def test_read_with_cent(self):
""" Test read_footprints while passing in a Centroids object """
storms = StormEurope()
storms.read_footprints(TEST_NCS, centroids=TEST_CENTROIDS)
self.assertEqual(storms.intensity.shape, (2, 9944))
self.assertEqual(
np.count_nonzero(~np.isnan(storms.centroids.region_id)), 6401)
def test_set_ssi(self):
""" Test set_ssi with both dawkins and wisc_gust methodology. """
storms = StormEurope()
storms.read_footprints(TEST_NCS)
storms.set_ssi(method='dawkins')
ssi_dawg = np.asarray([1.51114627e+09, 6.44053524e+08])
self.assertTrue(np.allclose(storms.ssi, ssi_dawg))
storms.set_ssi(method='wisc_gust')
ssi_gusty = np.asarray([1.48558417e+09, 6.13437760e+08])
self.assertTrue(np.allclose(storms.ssi, ssi_gusty))
storms.set_ssi(threshold=20, on_land=False)
ssi_special = np.asarray([3.09951236e+09, 1.29563312e+09])
self.assertTrue(np.allclose(storms.ssi, ssi_special))
def test_centroids_from_nc(self):
""" Test if centroids can be constructed correctly """
cent = StormEurope._centroids_from_nc(TEST_NCS[0])
self.assertTrue(isinstance(cent, Centroids))
self.assertTrue(isinstance(cent.coord, np.ndarray))
self.assertEqual(cent.size, 9944)
self.assertEqual(cent.coord.shape[0], cent.id.shape[0])
def test_generate_prob_storms(self):
""" Test the probabilistic storm generator; calls _hist2prob as well as
Centroids.set_region_id() """
storms = StormEurope()
storms.read_footprints(TEST_NCS)
storms_prob = storms.generate_prob_storms()
self.assertEqual(
np.count_nonzero(storms.centroids.region_id), 6190
# here, we don't rasterise; we check if the centroids lie in a
# polygon. that is to say, it's not the majority of a raster pixel,
# but the centroid's location that is decisive
)
self.assertEqual(storms_prob.size, 60)
self.assertEqual(np.count_nonzero(storms_prob.orig), 2)
self.assertEqual(storms_prob.centroids.size, 3054)
self.assertIsInstance(storms_prob.intensity, sparse.csr.csr_matrix)
def test_read_with_ref(self):
""" Test read_footprints while passing in a reference raster. """
storms = StormEurope()
storms.read_footprints(TEST_NCS, ref_raster=TEST_NCS[1])
self.assertEqual(storms.tag.haz_type, 'WS')
self.assertEqual(storms.units, 'm/s')
self.assertEqual(storms.event_id.size, 2)
self.assertEqual(storms.date.size, 2)
self.assertEqual(dt.datetime.fromordinal(storms.date[0]).year, 1999)
self.assertEqual(dt.datetime.fromordinal(storms.date[0]).month, 12)
self.assertEqual(dt.datetime.fromordinal(storms.date[0]).day, 26)
self.assertEqual(storms.event_id[0], 1)
self.assertEqual(storms.event_name[0], 'Lothar')
self.assertTrue(isinstance(storms.intensity, sparse.csr.csr_matrix))
self.assertTrue(isinstance(storms.fraction, sparse.csr.csr_matrix))
self.assertEqual(storms.intensity.shape, (2, 9944))
self.assertEqual(storms.fraction.shape, (2, 9944))
def test_read_footprints(self):
""" Test read_footprints function, using two small test files"""
storms = StormEurope()
storms.read_footprints(TEST_NCS, description='test_description')
self.assertEqual(storms.tag.haz_type, 'WS')
self.assertEqual(storms.units, 'm/s')
self.assertEqual(storms.event_id.size, 2)
self.assertEqual(storms.date.size, 2)
self.assertEqual(dt.datetime.fromordinal(storms.date[0]).year, 1999)
self.assertEqual(dt.datetime.fromordinal(storms.date[0]).month, 12)
self.assertEqual(dt.datetime.fromordinal(storms.date[0]).day, 26)
self.assertEqual(storms.event_id[0], 1)
self.assertEqual(storms.event_name[0], 'Lothar')
self.assertIsInstance(storms.intensity, sparse.csr.csr_matrix)
self.assertIsInstance(storms.fraction, sparse.csr.csr_matrix)
self.assertEqual(storms.intensity.shape, (2, 9944))
self.assertEqual(storms.fraction.shape, (2, 9944))
from climada.hazard import StormEurope
# All these variables need to be defined correctly for the code to work.
# The strings in these variables should point to existing folders on your computer.
project_folder = 'C:\\Users\\ThomasRoosli\\Documents\\PhD\\WISC_phd\\paper GVZ\\jupyter'
file_identifier = '_v01' # this string is added to all files written by this code
wisc_hist_filename = os.path.join(project_folder,
'WISC_hist' + file_identifier + '.hdf5')
wisc_prob_filename = os.path.join(project_folder,
'WISC_prob_CH' + file_identifier + '.hdf5')
### tryout GEV with 5 year maxima
wisc_hist = StormEurope()
wisc_hist.read_hdf5(wisc_hist_filename)
#get 5 year maxima
block_size_years = 5
quinquenniums = np.arange(0, 80, block_size_years) + 1940
ssi_5y_maxima = np.zeros_like(quinquenniums[:-1], dtype=float)
for ind_i, start_year_i in enumerate(quinquenniums[:-1]):
start_i = datetime.datetime(start_year_i, 1, 1).toordinal()
end_i = datetime.datetime(quinquenniums[ind_i + 1], 1, 1).toordinal()
selection_i = (wisc_hist.date >= start_i) & (wisc_hist.date < end_i)
ssi_5y_maxima[ind_i] = wisc_hist.ssi[selection_i].max()
#params_first = using R script
params_final_gev = scipy.stats.genextreme.fit(ssi_5y_maxima,
-0.1154771,
loc=21360556255,