def _fill_dfr(self, dfr, var_names):
def _get_xls_funcs(dfr, var_names):
"""Parse individual impact functions."""
dist_func = []
for (haz_type,
imp_id) in zip(dfr[var_names['col_name']['peril']],
dfr[var_names['col_name']['func_id']]):
if (haz_type, imp_id) not in dist_func:
dist_func.append((haz_type, imp_id))
return dist_func
try:
dist_func = _get_xls_funcs(dfr, var_names)
for haz_type, imp_id in dist_func:
df_func = dfr[dfr[var_names['col_name']['peril']] == haz_type]
df_func = df_func[df_func[var_names['col_name']['func_id']] ==
imp_id]
func = ImpactFunc()
func.haz_type = haz_type
func.id = imp_id
# check that the unit of the intensity is the same
try:
if len(df_func[var_names['col_name']
['name']].unique()) != 1:
raise ValueError(
'Impact function with two different names.')
func.name = df_func[var_names['col_name']
['name']].values[0]
except KeyError:
func.name = str(func.id)
# check that the unit of the intensity is the same, if provided
try:
if len(df_func[var_names['col_name']
['unit']].unique()) != 1:
raise ValueError('Impact function with two different \
intensity units.')
func.intensity_unit = \
df_func[var_names['col_name']['unit']].values[0]
except KeyError:
pass
func.intensity = df_func[var_names['col_name']['inten']].values
func.mdd = df_func[var_names['col_name']['mdd']].values
func.paa = df_func[var_names['col_name']['paa']].values
self.append(func)
except KeyError as err:
LOGGER.error("Not existing variable: %s", str(err))
raise err
def read_mat(self, file_name, description='', var_names=DEF_VAR_MAT):
"""Read MATLAB file generated with previous MATLAB CLIMADA version.
Parameters:
file_name (str): absolute file name
description (str, optional): description of the data
var_names (dict, optional): name of the variables in the file
"""
def _get_hdf5_funcs(imp, file_name, var_names):
"""Get rows that fill every impact function and its name."""
func_pos = dict()
for row, (fun_id, fun_type) in enumerate(
zip(imp[var_names['var_name']['fun_id']].squeeze(),
imp[var_names['var_name']['peril']].squeeze())):
type_str = u_hdf5.get_str_from_ref(file_name, fun_type)
key = (type_str, int(fun_id))
if key not in func_pos:
func_pos[key] = list()
func_pos[key].append(row)
return func_pos
def _get_hdf5_str(imp, idxs, file_name, var_name):
"""Get rows with same string in var_name."""
prev_str = ""
for row in idxs:
cur_str = u_hdf5.get_str_from_ref(file_name, imp[var_name][row][0])
if prev_str == "":
prev_str = cur_str
elif prev_str != cur_str:
LOGGER.error("Impact function with two different %s.", var_name)
raise ValueError
return prev_str
imp = u_hdf5.read(file_name)
self.clear()
self.tag.file_name = str(file_name)
self.tag.description = description
try:
imp = imp[var_names['sup_field_name']]
except KeyError:
pass
try:
imp = imp[var_names['field_name']]
funcs_idx = _get_hdf5_funcs(imp, file_name, var_names)
for imp_key, imp_rows in funcs_idx.items():
func = ImpactFunc()
func.haz_type = imp_key[0]
func.id = imp_key[1]
# check that this function only has one intensity unit, if provided
try:
func.intensity_unit = _get_hdf5_str(imp, imp_rows,
file_name,
var_names['var_name']['unit'])
except KeyError:
pass
# check that this function only has one name
try:
func.name = _get_hdf5_str(imp, imp_rows, file_name,
var_names['var_name']['name'])
except KeyError:
func.name = str(func.id)
func.intensity = np.take(imp[var_names['var_name']['inten']], imp_rows)
func.mdd = np.take(imp[var_names['var_name']['mdd']], imp_rows)
func.paa = np.take(imp[var_names['var_name']['paa']], imp_rows)
self.append(func)
except KeyError as err:
LOGGER.error("Not existing variable: %s", str(err))
raise err
def from_mat(cls, file_name, description='', var_names=None):
"""Read MATLAB file generated with previous MATLAB CLIMADA version.
Parameters
----------
file_name : str
absolute file name
description : str, optional
description of the data
var_names : dict, optional
name of the variables in the file
Return
------
impf_set : climada.entity.impact_func_set.ImpactFuncSet
Impact func set as defined in matlab file.
"""
if var_names is None:
var_names = DEF_VAR_MAT
def _get_hdf5_funcs(imp, file_name, var_names):
"""Get rows that fill every impact function and its name."""
func_pos = dict()
for row, (fun_id, fun_type) in enumerate(
zip(imp[var_names['var_name']['fun_id']].squeeze(),
imp[var_names['var_name']['peril']].squeeze())):
type_str = u_hdf5.get_str_from_ref(file_name, fun_type)
key = (type_str, int(fun_id))
if key not in func_pos:
func_pos[key] = list()
func_pos[key].append(row)
return func_pos
def _get_hdf5_str(imp, idxs, file_name, var_name):
"""Get rows with same string in var_name."""
prev_str = ""
for row in idxs:
cur_str = u_hdf5.get_str_from_ref(file_name,
imp[var_name][row][0])
if prev_str == "":
prev_str = cur_str
elif prev_str != cur_str:
raise ValueError("Impact function with two different %s." %
var_name)
return prev_str
imp = u_hdf5.read(file_name)
impf_set = cls()
impf_set.tag.file_name = str(file_name)
impf_set.tag.description = description
try:
imp = imp[var_names['sup_field_name']]
except KeyError:
pass
try:
imp = imp[var_names['field_name']]
funcs_idx = _get_hdf5_funcs(imp, file_name, var_names)
for imp_key, imp_rows in funcs_idx.items():
func = ImpactFunc()
func.haz_type = imp_key[0]
func.id = imp_key[1]
# check that this function only has one intensity unit, if provided
try:
func.intensity_unit = _get_hdf5_str(
imp, imp_rows, file_name,
var_names['var_name']['unit'])
except KeyError:
pass
# check that this function only has one name
try:
func.name = _get_hdf5_str(imp, imp_rows, file_name,
var_names['var_name']['name'])
except KeyError:
func.name = str(func.id)
func.intensity = np.take(imp[var_names['var_name']['inten']],
imp_rows)
func.mdd = np.take(imp[var_names['var_name']['mdd']], imp_rows)
func.paa = np.take(imp[var_names['var_name']['paa']], imp_rows)
impf_set.append(func)
except KeyError as err:
raise KeyError("Not existing variable: %s" % str(err)) from err
return impf_set