bundles / numpy 2.4.3 / numpy / random / RandomState / geometric
cython_function_or_method
numpy.random:RandomState.geometric
Signature
def geometric ( p , size = None ) Summary
Draw samples from the geometric distribution.
Extended Summary
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 floatsThe probability of success of an individual trial.
size: int or tuple of ints, optionalOutput 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
out: ndarray or scalarDrawn 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.geometric(p=0.35, size=10000)
✓(z == 1).sum() / 10000.
✗See also
- random.Generator.geometric
which should be used for new code.
Aliases
-
numpy.random.geometric -
numpy.random.RandomState.geometric