def from_excel(cls, file_name, description=''):
"""Read csv or xls or xlsx file following climada's template.
Parameters
----------
file_name : str, optional
file name(s) or folder name
containing the files to read
description : str or list(str), optional
one description of the
data or a description of each data file
Returns
-------
ent : climada.entity.Entity
The entity from excel file
"""
exp = Exposures(pd.read_excel(file_name))
exp.tag = Tag()
exp.tag.file_name = str(file_name)
exp.tag.description = description
dr = DiscRates.from_excel(file_name, description)
impf_set = ImpactFuncSet.from_excel(file_name, description)
meas_set = MeasureSet.from_excel(file_name, description)
return cls(exposures=exp,
disc_rates=dr,
impact_func_set=impf_set,
measure_set=meas_set)
def test_read_template_pass(self):
"""Wrong exposures definition"""
df = pd.read_excel(ENT_TEMPLATE_XLS)
exp_df = Exposures(df)
# set metadata
exp_df.ref_year = 2020
exp_df.tag = Tag(ENT_TEMPLATE_XLS, 'ENT_TEMPLATE_XLS')
exp_df.value_unit = 'XSD'
exp_df.check()
def test_io_hdf5_pass(self):
"""write and read hdf5"""
exp_df = Exposures(pd.read_excel(ENT_TEMPLATE_XLS), crs="epsg:32632")
exp_df.set_geometry_points()
exp_df.check()
# set metadata
exp_df.ref_year = 2020
exp_df.tag = Tag(ENT_TEMPLATE_XLS, 'ENT_TEMPLATE_XLS')
exp_df.value_unit = 'XSD'
file_name = DATA_DIR.joinpath('test_hdf5_exp.h5')
# pd.errors.PerformanceWarning should be suppressed. Therefore, make sure that
# PerformanceWarning would result in test failure here
import warnings
with warnings.catch_warnings():
warnings.simplefilter("error",
category=pd.errors.PerformanceWarning)
exp_df.write_hdf5(file_name)
exp_read = Exposures.from_hdf5(file_name)
self.assertEqual(exp_df.ref_year, exp_read.ref_year)
self.assertEqual(exp_df.value_unit, exp_read.value_unit)
self.assertDictEqual(exp_df.meta, exp_read.meta)
self.assertTrue(u_coord.equal_crs(exp_df.crs, exp_read.crs))
self.assertTrue(u_coord.equal_crs(exp_df.gdf.crs, exp_read.gdf.crs))
self.assertEqual(exp_df.tag.file_name, exp_read.tag.file_name)
self.assertEqual(exp_df.tag.description, exp_read.tag.description)
np.testing.assert_array_equal(exp_df.gdf.latitude.values,
exp_read.gdf.latitude.values)
np.testing.assert_array_equal(exp_df.gdf.longitude.values,
exp_read.gdf.longitude.values)
np.testing.assert_array_equal(exp_df.gdf.value.values,
exp_read.gdf.value.values)
np.testing.assert_array_equal(exp_df.gdf.deductible.values,
exp_read.gdf.deductible.values)
np.testing.assert_array_equal(exp_df.gdf.cover.values,
exp_read.gdf.cover.values)
np.testing.assert_array_equal(exp_df.gdf.region_id.values,
exp_read.gdf.region_id.values)
np.testing.assert_array_equal(exp_df.gdf.category_id.values,
exp_read.gdf.category_id.values)
np.testing.assert_array_equal(exp_df.gdf.impf_TC.values,
exp_read.gdf.impf_TC.values)
np.testing.assert_array_equal(exp_df.gdf.centr_TC.values,
exp_read.gdf.centr_TC.values)
np.testing.assert_array_equal(exp_df.gdf.impf_FL.values,
exp_read.gdf.impf_FL.values)
np.testing.assert_array_equal(exp_df.gdf.centr_FL.values,
exp_read.gdf.centr_FL.values)
for point_df, point_read in zip(exp_df.gdf.geometry.values,
exp_read.gdf.geometry.values):
self.assertEqual(point_df.x, point_read.x)
self.assertEqual(point_df.y, point_read.y)
def test_io_hdf5_pass(self):
"""write and read hdf5"""
exp_df = Exposures(pd.read_excel(ENT_TEMPLATE_XLS))
exp_df.set_geometry_points()
exp_df.check()
# set metadata
exp_df.ref_year = 2020
exp_df.tag = Tag(ENT_TEMPLATE_XLS, 'ENT_TEMPLATE_XLS')
exp_df.value_unit = 'XSD'
file_name = DATA_DIR.joinpath('test_hdf5_exp.h5')
exp_df.write_hdf5(file_name)
exp_read = Exposures()
exp_read.read_hdf5(file_name)
self.assertEqual(exp_df.ref_year, exp_read.ref_year)
self.assertEqual(exp_df.value_unit, exp_read.value_unit)
self.assertEqual(exp_df.crs, exp_read.crs)
self.assertEqual(exp_df.tag.file_name, exp_read.tag.file_name)
self.assertEqual(exp_df.tag.description, exp_read.tag.description)
self.assertTrue(
np.array_equal(exp_df.gdf.latitude.values,
exp_read.gdf.latitude.values))
self.assertTrue(
np.array_equal(exp_df.gdf.longitude.values,
exp_read.gdf.longitude.values))
self.assertTrue(
np.array_equal(exp_df.gdf.value.values, exp_read.gdf.value.values))
self.assertTrue(
np.array_equal(exp_df.gdf.deductible.values,
exp_read.gdf.deductible.values))
self.assertTrue(
np.array_equal(exp_df.gdf.cover.values, exp_read.gdf.cover.values))
self.assertTrue(
np.array_equal(exp_df.gdf.region_id.values,
exp_read.gdf.region_id.values))
self.assertTrue(
np.array_equal(exp_df.gdf.category_id.values,
exp_read.gdf.category_id.values))
self.assertTrue(
np.array_equal(exp_df.gdf.if_TC.values, exp_read.gdf.if_TC.values))
self.assertTrue(
np.array_equal(exp_df.gdf.centr_TC.values,
exp_read.gdf.centr_TC.values))
self.assertTrue(
np.array_equal(exp_df.gdf.if_FL.values, exp_read.gdf.if_FL.values))
self.assertTrue(
np.array_equal(exp_df.gdf.centr_FL.values,
exp_read.gdf.centr_FL.values))
for point_df, point_read in zip(exp_df.gdf.geometry.values,
exp_read.gdf.geometry.values):
self.assertEqual(point_df.x, point_read.x)
self.assertEqual(point_df.y, point_read.y)
def _build_exp(self):
eai_exp = Exposures()
eai_exp['value'] = self.eai_exp
eai_exp['latitude'] = self.coord_exp[:, 0]
eai_exp['longitude'] = self.coord_exp[:, 1]
eai_exp.crs = self.crs
eai_exp.value_unit = self.unit
eai_exp.ref_year = 0
eai_exp.tag = Tag()
eai_exp.meta = None
return eai_exp
def _build_exp_event(self, event_id):
"""Write impact of an event as Exposures
Parameters:
event_id(int): id of the event
"""
impact_csr_exp = Exposures()
impact_csr_exp['value'] = self.imp_mat.toarray()[event_id - 1, :]
impact_csr_exp['latitude'] = self.coord_exp[:, 0]
impact_csr_exp['longitude'] = self.coord_exp[:, 1]
impact_csr_exp.crs = self.crs
impact_csr_exp.value_unit = self.unit
impact_csr_exp.ref_year = 0
impact_csr_exp.tag = Tag()
impact_csr_exp.meta = None
return impact_csr_exp
