def test_calc_sector_total_impact(self):
"""Test running total impact calculations."""
sup = SupplyChain()
sup.read_wiod16(year='test',
range_rows=(5, 117),
range_cols=(4, 116),
col_iso3=2,
col_sectors=1)
# Tropical cyclone over Florida and Caribbean
hazard = Hazard('TC')
hazard.read_mat(HAZ_TEST_MAT)
# Read demo entity values
# Set the entity default file to the demo one
exp = Exposures()
exp.read_hdf5(EXP_DEMO_H5)
exp.check()
exp.gdf.region_id = 840 #assign right id for USA
exp.assign_centroids(hazard)
impf_tc = IFTropCyclone()
impf_tc.set_emanuel_usa()
impf_set = ImpactFuncSet()
impf_set.append(impf_tc)
impf_set.check()
sup.calc_sector_direct_impact(hazard, exp, impf_set)
sup.calc_indirect_impact(io_approach='ghosh')
sup.calc_total_impact()
self.assertAlmostEqual((sup.years.shape[0], sup.mriot_data.shape[0]),
sup.total_impact.shape)
self.assertAlmostEqual((sup.mriot_data.shape[0], ),
sup.total_aai_agg.shape)
def test_assign_pass(self):
"""Check that attribute `assigned` is correctly set."""
np_rand = np.random.RandomState(123456789)
haz = Hazard('FL')
haz.set_raster([HAZ_DEMO_FL], window=Window(10, 20, 50, 60))
haz.raster_to_vector()
ncentroids = haz.centroids.size
exp = Exposures()
exp.gdf.crs = haz.centroids.crs
# some are matching exactly, some are geographically close
exp.gdf['longitude'] = np.concatenate([
haz.centroids.lon,
haz.centroids.lon + 0.001 * (-0.5 + np_rand.rand(ncentroids))
])
exp.gdf['latitude'] = np.concatenate([
haz.centroids.lat,
haz.centroids.lat + 0.001 * (-0.5 + np_rand.rand(ncentroids))
])
expected_result = np.concatenate(
[np.arange(ncentroids),
np.arange(ncentroids)])
# make sure that it works for both float32 and float64
for test_dtype in [np.float64, np.float32]:
haz.centroids.lat = haz.centroids.lat.astype(test_dtype)
haz.centroids.lon = haz.centroids.lon.astype(test_dtype)
exp.assign_centroids(haz)
self.assertEqual(exp.gdf.shape[0],
len(exp.gdf[INDICATOR_CENTR + 'FL']))
np.testing.assert_array_equal(
exp.gdf[INDICATOR_CENTR + 'FL'].values, expected_result)
def test_assign_raster_same_pass(self):
"""Test assign_centroids with raster hazard"""
exp = Exposures()
exp.set_from_raster(HAZ_DEMO_FL, window=Window(10, 20, 50, 60))
exp.check()
haz = Hazard('FL')
haz.set_raster([HAZ_DEMO_FL], window=Window(10, 20, 50, 60))
exp.assign_centroids(haz)
np.testing.assert_array_equal(exp.gdf[INDICATOR_CENTR + 'FL'].values,
np.arange(haz.centroids.size, dtype=int))
def test_assign_raster_pass(self):
""" Test assign_centroids with raster hazard """
exp = Exposures()
exp['longitude'] = np.array([-69.235, -69.2427, -72, -68.8016496, 30])
exp['latitude'] = np.array([10.235, 10.226, 2, 9.71272097, 50])
exp.crs = DEF_CRS
haz = Hazard('FL')
haz.set_raster([HAZ_DEMO_FL], window=Window(10, 20, 50, 60))
exp.assign_centroids(haz)
self.assertEqual(exp[INDICATOR_CENTR + 'FL'][0], 51)
self.assertEqual(exp[INDICATOR_CENTR + 'FL'][1], 100)
self.assertEqual(exp[INDICATOR_CENTR + 'FL'][2], -1)
self.assertEqual(exp[INDICATOR_CENTR + 'FL'][3], 3000 - 1)
self.assertEqual(exp[INDICATOR_CENTR + 'FL'][4], -1)
def test_assign_large_hazard_subset_pass(self):
"""Test assign_centroids with raster hazard"""
exp = Exposures()
exp.set_from_raster(HAZ_DEMO_FL, window=Window(10, 20, 50, 60))
exp.gdf.latitude[[0, 1]] = exp.gdf.latitude[[1, 0]]
exp.gdf.longitude[[0, 1]] = exp.gdf.longitude[[1, 0]]
exp.check()
haz = Hazard('FL')
haz.set_raster([HAZ_DEMO_FL])
haz.raster_to_vector()
exp.assign_centroids(haz)
assigned_centroids = haz.centroids.select(
sel_cen=exp.gdf[INDICATOR_CENTR + 'FL'].values)
np.testing.assert_array_equal(assigned_centroids.lat, exp.gdf.latitude)
np.testing.assert_array_equal(assigned_centroids.lon,
exp.gdf.longitude)
def test_assign_raster_pass(self):
"""Test assign_centroids with raster hazard"""
haz = Hazard('FL')
# explicit, easy-to-understand raster centroids for hazard
haz.centroids = Centroids()
haz.centroids.meta = {
'count': 1, 'crs': DEF_CRS,
'width': 20, 'height': 10,
'transform': rasterio.Affine(1.5, 0.0, -20, 0.0, -1.4, 8)
}
# explicit points with known results (see `expected_result` for details)
exp = Exposures(crs=DEF_CRS)
exp.gdf['longitude'] = np.array([
-20.1, -20.0, -19.8, -19.0, -18.6, -18.4,
-19.0, -19.0, -19.0, -19.0,
-20.1, 0.0, 10.1, 10.1, 10.1, 0.0, -20.2, -20.3,
-6.4, 9.8, 0.0,
])
exp.gdf['latitude'] = np.array([
7.3, 7.3, 7.3, 7.3, 7.3, 7.3,
8.1, 7.9, 6.7, 6.5,
8.1, 8.2, 8.3, 0.0, -6.1, -6.2, -6.3, 0.0,
-1.9, -1.7, 0.0,
])
exp.assign_centroids(haz)
expected_result = [
# constant y-value, varying x-value
-1, 0, 0, 0, 0, 1,
# constant x-value, varying y-value
-1, 0, 0, 20,
# out of bounds: topleft, top, topright, right, bottomright, bottom, bottomleft, left
-1, -1, -1, -1, -1, -1, -1, -1,
# some explicit points within the raster
149, 139, 113,
]
np.testing.assert_array_equal(exp.gdf[INDICATOR_CENTR + 'FL'].values, expected_result)
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()
exp.read_mat(ENT_TEST_MAT)
exp.gdf.rename(columns={'if_': 'if_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()
imp_set.read_mat(ENT_TEST_MAT)
haz = Hazard('TC')
haz.read_mat(HAZ_TEST_MAT)
exp.assign_centroids(haz)
new_exp = copy.deepcopy(exp)
new_exp.gdf['value'] *= 3
new_exp.gdf['if_TC'].values[:20] = 2
new_exp.gdf['if_TC'].values[20:40] = 3
new_exp.gdf['if_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.assertEqual(res_exp.crs, exp.crs)
self.assertEqual(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.if_TC.values[:25], new_exp.gdf.if_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.if_TC.values[25:], exp.gdf.if_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 + IF_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 + IF_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 + IF_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 + IF_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 + IF_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 + IF_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 calc_sector_direct_impact(self):
"""Test running direct impact calculations."""
sup = SupplyChain()
sup.read_wiod16(year='test',
range_rows=(5, 117),
range_cols=(4, 116),
col_iso3=2,
col_sectors=1)
# Tropical cyclone over Florida and Caribbean
hazard = Hazard('TC')
hazard.read_mat(HAZ_TEST_MAT)
# Read demo entity values
# Set the entity default file to the demo one
exp = Exposures()
exp.read_hdf5(EXP_DEMO_H5)
exp.check()
exp.gdf.region_id = 840 #assign right id for USA
exp.assign_centroids(hazard)
impf_tc = IFTropCyclone()
impf_tc.set_emanuel_usa()
impf_set = ImpactFuncSet()
impf_set.append(impf_tc)
impf_set.check()
subsecs = list(range(10)) + list(range(15, 25))
sup.calc_sector_direct_impact(hazard,
exp,
impf_set,
selected_subsec=subsecs)
self.assertAlmostEqual((sup.years.shape[0], sup.mriot_data.shape[0]),
sup.direct_impact.shape)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual((sup.mriot_data.shape[0], ),
sup.direct_aai_agg.shape)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual(sup.reg_dir_imp[0], 'USA')
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, subsecs].sum(),
places=3)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[subsecs].sum(),
places=3)
sup.calc_sector_direct_impact(hazard,
exp,
impf_set,
selected_subsec='manufacturing')
self.assertAlmostEqual((sup.years.shape[0], sup.mriot_data.shape[0]),
sup.direct_impact.shape)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual((sup.mriot_data.shape[0], ),
sup.direct_aai_agg.shape)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual(sup.reg_dir_imp[0], 'USA')
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, range(4, 23)].sum(),
places=3)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[range(4, 23)].sum(),
places=3)
sup.calc_sector_direct_impact(hazard,
exp,
impf_set,
selected_subsec='agriculture')
self.assertAlmostEqual((sup.years.shape[0], sup.mriot_data.shape[0]),
sup.direct_impact.shape)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual((sup.mriot_data.shape[0], ),
sup.direct_aai_agg.shape)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, range(0, 1)].sum(),
places=3)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[range(0, 1)].sum(),
places=3)
sup.calc_sector_direct_impact(hazard,
exp,
impf_set,
selected_subsec='mining')
self.assertAlmostEqual((sup.years.shape[0], sup.mriot_data.shape[0]),
sup.direct_impact.shape)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual((sup.mriot_data.shape[0], ),
sup.direct_aai_agg.shape)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, range(3, 4)].sum(),
places=3)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[range(3, 4)].sum(),
places=3)
sup.calc_sector_direct_impact(hazard,
exp,
impf_set,
selected_subsec='service')
self.assertAlmostEqual((sup.years.shape[0], sup.mriot_data.shape[0]),
sup.direct_impact.shape)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual((sup.mriot_data.shape[0], ),
sup.direct_aai_agg.shape)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[sup.reg_pos['USA']].sum(),
places=3)
self.assertAlmostEqual(sup.direct_impact.sum(),
sup.direct_impact[:, range(26, 56)].sum(),
places=3)
self.assertAlmostEqual(sup.direct_aai_agg.sum(),
sup.direct_aai_agg[range(26, 56)].sum(),
places=3)
