numpy.random.set_state()

numpy.random.set_state(state)

Set the internal state of the generator from a tuple.

For use if one has reason to manually (re-)set the internal state of the ?Mersenne Twister?[R261] pseudo-random number generating algorithm.

Parameters:

Parameters:	state : tuple(str, ndarray of 624 uints, int, int, float) The `state` tuple has the following items: the string ?MT19937?, specifying the Mersenne Twister algorithm. a 1-D array of 624 unsigned integers `keys`. an integer `pos`. an integer `has_gauss`. a float `cached_gaussian`.
Returns:	out : None Returns ?None? on success.

state : tuple(str, ndarray of 624 uints, int, int, float)

The state tuple has the following items:

the string ?MT19937?, specifying the Mersenne Twister algorithm.
a 1-D array of 624 unsigned integers keys.
an integer pos.
an integer has_gauss.
a float cached_gaussian.

Returns:

out : None

Returns ?None? on success.

Notes

set_state and get_state are not needed to work with any of the random distributions in NumPy. If the internal state is manually altered, the user should know exactly what he/she is doing.

For backwards compatibility, the form (str, array of 624 uints, int) is also accepted although it is missing some information about the cached Gaussian value: state = ('MT19937', keys, pos).

References

[R261]

(1, 2) M. Matsumoto and T. Nishimura, ?Mersenne Twister: A 623-dimensionally equidistributed uniform pseudorandom number generator,? ACM Trans. on Modeling and Computer Simulation, Vol. 8, No. 1, pp. 3-30, Jan. 1998.

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.random.set_state.html

doc_NumPy

2017-01-10 18:18:16

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