def plotIntermediateResults(self):
print("\n--- Plotting results ---\n")
# Individual intracellular traces
if self.plot_intracellular and self.record_Vm:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
start_pos = int(self.start_time /
self.newSimulation.Params['resolution'])
time = self.newSimulation.time[start_pos:len(self.newSimulation.
time)]
data_analysis.membranePotentials(
self.start_time, self.newSimulation.Params['resolution'],
self.simtime, self.potentials, self.layers_to_record,
self.labels, self.selected_cell, self.intracellular_rows,
self.intracellular_cols, self.intracellular_starting_row,
self.intracellular_starting_col, "thalamocortical_system")
# PSTHs
if self.plot_PSTH:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
start_pos = int(self.start_time /
self.newSimulation.Params['resolution'])
time = self.newSimulation.time[start_pos:len(self.newSimulation.
time)]
data_analysis.PSTH(
self.start_time, self.newSimulation.Params['resolution'],
self.simtime, self.spikes, self.layers_to_record, self.labels,
self.selected_cell, self.PSTH_rows, self.PSTH_cols,
self.PSTH_starting_row, self.PSTH_starting_col, self.trials,
self.PSTHs, self.bin_size, "thalamocortical_system")
plt.show()
def plotIntermediateResults(self):
print("\n--- Plotting results ---\n")
# Individual intracellular traces
if self.plot_intracellular:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
start_pos = int(self.start_time /
self.newSimulation.Params['resolution'])
time = self.newSimulation.time[start_pos:len(self.newSimulation.
time)]
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (0, 0))
ax.plot(
time,
self.L_cone_input[self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('Input')
# Save input stimulus
np.savetxt(
'../../data/retina/input/L_input',
self.L_cone_input[self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (0, 1))
ax.plot(
time, self.newSimulation.cone_response[
0, self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('L cones')
# Save cone response
np.savetxt(
'../../data/retina/input/L_cone',
self.newSimulation.cone_response[
0, self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (0, 2))
ax.plot(
time, self.newSimulation.cone_response[
1, self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('M cones')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (0, 3))
ax.plot(
time, self.newSimulation.cone_response[
2, self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('S cones')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (1, 0))
ax.plot(
time, self.newSimulation.L_cone_metabotropic[
self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('L cones metabotropic')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (1, 1))
ax.plot(
time, self.newSimulation.M_cone_metabotropic[
self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('M cones metabotropic')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (1, 2))
ax.plot(
time, self.newSimulation.S_cone_metabotropic[
self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('S cones metabotropic')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (1, 3))
ax.plot(
time, self.newSimulation.L_cone_ionotropic[
self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('L cones ionotropic')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (2, 0))
ax.plot(
time, self.newSimulation.M_cone_ionotropic[
self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('M cones ionotropic')
ax = plt.subplot2grid(
(self.intracellular_rows, self.intracellular_cols), (2, 1))
ax.plot(
time, self.newSimulation.S_cone_ionotropic[
self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('S cones ionotropic')
data_analysis.membranePotentials(
self.start_time, self.newSimulation.Params['resolution'],
self.simtime, self.potentials, self.layers_to_record,
self.labels, self.selected_cell, self.intracellular_rows,
self.intracellular_cols, self.intracellular_starting_row,
self.intracellular_starting_col, "retina")
# PSTHs
if self.plot_PSTH:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
start_pos = int(self.start_time /
self.newSimulation.Params['resolution'])
time = self.newSimulation.time[start_pos:len(self.newSimulation.
time)]
ax = plt.subplot2grid((self.PSTH_rows, self.PSTH_cols), (0, 0))
ax.plot(
time,
self.L_cone_input[self.selected_cell,
start_pos:len(self.newSimulation.time)])
ax.set_title('Input')
data_analysis.PSTH(
self.start_time, self.newSimulation.Params['resolution'],
self.simtime, self.spikes, self.s_layers_to_record,
self.sp_labels, self.selected_cell, self.PSTH_rows,
self.PSTH_cols, self.PSTH_starting_row, self.PSTH_starting_col,
self.trials, self.PSTHs, self.bin_size, "retina")
# Topographical plot
if self.plot_topographical:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
if self.topographical_isSpikes:
recs = self.spikes
else:
recs = self.potentials
data_analysis.topographical(
fig, self.newSimulation.Params['N'],
self.topographical_time_intervals,
self.newSimulation.Params['resolution'], self.simtime, recs,
self.top_layers_to_record, self.top_labels,
self.topographical_rows, self.topographical_cols,
self.topographical_V_mins, self.topographical_V_maxs,
self.topographical_isSpikes, self.trials, self.top_PSTHs,
self.bin_size, self.top_PSTH_index, 0)
# Video sequence
# data_analysis.videoSeq(self.newSimulation.Params['N'],self.inputIm,
# self.simtime,self.newSimulation.Params['resolution'],self.intracellular_video_step)
plt.show()
def plotResults(self):
print("\n--- Plotting results ---\n")
# Individual intracellular traces
if self.plot_intracellular and self.record_Vm:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
start_pos = int(self.start_time /
self.newSimulation.Params['resolution'])
time = self.newSimulation.time[start_pos:len(self.newSimulation.
time)]
data_analysis.membranePotentials(
self.start_time, self.newSimulation.Params['resolution'],
self.simtime, self.potentials, self.layers_to_record,
self.labels, self.selected_cell, self.intracellular_rows,
self.intracellular_cols, self.intracellular_starting_row,
self.intracellular_starting_col, "thalamocortical_system")
# PSTHs
if self.plot_PSTH:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
start_pos = int(self.start_time /
self.newSimulation.Params['resolution'])
time = self.newSimulation.time[start_pos:len(self.newSimulation.
time)]
data_analysis.PSTH(
self.start_time, self.newSimulation.Params['resolution'],
self.simtime, self.spikes, self.layers_to_record, self.labels,
self.selected_cell, self.PSTH_rows, self.PSTH_cols,
self.PSTH_starting_row, self.PSTH_starting_col, self.trials,
self.PSTHs, self.bin_size, "thalamocortical_system")
# Topographical plot
if self.plot_topographical:
fig = plt.figure()
fig.subplots_adjust(hspace=1.5)
fig.subplots_adjust(wspace=0.4)
data_analysis.topographical(
fig, self.newSimulation.Params['N_cortex'],
self.topographical_time_intervals,
self.newSimulation.Params['resolution'], self.simtime,
self.spikes, self.top_layers_to_record, self.top_labels,
self.topographical_rows, self.topographical_cols,
self.topographical_V_mins, self.topographical_V_maxs,
self.topographical_isSpikes, self.trials, self.top_PSTHs,
self.bin_size, self.top_PSTH_index, self.layer_sizes_top)
data_analysis.topographical(
fig, self.newSimulation.Params['N_cortex'],
self.topographical_time_intervals,
self.newSimulation.Params['resolution'], self.simtime,
self.spikes, self.pop_layers_to_record, self.pop_labels,
self.topographical_rows, self.topographical_cols,
self.pop_V_mins, self.pop_V_maxs, self.topographical_isSpikes,
self.trials, self.top_PSTHs, self.bin_size,
self.pop_PSTH_index, self.layer_sizes_pop, True)
plt.show()