ohbm 2023: update to siibra v1.0a14

ohbm-2023-example.ipynb

@@ -23,7 +23,7 @@
    "source": [
     "import siibra as sb\n",
     "from packaging.version import Version\n",
-    "assert Version(sb.__version__) >= Version('1.0a08')\n",
+    "assert Version(sb.__version__) >= Version('1.0a14')\n",
     "from nilearn import plotting\n",
     "import matplotlib.pyplot as plt\n",
     "%matplotlib notebook"
@@ -185,25 +185,25 @@
     "# row 1 - receptor densities for different receptor types\n",
     "for i, m in enumerate(matches.itertuples()):\n",
     "    features = sb.features.get(\n",
-    "        m.Region, \n",
+    "        m.region, \n",
     "        sb.features.molecular.ReceptorDensityFingerprint\n",
     "    )\n",
     "    features[0].plot(ax=axs[0, i])\n",
     "\n",
     "# row 2 - cell densities per cortical layer\n",
     "for i, m in enumerate(matches.itertuples()):\n",
     "    features = sb.features.get(\n",
-    "        m.Region, \n",
+    "        m.region, \n",
     "        sb.features.cellular.LayerwiseCellDensity\n",
     "    )\n",
     "    features[0].plot(ax=axs[1, i])\n",
     "        \n",
     "# row 3 - structural connectivity profiles\n",
     "for i, m in enumerate(matches.itertuples()):\n",
     "    features = sb.features.get(\n",
-    "        m.Region.parcellation, sb.features.connectivity.StreamlineLengths\n",
+    "        m.region.parcellation, sb.features.connectivity.StreamlineLengths\n",
     "    )\n",
-    "    f = features[0].get_profile(m.Region, max_rows=12)\n",
+    "    f = features[0][0].get_profile(m.region, max_rows=12)\n",
     "    f.plot(ax=axs[2, i])\n",
     "\n",
     "# optimize plot layout\n",
@@ -258,7 +258,7 @@
     "# from the full resolution Big Brain (20 micron) at this position.\n",
     "for i, match in enumerate(matches.itertuples()):\n",
     "\n",
-    "    point = julich_pmaps.sample_locations(match.Region, 1)[0].warp('bigbrain')\n",
+    "    point = julich_pmaps.sample_locations(match.region, 1)[0].warp('bigbrain')\n",
     "    view = plotting.plot_img(bigbrain_volume, axes=axs[0, i], cut_coords=tuple(point), **plot_kwargs)\n",
     "    view.add_markers([tuple(point)])\n",
     "\n",
@@ -294,7 +294,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.9.15"
   },
   "vscode": {
    "interpreter": {