Cleaned example for clustering

Author: avmarchenko

docs/source/notebooks/04_cluster_extraction.ipynb

@@ -322,7 +322,7 @@
     "dct = periodic_nearest_neighbors_by_atom(u,       # Universe with all frames from which we want to extract clusters\n",
     "                                         \"Rh\",    # Source atom from which we will search for neighbors\n",
     "                                         a,       # Cubic cell dimension\n",
-    "                                         # Cluster sizes we want (increasing the number here doesn't change how long the function takes)\n",
+    "                                         # Cluster sizes we want\n",
     "                                         [0, 1, 2, 3, 4, 8, 12, 16],\n",
     "                                         # Additional arguments to be passed to the atomic two body calculation\n",
     "                                         # Note that it is critical to increase dmax (in compute_atom_two)!!!\n",
@@ -451,39 +451,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "exatomic.UniverseWidget(dct[8])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a6affab55b674876b30baaca3aa1b092",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "UniverseWidget(active_scene_indices=[0], children=(GUIBox(children=(Button(description=' Close', icon='trash',…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "exatomic.UniverseWidget(dct[16])"
+    "exatomic.UniverseWidget(dct[0])    # Just the analyte"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "exatomic.UniverseWidget(dct[16])   # View the universe with 16 nearest molecules"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -494,15 +472,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 20.9 s, sys: 3.75 s, total: 24.6 s\n",
-      "Wall time: 24.9 s\n"
+      "CPU times: user 3.17 s, sys: 281 ms, total: 3.45 s\n",
+      "Wall time: 3.51 s\n"
      ]
     }
    ],
@@ -514,16 +492,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "86.07053661346436"
+       "10.53761100769043"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,17 +510,14 @@
     "u.memory_usage().sum()/1024**2    # RAM usage (MB)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "exatomic.UniverseWidget(u)"
+   ]
   },
   {
    "cell_type": "code",