method
RandomState.
standard_normal
Draw samples from a standard Normal distribution (mean=0, stdev=1).
Note
New code should use the standard_normal method of a default_rng() instance instead; see random-quick-start.
default_rng()
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.
(m, n, k)
m * n * k
A floating-point array of shape size of drawn samples, or a single sample if size was not specified.
size
See also
normal
Equivalent function with additional loc and scale arguments for setting the mean and standard deviation.
loc
scale
Generator.standard_normal
which should be used for new code.
Notes
For random samples from
System Message: WARNING/2 (N(\mu, \sigma^2))
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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
System Message: WARNING/2 (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