pysteps.postprocessing¶
Methods for post-processing of forecasts.
pysteps.postprocessing.ensemblestats¶
Methods for the computation of ensemble statistics.
mean (X[, ignore_nan, X_thr]) |
Compute the mean value from a forecast ensemble field. |
excprob (X, X_thr[, ignore_nan]) |
For a given forecast ensemble field, compute exceedance probabilities for the given intensity thresholds. |
pysteps.postprocessing.probmatching¶
Methods for matching the probability distribution of two data sets.
compute_empirical_cdf (bin_edges, hist) |
Compute an empirical cumulative distribution function from the given histogram. |
nonparam_match_empirical_cdf (R, R_trg) |
Matches the empirical CDF of the initial array with the empirical CDF of a target array. |
pmm_init (bin_edges_1, cdf_1, bin_edges_2, cdf_2) |
Initialize a probability matching method (PMM) object from binned cumulative distribution functions (CDF). |
pmm_compute (pmm, x) |
For a given PMM object and x-coordinate, compute the probability matched value (i.e. |
shift_scale (R, f, rain_fraction_trg, …) |
Find shift and scale that is needed to return the required second_moment and rain area. |