def addExpectedMeta(self,keys, params={}):
"""
Registers meta to look for in realizations.
@ In, keys, set(str), keys to register
@ In, params, dict, optional, {key:[indexes]}, keys of the dictionary are the variable names,
values of the dictionary are lists of the corresponding indexes/coordinates of given variable
@ Out, None
"""
extraKeys = DataSet.addExpectedMeta(self, keys, params)
self._inputMetaVars.extend(list(key for key in extraKeys if key not in params))
if params:
self._outputMetaVars.extend(list(key for key in extraKeys if key in params))
return extraKeys
def addExpectedMeta(self, keys, params={}, overwrite=False):
"""
Registers meta to look for in realizations.
@ In, keys, set(str), keys to register
@ In, params, dict, optional, {key:[indexes]}, keys of the dictionary are the variable names,
values of the dictionary are lists of the corresponding indexes/coordinates of given variable
@ In, overwrite, bool, optional, if True then allow existing data while changing keys
@ Out, None
"""
extraKeys = DataSet.addExpectedMeta(self,
keys,
params=params,
overwrite=overwrite)
self._inputMetaVars.extend(
list(key for key in extraKeys if key not in params))
# ensure there are no duplicates
self._inputMetaVars = list(set(self._inputMetaVars))
if params:
self._outputMetaVars.extend(
list(key for key in extraKeys if key in params))
return extraKeys
