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