# numpy.matlib.randn#

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
*argsArguments

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
Zmatrix of floats

A matrix of floating-point samples drawn from the standard normal distribution.

Notes

For random samples from $$N(\mu, \sigma^2)$$, use:

sigma * np.matlib.randn(...) + mu

Examples

>>> np.random.seed(123)
>>> import numpy.matlib
>>> np.matlib.randn(1)
matrix([[-1.0856306]])
>>> np.matlib.randn(1, 2, 3)
matrix([[ 0.99734545,  0.2829785 , -1.50629471],
[-0.57860025,  1.65143654, -2.42667924]])


Two-by-four matrix of samples from $$N(3, 6.25)$$:

>>> 2.5 * np.matlib.randn((2, 4)) + 3
matrix([[1.92771843, 6.16484065, 0.83314899, 1.30278462],
[2.76322758, 6.72847407, 1.40274501, 1.8900451 ]])