Mercurial > cpython-lru_cache-weakref
annotate Lib/random.py @ 80661:94de77bd0b4b 2.7
Issue #16194: document imp.load_dynamic problems
when read several extension modules from the same binary object file.
| author | Andrew Svetlov <andrew.svetlov@gmail.com> |
|---|---|
| date | Thu, 29 Nov 2012 19:51:28 +0200 |
| parents | 4970fa3c4a0b |
| children | 6a3d18cede49 |
| 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 triangular |
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17 normal (Gaussian) |
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18 lognormal |
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19 negative exponential |
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20 gamma |
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21 beta |
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22 pareto |
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23 Weibull |
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25 distributions on the circle (angles 0 to 2pi) |
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26 --------------------------------------------- |
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27 circular uniform |
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28 von Mises |
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30 General notes on the underlying Mersenne Twister core generator: |
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31 |
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32 * The period is 2**19937-1. |
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33 * It is one of the most extensively tested generators in existence. |
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34 * Without a direct way to compute N steps forward, the semantics of |
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35 jumpahead(n) are weakened to simply jump to another distant state and rely |
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36 on the large period to avoid overlapping sequences. |
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37 * The random() method is implemented in C, executes in a single Python step, |
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38 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 __future__ import division |
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43 from warnings import warn as _warn |
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44 from types import MethodType as _MethodType, BuiltinMethodType as _BuiltinMethodType |
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45 from math import log as _log, exp as _exp, pi as _pi, e as _e, ceil as _ceil |
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46 from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin |
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47 from os import urandom as _urandom |
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48 from binascii import hexlify as _hexlify |
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49 import hashlib as _hashlib |
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50 |
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51 __all__ = ["Random","seed","random","uniform","randint","choice","sample", |
| 16613 | 52 "randrange","shuffle","normalvariate","lognormvariate", |
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53 "expovariate","vonmisesvariate","gammavariate","triangular", |
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54 "gauss","betavariate","paretovariate","weibullvariate", |
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55 "getstate","setstate","jumpahead", "WichmannHill", "getrandbits", |
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56 "SystemRandom"] |
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58 NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0) |
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59 TWOPI = 2.0*_pi |
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60 LOG4 = _log(4.0) |
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61 SG_MAGICCONST = 1.0 + _log(4.5) |
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62 BPF = 53 # Number of bits in a float |
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63 RECIP_BPF = 2**-BPF |
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64 |
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65 |
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66 # Translated by Guido van Rossum from C source provided by |
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67 # Adrian Baddeley. Adapted by Raymond Hettinger for use with |
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68 # the Mersenne Twister and os.urandom() core generators. |
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69 |
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70 import _random |
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71 |
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72 class Random(_random.Random): |
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73 """Random number generator base class used by bound module functions. |
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74 |
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75 Used to instantiate instances of Random to get generators that don't |
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76 share state. Especially useful for multi-threaded programs, creating |
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77 a different instance of Random for each thread, and using the jumpahead() |
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78 method to ensure that the generated sequences seen by each thread don't |
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79 overlap. |
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80 |
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81 Class Random can also be subclassed if you want to use a different basic |
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82 generator of your own devising: in that case, override the following |
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83 methods: random(), seed(), getstate(), setstate() and jumpahead(). |
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84 Optionally, implement a getrandbits() method so that randrange() can cover |
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85 arbitrarily large ranges. |
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86 |
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87 """ |
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88 |
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89 VERSION = 3 # used by getstate/setstate |
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90 |
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91 def __init__(self, x=None): |
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92 """Initialize an instance. |
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93 |
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94 Optional argument x controls seeding, as for Random.seed(). |
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95 """ |
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96 |
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97 self.seed(x) |
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98 self.gauss_next = None |
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99 |
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100 def seed(self, a=None): |
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101 """Initialize internal state from hashable object. |
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102 |
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103 None or no argument seeds from current time or from an operating |
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104 system specific randomness source if available. |
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105 |
| 16386 | 106 If a is not None or an int or long, hash(a) is used instead. |
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107 """ |
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108 |
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109 if a is None: |
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110 try: |
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111 a = long(_hexlify(_urandom(16)), 16) |
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112 except NotImplementedError: |
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113 import time |
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114 a = long(time.time() * 256) # use fractional seconds |
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115 |
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116 super(Random, self).seed(a) |
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117 self.gauss_next = None |
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118 |
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119 def getstate(self): |
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120 """Return internal state; can be passed to setstate() later.""" |
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121 return self.VERSION, super(Random, self).getstate(), self.gauss_next |
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122 |
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123 def setstate(self, state): |
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124 """Restore internal state from object returned by getstate().""" |
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125 version = state[0] |
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126 if version == 3: |
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127 version, internalstate, self.gauss_next = state |
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128 super(Random, self).setstate(internalstate) |
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129 elif version == 2: |
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130 version, internalstate, self.gauss_next = state |
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131 # In version 2, the state was saved as signed ints, which causes |
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132 # inconsistencies between 32/64-bit systems. The state is |
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133 # really unsigned 32-bit ints, so we convert negative ints from |
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134 # version 2 to positive longs for version 3. |
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135 try: |
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136 internalstate = tuple( long(x) % (2**32) for x in internalstate ) |
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137 except ValueError, e: |
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138 raise TypeError, e |
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139 super(Random, self).setstate(internalstate) |
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140 else: |
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141 raise ValueError("state with version %s passed to " |
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142 "Random.setstate() of version %s" % |
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143 (version, self.VERSION)) |
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144 |
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145 def jumpahead(self, n): |
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146 """Change the internal state to one that is likely far away |
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147 from the current state. This method will not be in Py3.x, |
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148 so it is better to simply reseed. |
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149 """ |
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150 # The super.jumpahead() method uses shuffling to change state, |
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151 # so it needs a large and "interesting" n to work with. Here, |
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152 # we use hashing to create a large n for the shuffle. |
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153 s = repr(n) + repr(self.getstate()) |
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154 n = int(_hashlib.new('sha512', s).hexdigest(), 16) |
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155 super(Random, self).jumpahead(n) |
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156 |
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157 ## ---- Methods below this point do not need to be overridden when |
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158 ## ---- subclassing for the purpose of using a different core generator. |
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159 |
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160 ## -------------------- pickle support ------------------- |
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161 |
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162 def __getstate__(self): # for pickle |
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163 return self.getstate() |
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164 |
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165 def __setstate__(self, state): # for pickle |
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166 self.setstate(state) |
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167 |
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168 def __reduce__(self): |
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169 return self.__class__, (), self.getstate() |
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170 |
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171 ## -------------------- integer methods ------------------- |
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172 |
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173 def randrange(self, start, stop=None, step=1, int=int, default=None, |
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174 maxwidth=1L<<BPF): |
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175 """Choose a random item from range(start, stop[, step]). |
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176 |
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177 This fixes the problem with randint() which includes the |
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178 endpoint; in Python this is usually not what you want. |
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179 Do not supply the 'int', 'default', and 'maxwidth' arguments. |
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180 """ |
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181 |
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182 # This code is a bit messy to make it fast for the |
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183 # common case while still doing adequate error checking. |
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184 istart = int(start) |
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185 if istart != start: |
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186 raise ValueError, "non-integer arg 1 for randrange()" |
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187 if stop is default: |
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188 if istart > 0: |
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189 if istart >= maxwidth: |
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190 return self._randbelow(istart) |
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191 return int(self.random() * istart) |
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192 raise ValueError, "empty range for randrange()" |
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193 |
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194 # stop argument supplied. |
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195 istop = int(stop) |
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196 if istop != stop: |
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197 raise ValueError, "non-integer stop for randrange()" |
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198 width = istop - istart |
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199 if step == 1 and width > 0: |
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200 # Note that |
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201 # int(istart + self.random()*width) |
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202 # instead would be incorrect. For example, consider istart |
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203 # = -2 and istop = 0. Then the guts would be in |
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204 # -2.0 to 0.0 exclusive on both ends (ignoring that random() |
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205 # might return 0.0), and because int() truncates toward 0, the |
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206 # final result would be -1 or 0 (instead of -2 or -1). |
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207 # istart + int(self.random()*width) |
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208 # would also be incorrect, for a subtler reason: the RHS |
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209 # can return a long, and then randrange() would also return |
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210 # a long, but we're supposed to return an int (for backward |
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211 # compatibility). |
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212 |
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213 if width >= maxwidth: |
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214 return int(istart + self._randbelow(width)) |
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215 return int(istart + int(self.random()*width)) |
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216 if step == 1: |
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217 raise ValueError, "empty range for randrange() (%d,%d, %d)" % (istart, istop, width) |
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218 |
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219 # Non-unit step argument supplied. |
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220 istep = int(step) |
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221 if istep != step: |
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222 raise ValueError, "non-integer step for randrange()" |
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223 if istep > 0: |
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224 n = (width + istep - 1) // istep |
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225 elif istep < 0: |
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226 n = (width + istep + 1) // istep |
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227 else: |
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228 raise ValueError, "zero step for randrange()" |
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229 |
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230 if n <= 0: |
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231 raise ValueError, "empty range for randrange()" |
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232 |
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233 if n >= maxwidth: |
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234 return istart + istep*self._randbelow(n) |
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235 return istart + istep*int(self.random() * n) |
| 1575 | 236 |
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237 def randint(self, a, b): |
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238 """Return random integer in range [a, b], including both end points. |
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239 """ |
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240 |
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241 return self.randrange(a, b+1) |
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242 |
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243 def _randbelow(self, n, _log=_log, int=int, _maxwidth=1L<<BPF, |
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244 _Method=_MethodType, _BuiltinMethod=_BuiltinMethodType): |
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245 """Return a random int in the range [0,n) |
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246 |
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247 Handles the case where n has more bits than returned |
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248 by a single call to the underlying generator. |
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249 """ |
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250 |
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251 try: |
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252 getrandbits = self.getrandbits |
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253 except AttributeError: |
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254 pass |
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255 else: |
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256 # Only call self.getrandbits if the original random() builtin method |
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257 # has not been overridden or if a new getrandbits() was supplied. |
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258 # This assures that the two methods correspond. |
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259 if type(self.random) is _BuiltinMethod or type(getrandbits) is _Method: |
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260 k = int(1.00001 + _log(n-1, 2.0)) # 2**k > n-1 > 2**(k-2) |
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261 r = getrandbits(k) |
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262 while r >= n: |
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263 r = getrandbits(k) |
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264 return r |
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265 if n >= _maxwidth: |
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266 _warn("Underlying random() generator does not supply \n" |
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267 "enough bits to choose from a population range this large") |
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268 return int(self.random() * n) |
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269 |
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270 ## -------------------- sequence methods ------------------- |
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271 |
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272 def choice(self, seq): |
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273 """Choose a random element from a non-empty sequence.""" |
| 32287 | 274 return seq[int(self.random() * len(seq))] # raises IndexError if seq is empty |
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275 |
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276 def shuffle(self, x, random=None, int=int): |
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277 """x, random=random.random -> shuffle list x in place; return None. |
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278 |
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279 Optional arg random is a 0-argument function returning a random |
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280 float in [0.0, 1.0); by default, the standard random.random. |
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281 """ |
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282 |
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283 if random is None: |
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284 random = self.random |
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285 for i in reversed(xrange(1, len(x))): |
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286 # pick an element in x[:i+1] with which to exchange x[i] |
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287 j = int(random() * (i+1)) |
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288 x[i], x[j] = x[j], x[i] |
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289 |
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290 def sample(self, population, k): |
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291 """Chooses k unique random elements from a population sequence. |
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292 |
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293 Returns a new list containing elements from the population while |
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294 leaving the original population unchanged. The resulting list is |
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295 in selection order so that all sub-slices will also be valid random |
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296 samples. This allows raffle winners (the sample) to be partitioned |
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297 into grand prize and second place winners (the subslices). |
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298 |
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299 Members of the population need not be hashable or unique. If the |
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300 population contains repeats, then each occurrence is a possible |
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301 selection in the sample. |
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302 |
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303 To choose a sample in a range of integers, use xrange as an argument. |
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304 This is especially fast and space efficient for sampling from a |
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305 large population: sample(xrange(10000000), 60) |
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306 """ |
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307 |
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308 # Sampling without replacement entails tracking either potential |
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309 # selections (the pool) in a list or previous selections in a set. |
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310 |
| 31578 | 311 # When the number of selections is small compared to the |
| 312 # population, then tracking selections is efficient, requiring | |
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313 # only a small set and an occasional reselection. For |
| 31578 | 314 # a larger number of selections, the pool tracking method is |
| 315 # preferred since the list takes less space than the | |
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316 # set and it doesn't suffer from frequent reselections. |
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317 |
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318 n = len(population) |
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319 if not 0 <= k <= n: |
| 70193 | 320 raise ValueError("sample larger than population") |
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321 random = self.random |
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322 _int = int |
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323 result = [None] * k |
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324 setsize = 21 # size of a small set minus size of an empty list |
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325 if k > 5: |
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326 setsize += 4 ** _ceil(_log(k * 3, 4)) # table size for big sets |
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327 if n <= setsize or hasattr(population, "keys"): |
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328 # An n-length list is smaller than a k-length set, or this is a |
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329 # mapping type so the other algorithm wouldn't work. |
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330 pool = list(population) |
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331 for i in xrange(k): # invariant: non-selected at [0,n-i) |
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332 j = _int(random() * (n-i)) |
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333 result[i] = pool[j] |
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334 pool[j] = pool[n-i-1] # move non-selected item into vacancy |
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335 else: |
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336 try: |
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337 selected = set() |
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338 selected_add = selected.add |
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339 for i in xrange(k): |
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340 j = _int(random() * n) |
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341 while j in selected: |
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342 j = _int(random() * n) |
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343 selected_add(j) |
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344 result[i] = population[j] |
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345 except (TypeError, KeyError): # handle (at least) sets |
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346 if isinstance(population, list): |
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347 raise |
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348 return self.sample(tuple(population), k) |
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349 return result |
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350 |
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351 ## -------------------- real-valued distributions ------------------- |
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352 |
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353 ## -------------------- uniform distribution ------------------- |
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354 |
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355 def uniform(self, a, b): |
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356 "Get a random number in the range [a, b) or [a, b] depending on rounding." |
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357 return a + (b-a) * self.random() |
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359 ## -------------------- triangular -------------------- |
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360 |
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361 def triangular(self, low=0.0, high=1.0, mode=None): |
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362 """Triangular distribution. |
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363 |
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364 Continuous distribution bounded by given lower and upper limits, |
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365 and having a given mode value in-between. |
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366 |
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367 http://en.wikipedia.org/wiki/Triangular_distribution |
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368 |
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369 """ |
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370 u = self.random() |
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371 c = 0.5 if mode is None else (mode - low) / (high - low) |
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372 if u > c: |
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373 u = 1.0 - u |
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374 c = 1.0 - c |
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375 low, high = high, low |
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376 return low + (high - low) * (u * c) ** 0.5 |
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377 |
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378 ## -------------------- normal distribution -------------------- |
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380 def normalvariate(self, mu, sigma): |
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381 """Normal distribution. |
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382 |
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383 mu is the mean, and sigma is the standard deviation. |
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384 |
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385 """ |
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386 # mu = mean, sigma = standard deviation |
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387 |
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388 # Uses Kinderman and Monahan method. Reference: Kinderman, |
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389 # A.J. and Monahan, J.F., "Computer generation of random |
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390 # variables using the ratio of uniform deviates", ACM Trans |
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391 # Math Software, 3, (1977), pp257-260. |
| 1575 | 392 |
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393 random = self.random |
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394 while 1: |
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395 u1 = random() |
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396 u2 = 1.0 - random() |
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397 z = NV_MAGICCONST*(u1-0.5)/u2 |
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398 zz = z*z/4.0 |
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399 if zz <= -_log(u2): |
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400 break |
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401 return mu + z*sigma |
| 1575 | 402 |
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403 ## -------------------- lognormal distribution -------------------- |
| 1575 | 404 |
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405 def lognormvariate(self, mu, sigma): |
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406 """Log normal distribution. |
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407 |
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408 If you take the natural logarithm of this distribution, you'll get a |
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409 normal distribution with mean mu and standard deviation sigma. |
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410 mu can have any value, and sigma must be greater than zero. |
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411 |
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412 """ |
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413 return _exp(self.normalvariate(mu, sigma)) |
| 1575 | 414 |
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415 ## -------------------- exponential distribution -------------------- |
| 1575 | 416 |
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417 def expovariate(self, lambd): |
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418 """Exponential distribution. |
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419 |
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420 lambd is 1.0 divided by the desired mean. It should be |
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421 nonzero. (The parameter would be called "lambda", but that is |
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422 a reserved word in Python.) Returned values range from 0 to |
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423 positive infinity if lambd is positive, and from negative |
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424 infinity to 0 if lambd is negative. |
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425 |
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426 """ |
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427 # lambd: rate lambd = 1/mean |
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428 # ('lambda' is a Python reserved word) |
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430 # we use 1-random() instead of random() to preclude the |
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431 # possibility of taking the log of zero. |
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432 return -_log(1.0 - self.random())/lambd |
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434 ## -------------------- von Mises distribution -------------------- |
| 1575 | 435 |
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436 def vonmisesvariate(self, mu, kappa): |
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437 """Circular data distribution. |
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438 |
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439 mu is the mean angle, expressed in radians between 0 and 2*pi, and |
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440 kappa is the concentration parameter, which must be greater than or |
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441 equal to zero. If kappa is equal to zero, this distribution reduces |
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442 to a uniform random angle over the range 0 to 2*pi. |
|
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443 |
|
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|
444 """ |
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|
445 # mu: mean angle (in radians between 0 and 2*pi) |
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|
446 # kappa: concentration parameter kappa (>= 0) |
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|
447 # if kappa = 0 generate uniform random angle |
| 1575 | 448 |
|
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|
449 # Based upon an algorithm published in: Fisher, N.I., |
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|
450 # "Statistical Analysis of Circular Data", Cambridge |
|
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|
451 # University Press, 1993. |
|
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|
452 |
|
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|
453 # Thanks to Magnus Kessler for a correction to the |
|
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454 # implementation of step 4. |
|
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|
455 |
|
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456 random = self.random |
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457 if kappa <= 1e-6: |
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458 return TWOPI * random() |
|
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459 |
|
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460 a = 1.0 + _sqrt(1.0 + 4.0 * kappa * kappa) |
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461 b = (a - _sqrt(2.0 * a))/(2.0 * kappa) |
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462 r = (1.0 + b * b)/(2.0 * b) |
| 1575 | 463 |
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464 while 1: |
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|
465 u1 = random() |
| 1575 | 466 |
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467 z = _cos(_pi * u1) |
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468 f = (1.0 + r * z)/(r + z) |
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|
469 c = kappa * (r - f) |
| 1575 | 470 |
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471 u2 = random() |
| 1575 | 472 |
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473 if u2 < c * (2.0 - c) or u2 <= c * _exp(1.0 - c): |
|
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474 break |
| 1575 | 475 |
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476 u3 = random() |
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477 if u3 > 0.5: |
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478 theta = (mu % TWOPI) + _acos(f) |
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479 else: |
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480 theta = (mu % TWOPI) - _acos(f) |
| 1575 | 481 |
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482 return theta |
| 1575 | 483 |
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484 ## -------------------- gamma distribution -------------------- |
| 1575 | 485 |
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|
486 def gammavariate(self, alpha, beta): |
|
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487 """Gamma distribution. Not the gamma function! |
|
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488 |
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489 Conditions on the parameters are alpha > 0 and beta > 0. |
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490 |
|
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491 The probability distribution function is: |
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492 |
|
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493 x ** (alpha - 1) * math.exp(-x / beta) |
|
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494 pdf(x) = -------------------------------------- |
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|
495 math.gamma(alpha) * beta ** alpha |
|
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496 |
|
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497 """ |
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498 |
|
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|
499 # alpha > 0, beta > 0, mean is alpha*beta, variance is alpha*beta**2 |
|
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500 |
|
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501 # Warning: a few older sources define the gamma distribution in terms |
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502 # of alpha > -1.0 |
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503 if alpha <= 0.0 or beta <= 0.0: |
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504 raise ValueError, 'gammavariate: alpha and beta must be > 0.0' |
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|
505 |
|
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506 random = self.random |
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507 if alpha > 1.0: |
| 1575 | 508 |
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|
509 # Uses R.C.H. Cheng, "The generation of Gamma |
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|
510 # variables with non-integral shape parameters", |
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|
511 # Applied Statistics, (1977), 26, No. 1, p71-74 |
| 1575 | 512 |
|
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513 ainv = _sqrt(2.0 * alpha - 1.0) |
|
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|
514 bbb = alpha - LOG4 |
|
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|
515 ccc = alpha + ainv |
|
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|
516 |
|
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517 while 1: |
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|
518 u1 = random() |
|
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|
519 if not 1e-7 < u1 < .9999999: |
|
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|
520 continue |
|
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|
521 u2 = 1.0 - random() |
|
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|
522 v = _log(u1/(1.0-u1))/ainv |
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|
523 x = alpha*_exp(v) |
|
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|
524 z = u1*u1*u2 |
|
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|
525 r = bbb+ccc*v-x |
|
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|
526 if r + SG_MAGICCONST - 4.5*z >= 0.0 or r >= _log(z): |
|
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|
527 return x * beta |
| 1575 | 528 |
|
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|
529 elif alpha == 1.0: |
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|
530 # expovariate(1) |
|
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|
531 u = random() |
|
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|
532 while u <= 1e-7: |
|
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|
533 u = random() |
|
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|
534 return -_log(u) * beta |
| 1575 | 535 |
|
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|
536 else: # alpha is between 0 and 1 (exclusive) |
| 1575 | 537 |
|
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|
538 # Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle |
| 1575 | 539 |
|
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|
540 while 1: |
|
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changeset
|
541 u = random() |
|
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|
542 b = (_e + alpha)/_e |
|
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changeset
|
543 p = b*u |
|
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|
544 if p <= 1.0: |
|
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|
545 x = p ** (1.0/alpha) |
|
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|
546 else: |
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|
547 x = -_log((b-p)/alpha) |
|
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|
548 u1 = random() |
|
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|
549 if p > 1.0: |
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|
550 if u1 <= x ** (alpha - 1.0): |
|
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|
551 break |
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|
552 elif u1 <= _exp(-x): |
|
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|
553 break |
|
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|
554 return x * beta |
|
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|
555 |
|
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|
556 ## -------------------- Gauss (faster alternative) -------------------- |
|
1576
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Added gauss() (same as normal but twice as fast) and betavariate();
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|
557 |
|
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|
558 def gauss(self, mu, sigma): |
|
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|
559 """Gaussian distribution. |
|
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|
560 |
|
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|
561 mu is the mean, and sigma is the standard deviation. This is |
|
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|
562 slightly faster than the normalvariate() function. |
|
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563 |
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|
564 Not thread-safe without a lock around calls. |
|
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|
565 |
|
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|
566 """ |
|
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567 |
|
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|
568 # When x and y are two variables from [0, 1), uniformly |
|
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|
569 # distributed, then |
|
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Reworked random.py so that it no longer depends on, and offers all the
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|
570 # |
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571 # cos(2*pi*x)*sqrt(-2*log(1-y)) |
|
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|
572 # sin(2*pi*x)*sqrt(-2*log(1-y)) |
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573 # |
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574 # are two *independent* variables with normal distribution |
|
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|
575 # (mu = 0, sigma = 1). |
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Reworked random.py so that it no longer depends on, and offers all the
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|
576 # (Lambert Meertens) |
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|
577 # (corrected version; bug discovered by Mike Miller, fixed by LM) |
|
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|
578 |
|
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|
579 # Multithreading note: When two threads call this function |
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580 # simultaneously, it is possible that they will receive the |
|
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|
581 # same return value. The window is very small though. To |
|
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582 # avoid this, you have to use a lock around all calls. (I |
|
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|
583 # didn't want to slow this down in the serial case by using a |
|
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|
584 # lock here.) |
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585 |
|
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586 random = self.random |
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|
587 z = self.gauss_next |
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588 self.gauss_next = None |
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589 if z is None: |
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590 x2pi = random() * TWOPI |
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591 g2rad = _sqrt(-2.0 * _log(1.0 - random())) |
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592 z = _cos(x2pi) * g2rad |
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593 self.gauss_next = _sin(x2pi) * g2rad |
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594 |
|
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595 return mu + z*sigma |
|
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|
596 |
|
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|
597 ## -------------------- beta -------------------- |
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|
598 ## See |
|
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|
599 ## http://mail.python.org/pipermail/python-bugs-list/2001-January/003752.html |
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|
600 ## for Ivan Frohne's insightful analysis of why the original implementation: |
|
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|
601 ## |
|
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|
602 ## def betavariate(self, alpha, beta): |
|
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603 ## # Discrete Event Simulation in C, pp 87-88. |
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604 ## |
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|
605 ## y = self.expovariate(alpha) |
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606 ## z = self.expovariate(1.0/beta) |
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607 ## return z/(y+z) |
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608 ## |
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|
609 ## was dead wrong, and how it probably got that way. |
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610 |
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611 def betavariate(self, alpha, beta): |
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612 """Beta distribution. |
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613 |
|
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614 Conditions on the parameters are alpha > 0 and beta > 0. |
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|
615 Returned values range between 0 and 1. |
|
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616 |
|
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617 """ |
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618 |
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|
619 # This version due to Janne Sinkkonen, and matches all the std |
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|
620 # texts (e.g., Knuth Vol 2 Ed 3 pg 134 "the beta distribution"). |
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|
621 y = self.gammavariate(alpha, 1.) |
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622 if y == 0: |
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623 return 0.0 |
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|
624 else: |
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|
625 return y / (y + self.gammavariate(beta, 1.)) |
|
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|
626 |
|
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|
627 ## -------------------- Pareto -------------------- |
|
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|
628 |
|
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|
629 def paretovariate(self, alpha): |
|
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630 """Pareto distribution. alpha is the shape parameter.""" |
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|
631 # Jain, pg. 495 |
|
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|
632 |
|
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|
633 u = 1.0 - self.random() |
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|
634 return 1.0 / pow(u, 1.0/alpha) |
|
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|
635 |
|
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636 ## -------------------- Weibull -------------------- |
|
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|
637 |
|
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|
638 def weibullvariate(self, alpha, beta): |
|
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639 """Weibull distribution. |
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|
640 |
|
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|
641 alpha is the scale parameter and beta is the shape parameter. |
|
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|
642 |
|
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|
643 """ |
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|
644 # Jain, pg. 499; bug fix courtesy Bill Arms |
|
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Add Tim Peters' shuffle() algorithm.
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|
645 |
|
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|
646 u = 1.0 - self.random() |
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647 return alpha * pow(-_log(u), 1.0/beta) |
|
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648 |
|
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|
649 ## -------------------- Wichmann-Hill ------------------- |
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650 |
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651 class WichmannHill(Random): |
|
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|
652 |
|
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|
653 VERSION = 1 # used by getstate/setstate |
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654 |
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655 def seed(self, a=None): |
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656 """Initialize internal state from hashable object. |
|
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657 |
|
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|
658 None or no argument seeds from current time or from an operating |
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659 system specific randomness source if available. |
|
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|
660 |
|
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|
661 If a is not None or an int or long, hash(a) is used instead. |
|
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|
662 |
|
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663 If a is an int or long, a is used directly. Distinct values between |
|
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|
664 0 and 27814431486575L inclusive are guaranteed to yield distinct |
|
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|
665 internal states (this guarantee is specific to the default |
|
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|
666 Wichmann-Hill generator). |
|
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|
667 """ |
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668 |
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669 if a is None: |
|
33409
8e23bd3d5b1a
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|
670 try: |
|
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671 a = long(_hexlify(_urandom(16)), 16) |
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672 except NotImplementedError: |
|
33329
97fca735c8da
Teach the random module about os.urandom().
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673 import time |
|
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Teach the random module about os.urandom().
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674 a = long(time.time() * 256) # use fractional seconds |
|
26829
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|
675 |
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676 if not isinstance(a, (int, long)): |
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677 a = hash(a) |
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|
678 |
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|
679 a, x = divmod(a, 30268) |
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680 a, y = divmod(a, 30306) |
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|
681 a, z = divmod(a, 30322) |
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682 self._seed = int(x)+1, int(y)+1, int(z)+1 |
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|
683 |
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|
684 self.gauss_next = None |
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|
685 |
|
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|
686 def random(self): |
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687 """Get the next random number in the range [0.0, 1.0).""" |
|
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688 |
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|
689 # Wichman-Hill random number generator. |
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690 # |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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691 # Wichmann, B. A. & Hill, I. D. (1982) |
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|
692 # Algorithm AS 183: |
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693 # An efficient and portable pseudo-random number generator |
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694 # Applied Statistics 31 (1982) 188-190 |
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|
695 # |
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|
696 # see also: |
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
697 # Correction to Algorithm AS 183 |
|
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|
698 # Applied Statistics 33 (1984) 123 |
|
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|
699 # |
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700 # McLeod, A. I. (1985) |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
701 # A remark on Algorithm AS 183 |
|
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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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|
702 # Applied Statistics 34 (1985),198-200 |
|
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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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|
703 |
|
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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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|
704 # 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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changeset
|
705 # BEGIN CRITICAL SECTION |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
706 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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|
707 x = (171 * x) % 30269 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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|
708 y = (172 * y) % 30307 |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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diff
changeset
|
709 z = (170 * z) % 30323 |
|
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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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|
710 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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|
711 # END CRITICAL SECTION |
|
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SF patch 658251: Install a C implementation of the Mersenne Twister as the
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diff
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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diff
changeset
|
713 # Note: on a platform using IEEE-754 double arithmetic, this can |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
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changeset
|
714 # never return 0.0 (asserted by Tim; proof too long for a comment). |
|
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
|
715 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
Raymond Hettinger <python@rcn.com>
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diff
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|
716 |
|
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
|
717 def getstate(self): |
|
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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 """Return internal state; can be passed to setstate() later.""" |
|
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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|
719 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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parents:
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diff
changeset
|
720 |
|
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
|
721 def setstate(self, state): |
|
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
|
722 """Restore internal state from object returned by getstate().""" |
|
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 version = state[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
|
724 if version == 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
|
725 version, self._seed, self.gauss_next = state |
|
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
|
726 else: |
|
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
|
727 raise ValueError("state with version %s passed to " |
|
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
|
728 "Random.setstate() of version %s" % |
|
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
|
729 (version, self.VERSION)) |
|
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
|
730 |
|
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
|
731 def jumpahead(self, n): |
|
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
|
732 """Act as if n calls to random() were made, but quickly. |
|
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 n is an int, greater than or equal to 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
|
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 Example use: If you have 2 threads and know that each will |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
737 consume no more than a million random numbers, create two Random |
|
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 objects r1 and r2, then do |
|
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 r2.setstate(r1.getstate()) |
|
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 r2.jumpahead(1000000) |
|
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 Then r1 and r2 will use guaranteed-disjoint segments of the full |
|
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 period. |
|
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 """ |
|
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 |
|
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 if not n >= 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
|
746 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:
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diff
changeset
|
747 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
|
748 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
|
749 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:
26564
diff
changeset
|
750 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
|
751 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:
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diff
changeset
|
752 |
|
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 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
|
754 """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:
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diff
changeset
|
755 |
|
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 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:
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diff
changeset
|
757 """ |
|
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 |
|
f64c96922708
SF patch 658251: Install a C implementation of the Mersenne Twister as the
Raymond Hettinger <python@rcn.com>
parents:
26564
diff
changeset
|
759 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:
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diff
changeset
|
760 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:
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diff
changeset
|
761 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
|
762 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
|
763 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
|
764 # Initialize from current time |
|
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
|
765 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
|
766 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
|
767 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
|
768 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
|
769 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
|
770 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
|
771 # 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
|
772 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
|
773 |
|
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
|
774 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
|
775 |
|
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
|
776 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
|
777 """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
|
778 |
|
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
|
779 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
|
780 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
|
781 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
|
782 |
|
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
|
783 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
|
784 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
|
785 """ |
|
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
|
786 |
|
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
|
787 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
|
788 self.__whseed() |
|
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
|
789 return |
|
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
|
790 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
|
791 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
|
792 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
|
793 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
|
794 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:
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diff
changeset
|
795 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
|
796 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
|
797 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
|
798 |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
799 ## --------------- Operating System Random Source ------------------ |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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changeset
|
800 |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
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parents:
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diff
changeset
|
801 class SystemRandom(Random): |
|
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
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parents:
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diff
changeset
|
802 """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
|
803 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
|
804 CryptGenRandom on Windows). |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
805 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
806 Not available on all systems (see os.urandom() for details). |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
807 """ |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
808 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
809 def random(self): |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
810 """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
|
811 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
|
812 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
813 def getrandbits(self, k): |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
814 """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
|
815 if k <= 0: |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
816 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
|
817 if k != int(k): |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
818 raise TypeError('number of bits should be an integer') |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
819 bytes = (k + 7) // 8 # bits / 8 and rounded up |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
820 x = long(_hexlify(_urandom(bytes)), 16) |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
821 return x >> (bytes * 8 - k) # trim excess bits |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
822 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
823 def _stub(self, *args, **kwds): |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
33409
diff
changeset
|
824 "Stub method. Not used for a system random number generator." |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
825 return None |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
826 seed = jumpahead = _stub |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
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diff
changeset
|
827 |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
828 def _notimplemented(self, *args, **kwds): |
|
33481
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
33409
diff
changeset
|
829 "Method should not be called for a system random number generator." |
|
eacdc29606d8
SF #1027105: HardwareRandom should be renamed OSRandom
Raymond Hettinger <python@rcn.com>
parents:
33409
diff
changeset
|
830 raise NotImplementedError('System entropy source does not have state.') |
|
33329
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
831 getstate = setstate = _notimplemented |
|
97fca735c8da
Teach the random module about os.urandom().
Raymond Hettinger <python@rcn.com>
parents:
32287
diff
changeset
|
832 |
|
16265
d614b6e9fb4e
Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents:
16243
diff
changeset
|
833 ## -------------------- test program -------------------- |
| 1575 | 834 |
|
30243
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
835 def _test_generator(n, func, args): |
|
15871
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
836 import time |
|
30243
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
837 print n, 'times', func.__name__ |
|
29250
34609fa35b11
'sum' is no longer a good variable name. Use 'total' instead.
Raymond Hettinger <python@rcn.com>
parents:
27279
diff
changeset
|
838 total = 0.0 |
|
15871
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
839 sqsum = 0.0 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
840 smallest = 1e10 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
841 largest = -1e10 |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
842 t0 = time.time() |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
843 for i in range(n): |
|
30243
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
844 x = func(*args) |
|
29250
34609fa35b11
'sum' is no longer a good variable name. Use 'total' instead.
Raymond Hettinger <python@rcn.com>
parents:
27279
diff
changeset
|
845 total += x |
|
15871
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
846 sqsum = sqsum + x*x |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
847 smallest = min(x, smallest) |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
848 largest = max(x, largest) |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
849 t1 = time.time() |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
850 print round(t1-t0, 3), 'sec,', |
|
29250
34609fa35b11
'sum' is no longer a good variable name. Use 'total' instead.
Raymond Hettinger <python@rcn.com>
parents:
27279
diff
changeset
|
851 avg = total/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
|
852 stddev = _sqrt(sqsum/n - avg*avg) |
|
15871
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
853 print 'avg %g, stddev %g, min %g, max %g' % \ |
|
62aeefa01fdd
Whitespace normalization.
Tim Peters <tim.peters@gmail.com>
parents:
14617
diff
changeset
|
854 (avg, stddev, smallest, largest) |
| 1575 | 855 |
|
26155
8ceb455f5541
SF patch 629637: Add sample(population, k) method to the random module.
Raymond Hettinger <python@rcn.com>
parents:
24861
diff
changeset
|
856 |
|
8ceb455f5541
SF patch 629637: Add sample(population, k) method to the random module.
Raymond Hettinger <python@rcn.com>
parents:
24861
diff
changeset
|
857 def _test(N=2000): |
|
30243
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
858 _test_generator(N, random, ()) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
859 _test_generator(N, normalvariate, (0.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
860 _test_generator(N, lognormvariate, (0.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
861 _test_generator(N, vonmisesvariate, (0.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
862 _test_generator(N, gammavariate, (0.01, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
863 _test_generator(N, gammavariate, (0.1, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
864 _test_generator(N, gammavariate, (0.1, 2.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
865 _test_generator(N, gammavariate, (0.5, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
866 _test_generator(N, gammavariate, (0.9, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
867 _test_generator(N, gammavariate, (1.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
868 _test_generator(N, gammavariate, (2.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
869 _test_generator(N, gammavariate, (20.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
870 _test_generator(N, gammavariate, (200.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
871 _test_generator(N, gauss, (0.0, 1.0)) |
|
53a322c6de52
Eliminate unnecessary eval() in tests
Raymond Hettinger <python@rcn.com>
parents:
30114
diff
changeset
|
872 _test_generator(N, betavariate, (3.0, 3.0)) |
|
46029
f1e51785947f
Issue 1681432: Add triangular distribution the random module.
Raymond Hettinger <python@rcn.com>
parents:
44122
diff
changeset
|
873 _test_generator(N, triangular, (0.0, 1.0, 1.0/3.0)) |
|
16265
d614b6e9fb4e
Cosmetic changes after some sleep; no change in semantics.
Tim Peters <tim.peters@gmail.com>
parents:
16243
diff
changeset
|
874 |
|
16292
0501c2a10315
New comment block to Clarify a subtlety.
Tim Peters <tim.peters@gmail.com>
parents:
16272
diff
changeset
|
875 # 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
|
876 # 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
|
877 #(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
|
878 # 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
|
879 # 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
|
880 |
|
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
|
881 _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
|
882 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:
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883 random = _inst.random |
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884 uniform = _inst.uniform |
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885 triangular = _inst.triangular |
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886 randint = _inst.randint |
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887 choice = _inst.choice |
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888 randrange = _inst.randrange |
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889 sample = _inst.sample |
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890 shuffle = _inst.shuffle |
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891 normalvariate = _inst.normalvariate |
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892 lognormvariate = _inst.lognormvariate |
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893 expovariate = _inst.expovariate |
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894 vonmisesvariate = _inst.vonmisesvariate |
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895 gammavariate = _inst.gammavariate |
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896 gauss = _inst.gauss |
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897 betavariate = _inst.betavariate |
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898 paretovariate = _inst.paretovariate |
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899 weibullvariate = _inst.weibullvariate |
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900 getstate = _inst.getstate |
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901 setstate = _inst.setstate |
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902 jumpahead = _inst.jumpahead |
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903 getrandbits = _inst.getrandbits |
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904 |
| 1575 | 905 if __name__ == '__main__': |
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906 _test() |
