cum_counts = list(_accumulate(counts))
if len(cum_counts) != n:
raise ValueError('The number of counts does not match the population')
- total = cum_counts.pop()
+ total = cum_counts.pop() if cum_counts else 0
if not isinstance(total, int):
raise TypeError('Counts must be integers')
- if total <= 0:
- raise ValueError('Total of counts must be greater than zero')
+ if total < 0:
+ raise ValueError('Counts must be non-negative')
selections = self.sample(range(total), k=k)
bisect = _bisect
return [population[bisect(cum_counts, s)] for s in selections]
sample(['red', 'green', 'blue'], counts=10, k=10) # counts not iterable
with self.assertRaises(ValueError):
sample(['red', 'green', 'blue'], counts=[-3, -7, -8], k=2) # counts are negative
- with self.assertRaises(ValueError):
- sample(['red', 'green', 'blue'], counts=[0, 0, 0], k=2) # counts are zero
with self.assertRaises(ValueError):
sample(['red', 'green'], counts=[10, 10], k=21) # population too small
with self.assertRaises(ValueError):
with self.assertRaises(ValueError):
sample(['red', 'green', 'blue'], counts=[1, 2, 3, 4], k=2) # too many counts
+ # Cases with zero counts match equivalents without counts (see gh-130285)
+ self.assertEqual(
+ sample('abc', k=0, counts=[0, 0, 0]),
+ sample([], k=0),
+ )
+ self.assertEqual(
+ sample([], 0, counts=[]),
+ sample([], 0),
+ )
+ with self.assertRaises(ValueError):
+ sample([], 1, counts=[])
+ with self.assertRaises(ValueError):
+ sample('x', 1, counts=[0])
+
def test_choices(self):
choices = self.gen.choices
data = ['red', 'green', 'blue', 'yellow']