def individual_plot(ax, info_idx, names_idx):
"""
"""
ch_name = ch_names[names_idx]
for color_idx, (key, psd) in enumerate(sorted(data.items())):
if log_transformed:
curve = 10 * np.log10(psd[names_idx])
else:
curve = psd[names_idx]
ax.plot(freqs, curve, color=colors[color_idx], label=key)
title = ' '.join([name, ch_name])
ax.figure.canvas.set_window_title(title.replace(' ', '_'))
ax.figure.suptitle(title)
ax.set_title('')
ax.legend()
ax.set_xlabel('Frequency (Hz)')
ax.set_ylabel('Power ({})'.format(
get_power_unit(mne.io.pick.channel_type(info, info_idx),
log_transformed)))
plt.show()
def individual_plot(ax, info_idx, names_idx):
"""
"""
ch_name = ch_names[names_idx]
title = ' '.join([tfr_name, ch_name])
ax.figure.canvas.set_window_title(title.replace(' ', '_'))
ax.figure.suptitle(title)
ax.set_title('')
for color_idx, (key, tse) in enumerate(sorted(tses.items())):
times, tse = _crop_and_correct_to_baseline(tse, blmode, blstart,
blend, tmin, tmax,
meggie_tfr.times)
ax.plot(times, tse[names_idx], color=colors[color_idx], label=key)
ax.axhline(0, color='black')
ax.axvline(0, color='black')
ax.legend()
ax.set_xlabel('Time (s)')
ax.set_ylabel('Power ({})'.format(
get_power_unit(mne.io.pick.channel_type(info, info_idx), False)))
plt.show()
def plot_spectrum_averages(experiment, name, log_transformed=True):
"""
"""
subject = experiment.active_subject
subject_name = subject.name
spectrum = subject.spectrum.get(name)
data = spectrum.content
freqs = spectrum.freqs
ch_names = spectrum.ch_names
channel_groups = experiment.channel_groups
info = subject.get_raw().info
colors = color_cycle(len(data))
logging.getLogger('ui_logger').info('Plotting spectrum channel averages..')
averages = {}
for idx, (key, psd) in enumerate(data.items()):
data_labels, averaged_data = average_to_channel_groups(
psd, info, ch_names, channel_groups)
if not data_labels:
raise Exception('No channel groups matching the data found.')
averages[key] = data_labels, averaged_data
shape = averaged_data.shape
for ii in range(shape[0]):
fig, ax = plt.subplots()
for color_idx, key in enumerate(averages.keys()):
ax.set_xlabel('Frequency (Hz)')
ax.set_ylabel('Power ({})'.format(
get_power_unit(averages[key][0][ii][0], log_transformed)))
if log_transformed:
curve = 10 * np.log10(averages[key][1][ii])
else:
curve = averages[key][1][ii]
ax.plot(freqs, curve, color=colors[color_idx], label=key)
ax.legend()
ch_type, ch_group = averages[key][0][ii]
title = 'spectrum_{0}_{1}_{2}'.format(name, ch_type, ch_group)
fig.canvas.set_window_title(title)
fig.suptitle(title)
plt.show()
def plot_fun(ax_idx, ax):
ch_group = ch_groups[ax_idx]
ax.set_title(ch_group)
ax.set_xlabel('Time (s)')
ax.set_ylabel('Power ({})'.format(get_power_unit(ch_type, False)))
for color_idx, (key, times,
curve) in enumerate(averages[(ch_type, ch_group)]):
ax.plot(times, curve, color=colors[color_idx], label=key)
ax.axhline(0, color='black')
ax.axvline(0, color='black')
def plot_fun(ax_idx, ax):
ch_group = ch_groups[ax_idx]
ax.set_title(ch_group)
ax.set_xlabel('Frequency (Hz)')
ax.set_ylabel('Power ({})'.format(
get_power_unit(ch_type, log_transformed)))
for color_idx, (key, curve) in enumerate(averages[(ch_type,
ch_group)]):
if log_transformed:
curve = 10 * np.log10(curve)
ax.plot(freqs, curve, color=colors[color_idx])
def plot_tse_averages(experiment, subject, tfr_name, blmode, blstart, blend,
tmin, tmax, fmin, fmax):
"""
"""
meggie_tfr = subject.tfr.get(tfr_name)
times, tses = _compute_tse(meggie_tfr, fmin, fmax, tmin, tmax, blmode,
blstart, blend)
ch_names = meggie_tfr.ch_names
info = meggie_tfr.info
colors = color_cycle(len(tses))
channel_groups = experiment.channel_groups
logging.getLogger('ui_logger').info('Plotting TSE channel averages..')
averages = {}
for idx, (key, tse) in enumerate(tses.items()):
data_labels, averaged_data = average_to_channel_groups(
tse, info, ch_names, channel_groups)
if not data_labels:
raise Exception('No channel groups matching the data found.')
averages[key] = data_labels, averaged_data
shape = averaged_data.shape
for ii in range(shape[0]):
fig, ax = plt.subplots()
for color_idx, key in enumerate(averages.keys()):
ax.set_xlabel('Time (s)')
ax.set_ylabel('Power ({})'.format(
get_power_unit(averages[key][0][ii][0], False)))
ax.plot(times,
averages[key][1][ii],
color=colors[color_idx],
label=key)
ax.axhline(0)
ax.legend()
ch_type, ch_group = averages[key][0][ii]
title = 'TSE_{0}_{1}_{2}'.format(tfr_name, ch_type, ch_group)
fig.canvas.set_window_title(title)
fig.suptitle(title)
plt.show()
def individual_plot(ax, info_idx, names_idx):
"""
"""
ch_name = ch_names[names_idx]
title = 'TSE_{0}_{1}'.format(tfr_name, ch_name)
ax.figure.canvas.set_window_title(title)
ax.figure.suptitle(title)
ax.set_title('')
for color_idx, (key, tse) in enumerate(tses.items()):
ax.plot(times, tse[names_idx], color=colors[color_idx], label=key)
ax.axhline(0)
ax.axvline(0)
ax.legend()
ax.set_xlabel('Time (s)')
ax.set_ylabel('Power ({})'.format(
get_power_unit(mne.io.pick.channel_type(info, info_idx), False)))
plt.show()