Mercurial > cpython-lru_cache-weakref
annotate Lib/test/test_random.py @ 78069:a8aa77458e12 3.2
Add c_size_t and c_ssize_t to the ctypes summary table.
| author | Antoine Pitrou <solipsis@pitrou.net> |
|---|---|
| date | Thu, 12 Jul 2012 20:31:50 +0200 |
| parents | f4f56efa2870 |
| children | 41e97652a9f9 62d9f1285f51 |
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1 #!/usr/bin/env python3 |
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2 |
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3 import unittest |
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4 import random |
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5 import time |
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6 import pickle |
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7 import warnings |
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8 from math import log, exp, pi, fsum, sin |
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9 from test import support |
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10 |
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11 class TestBasicOps(unittest.TestCase): |
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12 # Superclass with tests common to all generators. |
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13 # Subclasses must arrange for self.gen to retrieve the Random instance |
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14 # to be tested. |
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15 |
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16 def randomlist(self, n): |
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17 """Helper function to make a list of random numbers""" |
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18 return [self.gen.random() for i in range(n)] |
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19 |
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20 def test_autoseed(self): |
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21 self.gen.seed() |
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22 state1 = self.gen.getstate() |
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23 time.sleep(0.1) |
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24 self.gen.seed() # diffent seeds at different times |
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25 state2 = self.gen.getstate() |
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26 self.assertNotEqual(state1, state2) |
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27 |
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28 def test_saverestore(self): |
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29 N = 1000 |
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30 self.gen.seed() |
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31 state = self.gen.getstate() |
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32 randseq = self.randomlist(N) |
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33 self.gen.setstate(state) # should regenerate the same sequence |
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34 self.assertEqual(randseq, self.randomlist(N)) |
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35 |
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36 def test_seedargs(self): |
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37 for arg in [None, 0, 0, 1, 1, -1, -1, 10**20, -(10**20), |
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38 3.14, 1+2j, 'a', tuple('abc')]: |
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39 self.gen.seed(arg) |
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40 for arg in [list(range(3)), dict(one=1)]: |
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41 self.assertRaises(TypeError, self.gen.seed, arg) |
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42 self.assertRaises(TypeError, self.gen.seed, 1, 2, 3, 4) |
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43 self.assertRaises(TypeError, type(self.gen), []) |
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44 |
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45 def test_choice(self): |
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46 choice = self.gen.choice |
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47 with self.assertRaises(IndexError): |
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48 choice([]) |
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49 self.assertEqual(choice([50]), 50) |
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50 self.assertIn(choice([25, 75]), [25, 75]) |
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51 |
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52 def test_sample(self): |
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53 # For the entire allowable range of 0 <= k <= N, validate that |
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54 # the sample is of the correct length and contains only unique items |
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55 N = 100 |
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56 population = range(N) |
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57 for k in range(N+1): |
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58 s = self.gen.sample(population, k) |
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59 self.assertEqual(len(s), k) |
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60 uniq = set(s) |
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61 self.assertEqual(len(uniq), k) |
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62 self.assertTrue(uniq <= set(population)) |
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63 self.assertEqual(self.gen.sample([], 0), []) # test edge case N==k==0 |
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64 |
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65 def test_sample_distribution(self): |
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66 # For the entire allowable range of 0 <= k <= N, validate that |
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67 # sample generates all possible permutations |
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68 n = 5 |
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69 pop = range(n) |
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70 trials = 10000 # large num prevents false negatives without slowing normal case |
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71 def factorial(n): |
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72 if n == 0: |
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73 return 1 |
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74 return n * factorial(n - 1) |
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75 for k in range(n): |
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76 expected = factorial(n) // factorial(n-k) |
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77 perms = {} |
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78 for i in range(trials): |
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79 perms[tuple(self.gen.sample(pop, k))] = None |
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80 if len(perms) == expected: |
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81 break |
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82 else: |
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83 self.fail() |
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84 |
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85 def test_sample_inputs(self): |
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86 # SF bug #801342 -- population can be any iterable defining __len__() |
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87 self.gen.sample(set(range(20)), 2) |
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88 self.gen.sample(range(20), 2) |
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89 self.gen.sample(range(20), 2) |
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90 self.gen.sample(str('abcdefghijklmnopqrst'), 2) |
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91 self.gen.sample(tuple('abcdefghijklmnopqrst'), 2) |
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92 |
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93 def test_sample_on_dicts(self): |
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94 self.assertRaises(TypeError, self.gen.sample, dict.fromkeys('abcdef'), 2) |
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95 |
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96 def test_gauss(self): |
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97 # Ensure that the seed() method initializes all the hidden state. In |
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98 # particular, through 2.2.1 it failed to reset a piece of state used |
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99 # by (and only by) the .gauss() method. |
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100 |
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101 for seed in 1, 12, 123, 1234, 12345, 123456, 654321: |
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102 self.gen.seed(seed) |
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103 x1 = self.gen.random() |
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104 y1 = self.gen.gauss(0, 1) |
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105 |
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106 self.gen.seed(seed) |
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107 x2 = self.gen.random() |
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108 y2 = self.gen.gauss(0, 1) |
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109 |
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110 self.assertEqual(x1, x2) |
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111 self.assertEqual(y1, y2) |
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112 |
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113 def test_pickling(self): |
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114 state = pickle.dumps(self.gen) |
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115 origseq = [self.gen.random() for i in range(10)] |
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116 newgen = pickle.loads(state) |
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117 restoredseq = [newgen.random() for i in range(10)] |
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118 self.assertEqual(origseq, restoredseq) |
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119 |
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120 def test_bug_1727780(self): |
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121 # verify that version-2-pickles can be loaded |
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122 # fine, whether they are created on 32-bit or 64-bit |
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123 # platforms, and that version-3-pickles load fine. |
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124 files = [("randv2_32.pck", 780), |
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125 ("randv2_64.pck", 866), |
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126 ("randv3.pck", 343)] |
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127 for file, value in files: |
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128 f = open(support.findfile(file),"rb") |
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129 r = pickle.load(f) |
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130 f.close() |
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131 self.assertEqual(int(r.random()*1000), value) |
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132 |
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133 def test_bug_9025(self): |
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134 # Had problem with an uneven distribution in int(n*random()) |
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135 # Verify the fix by checking that distributions fall within expectations. |
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136 n = 100000 |
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137 randrange = self.gen.randrange |
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138 k = sum(randrange(6755399441055744) % 3 == 2 for i in range(n)) |
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139 self.assertTrue(0.30 < k/n < .37, (k/n)) |
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140 |
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141 class SystemRandom_TestBasicOps(TestBasicOps): |
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142 gen = random.SystemRandom() |
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143 |
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144 def test_autoseed(self): |
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145 # Doesn't need to do anything except not fail |
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146 self.gen.seed() |
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147 |
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148 def test_saverestore(self): |
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149 self.assertRaises(NotImplementedError, self.gen.getstate) |
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150 self.assertRaises(NotImplementedError, self.gen.setstate, None) |
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151 |
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152 def test_seedargs(self): |
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153 # Doesn't need to do anything except not fail |
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154 self.gen.seed(100) |
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155 |
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156 def test_gauss(self): |
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157 self.gen.gauss_next = None |
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158 self.gen.seed(100) |
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159 self.assertEqual(self.gen.gauss_next, None) |
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160 |
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161 def test_pickling(self): |
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162 self.assertRaises(NotImplementedError, pickle.dumps, self.gen) |
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163 |
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164 def test_53_bits_per_float(self): |
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165 # This should pass whenever a C double has 53 bit precision. |
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166 span = 2 ** 53 |
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167 cum = 0 |
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168 for i in range(100): |
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169 cum |= int(self.gen.random() * span) |
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170 self.assertEqual(cum, span-1) |
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171 |
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172 def test_bigrand(self): |
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173 # The randrange routine should build-up the required number of bits |
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174 # in stages so that all bit positions are active. |
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175 span = 2 ** 500 |
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176 cum = 0 |
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177 for i in range(100): |
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178 r = self.gen.randrange(span) |
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179 self.assertTrue(0 <= r < span) |
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180 cum |= r |
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181 self.assertEqual(cum, span-1) |
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182 |
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183 def test_bigrand_ranges(self): |
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184 for i in [40,80, 160, 200, 211, 250, 375, 512, 550]: |
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185 start = self.gen.randrange(2 ** i) |
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186 stop = self.gen.randrange(2 ** (i-2)) |
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187 if stop <= start: |
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188 return |
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189 self.assertTrue(start <= self.gen.randrange(start, stop) < stop) |
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190 |
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191 def test_rangelimits(self): |
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192 for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]: |
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193 self.assertEqual(set(range(start,stop)), |
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194 set([self.gen.randrange(start,stop) for i in range(100)])) |
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195 |
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196 def test_genrandbits(self): |
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197 # Verify ranges |
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198 for k in range(1, 1000): |
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199 self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k) |
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200 |
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201 # Verify all bits active |
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202 getbits = self.gen.getrandbits |
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203 for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]: |
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204 cum = 0 |
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205 for i in range(100): |
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206 cum |= getbits(span) |
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207 self.assertEqual(cum, 2**span-1) |
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208 |
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209 # Verify argument checking |
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210 self.assertRaises(TypeError, self.gen.getrandbits) |
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211 self.assertRaises(TypeError, self.gen.getrandbits, 1, 2) |
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212 self.assertRaises(ValueError, self.gen.getrandbits, 0) |
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213 self.assertRaises(ValueError, self.gen.getrandbits, -1) |
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214 self.assertRaises(TypeError, self.gen.getrandbits, 10.1) |
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215 |
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216 def test_randbelow_logic(self, _log=log, int=int): |
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217 # check bitcount transition points: 2**i and 2**(i+1)-1 |
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218 # show that: k = int(1.001 + _log(n, 2)) |
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219 # is equal to or one greater than the number of bits in n |
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220 for i in range(1, 1000): |
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221 n = 1 << i # check an exact power of two |
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222 numbits = i+1 |
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223 k = int(1.00001 + _log(n, 2)) |
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224 self.assertEqual(k, numbits) |
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225 self.assertEqual(n, 2**(k-1)) |
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226 |
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227 n += n - 1 # check 1 below the next power of two |
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228 k = int(1.00001 + _log(n, 2)) |
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229 self.assertIn(k, [numbits, numbits+1]) |
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230 self.assertTrue(2**k > n > 2**(k-2)) |
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231 |
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232 n -= n >> 15 # check a little farther below the next power of two |
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233 k = int(1.00001 + _log(n, 2)) |
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234 self.assertEqual(k, numbits) # note the stronger assertion |
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235 self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion |
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236 |
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237 |
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238 class MersenneTwister_TestBasicOps(TestBasicOps): |
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239 gen = random.Random() |
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240 |
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241 def test_guaranteed_stable(self): |
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242 # These sequences are guaranteed to stay the same across versions of python |
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243 self.gen.seed(3456147, version=1) |
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244 self.assertEqual([self.gen.random().hex() for i in range(4)], |
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245 ['0x1.ac362300d90d2p-1', '0x1.9d16f74365005p-1', |
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246 '0x1.1ebb4352e4c4dp-1', '0x1.1a7422abf9c11p-1']) |
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247 self.gen.seed("the quick brown fox", version=2) |
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248 self.assertEqual([self.gen.random().hex() for i in range(4)], |
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249 ['0x1.1239ddfb11b7cp-3', '0x1.b3cbb5c51b120p-4', |
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250 '0x1.8c4f55116b60fp-1', '0x1.63eb525174a27p-1']) |
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251 |
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252 def test_setstate_first_arg(self): |
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253 self.assertRaises(ValueError, self.gen.setstate, (1, None, None)) |
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254 |
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255 def test_setstate_middle_arg(self): |
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256 # Wrong type, s/b tuple |
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257 self.assertRaises(TypeError, self.gen.setstate, (2, None, None)) |
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258 # Wrong length, s/b 625 |
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259 self.assertRaises(ValueError, self.gen.setstate, (2, (1,2,3), None)) |
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260 # Wrong type, s/b tuple of 625 ints |
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261 self.assertRaises(TypeError, self.gen.setstate, (2, ('a',)*625, None)) |
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262 # Last element s/b an int also |
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263 self.assertRaises(TypeError, self.gen.setstate, (2, (0,)*624+('a',), None)) |
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264 |
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265 def test_referenceImplementation(self): |
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266 # Compare the python implementation with results from the original |
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267 # code. Create 2000 53-bit precision random floats. Compare only |
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268 # the last ten entries to show that the independent implementations |
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269 # are tracking. Here is the main() function needed to create the |
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270 # list of expected random numbers: |
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271 # void main(void){ |
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272 # int i; |
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273 # unsigned long init[4]={61731, 24903, 614, 42143}, length=4; |
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274 # init_by_array(init, length); |
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275 # for (i=0; i<2000; i++) { |
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276 # printf("%.15f ", genrand_res53()); |
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277 # if (i%5==4) printf("\n"); |
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278 # } |
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279 # } |
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280 expected = [0.45839803073713259, |
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281 0.86057815201978782, |
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282 0.92848331726782152, |
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283 0.35932681119782461, |
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284 0.081823493762449573, |
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285 0.14332226470169329, |
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286 0.084297823823520024, |
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287 0.53814864671831453, |
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288 0.089215024911993401, |
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289 0.78486196105372907] |
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290 |
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291 self.gen.seed(61731 + (24903<<32) + (614<<64) + (42143<<96)) |
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292 actual = self.randomlist(2000)[-10:] |
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293 for a, e in zip(actual, expected): |
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294 self.assertAlmostEqual(a,e,places=14) |
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295 |
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296 def test_strong_reference_implementation(self): |
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297 # Like test_referenceImplementation, but checks for exact bit-level |
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298 # equality. This should pass on any box where C double contains |
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299 # at least 53 bits of precision (the underlying algorithm suffers |
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300 # no rounding errors -- all results are exact). |
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301 from math import ldexp |
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302 |
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303 expected = [0x0eab3258d2231f, |
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304 0x1b89db315277a5, |
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305 0x1db622a5518016, |
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306 0x0b7f9af0d575bf, |
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307 0x029e4c4db82240, |
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308 0x04961892f5d673, |
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309 0x02b291598e4589, |
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310 0x11388382c15694, |
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311 0x02dad977c9e1fe, |
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312 0x191d96d4d334c6] |
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313 self.gen.seed(61731 + (24903<<32) + (614<<64) + (42143<<96)) |
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314 actual = self.randomlist(2000)[-10:] |
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315 for a, e in zip(actual, expected): |
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316 self.assertEqual(int(ldexp(a, 53)), e) |
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317 |
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318 def test_long_seed(self): |
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319 # This is most interesting to run in debug mode, just to make sure |
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320 # nothing blows up. Under the covers, a dynamically resized array |
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321 # is allocated, consuming space proportional to the number of bits |
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322 # in the seed. Unfortunately, that's a quadratic-time algorithm, |
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323 # so don't make this horribly big. |
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324 seed = (1 << (10000 * 8)) - 1 # about 10K bytes |
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325 self.gen.seed(seed) |
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326 |
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327 def test_53_bits_per_float(self): |
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328 # This should pass whenever a C double has 53 bit precision. |
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329 span = 2 ** 53 |
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330 cum = 0 |
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331 for i in range(100): |
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332 cum |= int(self.gen.random() * span) |
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333 self.assertEqual(cum, span-1) |
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334 |
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335 def test_bigrand(self): |
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336 # The randrange routine should build-up the required number of bits |
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337 # in stages so that all bit positions are active. |
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338 span = 2 ** 500 |
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339 cum = 0 |
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340 for i in range(100): |
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341 r = self.gen.randrange(span) |
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342 self.assertTrue(0 <= r < span) |
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343 cum |= r |
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344 self.assertEqual(cum, span-1) |
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345 |
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346 def test_bigrand_ranges(self): |
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347 for i in [40,80, 160, 200, 211, 250, 375, 512, 550]: |
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348 start = self.gen.randrange(2 ** i) |
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349 stop = self.gen.randrange(2 ** (i-2)) |
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350 if stop <= start: |
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351 return |
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352 self.assertTrue(start <= self.gen.randrange(start, stop) < stop) |
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353 |
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354 def test_rangelimits(self): |
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355 for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]: |
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356 self.assertEqual(set(range(start,stop)), |
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357 set([self.gen.randrange(start,stop) for i in range(100)])) |
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358 |
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359 def test_genrandbits(self): |
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360 # Verify cross-platform repeatability |
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361 self.gen.seed(1234567) |
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362 self.assertEqual(self.gen.getrandbits(100), |
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363 97904845777343510404718956115) |
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364 # Verify ranges |
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365 for k in range(1, 1000): |
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366 self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k) |
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367 |
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368 # Verify all bits active |
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369 getbits = self.gen.getrandbits |
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370 for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]: |
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371 cum = 0 |
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372 for i in range(100): |
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373 cum |= getbits(span) |
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374 self.assertEqual(cum, 2**span-1) |
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375 |
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376 # Verify argument checking |
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377 self.assertRaises(TypeError, self.gen.getrandbits) |
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378 self.assertRaises(TypeError, self.gen.getrandbits, 'a') |
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379 self.assertRaises(TypeError, self.gen.getrandbits, 1, 2) |
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380 self.assertRaises(ValueError, self.gen.getrandbits, 0) |
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381 self.assertRaises(ValueError, self.gen.getrandbits, -1) |
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382 |
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383 def test_randbelow_logic(self, _log=log, int=int): |
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384 # check bitcount transition points: 2**i and 2**(i+1)-1 |
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385 # show that: k = int(1.001 + _log(n, 2)) |
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386 # is equal to or one greater than the number of bits in n |
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387 for i in range(1, 1000): |
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388 n = 1 << i # check an exact power of two |
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389 numbits = i+1 |
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390 k = int(1.00001 + _log(n, 2)) |
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391 self.assertEqual(k, numbits) |
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392 self.assertEqual(n, 2**(k-1)) |
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393 |
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394 n += n - 1 # check 1 below the next power of two |
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395 k = int(1.00001 + _log(n, 2)) |
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396 self.assertIn(k, [numbits, numbits+1]) |
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397 self.assertTrue(2**k > n > 2**(k-2)) |
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398 |
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399 n -= n >> 15 # check a little farther below the next power of two |
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400 k = int(1.00001 + _log(n, 2)) |
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401 self.assertEqual(k, numbits) # note the stronger assertion |
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402 self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion |
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403 |
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404 def test_randrange_bug_1590891(self): |
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405 start = 1000000000000 |
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406 stop = -100000000000000000000 |
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407 step = -200 |
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408 x = self.gen.randrange(start, stop, step) |
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409 self.assertTrue(stop < x <= start) |
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410 self.assertEqual((x+stop)%step, 0) |
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411 |
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412 def gamma(z, sqrt2pi=(2.0*pi)**0.5): |
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413 # Reflection to right half of complex plane |
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414 if z < 0.5: |
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415 return pi / sin(pi*z) / gamma(1.0-z) |
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416 # Lanczos approximation with g=7 |
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417 az = z + (7.0 - 0.5) |
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418 return az ** (z-0.5) / exp(az) * sqrt2pi * fsum([ |
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419 0.9999999999995183, |
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420 676.5203681218835 / z, |
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421 -1259.139216722289 / (z+1.0), |
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422 771.3234287757674 / (z+2.0), |
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423 -176.6150291498386 / (z+3.0), |
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424 12.50734324009056 / (z+4.0), |
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425 -0.1385710331296526 / (z+5.0), |
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426 0.9934937113930748e-05 / (z+6.0), |
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427 0.1659470187408462e-06 / (z+7.0), |
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428 ]) |
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429 |
| 27092 | 430 class TestDistributions(unittest.TestCase): |
| 431 def test_zeroinputs(self): | |
| 432 # Verify that distributions can handle a series of zero inputs' | |
| 433 g = random.Random() | |
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434 x = [g.random() for i in range(50)] + [0.0]*5 |
| 27092 | 435 g.random = x[:].pop; g.uniform(1,10) |
| 436 g.random = x[:].pop; g.paretovariate(1.0) | |
| 437 g.random = x[:].pop; g.expovariate(1.0) | |
| 438 g.random = x[:].pop; g.weibullvariate(1.0, 1.0) | |
| 439 g.random = x[:].pop; g.normalvariate(0.0, 1.0) | |
| 440 g.random = x[:].pop; g.gauss(0.0, 1.0) | |
| 441 g.random = x[:].pop; g.lognormvariate(0.0, 1.0) | |
| 442 g.random = x[:].pop; g.vonmisesvariate(0.0, 1.0) | |
| 443 g.random = x[:].pop; g.gammavariate(0.01, 1.0) | |
| 444 g.random = x[:].pop; g.gammavariate(1.0, 1.0) | |
| 445 g.random = x[:].pop; g.gammavariate(200.0, 1.0) | |
| 446 g.random = x[:].pop; g.betavariate(3.0, 3.0) | |
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447 g.random = x[:].pop; g.triangular(0.0, 1.0, 1.0/3.0) |
| 27092 | 448 |
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449 def test_avg_std(self): |
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450 # Use integration to test distribution average and standard deviation. |
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451 # Only works for distributions which do not consume variates in pairs |
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452 g = random.Random() |
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453 N = 5000 |
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454 x = [i/float(N) for i in range(1,N)] |
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455 for variate, args, mu, sigmasqrd in [ |
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456 (g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12), |
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457 (g.triangular, (0.0, 1.0, 1.0/3.0), 4.0/9.0, 7.0/9.0/18.0), |
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458 (g.expovariate, (1.5,), 1/1.5, 1/1.5**2), |
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459 (g.paretovariate, (5.0,), 5.0/(5.0-1), |
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460 5.0/((5.0-1)**2*(5.0-2))), |
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461 (g.weibullvariate, (1.0, 3.0), gamma(1+1/3.0), |
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462 gamma(1+2/3.0)-gamma(1+1/3.0)**2) ]: |
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463 g.random = x[:].pop |
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464 y = [] |
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465 for i in range(len(x)): |
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466 try: |
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467 y.append(variate(*args)) |
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468 except IndexError: |
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469 pass |
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470 s1 = s2 = 0 |
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471 for e in y: |
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472 s1 += e |
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473 s2 += (e - mu) ** 2 |
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474 N = len(y) |
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475 self.assertAlmostEqual(s1/N, mu, places=2) |
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476 self.assertAlmostEqual(s2/(N-1), sigmasqrd, places=2) |
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477 |
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478 class TestModule(unittest.TestCase): |
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479 def testMagicConstants(self): |
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480 self.assertAlmostEqual(random.NV_MAGICCONST, 1.71552776992141) |
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481 self.assertAlmostEqual(random.TWOPI, 6.28318530718) |
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482 self.assertAlmostEqual(random.LOG4, 1.38629436111989) |
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483 self.assertAlmostEqual(random.SG_MAGICCONST, 2.50407739677627) |
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484 |
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485 def test__all__(self): |
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486 # tests validity but not completeness of the __all__ list |
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487 self.assertTrue(set(random.__all__) <= set(dir(random))) |
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488 |
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489 def test_random_subclass_with_kwargs(self): |
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490 # SF bug #1486663 -- this used to erroneously raise a TypeError |
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491 class Subclass(random.Random): |
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492 def __init__(self, newarg=None): |
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493 random.Random.__init__(self) |
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494 Subclass(newarg=1) |
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495 |
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496 |
| 27668 | 497 def test_main(verbose=None): |
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498 testclasses = [MersenneTwister_TestBasicOps, |
| 27092 | 499 TestDistributions, |
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500 TestModule] |
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501 |
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502 try: |
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503 random.SystemRandom().random() |
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504 except NotImplementedError: |
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505 pass |
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506 else: |
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507 testclasses.append(SystemRandom_TestBasicOps) |
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508 |
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509 support.run_unittest(*testclasses) |
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510 |
| 27668 | 511 # verify reference counting |
| 512 import sys | |
| 513 if verbose and hasattr(sys, "gettotalrefcount"): | |
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514 counts = [None] * 5 |
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515 for i in range(len(counts)): |
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516 support.run_unittest(*testclasses) |
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517 counts[i] = sys.gettotalrefcount() |
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518 print(counts) |
| 27668 | 519 |
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520 if __name__ == "__main__": |
| 27668 | 521 test_main(verbose=True) |
