Though this article tackles Poisson distribution, a type of discrete probability distribution, it is rather focused on practical questions how to use matplotlib to construct graphs of that distribution.
Numpy offers three parameters that effect graphical appearance:
| parameter |
meaning |
usage |
| mu |
shape parameter |
essential, to construct a probability distribution |
| loc |
origin |
optional, the origin of the probability distribution default = 0 |
| size |
vector length |
optional, size of the one dimensional array of random variables default=0 => no array but a single random variable is returned |
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The probability mass function can be written:
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The cumulative probability function can be described by the equation:
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The function of the Numpy parameters can be tested by the following sage cell.
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