def read_att_excel(measures, dfr, var_names):
"""Read Excel measures attributes"""
num_mes = len(dfr.index)
for idx in range(0, num_mes):
meas = Measure()
meas.name = dfr[var_names['col_name']['name']][idx]
try:
meas.haz_type = dfr[var_names['col_name']['haz']][idx]
except KeyError:
pass
meas.color_rgb = np.fromstring(
dfr[var_names['col_name']['color']][idx],
dtype=float,
sep=' ')
meas.cost = dfr[var_names['col_name']['cost']][idx]
meas.hazard_freq_cutoff = dfr[var_names['col_name']
['haz_frq']][idx]
meas.hazard_set = dfr[var_names['col_name']['haz_set']][idx]
# Search for (a, b) values, put a = 1 otherwise
try:
meas.hazard_inten_imp = (
dfr[var_names['col_name']['haz_int_a']][idx],
dfr[var_names['col_name']['haz_int_b']][idx])
except KeyError:
meas.hazard_inten_imp = (
1, dfr['hazard intensity impact'][idx])
try:
meas.exposures_set = dfr[var_names['col_name']
['exp_set']][idx]
meas.exp_region_id = ast.literal_eval(
dfr[var_names['col_name']['exp_reg']][idx])
except KeyError:
pass
except ValueError:
meas.exp_region_id = dfr[var_names['col_name']
['exp_reg']][idx]
meas.mdd_impact = (dfr[var_names['col_name']['mdd_a']][idx],
dfr[var_names['col_name']['mdd_b']][idx])
meas.paa_impact = (dfr[var_names['col_name']['paa_a']][idx],
dfr[var_names['col_name']['paa_b']][idx])
meas.imp_fun_map = dfr[var_names['col_name']['fun_map']][idx]
meas.risk_transf_attach = dfr[var_names['col_name']
['risk_att']][idx]
meas.risk_transf_cover = dfr[var_names['col_name']
['risk_cov']][idx]
try:
meas.risk_transf_cost_factor = dfr[var_names['col_name']
['risk_fact']][idx]
except KeyError:
pass
measures.append(meas)
def read_att_mat(measures, data, file_name, var_names):
"""Read MATLAB measures attributes"""
num_mes = len(data[var_names['var_name']['name']])
for idx in range(0, num_mes):
meas = Measure()
meas.name = hdf5.get_str_from_ref(
file_name, data[var_names['var_name']['name']][idx][0])
color_str = hdf5.get_str_from_ref(
file_name, data[var_names['var_name']['color']][idx][0])
meas.color_rgb = np.fromstring(color_str, dtype=float, sep=' ')
meas.cost = data[var_names['var_name']['cost']][idx][0]
meas.haz_type = hdf5.get_str_from_ref(
file_name, data[var_names['var_name']['haz']][idx][0])
meas.hazard_freq_cutoff = data[var_names['var_name']
['haz_frq']][idx][0]
meas.hazard_set = hdf5.get_str_from_ref(
file_name, data[var_names['var_name']['haz_set']][idx][0])
try:
meas.hazard_inten_imp = (
data[var_names['var_name']['haz_int_a']][idx][0],
data[var_names['var_name']['haz_int_b']][0][idx])
except KeyError:
meas.hazard_inten_imp = (
data[var_names['var_name']['haz_int_a'][:-2]][idx][0],
0)
# different convention of signes followed in MATLAB!
meas.mdd_impact = (
data[var_names['var_name']['mdd_a']][idx][0],
data[var_names['var_name']['mdd_b']][idx][0])
meas.paa_impact = (
data[var_names['var_name']['paa_a']][idx][0],
data[var_names['var_name']['paa_b']][idx][0])
meas.imp_fun_map = hdf5.get_str_from_ref(
file_name, data[var_names['var_name']['fun_map']][idx][0])
meas.exposures_set = hdf5.get_str_from_ref(
file_name, data[var_names['var_name']['exp_set']][idx][0])
exp_region_id = data[var_names['var_name']['exp_reg']][idx][0]
if exp_region_id:
meas.exp_region_id = [exp_region_id]
meas.risk_transf_attach = data[var_names['var_name']
['risk_att']][idx][0]
meas.risk_transf_cover = data[var_names['var_name']
['risk_cov']][idx][0]
measures.append(meas)
def test_change_all_hazard_pass(self):
"""Test _change_all_hazard method"""
meas = Measure()
meas.hazard_set = HAZ_DEMO_H5
ref_haz = Hazard('TC')
ref_haz.read_hdf5(HAZ_DEMO_H5)
hazard = Hazard('TC')
new_haz = meas._change_all_hazard(hazard)
self.assertEqual(new_haz.tag.file_name, ref_haz.tag.file_name)
self.assertEqual(new_haz.tag.haz_type, ref_haz.tag.haz_type)
self.assertTrue(np.array_equal(new_haz.frequency, ref_haz.frequency))
self.assertTrue(np.array_equal(new_haz.date, ref_haz.date))
self.assertTrue(np.array_equal(new_haz.orig, ref_haz.orig))
self.assertTrue(np.array_equal(new_haz.centroids.coord, ref_haz.centroids.coord))
self.assertTrue(np.array_equal(new_haz.intensity.data, ref_haz.intensity.data))
self.assertTrue(np.array_equal(new_haz.fraction.data, ref_haz.fraction.data))