def plot_speed_histogram(raw_position_data, processed_position_data, prm):
print('plotting speed histogram...')
save_path = prm.get_output_path() + '/Figures/behaviour'
if os.path.exists(save_path) is False:
os.makedirs(save_path)
speed_histogram = plt.figure(figsize=(6, 4))
ax = speed_histogram.add_subplot(1, 1, 1) # specify (nrows, ncols, axnum)
position_bins = np.array(
processed_position_data["position_bins"].dropna(axis=0))
average_speed = np.array(
processed_position_data["binned_speed_ms"].dropna(axis=0))
ax.plot(position_bins, average_speed, '-', color='Black')
plt.ylabel('Speed (cm/s)', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
x_max = max(processed_position_data.binned_speed_ms) + 0.5
plot_utility.style_vr_plot(ax, x_max)
plt.subplots_adjust(hspace=.35,
wspace=.35,
bottom=0.2,
left=0.12,
right=0.87,
top=0.92)
plt.savefig(prm.get_output_path() + '/Figures/behaviour/speed_histogram' +
'.png',
dpi=200)
plt.close()
def plot_convolved_rates_in_time(spike_data, prm):
print('plotting spike rastas...')
save_path = prm.get_output_path() + '/Figures/ConvolvedRates_InTime'
if os.path.exists(save_path) is False:
os.makedirs(save_path)
for cluster_index in range(len(spike_data)):
cluster_index = spike_data.cluster_id.values[cluster_index] - 1
spikes_on_track = plt.figure(figsize=(4, 5))
ax = spikes_on_track.add_subplot(1, 1,
1) # specify (nrows, ncols, axnum)
firing_rate = spike_data.loc[cluster_index].spike_rate_in_time
speed = spike_data.loc[cluster_index].speed_rate_in_time
x_max = np.max(firing_rate)
ax.plot(firing_rate, speed, '|', color='Black', markersize=4)
plt.ylabel('Firing rate (Hz)', fontsize=12, labelpad=10)
plt.xlabel('Speed (cm/sec)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
plot_utility.style_vr_plot(ax, x_max)
plt.locator_params(axis='y', nbins=4)
try:
plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)
except ValueError:
continue
plt.savefig(save_path + '/' + spike_data.session_id[cluster_index] +
'_rate_versus_SPEED_' + str(cluster_index + 1) + '.png',
dpi=200)
plt.close()
spikes_on_track = plt.figure(figsize=(4, 5))
ax = spikes_on_track.add_subplot(1, 1,
1) # specify (nrows, ncols, axnum)
position = spike_data.loc[cluster_index].location_rate_in_time
ax.plot(firing_rate, position, '|', color='Black', markersize=4)
plt.ylabel('Firing rate (Hz)', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
plot_utility.style_vr_plot(ax, x_max)
plt.locator_params(axis='y', nbins=4)
try:
plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)
except ValueError:
continue
plt.savefig(save_path + '/' + spike_data.session_id[cluster_index] +
'_rate_versus_POSITION_' + str(cluster_index + 1) + '.png',
dpi=200)
plt.close()
def plot_gc_firing_rate_maps(spike_data, prm, prefix):
print('I am plotting firing rate maps...')
save_path = prm.get_output_path() + '/Figures/spike_rate'
if os.path.exists(save_path) is False:
os.makedirs(save_path)
for cluster_index in range(len(spike_data)):
cluster_index = spike_data.cluster_id.values[cluster_index] - 1
avg_spikes_on_track = plt.figure(figsize=(6, 4))
avg_beaconed_spike_rate, avg_nonbeaconed_spike_rate, avg_probe_spike_rate = PostSorting.vr_extract_data.extract_gc_firing_rate_data(
spike_data, cluster_index)
ax = avg_spikes_on_track.add_subplot(
1, 1, 1) # specify (nrows, ncols, axnum)
ax.plot(avg_beaconed_spike_rate, '-', color='Black')
ax.plot(avg_nonbeaconed_spike_rate, '-', color='Red')
ax.plot(avg_probe_spike_rate, '-', color='Blue')
ax.locator_params(axis='x', nbins=3)
ax.set_xticklabels(['0', '100', '200'])
plt.ylabel('Spike rate (hz)', fontsize=14, labelpad=10)
plt.xlabel('Location (cm)', fontsize=14, labelpad=10)
plt.xlim(0, 200)
nb_x_max = np.nanmax(avg_beaconed_spike_rate)
b_x_max = np.nanmax(avg_nonbeaconed_spike_rate)
p_x_max = np.nanmax(avg_probe_spike_rate)
if b_x_max > nb_x_max and b_x_max > p_x_max:
plot_utility.style_vr_plot(ax, b_x_max)
elif b_x_max < nb_x_max and b_x_max > p_x_max:
plot_utility.style_vr_plot(ax, nb_x_max)
elif b_x_max > nb_x_max and b_x_max < p_x_max:
plot_utility.style_vr_plot(ax, p_x_max)
plot_utility.style_track_plot(ax, 200)
plt.subplots_adjust(hspace=.35,
wspace=.35,
bottom=0.15,
left=0.12,
right=0.87,
top=0.92)
plt.savefig(save_path + '/' + spike_data.session_id[cluster_index] +
'_rate_map_Cluster_' + str(cluster_index + 1) + '.png',
dpi=200)
plt.close()
def plot_stops_on_track(raw_position_data, processed_position_data, prm):
print('I am plotting stop rasta...')
save_path = prm.get_output_path() + '/Figures/behaviour'
if os.path.exists(save_path) is False:
os.makedirs(save_path)
stops_on_track = plt.figure(figsize=(6, 6))
ax = stops_on_track.add_subplot(1, 1, 1) # specify (nrows, ncols, axnum)
beaconed, nonbeaconed, probe = split_stop_data_by_trial_type(
processed_position_data)
ax.plot(beaconed[:, 0], beaconed[:, 1], 'o', color='0.5', markersize=2)
ax.plot(nonbeaconed[:, 0],
nonbeaconed[:, 1],
'o',
color='red',
markersize=2)
ax.plot(probe[:, 0], probe[:, 1], 'o', color='blue', markersize=2)
ax.plot(processed_position_data.rewarded_stop_locations,
processed_position_data.rewarded_trials,
'>',
color='Red',
markersize=3)
plt.ylabel('Stops on trials', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
#plt.xlim(min(spatial_data.position_bins),max(spatial_data.position_bins))
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
x_max = max(raw_position_data.trial_number) + 0.5
plot_utility.style_vr_plot(ax, x_max)
plt.subplots_adjust(hspace=.35,
wspace=.35,
bottom=0.2,
left=0.12,
right=0.87,
top=0.92)
plt.savefig(prm.get_output_path() + '/Figures/behaviour/stop_raster' +
'.png',
dpi=200)
plt.close()
def plot_spikes_on_track(spike_data, raw_position_data,
processed_position_data, prm, prefix):
print('plotting spike rastas...')
save_path = prm.get_output_path() + '/Figures/spike_trajectories'
if os.path.exists(save_path) is False:
os.makedirs(save_path)
rewarded_locations = np.array(
processed_position_data['rewarded_stop_locations'].dropna(axis=0)) #
rewarded_trials = np.array(
processed_position_data['rewarded_trials'].dropna(axis=0))
for cluster_index in range(len(spike_data)):
cluster_index = spike_data.cluster_id.values[cluster_index] - 1
x_max = max(
np.array(spike_data.at[cluster_index,
'beaconed_trial_number'])) + 1
spikes_on_track = plt.figure(figsize=(4, (x_max / 32)))
ax = spikes_on_track.add_subplot(1, 1,
1) # specify (nrows, ncols, axnum)
#uncomment if you want to plot stops
#ax.plot(beaconed[:,0], beaconed[:,1], 'o', color='LimeGreen', markersize=2, alpha=0.5)
#ax.plot(nonbeaconed[:,0], nonbeaconed[:,1], 'o', color='LimeGreen', markersize=2, alpha=0.5)
#ax.plot(probe[:,0], probe[:,1], 'o', color='LimeGreen', markersize=2, alpha=0.5)
ax.plot(spike_data.loc[cluster_index].beaconed_position_cm,
spike_data.loc[cluster_index].beaconed_trial_number,
'|',
color='Black',
markersize=4)
ax.plot(spike_data.loc[cluster_index].nonbeaconed_position_cm,
spike_data.loc[cluster_index].nonbeaconed_trial_number,
'|',
color='Red',
markersize=4)
ax.plot(spike_data.loc[cluster_index].probe_position_cm,
spike_data.loc[cluster_index].probe_trial_number,
'|',
color='Blue',
markersize=4)
ax.plot(rewarded_locations,
rewarded_trials,
'>',
color='Red',
markersize=3)
plt.ylabel('Spikes on trials', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
plot_utility.style_vr_plot(ax, x_max)
plt.locator_params(axis='y', nbins=4)
try:
plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)
except ValueError:
continue
plt.savefig(save_path + '/' + spike_data.session_id[cluster_index] +
'_track_firing_Cluster_' + str(cluster_index + 1) + '.png',
dpi=200)
plt.close()
def plot_combined_behaviour(raw_position_data, processed_position_data, prm):
print('making combined behaviour plot...')
save_path = prm.get_local_recording_folder_path() + '/Figures/behaviour'
if os.path.exists(save_path) is False:
os.makedirs(save_path)
combined = plt.figure(figsize=(6, 9))
ax = combined.add_subplot(3, 1, 1) # specify (nrows, ncols, axnum)
beaconed, nonbeaconed, probe = split_stop_data_by_trial_type(
processed_position_data)
ax.plot(beaconed[:, 0], beaconed[:, 1], 'o', color='0.5', markersize=2)
ax.plot(nonbeaconed[:, 0],
nonbeaconed[:, 1],
'o',
color='red',
markersize=2)
ax.plot(probe[:, 0], probe[:, 1], 'o', color='blue', markersize=2)
plt.ylabel('Stops on trials', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
x_max = max(raw_position_data.trial_number) + 0.5
plot_utility.style_vr_plot(ax, x_max)
ax = combined.add_subplot(3, 1, 2) # specify (nrows, ncols, axnum)
position_bins = np.array(
processed_position_data["position_bins"].dropna(axis=0))
average_stops = np.array(
processed_position_data["average_stops"].dropna(axis=0))
ax.plot(position_bins, average_stops, '-', color='Black')
plt.ylabel('Stops (cm/s)', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
x_max = max(processed_position_data.average_stops) + 0.5
plot_utility.style_vr_plot(ax, x_max)
ax = combined.add_subplot(3, 1, 3) # specify (nrows, ncols, axnum)
position_bins = np.array(
processed_position_data["position_bins"].dropna(axis=0))
average_speed = np.array(
processed_position_data["binned_speed_ms"].dropna(axis=0))
ax.plot(position_bins, average_speed, '-', color='Black')
plt.ylabel('Speed (cm/s)', fontsize=12, labelpad=10)
plt.xlabel('Location (cm)', fontsize=12, labelpad=10)
plt.xlim(0, 200)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
plot_utility.style_track_plot(ax, 200)
x_max = max(processed_position_data.binned_speed_ms) + 0.5
plot_utility.style_vr_plot(ax, x_max)
plt.subplots_adjust(hspace=.3,
wspace=.3,
bottom=0.06,
left=0.12,
right=0.87,
top=0.92)
plt.savefig(prm.get_local_recording_folder_path() +
'/Figures/behaviour/combined_behaviour' + '.png',
dpi=200)
plt.close()