numpy.random.Generator.geometric#
method
- random.Generator.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
\[f(k) = (1 - p)^{k - 1} p\]where p is the probability of success of an individual trial.
- Parameters
- pfloat or array_like of floats
The probability of success of an individual trial.
- sizeint or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k), thenm * n * ksamples are drawn. If size isNone(default), a single value is returned ifpis a scalar. Otherwise,np.array(p).sizesamples are drawn.
- Returns
- outndarray or scalar
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