def load(userFileName, dataType):
"""
load(userFileName, dataType)
Convenient data loader for results saved as NeuroTools StandardPickleFile.
Return the corresponding NeuroTools object. Datatype argument may become
optionnal in the future, but for now it is necessary to specify the type
of the recorded data. To have a better control on the parameters of the
NeuroTools objects, see the load_*** functions.
Inputs:
userFileName - the user file name
datatype - A string to specify the type od the data in
's' : spikes
'g' : conductances
'v' : membrane traces
'c' : currents
"""
userFile = StandardPickleFile(userFileName)
if dataType in ('s', 'spikes'):
return signals.load_spikelist(userFile)
elif dataType == 'v':
# Need t_start to be None, othervice NeuroTools overwrite loaded
# t_start with default value 0
return signals.load_vmlist(userFile, t_start=None)
elif dataType == 'c':
return signals.load_currentlist(userFile, t_start=None)
elif dataType == 'g':
return signals.load_conductancelist(userFile, t_start=None)
else:
raise Exception(
"The datatype %s is not handled ! Should be 's','g','c' or 'v'" %
datatype)
def save(self, userFileName):
'''
Save spike list
Inputs:
userFileName - name of file to save
Examples:
>> userFileName = /home/savename.dat
>> aslist.save(userFileName)
'''
userFile = StandardPickleFile(userFileName) # create user file
# Invoke save function of base class ConductanceList which has
# AnalogSignalList as base class where the method exist.
super(MyVmList, self).save(userFile)