cupynumeric.random.normal#

cupynumeric.random.normal(loc=0.0, scale=1.0, size=None)#

Draw random samples from a normal (Gaussian) distribution.

The probability density function of the normal distribution, first derived by De Moivre and 200 years later by both Gauss and Laplace independently [1], is often called the bell curve because of its characteristic shape.

The normal distribution occurs often in nature. For example, it describes the commonly occurring distribution of samples influenced by a large number of tiny, random disturbances, each with its own unique distribution [1].

Parameters:

loc (float) – Mean (“centre”) of the distribution.
scale (float) – Standard deviation (spread or “width”) of the distribution. Must be non-negative.
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. If size is None (default), a single value is returned.

Returns:

out – Drawn samples from the parameterized normal distribution.

Return type:

ndarray or scalar