class Network:
def __init__(self):
savedparams = []
savedcells = []
net = Network()
net.savedparams = savedparams
net.savedcells = savedcells
# Plot the mean number of spikes
if ShowMean:
ns.plot_mean_spikes(net, "IC-soma")
ns.show()
if SaveMean:
ns.save_mean_spikes(net, "IC-soma", param, base_filename + "_mean.dat")
ns.save_mean_spikes(net, "DNLL-soma", param, base_filename + "_DNLL_mean.dat")
if SaveSpikes:
for a in param:
ns.save_spikes(net, "IC-soma", a, base_filename + "_spikes_" + ns.list_to_string(a) + ".dat", repeats)
if SaveFSL:
ns.save_fsl(net, "IC-soma", param, base_filename + "_fsl.dat", repeats)
if SaveVoltage:
for d in stims:
networks["C"].cells["IC"]["cells"][0].sec["soma"].diam = a
for d in stims*repeats:
progress.update(count, total)
count += 1
for net in networks:
s[net].stim_dur = d
s[net].run()
key = [a,d]
networks[net].savecells([["IC","soma"],["IC","dendE"]], key, spikes=True,
conductance=False,
current=False,
voltage=True)
if True:
ns.plot_mean_spikes(networks["C"], "IC-soma", "c_soma_size.dat")
ns.plot_mean_spikes(networks["AC"], "IC-soma", "ac_soma_size.dat")
ns.show() # Comment out to just save the results to file
# Plot the results
if False:
count = 0
for a in param:
for d in stims:
count += 1
key = [a,d]
ns.subplot(len(param),len(stims),count)
ns.plot_voltage(networks["C"], "IC-soma", key)
progress.update(count, len(stims))
ns.show()
