Class_kernel_Dual_of_SVM_hard_constraint.ipynb

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          "text": [
            "Requirement already satisfied: pyomo in /usr/local/lib/python3.11/dist-packages (6.8.2)\n",
            "Requirement already satisfied: ply in /usr/local/lib/python3.11/dist-packages (from pyomo) (3.11)\n"
          ]
        }
      ],
      "source": [
        "!pip install pyomo\n",
        "from pyomo.environ import *\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import random\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/Kernel SVM.csv')\n",
        "df"
      ],
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          "height": 1000
        },
        "id": "zrbUeAoyGth-",
        "outputId": "47f27739-a5b9-4ab7-b016-4c626b05161c"
      },
      "execution_count": null,
      "outputs": [
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              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d99207bb-17ab-48c5-9353-4147b0b13116 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_139845f3-bafe-4d40-a2d8-08a9c875d16f\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_139845f3-bafe-4d40-a2d8-08a9c875d16f button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 49,\n  \"fields\": [\n    {\n      \"column\": \"x1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5346414082145933,\n        \"min\": -0.928137962,\n        \"max\": 0.9742821202,\n        \"num_unique_values\": 49,\n        \"samples\": [\n          -0.5946103161,\n          0.7955124156,\n          -0.6304073893\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"x2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.6537314455756854,\n        \"min\": -0.9813815415,\n        \"max\": 0.9560941357,\n        \"num_unique_values\": 49,\n        \"samples\": [\n          -0.5277304802,\n          0.7156344186,\n          -0.896849117\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"y\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": -1,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          -1,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "id": "hCss9gEhNCUV",
        "outputId": "165803ee-02c9-48b1-a15a-1205a2d1e72d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "\"\\nn = 10\\ndf = pd.DataFrame()\\nred = [1 for i in range(n)]\\ngreen = [-1 for i in range(n)]\\n\\ndf['f1'] = [np.random.randint(3, 15) for n in range(n) ] + [np.random.randint(1, 7) for n in range(n) ]\\ndf['f2'] = [np.random.randint(3, 15) for n in range(n)] + [np.random.randint(1, 7) for n in range(n)]\\ndf['y'] = red+green\\ndf\\n\""
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget -N -q \"https://github.com/thomasfork/ipopt_linux/raw/main/ipopt-linux64.zip\"\n",
        "!unzip -o -q ipopt-linux64\n",
        "\n",
        "opt = SolverFactory('ipopt', executable='/content/ipopt')"
      ],
      "metadata": {
        "id": "s8zQrvAxJxfs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "![Screenshot 2025-02-07 at 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SpWSLVu2SI4cOaxEiIcABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACyQigOEyGJGNEjB49Wh588EHJlSuXXHvttdKwYUPTvKaekCtSpIh56u6PP/6QnTt3mgqxSZMmmWYz9TSfVVD/h99++63oZ3oEPUGpSjc9IRgu3HjjjdKzZ0+5/vrrzZOE4WRSGqd+EydOnCgDBgyQdevWmQpDVRy6DWqWVE2c9urVy/YUaL58+aRWrVqi5mJVUbly5UrRvKFB29GjR4/QaO4hAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAgCUBFIeWaBI7QZVrerqtSpUqki1bNlcPu3fvXnn77bdl4MCBYZVVWkilSpVkyZIlaX7yUM2Svvzyy2GfQxWFr7zyilx33XVh06MduXjxYqlYsaLoyUY3Yf/+/dKqVSvR05JWQU9GDh48WK688sogpeeaNWukU6dO8v333wdlVeXtrl27guK4gQAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAJ2BFAc2tEhLSyBOXPmSNu2beXQoUNh02vXri1ff/215M6dO2x6tCO7du1qKjRDy1VTne+8846pWAtN88q9nhq8+eab5eeffw7bJPW1qKcH9XSo+k4MF3799VdTARzoz1Fljx49ap4oDZeHOAhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAQSgDFYSgR7l0R2Lp1q9SpU8dSefjUU0/Ja6+95qqs1AipedA2bdokK6JcuXIyefJkqV69erI0r0Sof0RVGupJznChRIkSsmDBAqlQoUK45KC4hx9+WEaOHBkU98MPP8jll18eFMcNBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACELAigOLQigzxjgSmTZsmt912W1i57Nmzy+bNm6VMmTJh06MRuW3bNqlZs6YcPnw4qDhVlqnZTz2t59WwdOlSadasmaXi9aKLLjKVhuXLl3f1COrPMFRRO3PmTLnllltc5UcIAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCKA4ZAykikCXLl1k6NChYcvQk4Djx48PmxaNyLp168qyZcuCirrwwgtlxYoVMVVYBlWYgptZs2ZJy5Yt5dixY2Fz60nDRYsWiZ6adBvUv6P6eQwM6mtSfSMSIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgIAbAigO3VBCxpLAvn37TCXdyZMnw8qsXr3aPBUYNjEVkaowVMVhYMiWLZt5Si80PlAmva9Vkdq+fXs5ffp02KZkyZJFFi9eLFdffXXYdKvIjh07ygcffBCUrL4P9eQiAQIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQi4IYDi0A0lZGwJdO7cWd59992wMk8++aQMHjw4bFpqIu+55x755JNPgop48MEHZdSoUUFxXrpRf4WNGjWyVBpqW9XcqPqHjCScO3dOSpYsKXv27EnKdv7558vBgwflvPPOS4rjAgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQjYEUBxaEeHNFcE1q9fL9WqVQsrW6pUKdm5c2fYtJRG7t+/X7TcU6dOJRWhCjL1qVihQoWkOC9dbNmyxTxFeOjQIctmqc9D9RuZKVMmS5lwCQsXLpQGDRoEJd13333y/vvvB8VxAwEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAATsCKA4tKNDmmsCahLzt99+CyuvPgdr1aoVNi0lkapcu+2224KytmjRQiZPnhwU55Wbv/76S6688krZtm2bZZPUN+OmTZukYMGCljJWCa1bt5ZJkyYFJc+ZM0duvvnmoDhuIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgIAdARSHdnRIc03g/vvvtzzh1qNHDxkwYIDrspwE33zzTVETqIFB/ft16NAhMMoz161atXJUao4ZM0bUT2Gk4dtvv5V69eoFZatevbqob0nMlAZh4QYCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEHAigOHQCR7I6AKu6sFF9XXXWVLFu2zF1BLqQee+wxGTJkSJCkKtDq1q0bFOeFm9GjR4v6XrQL2u4lS5ZEbKL0zJkzpvnTVatWBRU/b948ufHGG4PiuIEABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACTgRQHDoRIt0VAVVWWZnGzJcvn/z999+uynEj1Lx5c5k+fXqQ6O+//y5q7tNLYceOHXLZZZfJsWPHLJuVOXNm83SglY9Iy4xGQrdu3eSNN94IElE2asqVAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQiJYDiMFJiyIcl8MMPP0jVqlXDpmnkrl27pGTJkpbpkSTceeedMnXq1KAsevpOlXBeCm5MlD7yyCMybNiwiJs9ceJEadOmTVC+4sWLy9q1az2nQA1qJDcQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQh4lgCKQ892TXw17I8//pDChQtbNnr27NnSqFEjy/RIErp37y6DBw8OyqKn+0qXLh0Ul54333zzjVx33XW2TciRI4ds27ZNVOEXSVClYbt27eTUqVNJ2VRpOn/+fLn++uuT4riAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAApEQQHEYCS1kLQmcO3dOsmfPLnryL1x4/fXXTdOa4dIijVP/hurnMDAsWLBA6tevHxiVbtfKolatWvL999/btqFr167y5ptv2sqEJg4fPly6dOkiWkdgePuqeVrGAABAAElEQVTtt5MxCUznGgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQg4EUBx6ESIdNcE9OTc3r17w8qrok+VW9EIM2bMkGbNmgUVpeY+1eynF8L7778v999/v21TcubMKb/88osULVrUVi4wsXfv3vLCCy8ERpnXffr0keeeey5ZPBEQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAIBICKA4joYWsLQH1cai+DsOF++67T1ShFo2wefNmqVy5clBRV155paxcuTIoLj1ujh49KhUqVJB9+/bZVt+tWzfRU5hugs/nkyeeeCKs4vWZZ56R/v37uykGGQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCBgSwDFoS0eEiMhUKlSJdmyZUvYLC1btpRJkyaFTUtJZLVq1WT9+vVBWZcvXy516tQJikvrm549ezoq8s477zzTt2GZMmUcm/fzzz9Lp06dZNGiRUGyWsbAgQNF/T0SIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgEA0CKA4jAbFBCrjn3/+kV27dsnOnTuT/v7++28pVqyYqKJL/1Rplzdv3mRPbWeqtHHjxjJr1qxkeVIa8d5775kKtcD8rVu3lgkTJgRGpem1crvkkkvkxIkTtvU2adJE1NyqXTh79qwMHjxYXnzxRTl+/HiQqJo5/fjjj+WOO+4IiucGAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCKSGAIrD1NBLkLy7d++WcePGyYcffiibNm1yfKp8+fLJAw88II8//ripSPRnyJ07txw7dsx/G/R5zTXXyJIlS4LiUnOjyrSSJUvKgQMHgor54IMPpEOHDkFxaXXz4IMPyujRox2r+/LLL5P5aAzMpOZe1UfiqlWrAqPN64svvthUjqppVgIEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQiCYBFIfRpBlHZZ06dco0HTp27FiZP3++nDt3LuLWZ86cWe69914ZPny46EnFCy+80LIMPaW4du1ay/SUJOhpvFdeeSUoa44cOWTp0qVSo0aNoPhY32zbtk3UVOuZM2dsqypVqpRs375d1NRoaPjrr79kwIABpu/D06dPhyZLu3btZOjQoWFPeyYTJgICEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIREgAxWGEwBJB/LvvvjPNfG7YsCEqj6On3/r06SNqjtQqqFLNzWlGq/zh4lW51rBhQ/nmm2+CkvUkopoCrVKlSlB8LG/0lKOe2HQKyum5554LElNTsG+88Ya8+eaboteh4YILLpBhw4bJXXfdFZrEPQQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCIGgEUh1FD6f2C9FSgKq3eeecdxxOGFSpUkBYtWpj+DPW0YP78+WXNmjUyaNAgWbBgQcQPe8UVV4Q1vRlxQSEZfv/9d9Gy1dxqYMiVK5e8++67cvfddwdGx+R68+bNcvnll4v6JbQLWbNmNf1HFi1a1BQ7fPiwvPXWW6YvQz1tGBr0VKKahO3Xr58UKlQoNJl7CEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIBBVAigOo4rTu4Xpqbz27dvLjh07bBup5kbVBGjnzp1FFV2hQU2a9u/fX55//vnQJNv7+vXrp0jhaFvo/xJXrlwpWn44/4qPPvqoac60YMGCbopKkUybNm1k4sSJjnlbtWpl+idcvHix6VNy0qRJYU8YakF16tSRIUOGCL4MHbEiAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQJQIoDiMEkgvFzN79my588475fjx47bN7NKli3m6LW/evLZymqhKsMmTJzvK+QWaN28u06ZN899G/XPdunXmCUn1NRga8uTJI48//rh0795dChQoEJqcqnutV/0p+nw+x3Jq164t+/btM08dWgnXq1dPnnnmGWnSpIlkypTJSox4CEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIBB1AigOo47UWwV+8cUX0rp1azl16pRtwwYMGCA9evSwlQlMVAVd5cqVRf0MuglqMvTjjz92I5piGTX32a5dO5k+fXrYMlQhes8998jtt98uDRo0kGzZsoWViyRSFaJW9bktRxWEzZo1MxWGdevWdZsNOQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAQVQIoDqOK01uFqflMVZSdOXPGsmGZM2eWESNGSKdOnSxlrBLU/96YMWOskoPiH3roIbOeoMgY3OjJPzXxqX4B9XSfVciXL595qu/GG280/RNeeuml4uakZWB5y5cvl6uvvjowKqLrHDlyiJo5VYWt1k+AAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAulJAMVhetKPYd3z5s2TW265Rc6ePWtby9ixY03fh7ZCFol6gvDee++1SA2Ofvrpp2XgwIHBkTG8U7OsqhDVOu0UiIFNKFWqlKnAK1KkiKlEVEWi/uXOndtUvqoPxYMHD8qePXtMc6ObNm0SPeUYSciZM6c0btzYNPWqpwwjVVZGUheyEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQCASAigOI6EVJ7J//vmnVK1aVfbu3WvbYj0xOHr0aFsZu8QNGzZIlSpV7ESS0oYNGyaPPPJI0n1aXagCcdSoUTJu3DhZvXq1K1+E0W6bKgtViat+IVVZqD4XCRCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEDAawRQHHqtR6LQnltvvVW+/PJL25LUNObKlSslV65ctnJ2iXryrkSJEnYiSWlfffWVNGzYMOk+PS5+++03k8u0adPk66+/lpMnT8a8Gcr3559/lmLFisW8LiqAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAqkhgOIwNfQ8mHfo0KHSpUsX25bpCbgVK1aYvv1sBR0Sd+/eLSVLlnSQ+v/kX3/9VS666CJXsmkhpCcRf/zxR9m4caP5p9dqelRPax45ckTOnTsXthlZs2aV06dPh00LF5nWJlrDtYE4CEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIOCGAIpDN5TiRGbbtm2mMvDEiRO2LX755ZflhRdesJVxk+jWVKmeujt69KhkypTJTbHpLuPz+eSff/4xFYiqRNR258uXz/zLkiWLVK9e3VQ6OjVUTZJu375dChUq5CRKOgQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhBIdwIoDtO9C6LXAPVZOGbMGNsCVYn1yy+/SN68eW3l3CSquU835kdV0bZmzRo3RXpeZtCgQaKnCN2EZ599Vvr16+dGFBkIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgkO4EUBymexdEpwG7du2S8uXLO5rRVMVX9+7do1Lp+PHjpW3bto5ltW7dWiZMmOAo53UB9ZFYqVIl8/SkU1tVMbtjxw4pUKCAkyjpEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQMATBFAceqIbUt8I9Wuo/g3tQokSJeTnn3+WHDly2Im5TnvzzTflySefdJTv3bu3PP/8845yXhe46667XCtAX331Vfnvf//r9UeifRCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgiQCKwyQU8Xuxb98+KVu2rDj5NlRFX9euXaP2oB06dJAPP/zQsbylS5fK1Vdf7SjnZQG3Zln1GS655BJZv369ZMuWzcuPRNsgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQBABFIdBOOLzpk+fPtKrVy/bxmfJkkX27NkjF154oa1cJImqIPvpp59ss+TLl08OHDggWn+8htOnT0u1atVk06ZNrh5h7ty5ctNNN7mSRQgCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIeIUAikOv9EQq2lG3bl1ZtmyZbQlNmzaV6dOn28pEknjw4EEpVKiQ+Hw+22zNmzeXadOm2cp4PfG1116THj16uGpmixYtZPLkya5kEYIABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACXiKA4tBLvZGCtqgCr3DhwnL27Fnb3J9++qmoj75ohVmzZkmTJk0ci3vrrbfk8ccfd5TzqsDu3bulcuXKcvToUccm5s6dW3788UcpVaqUoywCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQMBrBFAceq1HImzP+PHjpW3btra58ubNK/v375ecOXPaykWS+Pzzz0vfvn0ds2zcuFEuvfRSRzkvCuhpykaNGsm8efNcNW/48OHy8MMPu5JFCAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQh4jQCKQ6/1SITt6dChg3z44Ye2uWJhPrNixYqydetW23qLFStm+lW0FfJw4ttvvy1du3Z11cJbbrlFZs6c6UoWIQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCDgRQIoDr3YKxG0qVy5cvLLL7/Y5lAffU899ZStTCSJK1eulNq1aztm0dN3egovHoOaHL3iiivkxIkTjs0vWLCg/PDDD6KKUgIEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQiFcCKA7jtef+1241P+qk3Fq8eLFce+21UXtSPYWnp/Gcwvr166VKlSpOYp5LP3nypFx11VWydu1aV22bNGmStGzZ0pUsQhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEDAqwRQHHq1Z1y06++//5b8+fPbSmbJkkVULleuXLZybhPPnj0rJUqUMH0m2uVRRaUqLOMx6EnJkSNHumr6gw8+KKNGjXIlixAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQ8DIBFIde7h2Htm3evFkqV65sK1WjRg35/vvvbWUiSZwzZ440btzYMcv48eOlTZs2jnJeE1B/keo30k3QU4mLFi2SbNmyuRFHBgIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQh4mgCKQ093j33jFi5cKA0aNLAVat++vYwdO9ZWJpJELe+jjz6yzVK0aFHZtWuXZM2a1VbOa4lqWlWVgcePH3dsmj7j6tWrpXjx4o6yCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBeCCA4jAeesmijRMnTnQ81de9e3cZNGiQRQmRRR87dkyKFCkiR48etc3Yq1cveeWVV2xlvJb4559/Sp06deSXX35xbJoqRFVpW7duXUfZSASeeOIJWbJkieipx0svvTSSrMhCAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgVQTQHGYaoTpV8CUKVOkRYsWtg3o16+fPPvss7YybhPfeustUeWWXVCfijt27DD9INrJeSnt5MmT0rBhQ/n2229dNWvMmDHSsWNHV7JuhZ555hkZMGCAKa7+KL/55hupWbOm2+zIQQACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAIFUE0BxmGqE6VfA/Pnz5cYbb7RtwMiRI6Vz5862Mm4S1XznxRdfLPv27bMVVwVY//79bWW8lOjz+eSee+6RTz/91FWz9PSmnuKMZujdu7e88MILSUXqaUM9eXjBBRckxXEBAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABGJNAMVhrAnHsPxVq1ZJrVq1bGuYPHmy46lE2wL+lzh48GBHhVnFihVl3bp1kiNHDjdFekLmv//9rwwcONBVW5577jnp06ePK1m3QqFKw4suukiWLl0qJUuWdFsEchCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgKgRQHEYFY/oUsmfPHkeToF9++aU0a9YsVQ08ePCgVKpUSf744w/LcjJlyiSLFi2Sa6+91lLGbYL6UNRn++2332Tv3r2SOXNmKV68uKhSTT+zZ8/utihbOfXD+OKLL9rK+BMfffRRGTp0qP821Z9nz56VLl26yIgRI5LK0hOGetIQ/4ZJSLiAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgDQmgOExD2LGoqnDhwrYKvfHjx0ubNm1SVfV9990nY8eOtS3j4YcfluHDh9vKWCWeOXNG5s6da9YxZ84c+fvvv61EzfiiRYtK/fr1pVGjRuZfsWLFbOXDJarJ0aeffjpcUrK4bt26icqrcjQaQc2+3n333fL5558nFZc7d26TQd26dZPiuIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACaUkAxWFa0o5BXTfffLPMmzfPsuR3331XOnXqZJnulKAKPVXQ2QU9Cbhx40bJly+fnVjYtNGjR8vzzz8v+/fvD5vuJrJatWqmcrR9+/aOJzC1vJdeeklefvllx6JVUfjaa685mmh1LChAYNu2bWZbV69enRSrJw1nzJghV199dVIcFxCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgrQmgOExr4lGur3///tKzZ0/LUp944gl54403LNPtEn7//XfTh+KuXbvsxGT69OnStGlTW5nQxHPnzpkn/tR3YrTCeeedJ6pI7dixo9x2223JTJpqnWpydOTIkY5VZs2aVT744APzZKCjsEuBiRMnyoMPPiiHDx9OylGkSBHzpGHVqlWT4riAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAulBAMVhelCPYp07duyQiy++WHw+X9hSq1SpIuvXrw+bZhd54sQJadCggSxfvtxSTBV1qoRLyYnGIUOGyGOPPZas7AsvvNBU+l1++eVSoUIF8xSjtkX9K27evFkWLlwo3333nZw8eTJZ3sCIggULSocOHUxFnfpn3Ldvn9x7770yf/78QLGw12XLlpWPP/44aicADx06JD169BA9XRkYypQpY54WLV++fGA01xCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgXQigOEwX7NGt9Nprr5UlS5aELVTNbaoZUFXIuQ16Mu+uu+6SSZMmWWbJkiWL6ZNQffWlJKgvv2XLliVl1RN+Q4cONZV92bJlS4oPd6E+AqdMmSKjRo2SxYsXhxMJiqtdu7Zs3bpVVIHnFFS5qO1IidnV0LJVmTtmzBh55pln5M8//wxKvummm+STTz6RQoUKBcVzAwEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAATSiwCKw/QiH8V69RTdjTfeaFlinz595LnnnrNMD0xQM5r33HOPaX40MD7wOnv27DJhwgTzZGBgvNtrPS2YI0eOIHE9Fbhp06agODc3egrx9ddfN82Knjlzxk2WsDKlS5eWAQMGmP4HwwpEEKkKQ/VZ2Lt3b1mxYkVQTlXkal+oj0U9sUmAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAl4hgOLQKz2Rynbccccd8vnnn4ctJVeuXOaJxBo1aoRN90du2bJFtBw7BZ6WNXXqVNOXoD9fSj7LlSsnv/zyS1BWbb/6JkxJ+Omnn6RXr16ifgQjDa+++qo8+eST4nTS0alcNan66aefyqBBg+THH39MJl68eHF59913pUmTJsnSiIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAAC6U0AxWF690CU6t+9e7dcddVV8ttvv4Ut8fzzz5cRI0ZIq1atJHPmzEEyqjDs16+faTrT7tRe4cKFZfLkyaKmUVMbHn30URk+fHiyYlq2bClt27YVNWVatGjRZOmhEX///bfp83Dp0qWm6dO5c+eGijjeq5lUfaamTZuaSj09/eg2HDlyRGbOnGmaTtXPo0ePJsuqJwv1efv27RsVE6jJKiACAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCESBAIrDKED0ShF6yk0VYAcPHrRsUpkyZUwFoyoBVcmopwvV3Kf6NbQKqvh66KGHTOVi/vz5rcQiitcTgg0aNJA9e/ZY5itRooQUKFDAVLblzZvXbKMq6gL//vrrL9u2WxZuk6BmSy+77DIpX768+aenI7V+NeOq9amSdu3ateafPocdO1Xmvv3221KrVi2bGkmCAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAulPAMVh+vdBVFuwfv16adeunehnaoMqDBs1aiSvvPKKXHnllaktLll+NVWqvhm3b9+eLC1aEXny5DEVpYcOHZLVq1dHq1jHcm644Qbp2bOnNGzY0FEWAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCDgBQIoDr3QC1Fuw+nTp83TgYMHDzZPyUVafJEiReS+++4zTxmWLVs20uwRyR87dkxGjx5tmi3Vk4+pDWqSVU9dXnfddXL99ddLzZo1JUuWLGaxqqgcP368zJgxQ1asWCF2ZllT0g49xdmiRQuTXe3atVNSBHkgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAQLoRQHGYbuhjX/HJkydN/3sTJ06UjRs3mmZBDxw4kFRx7ty5pWDBguZf1apVpV69enLNNdeI+vjLlClTklxaXezatUsWLFgg6nNx27ZtpknQf/75R1S5eOLECcmRI0dSe9WEqb/t/s8KFSpItWrVRE9KOgU1d7p48WJZuHChyUaVljt37rQ1OxpaZq5cuaR69eqmGdLmzZtL/fr1k/mPDM3DPQQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhDwKgEUh17tmRi1S5WJ6qsvX758kj179hjVEp/FqnJSfRb+8ccfcvTo0SRfinqtpxOV2QUXXGD+lSpVylSwZs6cOT4fllZDAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAgRACKA5DgHALAQhAAAKpJ3Du3DnzlLOaCFY/pqp8L1OmjJQrV05KlizJ6dzUI6YECEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAJRJ4DiMOpIKRACEIBAxiOgvlXVLPInn3wiP//8s+zYsUNOnToVFkTWrFlNJeLNN98sjz/+uFSsWDGsHJEQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCCQtgRQHKYtb2qDAAQgkFAE/vzzTxk5cqQMGzbMPGEY6cOpP9UmTZrIE088ITfeeGOk2ZGHAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIACBKBJAcRhFmBQFAQhAIKMQ0BOGzzzzjKkwVP+gVkFPF5YoUUL27t0r6mPVLqjicPz48VKwYEE7MdIgAAEIQAACEMggBM6ePStq/lznEwQIQAACEIAABCDghgDzBzeUkIEABCBgTwDFoT0fUiEAAQhAIITAgQMHpGXLlrJw4cKQlP+/zZw5s3Tt2lXat28vl156qbnYpxP3rVu3yowZM+SVV16Rw4cPh81bunRpmTp1qtSoUSNsOpEQgAAEIAABCCQ2Ad2QNHToUPnoo49k8+bNotYJbrnlFrnvvvvk1ltvTeyH5+kgAIEkAkeOHJFVq1aJ32e6//PgwYNSvHhx03e6+k/Xv/r160vhwoWT8nIBAQhkPALMHzJen/PEEIBAbAmgOIwtX0qHAAQgkFAENmzYYC7abd++Pexz1axZU959913RT6uwb98+efrpp2XcuHFhRXLmzGmWcc8994RNJxICiU5g06ZNsmjRItm2bZv88ccf8vvvv5t/eq1Kd1XO6+mb888/X4oVK5b0V6lSJWnQoIGUL1/eFtHu3bvl/vvvN/2Q6nd18ODBtvIkQgACEEgrAjt37pRGjRrJli1bwlY5YcIEad26ddg0IiEAgcQgoArCd955R8aMGWO52TD0SbNnzy5333236f6gatWqocncQwACCU6A+UOCdzCPl0SAtYIkFFykAQEUh2kAmSogAAEIJAKBefPmSYsWLUR3/4YL+iP922+/lTx58oRLThb35JNPyptvvpks3h/x/vvvm6cL/Pd8QiBRCagifu7cueYpXj3Jq8r11ISLLrrIVCCqElF34JctWzapuF9//dVU/q9du9aM69ixo7kwlyTABQQgAIF0IrBnzx6pU6eO6OYGq5A7d25ZunSpoBiwIkQ8BOKXwIoVK6R///4ybdo000RxSp/khhtukCFDhkjlypVTWgT5IACBOCLA/CGOOoumRkyAtYKIkZEhigRQHEYRJkVBAAIQSFQCu3btkurVq8uhQ4fCPqKaBtIf+2pq1G1Qn0V33HGHuTgQLk+OHDlkyZIlcsUVV4RLJg4CcU3A5/PJ7NmzzR31+qn3sQolS5Y0fY3q91h/WAcGVd6raWECBCAAgfQkoHOChg0bWppBD2yb+kTWzUwECEAgcQgMGzbMnI+cOXMm2UOpuWLdvFi3bl257LLLRM0R/vDDD7JgwQKZP39+MnmNyJs3r4wdO9b8rRFWgEgIQCAhCDB/SIhu5CFCCLBWEAKE23QjgOIw3dBTMQQgAIH4IKA/4K+77jpZtmyZZYP1lNT1119vmW6V8M8//5iKQSuTZKVKlZLVq1dLoUKFrIogHgJxRUBNjX7wwQfmTnj1+5neQRfd9FQiAQIQgEB6EnjvvfekU6dOrpqg5pr3798vBQsWdCWPEAQg4F0C+jvjsccekxEjRoRtpPpLHzVqlFxzzTVh0/V0om6A2rFjR7J0VTj27NnT9K9+3nnnJUsnAgIQiH8CzB/ivw95gn8JsFbwLwuuvEEAxaE3+oFWQAACEPAsgR49eshrr71m2b5mzZrJl19+aZnulDBx4kRp06aNpZiaG1IzjrpQSIBAPBP48MMP5amnnjL9Frp9Dt1dX69ePSlTpkzSnyrUdbe9+jxU5eOcOXNk1qxZoj6BIg0HDx6UCy64INJsyEMAAhCIGoGzZ8+K+mj9+eefXZc5evRoeeCBB1zLIwgBCHiPwN9//y2333675Ulj/Q2g85ts2bLZNv7YsWOist99911YOfWbbuVbPWwGIiEAgbggwPwhLrqJRrokwFqBS1CIpSkBFIdpipvKIAABCMQXAf2x3rRpU1sziitXrpQrr7wyxQ+mZhiqVatmmhyyKgRzilZkiI8HAurA/JFHHpFFixa5aq76KGzfvr106NBBKlas6CqPfo8mT55s7qx3u/iuCsidO3e6Kh8hCEAAArEiMH78eGnbtm1Q8c2bN5fy5cub783vv/8+KE1vGjdubCoUkiUQAQEIxA0BdVnw+eefh22vfv9VEVigQIGw6aGRv//+u+kjNdzJQ5UdNGiQdO/ePTQb9zEioNZkdBFcT3yqb1oCBGJBgPlDLKh6q8yM8C5hrcBbY47WBBNAcRjMgzsIQAACEPgfAfUXoH5ENm/ebMlElYrTp0+3THebMHXqVLnzzjstxdWHop6m4oenJSISPEjg5MmT8vLLL5uLVadPn3Zsofrz7Nevn6j/rpSa1NJ6unTpYpr1cqpQF+bVxBcBAhCAQHoRCN08lC9fPtHThK1atUpqUseOHU0Tz0kRxoXOC9RcKQECEIhPAm+//balj+Xs2bPL2rVrzZPIkTzdxo0bTRcIOv8KDWq5RC2Y6MlEQuwIqO/Jvn37yqRJk0R/Sy5fvtxU6MauRkrOqASYPyR2z2eEdwlrBYk9hhPl6VAcJkpP8hwQgAAEokzgs88+k5YtW9qWqicSddd/aoNO/EuXLi2//vqrZVH6I1R3rRIgEA8EdOe77qRfunSpY3NVId67d295/PHHo2aSV8t74YUXbOvu1auX6ffHVohECEAAAjEk8M0335h+lLUK3TChps+bNGkSVKMurNSpU0fWrVuXFK9KgFOnTqV4k0VSQVxAAAJpTkD9l6spdv0Ohwv/+c9/TF/Q4dKc4nTz1NChQ8OKqc90rVstLhCiS0C59unTJ9kJUhSH0eVMaf8SYP7wL4tEusoo7xLWChJp1Cb2s6A4TOz+5ekgAAEIpJiAnn4KZx7MX6CeClAfa05+R/zyTp+PPfaY7SJB/vz5Zfv27aKfBAh4mcCGDRtET/NZmcsKbLue2h02bFhMFrHatWtn69NHTZu2aNEisDlcQwACEEhTAoF+lHXDw/PPPx+2/jfeeEO6desWlKaLLhdeeGFQHDcQgIC3Cfzzzz9StWpVS7/Metpw27ZtUqJEiRQ9yJ49e6RcuXKmL+hwBWBtIRyVlMctW7bM3Pymm0nDBRSH4agQFw0CzB+iQdE7ZWSkdwlrBd4Zd7TEmQCKQ2dGSEAAAhDIcATmzJnjeJKwTZs2on4FohXmz59vmmi0K++5554zd7PayZAGgfQkMGPGDNNX15EjR2yboadlVGHYuXNnW7nUJGobatSoYS7AhStn69atpg+xcGnEQQACEEgLApUrVzZNoutCv/qx0XdjuKBplSpVCkrShRc1qU6AAATih8DgwYNtfQ2m5rShn8ITTzwhb731lv822SfKrGRIIo5YuHCh+ZtMf7/ZBVjb0SEtNQSYP6SGnnfyZrR3CWsF3hl7tMQdARSH7jghBQEIQCBDEbj++utl8eLFts/8ySefmAoSW6EIEs+cOWOeHPjrr78sc11wwQWmT6OsWbNaypAAgfQioCdinnrqKdOni10bcuTIYSrdb7vtNjuxqKSpj5nWrVsnKytPnjxy+PBhyZQpU7I0IiAAAQikBYGff/5ZKlSoYFY1cuRIx40UZcqUkZ07dyY17euvv5YGDRok3XMBAQh4m4CaHb744otFTwVaBbV2opueUhN+/PFH200FDRs2lK+++io1VWTYvOonUk+HL1myxBUDFIeuMCEUIQHmDxEC86B4RnyXsFbgwYFIkxwJoDh0RIQABCAAgYxFYNeuXaa/Qbun1hMBBw4ckPPPP99OLOK0e+65R1QhaRei5VfRrg7SIBApgX79+omeiHUK+p2ZNm1akk8vJ/nUpp87d050R+5PP/0UVJT6Fvr222+D4riBAAQgkJYEpkyZYppLLlasmGmKXE0U2gVVEurOdH/A3LKfBJ8QiA8Co0aNkoceesiysep7MHBzgKWgi4SKFSuKWlawCmw8sCKTPF590U+fPt1UGK5cuTK5gE3MihUrpFatWjYSJEEgcgLMHyJn5oUcGfldwlqBF0YgbUgJARSHKaFGHghAAAIJTEDNJ6qZILtw6aWXysaNG+1EUpT29ttvS9euXW3zPvDAAzJ69GhbGRIhkJYEPv30U1Glt/4YsgtFixYVNQOsvn3SMowYMUIeeeSRoCr1Xr/rBAhAAALpSUBPBuXNm1dKlizp2Iw777xTpk6dmiSn17fffnvSPRcQgIB3CZw9e1YuueQSS/Pp2nL1d66/BaIRnn76aRk0aJBlUfXq1ZNvvvnGMp0EMS1oqIKmT58+sm7duoiQqPWaF198kVPhEVFDOBICzB8ioZW+srqRNSO/S1grSN/xR+2pI4DiMHX8yA0BCEAg4Qg0bdpUZs6caftcd999t3z88ce2MilJXLRokdSvX982a8GCBWXfvn2SJUsWWzkSIZAWBNRU04033ihqfssu6HjVBaqrrrrKTiwmaXv37pUSJUoEKTZVmWi36z8mDaFQCEAAAqkg0KlTJ3nvvfeSSsACQRIKLiDgeQKq6Fflv11Qf3k33HCDnYjrNLWqoMpBu/DLL79I2bJl7UQyZJoqedWPvZ6QUeVMJEF/x6nC0On3XCRlIguB1BJg/pBaginLz7tETLPOrBWkbPyQyxsEUBx6ox9oBQQgAAFPEDh27JioYu7EiRO27Rk4cKDoTt5oB/VvqH4MnYLaxL/pppucxEiHQEwJqPlPNfmpZnudwoABA6RHjx5OYjFLv/LKK2X16tVJ5eNzJgkFFxCAQJwQUB+yr7/+elJrFyxYwOJ0Eg0uIOBtAvfdd5+MHTvWspHZsmWTo0ePSrT8mOsJFzUPr2VahVj9nrGqz+vxp0+flnHjxpkKQ/UhF0lQU9KqMNSThgQIeI0A84e07RHeJf/Pm7WCtB131BYbAigOY8OVUiEAAQjEJYEvv/xSbr31Vse2x1JxV6ZMGUf/Jp07d5aRI0c6thMBCMSKwJ9//ilXX321uFlYadSokejJmEyZMsWqOY7lPv/889K3b19T7rzzzpMjR45Irly5HPMhAAEIQMArBALfY9qmZcuWpcspbq/woB0QiBcCqsRTc+1//PGHZZNr1Kgh33//vWV6ShJ0c5e+J6xC7dq15bvvvrNKzjDxajXj/fffl1dffdXxN1goFD0hqgrD6667LjSJewh4hgDzh7TpCt4l/3JmreBfFlzFNwEUh/Hdf7QeAhCAQFQJqG9DN37P9u/fL4ULF45q3f7CbrvtNpk2bZr/Nuxn5cqVIzadE7YgIiGQQgLNmjWTGTNmOOYuVqyYrF27NmbfF8cG/E9g0qRJ0rp1a/OuYsWKsmXLFrdZkYMABCDgCQJ6avu1115LasuaNWukevXqSfdcQAAC3iSgVg50s5Vd6Nixo4wZM8ZOJOK0Rx99VIYPH26bb+fOnVKqVClbmURNPH78uIwaNcp8r/72228RPWbDhg3lpZdecjQHG1GhCEMgRgSYP8QI7P+K5V2SnC9rBcmZEBOfBFAcxme/0WoIQAACMSGgvkDUJ4hdULM/alI0VuG///2vqOkgu5A5c2bT9FCOHDnsxEiDQEwIqHP3Fi1aOJatJ/vmzZsXNX89jhXaCGzcuFEuv/xyU0IViBMmTLCRJgkCEICA9wg8/vjj8s477yQ1bNOmTVKpUqWkey4gAAFvEujVq5f06dPHtnFvvfWW6Hc8mkGtkzz88MO2Rar5427dutnKJFqimm/VjaL67L///ntEj6e+ulRheM0110SUD2EIpCcB5g+xoc+7JDxX1grCcyE2PgmgOIzPfqPVEIAABGJCQP0bHjx40LZsXaTTxbpYhTfffFOefPJJx+JXrVolV1xxhaMcAhCIJgE18XnppZfK7t27HYt97rnnHBfKHAuJkoD6mlDTpGfOnDFNlvbs2TNKJVMMBCAAgbQh8NBDD5mnY/y1bd++XdS8OQECEPA2gZo1a4qeELYLCxcujLp/PDcnHW+55RaZOXOmXdMSJu3vv/82N1+88cYbjr/3Qh9afcurwlDNvxIgEG8EmD9Et8d4l1jzZK3Amg0p8UkAxWF89huthgAEIBB1ArrjtEiRIo7lNmjQQL7++mtHuZQKjB8/Xtq2beuYXc0ZqVkjAgTSkoDuStcFF6dQoEAB+fXXXz3lR1B/5KnSXxfa1dcQAQIQgEA8EWjTpo1MnDgxqcl79+7lXZZEgwsIeJOAbljSjUu6gckuxMINwuHDh0UtpdiFEiVKuNoMZleG19MOHDggujFTT2zrXDCSoH661Yehk6nZSMpEFgJpTYD5Q3SI8y5x5shagTMjJOKLAIrD+OovWgsBCEAgZgQWLVok9evXdyz/7rvvlo8//thRLqUCbtvRtWtX80dwSushHwQiJaC+Cq+88ko5e/asY9bnn39eevfu7SiHAATSi4DP5xNdqFW/RtmzZ5fixYuLKrwJEPAqAfWpFbhxSS0kXHDBBV5tLu2CAAQMAps3bxb1TW4XsmTJIqdOnZJMmTLZiaUoLU+ePPLPP//Y5tXF8ET8/6f/49Ucqfp5VJOCkYTGjRubCsOrrroqkmwZSpZ5VPx0N/OH1PUV7xJ3/FgrcMcJqfgigOIwvvqL1kIAAhCIGYERI0bII4884lh+9+7dZdCgQY5yKRXYsmWLK59FsT75mNL2ky8xCejigC6erFixwvEB1ffmjh07XJ3gdSwMAQhEicCuXbtM35bqd1PHp56IPXHiRFDpqkCsXr26tGrVStQXZsmSJYPSw92oIl2/H1ZBfdLGYjHYqj7iE5dA1apV5Ycffkh6wJMnT0q2bNmS7rmAAAS8R2Dq1Kly55132jYslqf+ypcvL9u2bbOtXzck6O+KRAm6Iei1114zTTsfP348osdS0616wrBOnToR5csIwsyj4reXmT+krO94l7jnxlqBe1ZIxhcBFIfx1V+0FgIQgEDMCDzxxBPy1ltvOZavSkNVHsYqqAmd/PnzOxavZlX37dvnKIcABKJB4KuvvhL17+ImPPjgg0F+uNzkQQYCsSDw119/yUcffSRqAnrZsmW2Cr7Q+vUEyLPPPiu9evWSrFmzhiab96o0LFeunOzcuTNsuka2a9dOPvzwQ8t0EiDghoBaI7jhhhvk3Llzpnju3LkjPkHjph5kIACB6BLo16+fqM9nu6DWHFauXGknkuK0a6+9VpYsWWKbX814qiWTeA+6KWjAgAGi7hz0BGckoUmTJqbCsHbt2pFkS3hZ5lHx38XMHyLvQ94lkTNjrSByZuSIDwIoDuOjn2glBCAAgZgTuPfee12ZINUFYF0IjmXImTNnspMwofXporaTv5TQPNxDIKUEWrZsKZ999pljdj1ZpX4EL7nkEkdZBCAQKwLqU0pPkb/00kuiJthCgyoC69WrJ9dcc42oGTc9xaW+48K9U/UE4qeffhr2JLh+J/S7YRfUtLWauCZAIKUE1CRptWrVgvyQXXTRReap2ZSWST4IQCBtCOhvhnHjxtlW1rx5c5k2bZqtTEoT9QT95MmTbbPff//98t5779nKeDlx69at0r9/f3OjkP7/jyQ0bdrUVBjWqlUrkmwJL8s8KjG6mPlDZP3IuyQyXoHSrBUE0uA6kQigOEyk3uRZIJAgBIYOHSqTJk1KkKexfww94aeLYV4It912m6sf7do3TgvFqX2eggULik70ncKxY8dElYwECMSSwJ49e6R06dLiZjHm1ltvlS+++CKWzaFsCNgSmDVrlnkqXBXY4YIqC0eOHCmXXXZZUPJPP/1kbgoJZ463TJkysmrVKtF3c2C47rrr5JtvvgmMCrquWbOmmQ9TpUFYuImQgJo5VHOHgUHNjq1bty4wimsIQMCDBNTM+3fffWfbss6dO5v/l2yFUpj42GOPyZAhQ2xz66nExYsX28p4MfHHH3+Uvn37mlYF/Kex3bazWbNmpsJQT3sSggkwjwrmEc93zB/c9R7vEnecrKRYK7AiQ3wiEEBxmAi9yDNAIMEIdOvWTd54440Ee6rwj7Nw4UK5/vrrwyemcayaAFuwYIFjrbojWHcGxzIUL15c9u7d61iFyhQtWtRRLtEEtm/fHvZkULw/Z+HChV2ZqU3r53zllVfMxRU39ep3qH79+m5EkYFAVAmoYlsXSPWkYbigp7R1s4r6srVS5OnpxLp164oqEUODmuqdPXu2nHfeeWbSmjVrRBWDdkHN9jRs2NBOhDQI2BKw8r+scyedQxEgAAFvE6hcubJs3rzZtpHPPPOMeWLOViiFiS+//LJ5+t4ue7xtRFi7dq2pMNRT/3Y+hsM9s/6GUx+GV1xxRbjkDB3HPCqxup/5g3N/8i5xZuRGgrUCN5SQiVsCxkSDAAEIQMBTBJ588kmf8VLNEH/Gopdn2Bs7Tl0xnzNnTszbbJxucdWWLVu2xLwtXqygVKlSrvjE2/eoQoUKnsNtLCL4DJN4rnjny5fPp/IECKQ1gUOHDvluvPFGy3GaLVs235QpU1w1yzhBaFnO+++/n1RGhw4dLOX03dOoUaMkWS4gkBICGzZs8BlWBcKOszvuuCMlRZIHAhBIYwIlSpQI+x0OnKMaiqyYterVV191rN+wKhGz+qNZsHFy02co/hyfJ5Ct/9qwiOFbvXp1NJuTUGUxj0qo7vQxf7DvT94l9nwiSWWtIBJayMYjAd2hRIAABCDgKQIoDtOnOwyfbK5+iBoOxmPeQLdtMUzqxbwtXqwgURWHuXPn9hzuzz//3NX3QhdmDD8xnms/DUp8Aj///LPP7p2ZI0cO38yZMyMCYaWErF27tlnO/v37fdmzZ7f8bhinEn3GLuaI6kQYAoEEjh8/7qtSpYrlGDN8kgWKcw0BCHiUgG6q8iuvrD4N/3wxa71hxcax/gsuuCBm9UejYN3Qc/PNNzs+Rzi+hisK3/fffx+NZiRsGcyjEqtrmT9Y9yfvEms2KU1hrSCl5MgXLwRQHMZLT9FOCGQgAigO06ez3ewI1h+ky5cvj3kDDZNBrn4cG2bwYt4WL1aA4jDteqVdu3auxqJ+NwYNGpR2DaMmCBgEDF+wvosvvth2jE6YMCFiVsOHD7cs0zBR6jNMv1mm63ehffv2EddJBggEEvjPf/5jO8aeeuqpQHGuIQABjxLQjSThFFqBcYMHD45Z6+3+n/nbkDlz5pjVn5qC9XeOYZbZkZ//Ofyfhjlyn57K1v/XBHsCzKPs+cRjKvOH5L3GuyQ5k2jFsFYQLZKU41UCKA692jO0CwIZmACKw/Tp/AIFCrj6YZoWp0j0VIv/x6/d5/Tp09MHVjrXiuIw7TqgbNmyrsaijtNVq1alXcOoKcMTOHv2rK9x48a241MXT1ISNm7caFmunt4wfMtaputJxJ07d6akWvJAwCTwxRdfWI4v/5ygb9++0IIABDxO4J9//nH8Lut3etiwYTF7kjFjxrhqw9GjR2PWhkgLnjFjhu/qq6921W7/O1E/VWF45513cuLfJXDmUS5BxZEY84fgzuJdEswjFnesFcSCKmV6iQCKQy/1Bm2BAARMArqLPPBHUCJfe8nHYfHixV1xX79+fcxHavny5V21Zf78+TFvixcrQHGYNr3y22+/uRqH+o7Knz+/TxcgCBBIKwLPPvus7fhUv7UnT55MUXPOnTvnK1SoUNjy7ZSG+l3gJFiKkJPpfwR2797tK1iwYNixFzgf1FNEBAhAwNsEfv/9d8fvsn6v33vvvZg9yMcff+yqDXv27IlZG9wWrCcEr7jiClftDXwfqsKwRYsWvnXr1rmtCjmDAPOoxBoGzB/+7U/eJf+yiOUVawWxpEvZXiGQSRtiTDoIEIAABDxDYPv27bJ48WLPtCeWDTFOi0iRIkViWYXrsitWrChbt251lF+5cqUYC9KOcqkRqFOnjhj+Cx2LmDVrlijDjBZKly4tu3btSrjHNnwcirHj2zPPNXHiRGnTpo2r9jRv3lymTZvmShYhCKSWwGeffSYtW7a0LCZnzpxinBoUYxespYxTgmHmTAy/HU5iQemGnyjZtm2b6CcBApESMBTWYvjXlAULFjhmNUzwSuvWrR3lEIAABNKPgGEGUoyNAI4NGDt2rBgmrh3lUiIwdOhQ6dKli21W46S87Nu3T4xNYLZysU4cMWKEPPLIIxFX061bNxk4cKAYJlcjzptRMzCPSqyeZ/4Q3J+8S4J5xOqOtYJYkaVcLxFAceil3qAtEIAABNKRQI0aNcQwQ+rYgiVLlsg111zjKJcagWrVqolxstGxCMPBt9SrV89RLtEEPvjgA9myZUuiPZZky5ZNDN9pnnmurl27yttvv+2qPYZ/HjHMLLuSRQgCqSGwf/9+qVChghw5csSymOeff1569+5tme4m4cUXX5RXXnnFjWiSzGuvvSbGicOkey4gEAmBfv36yXPPPecqy7x580wloythhCAAgXQhYJx6lxw5cjjWPXr0aHnggQcc5VIiMH78eGnbtq1jVv3fWrhwYUe5WAoYp1fM/7s6zz916lREVZUrV070f/+9994rWbJkiShvRhNmHpV4Pc78IbhPeZcE84jVHWsFsSJLuV4igOLQS71BWyAAAQikIwFVwH377beOLTDMg8oNN9zgKJcagUqVKrlSjBlmOKR69eqpqYq8ELAkYPiXkeXLl1umBybMnTtXbrrppsAoriEQEwKPP/64vPPOO5ZlFytWTH766SfJkyePpYybBFWGd+/e3Y2oKWOYUDbf224WiV0XimCGIaDv2muvvVbOnDnj6plXr14tNWvWdCWLEAQgkH4EsmbN6vi9HjJkiBg+eWPSyA8//FA6dOjgWLbhj1Fy5crlKJcWArrorxtxRo0aJcePH4+oSlUg6gaMdu3aoUC0IMc8ygJMnEYzf7DuON4l1myikcJaQTQoUobXCaA49EgPqXkzw5G1R1pDMzIagT59+sgzzzyT0R6b5w0h0KhRI1Hlh1MwnGxLkyZNnMRSlV6mTBnZuXOnYxlqWtXwh+gohwAEUkLg4osvFjWd7CagxHZDCZnUElATxWpWWk9xWAXDV5Tcf//9Vsmu47WcTp06uZaPpak5141AMC4JHD582NwEZPe+VaWiWhnwh19++SVVpnj95fAJAQjEloCa//z7779tK3n99ddFzW3GIqjy7aGHHrIt+rzzzhPDT7WtTHokGj4iRTfxDBs2zNbKQLi26RxWFYhqApYTiP8SYh71L4tEuGL+4K4XeZe44xSpFGsFkRJDPh4JoDj0SK998cUXcvvtt3ukNTQjoxHo27ev9OzZM6M9Ns8bQkA3L0ydOjUkNvntlClTRH1fxTLoiRn1NeIU9u7dK0WLFnUSIx0CKSKQL18+1ws1u3fvlhIlSqSonkTONGbMmJgtBqYHt169ekV0Ci/abVRFnir0rELlypVlw4YNoougqQ2TJ0+WVq1auSpGzUt///33UanXVYVRFmKcRhlohMXdfffd8umnn1rmUkX4+eefL2+88UaSzF9//WXGJUVwAQEIeJKAzo327Nlj2zY1M/jss8/ayqQ0UU3Oqzk5u5A3b15RBYRXw6FDh0zT+W+99ZbodSRBfR37FYh6+jOjB+ZRiTUCmD9E1p+8SyLj5STNWoETIdITgoCP4AkCn3/+uc8YUPzBIF3GgKE49MT3gEakL4FHH33U1fgzFvdi3lBjd7Krthw9ejTmbaGCjEnAONHlagz6/3efOHEiY4JyeOrhw4dHxNHP06ufxgl9hyeOXbLh19RnnBqw5WksKkatAe+//75tXYF9NHv27KjVmx4FMU7Tg/r/12n48rIdZxdddJHPUBL6DLN7SXKZM2f2nTt3Lv0aTc0QgIBrAoZP3qTvbuD/jcDrF154wXV5kQoOHDjQsX5jw2KkxaaLvKHc9L366qs+wxej4zMF8tVrw5qLzzh96TN8J6ZL271QKfMoL/RC9NrA/CHlLHmXpJydPydrBX4SfCY6AUn0B4yX50NxiNI0dHKflvcoDuPlTRHbdhqmcFz9CDXM5cS0IboY6LQ4rt+PQoUKxbQdFJ6xCRg+IVx9H3QsGjvVMzYsm6dHIWMDJ8KkBx980HZMGr4FfQcPHoywVGvxcePG2dbnn6c0bNjQupA4SWGcpk9HGb44fYYvTttxNnPmTLNxhon0JDn+/6dPf1ErBFJCwPCLnvTd9f/fCP3s0aNHSop2leeVV15xrN/wre6qLK8IHTt2zKcbhXRjRShLp/vSpUv7Ro4cmSEViMyjvDKCU98O5g+pZ6gl8C5JOUfWClLOjpzxRQDFoUf6C8UhikOnSX4s01EceuRFkM7NMEwmu/rxaZjqi2lLDRv8rtpRt27dmLaDwjM2gXXr1rkah/puNvwbZGxYNk+PQsYGTgRJhu8lxxMGeiIrmkFPgDjNPTJlyuRbvXp1NKtNl7IYp2mPXXdqX3HFFbZj7L777ktqWO3atZNkDT+fSfFcQAAC3ibgpKzR/zOGOeKYPcQTTzyR9O6w+p/WrFmzmNUfy4L1PapKQJ2HWj2bVbwqEEeMGOHTMjJCYB6VOL3M/CH6fcm7JHKmrBVEzowc8UkAxaFH+g3FIYpDq0l9WsSjOPTIiyCdm7Fx40ZXPzoN3xAxbenatWtdtaNjx44xbQeFZ2wCy5cvdzUO9R1dp06djA3L5ulRyNjAiSBp6dKljuPxm2++iaBEZ9H69es71tm2bVvnguJAqrQ8vAAAQABJREFUgnGa9p301FNP2Y6v4sWL+wxfPEkNC1wY552bhIULCHiewIABA2y/6zqPuuWWW2L2HK1bt3asv1u3bjGrPy0KPn36tO/DDz/06cnJSNcOSpUq5dP/gYmuQGQelRYjMW3qYP4QO868S9yzZa3APSsk45tAJm2+MbkgpDOBH3/8UcaOHZvOraD6jEqgcePG0qBBg4z6+Dz3/wgYPtokV65cuqHElknTpk1l+vTptjKpSZw1a5YYJskci+jfv78888wzjnIIQCAlBPT/8mWXXeYqq2GqUb766itXshlNyNjNLo888kjCPLbh41Cee+65NH+eZ599Vgy/Rpb1Fi1aVPbu3WuZHmnCP//8IwULFhRjIdEya7Zs2WTz5s1StmxZS5l4SWCcpm1PzZ07V3TuaTff+PLLL8U4BZTUsHz58smRI0fMe0OpLQsWLEhK4wICEPAugc8++0xatmxp28Dq1avLmjVrbGVSmnjdddeJsbHGNrtxak86d+5sKxMPiYa7B5kyZYoYm4LF2IgZUZNLliwpOtd44IEHRP+/J1pgHpUYPcr8IW36kXeJM2fWCpwZIZEYBFAcJkY/8hQQgAAEokJAfzTu3r3btizDtJisWrXKViY1ie+9954Ypxodi9AfxnfccYejHAIQSAmBPXv2SIkSJVxlveqqq2TZsmWuZDOa0MqVKxNKwW+YU5N77rknzbtRldj6A9UqGCcqZMKECVbJEccbpqvl9ttvt81nmH+TN954w1bGbeK+ffvE2LkrOXPmFMMflmTNmtVt1qjIMU6jgtFVIYY5cqlatars37/fUt4wuyvG6ZmkdN3YpGPDH4zTSWL4PvTfRuUzvcdgVB6CQiDgQQKGOTdRxaBdKFKkiOh3MBahfPnysm3bNtuidSOCbkhIpKCbPFWBqP9bIwmG38QkBWL27NkjyeppWeZRnu4eV43z6vxBG5/IcwjeJeGHJ2sF4bkQm4AE9MQhAQIQgAAEIKAEmjdv7mjiRs2HxTL07t3bsQ3Gv2OfmlYlQCBWBIwTV67GoY7FypUrx6oZlAsBn7Hg6TgWhwwZElVSTj6pzj//fN+ff/4ZlToNhafPUAolPaNx0tE3Y8aMqJRNId4iYOxgN00S6nvT6q9YsWK+gwcPBjV8165dQfLGpqGg9NTeMAZTS5D8ELAmcPToUV/mzJmDvsOh3//zzjvPd+bMGetCUpES+P8ltF7/vbEAnIoavJ3VsIjhc2N63M/C/2lsnvPp3MLYuOHtB3TROuZRLiB5XMSr8wfFllHmELxLgr8krBUE8+AucQng4zBx+5YngwAEIBAxAeP0iO0Pe/0xqT/+jx8/HnHZbjOoD0X/j1arzwIFCvjUyT0BArEkYOy0dhyLOkZ1oZsAgVgRmDZtmuM4XL9+fdSqP3DggC9v3ry2dfbr1y8q9WldqoQMfdcbZil9xun3qNRBId4hMHjw4GR9Hdr3xmnXZA1evXp1UL5o+tZkDCbDTQQEok6gdu3aQd/h0O+93v/6669Rr1c3IYSrKzCucOHCUa/XiwUuWbLEceNGIBf/tSoQ33nnnZj+9os1L+ZRsSYc+/K9OH/Qp86Ic4iM/C4JHemsFYQS4T4RCWCq1JgRESAAAW8RMBxey1tvveWtRsWgNfnz5xc1j1amTJkYlJ6yIo3FZ6lWrZpj5hUrVkitWrUc5VIioOU6mUJt06aNjB8/PiXFJ0See++9V9RcS6IFY2FJ1IecV0KNGjVc+YjJkSOHqE84Y8e8V5pOOxKIgJP/PWMjhRin/yRTpkxReeoXXnhBjJPflmWpCd+tW7cGmY60FHZImD17tqjZyXBhzJgx0rFjx3BJxMUhAfVfpmadT506Zdl6NQM8bty4ZOlz5swxfSL6E3Rc6PiIRmAMRoMiZUDAnoCTfznNreaHrf4f2Jdunaq+DdXHoV3QOfVHH31kJ5JQacZGDNOE6eeff27rZzb0oQ2LM/Lf//7X9AWp8954Csyj4qm3krfVq/MHbWlGnkNkxHdJ6OhkrSCUCPcJSSARtaE8EwQgEN8EnnzyScfdocYLOSFkFi5c6KnOUjMghQoVcmQ7atSomLT79OnTPjc7t4wFw5jUHy+FlipVyrGP4vE7kjt3bk91gZvTr37Ohv85T7WdxiQOgV69etl+36+//vqoPayaH9XTfv5xHe7T8EMbtfrGjh1rWdfAgQOjVg8FpS8BNVV4ySWXWPa1jjPDx5m5cz9cSz/++OOgvI8++mg4sRTFMQZThI1MEIiIwNy5c4O+w+H+t0TrJHtgw958803Heg2lYWCWDHO9YcMG39133+1oRja0r9TKhnKNpfWZaHcC86hoE0278rw8f1AKzCF8voz0Lgkd+awVhBLhPhEJYKo0EXuVZ4JAnBNAcZi+HdiqVSvHH9nRXLQLfNp169Y51q0/YDO6CTsUh4GjJnbXxg5lV+NRx6T+cCRAIBYE7r//fttx2LJly6hV+/TTT9vWVbZs2aj6odq0aZNlfWoajZAYBJzGsL5Dp0yZYvmwOhYCF6+7detmKRtpAmMwUmLIQyByAuoLKlu2bEHf48DvtF63bt068oIdcnTo0MG2TuOkvm///v0OpSR2smFBwKfv6KxZs9qyCu0vVSCqi4tjx455HpDT/yDmUd7tQqe+03GZXvMHpcYc4t+xkxHeJf8+7f9fsVYQSoT7RCSA4jARe5VngkCcE0BxmL4dOHz4cMcfjnXr1o1JIz/44APHui+//PKY1B1PhaI4TJveWrt2reN49C+k/Oc//0mbRrms5cSJEy4lEfM6gUaNGtmOw2ht5NANGTlz5rStyzA1GXVcpUuXTlan+j3M6BtEog46nQo0zIon61//e9P/edddd9m27uWXXw4qo2fPnrbykSYyBiMlhjwEIidw7bXXBn2P/d9//2fFihUjL9QhR5UqVWzrNMzMOZSQcZJ37tzp07msYYbUlpm/v/yfRYsW9an/OS8rEJlHxec4jof5g5JlDhE8vhL5XRL8pD4fawWhRLhPRAIoDhOxV3kmCMQ5ARSH6duBf/zxh6O50Dx58vjUrGi0Q5cuXRx/rPbo0SPa1cZdeSgO067LdCHLvzhi91m1atW0a5RDTdOnTze/w/pdOXv2rIM0yV4noAubdmPvxRdfjMojGL5jbevRNsRi44buUNbNKP5nNPz++rxmxjsqgDNgIdu3b/epEtjft+E+Cxcu7FMTuXaha9euQWUY/tLsxCNOYwxGjIwMEIiYgNPJDMNPtO+vv/6KuFyrDHrKMUuWLEHvjtB30PPPP2+VPcPG792719e9e3efug8I5WV3r+amX3/9dZ9y91pgHuW1HnFuT7zMH/RJmEOE789EfJeEe1LWCsJRIS6RCKA4TKTe5FkgkCAEUBymf0e2b9/e8cfiV199FfWGXnzxxbb1Zs6c2ffLL79Evd54KxDFYdr1WJ8+fWzHZOAiyooVK9KuYRY1ffHFF0HmwPr27WshSXS8EFAfhoHjLPR6yJAhqX6U2bNn29bhr/Oiiy6yrevMmTO26VaJquDetm2bb8eOHVYixMcZAd1cFKgQ9o+h0M/Jkyc7Plm7du2Cxufjjz/umCdSAcZgpMSQh0BkBNRXmdNGgk8++SSyQm2kP/vss6D3Rui7R5WKu3btsikhYyfphg5VrDr1WShXVSAOGjTIUwpE5lHxNZbjbf6gdJlDWI+xRHqXhHtK1grCUSEukQigOEyk3uRZIJAgBF544QXbH3qhP1Di+d6rpyq+++47xz6ItmnGNWvWONYZTR8U8fx1adCggS9v3rwJ96fmjrwWVJGhPnDcvGfUD0d6Bl0kC/RRozxRtKdnj0SnbqeNHCNHjkxVRcePH/eVK1fO1RjX0+ZWYdmyZabSWn1KYSrXilLGie/Vq5fjmHLr0+zOO+8MKsvpXTtv3jxfgQIFfNWrV884wHlSCMQBAVX6282n1M96tMLdd99tW5emE5wJ6ClQXRgvVKiQLc/QftXT5K+99ppP5xjpHZhHpXcPRFY/84fIeMWLdCK8S8KxZq0gHBXiEolAJn0Y4588AQIQgIBnCBg+EsQwbeCZ9sSyISVKlBDDl0Qsq0hx2bVq1ZJVq1ZZ5te2//rrr2IoVSxlIkkwfiSI8cPUNsvSpUvl6quvtpUhEQLRJmCYcJSJEyc6FpsrVy4x/DqIsbjiKBttgaFDh4phzk+MHa9m0fny5ZNFixaJsXAe7aooL40JGJtppHfv3pa19uvXTwzTjZbpTgnGiQIxTqY6iSWl79u3T4wTBUn3/ot77rlHjNMiomPPMHkt2bJl8yfxmcEI6LvnhhtukHPnzlk++YUXXigbN24U/XQKTZs2lZkzZyaJGcoF23fyrbfeKl9++aXUr19fFixYkJSPCwhAIH0JbNmyRSpXrqyb18M2xNicIsbpFMmePXvYdLeRp06dMt8thw8ftsyiv3GuuOIKy3QSggkYJkjF2KgkxmnCiH6nL1++XOrUqRNcWBrfMY9KY+CpqI75QyrgxUnWeH6XWCFmrcCKDPEJQSCRtKA8CwQgAAEIRI/A+++/77izVE8mRitceumltvUZCsNoVUU5EIiIgJ7aMxaxbMenMSk006O5W95NI9U0Trdu3YLapm39+uuv3WRHJg4IvPfee0H96x9r/s8nnngixU/x448/Bpm29Zdp96k+NEOD+jHxn3bt2LFjaDL3GYjAgQMHfGrS1m4MadqECRNcUzGUkEHlGYv9lnnV5K36StM6BgwYYClHAgQgkD4EbrrppqDvc+i7Qk2upzYYGwds61DTlYSUEVCLAsZmNV/p0qVtGfv71VAcpqyiKOZiHhUe5owZM3zGRhvT6oS6AylbtqxPLQHoSdGDBw+GzxTDWOYPMYTrwaLj8V1ihZG1AisyxCcCAUyVJkIv8gwQgAAEYkBAJ3OXXHKJ7Y9CJ3Nhbpu1ePFi23r0x+eUKVPcFoccBKJOoEePHo5j1L9IMm7cuKjXH65A41SXzziJE9Qu45SXb+rUqeHEiYtTAupP1j+2wn3eddddKXoyVTpfd911tmWHq+/FF19MVl+g8nr+/PnJ0onIOATuuOMOxzHVokWLiICE+kpU32TqLy1c6Ny5c1L969evDydCHAQgkI4EfvjhB9sNK/p9T22oV69e0nsg9P+Ymp/n/1RqCft8xqlO35gxY3wVKlSwZK3svaA4ZB4V3N+GNQCfYSXCtt/UV2Va//Zm/hDcTxnlLp7eJXZ9wlqBHR3S4pkAisN47j3aDgEIQCDGBAzToEk790N/eOu9Lt799NNPqW6F0+L1bbfdluo6KAACqSFw5MgR32WXXWb7I9v/HTn//PNjvlCi/lENc8FB7cmZM6dv1qxZqXlM8nqQwO7du239bBYrVsyni0CRBsO8adD48Y9f/dTFG8OEadh0XSRUpaM/bN68Oem0oZ40C0zzy/CZMQgMHz487JgJHFsFCxb07d+/PyIghun0ZOWGO1VtmDhL+q7o+5EAAQh4k4BhfjvZdzrwPWGYJk5xw3UeFFhW6PVjjz2W4rLJmJzAmTNnfJ9++qnv8ssvD8vdC4pD5lHB/fbOO++E7avQ74qeQkzNdzG4Vvs75g/2fDJCajy8S+z6gbUCOzqkxTMBFIfx3Hu0HQIQgEAaEAg8SRL6g0LvdcdiasKcOXNsf7wULVrUpyerCBBIbwJbt2715c+f33a8+r8jhr9D37Rp06LeZMP3j+/hhx9OptDPmzevTxfNCYlJ4Nprr7Udd7rJI5Kgu8j11IV/vAZ+NmnSxHfy5EnfsGHDwqarrOHz06zO8Ensu+aaa5LkdLdtSoLhN9E3e/Zsny5mHTp0KCVFkCedCWzYsMGnmxcCx1K4a11gjjTcfPPNycrVE0WBSurff//dV758+SS5Tp06RVQNYzAiXAhDIFUETp8+7atRo0bS9zX0XWFnjtiuYt1Eo3lDy/Pfq1uE48eP2xVBWgoJKHu1eHHllVcG8feC4lAfiXnUvx2rpwn93wmnT8NvtU/N0ccyxPv8Qdkwh4jeCPH6u8TuSVkrsKNDWrwSQHEYrz1HuyEAAQikEQFdGLYzQ6O+hFavXp2i1qhpipo1a9r+eOEEVYrQkilGBHQ86klbpx/amq47dXv27On766+/Ut0aXRQfNGiQr0CBAsnqVj8z33//farroADvEhg9enSyfg8cg0899ZTrxi9btsyniubA/P5r9SXnX1SdPHlyWBmVLVy4sKnkUz9R/ry5c+f2/fbbb7bt0E0guoio5s10U4oqhEIXsLZs2WJbBoneI6BjpkqVKkljwT8mQj/1JGtKwn333Re27IceesinfjrV33LoPMXqncgYTEkPkAcC0Sewdu3apNPqoe8KvX/ppZcirlRNaYcrS+PUlPuaNWsiLpMMkRPQjUB+c7FeURwyj/r/flQloNV3xCo+nIn6yEdF+BzxNH/QJ2AOEb4fYxXrxXeJ07OyVuBEiPR4I4DiMN56jPZCAAIQSAcC33zzja0/EjVP57RgHK7Z7du3t/3x0qVLl3DZiINAuhLQHzF58uSxHbuBP74vuOACX//+/SM2z6c/psePH2/6MbRSVt50000+PYVISGwCegKwcuXKlmOuUKFCvp07dzpC0He5ldJQlTC6UcQf1ARp4Dh2urZa5NVFKj0J5uY7o/9LCPFH4D//+Y/jWNFND7ojPyVBN2A4jb/A9ObNmwdVwxgMwsENBDxDQOc4qtAL/P4GXn/44Yeu2zp27FjLcnST46hRo1yXhWB0COimjoMHD0ansFSWwjzq/wF+++23lt+TwO9e4HUsTX97ff6g1JhDpPLLF4XsXnqXuHkc1grcUEImXgigOIyXnqKdEIAABNKZgJoU1RMlgT8kAq+rV6/uU9vuboMuMgfmD71u1aqV78SJE26LQw4CaUpAT9mqGd3QcWt3r6Yhq1at6uvevbvpD2bevHnm7nf1E6qnwD777DPzFJf6nrvrrrt8ah7IqjxVJKoPukBTfWkKgMrSnMCCBQsszYvqONF38D///GPZrgkTJoR9h6tiW8deuKCKPKsxGBivi0pWde/Zs8dXtmxZ85SinsINzBd63bFjx3DNIM7DBL744gvbPvX38bhx41L8FEOHDnVVh7+ulStXBtXFGAzCwQ0EPEVg7ty5lhtLVKmovs/s5jqapqa1s2bNGvY9oSaU1Tw3AQLMo3w+/c3h/18ZyWc0rKeEjsB4mD9om5lDhPYc924IsFbghhIy8UAAxWE89BJthAAEIOARArrbq2DBgpY/ONRfiZNJmgMHDvj0ZIvdj5Wnn37ap/btCRDwMgE9PaMKPruxHIu0q666yrdu3Tovo6FtMSIwZMgQ2/F26623JjvZumPHDl+zZs3C5lOfP7t27bJsrZWJyMBxrQpxv89Dy4L+l6CnaFWBFJg/8Dol/u+c6iQ9dgR2795tOyfw962Oy9QEHaN6Yshfnt2n+ui0C4xBOzqkQSB9COjvCz05b/XdVr+F8+fPDzoVr9/lr7/+2tan4YUXXuj4uyR9npha04tARp9HqZsQNxYgQr+L0TbzG4/zBx2zzCHS65sbn/WyVhCf/UargwmgOAzmwR0EIAABCDgQ2LRpk69kyZKWP+51Efn+++/3LV261Hf48GGztDNnzvg0n/5Ys1sY0NMourOYAIF4IqC+DMqVK2f5nQj98Z3S+zJlypimtux23scTN9qaMgJ6siJ79uyW4y1Xrlw+NdXYtm1bX6VKlcKeUtTTie+//75P3812QXfL2pmR03f2Bx98YFdEsjQ1hxruO6D/O9R3DCE+COh7qEGDBmH7MrB/9USr7tZPbWjatKljXaoksFOE+9vAGPST4BMC3iGg/m2tNrn43ym6gUBNX6tPU6cT7OqDd9u2bd55QFriGQIZfR6lFkv83ym3nwsXLoxa/8Xz/EEhMIeI2lDIMAWxVpBhujohHxTFYUJ2Kw8FAQhAILYE1J9h586dbReU9YeILgQXKVLElyNHDscfKFWqVPGpOVQCBOKRgCpgpk6d6rvhhhscx7rbH+l+OVXyfPzxx77Tp0/HIxraHAMCW7du9enJKv8YcfOpC6633367T011RRIGDhwYth41Czdp0qRIijJldVNJuPbqiRJC/BDQkz7h+jE0LhIfZXZPv3jxYts5h/pQVN9NbgJj0A0lZCCQPgTUokKbNm1cnzIOfOfo/7mWLVv69AQjAQJ2BDLyPEp/s3Tt2tVR+R743frhhx/scEaUFs/zB31Q5hARdTfC/yPAWgFDIV4JZNKGG/8QCBCAAAQgAIGICRgKRBk0aJCMGjVKjN13EefXDMaJBenRo4c0btw4RfnJBAGvEdi8ebMYPntk0aJFYix2y59//hlREw3/hWIoUcRQ8sgdd9whl1xySUT5Ec44BAwzpGL4iBFj04X8+uuvYpjEEcMctBinDsU4kSEVK1ZM+qtXr54YvgYjhqM/FXQ8T548WVasWCHGZhBzfD788MNSunTpiMvr37+/9OzZM1k+jevbt2+yeCIg4Ccwc+ZMufPOO+XkyZP+KPPzpptuEsNagRgnv4PirW4Yg1ZkiIeAdwgYvthk5MiRsmTJElm7dq0YJhaTNc7YwCKGNQbzu3/55ZeL/l9y+x5IVhgRGZJARp5H6ZxR/68aZkPlyJEjYvhuN79PhmJMBg8eHDQeDIsQYlgNCoqLp5tozR/0mZlDxFPPe7OtrBV4s19oVXgCKA7DcyEWAhCAAAQiIKCKkaFDh8pXX30lhmk7Mez/W+bWHyX6o/7SSy8Vw9ehuQBtKUwCBOKcgCpdfvzxRzFM9ZoKRFXq+P+MnYdi+BmRfPnymX8XX3yxGCdvxTAvKYZ5yDh/cpqfXgR0zBmnvdOresd6GzZsKMZu82RyhhksMUzLJYsnAgKBBA4dOiQ6VlSpcNFFF0nNmjWlcuXKgSKO14xBR0QIQMBTBHSzgG5WPHjwoOg7QDdY6UYYw3WCGCZLPdVWGhP/BDL6PEoVisWKFUvqSP19Ypj9TbqP14tozB/02ZlDxOsI8Ga7WSvwZr/Qqn8JoDj8lwVXEIAABCAQBQKqDNFdVKpM1B/4hp9DyZ8/v6ks1B8euXPnjkItFAEBCEAAAvFGQE+mGyYlk50YUwW6/r/Q0yMECMSSAGMwlnQpGwIQSA0B/e2k1gMSJejGOE6ARrc30+J/mJ7OM/wKJzVcN/qOGDEi6T4jX6QF/2jw5V0SDYqUAQEIKAEUh4wDCEAAAhCAAAQgAAEIQCDmBGbPni233HJLsnqaNWsmX375ZbJ4IiAQbQKMwWgTpTwIQCBaBFQ588gjj0SruHQvR0+GbtiwAZP7UeyJtPgfdu+994rhW91steE3VNasWSNVq1aN4lPEb1FpwT8adHiXRIMiZUAAAkoAxSHjAAIQgAAEIAABCEAAAhCIOYHu3bsn85ujlb799tvy2GOPxbx+KoAAY5AxAAEIeJVAoi32K+fly5dLnTp1vIo87toV6/9h3377rahPbH9o3769jB071n+b4T9jzT9agHmXRIsk5UAAAigOGQMQgAAEIAABCEAAAhCAQMwJqA9PPX0QGtS89SWXXBIazT0Eok6AMRh1pBQIAQhEiQCL/VECmcDFxPJ/2PHjx+Xqq6+WdevWmQSzZ89u+hMuVapUAhON7NFiyT+ylthL8y6x50MqBCDgngCKQ/eskIQABCAAAQhAAAIQgAAEUkBg7969Urx48WQ5S5cuLTt27EgWTwQEok2AMRhtopQHAQhEkwCL/dGkmXhlxfJ/2KlTp+S2224TNcXpD3q6btCgQf7bDP8ZS/7Rhsu7JNpEKQ8CGZcAisOM2/c8OQQgAAEIQAACEIAABNKEwEcffSRq8io0dOrUSd59993QaO4hEHUCjMGoI6VACEAgigRY7I8izAQsKlb/w86ePSutW7eWKVOmJFHTk4dz586VPHnyJMVl9ItY8Y8FV94lsaBKmRDImARQHGbMfo/JU//555/mjvE9e/aI/umOnH379pl1FS1aVPx/JUuWlBo1akjmzJlj0g4KhQAEIAABCEAAAhDwFoF27drJuHHjkjVq0qRJ0rJly2TxREAg2gQYg9EmSnkQgEA0CYwcOVIefvjhaBaZ7mX9X3t3AmRVdSYA+GdREAF1AHFDQJQQFbLgxiCVMDqi0UwEMQajYoZFjFtMTDQaTGAUjQojuKEwcUnioBL3oI5LVBSNCypokIgGGRaJoIEBBUGYnJd0p+EtTTfd/V7b362i+t7/rPe7r3gUf59zveOw5h5BbXyHLV++PE466aRNVhp++ctfjieeeCJ22GGHmpv8Z6Cn2vCvLRZ/l9SWrH4JNDwBicOG98xr9I4XLVqU+S3x3/72t/Hyyy/Hxo0bt6j/du3aRf/+/TP/UdS3b99o2rTpFrVTiQABAgQIECBAoH4JpH8fpm1Ky36hrGz2jRs3jvSLZzvttFNZyE8CtSLgM1grrDolQKAGBRYuXBi33HJLDfZY/K6+853vxO677178idTzGdTGd9gLL7wQxx9/fCxYsKBcZ7/99ounnnoq2rRpUx5zEpn/56xP/471d4lPLQECNSUgcVhTkg2sn/QPl/TbcOkftmk/9K05OnXqFGkpfb9+/bamG20JECBAgAABAgRKUGD27NnRo0ePrJkdfPDBkVYjOAjUtoDPYG0L658AAQIEakugpr/D7rzzzkgr6Cr+X97hhx8eaTvOtFOYY1OBmvbftHdXBAgQKF0BicPSfTYlPbOUONxrr70yW5PW1ETTFglXX321326qKVD9ECBAgAABAgRKQGDs2LFx3nnnZc1k5MiRMXr06Ky4AIGaFvAZrGlR/REgQIBAXQnU9HfYtddeG2eddVZm+m3bto1x48ZlEol1dT/1bZya9q9v92++BAg0XAGJw4b77Lf6zidPnhzDhg2LFi1aRJ8+feKwww6Lnj17xq677hrt27fPbDv1/vvvx7vvvht/+tOfIr3D5t57743169fnHTu9//DZZ5+N9NNBgAABAgQIECBQ/wWOOuqoTd6fU3ZH06dPj0MPPbTs0k8CtSbgM1hrtDomQIAAgVoWqOnvsLVr10a3bt0y/4+XkoYpeejIL1DT/vlHUkKAAIHSEpA4LK3nUa9ms27dupg1a1Z07949tt122y2a+5IlS2LChAlxxRVXxIYNG3K2Sf+AeeaZZ6w8zKkjSIAAAQIECBCoPwLp34vpHYarV6/eZNKtW7eO5cuXe8/1JiouakPAZ7A2VPVJgAABAnUh4DusLpTzj8E/v40SAgQ++wISh5/9Z1ySd/jII4/EoEGD4sMPP8w5v4MOOiieeOKJ2H777XOWCxIgQIAAAQIECJS+wIwZM6J3795ZE/3GN76R2YmiYsHHH38c2223XcWQcwJbLeAzuNWEOiBAgACBIgn4DisS/N+H5V9cf6MTIFBcAYnD4vo36NHfeuutOPjgg/MmD9O7cK688soGbeTmCRAgQIAAAQL1WSDtMnH++edn3cJ1110X3/3ud8vjTz31VBxxxBExfvz4GDFiRHncCYGtFfAZ3FpB7QkQIECgWAK+w4ol/7dx+RfX3+gECBRXQOKwuP4NfvT7778/0m+c5zqaNWsWb775ZnTq1ClXsRgBAgQIECBAgECJCwwYMCDuueeerFnOmzcvunTpkokvXLgw857sP//5zzFmzJj48Y9/nFVfgEB1BXwGqyunHQECBAgUW8B3WHGfAP/i+hudAIHiCkgcFtff6H8VOPPMMyP91nmu44QTTogpU6bkKhIjQIAAAQIECBAocYGUHHznnXc2mWXXrl1j7ty5mdjKlSujb9++MXPmzOjVq1dMnz49mjRpskl9FwS2RsBncGv0tCVAgACBYgr4DiumfmR+yc2/Y4v7DIxOgEDxBCQOi2dv5L8LvPfee5lVhWvXrs1p8vLLL8eXv/zlnGWCBAgQIECAAAECpSmwbt26SDtIbNy4cZMJnn766XH99dfHRx99FEceeWQmWdiyZct49dVXy1chbtLABYFqCvgMVhNOMwIECBAouoDvsOI+Av7F9Tc6AQLFF5A4LP4zMIO/CgwfPjwmTZqU0+Lcc8+NcePG5SwTJECAAAECBAgQKE2BtPVo+/btsyZ38sknxxlnnBHDhg2L2bNnZ8pvueWWGDx4cFZdAQJbI+AzuDV62hIgQIBAMQV8hxVTP4J/cf2NToBA8QUkDov/DMzgrwKzZs2KL3zhCzkt9txzz3j33XdzlgkSIECAAAECBAiUpsCqVauiVatWlU7u4osvjlGjRlVaTwUCVRXwGayqmPoECBAgUCoCvsOK+yT4F9ff6AQIFF9A4rD4z8AM/i6wxx57xKJFi3J6vPDCC3HggQfmLBMkQIAAAQIECBAoTYFddtklli5dmndy6V3X11xzTd5yBQS2VsBncGsFtSdAgACBYgn4DiuW/N/G5V9cf6MTIFBcAYnD4vobvYLAv//7v8fNN99cIfKP0x/96Efx85///B8BZwQIECBAgAABAiUvcMUVV8T555+fNc9/+qd/issvvzyGDh0ajRo1yioXIFBTAj6DNSWpHwIECBCoawHfYXUtvul4/Df1cEWAQMMSkDhsWM+7pO82vdvmO9/5Ts45HnLIIfHcc8/lLBMkQIAAAQIECBAoXYE77rgjHn744cy7Yjp16hTdu3ePgQMHRtu2bUt30mb2mRLwGfxMPU43Q4AAgQYl4DusuI+bf3H9jU6AQPEEJA6LZ2/kzQQeffTROOKIIzaL/u2ydevWsWLFipxlggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAlsvIHG49YZ6qCGB2bNnR48ePfL2tmDBgujQoUPecgUECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLVF5A4rL6dljUs8P7778fOO++ct9e0xVW/fv3ylisgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCovoDEYfXttKxhgQ0bNkSzZs1i/fr1OXseO3ZsfP/7389ZJkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQILB1AhKHW+endQ0L7LbbbrFkyZKcvZ511lkxYcKEnGWCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECWycgcbh1flrXsEB6x2F612Gu49RTT42bb745V5EYAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAVgpIHG4loOY1K9CtW7eYO3duzk4HDhwYd911V86ymg5+/PHH8e6778bGjRujXbt20aZNm2jUqFHeYZYtWxaLFi2K7bbbLrp27Zq3ngICBAgQIECAAAECBAgQIECAAAECBAgQIECAQKkKSByW6pOpx/NavXp1LFiwIJN4S8m39GfFihWx6667RqdOnTJ/vvCFL0SrVq2y7rLQVqVHHnlkPPTQQ1lttjbw3nvvxe233x6vv/56vP3225k/ixcvziQNy/pu0qRJdO7cOfr27Rv/+q//GmkuZfNPycVevXrF73//+zjkkEPiueeeK2vmJwECBAgQIECAAAECBAgQIECAAAECBAgQIECg3ghIHNabR1XaE124cGH86le/ittuuy3mzJlT6WRbt24dQ4YMibPPPjuTSCxrsP3228dHH31UdrnJz969e8czzzyzSWxrLp544omYOHFi3HvvvbFu3boqddWsWbNMsnCPPfaI559/PubNm5dpP2jQoEwSskqdqUyAAAECBAgQIECAAAECBAgQIECAAAECBAgQKAEBicMSeAj1dQqffPJJZuvQW2+9NR5//PHYsGFDlW8lreQ76aST4oYbboi0UjFtC5rvSKsUX3311XzFWxy/5ZZb4vLLL8+7JWrabnS//faLjh07xocffphZgZhWTW7JMXLkyBg9evSWVFWHAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBSAhKHJfU46s9k0racQ4cOzWzvWROzPuCAA+KSSy7JbAGar7/0/sMtWc2Yr33aknTYsGHx4IMP5qzyuc99Li6++OI44YQTIiU0Kx4vvfRS3HTTTTF58uRNtjCtWCedp6Tk4MGDNw+7JkCAAAECBAgQIECAAAECBAgQIECAAAECBAiUvIDEYck/otKaYFoVeNFFF8U111xT6QrDffbZJ4477rhIKwXTnx133DFeeeWVuOqqq+J3v/tdlW+sZ8+ekRJ41Tl+85vfxIgRI2LZsmVZzbfZZpsYN25cnH766VkJw80rp+1NTzzxxFi6dOnmRZnrtJVq2lLVQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCobwISh/XtiRVxvtOnT49TTjkl5s+fX3AWabvRn/70pzF8+PBISbnNj7Sl6WWXXRY/+clPNi8qeP3Vr361ygnH9O7CtMowbaea62jfvn2kpGJVkn0zZ86Mr3zlK7Fq1aqsLtOqxtSngwABAgQIECBAgAABAgQIECBAgAABAgQIECBQ3wQkDuvbEyvSfB9++OEYMGBAfPzxxwVncOaZZ8aYMWOiVatWBeulwuOPPz6mTp1aab2yCl//+tfj/vvvL7us9GdKGqZtR++5556cdTt06BBpheCee+6Zs7xQ8Prrr48zzjhjkyotW7aM//u//9sk5oIAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUF8EJA7ry5Mq4jzvu++++OY3vxmffPJJwVn8/Oc/jx/96EcF61QsfPvtt+Pzn/98pATflhxpi9Bf//rXW1I11q9fn0ka3n333Tnrt2nTJpM0TO9NrM6xZs2a6Ny5c6QVhmVH2o711VdfLbv0kwABAgQIECBAgAABAgQIECBAgAABAgQIECBQrwQkDuvV46r7yd55553x7W9/O5OIyzd6kyZNYuLEiTF06NB8VfLGhwwZEr/4xS/yllcsOO200zLjVIzlOk9Jw0GDBuVdzbjtttvG008/HQcffHCu5lscS4nSCy64oLx+ep9jVVZQljd0QoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoAQGJwxJ4CKU6hUcffTSOOuqo+PTTTwtOMb0/ML37sDpHWkF40kknbVHTH/7wh3HFFVdUWnfw4MFx22235a03cuTIGD16dN7yLS1YuXJl7LrrrvHRRx9lmqTVlimZ6CBAgAABAgQIECBAgAABAgQIECBAgAABAgQI1EcBicP6+NTqYM7Lli2LHj16xJIlSwqOllYMTp48uWCdQoWvv/56dO/evVCV8rL0XsHTTz+9/DrXya9+9as4+eSTcxVlYmlr0rSdaLNmzfLWqUpB375948knn8w0uemmm2LYsGFVaa4uAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBkBCQOS+ZRlNZE/u3f/i0eeOCBgpPad99948UXX4wWLVoUrFeocPHixbH77rsXqlJe9thjj8Vhhx1Wfr35ybvvvhvpPYMrVqzYvChz3ahRo3jqqaeiT58+OcurE7zwwgvjsssuyzR94oknIiUSHQQIECBAgAABAgQIECBAgAABAgQIECBAgACB+iggcVgfn1otz/m6666LM888s+Ao2223Xbzwwgux//77F6xXWeHChQujQ4cOlVXLlP/v//5v7LHHHjnrbtiwIb761a/G9OnTc5an4PDhw+PGG2/MW16dgpRcTUnWdKTE5Z577lmdbrQhQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBRdQOKw6I+gtCbw9ttvZ5KBa9asKTixUaNGxcUXX1ywzpYUbulWpWlV46pVqyKtGsx1pFV/afVfviO9i3DOnDmxww475KtSrfjatWvjnXfeybRN26Dmm1+1OteIAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCHAhKHdYhdH4ZK7yz8xS9+UXCqbdu2zSTLWrVqVbDelhSm7T0LbT9a1scXv/jFeOWVV8ouN/mZ3sO41157RaFk56RJk2Lo0KGbtHNBgAABAgQIECBAgAABAgQIECBAgAABAgQIECDwDwGJw39YNPizBQsWxN577x3r1q0raHHVVVfFD37wg4J1trRwypQpMWjQoEqrf/Ob34w77rgjZ73zzjsvxo4dm7MsBVOiM21z2rx587x1FBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEGrqAxGFD/wRUuP/0XsP0fsNCx+677x7z5s2rsSTc1VdfHeeee26hITNl//Ef/xE/+clPsuotW7YsOnXqFKtXr84qKwukdqm9gwABAgQIECBAgAABAgQIECBAgAABAgQIECBAIL+AxGF+mwZV8t5770Xnzp0LbveZQFKi75xzzqkxm8GDB8dtt91WaX8zZsyIXr16ZdW76KKLYsyYMVnxioGU6OzSpUvFkHMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHNBCQONwNpqJeXXHJJjBw5suDtN23aNBYvXhzt2rUrWK8qhZ/73Ofij3/8Y8EmrVu3juXLl0cav+Lxl7/8JTp27BgrV66sGN7kfN9994033nhjk5gLAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBbAGJw2yTBhn553/+53juuecK3vvRRx8dDz74YME6VSn84IMPMu8f3LhxY8FmX//61+P+++/PqjNp0qQYPnx4VrxioHHjxtG9e/eKoWqdT5s2LXbbbbdqta2s0csvvxzTp0+PZs2aRf/+/WOXXXaprIlyAgQIECBAgAABAgQIECBAgAABAgQIECBAgECNC0gc1jhp/eswJfB23nnn+PTTTwtO/r//+7/jW9/6VsE6VSl86KGH4mtf+1qlTcaPHx9nn312Vr1jjz027rvvvqx4TQe23XbbWLVqVWyzzTY13XX87Gc/i1GjRpX326RJk0ws1/scyys5IUCAAAECBAgQIECAAAECBAgQIECAAAECBAjUgoDEYS2g1rcup0yZEoMGDSo47VatWsXSpUtju+22K1ivKoUpOXbppZdW2iRtNZq2HK14rF27Ntq0aROrV6+uGK6V8y9+8Yvxyiuv1Hjfqc+ePXtGrhWXKal65JFH1viYOiRAgAABAgQIECBAgAABAgQIECBAgAABAgQI5BOQOMwn04DigwcPjttuu63gHR933HExderUgnWqWti1a9d46623CjbbddddM+9V3LzSI488UmliLa3ea9GixeZNq3x94oknxsSJE6vcrrIGV1xxRZx//vk5qw0ZMiQmT56cs0yQAAECBAgQIECAAAECBAgQIECAAAECBAgQIFAbAhKHtaFaz/rs0qVLvPPOOwVnfeWVV8Z5551XsE5VCl988cU46KCDKm0yYsSIuOGGG7Lqpa1Lr7nmmqx4xcCpp54aN998c8VQSZ2fddZZce211+acU1ptmFYdOggQIECAAAECBAgQIECAAAECBAgQIECAAAECdSUgcVhX0iU8Ttp+dM2aNQVn+PTTT0efPn0K1qlK4TnnnBMTJkyotMmsWbOie/fuWfXS9qGvvfZaVrxiIK3YSyv3SvWYNGlSDB8+POf0jjrqqJg2bVrOMkECBAgQIECAAAECBAgQIECAAAECBAgQIECAQG0ISBzWhmo96nPFihWx4447Fpxx06ZNI9WriW0/00Cffvpp7L777pl3JhYaOCUqU8Iy19GuXbtYtmxZrqLy2Jw5c6Jbt27l16V2smDBgujYsWPOaV133XXx3e9+N2eZIAECBAgQIECAAAECBAgQIECAAAECBAgQIECgNgQkDmtDtR71+eabb8bnP//5gjP+0pe+FDNnzixYpyqFW/J+wtTflClT4oQTTsjqeu3atdG8efOseMVASnKuXr26Yqgkzy+99NIYNWpUrFu3rnx+6X2Sd955ZzRu3Lg85oQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUNsCEoe1LVzi/T/55JPRt2/fgrM85ZRT4tZbby1YpyqFqb9f/vKXBZvssssukVbkbbPNNln15s+fH507d86KVwykFY0LFy6sGCrZ81deeSXuueeeTKKwV69e0a9fv5Kdq4kRIECAAAECBAgQIECAAAECBAgQIECAAAECn10BicPP7rPdojtLK9tyreqr2PgHP/hBXHXVVRVD1T7/6KOPon379rFq1aqCfYwcOTJGjx6ds86MGTOid+/eOcvKgvvuu2+88cYbZZd+EiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVCIgcVgJ0Ge9+O677460NWahY8yYMfHjH/+4UJUtLhs/fnx873vfK1g/vVMxrSpMqwZzHWl13oABA3IVlcf233//mD17dvm1EwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcICEoeFfT7zpY8//ngcfvjhBe/zxhtvjOHDhxessyWFH3/8cey1117x3nvvFax+wQUXxGWXXZa3zrRp0+Loo4/OW54K2rRpE8uWLStYRyEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgMA/BCQO/2HRIM9eeumlOPDAAwve+9SpUytdlViwg78Xjhs3LtK2p4WOrl27xmuvvRbNmzfPW23OnDmRtiKt7Fi9enW0aNGismrKCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE/iogcdjAPwaLFy/OuyVoGc0DDzwQxxxzTNlltX5+8MEH0a1bt3j//ffztm/UqFE89dRT0adPn7x1UsGaNWsyCcGNGzcWrDd37txIiciaPhYtWhQ77bSTpGRNw+qPAAECBAgQIECAAAECBAgQIECAAAECBAgQKKqAxGFR+Utj8J133rlgQm/KlClxwgknbNVkTz311Lj11lsL9jFixIi44YYbCtYpK9xtt91iyZIlZZc5fz722GNx2GGH5SyrbvB//ud/on///pHMJk+eXOP9V3de2hEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEtlZA4nBrBT8D7Y844oh49NFH897JpEmTYujQoXnLKytIybZ+/foVrLbHHnvEG2+8Ea1bty5Yr6zw0EMPjWeffbbsMufP73//+zF27NicZdUJ3n333TFo0KD45JNPMs1HjhwZo0ePrk5X5W1SX3/4wx/i1VdfjbRCctiwYZn3QJZXcEKAAAECBAgQIECAAAECBAgQIECAAAECBAgQqCMBicM6gi7lYS677LK48MIL807xe9/7Xvznf/5n3vJCBX/+858z71BcsGBBoWrx4IMPxtFHH12wTsXCc889N66++uqKoazzlIRcuHBhtGrVKqusqoG0WnLIkCHx6aefZpqmVYfp3Y+NGzfeoq7Wrl0bf/rTn+KPf/xjJkH6+uuvx+zZs+PNN9+MdevWlffx3HPPxSGHHFJ+7YQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUFcCEod1JV3C48yfPz+zyi3fOwO7d+8es2bNqvIdpHcR9u3bN55//vm8bVPi7cYbb6zyisaUhNtnn33KE3n5BkgJz5T4rO6RTK688sq44IILoswnrXZMKzSbN29eabcDBw6M6dOnZ7aCLWufr9EOO+wQy5Yti6ZNm+arIk6AAAECBAgQIECAAAECBAgQIECAAAECBAgQqDUBicNao61fHffp0yeeeeaZnJNu1KhRLF26NNq1a5ezPFdww4YN8a1vfSvuuuuuXMWZWEqQpZV8J554Yt46hQpS/3fccUehKtGpU6fMCr8WLVoUrJerMCXxBg8eHNOmTSsv3nfffTNOO+20U3ms0ElKMv7+97+P9evXF6qWKUurGNN2qA4CBAgQIECAAAECBAgQIECAAAECBAgQIECAQDEEJA6LoV6CYz7++ONx+OGH553ZJZdcEhdddFHe8ooFK1eujG9/+9uZ7UcrxiueN2vWLJP0+8Y3vlExXKXzl19+OQ444IBK26Q6DzzwQOyyyy6V1i2r8Lvf/S5OOumkWLx4cVko0nsYZ8yYER06dCiPbenJ6tWrMwnMc845J+8KzBtuuCFGjBixpV2qR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoUQGJwxrlrN+dpRVv9957b86bSCv20orEL33pSznLy4Jz586N1M+cOXPKQlk/U1/33HNPHHHEEVllVQ0ceeSR8cgjj1TarGPHjpmVg2nFYL4jbSX68MMPx4QJEzJ9Vtxa9KCDDorf/OY3meRhvvZbEr/mmmvi7LPPzln17bffzmwZm7NQkAABAgQIECBAgAABAgQIECBAgAABAgQIECBQywISh7UMXJ+6X7hwYRxyyCGxaNGinNNO7+CbOHFiHH/88dGkSZNN6qSE4ZgxY+L2228vuC3nzjvvHFOnTo20NWpNHCtWrIh+/fpltgOtrL+UsBwwYEDmT5cuXSKtekz3nN7x+M4772S2VX3rrbeyuhkyZEhcd911mfpZhVUMnHvuuXH11VdntUrzmTdvXlZcgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQVwISh3UlXU/G+cMf/pBJ6n3wwQd5Z5zeG5gSjCkJmJKMaXXhm2++Gem9hvmOxo0bx2mnnZZJLu644475qlUrnrZGPeqoozLbiFargzyNtt122xg/fnyNbh/as2fPmDlzZtaIp59+elx//fVZcQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQF0JSBzWlXQ9GmfWrFlx8sknR/q5tUdKGKYVgaNHj96i9xFWd7xVq1bF1772tZg+fXp1uyhvlxKGxx13XPzwhz+sdGvW8kZbcJKSse3atcuZYE1btx577LFb0IsqBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHaEZA4rB3Xet/runXrMqsDx40bF2lFX1WP9u3bx6mnnppZZdi5c+eqNq9W/TTn//qv/4pLLrkk73arhTru0KFDZr5Dhw6NNP+aPtIWrWmb182Ppk2bxvLly6N169abF7kmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNSZgMRhnVHXz4HWrl0b06ZNizvvvDPeeOONWLx4cSbJVXY322+/fbRp0ybzp0ePHnHooYdG7969o1u3btGoUaOyanX6M835sccey8z76aefjiVLlkRa7bdx48bMPNK80rzbtm0b+++/f6R59+rVK7Pd6ebvbqzJiQ8fPjwmTZqU1WUyq4mVklkdCxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEqiAgcVgFLFX/JpASc2kVYloh16xZs3rBklYj/uUvf8nMt2XLlpG2UK3rI628nD9/ftawaRvXkSNHZsUFCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJ1KSBxWJfaxmqwAvPmzYt99tkn5/0///zzcfDBB+csEyRAgAABAgQIECBAgAABAgQIECBAgAABAgQI1JWAxGFdSRunQQtcf/31ccYZZ2QZ7LTTTvH+++9HbW6RmjWoAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgh4DEYQ4UIQI1LdC/f/+49957s7odOHBg3HXXXVlxAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAXQtIHNa1uPEanMD69eujbdu2sWLFiqx7v+mmm2LYsGFZcQECBAgQIECAAAECBAgQIECAAAECBAgQIECAQF0LSBzWtbjxGpzAjBkzonfv3jnve/78+dGxY8ecZYIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgboUkDisS21jNUiBUaNGxc9+9rOse+/atWvMnTs3Ky5AgAABAgQIECBAgAABAgQIECBAgAABAgQIECiGgMRhMdSN2aAE0mrDtOpw8+Oss86KCRMmbB52TYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoioDEYVHYDdpQBFauXBlt2rSJ9J7DzY8HHnggjjnmmM3DrgkQIECAAAECBAgQIECAAAECBAgQIECAAAECRQVJp4EAAAa0SURBVBGQOCwKu0EbisB9990Xxx57bNbtbrPNNvHBBx9Ey5Yts8oECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLFEJA4LIa6MRuMwDnnnJNzO9KvfOUr8eSTTzYYBzdKgAABAgQIECBAgAABAgQIECBAgAABAgQIlL6AxGHpPyMzrMcC3bt3j9dffz3rDi699NK48MILs+ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFiCUgcFkveuJ95geXLl0e7du1i48aNWff64osvxgEHHFAe/+STT+Kiiy6K0047Lfbee+/yuBMCBAgQIECAAAECBAgQIECAAAECBAgQIECAQF0JSBzWlbRxGpzAb3/72zjmmGOy7rtt27axdOnSaNy4cXlZShjedNNNYQvTchInBAgQIECAAAECBAgQIECAAAECBAgQIECAQB0LSBzWMbjhGo7AT3/60xg9enTWDQ8aNChuv/328vikSZNi+PDh0ahRo3jooYeiX79+5WVOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJ1JSBxWFfSxmlwAscdd1zcfffdWff961//Ok488cRM/MEHH4wBAwbEunXr4uyzz47x48dn1RcgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNSFgMRhXSgbo0EK9OzZM2bOnJl172+99VbmPYYPP/xw9O/fP9asWRP77bdfvPTSS9G8efOs+gIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgboQkDisC2VjNEiBffbZJ+bNm5d175dffnksX748xo4dGxs2bIiWLVvGs88+Gz169MiqK0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQqCsBicO6kjZOgxM46KCD4sUXXyx4382aNYtp06bFv/zLvxSsp5AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUNsCEoe1Laz/BitwyimnxC9/+cu899+kSZOYOnVqHHvssXnrKCBAgAABAgQIECBAgAABAgQIECBAgAABAgQI1JWAxGFdSRunwQm89tprceCBB8a6deuy7j29/3DixIlxwAEHZJUJECBAgAABAgQIECBAgAABAgQIECBAgAABAgSKISBxWAx1YzYYgVmzZsW1116beddh8+bNY7/99sskEwcOHBiNGzduMA5ulAABAgQIECBAgAABAgQIECBAgAABAgQIECh9AYnD0n9GZkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg1gUkDmud2AAECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIESl9A4rD0n5EZEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKh1AYnDWic2AAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHSF5A4LP1nZIYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEal1A4rDWiQ1AgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoPQFJA5L/xmZIQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFaF5A4rHViAxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAofQGJw9J/RmZIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoNYFJA5rndgABAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEpfQOKw9J+RGRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCodQGJw1onNgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0heQOCz9Z2SGBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGpdoNGHH364sdZHMQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAiUtIHFY0o/H5AgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUjUCjvfbay4rDurE2CgECBAgQIECAAAECBAgQaHACGzf6b4cG99DdMAECBAgQIECAQL0VkDist4/OxAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUnECjLl26+NW/mvPUEwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIF6KSBxWC8fm0kTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqFmBRnvvvbcVhzVrqjcCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC9U5A4rDePTITJkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFDzAv8PSBJShvmxs0AAAAAASUVORK5CYII=)"
      ],
      "metadata": {
        "id": "A6EZg17Yvrcb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = AbstractModel()\n",
        "model.i = RangeSet(len(df))\n",
        "features = [f for f in df.columns if f not in ['y'] ]\n",
        "C = 100\n",
        "model.alpha = Var(model.i, bounds=(0,100), within = Reals)\n",
        "model.L = Var(model.i,bounds=(0,100), within = Reals)\n",
        "\n",
        "def rule_c1(model):\n",
        "  return sum(df['y'][i-1]*model.alpha[i] for i in model.i) ==0\n",
        "model.C1 = Constraint( rule = rule_c1)\n",
        "\n",
        "def rule_c2(model,i):\n",
        "  return model.alpha[i] + model.L[i] ==C\n",
        "model.C2 = Constraint(model.i, rule = rule_c2)\n",
        "\n",
        "def kernel(i,j):\n",
        "  # (1+Xi*Xj)^2\n",
        "  return (1+sum(df.loc[i-1,f]*df.loc[j-1,f] for f in features))**2\n",
        "\n",
        "def rule_obj(model):\n",
        "  expr = sum(model.alpha[i]*model.alpha[j]*df['y'][i-1]*df['y'][j-1]*kernel(i,j) for i in model.i for j in model.i)\n",
        "  return sum(model.alpha[i] for i in model.i) -0.5*expr\n",
        "model.obj = Objective(rule = rule_obj, sense = maximize)\n",
        "instance = model.create_instance()\n",
        "results = opt.solve(instance)\n",
        "\n",
        "\n",
        "from pyomo.opt import SolverStatus, TerminationCondition\n",
        "if (results.solver.status == SolverStatus.ok) and (results.solver.termination_condition == TerminationCondition.optimal):\n",
        "     print (\"this is optimal\")\n",
        "elif results.solver.termination_condition == TerminationCondition.infeasible:\n",
        "     print (\"do something about it? or exit?\")\n",
        "else:\n",
        "     print ('ERROR ' + str(results.solver))\n",
        "\n",
        "# CPLEX\n",
        "# Gurobi\n",
        "# Mosek (maybe)\n",
        "\n",
        "svm_points = []\n",
        "for i in model.i:\n",
        "  print(i, value(instance.alpha[i]), value(instance.L[i]))\n",
        "  if value(instance.alpha[i]) > 0.1 and value(instance.L[i]) >0.1:\n",
        "    svm_points.append(i)\n",
        "print(svm_points)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XhQW-Hd3wHX9",
        "outputId": "e015a02b-e97a-4237-a56e-dff950d6d060"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "this is optimal\n",
            "1 0.0 100.0\n",
            "2 0.0 100.0\n",
            "3 57.27563647163788 42.72436352836212\n",
            "4 0.0 100.0\n",
            "5 0.0 100.0\n",
            "6 0.0 100.0\n",
            "7 0.0 100.0\n",
            "8 0.0 100.0\n",
            "9 0.0 100.0\n",
            "10 100.0 0.0\n",
            "11 0.0 100.0\n",
            "12 0.0 100.0\n",
            "13 0.0 100.0\n",
            "14 0.0 100.0\n",
            "15 0.0 100.0\n",
            "16 4.094785202759253e-09 99.99999999590521\n",
            "17 0.0 100.0\n",
            "18 100.0 0.0\n",
            "19 0.0 100.0\n",
            "20 0.0 100.0\n",
            "21 19.54625624995872 80.45374375004128\n",
            "22 0.0 100.0\n",
            "23 99.99999988192309 1.1807690715126403e-07\n",
            "24 47.623539842818204 52.376460157181796\n",
            "25 0.0 100.0\n",
            "26 0.0 100.0\n",
            "27 0.0 100.0\n",
            "28 100.0 0.0\n",
            "29 0.0 100.0\n",
            "30 0.0 100.0\n",
            "31 0.0 100.0\n",
            "32 0.0 100.0\n",
            "33 1.0407408805465453e-08 99.99999998959258\n",
            "34 0.0 100.0\n",
            "35 0.0 100.0\n",
            "36 0.0 100.0\n",
            "37 93.36882208941168 6.63117791058832\n",
            "38 0.0 100.0\n",
            "39 0.0 100.0\n",
            "40 0.0 100.0\n",
            "41 0.0 100.0\n",
            "42 0.0 100.0\n",
            "43 11.13851799521891 88.86148200478108\n",
            "44 0.0 100.0\n",
            "45 0.0 100.0\n",
            "46 19.938092103391625 80.06190789660837\n",
            "47 0.0 100.0\n",
            "48 2.7545145716434763e-08 99.99999997245484\n",
            "49 0.0 100.0\n",
            "[3, 21, 24, 37, 43, 46]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "$$f = \\sum_i \\alpha_i k(X_i,x) y_i +b$$"
      ],
      "metadata": {
        "id": "5zpF-SZTz5l3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "j = 21\n",
        "b = df.loc[j-1,'y'] - sum(value(instance.alpha[i])*kernel(i,j)*df.loc[i-1,'y'] for i in instance.i)\n",
        "print(b,df.loc[j-1,'y'] )\n",
        "\n",
        "j = 46\n",
        "b = df.loc[j-1,'y'] - sum(value(instance.alpha[i])*kernel(i,j)*df.loc[i-1,'y'] for i in instance.i)\n",
        "print(b,df.loc[j-1,'y'] )\n",
        "\n",
        "\n",
        "j = 24\n",
        "b = df.loc[j-1,'y'] - sum(value(instance.alpha[i])*kernel(i,j)*df.loc[i-1,'y'] for i in instance.i)\n",
        "print(b,df.loc[j-1,'y'] )\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-uIrj6691Kod",
        "outputId": "5bac9a01-972b-4efa-ac0b-1dc6f50805d8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9.772935211408335 1\n",
            "9.77293513741383 -1\n",
            "9.772935116707165 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D6jJLSYowHVn",
        "outputId": "b444a9f3-e94f-4d64-de6d-75aaae9aaec5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.16393484995728436, 0.19672182348054726]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "s5qIFnUt1l4C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "i = 2\n",
        "i = 19\n",
        "b = df.loc[i-1,'y'] - W[0]*df.loc[i-1,'f1'] - W[1]*df.loc[i-1,'f2']\n",
        "print(b)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-j8KH2ts1MLL",
        "outputId": "ba3a06a7-72d8-43f5-8161-426541b3840c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "-2.4426266937513263\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "c6Ua0MowwHTA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "5KN-P0MmwHQY"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}