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This is documentation for an old release of NumPy (version 1.15). Read this page in the documentation of the latest stable release (version 2.2).

numpy.random.RandomState.set_state

RandomState.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”[1] pseudo-random number generating algorithm.

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

The state tuple has the following items:

  1. the string ‘MT19937’, specifying the Mersenne Twister algorithm.
  2. a 1-D array of 624 unsigned integers keys.
  3. an integer pos.
  4. an integer has_gauss.
  5. a float cached_gaussian.
Returns:
out : None

Returns ‘None’ on success.

See also

get_state

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

[1](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.