Laser-Hockey-Env.ipynb

{
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   "metadata": {
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     "end_time": "2019-08-21T19:12:18.980322Z",
     "start_time": "2019-08-21T19:12:18.819269Z"
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   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import laserhockey.laser_hockey_env as lh\n",
    "import gymnasium as gym\n",
    "from importlib import reload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:12:19.327491Z",
     "start_time": "2019-08-21T19:12:19.321977Z"
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   },
   "outputs": [],
   "source": [
    "np.set_printoptions(suppress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-20T21:03:35.086427Z",
     "start_time": "2018-12-20T21:03:35.082123Z"
    }
   },
   "source": [
    "# Normal Game Play"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:12:20.113779Z",
     "start_time": "2019-08-21T19:12:20.096161Z"
    }
   },
   "outputs": [],
   "source": [
    "reload(lh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:12:20.679643Z",
     "start_time": "2019-08-21T19:12:20.671317Z"
    }
   },
   "outputs": [],
   "source": [
    "env = lh.LaserHockeyEnv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "have a look at the initialization condition: alternating who starts and are random in puck position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:12:21.968928Z",
     "start_time": "2019-08-21T19:12:21.528122Z"
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   },
   "outputs": [],
   "source": [
    "obs, info = env.reset()\n",
    "obs_agent2 = env.obs_agent_two()\n",
    "env.render()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "one episode with random agents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:14:39.528415Z",
     "start_time": "2019-08-21T19:14:31.154821Z"
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   },
   "outputs": [],
   "source": [
    "#obs = env.reset()\n",
    "obs_agent2 = env.obs_agent_two()\n",
    "\n",
    "for _ in range(600):\n",
    "    env.render()\n",
    "    a1 = np.random.uniform(-1,1,3)\n",
    "    a2 = np.random.uniform(-1,1,3)    \n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Without rendering, it runs much faster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:00:20.475049Z",
     "start_time": "2019-01-11T08:00:20.312847Z"
    }
   },
   "outputs": [],
   "source": [
    "obs, info  = env.reset()\n",
    "obs_agent2 = env.obs_agent_two()\n",
    "\n",
    "for _ in range(600):    \n",
    "    a1 = [1,-.5,0] # np.random.uniform(-1,1,3)\n",
    "    a2 = [1,0.,0] # np.random.uniform(-1,1,3)*0    \n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T07:57:48.631793Z",
     "start_time": "2019-01-11T07:57:48.627528Z"
    }
   },
   "source": [
    "\"info\" dict contains useful proxy rewards and winning information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:00:20.784862Z",
     "start_time": "2019-01-11T08:00:20.779373Z"
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   },
   "outputs": [],
   "source": [
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
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   },
   "source": [
    "Winner == 0: draw\n",
    "\n",
    "Winner == 1: you (left player)\n",
    "\n",
    "Winner == -1: opponent wins (right player)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-20T20:37:41.013424Z",
     "start_time": "2018-12-20T20:37:41.009298Z"
    }
   },
   "source": [
    "# Train Shooting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:00:32.294924Z",
     "start_time": "2019-01-11T08:00:32.288528Z"
    }
   },
   "outputs": [],
   "source": [
    "env = lh.LaserHockeyEnv(mode=lh.LaserHockeyEnv.TRAIN_SHOOTING)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:01:01.754465Z",
     "start_time": "2019-01-11T08:01:01.728781Z"
    }
   },
   "outputs": [],
   "source": [
    "o, info = env.reset()\n",
    "env.render()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:01:05.573939Z",
     "start_time": "2019-01-11T08:01:02.243221Z"
    }
   },
   "outputs": [],
   "source": [
    "for _ in range(200):\n",
    "    env.render()\n",
    "    a1 = [1,0,0] # np.random.uniform(-1,1,3)\n",
    "    a2 = [0,0.,0] \n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-20T20:37:41.013424Z",
     "start_time": "2018-12-20T20:37:41.009298Z"
    }
   },
   "source": [
    "# Train DEFENDING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:01:07.630627Z",
     "start_time": "2019-01-11T08:01:07.625675Z"
    }
   },
   "outputs": [],
   "source": [
    "reload(lh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:01:07.981240Z",
     "start_time": "2019-01-11T08:01:07.974283Z"
    }
   },
   "outputs": [],
   "source": [
    "env = lh.LaserHockeyEnv(mode=lh.LaserHockeyEnv.TRAIN_DEFENSE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:01:08.317742Z",
     "start_time": "2019-01-11T08:01:08.312949Z"
    }
   },
   "outputs": [],
   "source": [
    "o, info = env.reset()\n",
    "env.render()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-01-11T08:01:17.885328Z",
     "start_time": "2019-01-11T08:01:17.159573Z"
    }
   },
   "outputs": [],
   "source": [
    "for _ in range(60):\n",
    "    env.render()\n",
    "    a1 = [1,0,0] # np.random.uniform(-1,1,3)\n",
    "    a2 = [0,0.,0] \n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-20T20:37:41.013424Z",
     "start_time": "2018-12-20T20:37:41.009298Z"
    }
   },
   "source": [
    "# Using discrete actions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-21T13:08:25.605760Z",
     "start_time": "2018-12-21T13:08:25.593455Z"
    }
   },
   "outputs": [],
   "source": [
    "env = lh.LaserHockeyEnv(mode=lh.LaserHockeyEnv.TRAIN_SHOOTING)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-21T13:08:25.849615Z",
     "start_time": "2018-12-21T13:08:25.845081Z"
    }
   },
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-21T13:08:29.582257Z",
     "start_time": "2018-12-21T13:08:26.211196Z"
    }
   },
   "outputs": [],
   "source": [
    "for _ in range(200):\n",
    "    env.render()\n",
    "    a1_discrete = random.randint(0,7)\n",
    "    a1 = env.discrete_to_continous_action(a1_discrete)\n",
    "    a2 = [0,0.,0] \n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-20T20:37:41.013424Z",
     "start_time": "2018-12-20T20:37:41.009298Z"
    }
   },
   "source": [
    "# Hand-crafted Opponent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:04.371746Z",
     "start_time": "2019-08-21T19:16:04.353350Z"
    }
   },
   "outputs": [],
   "source": [
    "reload(lh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:04.516774Z",
     "start_time": "2019-08-21T19:16:04.510863Z"
    }
   },
   "outputs": [],
   "source": [
    "env = lh.LaserHockeyEnv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:04.729445Z",
     "start_time": "2019-08-21T19:16:04.666357Z"
    }
   },
   "outputs": [],
   "source": [
    "o, info = env.reset()\n",
    "env.render()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:09.794765Z",
     "start_time": "2019-08-21T19:16:09.790764Z"
    }
   },
   "outputs": [],
   "source": [
    "player1 = lh.BasicOpponent()\n",
    "player2 = lh.BasicOpponent()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:10.202581Z",
     "start_time": "2019-08-21T19:16:10.198608Z"
    }
   },
   "outputs": [],
   "source": [
    "obs_buffer = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:22.594530Z",
     "start_time": "2019-08-21T19:16:18.495500Z"
    }
   },
   "outputs": [],
   "source": [
    "obs, info = env.reset()\n",
    "obs_agent2 = env.obs_agent_two()\n",
    "for _ in range(100):\n",
    "    env.render()\n",
    "    a1 = player1.act(obs)\n",
    "    a2 = player2.act(obs_agent2)\n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_buffer.append(obs)\n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-12-28T12:27:58.824246Z",
     "start_time": "2018-12-28T12:27:58.813103Z"
    }
   },
   "outputs": [],
   "source": [
    "obs_buffer = np.asarray(obs_buffer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:27.114353Z",
     "start_time": "2019-08-21T19:16:27.103201Z"
    }
   },
   "outputs": [],
   "source": [
    "np.mean(obs_buffer,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:27.902145Z",
     "start_time": "2019-08-21T19:16:27.894650Z"
    }
   },
   "outputs": [],
   "source": [
    "np.std(obs_buffer,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:28.497119Z",
     "start_time": "2019-08-21T19:16:28.492780Z"
    }
   },
   "outputs": [],
   "source": [
    "scaling = [ 1.0,  1.0 , 3.14, 4.0, 4.0, 2.0,  \n",
    "            1.0,  1.0,  3.14, 4.0, 4.0, 2.0,  \n",
    "            2.0, 2.0, 10.0, 10.0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Human Opponent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:32.838454Z",
     "start_time": "2019-08-21T19:16:32.834847Z"
    }
   },
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:33.295971Z",
     "start_time": "2019-08-21T19:16:33.290071Z"
    }
   },
   "outputs": [],
   "source": [
    "env = lh.LaserHockeyEnv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:33.801588Z",
     "start_time": "2019-08-21T19:16:33.738351Z"
    }
   },
   "outputs": [],
   "source": [
    "o, info = env.reset()\n",
    "env.render()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from laserhockey.hockey_env import HumanOpponent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:16:38.262611Z",
     "start_time": "2019-08-21T19:16:38.257285Z"
    }
   },
   "outputs": [],
   "source": [
    "player1 = HumanOpponent(env=env, player=1)\n",
    "player2 = lh.BasicOpponent()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-21T19:17:37.603826Z",
     "start_time": "2019-08-21T19:17:34.793733Z"
    },
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "obs, info = env.reset()\n",
    "time.sleep(1)\n",
    "obs_agent2 = env.obs_agent_two()\n",
    "for _ in range(1600):\n",
    "    time.sleep(0.2)\n",
    "    env.render()\n",
    "    a1 = player1.act(obs)\n",
    "    a2 = player2.act(obs_agent2)\n",
    "    obs, r, d, _, info = env.step(np.hstack([a1,a2]))    \n",
    "    obs_agent2 = env.obs_agent_two()\n",
    "    if d: break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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