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)
, thenm * n * k
samples are drawn. If size isNone
(default), a single value is returned.
- Returns:
out – Drawn samples from the parameterized normal distribution.
- Return type:
ndarray or scalar
See also
References
- Availability:
Multiple GPUs, Multiple CPUs