pysteps.postprocessing.probmatching.nonparam_match_empirical_cdf

pysteps.postprocessing.probmatching.nonparam_match_empirical_cdf#

pysteps.postprocessing.probmatching.nonparam_match_empirical_cdf(initial_array, target_array, ignore_indices=None)#

Matches the empirical CDF of the initial array with the empirical CDF of a target array. Initial ranks are conserved, but empirical distribution matches the target one. Zero-pixels (i.e. pixels having the minimum value) in the initial array are conserved.

Parameters:
  • initial_array (array_like) – The initial array whose CDF is to be matched with the target.

  • target_array (array_like) – The target array

  • ignore_indices (array_like, optional) – Indices of pixels in the initial_array which are to be ignored (not rescaled) or an array of booleans with True at the pixel locations to be ignored in initial_array and False elsewhere.

Returns:

output_array – The matched array of the same shape as the initial array.

Return type:

ndarray