schedule_optim.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Flight scheduling optimization with RL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from stable_baselines3 import DQN, PPO, A2C\n",
    "from stable_baselines3.common.env_checker import check_env\n",
    "from stable_baselines3.common.monitor import Monitor\n",
    "from gymnasium.wrappers import NormalizeObservation, NormalizeReward\n",
    "from pandas import Timestamp\n",
    "import warnings\n",
    "\n",
    "from schedule_optimizer.flight_scheduling import FlightSchedulingEnv\n",
    "from schedule_optimizer.utils import generate_random_flight_schedule, generate_lambdas\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple case : 2 connecting flights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate flight schedule and lambdas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>departure</th>\n",
       "      <th>arrival</th>\n",
       "      <th>way</th>\n",
       "      <th>airport</th>\n",
       "      <th>departure_minutes</th>\n",
       "      <th>arrival_minutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1900-01-01 08:00:00</td>\n",
       "      <td>1900-01-01 10:00:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>480</td>\n",
       "      <td>600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1900-01-01 13:30:00</td>\n",
       "      <td>1900-01-01 14:30:00</td>\n",
       "      <td>1</td>\n",
       "      <td>MAD</td>\n",
       "      <td>910</td>\n",
       "      <td>970</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            departure             arrival  way airport  departure_minutes  \\\n",
       "0 1900-01-01 08:00:00 1900-01-01 10:00:00   -1     JFK                480   \n",
       "1 1900-01-01 13:30:00 1900-01-01 14:30:00    1     MAD                910   \n",
       "\n",
       "   arrival_minutes  \n",
       "0              600  \n",
       "1              970  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "schedule_0 = pd.DataFrame({\n",
    "    'departure' : [Timestamp('1900-01-01 08:00:00'), Timestamp('1900-01-01 13:30:00')],\n",
    "    'arrival' : [Timestamp('1900-01-01 10:00:00'), Timestamp('1900-01-01 14:30:00')],\n",
    "    'way' : [-1, 1],\n",
    "    'airport' : ['JFK', 'MAD'],\n",
    "    'departure_minutes' : [480, 910],\n",
    "    'arrival_minutes' : [600, 970],\n",
    "})\n",
    "schedule_0 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'JFKMAD': 1000, 'MADJFK': 1000}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lambdas = generate_lambdas(schedule_0)\n",
    "lambdas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = FlightSchedulingEnv(\n",
    "    flight_schedule=schedule_0, \n",
    "    lambdas=lambdas, \n",
    "    max_steps=1000,\n",
    "    revenue_estimation='classic',\n",
    "    obs='cnx'\n",
    ")\n",
    "env = NormalizeObservation(env)\n",
    "#env = NormalizeReward(env)\n",
    "check_env(env)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "Observation: [-0.25768915] Reward: 0.0\n",
      "2\n",
      "Observation: [-1.4727309] Reward: 27.7777777777776\n",
      "1\n",
      "Observation: [-2.26575222] Reward: 27.77777777777783\n",
      "1\n",
      "Observation: [-2.60875862] Reward: 27.77777777777783\n",
      "0\n",
      "Observation: [-1.54152496] Reward: -27.77777777777783\n",
      "4\n",
      "Observation: [-1.42586313] Reward: 0.0\n",
      "2\n",
      "Observation: [-2.00443255] Reward: 27.77777777777783\n",
      "0\n",
      "Observation: [-1.15364401] Reward: -27.77777777777783\n",
      "4\n",
      "Observation: [-1.09928565] Reward: 0.0\n",
      "3\n",
      "Observation: [-0.31609357] Reward: -27.77777777777783\n"
     ]
    }
   ],
   "source": [
    "obs = env.reset()\n",
    "\n",
    "for _ in range(10):\n",
    "    action = env.action_space.sample()\n",
    "    obs, reward, done, truncated, _ = env.step(action)\n",
    "    print(action)\n",
    "    print(\"Observation:\", obs, \"Reward:\", reward)\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RL Policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = PPO(\"MlpPolicy\", env).learn(total_timesteps=100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "250.0\n",
      "250.0\n",
      "250.0\n",
      "250.0\n",
      "250.0\n",
      "222.22222222222217\n",
      "250.0\n",
      "250.0\n",
      "250.0\n",
      "250.0\n"
     ]
    }
   ],
   "source": [
    "for _ in range(10):\n",
    "    obs, _ = env.reset()\n",
    "    total_reward = 0\n",
    "    done = False\n",
    "    count = 0\n",
    "    while not done:\n",
    "        action, _ = model.predict(obs)\n",
    "        '''if count < 9:\n",
    "            action = 1\n",
    "            count += 1\n",
    "        else:\n",
    "            action = 4\n",
    "            count += 1'''\n",
    "        obs, reward, done, _, _ = env.step(action)\n",
    "        #print('action : ', action)\n",
    "        #print('obs : ', obs)\n",
    "        #print('reward : ', reward)\n",
    "        total_reward += reward\n",
    "    print(total_reward)\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = Monitor(env, 'logs/')\n",
    "model = PPO(\"MlpPolicy\", env, verbose=1, tensorboard_log=\"logs/\").learn(total_timesteps=100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%tensorboard --logdir=logs/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random schedule"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generating schedule and lambdas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>departure</th>\n",
       "      <th>arrival</th>\n",
       "      <th>way</th>\n",
       "      <th>airport</th>\n",
       "      <th>departure_minutes</th>\n",
       "      <th>arrival_minutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1900-01-01 08:22:00</td>\n",
       "      <td>1900-01-01 10:42:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>502</td>\n",
       "      <td>642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1900-01-01 08:32:00</td>\n",
       "      <td>1900-01-01 10:52:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>512</td>\n",
       "      <td>652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1900-01-01 08:32:00</td>\n",
       "      <td>1900-01-01 09:03:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>512</td>\n",
       "      <td>543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1900-01-01 08:35:00</td>\n",
       "      <td>1900-01-01 10:43:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>515</td>\n",
       "      <td>643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1900-01-01 08:37:00</td>\n",
       "      <td>1900-01-01 10:47:00</td>\n",
       "      <td>1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>517</td>\n",
       "      <td>647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>1900-01-01 21:04:00</td>\n",
       "      <td>1900-01-01 21:53:00</td>\n",
       "      <td>1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>1264</td>\n",
       "      <td>1313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1900-01-01 21:14:00</td>\n",
       "      <td>1900-01-01 21:58:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>1274</td>\n",
       "      <td>1318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1900-01-01 21:16:00</td>\n",
       "      <td>1900-01-01 22:58:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>1276</td>\n",
       "      <td>1378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1900-01-01 21:35:00</td>\n",
       "      <td>1900-01-01 23:07:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>1295</td>\n",
       "      <td>1387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1900-01-01 21:51:00</td>\n",
       "      <td>1900-01-01 22:41:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>1311</td>\n",
       "      <td>1361</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             departure             arrival  way airport  departure_minutes  \\\n",
       "0  1900-01-01 08:22:00 1900-01-01 10:42:00    1     FCO                502   \n",
       "1  1900-01-01 08:32:00 1900-01-01 10:52:00   -1     FCO                512   \n",
       "2  1900-01-01 08:32:00 1900-01-01 09:03:00   -1     JFK                512   \n",
       "3  1900-01-01 08:35:00 1900-01-01 10:43:00    1     FCO                515   \n",
       "4  1900-01-01 08:37:00 1900-01-01 10:47:00    1     JFK                517   \n",
       "..                 ...                 ...  ...     ...                ...   \n",
       "95 1900-01-01 21:04:00 1900-01-01 21:53:00    1     JFK               1264   \n",
       "96 1900-01-01 21:14:00 1900-01-01 21:58:00    1     FCO               1274   \n",
       "97 1900-01-01 21:16:00 1900-01-01 22:58:00   -1     JFK               1276   \n",
       "98 1900-01-01 21:35:00 1900-01-01 23:07:00    1     FCO               1295   \n",
       "99 1900-01-01 21:51:00 1900-01-01 22:41:00   -1     FCO               1311   \n",
       "\n",
       "    arrival_minutes  \n",
       "0               642  \n",
       "1               652  \n",
       "2               543  \n",
       "3               643  \n",
       "4               647  \n",
       "..              ...  \n",
       "95             1313  \n",
       "96             1318  \n",
       "97             1378  \n",
       "98             1387  \n",
       "99             1361  \n",
       "\n",
       "[100 rows x 6 columns]"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_schedule = generate_random_flight_schedule(100)\n",
    "random_schedule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [],
   "source": [
    "perfect_schedule = random_schedule.copy()\n",
    "perfect_schedule.loc[perfect_schedule['way']==-1, \"arrival_minutes\"] = 680\n",
    "perfect_schedule.loc[perfect_schedule['way']==1, \"departure_minutes\"] = 800\n",
    "perfect_schedule.loc[perfect_schedule['way']==1, \"arrival_minutes\"] = 1000\n",
    "perfect_schedule.loc[perfect_schedule['way']==-1, \"departure_minutes\"] = 400"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'FCOJFK': 1000,\n",
       " 'JFKFCO': 1000,\n",
       " 'FCOMAD': 1000,\n",
       " 'MADFCO': 1000,\n",
       " 'JFKMAD': 1000,\n",
       " 'MADJFK': 1000}"
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_lambdas = generate_lambdas(random_schedule)\n",
    "random_lambdas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = FlightSchedulingEnv(\n",
    "    flight_schedule=random_schedule,\n",
    "    lambdas=random_lambdas,\n",
    "    max_steps=1000,\n",
    "    revenue_estimation='classic'\n",
    ")\n",
    "perfect_env = FlightSchedulingEnv(\n",
    "    flight_schedule=perfect_schedule,\n",
    "    lambdas=random_lambdas,\n",
    "    max_steps=1000,\n",
    "    revenue_estimation='classic'\n",
    ")\n",
    "env = NormalizeObservation(env)\n",
    "env = NormalizeReward(env)\n",
    "check_env(env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1674000.0"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perfect_env.calculate_revenue()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>departure</th>\n",
       "      <th>arrival</th>\n",
       "      <th>way</th>\n",
       "      <th>airport</th>\n",
       "      <th>departure_minutes</th>\n",
       "      <th>arrival_minutes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1900-01-01 08:22:00</td>\n",
       "      <td>1900-01-01 10:42:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>502</td>\n",
       "      <td>642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1900-01-01 08:32:00</td>\n",
       "      <td>1900-01-01 10:52:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>512</td>\n",
       "      <td>652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1900-01-01 08:32:00</td>\n",
       "      <td>1900-01-01 09:03:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>512</td>\n",
       "      <td>543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1900-01-01 08:35:00</td>\n",
       "      <td>1900-01-01 10:43:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>515</td>\n",
       "      <td>643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1900-01-01 08:37:00</td>\n",
       "      <td>1900-01-01 10:47:00</td>\n",
       "      <td>1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>517</td>\n",
       "      <td>647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>1900-01-01 21:04:00</td>\n",
       "      <td>1900-01-01 21:53:00</td>\n",
       "      <td>1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>1264</td>\n",
       "      <td>1313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1900-01-01 21:14:00</td>\n",
       "      <td>1900-01-01 21:58:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>1274</td>\n",
       "      <td>1318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1900-01-01 21:16:00</td>\n",
       "      <td>1900-01-01 22:58:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>JFK</td>\n",
       "      <td>1276</td>\n",
       "      <td>1378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1900-01-01 21:35:00</td>\n",
       "      <td>1900-01-01 23:07:00</td>\n",
       "      <td>1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>1295</td>\n",
       "      <td>1387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1900-01-01 21:51:00</td>\n",
       "      <td>1900-01-01 22:41:00</td>\n",
       "      <td>-1</td>\n",
       "      <td>FCO</td>\n",
       "      <td>1311</td>\n",
       "      <td>1361</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             departure             arrival  way airport  departure_minutes  \\\n",
       "0  1900-01-01 08:22:00 1900-01-01 10:42:00    1     FCO                502   \n",
       "1  1900-01-01 08:32:00 1900-01-01 10:52:00   -1     FCO                512   \n",
       "2  1900-01-01 08:32:00 1900-01-01 09:03:00   -1     JFK                512   \n",
       "3  1900-01-01 08:35:00 1900-01-01 10:43:00    1     FCO                515   \n",
       "4  1900-01-01 08:37:00 1900-01-01 10:47:00    1     JFK                517   \n",
       "..                 ...                 ...  ...     ...                ...   \n",
       "95 1900-01-01 21:04:00 1900-01-01 21:53:00    1     JFK               1264   \n",
       "96 1900-01-01 21:14:00 1900-01-01 21:58:00    1     FCO               1274   \n",
       "97 1900-01-01 21:16:00 1900-01-01 22:58:00   -1     JFK               1276   \n",
       "98 1900-01-01 21:35:00 1900-01-01 23:07:00    1     FCO               1295   \n",
       "99 1900-01-01 21:51:00 1900-01-01 22:41:00   -1     FCO               1311   \n",
       "\n",
       "    arrival_minutes  \n",
       "0               642  \n",
       "1               652  \n",
       "2               543  \n",
       "3               643  \n",
       "4               647  \n",
       "..              ...  \n",
       "95             1313  \n",
       "96             1318  \n",
       "97             1378  \n",
       "98             1387  \n",
       "99             1361  \n",
       "\n",
       "[100 rows x 6 columns]"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random_schedule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = PPO(\"MlpPolicy\", env).learn(total_timesteps=100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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SLc6apiuv6vTp08bdd99tREVFGS1atDBGjRplHDx40Kn3aU9FnFu2bDEGDBhghIaGGp07dzaef/55m/PsTX9+6NAh46abbjLatGljtG7d2rjllluM3NzcajFWxPLTTz/ZXNNe/wLGnXfeWS3Ozp0720xRX9P059dff73d93jVVVfZtG3fvt0YPHiwERISYnTs2NFYuHChsWTJEgMw8vPza+4wi7/+9a9Gjx49jJCQEOMXv/iFsWbNmhr/bF955RWjb9++RlhYmBEREWH06tXLuP/++43c3Nw672MYhvHqq68agBEREWEzxXllq1evNvr06WOEhIQYkZGRxqRJk4xDhw7ZnKPpz0XE3QIMwwsVqSIiIl4wdOhQCgoK2L17t7dD8bpZs2bx8ssvU1RUVOOkFSIiUjPVSImIiDRyp0+fttk/duwYb731FoMGDVISJSLSQKqREhERaeQGDBjA0KFD6dGjB0eOHOG1117j1KlTPPTQQ94OTUTEbymREhERaeSuu+463nvvPV555RUCAgJITk7mtddeY8iQId4OTUTEb3l1aF9mZiajRo0iPj6egIAA3n//fZvjhmHw8MMPExcXR1hYGMOHD6+2lkVhYSGTJk2iVatWtGnThttuu81mFiEREZEKn376aZOsj3r88cf54YcfKCkpobi4mM8//9xl64CJiDRVXk2kiouLSUpK4oUXXrB7/Mknn2TJkiUsW7aMr776ihYtWjBixAhKS0ut50yaNIlvv/2WjRs38ve//53MzExmzJjhqbcgIiIiItJga9bANddAVBQEBEClJd/Ex/nMrH0BAQGsXbuWlJQUwPw0Kj4+nvvuu485c+YAcPLkSWJiYsjIyGD8+PHs2bOHX/ziF3zzzTf069cPgI8++ojrrruOQ4cOER8f7623IyIiIiJSp7fegv37IT4epk+H7duhd29vRyX14bOz9u3fv5/8/HyboQetW7emf//+fPHFFwB88cUXtGnTxppEAQwfPpzAwEC++uorj8csIiIiIuKIKVPg4YdBo239j89ONpGfnw9ATEyMTXtMTIz1WH5+Pu3bt7c53rx5cyIjI63n2FNWVkZZWZl1v7y8nMLCQqKioupc4V1ERERExNV+/jkAiKCoqIhTp8q9HU6TZhgGP//8M/Hx8QQG1vzcyWcTKXdauHAhCxYs8HYYIiLikwYDc4G+QDyQAnzgzYBEpEnoDGQzePAgYKe3gxHg4MGDdOzYscbjPptIxcbGAnDkyBHi4uKs7UeOHKG3ZeBobGwsR48etXnd2bNnKSwstL7ennnz5jF79mzr/smTJ0lISOCHH34gMjLShe9CAEwmE5988gnDhg0jKCjI2+E0Oupf91Mfu5ev9e+//hXE1183JynpHKmp8Je//IXrrjN5Oyyn+FofNzbqX/drFH383//y7jVvMifwFQgwP+V4+0+7GHDpSQBy8kNJngCfvPpnenV1YAbqH3+Eu++GDRugV68GhdYo+teFfv75ZxITE4mIiKj1PJ9NpBITE4mNjWXTpk3WxOnUqVN89dVX3HHHHYB5gcETJ06wdetW+vbtC8DHH39MeXk5/fv3r/HaISEhhISEVGuPjIwkKirK9W+miTOZTISHhxMVFaX/Od1A/et+6mP38rX+vfVW8waQmgoREa3w938afK2PGxv1r/s1ij5u1YpJpvcY/v4cuOQSADp06ENYmPnwz9nmn2369SOqt2PXpbTU/LOBf1k1iv51oYo+qKvkx6uJVFFREXv37rXu79+/nx07dhAZGUlCQgKzZs3i0UcfpVu3biQmJvLQQw8RHx9vndmvR48eXHvttUyfPp1ly5ZhMpm46667GD9+vGbsExERx+TkQEFBlcZk2LcPtp30SkjVREdDQoK3oxCRBoqgiIiiHXDKUqt/qtLB3GCgJ+zZA+Wn63/RPXtcGKE4wquJ1JYtWxg2bJh1v2K4XWpqKhkZGdx///0UFxczY8YMTpw4waBBg/joo48IDQ21vmbFihXcdddd/OpXvyIwMJCxY8eyZMkSj78XERHxYzk50KMHlJRUOWDAnPvwmRqp8HDzlyYlU+Kj1qyBZctg61YoLNRU3jaio83/D0+ebNNcSFtySCCXeGA9WRPTgSxiySeWI/W7dni4+friUV5NpIYOHUpty1gFBATwyCOP8Mgjj9R4TmRkJCtXrnRHeCIi0lQUFJiTqOXLzQlVhb7AU0/DsIe9FprVnj3mL2AFBUqkxGcVF8OgQTBunHlNJKkkIcH8/3GVJ9/r1kUydcEF1v3xrAZg/ow80mfm1e/aelrtFT5bIyUiIiIi/mXKFPPP7GyvhuG7EhKqJTxpyZCWbu/kOMsmvkqJlIiISA1DbnxyaJ+G74gvsFtTWElD631qUm5ZV2nnTqhlXZ9a6amNuJgSKRERkUpDbopKAtl70DKz60TYP/t5dvRbSGSrsyTEeXkadH0RbPIyM2HRInMNUl4erF0Lljm4PKfGmsLKzGsiMXECLlkTKSwMVq2CIUPgdAMTM9UYiospkRIREQHrkJstn8KwieebZz9jXowxNRUyMrwSmYhVcTEkJcG0aTBmjJeCsNQUrrhjMzMzrrA2b1i6l8F9is07ucEwCli5Crq76InU4cPmTLIhT6RUYyhuoERKRESkkqFDoZZ5kES8auRI8+YLRicfov+I7637Hdqd8WI0Ip6nREpERETE17lynbMGDhG1Div8+lLyMFg7PYWUGusHfXRon2oMxYWUSImIiIj4Mlevc9bAWqHzwwqbm4cV2lkaoPBkM3Lyg8n9KQjugayFa6FzKbFRJmKjzzoWZ2XODu0D1RiKyymREhEREfFlrlznzIlaoWrDCrt0gWTbc9ZlwNSp5/fHz0sEYP58SE936Ha2TCZzIpWUBEFBTlxIxHWUSImIiIiIS6SlmTeRpkCJlIiIiIgbrVkDy5aZpywvLITt26F3bwcu4Op1zhytFXJlfVZlGmonfk6JlIiIiIgbFRfDoEEwbhxMn96AC7h6nTNHEhhX12dVpnWdxM8pkRIRERFxoylTzD+zs524iLfWOXNlfVZlWtdJGgElUiIiIiJ+QuucifgOJVIiIiLiEU7XCvm6Q4fg+PGaj+cGAz3NT2PKG7gWUlXurjOqVJ9VRAv20tVyYAf75zzPDj4hkkISOOj4tbWuk/g5JVIiIiLiEU7XCvm6yy5jxbERzORla9MGRjKYzZY9Fy9SC+6vM6pUn7VlS0uGzbzIemg2zwKQesMxMhYccPzammxC/JwSKREREfEIl9QK+bKSEka/Opr+7c4nFR3aLYFQy1i83GAYBaxcBd1d8ETKU3VGlvqsoclgzLB3QpRlE2lalEiJiIiIa9mdLrsSdwxx85Q6nqJEhJ0lolOZBwMSEW9RIiUiIiKuU+N02ZW5dohbJoNZxFy20pc84llLCinOTMtdm9qG0tld6wkKaUsOCeQSD6wna2I6kEUs+cRyxPl4VGck4hVKpERERMR1LNNlr7hjMzMzrrA2b1i6l8F9is07Lh7iVvzvViTtbMG0i0sYMxfnpuWuTV1D6b75xu5kE+vWRTJ1wQXW/fGsBmD+jDzSZ+Y5F5PqjES8RomUiIiIuNzo5EP0H/G9db9DuzNuu9fIgacYOfCU265fbx07QmJitea0ZEhLt/eCOMsmIv5IiZSIiIi4jmW67Ijp44mo8SQ3zF5nZcCc+8BdQ/tCQyEvD7ZtO99WXm7+uXMntG+vJ0QiTYQSKREREXGdStNlV1V4shk5+cHk/hQE90DWwrXQuZTYKBOx0Wcdu09eHtx8M5SWuijweiothRtusG0LC4NVq2DIEAgIcO905CJOsree2yWXeDsq/6RESkRERFzLMl12VesyYOrU8/vj55mHwc2fD+npDt5j2zZzUrN8uXlyiwp9cV+NVE3Ky+HwYXj1Vc9MRy7ihEa/npsHKZESERERj0hLM28i4j2Nfj03D1IiJSIiIv7HUotVfbpxN9dI2VMxtG/6dJdOR56ZCYsWmYdg5eXB2rWQkuKSS0tT4Mh6bmctM2ru3AmBga6PpZHOLqlESkRERPxPpVqsopJA9h4MMbdPhP2zn2dHv4VEtjpLQpzJ/bFUDO3LzHTpZBPFxZCUBNOmwZgxLrmkNBWOrucW9sP5Or/Tblgku7b11/yYEikRERHxT5ZarC2fwrCJ55tnP9MRgNRUyMjwQBwmkzmRSkqCoCCXXXbkSPMm4jBH13PrVnz+lwGufiJV1/prfkyJlIiIiPi1oUPBMLwdhYjv8eR6bk2REikRERERX2K3tiUZ9u2DbSfJ3NaSRX+JYeueMPIKgln71D5Shp1s2L0aae1Kk+foem6eGNrnotpBX6JESkRERMRX1Fjbcn4SjWKuJYmBTGMrY1jr3OQajbR2pclzcD03U6cSjh8/6J6hfdBoE3YlUiIiIiK+wlLbUtv6WCMBc+nUdc6tm9WIa1cEh9dzu/XWZkya1MWldX6NnRtSThERERER8UVpaeaawsrbmTMmJkzI8nZofkdPpERERER8RaX1sYpowV66Wg7sYP+c59nBJ0RSSAIHLe1OrpsVGmpepGrbtupx6ClVva1ZA8uWmdf8KiyE7duhd29vRyXupkRKRERExFdUqm3ZsqUlw2ZeZD00m2cBSCWDDKbWdAXHlJbCDTdUb1ftlEOKi2HQIBg3zrwuszQNSqREREREfImltmVoMhgzLG3btkHfvpbaqUuBreZ2Z2qkaqLaKYdNmWL+mZ3t1TDEw5RIiYiIiIjUl93p6S1yg4Ge5mS03MlpxDW80ucpkRIRERGfl5kJixaZa1Dy8mDtWkhJ8XZUHuRw7ZSTGum6P06rcXr6CpXWZmKnc/fS8Eqfp0RKREREfF5xMSQlwbRpMGaMt6PxgvrUTt1wjIwFB1xzPz0Nsa+ggBUlKcwMybCut7Rh6V4G9yk2H88NhlHAylXQ3YknUhpe6ReUSImIiIjPGznSvDVp9mqnbERZNnGn0ayj/2Proav5qWCHdme8HJF4ixIpERER8W3ValKSYd8+2Hayfq/X0xVxlehoIsLLiZiTUsMJLh7ap+GVPk2JlIiIiPguuzUpDq6d5IVakyZf09VYVRpiWVnhyWbk5AeT+1MQ3ANZC9dC51Jio0zERp9t2L30CwCfp0RKREREfFdBgTmJWr7cnFCBY1N+e6nWpMnXdDVmliGWla3LgKmVlvYaPy8RgPnzIT3dc6GJZymREhEREXEx1XQ1LWlp5k2aFiVSIiIi4rsqTft9XgOG9nmq1sTuGkMO1nR5mheHkK1ZA8uWmYdAFhbC9u3Qu7dXQhFxmBIpERER8V2WmpSinEL2Hgwxt02E/bOfZ0e/hUS2OktCnKn2a3gqUTh0CHr2tLPGkIOJn6d5cb2i4mIYNAjGjYPp0z1+exGnKJESERER35aQwJb/JTBs4vmm2c90BCA1FTIyvBNWNceOVa/nAsdqujzNy+sVTZli/pmd7fFbizhNiZSIiIj4vKFDwTC8HYWIyHlKpETEZTTWXUSatKgoO/Vc4BdD+zxRQ2a3fswiNxjoaX5CVn66+vHycvPPnTshMNBtIQKadlzqTYmUiLiMxrqLSJPWsaN1jaGiksCG13R5micSh5wcVnRLZ+aZJdamDYxkMJste3UsZBsWBqtWwZAhcNpOouVKXqwZE/+iREpEXEZj3UWkybOsMbTlU3y/psuTCgoYfeZd+j91I3TtCkCHdksg1DJeMzcYRgErV0H3Gp5IHT5sXunYnU+kvFwzJv5FiZSIiIiIi6mmq7oIioiILYJOZd4ORcQllEiJiONqG+cOdY91d4TGqouINJjP1K7aXQ8MCmlLDgnkEg+sJ2tiOpBFLPnEcuT8iZ4e2uepdcfErymREhHH5ORAjx6sKElhJi9bmx0a6+4IjVUXEWkwn6ldtawHVvWXcOvWRTJ1wQXW/fGsBmD+jDzSZ+adP9FTQ/tAv8CTelMiJSKOKSiAkhJGvzqa/u0OWJsdGuteXxqrLiLiFJ+qXbXUj1WWlgxp6fZOjrNsFiaTOZFKSoKgIDcGKVJ/SqREpEEiws4SoXHuIiK+wZNDrt1BT4HEDymREhHH1DDOHRwY6+4IjVUXES/IzIRFi8y1RXl5sHYtpKR4O6oaWIZcU1JSy0kuHHLtDhrGLX5IiZSIOKaGce7gwFh3R+i3lCLiBcXF5lFk06bBmDHejqYOliHXK+7YzMyMK6zNG5buZXCfYvOOq4Zcu4OGcYufUiIlIo6zM84dHBjrLiLi40aONG/+ZPSEFvSf3cy636FDdwiz7ERafvboAb09HZlI46RESkRERKSC3VqjZNi3D7adtP+a8nK3h1UfETnfEtGiUiynKh305RqpPXu8HYFIgyiREhEREYFaao0M0uec4jY6U0gU2+lN78p1RhVrHB06BImJHg0Z8HztqjuoHlb8kBIpEREREbDWGrF8uTmhqtAXelzTmbsu/5npj0ZVrzOqeKJy7Jh3EilP1666g+phxQ8pkRIRERGpw63XHKe3r03SUJlqV0U8TomUiIiICJifioSF2RkiZ8Cc+4Ad2J1CvGJoX34+bNvmfAx6MiPiF5RIiYiIiN9YswaWLTOv71RYCNu3Q+/eLryBYQBQRAv20tXavJ9EgjlT+2vHjYPTTj610npKIn5DiZSIiIj4jeJiGDTInLNMn+7iixcUsKJ0DDNDMjhnBFJ65vxU4rN59vx5VWukysvh8GHzKr6BgQ2/v9ZTEvErSqRERETEb0yZYv6Zne2e649mHf0fWw9dzU+jOrQ7Q1io+SlVdm4wiaN6uufGIuJ3fDqROnfuHOnp6Sxfvpz8/Hzi4+NJS0vjj3/8IwEBAQAYhsH8+fN59dVXOXHiBAMHDuSll16iW7duXo5exDFuH64iIuJP7K7nVElD10WqrQYpOpqI8HIi5qTU8OLO1FojNWSIa4b2aRpwEb/g04nUn/70J1566SXefPNNLrnkErZs2cLUqVNp3bo1d999NwBPPvkkS5Ys4c033yQxMZGHHnqIESNG8N133xEaGurldyBSf24driIi4k9qXM+pshqSmrrUVoNUwzTihSebkZMfTO5PQXAPZC1cC51LiY0yERt91nVD+0CTTYj4EZ9OpP7zn/9w4403cv311wNwwQUXsGrVKr7++mvA/DRq8eLF/PGPf+TGG28E4C9/+QsxMTG8//77jB8/3muxizjK3cNVRET8hmU9pxV3bGZmxhXW5g1L9zK4T7F5JzcYRlG9Xqk29alBsjON+LoMmDr1/P74eea1oubPh/R0wGQyJ1JJSRAUVL9YRMTv+XQideWVV/LKK6/www8/cNFFF7Fz5042b97MM888A8D+/fvJz89n+PDh1te0bt2a/v3788UXX9SYSJWVlVFWVmbdP3XqFAAmkwmTyeTGd9Q0VfSp+rZ+zN0UZPk81ud89a+7qY/dS/3rfn7Xx+XlEBbGyORDfHP1d9bmDu3OYCo31yuZysutPyv+u17CwszXd6AvJk0yb/aYTH7Yv35Ifexe6l9b9e0Hn06kHnzwQU6dOsXFF19Ms2bNOHfuHI899hiTLH+b5efnAxATE2PzupiYGOsxexYuXMiCBQuqtX/yySeEh4e78B1IZRs3bvR2CH7hyJEw4Bo2b95Mbu6per9O/et+6mP3Uv+6n1/18apVAHz77UnWru3Kvn1tOH48lAcf/Iorrsi3/F15KZuPHiW3ZT3/rmzZ0nzdw4fNm4v5Vf/6KfWxe6l/zUpqHVZ8nk8nUu+88w4rVqxg5cqVXHLJJezYsYNZs2YRHx9Pampqg687b948Zs+ebd0/deoUnTp1YtiwYURFRbkidKnEZDKxceNGrr76aoI05AEOHWLlpX/izqKnrE1/C05hULP/AJBdngB8z6B58+gduKvOy5nCwtj4+utcPW0aQRVFzuHh8M030LGjO95Bk6PPsHupf93PL/v40CE4dozA7Fb8fGk59487xLj7u3JRWDvii1oScDoYgPanE4gvqlSvVJeoKJf/3eiX/etn1Mfupf61VTFarS4+nUjNnTuXBx980DpEr1evXhw4cICFCxeSmppKbGwsAEeOHCEuLs76uiNHjtC7lunOQkJCCAkJqdYeFBSkD48bqX8tjh9nTNEKBj41stL0uosIskyvG2QZ9x/0xhsE1Wfcv6XIOegf/yAoMPB8DcDx45CY6M530uToM+xe6l/386s+TkyExERG9TOXQgFwP2wvuJBp88+fNvkPXYBK9Upe5Ff966fUx+6l/jWrbx84ObWMe5WUlBBYZfabZs2aUW4ZC52YmEhsbCybNm2yHj916hRfffUVAwYM8GisIo6IoIiusUV07VRG105l1jVKRESkdr/8JRhG9c3bSZSIND0+/URq1KhRPPbYYyQkJHDJJZewfft2nnnmGaZNmwZAQEAAs2bN4tFHH6Vbt27W6c/j4+NJSUnxbvAiNYmONg+9mzzZprmQtuSQQC7xwHqyJqYDWcSSTyxHar6evfVLtA6JiPg7u+tIJcO+fbDtJGs+bsOy96LZ+n04hSebs33lHnpXPMXXFOIi4gE+nUgtXbqUhx56iN/+9rccPXqU+Ph4Zs6cycMPP2w95/7776e4uJgZM2Zw4sQJBg0axEcffaQ1pMR31bBOybp1kUxdcIF1fzyrAZg/I4/0mXk1X8/e+iX6EiEi/qzGdaQMmHMf8AHFTGYQiYwjl+n82XY9qdrWihIRcRGfTqQiIiJYvHgxixcvrvGcgIAAHnnkER555BHPBSbiLDvrlKQlQ1q6vZPjLFsNtH6JiDQ2lnWkWL7cnFBV6As89TQMexjL0ntkV11Pqj5rRYmIuIBPJ1IiIiIi5OXBiRNAsnk2vz2Hzh/7qQXQE/bvh/Lj5p9gTqg8pWIdq507z48MaAiNJhDxK0qkRERExLdUqiUtogV76Wo5MIn9i99nB5/wI135C6l8xeUAfPKHjfRm8flrVKlDdSt7taoNoSGJIn5FiZSIiIj4lkq1pFv+eoxhj19tPTSbZwEYfkke/bse44bI/dz+RgxMnATX9TOf1KYNxNUyJNrV7NWqOkpDEkX8jhIpERER8T2WWtKhbOPU4xEceWp5pbX3zliXjcjObQlvADEx0MOnV3URkUZGiZSIiIj4ruhoIsLLiZiTUsMJnYFsePYZeHaxx8Ky4cqhfVq6QsRvKJESERER31V5yYi8PLj5ZigtrbL2Hhwmnh0k1b32XmgovPdeg4b+1bh2lSuG9oEmmxDxM0qkRERExLdVLBmxbRuUlsLy5az7caDN2ntPM5enmVv72nsVdUhxcZCc7HAYxd/CoOtg3G9g+nTMU7P3RstQiDRRSqRERETE76SNLiRtdCEAAX2TWfvUPlKGnXTrPadYFq/KznbrbUTETyiREhERr1mzBl56qRlffTWSn38OYvt26N3b21GJz6o0LbotA+bcB3xQ9zXqW4eUk2MeTmhPbjDQ0/yEq/y069aRqqAhfiJ+QYmUiIh4TXExXHmlQffu3/LCC328HY74ukr1UkUlgew9GGJunwj7Zz/Pjn4LiWx1loQ4U83XqE+SkpNjHrZXUlLDCZYJLiZOAHa6brKJClpPSsQvKJESERGvmTIFTKZy3njjJ2+HIv7CUi+15VMYNvF88+xnOgKQmgoZGU7eo6CAFSUpzAzJsD5h2rB0L4P7FJuP5wbDKGDlKnDlZBOg9aRE/IgSKREREfE7Q4eCYbjv+qNZR//H1tusXSUiUpkSKRER8Yyaak4q6kvgfM2Ju/h57cmaNbBsGWzdCoWFqKbMXeq7dpU7h/ZpPSkRn6dESkRE3C8nhxXd0pl5Zom1aQMjGcxm85fQxe+bGyu+mLqLn9eeFBfDoEEwbpxl+m1xj8prV1VSeLIZOfnB5P4UBPdA1sK10LmUqLZlUHbANUP7wO8TfpGmQomUiIi4X0EBo8+8S/+nbqw0VGoJhBrmJ1LbzNNYW2tO3KER1J5o+m0Pqli7qpJ1GTB16vn98fMSAfjjH8/Rr98BrSMl0sQokRIREY+IoIiI2CLoVObtUEQaJC3NvFVlMpWzfr2noxERb1MiJSIi7lfD+j+FtGVfyEUcnPssAFkT04EsYsknliOuj8Ofak8cWceoLq5e56ihfGTIWmYmLFpkrjXLy4O1ayElxdtRiYi/USIlIiLuV0PNybp1kUxdcAE8at4fz2oA5s/II31mnuvj8JEv8nWqraYMqDbZQV1cPRlCQ/lIjVpxsXkU3rRpMGaMV0MRET+mREpERDzDTs1JWjJM+oOJ9evXc9111xFkrS+Js2xNVG01ZVB9HaO6uHKdo4byoRq1kSPNm4iIM5RIiYiI+CDVlLmB3eGSybBvH2w7Wb9r+MtTTRFxOyVSIiIivqaWmrIcEsglHlhf/5oyXxra560atZwc6NEDSkqqHDBgzn3AB/W7jo8MT/QG1ZaJ2FIiJSIi4mvqqimzqHdNmS8M7QPvPs0pKDAnUcuXmxOqCn2Bp56GYQ/XfQ0fGp7oDaotE7GlREpERMQX1VBTlpZu7+Q6aspMJnMipXWOxAmqLROxpURKREREGr8ahks2aGifv0yh70rV6svqWVummjJpxJRIiYiISONXabhkUUkgew+GmNsnwv7Zz7Oj30IiW50lIc5k9+WZ21qy6C8xbM1qQV7n5k2rPshufVk9E9AmXFMmjZ8SKREREWkaLMMlt3wKwyaeb579TEcAUlMhI8P+S4uPQNIQmHZvE6wPsldfVp/asiZeUyaNnxIpERERaVKGDgXDcOw1qg8SkaqUSImIiEiTt2YNLFtmntq7sBC2b4fevanf2lPl5eafO3d6blZET9Ye2a0vc2BoX1OsKZMmQYmUiIiINHnFxTBoEIwbB9OnWxrru/aUN9bp8mTtkaW+rCin0OHaMk02IY2ZEikRERFp8qZMMf/Mzq7UWN+1pzy9Tpc3ao8SEtjyvwSHa8tEGjMlUiIiIiJSp4bUlok0ZkqkREREpEEyM2HRInNdUV4e/jEluN2ap0pyg4Ge5qc+rfIgNLTutae8NbRPtUciXqVESkRERBqkuBiSkmDaND+ZEtxS87SiJIWZvGxt3sBIBrPZstcZyIaJE4Cd1nOKaMFeulr395PIDpKIpJA4aknM6hIaCu+9B3Fxjr1OtUciXqdESkRERBrE76YEt9Q8jX51NP3bHbA2d2i3BEItY9Zyg2EUsHIVdD//dGnLlpYMm3mRdX82zwKQesMxXp2/v2E1UhW1TnFxkJzs1FsTEc9TIiUiIiJNSkTYWSI6lTn0mqH9ijC2brN7zFTuiqhExN8okRIREfFRPl2DVK3WqMraSr6kYhic3fWQzAppSw4J5BIPrCdrYjqQRSz5xHKk9us7UyOlWicRv6VESkRExEf5bA2S3fWV6rlAqzdUXnNpzx67k02sWxfJ1AUXWPfHsxqA+TPySJ+ZV/v1nZn+XLVOIn5LiZSIiIiP8tkaJHvrK1VdW8lXVF1zqWKrIi0Z0tLtXSDOstXCZDInUklJEBTkgqBFxB8okRIREfE1dqfodmLoXLmliGfnzupPTPRERESkQZRIiYiI+BK7w+bAqaFzlWp4Mk/3YxFz2Upf8ohnbfCtpPy4yLFkylJrVDR5ZqUpwXewf87z7OATIikkgYOOx+kuqkMSETdQIiUiIuJL7A2bA+eGzlWq4Sn+og1JO1sw7eISxswFzpSdH/ZWX5Zaoy0fldY4JXjGggM1vdrz9NRNRNxAiZSIiIgv6tGj+tpCXbpAQ5YbqlTDM7JfENayq7lOxJeQwNAZYMywdzDKsomINF5KpERERHzRnj1VGlxQI/XOO1UOTKrhXn5MT59ExEOUSImIiPiSSmsdFdHCNTVIFTVS06dXWefIkkjZWVfJWZkMtq3FIoUUT0yNXnmqcxERN1IiJSIi4ksqrXW0ZUtL19QgVTxx+uMfoXPn8+2TgT/8Eca4fsry4n+3sq3F8sTU6FWnOhcRcSMlUiIiIr7GstbR0GQX1SBVTDbRubPtBBYAbdsCDRguWIeRA08xcuApl19XRMRXKJESERFp7KKizIlUtaF9Tkyp7hBP3QcIDYW8PNi2zT3XVw2WiFgokRKRJmfNGli2DLZuhcJC2L4devf2dlQibtSxI+zaBZmZFJU2Z+/BEHP7RNg/+3l29FtIZKuzJMSZnL9XXh7cfDOUljp/rYYoLYUbbnDf9VWDJSIWSqREpMkpLoZBg2DcOPMv6EWajKQktvw7iGETzzfNfqYjAKmpkJHhgnts22ZOZiqvg+XMGli+RDVYIlKJEikRaXKmTDH/zM72ahgiXjF0KBiGt6MQEfF/SqREpHHLyTH/9tie3GCgp/m3zOWn7Z8D59fg2bkTAgNdHqLLqYaj0fGr4aiVpm8/z4M1Uu4WHm5+jyLS5CmREpHGKyfHPLSopKSGEzoD2TBxArCz5utUrMEzZEiVQn0fpRqORsevhqNapm8vyil0by2Wt+gXFSJioURKRBqvggJWlKQwMyTD+iRpw9K9DO5TbD6eGwyjgJWroHsdT6QOH4bMTN9/IqUajkbJ74ajJiSw5X8J7q3FEhHxMiVSItKojWYd/R9bD127AtCh3RkvRyTSNKgWS0QaOyVSItJ4RUcTEV5OxJyUGk5oxEP7VMPhv1xR11eVq+v8HBzelpkJixaZa7zy8mDtWkhJcT4MERFvUiIlIo2XpVaj6pfSwpPNyMkPJvenILgHshauhc6lxEaZiI0+W/06/jS0D1TD4c9ycljRLZ2ZZ5ZYmzYwksFstuzVM/mvytW/DHCwDq+4GJKSYNo0GDPG+duLiPgCJVIi0rglJFT7srcuA6ZOPb8/fl4iAPPnQ3q6nWuYTOZEKikJgoLcFqoIBQWMPvMu/Z+6sdJw1CUQahkjV9+6vqpc+cuABtThjRxp3kREGhMlUiLS5KSlmTcRXxRBERGxRdCpzNuhiIhILZRIiYiI1MDjtT1212CCQtqSQwK5xAPryZqYDmQRSz6xHKn7uu4Y2lffOrxqNV/JsG8fbDvpfByepmGzIlKJEikREZEaeLy2p4a6vnXrIpm64ALr/nhWAzB/Rh7pM/Pqvq6r6/zqm1DYXcvNjxfn1RptIlKJEikREZEaeKW2x05dX1oypKXbOznOstXBW3V+BQXmJGr5cnNCBdAXeOppGPaw5+JwBa3RJiJVKJESERGxpzENSas6/bmGqImIOE2JlIiISFWNbUha1RopTw1Rs9R8FU2eyV66Whp3sH/O8+zgEyIpJIGDTt8mk8EsYi5b6Use8awlhRR3/DlpjTYRqUSJlIiISFWNaUga2NZIZWV5boiapeZry0elDJt5kbV5Ns8CkHrDMTIWHHD6NsX/bkXSzhZMu7iEMXNx35+TnuSJSCVKpERERMR9EhIYOgOMGfYORlk254xMBmsp21ygSxdIdvqyIiK18vlE6vDhwzzwwANs2LCBkpISunbtyhtvvEG/fv0AMAyD+fPn8+qrr3LixAkGDhzISy+9RLdu3bwcuYiI+C2705A3sqF9jWGIWrU6NvB4LVt0NMTVY8IPEWl0fDqROn78OAMHDmTYsGFs2LCBdu3a8eOPP9K2bVvrOU8++SRLlizhzTffJDExkYceeogRI0bw3XffERoa6sXoRUTEb1mGpBXlFLL3YIi5bSLsn/08O/otJLLVWRLiTN6NEVjzcRuWvRfN1u/DKTzZnO0r99C7u511oqpOf94YhqjZrWMDjye84eGwe7dn7iUiPsWnE6k//elPdOrUiTfeeMPalpiYaP1vwzBYvHgxf/zjH7nxxhsB+Mtf/kJMTAzvv/8+48eP93jMIiLSSCQksOV/CQybeL5p9jMdAUhNhYwM74RVWfG3MOg6GPcbmD4dc2LR286J3pr+3J3s1bGBZ2vZKqZEP3bM/fcSEZ/j04nUunXrGDFiBLfccgufffYZHTp04Le//S3Tp08HYP/+/eTn5zN8+HDra1q3bk3//v354osvakykysrKKCsrs+6fOnUKAJPJhMnk/d8wNjYVfaq+dQ/1r/upj93Ll/t34EA4c8b+MV8It+KfuexsgCDLv2PVz/PlPm6w8nLzkMWK/67krGFgqtLmNmFh1ns1qv71MY3yM+xD1L+26tsPAYZhGG6OpcEqhubNnj2bW265hW+++YZ77rmHZcuWkZqayn/+8x8GDhxIbm4ucZXGJ48bN46AgABWr15t97rp6eksWLCgWvvKlSsJDw93z5sRERFxsS++iOOjjy5g7942FBcHc9993zB4cK63w/KqlJQbefDBr7jiinxvhyIifqqkpISJEydy8uRJWrVqVeN5Pv1Eqry8nH79+vH4448D0KdPH3bv3m1NpBpq3rx5zJ4927p/6tQpOnXqxLBhw4iKcn72ILFlMpnYuHEjV199NUGNZUiJD1H/up/62L3Uv/Vw6BBcdlm1eqDCsxMIMS4gmDL+yKP0WbKE6178a7WXm8LC2Pj661w9bRpBp+3UUHlTeDh88w107Oj4aw8dgmPHKCoJPF/LBkSVxRNf1JLI1udIiK3hkaKrREVhionRZ9jN9PeEe6l/bVWMVquLTydScXFx/OIXv7Bp69GjB3/9q/kfidjYWACOHDli80TqyJEj9O7du8brhoSEEBISUq09KChIHx43Uv+6l/rX/dTH7qX+rcXx46w4NoKZIRnmySKADUv3MrVPMQCbt7eA30DzBQsIGnFv9ddbJpsI+sc/CLK83idU1BgdPw6VaqDrLTEREhPZ+SkMqzTB4txnOwEerGWzDAPSZ9j91Mfupf41q28f+HQiNXDgQLKysmzafvjhBzp37gyYJ56IjY1l06ZN1sTp1KlTfPXVV9xxxx2eDldERMRtRrOO/o+th65dAejQzs1PWvzI0KHgu4UKItJY+XQide+993LllVfy+OOPM27cOL7++mteeeUVXnnlFQACAgKYNWsWjz76KN26dbNOfx4fH09KSop3gxcREXGVsjIiQs8SMSelhhMGApvh9/NY83sTy7idrfSlkCi205tLwn6wXUfKlzSWNa1EpMnx6UTqsssuY+3atcybN49HHnmExMREFi9ezKRJk6zn3H///RQXFzNjxgxOnDjBoEGD+Oijj7SGlIiINA45OTB8OCtKxzCTl63NGxjJJXxLDgn8iPkpVTadMRFEEjsYxztM58+ujyc0FN57z3WL0DaGNa1EpEny6UQK4IYbbuCGG26o8XhAQACPPPIIjzzyiAejEhER8RDLekmjXx1N/3YHrM0d2i1h9T/bMnXBBda2B3kSgPkz8hg+6hiMAlaugm7FtgvyNlRFTVNcHCQnN/w6IiKNgM8nUiIiIgIRYWeJ6FRm05Y2upC00YVk5waTOKon21fuoXd389C97Nxgb4QpItJkKJESERHxZdHR5jqiyZOrHSqkLTkkkEs8sJ6sielAFrHkA6FANkycAK6skVJNU60yM2HRIti6FfLyYO1aUNm2SOOkREpERMSXJSSYh9QVFJxvy8uDm29mXulCXmGmtXk85oXo55NOGhk1X9OZOifVNNWquBiSkmDaNBgzxtvRiIg7KZESERHxdQkJtsnLtm1QWspTr7Zhbrtvrc0d2p0hLNQARpOde7P9GqmsLNU5udHIkeZNRBo/JVIiIiJ+yl7dlHjRzp1VJvNIhn37YNtJr4VUIz1ZFHGaEikRERF/42DdlCnkAMeXpcMES41UeDhrvunEsgfNtTyFhbB9O1jWthdHHTpk/lmtBs2AOfcBH3gjqtqFh5uHjCqZEmkwJVIiIiL+xl7dlMW6dZE2U6KPZzWUwa0ffc+kiunPo6Mp/qwdgwbBuHEwfboHY2+Mjh0z/3z1VejR43x7X+Cpp2HYw14Jq0YV09gXFCiREnGCEikRERF/VLVuyiItGdLSbdtMJhPr12dB0nUQFATAlCnmY9nZ7g1TRKSxUiIlIiLS2FUMPatWwwPkBgM9zU8pyp2cGt0TfLG2JyrKPJnH9On+NbRP09iLOEWJlIiINDpr1sCyZar/ASAnBy67DF57rYZ1pDpjXW+KnZ6Pz1G+WNvTsSPs2gWZmRSVNmfvwRBz+0TYP/t5dvRbSGSrsyTEmbwbZ2W+mJCK+BklUiIi0ugUF6P6nwoFBaw8NYrbx19Ps4CfIQw2LN3L4D7F5uO5weenSe/u40+kfL22JymJLf8OYtjE802zn+kIQGoqZGR4JywRcQ8lUiIi0uio/sfWqGYfcvrZT7kqJoagwEA6tDvj7ZAaraFDwTC8HYWIeIISKRER8V85OXZnrrNqaP2Pl4Y9uWVIYnQ0ES3KiYsrpuuE/gQ1hqF9qu0RER+gREpERPxTTo55qumSklpOamCS4KU6HLcMSUxIgG++sdbwVEw2UXiyGTn5weT+FAT3QNbCtdC5lNgoE7HRZ110czdQbY+I+AglUiIi4p8KCqCkhBV3bGZmxhXWZqfrf7xYh+O2IYkVkyEkJVmnP1+XAVOnnj9l/LxEAObPh/R0F99fRKQRUiIlIiJ+bXTyIfqP+N66r/qf+klLM28iItIwSqRERMQ/RUdDeDgR08cTUeNJTgztc1MdTmYmLHrkNFt3NiOvIJi1T+0jZdhJ25NcvbZTebn5p711pDxBw/FEpBFSIiUiIv4pIcGcaNiZbMLp+h83fvEv3n+UpM/eoMvZYJ7jXibMiacZMWxgJIPZbDnLxRNAhIXBqlU1rCPlAb649pOIiJOUSImIiP9KSLD75dyX639G9jrEyLMP8vOrb/PcdHjmwaNcfUURHdotgVDLvNmuXtupvBwOH7aZbMJjfH3tJxGRBlIiJSIijY4/1P9EhJmfjMVFn6VrpzIvRyMiIo5SIiUiImJHZiYsWmRe0ykvD9auhZQUJy+ak2O+WGio+SkNk2DOfcAHABTSlhwSyCUeWE/WxHQgi1jyieVIw+/rC0P7tPaTiDQyTidS586d47///S+dO3embdu2rohJRETE64qLzbOFT5sGY8a44IL1WPdqHaOZSoZ1fzyrAZhPOuksqP6C0FB47z2Ii6v93t4c2geabEJEGiWHE6lZs2bRq1cvbrvtNs6dO8dVV13Ff/7zH8LDw/n73//O0KFD3RCmiIiIZ40cad5cxrLuFcuXmxMqgL7AU0/DsIcBSAPS2GbnxaMtWyUVtUdxcZCcXPu9TSZzIlVpHSkREXGOw4nUe++9x+TJkwH429/+xv79+/n+++956623+MMf/sC///1vlwcpIiLiMTk5dmYCTIZ9+2DbSbsvqZc9e8w/9++3ve6hQ7DnkOPXq7hOxXX11EdExKMcTqQKCgqIjY0FYP369dxyyy1cdNFFTJs2jeeee87lAYqIiFRwS91SZTUOvzNsapmcUfTQE+ylq2VvEvsXv88OPiGSQhI46PgFLb/c1BTjIiKe5XAiFRMTw3fffUdcXBwfffQRL730EgAlJSU0a9bM5QGKiIhUcHndUlX2ht9BtSF4DZaXx5b/BDPs8autTbN5FoDUwfvImPmlY9dr08Y8tE9TjIuIeJzDidTUqVMZN24ccXFxBAQEMHz4cAC++uorLr74YpcHKCIiUsHldUs16dGjet1Rly5QRylSfQy9HozH7B3pYtlERMQfOJxIpaen07NnTw4ePMgtt9xCSEgIAM2aNePBBx90eYAiIiJuq1uqqqLeaP368/8NwCT47DMobkAtU31VPF1qCJtYRUTEExo0/fnNN99crS01NdXpYERERKrxQN1SNQ89RBEtXFvLBKzhJpZxO1vpSyFRbKc3vdnpmpi1VpOIiEfVK5FasmRJvS949913NzgYERGRatxdt1RVXh6cOMGW79q7rpbJonhzIoN+asG4Nj8y/bUoeOxx6HzcPAPfQw9Vf4+O0Kx9IiIeVa9E6tlnn63XxQICApRIiYiIf4uLg7g4hvYAY6y9NZ0AGpbsTOkBcI7s3JbwGpCYCN1jK13WTm2WiIj4pHolUvtt1rwQERHxoOho87C1imm+rdw4tM/tOgPZMHECVAztCw01Pw3bVlPyVoWeQImIeFWDaqQqGIYBmJ9EiYiIuEVCgnkyhYICikoC2XvQPMkRE2H/7OfZ0W8hka3OkhBn8m6cFfLy4OabobTUsdeVlsINN9R52vk6q84UAtu3Q+/eDYpURESc0KBE6i9/+QuLFi3ixx9/BOCiiy5i7ty5TJkyxaXBiYiIAOZkKiGBLZ/CsInnm2c/0xGA1FTIyPBKZNVt2walpay4YzMzM66wNm9YupfBfYrNO7nBMApYuQq6n3bo8sUfRjJo50nG/fUBpvNnFwYuIiKOcDiReuaZZ3jooYe46667GDhwIACbN2/m9ttvp6CggHvvvdflQYqIiAAMHQqWwRA+b3TyIfqP+N6636HdGZdcd8r1hXDhHrL/+i+XXE9ERBrG4URq6dKlvPTSS/z617+2to0ePZpLLrmE9PR0JVIiIuK31qyBZctg61YoLGzgsDlLTVfE9PFE1HiSnRopRwVfBGcwD3ssr+OpVnm5+efOnRAY2LD7uYtqvUTETzmcSOXl5XHllVdWa7/yyivJy8tzSVAiIiLeUFwMgwbBuHEwfXoDL1KppquqwpPNyMkPJvenILgHshauhc6lxEaZiI0+e/7E+tRZnSkz/6xPMhYWBqtWwZAhcNqxoYRuFx5u7i8lUyLiZxxOpLp27co777zD73//e5v21atX061bN5cFJiIi4mkVpb7Z2U5eyFLTVdW6DJg69fz++HmJAMyfD+nplU50dZ1VeTkcPgyZmb71RGrPHvNsjAUFSqRExO/UO5HavXs3PXv25JFHHmHcuHFkZmZaa6T+/e9/s2nTJt555x23BSoiIuLv0tLMW325q85KREScV+9E6tJLL+Wyyy7jtttu4+OPP+aVV17h/fffB6BHjx58/fXX9OnTx11xioiIOC0zExYtMtdA5eXB2qf2kTLsZPUTc4OBnvWrP3KHvDwIDXVdnZWvD+2LjvZ2FCIiDqt3IvXZZ5/xxhtvMGfOHMrLyxk7dizPPvssQ4YMcWd8IiIiLlNcDElJMG3UT4yZ2Y4Jc+JpRgwAGxjJYDZbznTBZBBuUhgSR86i1eQacbXXWVXmq0P7QJNNiIjfqnciNXjwYAYPHszSpUt55513yMjIYNiwYXTp0oXbbruN1NRUYmNj3RmriIiIU0aONG9sOwi045m0XVyd0hKADu2WQKhlbnUn1nlyqz17WDd5I1PvHmxtqrHOqjKTyZxIJSVBUJD74xQRaQIc/rVUixYtmDp1Kp999hlZWVnccsstvPDCCyQkJDB69Gh3xCgiIuIWcW1K6dqpjK6dyggL9Y8FqtJ4E2PrNgwDm63GJEpERNzC4Vn7KuvatSu///3v6dy5M/PmzePDDz90VVwiIiKuk5NjOx15xXIdi5+FxR9YmwtpSw4J5BIPrCdrYjqQRSz5xHKkztus4SaWcTtb6UshUWynN71dPTRQNUUiIj6hwYlUZmYmr7/+On/9618JDAxk3Lhx3Hbbba6MTURExHk5OdCjB5SUVDlQ/QnUOkYzlQzr/nhWAzCfdNJD/wTvvQdxcTXeqvjDSAYdDmZcuyKmPxrlnqGBqikSEfEJDiVSubm5ZGRkkJGRwd69e7nyyitZsmQJ48aNo0WLFu6KUUREpOEKCsxJ1PLl5oSqQl/gqadh2MPWpjQgjW3Vr7GnG0wuNSdRyck13mqK5VB2NvAo5vv1dvodiIiID6p3IjVy5Ej+9a9/ER0dza9//WumTZtG9+7d3RmbiIiIb6o6VLAqZ6dP11MnERGfV+9EKigoiPfee48bbriBZs2auTMmERER14mONtcVTZ5MES3YS1fLgR3sn/M8O/iESApJ4GDt16moTapxqGBlTk6fHh5uTsKUTPks2zXJgnjwwViuu87bUYmIJ9U7kVq3bp074xAREXGPhARzUlJQwJYtLRk28yLrodk8C0DqDcfIWHCg9utUPCXatg1KSlhxx2ZmZlxhPbxh6V4G9yk27zgzffqePTB5svmJlxIpn2Vdk2wajBnj7WhExBucmrVPRETELyQkQEICQ5PBmGHvhCjLVn+jkw/Rf8T31v0O7c44FaL4F+uaZCLSZCmREhERcYRlqGDE9PFE1HiSC4b2aYpz32S3Ps4yy8jOnRDo8BKdnqG6OxGXUyIlIiI+Z80aWLbMXH9SWAjbt0Pv3t6OyqLSUMGqCk82Iyc/mNyfguAeyFq4FjqXEhtlIjb6bP3voS+9vqmuqfSHDIHTLp7u3lVUdyfickqkRETE5xQXw6BBMG4cTJ/u7WjssAwVrGpdBkyden5//LxEAObPh/R0z4QmblTbVPpgnoHCF59Iqe5OxC2USImIiM+ZMsX8Mzvbq2E4LC3NvImISOOnREpERLzr0CHzT3v1Jc6ux+RKGm7XJNlOc57M2uBxpEyeXOUsPxnap7o7EZdSIiUiIt6TkwOXXQavvVbDl1AnJ21wJdWYNEnVpjl//nno+wBFJYHsPRhiPmkiHD0azo5XvyGmTTkJcSavxmyXfhEg4nJKpERExHsKClh5ahS3j7+eZgE/Q5gL12NyJdWYNFnVpjlv1w6S27HlUxg28Xzz66/34vXXITUVMjI8HKSIeIUSKRER8apRzT7k9LOfclVMDEGBgVqPSfzC0KFgWEb0mUwm1q9fz3XXXUdQUJBX4xIRz1EiJSIi3hMdTUSLcuLiiuk6oT9Bbhjal8lgFjGXrfQlj3jWkkIKHzh+IdWYNC01rRe1bx9sO2nbXF5u/umr60hpWJ+IWyiREhER70lIgG++gV27bKaOdtl6TEDxv1uRtLMF0y4uYcxc4KmnYdjDjseqL6NNR23rRc25D6om4mFhsGqV7042ofo+EbdQIiUiIt7VsaM5kUpKAsuwKFeuxzQyGawlLnOBLl0g2cmYpXGrbb0oe4l4eTkcPuyb60ipvk/EbZRIiYiIz9F6TCIi4uuUSImIeIHt2jSwdi2kpHg7qkbGkRoXX6XhhN4RHW0eDjd5MkW0YC9dLQd2sH/O8+zgEyIpJIGD5mZ/GNqn+j4Rl1MiJSLiBdXWphHXcrTGxVeptsU7EhLM/V5QwJYtLRk28yLrodk8C0DqDcfIWHDA3OjLQ/tACbmImyiREhHxgmpr04hrOVrj4otU2+JdCQmQkMDQZDBm2DshyrIBJpM5kapU5ycijZ9fJVJPPPEE8+bN45577mHx4sUAlJaWct999/H2229TVlbGiBEjePHFF4mJifFusCIi9jSG4Wb1od+Ai4hII+c3idQ333zDyy+/zKWXXmrTfu+99/Lhhx/y7rvv0rp1a+666y7GjBnDv//9by9FKiJSg8Yy3Kw+vD0kzdEaF1/l5tqWNWtg2TJzrV5hIWzfDr17u+12IiKNil8kUkVFRUyaNIlXX32VRx991Np+8uRJXnvtNVauXMkvf/lLAN544w169OjBl19+yRVXXOGtkEVEqmsMw83qwxeGpDla4+Kr3Pxkr7gYBg2CceNg+nS33UZEpFHyi0Tqzjvv5Prrr2f48OE2idTWrVsxmUwMHz7c2nbxxReTkJDAF198UWMiVVZWRllZmXX/1KlTAJhMJkwmk5veRdNV0afqW/dQ/7qfy/q4vNw8u1fFf1dy1jAwVWnza2Fh5vdYjz5z22c4Lg7i4hjYC85MtXftVpjo5dp7uoML+qWmPh4/3vwzOxsgyPLvoNO3a3L097D7qY/dS/1rq7794POJ1Ntvv822bdv45ptvqh3Lz88nODiYNm3a2LTHxMSQn59f4zUXLlzIggULqrV/8sknhIeHOx2z2Ldx40Zvh9CoqX/dzyV9vGqV+efhw5Ua+7H12DGCDtf895ZfadnS/D4PH67yPmunz7D71dTHR46EAdewefNmcnNPeTaoRkSfYfdTH7uX+tespNoQfPt8OpE6ePAg99xzDxs3biQ0NNRl1503bx6zZ8+27p86dYpOnToxbNgwoqKiXHYfMTOZTGzcuJGrr76aIM1m5HLqX/dzaR8fOgTHjlFUEsjegyHW5qiyeOKLWhLZ+hwJsWecjNgHREVBx471OrUpfIbXrg3g1VcD2bYtgMLCAL7+2uTRWiTTgQNs/PZbrp42jSA76xxllycA3zNo3jx6B+5y7c3Dw+Gbb+r9efBHTeEz7G3qY/dS/9qqGK1WF59OpLZu3crRo0dJTk62tp07d47MzEyef/55/vGPf3DmzBlOnDhh81TqyJEjxMbG1njdkJAQQkJCqrUHBQXpw+NG6l/3Uv+6n0v6ODEREhPZ+SkMm3y+ee6znQBITYWMDOdu4a8a82e4rAwGD4ZbbzXXIpnfqwcDOHGCzz7ryKTifOs6RxuW7mVwn2IAgnKDYRQEvfEGQd1duKBsRb3c8ePmz34j15g/w75Cfexe6l+z+vaBTydSv/rVr/jvf/9r0zZ16lQuvvhiHnjgATp16kRQUBCbNm1i7NixAGRlZZGTk8OAAQO8EbKISL0MHQqG4e0oxFOmTDH/NNciecfll+czvcMhgrqaZzDs0K4RPPkUEfEin06kIiIi6Nmzp01bixYtiIqKsrbfdtttzJ49m8jISFq1asXvfvc7BgwYoBn7RETcRFNm18HuWmEWucFAT/OTmnIXPvmpS34+YWHn6PrQBLtD+6AzkA0TJwA7XXtvN0/hLiLiLT6dSNXHs88+S2BgIGPHjrVZkFdERNxDU2bXosa1wiq4MWGpTVjY+YlOAEJD4b33KAzvSE5+MLk/BcE9kLVwLXQuJTbKRGz0WdfcW4szi0gj5XeJ1KeffmqzHxoaygsvvMALL7zgnYBERJoYXxim5rMKClhRksLMkAy7tUhYapFYuQpcWYtUl/Jy8wyKmZmQlWWuW4qLY92uJKZOPX/a+HnmOqb58yE93XPhiYj4I79LpERERHzZaNbR/7H14Ae1SGlp5k1ERBynREpEROyrrdYHXFfvU7EQ8c6d1qc4tfLloWLR0USElxMxJ6WGE7w8tG/IEDh92uG6pcxMWLTIXBeXlwdr10JKivvCFRHxB0qkRESkOkutz4qSFGbysrV5AyMZzGbLnouSgqpf8usSHm5O3nwxmUpIMMdWJQEtPNnM/bVItak8tC8w0OFktLgYkpJg2jQYM8aNcYqI+BElUiIiUl1BAZSUMPrV0fRvd8Da3KHdEgi1zNvuqnqfql/ya1OxLlFBgW8mUmCOq0ps6zLwbi2SyWTu46QkGrKA1ciR5k1ERM5TIiUiIjWKCDtLRKcyb4fh91SLJCLS+CiREhGR6qKjzUPoJk+udqiQtuSQQC7xwHqyJqYDWcSSTyxHHL9XQ4b2NYJ1ifyi7shunVwy7NsH2066996+XAsnIoISKRERsaeGWh+AdesimbrgAuv+eFYDMH9GHukz8xy/lyND+6DRfMH2+bqjGtfEMmDOfcAH7r2/L9fCiYigREpERGpip9YHIC0Z0tLtvSDOsjnIyfodf+XzdUeWOjmWLzcnVBX6Ak89DcMedt+9/aEWTkSaPCVSIiIinuTq4XKN5AmdiIi/USIlIiJ+zS9qjSq4Y7icu4bAVaqTK6IFe+lqObCD/XOeZwefEEkhCRx07X0rNJJaOBFpvJRIiYiIX/P5WqPKXD1czp1D4CrVyW3Z0pJhMy+yHprNswCk3nCMjAUHarqCc/SkTUR8nBIpERHxaz5fa+TPLHVyQ5PBmGHvhCjLJiLS9CiREhER/+TOqbnd9TSkxmnlnRzapyFwIiIep0RKRET8j7un5nZX3VGl4XJFJYHsPRhibp8I+2c/z45+C4lsdZaEOFP9r6khcFZ+VS8nIn5PiZSIiPgfd07N7e6pty3D5bZ8CsMmnm+e/UxHAFJTISPD9bdtCvyqXk5E/J4SKRERES8YOhQMw9tRNC6qlxMRT1IiJSIi/scdtUaVqe7I/1SrmXNRvVx9lJebf+7cCYGBtsc09FKk0VIiJSIi/qcBtUZrPm7Dsvei2fp9OIUnm7N95R56dz9t//r68utf7NbMuSipro+wMFi1CoYMgdNVPlPuqrcTEa9TIiUiIv7JwVqj4m9h0HUw7jcwfTrmL969PRivuI+9mjlX1MvVV3k5HD5snu2i8hMpd9fbiYhXKZESERG/Vt9aoylTzD+zs90ZjYiINBVKpERExOXWrIFly8zTUBcWwvbt0Lu3BwOwu8aURW4w0NP8tKC8hqF9/kJDEM3s1sz50NA+1duJNEpKpERExOWKi2HQIBg3zjKMzpNqXGOqQmcgGyZOAHZ6Li53UP2NmaVmriin0DVrczmqpqF9oGRXpBFTIiUiIi7n1WF0BQWsKElhZkiG9UvthqV7Gdyn2Hw8NxhGAStXQU2TTfgD1d/YSkhgy/8SvLM2l8lkTqSSkiAoyI03EhFfokRKREQandGso/9j66FrVwA6tDvj5YjEE7Q2l4h4khIpERFxjjP1SNHREBfn2niio4kILydiTkoNJzSyoX2qv/ErmZmwaJG5fjAvD9auhZQUb0clIg2hREpERBouJ4cV3dKZeWaJtWkDIxnMZsteHUlLeDjs3u3amCqtMVVZ4clm5OQHk/tTENwDWQvXQudSYqNMxEafdW0MnqL6G79TXGweAThtGowZ4+1oRMQZSqRERKThCgoYfeZd+j91Y6VhdEsg1DK+qrZ6pIoan2PHXB+XZY2pytZlwNSp5/fHz0sEYP58SE93fQgi9owcad5ExP8pkRIREadEUEREbBF0KvN2KLVKSzNvIiIirqBESkRE7KrXWlB21++BQtqSQwK5xAPryZqYDmQRSz6xHDl/Yng4REWZZzwTaeyq1RMmw759sO1k3a/VME4Rn6NESkRE7KrXWlA11COtWxfJ1AUXWPfHsxqA+TPySJ+Zd/7Eiskmdu1ycfQiPsbu+mYOLBqsNcNEfI4SKRERsavea0HZqUdKS4a0dHsnx1m2SkxuXChVxFcUFJiTqOXLzQkVQF/gqadh2MO1v1Zrhon4JCVSIiJNXW3Tl0PdU5g7q7zc/HPnTusCujY0pElERHyQEikRkabM7nCjqty87lJYGKxaBUOGwGk7iZqGNEljYKknLJo8k710tTTuYP+c59nBJ0RSSAIHa369g2uGab0qEfdTIiUi0pRZhhutuGMzMzOusDZvWLqXwX2KzTu1TWHuCuXl5skmMjOrP5HSkCZpLCz1hFs+KmXYzIuszbN5FoDUG46RseBAza938Mms1qsScT8lUiIiwujkQ/Qf8b11v0O7M16MRqSRSkhg6AwwZtg7GGXZXEPrVYm4nxIpEZGmzDLcKGL6eCJqPMkHhvY5MKRJpMlzZpp1b1NNpPgRJVIiIk1ZDdOXAxSebEZOfjC5PwXBPZC1cC10LiU2ykRs9NkaL5m5rSWL/hLD1j1h5BUEs/apfaQMq+ULXG1D+0BfrEQc4ew0696mmkjxI0qkRESaOjvTlwOsy4CpU8/vj5+XCMD8+ZCeXvPlio9A0hCYdq+lNqNLF0iu5f4mkzmRSkqCoKCGvAMRqeDMNOvepppI8TNKpERExK60NPPmKNVmiIhIU6BESkREXMPuelT1qM2oax2pyrw8zE9TSovPs9Q9MnlypUY/G9qnmkjxE0qkRETEeTWuR1WPL3B1TTZRmZfrJzSltPg8S91jUU4hew+GmNsmwv7Zz7Oj30IiW50lIc7k3Rhro5pI8SNKpERExHn26jKgfrUZdU02UcEH6ic0bFH8QkICW/6XwLCJ55tmP9MRgNRUyMjwTlgijY0SKREREZFGZuhQMAxvRyHSuCmREhER59mtywB7Q/vWcBPLuJ2t9KWQKL4OuQJWz6v/0D5v1U94Ym0eDWsSEfEbSqRERMR5ldajKioJrLU2o/jDSAYdDmZcuyKmPxoFr70G7K17aB94L9Hw1No8WkNHRMRvKJESERHXsKxHteVTaq3NmGJZUyo7G3gUuOgiyN3r2+tIeWJtHh+oARMRkfpTIiUiIi6l2gwREWkKlEiJiPiANWtg2TLz+kSFhbB9O/Tu7e2onGR3XalKcoOBnvDDD9CS+q0jVZWnhvpZasCKJs9kL10tjTvYP+d5dvAJkRSSwEHn76M1dERE/IYSKRERH1BcDIMGwbhxMH26t6NxAUtN0YqSFGbysrV5AyMZzGbLXmcgG267rf6TTVTlqZoiSw3Ylo9KGTbzImvzbJ4FIPWGY2QsOOD8fTTZhIiI31AiJSLiA6ZMMf/MzvZqGK5jqSka/epo+rc7n2B0aLcEQi3j/nKDYRSOTTZRmadrihISGDoDjBn2DkZZNhERaSqUSImIeFJ9h7vt2QPlDj6dcRcnnpJEhJ0lolOZiwMSERHxPiVSIiKekpND5kW/YVHZ79hKX/KIZy0ppNhMn20Z7jZxArDTO3FW1ZDhczWuKwWFtCWHBHKJB9bzw9QnOPqnaeSPv4VOpdmOx6aaIhER8QIlUiIinlJQQHFZM5ol9+b47lg4AxOC1/DPF39kcJ9i8zkVw91WroLuPvBEqqHD5yqtK1XVunWRTF1wgXV/suktmA2F0//N/92e71h8qikSEREvUSIlIuJBI/mIQXf8hyPtetIt5RKemX2Qfj1K6n6hP7KsK1VVWjKkpZ/fN5lMrF+/nuuuuw6C4j0Xn4iIiBOUSImIeEpZGYSGEjF9PBEAGMQ9cQ9hT/j40L7QUMjLg23baj9PT4dERKQJUSIlIuIimZmwaJF5Lai8PFi7FlJSLAdzcmD4cCgttfta27ohyKI7ALHkE8sRD0Rfi9JSuOGGus/z1FTkIiIiPkCJlIiIixQXQ1ISTJsGY8ZUOWiZDpzly6FHD3NbX+Cpp2HYw9XqhsazGoD5M/JIn5nnkfid4umpyEVERLxMiZSIiIuMHGneGiJtdCFpowtdG5CIiIi4jRIpERFn2V0bKhn27YNtJ827eXnmWiOb6cANmHMfVJr+fA03sYzb2UpfColiO73p7Su1UnXRVOQiItKEKJESEXFGTo55qF5J1Zn3qidJAEW0YC9drfv7SWQHSURSSAIHKaYFg9jMON5hOn92b+yhofDeexAX55rrabIJERFpQpRIiYg4w17tE9jUP1W2ZUtLhs28yLo/m2cBSL3hGBkLDjDF0p7t7vWkKmqa4uIgOdn11xcREWnklEiJiHjQ0H5FGFvrmEZcREREfJ4SKRERZ0RHm2uDbGqfoKahffXngfWk6rs+VAUN3RNpkmpd2kGkCVMiJSLijIQE8zC5ggKKSgLZezDE3D4R9s9+nh39FhLZ6iwJcabzr8nLg5tvZkXpGGbysrV5AyMZzGbPxV7f9aEqaJ0okSap1qUdRJowJVIiIs5KSICEBLZ8CsMmnm+e/UxHAFJTISOj0vnbtkFpKaNfHU3/dgeszR3aLYFQw7zj7hopR2mdKJEmy5mlHUQas0BvB1CbhQsXctlllxEREUH79u1JSUkhKyvL5pzS0lLuvPNOoqKiaNmyJWPHjuXIkSNeilhEmrKhQ8Ewqm82SVQlEWFn6dqpzLqFVSRRIiIi4vN8+onUZ599xp133slll13G2bNn+f3vf88111zDd999R4sWLQC49957+fDDD3n33Xdp3bo1d911F2PGjOHf//63l6MXEalBjXVVUEhbckggl3hgPVkT04EsYsnnP1zp3TWmtE6USNNTbZ28KmvkeUp5ufnnzp0QWI/nAKrpFA/w6UTqo48+stnPyMigffv2bN26lSFDhnDy5Elee+01Vq5cyS9/+UsA3njjDXr06MGXX37JFVdc4Y2wRURqV6muqqp16yKZuuAC6/54VgMwf0YeXTqWMehwMOPaFTH90SjPD/vTFxORpsXuOnnOTqTTQGFhsGoVDBkCp+vx955qOsUDfDqRqurkSfNvPyIjIwHYunUrJpOJ4cOHW8+5+OKLSUhI4IsvvlAiJSK+y1JXVVVaMqSl23vB+UVzs7OBRzF/wentluhEROyvk1fDGnluV14Ohw+bpxCs64mUajrFQ/wmkSovL2fWrFkMHDiQnj17ApCfn09wcDBt2rSxOTcmJob8/Pwar1VWVkZZWZl1/9SpUwCYTCZMJlNNL5MGquhT9a17qH/dz+N9fOgQHDtWczy5wcClmL79FtNZL01EERUFHTu65FL6DLuf+ti9Gm3/lpebnwRV/LfFWcPAVGnfEyruV+/7hoWZY25sfyZu0mg/ww1U337wm0TqzjvvZPfu3Wze7PzUwAsXLmTBggXV2j/55BPCw8Odvr7Yt3HjRm+H0Kipf93PFX387bdRrF3blX372nD8eCgPPvgVV1xR8y9+7DlyJAy4lM1Hj5Lb8pTTMTXI4cOwa5dLL6nPsPupj92rUfbvqlWcPt2MvM9/tjZt2HOag81+JiLCRLt2nv1lzsa8vLpPatnSPAzw8GHzJvXWKD/DDVBiM5y1Zn6RSN111138/e9/JzMzk46VfgMaGxvLmTNnOHHihM1TqSNHjhAbG1vj9ebNm8fs2bOt+6dOnaJTp04MGzaMqKgot7yHpsxkMrFx40auvvpqgoKCvB1Oo6P+dT9X9nFgYAA//xzA/fcbjBsHffv25brrKs3Wt3MnDBnCyrSN3Jlxfnjy3577kUF9igDIDggGYFD79vTuEOFUPA2SlQXTp5uH2CQlOX05fYbdT33sXo26fw8d4rN/nmHC7O7Wptdf7wXAlOsLeC092yNhmMrL2ZiXx9VxcQTVZ7IJFz41bwoa9We4ASpGq9XFpxMpwzD43e9+x9q1a/n0009JTEy0Od63b1+CgoLYtGkTY8eOBSArK4ucnBwGDBhQ43VDQkIICQmp1h4UFKQPjxupf91L/et+rujjUaPMW4XmzZtjc8nAQDh9mjHJhxg44ntrc4d2Z6xfHir/rNcXCnc4fdocqws/c/oMu5/62L0aZf8mJjJ8Jhgz7R2MtmweYDJBXh5Bffo0vj72IY3yM9wA9e0Dn06k7rzzTlauXMkHH3xARESEte6pdevWhIWF0bp1a2677TZmz55NZGQkrVq14ne/+x0DBgzQRBMi4nvqM41wXh6EhhIxfTw1P2vqDGTDxAngyenPK9NU6CIi0sT5dCL10ksvATB06FCb9jfeeIO0tDQAnn32WQIDAxk7dixlZWWMGDGCF1980cORiojUISeHNd0eYNmZqdZ1oACHphG2XWMKsjAPtYkln1jcvBB5aCi89x7EWWYP1FToIiLSxPl0ImUYRp3nhIaG8sILL/DCCy94ICIRkQYqKKD4THMGjY1hXA/LOlDg0DTCta0xlT6zHgXYDVUxlXBcHCQnu+8+IiIifsSnEykRkcZkCsvhpmvJbt2wCRrSRheSNrrQxVGJiIhIQyiREhFxtWq1UFhrn5g8GWuNEzg0tM+rVBMlIiJiQ4mUiIgr5eRAjx5QwxoURbTgO35h3f+A0fyJB9jDxZykLdvpTW9vTSAB1WuhKqgmSkRExIYSKRERVyoogJISVtyxmZmV1oHasHQvg/sUs2VLS66feZG1PYNpAAy4tIgvdgErV0F3zy5waaVaKBERkXpTIiUi4gajkw/Rv8o6UABD+xWx/2+7SRzVk+0r99DbkjRl5waTOKqnV2IVERERxymREhFxpehoCA9vwDpQzq0NtYabWMbt1qnVGzxEULVQIiIi9aJESkTElRISzEPk7Ew2UTh2Ojll7e2uA+WU0FCKf/swg4rbM66dZWr1hg4RVC2UiIhIvSiREhFxtYSE6snItm3MK5vPK8y0NlVeBypt1DEYheMJkKWuacqkckiOJzsbeBTzhBe9nXwfIiIiUiMlUiIiHvIUc5j7VCx07QqY66bCQs0Lj2fnBnszNBEREXGQEikRL8rMhEWLYOtW8zJDa9dCSoq3oxK3iI4mIryciDkpNZzgRI1UaKj5A7RtG+QGAz3NT6rKnZj9T0P8REREaqVESsSLioshKQmmTYMxY7wdjbhVDbVThSebkZMfTO5PQXAPZC1cC51LiY0yERt91vYaeXlw882sKB3DTF62Nm8oHcngG26w7Dk3aYVVeLg5XiVTIiIidimREvGikSPNmzQRdmqn1mXA1Knn98fPSwRg/nxIT6/y+m3boLSU0a+Opn+7A9bmDu2WgGWIILnBDau1qqxiPamCAiVSIiIiNVAiJeINOTnVZ3UjGfbtg20nHbtWebn5586dEBjokvAcoiFgTklLM2+OiAg7S0SnMneEIyIiIvWkRErE03JyzDOqlZRUOWDAnPuADxy7XlgYrFoFQ4bAaSdqYhpKQ8A8V+tmWaOKyZOrHSqkLTkkWKZWX0/WxHQgi1jyieWI4/fSelIiIiK1UiIl4mkFBeYkavlyc0JVoS/w1NMw7GHHrldeDocPm7/Ne/qJlIaAAR6sdatpjSpg3bpIpi64wLpfeWr19Jl5jt9LTxpFRERqpURKxFt69IDkZNu2Ll0g2f7pNTKZzIlUUhIEBbksPKk/j9a62VujCkhLhrR0ey+Is2wiIiLiSkqkRLxlz54qDX5YI1XtPTQxrqx18wV6CiUiIlJvSqREPK1SnUsRLdhLV8uBHeyf8zw7+IRICkngYP2u5ws1Uk2xlsbFtW5ruIll3M5W+lJIFNvpTW9npi9vCNW7iYiI1JsSKRFPq1TnsmVLS4bNvMh6aDbPApB6wzEyFhyo6Qq2vFkjBU33KYaLa92KP4xk0OFgxrUrYvqjUc5NX94QqncTERFxiBIpEW+w1LkMTQZjhr0ToixbPahGqlGYcn0hANm5wV6OREREROpDiZSISEPUOBV5A6ext+oMZMPECeCNoX1NcZimiIhIAyiREvEAj60zJJ5TaYhmUUkgew+GmNsnwv7Zz7Oj30IiW50lIc50/jV5eXDzzVBa2vD7hobCe+9BnBtm4muqwzRFREQaQImUiAd4bJ0h8SzLEM0tn8KwieebZz/TEYDUVMjIqHT+tm1QWsqKOzYzM+MKa/OGpXsZ3KfYvJMbDKOwXyNVUccUF1d96nwRERHxKCVSIh7g0XWGxOOGDgXDqP/5o5MP0X/E99b9Du3OuD4oERERcSslUiLu5Mp1hjTsyq/YHc6ZbK6ripg+nogaX1lHjZTqmERERHyCEikRd3HxOkNa48e/2B3OWamuqqrCk83IyQ8m96cguAeyFq6FzqXERpmIjT57/kQl1CIiIj5BiZSIu7hynSGt8eN3ahzOaamrqmpdBkyden5//LxEAObPh/R0t4QoIiIiTlAiJSLiA9LSzJuIiIj4ByVSIu5iZ52hTAYDmUyb05ab6MJaUkip7xA/1cb4B1fWxdVGQ/xERES8SomUiLvYWWdo144W8CSkjCrnjb/BT394DsbUc4ifvjj7PlfXxdVGNXMiIiJepURKxJ1qWGfojb+Znyyt+k9npj/a2Tuxieu5si6uNqqZExER8TolUiIeYG+doYAAuPtur4QjIiIiIk5SIiXiCe6smykvN//cuRMCAxt+nSY4dHDNGli2zLzWU2EhbN8OvXs7ccFKdXFFtGAvXS0HdrB/zvPs4BMiKSSBg84Hr5o5ERERr1IiJeJu7q6bCQuDVatgyBA4fbrh12mCNTfFxTBoEIwbB9Onu+CCleritmxpybCZF1kPzeZZAFJvOEbGggPO36sJJr4iIiK+RImUiLu5u26mvBwOH4bMzIY/kWqiNTdTpph/Zme78KKWurihyWDMsHdClGUTERERf6ZESkQaP7tDKyvJDQZ6mhPKcjtP9TR8UkRERKpQIiXibu6um3Hl0L7GWHNT49DKyjoD2TBxArCz+uE6+ngNN7GM29lKXwqJYju96W3vOk1w+KSIiEhjpURKxN3cXTfjiqF90HiflliGVq64YzMzM66wNm9YupfBfYrNO7nBMApYuQq61/BEqpY+Lv4wkkGHgxnXrojpj0bZv04THT4pIiLSWCmREvEEd9bNmEzmL/lJSRAU5ESQjdvo5EP0H/G9db9DuzMuu/aU6wsByM4Ndtk1RURExLcpkRKRxs0ytDJi+ngiajzJuaF99b5OaCjk5cG2bbbx6QmViIiI31EiJSJe4fI1nGpSaWhlVYUnm5GTH0zuT0FwD2QtXAudS4mNMhEbffb8iRVD+0JDnatDKy2FG26wbVPdlIiIiF9SIiUiXuHyNZxqYxlaWdW6DJg69fz++HmJAMyfD+nplU6sGD5ZWupcrVVVqpsSERHxW0qkRMQr3LKGk4PS0sybI9xZayUiIiL+Q4mUiLiXs2s4OWHNx21Y9l40W78Pp/Bkc7av3EPv+jwpqqpiHanQUOdqrexprNPOi4iINHJKpETEfVyxhpMTipnMIBIZRy7T+XPD71Ex2URpqd3DhbQlhwRyiQcgK6gXPL2U2O6tbWut7NFkEyIiIn5JiZSIuI8r1nBygmX0oHlacmfuUcc6UuvWRTJ1wQXW/fGmt+BuO7VWIiIi0mgokRIRt2vsdUVpowtJG21eS8o6gcTWrZCc7N3ARERExG2USIk0Ep9/HsCzz5q/v+flwdq1kJLi5aBcsYaTSzh5j3qvI2WhuicREZFGT4mUSCNRXAxJSTBtGowZ4+1oLFyxhlN95OWx4qb3mGlaam3awEgGs9nZd1A/oaHw3nsQF2feV92TiIhIo6dESqSRuPZag1GjvB2FHc6u4VQf27Yx2vQe/Z9Kga5dAejQbgmEGubj7qyRqhjKFxenoXwiIiJNiBIpEfGKhqzhVJsIioiILYJOZa67qIiIiEgNlEiJ+LtDh8w/d+6s9LQkGfbtg20nradlbmvJor/EsHVPGHkFwax9ah8pw05Wv56vqm24nKUWi8mTbZptpyVfT9bEdCCLWPKJ5Uj9711XjZRqokRERJocJVIi/iwnBy67DF57rcqXfAPm3Ad8YD21mGtJYiDT2MoY1lY77vPCw83D6OwlUzXUYlWblpzVAMyfkUf6zLz637uO6c9VEyUiItL0KJES8WeWdZoA2y/5fYGnnoZhD1tPHWnZ4Dq7x31aRR1SQUHNCYudWqy0ZEhLt3dynGWrJ5PJnEglJUFQUP1fJyIiIo2WEimRxi4vD06cqNKYbB4SuOeQNyJy3P795p979tg/ridCIiIi4mFKpET8WUVtEFA0eCQHSjtYDuxg/5zn2cEnRFJIAgervHASLH4WvxraB9VqoKxqG/YnLrFmDSxbZl6nrLAQtm+H3r29HZWIiIj3KJES8WcJCfDNN7BrF1sXb+bq27tbD83mWQBSySDj/w5BYuL5100GZt0L/W7xcMBOaNPm/DpNldVn2J84rbgYBg2CceNg+nRvRyMiIuJ9SqRE/F3HjrBrF1dNuxBjZpVj27ZB36mQuBx69Kj+uh4RHgtT/NuUKeaf2dleDUNERMRnKJESacxqmBbc3qx+fk3Tj7tOTk612Q9t5AYDPc1PAssrTQWvOjUREWlilEiJNGaVpgUvKglk78EQc/tE2D/7eXb0W0hkq7MkxJm8G6ezPPglvlHXCuXkmJ9cVswEaVdnIBsmTgB2nm9WnZqIiDQxSqREGjvLtOBbPoVhE883z36mIwCpqZCR4ZXI/FKjrhWyTKe/4o7NzMy4wtq8YeleBvcpNu/kBsMoYOUq6G55IqU6NRERaYKUSIk0EUOHgmF4Owr/1xRqhUYnH6L/iO+t+x3anfFiNCIiIr5JiZSIj8jMhEWLzEPG8vJg7VpISfF2VE1Y5Vqh8nLzz507zy96XFOtkD/Ly4OwMCKmj6fmaUhqGdqnOjUREWlClEiJ+IjiYkhKgmnTYMwYb0fTxFWtFQoLg1WrYMgQOF2RNNWQUPi70FD4+9+rTTVfeLIZOfnB5P4UBPdA1sK10LmU2CgTsdFnNdmEiIg0OUqkRHzEyJHmTXyAnVqhc+MN1i/ZxrC+luTKXq2Qv6uodYqLg+Rkm0PrMmDq1PP74+eZ1yWbPx/S0z0XooiIiK9QIiUiUoOKWiFTeTmfHTlC3x5tgQBvh+UVaWnmTURERMwaTSL1wgsvsGjRIvLz80lKSmLp0qVcfvnl3g5LpH6qrd2TDPv2wbaTdb/WXv2Ov/DV4WCW9bcqaoVMYWH8sGoVYdeMbvxD+1TrJCIiUi+NIpFavXo1s2fPZtmyZfTv35/FixczYsQIsrKyaN++vbfDE6md3bV7HFgw1279jp/w1bWHKq2/BZiT1cOHITOTwp+Daq8V8ne+mtyKiIj4mEaRSD3zzDNMnz6dqZYB/MuWLePDDz/k9ddf58EHH/RydCJ1sNTjsHy5OaEC6As89TQMe7ju11f6ku9XT6R8fe0hy/pbAJhM5j5OSmLdiiDVComIiIj/J1Jnzpxh69atzJs3z9oWGBjI8OHD+eKLL+y+pqysjLKyMuv+qVOnADCZTJhMJvcG3ARV9Kn6tgbl5eanShX/bXHWMDBV2q9JxTn1OdfnhIWZ37OPfzYqf4YnTYJJk2o6z4NBNSL6O8L91Mfupf51P/Wxe6l/bdW3HwIMw7+X6MzNzaVDhw785z//YcCAAdb2+++/n88++4yvvvqq2mvS09NZsGBBtfaVK1cSHh7u1nhFanL6dDPy8loAMHv2MKZN+y89exYQEWGiXTs/G7InIiIi4qdKSkqYOHEiJ0+epFWrVjWe5/dPpBpi3rx5zJ4927p/6tQpOnXqxLBhw4iKivJiZI2TyWRi48aNXH311QQFBXk7HN906BCf/fMME2Z3tza9/novAKZcX8Br6dk1vtRUXs7GvDyujosjyJ+G9gFERUHHjt6Ook76DLuX+tf91Mfupf51P/Wxe6l/bVWMVquL3ydS0dHRNGvWjCNHjti0HzlyhNjYWLuvCQkJISQkpFp7UFCQPjxupP6tRWIiw2eCMdPewWjLVgOTCfLyCOrTR/3rZvoMu5f61/3Ux+6l/nU/9bF7qX/N6tsHfp9IBQcH07dvXzZt2kRKSgoA5eXlbNq0ibvuuqte16gY3fjzzz/rw+MGJpOJkpISTp06pf51A/Wv+6mP3Uv9637qY/dS/7qf+ti91L+2Kp5I1VUB5feJFMDs2bNJTU2lX79+XH755SxevJji4mLrLH51OXbsGACJiYnuDFNERERERPzEzz//TOvWrWs83igSqVtvvZWffvqJhx9+mPz8fHr37s1HH31ETExMvV4fGRkJQE5OTq2dJQ1TUYN28ODBWgv2pGHUv+6nPnYv9a/7qY/dS/3rfupj91L/2jIMg59//pn4+Phaz2sUiRTAXXfdVe+hfFUFWgr0W7durQ+PG7Vq1Ur960bqX/dTH7uX+tf91Mfupf51P/Wxe6l/z6vPwxU/m+JLRERERETE+5RIiYiIiIiIOEiJFObp0OfPn293SnRxnvrXvdS/7qc+di/1r/upj91L/et+6mP3Uv82TIBR17x+IiIiIiIiYkNPpERERERERBykREpERERERMRBSqREREREREQcpERKRERERETEQU0+kXrhhRe44IILCA0NpX///nz99dfeDskvLFy4kMsuu4yIiAjat29PSkoKWVlZNueUlpZy5513EhUVRcuWLRk7dixHjhyxOScnJ4frr7+e8PBw2rdvz9y5czl79qwn34pfeOKJJwgICGDWrFnWNvWv8w4fPszkyZOJiooiLCyMXr16sWXLFutxwzB4+OGHiYuLIywsjOHDh/Pjjz/aXKOwsJBJkybRqlUr2rRpw2233UZRUZGn34rPOXfuHA899BCJiYmEhYXRpUsX/u///o/K8xupfx2TmZnJqFGjiI+PJyAggPfff9/muKv6c9euXQwePJjQ0FA6derEk08+6e635hNq61+TycQDDzxAr169aNGiBfHx8fz6178mNzfX5hrq39rV9Rmu7PbbbycgIIDFixfbtKuPa1af/t2zZw+jR4+mdevWtGjRgssuu4ycnBzrcX23cJDRhL399ttGcHCw8frrrxvffvutMX36dKNNmzbGkSNHvB2azxsxYoTxxhtvGLt37zZ27NhhXHfddUZCQoJRVFRkPef22283OnXqZGzatMnYsmWLccUVVxhXXnml9fjZs2eNnj17GsOHDze2b99urF+/3oiOjjbmzZvnjbfks77++mvjggsuMC699FLjnnvusbarf51TWFhodO7c2UhLSzO++uor43//+5/xj3/8w9i7d6/1nCeeeMJo3bq18f777xs7d+40Ro8ebSQmJhqnT5+2nnPttdcaSUlJxpdffml8/vnnRteuXY0JEyZ44y35lMcee8yIiooy/v73vxv79+833n33XaNly5bGc889Zz1H/euY9evXG3/4wx+MNWvWGICxdu1am+Ou6M+TJ08aMTExxqRJk4zdu3cbq1atMsLCwoyXX37ZU2/Ta2rr3xMnThjDhw83Vq9ebXz//ffGF198YVx++eVG3759ba6h/q1dXZ/hCmvWrDGSkpKM+Ph449lnn7U5pj6uWV39u3fvXiMyMtKYO3eusW3bNmPv3r3GBx98YPO9V98tHNOkE6nLL7/cuPPOO637586dM+Lj442FCxd6MSr/dPToUQMwPvvsM8MwzP/oBAUFGe+++671nD179hiA8cUXXxiGYf4fPjAw0MjPz7ee89JLLxmtWrUyysrKPPsGfNTPP/9sdOvWzdi4caNx1VVXWRMp9a/zHnjgAWPQoEE1Hi8vLzdiY2ONRYsWWdtOnDhhhISEGKtWrTIMwzC+++47AzC++eYb6zkbNmwwAgICjMOHD7sveD9w/fXXG9OmTbNpGzNmjDFp0iTDMNS/zqr6JclV/fniiy8abdu2tfk74oEHHjC6d+/u5nfkW2r7kl/h66+/NgDjwIEDhmGofx1VUx8fOnTI6NChg7F7926jc+fONomU+rj+7PXvrbfeakyePLnG1+i7heOa7NC+M2fOsHXrVoYPH25tCwwMZPjw4XzxxRdejMw/nTx5EoDIyEgAtm7dislksunfiy++mISEBGv/fvHFF/Tq1YuYmBjrOSNGjODUqVN8++23Hozed915551cf/31Nv0I6l9XWLduHf369eOWW26hffv29OnTh1dffdV6fP/+/eTn59v0cevWrenfv79NH7dp04Z+/fpZzxk+fDiBgYF89dVXnnszPujKK69k06ZN/PDDDwDs3LmTzZs3M3LkSED962qu6s8vvviCIUOGEBwcbD1nxIgRZGVlcfz4cQ+9G/9w8uRJAgICaNOmDaD+dYXy8nKmTJnC3LlzueSSS6odVx83XHl5OR9++CEXXXQRI0aMoH379vTv399m+J++WziuySZSBQUFnDt3zuaDABATE0N+fr6XovJP5eXlzJo1i4EDB9KzZ08A8vPzCQ4Otv4DU6Fy/+bn59vt/4pjTd3bb7/Ntm3bWLhwYbVj6l/n/e9//+Oll16iW7du/OMf/+COO+7g7rvv5s033wTO91Ftf0fk5+fTvn17m+PNmzcnMjKyyffxgw8+yPjx47n44osJCgqiT58+zJo1i0mTJgHqX1dzVX/q7436KS0t5YEHHmDChAm0atUKUP+6wp/+9CeaN2/O3Xffbfe4+rjhjh49SlFREU888QTXXnst//znP7npppsYM2YMn332GaDvFg3R3NsBiP+788472b17N5s3b/Z2KI3GwYMHueeee9i4cSOhoaHeDqdRKi8vp1+/fjz++OMA9OnTh927d7Ns2TJSU1O9HJ3/e+edd1ixYgUrV67kkksuYceOHcyaNYv4+Hj1r/g1k8nEuHHjMAyDl156ydvhNBpbt27lueeeY9u2bQQEBHg7nEanvLwcgBtvvJF7770XgN69e/Of//yHZcuWcdVVV3kzPL/VZJ9IRUdH06xZs2ozkRw5coTY2FgvReV/7rrrLv7+97/zySef0LFjR2t7bGwsZ86c4cSJEzbnV+7f2NhYu/1fcawp27p1K0ePHiU5OZnmzZvTvHlzPvvsM5YsWULz5s2JiYlR/zopLi6OX/ziFzZtPXr0sM5eVNFHtf0dERsby9GjR22Onz17lsLCwibfx3PnzrU+lerVqxdTpkzh3nvvtT5hVf+6lqv6U39v1K4iiTpw4AAbN260Po0C9a+zPv/8c44ePUpCQoL1370DBw5w3333ccEFFwDqY2dER0fTvHnzOv/d03cLxzTZRCo4OJi+ffuyadMma1t5eTmbNm1iwIABXozMPxiGwV133cXatWv5+OOPSUxMtDnet29fgoKCbPo3KyuLnJwca/8OGDCA//73vzZ/KVb8w1T1f/Sm5le/+hX//e9/2bFjh3Xr168fkyZNsv63+tc5AwcOrDZl/w8//EDnzp0BSExMJDY21qaPT506xVdffWXTxydOnGDr1q3Wcz7++GPKy8vp37+/B96F7yopKSEw0PafmGbNmll/K6r+dS1X9eeAAQPIzMzEZDJZz9m4cSPdu3enbdu2Hno3vqkiifrxxx/517/+RVRUlM1x9a9zpkyZwq5du2z+3YuPj2fu3Ln84x//ANTHzggODuayyy6r9d89fXdrAG/PduFNb7/9thESEmJkZGQY3333nTFjxgyjTZs2NjORiH133HGH0bp1a+PTTz818vLyrFtJSYn1nNtvv91ISEgwPv74Y2PLli3GgAEDjAEDBliPV0yhec011xg7duwwPvroI6Ndu3ZNdgrNulSetc8w1L/O+vrrr43mzZsbjz32mPHjjz8aK1asMMLDw43ly5dbz3niiSeMNm3aGB988IGxa9cu48Ybb7Q7nXSfPn2Mr776yti8ebPRrVu3Jjs9d2WpqalGhw4drNOfr1mzxoiOjjbuv/9+6znqX8f8/PPPxvbt243t27cbgPHMM88Y27dvt84a54r+PHHihBETE2NMmTLF2L17t/H2228b4eHhTWLq6Nr698yZM8bo0aONjh07Gjt27LD5d6/yTGXq39rV9RmuquqsfYahPq5NXf27Zs0aIygoyHjllVeMH3/80Vi6dKnRrFkz4/PPP7deQ98tHNOkEynDMIylS5caCQkJRnBwsHH55ZcbX375pbdD8guA3e2NN96wnnP69Gnjt7/9rdG2bVsjPDzcuOmmm4y8vDyb62RnZxsjR440wsLCjOjoaOO+++4zTCaTh9+Nf6iaSKl/nfe3v/3N6NmzpxESEmJcfPHFxiuvvGJzvLy83HjooYeMmJgYIyQkxPjVr35lZGVl2Zxz7NgxY8KECUbLli2NVq1aGVOnTjV+/vlnT74Nn3Tq1CnjnnvuMRISEozQ0FDjwgsvNP7whz/YfOlU/zrmk08+sfv3bmpqqmEYruvPnTt3GoMGDTJCQkKMDh06GE888YSn3qJX1da/+/fvr/HfvU8++cR6DfVv7er6DFdlL5FSH9esPv372muvGV27djVCQ0ONpKQk4/3337e5hr5bOCbAMCotMy8iIiIiIiJ1arI1UiIiIiIiIg2lREpERERERMRBSqREREREREQcpERKRERERETEQUqkREREREREHKRESkRERERExEFKpERERERERBykREpERJqUhx56iBkzZjh1jU8//ZSAgABOnDjhmqDcaPz48Tz99NPeDkNEpNHRgrwiIlKngICAWo/Pnz+f9PR0zwTjhPz8fC666CL++9//0rlz5wZf58yZMxQWFhITE1Nn3zjiggsuYNasWcyaNctl19y9ezdDhgxh//79tG7d2mXXFRFp6vRESkRE6pSXl2fdFi9eTKtWrWza5syZ4+0Q6+XPf/4zV155pVNJFEBwcDCxsbEuTaLcpWfPnnTp0oXly5d7OxQRkUZFiZSIiNQpNjbWurVu3ZqAgACbtrfffpsePXoQGhrKxRdfzIsvvmh9bXZ2NgEBAbzzzjsMHjyYsLAwLrvsMn744Qe++eYb+vXrR8uWLRk5ciQ//fST9XVpaWmkpKSwYMEC2rVrR6tWrbj99ts5c+aM9Zz33nuPXr16ERYWRlRUFMOHD6e4uLjG9/H2228zatQom7ahQ4fyu9/9jlmzZtG2bVtiYmJ49dVXKS4uZurUqURERNC1a1c2bNhgfU3VoX0ZGRm0adOGf/zjH/To0YOWLVty7bXXkpeXZ3Ofqk+aUlJSSEtLsx4/cOAA9957LwEBATZJ2ubNm61916lTJ+6++26b9/niiy/SrVs3QkNDiYmJ4eabb7a5z6hRo3j77bdr7BcREXGcEikREXHKihUrePjhh3nsscfYs2cPjz/+OA899BBvvvmmzXnz58/nj3/8I9u2baN58+ZMnDiR+++/n+eee47PP/+cvXv38vDDD9u8ZtOmTezZs4dPP/2UVatWsWbNGhYsWACYn5JNmDCBadOmWc8ZM2YMNY1YLyws5LvvvqNfv37Vjr355ptER0fz9ddf87vf/Y477riDW265hSuvvJJt27ZxzTXXMGXKFEpKSmrsh5KSEp566ineeustMjMzycnJcehJ3Zo1a+jYsSOPPPKI9UkfwL59+7j22msZO3Ysu3btYvXq1WzevJm77roLgC1btnD33XfzyCOPkJWVxUcffcSQIUNsrn355Zfz9ddfU1ZWVu94RESkDoaIiIgD3njjDaN169bW/S5duhgrV660Oef//u//jAEDBhiGYRj79+83AOPPf/6z9fiqVasMwNi0aZO1beHChUb37t2t+6mpqUZkZKRRXFxsbXvppZeMli1bGufOnTO2bt1qAEZ2dna94t6+fbsBGDk5OTbtV111lTFo0CDr/tmzZ40WLVoYU6ZMsbbl5eUZgPHFF18YhmEYn3zyiQEYx48ft/YJYOzdu9f6mhdeeMGIiYmxuc8999xjc+8bb7zRSE1Nte537tzZePbZZ23Oue2224wZM2bYtH3++edGYGCgcfr0aeOvf/2r0apVK+PUqVM1vvedO3c61FciIlK35t5L4URExN8VFxezb98+brvtNqZPn25tP3v2bLWJDS699FLrf8fExADQq1cvm7ajR4/avCYpKYnw8HDr/oABAygqKuLgwYMkJSXxq1/9il69ejFixAiuueYabr75Ztq2bWs31tOnTwMQGhpa7Vjl2Jo1a0ZUVFS12IBq8VUWHh5Oly5drPtxcXG1nl9fO3fuZNeuXaxYscLaZhgG5eXl7N+/n6uvvprOnTtz4YUXcu2113Lttddy00032fRbWFgYQK1P1ERExDEa2iciIg1WVFQEwKuvvsqOHTus2+7du/nyyy9tzg0KCrL+d0X9T9W28vLyet+7WbNmbNy4kQ0bNvCLX/yCpUuX0r17d/bv32/3/OjoaACOHz9e7VjlOCpisRdvbfHZu4ZRaZhhYGBgtWGHJpOpxutVKCoqYubMmTb9u3PnTn788Ue6dOlCREQE27ZtY9WqVcTFxfHwww+TlJRkMzV7YWEhAO3atavzfiIiUj9KpEREpMFiYmKIj4/nf//7H127drXZEhMTnb7+zp07rU+SAL788ktatmxJp06dAHOyMnDgQBYsWMD27dsJDg5m7dq1dq/VpUsXWrVqxXfffed0XA3Rrl07m8knzp07x+7du23OCQ4O5ty5czZtycnJfPfdd9X6t2vXrgQHBwPQvHlzhg8fzpNPPsmuXbvIzs7m448/tl5j9+7ddOzY0ZpMioiI8zS0T0REnLJgwQLuvvtuWrduzbXXXktZWRlbtmzh+PHjzJ4926lrnzlzhttuu40//vGPZGdnM3/+fO666y4CAwP56quv2LRpE9dccw3t27fnq6++4qeffqJHjx52rxUYGMjw4cPZvHkzKSkpTsXVEL/85S+ZPXs2H374IV26dOGZZ56ptqDvBRdcQGZmJuPHjyckJITo6GgeeOABrrjiCu666y5+85vf0KJFC7777js2btzI888/z9///nf+97//MWTIENq2bcv69espLy+ne/fu1ut+/vnnXHPNNR5+xyIijZsSKRERccpvfvMbwsPDWbRoEXPnzqVFixb06tXLJYvK/upXv6Jbt24MGTKEsrIyJkyYYF34t1WrVmRmZrJ48WJOnTpF586defrppxk5cmStsU6fPp0nn3ySwEDPDsqYNm0aO3fu5Ne//jXNmzfn3nvvZdiwYTbnPPLII8ycOZMuXbpQVlaGYRhceumlfPbZZ/zhD39g8ODBGIZBly5duPXWWwFo06YNa9asIT09ndLSUrp168aqVau45JJLACgtLeX999/no48+8uj7FRFp7AKMqgO2RUREfEBaWhonTpzg/fffd9k1DcOgf//+3HvvvUyYMMFl1/VlL730EmvXruWf//ynt0MREWlUVCMlIiJNRkBAAK+88gpnz571digeExQUxNKlS70dhohIo6MnUiIi4pPc8URKRETEVZRIiYiIiIiIOEhD+0RERERERBykREpERERERMRBSqREREREREQcpERKRERERETEQUqkREREREREHKRESkRERERExEFKpERERERERBykREpERERERMRBSqREREREREQc9P/emvPOT1jJTwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17.107807486899343\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.4188568443226643\n"
     ]
    }
   ],
   "source": [
    "for _ in range(2):\n",
    "    obs, _ = env.reset()\n",
    "    env.renderer()\n",
    "    total_reward = 0\n",
    "    done = False\n",
    "    count = 0\n",
    "    while not done:\n",
    "        action, _ = model.predict(obs)\n",
    "        obs, reward, done, _, _ = env.step(action)\n",
    "        #print('action : ', action)\n",
    "        #print('obs : ', obs)\n",
    "        #print('reward : ', reward)\n",
    "        total_reward += reward\n",
    "    env.renderer()\n",
    "    print(total_reward)\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = Monitor(env, 'logs/')\n",
    "model = PPO(\"MlpPolicy\", env, verbose=1, tensorboard_log=\"logs/\").learn(total_timesteps=100000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%tensorboard --logdir=logs/"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}