#### Previous topic

numpy.random.RandomState.tomaxint

#### Next topic

numpy.random.RandomState.uniform

# numpy.random.RandomState.triangular

`RandomState.``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. If the given shape is, e.g., `(m, n, k)`, then `m * 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

  [R198] | 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)