TST: Run fMRI notebook on push and print output

Author: jhlegarreta

.github/workflows/notebooks.yml

@@ -1,6 +1,14 @@
 name: Run notebooks
 
 on:
+  push:
+    branches:
+      - main
+      - maint/*
+  pull_request:
+    branches:
+      - main
+      - maint/*
   schedule:
     - cron: '0 0 * * 1'  # Every Monday at 00:00 UTC
   # Allow job to be triggered manually from GitHub interface
@@ -99,5 +107,17 @@ jobs:
         run: |
           ${{ github.workspace }}/scripts/fetch_fmri_nb_openneuro_data.sh "${TEST_DATA_HOME}"
 
+      - name: Install notebook env dependencies from tox
+        run:  |
+          tox run -e notebooks --notest
+
       - name: Run notebooks with tox
-        run: tox -e notebooks
+        # run: tox -e notebooks
+        run: |
+          pip install nbconvert jupyter
+          pip install nbval
+          # jupyter nbconvert --to notebook --execute ${{ github.workspace }}/docs/notebooks/bold_realignment.ipynb \
+          #   --output executed_bold_realignment.ipynb
+          # jupyter nbconvert --to python ${{ github.workspace }}/docs/notebooks/bold_realignment.ipnb
+          python ${{ github.workspace }}/docs/notebooks/bold_realignment.py
+          # pytest -s --nbval ${{ github.workspace }}/docs/notebooks/bold_realignment.ipynb

docs/notebooks/bold_realignment.ipynb

@@ -81,7 +81,27 @@
     "    if not DATA_PATH.exists() or not DATA_PATH.is_dir():\n",
     "        raise FileNotFoundError(f\"Directory does not exist: {DATA_PATH}\")\n",
     "\n",
+    "    import hashlib\n",
+    "    model_path = DATA_PATH / \"synthstrip.1.pt\"\n",
+    "    md5_hash = hashlib.md5()\n",
+    "    try:\n",
+    "        with open(model_path, \"rb\") as file:\n",
+    "            # Read the file in chunks to handle large files efficiently\n",
+    "            for chunk in iter(lambda: file.read(4096), b\"\"):\n",
+    "                md5_hash.update(chunk)\n",
+    "    except FileNotFoundError:\n",
+    "        raise FileNotFoundError(f\"File not found.\")\n",
+    "\n",
+    "    md5_value = md5_hash.hexdigest()\n",
+    "    print(f\"The MD5 hash of {model_path} is: {md5_value}\")\n",
+    "\n",
     "    if not bmask_path.exists():\n",
+    "        bmsk_results = SynthStrip(\n",
+    "            in_file=str(avg_path),\n",
+    "            use_gpu=True,\n",
+    "            model=model_path,\n",
+    "        ).run(cwd=str(WORKDIR))\n",
+    "\n",
     "        ssiface = SynthStrip(\n",
     "            in_file=str(avg_path),\n",
     "            use_gpu=True,\n",