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98 lines
2.4 KiB
Python
98 lines
2.4 KiB
Python
# WICHMANN-HILL RANDOM NUMBER GENERATOR
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#
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# Wichmann, B. A. & Hill, I. D. (1982)
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# Algorithm AS 183:
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# An efficient and portable pseudo-random number generator
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# Applied Statistics 31 (1982) 188-190
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#
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# see also:
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# Correction to Algorithm AS 183
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# Applied Statistics 33 (1984) 123
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#
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# McLeod, A. I. (1985)
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# A remark on Algorithm AS 183
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# Applied Statistics 34 (1985),198-200
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#
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#
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# USE:
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# whrandom.random() yields double precision random numbers
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# uniformly distributed between 0 and 1.
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#
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# whrandom.seed(x, y, z) must be called before whrandom.random()
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# to seed the generator
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#
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# There is also an interface to create multiple independent
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# random generators, and to choose from other ranges.
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# Translated by Guido van Rossum from C source provided by
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# Adrian Baddeley.
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class whrandom:
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#
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# Initialize an instance.
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# Without arguments, initialize from current time.
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# With arguments (x, y, z), initialize from them.
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#
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def __init__(self, x = 0, y = 0, z = 0):
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self.seed(x, y, z)
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#
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# Set the seed from (x, y, z).
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# These must be integers in the range [0, 256).
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#
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def seed(self, x = 0, y = 0, z = 0):
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if not type(x) == type(y) == type(z) == type(0):
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raise TypeError, 'seeds must be integers'
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if not 0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256:
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raise ValueError, 'seeds must be in range(0, 256)'
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if 0 == x == y == z:
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# Initialize from current time
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import time
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t = int(time.time() % 0x80000000)
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t, x = divmod(t, 256)
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t, y = divmod(t, 256)
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t, z = divmod(t, 256)
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self._seed = (x, y, z)
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#
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# Get the next random number in the range [0.0, 1.0).
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#
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def random(self):
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x, y, z = self._seed
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#
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x1, x2 = divmod(x, 177)
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y1, y2 = divmod(y, 176)
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z1, z2 = divmod(z, 178)
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#
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x = (171 * x2 - 2 * x1) % 30269
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y = (172 * y2 - 35 * y1) % 30307
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z = (170 * z2 - 63 * z1) % 30323
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#
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self._seed = x, y, z
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#
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return (x/30269.0 + y/30307.0 + z/30323.0) % 1.0
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#
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# Get a random number in the range [a, b).
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#
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def uniform(self, a, b):
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return a + (b-a) * self.random()
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#
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# Get a random integer in the range [a, b] including both end points.
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#
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def randint(self, a, b):
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return a + int(self.random() * (b+1-a))
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#
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# Choose a random element from a non-empty sequence.
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#
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def choice(self, seq):
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return seq[int(self.random() * len(seq))]
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# Initialize from the current time
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#
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_inst = whrandom()
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seed = _inst.seed
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random = _inst.random
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uniform = _inst.uniform
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randint = _inst.randint
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choice = _inst.choice
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