Charts_in_Colaboratory.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Charts in Colaboratory",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "metadata": {
        "colab_type": "text",
        "id": "QSMmdrrVLZ-N"
      },
      "cell_type": "markdown",
      "source": [
        "# Charting in Colaboratory\n",
        "\n",
        "A common use for notebooks is data visualization using charts. Colaboratory makes this easy with several charting tools available as Python imports."
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "xNzEBRkzL3B0"
      },
      "cell_type": "markdown",
      "source": [
        "## Matplotlib\n",
        "\n",
        "[Matplotlib](http://matplotlib.org/) is the most common charting package, see its [documentation](http://matplotlib.org/api/pyplot_api.html) for details, and its [examples](http://matplotlib.org/gallery.html#statistics) for inspiration."
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "WALI8x49GUpe"
      },
      "cell_type": "markdown",
      "source": [
        "### Line Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "08RTGn_xE3MP",
        "outputId": "908732cc-757d-46d8-ac75-5bdb5ba51cfe",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "x  = [1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
        "y1 = [1, 3, 5, 3, 1, 3, 5, 3, 1]\n",
        "y2 = [2, 4, 6, 4, 2, 4, 6, 4, 2]\n",
        "plt.plot(x, y1, label=\"line L\")\n",
        "plt.plot(x, y2, label=\"line H\")\n",
        "plt.plot()\n",
        "\n",
        "plt.xlabel(\"x axis\")\n",
        "plt.ylabel(\"y axis\")\n",
        "plt.title(\"Line Graph Example\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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kHcNcKbkTM6TyMVeqLRzYKmCGtOOYKyV3YIa045gr1Q4ObIUxQ9o5zJWSOzBD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\niHSAA5uIiEgHOLCJiIh0gAObiIhIB/4/7xMZYKj1tQoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674bad6690>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "sIZLTZ0pdo0Z"
      },
      "cell_type": "markdown",
      "source": [
        "### Bar Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "bZv4MenQpYOF",
        "outputId": "ce9608d5-e7ea-4ac7-856f-a265b3d0eee9",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Look at index 4 and 6, which demonstrate overlapping cases.\n",
        "x1 = [1, 3, 4, 5, 6, 7, 9]\n",
        "y1 = [4, 7, 2, 4, 7, 8, 3]\n",
        "\n",
        "x2 = [2, 4, 6, 8, 10]\n",
        "y2 = [5, 6, 2, 6, 2]\n",
        "\n",
        "# Colors: https://matplotlib.org/api/colors_api.html\n",
        "\n",
        "plt.bar(x1, y1, label=\"Blue Bar\", color='b')\n",
        "plt.bar(x2, y2, label=\"Green Bar\", color='g')\n",
        "plt.plot()\n",
        "\n",
        "plt.xlabel(\"bar number\")\n",
        "plt.ylabel(\"bar height\")\n",
        "plt.title(\"Bar Chart Example\")\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ut+u11xL0wQfv6ssv/6P8/ALFxNypoUOHSZI+/3ydPv54mWy2At1yS2M9+eR4WSwWde0a\no/vu669t27YqMDBQ06fPUpUqVS7p5eLLp+bm5igkpPCCKv/97xa9884iFRQUqHLlynruuZdUpUoV\nLV78lo4cOaxffz2iatWqX9b11S8H4Q0A8CkHDx5QVFSDUqdJTd2vpUs/VHBwsHbu3KHDh3/RggVL\n5XA49MwzY5WS8o1CQ0O1YcPnevPNxbJarZo16xV9/vk6xcberdzcHEVHN9GwYSM1f/5crVqVqMGD\nh15SZ8OG/+jbb1N06tQp/fnPtdSuXYwk6dZbb9Nbby2RJK1evVIffLBUjz76uKTCa7G/8cYi+fv7\nX9uBuQjhDQDwaa+++or27EmRv7+/Fix4R5LUsmVrBQcHS5KSkr7Szp1Jzmuh5+Tk6vDhX/TTT6na\nv3+fHnlksBwOh/Ly8nTDDTdIkvz9/dWmTeEtPuvXb6jk5KRia1+823zWrFf0/vvvaODAv+nEiWN6\n7rl/6rffTqmgoEDVq9dwznPHHTGGBrdEeAMAfEydOpHauPEL5+OxY5/R6dOZevjhIc7ngoJ+vy2n\nw+HQoEF/K7KbXZJWrPhQ3brdo7///dFLapQr93u4Wq1+stkKXPbVrl17ffJJ4T3FZ8+eqQEDBqlt\n2zv09de79PbbC5zTBQYGuvEqrw4/FQMA+JTmzVsqPz9fK1eucD6Xk5Nb4vStW9+uNWv+pZycHEnS\nqVMnlZGRoebNW2njxg3KyMiQJJ05c0bHjx+TVPSWo6W5eLo9e75RjRp/kiSdPXtW4eGFJwKsW7f6\nMl7dtcGWNwCgdJmeX9b06f/QnDmz9MEHSxUaWkVBQUEaOfKxYqdt2fJ2/e9/aRo+/EFJUoUKFTRp\n0hTVrl1HjzwyUmPHPiq73SF/f3+NHTtOVatWc/vWnl98sV7ffpsim82uqlWrKj5+siRp6NBHNHHi\nM6pUqbKaNWuhY8eOuvfCrhFuCWpS3K3HPYyT+3xtrLglqG/glqDG45agAIBriluC+iZDw/vgwYMa\nM2aMLBaLHA6HDh06pMcff1yDBw82siwAAGWaoeFdp04drVy5UpJkt9sVExOjrl27GlkSAIAyz2Nn\nm2/btk1//vOfVb16dU+VBACgTPLYMe+1a9eqe/funioHD7uak1quFie/XD2bzabU1NRiTy4yGu8f\ncPk8crZ5fn6+2rdvr7Vr1yosLMzocvCC1NRU1a9/UFIdD1c+qP376ygqytNnJJctvvj+FfYkeeNs\n8/37xToFn+aRLe/NmzerUaNGbgc3Zye65mtncRZusdWR5z9oC2uXNBa+Nk6+yhffv8Kegj3ez4Xa\nrFNXj7Fyz5X8VMwjx7zXrFmje+5x7xZqAACgdIaHd25urrZt28ZZ5gAAXCOG7zYPDAzUjh07jC4D\nAMB1gxuTAABgMoQ3AAAmQ3gDAGAyhDcAACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gDAGAyhDcA\nACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gDAGAyhDcAACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAm\nQ3gDAGAyhDcAACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gDAGAyhDcAACZDeAMAYDKGh3dWVpZG\njx6tbt26qXv37kpJSTG6JAAAZVo5owtMnTpVHTp00Ny5c1VQUKDc3FyjSwIAUKYZuuWdnZ2t5ORk\n9e7dW5JUrlw5BQcHG1kSAIAyz9DwPnz4sKpUqaIJEyYoLi5OkyZNYssbAICrZOhu84KCAu3du1fP\nPfecoqOjNXXqVL311lsaPXq0kWUBSZLNZlNqaqrS07M9Xrt27bqyWq0erwtjsU7BVxga3tWqVVO1\natUUHR0tSYqNjdXChQtdzhcREWJkW2WGL41TRob3DoeEhQUXOxapqamqP6W+FOrhhjKl/ZP2Kyoq\nysOFr5wvvn++2BPr1OXzpc+pssTQ8A4PD1f16tV18OBB1alTRzt27FBkZKTL+U6ezDKyrTIhIiLE\np8apcEvEOx+26enZxY5Fenp24YdsuO/05Kt89v3zxZ5Yp9zma59TvupKvuAYfrb5xIkT9dRTT6mg\noEA1a9bU9OnTjS4JAECZZnh4N2jQQCtWrDC6DAAA1w2usAYAgMkQ3gAAmAzhDQCAyRDeAACYDOEN\nAIDJEN4AAJgM4Q0AgMkQ3gAAmAzhDQCAyRDeAACYDOENAIDJEN4AAJgM4Q0AgMkQ3gAAmAzhDQCA\nyRDeAACYDOENAIDJEN4AAJgM4Q0AgMkQ3gAAmAzhDQCAyRDeAACYDOENAIDJEN4AAJgM4Q0AgMkQ\n3gAAmAzhDQCAyRDeAACYDOENAIDJlDO6QKdOnRQcHCw/Pz+VK1dOy5cvN7okAABlmuHhbbFY9O67\n76py5cpGlwIA4Lpg+G5zh8Mhu91udBkAAK4bhoe3xWLRQw89pN69e+ujjz4yuhwAAGWe4bvNly1b\npoiICKWnp+vBBx9U3bp11aJFC6PLlmk2m02pqalKT8/2eO3atevKarV6vC4A4HeGh3dERIQkKSws\nTF27dtW3337rMrwjIkKMbsvUUlNTVX9KfSnUw4Uzpf2T9isqKuqSP2VkBHu4md+FhQUXu874Yk++\nyhfHip6KMts6dYEZezYDQ8M7JydHdrtdFStW1Llz57R161aNGjXK5XwnT2YZ2ZbppadnFwZ3uHdq\nF/f+FO4F8M4HW+k9eUdJPfkq333/fLEn7zDbOiUVBrfZevaGK/mCY2h4nzp1SqNGjZLFYpHNZlOP\nHj10xx13GFkSAIAyz9Dwrlmzpj799FMjSwAAcN3hCmsAAJgM4Q0AgMkQ3gAAmAzhDQCAyRDeAACY\nDOENAIDJEN4AAJiMy/AeMGCAW88BAADPcBneubm5RR7b7XadPn3asIYAAEDpSrzC2sKFC7Vw4UJl\nZ2erTZs2zudzc3PVo0cPjzQHAAAuVWJ49+vXT3fddZemTJmi5557zvl8cHCwKleu7JHmAADApUoM\n75CQEIWEhCghIcGT/QAAABdc3phk9+7dmjlzpg4dOiSbzSaHwyGLxaLt27d7oj8AAPAHLsP72Wef\n1ciRI9W0aVP5+fHLMgAAvM1leAcGBnKCGgAAPsTlpnRMTIw2bdrkiV4AAIAbStzyvv3222WxWORw\nOJSQkKCKFSsqICCAY94AAHhZieG9YsUKT/YBAADcVGJ433TTTZ7sAwAAuMnlCWsXdp9fLCQkRE2b\nNtXTTz+tiIgIw5oDAACXchneDzzwgLKysnTvvfdKklauXCmr1aqgoCBNmjRJb775puFNAgCA37kM\n782bN+vjjz92Ph4/frx69+6tFStWqHv37oY2BwAALuXyp2JnzpxRZmam83FGRoays7MlSf7+/sZ1\nBgAAiuVyy3vQoEHq2bOnOnToIKlwS/zhhx/W2bNn1axZM8MbBAAARbkM74EDB6pFixbauXOnHA6H\n7r//fjVo0ECSitxtDAAAeIbL8JakBg0aOAMbAAB4V4nh/fTTT2vmzJnq3bv3JT8Vk6Tly5cb2hgA\nACheieE9ZMgQSdIzzzzjsWYAAIBrJYZ348aNJUmtWrWSJKWnpyssLMwzXQEAgBK5/KlYSkqKOnbs\nqLi4OEnSt99+q0mTJhneGAAAKJ7L8J4+fboWLFigKlWqSJKio6O1e/fuyypit9sVFxen4cOHX1mX\nAADAyWV45+fn6+abby7y3OVenGXp0qWKjIy8vM4AAECxXIZ3QECAzp496zzj/KefflL58uXdLnDs\n2DFt2rRJ991335V3CQAAnFz+znv48OF66KGHdOLECY0fP15btmzRzJkz3S4wbdo0jRs3TllZWVfV\nqLfYbDalpf3sldq1a9eV1Wr1Sm0Yx1vrFOsTUHa4DO8OHTqobt262rJlixwOh0aMGKFatWq5tfCN\nGzcqPDxcDRs21FdffeV2UxERIW5Pa7TU1FS1aXNSUh0PVz6o/fuDFRUVdclfMjKCPdzL78LCgot9\nf+ipqJJ6kry1TpW8Pkm+OVb0VFRp65QvM2PPZuDWFdZq1qyp+++//7IXvnv3bn3xxRfatGmTzp8/\nr7Nnz2rcuHGaMWNGqfOdPOk7W+np6dkq/JAt/kPP6NrFjUVhT95Rek/e+WAz0zhd+Js31inXPfni\n++eLPXlHae+fr4qICDFdz95wJV9wXIb37t27NXPmTB06dEg2m00Oh0MWi0Xbt293ufCxY8dq7Nix\nkqSkpCQtXrzYZXADAIDSuQzvZ599ViNHjlTTpk3l5+fy/DYAAGAwl+EdGBioHj16XHWhVq1aOa/W\nBgAArpzLTemYmBht2rTJE70AAAA3lLjlffvtt8tiscjhcCghIUEVK1ZUQEDAZR3zBgAA116J4b1i\nxQpP9gEAANxUYnjfdNNNnuwDAAC4idPHAQAwGcIbAACTKTW87XY7Z5oDAOBjSg1vPz8//fOf//RU\nLwAAwA0ud5s3aNBAe/bs8UQvAADADS6vsPb9999rwIABqlWrlipUqOB8fvny5YY2BgAAiucyvCdO\nnOiJPgAAgJtchjfXIwcAwLe4DO+srCwtWLBAP/zwg86fP+98funSpYY2BgAAiufyhLX4+Hj5+fkp\nLS1Nffv2ldVqVZMmTTzRGwAAKIbL8P7f//6nJ554QoGBgbrnnnuUkJCg5ORkT/QGAACK4TK8AwIC\nJEn+/v7KzMyUv7+/0tPTDW8MAAAUz+Ux79q1ayszM1M9evRQv379FBISokaNGnmiNwAAUAyX4f2P\nf/xDkvTggw8qOjpaWVlZiomJMbwxAABQPJfhLUnp6elKSUmRxWLRrbfeKqvVanRfAACgBC6PeX/+\n+efq1q2b3nvvPb3zzjvq3r271q9f74neAABAMVxuec+ePVvLli1TnTp1JElpaWkaMWKEunTpYnhz\nAADgUi63vMuXL+8MbqnwBLbAwEBDmwIAACUrMbxzcnKUk5Ojzp0764033tDJkyd14sQJvfnmm+rc\nubMnewQAABcpcbf5bbfdJovFIofDIUmaM2eO828Wi0WjRo0yvjsAAHCJEsN73759nuwDAAC4yeUx\nbwAA4FsIbwAATIbwBgDAZAhvAABMxq3Lo16pvLw8PfDAA8rPz5fNZlNsbCxnqQMAcJUMDe+AgAAt\nXbpUQUFBstlsGjBggGJiYtSkSRMjywIAUKYZvts8KChIUuFWeEFBgdHlAAAo8wwPb7vdrl69eqld\nu3Zq164dW90AAFwlQ3ebS5Kfn59Wrlyp7OxsjRw5Uj/99JNuvvlmo8sCwHXBZrMpLe1nr9SuXbsu\nt4j2EsPD+4Lg4GC1atVKW7ZscRneEREhHurKtYyMYK/VDgsLLnYs6KkoM/Ukea8vX+xJMtf754s9\npaamqk2bk5LqXDqToQ5q//5gRUVFlTqVL32elyWGhnd6err8/f0VEhKi3Nxcbd++XcOGDXM538mT\nWUa2dVnS07MleecfbHp6drFjUdiTd5TeE+N0ce2S1mNvjZUv9nShNuuUa6X3VEdS6SHqyZ4uiIgI\n8anPc191JV9wDA3vkydPavz48bLb7bLb7br77rvVoUMHI0sCAFDmGRre9evXV2JiopElAAC47nCF\nNQAATIbwBgDAZAhvAABMhvAGAMBkCG8AAEyG8AYAwGQIbwAATIbwBgDAZAhvAABMhvAGAMBkCG8A\nAEyG8AYAwGQIbwAATIbwBgDAZAhvAABMhvAGAMBkCG8AAEyG8AYAwGQIbwAATIbwBgDAZAhvAABM\nhvAGAMBkCG8AAEyG8AYAwGQIbwAATIbwBgDAZAhvAABMhvAGAMBkCG8AAEymnJELP3bsmMaNG6dT\np07JarXqvvvu0+DBg40sCQBAmWdoeFutVk2YMEENGzbU2bNnde+996pdu3aKjIw0siwAAGWaobvN\nIyIi1LBhQ0lSxYoVFRkZqRMnThhZEgCAMs9jx7wPHz6sffv2qUmTJp4qCQBAmWTobvMLzp49q9Gj\nRys+Pl4VK1b0RElANpv9uqx9JWw2m6SDXqh8UDZbmBfqwmg2m02pqalKT8/2aN3atevKarV6tKY3\nGB7eBQUFGj16tHr27KkuXbq4NU9ERIjBXbkvIyPYa7XDwoKLHQt6Kqqknnbv/s0L3RTKzv6txPXY\nW2NV0jgT7q8NAAAMTElEQVRJ0u7d6dLAu6RQDzeVKWVnf2aadYqeiiptnUpNTVX9KfU9u05lSvsn\n7VdUVJQHi3qH4eEdHx+vm2++WUOGDHF7npMnswzs6PIUfmv0zj+O9PTsYsfC099k/1i75J58a5xO\nnz7nhW5+r13SeuytsSppnKT/P1ahksI929OF2mZZp/i3d2ntUtdzL6xTpfXkq65kg9XQY967du3S\nqlWrtGPHDvXq1UtxcXHavHmzkSUBACjzDN3ybt68uX744QcjSwAAcN3hCmsAAJgM4Q0AgMkQ3gAA\nmAzhDQCAyRDeAACYDOENAIDJEN4AAJgM4Q0AgMkQ3gAAmAzhDQCAyRDeAACYDOENAIDJEN4AAJgM\n4Q0AgMkQ3gAAmAzhDQCAyRDeAACYDOENAIDJEN4AAJgM4Q0AgMkQ3gAAmAzhDQCAyRDeAACYDOEN\nAIDJEN4AAJgM4Q0AgMkQ3gAAmAzhDQCAyRDeAACYDOENAIDJGBre8fHxatu2rXr06GFkGQAAriuG\nhve9996rRYsWGVkCAIDrjqHh3aJFC1WqVMnIEgAAXHc45g0AgMmU83YDxYmICPF2C04ZGcFeqx0W\nFlzsWNBTUSX1VLlyBS9083vtktZjb41VSeMk+eZY+eI6RU9FlbZO+eJ6Xpb4ZHifPJnl7Rac0tOz\nJXlnJUxPzy52LAp78o7Se/KtcTp9+pwXuvm9dknrsbfGqqRxknxzrHxxneLf3qW1S1/PPa+0nnzV\nlXzZMHy3ucPhMLoEAADXFUPD+8knn1T//v118OBB3XnnnVqxYoWR5QAAuC4Yutt81qxZRi4eAIDr\nEmebAwBgMoQ3AAAmQ3gDAGAyhDcAACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gDAGAyhDcAACZD\neAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gDAGAyhDcAACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gD\nAGAyhDcAACZDeAMAYDKENwAAJkN4AwBgMoQ3AAAmQ3gDAGAyhDcAACZDeAMAYDKGh/fmzZt11113\nKTY2Vm+99ZbR5QAAKPMMDW+73a4pU6Zo0aJFWr16tdasWaMDBw4YWRIAgDLP0PDes2ePatWqpZtu\nukn+/v7q3r27NmzYYGRJAADKPEPD+/jx46pevbrzcdWqVXXixAkjSwIAUOaVM3LhDofDyMV70EEv\n1Ywo+c+ZHmvkMmoyTu7X9PRYuRgnyUfHinXKvZo+OE6S58fKG++Nl1gcBibsN998o9dee02LFi2S\nJOcJa8OGDTOqJAAAZZ6hu82jo6P1yy+/6MiRI8rLy9OaNWvUuXNnI0sCAFDmGbrb3Gq1atKkSRo6\ndKgcDof69OmjyMhII0sCAFDmGbrbHAAAXHtcYQ0AAJMhvAEAMBnCGwAAk/GZ8OYa6O45duyYBg8e\nrLvvvls9evTQ0qVLvd2ST7Pb7YqLi9Pw4cO93YrPysrK0ujRo9WtWzd1795dKSkp3m7JZy1ZskT3\n3HOPevTooSeffFJ5eXnebsknxMfHq23bturRo4fzudOnT2vo0KGKjY3VQw89pKysLC926DuKG6sZ\nM2aoW7du6tmzpx577DFlZ2e7XI5PhDfXQHef1WrVhAkTtHbtWi1btkzvv/8+Y1WKpUuX8gsHF6ZO\nnaoOHTpo3bp1+vTTTxmvEhw/flzvvvuuPvnkE61atUo2m01r1671dls+4d5773Vez+OCt956S23a\ntNG///1vtW7dWgkJCV7qzrcUN1Z33HGH1qxZo08//VS1atVya6x8Iry5Brr7IiIi1LBhQ0lSxYoV\nFRkZySVnS3Ds2DFt2rRJ9913n7db8VnZ2dlKTk5W7969JUnlypVTcHCwl7vyXXa7XTk5OSooKFBu\nbq5uvPFGb7fkE1q0aKFKlSoVeW7Dhg2Ki4uTJMXFxWn9+vXeaM3nFDdWbdu2lZ9fYRw3bdpUx44d\nc7kcnwhvroF+ZQ4fPqx9+/apSZMm3m7FJ02bNk3jxo2TxWLxdis+6/Dhw6pSpYomTJiguLg4TZo0\nSbm5ud5uyydVrVpVDz74oO68807FxMQoJCREbdu29XZbPis9PV3h4eGSCjc6MjIyvNyROSxfvlwx\nMTEup/OJ8Oan5pfv7NmzGj16tOLj41WxYkVvt+NzNm7cqPDwcDVs2JD1qxQFBQXau3ev7r//fiUm\nJiowMJBzTkpw5swZbdiwQV9++aW2bNmic+fOadWqVd5uC2XIG2+8IX9//yLHw0viE+FdrVo1/frr\nr87Hx48fZ3dUKQoKCjR69Gj17NlTXbp08XY7Pmn37t364osv1LlzZz355JP66quvNG7cOG+35XOq\nVaumatWqKTo6WpIUGxurvXv3erkr37Rt2zbVrFlToaGhslqt6tq1q77++mtvt+WzbrjhBp06dUqS\ndPLkSYWFhXm5I9+WmJioTZs2adasWW5N7xPhzTXQL098fLxuvvlmDRkyxNut+KyxY8dq48aN2rBh\ng1599VW1bt1aM2bM8HZbPic8PFzVq1fXwYOFd6XasWMHJ6yVoEaNGkpJSdH58+flcDgYqz/44x6u\nTp066ZNPPpFUGEx8pv/uj2O1efNmLVy4UG+88YYCAgLcWobPXB518+bNmjp1qvMa6Nx5rHi7du3S\nwIEDFRUVJYvFIovFojFjxrh1jOR6lZSUpMWLF+vNN9/0dis+ad++fXr22WdVUFCgmjVravr06QoJ\nCfF2Wz5p3rx5WrNmjcqVK6dbbrlFL730kvz9/b3dltdd2LuVmZmp8PBwPfbYY+rSpYsef/xxHT16\nVDVq1NCcOXMuOVHrelTcWCUkJCg/P1+hoaGSpFtvvVWTJ08udTk+E94AAMA9PrHbHAAAuI/wBgDA\nZAhvAABMhvAGAMBkCG8AAEyG8AYAwGQIb8BHNGjQQDk5Od5u47LNmzePC+AAHkZ4Az7iWtxAxW63\nX4NOPM9ms3m7BcBUynm7AQCFHA6HFi5cqA0bNuj8+fMaM2aM/vKXv0iSnnrqKaWlpSkvL0+1atXS\ntGnTFBISoqSkJL300ktq1KiR9u3bpyeeeEIdOnRwLvPIkSPq3bu3+vXrp82bNys3N1dTp05Vs2bN\nlJSUpFdeeUUrVqyQpCKPk5KSNHXqVDVp0kTffPON/P39NWPGDM2bN08//vijqlevrnnz5ikwMFCS\n9Ouvv2rIkCE6ceKE6tWrp2nTpik4OFj5+fmaPXu2kpOTlZ+fr6ioKE2ePFlBQUGaMGGCrFarDh48\nqHPnzikxMdHzgw6YFFvegA8pV66cVq5cqfnz52vSpElKT0+XJE2cOFHLly/Xv/71L0VGRmrBggXO\neQ4cOKABAwYoMTGxSHBfkJmZqWbNmikxMVEjR47UzJkznX/749b+xY8PHDiggQMHatWqVWratKke\nfvhhxcfHa82aNfLz89Pq1aud0+7atUuzZ8/WunXrFBwcrPnz50uSFi5cqEqVKumjjz5SYmKiIiIi\nlJCQ4Jxv3759Wrx4McENXCa2vAEf0qdPH0lSnTp11LhxY6WkpKhjx45KTEzUqlWrlJ+fr9zcXNWu\nXds5T61atUq9p3vFihWdod60aVO98sorbvVSp04d1a9fX5J0yy236Ndff3Xe7a9Ro0b65ZdfnNN2\n7NjRedeoPn366KWXXpIkffHFFzp79qw+++wzSVJ+fr4aNGjgnC82Nlbly5d3qx8AvyO8AR9y8a0G\n7Ha7LBaLkpOTtWzZMn344YcKDQ3V6tWr9dFHHzmnq1ChQqnLvPguRX5+fs7jy1artcgx8vPnzxeZ\n7+JQtVqtlzz+4/QXv4YLW/AOh0PPP/+8WrduXey0rnoHUDx2mwM+5MItFNPS0rRv3z41adJEWVlZ\nCgkJUeXKlZWXl+c8Ru2uP9576MLjP/3pTzp8+LCysrLkcDi0Zs2aK+5748aNysjIkFR4+8cLYd2p\nUye9/fbbzqA/e/asDhw4cMV1ABRiyxvwERaLRQUFBYqLi1Nubq6mTJmisLAwxcTE6F//+pdiY2MV\nFhamFi1aaM+ePZe13OIeV61aVQ8++KDi4uIUHh6uVq1a6aeffrqi3lu0aKExY8bo+PHjqlevnsaP\nHy9JGjZsmF577TX16dNHFotFfn5+GjVqFPfBBq4StwQFAMBk2G0OAIDJEN4AAJgM4Q0AgMkQ3gAA\nmAzhDQCAyRDeAACYDOENAIDJEN4AAJjM/wPjs+5LxyqfZwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674b970090>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "YQO2Lw8Xdu7x"
      },
      "cell_type": "markdown",
      "source": [
        "### Histograms"
      ]
    },
    {
      "metadata": {
        "cellView": "both",
        "colab_type": "code",
        "id": "SZ-DMbnPMbMY",
        "outputId": "8c1089d5-ecf0-492b-cf21-8f30ddc45862",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Use numpy to generate a bunch of random data in a bell curve around 5.\n",
        "n = 5 + np.random.randn(1000)\n",
        "\n",
        "m = [m for m in range(len(n))]\n",
        "plt.bar(m, n)\n",
        "plt.title(\"Raw Data\")\n",
        "plt.show()\n",
        "\n",
        "plt.hist(n, bins=20)\n",
        "plt.title(\"Histogram\")\n",
        "plt.show()\n",
        "\n",
        "plt.hist(n, cumulative=True, bins=20)\n",
        "plt.title(\"Cumulative Histogram\")\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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v0/Mtu1BlDiqy1rrPZmEVakWhTUaeItLsJu1e40q6zwzqfPkO2B0dHdizZw+uv/56AMDQ\noUMxevRoaQlTjUolWivDSKC2tjZlhhPUDeT2RjeMhBajs8+lk5m3mZ/abxSqqk6aZpi4u4Yy17oP\ngy6L0vhNo+qVsoqKYzhx4pNI8gnfAbu6uhrjxo3Dvffei/LycqxduxY9PT0y06aU/v7+jAccyQz6\n5gDc19WG5zd/bJvhqDK6srczjof+/W3U1cUCO4aMWqBI57Zt77KZ3CJVRqpSt4KYYeIlAKseJHLJ\nuQqIuoX7WKwukgKs74B95swZHDp0CN/+9rexceNGjBw5EuvWrZOZNqXU1FTjmVc+8PSe2traQUG+\nqupkgKOMDdvCQE1NNb5/3zrs3r0z8AcgXf9TUJmiqBVXVVVJeYh0z7yt10H87IdKgdiLMK9hIqHn\n3P6oOd1bvZ1xPPPKB8p3tUWRT/je/GPy5MmYPHkyLr30UgBAWVkZnnvuubTvmzChCMXFowAA48eP\nxoQJRee9Jh4fjdbWgdcUF49Kvi4eH53yfUePHgUAzJgxI/k51mPbHQsAiopG2v5dKC4elez3cjq+\n9XOLikYOen1x8Si0t48873tZ05Lus82vFedJfKbdv3l5eXjmlQ8wc+b05HlsbR04vpDqOrS2NgAA\nPv/5z2PChKLk9xL/iu/S1laPtU/8Bvd8d/GgzxavM//fek1TXRtBfNfx40cjHj+V/L+oFd/5rdkY\nOXq843kV5wMA2tubEY+fwowZMxzP5fjxozF+/ChUVFSgtLR00DUtLh51Xpq9XD/re9yk2Zwup+PE\n46NRWVmZvA4XXXQROjqasfaJ36B40hcGvd/6+Xb3tfi89vbm5GuAwdfC7jqKz/Vyjsz5wsAxGs77\nfPOxzefDfF+bv4/5dXavMd+b6Z4Hu/TH46OxZcuf8N9ba/DYT65NPiNu7mvzZ7h5Hs2v7e/vx6lT\n554Bp/fZpcN6DlLdrwMtdBUoLi5Afn5+8vetrQ2Ix0djxowZyesm8gnA/r6yPs92xxfvG1FYPOgZ\nMz8P4rnct69h0O+sn+cm/ze/znz/W2OJ9fXWfMzpM73kBW74DtglJSWYMmUKKisr8fnPfx47duxw\nNeisoaEdra1dAIDm5g40NLSft+tKc3NH8jWtrV3J1zU3dwx6n5X4u/ib+Nl8bKf3tLf32P5dEOlJ\ndXzr57a39wx6fWtrV/J35u/llP50n29Nl/mcWf82orAYra1dyfMoji84nRu77y2+g/W7iOO0t/cM\n+mzxOvP/rdc01bWxfj/r7weOOxYVFScHfbb1c8zfRaTRnAbruWxu7kBz8wGsWPsc1j34vfO+szXN\nXq6f9T3793+M5uaO5E5Ddmkyp8vuOOYuF3EdxPtFYdN63dPd1+IeMF838b6ejibs3/8xxo2bcl6a\nxOd6OUfn3tOKmppqFBWNPO8aWdNszR+s38f8uoaGdjQ0tOLw4ePJ35vvzXTPg136m5s70NnZi5Gj\nx9vmVW7zKTfPo/m1tbW1eOaVD1A86Qsp32eXDut5SnW/VlQcw4q1z+G+71+Bz352WvL35u9ql9/Y\n3Vd2z631+NbPsObl5udy5T+8iOJJX0A83o7W1o/xmc9MRX7+EE/5v/l15vs/3fWz5mNOn9nQ0C41\naGc0Svy+++7DT37yE1x77bU4cuQIbrvtNl+fo9OwejdEE2QiwSaysPR2xvHym/s8vUdMCfLblO+m\nuViVJuXezpaokwDA3TgDMe3K2n0kY7CVn66tIGUyriWT6VNeqNpFJL6/6E9204Qu83mMYoBqRgH7\ni1/8Il599VW8/vrreOqpp1BU5L8koepN4YdYPKCxsSH9i0ma4QX+7j8xAjrIAXFWYQVy6ziKqLkd\nbR5kMPL62ZkurGG91mFNkVNBpkHN7aDZKOKH6IoLs6Kp9NKkQctkME46YZR+7QaxHT16VKkM2km6\nBzFdzUP2AgvZVGBUXZDnOpHIfDaHlewWwKCmyKm4YlemQS3MJWT9nL+w8w0lAnZUcwpFTZjCl+nm\nLjIXWAhbptP7gpyHm67mb1dQUmmNglisLpAmb9kZs5fPc9saY53OZnddorhWbr9rRcUx226QsIKi\nn+mAYTeLRxKwa2trlVmgIqiacG9nC5qamgCotU6wSplrpg+iCrVila5tGET/srX7wGmJTze1liBX\nMQuSKLwYhuH6PXZBSaYgnwkZBUU/n9HT0RRaq6HX82duQQijhSOyGnYU7f9eqNa8JCtTC3YuuFpU\nGfAlK6irsqCEl4Do1JycDQUd0ULX3Nzs+j1VVSdRX18XYKr0IbOlSDwbbvdQl5m/iyAfxuDpSJvE\nVaghOdFl5LoqD7+f8QBhlpz96O/vx44dH/p+v+zWDLGinZvBcYaRQH19nRIzFdI9537GI6hy34RV\nmw9CT0cTKisro06GFGKxFbcDR4PK34OOaUr0YcsQRFNv2AUKa4lTlRqiG+YdkHSSasnZmppqPPni\nmyGnKDXrPel0j/R1teHVrceVnalgbkIPYpR+qg1xVJniZn3exXoUlZWVrmp+QX0PN/mOiruceS08\nqVxhdJI1AVtViYS/ZkyV+prdcnpgVGkFsJMuKIupYjrOrR8+qghNTU1apFlknqJpM5eIke1VVVW4\n9/+9gEee35KVXQip6Ph8RSHUgC2We1NVEDXaxsaGQeviZhq8MkmjanNyw5Sq+d3N/G3RgqBqjdVO\nX1cbfr/rpFZpFk2buUSMbK+ri2F4QZGWNT8rr3lNVGtXeOlH7+/vx9GjR1BZWRlZwcL30qTZTmbt\nNtMN3cV85fx8Nog4cWoeVOU6RsXvYjJROreCVQxFRSeTy7XK1tPRhPr6IZg4cZKr11ZVnRy0PKdM\nOt5bsql+Dk6c+AS33v0vAIDrF06PJA2MAC7I2FrTjptmrkznKxOpQkxpEgPi3HQT1dbWKtcUnGrR\nn7CbrnXZZz5bjCgsjrRgEWoNu7Ky0nEB+FRk9+V6faBOnPgET774JopKpvo6nmEksH//RygpmZD2\ntYnE+ZlBNjSR+SG2LRSL+qskqK4FMfAomzPggXXfP3VVswUGzklNTbUyrUxikNx9378i6qQkp8eu\n+e4ixGLqjhVRgY7jgqwivftTjeRUjV3Totv+ZOuI3VTzaWOxOt81ajEP0fo7mSoqjoU2iMztov5B\njZaNor8/zKUYo+Slqd5psRavZC5akkkhWiyo5EV1dTV27PjQNs8YOXp8YCu8ZULlwaZeuF3PPAzR\nF1cDkm5up8xJ+24m4ZubUdLNGYyiRq3qFDKZ56K+vk6LQXdBXX9VFl7xI6y1+VWtQDQ2NuD5zR+n\nLMiJc+SlWV61BaKC5mfgrUqFaK0DdqqbTYw69HuSvY5w9DoJP4p+kPr6ukBKvdkw+nxgAFJ21Aic\niIJiTc2nygYmL2QtvGO97uZtV1WpWQHBFOROnTql3AJRqsyTN3M692GnVeuAnS5QhhkUs6mfWdXa\ndip93W2Dfla5v0oMYrQGgjBqeF6eCTfnUIwz0GX+rJdCmchfdu/eGWCKgpeuxp0u7xItM9XV1doX\nzAWZ3yPMrl1tp3WJJu8oAqX54kQVFESm72XjgSCpUjs1j5qtq4vhwgsvjDpJ56mpqcYzr3yQMm3m\nDEXlTFL0nV6/cDouuugiz+8PejOMTGVTQdyv3s44nnzxIJbOm4aZMy+JOjmhU6ngr20NO9e3xhSZ\nvpeNB3KBGDUrc5nLc599bgc2vyvYCarPOfXC6buI2nc20Ln/X4ag5/MHeZ84jWdyuqYqj2VQJmD7\naVbwkun5nR/pdPFUuKiyMn0VvotMYdSKxAp2QRQMskUsVqdsodpr36PYeEWFgUdBMneD+NnQJ1N+\nRtCnI6bhWa+ddfCvyi09gjZN4tYbR5UAk0j0u57/mEgkEI/HA05R+BKJRCAPmhNVtgj1U2AKahEe\nVZlHLusu15rHRStmWK1BvZ0taGkJpg7pdO10a+lSpoYtU5gDjrzMf4zH4/j9rmDSFcZ2iqLEbe03\nb2xskPa90o3MVX1LznTEIjxBcBrMRv6J5wpwf+/52S7UTKX1KYIOaHYLRbkV5ghtVfKdrAzYYXPu\nwzu/5in6gno7W1IO1BI7+Li9kcXiLEHcVObdhNY+8RvbfnNZfVxiZO6nn55AfX1dVvYdBtUfKMY1\nqNBMn0j0D7q/dZ36N7Aq2z5P7xELvXz66Ym0wch6nqycCslRspsCmSqgpSqAiIWiVLhndaBUwM6k\ntBU067QhN9ra2nzXPM07+JilKr0HVRo2pyWMJiSxctPLb+4bNHeY0lOliS8Wq8OrW49HnQwp/BSw\nRhQWu1q1UNzndioqjmHbtncdC8mqEq0SbgsZbrsaVKnlRkmpgO3mBvfaXCR7o3WvN42fh12UYEXm\naz6mGEDht0SaSLjfeMEsikAgzp0qQchOIiGmkUW3UpTXAZWixSQV0a0kXuunq0Xl62YVXEuOkfZc\np8sjwjqPmTblC6K1L4xChrnLQgbVCwVKBWxA74EdYe3U4+YciQzImtHG43G8uvV45E1QMh4KFR6u\nxsYGPPTvb7teKUqFvslYrM51P7poXdFpT20/0i0XnAlZhbqgu4fEIDMZ5yDVVD+Z38Ftl4VTfqgb\n5QJ2GPyOMlZxyTwnIgOyy2hVrPn4WV1NdunaLx0LmV5aflS8X4IQ1Pf0Wqhz4qdQ4TVABn2tRQFQ\nZhdXunu5trZ2UH4oWhmdZLrGgpnsClxOBuxcIevhUyEo2hFNb2Y6Far8OpehyG2GdzMfP+oWjUxU\nVZ10nH4Y9H3jtVDn1JXn9ZkOIkBmKooCYG9nS/K4jY0NKWvlYo2FVOcszGmsZgzYmjjXrKZ3k45s\nKtT+zMuh+uG1aV/s3HTixCe2rUWHDx/ylQ6VDMyiqPc13iIqspt7ZcnkGUlXkAl7XQG3+WC6qb3p\nauXDRxUNKhSr0pqnXMAOul9SrF3sZqvFMKYUue33Fs1q5uawgYUGoqtR1tfXoaejKbLSZljEfeBE\nLIcqdsEyX8+gpjOp3Azf3596qpJbra2tSoy3cMtpZkc2C3JdATsiH5TVYuA0vVasbCe6Mexa86Kg\nXMBWSZADUfwIM5OWNWI0FVFqVa1GYjWw+UHqTMl8bcIafKii/v5+bNv2Ll7auE3K57mtHYr7NepB\nRU7pjXoxlNra2sDuySDWFUhVWQorH7Qex2tLRRBLu0YesGXUQIJcC9vLRZI9hSxKYvEHmYUV64IL\notQqSsuprqObqUhBCiJTsrv3de4jBs6NNB42sjCS42b7aPZM6LRngKjhRlFZyqTFsKejCTt2fIiq\nqpPJPFSm0AN2VdVJJfoC3AhzAJOK2wyG0T/s9hhepiIJMkd7Bk2kNaoaosz+1zDXnjbnJXbH9Rqg\n3HSVqfacBsEpuIeZd6vc7ZOOKIzLfhYir2GrIqpBXWILQh2CStRELbe+vs5VxhHmjlqZjncQafVS\nQxQDfmQE+Vzsf80GYVQqxDHC3uQnClGPC0qHAfusxsYGrH3iN+cNZgh6dGAsVuc4iCLdeuMyqLLz\nVVAbV4RX2xsY7/DHPx5Iji712qdqXtnOzXWvqanGky++mTbIu81krecq3TrXMrn9zhSdTJZazhZO\nBaSwukNzOmCbM4impibbzN06OjCIgVI6N/24la4mYN64QtfM23z/iP6rdME00+8Z1EYiAEzrubdI\nqVmlW7Ai22Tjdw3yftOZ6NIKmrIBO+xaX+pmkHOL2IsAzqZD+UYUFkeayTU1NUltYhxRWOx77fYg\n+PluMjPodAtW+MH1CaLjtVYZ9fglwxho0g9i5zPRpRU0ZQN2poIM+KImJavJMKi557JqRkFy6vt1\nSneQD10QxNrtsuaN6j7vXXYNLR6PS52XGxUvXW9ux3BY35Mqj6mqOokdOz709JkypPoe5pY2Gfls\nX9dAk35Qm5KE0f2WtQHbiVjUwSnDF1t8uul7PHjwoPQag5kITmZij+hsaW7zOn0j6IcuCCqsxiYE\nce9EXTBUvUvJzbkJemEOlVp6wpJI9GPHjg8H5S26N+lHGrBF5hHUVBa7/uaammq8/OY+xwxfbPHp\ndrSu3Q0ga/DB6Z4ObP1j/Lzfu92hxuxc8PdXMw2ykOAmwzUfO91D57YPXMbcbpmBylpAC2KHIWtg\nyGT7TK89PkhTAAAXj0lEQVT3RFRBPYwVC2UQBbsgBpuqsktfmMTMh3SFe51arCIN2CLz8LvYQbo+\nOaf+5nQZvkoldqfamdeSoqiZtrS0pnyd0xq8doPvdLrR7YgHWhXiGgmpdlzLhPmeymT7TFWWa0wn\nykU4VKJSS0+QzHPIs+07R94k7vaEOtWG0pWes+2CZcJNkBfTvOzOtflcWoOLmZuBQOYaRJSjwlW7\nP6zXSKXFa/y+91xNPJxxB6Igb76PVSqEq0CFqZx+pKok+J3Bo/K8a6vIA7ZbTrWhTNf7zoXtGIPi\nVACQvUC/qqJcZCHoTXL8smudEV046Vp3dCHGkezf/1HUSTmPLs3/QRAtPqdO1Xru5tFlKqk2ARtw\nLs2rVksKmptChnhNdKVHQ6kMzevAKLGjWy4JcjMWXQf7OD1rfsaRyOS8r3dcuf2v05EZLEcUFqdd\nNVCnGrWVVgGbSGcqrhdvZt2MxQundduzuQVL1UJIJhUYXXbQSydbK3GhB+za2lrtBysFKddqdZSe\nmxXCxNKufphbH/xmdG1tHNiVDbgwlHdhTmtkDZu04PeBMIwEDh8+JDk14YrH0ze/inXFo8SBXZmJ\nsjXC3AWkau3Uy5iRIGaxqNBaNDTqBFB2kvXA9Ha2YEThWN/vHxjN3u6r+TKT9Mtq+h7IpIa4Sr/b\n7xh1xiP7+GKgFSBvTm26tRSiPoc6EQP0SkomOP5ddnAVz31RyVSpn2uW6h5IJBKB7M0eWQ3bzQ0v\nHsTTp09nVVOxKg97kDt1pZr2Fbag+xpVuJ4q9427kUmzohhoRe5Yl1S2DvqS3Y/d19WG9e8exZ/+\ndMR2hcmg8oowxxhYa/6NjQ2BrFGgVJO4NSiLB/Hjj/8vuWsQRcfr+bc+MFEvtqLCblFRHz+dVNOC\nzCubhfk9xLFSDWwLqxm3vr7O1z1sPa9BT8tLJJy3dxW7sDkJoh87Ly8v5ZLCXoJrEOcuiLwpiHtS\nqYBtR3xpr6Ul1TNGP2Rt/BDVSNCoa91tbW2RTsVxK8qCjVgVzH5/9minMonpOjoMiLJew1SrrfV1\nt0k/fixWh/v+5b/xpz8dsf17uvw0iGATRI1XViXOLm/q6WgKZY9rL5QP2EFJJNRZWjPoNdWt3Jag\nRbpk7owl66H1O5fSfHxzoc7NgBbDSIQyhzPqgk2qwWOyM12xGY9bqg6IsrK7hiMKx4a64puo1ZI7\nqk7TM8uKgG1eLL+/f6ApKF2QaWtTp4810zXV/XCT8Yl06bQzlldeSuinezqw62hrKDVgHTIPGcRm\nPILu3V7mvMh6DcNa8S1VGoQgavUUPC0CtpfMsaamGmuf+I2rIKNSpqhCzcFuEFoQ6dJ5T+fhBUWR\n14CzjUrPYdBU/q5en0kxpiBKuVbwyDhgJxIJlJeX47bbbpORHimcgkwmi0u45bRxRjpR7insNJiH\nnHnNeMUgIJndC5lyWhJS1XXKgxb1vt5mmT6TQX4P0cLU0FDvODo/rO4jO7K+u4rrsmccsF966SWU\nlpbKSEtg6uvrUFtb62pxiWwcrJZO0IN5ws4ERYaiUnCMxepct/yEJazBbW6budNl8KnSqntTulU8\nntmmRkESLUzNzc2OlaO+rjZ8cLAm5JTJpeK2rBkF7Fgshvfeew833HCDrPS4Yq7FZjrViAao0CQv\nizlD8SOo7SBVO8d+m/Zl1URFQTrbyCoEqXa/mLnJR4eNLAykIGWeXhg01VbvyyhgP/zww7jnnnuQ\nl5fn6vXnRoSqU/PJVWGPTA+KU4aQScEs27aDTCVbC7Bh3d9RbrGaK+ymyAWxKIkOfAfsrVu3oqSk\nBDNnznTd9Hjq1KmsyAiDmO4UNruR6WJhkbq6mK8SbDY1SwY1Z1SXzN3tIjOqXnO3My9Umt5ppst9\nEgb7KXLqtj4EyXfA3rdvH9555x0sXrwYq1evxs6dO3HPPfekfd/wgiIUFAwb9LvCwhEwjAS6u9sB\nAEVFI1FUNDL591Gjhg96vfXv4jOKi0ehuHjUee8pLByBoqKRyb8BOC8N4ufCwhGD/rUjMoOeng7b\ndIm0WY9h/R4iXea/Ox1f/Gz9DOsxRDqc/m7+eURhMQoKhiXPe3f3wMIiPT0dg45vPWaqn3s7W5Kf\n5/R6u99Zv3e6Y9p973THML+nqGjkeec41blyYncvm+8BkQa7e8KchlT3m9N9JD7T7j6ye30q1teI\ne8Hp7729nbZptD6Xdq8x/9xpCvhO59t6T9idX7t0jigsHnRei4pG2n4PczAYNWp4Mq8w5xfmtDjd\nV27SZH290/lK9Zl2abB+jlManI7p5jPt7kNzgc2ax9oRxxDnN90zKP4uCtB+nvt0eUe6n+3Ol9e8\nRRbfm3+sWrUKq1atAgDs2rULzz//PB599FFX7+3uPj3o587OXvR1teG1rTUoKpmK9vaeQX/v6uob\n9LP17+IzWlu7AAwEjdraIYP+1t7ek/y7XRoGfi5AZ2fv2RVuUpdlRhQWD0pXT0cTKiqGYOLESY7H\nsH4PkS7z3zs7e5N/s77W7jOsxwAGnx/xvZxeX10dw+93nURRyVR0dvZieEHRoHTYHTPTn+1+Z/3e\n6T7D7nunO4b5Pe3tPeedY/t7InUt0u5etl5TcbxUabCmJdUxurr6YBgJVFScTHlMp5/t2F0PcytD\nuvMvfrZ7Np3e83//dwS7jrYmj+N0Ta33hJfvaj6v7e09tq+3fk9rXmH9PKdzIdLl5t41jBGoqDjp\nuCGGeG7tPtOaBpH3pDqm3blL972sr02Xn6U6b9b3iNelewbT/T3VMZx+drp3nX62O2f2nzmQz1ZU\nnAys1SbUedixWOrRdm6bIevr67J6NHdYo3fF1AvreVe1mZDOkd2PF1UTrOp96EHN841isSTSn5Tt\nNefNm4d58+alfd1z6z9U/gEFzm1pGBWxNVwYx/mg5hQKx00Z9Pu2trZBNR9yZ2D09OBWliCNKCwO\nrQ95IKCPCeVYuUJ2P6x5K1pzAexcfpZ71y/qvFy2UL+JnwCQ6UAdUVvVbTS032DpdUeqYSMLpR4f\n4IAZqzCnoVD2CnuAH+9Z9WRP0cOBGGGYK01P9fX1yu9IZS2E9Xa2oKKiIsIUBSvoaSgqbBuaC851\nVYUzO0Sngp55/XIvoux6U3WGQypZF7DtFmIIq2lXZJxR1eZ7O1vQ2NjIpuw0opiWF+Q0lHg82m0v\no5Ju+UvZS42Kwn9Y01JFQU+n6YBuqLjkpwxhFACyImCLkm/UN0A8HudAEg0EsQtZuoc11d9lDDLM\nxUKa2D0tCIlEP/bv/+i834d9nrNxvrGKS37qIisC9umeDmz9Y1yJG0DFB0zHpp+gqXCd6uvr0NTU\nlDW7f4XRhGtdwSyoABqL1XlqtfDz3cOaDaIi1Zb81IWWAdtu2pEKGTCRmZemzGyoIYslXYMkczqU\n0/URXVteromb724tOGdLQc0LL037Ku2e5kcQFSUtA3Y8Hvd8ozc1qb9loA7zn7OtP43s+b0PZRc8\n7GqhQRfOGxsbfBU8/Hz3bCioqSCoVkTVBv5pGbAB+xtd99GybW2Zl7jj8bik1BBFz0stVGZhkoHU\nH9UrRV6F0WrkhZSFU2TzG3RFyVjnh03ntGcql/v0skFQtZxcfiZkSyQSSgyK7eloQn29HvVF6/0X\n5WIsSgbsTPDh1pdY4W14QVFWrU7kFwcLkmxum/sH1kYIZllW8i9rckXWzjKjyvnLlQJX2Itw6IQF\nlWDlyjMWhaCf66wJ2Lk44lImnj953IylCHsRjlx3bvBQ8AUkDsrMHl4Lj0E/15E3ictselGh5KhK\nTdWPIM7fwGpUudW05nYshQr3axBUrCG31Vfi5ZPtmDcj9QhzHWZqkNqCfK6zpoatCtZUB+vrasMH\nB2uiTkbowgjGKgZGlbm5JjJmalDwcvXeZ8CWwHrzZGvNyS+nHcGilE3zydN9j2z5nmHJpec3Fot+\ndUhyT7mArfvqNkHKpiBDlE2irvHplmdy0KU/ygVsolzW151Zfz8LdaQDDrr0hwFbAzoPZMs1Ogxa\nSlcoyKagny3fIxsF0fWQTfeuHQZsDXAgmz44aIkou2Ta6iVTTgVs1dYZ97L2eS4NhIlapv2RvFZE\nFITI52F7FeU6rrKJXceYwRMRUTpKB+yoR1564bcgwWBNRNlA9bEb2SA7qqpERERZTukadtg4Gtu7\nbOqioNR0avGi4GXzaGxVKZnTRjU1hqOxiUglLCSRmZI17La2Nuw62hpJ/y77lInkYLAhkkvJGjbA\nwCkw0yMiIkDhgE1ERETnMGATEZGSOLBtMAZsIqIswS607KbkoDMiInLH7dRKTlvVHwN2SDhfmUgO\nBh5/BqattnNAr8YYsIk0woLfucBD3jFY6y23n/yIcUAFkT8MPJSLGLCJiIg0wIBNRESkAfZh+8S+\nxPDwXBMRsYZNRESkBQZsIiIiDTBgExERaYABm4iISAMM2EREOcgwEmhsbJT2eYkEV6ALGgM2EVFA\nBmY4qLlAUl9XG17bekza57W1teH3u05K+zw6HwM2EVGOGl5QZFqb3ZDyeRScnAnYbK4hIjrfwNrs\nJ9HS0hp1UiiNnFk4pa2tDbuOtrIE6BEXLSHKfswX9ZBTOTFvSiIi0lVOBWwiIiJdMWATEWlC5gAx\n0g8DNhGRJjhALLcxYBMRaYRjcXIXAzYREZEGGLCJiIg04HsediwWwz333IPGxkbk5+fjhhtuwM03\n3ywzbURERHSW74Cdn5+Pe++9FzNnzkRnZyeuu+46LFiwAKWlpTLTR+Sbqms4ExH54btJfMKECZg5\ncyYAoLCwEKWlpaivr5eWMCIiIjpHSh92dXU1jhw5gssuu0zGxxEREZFFxgG7s7MTK1euxJo1a1BY\nWOjqPQUFw6T+nC3HkHHMTF/v5j0qnjseI/uOYTVq1HDpx8iWc6XiMXkM+TIK2GfOnMHKlStx7bXX\nYsmSJa7f1919WurP2XIMGcfM9PVu3qPiueMxsu8YVl1dfdKPkS3nSsVj8hjyZbRb15o1azB9+nTc\ncsststJDRHQe7hpHlEENe+/evdi0aRN27NiB5cuXo7y8HNu2bZOZNiIiIjrLdw179uzZOHz4sMy0\nEBERkQO2MREREWmAAZuIiEgDDNhEREQaYMAmIiLSAAM2ERGRBhiwiYiINMCATUREpAEGbCIiIg0w\nYBMREWmAAZuIiEgDDNhEREQaYMAmIiLSAAM2ERGRBhiwiYiINMCATUREpAEGbCIiIg0wYBMREWmA\nAZuIiEgDDNhEREQaYMAmIiLSAAM2ERGRBhiwiYiINMCATUREpAEGbCIiIg0wYBMREWmAAZuIiEgD\nDNhEREQaYMAmIiLSAAM2ERGRBhiwiYiINMCATUREpAEGbCIiIg0wYBMREWmAAZuIiEgDDNhEREQa\nYMAmIiLSAAM2ERGRBhiwiYiINMCATUREpAEGbCIiIg0wYBMREWmAAZuIiEgDDNhEREQaYMAmIiLS\nAAM2ERGRBhiwiYiINMCATUREpAEGbCIiIg0wYBMREWmAAZuIiEgDDNhEREQaYMAmIiLSQEYBe9u2\nbfjGN76BsrIyrFu3TlaaiIiIyMJ3wE4kEnjwwQfxy1/+Em+88QY2b96MiooKmWkjIiKis3wH7IMH\nD2LatGn4zGc+g2HDhuHqq6/Gli1bZKaNiIiIzvIdsOvq6jBlypTkz5MmTUJ9fb2URBEREdFgQ/2+\n0TAMz+/p624/+79i0/8z//l0TyeAPMvR9DuGnGOOUO578Rg8hr/PTH0v6/M9oj9Gtn4v9Y9hfV9m\nfAfsyZMno7a2NvlzXV0dJk6cmPI9lR+94fdwREREOc13k/ill16Kqqoq1NTUoK+vD5s3b8bixYtl\npo2IiIjO8l3Dzs/Px9q1a3HrrbfCMAx885vfRGlpqcy0ERER0Vl5hp/OaCIiIgoVVzojIiLSAAM2\nERGRBhiwiYiINBBKwOaa43LEYjHcfPPNuOqqq7Bs2TK89NJLAIDW1lbceuutKCsrw3e/+120t5+b\nD/jQQw9h6dKluPbaa3H48OGokq6dRCKB8vJy3HbbbQCA6upq3HjjjSgrK8OqVatw5swZAEBfXx/u\nuusuLF26FDfddNOgqY6UWnt7O1auXIkrr7wSV199NQ4cOMB7WbIXXngB11xzDZYtW4bVq1ejr6+P\n97IEa9aswVe/+lUsW7Ys+Ts/9+7GjRtRVlaGsrIyvPbaa+kPbASsv7/fWLJkiVFdXW309fUZf/VX\nf2UcP3486MNmpfr6euPQoUOGYRhGR0eHsXTpUuP48ePGo48+aqxbt84wDMN49tlnjccee8wwDMPY\nunWr8f3vf98wDMPYv3+/ccMNN0STcA396le/MlavXm384Ac/MAzDMO68807jt7/9rWEYhnH//fcb\nL7/8smEYhvGf//mfxgMPPGAYhmFs3rzZ+PGPfxxJenX0d3/3d8b69esNwzCM06dPG21tbbyXJYrF\nYsaiRYuM3t5ewzAG7uENGzbwXpZg9+7dxqFDh4xrrrkm+Tuv925LS4uxePFio62tzWhtbU3+P5XA\na9hcc1yeCRMmYObMmQCAwsJClJaWoq6uDlu2bEF5eTkAoLy8PHl+t2zZguXLlwMAvvSlL6G9vR2N\njY3RJF4jsVgM7733Hm644Ybk73bs2IGysjIAA+f4D3/4AwAMOvdlZWX48MMPw0+whjo6OrBnzx5c\nf/31AIChQ4eiqKiI97JkiUQC3d3dOHPmDHp6ejBx4kTs3LmT93KG5syZgzFjxgz6ndd793//93+x\nYMECFBUVYcyYMViwYAHef//9lMcNPGBzzfFgVFdX48iRI/jSl76EpqYmlJSUABgI6s3NzQCA+vp6\nTJ48OfmeSZMmoa6uLpL06uThhx/GPffcg7y8gWUF4/E4iouLMWTIwOMyefLk5Hk0n+P8/HyMGTMG\nLS0t0SRcI9XV1Rg3bhzuvfdelJeXY+3ateju7ua9LNGkSZPwne98BwsXLsTXvvY1FBUV4ZJLLsGY\nMWN4LwegubnZ1b0rzrldbEx3TwcesA1O85aus7MTK1euxJo1a1BYWJgMLFZ2597ptTRg69atKCkp\nwcyZM5PnzzCM886lOI/W3xuGwXPswpkzZ3Do0CF8+9vfxsaNG1FQUIB169bxXpaora0NW7Zswbvv\nvov3338f3d3d2LZt23mv470cLKfz6ueeDjxg+1lznJydOXMGK1euxLXXXoslS5YAAC644IJk82BD\nQwPGjx8PYKDEFovFku+NxWI892ns27cP77zzDhYvXozVq1dj586dePjhh9He3o5EIgFg8Hk0n+P+\n/n50dHSguLg4svTrYvLkyZg8eTIuvfRSAMDSpUtx6NAh3ssSbd++HVOnTsXYsWORn5+PJUuW4KOP\nPkJbWxvv5QB4vXetsdHNPR14wOaa43KtWbMG06dPxy233JL83aJFi7BhwwYAA6MOxfldvHhxcuTh\n/v37MWbMmGSTDdlbtWoVtm7dii1btuDxxx/H/Pnz8fOf/xzz58/H7373OwCDz/GiRYuwceNGAMDv\nfvc7fOUrX4ks7TopKSnBlClTUFlZCWBgjMD06dN5L0t04YUX4sCBA+jt7YVhGNixYwcuvvhi3suS\nWGvIXu/dyy+/HNu3b0d7eztaW1uxfft2XH755SmPGcrSpNu2bcPPfvaz5JrjK1asCPqQWWnv3r34\n67/+a8yYMQN5eXnIy8vDXXfdhcsuuww//vGPcerUKVx44YV48sknkwMi/vEf/xHvv/8+CgoK8Mgj\nj+DP/uzPIv4W+ti1axeef/55/OIXv8Cnn36KVatWoa2tDTNnzsRjjz2GYcOGoa+vD3fffTcOHz6M\nsWPH4vHHH8dFF10UddK1cOTIEfz0pz/FmTNnMHXqVDzyyCPo7+/nvSzRU089hc2bN2Po0KG45JJL\n8NBDDyEWi/FezpBofWtpaUFJSQl+9KMfYcmSJbjzzjs93bsbNmzAL37xC+Tl5eGHP/xhcnCaE64l\nTkREpAGudEZERKQBBmwiIiINMGATERFpgAGbiIhIAwzYREREGmDAJiIi0gADNhERkQYYsImIiDTw\n/wHp1hHKo/eYswAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674b970610>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674c17c950>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674b970110>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "9-CelVUmdz8r"
      },
      "cell_type": "markdown",
      "source": [
        "### Scatter Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "79C7jc9mv-Ji",
        "outputId": "cf0c0e0e-8443-465e-f135-c518d818d486",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "x1 = [2, 3, 4]\n",
        "y1 = [5, 5, 5]\n",
        "\n",
        "x2 = [1, 2, 3, 4, 5]\n",
        "y2 = [2, 3, 2, 3, 4]\n",
        "y3 = [6, 8, 7, 8, 7]\n",
        "\n",
        "# Markers: https://matplotlib.org/api/markers_api.html\n",
        "\n",
        "plt.scatter(x1, y1)\n",
        "plt.scatter(x2, y2, marker='v', color='r')\n",
        "plt.scatter(x2, y3, marker='^', color='m')\n",
        "plt.title('Scatter Plot Example')\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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xifJ6vZo8ebJuv/129e/fP9jjhLxGjRopOTlZH330UbBHCTl///vftXbtWvXr\n109Tp07Vxx9/zPsqzsHj8UiSmjVrpgEDBmjHjh1Bnig0xcXFKS4uTp06dZIkpaamaufOnTVuX2vR\n7dSpk/bv369Dhw7pzJkzWr16tfr161dbuw87nGm7M2PGDF199dW6++67gz1KyCopKVFZWZkkqaKi\nQps2bVLbtm2DPFXoeeihh5Sfn681a9boueeeU48ePTRv3rxgjxWSysvLderUKUnS6dOntWHDBrVr\n1y7IU4Wm2NhYxcfHq6CgQJK0efPmc77Zs9bevRwZGamZM2fqnnvukTFGw4cP512mNfjPWfbx48eV\nkpKiBx54wP8iPP7r008/VV5entq3b6+hQ4fKcRw9+OCD6t27d7BHCynFxcV69NFH5fP55PP5lJaW\npj59+gR7LFzEjh07pkmTJslxHFVXV2vIkCG66aabgj1WyHr88cf18MMPy+v1qnXr1po7d26N2/LZ\nywAAWMInUgEAYAnRBQDAEqILAIAlRBcAAEuILgAAlhBdAAAsIboAAFhCdAEAsOT/AcZ5nJs+bIoi\nAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674ccd7c10>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "nlk-Sk0Nd82p"
      },
      "cell_type": "markdown",
      "source": [
        "### Stack Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "5sxEM0pJzpgr",
        "outputId": "264a9408-1739-46c6-d978-3987c275dabf",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "idxes = [ 1,  2,  3,  4,  5,  6,  7,  8,  9]\n",
        "arr1  = [23, 40, 28, 43,  8, 44, 43, 18, 17]\n",
        "arr2  = [17, 30, 22, 14, 17, 17, 29, 22, 30]\n",
        "arr3  = [15, 31, 18, 22, 18, 19, 13, 32, 39]\n",
        "\n",
        "# Adding legend for stack plots is tricky.\n",
        "plt.plot([], [], color='r', label = 'D 1')\n",
        "plt.plot([], [], color='g', label = 'D 2')\n",
        "plt.plot([], [], color='b', label = 'D 3')\n",
        "\n",
        "plt.stackplot(idxes, arr1, arr2, arr3, colors= ['r', 'g', 'b'])\n",
        "plt.title('Stack Plot Example')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9U1m16i0SEu7/wUZHd2bcuAMKpxOF9eefB9i3zzxOVVqTlJQGLF8+BH//s8yZ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\nccK/9yuNwLO55dzZuR2VlygaXWuCshHzSPpoOOW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66qtZv349V111FW+88YY/6xUiIs0+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\nSUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674d9bfb50>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "C0LOohpqeCjx"
      },
      "cell_type": "markdown",
      "source": [
        "### Pie Charts"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "ZdEG-d4g4U6v",
        "outputId": "51f53730-aa0a-4a10-d5f0-ed4293dc832b",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "labels = 'S1', 'S2', 'S3'\n",
        "sections = [56, 66, 24]\n",
        "colors = ['c', 'g', 'y']\n",
        "\n",
        "plt.pie(sections, labels=labels, colors=colors,\n",
        "        startangle=90,\n",
        "        explode = (0, 0.1, 0),\n",
        "        autopct = '%1.2f%%')\n",
        "\n",
        "plt.axis('equal') # Try commenting this out.\n",
        "plt.title('Pie Chart Example')\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ixYs3/378+HGKFy9+8++KoqhyHXPumjWckWuXQjiN7GyIjX2UMmVWMHz4twVS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\nmCIiIp2gwhQREekEFaaIiEgn/D++fFnOQ+X/4gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674b90b850>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "sX97x87MTyIf"
      },
      "cell_type": "markdown",
      "source": [
        "### fill_between and alpha"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "BCUl8mTMT4sN",
        "outputId": "f52ac738-a80d-4d4a-b112-e3acb9334eed",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "ys = 200 + np.random.randn(100)\n",
        "x = [x for x in range(len(ys))]\n",
        "\n",
        "plt.plot(x, ys, '-')\n",
        "plt.fill_between(x, ys, 195, where=(ys > 195), facecolor='g', alpha=0.6)\n",
        "\n",
        "plt.title(\"Fills and Alpha Example\")\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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frEcJ1qyVSHZu0zSxdu1arF69GhdddBEAYPHixRgbG8OSJUswOjqKRYsWTWsg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EPIgBMEQRBEG0IGnCAIgiDaEDLgBEEQBNGGkAEnCIIgiDaEDDhBEARBtCFkwAmCIAiiDSEDThAE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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674daf8250>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "jONspxyzeT4Y"
      },
      "cell_type": "markdown",
      "source": [
        "### Subplotting using Subplot2grid"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "JF-dVGj3ExQm",
        "outputId": "df00765b-d58a-4ad0-ce52-b1670a86f486",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 401
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "def random_plots():\n",
        "  xs = []\n",
        "  ys = []\n",
        "  \n",
        "  for i in range(20):\n",
        "    x = i\n",
        "    y = np.random.randint(10)\n",
        "    \n",
        "    xs.append(x)\n",
        "    ys.append(y)\n",
        "  \n",
        "  return xs, ys\n",
        "\n",
        "fig = plt.figure()\n",
        "ax1 = plt.subplot2grid((5, 2), (0, 0), rowspan=1, colspan=2)\n",
        "ax2 = plt.subplot2grid((5, 2), (1, 0), rowspan=3, colspan=2)\n",
        "ax3 = plt.subplot2grid((5, 2), (4, 0), rowspan=1, colspan=1)\n",
        "ax4 = plt.subplot2grid((5, 2), (4, 1), rowspan=1, colspan=1)\n",
        "\n",
        "x, y = random_plots()\n",
        "ax1.plot(x, y)\n",
        "\n",
        "x, y = random_plots()\n",
        "ax2.plot(x, y)\n",
        "\n",
        "x, y = random_plots()\n",
        "ax3.plot(x, y)\n",
        "\n",
        "x, y = random_plots()\n",
        "ax4.plot(x, y)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fo7tPi7+XmltWx3LJPPu9eU6FQi7nB9cl4u7qwmenq/jD62f49ZaUGY1IT5ck\nSWQWN/P24VIaWntxVSm4ZfVs1i+OnNbIj62Sy2X8+IZ5dPdlcaawib+9e5a8c21IksTdN81nydwg\nazfR5ETgYibXLp9FenEzx3LrWTwncErD88fzGiiq7iA1PoCFseapwuvs3NRKNl8exwsf5vHm58Xc\nt2nhpO/p7tPy6icFKOQyfmSDc+Cj+Xu78qtbU3jyjXTSi5oI9HHl/i2pF73KTRjLRakgOsRrTJE1\nSZJo7ug3BjKN3VQ2dFHV2E3uuTZyz7WNeb+bWsGmNbGsXxzhNA8ocpmMLevi8HBT8v6Rcp7ccYZf\nbU4hKth8o5fldZ28fbCEwqp25DIZl6eFc+OKGLxsYJmzKbkoFdy7cSF/fCOds6UtqFzk3Ltx4Zhg\n25GIwMVMFHI5P7oukd+9copX9xUSH+lzwdoLfQM63j5YgotSztZ18RZsqfNZOi+YLzJrySxpJquk\nedK6Ozs/K6Kjx7h82B5GLSKCPPjV5mS+zq5nw4pomy0w5WhkMhmBPm4E+riRNupBpbdfR3XTN4GM\nh5sLVy2NwmuSJayOSCaTccOKGDRuLryxv4g/7czg55sWmnx/pZaOft77spRjuQ0ApMQFsGlNrNl3\nzLYmd1clv7w1mQ+PnuOyBaHMDnPc3bpF4GJG4YEe3LxyNu8cLmXH/kLuvnH+hL/7n6/K6egZ5KaV\nMQSIp2OzkslkfPfKBB5/+RQ7Py9iXrTvhE+9Z4ZKmMeEetlVzlFsmDexVtpbRRjL3VVJQqSPRTc/\ntHVr0yJwd1Xy0kf5PLMr02S7LvcN6Nh7rIL9p6rQ6Q3MCvbk1rVxJJpp81Nb4+upZvtVc6zdDLOz\n3TFvB3HVJVHEhnmNlGkeT3VTN5+fNibkXmNHN0d7FjGUqNvU3s8nJyrH/Z3O3kFe21c4knBt7f1g\nBMGRLJsXws9uWQDAc+9mczy3fsZ/S6c3cDC9mof+eYyPj1fg6e7Cj65P5NHvL3aaoMWZiCuxmcnl\nMn54XSIuSjmv7yuks2fssjZjQm4RBkli6xXxTjPfbQtuvCwGb42KvccqaGrvG/OaJEns2FdIV6+W\njatmO/QQsyBYy8LYAH61OQWVi4IXP8zjwJnqab3fWDm6if9+6SQ79hcxqDOwcdVsnrxzGZfOD3Xo\nhGdnJgIXCwj113DL6li6+7S8tq8QSZJGXhve8C0lLsBkexwJU+OmVnLr2ji0OgNvHSge89rJ/EZO\nFzYRF+HNlUsirdRCQXB8CZE+PHhbKp4aFW98VsSer8vHXCMncq6+k6fezOC5d7NpbOtjTWo4f7xr\nOddfGu0Qq4WEiYkcFwu5YnGFrwzQAAAgAElEQVQE6YWNpBc1cSKvgWVJIfQN6Ng1nJB7hUjItYZl\nQ4m6GcXNnC1tZmFsAB3dA+zYX4hKKeeOaxMnLKEvCIJpRAV78vC2NP7yViYfHDHWWdmyLn7cEZPW\nzn7e/aKMY0NTS8mx/my6PI5wMSrqNKY04vKHP/yBzZs3s2XLFs6ePWvuNjkkucw4ZaRykfPGZ0W0\ndQ2MJORet2zWlOuJCKYlk8mMuyPLZOz8rBitTs+rnxbS069j05pYi9SZEAQBgn3deXjbIsIDNHx+\nupqX9+aj0xtGXu8b0PHuF6U8/MJxjuUaayr9ZksKP/9OsghanMykIy4nT56koqKCXbt2UVpayiOP\nPMKuXbss0TaHE+Trzq2Xx7FjfxH/+3425XVdBPq4cs0ykZBrTRGjKur+5a1Miqo7mBvlw9pFEdZu\nmiA4FV9PNQ9+N42/vpPF0Zx6evt1PPyDSziUXs0HX5XT1avF11PNxlWzWT4/ROSwOKlJA5djx45x\nxRVXABAbG0tHRwfd3d14eNh+PQtbtCY1nDOFTeRXGAtS3XaFqJBrC268LMaYb1TdgVql4AfXJoqL\noiBYgYebC7/eksLf38sms6SZ7b/bx8CgHrVKwc2rZnPlkkib2r1ZsLxJA5fm5maSkpJG/u3n50dT\nU9OEgYuvrztKM9+IAwNta5+Y6fr1tsX8+m9fsjAukCuWT2+/HLD//l8Mc/b9J7ck88yb6dx98wLm\nxdtmmWxx7p2Xs/X///vJCv6yM51jZ2u5enk0t101B19Py25saiuc7dxPZtrJuZNle7e19c64MVMR\nGOhJU1OXWY9hbjLgj3ctR6mQTbsvjtD/mTJ33xPCPHnu5ytxUcpt8r+xOPfO2Xdw3v7/8Oo53Hdr\nCj1d/ej6tTT1a63dJItz1nN/oWBt0sAlKCiI5ubmkX83NjYSGDjxvjuWiAydPfp05v47c9/Bufvv\nzH0H5+6/u+vE26U4A2c+9+OZdFXRihUr2LdvHwC5ubkEBQWJ/BZBEARBEKxi0hGXtLQ0kpKS2LJl\nCzKZjMcee8wS7RIEQRAEQTiPTJpKiUJBEARBEAQbIEr+C4IgCIJgN0TgIgiCIAiC3RCBiyAIgiAI\ndkMELoIgCIIg2A2b3R36D3/4A1lZWchkMh555BEWLlw48trRo0d55plnUCgUrFq1invuuceKLTWP\nP//5z5w5cwadTsddd93FlVdeOfLa2rVrCQkJQaEwVih++umnCQ4OtlZTTe7EiRP8/Oc/Jz7euGN2\nQkICjz766Mjrjnz+33nnHfbs2TPy75ycHDIyMkb+nZSURFpa2si/X3nllZHPgT0rKiripz/9Kd//\n/vfZtm0bdXV1PPDAA+j1egIDA3nqqadQqVRj3nOha4S9Ga//Dz/8MDqdDqVSyVNPPTWmftZk3xF7\n8u2+P/TQQ+Tm5uLj4wPAHXfcwZo1a8a8x5HP/X333Udbm3FLmPb2dlJSUnjiiSdGfv+9997j2Wef\nJSrKuMfdpZdeyk9+8hOrtN1qJBt04sQJ6c4775QkSZJKSkqkW2+9dczr11xzjVRbWyvp9Xpp69at\nUnFxsTWaaTbHjh2TfvSjH0mSJEmtra3S6tWrx7x++eWXS93d3VZomWUcP35c+tnPfjbh645+/oed\nOHFCevzxx8f87JJLLrFSa8ynp6dH2rZtm/Tb3/5Wev311yVJkqSHHnpI+vjjjyVJkqS//OUv0htv\nvDHmPZNdI+zJeP1/4IEHpL1790qSJEk7duyQ/vSnP415z2TfEXsxXt8ffPBB6eDBgxO+x9HP/WgP\nPfSQlJWVNeZn7777rvTHP/7RUk20STY5VTTRxo4AVVVVeHt7ExoailwuZ/Xq1Rw7dsyazTW5JUuW\n8OyzzwLg5eVFX18fer3eyq2yDc5w/oc9//zz/PSnP7V2M8xOpVLx4osvEhT0zf5QJ06cYN26dQBc\nfvnl553jC10j7M14/X/ssce46qqrAPD19aW9vd1azTOr8fo+GUc/98PKysro6uqy69Ekc7HJwKW5\nuRlfX9+Rfw9v7AjQ1NSEn5/fuK85CoVCgbu7OwC7d+9m1apV500HPPbYY2zdupWnn3560v2j7FFJ\nSQl33303W7du5euvvx75uTOcf4CzZ88SGhp63vYag4OD3H///WzZsoV///vfVmqdaSmVSlxdx26e\n19fXNzI15O/vf945vtA1wt6M1393d3cUCgV6vZ6dO3dyww03nPe+ib4j9mS8vgPs2LGD7du388tf\n/pLW1tYxrzn6uR/22muvsW3btnFfO3nyJHfccQe33347eXl55myiTbLZHJfRHPHGPBWff/45u3fv\n5uWXXx7z8/vuu4+VK1fi7e3NPffcw759+7j66qut1ErTi46O5t577+Waa66hqqqK7du3s3///vNy\nHBzZ7t27ufnmm8/7+QMPPMCGDRuQyWRs27aNxYsXs2DBAiu00HKm8v13xGuEXq/ngQceYNmyZSxf\nvnzMa478Hbnxxhvx8fEhMTGRF154gb///e/893//94S/74jnfnBwkDNnzvD444+f91pycjJ+fn6s\nWbOGjIwMHnzwQT788EPLN9KKbHLE5UIbO377tYaGhmkNM9qLI0eO8I9//IMXX3wRT8+xG2zddNNN\n+Pv7o1QqWbVqFUVFRVZqpXkEBwdz7bXXIpPJiIqKIiAggIaGBsB5zv+JEydITU097+dbt25Fo9Hg\n7u7OsmXLHO7cD3N3d6e/vx8Y/xxPd/NXe/Twww8za9Ys7r333vNeu9B3xN4tX76cxMREwLgQ4duf\ncWc496dOnZpwiig2NnYkWTk1NZXW1lanSyWwycDlQhs7RkRE0N3dTXV1NTqdjkOHDrFixQprNtfk\nurq6+POf/8w///nPkcz60a/dcccdDA4OAsYP+PDKAkexZ88eXnrpJcA4NdTS0jKyasoZzn9DQwMa\njea8p+eysjLuv/9+JElCp9ORnp7ucOd+2KWXXjpyDdi/fz8rV64c87qjb/66Z88eXFxcuO+++yZ8\nfaLviL372c9+RlVVFWAM4L/9GXf0cw+QnZ3N3Llzx33txRdf5KOPPgKMK5L8/PwcYmXhdNjsXkVP\nP/00p0+fHtnYMS8vD09PT9avX8+pU6d4+umnAbjyyiu54447rNxa09q1axfPPfccMTExIz9bunQp\nc+bMYf369bz66qt88MEHqNVq5s2bx6OPPopMJrNii02ru7ubX//613R2dqLVarn33ntpaWlxmvOf\nk5PDX//6V/71r38B8MILL7BkyRJSU1N56qmnOH78OHK5nLVr1zrEMsicnBz+9Kc/UVNTg1KpJDg4\nmKeffpqHHnqIgYEBwsLCePLJJ3FxceGXv/wlTz75JK6uruddIya60Nu68frf0tKCWq0euSHHxsby\n+OOPj/Rfp9Od9x1ZvXq1lXsyfeP1fdu2bbzwwgu4ubnh7u7Ok08+ib+/v9Oc++eee47nnnuORYsW\nce2114787k9+8hP+7//+j/r6en7zm9+MPMDY+3LwmbDZwEUQBEEQBOHbbHKqSBAEQRAEYTwicBEE\nQRAEwW6IwEUQBEEQBLshAhdBEARBEOyGCFwEQRAEQbAbInARBEEQBMFuiMBFEARBEAS7IQIXQRAE\nQRDshghcBEEQBEGwGyJwEQRBEATBbojARRAEQRAEuyECF0EQBEEQ7IYIXARBEARBsBtKU//BpqYu\nU//JMXx93Wlr6zXrMWyZM/ffmfsOzt1/Z+47OHf/nbnv4Lz9Dwz0nPA1uxtxUSoV1m6CVTlz/525\n7+Dc/XfmvoNz99+Z+w6i/+Oxu8BFEARBEATnJQIXQRAEQRDshghcBEEQBEGwGyJwEQRBEATBbojA\nRRAEQRAEuyECF0EQBEEQ7IbJ67gItqOpvY8zhU1IkmTW48jlMhbPCcLf29Wsx3EUxdXtqF0URAVP\nXKdAEARBGJ8IXBzYK58UkF/RZpFjfXT0HHffOJ+kGD+LHM9eaXUGntmVhatKwVM/vRSlQgx6CoIg\nTIcIXBxUTXMP+RVtxIZ7ccOl0WY9Vm1zL+9+Ucozb2eyaXUsVy+NQiaTmfWY9qqstoMBrZ4BrZ4z\nhU0snRds7SYJgiDYFRG4OKhD6dUAXH1JFAtjA8x6rIWxEBfhzf++n807h0spr+/ih9fOxVUlPl7f\nVljZPvL/D6ZXi8BFEARhmsQ4tQPqG9DxdU49vp5qUuLNG7QMiwv35rHvLyE+wpvTBY38/rUzNDjh\n/hqTKahsQwbEhnlRXN1BZYN59/YSBEFwNCJwcUBHc+oZGNSzJjUchdxyp9jbQ81vtqayLi2CmuYe\n/t8rp8kqabbY8W2dVqenpKaTiCAPrhuavjuYXmPdRgmCINgZEbg4GEmSOJhejVIhY3VymMWPr1TI\n+e6VCdxxXSJanYG/7T7Lnq/KMZh5ZZM9KK3pRKc3MDfKl4Wz/QnwduV4bj09/VprN00QBMFuiMDF\nwRRUtFHX0sviuUF4aVRWa8eKBaE88r00/LzUfPBVOX9/N5vefp3V2mMLCiqNK7zmRvkgl8u4PC2c\nQZ2Br8/WWbllgiAI9kMELg7mwNDUw7q0CCu3BKJDvHj0+0tInOVLZkkzT7x2mtrmHms3y2oKK9uR\nAQlRPgCsXBiGi1LOwfQaMSIlCIIwRSJwcSAtHf1kFDcxK9iT2WFe1m4OAF7uKn61OZmrL4miobWX\nJ147zZnCRms3y+IGtXpKazuIDPZA4+oCgIebC0sTg2ls7yO3vNXKLRQEQbAPInBxIIcza5AkWLso\n3KbqqCjkcm5dG8ddG5KQJInn38/h3S9KMRicZ5ShtLYTnV5ibpTvmJ+vW2QcGTtwptoazRIEQbA7\nInBxEFqdgS+zatG4KlmaaJu1QZbOC+a/vreYQB9X9h6r4K+7s+juc47E1IKK4fyWsYHLrBBPYsO8\nyC5tobG9zxpNEwRBsCsicHEQpwsa6erVsjI5DJWLwtrNmVBkkAeP3r6E+bP9yClr5YlXT1HV2G3t\nZpldYWUbMhkkRHqf99ratAgk4LBYGi0IgjApEbg4iIPp1ciAy1PDrd2USXm4ufCLTclcf+ksmtr7\n+f3rpzmR12DtZpnNgFZPaW0nUcGeuA/lt4y2eG4Qnu4uHDlby6BWb4UWCoIg2A8RuDiAc/WdlNZ2\nsjDWn0AfN2s3Z0rkchkbV8Vyz80LkMtk/HNPLm8dKEZvMFi7aSZXWtOB3iAxd2g10be5KOWsSg6j\np1/HiXzHDeAEQRBMQQQuDuDgGeMUw9pF1l8CPV2L5gTy2+2LCfFzZ/+pKp7ZlUVn76C1m2VS39Rv\n8Z3wdy5PDUcmM55LSSyNFgRBmJAIXOxcd5+WE/kNBPm6kRTjZ+3mzEhYgIZHb19ManwA+RVtPPHK\nKc7Vd1q7WSZTUNmOTAbxEeOPuAD4ebmSGh9IRUMXZbWO03dBEARTE4GLnTtythatzsDa1HDkNrQE\nerrc1Eru2biAm1fG0No5wB9eT+crB6goOzCop7y2k+gQT9xdL7xb9ro0Y37SgXSxNFoQBGEikwYu\nPT093HvvvXzve99jy5YtHDlyxBLtEqbAYJA4lF6DSilnxcJQazfnosllMm5YEcPPv7MQF6Wclz/O\nZ8f+QnR6+817KRnKb5lzgWmiYXNn+RLq787pgkY6ehxrukwQBMFUJg1c3n//fWJiYnj99dd59tln\n+f3vf2+JdglTcLasheaOfpYlhYxUY3UEC2MD+O/vLyY8UMPB9BqeejODju4BazdrRqaS3zJMJpOx\nNi0CnV7iy6xaczdNEATBLk0auPj6+tLe3g5AZ2cnvr6TX4DtmU5voKbJPuqKHByaUlibZvtLoKcr\n2Ned//reIpbMDaK4uoPHXzlFQYX9lcUvqGxDLpMRH3F+/ZbxXDo/BLVKweGMGodcYSUItqixvY8B\nUYrAbkwauFx33XXU1tayfv16tm3bxoMPPmiJdlnNgTPVPPrSSY7m2HZ+RUNrLzllrcRHeBMV7Gnt\n5piFq0rJ3Tcm8Z3LY+nsGeR3Lx5Hq7Ofi0v/oI5zdV1Eh3ripr5wfsswN7WSFfNDaOsaILO42cwt\nFAShtbOf3754gve+KLN2U4QpmvRq+p///IewsDBeeuklCgoKeOSRR3jvvfcm/H1fX3eUSvNWbg0M\nNN+NuqDKOLq062Apa5bMwttDbbZjzVRgoCf/OVoBwE1r4sz638MWbL9+PloDfPBFKbXtAyy20S0N\nvi29oBG9QSJ1TtC0ztEt6xI4mF7Dkex6rr4sdsxrjn6uL8SZ+w7O3X+zXvOrO9HpDVQ1ddvsf2Nb\nbZe1TBq4pKenc9lllwEwd+5cGhsb0ev1KBTjBydtbb2mbeG3BAZ60tTUZZa/rdUZyC9vRS6T0dU7\nyP++k8mPrp9nlmPNVGCgJ9U17ew/UYG3RkV8qPn+e9iSxEhvPgAOnapgVoC7tZszJcezjfV1ZgVq\npnWO3BQy5kb5cLakmaz8esICNIB5P/u2zpn7Ds7df3P3PavIWPSxsr6LxsZOm9qgFpz33F8oWJt0\nqmjWrFlkZWUBUFNTg0ajmTBosXfldZ0M6gysTgljVrAnR3PqyTtne3kVx/Pq6RvQsTolDKXCOVa0\nx4Z74+OpJqO42W52lS6sbEchlxE3xfyW0YZ3jT4olkYLglmVD9VN6h3Q0dnrHJu+2rtJ73qbN2+m\npqaGbdu2cf/99/P4449boFnWMbwCZF60L9+/Zi4yGby2r9Cm9o+RJIkDZ2pQyGWsTnG8pNyJyGUy\nliaF0NWrpaSmw9rNmVTfwDf5La6qqeW3jJYSH4Cvp5qvc4xBqiAIpqc3GDjX8M1oRn1LjxVbI0zV\npIGLRqPh2WefZceOHbz11lssX77cEu2yisJKY37LnChfZoV4sn5xJI1tfXx07JxV2zVaXnkr1U3d\npCYE4utpe/k35rRsvrFWTXpRk5VbMrni6g4MkjSlZdDjUcjlrEkNZ2BQz9GcehO3ThAEgLrmXga1\nBlxVxlmE2hbzpjoIpuEc8wxToNUZKKnpICLQAw83Y02Um1bG4O+l5pPjlVTbyBLpvV+XA99UWXUm\nyfEBuKoUZBQ32fx+PoXTqN8ykVXJYSjkMg6mV9t8fwXBHpXVGaeJFs8NAqBOjLjYBRG4DCmr7UCr\nMzB31jf7ybiqlGy7cg56g8RrnxZisPLNo717gKNnawkP1JAQOfG+N47KRalgYaw/Te39VDfZ9gWm\noLLNmN8SPv38lmHeGhVLEoOoa+mloKLNhK0TBAGMeY0AlyaFAFAvRlzsgghchhQMTRN9+wk5OS6A\nxXODKKnp4ItM61Yz/TKzFr1BYl1ahM1lvltKWkIgYNvTRX0DOs7VdxET5oVadXGJ7GvThpN0a0zR\nNEEQRimv7cRFKScuwhtvDxV1InCxCyJwGVJY2YYMxh3JuO2KeNzUSnYfLqXdSqXndXoDhzJrcHdV\nsizJPuqYmMOC2f4oFTIybDhwKapqR5JgbtTFj4rFhnkxK9iT9OImmtr6TNA6QRAABrV6qpt6iAr2\nQKmQE+avoaWzn4FB21mMIYxPBC6AVqenpKaTyKBv8ltG8/FQ8501sfQN6Nj5ebEVWggZxc10dA+y\nbknUjFapOAo3tZLEWX5UNnbT1G6bN/LCCUbvZsK4f1E4kgSfHj930X9PEASjyoZuDJJETKgXACH+\nxvpQ9a1i1MXWicAFKK0xVk680A6+q1LCiIvw5nRBI5klli/FfuCMsZ7HtZdGW/zYtiYtIQAwBnO2\nKH8ovyX2IvJbRrtkXjAaVyX7jp9DqxP7FwmCKQwn5s4eClxC/YyBS12rbefPCSJwAUbt4Dtr4qF9\nuUzG7VfNQSGX8cb+QvoHLVdbo7qxm6KqdpKifYkIEqWfU+IDkWGbeS69/VoqG7qIDfNC7WKaQo1q\nFwUrF4bR0T3I6cJGk/xNQXB2w4m5wyMuoUMVquuaxYiLrROBC8bE3InyW0YLD/TgmmVRtHQO8MGR\ncss0jlG7QA9VU3V23hoVsRHeFFe309k7aO3mjFFU1YEkccHRu5lYkxaOTCYq6QqCqZTXdeKuVhLk\n6waMHnERgYutc/rAZVCrp6y2g6hgTzSu5+e3fNv1y6MJ8nXjs9NVnKvvNHv7evu1HM2tx9/LleTY\nALMfz16kxQciSZBlY9NF34zemTZwCfJxY9HcYEprOqmod759SwTBlLr7tDS29RET5jWyQtPXU41a\npRDVc+2A0wcupTUd6PQSc6a4AkTlomD7VXOQJHj1k0L0BvPmHHydXc+g1sDlaeHI5c65BHo8w3ku\ntjZdVFDZhlIhIzbMy+R/+7oVMQAcEKMugnBRzn1rmgiMifChfu7Ut/bZzX5ozsrpA5f84RUg03hC\nnhftx4r5IVQ0dPH5afPdRAySxMGMGpQKOSsXhprtOPYoyNediEANuefaLJpvdCE9/VqqGrqJDfNG\nZaL8ltHS5gQR5OPGibwGuvvEZnCCMFPf5LeMzRkM9XdHpzfQ3GGbKxYFI6cPXAor25DJICFiejU3\nbl0bh4ebC+8fKTPbhzzvXCsNrb0sTQzC011llmPYs9T4QHR6AzlltrGDd1FlOxJMefRuuuRyGZen\nhaPVGfjqbJ1ZjiEIzqC8zjjdOnrEBSDEfyhBVxSis2lOHbgMaPWU1XYyK9gTd9fp1UbxdFexeW0c\ng1oDO/YXmWUvmYNnjNVSRVLu+Eaq6BbbxnTRcPXlRBPnt4x22cJQVEo5B9OrxXC2IMyAJEmU1XXi\n56XGx2PsRrUjCboicLFpTh24lNR0oDfMfAffS+eHkDjLl7OlLZwuNO3Ns7m9j6ySZmJCvc57KhCM\nooI98PdyJaukBZ3e+vVNjPktcmabIb9lmMbVhWVJwTR39JNd1mK249gSSZLQiyBNMJHWzgE6ewbH\nva6OLIkWCbo2zakDl+GN6y5Uv+VCZDIZ26+ag1IhZ+dnRfT2my7v4FBmDRKw1gl3gZ4qmUxGakIA\nfQO6kdU81tLdp6W6sZu4cC9clKbPbxlteP8iZ0nSfedQKT/4f/tEXo9gEt+u3zJakI8bcplMLIm2\ncU4duBRWtiOXyYifZn7LaMF+7tywIpqOnkF2Hy41Sbu0Oj1HsurwcHPhksQgk/xNR5UWb5wuyiiy\n7rLowqH8FlOU+Z9MVLAncRHe5JS10tDm2BdYvcHAV9l1tHUNcOSsdTc5FRzDhQIXF6WcQB9XsUu0\njXPawGVgUE95XSezQjxxU1/c3j/XLI0iPEDD4cxaiqvbL7ptJ/Mb6e7Tsio5zOxP7/YuPtIbDzcX\n0oubMJghz2iqCodGfMyVmPttwyNxhxx81+jiqo6RkZZD6TUir0e4aOV1nciA6JDxq5CH+mvo7tPa\nXHFL4RtOG7gU17QP5bdc/I1GqZBz+9VzAXj108KLzrc4mF6NTAZrUsMuum2OTiGXkxIXQEf34MiT\nlDUUVLbhopQzO8w0+xNNZvGcILw0Kr46W8eA1nF3sx1OvI4M9qC5o5+zTpLXI5iHwSBxrr6LEH/3\nCR9YQ4c3WxSjLjbLaQOXwhnUb7mQuAhv1qSGU9vcwycnKmf8d8pqOymv6yIlLoAAbzeTtM3RpVq5\nGF1X7yDVTT3EhXvjorTMV0qpkLM6OYzeAR0n8hosckxLkySJjKIm3NRKfrk1DRBbHggXp661l/5B\n/cjGiuMZ3iVaJOjaLqcNXAoq2pDLZMSZaAdfgE2rZ+OtUfHh1+domGFy18i+RGliCfRUJUX7oXKR\nk17UbJZl6ZMpqhoKgi00TTRsTWo4cpmMA2eqrdJvc6ts6Kalc4DkWH/iI32JH87rEYmTwgyV1w7l\nt1xg5V+YqOVi85wycOkf1FFe10VM6MXnt4zm7urCbesT0OkNvLavcNo3k87eQU7mNxDi505itPmT\nPB2FykXBghh/Glp7rXKxKagwBi6m3lhxMr6eatISAqhq7KakpsOix7aE4RG04Xo9w8H8oQzHzusR\nzOdCibnDvhlxEYGLrXLKwKW4ugODJJnlRrN4TiDJsf7kV7RxNKd+Wu89klWLTi8Z9yWSiX2JpmOk\nGJ0VposKqtpQKc1bv2Ui64aKEx4443hTKOnFTSgVcubP9gNg0ZzAb/J6Bh03r0cwn/K6TpQKGZFB\nHhP+jsbVBS+NSkwV2TCnDFy+2cHX9EP7MpmMbVfOQe2iYNfBErqmmJluMEgczqhB7aJgxXyxL9F0\nLYzzRyGXkWHhKrqdvYPUNPUQF+GNUmH5r1NCpA/hARrOFDbR3j1g8eObS0NbLzVNPSRF++KqMo6K\nKhVy1qQY83qO503voUAQtDo9VY3dRAZ5TvpdDfVzp6Wjn0EHTny3Z84ZuFS0o5CbNr9lNH9vV25e\nGUN3n5ZdB0um9J6skmZaOgdYPj9k2tsPCManpDlRPpTXddHa2W+x4xYNJ3lbeJpomEwmY+2iCPQG\niS8zHafOyXBdnuGRtGGrU4yjkQfTaxwyr0cwn8rGbvQG6YKJucNCAzRIQL3Ip7JJThe49A3oqKjv\nIibUa+RJzhzWLY5gVrAnR3PqyTs3+SaAB0aSckWl3JkavsllFFuuGF3+8OidlQIXgOVJwbipFRzO\nrLGJrQ9MIb2oCZkMkuMDxvzc11NN2pxAqhq7Ka52vLwewXy+Scwdv37LaMN7FonAxTY5XeBSXN0+\nlN9i3hUgCrmc718zF5kMXttXeMEhx7qWHvLOtTEn0oeIwInnXoULS423fJ5LYWU7Khc50aGTXwzN\nxVWl5NL5obR3D1o0aDOXju4BSms6iI/wwWucXdHXDQX3Ymm0MB0T7Qg9nlCRoGvTnC5wKTBx/ZYL\nmRXiyfrFkTS29fHh0XMT/t7Boeqn68Qu0BfF11NNTKgXhZXtFtnXpqNnkNrmHuIjfKyS3zLa8Ejd\nQQdI0s0oaUYC0r412jIsIdKH8EDHy+sRzKu8rhM3tYLgodGUCwn1F5st2jLnC1wq2oz5LRaqcHrT\nyhj8vdR8eqKS6qbu80darYAAACAASURBVF7vG9BxNKcOHw8VKRNcqIWpS0sIwCBJnC01/8hD4cg0\nkWXrt4wn1F/DvGhfCqvax/2c2ZOJ8luGyWQy1qY5Xl6PYD69/VrqW3uJDvGa0opNXy81Khe5GHGx\nUU4VuPT266ho6CImzAu1yjJ7ALmqlGy7cg56g8Rrnxaet5/O8dx6+gb0rEkNt/pTuyP4Zlm0+QOX\nAisn5n7buqE6JwfteP+ivgEd+RWtRAV5EOAzceXo4byeQw6U1yOYz7l64zTRVEsWyGUyQvzcqW/t\nteoeaML4nOpOWVTdjiRZ/kaTHBfA4rlBlNR08MWoJ0RJkjiYXoNCLmN1stiXyBRC/TWE+ruTU9Zi\n9j18CivbUKsUzJpgszZLS44LwN9LzbGcenr7ddZuzoycLW1Bp5dInWC0ZZirSsmK+aF0OEhej2Be\nw4XnokOmXmspzF+DVmegtcNyqxSFqXGqwMWaQ/u3XRGPm1rJ7sMltHUZ5+WLqtqpae5h8dwgvD3U\nFm+To0qND2RQZyCvfPLVXDPV3j1AXUsv8Vaq3zIeuVzGmtRwBrR6vs6ps3ZzZmS4Ds9E00SjXT6U\n1+OIxfcE0yobWlE0nSKRwxV0a8V0kc2Z0hV3z549bNiwgY0bN3L48GEzN8l8CiraUSpkxJqpfsuF\n+Hio2bQmlr4BPW9+XgR8c8EVS6BNyxJVdIc36Uy0kWmiYSuTw1AqjHVO7G2IW6szcLa0hQBvVyIC\nNZP+fqi/hqRoX4qq2qlutO+8HsG8yus68fFQ4es59QfE4QTdepGga3MmDVza2tp4/vnn2blzJ//4\nxz84cOCAJdplcr39Wiobupgd6oXaxTL5Ld+2OiWMuHBvThc2cTijhvSiZqKCPMxWCM9ZRYd64uOh\nIrOkGb3BPPkPw9WXLb0/0WS83FVckhhMQ2sv+efarN2cacmvaKN/UE9aQiCyKW55sXYkr0eMugjj\na+saoL17cErLoEcbruVSJ2q52JxJA5djx46xfPlyPDw8CAoK4oknnrBEu0yuqKoDCcssg56IXCbj\n9qvnoJDLeG2fMVF37aKIKV+khamRy2SkJgTS06+jqMo8RcoKKttxVSmYFWJ7dXfs9Wb+7U0Vp2Ik\nrye3wW7zegTzmsrGiuMJ9nNDJhO1XGzRpIFLdXU1/f393H333dx2220cO3bMEu0yOVt5Qg4P9OCa\nZVEAuKuVLJ0XbNX2OCpzThe1dQ3Q0NpLQqQPCrlt5LeMNjvMi5hQTzJLmmnu6LN2c6bEYJDILG7C\n091lWiOQ9pbX88ZnRby0N8/azXAqI4HLNDdBdVEqCPR2E7VcbNCUat63t7fz97//ndraWrZv386h\nQ4cmHCXw9XVHqTTvVExg4PRXcZTUduKilLMsORyVlaaKhv1gwwKaOwdInRNERNj0E4Vn0n9HMdW+\nX+an4R//ySWrtIWfb/Uw6ahW7tAozqLEEIufi6ke78bVcfz1rQxOFjZz+3XzzNyqi5dX3kJnr5Yr\nl84iOHj8G8xEfb95bQJ7vj7Hl1m1bLkqEbncNkcwj+fUjeS13XVLMr6ertN6v/jez0x1szHwWDw/\nDA83l2m9NyrUi9P5Dajd1Xhpzq/ibCnOfO7HM2ng4u/vT2pqKkqlkqioKDQaDa2trfj7+4/7+21t\n5h1WCwz0pKmpa1rv6e7TUl7TQUKkDx3ttjHsd+f1xpvJdPsyk/47iun2feFsP47lNnA6p3ZayyAn\ncyrHuKQ9wt/NoudiOv1PjPDCw82FT4+dY31aGC5mfpi4WAdPVgCQGOk9bh8n6/uSuUEczanny9OV\nJMX4ma2dM9U3oON/d2eN/PtoRjWXJE59tFV872fWd4MkUVTZTrCfO33d/fR1T29pc8BQMm9uUSNx\nEdbJRXTWc3+hYG3Sce7LLruM48ePYzAYaGtro7e3F19f20pInExxVbvV81sEy/tm7yLT1vkoqGzH\nTa1gVrDtPgW5KBWsTA6lu0/LyfxGazfngiRJIqOoGbVKwbzomX1Hh7fLsNWl0e99WUZb1wALY40P\nfMPFCwXzamjtpW9Ax+wZ7iX2zZJoMV1kSyYNXIKDg7nqqqu49dZb+fGPf8xvf/tb5DY4r38h+TZU\nml2wnAWz/XFRyskwYZ5La2c/jW19JET42OyUxLDLU8KRYftJujVNPTS297Fwtv+MR4ZiQo15PVml\nzTS321ZeT1ltJwfPVBPi585PbpyPWqWgoMK+VnzZq5km5g4b3myxXiTo2pQpRSBbtmxh9+7d7N69\nm3Xr1pm7TSZXWNmOi1I+reJDgv1TqxQkRftR09xDg4mWNBZacJPOixXg40ZyXADldV0jF3BbNJxA\nnZpwcXt1rU2LQJLgUKbtbHmg0xt49dMCJOD2q+f8/+zdd1yb57k//s+jCWJogEBiGrONzfKMHRsb\nx3biNruZdZL2pKcro+0rbZqeb9Pk922bnIzTX9Ocnuw2adI2OXHSxJl2vB2DsQ0YDDYbsxESCIRA\naD7fP4RkbDMEaOt6/2XQuh8/Qrqe+76u64ZQwEVWkgT9Q+O0QaQXOHeEXuBnP2226J8Ca+pkAfQG\nM7oG9EhPiPb7dX7ifo4vw6pm98y6NDhn7/w/cAGA0pX+v2t0VbMaXA6D/KWLC1zW5MYhMpyPYzV9\nMFs8u92Dq7463YWuAT2uzlc6KxpzUu0zv420XORx7X06cDkMUuIW1rYgMpyPKBGfSqL9TNAHLoF0\nhUzcrzAjFgzjvrLohk4tREIekhf4Qehty5bIEC8ToeL8AEbHTb4ezhU0wwZ0qvTITZVCFOZSkeOM\n/C2vRz1swMfH2hEl4uP2LRnO3zuCXkcQTDzDYrWhUzWKpLjIRV20KmUiqEcMfhMMkxAIXALtCpm4\nV5RIgKwkCdp6dIuemh8cmYB6eAJZyf6f3+LAYRiUFiXCYrXhWK3/9TlxbJA4n6Zzs9lSmAiG8X1e\nD8uyeHtvI0wWG+7cmnlJGW5KfCTChVxK0PWwrgE9LFYWSxeY3+KgiIkAywIqrX/lToWyoA9cGju1\nEPA4C07OIoGvOEsOFsCZRe4i7AyCA2z2bsMKBYR8Lg5V9cBm86/9i6qa1GAAFGUubpnIIVYSjoJ0\ne16PY2M9X6g4r0Jd+xDy0mRYd1mTSS6Hg8wkCVRD484NV4n7XVhkYq5DAiXo+p2gDlx04yZ0q8eQ\nnigGnxfUh0pm4cxzWeRykXPZMcCq00RhfFyVF49B3QRqWt1bGr4YunETmrqHsTQx2q27oztKo301\n66I3mPHu/mYIeBzcsyN72uaHjhngRlou8pg2Z+CyuLYFiskEXSqJ9h9B/W3eRPktBECsOBwp8ZE4\n36Fd1H42DZ1aRITxkBQg+S1TOfcv8qMk3ZoWDVjWfctEDrlLpIiXiXDyvAo6H+T17D7cAt24GTdc\nnYY4Sfi093Ek6FKei+e0941CKOA6K4MWikqi/U9QBy4N1L+FTCrOksNqY1HbtrAZB82wAZqRyfyW\nANwUMykuElnJEtRf0PpNaWf1ZGPA4kz3Bi4chkFpcSIsVhbHanrd+txzaezU4mhNH5Lkkdi+OnnG\n+6XERSFcyKM8Fw8xGC3o04whTRG16Hy0GHEY+DwOVRb5kaAOXBo7hyHgU34LufjlWL3ALroNzmWi\nwJ29cyyhHKryfZ+TCZMFde1DSIyNQLxM5Pbn37BcCSGfi8PV3svrMVtseOvLRjAA7rsuGzzuzB+v\nHA6D7GQJBrQGDOnm14aezK2jfxQsgCVu+OznMAwUMhH6hsZgY/0rRyxUBW3gohszoUczhsxE8awf\nICQ0JMojECcJR23b4ILKGhsDNDF3qqLMWEgiBThe14cJ08KXzNyhrm0IFqsNRW5eJnIQhfFw1XIF\nBnVG1LR4J6/n8xMd6B8aR2lxEtIT5t7XJjuF+rl4iqPh4mIrihyUMSKYzDZodZRM7Q+C9hu9sYvy\nW8hFDMOgKCsWRpMV5y7ML6+AZVk0dGoRGc5Honxx6+W+xONysLkwEQajFeX1Kp+OxdEQsHiR3XJn\nU1o82XzPC0m6fYNj+Kz8AqRRQtxSstSlxzhm785TnovbtbmposjB2UF3yD+WWUNd0AYujr1AsgN4\nap+4lyMJtHqeXXQ1IxMY1BmRHaD5LVNtKkwAl8PgYFU3WB9Ne1usNtS0DEIWLfToRpVJcu/k9bAs\ni7992QiLlcXd12QhXOhaI73kuEiIhDyqLPKAC306REcIIIt2T7WaI0GX8lz8Q/AGLp1aCPlcLFH4\n7w6+xLvSE8SIjhCgulkzr7yHi0Fw4Cd5SyKFWJktR496DE1dvlmiaOwchsFoQVGmfNpSYXfyRl7P\n17V9aOwaRlFmLFZmu770xeEwyE6RQD08gcERynNxlxG9EYM6I9IUUW57fylkFLj4k6AMXEbGTOgb\nHEdmEuW3kIs4HAaFGbEYHTejpWfE5cc1BFlZvaM0+oCPknQvLhN5Jr9lKk/n9ejGTPjfQy0QCrj4\n9raseT8+m9r/u91iN1acjkImAgOg308q8kJdUH6rO6Zeg+EKmbiX48vS1WZ0U/NbEmIDN79lqswk\nMZLkkahqVHu9c6uNZVHdpEZEGA9ZyXMnsC6Wp/N63j3QjLEJC27dtBSy6LB5P97RqoECF/dpc3Ni\nLgAI+FzEiMNoxsVPBGXgEmxXyMR9clOlCBNwUdWkdinHQz1sgHbUiJyUwM9vcWAYBltXJsLGsjhy\nxruzLu19OgzrTSjMiAWX452PH2deT6V783rq2gZx4pwKacpo5yzWfCXFRSIijEeVRW7kaPXvjlLo\nqZQxERgZM2F8wuzW5yXzF5yBS4cWQgHXo4l/JDDxeRzkp8dAMzKBbvXc076OIDjYkrzXLVMgXMjD\n4TO9sFhtXntdZ9M5LywTOTjzejTuy+sxmq34295GcBgG912bveAmZxyGQXaKFJqRCWiGaRO/xWJZ\nFu19OsRJwi/Z2NIdKEHXfwRd4DKsN6J/aBxZSRLKbyHTms9yUaBurDgXoYCLjflK6MZMqGxc3B5O\n81HVpIaAx8GyNJnXXhOYktfjpi0P9hxvh2ZkAtvXJCNlkRdI2c7lIpp1WayBYQPGJixuzW9xoMDF\nfwTdNzu1+SdzWbE0Bjwug+o5AheWZdHQoUW0iO/cITaYbCmy9zk54KXNCPsGx9A/NI7lS2Mg5HO9\n8poOmUliJMdFoqpJs+i8nq4BPfZWdCFWHIYbN6Qtemy5lKDrNu1u7t8ylbOXCyXo+lzQBS6NlN9C\n5hAu5CE3VYbOAT3Us0zPD2gNGNabkJ0i9XjZri/Ey0RYvlSGlu4RdKpGPf56jhkuTzadmwkzuX+R\njWVxuHrheT02G4s3v2iAjWVx745sCAWLD8AS5BGIDOejsVPrs946waK91/4+dmdiroOCZlz8RtAF\nLg0dWoQJuEiJD7wdfIn3FE1+ec426xIKs3fOXaO9UBpd1aQGh2GQn+79wAW4mNdzpGbheT2HqnvQ\n3qfD2mXxWL40xi3jsue5SDCoM0JN/VwWpb1PBw7DINkDn//RIgEiw/noG6LAxdeCKnDRjhqh0hqQ\nlSzxWsUCCUxFmXIwAKqaZ97HJhSq0/KXxiBWHIYT9f0Y82C1xJBuAu19o8hOkbg9adJVU/N6TjcO\nzPvx2lEjPjjSCpGQhzu3Zrp1bI72/40dtFy0UBarDR2qUSTJIzy2FKmIEUGtNXg1oZ1cKai+3S9e\nIQfvFw1xD3GEAOlJYjR3D0M3brridkf/FnGEwNk1MxhxOAy2FCfCZLHheG2fx16nutn71UTTceT1\nLGSG6e9fNWHCZMXtpRkQRwjcOi7q57J4vZoxmC02jyTmOihlIthYFiotVYD5UlAFLhd38A3eqX3i\nPsWZcrAsUDPNrEv/0DhG9CZkp0iCMr9lqo35CeDzODhY1QObh3IsHPtDFWX6ZpnIYaF5PVVNalQ1\nqZGVLMHV+Uq3jysh1p7n0tA5THkuC+TujRWn40jQpQ66vhVUgUtDxzDChTykxFH/FjI3R57LdGXR\nziTvEJi9iwznY21uPAaGDahvH3L7849NmNHYOYw0ZdSCusu628W8HteqqQxGC/7+VRN43MmeLR4I\nZBmGQU6KBNpRIwaon8uCtPd6I3ChBF1/EDSBy5BuAgPDBvsOvgtsBkVCS7xUhER5BOovaGEwXrqP\nTbD2b5mJYzNCd/U5maqmRQOrjUVRpm+XiRwu5vWoXMrr+fBoG7SjRuxcl+q84vYEx3uNuuguTHuf\nDgI+BwmxnlvavRi40IyLLwVN4NJA+xORBSjOlMNitV0y02DPbxmGOFKAeGm4D0fnPamKKKQnRONs\n66Dbr/h90S13NlPzer6eI6+nrVeHg5XdUMhE+MZVSzw6LueGi5SgO29GkxU9mjEsiY/yaGFGrDgc\nPC6HZlx8LIgCl9CZ2ifuM10X3b7BcejGTMgN0v4tMyktTgIL4LAbS6NNZivOtg8iXiZyXq36A0de\nz6FZ8nosVhve+rIBLID7rs0Gn+fZj8uEGBGiRXw0UD+XeetQjYJl3b8/0eU4HAYKWTj6hsbpHPlQ\n8AQuHVqIhDwkx1H/FuK6lPhIxESHoaZ10FniGKq7i6/KiUOUiI9jtb0wmq1uec76C0MwmW0ozor1\nqyBwal5PXdv0eT1fne5C14AeG/OVXtmripnct2hYb8IAVa3MS9tkfstSD1YUOShiImA0WTGsv7Ia\nkXhHUAQumhEDNCMTyE6h/BYyPwzDoCgrFgajxbnceD4E+rdMh8/jYFNBAsYmLDh5TuWW57zYLdc/\nlommcuT1TJekqx424ONj7YgW8XHblgyvjcnxnjtPZdHzcqHf84m5DsrJ9gi9lOfiM0ERuDQG6Q6+\nxDuKMx3LRRqwLIvGTi2kUULESUIjv2WqLUWJYBj7/kWLnQq32myoaRmEOFLglS+U+Zopr4dlWby9\ntxEmiw13bs30asM8Rz8XStCdn7ZeHSLD+YgVe75qTTmZ/NtPeS4+ExSBSyi0Zieek5ksRmQ4H9XN\navRoxjA6bkZOCPRvmY4sOgxFmXJ0qvRonZx+X6jmrhHoDWYUZ8o9UkLsDtPl9VScV6GufQh5aTKs\nXRbv1fEoZCKIIwRo6KA8F1fpxk3QjEwgTRntlb9ZpYw2W/S1oAhcGjuHERHGQxLlt5AF4HI4KMiI\nwYjehC9OdAAI7dm7rcWO7rKLK412LBMV+WBTRVddntejN5jx7v5mCHgc3LMj2+vBKzO5b9HImAn9\ntCeOSy44G895p3+Xo5M2VRb5jkuBy8TEBK655hp8+OGHnh7PvGmGHfktUr+9qiP+z5GDUV5vz+0I\ntfyWqXJSpVDGiHDq/ABGxhaWgMiyLKqb1QgX8vy60u/yvJ7dh1ugGzfjxqvTfLZU6HjvNdBykUva\n+yZ3hPZCYi5g3/MqJlpIMy4+5FLg8tJLL0EsFnt6LAvS4MxvoWUisnB5S2QQ8O1/DrJoIeReWCv3\nVwzDoLQ4CVYbi6M1vQt6jk6VHoM6IwoyYsDj+vfEriOv51/H2nC0pg9J8khsW53ss/E4N1ykBF2X\ntE/OuHi6FHoqZUwEhvWmKxpXEu+Y8xOltbUVLS0t2Lx5sxeGM3+O/JZcP76qI/5PwOdiRVoMACA7\nObT6t0xn/XIFhAIuDlf3wGqb/064lY5qIj/pljsbR17PsN4EBsB3rsvxabAVLw2HJFJA+xa5gGVZ\ntPXqECsOQ7TIvRtfzkYx2ZOIlvN8gzfXHZ555hk8/vjj+Oijj1x6QqlUBB7PM1uKO8jl9rVMlmXR\n3DOCKJEABbmKkCmFdhx/KPLkse9YvwSVTWqUrEz22/9jb47rmtUp+Ox4O9pUY1ifnzCvx55tGwSf\nx8HmNakIF875MeMSTx77bddkoapJjes3LsXagkSPvY6rCjLjcKS6G0aWQfLk3mv++p70hpmOvX9w\nDHqDGYVZcq/+/2SlyrD/dDf0JqtXXjeUz/10Zv1E+eijj1BYWIjkZNenTbVaz0agcnkU1Gr7mubA\nsAFqrQErs+UYHNR79HX9xdTjDzWePvYMRRSe+eFViBWH+eX/sbfP/brcOHx2vB0fHW5B5jwSH1Xa\ncXT0j6IgPQZ6nQHu+Mv09LHHRwvxnz9Yh1hJuF+c+zRFJI4AKDvTjdLiJPq7n+HYK8/bc9ISZCKv\n/v9ECe0X500XhrDCw/lwoXruZwvWZg1cDh8+jK6uLhw+fBj9/f0QCARQKBRYv3692we5EI0djjJo\nWiYi7iEPwd4tM0mMjUBuqhTnO7To0YwhMda1DQb9bW8iV8VJ/WdLAkfOXkPnsHM3a3Kldi9XFDko\nYhwl0bRU5AuzBi5//OMfnf9+8cUXkZiY6DdBC0AbKxLiaaXFiTjfocWhqm7s2p7t0mOqmtRgGKAg\n03/LoP1dnCQc0ighGmnfolm19+rAMPZmgt4ULeJDJORRZZGP+He6/ywcO/hGhvNdvhIkhMxPYWYs\npFFCHK/rd6mCYkRvRGvPCDKTJF5Nlgw2DMMgJ0WC0XEzejX05Tgdq82GC6pRJMZGIEzgnjwqVzEM\nA2WsCANag3OPM+I9LgcuDz30EG655RZPjmVeBoYN0I4aQ7bDKSHewOVwsLkoEUaTFWV1/XPev7pF\nAxaBt0zkjxxNEKmfy/T6NOMwmW0+205CKYuA1cZCPUwbYnpbwM64NIboRniEeFtJQQJ4XAYHXdi/\nyLmpIi0TLdrFRnTUz2U6bX3e21hxOsoY6qDrKwEbuDR0OPJbKHAhxJOiIwRYlROHvsFx59/ddAxG\nC85f0CIlLhKxlOS8aHJxGGTRQjR2DsNmozyXy7X7OHBROAMXWsrztoAMXOz5LVpEi/hIiPGfSgBC\ngpWjsuXAlM0IL1fbOgirjUURLRO5hT3PRQq9wYxOVeiVw86lvU8HPo+DRLlvchwTJiuLaJdo7wvI\nwEWlNWBYb0J2CnU4JcQb0hOikRofhepmNQZHJqa9j3OZiAIXt3FUTNa2qH08Ev9iMlvRPTCG1Pgo\nn3U5jpWEgcth0Efdc70uIAMXx5ov5bcQ4h32/YsSwbLA4TNXzrqYLTbUtg1CLglDko+ugIORYyuT\nutZBH4/Ev3Sq9LCxLJZ4uX/LVFwOB/EyEfoGx6hk3csCM3BxNp6j/i2EeMvaZfGICOPhaE0vzJZL\nS0DPdwzBaLKiKFNOs6BuFCsJR0x0GOpaNbDRl6OTI79lqY/yWxyUMSIYjNYF76JOFibgAheWZdHY\nOQxxhAAKGeW3EOItAj4XG/MTMDpuxumGgUtuqwrQbrmBICfV3s+leyA0tjVxhTMxN8H3gQtAlUXe\nFnCBS/eAHiNjJmRT/xZCvG5zcSIYAAerup2/s9lYnGlWI0rER0ai2HeDC1I51M/lCm19OkSE8RDn\n4+o1pczR+p8qi7wp4AKXulb7lR3ltxDifXGScKxIj0Frrw4X+u1XvS09I9CNm1GUGRsyO7R7kyNB\nt5H6uQAA9AYzBrQGLFFG+/ziVRlLMy6+EHCBy9nJJDXaWJEQ39i60l4afbDSnqRb3UzVRJ4UKw5H\nvExE/VwmOQJmX/VvmcqRrtBPMy5eFVCBC8uyONuqgSRSgHgpNbgixBfy0mSIk4aj4rwKeoMZVU1q\nCAVc5NIsqMfkZ8Ri3GhBF+W5oL3XPxJzASBMwIM0Skgl0V4WUIFL3+A4hkeNyKH+LYT4DIdhUFqU\nCLPFhn/ub4Z6eAL5S2PA53F9PbSgtTzdvoUCtf8H2vvszfjSfFgKPVVCjAhDOiMmTHNvQkrcI6AC\nF+rfQoh/2JCvhIDHQXm9fePFoizam8iTVkwGLo0hnqDLsiza+nSQRQshjhT6ejgAAIWjgy7NunhN\ngAUu9j/abOrfQohPRYTxsS5PAQDgchjkL6XAxZPk0nDEScLR2BXaeS7aUSN0Yya/yG9x8KeSaJZl\n0dw9DIvVNvedA1hABS59mjHETf4BE0J8q7Q4EYA950UUxvPxaIJfTqoEBqMFnQOhu29Rmx/ltzgo\nZf6z2WJloxpPv1OFPcfbfT0UjwqoT5vvfXMZ5LGRlN9CiB9IiY/Co3cVIZ4aQXpFdooUR2v60NAx\njCUK//ni9iZH47kl/hS4xDp6ufh+xmX/6S4AwOHqXly/fknQ5p0F1IxLqiIKqX70hiUk1OWkSiGN\n8o9cg2B3sRFd6CbotvfpwABYovCPxFwAEEcIEC7k+nyX6K4BPZq6R8BhGOgNZpw8PzD3gwJUQAUu\nhBASqqRRQsRLw9HcPQyrLbhzGKZjs7G40D8KZWwEwoX+s1jAMAwUsgj0D4379Lw4ulnfsTVjsrv1\nlZuhBgsKXAghJEBkp0hhMFrRqQq9fi59Q+OYMFn9pgx6qoQYEaw2FprhCZ+8/viEGeX1/YiJDsPW\n4iTkp8egvU/nXFoLNhS4EEJIgMhJtVdUhuJykaPxnD9VFDkofFxZ9PXZfpjMNpQWJ4LDYaZ0t+6e\n45GBiQIXQggJEM48l47Q6+fS7ket/i+nnOzl0jfk/coiG8viYFU3eFwOrs5XAgCWObtbD2B03OT1\nMXkaBS6EEBIgJJFCKGQiNIVgnkt7rw48LoPkuEhfD+UKzl4uGu/PuJxrH8KA1oC1y+IQJRIAmOxu\nXZwEi9WGY7V9Xh+Tp1HgQgghASQnRQKjyYoL/aHTz8VssaJrQI+U+CjwuP73tSWXhIPLYXwy4+JI\nwi0tTrrk91evUEDA5+BQVU/QNS30v3cAIYSQGTm2PAml9v+dA3pYbSzS/LR/DY/LQZw0HP2D42BZ\n7wUJ6mEDalo0WJoQfcUSmiiMj6vyFBjUTaCmVeO1MXkDBS6EEBJAspMnE3Q7QidB94JjY8UE/6so\nclDIRBibsEA3bvbaax6u7gGLi12sL+eYhQm20mgKXAghJICII4VQxojQ3D0S9HvSOLT5cUWRQ8Jk\nB91+L7X+N5mtOFrTiygRH6tz4qa9T3JcJLKSxKhvHwqqTSApcCGEkACTkyKF0Rw6eS7tfTqEC7l+\nvb2EQubdkuiTDs1ZGAAAIABJREFU5wcwNmHBpoKEWVv7lzpKo6uCpzSaAhdCCAkwF/Ncgn+5aMxg\nRv/QOJYoosHx433qnCXRXghcWJbFgapuMAywuXD6ZSKH4iw5xJECHD/bhwmTxeNj8wYKXAghJMCE\nUp5LS5c9CXlpgv8uEwFTSqK9sFTU1qdDR/8oCjNiESMOm/W+PC4HJQUJMBitOFGv8vjYvIECF0II\nCTDREQIkxkaguSf481yauuzBmT/ntwBAuJAHSaTAKzMujo64jg65cykpTASXw+BgVbdXq548hQIX\nQggJQNkpEpjMtqDdj8ahqTMwAhfAvlw0qJuA0Wz12Gvoxkw41TAAZYwIuZNLhnORRglRnCVHt3oM\nTV2BX0bvUuDy7LPP4o477sCtt96Kffv2eXpMhBBC5uBs/x/k/Vyau4YhiRRAGiX09VDm5Fgu6vfg\nrMvRml5YrCxKi5PAzCPnx7l/URCURs8ZuJw4cQLNzc1477338Prrr+Opp57yxrgIIYTMIjsl+PNc\ntKNGDI5MBMRsC+D5PYusNhsOn+mBUMDF+uWKeT02M0mMJHkEqprU0I4aPTI+b5kzcFm9ejVeeOEF\nAEB0dDQMBgOsVs9NgxFCCJlblEiAJHkEWntGYLYEZ56LYxnM3xNzHRQennE50zyIIZ0R6/MUCBfy\n5vVYZnL/IquNxZEzgT3rMmfgwuVyIRLZT8bu3buxadMmcLkz14wTQgjxjuwUKUyW4Mxz0RvM2Heq\nCwCwJFBmXDzcy8XRi2WmTrlzWZcXj3AhD0fO9AZ0UrfLIdv+/fuxe/du/OUvf5n1flKpCLxZmuG4\ng1zuv22fvSGUjz+Ujx0I7eMP5WMHpj/+NcuVOFDZja7BcWwoTvbBqDyjrWcEv3+7EgND41ibp8DG\n4mRw/XBzxcvFxkYiXMiFemTCre9XuTwKXapRnO/QYkV6LAqXKRf8XNvWpGDPsTa09OmxsWhhAZCv\nuRS4HDt2DC+//DJef/11REXNfjK0Ws+WgsnlUVCrQ6Nb5HRC+fhD+diB0D7+UD52YObjV0rsPTwq\nz/Vja2GCt4flEeX1/XjriwaYLDbcsGEJ7r8pH4ODel8Py2XxUhG6B/RQqXTgcBbfMM9x7j/Y3wQA\n2LhCsai/hXW5cdhzrA3/OtyMnCT/ncmaLfCbM4QdHR3Fs88+i1deeQUSicStAyOEELJwkeF8JMkj\n0dqrg9kS2LmHFqsN/9zfjNc+OQcul8HDt+bjpo1L3fLl703KGBEsVhs0ugm3PafBaMHxuj5Io4Qo\nyopd1HMpZCLkpcnQ3D2CTlVgXgzMGbh8/vnn0Gq1+OlPf4p77rkH99xzD3p7e70xNkIIIXPISZXA\nbLE5NyIMRLoxE/7r3TP46nQXlDEiPH7fahRmLu4L2leclUUa91UWldf3Y8JkxebCBHA5i18y2xrg\nu0bPuVR0xx134I477vDGWAghhMxTTooU+093o6FzGNkprjUk8yftfTr894dnoR01YmW2HP+2M3fe\nFTP+5GLr/3EUZCz++ViWxcGqHnA5DDbNsS+Rq/LTYxATHYYT5/px+5Z0iML4bnleb/H/bCdCCCEz\nykqWgEFgbrh4rKYXT79TheFRI24tWYof37Q8oIMWAFBMzrj0u6mXy9lWDXo1Y1idEwdxhMAtz8nh\nMCgtToTJbMPXZ/vd8pzeRIELIYQEsMhwPpLjItHSEzh5LharDX/b24i/ftEAIZ+Dn91egG9ctWRe\nnWD9Vbw0HByGQa+bSqI/O94OACgtdm1fIlddna8Ej8vBwapu2AJs/yIKXAghJMDlpEphsdrQ2uP/\neS7aUSOe/Uc1Dlf3IDkuEo9/ZzWWL43x9bDchsflQC4Nd0sTuiHdBE7U9SMlPhLpie6tAIoSCbB2\nWRwGtAacax9y63N7GgUuhBAS4Jzt//18uai5exj/981TaOkZwbpl8fiPe1YiThLu62G5nVImgt5g\nxui4aVHPc/hML2y2+e9L5CrHLM6Byd2mA0VgLyYSQghB9mSei79uuMiyLA5V9+Cf+5vBssCdpRnY\ntjo5KJaGpqOMEeFMiz1BN0q0sLwUs8WGo2d6EBnOx9pl8W4eoV2aMhpLE6JR2zoI9bAB8gAJImnG\nhRBCApwojI+U+Ci09Y7AZPavPBezxYq/ft6Ad/Y1QRTGwyN3FmL7mpSgDVqAKSXRgwtP0K1sHIBu\n3Ixr1qRAyPdcN/rS4kSwAA5VB05pNAUuhBASBHJSJbBYWbT2jPh6KE6DIxN4+p0qfH22D0sUUXji\nO6uRmxp4JdvzNbUkeqEOVHWDAbBzfZqbRjW91TlxiBLxcaym1++C3plQ4EIIIUHA0cPlvJ8sF53v\n0OL/e/MULvSP4uoVSvxqVzFk0WG+HpZXOAKX/qGFBS4d/aNo7dFhRXoMlLER7hzaFfg8LjYVJGBs\nwoKK8yqPvpa7UOBCCCFBICtJAobxfT8XlmWx72Qn/uvdMzAYLbhnexa+uzMHfA9vvutPRGF8iCME\n6F1g99wDi9wFer42FyaCYYCDlT1gA6A0mgIXQggJAqIwHlLjo9DWq4PRR1P+RrMVr35yDu8ebEGU\niI9H7y7CFg9VxPg7ZYwIgyMT815+0RvMqDinglwS5rUy8RhxGAozYtGhGg2IrSMocCGEkCCRkyqF\n1caixQd5LgPDBvz+b5WoOKdCemI0fvOd1chMCt2NeRUxEWABqLSGeT3u69o+mC02bClKAseLAV/p\nSsf+Rf5fGk2BCyGEBIkcRz+XDu8uF9W1DeK3b55Ct1qPzUWJ+OXdxZBGCb06Bn9zMUHX9eUim43F\noepuCHgcXJ2v9NTQprUsVQqFTIRTDQPQjS2u/4ynUeBCCCFBIjNJAg7DoNFLCbosy+Kz8gv4//+3\nBkazFd+9Lgf37sgGj0tfLQupLDrbNgj18ATWLotHZLh3Nz5kGPv+RRYri6M1vV597fmidxchhASJ\ncCEPqYootPfpMGGyePS1DEYL/udfdfjgSBskUUI89u2V2FiQ4NHXDCRK2fx7uRyssvdScfe+RK7a\nsEIJoYCLw2d6YLXZfDIGV1DnXEIICSI5KRK09+nwkz99DU+mSFitLKw2FtnJEvzopuWIdtPOxcFC\nGi2EgM9xec8ilXYcZ9sGkZEoRqoiysOjm164kIf1eQocqu7BmeZBrMyW+2Qcc6HAhRBCgsjV+Uq0\n9uq80kwsL02GG69Oo6WhaXAYBkpZBPoGx2Bj2TkTbQ85ZltWeqcEeialxYk4VN2Dg1XdFLgQQgjx\nPGVMBB77drGvh0Fgz3PpUI1iaGQCsbPsA2Q0W/F1bR+iIwRYlR3nxRFeKVEeiZwUCc53aNGrGUOC\nhxvgLQSFyYQQQogHKBwJunN00K04p8K40YKSggS/mL1y5Ng4ZoH8je//hwghhJAglODYbHGWDros\ny+JgZTc4DIPNRb5dJnIoyoqFNEqI43V9MBg9m+S9EBS4EEIIIR7gyoxLS88IOgf0KJ4MFvwBl8PB\n5sIETJisKK/v9/VwrkCBCyGEEOIB8VIRGGb2Xi6+LoGeyabCRHA5DA5W+d/+RRS4EEIIIR7A53Eg\nl4Sjf4ZeLiN6I043DCAxNgLZKf61PYI4QoDVOXHo1YyhwU92HHegwIUQQgjxEKVMBN24GXqD+Yrb\njtT0wmpjUVqc6JcbUTpmgfxt/yIKXAghhBAPUU4m6F7eiM5iteFwdQ/CBFysy1P4YmhzSk+MRkpc\nJKqbNBjSTfh6OE4UuBBCCCEeophhs8UzzRoM603YsEKJcKF/tlRjGAalK5NgY1kcPuM/+xdR4EII\nIYR4iLMk+rIZlwOV9uWX0mL/KIGeydpl8YgI4+HomR6YLf6xfxEFLoQQQoiHTDfj0q3Wo7FrGMuW\nSJ1LSf5KyOfi6nwldONmVDYO+Ho4AChwIYQQQjwmMpyPKBH/kl4u/loCPZMtRYlgABzwkyRdClwI\nIYQQD1LGREA9bIDZYsP4hAXldf2IiRaiICPG10NzSZxUhBXpMWjt0aGjf9TXw6HAhRBCCPEkZYwI\nLAuotOM4XtcHo9mKzUWJ4HIC5yvYkYvjD7MugfO/RgghhAQgpcye59KrGcPBqh7wuAw2FiT4eFTz\ns3xpDOSSMFScU03bk8abKHAhhBBCPEgZa0/APVjVA9XQOFbnxCNaJPDxqOaHwzDYUpQEs8WGr2v7\nfDsWV+701FNP4Y477sCdd96J2tpaT4+JEEIICRqOGZemLnvr/K0rAyMp93JX5ysh4HFwqLobNh/u\nXzRn4HLy5El0dHTgvffew+9//3v8/ve/98a4CCGEkKAgE4eBz7N/3S5RRGFpQrSPR7QwkeF8rF0W\nD/XwBOraBn02jjkDl/LyclxzzTUAgPT0dIyMjECv13t8YIQQQkgw4DAMFJOzLoE62+Jwcf+iHp+N\nYc4+wxqNBnl5ec6fZTIZ1Go1IiMjp72/VCoCj8d13winIZdHefT5/V0oH38oHzsQ2scfyscOhPbx\nB8Oxb16ZjIr6PuzcmA4Bf37fkf50/HJ5FDYWJoLDMD4b17w3SGDnWNfSasdnvX2x5PIoqNW+ryP3\nlVA+/lA+diC0jz+Ujx0I7eMPlmPfUqDElgIlRobn9x3pj8f/3WuzAcCj45otKJpzqSguLg4ajcb5\n88DAAORyuXtGRgghhBAyD3MGLhs2bMDevXsBAPX19YiLi5txmYgQQgghxJPmXCoqLi5GXl4e7rzz\nTjAMgyeeeMIb4yKEEEIIuYJLOS4///nPPT0OQgghhJA5UedcQgghhAQMClwIIYQQEjAocCGEEEJI\nwGDYuRqzEEIIIYT4CZpxIYQQQkjAoMCFEEIIIQGDAhdCCCGEBAwKXAghhBASMChwIYQQQkjAoMCF\nEEIIIQGDAhdCCCGEBAyX9iryhaeeego1NTVgGAb/8R//gfz8fOdtZWVl+MMf/gAul4tNmzbhgQce\n8OFIPePZZ59FZWUlLBYLfvCDH2D79u3O20pLS6FQKMDlcgEAzz//POLj4301VLerqKjAT37yE2Rm\nZgIAsrKy8PjjjztvD+bz//7772PPnj3On+vq6lBdXe38OS8vD8XFxc6f33zzTef7IJA1NTXhxz/+\nMb7zne9g165d6Ovrw6OPPgqr1Qq5XI7nnnsOAoHgksfM9hkRaKY7/l/96lewWCzg8Xh47rnnIJfL\nnfef628kkFx+7I899hjq6+shkUgAAPfffz82b958yWOC+dw//PDD0Gq1AIDh4WEUFhbit7/9rfP+\nH374IV544QWkpKQAANavX48f/ehHPhm7z7B+qKKigv3+97/PsizLtrS0sLfffvslt1933XVsb28v\na7Va2bvuuottbm72xTA9pry8nP3e977HsizLDg0NsSUlJZfcvmXLFlav1/tgZN5x4sQJ9qGHHprx\n9mA//w4VFRXsk08+ecnv1qxZ46PReM7Y2Bi7a9cu9te//jX79ttvsyzLso899hj7+eefsyzLsv/1\nX//F/v3vf7/kMXN9RgSS6Y7/0UcfZT/77DOWZVn2nXfeYZ955plLHjPX30igmO7Yf/nLX7IHDx6c\n8THBfu6neuyxx9iamppLfvfBBx+w//mf/+mtIfolv1wqKi8vxzXXXAMASE9Px8jICPR6PQCgq6sL\nYrEYSqUSHA4HJSUlKC8v9+Vw3W716tV44YUXAADR0dEwGAywWq0+HpV/CIXz7/DnP/8ZP/7xj309\nDI8TCAR47bXXEBcX5/xdRUUFtm7dCgDYsmXLFed4ts+IQDPd8T/xxBPYsWMHAEAqlWJ4eNhXw/Oo\n6Y59LsF+7h3a2towOjoa0LNJnuKXgYtGo4FUKnX+LJPJoFarAQBqtRoymWza24IFl8uFSCQCAOze\nvRubNm26YjngiSeewF133YXnn38ebBDu2tDS0oIf/vCHuOuuu3D8+HHn70Ph/ANAbW0tlErlJcsD\nAGAymfDII4/gzjvvxF//+lcfjc69eDwewsLCLvmdwWBwLg3FxMRccY5n+4wINNMdv0gkApfLhdVq\nxT/+8Q9cf/31Vzxupr+RQDLdsQPAO++8g3vvvRc/+9nPMDQ0dMltwX7uHf72t79h165d09528uRJ\n3H///bjvvvtw7tw5Tw7RL/ltjstUwfjF7Ir9+/dj9+7d+Mtf/nLJ7x9++GFs3LgRYrEYDzzwAPbu\n3Ytrr73WR6N0vyVLluDBBx/Eddddh66uLtx7773Yt2/fFTkOwWz37t24+eabr/j9o48+ihtuuAEM\nw2DXrl1YtWoVVqxY4YMReo8rf//B+BlhtVrx6KOPYt26dbjqqqsuuS2Y/0ZuvPFGSCQS5Obm4tVX\nX8V///d/4ze/+c2M9w/Gc28ymVBZWYknn3zyitsKCgogk8mwefNmVFdX45e//CU++eQT7w/Sh/xy\nxiUuLg4ajcb588DAgPPK8/LbVCrVvKYZA8WxY8fw8ssv47XXXkNUVNQlt910002IiYkBj8fDpk2b\n0NTU5KNRekZ8fDx27twJhmGQkpKC2NhYqFQqAKFz/isqKlBUVHTF7++66y5ERERAJBJh3bp1QXfu\nHUQiESYmJgBMf45n+4wIFr/61a+QmpqKBx988IrbZvsbCXRXXXUVcnNzAdgLES5/j4fCuT916tSM\nS0Tp6enOZOWioiIMDQ2FXCqBXwYuGzZswN69ewEA9fX1iIuLQ2RkJAAgKSkJer0e3d3dsFgsOHTo\nEDZs2ODL4brd6Ogonn32WbzyyivOzPqpt91///0wmUwA7G9wR2VBsNizZw/eeOMNAPalocHBQWfV\nVCicf5VKhYiIiCuuntva2vDII4+AZVlYLBZUVVUF3bl3WL9+vfMzYN++fdi4ceMlt8/2GREM9uzZ\nAz6fj4cffnjG22f6Gwl0Dz30ELq6ugDYA/jL3+PBfu4B4OzZs8jJyZn2ttdeew2ffvopAHtFkkwm\nC4rKwvlgWD+dZ3v++edx+vRpMAyDJ554AufOnUNUVBS2bduGU6dO4fnnnwcAbN++Hffff7+PR+te\n7733Hl588UWkpaU5f7d27VpkZ2dj27ZteOutt/DRRx9BKBRi2bJlePzxx8EwjA9H7F56vR4///nP\nodPpYDab8eCDD2JwcDBkzn9dXR3++Mc/4vXXXwcAvPrqq1i9ejWKiorw3HPP4cSJE+BwOCgtLQ2K\nMsi6ujo888wz6OnpAY/HQ3x8PJ5//nk89thjMBqNSEhIwNNPPw0+n4+f/exnePrppxEWFnbFZ8RM\nH/T+brrjHxwchFAodH4hp6en48knn3Qev8ViueJvpKSkxMdHMn/THfuuXbvw6quvIjw8HCKRCE8/\n/TRiYmJC5ty/+OKLePHFF7Fy5Urs3LnTed8f/ehHeOmll9Df349f/OIXzguYQC8HXwi/DVwIIYQQ\nQi7nl0tFhBBCCCHTocCFEEIIIQGDAhdCCCGEBAwKXAghhBASMChwIYQQQkjAoMCFEEIIIQGDAhdC\nCCGEBAwKXAghhBASMChwIYQQQkjAoMCFEEIIIQGDAhdCCCGEBAwKXAghhBASMChwIYQQQkjA4Ln7\nCdXqUZfvK5WKoNWOu3sIfomONfiEynHK5VG+HsKc6HPnSqFynAAdazCa7XPHpzMuPB7Xly+/ICzL\n4mhNL76o6MCI3ujy4wLxWBfK1WPt1Yzhy4pOWKw2D4/IM0LpnAaTUDlvoXKcAB2rO4yMmfDh0Vbo\nDWaPPL87uX3GJZgZzVa8+UUDKs6pAAAfHmlDYWYsNhcmIneJFByG8fEIA4eNZfHyx/XoVuuh0o7j\n3h3ZYOj/jxBCvM5mY/HyR3Vo7BoGANyyKd3HI5odBS4u0gwb8N8fnkXngB7pidFYkxuPYzV9qGxU\no7JRDbkkDJsKEnB1fgLEEQJfD9fvVTep0a3Wg2GAI2d6kRAbgW2rkn09LEIICTl7jrc7g5byun7c\ntHGpX1+IU+DignMXhvDyx/XQG8zYXJiAu7dlgcfl4JqVSWjr0+FIdS9OnlfhgyNt+OhYO4oyY1FS\nlIjcVJqFmY6NZfHx1xfAMMAjdxTi1U/O4d0DzVDKRFi+NMbXwyOEkJBxvkOLT45fQEx0GJYoo1DZ\nqEZj5zByU6W+HtqMKHCZBcuy+OpUF9471AIOw+Dea7OxuTDReTvDMEhPECM9QYw7t2agvF6FI2d6\ncLpRjdONasRJwrGpMAFXr1BCLvfhgfgZx2zLurx4LFsiw0O3rMAz/6jGSx/X49f3roQyJsLXQySE\nkKCnGzPh1U/qweEw+OGNebBYbahsVKPsbB8FLoHIaLbirS8bcKJeBXGEAA/cvAIZSeIZ7y8K42Pr\nyiSUFieirVeHw2d6cOr8AHYfbsW/jrZBEiWEzca69NoCHgc/vHE5UhX+X80xXzaWxZ7j9tmW69cv\nAQCkJ4rx3Z05eO2Tc3hhdy1+fe8qRIbzfTtQQgKY0WxFY8cQooVc8LiB1fXCZmPR1qtDqiIKfF7g\njf18pxZms+sFB9IooU8+620si9c/O4cRvQm3bU5HeqIYNpZFrDgMpxvV2LXdCqHAP5OeKXCZhmZk\nMp9FpUd6QjR+fPMKSKOELj2WYRikJ4qRnijGXVszUV6vQlldPyZMVlhdqJ6x2mxQaQ04WtOLexTZ\niz0Uv1PdpEHXgH22ZerMylV5CvRqxvBZeQde+qgOP7u9IOA+cIlr3n//fezZs8f5c11dHaqrq50/\n5+Xlobi42Pnzm2++CS7XPz9A/Y1uzISDVd04WNUDvcEMSaQAW1cmYXNRIiLCAuNi4N2Dzdh/uhvi\nCAGuWZWEksLEgLmQOXKmB2/va5rXYxgGeOrf1yFeJvLQqKa392Qn6tqGsDxNhh1rUwAAHIbBVXkK\nfFJ2AZVNA1i/XOnVMbmKApfLnO/Q4qWP6qA3mLGpQIlvb8tecNTvmIXZujIJcnmUS70mrDYbfvqn\nr3GmRYNvb88KqhwZ+2xLOxhcnG2Z6uZNS9GrGUN1swb/3N+Me3YEX+BGgNtuuw233XYbAODkyZP4\n4osvLrk9MjISb7/9ti+GFrD6Bsew92QXyur6YbHaEBHGQ0lREirq+/DBkTZ8WtaBjflKbFudDLkk\n3NfDnVF1sxr7T3dDGiWEwWjBB0fa8EnZBWzMT8C21cmI8+OxA8Cx2j5wGAa3lLiW3No/NI6jNb04\nXtePWzYt9cII7Vp7RvDhkTaIIwX43jeXXTLW9SvsgUtZXT8FLv6OZVnsP92N9w62gGGAe3ZkY3Nh\ngtdLdLkcDgoyYlFW14+O/lGkKaO9+vqedKZ5crZlWfy0eSwchsG/X78MT71dhUPVPUiIjcDWlUk+\nGCnxlj//+c94/vnnfT2MgMSyLJq6hvFlRSdqWgcBAHGScGxfk4wNy5VISpSgo0uLozW9+Op0F/ZX\nduNAVTdWZsdhx5pkpCfMvPTtC4MjE/jLZ+fB53Hws9sLEBMd5hz7gcpuHKzqxsosOXasSUF6on+N\nHQB6NGO40D+K/PQY7FyX6tJjjGYrKs6rUF7Xh5s2pnnlQnV8woxX9tTDZmPx/evzEH1ZFWy8VISM\nJDHOX9BiSDcBWXSYx8c0XxS4ADCZrXjry0aU1/cjOkKAB25ejswkic/GU5QpR1ldP6qa1D4PXEb0\nRkSE8xe9bMOyLPZ8PTnbsmHJjPcLE/Dw8LdW4HdvncY/9zdDIRMhL022qNcml7JYbRg3WhAt8m3Z\nfm1tLZRKJeSXZa6bTCY88sgj6OnpwY4dO/Dd7353zueSSkXzaswVCN2AZ2Kx2nC8phcfHWlBS/cI\nACB3iQw3b07HmjwluJyLX36pyVLckyzFXdfl4uuaXvzrcAtONwzgdMMAlqXJcFNJBtbkKS55jC9Y\nrTY89+4ZjE1Y8MC3ClC0zH6lvytJijuvzcXxml7860iLs/BhuuP19Tn9rKITAHDtVWnzGsvGgkTs\nP9WJAZ0JKzJiXXrMQo+VZVn8599OQTMygTu3ZWPTqpRp77dj3RL8eXcNai9ocdvWrAW9lidR4ALg\n7X32oCVNGY0Hb3E9n8VTlqfJwOdxUN2swa0l3m8EZLbYUNWkxpEzPWjoHEZemgw/vS0fXM7Cg5fq\nZg06B/RYO8Nsy1Sx4nA8eEs+nv1nFV76qA6/vm8VFF5e/w1GA9pxHKnpxfHaPowbrfjDgxt8mjuw\ne/du3HzzzVf8/tFHH8UNN9wAhmGwa9curFq1CitWrJj1uebTAt3VZVt/YzBacLSmF/tPd2FQZwTD\nACuz7TMQGZMzEEODeuf9Lz/OvGQxlu0qRkOHFntPdaG2dRDn2k8iXhqO7auTsX6FEkK+b3KJPjjS\nivMXhrA6Jw7F6bIrzs+yZDFyv12Mxs5h7D1pn2E6/+YQ4ibHfuOWTIyOGHwydsCelHvgVCfChTws\njY+Y1/trZWYM9p/qxGdft0Ihnvu7ZzHv30NV3Sir7UNWsgRbi5QzPk9uUjR4XA6+quhAyQqFT5qD\nzhachXzg0j80jrK6fiTKI/DYt4vA94PW0UIBF3lLZDjTokH/0LjXvrRVQ/Yvtq9r+5xtn8WRAtS3\nD+Hd/S349vaFRd6XzLZMk9synYwkMe67NgdvfHZ+stJoZcAkF/oTi9WGM80aHD7Tg3MXtACAiDAe\nrl2bDJHQt3/+FRUV+PWvf33F7++66y7nv9etW4empqY5A5dgNqSbwP7T3ThS0wOD0QoBn4OtxUnY\ntjoJcdL5fTYwDIPcJTLkLpGhRzOGfSc7UV7fj7f3NeGLik48+d01EIV5931Rf2EIn5d3QC4Jw33X\n5sz4JckwDHJSpchJlaJXM4Z9p+w5Pe/sa8K+0934zb2rvD52h3MdQxjWm7CpIAGCeQZ/mckSxERP\nVvJs81wlT6dqFP880ILIcD5+cEPerBeiojA+ijJjcaphAO19o1ia4F8pCyEfuHxy/AJYFrhxQ5pf\nBC0ORVmxONOiQXWzGtetdW29dCEsVsfsSi/Od9i/2CLD+dixJhklhYkQRwjw1DuVOFDVjQR5BLYU\nJc7xjFegdpUoAAAgAElEQVQ6M2W2JSHW9R4tG1Yo0asZwxcVnXjpozr89DaqNHLVwLABR8/04uuz\nfdCNmQAAWUlilBQlYlW23OfvdZVKhYiICAgEly5XtbW1OfNerFYrqqqqcO211/polL7V0T+Kvac6\ncer8AKw2FuIIAa5dm4otRe6pskmMjcB3d+bilk1L8f7hVpTV9eNoTS+uXTv98oEnjIyZ8Non5yb7\niCx3OfBIiI3Ad67LwS2bluK9g80or1fhdOMANhUkeHjE0yur6wcAbFihmPdjOQyD9cvtCbFVTWpc\ntXz+zzGXCZMFL31cD4vVhvu/sdylVYUNKxQ41TCAsro+Clz8Sf/QOE6c60eSPALF2f7VIa4gIxYM\nY19i8UTgotKOO7/YRsftsyvZyRKUFCVgZVbcJZVUD9+aj9++dRp/39cEhTQcuUtczzlhWRYfz1JJ\nNJdbS9LRNziOMy0avHugGbu2U6XRTByzK0dqelHfPgTAPruybVUyNhUmIHEeQaOnqdVqyGQX30ev\nvvoqVq9ejaKiIigUCnzrW98Ch8NBaWkp8vPzfThS72JZFmfbhrD3ZKfzQiIxNgLb1yRj3TKFR/qa\niCOFuHNrJk43DuBAZRe2rU5a1LKwq2wsi9c/qYduzIQ7SzMWlM8XHSHArSXpOHFOhbKzfT4JXAxG\nC6omG45mLDBp2FHJc7yuzyOByzv7mqAaGsf21ckocDGPJi9NhugIASrOqXBHaaZf9dQJ6cDl0zL7\nbMsNG7yTzT0f0SIBMhPFaO4ewciYyW37HzV3D+Pjr9svWTbYvjoZJYUJM+aeyCXhePCWFXjun9X4\nn8mck3gXp6jPtGjQqdJjTW7cvGZbHDicyUqjdypxsKoH0ightq9O8as/InezsSxOnldhcGTC5ceM\njptx4pzKObuSmSRGSWECVmXHzXvq2huWL1+O119/3fnz97//fee/f/GLX/hiSD5ltlhRXq/CvlNd\n6NWMAQCWLZFix5oULE+TeTzHIDKcjw0rlDhU1YPKRjXW5MZ79PUA4IsTHai/oEVBegy2rV74PmWy\n6DDkZ8SiplmDgWGD10umTzcOwGSxYf3yheeCxEtFyEj0TCXP8bN9KKvrR5oyCt/a7HrOJJfDwbpl\n8dg3mQ+10o8u7kM2cFENjaO83p7b4m+zLQ5FWXI0dY+gpkXjlisJo9mKF96vxbjRYp9dKUzASheX\nDbKSJbh3Rzb++kUD/rS7Fv/nnpUQzZFzwrIsPnZWEqUteNzhQh5+cms+/u9bp/HBkTbsPdmFq1co\nsakwIeiSdg1GC9747DyqmtTzfqxIyLM37CpIQKI80gOjI+6mN5hxqKobB6p6oBszgcuxNwDbsSYZ\nKfHerZLZtioZh6t6sO9Ul8cDl+buYfzraDukUUL82zdyFx2Yla5KRk2zBmVn+3DTRu/1QwGAsrP2\nZaLFzpSsX6FAS88Iyuv78Y2rlrhhZPb+Pu/sa0K4kIsf3Lh83kvtG1YoJ3OJ+ihw8QeflF3MbfG3\n2RaHosxYvHewBVVNarcELhXnVBg3WvDN9akL2rZ8Y0GCPaHvVBde/rgeP5mj0mjqbMtilyliJeF4\n4jurcaCqG1/X9uHLk5348mQnclIkKClMRHGWPOBnYVRD43jxw7Po1YwhJ0WCa9emwtW3JpfDICNR\n7JezK/7CbLHhfw+14LoNaZCJ3J/oXdOiwZEzvWBZ17b2sLIsmjqHYbLYEC7k4bq1Kdi6MslnfTMU\nMhEKMuy5dS09Iwte9piL3mDvI8KCxQ9uyEOUG8ryr1qRgP/ZXYuyun7ceHWa16pg1MMGNHYNIytZ\nsujGfmty4vCPr5pRVtePnetSF30MFqsNL39cD6PZih/dtHxBM1HJcZFIjotEbesgdOMmn7dQcJgz\ncKmoqMBPfvITZGZmAgCysrLw+OOPe3xgnqTSjuNEvcqvZ1sAIE4qQpI8AucuaDFhsiBMsPA4k2VZ\nHKzsBodhsKVo4U3dbt+Sgf6hcdS2DuK9gy24+5rpK43slUQXFj3bMlWMOAy3b8nAzRuXXlKu3dA5\njMhwPq7OV6KkIMHrrbPdobZ1EK/sqYfBaMG2Vcm4vTTdK3kGocRotuJgVTc6VKP41beL3frlZrHa\n8Le9jdCOGuf1uJjoMGxbnYyN+UqE+7jKCwC2r07GmRYN9p3sRMbN7q/kYlkWf/nsPIZ0Rty0MQ1Z\nye7plxUu5GFltr3/VXP3iNuedy7l9ZNJuW7IS5layXPBDc1HD1b1oGtAj00FSqzOiVvw82xYrsC7\nB1tw8pwK16xa+JKeO7n0l7JmzRr86U9/8vRYvObT4xdgY1m/zG25XFGmHJ+UXUBd2xBWLeLN19qr\nQ+eAHiuz5YvqU8PhMPjBDXn4/duV2H+6G4mxESgpvLLSqKZlEB2qUbfMtlyOz+Ng7bJ4rF0Wj/6h\ncRw504PjZ/vxZUUnvqzoRG6qFCWFCSjOkvt9FRLLsvisvAP/OtoGLpeD730z12/bbAe6yHA+ijPl\nqGxSu/3LrbJRDe2oEVuKEueVRxAm4PqkR8ZMslMkSImLRGWTGpphA2LdnC+yv7IbZ1o0yE2V4ptu\nWg5x2LBcgbK6fpTV9XklcGFZFmV1/RDwOIv6bJ7KUclz/GzfogKXsQkzPjnejnAhb9G9wNbmKfC/\nh1pxvK4/sAKXYKLSjqO8XoXE2Ai/WrObSVFWLD4pu4DqZvWi/jgOVXUDAEoXUM58uXAhDw9/Kx+/\ne+s03tnXhHipCDlTtkC/JLdlAZVE86GQiXBHaSZu2bQUlU1qHKm2l3Wf79AiSsSfs9ndVGECLm4t\nSUdynHfyQyZM9nyWykY1pFFCPHjLCp93SvaGuWZxy8rK8Ic//AFcLhebNm3CAw884LbX3r4mGZVN\nauw92em2LzeWZbHvVCeYyef3h5mThWIYBtvXJOP1T89jf2U37tya6bbn7ugfxfuHWhAl4uPfr18G\njpu79WanSiGLFuJUwwDuvibL48umrT06DGgNWLcs3m3n3F2VPJ+WXcDYhAW3bUlf9FKcOEKA5Utl\nqG0dRI9a7xf5cy79b7e0tOCHP/whRkZG8OCDD2LDhg0z3tffW2///UAzbCyLXTtzER/n3S+JhRxr\nbGwkYsVhqG0bglQWsaAZhOFRI041qJEUF4mNq1LccoUnl0fhP767Bo+/XIaXPq7DH35aAsVkkHCy\nvh8dqlFcXZCAwmXemz1IUEpwfUkmugdGsfdEBw6e7kJT1/C8nqNHM4Y//LTE5TyDhb5/+zRjeOYf\n1ejoH0Xe0hg8du9qSHzcsdmbZpvF/d3vfoc33ngD8fHx2LVrF3bs2IGMjAy3vG5GohiZyRKcadZg\nQDs+7wZu02npGUF73yiKMmNdrrbzZ2ty4/H+4VYcrenFjVenueVL2WC04KWP62Cxsvj3by6DJNL9\n73XHzsaflXegqlmNdcvcX1Y81fG6PgD2pFp3cUclz8CwAQcquxETHYZr3LTX24YVStS2DqKsrh+3\nbXHP3+JizPmOXLJkCR588EFcd9116Orqwr333ot9+/Zd0TjKwZ9bb6u04zg0ubyRqfTuay/mWAvS\nY3GgqhvHq7qwbB49VBw+K78Ai9WGTflKaDT6Oe/vKkW0EPfsyMabXzTgiVfL8X/uWYkwARf/3Ndg\nv/pcleST1upCBrjhqlTccNX8+t98fqIDuw+34slXy/HLu4vmvGJb6Dk92zaIVz6ux7jRgq0rk3BH\naQbMEyaoJ0zzfi5v8ObFRVdXF8RiMZRKe8BbUlKC8vJytwUuDMPgppJ0PPdOJb463Y1vb1v8Piz7\nTnYBsOeHBAMe196Z98OjbThW04vtaxbXkI5lWby9txEDWgOuW5eC5Utj3DTSK61fbg9cyur6PRq4\nmC1WnDw/AEmkAMtS3buX2mIreT480gqLlcWtm5e6rdFkYUYMREIeyuv7cWtJuttny+ZrzsAlPj4e\nO3fuBACkpKQgNjYWKpUKycmB90f6aZk9t+X6DUv8PrdlqqIse+BS3aSZd+Bis7E4XN0LIZ/rkdyJ\nTQUJ6FGP4avTXXhlTz1KChLQ0j2C1TlxSPKDKcX5uG5tCno1Yyir68ebXzTg369f5tb8A5Zl8fmJ\nDnx4xJ7P8m87c3F1fmjms8w0i3t5YzqZTIaurq45n28+M71SWQRixfU4frYP37s5f1FdaPsHx1DV\nrEZ6khgbipP9Kl8FWHjQees12fi0vAMHz/TizmtzwV1Erti+ig6cOKdCdqoU37/Fc92v5fIoyOVR\nyE6R4lz7EDgCHmLEnunpcuxMDwxGC3auz0B8vHtn7uXyKKQlRKO2dRCCcAHE08xOzXReGzuGcPL8\nADKTJfjGxgy3BhibipPwZfkF9AxPoDjbPTk9CzVn4LJnzx6o1Wrcf//9UKvVGBwcRHy855sTuduA\ndhzldSokxEa4LZHKW7KSJRAJeahuUePubZnz+nCsbR3EoG4CmwsTPLaPx+2l6egbGkNt66Cz2+ds\nO0D7K4ZhcN+12faqs3P298o33ZSjYzRZ8ZfPz+NUw0BI5bNMZ76zuK6Y70zvluJEvH+oFR8eaFxU\nZ+r39jeBZe25Y+6czXSHxc5or1+uwOHqHuwra1/wZ2aPWo9XPqyFSMjD/TtzoB0aW/B4ZjP1WNfk\nyNHYqcVnx1o9tl3Kl2XtAIDCpVduCOkOa3Pi0N6rw+fHWq9IiJ3pvLIsi1c+rAUA3LIxDYOD7n0/\nFqfH4MvyC/ji6zYkyzzf5G+2oHvO0Le0tBSnTp3C3XffjR//+Md48sknF/UB4yuflnVMVhIF1mwL\nYJ+6LciIwZDOiE7V/N6MB6vtSbmb3ZCUOxMuh4Mf3rAcyhgRzBYbNhQkBNxsiwOfx8WDt+QjJlqI\nD4+2obJx/o3gLjcwbMDv3z6NUw0DyEwS4zffWR2yQQtwcRaXYZhLZnEBIC4uDhqNxnlflUqFuDj3\nX2iUFCRAyOdi/+luWKy2BT3H+IQFx2r7IIkULKrc1F9tW2XPj9h3au4Zr+kYzVa8/HE9TBYbvrsz\nF7Eemv243OrcePC4DMrO9rvcU2c+RvRG1LUNIVUR5bFE1bV5CnAYBscn90ByRVWTBs3dIyjKjEV2\ninTuB8xTemI04qXhqGpSw2C0uP3552POwCUyMhIvv/wy/vGPf+D9999HSUmJN8blVgNa+w7QgTjb\n4lCUaV/rnE9HVZV2HHVtQ8hIEnu8C6cojIef3laArcVJuP/65R59LU8TRwjw0K35EPK5eO3TenSq\nFn5FVd8+hN++eQrd6jFsKUrEL+4qctv2DYFqz549eOONNwDgilncpKQk6PV6dHd3w2Kx4NChQ7MW\nAyyUKMze9+f/tXfnUVGe9wLHv+/MsO8yLAKCCsgmCKioGCVuUWyTaGyDkqDpze05aWOSZjmtN70n\n9tSqJ7netNqcNlGTtFfvtaSkJzUxqaiVmqhBRQKCC4tRWWSVRWDYZub+gRAXkEFm5mVmns9fnplx\n5nkZeN7nfd7f0nSz64EXp8cKqunq1rJoetCYT7t/EOO9XYgL9aasqoXyqpYR//99h0upamhnUWKQ\nWTM4XZ3smBampqqhfcQXeob4+nwtOr3eKLVbhtKfyXO15iZV9cMfQ69Wx19zylAqJJMFz0q3mkF2\n9+o4c7HOJJ9hKOv7axvEZyctd7elX8ykcaiUCvJLDZ9kc/KrAFiYaLrdltv5eDrx1CNT8PEyb68Q\nUwj2c+PHj0bT3aNjx8eFtLSNrLCYXq/ni9yrvP3RN3T1aHkmNZKMpRFWeYIbqcF2cT/77DMOHToE\nwK9+9SteffVVnnrqKZYvX86kScYpYHi3JTOCkIDs09dGfGWu1ek4kleBvZ1i0DpG1qI/4Hikuy65\n52s5VlBNsK8rTy4cXR2RBzH3Vjxff+aPMZ0oqkGpkJgVbdqQibmx4wc+bzg5+VXUNWlIMXEblDkx\n/gaPyZQst+CAgeqaNZw4d2u3ReaAotFwclARPdGLwvJGg9I4u3q0fFV4HXdnO6ZPsdzjllPiFB9W\npUzm439d5p2/nePn6QkGRel3dWv58IsLA1kHzz8RS2iAacqnW6L+XdyhzJw5k8zMTJOPw9fLmfhw\nNfmlfSXuw4MMr+uSd6mextYuFiQGjiq4d6yLCvEiyMeVvEv1NLRoDLrdU9vUwZ//cREHOyXPrZhq\ntMyWkZg6eRxuznbknq/lyQVhRrtguFZ7k4q6NhLC1UZpVXA/hmbydHT2sP/4FRztlTz2kGkW+f3U\nnk5EBnty8Voz9c2aUbc5eFCyXf7VNWuovWF4QN2D6s8kemzuRNlTuEYrcUrfdmt+acMwr4RTF2pp\n7+xlfnyAxffwkdPy2SHMjvGjvLqVP31xcdgr8/pmDZv35HHqQh1hgR5sfGamWLSMYUtvpfr2pzQb\nKvt0BRJ9jQmtmSRJLE2agE6v50he5bCv7+nt64/T2a1l7bII2ZqgqpR91bVvdvRw7nKj0d63f6fB\nHNWt7VRKkqJ8aW7r5vzVG0O+7sDJq7RpevjenBCz9BLqbybZ3+5ADrKd0d77ezEv/fdRrjeaJsoc\nvtttGe/tbNG7Lf2mhamRMGzhcvRsFZIEKdOsdxvbHCRJ4kepkUwOcOdkcS1f5F4b8rXFV27w6z+d\nprK+jYcTAvl5esKgqYzC2BEe5EGIvxtnS+upa9YY9H/Kqlq4XN3KtDC11XUnH0xSlB/uLvYcK6ge\nNigzK6ecqzU3eSh2/MBtBbn03y4y1m0NrU7H18U1uDiqiAs1XS2a2/UvkPo7UN+toVnDoTOVjHN3\nMNsiekaEL/Z2Ck4UmSb42RCyLVwWzwiivbOX7VmFtGl6TPIZB07c1pPIwndboC9gKzTQg9LKZlo7\nhi5Wdrm6lSs1N4kPU+PtIU+nWWtip1LywhOxeLk58HFO+T1xRnq9nn/kXuPtzG/o7NayblkEa0U8\ni0WQJImlMyeg18PhM4btumSf6lu8WkvBueHYqRQsSgxE09V3+3ko+aX1HDpTwXhvZ6MU9hutYD9X\nAn1cKChrMMo5pujyDVo7epgV7We2XezhMnn+duwyvVodq+aHmq0zvJODiulTfKhr0lD2AEHbxiDb\nzDonxp8fLgqnrknDHz8peuCUxKHUNWs4UdS322JNqYoJU9To9VBQNvSuy0BfokTjlHsWwMPVgRdX\nxWFnp2Dn/vNU1PVF+nf1aNn56Xk+OlqGu4s9v3gq0aqDNa3RjEhfvNwc+LLwOh2d999RaGjWkFdS\nT7CvKxHB5ulAPBY8nBCInUrBoTMV6HT3XmXfaO3kgwMXsFMp+MnjU3GwN39cy936s2B6tXpOX6gd\n9fv179z0B82aw/0yeb693srX52sJ8XNjVox5a6slG3k3a6RkvSR8elkUCeFqLlxtYt/hUqO+94ET\nV9DqblXJtYLdln6Jt9Ki80sGX7jc7Ogm90Idfl5ORE00fi6/LQvxd+PH34+mq0fLjqwCSq41sXVP\nHrnnawkNdOeNdTMJCxTxLIZ46623SEtLY9WqVWRnZ9/x3MKFC0lPTycjI4OMjIyBGi+molIqWDQ9\niK5uLccKqu/72sN5lej1fc0Ux1qVXFNyc7Yneao/DS2d9+w4anU63t1fTHtnL2sWhRNkpialhpgT\n448kMaJ6KINp7+whv7SB8d7OTPQ3b3+9/ltutx+DXq/no3+WAfDkwjCzZ8tGhXjh5ebAqQt1NN0c\nWcalMci6cFEoJH78aDRBPq4cza8yKPjLEFW3yraP93YmKdLyqvzej984ZwLULhRfuUFXt/ae5786\nd51erY4FCYEWm/o9lk2P8GXlvEk0tnbx6vZjXKtrIyU+gJ+vScTLhpokjsbXX39NaWkpmZmZ7N69\nmy1bttzzml27drFnzx727NljlkrdKfEB2NspOJJXgVY3+O6vpquXYwXVeLjakxRlXfOKIfpjKO5O\njf77V98OtPlIiQ+QY2hD8nR1IGbSOC5Xt44qnvL0hTp6tTqSp/qbfcHan8lTUtGXyQPwTVkDlyqa\niQ9TExVi/gtUhUJiyYwJaLp62bInz6SxqoN+vlk/bRCO9ipe/EEs7s527DtcSvG3Q0dPG+Lc5Ua2\n7slDq9OzYt5kq9pt6ZcQrqanV0fxlTt/Vjq9nqNnq7BXKZhroz1wzOH7yROZE+OPSqlg7dII1i2L\nFJlbIzBz5ky2b98OgLu7OxqNBq323kW4Obk42vFQ7HgaW4cuSPdlQTWd3VoWJVpnwbnhBKhdiJ3s\nTWllC99ebwX6AtIPnLiKj6cj65ZFjsldqOSpo689cqKoBglkCzgeyOQpqukrNne0HIUk8YOHzV8j\np9/SpAmsnD+ZxtZOtu49S3m1+eJdxsRfn9rDifVPxKFQwB8/KaLmAdKk9Xo9B05e4XcfFdDdq+Pf\nlkdZVWzL7QbSou+qolt0uZGGlk5mRfvh4mi9tSXkJkkS//79KPZtSjVpKwVrpVQqcXbuy8bJyspi\n/vz5KJV3xkRs3LiRNWvWsG3bNrNlLiyZMQEJODRIsTWtTsfhvErsVQqb/s5vL0jX0t7Nrk/Po1BI\nPPf4VJP1QhutxHAfnByUnCyuQfcAv0u1Nzooq2ohaqIX49zlSXa4PZPn4Mkr1NzoICU+gAC1iyzj\ngb558NHkiTyTGkl7Zw//tS+fwnLjpZ7fz5j5TQsL8mDdskjeP3CB7VmF/Ofa6QaffDu7e/ng84uc\nsZEGdiH+bni62vNNWQNanQ6lom/9+c+z/ZVyRVCuqUmShKODCuO3V7Mdhw8fJisriw8++OCOx198\n8UXmzZuHh4cHzz//PAcPHmTZsmX3fa+RdIeGwRu4+fi4kRTjT25xDY3tPUTe1on9eEE1DS2dpM6Z\nyKTgkXVol9ODdoceSoralax/lXP6Yh0t7d20tnfz7GMxJMXJv5i737E+NC2QQ6euUdPSxbTwkbUf\nOHgrhGFZ8iSj/zxHIjkugJy8Sj74tBgnByU/enwqXm7yZ42uWhzBhPEevPk/p9nxcSEvPhnPopnB\nJv3MMbNwgb5o7eqGdr7IvcYfPyni5SenDZyUh1LXrOGdjwuprG9nSpAHP1kZa/W9YBSSREK4D0fz\nqyitaCEyxIv6Zg3nyhsJDXAnxMzBY4IwUl9++SXvvvsuu3fvxs3tzt/XFStWDPx7/vz5lJSUDLtw\nGWl36KE6+qbEjSe3uIbMQ5f46Yrvem5lHSkB4KGpfibpBmwKo+0OPZSFCYF8+MVFLl5tIi7Um+Qo\nX9l/JsMd6/RwNYdOXePzry4T4Gn4yb5N08Ph3Gs42CsJ9zfNz9NQ08PU5ORV0t2rY2XyZHo7e6jv\nNE0pkZGa5OvCa6sT2J5VwO/+kk9VTSvLZgWP6tbhqLpDm9uqlFDiw9Scv9LEXw6X3fe1Rd82DjSw\nW5gYyGs21MAuYYoagLO3Ivxz8qvQAwvM1JdIEB7UzZs3eeutt3jvvffw9PS857lnn32W7u6+OkWn\nT58mPDzcbGOLCPYk2M+VvEt1NNwKhCyvbqGsqoW4UG/Ge8u3NT9WzI7xw8vNAS83B579XtSYjGu5\nW1iQB2oPR/Iu1dPZPXxn47qmDvZmX+K1PxynsbWTOdF+sqd4R4V44ePpiI+X05isIRQW5MGGp6fj\n5ebAX3PK+cuRsge6NWeIMbXjAt9lGm3Zm8eRs5UE+Liw4K57ynq9nn+cukZWTjlKRV9l03nTxlY0\nu6lFBnvh5KAkv6SBH6SE8mXhdVyd7Kw2rkewHp9//jlNTU387Gc/G3hs1qxZREREsGTJEubPn09a\nWhoODg5ER0cPu9tiTJIk8cjMCez+7AKH8ypZvSh8IOZlLJ4s5GCnUvLGuhkoFJLJ+/UYi+JWPZT9\nx6+Qd6l+yFosZZUtHDx1jbMl9egBb3cHlsybMCbimhQKiV9mzECtdqVbM3QBUjkFql34ZcZ0fvtR\nAYfOVNDS3sWz34s2evKCQQuXLVu2UFBQgCRJvP7668TFxRl1EHdzclDx0qo4fv3nM/xvdgn+Xk5E\n3brfLBrY9VEpFcSFqsk9X8vfjl2mTdND6uxgWRqaCcJIpKWlkZaWNuTz69atY926dWYc0Z2Sovz4\na045xwqqeSh2PGcu1hPk4ypL2ulYZYmtLJJjx7P/+BVOFNXcsXDR6fScLann4OlrlFf1ZUuF+Lux\nLCmYGZE+w4YrmJO7iz0erg7Uj9GFC8A4d0c2PJ3IjqxCTl2o42ZHD+ufiMXJwXj7JMN+I6dOneLq\n1atkZmayefNmNm/ebLQPvx+1pxPrn4hFkuAPnxRR29RBfbOGLXtvNbALEg3sEsL7bhf1N3xbICq2\nCsKoqZQKFiUG0dmt5XdZBej0eh6ZaVsF56yRr6cT4UEeXLzaRGNLJ13dWo7kVfIfO0/yh0+KKK9q\nJT5MzS/SE3hj3QxmRfuNqUWLJXFxtOPVtPiBArNv/t9ZWtqNt9gadgl08uRJFi9eDEBoaCgtLS20\ntbXh6mr66ohTJniydlkEH35+kd9mFtDe2UN7Zy8PJwSSvjjcJmsp3C52sjdKhYRWpycu1Bu1TC3G\nBcHaPJwQyGcnrnCjtQt3F3tmRdtewTlrNDd2PKWVLez6tJiqhnbaO3tRKRWkxAfwyMwJIobJiOzt\nlPx05VT2Zpfwr2+q2bLnDK+kxePnNfrGpMOe+RsaGvDy+m6LdNy4cdTXD16gyRTmxQWwNGkCdc0a\nunq0PJMaKRrY3eLkoBoo679ApEALgtG4OtkN3E5YlBgoCgxaiRkRvtipFJRUtiBJEo/Nnci2nyaz\nblmkWLSYgFLRV6TzsbkTqW/u62dlDCO+6TRcMShj1FO4209+mMCkQE8iQsYRNsFyG5uZogbA8z+M\n51x5IwtnhYyprWw56x2Yk60cpy1aOX8yag9HFk4XFwXWwtlRxfMrp9LS3s2sKD+zdVS2ZZIksWLe\nZIL93FApjXOOGnbh4uvrS0PDdw396urq8PEZuoCPseop3C0pou8z5a4X8KBMVVPBQYIZYd40NLQZ\n/fR2b2cAAAPPSURBVL0flKmOdayxpeO0Ra5OdqTODpF7GIKRxYWq5R6CTeqv+G4Mkn6YLZSzZ8/y\n+9//ng8//JDi4mJ+85vfsG/fPqMNQBAEQRAEwVDD7rgkJiYSExPD6tWrkSSJjRs3mmNcgiAIgiAI\n9xh2x0UQBEEQBGGsEKHygiAIgiBYDLFwEQRBEATBYoiFiyAIgiAIFkMsXARBEARBsBiyLVy2bNlC\nWloaq1evprCwUK5hmFRubi6zZ88mIyODjIwMNm3aJPeQTKKkpITFixezd+9eAK5fv05GRgbp6em8\n9NJLdHeP3YZgI3H3cW7YsIFHH3104PvNycmRd4DCfdnCnAO2Me/YypwDYt4ZjPHaNY7A7Y0by8vL\nef3118nMzJRjKCaXlJTEjh075B6GyXR0dLBp0ybmzJkz8NiOHTtIT08nNTWVt99+m6ysLNLT02Uc\n5egNdpwAr7zyCgsWLJBpVIKhbGnOAeued2xlzgEx7wxFlh2XoRo3CpbH3t6eXbt24evrO/BYbm4u\nixYtAmDBggWcPHlSruEZzWDHKVgOMedYD1uZc0DMO0ORZeEid+NGcyorK+O5555jzZo1HD9+XO7h\nGJ1KpcLR0fGOxzQaDfb29gB4e3tbxXc72HEC7N27l7Vr1/Lyyy9z48YNGUYmGMKW5hyw7nnHVuYc\nEPPOUGS5VXQ3a62BN3HiRNavX09qaioVFRWsXbuW7OzsgT8wW2Ct3y3A448/jqenJ1FRUezcuZN3\n3nmHN954Q+5hCQaw5t9LW593rPm7BTHvgEw7LiNt3Gip/Pz8WL58OZIkERwcjFqtpra2Vu5hmZyz\nszOdnZ0A1NbWWu0255w5c4iKigJg4cKFlJSUyDwiYSi2MueAbc47tjLngJh3QKaFy9y5czl48CAA\nxcXF+Pr64urqKsdQTGr//v28//77ANTX19PY2Iifn5/MozK95OTkge83OzubefPmyTwi03jhhReo\nqKgA+u6xh4eHyzwiYSi2MueAbc47tjLngJh3QMZeRdu2bePMmTMDjRsjIyPlGIZJtbW18dprr9Ha\n2kpPTw/r168nJSVF7mEZVVFREW+++SZVVVWoVCr8/PzYtm0bGzZsoKuri4CAALZu3YqdnZ3cQx2V\nwY7z6aefZufOnTg5OeHs7MzWrVvx9vaWe6jCEGxhzgHrn3dsZc4BMe8MRTRZFARBEATBYojKuYIg\nCIIgWAyxcBEEQRAEwWKIhYsgCIIgCBZDLFwEQRAEQbAYYuEiCIIgCILFEAsXQRAEQRAshli4CIIg\nCIJgMcTCRRAEQRAEi/H/IcpOSw4lrGAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f6c9aca59d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "fllyxKu8edm6"
      },
      "cell_type": "markdown",
      "source": [
        "## Plot styles\n",
        "\n",
        "Colaboratory charts use [Seaborn's](https://seaborn.pydata.org) custom styling by default. To customize styling further please see the [matplotlib docs](https://matplotlib.org/users/style_sheets.html)."
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "Xn0jLwr8evoR"
      },
      "cell_type": "markdown",
      "source": [
        "## 3D Graphs"
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "DrRCtocXe9SB"
      },
      "cell_type": "markdown",
      "source": [
        "### 3D Scatter Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "Eo2bdDQ5GZ76",
        "outputId": "7aceedf3-d92f-464c-b22c-34b34adb3e12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 401
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from mpl_toolkits.mplot3d import axes3d\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(111, projection = '3d')\n",
        "\n",
        "x1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
        "y1 = np.random.randint(10, size=10)\n",
        "z1 = np.random.randint(10, size=10)\n",
        "\n",
        "x2 = [-1, -2, -3, -4, -5, -6, -7, -8, -9, -10]\n",
        "y2 = np.random.randint(-10, 0, size=10)\n",
        "z2 = np.random.randint(10, size=10)\n",
        "\n",
        "ax.scatter(x1, y1, z1, c='b', marker='o', label='blue')\n",
        "ax.scatter(x2, y2, z2, c='g', marker='D', label='green')\n",
        "\n",
        "ax.set_xlabel('x axis')\n",
        "ax.set_ylabel('y axis')\n",
        "ax.set_zlabel('z axis')\n",
        "plt.title(\"3D Scatter Plot Example\")\n",
        "plt.legend()\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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oWhA3gn2diqGpZ6MvFjKFBy1L4UAPGcIfOLnfybICWS6Nzxk7tgeZTBaCwCMS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\nIxYrfz6V3lPGXAfEnCan8CKHFHyxWLxkr6VcnRyv111y4XGx3RLjkE5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4ympiYsWDAf//nPZ7jjjr+gS5euJTmqTCnaqWnjynFyaGuLoK0t4phRSSk9ZYxCAbM59yYSCYii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\nv1EwCkbBKBjyAACdDQIhJySz+gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f6c98bf9b50>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "MXVPkFpTfCE-"
      },
      "cell_type": "markdown",
      "source": [
        "### 3D Bar Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "YGi1XPCrGsQz",
        "outputId": "a6cfb9a4-8e96-47e4-9f51-8629508590d8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 401
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(111, projection = '3d')\n",
        "\n",
        "x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
        "y = np.random.randint(10, size=10)\n",
        "z = np.zeros(10)\n",
        "\n",
        "dx = np.ones(10)\n",
        "dy = np.ones(10)\n",
        "dz = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
        "\n",
        "ax.bar3d(x, y, z, dx, dy, dz, color='g')\n",
        "\n",
        "ax.set_xlabel('x axis')\n",
        "ax.set_ylabel('y axis')\n",
        "ax.set_zlabel('z axis')\n",
        "plt.title(\"3D Bar Chart Example\")\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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I0BCEA44DhoZUlErlhjv5ViFT6Hin749BiKFJJo1Cp45dQ2d0dKiWdSWKQgA1dEjoEESc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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f6c9b4ead90>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "Xbey0KVpfIbQ"
      },
      "cell_type": "markdown",
      "source": [
        "### Wireframe Plots"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "60f2SO4jIfQz",
        "outputId": "3600f6d7-501d-4144-9c99-6b8f807b0d5c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 401
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "fig = plt.figure()\n",
        "ax = fig.add_subplot(111, projection = '3d')\n",
        "\n",
        "x, y, z = axes3d.get_test_data()\n",
        "\n",
        "ax.plot_wireframe(x, y, z, rstride = 2, cstride = 2)\n",
        "\n",
        "plt.title(\"Wireframe Plot Example\")\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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jHaM8ERojtaSkBxAmbJsqISWZRMjEYgnd6EeiIRPdu/KG3mJMyJnRnKlbXmrX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lN65r\n5sCpMXZ3jKLIEpZpsevoqPsaumHw2e/uwaPKJDJF1iyq5opl9ZzoiXJyIMHCpjB/946ryOR0Pv5f\nLyBLFu/IHX8TAAAgAElEQVR63UriySyPvtDPRKqA16PQ3hWjvSvmvu5nvrOf2kov/aMZ2ppCVAY1\nxuIiHbm1PsjmVfXkCzpP7xsi4FW4+YpGFFli5xGxn3942yKqw1722H4kH7pnNQ3Vfv7jp4eJp2N8\n9l1XUlvh5d9+3E7nYJJPvHU9QZ/KF/7nMMlMkX9450ZUVeav79tNU02AT//pBk4OJDjcfYhNK+pY\nvbCKXz7fC8DKBUI9caI/gc+jCIBoL6BL7BwfJzRxSUsYyxIy+Hn1ASKxHAV79LhpRS1dQym3y3Wh\nNZOFZabf9ETmwm9wwn6VgE911WZeTTjyTpWcl5bfo2CYlksqLr00TQVYfq9ij1vPjTenGxb/5z9e\nIOAVi6luWvSMpFi/pMbld61eWEXQp7Ln+Bh3bm7lN7sGxB9bsLdUvu0RgB/6MEzrjIDVtOC7vznG\n1SvqeHI3LGwMsrw1zCMv9PPI9h6uXyvypZbPr6JvJEUqKwz4ntjVy+2bmjBN65IENZdHTrNTlwHN\neZQDZHR9ZnyOl7vOJ8toruXhUwGT6Bx50DSVXK5AOn1huVCWZfHMngG+/cgR9265OqxhWR6GxjIo\nssQVS2vRTZOjXRNkbe5QNm/w8I5e93UWNYe5bk0j7V0THDw1Rl2lj+vWNtEzkuTQqTH3gvv8wWGe\nPyhm9h5NprbCx8hEhgMnx/BoMp96+1XMawjyrz/cT0dvjNULq6gIejneG2M8KRbhw10TfODfnhHH\nA1jYFOJw1zjbD42Qzum89dXL2LyqgZ2Hh5hIFVi3uJoP/sFqBqNp/vEHB5ElYZXfH0m7zrM9wyk+\n8Q0BmgzTYn5jmJMDCQZHUyQzRV59dQs+j8qpQSH3vWpFLdVhL5GJLMf6EqxYUElDtZ9YqsDRnhiL\nm8M0VvuJpfLiDnleBYuawwxGBYH6yuW11Fb6OHBqHN2wWLdYWPkfsbOKVi8Uj4/1xZEkWD6/kngq\nz/B4lrWLqlBkie5hO5ix2QE0aQI+lZoKDw9uEQ67/aMZQn6VoE8lk9N5z++t4MWOKN98+Dhvvm0R\nm1bW8SnbpbY65GE0npvzDsiFlgQEbbdbpzRVoqhbNvdlEhhNBSSKLFEV9jBWklI9dbQmS+J5TodE\ns2MK8kWzbCw0XWkqTNd8zuQn/ZA+94ODZb8bHs9QVyWIyHtt0rzfI3hCVSEN3bBIZXU6B1N8+cHD\neDWZA6fGsSxhBOiouK5dXccLR6LsOhql0/a92XdijH96z1Xs6ogyGsuxvV10iY71xvibP17H5+4/\niGUJtVNHb4rr1rcIo8Ciga6LnCRd12fVkuJil7hOX6IumBe5LgOal6ipJnM+n3ChPZMvS2kg4tzv\n00sTdj0eDb///IDXXHdoHMDk5EJ5PJ5ZU4MlMwW+8JOD7D8RxavJrF5YTTo3SfwFwTnYezzqkjUX\nt4R55VWtHO6eYIejDFFkuobKU4e9HoVoPMeJvjiWBX9y53KWtFTy0HNd7D0utmdZQk3ilCJL/PCJ\nE0hAR2+MNYuq+as/2kA8VeBv7tuJR5V5z+tXk8oWeOLFAQajaSxgy/4htuwXd7maKhOJZdl3IsrP\ntnYjS/CmWxcCsL19lKJu8ubbFvHKq1o41hfn337czpKWMBuX1XBiIMkB2w/khfZhXmifJCenszp7\njkVdddZN68Qd7q4O0Z25fo0wStt7XIC3zauFkda+4+NYwFUrxOMDp8Trb1gq0qDbOwWp2lG1HO2J\nIUmiI1PUTbqGkixoCBLwqa5h2yIbwDjBhYuaQmRyOqOxHK11AT73g4MuyXTDshredvsSPn7fbuY3\nBJEliUF7RNFSF8CjyuQKBmsWVvHhe9fw3cdOsO1QhLamID3D4jX8XgXDsM4qi77YVQpmQPjCzKQM\n0yoDM2cq0wKzZMQ0lZfk1YSPUDp35uNxvpP07e2TXcmRiRyKLNFQ7aNnJE0sVXSX4qBPQVXkMhn6\ndWvqeWzXID6Pwp/euYyO3gSpbJHxpBgNR+N59p8cZ/OqOh7Z0c+ahVVu0Odvdw9y/ZoGttmcoCd3\ndbOkyYeiyKiqiqap+P1eVDWILEvougNyxP91Xb8oVgOzIb6Y+zic3426DGhmUM6Jb5qmTZ49892M\ns0jPdUvTMfGbbjOl+3v+hnhnHgnNZgnzvuAF50KV1oGTUb71cAexlOB/5YsmR7on3OM1vyHI5lUN\ndPTGONI14XIDOgeTdA52AAKA3Li+mRvWN/HzrV109EwIqXHYR+9wkoHRSeXGQ891Ux320j2UpDrs\n5TPvvIqgT+Oz39tDz3CKxc0VFA2TY72TI6EjXRP843f3kMgUSed03nbHMq5Z3UBHzwSD0TTzG0L8\n9R9voHMo4b4X0zT57a5+fmubmVWFPOw/Mc7iliLP7BuiKuTh5iuaAHhsp2jp33vrIpa0hPHsHeLA\nyXFefXUL65Y1suPggEv83NYecS/4sgQ7DkeITGR5/tAIqiKxcZkAKHvt8dOVy2oBONg5BcB0TSAB\naxdNAhivJrO4OUyhaNA1lGJBY0i4yvYn0A2LpfMqADjeK8DPYnvE1D2cIuBT8XsVfv5cNyBIypL9\nvmOpAm+7fYnr/9NSK0zahsYEoGmuDbgRAU22AaFjRtcznKa1LsBANMPvXT+f2ze18rGv7UJTZf7i\nDav4wROnODmQpLbSSyZXJJu/eGDn5W4gCdPEs5CWFRHVcbYxl1MVfpVE9swIyDDLzfucLaZzBtes\nqiaZLnCkVxCMH9sl1FWFokFRt7hyeS1P7x3i7Xcs4am9QwyMZvivhzq4drWIRPB6FN52+xJ+8MQp\ndh2NuueU36uw/+Q46WyRoF/DMArk85McUUmSUFUFTRNAJxDwoaoKhmGUAZxi0Zj1jrwsXzpq0t/1\nugxoXqLC4YBQgcwgF2hyTDPXJ+eZt6NpCj6fIEydTyhj2RbmcOTk8QjAJUmSHVNw4ReIbF7ngSdO\nsNXuaCybX8ny+ZUcODFG/+hk16cvkqYv0gUI4HLTFU0sn1/F47v66BlOuR2brfsH2bpfXEyDPpUb\n1zczvyHIA0+cJJYqcM2aRizTor1rnG67gzORzPPpb+3G51EYHs9y1Yo6PnjPOpKZIp/8710k0gWu\nW9PIyESWkwOTMtUHn+nkaE+Mk/1iDPOu160kHPSQSBeJpcTfvPv3VnJyMMV//Hg/+aJBLFXgZ8/2\nuK+xqMZP52CSgF+lvWuCpa0VLufk6X1DqIrEHVe3snB+PQePCwDz3tctpzLk4Zl9w+w+FkWWJXYe\njbLzqAAvsgRffaiDllo/x/sSLGgMUhXykCsYdPTGmVcfpKbCS66gc2ogSVtTiHBAYzyZZ2Qix7rF\n1aiKzLGBOIZpsdwGMM57X9IiHh+zAc2i5jCRWE6Qrv0q//fru13S6soFlfzx7Yv50oNHCAc0KoIe\njttSeiexeng8S8CrUBnU3PTqxho/iXSBbjukcuOyGhY0hBiI9tJQJYjO8XSR1QuraKkP0ljt5+RA\nkk+/6xpi8TR/9y0RoBj0q1QGNAbHsqxbVMVILEtkIo9icx/+NyxHuoFrQ/BSNRXMeGcof3fOPaec\nq5xpwV/91y6uWi46gicHkvz1W9bxka/uwrQsdhwZRZbgwMlx/uSOJWw9OEzvSJrOwaTIfCqI0MoX\njo7yyitbTtuuGEPpp4kUVFWxuzkKgYAfVVWRJOxRleGOrC7kWitJF86fudyhEXUZ0LxEpdPZGaPn\ni5OE7XRmJrejqiKxW5IkstnCrKis5mLkJDpHHkzTIp3OEQz6ZgXMHDg5xn2/PEIqW3Q5FSf64pzo\nE6ZcqiJx5Yo66iv9bDs0TCxVcIHLln1DbNknQFA4oHHvK5fRXBvg6784xFg8T9Cnks7p/HrbJHiY\n3xBi4/J6PIrEvhNRNFXmjs3zGI3l2H8i6naH9h6L8rnv7yWRKRJPFXjTbUt43fVtjE5k+Ztv7AIs\nNq1s4FhvjN0doi0vAQ9u6WTD0lp+va0Hjyrz1jtXUFdbwdYDI+QKBndeM4/bN7Vw4OQ49z9xCsO0\nONYb51hvHM22ib9iWR2qpnK0a5zh8SzXrKqnIuihqBtsbx+hIqCxcXktqiLzmE3S/NTbr0BC4sGt\n3RzqnKAy5OG4/boAvSNpPvyfu6gKCt5DZUjjWG+c0XgOw7Qm+TH28x3C7/F+8dgBNKcGBQBc0hIi\nEsvS0S2k31/52RE67d8lbdWLqkj0jKT549sXUxXyEo3nWWG/rjNiaq0LoBsmkYmcHYYoMWzHAWiq\nzD/ef0Co0EIe3vf6ldz/25OAUF85Sq0Gm+MxGs8hIYDQEzu73fPno/eu4WsPdVAV8vDBe9bw9N4h\nfvRUJ++4axmbV9bxwS/vpCrk4f13r+RXz/e4ZFfJ+Y8tIdaN/x3gxykHkJyvl0/pX+UKpttN3N4e\nwTAtWusC9IykuW5NPTuPRjFMi8/94CBXLq+ldyTNFUuqOdQ54fKnnj0wwm0bm2d8nRZjKINcCaXP\ncYXXNBWv12PbSiinAZxiUZ/R2nEp+X39rtdlQPMSZRjWjL1oZhpQeaHljJxK3X1zufNXBE2/jdl5\nL4qiEAg4naM8um7MCpEtkS7ww9+eYMfhSb6Kpki01AcFD8WCmrCXZKbAriOTc/yQX+PGdY14PQq/\nfbGfbN7AqykkM0W+/esj7vPamkL80auWoioyX/jJQdI5nZBPpS+S4uu/aHefd8O6Jm5c38xYPMeL\nR0cJ+VVuWt/M8f44x/smnYRfODyMZVnsPRYlXzR43+tXccP6ZkbGM3zivp2oikxLfYj2znHa7ZFO\nc22AE30JJMviF1tP4fcq3LG5laBPJZktYpgWv3/jAhY1h9l5ZJTth8UF/2dbOnnyxX4CfpHp9Nob\nFxEKBdh7bJR0TufVtlFeMlPkSHeMBQ1BWutETlE0nkNTZf7hnVdiWhZf/tkRTg0kWbuoishEzk1n\nPtwV43CJumrboRGO98VdSW/PcIoHt3Sz287TOXBqnN3HhHeNLEv87bf3Tcqbi9A5lKS6wst4Is+9\nty7k1Zta+Yfv7cejyjRU+d0uyzy7IzNQwpmJxvMYpkVTzWS3BuAnz3SRswmvG5fVoMgSkZgALXWV\nPg7ZXJ96B9DYeV6dA0ke3dEHwF3XzqOlLsB4Ms/S1gr3eQD1lT5SWZ1cwaCxxk9rXcAl7/q9Ch98\n4yr+5UftrGqr5KNvWstvdvbz82d7+LO7V7B8fgWf+8FBUlmd1163gKGxDNvbR2is8ePVFCITWXIF\nA0WCl9lQ+bzrbLutKTATM/Lpet47S77TOw6PEvarJLM6kViOx3YNICE4Ox++dw1f+B9hYjkYzXBy\nQJDZz7dM06RQMMty4yRJWEU4QMfn86Kqitv5KQU7UykAlxVOs1eXAc0s1ksFVM7mdnw+D4oik8sV\nLthkb65KSLC99n6WA64LOVamZbF13yA/evIkuYJBRVBjxYIqkukix/tixEpIhaoiU1PpY2Q8i6JI\nNFT5GRnP8JjNRQGhprl90zxS2QIPbumiaIfl9Qyn+Pz9+90L6i0bmnn7nSs43hfnSz89SDYv4hK2\nHRpm26FhO2Fb4h13reTqVYIT8/n79+H3qixsCnGsN85Pn+kEJjN6MrkiP3j8BLph8d7Xr+SO6xdz\n4Ngw//Cd3ViW4IV88Sf73bv7WzY2E/JrFIoGT+4exO9RuPXKZgJe1XVqvWWD4NLsPhZlKCq4Cl/+\nnwPcvKHF7Y689uZl1NQE2XWsG8O0uNYm/w6NZRgay7JhaQ0+j0JRN+mPpGms9vGhe9ZgWRZ/fd9u\nMnmDP7xtEZGJHM/sGyJvr0ynBpPueM8hFjv1vO0qDGLc11jtR1MkOodS3LKhiT94RRs/+O0pdiXy\nbFhSg26YDI1lmFcvSJsD9ntprZ8ELT6PQlXIw8FTApg01fixLItTdixBoWC4zrUNNp8mMpGjpsKL\npsqM2gaJ9VU+irpJLFmgrSnE5777osuv2rC0lvFE3nZUFsAnaoch1lf5ysDNE7sHXFfpD9+zxu2Y\nNVY72xbba64N4PdqTCQLLGgM8prNLew5FmV7+wg3r2/kzmsX8K1HjrHtkPArMuzjK0nwzteuoq3B\nz+d+sB9Nlbnzmlbb1XkMVZGoCGhk8jq5GXBdXs4qBTOyJLLRYmeIgChd6s/2vOSUMZeFOEfu+1UH\ntZU+N8Dy6b1DFwRozlSWhTuyymYnydnlBGQfmqYgSVIZwLlwDs3lcZNTlwHNLNZcj5xKpc3Fok48\nnn7pPzrPOt+sJZg079M0xZZgzx7g6hxM8I1fHWEwmnFlp4l0kRdL/F1a6gKsXVRL93CS432THQTJ\nguqwF0WW6B9N49Vk/F6V7qEk//3ro+I5wE3rm7n7pjZePBrhwS1d7sK2Zf8QLxyJYFnCMfWtdyzj\nhrVN7Dg8wo+fPElBN7Gw+MrP2lnSWsGQTWT9yJvWs2JBFacGRBgmiIye7zx6zAYzJotbwly3thGQ\neO7gCLph8Y67VrBiQRVb9w/y2E7RLdiyb4jOwQStdQESmSJ3bG4l4BVBnFv2D+PRZH7/pjaCPpX6\nah8/faabtsYgQ+NZfr5VcIe8msy+IwN41zaxw1Y83Xr1Qhobwmw9JEDItWub0DSVI92j5Ism65cI\n8m8klmM8WeCq5bXcuK6RWKrAb3b2s3ZRFR+6Zw1jiRx/fd8eVi6o5E23LqIvkuY7vznBhqU13H3j\nAo73JfjRU5288eY2Xn11Kz95uovOoRTXrKrH51Hpi6TxeRTqqnwMRTPoxmQy88CoM2IKYpgWI+PZ\nyRGTnfJcV+HlW48ct8M84a/evI4OewTWUOV3+Uer7LHVaEwsPvWVPqJx4WI7EE1T1C3m1QvH57pK\nrzsKq6/y2n+Xw+9RCPlVjvSIhXIskePJPYPIEvi9Kotbwm7as9MBikxMdoei9qjOIS47XaXKkIcf\nP3WS7bbazqNJ3LF5Po/uHGBefYhXXT2PeLpIvmhy5YpG3nzHGroHY+zq2M61axr4kzuWEpnI8slv\n7mXzqjre8/+z995hktT3nf+rOufpNDnP7uxsTrDsAiIKCQQKKFjJsmRZjief5XTWT3cOJ9ln63yO\n0k+2JBSwQBKIJECwsMCyy8LmvLM7Oeee7unpHKvq/vhWVc8sCBYYkHzPfp9Hz6Nepruqq7ur3vX+\nvMN7u8gXyvzB149QF3Dy7h0NzMWz7D05R7Gs4HWayReVX2ivlqLyiiDljf7d0pXJy8sqLo73RRn4\ntwRtdR7qQi5aaty01HqoCTgwrfD5W5aVVxQgW62CzbHZrNhsVkwmE1ar/2V28svMzetblwHNCq63\nCtBcXHRZKJTe8uybN6KhERZsu7GficSby5JZuhLpIvc/N8hL52YrTdhas24sWaBQkg0WYzqaNfQV\nAOta/bTUejjZH+XCaKWjqTbo5MquanrGFukZWzR0NQfOznDg7Iyhf/js7V00VXvYd3qal87OGPP4\nJw+NE08WODsUo1hWuOOaFuqDLl48O2NcRC1miUPdc9htJu55uh9ZUfn9D2+ko97L86emeeKg0OYM\nT6f4yt0n2bWpjmePjdMYdnP91nrMJhNelw1VhWs21pIvypzsjzKuuUQKRZmFVIGJSIZYssB1m2tx\nOyyoqsrBcxHMJokvaEzBj58b5mB3hEJJ4e6nBvnhs0OUyuKCalYKzM0VOXxuBkmCK9fV4PO5GJwR\nQOrqTY24XE76zgqWZWmeDEBXswAIOjOysd1Pc43bEABvWR2kqdptuKva6jyACM0zScJ9VijJzC7k\nWNXgwyRJRpZOU40YhU3H9BGTk/nFVwYDP31p3GBMNrQHWN3k4wUtH6g24CC6WGFWoDI6CvsdhpOr\nVFb53PvX87MXR/A4LTi1dGj9eaqqMp/IUxtwIkmS8d9ODSxQ5baSypYqjIyu0dEKIefiOUJVgh3S\n97lWd2Jpo7x79wySLypIkmjH/urvXEk8VeDRlyZoqfeSTmfp0brGwj4LqVSGkWnxOXS2hKitDdE3\nLRjI1U0BbDYrwxpztr7dzzs211Eoyjx9TDAVf/aJTQD8w33n6J9I8tXfuYJEpsT9e4cZmk7zy7ze\naExGIlPizFCcM0OV84HNYqLab6e1zkN7nZemGjdN1S4ctpW9TKqqSrFYMkZWbrcTk0kilysYbI7b\n7cRqtYgeNgPgyG9agPxG19e+9o+cP9+NJEl84Qt/wrp1G972fbiUdRnQvMZ6PT8WVRXz0JVcr5Tu\n63DY3nKtzusFZ2I/ra/Lgn0puT3FsswzRyd59MVRo09pVaMPm8VE/0TCuMiBCOuqDbmZmEtRKCnG\nbLpnbJH+iYSRPrqxI0i5rNA7tmgAA7vVzB1Xt7BtTYiH9o+IHiUAFe7dM8CGtgBDU0kUFW7a3oDZ\nbObA6Sme0EL4Al4bnY1VbO0MMxHJ0DueoCHkIlcos/fkFHtPCuHtulY/V66txiRJFEsKigrXb2sk\nmytxojfCgMYorWr0USwpSJIorXTZLfzabWtwO6zsPT7B3U8NYDFL7Ds9y4Gzc3hdQiujj5vGIxmm\nolm2dQaN/6aPSf7iM9s4Mxhl78kZSuUysws5/vy7J7myK8zQVJLOJh9quUQsluDYhRnsVhPt9W7M\nZhO9Wl/PO7a34vfaGJ4ZBWBtq7Br6+OW1U0C4AwbAuBKxowkQUutB0VVGZ/L0FjjwW4zG6WILbUC\nwOgjpiZN2zMTyxH02nDYLMwuiAt4fciFoqgGgJxfzLN1dZDTgws0a0AoEs9jkiDosxuaGR1gzCfy\n+FxihPfgfgEur1gT4j1Xt/MfT/QYrzGvHbtwlYNUtkSxpFCtjZ/01/Q4LXzujjX800/OG6+vj5iE\no6pMIlNigwYG9cj+uoCT8bl0paldhfdf08xjByfoaPBitZgMgN5aJ0YlenRAY9hFqVRmaFJ8b4Ju\nibm5GL0jgrFsb/Dh8biIZQRYW9dejcfjYnQoiqpCa60AloqiMjqbpi7kJOhzEPQ5aKx2MzSd5nO3\nd3J+dJEjF+ZRERf+D7yjGZvFzHMnp5ldEGxVoSS/7eGFF5873ozHtFhWmIrmmIrmlmXnBL022uq9\nNFe7aa4R/wt4V+4crLucKgLkyshKMDfCaeVw2LBYXJjNJmZmZvj3f/8mLS0ttLevYtWqtXg8nhXZ\nn4vXqVMnmJyc4Fvf+j6joyP83d99hW996/tvybbe7LoMaFZwrSRD82rpvm8FcHr5urQcmuXhfdnX\nSZHq23j5cxRV5eiFCD96ZoDFdBG71US1X8zBdUsuCDvtuhY/+aJsWJ9BHJ+tnWGcNjOnBqJk82K+\nrqrQMxqnUdNlyIpKUBOiPvzCCI+8MIKKEA7/1vu6mIhkef7kNKcHxcXG47RQH3Jz69VtLCbzHO+b\nx+WwEE8V+ZcHzhnCxPqQi7/6jSuxW808cWjM0M70jC3ypW8e4eqNdTxzbIL6kItff88aLCaJA2dm\nuOvxHiQJXjgzw/G+edrqvKRzJT50fTtuhwAmBzUR9Bc/uYmJSJbdRyaM0cljL41z+65mjmgjuGu1\nKPiFVIGBiSTr2gJ0NvtpqXExMpPm3HCcrauDnB9d5MnD4q4+lStxsj9GY9jJ7EKOLasClEslEoUi\n3UNRqqscWCmRy6n0jsVx2s1sX9+IxWJiZPYsNquJrtYAqqIIK7ndTG3QiayojEfSNIRcmrU9S6Ek\ns6pRgB89NK+pWgc0FdFvtlBmMV00wIDOZtgtJv7+x+eIJgpIEnz+g+tIpIucHlyogIrFPKEqBxaz\nqcLIVDmQFZWFZIHmGjf//MAFUllxx3zrjgbiyTxlWa1oZrTjW7NUM+N3cLA7YoC2P/7oBlJazYEx\nYtIEyNV+hwG+dUZGBzTnRxd58ewcKuCym/nrz23X3t8EDSHxt1MxHdAIYKizV43asZqIiMfN2uNR\nLZww5DGzsJCge1AwYw0hsV8T82LbW7rqCAarGJyIUygphugZBNtms5i4cm2YXRtqaK5x88C+UUqy\nwgP7xqgPOSmVVSxmiW/+2Q1YLSb6R6P8z7tPs6bZR9BjY2Q2TSxRoPw2IZ1X24rDAvlX8E04bCaK\nZRVFUZe1retrIVVkIRXjZH/M+Den3UxzjZv6oJP2ei8ttR7qQ04s5tc/pheA5pUZd0VRKBSUZTpJ\ncY0x097eweDgALt372Z4eAi/P8jq1Z2sWdPFRz/6CdzulQE4J04c47rrbgSgra2dVCpJJpNesddf\nyXUZ0KzgWglAcynpvm+HPfy1Rk5LLdhvNLzv5zE0PaNxvv9kH7MLWXTcVigpzC/mjce6/mUxXTRc\nNCDuwjubqhiPpDnZV7nLqgk4uGFLPfF0kQNnZhjTHDMOm5kruqppq/Xwk33DJDTLdTpX4u7dA6xr\n9ZPKFZEk6GjwMT6b5kfPDHDfc4Moikp7vZf//untzC1keeD5ISORdzFV4MlD47xjcx17T0whSfCb\n71tH3/giL52d4eH9AuBsWR0CrZ9o9+FxJAn+/DNX0DMaZ/fhcWNEVpRlcoUyM7Es/RNJ1rf5aavz\n0lbnZS6e4+mjU9T4HQaNbjZJuBwWNrQLAHCiL4oKXLu5HoB8sUzP2CKNYRef/+A6svky/3h/N+OR\nDDOxHP/+aC92qzg514WE0HYikiFXkLmyK4wsK8STaaajWTa0+VlYWKRQUhifTdHV6sfjdpIrijbz\nLZ1hqnweRqYXKZYUY9yks2MdGqCZ1FiH5hqhmZmOZvG6rHhdVkPMXK+F6Ol/e//zI8YFaG1zFVtW\nBXlgn9AK1fqdZAtlUtkSrRrrsxSMLCSFM2p+MU8mXybksxNLFgj7nYYmp3qJndtmNeF1WY0ah2yh\nzN1PiQRon9tKc43HiACoWaKZCWgCZB3A6EBLB3AHzs4ZgYHr2vz43DZOaBdPPTRQZ2iaa71QzjOl\nacj07UxE0gS9NtxOK6oq+pSCPrvBzo3OprFbTYQ8FtLpLBeGxW8j5JZIp7NGuOHG1TXU1oZIpPNM\nx8/jYAQAACAASURBVLKsbfHj1Gpe9BHZ5+9cy+nBBUPk7bCZGZ9L09HgNRq3d62v5rrNgi38xiM9\nnB5c4C8/vUVUZsyk2H1kelnh5duxLgYzklYFsVQ8ffEuuexmHDYTiUx52f7mCjL9E0n6J5LsPyNu\nMEwmiaDXRkeDj+YaF1tXh4yR6KstkVJ86cdC6BvN3H77e7X3YUJVTUxNTTAwMMDo6DDFYgm3+5Jf\n8lVXLBajq2ut8djvDxCLxS4Dmv/X15sBGq8v3fetT/H9ee9FZN4st2C/+W2IH/P4XIof7hmgZwkD\nYzZBXcBFLFFYRmkXSgqKWjZ0M1azCVlRWEgWOHIhYoAxn9uK02ZhLp4zLnQg7mw7m3yc7IvyzLGK\n42l9W4APXtfKwfMRDpyZMSoM1rb4+dStnfhcNv7hvjOGo2hkJsV3Hu9h14ZaBieTmEwS12ys5fRA\njEdfHOXxl0ZRVHjfta3cuqud915npspzjsdfHEWS4KkjE5zsm6er1c/kfIZbdjSztjVAZ1MVZVnh\npwdGsVlN/OylcfafmiHoE8f+1h2NgIivP9gdwe2w8Fe/vpWRmTQ/em6Y6WiWbL7MNx7p5c7rWjjW\nG0WSYNcGwdh0jyxSllW2acm/NqtgL6qrHPzenV0c7J43aheePjrN2aE4Aa/Ytq6XGdT0MrpjZHg6\niYooDFxcTNGt6Txaa9zIsmKwChs7awmFqogkRHBhe4N4val5IaKuD7koFGWiiYKRZTOrMRQ1fjt7\njk1xXHNQBbw2btpWz4P7xwz3UyRe0a1UAIy4sMwv0bT0jgk2L5Mvc+3GGkZn0zg0oe/ImAAb4Sqh\nmYlqx0aSJGP89NI50RtULKsG0DK2F3BSKC4XIM9p46fagJMTfVFGNFC9a3012zqD/PujfS9PPQ5X\nBNGCpXQyO5dd5v5KpIskMiW2aKnN8XSRVLZkpDznizIzsSydjT6D2R2ZSeNxWghX2SkWS/SMCiBe\n4zWLkdVEElWFrtYAXq8bi8XC8IwQbO/c2MBVG+porfPyw2eGyBdl/uKuo+zaUEsqUzB+LyCC+PrG\nE4Sr7DTXemiu9VAfdvOzQ1Osa6kir6VI+1wWktkyVrP0tomTVZVlbeNLQxL1cXW2IC8r7HTZzbgc\nFpKZ0ssqMxRFJZooEE3Mc7RHmBU+elP7a+7Hmw/WkzCbzbS0tNHS0vYmXufS1i9zZs5lQPMa6/Vp\naF4/oFkOEC4t3fftyLu5mKFZmnmTyxVWJLxPX5F4jof3D3OoW9DuVouJlloPqgoTc6llAt9qv50q\nt53J+Qz5JeV7iqrQ3ljFbCxLJlcyPrdkpkSV207AayeeKhgDrqn5DGVZweuykcyWjBPYhdE443Mp\n/B670b7tslvoHV/kz+86htclRJ9drQHesbGGZ09MceRChCMXxN3qR25s5/3vaKdQlPn6Q+c4q3Uc\nPXdiCq/LzppmL7sPjeH32Pjip7bx3PEp9p6YJHJG2L6v6KpGkiSy+TLPHJvE7bDwv377Kg6cmeFn\nB8eMNONcQYR2nRqIkcqWeNeVDdisZlEm6XcwHc3SWuumeyRuAItVDV58bjuFQsHQa+gXvaHpFLmi\nrI0WPPzKjW4Ods/htJvobPRydjhujHl2H5lgIVUwQEbnRYF5RoWBNvZornGSzeboHRXbDLogmcww\nMi3u5jsaq/A4RQpvXchFoMpD/7g4bnoKsJ5B88iL40aRosdp4a8/d4XhJKrRhLhz8RxOmxmvy2qk\nCdcsEQF7XVYUVbA7+nH5tXev4gtfP0K137nMNVXtt5PJl8kVZaNgUR8xSRJ88pZV3P3U4LIRk769\niiBYHzGJxyf6oga70VTt4nN3rOHZEwLc1WsjpmnNIVcXdFKWFWY1R5fJJDG7kKMsq4a+Z0Jjq1q0\nxzrY1vUxeoeZzowlM0ViyQKbOgLGeWRoKonTZjaOd9+Y+M40hR0sLCRIZopMzafZtCqoZa3YSebE\nBf2z713HC6enOayNQl12YaUHAZxyRZmr1olqAqj0fG1fE+LaTbXct3eYFzSW44Zt9Rw4M4vXZeVj\nN7dxamCB/omk6G56i3wQYuSkLGNgLgYYLocZu81MMl18WSO51aIFJl7EONsslzZ++mUP1guHw8Ri\nlXFbNBolHA7/Avfo56/LgGYF1+txBpnNIt1XqNtfX7rv25N3I1ggk0nC4ahYsFcy8yaWyHH/M308\ne3wSVRW6Fb/HSiSeY2hJNYDbYaGt3ksqW2JiLm3oRawWk9BUSCZ6RuMMGfoZ2NwRoi7k4cj5GSYi\n4gQvSXDFmjBdLX4OnZ9bdmHaub6a67c0cLBbtGanc2UkYGtnmA9d387QdIK7n+w3dBZWs4mGsIc/\n+uhm/uf3jhvpwA/tG2EmlmNdW4BzwwuEqhzctL2Jpw6P8qNn+g0n1Wdv76Ix7ObTt60hmy9xsHsO\nVYX/fe9JrlpXg99rI5Mv85EbOwj6HHzgunZiyQL7Tk2jqCrffKyPrpYqIzTuBk0MnMqWODccp6na\nzZ9/eis9Y4t8f/cA8VSR4ekU3/ppN++9uonu4ThBn924KOrC1k1ameR4JE22IPOOTSE+c1snqVyJ\nL/77MSSTxOxCnoeX1C4c64tSKCkMauCho17vZNJaszXdx/hcBkkStutSqczYbJKg147HaaVvaIZ0\nrsS6Vj9ms4loSvwebDYb39s9ZNjLVVXl5u317D05w+pGnxjlLGE+FFU1yiwlSTLYmmq/0MzENM3M\nvzxwnqhW5vih61rJ5MsUSophy57TwFq4amnOjJ3JSMYYOf32+9YaoZtLXVO6nVt3gOkjppmYACkv\nnosYui2dgTIYGS0YcDom3FB2q5mp+QyyotJULUD+5EVaI310p3+WevlmiwZodDDYqgGaYa2qQ/+c\nUtkSc/E869v8BoMzMJlEAkNTo7Nxq+o9pNNiX0/1RbBaTFy7Mcwd17Rz/7P9PLB3kGxB5sv/cYbP\n3N5F/6R4nj76BDg3UikutVpM/Nq7V3N+ZJFYssCzxwWwu6EzxNbVYbaurlw4VVVlbDbFsydm6Rlf\nJLlCcRCvltdjMUvIsko2L5NdYv122k047VaSmeKyAlEdOH7ylg6jbPW11pvJoXk75AdXXbWL7373\nW9x554fp6+slHA7jcq3QPGuF12VAs4LrUr5cZrMJh+OVw+ZWcjsrsUwmCa/XveIW7HSuxBOHxnjq\n8ASyIliQXEEmnSuRzlVOUh6nFbfTwtxCjvMjFXul32OjPuRiIpLmtKZZAahy21jV6GMykhYiXk3I\n63ZYWN8eZHw2xfG+qKG5sZglNrYHmYikOdQd4VB3xLjDWtfmJxrPcah7jsPdc9isJgolhU0dQRRV\npXs4RvdwDLv27++9poXOZj8PPj9sBO2ZTBK/d+d61jT7eecV9fyfH502QNQTh8YJVTlQFDh0fo76\nkIvP3bGWB/aPcLRH3L3brWZuvqLBOGaHuucIeu38wUc28ND+EQOEBL02qtzijvho7zyyonL1BnFH\nvK7VT5Vb6DOqqxw8d3yS/aemKMsqV64NG9+j8yNxrBYTXc3iAtajjWPWtYoLUSyRpySrXLehhg9f\n38rxvhj3PjOEJMG+U7PsOzVrHNPdRyZpqXUzNJ3C77Hh99g0R1OauqBT3OlmxJhk8yoBoHQBsM0i\n8cjzA+zVtChPHRbAyWySsFpMfP8v3s3IdIK9J2doqvVit9uIaAC3NugknipSllWDFVkanKdrZiLx\nHNmCbGhmaoIO5hOVPBqAuYUsZpNE0Gs32tYdNjP/8uB5FBW8Tgvb14TYc0y412r8DhRVJbKYpz4k\nWJ6lQCsSzzExL1rUN68KsKkjwA+fGTaSjWdiOSRJvIdUtkQqW6JdOzaTUd2+7gJUQ3ujA5hxDbC3\n1LhRVNWwyhdLMmcGFww2TlZURmdTBiBrr18OcHQnWllWGJ5J0xB24XaIS4SeeN2pfT/SuRKT8xm6\nWqpQZQVVVVAVccHf3BHg/Ogif3/vKdwOCyZJ4vor27FbTWSyBXrHEjSEXVT7hTYrnioQSxZor/Mw\nHctSKCnGKHTpkiSJtnofv/neinC5VFY4cGaWg+cjzMSyFF+HFuVSVvmi8ZfLbsZmNZHMlskVlreb\n260m3n9tC7dc0fC6TBsr0eX0Vq5Nm7bQ1bWO3/3d30CSJP74j7/4i96ln7suA5oVXK8GNEwmSauq\nf/Nhc281oNEt2MCKtWCDKJDUgczS+XOuIOzYJe3fdF3MxQDH5bBQKiksposGIwLgsltQUUlkipzs\njxrCYYvZhCQJjcSxnggBr23Z/pRllaHpJDu6qjk3vMB8Im/QxRISn3vvOl7qnuXAmVkKJZELUu13\n8MHrOxidz/Kv952ioEX3p7Ml1jT7+R+f3cGffu1F0rkSiqLyjYe7+eS7OnHaLYxMpwhXOWiq8XB6\nIMpf3HUMn9uKqsKnb1vDmhY/f/u7V/Pl7xzh7FCMQknmb39wit+4Yy3dIwsUSjIfuqGdpmo3f/Dh\n9XztoQucG46zkCryl987ySdv6eDQeVHSt1Oj+OcX84zOptnQ5ue/fng9JwcXufvJXpBVjvdGaanx\nsLEjwOR8lo3tfmxWMwA92kXP6GPSxJ5rmn24nVZD7Hjz9nq2rApyvC/GC2dmkWWV507OLDvOX/zm\nMdxOK4WSQqmscM+eQeIpcTGIxPN86d9eMnJU9K4efd28rZ4r14b4P/d101LjJp1M0q9ZkutDLpxO\nO9FkEZvFxKqWas4MiOfrQGF+icvolCa0zRZkbthSx8hsimS2hM9to09rd9bHSrMLGUI+OyatKgFE\nD1BSY+h0dmSpyHgxXaRUVpakAov/VirL/O0Pz6KqAvh8/s51PHJAALW6kJ5BkyVc5cBqMTGkjeL0\nKgrdot1c7RZjWO1xXdDByEyKvvEEZpPEvzx4XsvnEcfum4/1LTuW33tyYNnjH+wZpCHkIpOvOLOE\noDhDqawsS9Ptm0hgs5ho19g2/fuwVtNTSZJk3HT8+ns6SWZL3PP0IENaOeRDz/Zw685mescTFMsK\nO9bXUV0dQFVVjvaJ0d/Vm+p47MVRHDYzHY2Xxm5YLSZuvqLBAP6qqtI3vsi+07P0jieN9/Zml81i\nQpJerqnR1851YT52c4chwn49S4h6f3kBDcDv/d5//UXvwiWty4DmEtabKWpcmu5bKJTIZN480/FW\nFEfCyy3YPp97RX5oxbLMk4fG2XN0chlAqQs6KZaFkLe0BOCUZdUohVy6svkyTruZsrLcIZUtlA1g\nkC9WhMOyrLChPSjaoKeTxFMCBPk9Nt55ZSOJdJF9p6bZe0rXL7h47zWtHOqepXskbjiMnHYzN21v\n4ERvlL0np3nx7CxIAnRdu6mW4akk+07PcLR3HqvZJGzWN7RTllV2HxrnGw+fx2wS47vf//BGOhp8\nnB2K8c1HzpPIlAw3EUAknuXC6AIhn52NHUH2n57hK3efwGox4XJYuHFbA5KkkivIDEwmqXJbuXZT\nDU8fneYbj/QCsK6liipNw6DrS67oCmM2Sdx8RRMP7xtmMV2gLCvc+8wQVW5xEtYt0aWywuB0isaw\nC5/G/OhalDVavszgdOXxulY/yWyJF87M8qHrW1nd6BOi6rNzhKvsyIpquJKiiYKhlwARiDcXz2HV\n7K67NlSzvtXPIwfGkGWVT9zSwZTWlq6DqBlN3+J3m4nHk0xFUlT7HWSzOUPX09YUoKYmRCxZJOiz\nk8gp/PDZIUCE/v3quzr4w///KOEqO6YlQt9qv0M0cC+xiM9q2qFktsSNW+vYd3r2ZcF8NQGHMdqp\npALnkIDv7R4wxhLb14QMHQxAvcbIpHNlQ3s0taR0EyoW7eYaD/lCiZEZ4Vj6H3edJLdER5ZIl6gP\nuZicz1Ltt7NrfQ2oKo8fmqQu6GTH2jDpfIn9p+cwa86a7iVdXN97coBHDozh0y7KOgMk2Jgs61qq\njCoHXbivA95iSWFgMkFLjdtwpt20vZ6h6RRWs4kH9o1y+MK8oWXqbHARiSxgNps4cl5zhgU9pHNl\nbt3VSjjkN9Jy9VC5S1mSJLG2NWDkIgEkC7D7pVGO9kZe95hK1JnwMgGwvlY1ePnELR2GXumNLKGh\neWMCIUmSkKQ3luj+/+K6DGhWeFUEu6qRmlsJxVupbawsQ/P6HFaXvsqywgunZ3j0xVHjjjzosxPy\nOZhdyBondRAdLY1hN+l8iXiquAzMBLw2rBYz84s5QxAKEPBYCfgcTM5nl52oVjf6aAi7OD+6SPeI\n1nosCQdTlcfGsQsRHlriePI4LUZv0t27e9nQHjTGYCAYpMVUkT/9+GYe2FcZCXmdFq7d0sgf/+oO\nHnyuj/ueHSCrCmfVllUh2ht87Fpfw1fuPiFKBk0Sg5MJ2uq91AYEmLNZTBRLCv/7h6e5+YpGsgWZ\nsqzyKzet4ppNdVy7qY6vPdhNOieAz0wsS3O1k8MXIuSLMu+6soH3X9vCznU1/PMD51lMFxmeSXH4\nQoSd66o53h/DbJLYrol/J+bSRBN5dqwN89Gb2nnspXEOnBUA43hfjLUtfjKFMqWywtpWcbFSVJWB\nySShKrvhstITgSsC4JRx7Fc3+TivMTyfvGUVmzoCPLR/lKeOTvGbd3TSUuvh4RfGOD24wP/3q5u5\nalMzf/Qv+5maz/Drt3VSlhW+/+QAa3SH00WJuksD6ZJaBUBNwEGxWGJiTgAtp1lhemaeWCJPc62H\nv7n7hHFn/Ylb12GxO8jmy3Q2+ZAkyUgQDlfZjQDCsN9BQRvbAFy/pZb1bf6XARqvy4rDZlnmrgLh\nTBI/eYkbt9ay7/SswcjMLuRwOSzLhMuGRXt+OaCZms/gdVq17968IYYP+ex0Nvs4OxTn+s21fOrd\nqzg1sMC/P9rLdZvreM/OJmPfr1oX5n3XtDA+l+b5k7Ncu7GGT9+6mkS6wBe/dQKP00J7vZfBqSRj\nmibn3j1DHO2Zp0ZziOmfBwhAY7eaaNPGVhdGFyjLqjGiBAzG5vc/tI4jF+Z5qTvCRCSDxSzRrL23\ndLbIhVGh+To3IL6H65uFTsdisWCzWXG5nFgsy9usdZBzKTdcrXU+fu22Tj52cxsA0cUcz56Y4Xhf\nlMRrABxVfeVsm9ZaN3de18qGNv+bPhe/0bTjy+vl6zKgWeElknxFP8frSc39RazXcljpwOn17r+i\nqBzsnuXhF0aIatkxNQEniqwQTRaMNmZJEvoCr9PCZDRrUOkAPpeVhrCbyGLO+HsQbElncxULiQJT\n8xkWUuKE5HFa6Gr2E08VGJxKGjoCs0miPuRidiHLhdE4NosJq9VEeQkwKssK776qmXJZYc+xSU5r\nmoOtq0PcdEUDj+wf5WD3HIfPz6GoIsxv65oaDp+b4e/vPcmmjlHmFnKoqmB5ZmJZvvz9E9x+dTNz\nC6IxuavFz0Qkxb17BjjeK8BIsazwXz64gdqgk7se62HvCaHHaKx2s0sLxOto9GE2S5hNEulcma98\n/wTvu7aZYz3zmE0S128RYuBarZTRZjGhqCrffWKAQ+cjjM2m2djux621bh/vFWBsy6ogfo+NT71r\nFcd6o8iywtB0iq/84LTRnWQIVjUL+GZNMKyqKsPTKUJV9mVuFpMEzbXLdR16/ovOMmxoD+BxWllI\nFbCYJdrrvUiSxEwsKyoYTBJT8zlUBHsBMKOzGUvAgNMuXEy6WNXQzMQrLqP5RdHNNDGXxmSSaKvz\nMDqbxmlRmIqI5zXW+KiuDpLIiqLRlvoAJ7VjFPLZ+NZjfeS0hOpffdcqntPcSEtFxvrduQ5oav1O\n9p6cJleUMUnwhx9Zb2i96gLCtTS/mKetzoMkSYaLr2FJi7jZJFEbdHCyP8aCxiy+cGYWn8tKvihz\n49Y6PnlLB3uOCUv9Ou3Cqut92n6OAFgHorpeZn5R6Iq2rwnzyVs6KMsKf/h10fxeG3DSP5E0smVO\nDy4QrrLTXudhLp5nU0fACJI7MyCYQL0SQ1FVzo8s4nVZ6WoRLN7qRi//8fQQZVnlK/ec4VPvWkVO\nA/BbVwc42B3BaTezptm3rBpAX6L/yILVatbarC0oirKs+6hUkl+W3XXxOSzsd/Lxd3bw8Xd2AMIV\n99SRKY73zb+qQNgkCYbt5u0NrG70rshN5S+7w+k/27oMaFZw2e1WTCaRCfD6U3PfvnWpFuxLqSZY\nuhRV5XjvPD9+dpBYIo/JJBl6GD0CHoRGJlzlIFcUYV2z+n6ZJBrCLswmifFIht5xcZcvSQIoVHls\nDE0mObtECByucuBzi66aE/2VgD19xFMqK0xHM7TWeZlbyJEtlKEsTk5Xb6wl5HPw3MkpHnux4tqp\nD7lYTBU4PRhjcj7Drg01RBZzRtqwy27h3Ve18IFrW/jGw92cGxb7s7EjwJ9+fAsXRhf57s96+NlB\nUYvQWuvhv31yC7m8zN27e40x0OpGHzvX1yBJEn/52Sv4028cIpkpMRPN8OShcW6/uoUXTs+QSBe5\n4+oWNnUE+fZjPTz6onjdrauDBqC4MLpIIiNGIu/e0cjduwe4MLrcZQNwoi+CSZLYqIGTkdk0+aLM\n9Ztr2bYmxAP7Ro3U2aGpFGtb/Eadga6pmIvnyOTLhnOlLCuMRzI0Vruxaxqcsdk0fo/NGFlNRNIE\nvDY8TiuyojITy9EQEp/1/GKOYkkxLui6PVzPdjEYmaCoOZhfzNNc49ZcTHq1QMU2bbeacDnM3PvM\noPi+WUx84cPreWDfCFaLCbfDTL/23fI6JCKRGDPRNAGvHbvNzKKW9ts7keaCxjK01Xk0lvDlwXyV\nRGKxL/2TCR45ID6jK7rCrGmu4qmjU9p7qPRQ6YzTUkCjqqKLzO+x8Y/3nzes8CGfnV+7rZPpWJ6f\nPDdoWK7HLrJov8zRpD1fd9zoo8JVmntpYGr5ZzsVFaLcHWvDfOa2TuKpAn9zzxlS2RJjs2m++8QA\nNou4kOsMEsDp/nlsVpPxOhORDMlsias3VBuFj0ntuG5ZFaB7ZJF/ffACIY3xqw26WEgV2bW++uem\n7VbarCv/ZjabjWoAl0v0Hy3923JZfk3QUBtw8pnbVvOZ21ajqmIMd340zkQkQ2PYhaqK31pnk8/Q\nmK3UevNN2299hMd/pnUZ0FzCei3Nis1mweGwI8uK1sVRfMvBzBthTy4WJr+WBfvi4LtX+7uzQzHu\nearfiHoHwdQoVEDRUpCxdNxks5rwe+zEEjnDwQFC8Fdd5SCRKSwrnJQAv9dGOlsimsgTTeSNyHJ9\nW7Ki0lbvw2RSGZ5KGXeuAY+dLauDdI/EeencnBAQax+u/txSWeZTt65hYGKR/adnDGBy264WzGYT\nuw+N8Vd3HaazucoYD1jNJrqH4/zDj8/wm+9bz9Uba43nTc6nee74FLfubOZdVzZxUkvtHZxK8p2f\n9fLp29bw4tlZkpkSm1eFmIik+cneIS6MxJmIpLFZTbxnVws+t42/+e2r+NI3D5PIlOgbT3BueIFN\nHUFe0pqZr9lYQ7XfwZ98fCNf/Kawk+89OUuxpHDbziYGJ5OsbwsY7hV9LLChPcDG9gAdDV7+6OtH\nQJJ46ugUB7srYupKgJ64aOrjpulollK5kgC8eFHQ28WOpkg8R6msGEF445q92xi56BbmUIWhsZgl\nw5UkK+rLyh9rA4Khml/MEfTZ+dcHLxjMwoeua6GrpYr5xbyhmYkYVmwHZVnouDqbfKRSWcZnBNi5\nMLJAc62bibkMDdUegsEqI3ulvSlIrx5GF6ikAlvMEo8cGMdpM5MrynRqwGF2IYfHacHttBq9U0vf\nr545M6zlAeWKMrFkgYawi+lolg9d38q2zjAvdYtW+KWWbJdDBOQpqtbHFHQaDewjMynqQ05c2uc9\nNJXC47RQq+3zxWC1b3x52agkSSS1/qmPv7ODg90Rnj0uwNlTR6cYmUlx1bpqJiJpNmk2bIBzWunj\nxvaKluXs0AKSJETD8VSRu3f3Mx7JIklwvFcIvbevebm76dWWLMvIsgxUTAIv7z8yE1qmyak0Wl+8\nJEliU0fAiC94q9cvu8PpP9u6DGjexFoa/5/J5JFlGbfb8bYg5tcDaCpt3W9EmPzq7+XsUIyH948w\nPF3JjbFaJDxOK4lMCVlRDYZHVtRl4VVWs0RZUSmWlGUMjs1iwmyWyBXkZeWTkiScS6WyQjxVxGEz\nU1ZkVLUSWe6ym+lqDjAxn2ZoKmE8tyHswmYxMzqbYt/pGYJemxGmh6pitUjcurOZQlHmueNTRqeS\ninBXZfNlnjs+yZ3XtfHFX93C1x88z4BmZb3zujZu3NbI95/s5cxgjP/2jYOUZJVqv4M7r2vn/r2D\n/PjZQU4PRJmIZDCZJH73zvU8cXCcA2dmGJxcZCFZxGW38F8/ugVVUfn6A2cM5ucdm+sMpiOVLZHI\nlAhX2VlMF/naQz2884p6Tg8u0Bh2GaAiEs+xmC7S2eQjV5B58VyEM1rI3xVdlWyP8yOLmCQMvczI\ndApFhVu21+G0W9hzbIoxLT9mbC5NrXbRhcrYQmcF9G1PLLERw1JR6/KOJt3FMz6XMj4jqIhw60OC\nsZhbyFETEI3EuhV6aXs1QHVAlEbqFRkzsRzV2thpdZOPTL5MtiCzuknvZqpoZmLJAioVh9N5TShb\nH3Ry+84mvvVYH36Xhfn5OJNzAhA4bGZi2rhzdWs1fr+P2YUcsqJS5baxtTPI/tOz1AadlMoK0UTe\nOF46A9UQrjA0Yb+Dfadm+anGFAa8Nn7nfV3sPzPHdDRrHLuRqQRVbit+j8gpml/Ms75VjJtmolny\nRdn4HHS2RR83LSSFPXrL6qBxIR2cSlLtdxhMn27P1vUyOku6rtVPXdDJnde1cODsLDYVmqtd9C4Z\nSdksJgpFGbvNzNnhBUxSBdAkMyIHaXWTD4/Tisdp5QPvaOXrD/eACmeG4pVcqTe5Lu4/qq4OsrCw\nqAEd0WbtcjmwWMzIsmwwOTqr83aOgC6PnFZ2XQY0b2C9Wvz/W+VAunhd6nZ0C3axWCaZzL6uJtIz\nrwAAIABJREFUH8+rBfgNTyd58PkhI4XWYTNTE3CSK5SJJvLG3B/AZgGHzWpYXvVVklVjJAVgkiQU\nVRWOgnKFMdE5IvH/VSOtd2lScGdzFVaTRP9kgpPaPN9skqgJOIku5piOZnHZxT5G4jlj/xrDbjat\nCvLi2Vl+9pJotbZaRLaMqorR1Lt2NFMfcvDjZ4d44PlhIxwv4LWTzBT46YFREpkiv/OBdfzz/ecY\nmEwY+7RzQw2bV4X4t0e6DWfI7bta2Lm+lu1rqvnhnn72nhS6jFuubMTvEeLs371zPX/4tYOUygqH\nu+dY1xrg+q0NhobjM3esJ+yz80/3nea5E8IlsmNJrswxrRrgus21XNkV5qcvjrHnmHjuYqqIoqrk\n8mVGZlOsavDhsotTgc4e6IzNllUB/uYeYTn+7hMDPHVkymg9163LFwMaXVSqt2a/rHTSKFYUAGZi\nbnlP08xCFqfNTJVbgOJ8UaZuSQowVATC8/E8VosJh83M3ZotWVZUPn5zOxdGF406h+gSRgYwQvXC\nVQ5j7FJd5WDPsSnBMkrwxx/baGS4hP12FEUllhTjrkwmx9i0+DwdZpn79vQgKypWi4m//p2reWCv\n2JfO1hCpbEFzaV3MQLlIZoqkc6In6MH9o1q6rMonb+lgVaOPe58ZwmYVepZUtkg0kTfYg7GLxktD\nFwHNQaP5XLAv/dr3co32eDySNrq59OPWP5mkxu8gqNVcVPKItALRuQzpXJlrNtbw2fd0MhXN8vWH\nLhBLFjjRH6N3PCFqJGbSdDb7DGbo7HAcFaHd0peuK/rg9a08/MIYmzsCKz7SgUr5oywrL2NlLBaz\npsux4PG4sFjMqKq6jMUpl8srZpR4pX17c4Dm8rhp6boMaF7HuhTtydsVevda21ne1v3G9DyvtI3J\nSJqH9g8bOhC/x4bDamY+kTci10EAnLqQU2TGpIoUy0vzZMxYTCaS2dKy4CpFVfE4rWTyorpA/52r\nCI1EKlciV5CN1/I4LHQ0epmJ5Qy2BMQIy2mzkMgUmYllqQ06yeTKpHMlsoUcJgm6WvyUyjKDUymm\no0L/kS+WhcYG0aHznl2tPHpghEcPjBCuchDy2Umki8iKAHrv2tHMplUBvv1oD8+fnOals7MUywqN\n1cLufvDcHFPzGX7vAxuWBW09fXSc+pCLG7Y10FbvA6aRJHj2+BRhv4s7r2/niUPjlMoK122p50Tf\nPHc93sP4fIbnT05S7XewvsWLw27lq//laj7/Dy+QL8q81B3hmi2N1AedHOuNYTFLbF0dxGox8b5r\nWgzg8/jBMYamEmxfE0JVl6e49k2ITBM9IVYX5N6+s4l4usCh82I0YLOYONEfY0dXmLHZNFaLyWBY\nJuaWJ9Xqlm0d0Oijw6YlgMZilgyhbSSep6XWvTycLrg826U2IDJTIprL6Ct3nyamicdv39nEO69o\nYP+ZWVx2M26nlR4NqOkszHwij89lxW4zG2AnlswblQQttV78HlsFCPmdxFMFyhrzBpXQvqGpJA/t\nHwXgmg3VOM1lxqZFbovHaWZwUrzGqpYQ4XCAyGIBu9VMbcjND/cI4JMryOxaX02+KHN6cIHmGg+l\nssJMLEdrrQeTSWJUAyw6W6MzZR31OqB5ZX2M/lkuzRKCl4+XRmcFwLlqrcgwUlWVnrFFPE4LTdo2\nu7UoA51JqfE7SOdK1AZd7OgK8fypGfZoab+ogpnxuW0Vob3mtlMUldODC4bIGZYzhyu5Xk0HWC7L\nmkygYjwwm00GyHE67Vit4rv4Si6rN7sMlvjyWpF1GdBcwjKZTLjdYhabyxVfpr5fun7RgGYlLdhL\nWaC5hSwP7R/m8HmtYddqJl+SlwXcSQhbttNuZnYhZ3T5AFoRnoNooqBl0VROBjV+O8WyymK6uCyn\nptpvx2IWpYm65gHECd1ptzA8neTsUCVB2O2wUCjJFEsKilKkPuQiEs8ZolKn3Ux7vZeR6ZRxoq4L\nOpldyBkX3Y0dIVRV5fzIAvc81cfN2xs4N7zAdDRLNJEn5LNz285mfnZonJ/sHeT8SIBbr2riB0/1\nUyyL8L1372ji2k113PN0P/tPz/A/7jqKrKhs6wxz0/YGvvXYBb77RC8943GO987jslv4vTvXc/du\nYf0emFjkzGCUkM/Ob75vPZ+8VeVvvn+Epw8LTc5N2+pRZJlsVqZ/IkG+KNMYdjEVzfIX3z7Cr9y8\nmplYlms219PUEKZUKtN9VrQb3351CzPRLKcGogaTtFEDNNlCmdHZNB31Xhw2cac8qEXXb+0M0l7v\nZV2rn+89OUCxrPCdn/XzyAujLKSKtNZ6DDHneEQUHwa0McbkfBabtdIMPRXN4HJYqHKLBOHJSNpw\nOM3FxdhGZzPmDMt2JdsFhKtJf++6JX51o5fBqRRdLVUoqigK1HU480sYGllRWUgWDEZJZ2tePBfB\n5TCTzcui1Roq+TRVdmNUtlSAbLOauH/viJEYvarRJ8Zk8Rw1AQeFfJGhSfEd9dlVorEE0/MCQH/z\n0T6OXhDapzuuaeVTt67hj/71RVx2C0GvjYmIqDzQmS5dB9Z+kYNJF/wOT6ewW02akFVY7b0u6zK9\njMNmprlGPL9XCxPs0sZLepiizsZMx3LEU0WuWhc2hL3nRxaRqCRID0wmKZQUrtpQx/t31XPrVY18\n9UdnmZrP0j+Z5EvfPsE1G2s4P7pIQ9hlaJ8GJpOksiWu21TDyf4YNovpLdGtvBFLtCwryHKRQmHJ\nuU2SDJfVSljJl77u5ZHTyq3LgOYSltlsolyWL0l7Iqrd3/qgo4tHTm+k5PIStsJCssB/PNnDsZ55\nlCU/vHxJrghxETqTTL5s3CWDNvLxOzCZxXx/NFcBOEGfnSq3lbl43oiuB3DazDTWiHbt+cXldu2m\nsId4Or9MOLx025l8Ga/LioQIQZtZ0sfj99oYnExyYXRROCskSOfKpHNlrBYTa1v9DE4m6B6O0VLr\n5ubtDbxwZoanj4om7oBXHzkUeOHMDH/2qSv48Z4+uocXOD8Sx2SSuH5LPcd6Inz/yT7G5tJ89OZV\nDEwmDEaiq6WKLatDfPk3dvCPPz7DQU3I+9n3d7GlM8yXG3z864PnONEnWJBPvLsLn9eJNVfgjz66\niT/7t8MoKrzUPceVXSECXjv7zwiP2Cdu6SCTK/O9J/u59+l+ALa0+0gk0litFk5qDrBbdrbRXu/j\n4ef7uecp8Xcn+mI0VbsZmBQNy7qeBoRw2WY1GayADmA/8c4OpqIZXuqOiPTaSIYfPTvEjrVhoomC\noesoywozsaxRrFgqK0QW86xuFPkvC8kC+aJsjJsq+pmXZ86Ix3ncDgs/fnaYwxfmtc/Gxh9+ZANP\nHJ6AKRGyl9BSey8OwAv7HcRTQlgcrtIv9Antu2fiIze08YOnh6hd0p5tt5rwuqxLeqGcKIrKXDyP\noqg4bWY2rw5y5MI8tQHBShZKisEqzSwZMc0tZCjJCrOxDKOzKXxuK8lMiWs31ZIvyszFc6xvD1Jb\nG+LUsAAc7Y1VmM1mhjXLdVu9F1UVgt+Qz06Vx0YmV2ImlmN1o4++iQSjsykW00XCVXbu+lk/2XyZ\n2YUcXqeFbz/eh81qomdsEa/LItqw/Q66R+JIwFoNrBiC8TYBNDK5EkNTSdrrvUYirq7zunJtDSBG\ntPOLeWoDDm65ooHdRybZd1p8R20Wk8HY6PUjbfVeDpyLsK0zaIDolVwrBRhUVX0VK7kZq9Xyuqzk\nlf0zveFQPfH8yyOnpesyoLmEVSyWkS8RH7x9GhrB0LxVLdjpXIn79w6z5+i4keJrkgQQ0cWXypKR\n0NIgPItZwuuyspgqGiMLECe02qCTQkkmEs8b+TImSdg2bVYTU/MZgxUAYVf1uCxMRDIMLBH5WswS\nkiQukJl8Gb/HRjpXMsojJUmMDYolmZmYYFd8LqHj0UGX32OjJuikfzzBuaEFtneFWEgUGZ1NGYV/\nuiA4lSnywRs6mF/Mse/UNH/57cPLxkiKZsP98m/u4OsPdrP3xBQvnZ2hUFJY0yxawO97boi5eI5P\nvbuT6oDDSLzdfWSCdW1Bgj47t+1sYWDiHAAPPT9Ae52bar+TF87MoqhinDA0leRv7z3L5+5Yw4m+\nGPUhJ2u0gLiQbxP/694zqKoAKps6guQLRU70CrdSnd9GoVA07rAdNjNPHZ1idC5rjIw2dYSQJIl0\nrsRUNEtXS5XBvuhjjq2dQW7eXk+4ysHDL4xht5p4/tQsz2udTmVFiHMLJVkrVhSAaCaWRVUrll9d\nT6I7fvSWaz0VeFZjZEJVdo71Rg3G5PCFeQJeG/FUkTt2NdEQdjG/mDf6l3R7sqGZWSIC1t9Dtd/O\nyf4YwxqT+IWPbDC2Vx9ya66pPNV+IfRfmgp8vG8eRVExSfAHH17Pbg341gYcjGuAW2cjZmM5rBYT\nIZ/dqDzIlxTes7ORnrEE2XyZgNtM32hUaG38dqLROH2ai2ptaxC/38vIbIpQlYPm+gBTkSTpXJmW\nWg+7j0xyUqt1GJxK8k8/OW98L6OJgsFAAaRyZeNvAVLZMt95ot94bDJJfPuxPlq0pnaojJe6RxdR\nVAy3mqqqnBmKY7ea2dARJL6QoGc8QbGksLUzxI3b6rl2Uy1//+NzjM6mGZ1N86W7TnDT1jpO9Mfw\nOC3Gvu1YW2njXsn1VjMgFSv50pHVciu5xWJBklgGcEqlMrIsXx45rfC6DGhWeL1dIydJElUFDoft\nNcdgr2fli2WePjLBk4fHyRVkIxvGJEnMLWSXnRxBjHlyhfIyy3RZVo2aARDsitNmZiFVXMau6ELi\nWCJn3MUCmkXXQbYgwMdS1ken9suyisWEUZGgMwd2q4mWWg+zsSxjs6JHRhfx6qLkxrALi8XE2Gya\nZLbI2hY/Y3NpTvaJE70EWK0iwdfnsvL+a1t54tA4Dzw/RG3AicNmJl8UF+qOBi8fubGDux7v5YHn\nhxmbTfOenc1894leCiUFh83Mp2/rwuO08E/3n+X5k9OcHYwRSxZY3xagOuBg/6kZvnL3cf7o41u5\n5+l+bBYTV2+sZf/pGf767hP8lw9uYM/RCXxuK1/81a3sOTrBg/tG+NqD55EVlZu31RvfuUy+jKqC\n12XhaG+UeLrILdvryRZkrt5QYwgkj/cIdugjN7bRN57gWG+U/vE4ZpPElq46XE4bw+cFONnQHtSC\nIkuMzIjCSV00qtvv/+RjG4klC/z0xXGmo1n6J5L897tOGO4ZUEllSy8LkZu5iJGZMTJnnCykCozN\nprGYJf7q+6eNHCCvy8qnb13F6EyaJw5PLimizBOqEv1LS/NiQIyOqtxW7FazkQSczZf51mOiLiJc\nZWdVo8+4iNcGXQZwN6oMNM1Mvljm7t0i42bH2mpWN/mYe6piy15aa6CoKrMLOeqCTp4+NmXk0bzn\nqkbufEcrz504TH3IhcVsqrRo17hRFJXh6SQWs4TPAQMjcyymCuxYV8P54Sg/PTAKiPwhvWwSYFWj\nl3UtfvomFhmYTPHb7+uis8nLw/vHOHRhnj/52AYaw24ePzjO86dmec/ORgJeO+dHFzkzuIDdauLC\n2CIXxiqv+Q/3d9PVXGWAz82asHc6mmV+UaRO64BX18psW10R/87EsoR8dm7d0cCTR6Z4WhOnN1e7\nONY7j91qMkIbV3r9IkY6P89KXmFybHg8Lkwm0eEkyzKKov5cK/mrr8sMzdJ1GdBcwno9v4e3GtBU\nLNhWymWZRCL72k+6hFUqKzx/aoqH9g2TK8jYrCbDxaNfhECAA72DKZbIL2NmVJVXLJnMFeRllQUu\nhwUJcfG9WEjstJuJp4qGGFRfVrNESVYNkFCSBagpa9uv8tioDTgZmUka2Rr6PsmqigSsavKRzpaZ\nimaxmCRh2U0UDGuq026mVBav21Hvo9rv4MDZWX6yd4iGsJt0rmTs19Ub65iJZhieTnHfc0N84Vc2\ncc9TfRztiXC0JyIEuZ0hTg/E+NsfnOQPfmUT//3XtvHndx0lmihgs5j47O1d1ASc1Ifc3PfsIF/+\n7lHKssqnbuvi3Vc20lTj4Yd7Bvj7H52mLKt85KYOHDYLt+9qxm038R9Pi24iz5JCvEOaxum33tvF\n/jOznOiLGfqgbWtCxvdTHy9s7wxx/eZa2uo8PLBvFFSV7zx6lg9f38apXiEi7moN4HY7WUybSWRK\n7NxQi8fjolQqMzYrcnKaqt201Ho4NRBjOprlA+9oZng6bYwtDpyNcOBsxOitOju0wGK6aFQkDE0l\nGY9kjPySf7jvnBHEBuB1mVjTFOT04ALvvKKeratDhpNLd9elc+WKLmYJoNFzZjqWpOMC7Ds9i8Us\nUSyrNGoMkpFrE3QxNCaOpR79P7+Yx2Yx8Z2f9VPSxOwb2v2UZYVooqLJ0UFaXchJLFGgWFbIF2Ue\nfmFMVF2UFW7YWkdkMU+xrBji6KWt2WVZYXI+Q1O1G4vZZDjkekbjHOupFHhubA/wjs11PH10krG5\nNF/+ravxuh389t89g9th4fptTciyzMBUEpfdzJqmKkwmibHZDCYJ3rOzCafdYnxH/uDD62kIuXj2\nxDSPH5ygWosH0EebAPftHWbr6qBx07JNE5eXZYVTAwtUua20a8f6/GicQknhxq1CP3btplr+6Sci\nMHBCc7tdtS6M/S0YN8Evj0ZFURSKRWXZjackSVRVeVBV9RWs5BWX1dttJf/PvC4DmhVebyWgERZs\nG8ViiVyusCJaHb2m4EfPDJLOlTBrY5RiSaFYqjAjboeFoM9GLFEwxJGA0UCdL8gks6WXlUzq7AhU\nAE72otJJh81MsSQbAk996TZuEBZvnRlZ+jf1ISc2q5nx2TSJJQJl4zVMwsURiecZnEwiSYJWLytC\nNCpJ4oIVS4ieqPVtflRVdNUMTEpGp9PkfAarxcSa5ioujMQ5cn6WX7l5FW31XvadmuZv7zm5bLsu\nu4UP3dDBzvW1fOfxHv7Pj06xptlPNFHAZbeQLZT5p/vP8uXfupqPvWst47MpDnbPIUmwqkFoWG69\nqplSWeYne4cBaAhWkln1uaZJgu/8rB9ZUdnUEeDkQIxqv4O1LVV0tVTxkHeUPcenBetkFs/J5ksM\nTaVoqfMYWgg9sdXjtPDciRkGJpIgiddvCFiJx5MGgGjTRKpmi5WZWJau1iChUBWlUpnJ+Sx2q4nb\ndzZjMkn880+6uTCW4LadjUzNZw1bePfI4rJixGdOLG/otljMrG1x0zueYPOqAL//wXU8e2Ka04ML\ny9qsLWaJgNdmsBvVSwS7+uN4qoiiYmhm+jQAa7WY+NhN7fxgzxDVVeL9RxcLmE0SYb+Tw2cqr6Gq\nwn0lKyrFvMK61ip6xhLUBpxG2J/OFFXGZi4jaXh+UTi3CkWZRKZE0Gc3Rj/6OG5sTvQcNWgC77Ks\nUhd0ct/eYZ4/JY5PrlBm1/pqBqeSJDIlPv/BtciKyl2P99JS4yaXyTA5HWNuIcf2NWEsFjOJnEw0\nUWDXxjqCQR+LqTwjsylWN/pw2i0iHXc4jtthoaPei8kkGePg33pfFy21HvadnuG+50ZE99RE0nBM\n6Z/D3EKG/gnRbn3TtnpDRHy8V7zHK7pC2u9RFHP6XFbCfgfD0yl2rH1r3E3wywNoXmnp+yVCTivn\nrteyki8uJohGo9TW1r1l8oZyucxXv/rXTE1NIssyn//8H7Jly1YGBvr5x3/8qjhPrerkT//0S2/N\nDrzBdbmmc4XXW6GhsdutVFW5MZlMpFIZcrnCmwZOqqpy+PwcX/rWEb79WI/hLpIVdZk4z6Ylf2by\nZSYiWaPgL+i101bnwWEzE4nnl2XM+D1W4zWWBunpAEdf+u7ni/KyLGL93xVV5HpYtAuxDmTMksg8\nCfrszMRyjM2mjefruhaTBKv/L3vvHSfHXd//P2dmZ3vf6026O0mnLqtYlpENuBvHNtUG25BAKA4x\nwXRI8suX5BsCgZjmAAYTwIBxw7KNOy4CuahZvdypnHS93+5t77vz++MzM7cr2d+4SODkoffj4Ydv\nV7czs7NzO6/P+/0qLT4cVgs9AzFzbKVpAsSpikRnkwdZEsqZOQ0eGoIOuvuj5mq4VBbdpYDHSkeT\nl0KxzOBEkusvmY/fY+PeZ49xdEiE9AkAWOYtS+u59sJOEukCX//VLnwuKze9e4kJkoJeG9+6aR3v\nemsHY+E0/3Dbizy99TjbukWOjQR849c7OKCTLQ1prSzBd3+7n33HwpQ1jadeGkGRJW68eiFWVeZn\njx7h7meOky+UWb9UjJZkSTLHAxrwnfsOsufoNPuPRSiVtao2v+E38omruli/tI7ByRSDEykRB6B7\ngxjck7Z6J8lkmn1Hxihr0FJjJ53Oki+UGJ1OM7fJR0NDiEDAy/hMlqDXxrUXdPDp9y7G6xJJzF/7\n2Cq++IGl2FSZkM/Op9+7iL9990IAlnUE+OaNa7h4TRMAnU1ePeZgNqcJBGip9durnX8rSMAGn6Zy\n/LRx15jJmfnctUuw28R7q5Rzh3w2PZJh9nWj02nyxTKlssb73jbHHLHUB+yzSixdTTQeyRDwCMPN\n+/7YDwiJ+mfet5ipaJbmGieSJJldkeYaJ8VSmZEpYbVvUWTzc9/eM8WzO8eQJQkJ+N7N67nuog7C\nsRwdjUJZ1jeWoFTWTH8Zw+hufrOHRCLFlj1D4jw2ushkchw4HkHTYM3iRurqgiTzMpFEnuWdQVRV\nOAzvOz6Dz6Uyp8Et1GcRcS4+9hcL+I9Pns0717eZ185Dzw/wN9/8Az/TuTiGai6XL7GnN0ytz252\nrw72R0lli6xeGGIqmsXtsFS5CZ/qejMDGnj54zNk5IlEikgkxuRkhEgkRiYjPoP9+/dy882f4sor\nL+fv/u6TfO97t/DYYw9z5Mgh8vmTF3Wvp37/+8ex2x3cdtvP+MpX/okf/OA7ANx667e5+ebPc9tt\nPyeZTLJly4unZH+nqs50aE5xncoOTWWkQiKRqWLKvxHgdHgwyn0bj5nqDoPLkkgXmEnkqjog+WLZ\nNLaTJPC5rGQLRSKJHJHEbMhkrc+OVVV0h9pqPo/XqZLJlSiUylUAh4oRVeXftKaJDkdGT302ymW3\nEPTZmJzJmmZugBnIWCxpaGWNkFfEJfQOz5KIDfKdRYHOZh99owmOjSZwO1SKpbJ5s66s5lrhLtw3\nlgANLl/bylMvDfGbp4+aCpaR6TSyJLgUB/oibD4wwbvOd3DTe5bw4991c8vde7BbLZQ10aGKxHNs\n6wlz/aULUBX47R+Oc9uD3UiyxM3vW4YmyXznnj189759XLGulb29YRbPDfCOda3cev8Bvn/ffi47\np5mxcIZzl9SxakGIGp+N7/72IFu7p5AQ8QdGGWqSq9e38sS2EW65ay/zdd8Rg9wJ0DMYxW5VWNAq\nggT9HiuPbRkmHM/xX48d4YZLOukbSyBLs7lBhrFbW52LXC7PwHiSUlmjMSBIrdm8UMmtXFBLIOAj\nVygRjuVY0h5kTqOf6WiKXKHMylY/yzqC5qiw6YQMp/oTXIHrAg5SmYJIy242xkjVgGY6ljuJTzM0\nmWJPb8S0F+ho8tIzKG72tT472XyRRLpAW50LTZv1vPG5VW773WEA2hvdXLa2hef37TyJM9MQdJDN\nF5lJ5FnQ4uU/7jlgAumP/sUCoskC5QpCtEEebqt3M6p3ZFrrXDyzc5QHnhPkYY9T5ar1bdzz7HHa\nGtzU+B1s2RdGo8IwzwAwur+MAciNcFGDF7R4jo9cLs/2g6Lb01lvZ3p6hs37BK/n7MUNBAJeDg/O\nkEgXuGBVMy6nSDHf0xvGabewoNWLRRFO3gAfuLAdu03lpUPTHNST7X/0UA+rFtRQ47MJSffiWcPH\nbboyrc4nnJ0vWNnwitlNp6IEYDhtm3/D9WoBV6WUfOXKNdx77wZisRjHjh2nt7eXnTtf4p577sTh\ncHL77Xe84eO67LIruPjiywAIBALEYjEKhQJjY6MsWrQEgPXrz2fHju2ce+76N7y/U1VnAM2rrFcL\nIE4FoHk1EuzXs5/BiSS//cMx9vaKNnDIZ8Oq+7xUclmML/xkpkiuMNs90TSqfGesqkyNz04yXajy\niZHQreklielo9iSHYK/LSjorTPUqAYvTLlaH2XzJNLgD/SalCeOzoQnxvCSJL/t0tmiCLoMwHI6L\nY7GpMhaLTCpTpFzWaKkVShhj9QuYnSmbKtq6+WKZphoHDpvKsZE4LrvCis4ge49FeHL7UIUvTwan\n3UJj0Mmx0Ti9IzE+ftUi7nmml4ee7+ecxXV0Nns5PBgjnSuydlEdf3nlYv759q38+okekqks5y1v\n4LEtg6SzReyqjN9jY26Tny9/aBX//sud/O6FARRZ4q/e0UVjyMlnr13Od+7dy6Obh5CAK9a1AOKG\neMPFnfzkkcNoCHXTxWuaKJU1dh4J43GqXLGulUVz/Pznhm4OD4qukiHFjsRzTM5kWd4ZMDtoqtGB\n8NvZ3jPN0eE48VSBlrrZAErTIVg3djNu0K06qbVvNKZvw8r09Iz5+y11Lmw2K/FsWj9+Dx6Pi0hS\nXJcNoZd3BZ6MCmKv3arQN5bWr41qn5k6v6MKmMCsd82e3ghBr5VIPG/KxCu5NmYHKOAANLPLc88z\nx01wdf7yekr6uNIAdiagCTnNn4enUqRzJTwOCxldlv6Snldk8HUGJ1L43VY8TtV0zT1wfIYX9k/q\nMR8SX/vYahPsdLUFdH8ZAb4Nw7yegRiSBPNbhP/Owf4oPpdKc63o/PQMRKkL2EXifVlj//EZ/G4r\nbfXic3rpkEhu72hwMD09w7Pb+gBYs7AGq1VlaDrLTCLP21c1Ewx4KRaFUkqRJdYtriXgc9JQ6+Fg\nX4TOZg/pbNEcTwKkMkUi8Rx2q8Luo2Eagg7T1ficxbPg+3SUECq8eRHNG1E5eb1eVq9ey9lnrzvF\nRwUWi/DcAbjvvru55JLLicWieDwe83cCgSDh8PQrbeLPUmdGTm+iUhQZt9uB02kjm811/iLDAAAg\nAElEQVSTSKRf0U/mtQCaqZkM379vH//fT7eztzds3rTCsRxjkQxFXX5aH3TQVufCYpEJx3PkCrP7\ntqmyeTO3KBKKIpEvlBmdTpuAxeWw0Fbvxu0U/jITeraNBDQGhNOuJAn3UMMh2GYVclaLIpHOFs3u\nkGqRaAo5cDksTEWzTMWylDVxHLU+u+5COus0rAG5ggBHHpcwE8sVyqQyRRxWBVkSBm/G7xjlc1up\n9dvJFYSd/7xmL6PTGY6PCFOyVLZkZiCJ8y64EXMbxRd3oVTinefNJZrIc/vDPbx9ZRMuu4Vt3ZMc\nHozRWufG5bCwvWeSrXtH+IcPraTWb+fB5/r4x9u3k84WWTm/hkyuxDfu3M3odIoV82ro0G9WALGk\nWOUv7QhyxTq91S9BNDnLcTIcXJ02hXv/0MdTL41waCBKIl1g9YKQ6f77kSvFWCdXKLNh0wBlTTMV\nLYaUG+CI3i35wnXLuPLcVqIJ4ZBcLmvk9etiYCJpdvdgNsPJAErD0ydGHojHdT4rsViCw8cFubW5\nzk2pVGJCBxSLOusJhXyE4wI8N9UI19xIPHdSKGXdCZyZGr2DBwKkJDMFkyjdXOvkry6bp/+bWDBM\nVUQgnKSMiopQzENDcXM/9QEH4ZiRlj07YhJcLDu9uldMOlfiktWNZAtlGoIiVbwy8iGeyhNN5mmr\ndwlCvh5/EU2JhGo0EWFgtyqmA/ACvbN2ZCiGLIl/z+aL9I0lmNvgxmW3MDyZIpEusHiuSOM2jO/m\nN3sZnkzxwv4Jkzw9OJHi8GCUgfEk81u8uOwWyprGzsPTOGwKHQ1OYrEkz+gAZ+W8AIVCkalYjv7x\nJCvm1zKntRa328mLe0XX5/0XdvAvH1nJp9+zSFymkiBff+X2HXzrnv0USxqr5wtyd2PIYbocn676\nnzhyei2vPRXTgEceeYhPfOLDVf9t27YFgA0b7uPw4UN85CMfP+l1b8bzeqZDcxrqtSZhV6Zgv1oJ\n9qvpGMVTee59tpfNByaqRj2lsmauDGRJwuO0kEgXzFUoYAKcsiYxNVMNBCrjCkB0VjRNI5Upkqow\nz/O5rfjdKtPRHGMzsx0cRZZoCDhI54tEE3nC+dkbc8hrQ1FkwrEso+FM1bbsFomJaM70IjmxvE4V\nm01haiZLIjV7DjM6SLLrwCadKwlgFHCYZFJD/t2r28VriCBIiyJhUWThxlvrxKYKh+LWOjdvWdbA\n5v3jRJMFls8Lsa83zH1/EAReo1sU8Nr4m3cv4Za7dnPnU0cpljSuPm8uP3/0ENl8iaXtQT77/uU8\n9dIQd/7+KF+74yUuO2cOR4ZiNNc4GQun+fY9+/jyDWcxt9HDtu5JZEl89v/5QA+ffd8SGkMOXuqZ\npsZn49PvW8x37j3Ib//Yb/IWzlk06/ExpHfiAh4rT+8YJZEuUNTdpBfrgKZU1jg2Eqch6MDvtvLO\n89rI5Es8u3OU4ak0//qrvVx/cQfj4QwLWr0mAXRwQihnXimzyZRsV2Q2AbTWuUmnswyO6SNQuUA8\nnhKhjT47tTW+Wf+aeg9Op90EO7WBWc6M323FqiqmtYBVlfn6nftIZIpIEnzlumWmqqqSa+N3W1Et\nsglo6gMOUpk8iYzoBi5oFVlXk9EsdQGHaT0wSwLOiE5lpsDDLwo357ULa3jbykae3jlmjpjMCIga\nJ316t8rvtvK1X+81z81nrlmMhMSWg1N0NAlQa4CkBW0B0lnh5jy3wYPDZmGfzodaNMfPVDRrysJH\nplL8n5/vMrtTLx6Y5MUDs+qoPb0RsysEIsPr5v/chssu7BUagw5e2D9BY9DJSz3TuOwWFrR4yGSy\nPLNNjMNWdvqIRhMgW9jePUFDyMnaZa0AxLrFtq+9sAOHqrBp7xh9Ondp4+5xiiWN9UvrT7vFxZsf\n0Mh/9uO76qp3cdVV7zrp+UcffYgXX3yeb3zjFiwWC36/GD0ZNT09RU3N6fEPer11BtCchjLAxn93\nnUqShMNhRVUtZLOvNQX7lTs02XyRJ7cN8fiWQbPj4XepuBwq07GsMMXTAU5Z04ilKnOWLIS8NiKJ\nnCk/NSrgtpLXjewqq1K1JEngd9soFcvEkvkq5VHQa8PjUBmfSTNS4TtjtyrU+e1Ek/kqzxmLIhHy\n2clkC2JbFfusVE85bAqKLIlOUbpSFik+A6sqE/RYGdeJjXarQq5QMsEMzBoDGkDEapFpCDoYnExh\ntQj31EMDUVx2hYVtfg4NRhkLp3DYFOKpPHt7w0JBpacYX39ZF3uPTrPr8BS5fInPf2AFt9y9l3ue\nFf4lqiJjtykc6Ivw6OYBrnzLHArFMvc+e4y7nz6Cy27h8x9YQf94kh9sOMC379nL285qYmImw4Wr\nmljU5uXHDx/m1ge6Wbe4lnyxzAUrG2kMOvnCB5byrbv20T+exKnnXRm18/A0qkXmK9cv4ycPH2Fr\ntxg3+Fyq6QUzNJkUq/qW2S5RPCU+x3MX17Kle8o0bzPAS1nTGJ5K0RhyoupE8uGplCnzh4pQxhM8\naJrr3MSjccYiupeLXSWRyjGTEI7D4XCUbn1MWucX0tYZnafV1V6H06UyE8+xoNWnG+CJ7W7cNSb8\nihThWG23WaoiEERqe84c3Zj/FrDz80d6AKH6uundi/iPu/djU2V8LpUdJrfHYZo5ttQ6ueXeA6Y9\nwbUXzDVv4GYI52SKoNeGy6GaI94X9k9QLutGkHUulswN8OhmwevpaHKbEQYBj+gk7jo8SamssXCO\nj1S2yEZd/bRpzxiPbx02P6/ByRQOqwxIyJLGmq4anHaFbd3T4lpZ1QiaxvaeaeLpAp1NHtK5ogmA\nxiIZfvP0cXN7dquQq89tcPP8vglsqszK+SGKxRJbeybJFUqcs6iGqSnhmr1xxxCKInHZunaCPidn\nLWriM9/dRNBjZSaZR9bHVae73vyA5s3Z6RgZGeahhx7gBz+4HZtNdDMtFgtz5sxl7949rFhxFps2\nbeS9733/n/lIq+vMyOlV1qn0opEkIcH2eoUbaTyeqpLtvdp9nGiqVCyVeWbHMJ+9dTMPbOoTBM2Q\nkzq/nVhKuL4anRZFBrdj1r/EYkp6iwxNpkjpq9Man53OZtGOnknmq8CMqo+ejPekyIKAN5PIEde5\nKUbooNdpIRLPMTCRJJcXmUc1PhstdaLlPjiZMkdXboeFpgrre8OPRJYl08ekVNZ0t2AR7JfUj9dh\nVUyFlaaJMVixWDbBDOiqKh3oGGewxifGXrlCmaYaJxoag5Mpanw2MvkShwaiWFWZVLZk+tYYHjtC\naSPOwQ2XdeF3W/nFoz20N7hZu6iOw4NRbr1/f1Vn69K1LfzzX68h6LVx38ZjPLtzmLPm1ZhgwGm3\n4LBZWLOwlo9euZBUtsjjWwdx2BTedf5czpof4iNXzCeTK/HH3ePYVJnzl9cD4kZ76dkt5uf5wj5h\nojc5k2FkKsXyzhBBr53PXbuEzia3OUoygOlhI+OndTYCQRCoLXzkivl88QNLcTvEWmhr9yS7j4aZ\njGTIFcrmuKmsaYxMp2kMOUzS58h0Gr/biktPYDYM1+xWi/ByiWYrJNkGAdjIcBKfX9CtEo+nGBqP\no8gSVrnEyGQcDWiu8+DyeNjcPZu2/tEru6oDJWOzY6VwPIumnTy22n00zLM7BKi4aFUjDqtidmck\nSaoiARs/D0ykmJzJ4rQpuB0WfG6bCdqbapwCkKcKtNa5yBVKbNLjAGyqwvveNgdNw+zIHDNDJ0Xw\naiJdoKtV+Mfs08ef3f0zfP6H2zmoS98lSWLFPEHybgo5+c5Na/nSdcsplTVWd9Xw8au6OG95A5l8\nidVdId5/QTsXr2kmni7Q1ebjKzcs56sfXonTruKyW/jSdcv4yDvmmyBXQmLnkTAbnhsgliqQL5a5\n9YFuHn5xkCe3CU7XW5YIPkzvcJyhyRQrOoKU8lmmpiI8vEkooC5Z24qmwbolDczvaCAY9OHxuPTY\ngDdv9MHpqFNxbKerw/Xoo78jFovxhS98mk996hN86lOfoFAo8OlPf56f/OQHfPKTf01zcwtnn33O\nadn/660zHZrTUP8vQDObgl0kHk+97gu6cuRU1jS2d09y51NHiafy5o1epPXOdkIcNoWGoJjfR+K5\nqiDIYkmbzWbSuyz5YonpWNZ0VgUIeqwioTiWqyL0GgZ2RlkUCUUWAGGqgjBsVWX8bhuJVF4fDejx\nB7JkSl1nEnkToBjHXS4LU72czsnRqB59uR0WLIp0ksLKAGYGb6hU1rBaJBw2C7FUAVkCh01YsEsI\n35pKI8FKZ+R8oYxNlSlr4tx2tQUYGI8xFc1y6TmtvLBnjDufOMS739rOH/eMsmFTHwtafagWmcmZ\nLJIEF61u5qVDkzy2ZZCGoJOvfHAlX/vlTn75xBHT2G9ZZ4j9x8J85959fOmGszhveQNPbhtkaDKF\nRZFNcH3Oolr2HYuwvWcaSZLIFUo4bOJP2lC2OG0Kdz51DIsiE9O7LGcvFsDHZlVY2hHk2GiSRKbI\nt+45wGfet5gjujrMSGWOJnNE4jlWdApexoJWH12tPnYeCZPJlfjRQ4fMLoQRpDgdzZIvlM0OTjon\n1D+LdRv9dLZILFVgqS4dn4oKjtSJhGCju2MqnCrAR8hrQyuXGRoXACyfz/OpWzYS1j+z//vxc9B0\nyNrW6Mfv9zCTENdHXcBhAtPK8ZPDpvDgcwM4dJXdnAY30WSefKFsgqvxSNokvr+og8V0tsiFKxv4\nw+5x87wZI7emkJMhfdxU47Xxzbv2E0nkkSWJr/7VWezWRz8djW7KZY1jo4Kz43VZ2al71TSFnPz6\nySM8tV0Arf7xFE0hB6PhDF2tXj7//qVsOTjF3t4Z1i2pxeNUTe+alXrC9U5d8bZ6gfB92aGTlNfq\nPjDd/VFTeTS/xUtLrZPfPH2MWr+dr310JZFEnp89doTekQQ1PjtHK/xoZAnuevY4S9v9HNItAN52\nVgMgFhBbDkzic6kmUfzcxUGmpmbMwEebTcXtdqAoSlU8wOtzz52t/+2A5nTVjTfexI033nTS8+3t\nHfzoR//1ZziiV1dnOjSnoV4O0FitFnw+FxaLQiKRIZ3OnZKLeW/vNP/00+386MGD5lhAgJPZ/Ttt\nCkGPlUyuRN9YgnA8h4YYrzSGHOZN0Mxm0rssBhiw6gm+Qa+VSCLPWDhjghmXXcHvtp7E5ynqrr5G\n2VTF9GuZnMlU8VpCXhuSphGO5Uz3UVkCj0NF1jswlduqPGsOq4LTbiGZKZ4EZkAAGb/HSqmsUdL9\nZwrF2TFbWZsdmWlAuSxeY9jl+FzCul9CjA5yhTJOm4XGGieHB2doa/AS9Np5atsQ81t92KwKDzzX\nR05/f0eGYmiaSI/WNJFa/vkPrMDjVPn544cYmkzy7vPbAfE+L13byv/563NYt7iOo8MxfvzQQbYc\nmDDHFYl0ge/fv59cvkSxVObYSAJZlsjmS3zvt92kskWmolkODcZY0OLlCx9YhsNu4Y4nj/L8vgkU\nWarKzenuF+nJb11ez+h0mm/8Zh+HB2PU+e0E9HiDYzqHw+gggODLuB0Wvvrhs1g812/evHsGYkQS\nOYb1xy2vxJ8xxk/BWR5K5WPD98RQOE3NzI6DMjmhYjIAhsFpeWH/JJF4DodNwetSCbpkegfFTdzr\nkMlmc0zMZPC7rTQ31ZAuiq+/1gYfikV0EDO5Em6HyrJOYQRXF3BU+N/MHmvQa0PTNB7fJsY8Z80L\ncu6SOjRmYx2Gp1I4rAo1Ppt5jC8emDR/XjTHR8hnn03RbvIwPJUikyuZEmyD5/LA8wM8+mI/miZ4\nZv/60ZW8dYUADGsX1SJJkkleP0uPHdh1JIxFkVjaHhCLnp5pbKrM0nY/mqax+aAYN65aIN7r5gMC\nnK3TlUcvHRLjqbcsrUOWZRxWhf7xJPUBO//2sVV89+/OMT1nvC4re3sj/Obp4+zUFVCHBqP0jQnD\nyEy+xDmLa9l5WKiculp9ZuBjOp0hFksyPR1lcjJMPJ6iWCyiqha8Xjf19SFCIT8+nxun047Vqr7q\nzsSbGTS88RynM7EHJ9YZQHMaqrJ7oqoKXq8Tq1UlmcyQSmVfMXn1tdTAeIKv3r6Fb9+zT1+5SzTX\nuqjx2ZGoNrRL50pEKoBCXcCuS2sFjyFTIZF22ixVaibVIkDIyHSaiE7EdDkstDd6CHhspLIlosm8\n2TVQJKqM+Yxt5QrVoMRhU1AVcSMOx3MYzRabKutqC0hkClT+vVd48qEqsgA7+ZIJSKwW2TRKA+Fx\nU9Y0ohW5UoWShoYALcaxOWyKue2AWxUjGE2QjGOpPHarogdnpvG5xHMT4TQuu4Ujg1FTbbS3N2xy\nllLZIvUBBx6nSrGkce6SOlYuqOFA3wwPPd/PZ9+/DKtF5gcbDvDLJ4+gyBKKJPHcnlEGxuN84p2L\nWTTHz87D0/z0kR5sqsKXbziL9csaOD6a4L8eP8IL+yYIx3O8fUU9F6xsZGQ6zY8e7OGPe8TKfP2y\nelrrXHzmfYux6qTXlloXHh2kpXNFjo3Emdvo5oOXdvKu89qYSeTNsZtRBim1U+fiJDMFpmJZ5tS7\naaoR2zdGTfuPz/CPP93J41tFJ8GQKBuAxiQImxlORihltUTblGwbKds6edemKmbHL+i18diWIR7R\nOSf1ATtfum4ZuXzJ7OQYsuyQ10oylWU6miHktTE5GaF/eMbc5+aDU+Z18dWPrSWeEh2UuoCj4lgE\nmIqlCtT57fzgwUMmMP7QZZ3me2oKOckXSoxHMjTXupAkyQQmuXyJt+udCyOK4fhoApfdQp3fbqrL\nmkJOfvbYYTOnqSnk4KI1Yox44apGGoJO9h0Xx7+0I0AuX+JA3wx1ATsNQQfDUylGptMs6wjgsFk4\nOhwnHM+xpqsGqyqAyeh0mrPmBXE7VOKpPLuPRmiucdLeKLg7m/aMI0uzvkYvHpikWNI4f3mDbtwI\nR4fjhHx2/vOz5/H1j69mhWHkqGk8sW2Er9+5j3s39iFJogNWKmtcvLrpFQGJpokQx3Q6SzyeJByO\nMjERJhZLkM8XUBQFt9tJbW2AmpoAfr8Hl8uB1apWhcUa9Wb2oXkzg63/qXVm5PQq67VyaAwJtixL\negr2q4zr/m9qKpphwx+Pm6upoMeGy2lheiZrymKNctkVCiWNfEH4tFh1wutkheJItcg017jIFUtM\nRDJV/i9ipDP7xj0OFasqEY7n6cskKvZjIei1EYnnSGWLlCqM+TRtNvIAZlclldlOgBlrkCuUq4CP\nIov4A00T3RRjLFYoVYAjq4yqKsRTBajoThtdJEnCBGYgOlaG47FFkaqOZaaiy2NweiqNBis7Owaf\nqFwWDsg2q0I6W6SzyUskkWViJsPl57Sw49A0Dz7fz/sv6iRfKLH7yDTpTAGHzUKukEcCPnbVIlSL\nzA83HOBrd7zE//mrVXzsqkV8+batFEsaaxfVUB9w8FeXz2cmkWXP0QjdfcJP5sq3tOFxqSTSBXYc\nnub4mLhBGpby7Y0ezllcy3N7JxieStHdF6E5aKVHT09e2i5GSX9xbiuDkyl2HQmzv2+GA30zLG0P\ncGxU8FUM1dSJ/jMgOno1PhtXntvKY1uGGdDTyp/dOSokyyd0aMbD1SGVs7wU3VRvJoMiS4S8NkHe\njefMUY5h6Lf14BT5YtkcJ37p+uVk9aDUyjESiMeReI6yNsvLMYDK4FiUnz8qOB7rl9XTFLQzNp2i\nNuCgrjZAIisAYntLgJmU+MynYlkzk8tuVfA6rbPJ4Xp0gaYJCftTL42Yxo2ffu8i06m4vdHNTEKk\nYRvjPCMa4oHn+jEu8YVtPj577RLu+L0g6S5tD5DOFXVbABdBj0gizxfKrOkSJnaGgV1LrZPNBybZ\nqMvCE+kCP3vsCMd0NV9cfzw5IywWanw2Nh+YJJ0rMjiZYkVnkKDHRqmssXHXGFaLzHnLdICzf5Jc\nocw7VzejKDIBj5WBiSQ2VeZfP7qKvrEkG3eNcXhIvKfdRyO47BbWLXntZOBisaRbWLx8qrXL5UBV\nLSJTqiID6c1KuoUzgOZ01BlAc4pLlsXNVZJkMpks+fzrn/9WViKd5/4/HGfTnjEzEqBQLJ/k2Fvj\nt+NxiIydVLYCWEAVULBbFYJeG1PRDP3js+BEQmwjmy+ROMEQL5EpgC58kiWJGr9Nt0XPMDQ5+z6t\nFgmf20YsmSevhz0aVS5rpvpIAiRZjHkqQQOARZEpnugsDFUdG5sqI0sSmXyJTL4aBBmvs6uyCeqM\nSlcAGOPYDF6O8d4qz7GEDoiKZTwOlUSmgNUiY7UqJNMF5jS49ZusxtwGD8dG4yya40eRZZ7cNswV\n57bx4r4x7n32GCvmhbAoEoeHhBna8s4g+45FuG9jL//04TV88PIufv3kYW65Z6/uYqxhU2W2Hpzg\n7EU1rJwf4qZ3L+YrP95OIlNkWUeAgFfcoD9x9UKGf7ZTdAZqbGbgX7kMx0eTyPqX+7//ehefu3YJ\ne/UgyErHYMNjRgJ+8EAP11/cweBEirb6CkM9/YZsAJyZpOA8LWj1sX5ZPeuW1PHF214ilSmYmU0m\n6TwnTA6NVG2zQxMWAKbGJ0Y5E5EMdQE7siwxFskIp2pZ4rbfHWK3nugsSXDVW1rZ1j1FOlfE65xV\nD1WSgCUg5LWbN9ZKsGNTZX7++FFTErewzUc0niWWytNa52RqaobjI+I8NQadJil3OpZjaUeQA8cj\nzGvxYbEoVUnixjFOzmRMLktHo5ulHUE27h7Xz5/H5PHMa/ay/3jE3L7bodLZ7GXXkTDnL69H02Bf\nb5iQ10ZjyMHW7ilKZc0cF72wXyd+RzL826/30D8uAOUjm2eVT4DZ1THq6HCcoxWP9x6bMa8L8TjC\n5364HadNIawHfPaNJ2kOOXh6xwhWVdaJvmKkFU3muWh1IwGPDb/bylMvCRn5mq4QOw6HuWBlo3kd\nvdF6pVRrVRU5SA6HDatVRVXVKpBTLBZf0d/rT1lvdOR0uiXv/xPrDKA5RVUpwS4WS5TLpVMCZnKF\nEo+82M/TLw1XdRIKxTKqIlMoCcWQ12klky8wNZM1+QYg1DuSJBGO5Shrs4TabL5URX4Nem0E3FbG\nI5kqEi8IkzuRpiuIw6rl5Ts99QE7xaLGVCxbtQ0J4eqbzIqbmbEo0QCtPAsmKkFFsVSuelx1PIoA\nLCd2cpw2hUSmWAWCshW/Uymlt1pEyrKxPSM9WZHFuE6RJbPDI8sS+WIZqyrrYEaiWCqTT5fxOFUG\nxpPU+oUx28hUkoagg56BKPUBO3arwuNbBk11lmFsaIReLu0IsaQ9yN3P9PKde/by1b8+m4lIhqe2\nCz+TVQtq+It1LXzz7n38+Hc9/OOHzkK1yKRzJSRJjHj2H4uwrDOIRZHMtvvARIqNu8a4eE0z45E0\nw1MpVs4PcfHaOdxy1y6+99uDgJBrt+mOt8VSmaPDcRpDDj506Tx+8GAPv35KJHp3Ns1Kv/t0ANze\nIJ4zQIRBCM4XBBhe2ObjXee18eKBSZ7XybPfv78bh1WhWNawqjL7j0VIFSTGwmmCXhvxdIFILEs6\nVyLkk/ntH/vYp49rDLKp0WH74nXLaK118fjWYXPfJ5vjZQl4qn1mav12ymXhBFwuayiKxLJ2P3uP\niZGNIfs2fWbCQk5OucBjm4XJXGPQwVXrWzlwPEJbgwe/38toWHBrGuv8PLZV3MgP9kcJeKzMJPJ0\ntQneSN9YgpDPhsepmnEPh4dibNDjDppCDv7+gyv4zw3dSMDiuX6ODMVIZQqsWyzGNUakxXg4zVd+\nssO0O9hxJGyOT2t8NtYuqmU6mmX7oWneuqKei1c38dKhaR7ZPMQ7zmnmwlVN7D4a5q5njrNyfpD1\nywSX6oHnBnDZLbTVu5iKZk3Tw+OjCb5/f7d5LdT4bDy1fYg5dS4e3TKEIktcuqbZfE/HRhMsa/dz\ndDiOTZW5aHUjp7PK5TK53GzYYyjkJx5PIkkSqmrBZrPqnXNFBzbVBOQ/ZZ3p0Jz6OsOheYMlSeBw\n2PB6hY14PJ6iUCi94YDKUrnMH3eP8qUfbeHhFwbI5ErU+Gy0N3pw6rJXY+yiaRBL5ckXZn1Z5jS4\nCXpsTMdyuoLEGPlQtUJy2i3IkrC/PzaaIJUtIiGcVFvrnNhUhUJRMzsZZe3kTk/Ia6VUKjM8lWZc\nb12rFmGtH/LaQBKt7crViBHECLOgxfj/ic8bZYwWCiXN7NRYZAGWNE0zjdBOLFWRUJXZWboEJpgx\ntjd73o3/VxsRAmaXJ1+c3b/RxTJuloWSZo5PJmayZucpVyjTXOPUE681PvyOLnxuK3c/fZSQz84l\nZ7cwPJXiP+7aTU//rOGZ36XS0ezlE1ctJF8o873fHuD2hw/pIYlzsSgSP3qoh5GpFAf6ZkxehNep\nctczx9hzNMzmgwJMXHj2HFbOD/DhdywgnRPxEgtafVgUGVmW6BsT/jML2/zMb/HyleuX4dA5ScNT\nKYqlsn5DThL02vC5BRdnUB8vGVEABkG4tc5FZ7OXd58/BxAdnbcur8frUikURZjnfz12hH+4bQuZ\nfImpaJYv/3gH37z7ACDIvk+9NGreTNd0hfinv1xBU40TSRKZSJGESLo+ecTkIF8oMZPIU1uRzg2C\n3Gt0OJDgpncvMq/v+oDd/PzqAnYhJ49laQg6eHL7iOktc+PVXYzrC4KQx8LA0CThmOAo5QsFtncL\nE7u5TV4uWiPM5ha0BZmOF0hmiiZAPHBcdGgO9EXxu4WNwjvOaUHTNI6NJpjT4MbtUM2OT2udizuf\n6mWf3kXZ1jNtigGWdwT4xw8tNwNJP3FVF+86r42R6TSKLHH1W9qoDzjY1j2FRZG4ZE0zPpdqOim/\n561zWdEZNJO2r7uog89du5QbLukEhPHijVd3ccW6Zqw6QJ+O5fjtxmPccs8+s+P12NYhth6cZMMm\nAdDqgw5iqQJvX9lYZRXxpyjRBSmTzxdIpTLEYgmmp6NMTUVIJFIUiyVU1YLPd31pJAcAACAASURB\nVDL5WFUtp7UL8mYw1fvfVmcAzausl7vubDbhJSNJEI+nyGYFOfZU5Dn96skj/PyxQ8RTBeoDDoIe\nK9OxHH1jCZME67DKBL02c0Vm3PAzuRID40lzFBXw2uhq8+N1WSmVqYo0SGeL5s1ZVYTqyeu2MhXN\nMTSZNn/X47AQ8MyqmSqTssPxvLkNn0ultVack6HJlFBUabPuwB6nah5j5Sk1OhhQDWQMfxeoBhkW\nWbymWBagwvgnh1VBrriqJQTIqAQts6Oliv1UvMZ43niu8veMH83MI903xq6DRLuqIOnHXOMTKqF5\nzV5cdoXRcJorzp0DSNzxxGFuuGQ+VlXhJ7/rZk1XDQ1BB0eGYgxNJrlsXRtt9W427h5j88Fp1q9o\n5poL2plJ5OkfT3L2whquOLeNj13ZpSucDvCgvsJ/5/lzuPmapaiKzG2/6+H5vRPC6bXJQS5X4K0r\nGszgwsNDMeLpArIsmyOZxXP9yLIgmbfWCZByaDDOrRu6TWv99gr+jNmh0YnBhkS55QRC8KI5Pj50\n2Tw+flUXACvmBbn+4g7etlKs6BtDDtYuqjFTo9ctruWLH1jKOt3f5Kq3iHMypUu2LYp8kgKpMhLB\niDWoO8GDZiyc5pdPikHLmq4alrYHmJzJ4nWq2K0WxnUH4/qAw5STAzzw3ACyLGG3KjTVOKs4M4aq\nqyFo53v37CWeLqBaZD53zSJTqrxgToCRsDimZfPqeHjziHlMV69vNcdvi+b4OdA3Q6mssawjQKFU\nZlv3FLIscccTR9m0VwDU9gY3n7t2CU01TmQJPnTZPPxuK/uPz9BS62Jug5vu/igj02lWLQjhc1vZ\neWSayWiWdYuFtLu7P0rfWJKz5gVpCDoIx3O8sH+CGp+NNQtr0DTNdD9+79vmsKarhjq/g3yhzNtW\nNHDLJ8/m89edVbXIem7vBD97/Cj940lUReK5vRM4rAqXr23mT12S9PJjHU3T/lvyscfjorY2+KrI\nx6+nDLD1+uvMyOnEOgNoXkdZraouwZZJJNInSbBPBaAxyJOlssbETMZUKdmtCp3NXhqCDnKFskl0\nNH5XqfhjC3pthHx2ZuI5Dg9GzZWcwyZTH3SYAYTGoRZKZcbCGdPd1+2wsKDVR8hnI5ERPiLmuEg3\npjPKUDbFUgWGplKCiCwJY762OhcWRWJ8JlPFy6nx2U3J+IkZS1YdKJS1ajBptQh1U7E8+xoJAbis\nFplMvkTld0TlV5kBPoz3XPk9V/ka43njuRMCwk0VmTGWslsVsoUSXqdKtiBkvxZFJhLP0Vbvpnck\nztxGLzZV4bEtwhU4kytx9zO9vPdt7RSKZf79N3sYj2RM8FTvt/Kp9ywS8u5Hezg6HGPBnJB5HE6H\nFbvdxvrljVz1ljYT7J41L8jcBg8L5wb57HUryRfKxFN5VswLYlUNw0GNcDwn3JVTBW65Zz/JTIED\nx2eQJVg8N4Asy2hIDE6IEdqKeUF6BmLcukGMGzoaPea2+seT+N1WvLp6ynBgNiTbI9PVBGAD4CyZ\n6+fCVU0sbhcdhcvXtvDxK7to17sX56+oZ0Grj3A8q3cNRSK2UBkZAKbagG8qmsVuFeZ25ujI8K6Z\nyWC1yPzyyV7T1mBpe0B0YeLZWZ+Z8MnGeb0jCVx2BTSN5honkiRVSdENEHd4KMauo6LDtnJ+EIfV\nQt+oyAVTKbLniODPbNwxxCMv9gNw8dkt/OWVyzk2IjoyjXVe9h2L6tegxt//ZAfpXIlyWWN5Z5DG\nkAMJuPGdC3HZLQxMpFjaEcDvtrJx1xilssYFKxtIZYs8+LwAI363lQee6zfdf2cSeX7wQDe3PyJS\nxPPFMr944ijfv/8gxZJGZ5OHHYfFaKpvLMmq+SHa6t3k8iUeemEQ1SJzxbkt+NxWIvEc6WyRi1Y1\ncuun1/Hl65eZC5dyWQS+Xrq2+U/enYHXPtYpFktkMjkSiRSRSIzJyTAzM3GyWeFu7HI5qKkJUFsb\nwO/34nY7sdmsKK8jMfzMyOnU1xkOzWsoQTQT5m/JZIZS6eXR9akANJed08baxfX0jcXpG01weGiG\n/rEk2XzJVCiAIA8214iU31gqX9XFiFTECKi6lX+pVGZcD46cPd5Zy38Q4yA0jWSmyJGh2cABr0sl\n6LEzHcuSzBSqiLbZfMnkvMi6lX4yU6gy5ZMkcVOyqhYmIumqfwPwOC3k8mXyRfGf+TpmSbmVz4NQ\nWGXzpapx06yxYPWXxYlGgK+3jJca59oYK8XTwqjPyIBCkhiaSBLw2DjYN8OcejeDk0ke2zIgVvjT\nae56ptc8HrdD5dPvXcStG3r4zVPH+MJ1y/jbdy3iP+7exzd/tZOi7o5c47OzafcoC1r9XLG+nQ9f\nvZxnd42SzhZxOaz4fB4kSWJZu0ZTSHQSjo8lyOVL2KwKQ5MppqJZ1i6qweO08uzOUW65Zz+DE0nm\nNXvN1fbQhLjeutp8/OVl87nvD338frsgmSo6X2cmIRxwDe8TEB0aRZbMjsOImWEkOjZjJyichqdE\nh6exwh0aoCEw+zjos6FaZMYmxGtNADMz25Epa4IX0xgSjr6V6dmlcpmJGcGZcdotLG33s71nmrqA\nnemY6CIanJmxSBrVIhP02EyfGYsicf3Fnfz00SPmcY9MCxm/26GaGVkD4ykaQg7Gwxk6mjzClDCR\nZ7muYuoZiCGByaMJx3Ksnhfg+Z195ItllrQHKZVg19FpZFnisa3DJsj9u2tW0BKy8eUfb2dRm4+Q\n12Z2T1YtCLH5wCRP7xCqsg2b+k3+E8DTO0arrmEj08qo7hMeb+uZZlvPbJLyrqNhPv/D7SiyRDSZ\nZ0Grl/6xJJF4lvuePYrTpvAX57ZiUWQGxpMk0gXO7gqxuzdCwKFyyZom/qeWQT7OVnxdVZOP7boQ\nRKowAxS8HEFafvk6A2hOfZ0BNK+yJEnCbreSTuf+W4a88KF54+3AgMdGwFPLqgW1+nY1pqNZ+sYS\ndA9EGJlKMziRMEcFIMYjDUEnk9EMxZLoIig6qXWoIrvIYVNoCjmJpQqE9XwnoyrJxwKEOFBkIa2N\nV+Q+WWTweezEkznT3wUw3X6NsqlCUZXM5KuIxKCvniWJcCxLIl3NgXE5LLqBnFYFZCpdiCujGKyq\njKpIVequE8u4ObwhP6v/RxnbrVR2zeijvwH9plcsaYxOp02VQ0utk/ZGD8/vm+DxbSP87bsX8e17\n9vOjB3v46odXcvGaZlMtcuPVC5nX7OVf7tjFzx/toc5nZWQ6RTpbxGm38OL+cVbtGuGStW0kcxpj\nkTQep8p4OMPtjxzipvcs5iXdIXZ1Vy1rFtaQzhZNHoXh5AuY19UC3Xb/Axd1sOvINFPRLPc82wdI\nZvejvdGDosiUSmUz8kC1KICIQDDCToEqvxaAET2lu77CZM9pU/A4VbMjYxyXMVI6MXW7Vs8CKxTL\nsyMm04PGxi+fPEZZ53Z96bplPPT8gLkdw9iuLmA3FVaNISfDUyk27xfn5YZLOs1RQ2PIQTpbJBLP\nsWSun3JZY4/OaVnQ4qGpxsV4OMPcerdpSjiv2csL+8bNRca7zmtjy8FJbKrM3EY3924UZOOAy8IX\nf/ii2eG8cGUjW7unsFkVLjy7jTseFRlaF61tY39fjC0HJ1FkiTue6K26Dl12wf9IZYtcuKqRziYP\n9/2hj0SmyOevXUKNz8a37j7ATDLPV65bit9j40cPHaJ/PMn73jaHGp+dFw9Msv/4DE0hB16XlYlI\nhhm9e3ukwiUYhIP4hk391PjsPLFtGLtVJpYuUCxpXHPB3FOmbHotdToBw4nkYxALOYvFUkE+diLL\ncgX52FBZlczff70qp1OxaP7fWGcAzasskbmUflVkX3GxnfpjkCSJ2oCD2oCDtYvrsNlUQGJ0OsnR\n4TjHR6L0DkUZmEiaN1TRRajwknGquO0iOdjIjAFxow/5bCQzRRPQGKogI1cHxMinIeSgpJNfwyd0\nWSo7PRZF0iMLSlURDIZvTTSZN29IRgXcVjQEyTl1AsnX6MYUS1oVYHDaFEqaMC2rDCq3WoQKrPI7\n7XQBmRPL8N4xFFkgxnLpXImOJg/HRxPU+234PXZ6BqJ0tfpZPNfPnqNhWmtdXH9xJ79+qpdv3LnX\n9MMBODQYZd2SOj75rkXccs9+/nPDQYplDbtV4e8/tIpv/HoXt23Yi98hlDCaBh+8vIvn946x60iY\nx7aO8NKhaWxWhVVdtcgSfPTKLg4PCoffQwNRSus13elVABoj06lQFCNOcUMvcc+zx82uypwG0RWa\niuXIF8rMafBgsciUy2VGp9PUBx3YrIowc5xO43ZYzDyo4ckkPpeK02ahpKuP2updVV2W+hMynYyU\n7cloFodVgB/jBlt3Ath54PkBswNx3rI6mmucTMxkcOi5S5UmfrFUnmy+RNBr53v3d4tkegnOXVLH\nY1uEgV9jyMnwtFgcNNc6+fkTR0lni9hUmb977xK+f/9BkTpe5zKjC6ajWR54znDireXcpXU89MIg\nyzoCKLLE7qPC1fc3z8wGQt54dRdosHH3GOctqyOTzfPk1gFUi8zPHume/TuVYeX8Gg72R5AliX//\nm7X0jcb5/v0HWdYR4LqLOnh86zCxVIGLVjWyoNXH714YIBzPcfHqJtqbvDy/b5z+ccGluWxtCyPT\naXoGovjdVv7+g8uxqgrfvkcAoOsuaifks7P7SJgXD0xiVUWsRmWaNwjQs7Tdz5qumtf653NK6tUE\nBJ/KKpeF83E+XxmQK2GxKKiqBatVxel0YLEoFIslZFmiVCpTLpcpFktnujWnoM4AmtNQfyr0rCgK\nVquFtgYvtT4b6xaJL45iqczwVIq+0TjHR+P0jSVM4mYiXTB5LMaq2WGzMDKVZiqaq96+7ueia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KM4G5Wz0BpF+KZShMBhNo9pAT5/IuN44MhzE0EcHSdhee2TGG6y9bhdGZOO57dB8+eHkfXBKL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\nNARBEARBaJ7/BwX8hlFmu2S+AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f6c9aca4610>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "cRkuifc7PazR"
      },
      "cell_type": "markdown",
      "source": [
        "## Seaborn\n",
        "\n",
        "There are several libraries layered on top of Matplotlib that you can use in Colab. One that is worth highlighting is [Seaborn](http://seaborn.pydata.org):"
      ]
    },
    {
      "metadata": {
        "cellView": "both",
        "colab_type": "code",
        "id": "el13bTbyPRw4",
        "outputId": "9063327c-064d-4213-ccf8-8af4e26c5106",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "\n",
        "# Generate some random data\n",
        "num_points = 20\n",
        "# x will be 5, 6, 7... but also twiddled randomly\n",
        "x = 5 + np.arange(num_points) + np.random.randn(num_points)\n",
        "# y will be 10, 11, 12... but twiddled even more randomly\n",
        "y = 10 + np.arange(num_points) + 5 * np.random.randn(num_points)\n",
        "sns.regplot(x, y)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FZLLUYGD//v3Yvn27NyOlpuG6LrK5PEzLhmk5sF20XCAD/i76si0DsuQiFtZZ\n6EXUIBX/KNy9ezf27t2Le++9d8bX9+3bh3379tV8YNQ8yoFsmDYsu7T9SSsHshbsrl2LsXDRV2M6\nfQkhYJtFhDQZqc4oz1YmarCKA3rz5s0YGBi44OtCiFm+m1qZ4zhnb1k7MG0HjpBKfa0l/29/coXA\n0VNpDI7m0ZeI4oq1qZpdvS5U9NWo4x1ty4IEG5GQit5eXi0T+cWSbyY++eSTeO6553D55Zfjvvvu\nQzwer8W4KEBKV8iloi7DcuEKQNPDkCQFigYEacXy6Kk0Dh0fAgB8OFg6QWnzZT2Lfj3HFTj10RgO\nvTuE9wcmZvxZI4u+ylujwrqCjo4wIuGOur4/ES1MElVcAg8MDOCOO+6YWoMeHR1FV1cXJEnCww8/\njHQ6jYceesizwZJ/WJaFiUwOhunAsFzooXBTbLN56uVTeP9P586HXX1RJ/bsWlv160zmDPzqnY/x\ny98MYGzSmPFnqc4Itn9mBa7euBxtkfpu3nZsG3AttLeF0NEeb4q/M6JmtaQr6EQiMfW/9+zZgzvu\nuKPi5/J8V2+lUrU9Q3f6OrJpO3CFBE0/t0aay+fneXZwdEZ12I6Y8Xh0NDfn9ycSsak/F0Lgo6Es\nfv3uYEVFX2bBxGjBnOOVa8u2DCiSi/a2CGLRKCwTGBnJ1uW9l6rWn2W6EOfYe6lU9XeXqwro8y+2\n0+k0UqkUAOCll17CmjVrqh4A+ZMQArl8HkXDumDrU9BuW1fjirWlz/P0NeiFmJaD37xfOt7x9Bn/\nFH0BgGUZ0BWB7s4Ywiz6IgqUigP6nnvuweHDhzE+Po7Pf/7zuOuuu3D48GGcOHECsixjxYoVePDB\nB70cK3nogm5d05qDtNLWJ1mSKl5zHhkv4OWjA/i/xz5G0ZxZ9LUyFcPWDX0NKfoCANMoIKzJ6Eu0\nQdOatAcqUZOrag26lng7xVsL3bKaO5Cb9dq4Nvxa9AWUqueFYyISUtDZHm+av0vefvUe59h7nt/i\npuASQqBQKCJfNC64Qm729pm1kMmbOHIqjcPHhy7s9BUPYcuGXly5JoVouP5Xq6ZRQEiT0RHV0RZL\n1v39icgb/LHcxIrFIvIFA4btlAJZZSBXo5Kiry9s/QR6O0J17/RVvlqOhlSkejqb5mqZiM7hj+km\nYhgG8oUiTNtFtljE+IQBVdMgKRp0/vyumFnu9DVn0de54x2nV3HXQ7kFZzwSQnu8sqtlVwi8fuw0\n+tM5rEy4KS4BAAAVHElEQVTFsG3jsoadF01ElWNAB5jjOKWtT5YN03IhIEPTQ4AM6OEI1Lzb6CEG\nyki509d76QuKvhrZ6QsonSIVUrGoauzXj53Gz98udQF8r7+0x/uaTctrPkYiqi0GdIBML+wyLQf2\nVAvN5j4X2Ut+LvoCAMsoIKzLWJaML7oauz+dm/cxEfkTA9rnTNNELl+AYTkwp60jt+IhE7WULVh4\n88Qw3jgxS9HX1PGOjSn6Kh3xWEAsrKKnBr2xV6ZiU1fO5cdE5H8MaJ8RQiCTzcEwLRiWCyHJ0LQQ\nwHXkJSsXfR06Poj/9/vZi762rO/FJy/qbMgabfk0qVhYRW9vomaHVmzbuAwAZqxBE5H/MaB9oFAs\nolAwYFgObEdA0UKQZd62rpWFi7568Nl1PUi017/TV5lp5NEW1tDXl6h5f2xZkrjmTBRADOgGKBd3\nFU0bpuVAkrVStbWqQePfSM34ueirzDQKiOgyVtbwipmImgPjoA6mNwmZUdwlh6CxPXJN+b3oq8wy\niwipEpZ1t7MVJxHNigHtkenFXZYtIKs6i7s8lMmbeOtk2pdFX9PZtgVVcpDq4uEVRDQ/BnSNOI5T\nCuRZirs0Fnd5opKir+nHOzaS4ziAa6IrHkEs2tHQsRBRMDCgF6lYLKJQNGCe7WvtCkDTw9yTXAfV\ndPpqNNsyIcNBPFp55y8iIoABXZHy1bFp2aWDJhwX8tnCLshgINfJfEVfjT7e8XyWZUCTBZLtUUQi\njf9FgYiChwE9C8MwkCsUp059Ond1zIMm6i0oRV9llmUgpAj0JRbf+YuICGBAA7iwOQigQNV1Xh03\nkJ+Pd5xNOZh7u9qg6/zQENHStWxA5wsFFItm6ShGy4Wqh9kcpMH83ulrNpZpQnKLDGYiqrmWCGgh\nBArFIopFE6btwLRcKKoOReVRjH4QpKKvMtsyocou+pKdyOj+uIonoubStAE9vX2m5biQFR2qqrGn\ntY8EodPX+WzLhCI5SLbHEImEEQ6HkMmYCz+RiKhKTRPQ87XPZFGXfwSt6KvMMovQFCDZEUUk7J8r\neSJqXoGOrny+wPaZATHv8Y4+LPoqM40CwpqE3gTXmImovgIV0LZtI5vLwbBcmJYLSdGgqmyf6VdB\nLPoCzh37GA0rSPV0QlG4JkJE9efrgBZCIJfPo2hYMCwHrpCg6WFABq+SfSyIRV9AaZnEtU20xzS0\nJ2p/7CMRUTV8F9CmaSKbL8C0HJi2C0UNQVF0KBrA6xh/C1Knr+lsy4IMm+04p3GFwOvHTqM/ncPK\nVAzbNi7z1V0OolbQ8IA+1yTEhmE5Mw6ZYLW1/1VS9LVlQy9W+qzoCwBsy4AqCyTiEUR5gMUMrx87\njZ+/PQAAeK9/HABwzabljRwSUctpSECbponRsYnzmoTobBISIPMe7+jjoi/gXEV2dyePfJxLfzo3\n72Mi8l5DAnr4zCRMwSYhQRPUoq8yyzKgK4IV2RVYmYpNXTmXHxNRfTUkoGVZBuAs+H3kD0Et+ior\nd/1iO87Kbdu4DABmrEETUX01fA2a/GtkvIDDx4dwJGBFX2Wu4wCuOdX1iyonSxLXnIkarOKAPnDg\nAF599VUkk0k8//zzAICJiQns378fAwMDWLlyJR555BHE43HPBkve82vRlysEjp5KY3A0j75EFFes\nTc15G10IAccqoj3GqmwiCq6KA3r37t3Yu3cv7r333qmvPfHEE7j66qtx22234YknnsDjjz+O733v\ne54MlLzl9+Mdj55K49DxIQDAh4MZAMDmy3ou+D7LKCAWUdG1hH3M3GJERH5QcUBv3rwZAwMDM772\nyiuv4Mc//jEA4KabbsLevXsZ0AGyUNHXmos7sdUnRV+Do/l5H1tmEWFNQk9v19kah8XjFiMi8oMl\nrUGPjo6iu7sbAJBKpTA2NlaTQZG3glj01ZeITl05lx8D0499jEPTanN1zy1GROQHLBJrIUEq+jp/\nzfkza0q/CJYfb1rVBdcqeFIAxi1GROQHSwroZDKJkZERdHd3I51OI5FIVPzcRII/9LyWSMTguC5+\n+/4Z/OJoP058ODrjzzVVxuZ1vfj8FStxybL2Bo1ydq+/M4C3Tg0DAPrTWcRiOq773J/BdV04VhFd\n7VF0tHtTqHbjjjWIx8P4cHASn+hrx86rLoYsz32LP5ViYaTXOMfe4xz7T1UBLYSY8XjHjh04ePAg\nbr/9djzzzDPYuXNnxa81Osrbhl5SQxpePvQh3jgxhPHsLEVf63tx5dpzRV9++/v44E/jsB0x4/Hq\nnhDaIio6O9phGgLpdGaeV1iaT1+awKcvLf3CeeZMds7vS6Xino6DOMf1wDn23mJ+Aao4oO+55x4c\nPnwY4+Pj+PznP4+77roLt99+O7797W/jpz/9KZYvX45HH3206gFQ7QSp6Gsh09ecbcvAso4OrKhB\nARgRUVBI4vzL4jr4eGgUZ8ater9t0wpi0ddCXCHwxv8bwPBoFp+8OIlrr7jYl79U8MrDe5xj73GO\nvefpFTT5z3zHO35iWTs2r035puirGrZtQYGNL269hIdZEFHLYkAHzEKdvjau6sbWDb3YuLbXd+vK\nC3HOtubsikcQ4/GPRNTiGNABkS1YeOvk8Nydvs4r+goStuYkIroQA9rHmqnoay6WUUAsrKKrd/Gt\nOYmImhED2oeasejrfPbZs5mX93RCUXgoOBHR+RjQPhKkTl+L5dg2JFjo7mxjARgR0TwY0A3m5fGO\n5XaZp0dzMAwHIV3BsmRs3qMavVLqAGago43rzERElWBAN0i56KvSTl+LUT6iMV+wkCtaiIU1/HGo\n1BVrtqMavSCEgG0WEI/q6EhynZmIqFIM6Dqqd9FX+UhGy3Fn/P/zj2r0imUUEAnJ6O1NsAMYEVGV\nGNB1YFoO3vngDA69O1jXoq9yu0xNkWFaDjRFnvq6l0yziLAqsQCMiGgJGNAeanTR1xVrUwAw6xq0\nF2zLgKYILKvh2cxERK2KAV1jritwsoJOX4sp+qqWLEl1WWu2LROq7KK7M8bKbCKiGmFA10g9ir78\nxrYsyJKNZHsMkUhw92QTEfkRA3oJykVfh48P4be/P9OUnb5m49g2ICz2zCYi8hADehEaVfTVaK7r\nwrUN9swmIqoDBnQVGl301SjlwyziUR0d3QxmIqJ6YEAvwE9FX/VWbjLSFtHQmWCTESKiemJAz2G+\noq+us0Vfm5us6Gs608ijLayhry/JYCYiagAG9DQLFn1d1ImtG5qv6Gs6yyggrMtYye5fREQNxYDG\n/Mc7RkIqNq9NYcv65iv6ms4yiwipQF93O5uMEBH5QEsH9HxFXytSMWxd34uNq7qbruhrunKTkVQX\nm4wQEflJywX0wkVfSWxd34eVPc1X9DWd4ziAa57dy+xtb24iIqpeywR0qxd9lZUrs9tjIXS0c8sU\nEZFfNXVAV1z0tbITstycRV/TlY9/ZGU2EZH/NWVAz9fpq1WKvqazLQO6IlgARkQUIE0V0At1+trS\nAkVf0zm2DRkWujvbWABGRBQwgQ/octHX4eND+F1/6xZ9TSeEgGXk0R5VEG9rb/RwiIhoEQIb0Cz6\nmp1lFhALq7hkxQqMjGQbPRwiIlqkQAV0JUVfWzb0Yk2LFH1NV15nXp7qhKIoLAIjIgq4mgT0jh07\n0NbWBlmWoaoqnn766Vq87BTTdvDO+yz6mo1tW1Bgc52ZiKjJ1CSgJUnCf//3f6Ojo6MWLzdlZOJs\n0dep1u30NRfHtiEJC4l4FNFobeediIgaryYBLYSA67q1eCkWfS3AdV24toH2WAjtcTYaISJqVjW7\ngv7GN74BSZLwV3/1V9izZ0/Vr8Gir/md6wCmo6ObwUxE1OxqEtA/+clPkEqlMDo6in379uHSSy/F\n5s2bF3wej3esjGWUKrPZAYyIqHVIQgix8LdV7rHHHkMsFsO+ffvm/J4P+9M4fHIUvzjSjz8Nz9wK\nFAur+Nym5dj+mZVIdUZqObTAsUwTYQ1IJTugKEqjh0NERHW05CvoQqEA13URi8WQz+fxq1/9Cnfe\neee8z/n7//MG8oY942sXFH25LkZHc0sdXiDZlgVFstHV0QZFCmF0NL/wk86TSsWRTmc8GB1Nx3n2\nHufYe5xj76VS8aqfs+SAHhkZwZ133glJkuA4Dr7yla/gz//8z+d9Tjmcy0VfW9b34aIWLfqaznVd\nCNtAV3sEMVZmExG1tCUH9EUXXYTnnnuuqucsS0axaXV3Sxd9TccCMCIiOl9DOon9729ciTPjViPe\n2nd4BCQREc0mUK0+mwmPgCQiovkwoOvMsW1IPAKSiIgWwICuk3IHsI62MI+AJCKiBTGgPXauACzE\nAjAiIqoYA9pDppFHW1hjARgREVWNAe0ByywirElY0dPFDmBERLQoDOgasiwDIUWgLxlnZTYRES0J\nA7oGbMuEKrvo6WpDSNcbPRwiImoCDOglKG+ZSrbHEImEGz0cIiJqIgzoReCWKSIi8hoDukqWUUA8\nqqEjmWBlNhEReYYBXSHLMhBWgZ7eLsiy3OjhEBFRk2NAL8CxbciwkGJrTiIiqiMG9BxKHcCK6Ixz\nnZmIiOqPAT0L08ijLaKhr4/rzERE1BgM6GlKR0CCHcCIiKjhGNDgEZBEROQ/LR3QruvCsQyuMxMR\nke+0bEBbRgFtERWd3M9MREQ+1HIBzf3MREQUBC0T0OUDLXq72qDzQAsiIvK5pg9oHmhBRERB1LQB\nzQMtiIgoyJouoEsdwApoj+no6E42ejhERESL0lQBbRp5tIU19PUlWZlNRESB1hQBXa7MZgcwIiJq\nFoEOaFZmExFRswpkQLMym4iIml2gApqV2URE1Cpq0krrtddewxe/+EVcf/31eOKJJ2rxkjMIIWAZ\necR0gZV9ScTbYjV/DyIiIj9ZckC7rot/+qd/wn/8x3/ghRdewIsvvogPPvigFmMDUOqZHZJtrOxL\noqM9XrPXJSIi8rMlB/SxY8dwySWXYMWKFdA0DV/+8pfxyiuvLHlglmVAdg0s7+lEoquD26aIiKil\nLDmgh4aGsGzZsqnHvb29GB4eXvTrObYNYReQ6oyip5vbpoiIqDUtuUhMCLGo5yUSM9eRyx3Akp2d\nXGOukVSKSwL1wHn2HufYe5xj/1lyQPf19eHjjz+eejw0NISenp4Fnzc6mpv635ZRQCyioqujHcWC\ni2Ihs9RhtbxUKo50mvPoNc6z9zjH3uMce28xvwAt+Rb3pz71KXz00UcYGBiAaZp48cUXsXPnzoqe\na1sGZLdYWmfu5DozERFR2ZKvoBVFwQMPPIC/+7u/gxACN998M1atWjXvc2zbhmsV2GiEiIhoDjVp\nVLJ9+3Zs37694u/v7e5ARI/U4q2JiIiaUk0alVQrFAo14m2JiIgCoyEBTURERPNjQBMREfkQA5qI\niMiHGNBEREQ+xIAmIiLyIQY0ERGRDzGgiYiIfIgBTURE5EMMaCIiIh9iQBMREfkQA5qIiMiHGNBE\nREQ+xIAmIiLyIQY0ERGRDzGgiYiIfIgBTURE5EMMaCIiIh9iQBMREfkQA5qIiMiHGNBEREQ+xIAm\nIiLyIQY0ERGRDzGgiYiIfIgBTURE5EMMaCIiIh9iQBMREfkQA5qIiMiHGNBEREQ+pC7lyY899hie\neuopJJNJAMD+/fuxffv2mgyMiIiolS0poAFg37592LdvXy3GQkRERGct+Ra3EKIW4yAiIqJplhzQ\nTz75JG644Qb8wz/8AzKZTC3GRERE1PIkscAl8L59+zAyMnLB1/fv349Pf/rT6OrqgiRJePjhh5FO\np/HQQw9V9MbpNMPcS6lUnHNcB5xn73GOvcc59l4qFa/6OQsGdKUGBgZwxx134Pnnn6/FyxEREbW0\nJd3iTqfTU//7pZdewpo1a5Y8ICIiIlpiFfcPf/hDnDhxArIsY8WKFXjwwQdrNS4iIqKWVrNb3ERE\nRFQ77CRGRETkQwxoIiIiH2JAExER+dCSW31W47XXXsNDDz0EIQS++tWv4vbbb6/n27eMHTt2oK2t\nDbIsQ1VVPP30040eUuAdOHAAr776KpLJ5NRWwomJCezfvx8DAwNYuXIlHnnkEcTj1e91pHNmm2f2\n/K+twcFB3HvvvRgZGYGiKPja176Gr3/96/w819D5c7xnzx7s3bu3+s+yqBPHccSuXbtEf3+/ME1T\n/OVf/qV4//336/X2LWXHjh1ifHy80cNoKm+++aY4fvy4+Iu/+Iupr/3gBz8QTzzxhBBCiMcff1z8\n8Ic/bNTwmsZs8/xv//Zv4j//8z8bOKrmMjw8LI4fPy6EECKbzYrrrrtOvP/++/w819Bcc1ztZ7lu\nt7iPHTuGSy65BCtWrICmafjyl7+MV155pV5v31KEEHBdt9HDaCqbN29Ge3v7jK+98soruOmmmwAA\nN910E15++eVGDK2pzDbPAHv+11IqlcK6desAALFYDKtWrcLQ0BA/zzU02xwPDw8DqO6zXLeAHhoa\nwrJly6Ye9/b2Tg2YakuSJHzjG9/AV7/6VTz11FONHk7TGh0dRXd3N4DSP8ixsbEGj6h5see/N/r7\n+3Hy5Els2rQJZ86c4efZA+U53rhxI4DqPst1C2j+Blw/P/nJT3Dw4EH8+7//O5588km89dZbjR4S\n0aL9zd/8DV5++WU899xz6O7uxve///1GD6kp5HI53H333Thw4ABisRgkSWr0kJrO+XNc7We5bgHd\n19eHjz/+eOrx0NAQenp66vX2LSWVSgEAEokEvvCFL+C3v/1tg0fUnJLJ5NRBMul0GolEosEjak6J\nRGIqPPbs2cPPcw3Yto27774bN9xwA3bt2gWAn+dam22Oq/0s1y2gP/WpT+Gjjz7CwMAATNPEiy++\niJ07d9br7VtGoVBALpcDAOTzefzqV7/CJz/5yQaPqjmcfxdox44dOHjwIADgmWee4ee5Rs6fZ/b8\nr70DBw5g9erVuPXWW6e+xs9zbc02x9V+luva6vO1117DP//zP0MIgZtvvpnbrDzwpz/9CXfeeSck\nSYLjOPjKV77Cea6Be+65B4cPH8b4+Di6u7tx1113YdeuXfj2t7+N06dPY/ny5Xj00UdnLXCiys02\nz4cPH76g5395rZSqd+TIEfzt3/4t1qxZA0mSIEkS9u/fj40bN+I73/kOP881MNccv/DCC1V9ltmL\nm4iIyIfYSYyIiMiHGNBEREQ+xIAmIiLyIQY0ERGRDzGgiYiIfIgBTURE5EMMaCIiIh9iQBMREfnQ\n/wc32622TZPq9wAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674c6fc890>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "MoWj1knmTZPI"
      },
      "cell_type": "markdown",
      "source": [
        "That's a simple scatterplot with a nice regression line fit to it, all with just one call to Seaborn's [regplot](http://seaborn.pydata.org/generated/seaborn.regplot.html#seaborn.regplot).\n",
        "\n",
        "Here's a Seaborn [heatmap](https://seaborn.pydata.org/generated/seaborn.heatmap.html):"
      ]
    },
    {
      "metadata": {
        "cellView": "both",
        "colab_type": "code",
        "id": "Fjw7UfGZQcL9",
        "outputId": "db8cf44f-dd21-491f-ef2d-e504d8ee7fe1",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Make a 10 x 10 heatmap of some random data\n",
        "side_length = 10\n",
        "# Start with a 10 x 10 matrix with values randomized around 5\n",
        "data = 5 + np.random.randn(side_length, side_length)\n",
        "# The next two lines make the values larger as we get closer to (9, 9)\n",
        "data += np.arange(side_length)\n",
        "data += np.reshape(np.arange(side_length), (side_length, 1))\n",
        "# Generate the heatmap\n",
        "sns.heatmap(data)\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x55674c44f410>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "beTgCbVa_wFA"
      },
      "cell_type": "markdown",
      "source": [
        "## Altair"
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "610XkhS2Atb0"
      },
      "cell_type": "markdown",
      "source": [
        "Altair is installed and correctly enabled by default, and can be imported and used directly in Colab: "
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "bqIjKoB0s2MF",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import altair as alt"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "Him9xzhWtMD0"
      },
      "cell_type": "markdown",
      "source": [
        "### Interactive Scatter Chart\n",
        "\n",
        "Now you can use Altair to create any available chart type; for example, here is an interactive scatter plot of the cars dataset:"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "SYsgSJsyeaCA",
        "outputId": "4f2b6dac-3df8-4d78-d69b-834674b2a90d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 389
        }
      },
      "cell_type": "code",
      "source": [
        "from vega_datasets import data\n",
        "cars = data.cars()\n",
        "\n",
        "alt.Chart(cars).mark_point().encode(\n",
        "    x='Horsepower',\n",
        "    y='Miles_per_Gallon',\n",
        "    color='Origin',\n",
        ").interactive()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "<!DOCTYPE html>\n",
              "<html>\n",
              "<head>\n",
              "  <style>\n",
              "    .vega-actions a {\n",
              "        margin-right: 12px;\n",
              "        color: #757575;\n",
              "        font-weight: normal;\n",
              "        font-size: 13px;\n",
              "    }\n",
              "    .error {\n",
              "        color: red;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "<script src=\"https://cdn.jsdelivr.net/npm//[email protected]\"></script>\n",
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1950, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 14.0, \"Cylinders\": 8, \"Displacement\": 400.0, \"Horsepower\": 150.0, \"Miles_per_Gallon\": 11.0, \"Name\": \"chevrolet impala\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4997, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 12.5, \"Cylinders\": 8, \"Displacement\": 400.0, \"Horsepower\": 167.0, \"Miles_per_Gallon\": 12.0, \"Name\": \"ford country\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4906, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 13.0, \"Cylinders\": 8, \"Displacement\": 360.0, \"Horsepower\": 170.0, \"Miles_per_Gallon\": 13.0, \"Name\": \"plymouth custom suburb\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4654, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 12.5, \"Cylinders\": 8, \"Displacement\": 350.0, \"Horsepower\": 180.0, \"Miles_per_Gallon\": 12.0, \"Name\": \"oldsmobile vista cruiser\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4499, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 6, \"Displacement\": 232.0, \"Horsepower\": 100.0, \"Miles_per_Gallon\": 18.0, \"Name\": \"amc gremlin\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2789, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 19.0, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 20.0, \"Name\": \"toyota carina\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2279, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 19.5, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 72.0, \"Miles_per_Gallon\": 21.0, \"Name\": \"chevrolet vega\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2401, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 16.5, \"Cylinders\": 4, \"Displacement\": 108.0, \"Horsepower\": 94.0, \"Miles_per_Gallon\": 22.0, \"Name\": \"datsun 610\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2379, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 13.5, \"Cylinders\": 3, \"Displacement\": 70.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 18.0, \"Name\": \"maxda rx3\", \"Origin\": \"Japan\", 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\"Displacement\": 400.0, \"Horsepower\": 230.0, \"Miles_per_Gallon\": 16.0, \"Name\": \"pontiac grand prix\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4278, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 19.5, \"Cylinders\": 4, \"Displacement\": 68.0, \"Horsepower\": 49.0, \"Miles_per_Gallon\": 29.0, \"Name\": \"fiat 128\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1867, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 116.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 24.0, \"Name\": \"opel manta\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2158, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 14.0, \"Cylinders\": 4, \"Displacement\": 114.0, \"Horsepower\": 91.0, \"Miles_per_Gallon\": 20.0, \"Name\": \"audi 100ls\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2582, \"Year\": \"1973-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 121.0, \"Horsepower\": 112.0, \"Miles_per_Gallon\": 19.0, \"Name\": \"volvo 144ea\", \"Origin\": 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14.0, \"Name\": \"dodge coronet custom (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4457, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 16.0, \"Cylinders\": 8, \"Displacement\": 302.0, \"Horsepower\": 140.0, \"Miles_per_Gallon\": 14.0, \"Name\": \"ford gran torino (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4638, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 8, \"Displacement\": 304.0, \"Horsepower\": 150.0, \"Miles_per_Gallon\": 14.0, \"Name\": \"amc matador (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4257, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 16.5, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 83.0, \"Miles_per_Gallon\": 29.0, \"Name\": \"audi fox\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2219, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 79.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 26.0, \"Name\": \"volkswagen dasher\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1963, \"Year\": 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\"Miles_per_Gallon\": 24.0, \"Name\": \"fiat 128\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2108, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 14.0, \"Cylinders\": 4, \"Displacement\": 116.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 26.0, \"Name\": \"fiat 124 tc\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2246, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 4, \"Displacement\": 120.0, \"Horsepower\": 97.0, \"Miles_per_Gallon\": 24.0, \"Name\": \"honda civic\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2489, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 108.0, \"Horsepower\": 93.0, \"Miles_per_Gallon\": 26.0, \"Name\": \"subaru\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2391, \"Year\": \"1974-01-01\"}, {\"Acceleration\": 16.0, \"Cylinders\": 4, \"Displacement\": 79.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 31.0, \"Name\": \"fiat x1.9\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2000, \"Year\": 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170.0, \"Miles_per_Gallon\": 16.0, \"Name\": \"pontiac catalina\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4668, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 14.0, \"Cylinders\": 8, \"Displacement\": 350.0, \"Horsepower\": 145.0, \"Miles_per_Gallon\": 15.0, \"Name\": \"chevrolet bel air\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4440, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 8, \"Displacement\": 318.0, \"Horsepower\": 150.0, \"Miles_per_Gallon\": 16.0, \"Name\": \"plymouth grand fury\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4498, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 13.5, \"Cylinders\": 8, \"Displacement\": 351.0, \"Horsepower\": 148.0, \"Miles_per_Gallon\": 14.0, \"Name\": \"ford ltd\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4657, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 21.0, \"Cylinders\": 6, \"Displacement\": 231.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 17.0, \"Name\": \"buick century\", \"Origin\": \"USA\", \"Weight_in_lbs\": 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171.0, \"Horsepower\": 97.0, \"Miles_per_Gallon\": 18.0, \"Name\": \"ford pinto\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2984, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 14.0, \"Cylinders\": 4, \"Displacement\": 90.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 29.0, \"Name\": \"volkswagen rabbit\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1937, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 17.0, \"Cylinders\": 6, \"Displacement\": 232.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 19.0, \"Name\": \"amc pacer\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3211, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 4, \"Displacement\": 115.0, \"Horsepower\": 95.0, \"Miles_per_Gallon\": 23.0, \"Name\": \"audi 100ls\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2694, \"Year\": \"1975-01-01\"}, {\"Acceleration\": 17.0, \"Cylinders\": 4, \"Displacement\": 120.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 23.0, \"Name\": \"peugeot 504\", \"Origin\": \"Europe\", 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116.0, \"Horsepower\": 81.0, \"Miles_per_Gallon\": 25.0, \"Name\": \"opel 1900\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2220, \"Year\": \"1976-01-01\"}, {\"Acceleration\": 14.9, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 92.0, \"Miles_per_Gallon\": 25.0, \"Name\": \"capri ii\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2572, \"Year\": \"1976-01-01\"}, {\"Acceleration\": 17.7, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 79.0, \"Miles_per_Gallon\": 26.0, \"Name\": \"dodge colt\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2255, \"Year\": \"1976-01-01\"}, {\"Acceleration\": 15.3, \"Cylinders\": 4, \"Displacement\": 101.0, \"Horsepower\": 83.0, \"Miles_per_Gallon\": 27.0, \"Name\": \"renault 12tl\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2202, \"Year\": \"1976-01-01\"}, {\"Acceleration\": 13.0, \"Cylinders\": 8, \"Displacement\": 305.0, \"Horsepower\": 140.0, \"Miles_per_Gallon\": 17.5, \"Name\": \"chevrolet chevelle malibu classic\", \"Origin\": \"USA\", 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{\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 122.0, \"Horsepower\": 96.0, \"Miles_per_Gallon\": 25.5, \"Name\": \"plymouth arrow gs\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2300, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 16.8, \"Cylinders\": 4, \"Displacement\": 85.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 33.5, \"Name\": \"datsun f-10 hatchback\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1945, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 12.5, \"Cylinders\": 8, \"Displacement\": 305.0, \"Horsepower\": 145.0, \"Miles_per_Gallon\": 17.5, \"Name\": \"chevrolet caprice classic\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3880, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 19.0, \"Cylinders\": 8, \"Displacement\": 260.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 17.0, \"Name\": \"oldsmobile cutlass supreme\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4060, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 13.7, \"Cylinders\": 8, \"Displacement\": 318.0, 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14.5, \"Cylinders\": 8, \"Displacement\": 351.0, \"Horsepower\": 149.0, \"Miles_per_Gallon\": 16.0, \"Name\": \"ford thunderbird\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4335, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 78.0, \"Miles_per_Gallon\": 29.0, \"Name\": \"volkswagen rabbit custom\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1940, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 16.0, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 24.5, \"Name\": \"pontiac sunbird coupe\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2740, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 18.2, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 26.0, \"Name\": \"toyota corolla liftback\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2265, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 15.8, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 89.0, \"Miles_per_Gallon\": 25.5, \"Name\": \"ford mustang ii 2+2\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2755, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 17.0, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 63.0, \"Miles_per_Gallon\": 30.5, \"Name\": \"chevrolet chevette\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2051, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 15.9, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 83.0, \"Miles_per_Gallon\": 33.5, \"Name\": \"dodge colt m/m\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2075, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 30.0, \"Name\": \"subaru dl\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1985, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 14.1, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 78.0, \"Miles_per_Gallon\": 30.5, \"Name\": \"volkswagen dasher\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2190, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 6, \"Displacement\": 146.0, \"Horsepower\": 97.0, \"Miles_per_Gallon\": 22.0, \"Name\": \"datsun 810\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2815, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 12.8, \"Cylinders\": 4, \"Displacement\": 121.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 21.5, \"Name\": \"bmw 320i\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2600, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 13.5, \"Cylinders\": 3, \"Displacement\": 80.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 21.5, \"Name\": \"mazda rx-4\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2720, \"Year\": \"1977-01-01\"}, {\"Acceleration\": 21.5, \"Cylinders\": 4, \"Displacement\": 90.0, \"Horsepower\": 48.0, \"Miles_per_Gallon\": 43.1, \"Name\": \"volkswagen rabbit custom diesel\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1985, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.4, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 66.0, \"Miles_per_Gallon\": 36.1, \"Name\": \"ford fiesta\", \"Origin\": \"USA\", \"Weight_in_lbs\": 1800, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 19.4, \"Cylinders\": 4, \"Displacement\": 78.0, \"Horsepower\": 52.0, \"Miles_per_Gallon\": 32.8, \"Name\": \"mazda glc deluxe\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1985, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 18.6, \"Cylinders\": 4, \"Displacement\": 85.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 39.4, \"Name\": \"datsun b210 gx\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2070, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 60.0, \"Miles_per_Gallon\": 36.1, \"Name\": \"honda civic cvcc\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1800, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 8, \"Displacement\": 260.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 19.9, \"Name\": \"oldsmobile cutlass salon brougham\", \"Origin\": 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6, \"Displacement\": 200.0, \"Horsepower\": 85.0, \"Miles_per_Gallon\": 20.2, \"Name\": \"ford fairmont (auto)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2965, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.4, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 25.1, \"Name\": \"ford fairmont (man)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2720, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 17.2, \"Cylinders\": 6, \"Displacement\": 225.0, \"Horsepower\": 100.0, \"Miles_per_Gallon\": 20.5, \"Name\": \"plymouth volare\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3430, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 17.2, \"Cylinders\": 6, \"Displacement\": 232.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 19.4, \"Name\": \"amc concord\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3210, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.8, \"Cylinders\": 6, \"Displacement\": 231.0, \"Horsepower\": 105.0, \"Miles_per_Gallon\": 20.6, \"Name\": \"buick century 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{\"Acceleration\": 13.4, \"Cylinders\": 6, \"Displacement\": 231.0, \"Horsepower\": 165.0, \"Miles_per_Gallon\": 17.7, \"Name\": \"buick regal sport coupe (turbo)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3445, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 11.2, \"Cylinders\": 8, \"Displacement\": 302.0, \"Horsepower\": 139.0, \"Miles_per_Gallon\": 18.1, \"Name\": \"ford futura\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3205, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 13.7, \"Cylinders\": 8, \"Displacement\": 318.0, \"Horsepower\": 140.0, \"Miles_per_Gallon\": 17.5, \"Name\": \"dodge magnum xe\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4080, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 16.5, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 68.0, \"Miles_per_Gallon\": 30.0, \"Name\": \"chevrolet chevette\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2155, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.2, \"Cylinders\": 4, \"Displacement\": 134.0, \"Horsepower\": 95.0, \"Miles_per_Gallon\": 27.5, \"Name\": \"toyota corona\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2560, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.7, \"Cylinders\": 4, \"Displacement\": 119.0, \"Horsepower\": 97.0, \"Miles_per_Gallon\": 27.2, \"Name\": \"datsun 510\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2300, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 30.9, \"Name\": \"dodge omni\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2230, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.8, \"Cylinders\": 4, \"Displacement\": 134.0, \"Horsepower\": 95.0, \"Miles_per_Gallon\": 21.1, \"Name\": \"toyota celica gt liftback\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2515, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 16.7, \"Cylinders\": 4, \"Displacement\": 156.0, \"Horsepower\": 105.0, \"Miles_per_Gallon\": 23.2, \"Name\": \"plymouth sapporo\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2745, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 17.6, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 85.0, \"Miles_per_Gallon\": 23.8, \"Name\": \"oldsmobile starfire sx\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2855, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.9, \"Cylinders\": 4, \"Displacement\": 119.0, \"Horsepower\": 97.0, \"Miles_per_Gallon\": 23.9, \"Name\": \"datsun 200-sx\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2405, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.9, \"Cylinders\": 5, \"Displacement\": 131.0, \"Horsepower\": 103.0, \"Miles_per_Gallon\": 20.3, \"Name\": \"audi 5000\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2830, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 13.6, \"Cylinders\": 6, \"Displacement\": 163.0, \"Horsepower\": 125.0, \"Miles_per_Gallon\": 17.0, \"Name\": \"volvo 264gl\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3140, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.7, \"Cylinders\": 4, \"Displacement\": 121.0, \"Horsepower\": 115.0, \"Miles_per_Gallon\": 21.6, \"Name\": \"saab 99gle\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2795, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.8, \"Cylinders\": 6, \"Displacement\": 163.0, \"Horsepower\": 133.0, \"Miles_per_Gallon\": 16.2, \"Name\": \"peugeot 604sl\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3410, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 14.9, \"Cylinders\": 4, \"Displacement\": 89.0, \"Horsepower\": 71.0, \"Miles_per_Gallon\": 31.5, \"Name\": \"volkswagen scirocco\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1990, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 16.6, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 68.0, \"Miles_per_Gallon\": 29.5, \"Name\": \"honda Accelerationord lx\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2135, \"Year\": \"1978-01-01\"}, {\"Acceleration\": 15.4, \"Cylinders\": 6, \"Displacement\": 231.0, \"Horsepower\": 115.0, \"Miles_per_Gallon\": 21.5, \"Name\": \"pontiac lemans v6\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3245, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 18.2, \"Cylinders\": 6, \"Displacement\": 200.0, \"Horsepower\": 85.0, \"Miles_per_Gallon\": 19.8, \"Name\": \"mercury zephyr 6\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2990, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 17.3, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 22.3, \"Name\": \"ford fairmont 4\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2890, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 18.2, \"Cylinders\": 6, \"Displacement\": 232.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 20.2, \"Name\": \"amc concord dl 6\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3265, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 16.6, \"Cylinders\": 6, \"Displacement\": 225.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 20.6, \"Name\": \"dodge aspen 6\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3360, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 15.4, \"Cylinders\": 8, \"Displacement\": 305.0, \"Horsepower\": 130.0, \"Miles_per_Gallon\": 17.0, \"Name\": \"chevrolet caprice classic\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3840, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 13.4, \"Cylinders\": 8, \"Displacement\": 302.0, \"Horsepower\": 129.0, \"Miles_per_Gallon\": 17.6, \"Name\": \"ford ltd landau\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3725, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 13.2, \"Cylinders\": 8, \"Displacement\": 351.0, \"Horsepower\": 138.0, \"Miles_per_Gallon\": 16.5, \"Name\": \"mercury grand marquis\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3955, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 15.2, \"Cylinders\": 8, \"Displacement\": 318.0, \"Horsepower\": 135.0, \"Miles_per_Gallon\": 18.2, \"Name\": \"dodge st. regis\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3830, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.9, \"Cylinders\": 8, \"Displacement\": 350.0, \"Horsepower\": 155.0, \"Miles_per_Gallon\": 16.9, \"Name\": \"buick estate wagon (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4360, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.3, \"Cylinders\": 8, \"Displacement\": 351.0, \"Horsepower\": 142.0, \"Miles_per_Gallon\": 15.5, \"Name\": \"ford country squire (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 4054, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 8, \"Displacement\": 267.0, \"Horsepower\": 125.0, \"Miles_per_Gallon\": 19.2, \"Name\": \"chevrolet malibu classic (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3605, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 13.0, \"Cylinders\": 8, \"Displacement\": 360.0, \"Horsepower\": 150.0, \"Miles_per_Gallon\": 18.5, \"Name\": \"chrysler lebaron town @ country (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3940, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.0, \"Cylinders\": 4, \"Displacement\": 89.0, \"Horsepower\": 71.0, \"Miles_per_Gallon\": 31.9, \"Name\": \"vw rabbit custom\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1925, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 15.2, \"Cylinders\": 4, \"Displacement\": 86.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 34.1, \"Name\": \"maxda glc deluxe\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1975, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.4, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 80.0, \"Miles_per_Gallon\": 35.7, \"Name\": \"dodge colt hatchback custom\", \"Origin\": \"USA\", \"Weight_in_lbs\": 1915, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 4, \"Displacement\": 121.0, \"Horsepower\": 80.0, \"Miles_per_Gallon\": 27.4, \"Name\": \"amc spirit dl\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2670, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 20.1, \"Cylinders\": 5, \"Displacement\": 183.0, \"Horsepower\": 77.0, \"Miles_per_Gallon\": 25.4, \"Name\": \"mercedes benz 300d\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3530, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 17.4, \"Cylinders\": 8, \"Displacement\": 350.0, \"Horsepower\": 125.0, \"Miles_per_Gallon\": 23.0, \"Name\": \"cadillac eldorado\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3900, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 24.8, \"Cylinders\": 4, \"Displacement\": 141.0, \"Horsepower\": 71.0, \"Miles_per_Gallon\": 27.2, \"Name\": \"peugeot 504\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3190, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 22.2, \"Cylinders\": 8, \"Displacement\": 260.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 23.9, \"Name\": \"oldsmobile cutlass salon brougham\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3420, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 13.2, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 34.2, \"Name\": \"plymouth horizon\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2200, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.9, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 34.5, \"Name\": \"plymouth horizon tc3\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2150, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 19.2, \"Cylinders\": 4, \"Displacement\": 85.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 31.8, \"Name\": \"datsun 210\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2020, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.7, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 69.0, \"Miles_per_Gallon\": 37.3, \"Name\": \"fiat strada custom\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2130, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 16.0, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 28.4, \"Name\": \"buick skylark limited\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2670, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 11.3, \"Cylinders\": 6, \"Displacement\": 173.0, \"Horsepower\": 115.0, \"Miles_per_Gallon\": 28.8, \"Name\": \"chevrolet citation\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2595, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 12.9, \"Cylinders\": 6, \"Displacement\": 173.0, \"Horsepower\": 115.0, \"Miles_per_Gallon\": 26.8, \"Name\": \"oldsmobile omega brougham\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2700, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 13.2, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 33.5, \"Name\": \"pontiac phoenix\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2556, \"Year\": \"1979-01-01\"}, {\"Acceleration\": 14.7, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 76.0, \"Miles_per_Gallon\": 41.5, \"Name\": \"vw rabbit\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2144, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 18.8, \"Cylinders\": 4, \"Displacement\": 89.0, \"Horsepower\": 60.0, \"Miles_per_Gallon\": 38.1, \"Name\": \"toyota corolla tercel\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1968, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 32.1, \"Name\": \"chevrolet chevette\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2120, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 4, \"Displacement\": 86.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 37.2, \"Name\": \"datsun 310\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2019, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 16.5, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 28.0, \"Name\": \"chevrolet citation\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2678, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 18.1, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 26.4, \"Name\": \"ford fairmont\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2870, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 20.1, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 24.3, \"Name\": \"amc concord\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3003, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 18.7, \"Cylinders\": 6, \"Displacement\": 225.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 19.1, \"Name\": \"dodge aspen\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3381, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.8, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 78.0, \"Miles_per_Gallon\": 34.3, \"Name\": \"audi 4000\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2188, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.5, \"Cylinders\": 4, \"Displacement\": 134.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 29.8, \"Name\": \"toyota corona liftback\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2711, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 17.5, \"Cylinders\": 4, \"Displacement\": 120.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 31.3, \"Name\": \"mazda 626\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2542, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 4, \"Displacement\": 119.0, \"Horsepower\": 92.0, \"Miles_per_Gallon\": 37.0, \"Name\": \"datsun 510 hatchback\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2434, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.2, \"Cylinders\": 4, \"Displacement\": 108.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 32.2, \"Name\": \"toyota corolla\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2265, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 17.9, \"Cylinders\": 4, \"Displacement\": 86.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 46.6, \"Name\": \"mazda glc\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2110, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 14.4, \"Cylinders\": 4, \"Displacement\": 156.0, \"Horsepower\": 105.0, \"Miles_per_Gallon\": 27.9, \"Name\": \"dodge colt\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2800, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 19.2, \"Cylinders\": 4, \"Displacement\": 85.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 40.8, \"Name\": \"datsun 210\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2110, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 21.7, \"Cylinders\": 4, \"Displacement\": 90.0, \"Horsepower\": 48.0, \"Miles_per_Gallon\": 44.3, \"Name\": \"vw rabbit c (diesel)\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2085, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 23.7, \"Cylinders\": 4, \"Displacement\": 90.0, \"Horsepower\": 48.0, \"Miles_per_Gallon\": 43.4, \"Name\": \"vw dasher (diesel)\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2335, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 19.9, \"Cylinders\": 5, \"Displacement\": 121.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 36.4, \"Name\": \"audi 5000s (diesel)\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2950, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 21.8, \"Cylinders\": 4, \"Displacement\": 146.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 30.0, \"Name\": \"mercedes-benz 240d\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3250, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 13.8, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 44.6, \"Name\": \"honda civic 1500 gl\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1850, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 17.3, \"Cylinders\": 4, \"Displacement\": 85.0, \"Horsepower\": null, \"Miles_per_Gallon\": 40.9, \"Name\": \"renault lecar deluxe\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1835, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 18.0, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 33.8, \"Name\": \"subaru dl\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2145, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.3, \"Cylinders\": 4, \"Displacement\": 89.0, \"Horsepower\": 62.0, \"Miles_per_Gallon\": 29.8, \"Name\": \"vokswagen rabbit\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1845, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 11.4, \"Cylinders\": 6, \"Displacement\": 168.0, \"Horsepower\": 132.0, \"Miles_per_Gallon\": 32.7, \"Name\": \"datsun 280-zx\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2910, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 12.5, \"Cylinders\": 3, \"Displacement\": 70.0, \"Horsepower\": 100.0, \"Miles_per_Gallon\": 23.7, \"Name\": \"mazda rx-7 gs\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2420, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.1, \"Cylinders\": 4, \"Displacement\": 122.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 35.0, \"Name\": \"triumph tr7 coupe\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2500, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 14.3, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": null, \"Miles_per_Gallon\": 23.6, \"Name\": \"ford mustang cobra\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2905, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 17.0, \"Cylinders\": 4, \"Displacement\": 107.0, \"Horsepower\": 72.0, \"Miles_per_Gallon\": 32.4, \"Name\": \"honda Accelerationord\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2290, \"Year\": \"1980-01-01\"}, {\"Acceleration\": 15.7, \"Cylinders\": 4, \"Displacement\": 135.0, \"Horsepower\": 84.0, \"Miles_per_Gallon\": 27.2, \"Name\": \"plymouth reliant\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2490, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 84.0, \"Miles_per_Gallon\": 26.6, \"Name\": \"buick skylark\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2635, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.4, \"Cylinders\": 4, \"Displacement\": 156.0, \"Horsepower\": 92.0, \"Miles_per_Gallon\": 25.8, \"Name\": \"dodge aries wagon (sw)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2620, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 12.6, \"Cylinders\": 6, \"Displacement\": 173.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 23.5, \"Name\": \"chevrolet citation\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2725, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 12.9, \"Cylinders\": 4, \"Displacement\": 135.0, \"Horsepower\": 84.0, \"Miles_per_Gallon\": 30.0, \"Name\": \"plymouth reliant\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2385, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.9, \"Cylinders\": 4, \"Displacement\": 79.0, \"Horsepower\": 58.0, \"Miles_per_Gallon\": 39.1, \"Name\": \"toyota starlet\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1755, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 4, \"Displacement\": 86.0, \"Horsepower\": 64.0, \"Miles_per_Gallon\": 39.0, \"Name\": \"plymouth champ\", \"Origin\": \"USA\", \"Weight_in_lbs\": 1875, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.1, \"Cylinders\": 4, \"Displacement\": 81.0, \"Horsepower\": 60.0, \"Miles_per_Gallon\": 35.1, \"Name\": \"honda civic 1300\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1760, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.8, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 32.3, \"Name\": \"subaru\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2065, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 19.4, \"Cylinders\": 4, \"Displacement\": 85.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 37.0, \"Name\": \"datsun 210\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1975, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.3, \"Cylinders\": 4, \"Displacement\": 89.0, \"Horsepower\": 62.0, \"Miles_per_Gallon\": 37.7, \"Name\": \"toyota tercel\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2050, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.0, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 68.0, \"Miles_per_Gallon\": 34.1, \"Name\": \"mazda glc 4\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1985, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.9, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 63.0, \"Miles_per_Gallon\": 34.7, \"Name\": \"plymouth horizon 4\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2215, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.2, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 34.4, \"Name\": \"ford escort 4w\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2045, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 20.7, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 65.0, \"Miles_per_Gallon\": 29.9, \"Name\": \"ford escort 2h\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2380, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.2, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 74.0, \"Miles_per_Gallon\": 33.0, \"Name\": \"volkswagen jetta\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2190, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.8, \"Cylinders\": 4, \"Displacement\": 100.0, \"Horsepower\": null, \"Miles_per_Gallon\": 34.5, \"Name\": \"renault 18i\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2320, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.4, \"Cylinders\": 4, \"Displacement\": 107.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 33.7, \"Name\": \"honda prelude\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2210, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.8, \"Cylinders\": 4, \"Displacement\": 108.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 32.4, \"Name\": \"toyota corolla\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2350, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.8, \"Cylinders\": 4, \"Displacement\": 119.0, \"Horsepower\": 100.0, \"Miles_per_Gallon\": 32.9, \"Name\": \"datsun 200sx\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2615, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 18.3, \"Cylinders\": 4, \"Displacement\": 120.0, \"Horsepower\": 74.0, \"Miles_per_Gallon\": 31.6, \"Name\": \"mazda 626\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2635, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 20.4, \"Cylinders\": 4, \"Displacement\": 141.0, \"Horsepower\": 80.0, \"Miles_per_Gallon\": 28.1, \"Name\": \"peugeot 505s turbo diesel\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3230, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.4, \"Cylinders\": 4, \"Displacement\": 121.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": null, \"Name\": \"saab 900s\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2800, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 19.6, \"Cylinders\": 6, \"Displacement\": 145.0, \"Horsepower\": 76.0, \"Miles_per_Gallon\": 30.7, \"Name\": \"volvo diesel\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 3160, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 12.6, \"Cylinders\": 6, \"Displacement\": 168.0, \"Horsepower\": 116.0, \"Miles_per_Gallon\": 25.4, \"Name\": \"toyota cressida\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2900, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 13.8, \"Cylinders\": 6, \"Displacement\": 146.0, \"Horsepower\": 120.0, \"Miles_per_Gallon\": 24.2, \"Name\": \"datsun 810 maxima\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2930, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.8, \"Cylinders\": 6, \"Displacement\": 231.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 22.4, \"Name\": \"buick century\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3415, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 19.0, \"Cylinders\": 8, \"Displacement\": 350.0, \"Horsepower\": 105.0, \"Miles_per_Gallon\": 26.6, \"Name\": \"oldsmobile cutlass ls\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3725, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.1, \"Cylinders\": 6, \"Displacement\": 200.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 20.2, \"Name\": \"ford granada gl\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3060, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.6, \"Cylinders\": 6, \"Displacement\": 225.0, \"Horsepower\": 85.0, \"Miles_per_Gallon\": 17.6, \"Name\": \"chrysler lebaron salon\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3465, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 19.6, \"Cylinders\": 4, \"Displacement\": 112.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 28.0, \"Name\": \"chevrolet cavalier\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2605, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 18.6, \"Cylinders\": 4, \"Displacement\": 112.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 27.0, \"Name\": \"chevrolet cavalier wagon\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2640, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 18.0, \"Cylinders\": 4, \"Displacement\": 112.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 34.0, \"Name\": \"chevrolet cavalier 2-door\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2395, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.2, \"Cylinders\": 4, \"Displacement\": 112.0, \"Horsepower\": 85.0, \"Miles_per_Gallon\": 31.0, \"Name\": \"pontiac j2000 se hatchback\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2575, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.0, \"Cylinders\": 4, \"Displacement\": 135.0, \"Horsepower\": 84.0, \"Miles_per_Gallon\": 29.0, \"Name\": \"dodge aries se\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2525, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 18.0, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 27.0, \"Name\": \"pontiac phoenix\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2735, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 92.0, \"Miles_per_Gallon\": 24.0, \"Name\": \"ford fairmont futura\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2865, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 20.5, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": null, \"Miles_per_Gallon\": 23.0, \"Name\": \"amc concord dl\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3035, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.3, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 74.0, \"Miles_per_Gallon\": 36.0, \"Name\": \"volkswagen rabbit l\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 1980, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 18.2, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 68.0, \"Miles_per_Gallon\": 37.0, \"Name\": \"mazda glc custom l\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2025, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.6, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 68.0, \"Miles_per_Gallon\": 31.0, \"Name\": \"mazda glc custom\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1970, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.7, \"Cylinders\": 4, \"Displacement\": 105.0, \"Horsepower\": 63.0, \"Miles_per_Gallon\": 38.0, \"Name\": \"plymouth horizon miser\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2125, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.3, \"Cylinders\": 4, \"Displacement\": 98.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 36.0, \"Name\": \"mercury lynx l\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2125, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 4, \"Displacement\": 120.0, \"Horsepower\": 88.0, \"Miles_per_Gallon\": 36.0, \"Name\": \"nissan stanza xe\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2160, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 4, \"Displacement\": 107.0, \"Horsepower\": 75.0, \"Miles_per_Gallon\": 36.0, \"Name\": \"honda Accelerationord\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2205, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.9, \"Cylinders\": 4, \"Displacement\": 108.0, \"Horsepower\": 70.0, \"Miles_per_Gallon\": 34.0, \"Name\": \"toyota corolla\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2245, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.0, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 38.0, \"Name\": \"honda civic\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1965, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.7, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 32.0, \"Name\": \"honda civic (auto)\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1965, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.2, \"Cylinders\": 4, \"Displacement\": 91.0, \"Horsepower\": 67.0, \"Miles_per_Gallon\": 38.0, \"Name\": \"datsun 310 gx\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 1995, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 16.4, \"Cylinders\": 6, \"Displacement\": 181.0, \"Horsepower\": 110.0, \"Miles_per_Gallon\": 25.0, \"Name\": \"buick century limited\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2945, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.0, \"Cylinders\": 6, \"Displacement\": 262.0, \"Horsepower\": 85.0, \"Miles_per_Gallon\": 38.0, \"Name\": \"oldsmobile cutlass ciera (diesel)\", \"Origin\": \"USA\", \"Weight_in_lbs\": 3015, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.5, \"Cylinders\": 4, \"Displacement\": 156.0, \"Horsepower\": 92.0, \"Miles_per_Gallon\": 26.0, \"Name\": \"chrysler lebaron medallion\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2585, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 14.7, \"Cylinders\": 6, \"Displacement\": 232.0, \"Horsepower\": 112.0, \"Miles_per_Gallon\": 22.0, \"Name\": \"ford granada l\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2835, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 13.9, \"Cylinders\": 4, \"Displacement\": 144.0, \"Horsepower\": 96.0, \"Miles_per_Gallon\": 32.0, \"Name\": \"toyota celica gt\", \"Origin\": \"Japan\", \"Weight_in_lbs\": 2665, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 13.0, \"Cylinders\": 4, \"Displacement\": 135.0, \"Horsepower\": 84.0, \"Miles_per_Gallon\": 36.0, \"Name\": \"dodge charger 2.2\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2370, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 17.3, \"Cylinders\": 4, \"Displacement\": 151.0, \"Horsepower\": 90.0, \"Miles_per_Gallon\": 27.0, \"Name\": \"chevrolet camaro\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2950, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 15.6, \"Cylinders\": 4, \"Displacement\": 140.0, \"Horsepower\": 86.0, \"Miles_per_Gallon\": 27.0, \"Name\": \"ford mustang gl\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2790, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 24.6, \"Cylinders\": 4, \"Displacement\": 97.0, \"Horsepower\": 52.0, \"Miles_per_Gallon\": 44.0, \"Name\": \"vw pickup\", \"Origin\": \"Europe\", \"Weight_in_lbs\": 2130, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 11.6, \"Cylinders\": 4, \"Displacement\": 135.0, \"Horsepower\": 84.0, \"Miles_per_Gallon\": 32.0, \"Name\": \"dodge rampage\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2295, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 18.6, \"Cylinders\": 4, \"Displacement\": 120.0, \"Horsepower\": 79.0, \"Miles_per_Gallon\": 28.0, \"Name\": \"ford ranger\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2625, \"Year\": \"1982-01-01\"}, {\"Acceleration\": 19.4, \"Cylinders\": 4, \"Displacement\": 119.0, \"Horsepower\": 82.0, \"Miles_per_Gallon\": 31.0, \"Name\": \"chevy s-10\", \"Origin\": \"USA\", \"Weight_in_lbs\": 2720, \"Year\": \"1982-01-01\"}]}, \"mark\": \"point\", \"encoding\": {\"color\": {\"type\": \"nominal\", \"field\": \"Origin\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"Horsepower\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"Miles_per_Gallon\"}}, \"selection\": {\"selector002\": {\"type\": \"interval\", 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              "    var opt = {\"mode\": \"vega-lite\"};\n",
              "\n",
              "    function showError(el, error){\n",
              "        el.innerHTML = ('<div class=\"error\">'\n",
              "                        + '<p>JavaScript Error: ' + error.message + '</p>'\n",
              "                        + \"<p>This usually means there's a typo in your chart specification. \"\n",
              "                        + \"See the javascript console for the full traceback.</p>\"\n",
              "                        + '</div>');\n",
              "        throw error;\n",
              "    }\n",
              "    const el = document.getElementById('vis');\n",
              "    vegaEmbed(\"#vis\", spec, opt)\n",
              "      .catch(error => showError(el, error));\n",
              "  </script>\n",
              "</body>\n",
              "</html>\n"
            ],
            "text/plain": [
              "Chart({\n",
              "  data:      Acceleration  Cylinders  Displacement  Horsepower  Miles_per_Gallon  \\\n",
              "  0            12.0          8         307.0       130.0              18.0   \n",
              "  1            11.5          8         350.0       165.0              15.0   \n",
              "  2            11.0          8         318.0       150.0              18.0   \n",
              "  3            12.0          8         304.0       150.0              16.0   \n",
              "  4            10.5          8         302.0       140.0              17.0   \n",
              "  5            10.0          8         429.0       198.0              15.0   \n",
              "  6             9.0          8         454.0       220.0              14.0   \n",
              "  7             8.5          8         440.0       215.0              14.0   \n",
              "  8            10.0          8         455.0       225.0              14.0   \n",
              "  9             8.5          8         390.0       190.0              15.0   \n",
              "  10           17.5          4         133.0       115.0               NaN   \n",
              "  11           11.5          8         350.0       165.0               NaN   \n",
              "  12           11.0          8         351.0       153.0               NaN   \n",
              "  13           10.5          8         383.0       175.0               NaN   \n",
              "  14           11.0          8         360.0       175.0               NaN   \n",
              "  15           10.0          8         383.0       170.0              15.0   \n",
              "  16            8.0          8         340.0       160.0              14.0   \n",
              "  17            8.0          8         302.0       140.0               NaN   \n",
              "  18            9.5          8         400.0       150.0              15.0   \n",
              "  19           10.0          8         455.0       225.0              14.0   \n",
              "  20           15.0          4         113.0        95.0              24.0   \n",
              "  21           15.5          6         198.0        95.0              22.0   \n",
              "  22           15.5          6         199.0        97.0              18.0   \n",
              "  23           16.0          6         200.0        85.0              21.0   \n",
              "  24           14.5          4          97.0        88.0              27.0   \n",
              "  25           20.5          4          97.0        46.0              26.0   \n",
              "  26           17.5          4         110.0        87.0              25.0   \n",
              "  27           14.5          4         107.0        90.0              24.0   \n",
              "  28           17.5          4         104.0        95.0              25.0   \n",
              "  29           12.5          4         121.0       113.0              26.0   \n",
              "  ..            ...        ...           ...         ...               ...   \n",
              "  376          18.6          4         112.0        88.0              27.0   \n",
              "  377          18.0          4         112.0        88.0              34.0   \n",
              "  378          16.2          4         112.0        85.0              31.0   \n",
              "  379          16.0          4         135.0        84.0              29.0   \n",
              "  380          18.0          4         151.0        90.0              27.0   \n",
              "  381          16.4          4         140.0        92.0              24.0   \n",
              "  382          20.5          4         151.0         NaN              23.0   \n",
              "  383          15.3          4         105.0        74.0              36.0   \n",
              "  384          18.2          4          91.0        68.0              37.0   \n",
              "  385          17.6          4          91.0        68.0              31.0   \n",
              "  386          14.7          4         105.0        63.0              38.0   \n",
              "  387          17.3          4          98.0        70.0              36.0   \n",
              "  388          14.5          4         120.0        88.0              36.0   \n",
              "  389          14.5          4         107.0        75.0              36.0   \n",
              "  390          16.9          4         108.0        70.0              34.0   \n",
              "  391          15.0          4          91.0        67.0              38.0   \n",
              "  392          15.7          4          91.0        67.0              32.0   \n",
              "  393          16.2          4          91.0        67.0              38.0   \n",
              "  394          16.4          6         181.0       110.0              25.0   \n",
              "  395          17.0          6         262.0        85.0              38.0   \n",
              "  396          14.5          4         156.0        92.0              26.0   \n",
              "  397          14.7          6         232.0       112.0              22.0   \n",
              "  398          13.9          4         144.0        96.0              32.0   \n",
              "  399          13.0          4         135.0        84.0              36.0   \n",
              "  400          17.3          4         151.0        90.0              27.0   \n",
              "  401          15.6          4         140.0        86.0              27.0   \n",
              "  402          24.6          4          97.0        52.0              44.0   \n",
              "  403          11.6          4         135.0        84.0              32.0   \n",
              "  404          18.6          4         120.0        79.0              28.0   \n",
              "  405          19.4          4         119.0        82.0              31.0   \n",
              "  \n",
              "                                    Name  Origin  Weight_in_lbs       Year  \n",
              "  0            chevrolet chevelle malibu     USA           3504 1970-01-01  \n",
              "  1                    buick skylark 320     USA           3693 1970-01-01  \n",
              "  2                   plymouth satellite     USA           3436 1970-01-01  \n",
              "  3                        amc rebel sst     USA           3433 1970-01-01  \n",
              "  4                          ford torino     USA           3449 1970-01-01  \n",
              "  5                     ford galaxie 500     USA           4341 1970-01-01  \n",
              "  6                     chevrolet impala     USA           4354 1970-01-01  \n",
              "  7                    plymouth fury iii     USA           4312 1970-01-01  \n",
              "  8                     pontiac catalina     USA           4425 1970-01-01  \n",
              "  9                   amc ambassador dpl     USA           3850 1970-01-01  \n",
              "  10                citroen ds-21 pallas  Europe           3090 1970-01-01  \n",
              "  11    chevrolet chevelle concours (sw)     USA           4142 1970-01-01  \n",
              "  12                    ford torino (sw)     USA           4034 1970-01-01  \n",
              "  13             plymouth satellite (sw)     USA           4166 1970-01-01  \n",
              "  14                  amc rebel sst (sw)     USA           3850 1970-01-01  \n",
              "  15                 dodge challenger se     USA           3563 1970-01-01  \n",
              "  16                  plymouth 'cuda 340     USA           3609 1970-01-01  \n",
              "  17               ford mustang boss 302     USA           3353 1970-01-01  \n",
              "  18               chevrolet monte carlo     USA           3761 1970-01-01  \n",
              "  19             buick estate wagon (sw)     USA           3086 1970-01-01  \n",
              "  20               toyota corona mark ii   Japan           2372 1970-01-01  \n",
              "  21                     plymouth duster     USA           2833 1970-01-01  \n",
              "  22                          amc hornet     USA           2774 1970-01-01  \n",
              "  23                       ford maverick     USA           2587 1970-01-01  \n",
              "  24                        datsun pl510   Japan           2130 1970-01-01  \n",
              "  25        volkswagen 1131 deluxe sedan  Europe           1835 1970-01-01  \n",
              "  26                         peugeot 504  Europe           2672 1970-01-01  \n",
              "  27                         audi 100 ls  Europe           2430 1970-01-01  \n",
              "  28                            saab 99e  Europe           2375 1970-01-01  \n",
              "  29                            bmw 2002  Europe           2234 1970-01-01  \n",
              "  ..                                 ...     ...            ...        ...  \n",
              "  376           chevrolet cavalier wagon     USA           2640 1982-01-01  \n",
              "  377          chevrolet cavalier 2-door     USA           2395 1982-01-01  \n",
              "  378         pontiac j2000 se hatchback     USA           2575 1982-01-01  \n",
              "  379                     dodge aries se     USA           2525 1982-01-01  \n",
              "  380                    pontiac phoenix     USA           2735 1982-01-01  \n",
              "  381               ford fairmont futura     USA           2865 1982-01-01  \n",
              "  382                     amc concord dl     USA           3035 1982-01-01  \n",
              "  383                volkswagen rabbit l  Europe           1980 1982-01-01  \n",
              "  384                 mazda glc custom l   Japan           2025 1982-01-01  \n",
              "  385                   mazda glc custom   Japan           1970 1982-01-01  \n",
              "  386             plymouth horizon miser     USA           2125 1982-01-01  \n",
              "  387                     mercury lynx l     USA           2125 1982-01-01  \n",
              "  388                   nissan stanza xe   Japan           2160 1982-01-01  \n",
              "  389              honda Accelerationord   Japan           2205 1982-01-01  \n",
              "  390                     toyota corolla   Japan           2245 1982-01-01  \n",
              "  391                        honda civic   Japan           1965 1982-01-01  \n",
              "  392                 honda civic (auto)   Japan           1965 1982-01-01  \n",
              "  393                      datsun 310 gx   Japan           1995 1982-01-01  \n",
              "  394              buick century limited     USA           2945 1982-01-01  \n",
              "  395  oldsmobile cutlass ciera (diesel)     USA           3015 1982-01-01  \n",
              "  396         chrysler lebaron medallion     USA           2585 1982-01-01  \n",
              "  397                     ford granada l     USA           2835 1982-01-01  \n",
              "  398                   toyota celica gt   Japan           2665 1982-01-01  \n",
              "  399                  dodge charger 2.2     USA           2370 1982-01-01  \n",
              "  400                   chevrolet camaro     USA           2950 1982-01-01  \n",
              "  401                    ford mustang gl     USA           2790 1982-01-01  \n",
              "  402                          vw pickup  Europe           2130 1982-01-01  \n",
              "  403                      dodge rampage     USA           2295 1982-01-01  \n",
              "  404                        ford ranger     USA           2625 1982-01-01  \n",
              "  405                         chevy s-10     USA           2720 1982-01-01  \n",
              "  \n",
              "  [406 rows x 9 columns],\n",
              "  encoding: EncodingWithFacet({\n",
              "    color: Color({\n",
              "      shorthand: 'Origin'\n",
              "    }),\n",
              "    x: X({\n",
              "      shorthand: 'Horsepower'\n",
              "    }),\n",
              "    y: Y({\n",
              "      shorthand: 'Miles_per_Gallon'\n",
              "    })\n",
              "  }),\n",
              "  mark: 'point',\n",
              "  selection: SelectionMapping({\n",
              "    selector002: SelectionDef({\n",
              "      bind: 'scales',\n",
              "      encodings: ['x', 'y'],\n",
              "      type: 'interval'\n",
              "    })\n",
              "  })\n",
              "})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 0
        }
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "zPAYx6C_tSdc"
      },
      "cell_type": "markdown",
      "source": [
        "For more ideas of plots you can create, see the [Altair Gallery](https://altair-viz.github.io/gallery/index.html)."
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "JNVxSV2Es2rU"
      },
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "MYqcrcKLO4xe"
      },
      "cell_type": "markdown",
      "source": [
        "## Plotly"
      ]
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "niTJd49yO4xf"
      },
      "cell_type": "markdown",
      "source": [
        "### Cell configuration\n",
        "This method pre-populates the outputframe with the configuration that Plotly expects and must be executed for every cell which is displaying a Plotly graph.\n"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "WWbPMtDkO4xg",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "def enable_plotly_in_cell():\n",
        "  import IPython\n",
        "  from plotly.offline import init_notebook_mode\n",
        "  display(IPython.core.display.HTML('''\n",
        "        <script src=\"/static/components/requirejs/require.js\"></script>\n",
        "  '''))\n",
        "  init_notebook_mode(connected=False)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "colab_type": "text",
        "id": "ZFFeVI4yO4xi"
      },
      "cell_type": "markdown",
      "source": [
        "### Sample"
      ]
    },
    {
      "metadata": {
        "colab_type": "code",
        "id": "hFCg8XrdO4xj",
        "outputId": "06d42f56-924f-4dce-84fa-7cf7e18bf0e1",
        "colab": {
          "resources": {
            "http://localhost:8080/static/components/requirejs/require.js": {
              "data": "/** vim: et:ts=4:sw=4:sts=4
 * @license RequireJS 2.1.22 Copyright (c) 2010-2015, The Dojo Foundation All Rights Reserved.
 * Available via the MIT or new BSD license.
 * see: http://github.com/jrburke/requirejs for details
 */
//Not using strict: uneven strict support in browsers, #392, and causes
//problems with requirejs.exec()/transpiler plugins that may not be strict.
/*jslint regexp: true, nomen: true, sloppy: true */
/*global window, navigator, document, importScripts, setTimeout, opera */

var requirejs, require, define;
(function (global) {
    var req, s, head, baseElement, dataMain, src,
        interactiveScript, currentlyAddingScript, mainScript, subPath,
        version = '2.1.22',
        commentRegExp = /(\/\*([\s\S]*?)\*\/|([^:]|^)\/\/(.*)$)/mg,
        cjsRequireRegExp = /[^.]\s*require\s*\(\s*["']([^'"\s]+)["']\s*\)/g,
        jsSuffixRegExp = /\.js$/,
        currDirRegExp = /^\.\//,
        op = Object.prototype,
        ostring = op.toString,
        hasOwn = op.hasOwnProperty,
        ap = Array.prototype,
        isBrowser = !!(typeof window !== 'undefined' && typeof navigator !== 'undefined' && window.document),
        isWebWorker = !isBrowser && typeof importScripts !== 'undefined',
        //PS3 indicates loaded and complete, but need to wait for complete
        //specifically. Sequence is 'loading', 'loaded', execution,
        // then 'complete'. The UA check is unfortunate, but not sure how
        //to feature test w/o causing perf issues.
        readyRegExp = isBrowser && navigator.platform === 'PLAYSTATION 3' ?
                      /^complete$/ : /^(complete|loaded)$/,
        defContextName = '_',
        //Oh the tragedy, detecting opera. See the usage of isOpera for reason.
        isOpera = typeof opera !== 'undefined' && opera.toString() === '[object Opera]',
        contexts = {},
        cfg = {},
        globalDefQueue = [],
        useInteractive = false;

    function isFunction(it) {
        return ostring.call(it) === '[object Function]';
    }

    function isArray(it) {
        return ostring.call(it) === '[object Array]';
    }

    /**
     * Helper function for iterating over an array. If the func returns
     * a true value, it will break out of the loop.
     */
    function each(ary, func) {
        if (ary) {
            var i;
            for (i = 0; i < ary.length; i += 1) {
                if (ary[i] && func(ary[i], i, ary)) {
                    break;
                }
            }
        }
    }

    /**
     * Helper function for iterating over an array backwards. If the func
     * returns a true value, it will break out of the loop.
     */
    function eachReverse(ary, func) {
        if (ary) {
            var i;
            for (i = ary.length - 1; i > -1; i -= 1) {
                if (ary[i] && func(ary[i], i, ary)) {
                    break;
                }
            }
        }
    }

    function hasProp(obj, prop) {
        return hasOwn.call(obj, prop);
    }

    function getOwn(obj, prop) {
        return hasProp(obj, prop) && obj[prop];
    }

    /**
     * Cycles over properties in an object and calls a function for each
     * property value. If the function returns a truthy value, then the
     * iteration is stopped.
     */
    function eachProp(obj, func) {
        var prop;
        for (prop in obj) {
            if (hasProp(obj, prop)) {
                if (func(obj[prop], prop)) {
                    break;
                }
            }
        }
    }

    /**
     * Simple function to mix in properties from source into target,
     * but only if target does not already have a property of the same name.
     */
    function mixin(target, source, force, deepStringMixin) {
        if (source) {
            eachProp(source, function (value, prop) {
                if (force || !hasProp(target, prop)) {
                    if (deepStringMixin && typeof value === 'object' && value &&
                        !isArray(value) && !isFunction(value) &&
                        !(value instanceof RegExp)) {

                        if (!target[prop]) {
                            target[prop] = {};
                        }
                        mixin(target[prop], value, force, deepStringMixin);
                    } else {
                        target[prop] = value;
                    }
                }
            });
        }
        return target;
    }

    //Similar to Function.prototype.bind, but the 'this' object is specified
    //first, since it is easier to read/figure out what 'this' will be.
    function bind(obj, fn) {
        return function () {
            return fn.apply(obj, arguments);
        };
    }

    function scripts() {
        return document.getElementsByTagName('script');
    }

    function defaultOnError(err) {
        throw err;
    }

    //Allow getting a global that is expressed in
    //dot notation, like 'a.b.c'.
    function getGlobal(value) {
        if (!value) {
            return value;
        }
        var g = global;
        each(value.split('.'), function (part) {
            g = g[part];
        });
        return g;
    }

    /**
     * Constructs an error with a pointer to an URL with more information.
     * @param {String} id the error ID that maps to an ID on a web page.
     * @param {String} message human readable error.
     * @param {Error} [err] the original error, if there is one.
     *
     * @returns {Error}
     */
    function makeError(id, msg, err, requireModules) {
        var e = new Error(msg + '\nhttp://requirejs.org/docs/errors.html#' + id);
        e.requireType = id;
        e.requireModules = requireModules;
        if (err) {
            e.originalError = err;
        }
        return e;
    }

    if (typeof define !== 'undefined') {
        //If a define is already in play via another AMD loader,
        //do not overwrite.
        return;
    }

    if (typeof requirejs !== 'undefined') {
        if (isFunction(requirejs)) {
            //Do not overwrite an existing requirejs instance.
            return;
        }
        cfg = requirejs;
        requirejs = undefined;
    }

    //Allow for a require config object
    if (typeof require !== 'undefined' && !isFunction(require)) {
        //assume it is a config object.
        cfg = require;
        require = undefined;
    }

    function newContext(contextName) {
        var inCheckLoaded, Module, context, handlers,
            checkLoadedTimeoutId,
            config = {
                //Defaults. Do not set a default for map
                //config to speed up normalize(), which
                //will run faster if there is no default.
                waitSeconds: 7,
                baseUrl: './',
                paths: {},
                bundles: {},
                pkgs: {},
                shim: {},
                config: {}
            },
            registry = {},
            //registry of just enabled modules, to speed
            //cycle breaking code when lots of modules
            //are registered, but not activated.
            enabledRegistry = {},
            undefEvents = {},
            defQueue = [],
            defined = {},
            urlFetched = {},
            bundlesMap = {},
            requireCounter = 1,
            unnormalizedCounter = 1;

        /**
         * Trims the . and .. from an array of path segments.
         * It will keep a leading path segment if a .. will become
         * the first path segment, to help with module name lookups,
         * which act like paths, but can be remapped. But the end result,
         * all paths that use this function should look normalized.
         * NOTE: this method MODIFIES the input array.
         * @param {Array} ary the array of path segments.
         */
        function trimDots(ary) {
            var i, part;
            for (i = 0; i < ary.length; i++) {
                part = ary[i];
                if (part === '.') {
                    ary.splice(i, 1);
                    i -= 1;
                } else if (part === '..') {
                    // If at the start, or previous value is still ..,
                    // keep them so that when converted to a path it may
                    // still work when converted to a path, even though
                    // as an ID it is less than ideal. In larger point
                    // releases, may be better to just kick out an error.
                    if (i === 0 || (i === 1 && ary[2] === '..') || ary[i - 1] === '..') {
                        continue;
                    } else if (i > 0) {
                        ary.splice(i - 1, 2);
                        i -= 2;
                    }
                }
            }
        }

        /**
         * Given a relative module name, like ./something, normalize it to
         * a real name that can be mapped to a path.
         * @param {String} name the relative name
         * @param {String} baseName a real name that the name arg is relative
         * to.
         * @param {Boolean} applyMap apply the map config to the value. Should
         * only be done if this normalization is for a dependency ID.
         * @returns {String} normalized name
         */
        function normalize(name, baseName, applyMap) {
            var pkgMain, mapValue, nameParts, i, j, nameSegment, lastIndex,
                foundMap, foundI, foundStarMap, starI, normalizedBaseParts,
                baseParts = (baseName && baseName.split('/')),
                map = config.map,
                starMap = map && map['*'];

            //Adjust any relative paths.
            if (name) {
                name = name.split('/');
                lastIndex = name.length - 1;

                // If wanting node ID compatibility, strip .js from end
                // of IDs. Have to do this here, and not in nameToUrl
                // because node allows either .js or non .js to map
                // to same file.
                if (config.nodeIdCompat && jsSuffixRegExp.test(name[lastIndex])) {
                    name[lastIndex] = name[lastIndex].replace(jsSuffixRegExp, '');
                }

                // Starts with a '.' so need the baseName
                if (name[0].charAt(0) === '.' && baseParts) {
                    //Convert baseName to array, and lop off the last part,
                    //so that . matches that 'directory' and not name of the baseName's
                    //module. For instance, baseName of 'one/two/three', maps to
                    //'one/two/three.js', but we want the directory, 'one/two' for
                    //this normalization.
                    normalizedBaseParts = baseParts.slice(0, baseParts.length - 1);
                    name = normalizedBaseParts.concat(name);
                }

                trimDots(name);
                name = name.join('/');
            }

            //Apply map config if available.
            if (applyMap && map && (baseParts || starMap)) {
                nameParts = name.split('/');

                outerLoop: for (i = nameParts.length; i > 0; i -= 1) {
                    nameSegment = nameParts.slice(0, i).join('/');

                    if (baseParts) {
                        //Find the longest baseName segment match in the config.
                        //So, do joins on the biggest to smallest lengths of baseParts.
                        for (j = baseParts.length; j > 0; j -= 1) {
                            mapValue = getOwn(map, baseParts.slice(0, j).join('/'));

                            //baseName segment has config, find if it has one for
                            //this name.
                            if (mapValue) {
                                mapValue = getOwn(mapValue, nameSegment);
                                if (mapValue) {
                                    //Match, update name to the new value.
                                    foundMap = mapValue;
                                    foundI = i;
                                    break outerLoop;
                                }
                            }
                        }
                    }

                    //Check for a star map match, but just hold on to it,
                    //if there is a shorter segment match later in a matching
                    //config, then favor over this star map.
                    if (!foundStarMap && starMap && getOwn(starMap, nameSegment)) {
                        foundStarMap = getOwn(starMap, nameSegment);
                        starI = i;
                    }
                }

                if (!foundMap && foundStarMap) {
                    foundMap = foundStarMap;
                    foundI = starI;
                }

                if (foundMap) {
                    nameParts.splice(0, foundI, foundMap);
                    name = nameParts.join('/');
                }
            }

            // If the name points to a package's name, use
            // the package main instead.
            pkgMain = getOwn(config.pkgs, name);

            return pkgMain ? pkgMain : name;
        }

        function removeScript(name) {
            if (isBrowser) {
                each(scripts(), function (scriptNode) {
                    if (scriptNode.getAttribute('data-requiremodule') === name &&
                            scriptNode.getAttribute('data-requirecontext') === context.contextName) {
                        scriptNode.parentNode.removeChild(scriptNode);
                        return true;
                    }
                });
            }
        }

        function hasPathFallback(id) {
            var pathConfig = getOwn(config.paths, id);
            if (pathConfig && isArray(pathConfig) && pathConfig.length > 1) {
                //Pop off the first array value, since it failed, and
                //retry
                pathConfig.shift();
                context.require.undef(id);

                //Custom require that does not do map translation, since
                //ID is "absolute", already mapped/resolved.
                context.makeRequire(null, {
                    skipMap: true
                })([id]);

                return true;
            }
        }

        //Turns a plugin!resource to [plugin, resource]
        //with the plugin being undefined if the name
        //did not have a plugin prefix.
        function splitPrefix(name) {
            var prefix,
                index = name ? name.indexOf('!') : -1;
            if (index > -1) {
                prefix = name.substring(0, index);
                name = name.substring(index + 1, name.length);
            }
            return [prefix, name];
        }

        /**
         * Creates a module mapping that includes plugin prefix, module
         * name, and path. If parentModuleMap is provided it will
         * also normalize the name via require.normalize()
         *
         * @param {String} name the module name
         * @param {String} [parentModuleMap] parent module map
         * for the module name, used to resolve relative names.
         * @param {Boolean} isNormalized: is the ID already normalized.
         * This is true if this call is done for a define() module ID.
         * @param {Boolean} applyMap: apply the map config to the ID.
         * Should only be true if this map is for a dependency.
         *
         * @returns {Object}
         */
        function makeModuleMap(name, parentModuleMap, isNormalized, applyMap) {
            var url, pluginModule, suffix, nameParts,
                prefix = null,
                parentName = parentModuleMap ? parentModuleMap.name : null,
                originalName = name,
                isDefine = true,
                normalizedName = '';

            //If no name, then it means it is a require call, generate an
            //internal name.
            if (!name) {
                isDefine = false;
                name = '_@r' + (requireCounter += 1);
            }

            nameParts = splitPrefix(name);
            prefix = nameParts[0];
            name = nameParts[1];

            if (prefix) {
                prefix = normalize(prefix, parentName, applyMap);
                pluginModule = getOwn(defined, prefix);
            }

            //Account for relative paths if there is a base name.
            if (name) {
                if (prefix) {
                    if (pluginModule && pluginModule.normalize) {
                        //Plugin is loaded, use its normalize method.
                        normalizedName = pluginModule.normalize(name, function (name) {
                            return normalize(name, parentName, applyMap);
                        });
                    } else {
                        // If nested plugin references, then do not try to
                        // normalize, as it will not normalize correctly. This
                        // places a restriction on resourceIds, and the longer
                        // term solution is not to normalize until plugins are
                        // loaded and all normalizations to allow for async
                        // loading of a loader plugin. But for now, fixes the
                        // common uses. Details in #1131
                        normalizedName = name.indexOf('!') === -1 ?
                                         normalize(name, parentName, applyMap) :
                                         name;
                    }
                } else {
                    //A regular module.
                    normalizedName = normalize(name, parentName, applyMap);

                    //Normalized name may be a plugin ID due to map config
                    //application in normalize. The map config values must
                    //already be normalized, so do not need to redo that part.
                    nameParts = splitPrefix(normalizedName);
                    prefix = nameParts[0];
                    normalizedName = nameParts[1];
                    isNormalized = true;

                    url = context.nameToUrl(normalizedName);
                }
            }

            //If the id is a plugin id that cannot be determined if it needs
            //normalization, stamp it with a unique ID so two matching relative
            //ids that may conflict can be separate.
            suffix = prefix && !pluginModule && !isNormalized ?
                     '_unnormalized' + (unnormalizedCounter += 1) :
                     '';

            return {
                prefix: prefix,
                name: normalizedName,
                parentMap: parentModuleMap,
                unnormalized: !!suffix,
                url: url,
                originalName: originalName,
                isDefine: isDefine,
                id: (prefix ?
                        prefix + '!' + normalizedName :
                        normalizedName) + suffix
            };
        }

        function getModule(depMap) {
            var id = depMap.id,
                mod = getOwn(registry, id);

            if (!mod) {
                mod = registry[id] = new context.Module(depMap);
            }

            return mod;
        }

        function on(depMap, name, fn) {
            var id = depMap.id,
                mod = getOwn(registry, id);

            if (hasProp(defined, id) &&
                    (!mod || mod.defineEmitComplete)) {
                if (name === 'defined') {
                    fn(defined[id]);
                }
            } else {
                mod = getModule(depMap);
                if (mod.error && name === 'error') {
                    fn(mod.error);
                } else {
                    mod.on(name, fn);
                }
            }
        }

        function onError(err, errback) {
            var ids = err.requireModules,
                notified = false;

            if (errback) {
                errback(err);
            } else {
                each(ids, function (id) {
                    var mod = getOwn(registry, id);
                    if (mod) {
                        //Set error on module, so it skips timeout checks.
                        mod.error = err;
                        if (mod.events.error) {
                            notified = true;
                            mod.emit('error', err);
                        }
                    }
                });

                if (!notified) {
                    req.onError(err);
                }
            }
        }

        /**
         * Internal method to transfer globalQueue items to this context's
         * defQueue.
         */
        function takeGlobalQueue() {
            //Push all the globalDefQueue items into the context's defQueue
            if (globalDefQueue.length) {
                each(globalDefQueue, function(queueItem) {
                    var id = queueItem[0];
                    if (typeof id === 'string') {
                        context.defQueueMap[id] = true;
                    }
                    defQueue.push(queueItem);
                });
                globalDefQueue = [];
            }
        }

        handlers = {
            'require': function (mod) {
                if (mod.require) {
                    return mod.require;
                } else {
                    return (mod.require = context.makeRequire(mod.map));
                }
            },
            'exports': function (mod) {
                mod.usingExports = true;
                if (mod.map.isDefine) {
                    if (mod.exports) {
                        return (defined[mod.map.id] = mod.exports);
                    } else {
                        return (mod.exports = defined[mod.map.id] = {});
                    }
                }
            },
            'module': function (mod) {
                if (mod.module) {
                    return mod.module;
                } else {
                    return (mod.module = {
                        id: mod.map.id,
                        uri: mod.map.url,
                        config: function () {
                            return getOwn(config.config, mod.map.id) || {};
                        },
                        exports: mod.exports || (mod.exports = {})
                    });
                }
            }
        };

        function cleanRegistry(id) {
            //Clean up machinery used for waiting modules.
            delete registry[id];
            delete enabledRegistry[id];
        }

        function breakCycle(mod, traced, processed) {
            var id = mod.map.id;

            if (mod.error) {
                mod.emit('error', mod.error);
            } else {
                traced[id] = true;
                each(mod.depMaps, function (depMap, i) {
                    var depId = depMap.id,
                        dep = getOwn(registry, depId);

                    //Only force things that have not completed
                    //being defined, so still in the registry,
                    //and only if it has not been matched up
                    //in the module already.
                    if (dep && !mod.depMatched[i] && !processed[depId]) {
                        if (getOwn(traced, depId)) {
                            mod.defineDep(i, defined[depId]);
                            mod.check(); //pass false?
                        } else {
                            breakCycle(dep, traced, processed);
                        }
                    }
                });
                processed[id] = true;
            }
        }

        function checkLoaded() {
            var err, usingPathFallback,
                waitInterval = config.waitSeconds * 1000,
                //It is possible to disable the wait interval by using waitSeconds of 0.
                expired = waitInterval && (context.startTime + waitInterval) < new Date().getTime(),
                noLoads = [],
                reqCalls = [],
                stillLoading = false,
                needCycleCheck = true;

            //Do not bother if this call was a result of a cycle break.
            if (inCheckLoaded) {
                return;
            }

            inCheckLoaded = true;

            //Figure out the state of all the modules.
            eachProp(enabledRegistry, function (mod) {
                var map = mod.map,
                    modId = map.id;

                //Skip things that are not enabled or in error state.
                if (!mod.enabled) {
                    return;
                }

                if (!map.isDefine) {
                    reqCalls.push(mod);
                }

                if (!mod.error) {
                    //If the module should be executed, and it has not
                    //been inited and time is up, remember it.
                    if (!mod.inited && expired) {
                        if (hasPathFallback(modId)) {
                            usingPathFallback = true;
                            stillLoading = true;
                        } else {
                            noLoads.push(modId);
                            removeScript(modId);
                        }
                    } else if (!mod.inited && mod.fetched && map.isDefine) {
                        stillLoading = true;
                        if (!map.prefix) {
                            //No reason to keep looking for unfinished
                            //loading. If the only stillLoading is a
                            //plugin resource though, keep going,
                            //because it may be that a plugin resource
                            //is waiting on a non-plugin cycle.
                            return (needCycleCheck = false);
                        }
                    }
                }
            });

            if (expired && noLoads.length) {
                //If wait time expired, throw error of unloaded modules.
                err = makeError('timeout', 'Load timeout for modules: ' + noLoads, null, noLoads);
                err.contextName = context.contextName;
                return onError(err);
            }

            //Not expired, check for a cycle.
            if (needCycleCheck) {
                each(reqCalls, function (mod) {
                    breakCycle(mod, {}, {});
                });
            }

            //If still waiting on loads, and the waiting load is something
            //other than a plugin resource, or there are still outstanding
            //scripts, then just try back later.
            if ((!expired || usingPathFallback) && stillLoading) {
                //Something is still waiting to load. Wait for it, but only
                //if a timeout is not already in effect.
                if ((isBrowser || isWebWorker) && !checkLoadedTimeoutId) {
                    checkLoadedTimeoutId = setTimeout(function () {
                        checkLoadedTimeoutId = 0;
                        checkLoaded();
                    }, 50);
                }
            }

            inCheckLoaded = false;
        }

        Module = function (map) {
            this.events = getOwn(undefEvents, map.id) || {};
            this.map = map;
            this.shim = getOwn(config.shim, map.id);
            this.depExports = [];
            this.depMaps = [];
            this.depMatched = [];
            this.pluginMaps = {};
            this.depCount = 0;

            /* this.exports this.factory
               this.depMaps = [],
               this.enabled, this.fetched
            */
        };

        Module.prototype = {
            init: function (depMaps, factory, errback, options) {
                options = options || {};

                //Do not do more inits if already done. Can happen if there
                //are multiple define calls for the same module. That is not
                //a normal, common case, but it is also not unexpected.
                if (this.inited) {
                    return;
                }

                this.factory = factory;

                if (errback) {
                    //Register for errors on this module.
                    this.on('error', errback);
                } else if (this.events.error) {
                    //If no errback already, but there are error listeners
                    //on this module, set up an errback to pass to the deps.
                    errback = bind(this, function (err) {
                        this.emit('error', err);
                    });
                }

                //Do a copy of the dependency array, so that
                //source inputs are not modified. For example
                //"shim" deps are passed in here directly, and
                //doing a direct modification of the depMaps array
                //would affect that config.
                this.depMaps = depMaps && depMaps.slice(0);

                this.errback = errback;

                //Indicate this module has be initialized
                this.inited = true;

                this.ignore = options.ignore;

                //Could have option to init this module in enabled mode,
                //or could have been previously marked as enabled. However,
                //the dependencies are not known until init is called. So
                //if enabled previously, now trigger dependencies as enabled.
                if (options.enabled || this.enabled) {
                    //Enable this module and dependencies.
                    //Will call this.check()
                    this.enable();
                } else {
                    this.check();
                }
            },

            defineDep: function (i, depExports) {
                //Because of cycles, defined callback for a given
                //export can be called more than once.
                if (!this.depMatched[i]) {
                    this.depMatched[i] = true;
                    this.depCount -= 1;
                    this.depExports[i] = depExports;
                }
            },

            fetch: function () {
                if (this.fetched) {
                    return;
                }
                this.fetched = true;

                context.startTime = (new Date()).getTime();

                var map = this.map;

                //If the manager is for a plugin managed resource,
                //ask the plugin to load it now.
                if (this.shim) {
                    context.makeRequire(this.map, {
                        enableBuildCallback: true
                    })(this.shim.deps || [], bind(this, function () {
                        return map.prefix ? this.callPlugin() : this.load();
                    }));
                } else {
                    //Regular dependency.
                    return map.prefix ? this.callPlugin() : this.load();
                }
            },

            load: function () {
                var url = this.map.url;

                //Regular dependency.
                if (!urlFetched[url]) {
                    urlFetched[url] = true;
                    context.load(this.map.id, url);
                }
            },

            /**
             * Checks if the module is ready to define itself, and if so,
             * define it.
             */
            check: function () {
                if (!this.enabled || this.enabling) {
                    return;
                }

                var err, cjsModule,
                    id = this.map.id,
                    depExports = this.depExports,
                    exports = this.exports,
                    factory = this.factory;

                if (!this.inited) {
                    // Only fetch if not already in the defQueue.
                    if (!hasProp(context.defQueueMap, id)) {
                        this.fetch();
                    }
                } else if (this.error) {
                    this.emit('error', this.error);
                } else if (!this.defining) {
                    //The factory could trigger another require call
                    //that would result in checking this module to
                    //define itself again. If already in the process
                    //of doing that, skip this work.
                    this.defining = true;

                    if (this.depCount < 1 && !this.defined) {
                        if (isFunction(factory)) {
                            try {
                                exports = context.execCb(id, factory, depExports, exports);
                            } catch (e) {
                                err = e;
                            }

                            // Favor return value over exports. If node/cjs in play,
                            // then will not have a return value anyway. Favor
                            // module.exports assignment over exports object.
                            if (this.map.isDefine && exports === undefined) {
                                cjsModule = this.module;
                                if (cjsModule) {
                                    exports = cjsModule.exports;
                                } else if (this.usingExports) {
                                    //exports already set the defined value.
                                    exports = this.exports;
                                }
                            }

                            if (err) {
                                // If there is an error listener, favor passing
                                // to that instead of throwing an error. However,
                                // only do it for define()'d  modules. require
                                // errbacks should not be called for failures in
                                // their callbacks (#699). However if a global
                                // onError is set, use that.
                                if ((this.events.error && this.map.isDefine) ||
                                    req.onError !== defaultOnError) {
                                    err.requireMap = this.map;
                                    err.requireModules = this.map.isDefine ? [this.map.id] : null;
                                    err.requireType = this.map.isDefine ? 'define' : 'require';
                                    return onError((this.error = err));
                                } else if (typeof console !== 'undefined' &&
                                           console.error) {
                                    // Log the error for debugging. If promises could be
                                    // used, this would be different, but making do.
                                    console.error(err);
                                } else {
                                    // Do not want to completely lose the error. While this
                                    // will mess up processing and lead to similar results
                                    // as bug 1440, it at least surfaces the error.
                                    req.onError(err);
                                }
                            }
                        } else {
                            //Just a literal value
                            exports = factory;
                        }

                        this.exports = exports;

                        if (this.map.isDefine && !this.ignore) {
                            defined[id] = exports;

                            if (req.onResourceLoad) {
                                var resLoadMaps = [];
                                each(this.depMaps, function (depMap) {
                                    resLoadMaps.push(depMap.normalizedMap || depMap);
                                });
                                req.onResourceLoad(context, this.map, resLoadMaps);
                            }
                        }

                        //Clean up
                        cleanRegistry(id);

                        this.defined = true;
                    }

                    //Finished the define stage. Allow calling check again
                    //to allow define notifications below in the case of a
                    //cycle.
                    this.defining = false;

                    if (this.defined && !this.defineEmitted) {
                        this.defineEmitted = true;
                        this.emit('defined', this.exports);
                        this.defineEmitComplete = true;
                    }

                }
            },

            callPlugin: function () {
                var map = this.map,
                    id = map.id,
                    //Map already normalized the prefix.
                    pluginMap = makeModuleMap(map.prefix);

                //Mark this as a dependency for this plugin, so it
                //can be traced for cycles.
                this.depMaps.push(pluginMap);

                on(pluginMap, 'defined', bind(this, function (plugin) {
                    var load, normalizedMap, normalizedMod,
                        bundleId = getOwn(bundlesMap, this.map.id),
                        name = this.map.name,
                        parentName = this.map.parentMap ? this.map.parentMap.name : null,
                        localRequire = context.makeRequire(map.parentMap, {
                            enableBuildCallback: true
                        });

                    //If current map is not normalized, wait for that
                    //normalized name to load instead of continuing.
                    if (this.map.unnormalized) {
                        //Normalize the ID if the plugin allows it.
                        if (plugin.normalize) {
                            name = plugin.normalize(name, function (name) {
                                return normalize(name, parentName, true);
                            }) || '';
                        }

                        //prefix and name should already be normalized, no need
                        //for applying map config again either.
                        normalizedMap = makeModuleMap(map.prefix + '!' + name,
                                                      this.map.parentMap);
                        on(normalizedMap,
                            'defined', bind(this, function (value) {
                                this.map.normalizedMap = normalizedMap;
                                this.init([], function () { return value; }, null, {
                                    enabled: true,
                                    ignore: true
                                });
                            }));

                        normalizedMod = getOwn(registry, normalizedMap.id);
                        if (normalizedMod) {
                            //Mark this as a dependency for this plugin, so it
                            //can be traced for cycles.
                            this.depMaps.push(normalizedMap);

                            if (this.events.error) {
                                normalizedMod.on('error', bind(this, function (err) {
                                    this.emit('error', err);
                                }));
                            }
                            normalizedMod.enable();
                        }

                        return;
                    }

                    //If a paths config, then just load that file instead to
                    //resolve the plugin, as it is built into that paths layer.
                    if (bundleId) {
                        this.map.url = context.nameToUrl(bundleId);
                        this.load();
                        return;
                    }

                    load = bind(this, function (value) {
                        this.init([], function () { return value; }, null, {
                            enabled: true
                        });
                    });

                    load.error = bind(this, function (err) {
                        this.inited = true;
                        this.error = err;
                        err.requireModules = [id];

                        //Remove temp unnormalized modules for this module,
                        //since they will never be resolved otherwise now.
                        eachProp(registry, function (mod) {
                            if (mod.map.id.indexOf(id + '_unnormalized') === 0) {
                                cleanRegistry(mod.map.id);
                            }
                        });

                        onError(err);
                    });

                    //Allow plugins to load other code without having to know the
                    //context or how to 'complete' the load.
                    load.fromText = bind(this, function (text, textAlt) {
                        /*jslint evil: true */
                        var moduleName = map.name,
                            moduleMap = makeModuleMap(moduleName),
                            hasInteractive = useInteractive;

                        //As of 2.1.0, support just passing the text, to reinforce
                        //fromText only being called once per resource. Still
                        //support old style of passing moduleName but discard
                        //that moduleName in favor of the internal ref.
                        if (textAlt) {
                            text = textAlt;
                        }

                        //Turn off interactive script matching for IE for any define
                        //calls in the text, then turn it back on at the end.
                        if (hasInteractive) {
                            useInteractive = false;
                        }

                        //Prime the system by creating a module instance for
                        //it.
                        getModule(moduleMap);

                        //Transfer any config to this other module.
                        if (hasProp(config.config, id)) {
                            config.config[moduleName] = config.config[id];
                        }

                        try {
                            req.exec(text);
                        } catch (e) {
                            return onError(makeError('fromtexteval',
                                             'fromText eval for ' + id +
                                            ' failed: ' + e,
                                             e,
                                             [id]));
                        }

                        if (hasInteractive) {
                            useInteractive = true;
                        }

                        //Mark this as a dependency for the plugin
                        //resource
                        this.depMaps.push(moduleMap);

                        //Support anonymous modules.
                        context.completeLoad(moduleName);

                        //Bind the value of that module to the value for this
                        //resource ID.
                        localRequire([moduleName], load);
                    });

                    //Use parentName here since the plugin's name is not reliable,
                    //could be some weird string with no path that actually wants to
                    //reference the parentName's path.
                    plugin.load(map.name, localRequire, load, config);
                }));

                context.enable(pluginMap, this);
                this.pluginMaps[pluginMap.id] = pluginMap;
            },

            enable: function () {
                enabledRegistry[this.map.id] = this;
                this.enabled = true;

                //Set flag mentioning that the module is enabling,
                //so that immediate calls to the defined callbacks
                //for dependencies do not trigger inadvertent load
                //with the depCount still being zero.
                this.enabling = true;

                //Enable each dependency
                each(this.depMaps, bind(this, function (depMap, i) {
                    var id, mod, handler;

                    if (typeof depMap === 'string') {
                        //Dependency needs to be converted to a depMap
                        //and wired up to this module.
                        depMap = makeModuleMap(depMap,
                                               (this.map.isDefine ? this.map : this.map.parentMap),
                                               false,
                                               !this.skipMap);
                        this.depMaps[i] = depMap;

                        handler = getOwn(handlers, depMap.id);

                        if (handler) {
                            this.depExports[i] = handler(this);
                            return;
                        }

                        this.depCount += 1;

                        on(depMap, 'defined', bind(this, function (depExports) {
                            if (this.undefed) {
                                return;
                            }
                            this.defineDep(i, depExports);
                            this.check();
                        }));

                        if (this.errback) {
                            on(depMap, 'error', bind(this, this.errback));
                        } else if (this.events.error) {
                            // No direct errback on this module, but something
                            // else is listening for errors, so be sure to
                            // propagate the error correctly.
                            on(depMap, 'error', bind(this, function(err) {
                                this.emit('error', err);
                            }));
                        }
                    }

                    id = depMap.id;
                    mod = registry[id];

                    //Skip special modules like 'require', 'exports', 'module'
                    //Also, don't call enable if it is already enabled,
                    //important in circular dependency cases.
                    if (!hasProp(handlers, id) && mod && !mod.enabled) {
                        context.enable(depMap, this);
                    }
                }));

                //Enable each plugin that is used in
                //a dependency
                eachProp(this.pluginMaps, bind(this, function (pluginMap) {
                    var mod = getOwn(registry, pluginMap.id);
                    if (mod && !mod.enabled) {
                        context.enable(pluginMap, this);
                    }
                }));

                this.enabling = false;

                this.check();
            },

            on: function (name, cb) {
                var cbs = this.events[name];
                if (!cbs) {
                    cbs = this.events[name] = [];
                }
                cbs.push(cb);
            },

            emit: function (name, evt) {
                each(this.events[name], function (cb) {
                    cb(evt);
                });
                if (name === 'error') {
                    //Now that the error handler was triggered, remove
                    //the listeners, since this broken Module instance
                    //can stay around for a while in the registry.
                    delete this.events[name];
                }
            }
        };

        function callGetModule(args) {
            //Skip modules already defined.
            if (!hasProp(defined, args[0])) {
                getModule(makeModuleMap(args[0], null, true)).init(args[1], args[2]);
            }
        }

        function removeListener(node, func, name, ieName) {
            //Favor detachEvent because of IE9
            //issue, see attachEvent/addEventListener comment elsewhere
            //in this file.
            if (node.detachEvent && !isOpera) {
                //Probably IE. If not it will throw an error, which will be
                //useful to know.
                if (ieName) {
                    node.detachEvent(ieName, func);
                }
            } else {
                node.removeEventListener(name, func, false);
            }
        }

        /**
         * Given an event from a script node, get the requirejs info from it,
         * and then removes the event listeners on the node.
         * @param {Event} evt
         * @returns {Object}
         */
        function getScriptData(evt) {
            //Using currentTarget instead of target for Firefox 2.0's sake. Not
            //all old browsers will be supported, but this one was easy enough
            //to support and still makes sense.
            var node = evt.currentTarget || evt.srcElement;

            //Remove the listeners once here.
            removeListener(node, context.onScriptLoad, 'load', 'onreadystatechange');
            removeListener(node, context.onScriptError, 'error');

            return {
                node: node,
                id: node && node.getAttribute('data-requiremodule')
            };
        }

        function intakeDefines() {
            var args;

            //Any defined modules in the global queue, intake them now.
            takeGlobalQueue();

            //Make sure any remaining defQueue items get properly processed.
            while (defQueue.length) {
                args = defQueue.shift();
                if (args[0] === null) {
                    return onError(makeError('mismatch', 'Mismatched anonymous define() module: ' +
                        args[args.length - 1]));
                } else {
                    //args are id, deps, factory. Should be normalized by the
                    //define() function.
                    callGetModule(args);
                }
            }
            context.defQueueMap = {};
        }

        context = {
            config: config,
            contextName: contextName,
            registry: registry,
            defined: defined,
            urlFetched: urlFetched,
            defQueue: defQueue,
            defQueueMap: {},
            Module: Module,
            makeModuleMap: makeModuleMap,
            nextTick: req.nextTick,
            onError: onError,

            /**
             * Set a configuration for the context.
             * @param {Object} cfg config object to integrate.
             */
            configure: function (cfg) {
                //Make sure the baseUrl ends in a slash.
                if (cfg.baseUrl) {
                    if (cfg.baseUrl.charAt(cfg.baseUrl.length - 1) !== '/') {
                        cfg.baseUrl += '/';
                    }
                }

                //Save off the paths since they require special processing,
                //they are additive.
                var shim = config.shim,
                    objs = {
                        paths: true,
                        bundles: true,
                        config: true,
                        map: true
                    };

                eachProp(cfg, function (value, prop) {
                    if (objs[prop]) {
                        if (!config[prop]) {
                            config[prop] = {};
                        }
                        mixin(config[prop], value, true, true);
                    } else {
                        config[prop] = value;
                    }
                });

                //Reverse map the bundles
                if (cfg.bundles) {
                    eachProp(cfg.bundles, function (value, prop) {
                        each(value, function (v) {
                            if (v !== prop) {
                                bundlesMap[v] = prop;
                            }
                        });
                    });
                }

                //Merge shim
                if (cfg.shim) {
                    eachProp(cfg.shim, function (value, id) {
                        //Normalize the structure
                        if (isArray(value)) {
                            value = {
                                deps: value
                            };
                        }
                        if ((value.exports || value.init) && !value.exportsFn) {
                            value.exportsFn = context.makeShimExports(value);
                        }
                        shim[id] = value;
                    });
                    config.shim = shim;
                }

                //Adjust packages if necessary.
                if (cfg.packages) {
                    each(cfg.packages, function (pkgObj) {
                        var location, name;

                        pkgObj = typeof pkgObj === 'string' ? {name: pkgObj} : pkgObj;

                        name = pkgObj.name;
                        location = pkgObj.location;
                        if (location) {
                            config.paths[name] = pkgObj.location;
                        }

                        //Save pointer to main module ID for pkg name.
                        //Remove leading dot in main, so main paths are normalized,
                        //and remove any trailing .js, since different package
                        //envs have different conventions: some use a module name,
                        //some use a file name.
                        config.pkgs[name] = pkgObj.name + '/' + (pkgObj.main || 'main')
                                     .replace(currDirRegExp, '')
                                     .replace(jsSuffixRegExp, '');
                    });
                }

                //If there are any "waiting to execute" modules in the registry,
                //update the maps for them, since their info, like URLs to load,
                //may have changed.
                eachProp(registry, function (mod, id) {
                    //If module already has init called, since it is too
                    //late to modify them, and ignore unnormalized ones
                    //since they are transient.
                    if (!mod.inited && !mod.map.unnormalized) {
                        mod.map = makeModuleMap(id, null, true);
                    }
                });

                //If a deps array or a config callback is specified, then call
                //require with those args. This is useful when require is defined as a
                //config object before require.js is loaded.
                if (cfg.deps || cfg.callback) {
                    context.require(cfg.deps || [], cfg.callback);
                }
            },

            makeShimExports: function (value) {
                function fn() {
                    var ret;
                    if (value.init) {
                        ret = value.init.apply(global, arguments);
                    }
                    return ret || (value.exports && getGlobal(value.exports));
                }
                return fn;
            },

            makeRequire: function (relMap, options) {
                options = options || {};

                function localRequire(deps, callback, errback) {
                    var id, map, requireMod;

                    if (options.enableBuildCallback && callback && isFunction(callback)) {
                        callback.__requireJsBuild = true;
                    }

                    if (typeof deps === 'string') {
                        if (isFunction(callback)) {
                            //Invalid call
                            return onError(makeError('requireargs', 'Invalid require call'), errback);
                        }

                        //If require|exports|module are requested, get the
                        //value for them from the special handlers. Caveat:
                        //this only works while module is being defined.
                        if (relMap && hasProp(handlers, deps)) {
                            return handlers[deps](registry[relMap.id]);
                        }

                        //Synchronous access to one module. If require.get is
                        //available (as in the Node adapter), prefer that.
                        if (req.get) {
                            return req.get(context, deps, relMap, localRequire);
                        }

                        //Normalize module name, if it contains . or ..
                        map = makeModuleMap(deps, relMap, false, true);
                        id = map.id;

                        if (!hasProp(defined, id)) {
                            return onError(makeError('notloaded', 'Module name "' +
                                        id +
                                        '" has not been loaded yet for context: ' +
                                        contextName +
                                        (relMap ? '' : '. Use require([])')));
                        }
                        return defined[id];
                    }

                    //Grab defines waiting in the global queue.
                    intakeDefines();

                    //Mark all the dependencies as needing to be loaded.
                    context.nextTick(function () {
                        //Some defines could have been added since the
                        //require call, collect them.
                        intakeDefines();

                        requireMod = getModule(makeModuleMap(null, relMap));

                        //Store if map config should be applied to this require
                        //call for dependencies.
                        requireMod.skipMap = options.skipMap;

                        requireMod.init(deps, callback, errback, {
                            enabled: true
                        });

                        checkLoaded();
                    });

                    return localRequire;
                }

                mixin(localRequire, {
                    isBrowser: isBrowser,

                    /**
                     * Converts a module name + .extension into an URL path.
                     * *Requires* the use of a module name. It does not support using
                     * plain URLs like nameToUrl.
                     */
                    toUrl: function (moduleNamePlusExt) {
                        var ext,
                            index = moduleNamePlusExt.lastIndexOf('.'),
                            segment = moduleNamePlusExt.split('/')[0],
                            isRelative = segment === '.' || segment === '..';

                        //Have a file extension alias, and it is not the
                        //dots from a relative path.
                        if (index !== -1 && (!isRelative || index > 1)) {
                            ext = moduleNamePlusExt.substring(index, moduleNamePlusExt.length);
                            moduleNamePlusExt = moduleNamePlusExt.substring(0, index);
                        }

                        return context.nameToUrl(normalize(moduleNamePlusExt,
                                                relMap && relMap.id, true), ext,  true);
                    },

                    defined: function (id) {
                        return hasProp(defined, makeModuleMap(id, relMap, false, true).id);
                    },

                    specified: function (id) {
                        id = makeModuleMap(id, relMap, false, true).id;
                        return hasProp(defined, id) || hasProp(registry, id);
                    }
                });

                //Only allow undef on top level require calls
                if (!relMap) {
                    localRequire.undef = function (id) {
                        //Bind any waiting define() calls to this context,
                        //fix for #408
                        takeGlobalQueue();

                        var map = makeModuleMap(id, relMap, true),
                            mod = getOwn(registry, id);

                        mod.undefed = true;
                        removeScript(id);

                        delete defined[id];
                        delete urlFetched[map.url];
                        delete undefEvents[id];

                        //Clean queued defines too. Go backwards
                        //in array so that the splices do not
                        //mess up the iteration.
                        eachReverse(defQueue, function(args, i) {
                            if (args[0] === id) {
                                defQueue.splice(i, 1);
                            }
                        });
                        delete context.defQueueMap[id];

                        if (mod) {
                            //Hold on to listeners in case the
                            //module will be attempted to be reloaded
                            //using a different config.
                            if (mod.events.defined) {
                                undefEvents[id] = mod.events;
                            }

                            cleanRegistry(id);
                        }
                    };
                }

                return localRequire;
            },

            /**
             * Called to enable a module if it is still in the registry
             * awaiting enablement. A second arg, parent, the parent module,
             * is passed in for context, when this method is overridden by
             * the optimizer. Not shown here to keep code compact.
             */
            enable: function (depMap) {
                var mod = getOwn(registry, depMap.id);
                if (mod) {
                    getModule(depMap).enable();
                }
            },

            /**
             * Internal method used by environment adapters to complete a load event.
             * A load event could be a script load or just a load pass from a synchronous
             * load call.
             * @param {String} moduleName the name of the module to potentially complete.
             */
            completeLoad: function (moduleName) {
                var found, args, mod,
                    shim = getOwn(config.shim, moduleName) || {},
                    shExports = shim.exports;

                takeGlobalQueue();

                while (defQueue.length) {
                    args = defQueue.shift();
                    if (args[0] === null) {
                        args[0] = moduleName;
                        //If already found an anonymous module and bound it
                        //to this name, then this is some other anon module
                        //waiting for its completeLoad to fire.
                        if (found) {
                            break;
                        }
                        found = true;
                    } else if (args[0] === moduleName) {
                        //Found matching define call for this script!
                        found = true;
                    }

                    callGetModule(args);
                }
                context.defQueueMap = {};

                //Do this after the cycle of callGetModule in case the result
                //of those calls/init calls changes the registry.
                mod = getOwn(registry, moduleName);

                if (!found && !hasProp(defined, moduleName) && mod && !mod.inited) {
                    if (config.enforceDefine && (!shExports || !getGlobal(shExports))) {
                        if (hasPathFallback(moduleName)) {
                            return;
                        } else {
                            return onError(makeError('nodefine',
                                             'No define call for ' + moduleName,
                                             null,
                                             [moduleName]));
                        }
                    } else {
                        //A script that does not call define(), so just simulate
                        //the call for it.
                        callGetModule([moduleName, (shim.deps || []), shim.exportsFn]);
                    }
                }

                checkLoaded();
            },

            /**
             * Converts a module name to a file path. Supports cases where
             * moduleName may actually be just an URL.
             * Note that it **does not** call normalize on the moduleName,
             * it is assumed to have already been normalized. This is an
             * internal API, not a public one. Use toUrl for the public API.
             */
            nameToUrl: function (moduleName, ext, skipExt) {
                var paths, syms, i, parentModule, url,
                    parentPath, bundleId,
                    pkgMain = getOwn(config.pkgs, moduleName);

                if (pkgMain) {
                    moduleName = pkgMain;
                }

                bundleId = getOwn(bundlesMap, moduleName);

                if (bundleId) {
                    return context.nameToUrl(bundleId, ext, skipExt);
                }

                //If a colon is in the URL, it indicates a protocol is used and it is just
                //an URL to a file, or if it starts with a slash, contains a query arg (i.e. ?)
                //or ends with .js, then assume the user meant to use an url and not a module id.
                //The slash is important for protocol-less URLs as well as full paths.
                if (req.jsExtRegExp.test(moduleName)) {
                    //Just a plain path, not module name lookup, so just return it.
                    //Add extension if it is included. This is a bit wonky, only non-.js things pass
                    //an extension, this method probably needs to be reworked.
                    url = moduleName + (ext || '');
                } else {
                    //A module that needs to be converted to a path.
                    paths = config.paths;

                    syms = moduleName.split('/');
                    //For each module name segment, see if there is a path
                    //registered for it. Start with most specific name
                    //and work up from it.
                    for (i = syms.length; i > 0; i -= 1) {
                        parentModule = syms.slice(0, i).join('/');

                        parentPath = getOwn(paths, parentModule);
                        if (parentPath) {
                            //If an array, it means there are a few choices,
                            //Choose the one that is desired
                            if (isArray(parentPath)) {
                                parentPath = parentPath[0];
                            }
                            syms.splice(0, i, parentPath);
                            break;
                        }
                    }

                    //Join the path parts together, then figure out if baseUrl is needed.
                    url = syms.join('/');
                    url += (ext || (/^data\:|\?/.test(url) || skipExt ? '' : '.js'));
                    url = (url.charAt(0) === '/' || url.match(/^[\w\+\.\-]+:/) ? '' : config.baseUrl) + url;
                }

                return config.urlArgs ? url +
                                        ((url.indexOf('?') === -1 ? '?' : '&') +
                                         config.urlArgs) : url;
            },

            //Delegates to req.load. Broken out as a separate function to
            //allow overriding in the optimizer.
            load: function (id, url) {
                req.load(context, id, url);
            },

            /**
             * Executes a module callback function. Broken out as a separate function
             * solely to allow the build system to sequence the files in the built
             * layer in the right sequence.
             *
             * @private
             */
            execCb: function (name, callback, args, exports) {
                return callback.apply(exports, args);
            },

            /**
             * callback for script loads, used to check status of loading.
             *
             * @param {Event} evt the event from the browser for the script
             * that was loaded.
             */
            onScriptLoad: function (evt) {
                //Using currentTarget instead of target for Firefox 2.0's sake. Not
                //all old browsers will be supported, but this one was easy enough
                //to support and still makes sense.
                if (evt.type === 'load' ||
                        (readyRegExp.test((evt.currentTarget || evt.srcElement).readyState))) {
                    //Reset interactive script so a script node is not held onto for
                    //to long.
                    interactiveScript = null;

                    //Pull out the name of the module and the context.
                    var data = getScriptData(evt);
                    context.completeLoad(data.id);
                }
            },

            /**
             * Callback for script errors.
             */
            onScriptError: function (evt) {
                var data = getScriptData(evt);
                if (!hasPathFallback(data.id)) {
                    var parents = [];
                    eachProp(registry, function(value, key) {
                        if (key.indexOf('_@r') !== 0) {
                            each(value.depMaps, function(depMap) {
                                if (depMap.id === data.id) {
                                    parents.push(key);
                                }
                                return true;
                            });
                        }
                    });
                    return onError(makeError('scripterror', 'Script error for "' + data.id +
                                             (parents.length ?
                                             '", needed by: ' + parents.join(', ') :
                                             '"'), evt, [data.id]));
                }
            }
        };

        context.require = context.makeRequire();
        return context;
    }

    /**
     * Main entry point.
     *
     * If the only argument to require is a string, then the module that
     * is represented by that string is fetched for the appropriate context.
     *
     * If the first argument is an array, then it will be treated as an array
     * of dependency string names to fetch. An optional function callback can
     * be specified to execute when all of those dependencies are available.
     *
     * Make a local req variable to help Caja compliance (it assumes things
     * on a require that are not standardized), and to give a short
     * name for minification/local scope use.
     */
    req = requirejs = function (deps, callback, errback, optional) {

        //Find the right context, use default
        var context, config,
            contextName = defContextName;

        // Determine if have config object in the call.
        if (!isArray(deps) && typeof deps !== 'string') {
            // deps is a config object
            config = deps;
            if (isArray(callback)) {
                // Adjust args if there are dependencies
                deps = callback;
                callback = errback;
                errback = optional;
            } else {
                deps = [];
            }
        }

        if (config && config.context) {
            contextName = config.context;
        }

        context = getOwn(contexts, contextName);
        if (!context) {
            context = contexts[contextName] = req.s.newContext(contextName);
        }

        if (config) {
            context.configure(config);
        }

        return context.require(deps, callback, errback);
    };

    /**
     * Support require.config() to make it easier to cooperate with other
     * AMD loaders on globally agreed names.
     */
    req.config = function (config) {
        return req(config);
    };

    /**
     * Execute something after the current tick
     * of the event loop. Override for other envs
     * that have a better solution than setTimeout.
     * @param  {Function} fn function to execute later.
     */
    req.nextTick = typeof setTimeout !== 'undefined' ? function (fn) {
        setTimeout(fn, 4);
    } : function (fn) { fn(); };

    /**
     * Export require as a global, but only if it does not already exist.
     */
    if (!require) {
        require = req;
    }

    req.version = version;

    //Used to filter out dependencies that are already paths.
    req.jsExtRegExp = /^\/|:|\?|\.js$/;
    req.isBrowser = isBrowser;
    s = req.s = {
        contexts: contexts,
        newContext: newContext
    };

    //Create default context.
    req({});

    //Exports some context-sensitive methods on global require.
    each([
        'toUrl',
        'undef',
        'defined',
        'specified'
    ], function (prop) {
        //Reference from contexts instead of early binding to default context,
        //so that during builds, the latest instance of the default context
        //with its config gets used.
        req[prop] = function () {
            var ctx = contexts[defContextName];
            return ctx.require[prop].apply(ctx, arguments);
        };
    });

    if (isBrowser) {
        head = s.head = document.getElementsByTagName('head')[0];
        //If BASE tag is in play, using appendChild is a problem for IE6.
        //When that browser dies, this can be removed. Details in this jQuery bug:
        //http://dev.jquery.com/ticket/2709
        baseElement = document.getElementsByTagName('base')[0];
        if (baseElement) {
            head = s.head = baseElement.parentNode;
        }
    }

    /**
     * Any errors that require explicitly generates will be passed to this
     * function. Intercept/override it if you want custom error handling.
     * @param {Error} err the error object.
     */
    req.onError = defaultOnError;

    /**
     * Creates the node for the load command. Only used in browser envs.
     */
    req.createNode = function (config, moduleName, url) {
        var node = config.xhtml ?
                document.createElementNS('http://www.w3.org/1999/xhtml', 'html:script') :
                document.createElement('script');
        node.type = config.scriptType || 'text/javascript';
        node.charset = 'utf-8';
        node.async = true;
        return node;
    };

    /**
     * Does the request to load a module for the browser case.
     * Make this a separate function to allow other environments
     * to override it.
     *
     * @param {Object} context the require context to find state.
     * @param {String} moduleName the name of the module.
     * @param {Object} url the URL to the module.
     */
    req.load = function (context, moduleName, url) {
        var config = (context && context.config) || {},
            node;
        if (isBrowser) {
            //In the browser so use a script tag
            node = req.createNode(config, moduleName, url);
            if (config.onNodeCreated) {
                config.onNodeCreated(node, config, moduleName, url);
            }

            node.setAttribute('data-requirecontext', context.contextName);
            node.setAttribute('data-requiremodule', moduleName);

            //Set up load listener. Test attachEvent first because IE9 has
            //a subtle issue in its addEventListener and script onload firings
            //that do not match the behavior of all other browsers with
            //addEventListener support, which fire the onload event for a
            //script right after the script execution. See:
            //https://connect.microsoft.com/IE/feedback/details/648057/script-onload-event-is-not-fired-immediately-after-script-execution
            //UNFORTUNATELY Opera implements attachEvent but does not follow the script
            //script execution mode.
            if (node.attachEvent &&
                    //Check if node.attachEvent is artificially added by custom script or
                    //natively supported by browser
                    //read https://github.com/jrburke/requirejs/issues/187
                    //if we can NOT find [native code] then it must NOT natively supported.
                    //in IE8, node.attachEvent does not have toString()
                    //Note the test for "[native code" with no closing brace, see:
                    //https://github.com/jrburke/requirejs/issues/273
                    !(node.attachEvent.toString && node.attachEvent.toString().indexOf('[native code') < 0) &&
                    !isOpera) {
                //Probably IE. IE (at least 6-8) do not fire
                //script onload right after executing the script, so
                //we cannot tie the anonymous define call to a name.
                //However, IE reports the script as being in 'interactive'
                //readyState at the time of the define call.
                useInteractive = true;

                node.attachEvent('onreadystatechange', context.onScriptLoad);
                //It would be great to add an error handler here to catch
                //404s in IE9+. However, onreadystatechange will fire before
                //the error handler, so that does not help. If addEventListener
                //is used, then IE will fire error before load, but we cannot
                //use that pathway given the connect.microsoft.com issue
                //mentioned above about not doing the 'script execute,
                //then fire the script load event listener before execute
                //next script' that other browsers do.
                //Best hope: IE10 fixes the issues,
                //and then destroys all installs of IE 6-9.
                //node.attachEvent('onerror', context.onScriptError);
            } else {
                node.addEventListener('load', context.onScriptLoad, false);
                node.addEventListener('error', context.onScriptError, false);
            }
            node.src = url;

            //For some cache cases in IE 6-8, the script executes before the end
            //of the appendChild execution, so to tie an anonymous define
            //call to the module name (which is stored on the node), hold on
            //to a reference to this node, but clear after the DOM insertion.
            currentlyAddingScript = node;
            if (baseElement) {
                head.insertBefore(node, baseElement);
            } else {
                head.appendChild(node);
            }
            currentlyAddingScript = null;

            return node;
        } else if (isWebWorker) {
            try {
                //In a web worker, use importScripts. This is not a very
                //efficient use of importScripts, importScripts will block until
                //its script is downloaded and evaluated. However, if web workers
                //are in play, the expectation is that a build has been done so
                //that only one script needs to be loaded anyway. This may need
                //to be reevaluated if other use cases become common.
                importScripts(url);

                //Account for anonymous modules
                context.completeLoad(moduleName);
            } catch (e) {
                context.onError(makeError('importscripts',
                                'importScripts failed for ' +
                                    moduleName + ' at ' + url,
                                e,
                                [moduleName]));
            }
        }
    };

    function getInteractiveScript() {
        if (interactiveScript && interactiveScript.readyState === 'interactive') {
            return interactiveScript;
        }

        eachReverse(scripts(), function (script) {
            if (script.readyState === 'interactive') {
                return (interactiveScript = script);
            }
        });
        return interactiveScript;
    }

    //Look for a data-main script attribute, which could also adjust the baseUrl.
    if (isBrowser && !cfg.skipDataMain) {
        //Figure out baseUrl. Get it from the script tag with require.js in it.
        eachReverse(scripts(), function (script) {
            //Set the 'head' where we can append children by
            //using the script's parent.
            if (!head) {
                head = script.parentNode;
            }

            //Look for a data-main attribute to set main script for the page
            //to load. If it is there, the path to data main becomes the
            //baseUrl, if it is not already set.
            dataMain = script.getAttribute('data-main');
            if (dataMain) {
                //Preserve dataMain in case it is a path (i.e. contains '?')
                mainScript = dataMain;

                //Set final baseUrl if there is not already an explicit one.
                if (!cfg.baseUrl) {
                    //Pull off the directory of data-main for use as the
                    //baseUrl.
                    src = mainScript.split('/');
                    mainScript = src.pop();
                    subPath = src.length ? src.join('/')  + '/' : './';

                    cfg.baseUrl = subPath;
                }

                //Strip off any trailing .js since mainScript is now
                //like a module name.
                mainScript = mainScript.replace(jsSuffixRegExp, '');

                //If mainScript is still a path, fall back to dataMain
                if (req.jsExtRegExp.test(mainScript)) {
                    mainScript = dataMain;
                }

                //Put the data-main script in the files to load.
                cfg.deps = cfg.deps ? cfg.deps.concat(mainScript) : [mainScript];

                return true;
            }
        });
    }

    /**
     * The function that handles definitions of modules. Differs from
     * require() in that a string for the module should be the first argument,
     * and the function to execute after dependencies are loaded should
     * return a value to define the module corresponding to the first argument's
     * name.
     */
    define = function (name, deps, callback) {
        var node, context;

        //Allow for anonymous modules
        if (typeof name !== 'string') {
            //Adjust args appropriately
            callback = deps;
            deps = name;
            name = null;
        }

        //This module may not have dependencies
        if (!isArray(deps)) {
            callback = deps;
            deps = null;
        }

        //If no name, and callback is a function, then figure out if it a
        //CommonJS thing with dependencies.
        if (!deps && isFunction(callback)) {
            deps = [];
            //Remove comments from the callback string,
            //look for require calls, and pull them into the dependencies,
            //but only if there are function args.
            if (callback.length) {
                callback
                    .toString()
                    .replace(commentRegExp, '')
                    .replace(cjsRequireRegExp, function (match, dep) {
                        deps.push(dep);
                    });

                //May be a CommonJS thing even without require calls, but still
                //could use exports, and module. Avoid doing exports and module
                //work though if it just needs require.
                //REQUIRES the function to expect the CommonJS variables in the
                //order listed below.
                deps = (callback.length === 1 ? ['require'] : ['require', 'exports', 'module']).concat(deps);
            }
        }

        //If in IE 6-8 and hit an anonymous define() call, do the interactive
        //work.
        if (useInteractive) {
            node = currentlyAddingScript || getInteractiveScript();
            if (node) {
                if (!name) {
                    name = node.getAttribute('data-requiremodule');
                }
                context = contexts[node.getAttribute('data-requirecontext')];
            }
        }

        //Always save off evaluating the def call until the script onload handler.
        //This allows multiple modules to be in a file without prematurely
        //tracing dependencies, and allows for anonymous module support,
        //where the module name is not known until the script onload event
        //occurs. If no context, use the global queue, and get it processed
        //in the onscript load callback.
        if (context) {
            context.defQueue.push([name, deps, callback]);
            context.defQueueMap[name] = true;
        } else {
            globalDefQueue.push([name, deps, callback]);
        }
    };

    define.amd = {
        jQuery: true
    };

    /**
     * Executes the text. Normally just uses eval, but can be modified
     * to use a better, environment-specific call. Only used for transpiling
     * loader plugins, not for plain JS modules.
     * @param {String} text the text to execute/evaluate.
     */
    req.exec = function (text) {
        /*jslint evil: true */
        return eval(text);
    };

    //Set up with config info.
    req(cfg);
}(this));
",
              "headers": [
                [
                  "content-type",
                  "text/javascript"
                ]
              ],
              "ok": true,
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 542
        }
      },
      "cell_type": "code",
      "source": [
        "import plotly.plotly as py\n",
        "import numpy as np\n",
        "from plotly.offline import iplot\n",
        "from plotly.graph_objs import Contours, Histogram2dContour, Marker, Scatter\n",
        "\n",
        "enable_plotly_in_cell()\n",
        "\n",
        "x = np.random.randn(2000)\n",
        "y = np.random.randn(2000)\n",
        "iplot([Histogram2dContour(x=x, y=y, contours=Contours(coloring='heatmap')),\n",
        "       Scatter(x=x, y=y, mode='markers', marker=Marker(color='white', size=3, opacity=0.3))], show_link=False)\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "        <script src=\"/static/components/requirejs/require.js\"></script>\n",
              "  "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<script type='text/javascript'>if(!window.Plotly){define('plotly', function(require, exports, module) {/**\n",
              "* plotly.js v1.20.5\n",
              "* Copyright 2012-2016, Plotly, Inc.\n",
              "* All rights reserved.\n",
              "* Licensed under the MIT license\n",
              "*/\n",
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              "function n(t){var e=32;return t&=-t,t&&e--,65535&t&&(e-=16),16711935&t&&(e-=8),252645135&t&&(e-=4),858993459&t&&(e-=2),1431655765&t&&(e-=1),e}var i=32;r.INT_BITS=i,r.INT_MAX=2147483647,r.INT_MIN=-1<<i-1,r.sign=function(t){return(t>0)-(t<0)},r.abs=function(t){var e=t>>i-1;return(t^e)-e},r.min=function(t,e){return e^(t^e)&-(t<e)},r.max=function(t,e){return t^(t^e)&-(t<e)},r.isPow2=function(t){return!(t&t-1||!t)},r.log2=function(t){var e,r;return e=(t>65535)<<4,t>>>=e,r=(t>255)<<3,t>>>=r,e|=r,r=(t>15)<<2,t>>>=r,e|=r,r=(t>3)<<1,t>>>=r,e|=r,e|t>>1},r.log10=function(t){return t>=1e9?9:t>=1e8?8:t>=1e7?7:t>=1e6?6:t>=1e5?5:t>=1e4?4:t>=1e3?3:t>=100?2:t>=10?1:0},r.popCount=function(t){return t-=t>>>1&1431655765,t=(858993459&t)+(t>>>2&858993459),16843009*(t+(t>>>4)&252645135)>>>24},r.countTrailingZeros=n,r.nextPow2=function(t){return t+=0===t,--t,t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,t|=t>>>16,t+1},r.prevPow2=function(t){return t|=t>>>1,t|=t>>>2,t|=t>>>4,t|=t>>>8,t|=t>>>16,t-(t>>>1)},r.parity=function(t){return t^=t>>>16,t^=t>>>8,t^=t>>>4,t&=15,27030>>>t&1};var a=new Array(256);!function(t){for(var e=0;e<256;++e){var r=e,n=e,i=7;for(r>>>=1;r;r>>>=1)n<<=1,n|=1&r,--i;t[e]=n<<i&255}}(a),r.reverse=function(t){return a[255&t]<<24|a[t>>>8&255]<<16|a[t>>>16&255]<<8|a[t>>>24&255]},r.interleave2=function(t,e){return t&=65535,t=16711935&(t|t<<8),t=252645135&(t|t<<4),t=858993459&(t|t<<2),t=1431655765&(t|t<<1),e&=65535,e=16711935&(e|e<<8),e=252645135&(e|e<<4),e=858993459&(e|e<<2),e=1431655765&(e|e<<1),t|e<<1},r.deinterleave2=function(t,e){return t=t>>>e&1431655765,t=858993459&(t|t>>>1),t=252645135&(t|t>>>2),t=16711935&(t|t>>>4),t=65535&(t|t>>>16),t<<16>>16},r.interleave3=function(t,e,r){return 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a(t,e,r){for(var n=0,i=Math.min(t.length,r),a=e;a<i;a++){var o=t.charCodeAt(a)-48;n<<=4,n|=o>=49&&o<=54?o-49+10:o>=17&&o<=22?o-17+10:15&o}return n}function o(t,e,r,n){for(var i=0,a=Math.min(t.length,r),o=e;o<a;o++){var s=t.charCodeAt(o)-48;i*=n,i+=s>=49?s-49+10:s>=17?s-17+10:s}return i}function s(t,e){this.name=t,this.p=new i(e,16),this.n=this.p.bitLength(),this.k=new i(1).ishln(this.n).isub(this.p),this.tmp=this._tmp()}function l(){s.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function u(){s.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function c(){s.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function h(){s.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function f(t){if(\"string\"==typeof t){var e=i._prime(t);this.m=e.p,this.prime=e}else this.m=t,this.prime=null}function 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this.length>t.length?this.clone().ior(t):t.clone().ior(this)},i.prototype.iand=function(t){this.sign=this.sign&&t.sign;var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},i.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},i.prototype.ixor=function(t){this.sign=this.sign||t.sign;var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},i.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},i.prototype.setn=function(t,e){r(\"number\"==typeof t&&t>=0);for(var n=t/26|0,i=t%26;this.length<=n;)this.words[this.length++]=0;return e?this.words[n]=this.words[n]|1<<i:this.words[n]=this.words[n]&~(1<<i),this.strip()},i.prototype.iadd=function(t){if(this.sign&&!t.sign){this.sign=!1;var e=this.isub(t);return this.sign=!this.sign,this._normSign()}if(!this.sign&&t.sign){t.sign=!1;var e=this.isub(t);return t.sign=!0,e._normSign()}var r,n;this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++){var e=r.words[a]+n.words[a]+i;this.words[a]=67108863&e,i=e>>>26}for(;0!==i&&a<r.length;a++){var e=r.words[a]+i;this.words[a]=67108863&e,i=e>>>26}if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},i.prototype.add=function(t){if(t.sign&&!this.sign){t.sign=!1;var e=this.sub(t);return t.sign=!0,e}if(!t.sign&&this.sign){this.sign=!1;var e=t.sub(this);return this.sign=!0,e}return this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(t.sign){t.sign=!1;var e=this.iadd(t);return t.sign=!0,e._normSign()}if(this.sign)return this.sign=!1,this.iadd(t),this.sign=!0,this._normSign();var r=this.cmp(t);if(0===r)return this.sign=!1,this.length=1,this.words[0]=0,this;var n,i;r>0?(n=this,i=t):(n=t,i=this);for(var a=0,o=0;o<i.length;o++){var e=n.words[o]-i.words[o]+a;a=e>>26,this.words[o]=67108863&e}for(;0!==a&&o<n.length;o++){var e=n.words[o]+a;a=e>>26,this.words[o]=67108863&e}if(0===a&&o<n.length&&n!==this)for(;o<n.length;o++)this.words[o]=n.words[o];return this.length=Math.max(this.length,o),n!==this&&(this.sign=!0),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)},i.prototype._smallMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0;n<e.length-1;n++){for(var i=r>>>26,a=67108863&r,o=Math.min(n,t.length-1),s=Math.max(0,n-this.length+1);s<=o;s++){var l=n-s,u=0|this.words[l],c=0|t.words[s],h=u*c,f=67108863&h;i=i+(h/67108864|0)|0,f=f+a|0,a=67108863&f,i=i+(f>>>26)|0}e.words[n]=a,r=i}return 0!==r?e.words[n]=r:e.length--,e.strip()},i.prototype._bigMulTo=function(t,e){e.sign=t.sign!==this.sign,e.length=this.length+t.length;for(var r=0,n=0,i=0;i<e.length-1;i++){var a=n;n=0;for(var o=67108863&r,s=Math.min(i,t.length-1),l=Math.max(0,i-this.length+1);l<=s;l++){var u=i-l,c=0|this.words[u],h=0|t.words[l],f=c*h,d=67108863&f;a=a+(f/67108864|0)|0,d=d+o|0,o=67108863&d,a=a+(d>>>26)|0,n+=a>>>26,a&=67108863}e.words[i]=o,r=a,a=n}return 0!==r?e.words[i]=r:e.length--,e.strip()},i.prototype.mulTo=function(t,e){var r;return r=this.length+t.length<63?this._smallMulTo(t,e):this._bigMulTo(t,e)},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.imul=function(t){if(0===this.cmpn(0)||0===t.cmpn(0))return this.words[0]=0,this.length=1,this;var e=this.length,r=t.length;this.sign=t.sign!==this.sign,this.length=this.length+t.length,this.words[this.length-1]=0;for(var n=this.length-2;n>=0;n--){for(var i=0,a=0,o=Math.min(n,r-1),s=Math.max(0,n-e+1);s<=o;s++){var l=n-s,u=this.words[l],c=t.words[s],h=u*c,f=67108863&h;i+=h/67108864|0,f+=a,a=67108863&f,i+=f>>>26}this.words[n]=a,this.words[n+1]+=i,i=0}for(var i=0,l=1;l<this.length;l++){var d=this.words[l]+i;this.words[l]=67108863&d,i=d>>>26}return this.strip()},i.prototype.imuln=function(t){r(\"number\"==typeof t);for(var e=0,n=0;n<this.length;n++){var i=this.words[n]*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[n]=67108863&a}return 0!==e&&(this.words[n]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.mul(this)},i.prototype.ishln=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=67108863>>>26-e<<26-e;if(0!==e){for(var a=0,o=0;o<this.length;o++){var s=this.words[o]&i,l=this.words[o]-s<<e;this.words[o]=l|a,a=s>>>26-e}a&&(this.words[o]=a,this.length++)}if(0!==n){for(var o=this.length-1;o>=0;o--)this.words[o+n]=this.words[o];for(var o=0;o<n;o++)this.words[o]=0;this.length+=n}return this.strip()},i.prototype.ishrn=function(t,e,n){r(\"number\"==typeof t&&t>=0);var i;i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=n;if(i-=o,i=Math.max(0,i),l){for(var u=0;u<o;u++)l.words[u]=this.words[u];l.length=o}if(0===o);else if(this.length>o){this.length-=o;for(var u=0;u<this.length;u++)this.words[u]=this.words[u+o]}else this.words[0]=0,this.length=1;for(var c=0,u=this.length-1;u>=0&&(0!==c||u>=i);u--){var h=this.words[u];this.words[u]=c<<26-a|h>>>a,c=h&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip(),this},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.testn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n)return!1;var a=this.words[n];return!!(a&i)},i.prototype.imaskn=function(t){r(\"number\"==typeof t&&t>=0);var e=t%26,n=(t-e)/26;if(r(!this.sign,\"imaskn works only with positive numbers\"),0!==e&&n++,this.length=Math.min(n,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return r(\"number\"==typeof t),t<0?this.isubn(-t):this.sign?1===this.length&&this.words[0]<t?(this.words[0]=t-this.words[0],this.sign=!1,this):(this.sign=!1,this.isubn(t),this.sign=!0,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(r(\"number\"==typeof t),t<0)return this.iaddn(-t);if(this.sign)return this.sign=!1,this.iaddn(t),this.sign=!0,this;this.words[0]-=t;for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.sign=!1,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,n){var i,a=t.length+n;if(this.words.length<a){for(var o=new Array(a),i=0;i<this.length;i++)o[i]=this.words[i];this.words=o}else i=this.length;for(this.length=Math.max(this.length,a);i<this.length;i++)this.words[i]=0;for(var s=0,i=0;i<t.length;i++){var l=this.words[i+n]+s,u=t.words[i]*e;l-=67108863&u,s=(l>>26)-(u/67108864|0),this.words[i+n]=67108863&l}for(;i<this.length-n;i++){var l=this.words[i+n]+s;s=l>>26,this.words[i+n]=67108863&l}if(0===s)return this.strip();r(s===-1),s=0;for(var i=0;i<this.length;i++){var l=-this.words[i]+s;s=l>>26,this.words[i]=67108863&l}return this.sign=!0,this.strip()},i.prototype._wordDiv=function(t,e){var r=this.length-t.length,n=this.clone(),a=t,o=a.words[a.length-1],s=this._countBits(o);r=26-s,0!==r&&(a=a.shln(r),n.ishln(r),o=a.words[a.length-1]);var l,u=n.length-a.length;if(\"mod\"!==e){l=new i(null),l.length=u+1,l.words=new Array(l.length);for(var c=0;c<l.length;c++)l.words[c]=0}var h=n.clone()._ishlnsubmul(a,1,u);h.sign||(n=h,l&&(l.words[u]=1));for(var f=u-1;f>=0;f--){var d=67108864*n.words[a.length+f]+n.words[a.length+f-1];for(d=Math.min(d/o|0,67108863),n._ishlnsubmul(a,d,f);n.sign;)d--,n.sign=!1,n._ishlnsubmul(a,1,f),0!==n.cmpn(0)&&(n.sign=!n.sign);l&&(l.words[f]=d)}return l&&l.strip(),n.strip(),\"div\"!==e&&0!==r&&n.ishrn(r),{div:l?l:null,mod:n}},i.prototype.divmod=function(t,e){if(r(0!==t.cmpn(0)),this.sign&&!t.sign){var n,a,o=this.neg().divmod(t,e);return\"mod\"!==e&&(n=o.div.neg()),\"div\"!==e&&(a=0===o.mod.cmpn(0)?o.mod:t.sub(o.mod)),{div:n,mod:a}}if(!this.sign&&t.sign){var n,o=this.divmod(t.neg(),e);return\"mod\"!==e&&(n=o.div.neg()),{div:n,mod:o.mod}}return this.sign&&t.sign?this.neg().divmod(t.neg(),e):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e)},i.prototype.div=function(t){return this.divmod(t,\"div\").div},i.prototype.mod=function(t){return this.divmod(t,\"mod\").mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(0===e.mod.cmpn(0))return e.div;var r=e.div.sign?e.mod.isub(t):e.mod,n=t.shrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:e.div.sign?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){r(t<=67108863);for(var e=(1<<26)%t,n=0,i=this.length-1;i>=0;i--)n=(e*n+this.words[i])%t;return n},i.prototype.idivn=function(t){r(t<=67108863);for(var e=0,n=this.length-1;n>=0;n--){var i=this.words[n]+67108864*e;this.words[n]=i/t|0,e=i%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),u=0;e.isEven()&&n.isEven();)e.ishrn(1),n.ishrn(1),++u;for(var c=n.clone(),h=e.clone();0!==e.cmpn(0);){for(;e.isEven();)e.ishrn(1),a.isEven()&&o.isEven()?(a.ishrn(1),o.ishrn(1)):(a.iadd(c).ishrn(1),o.isub(h).ishrn(1));for(;n.isEven();)n.ishrn(1),s.isEven()&&l.isEven()?(s.ishrn(1),l.ishrn(1)):(s.iadd(c).ishrn(1),l.isub(h).ishrn(1));e.cmp(n)>=0?(e.isub(n),a.isub(s),o.isub(l)):(n.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:n.ishln(u)}},i.prototype._invmp=function(t){r(!t.sign),r(0!==t.cmpn(0));var e=this,n=t.clone();e=e.sign?e.mod(t):e.clone();for(var a=new i(1),o=new i(0),s=n.clone();e.cmpn(1)>0&&n.cmpn(1)>0;){for(;e.isEven();)e.ishrn(1),a.isEven()?a.ishrn(1):a.iadd(s).ishrn(1);for(;n.isEven();)n.ishrn(1),o.isEven()?o.ishrn(1):o.iadd(s).ishrn(1);e.cmp(n)>=0?(e.isub(n),a.isub(o)):(n.isub(e),o.isub(a))}return 0===e.cmpn(1)?a:o},i.prototype.gcd=function(t){if(0===this.cmpn(0))return t.clone();if(0===t.cmpn(0))return this.clone();var e=this.clone(),r=t.clone();e.sign=!1,r.sign=!1;for(var n=0;e.isEven()&&r.isEven();n++)e.ishrn(1),r.ishrn(1);for(;;){for(;e.isEven();)e.ishrn(1);for(;r.isEven();)r.ishrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.ishln(n)},i.prototype.invm=function(t){return this.egcd(t).a.mod(t)},i.prototype.isEven=function(){return 0===(1&this.words[0])},i.prototype.isOdd=function(){return 1===(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){r(\"number\"==typeof t);var e=t%26,n=(t-e)/26,i=1<<e;if(this.length<=n){for(var a=this.length;a<n+1;a++)this.words[a]=0;return this.words[n]|=i,this.length=n+1,this}for(var o=i,a=n;0!==o&&a<this.length;a++){var s=this.words[a];s+=o,o=s>>>26,s&=67108863,this.words[a]=s}return 0!==o&&(this.words[a]=o,this.length++),this},i.prototype.cmpn=function(t){var e=t<0;if(e&&(t=-t),this.sign&&!e)return-1;if(!this.sign&&e)return 1;t&=67108863,this.strip();var r;if(this.length>1)r=1;else{var n=this.words[0];r=n===t?0:n<t?-1:1}return this.sign&&(r=-r),r},i.prototype.cmp=function(t){if(this.sign&&!t.sign)return-1;if(!this.sign&&t.sign)return 1;var e=this.ucmp(t);return this.sign?-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=this.words[r],i=t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},i.red=function(t){return new f(t)},i.prototype.toRed=function(t){return r(!this.red,\"Already a number in reduction context\"),r(!this.sign,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return r(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return r(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return r(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return r(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return r(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return r(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return r(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return r(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return r(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return r(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return r(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return r(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return r(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return r(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};s.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},s.prototype.ireduce=function(t){var e,r=t;do this.split(r,this.tmp),r=this.imulK(r),r=r.iadd(this.tmp),e=r.bitLength();while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},s.prototype.split=function(t,e){t.ishrn(this.n,0,e)},s.prototype.imulK=function(t){return t.imul(this.k)},n(l,s),l.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i<n;i++)e.words[i]=t.words[i];if(e.length=n,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];e.words[e.length++]=a&r;for(var i=10;i<t.length;i++){var o=t.words[i];t.words[i-10]=(o&r)<<4|a>>>22,a=o}t.words[i-10]=a>>>22,t.length-=9},l.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e,r=0,n=0;n<t.length;n++){var i=t.words[n];e=64*i,r+=977*i,e+=r/67108864|0,r&=67108863,t.words[n]=r,r=e}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},n(u,s),n(c,s),n(h,s),h.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*t.words[r]+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function t(e){if(v[e])return v[e];var t;if(\"k256\"===e)t=new l;else if(\"p224\"===e)t=new u;else if(\"p192\"===e)t=new c;else{if(\"p25519\"!==e)throw new Error(\"Unknown prime \"+e);t=new h}return v[e]=t,t},f.prototype._verify1=function(t){r(!t.sign,\"red works only with positives\"),r(t.red,\"red works only with red numbers\")},f.prototype._verify2=function(t,e){r(!t.sign&&!e.sign,\"red works only with positives\"),r(t.red&&t.red===e.red,\"red works only with red numbers\")},f.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.mod(this.m)._forceRed(this)},f.prototype.neg=function(t){var e=t.clone();return e.sign=!e.sign,e.iadd(this.m)._forceRed(this)},f.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},f.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},f.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},f.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},f.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.shln(e))},f.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},f.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},f.prototype.isqr=function(t){return this.imul(t,t)},f.prototype.sqr=function(t){return this.mul(t,t)},f.prototype.sqrt=function(t){if(0===t.cmpn(0))return t.clone();var e=this.m.andln(3);if(r(e%2===1),3===e){var n=this.m.add(new i(1)).ishrn(2),a=this.pow(t,n);return a}for(var o=this.m.subn(1),s=0;0!==o.cmpn(0)&&0===o.andln(1);)s++,o.ishrn(1);r(0!==o.cmpn(0));var l=new i(1).toRed(this),u=l.redNeg(),c=this.m.subn(1).ishrn(1),h=this.m.bitLength();for(h=new i(2*h*h).toRed(this);0!==this.pow(h,c).cmp(u);)h.redIAdd(u);for(var f=this.pow(h,o),a=this.pow(t,o.addn(1).ishrn(1)),d=this.pow(t,o),p=s;0!==d.cmp(l);){for(var g=d,m=0;0!==g.cmp(l);m++)g=g.redSqr();r(m<p);var v=this.pow(f,new i(1).ishln(p-m-1));a=a.redMul(v),f=v.redSqr(),d=d.redMul(f),p=m}return a},f.prototype.invm=function(t){var e=t._invmp(this.m);return e.sign?(e.sign=!1,this.imod(e).redNeg()):this.imod(e)},f.prototype.pow=function(t,e){var r=[];if(0===e.cmpn(0))return new i(1);for(var n=e.clone();0!==n.cmpn(0);)r.push(n.andln(1)),n.ishrn(1);for(var a=t,o=0;o<r.length&&0===r[o];o++,a=this.sqr(a));if(++o<r.length)for(var n=this.sqr(a);o<r.length;o++,n=this.sqr(n))0!==r[o]&&(a=this.mul(a,n));return a},f.prototype.convertTo=function(t){var e=t.mod(this.m);return e===t?e.clone():e},f.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new d(t)},n(d,f),d.prototype.convertTo=function(t){return this.imod(t.shln(this.shift))},d.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},d.prototype.imul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).ishrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},d.prototype.mul=function(t,e){if(0===t.cmpn(0)||0===e.cmpn(0))return new i(0)._forceRed(this);var 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