# print 'Vm : ', Vm[-1]
# print 'm : ', m[-1]
# print 'h : ', h[-1]
# print 'n : ', n[-1]
# print 'a : ', a[-1]
# print 'b : ', b[-1]
return Vm, I
##############################################################################################
## main program
##############################################################################################
if __name__ == "__main__":
# Set global matplotlib parameters.
lplot.set_rc_param()
## set parameters
p = set_parameters()
## simulate
Vm, I = simulate(p)
print "plotting original signal"
plt.figure(figsize=lplot.size_common)
ax = plt.gca()
lplot.nice_axes(ax)
ax.set_ylabel(r"Mem. Pot. \textbf{[\si{\milli\volt}]}")
ax.set_xlabel(r"Time \textbf{[\si{\milli\second}]}")
plt.plot(p['time'], Vm, color=lcmaps.get_color(0))
lplot.save_plt(plt, "cs_ap_original_signal", ".")
if dt is None:
dt = data['dt']
if data['dt'] != dt:
raise ValueError("Mismatching simulations.")
dt = data['dt']
# Collecting data from PC neurons.
LFPy_util.other.collect_data(dir_input, sim_sphere, gather_data)
sort_indices = np.argsort(neuron_names[:])
neuron_names = np.take(neuron_names, sort_indices)
widths_I = np.take(widths_I, sort_indices)
widths_II = np.take(widths_II, sort_indices)
amps_II = np.take(amps_II, sort_indices)
lplot.set_rc_param(True)
lplot.plot_format = ['pdf']
width_bins = np.arange(0, 2.5, dt)
ampli_bins = np.linspace(0,300,80)
bins = [ampli_bins, width_bins]
amp_width_hist = np.zeros([len(neuron_names), len(ampli_bins)-1, len(width_bins)-1])
for i in xrange(len(widths_I)):
hist, _, _ = np.histogram2d(amps_II[i], widths_I[i], bins)
hist = hist/float(hist.sum())
amp_width_hist[i] = hist
for grp in groups:
hist = np.zeros(amp_width_hist[0].shape)
for i, name in enumerate(neuron_names):
