numpy.matlib.randn(標准正態分布)

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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)產生相同的效果，不知道為什么要加1，另外不能產生維度更高的，比如np.matlib.randn( 2, 3，4)系統會報錯 matrix([[ 0.16198284, 0.0194571 , 0.18312985],  [-0.7509172 , 1.61055 , 0.45298599]]) #random 

Two-by-four matrix of samples from : #這點非常重要，知道如何產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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