# Plot
tmp_epochs = ic_rm_epochs.copy()[these_epochs]
tmp_colors = [epoch_colors[x] for x in these_epochs]
figs.append(
tmp_epochs.plot(n_channels=66,
n_epochs=epochs_per_plot,
scalings=dict(eeg=100e-6, eog=200e-6),
show=False,
epoch_colors=tmp_colors,
picks=['eeg', 'eog']))
print(f'Figs completed: {len(figs)}')
# Add slidebar figs
report.add_slider_to_section(figs,
captions=captions,
section='EEG',
title='EEG: Cleaned Epochs',
scale=2)
plt.close()
# ICA Section
# Load ICA epochs
ica_epoch_fif_file = deriv_path / \
f'{sub}_task-{task}_ref-FCz_desc-ica_epo.fif.gz'
ica_epochs = mne.read_epochs(ica_epoch_fif_file, preload=True)
# Load ICA
ica_file = deriv_path / f'{sub}_task-{task}_ref-FCz_desc-ica_ica.fif.gz'
ica = read_ica(ica_file)
# Plot ICA Component maps
# Update caption
captions.append(f'Epochs {these_epochs[0]}-{these_epochs[-1]}')
# Plot
tmp_epochs = ic_rm_epochs.copy()[these_epochs]
tmp_colors = [epoch_colors[x] for x in these_epochs]
figs.append(
tmp_epochs.plot(n_channels=66, n_epochs=epochs_per_plot,
scalings=dict(eeg=100e-6, eog=200e-6),
show=False, epoch_colors=tmp_colors,
picks=['eeg', 'eog'])
)
print(f'Figs completed: {len(figs)}')
# Add slidebar figs
report.add_slider_to_section(figs, captions=captions, section='EEG',
title='EEG: Cleaned Epochs', scale=2)
plt.close()
# ICA Section
# Load ICA epochs
ica_epoch_fif_file = deriv_path / \
f'{sub_string}_task-{task}_ref-FCz_desc-ica_epo.fif.gz'
ica_epochs = mne.read_epochs(ica_epoch_fif_file, preload=True)
# Load ICA
ica_file = deriv_path / \
f'{sub_string}_task-{task}_ref-FCz_desc-ica_ica.fif.gz'
ica = read_ica(ica_file)
# Plot ICA Component maps
figs = ica.plot_components(reject=None, psd_args=dict(fmax=70), show=False)
# Plot
tmp_epochs = ic_rm_epochs.copy()[these_epochs]
tmp_colors = [epoch_colors[x] for x in these_epochs]
figs.append(
tmp_epochs.plot(n_channels=66,
n_epochs=epochs_per_plot,
scalings=dict(eeg=100e-6, eog=200e-6),
show=False,
epoch_colors=tmp_colors,
picks=['eeg', 'eog']))
print(f'Figs completed: {len(figs)}')
# Add slidebar figs
report.add_slider_to_section(figs,
captions=captions,
section='EEG',
title='EEG: Cleaned Epochs',
scale=2)
plt.close()
# ICA Section
# Load ICA epochs
ica_epoch_fif_file = deriv_path / \
f'{sub}_task-{task}_ref-FCz_desc-ica_epo.fif.gz'
ica_epochs = mne.read_epochs(ica_epoch_fif_file, preload=True)
# Load ICA
ica_file = deriv_path / f'{sub}_task-{task}_ref-FCz_desc-ica_ica.fif.gz'
ica = read_ica(ica_file)
# Plot ICA Component maps
