def visualise_connectivity(S):
Ns = len(S.source)
Nt = len(S.target)
b.figure(figsize=(10, 4))
b.subplot(121)
b.plot(b.zeros(Ns), b.arange(Ns), 'ok', ms=10)
b.plot(b.ones(Nt), b.arange(Nt), 'ok', ms=10)
for i, j in zip(S.i, S.j):
b.plot([0, 1], [i, j], '-k')
b.xticks([0, 1], ['Source', 'Target'])
b.ylabel('Neuron index')
b.xlim(-0.1, 1.1)
b.ylim(-1, max(Ns, Nt))
b.subplot(122)
b.plot(S.i, S.j, 'ok')
b.xlim(-1, Ns)
b.ylim(-1, Nt)
b.xlabel('Source neuron index')
b.ylabel('Target neuron index')
save_theta()
if not test_mode:
save_connections()
else:
np.save(data_path + 'activity/resultPopVecs' + str(num_examples), result_monitor)
np.save(data_path + 'activity/inputNumbers' + str(num_examples), input_numbers)
#------------------------------------------------------------------------------
# plot results
#------------------------------------------------------------------------------
if rate_monitors:
b2.figure(fig_num)
fig_num += 1
for i, name in enumerate(rate_monitors):
b2.subplot(len(rate_monitors), 1, 1+i)
b2.plot(rate_monitors[name].t/b2.second, rate_monitors[name].rate, '.')
b2.title('Rates of population ' + name)
if spike_monitors:
b2.figure(fig_num)
fig_num += 1
for i, name in enumerate(spike_monitors):
b2.subplot(len(spike_monitors), 1, 1+i)
b2.plot(spike_monitors[name].t/b2.ms, spike_monitors[name].i, '.')
b2.title('Spikes of population ' + name)
if spike_counters:
b2.figure(fig_num)
fig_num += 1
b2.plot(spike_monitors['Ae'].count[:])
save_theta()
if not test_mode:
save_connections()
else:
np.save(data_path + 'activity/resultPopVecs' + str(num_examples), result_monitor)
np.save(data_path + 'activity/inputNumbers' + str(num_examples), input_numbers)
#------------------------------------------------------------------------------
# plot results
#------------------------------------------------------------------------------
if rate_monitors:
b2.figure(fig_num)
fig_num += 1
for i, name in enumerate(rate_monitors):
b2.subplot(len(rate_monitors), 1, 1+i)
b2.plot(rate_monitors[name].t/b2.second, rate_monitors[name].rate, '.')
b2.title('Rates of population ' + name)
if spike_monitors:
b2.figure(fig_num)
fig_num += 1
for i, name in enumerate(spike_monitors):
b2.subplot(len(spike_monitors), 1, 1+i)
b2.plot(spike_monitors[name].t/b2.ms, spike_monitors[name].i, '.')
b2.title('Spikes of population ' + name)
if spike_counters:
b2.figure(fig_num)
fig_num += 1
b2.plot(spike_monitors['Ae'].count[:])