[skip ds210][skip ds054][skip tests] switch n_volumes* to skip_vols and use nonsteady calculation from bold_reference_wf (review by effigies)

Author: jdkent

fmriprep/interfaces/confounds.py

@@ -94,7 +94,7 @@ def _run_interface(self, runtime):
 
 class ICAConfoundsInputSpec(BaseInterfaceInputSpec):
     in_directory = Directory(mandatory=True, desc='directory where ICA derivatives are found')
-    n_volumes = traits.Int(desc='number of non steady state volumes identified')
+    skip_vols = traits.Int(desc='number of non steady state volumes identified')
     ignore_aroma_err = traits.Bool(False, usedefault=True, desc='ignore ICA-AROMA errors')
 
 
@@ -112,7 +112,7 @@ class ICAConfounds(SimpleInterface):
 
     def _run_interface(self, runtime):
         aroma_confounds, motion_ics_out, melodic_mix_out = _get_ica_confounds(
-            self.inputs.in_directory, self.inputs.n_volumes, newpath=runtime.cwd)
+            self.inputs.in_directory, self.inputs.skip_vols, newpath=runtime.cwd)
 
         if aroma_confounds is not None:
             self._results['aroma_confounds'] = aroma_confounds
@@ -199,7 +199,7 @@ def _adjust_indices(left_df, right_df):
     return combined_out, confounds_list
 
 
-def _get_ica_confounds(ica_out_dir, n_volumes, newpath=None):
+def _get_ica_confounds(ica_out_dir, skip_vols, newpath=None):
     if newpath is None:
         newpath = os.getcwd()
 
@@ -219,8 +219,8 @@ def _get_ica_confounds(ica_out_dir, n_volumes, newpath=None):
     melodic_mix_arr = np.loadtxt(melodic_mix, ndmin=2)
 
     # pad melodic_mix_arr with rows of zeros corresponding to number non steadystate volumes
-    if n_volumes > 0:
-        zeros = np.zeros([n_volumes, melodic_mix_arr.shape[1]])
+    if skip_vols > 0:
+        zeros = np.zeros([skip_vols, melodic_mix_arr.shape[1]])
         melodic_mix_arr = np.vstack([zeros, melodic_mix_arr])
 
     # save melodic_mix_arr

fmriprep/workflows/bold/base.py

@@ -18,7 +18,6 @@
 from nipype.interfaces.fsl import Split as FSLSplit
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
-from nipype.algorithms import confounds as nac
 
 from ...interfaces import (
     DerivativesDataSink,
@@ -425,9 +424,6 @@ def init_func_preproc_wf(bold_file, ignore, freesurfer,
                                              omp_nthreads=omp_nthreads,
                                              use_compression=False)
 
-    # get non steady-state volumes
-    non_steady_state = pe.Node(nac.NonSteadyStateDetector(), name='non_steady_state')
-
     # get confounds
     bold_confounds_wf = init_bold_confs_wf(
         mem_gb=mem_gb['largemem'],
@@ -529,18 +525,15 @@ def init_func_preproc_wf(bold_file, ignore, freesurfer,
             ('outputnode.out_warp', 'inputnode.fieldwarp'),
             ('outputnode.bold_mask', 'inputnode.bold_mask')]),
         (bold_sdc_wf, summary, [('outputnode.method', 'distortion_correction')]),
-        # Calculate nonsteady state
-        (bold_bold_trans_wf, non_steady_state, [
-            ('outputnode.bold', 'in_file')]),
         # Connect bold_confounds_wf
         (inputnode, bold_confounds_wf, [('t1_tpms', 'inputnode.t1_tpms'),
                                         ('t1_mask', 'inputnode.t1_mask')]),
         (bold_hmc_wf, bold_confounds_wf, [
             ('outputnode.movpar_file', 'inputnode.movpar_file')]),
         (bold_reg_wf, bold_confounds_wf, [
             ('outputnode.itk_t1_to_bold', 'inputnode.t1_bold_xform')]),
-        (non_steady_state, bold_confounds_wf, [
-            ('n_volumes_to_discard', 'inputnode.n_volumes_to_discard')]),
+        (bold_reference_wf, bold_confounds_wf, [
+            ('outputnode.skip_vols', 'inputnode.skip_vols')]),
         (bold_confounds_wf, outputnode, [
             ('outputnode.confounds_file', 'confounds'),
         ]),
@@ -739,8 +732,8 @@ def init_func_preproc_wf(bold_file, ignore, freesurfer,
                     ('outputnode.bold_mask', 'inputnode.bold_mask')]),
                 (bold_sdc_wf, ica_aroma_wf, [
                     ('outputnode.out_warp', 'inputnode.fieldwarp')]),
-                (non_steady_state, ica_aroma_wf, [
-                    ('n_volumes_to_discard', 'inputnode.n_volumes_to_discard')]),
+                (bold_reference_wf, ica_aroma_wf, [
+                    ('outputnode.skip_vols', 'inputnode.skip_vols')]),
                 (bold_confounds_wf, join, [
                     ('outputnode.confounds_file', 'in_file')]),
                 (ica_aroma_wf, join,

fmriprep/workflows/bold/confounds.py

@@ -92,7 +92,7 @@ def init_bold_confs_wf(mem_gb, metadata, name="bold_confs_wf"):
             BOLD series mask
         movpar_file
             SPM-formatted motion parameters file
-        n_volumes_to_discard
+        skip_vols
             number of non steady state volumes
         t1_mask
             Mask of the skull-stripped template image
@@ -138,7 +138,7 @@ def init_bold_confs_wf(mem_gb, metadata, name="bold_confs_wf"):
 placed within the corresponding confounds file.
 """
     inputnode = pe.Node(niu.IdentityInterface(
-        fields=['bold', 'bold_mask', 'movpar_file', 'n_volumes_to_discard',
+        fields=['bold', 'bold_mask', 'movpar_file', 'skip_vols',
                 't1_mask', 't1_tpms', 't1_bold_xform']),
         name='inputnode')
     outputnode = pe.Node(niu.IdentityInterface(
@@ -253,13 +253,13 @@ def _pick_wm(files):
 
         # tCompCor
         (inputnode, tcompcor, [('bold', 'realigned_file')]),
-        (inputnode, tcompcor, [('n_volumes_to_discard', 'ignore_initial_volumes')]),
+        (inputnode, tcompcor, [('skip_vols', 'ignore_initial_volumes')]),
         (tcc_tfm, tcc_msk, [('output_image', 'roi_file')]),
         (tcc_msk, tcompcor, [('out', 'mask_files')]),
 
         # aCompCor
         (inputnode, acompcor, [('bold', 'realigned_file')]),
-        (inputnode, acompcor, [('n_volumes_to_discard', 'ignore_initial_volumes')]),
+        (inputnode, acompcor, [('skip_vols', 'ignore_initial_volumes')]),
         (acc_tfm, acc_msk, [('output_image', 'roi_file')]),
         (acc_msk, acompcor, [('out', 'mask_files')]),
 
@@ -466,7 +466,7 @@ def init_ica_aroma_wf(template, metadata, mem_gb, omp_nthreads,
             Affine transform from ``ref_bold_brain`` to T1 space (ITK format)
         movpar_file
             SPM-formatted motion parameters file
-        n_volumes_to_discard
+        skip_vols
             number of non steady state volumes
         name_source
             BOLD series NIfTI file
@@ -506,7 +506,7 @@ def init_ica_aroma_wf(template, metadata, mem_gb, omp_nthreads,
             'itk_bold_to_t1',
             't1_2_mni_forward_transform',
             'name_source',
-            'n_volumes_to_discard',
+            'skip_vols',
             'bold_split',
             'bold_mask',
             'hmc_xforms',
@@ -584,7 +584,7 @@ def _getbtthresh(medianval):
             ('fieldwarp', 'inputnode.fieldwarp')]),
         (inputnode, ica_aroma, [('movpar_file', 'motion_parameters')]),
         (inputnode, rm_non_steady_state, [
-            ('n_volumes_to_discard', 'n_volumes')]),
+            ('skip_vols', 'skip_vols')]),
         (bold_mni_trans_wf, rm_non_steady_state, [
             ('outputnode.bold_mni', 'bold_file')]),
         (bold_mni_trans_wf, calc_median_val, [
@@ -613,7 +613,7 @@ def _getbtthresh(medianval):
         # generate tsvs from ICA-AROMA
         (ica_aroma, ica_aroma_confound_extraction, [('out_dir', 'in_directory')]),
         (inputnode, ica_aroma_confound_extraction, [
-            ('n_volumes_to_discard', 'n_volumes')]),
+            ('skip_vols', 'skip_vols')]),
         # output for processing and reporting
         (ica_aroma_confound_extraction, outputnode, [('aroma_confounds', 'aroma_confounds'),
                                                      ('aroma_noise_ics', 'aroma_noise_ics'),
@@ -624,15 +624,15 @@ def _getbtthresh(medianval):
         (bold_mni_trans_wf, add_non_steady_state, [
             ('outputnode.bold_mni', 'bold_file')]),
         (inputnode, add_non_steady_state, [
-            ('n_volumes_to_discard', 'n_volumes')]),
+            ('skip_vols', 'skip_vols')]),
         (add_non_steady_state, outputnode, [('bold_add', 'nonaggr_denoised_file')]),
         (ica_aroma, ds_report_ica_aroma, [('out_report', 'in_file')]),
     ])
 
     return workflow
 
 
-def _remove_volumes(bold_file, n_volumes):
+def _remove_volumes(bold_file, skip_vols):
         import nibabel as nb
         from nipype.utils.filemanip import fname_presuffix
 
@@ -641,11 +641,11 @@ def _remove_volumes(bold_file, n_volumes):
         bold_data = bold_img.get_data()
 
         # cut off the beginning volumes
-        bold_data_cut = bold_data[..., n_volumes:]
+        bold_data_cut = bold_data[..., skip_vols:]
 
         # modify header with new shape (fewer volumes)
         data_shape = list(bold_img.header.get_data_shape())
-        data_shape[-1] -= n_volumes
+        data_shape[-1] -= skip_vols
         bold_img.header.set_data_shape(tuple(data_shape))
 
         # save the resulting bold file
@@ -654,8 +654,8 @@ def _remove_volumes(bold_file, n_volumes):
         return out
 
 
-def _add_volumes(bold_file, bold_cut_file, n_volumes):
-    """prepend n_volumes from bold_file onto bold_cut_file"""
+def _add_volumes(bold_file, bold_cut_file, skip_vols):
+    """prepend skip_vols from bold_file onto bold_cut_file"""
     import nibabel as nb
     from nipype.utils.filemanip import fname_presuffix
 
@@ -665,8 +665,8 @@ def _add_volumes(bold_file, bold_cut_file, n_volumes):
     bold_cut_img = nb.load(bold_cut_file)
     bold_cut_data = bold_cut_img.get_data()
 
-    # assign everything from n_volumes foward to bold_cut_data
-    bold_data[..., n_volumes:] = bold_cut_data
+    # assign everything from skip_vols foward to bold_cut_data
+    bold_data[..., skip_vols:] = bold_cut_data
 
     out = fname_presuffix(bold_cut_file, suffix='_addnonsteady')
     bold_img.__class__(bold_data, bold_img.affine, bold_img.header).to_filename(out)