def test_append_all_pass(self):
"""Test _append_all function."""
haz_1 = Hazard('TC')
haz_1.tag.file_name = 'file1.mat'
haz_1.tag.description = 'Description 1'
haz_1.centroids = Centroids()
haz_1.centroids.set_lat_lon(np.array([1, 3, 5]), np.array([2, 4, 6]))
haz_1.event_id = np.array([1])
haz_1.event_name = ['ev1']
haz_1.date = np.array([1])
haz_1.orig = np.array([True])
haz_1.frequency = np.array([1.0])
haz_1.fraction = sparse.csr_matrix([[0.02, 0.03, 0.04]])
haz_1.intensity = sparse.csr_matrix([[0.2, 0.3, 0.4]])
haz_1.units = 'm/s'
haz_2 = Hazard('TC')
haz_2.tag.file_name = 'file2.mat'
haz_2.tag.description = 'Description 2'
haz_2.centroids = Centroids()
haz_2.centroids.set_lat_lon(np.array([1, 3, 5]), np.array([2, 4, 6]))
haz_2.event_id = np.array([1])
haz_2.event_name = ['ev2']
haz_2.date = np.array([2])
haz_2.orig = np.array([False])
haz_2.frequency = np.array([1.0])
haz_2.fraction = sparse.csr_matrix([[1.02, 1.03, 1.04]])
haz_2.intensity = sparse.csr_matrix([[1.2, 1.3, 1.4]])
haz_2.units = 'm/s'
haz = Hazard('TC')
haz._append_all([haz_1, haz_2])
hres_frac = sparse.csr_matrix([[0.02, 0.03, 0.04], \
[1.02, 1.03, 1.04]])
hres_inten = sparse.csr_matrix([[0.2, 0.3, 0.4], \
[1.2, 1.3, 1.4]])
self.assertTrue(sparse.isspmatrix_csr(haz.intensity))
self.assertTrue(
np.array_equal(haz.intensity.todense(), hres_inten.todense()))
self.assertTrue(sparse.isspmatrix_csr(haz.fraction))
self.assertTrue(
np.array_equal(haz.fraction.todense(), hres_frac.todense()))
self.assertEqual(haz.units, haz_2.units)
self.assertTrue(np.array_equal(haz.frequency, np.array([1.0, 1.0])))
self.assertTrue(np.array_equal(haz.orig, np.array([True, False])))
self.assertTrue(np.array_equal(haz.date, np.array([1, 2])))
self.assertTrue(np.array_equal(haz.event_id, np.array([1, 2])))
self.assertTrue(haz.event_name, ['ev1', 'ev2'])
self.assertTrue(
np.array_equal(haz.centroids.coord, haz_1.centroids.coord))
self.assertTrue(
np.array_equal(haz.centroids.coord, haz_2.centroids.coord))
self.assertTrue(haz.tag, 'file_1.mat + file_2.mat')
self.assertTrue(haz.tag, 'Description 1 + Description 2')
def test_same_centroids_extend(self):
"""Append hazard with same centroids, different events."""
haz1 = dummy_hazard()
haz2 = Hazard('TC')
haz2.tag.file_name = 'file2.mat'
haz2.tag.description = 'Description 2'
haz2.centroids = haz1.centroids
haz2.event_id = np.array([5, 6, 7, 8])
haz2.event_name = ['ev5', 'ev6', 'ev7', 'ev8']
haz2.frequency = np.array([0.9, 0.75, 0.75, 0.22])
haz2.fraction = sparse.csr_matrix([[0.2, 0.3, 0.4], \
[0.1, 0.1, 0.1], \
[0.3, 0.1, 0.9], \
[0.3, 0.2, 0.8]])
haz2.intensity = sparse.csr_matrix([[0.2, 3.3, 6.4], \
[1.1, 0.1, 1.01], \
[8.3, 4.1, 4.0], \
[9.3, 9.2, 1.7]])
haz2.units = 'm/s'
haz1.append(haz2)
haz1.check()
# expected values
haz1_orig = dummy_hazard()
exp_inten = np.zeros((8, 3))
exp_inten[0:4, 0:3] = haz1_orig.intensity.todense()
exp_inten[4:8, 0:3] = haz2.intensity.todense()
exp_frac = np.zeros((8, 3))
exp_frac[0:4, 0:3] = haz1_orig.fraction.todense()
exp_frac[4:8, 0:3] = haz2.fraction.todense()
self.assertEqual(haz1.event_id.size, 8)
self.assertTrue(sparse.isspmatrix_csr(haz1.intensity))
self.assertTrue(sparse.isspmatrix_csr(haz1.fraction))
for i_ev in range(haz1.event_id.size):
self.assertTrue(
any((haz1.intensity[i_ev].todense() == exp_inten).all(1)))
self.assertTrue(
any((haz1.fraction[i_ev].todense() == exp_frac).all(1)))
self.assertTrue(haz1.event_name[i_ev] in haz1_orig.event_name +
haz2.event_name)
self.assertTrue(
haz1.date[i_ev] in np.append(haz1_orig.date, haz2.date))
self.assertTrue(
haz1.orig[i_ev] in np.append(haz1_orig.orig, haz2.orig))
self.assertTrue(haz1.event_id[i_ev] in np.append(
haz1_orig.event_id, haz2.event_id))
self.assertTrue(haz1.frequency[i_ev] in np.append(
haz1_orig.frequency, haz2.frequency))
self.assertEqual(haz1.centroids.size, 3)
self.assertTrue(
np.array_equal(haz1.centroids.coord, haz2.centroids.coord))
self.assertEqual(haz1.tag.file_name, \
[haz1_orig.tag.file_name, haz2.tag.file_name])
self.assertEqual(haz1.tag.haz_type, haz1_orig.tag.haz_type)
self.assertEqual(haz1.tag.description, \
[haz1_orig.tag.description, haz2.tag.description])
def test_write_fraction_pass(self):
"""Test write_raster with fraction"""
haz_fl = Hazard('FL')
haz_fl.event_id = np.array([1])
haz_fl.date = np.array([1])
haz_fl.frequency = np.array([1])
haz_fl.orig = np.array([1])
haz_fl.event_name = ['1']
haz_fl.intensity = sparse.csr_matrix(np.array([0.5, 0.2, 0.1]))
haz_fl.fraction = sparse.csr_matrix(np.array([0.5, 0.2, 0.1]) / 2)
haz_fl.centroids.set_lat_lon(np.array([1, 2, 3]), np.array([1, 2, 3]))
haz_fl.check()
haz_fl.write_raster(os.path.join(DATA_DIR, 'test_write_hazard.tif'),
intensity=False)
haz_read = Hazard('FL')
haz_read.set_raster(
[os.path.join(DATA_DIR, 'test_write_hazard.tif')],
files_fraction=[os.path.join(DATA_DIR, 'test_write_hazard.tif')])
self.assertEqual(haz_read.intensity.shape, (1, 9))
self.assertEqual(haz_read.fraction.shape, (1, 9))
self.assertTrue(
np.allclose(np.unique(np.array(haz_read.fraction.toarray())),
np.array([0.0, 0.05, 0.1, 0.25])))
self.assertTrue(
np.allclose(np.unique(np.array(haz_read.intensity.toarray())),
np.array([0.0, 0.05, 0.1, 0.25])))
def test_degenerate_pass(self):
""" Test degenerate call. """
haz = Hazard('TC')
haz.read_mat(HAZ_TEST_MAT)
return_period = np.array([25, 50, 100, 250])
haz.intensity = sparse.csr.csr_matrix(np.zeros(haz.intensity.shape))
inten_stats = haz.local_exceedance_inten(return_period)
self.assertTrue(np.array_equal(inten_stats, np.zeros((4, 100))))
def test_same_events_append(self):
"""Append hazard with same events (and diff centroids).
Events are appended with all new centroids columns. """
haz1 = dummy_hazard()
haz2 = Hazard('TC')
haz2.tag.file_name = 'file2.mat'
haz2.tag.description = 'Description 2'
haz2.centroids = Centroids()
haz2.centroids.set_lat_lon(np.array([7, 9, 11]), np.array([8, 10, 12]))
haz2.event_id = haz1.event_id
haz2.event_name = haz1.event_name.copy()
haz2.frequency = haz1.frequency
haz2.date = haz1.date
haz2.fraction = sparse.csr_matrix([[0.22, 0.32, 0.44], \
[0.11, 0.11, 0.11], \
[0.32, 0.11, 0.99], \
[0.32, 0.22, 0.88]])
haz2.intensity = sparse.csr_matrix([[0.22, 3.33, 6.44], \
[1.11, 0.11, 1.11], \
[8.33, 4.11, 4.4], \
[9.33, 9.22, 1.77]])
haz2.units = 'm/s'
haz1.append(haz2)
# expected values
haz1_ori = dummy_hazard()
res_inten = sparse.lil_matrix(np.zeros((8, 6)))
res_inten[0:4, 0:3] = haz1_ori.intensity
res_inten[4:, 3:] = haz2.intensity
res_frac = sparse.lil_matrix(np.zeros((8, 6)))
res_frac[0:4, 0:3] = haz1_ori.fraction
res_frac[4:, 3:] = haz2.fraction
self.assertTrue(np.array_equal(res_inten.todense(),
haz1.intensity.todense()))
self.assertTrue(sparse.isspmatrix_csr(haz1.intensity))
self.assertTrue(np.array_equal(res_frac.todense(), \
haz1.fraction.todense()))
self.assertTrue(sparse.isspmatrix_csr(haz1.fraction))
self.assertEqual(haz1.event_name,
haz1_ori.event_name + haz2.event_name)
self.assertTrue(np.array_equal(haz1.date,
np.append(haz1_ori.date, haz2.date)))
self.assertTrue(np.array_equal(haz1.orig,
np.append(haz1_ori.orig, haz2.orig)))
self.assertTrue(np.array_equal(haz1.event_id, np.arange(1,9)))
self.assertTrue(np.array_equal(haz1.frequency,
np.append(haz1_ori.frequency, haz2.frequency)))
self.assertEqual(haz1_ori.units, haz1.units)
self.assertEqual(haz1.tag.file_name, \
[haz1_ori.tag.file_name, haz2.tag.file_name])
self.assertEqual(haz1.tag.haz_type, haz1_ori.tag.haz_type)
self.assertEqual(haz1.tag.description, \
[haz1_ori.tag.description, haz2.tag.description])
def _event_probabilistic(self, ev_id, i_ens):
""" Append a row in the intensity matrix for the probabilistic event.
The brightness value of the probabilistic event are randomly selected
in the intensity matrix corresponding to the historical event.
Fill in the hazard file for the probabilistic event.
Parameters:
ev_id: id of the selected historical event
i_ens (int): number of the generated probabilistic event
Returns:
new_haz (Hazard): new hazard corresponding to one probabilistic event
"""
LOGGER.debug('Brightness probabilistic event.')
# Probabilistic event
ev_proba = np.argwhere(self.centroids.burned >= 1)
ev_proba_uni = (ev_proba[:, 0]-1) * self.centroids.nb_centr_lon + ev_proba[:, 1]
# Append a row to the intensity matrix with the brightness values of the
# probabilistic event
# The brightness value is chosen randomly from the brightness values of
# the historical event.
new_haz = Hazard(HAZ_TYPE)
new_haz.intensity = sparse.lil_matrix(np.zeros(len(self.centroids.id)))
for _, ev_prob in enumerate(ev_proba_uni):
bright_proba = np.random.choice(self.intensity[ev_id -1].data)
new_haz.intensity[0, ev_prob] = bright_proba
new_haz.intensity = new_haz.intensity.tocsr()
# Hazard
new_haz.tag = TagHazard(HAZ_TYPE)
new_haz.units = 'K' # Kelvin units brightness
new_haz.centroids = self.centroids
new_haz.event_id = np.ones(1, int)
new_haz.frequency = np.ones(1, float)
new_haz.event_name = [str(ev_id) + '_gen' + str(i_ens)]
new_haz.date = np.array([self.date[int(ev_id-1)]])
new_haz.orig = np.zeros(1, bool)
# Following values are defined for each event and centroid
new_haz.fraction = new_haz.intensity.copy()
new_haz.fraction.data.fill(1.0)
return new_haz
def test_same_events_same(self):
"""Append hazard with same events and diff centroids. After removing
duplicate events, initial events are obtained with 0 intensity and
fraction in new appended centroids."""
haz1 = dummy_hazard()
haz2 = Hazard('TC')
haz2.tag.file_name = 'file2.mat',
haz2.tag.description = 'Description 2'
haz2.centroids = Centroids()
haz2.centroids.set_lat_lon(np.array([7, 9, 11]), np.array([8, 10, 12]))
haz2.event_id = haz1.event_id
haz2.event_name = haz1.event_name
haz2.frequency = haz1.frequency
haz2.date = haz1.date
haz2.fraction = sparse.csr_matrix([[0.22, 0.32, 0.44], \
[0.11, 0.11, 0.11], \
[0.32, 0.11, 0.99], \
[0.32, 0.22, 0.88]])
haz2.intensity = sparse.csr_matrix([[0.22, 3.33, 6.44], \
[1.11, 0.11, 1.11], \
[8.33, 4.11, 4.4], \
[9.33, 9.22, 1.77]])
haz2.units = 'm/s'
haz1.append(haz2)
haz1.remove_duplicates()
haz1.check()
# expected values
haz_res = dummy_hazard()
haz_res.intensity = sparse.hstack([haz_res.intensity, \
sparse.lil_matrix((haz_res.intensity.shape[0], 3))], format='lil').tocsr()
haz_res.fraction = sparse.hstack([haz_res.fraction, \
sparse.lil_matrix((haz_res.fraction.shape[0], 3))], format='lil').tocsr()
self.assertTrue(np.array_equal(haz_res.intensity.todense(), \
haz1.intensity.todense()))
self.assertTrue(sparse.isspmatrix_csr(haz1.intensity))
self.assertTrue(np.array_equal(haz_res.fraction.todense(), \
haz1.fraction.todense()))
self.assertTrue(sparse.isspmatrix_csr(haz1.fraction))
self.assertEqual(haz1.event_name, haz_res.event_name)
self.assertTrue(np.array_equal(haz1.date, haz_res.date))
self.assertTrue(np.array_equal(haz1.orig, haz_res.orig))
self.assertTrue(np.array_equal(haz1.event_id, \
haz_res.event_id))
self.assertTrue(np.array_equal(haz1.frequency, haz_res.frequency))
self.assertEqual(haz_res.units, haz1.units)
self.assertEqual(haz1.tag.file_name, \
[haz_res.tag.file_name, haz2.tag.file_name])
self.assertEqual(haz1.tag.haz_type, haz_res.tag.haz_type)
self.assertEqual(haz1.tag.description, \
[haz_res.tag.description, haz2.tag.description])
def _event_probabilistic(self, ev_idx, i_ens, centr_burned):
""" Define synthetic hazard from randomly burned centroids.
Parameters:
ev_idx (int): the selected historical event
i_ens (int): number of the generated probabilistic event
centr_burned (np.array): array containing burned centroids
Returns:
new_haz (Hazard)
"""
LOGGER.debug('Brightness probabilistic event.')
# The brightness values are chosen randomly at every burned centroids
# from the brightness values of the historical event
ev_proba_uni = centr_burned.nonzero()[0] * self.centroids.shape[1] + \
centr_burned.nonzero()[1]
new_haz = Hazard(HAZ_TYPE)
new_haz.intensity = sparse.lil_matrix(np.zeros((1, self.centroids.size)))
for ev_prob in ev_proba_uni:
new_haz.intensity[0, ev_prob] = np.random.choice( \
self.intensity[ev_idx, :].data)
new_haz.intensity = new_haz.intensity.tocsr()
# Hazard
new_haz.tag = TagHazard(HAZ_TYPE)
new_haz.units = 'K' # Kelvin units brightness
new_haz.centroids = self.centroids
new_haz.event_id = np.ones(1, int)
new_haz.frequency = np.ones(1, float)
new_haz.event_name = [str(ev_idx+1) + '_gen' + str(i_ens+1)]
new_haz.date = np.array([self.date[ev_idx]], int)
new_haz.orig = np.zeros(1, bool)
# Following values are defined for each event and centroid
new_haz.fraction = new_haz.intensity.copy()
new_haz.fraction.data.fill(1.0)
return new_haz
def good_hazard():
"""Define well a hazard"""
haz = Hazard('TC')
haz.centroids = Centroids()
haz.centroids.set_lat_lon(np.array([1, 3]), np.array([2, 3]))
haz.centroids.region_id = np.array([1, 2])
haz.event_id = np.array([1, 2, 3])
haz.event_name = ['A', 'B', 'C']
haz.frequency = np.array([1, 2, 3])
# events x centroids
haz.intensity = sparse.csr_matrix([[1, 2], [1, 2], [1, 2]])
haz.fraction = sparse.csr_matrix([[1, 2], [1, 2], [1, 2]])
return haz
def test_read_write_vector_pass(self):
"""Test write_raster: Hazard from vector data"""
haz_fl = Hazard('FL')
haz_fl.event_id = np.array([1])
haz_fl.date = np.array([1])
haz_fl.frequency = np.array([1])
haz_fl.orig = np.array([1])
haz_fl.event_name = ['1']
haz_fl.intensity = sparse.csr_matrix(np.array([0.5, 0.2, 0.1]))
haz_fl.fraction = sparse.csr_matrix(np.array([0.5, 0.2, 0.1]) / 2)
haz_fl.centroids.set_lat_lon(np.array([1, 2, 3]), np.array([1, 2, 3]))
haz_fl.check()
haz_fl.write_raster(DATA_DIR.joinpath('test_write_hazard.tif'))
haz_read = Hazard('FL')
haz_read.set_raster([DATA_DIR.joinpath('test_write_hazard.tif')])
self.assertEqual(haz_read.intensity.shape, (1, 9))
self.assertTrue(
np.allclose(np.unique(np.array(haz_read.intensity.toarray())),
np.array([0.0, 0.1, 0.2, 0.5])))
def dummy_hazard():
hazard = Hazard('TC')
hazard.tag.file_name = 'file1.mat'
hazard.tag.description = 'Description 1'
hazard.centroids = Centroids()
hazard.centroids.set_lat_lon(np.array([1, 3, 5]), np.array([2, 4, 6]))
hazard.event_id = np.array([1, 2, 3, 4])
hazard.event_name = ['ev1', 'ev2', 'ev3', 'ev4']
hazard.date = np.array([1, 2, 3, 4])
hazard.orig = np.array([True, False, False, True])
hazard.frequency = np.array([0.1, 0.5, 0.5, 0.2])
hazard.fraction = sparse.csr_matrix([[0.02, 0.03, 0.04], \
[0.01, 0.01, 0.01], \
[0.3, 0.1, 0.0], \
[0.3, 0.2, 0.0]])
hazard.intensity = sparse.csr_matrix([[0.2, 0.3, 0.4], \
[0.1, 0.1, 0.01], \
[4.3, 2.1, 1.0], \
[5.3, 0.2, 1.3]])
hazard.units = 'm/s'
return hazard
basin_shp = MultiPolygon([basin_shp])
haz_pos.set_raster(files_intensity=[trend_file],
files_fraction=[trend_file],
band=[1],
geometry=basin_shp)
haz_neg.set_raster(files_intensity=[trend_file],
files_fraction=[trend_file],
band=[1],
geometry=basin_shp)
dis_map_pos = np.greater(haz_pos.intensity.todense(), 0)
new_trends = dis_map_pos.astype(int)
haz_pos.fraction = sp.sparse.csr_matrix(new_trends)
haz_pos.intensity = sp.sparse.csr_matrix(new_trends)
dis_map_neg = np.less(haz_neg.fraction.todense(), 0)
new_trends_neg = dis_map_neg.astype(int)
haz_neg.fraction = sp.sparse.csr_matrix(new_trends_neg)
haz_neg.intensity = sp.sparse.csr_matrix(new_trends_neg)
if new_trends.sum() > new_trends_neg.sum():
dis_reg_geo = 1
elif new_trends.sum() < new_trends_neg.sum():
dis_reg_geo = -1
else:
dis_reg_geo = 0
