numpy.matlib.randn
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numpy.matlib.randn(*args)
[source] -
Return a random matrix with data from the “standard normal” distribution.
randn
generates a matrix filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1.Parameters: *args : Arguments
Shape of the output. If given as N integers, each integer specifies the size of one dimension. If given as a tuple, this tuple gives the complete shape.
Returns: Z : matrix of floats
A matrix of floating-point samples drawn from the standard normal distribution.
See also
rand
,random.randn
Notes
For random samples from
, use:
sigma * np.matlib.randn(...) + mu
Examples
>>> import numpy.matlib >>> np.matlib.randn(1) matrix([[-0.09542833]]) #random >>> np.matlib.randn(1, 2, 3) matrix([[ 0.16198284, 0.0194571 , 0.18312985], [-0.7509172 , 1.61055 , 0.45298599]]) #random
Two-by-four matrix of samples from
:
>>> 2.5 * np.matlib.randn((2, 4)) + 3 matrix([[ 4.74085004, 8.89381862, 4.09042411, 4.83721922], [ 7.52373709, 5.07933944, -2.64043543, 0.45610557]]) #random
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.matlib.randn.html