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# numpy.random.triangular

`numpy.random.``triangular`(left, mode, right, size=None)

  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. 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

  ..[1] 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)

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