numpy.matlib.randn(标准正态分布)

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numpy.matlib.randn

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) #和np.matlib.randn( 2, 3)产生相同的效果，不知道为什么要加1，另外不能产生维度更高的，比如np.matlib.randn( 2, 3，4)系统会报错
matrix([[ 0.16198284,  0.0194571 ,  0.18312985],
        [-0.7509172 ,  1.61055   ,  0.45298599]])       #random

Two-by-four matrix of samples from : #这点非常重要，知道如何产生其它方差和均值的分布; 2.5*2.5=6.25

>>>

>>> 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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