Jupyter notebooks are ready for flatland3.

But they should be overworked. Might just one example per use case would be much more clear. TODO - cleanup

flatland/utils/jupyter_utils.py

 from typing import List, NamedTuple
 
+import numpy as np
 from IPython import display
 from ipycanvas import canvas
 
@@ -111,7 +112,12 @@ class EnvCanvas():
 
     def render(self):
         self.oRT.render_env(show_rowcols=True, show_inactive_agents=False, show_observations=False)
-        self.oCan.put_image_data(self.oRT.get_image()[:, :, 0:3])
+        gIm = self.oRT.get_image()
+        red_channel = gIm[:, :, 0]
+        blue_channel = gIm[:, :, 1]
+        green_channel = gIm[:, :, 2]
+        image_data = np.stack((red_channel, blue_channel, green_channel), axis=2)
+        self.oCan.put_image_data(image_data)
 
     def step(self):
         dAction = self.behaviour.getActions()

notebooks/flatland_animate.ipynb

@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19,10 +19,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
+    "import numpy as np\n",
     "import time\n",
     "from IPython import display\n",
     "from ipycanvas import canvas\n",
@@ -34,9 +35,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "pickle failed to load file: complex_scene_2.pkl  trying msgpack (deprecated)...\n",
+      "pickle failed to load file: complex_scene_2.pkl  trying msgpack (deprecated)...\n",
+      "pickle failed to load file: complex_scene_2.pkl  trying msgpack (deprecated)...\n",
+      "This env file has no max_episode_steps (deprecated) - setting to 100\n"
+     ]
+    }
+   ],
    "source": [
     "env, env_dict = RailEnvPersister.load_new(\"complex_scene_2.pkl\", load_from_package=\"env_data.railway\")\n",
     "_ = env.reset()\n",
@@ -49,7 +61,22 @@
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1989b7cb08b74047a8bdc81eca1917a6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Canvas()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "oRT = RenderTool(env, gl=\"PILSVG\", jupyter=False, show_debug=True)\n",
     "image_arr = oRT.get_image()\n",
@@ -65,25 +92,13 @@
     "    obs, rew, done, info = env.step(actions)\n",
     "    oRT.render_env(show_observations=False,show_predictions=False)\n",
     "    gIm = oRT.get_image()\n",
-    "    oCanvas.put_image_data(gIm[:,:,0:3])\n",
+    "    red_channel = gIm[:,:,0]\n",
+    "    blue_channel = gIm[:,:,1]\n",
+    "    green_channel = gIm[:,:,2]\n",
+    "    image_data = np.stack((red_channel, blue_channel, green_channel), axis=2)\n",
+    "    oCanvas.put_image_data(image_data)\n",
     "    time.sleep(0.1)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    ".shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {