Creating nireports

physioqc/data/bootstrap.yml

@@ -0,0 +1,79 @@
+# Copyright 2023 The NiPreps Developers <[email protected]>
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# We support and encourage derived works from this project, please read
+# about our expectations at
+#
+#     https://www.nipreps.org/community/licensing/
+#
+###########################################################################
+# Reports bootstrap file
+# ======================
+# This is a YAML-formatted file specifying how the NiReports assembler
+# will search for "reportlets" and compose them into a report file,
+# typically in HTML format.
+###########################################################################
+
+packagename: physioqc
+title: '{filename} :: Respiration QC Report (rawdata)'
+sections:
+- name: Rawdata
+  reportlets:
+  - bids: {datatype: figures, desc: raw}
+    caption: Here we see the rawdata over time.
+    style:
+      max-height: 700px
+- name: Average peak
+  reportlets:
+  - bids: {datatype: figures, desc: average}
+    caption: This panel shows the average peak, and its errobars (or traces).
+    style:
+      max-height: 700px
+- name: Power spectrum
+  reportlets:
+  - bids: {datatype: figures, desc: power}
+    caption: Plot of the power spectrum for the raw signal.
+    style:
+      max-height: 700px
+- name: Histogram of peak amplitudes
+  reportlets:
+  - bids: {datatype: figures, desc: histpeakamp}
+    caption: Histogram of peak amplitudes.
+    style:
+      max-height: 700px
+- name: Histogram of peak distances
+  reportlets:
+  - bids: {datatype: figures, desc: histpeakdist}
+    caption: Histogram of peak distanes.
+    style:
+      max-height: 700px
+
+- name: Others
+  nested: true
+  reportlets:
+  - metadata: "input"
+    settings:
+      # By default, only the first dictionary will be expanded.
+      # If folded is true, all will be folded. If false all expanded.
+      # If an ID is not provided, one should be generated automatically
+      id: 'about-metadata'
+  - custom: errors
+    path: '{reportlets_dir}/{run_uuid}'
+    captions: <em>PhysioQC</em> may have recorded failure conditions.
+    title: Errors
+
+# Rating widget
+plugins:
+- module: nireports.assembler
+  path: data/rating-widget/bootstrap.yml

physioqc/interfaces/interfaces.py

@@ -2,11 +2,19 @@
 
 import matplotlib.pyplot as plt
 import pandas as pd
+from bids import layout
 
 from physioqc.metrics.multimodal import peak_amplitude, peak_detection, peak_distance
 
+# Save pattern as global
+pattern = (
+    "sub-{subject}[_ses-{session}]_task-{task}[_acq-{acquisition}]"
+    + "[_rec-{reconstruction}][_run-{run}][_echo-{echo}]"
+    + "[_desc-{description}]_{suffix}.{extension}"
+)
 
-def generate_figures(figures, data, outdir):
+
+def generate_figures(figures, data, outdir, entities):
     """
     Generates all the figure needed to populate the visual report.
     Save the figures in the 'figures' folder
@@ -17,9 +25,22 @@ def generate_figures(figures, data, outdir):
         A list of functions to run to generate all the figures.
     data : np.array or peakdet Physio object
         Physiological data
+    outdir: str
+        The path to the output directory.
+    entities: dictionary
+        A dictionary of bids entities used to write out the files.
     """
     # Create the output directory if not existing
-    os.makedirs(os.path.join(outdir, "figures"), exist_ok=True)
+    sub_folders = []
+    for k in ["subject", "session"]:
+        if k in entities:
+            sub_folders.append("-".join([k[:3], entities[k]]))
+
+    out_folder = os.path.join(outdir, *sub_folders, "figures")
+    os.makedirs(out_folder, exist_ok=True)
+
+    out_entities = {k: v for k, v in entities.items()}
+    out_entities.update({"description": "", "extension": ".svg"})
 
     for figure in figures:
         # Get the plot name from the name of the function that was ran
@@ -35,21 +56,35 @@ def generate_figures(figures, data, outdir):
             peak_dist = peak_distance(data)
             fig, _ = figure(peak_dist)
 
-            plot_name = "histogram_peak_distance"
+            out_entities["description"] = "histpeakdist"
             # TO IMPLEMENT the subject name should be automatically read when the data are loaded
-            fig.savefig(os.path.join(outdir, "figures", f"sub-01_desc-{plot_name}.svg"))
+            fig.savefig(
+                os.path.join(
+                    out_folder, layout.writing.build_path(out_entities, pattern)
+                )
+            )
 
             # Plot histogram of peak amplitude
             peak_ampl = peak_amplitude(data)
             fig, _ = figure(peak_ampl)
 
-            plot_name = "histogram_peak_distance"
-            fig.savefig(os.path.join(outdir, "figures", f"sub-01_desc-{plot_name}.svg"))
-
+            out_entities["description"] = "histpeakamp"
+            # TO IMPLEMENT the subject name should be automatically read when the data are loaded
+            fig.savefig(
+                os.path.join(
+                    out_folder, layout.writing.build_path(out_entities, pattern)
+                )
+            )
         else:
             fig, _ = figure(data)
             # Save the figure
-            fig.savefig(os.path.join(outdir, "figures", f"sub-01_desc-{plot_name}.svg"))
+            out_entities["description"] = plot_name
+            # TO IMPLEMENT the subject name should be automatically read when the data are loaded
+            fig.savefig(
+                os.path.join(
+                    out_folder, layout.writing.build_path(out_entities, pattern)
+                )
+            )
 
 
 def run_metrics(metrics_dict, data):
@@ -90,7 +125,7 @@ def run_metrics(metrics_dict, data):
     return metrics_df
 
 
-def save_metrics(metrics_df, outdir, to_csv=False):
+def save_metrics(metrics_df, outdir, entities, to_csv=False):
     """
     Save the metrics in the defined output path
 
@@ -109,8 +144,24 @@ def save_metrics(metrics_df, outdir, to_csv=False):
         A dataframe containing the value of each metric
     """
     # TO IMPLEMENT : there may be a bug associated to the next line IsDirectoryError
-    os.makedirs(outdir, exist_ok=True)
+    sub_folders = []
+    for k in ["subject", "session"]:
+        if k in entities:
+            sub_folders.append("-".join([k[:3], entities[k]]))
+
+    out_folder = os.path.join(outdir, *sub_folders)
+    os.makedirs(out_folder, exist_ok=True)
+
+    out_entities = {k: v for k, v in entities.items()}
+
     if to_csv:
-        metrics_df.to_csv(os.path.join(outdir, "metrics.csv"), index=False)
+        out_entities.update({"description": "metrics", "extension": ".csv"})
+        metrics_df.to_csv(
+            os.path.join(out_folder, layout.writing.build_path(out_entities, pattern)),
+            index=False,
+        )
     else:
-        metrics_df.to_json(os.path.join(outdir, "metrics.json"))
+        out_entities.update({"description": "metrics", "extension": ".json"})
+        metrics_df.to_json(
+            os.path.join(out_folder, layout.writing.build_path(out_entities, pattern))
+        )

physioqc/workflow.py

@@ -4,6 +4,8 @@
 
 import numpy as np
 import peakdet as pk
+from bids import layout
+from nireports.assembler.report import Report
 
 from physioqc.cli.run import _get_parser
 from physioqc.interfaces.interfaces import generate_figures, run_metrics, save_metrics
@@ -25,6 +27,10 @@
     std,
 )
 
+BOOTSTRAP_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "data"))
+
+print("BOOTSTRAP path", BOOTSTRAP_PATH)
+
 
 def save_bash_call(outdir):
     """
@@ -74,6 +80,9 @@ def physioqc(
 
     figures = [plot_average_peak, plot_histogram, plot_power_spectrum, plot_raw_data]
 
+    # Stand in for further BIDS support:
+    bids_entities = layout.parse_file_entities(filename=filename)
+
     # Load the data
     d = np.genfromtxt(filename)
 
@@ -88,10 +97,40 @@ def physioqc(
     metrics_df = run_metrics(metrics, data)
 
     # Generate figures
-    generate_figures(figures, data, outdir)
+    generate_figures(figures, data, outdir, bids_entities)
 
     # Save the metrics in the output folder
-    save_metrics(metrics_df, outdir)
+    save_metrics(metrics_df, outdir, bids_entities)
+
+    metric_dict = metrics_df.to_dict(orient="list")
+    metric_dict = {i: j for i, j in zip(metric_dict["Metric"], metric_dict["Value"])}
+    metadata = {
+        "about-metadata": {
+            "Metrics": metric_dict,
+            "Version": {"version": "pre functional, Definitely does not work yet ;)"},
+        }
+    }
+
+    filters = {k: bids_entities[k] for k in ["subject"]}
+
+    sub_folders = []
+    for k in ["subject", "session"]:
+        if k in bids_entities:
+            sub_folders.append("-".join([k[:3], bids_entities[k]]))
+
+    out_folder = os.path.join(outdir, *sub_folders, "figures")
+
+    robj = Report(
+        outdir,
+        "test",
+        reportlets_dir=out_folder,
+        bootstrap_file=os.path.join(BOOTSTRAP_PATH, "bootstrap.yml"),
+        metadata=metadata,
+        plugin_meta={},
+        **filters,
+    )
+
+    robj.generate_report()
 
 
 def _main(argv=None):

setup.cfg

@@ -28,6 +28,7 @@ install_requires =
     pandas
     peakdet
     duecredit
+    nireports
 tests_require =
     pytest >=5.3
 test_suite = pytest