Merge pull request #333 from chrisfilo/fix/csv

Fix/csv

Author: chrisgorgo

examples/dmri_connectivity.py

@@ -551,7 +551,7 @@ def select_aparc_annot(list_of_files):
 mapping.connect([(gpickledNetworks, CFFConverter,[("out","gpickled_networks")])])
 mapping.connect([(niftiVolumes, CFFConverter,[("out","nifti_volumes")])])
 mapping.connect([(fiberDataArrays, CFFConverter,[("out","data_files")])])
-mapping.connect([(camino2trackvis, CFFConverter,[("trackvis","tract_files")])])
+mapping.connect([(creatematrix, CFFConverter,[("filtered_tractographies","tract_files")])])
 mapping.connect([(inputnode, CFFConverter,[("subject_id","title")])])
 
 """

examples/dmri_connectivity_advanced.py

@@ -268,7 +268,7 @@
 
 probCSDstreamtrack = pe.Node(interface=mrtrix.ProbabilisticSphericallyDeconvolutedStreamlineTrack(),name='probCSDstreamtrack')
 probCSDstreamtrack.inputs.inputmodel = 'SD_PROB'
-probCSDstreamtrack.inputs.maximum_number_of_tracks = 150000
+probCSDstreamtrack.inputs.desired_number_of_tracks = 150000
 tracks2prob = pe.Node(interface=mrtrix.Tracks2Prob(),name='tracks2prob')
 tracks2prob.inputs.colour = True
 MRconvert_tracks2prob = MRconvert_fa.clone(name='MRconvert_tracks2prob')
@@ -542,7 +542,7 @@
 mapping.connect([(creatematrix, CFFConverter,[("matrix_files","gpickled_networks")])])
 mapping.connect([(niftiVolumes, CFFConverter,[("out","nifti_volumes")])])
 mapping.connect([(fiberDataArrays, CFFConverter,[("out","data_files")])])
-mapping.connect([(creatematrix, CFFConverter,[("filtered_tractography","tract_files")])])
+mapping.connect([(creatematrix, CFFConverter,[("filtered_tractographies","tract_files")])])
 mapping.connect([(inputnode, CFFConverter,[("subject_id","title")])])
 
 """

nipype/interfaces/cmtk/cmtk.py

@@ -415,6 +415,7 @@ class CreateMatrixOutputSpec(TraitedSpec):
     fiber_labels_noorphans = File(desc='Saved Numpy array with the labels for each non-orphan fiber', exists=True)
     filtered_tractography = File(desc='TrackVis file containing only those fibers originate in one and terminate in another region', exists=True)
     filtered_tractography_by_intersections = File(desc='TrackVis file containing all fibers which connect two regions', exists=True)
+    filtered_tractographies = OutputMultiPath(File(desc='TrackVis file containing only those fibers originate in one and terminate in another region', exists=True))
 
 class CreateMatrix(BaseInterface):
     """
@@ -535,6 +536,7 @@ def _list_outputs(self):
 
         _, name , _ = split_filename(self.inputs.tract_file)
         outputs['filtered_tractography'] = op.abspath(name + '_streamline_final.trk')
+        outputs['filtered_tractographies'] = [outputs['filtered_tractography'], outputs['filtered_tractography_by_intersections']]
         return outputs
 
     def _gen_outfilename(self, ext):

nipype/interfaces/cmtk/convert.py

@@ -138,7 +138,7 @@ def _run_interface(self, runtime):
         count = 0
         if isdefined(self.inputs.tract_files):
             for trk in self.inputs.tract_files:
-                trk_name = 'Tract file {cnt}'.format(cnt=count)
+                _, trk_name, _ = split_filename(trk)
                 ctrack = cf.CTrack(trk_name, trk)
                 a.add_connectome_track(ctrack)
                 count += 1

nipype/interfaces/cmtk/parcellation.py

@@ -350,15 +350,28 @@ def crop_and_move_datasets(subject_id, subjects_dir, fs_dir, parcellation_name,
         mri_cmd = 'mri_convert -rl "%s" -rt nearest "%s" -nc "%s"' % (orig, d[0], d[1])
         runCmd( mri_cmd,log )
 
+
 class ParcellateInputSpec(BaseInterfaceInputSpec):
     subject_id = traits.String(mandatory=True, desc='Subject ID')
-    parcellation_name = traits.Enum('scale500', ['scale33', 'scale60', 'scale125', 'scale250','scale500'], usedefault=True)
+    parcellation_name = traits.Enum('scale500', ['scale33', 'scale60', 'scale125', 'scale250', 'scale500'], usedefault=True)
     freesurfer_dir = Directory(desc='Freesurfer main directory')
     subjects_dir = Directory(desc='Freesurfer main directory')
-    out_roi_file = File(genfile = True, desc='Region of Interest file for connectivity mapping')
+    out_roi_file = File(genfile=True, desc='Region of Interest file for connectivity mapping')
+
 
 class ParcellateOutputSpec(TraitedSpec):
-    roi_file = File(desc='Region of Interest file for connectivity mapping')
+    roi_file = File(desc='Region of Interest file for connectivity mapping',
+                    exists=True)
+    white_matter_mask_file = File(desc='White matter mask file')
+    cc_unknown_file = File(desc='Image file with regions labelled as unknown cortical structures',
+                    exists=True)
+    ribbon_file = File(desc='Image file detailing the cortical ribbon',
+                    exists=True)
+    aseg_file = File(desc='Automated segmentation file converted from Freesurfer "subjects" directory',
+                    exists=True)
+    roi_file_in_structural_space = File(desc='ROI image resliced to the dimensions of the original structural image',
+                    exists=True)
+
 
 class Parcellate(BaseInterface):
     """Subdivides segmented ROI file into smaller subregions
@@ -403,7 +416,7 @@ def _list_outputs(self):
         outputs['cc_unknown_file'] = op.abspath('cc_unknown.nii.gz')
         outputs['ribbon_file'] = op.abspath('ribbon.nii.gz')
         outputs['aseg_file'] = op.abspath('aseg.nii.gz')
-        outputs['ROI_HR_th_file'] = op.abspath('ROI_HR_th.nii.gz')
+        outputs['roi_file_in_structural_space'] = op.abspath('ROI_HR_th.nii.gz')
         return outputs
 
     def _gen_outfilename(self, ext, prefix='ROI'):

nipype/workflows/dmri/connectivity/nx.py

@@ -2,6 +2,7 @@
 import nipype.interfaces.utility as util
 import nipype.interfaces.cmtk as cmtk
 import nipype.algorithms.misc as misc
+from .group_connectivity import pullnodeIDs
 
 def create_networkx_pipeline(name="networkx", extra_column_heading="subject"):
     """Creates a workflow to calculate various graph measures (via NetworkX) on
@@ -52,6 +53,7 @@ def create_networkx_pipeline(name="networkx", extra_column_heading="subject"):
     pipeline.connect([(Matlab2CSV_node, MergeCSVFiles_node,[("csv_files","in_files")])])
     pipeline.connect([(inputnode, MergeCSVFiles_node,[("extra_field","out_file")])])
     pipeline.connect([(inputnode, MergeCSVFiles_node,[("extra_field","extra_field")])])
+    pipeline.connect([(inputnode, MergeCSVFiles_node, [(("network_file", pullnodeIDs), "row_headings")])])
 
     pipeline.connect([(inputnode, mergeNetworks,[("network_file","in1")])])
     pipeline.connect([(ntwkMetrics, mergeNetworks,[("gpickled_network_files","in2")])])
@@ -67,7 +69,7 @@ def create_networkx_pipeline(name="networkx", extra_column_heading="subject"):
     pipeline.connect([(Matlab2CSV_global, mergeCSVs, [("csv_files", "in2")])])
     pipeline.connect([(mergeNetworks, outputnode, [("out", "network_files")])])
     pipeline.connect([(mergeCSVs, outputnode, [("out", "csv_files")])])
-    pipeline.connect([(ntwkMetrics, outputnode,[("matlab_matrix_files","matlab_files")])])
+    pipeline.connect([(ntwkMetrics, outputnode,[("matlab_matrix_files", "matlab_files")])])
     return pipeline
 
 def create_cmats_to_csv_pipeline(name="cmats_to_csv", extra_column_heading="subject"):

nipype/workflows/dmri/mrtrix/connectivity_mapping.py

@@ -213,7 +213,7 @@ def create_connectivity_pipeline(name="connectivity", parcellation_name='scale50
 
     probCSDstreamtrack = pe.Node(interface=mrtrix.ProbabilisticSphericallyDeconvolutedStreamlineTrack(),name='probCSDstreamtrack')
     probCSDstreamtrack.inputs.inputmodel = 'SD_PROB'
-    probCSDstreamtrack.inputs.maximum_number_of_tracks = 150000
+    probCSDstreamtrack.inputs.desired_number_of_tracks = 150000
     tracks2prob = pe.Node(interface=mrtrix.Tracks2Prob(),name='tracks2prob')
     tracks2prob.inputs.colour = True
     MRconvert_tracks2prob = MRconvert_fa.clone(name='MRconvert_tracks2prob')
@@ -479,7 +479,7 @@ def create_connectivity_pipeline(name="connectivity", parcellation_name='scale50
     mapping.connect([(creatematrix, CFFConverter,[("matrix_files","gpickled_networks")])])
     mapping.connect([(niftiVolumes, CFFConverter,[("out","nifti_volumes")])])
     mapping.connect([(fiberDataArrays, CFFConverter,[("out","data_files")])])
-    mapping.connect([(creatematrix, CFFConverter,[("filtered_tractography","tract_files")])])
+    mapping.connect([(creatematrix, CFFConverter,[("filtered_tractographies","tract_files")])])
     mapping.connect([(inputnode_within, CFFConverter,[("subject_id","title")])])
 
     """