annotate Lib/random.py @ 22360:c8a6ea00a9e1 legacy-trunk

restructure a bit to not rely on test case execution ordering add test case for bug #482460
author Skip Montanaro <skip@pobox.com>
date Sun, 17 Mar 2002 23:03:42 +0000
parents fed5071da957
children 899002a882a0
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1 """Random variable generators.
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2
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3 integers
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4 --------
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5 uniform within range
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6
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7 sequences
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8 ---------
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9 pick random element
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10 generate random permutation
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11
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12 distributions on the real line:
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13 ------------------------------
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14 uniform
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15 normal (Gaussian)
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16 lognormal
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17 negative exponential
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18 gamma
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19 beta
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20
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21 distributions on the circle (angles 0 to 2pi)
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22 ---------------------------------------------
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23 circular uniform
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24 von Mises
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25
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26 Translated from anonymously contributed C/C++ source.
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27
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28 Multi-threading note: the random number generator used here is not thread-
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29 safe; it is possible that two calls return the same random value. However,
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30 you can instantiate a different instance of Random() in each thread to get
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31 generators that don't share state, then use .setstate() and .jumpahead() to
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32 move the generators to disjoint segments of the full period. For example,
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33
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34 def create_generators(num, delta, firstseed=None):
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35 ""\"Return list of num distinct generators.
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36 Each generator has its own unique segment of delta elements from
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37 Random.random()'s full period.
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38 Seed the first generator with optional arg firstseed (default is
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39 None, to seed from current time).
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40 ""\"
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41
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42 from random import Random
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43 g = Random(firstseed)
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44 result = [g]
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45 for i in range(num - 1):
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46 laststate = g.getstate()
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47 g = Random()
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48 g.setstate(laststate)
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49 g.jumpahead(delta)
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50 result.append(g)
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51 return result
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52
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53 gens = create_generators(10, 1000000)
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54
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55 That creates 10 distinct generators, which can be passed out to 10 distinct
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56 threads. The generators don't share state so can be called safely in
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57 parallel. So long as no thread calls its g.random() more than a million
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58 times (the second argument to create_generators), the sequences seen by
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59 each thread will not overlap.
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60
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61 The period of the underlying Wichmann-Hill generator is 6,953,607,871,644,
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62 and that limits how far this technique can be pushed.
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63
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64 Just for fun, note that since we know the period, .jumpahead() can also be
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65 used to "move backward in time":
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66
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67 >>> g = Random(42) # arbitrary
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68 >>> g.random()
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69 0.25420336316883324
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70 >>> g.jumpahead(6953607871644L - 1) # move *back* one
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71 >>> g.random()
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72 0.25420336316883324
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73 """
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74 # XXX The docstring sucks.
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75
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76 from math import log as _log, exp as _exp, pi as _pi, e as _e
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77 from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin
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78
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79 __all__ = ["Random","seed","random","uniform","randint","choice",
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80 "randrange","shuffle","normalvariate","lognormvariate",
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81 "cunifvariate","expovariate","vonmisesvariate","gammavariate",
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82 "stdgamma","gauss","betavariate","paretovariate","weibullvariate",
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83 "getstate","setstate","jumpahead","whseed"]
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84
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85 def _verify(name, computed, expected):
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86 if abs(computed - expected) > 1e-7:
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87 raise ValueError(
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88 "computed value for %s deviates too much "
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89 "(computed %g, expected %g)" % (name, computed, expected))
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90
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91 NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0)
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92 _verify('NV_MAGICCONST', NV_MAGICCONST, 1.71552776992141)
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93
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94 TWOPI = 2.0*_pi
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95 _verify('TWOPI', TWOPI, 6.28318530718)
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96
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97 LOG4 = _log(4.0)
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98 _verify('LOG4', LOG4, 1.38629436111989)
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99
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100 SG_MAGICCONST = 1.0 + _log(4.5)
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101 _verify('SG_MAGICCONST', SG_MAGICCONST, 2.50407739677627)
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102
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103 del _verify
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104
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105 # Translated by Guido van Rossum from C source provided by
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106 # Adrian Baddeley.
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107
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108 class Random:
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109
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110 VERSION = 1 # used by getstate/setstate
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111
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112 def __init__(self, x=None):
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113 """Initialize an instance.
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114
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115 Optional argument x controls seeding, as for Random.seed().
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116 """
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117
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118 self.seed(x)
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119 self.gauss_next = None
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120
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121 ## -------------------- core generator -------------------
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122
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123 # Specific to Wichmann-Hill generator. Subclasses wishing to use a
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124 # different core generator should override the seed(), random(),
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125 # getstate(), setstate() and jumpahead() methods.
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126
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127 def seed(self, a=None):
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128 """Initialize internal state from hashable object.
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129
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130 None or no argument seeds from current time.
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131
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132 If a is not None or an int or long, hash(a) is used instead.
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133
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134 If a is an int or long, a is used directly. Distinct values between
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135 0 and 27814431486575L inclusive are guaranteed to yield distinct
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136 internal states (this guarantee is specific to the default
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137 Wichmann-Hill generator).
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138 """
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139
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140 if a is None:
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141 # Initialize from current time
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142 import time
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143 a = long(time.time() * 256)
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144
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145 if type(a) not in (type(3), type(3L)):
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146 a = hash(a)
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147
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148 a, x = divmod(a, 30268)
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149 a, y = divmod(a, 30306)
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150 a, z = divmod(a, 30322)
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151 self._seed = int(x)+1, int(y)+1, int(z)+1
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152
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153 def random(self):
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154 """Get the next random number in the range [0.0, 1.0)."""
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155
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156 # Wichman-Hill random number generator.
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157 #
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158 # Wichmann, B. A. & Hill, I. D. (1982)
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159 # Algorithm AS 183:
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160 # An efficient and portable pseudo-random number generator
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161 # Applied Statistics 31 (1982) 188-190
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162 #
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163 # see also:
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164 # Correction to Algorithm AS 183
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165 # Applied Statistics 33 (1984) 123
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166 #
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167 # McLeod, A. I. (1985)
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168 # A remark on Algorithm AS 183
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169 # Applied Statistics 34 (1985),198-200
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170
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171 # This part is thread-unsafe:
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172 # BEGIN CRITICAL SECTION
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173 x, y, z = self._seed
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174 x = (171 * x) % 30269
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175 y = (172 * y) % 30307
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176 z = (170 * z) % 30323
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177 self._seed = x, y, z
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178 # END CRITICAL SECTION
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179
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180 # Note: on a platform using IEEE-754 double arithmetic, this can
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181 # never return 0.0 (asserted by Tim; proof too long for a comment).
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182 return (x/30269.0 + y/30307.0 + z/30323.0) % 1.0
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183
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184 def getstate(self):
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185 """Return internal state; can be passed to setstate() later."""
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186 return self.VERSION, self._seed, self.gauss_next
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187
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188 def setstate(self, state):
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189 """Restore internal state from object returned by getstate()."""
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190 version = state[0]
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191 if version == 1:
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192 version, self._seed, self.gauss_next = state
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193 else:
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194 raise ValueError("state with version %s passed to "
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195 "Random.setstate() of version %s" %
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196 (version, self.VERSION))
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197
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198 def jumpahead(self, n):
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199 """Act as if n calls to random() were made, but quickly.
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200
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201 n is an int, greater than or equal to 0.
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202
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203 Example use: If you have 2 threads and know that each will
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204 consume no more than a million random numbers, create two Random
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205 objects r1 and r2, then do
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206 r2.setstate(r1.getstate())
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207 r2.jumpahead(1000000)
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208 Then r1 and r2 will use guaranteed-disjoint segments of the full
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209 period.
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210 """
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211
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212 if not n >= 0:
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213 raise ValueError("n must be >= 0")
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214 x, y, z = self._seed
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215 x = int(x * pow(171, n, 30269)) % 30269
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216 y = int(y * pow(172, n, 30307)) % 30307
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217 z = int(z * pow(170, n, 30323)) % 30323
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218 self._seed = x, y, z
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219
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220 def __whseed(self, x=0, y=0, z=0):
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221 """Set the Wichmann-Hill seed from (x, y, z).
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222
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223 These must be integers in the range [0, 256).
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224 """
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225
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226 if not type(x) == type(y) == type(z) == type(0):
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227 raise TypeError('seeds must be integers')
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228 if not (0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256):
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229 raise ValueError('seeds must be in range(0, 256)')
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230 if 0 == x == y == z:
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231 # Initialize from current time
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232 import time
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233 t = long(time.time() * 256)
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234 t = int((t&0xffffff) ^ (t>>24))
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235 t, x = divmod(t, 256)
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236 t, y = divmod(t, 256)
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237 t, z = divmod(t, 256)
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238 # Zero is a poor seed, so substitute 1
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239 self._seed = (x or 1, y or 1, z or 1)
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240
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241 def whseed(self, a=None):
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242 """Seed from hashable object's hash code.
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243
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244 None or no argument seeds from current time. It is not guaranteed
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245 that objects with distinct hash codes lead to distinct internal
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246 states.
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247
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248 This is obsolete, provided for compatibility with the seed routine
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249 used prior to Python 2.1. Use the .seed() method instead.
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250 """
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251
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252 if a is None:
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253 self.__whseed()
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254 return
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255 a = hash(a)
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256 a, x = divmod(a, 256)
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257 a, y = divmod(a, 256)
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258 a, z = divmod(a, 256)
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259 x = (x + a) % 256 or 1
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260 y = (y + a) % 256 or 1
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261 z = (z + a) % 256 or 1
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262 self.__whseed(x, y, z)
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263
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264 ## ---- Methods below this point do not need to be overridden when
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265 ## ---- subclassing for the purpose of using a different core generator.
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266
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267 ## -------------------- pickle support -------------------
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268
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269 def __getstate__(self): # for pickle
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270 return self.getstate()
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271
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272 def __setstate__(self, state): # for pickle
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273 self.setstate(state)
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274
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275 ## -------------------- integer methods -------------------
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276
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277 def randrange(self, start, stop=None, step=1, int=int, default=None):
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278 """Choose a random item from range(start, stop[, step]).
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279
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280 This fixes the problem with randint() which includes the
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281 endpoint; in Python this is usually not what you want.
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282 Do not supply the 'int' and 'default' arguments.
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283 """
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284
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285 # This code is a bit messy to make it fast for the
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286 # common case while still doing adequate error checking
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287 istart = int(start)
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288 if istart != start:
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289 raise ValueError, "non-integer arg 1 for randrange()"
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290 if stop is default:
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291 if istart > 0:
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292 return int(self.random() * istart)
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293 raise ValueError, "empty range for randrange()"
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294 istop = int(stop)
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295 if istop != stop:
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296 raise ValueError, "non-integer stop for randrange()"
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297 if step == 1:
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298 if istart < istop:
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299 return istart + int(self.random() *
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300 (istop - istart))
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301 raise ValueError, "empty range for randrange()"
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302 istep = int(step)
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303 if istep != step:
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304 raise ValueError, "non-integer step for randrange()"
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305 if istep > 0:
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306 n = (istop - istart + istep - 1) / istep
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307 elif istep < 0:
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308 n = (istop - istart + istep + 1) / istep
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309 else:
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310 raise ValueError, "zero step for randrange()"
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311
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312 if n <= 0:
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313 raise ValueError, "empty range for randrange()"
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314 return istart + istep*int(self.random() * n)
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315
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316 def randint(self, a, b):
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317 """Return random integer in range [a, b], including both end points.
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318
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319 (Deprecated; use randrange(a, b+1).)
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320 """
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321
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322 return self.randrange(a, b+1)
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323
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324 ## -------------------- sequence methods -------------------
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325
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326 def choice(self, seq):
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327 """Choose a random element from a non-empty sequence."""
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328 return seq[int(self.random() * len(seq))]
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329
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330 def shuffle(self, x, random=None, int=int):
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331 """x, random=random.random -> shuffle list x in place; return None.
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332
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333 Optional arg random is a 0-argument function returning a random
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334 float in [0.0, 1.0); by default, the standard random.random.
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335
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336 Note that for even rather small len(x), the total number of
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337 permutations of x is larger than the period of most random number
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338 generators; this implies that "most" permutations of a long
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339 sequence can never be generated.
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340 """
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341
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342 if random is None:
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343 random = self.random
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344 for i in xrange(len(x)-1, 0, -1):
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345 # pick an element in x[:i+1] with which to exchange x[i]
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346 j = int(random() * (i+1))
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347 x[i], x[j] = x[j], x[i]
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348
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349 ## -------------------- real-valued distributions -------------------
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350
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351 ## -------------------- uniform distribution -------------------
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352
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353 def uniform(self, a, b):
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354 """Get a random number in the range [a, b)."""
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355 return a + (b-a) * self.random()
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356
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357 ## -------------------- normal distribution --------------------
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358
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359 def normalvariate(self, mu, sigma):
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360 # mu = mean, sigma = standard deviation
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361
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362 # Uses Kinderman and Monahan method. Reference: Kinderman,
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363 # A.J. and Monahan, J.F., "Computer generation of random
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364 # variables using the ratio of uniform deviates", ACM Trans
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365 # Math Software, 3, (1977), pp257-260.
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366
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367 random = self.random
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368 while 1:
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369 u1 = random()
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370 u2 = random()
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371 z = NV_MAGICCONST*(u1-0.5)/u2
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372 zz = z*z/4.0
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373 if zz <= -_log(u2):
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374 break
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375 return mu + z*sigma
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376
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377 ## -------------------- lognormal distribution --------------------
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378
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379 def lognormvariate(self, mu, sigma):
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380 return _exp(self.normalvariate(mu, sigma))
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381
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382 ## -------------------- circular uniform --------------------
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383
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384 def cunifvariate(self, mean, arc):
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385 # mean: mean angle (in radians between 0 and pi)
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386 # arc: range of distribution (in radians between 0 and pi)
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387
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388 return (mean + arc * (self.random() - 0.5)) % _pi
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389
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390 ## -------------------- exponential distribution --------------------
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391
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392 def expovariate(self, lambd):
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393 # lambd: rate lambd = 1/mean
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394 # ('lambda' is a Python reserved word)
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395
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396 random = self.random
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397 u = random()
16242
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398 while u <= 1e-7:
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399 u = random()
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400 return -_log(u)/lambd
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401
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402 ## -------------------- von Mises distribution --------------------
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403
16242
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404 def vonmisesvariate(self, mu, kappa):
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parents: 15871
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405 # mu: mean angle (in radians between 0 and 2*pi)
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parents: 15871
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406 # kappa: concentration parameter kappa (>= 0)
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parents: 15871
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407 # if kappa = 0 generate uniform random angle
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408
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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409 # Based upon an algorithm published in: Fisher, N.I.,
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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410 # "Statistical Analysis of Circular Data", Cambridge
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parents: 15871
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411 # University Press, 1993.
7881
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parents: 7412
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412
16242
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parents: 15871
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413 # Thanks to Magnus Kessler for a correction to the
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414 # implementation of step 4.
7881
6370f1593c72 Correction to vonmisesvariate() by Magnus Kessler: it should take and
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415
16242
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416 random = self.random
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417 if kappa <= 1e-6:
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parents: 15871
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418 return TWOPI * random()
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419
16242
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420 a = 1.0 + _sqrt(1.0 + 4.0 * kappa * kappa)
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parents: 15871
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421 b = (a - _sqrt(2.0 * a))/(2.0 * kappa)
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422 r = (1.0 + b * b)/(2.0 * b)
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423
16242
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Tim Peters <tim.peters@gmail.com>
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424 while 1:
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
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425 u1 = random()
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426
16242
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parents: 15871
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427 z = _cos(_pi * u1)
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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428 f = (1.0 + r * z)/(r + z)
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429 c = kappa * (r - f)
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430
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431 u2 = random()
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432
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433 if not (u2 >= c * (2.0 - c) and u2 > c * _exp(1.0 - c)):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
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parents: 15871
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434 break
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435
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436 u3 = random()
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Tim Peters <tim.peters@gmail.com>
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diff changeset
437 if u3 > 0.5:
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438 theta = (mu % TWOPI) + _acos(f)
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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439 else:
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Tim Peters <tim.peters@gmail.com>
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440 theta = (mu % TWOPI) - _acos(f)
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441
16242
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442 return theta
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443
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Tim Peters <tim.peters@gmail.com>
parents: 16243
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444 ## -------------------- gamma distribution --------------------
1575
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parents:
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445
16242
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parents: 15871
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446 def gammavariate(self, alpha, beta):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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447 # beta times standard gamma
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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448 ainv = _sqrt(2.0 * alpha - 1.0)
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parents: 15871
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449 return beta * self.stdgamma(alpha, ainv, alpha - LOG4, alpha + ainv)
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parents:
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450
16242
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parents: 15871
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451 def stdgamma(self, alpha, ainv, bbb, ccc):
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parents: 15871
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452 # ainv = sqrt(2 * alpha - 1)
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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453 # bbb = alpha - log(4)
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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454 # ccc = alpha + ainv
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455
16242
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Tim Peters <tim.peters@gmail.com>
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456 random = self.random
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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457 if alpha <= 0.0:
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
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458 raise ValueError, 'stdgamma: alpha must be > 0.0'
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parents:
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459
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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460 if alpha > 1.0:
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461
16242
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parents: 15871
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462 # Uses R.C.H. Cheng, "The generation of Gamma
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
463 # variables with non-integral shape parameters",
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
464 # Applied Statistics, (1977), 26, No. 1, p71-74
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465
16242
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diff changeset
466 while 1:
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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467 u1 = random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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468 u2 = random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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469 v = _log(u1/(1.0-u1))/ainv
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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470 x = alpha*_exp(v)
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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471 z = u1*u1*u2
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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472 r = bbb+ccc*v-x
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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473 if r + SG_MAGICCONST - 4.5*z >= 0.0 or r >= _log(z):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
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474 return x
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parents:
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475
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
476 elif alpha == 1.0:
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
477 # expovariate(1)
15871
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parents: 14617
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478 u = random()
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
479 while u <= 1e-7:
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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480 u = random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
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parents: 15871
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481 return -_log(u)
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parents:
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482
16242
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parents: 15871
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483 else: # alpha is between 0 and 1 (exclusive)
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parents:
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484
16242
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parents: 15871
diff changeset
485 # Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle
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parents:
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486
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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487 while 1:
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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488 u = random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
489 b = (_e + alpha)/_e
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parents: 15871
diff changeset
490 p = b*u
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
491 if p <= 1.0:
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
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parents: 15871
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492 x = pow(p, 1.0/alpha)
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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493 else:
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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494 # p > 1
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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495 x = -_log((b-p)/alpha)
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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496 u1 = random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
497 if not (((p <= 1.0) and (u1 > _exp(-x))) or
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
498 ((p > 1) and (u1 > pow(x, alpha - 1.0)))):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
499 break
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
500 return x
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parents:
diff changeset
501
1576
695fb494a3a2 Added gauss() (same as normal but twice as fast) and betavariate();
Guido van Rossum <guido@python.org>
parents: 1575
diff changeset
502
16265
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
503 ## -------------------- Gauss (faster alternative) --------------------
1576
695fb494a3a2 Added gauss() (same as normal but twice as fast) and betavariate();
Guido van Rossum <guido@python.org>
parents: 1575
diff changeset
504
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
505 def gauss(self, mu, sigma):
1577
444e349f962f Use float constants directly; cosmetic changes; initialize largest
Guido van Rossum <guido@python.org>
parents: 1576
diff changeset
506
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
507 # When x and y are two variables from [0, 1), uniformly
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
508 # distributed, then
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
509 #
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
510 # cos(2*pi*x)*sqrt(-2*log(1-y))
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
511 # sin(2*pi*x)*sqrt(-2*log(1-y))
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Tim Peters <tim.peters@gmail.com>
parents: 15871
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512 #
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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513 # are two *independent* variables with normal distribution
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
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514 # (mu = 0, sigma = 1).
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
515 # (Lambert Meertens)
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
516 # (corrected version; bug discovered by Mike Miller, fixed by LM)
1577
444e349f962f Use float constants directly; cosmetic changes; initialize largest
Guido van Rossum <guido@python.org>
parents: 1576
diff changeset
517
16242
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Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
518 # Multithreading note: When two threads call this function
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
519 # simultaneously, it is possible that they will receive the
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
520 # same return value. The window is very small though. To
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
521 # avoid this, you have to use a lock around all calls. (I
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
522 # didn't want to slow this down in the serial case by using a
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
523 # lock here.)
1577
444e349f962f Use float constants directly; cosmetic changes; initialize largest
Guido van Rossum <guido@python.org>
parents: 1576
diff changeset
524
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
525 random = self.random
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
526 z = self.gauss_next
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
527 self.gauss_next = None
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
528 if z is None:
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
529 x2pi = random() * TWOPI
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
530 g2rad = _sqrt(-2.0 * _log(1.0 - random()))
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
531 z = _cos(x2pi) * g2rad
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
532 self.gauss_next = _sin(x2pi) * g2rad
1577
444e349f962f Use float constants directly; cosmetic changes; initialize largest
Guido van Rossum <guido@python.org>
parents: 1576
diff changeset
533
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
534 return mu + z*sigma
1576
695fb494a3a2 Added gauss() (same as normal but twice as fast) and betavariate();
Guido van Rossum <guido@python.org>
parents: 1575
diff changeset
535
16265
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
536 ## -------------------- beta --------------------
16271
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
537 ## See
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
538 ## http://sourceforge.net/bugs/?func=detailbug&bug_id=130030&group_id=5470
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
539 ## for Ivan Frohne's insightful analysis of why the original implementation:
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
540 ##
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
541 ## def betavariate(self, alpha, beta):
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
542 ## # Discrete Event Simulation in C, pp 87-88.
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
543 ##
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
544 ## y = self.expovariate(alpha)
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
545 ## z = self.expovariate(1.0/beta)
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
546 ## return z/(y+z)
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
547 ##
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
548 ## was dead wrong, and how it probably got that way.
1576
695fb494a3a2 Added gauss() (same as normal but twice as fast) and betavariate();
Guido van Rossum <guido@python.org>
parents: 1575
diff changeset
549
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
550 def betavariate(self, alpha, beta):
16271
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
551 # This version due to Janne Sinkkonen, and matches all the std
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
552 # texts (e.g., Knuth Vol 2 Ed 3 pg 134 "the beta distribution").
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
553 y = self.gammavariate(alpha, 1.)
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
554 if y == 0:
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
555 return 0.0
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
556 else:
7ef2382f6123 SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents: 16265
diff changeset
557 return y / (y + self.gammavariate(beta, 1.))
1576
695fb494a3a2 Added gauss() (same as normal but twice as fast) and betavariate();
Guido van Rossum <guido@python.org>
parents: 1575
diff changeset
558
16265
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
559 ## -------------------- Pareto --------------------
6698
b73eb4e6face Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
Guido van Rossum <guido@python.org>
parents: 1618
diff changeset
560
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
561 def paretovariate(self, alpha):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
562 # Jain, pg. 495
6698
b73eb4e6face Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
Guido van Rossum <guido@python.org>
parents: 1618
diff changeset
563
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
564 u = self.random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
565 return 1.0 / pow(u, 1.0/alpha)
6698
b73eb4e6face Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
Guido van Rossum <guido@python.org>
parents: 1618
diff changeset
566
16265
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
567 ## -------------------- Weibull --------------------
6698
b73eb4e6face Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
Guido van Rossum <guido@python.org>
parents: 1618
diff changeset
568
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
569 def weibullvariate(self, alpha, beta):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
570 # Jain, pg. 499; bug fix courtesy Bill Arms
11200
bca2d14f3e36 Add Tim Peters' shuffle() algorithm.
Guido van Rossum <guido@python.org>
parents: 8802
diff changeset
571
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
572 u = self.random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
573 return alpha * pow(-_log(u), 1.0/beta)
11200
bca2d14f3e36 Add Tim Peters' shuffle() algorithm.
Guido van Rossum <guido@python.org>
parents: 8802
diff changeset
574
16265
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
575 ## -------------------- test program --------------------
1575
45728bfecb76 Random variable generators
Guido van Rossum <guido@python.org>
parents:
diff changeset
576
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
577 def _test_generator(n, funccall):
15871
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
578 import time
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
579 print n, 'times', funccall
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
580 code = compile(funccall, funccall, 'eval')
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
581 sum = 0.0
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
582 sqsum = 0.0
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
583 smallest = 1e10
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
584 largest = -1e10
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
585 t0 = time.time()
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
586 for i in range(n):
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
587 x = eval(code)
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
588 sum = sum + x
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
589 sqsum = sqsum + x*x
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
590 smallest = min(x, smallest)
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
591 largest = max(x, largest)
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
592 t1 = time.time()
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
593 print round(t1-t0, 3), 'sec,',
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
594 avg = sum/n
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
595 stddev = _sqrt(sqsum/n - avg*avg)
15871
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
596 print 'avg %g, stddev %g, min %g, max %g' % \
62aeefa01fdd Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents: 14617
diff changeset
597 (avg, stddev, smallest, largest)
1575
45728bfecb76 Random variable generators
Guido van Rossum <guido@python.org>
parents:
diff changeset
598
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
599 def _test(N=200):
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
600 print 'TWOPI =', TWOPI
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
601 print 'LOG4 =', LOG4
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
602 print 'NV_MAGICCONST =', NV_MAGICCONST
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
603 print 'SG_MAGICCONST =', SG_MAGICCONST
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
604 _test_generator(N, 'random()')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
605 _test_generator(N, 'normalvariate(0.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
606 _test_generator(N, 'lognormvariate(0.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
607 _test_generator(N, 'cunifvariate(0.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
608 _test_generator(N, 'expovariate(1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
609 _test_generator(N, 'vonmisesvariate(0.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
610 _test_generator(N, 'gammavariate(0.5, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
611 _test_generator(N, 'gammavariate(0.9, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
612 _test_generator(N, 'gammavariate(1.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
613 _test_generator(N, 'gammavariate(2.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
614 _test_generator(N, 'gammavariate(20.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
615 _test_generator(N, 'gammavariate(200.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
616 _test_generator(N, 'gauss(0.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
617 _test_generator(N, 'betavariate(3.0, 3.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
618 _test_generator(N, 'paretovariate(1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
619 _test_generator(N, 'weibullvariate(1.0, 1.0)')
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
620
16265
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
621 # Test jumpahead.
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
622 s = getstate()
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
623 jumpahead(N)
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
624 r1 = random()
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
625 # now do it the slow way
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
626 setstate(s)
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
627 for i in range(N):
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
628 random()
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
629 r2 = random()
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
630 if r1 != r2:
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
631 raise ValueError("jumpahead test failed " + `(N, r1, r2)`)
d614b6e9fb4e Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents: 16243
diff changeset
632
16292
0501c2a10315 New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents: 16272
diff changeset
633 # Create one instance, seeded from current time, and export its methods
0501c2a10315 New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents: 16272
diff changeset
634 # as module-level functions. The functions are not threadsafe, and state
0501c2a10315 New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents: 16272
diff changeset
635 # is shared across all uses (both in the user's code and in the Python
0501c2a10315 New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents: 16272
diff changeset
636 # libraries), but that's fine for most programs and is easier for the
0501c2a10315 New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents: 16272
diff changeset
637 # casual user than making them instantiate their own Random() instance.
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
638 _inst = Random()
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
639 seed = _inst.seed
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
640 random = _inst.random
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
641 uniform = _inst.uniform
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
642 randint = _inst.randint
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
643 choice = _inst.choice
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
644 randrange = _inst.randrange
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
645 shuffle = _inst.shuffle
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
646 normalvariate = _inst.normalvariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
647 lognormvariate = _inst.lognormvariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
648 cunifvariate = _inst.cunifvariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
649 expovariate = _inst.expovariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
650 vonmisesvariate = _inst.vonmisesvariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
651 gammavariate = _inst.gammavariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
652 stdgamma = _inst.stdgamma
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
653 gauss = _inst.gauss
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
654 betavariate = _inst.betavariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
655 paretovariate = _inst.paretovariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
656 weibullvariate = _inst.weibullvariate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
657 getstate = _inst.getstate
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
658 setstate = _inst.setstate
16243
9fd96e2455b6 Fix bugs introduced by rewrite (in particular, time-based initialization
Tim Peters <tim.peters@gmail.com>
parents: 16242
diff changeset
659 jumpahead = _inst.jumpahead
16379
5f0683a69efc Change random.seed() so that it can get at the full range of possible
Tim Peters <tim.peters@gmail.com>
parents: 16292
diff changeset
660 whseed = _inst.whseed
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
661
1575
45728bfecb76 Random variable generators
Guido van Rossum <guido@python.org>
parents:
diff changeset
662 if __name__ == '__main__':
16242
3c5f09422b69 Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents: 15871
diff changeset
663 _test()