def list2array(self):
"""
Set internal storage for timeseries data.
Open file and read data into internal storage.
"""
Model.list2array(self)
# read and store data
for ii in range(self.n):
idx = self.idx.v[ii]
path = self.path.v[ii]
sheet = self.sheet.v[ii]
try:
df = pd.read_excel(path, sheet_name=sheet)
except FileNotFoundError as e:
logger.error('<%s idx=%s>: File not found: "%s"',
self.class_name, idx, path)
raise e
except ValueError as e:
logger.error('<%s idx=%s>: Sheet not found: "%s" in "%s"',
self.class_name, idx, sheet, path)
raise e
for field in self.fields.v[ii]:
if field not in df.columns:
raise ValueError('Field {} not found in timeseries data'.format(field))
self._data[idx] = df
def list2array(self):
"""
Set internal storage for timeseries data.
Open file and read data into internal storage.
"""
# TODO: timeseries file must exist for setup to pass. Consider moving
# the file reading to a later stage so that adding sheets to xlsx file can work
# without the file existing.
Model.list2array(self)
# read and store data
for ii in range(self.n):
idx = self.idx.v[ii]
path = self.path.v[ii]
sheet = self.sheet.v[ii]
if not os.path.isabs(path):
path = os.path.join(self.system.files.case_path, path)
if not os.path.exists(path):
raise FileNotFoundError('<%s idx=%s>: File not found: "%s"',
self.class_name, idx, path)
# --- read supported formats ---
if path.endswith("xlsx") or path.endswith("xls"):
df = self._read_excel(path, sheet, idx)
elif path.endswith("csv"):
df = pd.read_csv(path)
for field in self.fields.v[ii]:
if field not in df.columns:
raise ValueError(
'Field {} not found in timeseries data'.format(field))
self._data[idx] = df
logger.info('Read timeseries data from "%s"', path)
