method
Generator.
poisson
Draw samples from a Poisson distribution.
The Poisson distribution is the limit of the binomial distribution for large N.
Expectation of interval, must be >= 0. A sequence of expectation intervals must be broadcastable over the requested size.
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 lam is a scalar. Otherwise, np.array(lam).size samples are drawn.
(m, n, k)
m * n * k
None
lam
np.array(lam).size
Drawn samples from the parameterized Poisson distribution.
Notes
The Poisson distribution
System Message: WARNING/2 (f(k; \lambda)=\frac{\lambda^k e^{-\lambda}}{k!} )
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For events with an expected separation
System Message: WARNING/2 (\lambda)
System Message: WARNING/2 (f(k; \lambda))
System Message: WARNING/2 (k)
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
Weisstein, Eric W. “Poisson Distribution.” From MathWorld–A Wolfram Web Resource. http://mathworld.wolfram.com/PoissonDistribution.html
Wikipedia, “Poisson distribution”, https://en.wikipedia.org/wiki/Poisson_distribution
Examples
Draw samples from the distribution:
>>> import numpy as np >>> rng = np.random.default_rng() >>> s = rng.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 = rng.poisson(lam=(100., 500.), size=(100, 2))
