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numpy.random.triangular(left, mode, right, size=None)
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Draw samples from the triangular distribution.
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.
Parameters: left : scalar
Lower limit.
mode : scalar
The value where the peak of the distribution occurs. The value should fulfill the condition
left <= mode <= right
.right : scalar
Upper limit, should be larger than
left
.size : int or tuple of ints, optional
Output shape. If the given shape is, e.g.,
(m, n, k)
, thenm * n * k
samples are drawn. Default is None, in which case a single value is returned.Returns: samples : ndarray or scalar
The returned samples all lie in the interval [left, right].
Notes
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.
References
[R269] Wikipedia, ?Triangular distribution? http://en.wikipedia.org/wiki/Triangular_distribution Examples
Draw values from the distribution and plot the histogram:
>>> import matplotlib.pyplot as plt >>> h = plt.hist(np.random.triangular(-3, 0, 8, 100000), bins=200, ... normed=True) >>> plt.show()
(Source code, png, pdf)
numpy.random.triangular()
2017-01-10 18:18:19
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