numpy.random.triangular(left, mode, right, size=None)
Draw samples from the triangular distribution over the interval [left, right]
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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 : float or array_like of floats Lower limit. mode : float or array_like of floats The value where the peak of the distribution occurs. The value should fulfill the condition right : float or array_like of floats Upper limit, should be larger than size : int or tuple of ints, optional Output shape. If the given shape is, e.g., |
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Returns: |
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.
[R539539] | Wikipedia, “Triangular distribution” http://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.triangular(-3, 0, 8, 100000), bins=200, ... normed=True) >>> plt.show()
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.random.triangular.html