exercise_3_sol.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "15db3f9b",
   "metadata": {},
   "source": [
    "# Best practices in data visualization - ASPP 2022, Bilbao\n",
    "## Exercise 3 - Working with images\n",
    "\n",
    "(Material adapted from [tutorials by Nicolas Rougier](https://github.com/ASPP/2021-bordeaux-dataviz))\n",
    "\n",
    "#### Initialization "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "17021f76",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "\n",
    "#p = plt.rcParams\n",
    "#p[\"figure.dpi\"] = 300\n",
    "\n",
    "%matplotlib inline \n",
    "# this line avoids writing plt.show() for every image"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5abc1762",
   "metadata": {},
   "source": [
    "### 1. Generating the data "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f094c2e",
   "metadata": {},
   "source": [
    "In this exercise, we are going to focus on function [imshow](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html) which means *image show*. We are going to learn to use it and then play with it a bit.\n",
    "\n",
    "Let's first generate some 2D data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "34596771",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(1)\n",
    "X = np.random.uniform(0,10,250)\n",
    "Y = X*np.abs(np.random.normal(0,1,len(X)))**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "07d0e9fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# f is an two-variable arbitrary function, we will sample from this function\n",
    "def f(x,y,n=100):\n",
    "    X,Y = np.meshgrid(np.linspace(-3, 3, n),\n",
    "                      np.linspace(-3, 3, n))\n",
    "    return (1-X/2+X**5+Y**3)*np.exp(-X**2-Y**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e5846f9",
   "metadata": {},
   "source": [
    "We are now ready to display them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c29a24c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "Z5  = f(X, Y, n=5) # 5 values along the x and y axis\n",
    "Z10 = f(X, Y, n=10) \n",
    "Z25 = f(X, Y, n=25) \n",
    "Z100 = f(X, Y, n=100) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fee97984",
   "metadata": {},
   "source": [
    "### 2. Making image plots "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "86533326",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f32fd688370>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,4))\n",
    "ax = plt.subplot(1,4,1); ax.imshow(Z5)\n",
    "ax = plt.subplot(1,4,2); ax.imshow(Z10)\n",
    "ax = plt.subplot(1,4,3); ax.imshow(Z25)\n",
    "ax = plt.subplot(1,4,4); ax.imshow(Z100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b634b6d",
   "metadata": {},
   "source": [
    "### 3. Extent \n",
    "To be able to display these images, matplotlib made several implicit choices. \n",
    "\n",
    "First, you may have noticed that the limit on the axis are different on each of the three plots and do not relate to the [-3,+3] domain we used to define the image. The reason is that matplotlib has not idea where your images come from and cannot guess what the axis' units and its limits are. To solve this problem, we thus need to specify the extent of the image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "771bff12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f32fdb4ba90>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SSeT/z0vrvw1meO4LfzKrW7DPXuAhAzxJdVwDxBbksTZbGGOdY7ZQ3e/7Dg+Yk9nT2OyHyhjzktt5tFhjUQFXVEtFnlKLqbHvBGmqxa7eg9F7NE0lTbX5xhjimnOgLJlEnog+AMDfAPAGZv5BIvqQS8vdBhjOyBJG2JQlquCpINhgcw8iC/MdU7VSf2Cu9uW0qU8wDdhhMTDritc2FhN4ekZoA1wNcg4UBzbF1jk+ryXSMAdUbvIi3VLVuZAbAkQGcFzPgbJkEvlPR5od7wcBgJl/7NJCrw+GC9TjqXPmGOHJIDgBgIuY4dj1rKji1IA1GPigYhhDEHT1JHFftADQbTNV4PpYMtZuHvAaNr8WS6zTDmyFp9yjqq1qDLSd7h4B0yzx1hniCd7kNSaR/08A3BHRNyJNIv9mZn7raTUu5bpgeM7NXHLOGPCNyOI+u3Vep9S/wd5Wl4qZeHY4BMEGSDbWveSeHzWbvL4xq2n/U6mP4XI1eQBqTsMvjlcfmbNAbGWW/iDCJ6nJa0wifwDwm5CmC30FgP+LiN7BzN+/tBK1XJ8ZjsiDMsIGG1zKIJt1m3pQx4zhC9M103imUeVXa2rOh1u/l+5dJTnOzfzqio+C38Q1JPAZT1Dk2VJzbR/ZsYL9VerxgBGGYV55O9+Nufe5CDp3N6F+Jqbbrzq2hCE2ZEvskLFqaM2SSeTfhwSqvwDgF4jomwD8egBng+H1vMmn3sQLGGHbccKDffOqdANU5+o1ku4ir3GtDlb7avbjgabVbzfnQWV+NbC4/aCRbYyAUV3fke1LZbbXSX1dlJnzwJ7YYJplugaIjrHN1n06RcY+qtcn5SZR2OHcf4HYJPJE9ARpEvmvq9J8LYD/jIgORPRKJDX6PZfUf5PMcO5rNxo+44812F7a11CJR9OO5F2XPVnZMr1/OQqWMXfuhHBDHdP62zEmd4xLgPaATVU6cvkA5TUvqPcY0A7U1OpYm+1ReW6Q/UHShDJvdmlKGyNPglTrftRqcW4PtuPGFivGNsYSB/sbDPFW7IeM9QZqWDKJPDO/h4j+IYB3A4gA3sLM33VJuZsEw4HMqccTDLCVRxP8dP0kdjlR5Ro8nOpTgFddx6XPUyt/di+GYFqxXpUzVJfdYQPGDByDUJIZ8UDo6z3m9JjOo/yPvXe1aj0EYH8Dc/mTHmUuj9ftWLS7l9ZH6kTZAtAtEQbhGB9vEnnZ/iIAX7RWmZsDw8Xs6wJGOAgIbmwvAcO0f1hBllFbUoJ8nrcVeUAchJ1MsZSKafptypdo12TA5q6xmLiJYeyG3XXbADSGLi6vhVJfU0t11rqM2f+U8TVthcr6aoboGaHaCgMPGSJcOVrnxnUMxpOtnzUHiPCaB9PgdmmRmNo/xRDrj2ArzZVk7463opykHrf2jzDCFhDWtr8xMB2CYv0U1pUp05hLwoMeDwFR0xRZT7GVVvr6kL6kbl3L1vTk6piCbMqsB9unspyaedVApMsBgxt+CAZAWe93ZdZ5DFVlV7eqrrVwkagExybA2U7pc13T7mdReB/P8GGlpZJy+/iA6ck+P3JLAYS6L/q07Xzq0V8mQdvYl6SVHRlw3LGaEfpsWuChGUyJIyZNRxB71levU2N/Zo16rC5rUkZAq7b/jS4DwIEKIBvYCI39uW1ji9wEQftA1PWbuhTPmpXVU7lPP0J5m4t775utBlBv4jjHfnhNdsjYwXA1Odk50QSt8rhnaAMgHDC+8vhU2M1onVECXWmXy6Boz/EpQOhBZOLc8gPB5b6qrbje30iXqVWVZ13WlBSAQyVbrAEw5HNqp0mL3dXqbulE4eF+VHloY1T1LMR/4LyDxH80qmbywEc+g4pVFurvqYDYquoVAXEHwxVk6uYtcpj49QVA11KXlSFSbIPgpCpe19e9GAUolm/ISAZ5mV94GhwDppkMcQJeX192IM/1Nbn1tu1Qt6nYtvOnpMW+PLjBsTvPCD0QerZXpHHrDUZYe5gHQFnVqSm+DVLDws/0Z6BI7Vtsp/nbWOOjA8ApQBy065WArxYGoV/RgXIN2QQYDqR1g8eAsPFS6ws/SNMCwpoNNoCyWAdKdlSLhKYMvLrILEEdLLa/fgkLwKAGk5k4p1FFfx1mw9I0ct1cXWcBglLXglW67aKMCWk6VGowNPCipmNkFBR1vzpK/LmAc6hwrosvf+bD4tvEP2OpDalopyYgUv7Q2twvdboFALhEXb6W7A6UteWUG1uzkxZbmQPCihE2gRIAmMdV+eLJZvnakyWhwbIx5aXk4w3+AyCsANEvWy/zwLssS2UqLVW4sBVyeZ7mWedn13kKIDYZsC5pGB+ogNdgeQVYKhCGnAaeKbYYIqo61XV27WQfOH0+5Oo9wDGjUJsV6DyQNdVZB2yXqMvX0FaZdzUZAEBEXw7gUwD8GDN/5EnnTpGs6oWr1d7hen4zx1RjivVxrkDR58ttm+RYnf2LromDUMOAxapy7TXlGhiq5aD8upqNj8Toddk+qj4GeTnWl7smzPW9bTmCDIeDrDiG6IFtwPYI4M6n4YGqXIDgiC0x16N9U31oEcDZeaL73ceUASBS6YDywBlRMETvlraPiXs+bk1d5h0MAQBfAeBLAJw0asSU02QMJJt2Qn+ue4FbjNCnL9RiST9ggg1AGBu9pfAY24rQBGUR7I7V5xeARyXbccAI5OWpdi+9Ts/uuGof/zI3j6nu79qqWcYU2FvCfK2+DfyyWK9ZoABey1NcqMnGGh0QQkBw4h1mZ8+gouIloGXgKlli8czJg6FpC4ZHDhAXyDUdJW1ZbzzDa8kqYMjM30REH7ZGXsPMq6WsN+2EY4zQsb6sHpdgV6jLRT6cn3sXhlMI6YKdekaOfTAQyABIwbIAjOLlp5IRNtjRqA1xyfPYYoRw+1ofgNg41wCRGoA5LK+QBog32W9DPVZGyF0qzLY9K/RMkTgxTnLgZ+VyUZ9WO2klWb9kDGPOCpY2HEZMz4zaEo05EsAxlUNR8dUBJ+eiashdpC5vgB3uzHChENELAF4AgLtXf+B02qU3dY491izR9nG5n1GwmzEVeowZFoHVMb2AFl828pD6kZ2bzpAJdlTYFp2DoJlXQ1oOAd1vrAooAM6uo/oI2XmN/bY9Vie3f8wO2ARH95HxdkLP/vL57PJgF7rjGOFU/eyrhQKpKv6XPcU1w9P0LCTSt4f/Ivp9lWyPBQ6FGejjDoaLRAZvfBEAXvGa1w9NNK2b3QC1Yt22SzZXs5cWIzTboTpOojJE2e7LvH19hoZvxy4I+eEO8uQTgKgvJTUvtX7h4Vggdw2G1OhuBjigcPk227R1PUxFO7cZeJnHgInX+dZpffFVPQfe5TGG2LFjhm6/gqDYEG3pwNPAMPh7NoI0hb0Q6Y0XRohIJVMUoFNvfcK5xBDJg4QwRNJrdOBYYKQv1527ZXa4e5PXkNYLUy9b5zTAavRlhmOEjZd0oFb7vAegUVbKe47TtvCGmE7iEx4SzxZrR4ru995SA8HaNrakyEFbcxVSQ0Mm6NtJm75ikmPMc4z1aL19/YvrGWGJ9b4aCPWDAsDZCktwNB9GC6lln6m8dhGU8tOLL+ov954spX0bZRCgOvvMDmuZYItbEwZ2NflRhYfPLOCIWfWilsyQHRusGCIA6jMjHHqYpYDIRZn53nPyGhurIZC8dBzEmhQpvahcfsAHnuGC6QAIQHQMSNlQ7LhMW4NF0TDj7ZkrMWR3pMwHuS1QeNtp0OZjDNJXx8p29Rplie4aB9ds3mMu1hESewSQQVC2KejDAbtHViz57xyX7SOs0LzJUfYL488fwpTWGGJMZab7ns4nzwiNKVbhOb69/Mdmjv1djR3uDhQAABH9bQAfjzS3wfsAfAEzf9nJ+YzcxJYnuKnCjoIiV9t1Gi7VZjsuTDLy9MtNAHp5sUJ6QTRURG2IWkcD0SZLoibj8S8+FypgeVxf8oI5oU06ivq3+h9z+tIby1MCFPIpWQ2UfFQdVAdB7XDybVjXyde1ce2q4hozxgQQOsCDAGgLBEmZoquOH84xq8ks7eHaBoqcjgIilU1ygzlSYUMsGCKV7LBlFzRTYp2men62YlO8xhQ5a8pa3uRPO//kiX1c3uTSY8nFvgGraTCVbCsswU+ZIvxxB4K+i54vezhUvbwg/s2StyA5VSY+2i3wc15S2+68l1QYEKVjgAKBz4/LMnwzF22rbzMy+0Gqe4vxUcwsSV/YzKAlz1gyzuZgD74+1m65LYqBFup4w44zC3RtkUBRAK9LlSbdDiy3Kj9crfh3H2jNTBnQGInJ6X0tTkKKGmABxJDNJRwgsYiUHxMFSn0waCQs52ps7zTZ1eSHkqmbz+WyBMkG6xOQ86Bnx1Qt9g4UD4KcwQ/GdJRNaKGUbVTKDhlgBROw2NeyulVIDQI161MHSufCSA4ZBNkxIAMPawyXP9x+oKgH+1hBX7/KCcCiHhZs2/Zpu0LAjw1ASluiA0ktxtcZKBniILTGO1DY2QnTuoIhEUBdLEEwxLTf2Qupgc6sKjE4r3NSBTVMxkwe9ryRmFKoZIhQ+7E0cI2++TuU1WVGCYIzgDhwpDyyJG/yen2TiegNAN6MNNL1W5j5C0fS/WYA7wDwh5j5711S5mZmxxs4Tqp0LcfKmGezpR6nP+djygjNPigA2GcATMCIDH5Wti9UvIq9fOk7ygypI8cwFDzbT6o6TGrHiVeNvVfZPKkGilLQnKNg5AZ4JlQPUAphQ3kf235EiDrNiTExknpogJgxIKuZPGjG3J4ogM/scc4zPPgA2LUjA2HHCfC6EgSDOJxCiHr7BmDICmKcQVH/gRkcg3zwWMwBJJ5h/dCxPRek2oFMe0DSpAqipi6Xt8PArwY5llu7Rba4lpq8ZBJ5l+6vIE0PcLFsghmeZCuEY2o+TQGCcIwlM0Jjhy1G2FdssE9Pv6rLRbkKdiE/+AY8zECXkYcIyYmiqpKrp8efwlbo1WJlhLrvwLbMKiJn21itFiowwhHG5svvmto5ClhBT/dFyvvVieDYIwtAkiyBkjkWqnVRqKugtglQ2kIHpgHJSFlhl647/YX9CQh2XQQRZzCkcqlt4lW9KGowi6ocoywpgnUd2r6h6qqXkEwVX1vKh3ZMXU44pyho2bRthxuTFdXkJZPIA8CfAfBVAH7zGoVuAgxNuFq2jonM2wgrwLR1zsfZMUJ/rgKhV5P9QA4q4oFGl85LdkGyngalyjhybTUAjDBEA0hTlxtA0FIL5eI8Axobxt5A0cBPY+nUDpZYH1iuUdmQAqSqnb3k4Ycekw9PEbunDKcldv05gLp0pHBmwKIet4AwiLqclmzg1xkzVFBMxUZPb0Tt6y1dQIxACILzEeIZdu1jHmbK16f/4p43Lt6xvTFnyVj64pwrCINOAcOLJ5Enog8F8AcA/C7cPBjO3LSB40TOmRy52kBRgQ4GeMYQJZh6wAh7Tuf1DgT7mNU6fZmbdZWHIBC4CwLEYj/pXV3V26peSMsAKLrgGQMCODBiJ+sHTv+OgUMCATqkiw4HLgDAXn5ZEoYsqLgdcg0aHqGMKEqdY0zMJwoYRs6gmAFSQLHPbBJ63QyxN6JgiPW9LpwoKJmhgaDu82w4MEKX26CTdWWEHcm2A8UMhGV7aBv08gEMwgJ7CBDGACJKEQO9onaQ63Mz7yFdOwdlhWxtQnJtnkHX7HBgO9R8N8gKgZOqtcYk8n8VwOcyc08T83GfIttihg0Z/dJNtbwDSHIvXPZAs4FcTsdZvRsBwtEBGnokZqIqozhKzGkS3UvAE1UfsERlP8gMyf5sSwqcbGDE6Lq0riCoIJAAQIoZadQMiMiqofSYySpdSC+1gqKaCOQDUDDgPl0US4AyUWoLZZ7ZodJuh6INit4knNtBmKGGzvgPQPEhCBGBEiM0MJTiPBhGJnQkI9AE/frpdUX0MSCECJZ4KVKbsdgFQQJ87r6BCUxiPzR7YoltRVe9xu1Zyvquxg5ZPorryJJJ5D8GwN8RIPwgAG8koiMz/+/nFnp1MPSsr1jW+zzjq9ig7VN7YMEYc+gM9cgOksiJDQojpCNDVWPqGYgxA2CUl8ICjlPFbJa5AGEAAoiBAArp2Q5s3mUSZlA/rIV6PLAXIqnFBwDGCiPoLoICozuk5eHQgwi463qEENEFRhciggBiiwnVIOCXLOyvN5YU0rawpGMMxhxjDMmeFmNmkwxwLyDSK3PkTP1kyCsd8GD4YGjb8LAXidpFnZMkiJ2069KHQK/9oMyw0RbBqc1eortmADgKOPYxoI+MPqbwF99WQAQjJEtAdM8u3PUFeYaM/S6wHbrAR686p7bDtBr9yLKizdAmkQfww0iTyH96WRb/Sl0noq8A8PWXACGwATC8VApgVPFAWIGmnoPCHgiYp7mvmKBTj21by9biIiV2oo4EVkN5VgepPHX4AFP1Byy8xrzJLnzEbGOiEofAxct/1/X24isQBIyrhkAFhEhg2AlD1HcuUJDwEkaMAT2R2CMTS4yRQBIIaHY0vd6EGZqRlMXuvtAwLtIBR/aSZxsoBbkWzwQV6EI0JjhoC2kPoGTKzIRAnPrZhoio23LNydaY2DG7c9VrXHuPrd56IfLRy7s8RxyRDQHelKzlTV4yifw6JZVyVTAcvI8erLjex+WxBsC1hvEqPcnDJZwXWRnhODOsEM2YIRXMkIN+0IN184OxQi6+oC2niYXOaF/bDumRCAwcGHSIxgifPDmCiPHcoUcXIp50sgx9ZkcUESjiIGqfBwIv2tE+CitM/4CIxAQTU0zL+75DFIaYGFNmi32vSwLLPrUtqn3RPPJmRwW4rpNXNQmD2EEzBRyi2QfTB6E3ZnynjNCYoQPDiXbwbdAHZcUBxxjyB8VurTibSO5tl0A+YZjQuMg2MEMawishotkOvT06N0lK4xmgA8YteZUT91iNGWLJJPJu/x9bo8xtMMORGzoGlqPnV0A4ULmFLaagav2nfeZB9swwRkuPihWmPEWNEc9qZoZsZSk7mrQVFhcNAwAGjA1ywQidSigv+kGY4F3X40DRlofQ4xAiAhQAIjp9masaKRj2CoKOIR4pIHLA09gZWzrGgECMPiRbGvWJLaamSYY+DUMx26LYF1kD7PybPWgLLtoj9yLR7RxArcy4c7bBzoHggRJgHhxLDgKMtaTrDonpcrq/AekaDiECMYBl2RGLYyUmx4rsp5DnlRG3fglote1QVWUMQW5LoDcqjPY9vCHZBhg6ad70CtQK5tcAQK8im63QBVV7VojIoD4aEzRG2PcZBGMUD3PNXETV64I9CIQARkzDvyOAOiQbUpTA56bNUF4U3+uEYHZDc5gcYmKFXcTh0KPrIp67O6ILEc8fjjiEiOe6Iw4U8fzhPoFi6I0Z3gn9OITk4u4q93gvxjnPCO9j6uf3kiyfxgMiE572Bxw5MaVelofQoWfCse8SUwwhqdJ9QGAg9gExZPthCkNx6nJqjOJBsDhJkg8BYeAs6roE44eux10XjRESMZ6EPi27HgGMQ+gHrLC2nabcemPDgTpTk3vraJ5AOLKaRQhEybESEUHcZXVZB2YAst0wPSx2rcntggow5dqtTapjjHK/PU+4iqylJl9LNgeGKvZ81ksvXmMt1OjSVjiMKXTqsXiNh8xQ1GMWsASyumyFKgDCBmZIOzpQz8n+5VR3hqhI3cQ1AchDUHExJJUywtAJIIZotsHnugSGz3f3OISIV3QeDHvcUW9qcoesMnrRFz0yoYeowyFV9i4e0DPhjiIiCAeKBoZP4wEdCUuMeUk9I4oNL8qgBSSqctQZAvVGmyPF31TAD6qg9kBS9diFzYQQDQiVESpDDsR4Eo7GEAH3QWh8fZUZm+OmByJCBjK9fzGgkxFp+sjJNyLqO0e2fsrJRoocZ6lqsLcdjqjCvi3AW2aNtKY3+SqyTTCcUJsL9qdpK8DMabicACqKt1hHobGlqMNmKxQ22KuaHIf2QsDAMJUpPZVJGQKl/EbqPGSHGNoPfTiJC6FRIDx0iQHddT2e7444hLR8LhyFIfZ4LhxxRwkQ7qhPNjOo7awEwyhg2Asr9MuXqDdwPHJnYPhSf0gqM3UJBCmAqEMvwNWLLbangJ5gjpYiNAcYj+FUFRlo9CZRRpg9xndBmWECfwNBMRUcQvp4KCi22iCAAIoInEwD6IDIEegPBmoxZJMCM6ELBEjYTRS7Ilv9XagN3OyJBesTFsmZ+LmHa8SMgIW2l0eSLdXlDNkOGE4wPz9Mv5esJpegU6+r/c72qdoq6jH1whRjBHrHBt22gaKX4DqmB/G46ssd0gtBfQRTCsQuQy78heSlvTQ+prCTMJIuqYZdF/Hk0JtafNf1pha/6vAS7ijiFd1TA8I76nEn653YylRFboXXJFYY0INwz6om3yVQjAf0SMtjTKD4HAfcxw6/1Kd91KchzEJ/wFFU0j4yjj2jDy4Uhyl34aN2DwbfgyZUjPAgqvBB2N+dMeXkSDpQb+rxc93RwBAA7hofA5WjXHOIHSInUDzGDuiOCDEAOKS6BuBOwo+6kFAySphNDIQgoFmyw0QHrXue3G+78oo1FsxvhB36Y1cTRvP+3ZJsBwyxgO7XAFefW7MvF3fo2SK880TCaixspgWEvXQjEYdILpMdO5TuBC7/YtSWuetTINR1OGCUC7BwEVUDg3OUUEyMUEDvuXDE8+Fe1u/RgXFHiSU9oaPUuFb7RR1EYoc9Au65Q+SkDvYgdBQNIJO6HfFSPCRLqQtLUdubMiSTPkgwswRvI9h3RofF8o3lR5ipA6l9bxJzliCB5EHYsNpL1YG0xG560G5DQVTmSEDoESNZnjEkx0rvQo1yXeW6veVErQDGEHXJdnBK5R0cuzb4tWRr9TlRrgaGA5sgqm3HCkelAsfCcWIeXZgt0EJpNIyGlQ0ycOyHQBjTn01NLl8clpFOqVPWeJAeCZA8yPKkGMBEzoPtjOJenBPFvMjCCs1WKOrxc93RbITKCN+vewl3occrw1M8J2D4PN3jjo54Qr2wQlGTR3TTiCBgSLjnZCu85wPuucPzdMQ9d3iOjrgPHV6KB9xRj/uQ1OQjB/M0AyhsifcxqdAhEiIxes4BxyEoM2T4b4yFsXjgazBCVY09I9QPRCCWZTSTQSAesOOSGRMCs/VIUUdSQJfjEAF0HMWxQgiUWC9CRNA4yphiIRPuE3SIrxoU2eyj1A7ArtjhNmVnhg8vp958D6QN+5yF2DgWl/Zz+S9Ca+LQZigvkwYlW37Wu0KZ5IkPCZV/8n/A7GOqKh7EU3wIPe5Cn1Vj+ycgVJvhnTDDDlwAorFCRIT02ks6BbZotr1emFEMydmCCBxDD0Qke1wADjEKuwrJkQIUQcsdIN3UMjNkAUhrCs8KyfcegXWpqwOp69CZoOzQ5dFyInUkTqQ0Vj86WQZmAVJCpJDYJ/WIREVvnl4ZoiwBMqZYaJDKgFcCts04UUbsvrci2wDDlspb7y9U3dJemNXgISssHCfKCk0ddl3v+l7GLxRW2PeJEfZ92gbSS+LmQdFud0BiiUR9pjR9hMYgEnFahlyv8oLzn6tl8ihnW9mhS6znTpwlT8IRz4Uer+ie4o4yI3xleIrn6SmeUC/q8hHP0z0AiO0wMcR8KTE7UEBmN3zKHSICfomTzfCOevRMeI6f4CW6wx07ZtizeZ+VZdUM8b7vDEBYQIOZ0GuYkoWpqJrM1kT6AbjTXjb6QaBogeZPJLRIQ4yUESpDfD7kNmgGXFN2HN2jQ4+QgNNCAADEgzhQjhaM3REDIZrtMPVhZsQUe5MeCxn52nrhIN9romq9fv7JDdxQPztbAEKv7dyobGZw17Xz9Lbx4gEScMxd8NzBOsDae5AdEKrdkCKS/UuM5sn9W7JMHbtOe6AsvgRiCzuxkBLHiJTx3DnWo6ywQ2I+TxwzvEN2njxBVpdVOjB6ZTkgdMzopRF7RPQgBCTVuUPAPSeG2SOxpV7U446TunovzpWaIXYhIvYdOg3UNhNhbSvMdSOgYIR+KK6yn3HNEDW+MrVDujYuPOopj/wh0O4gHZI9EBwTA0SyS0YrJ1hZUZfu/mZGmx0hhYhNkaaeCW9bbNkLtwKEInuc4UNLq4G5/S8YpbMX2nHreZIdKRIk5gKvhRX2EYh9Xgey2qzFpJFbJVYsgClmdnjgwhNNri42R3NLha5UZJ1OgKzvce9YUI/nhB2+Mjw1Z8nzdI9XhZfwyvASnlCPV4aX0CHieTqKI0VAQF5wLzoww70w3ntOgHfHPSIHPOEeT7lDoIhfincIzAay6bzEoA4SqBw4IHaEoAHMekP7DqHroYNBKkPkSuejCgQ1jjBQ6m0TwE07oQ8t0g9FADtTgYBjnh4x3WKxlWqcYc/JBDAIzK6AXsdHPIoZoI+pl03+kJEbg9HZi81B5j4GbnCGUSBsybXBcQfDdWTO5qHHl6bT9XyerBTMr9oGksOEOTPBmPf7NACArlNjVw7E9XZDG/x05uKBHGdYXAxMxfI2M2NBSAyoQ0wvuIXSHAv7YAdlR7EAw2QzLCV1L6PEiECI8oQ/QY+eIp5yhycE3PMBT6hHxDGpliADmJfokMNYIvBU6nyQgQ8OwgrV+5yuP5dVNIFjiqH+C4g27YTI6ZKiz9ZGObyo8TDl2ZsQdEnpedB8rP3dDVOGqOCndTaVV0Au9ULMWgKT9T0pbH+Nz+TgedmEndDLriavKLU6K9K0IaI8rvZEABZS4/sh5xAalI6TiiGaeqx2Qw2tUZD05UrIDYeQ1kMa8LPI12yFnLroVZr5mP3Qh9l4J4IGDB+C9juWeEPzHKud8Cmep3v5H3FHEc+LCn1HEr7oiu2I0EvFerB4e4F7iuiZ8BIEJEMCQgTgl/jO+mUnZ0pyOtxzh8CcYvMC8ISPAA6I3FtIShcSmCSrhYwIQ7n5iw49CmoSZK0Ok9zXWPofhwT4d9Iud4XTyC0NDLM3WVXcgCCDcaVrjRxS+AylmMtD6HPoEAUD/HsHvqxLqTsoO1VSMc6bzPl+D6CkoVqPAc4WwPHa5V8q2wJDLG9QVTMH6R0oFvv8MqKwGeqMeBZHyOol5hxeo2+pzzYAJK5QDiHnoyzS2w9PFVWfdNPZxnxsnb3wpgLKPnhvcsQdIu6QAOcOCfw8K+xABkAdgJ5lMFgWWxkIAYR7ZoCOeMpdshlSkPVe2GqKRUysL6IDGYAfnZ3tEGIaAQYwANFbExwK+GvWtGN/VZ+VLau3WIPOky01A6Gy0sSsU0hNQI97ublRbBqdsMU76YVTsENZKkNVb7+PmfRar91brwZPSDP4eovi+pnfqmwODL2MxRg2AbDez6WaXAPTgBXWarSwQQPIRpxhGr1E8ooRMk6VOVJ0cAe2KGoth/KyuDCpIpX7aruZBv4eqHrhTUU+pl4Y6PEECQifUMSdaPN3RAJ+qaAOyooEkAQIO2nICAm3YRIvLOEJ9QADPR3xhJICqWryHfWpd0ZM2wfq0EsYSqnSZtXZxg6EAGL1IWipyLmLnbQFxDao7SLmgeBAUIFQ61qE1iAmGyEBUVmjOIiA0nGVRv8JRZ2YS0bogVFjCLNTpLr/7niTJd6CbBmsF8g2wXCqUceOeZCrpHaaFJNFRQeSCmieAbqAa66YoQ7XBIqpa16sQFXVY+9VtjqOqzu5ABiiD+2G5Yut6xpQbUyN2IDwibDBO3m575yi3FEKMgaAKMASmQFKLLEXZ8s9Ijom3Eus4j0SK+yhzCmYLdPb8ToK0nOjl0Eb0rFIyW6Ze6+gYKx+iH5jxYWtMKJlK7TgavUea7C5Y4zNoHNTXZPCDA5iHwzFWIidluXU4+gA3OIgW7d5iVPk2s6Qc+TW6ltJbT/fnJyjGkz2WgGcPa9SY72nmIdqc2Z+MYMjD22J9fZZ0niJfDhJ59RCQFU9+atTRRkRXDdnJFZ4hw4dEToi3FGXgqxlOwVcJ+YYANmv56tTQstlKTOHqWg9lJ0pcNh1OKBsXrpjU/6ap5ZatrYFkFmfAqFnjMHScPEP2o4VUHYu71a/bn+PBqa+yuRRHmzvnpSt0kZe+F8gRPQGIvo+InovEX1e4/gfJqJ3y/9fENGvv7T622SGLRllhBPrMrS/PdexkUntITZPciwGZuAaOIGk0kQGdTC7orc/Fl5rZLXdchi7Jn1xNNqCslfVg4iPmQvyIutfvcZ3lOxhabBsBbhgoOftcym8mLNHNY3MB6jXmYA7x5bukGyHQfooP6Gj2QoDp9x0VJraEw50BnaqFnvvctEcupRjuS0yKHVun1elOweECmQJrPNHpCxMe6BAeqAAHac28SxwzHNdepLztt5HiBrdBLRq37j+sEFhjDp3TpWFk8j/WwC/g5l/iog+GcCLqKYTPVVWYYZzKL6a1GB3CgEz0Bs/1mR0kdtACGTG2ALZlaSpZqEcpbrsUqasLLq0pXQKUO5V69Quhgosxb7Y1XkoM6SyQZU1dkX5JXhpuiWiNVzCDFtjE46NTJOuYTrmyVgklUxzTpZe24N4RK6Invqxn/svEJtEnpmfAtBJ5E2Y+V8w80/J5juQZtC7SC4GQ4finwzgIwB8GhF9xKX5FjLTgCc/U7XTxIuPLSzOmX4RzPM8JisAptrJvOi2qqNeVE0GxCaojhP5pf3BgFDXw8gbZWqyU5HTee2YPWVLaX2oWnq2qNutkudV5egA19Wpco60bIW533KpYo8NYuFV77rsxdJ6YFvOs8X5nXHOQ8hyNfmDiOjb3P+FKqfWJPIfOlHynwDwDy6t/hpqsqE4ABCRovj3TJ51A7LI9sdJ5Su35+UhSIFKM5i4lY7Gv4UByTF0P5NV0b95Iz31a2Y2xQ6XStmP+/SbN8bwnyU5oVnWmEQ+JST6nUhg+NsWlz4ia6jJi1CciF7QL0H/i7+wQrEvX1nj5d5ll9XFhmif+c/LkknkQUQfBeAtAN7EzD9xafXXAMNFKM7MLzLzxzDzx3SvfNUKxT680JLPec2uJtiWl0tszTaowIXSL2Sxk3m42x/XMUFfLLFq3DXaq7jOM27erQ9iMCtLVeRl7WCTyBPRE6RJ5L/OJyCi/wjAVwP4I8z8/Wtcwhpq8iIUv0iWROmf8rD5AQJrkdnbdLDjfE4AuN7psyQU0wC08l1B4kRj6CAL+uKmobiGAWtRxitM50RTlxUcIxgR0brnFWWArA5WzgKwaQGSn5tYt1u30U/k3l4Gi/GLErHcS7xjrnf2EkcEdMgDM5TXJ5NijQB7njQrL6fuSVNaYKoBBOeA5laAdqV6LJxE/i8A+A8A/A0hLccZ1XtW1gBDQ3EAP4yE4p++Qr5DGQQkn3KuJPZTNVbHbJRqL4FAnKa2hA7LbOcFS/MY0ppjQids6hFw5/dzgI3EghQ4ncJmUne8KOHNATTJEKMEXPcom62vGt9v67oHOq3TOaxK8+pIR55GAaBWLhMOVJ8X0FHv0gRzguhYhVNl6riOeu7Sui6ShxjY4IrAuKb1Zm4SeWb+kwD+5HolrgCGYyh+cc1qGYvIrwGS3XoQ8Mp9vBqMT9OE1AWPKIFckLEJZTAGCgSOQyQlBcIQhB3K37NPHSqvNpnMvQtjDm9hZ7FS3XRcwR4BvUyAntghy6UzwMC99MKVARkb+Ufccy8gyHbFad4scswzyECoblY9ZacOOGrmNAeK/tiYh1nzCdJfuDdwDJlxUmawUbrZBWkDc/ZUZo2e0wTy2o5+SC8boIGl/X1Z8tcPlg5H5j9gKYBB3caNC6r23ZzPZSsM9UxZJei6heJryTkd1HWukVExkHJRzX4JYYlEsgzZS+xeHpKRrmvbooGi288j622La4n8/iXKYEPyD3m6TcDCroFSpdWxKWzKX0R0KSwagI7WIoyp0XYWt44MOlqebvfIABKR517WetdMkR2AtJiepXPpQWncwxxHXzJPUDRVN12LtIWMPZnZcrriXhingakDQi+WD/KxVl1bqj4zxlngLavFTk6IIdysbLMHyhgLnDpG6QAToX4cmQRRDdwyBnGgNPS/2vwoSJ9ieXmsF0lIfZGLMoMwwZDBtbZF+u163eqHRTSgBRiRs5rcs/yJ5KUlAcTUZr2oyWZL4z7bDh1ljoiJETKbit2zqNvIjFNZkwePKHVQSfWqWCxoHvQsLQZ2Qs0qjaQDx9IiomOtgTl9KHT+Y0rDi1ldNB/3uGRGmK/PwN0xQb0mzxaLerMA4wIGuIQl3oQ8hNr/iLJNMBQZY3iDUT0EIAsWSRlkCDCwLECzmGlJ1V05kWQicAXQgDQog5fg8gghDfaqKjalsQ3Zj/3u64uKIY43QlowKgalKlwwMOgpg1Nk7ZgX8RQBTygmuGMZbMEapgT4Xt7Ce0488akAYlpPYPAUIYOtAWIJcF5lziyysiEis0IGBoBi6bzDRM4LAjYRGQSj1OMY0+AR9+hwx72wRQFF+SCkj0NpM1RA16lQ77mzuaM9EFrbVypyDYyMSl323tT6Op36fLMM61brLbI5MFyqFiegS4kHwOjZY3AZakIdtYDJQIsCpWlEVS2u2CHFiNp+bh7k4FRlr3qLvZCLdVf/yQusL1ZWqxdQpYd7USmzQlWV01J6Z2gBjBKkkR0m2ekitsLKg6wMMCIDrwJkzZiA7OlO57ZBr6xHOh6Aon+vHXPssFgKAzQgVhDUUauh6jKgs+DVZRrj1Y+MU/vzx8fbDEMB6i1bYSG8YF2EBEBvASBvoY5Tsi0w9CDm1u3ZHzO7KANUhihAl7aF3QUGIoG75B2GqsueGXYB6AnUBbC8KNRJNVosVcCQOlWvO5CAI3fBqc/qPEkXYqBK7t+8MLfKZOqcsRAQjjHgHmmi93scTF2+54N1x7uTgRc64z5pms5IsGG7vJhqDJh6fO8AwhgTukJFz4ypdEDUwJHKqFhVZTu0unAe41CPkIFWWh5jwCFE3McOITDuOSBwhzukiakCpYmqgsxroiNZq90wl1Uxw3hAlOuNnNr6GDuZRzrIvg7H2rni2WG68QaSngFmljgCJAMQHf+AXB2IeF1v8jVkM2A4xwj1+KJ0bl21wcKWaEyNnVqszE69ysIOo6jLIQz7HmtcodkOlSm6/Ao7IfKy9VyPgX3FqlrSg3AHcawQFUzOYu/cF0ZV5laspQKhqseZJakdLdsFVUWGT1d7j421lcsx8dfrWaGq0uYEqtql9PIG9MQWX9gbYxQvul+6NvRLbycsHSfZSeTLrz3I7G2GoibXzhQq1nMbzCkOi8DzseXa5V8omwHDUfFs0e9r/A0oi/2yk5KzBFG3nb2vC+AY0gx5AnBWrHzuiOMQOHTeZGGGygqNEXYB3GkZlJmhsNKCKMywQ33J1GFyjAH31Nl8I/fxgC5wYoTMuOceT8Up8pR6dJxYYrIJJh9wpHHPsTLCp471PEXAU2OhHe75YCpyYk+ZGSqbUjueV1sHDApZ/c9ec2licQDl6ChGHwMQonmVj9zhgDQ3yb3MuxI4ABE2jFhgNvAKHGQAW0pD/Ptrd2qx2gozM+zwUjzgJWGDxxhs2ce0jMLg1XmSARL5hisrtL+7+Xp8TLYMOFuu2wK5Lhi2gG6NPAEfRVE6XAjC4PRAxeA8UwyUnCbCEDHmTfZe5TrGEJWK3GBis/bDhaKTv/swESCNPt1RX3WdQ2Ez9BGUhefY2R59OXm9ZoneBhcGtsI6tKYl9QA/Cnp+VB4WoG05UvI1kjHDVK70SqkYoRezDyoo6gfI2Qr9tdTqfYsZNh/x+trHmB43jnG13IhcXVW/ULbBDCtQLBie9w4j4QvrORXzSz1IXHgNCSgG+TJ3sC8vhZDcBDGxxbSNZBfUHikAbDDOAAxGpBHjO3XiST502V546BIr1G0lBZ34ZORfqM5SXtEQYGFOMA+lvoRHDjgqM+TOZqbrcMiDriINT5VA6WhOFJsUfaTLnYaO3Ds7mtoL7/mAe05l9AIUmSW2ApOzxxtACR7uerxd1Bii1ZfQx5Cm1tQ5isVWGJlwRECIySYYos7dLNMXEAFRQnSI8lBeTVacVWNlhC/FO0QQXuoPuOeAp/EgrLBLjNB5lvuY6hkjIcZM/zmmvwc30mfRgZ5fL4Rpm6rxMyTbAMM5OZVBSnoNzSmYoR4HHHtr2A6JEsD1vThUuBlaA0BCakpGyLZEZoSNbnt63NYnpFQvE+vrHfD4wGD1Kqu3t9PwEiCPV9jwJgMwIKz7OHsWmOqj+ZeZ9I19YzGSLSk9sTTwJnvbobaH9VFmhsYBBrVfiv0QHNFbAL32wPHXnYOp9RqUEVpcYe0QQskQfUiN1r/AXK8WrwRkm2FkW6nHmXI1MGyyP7jtCtAGx3Xd/RPoUZp2MshLJOyRu3QedfKwdiRGqOQgUWcCA0AUZUsniPfbQHY8qAMliN0wBPBBGGJH4ENihRxImCDZetPu2Wyo1Fh1Ny/1JBd2OnTCDNNk74HzNADZKcC2DBPMUIHqqXVJyyE0T7lLrND11rCYQ+9wcOCdysxL36Mm20NLEPGSPcCJUantUOcoLgyLeo6b1Q4AjujQo7eBXutxCT1g90ieY2WEujxywNP+gKcxscL7vhNGmMJreiZExwxZ72GU580D4YARClOE31eB3VYBhwfflpuTTTFDA8gx8UDZUq0JBdnREJusRgu46lLiDTmmg0ktdgwvmNke1n+5qA+ZoyQBbhgwRLMhhswSlTmeaiv0TVPYrpSdUA6+jhU7BCOxIsRZZpjAQPPPvTCytzgHHefwmWDhPjmfVgzf/EXXQOhV5gD9GOSqR2WB1gbKCGHLew420ENEl8wEjQEqfO+Te3dd9wKMRXtDHVqpTn3MzhILo2Eq2WGtBgsAAtPP/uDYFkFxi3U6QbYDhi1V2LFD0HDCeA8uBKcOKygWzMsxRk5LFtshiFMMIgPEQYBLGCFR/uS14gyBMq5QbIV8CJkJdmmZ4w2zvdB7lmHLSi10m7UnVlW4e2c7DBzxlA+JFQo7fEKQrmga58foKabJjgDxNGcQUgB8KoEsT+Xcez7kGEJTJWnADAvv8Qjt9c4HZYV1H2wgMTsPiMQk/i/O9tMUQCgnACEK8+sPjhkCfUh9kQMzjnJtQUNuAGvPyMkWCMCY4dO+w5G75D1WL7KwwtJWGFIPTqakkavt0NkMvb2QCnAEUO+DOzZ8PIpj15LGY3tzsh0w9NICRmTAIFRq9kC11jQEBE7OQwLQiQ1RgIliUpepBzgEOYZCLWffw6UBhuz7JmsoTXBM0dRjAT7vOJlTkf21O7DwdkPtfqYG/xz8TIiUg68BGamFdCzD5FFN4SqxAEJlgX49NrrflYHVOe7OD2TQO3CLVf3HxDtXyG0rz9QJB726jJBCaEjBMXZpfpJOuvEpS42wsQ9txHCzFeZ6Gxvk5KhKywSE97GzcBr/V1thmmAxlKzQ/mRA2AqpqVuF6nTFQzHahNeRrdXnRNkmGKJhU5xgjim9Y4fiVVZmmFRjzuxQeqQw5GvdpReL2S311Yuci20xQ68mW+8TElAsbYTc6Tko2KBdywwwsgMJtRvqwKY2MAGyxzdwmj60J0KH3FOlAyeGKBPB12Em6iyxdc5AmJokd7+rJavDQxV5cD2NfR4I/VJzSGDaUJfVueUsGwGEEPVD0OXjDGGHZb0UzO/FG20gKJ5jH0/YO1ZoM9JWtkJ2ADhwnHj2t0QFHmGFm2FjtW3zBmVzYNi0G3ogdCow6zHPFm2Z1WJ0Dk27tGRJTKIe2yCuwgwZEaDOuvEBGAbAiT0wgSDEgSLqsThOYpfV5OxIyfV2pqXhNWuDuKV1yUNmWN6jfM/JHqZOkHscTBVWZviUy4k/+8rybYOZCgDqsFYaXJ273zlbIvsueFlFLvMdgmKz54Zeuk+vI9YgfbB6TldExCkAG0AQ4FJATOrxAX7Eawu8RulAqYPCAZiDygKrXYD1vTFCUZN76Z8cCRyDhdKwOk7sGUJpNzS2iBIYPZDC7ZtbxxVBaUUHChG9AcCbkQLi3sLMX1gdJzn+RgC/COCPMfN3XFLmNsBwQi0ubuwYO3Ts0QOlX3rbocThJiYZJFEXgD4mb7MxwwiWGMRU1pjNEKIWk6nHTDB2aN5sA77STmj+jDFW6Iqtx/4bdD/jUDhSAtJYfR2SM0VZEQD0KNVELwUQqpqsIOkq6oe48uIHTsihQMj1nlCT9ToH22Ky0HCbyCgYoo87VEQ0Z0pMavExBpm4ngqQ1HpB8gFSzxZlhixLzwhZl3D2TnYeZGOFhALoANtHDvxMSZgDt40ysLVAeOEk8p8M4MPl/3EA/iYunET+qmA4BnbK8Eo7YBUzaMzJg0rpSOFAoCiApwmDZKqj0nRZXWEKQGRQz4lV9qJOq3o8oiYbCCojtLCaxAzVbhhdwLW3JWag5klVOVcjs8JjDDY4ASJwH3LwdWCdCzjd5sDJj1pL3/ikq6NFWaSqytmR0pm9sHacxAZo5nxnQLC43mHabLIgdCGmUKGYGSKkS1wnNkRzvARCoJDnWh5BlIJxCyg+jV0GQ9l/7B0YMoQZqtOkZoXI4KdB/k5NLlihB8cKLOsG2pxaul59lkw//CYAb+X0cr6DiD6AiF7LzD96bqHtPklbE2NO+eWotEendpIxsDIdFaqpD3WxMBcNefH9iTtRgzXURpchgENAHq+Q8mANCoyN/AsWOMcIndTxd0U/XpTMK4OTC8K2eEEyoCtCZdyj4I/rdl+VkepQ2xp9HRZcVOP66vVmWpeuPo9Reqn9iDJH13/Y9ru/9TfWPsayrzU8l8YUZscWKhZI+S/iB2WYUnO3yvwmZaD6T/zXmUT+1InmZ+XqarKxQ6fqDuyD1fFin0s3sB1KnCGzeJS7nCgCoECIiPKFlVjCXs4hTl7lyBDtsskMkzos3e2CAGgg8MGF1XQQUBU2KAwxnYNp2yEUHLhghDnwurOBT+/lZUaAdc+zYGQkm2Fmhh2eyEAOPaL0UMksEICpxjnOUIOuDznQ2oEJkFV3lbJrXqVKG2jlbX/NdXMn9VjW9XFggtxNdCGPiK2PhwZXH4UVTjFDrbeqyb2AYo4jdCE0Yh9UWyGL2hz79DCyLI0VGkNEitRiGEM0FXnAFt3FosES6/UrywlMdY1J5JekOUmuDoZniwPNlrrtsdKr0QicBnDQNIHAkcW+KAHZYNmP5HDpZeQaydHeWRvIFVlldqyQBexao9T4fDxL1O0pcjTonWFgkwDrkCAePQfc6ZwfTGIzTICY+iunbnoalF3kWbFD7VHSmirT1+NSmWWF+tUD0tBqUJDMNkQfduPDcrwxIILaDhTHKj0bLGIhUTJEHYyh8B4DBVOkYt+EHXBk/1Iv8lVV5/XKXjL98OpTFF8PDD0DbOzzAOfZI0MGYeDMAAFkH4A8jMk5ovlVdJMYOCYbZASVDFGpJbMEyTIQZGzoEWaow3OZt9h7kI0RQhii/L1nWatYgaIXewGRPMpHsZMdOSBwHtj0GFN3vJ5SKE0a1FRmSma2Ye7TMA4pvjAFXLedKHn8Qo01zIHWxUCuTiXXoOWxuZL1OsbEs8I2OKaD0cJpUiBpR8nWSwQwdyBhguQYYf6OlTXwIT26np0kXi0uGWHsxYHSy3WJTRDKDM1OiFFbYd3tTllh0164ISZYy4rd8ZZMP/x1AP602BM/DsDPXGIvBDbCDFvMbgoo7Rw4lblKywJ69iq50W0SA2S3FIZomQOIyKNj2+e5ejFtiC7KQOZthp1jeVQyxDnwO0V87wnAdSmjPB+KDYVPIanKOuQ9Y/QpViBMeZf9jlM5VJTbDJ254AJb/ZTJ9UYBFPi0HtkIHs1hBpjZw4Ktue3cceVFAUG/rUAYBSRteC45piMglZ5klOxu5JhczigzbDdQuXl1VrhS+Qsnkf8GpLCa9yKF1nzmpeVuAgzHxJifI3VpU5gfpm2Htl0zRIYN3AA4hqjlyITxzDJdgGVUCWUgTLZDyt3uDjBnDAekeEPxIntboa7PAqS+fI5ZqYczdIkhJm+yLEm65yk7FAYYjBlGxwyD7VMxwFNGqAzR9zhxITV13+OiS56A6JQK7FVSNJewbf9N0jEzSMmXqMzpu5QjARI7hK0Pmtfqmtc1bEa712UwFBshHCPs5SEwMKSSFdo2MuvjcVuh745Xd83bnBcZq33XTRZMIs8APmvFIrczuKtXhVussMkA/THNw+3TUBsPkuZk0fhCJPZH4GyP0jpEYRdo1EnLETaY7IOUQ2a0613FBNWO6J0mPq/mc+4ZcWXTAmonReqRot3zOrENAnnu4AjPCgEdp7FHV8whDKAAwiLIWlkol0CZ6rMsSGFshJpaRR46UnSNin02IhsAyHWo7ZCFHQJDgt/01MO1dfRLmLMkrbsb6RwjBoQ1uHngQ7ldVqrVYDPHry1brNMJsl1m2ADFlu2wAMkmMyRTl9M76kDQEnO5H6QOyjL/yMWYhIaTQdiheYqdiqzL4P5unMNRNjjBXnQ9eTqlG56oxWZDtOkAki0R0IEaRFVEBCiBWSfeZL1ElXJ8xDwXsx82bDiMf6mytzzIfl/dqWd4zUOw9MdUbTYvs4Fi2kHyYUjDtNGgmS0v164GitUoNGzbyblmNkIDQrKeJuTUZWJAOv/kL57/i7RshWc5Tq4ESltkrKfI9cFwhAkqJg0Y4RRzrLYL9VjCa2rA1PAbA0dyhcqDa3WogXAAhqjGLnTg57vhWdB1zqcAx4boXPYa2KvsRYODfde8NG+wACKxzfbWsQ7UQOh1n7BEBT5Vlf1gCwBwzwfZdnMzOxulSjE0vrMptkCxuD6gBB63rtffbheJAODM+Ej7oqPcNyWejXowBFCCoLFBZGcJIzlM7ELkHzMo1urvgBVOMcPW8S3KLdRxQq4Phk6M+bX2A7mx7blz7FCPU5VewUYZYPIlmJpMOhAD5ZMoanqkWEOnLZtoHdRmWAOgqchUgZ5zorjrG28UTZAu3tsLjY1J97tjBGJIavK9MMRjDNYbI7HFFIeYBmtIAzak+EOxF1I5SnXtLPHd77wXuWaFfrQalSV9lZtNYExphCG6tmkBY1pOv6kedG09umtwbNCAsLYRpsqkMJqBnXBEPfbrM7ZCd8GFbIKR6XXesFwEhkT0BwH8DwB+HYCPZeZvW6NSKXOMM8BCLc6ACHsBKmZoLJBE1YX72urbo2kpD+PFkn/jJhvLwwwgOnVZWWEdcJ3+bPm1HSiwF04Dlb398MgBB8AcKQeKOAr7CzrmVZBg4whEd1E6h3BaV3XZ9SZBthUW3e+ciuyHx9fzS/XZ150c+FDBxmpWyNV1a1OoJGBxDSYPR42bS5khqroAGAFBlEsFOmGIxghtYIacplaRB0BYq8cVcE5fyMzxh5QtgPIFcikz/C4A/wWAv3VRLg74BuywAYoDplin1ee+YIYonCuWLSGhZ+TidM8MbZCXmplqaE2jF0nLNugZ4SgpmiFLhRonwKJj+PlRnlVlDmrvo2RbBMkMchzK8fyqsf0AFzrDoXCYaI+T0rHi0jZYYWu7dW2T193aP9iRG7icc3lMz85lFmBrQNwAwgLcKkboK+UAtmaF4xdwu7IJhnqBXASGzPweYP6r2zx3AvTsmEOnAodm1GVbKgPUZRrJVB5irh5EyqZCzqNqFzFutbqs5ft+yMYKnZ2wsh0WNkMHpKNtJS9dZkwacCyz3sloKgBwpKQGvxTl1gYgyCxuCAJIwhBjTCO36BzCAAbzCAMwNgioEyYNfJrmCclzJutgqCUrzGE1ta3TM9uaDXpWaEDoVNnRtgKcM2XIGHPCssH9sPx2nrMZpm1kEHT7slrcZoSmJkv+Q89y29tsFzQhW3CcbKb8C+XRbIbSGfsFALh79QdemBlKdRkJaGxUG24Aqj8PGUBr1TQdz4HW/pWpAYuFVRoQ2r8MrtZ9niG2pPkscbk6xp5SnKSCDzuGqD1BctC1MkRjhDOhMN5ZMjqEf+UsqfsnnyqLgHCM7DV3Tn1ttEz3ECgY2zYcG8z7ye/TdScDsOLhsTlGtVhFvrI888yQiP4JgNc0Dn0+M3/t0oKY+UUALwLAK17z+nazNVTiSnctGKWpyz4t5B3nctm01zBJfhlEwQq0ZOujUgFeYobUDKlBFVjdXB9tPBImS8YKe46ZEYZoAzSozVDn/0B3BOIBd6G3/Tp38B31Fouocwh3lYE0D9ogzDF2hWp8z2lekJ4pzx+MzApt1BdU7JCT3TPH9JWssAZC6/eLCrQulUJN9u2NIQB6lbjoaTLCCEUbMW1GWV905fjraLDCKSDcHCt81h0ozPyJD1X4QFUeO1YBYrGvOCdPK9piiMom62M2ZQBKcyMm6qdllIBIg332R94/AL/RRsAoSCaAgdkMh95l7Y5HEkqT7IeQQRwAz/LaNkOfxsccQsrN4xlSsfRB4JaPU5ELZ4nbHhPPBtV+VyY4nXkO8i5YodvXAMLWR7XYRkPVrYBuwAoH1zRd762xMML26nSqXD20ZgCIDuTGwHIAcP6Yqr/IB5Qh+vWBZmgPtCbMi1Fzk+VPlreyQbj1RcP9U5V3US9lhQyOAZEitEdF6j8bcJRK9jpXsM75gQMQjqkbGcU0ExwFWabCDiHafMtj4tlgPZ3m0abRDDZviI4faGMHerBmP61m+Y/RsULHCAsQrFXmpWDYelnnwNDtK1XidFy/IYsYYbE+HOp/tNvdHMhsBYS2Uo8z5dLQmj8A4K8B+GAAf5+I3sXMn7RKzUYLBZrqsmOMjGw/BBwLlCQFgFK5jy3oGgXLbEkxkKyCm3eIUJUGeX9xPe3M4RGZuQTlQXAykNlYTOAYOAoodUDoxUmS4hDBAfeATcCehsLvBqO5AJnVAeW8wmaTRJ6HJacPUs8hC/Te8Hw9VDJA3xRF442wuTEZO+Zvag06TfW1AYQDoKu8xqiPZyCs6zbqNLkhgKEpz9YNyKXe5K8B8DUr1SVLix3WSOYBrgK7tJ0ZorFBzYYAmz88uHzZ5a+FT8hQTZZl1dvE7y8cKDUblGtld42+Lr4HhHqTORD6CLMd3vcduhBBkQEcEDkCXcUMWWyGoQcYOFBaBm2khhSDLiBPozk2pab1jEHZQ6Y9LmAGd71OuGtVoBnY9PS+FTfEb4/duJlzjKnJseiPVZ5fY4Y57SJG6Mpr2f4WdbsbucarqKsVq71FubqaDFTM7ozjA/uhfXgrG6JLRuJUYZ+FS1CE0TTy1jwBZJV74CQZ6YNc/+fEVGXPCNMyTfYkYBVDmuxJJj2yQGvdDmkGOe2Boi95T3li9THJtkNnF6yAUGeTKweOyDGPhTrswb1eBwqHSXagVKrsGDMcbE80cgWqVJdh6yPhL/V+tNKMMMIaBGsgvDFw2W2GK8kA8GqAq/fX6rIjC/ZAqsqsDBEZe/y6bqM6XpTZqgdq8MvLOpSm0vTa76erlL487OMhBRRLRkXoAYRIYCL0ISFcOWVmZ0CnIBkFHIEEkIOJ1SupJ1hXUCztgYkJ+tnkCsdOkxV626ALo1GmGB0QajvEEVBZAnqN7WawtAOvUdveKUAIjDPCoi4j9V1yTXUZjywv6+54Dy4tddnvbwBirT4rIKbTcj8EzwTrc6HnztVNlgVDVCC0vslogqVeU1NcfewfCawz+sVURkQaTIAogVlyqAQDNgBAAJ725cjOMfTlkPjECBQTq2R1wKT03iOsAAhICA+QJ09ywKiDwCog6oxyvaj3PZONEagjw5gZQAdBaAFhDYqebfm2a6zTWLoRQG2GuLg0TRCEA4SKEc7aBHkayDarHnu5dvkXyqbA8Cx1eSEgpn3VlAEtRunPmRMPdrZN5X5qpAOW5e8vXCtt6rKwRDkWOc303MvADNozBYAwwJiG9xIQtJ4oYieM3BXssHcVHMx5jJLt1fMLe29yzQDn1ON8ze7aayBsMcEKaEbBb2x9BASLfQ2m6NlgkacDwpaMgmNr+xZkBszXEiL65QD+NwAfBuD/AfBfMvNPVWleD+CtSPHREcCLzPzmubw3BYZAA/AqplaAnu6fA0SfP9JO8zZLerMRNoDQe63LA25/pRq3HCuF88Rdb1XB7ERhgJQRxrIMZqSg6x4IgdFTUn3T+H2i0grwMRNiSEuiPFNcFC9SoFjMHAd0BXNUqfsg+yk4NbA6MuG+7wo7YWtWuTx6NDIrZJTDYyn4+e5wvtEcoIz2Cx6s52saqKTc2D/GFAflt7bbjHB0X13Xup6t6xlLcw15nDp8HoB/ysxfSESfJ9ufW6U5AvizzPwdRPT+AL6diN5eTUI/kOl+WLckteo5sp3303i6isVxDWIO2FpAWO4v8yrqMiU12ygqYwTReWJhwOOXjDzm4VFHmzFGl8NjjrFzKi8V6+V2KIDQwFZshQp4yghbdkIg19cDYcEA6zYwZjgChMX5jTaUc0k+NlSnb+4fMsFaLS6OF9ttZvoQQLgFIaBo26n/hfImAF8p618J4PfXCZj5R5n5O2T95wC8BwvmVN7W7HgiU+rw4LjPxzFC3UR1uCgHOaGPSxw9AeX+GlBb6nHLVjiWt12KsVuhgDrARJoDM7EmvVakvsgAyjmFma27WwzRmJ6fQ/ggBq48e1w7zlDFxxF6JujtgwzYoBH3vQNmpG6EOoeIBldHBUQ/KIIHt8Z4gQm4aMgCawBDddytN4/X57aYoG5XgEutPMbSt+pxAUhsghUCEs61SD6IiPxwfy9Kd90l8it0Fjxm/lEi+pDJOhF9GICPBvDOuYw3pyarXAqIk3l6ddjy04eYm0A1K2OgN3POsJJyiB0w+mPGkNLsfizor7ZDm7gICTDSlM8BTAyEFGN4CBERwBEysTon5wg5wKzFj0cIYMgMHQv1I9IM4wlLhwmUFTavtaLtHgjrNnHpmgAzBT4TIAjMA2EtS5wlo3Wp8/GyhDleS0baYkQmJ5GfGg/hlCoR0fsB+CoAn8PMPzuXfrNgCFwIiMPN9r4KPHkJEk6o4gaIwR2r1OVRsPSMECyASDLyNmd2CE7OIEKanY0AIIBCCixkZnDIwMYcC6DrZUmA2Qr9NJpj4gHRs0Qdv3BqnmG/5OgZIUrPsTLBapY5AEVgs7UXj8wvjIXsr3Xe2P4GyHmVeJEKvCIQbk3WCq2ZGg+BiP4dEb1WWOFrAfzYSLo7JCB8GzN/9ZJyr2szPIeBVTKneo6l8eanwkbYUHMH/yof3eZWmrpOU0DY2KcvWBkMnBmVDTwK2KxtNp2lsLI+hhTSEiubIiBzpgRxckz/9TwfSO2dJDoSTek1rv6xZIRWfw98funbpwabkeOFbapg0zRyTM7T21Pvd/fB35cBENa3ei0gHJHNsEIVXvi/TL4OwGfI+mcA+No6AaUBVr8MwHuY+YuXZnx9Zjih1gL5eR94mHkkjb4f1fpYGv8+LcXmMXAdtRFOqM+mDvvshBGa/qgPkdkO9c2lAQjHPsiMcfpPySIxgjLDmFTiPgZnL8QkO6z7EZcsEUXojKnO1RSbpY1wISPUD0HxQi3x0i5QmTHcN8oqB0A2o1o/MCPcHBDi0er0hQD+LhH9CQA/COAPAgAR/YcA3sLMbwTwWwH8EQDfSUTvkvP+vMzFPCrXB0NgFhDPOqdWmxVXxoDTHVtcvp7eYoCNdAOROpCCsmcesmQtgBlpqC45KQIIzplCclE6gx+zzO6WAI/SaipS1WfZb/ZSeZp7DAFxYDPUNqtshoU6bOwPQyDU0WlM9a2ZL+aB8BQQdJczUIPd+qy98VQQnDvmZIsAt1jSzX/4Yph/AsAnNPb/CIA3yvq34Ay9cxtgCCxiiE37IfJ5AxY5whIHaetmG6tHla5gfrIcsEJgGcg2Xp4CFGNqIIL2RIEACJcMEWJPFOdIz0AIAFECUgVGjUkkYMAM63Ugg6CuGzgCFfDl9WI4LqCIIRx4jR3YDYCwHgzBjrv2mrAdAg0A9McWAdhCEFx6bE5uEDD37niPKE1ABJpq86haPcMGm+BY1aHI1y0HDPFEQDSVWeurdFFAsQjErq6pKNvIltLOhBw6n3CaVJ4KYAQqMKyv2687luin1tR5hvN8w6EEQa8WG9C5pRYk1zjGBpeC4MUACCxjmovzQlO2DHBLRRWTW5ZtgeECdfkiQIRLU2+78xbVs1GvYp2G+5uiLzRkpG3Ou9WbnG2Hbl1GpLH6RwCUGJhNlUqJNcYgLItYslAg1Bnk/HKmulqVChCBEgSLYy0g9FNturao2V8TCB1ba9oOUW5fAoLNc6byax2ry5uTWwRNs4fcrmwLDIHLARH5/FHni0uzxKY3KjXgVerxyVYLLY+RJ0MHrCteSpIuniBsq8PgxTbWaMxQ2oz0XGGBFQCWanKjev5jY2CYGsD3LS4CqIE2CDqwg1wjeXCMDdug64438O76NnTLKfArjzfAb+S8KZV48vxKTgmf2TQQitxCHadke2AIXAaII2mBGVAcq8fM/oHdcGk+DmiHDLBOm0FtkFaBMmoaVa0T1yQkh0UyDioqKvN0FSAWxihFjrRLPcq0gaLsGwzTzzNAaIyPUIDbKLg0QNK3aeP8k1XhRn6DuixhbyuB282AzK3Uc0S2CYbAYkAEGg/LjArcBMUTpcUAC2A81Ubotm2p7JATy6LA4KhqsGOIhDy8l2OX2ZYoQBmzqmyqsTJGX6mFFz+Ya9gB5ejQW2MgqNtVYDW5c5ogOMcEJ8BvuL+9flGahjxrjFDlluraku2CIbAIEM85fxREF8oiu+KJYqSuKKhUl21pRLHBJjVBZAmzyQe06x4FllOMIhbnTtkN665zeX4SZJBs2P2WACF8XhgBQneZk0A4wSyH++qLbJxXp1sLCB9Cqut/FGEA/W2j4bbBELiMIer5lrB93uAUnk9T591Sl6fy57peCkTgzAar/kHqRSbmNK+LMkSts2nIAoS9VCjo2y3MUMGK0onsHSfE081dhNhU+2pQGxlyay52cBQEeQiCs0xwLRY4la6VtpLms/mMMEKVW6yzl+2DIbCYIc7aEU/IZ1GdlqQfO1aSsQyIGK4rO/T5eZUaQGHjS3ZCzup69A1TNYLaEDUzZU6Nehd2xIrFeRW5WPfXey4QurYqts8BwgmwWwKWg3SN47WcChIXgco1AWn3Jj+SnAhkow9UQxU9qQ4j5RXHp8CRG8dln6q+FmajA7qyMwNqCA0hdbuzIkVFFRZIgawclhCbQf0G9c2gOdssLTCsvwpzAAhM2wYlj0kQHAHAk1lgna6xfWqozOgz+FCM8MpYtDPDx5QTbIiLvc1z4DhlP1vTdugB0S3thadsN9RqpRFtODM7ZFUajhlmeK0uypC0pqnDpJNAMQWCbrsFdiWwzThJgAFQlnlMAOEpwHYhE2yes+C8WwbCq9gpV5bbAkPgZEC005beqAUA1wTBimUtAsoag2r1TgdtlQeNCcUUp8muSMKe2E4lgrFHqMdY0VQK5BoAT2jXuv4ZlFpsMV/PQB1GPj7nKT4JBBtAdxELHDunIeewwcnzlsgGQIgA0O5AuYKc8eJe6kGu8xnU56RMhiTMh9l4dghUbFBU51JthgzYwAYiA1DUQuREC6cpbJ+NxhljhhgBv2K5EAThjqParoEVuC0QXHD+rQOhCu02wyvJOUwG54PiQ4TTpIxlWYGOqsEZJf1+WVf1mJUxZjY4AEU5oQBGXy5QxhueUvcChNp9hU8CQX9OM495ECyO12mm0o2ln5CrsMGtib9XNyq3C4bAJGuZk1XArc6jlSejYHtFcr/PAYKqzGYXVBXYFcN6jtgFWR0RFRvUwGrNl6yeVOwfVGxKqhPmvbrAgCVW1zxgfq28TmWCU2BYpx1JMyaXMMHZ85fI5oCH8bL2JhPRFwH4vQCeAvg3AD6TmX96hXqdWBFs8OGYEQHJwbpuAxlEZcWTxPo7UHejy8dz44x9O2iQ6cIvxRwjc0yuqe4Wady5Z7LBs0NjGmmm5OpAuFG59eu6dNj/twP4SGb+KADfD+DPXV6lM4Xc/7HKOvW0BhMZgERjHzFkSCsZtj5C+vmi3I6yzW47AtQTKBIoTa6ctnsC9Uh/S5f/iO2/T1Ocp+X4Mmw5rJ/VkV0+sdqnbFCvm8t2Ktpn5JgHSvJti2GauXs3OL+6l0vU4lUY4VZBp5y3dvx/gRDRLyeitxPR/y3LD5xI2xHRvyKir1+S90VgyMz/mJmPsvkOAK+7JL9nVha8JM19rZe1EciMxktueD0GHJrXIAawTFf/24BDBXNrpSvq45YtNjfLBiuAK47V63UZI2mmZJYJvozZoAkD1POi/4Wik8h/OIB/Kttj8tlIcyYvkjUnhPrjAP7BivmdL1T91853TfEAMMN4lC1RFNalrNAf9wyrYmKeRZbMzjG56Bhd699K4xiisdEaRD1TbdXTXRu4fX2TTBDl+oDJjX1cRmQNJujzuVi2zAhVRj+WOKntZ+RNmJlEHgCI6HUA/nMAb1ma8azNcGoOU2b+Wknz+QCOAN42kc8LAF4AgLtXjzLbh5E1bIpzILgQJFuOlEXCyNfhbXuVLbGuzuCyyR27tE1qBjZ2bMD4xvZPM8Hi2FQ96jQnXucseC3M75lng5WcEFrzGJPI/1UA/x2A919aqVkwnJrDFACI6DMAfAqAT2Aebw252BcB4BWvef3jPyY1AC2pwQUscAr0BscUFEaq1tpPBo46eINmjKKvc04neRShNFVBHmjnZAaUms6M1vGVHCMP5hk+Mb/VAfCWAHU5GD7oJPJE9CkAfoyZv52IPn5ppS71Jr8BwOcC+B3M/IuX5PXo8hiOFi+nAM3IuVQB3XB/Zop6Wi0tp/XZdarzHgOkJSBY57kVILwmGN0UEKKcwuGSrC6fRP63Avh9RPRGAM8DeDUR/S/M/F9NlXupzfBLkGjo24noXUT0pRfm90zJ1Es6qu61bGJTx6r9anOr7W5me6s9tv7f2jf252F6q0/DKzyo28h1zF1nyy5Yt9+S+7LIHngCG1zNNujrcENCYBAv+18os5PIM/OfY+bXMfOHAfhUAP9sDgiBC5khM//qS85/ZuRMxjdnPyyYoJbj1V+035kyeJvc/px6lXdtETuk9rElLO+xmeCJjfJgNsEbA0KT+ChzhS6ZRP4sue0eKLcoS9RlB34FYHr12B33p3ihqixGBUz121xvNuo5DSYjPVNa+S8BwKl0rbQjsrYqvINgQ1ZUkyeLWTCJfLX/GwF845K8dzC8hjiQmmSHNQtssUS3OUhTyaAYKXjK0bNUFsXyLQW26tgzD4LAbQOhyD5Qwy6TsiSUZgkgajqgAYrI24WDZC6kqMr3YlkAiLPA9nJigiq3jSFZdjDcZU6aYFepsAXQ1eKfsTGmKMdabLGVTbHjUs/6GBM9kS02z7mSPXA2vzXktrGjEt7BcJcLpGE/nGWSUyr2CFscY4Bcp1tBFgFgY9/i85aWeUY+i/O7VG4bM9rC2GfH2wWLnCKjzG8EEJtp/Tmatj50Qm+b2sFysYyVu8TrPJdHQ27CM+zltrFiVnab4S6XyyWgtETdnlKH6+f3kh4oC9NcwgJHzz8zr0X57bJMdjDc5RQZVYMbgOVf0lnVuSik/YIvelTn7IhbteFtFQBvGx+WCyNNQnbDsoPhFWSp93jxOa08MMxn1GY4lccZ8uiOjDVZ5Zpy29hwouwOlF1UTlR1ZwERw/wWM8U6n0Hhw/weRB4KUM/Ie2eCjyA7GO5yrpziOW6dC5zAFut8i8zOyGMuzzNlzRFkFue3ltw2FlwmDKB/lO54DyY7GK4pZzhCFgGiJW6fD5wJiq0yHlkWg9VWmSDw8gZBE4bNSnajsoPhBmQxoC1gipb0sYcoO0GeCQAEdhCsZVeTdynkgjCZRU6SGabo87JTrgyMJ4PUDoK3J7s3eZemXAiIls0DAOMgixWB8mxQOvO8XRXemOzMcJdNyFx84IhcNeD4FkAQ2IFwqexguEtTVujqdpYdcCac5iqywjuyA+DGhRno+2vX4iJZc6rQXWpZ+YW6CBDY/R9DVipv9eH0l8gOhOfJhiaRJ6IPIKK/R0TfS0TvIaL/dC7vHQwfWh4AEC+ec4Mf4X+mrHJ9p8pKdX/ZyyOAIZZPIv9mAP+QmX8tgF+PBZPJ72D4GPKAL9izMsjAVRggsIPfasLJm7zkf5m8CTOTyBPRqwH8dgBfBgDM/JSZf3ou4x0MH0sekHXUbGrrAHn1+u4scH1hgDku+kMmkXf/F04oqZhEHkBrEvlfBeDfA/ifiehfEdFbiOhVcxnvDpRnVLYUZwhsCKC3Uo9nUZZ3x3vQSeSRcO03AvgzzPxOInozkjr938+dtMtjypkhMJfIHBCtAZabAbuWbLluz4owrzZV6AqTyL8PwPuY+Z2y/fcwbls02dXka8mG1LSW2nrqf5OyoTZ+WcjjOFCWTCL//wH4ISL6NbLrEwB8z1zGOzO8tjCuGwP4LMoOgFcR3tYk8n8GwNuI6AmAHwDwmXMZ72C4BbmC6vzMyQ6AV5ZVWN98KQsnkWfmdwEYtUu2ZAfDLckOiqfLDoLbEMY+UMMuDyD+mdqBcSi3/c49k8IA+Ma7410EhkT0l5CCICOSV+ePCV3dZS3ZbYpZdhDcrjDj1gd3vdSb/EXM/FHM/BsAfD2Av3B5lXYZyIrd3W5GXo7XfOPCkRf9tyoXMUNm/lm3+Srsj+wuu7x85caZIfHlo0j8ZQB/FMDPAPidzPzvR9K9AEC73XwkgO+6qOB15YMA/Pi1K+Fka/UBtlenvT7T8muY+f0fqzAi+odIbbBEfpyZ3/CQ9TlHZsFwqmsMM3+tS/fnADzPzF8wWyjRt011x3ls2eszL1ur016fadlafW5BZtXkqa4xlfyvAP4+gFkw3GWXXXbZmlzkQCGiD3ebvw/A915WnV122WWX68ilcYZfKP3/IoD/F8CfWnjeixeWu7bs9ZmXrdVpr8+0bK0+m5eLHSi77LLLLs+C7KPW7LLLLrtgB8NddtllFwBXBEMi+ktE9G4iehcR/WMZgudqQkRfJDNpvZuIvoaIPuDK9fmDRPTdRBSJ6GohEkT0BiL6PiJ6LxHNDpD5CPX5ciL6MSLaRJwqEb2eiP65zMD23UT02Veuz/NE9C+J6F9Lff7iNetzS3I1myERvVp7sBDRfw3gI5h5qQPmIerzewD8M2Y+EtFfAQBm/twr1ufXITmm/haA/5aZv+0KdegAfD+A3400evC3Avg0Zp4dKPMB6/TbAfw8gLcy80deqx6uPq8F8Fpm/g4ien8A3w7g91+rjYiIALyKmX+eiO4AfAuAz2bmd1yjPrckV2OGW+vKx8z/mJmPsvkOAK+7cn3ew8zfd806APhYAO9l5h9g5qcA/g7SwBxXE2b+JgA/ec06eGHmH2Xm75D1n0OakvJDr1gfZuafl807+e9e0gVyVZshEf1lIvohAH8Y2xrk4Y8D+AfXrsQG5EMB/JDbfh+u+KJvXYjowwB8NIB3ziR96Hp0RPQupJGk3u7mAtllQh4UDInonxDRdzX+bwIAZv58Zn49gLcB+NMPWZcl9ZE0nw/gKHW6en2uLK3Bw3aW0RAiej8AXwXgcyqt59GFmXsZSep1AD6WiK5uTrgFedDBXbfWlW+uPkT0GQA+BcAn8CMYU09on2vJ+wC83m2/DsA+XmUlYpv7KgBvY+avvnZ9VJj5p4noGwG8AdsaGGWTck1v8qa68hHRGwB8LoDfx8y/eM26bEi+FcCHE9GvlIl1PhVpdrJdRMRh8WUA3sPMX7yB+nywRkIQ0SsAfCL2brKL5Jre5K8CUHTlY+YfvkplUn3eC+A5AD8hu95xZe/2HwDw1wB8MICfBvAuZv6kK9TjjQD+KoAOwJcz819+7DpU9fnbAD4eabiofwfgC5j5y65Yn98G4JsBfCfSswwAf56Zv+FK9fkoAF+JdL8CgL/LzP/jNepya7J3x9tll112wd4DZZdddtkFwA6Gu+yyyy4AdjDcZZdddgGwg+Euu+yyC4AdDHfZZZddAOxguMsuu+wCYAfDXXbZZRcAwP8P7/3m8X/eISYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,4))\n",
    "extent = [-3,+3,-3,+3]\n",
    "plt.imshow(Z100, extent=extent)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cffa4a30",
   "metadata": {},
   "source": [
    "### 4. Colormap \n",
    "\n",
    "The second choice matplotlib made concerns colors. Our arrays `Z5`, `Z10` and `Z25` are really two-dimensional scalar arrays and the question is thus, how do we map a scalar to a color? To do that, matplotlib uses what is called a colormap that map a normalized value to a given color. The default colormap is called \"viridis\" but there are [plenty of others](https://matplotlib.org/stable/tutorials/colors/colormaps.html). Let's try \"RdYlBu\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fea457c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f32fdc3da90>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,4))\n",
    "extent = [-3,+3,-3,+3]\n",
    "plt.imshow(Z100, extent=extent, cmap=\"RdYlBu\")\n",
    "plt.colorbar() # displays the colorbar on the right, with the corresponding numerical mapping"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2917ccb",
   "metadata": {},
   "source": [
    "### 5. Interpolation \n",
    "\n",
    "On important implicit choice when displaying image is the interpolation methods between pixels composing the output. The default method is to use the nearest filter which results in pixelated images. This is a sane default for scientific visualization. However, in some specific case, you might want to use a smoother interpolation method and you can do so by providing the name to method among [those availables](https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html?highlight=interpolation). Let's see the effect of the bicubic method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a220b34d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f32fda3a2b0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,4))\n",
    "\n",
    "extent = [-50,+50,-50,+50]\n",
    "cmap = \"RdYlBu\"\n",
    "interpolation = \"bicubic\"\n",
    "\n",
    "ax = plt.subplot(1,3,1);\n",
    "im = ax.imshow(Z25, extent=extent, cmap=cmap) # default interpolation is 'none'\n",
    "ax = plt.subplot(1,3,2);\n",
    "ax.imshow(Z25, extent=extent, cmap=cmap, interpolation=interpolation)\n",
    "ax = plt.subplot(1,3,3); \n",
    "ax.imshow(Z100, extent=extent, cmap=cmap)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c617923",
   "metadata": {},
   "source": [
    "### 6. Adding a colorbar and setting max and min for the color mapping \n",
    "\n",
    "Since we are using a colormap we need to show how scalar values are mapped to colors and for this we need to add a colorbar. We do this with the function `plt.colorbar()`, together with gridspec so to make room for the colorbar on the right. \n",
    "\n",
    "Finally, we can explicitely tell matplotlib what is the minimum and maximum values that will be mapped to the colormap. These are the argumetns `vmin` and `vmax` in `imshow`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e2b63385",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f32fdb89e80>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.gridspec import GridSpec\n",
    "\n",
    "fig = plt.figure(figsize=(5,4))\n",
    "G = GridSpec(1, 2, width_ratios=(20, 1))\n",
    "\n",
    "extent = [-50,+50,-50,+50]\n",
    "cmap = \"RdYlBu\"\n",
    "interpolation = \"bicubic\"\n",
    "vmin, vmax = -1, 1\n",
    "\n",
    "ax = plt.subplot(G[0], aspect=1);\n",
    "I = ax.imshow(Z25, extent=extent, interpolation=interpolation,\n",
    "              cmap=cmap,  vmin=vmin, vmax=vmax)\n",
    "plt.colorbar(I, cax=plt.subplot(G[1], aspect=10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "065a2241",
   "metadata": {},
   "source": [
    "### 7. Contour\n",
    "\n",
    "To finish our plot, let's add some contour levels using the [contour](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html) function. Since we have several arrays showing the same data with different resolution ( `Z5`, `Z10`, `Z25`, `Z50` and `Z100` ), we can use the highest resolution to compute the contours. This will result in much smoother curves. Note that we need to vertically re-orient the contour (using the `origin` argument) such that it matches the orientation of the image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "89417ca3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f32fd5706a0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(5,4))\n",
    "G = GridSpec(1, 2, width_ratios=(20, 1))\n",
    "\n",
    "extent = [-50,+50,-50,+50]\n",
    "cmap = \"RdYlBu\"\n",
    "interpolation = \"bicubic\"\n",
    "vmin, vmax = -1, 1\n",
    "\n",
    "ax = plt.subplot(G[0], aspect=1);\n",
    "I = ax.imshow(Z25, extent=extent, interpolation=interpolation,\n",
    "              cmap=cmap,  vmin=vmin, vmax=vmax)\n",
    "C = ax.contour(Z100, levels=10, extent=extent, origin=\"upper\",\n",
    "               colors=\"black\", linewidths=1)\n",
    "    \n",
    "plt.colorbar(I, cax=plt.subplot(G[1], aspect=20))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b30fc8",
   "metadata": {},
   "source": [
    "## Exercise A\n",
    "\n",
    "In this exercise we create an image and update it iteratively with new data points. We start with a grid full of zeros.\n",
    "\n",
    "- Write code that fills the template below. On each iteration you should update the matrix Z by adding +1 at a random location in the matrix (Hint: use `np.random.randint()` to get random integers)\n",
    "\n",
    "- Try different interpolation methods and see what happens.\n",
    "\n",
    "- Try different [colormaps](https://matplotlib.org/stable/tutorials/colors/colormaps.html). Which kind of colormap is appropiate and which not?\n",
    "\n",
    "\n",
    "- Now instead of adding always one, on each iteration randomly pick whether you add 1 or substract 1. Which color map does make sense for this case?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9d4cfd8b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"360\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# here we come back to 'notebook' mode, where we need to do plt.show() to show the figure\n",
    "%matplotlib notebook \n",
    "\n",
    "data_size = 25\n",
    "Z = np.zeros((data_size, data_size))\n",
    "\n",
    "fig = plt.figure(figsize=(5,4))\n",
    "ax = plt.subplot(G[0], aspect=1);\n",
    "fig.show()\n",
    "\n",
    "d = data_size / 2\n",
    "extent = [-d, +d, -d, +d]\n",
    "G = GridSpec(1, 2, width_ratios=(20, 1))\n",
    "\n",
    "for i in range(20):\n",
    "    \n",
    "    # your code here!\n",
    "    a, b = np.random.randint(data_size, size=2)\n",
    "    Z[a, b] = Z[a, b] + 1\n",
    "    I = ax.imshow(Z, extent=extent, interpolation=\"bicubic\", cmap=\"Reds\",  vmin=0, vmax=1)\n",
    "    plt.colorbar(I, cax=plt.subplot(G[1], aspect=20))\n",
    "    # end of your code here\n",
    "    \n",
    "    fig.canvas.draw() \n",
    "    plt.pause(0.25)\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "590ad5a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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LT1wjhYoKqDLK+fFyw9+drBlTn/mVaMAHXyuPA4cyaA8XmTe55jUgx5qHB/I7nGJ913Pm+bvPoCjCLEP6Sxgp4ylgJ736tHXD7FAYQG9ekG8+tDnhbwFc8y9n7hFAR1srZwOzB3QBK8HaAPmTjv5WymOe/8331MI5lIP1uWKBXUWrBXQOc26nmYvLVBUQFeO3D8++sO/EmyK73/kxQroYGvldGCugBY4x10kHnO3DQPlroO0/M+NP4ExgRwRziVzD/GoBdYZ4Q71oHNaBHqamVqgsIA+eiI+/phfD37v//TBFyqgg62V04G5Adr3mgljhjMI507L3vNvHQdrPxZNDzoqWyATzOWa+91Bmn8bEO5QQOe0CPQ0M7VAUQFdPXZRfPZjfyP4vX/vfb+ogA62Vk4H5gpo50GXGNJwcC51mkC7iVK3A/NYPGkZvwNwLGCu1GAel6vWoy47QPthD/G+c7KBnkYtMEsLFBbQZ10cn/v4/z34rX/33c9RQAdbK6cDcwG0eMQmnNG1QO60LJD5uL1jH7eaiJvbQLeDmMA2nnMZpVoDqDowV+oAIV1pWE+aj134w7xlL9ShHnROi0BPM1MLFBbQxy+Jz3viK4Lf+//7zn+jgA62Vk4H5gZoz3s2YY32NkqEc2sLpfY24u1N+7Ozhbjdcqy1oY1SfQGlxqL5MWCuLiCuNmy4o1wd6EUroHNaBDmfpjtkYqJDkRvVb9CiArp29qXx+T/+28Gz/+23P10BHWytnA7ME9BJnJnec2sTpdaOuY+31hFvrqG7tWE86HinV85fqjeMBx0tLKG0uILSwjLi6iLi2oKFNUMdzOyQWLR60DnNfH6nSQN52Adnms+HAdhFBvSF//q1wQvhf7z5yQroYGsNPvDvAawB6ABoj6qdzw3QJubsYs8MabS2rfe8vY7u+n3obpxBvHEGXQLahDm61nsWODeWEK0cRbS4irhBSFsvOpaQhwI6h6WR/ykEzgLl5Hdm7qRuJWboABAo+7A+yKAuKqDr51wWn3jK7wQviv/+pp9QQAdbazigKWjy/ZBz5Q1oCW9EzS3rPW+eQXftvh6ktzfR3d5G3O2iFEWIGg0T2oiWVhEtHzWQLi2uoltbQlxb7A9z+BkdADTEETLDszkmC8xxHENKkTL4DMdnsMCfsE6D+qBCurCAPvey+JKn/17wArnrD/+VAjrYWvsB0M11xGv3WkCv3YsOPenNTbS3mwmgK40ayssriBZXEK0cQ3TkOEpLq4hry+jWFgAX5jDZHAroHJbH9Kfw4czHAmaT7h7H5oPT/r33Wia9nfVIxoMuGVj7oBZv+iBCuqiAbtzv8viyn/794AXxjd/7MQV0sLUGH/h3rMp0DiY7GKT1WvueOTMPemcDJQJ6/TQ6p++2kKY3nQHoaHERZeM9H7Me9MoxBXQOC2FWpzDwTSAco+PAzPtOdzSgy5H1nsulEsqEtvOmLbxnNer5nbeogF447/L4ip9li8Cw2//1H39UAR1mqqFHXQDgHwGcC+BTrgfYbalnPBcAf3DixImb77qLnWfGu/VdR0Znw8ag+0IcBDTjzgbQ96LrNgqNB93polSOQA+aG4Qm/uwgvd886FkwpajhG/GeCWN6zgbKvO8CrS5/t499r9r3lstRD8zVMgF98CFdZEBf9Swqfobdvv7bT1BAh5kq+KiXuyaOvzvoGTPxoDtNlJqbiJobwPaG8aBNFgdhvb1hsjgE0MziiLhByBi0gzQWVtDlJmGBY9CzgPKgOSoSrMV7pqfMeHO7G6PVidF2gObvAmk+llslKkHgzMfVqIRKBPiQpmd9EL3oogJ68fwr4mt+/vXBMPnPr3i8AjrYWtkHLvFbosvi4GN60MxE//jMAU2NDVYJSpFKk2l2W4haW+is3Yt4Y83Cmal2zIPudmyRSqWKEj1oyeJYWrVwdoA2aXYsVilQFsdewlnmrQiQ9r1nC+EemJudGPwhlLfaHQNtetTdbozIAZkwblTKBs61soU07wlqwpnedC9OPeWVUKCnFxbQF1wRX/+8NwZb6qu3/EsFdLC1sg+8FMCH3L8qAN4N4FXDzpmbBy2AdmEOFqdIHjS9aIY3DJyZZtduAp0OUCaga7ZIxUEajSWbB12tFzIPeiw4D9O/lkkJaE5QFEj7sWfxlAXMvN/pxNhsdrDZ6mC700Wr0zWbhYRutRyhUY5Qr0RYqVcMnBsVAbSFNePRB9GLLiqgly64Mr7hl94UjJwvv+xfKKCDrZXTgXkCmjKjSRyaYQ7mQjMnmo0pWUHocqDjVjMZfalaM7nQpty77opTKvXCVhKOBHRWo4Jhc7WPGhT44Q3Gnntw7mK7E2N9p4O1ZtsAeqvVRavbNV42oVuNLJyXa2Ws1CpYqpVRr5QMtMWLNpA+gGGOwgL6/lfGJ1/ARidhtzt+4zEK6DBT5XdULoDmcGSj0Ok/m81CQtrT4uDfCGfqcCSFKgxzGB0OlnRTg4Oecy3Jfx5URWheMj8zBJ0puEmB2IP5vkO86L4GBXxOwZsU+IBm+MIAuhtjpx1js9XF6Z021vkjXnSbHnRs0uoY3lislhNAH2lUzO/0ousMd5hQR2/T8CBlcxQV0MsXXhk/8IVM9Aq73faiRyugw0yV31G5AjqtZkcQC6QNlJ3sqOhGO4U6E1+mcl1U7sHZCCkVS81uIKBTHWT6usf4DQz8afPV+dLa1z6sU1O91x9K/ssT0JK1wRCHeNBb7a6B8untdh+kt1qdxINeqJYTQBPOR+pVLNfLWKhEfaEOyepQQOd3jQ8608qJq+IfeNFbg1/os7/ySAV0sLVyOjBXQIvn6EIdFsgpMLMc3HiWsRXn583X2nCg3gXnDGjtNawyAZ0FZ9dBJukek4a014Qg6Sbjd5IZ4knv9XseBejtNjcFuya8cc92C2e22ybMsbbTxlazYzYN6Rkv1MomrLFcI5wrOLZQxWq9ggV60A7S6kHndFEHnmb1oqviH3zJ2wOPBj75Sw9XQAdbK6cDcwO097XehDsE0mbzsGNDIP6PjN+HFb1m8ap9HegBHuVew2ogoLPer2la4ORX3YdS0gqM71GA7H17MO2/huhfGxPnNO+TnCbLg84C9OmdFjaanbEAzTg0f9SDnmRmJnvOkYuujh/xsncEP/mjz/shBXSwtXI6MBTQIzfHZDyDvu57XqTxLN0t8aIF1AX+ur/LBukWX64xgS3aYaaK9w3CC+uIvrXRuyaoy7UkxFO0sM4oD5phDglx3LvVMmEOiUH7IY5aJTIhDnrPGuLI6eKd8jRHL746fsxv/UnwWT747B8MAfTjAbA8sQzgbQBek3qBRwH4MABWPPP2QZcKHDyOxLcb+xn78AmjAB0M5ixAe151slnmd/aW50RM3cbuZrEDPOfkpfbY3oMAncisSsyd2SvSsMA0LaA33d+kABXX3ks0rwu6MZoFaFYJ+puEW60Y2227SXh6u5UAeqfdNUUr9IptGINZHDbEoZuEe7x4M17urEuujh/3798VPJD3/OyDRwGaUP4WgMcC+AcAfwPgJwF803sRAvpFAJ4Y/MIDDhybTdO+4DyePwzQYxsgnbEQmnI2KNVsSI7wPL7q7ypvT2+Kus4xJv+bqYWSVsj7QamFNUqqsklBPcliGeZFz+N9y7pMZ3GwepAeNHOemcnBsAbjz+JBp/Og6UEvVi2kmQvNDA5Ns5vHVW9f8/gDromf+B/+LHgA7/ypm0cB+qEAWL38OHfSl7r7Vyugg83cf+AgQAfDeRiUR40pC8CBhRvzAFUWoPuaFEhxjsn73jTiUL3inFT1JHO/WZyzuAoQ0gUuzkkDmqBOF6owFk2vmpuDzIOm9yzaHPSgmeNML9pCmul1Nv9ZfopYqDKsM0zW0h6UeVLUNLuzL70mftKrWcsWdnvr006NAvSTATDE8Rx3xp8B8BAAz08B+gPOw6ZmEL3pb4SNoP+oYEZNcvKiPGdiQPuxZnkzwyrnhhVkBELZt1mhAC3l7QS06GCvn7ZNCqh/7SooZfymMIcaJJRYpQYJy9upf80c8Nqi7SJTsPJ2jt2vJPRLvW26HYFsBZO22w7QHavLYQBtSrttsQoLVGqmzDsyZd5mc7BApd5prWt578OgPKz5QFEBfc6l18ZPfe17glH0xiff9O2UzjyVMn21zKc479kH9IOdYJu8ziqXktMIeoKLV18RPAjvQAV0ltXSYGaWRtI0VuTaU0+cMMY8aNLmAWeOZZCCn9kUZHiDAlGtLWBrzTYooMTqFsvczwDtFuJOB6UyG+FW96VAlA9pVghKTnRaLMlocMQwpd5yY6m3SIxWI6BC75kVhl7mxryrCAc1ITDvO2Mx2p0TK5fKm+iIyKHiURcV0Odedm38U7/33mA2/v6/umGUBx0S4ki/HjtABTcY8Z98aAE9dkGGxGIz2mgkeb6mM3dkNwLNqo6CKucS5zx4Gc3uwLEkVimvalp9WRW/gyKxmqUFTS+ZkCawTejDKd1ZAX8HLifQTwjbfGeruyGhjXlrQo9qQsBVlXYMrPKeXRXDGhAUFdDnXX5d/Ow/fH/wBfOqJ1w7CtDU/+Em4Y8A+K7bJHxGKoRxHoB/cuakd/3nAC6eJINUAe1PXTp9zhVjmHzndJ5z38ccwVwxMDawNnm/DtReDnR6lczLSx62WoMBHdBFhk0KGH8uHzlumxQsH7FNCupLhe8iMwjSdJhZ2m21oul19mYxguuiIkL9TheaS2LeKnZZcPabEPidYtIeHAFNGVWuDdOIwGvnJevlEQ9/GO68887C8eSCK66Ln/dGhoPDbrf8y6tHAZonYtjidS7NjknWFGv7BfcKFP5gPPp/c/1StwD8GoAvho2g/6jCGXSSNzHqOVkx6KCCDFOEwdrfpi1KYWEG837TOc6DijLSlXOpOPS+BnSqSUFnfW1Xm6/MLjLVxX0DaPEo/ZZXWd1URIsj8TK9tlfpbioSJhi1ZkP/n7WOs9bVsA8c0bbmvb9paMIZ5ltBT+fab0bgfyMoKqDvf+X18fP/iGnIYbeXPubKEECHnSyHoxTQYsR0QYZ0TqHOhom/MkPB6WwQ1HKj1+xXynHjS4oyuBFGTzpD5zl52RwmMc9TBHnQWY1y2ayg2eo1yq1VUUq6mK/YPozsZk5A75M+jGmv0wDbNY2Vz2jCWW7pUIAFdk//eRI4T3OBpruQ+x1iTPaJp3XtQ7r3fug1M0RjPWcJ26Rj6jz+kQX1oC+86vr4V9/6F8GXyK8/8nIFdLC1cjowyIOWGLN4yemCDGYviFKdJ8ZPAFPvGUatzirVmewEV5xR5Kq5LPMOTLMTxT4WqLS2UNpe73UxN11kNo3UatKkoMYuMoumOa50M0edcKYWNvOi6z2hqAI3yvU9SulRmHy4ZrX1Tm2oGUi7J4wjjjQNmP15TfoqugwVgtjvECOZKVYYivrWvawU7nszK4VgtnKpgxsQFBXQJ66+Pn7xOz4STJIX/NClCuhga+V04EhAJxkatuegLWNumUKMvoIMdkuRggypFmS3FOo9E0aNRVuQkdJ6LpKc6CiTDs2DdrrX0qSAvRhjNirgPe2ys937YlG3+tfGi15aRWlx2eZB15wedkHT7AbZJw3qcew4Dph9oI96jV3/91NAXTjNB7RkpTBlUKokd1wBDnO6mdtt9K2d683NTWlCsFjrdYlh8Y3AWkI4j3pEMWPQF119Q/ybf/KXwab8hR+8RAEdbK2cDgwCtHjQojVh4LxtU8r8ggx6itItheNzYvxsCksYjQMi85U5p/eY12mGVRJKs1xpUkDbSP6zbfPlNSlgFxlCmoBeWLItvuSDix9iIruasYlaNJukbRtS3DEulP3XCPKeRxVPeZlEtKd0I09rXLNDDAtv1pttU8pOUMv7Y5pg0iHGa0BgCm+cVy253UUF9MXX3BD/1rs+Gnx5PPsHLlZAB1srpwNDAd1XMdfa3FWQkbS0Yr4vQU4hIOb70lOUr/KLKwhtCLsvAM1Bum7myTcL00lmx+lgs9x7x3rQ6SYF7CBTq9vw25zFAAAgAElEQVTGBH6pt4nNOx1shjeM2ygZt8X70MppGQadZiScM3L0B57Y+/CT9EA2HzCl656Eql+6bqsjbUY0wxusiFyoRqZDDLVF+LjO1l5eKy/O3KMe+XB8vYBZHJdcc0P8ij/7WJDtedC/ufmEAjrYWjkdOBagUw1hk1gr08qY78vSZtexm8OLZDNsaQXR8lFEK8cMrNNf500HlX3gLe4ChL95KhunomQnthLZUQLa3STdMInFj7F5WnQPOqdlmXmaoPx888meKp5Ke9R+Tn5UQQeRiT0T0AJn3lP4SZoQMMTBH4ZCeGMVpJStr5oGBJU+fWtpisswR1EBfem1N8avfs9fB0/Z0266vwI62Fo5HTg2oL2KuXjDVcu5qjnGXFsbW4hdBVmlUYPk+zLXlz/llWN2M6zO0uaGbXW1nwEtXjQh4MmLJlkt8rdUDDSRGnVZLtJRJtGJHpAjroBOLfwR8rZJ04S+OEkvJ9/ob5draHYBxpwF0BvNLox8qqfQR/nUJhWiCOhKhCUj+lQ2YD7SqOKshWqfAJTVty4uoC+79sb4d9778WCS/MQNFyigg62V04HBgGYM1S9pbm4g3jyD7um7+8qaWxv8Om8XMQFdNgUZKwbOTCdLAM0NMW6M7WdAO28taVDgIN1XvCOi/WlAGy/OFfBIo4IRueHm5XKa9/14mpH5+bQx15508jG/u6YJMlemYMpVsZpQUtVkznRKFdOVnNrWG60uBNB+lxh2iGGYgzfTALdeMT0WCWd2iKEXTbU+tvHqNSAoLqAvv+7G+Pff/8ngpfBj156ngA62Vk4HBgOaX9UlncxpTqQ9aL+kWQB9oD3oJGbR6xaT9CP0y9+zRKSksnLMRgUKaG/hZ+XnuxZrQ7/BSFs1fiBKZlFtEVsEdIsZG11stmPcs9WyXrTTuD5oHvQV190Uv/4D4YB+/NX3U0DnxN3g04wNaKbYNTf7830PawzaB7R4aO6+T0BqAKCZJ24Oz9IlGaDwp4DeDWizgd3tmvTPpJvNsD0AaUgsm7OVhqngbEc14z0T0Lxn/FnCHAcxBn3l9TfF/+eHPhXMih+54lwFdLC1cjpwLEAznir5vilZzSSLQzIWmHxQqdmCDOoeM5Nj+Wgvi6PaGKo5UcSv89NkESTAFiDL/KUbxI6QXlVAO8MNys/PyqJxmUWJyZnmaLJobLMEwjk2+yLLxnMWSPudynsa170sDhPmqJVNFgc7lPPxfsriuOr6m+K3fvgzwSR55GVnK6CDrZXTgaGANnHVwDzouNVCyZRa2QvhoORB0+QjIe170mkP25+zNIgDNLEPM5x32T6rutXl59OJSPLQWUDFzCIT+ugAURklFlDVF8zeCBpLbtN6Gd3GCpqlWuJBS7dyptr5TQhE3EkaEBDQ7FjOuHNP67qncV3UPOirb7gp/uO//GwwSR56yXEFdLC1cjowCNB8rXS+r19JKFWE6UpClnrXF0wVYVRf6C/IkHJvxgEH6HEUEUhBgE7PzaAQx5hzWER7jPkWJj58UIqjCW9kNUzYXO+v5Gx5HW2qTgvFfauLG8uIGyvo1vmzbDzoLZcLzayOzaZNsfMrCZmdUa+UTbGKX0mY7hBDvZGiAvqaG07Gf/pXnwuekwdddEwBHWytnA4cCWjxCH3FOnoiBLRsGvJrZVqLg8+jt8Kvkk6LwxRlSO89vyBjn6WUTQTpKefrMMM585uLZGiI/IDfMIHVrUaL+wxYcm+0UEwWUtcIdMm3Osq9GqlXpn7WVxA3Vo0XvROXDaCl12LSMcZpcXA80iXGdoWxehws/7a6HFZASTztompxXHvjyfg/ffzW4JV54wVHFdDB1srpwHEAnRQASKhjkJodLx4PuqYgw1QW7m81u7TJ9wLUhx3MSdw461uJ+1YnZfZRsi/C/PxewwSjieKrCTZYZr9oUj5N+ufqccQLq+guUJObIY9FC+h21xSvtI0+B0vCY6NzbWRGjWyqlRolmPejmt11N56M3/eJzweT5Lrzjyigg62V04FBgPa8aANp8VpcSpOUgVuAU63dAZobYmbHvCc7etALMqaBtsJ48KLODHF4gC6J/EBzHTH7QbLd2Nq96NCT3tzcpcddXna5+axwPXIcWD7LhjncZmEzjoyCHb1npj6LHjQlVY1H76RS6SUnOtCuCUFa57qoetDX3XQy/sAnwwF99f0U0DlhN/w0YwHaD3e4jiq7uqm4Mttdra2Ye7rPO6qEW1WPzNsCQwHtZxY5QHdYQEVIb55BZ30dnWY70eOWCteyg7PR4146asIbpqsNi6hYXeiU7URMSdTvROxJWl7ZrjC2/VVWE4KiAvr6m07FH/pUOKCvOHdVPei8F/ao8wUDWuDsQ1oqt0J6Ehq3w+tLOKInoXqTo2bucP1/lAfNPRET4iCgUx1tqCq4qyekEfBaMeENE4cmoJ33LN3V22wY5JrjsvlAVk9Cs9VScu28BjQhKGpPQgL6I58OB/Sl5yig9/yqywJ05qaMjGzCrt59HrXA2r9PvXMF9J4vhUK/YAigjQSuSBCs3YeYnWzMJqFNtTPLTbqqc4OQgGYcevkoTCYH86EpP0DpV+6XUEjJQZrPHdXZ2/esLbitSYsK6BtuOhV/9LO3Bc/7xcdX1IMOtlZOB44NaN+THvbYH1+6GGMImJPPgZzen57mYFggKM3OVbiaHGiCmT+ba7B63F6aXZKbv2gVFqVhggh4OUCb/RKnF20AneE1+NrWg7rDFBXQN548FX/ss18IXiAXnrWsgA62Vk4HTgRo/7WzcnyHjU0LMsaauRABfN9bG+vk++zgoR1t/C4/rU2AmRv0nAln5uf7gGahCnXKWeG6uAq2GzMVhRn9IOWbX8g8DGpEUGRAf+LWcECff1QBnccl83gAf+Danr8NwGuGnXQQoI2Tm8doJjjHYQ9vDGshJf9Lw8Cfq2k6lkwwXXv2lJEdbUyZN/Pzd0xLNrSapliFcI5bzIN2lYSuwtUv9zb5+U7+1njOngTutOuxqIC+6eSp+FOfvz14/s49shTiQY/iD6eRfHoCgE0APwfgb4MH4R04Lz5NMlZ5ThnAtwA8FsA/APgbAD8J4JuDTjoM0POA9LQXwzTGm/dzBzVhldSudAxU+qww5Uu86EmasM77fYe+/tAwh99pXioLO03T2Qbt9q6WY6hYHWhpmkDJUfM700IzqlunWZdFBfTJU6fiz90WDuhjKyMBHcIfgvkFDtAPcbDm/di3/QjohwJ4OYDHuXf7Unf/6kkBLc+btTGmuQDGntkCPkHg7HfHJpgJZabeMouAN7FTD8S7Mwj8D9aD5E2P6miT6ECnCqisPnfbzrroQfuSo+WaazNWtXD2K1tzaDdWVEDTOfv87XcEXw2rS4ujPOgQ/rwZAMsX3+Ne+C52BQPwveCBuANnzaRxxxNy/JMB8CvGc9zBPwOAn07PnxbQIS+ux0xuAQJa4CxgZopX7289SMurJOldpqrNlhfTq5YiCpunO/mYivbMTECbTy2rx91XQCWl4E6K1ByTeBsu3TPdzYbwZoeVAdID/gfkOLYpLqAfGN9+RziglxYXRgE6hD/sUsuwq7julNN7CYCvjWNT3wkZ93nzPP4pznv2Af1g95XCH9dzAfAHJ06cuPmuu/ghprd5WSANZ5PaFcdg5zCpYJMyY3+MtkDCFkcYOHu/TwLpUSyf97eczPGlW165AqqkqlU85zSgHYRN8RQfpz1nQ4Bes16x+yQ2KCqgH3jqVHzHGIBeWFz8NoDve2vwLQD4I7cQ/vwVAH6j9wH9YgCE/1i3Uet1rJPt0cEhXzH6hjIqBr1H4z60L+OHNqQoQuDcog4ECyWSYgl62a7UGAJkoGJ631mxnqTs2EE7KyY9q4U9CbzGmfiB4x7Wl9C4vRkZzH6hFKUI0l5zjg0TigzoL34hvFClsTyyUCWEP4c6xFFxm4Q/AuC7bpPwGQC+MehCUECPg4j8j/W9Zwtmq/1AOFsdCAr1xGh1YhOH5jG8WTW1yHjNItYjimppNbV0qGNWgJ7Gywyx7NBxZxRQGSc4Efb3IO13svE95ax8/dTAJvkQKi6gT8Zf/Hy43GhjdaTcaAh/ftSFXLlZyPDrHwLgt/yxb7Nex2MPKPAJfOOvc2l27wDwqmHPU0AHWnVGhwmgxUsWMFuJSwvn7Tb1iLtodbrJZiHjz41KZJqXNirs5CFSlz3pSwl9+IDeq0U9CchCTDxy/L63HJKj73vKM+pmU1hAn7wp/tKtnw4xuzmmfvScUTFoHpbFn19wL/JHLnv3DW6vjGl2z5wk/mw+V4NHvo8PVEDPd/II6F7M2UKZEpc77dh0mRaxeArGU5+462IiUVSyYvHVsvlhRw/TzYOgdrrEoklshXzs+xwaxw01RUCxEU81C0gHX5QhcJb3O+P3U1xA3xh/6bOfCJ111M86PwTQweeb9sDgtTDtC83z+Qro+VnfD29IKEM8551OF+yJt77TAVsusds0PWl61LwxrEHPeaEamZ54RxoV8zjdE09E4wnpXYBOhwUMVbMUJ1IbZoFe51wBnfO0TvNeCgvom26Iv/wpJlWE3WrnXqyADjNVfkcpoPOz5bhnygpv0HOmp8xWS6e3W1hrdnBm2/bE448fg6bnzEaly/UKjtQrWK1XjBe9UImSDh8UkrfZHR6gJxS8MvwuSAfyvfSepoEzbVZYQN94ffzlT34keNnWzrtUAR1srZwOVEDnZMgJTuMD2mZsIGmzxJjzvVstnN5pY73ZxtpOBxvNNpo8CECtEmGpVsFKvWzAfKRRNZBerEYJoBnukDi00SmWMbq84aRDDltBpSVjBeLOW07S0caQjDVAn8Au4z5lFrDOc9xFBvRXPv7BYHNXL7hSAR1srZwOVEDnZMgJTjMI0Fut2HjLp7fbuGe7ZTxoE+ZodrDjAM3NQXrO9KAFzscWqgbQ9KIZn2Y2h029c0LyEsJIYMxE67Yt8qBORRrc4jHzeV5jX1MOnS7qMPGTfPKGJzBloZ9SXEBfF3/lY+8Ptl31wmsV0MHWyulABXROhpzgNKEeNEMdjEdvtTp9HvSCC3EQ0IRzkAfNwg3X9YZwNmA21XZ83DbATtqWOej2FXO46jvbyqwyk8q7CUxZ6KcUFdA333Bt/JW/+k/BtqtcdKMCOthaOR2ogM7JkBOcJh2Dlg1CiUHfs9XC+k47CXOYJqZeiEMyOAhmbhIS1A3nPdOL9puZmian4jkLiAln05GdokJt05ndQNpB3LwlqbgjmCkmVKkaIXsrNDRcu2KvQhwTmH5Pn1JcQF8Tf+Uj7w62ReUBpxTQwdbK6UAFdE6GnOA0g3KgGcbY7sRJBofJ5mi2TZdpFqzwVi2XkhQ7G+Zg/LmMRrlkcqN7RSsuDs1ArehT+MpvBHS7ZeU5CermTqKdHHc7KFF2M4oQ1dmnr5pIco5SfxNz5BnLncDEhXhKYQF9/TXxVz/8rmAblS/7AQV0sLVyOlABnZMhB5xmlNC76djhSrmZoZF40czmaDPVTjI4uib+7GdxEMSMOS+bzcJKUqzCohUCnBkciVYHAe2HMXyB+7bVUGbvPqOfTB1lCtwbB7qMUr1hBe4bS0CtYSHt6yezPZTZPHRCQ54tFNDFzeK4+fqr469+6I+DL4DyFQ9VQAdbK6cDFdA5GdI7zTDB/fSrGS/ayYpa3Q04SHdNwYrNf+6aTUNmeqQLVSykXZFKZL1nG9pIbRBKeKNN4fq2FbWnuH1rC0mLKAE0O5C0HKCrVeNFlxqLfR1IutUFGC/aidwPUoFTQBcY0NddGX/lfZTGCLtVrnu0AjrMVPkdpYDOz5a+8BHP2gdqp6EhryYi+74Yv3jSftEKH5v0OxapOD0OnoOl3vSSWaxCGNvqQZe54XnPkgNt4s8Es4Q3pAt2axPx5hnbYHXtPutFmxZRzZ4HnbSHsk1WTQ+/Gn8Wel1IMkTueQIFdHEB/cBrr4i/8m5WXYfdqicfp4AOM1V+Rymgp7dlFpjFKzaQGkAp1wjFDECO8WVGTW50hwJJPflRX7BflOsYyhCvmSl1JrWOm4JOijTZIDSeMzcFbcy51NxCqbmOeP20hfPavbbJanMb3WYLcbeLqFoxIQ727svsgi1tolwX7ERL2ZlVAV1gQF9zefyVP6VsT9it+qAnKqDDTJXfUQro6WyZ7oSS7oLS3yHFvhbBnNbGoEdsvW4rKJrWgubvPvRFmD8tL0o4i060AbNRvrMbhEm2huvZZwC9dQbddQdnQnpzDZ3NTXSatgNJqRyhurSA0uIKoqVVlI8cR7R8FFhYQbe2ZMIccaUOKKAHLqSibhI+8OrL4i//ye8GXwC1H3ySAjrYWjkdqICezpBZYvtWFtRu/vkdUeSVBNBWZc5qOKer4dKdVHzQy3kSAHti/Wk4yzF9G4QC6J0NlLbXLaBP343O2r0m1NHa2EK3ZQFND7rSqBk4RytHDZwJaQV0+LopLKCvujT+0tsHdsPb9QbrD3+aAjp82vM5UgE9uR3FeyaM6d36oQiGJyRc4XvVBs6uLVXa+xWYijfte9T2cf9Y/eP98yZQdi2vDPz9DA7Pg46aG+icvtuGN5wH3d3eRnvbxqDLtQrKjbrxoMsrxxJIK6DD101hAX3lA+IvvvmVwW+k8eifVkAHWyunAxXQkxvSz2OmQobZ3HMxY9nok8wMSadjjNiEHdhlqWRT4fz4sZUGtWGK9C0dy5Zj/D6EJizhntgXRpEKwmEx6M0z6G6smVQ7xqCNB12rJil2xoNeOWpAbcIbsknIEIduEu6/EMcVF8dffNMtwRdA47HPUkAHWyunAxXQkxnS956zOqFIN5SmUabrJjKhfDUCWTIw+NjvhMK/E9y+RzxqhFlaz7v+lpHFwTQ7etAgkBnm2DiDeItw3gZcHjSYB11rIFpYSuLQpaVVxNVFzeIYNTHu/4X1oK+4KL7jD18W+C6Ahf/leQroYGvldCABfZtrvT5IFewgdYbOyWwm3CBxYeMle0UmhLMvts/SbdsNxW4OslVVIrZfKztt515HlPRG36AxZ81Xeq76FOxcml1fHrTJh2aq3br1nF2aHVo2xIGyBTSLVAhpxqJNDnSljri2mJR8ax704JVVVECfuvxEfMfvs6F22G3xx56vgA4zVX5HnTx1Kr71tttNSpZ/8y90/z8Ka2ulQToa9Ji32jE2mlZonwUmLDZpdbtm09CmwUVGXJ8FJhTbl24ohDa96ayegukZD52HtMRoIojUaVkdDharuJh0vL0J80M4GxGlLlCpolStJV60AbNUEooeh1YSDr0gCwvoSy+Mb3/trwTDZOnJ/1YBHWytnA686dSp+LOflw7o9qTy9do+tpe4v/Ekv+c0hH15GmlVxQ3ApI+gqfyzJdpGx9loOVuhff6N2R1+L0FfKpT9BSl0lFWmPam9+z5yfSlRSowab7plUu9KrZ2eaJIp8yagXWeVKLJ6HBURS2JaXRVxuTbSe+a4NQ+6uHnQpy69f3z7b/9S8PW39PTfVEAHWyunA288eSr+xOe+kJwtnQKWjoWmMwRyGsa+O43fS5AhDoY12AVFWlVRbN/vhkKpUPGgKRMq3VAockSpUMI6q12V309wXCPtCoFkqdkZUDcBbh466VHjZfuC/dR+NtKiTr1O4EzJUW4Oig6H+UTv14RWQBcY0A+4IL7tlc8LXlYrP32LAjrYWjkdeP1Np+KPfPrzSdZAhF5erp+jy6/mfrZAOlMgp+Hsm9MMAvQWBY52OonQ/umdlgl3UGyfIGfWxkLNNnk9Uq9ilTKhTi6USnQMfdgwR0/oKDSckTbeIEAP1IMmlEXA36WMJFrQkYW0EUQirH04SxssFezPXL9FDXGcvPj8+PO3PCf4mjvyrFcqoIOtldOB1954Mn7/J261oQ0HZ4I46Qjt0sH8nF2GPXo5uDkNZJ+dZhig2QmFIQ52QhkGaKrQidA+21YtsJ/gLAFtYg5+eyvqcziNDgLZZXqYqfCbxwqACWZ+peLv4jln9Sj05lI96OJ60CcvOi/+3MueGXzlHXveq6cB9FkA3gvgEgB/D+CpAO7NeHH+b43FtMxcBfCgQQOcRauzYGPs1YFXXX9T/PaPfMakdkVGAY2CO9aLlhxdm69rNYhFvvKwQ3qUB00wE9SMQXOzkEL7EuJgP0GGOBKh/XoVy/Wy6SXIOPTMPGgfvAJqfjAbMGf0JXSLMIGyhDDoTae95gzv2bzcXi3kAr9OUT3om07cL/7Mi38m2HJnv+B3pwH0awHcA+A1AH4DwDEAWSkkBDSh/P1RAzsUgL702hvj333vx13nZydXWbY6w1RKMzm7VEtLKaWJl23LlUeZ8uD93wc0wSupdYxDSz9Bglk2CUXLmR9wIrZPD1ogTc+ZgM7aJJzUvkOnxe/s7R4bUPMmG4Qybfzk9vsTCozT96lpVjhbgxQW0BeeG3/q154RfHGe+2uvmwbQdwF4FIDvATgfAL+2XzXAg1ZAi2EuuvqG+Df/5CNWvjKy8pUiBG83siqmCSnlLNNaw6KWxnNNCpHg1VGwA7P6CZqNwg6F9WOccd242Z3baDm7PGi+DdqRPys1a18R2xc7+2L704SSRn5u+mGMQY/Faxb7+57yAK9ZDlVAFxvQN97/nPiTv/y04CvrvJe8YRpA3wfgqPdiDG/Qi07f/s6FPrh8KFb9lkEDHLm+g99ZgQ887/Lr4p9/w5+bmPNirQw/w4BdowUikgbGr9/+V/BpAFJgs4wcWla7Km4C0oO2GR0WzPIjYvuRK+1msYrtKWjvuUE4SM95mg3ZoEXsw3nkO8/u3p31NAV0wQF9/tnxx573EyEzbo658OVv+XYq9EB4+gD9NIDzMk7IcsV3BgL6AgD/COBcAJ8C8AIAt2UNMmhtB7+7gh54/AHXxP/rq/7MeHTMLlhuVLHSqODoQtUUUUiWgWxiESLSkJQpYKItcVg9aBvqYCcUK6xvW1bZbij0pG1/QakktHnQEuagzSWMlFXuLZrO06Q2zmsRK5x7F3xRQxw3nHc8/qtn/3gwmS561Tum8aBDQxz+eF4OYB1ApibqvNZ2sMHyOPDIRVfHj/p3fwxuXBHQhPORxRqOL9dwtFFNsgyYbUBvj3BmxZvfUukwx6HTPQUplmRBzepBK6BkhZO6fu2HgTQ/7GQz1kDbtaqyGTROitQJ7+/Wjw6f/b1eyArn/rkpLKDvdzz+yM/+aPBCesBr3zUNoH8HwN3eJiGzOl6cevElRktdFgcf04N+BYCPH1oPevnCq+If+LdvNfoQBPSRxSqOLlZx1nId5yzXcdYCId0rppCNLHp80r3jsANa+gpSbtTIjDpvmp61/Z3ZDLEtD3f0koIgEUYy2TGS0ihwdr8PkxINvrrcgbOEtYI5ezaKCujrzz0r/vAzHhe8hC573XumAfRxAO8DcBGA7wB4isvqYEjjbQCeAOBSAB9yA6oAeDeAVx3qGPTy/a+MT73wzajUymhwU7BRMd4zAX3uah1nL9aMF31Wg0UVttqN+brprtGHLcQhi8YXTSKQCWC/bVW6MwqflyUb6hcB9aBtQ0i2r2CvjdU0IY/gq1EPzM0ChQX0OcfiDz31XwS/zyve+P5pAB38OqEHztLZCB3DzI9bvvDK+OZffQsixkOZm+s86HNWGzh3pW7g7AM671Swmb/BGb9AVssretLSVcUHdhfOm3ZdvPm/LBH+pJ+g51H7MqQmZ921s9qPH4yjLqyieeLTjreogL7u7KPxB5706OAr5Oq3fkgBHWytnA5cOXFV/OAXv83EQ/0Qx/HlOs5eruGYxKEbzOioJII+GuLoTcCwvoT0ps1GopEkzfauTRGfN58EQkhD2KJCehTQ8li6eUF8L8ZKQP/tnXfuxUuNZdrrjh+J3/9jjwx+zrV/8pcK6GBr5XTg0Yuvjh97yzvNJiHT7Bji4CYh49AsojClyA37WDcJBxt9UGdv35uW7iqmW7fZOLQdWLiByHt63byxmpMeM/cFuBnLHPQK0/Cc0L+EO4qWQTMPAk0K6r0ca1EBfe1Zq/F7H//wYJLc8O6PKaCDrZXTgedcek381Ne+xwC6VrFZHIS0n2LHxyxFZq4uU8MkJewwp9kNMv+gkIdsHjL9rs1UPJeGxzxppuIZvWhHG9qVkLYFQywcsnDmt5y0XrTp2F2AQqGJgZfW/JhgXU8C6anHO6JIx38bRQX0NUdX43c/5geDLX7qg59UQAdbK6cDL7jyuvgX3/RBB2jm5VoosMKNHvMsK91yeguFO40PaT+0QS+ZnVakLHxtxwr6C6Qlp9q2xLLl9jIXRS8UCgJeuiAm/XsW9AJAOC6gJxorV9mE4y0soI+sxH/6iIcEXz8P+uinFdDB1tp9IJO6fx7A/3T/+k0AHxt1vouvviH+rXd91H6lplBS2eY52yq3sgl7SN88qSLk78lGlkkJG/Uqh+//g1piiWY0u6xQTIl6HXy83e6YkAfDHBLikA9JypJSnpTZM0UsFBo5/b7uRxbo0ssjS+NjCKhzBXRWyfuoSssR4y0qoK9eXYnf+dCBYnG7LtqHfOJzCugpUDa06mbQeS+/7sb499/3CfglyAS00d0w0O7vlZfVjkkBvdu6aUBL1xVbWRgbzWhf8Y6l4YQ0b4wt02MmoP2uK0XdAxgI6Aww7xJkygpxiFoejTFCzlQsPw6kg8brC0iJeNSgcIyv7idj9u4LC+iV5fgdD3pgMHJ+6HO3KaCDrZXtQQ8sixx03qtvuCl+50c/a+VGjaxor2BCHluPuSdB6ivZFSH+OYXNZvbUQYCmoD+96NPbVo7UtMZqthNRfwE0dVD4DcYX9E9n0Zh5iajiPd9vMZnAS6nlZUqaDggZZGpOp2GdmrlQQIfCOXS8yVhNV5lsGdaiAvqqpeX47SdPBl8DD7/jdgV0sLWyAf1zAM4A+BqAXx8giN33zOtuPBl/4Mb/zvYAACAASURBVJO9jiqSY5sulpANwXRXFfWes2csC9DU5qAuhwD6nq2WUb1b2+lggw1mm9aD5gcjN2p9zWhpi1XESs6BgJYWW36nFrbVco0BEm/ambBPY1qaA5gOLq6byxB506kAnf4wka4y3liTLjTedCfj5RhNWzCvBZjn+T/s4Y8oZJrdVYtL8VuuvzEYOT/81S8poEdYa5ha1Jed0hTX6iud5uqzBpzvuQD4g/tfeOLmL379m72WV0kBRMn8TTQhssqNFc6DZ2scD5qeNMMbbIslHrTRRfHEqti7kOEOH9CF9aDTXVs67aTfoWlWy56H8je+YR7vgGYgRyCz76G01jL9EC0Ek56HE/Y+HPlhIg11/f6MMlavyUECZOkuQ0izy3kGpIsK6CsXFuM/uur6YEA/5utfVUAHW2v4gWwr81EAI63PprGfvNU2jfUFeRjuMN8quQnounv3/z+nkR7Q04TEoO/ZbvV1/qbAErM+mPIo2TRUESx6Hvou6Inn7IOY3cP50265juJNA2bTqNY0A3CttAyMa6ZBbcxu4tKsNg3pvADtf5j4cDZj5ZjdePle+OHi92o0HyDS7dzrdJ6C9MMe8cOF9KCvaCzGb7r02uAr8LHf/JoCOthauw9klwJ2K+DtVwEwf+bpo8538tSp+LO33d53mPRlpiB/Gtz+76POfdj/n9UWS7p/+11XmMVhRP3dZhQ/HAloanOLHjdBLUqCkk1TlDz0PkBnAa/TQqm9beDMe7CLeHMHcbuFuN20joDxnMso1RpAtYa40rCQrjasZyodxV04YdLu4UEfJmasBPSO7Xje3Lbj5HjdB4oZb6WKqL6AuFK3HypVey/jFa+/sICuL8Svv+jq4Mv08f/tTgV0sLV2H/inABjxZ4iDfb3YT12APfC0BPTnv3BH8v902MJf0AcppJHWwPANlNf7FEDHTtVO9KKl6wq7fTPNrlesYiOpjP/7XVck5ZFglp6Ftk9kMTQ5sgCdhDHogXaaiJpbDtI76G5tIN7eQLyzbYHHHwfnUr2BqLEEGPA1LPyq9t56016ow/OiJ45BSzxcvGf5MGntoNTaBHa20HVjNYAmqDlW/tQb5gOlxPHWGoirixbS7sNFGus+7JGPLqQHfXl1IX7d/S4PRs4T/+G/KKCDrZXTgadOnYq/cHsP0OnT5gWrnIY78WnSQB52Qae9rEltMKjrihX1t0Ur3Bi0wO6YSsJuN05SHk2nFdceSzquFK2SMNMjNaEAimHbEEGpuWm90dYm4s11dDfOWEDTM20xhOAA7eBcWlhCtLgCNJayoZfhRU8E6JS3b8IZ9J5b24haW8DOJrqbZxBvrBlIo9U0Xr/x+CtVlOoLKDUWES2tmp9udQGx+el5/fxAKSqgL6s04v/j7MuCr6kf//++oYAOtlZOBxLQd9wxGNA5vczcTuODWS7ipNIvrfvpYu15hXXSUqSiEy050dTjkA4srDKksJJ40OzTym4rzDunp9zruGJz0wsZ3uDgPY+0D3jNDWB7A931+wyguxtrFtD0SBnaiSLjjUYGzquIVo5a6NWWENecN80wR4UbcakNwzG6h4/y9k0oht5+c91+mKzdi+7mGmJ6/Wa8HqAbS2a8pcUVM97SwjLi2jK6tQWAXrSLRf/QDz8Gf3vn10fW8+z1RXJppRH/x7MowRx2e8o/f1MBHWaq/I46yIBO62IYfnhSn/xdBIoslIdvjPrgDp2BtBctWtG+YJII+vPeeGeuOlPCGFS2s91WemAuiuToLupwM42bf+I9C/DoPRPMp+82XqkB9PYGOts79j1HEaJGw3jOxiMloJePAgsrFtIS5pgVoH1vv7WF0va6/TAhoNfuS8Ic3VbbjDeqVtyHyQpKMt7Vs6zHX1/qC3MUFdAPqDTi/3D0AaFLGT/1/f9bAR1srZwOPKiAHiQBSi+Wfqrf3URM6fg8NLVwXEj7XjQ/HAZJjkpXFgtoF1v2hPqlDZa9L0bs2YzVX4d+yMAH9M4GouYGOgI7Am/zDDrr6+g024i7XQO8SqPmwgUrBs7RkeMoLYoXvdgfhxYv2r3+NCEOEy+XTUGGN+jtb62hww8TA+n7zIdJa2MLBDQ/TMq1CsqLi/YDhR8mK8fMmOOF1Z7Hz7h5uYKiAvqSciO+5QgTvsJuz7znvyqgw0yV31EHEdBpOKc7nfhi+hTRN9B1qKG3SugM6gs4SdVeGtJ0lOWDgl4zxyMfGv4HgBQLSUcVm5feg/O4Hxb5rZremcYGNKFnAL2GzuYm2tuSxREZQJeXHfAyAN2XHbHHgGZYhmP1Pejq0oIJb5QJ5yPHLaAbyz0PuuCAvqhcj1+2Eg7o5913lwJ6FhfRsHMeVED3vGTrtYrcJx9bXeYYBKUfhhYAili+LQTpbzc1ibznMEF/CbH48fF0PnqePQnzXl9BgJaY7vpp65U6D7q7uYlOq42407UeaaNuMiIkvGHiuktH7eZbzfOgmR/tF63kEYNOhzg2TyfeMz3/eHvTfKDQ4y+x2S9DHPSgZbxHjhtQ98XMCw7oE1E9fvHyxcFL4gVnvqWADrZWTgceZECnpT6Z5ubHfqXTCSGZpUMiQlF+5+1Ju5gMEvTnNLrQ864Z9fPRp+nqndNSyTzNwCwOVt+5rAiTYsdNN8ag3aabzeTYRMzMiE4XUa2apKxFS/SiXciAHqkAetabhMw0cTFzPyRjxs2NQm4SdmxhTalas5uaHCu9/aVVlJaPmE3Cvk3NAoc4Lozq8a8usodr2O3X1/+bAjrMVPkdddAAnc6cMJ1LOuxgArBSzwjmd2HS26STiQkVUIPZdSxZMNkTNnOilz1hN+oYH57Ei5YZS4PaAHpAANVP7ytqPvpIQLMir7nZS1tzWRxJHrSpLOzlQSdZEQTeos2KMLnF3HwbUqwyTQx616Ymc6D5gbLFTI41mxa4tYFuc9sUq5gbi1SYA+1S7CQtUDY0TRYHC21Mmt2jCpnFcUGpHv9i40QwTP7d1n9XQAdbK6cDRwF6WEGHP4RJc4VzehvJabJyj3t5x8w3jvtE8k3oI46T4pBEC7vGDuY9SNv84/w26ELtKm+sKPbNmq+BqWv+RqEr/DDQo+ecpK3ZGLQp/mBusaSumWKVRZdb3LBpaw54SXhj2kKVrDxofqC0mAu9ZT5UWFRjAE3vmYCWSsKK9aBNscriismHNh8ifkqgK6wpah70+aV6/Nz6hcGX4L/f/n8U0MHWyunALEBn5Q6nPcCiVhxmVe9J5R4LQ9jFhPKem1Je7XLbuClIofyFamREitjiyxSKaJuvkSttaByaQPNLp1nqvbOVAI8hjgTQLmxgyr1ZmUco+5V5UknIDULepgU0z+HrhvADpduxYQ5+oJhxu8pHU1TDnO1eiINetK0kZHy8V/WYLk0vaqn3eaVa/MxqOKBf3fwf0wD6KQCoWX8NgAc7xc2stfV4AH/AfXoAbwPwmkELsHCJ5SOvlAkOSAN6WKzUfB13ryHxUXOdeJodYrR5eXyD9C+owyxdTKjB7LeaMg6c07+wLabKoB6zNsoNW1C7AG0WildNSKiJZ8rKQiOc1LLxZ1Pq7QpVuPlXceJDaW0LESCakRaHCXNI3NwXdnKPbRWhV1RDj5+aIVHZ6nBwQ5A52qIb4pWlFxXQ90Mt/unK/cMmGcDvtf9uGkATzMTHmwG8aACgCeVvAXgsgH8A8DcAfhLAN0d+cwt+F/vsQAH0IDBLpkM626AHYitLKop3Fna9/Ni9BrUPaAlt8J6AFoH8M67VFCHdbFsFOXrQFCfy4Zwl8Sl5yFaGdZ9N9oyGO0iASKBnYC2qcM5LTWRHRYuZespG9J4KcU5XWYSHsnSW81Szc550nwwqwSz50SI9uktulFrVqfEm6ns9Deuiyo2ei1r8tOiC4FXx+u7fTwNoeZ1bhwD6oc7Lfpw7+KXu/tWHGtCixeGnpgmYGZ+Vog6/6k68Tql6k9zheQv6Gz0Ll0rnt5naase4L9XFhKAmoLmRyPiy0WB2njPhzF6Aqw3Goin/2Wv9ZbrLKKCTayYT0D706CEbHWh6y04P2pSEd/sbsUpXEiPSn4KfpNWl0utkEBNtEiZPduOgF+2aC8hYk28CTsS/DxROuMmUnnva1enOKkUF9Nmoxf8aFMEMu70Z3541oJ8MgCGO57gR/YxT5Xz+oQd0Om9Yijn8VLW0dEWSN2xgtTtneNKUtLDlkn2UAnoa60323KEi+AyBGS1lD4LSqSSr5ZUI94s+dLliPesRvQmnBrT7QEk6p8iHChe9t5nYZyFvXMbrz2p7VYpQ1JZXAD4O4OwxZr0BYNs7/i0A+CO3YQ1FPuwOGuZBM05N79kHNOPVL1BAu+o2es62kMMVd8Qx2kbIx5VHu8o7dsKzFW4wncDpVaYLO6RfnvW2x1gGUxyqIY4pjDfhUwdO7Yi+hPJyFME3gv28+SAe0OMvZJjjqBWa86XGaobie/lJE1l75l3jzWoc68IwBQZ0iCnzPkZDHONYlDHo226/w4QFrJCPzROWgg7Gb/mY/2+x44enuFYtRwa8IuTj5wzPSzNi2CbherPjumnbTA520maXbfsBYkXyB20S1jxFuSI0ah1njmd97NDPXh98DoR9vQilY7aZhN7Wc+I1C7QTmvvb06PfWRaoR36gCLD9zt7827Cxpj9cvBi5ArpvnoYBmuk53CT8EQDfdZuEzwDwjUPtQd/6hTuMypuURPdkMK0c5la7Y0BGoEkcWoBGYXnKYkrVnV/cMQ9JTE2zGw2tvI8Y+eXID2Wkwxrp39NADvl9xBtKQzqX8aY2Kfs6vKT+p4A2E/QkAK8HcA6A+wB83YUzuEvJdLonuGnk/etcmt07ALxq0PSOnMe8F/o8zkcPmoAW79lkPjidYhZ1sOuHpKTRk6YXbZ2dEpKijmoZS7WyqbpjWybxNueR8bBfClXmMdezfM3giyULyFl/G3hVpjzoNCgHPM+HdPBYxZMOMdyQcSigQww4/jFjzeP4py/GM9jy6tbbbk9kMKVn3k6nlzdMQDM8wM7ThDRv9JjpOfuFHUxRk4wHZkVI6GMvNwtDSr35wcNvBOlSb3r8/EYwy1LvYsx6/qOY6GIZ5FmPArYPQ3k8AtRje9E5mkgBnaMxvVNNtOZmM5TZndUHdDot7cxOGyzqWDfVdwS0hRpv3BSUXnmrjYppbsru00xHo2dNT3penT+yRPJFj2NeYkmzm8HinHmiC2bQ5hzflh/z9d+mi1VnxqkHgHqsWHTOJlVA52xQd7qJ1ttshjK7swqgLbgoKGSLOlgKTTif3m6BoF7bsR70VtOWutYqEZZqFazUWdxhq+6OLVSxWLVwJqTZrslmdjDnY28zOYokNzq72SvumYMunhFZHszuMDce55d1SwpeVlobj8+A9Kg0vKDxTmBuvi4Bfeedd87qJSYY1cF4yqEwaBrQoltBQN+71UogbTMg2knWgwkF0GuuU7eigrMaVbC4g171QnX+gDbXtVOKCxHs5/EU7fcF+0Uon6GPpMvJHn7QHIzLKNV1Rd5UFpxdMYgpEvGFjNyxffnQrDyU3OOcc6XztrsCOm+L2vMdSkCnPWgD6e2WCXFsudJoE+KISgbMjDsztEFQS2n0vD1o8+1YnK+kvZUV6N/rllezWZr766xDC1kGVe+xuIXaGFIo4jxjk39MIM+w2jBv6yqg87boIQQ0U+xEu4Je9HY7NmAW/QrJ5GBptIQ4mDfM8IZA+qyFqpHoXKhEiZbyPFLtZDmkIW286j1uGjubpbm/zjqwFFwElQhiEVSiBobRiHYl4a4JrXWZRKvDlVZXqLdcg1GP8/U6MtTu5BvVPCyngJ6N1Q+VBy050IS0yXnuxK6oo4U15z0T0tJ5mqEAZmzQizYbhPWqSbVbqDDVzgJ6XpuE/nJIS6f2/Z6uXU8p8/lfo/aqEnI2S3m+Zx0lpmSElERBjjKfnab5Hc0dxCLob2JQVjMaNTZjdcpxlCMVSA/Ri1ZAz3cNzOLVDwWg/Txov0CFHjSzNlhxR0ATziY1zRGaVYQEsWRyENJGP9mJCuUtcD/tBKcF8scpBVY4T2f9QYD21eISDebWJkDt5e0NqxltZD5tFxMj6C+a0RT0p2Y0RfJFM5peNCU/p5Qkne7d7n62etB5W/QQhTjShSqSycEwB71pG9pgVkfHwFnyoJlm1wO0zR02RSrsQuLKoudRqBKyFEZ1M1Egh1gx/Jg+QMvmoJEgdTKk6S4m7AHIjisJpB2gq17fwoUl0wfQNJQ1Pw3nVds2U0YNT8IibqijMjnC39F4Ryqgx7NX6NGHyoP2S70JZnrT9KIJZKbXZZV604s21YS14pR6h06uHrd3FtgFaOlikm6J5foAsuu36QWYaotVcm2mkr6F7Pq94PUtlLZYftfvCbqu5G0ZBXTeFj1kHjTFkpjdIEp2LOowzVXlvgtbRdihaJL1Q6jFUS3bakLmOydNVl3jVdFM3usc6NksBT3rNBbIAnQijh/QSbvbtB60dP5mg1bTrHXlKMorx2AatUovQHY2kSyPlHa0etDTzGLxnntoPOhBanbiSVsNDnrT3aS4i8Vc7OFHSEtJtwgmcQMxzwarxVsaOqJxLDAQ0L4HvbOB0vY6umfuBj3oztq9xovubO+g02yblyvXKig36qZJK8FMQEerxxE3lhHXl2xfQHb+HhCHVkCPM2vFP/bQA5phDimNNhKkQ+RGZVPQwtrmSdOL3ksdjuIvqcM5wpGAbm6aLtqlzdPort+Hzum7bSftzTW0NrbQbVlAR9UKqksLBtCMP5ePHEe0fBTx4hEbh64tKqAP0RI79ICexIM25d1lQloBfYiulaFvdSSg2T075UET0F160Jub/R704iIY4iCg1YM+3CvsUAHab22VjkFT/Y3hDW4UMl/afN00Qv021Y7ZGxKDTsIcrm+fxqAP90XEdz80Bs0u361NlJpbiJobJrRhNgkdoJlqFxyDZsodQxwagz4Ui+7QADot2O93w2aIY5NKdkyx60uzozRnOTOLowdpG+rYS6GkQ7Ey99mbHJXFwaKUqLllQB1v2tCG8aA31kwuNFhlaGIcZZRqDURL1oNmqKO0uGpyobu1hV6anWZx7LMVMtlwDxWg/XZXkgNNz5ndVNapZNcRD9q60JIHLaL9rCLcL3nQky2H4j5rVF63YdscV3NmoUpoHjSLVFpNa3wWqbBYpbEEptqNzINOqdrpJmFx1/AkI5vjkh46XHa+fTmAawCw4+3XvKNfCuDZ1AQC8MsAPjHqjVPN7vOuo0pWJSElR0WHg2JJDIUYQEclU+ptevi5cm+K94tgf9EqCUfZYb/9P13CPmr8/mLea1gPrSR0xSpJJSHj0e2dXg70zlZPFzqKUKovWC96gVkbdZu5IZWEQ8IbtI8CetQq2V//LyqgCWamLL8ZwIs8QF8L4D0O2uzzxRboVzpYD7T8IMH+tBaHkRo1YQ7XUYXtrTwtDoomrdYrhdPi2F9LbvRoB2mLsNBo0I1Sqb4XLQt7r0A9lhZHuwXC2mhxtNuI281+QDN8UanYcAbh7AsmqRbH6AV0gI4oKqDFxOnuuPSeeXu1u6f3TE/7S8PmxAf0MDU76YItanb0oBnW8NXsKDlKwf6iqNkdoLVo3sq46nwWyiU4PoPd/Hxdax/as7TVQDU7So2KrKinZmdkRrl5KEp2Uh7uCk+otZFsBqbV7ESHg29IQxyznNa5n3u/AfoNAL4M4M+c5d4O4K8B/HkIoLM6qowS7C+yHvTcV0/OAxikb03HmfsHps2Xc6L9ak/CuZeLztTHvYd05oWUFuQXyVFCOZEaJcDdBqGzp5EVjSjW7/Q2CGtfalSqByfoqpLzlCWn01Lv2Vh2noBmeOK8jLf1MgAfdn9Pe9BvdN6yD+iPAfhAxnmeC4A/OHHixM3/5Zv/1RWkwG0GUiRpdEcVAXTROqrMZjnM96x+M1zRTbEbu/SsY5P+SEB3U5FWKRYypfeRTXlLFxHN2pMeeCFlQJqdVIxIf9p7FvMLgAlmaX2V7qgyRl/CvZhVBfRsrDxPQIe8o5mFOIb1JOwX7C+bnoSMPUtXlSL0JAwx3n46ZhCcuR9AMBPU1E2xHWN678y27OoBuVfhufeVngO9aA5XxJN4z0axXjuspC+heNACZQlh0JtOe80F8p45TAX0bK62/Qbo6wC829sk/AyAKybdJNxqx6ZZrHT1FtlR6erNIhXbUcVmcTD+TFBLu6t5dvWezXKY31n9LuW+oJUpvzfNfm1JPo8TvW7rFdsCIv5UqY+S0k2RcAfv5+pFC6S9+1IiS+p94phBMpIOC2WBdNZ9arrmlcGhgJ7ddVNUQD8JwOsBnAPgPgBfB/A4ZwaGQJ4FgOIFL3Qx6KEWkk1CufC5UUiZUWZsbLW6RqyfGRxGsD+VxUFIE9BMtWM/wnSaHb9WEw6qxzH5IpXYsw1hiDaKBbNs6vqSsNarjq0OSmSb96arPanXvdfl+CMvJgGyD+v0Yx/Ewx5nmFsBPfkaLOozR66pog58nHENE+yXQhUR7Lel3lqoMo59pz3WD2+YUIYHZtOejE0Vmh2sNW3HdcJa5ogVnfyWI11v5APUNFXY45ZkwReTD+oQ4w2IN6efqoAOMeb+OiZ4Te2vt9U/WgJa9KClL2EaAk3TRHZ3JSG9MHpn7KYiF72vajfPhrH7eU78sfvhjXTfSIahNhyc2XXdNlXoJOl41nO2gDZ9Ixu2qa+p+JxD15t5XVDzhLOGOGZ3Jc5rPc3uHWWcWQBNEPjl3n5sk8AeJDcqYv2+JrTKjeY3hT6gJRXSlt3bTBvZI5CKT/mWwxAHP0BNpWfSed12YM+q9uSH6V4Uruz1RTVvOCug87sW0mfa67U0u3cy5MwE9Bduv8MkZ/ldVZgNQGCbr8zusZ8hwFMybUvStwwQKDEqf3PZA3tdtTYXI87wRQXQdh5s3JlhDWba0Gs+vd3byOXvfjn+gtsfWGGVZ6O3ket3Xuc3nl4q3gzfSOrUs764igBmecuaxTGbdTXrNTSbUY95Vh/QtthB0rVcClc3dvC2ObZSDGEKIGCr1HqpXDZ9K12xthee2Zhve98cbr/ZuFQ619mGoQ1u2J7Z7uD0TiuB9NpOG1vNjolT88ZekUu1ikmFPNaomo1chjkWKzY0JXFo3cid7XJQQM/GvocG0HfccYetRHPlxALpUVVqNLtUqtELs9Dur1RTOE+3OLMALR50GtDMtFnfbhtAG33uSmQAbcBsctUrONqo7tJLUUBPN0ejnq2AHmWhyf5/qABNEwmkk8fOm06XEIs5mWebQNoDs/nbnCUuJ5vy4j1rUIiDqZAE8j1bLS9X3W4SspiI32QIaLtB2AtxENINt7krG7vzCHEUz9KzG5ECeja2PXSAFjDzXmJ4iQbEALW0eSulzWbqi3PWYZuE9KRPb9sQB+PPBDazbVj6LV3XJcVOPGim2vliVtKabK82CYtj2b0biQJ6NrY+lID2Ie2DepSJfWNpWGOUtcL/PyzNjpKwJqyxY+EsxUTcTKQHLS3JWH7PTI4VVnq6NDsWsJj+kex449qT6byFz8s4Ryqgx7FW+LGHFtC+iUK6dfB4vbjDF9Y4R2YVqkjPSKbaMauDudDGe3Ztyfgcq8NhNwPFi2bRip+vbrJuvGwbncNxZib8WAV0uK3GOVIBPY619NiZWUA2CkXFTsq8+wuKbDER/yc3Api50I1K2XjK1OOolS2kNVd9ZtO168QK6NnYWgE9G7vqWce0QNqLZggjLZREWDNPXfLZ+RImvuzy0q1gkgUzoW3y19V7HnMmJjtcAT2Z3UY9SwE9ykL6/z2xgC/WTzhLXrRfQCRVoBS94n6un/LoFw/5cPa7q2h4Y3ZTqYCejW0V0LOxq551Agtk5akLrLPy1fkSfjcVU0Dk4tLprioK5wkmZIynKKDHMNYYhyqgxzCWHjp7CwwqJmJaXa/IqDcOATT/MqiQiP9TQM927hTQs7GvAno2dtWzTmGBQcVEPOWgxt5+uEOArBopU0zCmE9VQI9psMDDFdCBhtLD9s4CftqjFhPtnd2neSUF9DTWG/xcBfRs7KpnndICwyCddWo/hKGe85TGn+DpCugJjBbwlEMBaAD/E8C3A+wx7iFnA/j+uE+a0/H7aaw00X4a734a66xse7FrUTen5X0wX/awAHpWs/c1AA+a1clzPu9+Givf+n4a734a636zbc6Xwf46nQJ6uvnaTxfmfhrrfoOI2na660ifPcACCujplsZ+ujD301gV0NOty1HP3m9rYdT7ObD/V0BPN7XPBfCW6U6xZ8/eT2OlUfbTePfTWPebbffsAiniCymgizgrOia1gFpALeCagqgh1AJqAbWAWqCAFlAPevxJeQqAlwO4BsCDXbaBnOWlAJ7N5uEAfhnAJ8Y//UyfwXH/vEs75Av9JoCPzfQVxz/54wH8ASu3AbwNwGvGP8WePuPvAay5OW8XMKvnHQCeCOCfAVzvLHMWgPcCuAQAx/9UAPfuqdX0xYIsoIAOMlPfQQQzBdXeDOBFHqCvBfAeB+0LAHwawJXuwh3/VWbzDAJ6HcDvzub0U5+VUP4WgMcC+AcAfwPgJwF8c+ozz+4EBBxTLYuaD/9IN+fv8gD9WgD3uA+/3wBwDMBLZmciPfOkFlBAT2o54NYUoOk98/Zqd0/vmUD80uQvkfsziw7ohzqbPc6987RNczdIDicsOqD5Fukpf9QD9F0AHgXgewDOh13LV+VgCz1FzhZQQE9u0DSg3wDgywD+zJ3y7QD+GsCfT/4SuT+TgP45AGec5//rBftq+2QADHE8x73znwHwEADPz90S+Z3w75wNKRvCb1VFzOpJA/o+AEc9EzC8QS9abwWzgAI6e0IYnjgv418vA/Bh9/c0oN/ovGUf0IzvfmCP53zY2PkBwq/ihMkrnff0rD0e37CXY3yf3rMPdc2XkAAAAh9JREFUaMb5X1CgMaaHwnDWPwI4F8Cn3FhvK9h4FdAFm5DQ4SigQy21+7j9GOLw30X6op3cEvk9cz+GOPx3X9QQkoY48luje3omBfTk5k4D+joA7/Y2CT8D4IqCbRIy3si4I2+/6sIHT5/cBLk/s+I2CX8EwHfdJuEzAHwj91fK54RL7AXgsjj4mB70KwB8PJ/T53aWNKB/B8Dd3iYhszpenNur6Ylys4ACenxTPgnA651yF2N5X3dfy3kmhkAYMmC61QtdDHr8V5jdM/4UwEkX4uDm1vM8YM/uVcc78xMAvM6l2TFF7FXjPX1Pj74UwIfcK/LDhR/QRRsvM4u4IUjFvX8CcAuAvwDwPgAXAfgOAIaWmNWht4JZQAFdsAnR4agF1AJqAbGAAlrXglpALaAWKKgFFNAFnRgdllpALaAWUEDrGlALqAXUAgW1gAK6oBOjw1ILqAXUAgpoXQNqAbWAWqCgFlBAF3RidFhqAbWAWkABrWtALaAWUAsU1AIK6IJOjA5LLaAWUAsooHUNqAXUAmqBglpAAV3QidFhqQXUAmoBBbSuAbWAWkAtUFALKKALOjE6LLWAWkAtoIDWNaAWUAuoBQpqAQV0QSdGh6UWUAuoBRTQugbUAmoBtUBBLaCALujE6LDUAmoBtYACWteAWkAtoBYoqAUU0AWdGB2WWkAtoBZQQOsaUAuoBdQCBbWAArqgE6PDUguoBdQC/z/YoOy0Pjk/gAAAAABJRU5ErkJggg==\" width=\"360\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_size = 25\n",
    "Z = np.zeros((data_size, data_size))\n",
    "\n",
    "fig = plt.figure(figsize=(5,4))\n",
    "ax = plt.subplot(G[0], aspect=1);\n",
    "fig.show()\n",
    "\n",
    "d = data_size / 2\n",
    "extent = [-d, +d, -d, +d]\n",
    "G = GridSpec(1, 2, width_ratios=(20, 1))\n",
    "\n",
    "for i in range(20):\n",
    "    \n",
    "    # your code here!\n",
    "    a, b = np.random.randint(data_size, size=2)\n",
    "    p = np.random.randint(2)\n",
    "    if p==0:\n",
    "        Z[a, b] = Z[a, b] + 1\n",
    "    else:\n",
    "        Z[a, b] = Z[a, b] - 1\n",
    "    I = ax.imshow(Z, extent=extent, interpolation=\"bicubic\", cmap=\"RdBu\")\n",
    "    plt.colorbar(I, cax=plt.subplot(G[1], aspect=5))\n",
    "    # end of your code here\n",
    "    \n",
    "    fig.canvas.draw() \n",
    "    plt.pause(0.25)\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b201f06",
   "metadata": {},
   "source": [
    "## Exercise B\n",
    "\n",
    "Now let's say that we have a grid with a couple of gaussians, and one of them is updated (its mean)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d81607fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define normalized 2D gaussian\n",
    "def gaus2d(x=0, y=0, mx=0, my=0, sx=1, sy=1):\n",
    "    return 1. / (2. * np.pi * sx * sy) * np.exp(-((x - mx)**2. / (2. * sx**2.) + (y - my)**2. / (2. * sy**2.)))\n",
    "\n",
    "x = np.linspace(-5, 5)\n",
    "y = np.linspace(-5, 5)\n",
    "x, y = np.meshgrid(x, y) # get 2D variables instead of 1D"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8de99c6e",
   "metadata": {},
   "source": [
    "- Write code that fills the template below. On each iteration you should update the matrix Z by updating the location of z2 Gaussian. As in the previous exercise, you can use `np.random.randint()` to get random integers that you will use to update the location of the Gaussian.\n",
    "\n",
    "- Use contour to look at the interaction between the different Gaussians. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "aeba7c99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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8TT8PqIiI5ApWw6k9c5E4aXX66HX6aDTavDsQTjdZs9XADny+6Jg8UCUqVoTXqlSmdkaKl41i0EtAJtsiZqWg1PIIUcOonvHLvhtyhg0bdlApJ6lK+kEJQ2dqOyOAdoxlzwDtGPi6tx7lQJnsXq2BLWEpKAUOB87ehqd23bDtPmzUK12XROYdQa5STWbQ5lT0ATM5PHIyAjs37IBIfv34EroSQrbkpWrwbd4KXhny4nUGTIirnVJPr59jUe3/8PDWzdw5dQJXDp9HL7+xVGuZh2Ur1EHGbwzmdSzgippuUlRi++rFDJ+tqAON69eQYcmzTFwxEC07dTMDNJSPOnYiSzJy+pggHbMJc8A7Zi4OvdepQA6PvVsUe8cl3KmqpkvnSOeNLl//FgohfPClUtRukIl/vlYS0MMZnJfDOYP795h84rF2L5iKfIXDUD5uo1RpGxFeKRKbSq10xNLRFTCIb5P7A7hRq0PPiGoiYrExRNHELp/N84eOYByNeqgXe9ByOTjYwI1UdRiBW1+n/ObiS/dsk59DBg+AO1+am5md4ghrYDWrETPum9HIkrvvpHNwQDtmEueAdoxcXXevUqBsy31bDMxaLukjqhnPU3wxdYs0995OF++fBPN6rbGghVLUKZikAnOYkuDAJkDM+c/aw1GkCneq+ZMw55/VqN01Zpo2LknMufOS6EsAJmAmP4IlR1xFEITOJv8Z3Kf/yEQjvjwHtuWzsfedStRqW4jtO3VH96Zs1AFzUFazoOaU9YE1NwP50uH3/2PQnrEuGFo1rqhCdIKWSyUrUvyYvt2cFZHEqpoB/vQDNCOueSTI6B9AKwE4M2fwYsAzIorPMWLsYkqIsloO1TihkhJpJ7FSUE9X1oXHv4cdas0xphJ41CncVMzOHMw5mwMAc4EzOT+8X3/Yubw/igVXBNNuvZFau9MdKxWb+CATMbRZkhCyR15jPuoYvUsVs7kPvl/xVVm8IAmapqAVimnyjri3RtsXTIP+zesRvNfe6FVt95QKZUUxoKa5sBsDmmipG9dv4YWdepjwYr5qFi5DIW0GMq0ukPUu0OYOi4oaROkE5ow/AYqmgGaAVqIQCYA5Oc8AE8A5wA0BHDdXogYoEWRsaWg7XWrs1W1YZEYFHenExJ/Qn8Ny6TgpwgtapSvizad2tOEIGd7KGltswDk2K2BqubPERGYM3oYLoQcR++JM+EXWJaOJWDW6UhFBwdnDtQcjG0paAHc5O0TGHNwFk1Q4QGtVMTCWqmQm0D99tljzB7Si8J85NylSJ8xoyRIhx4/jF/bdcbuozuQO1dmamkIkBaX34lL88wBTf/FmDdViq+igwHaMbT8BntNjgraMkzbAMwFsJ8BOp4zSIq9kQTqWQ+ufE6wOgRwD+w9Ch8+fMKcZUvpcwTQQkKQQFdDoMv7zQTO927fwpiuHZHTtyB+HTsFLilSUGgTMBO1rOUBrdOZK2gxoD++eY23zx/TcjqFUsWV2ilVSJUxM1zUaq5ig1ZjxCpoop5JqFQKspVBALXcaMCGuVNxaPM6jJy3DIVLBMJFIY9XSS+ePZM2Xdqydx1IQpEDs95ke0iyOuJT0d+4ooMpaMfQO7kDOgeAYwAKAfjIAO1AQFtUbognpMQ1GYVYGwTEe/89jCF9/4f9p47CwyudFZyJraGhSppTzjevXMaQ9s3Qps8QBDdvSys3BNVM4UwVNGdrUAWtI8DW4mboMdw9fwrP7v2HF+G3oddqkSazDy0RNui1MOj10MbEIOLDG3jn8oWPrz+yFfBHnoDS8EydlsKYwJpsOatDRkEtQJrcv3B4H+aO6IfOQ0ahTksyg1AGNRlj8qG5+2qljJbgwahBizr1ULVmMHr172LlR4utDgHedlW01MkrX1lFM0AzQFtGwAPAUQATAGy2EZ4uAMgPsvmkLx5+c4ljIpic9vql9kY8lRvixKBQtUHU88tXH1E5sAbmL1+IwHIVKZy1BqKeBWuDU85EQRM4Xzl/FiM6tUa3cZNRqnpdxPB2hqCadQTkIhX96slDhO3eiHN7NyNlem/kC6yMDDnzIa1PHnimzWhz/oY2OgLP7lzD89tX8fTWZTy8eg5+5aqibKP28MnvR5W1ShkLZmJ9kN9dVAoK7BfhdzGmYzO06tkfDdt1slLSRFlTn5ooZujw5OE91KlUBRt3rUeRInlNVoeUqg7JXrQUFe2gZCEDtGNAkFwVNFmfaCeAvQDibVPHPGg+G2brHJKSHEyEehZXbXRu3xsZvTNh5MSJVr5zrK1hpCC+cu4Mhv/UGn0mzULRSlVNloZGqzdTzTEaPV48CseOeRPw8MZFFKpUB/7VGiNN1jzcTEO+76jgSYs/usl7JrYGUcoyIPrze1zatwnn/12HtFlyIKhlFxQoXZEqZwHULqrY+2qVAq8e3ceodk3Qts8g1Gvd3gRpAc4E0Nx9rvxuw6oVWDp/IfaH7IQLsVFkOghVHcldRTNAM0ALESD/VFYAeAugr5SwMEAnENASk4NCG1HLsjqikIWqjbNnrtKZgicuh8HFNaXJ2hCDWVDOjx89RPf61dBzwnQEBFWjwNZo9NTGiNFySUFyP1qjw+kd67Fv2QyUafITitZsAYVKzSUNhSShsOWbchhF5XYyITlI1K2ovE6pUsCo0+J26H4cWz0P+QIroG63YXBzczOpZ2J5EDgTcJPty4f3MbxlPYz88y8UL1POzO4Qg5pCGjG09K5hs/ro0LmVWVWHkDC0VxttU0U7UbKQAVoKiRI+Jjkq6PIAjgO4ElsoiuEAdjMPOo4TIEnsDeu6Z3HlhlBWJ1bPLRp0QrXaNdC2cxeTeo4h3rEoKUhAHBkVjR6NaqBCnYao/3MPk61BlLMA5xitHu9evcSGKcPx4fUL1Ov3O1JnzsWBm4ezTmsAgbGB9OzgIW0rKmYqWi6HQiV4znIQUGsiP2Lfn+Pw/vkjtBo5E97Zc5nATJr1iyF95cRhzB3eF/O2H6C10mqFoJy58jsXYo/wVsfl82Ho3LINQi6fQEoPVQJVtIS66G9kczBAJxy+Ul6RHAEt5XOZjfnhFfSXVG9ItDeEyg2x93z61CV0ad8DJy6F0QZI5DmNXmYGZ0E9zxn7PzwKv4ch85bThCCBsSWcb10Iw+pxveEf3Ahlm3eFUa6ETqvnAK01QK/Tx9ZEazmYcbC2nvBNAE2UNFXQvJJWKhX0MaWKL69TynH1wAYcXzMfdXuMQPFq9a0gLXjSWxfOwtnD+zB74y64ql1MSUNBRYutju4d2qNQYT/0G9LdpKIFL1pyRYeTJQsZoBOMJUkvYICWFKZkPighgJbYsU6wN0xTuME3OaLrB3KVG03qtkPdRg3QquNPVolBAmYBziGHD+KPgT0xc/thuHqlpl4zB2c9NBpib+hxPfQE1k7ohwb9JyG7fxnO+uCVs57aH3oe0oJyNtBqjVfh1/DxeThZ9gRyhQpypQpKlQvS+PjCI403D2c5FLS0ToCzgipqUm7nolbi9YOb2D51EPyD66Nmp94U0gTMgidN7ytk+L1LG+QvUhRdBv/PZHWQx4VJLEJVB5ll2CC4Ok5eOIoM6VPaVNH266KdsyaaAdoxjGCAdkxcnWuvDrA3bLUOFavnq1fvoGX99jh9/TzkyhR21XNEtAbtggLRdexkFC4XhBgeupyC5kD98PZ/WNCvDZoMmY5MvgEUzBTQvGrWxJAudRyYP719hUeXjuL5rTC8Dr8Cj3Q+8PLOQxfbMuh1MOi00Gmj8e7RNbinzYKshSvBp3AleKTJSK0NAupYBa2Ai1pBQa2NfI81IzqhYssuKF2nqRmkKbBdFIh8+wp96gZh9qZ/kStvXlofTZSzLRU9pGcP+GTLjEHDelhVdJjPNtTyjZiE5bec0+ZggHbMJc8A7Zi4Otde4wO0vckpibA3BPU8fvR0xMRoMWLCBJveM1HPxHvese5v7Nu0Hr+t2kIVtWBtRMVwFsfHDx8wu1tTlG7cCX6V6pvgrI0hCpqDtFajhyZGgzsh23D94EpkyFsK6XOXQJrsRaFUk2pM7kYAbmqUZNTjTfhFPL95HC9unUa6nP4o3rAPPNKkA7E6BFCrXJQU2ATAH57dw9qRndF5ygr45CsAtQunpNXkebpVgFgdj27fwOh5SymYhfpoDtSxXvSFsOMY2L0PTlw4CKWc68FBKjoSlCy0Z3N8Ax/aWQHt6VXAqNNGSL4eoyIfksqwmpJf4OCBDNAODrBT7N5BgLa0N4TkoN6gQMlCQViwcjEKFg00q9wQqjfINiJGi/ZBgej5+wz4lixD1bNgbUTH6BEdo8OqsX2hVLuhRvfRVDWTHwHOgnJ+ce86zm2ZAYVSjYK1esItVVYKY6PeSD1oehMv980v4U38ZhltFarD3RNr8PjyfhSt1wvZiwZRNa1yUVA4E0gTJU3sjpvHduD05mXoOX8jPFOm5JQ0nzQkkIYmCt2rlsakVRtRoHBh+yoaMShXuCiW/L0IAcULfH2bI4nroZ0V0Ck8shv9SoyQfBmePdKFtI4oIfkFDh7IAO3gAH/z3TvIf7ZXvUEeP3niPAb0HIojZ0NggAv0Rhfab4PMFBQATdTzzvVrsGvdKkxYsx1ROg6+Ymvj0D8rELbrH7SbvApGuQs0MToQKGs13DYmOgYXdy7Cg3P74Bv8EzIVDIaerFlIEoR6rpqDQFpIFgrHQiizo3AmkFYpKKg/Pb+JKzunI7VPAQQ06EXbl9qC9L75owGjHq1HTIUrgbdKATcCcF5F/7tyEa6ePoGJf601qWjBixZUtEKmwbTfxiEq8jN+++N/cSYLieVh1UCJ+1DkawH3sSxL7syWx3L8SitOC+iU2Y2FyoyWfBmG7f2JAVpytJJo4A9dxZEkgI4trxNUstCQX1y9Idgb/XqMQPacOdG1X3+z5KCQGBS27SqXRpdRE+FXurxJPQvWxuvnLzC1Uy10mLwKnhmzUXhHR+konAVb4/T6qfj48iGKNRoGuYsnSLLQqNVzlRvkPl1yJbaawxLQpOEGAbNcJTeB2mjU4M6x5Xh15wyCe86HZ5q0FNJEQavUSmp1yIwarB7aDkGtuqBkjYZwo49zpXcE0gqDFt2rlcZvS9agoL8/tTnEPrSQLLx36zrtdnfpbhhUCs5jtmdzUF+aLj7LA1looMQAHScl3FPlMPpXHieZJCFb2jNAS45WEg1kgLYRSFszCO1WcHCNjyyb8gtTu4WudQKgib2xdM1fyFfQn6pn0hApFs7cjEHSinNohxZYfPQ8nS1IlHMUUch8YnDnkpl49/I5qv060mRtxERpeQWtx/3zR3Bp1wJU6DwXULhCF6Pn4CwoaFIHLSq1oyJTb6RAJjeTvUGX7pZTSFNQE8Cq5Lh9ZBmiPjxH+Q7joHZVQUUUsouS3yrw7L+z2L9oIvot3QV3NxcrFb1h1iTodVr0HPmbWV10bNKQwFiDCv4BWLxqAYoW802czSEF0PTD21DRSWhzOKuC9kiT01i0BukGIe12Ym1rBmhpoUq6UQzQFrGU0l5UQoJQDGhyn9gbz5+9RrmAarj68BaMMrVde2Pp9Ml48+YNfhoxngKb+M0E0sR7joiIwu8tg9Bq3CKkypwL0dGx1kZMlA4fXj3HvpldUKL5aHhkzGeCM1XNNhS0YHOIo0BBbUNBU1CrlbTbXOiq/shTthHylatr8qGJH+3qpoRKJceqQa1QrVMfFCkfbFLRbsTycFHg6a3rmNitA9aGXIRaqeBVdOzEFReFkQJ59KCByJgxHQYM6WpWzSFM/XZoud2PAOi0uYzFG0yWDJOjy5oxQEuOVhINZIBOekCLS+rEbUW3btqLtas2YuWmddAZ1LTfs3jmoFC90al6RXT+32/IX4JLDnKA5rahe7bh1M71aP3bEg7OxJvm1bMmWouDCwYiVWZf5C7fhiYMDTE6ztLQ6umWKmcDZ3GIfWhLQAsq2kpBqxVUSUd/fIyw1UNRudts2p9DsDrUbioK4buhe3Fp/2Z0m/k3tTdc1Upa0UG2xGvuXbMchs1cgCL7XVpMAAAgAElEQVTFS5hsDsHqEGyOY/t3Yc7UGdhxcKNdH9p2h7skqIf+AQDtmT63sUSzqZJJcnh+IwZoydFKooEE0GHHp2HztlPIkN4LJYvnhaurSxLt3cl344AKDssEoRjWwwaMR3pvb3TrN9Cu/xwe/gBd6wVj5amr0BplZvYGsTlmdWtGy+pyBFQy856Jer52eCPCz+1D6XZToNPLYIjWQc/bGwKcBRVNAB3x/gFehh+BTEZ8Zhda6aF08UR6n9JQuLhzVRx8olCwOYiCpvddlXhyaSeeXTuC4B5z4OqmhpqoZ15FK+QGLO5RF+3HzkPOgv6cilbJ6ZYAe+OcP6CNjkKv0RNMNoe4Llol1yEm+hOK5syLC7dOI20aD7Nm/klaD+3g9qPOanF4ZsxjLN1uhuSLdP/UegzQkqOVRAMJoI8fmIRRv63BkWNXcOO/xwgomgsVyhVE3VolEVgiL+T2kmlJ9B6+2W4cCGhbCcJm9Trg525dEFSjlgnQgv8s9N/4d+tmHNi2CUPnLTdVb0SRygyNAW/fvMX4ZhUwcF0InRZOKjcImKOpgtZh+/hWCGgyHCnS5TJZG/pocxVNVbNWj7fPLuLe5aXI6BMMuUINg4H0g45B5OfH0Gk/w7dEX6jcPLkqDh7SClcFZKQOmmyJH+0ix+kVfeBfpyt8CgZSFe3qpqKgJmV3p9bPA2lFWrfLQCub48GVC1g4ZjAW/3vUrJrD0oduUqMWBg7vh8pVSpt8aHv10ILlwZ1PvIqW4kP/oID2ypTXWL7zHMmX367fajJAS45WEg20tDg+fYrE6bBbOHzsCrbvCsX79xFoWL80GtUrjUoVCtGJCt/N7UsAbaP/s9k6g/zKKUL3OrINKlUb0+bPQsGixe0mCJfPmob379+h7aBRVv7ztbAQ7F40lZbWie0NUsFB6p1PrhyLSt2WQEusDJF6FqtoAudn9w7g6Z2dyF24Gzy8cpvVQRvlMjy+swEf391AgcABcEmRisJYSBIKPrRCreBU9MUd+PTiLsq1G2FSz6Siw9VViWc3wnBywyL0mL2WV9BcyR2xOaCNQfuSvth2+S483FOYfOjYig7Ohx7Rtzfy+eZG1x4dkm2i0FkVdKrMeY2Vu82XfDlvGVmNAVpytJJoYHwe9H+3HmPL9tPUAnn2/B1+6lAVnTtWg0/W9En0Dr7hbr4yoP1ylMSeE/uRPlMOq+ndpA6aJATH9+uBvP4BCG7eDlF8UyRSXkf85wNrl+LFw/sI7jzMDNBERV/asxIR714jf3AXk/dsqZ71Gh0eXFmL9y8vI0+RXnBVp4udrGJmQgPPHu3C2xdh8A0cBNeU6a0B7aqgCUOD7hOOLfwF9YavhzuZnCKyOeRGDeZ0qoyRm0OR0tPdzIdWK+UY2CAY/SfPRJGA4mY+tLgeevmC+bh94wamz/3NbDksyYlCKQqafHYHVnI4K6BTZ81nrNGXrCst7bZuYJAUQJOZhmShaqLkyEogkyz27gvgLwABAMgsGekmuGW6SNrbTt6j4gO0+NNduRqOhcv2Yt2G4yhX2he9u9dDlaAidE27ZHn7ioDW6eXI7JUX914/gEwZ271OWMqKbMmElJ5N66JlzwHwDSxnlSBcMW4AshQohkJVGlFAE+UcE62lQN47uxdyl2kGL59i1N4gClpIEArb8Mtr8fntHeQu1ANKuVu8ScLnTw7g5eNDKBA4ECnSZokttSPqmXjRrkoo1Qpc2DgWOYpXQ55S1SmgSekdqY0mKvrvoW1Qt+tQ5C9emqpoYdKKm4sCf47ohwL+AWja8WebiUJSanfq6EFMmzDZKlEYfxN/50kUOiug0/rkN9YZLH01pZW9KsQHaALlWwCqAXgM4AyAVhaLVmcAkJ1fzPodA3Q85EwIoIVdRUREY+2GY/j9jw20p0Sl8oVQqWIhBFUohHx5syQfYH9FQH/4GI2COUvi7stw6Ixqk4IWZhAKFRytKpTAqEV/I332XCZACxNUZnRtiqD2fZExb1FTgpAAmijof4bWRHCfVYDCzQzQxN6gsNYaELbrVxQu8xtULqlMddFUPFq0HBXXQT99uBMazRvkKf5rLKB59SzYHM8u70bEm4co02qQlQ995K/JyJAlG4Jbd+arOYjNwSUK965aTL8R9J8w1SpRKFRyvHoejprlquDag/PJtpLDWQGdLruvsdH/lkvWVot/KR0foMsAGAOgBr/TYfx2oo0/QsZ9ZoB2AKCFXRqNRty7/xxHj1/D0eNXcOjoFaRIoUaj+qXRpGFZlAjI49yw/oqA1upkyJQyDx59eAqDzM0uoNsHl8Wg6QuQKa+vFaBn9WiJCq17wDtfMVP9sxjQ1fqtgUHmAl2kllZvmBQ0D+jTOzqhROU/AT0HZbN+HATS/GoqYkB/eH8dLx4fgF+ZgZwXrVbSJCHd8j706zsn8fLWSVToONaknkm5HUkYhm1aBLlRjzpdBlAwu6q5xknk/qldW3D+yH6MnrfEbiWHThuJfBmy4MnHe7RxEqnesOwP7bBSO3KiJ0G5nbMCOn2OAsbm41ZKBvS89iXjA3RTvplSZ36n7QCUAtCTAVpymM0HJkZB2/tTBNjnLtzB5m3Esw5BVJQGLZpWwC+dqiNvnsyJfIcOfFl8gCZ/2nIGIfk9jokqQpmdrSqObOkK4NLdq3D1SGsGaGHVbmJxdKkbTKd45yhU1ArQc/u2R6mGHZClYCkrQG8YXgdVei3nFLQNQBP/OZQAOngxoIvtxUHVs1hBiyBNEoIRkY/w4OYKFKk0zgRoU6KQB/XHZ5dx7/QGVO0+w5QoFAB9Ze86vH/2AE37jzWr5CCAvnLiEHauWIxpqzfZBTSBb37vrLh0JwypU6X48lI7sz4cwtRwOx70dw7ojLn8jG0mr5F8gU1vVvQBgNeiFxADW2xiN+PVsxjQgQB6MUBLDrPjAC3eM4H19RuPsGL1IaxcfQh+BXzwS6caVF07TZ11YntxJBLQJEm49+QBpPf2oVUc4hVUhCRh9yZ10KrXQBQILEeThOJJKgsGdYZ/9SbIGVDRzIMmFsfG/9VDUPclkCndqcWhj9RSG0OwOHTRMTiz+1eUCF5omlFopaDJAeRXU6F3VXJotO9x49wkFK823S6go9/fx5Xds1FrwGIrQN86sQvhF0PQbtQMq1K7h1cvYvG4YVi065AZoIUFZUktNAF0ab8i2LxnLXLnymK3J4czN01yVgXtndvP2HHaesnkmNSwcHwKmlkckqMpcWBSKmh7f1Kj0WLbzjAsXrYX1248RPMm5WlysWK5gvDycpf4Th00LD4VbUtBU3rJeXVt3YtDPDlFfL9UkapYsvov5ClQ2G6Z3YB2zVC9RTsUr1LTqopj6YgeyFemKvKWqW4CNGmQRAE9siEq/jIbMpfUVh40AbU2IgpndndDQOU5kEFp8qAt/WfuSwPfalQug84YjUsnBqJU7UVmFodQD61IoYL283OErf0f6o9YawXoBxeO4dK+Dfhl8lIrQL95eB/ju7TG38fOwY2s0GLROEkAdK3ylTBl9iSUKFkwzlpo86ZJCWze78BaaGcFdOa8BY2/zt4o+cIaXatAfIBW8knCYABP+CRhawDXmIKWHOavo6DtvZ3zF+5iz4HzOHzkMkLP3oKfrw/q1g5EkwZlUMDXJ5Gf4gte5mBAi6d6d2zVEzXq1kLDFm3MJqoIk1RIonD2+DGQq1Ro0WswreoQ9+HYtXQOPr1/h6COAzhARxM4c02SDi4YCu8C5ZAxf5B1mR0/3fvGyanw8MoDb59aNluOCq1GKaTJLEKVAq+eHsP71xdQoOwgu0nCj0+u4M6J1ajWa46VB30nZA/unjuK9qNnWQH61f07mNyzE1YcDo0T0A2Dq2H07/9DmbLFEgBo6k9IbztKhjuo1M5ZAZ0lXyFjnwWbJV88g6vkiw/QZF+1Aczky+yWASDdmLryf2QBAG8AZwGk5Be2JolCPwAfJb8RfmAyrR1L2Mf8Ggra3juKjtYg5PRNbN15Glu2nYaXVwo0blAGLZtWgF+BbAn7IIkdLRXQnLSM9aTjUNAClI38WoRCs6T5s5fj9q37mDRrulkvDnGr0aP792LdwrkYt3Iz7XJHpncLjZJunD+DTTNGo/PMDYimLUZJBQcH6BvHtuPxtVMo1mg4rfAQJqqQRCGphyYqOurDS1w7MQFZcjVAWu+yJkhTNvG9ocUd7SIiHuL25dkoUHog3FPliJ1ByPfjiKuKg3S4I0nCi7v/RuTbF2jUe6RVkvDB9cv4c+QALNp9xCaglXKuq13j6jUxfMwQlK9QXNJsQnqoaOtRBui4Lguf/IWMA5Zsk3zl9K2QWwqgJe/vSwcyQH9pBBPweoPBgLCzt7FxSwjWbTiGbD7p6aSYFk3Kw9MzRQL2lIihUiEttjvs+NCWswnF7UbPhl1Fn+5DcTD0OF081rJZPwHy6zdv0bRUYaw9dwsGuQJRZKUU2m5Uj88RURhZryR6Ld0LudrDLFH48fUbbBvfClX7rqKd8uzVQke+e4zrpyYjW75WSJ2+OBcs8Yoq5HeFHJqYd7h5biKy+7VB2qwlud7QQh8OvqudUAd9c/98pM6cE36Vm3HTvF2UdEvqoI+vngVPr1So0aG7qcxOqOK4de40Vk+fiHlb/rXpQQuAblarDp3uXSkoMF5AWzXvl9q4/wdU0Nl8CxtHrNwp+YL5NTA7A7TkaCXRwG+poO19BLKe3p7957F0+X4cPXGVetYd2wbTsj2HTDVPDKDJm7ejom01TCJAjtEYkTtTEZy/dQkeXunsJgrbBZdFr99nIFfhYlY+9J8DOqFI1UbIHRjM1UKb2RxDkCFfaWQpVM1KRYs72n1+fR83QqchR4HWSJWuOFkz1uym1X7AnUtzkdo7AFnz1bM51Vuo5CBKOfTvQShS8ydk9StJe0KTiSqk7Sjpardn3kjkKVoK5eq3sGqYdOXEYexcvhDT1myOM0nYsk599B7UA1WCyyQtoCmUHV/J4awWRw6/IsbRa3ZLJkmnolkZoCVHK4kGOiOgxR/t+fN3mLNgJ3buPoNHT17TyTDBlf1Rv05g0k43t4S0rab9ibA5BEUt2Bxtm3VFxSpBaPdLV7sd7eZPGo93b9+gy5g/TDaH0DDp2Lb1CNu9EW0m/EVbkIobJj2+fg4nV41Dpa7zAYUHXUXFZHHouHajQtvRT6/v4M6FxZDLScP9VFAo1JDLSRdDI96/uoQM2SrDx68p5MrYFVXMOtq5cl3tNB+f4tTKQag3Yi1SeHrSGYRCy1GioFcMbIX6PYajQInSVo37Q3ZsxPmjBzFm/tI4y+y+GNDkuJF6Zsulr35wQOcqWMT4+4Z9kknS0s+bAVpytJJooLMD2hLWB49cwv6DF7Fzz1nkyeVNJ8SQn1w5Se7hC26JUdGJsDlOnbyA7p0H4MSlMEDuatPmePb8OdoFlcLCg6FwTZnKrB46KioGkzrUQvVfhsCncBmrntDnti3A6wc3UaLFOOj1iLU6CJxFkKarq+h0+PjqFvTaSOj1MTDoYmAw6JA6UzGo3dKalryy7AktVs9Xdk6Dl3d2+NfsYNUTWmaIxuyOVTBm6xm4u7uZenHQdQpdFNg0fwb0mmh0HTY6TkA3rVkbQ0YORIWKJawUtAx608QVspCATYuDAdrmhZG7kL9xypb9ki+axnkzMEBLjlYSDUxOgBZ/ZK1Wh8NHr2DTtlPYuv00cmTPgI7tgtGqWQWkSuWRuOjEBWlT9zrpyUJ75XbBZRtg4IihtO2ovWWvxvfrDu9sOdG4a1+rtqOh+3biwN9/4qdp62jDf2HBWDqrMDKG9uXw9i2LHCUbc1YH392OKmid+dJX8S4cy7cbFXezI9UdpAdH9IenOLViIGoPXgWPVKlMS18J7UafXD2NU5uWoNvM1Wbd7OgCsko55g/vi8IlAtGobUfai0OofxY62glldraqOGQyA9c8KSGAFitmW2raQT60s1oceQr7G2dvPyj5WqmdMx0DtORoJdHA5Apo8ccnnjVR1cv/Poh9By+iVrUA/PJTdQRVLJzwqeZSrI4vTBYuX7oB+/ccxdJ1q+wmC69fvYKBbZpiyZGzMCpVZo2ToqK1mPZLQzqrMH+5miYVTZomkcqO98+fYM/MX1G6zW/wSJ/HBGnB3hA37Zeyqoq4ab/QelSplOPqrunwTJ8FRWp2NC17JdgbxH8OWTcPKpUStTv3M1s8lq6uopBjVPvGaNOjH8oEVbFaPJbAWgB0nYqVMWnGBJQMLJS4lqOCgk4soMWvT8R156yAzle4qHHh7sOSP1Fln9QM0JKjlUQDvwdAi0Px5s1HrN1wHHMX7ER0tBbVqxZDjarFEBxURLqyTgykKbTjnrQilN99+BiDEn5BWLVpDQoHBNpt3t+nTVMUCAhEk279rEvuzp7GyrG90WHySnikyyKCNLdG4b2zh3F28ywUbzYcXpkKQKczmFb2pkqa78VBl78S7vOBFJfama1NyPeFJnB+9/ASLmz9A7UGrjBTz9wCstzPioEtUafrEBQoWc6sgoM8RwD9S6UATF27FTlz57a77BVRyTXLVcT0eVMQULxAwgEtQPlL2o5+p4DOX6SocdmeI5JJUi5zKgZoydFKooHfG6CFsJCp5jduPsLeAxew78AFnDx9A6VK5EOTRmXRuH4ZZMiQKu4ISoW0oKbjqeiw7M2xZeNejB89BftCDsPVPbXN5kmPHj3CL3WqYNicpchXvJRZA3+ywsqhDStxdP0ydJyyCgo3L9MK31qyAniMHuEXTyB0/RT4FK2KvBXagtRlE1DTdQn15v04LBePNS13xS97RUrviM1B4Bz94TlClvdHmTYjkdm3hMl7VigVNElIVlN5/+gWNk7sgyGrD8FNrbJKEGojP6Nj2cLYef0B3FxUUMllZjMJhW52UgAtB2932PKg4wO0WFXbszi+U0AX8C9m/Hv/MckkKZ7BkwFacrSSaOD3CmjL8ERGxtDSvY2bT+Lf/edRzD8nbeTUvHF5pE5tx7NOAkiLqzgsJ6707DIERqMc0xfMtZq4IswuJBNXpgzpixlbDyBF6rTU6hDqosl2+8LpuH7qMNqMXwaZytUK0hHv3yJkzWREvH2OgMaDkSJNNg7S4m52PKzFMTPNKlRwVRwKUvssl0Hz+RVC1/wP+co3gW/FRlCQKdpqBS1/FKvng0smImWadKjZqTfURFET31kl57cK3Ll4BssmjMSCnQdNS14JHjTZigFNpnpPm/uHXQVtH9CUrLHVG1IqORwAaWe1OPz8ixn/OXRcMkkKpfVggJYcrSQa+N0BWlzXaidGpBJi78FLWPvPMaqwa1Yrhg5tglEtuKjtOmsxqG2V3wkzDG1UdZDyOqNRAfGUb+H+x08aBJWqi2Fjh6N2w2Z2y+7mTBiD/y5fwuhl66AzwjR5hZTZxWh0WDNxON48f4xmI+ZCD7kJ0qTMTqPRQavR49bJHbi4axFylKiNHCXqQeWWmkJa+KFc4mcTkvuCzUGgTH7Ix35yaQ9uHFoB38qt4Ve5OfWdlbyqJstcEetCSZKKBg3m/lQVvRduQ4YsWam94eIi57Z8gvDA+pW4e+Uihk2bS5ODxPIgK6ko5dxWRSbGgGuWRAA9dc5kFC/hZ3NVFQJoLmmoNVVx0M8gnk0oVsGWCULLcyaJ+3I4K6ALFQ0wbj16UjJJ8ni5MUBLjlYSDfwuAC0ByvbC9fbtJ6zfdJJ23Xv67C1aNa+EOjVLoGxpX3NY21PT4oShjVakFNDEmzYqKIANkIOoauH+2TPX0bLRz/hnx0bkL1TUZlVHtEaDHk3rIU/hougwdCy0BiOd/k0UNIE0+YezeFg3Og29Xt/xkKncTJDWaQ0gDZXI9sPLp7h2cC3Czx9AhtzF4FOsOtJmD4BcrgCZyckxjJu1QqDMbeV4//QGbhxcDr0mCoEthiBt1txUOQtwFqwNYn8QSF89tAX/hRxA5z+WmqBMVvTmQM35z4vHDoFPzjxo2aU7LbETwGwL0JZJQlJOZ9kTmgCaADneUjuxpfGVWo86K6ALFytm3HlMOqCze6ZggE4i7kreTbIG9BeA2VaALl6+j01bT+Hffedw/8FLVA8uigZ1S9HVzT083LiX2FLTlpAWxokSh4KStoQ0mWG4ecMeDB0wGsvWLkdAqXI2If3i1SsMbNcMPnnyo9tv0+g0cDGkP3+OwIbpY3H7XAgaDpwM77yFoeEnsggJQlLtQkAd9ekj7p7Zh/tn9uLT68fwTJcV7mmywD1tZrinzgRN1Ed8fvMUEW+eIOLtExgNehSo3Aa5S9eBi9qFWh5iOJP7VD0r5dBGf8LiHg3Rbtx85CkSABWBtoW9QRTz6PZN0LJbb5SpXNVUA00etwXo1vUaoFufX1GtRnkzBc3VPGvJvzyqoO0CWoCyvUShGNrCiZGEKtpZAV2kmL9xz4lDklmR2T0tA7TkaCXRwGQL6CSGs2U4iZrevfccXTD35OmbqFbFH00blaOwdnd3tQ9qyxI8G5AW2x3Cqt/7955A9879MWfxPFSsWsMmpD99/oRhv3SAETIMnr0YcrWbyZOmsNYYcObgbmyaNgqB9dugdOOfSW9+6jkLP8T2EEBN1HLUh7d4/+IhPr58hE+vnuDz26dQp0gJj7RZ4JEuK1JmzIqU6bJAqVJRMBNlTYBMtkQ5C6Am1gZRyXsXjIdCLkOT/uOoYlYS64K3N8h9qqIVcnQsWwhztu6HTzYfU4LQHqD7/tIF5SuVQdsOTUxWRqzvbIAC2jgATb8X2Pah7alp+rjF/HfhBEnECivOCmj/gCLG/Sf3SCZJBrfMDNCSo2V/YHyr6pq9MlkC2sFwtgwtsUG27gzFP5tOIvTsbTSoE4j2baogqGIhyJWkBS5/I0atLcvDogTPcvq3AOxTJy+hfctu+H3aJNRu1MQM0kLSMDI6BuMH9MaDO7cwcvFquHmlNkFaSxOIBrx4/AirfhsAUslSu+cYeHlziUE6acVgNJXcEVuDJgx571mwN4Qe0UKi0GR3ECtCSeAsNyUNye8EzkqFDC/uXsOGCb3Qf+lueKZKTZODFNC8vUHGkgkqMRGf0alcEey4/pD+LlRw2AP0xJEj4ZXKE30HdzetSygGNJmsYitRSI6KZB/agSraWQFdNKCQ8fAp6d3sUqtZN7sv5bOUVXWTN6C/MpwtD8jzF+9onfWqNUfw5u0ntGtdGW1aVIJv/qyQKUj4CRXiBrXgS4uXx+KUtBKXL91GiwY/oe+QfmjzcxcYoYLWoIS4Z7RWb8Dc38fi4PYtGPHncmTN50dL8AiAdXoD9aVJK9eD65bi4N8LULRqA5Rt1gUu7inN1DSFNV8TbelBiz+32I+mKtoEaqKmOTgTQC4b0AoVmnRCiZoNTeqZQpkkEqmSVlAY37t8HgvHDsXCXYdNCUIOzrYtjqXz5uJheDgmTh9j8p4VJCEomk3ozDaHswK6WICf8VjoP5KZ46kqxBS05GjZHpiQJWfoHpKVgnYUnBOzX5kcl6+G469Vh7BpawhdLLdB3dJoUDcQpUsXoCrTBGqxqlYQxR07oUWcMBTu377zBO2ad0eOXLkwefZ0pE6f2WbPjl2b/sGsUUPRoGMXNPylF6BQmFkeOp0Rb16+wK4lM3H5yL8o3bAdStZrC4U6BaecjYBOy6lqcTWHoKiFU4wAmdyEig5hy6lpGYXvoRXT8Sr8NjpNXAy1i5J6z+RxpVJmDmuFHKf37sCJnVswbtFKm4COhTVX33xs/x7MmTYD2/dvMFPK0hOFNmwOe/aGAyo6nBXQAcULGE+GrpaMHDdlgBRAx/cNnpxMs/jG/pEAOgI4L/lNiAYmx37QCVlVN3kBOjEQjeuoJ+H+iJVw/uI9bN15Btt2huLd+wjaIrVVi0ooTlY2FyaxiMvxeNvDnpqOjDbg93FzsW7VZvw+YxJq1m9k5UsTVf3o4UNMGNgH7968Rr8/5iALWQ1cz1kXpMqDqG3iTT97cA+7l87CzdCjKBxUGwE1WyBdtjxUcVM4k7Vj+fsUZ6KFZGMVNA9qMmlFBs7ukMlwO/QQ9iyaiF5/boZXmnQiOBNIy0yJQhXfb+PI5nW4FhaCYTPmSwJ0TNQH+OcsgEt3ziOVl6spURifzUH/qfDJQ+pDC1D+yslCZwV08eL5jaFnyKIn0m5Kebn4AC3lGzxZcYUsIku2ZMVvAmuyTfAtOQJa6qq6XQCQH9IYv3j4zSUJDs5XfUESwtSs/6+9D5HYv8cr5es3H2HthpNYt/E47QXSqnlFdGhXFblyZYpdlUUoyROB2tKbJrZHSMhldO88GMUDS2DsHxPhmcobBihpkyTB9ojR6bF1zUr8+ftYVGvaCi16DoDCNQUtxxPbHgTar589wYlt6xC6az3SZs6OgJrNkKdkJbi4ecBgtFDSojwZX3UXq6JlMkR//oAjq2bj5qmDaP/bn8ju509Vs1g9UyhTJS2HAOi9q5fhyb3b6Dt+CgW0pQdtqaCJj0wqOX7q2hG161cz86Gl2xzfTkU7L6DzGc+eIatQSbvJ5FXiA7SUb/ALAZD55Wv5v/ofgCAAz6S9i9hRyRHQUgJkFgentzgSC0tbRzuufSX2OVt/hwc1UdbnLt7HqnVHsfafEyhUMBs6tauKJo3LIYW7Wyysie0hI7aHEgZjbJ00mR5OIP3xswZj/zcDO7bswe8zJqN63QY2E4jPnz/H7HEjcf7UCfwy/DeUqlGXQpqoaAJnUumh03NJwpiYGFw6ug9h/27C/StnkSVfYeQNrIQ8JSohTeZspiIGAm1OiYouB6MB5/duwNG/56FIUG1U69gb7l6pKIhJBYcAZKKexb8TQJMKjs0LZyPq0wf8OnyMCdCkvC4WzJwfLZ6ssmjWTDwID8eU2eNt2hxcmZ1161FnUNFOC+iAvMazp2dL5qLMpVZ8gJbyDZ4s4TIJwAn+D5N2ekP4dfozj2kAACAASURBVAolvxcyMDkCOiGr6tJg/DCATiiAbY1PaImVqGY6RqPHjn/P4q+/D+PEqZu0gVPL5pVQu1ZJuLq5crCOB9THj19A764jkSNnDgz/bQzyFfQ386Z1BgM0eiNCTx7H1GEDkCpdevw8bCx8fAtRtS2Amtga3H0jtTiiIiJwI+wkroUcxH+hR6GJiUbG7HmRIUcepM+eF+oUHvj87hU+v3uDiPdv8PTWVXimSYe6Pf6HzLl9TT40gbHgSXNbzt4wKWg+CbjxzxmI+vwJ3UaMjRfQXK2zDvf+u4YWdRsj7PoppHCVm5XbObuKdlpAF8ttPHtyumQoylI0eADgtegFiwCQH+Em5Rv8LgATLQA9GACBf4JuyRHQ5APaWlXX7gd3akAnlXq2tx9bj1s+Zglle/Wx8Z1aggKVy/H27Wds2hGGdRtP4sLl+2hQpxTatqmCykFFIFe6mGBtS1FHRQNLFm3A9Ml/IrhGVQwePQLpMuawsj0iYzTYtPIvLJ85BUXLVUC7/sOROlNWu6DmfGgjSKnexzev8Tz8Np7d+w/P799GTFQEPNOkh2fqdPBIkw5pM2dDjkIB1L4hyprWRPNwJr9zyUNQS0MANrU4eEBfOnkE6+ZMw6xNu02qmXsutpJDbHMIkO7UrAUqVC6Prr06mTXpF5KFtlQ0p7QI5LmJLHF60WRwQvpEk/ES/mk7LaCL5jKePUrErLSbzKt5fApayjf4H9rikBZp0SinBfTXhnNcYLaEslWmX7Sunb0jYNXwn/v///TFe6zffBor1x7F+w8R6NA2GB3bV0OOnJkAuZJT1ZDTEjziUeuMLnT77n0Upv2xBCuXrcdPXX/Gr336wTWFFy3JI4vPCv70h48fsXL+HGz+axGqNmmJpt36IoVXaitQ60nJHVllRajo4P1o8jjHIeuJG0LyUAxnU4WHyN6gkOYBTQCui45E21IFsfH8f/BwdxepaA74YqtDsDkIfO/cuIKmtRvg5IVjSJfWI9moaKcFtH8O45mD4yQzQ56ufXyAlvINvg6AnqIkIfFYAiW/CdHA5KqgE/RZv2tAS1XO4nFiRSQGs72+DVYKOw5YiyEtbqxEqztkuHDlAZb9fYQq64CiudG7Z33UqhXIqWpaCcLVSotBff/+c4wdORsnj4diyKjhaNKmLYwyV2j0MhOkCayfPXuGJdMn49COrWjQ8RfU69gVLinczUAtKGguWchBWVDW8UFaUNIcoDnPWvCfBUArRPAd1Kw2Og4YhpIVgqxsDlohYuZJc+qXWB0j+vWDWu2C8VNGxulFS66LFqtgW+rZ7LjbmV0Yj5J2XkBnN57ZN0oyL+QZf44P0Pa+wXfl/wjJSBKuzgVAyvFImV2nxPjP3DejH+DmlIBOCvWcVHC2BWbLMi3xV2N6P44LmZ5ZolPLRie8aI0eG7aHYdafu/HpczR+7lAdrVtVRtZs3rxPzYFab1SbgH069AZGDJpEGyeN/WMCSpYLsulPh9+7i0VTJ+LMscNo13cwqrVoTzpZWIGagJn41AKo7QFauETEpXi2AE2ep5YHD991sybj0/t36MNXcgjVHGRrS0ULgH7/+hkqlSiHrXs3wdcvt9XEFa4fh+3p3+S9SrI67P0zjuvYxmF1OC2gi2Qzntk9VDLl5Fm7SwG05P196UAG6C+NYGJf/6WA/hI421LNwv7srsrBA9meEo8rDqZG/6IZiHwJHum5EXLmLpavPYbNO8JQqXxB9O3dCBUq+kOmVJkUtQBqncEFG/7ZizHDpyGgZABGjB+LTD55Tf602Pq4cfUKpg7rT+uf+06eBe8ceUCSjKTqQ5gOLpTdEZtDrKrtfZxYSMcqaHHSkEKaB/DH1y/Qp34wRsxdioAy5Uwq2hzOXGUHgbq4omPt8r+wfOFS7D66A+5uCqe3OpwW0IV9jGd2DJB8lcpz9GWAlhytJBrodAraGeEcF5jjg7elurY8buJZhlRdE3+A2Bn8TETiQ8vliIjSYeX6E5i14F+6QnafXg3QskUQtSmI9SF40zqjGp8jtJg1fRUWzluBX3t1RZc+/SBXEjtDTv1pAdTRWh3++Wsxls/4Ay2790Pt9p0hkytMoBYa+9sCtX1Ic88IFge1PPhEIvGhic0hqOgLRw9g7siBWPjvMaRJk4YDMZ9IFHxoc2DzHeugxa9t2yFL1syYMHVU0lgdcX0rsso5JKyRktMCumAW45lNvSWTRO47hAFacrSSaOAPAei4knqmC9NCBdsCr8mjNNpfpUM8hhYFiDxpe1+DeT+azjgULBDB+uBL76gtIlfCIJNjz6GrmLngX9y68xz/G9YCHdpXh8othQnUeoMapIb6/v1X6NtzHJ49e4Vp82eiULFS1PYQT3Ih/vS9u3cxoV93qpL7Tp6NDNly0vtCaZ7gRZOSPFPSkP+mYfmRhI8g1E1bV3fIKKQFK2PZhP/h1dPHGLNwpWkii6CyLeuiOVhzXvT7t29Qo2wFTJk9CdVqBSXI6iA2Bw2z1Ib+tv7JJqDbndMC2i+z8cy6bpJJIi8ykgFacrSSaKBTAdoR6vlL4SxOHAkXJXnMcvkk8hj/PIWyQC7xfXLM4oG0qd80NXLJclNkqzCrk6a/K5Q4dfYeRk3ciPsPX2Hk8FZo06YalGo1jDIXuoQWUdV6gxJr1+7FyCGT0bhlEwz43yi4uHqZqWlSO63R6bBuyUKsmDUF7fsPRc3WnSigyY+ewJpfJstSTdv6SGJIE0BTRc1PYBGqPARI6zUaDGpWC7VbtUPjDp1N/rNQdheXH33m5FF0bd8ZpGVmlixpHWt1fIGKdlpA+2Yynln5s2SSyAPHM0BLjlYSDfxuAC3Fd7blEYuhK1ZKVgDmVbP4qzCFMgdmm1AWQTo6SoNth2/i8s1nuH7vFaoE5kSv1qXx8+ituHHvFbw8XVEwd3pMHVQb1+++xKcoDYr5ZYGLK1/BoVTGwloov+NBffTUbQrq128+YeH8XihfwR9QulC1TPxpYnu8ePEZfXuNw7Onr7Bi4zo6ZdyyJI9YH/fu3MbAts3QafBIlK1VP0kgTcIal5J+8eAehrdthKade6BFl+5WkBa63HHWiPkMw5mTJuHE4aPY9O8/UKuMcfbp+FZN/Z0W0PkzGsOWdZBMEkW5PxigJUcriQY6DaC/pnq2VUonwFaQhJbKWayaRWDmmM4rZtHWqNfj2Jn7WLA+DI2r+KJuhXxoO2ITiubNCL9c6eGbPS0K5kyLC/89R7RGh3efovEpSocW1fywYudlzF4XhjuP3yGwUBas+aMFPD3VUKpdoHRRkS5FXGtTEaiNChW2/HsRvYcsR93agZg8sTO80qY2U9NavQojhs7AwX3HsWbbBqTPlMNkeQjeNNleuXAeg9s3x8wte5EuSzYTpLmqDm72IdmKk4fC6UgeF5KFnHKO35Mm0H3z7ClGd2yKKg2boWPfQXYhLdgeCvLFAjrAqEH7xk3hV7gAxvw+zK4fba+p/xdZHRJtDqcFdL4MxrA/W0kmiSJ4FgO05Ggl0cDvAtBJoZ7FnrNEONsD84tXn1Ct81+0YX7XJsXRtlYhpHJ3Adcyjvek45uBRtYCjNAg5MoT1CiXB+sO3MDgWQfQurY/2jcshsJ+WTlQkwUDFCqu/E6hwvsILYaM/Qe791/ArGm/onGTSoDSlbc7ODU9bcpKLFu0Fmu2/YPsefxsQvrvBfNwcMdm/LFuJ923UOEhWB2CHy1Ud3D/12wnz2xVd5Dp34LdITRR+vD6JUZ1aIqy1Wqh8+D/QcHXQsc3y/D9mxeoVSEI46eMRZ0G1W360d9yaSynBXSedMawWU0kk0RRZyEDtORoJdFApwC0o9WzVGsjLlvDpJotLA2djkKXKOZV2y5g/tpQHF/aAWeuPkGZgpkgI8yyVNhi41aKJ8370Tcff8Dfe69h9d5rOLy0E9Km84RrCleo3NSQqVScoiaTWhQqHAu7i1/6LKHTx2fN7AG1uwffYMmNQnr5X9sxfvRMrNi4Gn7+pU12B6ekjYjW6TGofQtky5sf7QePMlPRXC9pblq45aQWe6dlbC9p6woPodMdsTAi37/DqI7NUKxsBXQf+ZskSJOk4aWzp9GhaRvsPrIduXNnsbk0lrDyytdeYNZpAZ07rTFsagPJJFE0WsYALTlaSTQw2QPaFtztJQYtrQ2xUrbylkWesy0482Am8H375hM6DN+EZ68+4s9hdVAyf4ZYtUz2KxprU0XHBWkezrQGjdxXkpXBZZC7qDBn03nM/ecsxvetjqa1/SFTq7n6aB7SHyN16NRrMd59jMKOrePg7pUSerhCZ+AgvXXrcfTr8T8cOH0MaTJkQ4xeQeEs2B1kodr2Vcrgj3U74J0jN1XRMfz6hmJAk6ZLcc04NClovtwurtmGRC1Hf/qIMT+1QPY8+TBg8iy4ql1MK3/HVdmxYuGfWLfib1ofTRoqEXCLVwC3N4EldvIK/c9pv0JHuOYSmDB0WkDnTGMMHU9mXku7KdusYoCWFqqkG/XdAzo+9WxpbQjVGHY8Z6MYtvS+EReuP8HaXZcwvmsluJCiBUExm43V21TSdP0/O9YAhTItjY6FMwdp4j9zsN5/8QmG/XkEnh6uOPjXz5C7ukLmwqloqNTQy5T4ue8yPHryFju2jUMKr1QmJa01ulFP+sWL95i+cBF9PFono4COJi1J9QaM690V+QNKoEbLDvRxcY9pcf8OwZcm71coxbM8S4VEIXk81uKwbqpEKjxIv44pvX5GCg9P/G/OYripVVY10gKsTf06oMUvrdsiR65sGDdpxNdbHiseL9pZAR2QPY0xdFQNyTBR/byWAVpytJJo4DcH9JfYG4lRz7aqNgRrw6SojYCeJKCEKg2RrSFAV6fDriM3ceLsfUzsWYVXyWQNKc7yiN2KwKzTwQRkPV/5wS/YCr2R9mt+/TkGn6N1lM3Z07nDRU28ZRlXwUGWnpLLICOAJt4z/VHAoFTh0v03KFbYB3vPPEC1Sr4cqFVqrppDrsJPfZbi8dN3JkjrjK7QGtzw7oMegf71MH/5QhQvUwkaPYE0N5mF2BwbV/6FS2Gn0HfKPCtACy1LhcQhTRoKzZVsQEuojRZ3vxNALbQmFbrhEV/aoI3B5O4d4ZEyJYbPWiQJ0sSPJvXRsxbNQFBwObuLzMZ2wNNbdLtLhIqOa2q/wQCnBbRPauOpwVUlk0TdawMDtORoJdHA7xrQ9tRzQqwNAwE1D1MRfLcfvI4uY7Zi24yWKOWbEdDxICZjeGUthjUFM12g1QAC4xdvI7H/6jMcuvYch268QMjgqrjw6B26rTkLd7WSdpYbXbcgmpbwQfOFIcjnnRJ1imVBxYIZoVSTpCABtRwgapmA2kWFGMhRvd8GeHq6YuUfLZDGOw1neahcKaQ79V6Kz5EabNwwGnIXsuKKG4iK/uefQ5g6aSH2nDgMo9yTqmgCZwLq61cuY2TXTliw/5QVoMnitGZ+ND8lPOLjBzy4dhHamChooqOgjY6i/2DyBVZC6gzeXHJQ1KbUBGkl169DvAILgfTEbu2RMlVq/G/WQqhdzJU0WQDAcgWWE4f2o3/XXjgUuh/p03laWR1JkjBMgM3htIDOmsoY0reyZJK4DtzCAC05Wkk08IcAtK3ZglKtDYM+toyOB3To+XA07L0a22e05PxmSziT34XkIbnPg9kYo8f60w8QFaVBRLQeR/57geB8GVAlbwbkTucOfoKb2ZHV6AzYf+clrj7/iK2XnyDYNyN+b1YMd958Rh4fL8hdlJC58GraRQWtXIGhS0Kw9dhtHFjeGTnzZDZBWgMVgupPQJPGFTBgYEvo5SmoH60xuKJezS6oVb8e2nTuQb1oAmfyE6nRopZfdvx1/CJU7p4mD1pYnYWse0gbKxFvWm/A7XMh2DhlKNJkzg5Xd0+oXN2gUrtBGx2J22ePI3MeP/iVDUa+khWRMXtOE6jFy2QReJPfXVQKCmy9JhqTunVAqrRpMXzmAqhVyniXyfpt6BA8e/oES1fPj9PqEHxq857RIhVtb5o/GSKGdBwqumS5fjh3/o7T9fYJyOxlPPlrBckkcRu9kwFacrSSaOA3BbQj7Q2p6tmypM7C2iDVGWaesk4Pg06Hh4/fIkcGDw7OYltD+J3YGToDjFo9Vcwnr7/AoHXnKcT+aFgEFXKmo48Lz3PXO1+mJtge/Gra1IMm9xUy6Ij7opAhYPJ+5EjngXkdAymoZWoCahWnqF3V2HfhCYLK5oWLZwpAsDtUatx5/BFlqo/Gf9eWIE3G9NAa3KmK3v3vWUybtACb9u1FjN6VB7QeUToDmpQqjElrtsHLO4vVquF0YVpiiWi0OLBqLs7s3oAG/X9HTn/Su53Y67Gld3pNDO6eO447Z4/j9tmjyJK3IGp3GYpMufJQUItXXxGvxqJWKSikf+vcCr5FitHqDqKa1SL1LChpwY/WxHxG5eKlMHPBNFQKCjRVdYib+9urjZY8BVyiinZWQBfzTmk80aGsZJK4T97DAC05Wkk08LsHdGLVs2BtiOCridGgaZ81mNm/OnJ5e3LJPcHSoFse1iI464mfrAcGrD2HYllSoWXRrJDpDYCG2B2EtlyS0EgeswQ0OcY8pKn3TGZnqMj0bxl0CmDe6XBMOfgf1v5aDpWLZobMlVfTrq7U8ngZqUeXKfuwdlZbpEjlCSjVgIsbugxaibTpUmPipF9hVJDe0e54/1mOPD7lce7WFbh6ZkKUllPQxOpoGGgO6OgYHQR7gyjpty+fY834/rS7RaOBk+HqlTbWi7ZIgAoVHUa9Dud2rcHJjUvgX6UeqrXviZSp01D7Q1DPlpCO/PAOg5vUQMeBw1GzcXMbC87K6JqHQr+OXZs3YO7UmdgfspPrhifTQSHT8rDW0TUMY1cGj8OL/kIV7bSAzuBpPN5a+oLaHjMPMEAnEXcl7+a7AXR8pXXi5KC4QkP4qkqet6eeeQgPnbYH1++8xNYpTSEXEoEmQIvgHKOnyvj8ndfosOgUDvaphLRqFaeWBTAT24NAmdofsaCmqpM8zt/kBMrkxqtoqqYJpFUKyFRyhH+OQoY07rjzIRJGlQIlfDNA5qaiqtmodkHbiXvhlkKNJX+0omV4cEmBR68iUazSCFy98Ce8s2WhKlpjcEe9Wl3RrvPPqFq3OfWhI7XEh9ajQclCmLx2O1XQURo9iGomgCbbyKgYTPupLvzKV0e55l1pdQnnS5t/DvEMQ/KZuMIUGaI+vcOJtfNx4+R+1Ow8AKXqNDNbGdxFxa0SLtgdT27fwMj2TTB55UYU8C9qVn4n9qNVcgJgLRpXr4lW7ZqjbacWNhOGCVLR4m9bwgGSYHM4K6CLpvMwHm1cQjIrvBYdYYCWHK0kGpgsAR1f9UZC7A3LsjqqnPmqDZF6Pnr6DtoM/gcXVndGei83Ti1rNLyCtobz1tCH6LYiDHNbFEND30wUzkYtD2Te9qC/k8QamTpN7vM2h8nq4I8xgTL9odUcMsh5OJtA7arAv3df4df157Hk59KoUzq7CdKfDTKU6r4WgzpXQseWZSFTu1EV3WfUP3Riy6zZvaGTe0Bj8MD0aWtx+9ZjTJg1H1E64kPrKaQJoCet3Y6UGbPQSpOoGB00WgPdhuxYj/P7tqHt78toeR2Bs6mxkqiqw/QPR9Q8iSYLaVJQhtcPbmHLlEHIW6I86nUbBldXF5PlYQnpsL07sHzyWMzfcRAZMqQ386MtrY5rF7kJLCcvHkPqVG4JVNH8P0rhH7rYd7YFa/q89WxKZwW0f1oP46G6RSWTJO2KE18C6DQA1gPIASAcQHMA72z88WUA6gJ4CaBQXG/O6Ux9yZFMwMBvBuiv4T/bszdsTUoRq2chMSgC9LWbz/Du/WeUL5TZzMoQg5p6ztE6REZoUOn3/ZjXLADFM3lxcI7mVDVVzDyY9STBpjVQ6F169Rl5PF3x7HMMOh7/D08iY5BOrUJfvyxol9cb4y8/QJUsqVEhcyooVArIVXITqKm1oVYg7MVHNFl+CnsHB8OfKGnSaMlVjRsvo/Bea0SZMvkgcyOAToFnb6NRoMwQvHiyDi7uqajNERJ2H727jsKeU6cQrVNROJOf2v75MGv7QaRIk4FCOUqjQ3SMniY7J7erhnp9JyBLgf+3dx7gUVRfG3+3Z1NJ6DUU6Ugv0qv0LiC9SG8CglQVBBWQJr0jIEVQKYKAIF0QpPfQE3pNIX3r95w7M5vZzW6yu8nG5P/NPs8+m+zO3Jk5M/Pbd9977rmVLHC2AjTvpwtfOuwXAP0gIMuBn6tQeDUkxGDn7LHQ+vmj2+R5bLZzjVrBFDVBmrxoGnWoUcrx0+yvWZnS6SvXM1uDBrgIcE5S0lxp0tED+qNk6eIYPX6YRUULXrRTGR0pAVoM7awG6EAf88Em7ztNi9y/nEkLoL8HEA6AZqmlaVwCAUyws/F6AGIAbJQADeB/AtDO2Bu2qXWWHGebEYN2vOcrN54gX5A3cvpprOGs01s8aLPOwAB871EkCvl7QZZogpw6ARPofb6zkF4TjRDATCDbfPsFZl95hOwaJeZVKoJiPho8jE1EQY0a4ToDfNQK5PRSYeX9F9gaxs14P7liMNoWywk5zZ5NoOYBLfdWYffdlyic1x9VCNB+asi8NIC3Fu/MclwOi0K9eqUh8/JhKrpOm+/w5Rc90KxVfWZxPH9lQMUyzXHjSSjiDRoG51idAfUK58IvV0OhkylA/nN8opG9Xjx6AEe2rESf7zdzWRyip8lohpF+Zdip0cGNJOS8dAI1Nwu4DEqVAjDpsXfBJOjiotF7+lL4BQRYLA6NikvBU6sVgD4Rn7VthAETp6JhyzYWq0NN7cnloFehw/DuzUvo3q4zzoecYrnU9rxox3nRLo4szEIKunyAt3l//bJOAzr/7+fSAujbABoAeA4gL4BjAEo62Dip7L0SoLMioF21N2y9Z44YokEoPKBFCpplbvDq2aTToWKHJZj9aWO0qFE4CdDM3uCWM+v0MCcaEB4ej2pT92N1j6qoXyi7lXImMJN6JjgbEgxITDTifmQcJpx/iMml86NSgA/zosmrNQtZHKKrl9kbMuBMRAwDc7XcAdj55C16lckLhVoBhbeKqWiCtF6jwMbLjzCwaSko/QnQ3rj7NgG1h23BnUPjEZg7CND4YNayv/Dk5TssWfYZ9GY/JBh9kS97dfwbcgNefrkRozPgdXgE2lQug21XHiKeLI94PQM0KenFw7uiSquuKF6zKXQ6owXQRpYfzaXfEajFkLYM++YVNBu0olRASV80pII1StZxd2jVt3gdegcD5q6Hn79/knpWcX40qek7F85gwbhhWPfXPwjw97NkdZCCFqtohUyHHu06oEPntujZ56NkGR1iFU1/W6fcpd3myKwWx/t+WvPeGo4YmRydwX9dTgugIwFkE7VK9gapaHsPCdBCVLKcgnYW0CnZG5YcaCMHagHYdtTztr2XsXDjKZxa24fLviBwC3DmPWiCr0lnQKcFxxGcTYs5bctzypm3NQQ4E5ifv0vAsOO3UT27L0YVz8tgbCRrxGhmdodgBaTkQ5NqjjQa0ffcPeTz1WBZ/VII8FVbIG3QKtFi/T9oUi4vvupWGTIfDeDrg35zD6N4sdyYPKYlU9HXH4SjbY8FeHBvE/OhE43+qFaxIxatWYliZT9ggL577z6Gd26D1ccuMjUdG69n9sadq5ew4avhGL5qP5tBXJdoYIAW4GzQcyVJhS8d8V0oQJoUtABmpVIBBSlkJfdUqeQ4sGwadLHvmJJWq5QMymo1Z3UwSCvlWDx+BHLlzYehk6dZUu9sVTQBmgavTJs4BSfOH4JSboQAZS4P2v4ks1YTzKbBh86sgC7nqzXvrvSe0wq62MlrYQC4n3HcYxX/FP7/C0AeOw1OAbBBArTToU5a8P8FoJ2xN/jOQUveM5+dUbXTUkwfUh8tPyiSXD3rdDAbjEw9H774FJO2X8KxUQ2gZtYG+c4GZmmQciY4v4pJwId7LqN9gewYWyIf50fzYDYxSPNQc6CgCWyUaidYGwY58MWtx7gZHY8DrSvC21vFIC33VeOF0YBai49jz+cNUblsHqaiLzyJRtdpe3Dn8ETIvX1hVnsjT9lRuPDvUuQNLoJEkz/atRqJPoMHo3aTDgzQ58+dw6zxYzBn5yHEMnvDgLgEAzbO+ByB+QujSps+TD3TU59IKtoIgjN96bAh4JQnnRiHVw+uwj9XMHyD8kBGowiZguZUs4KgzCtolUZpgbRcZsS2aYNQpmYjNOo+yAJmwY8mqyP27WuMalUPK/cfR4GCBZmKtvWihYyOph/Uxjdzp7O86Iy0OTIroMt6e5l3lCniNDVKnr+VFgUtWRxOR1q04H8C6PTsILRKc7Iz/x9ZHKkBWrA3xJ2DfF7zk6fhyBeoTUqrs6OeBZ85PiYRGhLlPJiFV4Izebbt9l9F9UBfTCyZnwMYqUz2JF+aU8/CU1zgzjJVIXm2SjnL5qCOQoVGAZlShrPRcWhQKDuUXgootUooyHv2VmHRhTDkCPJG32YlIfPTwuzjjYdRehQtVQAymmxW44PGneZhwoRu+LBlPSQY/dCr+5do3KIVmn/UlwH6rwP7sXX1Cnyx9mcG6NgEPWJiEvFluxroN38bvANzIyHBAF2iEXqdwQJnAnX4kwe498/veHz1CINzzNtnlOaAoIKl2bNI1ebwDcrBQC1AmqlnHtJkd8S+fYr147pj2OJfkadQMOs09NJwFoegon/89gv4+vpi8MSvrLzoJFBzM60s/n4Wm8vwmzlfOuwstD+y0EWbw8aHzqyALuOlMf9cjNwE5x7lb9xOC6DnAHgr6iSkrI7xksWRSuz/pwGdmv9s4kcJsp+vfM0NSy0NEw7/fQeFc/uhWF5/QOgQFAFaUM+//v0Q0dGJ6F25UJK1kchZHMZEA4yJRjyNiMfyW08xqXg+ztZIoBGJcUnH3AAAIABJREFUnCfNIM0Up3XBO2tbgCtgx2omKTlQkyWg0Cih8FLgSlw8NoS9wZoPy0BJKppBWgl5gIb9Lff3YjbHnfAExMqUqFytBODli2GTf0bpcsUwcnQ3JBr9MHjw9yhbsSo+7jcCUQkGbN/0E86cOIrhs5cgNoEAbcD1f8/g1/lT8ckPv3Bw1hmRGK9nkKYvnjeP7uDCrsV49+oxgqu0QKFKLaD1z8kmMIiPeoXIpyF4E3oZL++cQZWPxiN/6eqsg9AW0qSQ6fnvznV4GnIJ/WethpdaycAsVtFvHj3E5G5tsPX0Vfj6aC0qWgC0huIFA25du4TBPXvj7PUTqdoczAKRcbOIcw++38LRoJUU8qEzK6BLazTmn4KdB3TVO2kCdHYA2wEUAvAIQGc+qyMfgDUAWvKB3sp3JuYA8BLAVABr7WFMSrNz7ovV9aXcVdDp5T87yH0W2xtmvR6VOi7Bos+boV75/CJA85kbZG/QT/o4HcpP/gM/dKqIRoVzwBSntyhoUwIH5z33XqFmoC+8adQ3QZmHMylrBmlWT5mzt41GM87FxSMkIZFN1qqVy5FLoUQDP18LoIVCdqxzkIe0SSNHs1O3ML1aUbQqkQtKXzXL4lhyMQxBpKJblYbM1wc/Hn+APy88ws8r+jMfetGGU7gd+gZLl49DojEA48YtQVDOgug/ahID9KpFP+DZ0yfoNXE6ouP1iI03YPsP38IkU6DWx8MYoBPiDUw9E6BjIt7izwWD8V6dzihYoTkgU3CdhaIRhULx/vCwq7i0ew4KVWiM8i36Q+2lsUBarVZCpeEArZCZsH5sFzTuPRJVGrdiKpograXPeS/624Hd0bB1e7Tu2pOpaHFHoWV0IRJRvWRZ/LpvG0qWDHbP5nAG0HRHiFR0ZgV0SbXGvDaP84Cu8yhNgHadE6msIQE63UPKN5iRgHbW3jBzs6IIQ7cpta7Dp5txb+dwu/aGkLmx7cQDLD10G0eG1wNoBCF5zyL1fPLhW/Q/HoI99Uojj0LJ1DJBWwxn1u+oN+P3qHfYGBEOpUyGShpvqCFDvNmEbAoFBmTLgeWRr1FFq0U9f1+ugB2VfaY8YS8lsztORcdiyo1H+LdzNXj7ezHlfOhZOKYfvo2zs9owm+NRrBHVBm/Bi7NTIffxx5//PMScJQfw15H50JkDMO3rjUjUqzBqyrcM0PNmfA2zQoF2Qz5DdJyOAXp6tw/RZtQMZC9cBnFxeuY9J8TrodcZcXT1RPgE5UfpxgOTMjlsMlPIohEgrY+PwrW9C6CLf4e6/b6Db2B2Bmm1RgEVqWWCsEaJl3cvY9eczzF2/QFkyxZgUdFaDdd5eO3vI9i8YCZW7TvG4Mx50eLcaM7mmDzqUxR7LxgjRve3qnLHrA0YLYWVqNB/smwOS+eyKPXOkcWWBQBdQqkxr8jhPKAbvZAA7SkkOmw3S1kc7ihoZwFt4z/PW3McoU/CsXhcU/v2BuU9E8B+v4HCAV7caEHeeyYVLajnTvuvonW+IHTOHch8ZgZn3vYg5SwkhTxJ1GP66xcY4J8DZZVeMJut9QFZG5d1cfgu4gXa+gVgUI4gqFUyC6RV3ioovZVY8egV+pcrgJzZtcyLNvupke+b/bg9rx1yFQxiNkfeTqtxcdco5CuSH7cev0PHPktwK2QDA/Ss2dvx6k0sxk+fxwA9Y+I4ZM9XEB/2HMgA/erVW3zZrhbG/fwPEnQmpqAFe+PprUs48/N3aDhsLUxmGcvqIDsnqQgUbxcouBxoAdQKhQx3jv2Idy/uo/7AOdB4qZIgrVEyFU3PXbNGoVzdD1GzdRcQmIWMDi+NEioZ0KdGaaw++Dfy5ctnZXOIc6L3/LoF+3b/jh+3rnDdh/4fA3Rxhca8yD/Yaea0iLiTFg/a6e04u6CkoJ2NlKvLZbSCtr2xmOecgv9sMCAyPAbxcQnIm81mWDd50by9wQHZAJNINZuZxcF5zy/D49F472Ucb1wOSgPnO9P7BoK0jnKFgedxBmyKiMCQgBwwGmV2fWjLzNhyINJswPSo5+jgH4A2gf4M0Cq1DCqtknnP9JqoUSAo0AtK8p4DNBhx4DqGNi+Nyu/nAfz9cPzOW1StXhy+ubLjTSxQstYkvH21A3pZAOYv2IUHoW8wZdYiBujJI4eiWIUqqN2hG6JjdQi5dBGbZ05CvwXbmXomeyMxQY/EeANTzzmLVkXBSi2ZL83gTKMoeXuD/ico04Or0MeBmmwaudyMv9cMR5km/VCkcn2mnimzg6wOjZaUtBL3zx7ClYO/YvD8jUw1E5hp8Ap7VcoxZ8QnqNeyDVp89LGVzWEZ/i03IPT+bXRr3Q6X7p5JVpvDrXzoLKygi8k15vla5wHdLlYCtKuoS/PyWVpBp5TBkVIHIcHZUf4zDTzR67HvaAhafFAEclrW0kHIw5kfmEKpdSdvvsSXH5ZK6hwkQFNGQ5yeqeX4eD3kOhP08ZwfTdaGkQ3qAOISzRj65AnKq7To55fDqmop65YSlXUQZr1isFaYQSWgw2UGFPZRcZD2UoBUtF4jR81j13GhUzXkzO7NdRIKzyAv5kNHyVXQeWmRKzgPTGofeBUcjNh3ewB1dixeshfXbjzC1/NXMECP6d8b1Rq3QOVmbRmgT+zZifN//YG24+YyQBOYyd54+fAOjq4ci8YjN8BoVnBZKTycrVQ0f8VaaotQXREe0pGPr+DavkVoNuZHaH29oSLlTFaHRgkvGi1p1mNp/yYYs2YvcuTNx6lolZy9ErAPbl6H0JDrmDxvSYo+dPnC7+HomUMoUCCHxYe2lw9t3VHofiZHZvWgi0Jjnql0HtAfGyRApxm4rjaQ4YB2Vz2zjhdRGp3t/+LP2MATnm7CkG57owdZ2gRXHEncQXj/wUs07LsWYXtGWA9O4UEt+M8jVp9BoWxajK39XjJ7I/JdIiaevoc5FYI55WyjnikZZPbzV3ik0+PbwHwwGckS4LM4qBIcn9EhnE/x3LHkP8sVZnzyNhRjcuREw0BfaLw4Fa3yVWPY9VA0KZQd/SsXhCJAg8cmIxadfYhFw2pD5uuN2btv4G2CEXO+7gxo/ZH3/TG4dH45sucrhhWr/sS//97Gt4vXMEAP6foRmnbtjVK1GzOLY+eKhYiOikSdHqMZoONjdUxFn1g/HT5BBVHkg85MPbNBNwRoPs+bS4QwcWkopKD5wk/sla8tQil2l377BkGFSqF8s14WD1rwognSfy6binxFS6JRtwEWm0NLXrVagZcP7uC7wb2w5dSlFH3ofp06oVvvLmjXoWmyjkKnqts501GYBTxoAAcAULaEsw8apNLc2YU9vZxkcXgiwp4GdGojCFPK4OBT7HYcuIoNuy5i99zO1lXrBHuD958rTtyLtT2romJO/6TsjThSygb8HvISq289w9bqxZmlIXjPhnhKS+M6BTe+jUALbQA0BoXdKQxtw8/PE8vmjCVIn9JHY1dcJNYWLshUtNpHCZVWhf1R0fj9ZSS2tSkPZYAGMRo5isw6iKj13SH398a2c0/x2+mH+GX1QJZqV67BNPy85QuUqlAea9Ydw5GjFzF35U8M0P3at0LHwZ+iWNXaDNDrv5kM/zyFUL5pVwug42MSsG1iCzQduwWQa1mnIcFZyPNmYBZNSCAUTGIlU1l1Pq58Klkd8ZFPcHbTRLT94lfmRXOZHFxGh5dWhbBLJ3Bx31YMmrueV9BJ2RxeSjl6VimOjScuIGfOHNDSEHK+iBLXYch1FM6bMR1KhRkTvxyVIZkcmVVBe+L2zsg2JUB7ItpZANDLNp3G9TvPsWx88xQ7CCtM3INjnzaAn0wGcyznR5P/bIjTY/a5h2zy14nF81nZG/oEGnUHvE00wssoh17PKWeh3r+jXGiLguYm82aQNqlM6PTqAfYGF0EOHwXUXnKofdV4rTDjUEQ0RlQNhoq3N/J8dwB3F7ZH9nxBOHw3HDO3nMdf20ZC5u2PGi1nYtGikahSszo2bvobe/eexg/rtjJA92nTHF1GjEORyh8gKkaHNV+ORv6yVVG8dmtWtY86CF8+vI+jq8aj0Yj10NFgFRGgbT1oQT2zV6WC6yjkAU2v1GF4fFlf1P3ke+QoWNRic2i0ZOUoEB/xHFu+HIDJPx+z60OPa9cY4+YsQrmKlex2FNKw701rVuLWteuYu+Rbq45CpzM5nFHQ7BuJ+xUnAdoTIKHpIf4fPLKMxeFOBodgg4j9ZrGCdjCC8Obt54iLTUDVErmsAe2og5DvGGQdhLz/PPjILTTI4Y+2ubJBz6tqoXMwIQHoHhaGUQG5UFKmtcDZYnGIBqwkszhEgCbVfNEYi6q+WgR5y5nNQYBW+arYq8ZfbQF09RUnsGlkXbxfLh8exZux69xjfDqsGWRaPzTu8gOmTOmBeh82wNZtZ7B9+2Es/elXBuherZui++iJCK5QnQF6ydiBKF23BYKrNGKAJovj7pnDuH92Pyp3+oqzNyi/mx8lSeqZjY7kszks6pm3OMjy4EqnciqalPLVPfOQs+j7KFW3HbM5vMi6EbI5VMC8rh9g6q5z8Pf3tcqH1qoVmD2sD5p16oomrdvZHbBCgD64Zxd+2bwVG39ZLQE6CzMuqwGahlK2AaADcB9APwBUQSrFhwRoLqODzbbNS9nYd/HQ0ugzAw1KERXmFwH6dmg4jl17jv5Vg+12EOpiKT+Yy/Ag/1kfz3Ua6nVm3I3RYfCTx9iWqyjMVGiIL4wn7IJYRTsENDeRN+QqM97K9Sjuq4bWO8mH7nflAb6sXhTVimZnnYTIpoEq0AvyQC2QLYBlc9BT5hOAtn2XY8DA1mjVoSl+2XERG9bvxcqfdzNA92zZBD3HfYFC71dlgJ4/vCeqtO6B/OVqWgB9ftca6BIS8V7dXskAzUZbilPt+AOydBLaqGilRoEXN/7C27DLqNP7KysfmkBNPvSake3R48sfUKhkGWZzWAasqBTY8O0U5CtUGN0GD2cdhV4im0MYUXj53N+YNmEKDpzYnb6pdsn6SCQFnRp/0vJ5VgN0UwBHABgAzOYP3F5BbKuY/E8D2s0c6HZDN6Bf24poX7uoQ0BvP3Efv/wTiq29a3CAjuPyoo18ZsOKy48xoEguZm8Y4uhnP5fFQYBe9yICoYk6jPbPbW9SlmQdhGJIC6MIBZvjpVyH8RFPsP+9ojTLFdQ+KtZR+OnNMLQonAM9KxWEPNALp8OjEZDTB5Ur5EO8Rovqw3/GtYMTIfP2Q7fh69GmfR183LMddu29huVLtmPdjn0M0N2bN0Lv8V9ZAD17wEeo2204cpWobAH0kVVfIXuRyshbppEF0HSsTmVxUD4030lIrwTo+IjHuPDLdLSasIml11GanaCkyebYOetTVG/RGZUbNU+WybF37VI2mnHEV98kS7UTAP0kNAQft+6ICyGnJUCnhZD/8bpZDdDicHUA0AlAj9RiKAGaV9Ci2VOcBfSvZ8KwpVf1ZICmVLrs607iSbuqMFK+swjQiQlmnI2KQ6zejMoqn1QBTTYm1YGmh+BDC5AmBR2tMGDw2zAcLFaMCtaxYklkb0y48wS182fDJ1WDmYIeczQEZYoEYUSnCtB7e8OnxRLobs9hgO43djPqNaiE3gM648BfdzDru7XYsvcgIhNM6NuuJT4aMhrFqtZiCnresO6o1qYX8okU9N+b5sArW34UqtQ6XQAd9zYMV3Z/j+Zj19kF9I7vRqJmu+6oWK9JMkDvWbMY8e+iMOyL6Q4B/fjhLVbA/9zNvyVApwaITPx5Vgb0Hn7+r02pxVcCdHJAd/50E7p8WAad6xd3qKB3nw7FumN38Vu/mskATeoxz48ncbNVZahotKANoLksDlFpaesJwa0UdGqAjlToMTL8MfYXLWoF6KVPXqNCXn+0L5ePAXrcsdt4r1A2jOpSEWY/XygbL4Th9mzI/bJh0KRtqFK1NAYM64Zjfz/ExM9/wI7DJ/Au0YxBH3dE0659UKp2I4ce9MU96xEf/Q7F6/d13eKwo6AjH13B/TPb0WjwfLuA/vmr/mja91OUrlYrGaB/WzIHCrkcA8ZNcgjo+yFXMKhXP5y6dEQCdGqAyMSfZ0ZAp1QQezcfSyqOTVP1dmS1He0/BgGgJwoVzFklNISKSWXQw90sjgzsJFy84W9UKZUHtUrndgjo6Mh4REbGI69GbRfQhTeewj/NKsCXCiTZeNBHw2NxMDoan/vnSVVBi8+KkGZHr9RBSJkciUojDuqj0C9HkBWgqYOQdRTyWRwTTtxBoXz++KxrJeY9lx+wGRf2fAZ1YBBGTv0NxUsVxvDRvXHm/DMMHfg1/jj1LwP0p317okaz1qjQuBVLs1v1xRjkL10Zxeu0sWRx3Dy+F09unEXFduORkMANcxd3EoonxKXjseooFHnQcqrMp5Lj1e0TeH3vLOr0mZrMgyaL46fPu+GjsTNQpGyFZIDeMncGAoOC0GvEGIeAvnX1HD4bMhJH/z0gATqDbntPbCYzAjq14+wDYAiAxgDiUluYPv+fVtB0gCkNVEmhDrS9mVOY7OWHeUeGx+H+0yhUyOUPYXi3OIvjnycRKKvVsLkJhUEq5EeTB30iIhbrwsMxP6ig1WZcyuLgOwlVKjM0GhnNDWvxoGnI9+6IKBTL4YsGJXIxBX3PoIc2uxZFi+e0dBCyTkLfAIz9ZjfyFMiNcRP74eK1CHTr/BkOX7jKAD1+6ECUqlYLH7TtjKiYRNYJF5CnEMp9+LElDzrs6r+4/Mda1Ow912Gane00XsJAFXtZHGHndyPh3QtU7zQ6WRYHdRKuGt4GfWYsR3DxksmyONbNmIyCRYuh28ChDsuOXjl/Cl99Pgl/nvzdbhYHTbnlsC60kBEkXFv2XoUbT0qzcwZBbi+T1QBNI3zmA6gP4LWzRy0BOnkWx7pf/gWMJnzS+n2HaXZ3QsPRcu5RhHzZnMt/FvKgyc5IMOBZeBwMOiOCTDKu9kac3lKD42WcEe0fPsRPuQvD16h0O82OvOjjhncIMcZjSr7cVlkc/a8+QJ8y+dDh/fwM0JQbHZDbF355uOyNcWvPYNaUdlBlC8LE2XsRkD0QE78YgNsPEtGkfm+cCbmDaJ0c0yeOg3+uvGjSaxAb6r1z5SJEhoejbs+kkYTvwiOxY1pnNBqxFnKVn92BKvam8CI42+ZB02jCs5vGo3jtDihWrUmyPGi5WYeFfRpg6s6z8PX1SVaPY+bgnmj5cU80bt3WYR70n7/vxLafNmPzjnVSmp2zoMiEy2U1QN8DoOFnLaBwnuHVdIqhzTKAFisVi0IRDf0WF0Riy7ox1JtPs1ux5R9cvPEEqya1TLI4xIX6dVy2RvbB23FvagsEKORcmVE+H5pgPOPMA1b7+fP38iarw0F50Ctfv0VllTeKC3nQvA/tykAVAvT06Geo5+ODTjkDrPKg6524gW3NyqFswUAG6F6/X0bHDwqja/NSFg9aHzILCv9AfDFvP7x8fTFl6iA8fytH6WItcOPpMwbopfPm4OXr1+g27itmcfy9fy/+3r0NH01ZzCtoKpikx8mN38HLP0+yod5syDdN4SWeIobODw9n25GEsa/v48KvM9BqwhZ4eWuSjSR8fPU0zu5Yi6ELtyQbSahVKdC/Tnn88Ot+BBcp7BDQy+bNRWT4K8yYNdm9kqPSQJVMgeusBmi3giYBWlSLg/cY/joZgpkrj+Hwsh4pDvWu9/WfmN6qLOoWDLIq1E/wPvzwDWZdCMOuOqX4gSpJZUbJ5iDeJ+rMSKT6G8JoQr7AXqp50PxQb4PChM6vHmB3kSLIpU0aSWjWKlDm4GU87lMb3jRdV4AGLTadxeSO5dGkZmEkemnh32oZEm/NYhbH1AV/QqbWYOqMoYjR+SHQuwoeRr5FnEGN7Vu24Oif+/HpvOWIitXh/q0QLP98AIau+IPN8B0Xq2fV7J7duY6T66ei0fB10FPlPlGxJIsHzc+1KK5oRwNUqKodvZJ6vvbHfGTLUwTlPuxutxbHyc0LodVq0aL/6GS1OBIiwzH0wxrYcz0UGqXCYU3ocUMGo9oHVdC3fxfPDfXOGrU43GJGZllJArSnzkR6dRS6Us1OrHrsVLMTF0sKDXuNTqO24PymAQ6GetOIQQMOnn+C9wK9EazVJCuW9C5GhxJb/sG1lpWg0icvNUqAnvn8FYIVarTWZrM73Ns2/KyTUMGl25F6fiPXY098JMbmyWmpaEcdg2pfFeLVcuQI0iaNJFx+Aj8Oq41K5fPjnUKNAp1W4d21mSzNbvqiQ9BDgenfDUe8MRtyB9bEuTshkHkF4fix41j83df4duseRMXp8C46AWM/rIDRGw7DpNBaOgqpqt0fcweiZMNeyB5cxTLDtzgXWnw8Fg9aBGdDfCSOLR+ElhM2wScgMFk1O+og3Di+B1oNHo9SVWtaOgipkh0NWLn17yn8vPB7LN2539JBmFSLQw6l3AQaSdihSVNM/noi6tar6kI1O9p796a9koZ6ewYkEqA9E9fkVemc3Y4r1ewEm0PoJGT3F3+DOVEPmo0gFIpk2JQbpfdpSDcNTHn5OgY5lMpkownJh15/7Sna5A2El8Fst9zohah4jH3+DMtyFkQuqC3TXjEFzTs0ogJwEEqOCtXsjOQra6hmMizV7KiD8HJiAoL8vVChYDZWLIlm+Z519gGGti6DnPmywejjg7BYE4qWKcQA/d2yw4hOMGHm9yMQbwxA8cItsePQAQTmLY47D0LRu3kD/Hj6OjflFU1SMLQbKjXvgsJVGvIF+7mSo7dP78fNw1tQb+AiGE1UAEpUsN9oU4lQVLSflDPlel/eORM+gblQpcOIZOpZmEB2w7jumLz9JHx9vC3+M5v+Sq3Ar0vnISEmGp9O+85hPWijIR4VCr+Hs9dPIldOfzZrioLNP2iATGaCUM2OSo0mm1FFsNnEX/ZZuB60s7ddZl1OArSnzkx6KWhbX9qeD53SaEIhi4MHtlk0WOX3Q9fh56VEwwr5U0y1Cx6zC3entoC/XMb50PyoQmGy2KvP3uE9LxVMuqRsDnHB/s2vI/FLVCTW5gqGgs1CYl1q1ArQwqSxCjN+jovAHX0C5hXMZ1HPNPUV1eHoeeEe+pbKh07l8rJyo2zS2AANFEFaNu1VlFyNkNdxqFG7NAP0rBVHERmrx6w5Ixmga1XvhW9/WIiSFWoiKkGPRqWLYPEfx6HOloP50Md2bMOFw/ssPrQwJ2FCnB4nfpwGpZcPyjUf6XDKKzpt4mmvTIZE3Dq0AtGvw9Bk+EJotFrmPQszfJNypuyNQ6u+hW9ANrQeNC7ZjCpquQyftqyLcbMXolKNDxxmcFw4cxxfjZuEw2f2OUyxI1DbBbTtxA+Orj9xH4hULMlTFJGKJXksspkF0LQfDlLtlm86jbNXH2P9V61T9KE7zjuGdu/nRc8KBS02hzDkm1R0w10XMaZUfnyY3d+q7CgNZqEpr8jquB6bgPeUXriZkIBiMg2b7sq2T43vV8M7sxHz3r3AS6MB3+fNi6JUHEktY3MSUqnRaCVQ+9h13Or2AbKR/+ynxvHX77D5ymOsH1UfsgAfnLwfgclrTuHkzjFs4tjZK4/i7Tsdvp/3KQN0u9aj0WvgINRq0gExOiMGdW6Hlj0/QZm6TVgmR0R4FL5sXwtDlu+B0ieQqWdh2qu4d++wf94AFKvVCcGVW7JJcG0njeWOhZuXMPrVQ1zcMRNBBUuhSodR8PH3t0x3pVByBftJPce8foIN43vg8w0HEJQjZ7I5CZ/dC8E3A3tgy+nL8FIpHfrPS+d+j4i3bzDj+y/cS7ET/xKTAO0xRDjTsKSgnYmSO8tkJKCFm8hRRTvbov28hKWi/fV6r8aTPz61LtrPF0+yTBp78gE2nniA3wfUSrI5RJPG7rr9EnMuhWF//TIw60zJJo2lDkM2u4rBhD6PHiGnUsmq3OVXcpaH8CDf2Ww247oxHqfiYjEiZ3Z4qzl7Q5g4loZ5b38VgZNvo7GxeTluyitfNRZffoSwmAQsGlILMn9f7L70DOsO3MTuHwezanZzVh7Bq8gEzJk/ColGP3zyyXeoWrMO2vcYghidAXO/ngqzUon2Q8ciNoGb2XvdtM8QmL8oqrTpnWxm77eP7uKfrbNgMplQ5sNPkD24MmQy+tLhDkgul7NjCT2/G3eOb0HF1sNQtHpTKJUKy6zeSVNecfMR7pk/AXmLlECzviPYrN5eGgUrNyrM6v3zgpkwm4wYbjPEW/CgBf+5V4eP0PuTHmjTvonnOgglBe0OFVxeRwK0yyFzcoXMBmgGb8rmMIPZHPyzVMsF2DG3M8oUCrSvog0mxEQlYMORexhSq0iSxZFoZFkdNKKOVHTzPZfRo3AudMoTyFLvhIErlOlgov/5yWMT9GZsCo/AT5HhmJe7APIqlVgS/ob5szEmI97XaNEnKIh1EAqjCeVKOSswpKCJU72V0KnliFUAwbl82aSxBOj+u6+gTtk8GNSmDJvyau3xBzh18wXWLejFAD1v9TE8fR2D+QsJ0AGYOGkFvHxyYCil1iUasWfnb9i5+SdMWb3F4kPf+PcfbJk5AYOW7ILeJIcu0QAdKwbFvRr0RoRdOoZrf66D0ssb+cs1gFGXgITot0iIDkfs26dQqDWo2f0L+OcqYAVnArVgcRCcn948j9/nT8T4nw7Bz9/Pop4ZoNUKyI0GDG9aE1+v3IiyFSs6tDf0ulhUKloCZ66dQO5cAQ79Z/KeaVZvBZvpW/iWdKGDUAK0kyBI22ISoNMWP8druwto25+UKf3EtDftlfjnqVAXOgUf+l1kLPy9lHzRDL54BpuGm/tbUNGmeAOu3n+L93P62VXRj8Lj4GuWwYvSgdms3txsI8ynFkFaSK97STO2mCipXY4jMdFsvD4pwYZ+Pgigym98FocAZzlVgfNW4nJsPAxKORoWyc4q2sm8lczi6PvbJXzdtRKK0yhCby2uPI9FpFGGBo1y6RzDAAAgAElEQVTKAxofzF9zDI9fRmPBotEM0MtX/oHz50Iwc8lqxOiAZ69eo121clh/+jqMSg1i4/WITzBg0ajeKFq5Niq17MFqcNCTZlMxGAjQ9MVjgkGvx9Ob/+DpzbNQa32h9c8ObUAOeGfLiaACJaDWaNjQb5ogliwPQTmT/0zwjX79FBsn9kK3yfNQunodTjWr5Vbq+cBPa3DxxBHM3fQr6xxUyuXgZlChzI2kmVT27/oNG1avxc4DP7vuPwvXmjM50KIUO1pNyuLwDEgkQHsmru5ncdgDtCNIi6e+crbsqDA3IW9zGBN1+G7FUUzqUwtKSs1LltWhY9kc0dEJKDl2N/YNr4ty2XlI81ke9DmpaH2CAW0OXMO0cgXxvq/WAmmmoPnpoWi0HalpYdftjO1gcFZQrWqlnJsNm6aKIgWtlqP1qRCMKFcAncvmhcJbxdQz6yD0U0HGXrUM0AYvLZTZaJi3LwP0gnUnEPYsCj8sHg2dyQ8HDl7D97PW4Oc//kSsXs586MGd2qBlj09QsVFzZnPEJxrx8PZtLB7eBUOW7mJeNAGaMjcESDPvmfegbUcS0mljg1REcCbPmUAtwNmoi8PG8T3xQdvuqPdRb2ZtMEuDZvtmrwokREdhRLPamLN1J0qWKWtRz0nWhgwquYHZGX07dUG7j1qjW8/27tkbbvjPEqA9BRFpRhXPRdYRaJ3ZoieKJol8aFubo1a3FfhyQF20qFGYszmYguYr7FNdDipIn2jAkj9uYd+lJ9gzuI5l6iuW0UFqmS8e9PvdVxh/9j5+r18a+VUqi91B8DLpjdzgDpp9hM+xszc8Whh5xzrZBDir5FgR9gp7n0XgcPtK0Pjw6tlXjZWXHyNXTh90afQeZN5eDNANx+7AjM+ao269sgzQP6w7jodPIrFwyRgG6Nv3otCicS+cvR2COL0KcXojNq5ajmuXLmLErEWITTQgPtGAuAQDdiyeicg3r9B61LfQ6TlAM1Dzx0JqmuNa8rpdQkchgVlOypfsGv4pgxE7Z32GgJy50XnsDN7WIEDz6lmtgEouw6bvpyM+NhoTvl9opZ4FFa1SyFju85sXj9Ggam1cvvcv/OnXhYP0OsHeSJZi52YGhwRoZ25q95aRFLR7cXNuLXdtjvQAtPAFYZsPLaTbiWZXofkJ/74Qii0z2iUBWmRzsOJJBhMSYxJRYeJerO5RFTULBllbHWRj8JBeeukRfn3wGn/ULw0zjbgzcB2HbPZrljdsssBMXGBIGH0ngFkANalog1KGAefuYUGdEgjO4QO5l5KpZ5mPEvWWncA3XSqhcQ3KedYCvj4I7rwKJ7YMReH38jFAL/zxBO4/CseiJaOhN/shVqdF3sBquPE0FGZlAAP0w9Aw9G5aj9kcepkcCQzSRkRGROK7Hk3RbMDnKFm7uQXSBGohe4NUtEMFzYOZU9IKKBUy6GKisGveBGZ/9Pp6MXy8tQzQSqXMYm2oFHK8eRyK8Z1bYN2hU8iVJ49d9Sx0Dq5YMB/3797F4pWzWb4zpdEJHjP9TQWSHKbXuWJv2PjPEqCdw4E7S0mAdidqzq7jLqBd9aGFG8ZVm4OHdMTbaFTsuBgXNw9Edl91chXNe9HQm3A3LAKF/TWQG5HUYUjwpawOHtJGnRFXXrxDGT9v7H/0Bg2z+0Mu2AD0yitP7jCTVKelRKcwCzZNtqqQYcvTt+hULDey+ak5q0Oj5LxnbxVux8Sj+fK/cX9xB3gFeDP1HGmUo1DH5Yg4/zWUfn6AWotF60/iXthbC6B1Jh/UqNwJ85YvRumKdRCrMzFID+rYCk06dUfN1h0RrzMyFa3Tm3Dv+lX8+MUwlKheHw37jgXkShjoWPgvG0dpdnSMAphpEA6p5/vnT+CPJdNQqUk7tBo0Fl4aNZQK8qM55Ux/06sxIQ4TurRCmx598VG/gclGDpLFQepZDgPiY96gToXq+Hn3RlSoWCZt9ob4+hNfU8J1b+M/S4B2FgiuLycB2vWYOb9GegLaFtruFk6yzebgIR0fk8DmKLQqOydW0QzSBGEj7oRFYvL2S9jYsxrUVHtCR4Dmp38SKWmyB7oeuo7IRAPmVCyM9wO8mYomRc0Oh69bIUBamMOPPlMo5dDLzBh/JQwh7+KxvVk55PHzAg1UITjLCNI+Smy/+Ryh7xIwpUtFyHw0DNAPI3VYuvsK5n7ZATIvLVPQi348jruhb7F46WgY4I1Eoz8GD/ga5StXRbf+IxCnBwP00UMHseybqViw5ygSjJyVEU9ZGzoTIsMjsHXWBES8fIaOE+ayzAyLgqbOUZuRhHIa4s3fYQTmxJh3OLrxBzy4dBpdJsxG8Uo1oKKOQl45k2Lm/pZDJQPmjuwP/8BATJizCPSZxtIhyHUMck9uaPfsadPw8vkzLFkzP8XOQU/YGxKgnUeCq0tKgHY1Yq4s/18CmvZTPOybVI940IpNZyGB+csfDqJx1WA0qFjA2uoQTSpLIKbMjC6LTsBXqcCablUAHU06aw1pUtvUMUhqenPIC3x94SHW1i6JSoE+iEs0wF+psABaHFKyOQwwQ6aQo+HBqyiRzRsr65eCn1bFwVmjgIx/NdE8fr4qyLyFpxasaDTZHDQ3lrcWMo2WKejF64/j9oPXWLLsMwZonckXK5bvwoXztzB76SrEGxRIMBgRqzOgZ5M66PP5l6hQtxHi9UZmaSTSq86EBJ0BJ37dgMM/LUO9roNQrGo9BOQuaJk1QvChSTWzh8nIgHz18C48uPQPyjdsiVaDJ8DX35/BmdSyYGtwf3Mg3rboe1z95yTmbd0FX28t86LFnYKCeiY4P3/yEM1qNcTRs3+iQIHcdtVzivWf02hvSIB2BQquLSsB2rV4ub60u5B21ocWQOyszSFAW5wTzavobXsvY96PJ3FmQ3/IKaNDqM/BMju4zkNKuyP4xsYkovG3h9C+Qn6Ma1iCWRwM0nyFN1qGWR589kZ4vA4qExASEYsOh26gcnZf1Mzpj+b5AlHCX4sVd54zxfrnswjUzOWPb6sVRWh8IooGaNkgFYVKYQVnaBTotPEshjQpgRY1giHTqrhq/t5ajF/1N1o1Lov69ctCptYCKg2WrD+BkAevsGTJaBjlBGgfnD33AMMHfYGDZ85AZ1QjwcDZHLu3b8Wun37EzK2/I9Fo5uCsN0LPFLUJBqMJD25cwamdP+HOub+hUKnxXuVaKFC6Egx6HeJjopAQ/Q6xUW9x7/zfCMpbAJWbdkDFRq3gF5ANCoItD2Pyo5NAzcH5zIHfsW7mNCzb8xdy5c7N4Cyk04k7BsnaoMyN0QMHoWCh/JgybUwy71lce8NT6lkCtOtYcHYNCdDORsrd5dwFtK2lIWxf3J4zNofQjr2caEFF84A26/Wo23MVujcvh2EfVbZR0aLcaIK13oTnL6MRHpWAEkE+kJFdQVCmrA4B0pStoTex95lXy3vP0YkGHHkcjktvY9CmUHaUzeaNGZfCGLga5A1EvfzZmJKk8pxcR6ECMvqb8rXZqwIr/w3DmjMPcXZGC2j8vSBj061oYNZoUKzLKvyxqh9Kly3EAVqtxZINx3Hr7gssXTrGAujYeAWK5q+FMzcuwjewIOL1JgbpmIREDOnQAuVq1EaPz6ZAZzQxSBOY2SsNuuG9Z3p9/uAubp87icch16D20kLr5w+tbwC8A7KhWIXqyB1cjPnQApiZJ60k/1hQ0HLub7kMl44fwg8TRmH2xl9QpkJFXjlzOc8EZ7G1QXA+dfQvjBk8AqcuH0EAxYHP3OA6A2kQipF1DtqfPYV9u3O/rBzlPiez1uzPMCflQbsLiJTXkwDtmbgmtZoRgLbYGaIC/uKfrQzO9ORtDlsVLcrouH3/JfYeuYWxPWok96NF1e8o9U4A8pTtl1jGwzcty0FNm9CTH001QAjQ/HLUGcg6CLmUNJZqx3vQthYHg7KCqibJAIWMg7NKYYHzmWdR6PrjGZyY0hTFCmVLUs9qFe6+jkPjkT8j7PgkyLUcnKHUYOnGE7h55zkDtFnhBZ3RB3qzFl0/GoNmbVqjQ7e+SDSSzcFBmgr4D+vQHM0+7o02/YZYQVpP2RtmGr7O1+Awc6/Cw2gyMxjTg2WkyLhcaO5Jh2WtmhUyGWRmE35ZMheHftmMr1duQPmq1S1wFqCcpKI54Ea+eY4PazbA4jUL0bDRB1aF+bkUuqTMDafUsxjG9joHhV9pdu4ZCdCeAYkEaM/E1bpVdyGdms0hvqHEg1bEqtm2bKQjL1qANHs14sTZ+6hWOg/fcSgawGIH0m/C4/DJqtNsCqz1vaqjVA5fDsxkeRC4WIodX19USEcT4CzOHRZ8W4KyBc5UHJqDNNRy1jmYCDPuRcWj/HvZuc5CUs9qzuLYd+ExDp1/hAVTO0Cm0QAqLwbppeuPWQFab9KCnuvX78eBP45hxeYtMJrVFhVNqvnRozAM79gSvcZMQv32XRikyeZg6XVmMwRQJw26cZQHzUGZoM3UM3UesgwMrhMx+u1rzPtsCFvmi0WrWDod5zmLFTPnQQtZGzLo0a/zxyhVtgS++maipWMwSS2bnFfPli94fsi3vV9pKcCZPpIA7RmQSID2TFzTB9BptTmcUdG2edE8qLuP24bs/l5YPK4pZ3WIVLa4jrSgpE06A9YduYc3UfH4/MNSMOmMkBkoN9iUBGo2LRQpZ1ExaHvxJyDzCpqBmaloBZ7FJWLotovYOKQ2grJr2XsytZKfSZb3oBmoudllaQYVBmiVJgnQS0bBrPRmcKbni1fxqFymEa48vAWFOhA6o4wpaIIxPe+EhGD0x23x6XcLUKVhUxhMJuhp0A3/JIuD4xsHZ1LPwsORihbATAC+9s9JzB83DC279Ubf0eOhohodqcCZ1PP6Fcvx69bt+OPoDnipZVbWRkarZwboWqNx4dL9/xc8yQhkCNv4fxHQDJ/yyvYMuqugXQG0oILESkewNhypaHujC/liGZHh0ajSaSm+G9kYHzculeRHW0CdpKoZpJnfzKnmf++8xhc7ruCL5qVRq3D2JFAToMUDOuxYHARjeogVtFEGrP03FDP238SopqUwoV05LpOD4Eyl7gjKajWuhIVjzd7rWDy1PQdoFQFaAyjVDNA3bj/HsqWjAKUXB2izFkaTGs0b98GQUSPQqEVbi4omOBtMZgbpy+fPY1K/rug6fAyade0DmUrNFDTn2tgvNSpcAkI2B/OgyeqgXGi5HA9vXsW2pQtw+/J5TJy/DNXqNeQUMp+tQWo6yW8WKWeZCVcvnEWvj7pi37FdeK9YcDJrI/WOQXaxJJUjECwv2+vN9rq1k//MfzuhWp3PJEB7gNwSoD0Q1GRNpgXQrkDans3hrIrmPWpxQf8rN59i3Pf7cGBpTyjoc8HesIW00MlI+c1GM/QJeqamF/wZwgoxbe5XA0UCfbgpVCy5z/zPaVtIM3tDzoVQIYNZIcOjqHgM33oB33ergveLBXHKWUmWRxKc6e+Ok3eiXrWiGN2/PmSU0aFQcYBWeWHZ+mO4HvLUAmiDWc0gbTRrsH7dHvy8ZTd+2bcbBrM3U9ECnHVGM1PNt2/ewIrvvsbD27fQfdR4NGjfGTK5ggc1B2sHPwaYdUEPer179SK2L5mHu9evoMvgkWjXsy98fHwsqpkDOGdvCH9bbA2ZCXduXEHXNh9h3tI5aNm6oSVrw561IR41yG2fbA+Kuw2cxdeYq/YGf81JgPYMSCRAeyauyVtNC6RT86LFnzvyogWF7ajDkH9fPG8h2Rr0f3RUHG7de4kaZfImtzt4z1qYJkWspilrY/+lp2hUIhdOhLzEgevPUSM4CNWCgxCcTcvqJ1uRTU71lM24/DwSJ+69wfG7r1E0ly8W9KjKedC81WGBM9UkJfWsVOL8/TfoOOE33N73GbRUJEmloiLSFgVtDWg1DGYvGE0aGMwaxOtUqFO1Nb74ZioaNm/DVLTeSOqZg7PwSt8lF8+cxqpZ0/EuIhxt+wxAsXIVUahEKWi8tMkgTYCNeReFG/+expV//saV0ycQFxONrkNGoXW3XtBqvbgOQ74jUVDMgnqm9cVwvnX1Inq074Jv5k7HR51bWsHZNmuD/nfYMSj+0nYGzuJfZbZXtgRojxJEArRHwytqPL0B7ejnaGoqWlgvtawOUafh2YuhaDdyM9ZNbYOWtYpZQ9qynJnL+hDUNElKwfYwmhHyJBK/X3iCfx+8xdn7b7BrOFdWc9z2yzDDzEDVt3YRdKxUAA3mHkXlwkGoWzIXmlfKzxX+IVVN2Rw0oyyBmT0VnIpWKvHribuIM5jRu1N19p5MSeCmSv+kor2w7McjnIJeMpL9TxAm9UyAJptj375T+GriTBz+929A7gMTlEikdDoTB2nulZQyZ3v8c+QQju7dhXs3ruHJg/vIUygYBYsWh8GgR0JcLOJjYxmM37x4hjKVq6FirXqoXLsuSr5fEWqV0grMglJOAjNnbzAbns91vn75Anp27IrZP8xEuw5NGZzFKXXO+c52rA1nAJ2CtSFc4ZKC9gxIJEB7Jq72W01vSDv6OeqsihaUkZAHywavcOl4rHNPBOkzF0LRYdRmLPi8ObqSJy0oZ5vsD/a+6D2WxcFbG6xN8qDphjeaERWvx/mHb7nsP7MZ7+X2Z4pZ8KGZYhbAzBWySJruWwC1Wo2IOB0CcwRYgC1jU7CIAK1UWwNaqYZZpoaBKWgO1HqjGu1b9EHLdq3Ra+AQmMxK6E1KKzCLIU2g5vo8zUhISETY3dt4/OAeVBoNtN4+0Pr4wNvHF/kLF4UXdVryFgdZ7CztzuJHC39zUGaT5jL/mQMwdQheOncW/T7uibmLv0frto3twtmR75zM2vCAeqYmJUB7BiQSoD0T14wBtCMVLdgZ4p+mgrXhpNVhD9JXbz3DxetP0LdNBRGERcpZrKYFUIteLbCmfbDXQShEje8oZOl1VtN8UxV/Srvjq/krlUgwy1C191os/6od6tYsziBusTcUSguoSUFfu/UEy5d+ypS1AGgCMaloAvWN6w/Qrll37Dy4B0VLlGGQJiVNdoc1nDkwc989nKoWHsJhCYcggFl4FQCc9Cp0HHKgFlQzARdmI37d9BO++Wo6Fq9aiKbN6zqEszAgxSlrQ3wNCDvuYt6z7YSSEqA9AxIJ0J6Ja/oD2hbGtjeW7f9psTpEPrWtkqYb88+Td7Bo02ksm9gCwbn9kywPMZSZ3UEEE41Ss/3bUeyFTkI2qkP0FMOZQVqBz5ccReiLd9i+sAcDM1PPcrJBRK8KFZb/eBhXbyYBGjICM2VjqBigGahNGqxbvQ1rV/6EP44dgNrL3wrSApAFq0PoGBQAbdtRKKR1J3UScupYDGtONXNgZp4xr5oj3r7C+JFjEPrgIZb/uBDlypVM5jlzHnNSvrNjODMiW2dtiK8nR7/ExF/wtudKuL749yVAewYkEqA9E1fHraa3zeGqihaWTyn1zgJoG7uDV8j6RD3mrjuJBT+dxpcD62FYx0qcKyEGcjIFzcNarO5t/xbAzAjGg5mjWZK9YZkLS4adJ+9h8pIjOL5xIHLlzpaknuWknHn1zL9aAZp9TtaGktkb9Eqg5mwNNQb0GgWtty/mLF0IyLj3zeQGm+Q2yplT0MJD/LfwnhjIwqEI9oYtmAXAHjt4AOOGj0GHLu0wado4eHupLal0Qk1nZ+BM23M7a8MFONOiEqA9AxIJ0J6Jq2cA7aqKFgNQAIk9q0No13YouD0lLQIvDQtftPE0Fn7eHImJOvholLxiFilnRwqa7Zud3DSL7ORT7WxVtFyOBKMZYS/foVjhnGzC18DsfhycmUdNFogNoOUKLF9/BFdvPMbyJSO47A4FQZdTzQRgIzgQE6wjoxLQtX1/+Pj6YfGaZQgIys0AbTYTHpXgxtlw+26rou2deHsKWqyYBTA/f/oI87+djRNHj2Px6vmoV/8Di6VBE7y6DWd7X8rCjrqaVmf7pSopaI8SRAK0R8ProPG0qGhXIS3+KeoBSHMWhhkfdFuBwvmy4csBdVC2SI4kUAs3tLAftq92iSaCs1hNy2V4FhGPTp//gipl82Pxl22tOg5lChGcxaBWqrB83V9JgCaAkw9NsOXVs1hFmyBHog6YNmUO9u7chyXrlqN6rVowmRUWUDNgg9tPcRloAdwClIXDIyALilZQv8L/4a9fYPHcH9jIwB79umPUuKEIpFRBUapcmuFs9WWdypBuF9WzpKA9BxEJ0J6LbcaqaFtwp5YbLV6eoCnuJLJV0haFbcfy4BVyTEw8lm85y2yPkV2rY1K/2tzxWxQ3r5bFXxg2PiZbPpnNwV+icjn+OheKT77egyFdqmHS4AZcZyBvebBsDzGU6W+yN5iaViQHNH0mSwK0oKKZSmZKWsUAvP+PYxgzdDz6De6H4Z99CpXaywJqjmMceQVY2zvpnM0ABlwBynKZEY8ePsDWjVuxcc16dPy4A0aPH468eXI4BWahPdtcZ6F95jnbnmPx/+ngO4uPVbI4PAMSCdCeiWvqrWakirZST3Yq3gmfO4K0FaDtQFoE4tiYBLwJj0XOAC80GbQBH35QFG3rlUDlUnkgExS8PTDbRowH9aNX0Vj520VM6FcH959FIjpOj3ofFEvyqMnaEOAsY9OBJ4GavZ8SoEkFJ0GaYCtYHZydQbBW4dmTVxg9fCIuX7iCNh3bolO3LqhUrRobaEOqWnjYQloAM/vekXFV/J49eYw9v+3G7t924fGjx2jboTWGfzYYhYPzW4GZrWPpBLTfGchB2sh3LCbB3yNwFl9Ddq5uCdCp3/LuLCEB2p2opcc6ngC0WCFZqMErqbRAWgxwsYctzpcWWxcmmk3FgH+uPMKeIyH4/egtdGhcGt+NaIwfNv2DoGzeKFEwEMUKBCJnoA8ioxNYuVIqPHT/SQTqVS6EI+fDMGPVcdx48Bq921bCpAH1kCO7rxWYST0zOFNmBIFYDGgrWMutFTR9xvvUBGgTU82cYiarwwwawq3kPWfynjlrI/ThE/zy825s37yDRbdxs8YILhKMQoULo1BwIeTJlxdGoxGJiYlITEhAfFw8Qh+G4tb1m7h5/QZCboQgIjwczVs3R/vOrZnHrKQvGJGVYQ/MDMR8XWdhWbfhbHuN2F6HTgxKsXf5S4BODygkb0MCtGfi6lyrWQXSwk2dzArha0yz+s58Op0NqFkgTCYk6gzQKBWYufo4btx/hbuhb5A/tz92LOiGkTP/wG9/3WQlOIvmD8S+Fb3xJiIOD55EoHqFAvD11XLxtOkwTAZnWyXNQMxZHcvXHuQ86MXDrRW2jMvQYGA2c2Am5UyQJhUtfMZCwIPaZJLh4rnLOH3qHB6FPcajh08QFhqGF89fQqVSQaPRwEvrBY2XBgULFUSZcqVRplwJlHm/NIoXL8yWEdsdpIJtwcwBOCmFLul/UtPc8lxKngvK2V04i7/cHVzZEqCdu+VdXUoCtKsRS8/l0wpo2xtOvG+pjTLkiMOtYTtIwTYFT1hWWE4Ata0lIga1+Ka21zGYks1h60PbwNkCZgKw8GRKmgcye+VVMqlre4AWFLaMszlIRROMmZLm7Q0xpIX3xKAWwi340CldGmIgc7BNgrIYvmIw24c2Z2mwzyzFj1iwrc+l+BxadlT0a8pZ5ewEnGkRCdDpCYaktiRAeyauzrfqKUgnuwHtWB3OQlqAuBjodiEuQIIfKm4P0k7e8JbOQvGgFVaGlLc07MGZYCwCL/e3gr2XTEEL65NnzWdkOII0FyYO4AKMSWULsHbmZAtAFqArgJi9ijoRycoQg1n43LFq/u/hLAHamSvAvWWyKqDHAZgDICeAN6kd+n9eDzqlHfQUoAWoirdtL7PDHqSFdW1VmEUx81NniWFrpaaTQJ0k3vj3nOkgZITi89IEKHNE4wDM/hYUs6Ci+c9s1TOvrJevpTS7MM7iEHvWgvK2gbRgZ4jVtBjUluPiszhSuwbFQLaFMve/fTBz61mrZvH6aVbO4vNvexDOnitJQTtz+t1aJisCuiCANQBKAaiS5QFtD6TunEpHoE9JSVsBVjRoJCXLQ7y/QjqeI1DbHpudDijmXfMPSx1o8fHzQ6OTgVmAOAO1DZwt6po6DzmAJwO0WIHbqGi220wtJ+U9s0PkvWkB1OLddCbNLjmkk9sc1vB25DVze8MedtMpHVgZ9q4RR52C4nPqxPUoWRxOBMmNRbIioH8FMAPAbgBV/ycAndUhLVx4Yo86GZxT8D/tXbiCUmbEEqlmMZg54tlR00JmR5JHvXwNdRKKFLQ9i0Skom0hLYayYG9wyySl2aV2/wkqmR2CTW60IzCzZa06Au3A2WowUsbDmfZIAnRqZ9+9z7MaoNtSdhOAUQBCJUDbOelpVdIciZKrM0fwteqMtLOeI3hYyU9TEoRtD0kMasH2EFSzAG/B1hD/z2wMJwAtrGNjdTAM8r4zFxIOxIJStu0YFENbfAgCiMXvCR2G9qAsfs8hmMVffpkAzhKg3YOvM2tlRkD/BSCPnZ2fAmAygKYAopwA9CAA9EShgjmrhIaQK5LJH+nhR4tvXtvDtfsTN5XOQ3F7zv6cFv9stt2mC76m1ahCi4rmL1mxqrYCN6+eab8dAZpRUKS8bQEvdACyrA7rkYICqMWwduWqEg9eEXccWg9qEafOsa+KpE3YflHanu/ULC3u28bxLrtyfkStSAralavA+WUzI6Ad7f37AA4DiOMXKEADswBUB/AipUPO1J2E4h1PL0CnF6TFN7NTaXt2fFF7QHDmOMXKWQAqe7VjdwjviyFuUcTcOlYWhy2ghfXFoBdBmiHSwZBuMbBTu+3EQGabFIFXUMvW7zuwK5xRzY6uAQ/AmTYlATq1s+/e51kJ0LZH+L9lcQhH5wy8nD3Xztod9m5me0WWUlJrKVkZDvfDgZITOgaF47TnR9NntspZAK+d9y2AXjiUV9Z2MkJs22Tbt1bQAqgtp4v/PDnVqt4AAAlRSURBVLVTIoaxsKx9KLOvg6TmHGbeiJaxd/482CFo71glQKd2Bbj3uQRo9+Lm2bUyAtLO3NS2P3cdWRep2RgpHY/4M1vVLI6yIy+aQVlQ1UmFlWyVtl1AW63L+9UpQJqFzA6QbaFt7+IQw9jyvSMGMXvTCTCn9CVp75xavknS39YQH6cEaM8gISsD2umIZBmLQ3xE/xWk7d3kzoLamXVtz5rtcTqCtHh0od0MDxGc7YB3+eoDXBaHoKDZMjYqWryeo+3ZAXRKKXaOYWwDZGdil5q/7KpqZrtgo8SdvqusF5QA7WbgUllNArRn4pr2VtMT0CkpK0ef2dt+SqC2105Kx+DsUG9xJB1ZHYIlYuUhW/vVDgFtC3Px//S3Q1ALO5Y0oCb1k24Hhk7FORU7w+E5TEE1pyOcqSkJ0KmffXeWkADtTtQyap3/GtKObvzUQO3OF4JtTB0paStIiy5fWzjbgDdFQNuDdEqgtshiV+DMr+TonNr7wkpNMacU55Q6A9MZzhKgPQcECdCei236tJyRkE7xhrej/uxCxYFqc/c47IHathPRnsq1Udt2Ac0gbJO2Zwtme/+Lt+fuWXb0CyK1VEhhe652vIr3M51sDXGTkoJ290JIeT0J0J6Ja/q26i7cHO2FM+25kgGS0g2fmpJzJVIpgdkWpDbpeFaApmUtilt0CyRL7bNRyCl1YorbFI7JWRC6EusUO1xTsTQ8oJyFQ5UA7cqF7PyyEqCdj9V/u6QzUHV1D1Nr09nsC1fVmTPQtoWxeBu2CjYlsPKfOQS0WEUL20gN1PZUtbOxdzfmaQWzB+FMTUuAdvYCcG05CdCuxeu/XTq1m9udvXOmTXdA7aqKTG3fHdkKqcHUGUA7A+m0QDm1Y3M3vs580XkYzJKCTu3kpu1zCdBpi1/Gr+0MUN3ZK2faTW2Z1D633S97FoCz/q5db9qxJZFMQdO+JFPiNrdDapZGap/bOw/OxMipZZywMzIIzpKCdueGc24dCdDOxSlzLeXMDezOHjvbbnov5+y+OjuQxY7adQrQ9pS0sG/uwNjZ46LlnI6pk2DOQDhLgHblRLu2rARo1+KVeZZ29oZ2Z49daduVZV0BkR3I2j0UZ9LxANgFtD0VnRKk0xPWrsTNWStD2D9nOyfduTYcrCN50OkYTFFTEqA9E9eMadWVm9ydPXK1fVeXd2efnIGkHWi7BGjLNv7j2yMLgFkIlQTotFzMjtf9j69AzxyUbatZcqi3s6HJCCi6sw131kntmJ2xGRws4xDQjlS0eF9SyihJbZ9d/dxVKP+Hqll8aBKgXT3Rzi0vAdq5OGXupTwBQ3tHnB7bcaUNZ4BsBVLHI/tSBLQzkPaUqnYXyJkEzJKC9iwaJEB7Nr4Z17or4EvrXmXktpzd11RgvnzNn7h6PZQrluTo4WwGiTvqOq0gtt3n/8BnTulUSAra2QvVteUkQLsWr8y99H8Bzv9im06qZvFiTgHaFSX9X10JmQzMkoL27IUgAdqz8c341v8rYP4X23XBAtn22yncufcMX078OPVz4o6STr3VtC2RScEsATptpzW1tSVApxahrPj5fwFLIU4ZsW0XwGw5fa6uk1kgncnBLAHas4CQAO3Z+P43rWcEJFM6Mk9v31XY0r66uk5mAHQWgTOFV/KgPXOr/78ANIDXAMI8EMIcAN54oF1PNJmV9pWOPyvtb1baV0/FNhhATk9cuP+f2/z/AmhPnePzAKp6qvF0bjcr7Ssdelba36y0r1kttul8G2St5iRAp+18ZaUbMyvta1aDiBTbtN1H0toOIiABOm2XRla6MbPSvkqATtt1mdraWe1aSO14/mc/lwCdtlM7CMCqtDWRYWtnpX2loGSl/c1K+5rVYpthN0hm3JAE6Mx4VqR9kiIgRUCKACUfSVGQIiBFQIqAFIHMGQEJ0Ol3XsYBmMOnGmXW1DvavzYAdADuA+gHIDL9QpAuLTUHsBCAAsAaALPSpVXPNFIQwEYAeQDQtOdkd9G+Z+YHxZU86KcAWmfmHZX2TVLQ6XUN0I1KMCkFoEomzo1uCuAIAAOA2fzBT0ivIKRDOwSPOwA+BPAEwDkA3QDcTIe2PdFEXgD0vAjAD8AFAO0z8f5SDD7jU0P9JUB74pJI3zYlBZ0+8fwVwAwAu/mLP7MqaPHRdgDQCUCP9AlBurRSE8A0AM341ibxrzPTpXXPN0LnfwmAQ57flFtbKABgA4BveVBLCtqtMGbcShKg0x7rtgAaAxgFIDQLAXoPgG0ANqU9BOnWAn1hkMUxgG+xF4AaAEak2xY811BhACcAlAPwznObSVPLJCToy47UPllyEqDTFE7PrywB2rkY/8X7jLZLTwEwGQBZB1GZBNAp7SspPHrQftMIyI40XalzIciQpTrz6lkM6OoARmbI1t3fiC+A47wy3eF+Mx5dk2DcEsAwAA0kQHs01unWuATotIXyfQCHAcTxzdBPyGcACCov0ta0x9buA2AIr/qF/fbYxlxsOCtaHCoAewH8CWC+i8ebkYuTcqZfJNT/4AWAPGj6MumZkTshbcu1CEiAdi1eqS2d2S0Osg8IIvX5AlKpHU9Gf67kOwnJMqIsA+ok7A7gRkbviJPbo/uHPN1wAKOdXCczLCYp6MxwFpzYBwnQTgTJhUUyO6DvAdAAeMsf0xleTbtwiB5flH6G/8Cn2a3jbQOPb9TNDdQBcBLANT7Njpohy2ufm+1l1GoSoDMq0mncjgToNAZQWl2KgBQBKQKeioAEaE9FVmpXioAUASkCaYyABOg0BlBaXYqAFAEpAp6KgARoT0VWaleKgBQBKQJpjIAE6DQGUFpdioAUASkCnoqABGhPRVZqV4qAFAEpAmmMgAToNAZQWl2KgBQBKQKeioAEaE9FVmpXioAUASkCaYyABOg0BlBaXYqAFAEpAp6KgARoT0VWaleKgBQBKQJpjIAE6DQGUFpdioAUASkCnoqABGhPRVZqV4qAFAEpAmmMgAToNAZQWl2KgBQBKQKeioAEaE9FVmpXioAUASkCaYyABOg0BlBaXYqAFAEpAp6KgARoT0VWaleKgBQBKQJpjIAE6DQGUFpdioAUASkCnoqABGhPRVZqV4qAFAEpAmmMgAToNAZQWl2KgBQBKQKeioAEaE9FVmpXioAUASkCaYyABOg0BlBaXYqAFAEpAp6KwP8BdgzBsW8oRWcAAAAASUVORK5CYII=\" width=\"360\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display, clear_output\n",
    "\n",
    "fig = plt.figure(figsize=(5,4))\n",
    "ax = plt.subplot(G[0], aspect=1);\n",
    "contour_axis = plt.gca()\n",
    "fig.show()\n",
    "\n",
    "extent = [-5,+5,-5,+5]\n",
    "G = GridSpec(1, 2, width_ratios=(20, 1))\n",
    "\n",
    "mx_i = -1\n",
    "my_i = 1\n",
    "z0 = gaus2d(x, y, mx=1, my=-1)\n",
    "z1 = gaus2d(x, y, mx=2, my=2)\n",
    "z2 = gaus2d(x, y, mx=mx_i, my=my_i)\n",
    "Z = z0 + z1 - z2\n",
    "\n",
    "for i in range(10):\n",
    "    contour_axis.clear()\n",
    "    \n",
    "    # your code here!\n",
    "    a, b = np.random.randint(3, size=2) - 1\n",
    "    z2 = gaus2d(x, y, mx=mx_i + a, my=my_i + b)\n",
    "    Z = z0 + z1 - z2\n",
    "    \n",
    "    I = ax.imshow(Z, extent=extent, interpolation=\"bicubic\", cmap=\"RdYlBu\",  vmin=Z.min(), vmax=Z.max())\n",
    "    C = ax.contour(Z, levels=10, extent=extent, origin=\"upper\", colors=\"black\", linewidths=1)\n",
    "    plt.colorbar(I, cax=plt.subplot(G[1], aspect=20))\n",
    "    # end of your code here\n",
    "    \n",
    "    fig.canvas.draw()\n",
    "    plt.pause(0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}