triangular(left, mode, right, size=None)¶
Draw samples from the triangular distribution over the interval
The triangular distribution is a continuous probability distribution with lower limit left, peak at mode, and upper limit right. Unlike the other distributions, these parameters directly define the shape of the pdf.
- left : float or array_like of floats
- mode : float or array_like of floats
The value where the peak of the distribution occurs. The value must fulfill the condition
left <= mode <= right.
- right : float or array_like of floats
Upper limit, must be larger than left.
- size : int 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
rightare all scalars. Otherwise,
np.broadcast(left, mode, right).sizesamples are drawn.
- out : ndarray or scalar
Drawn samples from the parameterized triangular distribution.
The probability density function for the triangular distribution is
The triangular distribution is often used in ill-defined problems where the underlying distribution is not known, but some knowledge of the limits and mode exists. Often it is used in simulations.
 Wikipedia, “Triangular distribution” https://en.wikipedia.org/wiki/Triangular_distribution
Draw values from the distribution and plot the histogram:
>>> import matplotlib.pyplot as plt >>> h = plt.hist(np.random.default_rng().triangular(-3, 0, 8, 100000), bins=200, ... density=True) >>> plt.show()