MII_Salin_Oleg_PIbd-33/lec7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Управление каденсом велосипедиста"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Создание лингвистических переменных\n",
    "\n",
    "Входные X: speed (текущая скорость) и target (желаемая скорость) /\n",
    "Выходные Y: cadence (необходимый каденс)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from skfuzzy import control as ctrl\n",
    "\n",
    "speed = ctrl.Antecedent(np.arange(0, 100, 1), \"speed\")\n",
    "target = ctrl.Antecedent(np.arange(0, 100, 1), \"target\")\n",
    "cadence = ctrl.Consequent(np.arange(0, 130, 1), \"cadence\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Формирование нечетких переменных для лингвистических переменных и их визуализация"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Методы искусственного интеллекта\\MII_Salin_Oleg_PIbd-33\\.venv\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import skfuzzy as fuzz\n",
    "\n",
    "speed[\"slow\"] = fuzz.zmf(speed.universe, 20, 60)\n",
    "speed[\"average\"] = fuzz.trapmf(speed.universe, [10, 30, 60, 80])\n",
    "speed[\"fast\"] = fuzz.smf(speed.universe, 60, 80)\n",
    "speed.view()\n",
    "\n",
    "target[\"slow\"] = fuzz.zmf(target.universe, 20, 60)\n",
    "target[\"average\"] = fuzz.trapmf(target.universe, [10, 30, 60, 80])\n",
    "target[\"fast\"] = fuzz.smf(target.universe, 60, 80)\n",
    "target.view()\n",
    "\n",
    "cadence[\"low\"] = fuzz.zmf(cadence.universe, 0, 80)\n",
    "cadence[\"average\"] = fuzz.trapmf(cadence.universe, [0, 60, 70, 90])\n",
    "cadence[\"high\"] = fuzz.smf(cadence.universe, 80, 110)\n",
    "cadence.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Формирование и визуализация базы нечетких правил\n",
    "\n",
    "В случае ошибки необходимо в файле\n",
    "```\n",
    ".venv/lib/python3.13/site-packages/skfuzzy/control/visualization.py\n",
    "```\n",
    "удалить лишний отступ на 182 строке, должно быть:\n",
    "```python\n",
    "        if not matplotlib_present:\n",
    "            raise ImportError(\"`ControlSystemVisualizer` can only be used \"\n",
    "                              \"with `matplotlib` present in the system.\")\n",
    "\n",
    "        self.ctrl = control_system\n",
    "\n",
    "        self.fig, self.ax = plt.subplots()\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>, <Axes: >)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rule1 = ctrl.Rule(speed[\"slow\"] & target[\"fast\"], cadence[\"high\"])\n",
    "rule2 = ctrl.Rule(speed[\"slow\"] & target[\"average\"], cadence[\"high\"])\n",
    "rule3 = ctrl.Rule(speed[\"slow\"] & target[\"slow\"], cadence[\"low\"])\n",
    "rule4 = ctrl.Rule(speed[\"average\"] & target[\"fast\"], cadence[\"high\"])\n",
    "rule5 = ctrl.Rule(speed[\"average\"] & target[\"average\"], cadence[\"average\"])\n",
    "rule6 = ctrl.Rule(speed[\"average\"] & target[\"slow\"], cadence[\"low\"])\n",
    "rule7 = ctrl.Rule(speed[\"fast\"] & target[\"fast\"], cadence[\"high\"])\n",
    "rule8 = ctrl.Rule(speed[\"fast\"] & target[\"average\"], cadence[\"low\"])\n",
    "rule9 = ctrl.Rule(speed[\"fast\"] & target[\"slow\"], cadence[\"low\"])\n",
    "\n",
    "rule1.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Создание нечеткой системы и добавление нечетких правил в базу знаний нечеткой системы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cadence_ctrl = ctrl.ControlSystem(\n",
    "    [\n",
    "        rule1,\n",
    "        rule2,\n",
    "        rule3,\n",
    "        rule4,\n",
    "        rule5,\n",
    "        rule6,\n",
    "        rule7,\n",
    "        rule8,\n",
    "        rule9,\n",
    "    ]\n",
    ")\n",
    "\n",
    "cadences = ctrl.ControlSystemSimulation(cadence_ctrl)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Пример расчета выходной переменной cadence на основе входных переменных speed и target\n",
    "\n",
    "Система также формирует подробный журнал выполнения процесса нечеткого логического вывода"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============\n",
      " Antecedents \n",
      "=============\n",
      "Antecedent: speed                   = 60\n",
      "  - slow                            : 0.0\n",
      "  - average                         : 1.0\n",
      "  - fast                            : 0.0\n",
      "Antecedent: target                  = 20\n",
      "  - slow                            : 1.0\n",
      "  - average                         : 0.5\n",
      "  - fast                            : 0.0\n",
      "\n",
      "=======\n",
      " Rules \n",
      "=======\n",
      "RULE #0:\n",
      "  IF speed[slow] AND target[fast] THEN cadence[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[slow]                                            : 0.0\n",
      "  - target[fast]                                           : 0.0\n",
      "                              speed[slow] AND target[fast] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                             cadence[high] : 0.0\n",
      "\n",
      "RULE #1:\n",
      "  IF speed[slow] AND target[average] THEN cadence[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[slow]                                            : 0.0\n",
      "  - target[average]                                        : 0.5\n",
      "                           speed[slow] AND target[average] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                             cadence[high] : 0.0\n",
      "\n",
      "RULE #2:\n",
      "  IF speed[slow] AND target[slow] THEN cadence[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[slow]                                            : 0.0\n",
      "  - target[slow]                                           : 1.0\n",
      "                              speed[slow] AND target[slow] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                              cadence[low] : 0.0\n",
      "\n",
      "RULE #3:\n",
      "  IF speed[average] AND target[fast] THEN cadence[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[average]                                         : 1.0\n",
      "  - target[fast]                                           : 0.0\n",
      "                           speed[average] AND target[fast] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                             cadence[high] : 0.0\n",
      "\n",
      "RULE #4:\n",
      "  IF speed[average] AND target[average] THEN cadence[average]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[average]                                         : 1.0\n",
      "  - target[average]                                        : 0.5\n",
      "                        speed[average] AND target[average] = 0.5\n",
      "  Activation (THEN-clause):\n",
      "                                          cadence[average] : 0.5\n",
      "\n",
      "RULE #5:\n",
      "  IF speed[average] AND target[slow] THEN cadence[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[average]                                         : 1.0\n",
      "  - target[slow]                                           : 1.0\n",
      "                           speed[average] AND target[slow] = 1.0\n",
      "  Activation (THEN-clause):\n",
      "                                              cadence[low] : 1.0\n",
      "\n",
      "RULE #6:\n",
      "  IF speed[fast] AND target[fast] THEN cadence[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[fast]                                            : 0.0\n",
      "  - target[fast]                                           : 0.0\n",
      "                              speed[fast] AND target[fast] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                             cadence[high] : 0.0\n",
      "\n",
      "RULE #7:\n",
      "  IF speed[fast] AND target[average] THEN cadence[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[fast]                                            : 0.0\n",
      "  - target[average]                                        : 0.5\n",
      "                           speed[fast] AND target[average] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                              cadence[low] : 0.0\n",
      "\n",
      "RULE #8:\n",
      "  IF speed[fast] AND target[slow] THEN cadence[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - speed[fast]                                            : 0.0\n",
      "  - target[slow]                                           : 1.0\n",
      "                              speed[fast] AND target[slow] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                              cadence[low] : 0.0\n",
      "\n",
      "\n",
      "==============================\n",
      " Intermediaries and Conquests \n",
      "==============================\n",
      "Consequent: cadence                  = 35.97074517705886\n",
      "  low:\n",
      "    Accumulate using accumulation_max : 1.0\n",
      "  average:\n",
      "    Accumulate using accumulation_max : 0.5\n",
      "  high:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "np.float64(35.97074517705886)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cadences.input[\"speed\"] = 60\n",
    "cadences.input[\"target\"] = 20\n",
    "cadences.compute()\n",
    "cadences.print_state()\n",
    "cadences.output[\"cadence\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Визуализация функции принадлежности для выходной переменной cadence\n",
    "\n",
    "Функция получена в процессе аккумуляции и используется для дефаззификации значения выходной переменной cadence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cadence.view(sim=cadences)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Пример решения задачи регрессии на основе нечеткого логического вывода"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Загрузка данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cars_train'"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Price</th>\n",
       "      <th>Prodyear</th>\n",
       "      <th>Engine volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3329</th>\n",
       "      <td>188</td>\n",
       "      <td>2009</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15830</th>\n",
       "      <td>16621</td>\n",
       "      <td>2005</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>3293</td>\n",
       "      <td>2014</td>\n",
       "      <td>5.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1672</th>\n",
       "      <td>59464</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10342</th>\n",
       "      <td>8500</td>\n",
       "      <td>2006</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8472</th>\n",
       "      <td>470</td>\n",
       "      <td>2015</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7958</th>\n",
       "      <td>6586</td>\n",
       "      <td>2014</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>16308</td>\n",
       "      <td>2008</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4525</th>\n",
       "      <td>7683</td>\n",
       "      <td>2013</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5251</th>\n",
       "      <td>7997</td>\n",
       "      <td>2004</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15389 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Price  Prodyear  Engine volume\n",
       "3329     188      2009            2.5\n",
       "15830  16621      2005            2.4\n",
       "3384    3293      2014            5.7\n",
       "1672   59464      2016            2.2\n",
       "10342   8500      2006            1.5\n",
       "...      ...       ...            ...\n",
       "8472     470      2015            3.0\n",
       "7958    6586      2014            1.4\n",
       "272    16308      2008            2.2\n",
       "4525    7683      2013            2.0\n",
       "5251    7997      2004            2.0\n",
       "\n",
       "[15389 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'cars_test'"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Price</th>\n",
       "      <th>Prodyear</th>\n",
       "      <th>Engine volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13393</th>\n",
       "      <td>3763</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4751</th>\n",
       "      <td>470</td>\n",
       "      <td>2011</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11945</th>\n",
       "      <td>706</td>\n",
       "      <td>2010</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5150</th>\n",
       "      <td>470</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10864</th>\n",
       "      <td>5488</td>\n",
       "      <td>2014</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5343</th>\n",
       "      <td>7840</td>\n",
       "      <td>1998</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9938</th>\n",
       "      <td>19444</td>\n",
       "      <td>2013</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6576</th>\n",
       "      <td>26343</td>\n",
       "      <td>2017</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12789</th>\n",
       "      <td>39750</td>\n",
       "      <td>2017</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5395</th>\n",
       "      <td>18189</td>\n",
       "      <td>2012</td>\n",
       "      <td>1.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3848 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Price  Prodyear  Engine volume\n",
       "13393   3763      2016            2.0\n",
       "4751     470      2011            2.4\n",
       "11945    706      2010            1.3\n",
       "5150     470      2019            2.0\n",
       "10864   5488      2014            2.5\n",
       "...      ...       ...            ...\n",
       "5343    7840      1998            2.8\n",
       "9938   19444      2013            2.0\n",
       "6576   26343      2017            3.0\n",
       "12789  39750      2017            1.6\n",
       "5395   18189      2012            1.9\n",
       "\n",
       "[3848 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from utils import split_stratified_into_train_val_test\n",
    "\n",
    "df = pd.read_csv(\"data/car_price_prediction.csv\")\n",
    "df = df.drop([\"ID\", \"Manufacturer\", \"Model\",  \"Leatherinterior\", \"Fueltype\", \"Cylinders\",\n",
    "          \"Doors\", \"Wheel\", \"Color\", \"Levy\", \"Drive wheels\", \"Airbags\", \"Gear box type\", \"Mileage\"], axis=1)\n",
    "df = df.dropna()\n",
    "df[\"Engine volume\"] = df[\"Engine volume\"].apply(\n",
    "    lambda x: float(x.split()[0])\n",
    ")\n",
    "\n",
    "\n",
    "cars_train, X_val, cars_test, y_train, y_val, y_test = split_stratified_into_train_val_test(\n",
    "    df,\n",
    "    stratify_colname=\"Category\",\n",
    "    target_colname=\"Price\",\n",
    "    frac_train=0.80,\n",
    "    frac_val=0,\n",
    "    frac_test=0.20\n",
    ")\n",
    "\n",
    "cars_train = cars_train.drop(\"Category\", axis=1)\n",
    "cars_test = cars_test.drop(\"Category\", axis=1)\n",
    "display(\"cars_train\", cars_train)\n",
    "display(\"cars_test\", cars_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Инициализация лингвистических переменных и автоматическое формирование нечетких переменных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "26307500\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\Методы искусственного интеллекта\\MII_Salin_Oleg_PIbd-33\\.venv\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prodyear = ctrl.Antecedent(np.arange(1885, 2025, 1), \"prodyear\")\n",
    "engine_volume = ctrl.Antecedent(cars_train[\"Engine volume\"].sort_values().unique(), \"engine_volume\")\n",
    "print(cars_train[\"Price\"].max())\n",
    "price = ctrl.Consequent(np.arange(cars_train[\"Price\"].min() // 100, \n",
    "                                  cars_train[\"Price\"].max() // 100, 1), \"price\")\n",
    "\n",
    "prodyear[\"old\"] = fuzz.zmf(prodyear.universe, 1885, 2020)\n",
    "prodyear[\"new\"] = fuzz.smf(prodyear.universe, 2015, 2020)\n",
    "prodyear.view()\n",
    "engine_volume.automf(3, variable_type=\"quant\")\n",
    "engine_volume.view()\n",
    "price[\"very cheap\"] = fuzz.trimf(price.universe, [0, 50, 100])\n",
    "price[\"cheap\"] = fuzz.trimf(price.universe, [80, 120, 200])\n",
    "price[\"average\"] = fuzz.trapmf(price.universe, [150, 250, 500, 1000])\n",
    "price[\"expensive\"] = fuzz.trimf(price.universe, [800, 1500, 2000])\n",
    "price[\"very expensive\"] = fuzz.smf(price.universe, 1800, 2500)\n",
    "price.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Нечеткие правила"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "rule11 = ctrl.Rule(\n",
    "    engine_volume[\"low\"] & prodyear[\"old\"],\n",
    "    price[\"very cheap\"],\n",
    ")\n",
    "rule12 = ctrl.Rule(\n",
    "    engine_volume[\"average\"] & prodyear[\"old\"],\n",
    "    price[\"cheap\"],\n",
    ")\n",
    "rule13 = ctrl.Rule(\n",
    "    engine_volume[\"high\"] & prodyear[\"old\"],\n",
    "    price[\"average\"],\n",
    ")\n",
    "rule21 = ctrl.Rule(\n",
    "    engine_volume[\"low\"] & prodyear[\"new\"],\n",
    "    price[\"average\"],\n",
    ")\n",
    "rule22 = ctrl.Rule(\n",
    "    engine_volume[\"average\"] & prodyear[\"new\"],\n",
    "    price[\"expensive\"],\n",
    ")\n",
    "rule23 = ctrl.Rule(\n",
    "    engine_volume[\"high\"] & prodyear[\"new\"],\n",
    "    price[\"very expensive\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Создание нечеткой системы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[IF engine_volume[low] AND prodyear[old] THEN price[very cheap]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF engine_volume[average] AND prodyear[old] THEN price[cheap]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF engine_volume[high] AND prodyear[old] THEN price[average]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF engine_volume[low] AND prodyear[new] THEN price[average]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF engine_volume[average] AND prodyear[new] THEN price[expensive]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax,\n",
       " IF engine_volume[high] AND prodyear[new] THEN price[very expensive]\n",
       " \tAND aggregation function : fmin\n",
       " \tOR aggregation function  : fmax]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fuzzy_rules = [\n",
    "    rule11,\n",
    "    rule12,\n",
    "    rule13,\n",
    "    rule21,\n",
    "    rule22, \n",
    "    rule23,\n",
    "]\n",
    "\n",
    "price_cntrl = ctrl.ControlSystem(fuzzy_rules)\n",
    "\n",
    "sim = ctrl.ControlSystemSimulation(price_cntrl)\n",
    "\n",
    "fuzzy_rules"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Пример использования полученной нечеткой системы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============\n",
      " Antecedents \n",
      "=============\n",
      "Antecedent: engine_volume           = 1.5\n",
      "  - low                             : 0.85\n",
      "  - average                         : 0.15\n",
      "  - high                            : 0.0\n",
      "Antecedent: prodyear                = 2016\n",
      "  - old                             : 0.0017558299039780523\n",
      "  - new                             : 0.08000000000000002\n",
      "\n",
      "=======\n",
      " Rules \n",
      "=======\n",
      "RULE #0:\n",
      "  IF engine_volume[low] AND prodyear[old] THEN price[very cheap]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - engine_volume[low]                                     : 0.85\n",
      "  - prodyear[old]                                          : 0.0017558299039780523\n",
      "                      engine_volume[low] AND prodyear[old] = 0.0017558299039780523\n",
      "  Activation (THEN-clause):\n",
      "                                         price[very cheap] : 0.0017558299039780523\n",
      "\n",
      "RULE #1:\n",
      "  IF engine_volume[average] AND prodyear[old] THEN price[cheap]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - engine_volume[average]                                 : 0.15\n",
      "  - prodyear[old]                                          : 0.0017558299039780523\n",
      "                  engine_volume[average] AND prodyear[old] = 0.0017558299039780523\n",
      "  Activation (THEN-clause):\n",
      "                                              price[cheap] : 0.0017558299039780523\n",
      "\n",
      "RULE #2:\n",
      "  IF engine_volume[high] AND prodyear[old] THEN price[average]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - engine_volume[high]                                    : 0.0\n",
      "  - prodyear[old]                                          : 0.0017558299039780523\n",
      "                     engine_volume[high] AND prodyear[old] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                            price[average] : 0.0\n",
      "\n",
      "RULE #3:\n",
      "  IF engine_volume[low] AND prodyear[new] THEN price[average]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - engine_volume[low]                                     : 0.85\n",
      "  - prodyear[new]                                          : 0.08000000000000002\n",
      "                      engine_volume[low] AND prodyear[new] = 0.08000000000000002\n",
      "  Activation (THEN-clause):\n",
      "                                            price[average] : 0.08000000000000002\n",
      "\n",
      "RULE #4:\n",
      "  IF engine_volume[average] AND prodyear[new] THEN price[expensive]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - engine_volume[average]                                 : 0.15\n",
      "  - prodyear[new]                                          : 0.08000000000000002\n",
      "                  engine_volume[average] AND prodyear[new] = 0.08000000000000002\n",
      "  Activation (THEN-clause):\n",
      "                                          price[expensive] : 0.08000000000000002\n",
      "\n",
      "RULE #5:\n",
      "  IF engine_volume[high] AND prodyear[new] THEN price[very expensive]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - engine_volume[high]                                    : 0.0\n",
      "  - prodyear[new]                                          : 0.08000000000000002\n",
      "                     engine_volume[high] AND prodyear[new] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                     price[very expensive] : 0.0\n",
      "\n",
      "\n",
      "==============================\n",
      " Intermediaries and Conquests \n",
      "==============================\n",
      "Consequent: price                    = 1065.2447541258305\n",
      "  very cheap:\n",
      "    Accumulate using accumulation_max : 0.0017558299039780523\n",
      "  cheap:\n",
      "    Accumulate using accumulation_max : 0.0017558299039780523\n",
      "  average:\n",
      "    Accumulate using accumulation_max : 0.08000000000000002\n",
      "  expensive:\n",
      "    Accumulate using accumulation_max : 0.08000000000000002\n",
      "  very expensive:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "np.float64(1065.2447541258305)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim.input[\"prodyear\"] = 2016\n",
    "sim.input[\"engine_volume\"] = 1.5\n",
    "sim.compute()\n",
    "sim.print_state()\n",
    "display(sim.output[\"price\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Функция для автоматизации вычисления целевой переменной Y на основе вектора признаков X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fuzzy_pred(row):\n",
    "    sim.input[\"prodyear\"] = row[\"Prodyear\"]\n",
    "    sim.input[\"engine_volume\"] = row[\"Engine volume\"]\n",
    "    sim.compute()\n",
    "    return sim.output[\"price\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Тестирование нечеткой системы на обучающей выборке"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Price</th>\n",
       "      <th>Prodyear</th>\n",
       "      <th>Engine volume</th>\n",
       "      <th>PricePred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3329</th>\n",
       "      <td>188</td>\n",
       "      <td>2009</td>\n",
       "      <td>2.5</td>\n",
       "      <td>99.900555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15830</th>\n",
       "      <td>16621</td>\n",
       "      <td>2005</td>\n",
       "      <td>2.4</td>\n",
       "      <td>99.815314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>3293</td>\n",
       "      <td>2014</td>\n",
       "      <td>5.7</td>\n",
       "      <td>99.970383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1672</th>\n",
       "      <td>59464</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1065.244754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10342</th>\n",
       "      <td>8500</td>\n",
       "      <td>2006</td>\n",
       "      <td>1.5</td>\n",
       "      <td>99.839062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11936</th>\n",
       "      <td>5018</td>\n",
       "      <td>2011</td>\n",
       "      <td>1.8</td>\n",
       "      <td>99.933398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15103</th>\n",
       "      <td>21012</td>\n",
       "      <td>2012</td>\n",
       "      <td>2.5</td>\n",
       "      <td>99.947365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4720</th>\n",
       "      <td>1568</td>\n",
       "      <td>2016</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1065.244754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9631</th>\n",
       "      <td>34811</td>\n",
       "      <td>2012</td>\n",
       "      <td>3.0</td>\n",
       "      <td>99.947365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6122</th>\n",
       "      <td>21181</td>\n",
       "      <td>2012</td>\n",
       "      <td>2.0</td>\n",
       "      <td>99.947365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3261</th>\n",
       "      <td>23521</td>\n",
       "      <td>2014</td>\n",
       "      <td>2.5</td>\n",
       "      <td>99.970383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12788</th>\n",
       "      <td>10349</td>\n",
       "      <td>2009</td>\n",
       "      <td>1.8</td>\n",
       "      <td>99.900555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11298</th>\n",
       "      <td>76029</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1065.244754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5113</th>\n",
       "      <td>17562</td>\n",
       "      <td>2012</td>\n",
       "      <td>1.8</td>\n",
       "      <td>99.947365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12635</th>\n",
       "      <td>22580</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1065.244754</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Price  Prodyear  Engine volume    PricePred\n",
       "3329     188      2009            2.5    99.900555\n",
       "15830  16621      2005            2.4    99.815314\n",
       "3384    3293      2014            5.7    99.970383\n",
       "1672   59464      2016            2.2  1065.244754\n",
       "10342   8500      2006            1.5    99.839062\n",
       "11936   5018      2011            1.8    99.933398\n",
       "15103  21012      2012            2.5    99.947365\n",
       "4720    1568      2016            3.5  1065.244754\n",
       "9631   34811      2012            3.0    99.947365\n",
       "6122   21181      2012            2.0    99.947365\n",
       "3261   23521      2014            2.5    99.970383\n",
       "12788  10349      2009            1.8    99.900555\n",
       "11298  76029      2016            2.3  1065.244754\n",
       "5113   17562      2012            1.8    99.947365\n",
       "12635  22580      2016            2.0  1065.244754"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_train = cars_train.copy()\n",
    "\n",
    "result_train[\"PricePred\"] = result_train.apply(fuzzy_pred, axis=1)\n",
    "\n",
    "result_train.head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Тестирование нечеткой системы на тестовой выборке"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Price</th>\n",
       "      <th>Prodyear</th>\n",
       "      <th>Engine volume</th>\n",
       "      <th>PricePred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13393</th>\n",
       "      <td>3763</td>\n",
       "      <td>2016</td>\n",
       "      <td>2.0</td>\n",
       "      <td>106524.475413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4751</th>\n",
       "      <td>470</td>\n",
       "      <td>2011</td>\n",
       "      <td>2.4</td>\n",
       "      <td>9993.339772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11945</th>\n",
       "      <td>706</td>\n",
       "      <td>2010</td>\n",
       "      <td>1.3</td>\n",
       "      <td>9991.779367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5150</th>\n",
       "      <td>470</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.0</td>\n",
       "      <td>77990.662719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10864</th>\n",
       "      <td>5488</td>\n",
       "      <td>2014</td>\n",
       "      <td>2.5</td>\n",
       "      <td>9997.038307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5343</th>\n",
       "      <td>7840</td>\n",
       "      <td>1998</td>\n",
       "      <td>2.8</td>\n",
       "      <td>9960.397848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9938</th>\n",
       "      <td>19444</td>\n",
       "      <td>2013</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9995.969432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6576</th>\n",
       "      <td>26343</td>\n",
       "      <td>2017</td>\n",
       "      <td>3.0</td>\n",
       "      <td>103432.672018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12789</th>\n",
       "      <td>39750</td>\n",
       "      <td>2017</td>\n",
       "      <td>1.6</td>\n",
       "      <td>90913.773797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5395</th>\n",
       "      <td>18189</td>\n",
       "      <td>2012</td>\n",
       "      <td>1.9</td>\n",
       "      <td>9994.736527</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3848 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Price  Prodyear  Engine volume      PricePred\n",
       "13393   3763      2016            2.0  106524.475413\n",
       "4751     470      2011            2.4    9993.339772\n",
       "11945    706      2010            1.3    9991.779367\n",
       "5150     470      2019            2.0   77990.662719\n",
       "10864   5488      2014            2.5    9997.038307\n",
       "...      ...       ...            ...            ...\n",
       "5343    7840      1998            2.8    9960.397848\n",
       "9938   19444      2013            2.0    9995.969432\n",
       "6576   26343      2017            3.0  103432.672018\n",
       "12789  39750      2017            1.6   90913.773797\n",
       "5395   18189      2012            1.9    9994.736527\n",
       "\n",
       "[3848 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_test = cars_test.copy()\n",
    "\n",
    "result_test[\"PricePred\"] = result_test.apply(fuzzy_pred, axis=1)\n",
    "result_test[\"PricePred\"] = result_test[\"PricePred\"].apply(lambda x: x * 100)\n",
    "\n",
    "display(result_test)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Оценка результатов на основе метрик для задачи регрессии"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'RMSE_train': 34126.997123579145,\n",
       " 'RMSE_test': 34126.997123579145,\n",
       " 'RMAE_test': 140.19755698149206,\n",
       " 'R2_test': -2.0018563819330226}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "from sklearn import metrics\n",
    "\n",
    "\n",
    "rmetrics = {}\n",
    "\n",
    "rmetrics[\"RMSE_train\"] = math.sqrt(\n",
    "    metrics.mean_squared_error(result_test[\"Price\"], result_test[\"PricePred\"])\n",
    ")\n",
    "rmetrics[\"RMSE_test\"] = math.sqrt(\n",
    "    metrics.mean_squared_error(result_test[\"Price\"], result_test[\"PricePred\"])\n",
    ")\n",
    "rmetrics[\"RMAE_test\"] = math.sqrt(\n",
    "    metrics.mean_absolute_error(result_test[\"Price\"], result_test[\"PricePred\"])\n",
    ")\n",
    "rmetrics[\"R2_test\"] = metrics.r2_score(\n",
    "    result_test[\"Price\"], result_test[\"PricePred\"]\n",
    ")\n",
    "\n",
    "rmetrics"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}