def test_catalog_binning_and_filtering_acceptance(self):
# create space-magnitude region
region = regions.create_space_magnitude_region(
regions.california_relm_region(),
regions.magnitude_bins(4.5, 10.05, 0.1)
)
# read catalog
comcat = csep.load_catalog(comcat_path(), region=region).filter(f"magnitude >= 4.5")
# create data set from data set
d = forecasts.MarkedGriddedDataSet(
data=comcat.spatial_magnitude_counts(),
region=comcat.region,
magnitudes=comcat.region.magnitudes
)
for idm, m_min in enumerate(d.magnitudes):
# catalog filtered cumulative
print(m_min)
c = comcat.filter([f'magnitude >= {m_min}'], in_place=False)
# catalog filtered incrementally
c_int = comcat.filter([f'magnitude >= {m_min}', f'magnitude < {m_min + 0.1}'], in_place=False)
# sum from overall data set
gs = d.data[:, idm:].sum()
# incremental counts
gs_int = d.data[:, idm].sum()
# event count from filtered catalog and events in binned data should be the same
numpy.testing.assert_equal(gs, c.event_count)
numpy.testing.assert_equal(gs_int, c_int.event_count)
def create_space_magnitude_region(name, min_mw, max_mw, dmw):
# if we include this in the package we can expand
mapper = {'california_relm_region': regions.california_relm_region}
region = regions.create_space_magnitude_region(
mapper[name](), regions.magnitude_bins(min_mw, max_mw, dmw))
return region
#################################################################################################################################### # Define spatial and magnitude regions # ------------------------------------ # # Before we can compute the bin-wise rates we need to define a spatial region and a set of magnitude bin edges. The magnitude # bin edges # are the lower bound (inclusive) except for the last bin, which is treated as extending to infinity. We can # bind these # to the forecast object. This can also be done by passing them as keyword arguments # into :func:`csep.load_catalog_forecast`. # Magnitude bins properties min_mw = 4.95 max_mw = 8.95 dmw = 0.1 # Create space and magnitude regions magnitudes = regions.magnitude_bins(min_mw, max_mw, dmw) region = regions.california_relm_region() # Bind region information to the forecast (this will be used for binning of the catalogs) forecast.region = regions.create_space_magnitude_region(region, magnitudes) #################################################################################################################################### # Compute spatial event counts # ---------------------------- # # The :class:`csep.core.forecasts.CatalogForecast` provides a method to compute the expected number of events in spatial cells. This # requires a region with magnitude information. _ = forecast.get_expected_rates(verbose=True) ####################################################################################################################################