# 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):