Merge branch 'master' into 3.12

.circleci/circle_bold.txt

@@ -30,8 +30,14 @@ sub-ds205s03/figures/sub-ds205s03_task-view_run-02_desc-stdev_bold.svg
 sub-ds205s03/figures/sub-ds205s03_task-view_run-02_desc-zoomed_bold.svg
 sub-ds205s03/func
 sub-ds205s03/func/sub-ds205s03_task-functionallocalizer_run-01_bold.json
+sub-ds205s03/func/sub-ds205s03_task-functionallocalizer_run-01_timeseries.json
+sub-ds205s03/func/sub-ds205s03_task-functionallocalizer_run-01_timeseries.tsv
 sub-ds205s03/func/sub-ds205s03_task-view_run-01_bold.json
+sub-ds205s03/func/sub-ds205s03_task-view_run-01_timeseries.json
+sub-ds205s03/func/sub-ds205s03_task-view_run-01_timeseries.tsv
 sub-ds205s03/func/sub-ds205s03_task-view_run-02_bold.json
+sub-ds205s03/func/sub-ds205s03_task-view_run-02_timeseries.json
+sub-ds205s03/func/sub-ds205s03_task-view_run-02_timeseries.tsv
 sub-ds205s03_task-functionallocalizer_run-01_bold.html
 sub-ds205s03_task-view_run-01_bold.html
 sub-ds205s03_task-view_run-02_bold.html
@@ -60,8 +66,14 @@ sub-ds205s07/figures/sub-ds205s07_task-view_run-02_desc-stdev_bold.svg
 sub-ds205s07/figures/sub-ds205s07_task-view_run-02_desc-zoomed_bold.svg
 sub-ds205s07/func
 sub-ds205s07/func/sub-ds205s07_task-functionallocalizer_run-01_bold.json
+sub-ds205s07/func/sub-ds205s07_task-functionallocalizer_run-01_timeseries.json
+sub-ds205s07/func/sub-ds205s07_task-functionallocalizer_run-01_timeseries.tsv
 sub-ds205s07/func/sub-ds205s07_task-view_run-01_bold.json
+sub-ds205s07/func/sub-ds205s07_task-view_run-01_timeseries.json
+sub-ds205s07/func/sub-ds205s07_task-view_run-01_timeseries.tsv
 sub-ds205s07/func/sub-ds205s07_task-view_run-02_bold.json
+sub-ds205s07/func/sub-ds205s07_task-view_run-02_timeseries.json
+sub-ds205s07/func/sub-ds205s07_task-view_run-02_timeseries.tsv
 sub-ds205s07_task-functionallocalizer_run-01_bold.html
 sub-ds205s07_task-view_run-01_bold.html
 sub-ds205s07_task-view_run-02_bold.html
@@ -90,8 +102,14 @@ sub-ds205s09/figures/sub-ds205s09_task-view_acq-RL_run-01_desc-stdev_bold.svg
 sub-ds205s09/figures/sub-ds205s09_task-view_acq-RL_run-01_desc-zoomed_bold.svg
 sub-ds205s09/func
 sub-ds205s09/func/sub-ds205s09_task-view_acq-LR_run-01_bold.json
+sub-ds205s09/func/sub-ds205s09_task-view_acq-LR_run-01_timeseries.json
+sub-ds205s09/func/sub-ds205s09_task-view_acq-LR_run-01_timeseries.tsv
 sub-ds205s09/func/sub-ds205s09_task-view_acq-LR_run-02_bold.json
+sub-ds205s09/func/sub-ds205s09_task-view_acq-LR_run-02_timeseries.json
+sub-ds205s09/func/sub-ds205s09_task-view_acq-LR_run-02_timeseries.tsv
 sub-ds205s09/func/sub-ds205s09_task-view_acq-RL_run-01_bold.json
+sub-ds205s09/func/sub-ds205s09_task-view_acq-RL_run-01_timeseries.json
+sub-ds205s09/func/sub-ds205s09_task-view_acq-RL_run-01_timeseries.tsv
 sub-ds205s09_task-view_acq-LR_run-01_bold.html
 sub-ds205s09_task-view_acq-LR_run-02_bold.html
 sub-ds205s09_task-view_acq-RL_run-01_bold.html

mriqc/data/bootstrap-func.yml

@@ -37,10 +37,28 @@ sections:
   - bids: {datatype: figures, desc: stdev}
     subtitle: Standard deviation of signal through time
     caption: The voxel-wise standard deviation of the signal (variability along time).
+  - bids: {datatype: figures, desc: background}
+    caption: This panel shows a mosaic enhancing the background around the head.
+      Artifacts usually unveil themselves in the air surrounding the head, where no signal
+      sources are present.
+    subtitle: View of the background of the voxel-wise average of the BOLD timeseries
+  - bids: {datatype: figures, desc: zoomed}
+    caption: This panel shows a mosaic of the brain. This mosaic is the most suitable to
+      screen head-motion intensity inhomogeneities, global/local noise, signal leakage
+      (for example, from the eyeballs and across the phase-encoding axis), etc.
+    subtitle: Voxel-wise average of BOLD time-series, zoomed-in covering just the brain
   - bids: {datatype: figures, desc: carpet}
     subtitle: Carpetplot and nuisance signals
     caption: The so-called «carpetplot» may assist in assessing head-motion
       derived artifacts and respiation effects.
+
+- name: Extended echo-wise reports
+  ordering: echo
+  reportlets:
+  - bids: {datatype: figures, desc: mean}
+    subtitle: Voxel-wise average of BOLD time-series
+    caption: The average signal calculated across the last axis (time).
+
 - name: Extended reports shared across echos
   reportlets:
   - bids: {datatype: figures, desc: brainmask}
@@ -54,23 +72,6 @@ sections:
     subtitle: Spatial normalization of the anatomical image
     static: false
 
-- name: Extended echo-wise reports
-  ordering: echo
-  reportlets:
-  - bids: {datatype: figures, desc: background}
-    caption: This panel shows a mosaic enhancing the background around the head.
-      Artifacts usually unveil themselves in the air surrounding the head, where no signal
-      sources are present.
-    subtitle: View of the background of the voxel-wise average of the BOLD timeseries
-  - bids: {datatype: figures, desc: mean}
-    subtitle: Average signal through time
-    caption: The average signal calculated across the last axis (time).
-  - bids: {datatype: figures, desc: zoomed}
-    caption: This panel shows a mosaic of the brain. This mosaic is the most suitable to
-      screen head-motion intensity inhomogeneities, global/local noise, signal leakage
-      (for example, from the eyeballs and across the phase-encoding axis), etc.
-    subtitle: Voxel-wise average of BOLD time-series, zoomed-in covering just the brain
-
 - name: About
   nested: true
   reportlets:

mriqc/interfaces/__init__.py

@@ -32,7 +32,7 @@
 )
 from mriqc.interfaces.bids import IQMFileSink
 from mriqc.interfaces.common import ConformImage, EnsureSize
-from mriqc.interfaces.functional import FunctionalQC, Spikes
+from mriqc.interfaces.functional import FunctionalQC, GatherTimeseries, Spikes
 from mriqc.interfaces.webapi import UploadIQMs
 
 
@@ -47,6 +47,7 @@ class DerivativesDataSink(_DDSink):
     "DerivativesDataSink",
     "EnsureSize",
     "FunctionalQC",
+    "GatherTimeseries",
     "Harmonize",
     "IQMFileSink",
     "RotationMask",

mriqc/interfaces/functional.py

@@ -38,6 +38,8 @@
     traits,
     Undefined,
 )
+from nipype.utils.misc import normalize_mc_params
+import pandas as pd
 
 
 class FunctionalQCInputSpec(BaseInterfaceInputSpec):
@@ -309,6 +311,185 @@ def _run_interface(self, runtime):
         return runtime
 
 
+class GatherTimeseriesInputSpec(TraitedSpec):
+    dvars = File(exists=True, mandatory=True, desc='file containing DVARS')
+    fd = File(exists=True, mandatory=True, desc='input framewise displacement')
+    mpars = File(exists=True, mandatory=True, desc='input motion parameters')
+    mpars_source = traits.Enum(
+        "FSL",
+        "AFNI",
+        "SPM",
+        "FSFAST",
+        "NIPY",
+        desc="Source of movement parameters",
+        mandatory=True,
+    )
+    outliers = File(
+        exists=True,
+        mandatory=True,
+        desc="input file containing timeseries of AFNI's outlier count")
+    quality = File(
+        exists=True,
+        mandatory=True,
+        desc="input file containing AFNI's Quality Index")
+
+
+class GatherTimeseriesOutputSpec(TraitedSpec):
+    timeseries_file = File(desc='output confounds file')
+    timeseries_metadata = traits.Dict(desc='Metadata dictionary describing columns')
+
+
+class GatherTimeseries(SimpleInterface):
+    """
+    Gather quality metrics that are timeseries into one TSV file
+
+    """
+    input_spec = GatherTimeseriesInputSpec
+    output_spec = GatherTimeseriesOutputSpec
+
+    def _run_interface(self, runtime):
+
+        # motion parameters
+        mpars = np.apply_along_axis(
+            func1d=normalize_mc_params,
+            axis=1,
+            arr=np.loadtxt(self.inputs.mpars),  # mpars is N_t x 6
+            source=self.inputs.mpars_source,
+        )
+        timeseries = pd.DataFrame(
+            mpars,
+            columns=[
+                "trans_x",
+                "trans_y",
+                "trans_z",
+                "rot_x",
+                "rot_y",
+                "rot_z"
+            ])
+
+        # DVARS
+        dvars = pd.read_csv(
+            self.inputs.dvars,
+            delim_whitespace=True,
+            skiprows=1,  # column names have spaces
+            header=None,
+            names=["dvars_std", "dvars_nstd", "dvars_vstd"])
+        dvars.index = pd.RangeIndex(1, timeseries.index.max() + 1)
+
+        # FD
+        fd = pd.read_csv(
+            self.inputs.fd,
+            delim_whitespace=True,
+            header=0,
+            names=["framewise_displacement"])
+        fd.index = pd.RangeIndex(1, timeseries.index.max() + 1)
+
+        # AQI
+        aqi = pd.read_csv(
+            self.inputs.quality,
+            delim_whitespace=True,
+            header=None,
+            names=["aqi"])
+
+        # Outliers
+        aor = pd.read_csv(
+            self.inputs.outliers,
+            delim_whitespace=True,
+            header=None,
+            names=["aor"])
+
+        timeseries = pd.concat((timeseries, dvars, fd, aqi, aor), axis=1)
+
+        timeseries_file = op.join(runtime.cwd, "timeseries.tsv")
+
+        timeseries.to_csv(timeseries_file, sep='\t', index=False, na_rep='n/a')
+
+        self._results['timeseries_file'] = timeseries_file
+        self._results['timeseries_metadata'] = _build_timeseries_metadata()
+        return runtime
+
+
+def _build_timeseries_metadata():
+    return {
+        "trans_x": {
+            "LongName": "Translation Along X Axis",
+            "Description": "Estimated Motion Parameter",
+            "Units": "mm"
+        },
+        "trans_y": {
+            "LongName": "Translation Along Y Axis",
+            "Description": "Estimated Motion Parameter",
+            "Units": "mm"
+        },
+        "trans_z": {
+            "LongName": "Translation Along Z Axis",
+            "Description": "Estimated Motion Parameter",
+            "Units": "mm",
+        },
+        "rot_x": {
+            "LongName": "Rotation Around X Axis",
+            "Description": "Estimated Motion Parameter",
+            "Units": "rad"
+        },
+        "rot_y": {
+            "LongName": "Rotation Around X Axis",
+            "Description": "Estimated Motion Parameter",
+            "Units": "rad"
+        },
+        "rot_z": {
+            "LongName": "Rotation Around X Axis",
+            "Description": "Estimated Motion Parameter",
+            "Units": "rad"
+        },
+        "dvars_std": {
+            "LongName": "Derivative of RMS Variance over Voxels, Standardized",
+            "Description": (
+                "Indexes the rate of change of BOLD signal across"
+                "the entire brain at each frame of data, normalized with the"
+                "standard deviation of the temporal difference time series"
+            )
+        },
+        "dvars_nstd": {
+            "LongName": (
+                "Derivative of RMS Variance over Voxels,"
+                "Non-Standardized"
+            ),
+            "Description": (
+                "Indexes the rate of change of BOLD signal across"
+                "the entire brain at each frame of data, not normalized."
+            )
+        },
+        "dvars_vstd": {
+            "LongName": "Derivative of RMS Variance over Voxels, Standardized",
+            "Description": (
+                "Indexes the rate of change of BOLD signal across"
+                "the entire brain at each frame of data, normalized across"
+                "time by that voxel standard deviation across time,"
+                "before computing the RMS of the temporal difference"
+            )
+        },
+        "framewise_displacement": {
+            "LongName": "Framewise Displacement",
+            "Description": (
+                "A quantification of the estimated bulk-head"
+                "motion calculated using formula proposed by Power (2012)"
+            ),
+            "Units": "mm"
+        },
+        "aqi": {
+            "LongName": "AFNI's Quality Index",
+            "Description": "Mean quality index as computed by AFNI's 3dTqual"
+        },
+        "aor": {
+            "LongName": "AFNI's Fraction of Outliers per Volume",
+            "Description": (
+                "Mean fraction of outliers per fMRI volume as"
+                "given by AFNI's 3dToutcount"
+            )
+        }
+    }
+
+
 def find_peaks(data):
     t_z = [data[:, :, i, :].mean(axis=0).mean(axis=0) for i in range(data.shape[2])]
     return t_z

mriqc/reports/group.py

@@ -200,6 +200,7 @@ def gen_html(csv_file, mod, csv_failed=None, out_file=None):
                 None,
             ),
         ],
+        "dwi": [],
     }
 
     if csv_file.suffix == ".csv":

mriqc/workflows/diffusion/output.py

@@ -44,7 +44,7 @@ def init_dwi_report_wf(name="dwi_report_wf"):
             wf = init_dwi_report_wf()
 
     """
-    from niworkflows.interfaces.plotting import FMRISummary
+    from nireports.interfaces import FMRISummary
     from niworkflows.interfaces.morphology import BinaryDilation, BinarySubtraction
 
     from nireports.interfaces import PlotMosaic, PlotSpikes