Section 6.4 done

Author: dellaert

S63_driving_sensing.ipynb

@@ -738,82 +738,7 @@
    "source": [
     "### Reading and Visualizing LIDAR clouds\n",
     "\n",
-    "The utility functions `read_lidar_points` and `visualize_clouds` are not part of GTSAM, but are part of the gtbook library that accompanies this book. On the [gtbook website](https://gtbook.github.io/gtbook/driving.html) you can find much more detailed documentation as well as the source code, but `help` is very comprehensive for those functions:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7CJmeFWrnGA8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Help on function read_lidar_points in module gtbook.driving:\n",
-      "\n",
-      "read_lidar_points(filename: str)\n",
-      "    Read 3D points in LIDAR scan stored as a binary_little_endian .ply file.\n",
-      "    \n",
-      "    Parameters:\n",
-      "        filename: of ply file\n",
-      "    \n",
-      "    Returns:\n",
-      "        A tuple (3,N) numpy array.\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "help(driving.read_lidar_points)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "RG3QiiDS08-U",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Help on function visualize_clouds in module gtbook.driving:\n",
-      "\n",
-      "visualize_clouds(clouds: list, show_grid_lines: bool = False, cloud_colors=None, marker_size: int = 1, do_subsampling: bool = True)\n",
-      "    Visualizes cloud(s) in a iterative 3D plot.\n",
-      "        Adapted from code by 3630 TAs Binit Shah and Jerred Chen\n",
-      "    \n",
-      "    Due to browser limitations, rendering above 5 frames requires\n",
-      "    subsampling of the point clouds, which is done automatically.\n",
-      "    \n",
-      "    Example input of arg:\n",
-      "    clouds = [clouda, cloudb, cloudc]\n",
-      "    where each cloud is a numpy array of shape (3, num_points).\n",
-      "    cloud[0] are the x coordinates, cloud[1] is y, and cloud[2] is z.\n",
-      "    \n",
-      "    Args:\n",
-      "        clouds (list):          ordered series of point clouds\n",
-      "        show_grid_lines (bool): plots gridlines\n",
-      "        cloud_colors (list):    colors for each cloud in the visualization\n",
-      "        marker_size (int):      size of each marker\n",
-      "        do_subsampling (bool):  whether or not subsampling occurs\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "help(driving.visualize_clouds)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "-JuzVChgrl5z",
-   "metadata": {},
-   "source": [
-    "{raw:tex}`\\noindent`\n",
-    "While the visualization code is statically rendered in the book, when you open the Colab things should be rendered as interactive plotly scatter plots. Try it!"
+    "The utility functions `read_lidar_points` and `visualize_clouds` are not part of GTSAM, but are part of the gtbook library that accompanies this book. On the [gtbook website](https://gtbook.github.io/gtbook/driving.html) {cite:p}`gtbook` you can find much more detailed documentation as well as the source code, but `help` is very comprehensive for those functions. While the visualization code is statically rendered in the book, when you open the Colab things should be rendered as interactive `plotly` scatter plots. Try it!"
    ]
   }
  ],