enh: split out reports to a new module

Author: oesteban

dmriprep/config/reports-spec.yml

@@ -30,6 +30,12 @@ sections:
   ordering: session,acquisition,run
   reportlets:
   - bids: {datatype: dwi, desc: validation, suffix: dwi}
+  - bids: {datatype: dwi, desc: brain, suffix: mask}
+      caption: Average b=0 that serves for reference in early preprocessing steps.
+      descriptions: The reference b=0 is obtained as the voxel-wise median across
+        all b=0 found in the dataset, after accounting for signal drift.
+        The red contour shows the brain mask calculated using this reference b=0.
+      subtitle: Reference b=0 and brain mask
 - name: About
   reportlets:
   - bids: {datatype: anat, desc: about, suffix: T1w}

dmriprep/workflows/base.py

@@ -1,10 +1,4 @@
-# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
-# vi: set ft=python sts=4 ts=4 sw=4 et:
-"""
-dMRIPrep base processing workflows.
-
-"""
-
+"""dMRIPrep base processing workflows."""
 import sys
 import os
 from packaging.version import Version

dmriprep/workflows/dwi/base.py

@@ -1,16 +1,12 @@
 """Orchestrating the dMRI-preprocessing workflow."""
-
 from nipype import logging
-
 from nipype.pipeline import engine as pe
 from nipype.interfaces import utility as niu
 
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
-
-from ...config import DEFAULT_MEMORY_MIN_GB
-
-from ...interfaces import DerivativesDataSink
 from ...interfaces.vectors import CheckGradientTable
+from .util import init_dwi_reference_wf
+from .outputs import init_reportlets_wf
 
 
 LOGGER = logging.getLogger('nipype.workflow')
@@ -100,10 +96,9 @@ def init_dwi_preproc_wf(
     See also
     --------
     * :py:func:`~dmriprep.workflows.dwi.util.init_dwi_reference_wf`
+    * :py:func:`~dmriprep.workflows.dwi.outputs.init_reportlets_wf`
 
     """
-    from .util import init_dwi_reference_wf
-
     wf_name = _get_wf_name(dwi_file)
 
     # Build workflow
@@ -147,7 +142,7 @@ def init_dwi_preproc_wf(
 
     gradient_table = pe.Node(CheckGradientTable(), name='gradient_table')
 
-    dwi_reference_wf = init_dwi_reference_wf(omp_nthreads=1, gen_report=True)
+    dwi_reference_wf = init_dwi_reference_wf(omp_nthreads=1)
 
     # MAIN WORKFLOW STRUCTURE
     workflow.connect([
@@ -158,7 +153,7 @@ def init_dwi_preproc_wf(
         (inputnode, dwi_reference_wf, [('dwi_file', 'inputnode.dwi_file')]),
         (gradient_table, dwi_reference_wf, [('b0_ixs', 'inputnode.b0_ixs')]),
         (dwi_reference_wf, outputnode, [
-            ('outputnode.dwi_file', 'out_dwi'),
+            ('outputnode.ref_image', 'out_dwi'),
             ('outputnode.dwi_mask', 'out_dwi_mask')]),
         (gradient_table, outputnode, [
             ('out_bvec', 'out_bvec'),
@@ -167,18 +162,14 @@ def init_dwi_preproc_wf(
     ])
 
     # REPORTING
-    ds_report_validation = pe.Node(
-        DerivativesDataSink(base_directory=reportlets_dir,
-                            desc='validation', keep_dtype=True),
-        name='ds_report_validation', run_without_submitting=True,
-        mem_gb=DEFAULT_MEMORY_MIN_GB)
-
+    reportlets_wf = init_reportlets_wf(reportlets_dir)
     workflow.connect([
-        (inputnode, ds_report_validation, [('dwi', 'source_file')]),
-        (dwi_reference_wf, ds_report_validation, [
-            ('outputnode.validation_report', 'in_file')]),
+        (inputnode, reportlets_wf, [('dwi_file', 'inputnode.source_file')]),
+        (dwi_reference_wf, reportlets_wf, [
+            ('outputnode.ref_image', 'inputnode.dwi_ref'),
+            ('outputnode.dwi_mask', 'inputnode.dwi_mask'),
+            ('outputnode.validation_report', 'inputnode.validation_report')]),
     ])
-
     return workflow
 
 

dmriprep/workflows/dwi/outputs.py

@@ -0,0 +1,36 @@
+"""Write outputs (derivatives and reportlets)."""
+from nipype.pipeline import engine as pe
+from nipype.interfaces import utility as niu
+from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from ...interfaces import DerivativesDataSink
+
+
+def init_reportlets_wf(reportlets_dir, name='reportlets_wf'):
+    """Set up a battery of datasinks to store reports in the right location."""
+    from niworkflows.interfaces.masks import SimpleShowMaskRPT
+    workflow = Workflow(name=name)
+
+    inputnode = pe.Node(niu.IdentityInterface(
+        fields=['source_file', 'dwi_ref', 'dwi_mask',
+                'validation_report']),
+        name='inputnode')
+    mask_reportlet = pe.Node(SimpleShowMaskRPT(), name='mask_reportlet')
+
+    ds_report_mask = pe.Node(
+        DerivativesDataSink(base_directory=reportlets_dir,
+                            desc='brain', suffix='mask'),
+        name='ds_report_mask', run_without_submitting=True)
+    ds_report_validation = pe.Node(
+        DerivativesDataSink(base_directory=reportlets_dir,
+                            desc='validation', keep_dtype=True),
+        name='ds_report_validation', run_without_submitting=True)
+
+    workflow.connect([
+        (inputnode, mask_reportlet, [('dwi_ref', 'background_file'),
+                                     ('dwi_mask', 'mask_file')]),
+        (inputnode, ds_report_validation, [('source_file', 'source_file')]),
+        (inputnode, ds_report_mask, [('source_file', 'source_file')]),
+        (inputnode, ds_report_validation, [('validation_report', 'in_file')]),
+        (mask_reportlet, ds_report_mask, [('out_report', 'in_file')]),
+    ])
+    return workflow

dmriprep/workflows/dwi/util.py

@@ -6,15 +6,14 @@
 from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 from niworkflows.interfaces.images import ValidateImage
 from niworkflows.interfaces.fixes import FixN4BiasFieldCorrection as N4BiasFieldCorrection
-from niworkflows.interfaces.masks import SimpleShowMaskRPT
 from niworkflows.interfaces.utils import CopyXForm
 
 from ...interfaces.images import ExtractB0, RescaleB0
 
 DEFAULT_MEMORY_MIN_GB = 0.01
 
 
-def init_dwi_reference_wf(omp_nthreads, name='dwi_reference_wf', gen_report=False):
+def init_dwi_reference_wf(omp_nthreads, name='dwi_reference_wf'):
     """
     Build a workflow that generates a reference b0 image from a DWI dataset.
 
@@ -40,8 +39,6 @@ def init_dwi_reference_wf(omp_nthreads, name='dwi_reference_wf', gen_report=Fals
         Maximum number of threads an individual process may use
     name : str
         Name of workflow (default: ``dwi_reference_wf``)
-    gen_report : bool
-        Whether a mask report node should be appended in the end
 
     Inputs
     ------
@@ -112,16 +109,6 @@ def init_dwi_reference_wf(omp_nthreads, name='dwi_reference_wf', gen_report=Fals
             ('outputnode.mask_file', 'dwi_mask'),
             ('outputnode.skull_stripped_file', 'ref_image_brain')]),
     ])
-
-    if gen_report:
-        mask_reportlet = pe.Node(SimpleShowMaskRPT(), name='mask_reportlet')
-        workflow.connect([
-            (enhance_and_skullstrip_dwi_wf, mask_reportlet, [
-                ('outputnode.bias_corrected_file', 'background_file'),
-                ('outputnode.mask_file', 'mask_file'),
-            ]),
-        ])
-
     return workflow