stock_analyzer.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "stock_analyzer.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "TPgHcsPHGLmm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Dependecies\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.model_selection import train_test_split\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('bmh')\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bTy64qXhHOME",
        "colab_type": "code",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "outputId": "15e7e300-88dc-4dd9-c67f-ee38a03cfdd7"
      },
      "source": [
        "#Load the data\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-5d07dc01-5a6b-45f4-b6ac-4b97d71b503c\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-5d07dc01-5a6b-45f4-b6ac-4b97d71b503c\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving TSLA.csv to TSLA.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U_MkofOkJw9g",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "cc325ce9-525d-4fdf-e777-830d0d26d5c4"
      },
      "source": [
        "#Store the data into a frame\n",
        "df = pd.read_csv('TSLA.csv')\n",
        "df.head(6)"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2019-05-20</td>\n",
              "      <td>202.800003</td>\n",
              "      <td>206.000000</td>\n",
              "      <td>195.250000</td>\n",
              "      <td>205.360001</td>\n",
              "      <td>205.360001</td>\n",
              "      <td>20526200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2019-05-21</td>\n",
              "      <td>197.759995</td>\n",
              "      <td>207.399994</td>\n",
              "      <td>196.039993</td>\n",
              "      <td>205.080002</td>\n",
              "      <td>205.080002</td>\n",
              "      <td>18003900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019-05-22</td>\n",
              "      <td>199.100006</td>\n",
              "      <td>203.940002</td>\n",
              "      <td>191.779999</td>\n",
              "      <td>192.729996</td>\n",
              "      <td>192.729996</td>\n",
              "      <td>18685200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2019-05-23</td>\n",
              "      <td>194.339996</td>\n",
              "      <td>199.470001</td>\n",
              "      <td>186.220001</td>\n",
              "      <td>195.490005</td>\n",
              "      <td>195.490005</td>\n",
              "      <td>26547100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2019-05-24</td>\n",
              "      <td>199.830002</td>\n",
              "      <td>199.979996</td>\n",
              "      <td>188.750000</td>\n",
              "      <td>190.630005</td>\n",
              "      <td>190.630005</td>\n",
              "      <td>14136600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2019-05-28</td>\n",
              "      <td>191.199997</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>187.850006</td>\n",
              "      <td>188.699997</td>\n",
              "      <td>188.699997</td>\n",
              "      <td>10312900</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Date        Open        High  ...       Close   Adj Close    Volume\n",
              "0  2019-05-20  202.800003  206.000000  ...  205.360001  205.360001  20526200\n",
              "1  2019-05-21  197.759995  207.399994  ...  205.080002  205.080002  18003900\n",
              "2  2019-05-22  199.100006  203.940002  ...  192.729996  192.729996  18685200\n",
              "3  2019-05-23  194.339996  199.470001  ...  195.490005  195.490005  26547100\n",
              "4  2019-05-24  199.830002  199.979996  ...  190.630005  190.630005  14136600\n",
              "5  2019-05-28  191.199997  195.000000  ...  188.699997  188.699997  10312900\n",
              "\n",
              "[6 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "606mg2JsKKKL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "0ddfbf20-6744-40fa-b91c-97e3185f1761"
      },
      "source": [
        "#Get the number of trading days\n",
        "df.shape"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(252, 7)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X9KFFi7nKTFM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "outputId": "8512e92c-7b75-4cc3-cc6a-761604aac1fd"
      },
      "source": [
        "#Visualize the close price data\n",
        "plt.figure(figsize=(16,8))\n",
        "plt.title('Tesla')\n",
        "plt.xlabel('Days')\n",
        "plt.ylabel('Close price USD $')\n",
        "plt.plot(df['Close'])\n",
        "plt.show()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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6V5M5JB2YkkMWsi7q7+9XPQQi5pC0wBySasygd/KlMsry7M+9MLWGZcUAEAr4EAv5YUlgfsGbfbzMIenAlByykHWRKW176mzMIemAOSTVmEHv1B/0BHi3tHgtd8g6vD7wiTkkHZiSQxayLurp6VE9BCLmkLTAHJJqzKB36vfHAgoK2QbukHX0VgtZb/bJMoekA1NyyELWRZbl3XHzRMthDkkHzCGpxgx6J2Pvjw34KvvwvFpa7JxYvLaOrLcHPjGHpANTcshC1kWZTEb1EIiYQ9ICc0iqMYPecZYWO8t2O2Fp8axHS4uZQ9KBKTlkIeuikZER1UMgYg5JC8whqcYMeidrF7L9dkHp2WFPTRSyvR53ZJlD0oEpOWQh66KxsTHVQyBiDkkLzCGpxgx6J1OsFK79dpHodUd2cA17ZL0+7Ik5JB2YkkMWsi4KBhufSIncwhySDphDUo0Z9I7Tke3r6qSlxd50ZJlD0oEpOWQh66JEIqF6CETMIWmBOSTVmEHv1PbIVn5YLlgSZSlX+iMtyxYs5IplhO27YRvl9WFPzCHpwJQcspB10eTkpOohEDGHpAXmkFRjBr2TtU8tjoX8CAcqP2q63ZWdrOvGCiEa/nO9Hi8tZg5JB6bkkIWsi0z5bQd1NuaQdMAckmrMoHecjmws6EPELmTdPvCpmWXFQK0jO5srQbrcNQaYQ9KDKTlkIeuiQqGgeghEzCFpgTkk1ZhB72Ttw54qHdlKd9TtjuxUZu0HPQFAJOBDbySAYlliYt79rixzSDowJYcsZF2Uy+VUD4GIOSQtMIekGjPoHacj2xXyI+z3Zmlxsx1ZANjZHwEAPD/tfkaYQ9KBKTlkIesiU+5oos7GHJIOmENSjRn0jnNq8dl7ZN1dtusUsv1NFbJRAMALHhSyzCHpwJQcspB1kSl3NFFnYw5JB8whqcYMeqfakfVwj+yks7S4iUL2PKeQnXG/kGUOSQem5JCFrItCoZDqIRAxh6QF5pBUYwa9c/YeWW+WFk87S4vXuEcWAHZUO7L5to5pKcwh6cCUHLKQdVF3d7fqIRAxh6QF5pBUYwa941y/0xX0VzuyOu+R3d4bgU8AJ1N5FFweJ3NIOjAlhyxkXTQ1NaV6CETMIWmBOSTVmEFvWGWJXLEMASAS9FU7sm4uLS5L2VIhGw74sKknjLIEjs+625VlDqkVuaKFJ8fmW74qypQcspB1UV9fn+ohEDGHpAXmkFRjBr2RK9ZOLPYJ4Ukhm86XUCpLdIdrS5nXytkn6/bJxcwhteJLB8bw3751BJ97+ExLX8eUHLKQdZEpR1tTZ2MOSQfMIanGDHojU6gUrF3Byo+YXiwtbuXEYodzcvGxGXc7sswhteJwMgsA+Mrj43j4ZLrpr2NKDlnIuiifd//QAKLVMIekA+aQVGMGveHsj42F/ADgyWFPTiHbzInFDq/ukmUOqRUnU7X8fOS+0Wr218rJ4Y+OTCOdL7VlbCqwkHWRKXc0UWdjDkkHzCGpxgx6o3b1joeFbKb5/bGOakfW5UKWOaRmzS+UMJMrIewXuGJTHKl8CR/+8TFY5bXvlx0ZGcFzU1n87f2jeM8dTzf1NXTAQtZFptzRRJ2NOSQdMIekGjPojcUd2eo9spb7HdlWCtnheAjRoA/TuRJmcs11uRrBHFKzTqQWAACbExG89/od6IsG8PiZefzBN5/FVx8fP6tbu5qxsTHcfWgSAPDK8/rg9wlXxuw2FrIuikQiqodAxBySFphDUo0Z9Ea1Ixuq/IjpRUd2soU7ZB0+IbCzz+nKurf8lzmkZjmF6tbeMPq7gnj/q3YgGvThcDKLz/ziNN71tafx0ftHG/pali+Ee49OAwDecOGgW0N2HQtZF0WjUdVDIGIOSQvMIanGDHqjdtjToo5sUe+lxUBtn+wLM+4tL2YOqVknZysd2a2JSk5ftKkbX/nPl+DP9+3Eq3f3wSeAHx2dxmwDKwr2jxWxYElcsakbW3s795crLGRdNDMzo3oIRMwhaYE5JNWYQW94ddhTsW6pcjuWFgO1fbIvuLhPljmkZp2wO7JbEuHqY9GgH6/Y2Ys/uX4Hrt7Sg7IEfj6aWvHrlKXEd5+t5PCNF3VuNxbwsJAVQvyhEOKgEOIpIcTtQoiIEGKnEOJBIcRRIcS/CSFC9mvD9udH7ed3eDXOdhoYGFA9BCLmkLTAHJJqzKA3akuLnUK2svduoY17ZJ8am8fNX3gCf/7955DMFGqnFrewtBioFbJunlzMHFKznD2yW5bpoL5iZy8A4D9emD3r8SfOzOOj949Wf0Fz4NQcJnJlDMWCuHZbwsURu8+TQlYIsRnA7wG4Wkp5CQA/gLcA+AiAv5dS7gYwA+BW+4/cCmDGfvzv7dd1nLm5OdVDIGIOSQvMIanGDHojay8tji26Rzbfxo7sgVNzKJUlHjyRxru//jRmcyX4BNAXba2Q3dFXKRBGZ/KuneLKHK4P09kiCm3MvFWWOJ12lhaHl3zNS7cl4BPAo6fnqlfqFK0yPnLfMfzgyDT+728cxteeGMddB5MAKntjO/WQJ4eXS4sDAKJCiACALgBnANwA4Ov2818A8Cb745vtz2E/v08I0XH/pQuFguohEDGHpAXmkFRjBr2R8WBp8ehsZYnlpp4QssUyJIDeaKDlH8q7wwEMxYIoWBKn7KKh3ZhDc+RL5SWXoZ9M5fG2rxzER3/S2MFLjZiYL6BoSQx2BRG1958v1hMJ4EWbulGWwP7jleXFPzwyjWSmiK6gD8WyxKcfOo0HT6QREMBrL+j81QEBL/4SKeUpIcRHARwHkAPwAwCPAJiVUjq38J4EsNn+eDOAE/afLQkhUgAGAEzWf92JiQnceuutCAQCsCwLt9xyC2677TaMjY0hFovB7/cjnU5jaGgI09PTkFJiaGgI4+PjiMfjAID5+XkMDw8jmUxCCIH+/n4kk0n09PTAsixkMhmMjIxgbGwMwWAQiUQCk5OTSCQSKBQKyOVy1edDoRC6u7sxNTWFvr4+BAIBjI6OVp+PRCKIRqOYmZnBwMAA5ubmUCgUqs9Ho1GEQiGkUikMDg4ilUqhWCxWn9fhPeVyOeTzeb6nDnpPlmVhfHzcqPdk4vfJ9PdkWRbm5+eNek8mfp9Mfk8+n++s/0824T3p+H2amcsCAEKijNHRUcwtVArZ+dwC0ul0W97T0Yk0AOBdF0Ywa8XxL0+lcFGvH9lstuX3tCUGJDPAI6NTkKlS279PlmVhYmJC+ffJxOx5/Z6+dDiPnxzP4k+v6cE1uzdW39PDMwEUyxL/8cIsRs8kgUK25fd00ooBADZEBebn55d9T5cP+HDgFPCDQ2dw7UgIX37kNADgd1+yEfn5FL70dBaphTKu2hBEqFzA6dNJ7b9PKxFSun8BrhCiD8AdAH4DwCyAr6HSaf2AvXwYQoitAL4rpbxECPEUgNdKKU/azz0H4CVSyrMK2f3798u9e/e6Pv5mjY6OYvv27aqHQescc0g6YA5JNWbQG3/87SN4/Mw8PnLTblyxuRtjcwt4+78dwnA8hC+95eKWv37RKuONn38cZQnc9duXIxLwwflZth2L9779zCQ+9tMTeNn2BD5w43ktf73FmENz/N5dh/FMMot3vXgj3nL5SPXxf/jpcXznmSkAwB+/chtu3NN65/OOJyfwyQdP4Q0XDuL3Xr512dfN5Ip4678+BZ8QePc1m/CJB05hSyKMT//qhfD7BFL5En4+msLOwBz27trR8ri8cODAgUf27dt39VLPebW0+NUAXpBSJqWURQD/DuDlAHrtpcYAsAXAKfvjUwC2AoD9fALAlEdjbRsesU46YA5JB8whqcYMesM5tXjxPbLt2iN7Or0ASwIj3aHq/lshRFuKWAB48ZYeAJV9hsU2HlDlYA7NkbL3oT6bPHt58XNTtc9/+sLKJwg3qnqH7DL7Yx190SAuHYmjVJb41IOVsuotlw9Xl90nIgHcdMEA+ru72jIu1bwqZI8DuFYI0WXvdd0H4BCAHwP4Nfs17wBwl/3x3fbnsJ+/V3rROm6zUCikeghEzCFpgTkk1ZhBbzj3yDp7ZNt92JOzP3abS3dfboiHsL0vglyxjKfGM23/+syhOZxC9shktvpYqSyrp14LAA+fSiNrn+TdipP2icWN3PnqnF7s/MLnht3957zGlBx6UshKKR9EZSnxAQBP2n/vpwC8F8AfCSGOorIH9p/tP/LPAAbsx/8IwPu8GGe7pVLt+S0MUSuYQ9IBc0iqMYPecH5o77IPpAn5a4c9taMncXymUshu73OnkAVqXdlfnEi3/Wszh2YoWGVki5VfzozPFzCbq1wBdWI2j6IlMdIdwoUbYihaEg+1IUcnZs+9Q3Y5L9/eW/34LZcPI7DEIWim5NCzU4ullH8ppdwrpbxESvk2KeWClPJ5KeU1UsrdUso3SykX7Nfm7c93288/79U422lwsLMvGSYzMIekA+aQVGMGvbH41GK/TyDor/wgXbBaL2Td7sgCwDVb7UL2ZPsLWebQDE431vGs3ZU9OlX59+6BLlxnd0Z/euzse13XKlOwMJ0rIeQX2BBfvZM6EAvi1y7dgJdvT+DVe87txgLm5NDL63fWHVN+20GdjTkkHTCHpBoz6L6CVUbRkvALIOSvdYEibbyCx4uO7MXDMUSDPozO5DEx397rcphDM6RyiwvZynLio/b+2N0DUVy3IwEAeOhEuqXsO/tjtyTC8DW4F/w9L9mMv7zxvOqKiMVMySELWRcVi0XVQyBiDkkLzCGpxgy6L1es7Y+tP3ypXQc+WWVZ2yuYcK+QDfp9uGJTN4D2d2WZQzPMLurIHklWOrHP2QXt7sEoRrrD2DMYRb5UxsMt5OjEbCXzW9qYeVNyyELWRSMjI6u/iMhlzCHpgDkk1ZhB92Wc/bH2smJHuzqyZ+YWUCxLbIgHz/k72u3F9vLiduxvrMccmsFZWrx7oHIK9bOTWZSlrC4t3jVQORX4uh1rX14spcS3np7E158Yx2yuiBOpxvfHNsqUHLKQddFql/gSeYE5JB0wh6QaM+i+xQc9OdrVkR2dcX9/rMM58OmxNl/DwxyawSlkLx6OoSvow1S2iEPjGWSLZfRHAxjoCgKonSD84PF0w4edPZPM4h9/dgKfeug0fvMrB/G9w5UbSBs5sbhRpuSQhayLYrGY6iEQMYekBeaQVGMG3VfryJ7942XY356OrFPIbvegkN0QD2GHC9fwMIdmcPbIJqJBnD9U6b5+xy44nW4sUFkOHPYLzBes6tL71XzzUBIAMBwPoWRJzNh/VzsLWVNyGFA9AJP5/e4ueyFqBHNIOmAOSTVm0H05u1CNudWRnXUOeoq29HUadcXmbhybyePp8Ux1z2yrmEMzOHtkeyMBnD/YhcdOz+Mnz88AqC03dnRHAljIFJFeKK26JH4mV8T9z89CAPi71+9GWQLfeWYSAsCegfbl3pQcsiPronS6/ce2E60Vc0g6YA5JNWbQfU7HKRI8+8fLZvfIzi+UMJmpnRp8fNb9E4vrDUQry0Pn7U5zOzCHZnCWFifsQhaoXS+1e7DrrNf2hCt9w/TC6jn63uEpFMsSL9nWg5HuMDb1hPE712zGrddsPusAtVaZkkN2ZF00NDSkeghEzCFpgTkk1ZhB9+XtO2SjgUWHPQXXVsim8yXc8eQE7jyYhFWW+OvX7sKlI3Gc8OAO2XpO9yzTxkKWOTRDfSE7FA+e9dzijmxPpJKj9KKTjhezypVDngDgjRe5mxNTcsiOrIump6dVD4GIOSQtMIekGjPoPmdpcTTY/B7Zuw4m8fZ/O4jbHx9HvlRGsSzxV/e8gEdOpVGwJAa7goi5fGKxI27/Pe3syDKHZkjVLS0eiYfQE65kJRbyY6Q7dNZrE3ZHdm5h5UJ2//EUkpkiNveEceXm9ixlX44pOWQh66JGTycjchNzSDpgDkk1ZtB9yy0tbnSP7KnUAj6+/ySyxTKu2BTH379hD166LYG5BQsf/NELAIBtHi0rBlAtmNvZkWUOzVDtyEYDEEJUD3za1R89ZwlwdyRg/5mVc3S3fcjTGy8ahK+Ny4iXYkoOWci6yJS2PXU25pB0wBySasyg+5ylxc6eWEckUPmhfLVC9tHTcwAqd29+5ElbrNIAACAASURBVHV7cPFIHO971XbsHohW9x96cWKxIx7m0mI6V6ksMbdgwSeAbjsje4cqpwA7BW09p1u70tLiw8kMHjs9j3DAhxv39Lsw6rOZkkMWsi4aHx9XPQQi5pC0wBySasyg+2pLi5c+tXi1pcVOIXvVltqyymjQjw++5rzqvZw7+r05sRionb7czkKWOex8TkHaHQ5UO6e/eukGvPPqjXjL5cPnvL4nsvLS4mSmgA/8sLLi4HV7BxAPu3+EkSk55GFPLorH46qHQMQckhaYQ1KNGXSfs7T4nD2yDRSyZSnxuF3Ivmjj2fsDB2MhfPT1e/DTY7O4YVdfO4e8opjdSZtv4LTZRjGHna9+f6wjFvLjrS8aWfL1K51anC1Y+PPvP4+pbBGXjsRx64s3uTDic5mSQxayRERERNSyaiF7ztJip5Bdfl/eC9M5pBcsbIgHsakndM7zmxNh/MYS3S43VffIFttXyFLnm607sbgRy51abJUl/vreY3h+OoctiTD+8tU7EfJzsexa8L+Wi+bn51UPgYg5JC0wh6QaM+i+fMneI7vcYU/W8h3ZR0/VurHtvC+zFWG/QMAnULQkCmu8A3c5zGHnm83VDnpqhNORTS0qZL/59CR+cTKNnrAff/WaXdUlyF4wJYcsZF00POztbw6JlsIckg6YQ1KNGXRfvrj0HtlIA0uLHztT+cH6RZvcvXZkLYQQbT+5mDnsfKk1d2SdPbJnZ+joZBYA8ParNmJzItzGEa7OlByykHVRMplUPQQi5pC0wBySasyg+6qHPQXWtke2VJZ4cqxSyF6hUSEL1JYXt+suWeaw8y21R3Yl1VOLFx32NJ0rAgCG4+cupXebKTlkIesiXZbG0PrGHJIOmENSjRl032qHPTkd28UOT2SQK5axNRHGQCzo7iDXKBaqjL1dHVnmUK2pbBG5Fvc8p3Jr68jGQn74ROV/H8W65fVTmUoh65zI7SVTcshC1kX9/e7fA0W0GuaQdMAckmrMoPuq98gud/3OMntkH7WXFV+xWa9uLADE29yRZQ7VOTqZxTv+7SB+5+tPYzpbbPrrrPWwJyHEkicXT2XVFbKm5JCFrItMadtTZ2MOSQfMIanGDLpvuaXFzh7Z/DJLix9zDnrSbFkxUFtanOXS4o62UCrjw/eNomBJJDNF/L/3vHBWd3QtqntkGzzsCajtk3VOLi5YZaQXLPjE2r5Ou5iSQxayLurp6VE9BCLmkLTAHJJqzKC7ylJWlw6Hl71+p/L86fQCPv7zk/jXR8fw4+dm8PREBgLAZSP63W3Z7B5ZKSV+dGQa777jadx7dLr6OHOoxmd/cRrHZ/PYkghjsCuIp8Yz+MQDp5r6WmvdIwvU7ZO1/6zTEe6PBuFTsMzXlBzyHlkXWRbvHSP1mEPSAXNIqjGD7loolSFRKWL9vrN/MF982NMn9p/EgyfSZ71mz2DU0+tHGtXMqcVTmSL+4afHq+/x7kOTuGF3ZSknc+i9A6fSuPNgEn4BvO/6HShLif/2rSP41tOT2DMQxU17B9f09dZ6ajEAdEfOXlo8na18DVV7wk3JITuyLspkMqqHQMQckhaYQ1KNGXRX9eqdwLk/WtYXsqfTC3joRBpBv8CvXboBL92ewJ7BKH7jcj2vA2l0j6xVljg4Po9PP3gK777jaTx4Il095OdwMlNdVs0cemt+oYSP3n8cAPCbV27E+UNd2Lshht+7bisA4J/2n8T8otOEV2KVZbWrupZfvCw+udjZH9uvYH8sYE4O9fvVl0FGRkZUD4GIOSQtMIekGjPorur+2ODyhWy+VMY3DyUhAVx/Xh/e85LNXg6xKY3skf3u4Sl8/uHTmMnVCqKXbO3B71+3FX/xg+dxdCqHpycyuGJTN3PosW89M4nJbBF7h7rw1rpflvzy+QO448kJHJvJ4/RcAeeHGyuJ5hZKkAC6w34EfI0vCU4s2iOr8qAnwJz5kB1ZF42NjakeAhFzSFpgDkk1ZtBdzpUmSxWyAZ9AwCdQlpWiDwBuvmjI0/E1q5GlxV97YhwzuRKG4yHccskQ/ucb9uCDrzkPg7EQLrX3/T5pn8zMHHqnLCW+Z+ftt64cOWfJ+1Cscn+rcw1OI5pZVgygdmqxJoWsKTlkR9ZFwaBed6HR+sQckg6YQ1KNGXSXs7Q4EvAv+Xw44EOpYCFbLOPCDV04f6jLy+E1rZHDnpzi5p/edME5Bc6lI3HceTCJJ8cqhSxz6J0nzszjdLqAwVgQV20+93Ajp4icWsNVPM0Wsov3yKpeWmxKDtmRdVEikVA9BCLmkLTAHJJqzKC7VlpaDNROLgaAN3ZINxao78gufVVLqSwxt2BBoLaftt4lIzEAwNMTGRStMnPoIaf7/9rzB87pxgK1g5bWcqfsWu+QdSx3avFAl5qeoik5ZCHrosnJSdVDIGIOSQvMIanGDLorV1y5kHX2yfZGAnjFzl7PxtWqeLWQXfpAoLm6g3+WKpZ6o0Fs642gYEk8O5llDj2Szpfw02OzEKjsh11KUx3ZXJOFrP36uUUdWVVLi03JIQtZF5ny2w7qbMwh6YA5JNWYQXc5e2QjwaWXFkcClSLv9RcOIuTvnB8/V+vIpuxTaJ2O21IutbuyT47NM4ceuefoNIqWxFVbujHcHVryNa0sLV7LHbIAkHD2yC4s7siqKWRNyWHnzCQdqFAoqB4CEXNIWmAOSTVm0F3O9TJLXb8DAC/b3ovtvRH8pwvXdmenaqvtka126KLLFza1A58yzKEHpJS1ZcUXLN2NBWpF5OKlxflSGf/y6BiSmXO/V9U9sit8v5fSHaktLV4olTG3YCHgE8ruTjYlhzzsyUW5XE71EIiYQ9ICc0iqMYPuylUPe1q6kH37VRvx9qs2ejmktqi/fqcsJXzi7OXDTkc2scL1LZfYhezB8Xlksst3bqk9nklmcWwmj0QkgJduW77zuFxH9gfPTuGLj5zB6fQC/uSV2896rvk9srWlxZMZ56CnwDl58oop8yE7si4y5Y4m6mzMIemAOSTVmEF3rXT9Tifz+wSiQR8kasV6Pacju1JnbUM8hJHuELLFMnLhztkf3Kl+eGQaAHDjnn4EV1jG3hsNwCeA2VwJpbKsPn5idgEAcNA+abpes6cW+30CsZAfEsDx2TwAoD+q7uRgU+ZDs2YbzZhyRxN1NuaQdMAckmrMoLucU4uX2yPbyWLB5e+STdmH96y2Z9JZXrz/6HibR0f1pJR4YDQFALh+V9+Kr/X7BHojAUgAM7laV3ZsrlLInpkrnLPs2PnFxVr3yAK1fdQvTFe6oar2xwLmzIcsZF0UCi29uZzIS8wh6YA5JNWYQXflVzm1uJPF7AJkfmGJQraBjixQK2SfSy1/Hy217uhUDpPZIga6gtgzEF319c49rlOZWsF6Zq62f/TQeOas1ze7RxaoZeSFGbuQjakrZE2ZD82bbTTS3d2teghEzCFpgTkk1ZhBd1WXFi+zR7aTVTuyxXOLUOcU2tWWmjqF7DPTRVh1y1ipvfbb3dhrt/VANLD/dPE+2bKU1Y4sAByaqBWyE/MFTOdKiAR86GtiWbCzT/bYdP6sv1sFU+ZD82YbjUxNTakeAhFzSFpgDkk1ZtBd1VOLDVxaHF+pI9vgnslNPSFs7A5hvlDG4WS2/YMkAMADxyuF7Eu3N3a9jNMVdQrZmWwJBav2i4aD47V9sk6RfPWWbgSWuDN4NT32ycUnUuoLWVPmQxayLurrW3ltPpEXmEPSAXNIqjGD7qqeWmzi0uLQCntkG1xqKoTAi7f2AAB+cTLd5hESACQzBRydyiEc8OFFGxvrOC7uyJ6xu7FbEmEIAEcmcyjYv6T5+ejaiuTFnI6s05DvV1jImjIfmjfbaMSUo62pszGHpAPmkFRjBt212j2ynayhQnaF63ccL95iF7InWMi64cHjlf+uV23uRqjBHC6+S9YpZHcPRLGjL4JSWeLZySzmF0p44swcfAJ4ydbmCtnuRV17lR1ZU+ZD3iPronw+r3oIRMwhaYE5JNWYQXflTD7saZlCVkq5psN/Lt/UjYAPeHYyi5lsEX0KCxkT7W+iY3pORzZdOehpY08YsZAfL8zkcWg8g2SmAEsCl43EVz3YazmJ8NnL7lUWsqbMh+bNNhox5Y4m6mzMIemAOSTVmEF31e6RNXCPrF3Izi8qZPOlMoqWRNgvEGmgAxgJ+HDZSAwA8PApdmXbKVe08NjpOQgA19hLuBuxuCPrHPS0sTuMi4crB3QdHM9UlxW/bEdz3Vjg7JOtgz6B7rC6/62YMh+ykHWRKXc0UWdjDkkHzCGpxgy6y1la3EhB12mW68jO5hu7eqfe+d2VDZIPcXlxWz1yag7FssSFG2JrOlG41pGtfC+dq3c2dodw0XDllw4Hx+ery8Gb3R8L1PbIApX9sY2cquwWU+ZD82YbjUQiEdVDIGIOSQvMIanGDLprPS4tTjd4YnG9qzZVunwHTs3xGp42esDumL5kW+PdWKCyJNwnKnudC1YZZ9J2R7YnjI3dIfRFA0gvWMgWy9jZF8HG7nDTY3ROLQbULisGzJkPzZttNBKNrn4RM5HbmEPSAXNIqjGD7ilaZZTKEgGfQNBv3o+WsVDlPS0uZBu9eqfezqFubOoJY27BwjPJzOp/gBrytH3f69Vb1lbI+oSonh48lq7cExvwCQzYHdOLNsSqr22lGwuc3bl3rv1RxZT50LzZRiMzMzOqh0DEHJIWmENSjRl0j8ndWACIhyoFyOI9ss0UsjMzM9XTi7m8uH2cw5pGukNr/rNOd9S5M3Y4HoLfvif24uFaIfuy7b0tjfGspcVrWP7sBlPmQ09mHCHEBUKIx+r+SQsh/kAI0S+E+KEQ4oj97z779UII8Y9CiKNCiCeEEFd6Mc52GxgYUD0EIuaQtMAckmrMoHtM3h8LrNSRrXy+lkJ2YGCgehgRr+Fpj2yhsvQ35BfVg7nWwilknxqvdHU39tSK4UtGKkvBB2NB7BlsrYsZDvgQ9lcK5IGY2otjTJkPPZlxpJSHpZQvklK+CMBVALIA7gTwPgD3SCn3ALjH/hwAbgKwx/7nPQA+4cU4221ubk71EIiYQ9ICc0iqMYPuMfnEYqDWkW3H0uK5uTlctjGOkF/g6FSuus+Wmjedq3RjB5o8QKl/UUd2pG4f7N4NMfzhK7bhz/ftbMvhTM5dsqr3yJoyH6r41dk+AM9JKUcB3AzgC/bjXwDwJvvjmwF8UVY8AKBXCLHR+6G2plAoqB4CEXNIWmAOSTVm0D2mLy3uWqYjm27i1OJCoYBwwIcN8UrXbzbHQrZVkxm7kG1y36lTVJ5O104srnfTBQO4sG6vbCucX3qoXlpsynyoYsZ5C4Db7Y+HpZRn7I/HAAzbH28GcKLuz5y0H+soptzRRJ2NOSQdMIekGjPonpzhS4sjAR/8AihYEgWrXH3cuX6ndw2FrJPD5e6mpbVz9sc22+Vc/OdaOZl4NTddMIDLRuLVq31UMWU+9HSBthAiBOCNAN6/+DkppRRCrOkc8omJCdx6660IBAKwLAu33HILbrvtNoyNjSEWi8Hv9yOdTmNoaAjT09OQUmJoaAjj4+OIxytr3ufn5zE8PIxkMgkhBPr7+5FMJtHT0wPLspDJZDAyMoKxsTEEg0EkEglMTk4ikUigUCggl8tVnw+FQuju7sbU1BT6+vpw8uRJxGKx6vORSATRaBQzMzMYGBjA3NwcCoVC9floNIpQKIRUKoXBwUGkUikUi8Xq8zq8p1wuh3w+z/fUQe/p8OHDGB4eNuo9mfh9Mv09HTt2DOedd55R78nE75PJ72l0dBTxeNyo96TL92l2rlKUBVDGxMSEEe9p8fcpGhCYL0ocfn4Ug/EIuru7kUxV9lRauTRGR1MNvafDhw9jZGQEEV/lR97J9DxOW8xeK+/puVMTAIAoihgdHV3ze7Lmp8+qLwYiAqOjo668pyt7BF59w2ZMnD6p9Pt0/Phx7Nq1qyPmvZUIKb27w0oIcTOA26SUr7E/PwzgeinlGXvp8H1SyguEEJ+0P7598evqv97+/fvl3r17PRv/Wk1MTGDDhg2qh0HrHHNIOmAOSTVm0D33Hp3Gh+8bxat29eH9r9qhejiu+O2vHsTpdAGfffOF2JKo3MH5rq8dwsnUAj79q3uxva+xg4CcHH7o3hdw3/OzeN/123HD7n43h268TzxwEnc+lcS7r9mEN182vPofWOT5qRz+rzufqX5+59svq94dbKpOmg8PHDjwyL59+65e6jmv14C8FbVlxQBwN4B32B+/A8BddY+/3T69+FoAqcVFbCcIhdZ+BDhRuzGHpAPmkFRjBt1j+tJiAOiyD7Kq3yfbzGFPTg6Xu9KH1m4q0+LS4rq9tT1hv/FFLGDOfOjZjCOEiAG4EcC/1z38YQA3CiGOAHi1/TkAfAfA8wCOAvg0gN/1apztlEqlVA+BiDkkLTCHpBoz6B7nsKeIoYc9AUA8bO9pXagUnlZZYn7BggDQHW68kHVyGAufWxhTc5w9soNNHvbUE/YjYN8bu7HHvf2xOjFlPvRsj6yUMgNgYNFjU6icYrz4tRLAbR4NzTWDg4Oqh0DEHJIWmENSjRl0T965fsfgjmzM6cja7zW9UIJEpQjy+xq/lsXJYfWwpwUWsq1q9bAnIQQGuoIYny9gpNuMTuVqTJkPzZ1xNGDKbzuoszGHpAPmkFRjBt1Tu37H3CWZTkc2YxeezVy9A9RyWO3wsiPbEilltZDtb+FuVqcIdvPEYp2YMh+ykHVRsVhUPQQi5pC0wBySasyge5w9sqbeIwsAXaGzlwKnmrh6B6jlkNfvtMfcgoWiJdEV9LX0ixRnWfJ6WVpsynzo6fU7640pdzRRZ2MOSQfMIanGDLonvw4Oe1pceKbylX+vtSPr5DDGpcVtUdsf29qS4DdftgHxsB+v2JFox7C0Z8p8aO6Mo4HV7j4i8gJzSDpgDkk1ZtA91T2yBi8tjlU7spWivZkTi4FaDuMhHvbUDrX9sa315i4YiuEPrtuG+BoO7upkpsyHLGRdFIvFVA+BiDkkLTCHpBoz6J7aHllzf6ysFZ6VArbZQtbJIffItkerBz2tV6bMh+bOOBrw+839zSR1DuaQdMAckmrMoHuqhazBS4udjmzSvrO02cOenBzWTi0utWuI61Krd8iuV6bMh+bOOBpIp9Oqh0DEHJIWmENSjRl0T75U6SqafI/shRtiCPsFHj8zj0PjGcw2ediTk8NY3Z7byq2T1IxJpyPb4h7Z9caU+dDcGUcDQ0NDqodAxBySFphDUo0ZdM96uH6nvyuIWy7dAAD41IOnqkuLeyJre89ODoN+H8IBH8qydlgWrR2XFjfHlPmQhayLpqenVQ+BiDkkLTCHpBoz6J71sLQYAH79smEkIgEcmsjgyTPzAIDeyNoKqPoc8gqe1k2zkG2KKfOh2TOOYlwqQjpgDkkHzCGpxgy6x7lH1uSlxUBlOfDbrqxcW1IsV/K01o5sfQ7jvIKnZdwj2xxT5kOzZxzFTGnbU2djDkkHzCGpxgy6wypLLJTKEADChndkAeB1ewexuSdc/XytpxbX5zDGjmxLrLLEdK5SyPa3eP3OemPKfGj+jKPQ+Pi46iEQMYekBeaQVGMG3bFQ1431CaF4NO4L+ATe9eJNACqFe2SNxXt9DrvD7Mi2YjZfQllWfpkQ9LOkWQtT5kP++sJF8Xhc9RCImEPSAnNIqjGD7nCWFZu+P7bedTsSeNuVIxjoCkKssXivz2GsejctC9lm8KCn5pkyH7KQJSIiIqKm5IvO1Tvmnli8mBACb7tyY8tfJx7m0uJWcH8srZ9fnykwPz+veghEzCFpgTkk1ZhBd9Su3uGPlI2ozyH3yLaGHdnmmTIfctZx0fDwsOohEDGHpAXmkFRjBt2xHpcWt6I+h7VTi0uqhtPRnEJ2MMZCdq1MmQ8567gomUyqHgIRc0haYA5JNWbQHbnq0mL+SNmI+hzGw5Udftwj2xxnaXE/O7JrZsp8yFnHRWs9AIDIDcwh6YA5JNWYQXfk7aXFkcD62SPbivoc8h7Z1nBpcfNMmQ9ZyLqov79f9RCImEPSAnNIqjGD7qguLWZHtiH1OYxzj2xLqoUslxavmSnzIWcdF5nStqfOxhySDphDUo0ZdAcPe1qb+hzGwrx+pxXVPbLsyK6ZKfMhZx0X9fT0qB4CEXNIWmAOSTVm0B3OQUU87Kkx9Tl0OrJzXFq8ZkWrjFS+BJ8AEhHeJrpWpsyHnHVcZFmcmEg95pB0wBySasxg+2UKFr71zCQAYGd/VPFoOkN9Dp1Clh3ZtUvnK//NeiMB+H1m7Pf0kinzIQtZF2UyGdVDIGIOSQvMIanGDLbf5x8+g+lsCRdu6ML1u/pUD6cj1OcwVlfIlqWsPu6cBE3LS+UrKwG62Y1tiinzIQtZF42MjKgeAhFzSFpgDkk1ZrC9nk1m8c2nk/AJ4PdevhU+Q05BdVt9Dv0+ga6gDxK1vcaPnprDzV94Arc/NqZohJ0hZS9pT4RZyDbDlPlwzYWsEMInhLhSCLHVjQGZZGyMkxCpxxySDphDUo0ZbB+rLPGxnx1HWQK3XLIBuwa6VA+pYyzOYWzRFTwPn0wDAP710TFMZgreDq6DpO2ObA87sk0xZT5ctZAVQvy5EOKX7I99AO4DcC+Aw0KI97g7vM4WDPIUNVKPOSQdMIekGjPYPt9+ZhJHJnMYigXxtivN6Ox4ZXEOa1fwVAqz47N5AMCCJfHFR8woNtzgLC1ORHh/cTNMmQ8b6ci+G8BB++PXAugFsAHAiwH8qUvjMkIikVA9BCLmkLTAHJJqzGD73P/8LADgd67ZhGiQhcRaLM5h3F4a63RknUIWAH5wZArHZnLeDa6DpO3/XuzINseU+XDZQlYI8TkhxOcADAP4O/vjvwYgAfxvAP8dwIAQ4rNCiM96MtoOMzk5qXoIRMwhaYE5JNWYwfaZylaWvO4Z5JLitVqcw1pH1sJCqYyxuQJ8ArjpggGUJfDPD51WMUztpasdWRayzTBlPlz2uy+lfCcACCFeBeDDUspnhRAHAPy+lPI++7l9Usp3eTLSDmTKbzuoszGHpAPmkFRjBttDSompTBEA0B81Y3milxbnMBaunVx8MpWHBLC5J4zfvnoj7nt+Bg+eSOOJM3O4bGO3gtHqy1la3MPDnppiynzYyNLiTwL4uRDiGQAWgPsBQAhxDYCjLo6t4xUK3KRP6jGHpAPmkFRjBtsjU7CwYElEgz50hbiseK0W57C+I+ssK97eG0FfNIg3XzYMALj9sXFvB9kBaoc9MYPNMGU+XLWQlVL+DYA3AHgvgFdKWb3oygLwRy6OrePlctzXQOoxh6QD5pBUYwbbYzpbKSAGutiNbcbiHMbrTi0enakUstt6IwCAffbdvCdTCx6OsDOkuLS4JabMhw1996WUDyzx2CPtH45ZTLmjiTobc0g6YA5JNWawPaaylWXFLGSbsziH8XCtIztpL9ne1lcpZJ0izSnaqCa9wOt3WmHKfLjme2Spcabc0USdjTkkHTCHpBoz2B5OIdvPQrYpi3O41NJipyMbDfoQ9AvkS2UslMreDlRz6Xzl1OIE98g2xZT5kIWsi0KhkOohEDGHpAXmkFRjBtuDHdnWLM5hzC5kU7kSTqXyEAC22oWsEIJd2SUslMrIl8oI+gSiQZYyzTBlPuR330Xd3TxhjtRjDkkHzCGpxgy2BzuyrVmcQ6cj++xkFpYENsRDiARqP5732oXsLAvZqvplxUIIxaPpTKbMhyxkXTQ1NaV6CETMIWmBOSTVmMH2YEe2NYtz6OyRdTqu2+39sQ5nD2gqx0LWUT2xOMwTi5tlyny4aiErhLhICPFVIcQZIcSC/e+vCiEu8mKAnayvr0/1EIiYQ9ICc0iqMYPtMc1CtiWLcxhbdIWRsz/WwaXF56reIcuDnppmyny4YiErhNgD4AEAUQB/CuCNAP7M/vwBIcQFro+wg5lytDV1NuaQdMAckmrMYHuwI9uaxTnsXnRY0eJClkuLz5VyDnpiIds0U+bD1RLwfgBfklLetujxzwoh/heA9wF4pysjM0A+n1c9BCLmkLTAHJJqzGDrpJR1e2RZRDRjcQ6jQR8EAGl/zo7s6uZ49U7LTJkPV0vAKwG8epnn/ieAH7d3OGYx5Y4m6mzMIemAOSTVmMHWzS1YKFoSXUEfokHuT2zG4hz6hEAs5Md8odJl3NYbPuv5RJR7ZBdzinp2ZJtnyny42h7ZIQDHlnnuOIDBto7GMKbc0USdjTkkHTCHpBoz2DouK27dUjl09sn2dwUQX7TUmB3Zc/Gwp9aZMh+uetiTlFIu83gZtZUQtIRIJLL6i4hcxhySDphDUo0ZbF21kI2xkG3WUjl0Ti7e3nvuc70sZM/BjmzrTJkPV0tAlxDiJ8s8J1A59ImWEY3yPw+pxxySDphDUo0ZbB1PLG7dUjl07pJdvD8WqBVrPOypxjnsiXtkm2fKfLhaAm5d5fnPtGsgJpqZmUFPT4/qYdA6xxySDphDUo0ZbB2XFrduqRw6hezWFQpZdmRreNhT60yZD1dMgJTyC14NxEQDAwOqh0DEHJIWmENSjRls3XT1xGIWss1aKoe/fMEA5gsWXr6j95zn4mE/fALIFCwUrTKC/lV3BRqvurQ4zEK2WabMh6vdI3uVEOKSus+HhBBfFkI8LoT430KIeKN/kRCiVwjxdSHEM0KIp4UQLxVC9AshfiiEOGL/u89+rRBC/KMQ4qgQ4gkhxJXNv0V15ubmVA+BiDkkLTCHpBoz2Dp2ZFu3VA6v3ZbA371+z5L/XX1CVLuyaXtJ7XpXPewpwsOemmXKfLjar3X+AUD9+cyfAXA+gE8BuATA367h7/oYgO9JKfcCuBzA06jcQ3uPlHIPgHvszwHgJgB77H/eA+ATa/h7tFEoFFQPgYg5JC0wh6QaM9g6FrKt58JM0QAAIABJREFUayaHtX2yxXYPp+PkS2UsWBIhv0AkwO50s0yZD1dLwIUA/gOodFRRKTB/U0r5cQBvBfCfGvlLhBAJAL8E4J8BQEpZkFLOArgZgLN8+QsA3mR/fDOAL8qKBwD0CiE2NvyuNGHKHU3U2ZhD0gFzSKoxg61jIdu6ZnLIfbI1tW5sAEIIxaPpXKbMh6stLg8AcEr2awGMSSmfBQAp5Qm7uG3ETgBJAJ8TQlwO4BEAvw9gWEp5xn7NGIBh++PNAE7U/fmT9mNn6h7DxMQEbr31VgQCAViWhVtuuQW33XYbxsbGEIvF4Pf7kU6nMTQ0hOnpaUgpMTQ0hPHxccTjlVXR8/PzGB4eRjKZhBAC/f39SCaT6OnpgWVZyGQyGBkZwdjYGILBIBKJBCYnJ5FIJFAoFJDL5arPh0IhdHd3Y2pqCn19fTh58iRisVj1+Ugkgmg0ipmZGQwMDGBubg6FQqH6fDQaRSgUQiqVwuDgIFKpFIrFYvV5Hd5TLpdDPp/ne+qg93T48GEMDw8b9Z5M/D6Z/p6OHTuG8847z6j3ZOL3yeT3NDo6ing8btR78vL7ND4xgalMpZCdnzyDhfDGjn9PKr5Phw8fxsjIyJreU0hW/rsn0zmMlma0e09efp+eOZMCAEREGadPnzbiPan4Ph0/fhy7du3qiPe0ErHMNbGVJ4X4GYCPSSm/KoT4PICylPJd9nObATwopdyy4t9Qee3VAB4A8HIp5YNCiI8BSAP4r1LK3rrXzUgp+4QQ3wLwYSnlT+3H7wHwXinlw/Vfd//+/XLv3r2r/fXKTExMYMOGDaqHQescc0g6YA5JNWawNbO5In79y0+hO+zHHW+7TPVwOlYzOfynn5/A3Ycm8V+u3YxfuWR9Z/iRk2m8/3vP4YpNcXzkdXtUD6djddJ8eODAgUf27dt39VLPrba0+L0APimEmAbwegAfqXvuNwD8rMExnARwUkr5oP351wFcCWDcWTJs/3vCfv4UgK11f36L/VhHCYVCqodAxBySFphDUo0ZbM10trKksz/KZcWtaCaHXFpck+bVO21hyny4YiFrd0S3AbgRwHlSysN1T38bwB828pdIKccAnBBCXGA/tA/AIQB3A3iH/dg7ANxlf3w3gLfbpxdfCyBVtwS5Y6RSKdVDIGIOSQvMIanGDLZmilfvtEUzOWQhW5OyT25OsJBtiSnz4YopEEL4AGQAPOp8LqUsA8CiorYR/xXAl4UQIQDPA3gnKoX0V4UQtwIYBfDr9mu/A+B1AI4CyNqv7TiDg4Oqh0DEHJIWmENSjRlsTfWgpxgL2VY0k8NeFrJV1cOeeIdsS0yZD1dLQQnAWZtohRBlVA5iuh3AB6WUC438RVLKxwAstb553xKvlQBua+Tr6iyVSiEWi6keBq1zzCHpgDkk1ZjB1vDE4vZoJoe163dYyDrFPDuyrTFlPlwtBTuXeCwI4DwAfwbgf6B29ystUizyvi9SjzkkHTCHpBoz2BoWsu3RTA4TUbsjm2MhW3/9DjXPlPlwxRRIKUeXeeqoEOIpVA57YiG7DFPuaKLOxhySDphDUo0ZbE1tjywLiFbwHtnWVA97CvsVj6SzmTIfrnZq8UrGADR6j+y6tNrdR0ReYA5JB8whqcYMtmaaHdm2aCaHPeEABIC5BQtWeflrM9cDHvbUHqbMh60UsjcAeK5dAzGRCWvPqfMxh6QD5pBUYwZbw6XF7dFMDv0+ge6wHxK1juR6xaXF7WHKfLjaqcUfXOLhIIAdqNwr+1YXxmQMv5/LHkg95pB0wBySasxg806l8pjMFBHyC16/06Jmc5iIBJBesJDKl9C3Tu/ylVIixXtk28KU+XC1juzWJf4ZROUO2GullN92d3idLZ1Oqx4CEXNIWmAOSTVmsHl3HZoEANywqx8hfyuL+ajZHPLAJyBfKqNoSYQDPkQCzGErTJkPVzvsqSPvb9XF0NCQ6iEQMYekBeaQVGMGm5MtWPjBs1MAgJsvNuPuSZWazSHvkq2/eseMbqJKpsyH/HWGi6anp1UPgYg5JC0wh6QaM9icHx6ZRrZYxqUjcewa6FI9nI7XbA55lyyQXqgc9NQT5rLiVpkyHzIJLpJyfZ8sR3pgDkkHzCGpxgwCC6Uy7n1uBt88lIRVlvibm3avuOe1LCXuOpQEALzpYjM6OKo1m0NewQNMZgoAeGJxO5gyHzIJLjKlbU+djTkkHTCHpNp6z+CdT03gXx8bP6sQ+uCPXsDfvn73svteD5yaw8nUAoZiQbxse8KroRqt2RyykAWeGssAAM4f4sqAVpkyH3JpsYvGx8dVD4GIOSQtMIek2nrO4HNTWXzigVNI5UvYPRDFH1y3FUOxIA5NZPC/fnZi2e7MNw5WurFvvGgIfp/wcsjGajaHvTzsCU+cmQcAXL4xrngknc+U+bChQlZUvFsIca8Q4gn7sV8SQvy6u8PrbPE4/4dG6jGHpAPmkFRbzxl85OQcAGDf7j58/E0X4HV7B/E/bjwPYb/A95+drhas9Y5MZvHQiTRCfoGbLhjwesjGajaH632PbKZg4ehUFgGfwIUbzLgDVSVT5sNGO7IfBHArgE8B2GY/dhLAe90YFBERERG1xyOnKoXsNVsTEKLSWd092IX//srtAIBPPngKD51IVV9fsMr42/tHAQCvv3CQd3ZqYL0vLX5qbB5lCVww1IVokKcWU0WjhexvA3iDlPIrAJz1Jy8AOM+NQZlifn5e9RCImEPSAnNIqq3XDC6UynhqvPLer9h0dhfmlef14TevGEFZAn91zzE8m8wCAL70yBmMzuSxuSeMd169yfMxm6zZHPZGKodyrddC9nF7WfFlI2Z0ElUzZT5stJD1A3DesVPIxuseoyUMDw+rHgIRc0haYA5JtfWawafG5lG0JHYPRNEbPfeE4rdfOYJX7+nHQqmM/+f7z+FHR6bxtScn4BPAH79yOyIBHqfSTs3msMe+OzWVL6FsyImza+Hsj72M+2PbwpT5sNHZ6TsA/j8hRBio7JkF8FcAvunWwEyQTJ6754TIa8wh6YA5JNXWawYP2MuKr9zcveTzQgj84XVbceXmbszmS/jb+0dRlsCbLxvGRcPci9huzeYw6PdhMBZEWQJPnllffSRnf6xfgJlsE1Pmw0YL2T8CsBFACkAClU7sdnCP7IqcfShEKjGHpAPmkFRbrxk8cHrlQhaoFEl/sW8ndg1EAQA7+iJ425UjnoxvvWklh689v3Lo1p1LHM5lstr+2Bj3x7aJKfNhQ7v3pZRpAL8ihNiASgF7Qko55urIDNDf3696CETMIWmBOSTV1mMGZ7JFPDeVQ8gvcMnwyksyu0J+fOi1u/DdZ6awb3f/snfLUmtayeEbLhzEVx4fx/7RFM7MLWBjd7iNI9PX47x2p+1MmQ8bvX7nNUKI86WUE1LKX0gpx4QQFwghbnR7gJ3MlLY9dTbmkHTAHJJq6zGDj9rd2EtG4gg1sNe1LxrEf75iBMPdIbeHtm61ksP+riBeeV4vJIC711FXlvtj28+U+bDRX7d9HMDcosfm7MdpGT09PaqHQMQckhaYQ1JtPWZwtf2x5L1Wc/grF28AAHzv2WnkilY7hqQ17o91hynzYaOF7AYp5ZlFj50BwA0UK7As8ycY0h9zSDpgDkm19ZZBKWW1kL2Khaw2Ws3h+UNduGhDDJmChR8emW7TqPT1+Jk57o91gSnzYaOF7PNCiBsWPXY9KnfJ0jIymYzqIRAxh6QF5pBUW28ZPDG7gMlsEb2RAHb2R1UPh2ztyOGvXDIEAPjGwaSxV/FkChY++4vT+NC9xwAAV/CXMW1lynzY0GFPAD4A4N+FEP8M4DkAuwC80/6HljEywoY1qccckg6YQ1JtvWXwyXH7gJxNcfgMOaHUBO3I4XU7ejEYC+JkagFPT2Rw8SoHeXWax07P4UP3HsNsvgQAuP68Xrz50g2KR2UWU+bDhjqyUsq7ALwGQAzA6+1//7L9OC1jbIwHO5N6zCHpgDkk1dZbBo/P5AGgeqUO6aEdOfT7BPYOdQEAprLFlr+ebj714CnM5ku4aEMMH3vj+fjTG3aiK8Rlxe1kynzYaEcWUsqHADzk4liMEwwGVQ+BiDkkLTCHpNp6y+DobKWQ3d7LQlYn7cphzC7sMoVyW76eLhZKZTw/nYNPAH9z0y7ui3WJKfPhsoWsEOLPpJR/bX/8weVeJ6X8CzcGZoJEIqF6CETMIWmBOSTV1lsGnY7stt6I4pFQvXblsKtayLp7aM9UpojZfBG7Brpc/Xscz03lUJbAjr4Ii1gXmTIfrrS0eEvdx1uX+WfLEn+ObJOTk6qHQMQckhaYQ1KtkzO4UCrjC4+cwbPJbEOvzxQsTGaLCPkFRngnrFbalcNY0JtC9gM/eh63feMwnpnw5nCgZycrGb9gyJvCeb3q5Pmw3rIdWSnlfwEAIYQPwJcA/ExKueDVwExgym87qLMxh6QD5pBU6+QMfuNgEl9+dAy/OJHGP73pglVff9xeVry1NwK/jwc96aRdOYyH3S9kF0plHJnMoiyBzzx0Gn/3+t0QLh8c9myyUjCfP8hC1k2dPB/WW/WwJyllGcBdLGLXrlAoqB4CEXNIWmAOSbVOzeD/Ye/O4xu76vv/v45kyZYl7/t4Zjz7TCaTZTIhG9knCQlLgEDZIaWhC4RHWVoaKJRSSlP4tiXQX2kLLZRQ1hAICZBQluxkssxkktlXj+3xbsu2ZO3b+f0hecvYHo9HV/fq+vN8PPKILcnSufE7R/7obIl0hgf2DQLZ0aqh8Omvo1OmFVtWvnLoLcDU4q6xGJnc6T57+kM8fzJo2GtNODw0MSLrNfy1lrJi7Q9faaHnyD6plLrM0JbYUDQaNbsJQkgOhSVIDoXZijWDvzs6wkg0Nfn9js7AaX+mczR7rW1SyFpOvnJYiKnFJ0aybS0ryZYL//1CL+mMcefWhhNpugNxXA7F6lrJrpGKtT98pYUWsp3AI0qpbyul/l4p9fmJf4xsXLGzyxlNorhJDoUVSA6F2Yoxgxmt+fHe7GjsxcsrAHhmIYVsbmrxyhopBqwmXzksxIjsRCF725YGmnxuOkdj/OboiGGvd3Q4ggbW1HlwORdaoojFKMb+cDYLTYkH+BmgyW7wJJs9LYBdzmgSxU1yKKxAcijMVowZfKYzQHcgTpPPzSeubsOh4OXecULx1Lw/1zV59I4UslaTrxwWpJDNTVHf0FDO+y9uAeDeXX3EUsYc+TOxmZmsjzVeMfaHs1nQObJa6/cb3RA7crtlp0BhPsmhsALJoTBbsWVQa819Lw8A8JbzGqkpd7Glycee/hAvdAe5bm3trD8XSaQZDCVxORTLKksL2WSxAPnKYSEK2Y7ciOzqGg9NFW7u3zvIMX+Uhw8Nc9uWxry/3mHZsbhgiq0/nMuCx+2VUuuVUp9WSn0t9+/1RjbMDioqKsxughCSQ2EJkkNhtmLL4L6BMIeGIlSWOnnNhmzResWq7E6jz3TMPb34ZCA7ira8qlR2LLagfOXQ687+CW9UIRuIpRiJpigrcdBU4cahFO/emp2O+uD+oXnXysZSGaLJM2/X5IisFLKGK7b+cC4LKmSVUu8CdgPnA2HgPODF3O1iDn6/3+wmCCE5FJYgORRmK7YMPt0xBsAtm+rx5Db2ubwtW8i+0B0kkZ59eufkjsWyPtaS8pXDiRHZUCKN1vnfgGlifeyqmjIcuSN3LltZRUuFm77xBM92zf5hitaaux4+yh/9+OAZTUEeiyYZCCUoK3Gwokqya7Ri6w/nstAR2S8Ar9Vav11r/Vda63cArwXuNq5pxa+mpsbsJgghORSWIDkUZiu2DPYHs8djrK/3TN7WUlHKmtoyIskML/eGZv05WR9rbfnKocvpwO1UZDSGrFmdKGRX107lz+lQvOncBgAe2Dc068/1BuMcHIzgjyTpzmVxIY7kphWvry+XmQQFUGz94VwWWshWADtecduzgBzyNA+7bG0tipvkUFiB5FCYrdgy2D8eB6C5YuY61yvaqgF4pnNs1p+TEVlry2cOfblR2UjCiEI2m6PphSzATRvqKHc52NMf4liu+JxuZ/f45Ne9wfiCX+/w5EZPntM8UuRDsfWHc1loIftl4G6lVBmAUsoD/EPudjGHWGzhn0QJYRTJobACyaEwWzFlUGtNfyg7Itvsm7kpy8T04seOj/JiT/CUn5URWWvLZw7LDdzw6cToxEZPM3PkdTt5zcY6AB7Yf+qo7M7uqUz2nEEhO7U+VsbICqGY+sP5LLSQ/RDwUSColBoAAsDHgA8qpbom/jGqkcXKLmc0ieImORRWIDkUZiumDAbjaaLJDOUuBxWlzhn3ravzcM3qaiLJDH/9q+M8dGCqmIilMvSPJ3AqZMdii8pnDqevk82njNaTI/uvHJEFeNPmBhTw+PFRRiLJyduT6Qwv901NeV/oiKzWenJqsexYXBjF1B/OZ6GF7HuAG4Abgbfl/n0D8N5X/COmscsZTaK4SQ6FFUgOhdmKKYPTpxUrNXO9oFKKT12/irdf0ERGw7890809T3URjKXoHouhgdaqMlzOBR9MIQoonzk06gie/vEEsVSG2vISKstOPamzpbKUy9uqSGY0Pz84PHn7gYEwsVSGiSWuPYGFFbJjsRSj0RTlLgctFfY4Fsbqiqk/nM9Cz5F9wuiG2FFZmUzrEeaTHAorkBwKsxVTBvvHc9OK5/ij3qEUd7xqGW3VZdzzdBePHPbzePsom3LTMttkfaxl5TOHRhWyJ6adHzuXt57XyDOdAR7cP8Rbz2vE63aysye7PvbVq6p56sTYgkdkJ0Z/V9V4TvngRhijmPrD+cjHdQbyeGTBujCf5FBYgeRQmK2YMtg3OSI7/+jUDetr+eobNnDx8gqiyQy7e7OFhKyPta585nBis6fwIs5snc+JeaYVT9jS7OOCFh+hRJqf5dbK7sqtj715Qx0up2IkmlrQebKTG5RJbgummPrD+Ugha6DR0VGzmyCE5FBYguRQmK2YMjgxIttScfp1ruvqy7n75nV89dYNvGp5JVVlJbx6VZXRTRSLlM8cGjUi2zHtDNn5vHtrdp3lT/cN0huMc8wfxe1UnN/im8zuQkZlOyc2KJOZBAVTTP3hfBY0tVgsTl1dndlNEEJyKCxBcijMVkwZPN3U4tmc0+jlH25ea1STRJ7kM4eTuxbH81vIts9yhuxsLmjxsaXZy77+MF/43QkAzmv2UVriYFmlm66xGD3BOGvr5t/AaWJEVgrZwimm/nA+ZzQiq5RyKKVaFvNCSqkOpdRepdRLSqmdudtqlVK/UUodzf27Jne7Ukr9q1LqmFJqj1LqosW8ptnGx8dP/yAhDCY5FFYgORRmK6YMLqaQFcUhnzn0urJ/xudzanEilaE3GMehTj/VVynFe3Kjssf82eJ32/JKAFpzu2afbsMnrTWduaN+pJAtnGLqD+ezoEJWKVWtlPo+EAOO5W67VSn1hTN8veu01hdqrS/Off9J4Hda6/XA73LfA9wCrM/98yfAf5zh61hCIpEwuwlCSA6FJUgOhdmKJYPpjGYwd4Zs0wKmFoviks8c+krzP7V4OJIko6He66K05PRlwtZlFWxunDr79eLlFcDU8U+nm1o8FksRjKcpdzmoL3edRcvFmSiW/vB0Fjoi+59kz45tAyaufAfw9rN8/TcC9+a+vhd407Tbv6OzngWqFzsSbCa7nNEkipvkUFiB5FCYrVgy6I8kSWU0NZ4SyhZQSIjiYsQ5svksZMeiKQBqPAsrKpVSvOei7DU1+lyTG421Vk0UsvMXTLJjsTmKpT88nYX2kNuBP9da9wEaQGs9BDSewWtp4NdKqV1KqT/J3daUe06AfqAp93UrcHLaz3bnbisqdjmjSRQ3yaGwAsmhMFuxZFCmFdtbXs+RdWUL2VAeC9lALFvIVs9yfuxctrVW8NfXreKz29dMFqMTI7I9wdi8Pys7FpujWPrD01loSgNAPTBRdKKUWjn9+wW4Umvdo5RqBH6jlDo0/U6ttVZK6TN4PgYHB7njjjsoKSkhnU5z2223ceedd9Lf34/X68XpdBIMBmloaGBkZAStNQ0NDQwMDODz+QAIhUI0NTUxNDSEUora2lqGhoaorKwknU4TDodpbm6mv78fl8tFVVUVw8PDVFVVkUgkiEajk/e73W4qKirw+/3U1NSQSCTo7OycvL+srAyPx8Po6Ch1dXWMj4+TSCQm7/d4PLjdbgKBAPX19QQCAZLJ5OT9VrimaDRKLBaTayqiawqHwwwMDNjqmuz4e7L7NYXDYUKhkK2uyY6/JztfUzwen/GebNVr6hzO/ilUV+ZgYGBgyf2e7H5N4XCYwcHBvFxT0D8GwFgoRnd3d16u6Xh3tsApJXlGf8NurvDgdik6O4eor68nFRyjRMFIJMWR9g5qK32zXlO7P1s4N5Sm8fv9lvk92TF7068pHA4TDoeL4prmo7Q+fe2olPokcCvwaeABsmtY7wYe1Fp/5bRPcOrzfQ4IAX8MXKu17stNHX5ca71RKfX13Nc/yD3+8MTjpj/Pjh079KZNm8705QtmbGyM6upqs5shljjJobACyaEwW7Fk8Du7+vju7n7eeUET73/VMrObI/IsnznsC8a5/b4DNPnc/O87zs3Lc/7gpX7+Z2cfbzu/kQ9ccnaTIe/48QFOBuL8x5s3zrlz8V/84ih7+0PcffNaLs5tFCWMVyz9IcCLL764a/v27RfPdt9CpxZ/CfgR8DXABXwLeBD46kJ+WCnlVUpVTHwN3ATsAx4Cbs897Pbcc5K7/X253YsvAwKvLGKLQSAQMLsJQkgOhSVIDoXZrJTBeCpDOjP7QEJ/SKYW21k+c2jkGtkzmVo8l6kNn2ZfJys7FpvHSv3h2VhQSnV22ParLLBwnUUT8EBu3nwJ8H2t9a+UUi8A9yml7gA6gbflHv8w8FqyOyRHgPcv8nVNVV9fb3YThJAcCkuQHAqzWSWD/eNx/uQnh7h0ZSWfvn71rPcDNFfKjsV2lM8cTi9kM1rjyMNmSWMTa2QXuNnTfFqrSuHk3DsXy47F5rFKf3i2FlTIKqWuAzq01ieUUs1kR2gzwKe01qddLay1bgcumOV2P9mNpF55uwbuXEjbrCwQCOD1ek//QCEMJDkUViA5FGazSgZ3dAaIpTI80T7GLRuDXNQ6czqlbPZkb/nModOhKCtxEEtliCYzk4Xt2RiLJgGo9uRvRHaus2Rlx2LzWKU/PFsLnVr878DEvIUvk51enAG+YUSj7CKZTJrdBCEkh8ISJIfCbFbJ4O7e8cmvv/Fcz4wpxol0Bn84iUNBo1cKWTvKdw7zPb04n1OLW09zlqzsWGweq/SHZ2uhKW3VWncppUqA1zB1nmyvYS2zAbuc0SSKm+RQWIHkUJjNChlMZzR7+kJAtlBoH4nxm6Mj3LyxDoDBUAJNtoh1OmSEyo7ynUOf24k/ksxbITt5/E4+RmSrJo7gmaOQHcsWsrI+tvCs0B/mw0JHZINKqSbgGuCA1jqUu10mtM/DLmc0ieImORRWIDkUZrNCBo8MR4gkM7RWlvJnl2V3hP32zl6iyWwRItOK7S/fOczniGxG68k1slV5GJFt9LopcSj8keRkxqebGJGVQrbwrNAf5sNCC9n/D3gB+B7ZnYsBXg0cmvMnhC3mnoviJzkUViA5FGazQgZ392SnFW9dVsG1a2vY2FDOSDTFj14eAKSQXQryncNyd/ZP+XwUsqF4mozOFscu50JLhLk5HWoyy32v2LlYdiw2lxX6w3xY6K7FX1JKPQCktdbHczf3AB8wrGU24HSe/aJ7Ic6W5FBYgeRQmM0KGZxYH3thqw+HUvzppa18/BdH+f5LA5wYieFyZqcTN1fIjsV2le8c5nNENp/rYye0VpbSHYjTNRZjTZ1n6rVkx2JTWaE/zIcz+bilHWhVSr1TKXU10K613mtQu2whGAya3QQhJIfCEiSHwmxmZzCeynBgMIwCLmypAGBLs48/uWQZpSUOdnQFePLEGCAjsnaW7xz68lnIxvK3Y/GEDQ3lABwaCs+4/bg/OxorOxabw+z+MF8WevzOJuDngAc4CawAYkqpN2itDxrYvqLW0NBgdhOEkBwKS5AcCrOZncH9AyGSac26Og+V00a83np+E9evq+UHL/Xzy0N+UhnN6hrPPM8kilm+czgxIhuy6IjsOY3ZKawHB2cWsnv7s9vtbG6yxxTXYmN2f5gvZ3L8zjeAFVrry7XWy4H/zN0u5jAyMmJ2E4SQHApLkBwKs5mdwd292T/cL1xWccp9teUu7rxiBf/zB5v5l9evnzEFU9hLvnM4UchG8jIim78diyec0+hFAceGoyRSmcnb9/dnC9vzmn15ey2xcGb3h/my0EL2QuDLWms97bav5G4Xc5j5n0sIc0gOhRVIDoXZzM7gS71TGz3NpanCLX/Y21y+czi1RjZzmkee3uSIrCd/a1a9bicra8pIZjRH/REge17yxFTjc2VE1hRm94f5stBCtpfs0TvTXYWcIzsvuwzbi+ImORRWIDkUZjMzg6F4iqPDEUocii3N8of7UpbvHJa7coXsLMfbnKnJEdk8Ti0G2DwxvXggW7weG46SSGvaqstmTLMXhWOX9+SFFrJ/DTyklPqhUupLSqkfAg/lbhdzGBgYMLsJQkgOhSVIDoXZzMzgy30hMho2NZbjcdljt1CxOPnOoa/UgF2L8zi1GKbWyR4YzI7I7sutjz1XPtQxjV3ekxdUyGqtHwIuAvYBFbl/b9NaP2hg24qezyfTg4T5JIfCCiSHwmxmZvDZrgAAF7VWmtYGYQ35zuHkZk/x/O1aXGXUiOxgGK315EZPW5rkfcEsdnlPXnBStdZHgC8Y2BYhhBBCCFtJpDM83ZEtZK9eXW1ya4TdePM5tdigEdnl1aX43E78kSSDoSQHcjsYyzR7cbbmTKpS6n+B066+NU+/AAAgAElEQVQE1lq/L68tspFQKERdXZ3ZzRBLnORQWIHkUJjNrAzu7A4STqRZW+dhZXVZwV9fWEu+c+jN4zmyAYPWyDqU4pxGLy90B/nVET/j8TT1XhdNPjkv2Sx2eU+eL6nHCtYKm2pqajK7CUJIDoUlSA6F2czK4OPHRwG4bk2NKa8vrCXfOZxYI3u2x++kMprxeBqHgorS/G/AdE5TtpB96MAQAFuavCil8v46YmHs8p48Z1K11n9XyIbY0dDQECtWrDC7GWKJkxwKK5AcCrOZkcFoMs2OriAAV6+RacUi/zn0uBwoIJLMkM5onI7FFYcTo7GVpSWLfo75bG4sB2A8t5Z3ixwzZSq7vCfPu9mTUuoKpdSX5rjvi0qpy4xplj3IJ03CCiSHwgokh8JsZmTw2a4g8VSGzY1emitKC/76wnrynUOHUnhc2T/nI2exTnYsmt3oKd/rYydsbPAy/crlvGRz2eU9+XS7Fn8aeHKO+57I3S/mUFtba3YThJAcCkuQHAqzmZHBx9uz04qvkdFYkWNEDvOxTtaojZ4meN1OVtVk14j73E7aamS9uJns8p58ukL2QuBXc9z3G2BbfptjL0NDQ2Y3QQjJobAEyaEwW6EzGIqn2HkyiEPBNbI+VuQYkcO8FLIGbfQ03TlN2V2Kz23y4rDJiGCxsst78ukK2Upgri3FXGTPlBVzqKyU8+KE+SSHwgokh8Jshc7g7zsDJDOa81t81Ja7CvrawrqMyKEvjyOyVWXGZfXGdbX43E5es6H4d8stdnZ5Tz7dxy6HgJuAB2e576bc/WIO6fTZb4UuxNmSHAorkBwKsxUyg4lUhvv3DgJwrYzGimmMyOHUiGxm0c8xOSJr0NRigHObffz0fecb9vxi4ezynny6Edl7gK8rpW5TSjkAlFIOpdRtwH8CXza6gcUsHA6b3QQhJIfCEiSHwmyFzOA3X+ilczRGa2Up162VQlZMMSKH5XkYkQ0YvEZWWItd3pPnTavW+vtKqWbgXqBUKTUM1ANx4G+11j8oQBuLVnNzs9lNEEJyKCxBcijMVqgM7uwO8sD+IZwKPnldGx6XsyCvK4qDETnMzxrZ3K7FBq6RFdZhl/fk043IorX+MtAKvAH4y9y/W3O3i3n09/eb3QQhJIfCEiSHwmyFyGAgluKfn+gE4H3bWtjY4DX8NUVxMSKHE2tkxy28a7GwFru8Jy8orVrrIPB/BrfFdlwu2dxBmE9yKKxAcijMVogMfvXpk4xEU2xp9vK285sMfz1RfIzI4fKq7BnFu7qDvGfr4kbapnYtlr56KbDLe/JpR2TF4lVVVZndBCEkh8ISJIfCbEZn8MhwhKc7xigrcXDXNatwOuR4EXEqI3J41epqyl0O9g+EOTESXdRzyIjs0mKX92QpZA00PDxsdhOEkBwKS5AcCrMZncEfvjQAwOvPqaepYq6TC8VSZ0QOPS4n29fVAvDLQ2f+/LFUhlgqg8upKHdJabAU2OU9WdJqILt82iGKm+RQWIHkUJjNyAx2jcX4fccYLofiLVsaDXsdUfyMyuHrNtUD8NujI0STZ7ZWNjB5hmwJSslMgqXALu/JUsgaKJFImN0EISSHwhIkh8JsRmbwx3sG0MCNG2qp89pj7ZkwhlE5XFPnYXOjl0gyw+PHR8/oZ2XH4qXHLu/JUsgaKBpd3DoFIfJJciisQHIozGZUBgdDCX57dASHQjZ4EqdlZF/4+nOyo7K/OMPpxQcHI4Csj11K7PKeLIWsgexyRpMobpJDYQWSQ2G2hWTwuD+7YdOBgTB9wTjJdOa0P3P/3kHSGq5ZU8OyytJ8NFXYmJF94VWrq6kodXJ0OMqRociCfmZnd5CvP9sNZDMslga7vCdLIWsgu5zRJIqb5FBYgeRQmO10GfzZ/iE++MBhPv/bE3z050e4/b4DvPdH+xmPp+b8mbFokkdyo19vl9FYsQBG9oWlJQ5uWr/wTZ+ODkf4+9+dIK3hrec18poNdYa1TViLXd6TZQ6Bgdxu2bVQmE9yKKxAcijMNlcGtdb84KUBvr2rD4CtyyqIJNN0B+KMRFI8emyUN57bMOvP3rdnkHhac+mKStbUeQxru7APo/vCK1dV85N9Q7TPcgzP/oEQvzs2ikOB06F4/Pgo0WSG69fW8IFLlhnaLmEtdnlPlkLWQBUVFWY3QQjJobAEyaEw22wZ1Frz38/38uO9gyjgo1eu4Jbc7q+PHx/l7sc6+NUR/6yF7Ggkyc8PDAHwvm0thrZd2IfRfWFtbrOx0WjylPu+/mwPh14x5Xjrsgr+4uqVOGS34iXFLu/JUsgayO/34/P5zG6GWOIkh8IKJIfCbK/MoNaaf9/Rw4MHhnAquOvaVVy7dmqN4BWrqqgodXLcH+XYcIR19eUznu9HewaIpzVXtFWx/hX3CTEXo/vCiZ2Hx6IptNYzjtMZCmeL29u3tVBW4qDc7eTaNdW4nLLScKmxy3uyFLIGqqmRRfPCfJJDYQWSQ2G26RmcXsS6HIq/uWE1l62cea6i2+ng+rW1PHhgiF8d8fPhacWqP5LkFwezaxDfe5E9Nk0RhWF0X+hxOSkrcRBLZYgmM5S7nQBktGYsN0r7B+c14i6R4nUps8t7sqTYQHbZ2loUN8mhsALJoTDbRAZfWcT+7Y2nFrETbt6Y3Tjn0WOjJFJTOxj/6OUBEmnNlauqWVsno7Fi4QrRF04cozMandqoLBRPk9bgczuliBW2eU+WJBsoFouZ3QQhJIfCEiSHwmwTGfzJvqEZRewlK2YvYgHW1pWzvt5DKJHm951jAHSMRid3hJXRWHGmCtEXTk4vjk2tk51YMytnxQqwz3uypNlAdjmjSRQ3yaGwAsmhMFtzczOJdIb79wwAcNd1bfMWsRNes6GOo8Pd/OKgnxMjMe7fO0gqo7lmTTWra2WnYnFmCtEX1ngmNnyaGpEdyX09cZ9Y2uzyniwjsgayyxlNorhJDoUVSA6F2fr7+3mifZSRaIo1tWVctap6QT93/doa3E7F3v4QP3x5gFRG85oNtXzk1SsMbrGwo0L0hROjrmPTCtmJ9bE1MiIrsM97sqTZQGVlZWY3QQjJobAEyaEwW2lpKT/ZlT0u57YtjTN2c52Pr7SE69fW8qsjftbVefjwFSvY3OQ1sqnCxgrRF04VstOnFsuIrJhil/dkKWQN5PHIlCNhPsmhsALJoTBbe0jRPhKlxlMy45idhfjwFcu5eWMdGxvKcTrkvE2xeIXoC6fWyE6NyE4VsvKnv7DPe7JMLTbQ6Oio2U0QQnIoLEFyKMz2033Z0dg3nFOP+wzPzXSXONjc5JUiVpy1QvSFE6Ou06cWj0ZkarGYYpf3ZClkDVRXV2d2E4SQHApLkBwKM3UHYuwZTuJyKl5/Tr3ZzRFLWCH6wtmO35n4ulqmFgvs854shayBxsfHzW6CEJJDYQmSQ1FoWmt6g3EePjTMPz/RBcAN62rlD3lhqkL0hbOvkc1+XVsuI7LCPu/JBU2zUsoJ7AR6tNavV0qtBn4I1AG7gPdqrRNKqVLgO8A2wA+8XWvdUci25kMikTC7CUJIDoUlSA5FISXTGf76V8d5uS80eVupE96ypdHEVglRmL5wcmrxrGtk5YMcYZ/35EKPyH4EODjt+y8B92it1wGjwB252+8ARnO335N7XNGxyxlNorhJDoUVSA5FIf384DAv94Uodzm4clU1H75iOV+7dR0ra+yxU6coXoXoCytKnTgUjMfTJNMZMlpPjs5ObAQllja7vCcXrJBVSi0HXgf8d+57BVwP3J97yL3Am3JfvzH3Pbn7t6uF7pNvIXY5o0kUN8mhsALJoSiU8XiK7+3O5u1T163iszes5tbNDejQiLkNE4LC9IUOpSYL1kAsRSieJq3B53biLpFVhcI+78mF/FjmK8BfARW57+uAMa31xLyHbqA193UrcBJAa51SSgVyjx+e/oSDg4PccccdlJSUkE6nue2227jzzjvp7+/H6/XidDoJBoM0NDQwMjKC1pqGhgYGBgbw+XwAhEIhmpqaGBoaQilFbW0tQ0NDVFZWkk6nCYfDNDc309/fj8vloqqqiuHhYaqqqkgkEkSj0cn73W43FRUV+P1+ampqSCQSdHZ2Tt5fVlaGx+NhdHSUuro6xsfHSSQSk/d7PB7cbjeBQID6+noCgQDJZHLyfitcUzQaJRaLyTUV0TWFw2EGBgZsdU12/D3Z/ZrC4TChUMhW12TH35MdrumXPdmRqM31bjZVQWdnJ3V1dcTj8RnvycV0TXb8PS3VawqHwwwODhp+TT6XYiQKg8EIgZHshzhVpQ46Ozvl9yTXRDgcJhwOF8U1zUdpred9QD4opV4PvFZr/SGl1LXAXwJ/CDybmz6MUmoF8IjWeotSah9ws9a6O3ffceBSrfWMQnbHjh1606ZNhrd/scbGxqiurja7GWKJkxwKK5AcikLoC8b5wP0HSWU0X3vTRtbVl0/eJxkUVlCoHN718DF2947zD69ZS4lTcdfDxziv2ce/vH694a8trK+Y+sMXX3xx1/bt2y+e7b5CzS94NXCrUqqD7OZO1wNfBaqVUhOjwsuBntzXPcAKgNz9VWQ3fSoqgUDA7CYIITkUliA5FIXwrZ29JDOa7etrZxSxIBkU1lCoHE6cFzsWS06uj5UzZMUEu/SHBSlktdaf0lov11qvAt4BPKq1fjfwGPDW3MNuBx7Mff1Q7nty9z+qCzF0nGf19XJWnTCf5FBYgeRQGO3ocIQn2sdwOxV/uK3llPslg8IKCpXDqSN4UrJjsTiFXfpDs1d83wV8XCl1jOwa2G/mbv8mUJe7/ePAJ01q31mxy6cdorhJDoUVSA6F0R7YPwTA68+pp9HnPuV+yaCwgsKNyGaL1tFoitGIjMiKmezSHxY80Vrrx4HHc1+3A5fM8pgY8AcFbZgBksnk6R8khMEkh8IKJIfCSKPRJE8cH0UBb9zcMOtjJIPCCgqVw8kR2VhqctRKClkxwS79oSTaQHY5o0kUN8mhsALJoTDSw4f8JDOay1dW0VJZOutjJIPCCgqVw4njd8aiSRTZEyyrZWqxyLFLf2j21GJbs8sZTaK4SQ6FFUgOhVFSGc0vDmYPNXjjuXOv+5IMCisoVA4nphZn18hmR99qy2X8SmTZpT+URBvI6/Wa3QQhJIfCEiSHwii/7xjDH0mysrqMrcsq5nycZFBYQaFyODG1eGKjJ5DNnsQUu/SHUsgayOl0mt0EISSHwhIkhyJfHj40zCOH/bx6VRU3b6jjwdwmT7durkcpNefPSQaFFRQqh9OnFr/yNiHs0h/K1GIDBYNBs5sghORQWILkUOSD1pofvDTA4aEI33qhj3f/YD/7BsKUuxzcuL523p+VDAorKFQO3SUOyl0O0hrSGnxuJ+4S+bNfZNmlP5REG6ihYfadE4UoJMmhsALJociHvvEEA6EEPreTS1dUkspkj5i/eWMdHtf8IwySQWEFhczh9M2dqmXHYjGNXfpDSbWBRkZGKC8vN7sZYomTHAorkByKfNjdOw7Ahcsq+OwNq+kbj7O/P8xVq6tP+7OSQWEFhcxhjaeE3mA897WsjxVT7NIfSiFrIK212U0QQnIoLEFyKPLhpZ5sIbt1mQ+AlopSWipmP27nlSSDwgoKmcPpa2LlDFkxnV36Q5labCC7DNuL4iY5FFYgORRnK6M1L/WFANjaOvfuxHORDAorKGQOp4/CyoismM4u/aEUsgYaGBgwuwlCSA6FJUgOxdk6MRIlEEtR73XRWrmwUdjpJIPCCgqZw+nrYmVEVkxnl/5QClkD+Xw+s5sghORQWILkUJyt3b250dhlFfMeszMXyaCwgkLmUApZMRe79IdSyAohhBDC8l7qnVgfe+bTioVYiqYXstUytVjYkBSyBgqFQmY3QQjJobAEyaE4G6mMZm//1IjsYkgGhRUUMofVZVPFa225jMiKKXbpD6WQNVBTU5PZTRBCcigsQXIozsbhwTDRZIYVVaXUeRc3siQZFFZQyBzWzJhaLCOyYopd+kMpZA00NDRkdhOEkBwKS5AcGi+d0aQy9jhSAWAwlGA0kgSmzo9dzG7FEySDwgoKmcMZU4vLZERWTLFLfyipNtBiNqMQIt8kh8IKJIfGiqcyfPwXRwjEUvzT69Yv+GxVq3q2K8DnftNORkOTz008lQHgwrNYHysZFFZQyBz63E4uXVFJaYkDd4mMXYkpdukPpZA1UG1trdlNEEJyKCxBcmis7+3u5+hwFIDP/rqdr7xhA1630+RWLc7R4Qj/8GgHGQ1up2IglADA5VBc0LL4nTYlg8IKCplDpRR//5q1BXs9UTzs0h/KxzMGssuwvShukkNhBZJD47T7o/x4zwCK7Ohl52iMLz7WQTqj0VrzYk+Qb73Qy0humq6VDYYS/M2vjxNPZbhhXQ0P3n4BX79tE39x9UruvnktFaWL//xdMiisQHIorMAuOZQRWQNVVlaa3QQhJIfCEiSH+aG1ZjiSpMbjosShSGc09zzdRVrDrZvrefO5jfz5Q4d57mSQf3j0BCfH4nSOxQAYj6f4yJUrTb6CuQViKT7zf8cZiaS4oMXHx65aidOhWF3rYXWt56yfXzIorEByKKzALjmUQtZA6XTa7CYIITkUliA5PDvpjOaZzgA/enmAI8MRqspKuHZNDaUlisNDEerLXbz/4mV43U4+s301n3rkGE93BACoLHUSjKfZ2T2O1tpya6O01jx2fJT/eLaHQCzFiqpSPnvDalzO/E4akwwKK5AcCiuwSw6lkDVQOBymvr7e7GaIJU5yKKxAcji/I8MRvvhYB9VlJXz4ihWsqcuOQKYz2SLv+y/10x2IA+ByKgKxFA8emJoa9uFXL59cE7t1WQV3XbuKR4+NcP26Gl69qpp3/2A/A6EEPcE4y6vKCn+Bc/CHk9zzdBfPnwwCcEGLj09c03ZWU4jnIhkUViA5FFZglxxKIWug5uZms5sghORQWILkcG6/OernK0+fJJnWdAfi3PmzQ7z1/CY2N3q5d1cv7SPZqcFNPjd/cH4jN22o4+RYjN8eG+GZjgAXL6/girbqGc953doarltbM/n9Ra0VPHZ8lJ3d45YpZNMZzd/+pp0jwxF8bid/fGkrN2+oNWzEWDIorEByKKzALjmUQtZA/f39tLW1md0MscRJDoUVSA5Plc5ovvFcDw/sz46s3rKxDrfTwUMHhvjRywOTj2vwurh9Wwvb19XidGSLvPX15ayvL+eDly1f0GttyxWyu7qDvOnchvxfzCL8ZN8gR4YjNHhd/OsbN1JX7jL09SSDwgokh8IK7JJDKWQN5HIZ+6YsxEJIDoUVSA5P9e1dfTywf4gSh+JDly/n9edkp3ldv66Grz59kuFwgndc2Myt59Sf9RmQ25ZnN/Z4qS9EIp3Bnef1p2eqJxDjO7v6APjIlSsML2JBMiisQXIorMAuOZRC1kBVVVVmN0EIyaGwBMnhTM92ZTducij4wmvWcFHr1A6S5zR6+Y83bySjmRyBPVt15S7W1JbRPhJj/0CYrcsq8vK8i5HRmnueOkkirblhXQ2XrChMNiSDwgokh8IK7JJDOUfWQMPDw2Y3QQjJobAEyeGUgfEE//REJwDvv3jZjCJ2glIqb0XshG2519nVHczr856pXxwcZk9/iOqyEv5sgVOj80EyKKxAciiswC45lELWQHb5tEMUN8mhsALJYVYineELj55gPJ7m0hWV/MH5jQV77W3Ls6OwO7vHC/aa041Eknzp8Q7+7ZluAD58xXIqywo3MUwyKKxAciiswC45lKnFBkokEmY3QQjJobCEpZzD8XiKx4+Psrt3nJd6Q4QSaZp8bj5xTRuOAp7puqXJR6lT0T4SZSSSBOD+vYN43U7edWHTGe0WPBpJcmgowsHBMAp4w+Z66r3uWR+rtebnB4f51gu9RJIZXE7Fey9q5qrV1bM+3ihLOYPCOiSHwgrskkMpZA0UjUbNboIQkkNhCUs1h/FUho/9/ChdY7HJ25ZXlfKp61YVdDQSwF3i4PyWCl7oDvIvT3axtz9ELJUBwOVQvO2CptM+R28wzj8+1sHhociM23+yb5BbNzfw9guaqJp2XemM5mvPdPOLQ9lpbJeuqORDly+npbI0j1e2MEs1g8JaJIfCCuySQylkDWSXM5pEcZMcCitYqjn89s5eusZiLKss5W3nN7J1WYUpRdyEi5dnC9kXcutkz2/2sac/xDdf6GVVbdm8Gy/t7hmfnBZdVuJgY0M55zR66Q3GefLEGPfvHeThQ8PcvLGON53bQG25iy893slTJ8ZwORWfuLqNa9ZUG3ZO7Oks1QwKa5EcCiuwSw6lkDWQXc5oEsVNciisYCnmcG9/iJ/uG8Kh4FPXtbGxwWt2k7hqdTX37x2kwevmjkuWcV6zj+++2Md3Xuzn7kc7uOcNG+gOxHnk8DB7+kIsrypjc6MXb6mTH+8ZIKOzo6qfvG4VXrdz8nmPDkf4n5297Owe56f7hvjZ/iGafG76xhOUuxx8/qa1nN/iM+/CWZoZFNYjORRWYJccSiFrILd79vVCQhSS5FBYgVVyOBROcNwfpcLtpKK0hDqva0ZBli/RZJp/ebITDbzjgiZLFLEA9V4333vnlhm3vWtrM+0jMZ7uGONPf3poxn3tI1HaR6amoL3jgiZu39Zyyo7K6+vLufvmdRwdjvDAvkEebx+jbzxBjaeEu29ey9q6cuMuaoGskkGxtEkOhRXYJYdSyBqoosK8c/qEmCA5FFZghRxqrfmrXx6jJxifvK3Eofin163j3Kb8jhZ+64VeeoMJ1tSW8Z6t1p7C5VCKT1yzkt5gnPaRKG01Zbx2Yx1Xrq6mL5jg4GCYrrEYV7RV8epV82/QtL6+nL+6dhV3vCrJM51jXLqyikafNf5gskIGhZAcCiuwSw6lkDWQ3+/H5zN3KpUQkkNhBVbI4VA4SU8wjtupWFvnYTicZCic5L+f7+XLr1+ft7Wbe/pCPHhgGKeCv7y6DZfT+ifdeVxO7nnDegZDCVZWl03+t2jwuhc1JbjO6+INmxvy3cyzYoUMCiE5FFZglxxa/921iNXU1JjdBCEkh8ISrJDDiZ12z2v28dVbN/KNt5xDZamT/QNhnj8ZzMtrJFIZvvJ0FwDvuLCZdfXmT6ldKI/LSVuNx7TNmIxmhQwKITkUVmCXHEohayC7bG0tipvkUFiBFXJ4eCgMwMaGbHHpdTt5x4XZab//s7OPjNZn/Rrf3d1PdyDOyuoy3nnh6Y+zEYVjhQwKITkUVmCXHEoha6BYLHb6BwlhMMmhsAIr5PDQYHZEdlPj1MZLbzinnvpyF+0jUZ5oHzur5z/uj3DfngEU8PGrVuIuginFS4kVMiiE5FBYgV1yKGtkDWSXM5pEcZMcCiswO4fpjObIcLaQ3Thtum9piYP3XNTMV54+yb27+rhqdTUljoVNrW33R3nk8DAaKCtx8NzJIBkNb9zcwOYma+xSLKaYnUEhQHIorMEuOZRC1kB2OaNJFDfJobACs3PYNRYjlsrQ5HNTU+6acd9NG+q4b88gvcE4f/7gYc5p9LK+vpza8hIcSuFUijqvixVVpSilSGc09+8d5N5dfaQyM6cjN/pc/NGrWgp5aWKBzM6gECA5FNZglxxKIWugsrIys5sghORQWILZOTyU2+hpU8Opmy+VOBQfuryVz//2BMf8UY75Z187VFfuYmtrBX3BOPsHsuttb95Qx5o6D/FUhkQ6w1Wrq/G48n8urTh7ZmdQCJAcCmuwSw6lkDWQx+MxuwlCSA6FJZidw1du9PRKl6yo4gfv2sKx4ShHhyMc80eIJDOkM5pURtM5GsMfSfLboyMA1JaX8PGrVnLJiqqCXYM4O2ZnUAiQHAprsEsOpZA10OjoKJWVlWY3QyxxkkNhBWbncLaNnl6porSEra0VbG099aB4rTUdozF29YwTT2V4wzn1VJbJW2gxMTuDQoDkUFiDXXIo78IGqqurM7sJQkgOhSWYmcNoMk3HaBSHgrV1i/sUWinF6loPq2vt8Sn2UiR9obACyaGwArvkUM4GMND4+LjZTRBCcigswcwcHvdHyWhYVeOR9atLmPSFwgokh8IK7JJDKWQNlEgkzG6CEJJDYQlm5vDQYHZ97KbG2dfHiqVB+kJhBZJDYQV2yWFBClmlVJlS6nml1MtKqf1Kqb/L3b5aKfWcUuqYUupHSil37vbS3PfHcvevKkQ7880uZzSJ4iY5FFZgZg4P53Ys3tggZ7suZdIXCiuQHAorsEsOCzUiGweu11pfAFwI3KyUugz4EnCP1nodMArckXv8HcBo7vZ7co8rOv39/WY3QQjJobAEM3M439E7YumQvlBYgeRQWIFdcliQQlZnhXLfunL/aOB64P7c7fcCb8p9/cbc9+Tu366UUoVoaz7ZZWtrUdwkh8IKzMrhWDTJQChBWYmDldX2ODdPLI70hcIKJIfCCuySw4LtWqyUcgK7gHXA14DjwJjWOpV7SDfQmvu6FTgJoLVOKaUCQB0wPP05BwcHueOOOygpKSGdTnPbbbdx55130t/fj9frxel0EgwGaWhoYGRkBK01DQ0NDAwM4PP5AAiFQjQ1NTE0NIRSitraWoaGhqisrCSdThMOh2lubqa/vx+Xy0VVVRXDw8NUVVWRSCSIRqOT97vdbioqKvD7/dTU1BAOh+ns7Jy8v6ysDI/Hw+joKHV1dYyPj5NIJCbv93g8uN1uAoEA9fX1BAIBksnk5P1WuKZoNEosFpNrKqJrGh0dRWttq2uy4+9pKVxTeXl5wa+pJ+EGoKVckUom6Jbf05K9plAoNOPn7XBNdvw92f2aRkdHAWx1TXb8Pdn9mkZHR/F6vUVxTfPWl1rreR+Qb0qpauAB4G+Ab+emD6OUWgE8orXeopTaB9yste7O3XccuFRrPaOQ3bFjh960aVNB238mOjs7aWtrM7sZYvIUODgAACAASURBVImTHAorMCuHvz7i55+f7OK6tTV86rpVBX99YR3SFworkBwKKyimHL744ou7tm/ffvFs9xV812Kt9RjwGHA5UK2UmhgVXg705L7uAVYA5O6vAvwFbupZq6+vN7sJQkgOhSWYlcO+8ezOjM0VblNeX1iH9IXCCiSHwgrsksNC7VrckBuJRSnlAW4EDpItaN+ae9jtwIO5rx/KfU/u/kd1oYeO8yAQCJjdBCEkh8ISzMphXzAOwLLKUlNeX1iH9IXCCiSHwgrsksNCrZFtAe7NrZN1APdprX+hlDoA/FAp9QVgN/DN3OO/CfyvUuoYMAK8o0DtzKtkMml2E4SQHApLMCuH/bkR2RYZkV3ypC8UViA5FFZglxwWpJDVWu8Bts5yeztwySy3x4A/KEDTDGWXM5pEcZMcCiswK4e9uRHZFhmRXfKkLxRWIDkUVmCXHBZ8jexSYpczmkRxkxwKKzAjh9FkmrFYCpdDUVfuKvjrC2uRvlBYgeRQWIFdciiFrIG8Xq/ZTRBCcigswYwcTkwrbqpw4yi+o8hFnklfKKxAciiswC45lELWQE6n0+wmCCE5FJZgRg57ZaMnMY30hcIKJIfCCuySQylkDRQMBs1ughCSQ2EJZuSwTzZ6EtNIXyisQHIorMAuOZRC1kANDQ1mN0EIyaGwBDNy2D+eHZFtrpARWSF9obAGyaGwArvkUApZA42MjJjdBCEkh8ISzMihTC0W00lfKKxAciiswC45lELWQFprs5sghORQWIIZOZzY7KlZphYLpC8U1iA5FFZglxxKIWsguwzbi+ImORRWUOgcpjOaASlkxTTSFworkBwKK7BLDqWQNdDAwIDZTRBCcigsodA59EeSJDOaWk8JHpc9dmcUZ0f6QmEFkkNhBXbJoRSyBvL5fGY3QQjJobCEQuewLygbPYmZpC8UViA5FFZglxxKISuEEMJ2Jo/eqZRpxUIIIYQdSSFroFAoZHYTRBFLpDL85qif4XDirJ5HciisoNA5nBiRbZERWZEjfaGwAsmhsAK75FAKWQM1NTWZ3QRRpHqDcT768yP80xNd/NfzvWf1XJJDYQWFzmFf7gxZGZEVE6QvFFYgORRWYJccSiFroKGhIbObIIrQ7zvGuPNnhznmjwJwdDhyVs8nORRWsJgcdoxG+e/ne/jA/Qe5d1cfmTM4LmByarGMyIoc6QuFFUgOhRXYJYclZjfAzpRSZjdBFJFURvOtF3q5f+8gAJevrOK5kwF6g3ES6Qxu5+I+d5IcCitYSA611nSNxXimM8BTJ8YmP8wB+N7uftpHonzy2rYF7UI8ObW4UgpZkSV9obACyaGwArvkUApZA9XW1prdBGFB/nCSrzzdRSqjee2mei5vq2I0muTuRzvYPxDGoeADr1rGW85r5I9+fJCeYJzusThr6jyLej3JobCC2XIYjKXY0x+iOxCjeyzOvoEwvbkCFMDrdnLNmmo2Nnj5r+d62NEZ4GM/P8Lnblwz727E4USaYDyN26mo9cjbnMiSvlBYgeRQWIFdcijv8AYaGhqira3N7GYIE0WTacpKHJOffL3UO87dj3YwFksBsKtnnLpyF6mMJhBLUV/u4tPXr+Lc5uy26G01ZfQE43SORRddyEoOhRW8Mof+cJIPPnBo8v+FCZWlTi5dWcXlbVVcsrwSd0l2JsJ5zV4+++t22kdi/NlPD/HOC5t587kNuEscZLTmwECYQ0MRGr0uMrkZyC0Vpbb51FmcPekLhRVIDoUV2CWHUsgaqLKy0uwmiALoHI3SP55gda2HBq+LZFrz5IkxfnFwmAODYWo9JWxq9FLjKeGRw34yGrYu83Hpyip+eXCYk4HsCNRFrRV88to2qj2uyeduqynjmc4AHaOxRbdPciisYHoOtdZ85ekuxmIp2mrK2NZawfKqMlbXlrGpwYvTcWrxubyqjH+9dQP//GQXz3QG+OYLvfzy0DCXrKjkmc4Aw+HkKT8jGz2J6aQvFFYgORRWYJccSiFroHQ6bXYThMFOjsX48INHiKcyAFSUZtfujcezv3sFjERTPNMZmPyZd13YxHsvasHpULz53Ab29IXwR5Jcs6bmlD/gV9WUAdB1FoWs5FBYwfQc/u7YKM+dDOJ1O/nHm9dS711YwekrLeFzN65hZ3eQrz/XQ+dojIcODAPQ6HOxrbWSsWiK7kCMkWiKK1dVG3ItojhJXyisQHIorMAuOZRC1kDhcJj6+nqzmyEMkkxn+MfHOoinMiyrdBOKZ9flAayr8/D6c+q5bm0NI5EUBwfDdI5GuWh5JVuXVUw+h1KKC6Z9/0orq7OFbOfY4gtZyaGwgokc+sNJ/n1HNwAfvKx1wUXsdBfn/j/6zdEReoNxLl1ZyeZGr0wjFvOSvlBYgeRQWIFdciiFrIGam5vNboIw0Ld39nHMH6W5ws3X3rSJcpcDfyRJNJlhedXU2rzWKietVYvbOXVFVRkOlT1XNpHKTK4XPBOSQ2EFzc3NpDPZKcWhRJpLV1Ry4/rFbzbhdChu3liXxxYKu5O+UFiB5FBYgV1yKIWsgfr7+22xkFqc6sWeID/eO4hDwSevXYXXnZ1SvJjRpfm4SxwsqyylOxDnZCDG2rryM34OyWFhHRuO8PnfnaCqrIQN9eVsaChnZXUZ9V4XtR7XrOs/5xKIpXhw/xDuEsXbzm/CUaQjjlprfvlyF490pegci+F1O/nIlStkBFUUlPSFwgokh8IK7JJDKWQN5HK5Tv8gUXSGwwn+3xOdALznohY2N3kNfb226jK6A3E6RxdXyEoOC0drzX8820P/eIL+8QSHhyJwcOp+h8r+Pm/aUMeN62upLCvBH0ny+44x9vaHaK4oZVNDOatqyvjtsVF+um+QaDK7/rovmOAjV64wpJgNxVM8sH+IZFpzQYuPc5t9lC1i9H/C/oEQT7SPEU2mSaQ1naMx2keyZ8I2+dx89MoVef/QR4jTkb5QWIHkUFiBXXIohayBqqqqzG6CyLNALMUnHznOSCTFlmYv77ygyfDXbKsp4/edAToXsOFTRmv29oXIaKj3uqj3uiSHBbSrZ5y9/SEqSp3cdW0bHSMxjgxH6B9PMBROMBpNcWI0xtef6+FbL/TSVlPGcX8UPc9zXrjMx8GBcG7Ha83Hrlp5RsXskeEIL5wM4nM7qSh1Uu0pYU2th2qPC601T50Y4993dDMSzR6D88OXByhxKK5cVcVfXtOG27nwgjad0fzgpX6+u7t/8gicCTUeJ+/e2sItG+twncFzCpEv0hcKK5AcCiuwSw6lkDXQ8PAwXq+xo3WicCKJNJ/5v+N0jcVoqynjczesOaNpoovVVpM9P7bjNBs+ZbTmy0928eujIzNuv7TZzd+9bnPRTkstFlprvr2zD4C3n9/EJSuquGTFzDeKRCrD891BHj40zK7ucY75o7iciouXV/Kq5ZUMhhIcGgrT7o+yts7D+y5q4dxmH7t7x/ns/x3n/46MMBZNUVvuwh9JEk9l+NDly1ldO/sZw8l0hr/9dTv+yKlH0zT53FR7SrKjxsDmRi+bm7y83DfOseEoj7ePsabOwzsuWNg6Gn8kyRcf6+DlvhAKeNO5DayuKcNd4qDc5aQuPcqGNQ1n8F9UiPyS92RhBZJDYQV2yaEUsgayy6cdS9WJkSi/PTpCaYkDj8vBs11BDg9FaKlw88Wb11FZVpj/fRZyBI/Wmq8/18Ovc+3dWF/OcCTJwHic5/oTfG93P++9qOWs2hFPZfBHkiyrXNzGVXb3+84AR4Yj1HpKuPXc2Qs2d4mDK1dVc+WqagbGE5wMxNjc6KU8t8Z6LluXVfCF16zlM79u57mTwRn33bdngLuuXTXrzz11Ygx/JEmTz80lKyoZj6cYDic56o8yEEowEEpQ7nLwgUtaee2muskPO3Z1B/nUr47zvd0DXL+2lkbf7NOAM1rzcl+IXx328/uOMRJpTXVZCXdd28a25TPPqBsbm2/cWQjjyXuysALJobACu+RQClkDJRIJs5sgFimSSPPZX7czEJr5O6wtL+GLt6yjzlu4tQWtVaU4FPSNz71z8fdeGuCBfUOUOBR/e8NqLs4VETu7g3z6V8f57ov9bGrw8qoVizsAu2M0yud+005vMMEVbVX80auWTR4NJLJTau/Njca+a2vzgtaXNlW4aapY+DrRC5ZV8K+3bmBHZ4DKshJcTsW/PNnFjs7ArLnQWvPA/iEA3nlhE6/dNLXNfjqj6RqL0R2Ic26Tl9rymXnetrySq1ZX89SJMb7xXA+f2b76lPb0jcf5m/9rp2vaTIHLV1bxkStXnPJ8IP2hMJ9kUFiB5FBYgV1yKIWsgaLRqNlNEDnhRJrnTwbZ1FhOS8XpRxS//lwPA6EEq2vKePWqaqLJ7Pmwrz+nnpYCj0i6nQ5aK0s5OcfOxb88NMx3dvVld1C+rm2yiIXseZu3rvXw4PEoX3y8g39700aafW4iyQxOh1pQwfX7jjH+3xOdk5sOPdMZ4NmuALdsrOOOVy3DVzqzG3nhZBBfqZNzGot/yspCZLTmvj0DdI7FaPK5ucXAI2FW13pmTCP+2f4hjvuj7OoZ5/K2mZ+uHhyMcHgoQmWpk+3rZh5z43SoU57rlf700laePxnkyRNjvNgT5KLWqVwNhRPc9fAx+scTNHhdvGZDHTdtqKV5nv+3pD8UZpMMCiuQHAorsEsOpZA1kF3OaLKDf3ysg+dzUzLbasq4bEUlN26om3VU8fmTAR457MflVHzq+lWsqpn7j/1CaavxcDIQp+MVOxcfGAjztWe6AfjzV6/g6tU1p/zsH12+iv5ED8+dDPKnPzlEOqNJZjSlTsXHr17JdWtnP8tzLJrkvj2D3L93EIDr1tZw+7YW7tszwK8O+/nlIT9HhiN88ZZ1VOSK2R/vGeC/nu+l3OXg++/cctops8WuYzTKvz59kn0DYQBu39ZS0I2Mrl5dzXF/lCfaR08pZB/Yl/29vXZTPaWL2IG40efmXRc28T87+/i3Z7r5+5vWsKyylNFoarKI3dhQzhdvWTd5/NR8pD8UZpMMCiuQHAorsEsOZetIA/X395vdBAE81xXg+ZNBSp2KcpeDztEYP9ozyAfuP8hnf32cvf0htM6u3wvGUnz5qS4A/nBbiyWKWMgW38CMnYtHI0n+/ncnSGU0bz63YcbU0ekGBwb4q2vbaK0sJZbKTBax8bTmS4938uixmZtDdYxGueepLt79w/3cnzsr9wOXLOOT17axrLKUj165km/cdg7LKt0cHY5y18PHCMZS3PdytogFiCQzPNE+atB/DfOlMpp7d/XxwZ8eYt9AmBpPCZ+6ro0b1s/+oYBRJj64eLYrO714wmAowVMdYzgVvGHz7LlYiLec10hr7hzj9//4IO/90X4+8tARugNx1tR6uPvmtQsqYkH6Q2E+yaCwAsmhsAK75FBGZA3kdss5iWZLpDP857M9APzhxcu4dXM9+wbCPH58lN8eG+HZriDPdgXxuLIbOmUyMBZLsaXJy21bGk1u/ZS23MjxiZEoWmsyGu5+rAN/JMm5TV7++NLWOX/W7XZTUVrCf962iUAsRWVZCWUlDr6zq4/v7u7n/z3RSSqjcToUvzw0zL7+8OTPXrqikndc2MS5Tb4Zz7mypox/et16PvHLoxzzR/mznx5iOJJEAZe3VfFMZ4CHD/u5ZY7iuljEUxke3D9EU4Wby1ZWUVrioDcY5x8f6+DwUARFdrr5H13ccsoU60JorSplXZ2HY/4oO3uCXNFWDcDPDwyR0XDtmmoazuK8VrfTwd/dtIbv7Opjd+84g6Hs7scrq8v4x1vWTo7EL+i5pD8UJpMMCiuQHAorsEsOpZA1UEVFhdlNWHJ6AnFcTjW5y+rP9g3RE4yzsrqMN57bQIlDsXVZBVuXVfCHF7fw0IFhfn5giGA8PbkGtNzl4C+vaSvI0ToLNTEi+9zJILfeu4eqMieDoSS1nhI+s301JfO0dSKHpSWOGbvPvm9bC0rB/77Yzz8/2TV5u8fl4IZ1tbx5SwPLq+be0KnB684Vs8foDcZRwMeuWsm1a2t45/f3cXgoQrs/ypq6049qJ9IZFFjufNH/fr6HBw8MA9n/Lq9aXskL3UGiyQwNXhd3XbuK81t8p3kWY12zpoZj/ihPtI9xRVs1x/0RfnHID8Cb8/BhzMrqMj6zfTUZrTnuj3J0OMIVbVVUe85swzPpD4XZJIPCCiSHwgrskkMpZA3k9/vx+cz9I7fQArEUGa3xuJy4nSo7UnQyyK6ecbxuB5+8dpUh6ybDiTTf3tnLzw8OozVc1lbFjetq+d5L2akTf3ZZ6ynFXo3Hxe3bWnjP1maiyTSxVIZoMkNlWQlVBTpaZ6Haasq4enU1u3vHGY+nGQxlcCr49PbV1M2yQ+x08+XwvRe14FCKe3f1sa7Ow+vOqee6NTUL/h01eN388+vW8T87+7hsZRVXrc6OCG5fV8NDB4Z55LCfO69YPu9zdIxG+cQvjzEeT7GsspSV1WVc0OLj1s0Nhn6YsLt3nL5gnLpyF3XlLloqS2dMk93dM86DB4YpcSjW1Ho4MhzhyRNjAFy1upqPXrnijEYkjXL16mq++UIvz3YFeP5kgLsf7SCSzHD5yqq8brjlUIr19eWsry8//YNnsRT7Q2EtkkFhBZJDYQV2yaGaWBtYjHbs2KE3bdpkdjPmFAwGqaxc3HEnxeipE2P8/e9OzPuYi5dX8Pmb1s46ghiMpTg0FGZVjWfOcysnaK0Zj6fxR5IcHY7wrRd6GYmmcKjsH9ypzFSuL2+r4u9uXLO4i7KgcCJN/3icshInrVWn30F5ITmMJNJ5/YDhuD/CBx84jM/t5Afv2jLnZkP+cJI/f+gwQ+HkKfdduqKST163asFrMBfKH0nyb78/ye87AzNudzsVf3xJK7durieSzPCnPz3IYCjJ7dtaePfWZnoCcZ7qGKXJ5+baNTUoZZ0R+w//7DBHhiOT31+zpppPXNOG20Ij3EutPxTWIxkUViA5FFZQTDl88cUXd23fvv3i2e4zfzjBxqLRaNGE5GxFEmn+fUd291yf20kinSGR1jT6XFy8vJLNjV7+6/lednaP85WnuviLq1eilKJ/PM4T7WM81xXgwGCYjIZSp+K921p4y5bGU0bkwok0332xj4cP+yenAk/Y3Pj/t3fn4VXVdx7H39/cJGQP2UggQAIxrC6ouC8VsbgXbTsW26plfEar1LYznY7WLqOddrRPn9ra1tpR61MdV9pqXetS1HawCm4gCiggCQGykks2suc3f9wLRiAImHvPuSef1/PwcO85d/ke8nl+4fuc3/mdTK45aTx56Sk8uaaJJ9c00e8cV+7j+tFElJka2uMWPPuyPzkc7rPkFQUZVBams66pk6VV2/e4/QtEMvP95zbQ2NHL9DEZ/Ne8Cho7eli/rZM7l0VWWf7mE+9z46cn09fvWNvYQU1LN+dMK9ivWyjtzjnHs+838z/LttDR0096ShInTMyltbuPpo5eqsJd3PbKZl7fHLlmuqG9l6lFGSw4ohiIXI+64Ah/rvJ36qTRuxrZ+TMKueqE8ST5qNGGkTUeij8pg+IHyqH4QVByqEY2hrq6uj7+RQFx31t1bNvRy7SiDH7xmSkkmdEfXUBop4mj0/j2U+t4bl0zA87R2NHLytr2XftDBpPz0/mguZO7lm/lpQ1hLjlqLEWZKeSmJ7Niaxt3Ld9KuLMPiFzLWpCRQmFmCqdNzuPMqQW7/vN+afQsWu+A2697pQaZVzk8e2oh65pq+MvabXs0sr39A/zohY2s39bJuJxR3PjpyeSkJZOTlkxFQQaHl2Txg+c+oDrcxVcWr/7Ie9+pa+eW8yoP6Iyoc47fv1HLgyvqATh2Qg5fP2nCR878/9/G7fxi6SaWRW/TlBIyvn2qv66VHsq8Kfm8trmV4ybk8LnDxvjqbPFOI2k8FH9SBsUPlEPxg6DkUFOLY6i7u5tRow78zFGiqQ5HVq0dcPCr+VOZUjT02cJXN7Vww/MfsHPmb2rIOKl8NCeXj+ao0mwyU0O8VtPKrS9v2rVC6u5mjMnk6hPHM+Ugr9UbabzKYUdPPwseeIfuvgEuPLSIhbPHkZacRM32Lm56sYr12zrJTUvmF+dP2esU6Y6efn7yUhWvbmqlMCOFaWMyWVXXTktXH9+bW77Xe+YOZecKzUkWWZBqXmX+Xpu9hvYefvq3albWtnPV8aXDsliSRIyU8VD8SxkUP1AOxQ8SKYf7mlqsRjaGqqurKSsr87qMg7JsUwv3v1XHudMLOXNKwZCvc85x7V/Ws2JrO+dOK+AbJ0/82M9+cUOYFzc0c8LEXE6dnLfXayA7e/t5aEU9axo7aOnso6W7j7TkEF86spi5h+T7btqkn3mZw8febeT2Vzcz4GBcTiqnV+Tzh1UNdPcNUJyVyg/OmPSxiwd19vaTnhLJyJNrmvjlyzWUZKdy1+en79c1oPe9Wcu9b0aa2O/MKedTk/fdAA84R3hHHwWZB7Yqr+xbIo+HEgzKoPiBcih+kEg51DWyHklLG/rWJX7V2dvPHcu28FT09h3vN21iXM4oDiv5cGWzrr4B1jZ0UB3uYm1jByu2tpM9KsTC2eP26zvmVOQxp2LfzUR6SoiFx+zf58m+eZnD+TOLmF6cyc/+Vs3GcBf3vRVZRfqMQ/JYdOKE/VrIaWcTC3D21AIeW91IdbiLx95t5J8OL6alq48HVtRR29pNac4oJoxOIzWUxKq6dlbWtrO1tZskg2tPK/vYJhYii4WpiR1+iTgeSrAog+IHyqH4QVByqEY2htLTP/7+mX5SFe7kxuc3sqW1m5QkY2ZJJiu2tvPjFzbymwumkZ+RwtqGDn70wsY9pv3+y7Gl5PjsljUS4XUOpxRm8OsLpvLginpertrOglnFzKnYc/Gn/RFKMq48rpTrn9nA/W/VYcCDK+tp6+4f8j2ZqSGuOXH8QX+nDA+vcyiiDIofKIfiB0HJoTqPGAqHwwmzIlhnb/+uJrY8L43rTiunLC+N/3h6Pavq2rnpxSpOmTSa3766hb4Bx/jcUcwszqQsL50ZYzKZUTx896uU4eWHHKaEkrj06LFcevTYT/xZs8fnMHt8Nq9vbuOO5VsBOHJcNmdNzaeurYealm529PQzY0wmh4/NorIwIyEWbAo6P+RQRjZlUPxAORQ/CEoO1cjGUEHB0NeW+s1vXtm8q4n91fypu+77ef3p5Vz96FpW1rbvWmF4/owirjhuHCk+ukelDC2Rcri/rjiulHfr3ycrNcRXjx/PyeW5vlypVz4UxBxKYlEGxQ+UQ/GDoORQnUgMtbW1eV3CfnlpQ5hn328mNWRcf3r5riYWoCAjhe+eXk6SQVpyEt+ZU86iE8eriU0giZLDA1Gel879C2Zyzxdmcsqk0WpiE0AQcyiJRRkUP1AOxQ+CkkOdkY2Re96oZUtjmDE1A6QlJ5GXkcK8ynzPG8De/gF++NeNbNvRy8ziTCoLM7j91S0AXHlcKeV5e86ZP3xsNnd9fjrpKSEKMrQITqLp6enxuoSYyBql4SuRBDWHkjiUQfED5VD8ICg5jMv/BM1sAnAvUAw44A7n3K1mlg88DJQDVcBFzrmwRU6v3AqcA+wAvuKcezMetQ6XlzaE2dLaDZsbdm1r7erj4lklHlYFD62sZ1lNKwDrt3Xu2n5iWS7nTS8c8n3jc4OxutlIVFLibeZEQDkU7ymD4gfKofhBUHIYr9ODfcC3nHMzgOOBRWY2A7gOWOKcqwSWRJ8DnA1URv9cAdwepzqHzcLZY/nitAwuP2Ycn5kRaRD/tKqBzt6hV1eNtapwJw+uqAfg6ydN4LKjx3JUaTZHjsvm306ZqOmZAVVXV+d1CSLKoXhOGRQ/UA7FD4KSw7ickXXO1QK10cdtZrYGKAXmA6dFX3YP8BJwbXT7vc45B7xqZqPNbGz0cxLCqZPzmJbVy5gxY3DOsb6pk9UNHTyxpomLDi+Oez39A45b/r6JvgHHudMK9nn2VYIlKEusS2JTDsVryqD4gXIofhCUHMb9IjMzKweOBJYBxYOa0zoiU48h0uTWDHrb5ui2jzSyDQ0NXH755SQnJ9Pf389nP/tZFi1aRF1dHZmZmYRCIVpbWykqKqK5uRnnHEVFRdTX15OVlQVAe3s7xcXFNDY2Ymbk5+fT2NhITk4O/f39dHR0UFJSQl1dHSkpKeTm5tLU1ERubi49PT10dnbu2p+amkp2djbbtm0jLy+Pjo4OqqurKSkp4YxSY3UD/GFlPbOyOhk3ppC2tjZ6enp2vT89PZ3U1FRaWlooLCykpaWF3t7eXfs/yTE9+HoNaxt3kJcWYl5JP93d3Qd1TJ2dnXR1de3an5aWRnp6OuFwmIKCgrge03D9nIJ+TOFwGOdcoI4piD+nkXBMGRkZgTumIP6cgnpM7e3tH3l/EI4piD+noB9TOBwGCNQxBfHnFPRjCofDZGZmJsQx7bOvjJz0jA8zywL+BvzYOfeImW13zo0etD/snMszsyeBm51zS6PblwDXOudeH/x5r7zyips2bVrc6j9Q1dXVlJWVAeCc45rH3uf9ph1cdXwpFx4aOVO7rqmTgowUCjJjs4hST/8Az7y3jTuXb6W7b4AbPz2ZE8pyY/Jd4k+DcyjiFeVQvKYMih8oh+IHiZTDN9988425c+fO3tu+uJ2RNbMU4E/A/c65R6Kb63dOGTazscDOlZG2ABMGvX18dFtCKSz8cPqumfHFI4u54fmNLH67gdHpyfxxVQPrmjrJTA3xnTllHDth+BrM/gHHk2uaeHhlPU07egE4ozJfTewINDiHIl5RDsVryqD4gXIofhCUHMZlsafoKsS/A9Y4524ZtOtx4LLo48uAxwZtv9QijgdaEun62J1aWlo+8vyEiblMzk9n245ebnqxmnVNnaSGjI6efr7/7Ac8tLKO4TpD/vDKem57ZTNNO3qZelpUaQAAC2ZJREFUlJfG9+aW8++nThyWz5bEsnsORbygHIrXlEHxA+VQ/CAoOYzXGdmTgEuAVWa2IrrteuBmYLGZXQ5UAxdF9z1N5NY764ncfmdhnOocVr29vR95bmYsnD2W/3z+A0qyR/H5w8ZwRmU+f1zVwL1v1HL3a7W8U9fB2VMLOHp8DmnJSTjnaOzoZUtrN+V5aeSlf/wU5L4Bx+OrGwH411MmcuaUfJK0IvGItXsORbygHIrXlEHxA+VQ/CAoOYzXqsVLgaE6qbl7eb0DFsW0qDjY2z2ajpuYy+IvHUZmaohQUuSf5MtHllCRn85PXqpieU0ry2taGZWcREV+OjUtXbR1f3jLnoqCdI4uzWZORR4VBRl7/d5/VG2nubOPsrw0zpqSr9vqjHBBuVeYJDblULymDIofKIfiB0HJYbzuIzsiDbXSVk5a8q4mdqcTynK543PT+edjxjK1KIPuvgFWN3TQ1t1PzqgQU4sySA0ZG7Z1svjtBq569D1++NcP2NjcucfnP7GmCYDzpxeqiZXA3CtMEptyKF5TBsUPlEPxg6DkMO633xlJMjMzD+j1Y7JSWXBECQuOKKGhvYdN27uYODqNoswUzIyevgHeqW/nH9UtPPPeNpZWtbC0qoV5lfl84+QJpISSqA53srK2nbTkJOYekh+jI5NEcqA5FIkF5VC8pgyKHyiH4gdByaEa2RgKhUIH/d4xWamMyUr9yLbU5CSOKs3hqNIcLp5VwsMr63lqbRPPrWumo6ef786dxJPRs7FnHJJPZurBf78ExyfJochwUQ7Fa8qg+IFyKH4QlBxqanEMtba2xuyzCzJSuPqE8dx6/hSyUkO8XN3Cf7+wkefXNQNw3vRgLKstn1wscyiyv5RD8ZoyKH6gHIofBCWHamRjqKioKObfcUhhBjedXUFGShJLq1rY0TvAzOJMJhekx/y7JTHEI4ciH0c5FK8pg+IHyqH4QVByqEY2hpqbm+PyPVOLMvnxWRWkp0R+nDobK4PFK4ci+6IciteUQfED5VD8ICg51DWyMRS5i1B8zCzO4pbzKnm3voM5FXlx+17xv3jmUGQoyqF4TRkUP1AOxQ+CkkM1sjEU79P2FQUZQ95bVkauoEwfkcSmHIrXlEHxA+VQ/CAoOdTU4hiqr6/3ugQR5VB8QTkUrymD4gfKofhBUHKoRjaGsrKyvC5BRDkUX1AOxWvKoPiBcih+EJQcqpEVERERERGRhKJGNoba29u9LkFEORRfUA7Fa8qg+IFyKH4QlByqkY2h4uJir0sQUQ7FF5RD8ZoyKH6gHIofBCWHamRjqLGx0esSRJRD8QXlULymDIofKIfiB0HJoRrZGDIzr0sQUQ7FF5RD8ZoyKH6gHIofBCWHamRjKD8/3+sSRJRD8QXlULymDIofKIfiB0HJoRrZGArKaXtJbMqh+IFyKF5TBsUPlEPxg6DkUI1sDOXk5HhdgohyKL6gHIrXlEHxA+VQ/CAoOVQjG0P9/f1elyCiHIovKIfiNWVQ/EA5FD8ISg7VyMZQR0eH1yWIKIfiC8qheE0ZFD9QDsUPgpJDNbIxVFJS4nUJIsqh+IJyKF5TBsUPlEPxg6DkUI1sDNXV1XldgohyKL6gHIrXlEHxA+VQ/CAoOVQjG0N//vOfvS5BRDkUX1AOxWvKoPiBcih+EJQcqpGNoUceecTrEkSUQ/EF5VC8pgyKHyiH4gdByaEa2Rjq6+vzugQR5VB8QTkUrymD4gfKofhBUHJozjmvazhoS5YsaQSqva5jKM3NzYX5+flNXtchI5tyKH6gHIrXlEHxA+VQ/CDBclg2d+7cor3tSOhGVkREREREREYeTS0WERERERGRhKJGVkRERERERBKKGlkRERERERFJKGpkY8TMzjKz98xsvZld53U9MjKYWZWZrTKzFWb2enRbvpk9b2bron/neV2nBIuZ3W1mDWb2zqBte82dRfwyOja+bWZHeVe5BMkQObzBzLZEx8QVZnbOoH3fiebwPTM705uqJUjMbIKZvWhmq83sXTP7RnS7xkOJm33kMHDjoRrZGDCzEHAbcDYwA7jYzGZ4W5WMIHOcc7Occ7Ojz68DljjnKoEl0eciw+n3wFm7bRsqd2cDldE/VwC3x6lGCb7fs2cOAX4eHRNnOeeeBoj+Tl4AzIy+5zfR390in0Qf8C3n3AzgeGBRNGsaDyWehsohBGw8VCMbG8cC651zHzjneoCHgPke1yQj13zgnujje4ALPKxFAsg593egebfNQ+VuPnCvi3gVGG1mY+NTqQTZEDkcynzgIedct3NuI7CeyO9ukYPmnKt1zr0ZfdwGrAFK0XgocbSPHA4lYcdDNbKxUQrUDHq+mX0HSGS4OOA5M3vDzK6Ibit2ztVGH9cBxd6UJiPMULnT+Cjx9rXotM27B11aoRxKTJlZOXAksAyNh+KR3XIIARsP1ciKBMvJzrmjiExXWmRmpw7e6SI3jtbNoyWulDvx0O1ABTALqAV+5m05MhKYWRbwJ+CbzrnWwfs0Hkq87CWHgRsP1cjGxhZgwqDn46PbRGLKObcl+ncD8CiRqSH1O6cqRf9u8K5CGUGGyp3GR4kb51y9c67fOTcA3MmH0+WUQ4kJM0sh0jzc75x7JLpZ46HE1d5yGMTxUI1sbLwGVJrZJDNLJXIB9eMe1yQBZ2aZZpa98zEwD3iHSPYui77sMuAxbyqUEWao3D0OXBpdrfN4oGXQlDuRYbXb9YYXEhkTIZLDBWY2yswmEVlsZ3m865NgMTMDfgescc7dMmiXxkOJm6FyGMTxMNnrAoLIOddnZl8DngVCwN3OuXc9LkuCrxh4NDJ+kQw84Jx7xsxeAxab2eVANXCRhzVKAJnZg8BpQKGZbQb+E7iZvefuaeAcIotJ7AAWxr1gCaQhcniamc0iMpWzCrgSwDn3rpktBlYTWeFzkXOu34u6JVBOAi4BVpnZiui269F4KPE1VA4vDtp4aJGp+iIiIiIiIiKJQVOLRUREREREJKGokRUREREREZGEokZWREREREREEooaWREREREREUkoamRFREREREQkoaiRFRERERERkYSiRlZERCTOzKzKzDrNrM3MtpvZP8zsq2am38siIiL7Qb8wRUREvHG+cy4bKANuBq4FfudtSSIiIolBjayIiIiHnHMtzrnHgS8Al5nZoWZ2rpm9ZWatZlZjZjfsfL2ZPWVm1wz+DDN728wutIifm1lD9L2rzOzQOB+SiIhIzKmRFRER8QHn3HJgM3AK0AFcCowGzgWuMrMLoi+9B/jyzveZ2RFAKfAUMA84FZgC5AIXAdvidAgiIiJxo0ZWRETEP7YC+c65l5xzq5xzA865t4EHgU9FX/M4MMXMKqPPLwEeds71AL1ANjANMOfcGudcbZyPQUREJObUyIqIiPhHKdBsZseZ2Ytm1mhmLcBXgUIA51wX8DDw5ejiUBcD/xvd9wLwa+A2oMHM7jCzHC8OREREJJbUyIqIiPiAmR1DpJFdCjxA5MzrBOdcLvBbwAa9/B7gS8BcYIdz7pWdO5xzv3TOHQ3MIDLF+NvxOQIREZH4USMrIiLiITPLMbPzgIeA+5xzq4hMD252znWZ2bHAFwe/J9q4DgA/I3o2NvpZx0TP5qYQuc62K/o6ERGRQFEjKyIi4o0nzKwNqAG+C9wCLIzuuxr4YXT/D4DFe3n/vcBhwH2DtuUAdwJhoJrIQk8/jUn1IiIiHjLnnNc1iIiIyAEys0uBK5xzJ3tdi4iISLzpjKyIiEiCMbMMImdt7/C6FhERES+okRUREUkgZnYm0AjUE1kUSkREZMTR1GIRERERERFJKDojKyIiIiIiIglFjayIiIiIiIgkFDWyIiIiIiIiklDUyIqIiIiIiEhCUSMrIiIiIiIiCeX/AdoB1W9i+kgDAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1152x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "COT3sjvWLKcz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "ca4952d0-73f2-48e6-81c8-742afaa1eeb6"
      },
      "source": [
        "#Get the close price\n",
        "df = df[['Close']]\n",
        "df.head(4)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>205.360001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>205.080002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>192.729996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>195.490005</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Close\n",
              "0  205.360001\n",
              "1  205.080002\n",
              "2  192.729996\n",
              "3  195.490005"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a15qim_sLVp2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "e690f070-b3a4-4c8e-e462-a366f347e06a"
      },
      "source": [
        "#Create a variable to predict the 'x' days out into the future\n",
        "future_days = 25\n",
        "#Create column for target data (x unints/days)\n",
        "df['Prediction'] = df[['Close']].shift(-future_days)\n",
        "df.tail(4)\n"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Close</th>\n",
              "      <th>Prediction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>248</th>\n",
              "      <td>790.960022</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>249</th>\n",
              "      <td>803.330017</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250</th>\n",
              "      <td>799.169983</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>251</th>\n",
              "      <td>813.630005</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Close  Prediction\n",
              "248  790.960022         NaN\n",
              "249  803.330017         NaN\n",
              "250  799.169983         NaN\n",
              "251  813.630005         NaN"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OaFXFMrfL2Gw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "c3e28b68-d2d6-4dda-f7cb-702446853d82"
      },
      "source": [
        "#Create the feature data set (X) and convert it tit np array and remove 'x' rows/days\n",
        "X = np.array(df.drop(['Prediction'], 1))[:-future_days]\n",
        "print(X)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[205.360001]\n",
            " [205.080002]\n",
            " [192.729996]\n",
            " [195.490005]\n",
            " [190.630005]\n",
            " [188.699997]\n",
            " [189.860001]\n",
            " [188.220001]\n",
            " [185.160004]\n",
            " [178.970001]\n",
            " [193.600006]\n",
            " [196.589996]\n",
            " [205.949997]\n",
            " [204.5     ]\n",
            " [212.880005]\n",
            " [217.100006]\n",
            " [209.259995]\n",
            " [213.910004]\n",
            " [214.919998]\n",
            " [225.029999]\n",
            " [224.740005]\n",
            " [226.429993]\n",
            " [219.619995]\n",
            " [221.860001]\n",
            " [223.639999]\n",
            " [219.759995]\n",
            " [219.270004]\n",
            " [222.839996]\n",
            " [223.460007]\n",
            " [227.169998]\n",
            " [224.550003]\n",
            " [234.899994]\n",
            " [233.100006]\n",
            " [230.339996]\n",
            " [230.059998]\n",
            " [238.919998]\n",
            " [238.600006]\n",
            " [245.080002]\n",
            " [253.5     ]\n",
            " [252.380005]\n",
            " [254.860001]\n",
            " [253.539993]\n",
            " [258.179993]\n",
            " [255.679993]\n",
            " [260.170013]\n",
            " [264.880005]\n",
            " [228.820007]\n",
            " [228.039993]\n",
            " [235.770004]\n",
            " [242.259995]\n",
            " [241.610001]\n",
            " [233.850006]\n",
            " [234.339996]\n",
            " [228.320007]\n",
            " [230.75    ]\n",
            " [233.419998]\n",
            " [238.300003]\n",
            " [235.009995]\n",
            " [229.009995]\n",
            " [235.      ]\n",
            " [219.619995]\n",
            " [215.639999]\n",
            " [219.940002]\n",
            " [226.830002]\n",
            " [225.860001]\n",
            " [220.830002]\n",
            " [222.149994]\n",
            " [211.399994]\n",
            " [215.      ]\n",
            " [214.080002]\n",
            " [215.589996]\n",
            " [221.710007]\n",
            " [225.610001]\n",
            " [225.009995]\n",
            " [220.679993]\n",
            " [229.580002]\n",
            " [227.449997]\n",
            " [231.789993]\n",
            " [235.539993]\n",
            " [247.100006]\n",
            " [245.869995]\n",
            " [245.199997]\n",
            " [242.809998]\n",
            " [244.789993]\n",
            " [243.490005]\n",
            " [246.600006]\n",
            " [240.619995]\n",
            " [241.229996]\n",
            " [223.210007]\n",
            " [228.699997]\n",
            " [242.559998]\n",
            " [242.130005]\n",
            " [240.869995]\n",
            " [244.690002]\n",
            " [243.130005]\n",
            " [233.029999]\n",
            " [231.429993]\n",
            " [237.720001]\n",
            " [240.050003]\n",
            " [244.529999]\n",
            " [244.740005]\n",
            " [247.889999]\n",
            " [256.959991]\n",
            " [257.890015]\n",
            " [259.75    ]\n",
            " [261.970001]\n",
            " [256.950012]\n",
            " [253.5     ]\n",
            " [255.580002]\n",
            " [254.679993]\n",
            " [299.679993]\n",
            " [328.130005]\n",
            " [327.709991]\n",
            " [316.220001]\n",
            " [315.01001 ]\n",
            " [314.920013]\n",
            " [313.309998]\n",
            " [317.470001]\n",
            " [317.220001]\n",
            " [326.579987]\n",
            " [335.540009]\n",
            " [337.140015]\n",
            " [345.089996]\n",
            " [349.929993]\n",
            " [346.109985]\n",
            " [349.350006]\n",
            " [352.170013]\n",
            " [349.98999 ]\n",
            " [359.519989]\n",
            " [352.220001]\n",
            " [354.829987]\n",
            " [333.040009]\n",
            " [336.339996]\n",
            " [328.920013]\n",
            " [331.290009]\n",
            " [329.940002]\n",
            " [334.869995]\n",
            " [336.200012]\n",
            " [333.029999]\n",
            " [330.369995]\n",
            " [335.890015]\n",
            " [339.529999]\n",
            " [348.839996]\n",
            " [352.700012]\n",
            " [359.679993]\n",
            " [358.390015]\n",
            " [381.5     ]\n",
            " [378.98999 ]\n",
            " [393.149994]\n",
            " [404.040009]\n",
            " [405.589996]\n",
            " [419.220001]\n",
            " [425.25    ]\n",
            " [430.940002]\n",
            " [430.380005]\n",
            " [414.700012]\n",
            " [418.329987]\n",
            " [430.26001 ]\n",
            " [443.01001 ]\n",
            " [451.540009]\n",
            " [469.059998]\n",
            " [492.140015]\n",
            " [481.339996]\n",
            " [478.149994]\n",
            " [524.859985]\n",
            " [537.919983]\n",
            " [518.5     ]\n",
            " [513.48999 ]\n",
            " [510.5     ]\n",
            " [547.200012]\n",
            " [569.559998]\n",
            " [572.200012]\n",
            " [564.820007]\n",
            " [558.02002 ]\n",
            " [566.900024]\n",
            " [580.98999 ]\n",
            " [640.809998]\n",
            " [650.570007]\n",
            " [780.      ]\n",
            " [887.059998]\n",
            " [734.700012]\n",
            " [748.960022]\n",
            " [748.070007]\n",
            " [771.280029]\n",
            " [774.380005]\n",
            " [767.289978]\n",
            " [804.      ]\n",
            " [800.030029]\n",
            " [858.400024]\n",
            " [917.419983]\n",
            " [899.409973]\n",
            " [901.      ]\n",
            " [833.789978]\n",
            " [799.909973]\n",
            " [778.799988]\n",
            " [679.      ]\n",
            " [667.98999 ]\n",
            " [743.619995]\n",
            " [745.51001 ]\n",
            " [749.5     ]\n",
            " [724.539978]\n",
            " [703.47998 ]\n",
            " [608.      ]\n",
            " [645.330017]\n",
            " [634.22998 ]\n",
            " [560.549988]\n",
            " [546.619995]\n",
            " [445.070007]\n",
            " [430.200012]\n",
            " [361.220001]\n",
            " [427.640015]\n",
            " [427.529999]\n",
            " [434.290009]\n",
            " [505.      ]\n",
            " [539.25    ]\n",
            " [528.159973]\n",
            " [514.359985]\n",
            " [502.130005]\n",
            " [524.      ]\n",
            " [481.559998]\n",
            " [454.470001]\n",
            " [480.01001 ]\n",
            " [516.23999 ]\n",
            " [545.450012]\n",
            " [548.840027]\n",
            " [573.      ]\n",
            " [650.950012]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5d3V-rBhMPsK",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 663
        },
        "outputId": "1a9b4b10-820b-471b-afbc-12bb2ab7dc9f"
      },
      "source": [
        "#Create the target data set (y) and convert it ti a np array and get all of target values except the last rows\n",
        "y = np.array(df['Prediction'])[:-future_days]\n",
        "print(y)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[219.759995 219.270004 222.839996 223.460007 227.169998 224.550003\n",
            " 234.899994 233.100006 230.339996 230.059998 238.919998 238.600006\n",
            " 245.080002 253.5      252.380005 254.860001 253.539993 258.179993\n",
            " 255.679993 260.170013 264.880005 228.820007 228.039993 235.770004\n",
            " 242.259995 241.610001 233.850006 234.339996 228.320007 230.75\n",
            " 233.419998 238.300003 235.009995 229.009995 235.       219.619995\n",
            " 215.639999 219.940002 226.830002 225.860001 220.830002 222.149994\n",
            " 211.399994 215.       214.080002 215.589996 221.710007 225.610001\n",
            " 225.009995 220.679993 229.580002 227.449997 231.789993 235.539993\n",
            " 247.100006 245.869995 245.199997 242.809998 244.789993 243.490005\n",
            " 246.600006 240.619995 241.229996 223.210007 228.699997 242.559998\n",
            " 242.130005 240.869995 244.690002 243.130005 233.029999 231.429993\n",
            " 237.720001 240.050003 244.529999 244.740005 247.889999 256.959991\n",
            " 257.890015 259.75     261.970001 256.950012 253.5      255.580002\n",
            " 254.679993 299.679993 328.130005 327.709991 316.220001 315.01001\n",
            " 314.920013 313.309998 317.470001 317.220001 326.579987 335.540009\n",
            " 337.140015 345.089996 349.929993 346.109985 349.350006 352.170013\n",
            " 349.98999  359.519989 352.220001 354.829987 333.040009 336.339996\n",
            " 328.920013 331.290009 329.940002 334.869995 336.200012 333.029999\n",
            " 330.369995 335.890015 339.529999 348.839996 352.700012 359.679993\n",
            " 358.390015 381.5      378.98999  393.149994 404.040009 405.589996\n",
            " 419.220001 425.25     430.940002 430.380005 414.700012 418.329987\n",
            " 430.26001  443.01001  451.540009 469.059998 492.140015 481.339996\n",
            " 478.149994 524.859985 537.919983 518.5      513.48999  510.5\n",
            " 547.200012 569.559998 572.200012 564.820007 558.02002  566.900024\n",
            " 580.98999  640.809998 650.570007 780.       887.059998 734.700012\n",
            " 748.960022 748.070007 771.280029 774.380005 767.289978 804.\n",
            " 800.030029 858.400024 917.419983 899.409973 901.       833.789978\n",
            " 799.909973 778.799988 679.       667.98999  743.619995 745.51001\n",
            " 749.5      724.539978 703.47998  608.       645.330017 634.22998\n",
            " 560.549988 546.619995 445.070007 430.200012 361.220001 427.640015\n",
            " 427.529999 434.290009 505.       539.25     528.159973 514.359985\n",
            " 502.130005 524.       481.559998 454.470001 480.01001  516.23999\n",
            " 545.450012 548.840027 573.       650.950012 709.890015 729.830017\n",
            " 745.210022 753.890015 746.359985 686.719971 732.109985 705.630005\n",
            " 725.150024 798.75     769.119995 800.51001  781.880005 701.320007\n",
            " 761.190002 768.210022 782.580017 780.039978 819.419983 811.289978\n",
            " 809.409973 790.960022 803.330017 799.169983 813.630005]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ttXatlkuMs-Q",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Split the data into 75% training and 25% testing\n",
        "x_train, x_test, y_train, y_test = train_test_split(X, y, test_size = 0.25)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8EU7_QWXM_fA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Create the models\n",
        "#Create the decision tree regressor model\n",
        "tree = DecisionTreeRegressor().fit(x_train, y_train)\n",
        "#Create the linear regression model\n",
        "lr = LinearRegression().fit(x_train, y_train)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bODwrjtPNoe9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 442
        },
        "outputId": "5ed6c26b-d430-4e01-c997-25d7496b1174"
      },
      "source": [
        "#Get the last x rows from the feature data set\n",
        "x_future = df.drop(['Prediction'], 1)[:-future_days]\n",
        "x_future = x_future.tail(future_days)\n",
        "x_future = np.array(x_future)\n",
        "x_future"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[608.      ],\n",
              "       [645.330017],\n",
              "       [634.22998 ],\n",
              "       [560.549988],\n",
              "       [546.619995],\n",
              "       [445.070007],\n",
              "       [430.200012],\n",
              "       [361.220001],\n",
              "       [427.640015],\n",
              "       [427.529999],\n",
              "       [434.290009],\n",
              "       [505.      ],\n",
              "       [539.25    ],\n",
              "       [528.159973],\n",
              "       [514.359985],\n",
              "       [502.130005],\n",
              "       [524.      ],\n",
              "       [481.559998],\n",
              "       [454.470001],\n",
              "       [480.01001 ],\n",
              "       [516.23999 ],\n",
              "       [545.450012],\n",
              "       [548.840027],\n",
              "       [573.      ],\n",
              "       [650.950012]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eP1r-dj8ONLg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "e564d9fb-a25d-403d-d43b-d00f26548821"
      },
      "source": [
        "#Show the model tree prediction\n",
        "tree_prediction = tree.predict(x_future)\n",
        "print(tree_prediction)\n",
        "print()\n",
        "#Show the model linear regression\n",
        "lr_prediction = lr.predict(x_future)\n",
        "print(lr_prediction)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[709.890015 729.830017 745.210022 745.51001  746.359985 686.719971\n",
            " 732.109985 705.630005 725.150024 725.150024 769.119995 800.51001\n",
            " 781.880005 701.320007 761.190002 768.210022 917.419983 800.030029\n",
            " 819.419983 811.289978 809.409973 790.960022 803.330017 679.\n",
            " 813.630005]\n",
            "\n",
            "[613.3810097  641.77704564 633.33351749 577.28693973 566.69073288\n",
            " 489.44412706 478.13288355 425.66146702 476.1855561  476.10186961\n",
            " 481.24404479 535.03141503 561.08455695 552.64864316 542.15132795\n",
            " 532.84827964 549.48425288 517.20117565 496.59447385 516.02213748\n",
            " 543.58140202 565.80075527 568.37945722 586.75736103 646.05203914]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "chjuGlylOsqG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 615
        },
        "outputId": "770ec53e-d10b-4894-fdd9-708343f7f848"
      },
      "source": [
        "#Visualizing\n",
        "predictions = tree_prediction\n",
        "\n",
        "valid = df[X.shape[0]:]\n",
        "valid['Predictions'] = predictions\n",
        "plt.figure(figsize=(16,8))\n",
        "plt.title('Model')\n",
        "plt.xlabel('Days')\n",
        "plt.ylabel('Close price USD $')\n",
        "plt.plot(df['Close'])\n",
        "plt.plot(valid[['Close', 'Predictions']])\n",
        "plt.legend(['Orig', 'Val', 'Pred'])\n",
        "plt.show()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AEG4ujaXQQFZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 615
        },
        "outputId": "ba9121bb-5548-47a1-8557-4c8343e69caf"
      },
      "source": [
        "#Visualizing\n",
        "predictions = lr_prediction\n",
        "\n",
        "valid = df[X.shape[0]:]\n",
        "valid['Predictions'] = predictions\n",
        "plt.figure(figsize=(16,8))\n",
        "plt.title('Model')\n",
        "plt.xlabel('Days')\n",
        "plt.ylabel('Close price USD $')\n",
        "plt.plot(df['Close'])\n",
        "plt.plot(valid[['Close', 'Predictions']])\n",
        "plt.legend(['Orig', 'Val', 'Pred'])\n",
        "plt.show()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}