def load_inputs(cfg: dict) -> Tuple[GeoDataFrame]:
"""
Loads all of the inputs specified by the `cfg` and returns a tuple of
:class:`GeoDataFrame` objects, the earthquake catalog and the bins.
:param cfg:
Configuration for the evaluations, such as that parsed from the YAML
config file.
"""
rupture_gdf = load_ruptures_from_ssm(cfg)
bin_gdf = make_bin_gdf_from_rupture_gdf(
rupture_gdf,
h3_res=cfg["input"]["bins"]["h3_res"],
min_mag=cfg["input"]["bins"]["mfd_bin_min"],
max_mag=cfg["input"]["bins"]["mfd_bin_max"],
bin_width=cfg["input"]["bins"]["mfd_bin_width"],
)
logger.info("bin_gdf shape: {}".format(bin_gdf.shape))
logger.info("rupture_gdf shape: {}".format(rupture_gdf.shape))
logger.debug("rupture_gdf memory: {} GB".format(
sum(rupture_gdf.memory_usage(index=True, deep=True)) * 1e-9))
logger.info("adding ruptures to bins")
add_ruptures_to_bins(rupture_gdf, bin_gdf)
if cfg["input"]["subset"]["file"] is not None:
logger.info(" Subsetting bin_gdf")
bin_gdf = subset_source(
bin_gdf,
subset_file=cfg["input"]["subset"]["file"],
buffer=cfg["input"]["subset"]["buffer"],
)
del rupture_gdf
logger.debug("bin_gdf memory: {} GB".format(
sum(bin_gdf.memory_usage(index=True, deep=True)) * 1e-9))
eq_gdf = load_obs_eq_catalog(cfg)
logger.info("adding earthquakes to bins")
add_earthquakes_to_bins(eq_gdf,
bin_gdf,
h3_res=cfg["input"]["bins"]["h3_res"])
if "prospective_catalog" in cfg["input"].keys():
logger.info("adding prospective earthquakes to bins")
pro_gdf = load_pro_eq_catalog(cfg)
add_earthquakes_to_bins(
pro_gdf,
bin_gdf,
h3_res=cfg["input"]["bins"]["h3_res"],
category="prospective",
)
return bin_gdf, eq_gdf, pro_gdf
else:
return bin_gdf, eq_gdf
def test_add_earthquakes_to_bins(self):
self.eq_df = make_earthquake_gdf_from_csv(self.test_dir +
"data/phl_eqs.csv")
add_earthquakes_to_bins(self.eq_df, self.bin_gdf)
sbin = self.bin_gdf.loc["836860fffffffff"].SpacemagBin
self.assertEqual(len(sbin.mag_bins[6.0].observed_earthquakes), 2)