mt19937predictor module¶
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mt19937predictor.
LOWER_MASK
= 2147483647¶
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mt19937predictor.
M
= 397¶
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mt19937predictor.
MATRIX_A
= 2567483615¶
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class
mt19937predictor.
MT19937Predictor
[source]¶ Bases:
random.Random
Usage:
>>> import random >>> from mt19937predictor import MT19937Predictor >>> predictor = MT19937Predictor() >>> for _ in range(624): ... x = random.getrandbits(32) ... predictor.setrandbits(x, 32) >>> random.getrandbits(32) == predictor.getrandbits(32) True >>> random.random() == predictor.random() True >>> a = list(range(100)) >>> b = list(range(100)) >>> random.shuffle(a) >>> predictor.shuffle(b) >>> a == b True
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gauss
(*args)[source]¶ Raises: NotImplementedError
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getrandbits
(bits)[source]¶ The interface for
random.Random.getrandbits()
in Python’s Standard Library
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getstate
(*args)[source]¶ Raises: NotImplementedError
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seed
(*args)[source]¶ Raises: NotImplementedError
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setrand_int32
(y)[source]¶ Feceive the target PRNG’s outputs and reconstruct the inner state. when 624 consecutive DOWRDs is given, the inner state is uniquely determined.
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setrandbits
(y, bits)[source]¶ The interface for
random.Random.getrandbits()
in Python’s Standard Library
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setstate
(*args)[source]¶ Raises: NotImplementedError
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mt19937predictor.
N
= 624¶ 624 values (of 32bit) is just enough to reconstruct the internal state
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mt19937predictor.
UPPER_MASK
= 2147483648¶