03-fit-first-tetromino.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "17e397f6-39dc-47a8-b328-e107b03bed68",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "UserWarning: Using SDL2 binaries from pysdl2-dll 2.30.0\n"
     ]
    }
   ],
   "source": [
    "from pyboy import PyBoy, WindowEvent\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e8caa96f-8ba5-4648-846e-38b4e95d6427",
   "metadata": {},
   "outputs": [],
   "source": [
    "from current_tetromino import current_tetromino"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "071e9172-2ecc-48ce-8802-fc2bb707cc8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "pyboy = PyBoy(\"Tetris.gb\", game_wrapper=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3078e4a8-ec2d-4d0e-a807-2fe6f6663c89",
   "metadata": {},
   "outputs": [],
   "source": [
    "pyboy.set_emulation_speed(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8e4a6e9e-a2f8-47b7-8ebf-c4fb672195f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "tetris = pyboy.game_wrapper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e2654de4-f5d7-4544-ab60-a06db346e0e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "tetris.start_game()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2ca2ed89-6208-4503-920a-1caeeca2aab6",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_screens = []\n",
    "for i in range(200):\n",
    "    tetris.reset_game()\n",
    "    start_screens.append(tetris.game_area().base)\n",
    "start_screens = np.array(start_screens)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "61dfd79b-dbe0-4871-b8da-8b297444233a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(200, 18, 10)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start_screens.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "23bb3c7f-7187-43c4-8e33-7be25c3d948a",
   "metadata": {},
   "outputs": [],
   "source": [
    "sc, co = np.unique(start_screens, axis=0, return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b6a46035-0a8c-462e-bcd4-d14e44e450eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((7, 18, 10), array([37, 33, 33, 32,  1, 28, 36], dtype=int64))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sc.shape, co"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d7d73682-dc15-4753-a584-36607f159c39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1,7, figsize=(10,10))\n",
    "for ax, s, c in zip(axs.flatten(), sc, co):\n",
    "    ax.imshow(s)\n",
    "    ax.set_title(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1603bbb7-a775-48df-be21-f1c80ae92482",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x1000 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1,7, figsize=(10,10))\n",
    "for ax, s in zip(axs.flatten(), sc):\n",
    "    ax.imshow(s[1:3,3:7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ce206b29-b202-4f67-b3db-076e2572c651",
   "metadata": {},
   "outputs": [],
   "source": [
    "rotations = [0, 0, 1, 0, 3, 2, 1]\n",
    "direction = [\"left\", \"left\", \"right\", \"right\", \"left\", \"left\", \"left\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3fa8ee31-8b9d-4a6a-8565-cedb843d8ee5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=160x144>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tetris.reset_game(timer_div=9)\n",
    "print(current_tetromino(tetris))\n",
    "pyboy.screen_image()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "777c9ac1-f0fb-4c18-a090-76e7226770a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "IOZSTOJIO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e14b4519-be2c-453c-a74d-c230e0042b34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "image/png": "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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=160x144>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tetris.reset_game()\n",
    "[pyboy.tick() for _ in range(60)]\n",
    "print(current_tetromino(tetris))\n",
    "pyboy.screen_image()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "e7c2fcf0-01b4-4831-86c2-561438591b21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rot</th>\n",
       "      <th>dir</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shape</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>O</th>\n",
       "      <td>0</td>\n",
       "      <td>left</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S</th>\n",
       "      <td>0</td>\n",
       "      <td>left</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>J</th>\n",
       "      <td>1</td>\n",
       "      <td>right</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Z</th>\n",
       "      <td>0</td>\n",
       "      <td>right</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L</th>\n",
       "      <td>3</td>\n",
       "      <td>left</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T</th>\n",
       "      <td>2</td>\n",
       "      <td>left</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>1</td>\n",
       "      <td>left</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       rot    dir\n",
       "shape            \n",
       "O        0   left\n",
       "S        0   left\n",
       "J        1  right\n",
       "Z        0  right\n",
       "L        3   left\n",
       "T        2   left\n",
       "I        1   left"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initial_info = pd.DataFrame({\"shape\": shape_names, \"rot\": rotations, \"dir\": direction}).set_index(\"shape\")\n",
    "initial_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "b07d91d0-3054-42db-904d-416bfeddd8dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "pyboy.set_emulation_speed(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "8e8dfa11-eb5c-49bd-84d3-fdf5228e8654",
   "metadata": {},
   "outputs": [],
   "source": [
    "tetris.reset_game()\n",
    "current = current_tetromino(tetris)\n",
    "for r in range(initial_info.loc[current,\"rot\"]):\n",
    "    pyboy.send_input(WindowEvent.PRESS_BUTTON_A)\n",
    "    pyboy.tick()\n",
    "    pyboy.send_input(WindowEvent.RELEASE_BUTTON_A)\n",
    "    [pyboy.tick() for _ in range(60)]\n",
    "press_arrow = WindowEvent.PRESS_ARROW_LEFT if initial_info.loc[current,\"dir\"] == \"left\" else WindowEvent.PRESS_ARROW_RIGHT\n",
    "release_arrow = WindowEvent.RELEASE_ARROW_LEFT if initial_info.loc[current,\"dir\"] == \"left\" else WindowEvent.RELEASE_ARROW_RIGHT\n",
    "pyboy.send_input(press_arrow)\n",
    "for _ in range(800):\n",
    "    pyboy.tick()\n",
    "pyboy.send_input(release_arrow)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "1ebba366-68b8-4a08-adc9-4a2e4ab3216f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pyboy.stop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0efb0b60-390a-45f1-931b-ae92ff5a0878",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}