changes reverted. will it pass tests now?

Author: Fabio Bernardoni

nipype/interfaces/spm/preprocess.py

@@ -204,14 +204,10 @@ class FieldMapOutputSpec(TraitedSpec):
 
 class FieldMap(SPMCommand):
     """Use the fieldmap toolbox from spm to calculate the voxel displacement map (VDM).
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=173
-
     .. important::
-
         This interface does not deal with real/imag magnitude images nor
         with the two phase files case.
-
     Examples
     --------
     >>> from nipype.interfaces.spm import FieldMap
@@ -223,7 +219,6 @@ class FieldMap(SPMCommand):
     >>> fm.inputs.total_readout_time = 15.6
     >>> fm.inputs.epi_file = 'epi.nii'
     >>> fm.run() # doctest: +SKIP
-
     """
 
     input_spec = FieldMapInputSpec
@@ -258,13 +253,11 @@ def _list_outputs(self):
 class ApplyVDMInputSpec(SPMCommandInputSpec):
 
     in_files = InputMultiObject(
-        traits.Either(
-            ImageFileSPM(exists=True), traits.List(ImageFileSPM(exists=True))
-        ),
-        field='data.scans',
+        ImageFileSPM(exists=True),
+        field="data.scans",
         mandatory=True,
         copyfile=True,
-        desc='list of filenames to apply the vdm to',
+        desc="list of filenames to apply the vdm to",
     )
     vdmfile = File(
         field="data.vdmfile",
@@ -321,14 +314,10 @@ class ApplyVDMOutputSpec(TraitedSpec):
 
 class ApplyVDM(SPMCommand):
     """Use the fieldmap toolbox from spm to apply the voxel displacement map (VDM) to some epi files.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=173
-
     .. important::
-
         This interface does not deal with real/imag magnitude images nor
         with the two phase files case.
-
     """
 
     input_spec = ApplyVDMInputSpec
@@ -339,11 +328,7 @@ class ApplyVDM(SPMCommand):
     def _format_arg(self, opt, spec, val):
         """Convert input to appropriate format for spm"""
 
-        if opt == 'in_files':
-            return scans_for_fnames(
-                ensure_list(val), keep4d=False, separate_sessions=False
-            )
-        if opt == 'vdmfile':
+        if opt in ["in_files", "vdmfile"]:
             return scans_for_fname(ensure_list(val))
         return super(ApplyVDM, self)._format_arg(opt, spec, val)
 
@@ -435,12 +420,9 @@ class SliceTimingOutputSpec(TraitedSpec):
 
 class SliceTiming(SPMCommand):
     """Use spm to perform slice timing correction.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=19
-
     Examples
     --------
-
     >>> from nipype.interfaces.spm import SliceTiming
     >>> st = SliceTiming()
     >>> st.inputs.in_files = 'functional.nii'
@@ -450,7 +432,6 @@ class SliceTiming(SPMCommand):
     >>> st.inputs.slice_order = list(range(32,0,-1))
     >>> st.inputs.ref_slice = 1
     >>> st.run() # doctest: +SKIP
-
     """
 
     input_spec = SliceTimingInputSpec
@@ -587,18 +568,14 @@ class RealignOutputSpec(TraitedSpec):
 
 class Realign(SPMCommand):
     """Use spm_realign for estimating within modality rigid body alignment
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=25
-
     Examples
     --------
-
     >>> import nipype.interfaces.spm as spm
     >>> realign = spm.Realign()
     >>> realign.inputs.in_files = 'functional.nii'
     >>> realign.inputs.register_to_mean = True
     >>> realign.run() # doctest: +SKIP
-
     """
 
     input_spec = RealignInputSpec
@@ -851,19 +828,15 @@ class RealignUnwarp(SPMCommand):
     of time series. Function accepts only one single field map. If in_files is a
     list of files they will be treated as separate sessions but associated to the
     same fieldmap.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=31
-
     Examples
     --------
-
     >>> import nipype.interfaces.spm as spm
     >>> realignUnwarp = spm.RealignUnwarp()
     >>> realignUnwarp.inputs.in_files = ['functional.nii', 'functional2.nii']
     >>> realignUnwarp.inputs.phase_map = 'voxeldisplacemap.vdm'
     >>> realignUnwarp.inputs.register_to_mean = True
     >>> realignUnwarp.run() # doctest: +SKIP
-
     """
 
     input_spec = RealignUnwarpInputSpec
@@ -1028,18 +1001,14 @@ class CoregisterOutputSpec(TraitedSpec):
 
 class Coregister(SPMCommand):
     """Use spm_coreg for estimating cross-modality rigid body alignment
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=39
-
     Examples
     --------
-
     >>> import nipype.interfaces.spm as spm
     >>> coreg = spm.Coregister()
     >>> coreg.inputs.target = 'functional.nii'
     >>> coreg.inputs.source = 'structural.nii'
     >>> coreg.run() # doctest: +SKIP
-
     """
 
     input_spec = CoregisterInputSpec
@@ -1205,16 +1174,13 @@ class NormalizeOutputSpec(TraitedSpec):
 
 class Normalize(SPMCommand):
     """use spm_normalise for warping an image to a template
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=203
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> norm = spm.Normalize()
     >>> norm.inputs.source = 'functional.nii'
     >>> norm.run() # doctest: +SKIP
-
     """
 
     input_spec = NormalizeInputSpec
@@ -1437,17 +1403,14 @@ class Normalize12(SPMCommand):
     known as ``New Segment`` in SPM8). Note that the normalisation in SPM12
     is done towards a file containing multiple tissue probability maps, which
     was not the case in SPM8.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=49
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> norm12 = spm.Normalize12()
     >>> norm12.inputs.image_to_align = 'structural.nii'
     >>> norm12.inputs.apply_to_files = 'functional.nii'
     >>> norm12.run() # doctest: +SKIP
-
     """
 
     input_spec = Normalize12InputSpec
@@ -1679,16 +1642,13 @@ class SegmentOutputSpec(TraitedSpec):
 class Segment(SPMCommand):
     """use spm_segment to separate structural images into different
     tissue classes.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=209
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> seg = spm.Segment()
     >>> seg.inputs.data = 'structural.nii'
     >>> seg.run() # doctest: +SKIP
-
     """
 
     input_spec = SegmentInputSpec
@@ -1840,22 +1800,17 @@ class NewSegmentOutputSpec(TraitedSpec):
 class NewSegment(SPMCommand):
     """Use spm_preproc8 (New Segment) to separate structural images into
     different tissue classes. Supports multiple modalities.
-
     NOTE: This interface currently supports single channel input only
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=43
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> seg = spm.NewSegment()
     >>> seg.inputs.channel_files = 'structural.nii'
     >>> seg.inputs.channel_info = (0.0001, 60, (True, True))
     >>> seg.run() # doctest: +SKIP
-
     For VBM pre-processing [http://www.fil.ion.ucl.ac.uk/~john/misc/VBMclass10.pdf],
     TPM.nii should be replaced by /path/to/spm8/toolbox/Seg/TPM.nii
-
     >>> seg = NewSegment()
     >>> seg.inputs.channel_files = 'structural.nii'
     >>> tissue1 = (('TPM.nii', 1), 2, (True,True), (False, False))
@@ -1865,7 +1820,6 @@ class NewSegment(SPMCommand):
     >>> tissue5 = (('TPM.nii', 5), 2, (False,False), (False, False))
     >>> seg.inputs.tissues = [tissue1, tissue2, tissue3, tissue4, tissue5]
     >>> seg.run() # doctest: +SKIP
-
     """
 
     input_spec = NewSegmentInputSpec
@@ -2088,19 +2042,15 @@ class MultiChannelNewSegmentOutputSpec(TraitedSpec):
 class MultiChannelNewSegment(SPMCommand):
     """Use spm_preproc8 (New Segment) to separate structural images into
     different tissue classes. Supports multiple modalities and multichannel inputs.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=45
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> seg = spm.MultiChannelNewSegment()
     >>> seg.inputs.channels = [('structural.nii',(0.0001, 60, (True, True)))]
     >>> seg.run() # doctest: +SKIP
-
     For VBM pre-processing [http://www.fil.ion.ucl.ac.uk/~john/misc/VBMclass10.pdf],
     TPM.nii should be replaced by /path/to/spm8/toolbox/Seg/TPM.nii
-
     >>> seg = MultiChannelNewSegment()
     >>> channel1= ('T1.nii',(0.0001, 60, (True, True)))
     >>> channel2= ('T2.nii',(0.0001, 60, (True, True)))
@@ -2112,7 +2062,6 @@ class MultiChannelNewSegment(SPMCommand):
     >>> tissue5 = (('TPM.nii', 5), 2, (False,False), (False, False))
     >>> seg.inputs.tissues = [tissue1, tissue2, tissue3, tissue4, tissue5]
     >>> seg.run() # doctest: +SKIP
-
     """
 
     input_spec = MultiChannelNewSegmentInputSpec
@@ -2270,9 +2219,7 @@ class SmoothOutputSpec(TraitedSpec):
 
 class Smooth(SPMCommand):
     """Use spm_smooth for 3D Gaussian smoothing of image volumes.
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=55
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
@@ -2345,12 +2292,10 @@ class DARTELInputSpec(SPMCommandInputSpec):
         field="warp.settings.param",
         desc="""\
 List of tuples for each iteration
-
   * Inner iterations
   * Regularization parameters
   * Time points for deformation model
   * smoothing parameter
-
 """,
     )
     optimization_parameters = traits.Tuple(
@@ -2360,11 +2305,9 @@ class DARTELInputSpec(SPMCommandInputSpec):
         field="warp.settings.optim",
         desc="""\
 Optimization settings a tuple:
-
   * LM regularization
   * cycles of multigrid solver
   * relaxation iterations
-
 """,
     )
 
@@ -2379,16 +2322,13 @@ class DARTELOutputSpec(TraitedSpec):
 
 class DARTEL(SPMCommand):
     """Use spm DARTEL to create a template and flow fields
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=185
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> dartel = spm.DARTEL()
     >>> dartel.inputs.image_files = [['rc1s1.nii','rc1s2.nii'],['rc2s1.nii', 'rc2s2.nii']]
     >>> dartel.run() # doctest: +SKIP
-
     """
 
     input_spec = DARTELInputSpec
@@ -2503,9 +2443,7 @@ class DARTELNorm2MNIOutputSpec(TraitedSpec):
 
 class DARTELNorm2MNI(SPMCommand):
     """Use spm DARTEL to normalize data to MNI space
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=188
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
@@ -2515,7 +2453,6 @@ class DARTELNorm2MNI(SPMCommand):
     >>> nm.inputs.apply_to_files = ['c1s1.nii', 'c1s3.nii']
     >>> nm.inputs.modulate = True
     >>> nm.run() # doctest: +SKIP
-
     """
 
     input_spec = DARTELNorm2MNIInputSpec
@@ -2598,17 +2535,14 @@ class CreateWarpedOutputSpec(TraitedSpec):
 
 class CreateWarped(SPMCommand):
     """Apply a flow field estimated by DARTEL to create warped images
-
     http://www.fil.ion.ucl.ac.uk/spm/doc/manual.pdf#page=190
-
     Examples
     --------
     >>> import nipype.interfaces.spm as spm
     >>> create_warped = spm.CreateWarped()
     >>> create_warped.inputs.image_files = ['rc1s1.nii', 'rc1s2.nii']
     >>> create_warped.inputs.flowfield_files = ['u_rc1s1_Template.nii', 'u_rc1s2_Template.nii']
     >>> create_warped.run() # doctest: +SKIP
-
     """
 
     input_spec = CreateWarpedInputSpec
@@ -2890,7 +2824,6 @@ class VBMSegmentOuputSpec(TraitedSpec):
 class VBMSegment(SPMCommand):
     """Use VBM8 toolbox to separate structural images into different
     tissue classes.
-
     Example
     -------
     >>> import nipype.interfaces.spm as spm