def test_excel_io(self):
"""Test write and read in excel"""
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
hazard = Hazard.from_mat(HAZ_TEST_MAT)
imp_write = Impact()
ent.exposures.assign_centroids(hazard)
imp_write.calc(ent.exposures, ent.impact_funcs, hazard)
file_name = DATA_FOLDER.joinpath('test.xlsx')
imp_write.write_excel(file_name)
imp_read = Impact.from_excel(file_name)
np.testing.assert_array_equal(imp_write.event_id, imp_read.event_id)
np.testing.assert_array_equal(imp_write.date, imp_read.date)
np.testing.assert_array_equal(imp_write.coord_exp, imp_read.coord_exp)
np.testing.assert_array_almost_equal_nulp(imp_write.eai_exp,
imp_read.eai_exp,
nulp=5)
np.testing.assert_array_almost_equal_nulp(imp_write.at_event,
imp_read.at_event,
nulp=5)
np.testing.assert_array_equal(imp_write.frequency, imp_read.frequency)
self.assertEqual(imp_write.tot_value, imp_read.tot_value)
self.assertEqual(imp_write.aai_agg, imp_read.aai_agg)
self.assertEqual(imp_write.unit, imp_read.unit)
self.assertEqual(
0,
len([
i for i, j in zip(imp_write.event_name, imp_read.event_name)
if i != j
]))
self.assertIsInstance(imp_read.crs, str)
def test_cutoff_hazard_pass(self):
"""Test _cutoff_hazard_damage"""
meas = MeasureSet.from_mat(ENT_TEST_MAT)
act_1 = meas.get_measure(name='Seawall')[0]
haz = Hazard.from_mat(HAZ_TEST_MAT)
exp = Exposures.from_mat(ENT_TEST_MAT)
exp.gdf.rename(columns={'impf': 'impf_TC'}, inplace=True)
exp.check()
imp_set = ImpactFuncSet.from_mat(ENT_TEST_MAT)
new_haz = act_1._cutoff_hazard_damage(exp, imp_set, haz)
self.assertFalse(id(new_haz) == id(haz))
pos_no_null = np.array([
6249, 7697, 9134, 13500, 13199, 5944, 9052, 9050, 2429, 5139, 9053,
7102, 4096, 1070, 5948, 1076, 5947, 7432, 5949, 11694, 5484, 6246,
12147, 778, 3326, 7199, 12498, 11698, 6245, 5327, 4819, 8677, 5970,
7101, 779, 3894, 9051, 5976, 3329, 5978, 4282, 11697, 7193, 5351,
7310, 7478, 5489, 5526, 7194, 4283, 7191, 5328, 4812, 5528, 5527,
5488, 7475, 5529, 776, 5758, 4811, 6223, 7479, 7470, 5480, 5325,
7477, 7318, 7317, 11696, 7313, 13165, 6221
])
all_haz = np.arange(haz.intensity.shape[0])
all_haz[pos_no_null] = -1
pos_null = np.argwhere(all_haz > 0).reshape(-1)
for i_ev in pos_null:
self.assertEqual(new_haz.intensity[i_ev, :].max(), 0)
def test_cutoff_hazard_region_pass(self):
"""Test _cutoff_hazard_damage in specific region"""
meas = MeasureSet.from_mat(ENT_TEST_MAT)
act_1 = meas.get_measure(name='Seawall')[0]
act_1.exp_region_id = [1]
haz = Hazard.from_mat(HAZ_TEST_MAT)
exp = Exposures.from_mat(ENT_TEST_MAT)
exp.gdf['region_id'] = np.zeros(exp.gdf.shape[0])
exp.gdf.region_id.values[10:] = 1
exp.check()
imp_set = ImpactFuncSet.from_mat(ENT_TEST_MAT)
new_haz = act_1._cutoff_hazard_damage(exp, imp_set, haz)
self.assertFalse(id(new_haz) == id(haz))
pos_no_null = np.array([
6249, 7697, 9134, 13500, 13199, 5944, 9052, 9050, 2429, 5139, 9053,
7102, 4096, 1070, 5948, 1076, 5947, 7432, 5949, 11694, 5484, 6246,
12147, 778, 3326, 7199, 12498, 11698, 6245, 5327, 4819, 8677, 5970,
7101, 779, 3894, 9051, 5976, 3329, 5978, 4282, 11697, 7193, 5351,
7310, 7478, 5489, 5526, 7194, 4283, 7191, 5328, 4812, 5528, 5527,
5488, 7475, 5529, 776, 5758, 4811, 6223, 7479, 7470, 5480, 5325,
7477, 7318, 7317, 11696, 7313, 13165, 6221
])
all_haz = np.arange(haz.intensity.shape[0])
all_haz[pos_no_null] = -1
pos_null = np.argwhere(all_haz > 0).reshape(-1)
centr_null = np.unique(exp.gdf.centr_[exp.gdf.region_id == 0])
for i_ev in pos_null:
self.assertEqual(new_haz.intensity[i_ev, centr_null].max(), 0)
def test_remove_measure(self):
"""Test remove_measure method"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_excel(ENT_DEMO_TODAY)
entity.check()
entity.exposures.ref_year = 2018
cost_ben = CostBenefit()
cost_ben.calc(hazard,
entity,
future_year=2040,
risk_func=risk_aai_agg,
imp_time_depen=None,
save_imp=True)
to_remove = 'Mangroves'
self.assertTrue(to_remove in cost_ben.benefit.keys())
cost_ben.remove_measure(to_remove)
self.assertTrue(to_remove not in cost_ben.color_rgb.keys())
self.assertTrue(to_remove not in cost_ben.benefit.keys())
self.assertTrue(to_remove not in cost_ben.cost_ben_ratio.keys())
self.assertTrue(to_remove not in cost_ben.imp_meas_future.keys())
self.assertTrue(to_remove not in cost_ben.imp_meas_present.keys())
self.assertEqual(len(cost_ben.imp_meas_present), 0)
self.assertEqual(len(cost_ben.imp_meas_future), 4)
self.assertEqual(len(cost_ben.color_rgb), 4)
self.assertEqual(len(cost_ben.cost_ben_ratio), 3)
self.assertEqual(len(cost_ben.benefit), 3)
def test_calc_imp_mat_pass(self):
"""Test save imp_mat"""
# Read default entity values
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# Create impact object
impact = Impact()
# Assign centroids to exposures
ent.exposures.assign_centroids(hazard)
# Compute the impact over the whole exposures
impact.calc(ent.exposures, ent.impact_funcs, hazard, save_mat=True)
self.assertIsInstance(impact.imp_mat, sparse.csr_matrix)
self.assertEqual(impact.imp_mat.shape,
(hazard.event_id.size, ent.exposures.gdf.value.size))
np.testing.assert_array_almost_equal_nulp(np.array(
impact.imp_mat.sum(axis=1)).ravel(),
impact.at_event,
nulp=5)
np.testing.assert_array_almost_equal_nulp(
np.sum(impact.imp_mat.toarray() * impact.frequency[:, None],
axis=0).reshape(-1), impact.eai_exp)
def test_impact(self):
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
hazard = Hazard.from_mat(HAZ_TEST_MAT)
impact = Impact()
ent.exposures.assign_centroids(hazard)
impact.calc(ent.exposures, ent.impact_funcs, hazard)
return impact
def test_combine_current_pass(self):
"""Test combine_measures with only future"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_excel(ENT_DEMO_TODAY)
entity.check()
entity.exposures.ref_year = 2018
cost_ben = CostBenefit()
cost_ben.calc(hazard,
entity,
future_year=2040,
risk_func=risk_aai_agg,
imp_time_depen=None,
save_imp=True)
new_name = 'combine'
new_color = np.array([0.1, 0.1, 0.1])
new_cb = cost_ben.combine_measures(['Mangroves', 'Seawall'],
new_name,
new_color,
entity.disc_rates,
imp_time_depen=None,
risk_func=risk_aai_agg)
self.assertTrue(np.allclose(new_cb.color_rgb[new_name], new_color))
self.assertEqual(len(new_cb.imp_meas_present), 0)
new_imp = cost_ben.imp_meas_future['no measure']['impact'].at_event - \
cost_ben.imp_meas_future['Mangroves']['impact'].at_event
new_imp += cost_ben.imp_meas_future['no measure']['impact'].at_event - \
cost_ben.imp_meas_future['Seawall']['impact'].at_event
new_imp = np.maximum(
cost_ben.imp_meas_future['no measure']['impact'].at_event -
new_imp, 0)
self.assertTrue(
np.allclose(new_cb.imp_meas_future[new_name]['impact'].at_event,
new_imp))
self.assertAlmostEqual(
new_cb.imp_meas_future[new_name]['risk'],
np.sum(new_imp *
cost_ben.imp_meas_future['no measure']['impact'].frequency),
5)
self.assertAlmostEqual(
new_cb.imp_meas_future[new_name]['cost'][0],
cost_ben.imp_meas_future['Mangroves']['cost'][0] +
cost_ben.imp_meas_future['Seawall']['cost'][0])
self.assertAlmostEqual(new_cb.imp_meas_future[new_name]['cost'][1], 1)
self.assertTrue(
np.allclose(
new_cb.imp_meas_future[new_name]['efc'].impact,
new_cb.imp_meas_future[new_name]
['impact'].calc_freq_curve().impact))
self.assertAlmostEqual(new_cb.imp_meas_future[new_name]['risk_transf'],
0)
self.assertAlmostEqual(new_cb.benefit[new_name],
51781337529.07264,
places=3)
self.assertAlmostEqual(new_cb.cost_ben_ratio[new_name],
0.19679962474434248)
def test_calib_instance(self):
"""Test save calib instance"""
# Read default entity values
ent = Entity()
ent.read_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# get impact function from set
imp_func = ent.impact_funcs.get_func(
hazard.tag.haz_type, ent.exposures.gdf.impf_TC.median())
# Assign centroids to exposures
ent.exposures.assign_centroids(hazard)
# create input frame
df_in = pd.DataFrame.from_dict({
'v_threshold': [25.7],
'other_param': [2],
'hazard': [HAZ_TEST_MAT]
})
df_in_yearly = pd.DataFrame.from_dict({
'v_threshold': [25.7],
'other_param': [2],
'hazard': [HAZ_TEST_MAT]
})
# Compute the impact over the whole exposures
df_out = calib_instance(hazard, ent.exposures, imp_func, df_in)
df_out_yearly = calib_instance(hazard,
ent.exposures,
imp_func,
df_in_yearly,
yearly_impact=True)
# calc Impact as comparison
impact = Impact()
impact.calc(ent.exposures, ent.impact_funcs, hazard)
IYS = impact.calc_impact_year_set(all_years=True)
# do the tests
self.assertTrue(isinstance(df_out, pd.DataFrame))
self.assertTrue(isinstance(df_out_yearly, pd.DataFrame))
self.assertEqual(df_out.shape[0], hazard.event_id.size)
self.assertEqual(df_out_yearly.shape[0], 161)
self.assertTrue(all(df_out['event_id'] == hazard.event_id))
self.assertTrue(
all(df_out[df_in.columns[0]].isin(df_in[df_in.columns[0]])))
self.assertTrue(
all(df_out_yearly[df_in.columns[1]].isin(df_in[df_in.columns[1]])))
self.assertTrue(
all(df_out_yearly[df_in.columns[2]].isin(df_in[df_in.columns[2]])))
self.assertTrue(
all(df_out['impact_CLIMADA'].values == impact.at_event))
self.assertTrue(
all(df_out_yearly['impact_CLIMADA'].values == [*IYS.values()]))
def test_ref_value_insure_pass(self):
"""Test result against reference value"""
# Read demo entity values
# Set the entity default file to the demo one
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# Create impact object
impact = Impact()
impact.at_event = np.zeros(hazard.intensity.shape[0])
impact.eai_exp = np.zeros(len(ent.exposures.gdf.value))
impact.tot_value = 0
# Assign centroids to exposures
ent.exposures.assign_centroids(hazard)
# Compute impact for 6th exposure
iexp = 5
# Take its impact function
imp_id = ent.exposures.gdf.impf_TC[iexp]
imp_fun = ent.impact_funcs.get_func(hazard.tag.haz_type, imp_id)
# Compute
insure_flag = True
impact._exp_impact(np.array([iexp]), ent.exposures, hazard, imp_fun,
insure_flag)
self.assertEqual(impact.eai_exp.size, ent.exposures.gdf.shape[0])
self.assertEqual(impact.at_event.size, hazard.intensity.shape[0])
events_pos = hazard.intensity[:, ent.exposures.gdf.
centr_TC[iexp]].nonzero()[0]
res_exp = np.zeros((ent.exposures.gdf.shape[0]))
res_exp[iexp] = np.sum(impact.at_event[events_pos] *
hazard.frequency[events_pos])
np.testing.assert_array_equal(res_exp, impact.eai_exp)
self.assertEqual(0, impact.at_event[12])
# Check first 3 values
self.assertEqual(0, impact.at_event[12])
self.assertEqual(0, impact.at_event[41])
self.assertEqual(1.0626600695059455e+06, impact.at_event[44])
# Check intermediate values
self.assertEqual(0, impact.at_event[6281])
self.assertEqual(0, impact.at_event[4998])
self.assertEqual(0, impact.at_event[9527])
self.assertEqual(1.3318063850487845e+08, impact.at_event[7192])
self.assertEqual(4.667108555054083e+06, impact.at_event[8624])
# Check last 3 values
self.assertEqual(0, impact.at_event[14349])
self.assertEqual(0, impact.at_event[14347])
self.assertEqual(0, impact.at_event[14309])
def test_calc_cb_no_change_pass(self):
"""Test _calc_cost_benefit without present value against reference value"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_mat(ENT_TEST_MAT)
entity.measures._data['TC'] = entity.measures._data.pop('XX')
for meas in entity.measures.get_measure('TC'):
meas.haz_type = 'TC'
entity.check()
cost_ben = CostBenefit()
cost_ben._calc_impact_measures(hazard,
entity.exposures,
entity.measures,
entity.impact_funcs,
when='future',
risk_func=risk_aai_agg,
save_imp=True)
cost_ben.present_year = 2018
cost_ben.future_year = 2040
cost_ben._calc_cost_benefit(entity.disc_rates)
self.assertEqual(cost_ben.imp_meas_present, dict())
self.assertEqual(len(cost_ben.imp_meas_future), 5)
self.assertEqual(cost_ben.present_year, 2018)
self.assertEqual(cost_ben.future_year, 2040)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Mangroves'],
0.04230714690616641)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Beach nourishment'],
0.06998836431681373)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Seawall'],
0.2679741183248266)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Building code'],
0.30286828677985717)
self.assertAlmostEqual(cost_ben.benefit['Mangroves'],
3.100583368954022e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Beach nourishment'],
2.468981832719974e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Seawall'],
3.3132973770502796e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Building code'],
3.0376240767284798e+10,
places=3)
self.assertAlmostEqual(cost_ben.tot_climate_risk,
1.2150496306913972e+11,
places=3)
def test_impact_pass(self):
"""Plot impact exceedence frequency curves."""
myent = Entity.from_excel(ENT_DEMO_TODAY)
myent.exposures.check()
myhaz = Hazard.from_mat(HAZ_DEMO_MAT)
myimp = Impact()
myimp.calc(myent.exposures, myent.impact_funcs, myhaz)
ifc = myimp.calc_freq_curve()
myax = ifc.plot()
self.assertIn('Exceedance frequency curve', myax.get_title())
ifc2 = ImpactFreqCurve()
ifc2.return_per = ifc.return_per
ifc2.impact = 1.5e11 * np.ones(ifc2.return_per.size)
ifc2.unit = ''
ifc2.label = 'prove'
ifc2.plot(axis=myax)
def test_ref_value_pass(self):
"""Test result against reference value"""
# Read default entity values
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# Create impact object
impact = Impact()
# Assign centroids to exposures
ent.exposures.assign_centroids(hazard)
# Compute the impact over the whole exposures
impact.calc(ent.exposures, ent.impact_funcs, hazard)
# Check result
num_events = len(hazard.event_id)
num_exp = ent.exposures.gdf.shape[0]
# Check relative errors as well when absolute value gt 1.0e-7
# impact.at_event == EDS.damage in MATLAB
self.assertEqual(num_events, len(impact.at_event))
self.assertEqual(0, impact.at_event[0])
self.assertEqual(0, impact.at_event[int(num_events / 2)])
self.assertAlmostEqual(1.472482938320243e+08, impact.at_event[13809])
self.assertEqual(7.076504723057620e+10, impact.at_event[12147])
self.assertEqual(0, impact.at_event[num_events - 1])
# impact.eai_exp == EDS.ED_at_centroid in MATLAB
self.assertEqual(num_exp, len(impact.eai_exp))
self.assertAlmostEqual(1.518553670803242e+08, impact.eai_exp[0])
self.assertAlmostEqual(1.373490457046383e+08,
impact.eai_exp[int(num_exp / 2)], 6)
self.assertAlmostEqual(1.373490457046383e+08,
impact.eai_exp[int(num_exp / 2)], 5)
self.assertAlmostEqual(1.066837260150042e+08,
impact.eai_exp[num_exp - 1], 6)
self.assertAlmostEqual(1.066837260150042e+08,
impact.eai_exp[int(num_exp - 1)], 5)
# impact.tot_value == EDS.Value in MATLAB
# impact.aai_agg == EDS.ED in MATLAB
self.assertAlmostEqual(6.570532945599105e+11, impact.tot_value)
self.assertAlmostEqual(6.512201157564421e+09, impact.aai_agg, 5)
self.assertAlmostEqual(6.512201157564421e+09, impact.aai_agg, 5)
def test_calc_impact_transf_pass(self):
"""Test calc_impact method: apply all measures and insurance"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_mat(ENT_TEST_MAT)
entity.exposures.gdf.rename(columns={'impf': 'impf_TC'}, inplace=True)
entity.measures._data['TC'] = entity.measures._data.pop('XX')
for meas in entity.measures.get_measure('TC'):
meas.haz_type = 'TC'
meas = entity.measures.get_measure(name='Beach nourishment',
haz_type='TC')
meas.haz_type = 'TC'
meas.hazard_inten_imp = (1, 0)
meas.mdd_impact = (1, 0)
meas.paa_impact = (1, 0)
meas.risk_transf_attach = 5.0e8
meas.risk_transf_cover = 1.0e9
entity.check()
imp, risk_transf = entity.measures.get_measure(
name='Beach nourishment',
haz_type='TC').calc_impact(entity.exposures, entity.impact_funcs,
hazard)
self.assertAlmostEqual(imp.aai_agg, 6.280804242609713e+09)
self.assertAlmostEqual(imp.at_event[0], 0)
self.assertAlmostEqual(imp.at_event[12], 8.648764833437817e+07)
self.assertAlmostEqual(imp.at_event[41], 500000000)
self.assertAlmostEqual(imp.at_event[11890], 6.498096646836635e+07)
self.assertTrue(np.array_equal(imp.coord_exp, np.array([])))
self.assertTrue(np.array_equal(imp.eai_exp, np.array([])))
self.assertAlmostEqual(imp.tot_value, 6.570532945599105e+11)
self.assertEqual(imp.unit, 'USD')
self.assertEqual(imp.imp_mat.shape, (0, 0))
self.assertTrue(np.array_equal(imp.event_id, hazard.event_id))
self.assertTrue(np.array_equal(imp.date, hazard.date))
self.assertEqual(imp.event_name, hazard.event_name)
self.assertEqual(imp.tag['exp'].file_name,
entity.exposures.tag.file_name)
self.assertEqual(imp.tag['haz'].file_name, hazard.tag.file_name)
self.assertEqual(imp.tag['impf_set'].file_name,
entity.impact_funcs.tag.file_name)
self.assertEqual(risk_transf.aai_agg, 2.3139691495470852e+08)
def test_select_event_identity_pass(self):
""" test select same impact with event name, id and date """
# Read default entity values
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# Create impact object
imp = Impact()
# Assign centroids to exposures
ent.exposures.assign_centroids(hazard)
# Compute the impact over the whole exposures
imp.calc(ent.exposures, ent.impact_funcs, hazard, save_mat=True)
sel_imp = imp.select(event_ids=imp.event_id,
event_names=imp.event_name,
dates=(min(imp.date), max(imp.date)))
self.assertTrue(u_coord.equal_crs(sel_imp.crs, imp.crs))
self.assertEqual(sel_imp.unit, imp.unit)
np.testing.assert_array_equal(sel_imp.event_id, imp.event_id)
self.assertEqual(sel_imp.event_name, imp.event_name)
np.testing.assert_array_equal(sel_imp.date, imp.date)
np.testing.assert_array_equal(sel_imp.frequency, imp.frequency)
np.testing.assert_array_equal(sel_imp.at_event, imp.at_event)
np.testing.assert_array_equal(sel_imp.imp_mat.todense(),
imp.imp_mat.todense())
np.testing.assert_array_equal(sel_imp.eai_exp, imp.eai_exp)
self.assertAlmostEqual(round(sel_imp.aai_agg, 5),
round(imp.aai_agg, 5))
self.assertEqual(sel_imp.tot_value, imp.tot_value)
np.testing.assert_array_equal(sel_imp.coord_exp, imp.coord_exp)
self.assertIsInstance(sel_imp, Impact)
self.assertIsInstance(sel_imp.imp_mat, sparse.csr_matrix)
def test_hazard_fraction_pass(self):
"""Generate all possible plots of the hazard fraction."""
hazard = Hazard.from_mat(HAZ_DEMO_MAT)
hazard.event_name = [""] * hazard.event_id.size
hazard.event_name[35] = "NNN_1185106_gen5"
hazard.event_name[11897] = "GORDON_gen7"
myax = hazard.plot_fraction(event=36)
self.assertIn('Event ID 36: NNN_1185106_gen5', myax.get_title())
myax = hazard.plot_fraction(event=-1)
self.assertIn('1-largest Event. ID 11898: GORDON_gen7',
myax.get_title())
myax = hazard.plot_fraction(centr=59)
self.assertIn('Centroid 59: (30.0, -79.0)', myax.get_title())
myax = hazard.plot_fraction(centr=-1)
self.assertIn('1-largest Centroid. 79: (30.0, -77.0)',
myax.get_title())
def test_calc_impact_pass(self):
"""Test calc_impact method: apply all measures but insurance"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_mat(ENT_TEST_MAT)
entity.exposures.gdf.rename(columns={'impf': 'impf_TC'}, inplace=True)
entity.measures._data['TC'] = entity.measures._data.pop('XX')
entity.measures.get_measure(name='Mangroves',
haz_type='TC').haz_type = 'TC'
for meas in entity.measures.get_measure('TC'):
meas.haz_type = 'TC'
entity.check()
imp, risk_transf = entity.measures.get_measure(
'TC', 'Mangroves').calc_impact(entity.exposures,
entity.impact_funcs, hazard)
self.assertAlmostEqual(imp.aai_agg, 4.850407096284983e+09)
self.assertAlmostEqual(imp.at_event[0], 0)
self.assertAlmostEqual(imp.at_event[12], 1.470194187501225e+07)
self.assertAlmostEqual(imp.at_event[41], 4.7226357936631286e+08)
self.assertAlmostEqual(imp.at_event[11890], 1.742110428135755e+07)
self.assertTrue(
np.array_equal(imp.coord_exp[:, 0], entity.exposures.gdf.latitude))
self.assertTrue(
np.array_equal(imp.coord_exp[:, 1],
entity.exposures.gdf.longitude))
self.assertAlmostEqual(imp.eai_exp[0], 1.15677655725858e+08)
self.assertAlmostEqual(imp.eai_exp[-1], 7.528669956120645e+07)
self.assertAlmostEqual(imp.tot_value, 6.570532945599105e+11)
self.assertEqual(imp.unit, 'USD')
self.assertEqual(imp.imp_mat.shape, (0, 0))
self.assertTrue(np.array_equal(imp.event_id, hazard.event_id))
self.assertTrue(np.array_equal(imp.date, hazard.date))
self.assertEqual(imp.event_name, hazard.event_name)
self.assertEqual(imp.tag['exp'].file_name,
entity.exposures.tag.file_name)
self.assertEqual(imp.tag['haz'].file_name, hazard.tag.file_name)
self.assertEqual(imp.tag['impf_set'].file_name,
entity.impact_funcs.tag.file_name)
self.assertEqual(risk_transf.aai_agg, 0)
def test_calc_impf_pass(self):
"""Execute when no impf_HAZ present, but only impf_"""
ent = Entity.from_excel(ENT_DEMO_TODAY)
self.assertTrue('impf_TC' in ent.exposures.gdf.columns)
ent.exposures.gdf.rename(columns={'impf_TC': 'impf_'}, inplace=True)
self.assertFalse('impf_TC' in ent.exposures.gdf.columns)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# Create impact object
impact = Impact()
impact.calc(ent.exposures, ent.impact_funcs, hazard)
# Check result
num_events = len(hazard.event_id)
num_exp = ent.exposures.gdf.shape[0]
# Check relative errors as well when absolute value gt 1.0e-7
# impact.at_event == EDS.damage in MATLAB
self.assertEqual(num_events, len(impact.at_event))
self.assertEqual(0, impact.at_event[0])
self.assertEqual(0, impact.at_event[int(num_events / 2)])
self.assertAlmostEqual(1.472482938320243e+08, impact.at_event[13809])
self.assertEqual(7.076504723057620e+10, impact.at_event[12147])
self.assertEqual(0, impact.at_event[num_events - 1])
# impact.eai_exp == EDS.ED_at_centroid in MATLAB
self.assertEqual(num_exp, len(impact.eai_exp))
self.assertAlmostEqual(1.518553670803242e+08, impact.eai_exp[0])
self.assertAlmostEqual(1.373490457046383e+08,
impact.eai_exp[int(num_exp / 2)], 6)
self.assertAlmostEqual(1.373490457046383e+08,
impact.eai_exp[int(num_exp / 2)], 5)
self.assertAlmostEqual(1.066837260150042e+08,
impact.eai_exp[num_exp - 1], 6)
self.assertAlmostEqual(1.066837260150042e+08,
impact.eai_exp[int(num_exp - 1)], 5)
# impact.tot_value == EDS.Value in MATLAB
# impact.aai_agg == EDS.ED in MATLAB
self.assertAlmostEqual(6.570532945599105e+11, impact.tot_value)
self.assertAlmostEqual(6.512201157564421e+09, impact.aai_agg, 5)
self.assertAlmostEqual(6.512201157564421e+09, impact.aai_agg, 5)
def test_calc_no_change_pass(self):
"""Test calc without future change"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_excel(ENT_DEMO_TODAY)
entity.check()
entity.exposures.ref_year = 2018
cost_ben = CostBenefit()
cost_ben.calc(hazard, entity, future_year=2040)
self.assertEqual(cost_ben.imp_meas_present, dict())
self.assertEqual(len(cost_ben.imp_meas_future), 5)
self.assertEqual(cost_ben.present_year, 2018)
self.assertEqual(cost_ben.future_year, 2040)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Mangroves'],
0.04230714690616641)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Beach nourishment'],
0.06998836431681373)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Seawall'],
0.2679741183248266)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Building code'],
0.30286828677985717)
self.assertAlmostEqual(cost_ben.benefit['Mangroves'],
3.100583368954022e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Beach nourishment'],
2.468981832719974e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Seawall'],
3.3132973770502796e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Building code'],
3.0376240767284798e+10,
places=3)
self.assertAlmostEqual(cost_ben.tot_climate_risk,
1.2150496306913972e+11,
places=3)
def test_local_exceedance_imp_pass(self):
"""Test calc local impacts per return period"""
# Read default entity values
ent = Entity.from_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard.from_mat(HAZ_TEST_MAT)
# Create impact object
impact = Impact()
# Assign centroids to exposures
ent.exposures.assign_centroids(hazard)
# Compute the impact over the whole exposures
impact.calc(ent.exposures, ent.impact_funcs, hazard, save_mat=True)
# Compute the impact per return period over the whole exposures
impact_rp = impact.local_exceedance_imp(return_periods=(10, 40))
self.assertIsInstance(impact_rp, np.ndarray)
self.assertEqual(impact_rp.size, 2 * ent.exposures.gdf.value.size)
self.assertAlmostEqual(np.max(impact_rp), 2916964966.388219, places=5)
self.assertAlmostEqual(np.min(impact_rp), 444457580.131494, places=5)
def test_hazard_intensity_pass(self):
"""Generate all possible plots of the hazard intensity."""
hazard = Hazard.from_mat(HAZ_DEMO_MAT)
hazard.event_name = [""] * hazard.event_id.size
hazard.event_name[35] = "NNN_1185106_gen5"
hazard.event_name[3898] = "NNN_1190604_gen8"
hazard.event_name[5488] = "NNN_1192804_gen8"
myax = hazard.plot_intensity(event=36)
self.assertIn('Event ID 36: NNN_1185106_gen5', myax.get_title())
myax = hazard.plot_intensity(event=-1)
self.assertIn('1-largest Event. ID 3899: NNN_1190604_gen8',
myax.get_title())
myax = hazard.plot_intensity(event=-4)
self.assertIn('4-largest Event. ID 5489: NNN_1192804_gen8',
myax.get_title())
myax = hazard.plot_intensity(event=0)
self.assertIn('TC max intensity at each point', myax.get_title())
myax = hazard.plot_intensity(centr=59)
self.assertIn('Centroid 59: (30.0, -79.0)', myax.get_title())
myax = hazard.plot_intensity(centr=-1)
self.assertIn('1-largest Centroid. 99: (30.0, -75.0)',
myax.get_title())
myax = hazard.plot_intensity(centr=-4)
self.assertIn('4-largest Centroid. 69: (30.0, -78.0)',
myax.get_title())
myax = hazard.plot_intensity(centr=0)
self.assertIn('TC max intensity at each event', myax.get_title())
myax = hazard.plot_intensity(event='NNN_1192804_gen8')
self.assertIn('NNN_1192804_gen8', myax.get_title())
def test_filter_exposures_pass(self):
"""Test _filter_exposures method with two values"""
meas = Measure()
meas.exp_region_id = [3, 4]
meas.haz_type = 'TC'
exp = Exposures.from_mat(ENT_TEST_MAT)
exp.gdf.rename(columns={
'impf_': 'impf_TC',
'centr_': 'centr_TC'
},
inplace=True)
exp.gdf['region_id'] = np.ones(exp.gdf.shape[0])
exp.gdf.region_id.values[:exp.gdf.shape[0] // 2] = 3
exp.gdf.region_id[0] = 4
exp.check()
imp_set = ImpactFuncSet.from_mat(ENT_TEST_MAT)
haz = Hazard.from_mat(HAZ_TEST_MAT)
exp.assign_centroids(haz)
new_exp = copy.deepcopy(exp)
new_exp.gdf['value'] *= 3
new_exp.gdf['impf_TC'].values[:20] = 2
new_exp.gdf['impf_TC'].values[20:40] = 3
new_exp.gdf['impf_TC'].values[40:] = 1
new_ifs = copy.deepcopy(imp_set)
new_ifs.get_func('TC')[1].intensity += 1
ref_ifs = copy.deepcopy(new_ifs)
new_haz = copy.deepcopy(haz)
new_haz.intensity *= 4
res_exp, res_ifs, res_haz = meas._filter_exposures(
exp, imp_set, haz, new_exp.copy(deep=True), new_ifs, new_haz)
# unchanged meta data
self.assertEqual(res_exp.ref_year, exp.ref_year)
self.assertEqual(res_exp.value_unit, exp.value_unit)
self.assertEqual(res_exp.tag.file_name, exp.tag.file_name)
self.assertEqual(res_exp.tag.description, exp.tag.description)
self.assertTrue(u_coord.equal_crs(res_exp.crs, exp.crs))
self.assertTrue(u_coord.equal_crs(res_exp.gdf.crs, exp.gdf.crs))
# regions (that is just input data, no need for testing, but it makes the changed and unchanged parts obious)
self.assertTrue(np.array_equal(res_exp.gdf.region_id.values[0], 4))
self.assertTrue(
np.array_equal(res_exp.gdf.region_id.values[1:25],
np.ones(24) * 3))
self.assertTrue(
np.array_equal(res_exp.gdf.region_id.values[25:], np.ones(25)))
# changed exposures
self.assertTrue(
np.array_equal(res_exp.gdf.value.values[:25],
new_exp.gdf.value.values[:25]))
self.assertTrue(
np.all(
np.not_equal(res_exp.gdf.value.values[:25],
exp.gdf.value.values[:25])))
self.assertTrue(
np.all(
np.not_equal(res_exp.gdf.impf_TC.values[:25],
new_exp.gdf.impf_TC.values[:25])))
self.assertTrue(
np.array_equal(res_exp.gdf.latitude.values[:25],
new_exp.gdf.latitude.values[:25]))
self.assertTrue(
np.array_equal(res_exp.gdf.longitude.values[:25],
new_exp.gdf.longitude.values[:25]))
# unchanged exposures
self.assertTrue(
np.array_equal(res_exp.gdf.value.values[25:],
exp.gdf.value.values[25:]))
self.assertTrue(
np.all(
np.not_equal(res_exp.gdf.value.values[25:],
new_exp.gdf.value.values[25:])))
self.assertTrue(
np.array_equal(res_exp.gdf.impf_TC.values[25:],
exp.gdf.impf_TC.values[25:]))
self.assertTrue(
np.array_equal(res_exp.gdf.latitude.values[25:],
exp.gdf.latitude.values[25:]))
self.assertTrue(
np.array_equal(res_exp.gdf.longitude.values[25:],
exp.gdf.longitude.values[25:]))
# unchanged impact functions
self.assertEqual(list(res_ifs.get_func().keys()), [meas.haz_type])
self.assertEqual(res_ifs.get_func()[meas.haz_type][1].id,
imp_set.get_func()[meas.haz_type][1].id)
self.assertTrue(
np.array_equal(res_ifs.get_func()[meas.haz_type][1].intensity,
imp_set.get_func()[meas.haz_type][1].intensity))
self.assertEqual(res_ifs.get_func()[meas.haz_type][3].id,
imp_set.get_func()[meas.haz_type][3].id)
self.assertTrue(
np.array_equal(res_ifs.get_func()[meas.haz_type][3].intensity,
imp_set.get_func()[meas.haz_type][3].intensity))
# changed impact functions
self.assertTrue(
np.array_equal(
res_ifs.get_func()[meas.haz_type][1 + IMPF_ID_FACT].intensity,
ref_ifs.get_func()[meas.haz_type][1].intensity))
self.assertTrue(
np.array_equal(
res_ifs.get_func()[meas.haz_type][1 + IMPF_ID_FACT].paa,
ref_ifs.get_func()[meas.haz_type][1].paa))
self.assertTrue(
np.array_equal(
res_ifs.get_func()[meas.haz_type][1 + IMPF_ID_FACT].mdd,
ref_ifs.get_func()[meas.haz_type][1].mdd))
self.assertTrue(
np.array_equal(
res_ifs.get_func()[meas.haz_type][3 + IMPF_ID_FACT].intensity,
ref_ifs.get_func()[meas.haz_type][3].intensity))
self.assertTrue(
np.array_equal(
res_ifs.get_func()[meas.haz_type][3 + IMPF_ID_FACT].paa,
ref_ifs.get_func()[meas.haz_type][3].paa))
self.assertTrue(
np.array_equal(
res_ifs.get_func()[meas.haz_type][3 + IMPF_ID_FACT].mdd,
ref_ifs.get_func()[meas.haz_type][3].mdd))
# unchanged hazard
self.assertTrue(
np.array_equal(res_haz.intensity[:, :36].toarray(),
haz.intensity[:, :36].toarray()))
self.assertTrue(
np.array_equal(res_haz.intensity[:, 37:46].toarray(),
haz.intensity[:, 37:46].toarray()))
self.assertTrue(
np.array_equal(res_haz.intensity[:, 47:].toarray(),
haz.intensity[:, 47:].toarray()))
# changed hazard
self.assertTrue(
np.array_equal(res_haz.intensity[[36, 46]].toarray(),
new_haz.intensity[[36, 46]].toarray()))
def test_calc_cb_change_pass(self):
"""Test _calc_cost_benefit with present value against reference value"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_mat(ENT_TEST_MAT)
entity.measures._data['TC'] = entity.measures._data.pop('XX')
for meas in entity.measures.get_measure('TC'):
meas.haz_type = 'TC'
entity.check()
cost_ben = CostBenefit()
cost_ben._calc_impact_measures(hazard,
entity.exposures,
entity.measures,
entity.impact_funcs,
when='present',
risk_func=risk_aai_agg,
save_imp=False)
ent_future = Entity.from_excel(ENT_DEMO_FUTURE)
ent_future.check()
haz_future = copy.deepcopy(hazard)
haz_future.intensity.data += 25
cost_ben._calc_impact_measures(haz_future,
ent_future.exposures,
ent_future.measures,
ent_future.impact_funcs,
when='future',
risk_func=risk_aai_agg,
save_imp=False)
cost_ben.present_year = 2018
cost_ben.future_year = 2040
cost_ben._calc_cost_benefit(entity.disc_rates, imp_time_depen=1)
self.assertEqual(cost_ben.present_year, 2018)
self.assertEqual(cost_ben.future_year, 2040)
self.assertAlmostEqual(cost_ben.tot_climate_risk,
5.768659152882021e+11,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_present['no measure']['risk'],
6.51220115756442e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_present['Mangroves']['risk'],
4.850407096284983e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_present['Beach nourishment']['risk'],
5.188921355413834e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_present['Seawall']['risk'],
4.736400526119911e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_present['Building code']['risk'],
4.884150868173321e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['no measure']['risk'],
5.9506659786664024e+10,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['Mangroves']['risk'],
4.826231151473135e+10,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['risk'],
5.0647250923231674e+10,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['Seawall']['risk'],
21089567135.7345,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['risk'],
4.462999483999791e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Mangroves'],
113345027690.81276,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Beach nourishment'],
89444869971.53653,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Seawall'],
347977469896.1333,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Building code'],
144216478822.05154,
places=3)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Mangroves'],
0.011573232523528404)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Beach nourishment'],
0.01931916274851638)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Seawall'],
0.025515385913577368)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Building code'],
0.06379298728650741)
self.assertAlmostEqual(cost_ben.tot_climate_risk,
576865915288.2021,
places=3)
def test_calc_impact_measures_pass(self):
"""Test _calc_impact_measures against reference value"""
self.assertTrue(HAZ_TEST_MAT.is_file(),
"{} is not a file".format(HAZ_TEST_MAT))
hazard = Hazard.from_mat(HAZ_TEST_MAT)
self.assertTrue(ENT_TEST_MAT.is_file(),
"{} is not a file".format(ENT_TEST_MAT))
entity = Entity.from_mat(ENT_TEST_MAT)
entity.check()
entity.measures._data['TC'] = entity.measures._data.pop('XX')
for meas in entity.measures.get_measure('TC'):
meas.haz_type = 'TC'
entity.check()
cost_ben = CostBenefit()
cost_ben._calc_impact_measures(hazard,
entity.exposures,
entity.measures,
entity.impact_funcs,
when='future',
risk_func=risk_aai_agg,
save_imp=True)
self.assertEqual(cost_ben.imp_meas_present, dict())
self.assertEqual(cost_ben.cost_ben_ratio, dict())
self.assertEqual(cost_ben.benefit, dict())
self.assertEqual(cost_ben.tot_climate_risk, 0.0)
self.assertEqual(cost_ben.present_year, 2016)
self.assertEqual(cost_ben.future_year, 2030)
self.assertEqual(cost_ben.imp_meas_future['no measure']['cost'],
(0, 0))
self.assertAlmostEqual(cost_ben.imp_meas_future['no measure']['risk'],
6.51220115756442e+09,
places=3)
new_efc = cost_ben.imp_meas_future['no measure'][
'impact'].calc_freq_curve()
self.assertTrue(
np.allclose(
new_efc.return_per,
cost_ben.imp_meas_future['no measure']['efc'].return_per))
self.assertTrue(
np.allclose(new_efc.impact,
cost_ben.imp_meas_future['no measure']['efc'].impact))
self.assertEqual(
cost_ben.imp_meas_future['no measure']
['impact'].at_event.nonzero()[0].size, 841)
self.assertAlmostEqual(
cost_ben.imp_meas_future['no measure']['impact'].at_event[14082],
8.801682862431524e+06,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['no measure']['impact'].tot_value,
6.570532945599105e+11,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['no measure']['impact'].aai_agg,
6.51220115756442e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Mangroves']['cost'][0],
1.3117683608515418e+09,
places=3)
self.assertEqual(cost_ben.imp_meas_future['Mangroves']['cost'][1], 1)
self.assertAlmostEqual(cost_ben.imp_meas_future['Mangroves']['risk'],
4.850407096284983e+09,
places=3)
new_efc = cost_ben.imp_meas_future['Mangroves'][
'impact'].calc_freq_curve()
self.assertTrue(
np.allclose(
new_efc.return_per,
cost_ben.imp_meas_future['Mangroves']['efc'].return_per))
self.assertTrue(
np.allclose(new_efc.impact,
cost_ben.imp_meas_future['Mangroves']['efc'].impact))
self.assertEqual(
cost_ben.imp_meas_future['Mangroves']['impact'].at_event.nonzero()
[0].size, 665)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Mangroves']['impact'].at_event[13901],
1.29576562770977e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Mangroves']['impact'].tot_value,
6.570532945599105e+11,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Mangroves']['impact'].aai_agg,
4.850407096284983e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['cost'][0],
1.728000000000000e+09,
places=3)
self.assertEqual(
cost_ben.imp_meas_future['Beach nourishment']['cost'][1], 1)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['risk'],
5.188921355413834e+09,
places=3)
new_efc = cost_ben.imp_meas_future['Beach nourishment'][
'impact'].calc_freq_curve()
self.assertTrue(
np.allclose(
new_efc.return_per,
cost_ben.imp_meas_future['Beach nourishment']
['efc'].return_per))
self.assertTrue(
np.allclose(
new_efc.impact,
cost_ben.imp_meas_future['Beach nourishment']['efc'].impact))
self.assertEqual(
cost_ben.imp_meas_future['Beach nourishment']
['impact'].at_event.nonzero()[0].size, 702)
self.assertEqual(
cost_ben.imp_meas_future['Beach nourishment']
['impact'].at_event[1110], 0.0)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['impact'].eai_exp[5],
1.1133679079730146e+08,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['impact'].tot_value,
6.570532945599105e+11,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['impact'].aai_agg,
5.188921355413834e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['Seawall']['cost'][0],
8.878779433630093e+09,
places=3)
self.assertEqual(cost_ben.imp_meas_future['Seawall']['cost'][1], 1)
self.assertAlmostEqual(cost_ben.imp_meas_future['Seawall']['risk'],
4.736400526119911e+09,
places=3)
new_efc = cost_ben.imp_meas_future['Seawall'][
'impact'].calc_freq_curve()
self.assertTrue(
np.allclose(new_efc.return_per,
cost_ben.imp_meas_future['Seawall']['efc'].return_per))
self.assertTrue(
np.allclose(new_efc.impact,
cost_ben.imp_meas_future['Seawall']['efc'].impact))
self.assertEqual(
cost_ben.imp_meas_future['Seawall']['impact'].at_event.nonzero()
[0].size, 73)
self.assertEqual(
cost_ben.imp_meas_future['Seawall']['impact'].at_event[1229], 0.0)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Seawall']['impact'].tot_value,
6.570532945599105e+11,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Seawall']['impact'].aai_agg,
4.736400526119911e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['cost'][0],
9.200000000000000e+09,
places=3)
self.assertEqual(cost_ben.imp_meas_future['Building code']['cost'][1],
1)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['risk'],
4.884150868173321e+09,
places=3)
new_efc = cost_ben.imp_meas_future['Building code'][
'impact'].calc_freq_curve()
self.assertTrue(
np.allclose(
new_efc.return_per,
cost_ben.imp_meas_future['Building code']['efc'].return_per))
self.assertTrue(
np.allclose(
new_efc.impact,
cost_ben.imp_meas_future['Building code']['efc'].impact))
self.assertEqual(
cost_ben.imp_meas_future['Building code']
['impact'].at_event.nonzero()[0].size, 841)
self.assertEqual(
cost_ben.imp_meas_future['Building code']['impact'].at_event[122],
0.0)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['impact'].eai_exp[11],
7.757060129393841e+07,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['impact'].tot_value,
6.570532945599105e+11,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['impact'].aai_agg,
4.884150868173321e+09,
places=3)
def test_apply_transf_future_pass(self):
"""Test apply_risk_transfer with present and future"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_excel(ENT_DEMO_TODAY)
entity.check()
entity.exposures.ref_year = 2018
fut_ent = copy.deepcopy(entity)
fut_ent.exposures.ref_year = 2040
cost_ben = CostBenefit()
cost_ben.calc(hazard,
entity,
ent_future=fut_ent,
risk_func=risk_aai_agg,
imp_time_depen=None,
save_imp=True)
new_name = 'combine'
new_color = np.array([0.1, 0.1, 0.1])
risk_transf = (1.0e7, 15.0e11, 1)
new_cb = cost_ben.combine_measures(['Mangroves', 'Seawall'],
new_name,
new_color,
entity.disc_rates,
imp_time_depen=None,
risk_func=risk_aai_agg)
new_cb.apply_risk_transfer(new_name,
risk_transf[0],
risk_transf[1],
entity.disc_rates,
cost_fix=0,
cost_factor=risk_transf[2],
imp_time_depen=1,
risk_func=risk_aai_agg)
tr_name = 'risk transfer (' + new_name + ')'
new_imp = cost_ben.imp_meas_future['no measure']['impact'].at_event - \
cost_ben.imp_meas_future['Mangroves']['impact'].at_event
new_imp += cost_ben.imp_meas_future['no measure']['impact'].at_event - \
cost_ben.imp_meas_future['Seawall']['impact'].at_event
new_imp = np.maximum(
cost_ben.imp_meas_future['no measure']['impact'].at_event -
new_imp, 0)
imp_layer = np.minimum(np.maximum(new_imp - risk_transf[0], 0),
risk_transf[1])
risk_transfer = np.sum(
imp_layer *
cost_ben.imp_meas_future['no measure']['impact'].frequency)
new_imp = np.maximum(new_imp - imp_layer, 0)
self.assertTrue(np.allclose(new_cb.color_rgb[new_name], new_color))
self.assertEqual(len(new_cb.imp_meas_present), 3)
self.assertTrue(
np.allclose(new_cb.imp_meas_future[tr_name]['impact'].at_event,
new_imp))
self.assertTrue(
np.allclose(new_cb.imp_meas_present[tr_name]['impact'].at_event,
new_imp))
self.assertAlmostEqual(
new_cb.imp_meas_future[tr_name]['risk'],
np.sum(new_imp *
cost_ben.imp_meas_future['no measure']['impact'].frequency),
5)
self.assertAlmostEqual(
new_cb.imp_meas_present[tr_name]['risk'],
np.sum(new_imp *
cost_ben.imp_meas_future['no measure']['impact'].frequency),
5)
self.assertAlmostEqual(new_cb.cost_ben_ratio[tr_name] *
new_cb.benefit[tr_name],
69715165679.7042,
places=3)
self.assertTrue(
np.allclose(
new_cb.imp_meas_future[tr_name]['efc'].impact,
new_cb.imp_meas_future[tr_name]
['impact'].calc_freq_curve().impact))
self.assertAlmostEqual(new_cb.imp_meas_future[tr_name]['risk_transf'],
risk_transfer)
# benefit = impact layer
self.assertAlmostEqual(new_cb.benefit[tr_name], 69715165679.7042, 4)
self.assertAlmostEqual(new_cb.cost_ben_ratio[tr_name], 1)
def test_calc_change_pass(self):
"""Test calc with future change"""
# present
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_excel(ENT_DEMO_TODAY)
entity.exposures.gdf.rename(columns={'impf_': 'impf_TC'}, inplace=True)
entity.check()
entity.exposures.ref_year = 2018
# future
ent_future = Entity.from_excel(ENT_DEMO_FUTURE)
ent_future.check()
ent_future.exposures.ref_year = 2040
haz_future = copy.deepcopy(hazard)
haz_future.intensity.data += 25
cost_ben = CostBenefit()
cost_ben.calc(hazard, entity, haz_future, ent_future)
self.assertEqual(cost_ben.present_year, 2018)
self.assertEqual(cost_ben.future_year, 2040)
self.assertAlmostEqual(cost_ben.tot_climate_risk,
5.768659152882021e+11,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_present['no measure']['risk'],
6.51220115756442e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_present['Mangroves']['risk'],
4.850407096284983e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_present['Beach nourishment']['risk'],
5.188921355413834e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_present['Seawall']['risk'],
4.736400526119911e+09,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_present['Building code']['risk'],
4.884150868173321e+09,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['no measure']['risk'],
5.9506659786664024e+10,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['Mangroves']['risk'],
4.826231151473135e+10,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Beach nourishment']['risk'],
5.0647250923231674e+10,
places=3)
self.assertAlmostEqual(cost_ben.imp_meas_future['Seawall']['risk'],
21089567135.7345,
places=3)
self.assertAlmostEqual(
cost_ben.imp_meas_future['Building code']['risk'],
4.462999483999791e+10,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Mangroves'],
113345027690.81276,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Beach nourishment'],
89444869971.53653,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Seawall'],
347977469896.1333,
places=3)
self.assertAlmostEqual(cost_ben.benefit['Building code'],
144216478822.05154,
places=3)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Mangroves'],
0.011573232523528404)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Beach nourishment'],
0.01931916274851638)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Seawall'],
0.025515385913577368)
self.assertAlmostEqual(cost_ben.cost_ben_ratio['Building code'],
0.06379298728650741)
self.assertAlmostEqual(cost_ben.tot_climate_risk,
576865915288.2021,
places=3)
def test_apply_ref_pass(self):
"""Test apply method: apply all measures but insurance"""
hazard = Hazard.from_mat(HAZ_TEST_MAT)
entity = Entity.from_mat(ENT_TEST_MAT)
entity.measures._data['TC'] = entity.measures._data.pop('XX')
for meas in entity.measures.get_measure('TC'):
meas.haz_type = 'TC'
entity.check()
new_exp, new_ifs, new_haz = entity.measures.get_measure(
'TC', 'Mangroves').apply(entity.exposures, entity.impact_funcs,
hazard)
self.assertTrue(new_exp is entity.exposures)
self.assertTrue(new_haz is hazard)
self.assertFalse(new_ifs is entity.impact_funcs)
new_imp = new_ifs.get_func('TC')[0]
self.assertTrue(
np.array_equal(
new_imp.intensity,
np.array([4., 24., 34., 44., 54., 64., 74., 84., 104.])))
self.assertTrue(
np.allclose(
new_imp.mdd,
np.array([
0, 0, 0.021857142857143, 0.035887500000000,
0.053977415307403, 0.103534246575342, 0.180414000000000,
0.410796000000000, 0.410796000000000
])))
self.assertTrue(
np.allclose(
new_imp.paa,
np.array([
0, 0.005000000000000, 0.042000000000000, 0.160000000000000,
0.398500000000000, 0.657000000000000, 1.000000000000000,
1.000000000000000, 1.000000000000000
])))
new_imp = new_ifs.get_func('TC')[1]
self.assertTrue(
np.array_equal(
new_imp.intensity,
np.array([4., 24., 34., 44., 54., 64., 74., 84., 104.])))
self.assertTrue(
np.allclose(
new_imp.mdd,
np.array([
0, 0, 0, 0.025000000000000, 0.054054054054054,
0.104615384615385, 0.211764705882353, 0.400000000000000,
0.400000000000000
])))
self.assertTrue(
np.allclose(
new_imp.paa,
np.array([
0, 0.004000000000000, 0, 0.160000000000000,
0.370000000000000, 0.650000000000000, 0.850000000000000,
1.000000000000000, 1.000000000000000
])))
