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Code Issues Projects Releases Packages Wiki Activity Actions 8

Issue #18844: Add random.weighted_choices()

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This commit is contained in:
Raymond Hettinger 2016-09-06 17:15:29 -07:00
parent 63d98bcd4c
commit e8f1e002c6
4 changed files with 118 additions and 1 deletions
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68
Lib/test/test_random.py
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@ -7,6 +7,7 @@ import warnings
from functools import partial
from math import log, exp, pi, fsum, sin
from test import support
from fractions import Fraction
class TestBasicOps:
# Superclass with tests common to all generators.
@ -141,6 +142,73 @@ class TestBasicOps:
def test_sample_on_dicts(self):
self.assertRaises(TypeError, self.gen.sample, dict.fromkeys('abcdef'), 2)
def test_weighted_choices(self):
weighted_choices = self.gen.weighted_choices
data = ['red', 'green', 'blue', 'yellow']
str_data = 'abcd'
range_data = range(4)
set_data = set(range(4))
# basic functionality
for sample in [
weighted_choices(5, data),
weighted_choices(5, data, range(4)),
weighted_choices(k=5, population=data, weights=range(4)),
weighted_choices(k=5, population=data, cum_weights=range(4)),
]:
self.assertEqual(len(sample), 5)
self.assertEqual(type(sample), list)
self.assertTrue(set(sample) <= set(data))
# test argument handling
with self.assertRaises(TypeError): # missing arguments
weighted_choices(2)
self.assertEqual(weighted_choices(0, data), []) # k == 0
self.assertEqual(weighted_choices(-1, data), []) # negative k behaves like ``[0] * -1``
with self.assertRaises(TypeError):
weighted_choices(2.5, data) # k is a float
self.assertTrue(set(weighted_choices(5, str_data)) <= set(str_data)) # population is a string sequence
self.assertTrue(set(weighted_choices(5, range_data)) <= set(range_data)) # population is a range
with self.assertRaises(TypeError):
weighted_choices(2.5, set_data) # population is not a sequence
self.assertTrue(set(weighted_choices(5, data, None)) <= set(data)) # weights is None
self.assertTrue(set(weighted_choices(5, data, weights=None)) <= set(data))
with self.assertRaises(ValueError):
weighted_choices(5, data, [1,2]) # len(weights) != len(population)
with self.assertRaises(IndexError):
weighted_choices(5, data, [0]*4) # weights sum to zero
with self.assertRaises(TypeError):
weighted_choices(5, data, 10) # non-iterable weights
with self.assertRaises(TypeError):
weighted_choices(5, data, [None]*4) # non-numeric weights
for weights in [
[15, 10, 25, 30], # integer weights
[15.1, 10.2, 25.2, 30.3], # float weights
[Fraction(1, 3), Fraction(2, 6), Fraction(3, 6), Fraction(4, 6)], # fractional weights
[True, False, True, False] # booleans (include / exclude)
]:
self.assertTrue(set(weighted_choices(5, data, weights)) <= set(data))
with self.assertRaises(ValueError):
weighted_choices(5, data, cum_weights=[1,2]) # len(weights) != len(population)
with self.assertRaises(IndexError):
weighted_choices(5, data, cum_weights=[0]*4) # cum_weights sum to zero
with self.assertRaises(TypeError):
weighted_choices(5, data, cum_weights=10) # non-iterable cum_weights
with self.assertRaises(TypeError):
weighted_choices(5, data, cum_weights=[None]*4) # non-numeric cum_weights
with self.assertRaises(TypeError):
weighted_choices(5, data, range(4), cum_weights=range(4)) # both weights and cum_weights
for weights in [
[15, 10, 25, 30], # integer cum_weights
[15.1, 10.2, 25.2, 30.3], # float cum_weights
[Fraction(1, 3), Fraction(2, 6), Fraction(3, 6), Fraction(4, 6)], # fractional cum_weights
]:
self.assertTrue(set(weighted_choices(5, data, cum_weights=weights)) <= set(data))
def test_gauss(self):
# Ensure that the seed() method initializes all the hidden state. In
# particular, through 2.2.1 it failed to reset a piece of state used