gwin.entropy module

The module contains functions for calculating the Kullback-Leibler divergence.

gwin.entropy.kl(samples1, samples2, pdf1=False, pdf2=False, bins=30, hist_min=None, hist_max=None)[source]

Computes the Kullback-Leibler divergence for a single parameter from two distributions.

Parameters:
  • samples1 (numpy.array) – Samples or probability density function (must also set pdf1=True).
  • samples2 (numpy.array) – Samples or probability density function (must also set pdf2=True).
  • pdf1 (bool) – Set to True if samples1 is a probability density funtion already.
  • pdf2 (bool) – Set to True if samples2 is a probability density funtion already.
  • bins (int) – Number of bins to use when calculating probability density function from a set of samples of the distribution.
  • hist_min (numpy.float64) – Minimum of the distributions’ values to use.
  • hist_max (numpy.float64) – Maximum of the distributions’ values to use.
Returns:

The Kullback-Leibler divergence value.
Return type:

numpy.float64