numpy.random.exponential(scale=1.0, size=None)

Exponential distribution.

Its probability density function is

f(x; \frac{1}{\beta}) = \frac{1}{\beta} \exp(-\frac{x}{\beta}),

for x > 0 and 0 elsewhere. \beta is the scale parameter, which is the inverse of the rate parameter \lambda = 1/\beta. The rate parameter is an alternative, widely used parameterization of the exponential distribution [R78].

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 [R76], or the time between page requests to Wikipedia [R77].


scale : float

The scale parameter, \beta = 1/\lambda.

size : tuple of ints

Number of samples to draw. The output is shaped according to size.


[R76](1, 2) Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57.
[R77](1, 2) “Poisson Process”, Wikipedia,
[R78](1, 2) “Exponential Distribution, Wikipedia,

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