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