plot_map.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x720 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = [20, 10]\n",
    "\n",
    "from env.static_env import TA_Static\n",
    "from utils import load_train_config\n",
    "\n",
    "row = 2\n",
    "col = 6\n",
    "config_name = \"simple_het\"\n",
    "\n",
    "fig, ax = plt.subplots(row, col)\n",
    "\n",
    "for r in range(row):\n",
    "  for c in range(col):\n",
    "    cfg = load_train_config(config_name)\n",
    "    env = TA_Static(cfg)\n",
    "    env.reset()\n",
    "\n",
    "    task_info = env.task\n",
    "    task_amount = env.task_total_num\n",
    "\n",
    "    ax[r,c].set_title(config_name)\n",
    "    ax[r,c].set_xlim((-0.1,1.1))\n",
    "    ax[r,c].set_ylim((-0.1,1.1))\n",
    "    ax[r,c].set_aspect(\"equal\")\n",
    "\n",
    "    task_colors = [\"k\",\"m\",\"c\"]\n",
    "    for i, (t_type_name, t_info) in enumerate(task_info.items()):\n",
    "        ax[r,c].scatter(task_info[t_type_name][\"position\"][0][:,0],task_info[t_type_name][\"position\"][0][:,1],\n",
    "                    marker='x', s=25,  facecolor=task_colors[i], label=t_type_name)\n",
    "\n",
    "    ax[r,c].legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.13 ('ta')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "3eee4d7e9a2bcfb4c8b62f98a1f306cfde5667446c5f72486be8456775579dcb"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}