nuclear_addition_ener_mix.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dc38108a-2bf5-4c88-b385-21379dd9ceaa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solver set: cplex_direct\n"
     ]
    }
   ],
   "source": [
    "#basic imports\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from unyt import kW, minute, hr, day, MW\n",
    "import sys\n",
    "\n",
    "# osier imports\n",
    "from osier import DispatchModel\n",
    "from osier import CapacityExpansion\n",
    "import osier.tech_library as lib\n",
    "\n",
    "# pymoo imports\n",
    "from pymoo.algorithms.moo.nsga2 import NSGA2\n",
    "from pymoo.optimize import minimize\n",
    "from pymoo.termination.ftol import MultiObjectiveSpaceTermination\n",
    "from pymoo.termination.robust import RobustTermination\n",
    "\n",
    "# automatically set the solver\n",
    "if \"darwin\" in sys.platform:\n",
    "    solver = 'cplex_direct'\n",
    "elif \"linux\" in sys.platform:\n",
    "    solver = \"cbc\"\n",
    "else:\n",
    "    solver = \"cbc\"\n",
    "\n",
    "print(f\"Solver set: {solver}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1b990a9e-5224-43ad-ab03-3299855139f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ya4k6TNWtG9Csmf3fq1pVLDkB6DvBAThMpUFMcIiI9EBrxcUFXb0KbNki9h0ZpgoOBsxmID5eHEPP1ASHd1JpBhMcIiKNU9q2FUsi5OSIyf20qDzDVEYYnlKpd1J17w6YTHJjIQBMcIiINE9Re29+/hm4ckVuMKVRh6m6dgUCAuz7jhEKjFWHDwPp6UCNGvnDbiQVExwiIg2zeXsDo0eLJ1ocnlJduwZs3iz27R2mMlKCk5OTf6s763A0gQkOEZGG3QwJAerUAS5dAtavlx1O2dRJ/+wZpqpcGWjXTuzreQ6cglhorClSE5yQkBCsXbsWVqsViqJg2LBhxT7Tpk0brFmzBjdu3MCtW7ewa9cuNG7cWEK0RETud/2RR8TO0qViCEjLVq0SPRlduog5YcoSFAR4eYlVyS9fdk98rsYER1OkJjj+/v6IiYnBxIkTS3y/efPm2L59O44fP46wsDAEBwdj1qxZyMjIcHOkRETupzRsiFu9eoknWpv7piSODFMZaXhKpSY4QUGih4qk8pZ58oiICERERJT6/vvvv49ff/0Vb7zxRt5rcXFx7giNiEi+sWNFL8fWrcDp07Kjsc+KFcCDD4oEJzy89M8ZMcG5cEH0SNWvL36+HTtkR+TRpCY4ZTGZTBgyZAg++OADREREoFOnToiLi8OcOXOwZs2aUr/n6+uLSpUq5T23WCwAALPZDLPZuR1W6jGdfVwqG9vd/djm7qeYTFDGjQMAmJcsEfPF6ICyZg2Uzz8HOneGKTAQplISM9udBMd08CBMGvvZKnK92/74Axg2DKaePWHatavcMSiAWHdswAAoAwcClSvD9MQTMOl1QVI7FG33iv57o9kEp27durBYLJg2bRreeustvPHGGxg8eDB++ukn9OvXD1u3bi3xe9OnT8fMmTOLvR4UFITU1FSnxmg2mxF453ZAm83m1GNT6dju7sc2d7+ULl1wqkULeKeno8OpUzB17Cg7JLud2rsXKb16ocHLL6P+4sXF3rf5+CCmQwcoANplZKCSxn62ilzvCfHxuASg+qBBaB4Z6dB3s2vUQEqPHkjp0QO3evRAdv36hd5vPGkSaq9e7dAx9aRou/v7+1foeJpNcNTMbc2aNViwYAEAICYmBvfffz+ef/75UhOcOXPmYN68eXnPLRYLrFYrDh06hJSUFJfEGB0dzX/03Yjt7n5sc/ezvfoqAKDG+vU4vHu3rtpdWbQI6NULl/r0QcKkScXf79wZio8PcP06YiMioLVp8SpyvSurVwMTJ+JGYCCio6PL/mylSkCfPlAGDAAGDMgftlNlZgLbtwN+fkDv3rhQsyYu3uWYela03dURmPLSbIJz7do1ZGdnIzY2ttDrx44dQ58+fUr9XlZWFrKysoq9brPZXPIPhHpcPf3jYwRsd/djm9/RvDnw17+Kot+TJ11zjurVgZEjAQD3rFmDJL21+08/AZ9+CnTsCFuLFsCpU4XfV3ts9u+HYrOJ4RiNKff1vmcPYLMBTZvCVqeOWG1dZTKJAuSBA8UWElK8GDkmBvjtN7Ft2yYmD3zmGaB3byAoSF/XQTkUbPeK/qyaTXCys7Oxd+9etG7dutDrgYGBOH/+vKSoiMjjff21WG/opZdEovPtt84/x5NPil98R46gypEjzj++qyUlAb//DvzpT6LYePbswu8bscBYlZICxMYC990nbhffty8/oRkwAKhXr/Dnrdb8hOb330ueqTomRjwGB7s+fgORmuD4+/ujZcuWec8DAgIQHByMpKQkxMfHY+7cufj++++xdetWREZGYvDgwXj44YcRFhYmL2gi8lyDBuUvpli1KvDNN0BoKDBpkhhOcJY7SzOYFi3S3PCN3VasEAnOqFHFExwjrUFVkj/+EAnOsmWiN66g27eBqKj8pKbIKEWJjh8HsrLEsZo1A86dc0XUhqTI2kJDQ5WSLF68OO8z48aNU06ePKmkpaUpBw8eVIYOHerQOSwWi6IoimKxWJwev9lsVjp37qyYzWZpbeiJG9udbS5t27lTgaIomD9fwbvvKsjNFc8PHFDQooVzztGhgzhmZqZiqltXv+1es6aCrCzxs7Runf+6t7eC9HTxurPazMlbha/3MWPEz6coCnJyFOzerWDWLAV9+yrw8SnfMQ8eVO7MiCu9fdzV7k74/S3/h3LlxgTHeBvbnW0uZXvwQfELJjVVQb164rWBAxUkJorXb95U8OijFT/PggXieD/8oP92/+UX8bO89Vb+a2oCl5wsP75Stgq3u5eXgr/9TcGIEQpq1HBOXIsXi3Z75x3p7eOudq/o729tTT5ARKRV6vQTn32WXzj6229Ap05iIr5q1cRaTB9/DPj6lu8cvr6ioBTQ9sKa9lqxQjwWnNVYHZ46eND98bhLbi7wxRei2PrGDecck3U4DmOCQ0R0NwMHAr16iTta5s4t/N6lS0D//sCcOeL5yy+LW3ubNXP8PMOGAffcA8THAxs3Vjhs6dasEbUjQUFAmzbiNSMXGLsSExyHMcEhIrqbknpvCsrNBd58E3joIeD6daBbN9FDUcICwmWaMEE8LlkibjXWuxs38hM1tReHCU75qAlOixZABeeH8RRMcIiIyjJwIHD//aL35oMPyv7s+vViyGrnTqBGDWD1auCjjwAfn7ufp0kTcS4AKGH2X9364QfxOGqUWG6iwBw45ICkJODiRbHfoYPcWHSCCQ4RUVnU3pvPPy+596ao+Hhx6/iHH4rnU6aIGp0mTcr+3l/+IhKAzZsBIy0qrA5T3Xcf8MgjgL+/uFW66OR/dHccpnIIExwiotIMGGB/701BOTnA3/8uhqiSk8XcOQcPAkOGlPx5kwm4s7CmIYqLC7p5E9iwQey//754jI42xhCcu6kJjsbW7tIqJjhERKUp2HuTkOD499euFTUne/YAtWoBP/8M/OtfgHeROVb79xdFyTduiDtvjEa9m0otNGb9TfmwB8chTHCIiEoyYIBY/8fR3puizp0Taw59/LF4/vrrQGQk0KhR/mfU4uKvvwYyMsp/Lq1au7bwTM+svykfdaHNDh3EcCaViS1ERFSSGTPE4xdflK/3pqCsLLGcw6OPiiGbPn3EkNWgQUDNmsDw4eJzixZV7DxadetW/jAVwB6c8jp9GkhLA6pUAQosc0QlY4JDRFTUAw+IJCQ9XQwpOcvKlWKiu4MHgTp1gIgI0bvh5yf+d27kX/zqMFV6OnDsmNxY9MpmAw4fFvscprorJjhEREWptTfO6L0p6swZMWngZ5+J5336iEejFRcX9dNPwKpVwKxZYt4gKh/W4dhN6mriRESa07+/SDoyMipWe1OWzEzgxRfF7eNffgmkpor6GyNLTwdGjJAdhf4xwbEbe3CIiAoq2Htz+bJrz/Xdd6LY+L77xO3kRHfDBMdu7MEhIlL17y/ueMrIcG7tTVlSUtxzHjKGQ4fEY+PGYuqBpCS58WgYe3CIiFTqnVNffun63hui8khJAc6eFfvsxSkTExwiIgDo1w/o29e9vTdE5aHOh8MEp0xMcIiIgPzamy+/BC5dkhoKUZlYh2MXJjhERGrvTWYme29I+5jg2IUJDhFRwdob9t6Q1qkJTrt2xdc1ozxMcIjIs4WFAaGhovcmPFx2NER3d+6cWPKjUqX8BUypGCY4ROTZWHtDeqTeLt6xo9QwtIwJDhF5rtDQ/N4b1t6QnrAO566Y4BCR51J7b776CrBapYZC5BAmOHfFBIeIPFNoqKi/Ye0N6RHnwrkrJjhE5JnUO6f+8x/23pD+HDkiVmWvWxeoX192NJrEBIeIPE9oqJj7hr03pFcZGcDJk2KfvTglYoJDRJ6nYO/NxYtyYyEqL9bhlIkJDhF5lr59Re9NVhZ7b0jfmOCUya4pEK9fv+7QQRVFQefOnXHhwoVyBUVE5DLsvSGjUBMczoVTIrsSnBo1amDy5Mm4efPmXT9rMpnw6aefwsvLq8LBERE5Vd++QP/+ovdmzhzZ0RBVjJrgtG4N+PmJuhzKY/ciFt999x2uXr1q12cXLlxY7oCIiFyGvTdkJJcuAdeuAbVrA+3bA/v3y45IU+yqwfHy8rI7uQGAatWqIS4urtxBERE5XUhIfu8Na2/IKFiHUyq7i4wrV67syjiIiFxL7b3573+B+Hi5sRA5Cyf8K5XdQ1Q3btzAH3/8gcjISERGRmLnzp3IyspyZWxERM7Rpw/wwAOsvSHjYQ9OqezuwZkwYQJOnDiBp556Cps2bUJycjI2bdqEt956C71794a3t925EhGRe6m9N4sWsfeGjIUJTqnsTnD+97//4bnnnkOrVq3QpEkTPP/884iLi8O4ceMQFRWF5ORkREREuDJWIiLHdewIDBjA3hsypmPHxLVdowbQpInsaDSlXBP9Wa1WLF++HM8++ywGDRqE2bNnIzc3FwMGDHB2fEREFfPoo+Jx7VqAc3OR0WRniyQH4Hw4RTic4AQEBGD8+PFYtmwZLly4gP3796Nbt27417/+hb59+7oiRiKi8hsxQjyuXCk3DiJX4TBViewunFmyZAn69esHi8WCHTt2YOvWrfjkk0+wb98+2Gw2V8ZIRFQ+bdoAbduKRTV/+UV2NESuwQSnRHYnOKNHj8aFCxcwe/ZsbNq0CQcPHnRlXEREFTd8uHj8/XcgJUVuLESuwgSnRHYnOO3atUNYWBjCwsIwZcoU+Pn5Yfv27YiKisKWLVtw4MABKIriyliJiByjDk/99JPcOIhcSU1wWrYEqlYFbt+WG49G2F2Dc+LECXzxxRd48skn0bBhQ/Tu3Ru//vorunfvjnXr1iEpKQnr1q1zZaxERPZr0gTo2hXIzRUFxkRGde0aYLWK/Q4d5MaiIeWevObYsWNISkpCcnIykpOT8cQTT+BPf/qTM2MjIio/dXhq2zbxC4DIyGJigEaNxDDVrl2yo9EEhxKcOnXqICwsDP369UNYWBgCAwORlZWFPXv2YP78+YiMjHRVnEREjuHwFHmSmBjgoYdYh1OA3QnO0aNH0bp1a+Tk5GDv3r1YuXIlIiMjsWPHDmRmZroyRiIix9StK5ZnAIBVq+TGQuQOah0O58LJY3eCs2bNGkRGRmL79u1IT093ZUxERBUzdChgNgN79gAXL8qOhsj11ASnQwdx7XP6FvsTnDfffNOVcRAROQ+Hp8jTnDoFpKcD/v5AixbiuYezO8F5++237frcrFmzyh0MEVGFVa8uVg4HmOCQ58jNBY4cAbp1E3U4THDsT3BmzpyJS5cu4cqVKzCZTCV+RlEUJjhEJNeQIYCvL3D0KP+RJ88SHZ2f4Pz4o+xopLM7wYmIiEC/fv2wb98+LFq0CL/88guXaCAi7eHwFHkqzmhciN0T/Q0ZMgTNmzfHH3/8gblz5+LixYsIDw9HYGCgK+MjIrJf5cqAOh8XExzyNExwCnFoNfGEhASEh4ejTZs2ePzxx1G3bl3s3bsX27dvh5+fn6tiJCKyz4MPAlWqAHFxorueyJMcOiQemzQBataUG4sGOJTgFLR3715ERkbi2LFj6NSpE3x8fJwZFxGR4zg8RZ7s1i2R3APsxUE5EpyePXviyy+/REJCAl5++WUsXboUDRs2RApX6iUimXx8gIcfFvtMcMhTcZgqj91Fxn//+98xbtw43HPPPfj666/Rp08fHDlyxJWxERHZLyxMdMsnJHAtHvJcMTHAI48wwYEDCU54eDguXLiAFStWQFEUjBs3rsTPvfbaa04LjojIburw1OrVgKJIDYVIGvbg5LE7wdm6dSsURUH79u1L/YzCf1SISAazWfyvFeDwFHk2tbi+fXvA2xvIyZEajkx2Jzj9+vVzZRxEROXXqxdQvz6QnAxs2SI7GiJ5zp0TxcbVqgGtW4sJLz1Uue+iIiLSjOHDxeO6dUB2ttxYiGRSlPzbxT18mMquBOejjz5ClSpV7D7o7NmzUdOOe/BDQkKwdu1aWK1WKIqCYcOGlfrZzz//HIqiYNKkSXbHQUQegreHE+VjHQ4AOxOcSZMmOZTgvPTSS6hRo8ZdP+fv74+YmBhMnDixzM8NGzYMPXr0gNVqtTsGIvIQHTsCAQFAaiqwcaPsaIjkUxOcjh2lhiGbXTU4JpMJJ0+etLuI2N/f367PRUREICIioszPNGzYEJ988gkGDRqEX375xa7jEpEHUXtvIiKA9HS5sRBpAXtwANiZ4JR2S3hZEhMTHf5OUSaTCcuXL8fcuXMRGxtr13d8fX1RqVKlvOcWiwUAYDabYTY7t+RIPaazj0tlY7u7n5bb3HYnwTGtXg2TBuOrCC23u5Hpvd2V2FgoNhtQrx5MDRrA5ITfx+5QtN0r2v52JTjLli2r0EnK64033kBOTg4+/vhju78zffp0zJw5s9jrQUFBSE1NdWJ0ovHVxUa5srr7sN3dT6ttntG0KWLbt4cpOxsdLlyAt8G65LXa7kZnhHY/euECMps1Q4sRI1BNJxNfFm13e0eDSmP3beLu1rlzZ0yaNAmdO3d26Htz5szBvHnz8p5bLBZYrVYcOnTI6ctJqNlldHS0bv8S6BHb3f202ubKgw+Kx02bcGT7dsnROJ9W293ojNDutr17gWbNcMbfHyadLDxbtN3VEZjy0myCExISgrp16+LChQt5r3l7e+Ojjz7C5MmTERAQUOL3srKykJWVVex1m83mkgtVPa5e/xLoFdvd/TTZ5urt4StXaisuJ9Jku3sA3bf7wYPAY49BCQoSw1U6UbDdK9r2mk1wli9fjt9//73Qaxs2bMDy5cuxePFiSVERkWY0bgx07w7YbMCaNbKjIdIWFhrLTXD8/f3RsmXLvOcBAQEIDg5GUlIS4uPjkZSUVOjz2dnZSEhIwMmTJ90dKhFpjbo0w/btwNWrUkMh0hw1wWnTBqhUCcjMlBuPBFJLxLt27Yro6GhE3xkfnD9/PqKjo/Hee+/JDIuI9ICT+xGVzmoFrl8X61GVsYakkdnVg7Ny5Uq7Dzhy5Ei7PxsVFQWTyWT350uruyEiD1OnDhASIvZXrZIbC5FWxcQA/fuLYaoDB2RH43Z29eDcvHkzb7t16xYeeOABdO3aNe/9Ll264IEHHsDNmzddFigRUZ6hQwEvL2DfPqDAjQhEVICH1+HY1YMzfvz4vP3w8HCsWLECzz//fF6Fs9lsxqeffopbt265JkoiooLUu6c4PEVUOg9PcByuwRk/fjw+/PDDQrdv2Ww2zJs3r1AiRETkEtWqAQMGiH0mOESlY4LjGG9vb7Rt27bY623bttXttNZEpCMPPSTuCjl2DDhxQnY0RNoVGwtkZwM1a4ppFTyMw7eJL168GIsWLcLs2bOxe/duAEDPnj0xbdo0zk9DRK7Hu6eI7JOVJf4jEBQkenHi42VH5FYOJzhTp05FQkICXn31VTRo0AAAcPnyZXzwwQf46KOPnB4gEVEePz/RgwMwwSGyR0yMSHA6dgR+/ll2NG7lcIKjKArmzp2LuXPn5q0T4ew1noiISvTgg4C/P3D+vEfe9krksJgYYPRoj6zDqdBMxkxsiMitePcUkWM8uNDY4argunXrYtmyZbBarcjOzkZOTk6hjYjIJby9xfw3ABMcInupCU6LFqL304M43IOzZMkSNGnSBLNmzcLly5ehKIor4iIiKiw0FKhVC7hyBdi5U3Y0RPpw9Spw+TLQoAHQoQNw5+YgT+BwgtOnTx+EhIQgRs0KiYjcQb17avVqsYI4EdknJkYkOMHBHpXgODxEFR8f79D6UUREFWYysf6GqLzuLGjtaXU4Dic4kydPRnh4OJo2beqKeIiIiuvZU/wP9OZNYPNm2dEQ6YuHFho7PET1/fffo0qVKjhz5gzS0tKQnZ1d6P177rnHacEREQHIH55at07MzEpE9lMTnKAg0RvqIbWzDic4kydPdkEYRERl4PAUUfmdPAlkZABVq4q7qU6flh2RWzic4CxbtswVcRARlSwoSPyjnJYGbNggOxoi/cnNBY4cAbp2FcNUHpLgVGh1TD8/P1gslkIbEZFTqcNTGzaIJIeIHOeBdTgOJzhVqlTBwoULkZiYiNu3byM5ObnQRkTkVFxck6jimODc3QcffID+/fvjxRdfRGZmJp599lnMmDEDly5dwpgxY1wRIxF5qlatxORk2dket1AgkVN5YILjcA3Oww8/jDFjxiAqKgqLFi3Ctm3bcObMGZw/fx5PP/00vvnmG1fESUSeSC0u3rwZuHFDaihEuqYmOE2bAjVqeMTfJ4d7cGrVqoW4uDgAwK1bt1CrVi0AwPbt29G3b1/nRkdEno3DU0TOcfMmcO6c2A8KkhqKuzic4Jw9exbNmjUDAMTGxmLUqFEARM/ODQ/ICInITRo1Anr0EMsyrFkjOxoi/VN7cTp2lBqGuzic4CxevBjBd8bw5syZgxdffBEZGRmYP38+5s6d6/QAichDPfKIeNy5E0hMlBoKkSF4WB2OwzU4CxYsyNvfsmUL2rRpg65du+LMmTM4dOiQM2MjIk/G4Ski52KC45j4+HjEx8c7IxYiIuGee4DQULG/apXcWIiMQk1w2rcHvLzEBIAGVq4Ep1u3bggLC0PdunVhNhce5XrttdecEhgRebChQ8U/wAcO5BdGElHFnD0LpKQAFgvQujUQG1v+Y9WuDbRtC7RrJ7affwZ++815sTqBwwnO9OnT8c9//hMnTpxAYmIilAKLdikesoAXEbkYh6eInE9RgMOHgfvvF8NU9iQ4DRuKBEZNZtTHOnUKfy4jQ/8JzqRJkzB+/HgsXbrUFfF4rjp1xIWkdiESeap77gEGDRL7K1fKjYXIaKKj8xOcb78Vr5lMYn6cggmMul+9esnHsdlE72psLHDsGLBxo7t+Ars5nODYbDbs2LHDFbF4rmbNxJ0idesCnTsDLNYmT/bYY4CPD7B/P3D8uOxoiIxF/U/0I4+IqRjatQPatAGqVCn58zk5YnHO2Nj8ZCY2FjhxAkhPd1vY5eFwgjN//ny89NJLePXVV10Rj+epU0dkvg0aiOdPPcUEhzzbM8+Ix//9T24cREYUHS0eW7cWmyozU/yHQk1g1MdTp8RSKTrkcILz4Ycf4pdffsHp06cRGxuL7CI/+MiRI50WnOH5+wO//CLW20lLExn0qFHAtGmyIyOSIyAA6N1b3N3x3XeyoyEynj17gPBwURJRsFcmLs5wd1U5nOAsXLgQ/fr1Q2RkJK5fv87C4vLy8RH1Bd26AVevAgMHAtu3i3/gu3YF9u2THSGR+z39tHjctAlISJAbC5FRTZ8uOwK3cDjBGTNmDEaOHIlff/3VFfF4BpMJWLxYFFKmpgJDhohx0Z9/Bp54QtQgMMEhT6QmOByeIqIKcniphqSkJJw5c8YVsXiODz8U/5BnZwMjRwJ794rXV6wQj3fW9yLyKF26iGLHtDRO7kdEFeZwgjNz5ky8++67qFy5siviMb6pU4EpU8T+uHHAhg35761fD9y+Le6q6tZNSnhE0qjFxatXi78HREQV4PAQ1SuvvIIWLVogMTER586dK1Zk3KVLF6cFZzijRwPqgqSvvQZ8/XXh9zMygLVrxZ1Ujz2W37NDZHReXsCTT4r9on8viIjKweEEZ/Xq1S4IwwMMHgwsWiT2P/wQmDev5M/98INIcEaNAl5/3X3xEck0YABQr54ouNfghGFEpD8OJzjvvfeeK+Iwtu7dgR9/BLy9geXLy05cIiLEWiFNm4rv7dnjvjiJZFGHp777TkwsRkRUQQ7X4ABA9erVMWHCBMyePRs1a9YEAHTq1AkNGzZ0anCGEBgo5rrx9xfJy/jxYj2Q0qjDVACLjckz+PsDw4eLfd49RURO4nCC06FDB5w8eRJvvPEGpk6diho1agAAhg8fjjlz5jg7Pn1r2FB0t9euLXpiHn3Uvv+d/vCDeHzsMdfGR6QFw4aJJOf0afZYEpHTOJzgzJs3D0uWLEFgYCAyMjLyXl+/fj369u3r1OB0rXp10WPTtClw8qSY6yY11b7vqsNUTZoAPXq4Nk4i2bg0AxG5gMMJTrdu3fDFF18Ue91qtaJ+/fpOCUr3KlUC1qwBOnQALl8WE/pdu2b/9zMzxfcBDlORsdWtCzz4oNjn3VNE5EQOJzgZGRmoVq1asddbt26Nq1evOiUoXTObgW++AUJDgZs3xd1T5845fhx10r9HHxUzHxM5U506wH/+AyxcKPf6euIJcYv47t1iiIqIyEkcTnDWrFmDd955B97e4gYsRVHQuHFjhIeHY+XKlU4PUHf+/W9gxAjRCzNsWPlXBt+4Ebh1i8NU5HyDBonrcsIEYOJEMZu2LFyagYhcxOEEZ+rUqahTpw6uXLmCypUrIyoqCqdPn0ZKSgr+8Y9/uCJG/XjnHeD55wGbTcxlExVV/mNxmIqcrVIlYMECUeNVv76o8wKAmTNFz6O7BQaKqRBycvJ7LImInMThf9VSUlIQEhKCkSNHYtq0afjkk0/w0EMPISwsDGlpaa6IUR/+9jfg3XfF/ksvAT/9VPFjqv/oP/YYh6moYtq3FzNjT5oknn/8MdCyJZCcLN57/HH3x6T23mzYICb4IyJyMsXIm8ViURRFUSwWi9OPbTablc6dOyumkSMV5OQoUBQFM2c67xy+vgpu3BDH7dVLeltqZVPb3Ww2S49FF9vEiQrS08V1lJCg4E9/yn/vzTfF68ePK/Dycm+bnzkjzv3EE/LbSKMbr3W2uydtRdu9or+/HerBMZlMGDduHNatW4fDhw/j0KFDWLNmDUaPHu3IYQwlpXNnKP/7nyiU/OIL0d3vLFlZHKai8qtbV0wyuXAh4Ocn9oOCxKKuqo8/Fnf4tW6d36PiDr16Ac2bi2Ey9RonInIihxKctWvX4j//+Q8aNWqEw4cP4+jRo2jatCmWLFmCVatWuSpGzVI6dMDZefPEL49Vq8TQlLNxmIrK46GHgMOHxWNGhigm/vOfgStXCn/u9m3ggw/E/jvviOVE3EFNpn76CUhPd885icjj2NXV85e//EW5efOmEhYWVuy9fv36KTdv3lRGjx4tvYur6OayIaqmTRVYraKLPSpKgZ+fa34GX18FycniPL17S29PLWzsPi5j8/NT8PHH4npRFAUxMQraty/7O1WqiKErRVEwfrzr29zHR8HVq+J8AwfKbzMNb7zW2e6etEkbonryyScxe/ZsbNmypdh7kZGRCA8Px9Pu7OKWbfZsoGFD+J0+DdPw4eJ/ya5QcJiKSzdQWTp0EIXEL78sni9YIO5SOnq07O+lpQHh4WL/7bcBHx+XholBg8TyJZcvA5s3u/ZcROSx7E5wgoKCEBERUer769evR3BwsFOC0oW//hVYtAgtJ06E6cYN156Lw1RUFpMJeOUVsY7TffcBCQligslXXxXTDdjj889FwtGsmVgQ1pXUpRm+/RbIzXXtuYjIY9md4NSqVQuJiYmlvp+YmJi3srhHSE2F+bnn4OuO21t/+w24cUMs3tm7t+vPR/pRrx7w66/A//2fqAVbt04UEm/Y4NhxMjJEryQA/OMfYs4cV7BYgKFDxT4n9yMiF7I7wfHy8kJOGSth5+bm5s1uTE6WnS2KmAEOU1G+IUNEIfHgwaJQ94UXRPJQ3qT7q6+A+HigcWPgueecG6tqxAigcmUgNhY4eNA15yAiAmB3RmIymbBkyRJkltLlXclV/+Mj4YcfgHHjxNpUr74qZksmz1S5MjB3bv5de9HRYubsY8cqdtzMTOD998Vw1ZtvirWqnF1bpg5PcWFNInIxu3twli5diitXruDmzZslbleuXMGyZctcGatn+/13Messh6k8W1AQsG9ffnLz0UdirbKKJjeqRYvE4rANGogeIWdq2BDo31/sf/ONc49NRFSE3T04411deEhlU4epxo8Xk/5t2yY7InK3Rx4BvvtO1MdcvgyMHSvqs5wpOxuYNQv473+BadPE5JXOWoLlySfFmlfbtokkiojIhSSssEflpt5NNXKknMURSR4/P+CTT0Rys3atuCXc2cmNatky4MwZMROyMyevVIenWFxMRG7A35J6smkTkJQkhg/69JEdDbnT888DjRoBFy6IQvPr1113rpyc/IVjX38dqFq14sds3x7o2FHM6/TDDxU/HhHRXUhNcEJCQrB27VpYrVYoioJhw4blveft7Y3w8HAcOnQIt2/fhtVqxdKlS9GgQQOJEUuWk5N/NxXXpvIc/v7A9Oli/733RJLgat98A5w4ISbke+WVih9PnQT0119FLRkRkYtJTXD8/f0RExODiRMnFnuvSpUq6Ny5M2bNmoXOnTtjxIgRCAwMxNq1ayVEqiEcpvI8L78shotOnwaWLnXPOXNz83txpk6FUq1a+Y9lMuUnOByeIiI3kr7+BABFURRl2LBhZX6ma9euiqIoSuPGje0+rsvWoiph3Qy3bN7eCq5dE+v4hIZK/3OTsXnUOjHVqytIShJ/3k895d5zm80KjhwR5545s/xt3revOMaNGwoqVZLfpjraPOpa19DGdtdGu1f097euZuarXr06bDYbbpSxNIKvr2+hOXksFgsAwGw2w+zkHg/1mM4+bplsNthWrwYmTAAefxxmD7ybSkq7S2J77TWgZk3g6FGYVqyAyc0/s/Lee1C+/x6YPBm2rVvL1ea20aPFzo8/wpydzZ5HB3jSta4lbHc5irZ7RdtfNwlOpUqVEB4ejm+++QYpKSmlfm769OmYOXNmsdeDgoKQmprq1JjMZjMCAwMBADY3Trx368ABnJ4wAd6jRqHDokUwedikf7La3d1yatTAkSlTYAMQsGQJagYFuT0G5cwZHD95EumBgch++WV0vHXLoTa3+fri8OOPIxdAqz/+gKVjR5fFakSecq1rDdtdjqLt7u/vX6HjmSC6cqRTFAWPPPII1qgrZxfg7e2NH374AU2aNEFYWFiZCU5JPThWqxU1atQo83vlYTab0bFjR0RHR7v1L4Hi7Q3FagVq14bpgQdgKmGFdyOT1e7uZgsPB/7+d+DAAZi6d4dJkfNXVRk2DMpPP8GclgZT8+ZQHFgKQhk+HMqPPwLx8TAFBEj7GfTKU651rWG7y1G03S0WC27cuIFq1aqV6/e35ntwvL29sWLFCgQEBKB///53/SGzsrKQVcJdJjabzSUXqnpct/4lyMoSd1M99xyURx+Fsnmz+86tEVLa3Z3q18+fg+btt6Hk5sr7n8iqVcD+/bB16QJMmQK88Yb9333qKfH4zTdyfwYdM/y1rlFsdzkKtntF217TA4xqctOqVSsMGDAASUlJskPSjoJ3U3l5yY2FnG/6dKBKFWDXLnFrtWQmddj3pZfEHV32qFlTLAgK8O4pInI76beJBwcHIzg4GAAQEBCA4OBgNG7cGF5eXvjxxx/RtWtXPP300/Dy8kK9evVQr149+Pj4yAxbGyIjgWvXxC+b0FDXn69mTdefg4TGjYG//U3s/+MfcmNR/forqhw+LObksbcH59FHxczLMTHAkSOujY+IqATSbgkLDQ1VSrJ48WKladOmJb6nKIoS6sDt0Ya7Tbzg9vnn4vbbzz5z3Tn8/BSsWaMgN1fB5MnSrhVNtburty+/FH+umzbJj6VAm7d88UURV1qaggYN7v69LVvE56dOlR6/XjfDX+sa3dju2mh3J/z+lv9DuXIzdILzwAPiF8iVKwq8vJx/fIsl/5eUuj35pPQ/U+nt7sqtRQsF2dmire+/X348Bdq8U+fOCrZtE7F9/HHZ32nSRHwuN1dBo0bS49frZuhrXcMb210b7V7R39+arsGhu9iyBbh6FahTBwgLc+6x77kH2LxZDH/dvJlf87NkCfDAA849F+WbMQPw9hZ1Nzt3yo6mEBMK1OL89a/AvfeW/mG1uHjLFsBqdXFkRETFMcHRs9xcYOVKse/MtakaNgS2bgW6dhUJVL9+wBNPAN99B/j6irtqOJ+J87Vtm7+kwdtvy42lFKbISFH/ValS2fVB6uR+LC4mIkmY4OidujLziBHOuZuqeXNg+3agXTvg4kUgJAQ4eBBQFGDsWNGrY7EA69cDzZpV/HyU7913xSy/K1cCBw7IjqZ077wjHidMAJo2Lf5+x47i+snIyE/AiYjcjAmO3kVFAVeuiFWf+/Wr2LHatxfJTUAAcOoU0KePWFFalZUFDB8u7oqpXx/YsEEMZVHFdewIPPYYYLOJYSot274d2LgR8PEB3nqr+PtqL9S6dcCtW+6NjYjoDiY4euesYapu3cSwVIMGwKFDoufm/Pnin7t1C/jTn4Bz54DAQODnn8V8LVQxs2aJx2+/BY4elRuLPdQk7C9/AVq0yH/dbM6vv+HwFBFJxATHCNQC4OHDRYGqo8LCgE2bgFq1xMRyYWFAYmLpn798GRg8GLh+HejZE/j+e042WBE9ewJ//jOQkyOGqfRg925RCO3tXbheqF8/UcN1/boYxiQikoQJjhFs3SoSkvIMUz38sPhFZLEAv/8ODBwIJCff/XsnTojvpqeLX85ffFG+2Cm/92bpUjE0qBdqLc4zzwCtW+fvAyLpzs6WExcREZjgGIPNVr5hqqeeAn76CfDzA1avFomKIyuu79oFPP64GCabMEE/vQ9aEhYGDBgg6pvUREcv9u8H1qwRvXfvvANUriyWDgE4PEVE0jHBMQpHh6mefx5Yvlx8dtkyMa1+Zqbj5123DnjhBbH/zjtifhSyn5rUfPllyTVPWqfW4jzxBDBtmugJjIvT3Bw+ROR5mOAYxbZtQEKCuKupf/+yP/vGG8Bnn4mC0IULRaFobm75z/3VV4A6AdynnwLDhpX/WJ5k0CBxp1p6OjB7tuxoyicmBvjxR3EtqUNWX38tNyYiIjDBMQ57h6nmzAHCw8X+rFnAK6+IOW4q6t13RS+El5e4E+j++yt+TKP75z/F47//LQq39WrmTHH9qZjgEJEGMMExkoLDVEVXXDeZRO/KtGni+dSp+f/jdpYXXwTWrhW1GOvWAW3aOPf4RvLII2Km6Nu3gX/9S3Y0FXP0qLiTDgD27QOOH5cbDxERmOAYy/btoiegVq3C60V5e4t6mxdeEP/Tfu454KOPnH/+3FxRi7Frl4ghIkLcMkyFmc35tTcLFgDXrkkNxymmThXX2KRJsiMhIgLABMdYCg5TPfaYePTzE3dKPf20uG33ySeB//zHdTGkp4vbx0+cENP4r18PVK/uuvPp0ahRwH33idvxP/xQdjTOcekSMGYMi4uJSDOY4BhNwWGqWrXEZGzqfDXDhuW/70rXr4sC2suXgaAgsTinr6/rz6sHXl75t9N/+KFYqZ2IiJyOCY7R7Ngh/jdds6ZYcqFfP7G8wqBB7p1Z9vx5saTDrVsihmXLRB2Qpxs9WixxcfUq8PHHsqMhIjIsJjhGY7OJ23YBoFEjUd/Rr5+4jdzdYmJET1JWlpgQcN4898egJb6++fPGhIeLAmMiInIJJjhGtHy5eLRagb59gQMH5MWyeTMwdqzYnzxZFKN6qgkTgGbNRA/bZ5/JjoaIyNCY4BjRvn1Ax46ikPXYMdnRAN99B0yZIvbnzhUFz57Gzw946y2x//77oiaKiIhchgmOUcXEADduyI4i3/z5+bemL14sFvX0JC+8IG6ZP3fOtXexERERACY45E5//zvwzTdiEsLvvgMqVZIdkXv4+wPTp4v9994TNUlERORSTHDIfRQFGDdOrJlVqxbQrZvsiNzjlVeAOnWAU6fE3WRERORyTHDIvbKygK1bxX7fvnJjcYfq1UXPFSDuoKrIoqZERGQ3JjjkflFR4tETEpzXXhNzEh05kr9eExERuRwTHHI/tQend28xs69R1aolbo0HgLffLrziNhERuRQTHHK/o0eBpCSgalWgc2fZ0bjO4MGAxSJ6b1avlh0NEZFHYYJD7qco+TMrG3mYKixMPLpziQwiIgLABIdk8YRCYzXB2bJFZhRERB6JCQ7JoRYah4QYcxHORo2AVq3EXVPbt8uOhojI4zDBITmio4GUFHGH0X33yY7G+UJDxeOBA2JFdSIicismOCRHbi6wY4fYN+IwFYeniIikYoJD8qh1OGpvh5EwwSEikooJDslj1EJj1t8QEUnHBIfk2bsXSE8H6tUDAgNlR+M8rL8hIpKOCQ7Jk5UF7N4t9o3Ui9Ovn3iMjJQbBxGRB2OCQ3IZcZiK9TdERNIxwSG5jJbg3Hsv0LIl62+IiCRjgkNy7d4NZGcDTZuKTe/U+pv9+8U8P0REJAUTHJIrLQ3Yt0/sG6EXh8NTRESawASH5DPSMBUTHCIiTWCCQ/Kp61LpPcFh/Q0RkWYwwSH5duwAbDYxF079+rKjKT/W3xARaQYTHJLv1i2x+CYgVhfXKw5PERFpBhMc0gYjrEvFBIeISDOY4JA26L3QmPU3RESawgSHtGHbNvHYoQNQq5bcWMqD9TdERJrCBIe04do14OhRsd+nj9xYyoPrTxERaQoTHNIOPQ9Tsf6GiEhTmOCQdui10LhxY6BFCyAnR9zyTkRE0jHBIe1Q63A6dQIsFrmxOIL1N0REmsMEh7TDagXOnAG8vID775cdjf04PEVEpDlMcEhb9LhsAxMcIiLNYYJD2qK3QmPW3xARaRITHNIWNcHp3h3w85Mbiz1Yf0NEpElMcEhb4uKAixcBX1+gZ0/Z0dwdh6eIiDSJCQ5pj56GqZjgEBFpEhMc0h69FBoXrL/h+lNERJrCBIe0R+3B6dUL8PGRG0tZ1PqbffuA27flxkJERIVITXBCQkKwdu1aWK1WKIqCYcOGFfvMjBkzYLVakZaWhsjISLRr105CpORWx48DV68CVaoAXbrIjqZ06vpTHJ4iItIcqQmOv78/YmJiMHHixBLff/311zFlyhRMnDgR3bp1Q0JCAn777TdUrVrVzZGS2+mhDof1N0REmiU1wYmIiMDbb7+NVatWlfj+5MmT8f7772PVqlU4evQoxo4diypVquCpp55yc6Tkdlpfl6pJE6B5c85/Q0SkUd6yAyhNQEAAGjRogI0bN+a9lpWVhaioKNx///348ssvS/yer68vKlWqlPfccmdNI7PZDLPZufmcekxnH5cAZft2KADQpw9M3t4w2Wx572mh3ZV+/UR8+/bBnJYGGPwa0EKbeyK2uxxsdzmKtntF21+zCU79+vUBAImJiYVeT0xMRNOmTUv93vTp0zFz5sxirwcFBSE1NdWpMZrNZgQGBgIAbAV+AVPFKWYzDqWkILdaNbQeNQpVjh/Pe08L7X5++HBcB1Dv+HE06thRSgzupIU290RsdznY7nIUbXd/f/8KHU+zCY5KUZRCz00mU7HXCpozZw7mzZuX99xiscBqteLQoUNIcfJMs2p2GR0dzb8ELmDbuhUYMgQn6taF6bvv8l7XQrvbOnQAAFxZsQJXo6OlxOBOWmhzT8R2l4PtLkfRdldHYMpLswlOQkICANGTo+4DQN26dYv16hSUlZWFrKysYq/bbDaXXKjqcfmXwAWiooAhQ6CEhEBZsKDQW1LbvUD9jbJtGxQP+bPntS4H210OtrscBdu9om2v2QHGuLg4XL58GQMHDsx7zcfHB6Ghodi5c6fEyMhtCt5JZTLJjaUgzn9DRKR5Untw/P390bJly7znAQEBCA4ORlJSEuLj47FgwQK8+eabOHXqFE6dOoU333wTaWlp+OabbyRGTW6zfz+QmgrUrg20bQvExsqOSODt4UREmic1wenatSu2FPglMX/+fADAkiVLMG7cOHzwwQeoXLkyPv30U9SsWRN//PEHHnzwQdzm/5o9Q04OsHMnMHCg6MVhgkNERHaSmuBERUXBdJehh3fffRfvvvuumyIizdm6NT/B+fxz2dEUnv+G608REWmWZmtwiABob0Zjtf5m714xfEZERJrEBIe0bc8eIDMTaNRI9JzIxuEpIiJdYIJD2paRIZIcQBvLNnCBTSIiXWCCQ9qnlWGqpk2BgACuP0VEpANMcEj7oqLEo+wEh/U3RES6wQSHtG/XLtFr0rw5cO+98uJg/Q0RkW4wwSHtu30bOHBA7IeEyIuDCQ4RkW4wwSF9kF2Hw/obIiJdYYJD+qAmOLLupGL9DRGRrjDBIX3Yvh2w2YC2baHUqeP+83N4iohIV5jgkD4kJwOHD4t9GXU4aoITGen+cxMRkcOY4JB+3BmmUtyd4Kj1N9nZYvFPIiLSPCY4pB9qHY67ExzW3xAR6Q4THNKPbdvEY3AwcqpWdd95WX9DRKQ7THBIPxITgRMnALMZqZ06ue+8XH+KiEh3mOCQvtxZtiHFXQlO06ZAs2asvyEi0hkmOKQvd+pwbnfu7J7zqcNTrL8hItIVJjikL3cSnLS2baH4+7v+fKy/ISLSJSY4pC/x8cC5c4C3N9Czp+vPxwSHiEiXmOCQ/ty5m0px9bpUrL8hItItJjikOyb1dnFXz4fD+hsiIt1igkP6c+dOKvToAVSq5LrzcHkGIiLdYoJD+nP6NLyvXQP8/IBu3Vx3HtbfEBHpFhMc0h0TgKoHDognrqrDYf0NEZGuMcEhXbK4OsFRe2/27AHS0lxzDiIichkmOKRLVQ8eFDu9e4tbxp2Nw1NERLrGBId0ye/MGeD6daBqVcAVyzYwwSEi0jUmOKRLJkUBtm8XT5w9TNWsGetviIh0jgkO6ZbpzrINTk9wWH9DRKR7THBIvwpO+GcyOe+4HJ4iItI9JjikX9HRQEoKULMmcN99zjsuExwiIt1jgkO6ZcrNBXbsEE+mTQOeeQbo3x9o0waoVq18B23WTMyBk5XF+hsiIh1zwf21RG60eTMweDDw1FNiKyg1Fbh0qfB2+XLx1wquM8X6GyIiQ2CCQ/r22WdiyYaWLYGGDcXWoIEYtvL3B1q1EltZbt3KT3buvVe8xuEpIiJdY4JD+nb7NjBrVvHXK1cWiY6a9JS2WSxiOKtaNTG0pdq0yX0/AxEROR0THDKm9HTg7FmxlaVq1eKJUHIye3CIiHSOCQ55ttu3gVOnxEZERIbBu6iIiIjIcJjgEBERkeEwwSEiIiLDYYJDREREhsMEh4iIiAyHCQ4REREZDhMcIiIiMhwmOERERGQ4THCIiIjIcJjgEBERkeEwwSEiIiLDYYJDREREhsMEh4iIiAzHY1YTt1gsTj+m2WyGv78/LBYLbDab049PJWO7ux/bXA62uxxsdzmKtntFf28bPsFRG8hqtUqOhIiIiBxlsViQkpLi8PdMABTnh6MtDRs2LFfj3I3FYoHVakWjRo1ccnwqGdvd/djmcrDd5WC7y1FSu1ssFly6dKlcxzN8Dw6AcjeOvVJSUviXQAK2u/uxzeVgu8vBdpejYLtXpP1ZZExERESGwwSHiIiIDIcJTgVkZmZi5syZyMzMlB2KR2G7ux/bXA62uxxsdzmc3e4eUWRMREREnoU9OERERGQ4THCIiIjIcJjgEBERkeEwwSEiIiLDYYJTTi+88ALOnj2L9PR07Nu3D3369JEdkqHNmDEDiqIU2i5fviw7LMMJCQnB2rVrYbVaoSgKhg0bVuwzM2bMgNVqRVpaGiIjI9GuXTsJkRrL3dp98eLFxa7/Xbt2SYrWGKZNm4Y9e/bg1q1bSExMxKpVqxAYGFjsc7zencuednfW9c4EpxxGjRqFBQsW4P3330enTp2wbds2rF+/Ho0bN5YdmqEdOXIE9evXz9s6dOggOyTD8ff3R0xMDCZOnFji+6+//jqmTJmCiRMnolu3bkhISMBvv/2GqlWrujlSY7lbuwPA+vXrC13/Dz30kBsjNJ7Q0FD8+9//Rs+ePTFw4EB4e3tj48aNqFKlSt5neL07nz3tDjjvele4Obbt3r1b+fTTTwu9Fhsbq8yePVt6bEbdZsyYoRw8eFB6HJ60KYqiDBs2rNBrly5dUl5//fW8576+vkpycrLy17/+VXq8RtlKavfFixcrq1atkh6bkbfatWsriqIoISEhea/xepfT7s663tmD4yAfHx906dIFGzduLPT6xo0bcf/990uKyjO0atUKVqsVZ8+exbfffouAgADZIXmUgIAANGjQoNC1n5WVhaioKF77bhAWFobExEScOHECX375JerUqSM7JEOpXr06ACApKQkAr3d3KdruKmdc70xwHFS7dm14e3sjMTGx0OuJiYmoX7++pKiM748//sCYMWMwaNAgPPfcc6hfvz527tyJWrVqyQ7NY6jXN69991u/fj2efvpp9O/fH6+99hq6deuGzZs3w9fXV3ZohjFv3jxs27YNR48eBcDr3V2KtjvgvOvdI1YTdwVFUQo9N5lMxV4j54mIiMjbP3LkCHbt2oUzZ85g7NixmD9/vsTIPA+vffdbsWJF3v7Ro0exb98+nD9/HkOGDMGqVaskRmYMn3zyCYKCgkq8WYTXu+uU1u7Out7Zg+Oga9euIScnp1gGX7du3WKZPrlOWloaDh8+jFatWskOxWMkJCQAAK99DUhISMD58+d5/TvBxx9/jKFDh6Jfv36wWq15r/N6d63S2r0k5b3emeA4KDs7G/v378fAgQMLvT5w4EDs3LlTUlSex9fXF23btuWt4m4UFxeHy5cvF7r2fXx8EBoaymvfzWrVqoXGjRvz+q+ghQsXYsSIEejfvz/OnTtX6D1e765TVruXpCLXu/Qqar1to0aNUjIzM5Vx48Ypbdq0UebNm6ekpKQoTZo0kR6bUbe5c+cqffv2VZo1a6Z0795dWbt2rXLz5k22uZM3f39/JTg4WAkODlYURVEmT56sBAcHK40bN1YAKK+//rqSnJysPPLII0r79u2Vr7/+WrFarUrVqlWlx67nrax29/f3V+bOnav07NlTadq0qRIaGqrs2LFDiY+PZ7tXYPv3v/+tJCcnK3379lXq1auXt/n5+eV9hte7+9vdyde7/B9Yj9sLL7ygxMXFKRkZGcq+ffsK3eLGzfnbt99+q1itViUzM1O5ePGi8uOPPypt27aVHpfRttDQUKUkixcvzvvMjBkzlEuXLinp6enKli1blPbt20uPW+9bWe3u5+enREREKImJiUpmZqZy7tw5ZfHixcq9994rPW49b6UZO3Zsoc/xendvuzvzejfd2SEiIiIyDNbgEBERkeEwwSEiIiLDYYJDREREhsMEh4iIiAyHCQ4REREZDhMcIiIiMhwmOERERGQ4THCIiIjIcJjgEBERkeEwwSEiIiLDYYJDREREhsMEh4iIiAzn/wFblS9tonNynwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_hours = 24  # hours per day\n",
    "n_days = 1  # days to model\n",
    "N = n_hours*n_days  # total number of time steps\n",
    "phase_shift = 0  # horizontal shift [radians]\n",
    "base_shift = 2  # vertical shift [units of demand]\n",
    "hours = np.linspace(0,N,N)\n",
    "total_demand = 328.16  # [MWh], sets the total demand [units of energy]\n",
    "\n",
    "demand = (np.sin((hours*np.pi/n_hours*2+phase_shift))*-1+np.ones(N)*(base_shift+1))\n",
    "\n",
    "np.random.seed(1234) # sets the seed for repeatability\n",
    "\n",
    "noise = np.random.random(N)\n",
    "demand += noise\n",
    "\n",
    "demand = demand/demand.sum() * total_demand  # rescale\n",
    "\n",
    "with plt.style.context(\"dark_background\"):\n",
    "    plt.plot(hours, demand, color='cyan')\n",
    "    plt.ylabel('Demand [MW]')\n",
    "    plt.grid(alpha=0.2)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "809fc0d1-3fd1-4408-a348-981e21a68bc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating wind profile\n",
    "np.random.seed(123)\n",
    "shape_factor = 2.5\n",
    "wind_speed = np.random.weibull(a=shape_factor,size=N)\n",
    "\n",
    "with plt.style.context('dark_background'):\n",
    "    plt.plot(wind_speed, color='lime')\n",
    "    plt.grid(alpha=0.2)\n",
    "    plt.ylabel('Demand [MW]')\n",
    "    plt.xlabel('Time [hr]')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "50fc9854-16ae-4eae-9dea-8d01441c1ed8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[NaturalGas_Conv: 8375.1331 MW,\n",
       " Coal_Conv: 0.0 MW,\n",
       " SolarPanel: 2810.3015 MW,\n",
       " WindTurbine: 0.0 MW,\n",
       " Nuclear: 18609.404000000002 MW]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating energy mix\n",
    "\n",
    "#based off osier documentation, we need to include geothermal and add the capacity for coal\n",
    "#adding capacity of coal, based on research\n",
    "from osier.tech_library import coal\n",
    "\n",
    "#finally, create the necessary energy mix\n",
    "UIUC_mix = [lib.natural_gas,lib.coal,lib.solar,lib.wind,lib.nuclear]\n",
    "display(UIUC_mix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fa23f27c-9b89-449d-8d02-8529d6c6eea8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "url = \"https://raw.githubusercontent.com/samgdotson/2021-dotson-ms/refs/heads/master/data/solarfarm_data.csv\"\n",
    "solar_power = pd.read_csv(url, usecols=['time', 'kw'], parse_dates=True, index_col='time')\n",
    "\n",
    "# choose a single day\n",
    "solar_day = solar_power.loc['2016-07-01']\n",
    "solar_day.plot();plt.show()\n",
    "solar_day_ener = [0,0,0,0,0,22.15,\n",
    "                  223.25,1052.75,2368.25,3433,3406.75,4161.75,\n",
    "                  3634.5,4030.25,3545,3090,3165.75,1637.75,\n",
    "                  940,273.25,18.0475,0,0,0]\n",
    "df_solar = pd.DataFrame(solar_day_ener, columns=['Energy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "88f61c7d-3bfe-4d80-a920-96c6c95989bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   0.    ,    0.    ,    0.    ,    0.    ,    0.    ,   22.15  ,\n",
       "        223.25  , 1052.75  , 2368.25  , 3433.    , 3406.75  , 4161.75  ,\n",
       "       3634.5   , 4030.25  , 3545.    , 3090.    , 3165.75  , 1637.75  ,\n",
       "        940.    ,  273.25  ,   18.0475,    0.    ,    0.    ,    0.    ])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solar_ener = df_solar['Energy'].values\n",
    "solar_ener"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "180060f8-964c-4bea-84ba-f8c3ea63b9ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "#now wanting to do a multi-objective run\n",
    "#considered total cost, lets consider limitng CO2 emissions\n",
    "from osier import annual_emission, total_cost\n",
    "problem2 = CapacityExpansion(technology_list = UIUC_mix,\n",
    "                            demand=demand*MW,\n",
    "                            solar=solar_ener,\n",
    "                            wind=wind_speed,\n",
    "                            upper_bound= 1 / lib.solar.capacity_credit,\n",
    "                            objectives = [total_cost,annual_emission],\n",
    "                            solver=solver)  # the objectives must be passed as a LIST of functions!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "44551574-11e9-41a0-9188-81ee9f6f11e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================\n",
      "n_gen  |  n_eval  | n_nds  |      eps      |   indicator  \n",
      "==========================================================\n",
      "     1 |       20 |      6 |             - |             -\n",
      "     2 |       40 |      3 |  0.2072994298 |         ideal\n",
      "     3 |       60 |      7 |  0.0373228047 |         ideal\n",
      "     4 |       80 |      5 |  0.9621096636 |         ideal\n",
      "     5 |      100 |      2 |  0.1080890263 |         ideal\n",
      "     6 |      120 |      5 |  0.2959389723 |         ideal\n",
      "     7 |      140 |     10 |  0.3513756637 |         ideal\n",
      "     8 |      160 |      6 |  0.0147456038 |         ideal\n",
      "     9 |      180 |      6 |  0.1190098124 |         ideal\n",
      "    10 |      200 |      7 |  0.4531006077 |         ideal\n",
      "    11 |      220 |     10 |  0.0650943336 |         ideal\n",
      "    12 |      240 |     12 |  0.2811896803 |         ideal\n",
      "    13 |      260 |     14 |  0.0612671653 |         ideal\n",
      "    14 |      280 |     20 |  0.0056690956 |         ideal\n",
      "    15 |      300 |     20 |  0.0072863900 |         ideal\n",
      "    16 |      320 |     19 |  0.0434979855 |         ideal\n",
      "    17 |      340 |     20 |  0.0181471380 |             f\n",
      "    18 |      360 |     18 |  0.0283622600 |             f\n",
      "    19 |      380 |     11 |  0.4566826028 |         nadir\n",
      "    20 |      400 |     14 |  0.0865638000 |         ideal\n",
      "    21 |      420 |     16 |  0.2308807230 |         nadir\n",
      "    22 |      440 |     15 |  0.2958615539 |         nadir\n",
      "    23 |      460 |     18 |  0.1789404228 |         ideal\n",
      "    24 |      480 |     20 |  0.0122453398 |         ideal\n",
      "    25 |      500 |     20 |  0.0159465861 |         ideal\n",
      "    26 |      520 |     20 |  0.0139664268 |             f\n",
      "    27 |      540 |     20 |  0.0087244820 |             f\n",
      "    28 |      560 |     19 |  0.0109641706 |         ideal\n",
      "    29 |      580 |     20 |  0.0473264580 |         ideal\n",
      "    30 |      600 |     20 |  0.0108672244 |             f\n",
      "    31 |      620 |     20 |  0.0106433783 |             f\n",
      "    32 |      640 |     20 |  0.0052577870 |         ideal\n",
      "    33 |      660 |     20 |  0.0056823424 |             f\n",
      "    34 |      680 |     20 |  0.1712157653 |         nadir\n",
      "    35 |      700 |     20 |  0.000000E+00 |             f\n",
      "    36 |      720 |     20 |  0.0065215230 |             f\n",
      "    37 |      740 |     20 |  0.0445109930 |         nadir\n",
      "    38 |      760 |     20 |  0.0024426213 |             f\n",
      "    39 |      780 |     20 |  0.0314436971 |         nadir\n",
      "    40 |      800 |     20 |  0.0059703030 |             f\n",
      "    41 |      820 |     20 |  0.0053661124 |             f\n",
      "    42 |      840 |     20 |  0.0289710939 |         nadir\n",
      "    43 |      860 |     20 |  0.0074268430 |             f\n",
      "    44 |      880 |     20 |  0.0042456759 |             f\n",
      "    45 |      900 |     20 |  0.0048219272 |             f\n",
      "    46 |      920 |     20 |  0.0122654121 |             f\n",
      "    47 |      940 |     20 |  0.0057280625 |         ideal\n",
      "    48 |      960 |     20 |  0.0004406764 |             f\n",
      "    49 |      980 |     20 |  0.0010716783 |             f\n",
      "    50 |     1000 |     20 |  0.0112672254 |             f\n",
      "    51 |     1020 |     20 |  0.0094111052 |             f\n",
      "    52 |     1040 |     20 |  0.0026452646 |             f\n",
      "    53 |     1060 |     20 |  0.0073433724 |         ideal\n",
      "    54 |     1080 |     20 |  0.0076510593 |             f\n",
      "    55 |     1100 |     20 |  0.0055847188 |             f\n",
      "    56 |     1120 |     20 |  0.0100709709 |         ideal\n",
      "    57 |     1140 |     20 |  0.0087696474 |             f\n",
      "    58 |     1160 |     20 |  0.0009116337 |             f\n",
      "    59 |     1180 |     20 |  0.0053128038 |             f\n",
      "    60 |     1200 |     20 |  0.0050772998 |             f\n",
      "    61 |     1220 |     20 |  0.0072307856 |             f\n",
      "    62 |     1240 |     20 |  0.0000160068 |             f\n",
      "    63 |     1260 |     20 |  0.0021571039 |             f\n",
      "    64 |     1280 |     20 |  0.0056918235 |             f\n",
      "    65 |     1300 |     20 |  0.0018961651 |             f\n",
      "    66 |     1320 |     20 |  0.0051599612 |             f\n",
      "    67 |     1340 |     20 |  0.0048582530 |             f\n",
      "    68 |     1360 |     20 |  0.0378948073 |         ideal\n",
      "    69 |     1380 |     20 |  0.0047158858 |             f\n",
      "    70 |     1400 |     20 |  0.0065254624 |             f\n",
      "    71 |     1420 |     20 |  0.0056077870 |             f\n",
      "    72 |     1440 |     20 |  0.0037542233 |             f\n",
      "    73 |     1460 |     20 |  0.0068466604 |             f\n",
      "    74 |     1480 |     20 |  0.0041265666 |             f\n",
      "    75 |     1500 |     20 |  0.0090796417 |         nadir\n",
      "    76 |     1520 |     20 |  0.0033882979 |             f\n",
      "    77 |     1540 |     20 |  0.0022129907 |             f\n",
      "    78 |     1560 |     20 |  0.0030698229 |             f\n",
      "    79 |     1580 |     20 |  0.0065369826 |             f\n",
      "    80 |     1600 |     20 |  0.0059792257 |         ideal\n",
      "    81 |     1620 |     20 |  0.1145827904 |         nadir\n",
      "    82 |     1640 |     20 |  0.0046154356 |             f\n",
      "    83 |     1660 |     20 |  0.0323290215 |         nadir\n",
      "    84 |     1680 |     20 |  0.0018973848 |             f\n",
      "    85 |     1700 |     20 |  0.0037324294 |             f\n",
      "    86 |     1720 |     20 |  0.0089603388 |         ideal\n",
      "    87 |     1740 |     20 |  0.000000E+00 |             f\n",
      "    88 |     1760 |     20 |  0.0014884776 |             f\n",
      "    89 |     1780 |     20 |  0.0083532385 |         ideal\n",
      "    90 |     1800 |     20 |  0.0036700551 |         nadir\n",
      "    91 |     1820 |     20 |  0.0053168627 |             f\n",
      "    92 |     1840 |     20 |  0.0092871223 |             f\n",
      "    93 |     1860 |     20 |  0.0171576698 |         nadir\n",
      "    94 |     1880 |     20 |  0.0060624583 |         nadir\n",
      "    95 |     1900 |     20 |  0.0016916332 |             f\n",
      "    96 |     1920 |     20 |  0.0024384275 |             f\n",
      "    97 |     1940 |     20 |  0.0235954705 |         ideal\n",
      "    98 |     1960 |     20 |  0.0048543641 |             f\n",
      "    99 |     1980 |     20 |  0.0561680916 |         nadir\n",
      "   100 |     2000 |     20 |  0.0042779961 |             f\n",
      "   101 |     2020 |     20 |  0.0003851787 |             f\n",
      "   102 |     2040 |     20 |  0.0027167147 |         nadir\n",
      "   103 |     2060 |     20 |  0.0073256537 |             f\n",
      "   104 |     2080 |     20 |  0.0019511152 |             f\n",
      "   105 |     2100 |     20 |  0.1923751490 |         nadir\n",
      "   106 |     2120 |     20 |  0.0051405665 |             f\n",
      "   107 |     2140 |     20 |  0.0001146118 |             f\n",
      "   108 |     2160 |     20 |  0.2422485424 |         nadir\n",
      "   109 |     2180 |     20 |  0.0028797354 |             f\n",
      "   110 |     2200 |     20 |  0.0030753977 |             f\n",
      "   111 |     2220 |     20 |  0.0047599913 |             f\n",
      "   112 |     2240 |     20 |  0.0066109434 |             f\n",
      "   113 |     2260 |     20 |  0.0030443275 |             f\n",
      "   114 |     2280 |     20 |  0.0037447484 |             f\n",
      "   115 |     2300 |     20 |  0.0025135633 |             f\n",
      "   116 |     2320 |     20 |  0.0017087505 |             f\n",
      "   117 |     2340 |     20 |  0.0033275310 |         nadir\n",
      "   118 |     2360 |     20 |  0.0064650470 |             f\n",
      "   119 |     2380 |     20 |  0.0027926912 |         nadir\n",
      "   120 |     2400 |     20 |  0.0023230432 |             f\n",
      "   121 |     2420 |     20 |  0.0072834583 |             f\n",
      "   122 |     2440 |     20 |  0.0065076232 |             f\n",
      "   123 |     2460 |     20 |  0.0033613863 |         nadir\n",
      "   124 |     2480 |     20 |  0.0026775103 |         nadir\n",
      "   125 |     2500 |     20 |  0.0003568383 |             f\n",
      "   126 |     2520 |     20 |  0.0005599425 |             f\n",
      "   127 |     2540 |     20 |  0.0008581828 |             f\n",
      "   128 |     2560 |     20 |  0.0078328258 |             f\n",
      "   129 |     2580 |     20 |  0.0062128005 |             f\n",
      "   130 |     2600 |     20 |  0.0043519133 |             f\n",
      "The simulation took 71.358 minutes.\n"
     ]
    }
   ],
   "source": [
    "algorithm = NSGA2(pop_size=20)\n",
    "termination = RobustTermination(MultiObjectiveSpaceTermination(tol=0.05, n_skip=5), period=20)\n",
    "import time\n",
    "start = time.perf_counter()\n",
    "res = minimize(problem2,\n",
    "               algorithm,\n",
    "               termination,\n",
    "               seed=1,\n",
    "               save_history=True,\n",
    "               verbose=True)\n",
    "end = time.perf_counter()\n",
    "print(f\"The simulation took {(end-start)/60:.3f} minutes.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "58516b02-c523-4bf5-b267-517a90fb8a37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[9.48449077e-01, 1.60620729e-04],\n",
       "       [3.55584917e+00, 3.83297976e-06],\n",
       "       [1.44490527e+00, 1.01076249e-04],\n",
       "       [1.27544699e+00, 1.24417899e-04],\n",
       "       [2.06009028e+00, 4.74256108e-05],\n",
       "       [2.18861471e+00, 3.37672692e-05],\n",
       "       [3.23349368e+00, 8.55442758e-06],\n",
       "       [1.89837774e+00, 5.87994415e-05],\n",
       "       [1.78530102e+00, 7.49910312e-05],\n",
       "       [2.37705387e+00, 2.61982869e-05],\n",
       "       [2.51665969e+00, 2.22008932e-05],\n",
       "       [2.73346076e+00, 1.76653348e-05],\n",
       "       [3.00920322e+00, 1.05168538e-05],\n",
       "       [1.60414946e+00, 8.65962590e-05],\n",
       "       [9.99934751e-01, 1.55758009e-04],\n",
       "       [3.49679536e+00, 5.47930797e-06],\n",
       "       [2.83742628e+00, 1.23567585e-05],\n",
       "       [1.81376635e+00, 6.64734081e-05],\n",
       "       [1.14572595e+00, 1.47845770e-04],\n",
       "       [1.61444092e+00, 8.58952274e-05]])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[9.87663602e-01, 7.73087388e-03, 1.56268487e-03, 1.63679915e-02,\n",
       "        8.51635344e-05],\n",
       "       [1.22717602e-03, 6.84157774e-04, 6.98229415e-03, 7.85427724e-01,\n",
       "        7.17849131e-01],\n",
       "       [9.33063859e-01, 1.33989099e-03, 8.63512887e-01, 1.78297079e-02,\n",
       "        7.95461754e-05],\n",
       "       [9.87663602e-01, 4.66935414e-03, 4.88650421e-01, 1.87984599e-02,\n",
       "        4.63799704e-03],\n",
       "       [5.72631758e-01, 1.47499857e-03, 3.31395143e-01, 6.96988892e-01,\n",
       "        8.54644041e-02],\n",
       "       [4.41405349e-01, 1.34276211e-03, 3.35641818e-01, 9.20107164e-01,\n",
       "        6.01118338e-02],\n",
       "       [7.08814227e-02, 1.33989099e-03, 4.80094816e-01, 1.49077474e+00,\n",
       "        1.94307334e-01],\n",
       "       [5.92790075e-01, 1.23679750e-03, 2.88114849e-01, 7.06702639e-01,\n",
       "        3.52422391e-02],\n",
       "       [7.35524882e-01, 1.47915036e-04, 2.84697145e-01, 4.91792461e-01,\n",
       "        5.87565091e-02],\n",
       "       [4.03025705e-01, 1.33795823e-03, 5.93774558e-01, 1.06655303e+00,\n",
       "        1.19572392e-02],\n",
       "       [4.03025705e-01, 3.57118709e-04, 5.88894061e-01, 1.18287951e+00,\n",
       "        3.48500392e-03],\n",
       "       [4.03025705e-01, 5.33144399e-03, 5.88894061e-01, 1.19400637e+00,\n",
       "        6.16280442e-02],\n",
       "       [2.45773466e-01, 6.87135469e-04, 4.69786385e-01, 9.20107164e-01,\n",
       "        3.35675013e-01],\n",
       "       [7.40534248e-01, 1.47915036e-04, 2.84697145e-01, 4.84832121e-01,\n",
       "        5.78053398e-03],\n",
       "       [9.87663602e-01, 4.64520872e-03, 7.83339060e-03, 4.13840604e-02,\n",
       "        4.63799704e-03],\n",
       "       [6.53562023e-03, 1.34276211e-03, 3.35641818e-01, 7.87185078e-01,\n",
       "        6.33659294e-01],\n",
       "       [2.45773466e-01, 1.34276211e-03, 2.01946935e-01, 9.20107164e-01,\n",
       "        3.35675013e-01],\n",
       "       [7.35524882e-01, 2.38814712e-04, 6.28448005e-01, 4.91792461e-01,\n",
       "        5.84767825e-04],\n",
       "       [9.87663602e-01, 7.71382021e-03, 4.42133101e-04, 1.63679915e-02,\n",
       "        5.98855724e-02],\n",
       "       [7.40534248e-01, 1.47915036e-04, 2.84697145e-01, 4.91792461e-01,\n",
       "        5.78053398e-03]])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(None, None)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#displaying multi-objective results\n",
    "display(res.F),display(res.X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "91394ffe-3b06-4b65-9471-743dbf2ddda6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SnjFjhqjVaklKSpKQkBDJysqSmpoaCQoKEgCSnp4uGzZsMMUPGDBAamtrJTMzU0JCQiQpKUnUarUkJCSYYiIiIkSr1UpaWpoEBwdLWlqaaDQaGT9+vM3jApBevXpJWFiY3HfffSIiMmPGDAkLC5M+ffo0+/VwtVfnacwh8+gpjTlkDj2hefpqL9i7Y41GI6dPn5bXXntN4uPj5Re/+IVLJ56amiplZWXS0NAgKpVKIiMjTdtycnIkPz/fLD4qKkqKioqkoaFBSktLJSUlxWKfiYmJcuzYMVGr1VJSUiLx8fF2jQtAZs+eLdYsX7682a+FxU/nacwh8+gpjTlkDj2hdbji55ZbbpF7771XVq5cKQcPHpSGhgY5cuSI/O1vf5PExETx9/d3e9Lbc2Px0z4bc8g8ekpjDplDT2ieXvzYfc7P1atXsXv3buzevRsA0K1bN0yaNAn33HMP0tLSsGnTJvz4448YOXKkvbsmIiIianVOL8Cvq6vDhQsXcOHCBVy8eBE6nQ533nmnK+ZGRERE5HJ2H/nx8vLCuHHjcPfdd+Oee+7BxIkT4efnh/LycuTn5+Pxxx9Hfn5+a8yViIiIyGl2Fz+XLl2Cn58fKisrsXfvXjz99NPIz89HaWlpa8yPiIiIyKXsLn7+/Oc/Iz8/Hz/++GNrzIeIiIioVdld/Lz55putMQ8iIiKiNmF38fPOO+/YFJecnGz3ZIiIiIham93Fz5w5c3D69GkcOnTIdBNRIiIiovbC7uLnjTfewMyZMzFo0CC8++67+OCDD3Dx4sXWmBsRERGRy9l9nZ/HH38cgYGBeOmllzB16lT89NNP2LZtG2JjY1tjfkREREQu5dBFDjUaDbZu3YrY2FgMGzYMxcXFWLt2LU6fPg0/Pz9Xz5GIiIjIZZy+wrOIQETg5eUFhcLp3RERERG1KoeqFV9fX8ycORN5eXn4/vvvMXLkSDzxxBMICgpCXV2dq+dIRERE5DJ2n/C8Zs0azJw5E2fOnEFOTg5mzpyJCxcutMbciIiIiFzO7uJn3rx5OHPmDMrKyhAdHY3o6GircYmJiU5PjoiIiMjV7C5+3n//fYhIa8yFiIiIqNXZXfwkJSW1xjyIbKYAEAkgEEAlgP0AGt06IyIiak/sPuH5xRdfxF133dUacyG6oXgAJwDsBbDF8HjC0E9ERGQLu4ufwMBAfPrpp6ioqMD69evxf//3f/D19W2NuRGZiQfwIYDvAIQD6GZ4/M7QzwKIiIhsYXfxM3fuXPTp0wczZszApUuXkJmZiXPnzuGjjz7C7Nmz8Ytf/KI15kmdnAJAJoBPAcQB+BpAneExztC/Ci64cBUREXV4Dv+t+Oqrr7Bo0SLceeedGD9+PA4ePIhHH30U5eXl2LdvHxYsWIC+ffu6cq7UiUUCGAggHUDT0+0FwEoAgwxxRERELbH7hGdrjh8/juPHj+OVV16Bv78/HnjgATzwwAMAgMzMTFcMQZ1coOHxaDPbjzaJIyIiao7dR37eeecddOvWrdnt586dw7vvvou4uDgWPuQylYbHEc1sH9EkjoiIqDl2Fz+zZ8/GzTff3BpzIWrWfgBlAJYC8GqyzQvAEgClhjgiIqKW2F38eHk1/dND1PoaASwAcD+AHTBf7bXD0L8QvN4PERHdmEMnPLfmFZ5TU1NRWlqK+vp6qFQqTJo0qcX4qKgoqFQq1NfX4+TJk0hJSbGISUhIQHFxMRoaGlBcXIy4uDi7x42Pj8fnn3+Os2fPQkQQFhZmtr1Xr15YvXo1jh8/jrq6Opw+fRqvvfYaunfvbn8SyKrtAKYDGAmgEECN4XGEoX+7+6ZGRETtiEPFzw8//IDz58+32BwxY8YMvPrqq3jxxRcxevRo7N+/H7t27UK/fv2sxg8YMAC5ubnYv38/Ro8ejfT0dKxevRoJCQmmmPDwcGzbtg0bN25EWFgYNm7ciL///e8YP368XeP6+fnhwIEDWLx4sdW59O3bF3379sXChQsxcuRIzJkzB7/5zW/wzjvvOJQLsm47gCEA7gbwkOHxl2DhQ0RE9hF72rVr1+SPf/yjPPLIIy02e/cLQA4ePChr16416yspKZH09HSr8RkZGVJSUmLWt27dOikoKDA937p1q+Tm5prF7Nq1SzZv3uzQuP379xcRkbCwsBt+PdOnT5eGhga56aabbM6BUqkUERGlUulQDh1pCoVCxowZIwqFos3G7GiNOWQePaUxh8yhJzR35dDWv6EOLXXfunUrzp4968hLm+Xj44OxY8ciIyPDrD8vLw8TJkyw+pqIiAjk5eWZ9e3evRvJycnw9vaGTqdDREQEsrOzLWLmz5/v8Li26tGjB65cuYJr1641G+Pr64suXbqYniuVSgCAQqGAQtE2l+wzjtVW43VEzKFrMI/OYw6dxxw6z105tHU8u4uf1jrfx9/fH97e3qiurjbrr66uRkBAgNXXBAQEWI338fGBv78/qqqqmo0x7tORcW1x66234tlnn8X69etbjFuyZAlWrFhh0R8aGoq6ujqHx7eHQqHA0KFDAQCNjTxl2BHMoWswj85jDp3HHDrPXTn08/OzKc7u4qe1V3s1La68vLxaLLisxTftt2Wf9o7bEqVSic8++wwlJSX4y1/+0mLsypUrkZWVZfba8vJyHDlyBDU1NQ6Nby9jpXz48GH+oDuIOXQN5tF5zKHzmEPnuSuHxk9PbsTu4uemm26yezK2OHfuHHQ6ncXRlt69e1sclTEyHtlpGq/Vak0nXTcXY9ynI+O2pFu3bvj8889RW1uL+Ph46HS6FuM1Gg00Go1Ff2NjY5u+YYzj8QfdccyhazCPzmMOncccOs8dObR1LLuLH1tXLyUnJ9u1X61Wi6KiIsTExGDHjh2m/piYGOzcudPqawoLCzF16lSzvtjYWKhUKlPRUVhYiJiYGLz66qtmMQUFBQ6P2xylUondu3dDrVbjgQcegFqttuv1RERE1PrsLn7mzJmD06dP49ChQy7/CCwrKwsbN26ESqVCYWEhHnvsMQQFBeGNN94AAKSnp+P222/H7NmzAQBvvPEGnnjiCWRmZuKtt95CREQEkpOT8dBDD5n2+dprr+HLL79EWloadu7ciWnTpuHXv/612XV8bjQuoL+OT1BQkOlmrcHBwQD0R5aqq6vRrVs35OXl4ZZbbsGsWbPQvXt30zV+zp49y/89EBEReRC7lpGtWbNGzp8/L4cOHZI//vGP0qtXL5cuU0tNTZWysjJpaGgQlUolkZGRpm05OTmSn59vFh8VFSVFRUXS0NAgpaWlkpKSYrHPxMREOXbsmKjVaikpKZH4+Hi7xgUgs2fPFmuWL18uACQ6OtrqdhGR/v37u3yZnisbl3Uyh57SmEfm0BMac9h+c2jH31D7d+7r6yszZ86UvLw8qa2tlW3btklsbKzbk90RGouf9tmYQ+bRUxpzyBx6QvP04sehBfgajQZbt25FbGwshg0bhuLiYqxduxanT5+2eZkZERERkTs4ffUhEYGIwMvLixeEIiIiIo/nULXi6+uLmTNnIi8vD99//z1GjhyJJ554AkFBQW12YT4iIiIiR9i92mvNmjWYOXMmzpw5g5ycHMycORMXLlxojbkRERERuZzdxc+8efNw5swZlJWVITo6GtHR0VbjEhMTnZ4cERERkavZXfy8//77rXZ/LyIiIqLWZnfxk5SU1BrzICIiImoTdp3wPHLkSLuu6jxs2LBWuxcYERERkSPsKn4OHTqEX/ziFzbHFxYWIigoyO5JEREREbUWuz728vLywl//+ldcvXrVpnhfX1+HJkVERETUWuwqfr788kvTDT1tUVhYiPr6ersnRURERNRa7Cp+7rnnntaaBxEREVGb4P0oiIiIqFNh8UNERESdCosfIiIi6lRY/BAREVGnwuKHiIiIOhWHi5+uXbvi5ptvNj0PCgrCk08+iZiYGJdMjIiIiKg1OFz87Ny5E4888ggAoEePHvj666+xYMEC7Ny5E/PmzXPZBImIiIhcyeHiZ8yYMdi/fz8AYPr06aiurkb//v3xyCOP4E9/+pPLJkhERETkSg4XP7fccgtqamoAALGxsfj4448hIjh48CD69+/vsgkSERERuZLDxc+JEycQFxeHO+64A/feey/y8vIAAL1798aVK1dcNkEiIiIiV3K4+Hn++eexatUqnDp1Ct988w0OHjwIQH8U6NChQy6bIJG7KQBEA5hpeOQSSSKi9s2ue3td76OPPkJQUBACAwNx+PBhU/+ePXvw8ccfu2JuRG4XDyATwMDr+soALACw3S0zIiIiZzlc/ADA8OHDMWXKFDz++ONQKMz/P5ycnOzUxIjcLR7AhwA+BfAQgKMARgBYauifDhZARETtkcNH8J977jnk5eVhypQp8Pf3R69evcyao1JTU1FaWor6+nqoVCpMmjSpxfioqCioVCrU19fj5MmTSElJsYhJSEhAcXExGhoaUFxcjLi4OLvHjY+Px+eff46zZ89CRBAWFmaxD19fX6xevRpnz55FbW0tdu7cidtvv92+BJBHUEB/xOdTAHEAvgZQZ3iMM/SvAj8CIyJqr8SRVlFRIbNmzXLotc21GTNmiFqtluTkZAkJCZHs7GypqamRfv36WY0fMGCA1NbWSnZ2toSEhEhycrKo1WpJSEgwxYSHh4tWq5XFixdLcHCwLF68WDQajYwfP96ucWfNmiXPPvusJCcni4hIWFiYxXzWrl0rP/30k0yZMkVGjRole/bskUOHDolCobA5B0qlUkRElEqlS3PbUlMoFDJmzBi75tnRWzQgAsivmtkebtgezRy6tDGPzKEnNOaw/ebQjr+hjg1w7tw5GTRokEsnffDgQVm7dq1ZX0lJiaSnp1uNz8jIkJKSErO+devWSUFBgen51q1bJTc31yxm165dsnnzZofG7d+/v9Xip3v37qJWq2XGjBmmvsDAQNHpdBIbG9sa3ziXNf6gW7aZ0Bc3fs1s72bYPpM5dGljHplDT2jMYfvNoa1/Qx0+5+ftt9/Gww8/jBdeeMHRXZjx8fHB2LFjkZGRYdafl5eHCRMmWH1NRESEaYm90e7du5GcnAxvb2/odDpEREQgOzvbImb+/PkOj2vN2LFj4evrazafyspKHD16FBMmTLCYp5Gvry+6dOlieq5UKgEACoXC4jyq1mIcq63Gaw+qDY+h0H/U1VTodXEKMIeuwjw6jzl0HnPoPHfl0NbxHC5+unbtisceewy//vWvceTIEWi1WrPtCxYssGt//v7+8Pb2RnV1tVl/dXU1AgICrL4mICDAaryPjw/8/f1RVVXVbIxxn46M29xc1Go1Ll26ZNd+lixZghUrVlj0h4aGoq6uzubxnaFQKDB06FAAQGNjY5uM6elqAJQDWAn9yi65bpsXgHQA/zXEjQJz6CrMo/OYQ+cxh85zVw79/PxsinO4+AkNDTUtcR8xYoTZNhGx8grbNH2tl5dXi/uzFt+035Z92juurW60n5UrVyIrK8v0XKlUory8HEeOHDFdQbu1GSvlw4cP8wf9Ok8C+DuA5wC8hP+t9loEIBLADAD/nyGWOXQN5tF5zKHzmEPnuSuHxk9PbsTh4mfy5MmOvtSqc+fOQafTWRwl6d27t8VRGSPjkZ2m8VqtFufPn28xxrhPR8Ztbi5dunRBz549zY7+9O7dGwUFBc2+TqPRQKPRWPQ3Nja26RvGOB5/0P/nI+iXs2cCOHBdfymsL3NnDl2DeXQec+g85tB57sihrWN5zAeaWq0WRUVFiImJMeuPiYlptngoLCy0iI+NjYVKpYJOp2sxxrhPR8a1pqioCBqNxmw/AQEBGDFihF37Ic+yHcAQAHdDf62fuwH8Ery+DxFRe+fwWdU9evSQp59+Wt566y1588035amnnpLu3bs7vD/jkvOkpCQJCQmRrKwsqampkaCgIAEg6enpsmHDBlO8cal7ZmamhISESFJSksVS94iICNFqtZKWlibBwcGSlpbW7FL35sYFIL169ZKwsDC57777RERkxowZEhYWJn369DHFrF27Vs6cOSOTJ0+WUaNGyb///W8ude8kjTlkHj2lMYfMoSc0T1/tBUcHGDt2rJw7d05++ukn+eijj+Tjjz+WM2fOyNmzZ2X06NEOTzw1NVXKysqkoaFBVCqVREZGmrbl5ORIfn6+WXxUVJQUFRVJQ0ODlJaWSkpKisU+ExMT5dixY6JWq6WkpETi4+PtGheAzJ49W6xZvny5KaZLly6yevVqOXfunNTV1cknn3wid9xxR2t949r9m7QjNeaQefSUxhwyh57QOmzx8+WXX8q7774rN910k6nvpptukpycHNm3b5/bE99eG4uf9tmYQ+bRUxpzyBx6QvP04sfhE57HjRuHRx99FNeuXTP1Xbt2DS+//DJUKpWjuyUiIiJqVQ6f8HzlyhUEBQVZ9Pfr16/NlmgTERER2cvh4mfbtm145513MGPGDNxxxx24/fbb8eCDD+Ltt9/Gli1bXDlHIiIiIpdx+GOvhQsXQkTw/vvvw9tbvxutVot169Zh8eLFLpsgERERkSs5XPxotVrMnz8fS5YsweDBg+Hl5YUTJ06gvr7elfMjIiIicimHix+j+vp6HD161BVzISIiImp1dhU/mZmZePbZZ3H16lVkZma2GGvvjU2JiIiI2oJdxc/o0aPh4+Nj+ndzXHFDUCIiIqLWYFfxc/3NTF19Y1MiIiKituDwUveuXbvi5ptvNj0PCgrCk08+aXGDUCIiIiJP4nDxs3PnTjzyyCMAgB49euCbb77BggULsHPnTsybN89lEyQiIiJyJYeLnzFjxmD//v0AgOnTp6Oqqgr9+/fHI488gj/96U8umyARERGRKzm81P2WW24x3cYiNjYWH3/8MUQEBw8eRP/+/V02QaLOQAEgEkAggEoA+wE0unVGREQdl8NHfk6cOIG4uDjccccduPfee5GXlwcA6N27N65cueKyCRJ1dPEATgDYC2CL4bESwDI48QNKRETNcvh36/PPP49Vq1bh1KlT+Prrr3Hw4EEA+qNAhw4dctkEiTqyeAAfAvgOwGIApwz9vQH8FUC5IYaIiFzH4Y+9PvroIwQFBSEwMBDffvutqX/Pnj3Yvn27SyZH1JEpAGQC+BTABgD/MPx7JoCjAEYAeAb64mg6AP5UERG5hsPFT9euXXHlyhVUV1cD0C91j4+Px7Fjx/Cf//zHZRMk6qgiAQwE8DsAm6AvfOIAGC8R+jWAaQB2AFgFYCd4HhARkSu4bKn7119/jQULFmDHjh1c6k5kg0DDYw/oi6B0/K/wMRIAKwEMgr5YIiIi57lsqXt1dTWXuhPZodLwOM7w2NztgY39gc1sJyIi+zhc/HCpO5Fz9gMoA/Abw/MRzcQZ+yub2U5ERPbhUnciN2kEsABABIAaAEsBeDWJ8QKwBEAp9MUSERE5j0vdidxoO/Qrua4CmAr9Sc3hALoZHncAuB/AQvBkZyIiV+FSdyI32w590bMUwBMACq/bVgoucycicjWHix8AqK6uNi11N+IydyL7NQJ4AfoVX7zNBRFR67LrY6/MzEzccsstpn+31ByVmpqK0tJS1NfXQ6VSYdKkSS3GR0VFQaVSob6+HidPnkRKSopFTEJCAoqLi9HQ0IDi4mLExcU5NO7y5ctRXl6Oq1evIj8/H8OGDTPb3qdPH7z//vuorKxEbW0tioqKkJiYaF8CqFNrBLAPwFbDIwsfIqLWIba2L774Qnr06GH6d3Ntz549Nu/z+jZjxgxRq9WSnJwsISEhkp2dLTU1NdKvXz+r8QMGDJDa2lrJzs6WkJAQSU5OFrVaLQkJCaaY8PBw0Wq1snjxYgkODpbFixeLRqOR8ePH2zVuWlqaXL58WeLj42X48OGyZcsWKS8vl27dupli8vLy5Ouvv5a77rpLBg4cKM8884zodDoZNWqUzTlQKpUiIqJUKh3KoSNNoVDImDFjRKFQtNmYHa0xh8yjpzTmkDn0hOauHNrxN9T9STK2gwcPytq1a836SkpKJD093Wp8RkaGlJSUmPWtW7dOCgoKTM+3bt0qubm5ZjG7du2SzZs32zVuRUWFpKWlmZ77+vrKxYsX5bHHHjP11dTUyKxZs8z2c+7cOZk7d25rfONc1viDzhx6SmMemUNPaMxh+82hrX9DPeam0T4+Phg7dqxpybxRXl4eJkyYYPU1ERERFvG7d+/GuHHj4O3t3WKMcZ+2jDtw4EAEBgaaxWg0Guzbt89sbl999RUefPBB9OrVC15eXnjwwQfRpUsX7N27145MEBERUWty6oTnLl26IDQ0FL1794ZCYV5H/fOf/7RrX/7+/vD29rY4gbq6uhoBAQFWXxMQEGA13sfHB/7+/qiqqmo2xrhPW8Y1PlqLuf6Cjg8++CC2bduGCxcuQKvV4urVq4iPj0dpaWmzX7evry+6dOlieq5UKgEACoXCIqetxThWW43XETGHrsE8Oo85dB5z6Dx35dDW8Rwufu699168//778Pf3t9gmIqYjL/YSEbPnXl5eFn03im/ab8s+XRHzwgsvoFevXpgyZQrOnTuHuLg4/OMf/0BkZCSOHrV+84IlS5ZgxYoVFv2hoaGoq6uz+hpXUygUGDp0KACgsZGn2DqCOXQN5tF5zKHzmEPnuSuHfn5+NsU5XPy8/vrr+Mc//oHnn38eP//8s6O7MTl37hx0Op3FUZ7evXtbHHExMh7ZaRqv1Wpx/vz5FmOM+7Rl3KqqKgD6I0DGfzeNGTRoEP74xz9i+PDhKCkpAQAcOXIEkZGRePzxx5Gammr1a1i5ciWysrJMz5VKJcrLy3HkyBHT7UNam7FSPnz4MH/QHcQcugbz6Dzm0HnMofPclUPjpyc34nDx07t3b2RlZbmk8AEArVaLoqIixMTEYMeOHab+mJgY7Ny50+prCgsLMXXqVLO+2NhYqFQq6HQ6U0xMTAxeffVVs5iCggKbxy0rK0NlZSViYmJw+PBhAPpzhaKjo7Fo0SIAMF0CoOk3+dq1ay0ehtNoNNBoNBb9jY2NbfqGMY7HH3THMYeuwTw6jzl0HnPoPHfk0J6xHDqj+p133rFrFZMtzbjkPCkpSUJCQiQrK0tqamokKChIAEh6erps2LDBFG9c6p6ZmSkhISGSlJRksdQ9IiJCtFqtpKWlSXBwsKSlpTW71L25cQH9UveLFy9KXFycDB8+XDZt2mS21N3b21t++OEH2bdvn9x1110yaNAgefrpp+XatWty3333ufxMdVc2rmxgDj2lMY/MoSc05rD95rDVl7rffPPN8umnn0pOTo48/fTT8sc//tGsObrf1NRUKSsrk4aGBlGpVBIZGWnalpOTI/n5+WbxUVFRUlRUJA0NDVJaWiopKSkW+0xMTJRjx46JWq2WkpISiY+Pt2tcY1u+fLlUVFRIfX297N27V4YPH262fciQIfLhhx9KVVWV1NbWyuHDhy2WvrvwG9fu36QdqbXXHCoAiQZkpuFR4e75tNM8elJjDplDT2gdtvhJTk4WrVYrV65ckbKyMiktLTW1kydPuj3x7bWx+GmfrT3mMB6QUkDkulZq6Gce229jDplDT2ieXvw4vAbthRdewHPPPYcePXpg4MCBGDRokKkNHjzY0d0SURuIB/AhgO9gfhf57wz98e6bGhFRq3O4+PH19cW2bdtaXIZORJ5HASATwKcA4gB8DaDO8Bhn6F8FJ345EBF5OId/v23YsAEPPvigK+dCRG0gEsBA6O8g3/S/LgJgJYBBhjgioo7I4aXuN910E9LS0nDvvffiyJEj0Gq1ZtsXLFjg9OSIyPUCDY/WL7v5v/7AZrYTEbV3Dhc/I0eOxKFDhwAAI0aMcNmEiKh1VRoeR0D/UVdTI5rEERF1NA4XP5MnT3blPIiojewHUAZgKfTn+Fz/0ZcXgCUASg1xREQdkd3n/Hz22Wfo3r276fnSpUvRo0cP0/Nbb70VxcXFrpkdEblcI4AFAO4HsAPmq712GPoXGuKIiDoiu4ufe++91+wu5IsWLcKtt95qeu7t7Y3g4GDXzI6IWsV2ANMBjARQCKDG8DjC0L/dfVMjImp1dn/sZbxrenPPiah92A5gJ/SrugKhP8dnP3jEh4g6PofP+SGi9q8RwD53T4KIqI3Z/bGXiFhc2JAXOiQiIqL2wqGPvd577z2o1WoAQNeuXfHGG2+grq4OAMzOByIiIiLyNHYXPxs2bDB7/sEHH1jEvP/++47PiIiIiKgV2V38zJ07tzXmQUQeQAGeAE1EHR/vXUhEAPR3cj8BYC+ALYbHE+Ad3omo42HxQ0SIB/AhgO9gftHD7wz9LICIqCNh8UPUySkAZAL4FPrbXXwNoM7wGGfoXwX+siCijoO/z4g6uUgAAwGkw/w+XzA8XwlgkCGOiKgjYPFD1MkFGh6PNrP9aJM4IqL2ziXFT9euXdG3b1+L/mHDhrli90TUiioNjyOa2T6iSRwRUXvndPGTmJiIH374Abm5ufj2228xfvx407aNGzc6u3siamX7AZQBWAqg6Z36vAAsAVBqiCMi6gicLn6WLVuGMWPGYNSoUZg7dy7effddPPTQQwB401Oi9qARwAIA9wPYAfPVXjsM/QvB6/0QUcfh9I1NfXx8cO7cOQBAUVERoqKi8PHHH2PIkCG85xdRO7EdwHToV30VXtdfaujf7o5JERG1EqeP/Pz8888YOXKk6fmFCxcQExODO++8E6Ghoc7unojayHYAQwDcDeAhw+MvwcKHiDoep4/8/P73v4dOpzPr02q1ePjhh/H66687u3siakONAPa5exJERK3M6SM/DQ0N0Gq1VrcVFBTYvb/U1FSUlpaivr4eKpUKkyZNajE+KioKKpUK9fX1OHnyJFJSUixiEhISUFxcjIaGBhQXFyMuLs6hcZcvX47y8nJcvXoV+fn5VlezhYeHY8+ePaitrcXFixeRn5+Prl272p4AIiIianVib+vRo4e8/vrrcvbsWdHpdKLT6eTs2bPyt7/9TXr06GH3/oxtxowZolarJTk5WUJCQiQ7O1tqamqkX79+VuMHDBggtbW1kp2dLSEhIZKcnCxqtVoSEhJMMeHh4aLVamXx4sUSHBwsixcvFo1GI+PHj7dr3LS0NLl8+bLEx8fL8OHDZcuWLVJeXi7dunUzG+vSpUuyaNEiGTZsmAwZMkQSExPF19fX5hwolUoREVEqlQ7n0d6mUChkzJgxolAo2mzMjtaYQ+bRUxpzyBx6QnNXDu34G2rfjnv16iXHjx+XmpoaeeONN+TJJ5+U+fPny/r166WmpkZKSkqkZ8+eDk364MGDsnbtWrO+kpISSU9PtxqfkZEhJSUlZn3r1q2TgoIC0/OtW7dKbm6uWcyuXbtk8+bNdo1bUVEhaWlppue+vr5y8eJFeeyxx0x9hYWF8vzzz7fVN67dv0k7UuvsOVQAEg3ITMOjgnl03/eCOWQOPaB5evFj9zk/zz33HDQaDQYPHoyff/7ZYlteXh6ee+45PP3003bt18fHB2PHjkVGRoZZf15eHiZMmGD1NREREcjLyzPr2717N5KTk+Ht7Q2dToeIiAhkZ2dbxMyfP9/mcQcOHIjAwECzsTQaDfbt24cJEybgzTffxG233Ybw8HBs2rQJBw4cwODBg3H8+HE888wzOHDgQLNft6+vL7p06WJ6rlQqAQAKhQIKRdtcgNs4VluN1xF15hzGA3gF+ltkGJUB+DPsP1m6M+fRVZhD5zGHznNXDm0dz+7iJy4uDikpKRaFDwBUV1cjLS0Nb7zxht3Fj7+/P7y9vVFdXW2xz4CAAKuvCQgIsBrv4+MDf39/VFVVNRtj3Kct4xofrcX0798fADBo0CAAwIoVK7Bw4UIcPnwYjzzyCPbs2YMRI0bgxIkTVr+GJUuWYMWKFRb9oaGhqKurs/oaV1MoFBg6dCgAoLGRV3NxRGfN4T0AXob+AogrAJwEMBjAXAB/B5AGIN+O/XXWPLoSc+g85tB57sqhn5+fTXF2Fz+BgYEoLi5udvvRo0ebLVZs0fTaQF5eXi1eL8hafNN+W/bpbIyx2ly/fj3ee+89AMDhw4cxZcoUzJ07F0uXLrU6/5UrVyIrK8v0XKlUory8HEeOHEFNTY3V17iace6HDx/mD7qDOmMOFQA+hP6u7wnQH0sG9NcJ2gTgYwB/APAabL9AYmfMo6sxh85jDp3nrhwaPz25EbuLn3PnzmHAgAEoLy+3un3gwIE4f/68vbvFuXPnoNPpLAqn3r17WxxxMTIe2Wkar9VqTXNoLsa4T1vGraqqAqA/AmT8d9OYykr9nY9KSkrM9nPs2DEEBQU1+3VrNBpoNBqL/sbGxjZ9wxjH4w+64zpbDo13g38IwDUr21dCXwhNhH3L5ztbHlsDc+g85tB57sihrWPZ/WHc559/jhdffBE+Pj4W23x9ffHXv/4Vn3/+ub27hVarRVFREWJiYsz6Y2Jiml0yX1hYaBEfGxsLlUpluvZQczHGfdoybllZGSorK81ifHx8EB0dbYo5deoUysvLERwcbLafoUOH4vTp0zblgKg94d3giag9s+tM6ttvv10qKyvl1KlT8uc//1mmTp0qU6dOlUWLFsnp06elqqpK7rjjDofO0jYuOU9KSpKQkBDJysqSmpoaCQoKEgCSnp4uGzZsMMUbl7pnZmZKSEiIJCUlWSx1j4iIEK1WK2lpaRIcHCxpaWnNLnVvblxAv9T94sWLEhcXJ8OHD5dNmzZZLHV/8skn5dKlS5KYmCiDBw+W559/Xq5evSqDBg1y+Znqrmxc2cAcOtKiARFAftXM9nDD9mjmsU0bc8gcekLz9NVecGTnAwYMkNzcXNHpdHLt2jW5du2a6HQ62bVrlwwePNipiaempkpZWZk0NDSISqWSyMhI07acnBzJz883i4+KipKioiJpaGiQ0tJSSUlJsdhnYmKiHDt2TNRqtZSUlEh8fLxd4xrb8uXLpaKiQurr62Xv3r0yfPhwi5hFixbJmTNnpLa2Vg4cOCATJ05srW9cu3+TdqTWGXOoAKQUkJ2AeDXZ5mXoPwn7lr13xjy6/PvCHDKHHtA6ZPFjbD179pS77rpL7rrrLunVq5fbk90RGouf9tk6aw7jAbkGfaETDkg3w+NOQ38889jmjTlkDj2heXrx49S9vS5duoT//Oc/zuyCiNqx7eDd4Imo/bH7hOd77rkHxcXFVpeTde/eHUePHr3h/biIqOPYDt4NnojaF7uLn/nz5+Ott96yeg2aK1euYP369XZf4JCI2jfj3eC3Gh65OJiIPJndxU9YWFiLS9nz8vIwduxYpyZFRERE1FrsLn769OkDrVbb7HadTofbbrvNqUkRERERtRa7i5/y8nKMHDmy2e2hoaGmqx0TEREReRq7i5/c3Fw8//zzZnciN+ratSv+8pe/4NNPP3XJ5IiIiIhcze6l7i+88AISEhLwww8/4PXXX8f3338PEcGdd96Jxx9/HDfddBNefPHF1pgrERERkdPsLn5+/vlnTJgwAevWrcPKlSvN7qK+e/du/OEPf8DPP//s8okSERERuYJDFzk8c+YM/t//+3/o2bMnhgwZAi8vL/z444+4dOmSi6dHRERE5FpOX+FZpVK5ai5ERERErc6p4oeIqC0pAEQCCARQCWA/eEFFIrKf3au9iIjcIR7ACQB7AWwxPJ4w9BMR2YPFDxF5vHgAHwL4DkA4gG6Gx+8M/SyAiMgeLH6IyKMpoL9r/KcA4gB8DaDO8Bhn6F8F/jIjIts59fti0qRJ2LhxIwoKCtC3b18AwKxZszBx4kSXTI6IKBLAQADpAKTJNgGwEsAgQxwRkS0cLn4SEhKwe/du1NfXY/To0aYrPiuVSixdutRlEySizi3Q8Hi0me1Hm8QREd2Iw8XPsmXLMG/ePDz22GNmNzotKCjAmDFjXDI5IiLjnQJHNLN9RJM4IqIbcbj4CQ4OxpdffmnRf+XKFfTs2dOZORERmewHUAZgKQCvJtu8ACwBUGqIIyKyhcPFT2VlJYYMGWLRP2nSJJSWljo1KSIio0YACwDcD2AHzFd77TD0LwSv90NEtnO4+Fm/fj1ee+01jB8/HiKCvn374uGHH8aqVauwdu1aV86RiDq57QCmAxgJoBBAjeFxhKF/u/umRkTtkMNXeH7llVfQo0cP5Ofno2vXrvjyyy+hVquxatUqrFmzxpVzJCLCdgA7wSs8E5HznLq9xbJly/Diiy9i2LBhUCgUKCkpQV1dnavmRkRkphHAPndPgojaPafv7VVfX4+ioiJXzIWIiIio1dlV/GRmZtocu2DBArsnQ0RERNTa7DrhefTo0Ta1UaNGOTyh1NRUlJaWor6+HiqVCpMmTWoxPioqCiqVCvX19Th58iRSUlIsYhISElBcXIyGhgYUFxcjLi7OoXGXL1+O8vJyXL16Ffn5+Rg2bFiz88rNzYWIYNq0aTf+oomIiKhNiae0GTNmiFqtluTkZAkJCZHs7GypqamRfv36WY0fMGCA1NbWSnZ2toSEhEhycrKo1WpJSEgwxYSHh4tWq5XFixdLcHCwLF68WDQajYwfP96ucdPS0uTy5csSHx8vw4cPly1btkh5ebl069bNYl7z58+Xzz77TEREpk2bZlcOlEqliIgolco2y7tCoZAxY8aIQqFw+3ugvTbmkHn0lMYcMoee0NyVQzv+hro/ScZ28OBBWbt2rVlfSUmJpKenW43PyMiQkpISs75169ZJQUGB6fnWrVslNzfXLGbXrl2yefNmu8atqKiQtLQ003NfX1+5ePGiPPbYY2avCw0NlTNnzkifPn1Y/HSixhwyj57SmEPm0BOapxc/Dp/wvHjxYlRXVyMnJ8esPykpCbfddhtefvllu/bn4+ODsWPHIiMjw6w/Ly8PEyZMsPqaiIgI5OXlmfXt3r0bycnJ8Pb2hk6nQ0REBLKzsy1i5s+fb/O4AwcORGBgoNlYGo0G+/btw4QJE/Dmm28CAG6++WZs2bIFTzzxBKqrq236un19fU33RQP090YDAIVCAYWibe5TbRyrrcbriJhD12AencccOo85dJ67cmjreA4XPykpKXj44Yct+ouLi7F161a7ix9/f394e3tbFA3V1dUICAiw+pqAgACr8T4+PvD390dVVVWzMcZ92jKu8dFaTP/+/U3Ps7OzUVBQgE8++cTWLxtLlizBihUrLPpDQ0Pb7LIBCoUCQ4cOBQA0NvKqKY5gDl2DeXQec+g85tB57sqhn5+fTXEOFz8BAQGorLS8leDZs2cRGOj4/ZVFxOy5l5eXRd+N4pv227JPZ2OmTp2KyZMnY/To0c3O1ZqVK1ciKyvL9FypVKK8vBxHjhxBTU2NXftylLFSPnz4MH/QHcQcugbz6Dzm0HnMofPclUPjpyc34nDx89NPP2HixIk4deqUWf/EiRNRUVFh9/7OnTsHnU5ncZSnd+/ezX6EZDyy0zReq9Xi/PnzLcYY92nLuFVVVQD0BZ/x301jJk+ejMGDB+PSpUtm+/noo4+wf/9+3HPPPVa/Bo1GA41GY9Hf2NjYpm8Y43j8QXccc+gazKPzmEPnMYfOc0cObR3L4Q/j3n77bbz66quYM2cOgoKCEBQUhKSkJGRnZ+Ott96ye39arRZFRUWIiYkx64+JiUFBQYHV1xQWFlrEx8bGQqVSQafTtRhj3Kct45aVlaGystIsxsfHB9HR0aaYjIwMhIaGYtSoUaYGAE899RSSkpLsSQURERG1MofPqs7IyJCrV6+KTqcTnU4ntbW18uyzzzq8P+OS86SkJAkJCZGsrCypqamRoKAgASDp6emyYcMGU7xxqXtmZqaEhIRIUlKSxVL3iIgI0Wq1kpaWJsHBwZKWltbsUvfmxgX0S90vXrwocXFxMnz4cNm0aVOzS92Njau9Ok9jDplHT2nMIXPoCc3TV3vB2YH8/Pxk3LhxMnz4cPH19XV64qmpqVJWViYNDQ2iUqkkMjLStC0nJ0fy8/PN4qOioqSoqEgaGhqktLRUUlJSLPaZmJgox44dE7VaLSUlJRIfH2/XuMa2fPlyqaiokPr6etm7d68MHz68xa+FxU/nacwh8+gpjTlkDj2hddjiJycnx2qBwNZm3ziXNf6gM4ee0tyRRwUg0YDMNDwqPCAP7S2HHa0xh+03h7b+DXX4nB+lUom8vDz88MMPWLJkCfr27evoroiI3CIewAkAewFsMTyeMPQTUcflcPEzffp03H777Xj99dfx29/+FqdOnUJubi4SExPh7e30zeKJiFpVPIAPAXwHIBxAN8Pjd4Z+FkBEHZdTl168cOECVq9ejTFjxmD8+PE4ceIENm7ciIqKCmRlZWHIkCGumicRkcsoAGQC+BRAHICvAdQZHuMM/avg5C9IIvJYLvnZDggIQGxsLGJjY3Ht2jXk5uZi+PDhKCkpMd1GgojIU0QCGAggHfoTAK4nAFYCGGSII6KOx+Hix9vbGwkJCfjnP/+J06dP47e//S2ys7MRGBiIOXPm4N5778Xvf/97PPfcc66cLxGR04zXoD/azPajTeKIqGNx+OScyspKKBQKbNmyBePHj8e3335rEbN7926LKx4TEbmb8cY8I6D/qKupEU3iiKhjcbj4eeqpp/CPf/wDarW62ZhLly5h0KBBjg5BRNQq9gMoA7AU+nN8rv/oywvAEgClhjgi6ngc/tjrjjvusHpX96SkJKSlpTk1KSKi1tQIYAGA+wHsgPlqrx2G/oWGOCLqeBwuflJSUnD8+HGL/uLiYsybN8+pSRERtbbtAKYDGAmgEECN4XGEoX+7+6ZGRK3M4Y+9AgICUFlp+Yn42bNnERjI0wSJyPNtB7AT+lVdgdCf47MfPOJD1NE5XPz89NNPmDhxIk6dOmXWP3HiRFRUVDg7LyKiNtEIYJ+7J0FEbcrh4uftt9/Gq6++Ch8fH3zxxRcAgClTpuDll19GZmamyyZIRERE5EoOFz8vv/wybr31Vqxduxa+vr4AgIaGBrz00kvIyMhw2QSJiIiIXMmpm3AtXrwYf/3rX3HnnXeivr4eP/74IzQajavmRkTUoSnA842I3MHpO5DW1dVBpVK5Yi5ERJ1GPPT3Fxt4XV8Z9EvwudKMqHU5dW+vSZMmYePGjThw4AD69u0LAJg1axYmTpzokskREXVEvKM8kXs5XPwkJCRg9+7dqK+vx5gxY9ClSxcAgFKpxNKlS102QSKijoR3lCdyP4d/vpYtW4Z58+bhscceg1arNfUXFBRgzJgxLpkcEVFHwzvKE7mfw8VPcHAwvvzyS4v+K1euoGfPns7MiYiow+Id5Yncz+Hip7KyEkOGDLHonzRpEkpLS52aFBFRR3X9HeWt4R3liVqfw8XP+vXr8dprr2H8+PEQEfTt2xcPP/wwVq1ahbVr17pyjkREHcb1d5T3arLNVXeUVwCIBjDT8Mjzh4jMObzU/ZVXXkGPHj2Qn5+Prl274ssvv4RarcaqVauwZs0aV86RiKjDMN5R/kPo7yC/EvqPukZAX/jcD/2NVR293k88gNcA3H5dH5fQE5mz6z8EI0eOhJfX//6vsmzZMvj7+2P8+PEIDw/Hbbfdhueee87lkyQi6kha647y8QD+DuAEgAngEnqi5th15OfQoUMIDAzE2bNncfLkSdx11124cOECioqKWmt+REQdkqvvKH/9EvrnARwy7Mu4hH4H9EvodzoxBlFHYVfxc+nSJQwcOBBnz57FgAEDoFDwk2QiIke58o7yxiX0v0PzS+gLDXG8iz11dnZVLx999BH27duH0tJSiAhUKhVOnjxptTkqNTUVpaWlqK+vh0qlwqRJk1qMj4qKgkqlQn19PU6ePImUlBSLmISEBBQXF6OhoQHFxcWIi4tzaNzly5ejvLwcV69eRX5+PoYNG2ba1qtXL6xevRrHjx9HXV0dTp8+jddeew3du3e3PwlERHbiEnoi29l15CclJQUff/wxhgwZgtWrV+Ott95CTU2NyyYzY8YMvPrqq/jDH/6AAwcOICUlBbt27cKwYcPw008/WcQPGDAAubm5eOutt0y31Vi7di3Onj2Ljz/+GAAQHh6Obdu24dlnn8X27dsRHx+Pv//975g0aRK++eYbm8dNS0vD008/jTlz5uCHH37AsmXL8K9//QvBwcGora1F37590bdvXyxcuBAlJSXo378/3njjDfTt2xe//e1vXZYjIiJrrl9Cr7aynUvoicyJI+3dd9+Vbt26OfTa5trBgwdl7dq1Zn0lJSWSnp5uNT4jI0NKSkrM+tatWycFBQWm51u3bpXc3FyzmF27dsnmzZvtGreiokLS0tJMz319feXixYvy2GOPNfv1TJ8+XRoaGuSmm26yOQdKpVJERJRKpUtz21JTKBQyZswYUSgUbTZmR2vMIfPo7qYApBSQnQqFjG2SQy9AdgJy0hDn7rl6euP7sP3m0Na/oQ4vdZ87d66jL7XKx8cHY8eORUZGhll/Xl4eJkyYYPU1ERERyMvLM+vbvXs3kpOT4e3tDZ1Oh4iICGRnZ1vEzJ8/3+ZxBw4ciMDAQLOxNBoN9u3bhwkTJuDNN9+0Or8ePXrgypUruHbtWrNft6+vr+m+aID+3mgAoFAo2uycKuNYPIfLccyhazCPzvkzgL8rFOihUGCZQoEj0B/xWQT9EvoZhri2zK4C+vOMAgBUwbmTutsK34fOc1cObR3PruInMzMTzz77LK5evYrMzMwWYxcsWGDPruHv7w9vb29UV1eb9VdXVyMgIMDqawICAqzG+/j4wN/fH1VVVc3GGPdpy7jGR2sx/fv3tzq3W2+9Fc8++yzWr1/f0peNJUuWYMWKFRb9oaGhqKura/G1rqJQKDB06FAAQGOjp/9a8kzMoWswj84pA7BYocDCoUP1F0k05PC/ANIM20e14XzuAfAUzK85VA4gG0B+G87DXnwfOs9dOfTz87Mpzq7iZ/To0fDx8TH9uzkiYs9uW3ytl5dXi/uzFt+035Z9uioG0B+9+eyzz1BSUoK//OUvzc4dAFauXImsrCyz15aXl+PIkSMuPZ+qJcZK+fDhw/xBdxBz6BrMo/OOKBTYB0B5+DB6Nza67WhLPICXoV96/1v870KOiw39M+C5F13k+9B57sqh8dOTG7Gr+Jk8ebLVf1/vjjvuuOEffGvOnTsHnU5ncZSnd+/eFkdcjIxHdprGa7VanD9/vsUY4z5tGbeqqgqA/giQ8d/Nza1bt274/PPPUVtbi/j4eOh0uha/bo1GA41GY9Hf2NjYpm8Y43j8QXccc+gazKPzdI2NyHdjDhUAXoG+8ImD/iQLQL/UPg76aw69DH3x46nfZb4PneeOHNo6lss/jLv11lsxe/Zsu1+n1WpRVFSEmJgYs/6YmBgUFBRYfU1hYaFFfGxsLFQqlanoaC7GuE9bxi0rK0NlZaVZjI+PD6Kjo83mplQqkZeXB41GgwceeABqtbU1F0REHZvxmkPp+F/hYyTQX3NokCGOyF1ceqZ1aGio6HQ6h147Y8YMUavVkpSUJCEhIZKVlSU1NTUSFBQkACQ9PV02bNhgih8wYIDU1tZKZmamhISESFJSkqjVaklISDDFREREiFarlbS0NAkODpa0tDTRaDQyfvx4m8cFIGlpaXLx4kWJi4uT4cOHy6ZNm6S8vNy04q1bt25SWFgo3377rQwaNEj69Oljavac7c7VXu2zMYfMo6c0T8jhTEAEEL9mtnczbJ/pAfny1By29+bpq73g6oGdKX4ASGpqqpSVlUlDQ4OoVCqJjIw0bcvJyZH8/Hyz+KioKCkqKpKGhgYpLS2VlJQUi30mJibKsWPHRK1WS0lJicTHx9s1rrEtX75cKioqpL6+Xvbu3SvDhw83bYuOjpbm9O/fvzW+ce3+TdqRGnPIPHpK84QcRkNf3Pyqme3hhu3RHpAvT81he28sftha6xvnssYfdObQUxrz2DFyaLrmEPTXGLp+W3u45pAn5LC9N08vfuy+zs9HH33U4vaePXvau0siIupAGgEsgP5O8jugP8fHuNprCfTXHJoOzz3ZmTo+u4ufy5cv33D7+++/7/CEiIio/dsOfYGTCf0qL6NSQ/92O/ZlvFBiIPS352gPF0okz2Z38ePqKzsTEVHHtB3ATjhXuMRDX0ANvK6vDPojS/YUUETX47W7iYio1TQC2Adgq+HR3sLnQwDfAQgH0M3w+J2hP96lM6XOhMUPERF5HAX0R3yMF0r8GkCd4THO0L8K/CNGjuH7hoiIPI47L5SoADAWwIMAosE/lB2Rw3d1JyIiai2BhsejzWw/2iTOVXiOUefAgpaIiDxOpeFxRDPbRzSJc4XrzzGaDaA7eI5RR8Xih4iIPM5+6I+4LAXg1WSbF/TXCyo1xLnC9ecYJUB/ZMmTzjFSQP8R3EzwozhXYP6IiMjjGC+UeD/0F0q8frXXDkP/Qrjuej+efDPWeAAnAOwFsMXweAI8EuUMFj9EROSRjBdKHAn9hRJrDI8jYP+FEm/EXecY3QiX+7cOnvBMREQeyxUXSrTF9ecY/cfK9tY4x+hGmi73Nx6RMn4UtwP6j+J2gle8theLHyIi8mjGCyW2puvPMUposq01zjGyhfGjuIfQ/EdxhYa41s5PR8OPvYiIqNO7/hyjj6H/qK01zzGyhad+FNcRsPghIiKC+TlG7wG4jNY7x8gW7lju7yzjqrQHob9QpKcWGfzYi4iIyGA7gH8CSAJQC6AC7ruL/PUfxcXB/KMvd30U1xJrF4hcAs+8QKSnFmVERERu0QigCMA22H8zVlfPoy2X+zuj6aq07tBfKNJTV6XxyA8REZGHMn4Ulwn9R3BGpXDPR3HWWFuVpoD+nKRN0J9D1XRVmgKtv4KvJSx+iIiIPFhbLfd3lL2r0jzh/mn82IuIiMjDGZf7b4V7P4qzxp5VaZ5y0UYWP0REROQwW1elVcP847Gv4b77p7H4ISIiIofZehNawHPun8bih4iIiBzW3Kq0kdCf7GxcldbHEO8JF21k8UNEREROaXoT2svQXyjy+gtEetJFGz2u+ElNTUVpaSnq6+uhUqkwadKkFuOjoqKgUqlQX1+PkydPIiUlxSImISEBxcXFaGhoQHFxMeLi4hwad/ny5SgvL8fVq1eRn5+PYcOGmW339fXF6tWrcfbsWdTW1mLnzp24/fbb7UsAERFRO7QdwBAAdwN4GMBjAILxvxVctn481lYXbRRPaTNmzBC1Wi3JyckSEhIi2dnZUlNTI/369bMaP2DAAKmtrZXs7GwJCQmR5ORkUavVkpCQYIoJDw8XrVYrixcvluDgYFm8eLFoNBoZP368XeOmpaXJ5cuXJT4+XoYPHy5btmyR8vJy6datmylm7dq18tNPP8mUKVNk1KhRsmfPHjl06JAoFAqbc6BUKkVERKlUtlneFQqFjBkzxq55sjGHzKNnNuaQOfSE1lwO4wG5BshOQMIB6WZ43Gnoj3dyXDv+hro/ScZ28OBBWbt2rVlfSUmJpKenW43PyMiQkpISs75169ZJQUGB6fnWrVslNzfXLGbXrl2yefNmu8atqKiQtLQ003NfX1+5ePGiPPbYYwJAunfvLmq1WmbMmGGKCQwMFJ1OJ7Gxsa3xjWv1Nykbc8g8tr/GHDKHntBaymE8IKWAyHXtJJwvfADb/4Z6zMdePj4+GDt2LPLy8sz68/LyMGHCBKuviYiIsIjfvXs3xo0bB29v7xZjjPu0ZdyBAwciMDDQLEaj0WDfvn2mmLFjx8LX19csprKyEkePHm12/kRERJ3Ndvzv47GHDI+/RNterdpjrvDs7+8Pb29vVFdXm/VXV1cjICDA6msCAgKsxvv4+MDf3x9VVVXNxhj3acu4xkdrMf379zfFqNVqXLp0yeb5A/rzhLp06WJ6rlQqAQAKhQIKRdvUpsax2mq8jog5dA3m0XnMofOYQ+fZksOm5/a4Itu2fs88pvgxEhGz515eXhZ9N4pv2m/LPl0V09SNYpYsWYIVK1ZY9IeGhqKurq7FfbuKQqHA0KFDAQCNjZ503dD2gzl0DebRecyh85hD57krh35+fjbFeUzxc+7cOeh0OoujJL1797Y44mJkPLLTNF6r1eL8+fMtxhj3acu4VVVVAPRHd4z/thbTpUsX9OzZ0+zoT+/evVFQUNDs171y5UpkZWWZniuVSpSXl+PIkSOoqalp9nWuZKyUDx8+zB90BzGHrsE8Oo85dB5z6Dx35dD46cmNeEzxo9VqUVRUhJiYGOzYscPUHxMTg507d1p9TWFhIaZOnWrWFxsbC5VKBZ1OZ4qJiYnBq6++ahZjLEhsGbesrAyVlZWIiYnB4cOHAejPFYqOjsaiRYsAAEVFRdBoNIiJicE//vEPAPpiacSIEUhLS2v269ZoNNBoNBb9jY2NbfqGMY7HH3THMYeuwTw6jzl0HnPoPHfk0J6x3H5WuLEZl5wnJSVJSEiIZGVlSU1NjQQFBQkASU9Plw0bNpjijUvdMzMzJSQkRJKSkiyWukdERIhWq5W0tDQJDg6WtLS0Zpe6NzcuoF/qfvHiRYmLi5Phw4fLpk2brC51P3PmjEyePFlGjRol//73v7nUvZM05pB59JTGHDKHntDclcN2udQdgKSmpkpZWZk0NDSISqWSyMhI07acnBzJz883i4+KipKioiJpaGiQ0tJSSUlJsdhnYmKiHDt2TNRqtZSUlEh8fLxd4xrb8uXLpaKiQurr62Xv3r0yfPhws+1dunSR1atXy7lz56Surk4++eQTueOOO1rrG9fu36QdqTGHzKOnNOaQOfSExuKHrbW+cS5r/EFnDj2lMY/MoSc05rD95tDWv6Eec84PmbP1pC1XUCgU8PPzg1Kp5OfbDmIOXYN5dB5z6Dzm0HnuymG7O+GZ9IzfuPLycjfPhIiIqH1SKpUtrpj2gv4QEHmQvn37ttkyd+B/y+tvv/32Nh23I2EOXYN5dB5z6Dzm0HnuzKFSqURFRUWLMTzy44Fu9E1rLTU1NfxBdxJz6BrMo/OYQ+cxh85zRw5tGY/X7iYiIqJOhcUPERERdSosfghqtRorVqyAWq1291TaLebQNZhH5zGHzmMOnefpOeQJz0RERNSp8MgPERERdSosfoiIiKhTYfFDREREnQqLHyIiIupUWPx0ApGRkfjkk09QXl4OEcG0adNu+JqoqCioVCrU19fj5MmTSElJaYOZei57cxgdHQ0RsWjBwcFtNGPPsnjxYnzzzTe4cuUKqqursX37dgwdOvSGr+P70JwjeeR70dy8efPw7bff4vLly7h8+TIKCgrwm9/8psXX8H1ozt4ceuJ7kMVPJ+Dn54dvv/0WTzzxhE3xAwYMQG5uLvbv34/Ro0cjPT0dq1evRkJCQivP1HPZm0OjoUOHIiAgwNR+/PHHVpqhZ4uOjsaaNWsQHh6OmJgYeHt7Iy8vD7fcckuzr+H70JIjeTTie1Hvv//9LxYvXoxx48Zh3Lhx+OKLL7Bz504MGzbMajzfh5bszaGRp70H3Xrbe7a2bSIi06ZNazEmIyNDSkpKzPrWrVsnBQUFbp+/JzRbchgdHS0iIj169HD7fD2x+fv7i4hIZGRkszF8H7omj3wv3ridP39e5s6da3Ub34fO59AT34M88kMWIiIikJeXZ9a3e/dujBs3Dt7evB2cPQ4dOoSKigr8+9//xt133+3u6XiMHj16AAAuXLjQbAzfhzdmSx6N+F60pFAo8OCDD8LPzw+FhYVWY/g+bJktOTTypPcgix+yEBAQgOrqarO+6upq+Pj4wN/f302zal8qKyvx6KOPIjExEQkJCfj++++xZ88eREZGuntqHiErKwv79+9HcXFxszF8H96YLXnke9HSiBEjUFNTA7VajTfeeAPx8fE4duyY1Vi+D62zJ4ee+B5k2UpWiYjZcy8vL6v9ZN0PP/yAH374wfT84MGD6NevHxYuXIj9+/e7cWbu9/rrryM0NBSTJk26YSzfh82zNY98L1r6/vvvMWrUKPTs2ROJiYnYsGEDoqOjm/3jzfehJXty6InvQR75IQtVVVUICAgw6+vduze0Wi3Onz/vplm1fwcPHsQvf/lLd0/DrVavXo0HHngA99xzD8rLy1uM5fuwefbk0ZrO/l7UarU4efIkioqKsHTpUnz77bd48sknrcbyfWidPTm0xt3vQRY/ZKGwsBAxMTFmfbGxsVCpVNDpdG6aVfs3evRoVFZWunsabvO3v/0NCQkJmDx5Mk6dOnXDeL4PrbM3j9Z09vdiU15eXujSpYvVbXwf2qalHFrjCe9Bt591zda6zc/PT8LCwiQsLExERObPny9hYWHSr18/ASDp6emyYcMGU/yAAQOktrZWMjMzJSQkRJKSkkStVktCQoLbv5b2ksMnn3xSpk2bJkOGDJFhw4ZJenq6iIjEx8e7/WtxR1uzZo1cvHhRoqKipE+fPqbWtWtXUwzfh62TR74XzduLL74okyZNkv79+8uIESPkhRdeEJ1OJ7/+9a+t5o/vQ+dz6KHvQfcnkq11m3GZYVM5OTkCQHJyciQ/P9/sNVFRUVJUVCQNDQ1SWloqKSkpbv862lMO//znP8uPP/4oV69elfPnz8uXX34p9913n9u/Dne15syePdsUw/dh6+SR70Xz9vbbb0tZWZk0NDRIdXW1/Otf/zL90baWP4DvQ2dz6InvQS/DP4iIiIg6BZ7zQ0RERJ0Kix8iIiLqVFj8EBERUafC4oeIiIg6FRY/RERE1Kmw+CEiIqJOhcUPERERdSosfoioQyorK7PrXkPuNHv2bIgIRATZ2dlO769///5Yvny51W1lZWWmsXr06OH0WETtEYsfImpVxj+0zbWcnJwbvn7atGmtMjelUokXXngBx44dQ319PSorK/Gvf/0L8fHxLtl/dHS0zUXG5cuXERAQgGeffdbUl5+fDxHBokWLLOI/++wziEizRU5z7rrrLiQkJNj1GqKOxtvdEyCiju36O2I/+OCDeP755xEcHGzqq6+vd8e00KNHD3z11Vfo0aMHli1bhv/85z/Q6XSIjo7Gyy+/jC+++AKXL19us/mICKqrqy36z5w5g6SkJLz00kumvsDAQEyePBkVFRVmsQMGDEBWVhYiIiLQvXt3zJw5E3v37kVqaqop5ty5c7hw4ULrfSFE7QCP/BBRq6qurja1y5cvm/7IG9vDDz+MEydOQK1W4/jx45g1a5bptWVlZQCAHTt2QERMzwcNGoQdO3agqqoKNTU1+OabbzBlyhS75pWeno4BAwbgV7/6Fd5//30cO3YMP/74I95++22MGjUKtbW1AICePXtiw4YNuHDhAurq6pCbm4shQ4aY9hMUFIRPPvkEFy5cQG1tLY4ePYr77rsP/fv3x969ewEAly5dsukolzWffvopfvGLX2DChAmmvjlz5iAvLw8///yzWez777+PPn36IDU1Fe+99x6efPJJnD9/3u4xiTo6Fj9E5DZxcXF47bXXkJmZiREjRmD9+vXIycnB3XffDUD/EQ2g/2MfEBBget6tWzfk5ubi17/+NUaPHo3du3fjn//8J/r162fTuF5eXpg5cyY2bdqEyspKi+11dXW4du0aAOC9997DuHHj8MADDyAiIgJeXl7Izc2Ft7f+wPmaNWvQpUsXREVFYeTIkVi0aBFqa2vx008/mT5eGjp0KAICAhw6B0mj0WDTpk1ISkoy9c2ZMwfvvvuuRezo0aOxZs0aHDp0CD///DPy8vKwbNkyu8ck6gzcfodYNja2ztFmz54tFy9eND3/6quvZP369WYx27Ztk08//dT0XERk2rRpN9z30aNH5fHHHzc9LysrkyeffNJq7G233SYiIvPnz29xn0OGDBERkYiICFPfrbfeKnV1dTJ9+nQBIN9++60899xzVl8fHR0tIiI9evSwKy/Glp+fL9nZ2TJy5Ei5fPmy3HLLLRIZGSlVVVXi7e0thw4dkuXLl5viP//8c/nmm29k1qxZZv2OzouNraM2HvkhIre58847ceDAAbO+AwcO4M4772zxdbfccgteeuklFBcX4+LFi6ipqUFISAiCgoJsGtfLywsAICI3nJ9Wq8XXX39t6rtw4QK+//570xxXr16NZcuW4auvvsKKFSswcuRIm+Zgj++++w4//vgjpk+fjrlz52Ljxo3Q6XQWcb/73e9w8OBBpKen45lnnkFBQQESExNdPh+i9o7FDxG5VdMCxMvL64ZFySuvvILExEQ888wziIyMxKhRo/Ddd9/B19fXpjHPnj2LCxcu3LDIMhZJ1vqNc3znnXcwaNAgbNy4ESNHjoRKpcITTzxh0zzs8e677+Lxxx/H9OnTrX7kBQDnz5/Hn/70J0RGRuKdd97Bzp07sW3bNsTExLh8PkTtGYsfInKbY8eOYdKkSWZ9EyZMwLFjx0zPNRoNbrrpJrOYyMhIvPfee9ixYweOHj2KqqoqDBgwwOZxRQTbtm3D7373OwQGBlpsv+WWW3DTTTehpKQEPj4++NWvfmXaduutt2Lo0KFmc/zvf/+L9evXIzExEZmZmXj00UdNcwdgMX9HbN68GSNHjsTRo0fNxm5OVVUVXnrpJRw+fBiRkZFOj0/UkbD4ISK3eeWVVzBnzhykpKRgyJAheOqpp5CQkIBVq1aZYk6dOoUpU6agT58+6NmzJwDgxIkTSEhIQFhYGEJDQ7F582YoFPb9Olu6dCl++uknfP311/j973+PO++8E0OGDEFSUhIOHz6Mbt264cSJE9ixYwfeeustTJw4EaGhofjggw9QXl6OnTt3AgCys7MRGxuLAQMGYPTo0Zg8ebKpODl9+jQaGxtx//33w9/fH35+fg7n6tKlSwgMDGxxVdvbb7+Nu+66C35+fujSpQvi4+MxfPhwFBUVOTwuUUfl9hOP2NjYOkezdmLvvHnz5MSJE6JWq+X48eMya9Yss+3333+//PDDD6LRaKSsrEwASP/+/WXPnj1SV1cnp0+flj/84Q+mk4ONr2vphGdj6969u6Snp8v3338vDQ0NUllZKXl5eWYnWPfs2VM2bNggFy9elLq6Otm1a5cMGTLEtH316tXy448/Sn19vVRXV8uGDRvk1ltvNW1ftmyZVFRUyLVr1yQnJ8fmvACw+JqatqYnPKenp8t3330ntbW1otVq5eTJk7Jw4UKL1/GEZzY290+AjY2NrVO35oofR1v//v252ouNrYXGj72IiDxAz549UVNTg4yMjFYd5+jRo9i1a1erjkHk6bygr4KIiMhNunXrhj59+gDQn9vTmldlDgoKgo+PDwCgtLT0hivriDoiFj9ERETUqfBjLyIiIupUWPwQERFRp8Lih4iIiDoVFj9ERETUqbD4ISIiok6FxQ8RERF1Kix+iIiIqFNh8UNERESdCosfIiIi6lT+f+icYbfbU0ZBAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with plt.style.context('dark_background'):\n",
    "    fig, ax = plt.subplots(1,1,figsize=(6,4))\n",
    "\n",
    "    ax.scatter(res.F[:,0], res.F[:,1], edgecolors='red', facecolors='k')\n",
    "    ax.set_ylabel(r\"Lifecycle CO$_2$ Emissions [MT/MWh]\")\n",
    "    ax.set_xlabel(r\"Total Cost [M\\$]\")\n",
    "    ax.grid(alpha=0.2)\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "009038f3-85e7-44e6-aae7-577b351876dd",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "osier_new",
   "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": "3.10.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}