Merge pull request #151 from rwblair/issue147

[WIP] Issue147

fmriprep/interfaces/bids.py

@@ -7,17 +7,18 @@
 # @Date:   2016-06-03 09:35:13
 # @Last Modified by:   oesteban
 # @Last Modified time: 2016-08-17 15:32:43
+from lockfile import LockFile
 import os
 import os.path as op
-from shutil import copy
+import pkg_resources as pkgr
 import re
+from shutil import copy
 import simplejson as json
-import pkg_resources as pkgr
-from lockfile import LockFile
 
 from nipype import logging
 from nipype.interfaces.base import (traits, isdefined, TraitedSpec, BaseInterface,
                                     BaseInterfaceInputSpec, File, InputMultiPath, OutputMultiPath)
+
 from fmriprep.utils.misc import collect_bids_data
 
 LOGGER = logging.getLogger('interface')
@@ -27,10 +28,9 @@ class FileNotFoundError(IOError):
 
 
 class BIDSDataGrabberInputSpec(BaseInterfaceInputSpec):
-    bids_root = traits.Directory(exists=True, mandatory=True,
-                                 desc='root folder of the BIDS dataset')
+    subject_data = traits.DictStrAny()
     subject_id = traits.Str()
-    spec = File(exists=True, desc='grabbids specification file')
+
 
 class BIDSDataGrabberOutputSpec(TraitedSpec):
     out_dict = traits.Dict(desc='output data structure')
@@ -49,31 +49,25 @@ def __init__(self, **inputs):
         super(BIDSDataGrabber, self).__init__(**inputs)
 
     def _run_interface(self, runtime):
-        if isdefined(self.inputs.spec):
-            spec = self.inputs.spec
-        else:
-            spec = pkgr.resource_filename('fmriprep', 'data/bids.json')
-
-        bids_dict = collect_bids_data(
-            self.inputs.bids_root, self.inputs.subject_id, spec=spec)
+        bids_dict = self.inputs.subject_data
 
         self._results['out_dict'] = bids_dict
 
         self._results['t1w'] = bids_dict['t1w']
         if not bids_dict['t1w']:
-            raise FileNotFoundError('No T1w images found for subject sub-{}, bids_root={}'.format(
-                self.inputs.subject_id, self.inputs.bids_root))
+            raise FileNotFoundError('No T1w images found for subject sub-{}'.format(
+                self.inputs.subject_id))
 
         self._results['func'] = bids_dict['func']
         if not bids_dict['func']:
-            raise FileNotFoundError('No functional images found for subject sub-{}, bids_root={}'.format(
-                self.inputs.subject_id, self.inputs.bids_root))
+            raise FileNotFoundError('No functional images found for subject sub-{}'.format(
+                self.inputs.subject_id))
 
         for imtype in ['fmap', 'sbref']:
             self._results[imtype] = bids_dict[imtype]
             if not bids_dict[imtype]:
-                LOGGER.warn('No \'{}\' images found for sub-{} in BIDS dataset ({})'.format(
-                    imtype, self.inputs.subject_id, self.inputs.bids_root))
+                LOGGER.warn('No \'{}\' images found for sub-{}'.format(
+                    imtype, self.inputs.subject_id))
 
 
         return runtime

fmriprep/run_workflow.py

@@ -29,7 +29,7 @@ def main():
     from nipype.pipeline import engine as pe
     from fmriprep import __version__
     from fmriprep.workflows import base as fwb
-
+    from fmriprep.workflows.base import base_workflow_enumerator
     parser = ArgumentParser(description='fMRI Preprocessing workflow',
                             formatter_class=RawTextHelpFormatter)
 
@@ -62,7 +62,7 @@ def main():
                          help='nipype plugin configuration file')
     g_input.add_argument('-w', '--work-dir', action='store',
                            default=op.join(os.getcwd(), 'work'))
-    g_input.add_argument('-t', '--workflow-type', default='ds005', required=True,
+    g_input.add_argument('-t', '--workflow-type', default='ds005', required=False,
                          action='store', choices=['ds005', 'ds054', 'HPC', 'spiral'],
                          help='workflow type, a monkeypatch while it is not automatically identified')
 
@@ -150,8 +150,7 @@ def main():
     logger.info('Subject list: %s', ', '.join(subject_list))
 
     # Build main workflow and run
-    workflow_generator = getattr(fwb, 'wf_{}_type'.format(opts.workflow_type))
-    preproc_wf = workflow_generator(subject_list, settings=settings)
+    preproc_wf = base_workflow_enumerator(subject_list, settings=settings)
     preproc_wf.base_dir = settings['work_dir']
     preproc_wf.run(**plugin_settings)
 

fmriprep/utils/misc.py

@@ -5,7 +5,7 @@
 import os
 import re
 
-from grabbit import Layout
+from bids.grabbids import BIDSLayout
 
 INPUTS_SPEC = {'fieldmaps': [], 'func': [], 't1': [], 'sbref': []}
 
@@ -23,6 +23,7 @@ def is_fieldmap_file(string):
             is_fieldmap_file = True
     return is_fieldmap_file
 
+
 fieldmap_suffixes = {
     'phasediff': r"phasediff[0-9]*\.nii(\.gz)?",
     'magnitude': r"magnitude[0-9]*\.nii(\.gz)?",
@@ -32,15 +33,12 @@ def is_fieldmap_file(string):
 }
 
 
-def collect_bids_data(dataset, subject, spec=None, session=None, run=None):
+def collect_bids_data(dataset, subject, session=None, run=None):
     subject = str(subject)
-    if not subject.startswith('sub-'):
-        subject = 'sub-{}'.format(subject)
-
-    if spec is None:
-        raise RuntimeError('A spec file should be specified')
+    if subject.startswith('sub-'):
+        subject = subject[4:]
 
-    layout = Layout(dataset, config=spec)
+    layout = BIDSLayout(dataset)
 
     if session:
         session_list = [session]
@@ -75,7 +73,10 @@ def collect_bids_data(dataset, subject, spec=None, session=None, run=None):
     imaging_data['t1w'] = t1_files
     sbref_files = [x.filename for x in layout.get(**queries['sbref'])]
     imaging_data['sbref'] = sbref_files
+    epi_files = [x.filename for x in layout.get(**queries['epi'])]
+    imaging_data['func'] = epi_files
 
+    '''
     loop_on = ['session', 'run', 'acquisition', 'task']
     get_kwargs = {}
 
@@ -95,6 +96,8 @@ def collect_bids_data(dataset, subject, spec=None, session=None, run=None):
                      in layout.get(**dict(dict(elem), **queries['epi']))]
         if epi_files:
             imaging_data['func'] += epi_files
+    '''
+
     return imaging_data
 
 

fmriprep/workflows/base.py

@@ -7,22 +7,41 @@
 
 @author: craigmoodie
 """
-
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
 from nipype.interfaces import fsl
 from nipype.interfaces import freesurfer as fs
 from nipype.interfaces import io as nio
 
 from fmriprep.interfaces import BIDSDataGrabber
+from fmriprep.utils.misc import collect_bids_data
 from fmriprep.workflows.anatomical import t1w_preprocessing
 from fmriprep.workflows.sbref import sbref_preprocess, sbref_t1_registration
 from fmriprep.workflows.fieldmap import phase_diff_and_magnitudes
 from fmriprep.workflows.epi import (
     epi_unwarp, epi_hmc, epi_sbref_registration,
     epi_mean_t1_registration, epi_mni_transformation)
 
-def wf_ds054_type(subject_list, name='fMRI_prep', settings=None):
+def base_workflow_enumerator(subject_list, settings):
+    workflow = pe.Workflow(name='workflow_enumerator')
+    generated_list = []
+    for subject in subject_list:
+        generated_workflow = base_workflow_generator(subject, settings)
+        if generated_workflow:
+            generated_list.append(generated_workflow)
+    workflow.add_nodes(generated_list)
+
+    return workflow
+
+def base_workflow_generator(subject_id, settings):
+    subject_data = collect_bids_data(settings['bids_root'], subject_id)
+    if (subject_data['t1w'] != [] and subject_data['sbref'] != []):
+        return wf_ds054_type(subject_data, settings, name=subject_id)
+    if (subject_data['t1w'] != [] and subject_data['sbref'] == []):
+        return wf_ds005_type(subject_data, settings, name=subject_id)
+    return None
+
+def wf_ds054_type(subject_data, settings, name='fMRI_prep'):
     """
     The main fmri preprocessing workflow, for the ds054-type of data:
 
@@ -39,12 +58,11 @@ def wf_ds054_type(subject_list, name='fMRI_prep', settings=None):
 
     workflow = pe.Workflow(name=name)
 
-    inputnode = pe.Node(niu.IdentityInterface(fields=['subject_id']),
-                        name='inputnode')
-    inputnode.iterables = [('subject_id', subject_list)]
+    #  inputnode = pe.Node(niu.IdentityInterface(fields=['subject_id']),
+    #                    name='inputnode')
+    #  inputnode.iterables = [('subject_id', subject_list)]
 
-    bidssrc = pe.Node(BIDSDataGrabber(bids_root=settings['bids_root']),
-                      name='BIDSDatasource')
+    bidssrc = pe.Node(BIDSDataGrabber(subject_data=subject_data), name='BIDSDatasource')
 
     # Preprocessing of T1w (includes registration to MNI)
     t1w_pre = t1w_preprocessing(settings=settings)
@@ -60,6 +78,7 @@ def wf_ds054_type(subject_list, name='fMRI_prep', settings=None):
 
     # HMC on the EPI
     hmcwf = epi_hmc(settings=settings)
+    hmcwf.get_node('inputnode').iterables = ('epi', subject_data['func'])
 
     # EPI to SBRef
     epi2sbref = epi_sbref_registration()
@@ -68,7 +87,6 @@ def wf_ds054_type(subject_list, name='fMRI_prep', settings=None):
     epiunwarp_wf = epi_unwarp(settings=settings)
 
     workflow.connect([
-        (inputnode, bidssrc, [('subject_id', 'subject_id')]),
         (bidssrc, t1w_pre, [('t1w', 'inputnode.t1w')]),
         (bidssrc, fmap_est, [('fmap', 'inputnode.input_images')]),
         (bidssrc, sbref_pre, [('sbref', 'inputnode.sbref')]),
@@ -79,19 +97,18 @@ def wf_ds054_type(subject_list, name='fMRI_prep', settings=None):
         (t1w_pre, sbref_t1, [
             ('outputnode.t1_brain', 'inputnode.t1_brain'),
             ('outputnode.t1_seg', 'inputnode.t1_seg')]),
-        (bidssrc, hmcwf, [(('func', _first), 'inputnode.epi')]),
         (sbref_pre, epi2sbref, [('outputnode.sbref_unwarped', 'inputnode.sbref_brain')]),
         (hmcwf, epi2sbref, [('outputnode.epi_brain', 'inputnode.epi_brain')]),
 
-        (bidssrc, epiunwarp_wf, [(('func', _first), 'inputnode.epi')]),
+        (hmcwf, epiunwarp_wf, [('inputnode.epi', 'inputnode.epi')]),
         (fmap_est, epiunwarp_wf, [('outputnode.fmap', 'inputnode.fmap'),
                                   ('outputnode.fmap_mask', 'inputnode.fmap_mask'),
                                   ('outputnode.fmap_ref', 'inputnode.fmap_ref')])
     ])
     return workflow
 
 
-def wf_ds005_type(subject_list, name='fMRI_prep', settings=None):
+def wf_ds005_type(subject_data, settings, name='fMRI_prep'):
     """
     The main fmri preprocessing workflow, for the ds005-type of data:
 
@@ -108,35 +125,35 @@ def wf_ds005_type(subject_list, name='fMRI_prep', settings=None):
 
     workflow = pe.Workflow(name=name)
 
-    inputnode = pe.Node(niu.IdentityInterface(fields=['subject_id']),
-                        name='inputnode')
-    inputnode.iterables = [('subject_id', subject_list)]
+    #  inputnode = pe.Node(niu.IdentityInterface(fields=['subject_id']),
+    #                      name='inputnode')
+    #  inputnode.iterables = [('subject_id', subject_list)]
 
-    bidssrc = pe.Node(BIDSDataGrabber(bids_root=settings['bids_root']),
+    bidssrc = pe.Node(BIDSDataGrabber(subject_data=subject_data),
                       name='BIDSDatasource')
 
     # Preprocessing of T1w (includes registration to MNI)
     t1w_pre = t1w_preprocessing(settings=settings)
 
     # HMC on the EPI
     hmcwf = epi_hmc(settings=settings)
+    hmcwf.get_node('inputnode').iterables = ('epi', subject_data['func'])
 
     # mean EPI registration to T1w
     epi_2_t1 = epi_mean_t1_registration(settings=settings)
 
     # Apply transforms in 1 shot
     epi_mni_trans_wf = epi_mni_transformation(settings=settings)
 
+
     workflow.connect([
-        (inputnode, bidssrc, [('subject_id', 'subject_id')]),
         (bidssrc, t1w_pre, [('t1w', 'inputnode.t1w')]),
-        (bidssrc, hmcwf, [(('func', _first), 'inputnode.epi')]),
-        (bidssrc, epi_2_t1, [(('func', _first), 'inputnode.epi')]),
+        (hmcwf, epi_2_t1, [('inputnode.epi', 'inputnode.epi')]),
 
         (hmcwf, epi_2_t1, [('outputnode.epi_mean', 'inputnode.epi_mean')]),
         (t1w_pre, epi_2_t1, [('outputnode.t1_brain', 'inputnode.t1_brain'),
                              ('outputnode.t1_seg', 'inputnode.t1_seg')]),
-        (bidssrc, epi_mni_trans_wf, [(('func', _first), 'inputnode.epi')]),
+        (hmcwf, epi_mni_trans_wf, [('inputnode.epi', 'inputnode.epi')]),
         (epi_2_t1, epi_mni_trans_wf, [('outputnode.mat_epi_to_t1', 'inputnode.mat_epi_to_t1')]),
         (hmcwf, epi_mni_trans_wf, [('outputnode.xforms', 'inputnode.hmc_xforms'),
                                    ('outputnode.epi_mask', 'inputnode.epi_mask')]),
@@ -145,6 +162,7 @@ def wf_ds005_type(subject_list, name='fMRI_prep', settings=None):
                                       'inputnode.t1_2_mni_forward_transform')])
 
     ])
+
     return workflow
 
 def _first(inlist):

requirements.txt

@@ -1,4 +1,5 @@
 -e git+https://github.com/nipy/nipype.git@master#egg=nipype
+-e git+https://github.com/incf/pybids.git@master#egg=pybids
 numpy
 lockfile
 future
@@ -8,4 +9,3 @@ nilearn
 sklearn
 nibabel
 niworkflows>=0.0.3a3
-grabbit

setup.py

@@ -19,7 +19,7 @@ def main():
     # Read vars from info file
     module_file =os.path.join(this_path, 'fmriprep', 'info.py')
     with open(module_file) as fvars:
-        exec(compile(fvars.read(), module_file, 'exec'))
+       exec(compile(fvars.read(), module_file, 'exec'))
 
     REQ_LINKS = []
     with open('requirements.txt', 'r') as rfile:

test/utils/test_misc.py

@@ -32,10 +32,7 @@ def setUp(cls):
 
         cls.imaging_data = {
             cls.subject_id: misc.collect_bids_data(os.path.join(cls.fake_ds_location),
-                                                   cls.subject_id,
-                                                   spec=pkgr.resource_filename(
-                                                       'fmriprep',
-                                                       'data/bids.json'))
+                                                   cls.subject_id)
         }
 
     def test_collect_bids_data(self):
@@ -72,5 +69,5 @@ def assert_fieldmap_files_exist(self, pattern, key):
     def assert_key_exists(self, template, key):
         for subject in self.imaging_data:
             self.assertIn(template.format(subject=subject),
-                          self.imaging_data[subject][key])
+                          '\n'.join(self.imaging_data[subject][key]))