September 2014
Intermediate to advanced
512 pages
12h 39m
English
Content preview from IPython Interactive Computing and Visualization CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Simulating a Poisson process
A Poisson process is a particular type of point process, a stochastic model that represents random occurrences of instantaneous events. Roughly speaking, the Poisson process is the least structured, or the most random, point process.
The Poisson process is a particular continuous-time Markov process.
Point processes, and notably Poisson processes, can model random instantaneous events such as the arrival of clients in a queue or on a server, telephone calls, radioactive disintegrations, action potentials of nerve cells, and many other phenomena.
In this recipe, we will show different methods to simulate a homogeneous stationary Poisson process.
How to do it...
- Let's import NumPy and matplotlib:
In [1]: import numpy as np ...
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