Improve executive summary carpet plots (#747)

.circleci/NiftiWithoutFreeSurferTest.sh

@@ -33,7 +33,8 @@ XCPD_CMD="$BASE_XCPD_CMD \
     -vv \
     --nuisance-regressors 27P \
     --disable-bandpass-filter \
-    --dummy-scans 1"
+    --dummy-scans 1 \
+    --dcan_qc"
 
 echo $XCPD_CMD
 

docs/api.rst

@@ -53,8 +53,8 @@ xcp_d-combineqc
    xcp_d.interfaces.bids
    xcp_d.interfaces.c3
    xcp_d.interfaces.connectivity
+   xcp_d.interfaces.executive_summary
    xcp_d.interfaces.filtering
-   xcp_d.interfaces.layout_builder
    xcp_d.interfaces.nilearn
    xcp_d.interfaces.prepostcleaning
    xcp_d.interfaces.qc_plot
@@ -89,7 +89,7 @@ xcp_d-combineqc
    xcp_d.utils.fcon
    xcp_d.utils.filemanip
    xcp_d.utils.modified_data
-   xcp_d.utils.plot
+   xcp_d.utils.plotting
    xcp_d.utils.qcmetrics
    xcp_d.utils.sentry
    xcp_d.utils.utils

xcp_d/cli/run.py

@@ -583,7 +583,6 @@ def main(args=None):
                 subjects=subject_list,
                 fmri_dir=str(fmri_dir),
                 output_dir=str(Path(str(output_dir)) / "xcp_d/"),
-                work_dir=work_dir,
                 cifti=opts.cifti,
                 dcan_qc=opts.dcan_qc,
                 dummy_scans=opts.dummy_scans,

xcp_d/interfaces/__init__.py

@@ -6,16 +6,15 @@
     bids,
     c3,
     connectivity,
+    executive_summary,
     filtering,
-    layout_builder,
     nilearn,
+    plotting,
     prepostcleaning,
-    qc_plot,
     regression,
     report,
     report_core,
     resting_state,
-    surfplotting,
     workbench,
 )
 
@@ -25,14 +24,13 @@
     "c3",
     "connectivity",
     "filtering",
-    "layout_builder",
+    "executive_summary",
     "nilearn",
     "prepostcleaning",
-    "qc_plot",
+    "plotting",
     "regression",
     "report_core",
     "report",
     "resting_state",
-    "surfplotting",
     "workbench",
 ]

xcp_d/interfaces/layout_builder.py → xcp_d/interfaces/executive_summary.py

@@ -178,6 +178,9 @@ def collect_inputs(self):
 
         for task_entity_set in task_entity_sets:
             task_file_figures = task_entity_set.copy()
+            task_file_figures[
+                "key"
+            ] = f"task-{task_entity_set['task']}_run-{task_entity_set.get('run', 0)}"
 
             query = {
                 "subject": self.subject_id,
@@ -208,6 +211,9 @@ def collect_inputs(self):
 
             task_files.append(task_file_figures)
 
+        # Sort the files by the desired key
+        task_files = sorted(task_files, key=lambda d: d["key"])
+
         self.task_files_ = task_files
 
     def generate_report(self, out_file=None):

xcp_d/interfaces/qc_plot.py → xcp_d/interfaces/plotting.py

@@ -1,12 +1,13 @@
 # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
 # vi: set ft=python sts=4 ts=4 sw=4 et:
-"""Quality control plotting interfaces."""
+"""Plotting interfaces."""
 import os
 
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import seaborn as sns
+from nilearn.plotting import plot_anat
 from nipype import logging
 from nipype.interfaces.base import (
     BaseInterfaceInputSpec,
@@ -20,7 +21,7 @@
 from xcp_d.utils.confounds import load_confound, load_motion
 from xcp_d.utils.filemanip import fname_presuffix
 from xcp_d.utils.modified_data import compute_fd
-from xcp_d.utils.plot import FMRIPlot
+from xcp_d.utils.plotting import FMRIPlot, plot_fmri_es
 from xcp_d.utils.qcmetrics import compute_dvars, compute_registration_qc
 from xcp_d.utils.write_save import read_ndata, write_ndata
 
@@ -183,7 +184,7 @@ def _run_interface(self, runtime):
         return runtime
 
 
-class _QCPlotInputSpec(BaseInterfaceInputSpec):
+class _QCPlotsInputSpec(BaseInterfaceInputSpec):
     bold_file = File(exists=True, mandatory=True, desc="Raw bold file from fMRIPrep")
     dummy_scans = traits.Int(mandatory=True, desc="Dummy time to drop")
     tmask = File(exists=True, mandatory=True, desc="Temporal mask")
@@ -205,14 +206,14 @@ class _QCPlotInputSpec(BaseInterfaceInputSpec):
     bold2temp_mask = File(exists=True, mandatory=False, desc="Bold mask in T1W")
 
 
-class _QCPlotOutputSpec(TraitedSpec):
+class _QCPlotsOutputSpec(TraitedSpec):
     qc_file = File(exists=True, mandatory=True, desc="qc file in tsv")
     raw_qcplot = File(exists=True, mandatory=True, desc="qc plot before regression")
     clean_qcplot = File(exists=True, mandatory=True, desc="qc plot after regression")
 
 
-class QCPlot(SimpleInterface):
-    """Generate a quality control (QC) figure.
+class QCPlots(SimpleInterface):
+    """Generate pre- and post-processing quality control (QC) figures.
 
     Examples
     --------
@@ -221,20 +222,20 @@ class QCPlot(SimpleInterface):
     >>> tmpdir = TemporaryDirectory()
     >>> os.chdir(tmpdir.name)
     .. doctest::
-    computeqcwf = QCPlot()
-    computeqcwf.inputs.cleaned_file = datafile
-    computeqcwf.inputs.bold_file = rawbold
-    computeqcwf.inputs.TR = TR
-    computeqcwf.inputs.tmask = temporalmask
-    computeqcwf.inputs.mask_file = mask
-    computeqcwf.inputs.dummy_scans = dummy_scans
-    computeqcwf.run()
+    qcplots = QCPlots()
+    qcplots.inputs.cleaned_file = datafile
+    qcplots.inputs.bold_file = rawbold
+    qcplots.inputs.TR = TR
+    qcplots.inputs.tmask = temporalmask
+    qcplots.inputs.mask_file = mask
+    qcplots.inputs.dummy_scans = dummy_scans
+    qcplots.run()
     .. testcleanup::
     >>> tmpdir.cleanup()
     """
 
-    input_spec = _QCPlotInputSpec
-    output_spec = _QCPlotOutputSpec
+    input_spec = _QCPlotsInputSpec
+    output_spec = _QCPlotsOutputSpec
 
     def _run_interface(self, runtime):
         # Load confound matrix and load motion with motion filtering
@@ -445,3 +446,111 @@ def _run_interface(self, runtime):
         df.to_csv(self._results["qc_file"], index=False, header=True)
 
         return runtime
+
+
+class _QCPlotsESInputSpec(BaseInterfaceInputSpec):
+    rawdata = File(exists=True, mandatory=True, desc="Raw data")
+    regressed_data = File(
+        exists=True,
+        mandatory=True,
+        desc="Data after regression and interpolation, but not filtering.",
+    )
+    residual_data = File(exists=True, mandatory=True, desc="Data after filtering")
+    filtered_motion = File(
+        exists=True,
+        mandatory=True,
+        desc="TSV file with filtered motion parameters.",
+    )
+    TR = traits.Float(default_value=1, desc="Repetition time")
+
+    # Optional inputs
+    mask = File(exists=True, mandatory=False, desc="Bold mask")
+    seg_data = File(exists=True, mandatory=False, desc="Segmentation file")
+    dummy_scans = traits.Int(
+        0,
+        usedefault=True,
+        desc="Number of dummy volumes to drop from the beginning of the run.",
+    )
+
+
+class _QCPlotsESOutputSpec(TraitedSpec):
+    before_process = File(exists=True, mandatory=True, desc=".SVG file before processing")
+    after_process = File(exists=True, mandatory=True, desc=".SVG file after processing")
+
+
+class QCPlotsES(SimpleInterface):
+    """Plot fd, dvars, and carpet plots of the bold data before and after regression/filtering.
+
+    This is essentially equivalent to the QCPlots
+    (which are paired pre- and post-processing FMRIPlots), but adapted for the executive summary.
+
+    It takes in the data that's regressed, the data that's filtered and regressed,
+    as well as the segmentation files, TR, FD, bold_mask and unprocessed data.
+
+    It outputs the .SVG files before after processing has taken place.
+    """
+
+    input_spec = _QCPlotsESInputSpec
+    output_spec = _QCPlotsESOutputSpec
+
+    def _run_interface(self, runtime):
+        before_process_fn = fname_presuffix(
+            "carpetplot_before_",
+            suffix="file.svg",
+            newpath=runtime.cwd,
+            use_ext=False,
+        )
+
+        after_process_fn = fname_presuffix(
+            "carpetplot_after_",
+            suffix="file.svg",
+            newpath=runtime.cwd,
+            use_ext=False,
+        )
+
+        mask_file = self.inputs.mask
+        mask_file = mask_file if isdefined(mask_file) else None
+
+        segmentation_file = self.inputs.seg_data
+        segmentation_file = segmentation_file if isdefined(segmentation_file) else None
+
+        self._results["before_process"], self._results["after_process"] = plot_fmri_es(
+            preprocessed_file=self.inputs.rawdata,
+            residuals_file=self.inputs.regressed_data,
+            denoised_file=self.inputs.residual_data,
+            dummy_scans=self.inputs.dummy_scans,
+            TR=self.inputs.TR,
+            mask=mask_file,
+            filtered_motion=self.inputs.filtered_motion,
+            seg_data=segmentation_file,
+            processed_filename=after_process_fn,
+            unprocessed_filename=before_process_fn,
+        )
+
+        return runtime
+
+
+class _AnatomicalPlotInputSpec(BaseInterfaceInputSpec):
+    in_file = File(exists=True, mandatory=True, desc="plot image")
+
+
+class _AnatomicalPlotOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc="out image")
+
+
+class AnatomicalPlot(SimpleInterface):
+    """Python class to plot x,y, and z of image data."""
+
+    input_spec = _AnatomicalPlotInputSpec
+    output_spec = _AnatomicalPlotOutputSpec
+
+    def _run_interface(self, runtime):
+        self._results["out_file"] = fname_presuffix(
+            self.inputs.in_file, suffix="_file.svg", newpath=runtime.cwd, use_ext=False
+        )
+
+        fig = plt.figure(constrained_layout=False, figsize=(25, 10))
+        plot_anat(self.inputs.in_file, draw_cross=False, figure=fig)
+        fig.savefig(self._results["out_file"], bbox_inches="tight", pad_inches=None)
+
+        return runtime

xcp_d/interfaces/regression.py

@@ -118,7 +118,7 @@ def _run_interface(self, runtime):
                 standardize=False,
                 sample_mask=None,
                 confounds=confound,
-                standardize_confounds=False,  # do we want to set this to True?
+                standardize_confounds=True,  # do we want to set this to True?
                 filter=None,
                 low_pass=None,
                 high_pass=None,

xcp_d/interfaces/report_core.py

@@ -11,7 +11,7 @@
 
 from niworkflows.reports.core import Report as _Report
 
-from xcp_d.interfaces.layout_builder import ExecutiveSummary
+from xcp_d.interfaces.executive_summary import ExecutiveSummary
 from xcp_d.utils.bids import get_entity
 from xcp_d.utils.doc import fill_doc