def plot_and_save(self):
if create_raster_plot and sim.rank() == 0 :
# Numbers of neurons from which spikes were recorded
n_rec = [[0] * n_pops_per_layer] * n_layers
for layer, i in layers.items() :
for pop, j in pops.items() :
if record_fraction:
n_rec[i][j] = round(N_full[layer][pop] * N_scaling * frac_record_spikes)
else:
n_rec[i][j] = n_record
plotting.show_raster_bars(raster_t_min, raster_t_max, n_rec,
frac_to_plot, system_params['output_path'] + '/')
spikes = n.pops[layer][pop].get_data('spikes', gather=False)
for segment in spikes.segments :
io.write_segment(segment)
if record_v :
io = PyNNTextIO(filename=system_params['output_path'] \
+ "/vm_" + layer + '_' + pop + '_' + str(sim.rank()) + ".txt")
vm = n.pops[layer][pop].get_data('v', gather=False)
for segment in vm.segments :
try :
io.write_segment(segment)
except AssertionError :
pass
end_writing = time.time()
print("Writing data took %g s" % (end_writing - start_writing,))
if create_raster_plot and sim.rank()==0 :
# Numbers of neurons from which spikes were recorded
n_rec = [[0]*n_pops_per_layer]*n_layers
for layer, i in layers.items() :
for pop, j in pops.items() :
if record_fraction:
n_rec[i][j] = round(N_full[layer][pop]*N_scaling*frac_record_spikes)
else:
n_rec[i][j] = n_record
plotting.show_raster_bars(raster_t_min, raster_t_max, n_rec, frac_to_plot, \
system_params['output_path'] + '/')
sim.end()
tt = numpy.array([t*sim.get_time_step()/1000. for t in range(len(analogsignal.transpose()[0]))])
times_vm_a.append(tt)
for i in range(len(source_ids)):
glob_id = source_ids[i]
index_in_pop = n.pops[layer][pop].id_to_index(glob_id)
#print("Writing data for cell %i = %s[%s] (gid: %i) to %s "%(i, pop,index_in_pop, glob_id, filename))
vm = analogsignal.transpose()[i]
times_vm_a.append(vm/1000.)
times_vm = numpy.array(times_vm_a).transpose()
numpy.savetxt(filename, times_vm , delimiter = '\t', fmt='%s')
end_writing = time.time()
print("Writing data took %g s" % (end_writing - start_writing,))
if create_raster_plot and sim.rank() == 0 :
# Numbers of neurons from which spikes were recorded
n_rec = [[0] * n_pops_per_layer for i in range(n_layers)]
for layer, i in layers.items() :
for pop, j in pops.items() :
if record_fraction:
n_rec[i][j] = round(N_full[layer][pop] * N_scaling * frac_record_spikes)
else:
n_rec[i][j] = n_record
if n_rec > 0:
plotting.show_raster_bars(raster_t_min, raster_t_max, n_rec, frac_to_plot,
system_params['output_path'] + '/', N_scaling, K_scaling)
sim.end()