method
Generator.
geometric
Draw samples from the geometric distribution.
Bernoulli trials are experiments with one of two outcomes: success or failure (an example of such an experiment is flipping a coin). The geometric distribution models the number of trials that must be run in order to achieve success. It is therefore supported on the positive integers, k = 1, 2, ....
k = 1, 2, ...
The probability mass function of the geometric distribution is
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where p is the probability of success of an individual trial.
The probability of success of an individual trial.
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 p is a scalar. Otherwise, np.array(p).size samples are drawn.
(m, n, k)
m * n * k
None
p
np.array(p).size
Drawn samples from the parameterized geometric distribution.
Examples
Draw ten thousand values from the geometric distribution, with the probability of an individual success equal to 0.35:
>>> z = np.random.default_rng().geometric(p=0.35, size=10000)
How many trials succeeded after a single run?
>>> (z == 1).sum() / 10000. 0.34889999999999999 #random
