Mercurial > cpython-lru_cache-weakref
annotate Lib/random.py @ 38664:7619216bbc19 2.4
Bug #1502728: Correctly link against librt library on HP-UX.
(backport from rev. 46743)
| author | Georg Brandl <georg@python.org> |
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| date | Thu, 08 Jun 2006 12:54:16 +0000 |
| parents | f05bd98d935d |
| children | 195a0d3eecd4 |
| rev | line source |
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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 pick random sample |
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11 generate random permutation |
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12 |
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13 distributions on the real line: |
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14 ------------------------------ |
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15 uniform |
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16 normal (Gaussian) |
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17 lognormal |
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18 negative exponential |
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19 gamma |
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20 beta |
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21 pareto |
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22 Weibull |
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24 distributions on the circle (angles 0 to 2pi) |
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25 --------------------------------------------- |
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26 circular uniform |
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27 von Mises |
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29 General notes on the underlying Mersenne Twister core generator: |
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30 |
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31 * The period is 2**19937-1. |
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32 * It is one of the most extensively tested generators in existence |
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33 * Without a direct way to compute N steps forward, the |
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34 semantics of jumpahead(n) are weakened to simply jump |
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35 to another distant state and rely on the large period |
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36 to avoid overlapping sequences. |
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37 * The random() method is implemented in C, executes in |
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38 a single Python step, and is, therefore, threadsafe. |
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39 |
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40 """ |
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41 |
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42 from warnings import warn as _warn |
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43 from types import MethodType as _MethodType, BuiltinMethodType as _BuiltinMethodType |
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44 from math import log as _log, exp as _exp, pi as _pi, e as _e |
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45 from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin |
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46 from os import urandom as _urandom |
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47 from binascii import hexlify as _hexlify |
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48 |
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49 __all__ = ["Random","seed","random","uniform","randint","choice","sample", |
| 16613 | 50 "randrange","shuffle","normalvariate","lognormvariate", |
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51 "expovariate","vonmisesvariate","gammavariate", |
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52 "gauss","betavariate","paretovariate","weibullvariate", |
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53 "getstate","setstate","jumpahead", "WichmannHill", "getrandbits", |
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54 "SystemRandom"] |
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56 NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0) |
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57 TWOPI = 2.0*_pi |
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58 LOG4 = _log(4.0) |
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59 SG_MAGICCONST = 1.0 + _log(4.5) |
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60 BPF = 53 # Number of bits in a float |
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61 RECIP_BPF = 2**-BPF |
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62 |
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63 |
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64 # Translated by Guido van Rossum from C source provided by |
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65 # Adrian Baddeley. Adapted by Raymond Hettinger for use with |
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66 # the Mersenne Twister and os.urandom() core generators. |
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67 |
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68 import _random |
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69 |
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70 class Random(_random.Random): |
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71 """Random number generator base class used by bound module functions. |
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72 |
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73 Used to instantiate instances of Random to get generators that don't |
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74 share state. Especially useful for multi-threaded programs, creating |
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75 a different instance of Random for each thread, and using the jumpahead() |
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76 method to ensure that the generated sequences seen by each thread don't |
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77 overlap. |
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78 |
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79 Class Random can also be subclassed if you want to use a different basic |
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80 generator of your own devising: in that case, override the following |
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81 methods: random(), seed(), getstate(), setstate() and jumpahead(). |
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82 Optionally, implement a getrandombits() method so that randrange() |
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83 can cover arbitrarily large ranges. |
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84 |
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85 """ |
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86 |
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87 VERSION = 2 # used by getstate/setstate |
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88 |
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89 def __init__(self, x=None): |
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90 """Initialize an instance. |
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91 |
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92 Optional argument x controls seeding, as for Random.seed(). |
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93 """ |
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94 |
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95 self.seed(x) |
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96 self.gauss_next = None |
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97 |
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98 def seed(self, a=None): |
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99 """Initialize internal state from hashable object. |
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100 |
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101 None or no argument seeds from current time or from an operating |
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102 system specific randomness source if available. |
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103 |
| 16386 | 104 If a is not None or an int or long, hash(a) is used instead. |
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105 """ |
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106 |
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107 if a is None: |
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108 try: |
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109 a = long(_hexlify(_urandom(16)), 16) |
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110 except NotImplementedError: |
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111 import time |
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112 a = long(time.time() * 256) # use fractional seconds |
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113 |
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114 super(Random, self).seed(a) |
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115 self.gauss_next = None |
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116 |
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117 def getstate(self): |
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118 """Return internal state; can be passed to setstate() later.""" |
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119 return self.VERSION, super(Random, self).getstate(), self.gauss_next |
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120 |
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121 def setstate(self, state): |
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122 """Restore internal state from object returned by getstate().""" |
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123 version = state[0] |
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124 if version == 2: |
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125 version, internalstate, self.gauss_next = state |
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126 super(Random, self).setstate(internalstate) |
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127 else: |
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128 raise ValueError("state with version %s passed to " |
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129 "Random.setstate() of version %s" % |
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130 (version, self.VERSION)) |
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131 |
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132 ## ---- Methods below this point do not need to be overridden when |
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133 ## ---- subclassing for the purpose of using a different core generator. |
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134 |
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135 ## -------------------- pickle support ------------------- |
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136 |
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137 def __getstate__(self): # for pickle |
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138 return self.getstate() |
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139 |
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140 def __setstate__(self, state): # for pickle |
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141 self.setstate(state) |
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142 |
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143 def __reduce__(self): |
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144 return self.__class__, (), self.getstate() |
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145 |
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146 ## -------------------- integer methods ------------------- |
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147 |
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148 def randrange(self, start, stop=None, step=1, int=int, default=None, |
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149 maxwidth=1L<<BPF): |
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150 """Choose a random item from range(start, stop[, step]). |
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151 |
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152 This fixes the problem with randint() which includes the |
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153 endpoint; in Python this is usually not what you want. |
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154 Do not supply the 'int', 'default', and 'maxwidth' arguments. |
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155 """ |
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156 |
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157 # This code is a bit messy to make it fast for the |
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158 # common case while still doing adequate error checking. |
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159 istart = int(start) |
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160 if istart != start: |
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161 raise ValueError, "non-integer arg 1 for randrange()" |
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162 if stop is default: |
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163 if istart > 0: |
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164 if istart >= maxwidth: |
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165 return self._randbelow(istart) |
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166 return int(self.random() * istart) |
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167 raise ValueError, "empty range for randrange()" |
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168 |
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169 # stop argument supplied. |
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170 istop = int(stop) |
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171 if istop != stop: |
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172 raise ValueError, "non-integer stop for randrange()" |
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173 width = istop - istart |
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174 if step == 1 and width > 0: |
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175 # Note that |
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176 # int(istart + self.random()*width) |
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177 # instead would be incorrect. For example, consider istart |
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178 # = -2 and istop = 0. Then the guts would be in |
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179 # -2.0 to 0.0 exclusive on both ends (ignoring that random() |
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180 # might return 0.0), and because int() truncates toward 0, the |
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181 # final result would be -1 or 0 (instead of -2 or -1). |
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182 # istart + int(self.random()*width) |
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183 # would also be incorrect, for a subtler reason: the RHS |
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184 # can return a long, and then randrange() would also return |
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185 # a long, but we're supposed to return an int (for backward |
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186 # compatibility). |
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187 |
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188 if width >= maxwidth: |
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189 return int(istart + self._randbelow(width)) |
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190 return int(istart + int(self.random()*width)) |
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191 if step == 1: |
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192 raise ValueError, "empty range for randrange() (%d,%d, %d)" % (istart, istop, width) |
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193 |
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194 # Non-unit step argument supplied. |
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195 istep = int(step) |
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196 if istep != step: |
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197 raise ValueError, "non-integer step for randrange()" |
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198 if istep > 0: |
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199 n = (width + istep - 1) // istep |
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200 elif istep < 0: |
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201 n = (width + istep + 1) // istep |
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202 else: |
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203 raise ValueError, "zero step for randrange()" |
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204 |
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205 if n <= 0: |
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206 raise ValueError, "empty range for randrange()" |
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207 |
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208 if n >= maxwidth: |
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209 return istart + self._randbelow(n) |
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210 return istart + istep*int(self.random() * n) |
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212 def randint(self, a, b): |
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213 """Return random integer in range [a, b], including both end points. |
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214 """ |
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215 |
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216 return self.randrange(a, b+1) |
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217 |
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218 def _randbelow(self, n, _log=_log, int=int, _maxwidth=1L<<BPF, |
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219 _Method=_MethodType, _BuiltinMethod=_BuiltinMethodType): |
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220 """Return a random int in the range [0,n) |
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221 |
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222 Handles the case where n has more bits than returned |
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223 by a single call to the underlying generator. |
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224 """ |
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225 |
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226 try: |
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227 getrandbits = self.getrandbits |
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228 except AttributeError: |
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229 pass |
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230 else: |
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231 # Only call self.getrandbits if the original random() builtin method |
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232 # has not been overridden or if a new getrandbits() was supplied. |
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233 # This assures that the two methods correspond. |
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234 if type(self.random) is _BuiltinMethod or type(getrandbits) is _Method: |
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235 k = int(1.00001 + _log(n-1, 2.0)) # 2**k > n-1 > 2**(k-2) |
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236 r = getrandbits(k) |
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237 while r >= n: |
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238 r = getrandbits(k) |
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239 return r |
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240 if n >= _maxwidth: |
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241 _warn("Underlying random() generator does not supply \n" |
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242 "enough bits to choose from a population range this large") |
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243 return int(self.random() * n) |
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244 |
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245 ## -------------------- sequence methods ------------------- |
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246 |
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247 def choice(self, seq): |
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248 """Choose a random element from a non-empty sequence.""" |
| 32287 | 249 return seq[int(self.random() * len(seq))] # raises IndexError if seq is empty |
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250 |
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251 def shuffle(self, x, random=None, int=int): |
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252 """x, random=random.random -> shuffle list x in place; return None. |
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253 |
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254 Optional arg random is a 0-argument function returning a random |
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255 float in [0.0, 1.0); by default, the standard random.random. |
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256 |
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257 Note that for even rather small len(x), the total number of |
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258 permutations of x is larger than the period of most random number |
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259 generators; this implies that "most" permutations of a long |
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260 sequence can never be generated. |
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261 """ |
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262 |
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263 if random is None: |
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264 random = self.random |
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265 for i in reversed(xrange(1, len(x))): |
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266 # pick an element in x[:i+1] with which to exchange x[i] |
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267 j = int(random() * (i+1)) |
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268 x[i], x[j] = x[j], x[i] |
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269 |
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270 def sample(self, population, k): |
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271 """Chooses k unique random elements from a population sequence. |
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272 |
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273 Returns a new list containing elements from the population while |
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274 leaving the original population unchanged. The resulting list is |
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275 in selection order so that all sub-slices will also be valid random |
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276 samples. This allows raffle winners (the sample) to be partitioned |
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277 into grand prize and second place winners (the subslices). |
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278 |
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279 Members of the population need not be hashable or unique. If the |
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280 population contains repeats, then each occurrence is a possible |
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281 selection in the sample. |
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282 |
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283 To choose a sample in a range of integers, use xrange as an argument. |
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284 This is especially fast and space efficient for sampling from a |
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285 large population: sample(xrange(10000000), 60) |
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286 """ |
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287 |
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288 # XXX Although the documentation says `population` is "a sequence", |
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289 # XXX attempts are made to cater to any iterable with a __len__ |
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290 # XXX method. This has had mixed success. Examples from both |
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291 # XXX sides: sets work fine, and should become officially supported; |
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292 # XXX dicts are much harder, and have failed in various subtle |
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293 # XXX ways across attempts. Support for mapping types should probably |
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294 # XXX be dropped (and users should pass mapping.keys() or .values() |
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295 # XXX explicitly). |
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296 |
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297 # Sampling without replacement entails tracking either potential |
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298 # selections (the pool) in a list or previous selections in a |
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299 # dictionary. |
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300 |
| 31578 | 301 # When the number of selections is small compared to the |
| 302 # population, then tracking selections is efficient, requiring | |
| 303 # only a small dictionary and an occasional reselection. For | |
| 304 # a larger number of selections, the pool tracking method is | |
| 305 # preferred since the list takes less space than the | |
| 306 # dictionary and it doesn't suffer from frequent reselections. | |
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307 |
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308 n = len(population) |
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309 if not 0 <= k <= n: |
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310 raise ValueError, "sample larger than population" |
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311 random = self.random |
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312 _int = int |
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313 result = [None] * k |
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314 if n < 6 * k or hasattr(population, "keys"): |
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315 # An n-length list is smaller than a k-length set, or this is a |
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316 # mapping type so the other algorithm wouldn't work. |
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317 pool = list(population) |
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318 for i in xrange(k): # invariant: non-selected at [0,n-i) |
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319 j = _int(random() * (n-i)) |
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320 result[i] = pool[j] |
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321 pool[j] = pool[n-i-1] # move non-selected item into vacancy |
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322 else: |
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323 try: |
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324 selected = {} |
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325 for i in xrange(k): |
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326 j = _int(random() * n) |
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327 while j in selected: |
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328 j = _int(random() * n) |
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329 result[i] = selected[j] = population[j] |
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330 except (TypeError, KeyError): # handle (at least) sets |
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331 if isinstance(population, list): |
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332 raise |
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333 return self.sample(tuple(population), k) |
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334 return result |
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335 |
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336 ## -------------------- real-valued distributions ------------------- |
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337 |
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338 ## -------------------- uniform distribution ------------------- |
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339 |
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340 def uniform(self, a, b): |
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341 """Get a random number in the range [a, b).""" |
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342 return a + (b-a) * self.random() |
| 1575 | 343 |
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344 ## -------------------- normal distribution -------------------- |
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346 def normalvariate(self, mu, sigma): |
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347 """Normal distribution. |
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348 |
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349 mu is the mean, and sigma is the standard deviation. |
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350 |
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351 """ |
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352 # mu = mean, sigma = standard deviation |
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353 |
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354 # Uses Kinderman and Monahan method. Reference: Kinderman, |
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355 # A.J. and Monahan, J.F., "Computer generation of random |
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356 # variables using the ratio of uniform deviates", ACM Trans |
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357 # Math Software, 3, (1977), pp257-260. |
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359 random = self.random |
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360 while 1: |
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361 u1 = random() |
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362 u2 = 1.0 - random() |
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363 z = NV_MAGICCONST*(u1-0.5)/u2 |
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364 zz = z*z/4.0 |
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365 if zz <= -_log(u2): |
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366 break |
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367 return mu + z*sigma |
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369 ## -------------------- lognormal distribution -------------------- |
| 1575 | 370 |
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371 def lognormvariate(self, mu, sigma): |
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372 """Log normal distribution. |
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373 |
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374 If you take the natural logarithm of this distribution, you'll get a |
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375 normal distribution with mean mu and standard deviation sigma. |
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376 mu can have any value, and sigma must be greater than zero. |
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377 |
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378 """ |
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379 return _exp(self.normalvariate(mu, sigma)) |
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381 ## -------------------- exponential distribution -------------------- |
| 1575 | 382 |
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383 def expovariate(self, lambd): |
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384 """Exponential distribution. |
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385 |
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386 lambd is 1.0 divided by the desired mean. (The parameter would be |
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387 called "lambda", but that is a reserved word in Python.) Returned |
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388 values range from 0 to positive infinity. |
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389 |
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390 """ |
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391 # lambd: rate lambd = 1/mean |
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392 # ('lambda' is a Python reserved word) |
| 1575 | 393 |
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394 random = self.random |
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395 u = random() |
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396 while u <= 1e-7: |
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397 u = random() |
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398 return -_log(u)/lambd |
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400 ## -------------------- von Mises distribution -------------------- |
| 1575 | 401 |
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402 def vonmisesvariate(self, mu, kappa): |
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403 """Circular data distribution. |
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404 |
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405 mu is the mean angle, expressed in radians between 0 and 2*pi, and |
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406 kappa is the concentration parameter, which must be greater than or |
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407 equal to zero. If kappa is equal to zero, this distribution reduces |
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408 to a uniform random angle over the range 0 to 2*pi. |
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409 |
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410 """ |
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411 # mu: mean angle (in radians between 0 and 2*pi) |
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412 # kappa: concentration parameter kappa (>= 0) |
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413 # if kappa = 0 generate uniform random angle |
| 1575 | 414 |
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415 # Based upon an algorithm published in: Fisher, N.I., |
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416 # "Statistical Analysis of Circular Data", Cambridge |
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417 # University Press, 1993. |
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418 |
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419 # Thanks to Magnus Kessler for a correction to the |
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420 # implementation of step 4. |
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421 |
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422 random = self.random |
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423 if kappa <= 1e-6: |
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424 return TWOPI * random() |
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425 |
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426 a = 1.0 + _sqrt(1.0 + 4.0 * kappa * kappa) |
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427 b = (a - _sqrt(2.0 * a))/(2.0 * kappa) |
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428 r = (1.0 + b * b)/(2.0 * b) |
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430 while 1: |
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431 u1 = random() |
| 1575 | 432 |
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433 z = _cos(_pi * u1) |
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434 f = (1.0 + r * z)/(r + z) |
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435 c = kappa * (r - f) |
| 1575 | 436 |
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437 u2 = random() |
| 1575 | 438 |
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439 if u2 < c * (2.0 - c) or u2 <= c * _exp(1.0 - c): |
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440 break |
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442 u3 = random() |
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443 if u3 > 0.5: |
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444 theta = (mu % TWOPI) + _acos(f) |
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445 else: |
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446 theta = (mu % TWOPI) - _acos(f) |
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448 return theta |
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450 ## -------------------- gamma distribution -------------------- |
| 1575 | 451 |
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452 def gammavariate(self, alpha, beta): |
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453 """Gamma distribution. Not the gamma function! |
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|
454 |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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|
455 Conditions on the parameters are alpha > 0 and beta > 0. |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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|
456 |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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changeset
|
457 """ |
|
23521
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Whitespace normalization.
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diff
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|
458 |
|
23447
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Closes patch 529408 deprecating random.stdgamma().
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|
459 # alpha > 0, beta > 0, mean is alpha*beta, variance is alpha*beta**2 |
|
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|
460 |
|
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Use spaces, not tabs for indents.
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|
461 # Warning: a few older sources define the gamma distribution in terms |
|
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|
462 # of alpha > -1.0 |
|
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|
463 if alpha <= 0.0 or beta <= 0.0: |
|
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|
464 raise ValueError, 'gammavariate: alpha and beta must be > 0.0' |
|
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|
465 |
|
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|
466 random = self.random |
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|
467 if alpha > 1.0: |
| 1575 | 468 |
|
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|
469 # Uses R.C.H. Cheng, "The generation of Gamma |
|
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|
470 # variables with non-integral shape parameters", |
|
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|
471 # Applied Statistics, (1977), 26, No. 1, p71-74 |
| 1575 | 472 |
|
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|
473 ainv = _sqrt(2.0 * alpha - 1.0) |
|
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|
474 bbb = alpha - LOG4 |
|
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Closes SF bug 527139. Moved temp variables inside guard.
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|
475 ccc = alpha + ainv |
|
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|
476 |
|
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|
477 while 1: |
|
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|
478 u1 = random() |
|
27085
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479 if not 1e-7 < u1 < .9999999: |
|
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|
480 continue |
|
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|
481 u2 = 1.0 - random() |
|
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482 v = _log(u1/(1.0-u1))/ainv |
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483 x = alpha*_exp(v) |
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484 z = u1*u1*u2 |
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|
485 r = bbb+ccc*v-x |
|
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|
486 if r + SG_MAGICCONST - 4.5*z >= 0.0 or r >= _log(z): |
|
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Closes patch 529408 deprecating random.stdgamma().
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|
487 return x * beta |
| 1575 | 488 |
|
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489 elif alpha == 1.0: |
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|
490 # expovariate(1) |
|
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|
491 u = random() |
|
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492 while u <= 1e-7: |
|
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|
493 u = random() |
|
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|
494 return -_log(u) * beta |
| 1575 | 495 |
|
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|
496 else: # alpha is between 0 and 1 (exclusive) |
| 1575 | 497 |
|
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|
498 # Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle |
| 1575 | 499 |
|
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500 while 1: |
|
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|
501 u = random() |
|
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|
502 b = (_e + alpha)/_e |
|
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|
503 p = b*u |
|
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504 if p <= 1.0: |
|
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|
505 x = p ** (1.0/alpha) |
|
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|
506 else: |
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|
507 x = -_log((b-p)/alpha) |
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508 u1 = random() |
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|
509 if p > 1.0: |
|
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510 if u1 <= x ** (alpha - 1.0): |
|
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|
511 break |
|
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|
512 elif u1 <= _exp(-x): |
|
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|
513 break |
|
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|
514 return x * beta |
|
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|
515 |
|
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|
516 ## -------------------- Gauss (faster alternative) -------------------- |
|
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|
517 |
|
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|
518 def gauss(self, mu, sigma): |
|
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|
519 """Gaussian distribution. |
|
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|
520 |
|
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|
521 mu is the mean, and sigma is the standard deviation. This is |
|
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|
522 slightly faster than the normalvariate() function. |
|
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|
523 |
|
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|
524 Not thread-safe without a lock around calls. |
|
23536
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Whitespace normalized.
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|
525 |
|
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|
526 """ |
|
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|
527 |
|
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|
528 # When x and y are two variables from [0, 1), uniformly |
|
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|
529 # distributed, then |
|
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|
530 # |
|
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|
531 # cos(2*pi*x)*sqrt(-2*log(1-y)) |
|
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|
532 # sin(2*pi*x)*sqrt(-2*log(1-y)) |
|
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|
533 # |
|
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|
534 # are two *independent* variables with normal distribution |
|
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|
535 # (mu = 0, sigma = 1). |
|
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|
536 # (Lambert Meertens) |
|
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|
537 # (corrected version; bug discovered by Mike Miller, fixed by LM) |
|
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|
538 |
|
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|
539 # Multithreading note: When two threads call this function |
|
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|
540 # simultaneously, it is possible that they will receive the |
|
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|
541 # same return value. The window is very small though. To |
|
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|
542 # avoid this, you have to use a lock around all calls. (I |
|
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|
543 # didn't want to slow this down in the serial case by using a |
|
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|
544 # lock here.) |
|
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|
545 |
|
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|
546 random = self.random |
|
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|
547 z = self.gauss_next |
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548 self.gauss_next = None |
|
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|
549 if z is None: |
|
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|
550 x2pi = random() * TWOPI |
|
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|
551 g2rad = _sqrt(-2.0 * _log(1.0 - random())) |
|
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|
552 z = _cos(x2pi) * g2rad |
|
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|
553 self.gauss_next = _sin(x2pi) * g2rad |
|
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|
554 |
|
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|
555 return mu + z*sigma |
|
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|
556 |
|
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|
557 ## -------------------- beta -------------------- |
|
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|
558 ## See |
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|
559 ## http://sourceforge.net/bugs/?func=detailbug&bug_id=130030&group_id=5470 |
|
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|
560 ## for Ivan Frohne's insightful analysis of why the original implementation: |
|
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|
561 ## |
|
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|
562 ## def betavariate(self, alpha, beta): |
|
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SF bug 130030: Claim of bad betavariate algorithm.
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parents:
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|
563 ## # Discrete Event Simulation in C, pp 87-88. |
|
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|
564 ## |
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|
565 ## y = self.expovariate(alpha) |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
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diff
changeset
|
566 ## 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
|
567 ## return z/(y+z) |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
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diff
changeset
|
568 ## |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
16265
diff
changeset
|
569 ## 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
|
570 |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
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parents:
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diff
changeset
|
571 def betavariate(self, alpha, beta): |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
Raymond Hettinger <python@rcn.com>
parents:
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|
572 """Beta distribution. |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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parents:
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diff
changeset
|
573 |
|
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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parents:
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diff
changeset
|
574 Conditions on the parameters are alpha > -1 and beta} > -1. |
|
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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parents:
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diff
changeset
|
575 Returned values range between 0 and 1. |
|
23536
0a4c92559a0b
Whitespace normalized.
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parents:
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diff
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|
576 |
|
23531
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
577 """ |
|
23536
0a4c92559a0b
Whitespace normalized.
Raymond Hettinger <python@rcn.com>
parents:
23531
diff
changeset
|
578 |
|
16271
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
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diff
changeset
|
579 # This version due to Janne Sinkkonen, and matches all the std |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
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parents:
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diff
changeset
|
580 # texts (e.g., Knuth Vol 2 Ed 3 pg 134 "the beta distribution"). |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
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parents:
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diff
changeset
|
581 y = self.gammavariate(alpha, 1.) |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
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diff
changeset
|
582 if y == 0: |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
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diff
changeset
|
583 return 0.0 |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
Tim Peters <tim.peters@gmail.com>
parents:
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diff
changeset
|
584 else: |
|
7ef2382f6123
SF bug 130030: Claim of bad betavariate algorithm.
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parents:
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changeset
|
585 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
|
586 |
|
16265
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Cosmetic changes after some sleep; no change in semantics.
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parents:
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changeset
|
587 ## -------------------- Pareto -------------------- |
|
6698
b73eb4e6face
Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
Guido van Rossum <guido@python.org>
parents:
1618
diff
changeset
|
588 |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
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parents:
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|
589 def paretovariate(self, alpha): |
|
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parents:
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|
590 """Pareto distribution. alpha is the shape parameter.""" |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
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parents:
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changeset
|
591 # Jain, pg. 495 |
|
6698
b73eb4e6face
Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
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parents:
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diff
changeset
|
592 |
|
27085
90350b5d3397
Correct long standing bugs in the methods for random distributions.
Raymond Hettinger <python@rcn.com>
parents:
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diff
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|
593 u = 1.0 - self.random() |
|
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parents:
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|
594 return 1.0 / pow(u, 1.0/alpha) |
|
6698
b73eb4e6face
Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
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parents:
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diff
changeset
|
595 |
|
16265
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|
596 ## -------------------- Weibull -------------------- |
|
6698
b73eb4e6face
Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
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parents:
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diff
changeset
|
597 |
|
16242
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Reworked random.py so that it no longer depends on, and offers all the
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parents:
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changeset
|
598 def weibullvariate(self, alpha, beta): |
|
23531
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parents:
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|
599 """Weibull distribution. |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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parents:
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|
600 |
|
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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changeset
|
601 alpha is the scale parameter and beta is the shape parameter. |
|
23536
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Whitespace normalized.
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|
602 |
|
23531
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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parents:
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|
603 """ |
|
16242
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parents:
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changeset
|
604 # 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
|
605 |
|
27085
90350b5d3397
Correct long standing bugs in the methods for random distributions.
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parents:
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diff
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|
606 u = 1.0 - self.random() |
|
16242
3c5f09422b69
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parents:
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diff
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|
607 return alpha * pow(-_log(u), 1.0/beta) |
|
11200
bca2d14f3e36
Add Tim Peters' shuffle() algorithm.
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parents:
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diff
changeset
|
608 |
|
26829
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
609 ## -------------------- Wichmann-Hill ------------------- |
|
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|
610 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
611 class WichmannHill(Random): |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
612 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
613 VERSION = 1 # used by getstate/setstate |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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|
614 |
|
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parents:
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|
615 def seed(self, a=None): |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
616 """Initialize internal state from hashable object. |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
617 |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
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parents:
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diff
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|
618 None or no argument seeds from current time or from an operating |
|
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
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|
619 system specific randomness source if available. |
|
26829
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|
620 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
621 If a is not None or an int or long, hash(a) is used instead. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
622 |
|
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diff
changeset
|
623 If a is an int or long, a is used directly. Distinct values between |
|
f64c96922708
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|
624 0 and 27814431486575L inclusive are guaranteed to yield distinct |
|
f64c96922708
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parents:
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|
625 internal states (this guarantee is specific to the default |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
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|
626 Wichmann-Hill generator). |
|
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|
627 """ |
|
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diff
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|
628 |
|
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changeset
|
629 if a is None: |
|
33409
8e23bd3d5b1a
Fulfill Martin's request to use try/except rather than a "look before
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parents:
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diff
changeset
|
630 try: |
|
8e23bd3d5b1a
Fulfill Martin's request to use try/except rather than a "look before
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parents:
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diff
changeset
|
631 a = long(_hexlify(_urandom(16)), 16) |
|
8e23bd3d5b1a
Fulfill Martin's request to use try/except rather than a "look before
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parents:
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|
632 except NotImplementedError: |
|
33329
97fca735c8da
Teach the random module about os.urandom().
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parents:
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diff
changeset
|
633 import time |
|
97fca735c8da
Teach the random module about os.urandom().
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parents:
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diff
changeset
|
634 a = long(time.time() * 256) # use fractional seconds |
|
26829
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diff
changeset
|
635 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
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|
636 if not isinstance(a, (int, long)): |
|
f64c96922708
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|
637 a = hash(a) |
|
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parents:
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changeset
|
638 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
639 a, x = divmod(a, 30268) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
640 a, y = divmod(a, 30306) |
|
f64c96922708
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Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
641 a, z = divmod(a, 30322) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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changeset
|
642 self._seed = int(x)+1, int(y)+1, int(z)+1 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
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|
643 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
644 self.gauss_next = None |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
645 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
646 def random(self): |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
647 """Get the next random number in the range [0.0, 1.0).""" |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
648 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
649 # Wichman-Hill random number generator. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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|
650 # |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
651 # Wichmann, B. A. & Hill, I. D. (1982) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
652 # Algorithm AS 183: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
653 # An efficient and portable pseudo-random number generator |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
654 # Applied Statistics 31 (1982) 188-190 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
655 # |
|
f64c96922708
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|
656 # see also: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
657 # Correction to Algorithm AS 183 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
658 # Applied Statistics 33 (1984) 123 |
|
f64c96922708
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|
659 # |
|
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changeset
|
660 # McLeod, A. I. (1985) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
661 # A remark on Algorithm AS 183 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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|
662 # Applied Statistics 34 (1985),198-200 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
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|
663 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
664 # This part is thread-unsafe: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
665 # BEGIN CRITICAL SECTION |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
666 x, y, z = self._seed |
|
f64c96922708
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Raymond Hettinger <python@rcn.com>
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|
667 x = (171 * x) % 30269 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
668 y = (172 * y) % 30307 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
669 z = (170 * z) % 30323 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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|
670 self._seed = x, y, z |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
671 # END CRITICAL SECTION |
|
f64c96922708
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diff
changeset
|
672 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
673 # Note: on a platform using IEEE-754 double arithmetic, this can |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
674 # never return 0.0 (asserted by Tim; proof too long for a comment). |
|
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|
675 return (x/30269.0 + y/30307.0 + z/30323.0) % 1.0 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
676 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
677 def getstate(self): |
|
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|
678 """Return internal state; can be passed to setstate() later.""" |
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|
679 return self.VERSION, self._seed, self.gauss_next |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
680 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
681 def setstate(self, state): |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
682 """Restore internal state from object returned by getstate().""" |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
683 version = state[0] |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
684 if version == 1: |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
685 version, self._seed, self.gauss_next = state |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
686 else: |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
687 raise ValueError("state with version %s passed to " |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
688 "Random.setstate() of version %s" % |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
689 (version, self.VERSION)) |
|
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changeset
|
690 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
691 def jumpahead(self, n): |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
692 """Act as if n calls to random() were made, but quickly. |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
693 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
694 n is an int, greater than or equal to 0. |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
695 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
696 Example use: If you have 2 threads and know that each will |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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697 consume no more than a million random numbers, create two Random |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
698 objects r1 and r2, then do |
|
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|
699 r2.setstate(r1.getstate()) |
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|
700 r2.jumpahead(1000000) |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
701 Then r1 and r2 will use guaranteed-disjoint segments of the full |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
702 period. |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
703 """ |
|
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changeset
|
704 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
705 if not n >= 0: |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
706 raise ValueError("n must be >= 0") |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
707 x, y, z = self._seed |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
708 x = int(x * pow(171, n, 30269)) % 30269 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
709 y = int(y * pow(172, n, 30307)) % 30307 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
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|
710 z = int(z * pow(170, n, 30323)) % 30323 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
711 self._seed = x, y, z |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
712 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
713 def __whseed(self, x=0, y=0, z=0): |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
714 """Set the Wichmann-Hill seed from (x, y, z). |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
715 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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diff
changeset
|
716 These must be integers in the range [0, 256). |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
717 """ |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
718 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
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|
719 if not type(x) == type(y) == type(z) == int: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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changeset
|
720 raise TypeError('seeds must be integers') |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
721 if not (0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256): |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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diff
changeset
|
722 raise ValueError('seeds must be in range(0, 256)') |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
723 if 0 == x == y == z: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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changeset
|
724 # Initialize from current time |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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changeset
|
725 import time |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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|
726 t = long(time.time() * 256) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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changeset
|
727 t = int((t&0xffffff) ^ (t>>24)) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
728 t, x = divmod(t, 256) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
729 t, y = divmod(t, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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changeset
|
730 t, z = divmod(t, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
731 # Zero is a poor seed, so substitute 1 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
732 self._seed = (x or 1, y or 1, z or 1) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
733 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
734 self.gauss_next = None |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
735 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
736 def whseed(self, a=None): |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
737 """Seed from hashable object's hash code. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
738 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
739 None or no argument seeds from current time. It is not guaranteed |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
740 that objects with distinct hash codes lead to distinct internal |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
741 states. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
742 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
743 This is obsolete, provided for compatibility with the seed routine |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
744 used prior to Python 2.1. Use the .seed() method instead. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
745 """ |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
746 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
747 if a is None: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
748 self.__whseed() |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
749 return |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
750 a = hash(a) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
751 a, x = divmod(a, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
752 a, y = divmod(a, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
753 a, z = divmod(a, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
754 x = (x + a) % 256 or 1 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
755 y = (y + a) % 256 or 1 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
756 z = (z + a) % 256 or 1 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
757 self.__whseed(x, y, z) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
758 |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
759 ## --------------- Operating System Random Source ------------------ |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
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diff
changeset
|
760 |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
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parents:
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diff
changeset
|
761 class SystemRandom(Random): |
|
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
762 """Alternate random number generator using sources provided |
|
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
763 by the operating system (such as /dev/urandom on Unix or |
|
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
764 CryptGenRandom on Windows). |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
765 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
766 Not available on all systems (see os.urandom() for details). |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
767 """ |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
768 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
769 def random(self): |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
770 """Get the next random number in the range [0.0, 1.0).""" |
|
33350
c44f083465f9
HardwareRandom: Go back to multiplying by 2**-BPF instead of using
Tim Peters <tim.peters@gmail.com>
parents:
33349
diff
changeset
|
771 return (long(_hexlify(_urandom(7)), 16) >> 3) * RECIP_BPF |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
772 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
773 def getrandbits(self, k): |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
774 """getrandbits(k) -> x. Generates a long int with k random bits.""" |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
775 if k <= 0: |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
776 raise ValueError('number of bits must be greater than zero') |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
777 if k != int(k): |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
778 raise TypeError('number of bits should be an integer') |
|
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779 bytes = (k + 7) // 8 # bits / 8 and rounded up |
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780 x = long(_hexlify(_urandom(bytes)), 16) |
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781 return x >> (bytes * 8 - k) # trim excess bits |
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782 |
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783 def _stub(self, *args, **kwds): |
|
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784 "Stub method. Not used for a system random number generator." |
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785 return None |
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786 seed = jumpahead = _stub |
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787 |
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788 def _notimplemented(self, *args, **kwds): |
|
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789 "Method should not be called for a system random number generator." |
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790 raise NotImplementedError('System entropy source does not have state.') |
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791 getstate = setstate = _notimplemented |
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792 |
|
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793 ## -------------------- test program -------------------- |
| 1575 | 794 |
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795 def _test_generator(n, func, args): |
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796 import time |
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797 print n, 'times', func.__name__ |
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798 total = 0.0 |
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799 sqsum = 0.0 |
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800 smallest = 1e10 |
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801 largest = -1e10 |
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802 t0 = time.time() |
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803 for i in range(n): |
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804 x = func(*args) |
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805 total += x |
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806 sqsum = sqsum + x*x |
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807 smallest = min(x, smallest) |
|
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808 largest = max(x, largest) |
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809 t1 = time.time() |
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810 print round(t1-t0, 3), 'sec,', |
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811 avg = total/n |
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812 stddev = _sqrt(sqsum/n - avg*avg) |
|
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813 print 'avg %g, stddev %g, min %g, max %g' % \ |
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814 (avg, stddev, smallest, largest) |
| 1575 | 815 |
|
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816 |
|
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817 def _test(N=2000): |
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818 _test_generator(N, random, ()) |
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819 _test_generator(N, normalvariate, (0.0, 1.0)) |
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820 _test_generator(N, lognormvariate, (0.0, 1.0)) |
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821 _test_generator(N, vonmisesvariate, (0.0, 1.0)) |
|
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822 _test_generator(N, gammavariate, (0.01, 1.0)) |
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823 _test_generator(N, gammavariate, (0.1, 1.0)) |
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824 _test_generator(N, gammavariate, (0.1, 2.0)) |
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825 _test_generator(N, gammavariate, (0.5, 1.0)) |
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826 _test_generator(N, gammavariate, (0.9, 1.0)) |
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827 _test_generator(N, gammavariate, (1.0, 1.0)) |
|
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828 _test_generator(N, gammavariate, (2.0, 1.0)) |
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829 _test_generator(N, gammavariate, (20.0, 1.0)) |
|
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830 _test_generator(N, gammavariate, (200.0, 1.0)) |
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831 _test_generator(N, gauss, (0.0, 1.0)) |
|
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832 _test_generator(N, betavariate, (3.0, 3.0)) |
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833 |
|
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834 # Create one instance, seeded from current time, and export its methods |
|
26829
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835 # as module-level functions. The functions share state across all uses |
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836 #(both in the user's code and in the Python libraries), but that's fine |
|
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837 # for most programs and is easier for the casual user than making them |
|
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838 # instantiate their own Random() instance. |
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839 |
|
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840 _inst = Random() |
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841 seed = _inst.seed |
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842 random = _inst.random |
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843 uniform = _inst.uniform |
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844 randint = _inst.randint |
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845 choice = _inst.choice |
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846 randrange = _inst.randrange |
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847 sample = _inst.sample |
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848 shuffle = _inst.shuffle |
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849 normalvariate = _inst.normalvariate |
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850 lognormvariate = _inst.lognormvariate |
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851 expovariate = _inst.expovariate |
|
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852 vonmisesvariate = _inst.vonmisesvariate |
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|
853 gammavariate = _inst.gammavariate |
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854 gauss = _inst.gauss |
|
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855 betavariate = _inst.betavariate |
|
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|
856 paretovariate = _inst.paretovariate |
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857 weibullvariate = _inst.weibullvariate |
|
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858 getstate = _inst.getstate |
|
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859 setstate = _inst.setstate |
|
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|
860 jumpahead = _inst.jumpahead |
|
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861 getrandbits = _inst.getrandbits |
|
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|
862 |
| 1575 | 863 if __name__ == '__main__': |
|
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864 _test() |
