numpy.random.standard_normal()

numpy.random.standard_normal(size=None)

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

Parameters:

Parameters:	size : int 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:	out : float or ndarray Drawn samples.

size : int 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:

out : float or ndarray

Drawn samples.

Examples

>>> 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)

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.random.standard_normal.html

doc_NumPy

2025-01-10 15:47:30

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