def randn(*args):
if isinstance(args[<NUM_LIT:0>], tuple):<EOL><INDENT>args = args[<NUM_LIT:0>]<EOL><DEDENT>return asmatrix(np.random.randn(*args))<EOL>
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 :math:`N(\\mu, \\sigma^2)`, 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 :math:`N(3, 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