randomgen.mtrand.RandomState.standard_normal

RandomState.standard_normal(size=None)

Draw samples from a standard Normal distribution (mean=0, stdev=1).

Parameters

sizeint or tuple of ints, optional

Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.

Returns

outfloat or ndarray

A floating-point array of shape size of drawn samples, or a single sample if size was not specified.

See also

normal

Equivalent function with additional loc and scale arguments for setting the mean and standard deviation.

Notes

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

mu + sigma * np.random.standard_normal(size=...)
np.random.normal(mu, sigma, size=...)

Examples

>>> np.random.standard_normal()
2.1923875335537315 # random

>>> s = np.random.standard_normal(8000)
>>> s
array([ 0.6888893 ,  0.78096262, -0.89086505, ...,  0.49876311,  # random
       -0.38672696, -0.4685006 ])                                # random
>>> s.shape
(8000,)
>>> s = np.random.standard_normal(size=(3, 4, 2))
>>> s.shape
(3, 4, 2)

Two-by-four array of samples from \(N(3, 6.25)\):

>>> 3 + 2.5 * np.random.standard_normal(size=(2, 4))
array([[-4.49401501,  4.00950034, -1.81814867,  7.29718677],   # random
       [ 0.39924804,  4.68456316,  4.99394529,  4.84057254]])  # random