numpy.random.RandomState.randn¶
method

RandomState.
randn
(d0, d1, ..., dn)¶ Return a sample (or samples) from the “standard normal” distribution.
Note
This is a convenience function for users porting code from Matlab, and wraps
standard_normal
. That function takes a tuple to specify the size of the output, which is consistent with other NumPy functions likenumpy.zeros
andnumpy.ones
.If positive int_like arguments are provided,
randn
generates an array of shape(d0, d1, ..., dn)
, filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1. A single float randomly sampled from the distribution is returned if no argument is provided. Parameters
 d0, d1, …, dnint, optional
The dimensions of the returned array, must be nonnegative. If no argument is given a single Python float is returned.
 Returns
 Zndarray or float
A
(d0, d1, ..., dn)
shaped array of floatingpoint samples from the standard normal distribution, or a single such float if no parameters were supplied.
See also
standard_normal
Similar, but takes a tuple as its argument.
normal
Also accepts mu and sigma arguments.
Notes
For random samples from , use:
sigma * np.random.randn(...) + mu
Examples
>>> np.random.randn() 2.1923875335537315 # random
Twobyfour array of samples from N(3, 6.25):
>>> 3 + 2.5 * np.random.randn(2, 4) array([[4.49401501, 4.00950034, 1.81814867, 7.29718677], # random [ 0.39924804, 4.68456316, 4.99394529, 4.84057254]]) # random