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))
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))