numpy.random.geometric(p, size=None)
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, ...
.
The probability mass function of the geometric distribution is
where p
is the probability of success of an individual trial.
Parameters: |
p : float or array_like of floats The probability of success of an individual trial. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., |
---|---|
Returns: |
out : ndarray or scalar Drawn samples from the parameterized geometric distribution. |
Draw ten thousand values from the geometric distribution, with the probability of an individual success equal to 0.35:
>>> z = np.random.geometric(p=0.35, size=10000)
How many trials succeeded after a single run?
>>> (z == 1).sum() / 10000. 0.34889999999999999 #random
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.random.geometric.html