Mercurial > cpython-lru_cache-weakref
annotate Lib/test/test_random.py @ 79691:05c8928362ee
Merge __next__ method link fixes with 3.3.
| author | Ezio Melotti <ezio.melotti@gmail.com> |
|---|---|
| date | Fri, 12 Oct 2012 13:46:37 +0300 |
| parents | 62d9f1285f51 |
| children | e9b4f2927412 58776cc74e89 |
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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 # Seed value with a negative hash. |
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38 class MySeed(object): |
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39 def __hash__(self): |
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40 return -1729 |
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41 for arg in [None, 0, 0, 1, 1, -1, -1, 10**20, -(10**20), |
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42 3.14, 1+2j, 'a', tuple('abc'), MySeed()]: |
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43 self.gen.seed(arg) |
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44 for arg in [list(range(3)), dict(one=1)]: |
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45 self.assertRaises(TypeError, self.gen.seed, arg) |
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46 self.assertRaises(TypeError, self.gen.seed, 1, 2, 3, 4) |
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47 self.assertRaises(TypeError, type(self.gen), []) |
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48 |
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49 def test_choice(self): |
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50 choice = self.gen.choice |
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51 with self.assertRaises(IndexError): |
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52 choice([]) |
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53 self.assertEqual(choice([50]), 50) |
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54 self.assertIn(choice([25, 75]), [25, 75]) |
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55 |
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56 def test_sample(self): |
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57 # For the entire allowable range of 0 <= k <= N, validate that |
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58 # the sample is of the correct length and contains only unique items |
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59 N = 100 |
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60 population = range(N) |
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61 for k in range(N+1): |
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62 s = self.gen.sample(population, k) |
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63 self.assertEqual(len(s), k) |
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64 uniq = set(s) |
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65 self.assertEqual(len(uniq), k) |
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66 self.assertTrue(uniq <= set(population)) |
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67 self.assertEqual(self.gen.sample([], 0), []) # test edge case N==k==0 |
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68 |
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69 def test_sample_distribution(self): |
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70 # For the entire allowable range of 0 <= k <= N, validate that |
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71 # sample generates all possible permutations |
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72 n = 5 |
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73 pop = range(n) |
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74 trials = 10000 # large num prevents false negatives without slowing normal case |
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75 def factorial(n): |
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76 if n == 0: |
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77 return 1 |
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78 return n * factorial(n - 1) |
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79 for k in range(n): |
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80 expected = factorial(n) // factorial(n-k) |
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81 perms = {} |
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82 for i in range(trials): |
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83 perms[tuple(self.gen.sample(pop, k))] = None |
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84 if len(perms) == expected: |
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85 break |
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86 else: |
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87 self.fail() |
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88 |
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89 def test_sample_inputs(self): |
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90 # SF bug #801342 -- population can be any iterable defining __len__() |
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91 self.gen.sample(set(range(20)), 2) |
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92 self.gen.sample(range(20), 2) |
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93 self.gen.sample(range(20), 2) |
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94 self.gen.sample(str('abcdefghijklmnopqrst'), 2) |
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95 self.gen.sample(tuple('abcdefghijklmnopqrst'), 2) |
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96 |
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97 def test_sample_on_dicts(self): |
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98 self.assertRaises(TypeError, self.gen.sample, dict.fromkeys('abcdef'), 2) |
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99 |
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100 def test_gauss(self): |
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101 # Ensure that the seed() method initializes all the hidden state. In |
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102 # particular, through 2.2.1 it failed to reset a piece of state used |
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103 # by (and only by) the .gauss() method. |
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104 |
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105 for seed in 1, 12, 123, 1234, 12345, 123456, 654321: |
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106 self.gen.seed(seed) |
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107 x1 = self.gen.random() |
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108 y1 = self.gen.gauss(0, 1) |
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109 |
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110 self.gen.seed(seed) |
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111 x2 = self.gen.random() |
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112 y2 = self.gen.gauss(0, 1) |
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113 |
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114 self.assertEqual(x1, x2) |
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115 self.assertEqual(y1, y2) |
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116 |
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117 def test_pickling(self): |
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118 state = pickle.dumps(self.gen) |
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119 origseq = [self.gen.random() for i in range(10)] |
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120 newgen = pickle.loads(state) |
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121 restoredseq = [newgen.random() for i in range(10)] |
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122 self.assertEqual(origseq, restoredseq) |
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123 |
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124 def test_bug_1727780(self): |
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125 # verify that version-2-pickles can be loaded |
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126 # fine, whether they are created on 32-bit or 64-bit |
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127 # platforms, and that version-3-pickles load fine. |
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128 files = [("randv2_32.pck", 780), |
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129 ("randv2_64.pck", 866), |
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130 ("randv3.pck", 343)] |
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131 for file, value in files: |
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132 f = open(support.findfile(file),"rb") |
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133 r = pickle.load(f) |
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134 f.close() |
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135 self.assertEqual(int(r.random()*1000), value) |
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136 |
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137 def test_bug_9025(self): |
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138 # Had problem with an uneven distribution in int(n*random()) |
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139 # Verify the fix by checking that distributions fall within expectations. |
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140 n = 100000 |
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141 randrange = self.gen.randrange |
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142 k = sum(randrange(6755399441055744) % 3 == 2 for i in range(n)) |
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143 self.assertTrue(0.30 < k/n < .37, (k/n)) |
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144 |
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145 class SystemRandom_TestBasicOps(TestBasicOps): |
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146 gen = random.SystemRandom() |
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147 |
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148 def test_autoseed(self): |
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149 # Doesn't need to do anything except not fail |
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150 self.gen.seed() |
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151 |
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152 def test_saverestore(self): |
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153 self.assertRaises(NotImplementedError, self.gen.getstate) |
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154 self.assertRaises(NotImplementedError, self.gen.setstate, None) |
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155 |
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156 def test_seedargs(self): |
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157 # Doesn't need to do anything except not fail |
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158 self.gen.seed(100) |
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159 |
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160 def test_gauss(self): |
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161 self.gen.gauss_next = None |
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162 self.gen.seed(100) |
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163 self.assertEqual(self.gen.gauss_next, None) |
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164 |
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165 def test_pickling(self): |
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166 self.assertRaises(NotImplementedError, pickle.dumps, self.gen) |
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167 |
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168 def test_53_bits_per_float(self): |
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169 # This should pass whenever a C double has 53 bit precision. |
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170 span = 2 ** 53 |
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171 cum = 0 |
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172 for i in range(100): |
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173 cum |= int(self.gen.random() * span) |
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174 self.assertEqual(cum, span-1) |
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175 |
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176 def test_bigrand(self): |
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177 # The randrange routine should build-up the required number of bits |
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178 # in stages so that all bit positions are active. |
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179 span = 2 ** 500 |
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180 cum = 0 |
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181 for i in range(100): |
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182 r = self.gen.randrange(span) |
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183 self.assertTrue(0 <= r < span) |
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184 cum |= r |
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185 self.assertEqual(cum, span-1) |
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186 |
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187 def test_bigrand_ranges(self): |
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188 for i in [40,80, 160, 200, 211, 250, 375, 512, 550]: |
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189 start = self.gen.randrange(2 ** i) |
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190 stop = self.gen.randrange(2 ** (i-2)) |
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191 if stop <= start: |
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192 return |
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193 self.assertTrue(start <= self.gen.randrange(start, stop) < stop) |
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194 |
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195 def test_rangelimits(self): |
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196 for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]: |
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197 self.assertEqual(set(range(start,stop)), |
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198 set([self.gen.randrange(start,stop) for i in range(100)])) |
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199 |
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200 def test_genrandbits(self): |
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201 # Verify ranges |
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202 for k in range(1, 1000): |
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203 self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k) |
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204 |
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205 # Verify all bits active |
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206 getbits = self.gen.getrandbits |
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207 for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]: |
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208 cum = 0 |
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209 for i in range(100): |
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210 cum |= getbits(span) |
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211 self.assertEqual(cum, 2**span-1) |
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212 |
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213 # Verify argument checking |
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214 self.assertRaises(TypeError, self.gen.getrandbits) |
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215 self.assertRaises(TypeError, self.gen.getrandbits, 1, 2) |
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216 self.assertRaises(ValueError, self.gen.getrandbits, 0) |
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217 self.assertRaises(ValueError, self.gen.getrandbits, -1) |
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218 self.assertRaises(TypeError, self.gen.getrandbits, 10.1) |
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219 |
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220 def test_randbelow_logic(self, _log=log, int=int): |
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221 # check bitcount transition points: 2**i and 2**(i+1)-1 |
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222 # show that: k = int(1.001 + _log(n, 2)) |
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223 # is equal to or one greater than the number of bits in n |
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224 for i in range(1, 1000): |
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225 n = 1 << i # check an exact power of two |
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226 numbits = i+1 |
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227 k = int(1.00001 + _log(n, 2)) |
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228 self.assertEqual(k, numbits) |
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229 self.assertEqual(n, 2**(k-1)) |
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230 |
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231 n += n - 1 # check 1 below the next power of two |
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232 k = int(1.00001 + _log(n, 2)) |
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233 self.assertIn(k, [numbits, numbits+1]) |
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234 self.assertTrue(2**k > n > 2**(k-2)) |
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235 |
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236 n -= n >> 15 # check a little farther below the next power of two |
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237 k = int(1.00001 + _log(n, 2)) |
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238 self.assertEqual(k, numbits) # note the stronger assertion |
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239 self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion |
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240 |
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241 |
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242 class MersenneTwister_TestBasicOps(TestBasicOps): |
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243 gen = random.Random() |
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244 |
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245 def test_guaranteed_stable(self): |
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246 # These sequences are guaranteed to stay the same across versions of python |
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247 self.gen.seed(3456147, version=1) |
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248 self.assertEqual([self.gen.random().hex() for i in range(4)], |
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249 ['0x1.ac362300d90d2p-1', '0x1.9d16f74365005p-1', |
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250 '0x1.1ebb4352e4c4dp-1', '0x1.1a7422abf9c11p-1']) |
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251 self.gen.seed("the quick brown fox", version=2) |
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252 self.assertEqual([self.gen.random().hex() for i in range(4)], |
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253 ['0x1.1239ddfb11b7cp-3', '0x1.b3cbb5c51b120p-4', |
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254 '0x1.8c4f55116b60fp-1', '0x1.63eb525174a27p-1']) |
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255 |
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256 def test_setstate_first_arg(self): |
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257 self.assertRaises(ValueError, self.gen.setstate, (1, None, None)) |
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258 |
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259 def test_setstate_middle_arg(self): |
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260 # Wrong type, s/b tuple |
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261 self.assertRaises(TypeError, self.gen.setstate, (2, None, None)) |
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262 # Wrong length, s/b 625 |
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263 self.assertRaises(ValueError, self.gen.setstate, (2, (1,2,3), None)) |
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264 # Wrong type, s/b tuple of 625 ints |
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265 self.assertRaises(TypeError, self.gen.setstate, (2, ('a',)*625, None)) |
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266 # Last element s/b an int also |
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267 self.assertRaises(TypeError, self.gen.setstate, (2, (0,)*624+('a',), None)) |
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268 |
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269 def test_referenceImplementation(self): |
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270 # Compare the python implementation with results from the original |
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271 # code. Create 2000 53-bit precision random floats. Compare only |
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272 # the last ten entries to show that the independent implementations |
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273 # are tracking. Here is the main() function needed to create the |
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274 # list of expected random numbers: |
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275 # void main(void){ |
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276 # int i; |
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277 # unsigned long init[4]={61731, 24903, 614, 42143}, length=4; |
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278 # init_by_array(init, length); |
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279 # for (i=0; i<2000; i++) { |
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280 # printf("%.15f ", genrand_res53()); |
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281 # if (i%5==4) printf("\n"); |
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282 # } |
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283 # } |
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284 expected = [0.45839803073713259, |
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285 0.86057815201978782, |
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286 0.92848331726782152, |
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287 0.35932681119782461, |
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288 0.081823493762449573, |
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289 0.14332226470169329, |
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290 0.084297823823520024, |
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291 0.53814864671831453, |
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292 0.089215024911993401, |
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293 0.78486196105372907] |
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294 |
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295 self.gen.seed(61731 + (24903<<32) + (614<<64) + (42143<<96)) |
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296 actual = self.randomlist(2000)[-10:] |
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297 for a, e in zip(actual, expected): |
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298 self.assertAlmostEqual(a,e,places=14) |
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299 |
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300 def test_strong_reference_implementation(self): |
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301 # Like test_referenceImplementation, but checks for exact bit-level |
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302 # equality. This should pass on any box where C double contains |
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303 # at least 53 bits of precision (the underlying algorithm suffers |
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304 # no rounding errors -- all results are exact). |
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305 from math import ldexp |
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306 |
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307 expected = [0x0eab3258d2231f, |
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308 0x1b89db315277a5, |
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309 0x1db622a5518016, |
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310 0x0b7f9af0d575bf, |
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311 0x029e4c4db82240, |
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312 0x04961892f5d673, |
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313 0x02b291598e4589, |
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314 0x11388382c15694, |
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315 0x02dad977c9e1fe, |
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316 0x191d96d4d334c6] |
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317 self.gen.seed(61731 + (24903<<32) + (614<<64) + (42143<<96)) |
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318 actual = self.randomlist(2000)[-10:] |
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319 for a, e in zip(actual, expected): |
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320 self.assertEqual(int(ldexp(a, 53)), e) |
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321 |
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322 def test_long_seed(self): |
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323 # This is most interesting to run in debug mode, just to make sure |
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324 # nothing blows up. Under the covers, a dynamically resized array |
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325 # is allocated, consuming space proportional to the number of bits |
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326 # in the seed. Unfortunately, that's a quadratic-time algorithm, |
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327 # so don't make this horribly big. |
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328 seed = (1 << (10000 * 8)) - 1 # about 10K bytes |
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329 self.gen.seed(seed) |
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330 |
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331 def test_53_bits_per_float(self): |
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332 # This should pass whenever a C double has 53 bit precision. |
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333 span = 2 ** 53 |
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334 cum = 0 |
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335 for i in range(100): |
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336 cum |= int(self.gen.random() * span) |
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337 self.assertEqual(cum, span-1) |
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338 |
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339 def test_bigrand(self): |
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340 # The randrange routine should build-up the required number of bits |
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341 # in stages so that all bit positions are active. |
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342 span = 2 ** 500 |
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343 cum = 0 |
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344 for i in range(100): |
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345 r = self.gen.randrange(span) |
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346 self.assertTrue(0 <= r < span) |
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347 cum |= r |
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348 self.assertEqual(cum, span-1) |
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349 |
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350 def test_bigrand_ranges(self): |
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351 for i in [40,80, 160, 200, 211, 250, 375, 512, 550]: |
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352 start = self.gen.randrange(2 ** i) |
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353 stop = self.gen.randrange(2 ** (i-2)) |
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354 if stop <= start: |
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355 return |
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356 self.assertTrue(start <= self.gen.randrange(start, stop) < stop) |
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357 |
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358 def test_rangelimits(self): |
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359 for start, stop in [(-2,0), (-(2**60)-2,-(2**60)), (2**60,2**60+2)]: |
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360 self.assertEqual(set(range(start,stop)), |
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361 set([self.gen.randrange(start,stop) for i in range(100)])) |
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362 |
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363 def test_genrandbits(self): |
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364 # Verify cross-platform repeatability |
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365 self.gen.seed(1234567) |
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366 self.assertEqual(self.gen.getrandbits(100), |
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367 97904845777343510404718956115) |
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368 # Verify ranges |
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369 for k in range(1, 1000): |
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370 self.assertTrue(0 <= self.gen.getrandbits(k) < 2**k) |
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371 |
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372 # Verify all bits active |
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373 getbits = self.gen.getrandbits |
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374 for span in [1, 2, 3, 4, 31, 32, 32, 52, 53, 54, 119, 127, 128, 129]: |
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375 cum = 0 |
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376 for i in range(100): |
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377 cum |= getbits(span) |
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378 self.assertEqual(cum, 2**span-1) |
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379 |
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380 # Verify argument checking |
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381 self.assertRaises(TypeError, self.gen.getrandbits) |
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382 self.assertRaises(TypeError, self.gen.getrandbits, 'a') |
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383 self.assertRaises(TypeError, self.gen.getrandbits, 1, 2) |
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384 self.assertRaises(ValueError, self.gen.getrandbits, 0) |
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385 self.assertRaises(ValueError, self.gen.getrandbits, -1) |
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386 |
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387 def test_randbelow_logic(self, _log=log, int=int): |
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388 # check bitcount transition points: 2**i and 2**(i+1)-1 |
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389 # show that: k = int(1.001 + _log(n, 2)) |
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390 # is equal to or one greater than the number of bits in n |
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391 for i in range(1, 1000): |
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392 n = 1 << i # check an exact power of two |
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393 numbits = i+1 |
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394 k = int(1.00001 + _log(n, 2)) |
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395 self.assertEqual(k, numbits) |
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396 self.assertEqual(n, 2**(k-1)) |
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397 |
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398 n += n - 1 # check 1 below the next power of two |
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399 k = int(1.00001 + _log(n, 2)) |
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400 self.assertIn(k, [numbits, numbits+1]) |
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401 self.assertTrue(2**k > n > 2**(k-2)) |
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402 |
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403 n -= n >> 15 # check a little farther below the next power of two |
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404 k = int(1.00001 + _log(n, 2)) |
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405 self.assertEqual(k, numbits) # note the stronger assertion |
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406 self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion |
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407 |
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408 def test_randrange_bug_1590891(self): |
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409 start = 1000000000000 |
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410 stop = -100000000000000000000 |
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411 step = -200 |
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412 x = self.gen.randrange(start, stop, step) |
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413 self.assertTrue(stop < x <= start) |
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414 self.assertEqual((x+stop)%step, 0) |
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415 |
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416 def gamma(z, sqrt2pi=(2.0*pi)**0.5): |
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417 # Reflection to right half of complex plane |
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418 if z < 0.5: |
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419 return pi / sin(pi*z) / gamma(1.0-z) |
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420 # Lanczos approximation with g=7 |
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421 az = z + (7.0 - 0.5) |
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422 return az ** (z-0.5) / exp(az) * sqrt2pi * fsum([ |
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423 0.9999999999995183, |
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424 676.5203681218835 / z, |
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425 -1259.139216722289 / (z+1.0), |
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426 771.3234287757674 / (z+2.0), |
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427 -176.6150291498386 / (z+3.0), |
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428 12.50734324009056 / (z+4.0), |
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429 -0.1385710331296526 / (z+5.0), |
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430 0.9934937113930748e-05 / (z+6.0), |
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431 0.1659470187408462e-06 / (z+7.0), |
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432 ]) |
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433 |
| 27092 | 434 class TestDistributions(unittest.TestCase): |
| 435 def test_zeroinputs(self): | |
| 436 # Verify that distributions can handle a series of zero inputs' | |
| 437 g = random.Random() | |
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438 x = [g.random() for i in range(50)] + [0.0]*5 |
| 27092 | 439 g.random = x[:].pop; g.uniform(1,10) |
| 440 g.random = x[:].pop; g.paretovariate(1.0) | |
| 441 g.random = x[:].pop; g.expovariate(1.0) | |
| 442 g.random = x[:].pop; g.weibullvariate(1.0, 1.0) | |
| 443 g.random = x[:].pop; g.normalvariate(0.0, 1.0) | |
| 444 g.random = x[:].pop; g.gauss(0.0, 1.0) | |
| 445 g.random = x[:].pop; g.lognormvariate(0.0, 1.0) | |
| 446 g.random = x[:].pop; g.vonmisesvariate(0.0, 1.0) | |
| 447 g.random = x[:].pop; g.gammavariate(0.01, 1.0) | |
| 448 g.random = x[:].pop; g.gammavariate(1.0, 1.0) | |
| 449 g.random = x[:].pop; g.gammavariate(200.0, 1.0) | |
| 450 g.random = x[:].pop; g.betavariate(3.0, 3.0) | |
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451 g.random = x[:].pop; g.triangular(0.0, 1.0, 1.0/3.0) |
| 27092 | 452 |
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453 def test_avg_std(self): |
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454 # Use integration to test distribution average and standard deviation. |
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455 # Only works for distributions which do not consume variates in pairs |
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456 g = random.Random() |
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457 N = 5000 |
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458 x = [i/float(N) for i in range(1,N)] |
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459 for variate, args, mu, sigmasqrd in [ |
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460 (g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12), |
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461 (g.triangular, (0.0, 1.0, 1.0/3.0), 4.0/9.0, 7.0/9.0/18.0), |
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462 (g.expovariate, (1.5,), 1/1.5, 1/1.5**2), |
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463 (g.paretovariate, (5.0,), 5.0/(5.0-1), |
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464 5.0/((5.0-1)**2*(5.0-2))), |
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465 (g.weibullvariate, (1.0, 3.0), gamma(1+1/3.0), |
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466 gamma(1+2/3.0)-gamma(1+1/3.0)**2) ]: |
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467 g.random = x[:].pop |
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468 y = [] |
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469 for i in range(len(x)): |
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470 try: |
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471 y.append(variate(*args)) |
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472 except IndexError: |
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473 pass |
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474 s1 = s2 = 0 |
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475 for e in y: |
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476 s1 += e |
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477 s2 += (e - mu) ** 2 |
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478 N = len(y) |
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479 self.assertAlmostEqual(s1/N, mu, places=2) |
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480 self.assertAlmostEqual(s2/(N-1), sigmasqrd, places=2) |
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481 |
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482 class TestModule(unittest.TestCase): |
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483 def testMagicConstants(self): |
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484 self.assertAlmostEqual(random.NV_MAGICCONST, 1.71552776992141) |
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485 self.assertAlmostEqual(random.TWOPI, 6.28318530718) |
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486 self.assertAlmostEqual(random.LOG4, 1.38629436111989) |
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487 self.assertAlmostEqual(random.SG_MAGICCONST, 2.50407739677627) |
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488 |
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489 def test__all__(self): |
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490 # tests validity but not completeness of the __all__ list |
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491 self.assertTrue(set(random.__all__) <= set(dir(random))) |
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492 |
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493 def test_random_subclass_with_kwargs(self): |
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494 # SF bug #1486663 -- this used to erroneously raise a TypeError |
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495 class Subclass(random.Random): |
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496 def __init__(self, newarg=None): |
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497 random.Random.__init__(self) |
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498 Subclass(newarg=1) |
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499 |
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500 |
| 27668 | 501 def test_main(verbose=None): |
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502 testclasses = [MersenneTwister_TestBasicOps, |
| 27092 | 503 TestDistributions, |
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504 TestModule] |
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505 |
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506 try: |
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507 random.SystemRandom().random() |
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508 except NotImplementedError: |
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509 pass |
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510 else: |
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511 testclasses.append(SystemRandom_TestBasicOps) |
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512 |
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513 support.run_unittest(*testclasses) |
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514 |
| 27668 | 515 # verify reference counting |
| 516 import sys | |
| 517 if verbose and hasattr(sys, "gettotalrefcount"): | |
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518 counts = [None] * 5 |
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519 for i in range(len(counts)): |
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520 support.run_unittest(*testclasses) |
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521 counts[i] = sys.gettotalrefcount() |
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522 print(counts) |
| 27668 | 523 |
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524 if __name__ == "__main__": |
| 27668 | 525 test_main(verbose=True) |
