Fix activation function bug causing this demo to break

Author: TomGeorge1234

demos/path_integration_example.ipynb

@@ -441,7 +441,7 @@
     "Env = Environment(params={\"dimensionality\": \"1D\", \"boundary_conditions\": \"periodic\"})\n",
     "\n",
     "# Put agent (who will move randomly under the ratinabox Ornstein Uhlenbeck random motion policy) inside the environement\n",
-    "Ag = Agent(Env, params={'dt':0.01})\n",
+    "Ag = Agent(Env, params={'dt':0.02})\n",
     "Ag.speed_mean = 0\n",
     "Ag.speed_std = 0.3\n",
     "\n",
@@ -461,6 +461,11 @@
     "    params={\n",
     "        \"n\": n_cells,\n",
     "        \"name\": \"ConjunctiveCells_left\",\n",
+    "        # nb. this tutorial is now quite old so the way that FeedForwardLayer --- define in the main codebase --- activations are set (passing \"activation_function\" at initialisation) no longer matches the way DendriticCompartment --- defined above --- activations are set (setting \"activation_params\" after initialisation). Sorry about this! TODO: update DendriticCompartment to be FeedForwardLayer subclass\n",
+    "        \"activation_function\": {\n",
+    "            \"activation\": \"relu\",\n",
+    "            \"threshold\": 1,\n",
+    "            }\n",
     "    },\n",
     ")\n",
     "\n",
@@ -469,6 +474,10 @@
     "    params={\n",
     "        \"n\": n_cells,\n",
     "        \"name\": \"ConjunctiveCells_right\",\n",
+    "        \"activation_function\": {\n",
+    "            \"activation\": \"relu\",\n",
+    "            \"threshold\": 1,\n",
+    "            }\n",
     "    },\n",
     ")\n",
     "\n",
@@ -497,17 +506,7 @@
     "    [-1, 1]\n",
     ")  # thus right velocity excites these cells and rigleftht velocity shuts them off\n",
     "ConjunctiveCells_left.inputs[\"RingAttractor\"][\"w\"] = np.identity(n_cells)\n",
-    "ConjunctiveCells_right.inputs[\"RingAttractor\"][\"w\"] = np.identity(n_cells)\n",
-    "ConjunctiveCells_left.activation_params = {\n",
-    "    \"activation\": \"relu\",\n",
-    "    \"threshold\": 1,\n",
-    "    \"width_x\": 2,\n",
-    "}\n",
-    "ConjunctiveCells_right.activation_params = {\n",
-    "    \"activation\": \"relu\",\n",
-    "    \"threshold\": 1,\n",
-    "    \"width_x\": 2,\n",
-    "}"
+    "ConjunctiveCells_right.inputs[\"RingAttractor\"][\"w\"] = np.identity(n_cells)"
    ]
   },
   {
@@ -516,7 +515,7 @@
    "source": [
     "### Train the network\n",
     "\n",
-    "Train it for 20 minutes"
+    "Train it for 60 minutes"
    ]
   },
   {
@@ -525,7 +524,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "for i in tqdm(range(int(10 * 60 / Ag.dt))):\n",
+    "for i in tqdm(range(int(60 * 60 / Ag.dt))):\n",
     "    # update agent\n",
     "    Ag.update()\n",
     "    # update firing rates of all the cell layers\n",
@@ -556,6 +555,7 @@
    "source": [
     "fig, ax = RingAttractor.plot_loss()\n",
     "\n",
+    "save_plots = False\n",
     "if save_plots == True:\n",
     "    tpl.saveFigure(fig, \"PI_loss\")"
    ]