Finalise the refactor. It works well now.

src/primaite/notebooks/uc2_demo.ipynb

@@ -335,9 +335,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%load_ext autoreload\n",
@@ -347,9 +345,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Imports\n",
@@ -372,9 +368,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# create the env\n",
@@ -385,10 +379,10 @@
     "    cfg['simulation']['network']['nodes'][9]['applications'][0]['options']['data_manipulation_p_of_success'] = 1.0\n",
     "    cfg['simulation']['network']['nodes'][8]['applications'][0]['options']['port_scan_p_of_success'] = 1.0\n",
     "    cfg['simulation']['network']['nodes'][9]['applications'][0]['options']['port_scan_p_of_success'] = 1.0\n",
-    "game = PrimaiteGame.from_config(cfg)\n",
-    "env = PrimaiteGymEnv(game = game)\n",
-    "# Don't flatten obs as we are not training an agent and we wish to see the dict-formatted observations\n",
-    "env.agent.flatten_obs = False\n",
+    "    # don't flatten observations so that we can see what is going on\n",
+    "    cfg['agents'][3]['agent_settings']['flatten_obs'] = False\n",
+    "\n",
+    "env = PrimaiteGymEnv(game_config = cfg)\n",
     "obs, info = env.reset()\n",
     "print('env created successfully')\n",
     "pprint(obs)"
@@ -422,9 +416,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "for step in range(35):\n",
@@ -442,9 +434,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "pprint(obs['NODES'])"
@@ -460,9 +450,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "obs, reward, terminated, truncated, info = env.step(9)  # scan database file\n",
@@ -488,9 +476,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "obs, reward, terminated, truncated, info = env.step(13)  # patch the database\n",
@@ -515,9 +501,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "obs, reward, terminated, truncated, info = env.step(0)  # patch the database\n",
@@ -540,9 +524,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "env.step(13)  # Patch the database\n",
@@ -582,6 +564,22 @@
     "obs['ACL']"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Reset the cell, you can rerun the other cells to verify that the attack works the same every episode."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "env.reset()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -592,7 +590,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "venv",
    "language": "python",
    "name": "python3"
   },
@@ -606,9 +604,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 2
 }