scipy.special.pdtr#
- scipy.special.pdtr(k, m, out=None) = <ufunc 'pdtr'>#
- Poisson cumulative distribution function. - Defined as the probability that a Poisson-distributed random variable with event rate \(m\) is less than or equal to \(k\). More concretely, this works out to be [1] \[\exp(-m) \sum_{j = 0}^{\lfloor{k}\rfloor} \frac{m^j}{j!}.\]- Parameters:
- karray_like
- Number of occurrences (nonnegative, real) 
- marray_like
- Shape parameter (nonnegative, real) 
- outndarray, optional
- Optional output array for the function results 
 
- Returns:
- scalar or ndarray
- Values of the Poisson cumulative distribution function 
 
 - See also - References - Examples - >>> import numpy as np >>> import scipy.special as sc - It is a cumulative distribution function, so it converges to 1 monotonically as k goes to infinity. - >>> sc.pdtr([1, 10, 100, np.inf], 1) array([0.73575888, 0.99999999, 1. , 1. ]) - It is discontinuous at integers and constant between integers. - >>> sc.pdtr([1, 1.5, 1.9, 2], 1) array([0.73575888, 0.73575888, 0.73575888, 0.9196986 ])