dask.array.random.poisson
dask.array.random.poisson¶
- dask.array.random.poisson(*args, **kwargs)¶
Draw samples from a Poisson distribution.
This docstring was copied from numpy.random.mtrand.RandomState.poisson.
Some inconsistencies with the Dask version may exist.
The Poisson distribution is the limit of the binomial distribution for large N.
Note
New code should use the ~numpy.random.Generator.poisson method of a ~numpy.random.Generator instance instead; please see the Quick start.
- Parameters
- lamfloat or array_like of floats
Expected number of events occurring in a fixed-time interval, must be >= 0. A sequence must be broadcastable over the requested size.
- sizeint or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k)
, thenm * n * k
samples are drawn. If size isNone
(default), a single value is returned iflam
is a scalar. Otherwise,np.array(lam).size
samples are drawn.
- Returns
- outndarray or scalar
Drawn samples from the parameterized Poisson distribution.
See also
random.Generator.poisson
which should be used for new code.
Notes
The Poisson distribution
\[f(k; \lambda)=\frac{\lambda^k e^{-\lambda}}{k!}\]For events with an expected separation \(\lambda\) the Poisson distribution \(f(k; \lambda)\) describes the probability of \(k\) events occurring within the observed interval \(\lambda\).
Because the output is limited to the range of the C int64 type, a ValueError is raised when lam is within 10 sigma of the maximum representable value.
References
- 1
Weisstein, Eric W. “Poisson Distribution.” From MathWorld–A Wolfram Web Resource. https://mathworld.wolfram.com/PoissonDistribution.html
- 2
Wikipedia, “Poisson distribution”, https://en.wikipedia.org/wiki/Poisson_distribution
Examples
Draw samples from the distribution:
>>> import numpy as np >>> s = np.random.poisson(5, 10000)
Display histogram of the sample:
>>> import matplotlib.pyplot as plt >>> count, bins, ignored = plt.hist(s, 14, density=True) >>> plt.show()
Draw each 100 values for lambda 100 and 500:
>>> s = np.random.poisson(lam=(100., 500.), size=(100, 2))