diff options
Diffstat (limited to 'Lib/test/test_random.py')
| -rw-r--r-- | Lib/test/test_random.py | 86 |
1 files changed, 78 insertions, 8 deletions
diff --git a/Lib/test/test_random.py b/Lib/test/test_random.py index df07b76..97d8098 100644 --- a/Lib/test/test_random.py +++ b/Lib/test/test_random.py @@ -1,11 +1,11 @@ -#!/usr/bin/env python +#!/usr/bin/env python3 import unittest import random import time import pickle import warnings -from math import log, exp, sqrt, pi, fsum, sin +from math import log, exp, pi, fsum, sin from test import support class TestBasicOps(unittest.TestCase): @@ -39,9 +39,16 @@ class TestBasicOps(unittest.TestCase): self.gen.seed(arg) for arg in [list(range(3)), dict(one=1)]: self.assertRaises(TypeError, self.gen.seed, arg) - self.assertRaises(TypeError, self.gen.seed, 1, 2) + self.assertRaises(TypeError, self.gen.seed, 1, 2, 3, 4) self.assertRaises(TypeError, type(self.gen), []) + def test_choice(self): + choice = self.gen.choice + with self.assertRaises(IndexError): + choice([]) + self.assertEqual(choice([50]), 50) + self.assertIn(choice([25, 75]), [25, 75]) + def test_sample(self): # For the entire allowable range of 0 <= k <= N, validate that # the sample is of the correct length and contains only unique items @@ -121,7 +128,15 @@ class TestBasicOps(unittest.TestCase): f = open(support.findfile(file),"rb") r = pickle.load(f) f.close() - self.assertEqual(r.randrange(1000), value) + self.assertEqual(int(r.random()*1000), value) + + def test_bug_9025(self): + # Had problem with an uneven distribution in int(n*random()) + # Verify the fix by checking that distributions fall within expectations. + n = 100000 + randrange = self.gen.randrange + k = sum(randrange(6755399441055744) % 3 == 2 for i in range(n)) + self.assertTrue(0.30 < k/n < .37, (k/n)) class SystemRandom_TestBasicOps(TestBasicOps): gen = random.SystemRandom() @@ -211,7 +226,7 @@ class SystemRandom_TestBasicOps(TestBasicOps): n += n - 1 # check 1 below the next power of two k = int(1.00001 + _log(n, 2)) - self.assertTrue(k in [numbits, numbits+1]) + self.assertIn(k, [numbits, numbits+1]) self.assertTrue(2**k > n > 2**(k-2)) n -= n >> 15 # check a little farther below the next power of two @@ -223,6 +238,17 @@ class SystemRandom_TestBasicOps(TestBasicOps): class MersenneTwister_TestBasicOps(TestBasicOps): gen = random.Random() + def test_guaranteed_stable(self): + # These sequences are guaranteed to stay the same across versions of python + self.gen.seed(3456147, version=1) + self.assertEqual([self.gen.random().hex() for i in range(4)], + ['0x1.ac362300d90d2p-1', '0x1.9d16f74365005p-1', + '0x1.1ebb4352e4c4dp-1', '0x1.1a7422abf9c11p-1']) + self.gen.seed("the quick brown fox", version=2) + self.assertEqual([self.gen.random().hex() for i in range(4)], + ['0x1.1239ddfb11b7cp-3', '0x1.b3cbb5c51b120p-4', + '0x1.8c4f55116b60fp-1', '0x1.63eb525174a27p-1']) + def test_setstate_first_arg(self): self.assertRaises(ValueError, self.gen.setstate, (1, None, None)) @@ -367,7 +393,7 @@ class MersenneTwister_TestBasicOps(TestBasicOps): n += n - 1 # check 1 below the next power of two k = int(1.00001 + _log(n, 2)) - self.assertTrue(k in [numbits, numbits+1]) + self.assertIn(k, [numbits, numbits+1]) self.assertTrue(2**k > n > 2**(k-2)) n -= n >> 15 # check a little farther below the next power of two @@ -410,6 +436,7 @@ class TestDistributions(unittest.TestCase): g.random = x[:].pop; g.paretovariate(1.0) g.random = x[:].pop; g.expovariate(1.0) g.random = x[:].pop; g.weibullvariate(1.0, 1.0) + g.random = x[:].pop; g.vonmisesvariate(1.0, 1.0) g.random = x[:].pop; g.normalvariate(0.0, 1.0) g.random = x[:].pop; g.gauss(0.0, 1.0) g.random = x[:].pop; g.lognormvariate(0.0, 1.0) @@ -430,6 +457,7 @@ class TestDistributions(unittest.TestCase): (g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12), (g.triangular, (0.0, 1.0, 1.0/3.0), 4.0/9.0, 7.0/9.0/18.0), (g.expovariate, (1.5,), 1/1.5, 1/1.5**2), + (g.vonmisesvariate, (1.23, 0), pi, pi**2/3), (g.paretovariate, (5.0,), 5.0/(5.0-1), 5.0/((5.0-1)**2*(5.0-2))), (g.weibullvariate, (1.0, 3.0), gamma(1+1/3.0), @@ -446,8 +474,50 @@ class TestDistributions(unittest.TestCase): s1 += e s2 += (e - mu) ** 2 N = len(y) - self.assertAlmostEqual(s1/N, mu, places=2) - self.assertAlmostEqual(s2/(N-1), sigmasqrd, places=2) + self.assertAlmostEqual(s1/N, mu, places=2, + msg='%s%r' % (variate.__name__, args)) + self.assertAlmostEqual(s2/(N-1), sigmasqrd, places=2, + msg='%s%r' % (variate.__name__, args)) + + def test_constant(self): + g = random.Random() + N = 100 + for variate, args, expected in [ + (g.uniform, (10.0, 10.0), 10.0), + (g.triangular, (10.0, 10.0), 10.0), + #(g.triangular, (10.0, 10.0, 10.0), 10.0), + (g.expovariate, (float('inf'),), 0.0), + (g.vonmisesvariate, (3.0, float('inf')), 3.0), + (g.gauss, (10.0, 0.0), 10.0), + (g.lognormvariate, (0.0, 0.0), 1.0), + (g.lognormvariate, (-float('inf'), 0.0), 0.0), + (g.normalvariate, (10.0, 0.0), 10.0), + (g.paretovariate, (float('inf'),), 1.0), + (g.weibullvariate, (10.0, float('inf')), 10.0), + (g.weibullvariate, (0.0, 10.0), 0.0), + ]: + for i in range(N): + self.assertEqual(variate(*args), expected) + + def test_von_mises_range(self): + # Issue 17149: von mises variates were not consistently in the + # range [0, 2*PI]. + g = random.Random() + N = 100 + for mu in 0.0, 0.1, 3.1, 6.2: + for kappa in 0.0, 2.3, 500.0: + for _ in range(N): + sample = g.vonmisesvariate(mu, kappa) + self.assertTrue( + 0 <= sample <= random.TWOPI, + msg=("vonmisesvariate({}, {}) produced a result {} out" + " of range [0, 2*pi]").format(mu, kappa, sample)) + + def test_von_mises_large_kappa(self): + # Issue #17141: vonmisesvariate() was hang for large kappas + random.vonmisesvariate(0, 1e15) + random.vonmisesvariate(0, 1e100) + class TestModule(unittest.TestCase): def testMagicConstants(self): |