deriv_path = deriv_dir / sub_string
fig_path = deriv_path / 'figures'
print(f'Generating report for task-{task} data from {sub_string}')
# Initialize the report
# Make the report object
report = Report(subject=sub_string,
title=f'{sub_string}: task-{task} report',
image_format='png', verbose=True, projs=False,
subjects_dir=None)
# Behavioral Section
# Plot behavioral data
behav_fig_file = fig_path / f'{sub_string}_task-{task}_beh_performance.png'
report.add_images_to_section(behav_fig_file,
captions='Behavior: Performance Summary',
section='Behavior')
# EEG Section
# Load the Raw data
raw_fif_file = deriv_path / \
f'{sub_string}_task-{task}_ref-FCz_desc-resamp_raw.fif.gz'
raw = mne.io.read_raw_fif(raw_fif_file, preload=True)
# Load the Epochs
epoch_fif_file = deriv_path / \
f'{sub_string}_task-{task}_ref-mastoids_desc-cleaned_epo.fif.gz'
epochs = mne.read_epochs(epoch_fif_file, preload=True)
# Load Epochs json
json_file = deriv_path / \
