class RandomState(object):
'''
RandomState(seed=None)
Container for the slow Mersenne Twister pseudo-random number generator
:param seed: (*int*) optional
Random seed used to initialize the pseudo-random number generator or
an instantized BitGenerator.
'''
def __init__(self, seed=None):
self._seed = seed
if seed is None:
self._mtrand = MTRandom()
else:
self._mtrand = MTRandom(seed)
def seed(self, seed=None):
"""
Set seed.
:param seed: The seed.
"""
self._mtrand.setSeed(seed)
def rand(self, *args):
"""
Random values in a given shape.
Create an array of the given shape and propagate it with random samples from a uniform
distribution over [0, 1).
:param d0, d1, ..., dn: (*int*) optional. The dimensions of the returned array, should all
be positive. If no argument is given a single Python float is returned.
:returns: Random values array.
"""
if len(args) == 0:
return self._mtrand.rand()
elif len(args) == 1:
return NDArray(self._mtrand.rand(args[0]))
else:
return NDArray(self._mtrand.rand(args))
def shuffle(self, x, axis=0):
'''
Modify a sequence in-place by shuffling its contents.
This function only shuffles the array along the first axis of a
multi-dimensional array. The order of sub-arrays is changed but
their contents remains the same.
:param x: (*array*) Input array
:param axis: (*int*) The axis which x is shuffled along. Default is 0. It is only supported
on ndarray objects.
:return: None
'''
self._mtrand.shuffle(x._array, axis)
def permutation(self, x, axis=0):
'''
MRandomly permute a sequence, or return a permuted range.
If x is a multi-dimensional array, it is only shuffled along its first index.
:param x: (*array*) Input array
:param axis: (*int*) The axis which x is shuffled along. Default is 0. It is only supported
on ndarray objects.
:return: Permutation array
'''
if isinstance(x, int):
arr = np.arange(x)
else:
x = np.asanyarray(x)
arr = x.copy()
self._mtrand.shuffle(arr._array, axis)
return arr
def __init__(self, seed=None):
self._seed = seed
if seed is None:
self._mtrand = MTRandom()
else:
self._mtrand = MTRandom(seed)