Draw samples from a standard Normal distribution (mean=0, stdev=1).
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.
A floating-point array of shape size of drawn samples, or a single sample if size was not specified.
Notes
For random samples from the normal distribution with mean mu and standard deviation sigma, 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 the normal distribution with mean 3 and standard deviation 2.5:
>>> 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
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