numpy.random.exponential

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

Exponential distribution.

Its probability density function is

for x > 0 and 0 elsewhere. is known as the rate parameter.

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 [61], or the time between page requests to Wikipedia [62].

Parameters:

scale : float

The rate parameter, .

size : tuple of ints

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

References

[61]	Peyton Z. Peebles Jr., “Probability, Random Variables and Random Signal Principles”, 4th ed, 2001, p. 57.

[62]	“Poisson Process”, Wikipedia, http://en.wikipedia.org/wiki/Poisson_process