numpy.random.poisson
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numpy.random.poisson(lam=1.0, size=None)
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Draw samples from a Poisson distribution.
The Poisson distribution is the limit of the binomial distribution for large N.
Parameters: -
lam : float or array_like of floats
-
Expectation of interval, should be >= 0. A sequence of expectation intervals must be broadcastable over the requested size.
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size : int or tuple of ints, optional
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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: -
out : ndarray or scalar
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Drawn samples from the parameterized Poisson distribution.
Notes
The Poisson distribution
For events with an expected separation
the Poisson distribution
describes the probability of
events occurring within the observed interval
.
Because the output is limited to the range of the C long 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. http://mathworld.wolfram.com/PoissonDistribution.html [2] Wikipedia, “Poisson distribution”, http://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))
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Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.15.4/reference/generated/numpy.random.poisson.html