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# 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

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