# numpy.random.set_state

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 bit generator used by the RandomState instance. By default, RandomState uses the “Mersenne Twister”[1] pseudo-random number generating algorithm.

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

      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`.

      If state is a dictionary, it is directly set using the BitGenerators state property.

  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]

  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.