[ENH] Remaining TemplateFlow integrations

Author: oesteban

fmriprep/workflows/bold/confounds.py

@@ -13,7 +13,7 @@
 from nipype.interfaces import utility as niu, fsl
 from nipype.algorithms import confounds as nac
 
-from niworkflows.data import get_template
+from templateflow.api import get as get_template
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from niworkflows.interfaces.images import SignalExtraction
@@ -360,9 +360,8 @@ def init_carpetplot_wf(mem_gb, metadata, name="bold_carpet_wf"):
     # Warp segmentation into EPI space
     resample_parc = pe.Node(ApplyTransforms(
         float=True,
-        input_image=str(
-            get_template('MNI152NLin2009cAsym') /
-            'tpl-MNI152NLin2009cAsym_space-MNI_res-01_label-carpet_atlas.nii.gz'),
+        input_image=get_template('MNI152NLin2009cAsym',
+                                 '_res-01_desc-carpet_dseg.nii.gz'),
         dimension=3, default_value=0, interpolation='MultiLabel'),
         name='resample_parc')
 
@@ -537,8 +536,7 @@ def init_ica_aroma_wf(template, metadata, mem_gb, omp_nthreads,
         freesurfer=False,
         mem_gb=mem_gb,
         omp_nthreads=omp_nthreads,
-        template_out_grid=str(
-            get_template('MNI152Lin') / 'tpl-MNI152Lin_space-MNI_res-02_T1w.nii.gz'),
+        template_out_grid=get_template('MNI152Lin', 'res-02_T1w.nii.gz'),
         use_compression=False,
         use_fieldwarp=use_fieldwarp,
         name='bold_mni_trans_wf'

fmriprep/workflows/bold/resampling.py

@@ -14,7 +14,7 @@
 from nipype.interfaces import utility as niu, freesurfer as fs
 from nipype.interfaces.fsl import Split as FSLSplit
 
-from niworkflows.data import get_template, TEMPLATE_ALIASES
+from templateflow.api import get as get_template
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from niworkflows.interfaces.freesurfer import (
@@ -282,13 +282,7 @@ def _aslist(in_value):
 
     gen_ref = pe.Node(GenerateSamplingReference(), name='gen_ref',
                       mem_gb=0.3)  # 256x256x256 * 64 / 8 ~ 150MB)
-    # Account for template aliases
-    template_name = TEMPLATE_ALIASES.get(template, template)
-    # Template path
-    template_dir = get_template(template_name)
-
-    gen_ref.inputs.fixed_image = str(
-        template_dir / ('tpl-%s_space-MNI_res-01_T1w.nii.gz' % template_name))
+    gen_ref.inputs.fixed_image = get_template(template, '_res-01_T1w.nii.gz')
 
     mask_mni_tfm = pe.Node(
         ApplyTransforms(interpolation='MultiLabel', float=True),
@@ -348,12 +342,10 @@ def _aslist(in_value):
         ])
     elif template_out_grid in ['1mm', '2mm']:
         res = int(template_out_grid[0])
-        mask_mni_tfm.inputs.reference_image = str(
-            template_dir /
-            ('tpl-%s_space-MNI_res-%02d_brainmask.nii.gz' % (template_name, res)))
-        bold_to_mni_transform.inputs.reference_image = str(
-            template_dir /
-            ('tpl-%s_space-MNI_res-%02d_T1w.nii.gz' % (template_name, res)))
+        mask_mni_tfm.inputs.reference_image = get_template(
+            template, '_res-%02d_desc-brain_mask.nii.gz' % res)
+        bold_to_mni_transform.inputs.reference_image = get_template(
+            template, '_res-%02d_T1w.nii.gz' % res)
     else:
         mask_mni_tfm.inputs.reference_image = template_out_grid
         bold_to_mni_transform.inputs.reference_image = template_out_grid
@@ -382,12 +374,10 @@ def _aslist(in_value):
             ])
         elif template_out_grid in ['1mm', '2mm']:
             res = int(template_out_grid[0])
-            aseg_mni_tfm.inputs.reference_image = str(
-                template_dir /
-                ('tpl-%s_space-MNI_res-%02d_brainmask.nii.gz' % (template_name, res)))
-            aparc_mni_tfm.inputs.reference_image = str(
-                template_dir /
-                ('tpl-%s_space-MNI_res-%02d_T1w.nii.gz' % (template_name, res)))
+            aseg_mni_tfm.inputs.reference_image = get_template(
+                template, '_res-%02d_desc-brain_mask.nii.gz' % res)
+            aparc_mni_tfm.inputs.reference_image = get_template(
+                template, '_res-%02d_desc-brain_mask.nii.gz' % res)
         else:
             aseg_mni_tfm.inputs.reference_image = template_out_grid
             aparc_mni_tfm.inputs.reference_image = template_out_grid

fmriprep/workflows/bold/util.py

@@ -15,7 +15,9 @@
 
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu, fsl, afni, ants
-from niworkflows.data import get_template
+
+from templateflow.api import get as get_template
+
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 from niworkflows.interfaces.ants import AI
 from niworkflows.interfaces.fixes import (
@@ -273,9 +275,8 @@ def init_enhance_and_skullstrip_bold_wf(
     apply_mask = pe.Node(fsl.ApplyMask(), name='apply_mask')
 
     if not pre_mask:
-        bold_template = get_template('fMRIPrep') / 'tpl-fMRIPrep_space-MNI_res-02_boldref.nii.gz'
-        brain_mask = get_template('MNI152NLin2009cAsym') / \
-            'tpl-MNI152NLin2009cAsym_space-MNI_res-02_brainmask.nii.gz'
+        bold_template = get_template('fMRIPrep', 'space-MNI_res-02_boldref.nii.gz')
+        brain_mask = get_template('MNI152NLin2009cAsym', 'res-02_desc-brain_mask.nii.gz')
 
         # Initialize transforms with antsAI
         init_aff = pe.Node(AI(