Add BCT metrics projection widget

notebooks/BCT_metrics_projection.ipynb

@@ -0,0 +1,54 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b572799a",
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from tvb.datatypes.connectivity import Connectivity\n",
+    "from tvbwidgets.ui.bct.bct_metrics_widget import BCTMetricsProjectionWidget\n",
+    "\n",
+    "conn = Connectivity.from_file()\n",
+    "conn.configure()\n",
+    "\n",
+    "wid = BCTMetricsProjectionWidget(conn)\n",
+    "wid.display()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "67a11694-f552-4ae0-8d34-725a0c0c8405",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

tvbwidgets/ui/bct/bct_compat.py

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+
+import numpy as np
+import bct.algorithms.modularity as _bct_modularity
+def apply_bct_patches():
+
+    if getattr(_bct_modularity, "_tvb_ls2ci_patched", False):
+        return
+
+    def _patched_ls2ci(ls, zeroindexed=False):
+        if ls is None or len(ls) == 0:
+            return ()
+
+        nr_indices = sum(map(len, ls))
+        ci = np.zeros((nr_indices,), dtype=int)
+        z = int(not zeroindexed)
+
+        for i, group in enumerate(ls):
+            for node in group:
+                ci[node] = i + z
+
+        return ci
+
+    _bct_modularity.ls2ci = _patched_ls2ci
+    _bct_modularity._tvb_ls2ci_patched = True

tvbwidgets/ui/bct/bct_helper_widgets.py

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+
+import numpy as np
+import ipywidgets as widgets
+import k3d
+
+from tvbwidgets.ui.head_widget import HeadWidget
+from tvbwidgets.ui.connectivity_matrix_editor_widget import ConnectivityMatrixEditor
+
+class BCTConnectivityMatrixEditor(ConnectivityMatrixEditor):
+    """ConnectivityMatrixEditor stripped to weights tab only."""
+
+    def __init__(self, connectivity, **kwargs):
+        super().__init__(connectivity, **kwargs)
+        self.tab.children = [self.tab.children[0]]
+        self.tab.set_title(0, "weights")
+
+class BCTTractLengthsMatrixEditor(ConnectivityMatrixEditor):
+    """ConnectivityMatrixEditor stripped to tract_lengths tab only.
+    """
+
+    def __init__(self, connectivity, **kwargs):
+        super().__init__(connectivity, **kwargs)
+        self.tab.children = [self.tab.children[1]]
+        self.tab.set_title(0, "tract_lengths")
+
+class ColoredConnectivityHeadWidget(HeadWidget):
+    """HeadWidget with per-node coloring driven by BCT metric values."""
+
+    def __init__(self, datatypes, node_values=None, region_labels=None, **kwargs):
+        self.node_values = node_values
+        self.region_labels = region_labels
+        super().__init__(datatypes, **kwargs)
+
+    def _HeadWidget__draw_connectivity(self, connectivity):
+        self._centres = connectivity.centres
+        self._labels = (
+            self.region_labels if self.region_labels is not None
+            else connectivity.region_labels
+        )
+
+        values = self.node_values if self.node_values is not None else np.ones(len(connectivity.centres))
+        values = np.array(values, dtype=float)
+        values[np.isinf(values)] = 0
+        values[np.isnan(values)] = 0
+        self._values = values
+
+        vmin, vmax = float(values.min()), float(values.max())
+        if vmin == vmax:
+            vmin -= 0.5
+            vmax += 0.5
+
+        self._points_obj = k3d.points(
+            connectivity.centres,
+            point_size=8,
+            shader='dot',
+            attribute=values,
+            color_map=k3d.matplotlib_color_maps.viridis,
+            color_range=[vmin, vmax],
+        )
+
+        edge_indices = np.nonzero(connectivity.weights)
+        edges = list(zip(edge_indices[0], edge_indices[1]))
+        lines = k3d.lines(
+            connectivity.centres,
+            indices=edges,
+            shader='simple',
+            color=0xffffff,
+            width=2,
+        )
+
+        self.plot += self._points_obj
+        self.plot += lines
+
+    def display(self):
+        pass