floatcsep.extras.binomial_spatial_test

floatcsep.extras.binomial_spatial_test(gridded_forecast, observed_catalog, num_simulations=1000, seed=None, random_numbers=None, verbose=False)[source]

Performs the binary spatial test on the Forecast using the Observed Catalogs. Note: The forecast and the observations should be scaled to the same time period before calling this function. This increases transparency as no assumptions are being made about the length of the forecasts. This is particularly important for gridded forecasts that supply their forecasts as rates. :param gridded_forecast: csep.core.forecasts.GriddedForecast :param observed_catalog: csep.core.catalogs.Catalog :param num_simulations: number of simulations used to compute the quantile score :type num_simulations: int :param seed: used fore reproducibility, and testing :type seed: int :param random_numbers: random numbers used to override the random number generation. injection point for testing. :type random_numbers: numpy.ndarray

Returns:: csep.core.evaluations.EvaluationResult
Return type:: evaluation_result