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)
"""
import NeuroTools.signals as signals
# loading spiking data
s = signals.load_spikelist('spike_data')
# raster plot
s.raster_plot()
# mean rate
print 'mean rate: ', s.mean_rate()
print 'mean rates: ', s.mean_rates()
# fano factor of isi
print 'fano factor of isi: ', s.fano_factors_isi()
# cv of isi
print 'cv of isi:', s.cv_isi()
# isi distribution
hs = s.isi_hist(bins=20, display=True)
# loading voltage data
v = signals.load_vmlist('vm_data')
# plot all the signals
v.plot()
# plot only one AnalogSignal
v[1].plot()
# spike triggered averages
v.event_triggered_average(s, t_min=50.)
import numpy
import sys
import NeuroTools.signals as nts
import pylab
for fn in sys.argv[1:]:
print "Plotting", fn
vmlist= nts.load_vmlist(fn)
n = len(vmlist.analog_signals)
t_axis = vmlist.time_axis()
print "debug", vmlist.analog_signals
print "debug", vmlist.analog_signals[1]
vmlist.analog_signals[1].plot()
# print len(vmlist)
# for i in xrange(n):
# vmlist.analog_signals[i].plot()
pylab.show()
# loading spiking data
s = signals.load_spikelist('spike_data')
# raster plot
s.raster_plot()
# mean rate
print 'mean rate: ',s.mean_rate()
print 'mean rates: ',s.mean_rates()
# fano factor of isi
print 'fano factor of isi: ',s.fano_factors_isi()
# cv of isi
print 'cv of isi:',s.cv_isi()
# isi distribution
hs = s.isi_hist(bins=20, display=True)
# loading voltage data
v = signals.load_vmlist('vm_data')
# plot all the signals
v.plot()
# plot only one AnalogSignal
v[1].plot()
# spike triggered averages
v.event_triggered_average(s,t_min=50.)
