Merge pull request #850 from satra/enh/openfmri

Enh/openfmri

Author: satra

examples/fmri_openfmri.py

@@ -121,15 +121,15 @@ def analyze_openfmri_dataset(data_dir, subject=None, model_id=None,
  Set up openfmri data specific components
  """
 
- subjects = [path.split(os.path.sep)[-1] for path in
- glob(os.path.join(data_dir, 'sub*'))]
+ subjects = sorted([path.split(os.path.sep)[-1] for path in
+  glob(os.path.join(data_dir, 'sub*'))])
 
  infosource = pe.Node(niu.IdentityInterface(fields=['subject_id',
  'model_id',
  'task_id']),
  name='infosource')
  if subject is None:
- infosource.iterables = [('subject_id', subjects[:2]),
+ infosource.iterables = [('subject_id', subjects),
  ('model_id', [model_id]),
  ('task_id', [task_id])]
  else:
@@ -200,13 +200,19 @@ def get_highpass(TR, hpcutoff):
  def get_contrasts(contrast_file, task_id, conds):
  import numpy as np
  contrast_def = np.genfromtxt(contrast_file, dtype=object)
+ if len(contrast_def.shape) == 1:
+ contrast_def = contrast_def[None, :]
  contrasts = []
  for row in contrast_def:
  if row[0] != 'task%03d' % task_id:
  continue
- con = [row[1], 'T', ['cond%03d' % i for i in range(len(conds))],
+ con = [row[1], 'T', ['cond%03d' % (i + 1) for i in range(len(conds))],
  row[2:].astype(float).tolist()]
  contrasts.append(con)
+ # add auto contrasts for each column
+ for i, cond in enumerate(conds):
+ con = [cond, 'T', ['cond%03d' % (i + 1)], [1]]
+ contrasts.append(con)
  return contrasts
 
  contrastgen = pe.Node(niu.Function(input_names=['contrast_file',