[PIN] sMRIPrep 0.1.0, Niworkflows 0.8.0 and TemplateFlow 0.1.0

- [x] Use new TemplateFlow interface
- [x] Let sMRIPrep decide pinned versions of niworkflows and
templateflow

Author: oesteban

fmriprep/__about__.py

@@ -89,21 +89,23 @@
     'nilearn',
     'nipype>=1.1.6',
     'nitime',
-    'niworkflows>=0.7.2,<0.8.0a0',
+    'niworkflows',
     'numpy',
     'pandas',
     'psutil>=5.4',
-    'pybids>=0.7.0,<0.8.0a0',
+    'pybids',
     'pyyaml',
     'scikit-image',
-    'smriprep>=0.0.5,<0.1.0a0',
+    'smriprep',
     'statsmodels',
     'tedana>=0.0.5',
-    'templateflow>=0.0.4',
+    'templateflow',
 ]
 
 
 LINKS_REQUIRES = [
+    'git+https://github.com/oesteban/smriprep@'
+    '1cfa100ab7fc92d07d988f0a99b720739d3812d3#smriprep-0.0.5',
 ]
 
 TESTS_REQUIRES = [

fmriprep/workflows/bold/confounds.py

@@ -360,8 +360,9 @@ 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=get_template('MNI152NLin2009cAsym',
-                                 '_res-01_desc-carpet_dseg.nii.gz'),
+        input_image=str(get_template(
+            'MNI152NLin2009cAsym', resolution=1, desc='carpet',
+            suffix='dseg', extensions=['.nii', '.nii.gz'])),
         dimension=3, default_value=0, interpolation='MultiLabel'),
         name='resample_parc')
 
@@ -536,7 +537,9 @@ def init_ica_aroma_wf(template, metadata, mem_gb, omp_nthreads,
         freesurfer=False,
         mem_gb=mem_gb,
         omp_nthreads=omp_nthreads,
-        template_out_grid=get_template('MNI152Lin', 'res-02_T1w.nii.gz'),
+        template_out_grid=str(get_template(
+            'MNI152Lin', resolution=2, desc=None, suffix='T1w',
+            extensions=['.nii', '.nii.gz'])),
         use_compression=False,
         use_fieldwarp=use_fieldwarp,
         name='bold_mni_trans_wf'

fmriprep/workflows/bold/resampling.py

@@ -282,7 +282,9 @@ def _aslist(in_value):
 
     gen_ref = pe.Node(GenerateSamplingReference(), name='gen_ref',
                       mem_gb=0.3)  # 256x256x256 * 64 / 8 ~ 150MB)
-    gen_ref.inputs.fixed_image = get_template(template, '_res-01_T1w.nii.gz')
+    gen_ref.inputs.fixed_image = str(get_template(
+        template, resolution=1, desc=None, suffix='T1w',
+        extensions=['.nii', '.nii.gz']))
 
     mask_mni_tfm = pe.Node(
         ApplyTransforms(interpolation='MultiLabel', float=True),
@@ -342,10 +344,11 @@ def _aslist(in_value):
         ])
     elif template_out_grid in ['1mm', '2mm']:
         res = int(template_out_grid[0])
-        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)
+        mask_mni_tfm.inputs.reference_image = str(get_template(
+            template, resolution=res, desc='brain', suffix='mask'))
+        bold_to_mni_transform.inputs.reference_image = str(get_template(
+            template, resolution=res, desc=None, suffix='T1w',
+            extensions=['.nii', '.nii.gz']))
     else:
         mask_mni_tfm.inputs.reference_image = template_out_grid
         bold_to_mni_transform.inputs.reference_image = template_out_grid
@@ -373,11 +376,13 @@ def _aslist(in_value):
                 (gen_ref, aparc_mni_tfm, [('out_file', 'reference_image')]),
             ])
         elif template_out_grid in ['1mm', '2mm']:
-            res = int(template_out_grid[0])
-            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)
+            entities = {'resolution': int(template_out_grid[0]),
+                        'desc': 'brain', 'suffix': 'mask',
+                        'extensions': ['.nii', '.nii.gz']}
+            aseg_mni_tfm.inputs.reference_image = str(
+                get_template(template, **entities))
+            aparc_mni_tfm.inputs.reference_image = str(
+                get_template(template, **entities))
         else:
             aseg_mni_tfm.inputs.reference_image = template_out_grid
             aparc_mni_tfm.inputs.reference_image = template_out_grid

fmriprep/workflows/bold/util.py

@@ -275,8 +275,10 @@ def init_enhance_and_skullstrip_bold_wf(
     apply_mask = pe.Node(fsl.ApplyMask(), name='apply_mask')
 
     if not pre_mask:
-        bold_template = get_template('MNI152NLin2009cAsym', 'res-02_desc-fMRIPrep_boldref.nii.gz')
-        brain_mask = get_template('MNI152NLin2009cAsym', 'res-02_desc-brain_mask.nii.gz')
+        bold_template = get_template(
+            'MNI152NLin2009cAsym', resolution=2, desc='fMRIPrep', suffix='boldref')
+        brain_mask = get_template(
+            'MNI152NLin2009cAsym', resolution=2, desc='brain', suffix='mask')
 
         # Initialize transforms with antsAI
         init_aff = pe.Node(AI(

requirements.txt

@@ -1,4 +1 @@
-pybids>=0.7.0,<0.8.0a0
-niworkflows>=0.7.2,<0.8.0a0
-smriprep>=0.0.5,<0.1.0a0
-templateflow>=0.0.4
+git+https://github.com/oesteban/smriprep@1cfa100ab7fc92d07d988f0a99b720739d3812d3#smriprep-0.0.5