def _calc_impact(self, new_exp, new_ifs, new_haz):
"""Compute impact and risk transfer of measure implemented over inputs.
Parameters:
new_exp (Exposures): exposures once measure applied
new_ifs (ImpactFuncSet): impact functions once measure applied
new_haz (Hazard): hazard once measure applied
Returns:
Impact, float
"""
from climada.engine.impact import Impact
imp = Impact()
imp.calc(new_exp, new_ifs, new_haz)
risk_transfer = 0
if self.risk_transf_attach + self.risk_transf_cover > 0:
imp_layer = np.minimum(np.maximum(imp.at_event - self.risk_transf_attach, 0),
self.risk_transf_cover)
risk_transfer = np.sum(imp_layer * imp.frequency)
imp.at_event = np.maximum(imp.at_event -imp_layer, 0)
imp.aai_agg = np.sum(imp.at_event * imp.frequency)
# expected annual impact per exposure no longer valid
imp.eai_exp = np.array([])
return imp, risk_transfer
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()
ent.read_excel(ENT_DEMO_TODAY)
ent.check()
# Read default hazard file
hazard = Hazard('TC')
hazard.read_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.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.if_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.shape[0])
self.assertEqual(impact.at_event.size, hazard.intensity.shape[0])
events_pos = hazard.intensity[:, ent.exposures.centr_TC[iexp]].nonzero(
)[0]
res_exp = np.zeros((ent.exposures.shape[0]))
res_exp[iexp] = np.sum(impact.at_event[events_pos] *
hazard.frequency[events_pos])
self.assertTrue(np.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_write_read_exp_test(self):
"""Test result against reference value"""
# Create impact object
num_ev = 5
num_exp = 10
imp_write = Impact()
imp_write.tag = {
'exp': Tag('file_exp.p', 'descr exp'),
'haz': TagHaz('TC', 'file_haz.p', 'descr haz'),
'if_set': Tag()
}
imp_write.event_id = np.arange(num_ev)
imp_write.event_name = [
'event_' + str(num) for num in imp_write.event_id
]
imp_write.date = np.ones(num_ev)
imp_write.coord_exp = np.zeros((num_exp, 2))
imp_write.coord_exp[:, 0] = 1.5
imp_write.coord_exp[:, 1] = 2.5
imp_write.eai_exp = np.arange(num_exp) * 100
imp_write.at_event = np.arange(num_ev) * 50
imp_write.frequency = np.ones(num_ev) * 0.1
imp_write.tot_value = 1000
imp_write.aai_agg = 1001
imp_write.unit = 'USD'
file_name = os.path.join(DATA_FOLDER, 'test.csv')
imp_write.write_csv(file_name)
imp_read = Impact()
imp_read.read_csv(file_name)
self.assertTrue(np.array_equal(imp_write.event_id, imp_read.event_id))
self.assertTrue(np.array_equal(imp_write.date, imp_read.date))
self.assertTrue(np.array_equal(imp_write.coord_exp,
imp_read.coord_exp))
self.assertTrue(np.array_equal(imp_write.eai_exp, imp_read.eai_exp))
self.assertTrue(np.array_equal(imp_write.at_event, imp_read.at_event))
self.assertTrue(np.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, dict)
def test_risk_trans_pass(self):
"""Test calc_risk_transfer"""
# Create impact object
imp = Impact()
imp.event_id = np.arange(10)
imp.event_name = [0, 1, 2, 3, 4, 5, 6, 7, 8, 15]
imp.date = np.arange(10)
imp.coord_exp = np.array([[1, 2], [2, 3]])
imp.crs = DEF_CRS
imp.eai_exp = np.array([1, 2])
imp.at_event = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 15])
imp.frequency = np.ones(10) / 5
imp.tot_value = 10
imp.aai_agg = 100
imp.unit = 'USD'
imp.imp_mat = sparse.csr_matrix(np.empty((0, 0)))
new_imp, imp_rt = imp.calc_risk_transfer(2, 10)
self.assertEqual(new_imp.unit, imp.unit)
self.assertEqual(new_imp.tot_value, imp.tot_value)
np.testing.assert_array_equal(new_imp.imp_mat.toarray(),
imp.imp_mat.toarray())
self.assertEqual(new_imp.event_name, imp.event_name)
np.testing.assert_array_almost_equal_nulp(new_imp.event_id,
imp.event_id)
np.testing.assert_array_almost_equal_nulp(new_imp.date, imp.date)
np.testing.assert_array_almost_equal_nulp(new_imp.frequency,
imp.frequency)
np.testing.assert_array_almost_equal_nulp(new_imp.coord_exp, [])
np.testing.assert_array_almost_equal_nulp(new_imp.eai_exp, [])
np.testing.assert_array_almost_equal_nulp(
new_imp.at_event, [0, 1, 2, 2, 2, 2, 2, 2, 2, 5])
self.assertAlmostEqual(new_imp.aai_agg, 4.0)
self.assertEqual(imp_rt.unit, imp.unit)
self.assertEqual(imp_rt.tot_value, imp.tot_value)
np.testing.assert_array_equal(imp_rt.imp_mat.toarray(),
imp.imp_mat.toarray())
self.assertEqual(imp_rt.event_name, imp.event_name)
np.testing.assert_array_almost_equal_nulp(imp_rt.event_id,
imp.event_id)
np.testing.assert_array_almost_equal_nulp(imp_rt.date, imp.date)
np.testing.assert_array_almost_equal_nulp(imp_rt.frequency,
imp.frequency)
np.testing.assert_array_almost_equal_nulp(imp_rt.coord_exp, [])
np.testing.assert_array_almost_equal_nulp(imp_rt.eai_exp, [])
np.testing.assert_array_almost_equal_nulp(
imp_rt.at_event, [0, 0, 0, 1, 2, 3, 4, 5, 6, 10])
self.assertAlmostEqual(imp_rt.aai_agg, 6.2)
def test_risk_trans_pass(self):
""" Test calc_risk_transfer """
# Create impact object
imp = Impact()
imp.event_id = np.arange(10)
imp.event_name = [0, 1, 2, 3, 4, 5, 6, 7, 8, 15]
imp.date = np.arange(10)
imp.coord_exp = np.array([[1, 2], [2, 3]])
imp.crs = DEF_CRS
imp.eai_exp = np.array([1, 2])
imp.at_event = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 15])
imp.frequency = np.ones(10) / 5
imp.tot_value = 10
imp.aai_agg = 100
imp.unit = 'USD'
imp.imp_mat = []
new_imp, imp_rt = imp.calc_risk_transfer(2, 10)
self.assertEqual(new_imp.unit, imp.unit)
self.assertEqual(new_imp.tot_value, imp.tot_value)
self.assertEqual(new_imp.imp_mat, imp.imp_mat)
self.assertEqual(new_imp.event_name, imp.event_name)
self.assertTrue(np.allclose(new_imp.event_id, imp.event_id))
self.assertTrue(np.allclose(new_imp.date, imp.date))
self.assertTrue(np.allclose(new_imp.frequency, imp.frequency))
self.assertTrue(np.allclose(new_imp.coord_exp, np.array([])))
self.assertTrue(np.allclose(new_imp.eai_exp, np.array([])))
self.assertTrue(
np.allclose(new_imp.at_event,
np.array([0, 1, 2, 2, 2, 2, 2, 2, 2, 5])))
self.assertAlmostEqual(new_imp.aai_agg, 4.0)
self.assertEqual(imp_rt.unit, imp.unit)
self.assertEqual(imp_rt.tot_value, imp.tot_value)
self.assertEqual(imp_rt.imp_mat, imp.imp_mat)
self.assertEqual(imp_rt.event_name, imp.event_name)
self.assertTrue(np.allclose(imp_rt.event_id, imp.event_id))
self.assertTrue(np.allclose(imp_rt.date, imp.date))
self.assertTrue(np.allclose(imp_rt.frequency, imp.frequency))
self.assertTrue(np.allclose(imp_rt.coord_exp, np.array([])))
self.assertTrue(np.allclose(imp_rt.eai_exp, np.array([])))
self.assertTrue(
np.allclose(imp_rt.at_event,
np.array([0, 0, 0, 1, 2, 3, 4, 5, 6, 10])))
self.assertAlmostEqual(imp_rt.aai_agg, 6.2)
def dummy_impact():
imp = Impact()
imp.event_id = np.arange(6)
imp.event_name = [0, 1, 'two', 'three', 30, 31]
imp.date = np.arange(6)
imp.coord_exp = np.array([[1, 2], [1.5, 2.5]])
imp.crs = DEF_CRS
imp.eai_exp = np.array([7.2, 7.2])
imp.at_event = np.array([0, 2, 4, 6, 60, 62])
imp.frequency = np.array([1 / 6, 1 / 6, 1, 1, 1 / 30, 1 / 30])
imp.tot_value = 7
imp.aai_agg = 14.4
imp.unit = 'USD'
imp.imp_mat = sparse.csr_matrix(
np.array([[0, 0], [1, 1], [2, 2], [3, 3], [30, 30], [31, 31]]))
return imp