bpo-24567: Random subnormal.diff (#7954)
Handle subnormal weights for choices()
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@ -383,7 +383,9 @@ class Random(_random.Random):
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raise ValueError('The number of weights does not match the population')
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bisect = _bisect.bisect
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total = cum_weights[-1]
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return [population[bisect(cum_weights, random() * total)] for i in range(k)]
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hi = len(cum_weights) - 1
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return [population[bisect(cum_weights, random() * total, 0, hi)]
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for i in range(k)]
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## -------------------- real-valued distributions -------------------
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@ -227,6 +227,14 @@ class TestBasicOps:
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with self.assertRaises(IndexError):
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choices([], cum_weights=[], k=5)
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def test_choices_subnormal(self):
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# Subnormal weights would occassionally trigger an IndexError
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# in choices() when the value returned by random() was large
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# enough to make `random() * total` round up to the total.
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# See https://bugs.python.org/msg275594 for more detail.
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choices = self.gen.choices
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choices(population=[1, 2], weights=[1e-323, 1e-323], k=5000)
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def test_gauss(self):
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# Ensure that the seed() method initializes all the hidden state. In
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# particular, through 2.2.1 it failed to reset a piece of state used
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@ -0,0 +1,2 @@
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Improve random.choices() to handle subnormal input weights that could
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occasionally trigger an IndexError.
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