- numpy.random.exponential(scale=1.0, size=None)¶
Draw samples from an exponential distribution.
Its probability density function is
for x > 0 and 0 elsewhere. is the scale parameter, which is the inverse of the rate parameter . The rate parameter is an alternative, widely used parameterization of the exponential distribution [R218].
The exponential distribution is a continuous analogue of the geometric distribution. It describes many common situations, such as the size of raindrops measured over many rainstorms [R216], or the time between page requests to Wikipedia [R217].
scale : float or array_like of floats
The scale parameter, .
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 if scale is a scalar. Otherwise, np.array(scale).size samples are drawn.
out : ndarray or scalar
Drawn samples from the parameterized exponential distribution.
[R216] (1, 2) Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57. [R217] (1, 2) Wikipedia, “Poisson process”, http://en.wikipedia.org/wiki/Poisson_process [R218] (1, 2) Wikipedia, “Exponential distribution”, http://en.wikipedia.org/wiki/Exponential_distribution