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Merge pull request #2 from EglantineGiraud/physrisk_commercial_real_e…
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Fix format
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@EglantineGiraud
EglantineGiraud authored Sep 24, 2023
2 parents 5949178 + 5da4683 commit fc5b35d
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Showing 2 changed files with 49 additions and 17 deletions.
4 changes: 3 additions & 1 deletion src/physrisk/kernel/impact.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,7 +61,9 @@ def calculate_impacts( # noqa: C901
hazard_data = [responses[req] for req in get_iterable(requests)]
if isinstance(model, VulnerabilityModelAcuteBase):
impact, vul, event = model.get_impact_details(asset, hazard_data)
results[ImpactKey(asset, model.hazard_type)] = AssetImpactResult(impact, vulnerability=vul, event=event, hazard_data=hazard_data)
results[ImpactKey(asset, model.hazard_type)] = AssetImpactResult(
impact, vulnerability=vul, event=event, hazard_data=hazard_data
)
elif isinstance(model, VulnerabilityModelBase):
impact = model.get_impact(asset, hazard_data)
results[ImpactKey(asset, model.hazard_type)] = AssetImpactResult(impact, hazard_data=hazard_data)
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62 changes: 46 additions & 16 deletions src/test/models/test_real_estate_models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,9 @@ def test_real_estate_model_details(self):
np.testing.assert_almost_equal(hazard_bin_probs[1], 0.1)

# check that intensity bin edges for vulnerability matrix are same as for hazard
vulnerability_intensity_bin_edges = results[ImpactKey(assets[0], RiverineInundation)].vulnerability.intensity_bins
vulnerability_intensity_bin_edges = results[
ImpactKey(assets[0], RiverineInundation)
].vulnerability.intensity_bins
np.testing.assert_almost_equal(vulnerability_intensity_bin_edges, hazard_bin_edges)

# check the impact distribution the matrix is size [len(intensity_bins) - 1, len(impact_bins) - 1]
Expand All @@ -58,7 +60,9 @@ def test_real_estate_model_details(self):
np.testing.assert_allclose([mean, std], [0.09090909, 0.08184968], rtol=1e-6)

# probability that impact occurs between impact bin edge 1 and impact bin edge 2
prob_impact = np.dot(hazard_bin_probs, results[ImpactKey(assets[0], RiverineInundation)].vulnerability.prob_matrix[:, 1])
prob_impact = np.dot(
hazard_bin_probs, results[ImpactKey(assets[0], RiverineInundation)].vulnerability.prob_matrix[:, 1]
)
np.testing.assert_almost_equal(prob_impact, 0.19350789547968042)

# no check with pre-calculated values for others:
Expand Down Expand Up @@ -122,7 +126,9 @@ def test_coastal_real_estate_model(self):
)

def test_commercial_real_estate_model_details(self):
curve = np.array([2.8302893e-06, 0.09990284, 0.21215445, 0.531271, 0.7655724, 0.99438345, 1.2871761, 1.502281, 1.7134278])
curve = np.array(
[2.8302893e-06, 0.09990284, 0.21215445, 0.531271, 0.7655724, 0.99438345, 1.2871761, 1.502281, 1.7134278]
)
store = mock_hazard_model_store_inundation(TestData.longitudes, TestData.latitudes, curve)
hazard_model = ZarrHazardModel(source_paths=get_default_source_paths(), store=store)

Expand All @@ -136,7 +142,27 @@ def test_commercial_real_estate_model_details(self):
year = 2080

# impact bin edges are calibrated so that hazard_bin_probs == impact_bin_probs when the impact standard deviation is negligible:
vulnerability_models = {RealEstateAsset: [RealEstateRiverineInundationModel(impact_bin_edges=np.array([0, 0.030545039098059, 0.125953058445539, 0.322702019487674, 0.566880882840096, 0.731980974578735, 0.823993215529066, 0.884544511664047, 0.922115133960502, 0.969169745946688, 1.0]))]}
vulnerability_models = {
RealEstateAsset: [
RealEstateRiverineInundationModel(
impact_bin_edges=np.array(
[
0,
0.030545039098059,
0.125953058445539,
0.322702019487674,
0.566880882840096,
0.731980974578735,
0.823993215529066,
0.884544511664047,
0.922115133960502,
0.969169745946688,
1.0,
]
)
)
]
}

results = calculate_impacts(assets, hazard_model, vulnerability_models, scenario=scenario, year=year)

Expand All @@ -151,7 +177,9 @@ def test_commercial_real_estate_model_details(self):
np.testing.assert_almost_equal(hazard_bin_probs[2], 0.06)

# check that intensity bin edges for vulnerability matrix are same as for hazard
vulnerability_intensity_bin_edges = results[ImpactKey(assets[0], RiverineInundation)].vulnerability.intensity_bins
vulnerability_intensity_bin_edges = results[
ImpactKey(assets[0], RiverineInundation)
].vulnerability.intensity_bins
np.testing.assert_almost_equal(vulnerability_intensity_bin_edges, hazard_bin_edges)

# check the impact distribution the matrix is size [len(intensity_bins) - 1, len(impact_bins) - 1]
Expand All @@ -162,24 +190,26 @@ def test_commercial_real_estate_model_details(self):
np.testing.assert_allclose([mean, std], [0.1, 0.2884275164878624], rtol=1e-6)

# probability that impact occurs between impact bin edge 2 and impact bin edge 3
prob_impact = np.dot(hazard_bin_probs, results[ImpactKey(assets[0], RiverineInundation)].vulnerability.prob_matrix[:, 2])
prob_impact = np.dot(
hazard_bin_probs, results[ImpactKey(assets[0], RiverineInundation)].vulnerability.prob_matrix[:, 2]
)
np.testing.assert_almost_equal(prob_impact, 0.10040196672295522)

# no check with pre-calculated values for others:
np.testing.assert_allclose(
results[ImpactKey(assets[0], RiverineInundation)].impact.prob,
np.array(
[
2.009085E-07,
3.001528E-01,
1.004020E-01,
5.885136E-02,
1.760415E-02,
1.159864E-02,
6.130639E-03,
2.729225E-03,
1.446537E-03,
8.450993E-05
2.009085e-07,
3.001528e-01,
1.004020e-01,
5.885136e-02,
1.760415e-02,
1.159864e-02,
6.130639e-03,
2.729225e-03,
1.446537e-03,
8.450993e-05,
]
),
rtol=2e-6,
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