def test_ward_spatial_real_data(self): from pyhrf.glm import glm_nipy_from_files fn = 'subj0_parcellation.nii.gz' mask_file = pyhrf.get_data_file_name(fn) bold = 'subj0_bold_session0.nii.gz' bold_file = pyhrf.get_data_file_name(bold) paradigm_csv_file = pyhrf.get_data_file_name('paradigm_loc_av.csv') output_dir = self.tmp_dir output_file = op.join(output_dir, 'parcellation_output_test_real_data.nii') tr = 2.4 bet = glm_nipy_from_files(bold_file, tr, paradigm_csv_file, output_dir, mask_file, session=0, contrasts=None, hrf_model='Canonical', drift_model='Cosine', hfcut=128, residuals_model='spherical', fit_method='ols', fir_delays=[0])[0] logger.info('betas_files: %s', ' '.join(bet)) cmd = 'pyhrf_parcellate_glm -m %s %s -o %s -v %d -n %d '\ '-t ward_spatial ' \ % (mask_file, ' '.join(bet), output_file, logger.getEffectiveLevel(), 10) if os.system(cmd) != 0: raise Exception('"' + cmd + '" did not execute correctly') logger.info('cmd: %s', cmd)
def test_glm_with_files(self): output_dir = self.tmp_dir bold_name = 'subj0_bold_session0.nii.gz' bold_file = pyhrf.get_data_file_name(bold_name) tr = 2.4 paradigm_name = 'paradigm_loc_av.csv' paradigm_file = pyhrf.get_data_file_name(paradigm_name) mask_name = 'subj0_parcellation.nii.gz' mask_file = pyhrf.get_data_file_name(mask_name) from pyhrf.glm import glm_nipy_from_files glm_nipy_from_files(bold_file, tr, paradigm_file, output_dir, mask_file) self.assertTrue(op.exists(output_dir))