 2.59528, 2.64199,
+ 1.04242, 1.21947, 1.32875, 2.10439, 2.48141, 2.54485,
+ 1.07584, 1.20487, 1.37029, 2.20656, 2.50952, 2.5572,
+ 1.07591, 1.18808, 1.41434, 2.3201, 2.53091, 2.58942,
+ 1.07615, 1.2674, 1.41198, 2.21842, 2.45229, 2.54095,
+ 1.15455, 1.31481, 1.50039, 2.30097, 2.50519, 2.56979,
+ 1.17038, 1.30037, 1.47778, 2.20108, 2.41823, 2.51101,
+ 1.16483, 1.29078, 1.43643, 2.04217, 2.4346, 2.51715,
+ 1.19386, 1.29319, 1.52759, 2.00881, 2.37081, 2.47326,
+ 1.26354, 1.38567, 1.59613, 2.04876, 2.42779, 2.50408,
+ 1.30519, 1.42101, 1.65888, 2.09585, 2.42943, 2.51858,
+ 1.3783, 1.49436, 1.71028, 2.07804, 2.47796, 2.55948,
+ 1.33373, 1.47526, 1.67404, 2.03963, 2.44671, 2.52705,
+ 1.34615, 1.46853, 1.67367, 1.96109, 2.4626, 2.56716,
+ 1.32426, 1.4669, 1.74709, 2.00944, 2.48056, 2.57128,
+ 1.30692, 1.41105, 1.74078, 2.0324, 2.46634, 2.57579,
+ 1.2773, 1.40831, 1.71568, 1.95693, 2.50597, 2.5973,
+ 1.23917, 1.40986, 1.63569, 1.84314, 2.51134, 2.59249,
+ 1.26227, 1.3779, 1.66588, 1.78528, 2.41492, 2.5191,
+ 1.22377, 1.37861, 1.70694, 1.81201, 2.47211, 2.5535,
+ 1.24828, 1.56097, 1.68845, 2.02442, 2.46468, 2.53208,
+ 1.55115, 1.67483, 1.86392, 2.2426, 2.42567, 2.51231,
+ 1.61354, 1.73636, 1.91583, 2.28434, 2.5051, 2.5755,
+ 1.67565, 1.76455, 2.01326, 2.3086, 2.47931, 2.57088,
+ 1.67679, 1.73219, 2.21691, 2.35074, 2.51681, 2.58494,
+ 1.67209, 1.76809, 2.1703, 2.27753, 2.41116, 2.49253,
+ 1.64585, 1.88123, 2.21635, 2.32063, 2.46081, 2.56493,
+ 1.71409, 1.93321, 2.22012, 2.3277, 2.45303, 2.55743,
+ 1.86416, 1.9656, 2.21189, 2.35407, 2.45155, 2.5437,
+ 1.84051, 1.9809, 2.14136, 2.27592, 2.48783, 2.60703,
+ 1.28163, 1.50854, 1.87809, 2.15331, 2.51039, 2.59772,
+ 1.28594, 1.55852, 1.89593, 2.1545, 2.51005, 2.62888,
+ 1.1797, 1.45797, 1.80582, 2.0887, 2.53683, 2.64835,
+ 1.21318, 1.47414, 1.79648, 1.88639, 2.42644, 2.59714,
+ 1.17576, 1.56663, 1.7868, 1.95963, 2.44398, 2.62181,
+ 1.24128, 1.49554, 1.77294, 1.95943, 2.51364, 2.61189,
+ 1.25286, 1.54735, 1.7413, 1.87367, 2.44728, 2.67464,
+ 1.23425, 1.43703, 1.74215, 1.83575, 2.37217, 2.58149,
+ 1.2624, 1.35128, 1.71028, 1.83349, 2.30891, 2.5836,
+ 1.33086, 1.4241, 1.67389, 1.80298, 2.27185, 2.55676,
+ 1.37492, 1.47319, 1.70336, 1.80452, 2.37449, 2.62583,
+ 1.35042, 1.47764, 1.74193, 1.86958, 2.46816, 2.63785,
+ 1.29945, 1.40927, 1.70733, 1.82882, 2.41262, 2.66007,
+ 1.28367, 1.41318, 1.69401, 1.91384, 2.235, 2.66336,
+ 1.13135, 1.54545, 1.7382, 1.92713, 2.24255, 2.52954,
+ 1.3104, 1.44532, 1.80081, 1.94176, 2.22418, 2.4307,
+ 1.20782, 1.40771, 1.79229, 1.89783, 2.27858, 2.58879,
+ 1.17208, 1.38037, 1.76961, 1.87071, 2.42071, 2.66541,
+ 1.05037, 1.29292, 1.70868, 1.81557, 2.3983, 2.64784,
+ 1.0122, 1.35284, 1.71047, 1.79843, 2.50105, 2.62211,
+ 0.949688, 1.51131, 1.80223, 2.05177, 2.38659, 2.54393,
+ 1.23953, 1.52331, 1.99264, 2.17592, 2.53584, 2.66332,
+ 1.17041, 1.42396, 1.91809, 2.07296, 2.37133, 2.60069,
+ 1.15328, 1.63164, 1.94366, 2.04139, 2.42629, 2.52794,
+ 1.13099, 1.68734, 1.9131, 1.98242, 2.36664, 2.59216,
+ 0.876015, 1.53912, 1.95282, 2.04039, 2.35419, 2.59247,
+ 0.741027, 1.33078, 2.01026, 2.08898, 2.40638, 2.51241,
+ 0.692068, 1.22098, 1.96684, 2.05317, 2.52761, 2.62537,
+ 0.697907, 1.40678, 2.01601, 2.08582, 2.57318, 2.65234,
+ 0.747161, 1.54248, 1.98219, 2.09109, 2.57331, 2.6146,
+ 0.759939, 1.51811, 1.93822, 2.16296, 2.53435, 2.63909,
+ 0.752015, 1.44593, 2.09774, 2.15063, 2.47989, 2.58714,
+ 0.80419, 1.42852, 2.01245, 2.19581, 2.47075, 2.57726,
+ 0.757784, 1.35654, 1.87818, 2.23225, 2.531, 2.6303,
+ 0.782189, 1.2517, 1.76691, 2.20655, 2.56445, 2.6177,
+ 0.692136, 1.30829, 1.59302, 1.84293, 2.50433, 2.65265,
+ 0.779817, 1.26499, 1.68969, 1.80369, 2.5305, 2.66946,
+ 0.774734, 1.19962, 1.64959, 1.72658, 2.4371, 2.59153,
+ 0.885025, 1.31194, 1.64647, 1.73919, 2.57872, 2.67199,
+ 0.949387, 1.38711, 1.64193, 1.76257, 2.52877, 2.58579,
+ 1.01204, 1.45536, 1.66673, 1.75258, 2.43427, 2.55352,
+ 1.10407, 1.52937, 1.68209, 1.97304, 2.34551, 2.51158,
+ 1.424, 1.61941, 1.99551, 2.29891, 2.43078, 2.52129,
+ 1.58246, 1.83207, 2.2751, 2.38313, 2.4828, 2.53932,
+ 1.70637, 2.00167, 2.30003, 2.39481, 2.48697, 2.58695,
+ 1.53226, 1.93376, 2.28401, 2.42231, 2.62294, 2.70604,
+ 1.67894, 1.88906, 2.33897, 2.51297, 2.63237, 2.6795,
+ 1.63441, 1.78371, 2.12418, 2.463, 2.61035, 2.69136,
+ 1.61835, 1.75102, 2.02613, 2.41802, 2.6094, 2.67895,
+ 1.5652, 1.7943, 1.90207, 2.40566, 2.62933, 2.69687,
+ 1.28214, 1.59125, 1.85203, 2.31423, 2.61778, 2.72294,
+ 1.22037, 1.42168, 1.69434, 1.88174, 2.5568, 2.65318,
+ 1.1394, 1.29901, 1.62237, 1.77043, 2.54387, 2.6407,
+ 1.21449, 1.46742, 1.62803, 1.79401, 2.56341, 2.6917,
+ 1.05963, 1.52181, 1.63195, 1.86516, 2.60104, 2.68366,
+ 1.1802, 1.53659, 1.67186, 2.13796, 2.58765, 2.63839,
+ 1.21365, 1.58211, 1.7095, 2.15751, 2.4768, 2.57401,
+ 1.24846, 1.55305, 1.6453, 1.89754, 2.57776, 2.68128,
+ 1.34058, 1.60143, 1.67999, 1.88914, 2.64709, 2.75513,
+ 1.19455, 1.57556, 1.69753, 1.80137, 2.59652, 2.75237,
+ 1.15299, 1.53138, 1.71641, 1.81272, 2.41715, 2.69646,
+ 1.17528, 1.56527, 1.65742, 1.73478, 2.51798, 2.67121,
+ 1.31588, 1.51598, 1.77517, 2.05808, 2.3073, 2.4493,
+ 1.24713, 1.38127, 1.56836, 1.85701, 2.15728, 2.43501,
+ 1.24025, 1.38365, 1.58057, 1.99147, 2.30357, 2.41106,
+ 1.2868, 1.38585, 1.7307, 2.06754, 2.32691, 2.47304,
+ 1.20411, 1.33789, 1.66549, 2.03875, 2.23142, 2.5434,
+ 1.18234, 1.31211, 1.52226, 1.97103, 2.23777, 2.48363,
+ 1.09543, 1.31991, 1.46571, 2.03259, 2.27994, 2.52364,
+ 1.1525, 1.29451, 1.45831, 2.03253, 2.30603, 2.40676,
+ 0.991441, 1.27466, 1.42822, 1.94058, 2.3991, 2.50937,
+ 0.850157, 1.27472, 1.45373, 1.89353, 2.38229, 2.47766,
+ 0.93606, 1.31321, 1.42674, 1.88897, 2.55174, 2.60439,
+ 0.972592, 1.32833, 1.43283, 2.01105, 2.57367, 2.61367,
+ 0.9094, 1.42276, 1.49463, 2.07395, 2.62063, 2.66268,
+ 0.828475, 1.4317, 1.56949, 2.05425, 2.62211, 2.66974,
+ 0.779249, 1.37567, 1.47663, 1.94919, 2.559, 2.62214,
+ 0.81571, 1.47269, 1.65049, 2.00091, 2.56521, 2.61168,
+ 0.822357, 1.33351, 1.55165, 1.86418, 2.59585, 2.70612,
+ 0.736497, 1.25989, 1.49082, 1.88222, 2.49441, 2.61998,
+ 0.90224, 1.431, 1.5205, 1.91079, 2.6054, 2.67859,
+ 0.900488, 1.36305, 1.46181, 2.00977, 2.66588, 2.71718,
+ 1.01539, 1.36153, 1.47485, 1.92044, 2.63748, 2.70257,
+ 0.950918, 1.33518, 1.44088, 1.87435, 2.67892, 2.74624,
+ 0.965674, 1.30691, 1.41289, 1.72718, 2.65632, 2.73947,
+ 1.12134, 1.29133, 1.41298, 1.73139, 2.62458, 2.736,
+ 1.13549, 1.29997, 1.44863, 1.63579, 2.61671, 2.68774,
+ 1.12041, 1.2482, 1.38368, 1.57976, 2.39717, 2.58524,
+ 1.11342, 1.2945, 1.48237, 1.60279, 2.39483, 2.63481,
+ 1.24175, 1.31817, 1.47317, 1.5775, 2.426, 2.64978,
+ 1.18438, 1.27289, 1.49775, 1.60805, 2.14445, 2.53727,
+ 1.28314, 1.37732, 1.54304, 1.64518, 2.10579, 2.4909,
+ 1.13801, 1.38076, 1.56048, 1.64098, 2.27101, 2.62552,
+ 1.24388, 1.35154, 1.60307, 1.73979, 2.03808, 2.44751,
+ 1.26726, 1.50996, 1.64165, 1.83198, 2.33133, 2.47283,
+ 1.27637, 1.4764, 1.62502, 1.93034, 2.31938, 2.52437,
+ 1.22268, 1.55941, 1.66998, 1.80547, 2.32691, 2.58028,
+ 1.26522, 1.50389, 1.83098, 2.09154, 2.39672, 2.56909,
+ 1.25605, 1.52888, 1.85303, 2.10617, 2.36514, 2.50328,
+ 1.2365, 1.47912, 1.7283, 2.04146, 2.52856, 2.6129,
+ 1.22064, 1.60519, 1.71377, 1.95092, 2.59764, 2.64949,
+ 1.25555, 1.59187, 1.70675, 2.06271, 2.56138, 2.6269,
+ 1.30708, 1.58002, 1.65355, 1.94129, 2.55273, 2.64371,
+ 1.31097, 1.5128, 1.65653, 1.83919, 2.5921, 2.67771,
+ 1.1886, 1.31608, 1.57937, 1.69077, 2.4385, 2.64188,
+ 1.11467, 1.23599, 1.59197, 1.74919, 2.35944, 2.54521,
+ 1.08007, 1.27713, 1.728, 2.04141, 2.33707, 2.54979,
+ 1.03222, 1.25021, 1.681, 1.99834, 2.31853, 2.5022,
+ 1.06472, 1.15918, 1.66673, 2.01929, 2.25657, 2.57347,
+ 1.02631, 1.14637, 1.67293, 2.05406, 2.43323, 2.61572,
+ 0.942929, 1.09279, 1.61352, 2.07778, 2.36514, 2.49974,
+ 0.98025, 1.25478, 1.492, 1.80119, 2.44532, 2.57571,
+ 0.957395, 1.25187, 1.37834, 1.74457, 2.50297, 2.66587,
+ 0.840336, 1.26799, 1.39773, 1.82798, 2.55587, 2.65128,
+ 1.0099, 1.17581, 1.27777, 2.04836, 2.6379, 2.7009,
+ 0.88384, 1.02678, 1.14669, 1.89368, 2.51869, 2.61056,
+ 0.997171, 1.13829, 1.24641, 1.83753, 2.54982, 2.64269,
+ 0.992125, 1.17887, 1.28227, 1.9744, 2.55911, 2.61297,
+ 1.06759, 1.2558, 1.35902, 1.96394, 2.54142, 2.59631,
+ 1.08633, 1.32907, 1.43233, 1.92884, 2.52833, 2.59824,
+ 1.10035, 1.34558, 1.46953, 1.94236, 2.46972, 2.56168,
+ 1.10102, 1.37438, 1.56114, 1.94256, 2.48429, 2.553,
+ 1.1775, 1.45517, 1.57149, 1.9435, 2.50031, 2.5509,
+ 1.26077, 1.4779, 1.60161, 2.02402, 2.48743, 2.55424,
+ 1.21644, 1.47008, 1.6396, 1.95721, 2.52383, 2.58819,
+ 1.25798, 1.4072, 1.65143, 1.91072, 2.4642, 2.62087,
+ 1.16209, 1.43654, 1.68217, 1.89692, 2.4473, 2.67707,
+ 1.25022, 1.48463, 1.65387, 1.93047, 2.49389, 2.63344,
+ 1.23798, 1.51339, 1.64878, 1.88034, 2.50409, 2.58149,
+ 1.2232, 1.41246, 1.63408, 1.79718, 2.45121, 2.62062,
+ 1.25874, 1.3584, 1.62772, 1.7261, 2.42829, 2.62133,
+ 1.23492, 1.34561, 1.55215, 1.70868, 2.38574, 2.60605,
+ 1.18642, 1.34181, 1.63691, 1.75468, 2.42972, 2.54439,
+ 1.21626, 1.30589, 1.63278, 1.75577, 2.32081, 2.58379,
+ 1.16534, 1.28415, 1.56053, 1.68204, 2.24322, 2.49467,
+ 1.08586, 1.21511, 1.5906, 1.71533, 2.23163, 2.52723,
+ 1.09165, 1.38416, 1.65516, 1.71656, 2.30278, 2.53555,
+ 1.06033, 1.23908, 1.62721, 1.73757, 2.42016, 2.59915,
+ 1.09008, 1.39478, 1.68248, 1.7999, 2.33181, 2.53286,
+ 1.16904, 1.56812, 1.78572, 2.03155, 2.37221, 2.49786,
+ 1.2419, 1.66208, 1.82249, 2.16954, 2.42454, 2.52519,
+ 1.04029, 1.69041, 1.8531, 2.03859, 2.47201, 2.53597,
+ 0.974879, 1.68906, 1.85014, 2.15131, 2.50742, 2.56254,
+ 0.879683, 1.74384, 1.96806, 2.16115, 2.46392, 2.54585,
+ 0.790116, 1.79441, 2.0373, 2.15974, 2.5084, 2.56488,
+ 0.793374, 1.79617, 2.06052, 2.33107, 2.5913, 2.64858,
+ 0.859332, 1.80046, 2.02545, 2.20064, 2.53432, 2.61132,
+ 0.825206, 1.89513, 2.06358, 2.26453, 2.51403, 2.6108,
+ 0.974068, 1.90478, 2.00264, 2.31585, 2.53967, 2.59516,
+ 0.961311, 1.82128, 2.01521, 2.27454, 2.60079, 2.65336,
+ 0.97104, 1.73701, 1.91495, 2.2439, 2.57236, 2.6126,
+ 0.999552, 1.8179, 1.9531, 2.17859, 2.57433, 2.62628,
+ 0.9773, 1.75604, 1.92914, 2.13535, 2.42421, 2.55609,
+ 1.06554, 1.74764, 1.89917, 2.30975, 2.58739, 2.63059,
+ 1.07706, 1.65572, 1.86833, 2.2386, 2.50891, 2.57184,
+ 1.07783, 1.71642, 1.79146, 2.26622, 2.61548, 2.65405,
+ 1.27602, 1.71338, 1.78883, 2.10144, 2.62562, 2.67959,
+ 1.26317, 1.69909, 1.77693, 2.03511, 2.61035, 2.65342,
+ 1.29714, 1.66767, 1.74401, 2.03012, 2.60806, 2.67807,
+ 1.26237, 1.62646, 1.78116, 2.02618, 2.63626, 2.69918,
+ 1.31803, 1.65777, 1.76358, 1.93904, 2.57545, 2.70561,
+ 0.980669, 1.55589, 1.72298, 1.97855, 2.56896, 2.63842,
+ 0.840013, 1.4634, 1.77278, 2.16486, 2.56689, 2.66623,
+ 0.832158, 1.50575, 1.93789, 2.23397, 2.63013, 2.69488,
+ 0.745541, 1.5301, 2.06073, 2.163, 2.61913, 2.69213,
+ 0.83205, 1.59799, 2.12768, 2.19666, 2.52887, 2.6193,
+ 0.820544, 1.61648, 2.04484, 2.13356, 2.58766, 2.66815,
+ 0.789348, 1.63857, 1.99603, 2.2128, 2.57293, 2.61543,
+ 0.806795, 1.74253, 2.04392, 2.18384, 2.60341, 2.66027,
+ 0.843597, 1.76138, 1.99882, 2.13297, 2.5965, 2.67316,
+ 0.927714, 1.7594, 1.98717, 2.20199, 2.59168, 2.65081,
+ 1.0705, 1.76711, 1.97829, 2.22719, 2.6427, 2.68638,
+ 1.02285, 1.85683, 1.98982, 2.21722, 2.48094, 2.57469,
+ 0.886409, 1.74269, 1.86307, 2.0549, 2.54233, 2.62705,
+ 0.996501, 1.55364, 1.80806, 1.94851, 2.51673, 2.60575,
+ 1.21822, 1.52501, 1.87802, 2.1072, 2.42395, 2.57889,
+ 1.27471, 1.49178, 1.90624, 2.10124, 2.45572, 2.56357,
+ 1.31948, 1.58708, 1.87982, 2.24044, 2.43946, 2.54799,
+ 1.47451, 1.699, 1.92926, 2.22822, 2.45187, 2.56313,
+ 1.54527, 1.72271, 1.8921, 2.16916, 2.52024, 2.60296,
+ 1.54616, 1.66889, 1.96149, 2.21208, 2.506, 2.62127,
+ 1.53562, 1.69929, 2.01636, 2.25082, 2.55009, 2.64562,
+ 1.58341, 1.68775, 2.05195, 2.33263, 2.49172, 2.59804,
+ 1.50093, 1.59405, 1.92923, 2.25985, 2.42262, 2.54776,
+ 1.46492, 1.61478, 1.8817, 2.21673, 2.52895, 2.62322,
+ 1.40673, 1.60503, 1.80598, 2.22272, 2.50901, 2.58784,
+ 1.10642, 1.52778, 1.73018, 2.04592, 2.54946, 2.6375,
+ 1.00815, 1.43972, 1.66547, 1.94137, 2.65244, 2.7511,
+ 0.971347, 1.40208, 1.7089, 1.95327, 2.61333, 2.68499,
+ 0.946352, 1.50104, 1.67215, 1.97587, 2.5279, 2.58557,
+ 0.909229, 1.45358, 1.7139, 2.06564, 2.52931, 2.61316,
+ 0.975079, 1.52329, 1.83956, 2.13855, 2.49869, 2.58372,
+ 0.899524, 1.55241, 1.83164, 2.06857, 2.54488, 2.61118,
+ 0.805175, 1.46233, 1.86054, 2.10134, 2.57044, 2.65485,
+ 0.859011, 1.51453, 1.8924, 2.01252, 2.57968, 2.64852,
+ 0.763528, 1.52243, 1.90254, 2.01852, 2.55645, 2.60958,
+ 0.814387, 1.49485, 1.94172, 2.07798, 2.54033, 2.61284,
+ 0.853805, 1.40187, 1.94299, 2.08809, 2.48839, 2.57861,
+ 0.782036, 1.34855, 1.9353, 2.02508, 2.51682, 2.59805,
+ 0.754386, 1.38495, 1.90024, 1.99966, 2.60037, 2.66376,
+ 0.746921, 1.42114, 1.93457, 2.03891, 2.55327, 2.6123,
+ 0.731911, 1.45076, 1.92451, 2.03274, 2.4979, 2.55649,
+ 0.706741, 1.54373, 1.8766, 1.99252, 2.51018, 2.56596,
+ 0.852548, 1.54995, 1.89917, 2.2265, 2.52279, 2.58394,
+ 0.885718, 1.657, 1.86579, 2.16289, 2.46739, 2.55377,
+ 0.951271, 1.64172, 1.814, 2.15306, 2.4271, 2.49961,
+ 0.928485, 1.50278, 1.80944, 2.22477, 2.4724, 2.55392,
+ 0.816616, 1.3911, 1.66558, 2.17614, 2.51072, 2.58282,
+ 0.915934, 1.39094, 1.76751, 2.16955, 2.47166, 2.65253,
+ 1.11534, 1.36231, 1.72259, 2.03303, 2.40636, 2.60188,
+ 1.13866, 1.25298, 1.68452, 1.93737, 2.38431, 2.6239,
+ 1.08432, 1.21195, 1.63364, 1.88994, 2.41309, 2.62623,
+ 1.12622, 1.34492, 1.6486, 2.07112, 2.48419, 2.60566,
+ 1.1239, 1.46156, 1.8451, 2.17246, 2.46266, 2.60514,
+ 1.13256, 1.46864, 1.74022, 2.18493, 2.46794, 2.5801,
+ 1.14825, 1.50617, 1.6766, 2.04929, 2.44677, 2.56542,
+ 0.999544, 1.4047, 1.64177, 1.86332, 2.52384, 2.59211,
+ 0.932167, 1.39598, 1.70943, 1.84574, 2.52479, 2.59962,
+ 0.870085, 1.47633, 1.72151, 1.89709, 2.49026, 2.59376,
+ 0.891107, 1.42911, 1.78973, 1.95843, 2.5191, 2.60499,
+ 0.85555, 1.42127, 1.90094, 2.01101, 2.54662, 2.60976,
+ 0.895038, 1.48258, 1.87357, 1.97483, 2.51943, 2.58445,
+ 0.809092, 1.4865, 1.90227, 2.00088, 2.51837, 2.59726,
+ 0.808211, 1.46017, 1.88158, 1.9614, 2.46839, 2.61633,
+ 0.774237, 1.47186, 1.90122, 2.01376, 2.56487, 2.66569,
+ 0.800018, 1.57695, 1.93818, 2.04372, 2.49438, 2.6301,
+ 0.804705, 1.57076, 1.88936, 1.97549, 2.44765, 2.55519,
+ 0.840709, 1.60338, 1.82708, 2.02632, 2.44289, 2.49242,
+ 0.887288, 1.53614, 1.78162, 1.9522, 2.50081, 2.57651,
+ 0.847527, 1.5047, 1.79295, 1.89159, 2.57889, 2.63732,
+ 0.959025, 1.53382, 1.82149, 1.97974, 2.46375, 2.5443,
+ 1.03632, 1.64079, 1.88602, 1.96289, 2.35866, 2.57776,
+ 0.981142, 1.48674, 1.7331, 1.87828, 2.53797, 2.61047,
+ 1.04649, 1.43851, 1.74084, 1.85001, 2.59088, 2.68414,
+ 1.1034, 1.48978, 1.73824, 1.8175, 2.58837, 2.70105,
+ 1.17692, 1.47368, 1.73285, 1.82327, 2.52453, 2.73354,
+ 1.17332, 1.43838, 1.69656, 1.79254, 2.58079, 2.66577,
+ 1.13496, 1.42186, 1.60407, 1.75613, 2.61795, 2.70664,
+ 1.13601, 1.38418, 1.6991, 1.85532, 2.59101, 2.68321,
+ 1.20171, 1.42193, 1.73786, 2.0112, 2.54096, 2.68109,
+ 1.22745, 1.62446, 2.12523, 2.34056, 2.59344, 2.67145,
+ 1.26513, 1.76569, 2.13134, 2.39177, 2.61396, 2.69985,
+ 1.34228, 1.58141, 1.97924, 2.29776, 2.52039, 2.60226,
+ 1.44901, 1.72555, 2.17628, 2.35474, 2.53876, 2.62732,
+ 1.41873, 1.89868, 2.20633, 2.2756, 2.48875, 2.58679,
+ 1.55571, 1.8376, 2.16574, 2.34619, 2.53018, 2.62876,
+ 1.44444, 1.79005, 1.91101, 2.30191, 2.46886, 2.54056,
+ 1.37805, 1.6685, 1.84527, 2.32489, 2.53771, 2.60147,
+ 1.39474, 1.68271, 1.81735, 2.07553, 2.51212, 2.56689,
+ 1.2972, 1.65588, 1.82541, 2.0621, 2.51331, 2.57737,
+ 1.28066, 1.6699, 1.82457, 2.16821, 2.52817, 2.60199,
+ 1.3069, 1.60081, 1.76797, 2.09529, 2.50987, 2.606,
+ 1.25768, 1.55975, 1.7878, 2.07689, 2.54039, 2.62718,
+ 1.19685, 1.59755, 1.81742, 2.15266, 2.5808, 2.65125,
+ 1.23593, 1.67664, 1.94231, 2.32648, 2.56154, 2.64559,
+ 1.18906, 1.81889, 2.0815, 2.36645, 2.60802, 2.67209,
+ 1.42759, 1.88542, 2.26491, 2.42422, 2.57137, 2.65115,
+ 1.71447, 1.93787, 2.39001, 2.45715, 2.55202, 2.60193,
+ 1.87414, 2.07351, 2.37047, 2.51126, 2.70918, 2.7495,
+ 1.64782, 1.9878, 2.28191, 2.4121, 2.60469, 2.67482,
+ 1.59637, 1.88153, 2.19399, 2.38052, 2.51192, 2.58456,
+ 1.55551, 1.77522, 2.06409, 2.3257, 2.51293, 2.59926,
+ 1.33005, 1.71296, 1.91762, 2.2859, 2.46659, 2.57928,
+ 0.990071, 1.41087, 1.63233, 1.96589, 2.46688, 2.58042,
+ 0.92515, 1.29903, 1.5514, 1.89749, 2.49848, 2.64521,
+ 0.96808, 1.36713, 1.52036, 1.98816, 2.31347, 2.54694,
+ 0.974374, 1.28381, 1.47481, 2.0783, 2.33109, 2.45515,
+ 1.00062, 1.29915, 1.41568, 1.95576, 2.26155, 2.35426,
+ 0.964045, 1.13649, 1.30593, 1.93641, 2.19754, 2.29942,
+ 1.01309, 1.20114, 1.37266, 1.82018, 2.06358, 2.21066,
+ 1.08648, 1.2167, 1.47666, 1.60404, 1.85596, 2.3245,
+ 1.09016, 1.20121, 1.46078, 1.56222, 2.01609, 2.45898,
+ 1.13375, 1.25747, 1.40719, 1.78768, 2.28953, 2.53085,
+ 1.13483, 1.34122, 1.63629, 1.81377, 2.21945, 2.58465,
+ 0.952747, 1.30093, 1.61689, 1.75101, 2.35211, 2.54788,
+ 1.0787, 1.49004, 1.57158, 1.80053, 2.46817, 2.65044,
+ 1.23905, 1.33303, 1.55138, 1.70782, 2.24292, 2.60425,
+ 1.17652, 1.29911, 1.58888, 1.71408, 2.12886, 2.53352,
+ 1.13583, 1.25306, 1.53841, 1.63448, 2.25809, 2.59387,
+ 1.09238, 1.25324, 1.54177, 1.67988, 2.4232, 2.61758,
+ 1.14266, 1.2564, 1.52828, 1.62968, 2.39158, 2.58969,
+ 1.17279, 1.28125, 1.4792, 1.60888, 2.33594, 2.59368,
+ 1.14678, 1.25195, 1.43292, 1.55329, 2.23894, 2.53418,
+ 1.10995, 1.23142, 1.4121, 1.51605, 2.30857, 2.5999,
+ 1.12027, 1.23554, 1.42574, 1.50952, 2.43553, 2.64381,
+ 1.08587, 1.1893, 1.39272, 1.49435, 2.12934, 2.50899,
+ 1.0205, 1.17314, 1.44097, 1.57442, 2.33586, 2.52405,
+ 1.04055, 1.17434, 1.52572, 1.69311, 2.49375, 2.63235,
+ 1.03452, 1.20526, 1.36509, 1.513, 2.47179, 2.57801,
+ 1.07938, 1.204, 1.33243, 1.4566, 2.50213, 2.66563,
+ 1.08886, 1.23695, 1.357, 1.56494, 2.60202, 2.70758,
+ 1.10679, 1.2624, 1.36727, 1.82395, 2.59858, 2.6763,
+ 1.08501, 1.23353, 1.31146, 1.73033, 2.56009, 2.69032,
+ 1.06921, 1.18022, 1.34302, 1.47483, 2.26805, 2.54431,
+ 1.03939, 1.37562, 1.72144, 2.03802, 2.464, 2.60081,
+ 1.26785, 1.38411, 1.6599, 1.93402, 2.20776, 2.42458,
+ 1.22528, 1.31662, 1.67815, 1.81923, 2.16534, 2.49855,
+ 1.11414, 1.28303, 1.65552, 1.87967, 2.35247, 2.55354,
+ 1.09476, 1.37002, 1.79913, 2.08238, 2.46949, 2.57882,
+ 1.04125, 1.47276, 1.74873, 2.04759, 2.5117, 2.58983,
+ 1.07167, 1.45655, 1.70052, 1.92732, 2.44148, 2.607,
+ 0.929006, 1.48724, 1.66955, 1.88562, 2.54427, 2.62832,
+ 0.844366, 1.33971, 1.81246, 2.30021, 2.56601, 2.63125,
+ 0.761441, 1.27995, 1.67045, 2.00635, 2.52682, 2.60756,
+ 0.716643, 1.37484, 1.84344, 2.12696, 2.55299, 2.61315,
+ 0.749967, 1.59846, 1.88327, 2.05044, 2.57918, 2.61411,
+ 0.759376, 1.59638, 1.9291, 1.98455, 2.56673, 2.65421,
+ 0.724977, 1.6829, 1.88829, 2.0348, 2.50386, 2.5655,
+ 0.812327, 1.66987, 1.96177, 2.10215, 2.53878, 2.59856,
+ 0.767334, 1.59463, 1.98432, 2.13342, 2.50169, 2.55781,
+ 0.76023, 1.65065, 1.92837, 2.09405, 2.56524, 2.59608,
+ 0.766762, 1.64806, 1.85855, 2.07859, 2.58708, 2.60821,
+ 0.860938, 1.62925, 1.82485, 2.06735, 2.56337, 2.60321,
+ 0.960953, 1.58363, 1.75221, 2.07844, 2.55553, 2.62851,
+ 1.00793, 1.548, 1.73495, 2.18566, 2.48935, 2.55145,
+ 1.0404, 1.47112, 1.64352, 2.05156, 2.50852, 2.57917,
+ 1.09602, 1.45743, 1.60401, 1.9262, 2.48203, 2.5522,
+ 1.13043, 1.43153, 1.59281, 2.01474, 2.51065, 2.56778,
+ 1.1979, 1.46548, 1.62293, 2.07595, 2.50705, 2.58275,
+ 1.25883, 1.5048, 1.65911, 1.97065, 2.59575, 2.68565,
+ 1.31545, 1.46745, 1.70572, 1.89863, 2.60257, 2.70498,
+ 1.27248, 1.43189, 1.71285, 1.94026, 2.65038, 2.71717,
+ 1.27886, 1.52865, 1.7962, 1.9952, 2.50176, 2.58761,
+ 1.45862, 1.69394, 2.0679, 2.26484, 2.50686, 2.62394,
+ 1.7188, 1.90961, 2.1476, 2.35417, 2.48558, 2.59127,
+ 1.81387, 1.87548, 2.09764, 2.32968, 2.4978, 2.59625,
+ 1.74429, 1.85945, 2.04317, 2.28459, 2.4309, 2.53857,
+ 1.51418, 1.8083, 1.93379, 2.23465, 2.46223, 2.54624,
+ 1.48926, 1.78119, 1.908, 2.14448, 2.41859, 2.51386,
+ 1.43479, 1.67979, 1.81735, 2.10537, 2.43137, 2.52824,
+ 1.46958, 1.58951, 1.81351, 2.21313, 2.4405, 2.52051,
+ 1.49629, 1.64005, 1.89386, 2.29862, 2.4847, 2.57621,
+ 1.33342, 1.58473, 1.89302, 2.12181, 2.52535, 2.63262,
+ 1.51872, 1.73584, 1.95653, 2.17643, 2.46534, 2.57234,
+ 1.52095, 1.74256, 2.01058, 2.13358, 2.44746, 2.5667,
+ 1.45812, 1.69223, 2.00192, 2.12054, 2.43104, 2.56511,
+ 1.52691, 1.66239, 2.02514, 2.12506, 2.53787, 2.62681,
+ 1.4983, 1.64421, 1.96073, 2.10329, 2.44031, 2.57241,
+ 1.41548, 1.54829, 1.7708, 2.09993, 2.45026, 2.59946,
+ 1.36719, 1.46063, 1.73948, 2.07403, 2.55195, 2.64
+};
+
+const struct lsp_codebook lsp_cbvq[] = {
+ /* codebook/lsp1.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes0
+ },
+ /* codebook/lsp2.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes1
+ },
+ /* codebook/lsp3.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes2
+ },
+ /* codebook/lsp4.txt */
+ {
+ 1,
+ 4,
+ 16,
+ codes3
+ },
+ /* ../unittest/lsp45678910.txt */
+ {
+ 6,
+ 12,
+ 4096,
+ codes4
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+/* THIS IS A GENERATED FILE. Edit generate_codebook.c and its input */
+
+/*
+ * This intermediary file and the files that used to create it are under
+ * The LGPL. See the file COPYING.
+ */
+
+#include "defines.h"
+
+ /* codebook/lspvqanssi1.txt */
+static const float codes0[] = {
+ 0.5862, 0.7213, 0.9146, 1.0909, 1.291, 1.4954, 1.837, 2.084, 2.3771, 2.5518,
+ 0.0871, 0.2049, 0.5849, 0.8552, 1.2096, 1.4686, 1.821, 2.0926, 2.4508, 2.7389,
+ 0.2274, 0.3126, 0.6088, 0.8338, 1.1824, 1.5948, 1.8228, 1.9856, 2.1832, 2.4793,
+ 0.1827, 0.2706, 0.5842, 0.7761, 1.0301, 1.2462, 1.6313, 1.9786, 2.3479, 2.679,
+ 0.3055, 0.3863, 0.7194, 1.1609, 1.3303, 1.5017, 1.7265, 1.9412, 2.4659, 2.6315,
+ 0.1794, 0.2522, 0.5477, 0.7892, 1.3887, 1.7101, 1.9471, 2.1667, 2.4361, 2.631,
+ 0.1825, 0.2729, 0.4185, 0.6024, 1.2531, 1.7291, 1.9937, 2.1849, 2.5865, 2.7748,
+ 0.3219, 0.4045, 0.7357, 1.2708, 1.4626, 1.6439, 1.9388, 2.1212, 2.5005, 2.6749,
+ 0.2234, 0.3496, 0.5054, 0.6981, 0.8672, 1.0431, 1.7091, 2.069, 2.329, 2.6195,
+ 0.3009, 0.3957, 0.7576, 0.9751, 1.1955, 1.7727, 2.0383, 2.2474, 2.5612, 2.7188,
+ 0.3841, 0.5544, 0.9209, 1.1811, 1.5441, 1.8126, 2.1175, 2.3192, 2.5486, 2.6935,
+ 0.2153, 0.3105, 0.5597, 0.8313, 1.2168, 1.4512, 1.7012, 1.8962, 2.3893, 2.5852,
+ 0.3196, 0.4814, 0.7629, 1.0869, 1.5517, 1.778, 2.0462, 2.2547, 2.5023, 2.6706,
+ 0.1964, 0.3055, 0.4307, 0.7178, 1.426, 1.624, 1.8392, 2.0576, 2.2976, 2.5492,
+ 0.426, 0.6888, 1.2019, 1.4194, 1.6437, 1.8221, 2.0469, 2.2508, 2.5142, 2.6795,
+ 0.3004, 0.3944, 0.5847, 1.005, 1.1812, 1.3559, 1.5479, 1.7847, 2.4924, 2.6703,
+ 0.1595, 0.2398, 0.4336, 0.9228, 1.2602, 1.5064, 1.7915, 1.984, 2.232, 2.5692,
+ 0.1832, 0.2985, 0.4205, 0.598, 0.762, 0.9894, 1.7499, 2.1151, 2.4814, 2.7214,
+ 0.2234, 0.3207, 0.5457, 0.9799, 1.2074, 1.7079, 1.9734, 2.1742, 2.4575, 2.6366,
+ 0.3598, 0.4819, 0.6385, 0.8878, 1.3226, 1.491, 1.7257, 1.9456, 2.2061, 2.4579,
+ 0.4671, 0.5911, 0.8513, 1.0923, 1.5104, 1.7043, 1.9727, 2.1839, 2.4484, 2.6111,
+ 0.2418, 0.3937, 0.542, 0.8971, 1.1152, 1.3054, 1.7928, 1.9796, 2.5441, 2.7572,
+ 0.3541, 0.473, 0.6546, 0.9063, 1.0792, 1.2743, 1.8545, 2.0555, 2.3083, 2.5404,
+ 0.3121, 0.4016, 0.7137, 0.8835, 1.0736, 1.5907, 1.8624, 2.0857, 2.5075, 2.6668,
+ 0.2232, 0.3631, 0.5273, 0.7438, 1.0492, 1.2235, 1.5449, 2.2198, 2.516, 2.6852,
+ 0.2557, 0.3528, 0.5051, 0.6528, 0.8351, 1.5688, 1.8838, 2.1056, 2.4401, 2.6111,
+ 0.4342, 0.5318, 0.9234, 1.1146, 1.3015, 1.5198, 1.8211, 2.034, 2.3694, 2.5506,
+ 0.431, 0.5269, 0.7431, 0.9018, 1.0734, 1.5196, 1.8267, 2.0244, 2.4508, 2.6177,
+ 0.215, 0.3249, 0.4966, 0.9434, 1.1627, 1.3497, 1.8003, 2.0045, 2.3567, 2.5909,
+ 0.2798, 0.4111, 0.5786, 0.7971, 1.0414, 1.2142, 1.6947, 2.0866, 2.3351, 2.5545,
+ 0.1688, 0.2693, 0.4004, 0.6337, 1.3058, 1.5064, 1.7535, 1.9689, 2.5542, 2.7424,
+ 0.4419, 0.6209, 1.0127, 1.2135, 1.4104, 1.6111, 1.882, 2.1005, 2.4238, 2.5966,
+ 0.3645, 0.512, 0.8977, 1.2209, 1.5286, 1.7204, 1.9787, 2.1779, 2.439, 2.6114,
+ 0.2897, 0.4136, 0.5504, 0.8515, 1.2641, 1.4334, 1.8079, 2.0656, 2.3509, 2.7593,
+ 0.1611, 0.4723, 0.742, 1.0071, 1.2571, 1.5891, 1.9224, 2.2345, 2.5647, 2.7991,
+ 0.2528, 0.4178, 0.8909, 1.3117, 1.6622, 1.8641, 2.1017, 2.2974, 2.5299, 2.6982,
+ 0.1749, 0.27, 0.4116, 0.6036, 1.143, 1.7776, 2.0394, 2.222, 2.4667, 2.6598,
+ 0.3451, 0.4325, 0.6194, 0.7406, 0.9176, 1.554, 1.8426, 2.0479, 2.4401, 2.5965,
+ 0.3672, 0.5164, 0.6558, 0.8441, 1.2332, 1.4114, 1.6955, 2.0875, 2.3674, 2.5471,
+ 0.2194, 0.3467, 0.7384, 1.1079, 1.5398, 1.8437, 2.1212, 2.3296, 2.58, 2.7403,
+ 0.1525, 0.2343, 0.3915, 0.6843, 1.0517, 1.502, 1.7905, 1.9667, 2.2027, 2.6725,
+ 0.3531, 0.5908, 0.7462, 0.9441, 1.2774, 1.4743, 1.8268, 2.1059, 2.4478, 2.6484,
+ 0.3611, 0.4981, 0.7598, 0.9676, 1.4024, 1.633, 1.9094, 2.1433, 2.4408, 2.613,
+ 0.2153, 0.3366, 0.4974, 0.6693, 1.1944, 1.6791, 1.9002, 2.1105, 2.41, 2.5922,
+ 0.2421, 0.3392, 0.5123, 0.9818, 1.5411, 1.7092, 1.9989, 2.1981, 2.5659, 2.7656,
+ 0.2116, 0.325, 0.4845, 0.8021, 1.0088, 1.2158, 1.8038, 2.0223, 2.2975, 2.581,
+ 0.1902, 0.2942, 0.8003, 1.1086, 1.3606, 1.6008, 1.8956, 2.1328, 2.4481, 2.6405,
+ 0.2772, 0.3914, 0.5826, 0.7654, 0.9495, 1.124, 1.3949, 2.0411, 2.3891, 2.5959,
+ 0.2678, 0.522, 0.763, 1.1, 1.3747, 1.6432, 1.9391, 2.2237, 2.5511, 2.7893,
+ 0.32, 0.4245, 0.6174, 0.9904, 1.1662, 1.3882, 1.7601, 1.9524, 2.3998, 2.5819,
+ 0.1702, 0.4871, 0.837, 1.0989, 1.3593, 1.583, 1.875, 2.1277, 2.4666, 2.6885,
+ 0.228, 0.3748, 0.6554, 0.9113, 1.2081, 1.4619, 1.8181, 2.0541, 2.3791, 2.5701,
+ 0.1752, 0.4363, 0.6454, 0.8798, 1.1079, 1.5367, 1.8667, 2.1716, 2.4804, 2.7249,
+ 0.3804, 0.47, 0.8224, 1.0099, 1.1892, 1.5906, 1.8879, 2.0907, 2.4544, 2.6238,
+ 0.1808, 0.291, 0.4683, 0.7059, 0.898, 1.4031, 1.7063, 1.9444, 2.4658, 2.6776,
+ 0.2418, 0.3803, 0.5443, 0.7589, 1.1496, 1.3185, 1.5451, 1.7433, 2.131, 2.6523,
+ 0.2698, 0.369, 0.5362, 1.0732, 1.2921, 1.4696, 1.744, 1.947, 2.5051, 2.6841,
+ 0.4099, 0.5102, 0.6983, 1.0468, 1.2459, 1.4185, 1.8851, 2.0815, 2.3464, 2.5605,
+ 0.0669, 0.1354, 0.3764, 0.8433, 1.1719, 1.4834, 1.8181, 2.1312, 2.4626, 2.8044,
+ 0.1614, 0.2372, 0.3878, 0.5708, 1.2759, 1.495, 1.8052, 2.0807, 2.3485, 2.6293,
+ 0.1688, 0.2875, 0.4301, 0.9059, 1.2361, 1.4054, 1.8057, 1.9924, 2.5589, 2.7495,
+ 0.2864, 0.3783, 0.7032, 1.0817, 1.2382, 1.5741, 1.8619, 2.0656, 2.5139, 2.6848,
+ 0.3829, 0.4781, 0.6766, 0.834, 1.0056, 1.4147, 1.665, 1.884, 2.3922, 2.5619,
+ 0.3259, 0.4187, 0.6139, 0.7338, 1.1831, 1.6497, 1.9, 2.1278, 2.4322, 2.593,
+ 0.2569, 0.379, 0.5426, 0.839, 0.9871, 1.485, 1.8652, 2.0732, 2.4314, 2.6005,
+ 0.1408, 0.2283, 0.4024, 0.8784, 1.1485, 1.4003, 1.7004, 1.9205, 2.3723, 2.6522,
+ 0.2971, 0.5039, 0.8005, 1.1212, 1.4232, 1.7801, 2.1255, 2.3907, 2.6795, 2.8487,
+ 0.1515, 0.2344, 0.4684, 0.804, 1.0401, 1.3774, 1.8329, 2.1235, 2.5555, 2.777,
+ 0.5778, 0.7157, 0.891, 1.0966, 1.4235, 1.6482, 1.9551, 2.1831, 2.4572, 2.6234,
+ 0.3017, 0.4161, 0.8088, 0.9971, 1.2, 1.4419, 1.7867, 2.0224, 2.3473, 2.54,
+ 0.1208, 0.2814, 0.6564, 0.9448, 1.2377, 1.5663, 1.9084, 2.2112, 2.5583, 2.8155,
+ 0.2127, 0.3127, 0.4635, 0.6416, 0.8449, 1.6652, 2.0577, 2.2656, 2.5811, 2.7434,
+ 0.1942, 0.3011, 0.4212, 0.6901, 1.5369, 1.7639, 1.9608, 2.1766, 2.4435, 2.6663,
+ 0.351, 0.4345, 0.7146, 0.9086, 1.0678, 1.2579, 1.4425, 2.0265, 2.4574, 2.6252,
+ 0.3225, 0.4323, 0.6168, 0.858, 1.5388, 1.791, 1.9927, 2.2013, 2.4494, 2.616,
+ 0.2271, 0.4488, 0.6287, 0.7857, 1.2086, 1.383, 1.6194, 2.1955, 2.5236, 2.6945,
+ 0.2568, 0.351, 0.5613, 1.05, 1.2521, 1.4359, 1.6995, 1.9187, 2.2148, 2.4275,
+ 0.2933, 0.3941, 0.6128, 0.8899, 1.072, 1.2862, 1.5331, 1.8301, 2.1553, 2.3865,
+ 0.348, 0.4626, 0.6009, 0.763, 0.9044, 1.1225, 1.8539, 2.1845, 2.5035, 2.7091,
+ 0.1337, 0.4722, 0.8099, 1.1273, 1.4252, 1.699, 2.0188, 2.2922, 2.6018, 2.8168,
+ 0.1138, 0.3263, 0.8059, 1.0473, 1.3262, 1.6202, 1.9439, 2.2007, 2.5347, 2.7702,
+ 0.1979, 0.313, 0.4635, 0.8504, 1.1143, 1.3221, 2.0371, 2.2421, 2.5406, 2.7491,
+ 0.3321, 0.4194, 0.8239, 1.0458, 1.1981, 1.3733, 1.5661, 1.9985, 2.3747, 2.5416,
+ 0.3729, 0.5958, 0.9551, 1.265, 1.5484, 1.9255, 2.2256, 2.4809, 2.7276, 2.8935,
+ 0.1664, 0.2516, 0.5347, 0.7545, 1.1971, 1.4089, 1.74, 2.0871, 2.4098, 2.6795,
+ 0.237, 0.3178, 0.6123, 1.3315, 1.547, 1.7257, 2.0063, 2.1977, 2.5449, 2.7252,
+ 0.203, 0.3328, 0.4766, 0.7357, 1.278, 1.4439, 1.7229, 1.9405, 2.2278, 2.6816,
+ 0.1702, 0.2919, 0.4598, 0.7123, 0.9077, 1.145, 1.8632, 2.0806, 2.499, 2.71,
+ 0.2421, 0.3578, 0.54, 0.7217, 0.8971, 1.4898, 1.8518, 2.1205, 2.6077, 2.7894,
+ 0.303, 0.3935, 0.5812, 0.7404, 0.9425, 1.8342, 2.0887, 2.2811, 2.5596, 2.7118,
+ 0.1322, 0.1997, 0.3466, 0.6981, 1.1811, 1.4849, 1.8594, 2.1114, 2.4708, 2.7804,
+ 0.2317, 0.3069, 0.686, 1.4306, 1.7121, 1.8671, 2.1249, 2.2995, 2.5705, 2.7456,
+ 0.3778, 0.4863, 0.6639, 0.9163, 1.156, 1.3186, 1.5389, 1.7169, 2.1603, 2.5797,
+ 0.2118, 0.3499, 0.5259, 0.72, 1.1348, 1.314, 1.5657, 2.0241, 2.2873, 2.5184,
+ 0.2902, 0.4368, 0.6331, 0.8971, 1.3102, 1.5219, 1.8674, 2.1512, 2.4708, 2.6809,
+ 0.1418, 0.3988, 0.6251, 0.8544, 1.1268, 1.3964, 1.7585, 2.0322, 2.3964, 2.6928,
+ 0.2314, 0.3462, 0.7282, 0.9211, 1.1766, 1.4941, 1.7368, 1.9546, 2.517, 2.7066,
+ 0.2076, 0.3251, 0.7423, 0.959, 1.1936, 1.5329, 1.8887, 2.1588, 2.4667, 2.6709,
+ 0.2058, 0.4139, 0.5745, 0.7832, 0.9595, 1.1688, 1.7561, 1.9562, 2.484, 2.7001,
+ 0.1834, 0.2971, 0.4643, 0.6625, 0.8802, 1.1137, 1.5183, 1.8417, 2.3842, 2.7042,
+ 0.1688, 0.4218, 0.707, 1.0465, 1.4496, 1.6953, 1.956, 2.2174, 2.5172, 2.7404,
+ 0.2323, 0.3981, 0.5489, 0.7227, 1.2886, 1.5221, 1.7158, 2.1184, 2.4066, 2.5898,
+ 0.347, 0.5265, 0.814, 1.0152, 1.3206, 1.5411, 1.849, 2.0588, 2.3556, 2.5393,
+ 0.1707, 0.2595, 0.6762, 0.9037, 1.2781, 1.4903, 1.7946, 2.061, 2.3741, 2.5771,
+ 0.1457, 0.2318, 0.6039, 1.0078, 1.3461, 1.5908, 1.8818, 2.1248, 2.4432, 2.6714,
+ 0.6574, 0.8086, 1.0243, 1.2183, 1.4837, 1.7129, 2.0197, 2.2464, 2.5059, 2.6716,
+ 0.2546, 0.4983, 0.8674, 1.2536, 1.6704, 1.9529, 2.2134, 2.4319, 2.6532, 2.8109,
+ 0.2455, 0.3379, 0.4632, 0.8635, 1.5286, 1.8047, 1.9909, 2.1806, 2.4031, 2.5729,
+ 0.4772, 0.6742, 1, 1.2474, 1.5288, 1.7415, 2.0102, 2.2168, 2.477, 2.6449,
+ 0.3357, 0.4382, 0.6033, 1.1317, 1.3681, 1.5576, 1.9251, 2.1119, 2.5548, 2.7395,
+ 0.2588, 0.7015, 0.8953, 1.083, 1.2828, 1.516, 1.8965, 2.1921, 2.515, 2.7258,
+ 0.2466, 0.3512, 0.5047, 0.6646, 0.8161, 1.2577, 1.8046, 2.0214, 2.4447, 2.6491,
+ 0.1631, 0.2283, 0.407, 0.5955, 1.1126, 1.3894, 1.8978, 2.1849, 2.5384, 2.7382,
+ 0.3424, 0.4748, 0.6222, 0.802, 0.9706, 1.1568, 1.7044, 1.9297, 2.2127, 2.5627,
+ 0.2088, 0.5143, 0.74, 0.9277, 1.1032, 1.3561, 1.8841, 2.2004, 2.5882, 2.7993,
+ 0.2016, 0.3488, 0.5894, 0.7419, 1.1488, 1.3626, 1.5566, 1.9694, 2.5488, 2.7209,
+ 0.2558, 0.3914, 0.536, 0.7521, 1.433, 1.6955, 1.8886, 2.1428, 2.419, 2.5966,
+ 0.4021, 0.5034, 0.6653, 0.8123, 0.9586, 1.2825, 1.9184, 2.112, 2.409, 2.597,
+ 0.2343, 0.48, 0.6934, 0.8523, 1.2786, 1.4763, 1.7235, 2.04, 2.3602, 2.5562,
+ 0.246, 0.3687, 0.5325, 0.7044, 1.1488, 1.3608, 1.8112, 2.0757, 2.4183, 2.663,
+ 0.1616, 0.3644, 0.5725, 0.9166, 1.2481, 1.4938, 1.8388, 2.1175, 2.4712, 2.7464,
+ 0.376, 0.4841, 0.635, 1.0082, 1.211, 1.4003, 1.8127, 2.0018, 2.5199, 2.7238,
+ 0.1988, 0.2824, 0.6553, 1.0337, 1.5413, 1.7369, 1.9751, 2.1751, 2.4372, 2.6265,
+ 0.2728, 0.4094, 0.7498, 1.0645, 1.3516, 1.5946, 1.991, 2.2172, 2.483, 2.6614,
+ 0.1657, 0.5327, 0.7281, 0.9966, 1.2385, 1.4629, 1.8119, 2.0973, 2.4469, 2.6979,
+ 0.1413, 0.2098, 0.354, 0.5492, 0.8486, 1.1288, 1.632, 1.9056, 2.2805, 2.5438,
+ 0.2856, 0.3666, 0.6259, 1.1424, 1.6605, 1.8197, 2.0147, 2.1986, 2.4121, 2.5919,
+ 0.2725, 0.4829, 0.765, 1.0119, 1.2977, 1.5488, 1.8755, 2.1155, 2.4383, 2.6377,
+ 0.2736, 0.3804, 0.5537, 1.0258, 1.2269, 1.4186, 1.9718, 2.1468, 2.5665, 2.7689,
+ 0.2341, 0.5953, 1.103, 1.4549, 1.7361, 1.9758, 2.2126, 2.4213, 2.6405, 2.8181,
+ 0.2273, 0.4638, 0.6228, 0.85, 1.1016, 1.2823, 1.7094, 1.9523, 2.2669, 2.7029,
+ 0.2438, 0.3798, 0.7299, 0.96, 1.3765, 1.6104, 1.8644, 2.1161, 2.5073, 2.7137,
+ 0.1551, 0.4869, 0.8676, 1.2274, 1.5069, 1.8857, 2.1868, 2.4411, 2.7106, 2.8767,
+ 0.2746, 0.5454, 0.7589, 0.9458, 1.1597, 1.3349, 1.6653, 2.1142, 2.4356, 2.6239,
+ 0.1793, 0.2646, 0.4344, 0.7482, 1.1502, 1.3733, 1.8558, 2.0817, 2.3248, 2.5171,
+ 0.2698, 0.4202, 0.5765, 0.8301, 1.0073, 1.2101, 1.9714, 2.2051, 2.5138, 2.7395,
+ 0.1929, 0.3091, 0.446, 0.6266, 1.1805, 1.3672, 1.599, 2.1514, 2.4729, 2.6468,
+ 0.1901, 0.3047, 0.4607, 1.1019, 1.3168, 1.5343, 1.9234, 2.1365, 2.5924, 2.7807,
+ 0.3139, 0.5009, 0.67, 0.8268, 1.0117, 1.181, 1.6539, 2.1984, 2.4828, 2.6576,
+ 0.1403, 0.2173, 0.4117, 0.7302, 1.0038, 1.2732, 1.7392, 2.0337, 2.3809, 2.7386,
+ 0.4166, 0.5101, 0.7449, 1.1663, 1.3492, 1.5543, 1.9, 2.0941, 2.4588, 2.6365,
+ 0.3342, 0.4335, 0.616, 0.8559, 1.0112, 1.2097, 1.4029, 1.6361, 2.4129, 2.6324,
+ 0.4543, 0.6159, 0.7932, 0.9843, 1.2562, 1.4308, 1.7116, 1.9919, 2.2671, 2.4631,
+ 0.2153, 0.3609, 0.5302, 0.7089, 0.8756, 1.0376, 1.6496, 2.2826, 2.568, 2.7441,
+ 0.438, 0.6439, 0.8282, 1.0651, 1.365, 1.5829, 1.8838, 2.1005, 2.4006, 2.5771,
+ 0.2523, 0.3636, 0.5879, 1.1628, 1.3542, 1.6756, 2.0488, 2.2543, 2.6093, 2.7953,
+ 0.4179, 0.5426, 0.7065, 0.8996, 1.0684, 1.3146, 1.9705, 2.2021, 2.5051, 2.7061,
+ 0.1659, 0.286, 0.6693, 0.9229, 1.3959, 1.6544, 1.9709, 2.2257, 2.5236, 2.746,
+ 0.254, 0.4356, 0.5946, 0.7627, 1.2274, 1.4222, 1.6573, 1.9601, 2.2514, 2.4711,
+ 0.1633, 0.2337, 0.3698, 0.5421, 1.1757, 1.5916, 2.1561, 2.3371, 2.5534, 2.7737,
+ 0.1953, 0.273, 0.4521, 1.2005, 1.7062, 1.8627, 2.1313, 2.3266, 2.5906, 2.7667,
+ 0.3053, 0.4054, 0.5651, 0.747, 0.891, 1.172, 1.8864, 2.1074, 2.3705, 2.5744,
+ 0.1761, 0.3033, 0.6501, 0.8268, 1.0369, 1.2687, 1.8534, 2.1889, 2.5074, 2.7339,
+ 0.2265, 0.399, 1.1359, 1.4137, 1.6839, 1.8912, 2.0948, 2.3042, 2.5489, 2.7234,
+ 0.3326, 0.54, 0.8711, 1.0948, 1.3752, 1.6155, 1.936, 2.1537, 2.4451, 2.6133,
+ 0.2162, 0.3522, 0.5309, 0.747, 0.9677, 1.1747, 1.5056, 1.7942, 2.1615, 2.48,
+ 0.1872, 0.2761, 0.4053, 0.7469, 1.5858, 1.8945, 2.1198, 2.3197, 2.5819, 2.7758,
+ 0.5381, 0.8651, 1.2695, 1.4918, 1.7774, 1.9696, 2.1865, 2.3687, 2.5739, 2.7158,
+ 0.2663, 0.3422, 0.6098, 1.212, 1.4516, 1.6092, 1.8506, 2.0376, 2.2929, 2.5088,
+ 0.1904, 0.3051, 0.5663, 0.7391, 1.1589, 1.5705, 1.8756, 2.1653, 2.5518, 2.7693,
+ 0.1543, 0.3519, 0.6976, 1.0664, 1.3696, 1.7817, 2.1308, 2.4259, 2.707, 2.8753,
+ 0.3304, 0.4283, 0.5942, 0.7425, 0.8906, 1.4067, 2.0676, 2.246, 2.5394, 2.7006,
+ 0.208, 0.3215, 0.6278, 0.7882, 1.3123, 1.5592, 1.8048, 2.0831, 2.4303, 2.6266,
+ 0.1188, 0.2481, 0.827, 1.242, 1.5824, 1.8976, 2.1816, 2.4248, 2.6645, 2.8459,
+ 0.0635, 0.1528, 0.5973, 0.9377, 1.2653, 1.5465, 1.8818, 2.1681, 2.5089, 2.7924,
+ 0.3249, 0.5179, 0.9143, 1.2973, 1.4966, 1.755, 2.0715, 2.3166, 2.65, 2.8305,
+ 0.1918, 0.3107, 0.4506, 0.6994, 1.3463, 1.5348, 1.8447, 2.1903, 2.448, 2.6877,
+ 0.3405, 0.4644, 0.7232, 0.9199, 1.2611, 1.5175, 1.8446, 2.0652, 2.3915, 2.5781,
+ 0.3289, 0.5152, 0.6602, 1.0213, 1.1886, 1.5496, 1.9553, 2.1883, 2.5394, 2.7362,
+ 0.3, 0.4097, 0.8372, 1.0793, 1.3095, 1.5684, 1.8746, 2.0783, 2.3643, 2.549,
+ 0.2421, 0.328, 0.5288, 0.9261, 1.6911, 1.8959, 2.1013, 2.2823, 2.5238, 2.696,
+ 0.107, 0.3131, 0.6226, 0.8881, 1.1808, 1.4867, 1.8146, 2.1088, 2.4594, 2.7186,
+ 0.44, 0.5533, 0.7025, 0.9206, 1.4089, 1.582, 1.808, 2.0832, 2.3577, 2.53,
+ 0.225, 0.3434, 0.4808, 0.6721, 0.8198, 1.1446, 2.0201, 2.2625, 2.552, 2.7604,
+ 0.1671, 0.2551, 0.4603, 0.6777, 0.9661, 1.5579, 1.8659, 2.1196, 2.4425, 2.6551,
+ 0.391, 0.5877, 1.0287, 1.3547, 1.6899, 1.9166, 2.1451, 2.3337, 2.5519, 2.7071,
+ 0.1435, 0.2165, 0.3968, 0.8376, 1.2572, 1.5298, 1.8791, 2.1352, 2.4636, 2.7011,
+ 0.1756, 0.2799, 0.412, 0.5808, 0.7573, 1.334, 1.8235, 2.12, 2.4993, 2.7365,
+ 0.1332, 0.2174, 0.4716, 0.9483, 1.2723, 1.6028, 1.9272, 2.219, 2.5588, 2.799,
+ 0.2122, 0.3143, 0.7042, 0.8849, 1.1312, 1.3711, 1.6832, 1.9633, 2.2685, 2.5156,
+ 0.2089, 0.3339, 0.4817, 0.8526, 1.0657, 1.2741, 1.5747, 1.8, 2.486, 2.6843,
+ 0.1636, 0.2617, 0.44, 0.7357, 1.0355, 1.2638, 1.5672, 1.8504, 2.1904, 2.6588,
+ 0.1945, 0.2934, 0.4869, 0.8567, 1.1262, 1.3604, 1.6898, 1.9143, 2.1475, 2.3503,
+ 0.1606, 0.2442, 0.3931, 0.9237, 1.5811, 1.7529, 2.0133, 2.2272, 2.525, 2.7265,
+ 0.4866, 0.7045, 1.0593, 1.2795, 1.5326, 1.8221, 2.1461, 2.3665, 2.6041, 2.7599,
+ 0.4012, 0.4911, 0.7103, 0.8585, 1.0495, 1.7244, 2.0116, 2.2041, 2.5189, 2.6643,
+ 0.4365, 0.6694, 0.8644, 1.133, 1.451, 1.7627, 2.1032, 2.369, 2.628, 2.8306,
+ 0.2072, 0.4018, 0.6227, 0.8913, 1.3038, 1.6056, 1.9704, 2.2816, 2.6135, 2.8182,
+ 0.3302, 0.4968, 0.8713, 1.0761, 1.2576, 1.4654, 1.8152, 2.14, 2.5404, 2.7493,
+ 0.1385, 0.2292, 0.353, 0.6006, 1.4699, 1.6571, 1.9438, 2.1663, 2.5027, 2.7308,
+ 0.1894, 0.2915, 0.4345, 0.6341, 1.0024, 1.1896, 1.6896, 2.0966, 2.4086, 2.6768,
+ 0.3841, 0.5197, 0.8889, 1.148, 1.4383, 1.6285, 1.8642, 2.0669, 2.3466, 2.5325,
+ 0.2008, 0.3097, 0.4664, 0.6638, 1.2798, 1.494, 1.727, 2.0264, 2.2915, 2.475,
+ 0.1864, 0.2857, 0.4481, 1.1025, 1.3096, 1.5035, 1.7614, 1.9891, 2.4255, 2.6031,
+ 0.4081, 0.6134, 0.9514, 1.1818, 1.3943, 1.6361, 1.9891, 2.2395, 2.5547, 2.7287,
+ 0.2964, 0.3876, 0.945, 1.2247, 1.3906, 1.5882, 1.8241, 2.0589, 2.4188, 2.5871,
+ 0.3127, 0.4038, 0.6168, 1.081, 1.3067, 1.4759, 1.8817, 2.0781, 2.3394, 2.5539,
+ 0.2066, 0.3059, 0.4989, 0.7132, 0.9066, 1.446, 1.7584, 1.9755, 2.221, 2.4741,
+ 0.2634, 0.3956, 0.5667, 0.8777, 1.0517, 1.6029, 2.059, 2.2607, 2.6064, 2.7647,
+ 0.4331, 0.5315, 0.7764, 1.0444, 1.2269, 1.4311, 1.7093, 1.9187, 2.4337, 2.6149,
+ 0.2161, 0.4429, 0.6851, 0.8336, 1.1037, 1.2966, 1.5283, 2.0299, 2.3407, 2.5384,
+ 0.2814, 0.3637, 0.5416, 0.9475, 1.5137, 1.6945, 1.8892, 2.1017, 2.319, 2.5007,
+ 0.4454, 0.6883, 1.1402, 1.4098, 1.7435, 2.0014, 2.2521, 2.4457, 2.6495, 2.7985,
+ 0.1641, 0.4083, 0.6426, 1.0592, 1.3258, 1.5754, 1.8666, 2.1381, 2.4572, 2.7177,
+ 0.3391, 0.4607, 0.6072, 0.8463, 1.4207, 1.6062, 1.8303, 2.0887, 2.3615, 2.5348,
+ 0.2414, 0.3396, 0.51, 0.747, 1.3329, 1.8618, 2.0751, 2.2564, 2.5147, 2.6874,
+ 0.1694, 0.2535, 0.4156, 0.8302, 1.2853, 1.5838, 2.0907, 2.3085, 2.5929, 2.7951,
+ 0.2047, 0.3652, 0.65, 0.8068, 1.0178, 1.1865, 1.4889, 2.0671, 2.5966, 2.7634,
+ 0.2425, 0.3247, 0.602, 1.2226, 1.4272, 1.5996, 1.8377, 2.0413, 2.5333, 2.7021,
+ 0.3842, 0.503, 0.6541, 0.8771, 1.0576, 1.2612, 1.6744, 1.8735, 2.4781, 2.6803,
+ 0.2042, 0.328, 0.7283, 0.8985, 1.1444, 1.3299, 1.6032, 2.1539, 2.4739, 2.6547,
+ 0.1268, 0.1924, 0.3208, 0.5153, 1.1304, 1.4443, 1.8047, 2.0552, 2.4385, 2.7572,
+ 0.2713, 0.3659, 0.5395, 1.0705, 1.4228, 1.5836, 1.9763, 2.1641, 2.4459, 2.6301,
+ 0.3047, 0.4043, 0.5727, 0.7368, 0.8997, 1.3242, 1.6473, 1.8879, 2.433, 2.6295,
+ 0.1224, 0.3948, 0.6903, 0.9199, 1.2852, 1.5516, 1.8645, 2.1231, 2.4657, 2.7044,
+ 0.2157, 0.3281, 0.5036, 0.9272, 1.0975, 1.5285, 1.808, 2.0569, 2.5448, 2.7221,
+ 0.167, 0.249, 0.3696, 0.5921, 1.3019, 1.8398, 2.2165, 2.3725, 2.6142, 2.8338,
+ 0.3899, 0.5573, 0.81, 1.0732, 1.3966, 1.6598, 2.0001, 2.2517, 2.5548, 2.7403,
+ 0.4905, 0.6064, 0.8222, 0.9966, 1.1912, 1.5714, 1.9628, 2.1727, 2.53, 2.7055,
+ 0.1309, 0.2342, 0.6232, 0.8795, 1.1283, 1.3655, 1.7371, 2.0251, 2.3992, 2.6885,
+ 0.1805, 0.2672, 0.4297, 1.244, 1.4967, 1.6796, 1.9592, 2.1784, 2.5439, 2.7289,
+ 0.228, 0.5429, 0.6967, 0.8732, 1.4074, 1.6074, 1.9516, 2.2124, 2.5486, 2.7722,
+ 0.2339, 0.3379, 0.4924, 0.9061, 1.3074, 1.4719, 1.8884, 2.111, 2.3618, 2.5545,
+ 0.1384, 0.2291, 0.5127, 1.045, 1.4017, 1.7884, 2.1134, 2.3664, 2.6588, 2.8435,
+ 0.2196, 0.6359, 0.91, 1.2007, 1.4589, 1.7053, 2.0128, 2.2722, 2.552, 2.7643,
+ 0.1698, 0.2615, 0.381, 0.5706, 1.4297, 1.8686, 2.0728, 2.2559, 2.486, 2.6701,
+ 0.1445, 0.2158, 0.3658, 0.5451, 0.9389, 1.3669, 1.79, 2.0846, 2.3924, 2.7161,
+ 0.2789, 0.3816, 0.5277, 0.8487, 1.3751, 1.5461, 1.7832, 2.0264, 2.2695, 2.4665,
+ 0.1733, 0.3023, 0.9216, 1.2368, 1.4776, 1.7229, 1.9952, 2.2471, 2.539, 2.7265,
+ 0.3374, 0.5033, 1.0951, 1.3262, 1.5284, 1.7336, 1.9733, 2.2009, 2.4992, 2.6751,
+ 0.1293, 0.2743, 0.7533, 1.0166, 1.2416, 1.4444, 1.7962, 2.0851, 2.477, 2.7204,
+ 0.3106, 0.4176, 0.6358, 0.9434, 1.1419, 1.3458, 1.9638, 2.1678, 2.439, 2.6235,
+ 0.4533, 0.576, 0.7392, 0.9136, 1.0829, 1.2759, 1.7903, 2.036, 2.3124, 2.5325,
+ 0.3702, 0.5218, 0.6977, 0.8776, 1.1096, 1.2855, 1.5612, 1.948, 2.217, 2.4361,
+ 0.1637, 0.2647, 0.4185, 0.6666, 1.1584, 1.327, 1.7829, 1.9821, 2.4361, 2.7094,
+ 0.1769, 0.2767, 0.3942, 0.5746, 1.3595, 1.711, 1.9176, 2.1405, 2.3722, 2.5705,
+ 0.2712, 0.382, 0.6524, 0.8317, 1.0341, 1.3972, 1.7312, 1.9918, 2.3854, 2.5886,
+ 0.1003, 0.2046, 0.7261, 1.1004, 1.4057, 1.6697, 1.9903, 2.2603, 2.5813, 2.8009,
+ 0.2534, 0.3752, 0.7192, 0.9323, 1.3698, 1.5955, 1.8653, 2.0656, 2.3368, 2.534,
+ 0.3589, 0.4508, 0.6631, 1.0521, 1.5065, 1.6697, 1.8929, 2.1074, 2.3466, 2.5242,
+ 0.1955, 0.2862, 0.6111, 0.8053, 1.0501, 1.5218, 1.7996, 2.0303, 2.3788, 2.5973,
+ 0.2982, 0.4033, 0.566, 0.8924, 1.1933, 1.3465, 1.7895, 2.0173, 2.2606, 2.5069,
+ 0.3356, 0.4711, 0.631, 0.8491, 1.0049, 1.4364, 1.8176, 2.0292, 2.571, 2.7525,
+ 0.2016, 0.2912, 0.4363, 0.98, 1.4897, 1.6494, 1.8862, 2.0819, 2.3636, 2.6091,
+ 0.4549, 0.6491, 0.845, 1.0209, 1.1747, 1.3745, 1.8824, 2.113, 2.376, 2.5768,
+ 0.251, 0.3524, 0.5171, 0.8931, 1.4094, 1.571, 1.8536, 2.0478, 2.4766, 2.732,
+ 0.1576, 0.2547, 0.3891, 0.8551, 1.4282, 1.588, 1.8583, 2.0521, 2.5359, 2.734,
+ 0.3481, 0.4382, 0.772, 1.1289, 1.3203, 1.5019, 1.7665, 1.957, 2.2231, 2.4465,
+ 0.3116, 0.4068, 0.6991, 0.8894, 1.0912, 1.5356, 1.8084, 2.0006, 2.2323, 2.4367,
+ 0.2706, 0.4033, 0.8272, 1.0851, 1.482, 1.6927, 1.9292, 2.1267, 2.4049, 2.5857,
+ 0.2745, 0.355, 0.8663, 1.3742, 1.5545, 1.7324, 1.9664, 2.1538, 2.4581, 2.6245,
+ 0.1736, 0.2553, 0.5357, 0.9009, 1.1888, 1.5132, 1.8579, 2.1181, 2.4273, 2.6847,
+ 0.3026, 0.4148, 0.9044, 1.1695, 1.3657, 1.7036, 1.9891, 2.2226, 2.5441, 2.7085,
+ 0.3998, 0.5108, 0.7205, 0.9848, 1.1828, 1.3716, 1.7154, 1.9191, 2.1875, 2.4257,
+ 0.2141, 0.3095, 0.7428, 1.0426, 1.2851, 1.5571, 1.7901, 1.9804, 2.2462, 2.5265,
+ 0.1574, 0.229, 0.3869, 0.5735, 1.0925, 1.3383, 1.6598, 1.9364, 2.2095, 2.4195
+};
+ /* codebook/lspvqanssi2.txt */
+static const float codes1[] = {
+ 0.012, 0.0022, 0.0068, -0.0112, -0.0508, -0.049, 0.2249, 0.1476, 0.0133, -0.0379,
+ 0.0598, 0.0477, 0.038, 0.066, 0.0517, 0.015, 0.0617, 0.0081, -0.0768, -0.1007,
+ -0.0087, -0.044, 0.0873, 0.0882, 0.0391, -0.006, 0.11, 0.0569, -0.0241, -0.0468,
+ 0.0146, -0.0005, 0.0322, -0.065, -0.0778, -0.078, -0.0255, -0.0527, -0.0301, -0.0401,
+ -0.024, -0.056, -0.0374, 0.0274, 0.0484, -0.0227, 0.0328, 0.1135, 0.0117, -0.03,
+ -0.0324, -0.0574, 0.0302, 0.0137, -0.0603, -0.1194, -0.0105, -0.0513, 0.0698, 0.0538,
+ 0.0635, 0.0382, 0.0531, 0.0897, 0.0495, 0.0039, -0.0421, -0.0919, 0.0407, 0.0167,
+ 0.0954, 0.0854, 0.036, -0.0025, -0.0252, -0.0528, -0.0435, -0.0561, -0.0405, -0.0432,
+ 0.011, -0.001, -0.0433, -0.0167, 0.1402, 0.0738, 0.0423, -0.0024, -0.092, -0.1099,
+ 0.0179, 0.0184, -0.0041, -0.064, 0.1004, 0.0608, -0.0023, -0.0357, 0.1509, 0.1262,
+ -0.0145, -0.024, -0.0595, -0.1063, 0.0597, -0.004, -0.0886, 0.1184, 0.038, 0.0126,
+ -0.0072, 0.0172, 0.0076, 0.0288, 0.081, 0.0278, 0.0709, 0.0051, 0.0214, -0.0301,
+ 0.0127, -0.0126, -0.0434, 0.161, 0.1178, 0.0704, 0.0257, -0.0073, -0.0425, -0.061,
+ -0.0165, -0.0369, -0.0785, 0.1007, 0.0309, -0.0651, 0.0142, -0.0614, 0.0426, 0.0289,
+ -0.0374, -0.0712, 0.0049, -0.0382, 0.0472, 0.0095, -0.0268, -0.0747, -0.0457, -0.0758,
+ -0.0211, -0.0432, -0.0547, -0.0446, -0.1078, 0.009, -0.0565, -0.1298, 0.0721, 0.0351,
+ -0.0014, -0.0072, -0.0283, -0.0324, -0.0208, -0.0703, 0.0979, 0.0865, -0.0007, 0.1881,
+ -0.0077, -0.0302, 0.1231, 0.0905, 0.0786, 0.0432, -0.0286, -0.0661, -0.0055, -0.0275,
+ 0.001, 0.0043, 0.0044, 0.038, -0.1201, -0.0098, -0.0166, 0.0105, 0.0153, 0.0134,
+ 0.0843, 0.0636, 0.0416, -0.0004, -0.057, -0.0592, 0.1158, 0.059, 0.0126, 0.0034,
+ 0.0346, 0.029, -0.0037, -0.0026, -0.0457, 0.1824, 0.1469, 0.087, 0.0291, -0.0074,
+ 0.0066, 0.0682, -0.0148, 0.0287, 0.0095, -0.0563, 0.1296, 0.0426, 0.1215, 0.0886,
+ -0.0132, -0.0399, 0.096, 0.0474, 0.014, 0.0306, -0.0192, -0.0703, -0.1559, -0.1556,
+ -0.06, 0.0482, 0.1257, 0.0521, 0.0229, -0.0031, 0.0817, 0.0571, -0.0138, -0.0277,
+ 0.0013, -0.0103, -0.047, -0.0687, -0.1444, 0.0181, 0.135, 0.0559, -0.0177, -0.0598,
+ -0.0215, -0.0318, -0.0689, -0.0268, 0.0917, 0.0307, 0.0135, -0.0184, -0.0857, 0.1231,
+ 0.0137, -0.0152, 0.0199, -0.0291, -0.0685, 0.0438, -0.1137, 0.0231, -0.0632, -0.0802,
+ -0.0011, 0.0314, 0.0535, -0.0135, -0.0291, -0.0579, -0.1049, 0.0288, -0.0628, 0.1355,
+ -0.0901, 0.0041, -0.017, 0.0351, 0.0144, -0.0505, 0.0396, 0.0638, -0.0145, 0.0141,
+ -0.04, -0.0603, -0.0714, 0.0329, -0.0049, -0.0529, -0.1251, 0.0022, -0.0449, -0.0778,
+ 0.0247, 0.0296, 0.0239, 0.0122, -0.0348, -0.1224, -0.0033, 0.1237, -0.0016, -0.0436,
+ 0.0246, 0.005, 0.0322, 0.0818, 0.0203, 0.0846, 0.0022, 0.0876, 0.0149, -0.0184,
+ -0.0204, -0.0228, 0.0365, -0.0164, 0.1087, 0.0374, -0.055, 0.033, -0.0582, -0.0736,
+ -0.0305, -0.0485, -0.0572, 0.0275, -0.0271, -0.0436, 0.1217, 0.07, 0.1253, 0.099,
+ -0.0079, -0.0204, -0.0325, 0.0491, 0.0158, -0.0365, -0.1309, -0.1812, 0.1428, 0.1148,
+ 0.068, 0.0547, 0.0309, 0.0079, -0.0332, 0.0391, -0.0287, 0.1258, 0.1123, 0.1016,
+ -0.0264, -0.0409, -0.0538, -0.0192, -0.0393, -0.0713, -0.0618, -0.1078, -0.185, 0.0532,
+ 0.0081, -0.0115, -0.009, 0.1201, -0.0413, -0.0995, 0.0445, -0.0032, -0.0286, -0.0497,
+ -0.0023, -0.0184, -0.0358, 0.1279, 0.0847, 0.053, 0.023, -0.0212, 0.1245, 0.0965,
+ 0.0111, 0.1038, 0.0597, 0.0413, 0.0533, 0.0011, 0.0031, 0.0705, 0.0242, 0.0198,
+ 0.002, -0.0071, -0.0262, -0.0496, -0.075, -0.1273, -0.1785, 0.0606, -0.0223, -0.0583,
+ -0.0202, 0.0669, 0.0081, 0.0335, -0.0218, -0.1073, -0.0146, -0.0673, 0.049, 0.021,
+ -0.0108, -0.023, -0.0614, -0.0986, 0.0629, 0.0006, 0.1496, 0.1099, 0.0316, 0.0098,
+ -0.0368, -0.0685, 0.0138, -0.0213, -0.0009, 0.0344, -0.0249, 0.0311, 0.0803, 0.0759,
+ 0.0038, -0.0158, 0.0142, 0.0254, 0.097, 0.0021, -0.1029, 0.0006, 0.0576, 0.0261,
+ -0.0083, 0.0698, 0.0406, -0.0348, 0.02, 0.0833, 0.0186, -0.0145, -0.0725, -0.0872,
+ -0.0506, -0.0673, 0.0776, -0.0172, -0.0444, -0.0531, -0.0799, 0.0005, -0.0359, -0.0446,
+ 0.0368, 0.0376, -0.0407, -0.019, 0.0987, 0.0212, -0.0349, -0.0951, -0.0084, -0.0342,
+ -0.0309, -0.0561, 0.095, -0.0125, -0.1028, -0.0133, 0.092, 0.0965, 0.0668, 0.0409,
+ -0.0898, 0.0036, -0.0353, -0.0024, -0.0365, -0.0259, -0.0485, -0.0843, -0.0063, -0.0167,
+ -0.0255, -0.0407, -0.0456, -0.0931, -0.0892, -0.0293, -0.051, 0.0183, -0.0104, 0.0472,
+ -0.0172, -0.0399, -0.0731, 0.0546, 0.032, -0.0283, 0.0415, -0.0107, -0.1237, -0.1102,
+ 0.021, 0.0294, -0.0038, -0.009, -0.0551, -0.0922, 0.0261, -0.0334, -0.1181, -0.1536,
+ 0.0092, 0.0032, -0.0162, 0.0398, 0.0205, 0.1266, -0.0107, -0.0858, 0.0392, 0.0032,
+ -0.0038, -0.0269, -0.0737, 0.1138, 0.0263, -0.0031, -0.1188, 0.1621, 0.0831, 0.0526,
+ 0.0023, -0.0149, -0.0497, 0.0898, 0.0456, -0.0145, -0.0928, -0.1507, -0.0611, -0.0938,
+ 0.012, 0.0124, -0.0286, -0.1319, 0.0219, 0.0311, -0.0398, -0.0465, -0.0008, -0.0375,
+ 0.0138, 0.0023, 0.0024, 0.1072, 0.0531, 0.0006, 0.0292, -0.0115, -0.062, 0.165,
+ 0.007, -0.0251, 0.0715, 0.038, -0.0404, 0.123, 0.0629, 0.0096, 0.0973, 0.0641,
+ -0.0586, 0.0772, 0.0128, 0.106, 0.0715, 0.0374, -0.0074, -0.0365, -0.0543, -0.0489,
+ -0.0392, 0.0871, -0.0069, -0.1084, 0.0264, -0.0495, 0.0396, 0.0005, -0.0293, -0.024,
+ -0.0327, 0.0605, 0.0662, 0.01, -0.0007, -0.0525, -0.0812, -0.0686, -0.0873, -0.083,
+ 0.0119, 0.0058, 0.003, -0.0307, 0.065, 0.0175, -0.0741, -0.15, -0.1947, 0.0881,
+ 0.0572, 0.0411, 0.0152, -0.0127, -0.0589, -0.051, -0.0212, -0.0834, 0.1434, 0.1318,
+ 0.0518, 0.0417, -0.043, 0.0963, -0.0014, 0.0173, 0.0234, -0.0273, 0.0359, -0.0118,
+ 0.0652, 0.0587, 0.0013, -0.07, 0.1262, 0.0975, 0.068, 0.0598, 0.0048, -0.0305,
+ -0.0185, -0.044, 0.1178, 0.0656, 0.0052, -0.0534, -0.1151, 0.1116, 0.0659, 0.0344,
+ 0.0788, 0.0577, 0.0452, 0.0283, -0.0278, 0.0911, 0.028, -0.0254, 0.0029, -0.0361,
+ -0.0165, -0.0322, -0.0526, -0.1057, 0.0927, 0.0293, -0.1026, -0.1671, 0.047, 0.0355,
+ 0.01, 0.0001, -0.0221, -0.0775, -0.1109, -0.1416, 0.0884, 0.0441, 0.0632, 0.0409,
+ 0.0204, 0.0432, 0.0141, -0.0296, 0.1073, 0.058, 0.0383, 0.027, -0.0857, 0.1246,
+ 0.0488, 0.0231, 0.0648, -0.0179, 0.0747, 0.0156, -0.0384, -0.0733, -0.0732, -0.097,
+ 0.0005, -0.0199, -0.026, -0.0511, -0.111, 0.067, -0.0413, 0.1571, 0.0498, 0.0191,
+ 0.0037, -0.0085, -0.0796, 0.0086, -0.0852, 0.085, 0.0115, -0.0065, 0.1161, 0.0727,
+ 0.0023, 0.0483, 0.0285, -0.0642, -0.0477, 0.0175, 0.0346, 0.0452, 0.0655, 0.0284,
+ -0.0986, 0.0463, 0.0326, -0.0055, 0.0702, 0.0194, -0.0423, -0.0107, 0.0338, 0.0619,
+ 0.0126, -0.0138, -0.1115, 0.0159, -0.0331, 0.0217, -0.0376, -0.0407, -0.0222, -0.0503,
+ 0.0222, 0.0071, -0.049, 0.1017, 0.0551, -0.0164, 0.1578, 0.1059, 0.0025, -0.0107,
+ 0.0124, -0.009, 0.0322, 0.093, 0.0281, -0.0403, -0.0781, 0.0125, -0.067, -0.1058,
+ 0.0363, 0.0077, 0.1052, 0.0039, 0.0676, 0.0891, 0.0433, 0.0252, 0.0224, -0.0043,
+ -0.0045, -0.0194, -0.0193, -0.048, -0.064, -0.0695, -0.1597, -0.003, 0.1728, 0.1231,
+ 0.0297, 0.0025, 0.0619, -0.0347, -0.1171, 0.1043, 0.0868, 0.0191, -0.0739, -0.1075,
+ 0.0073, 0.0914, 0.0367, -0.0236, 0.0232, 0.0304, -0.0787, -0.1099, 0.046, 0.0082,
+ 0.0296, 0.0297, -0.0444, 0.0184, 0.0602, -0.0295, -0.0934, 0.0636, -0.0347, -0.0722,
+ -0.029, -0.0629, 0.0598, 0.0013, 0.0064, 0.1431, 0.092, 0.0468, -0.0311, -0.0614,
+ -0.0152, -0.0311, -0.05, -0.0672, -0.1257, -0.0134, -0.022, -0.0612, -0.1131, -0.1417,
+ 0.0371, 0.0153, -0.0817, -0.0007, 0.0837, 0.0481, 0.046, 0.0678, 0.0524, 0.0432,
+ 0.0126, -0.0069, -0.0092, -0.0693, -0.025, 0.151, 0.0098, -0.0683, -0.0566, -0.0769,
+ -0.0199, -0.0423, 0.0806, 0.0562, 0.0009, -0.0563, -0.1358, -0.1578, -0.0456, 0.0032,
+ 0.0091, 0.0101, -0.009, -0.0279, -0.0489, -0.1038, -0.0815, 0.2184, 0.1172, 0.0902,
+ -0.0024, -0.0135, 0.0392, 0.0028, 0.0792, 0.0404, 0.0867, 0.161, 0.0954, 0.0846,
+ -0.0004, -0.022, -0.0282, -0.1022, -0.0799, 0.1278, 0.0765, 0.0402, 0.085, 0.0611,
+ 0.0443, 0.032, -0.0384, -0.0964, 0.003, -0.0398, -0.073, -0.0052, -0.0267, 0.1209,
+ -0.0706, 0.1151, 0.0722, -0.0175, -0.0927, -0.0559, 0.0316, 0.0186, 0.0105, 0.0314,
+ -0.0145, -0.0263, -0.0564, 0.0248, -0.0181, -0.0817, -0.0938, 0.0366, -0.0315, 0.1253,
+ 0.0307, 0.0039, 0.129, 0.0402, -0.0439, -0.0384, 0.0044, -0.0177, -0.0172, -0.031,
+ 0.0447, 0.0298, 0.0287, 0.0273, -0.035, -0.0708, -0.1829, -0.0317, 0.0643, 0.0057,
+ -0.082, -0.0326, 0.0209, -0.0711, 0.0084, 0.0111, 0.0426, 0.0262, -0.0061, 0.0005,
+ 0.0545, 0.0377, -0.0417, -0.0625, 0.0114, -0.0405, 0.0573, 0.0191, -0.0263, -0.0472,
+ -0.0053, -0.0049, -0.0255, -0.0578, -0.0237, -0.0721, -0.1487, -0.1636, 0.0046, -0.0355,
+ 0.0309, 0.0107, 0.0163, 0.0132, -0.0536, -0.0009, -0.0706, -0.135, -0.0514, -0.096,
+ 0.0306, 0.0003, 0.0494, 0.0701, 0.0027, -0.0458, 0.078, 0.0327, 0.0937, 0.0605,
+ -0.0017, -0.0275, 0.0797, -0.0268, -0.1014, 0.0593, -0.0528, -0.1103, 0.0682, 0.0322,
+ -0.0507, -0.0806, -0.0646, -0.0052, -0.0576, 0.0451, 0.0489, 0.015, 0.0029, -0.0189,
+ 0.027, 0.0143, -0.0375, -0.0071, -0.0607, -0.1157, -0.0345, -0.1115, 0.0201, -0.0104,
+ -0.0807, -0.1088, 0.0845, 0.072, 0.0441, 0.0301, 0.0043, 0.0052, 0.0016, 0.0201,
+ -0.029, -0.0532, 0.0036, -0.0201, -0.0723, -0.1321, 0.0867, 0.0479, -0.0556, -0.085,
+ -0.0271, 0.0126, 0.1283, 0.0533, -0.003, -0.0352, -0.0326, -0.0553, 0.1402, 0.1121,
+ -0.0358, -0.0518, -0.108, 0.0134, 0.095, 0.0384, -0.004, -0.0254, 0.0026, -0.0217,
+ -0.0152, -0.0375, -0.0827, 0.0916, 0.0188, 0.1306, 0.0983, 0.0606, 0.0381, 0.008,
+ -0.0107, -0.0269, -0.0573, -0.1189, 0.0258, 0.1009, 0.0565, 0.027, -0.0557, -0.0778,
+ -0.0193, -0.0242, -0.0784, -0.0816, 0.0287, -0.0484, 0.0292, -0.0414, 0.1124, 0.0767,
+ 0.0177, -0.0148, 0.0472, -0.0808, 0.0623, -0.0636, 0.075, -0.0107, 0.0673, 0.0425,
+ -0.022, 0.0577, -0.0769, -0.0247, -0.0321, 0.0341, -0.0108, 0.0109, -0.0142, 0.0122,
+ 0.0194, 0.0248, -0.0096, -0.0205, -0.046, -0.116, 0.0492, -0.0188, -0.1535, 0.0816,
+ 0.0301, -0.0286, -0.0077, -0.0117, -0.0036, -0.0026, 0.0133, -0.0032, 0.0007, -0.016,
+ 0.0115, -0.0111, 0.0246, -0.0639, 0.0325, -0.0313, 0.0808, 0.0435, -0.0777, -0.1108,
+ -0.0079, -0.0334, -0.0144, -0.0539, 0.1564, 0.1175, 0.0549, 0.034, 0.0319, 0.0027,
+ -0.0155, -0.0275, -0.0739, -0.0932, 0.0108, -0.0698, 0.0036, -0.0213, -0.0486, -0.067,
+ -0.0234, -0.0567, 0.002, 0.0908, -0.0151, 0.046, -0.0175, -0.0523, 0.0098, -0.0237,
+ 0.0057, -0.0066, -0.0418, 0.0418, -0.0449, 0.1069, 0.0629, -0.0016, -0.1068, -0.1492,
+ -0.0791, 0.0403, -0.0009, 0.0285, -0.0065, 0.0963, 0.055, 0.0634, 0.0693, 0.0694,
+ -0.0068, -0.0197, -0.0919, 0.0071, -0.0551, -0.1173, 0.0926, 0.0413, 0.0127, -0.0158,
+ 0.054, 0.0389, -0.0195, -0.08, -0.1383, 0.044, -0.0139, -0.0405, 0.0147, -0.0183,
+ 0.038, 0.0248, 0.052, -0.0609, 0.0339, -0.007, -0.0974, 0.1182, 0.0221, -0.031,
+ 0.0043, 0.0046, -0.0274, -0.0502, 0.0326, -0.0143, -0.0586, -0.0866, -0.1673, -0.1624,
+ 0.0428, 0.0385, -0.0228, 0.0704, 0.0069, -0.0145, -0.0623, -0.0639, -0.1479, 0.0212,
+ -0.0078, -0.0297, 0.0025, -0.0239, -0.0793, 0.0896, 0.0315, -0.0546, -0.1309, 0.108
+};
+ /* codebook/lspvqanssi3.txt */
+static const float codes2[] = {
+ -0.0291, 0.0272, -0.0364, -0.0313, -0.0487, -0.0205, 0.0501, 0.0225, 0.0178, 0.008,
+ -0.0406, -0.0383, 0.0013, -0.0155, -0.0261, -0.0598, 0.0003, -0.0242, 0.0151, -0.014,
+ -0.0445, 0.0356, 0.018, -0.0272, -0.0018, -0.0177, -0.0703, 0.0471, 0.0128, -0.0068,
+ -0.0033, -0.0285, -0.056, -0.0186, -0.0499, -0.007, 0.0068, -0.0126, 0.0388, -0.0097,
+ -0.0071, -0.0114, -0.0308, -0.0094, -0.0541, -0.0272, -0.0756, 0.0477, -0.0234, 0.0678,
+ 0.0048, 0.0307, -0.0174, -0.0593, 0.0097, -0.0134, 0.0034, -0.0212, -0.0418, 0.0869,
+ -0.0189, 0.0165, -0.0269, 0.0744, 0.0344, -0.0177, -0.0603, 0.0212, -0.0104, 0.0345,
+ -0.013, -0.0352, -0.0086, -0.0257, -0.0286, 0.0409, 0.0656, 0.0106, -0.0598, 0.0252,
+ 0.0041, 0.0097, -0.0032, -0.0154, -0.0405, 0.067, -0.0164, 0.0451, 0.0774, 0.0504,
+ 0.001, -0.0091, -0.0345, 0.0511, 0.0016, 0.0011, 0.0684, 0.0167, 0.0601, 0.0512,
+ 0.0204, -0.0038, -0.0426, 0.0185, -0.0191, -0.063, 0.0295, -0.0153, -0.0559, 0.056,
+ -0.0461, -0.0041, 0.0515, 0.0219, 0.0322, 0.0093, 0.0044, 0.0106, -0.0329, -0.0521,
+ 0.0304, 0.0017, 0.0209, -0.0002, 0.0689, 0.0136, 0.0216, -0.0268, -0.0682, 0.0333,
+ -0.0175, -0.0425, 0.0153, -0.005, -0.0113, 0.0297, -0.0659, -0.0344, 0.0302, -0.0272,
+ -0.0217, -0.0362, 0.0426, 0.0233, -0.0393, 0.0052, 0.0138, 0.0657, 0.0427, 0.022,
+ -0.0039, -0.0011, -0.0002, -0.0453, -0.0835, 0.0144, -0.0268, -0.0589, -0.0185, 0.0133,
+ 0.0081, -0.0032, 0.0638, 0.0032, 0.006, 0.0002, -0.0303, -0.0823, 0.0124, -0.0308,
+ 0.0108, 0.0011, 0.0059, 0.0396, 0.0392, 0.0351, -0.0045, -0.0323, -0.0512, -0.0975,
+ -0.0144, -0.0306, -0.0302, -0.007, 0.0123, -0.0042, -0.0083, -0.0514, 0.012, 0.1116,
+ -0.0046, -0.0131, 0.0472, 0.0144, -0.0296, -0.0518, 0.0337, -0.0145, -0.0733, 0.0793,
+ -0.0064, -0.0162, -0.0327, -0.0711, 0.0108, -0.0131, 0.0025, -0.0254, -0.0277, -0.068,
+ -0.0306, 0.0055, 0.0272, -0.0189, -0.0173, 0.0221, 0.0773, 0.0043, 0.0458, -0.0169,
+ -0.0006, 0.0299, 0.0259, 0.0227, -0.053, -0.0596, -0.0271, -0.0091, 0.0181, -0.0233,
+ -0.0116, -0.0398, 0.0089, 0.0708, -0.0028, -0.0084, -0.0206, -0.0354, -0.0275, -0.0037,
+ 0.0259, -0.0064, -0.038, 0.0572, 0.0083, 0.0286, -0.0565, 0.0158, 0.0396, -0.0123,
+ 0.0552, 0.0331, -0.0052, -0.0346, -0.018, -0.0194, -0.0237, 0.0184, 0.0056, -0.0199,
+ 0.0143, 0.0131, -0.0166, 0.0196, 0.0154, 0.031, -0.0048, 0.0901, -0.0333, 0.0761,
+ 0.0118, -0.0107, 0.0099, 0.0078, 0.0002, -0.0716, -0.0233, 0.0793, 0.0516, 0.03,
+ 0.0204, 0.0243, 0.0192, 0.0181, 0.0001, -0.0243, -0.0764, -0.0622, -0.0324, 0.064,
+ 0.0132, 0.0016, -0.0187, -0.0425, 0.0627, 0.0094, -0.0786, 0.0304, 0.0294, -0.0146,
+ -0.0221, -0.0154, 0.0285, -0.0709, 0.0406, 0.0114, 0.0073, -0.0199, 0.0081, 0.0268,
+ 0.0227, 0.0055, 0.0163, -0.0447, 0.0246, 0.0795, 0.0239, 0.0211, -0.0145, -0.0576,
+ -0.0119, 0.0637, 0.0278, 0.0202, -0.0086, 0.0389, 0.032, -0.0049, -0.0272, -0.0274,
+ 0.004, -0.0211, 0.0426, 0.048, 0.0415, 0.0659, 0.0408, 0.0198, 0.0327, 0.0029,
+ 0.043, 0.0311, 0.0083, 0.0353, 0.025, 0.0143, 0.0106, -0.0305, 0.0633, 0.0227,
+ -0.0277, 0.0302, 0.0337, 0.0176, 0.0191, -0.0156, 0.0231, 0.0118, 0.0465, 0.0875,
+ 0.0221, 0.0146, 0.0147, -0.0211, -0.0317, -0.0179, -0.0049, -0.0297, -0.1078, -0.0413,
+ -0.0531, 0.018, -0.0066, 0.0365, -0.0033, 0.009, -0.0158, -0.0698, 0.0315, -0.0048,
+ 0.0289, 0.0053, 0.0082, 0.0077, -0.0664, 0.0474, 0.0407, -0.0096, 0.0028, -0.0526,
+ -0.0106, -0.0129, -0.0315, 0.0335, -0.0217, -0.0427, 0.0582, 0.0193, -0.0288, -0.0777,
+ -0.0003, -0.0141, -0.0102, 0.0007, -0.0077, -0.0517, -0.0909, 0.0128, -0.0349, -0.0769,
+ -0.0227, -0.0159, -0.0327, 0.0011, 0.0312, 0.01, -0.018, -0.0537, -0.0997, 0.0122,
+ 0.019, -0.0139, 0.0341, -0.0131, -0.0368, -0.0138, -0.0074, -0.0415, 0.0791, 0.0503,
+ 0.0182, 0.0027, 0.0032, -0.0325, -0.0309, -0.0898, 0.0509, -0.017, 0.0301, -0.0137,
+ 0.0233, 0.01, 0.0231, 0.073, 0.0212, -0.0299, 0.044, 0.0041, -0.0101, -0.0251,
+ 0.0074, -0.0033, -0.0285, -0.035, 0.0101, 0.0735, 0.0036, -0.0659, 0.0429, -0.0052,
+ 0.0148, -0.0035, -0.0233, 0.0079, -0.0142, -0.0402, -0.0358, -0.0985, -0.008, -0.0549,
+ 0.0203, 0.0057, -0.0604, 0.0098, 0.0402, 0.0151, 0.05, 0.0058, -0.0086, -0.0401,
+ 0.0056, -0.0381, 0.042, -0.0125, 0.0157, -0.0268, 0.0433, 0.0123, -0.0176, -0.0685,
+ 0.003, 0.0502, 0.0067, -0.0222, 0.0405, -0.0226, 0.002, -0.0401, -0.0026, -0.0521,
+ 0.0317, 0.0089, 0.062, 0.0251, 0.0066, 0.0089, -0.0565, 0.0414, 0.0005, -0.0365,
+ -0.0058, 0.0086, -0.0291, -0.0164, -0.0134, -0.049, -0.0427, -0.0451, 0.0869, 0.0334,
+ 0.0024, 0.0328, -0.0415, 0.0003, -0.0287, 0.0193, -0.0547, -0.0222, -0.0196, -0.0571,
+ -0.0271, -0.0397, -0.0431, -0.0043, 0.0332, 0.0093, 0.0082, 0.0585, 0.0282, 0.0004,
+ -0.0251, -0.0167, -0.0289, 0.0196, -0.0363, 0.085, 0.0028, 0.0319, -0.0202, -0.0512,
+ 0.0389, 0.0226, 0.0401, -0.0091, -0.0152, 0.0001, 0.0738, 0.0402, 0.0097, 0.031,
+ -0.0126, 0.013, -0.0046, -0.0216, 0.0298, -0.0344, 0.0713, 0.0547, -0.047, -0.0294,
+ 0.0125, 0.0044, -0.0028, 0.0209, -0.02, 0.0854, 0.0018, -0.0386, -0.0703, 0.0778,
+ -0.0036, -0.0347, 0.0309, -0.0184, 0.029, -0.0025, -0.0644, 0.0347, -0.0523, 0.0644,
+ 0.0064, 0.0295, -0.0017, 0.0282, 0.0176, 0.0027, 0.0246, 0.0967, 0.0401, -0.0231,
+ 0.0054, -0.0109, 0.0055, -0.0479, -0.049, -0.0136, -0.0245, 0.0839, 0.0026, -0.0493,
+ 0.0128, -0.005, -0.0219, -0.0621, 0.0313, 0.0019, 0.0696, 0.0459, 0.0574, 0.0299,
+ -0.0091, -0.029, -0.0068, 0.0276, 0.0645, -0.015, 0.0015, -0.0374, 0.0415, -0.0124,
+ -0.0171, 0.0177, -0.0138, 0.0034, 0.084, 0.0584, 0.0233, 0.01, 0.0122, 0.0047
+};
+ /* codebook/lspvqanssi4.txt */
+static const float codes3[] = {
+ 0.0221, -0.0035, -0.0032, -0.0177, -0.0327, 0.0518, -0.011, -0.015, -0.0136, -0.0327,
+ 0.0099, -0.0059, 0.0031, -0.0174, 0.0464, -0.024, 0.0251, -0.027, 0.0454, -0.0082,
+ -0.0029, 0.0025, -0.0267, -0.0318, -0.0157, 0.0173, 0.0253, 0.0063, -0.0481, 0.0419,
+ -0.0332, -0.0179, -0.0042, 0.0241, 0.0044, -0.0098, -0.0081, 0.0024, -0.0414, 0.0339,
+ -0.006, 0.0182, -0.0051, -0.0479, 0.0016, -0.0179, 0.0316, 0.0222, -0.0029, -0.0351,
+ 0.0074, 0.0015, 0.0337, -0.0082, -0.0008, 0.0129, 0.0001, 0.065, 0.0175, 0.0309,
+ -0.0212, -0.0261, 0.0196, -0.0309, 0.0093, -0.0272, 0.026, 0.0169, 0.0132, 0.0116,
+ -0.001, 0.0202, 0.0228, -0.0227, -0.0141, 0.0192, -0.0423, -0.0097, -0.0342, 0.0338,
+ -0.0149, -0.011, -0.0156, 0.029, 0.0028, 0.0123, -0.035, -0.0501, 0.0272, -0.0245,
+ -0.0005, -0.0194, 0.046, -0.0001, -0.028, 0.0216, -0.0028, -0.0162, 0.0177, -0.0254,
+ -0.0109, -0.0026, 0.0038, -0.015, -0.0421, -0.0422, 0.0164, -0.0436, 0.0054, -0.0098,
+ 0.0061, -0.0106, 0.0062, 0.0207, -0.0329, 0.0177, -0.0578, 0.0408, 0.0077, -0.026,
+ 0.0001, -0.0098, 0.0106, -0.0003, -0.0292, 0.0032, 0.056, 0.0311, -0.0282, -0.0445,
+ 0.0033, 0.0345, -0.0022, -0.0029, -0.0228, 0.0242, 0.0197, -0.0286, 0.0194, -0.0328,
+ 0.0094, -0.001, 0.0121, 0.0229, 0.0161, 0.0363, -0.0124, 0.0179, -0.0626, 0.002,
+ -0.007, -0.0272, -0.0171, -0.0249, -0.0039, 0.0254, 0.0317, -0.0324, 0.0276, -0.009,
+ -0.0002, 0.0057, -0.0204, 0.0512, -0.017, 0.0113, 0.0157, 0.0427, -0.0024, 0.0162,
+ -0.0064, -0.0144, 0.0216, 0.0053, -0.0361, 0.0287, 0.023, -0.0161, -0.0189, 0.0589,
+ 0.0091, -0.0059, -0.0308, 0.0171, -0.0137, -0.0033, -0.0505, -0.0155, -0.0527, 0.0133,
+ -0.0121, -0.0051, 0.0219, 0.0136, 0.0476, -0.009, -0.046, 0.0208, 0.0072, -0.0076,
+ 0.0098, -0.0328, -0.0211, 0.0054, -0.0146, -0.0263, 0.0248, 0.0045, -0.0183, 0.0301,
+ 0.0101, 0.0139, -0.0073, 0.0234, 0.0083, -0.0194, -0.0365, 0.0307, 0.058, 0.0153,
+ -0.0111, 0.0019, 0.0265, -0.015, 0.0311, 0.0362, 0.0244, -0.0213, -0.0224, -0.0299,
+ 0.0061, 0.0082, -0.0181, 0.0081, -0.0344, 0.0133, -0.0095, -0.0411, 0.0462, 0.0371,
+ 0.0089, -0.0157, 0.0179, -0.0256, -0.0118, -0.0302, -0.0329, 0.0212, -0.0463, -0.0162,
+ -0.0313, 0.0096, -0.004, 0.0186, 0.0248, -0.0126, 0.0472, -0.0079, 0.0115, -0.027,
+ 0.0055, 0.0044, 0.0172, 0.0079, -0.0089, -0.0202, -0.0233, -0.0397, -0.0305, -0.062,
+ -0.0282, -0.0104, -0.0071, -0.0242, -0.0255, 0.0204, -0.0187, -0.0103, -0.0227, -0.0424,
+ -0.0056, 0.0065, 0.0151, -0.0376, 0.0039, 0.0009, -0.0507, -0.004, 0.0393, -0.0201,
+ 0.0128, -0.0228, 0.0115, -0.0446, 0.0316, 0.0266, -0.0036, 0.0117, -0.0009, 0.0048,
+ -0.0088, 0.0226, 0.0125, 0.009, 0.0008, -0.0341, 0.0243, -0.0178, -0.0589, 0.0278,
+ 0.0151, 0.0021, -0.0349, -0.0365, -0.0098, -0.0179, -0.0212, -0.0313, 0.0109, -0.0164,
+ -0.0211, -0.0112, -0.0446, 0.0014, -0.0034, -0.0179, 0.011, 0.0176, 0.0286, 0.0045,
+ 0.0034, -0.0151, 0.038, 0.0331, -0.0034, -0.0439, 0.0145, 0.012, 0.0036, 0.0017,
+ -0.0348, 0.0192, 0.0167, 0.0069, -0.0266, -0.0085, -0.0076, 0.026, 0.0234, 0.0075,
+ -0.0237, 0.015, -0.0094, -0.0201, 0.0234, -0.0041, -0.016, -0.0549, -0.0021, 0.0239,
+ -0.0019, 0.0173, 0.0295, 0.0443, 0.0081, 0.0181, -0.0039, -0.027, 0.0155, 0.0107,
+ 0.0065, -0.0055, -0.0368, 0.0232, 0.037, 0.0367, 0.0046, -0.0167, 0.0047, 0.0173,
+ 0.0116, 0.0053, -0.0229, 0.0382, 0.016, -0.0453, 0.0057, -0.0267, 0.002, -0.0051,
+ -0.014, 0.0302, -0.0208, 0.0106, 0.0101, -0.0049, -0.0319, 0.0227, -0.0206, -0.0371,
+ -0.0007, -0.0109, -0.0053, 0.0078, 0.041, -0.0001, 0.0543, 0.0328, -0.0196, 0.0332,
+ -0.0043, -0.0028, -0.0246, 0.0285, -0.0248, 0.0153, 0.0303, -0.031, -0.0335, -0.0315,
+ -0.0417, 0.1029, 0.0377, 0.0069, 0.0012, 0.0065, 0.0007, -0.0144, -0.0083, 0.0004,
+ 0.0295, 0.0099, -0.0144, -0.0145, 0.0141, -0.0013, 0.0362, -0.0142, -0.0428, -0.0161,
+ -0.0095, -0.0206, 0.0116, 0.0132, 0.0164, 0.0158, 0.0012, -0.0024, 0.064, 0.0364,
+ 0.0005, -0.0022, -0.0165, -0.0057, 0.0263, 0.0339, 0.0014, 0.0541, 0.0164, -0.0411,
+ 0.0039, -0.0143, -0.0107, 0.0032, -0.016, -0.0502, 0.001, 0.0272, 0.0161, -0.05,
+ 0.0083, 0.0292, -0.0076, -0.0201, 0.0313, 0.0213, 0.012, 0.0087, 0.0285, 0.0332,
+ 0.017, 0.0018, 0.0001, 0.0205, 0.0106, -0.0064, -0.0082, -0.0083, -0.0082, 0.0886,
+ 0.0075, -0.0078, -0.0038, -0.0337, -0.0491, 0.0048, 0.0069, 0.03, 0.0369, 0.0088,
+ -0.0091, -0.0327, 0.0041, 0.0376, 0.017, 0.0154, 0.0126, 0.0153, -0.0024, -0.0353,
+ 0.0289, -0.008, 0.0063, 0.0274, -0.0061, 0.0208, 0.039, -0.006, 0.0294, -0.0088,
+ -0.0037, -0.0195, 0.0058, 0.0023, -0.0149, -0.036, -0.0587, -0.0248, 0.0288, 0.0203,
+ -0.0031, 0.0081, -0.0112, -0.0221, 0.0067, -0.0505, -0.0233, 0.0353, -0.0131, 0.0417,
+ 0.0243, 0.0231, -0.0013, 0.0049, -0.0423, -0.0245, -0.0029, 0.0184, -0.0162, -0.001,
+ 0.0045, 0.0101, -0.0042, 0.0014, -0.0133, -0.0321, 0.0642, 0.0153, 0.0377, 0.0277,
+ 0.0275, 0.0083, 0.0286, -0.0243, -0.0084, -0.0236, 0.0027, -0.0289, 0.0201, 0.0235,
+ 0.0281, 0.0078, 0.0038, 0.0069, 0.0302, 0.017, -0.0423, -0.034, 0.0104, -0.0181,
+ 0.0334, -0.0034, -0.0257, -0.0061, 0.014, -0.0099, -0.0195, 0.0529, 0.0019, 0.001,
+ -0.0114, 0.0012, -0.0038, -0.0016, -0.014, 0.0697, 0.0372, 0.0243, 0.0172, 0.0066,
+ 0.0192, 0.0149, 0.0285, 0.0077, 0.0246, -0.0135, 0.0145, 0.0317, -0.0074, -0.0438,
+ -0.0034, -0.0175, -0.0245, -0.0153, 0.0357, -0.0102, -0.0062, -0.0053, -0.0308, -0.0499,
+ 0.0025, -0.0253, 0.0148, 0.0031, 0.0189, -0.0023, -0.0085, -0.0596, -0.0337, 0.0175,
+ -0.0091, -0.0171, -0.0217, -0.0189, 0.0056, 0.0249, -0.0499, 0.0236, 0.0042, 0.0449
+};
+
+const struct lsp_codebook lsp_cbvqanssi[] = {
+ /* codebook/lspvqanssi1.txt */
+ {
+ 10,
+ 8,
+ 256,
+ codes0
+ },
+ /* codebook/lspvqanssi2.txt */
+ {
+ 10,
+ 7,
+ 128,
+ codes1
+ },
+ /* codebook/lspvqanssi3.txt */
+ {
+ 10,
+ 6,
+ 64,
+ codes2
+ },
+ /* codebook/lspvqanssi4.txt */
+ {
+ 10,
+ 6,
+ 64,
+ codes3
+ },
+ { 0, 0, 0, 0 }
+};
--- /dev/null
+<?xml version="1.0" encoding="utf-8"?>
+<Project DefaultTargets="Build" ToolsVersion="14.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+ <ItemGroup Label="ProjectConfigurations">
+ <ProjectConfiguration Include="Debug|Win32">
+ <Configuration>Debug</Configuration>
+ <Platform>Win32</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Debug|x64">
+ <Configuration>Debug</Configuration>
+ <Platform>x64</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Release|Win32">
+ <Configuration>Release</Configuration>
+ <Platform>Win32</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Release|x64">
+ <Configuration>Release</Configuration>
+ <Platform>x64</Platform>
+ </ProjectConfiguration>
+ </ItemGroup>
+ <PropertyGroup Label="Globals">
+ <ProjectName>libcodec2</ProjectName>
+ <RootNamespace>libcodec2</RootNamespace>
+ <Keyword>Win32Proj</Keyword>
+ <ProjectGuid>{19E934D6-1484-41C8-9305-78DC42FD61F2}</ProjectGuid>
+ </PropertyGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
+ <ConfigurationType>StaticLibrary</ConfigurationType>
+ <CharacterSet>Unicode</CharacterSet>
+ <WholeProgramOptimization>true</WholeProgramOptimization>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
+ <ConfigurationType>StaticLibrary</ConfigurationType>
+ <CharacterSet>Unicode</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
+ <ConfigurationType>StaticLibrary</ConfigurationType>
+ <CharacterSet>Unicode</CharacterSet>
+ <WholeProgramOptimization>true</WholeProgramOptimization>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
+ <ConfigurationType>StaticLibrary</ConfigurationType>
+ <CharacterSet>Unicode</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
+ <Import Project="$(SolutionDir)w32\libcodec2.props" />
+ <ImportGroup Label="ExtensionSettings">
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="$(SolutionDir)w32\extlib.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="$(SolutionDir)w32\extlib.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="$(SolutionDir)w32\extlib.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="$(SolutionDir)w32\extlib.props" />
+ </ImportGroup>
+ <PropertyGroup Label="UserMacros" />
+ <PropertyGroup>
+ <_ProjectFileVersion>10.0.30319.1</_ProjectFileVersion>
+ </PropertyGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+ <ClCompile>
+ <Optimization>Disabled</Optimization>
+ <PreprocessorDefinitions>WIN32;_DEBUG;_WINDOWS;_USRDLL;LIBlibcodec2_EXPORTS;_CRT_SECURE_NO_DEPRECATE;_CRT_NONSTDC_NO_DEPRECATE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+ <MinimalRebuild>true</MinimalRebuild>
+ <BasicRuntimeChecks>EnableFastChecks</BasicRuntimeChecks>
+ <RuntimeLibrary>MultiThreadedDebugDLL</RuntimeLibrary>
+ <WarningLevel>Level4</WarningLevel>
+ <DisableSpecificWarnings>4127;%(DisableSpecificWarnings)</DisableSpecificWarnings>
+ </ClCompile>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+ <ClCompile>
+ <PreprocessorDefinitions>WIN32;NDEBUG;_WINDOWS;_USRDLL;LIBlibcodec2_EXPORTS;_CRT_SECURE_NO_DEPRECATE;_CRT_NONSTDC_NO_DEPRECATE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+ <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
+ <WarningLevel>Level4</WarningLevel>
+ <DisableSpecificWarnings>4127;%(DisableSpecificWarnings)</DisableSpecificWarnings>
+ </ClCompile>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
+ <Midl>
+ <TargetEnvironment>X64</TargetEnvironment>
+ </Midl>
+ <ClCompile>
+ <Optimization>Disabled</Optimization>
+ <PreprocessorDefinitions>WIN32;_DEBUG;_WINDOWS;_USRDLL;LIBlibcodec2_EXPORTS;_CRT_SECURE_NO_DEPRECATE;_CRT_NONSTDC_NO_DEPRECATE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+ <MinimalRebuild>true</MinimalRebuild>
+ <BasicRuntimeChecks>EnableFastChecks</BasicRuntimeChecks>
+ <RuntimeLibrary>MultiThreadedDebugDLL</RuntimeLibrary>
+ <WarningLevel>Level4</WarningLevel>
+ <DisableSpecificWarnings>4127;%(DisableSpecificWarnings)</DisableSpecificWarnings>
+ </ClCompile>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
+ <Midl>
+ <TargetEnvironment>X64</TargetEnvironment>
+ </Midl>
+ <ClCompile>
+ <PreprocessorDefinitions>WIN32;NDEBUG;_WINDOWS;_USRDLL;LIBlibcodec2_EXPORTS;_CRT_SECURE_NO_DEPRECATE;_CRT_NONSTDC_NO_DEPRECATE;%(PreprocessorDefinitions)</PreprocessorDefinitions>
+ <RuntimeLibrary>MultiThreadedDLL</RuntimeLibrary>
+ <WarningLevel>Level4</WarningLevel>
+ <DisableSpecificWarnings>4127;%(DisableSpecificWarnings)</DisableSpecificWarnings>
+ </ClCompile>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup>
+ <PreBuildEvent>
+ <Command>
+xcopy "$(ProjectDir)generated\*" "$(libcodec2LibDir)\src\" /C /D /Y
+</Command>
+ </PreBuildEvent>
+ </ItemDefinitionGroup>
+ <ItemGroup>
+ <ClCompile Include="$(libcodec2LibDir)\src\dump.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\lpc.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\nlp.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\postfilter.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\sine.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codec2.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\fifo.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\fdmdv.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\kiss_fft.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\interp.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\lsp.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\phase.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\quantise.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\pack.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebook.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookd.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookvq.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookjnd.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookjvm.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookvqanssi.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookdt.c" />
+ <ClCompile Include="$(libcodec2LibDir)\src\codebookge.c" />
+ </ItemGroup>
+ <ItemGroup>
+ <ClInclude Include="$(libcodec2LibDir)\src\dump.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\lpc.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\nlp.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\postfilter.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\sine.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codec2.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\fifo.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\fdmdv.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\kiss_fft.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\interp.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\lsp.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\phase.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\quantise.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\pack.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebook.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookd.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookvq.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookjnd.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookjvm.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookvqanssi.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookdt.h" />
+ <ClInclude Include="$(libcodec2LibDir)\src\codebookge.h" />
+ </ItemGroup>
+ <ItemGroup>
+ <ProjectReference Include="..\Download libcodec2.2015.vcxproj">
+ <Project>{9cfa562c-c611-48a7-90a2-bb031b47fe6d}</Project>
+ </ProjectReference>
+ </ItemGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
+ <ImportGroup Label="ExtensionTargets">
+ </ImportGroup>
+</Project>
\ No newline at end of file
--- /dev/null
+<?xml version="1.0" encoding="utf-8"?>
+<Project DefaultTargets="Build" ToolsVersion="14.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+ <ItemGroup Label="ProjectConfigurations">
+ <ProjectConfiguration Include="Debug|Win32">
+ <Configuration>Debug</Configuration>
+ <Platform>Win32</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Debug|x64">
+ <Configuration>Debug</Configuration>
+ <Platform>x64</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Release|Win32">
+ <Configuration>Release</Configuration>
+ <Platform>Win32</Platform>
+ </ProjectConfiguration>
+ <ProjectConfiguration Include="Release|x64">
+ <Configuration>Release</Configuration>
+ <Platform>x64</Platform>
+ </ProjectConfiguration>
+ </ItemGroup>
+ <PropertyGroup Label="Globals">
+ <ProjectName>mod_codec2</ProjectName>
+ <RootNamespace>mod_codec2</RootNamespace>
+ <Keyword>Win32Proj</Keyword>
+ <ProjectGuid>{CB4E68A1-8D19-4B5E-87B9-97A895E1BA17}</ProjectGuid>
+ </PropertyGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.Default.props" />
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="Configuration">
+ <ConfigurationType>DynamicLibrary</ConfigurationType>
+ <CharacterSet>MultiByte</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="Configuration">
+ <ConfigurationType>DynamicLibrary</ConfigurationType>
+ <CharacterSet>MultiByte</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="Configuration">
+ <ConfigurationType>DynamicLibrary</ConfigurationType>
+ <CharacterSet>MultiByte</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="Configuration">
+ <ConfigurationType>DynamicLibrary</ConfigurationType>
+ <CharacterSet>MultiByte</CharacterSet>
+ <PlatformToolset>v140</PlatformToolset>
+ </PropertyGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.props" />
+ <Import Project="$(SolutionDir)w32\libcodec2.props" />
+ <ImportGroup Label="ExtensionSettings">
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="..\..\..\..\w32\module_release.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="..\..\..\..\w32\module_debug.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="..\..\..\..\w32\module_release.props" />
+ </ImportGroup>
+ <ImportGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'" Label="PropertySheets">
+ <Import Project="$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props" Condition="exists('$(UserRootDir)\Microsoft.Cpp.$(Platform).user.props')" Label="LocalAppDataPlatform" />
+ <Import Project="..\..\..\..\w32\module_debug.props" />
+ </ImportGroup>
+ <PropertyGroup Label="UserMacros" />
+ <PropertyGroup>
+ <_ProjectFileVersion>10.0.30319.1</_ProjectFileVersion>
+ </PropertyGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|Win32'">
+ <ClCompile>
+ <PrecompiledHeader>
+ </PrecompiledHeader>
+ </ClCompile>
+ <Link>
+ <RandomizedBaseAddress>false</RandomizedBaseAddress>
+ <DataExecutionPrevention>
+ </DataExecutionPrevention>
+ </Link>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Debug|x64'">
+ <Midl>
+ <TargetEnvironment>X64</TargetEnvironment>
+ </Midl>
+ <ClCompile>
+ <PrecompiledHeader>
+ </PrecompiledHeader>
+ </ClCompile>
+ <Link>
+ <RandomizedBaseAddress>false</RandomizedBaseAddress>
+ <DataExecutionPrevention>
+ </DataExecutionPrevention>
+ <TargetMachine>MachineX64</TargetMachine>
+ </Link>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|Win32'">
+ <ClCompile>
+ <PrecompiledHeader>
+ </PrecompiledHeader>
+ </ClCompile>
+ <Link>
+ <RandomizedBaseAddress>false</RandomizedBaseAddress>
+ <DataExecutionPrevention>
+ </DataExecutionPrevention>
+ </Link>
+ </ItemDefinitionGroup>
+ <ItemDefinitionGroup Condition="'$(Configuration)|$(Platform)'=='Release|x64'">
+ <Midl>
+ <TargetEnvironment>X64</TargetEnvironment>
+ </Midl>
+ <ClCompile>
+ <PrecompiledHeader>
+ </PrecompiledHeader>
+ </ClCompile>
+ <Link>
+ <RandomizedBaseAddress>false</RandomizedBaseAddress>
+ <DataExecutionPrevention>
+ </DataExecutionPrevention>
+ <TargetMachine>MachineX64</TargetMachine>
+ </Link>
+ </ItemDefinitionGroup>
+ <ItemGroup>
+ <ClCompile Include="mod_codec2.c" />
+ </ItemGroup>
+ <ItemGroup>
+ <ProjectReference Include="..\..\..\..\libs\win32\libcodec2\libcodec2.2015.vcxproj">
+ <Project>{19e934d6-1484-41c8-9305-78dc42fd61f2}</Project>
+ </ProjectReference>
+ <ProjectReference Include="..\..\..\..\w32\Library\FreeSwitchCore.2015.vcxproj">
+ <Project>{202d7a4e-760d-4d0e-afa1-d7459ced30ff}</Project>
+ <ReferenceOutputAssembly>false</ReferenceOutputAssembly>
+ </ProjectReference>
+ </ItemGroup>
+ <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
+ <ImportGroup Label="ExtensionTargets">
+ </ImportGroup>
+</Project>
\ No newline at end of file
--- /dev/null
+<?xml version="1.0" encoding="utf-8"?>
+<Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+ <ImportGroup Label="PropertySheets" />
+ <PropertyGroup Label="UserMacros">
+ <libcodec2_Version>2.59</libcodec2_Version>
+ </PropertyGroup>
+ <PropertyGroup>
+ <libcodec2_VersionImported>true</libcodec2_VersionImported>
+ </PropertyGroup>
+ <PropertyGroup />
+ <ItemDefinitionGroup />
+ <ItemGroup>
+ <BuildMacro Include="libcodec2_Version">
+ <Value>$(libcodec2_Version)</Value>
+ </BuildMacro>
+ </ItemGroup>
+</Project>
\ No newline at end of file
--- /dev/null
+<?xml version="1.0" encoding="utf-8"?>
+<Project DefaultTargets="Build" ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
+ <ImportGroup Label="PropertySheets">
+ <Import Project="libcodec2-version.props" Condition=" '$(libcodec2_VersionImported)' == '' "/>
+ </ImportGroup>
+ <PropertyGroup Label="UserMacros">
+ <libcodec2LibDir>$(SolutionDir)libs\libcodec2-$(libcodec2_Version)</libcodec2LibDir>
+ </PropertyGroup>
+ <ItemDefinitionGroup>
+ <ClCompile>
+ <AdditionalIncludeDirectories>$(libcodec2LibDir)\src;%(AdditionalIncludeDirectories)</AdditionalIncludeDirectories>
+ </ClCompile>
+ </ItemDefinitionGroup>
+</Project>
\ No newline at end of file
projects / thirdparty / freeswitch.git / commitdiff
