def calc_tc(expo_dict, tracks, data_dir):
""" Compute tropical cyclone events from tracks at every island group,
if not contained in data_dir. """
try:
abs_path = os.path.join(data_dir, 'tc_isl.p')
with open(abs_path, 'rb') as f:
tc_dict = pickle.load(f)
print('Loaded tc_isl:', len(tc_dict))
except FileNotFoundError:
all_isl = BlackMarble()
for ent_iso, ent_val in expo_dict.items():
all_isl.append(ent_val)
centr = Centroids()
centr.coord = all_isl.coord
centr.id = np.arange(centr.lat.size) + 1
centr.region_id = all_isl.region_id
tc = TropCyclone()
tc.set_from_tracks(tracks, centr)
tc_dict = dict()
for ent_iso, ent_val in expo_dict.items():
reg_id = np.unique(ent_val.region_id)[0]
tc_dict[ent_iso] = tc.select(reg_id=reg_id)
save(os.path.join(data_dir, 'tc_isl.p'), tc_dict)
return tc_dict
def centroids(self, latlon=None, res_as=360):
"""Return centroids in this region
Parameters
----------
latlon : pair (lat, lon), optional
Latitude and longitude of centroids.
If not given, values are taken from CLIMADA's base grid (see `res_as`).
res_as : int, optional
One of 150 or 360. When `latlon` is not given, choose coordinates from centroids
according to CLIMADA's base grid of given resolution in arc-seconds. Default: 360.
Returns
-------
centroids : climada.hazard.Centroids object
"""
if latlon is None:
centroids = Centroids.from_base_grid(res_as=res_as)
centroids.set_meta_to_lat_lon()
lat, lon = centroids.lat, centroids.lon
else:
lat, lon = latlon
centroids = Centroids()
centroids.set_lat_lon(lat, lon)
msk = shapely.vectorized.contains(self.shape, lon, lat)
centroids = centroids.select(sel_cen=msk)
centroids.id = np.arange(centroids.lon.shape[0])
return centroids
def irma_tc(exp, data_irma):
centr = Centroids()
centr.coord = exp.coord
centr.id = np.arange(centr.lat.size)
tc_irma = TropCyclone()
data_irma.equal_timestep(0.1)
tc_irma.set_from_tracks(data_irma, centr)
return tc_irma
def irma_tc(exp, data_irma):
centr = Centroids()
centr.coord = np.zeros((exp.latitude.size, 2))
centr.coord[:, 0] = exp.latitude
centr.coord[:, 1] = exp.longitude
centr.id = np.arange(centr.lat.size)
tc_irma = TropCyclone()
data_irma.equal_timestep(0.1)
tc_irma.set_from_tracks(data_irma, centr)
return tc_irma