Mercurial > cpython-lru_cache-weakref
annotate Lib/random.py @ 28646:193b8aec00ce legacy-trunk
Changes from Jonathan Riehl to allow his pgen extension (PEP 269) to
work. This includes some more code that used to be part of pgen in
the main parser; I'm okay with that. I'll see if the Windows build
needs work next.
| author | Guido van Rossum <guido@python.org> |
|---|---|
| date | Thu, 17 Apr 2003 14:55:42 +0000 |
| parents | 9de064c7a247 |
| children | 34609fa35b11 |
| 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 |
| 1575 | 28 |
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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 math import log as _log, exp as _exp, pi as _pi, e as _e |
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43 from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin |
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44 from math import floor as _floor |
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45 |
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46 __all__ = ["Random","seed","random","uniform","randint","choice","sample", |
| 16613 | 47 "randrange","shuffle","normalvariate","lognormvariate", |
| 48 "cunifvariate","expovariate","vonmisesvariate","gammavariate", | |
| 49 "stdgamma","gauss","betavariate","paretovariate","weibullvariate", | |
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50 "getstate","setstate","jumpahead"] |
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52 NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0) |
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53 TWOPI = 2.0*_pi |
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54 LOG4 = _log(4.0) |
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55 SG_MAGICCONST = 1.0 + _log(4.5) |
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56 |
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57 # Translated by Guido van Rossum from C source provided by |
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58 # Adrian Baddeley. Adapted by Raymond Hettinger for use with |
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59 # the Mersenne Twister core generator. |
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60 |
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61 import _random |
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62 |
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63 class Random(_random.Random): |
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64 """Random number generator base class used by bound module functions. |
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65 |
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66 Used to instantiate instances of Random to get generators that don't |
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67 share state. Especially useful for multi-threaded programs, creating |
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68 a different instance of Random for each thread, and using the jumpahead() |
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69 method to ensure that the generated sequences seen by each thread don't |
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70 overlap. |
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71 |
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72 Class Random can also be subclassed if you want to use a different basic |
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73 generator of your own devising: in that case, override the following |
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74 methods: random(), seed(), getstate(), setstate() and jumpahead(). |
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75 |
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76 """ |
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77 |
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78 VERSION = 2 # used by getstate/setstate |
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79 |
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80 def __init__(self, x=None): |
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81 """Initialize an instance. |
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82 |
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83 Optional argument x controls seeding, as for Random.seed(). |
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84 """ |
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85 |
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86 self.seed(x) |
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87 self.gauss_next = None |
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88 |
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89 def seed(self, a=None): |
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90 """Initialize internal state from hashable object. |
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91 |
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92 None or no argument seeds from current time. |
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93 |
| 16386 | 94 If a is not None or an int or long, hash(a) is used instead. |
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95 """ |
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96 |
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97 super(Random, self).seed(a) |
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98 self.gauss_next = None |
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99 |
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100 def getstate(self): |
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101 """Return internal state; can be passed to setstate() later.""" |
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102 return self.VERSION, super(Random, self).getstate(), self.gauss_next |
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103 |
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104 def setstate(self, state): |
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105 """Restore internal state from object returned by getstate().""" |
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106 version = state[0] |
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107 if version == 2: |
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108 version, internalstate, self.gauss_next = state |
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109 super(Random, self).setstate(internalstate) |
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110 else: |
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111 raise ValueError("state with version %s passed to " |
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112 "Random.setstate() of version %s" % |
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113 (version, self.VERSION)) |
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114 |
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115 ## ---- Methods below this point do not need to be overridden when |
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116 ## ---- subclassing for the purpose of using a different core generator. |
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117 |
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118 ## -------------------- pickle support ------------------- |
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119 |
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120 def __getstate__(self): # for pickle |
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121 return self.getstate() |
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122 |
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123 def __setstate__(self, state): # for pickle |
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124 self.setstate(state) |
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125 |
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126 ## -------------------- integer methods ------------------- |
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127 |
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128 def randrange(self, start, stop=None, step=1, int=int, default=None): |
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129 """Choose a random item from range(start, stop[, step]). |
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130 |
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131 This fixes the problem with randint() which includes the |
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132 endpoint; in Python this is usually not what you want. |
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133 Do not supply the 'int' and 'default' arguments. |
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134 """ |
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135 |
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136 # This code is a bit messy to make it fast for the |
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137 # common case while still doing adequate error checking. |
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138 istart = int(start) |
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139 if istart != start: |
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140 raise ValueError, "non-integer arg 1 for randrange()" |
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141 if stop is default: |
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142 if istart > 0: |
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143 return int(self.random() * istart) |
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144 raise ValueError, "empty range for randrange()" |
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145 |
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146 # stop argument supplied. |
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147 istop = int(stop) |
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148 if istop != stop: |
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149 raise ValueError, "non-integer stop for randrange()" |
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150 if step == 1 and istart < istop: |
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151 try: |
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152 return istart + int(self.random()*(istop - istart)) |
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153 except OverflowError: |
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154 # This can happen if istop-istart > sys.maxint + 1, and |
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155 # multiplying by random() doesn't reduce it to something |
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156 # <= sys.maxint. We know that the overall result fits |
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157 # in an int, and can still do it correctly via math.floor(). |
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158 # But that adds another function call, so for speed we |
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159 # avoided that whenever possible. |
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160 return int(istart + _floor(self.random()*(istop - istart))) |
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161 if step == 1: |
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162 raise ValueError, "empty range for randrange()" |
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163 |
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164 # Non-unit step argument supplied. |
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165 istep = int(step) |
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166 if istep != step: |
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167 raise ValueError, "non-integer step for randrange()" |
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168 if istep > 0: |
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169 n = (istop - istart + istep - 1) / istep |
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170 elif istep < 0: |
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171 n = (istop - istart + istep + 1) / istep |
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172 else: |
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173 raise ValueError, "zero step for randrange()" |
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174 |
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175 if n <= 0: |
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176 raise ValueError, "empty range for randrange()" |
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177 return istart + istep*int(self.random() * n) |
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179 def randint(self, a, b): |
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180 """Return random integer in range [a, b], including both end points. |
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181 """ |
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182 |
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183 return self.randrange(a, b+1) |
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184 |
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185 ## -------------------- sequence methods ------------------- |
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186 |
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187 def choice(self, seq): |
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188 """Choose a random element from a non-empty sequence.""" |
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189 return seq[int(self.random() * len(seq))] |
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190 |
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191 def shuffle(self, x, random=None, int=int): |
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192 """x, random=random.random -> shuffle list x in place; return None. |
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193 |
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194 Optional arg random is a 0-argument function returning a random |
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195 float in [0.0, 1.0); by default, the standard random.random. |
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196 |
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197 Note that for even rather small len(x), the total number of |
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198 permutations of x is larger than the period of most random number |
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199 generators; this implies that "most" permutations of a long |
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200 sequence can never be generated. |
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201 """ |
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202 |
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203 if random is None: |
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204 random = self.random |
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205 for i in xrange(len(x)-1, 0, -1): |
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206 # pick an element in x[:i+1] with which to exchange x[i] |
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207 j = int(random() * (i+1)) |
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208 x[i], x[j] = x[j], x[i] |
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209 |
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210 def sample(self, population, k, int=int): |
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211 """Chooses k unique random elements from a population sequence. |
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212 |
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213 Returns a new list containing elements from the population while |
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214 leaving the original population unchanged. The resulting list is |
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215 in selection order so that all sub-slices will also be valid random |
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216 samples. This allows raffle winners (the sample) to be partitioned |
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217 into grand prize and second place winners (the subslices). |
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218 |
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219 Members of the population need not be hashable or unique. If the |
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220 population contains repeats, then each occurrence is a possible |
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221 selection in the sample. |
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222 |
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223 To choose a sample in a range of integers, use xrange as an argument. |
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224 This is especially fast and space efficient for sampling from a |
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225 large population: sample(xrange(10000000), 60) |
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226 """ |
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227 |
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228 # Sampling without replacement entails tracking either potential |
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229 # selections (the pool) in a list or previous selections in a |
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230 # dictionary. |
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231 |
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232 # When the number of selections is small compared to the population, |
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233 # then tracking selections is efficient, requiring only a small |
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234 # dictionary and an occasional reselection. For a larger number of |
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235 # selections, the pool tracking method is preferred since the list takes |
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236 # less space than the dictionary and it doesn't suffer from frequent |
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237 # reselections. |
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238 |
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239 n = len(population) |
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240 if not 0 <= k <= n: |
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241 raise ValueError, "sample larger than population" |
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242 random = self.random |
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243 result = [None] * k |
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244 if n < 6 * k: # if n len list takes less space than a k len dict |
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245 pool = list(population) |
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246 for i in xrange(k): # invariant: non-selected at [0,n-i) |
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247 j = int(random() * (n-i)) |
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248 result[i] = pool[j] |
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249 pool[j] = pool[n-i-1] # move non-selected item into vacancy |
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250 else: |
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251 selected = {} |
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252 for i in xrange(k): |
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253 j = int(random() * n) |
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254 while j in selected: |
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255 j = int(random() * n) |
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256 result[i] = selected[j] = population[j] |
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257 return result |
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258 |
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259 ## -------------------- real-valued distributions ------------------- |
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260 |
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261 ## -------------------- uniform distribution ------------------- |
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262 |
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263 def uniform(self, a, b): |
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264 """Get a random number in the range [a, b).""" |
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265 return a + (b-a) * self.random() |
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267 ## -------------------- normal distribution -------------------- |
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269 def normalvariate(self, mu, sigma): |
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270 """Normal distribution. |
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271 |
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272 mu is the mean, and sigma is the standard deviation. |
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273 |
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274 """ |
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275 # mu = mean, sigma = standard deviation |
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276 |
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277 # Uses Kinderman and Monahan method. Reference: Kinderman, |
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278 # A.J. and Monahan, J.F., "Computer generation of random |
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279 # variables using the ratio of uniform deviates", ACM Trans |
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280 # Math Software, 3, (1977), pp257-260. |
| 1575 | 281 |
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282 random = self.random |
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283 while True: |
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284 u1 = random() |
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285 u2 = 1.0 - random() |
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286 z = NV_MAGICCONST*(u1-0.5)/u2 |
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287 zz = z*z/4.0 |
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288 if zz <= -_log(u2): |
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289 break |
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290 return mu + z*sigma |
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292 ## -------------------- lognormal distribution -------------------- |
| 1575 | 293 |
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294 def lognormvariate(self, mu, sigma): |
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295 """Log normal distribution. |
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296 |
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297 If you take the natural logarithm of this distribution, you'll get a |
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298 normal distribution with mean mu and standard deviation sigma. |
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299 mu can have any value, and sigma must be greater than zero. |
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300 |
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301 """ |
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302 return _exp(self.normalvariate(mu, sigma)) |
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304 ## -------------------- circular uniform -------------------- |
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306 def cunifvariate(self, mean, arc): |
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307 """Circular uniform distribution. |
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308 |
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309 mean is the mean angle, and arc is the range of the distribution, |
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310 centered around the mean angle. Both values must be expressed in |
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311 radians. Returned values range between mean - arc/2 and |
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312 mean + arc/2 and are normalized to between 0 and pi. |
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313 |
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314 Deprecated in version 2.3. Use: |
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315 (mean + arc * (Random.random() - 0.5)) % Math.pi |
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316 |
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317 """ |
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318 # mean: mean angle (in radians between 0 and pi) |
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319 # arc: range of distribution (in radians between 0 and pi) |
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320 import warnings |
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321 warnings.warn("The cunifvariate function is deprecated; Use (mean " |
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322 "+ arc * (Random.random() - 0.5)) % Math.pi instead", |
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323 DeprecationWarning) |
| 1575 | 324 |
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325 return (mean + arc * (self.random() - 0.5)) % _pi |
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327 ## -------------------- exponential distribution -------------------- |
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329 def expovariate(self, lambd): |
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330 """Exponential distribution. |
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331 |
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332 lambd is 1.0 divided by the desired mean. (The parameter would be |
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333 called "lambda", but that is a reserved word in Python.) Returned |
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334 values range from 0 to positive infinity. |
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335 |
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336 """ |
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337 # lambd: rate lambd = 1/mean |
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338 # ('lambda' is a Python reserved word) |
| 1575 | 339 |
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340 random = self.random |
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341 u = random() |
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342 while u <= 1e-7: |
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343 u = random() |
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344 return -_log(u)/lambd |
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346 ## -------------------- von Mises distribution -------------------- |
| 1575 | 347 |
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348 def vonmisesvariate(self, mu, kappa): |
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349 """Circular data distribution. |
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350 |
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351 mu is the mean angle, expressed in radians between 0 and 2*pi, and |
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352 kappa is the concentration parameter, which must be greater than or |
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353 equal to zero. If kappa is equal to zero, this distribution reduces |
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354 to a uniform random angle over the range 0 to 2*pi. |
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355 |
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356 """ |
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357 # mu: mean angle (in radians between 0 and 2*pi) |
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358 # kappa: concentration parameter kappa (>= 0) |
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359 # if kappa = 0 generate uniform random angle |
| 1575 | 360 |
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361 # Based upon an algorithm published in: Fisher, N.I., |
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362 # "Statistical Analysis of Circular Data", Cambridge |
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363 # University Press, 1993. |
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364 |
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365 # Thanks to Magnus Kessler for a correction to the |
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366 # implementation of step 4. |
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367 |
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368 random = self.random |
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369 if kappa <= 1e-6: |
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370 return TWOPI * random() |
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371 |
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372 a = 1.0 + _sqrt(1.0 + 4.0 * kappa * kappa) |
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373 b = (a - _sqrt(2.0 * a))/(2.0 * kappa) |
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374 r = (1.0 + b * b)/(2.0 * b) |
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376 while True: |
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377 u1 = random() |
| 1575 | 378 |
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379 z = _cos(_pi * u1) |
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380 f = (1.0 + r * z)/(r + z) |
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381 c = kappa * (r - f) |
| 1575 | 382 |
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383 u2 = random() |
| 1575 | 384 |
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385 if not (u2 >= c * (2.0 - c) and u2 > c * _exp(1.0 - c)): |
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386 break |
| 1575 | 387 |
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388 u3 = random() |
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389 if u3 > 0.5: |
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390 theta = (mu % TWOPI) + _acos(f) |
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391 else: |
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392 theta = (mu % TWOPI) - _acos(f) |
| 1575 | 393 |
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394 return theta |
| 1575 | 395 |
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396 ## -------------------- gamma distribution -------------------- |
| 1575 | 397 |
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398 def gammavariate(self, alpha, beta): |
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399 """Gamma distribution. Not the gamma function! |
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400 |
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401 Conditions on the parameters are alpha > 0 and beta > 0. |
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402 |
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403 """ |
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404 |
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405 # alpha > 0, beta > 0, mean is alpha*beta, variance is alpha*beta**2 |
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406 |
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407 # Warning: a few older sources define the gamma distribution in terms |
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408 # of alpha > -1.0 |
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409 if alpha <= 0.0 or beta <= 0.0: |
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410 raise ValueError, 'gammavariate: alpha and beta must be > 0.0' |
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411 |
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412 random = self.random |
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413 if alpha > 1.0: |
| 1575 | 414 |
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415 # Uses R.C.H. Cheng, "The generation of Gamma |
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416 # variables with non-integral shape parameters", |
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417 # Applied Statistics, (1977), 26, No. 1, p71-74 |
| 1575 | 418 |
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419 ainv = _sqrt(2.0 * alpha - 1.0) |
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420 bbb = alpha - LOG4 |
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421 ccc = alpha + ainv |
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422 |
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423 while True: |
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424 u1 = random() |
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425 if not 1e-7 < u1 < .9999999: |
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426 continue |
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427 u2 = 1.0 - random() |
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428 v = _log(u1/(1.0-u1))/ainv |
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429 x = alpha*_exp(v) |
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430 z = u1*u1*u2 |
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431 r = bbb+ccc*v-x |
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432 if r + SG_MAGICCONST - 4.5*z >= 0.0 or r >= _log(z): |
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433 return x * beta |
| 1575 | 434 |
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435 elif alpha == 1.0: |
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436 # expovariate(1) |
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437 u = random() |
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438 while u <= 1e-7: |
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439 u = random() |
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440 return -_log(u) * beta |
| 1575 | 441 |
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442 else: # alpha is between 0 and 1 (exclusive) |
| 1575 | 443 |
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444 # Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle |
| 1575 | 445 |
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446 while True: |
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447 u = random() |
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448 b = (_e + alpha)/_e |
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449 p = b*u |
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450 if p <= 1.0: |
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451 x = pow(p, 1.0/alpha) |
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452 else: |
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453 # p > 1 |
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|
454 x = -_log((b-p)/alpha) |
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455 u1 = random() |
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456 if not (((p <= 1.0) and (u1 > _exp(-x))) or |
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457 ((p > 1) and (u1 > pow(x, alpha - 1.0)))): |
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|
458 break |
|
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|
459 return x * beta |
|
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|
460 |
|
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|
461 |
|
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462 def stdgamma(self, alpha, ainv, bbb, ccc): |
|
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463 # This method was (and shall remain) undocumented. |
|
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464 # This method is deprecated |
|
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465 # for the following reasons: |
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466 # 1. Returns same as .gammavariate(alpha, 1.0) |
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467 # 2. Requires caller to provide 3 extra arguments |
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468 # that are functions of alpha anyway |
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469 # 3. Can't be used for alpha < 0.5 |
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|
470 |
|
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|
471 # ainv = sqrt(2 * alpha - 1) |
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472 # bbb = alpha - log(4) |
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473 # ccc = alpha + ainv |
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474 import warnings |
|
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475 warnings.warn("The stdgamma function is deprecated; " |
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476 "use gammavariate() instead", |
|
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|
477 DeprecationWarning) |
|
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478 return self.gammavariate(alpha, 1.0) |
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|
479 |
| 1575 | 480 |
|
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481 |
|
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482 ## -------------------- Gauss (faster alternative) -------------------- |
|
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483 |
|
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484 def gauss(self, mu, sigma): |
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|
485 """Gaussian distribution. |
|
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486 |
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|
487 mu is the mean, and sigma is the standard deviation. This is |
|
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|
488 slightly faster than the normalvariate() function. |
|
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|
489 |
|
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490 Not thread-safe without a lock around calls. |
|
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|
491 |
|
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492 """ |
|
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|
493 |
|
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|
494 # When x and y are two variables from [0, 1), uniformly |
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|
495 # distributed, then |
|
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|
496 # |
|
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497 # cos(2*pi*x)*sqrt(-2*log(1-y)) |
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498 # sin(2*pi*x)*sqrt(-2*log(1-y)) |
|
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499 # |
|
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500 # are two *independent* variables with normal distribution |
|
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501 # (mu = 0, sigma = 1). |
|
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|
502 # (Lambert Meertens) |
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503 # (corrected version; bug discovered by Mike Miller, fixed by LM) |
|
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|
504 |
|
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|
505 # Multithreading note: When two threads call this function |
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506 # simultaneously, it is possible that they will receive the |
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|
507 # same return value. The window is very small though. To |
|
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|
508 # avoid this, you have to use a lock around all calls. (I |
|
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|
509 # didn't want to slow this down in the serial case by using a |
|
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|
510 # lock here.) |
|
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|
511 |
|
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512 random = self.random |
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513 z = self.gauss_next |
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|
514 self.gauss_next = None |
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|
515 if z is None: |
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|
516 x2pi = random() * TWOPI |
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|
517 g2rad = _sqrt(-2.0 * _log(1.0 - random())) |
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|
518 z = _cos(x2pi) * g2rad |
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|
519 self.gauss_next = _sin(x2pi) * g2rad |
|
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|
520 |
|
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|
521 return mu + z*sigma |
|
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|
522 |
|
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|
523 ## -------------------- beta -------------------- |
|
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|
524 ## See |
|
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|
525 ## http://sourceforge.net/bugs/?func=detailbug&bug_id=130030&group_id=5470 |
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|
526 ## for Ivan Frohne's insightful analysis of why the original implementation: |
|
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|
527 ## |
|
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|
528 ## def betavariate(self, alpha, beta): |
|
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SF bug 130030: Claim of bad betavariate algorithm.
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|
529 ## # Discrete Event Simulation in C, pp 87-88. |
|
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|
530 ## |
|
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SF bug 130030: Claim of bad betavariate algorithm.
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|
531 ## y = self.expovariate(alpha) |
|
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|
532 ## z = self.expovariate(1.0/beta) |
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|
533 ## return z/(y+z) |
|
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|
534 ## |
|
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|
535 ## was dead wrong, and how it probably got that way. |
|
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|
536 |
|
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|
537 def betavariate(self, alpha, beta): |
|
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|
538 """Beta distribution. |
|
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|
539 |
|
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|
540 Conditions on the parameters are alpha > -1 and beta} > -1. |
|
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|
541 Returned values range between 0 and 1. |
|
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|
542 |
|
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|
543 """ |
|
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|
544 |
|
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|
545 # This version due to Janne Sinkkonen, and matches all the std |
|
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|
546 # texts (e.g., Knuth Vol 2 Ed 3 pg 134 "the beta distribution"). |
|
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|
547 y = self.gammavariate(alpha, 1.) |
|
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|
548 if y == 0: |
|
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|
549 return 0.0 |
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|
550 else: |
|
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|
551 return y / (y + self.gammavariate(beta, 1.)) |
|
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|
552 |
|
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|
553 ## -------------------- Pareto -------------------- |
|
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|
554 |
|
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|
555 def paretovariate(self, alpha): |
|
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|
556 """Pareto distribution. alpha is the shape parameter.""" |
|
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|
557 # Jain, pg. 495 |
|
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|
558 |
|
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90350b5d3397
Correct long standing bugs in the methods for random distributions.
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|
559 u = 1.0 - self.random() |
|
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|
560 return 1.0 / pow(u, 1.0/alpha) |
|
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|
561 |
|
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Cosmetic changes after some sleep; no change in semantics.
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|
562 ## -------------------- Weibull -------------------- |
|
6698
b73eb4e6face
Added Pareto and Weibull distributions, courtesy Jeremy Hylton.
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diff
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|
563 |
|
16242
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diff
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|
564 def weibullvariate(self, alpha, beta): |
|
23531
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
Raymond Hettinger <python@rcn.com>
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|
565 """Weibull distribution. |
|
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Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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|
566 |
|
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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|
567 alpha is the scale parameter and beta is the shape parameter. |
|
23536
0a4c92559a0b
Whitespace normalized.
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|
568 |
|
23531
a98e93eafef7
Deprecated Random.cunifvariate clearing bug 506647. Also, added docstrings.
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|
569 """ |
|
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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|
570 # Jain, pg. 499; bug fix courtesy Bill Arms |
|
11200
bca2d14f3e36
Add Tim Peters' shuffle() algorithm.
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parents:
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diff
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|
571 |
|
27085
90350b5d3397
Correct long standing bugs in the methods for random distributions.
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|
572 u = 1.0 - self.random() |
|
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Reworked random.py so that it no longer depends on, and offers all the
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|
573 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
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|
574 |
|
26829
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
575 ## -------------------- Wichmann-Hill ------------------- |
|
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|
576 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
577 class WichmannHill(Random): |
|
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|
578 |
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parents:
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|
579 VERSION = 1 # used by getstate/setstate |
|
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|
580 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
581 def seed(self, a=None): |
|
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|
582 """Initialize internal state from hashable object. |
|
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|
583 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
584 None or no argument seeds from current time. |
|
f64c96922708
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changeset
|
585 |
|
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diff
changeset
|
586 If a is not None or an int or long, hash(a) is used instead. |
|
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parents:
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|
587 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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diff
changeset
|
588 If a is an int or long, a is used directly. Distinct values between |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
589 0 and 27814431486575L inclusive are guaranteed to yield distinct |
|
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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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|
590 internal states (this guarantee is specific to the default |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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parents:
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|
591 Wichmann-Hill generator). |
|
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|
592 """ |
|
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|
593 |
|
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
|
594 if a is None: |
|
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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
|
595 # Initialize from current time |
|
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|
596 import time |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
597 a = long(time.time() * 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
|
598 |
|
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
|
599 if not isinstance(a, (int, long)): |
|
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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
|
600 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
|
601 |
|
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
|
602 a, x = divmod(a, 30268) |
|
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
|
603 a, y = divmod(a, 30306) |
|
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
|
604 a, z = divmod(a, 30322) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
605 self._seed = int(x)+1, int(y)+1, int(z)+1 |
|
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parents:
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|
606 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
607 self.gauss_next = None |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
608 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
609 def random(self): |
|
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|
610 """Get the next random number in the range [0.0, 1.0).""" |
|
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|
611 |
|
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changeset
|
612 # Wichman-Hill random number generator. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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diff
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|
613 # |
|
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614 # Wichmann, B. A. & Hill, I. D. (1982) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
615 # Algorithm AS 183: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
616 # An efficient and portable pseudo-random number generator |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
617 # Applied Statistics 31 (1982) 188-190 |
|
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618 # |
|
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|
619 # see also: |
|
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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|
620 # 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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|
621 # Applied Statistics 33 (1984) 123 |
|
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Raymond Hettinger <python@rcn.com>
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|
622 # |
|
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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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|
623 # McLeod, A. I. (1985) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
624 # A remark on Algorithm AS 183 |
|
f64c96922708
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Raymond Hettinger <python@rcn.com>
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|
625 # Applied Statistics 34 (1985),198-200 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
626 |
|
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|
627 # This part is thread-unsafe: |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
628 # BEGIN CRITICAL SECTION |
|
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|
629 x, y, z = self._seed |
|
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|
630 x = (171 * x) % 30269 |
|
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|
631 y = (172 * y) % 30307 |
|
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|
632 z = (170 * z) % 30323 |
|
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|
633 self._seed = x, y, z |
|
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|
634 # END CRITICAL SECTION |
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|
635 |
|
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|
636 # Note: on a platform using IEEE-754 double arithmetic, this can |
|
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diff
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|
637 # never return 0.0 (asserted by Tim; proof too long for a comment). |
|
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|
638 return (x/30269.0 + y/30307.0 + z/30323.0) % 1.0 |
|
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changeset
|
639 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
640 def getstate(self): |
|
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diff
changeset
|
641 """Return internal state; can be passed to setstate() later.""" |
|
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|
642 return self.VERSION, self._seed, self.gauss_next |
|
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changeset
|
643 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
644 def setstate(self, state): |
|
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Raymond Hettinger <python@rcn.com>
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|
645 """Restore internal state from object returned by getstate().""" |
|
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|
646 version = state[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
|
647 if version == 1: |
|
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|
648 version, self._seed, self.gauss_next = state |
|
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diff
changeset
|
649 else: |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
650 raise ValueError("state with version %s passed to " |
|
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diff
changeset
|
651 "Random.setstate() of version %s" % |
|
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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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|
652 (version, self.VERSION)) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
653 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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changeset
|
654 def jumpahead(self, n): |
|
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|
655 """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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|
656 |
|
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changeset
|
657 n is an int, greater than or equal to 0. |
|
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changeset
|
658 |
|
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|
659 Example use: If you have 2 threads and know that each will |
|
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|
660 consume no more than a million random numbers, create two Random |
|
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parents:
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diff
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|
661 objects r1 and r2, then do |
|
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|
662 r2.setstate(r1.getstate()) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
663 r2.jumpahead(1000000) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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diff
changeset
|
664 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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|
665 period. |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
666 """ |
|
f64c96922708
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changeset
|
667 |
|
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parents:
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diff
changeset
|
668 if not n >= 0: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
669 raise ValueError("n must be >= 0") |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
670 x, y, z = self._seed |
|
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
|
671 x = int(x * pow(171, n, 30269)) % 30269 |
|
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
|
672 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>
parents:
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diff
changeset
|
673 z = int(z * pow(170, n, 30323)) % 30323 |
|
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
|
674 self._seed = x, y, z |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
675 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
676 def __whseed(self, x=0, y=0, z=0): |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
677 """Set the Wichmann-Hill seed from (x, y, z). |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
678 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
679 These must be integers in the range [0, 256). |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
680 """ |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
681 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
682 if not type(x) == type(y) == type(z) == int: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
683 raise TypeError('seeds must be integers') |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
684 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
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
685 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:
26564
diff
changeset
|
686 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:
26564
diff
changeset
|
687 # Initialize from current time |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
688 import time |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
689 t = long(time.time() * 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
690 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>
parents:
26564
diff
changeset
|
691 t, x = divmod(t, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
692 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:
26564
diff
changeset
|
693 t, z = divmod(t, 256) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
694 # 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>
parents:
26564
diff
changeset
|
695 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:
26564
diff
changeset
|
696 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
697 self.gauss_next = None |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
698 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
699 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:
26564
diff
changeset
|
700 """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:
26564
diff
changeset
|
701 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
702 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:
26564
diff
changeset
|
703 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:
26564
diff
changeset
|
704 states. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
705 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
706 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:
26564
diff
changeset
|
707 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:
26564
diff
changeset
|
708 """ |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
709 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
710 if a is None: |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
711 self.__whseed() |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
712 return |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
713 a = hash(a) |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
714 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:
26564
diff
changeset
|
715 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:
26564
diff
changeset
|
716 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:
26564
diff
changeset
|
717 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
|
718 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:
26564
diff
changeset
|
719 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
|
720 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:
26564
diff
changeset
|
721 |
|
16265
d614b6e9fb4e
Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents:
16243
diff
changeset
|
722 ## -------------------- test program -------------------- |
| 1575 | 723 |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
724 def _test_generator(n, funccall): |
|
15871
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
725 import time |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
726 print n, 'times', funccall |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
727 code = compile(funccall, funccall, 'eval') |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
728 sum = 0.0 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
729 sqsum = 0.0 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
730 smallest = 1e10 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
731 largest = -1e10 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
732 t0 = time.time() |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
733 for i in range(n): |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
734 x = eval(code) |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
735 sum = sum + x |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
736 sqsum = sqsum + x*x |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
737 smallest = min(x, smallest) |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
738 largest = max(x, largest) |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
739 t1 = time.time() |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
740 print round(t1-t0, 3), 'sec,', |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
741 avg = sum/n |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
742 stddev = _sqrt(sqsum/n - avg*avg) |
|
15871
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
743 print 'avg %g, stddev %g, min %g, max %g' % \ |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
744 (avg, stddev, smallest, largest) |
| 1575 | 745 |
|
26155
8ceb455f5541
SF patch 629637: Add sample(population, k) method to the random module.
Raymond Hettinger <python@rcn.com>
parents:
24861
diff
changeset
|
746 |
|
8ceb455f5541
SF patch 629637: Add sample(population, k) method to the random module.
Raymond Hettinger <python@rcn.com>
parents:
24861
diff
changeset
|
747 def _test(N=2000): |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
748 _test_generator(N, 'random()') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
749 _test_generator(N, 'normalvariate(0.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
750 _test_generator(N, 'lognormvariate(0.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
751 _test_generator(N, 'cunifvariate(0.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
752 _test_generator(N, 'vonmisesvariate(0.0, 1.0)') |
|
23447
08ccb0f3e2d4
Closes patch 529408 deprecating random.stdgamma().
Raymond Hettinger <python@rcn.com>
parents:
23442
diff
changeset
|
753 _test_generator(N, 'gammavariate(0.01, 1.0)') |
|
08ccb0f3e2d4
Closes patch 529408 deprecating random.stdgamma().
Raymond Hettinger <python@rcn.com>
parents:
23442
diff
changeset
|
754 _test_generator(N, 'gammavariate(0.1, 1.0)') |
|
23521
a90faa5f9417
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
23451
diff
changeset
|
755 _test_generator(N, 'gammavariate(0.1, 2.0)') |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
756 _test_generator(N, 'gammavariate(0.5, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
757 _test_generator(N, 'gammavariate(0.9, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
758 _test_generator(N, 'gammavariate(1.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
759 _test_generator(N, 'gammavariate(2.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
760 _test_generator(N, 'gammavariate(20.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
761 _test_generator(N, 'gammavariate(200.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
762 _test_generator(N, 'gauss(0.0, 1.0)') |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
763 _test_generator(N, 'betavariate(3.0, 3.0)') |
|
16265
d614b6e9fb4e
Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents:
16243
diff
changeset
|
764 |
|
16292
0501c2a10315
New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents:
16272
diff
changeset
|
765 # Create one instance, seeded from current time, and export its methods |
|
26829
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
766 # as module-level functions. The functions share state across all uses |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
767 #(both in the user's code and in the Python libraries), but that's fine |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
768 # for most programs and is easier for the casual user than making them |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
769 # instantiate their own Random() instance. |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
770 |
|
16242
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
771 _inst = Random() |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
772 seed = _inst.seed |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
773 random = _inst.random |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
774 uniform = _inst.uniform |
|
3c5f09422b69
Reworked random.py so that it no longer depends on, and offers all the
Tim Peters <tim.peters@gmail.com>
parents:
15871
diff
changeset
|
775 randint = _inst.randint |
|
3c5f09422b69
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776 choice = _inst.choice |
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777 randrange = _inst.randrange |
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778 sample = _inst.sample |
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779 shuffle = _inst.shuffle |
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780 normalvariate = _inst.normalvariate |
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781 lognormvariate = _inst.lognormvariate |
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782 cunifvariate = _inst.cunifvariate |
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783 expovariate = _inst.expovariate |
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784 vonmisesvariate = _inst.vonmisesvariate |
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785 gammavariate = _inst.gammavariate |
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786 stdgamma = _inst.stdgamma |
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787 gauss = _inst.gauss |
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788 betavariate = _inst.betavariate |
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789 paretovariate = _inst.paretovariate |
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790 weibullvariate = _inst.weibullvariate |
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791 getstate = _inst.getstate |
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792 setstate = _inst.setstate |
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793 jumpahead = _inst.jumpahead |
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794 |
| 1575 | 795 if __name__ == '__main__': |
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796 _test() |
