Improve debugging for bayes.

diff --git a/src/libstat/classifiers/bayes.c b/src/libstat/classifiers/bayes.c
index 2a7ea2b89e86650e56efa782c647b2dfffc1a5fd..966d5b458fea6657c49188495918c716821c31b6 100644 (file)
--- a/src/libstat/classifiers/bayes.c
+++ b/src/libstat/classifiers/bayes.c
@@ -32,6 +32,24 @@
 #include "stat_internal.h"
 #include "math.h"
 
+#define msg_err_bayes(...) rspamd_default_log_function (G_LOG_LEVEL_CRITICAL, \
+        "bayes", task->task_pool->tag.uid, \
+        G_STRFUNC, \
+        __VA_ARGS__)
+#define msg_warn_bayes(...)   rspamd_default_log_function (G_LOG_LEVEL_WARNING, \
+        "bayes", task->task_pool->tag.uid, \
+        G_STRFUNC, \
+        __VA_ARGS__)
+#define msg_info_bayes(...)   rspamd_default_log_function (G_LOG_LEVEL_INFO, \
+        "bayes", task->task_pool->tag.uid, \
+        G_STRFUNC, \
+        __VA_ARGS__)
+#define msg_debug_bayes(...)  rspamd_default_log_function (G_LOG_LEVEL_DEBUG, \
+        "bayes", task->task_pool->tag.uid, \
+        G_STRFUNC, \
+        __VA_ARGS__)
+
+
 static inline GQuark
 bayes_error_quark (void)
 {
@@ -46,7 +64,7 @@ bayes_error_quark (void)
  * @return
  */
 static gdouble
-inv_chi_square (gdouble value, gint freedom_deg)
+inv_chi_square (struct rspamd_task *task, gdouble value, gint freedom_deg)
 {
        double prob, sum, m;
        gint i;
@@ -56,7 +74,7 @@ inv_chi_square (gdouble value, gint freedom_deg)
        prob = exp (value);
 
        if (errno == ERANGE) {
-               msg_err ("exp overflow");
+               msg_err_bayes ("exp overflow");
                return 0;
        }
 
@@ -71,6 +89,11 @@ inv_chi_square (gdouble value, gint freedom_deg)
        return MIN (1.0, sum);
 }
 
+struct bayes_task_closure {
+       struct rspamd_classifier_runtime *rt;
+       struct rspamd_task *task;
+};
+
 static const double feature_weight[] = { 0, 3125, 256, 27, 4, 1 };
 
 #define PROB_COMBINE(prob, cnt, weight, assumed) (((weight) * (assumed) + (cnt) * (prob)) / ((weight) + (cnt)))
@@ -81,13 +104,18 @@ static gboolean
 bayes_classify_callback (gpointer key, gpointer value, gpointer data)
 {
        rspamd_token_t *node = value;
-       struct rspamd_classifier_runtime *rt = (struct rspamd_classifier_runtime *)data;
+       struct bayes_task_closure *cl = data;
+       struct rspamd_classifier_runtime *rt;
        guint i;
        struct rspamd_token_result *res;
        guint64 spam_count = 0, ham_count = 0, total_count = 0;
+       struct rspamd_task *task;
        double spam_prob, spam_freq, ham_freq, bayes_spam_prob, bayes_ham_prob,
                ham_prob, fw, w, norm_sum, norm_sub;
 
+       rt = cl->rt;
+       task = cl->task;
+
        for (i = rt->start_pos; i < rt->end_pos; i++) {
                res = &g_array_index (node->results, struct rspamd_token_result, i);
 
@@ -122,6 +150,15 @@ bayes_classify_callback (gpointer key, gpointer value, gpointer data)
                rt->spam_prob += log (bayes_spam_prob);
                rt->ham_prob += log (bayes_ham_prob);
                res->cl_runtime->processed_tokens ++;
+
+               msg_debug_bayes ("token: total_count: %L, spam_count: %L, ham_count: %L,"
+                               " spam_prob: %.3f, "
+                               "ham_prob: %.3f, bayes_spam_prob: %.3f, bayes_ham_prob: %.3f, "
+                               "current spam prob: %.3f, current ham prob: %.3f",
+                               total_count, spam_count, ham_count,
+                               spam_prob, ham_prob,
+                               bayes_spam_prob, bayes_ham_prob,
+                               rt->spam_prob, rt->ham_prob);
        }
 
        return FALSE;
@@ -151,6 +188,7 @@ bayes_classify (struct classifier_ctx * ctx,
        struct rspamd_statfile_runtime *st, *selected_st = NULL;
        GList *cur;
        char *sumbuf;
+       struct bayes_task_closure cl;
 
        g_assert (ctx != NULL);
        g_assert (input != NULL);
@@ -158,15 +196,17 @@ bayes_classify (struct classifier_ctx * ctx,
        g_assert (rt->end_pos > rt->start_pos);
 
        if (rt->stage == RSPAMD_STAT_STAGE_PRE) {
-               g_tree_foreach (input, bayes_classify_callback, rt);
+               cl.rt = rt;
+               cl.task = task;
+               g_tree_foreach (input, bayes_classify_callback, &cl);
        }
        else {
-               h = 1 - inv_chi_square (rt->spam_prob, rt->processed_tokens);
-               s = 1 - inv_chi_square (rt->ham_prob, rt->processed_tokens);
+               h = 1 - inv_chi_square (task, rt->spam_prob, rt->processed_tokens);
+               s = 1 - inv_chi_square (task, rt->ham_prob, rt->processed_tokens);
 
                if (isfinite (s) && isfinite (h)) {
                        final_prob = (s + 1.0 - h) / 2.;
-                       msg_debug ("<%s> got ham prob %.2f -> %.2f and spam prob %.2f -> %.2f,"
+                       msg_debug_bayes ("<%s> got ham prob %.2f -> %.2f and spam prob %.2f -> %.2f,"
                                        " %L tokens processed of %ud total tokens",
                                        task->message_id, rt->ham_prob, h, rt->spam_prob, s,
                                        rt->processed_tokens, g_tree_nnodes (input));
@@ -178,17 +218,17 @@ bayes_classify (struct classifier_ctx * ctx,
                         */
                        if (isfinite (h)) {
                                final_prob = 1.0;
-                               msg_debug ("<%s> spam class is overflowed, as we have no"
+                               msg_debug_bayes ("<%s> spam class is overflowed, as we have no"
                                                " ham samples", task->message_id);
                        }
                        else if (isfinite (s)){
                                final_prob = 0.0;
-                               msg_debug ("<%s> ham class is overflowed, as we have no"
+                               msg_debug_bayes ("<%s> ham class is overflowed, as we have no"
                                                " spam samples", task->message_id);
                        }
                        else {
                                final_prob = 0.5;
-                               msg_warn ("<%s> spam and ham classes are both overflowed",
+                               msg_warn_bayes ("<%s> spam and ham classes are both overflowed",
                                                task->message_id);
                        }
                }
@@ -213,7 +253,7 @@ bayes_classify (struct classifier_ctx * ctx,
                        }
 
                        if (selected_st == NULL) {
-                               msg_err (
+                               msg_err_bayes (
                                        "unexpected classifier error: cannot select desired statfile, "
                                        "prob: %.4f", final_prob);
                        }