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def _visualize(self, data, out_name):
contrast_matrix = pd.DataFrame({c['name']: c['weights'][0]
for c in self.inputs.contrast_info},
index=data.columns)
contrast_matrix.fillna(value=0, inplace=True)
if 'constant' in contrast_matrix.index:
contrast_matrix = contrast_matrix.drop(index='constant')
plot_and_save(out_name, plot_contrast_matrix, contrast_matrix,
ornt=self.inputs.orientation)
out_ents = reduce(dict_intersection,
map(fl_layout.parse_file_entities, data))
out_ents['type'] = 'stat'
contrasts_ents = out_ents.copy()
contrasts_ents['type'] = 'contrasts'
contrasts_ents.pop('contrast', None)
contrasts_ents.pop('space', None)
contrasts_fname = op.join(
deriv_dir,
fl_layout.build_path(contrasts_ents, strict=True))
# Make parent results directory
os.makedirs(os.path.dirname(contrasts_fname), exist_ok=True)
plot_and_save(contrasts_fname, plot_contrast_matrix, contrasts,
ornt='horizontal')
job_desc = {
'ents': out_ents,
'subject_id': ents.get('subject'),
'dataset': analysis.layout.root,
'model_name': analysis.model['name'],
'contrasts_svg': contrasts_fname,
}
for contrast in contrasts:
out_ents['contrast'] = snake_to_camel(contrast)
stat_fname = op.join(deriv_dir,
fl_layout.build_path(out_ents, strict=True))