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.
New code should use the
geometricmethod of a
default_rng()instance instead; see random-quick-start.
- 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), then
m * n * ksamples are drawn. If size is
None(default), a single value is returned if
pis a scalar. Otherwise,
np.array(p).sizesamples are drawn.
- outndarray or scalar
Drawn samples from the parameterized geometric distribution.
which should be used for new code.
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