exponential(self, scale=1.0, size=None, chunks='auto', **kwargs)
This docstring was copied from numpy.random.mtrand.RandomState.exponential.
Some inconsistencies with the Dask version may exist.
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 .
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 , or the time between page requests to Wikipedia .
New code should use the exponential
method of a default_rng()
instance instead; please see the :None:ref:`random-quick-start`.
The scale parameter, $\beta = 1/\lambda$ . Must be non-negative.
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.
Drawn samples from the parameterized exponential distribution.
Draw samples from an exponential distribution.
Generator.exponential
which should be used for new code.
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