evaluate.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2023-09-08T13:22:47.046650823Z",
     "start_time": "2023-09-08T13:22:44.518732487Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pygame 2.5.1 (SDL 2.28.2, Python 3.9.17)\n",
      "Hello from the pygame community. https://www.pygame.org/contribute.html\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from qlearning import QLearning\n",
    "from tqdm import tqdm\n",
    "import gymnasium as gym\n",
    "from wrappers import TltlWrapper, PredicateEvaluationResult, PositionPredicate, PositionWrapper, MoveActionWrapper\n",
    "from gymnasium.spaces.utils import flatten_space, flatten\n",
    "from gymnasium.spaces import Dict, Discrete\n",
    "from minigrid.wrappers import DictObservationSpaceWrapper, FullyObsWrapper\n",
    "from stable_baselines3.common.logger import configure\n",
    "import numpy as np\n",
    "import random\n",
    "from tools import save_frames_as_gif\n",
    "from qlearning import greedy_policy, transform_to_tuple\n",
    "from minigrid.core.world_object import Goal\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Test for the TLTL of: F p1 & F p2 & (! p1 U p2)\n",
    "\"\"\"\n",
    "# env = gym.make(\"MiniGrid-Empty-8x8-v0\", render_mode=\"rgb_array\", max_episode_steps=50)\n",
    "# goal1 = Goal()\n",
    "# goal1.color = 'red'\n",
    "# env.put_obj(goal1, 5,5)\n",
    "# goal2 = Goal()\n",
    "# goal2.color = 'blue'\n",
    "# env.put_obj(goal2, 3,3)\n",
    "# env = TltlWrapper(env, tltl=\"F p1 & F p2 & (! p1 U p2)\",\n",
    "#                   predicates={'p1': PositionPredicate(True, [3, 3]), 'p2': PositionPredicate(True, [5, 5])})\n",
    "# env = PositionWrapper(env)\n",
    "# env = MoveActionWrapper(env)\n",
    "# env = gym.wrappers.FilterObservation(env, [\"pos\", \"fspa\", \"direction\"])"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "q_table = np.load('q_table_random_5-2-3_X_snytex.npy')\n",
    "\n",
    "env = gym.make(\"MiniGrid-Empty-8x8-v0\", render_mode=\"rgb_array\", max_episode_steps=50)\n",
    "env = TltlWrapper(env, tltl=\"F p1 & F p2 & F p3 & (! p1 U p2) & (! p2 U p3)\",\n",
    "                  predicates={'p1': PositionPredicate(True, [3, 3]), 'p2': PositionPredicate(True, [5, 5]),\n",
    "                              'p3': PositionPredicate(True, [2, 2])})\n",
    "env = PositionWrapper(env)\n",
    "env = MoveActionWrapper(env)\n",
    "env = gym.wrappers.FilterObservation(env, [\"pos\", \"fspa\", \"direction\"])"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-09-08T09:05:07.453238257Z",
     "start_time": "2023-09-08T09:05:07.428089338Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "MovieWriter imagemagick unavailable; using Pillow instead.\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 256x256 with 1 Axes>",
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAANMAAADTCAYAAAAbBybZAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAAsTAAALEwEAmpwYAAAIVUlEQVR4nO3dT29T6RmG8fu4mBzHTmQHYmNGESIJmiXCsVh3CUJ8hq74Av0UXXbPF+mmVdWqnQVRmFatRiMlUvlTHKbFptiUBNs5XbiRWkScAPeTY4+u326G5H3f2LniYyd5kmRZlgnAFyvkfQDgx4KYABNiAkyICTAhJsCEmACTC9P+8cGDB+d1DmBuPHz48KP/n0cmwISYABNiAkyICTAhJsCEmAATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmAATYgJMiAkwISbAhJgAE2ICTKbOzTsPL1++VKfTCVv/ypUrGgwGGgwGYXtsbm5qb29PUX+dJ0kSbWxsaHd3N2R9SSqXy1peXp77++LGjRsql8th60+Te0ydTkfb29th67daLXU6ndBPkkajoZ2dHY3H45D1C4WCGo1G6O3UaDS0trY29/dFs9nMLSYu8wATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmAATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkymjvpqNBrhB7h586ZWV1fD1m82m9rc3FS/3w/bY3NzU3fu3NHR0VHI+sdz8+7evRuyviRdvHhR4/FYrVYrbI9ms6lKpaJmsxm2R15jvqQZiGk8Huv9+/dh69frdaVpqoWFhdA9Xr9+HRpTvV5Xt9sNWV+azOZ78uRJ6Ey7SqWiV69ehX4c169fD1v7NLkPoTw4OFCv1wtbf2VlRf1+P3SP4XCoXq8XGtNoNAr9GIrFogaDQfiAyG63G7pH5Bfm0+Qe04fWJH0t6Sef8b7PJf3VexzgzGYupoqkn0mqfuL7ZZJ+KWJCfmbu1bzvJX2nSRyf4rmkR/7jAGc2czEdSfr1Z7zfHyS9M58F+BQzF5Mk/UnS3z7h7f8haVvSKOQ0wNnMZExDSb/X2S71Mk0uDeNeHwLOZiZjGkvakfTiDG870ORR6U3oiYDTzWRM0iSkbzUJ6yTZf99u5zwOBJxiZmN6p8nL3NP+YGOmyfOruG9lAmc3szFJ0mNJf9fJz50OJP3q/I4DTDXTMQ0k/UYnX+r9VtI/z+00wHQzHZMkfaOPX+od6uyv+AHnYeZj6msSzYf+osklIDArZj6mTNLv9P+PToeavIL3r1xOBHzczMckTX7ubvuD//5Wkx89AmbFXMT0VpOXwP+tyYsR3+ts39AFztNcxHT8I0PPNAnqG/FzeJg9M/f7TCd5psnzpJ4ml3jArJmbmCTpj5L+nPchgBPMVUxPJCV5HwI4wVzFlIlv0mJ2zcULEMA8yP2Rqdlsqlqthq1fKpVUr9c1HA7D9lhaWtLW1payLOZxM0kSLS0tqd1uh6wvTUZkLSwshM5KrFQqunbtWug4rlqtFrb2aXKPaX9/X3t7e2Hrr6+vq9frhc6c29ra0uPHj8Pm5hUKBbVaLe3sxP3mVrFY1NOnT0P3uHXrljqdjvb398P2uHfvnur1etj60+QeU5ZlYZ+E/7v+PO+RZVn47XR0dKQsyzQeT/t1zC/f4+joKHSPqKuDs+A5E2BCTIAJMQEmxASYEBNgQkyACTEBJsQEmBATYEJMgAkxASbEBJgQE2BCTIAJMQEmxASYEBNgQkyACTEBJsQEmBATYJL7dKIkSZQkcUOPkyRRoVA4lz2iJuMcnz/yYzjeo1CI+/p6vH70HnnJPaboIZRpmmp1dVWjUdwfoVlaWlKr1QodQlmpVEKHUB4eHqpYLM79EMrIz6XT5B7TixcvtLu7G7b+xsaGut1u6BDKdrutnZ2dsLl2SZKo3W7r0aNHIetLkyGUz5490/b29ulv/JlarZY6nY46nU7YHvfv3w/9gjANz5kAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmAATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmAATYgJMch/1laZp+Ny8SqUSNtNOki5cuKBqtRo66ut4jyiFQkHlcjl8bl6tVgu7naTJyLK85B5TqVTS5cuXw9ZfXFxUkiRaWFgI26NYLOrSpUuhQyiLxWLo7TQej7W8vKy1tbWwPZaXl1UoFLS4uBi2R+T9fJrcY+r1enM/hLJarWpvby/0kalarYbeTsViUZ1OZ+6HUDabTZXL5bD1p+E5E2BCTIAJMQEmxASYEBNgQkyACTEBJsQEmBATYEJMgAkxASbEBJgQE2BCTIAJMQEmxASYEBNgQkyACTEBJsQEmBATYEJMgEnuo75qtZo2NjZC1y+VSlpZWQnbo1QqaX19PXRuXpqmobfTeDzWcDhUq9UK2yP7aab+V32pH7aF9IOk94HrT5F7TO/evVO32w1bv1Qq6c2bN+r34+7Ber2uXq8XOjdvdXU19HYqFAoaDAahM+36X/U1+PkgbH1J0i8k7cVucZLcYzo4OAgdELmysqJ+vx+6x3A4DI9pNBqFfgzFYjE8ptBHpBnAcybAhJgAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmAATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmACT3Ed9Xb16NXRAZJqmajQaGo1GYXtUKhW12+2w9Y/3uH37dtj6h4eHStNUzWYzbA/9oMlcu0C157XYDabIPaY0TZWmad7H+GLVanWu93j79q3K5bLK5XLYHnqv3AZEngcu8wATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkyICTAhJsCEmAATYgJMiAkwISbAhJgAE2ICTIgJMCEmwISYABNiAkyICTBJsizL8j4E8GPAIxNgQkyACTEBJsQEmBATYEJMgMl/AE4NHJwX//T6AAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state, info = env.reset()\n",
    "frames = []\n",
    "frames.append(env.render())\n",
    "for step in range(0, 50):\n",
    "    state = transform_to_tuple(state)\n",
    "    action = greedy_policy(q_table, state)\n",
    "    new_state, reward, terminated, truncated, info = env.step(action)\n",
    "    frames.append(env.render())\n",
    "    if terminated or truncated:\n",
    "        new_state, info = env.reset()\n",
    "    state = new_state\n",
    "env.close()\n",
    "save_frames_as_gif(frames,'./', '5-2-3-random.gif')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-09-08T09:05:25.017915189Z",
     "start_time": "2023-09-08T09:05:24.405934935Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "rewards = np.load(\"all_rewards_q_table_random_2-5-3_150000.npy\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-09-08T13:23:10.847760503Z",
     "start_time": "2023-09-08T13:23:10.806594239Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "outputs": [],
   "source": [
    "running_average = []\n",
    "window = 50\n",
    "for ind in range(len(rewards) - window + 1):\n",
    "    running_average.append(np.mean(rewards[ind:ind+window]))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-09-08T13:43:00.777885979Z",
     "start_time": "2023-09-08T13:43:00.192880206Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "outputs": [
    {
     "data": {
      "text/plain": "[<matplotlib.lines.Line2D at 0x7f131c300520>]"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(running_average)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-09-08T13:43:00.954247758Z",
     "start_time": "2023-09-08T13:43:00.787337538Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "(200,)"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.shape"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-09-08T13:33:22.443509838Z",
     "start_time": "2023-09-08T13:33:22.439085976Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
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     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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    "re"
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     "start_time": "2023-09-08T13:33:29.159045696Z"
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    {
     "data": {
      "text/plain": "array([-50.0390625,  49.9609375,  49.9609375, ..., -50.0390625,\n        49.21875  ,  48.28125  ])"
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     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
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    "ExecuteTime": {
     "end_time": "2023-09-08T13:33:37.389751300Z",
     "start_time": "2023-09-08T13:33:37.383208214Z"
    }
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  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
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