exercise-3_sol.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "15db3f9b",
   "metadata": {},
   "source": [
    "# Best practices in data visualization - ASPP 2023, Heraklion\n",
    "\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": 1,
   "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": 2,
   "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": 3,
   "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": 4,
   "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": 5,
   "id": "86533326",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f2ac8091f70>"
      ]
     },
     "execution_count": 5,
     "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": 6,
   "id": "771bff12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f2ab4f271c0>"
      ]
     },
     "execution_count": 6,
     "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": 7,
   "id": "fea457c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f2ab4e6d850>"
      ]
     },
     "execution_count": 7,
     "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": 8,
   "id": "a220b34d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f2ab4d82b80>"
      ]
     },
     "execution_count": 8,
     "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": 9,
   "id": "e2b63385",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f2ab44572b0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tAfvqGfYogNvU+1vhXGsQM/+Jev0gEf0YEd00Z91tdHqgXeJmt4VsbrmxRie9jTnHeWgJBAe38/YAlekalhkYk5RllQA7F7Y5oJbqeOZCtlQLlMYGiSybLGRTwKZgLbXyE+xgWQdSHwsUgJtztxW2e+uw8H4AdxDRswB8EsBLAfw9vQARPQ3Ap5iZiei5cEHVHwL4z1PrbqPTAu2+IbukplS/HuuRNedY52qps9P7TGGbutWxW3qr5WbBFigDd9+FkaWYIJPFpm42hax2sSlgh50WSl8M6VubONc8cFN3W8ptrxJs93UrG2beENFrAbwDQAPgTcz8MBG92s9/A4C/C+AfEdEGwJ8BeCkzM4Dsurse0+mAdpfW+10hOwewc3LaOdKwGCvEz2kb2MqmLTI/263frMBHJtshYOcAVZZJl01dTGjUShq2sg42Ae/AzZYhq11sCti5DWImTVj0qYQb/Q6Bm7rbsSjhKjWQ7WusA2Z+EMCDybQ3qNc/CuBH5667q04HtCVNNX6NQXYsj9UdB+YU2Y/V2M4RjYBrSW6Z9qgKQEwXlAmmfyoetg3uFtixZUCdF0mFgHuzPDaQ5XW1QfTeO9YCZLWLTR2uaKr7rU24YCK4yi8EPa3JutupKGGJUz1VV0tU77BQFBHdBuCnATwN7qN6PzP/CBE9BcDPA7gdwMcAfBMzf3qrnSwB11LILnGxpXlj+52j9Ge83nap/Emvmyrd1lzgGhSWgXNqHDtcIAPdkbEP+kMWQCow9jNjiOptlNxr7r2KDEqQFcACSU470mkhFXMMNQHvGHDF9Wp3W4JttK9k+rlFCHXg73FtAHwnM3+QiD4fwAeI6F0A/nsA72bm+3w3tnsBfM/irW+by+4K2ZKLjeaV9rfA8+V6Rsnr0fVG5o/NM+pFdP0sQI079kaOI11Gto8sdN1m+3EN+sMZiQo0GAfjElAGpiNuNooYVGQwAtkUsFt1WMjEBSXgkoKqdrcl2E41kJ0VbGlvVQdHp51By8yPA3jcv/4MEX0Yruj3HgDP94u9GcB7sBS0uzR+pdPnQHbKxc7p2ro4NlDuLtc4lSuDSsEzJQGo3nbYdZrj+nMYQBfx+evlZVrY3UTdaepC5Vnf/SAFZ+pWo/fDZaNcdgKypQoE9z5/LtEgMdxnrv318JcsAS4IO8N2iU4Jtgs7LJyU9prREtHtAL4SwK8CuNlDGMz8OBE9ddHGdmm1LzVQleankNUuNppeAGwuSkj3BeR/Dof5CXBnjauq/lPObd23HqIAII6NkvOScy1CV8FZ1hsMZTh23BnQmnFwBviaBLZ6vqoyEMhaXkWQtdyOAjYdTKakUDXgIZYDqt9ImB+qDdS8Kdj2+yvntefTTbdmtJMios8D8AsAvoOZ/4RmfjMR0asAvAoAnvnMm93EqQ/r3MggTFNudilkbWa5qTsTFI8jAWhgrHKwU33/NYxkXT09XS49niYDRKFEDrwDF5/JVaNtLfhAp8eeNozlIEspWNO6WYOO2z6X9QC1vMq62BSwaQ+xHGyjXl3wztRntR0cEHPA1TAO2e0EbOc2jp0FbM94mMS9gJaIVnCQ/Rlm/kU/+VNEdIt3s7cAeCK3ru+ffD8A3Hnnl/DeIDu3wiCFbBoVRMsuvCvBXGlTm3OJQPKaMpAqADe3fnqcA0erwGswPLcSfMf2X1LaIJY63BxkTdtD1rRuWtMihazldgDZbgS4QA9WO1pt4OYZgZ6HrEAXjDxw2UUOFmZr2GptA9tjFgFoq6PNi5x1/UkAH2bmH1KzHgDwCgD3+ee377qv2RrLZacgm/58FsDKOqVt6f2NHluXz1Wjn96mvEzakFQC7RxrUPryGcC18cv6CGEMvnqa1liEkh5zmr8aBVjtZPX7pMIghWzHbQRVDVwAPmaY3xhGZNFF8UHjwMuIgBtFCh62gI8StoDtLnntsatmtON6HoCXA/gtIvp1P+174QD7ViJ6JYCPA3jJznua42anGr/k9RLIjgF27l0I0vpRtyCiximLeYBMf0K7jSpQZX7eZ7cjWa2CaHoOcr5L4IvktVZpjIPBF0YmKihBltoIpiXIynQNXA3YQaeFggOMen8pJ2sZ0MAF9W5XwJpGCXNgm2qXCOHYVUFbEDP/e/T/fVK9YNftl3c840OdzmeLUcimcNGQzQA2wDV9zkkBJvyaNAaDolVvaEODVaox+LiN5mOEEsBLTtRkvrjSL63BMvo6NP160fHnDyObOadVBk0Tn7ePC1KYdvANYBq4OqvNAFbcMAB0chqZXygOBG65xkA5TfcswDUKsuJkc2Cdgq27hON57dmI3HU7R51Oz7A5jSw5N5uLCsK8BLK5PDZytxnA5iCbHmtpPFZ42Oa+xZnjry/KwLTUIDRoIIvpFnX3jHiega6Ga5Ncx9KvhhTA6TZzKkUguXNs2kHDlwC0BFmJCiy3WcB2tger1cY+ga0GgQOqA29oY9R5LaxbXsUGS2Dr/iLTee25uFoCZt2m5hR1GqDdJTLILT8GWdv1y3Wb/rWGbArYKUebDsaS9KwaOtuRDDMHoOhntAnrp2OvzpH+wBpycO2n2e0ALMulGquq0DHI4IvFgNEOSrg0ZLtMbODer7KAtTwE7RCyFKYZQnCuso6hHrgC17DMAti6S2jgam6vVoRQHe0pKpfLptUFWrYbd7GjkM3ARaQz2dxhQpytLGb7MqxUM7JK3bffbb88qHV0mOr4XGNPD1n5QMt709j5AAaSv0Wh0XCsx1hmJK4og1U1sh2vRh1tDrD9c39sdnCYHEAgWaIJP3cpbMcB14DYRu62wToLW3dJmijHDRHBRIRwTiIQ2jOt7zp+0G7rZku5bLqtFKpzIBseCVzHHK0xqrGrAOOcwxOlzm6itKk0eApQdreS+BFsCJIFBMRurvE5pEBYA3iWA5brPqZcFYIC7FRlgXa0EhUIYDfWBCBuLAe4pi52CFl/SJQ+MwxRBFwhaRPGqXCTO17BoIOhTQRbDVagd7NzIoRzcrVUM9pL0jZDDY59oEuRgWSyJchuNmXAzokO0sjAwn3C1NVna13X1RS2JnF06eumDT+jU4dX6s8PjEcJFDnbHrDuvYOwNPykAJb1JwGsJX+nwZdM30CVjsClzzHnXnVUIK/XXQ/WHrK56KBcpqedrDy7RwxciRZWTQxb+a+Tg214n4HuWIQwplODba06OAbNcbO55cZyWYFstxlCdgBYD9lSjAAMrZChQSNYD1zV0i7z5vw/M41zswlkdYt7rnZ0H7DNwdQE6PYwJu4iOJciCHeJYhBYFXPkIpBSJ4SO2yxsxcU6uAIba7ORQccxZPWfsndaDqgNSVYbw1WA6259RVh3DEPGvVewzVUj5N7PiRC2HU7xGFUd7UVrH262FBnk6mSnILvp8vEB0MM3e0zwIO2G/4usjxH8umwtSA8uo5W6WV+kn0LW/WyerhsFphvIQh6bwDEFZwBtaRrLOq6+VAPbXb78tRuMQ5Bx6aWqAnfuLTrrIgJxsNrJbqwNcJ0THWgXu0EP10a52da3fG0skvcxbKURrJTZynmXIoQlOhVXWzssXLRy0FriZqcig7BcroQrgexmM3SxG1+NoKeXjhvoXWwaGWw2QNvGsUJO0YDWfS2pODjLLTZ846C1PYVQNP6qbxAKl0hdw/Q/u/z6JdgBbDWEZdoUfK2Cr1s3Xw+ay5Z111n9RVKKCoaQHQK21BiWkwDVvfY/WBRwAROmtwYKuIhg22GFhtYRbJFWIRQiBHm/xNWeBmypgvZCxCPOcEq5RrOpUq4lkI0c7kR8oJWLDDbor7y17lMl20mHGByUc7lnRhscXO9kh8/llnaL1MXlNMwkG/+6cT+hTQ9gDd8UvNrJptOA2MlFf8bkrgdRRutf5xq8UsDK63XkaOc3hsWNYOxhGscGEhNJdLCxCBGC217sbC2aUPrlvoDMZIQg12Kpq3XndNwt+kT7G+uAiO4C8CNwtS9vZOb7kvnfjH7Y1v8C4B8x82/4eR8D8Bm49uHNyG3NZ+u4QFvSLm5Wa7TxK6kuEMhG4B2LD1SMIMrls62/5JLPWusiBJs5n7AdVWlAroxLIoMOK3T2hgBX7Wwttyqf1Llk7OTC5RlxtQIW/Tp+3/hHDF9DmwBeGzWkOYdrQ1VD+e82iBAyYxakDV4OrjZysWubB+xcR+vON2306t/Ln3WlIBs/u/X1rwrLQJM42aZUBrijqz0F7YOzRNQAeD2Ar4e7ffj7iegBZv6QWuz3AXwtM3+aiF4IN7DVV6v5X8fMT+5+NE6nAdopzXWzYd4wl10E2dTdpsegy7kAZ0vkf5DEBeJqA6yb4XkASUmXuFkPWW5jqPKN2NgbQz7pfjrbyNHlGn9KpUxaGrSNAm3s7NJpDQy1AbyGNn3coCsXkoaynNKxY+NRuPosNnWwG+tcbJrRCoA1cDtxs5kLYjwkG6JshYFRsYFcL/2sYdtZoDEmgFPntYQuymb37WqPWXvMaJ8L4BFm/igAENFb4G5EEEDLzP+PWv59AG7dx45LOn7Q5txseL+Fm5Vlbf+auy4BaJrJpvMLEUK6PyCJDnw+G7JZ5WTThjxgWO7kYWulpEnBVkN2bVtsLON6Z7M/mzVkgGnYDov0h4BN4dsaGoC3NTc46LKKGvy5Gupmudpc91nnYhFcrH6tXayeJ4BdW4b1D/dn0FUHHH3wjSHXCGbcANUNkT9PuUY2LN8aYG2du3X7dNPkNUCuk4qKEMSV5hrGwnUouNp+/mm72mY+Z28ioofU+/v9kKuAu8PLJ9S8RxG71VSvBPBv1XsG8E4iYgA/oba7tY4ftDnpD+Q2blYvxwksU9eaQjbXODaV0eqGrtTJhnzWQZetBZlMThvdPWDlW+HF2fqeUB6yAlh5FkeXa3nXP5eni/TLoE0B2wS46nkGJbcrlQcaGtKrKvxpVWNe3/Fg6FTlnPX79Nw1YK1cD38BusyFaAwBnYesdaC1htAxYWXiGEUksJXXKXDTCEGXfA0axiZc7SlCNRXRIkf75Eh2mttI9n83EX0dHGj/GzX5ecz8mL8rzLuI6HeY+b1zDyyn4wbtmEMt1c3mNNIANuj1FUUECrIpeNWD+5aUeL+GANuBjO2B27aIGr+0q80pVBxQiA10dBAcrb0xQNY9nIO71uXzSsvAurMDJ1cesUp+PseOrgRao9yegKg1jNjhemgRQTeuhVNXEAHiUbX0T/7UxXbhdSGn9Y+NP/8ugFb/l1F5tSFsOnZ/QktoDMFwD1y0JjgxiQhEsYuV9+SvP2PVDCME3TBWbCRUdbVjOiUAE/bWGPYogNvU+1sBPDbYH9GXA3gjgBcy8x/KdGZ+zD8/QURvg4sizhi0Wrk+8+n8OW421yCWRgFp5UHB3bKzhEDHfhfxscm4s9wQSJd0iSRWyLnjeENRSVdfD7vqHS36uOB6x7iWuNrgbj1cSpAp55O9MXdAdJAx5J7b1gTwinMV6G5MD17tdDc2BTXDWO0M5UMXVwXkGvW0U81VHGwso2PGZmOjc990cWyQbQzr4i8b93C9voy/u4R1ZQcAhrAFJEKgpBHS5bU6QtANYyVXiwTA5zM4+N7Ku94P4A4iehaATwJ4KYC/F+2J6JkAfhHAy5n5d9X0zwVg/I1mPxfANwD4p7se0PGCdsqlAuNOUC8zqFSwmSqDxKluunxjmIbs2vZw9bANzw257LchEAwYFjDsgKud7BhgB3It7h1iN9vxDVh3PUyvBVfbQ3ZtHWSur7sIMPpnc6eAE+3Vg7bRjpZoCB1DaBsDY6x7n0BXv15bB103LXa6QP4nZJoppx0P8oDtXaxAdpfzj5wsbP/FIFUkCrbuGCl8F5tw3G66fIEEQEqX45muFsCsRrGTcbUh695NzLwhotcCeAdcedebmPlhInq1n/8GAP8YwF8G8GP+/oZSxnUzgLf5aS2An2XmX971mI4XtFrbNIJNuVmgnMvqDHaziSDLmy64WLbWfYI67uMDkX9PHYEbZ0lo1eQdbLBrNj52iRu8m5UPIrMU6Ts3u7EmgqqOD653FtfWHTadxXpjcX3dO9r1xgbIaDeXZpQBsKmr87BdtQbXyXpn66avWhNB17lb9sDtHe7adm75kHNyBNxUpcoJHQ+kDYACWDnfzaaPDrrk3HOOXrJZ6wErwLXWOXnLXT+mgbtC+oiT9/301rhsVlyty6p7VxsavJTDFS1pFDsV7bHqAMz8IIAHk2lvUK//AYB/kFnvowC+Yi8HoXScoB2LB8bW0bFBus6Ym43A2sVxgYoTBLK87mLAdpx3pMaAOw9ZGDCkF9Wmjw1EYw1qQKg26GODNgyoIs7tetdnshqy19cdrq1tBJxNZ2PQJA1C7lA4uv2zMTSA7aoxuL6m4GabtXvedIy2sWgMYdMYtK3BqjG+Mcj46KB3tDpGaBLQ6nFgAUSAlWw22yDW2YGL3XjYrjc2OufJLxofH8h5t42JHD4GjtFEx9472WGEIK5WZ7W6AkHqanWHhpJDLbnX03C1fALHuJ2OD7RzIgNg+qd2VMKVVBrI+lOPDHQFsry2AbAsccGgMYxBjcvuGBYEV+LFhkGy/TbjbFOpygXre0V1ys2Ki1snjvbausOfXdvg+trB5tp152yvrbvg6Bx4AJtpGBsehgeNjwWMIVwXd9o68LSNd7Lr3tW2rcWqMwG4a8NY+ShhY7ukFIzDM9B3Egh/dlWKlnY8KEUFDrh9Lt07W/esv2xyikq6fHRgLaP1LtbltAYatsYQjD+mMI0oGyHkXK1UIEhd7a7xAXAasB07z1PW8YE21ZSLHUzjfO2tymqLbjZ6HT94YweQ5XUX4Oicq/qgGvIgdq0YhMbltA2BoqqDiXxW3cKGw8Aquutp37Ku4wNxstfX1jta9z642U3/CI5ORSA2OSbjQU+GYBqdzxLaVQOz7tB6sK5a4xrBOv++M9g0HIDbNgZWAdf1w+cQJ0D1vspV5Uw2hmWiAu3kB7FB4ubTigMAIZu1CrjpMq7DAsMYdwxo3XuB6sa6WGTK1aYNW2mjmDjcND5IlYsPpgYSukwR2I3/cIY6ftCKcl1uZbqODbLr2Hj9OW7WcnCzIR4QyK67ANYA2C45ro5dgxh8Q/G6A6EBrrvslTeda22eU3UAuIzWxqNXuX79HBrAwuuNDXGBhuy16+5ZQ7ZbW1gbw3bU0UaQNSBDaDeSzzrHuukcaNvOxwUerjfaBrZFqHQwRLCtgW0QGs5keuxoe+ma3xS0uqrAQTVtAHPnLJUXuvoixOTd8PqbxsD4BdrWBOCKWhi3DXLxhDhbYwgbdR7ueIeuVqorxNU6GPZO1sJE3XJ7wMbHevp3YKjRwWkpFxv46bPdbFpdsO56JyvATRvFUlnX+4ctgVbSIYGAdecihaghTB9nDnRxY1gfG3RRCdN1BRMN2T+7tnFVB9c7XL/eoVtbbDYdNr5xjIO7s7Bd7OyCq2skk3QVBk1rYBrC+jqhbRtsVibA1jQGbWdhV02Ug4qjdRkuhXnGUACurssVdxsu6QC0HEUFkr9qyGonuw5xCQ9ik9TRhvNW7y0DbUOhrCsvg8a7WokQdLyhXW1/Ln2Lu+tWHDeK7Ss+OHbV6OAyVIoNxn5qT8QGxe0VS72S6gIBbgrZpPKAjPzct315F3zNpFENaNrF5s5L3XabWd+exkSg0Q1A19Ydrl+3wcG6Z4vr1za4fq1Dt3Gudn3NZ7U+s5VHiA88cAWwck59ZGBgjEHTGmzWFu3GoFPAta3xrtHghlUTfqL3tbsmgLZt3LKtL/5PM1rdIKZhKy5WxwE5yIYoQZxtxxFgI9CqL83+y8W7eMsAmgDfVK46wf0djCFsNhbNqvGAzbnauLFMu9FSfIAFMDql6gNy47Jd9mEcRMcN2jGVxpxN50fgLcUG+emDyCAs20M3qjzQhyfVBr68i9CADQNrV1sLa12UMAe26LM1Pdh1PFiMz2rFzSm4XF932Kw7XL/WYX19g83aYn3dTRNIpRFCTgIbAGhXTXBsbWvQrhp0G4tN2wPX3ihwdS4xdbe4AQAMrHWAXHkw6/y37/seH1OntqPdqvsxkodsn88Ov1wkn06zabb+uqvYRK5F7vqsN268A2v71x1z5Gp1h4V+WtwoJvFBTrq+diqnPSlRdbSXqzn5rFah2qAYG8g6mTihd7AWvLZxQ1hU3sVgle9RI/3YfUbbWN8IxpEDphmQFUcbhggMJV59I0sY08D/NL6mYgOJC9bXxdE6dysZ7WbTBdgGV57JKtG4TJYaUpD1gN1YB1zbKIBZ2Btb97r152AZXev3cR2wrbTe9/WoulOAzQBNtqMbseZAVjf+hUbAjtFtumibWsb0sQFbA6xMONeN7/5liJyT9mDdeDdrDUJE0ayapMRLgCtj1WbO0Vcf5HJa939rmMWedk7LMLSZXuwEdRqgXaISdHMaaQzTbjbksio+6F2uAqz6xDAs0AFkDXhlQO63Yl/a1Zk4ly3FBjKbfcVBNBBJF/fz99lsVFXgf0avrzknK5DVjraTDNr68yx88sn4+KNxACTvatvWoO16wLbWNdyFrLfrB8mxbb/tdKQsB1w7GE8A6B2kHpNBdyHWnRBKkBVnvdlYbPyXylRDoDQAulgDwBoB/q6zArDxf//G9JB1z/6akGuoSx1txwTD7qu4VH0gf+s5OW1JpxUfnMZxLtXxgnZf+ay8zsUGQO9g9WuVzXKYxlFeK+MccNfntZFC1YF12abh4GqlUoE6vW0NeZsdfiicjrpbgut66ht3fL3oWgH3+rUN1td8Jnu9C5AVR2s9ZO3a1wPb3tVKfTCpsevcuRhQ4/JKMoS1z18DYD20bkCL63AJwXV1/KWf3f6V68vB3APXUJSb6lG2cpCNIBycL8IXi0BWnLwAti9t612s2wb5IRItjGHX8Lfu/38ZamANh6hg07mOGnIMxvhjMH0mK3DVkM0NOpXLaUswOvUGMQLj+G+3s52OF7RLNZXPpsrFBvIaKLrZANm1jSDb/+TmMKhm+NhY536p8SODCMisjaODnHT3W2kM42bgjkLLu3a00ii06Rxs110M2T/fwK4dbGE9dL2rja4FEDpMUEMg486FuyYAl1Vk0AYHu0Fr3esUti6flU3HrfjGd2111yo/bKEMhKNz2h68NuoVJplsCtlcxUX6X8QdnwH7LrjtymCz6dC2/flKjGKJh5DnGPb+v8MgPtDTp3Jage456vTijnk6TdAuiQdK+Wy6bhIbhGqCjJt18E0gqzssWAaMqqFF58Y56JyrReejhC5zHBPqKw6SxhXLUX2oZd/g0zE2Usq1sX0DmIIsbxJHm40PvDO3BDYGZAnUMczKoOsYpmOgM9h8zvC/lDEUnO1GWvElJvA/s1sYWHKucOXzTxmwJr1vZf8niyHb18QmkFPXZQyypegAfrwCA7jqipVrwMO6rzJwwyiyagzj8GXQkYevjw+0m+3YD09cyGkBZOtpB7W1M4dNPG5xbQy7UJV6fKXLzGkIKynnYnWEAMQ/obWbDdYjhqwudjdQjWEeLixxQdhX0zeIhWMqH7fu1ZM6WgcL5/7WKqPtNq7xyzX62BAXDCCbxAfhvL3Id75wsYGDLq3c8ZsVq4/8JsA2lEY1DgCbhmCMh+u6A9DAmPjv18IE2EJdFh03RKVYSRfaqIxLdcxIG/40dAWwpWoL63/+m8Y1/tmOsYH1NzA2Pcwb5Wp1dYWqF3bxwTA6SHNaIK6nzf5/yNyOXKanwDqFnJZQM9rL09yxD3LKucT0p3oCVyjXKrFB1s1mIKtdoB/kzr0xDDbeEa7gs13JaCe+ELyYm/Ac7gybONq0p5NuXRc3ay33UE0h63u8pRktAFcxAYAMB1drAMBSGJ8qXNXG+vEBPGB9L7LN2sKYLqrH3VDfam/IgQg+EkiGD/B/nkxjmHKvnb4O3EPZwdRfC53RKsjKttlyOEYpNwv7dwMYADCwxlVqiKsVkMoxpCODyX8z+ZvlYBv+3knVwDYNYqdXecBoatXBCShbO5s0hGlpuPrnKGvVy6RuVpZJIMudG0iGLQfYOtfau+BBw9lUTptRn1IMHVRwWF0PmE7KmZRrzUFWclp3fuqDbvuxDsgSyDgXS5YCDw0Abshty0gJmMQAXQAS6+NkqHIoDlUM4motPOhsf77ukvXPg6igEBnE9bI8gGzUUaPj4Mj1X8bluAakIwdxtVESpI9FuXB1l6L0OzaF7VXUaX0xzNd5gXaJSrEB/KAzelqme61AVyCr3Z9+jQYy6jOw8m4J8C6Z44+VBn8GvOJkda8wWS0HGgHKZu2gu9lYoFOxgYA1hWzizt1OnBONBiXxP//ZcChdE8jyuoNtCJtNF8qj5FjE1QYYkgkOEMa7yMa5XGm917vVVQfyPq0y0NO1m+0f8Xv2y7n15Nqb8K9Mccu4EjTrA9b+2ccHCVC1+jKvtFtx3yA2+LsX3O1SHXt8QFQz2ovTLlHBXBWz2T4jHfx8TmIDZMCa64JrfT2lW86CVsaXbzX9dqfkb3UCDEdf0j9L+9PrYaIbe0IsoMrWpKIiVBysu3BO6flw5525L943KwOyFnat3Kx3za4qwWeSXX8MMsQgp1D0Xw4CVokQAPSwVRoM2J1cB7146mbd32UI2WHVQQ9cAwD+OEwT58UmB/fkV0anlskdZ+SG9bGryoNzrjYQ1Yz22DW4C0PhP2TOMpQ2GQCa31YUGSTblffkRxBJ3WvIaMPGhs56Sv13wDAPTHNHAYoANJSshSoL72T1l4Y6p/SqEaxzrsaNuMS+PpgNg4wFdyZu0bcmcoDpT25r2RX2e5DlMtrG17WG8+PhOeZig1TiZuU8NWTT5dNGOMAfv+EQH+jrvURjUYEen/bq6HzraA8+OCUR3UVEHyGiR4jo3p02tjDHXLQt/b4r2AsPn1LPKc7M43T9nINdeF5x9UFuc0MA5Y4nAm76pTGIDvpz1zCOzy/ZRtfDK3WwAPqf6smg4zmXDuTraefMS2OCfnrigjPQDF8U2ZK3fvvRe843iEXRjjrHtDlgF9mJj7Q0qh6rCHbWY3I7E9whp3/l5/8mEX3V3HW30UFBS0QNgNcDeCGAZwN4GRE9+5D7LPYOA/JAy1UgAMNBYnLgwfAndnbZVHPiggkNfyq7D3UKHB0fiGPV9bLRcesGvwlxsr2wXSCCbbqPdOCaCHwcQ1A71Hgbw3OP14nz2VTpNA3KMRDHx5bJsbEfWM7RsQNzG7meYetZj9HtzOPOCwHc4R+vAvDjC9ZdrEM72ucCeISZP8rM1wG8BcA9B97nWWpsZPwheBZsV1zq3JUmlg2wTWGW6QyQdnkVZXuCJcum1QdLpWOAJdsZW27bY6kSucawOY8JzeHOPQB+mp3eB+ALieiWmesu1qFB+wwAn1DvH/XTgojoVUT0EBE99J+e/OMDH85pK/1ZWPqJvdtO5m1zEB/oqo2BY9zPcU4526rTF7Gd9QBwk3DDP16lNjPJnZFl5qy7WIduDMsl/dGng5nvB3A/ANz5X3/x5X5yTKZC/hBqZtRKpv1OT1SznfIlyTW8LVi+MGzj1LyqmZpfdfQkM99ZmDfJnZFl5qy7WIcG7aMAblPvbwXw2EH3SKb/Y+nXgIdXUj5SAlpDgIqCyI9d0K/nbkEdda81FPUqGqg4XXXoT4+HLhi4cp+VmQrnqo57MNrXgRSGTtwi8zaqZMz4L1hrOZmeP3Z9v7TBvAti7THXw24v3ld55xzulJa5Yca6i3XoT/H7AdxBRM8iohsAvBTAA1tvbZ8uL92Wfq8dp0leGxqFh8wrPYeRvRoqO9uZ55neuDB3yIPjS/ZJ/nyWAFEG/9bvR49z4fxmFHC++27p3A2FW6HLWLKD+er2NJP78VA1TfkameTvZagf3lGew33Q1OtwvvJdtQdITw2TeNSAZgC2m/cY1xzuPADgW3z1wdcA+GNmfnzmuot1UEfLzBsiei2Ad8D1lXkTMz98kJ2l7pUKMUAEzgzQ1HxqCLyWIeuG2zKNgdU9drwTCnAtfIJoDtQXaPznrHNexhDQOEfvhmt0g8Owdu3izoGyq9X7aobXj5rk3GU1dRuYsOyC8x09RyJ0vqtuzt26m0lyGF9Wtmf9r4+0/9eYox3eCTi+p9gSlb4sAHdpr1YNLQDEWf/WWylwh4he7ee/AcCDAO4G8AiAzwL41rF1dz2mg3dYYOYH4U5qnlJgHkJZN9tF0YJEBQJbd58vcndMsAz4QVYkiRg4Re+ATGPcug2BGvVzU7vI3FiAS0/Ju6hm4QefGjd2AVsz7RTE/Sp3Rw1FDyB28QPg+jvo9u/HXaW4wHRe2hCme48Zf92NjwLkrFwe6xyq7bqw3U5FCNZaBU8T1qMErPpYyAyBGzlYNS9zSaPn9LWG7VG70X1pT5/9HHc8YOU1A3jN3HV31fn0DNMiA/AUNDRcEYEuOFhpHPOQHWS2HQdXy5bzP6fTT1AaGaQfPnmv7n7rzqdwGhlOpSCTh44JBJZsDMj4XFmtl9td5EDl/mHJL4RBVIIhjNJjDMeZgaqW7hkWBprxl8h2/qaOlmCTo5d9xyD2+W7katFvUN5lIBt+JYRhIOXZFL/g5AuwiW6l7vehnG3u9FNnu63TPXpQ894y2qPTeYE2FxeQcf3DxTXqBjHtKD10Q6OXNIYpADkwKSDJ/awQRwgicbMBYipKiDLa6NiSaKGg3M9OgVV4nTip4DqNCXdJIOvjkca52sHN/pLGvdTNyvFH0+T4G5MHagZQU+cWQJW4UL2OxAfuXmPqbrr+3CQ+sOgbwOSeZPEwMr00ZHOxgTh0yYaj8wxfHvlfGMPv2D2EtKeuCtpL0i5RgjH5u7lqkAVHq6DXWAdRDSJjwA338YG/44B83E2uXVEcn44NFOx6CCtXPdZIV1BDFDUgpc5LXgNd72YDEG30kz83hunAqSs3m40OGoqAHGDU6GM0ybEOHa843FzjWJjmXa0ekCasr+IDq0AJwH1hwsFXS5/5IA7wA3+Lm9VOXYM11xAWtkny8NtOnuW13P02XHd/ZEtGtzrJjHef3eyPSMcJ2hxcieK7JkRlT0kJV2f98iP70O42jQ8iB+sbjazPaDvnaknGmUVhNwKVhvpPV0O9W5XXubIuov4xolzRQupiUydmmwS4co6wYXDvFLbZyCByx/1zGh2kgE3zTCB2do0ZOj+9rCg7+ItFFB+4wxq6Wre+iwvaVQN9GxuJGAbQb/qSrsjNisNttLPN5LOUg+4QtqmrNSM/94nsAMgyfbjskccGgB83+gSOcwsdJ2inlKuPtbYULALkckgOP9HT2lr/bDj8rIZysH1Zl5oG9ED2rwfDJHrIkmoQQ0OglVHzjd++ig8ytbMyFm2qKCqg+EMdYKdyRoEhS3ywakCWHVyVu5Muv5R0qZ9sDBPwNv5OuRHw+yhBg7gk7Qpz84JSV2tcfOCGNBy6Wlm/j3jjyCmCbNMft1zDdmXQtg2alUHbmhAbaLjqv0dwuKQgLPPi/0pZCTh16VZaxnU2wwvW6OCEJCAulXgBCmwqvxV3q+ID6ig0hgVXCx8doHHjtxoCpDGs4ySLNcDKeLi6Z4kNBoDVDpcEuu4n7pj0h7R3cN5tKVAYD0mzMqHxjqx7b2H7L5CxS9uoyGDVDNysjhAErqWGsAjCieMbOrvE0XJyi5muvxODuFrj/y7a1QINsOnc3WzXNoKtXHoZZEbHGxqyg8ig6YG78s42xAYqnzUKqv1jOF1Ku0oVByfhTrcSgytoL1ilbFbc69Q6uvIg1yDm3WvY5sBZKgfr72AL429IiM5FCIAbwNtyX2cbnJ7ftnavAldxtsn+Ikdb6BE25myzDU/pT11jYRvvZiN3yyFCcJeMBt1n0wavNKONgJu4x3A8Ew1hevmSm5Xz1WM9GKKBq21hsIENrrZt3Xt3Wx65m60b4YvUYDkyULucc9oI1rRN9L5t4qigVTHCqjFJR4V5kUHY/4KKg6nOCkcvRs1oT0apiy01iOn5At0oPiCw1M525GALgNfWAfgGgK73hURkmr7IX+AgML3BOPe3Mr0jXDUZN0vqHBCAKz/jS0PjpfFB5J60+1INOH2nBXbZrCVXPbEuf5ijKoMMXMMyPjYAoDLMTOOYBnASE0QOOPMlYi0HuPYTEblaAKECoV012Kx97ezKuL/ppneGpil0dmiSY/SQbVsTHhFU5TySaoM0NjBE/ns3hu2+GsK0TscB1/Kuy1WIAmi7BrFSTptmtoPpnFQb+AgBBrSGg62/HxhbjlqntIul4Fg9sG/QDrYQHyTVBrkBnbONJ9HPVhUb6JxW/fyHjRvE3M0k/W1rDGKHYXqAhshAA1fNC1GFgqscX9RQljFyudxZn1/UWKVqaQEHVgBo/HMaIbStu1mkU+NvQ2OjbWYbw/wXikQHGrRtY7DywBU327YmbhSL4oL+O1W/Hl4H9UWQ+fLLfSEKjE+y4gCIP99npNMAbU5TDWK5nJZSqPEQbjK9bUHWRq6WV43cQs/B1hIYnYNp6oYCdFRG6zNNkgajtu0fft+hKkHig5mDykgeGL+X3mk6p+3jA7NidB2DGi672aYJd/Z1hxWDNa00iCA6UsKVc6zauablarmMNwBRd1ywzuW2voFLRwgC2bb1kYFxlQbUOdfr1h/2DNPlXAGiEg+oY28bgybAFgG+IT4YfSCbz+ZcrFGO11UenIpjnRIDtt5u/OK1bU4LALB9TmsMwGpbqauNpqnpbQuC+8MzfFRgDGjlts+AiwA6Dh90tjYq4XK5rofSyjg3uzIRXON8lgaQtWzApduqApHrk5+t7pRiQKTxAYw0hAFAF8FWbq7oLqly6ilk9fuR2KCUz+Yy2BxU+/f+r2sTd+thG722hJW/dbmGrWVgs+6ifUhW26h8No0NItB6oLatwUo1hrUawJGbjZ/HYoNwrQNsu/B+aQxwOrEBakZ7FFracWEsPkh+Dg8jg2FuG3JZwHVgWMEtY90NCQH4yoMm/BakUN7lI4OkpR5tJqcl09fPJo42d5eF8BNUuyt5rRpl5GfvZuMcW7My2FjXCCSRCIA4OsgOyhNDNno2fTyhs2F3KsMIod/ksIxLxwapW5c/m79IEWx1RwaZlsIWPrPVN3A0htydd6N9JKBtDNwPEedQNWTj+IAGbrYN8MXAxaYisiE2mJvPnnxDGICa0R6TxnJayRRL8UGu+sB2EVBz4KXWs1pyWQBsydWdWuvWA+IRr5TbC7WzKw9hHReE+ECg28awNSYL2DH1sO1/wutnV6Tfj29Axn8RrBP342ODcKmT+CAq7VJuNo0NchGCPtbo2Cc6aej5rsQL0LCVjBaAAmsMW4kMLDl3a9VNJNPrCCAANq0qSCHrHG7fGOaAnLrZvhFsbmwwqJml/A0KTz6fBSpoL01jTrY0L1fmFRxuoVGsHbkUmw3IWPAqbgRjWKBpeuDqrloCWP87kVaNy2rbpgdr20axAWlXqxrEmJtQ1lVytbq12+0+cZZN/7NXoCSu1gCwaxuVd+Uvd+/U08aw1M3qYRF1xjrVEAb0rrQ/BznPApRNPzB+gKtXCttwV1riCLjAcGTI6NeC+sWwUo5WctkwrzEhUmiI0BoTudnY2Q5jgxSWaf2shu5UPpuLDY4ewrUx7II0NyIYy2llOwZ9fAATVy9oV9sC2KAcIXgI02bjYOsbwUigZ9h1Zoh2T3HVQQrZrJttesiKq1Ujd5VqaAeXhpLhEpshcMMYrT6jJRs3iEkdbTrMYTi3tDEscbO6pKz/k81rCJPp6TkBw0HBu1DmFX7GONdKDGkE1S7WeMCmwBWlY9GmX1x9Y1fc+OWg23/RrBoBbA/U1ky7WbfPLnKtJQcbrs1MeJ4EZLvaGHZxmnKqS+MDIG4UA2JXCyBXSxtc7gY9bK0FbzofA/i8t1B1QN7VwpCCrIoMJEaQ9xquIZ910cFUfNAk3T+BTMYYAGsdcH3pkx6RbE5GCyBuDENf0jVcPD+koD6+ePlh41cK2dx6/fBbsbs1hrHe2LgMzL+WYRejyCBpc9RVEPJlEKKDyNmSig9MBNfY1ZbdLJBGB93s2CDML9VAHztkRTU6uERtGx8AsatlIOtqgdjJylXZbIawtdZ9jK0FGw4DsUA3pOguuBINaPealnW1rYOywFWcLU0DNq2l1U6sbxCzDrCN7Z1Za3y3VYaVrqkTGS1QyGl1pUHkmpPGLZ3bZnqEDc5BrV+C7AC6FhFsJTKw1rtYFRm468SDRrBo+xR/cYWoIHK2MWRXA7giqjTIuVkg3wgmr6dig+HAMidUbSDi/dxh4Rh1vKCdEyHk4oMQGXTxNAAgX4aVulrZlsQEm40Dr7wW2FqKgWtt2D+rD2soh4riiRSySYxgGqBp3UNDFy4yYDawMLDchI5uYz+v0wYxPaiMuNlm5e4ooLumTjmfQU7bDEe0ynVb7f9kQ1BmhxMccbvZBjPN7Qxs3bFwBFwAEXTH9pcep8u73esyZOEdrW8cM6boZqOHagTbR7XBybhZoIL20qUrCMbig9AI5nNZAFGHBVbLSgUCMMxqNWSjZwDWA16BltKSMXkOoE0gq+ZRLjbw86wH7JRittPwERXcN2EQlrRrqsUwow31tIOeb33FQa4RLDo+cffqeHPLpRms5M25zFQUuuMC4U/egNAR+z+VH6c2A1wDApphxYHeRwpYaaBbNUk9beJgHVg9jCPwmsjNClxNoV5W3GxpWMSwXKYB7bR0MY6WiJ4C4OcB3A7gYwC+iZk/nSxzG4CfBvA0OIDcz8w/4uf9EwD/A4D/5Bf/Xn/7m6KOG7SzXS3Gl5NlgN7VSgVC4+NcHSEUIdsqwFIPXJFV4JZtjkYH/jWRc7I6m/XgkOjAwoyMdSC7610SoADRqPKuxrqxWL2rtTJdHPnKgAWyaoCZSI0J0yPIGj3QuHK3SS6bzVij85FtDKdP5roepmHAGet+LGjgGhAsMUymESzd5rCKA8HFhhIuQwGy4mDF1ZYawMTlkgZoxs2WM9dybBAvd0IOkTEs/TiM7gXwbma+j4ju9e+/J1lmA+A7mfmDRPT5AD5ARO9i5g/5+T/MzP987g6PG7QlTeWyAEKjWKgMwLACIazG4DG4DiBrY+CKrOmpBwyjg0yMQG2LUDvbtIPGMLZN1CuslNnmYoQoCzQuKmity2a1q+WG0KLBxg+yEq6saQYjeLnr1ccHUeNbIaftIZ85xsQp9pcugfNErDCQ/9Mbo91s/90YpouUqx1my/3xpvmsQFZc6sCxemfbVyD0f5e00gCYdrPR9TsliM4Rs/usHV73AHi+f/1mAO9BAlp/6/HH/evPENGHATwDwIewhY4ftIOaWPWfS8cHc9yv7p4buVw/Ipf+yQ+bgazPaGUZFR1klUYHGrjyHMBKCrZJxQFPu1m3u3hAGZnm4gKpn+1dbbvS27R52OYuY7Zr6jCrzV+S3mGX5muVxjyYA1sjHRlUXCCRAuCgm5xZvH7yy0CmiYttgjsdQrZNAKyXSyODJW621AiWrbs9RRDPjw5uIqKH1Pv7mfn+meve7EEKZn6ciJ46tjAR3Q7gKwH8qpr8WiL6FgAPwTnfT+fWFR0/aOdIN4pNuVqJGaTRzMo6FtS2YO1iBbbW9t+0ktEC46CNclpKeoIlbrZRrlbV0Wr3OlbiNT2CV199oGHI4jwlQgDQogmjWVnrxuAt/qxO3KrOad2fone2pfKv/KUbNnrl3G4z0igmjjU8+7jAzZMBZMZ/pqaNYaFiQ/X0ijsj9M51FU0vRAb+oetm03ENroybFc0H7ZPMfGdpJhH9Cly+mur7lhwOEX0egF8A8B3M/Cd+8o8D+H64sOP7AfwLAN82tp3TAG3O1eYaxXKuNkA42Ub4bYlQhRCcLpAA1uSjA/ktmpOAIY0OQo8wX2kgbtYYoInfW19tMKcLbvrzO0BBfcgFgm3beJD2+ayMbOX2JNcHYVuDQv7wbAq35B6627QSIm3Jj3u29ftOc1Kgh2zKbkMUYr6mIXQc3wdMoAsggDd7PQfnGQPWZGCbQjauOBhGBtIAltbNFhu7zt3N7rG8i5n/RmkeEX2KiG7xbvYWAE8UllvBQfZnmPkX1bY/pZb51wB+aep4jgu0ApxtLnbJ1UZRg0kY4mGr81ppHBPp2CBTbTDP0SbRQdu6wWckKjCJo5V81lcchO63UuZV6KYYBpc2SUabuFsrUULHQOu2vVl3EWxN0/gbFvqfswnRAjyb2K1GNzHUjWCZHmYl6db+7HQPuTB94GzjOy9YjqELYDDmbPEYFNBTwOZA2yTTBvMLkUHaC+wQbtZsOXD4hepiGsMeAPAKAPf557enCxARAfhJAB9m5h9K5t0i0QOAbwTw21M7PC7Qikr1sUtdre60kIsQAAzyWjjYwhgXI0QKLSzK1ZYcbTk6cCN8SWTQxFmtMW5eUmUwegubAnhSwLp7W7lIgK1Bu2Js1hZs+jKvMFarHwNBgDvYb3THhKTRK3G26f21ogaw5ItgcA6JU9eQ1cuk1wRA+EIy5AegUcvZXOwQbSNzHJQ+x3GANHzpaTo2EMga2mQjgzGA7upmTwKyFzdM4n0A3kpErwTwcQAvAQAiejqANzLz3QCeB+DlAH6LiH7drydlXP+MiJ7jj/hjAP7h1A6PE7TAds42dbW5W5ZP5bVBPrPNVhpkYgPZb1TeRb2jHesBZnQnBbdOuH0NmmId7fBnM6Kf49EzuR5MtuvdbJ+nGmBjA2z1BuUeXIM7/CL+WW08rANY9ZgKaXXChJPUsYGenkI2ynBzca2KESLIMmeX1+tF13SGq81nsv20VZPJZTORQc7N6ihhGzd7EpAFADD4AsY6YOY/BPCCzPTHANztX/97pK2j/XIvX7rP4wUtMITtHFeb1tUOXG2iNK9NYWtM/0M0rTTQzzJg9KCOtn+EuEDcbGj4ojg6APxg331skMK2CIPUxer4gKm/UeGq394GvrYW8EMoWh8bxMM+ptKNX+ktueUxuAMu9euW8llgOIJXeu4afun1iJftX/cOd8rNlkA7BKyukdUlXNrJasga2gTICkhLkNU662xWVLvgnqB0T7G5EUIOtgSQuEztWiU2yMUHST5LUTTQ9vWyIZ/1gA2NYSbksUB/U8Zco5gaViH5OR7/7Jb+/uJqBZBsTd/DuGNgI9fHRjcsLI/VmoFswc2OxQZ6u2kkUGqIipaZEQFPATZdLgfzHGA1fPsSroyTVY1faZVBTlfLzXpV0F6Stna1mQghRAQTsG38Otaq+MH6bNUDtwRZddz9/b+UYx042MTN+vpZ0dyKA3lu1GtxjW3Tj0Fr2EUHkda+os2fP1l2JV+W/WnabGNWesPFvqrBYFhXSyHa0G6235Ys17+PnguQLTnauVDNX894G/p9CbC5SgQ9kDeRRUPrAWTHIgPRtm725CALXFRj2IXr+EGbUzZ/HYkQ0nEQdMkXEMOWZLnE3YZ9euDKPorHSP168hAnq11s5pl9Q5iOC3TDmAMAq5/Q8rovwdI9mDoP2ZUa9FsiBGPI3cPMwzYMht2529ywZRgfi+R6TqUVBxFkJ9ysnIseghCIhyQUN9ufe38N0p/16TJzNYR0PL2J9pnud+hioxKuLSAbrq1qADvbulmtGh1cssYaxqZ6hOWqENiOwxZAFCUg45Dls5kDvn6dG8hbKguk+iAZUCbks2hm1dEOGmwCZAnWxq62d7MWMvjqZmPdwOQdARt100IfHQhgS+VWcXfbHrLSgyq9FczwDgoK1gq4OTcblhlMQ5iXuz5TivJhiqenjWHpMY1BNpfJliArKkUGZ+9mGRfVBffCdRqgBXaLEHJ5bW6UL80geUHiXv0C1ubhrRUyYdO/T52sAmvkakd6gEWXg+IPvpsWO8a0d5i7Ayy7XmBMvlGsd6sbD19jOfQOkyL/4nFoSOYg6yMDuaFh6mpj95p3s1M/1eXc5bro65FTqaQ3vZZ6e8PIYhywoaFrBmRFSyKDMZ0kZAFc1Ohdl6HTAe1cLYFtAKtytjLdqm1p4Ep+K8un/zE0XIECUBsFXAVd9Jns3NvWAPJh5/4DTz1UXV8J4w+Vw2vRRpV1tW1/yxfqHIjdejas705RZ6vGn24SFSi4a7jmBmUpudm4nKuch8p82QYwhGm5KmE8Nhi+jwEr07aBbNhnttPCeGRwNpUGqSpohyKiHwTwtwFcB/AfAXwrM/9nP+91AF4JoAPwPzHzO3Y7VMxztfEBlhvHxmIEqJeDOAE9dIF+ePx0v7IveU4hGzWO6YYwVWUwMRatADZuoGG0htCxe79q3ODexrqMNicH0Pj22zqrbXxGaxJnG+ppMzdibFdNiAvSW79EDWIjbrY/x9RBFmCXiQ/mRAnTsE3jArXPBLAAZkM2P20I2bOPDEQ1oy3qXQBex8wbIvpfAbwOwPcQ0bMBvBTAlwF4OoBfIaIvZubdRyReEiGkGkQMGdgyx3FAMTLA9FCNGqRAxskmuS1cPgsM62a1GgMY6xrBwmEmENKuVrJawxQqDzR4N7BurBzqb7+tgQt4GKfDHKZZqm74SiArrlYihDjW6AfRjiMD7SDLP9mB/jYx7loMYwQ9XV+z3Py0YS1bfWAU+DIuFsBsyIrm5LJnr1p1MBQzv1O9fR+Av+tf3wPgLcx8DcDvE9EjAJ4L4D9MbnSqcWuuxiKEHGwBxJ0aEtDlHG4unw3L63xWMtoEssl7GaGr7xU23D6RDXwduj1WUOpB5xrBVBbttdnYANv09tsauMCwjtadIkWv00YvcaerJJ9dtSaGcJrdmlIem8lFRwA7B7hLo4MSYN0y3WDaHMjGbnh8QO9d3OzRw/riuuBeuPaZ0X4b3O0hADdA7vvUvEf9tHmagu3cCGEJbHVXXKAM3Gbi2GS/0XMJsn02OybJa6NcL8kuG+IIRq0xsGzdADIh3kjiEfQATW+/rYELOOjmJDdZFMACiNxr7u6xJpqWRgjx3QryjWAxZEtVAe55GqrD5eJp4eaJyIGx7GKBOH9Npw23lc9l9xEZHD1kAQAXNvD3hWsStGPjOjLz2/0y3wc3JPbPyGqZ5bO/CYjoVQBeBQDPfObNasYFwja7ff9cAu6YNGDlWCl9JI1kkGERpaSrr5vVLhaQD03cUCTPraHQlz9ktSouMD520E7WresAmwOuWy5//ilcw2vTl5Xl3K1rJEO0TNuapMpgHmQ1GMfy1XDMGaim03NwDX8L9ICV19OOdRlk9xkZnAZkATAGd10+F02CdmxcRwAgolcAeBGAFzCH8fseBXCbWuxWAI8Vtn8/gPsB4M47vyRtbVkWIyyBLdDHACV3K9ktkPykGYGudk06n03drEzTz3NOMfxMLUGod7OG3NioiBrBnKtNIwGBagrccIuXBoPhGSNgqQas1KHmbtG9JJdNnW2pd1Z/XcpwnQKrvsY5uLr1YsD2r0sw7bIAXQLZbd3syUBWVDPaoYjoLrh77XwtM39WzXoAwM8S0Q/BNYbdAeDXttvJCGynRvgag61efyy3DftSr6duX6P3n4I2jQxMn8eO1c8SdQC7PxfBojEGGytg4RAf2ABbgYiDbgpbN/CYCY62S1ysAFfm9aeuGuCMBtXQ0ZZKukJcoKatGhleMB5mMAXqWBdYoORq4/fueNW1TToLuOtdhms6XwNW5qXudji9QnYgZuCqOtoJ/SiAGwG8y42Ti/cx86uZ+WEieivcjcw2AF6zU8XBEtimyy6BrVZalTCoRBg5Vv16UOKlIoMwv19nHLYWBh2sB27s+gDL2gkC0jjWGgIsXF7rt++A6UbtcpehvwV3GhsYfSeC/K3LsvWw6W2629a9jiKFDGQ1YPWIWHPGGZD999enHAcMXmcgNwZY977kVsfgux/IjunkIAuXjuVuBnoO2rXq4K+OzPsBAD+wy/YjHQK27kDjeCBX+qXhOZbryvbT1yXIKvdrVQeFsdIuwH9o2cKQiaAq+Wzvag3iMgmDTsq1xMkSQ6IEuQW3AHcsNtDSThbAALASFYSKgwBeg/QGhzoqyEE2jRFk/2lD2FhDlr6O4XXiXKN1CnWsY3Wu5XnbQTZ/3U8PpqOyAK7vXgF6jDq/nmGiObAFxt3tUsjKttPXAtmsVDlX4U63YXNSGO8fjXFVAdrdabhuLKvpfiMWgL9lTQt3v7DGMNadc7cC3NbDVUcFXcZtpHepBZAFrIavvots7saFcyGbawibAuyYa80tF0+b15HgEJA968ggiKujPQotzWuXwBbIu1vRHMjq/cgx6e3namjnbA5ucOgu+d3uWr5jVxtDt182GsObgWbVeLiKk6U+OmD245srVwt32zO3reEA2sPOC0PA6oavlYLqFGRzo2OVGsI0YPcJV2D/gC0d29WELFx2UDPaI9G+YQuU3a0ol+FOqQTZjOzMO926zbmcVu6+0BhkXK1bdm0R3m9sP90yYWMtVo2LEkIvMB0dkOsJ5qBKk3XkYRxZSkbnSgBbulV37v3KDIE61hCmu8PKtQLmxQLxtDJcc8uNO9MK2UW6AEdLRE+Bq/m/He6eX9/EzJ/OLPcxAJ+BG0ZgI7c3n7u+1kJ6HInm9MgaWz6FXtRoRf1Db1MeY/vVD72NbKOYawSbHAJRN6bosiL1GDYeUQCVzjtbY8ItsOX1yjdGta1/NO5x46rBqjVYNe5x48qgbSj7uHHVL7dS22jVdleNCccj+9ZxR3TrF7MMso0BWqOuCalOAr7eNfTagr85YrKMNGBJviqPOcvJ30f+Nv3fy41bkIsKtoHs2cvX0c557Kh7Abybme8A8G7/vqSvY+bnCGS3WB/AKTpa0TbOFii72+x7FSnobY8elwL0oIfY9PdabtQuog7MBgYWDAuGgSHnasEIWW1ryJd8cXgttwaz7DJbV2PLYZpl38GBAUvUN5aldbQYjw7cpYnLuwAgdwuaHDj1nWTTZXM9xGT/ORc7pyRLX1sg7zTjdYcuN7fNeN152063n84L+z13N3txwyTeA+D5/vWbAbwHrkz1YOufLmiB5bDNrTOID5JcFojhueTYcs8Ls1lxvPKaqAN5wIZpPqsFpJzLYGNtBNu1jw4cXN325bUGbgupXCCgATruwTumqKZ20Eg105mqeTqnLblYuS5px4E5JVnhuEeigeXLxjGBXmfuPtJ5YTtnD1k4R7uefS43EdFD6v39vvPTHN3MzI8DADM/TkRPLR8R3klEDOAn1Pbnrh902qCd0lzYjk0Tzemhloso9HPkhvOxgetua7Lv5TUVXC0s+TyWs7C1vh58E6DroRrgK++pd63CV0PF+EwxNrjctNRqLmDnRgU5FzsXsEty0nmg3M7FpvvKzXfX8ApAFljaGPZk8nM+0tjQAQuO6HnM/JgH6buI6HeY+b0L1g86fdDOGRMBmB8liMagO+eYSusl720mKkgrDAwsLCHEB5YQuVoQYHgDmBaw4iZj2IprNVFs0LtZN20IXfccH18xOkiAW3K1suyukM2NnAVMA3aJex1ffgjYueum+8vNd+d1RSALANhfz7CxoQOI6FNEdIt3o7cAeKKwjcf88xNE9Da4EQjfC2DW+lqnD1pgGrbAMncr00Vzx1sYg2riZrWyzhYdQHFmK1AVVwuC7ykGgABiV1sLOBcrsBWAbvyC2t0Oo4TezWrAxrDNRykarPFzJlvdErByHXIudmnZlV5GL6eXTZcfzptef2yfue2H7V0pyMJFBxdTR/sAgFcAuM8/vz1dgIg+F4Bh5s/4198A4J/OXT/VeYAW2B22QHn9paVd6TrpIDJLNhMcK4LLFVcrjtaQlHhtYLkNsBWIbvxp6YxW3K1VJmLMzY71DANidzsEbv96CrB6+ZKLleuSG57Qvd4/YIfgXA7YdL+5+WGbVw2yosJwnHvWfQDeSkSvBPBxAC8BACJ6OoA3MvPdAG4G8DY/tEAL4GeZ+ZfH1h/T+YAWmAYmUI4S9PpT25hzDOn+Es2tm402TZ3LsRR4ZQjFLGw9jXV0oOOBXJygoaufxcXmgFuKEFK4yrScw53b4DXmYuf23NLL6OX0svl5MSQH48YuiAlyywDjgC2tcy7iC3K0zPyHAF6Qmf4YgLv9648C+Iol64/pvEAr2sXd6m2I5g70ndvHYJllgA1j0Xq4Slbr5vXgTWHLbEDGNbitO7eQzM8BFxhCF8hFZhTBNoUsgMG9u4ZQ1a+ny7bmuth9AXbMvabbyC9/GMievZhdecwZ6jxBC8yHLTBdu7dNdJCF7ILVYWGBaADwsDkVJ4RbhyWwlfeAG/e1swhxgCsDowi4wBC6gPsPMnSx5XK3ORFCLlJYUlEwZwxYt+780qzhvGVwzW9vHmCBq+1kta7swN8nrTmwBWIo7lowPdqhYWb9LNlBx4USXOfCtjUurnDA7bvt5qoO3Ot+30t+zY2Dtuxs59yLS67NEhc7t/a1n3cYwOaWC/uokHVi1IG/T1ZzclutuS63tF5p/zOlOym498PqA90YNgZboINFE8ZFAFy9bQMKDtc5W/16mMVuD9rerZbe5wArr8duFSPXYfta2f0DVu9/ajlgXlRwZSALwJV3nef5nj9oRXPdrWiqq+3cfWaUNoSlcAXcB9twPzatzmpzGa2GLZENcBXXqqcxTORwgwNGrhGsd7xzle/A0L+fc7PD3PSpOxnoeeGaoQzYKbimy/fr7QZYoEI2q4sr77pwXR3QAsvd7T72FTQNbjemQZzJplltFCH4LrkD2AKRu208ZEO9LVw0QbChwUxcroMuB0BajsE5RznQbnOzw3i55THBtoCdC1e977nLAxWyRfGiLrgnpasFWtFSd7vN9ndZHTKuQZ/V6ghhCrbA0N3GwG2i6bI/GUZR3LWAV2tOeRewn5sdumV3y2FPDbBT2zh31cawc9Mh3G0RsLuB17naPkJIYQskGS0K7ta/FuBKhusmu+2HbQOgJD4R51vSoFFo5Gf8knEJjgWwY7eWqYDdXcz1Dgvnq310Uki3s83q6EfnYm4GrlZHCCls9RgIUmUAAhofEbixEfx2lZMFtGPtYqeL/oPfu+qZwCi08C+9H9euDV271r/2y20HWKBCdqlsdbRXQLuO1rVnlSKESdgCEXAj1+vnCVAlrwVipwsA1ufFOceXwjinHFj19uZmrHNuJ5MeZ6mLbO58LhOwc7Z1ZVQbw66g9gbR8e0YsoMRvHKNYm5LLkIowRbIQ1XmicMFqe1kXKwGL8Jm0vOYn1HOHUi7AvZqiwHwxQz8feGqoD0i6TKv8QihAFu3kXg56gJQZT4wBLJeRoAU1/Mu/wCMFfLPuRdXbrlDAXYXuALLu89WyGbEDFurDqqWa7vRukp1thq2APqPqodl0d1KZQIQRQqAcrlAcLr9ZvPOetZ5UDkfnRoPdvq2MhWwZymuVQdVB1QuPgDiCCGX1+bcLYABTI36vzvIcNHntUACXgBQILFTMUjxp/hYNcK8e3Gl26mAPU/VjLZqb8q51tL8EmwBDKIEIFOV4FYMCtBN3GsJvFrNHuIDOadwPLOc7ukCdu52q9zgXVP3pjtVVdAeTMtig9TVTsHWTU+jhB64gzgByEJaZJPy2F1ig2g7IxGCnEO/z7F5FbDnr73cSvwoVUF7xFoCWyDp2JAAF0DkWtN+Bybz/zuF71JtFyWk8w4D2EPBde62qzKq5V1VyzRjXINMfFDKasM6CWyBsktNgasz3ChWSLYRHc8e/s/PG1awDFegAvaqiBlnW3Vw2Ir7qsVKP+QEmzi+LoJI6gYFQgY2PNxyXQCYLBceKDzS5bZ5ZLabHoM+Pn27bn386fnlrk3u+owtm7v220YEFbL7EIOtnfXYRUT0FCJ6FxH9nn/+S5llvoSIfl09/oSIvsPP+ydE9Ek17+6pfVZHe4kqNYplOzEky5bcrZvXO1cA+QzXK6pWkGkLu9xOKedq3faHQNz3OATVwZ6QLq68614A72bm+4joXv/+e6JDYf4IgOcAABE1AD4J4G1qkR9m5n8+d4cVtHvXfn4kzIUtgMXABYbRgigH3n0pB9b0uMKyFbBXUheU0d4D4Pn+9ZsBvAcJaBO9AMB/ZOY/2HaHFbSXrLFSrzmwBWJ3K8sAQ+ACeegCZfDmlL+P2fR6ormNZG67pWUrYM9NF1jedTMzP+72yY8T0VMnln8pgJ9Lpr2WiL4FwEMAvpOZPz22gQravWr/kXcJtgBG3a1eTi9biglK8Mt1UpgL1dI2w3ZGgFcBewW1rAvuTUT0kHp/PzPfL2+I6FcAPC2z3vctOSQiugHAiwG8Tk3+cQDfD1fH8/0A/gWAbxvbTgXtEWiqA0Ox59hM4Oplh8vnwRv2vUfIbANWt16tgb0qWpDRPsnMdxa3w/w3SvOI6FNEdIt3s7cAeGJkPy8E8EFm/pTadnhNRP8awC9NHexeLBgRfRcRMRHdpKa9jogeIaKPENHf3Md+zlm7tIiXssupFvjSSFtzH9ssP/84ysev1x3TNlUEtYLgEuXraOc8dtQDAF7hX78CwNtHln0ZktjAw1n0jQB+e2qHOztaIroNwNcD+Lia9my4XOPLADwdwK8Q0Rcz8/wg7+S0+3fWlLMFlrnbME/BaszphmVmnsuSRrM58BpzrnO3UeOB05UbJvFCMtr7ALyViF4Jx62XAAARPR3AG5n5bv/+L8Cx7R8m6/8zInqOP+SPZeYPtI/o4IcBfDfib4V7ALyFma8B+H0iegTAcwH8hz3s76w1F7YARoELLIdubhuH1BRYw3IVsFdDF1Texcx/CFdJkE5/DMDd6v1nAfzlzHIvX7rPnUBLRC8G8Elm/g2Kb9D3DADvU+8f9dNy23gVgFcBwDOfefMuh3M2mgNbYBy4sh3RFHTDcnsY3yB7LDOhGpafCcAK2HMSX91BZSZa774XwDfkVstMy15B31J4PwDceeeXnOhV3n+1wVgUMNj7BHD19qa2uRSI+9IS8G0L16X7qbpYMQObzWUfxWE0CdpS6x0R/TUAzwIgbvZWAB8koufCOdjb1OK3Anhs56O9gprrboF5wJVtas3d/j61DfAqYM9fZ3onm+2jA2b+LQCh0JeIPgbgTmZ+kogeAPCzRPRDcI1hdwD4tR2P9Uh1eEgtcbdADKQp6Ortp9oHgHcFXIXr1REDONPk4DB1tMz8MBG9FcCHAGwAvOa8Kw4uRkvcrWgpdNP9XYZ2gStQAXuy4upoJ8XMtyfvfwDAD+xr+1VOS92t1i7QPaR2BauoAva0xaigrcrq8mC1C3CBPNwuAr77gqqowvWMVB1t1bFqV+Bq7RuCh1QF7PmJcYWrDqpKOp6f3sD88q1TVoXrmas62qpT0jlBt8L16qhmtFUnq1ODbgXrFVZ1tFWxjh9YOe0ygMwhVKFalYr5PAtpK2ivuA7ZWWFqH1VVWle6C25VqtN0s0tV4Vh1GarRQVVVVdUBVRvDqqqqqg6t2hhW5XQ1YoOqqstQdbRVVVVVh1Z1tFVVVVWHFQPYnOkYf/W38GzVS1VVdVB5RzvnsYuI6CVE9DARWSIq3rKciO7yd/F+hIjuVdOfQkTvIqLf889/aWqflR5VVVVHIcloDw1auNuD/3cA3ltagIgaAK8H8EIAzwbwMn93bwC4F8C7mfkOAO/270dVQVtVVXU0ugjQMvOHmfkjE4s9F8AjzPxRZr4O4C1wd/eGf36zf/1mAH9nap9HldF+4AO/+6Qx/+0fHGDTNwF48gDbPZRO6XhP6ViB0zreQx3rXznANnfW7+PaO74Zv3vTzMU/h4geUu/v9zd63ZeeAeAT6v2jAL7av76ZmR8HAGZ+nIiemq6c6qhAy8xfdIjtEtFDzFzMYo5Np3S8p3SswGkd7ykd6z7EzHfta1tjd+9m5rfP2URm2tYDMRwVaKuqqqr2odLduxdo7E7enyKiW7ybvQXAE1MbqxltVVVV1VDvB3AHET2LiG4A8FIAD/h5DwB4hX/9CgCTDvmqgHaf2c1F6JSO95SOFTit4z2lYz0ZEdE3EtGjAP46gP+diN7hpz+diB4EAGbeAHgtgHcA+DCAtzLzw34T9wH4eiL6PQBf79+P7/Ncx3+sqqqqOhZdFUdbVVVVdWmqoK2qqqo6sK4EaInou4iIiegmNe11vmvdR4job17m8fnj+UEi+h0i+k0iehsRfaGad1THCpS7Jx6LiOg2Ivo/iOjDvrvlt/vpi7tPXpSIqCGi/5eIfsm/P9pjrVqmswctEd0GF1h/XE17Nlwr4pcBuAvAj/kud5epdwH4r5j5ywH8LoDXAcd5rBPdE49FGwDfycxfCuBrALzGH+Pi7pMXqG+Ha3gRHfOxVi3Q2YMWwA8D+G7Excb3AHgLM19j5t8H8Ahcl7tLEzO/07d0AsD74Or2gCM8Vox3TzwKMfPjzPxB//ozcAB7BrboPnkRIqJbAfwtAG9Uk4/yWKuW66xBS0QvBvBJZv6NZFaue90zLuzApvVtAP6tf32Mx3qMx1QUEd0O4CsB/CqS7pMAJrtPXpD+JZwh0D35j/VYqxbq5HuGjXW1A/C9AL4ht1pm2sHr3OZ0CySi74P72fszslpm+cuuyTvGY8qKiD4PwC8A+A5m/hOi3KFfrojoRQCeYOYPENHzL/lwqg6gkwdtqasdEf01AM8C8Bv+w3UrgA8S0XMx3r3uYJrqFkhErwDwIgAv4L7A+VKOdULHeEwDEdEKDrI/w8y/6Ccv7j55AXoegBcT0d0APgfAFxDRv8FxHmvVFjrb6ICZf4uZn8rMtzPz7XBw+Cpm/v/gutC9lIhuJKJnAbgDwK9d4uGCiO4C8D0AXszMn1Wzju5YMd498ShE7tv1JwF8mJl/SM1a3H3y0GLm1zHzrf7/6UsB/Dtm/vs4wmOt2k4n72i3ETM/TERvBfAhuJ/pr2Hmy76Jxo8CuBHAu7wDfx8zv/oYj5WZN0Qk3RMbAG9S3ROPRc8D8HIAv0VEv+6nfS9cd8m3EtEr4SpRXnI5hzdLp3SsVSOqXXCrqqqqDqyzjQ6qqqqqjkUVtFVVVVUHVgVtVVVV1YFVQVtVVVV1YFXQVlVVVR1YFbRVVVVVB1YFbVVVVdWB9f8DFWb4VJEyV84AAAAASUVORK5CYII=\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": 10,
   "id": "89417ca3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f2ab43b58e0>"
      ]
     },
     "execution_count": 10,
     "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": 11,
   "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": {
      "text/html": [
       "<img 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Sf9gLA4YT1o4aDmMbZbDeCWAQ0HSm1VTz46tEJbDiFnIvt9KCzRtAAybAeUEFTT8c14IHM4NcJeRNQr6npD6/4fbhqATeip+myJg0Q2A8YcFAOOJBhjR26DMHkae2PoHAbyHUSYA3wPwMF811fJCDTCi88A22GIL5DYAhot/fbe4gkOzUFFIXdKs4zz7bZ2nEgDKdgCMc/sq6R+R7iTyevy8eRgxG5UZMGLnXvh7A4zCprINt9gCDT0czWhFWp5nyHOlXknwN/2thrUUIOr+XxQsyu5hEDD+eDxaG4PHzd9iIanI/DfA2OIFwg5vFohZINoIqDvIDUXlhKVk+5ywVn1upECyWw9d5hzGbfsr6YsKAMZj5wwwYnPRACNmIfveLFByC+TnQILqqizhHfBcZWGnxFVFEUDqP33IqoinUXbA+NMCgPEYA4zoTDfAiJrINjALlNsCDYJOIuzkmwGz8lyGpHIAI+vH8D0YWamtB5GCoFFmwLhdfyV9yQTrY1q/Hjn7YwtJWUjKBJRiN4p9370WaACLUGtcQaO++S/LWfgyWu36poehZIPr6PIuew6DgPHSAoDxCAOM6I1gHkbURLaBWaC8FmjoFvfSsEIF4oWZ+CkSsPJWfXGy3pIKpOJ4qOTtqUHY6Z0BhweVSD6j7B7GywoAxsMNMKIT3QAjaiLbwCxQTgs08lF5LXHljaIo09pRR2uuBIQKGP39SAgQZKwdHEYi+hdewzsDkCq1eTeTD9LDeHkBwHiYAUZ0ohtgBCZqVo1SJOkXtfQWbZB3Td18PVtkxlIetsa7ELZbehCerJCMt6RFF7U+L8BE8CBgMGxFkkEChNKjU1ODWhhCba5U6QGpYdLXtWy1BIxXTO6MjuFDj/zIchiWw8jPYay73r2uQaqMi25zEZ8msyC4pjJeT/QO7/ENHGAoRboPOZGZdm0Vog++NI+UIkwri15X46hjvqWuBgGDehoEieFRJ8s6Oul0MUK1vYDivFvZam9fEDB+yQAjekf1nIfRuKjWNTRFO2qD+vV11KlHR6KNDYrJhPoDNHQIl+962jBFT/20ChiBd0HNi2MrSJcXvMzrHLDolfuoC87vCTLMX6hEKzXBx6eQkD6Dn5RoHWCIyuc1mAD3tCHNQKPMOQwCxqun4h7Gzx82DyN2A/UUYBTj7KmX1MwheAuJ37YQNIpdD6dAeE0trsdXz5i3EbttyvF9Sg0N8TA8YKh3obrg84cBaoPPzwKLC+JlpGtr7uQrFSQEjNFxYGISmNoBTMwgGZ9BMjrhAIP5jVAbo4WIUtkB4zVTu6KD9nOH/89CUhaSciGpA5//rDOFsnjqzVbDCOqbnUKj1TB6egbPGnZPh7lbscg2Mp368ITU4Z+s1t2HXlMuQ6mntw6AcCuuJ3pH2wY1FqgFDIaiqKq3inRlEen8IYCAMXcYmCVwzCGlh3H0aAYYGBlBQu9ichqY3gFM7kDCN3mXRNe7LpfRpYBxh/5KWgQwftYAI3qH9YyHIYARgoOKy+gTGuO6WsNeAxhaq96+ZkB0NNaxQdP6+7BhS0DRN2xl+/YdvQQHDTVozX2droKBxjoGZAs2zQAjTHYzHMXcBQFj7iBwhJ+HkS4wLLUM0MPgnGC4iYAx7gFjZicwvcsBBiuKCBj0MAgaqujXxYDxZwU8jJ8xwIjO4t4BjGs/4564RQqzTs1Ma9czEPEhnKaqZLXVI7H4bnQU1rlBLljoNbEKRv59vLbb14ebHAVEncqaJjazWHVcw3mdp2ybb4AFGgAjzF8QMGZvcd7F7CEHGCsrwDHmMFJgYMABxtgYMDkDEDCmdiKZ3gUwLCV5jO0DGK/jdUVeDzlkIamYjXoIMD7twIJehADEceC4L0NkY9NxuvPHqmCiC6yvVa/RPebTWaajzMW3WHNTbDCKft9QTqkxbH56/Wdp1AqvSa+H512j4+wTm3JNHkiUHqLFE2XRc7XtNs4CNYDB+VwDGAxHHXQhKfUwFDB4HyhgqIfBHMb0TiSTO6shKSmxpb63nxtd6mHcsX8gfX0BwHjQoR8WyWE8EMDrAPQDeKvX5gkHeQrAO70EQwXAqwD81cbNgs3dc48AxkXpgc99ugoWYWMTF1WWIB5dQbq26kCENx9fvFGYHGQCcGhE3ok2N4UVJAWqSDo5rLnllAoQbNZioxavic1aXERYm8+nSp5n/wASPjnq9YR192GC04OghaU6OXKd3VdDDoMPCxzz1UVJdqeaw5Ck9zzS1RUXkiJgcF6P+KQ3cxj0MiQcNYNkbKoaktoGSe87VgbSNxQAjAcejAIGQeLbAO4P4PsADgB4FIBvBiP7fAAEjecA2A2AKqFnADjW2dHfmr31DmBc86lqqIY3li6srFFfXXLNTbLIBs1NfLrSxVUam8aBkXEkXGT5VjqFIAew0QtstFnr6DLAksrVZbku6fIlCGqzFq+HACjXMwqMTCAheFT806Q8UXpPAwkSYTC1VxktUFNW6z1LSMPeKrA058pq5T0HLC+5Xgw+QPDFcWYfhlRJTbly2okZ9zkc9GKENCHd6mFUBtI3FgCMq+KAcQ8ALwRwlZ8Pz/OfLw3mB/92NoCnAjgXwCcB3AkAq1C6/tUbgLGHHsYnazth+SRGsFielyShNDctL7oqEj6t80VAGPLNTQSLsUl5+nIdsUHZYcHmpk7MlgwwspxF0NlLsNBmLTZsLS06AJTa+9RJeHKRYDklG7UIfvzkNUmzlgeN4HpilBCduCbbx6lZoAYwNBwpYcij7gFocdbN7WVXUgt6GPLw4JPe2rhH0GDTHsGivqQ2nNstHh7KXFZLD+PPp/mw3/p1/4P/GwtJPRQAQ1JP8nt6LIDLADwt2PMEgA8BOA8A//0IAB+NHbtbvu8dwLjmEw4IxLs46jthZ91T2OJc9SlMbiofwhHvYgiQxqZJ9/RFXv2a5iZH4KYVRxv9RN64SPjcC8spCRa8lkV9qmSH7zJwdNUtEtrdywWCsevsqXIayXAdCGb5jGRLSoa75QbayvNseHjQvBznN70Mltd6D1pDlAIYfHF8Q++Zc4IPEHxw4MMQ53SWv3A5um7t9L5TQcC438H/vRnAwWBMrwbAt74oCU3vIgSMSwE8PdiGoPJTAH4HwO29h3ERgPmtnCudOnbvAMZn/8XlJsJadWlqYr36rG9u8nFefQobGEAyNOxcdjY3aZxXm5ukVp2A4UEj0g3biUFr6O7VJ0qG0yRufQhYmHXJzsUFpPSatDKmrw/J8LALQ0jceto1azF2ncWtw0RnfKHoxDXZPk7NArlMtcpKSy9D83MMudLTPO7DrQIYfVIyKwAhXudYY6h1HZ5mmT0MAsZfzMQ9jPveEvUwioSk6E28DMDn/aiyPPO5AK47tVEu1696CDA+7jyM+tJDrSSZp7fhSw+1Vj2rJCFY+OamKV+rzlDO4KgDDKlV1wqjjX0izwBDFwYuCj7RKUlOqb9nKaXznFLW3rNhS5Lefa6UcpSllHo9rjJGgCMspdzEMFu5bonuOpuaAojcCsA1V/igxQ8BW23mZRA4sgcfzuewCrAqpNTNHsZbZk6LDuyVt/wgFpJi1ROT3vcF8AOf9H40gG8EO/8LAD/yuY7TAXwFAD2M0HOJnktZN+gtwPDJbuHaYXxXqkh8c5MChjY3ccTC0sOpGSk7rCk95AK7jm7YTkwCWSDq8xe8Hu3uDZu15ueAJSa+WS7sGUqHh13tPTt7tZSSTU0EDAlLebZSA4xODNeG76OhJyfrMWK1ny8h1z6j9CSUTkYWf3rEfIjQslmGLE+xJ6fMHsadKwPp1TvigHHvH0cBg+P5YACv9WW1bwfwYgBP8QP9ZgBnAfhrAGd64XR6Gyyz3RavHgWMVaSLWnZ4ioDBipJ10id0YsbkAwYT+AvV7t6wWWvRh6QMMDph/lLuozY05R8olMEgY7Oto4pRwJCO/xzlvZD+pgD1TdkB4y8LAMblxQCjlHNgs06qtwBDQ1KaIFa+ndmDksNISdCW52Ew6T09457I2dhUE/MvTtDWiUFtDEl5OmtWxcwfcl6Tvx65Jl4PK780JCUexjhAj4lv4Q/a6T4JgIxna07G95dsdKlwJ+zSy/uoIaEUehuluQnobuRvTWhipPvfg0YIJPx7webNsgPGWwsAxr0MMKK3UQ8Bhk965zU3zXtGT4rNsKooZPRkrwIBg4lvSRTvdM1NLLPV0tqgVn1Tq6Sybm5f9cWkt1RIHQHm2Kw1J1VSqQIGVdaYxFeGUibxs6Q3czL1hHOW9I7eQSXZoBhzcQ4TM8+/npDSA4X7qtgSUXbAeNsOphNav+754+/HchixXWz774vNhi43w172YWhZLbueWUEiAjP0KliG6t8EC9ara+khk39sauMTuWoGMBQ1Nl3b7LYlZbXkxPL0HwqCmQbCrC8T9mW12odBj0H6SgiCWibMCjDNX7AXw1d9bVISv8unVqlOf126KHrmNfoop66NUnbAePvOOGD81I8MMGITuncAI2vc870YDEsxjJM1utWpktFy0rcw7BZYbXJrQ5UsNhhFvs9t3KOnwUopkeRkIyJDa6z48s1a9YAhwjmsu59w9Na8JmvcK2L+rtimtfKiehl1t36b6otlBozzKgPpXxcAjJ8wwIjO794AjIvpYYTUIAQNdkCzI5ZeRaB7zHp1VprwFTQ3SQVRm7rH0dEosEE+8aDv9lbQYN29dK2TOyigBtHrITjwWoZH3WcYigqpQSLNWgVO1zYpgQVqACTnfIqGnVpdStkB4292kc6p9euy//sfC0lFbNQ7gKHkgxmjq4ZzPFkfO2OVrC8ADCHqk47YUf8U7imfhUfKvzeZ3bWWfNBTmTOMxp4McmStHQVIE3LsqKvBV9p2nqeSKRI0SKaoFNbKi8VPLbc0wIitMfa9t0DZAeMdBQDjUgOM6HzuEcDYkx64NqA3VzpwFZ4hvXnG9uqJ+mg6v8AKw6tSJUgFEZv0ArDYZGbXhg7fmusJKdu951EDGK4rvdqoFQBfRtlerFkrOrtsg56xQJkB4/zKQFoEMPYZYETnaw8BRiCgFOog1wsqaVmiAEbY3ORBQhqdfFe3stSuo/wwOiIFNqgmN30JpQJCJgTlG7ZUQVDkWv0rrLmXZH3d9Wyyt1Tgcm2TLrBAqQFjYDD92wIexiU//J6FpCwkFWh6N+h5q/qeF1aSLuo6FmJZYAPgkHBNfzVss8lgoeOZr+fN8JS/FgERX3vfoOnNa2gmOev/vo6Syi5Yz+wUN9gCZQeMd53OxuvWr4u/f7MBhgFGABg0RggaKtkafoaLq3oZ2tiU9+mrSzqROIxN6Prvc0GjoWmrrvZeztc1ZKm0bPWz+t1WXM96r9+2L48FygwYdxkYTN91Rhww9vyPAUZsRvVMSOr6L1yT8ehkoFHf/Zr9PzCbNjXJn3ShDRbdLX4Sr4KGoGHVq6j5d931hECYXZ+/ti2+ntiEte/LaYFSA8bgYPruAoBx0fcMMGKzq6cAoyack3kbfqGt+X+O2fTJPFtsi3fBxgah3e9zG7YKXU8Agv4kzLNodzS65/et+zVyHjJazJGyA8bfn0lOwNavC2/+roWkIjbqScBoAI7qH/LNVUePUNZFtaHevj68Fl5dm41asZvPvi+vBVp2hOeddjZXmneClx0w/uGsOGDc7bsGGLFZ262A8V0ACwDYYUcJsUtaXejei/ekDEkVffGGKisoFL0G284sUG+BKN9UnleaE7KU/Fcd31TZAeM9t7pVdEJc8J3vmIexTT0MAgZBopAoyXoBIzqzbAOzQJdZoAEspBpQqwKDz7yij5DqPIfNlqbYd68rccNXbyzlA+hdhwbT99761tERO/+//tsAwwDDVUmtx8OIzizbwCzQRRZoSn+u/TvSixQCiL+4jMW2rh9Je3VYcu49jbIDxvvOjgPGef/PACM2rUv5RBA7aQDfAXDEPSLhLXVC7Q0/N8AoYFHbZNtaoLkqH/t2wnfQj0RrZP1HQaOqsByoHLFX7EOCfZffp8QexlD6/nPigHFFyDJFAAAgAElEQVTn//wv8zC2qYfBDNb/AqDu4icBPB3AtXXX+mQAfOOcs8/ee/O3vrZtFwS7MLNAMwu0lHAl/5hQ5K85ahxS//NvZAjgi8AgdPcVR41DWhwlp6yRciVg3Le0gHHB0FD6/nPjgHGn/zDAiN1J3ephhNf1QgCLAF7V7GLNw4hNA/t+u1ogn93YU/yTqJKElZ7VOCVTM7VV6HV4RoOEmjBKVCkU+HXkm571YN+9CRg3lXI9uWB4KP3AuWdHh/iO3/p/5mFsQw9jjM8+vkqK/6aH8SIAH+8GwNgMqunonWEb9IwFGpiN6UWIVDGZjI8KtT9Ih09tGAKGshurh0HJXjI1KxX+yBhQGfLAQS4yvvux74r7lRowPnjbOGDc4d8NMGI3RimfCCInfTsAH/DbVAC8C8CLW/1mKz2MeHMU0zCdFbOJDbp93zsWqALGCQcUojh5zAEGwUIEtyi25dUZSfN/wuvBMPwkYlteQGx0UpQaRRtGQKMaotp37/vjhhvL62F86PbnRAf9dt/4T/MwtqGHER34+g22AjBadl83a6jrkFzmug1kP9i2FkhDMkrJUahE8bJIE4sGvEgUzwPL9DK84BYtQq0UAsbomNO0pzTxOD+nnOgWvxe6/wr2XfGA0gLG3YaH0g/f4TbRMT736982wDDA2Pyy2miDlBIg1gxO0EVbX+vO7ZLEmgmjt7xtEFqgJn9R412sIqX+O8Fi/jAwfwRYmBfQSI+GgDGAhN7F+CQwOQ1MTCOZ3Ok04IdGXW5DkuAV7LvyqvICxshQ+pECgHGbrxlgxO6gbgxJxa6p4fvN9DByG6RUY0P1KepJDzUkpXXtqlmR0yRlHejrHv6e/UGt/ns10Y1jK0gXZ5EKWBwGZvk5i5RexuoqsLbmSmoHBoCREST0LqZmgOkdwMROJJM7kIxOACLt6z2MKx9YasD46B3Pjc6Dc/7tP8zDMA9jcz2MWjU8dtBSl8Lrbshn0CSlwJE1SPm6dtXcUHEj7bTdIu2N6J1mG5TSArmAwUS3AsbcQWD2IDB3REAjXVwAVlZcaS1fg4MeMCaB6Z0OMKZ2OcAYm3KAIWEpehjlBoyP3SkOGGffZIARm8jmYcQstI7vow1SmSKeAxGJLyudeAYS/U4rnGBRU+tOIScn5mRexjoGpYc3LQwYRw55D8MDhnoYIWDQw5jZ1ZWAceHocPrP58UB41Zf+ZZ5GOZhbJ6HUVPCSG9CAIKhANXZXkMqScdjAOvfxeNInfodk4d8WqsMBnrbrEJxZYvZ27yMHoaA9V16oZCUeBk+JLXESqmV2pDU6CiS8Qlgit5F4GF0UUiKgPHx8+OAcdYNBhixGWYeRsxCBb+vDUX5EBTBgaDBBimGAtggdXQF6RrjxASNNbd3ehMECiYRWfc+PIZkQGvdGSN2ceJMGta8jIKj0tub1QIGy2q1pNYnvZm/YOJ77jCwwEqpBZf0DnIYkvQem3BJ78kZCUdJ0nt4vGuS3gSMT9zlttHJcMb1/24ehnkYm+NhNNyc6lkcZzMUa96XgJUF1yC1ulxbvkgPgt7F0IgDi9FxYGTcAcjAsAMLpWTwnbUWlore/z2/QUOXt5bVHltFepRltbNIF44AS3MOMFaWgdUgh6FltfQwWE47PuXKasdn/Nwc6oqy2osIGHeNA8bpBwwwYjeNeRgxCxX8vrajVitS+ES36kCCN6c2SC2zu9bfmEx8k9CNnoU8zU0Co5NI+FTHz7p6d/UyEqmospdZoLUFXJ7MF194b9f1YtDLWES6PA9wXvKTgEEPw+fW5EFFG/fYsBc27vFBpksa9wgYn7yA/b6tX6dd903zMMzD2EwPw4ei9MZcO4b02Io8wcmTnDzNLYjrD3ocDEtJSKrfN0iNA3yao8s/MeOe6Oj6MzzFpz3SMPAmtuR37N63770FGh5kZG6ygY9zc9V7vcvA8oJ4wlmolHNMH2SGRlx398gEElKDSLiU7+6gBrlobDj9VAHA2L3fACN245iHEbNQwe9rO2pd3oJds+L6LxxBOn/IxYrnZwU0UnbVMlbMp7lKBckIO2rHXUctk4ssXSRwSPliQPqWUUtbtVTBoenpzRrDUlWGWpdb8+SDR5ch5IMMW7EUnC9hp60goTfBcCmBQ3Nrwl5bfYApM/kgAeMzF94+Og92fukb5mGYh7FJHkY9BYPw9axKGEoapBYOAVq+yHjxMvMYxxxgsEFqeBjJ2LhvkNopoCH17hM7qvXuZAr1ZG9WXhu9/20DBqPCJlHpAfL6F0pC6DvAs+o9/l2pa0J6c2Gp1QIMVu0F3m5fX6npzfcQMC66Q3Q+7Pji1w0wDDA2GTAyXYE11yAlgEHv4qADjLnDSEnDoIChOQzpqGU1CuvdCRjsqN3pPA3mMZjjyADD9WRY4ju6BtgGIWgo00AGHCz3rhNRUlYCWo4Npb7IoqYnKCzz9uwEZRZQ2jM+nH52TxwwZr5ggBG7YSwkFbNQwe+zkFQrwGBIapbhqVlX704Pg4DBWDABY2zMhaOko3YnkuldriKFvD2+R8N5GAYYBYfFNlPAoCXE2/CqeqFHnMdAoICRybEG4KEgElDXlFmidc/4SHrNxXHAmP7818zDMA9jkz0MuvxZ+eKKUEhLwpseBgFjbtaxhIYeBgFDQ1Ksd1cKBk1+C2ePDwlYSMpA4BQs0FTXOwSRLHwVHCDkMxM2Aq/jHeh5c+vSA8beO0atNv25fysCGA8E8DpmeAC8FcDLcnZ8BYDXku8XwEEA944evEs2MA+jQwMlN2QWH/aVKMxhZElv5jFYKTXnKqVWlpEePeqOzsSi0Egz6U1m0BkXiiKdNMtsmXRUKmlLendoxHpvN+tnUa5jUPYsAxKq0n97aptL7nlFaSVa90yMpJ+75M7RAZ/67I0xwCBIfBvA/QF8H8ABAI8C8M1g59MAvgiAwPI9LyP94+jBu2QDA4wODVRToRrmMUglrQ1SojvgxWpUP5nli6xCUSppaZCaqYrVSGWKTzgG4YCNymHkqgLWa3iodoe330adS4eGx3bjLdBSp0XDVqG1ajRaJE7lchvKgea3LT1gXHpedA5MffqrMcC4BwBKQl/ld/Y8//nSYOe/CeAsAL8fPWAXbmCA0aFBy5XCDMVqmPwWVbMFBxiZfnLQuCdNUuPOq2DTntS8B96F0oMgwUY07kUXk7yFxC0d7puchaRD5rXddNgCDQ8FzUS99LjBA0Lew0G5AWM0/dxlBQDjU1+JAcZDvefwJG+WxwK4DMDTguHRUNRdAUz48NU7Ojx8W7Y7A4wOmT633j1UOGMDHztrySfFzm/2aSiXFD0M5igGh5GIpzEBDI+6mne+pd6dQjUsZ+x8wrshVKFPmir0lLeYZAuIf+LMCVN0yLS2m02yQK5nWedJNDuVMgPGxZOj6ed+4vyoFSc/ccPNPueg214NgG99Pcx7FyFgXArg6cE2bwRwCYD7AhgB8CUAD/GhrOg5lH0DA4wOjVBuvbvUup/w4OAJCNldy4Y+7biVJ/M+JMxR8E3Q0EY9aZwKiAc3IByVK/hEKoksGer/zb/VvBQoHOW6dp+H8W0LU3VocnXBbkoPGPe4S9SKk/9yfczDKBKSei6AYR+64jHfBuDjAP4xegJdsIEBRgcHKZexVspsfeWUNknJp/+7AEaSAUOSddASKHyDVFb37itUOshW2wB09bX68n9xOaoNXepNkJY9K7usej8GGh2cVF2yq7IDxrU/xQhR69fEPx+IAUbFewr0Hn7gk96PBvCNYM90ZehlMM8xCOA6AI8E8PXY8bvhewOMDo5S08U3E04KOm3rG6SYB6hviMppkOpkh3euV5TpeNSfK4Ej9XkKnqsXdNIwWUi/Lp5QtZLGPI0OTrKS7qrUgDE1ll57rwuilpv4yP4YYHAfD/Yls6yYejuAFwN4it/5m/3n7wF4PAAyP7L0lnmNbfEywOjwMDYswsIUGki0qmhS+MSuXoaGdmqkWetCPgVjyrHLqoaivGRsKPgkHpETfZLQmQIe/y7dv04NMBHKdeUU8h5RjW6HKQTGxmG7fF92wPj85XeLmnr8w18uAhjR/WznDQwwNmB0a0BDm6HUo8g8i5wQj2p7i7eR3yDVqaf1hiS9NBx6cJCEvGczZc6FrLuaj/EspgmT9F7DQ/6dvasMptk1dDCEtgHDZbvsgAVKDxhXXBi9yvF/+pIBRsRKBhjRaXRqG1RBg7/XJDKTAQFQaPVRTa17k2apDnkWejW5ZcAZLbsXfFpdclVdbD4kiFBOli92phMghkYhimwUfRLdjqBfxBQCT23idOmvSg0Y02Pp56+4KGrZ8Q9+0QDDAGNzqEHy7LyuvgYNS8mONr6voUFYJ5TvpFbHsu8bkSZDr92htNcMRWmjITUSasSe6poMN6AMOHrn2wabboGyA8YX7hMHjLH3G2DEJo55GDELdeD7Qp3TNYDhDtqp8FP9JTSV7qSUrEh3ziFdcpxXSmMiCoHMYfAl0p3DwPik03smhQm70+tpTAIvY6OupQPDY7vogAVKDxj33RO9yrH3/at5GOZhbJ2HEZ2hW7RBBhihNoLqd5DGZNGrA5IsUajYF5GqpGwfe0YGvJysp2OfmHYKgSRLFGZdL98ZCOwYYGzRYG/SYUsNGDPj6b/e/+KoJUbf83kDDAMMA4ymHoYARlWyU/Q7qD1OwSe+jxwUwEiFLNFrkDPfMjiIZHRUJGQxNe0o2ad2OYXAkXEn+FTHfbURVCbRFcA22DQLlB4wrrp71Bajf3+tAYYBhgFGPmD4cloBDKoDHvPhqCNIZw96wDgkkrKpaJDXAgbGxpAwJDU9UwWMyZ0uLBUChtcgN8CIrlddvUGZAePuO8bTf71qb9S+I+/+nAGGAYYBRiHAOHYUKfmu5g97hUCVlD2CdMEDhvZhDA4Co6NISMVO70IUAneJQqABRnRd2pYblB4wHkR6p9avkb+7xgDDAMMAIx6Sch6GhKQWCBgUeqI6ICVljyBdYqWU9zBY9UTAoEIgxZ74JmBMUFKWGh45+h3kypK+EnttVwuUGzAm0n99cAHAeOdnDTAMMAww4oCx5sJSJEVcmnPaHQoaXvApXV0FqN/BhX9gwAk+TUw5wJicEbCQpPcwcxia9PYMuwYY2xUnsusqNWDsnEi/+NMklW39Gv6bTxtgGGAYYDQFDKUDyWjYV5GSen3hCFKW1BI4mL9gL4aU1R531CAsq6VWx+iYAw2Vkh2b8g18vvPbympja1Qpvm9Ga15/cq0q3coOGF/6GcpWtH4N/fWnDDAMMAww8uaANO4Jr1WVN0oS36Lb4Suj2Iuh6oAUfMr6MAYAEXsiaLBxbxIYn0Yy7AWfWCGlPFPWuBdbp7bk+8amUj2NHBp7/aqFiFLpAePnfiJq56G3f9IAY5sCRhEh9uzS9168J73+C9dEJ0wvbVAjKUvQoJiTvNm8tyLKgKl4FksA/88cBwGDAEBqEGneG3O0ICylpVKghKLY6R3ySTnmWuvDKMfsai2WVQ8atYwDGQMxN6tTVyw1YOyaTL9UBDDe9gkDjG0IGEWE2Gsu2wCjcRa0VAhU4kF2fR9dQSrehReD4kIhCoFDSAaHhE8qUwckvxTDUOJdECg8BboBRinQooHfjF5mM56zGq8iUFWUMa1S1zvsSFB2wPjyL1D7qPVr8C//xQBjGwJGEdUrA4zIwNfSsLOBz7+Z2BZwWEMqHoevoOLflHyQgEE1wIFBpxTIf4s6oPcsfO/FRsjJxm56+z7fAo0Myr4PR+n3oyzKfVUNFAWNDDyAffe6Ejd89cZSUg3dfddk+uVf/Mno1Bi8+uMGGNsQMIoIsRtgRG8P6iGFUqyBYJKqAbKpzwOJy3m4+LaUyHKxoBehie1NUAcscEm2SY4F8sGCDwg65j6fJTkteh3+pXT7MtZ+vHXcdQ7w/wD2XX6f8gLG7sl0/0PvGZ0bA3/xMQOMbQgYRYTYedlP9m+cc/bZe2/+1teiE6bXNljXQqLg4mIQHjCCp04NQanann/6tNzF1s+qdT8Y8CFBx0+BIhPKohSvSgdryLGv5IAxle5/eAHAeNNHDTC2IWBYSKqDa9C6QxVZpUwg06oAkhOqMMDo4GCdwq4Khx7XjgJ8S9WcZyWuCT0O+bAjw49UWfR5Ki/Ru+/y+5bYw5hK9z/iXlHrDbzxIwYY2xAwigixW0gqentUN8hVCMySoT5EoWJPYbiCuh1h2CInGbqO07BNN8AC6y5uUNDwyooUypLqN+qfsCKOOSuthAtAY9+9CRg3lTOHcRoB4/KodQfe8GEDjG0IGLykPCH2ppdqVVKtZ0HrUstAITDcTehphNKydeWWsbu0aNNYFadKuSbFLnPLvj+l8mkWPmg1HMFieFR6blz59IQDEFVXZKiqrx/7rrhfuQHjkfeOjsHA6z9kgLFNASM6+OEGBhhxczWXlOVvfTNXvaSsehia1wj+3yoUVQMSmedS3zBWf851PQEbKDAVt1b3bNGsQRNrngaG1PXL88DSPLCyDLCEmtVxfNGbYOn02DgwSrGsSSTs5hcK+1r6l31XPAA33FhWD2M63f/oK6KDNvDaDxpgGGBYp3fsTmnwMLIEd47+eBiSCkNQ+u8MPPIVA5sfKwJMul8Le8WGM/u+qbIiOcNWF52yotC/kAZmrpYCRgGDoajxCU8BM41kbNoLZVHzROV4Kyg1YJw+ne5/zH2idht4zfsNMAwwDDBazYH8BdyX0GptvngBoQcQ5C6yPIZv6GqyoDcFivr6/7xcSQ0wNR7HEuv5I9xUWZGsxFRWnKfeCcWySDY5K3K8QjK5tuY5wwaQjFAoa8LR2AvRpGclZpe/6p70VbDvyqvK62EQMH75vnHAePX7DDAMMAwwooChgKD8UlqPL4u5gkfgAQhISENGbTNXVptf2wkcPPI64NEO49zjndpxDDQaR7kWMAJlxaPLXlnxkKewJ2jMIqUcrwIGdzc05GjsmwllUYpXGjcJGA8sMWDMpPt/5X5xwHjlPxpgGGAYYDSbA7UllwEZoXZ9a2NXbkNX0MyV1er7Gv0c+gjX9OfBQoFIiQ/5nR6zab8H9+2bx+p7PryXY6BRO9KNgJGje0J1xSPUPTmMdGnJ6Z4EHkZVKGsGmNnlhbKoezLlPIxuAYzH3T8OGK94jwGGAYYBRmvA8N29IXNtxmDLTu/jSFmXrwu69lz0V5Bop7fU5fu31OUrj5T3NOQEfD4kAyNf7y80JHXH4blIzsIBRFKzfx4n6DA3vqqmt3iuh8GyWdVunztYFcqaJWB4oSwFDBXKCpUVGZKiuuLoRPcAxhkz6f7HPSAOGC//BwMMAwwDjLw5kNv9y+oYoQVxHFKpqPAxpk2m2jVHJSLrOMkHyVg7LNUyGZ8USQeFKsSVWmY9GoIXBIyQTr0aIklFvIkL2Wr+cZhcHRxCwlJO4axiL4A/hgKUeRkNw9w0JEXAWJp3yorMY1BdsV67nXsbHEQyOgqMTQDTO3weY4eT4mWlFMdfxnyg3DmMM3ak+59AguvWr4GXvMsAwwDDAKM5YHjvQp76uYDz7Tp+09VloTYXqnMu5FzUlTKCoMBQxNAoEm3oCmvztaFLcxwaZsoIDj2pIUFJGHGXkbKkc82DE7fji2AgxxkJjsMwiFbnKEBVPRoLS1VHu+ahIHsQWBM7pyuLrkJK1BVZKTXv3qsrzqPkg8HAAMCkNwFDhbJUWZEsxQIY7gGh1ElvAsYTHxTDCwy8+O8MMAwwDDByASNLPAcCSvQwWHLJRZxVNKzPJ3CsLFX1MLgzPlVSQIkNXez+pYCS6GGMuPr8jDrCcw2Jh+G9i1B3g1oby4v+OIyfsw+AXoYHDB6HiVeCEhvGuHDxk//Pnm7Vo3HHMsCoHe2GPoxQ82Rp1ikr8q19GFRWFCle0thznIeB0XEHGGMsq+U4+PyFCGUN+sa9EvdhnEnAYK9vxMP403caYBhgGGDUz4H8+nznXYhHES4kFFHi+6jnGeLORDzJLySitjcl9fkJF5ascibQxFDA0KfcUNlPFisuWvPuONI4dtydMp9eCQ5sHCNYhAuWHkc1OHzexACjDjAaQoFeKEu8yCUBinRlAVjxMrzauEfvkPbnAwC9DAI1w1Bs3hPvotqD4Tq971/eTm8CxpMeEsMLDPzJ3xpgGGAYYDQFDA0Rqaa31ucvaqjC1eZnoQpPfe1CFWNuEZ/yjVzjMw44WJ+vDV2emE6OLxVXPm+hjWPUDpewyKxrHKN+OAWbPGDIcejJhCGRiRnXOCZysEFoSgGDlVT2yixQpQZRKnMNPbJiig18TUKPGhKUUOOw68egNymVUXUhwaSv1NQge8/cme5/8k9HZ0Xlj//GAMMAwwCjNWAE9flaPSPJ0MPA7GHXDcyFnOWWEqroAwYGXDKUYQo2c0lTlzZ0BbQRkvzuqya86WFIIr2uccwnXQlM0jh27Fj1OCMeMHgcJl4n/HG0SscnXSUMxpCUAUbNcBcubmAYkp6faqH0Jb4KzgllSR5Jig38u65SrczkgwIYv/4zccB44V8bYBhgGGDkA4YmvAkYrj5fcheLR1z1jNbns3pGyy2VlI5P/mNj1Yau6aA+v2Yhd4u4vJjDUAW/EJhY2sk+AG0c0z4ACX0NIOsDIGA07QPwyW/T4Mi93Wu8jPryaY4JPb8TLJ/2gll19OaJimNpbqqhrDlBmenN9561M93/lJ+LA8Yfvt0AwwDDAKMQYBw7ivTYingWQhkxd8gv5AwbeQ+DCwn7MLQ+f3LKeRczO31D106XAFfKCJVqlZCUT64TnOo7jWfZcXy46smwD4AvPQ6pKehdZMfZgWR82h/HP/Fm/R+JJb7rBnz9DZpKA+M1T9S2LRony6y4t/esXen+3/z5OGD8/lsNMAwwDDAKAYaGihYIGN7DmDsCzB1xC3nIMcTKpdFRJNrQRdBgM9fkjmpDl/ZkFPEwGPrS49R7GKSm0ONIL4A/Tk2nsXkYsdUwFzTqKWBEs72ONbhG70Q77VVpr0oBU2ZNbwGMp/5CzESovOAviwAGGzpeB6AfwFsBvKzJjvcB+DKARwB4b/TgXbJBT4gLGL157Wxs2dC1SE6h2WpDF/mFNLegISk2dDEJGuQwCBYuGZ2Twwg9DAKTUGvP+4S38y4y8jvNlfiQVCI5jEmXXJdcCb2LGefJBI1jlsNoveK0Jpn0TZV5JJPcbaao6KV5c/RPSg0YtyJg/GJ0Sa48/+oYYBAkvg2APCPfB3AAwKMAfLNu59zukwBWAbzdACNq+nJtYIDRBDD4hJnT0AUBjaB6ieWurM/X2DaToKySCmmvWb3EslfpkfAd2RKS8s8k9VVSzJdolZTSa7MiS/oAAj0GVklpH8DENBIeZ3zaV0lpp7F2lpcn6R0Thtqq8t/muid1mic6ZQoKZV1yzytKK9G6l4DxtF+KLkqV570lBhhF5aGfCYCTmF7GRwwwoqYv1wYGGI3j0bKha3neNXSxcY/9ESqso4DB3MLQcAthHcdgKm+htfVJ76APQ7wMNgdKH8as68HQfo+wD4OAId3Gvt9jdLKOx6i223tLF+LQzPU07Xm3RLYY52uHbNRdVOttyOBUD5UrxStuhtumyTmXGzB2p/uf8dCoOSvP+YsYYHAnDEk9ye/ssQAuA/C0YOe3AvAuABTgeJsBRtTs5dvAACMHMMKGLiaktQObC7l0ei8KfQTpQdgbgaOrVWoQbegKpTu5kNOzqJPuzBaYsDqHx2LjGJPsBCfxYPxxwsYxVuNQ8U07velpaEd5TeOYL9/dok7vphK3shbnKAnqoltQdGoj76hcT6hBWbF6Bs0AudSAcevd6f7fenjUjJXfe9PNAA4GG14NgG99PQzAVXWAcSmApwfb/COAV/v8xV8bYETNXr4NDDBaAUZOQxc5nriY13BJ+ZJLLnLC8TTkwk/KJSULuCcFVC4pJSDk4VX7IgyByXFWa4/DHIdySQln1RASBQ02jtWDkpAdbg2XVFSpsCEnUPekHuYGgif4rfKS2rlzyw0Yp6X7f5u559avyrPeEPMwioSkvlN1x7ALwDKAJwP4YOz43fC9Jb27YZQ24BxzG7pkMfeNfGSnJRU2F3CWwtIr0CdPZasVplplkPWhoRAswia6zKPRju+AFTfrzyDJYc5xPEgkWZMeOYwCVlw5jlMB3KzFtgEsGkSh8hLJdUqFoeBUnYbIZl1Hp6ZW6QHjdx4ZvdTK77w+BhiMsTLpTfm+H/ik96MBfKPJzs3DiFq9hBuYh5E/KFlDlwoYZUlwz16rjVwnTyDLechDch9cMxffqoUR/D9bCEOaDq+HoaGpTHOj9lgNx+G+1IuQYwVaGJln4WRbN3ORbdrbkF2fAoZXLNQhUGBQGyl9Sr2GyCZfT7u3bekB41ksZop4GL/9uhhgcAdkMXytL6tlBdSLATzF7/nNdUcwwIgZvYzfG2C0AowmSnjCMxWIK6mokezKN3SFEq1hc5eKGsmmmvT2x6nJnWg4zH+G+t56HA3bhAurNpDp4ut7PTYLMJqCRQCwThTqRCZxy9/I+XlRKAe2BL9yAGC7922pAePs09L9z6IjEAGMZ762CGDEdrOtv7eQ1LYe3vjF1Sx+Ydgok1Gl+p16B0F0Nou/1+l6699DsNDT0Jh+3nH0b/LZ5DjZgtvYOLZZYMFLafDMQoVCT+QoNBtCuRKw/BIsRACq4kN59JicAFG3C0KVGzBOT/c/+5ejN0Pl6a82wIhYyQAjOo22/waNoBF6A8G/Q1NohU9NJ3C189fhRe30qukBCL2JTMfbA1Or46h3s0VJ4obcj+Z9FCCYyCcDLFl3Q0EoemviTQwgIQOsJPJH3b+lWMADR52ntplA2M5MLz1gPIcVsBEP42mvMsAwwDBqkNiNkj01u39UPYrs//KPut0EdfnrKA9tWoKalZ/GjiNQlIW6NnNBrQ1FeZ1zBWHc/04AACAASURBVAyWCdOb8KXIUpKsaoXsX+H1BQqCQhWuOhOsNFNKeAJHoIu+mddXZJ4026bUgHHO6en+5zwuenmVp77CAMMAwwAjeqf4DWpq8mv6B3J6CeQ3gQfhvYmiC1xj81geKOmZn/pxil57q+1yK6JqZG093cnKklMPpHodP9nwyP4VNiLSntpXQqBgTwl7V8an3Kd4GrWiRJLv6JLkd7kB44x0//MKAMZvvNwAwwDDAONUF80YvUW2nNeFntZ7vM06zimfl4KnhtEULLQEmd4FPQrtkCetCgkbM0oVJsBPVqVtR8ccDxcFp5TqhGp2OdxYBhjrHbXG7feec0a6//mPj+6o8pSXGmAYYBhgRO8U26DBAk3J+pQTKwxFsTM+I1NU9UBSniw6QSilOqHwFJl+xyed8JS8vSBURgvv8xkiPsWGxM0tFz7VqVB6D+MFT4heWuXXX2KAYYBhgBG9U2yDGgvkhqCyqjHSqNBjoHog6U1WgZUFR9ZIXiyvHiiU8MvLDUqFIF07SRtFEGonMO3o2kEGXtHKJg+XJsBdNVjRMN9WDmOpAeM2Z6b7/0Dpn5pbqfKkPzHAMMAwwNjKhaQbjx3ts/Cd6Rl9Cll2CRjzfDsPI11acoBBD4NeiQpPUUdkkh7GjAOMmd0OMOhpKGCwaiqgPDHAaG8W7SVg/CHZOVq/Kk/8YwMMAwwDjNiNYt9XLdASLDIeLMrZkjhxIctdECRqwGKRVVKkVqEEqi+pJcsvtdAnJ5GIeiBVBHcjmdrltEQMMDZkKgpg/NGvR/ddecILDTAMMAwwoneKbZBZoKbPQpLbXlrW91lI6Sz7LBiGYqKbFVHiYcxJojtd9p6FKgeGVO0iBjWGhNK2oh44kx+SoochOQwLSXViau4996x0/wuVvaNFSOpX/9AAwwDDAcaBz382M0U3uPiduFFsH+u3QNbFnZfc9n0WGVCIXsiCezPpTZDgWz2LrP+iDxgYAPMXGB93gCGytl5BkOGo0YmqFrr0YljSe/2jl/8LAYw//o3o7iqP+wMDDAMMDxjXfibfFHUlod0OJi31DWiBnBLYbr/m6EpQcIMG76JBjXAJ6RI9idmqV0Hvgtohmq9gCIpvIXT0oSiChQ9HZQlvJr0ZhmJZrYajpBfDg4WoFVofRsGha7mZAMaLnhrdVeVXXmCAYYAB7N1zUXrgc5TYbWwAqy6gtYpi3bSI5jfcNZHcrAGN7r3m6N1/ChtkgJGFotYc3fsxLypVL127OIesGorJbc1XECxEN8R7FsPD4l0k7L9gSS3f7MOgpC17MehdsAcjq5DaOo2PUzCb/KTUVVK3vVW6/09DjaP8q6w85rkGGNsMMF4I4NcA3OKv6/kAPhab5HsvujA98NmPVzcLeZBkAfU03Dni9mUHjuYiPrywHG6mDDCq9BoONLeGbiM2dpv5fUM4KtDpoGfhSmePALOHgbkjSJm3YDVUfb6CHd30KnwYKiFgjI0DYxMOLPjJ7m72XtQrFUp1VHflL7oCMF78jOhUqjz6OQYY2xAwFgG8Kjr6wQZ7L7pbeuATH3Z/kbXRL5AqvNPsc510F+s5p05s25Q0UMV8QlK/7ICBiE8o2hOIEDlM6QleypphqAKGT3QL26xXH1w8gnT+MDB7EDhySCqi0nnqnvteC9U7b/AqqEdOoJhwuuT898gEkkxuVilBPHNtwCPVLU175QeMW6f7X/Jb0Vuu8qjfM8AwwAD23u2u6YGPUWpXF8s6Sm7RV/CU2aGQTbaglm8BLURLrlQWNRrNtIH3qrrsmqN3fJsb5APGUaTUG58/jHT+EHDkFgGMdO4IsOCb85jkJmCoZ8FuboagxjwFCMNPfDP0NDqBhDQgKjersraa5Fbdj01WEGzTdOUOSd3u1un+lz4zeomVR/yuAcY2BIxfBTAP4HoAzwJwJDYT9t71vPS69/6V8yy8UlySqbipgI0PA2T00o6WoayJxwaabY27Z8JHviRUvQ01koobhTTaeeJHXUJJERv79XxfAxgSjmICe9UDBkHiIDBL0KgDDE1yE4AZfuKb1VATSgEy43ijRieBkXEkw6OO0jzTwfA5i1CpsMvsX+ocBgHjZb8dnQqVhz/LAKMLAeNTAM7IOe8XAPgygIOea/tPAJwJoBlJDFs7pb3znNN37/3vD1ydlSom1INmgpHsoINDSEI9AgEUvYH5783Xi47N7KZgEWoznDgOEfHJgOSkuxZReatAAFPepKEo/zXHbNKJ7xs8DNEzDzwMAQy+jyAlBQg9DOWKohfHnAW9C3Zzh2AxweT2tISkkpDK3I+FU+FTUShXGdVtYcFSA8btz073v4LPlq1flV96pgFGFwJGbFz1+3MBfATABbEf7OWEec3z3MKoYMGqlKERdwOzw3Z41AMHgaS88eSGTuR65tQTa0i50LET+Tg7jY8h1eaxvgQJAYJgyRLOAQXLcl9zbHw79X3LHIaGpJjHkHAUk+DzDjA0f6FJbmWjldLZaVc6y+T2yJinMKd3oRro9GQ9SJQ4BBqzcekB45W/F7sEVH7xGQYY2www6FH80F8TfczLADwyNhOE3vj3n+hjzFwsh4DhEadJMDwmnxIuYFy5RgFtaytWmtJ+19BsM0HrwydUeyNQrC65MAqJ8Y4xvk56Cgr4JC4UMjjsgJLXzhDJAHUYVPVta685NpYb+X3zKqkVpMpGyyopzxclbLSqd8EQEgGD80oroYTCfMZpXtDOOrfCcKh6F11SpdZsTu6715W44as3lrJSQh4YX/Xs6NSp/MLTDTC2GWD8LYA9PiT1XQAkiFEAaXqpdz9rZ7r/N37eexcDkDJHEbCp6hJIuIB18fy76hIIRYN/EtzgJqrm4kX1l6X62idraSuUOZWaDNRhWGG4hOR3K+JlgCCjim9c1Jh4ZQKWT768ZobnurgPILoaFNggtw9D8hgMSzkaENe4x7cXSBJAPuH2TvtJzwX7LXzpLB9EakJRCsg6r7ScuXxlza3nZK2o1r7L74MbvnpTSQHjnHT/q58TnQGVn3+qAcY2A4zooOdtcPfdk+n+R97bxZjZcaucPlmceWu6bhtvyJxmuxrlO70630UsPEdBcpYdx0vsQiZlBUs+CRzLDjDoYYSKb3wKJmAwtp4R33nQCHM4XZZ8PaUJ4n/UtNOb9mPye4U9FwvibQgY05ujh8Fx4AOFhjsJGAxxjrCE1ie56cVJvsjnjsSz0MKKcvXB1Pb20DhBP0+9lK7//74rHoAbbiwpYNzhnHT/a54bnRqVn/1NAwwDDODimfH0Xx9wdySDFfSPDCAZHQEmqEkwiWSqqkuAyR1INonXp3nDnXoQzWRR/Q0sXEfVfoGUIj7Secz4uouxC8fRyjJSfQquVJAwHMcmMoZLGGNnyISA0eUCPtHVoOAGNXmMzL4E5WNOs1u8tiUX+qPN2auhHobkyHx+KAj7uZCf17hoyF34hLeyEGwxQDedlxoGVfCoA45993kwbrjp38rpYRAw/ow9vq1flZ95igGGAQawZ2IkvfYn7yKA0TcyiMrEMPqmJoApsoZOI9mx22kTTO1EMr2rVsxmA5hDG25KLv5ZzwT/TbCoA476Rjpuz9+xEspLhEq4hL0CjLFLFc+cI8Q75hc1PgEPDzuKCoKFJ8DLBHwGR1x+R5+EfU9KLzXx5bPVEjCOe2+OjXzMDZEKhCBC782HpHzZthQW0NZZFZ6CRVA+WxPq1KR31dPYCpvnNoJmwlH1czTwPNIU+676Odzwb18vKWDcJt3/+t+P4QUqD/41AwwDDOCiseH0mj13QN/QAPrGCBgjqEyPOsDYsQPJzt3Ajl1VbYINFLOpAYsweR0qujF8FD7RySDWUXkIuZ3zMFI+5aqetFTxuLdU8bATmY1loildkbLPZHy8ChjTO6t6DEyCawK8ywR8oqtBwQ3yq9DY00LAUKrzNVeyTLur+p6ChgyVDzcRFIRMsB9JQ+myL9lu6IHxvT+b3G3ftBFUy7L1AYX/138Hc3TfTz8CN3ztm+UEjDsSMP4gOgMqD3qSAYYBhgOMz150e/QNVGoAI5mZ9oCxCxAvYzeS6d0upr9Bi2fzBUkb7cLPkz6/7wGjjr7DMaKecKESxtaZt2A4ioDBXgEmZsl1RMDgtvy9diCr4tvUDgcYDMdt0DVH79SSbVDb5+KBOexnIXgEWhmpeHokKuRiqmBPlT3PUSb9FnwPeODwfS+SzwjKazOWgc1nqW3Z26OerICm7+8RwGT1nQOQSx/xZNzwzW+XFzDe8EfRWVZ54BMMMAwwgD3jI+k1e++EvmEXkuoXD2PMeRgzM0joXShghOpnHQ7PVL0LH07KFiHefD7koR6D3pB8itOnVv+0Kk+sAh68V0+6J92VJaTUZxCp0FnHdcQ8huozKNW2sKbSu9rhRHwIFNtA8S26Gqxjg+YhQ583qu+m9w2SqXaHSyGCB5Wa8fP9PcxvaE5DPn0iPCs22Nxm0aZgkc3JNci1MW+z5kNxWq5NkDx5Apc9+Xm44dvfKSlgnJvuf2MBwLjq8QYYBhjAxZOj6bX3vhv6mMMYHUL/uA/LTE0hmaaXsRuY3ilvLp7J2JRr5tPehA6xh7aMjzOpyoVfkqkr7t8SHz9eDXFU+ITqu9S1Q5sDzBubFNxUgBPQoKdBJlWqwi3X5DASdiIz6c3eAAIGG8sYgmO1FHMY0gHffYpv68CDQpvmggbzSppvknCgKvLRu/ANkz6/kY0fF1qlO5ek+JArPGBPBhtHw96MutzRZpEP1vafBNeUaZevVnt7fJ+PE4liSM55GZc95zW44b+/X17A+PM/jo575f6PM8AwwADuvmMi/eLPXiqAkQw7Yjhy/bBSKhGZzED9jFVD9foEWYIyaYvFtfHG9G49k9ZezS1rupOnuSChqj0U0qE97BYdLu4EMz7FcsESnWmW0i66PgHKhbIUVPowGJLq99QVnmpbSPHYWLZx1xy9S0u8QcuKIa2g4me2sPqmSYI0K6iO+TEMq6iky559MGNVEkIBaq2kCmhpkr625ltR04qXKmDowUI9JdKicE5JKTGJFjmnOL84r3xuzM/RS1/+Dnzlf35cTsC4023T/X9BJqHWr8p9f9kAwwADuPvpM+n+X7lfletHE7+kmtbyUlk4vaiNX5RrKEI60LjXQD3B0IXW+ItqG29I3pgsh/W5B02mMmHN82LTHcnrhkZdt7aARr+72YWK2z0NCmiwaU8a9/iU6xv36GHwd9KHwWZF0m5PuyfdsPwzYO3dioqd2M29md/nehtKyULvTrxB16eRjSHtz0WV9mfIii+GEYfY2DfqGidJc77FAkq5vScCGB4stJiC/T3iubLHh82hfn56pt7L3voxfOX/DpcXMN78p9EpU7nPYwwwDDCAu996d7r/mY+QKqGMvoHNVSwvZZezMomyka0+8avVQkiyvEF05jXZQJ7kpMJE+yc8G2rYQ6FdxLwhudjw5uWLDYdc6LnYMKSkVCYKGtwmBA0JjfgnXJbV6oJFgPG0IEKzTVoUht9qegVUHrSv7Ws+VVuV8XeNi6vPVdQvrswjsblPPTzanx6egj5pz9n3wnlHnil+yrzzEq0amurAQ0rMjrnd7foQw34T6enxhRQsphAdEF99x/zY6irS4yfwE+/7Ir5ycL68gPGWl8RMgcqVjzLAMMAARNP3T57ma+P9kzqftHmTkj9KnvbGAiZRT8YXJiHbDA/ULDahVvSxFaTLrHBispo3JG9Q/xTHLmJ6B6zvJ9gRLAhw7FAXfQUS2o07z4PJU76k9HPN5TR442sCVj0Mbsekq/BpKXeWckmFtBWOPbXXvYvw/mkKGEqBTglXGUPXA8PGSaFpUfpzaZwcdGAhLAMzruhgCxsna8Ok6i0dk4eNVCVpydJL0SihdWePDz2NBZxYPoqTy8y9ncA9P30jvjq7VE7AuPPt0v1XFwCMez/SAMMAA9h7x3PT/X/+Ike+p2ytlUEXhhG22pGAqTasWlEm0fbLHGuf5HzugqEM3pjkKOJNKYpuvodiiSENehg+nKFMqAwhSdMd6bKnXLKawEcA0DJOyWkEZY9S7unLPJWJt2mlTueuOfpI14Ub1HqJnpZFCg4W3NM4x1HKmn3jJPtgVOubSW9WqZFnioAv+bNdyBonxdPb3KKDhjCpqgzS650/5ACQolGHb0F6mNTus/I+MbeEE0tH5Z0eO4F7X/ct3Li4Ul7A+MuXRWdb5fKHG2AYYAB7z79jet3fvSmoNvLljQODrryRnoR+NtTFu0aqdp+0mwLG0WX3JKdaC6TOnj2MlIDBxSYEDOosMBzFhYZvPp2qzgLBT7mJOOhZP0DqSm/5UtoJ1WGQZH5eL8DWNI9F7+gSbNAAGBq+IehL02SgmaF9MAxJhWXN2jgplXm7trSsOR8w6jRADv0IOHwQ6aFbBCzSI7M4PruM4wsrOLl0DCfXjuPKm/4LNy2tlhcw3vry6Oyp3OthBhgGGMDeC85Pr/vQu6sLZtaJG3TkqrhQ2DzVQfGkjgGGEiYqrcf4jGNDJWAE+RY37jm8VKFQj0rTbtA1R+/QLtzAAKMbAeP26XVvf2V0tvX/1C8aYBhgAHsvvCA98PEPZE/ZVcEa/yRdv4hmQjaOjqNd78I98PvFO6uucYR26wpJ0cNgOEN5oNg/MTHtchnKhipeg+ckUtBQj0P4qAJdc5Wgza5/a7mMond0CTaQccy6vAuGpDTpTe+VXF6ag7KQ1KaM6N7zCBivjh6r/yd/vghgPBDA6wD0A3grgPpY12MAKJf6IoDfAHBT9OBdskEpXchO227vRXdLD3zqowFghAun/3dIuxEsrJ0AixrA0PyC0pLnJb3ZqU1xHqmSquYwJOmtpcD0MCRZOuUS31rlFJTDSrK8nh69BjRy7NAhgOz0GJZlf1kIR+VwVfebMf+FI7VJbyF/9I2THIf+/qoWi5ZzE/QZWtwituB1J71nWZzB5tAFnFhaxcmVNZw8dhz3+sxN+OpcSZPe590hve6vXhOdQv33+NkYYBAkvg3g/gC+D+AAgEcB+Gaw858E8O8AjgB4EIAXeqG36PG7YYPeAIw9F6YHPvuJKmD4eL7/g6tCythgN07IpiNltcxhCGjU942QZdY3fWUqbnKhtXxUOis36Zq74SZYzzk27aWR4gXKtrJfwZfVenr5TMBKKtSo+c1S7omgrHbag76V1a5nLIpuu5eA8Td/Ft28/7KfiQHGPTwAXOV39jz/+dImO58B8HUAt4oevEs26A3AuPii9MDnPl0dkhqq8MAE/u+d8irq50BHGvfEy6BKniq5jVbLaiWBrT0UIQiGZ1I35Bt8zV1yHxQ+zcYn8kDAig2TTH4vzvoGTN88ycQ4X9ppLz1ArpdGmkX5yWo90qErt9QmNU72ROMeAeMdjCK1fvVf+pAYYDwUAENST/J7eqz3Hp7WZM+/C+C8YPvYKZT++x4BjD3pgWs/E3gRjeOyUSARHqmBGkQYTr2ehacGET4o1eMWrh4fktKmL5YASwPfBBIuPKEedw55XasZuBnXXPo7YJ0n2NDoRq4vlXFls6TSaFAiV3iXfKe3VkmJjKuTyBVFPpFv9Y2T9RK5HWgWLXJ5NdQgYahNGxIJgmQhEK4yStUues6zo04X5MQJXPrKd5aXGuR8Asbro6bo3/fgmwEcDDa8GgDf+noYAHoXIWBcCuDpOTu/EsCfA7gngEPRg3fJBj0DGNd/4ZotH5KOkA8ypEFaECWtI1Ggsp1m3kX7fSNbbqySnkDuE3kmk8ueBMfnlRL0ld1VQZ/enHbacwxJ8ULgJ+hvJZeUlmCrimMo/UtSTE83k12TXFsXkQ+yrP6db4zOqP69V8U8jKIhqQsBsMqGOQzmPLbNywBjE4eyyknUBr05Gw4JDKHkJ5sRNYThK57Me9iYgW2gAq95IlcZVwcWQtxHz1G5pBQwVL5V+cAkFNV5doGiFmi4poyEUCn3u5zeXPqw+LDf+tV/9/vHAKPiAeC+AH7gk96PBvCNYM/nAPgMgF8B8MXYMbvtewOMTR6x2pszFOehfkLAM6WqZuylkFfiyOsyhTYmuMP/ewU3XzZrgLExA5uNX8juql31osB3DCl1vwkYXjsi4wPjeFFESbxEMgyEnqKXca1T4NuscWwKGgKIqjjoND4y3Y9Aja/UAkp3uVN63bsKAMae+8UAg5PqwQBe68tq3w7gxQCe4mfbm32p7S8BYHiLL8aUL9mY2bj5ezXA2GSb1zCfnopEq1ZAae9E6FkYWGz4aOYCBnMYXrJVaOoFMJaRUmToON/Hq2zByuWllDSkNhfvYus8DBqt5rryQlTdLNFKwHg31/KIh3HRfYoARmw32/p7A4wtGN4a0AhFeQI6j4Yu7awMNmi8096ROunWzXoq3QLTbfkhm+ehyDzMHEYgNiSMwQxJecZhgj2BQUNSQnw55v4mjZeeska8jM0nf2wEjUBuVpmWszkqMOMpaFLsu+rncMO/fb2U68leAsbfvyU6d/ovvNIAI2KlUg5wdGTXucHei/ekZUh6h6fdABraCd5A5xGEpCQypeWyChxB85183RNDus4Z0LnNm5ehVjUxpFKKiWF6GgQNkWs96fS7Q3p5ltYy6V1fUhv002z2eDadl+oNN5mf++7zINxw09dKOfn23uXO6XXv+cvoJOi/4HIDDAMMoIyAkYUBdICkI9uDQ9idrf8OgWATmgyjd1ePbpBbGp11e6+4PgwRwmIZqhdQUplW7cPwZbXaT9Og8Bg2YG5B530taASehJu0fuRr5+q+Kx6AG268qZyAcVcCxtuiM7b/rvc0wDDAKC9g5HocNTdlk9ELwGOzn0Cjd9023yC3+ZKAIBQvi0hFmY6d3guuX4GgIRK5J11lGxPebL6k4iGFk6gfPz7tejFU16SuAXOrxjgDjoY5qaBRHex9l98HN3y1rIBxXnrde5mfbv3qP/8nDTAMMLoDMPLGqeaGtXBT7H7flO9rAEOS3T53wRJacklRCEtU6rycKWVbVUCprw8JvQsVwaKAEvXUSfNCHXlJgA9UqfY9Xf1WAUaROanb7LvXlbjhqzeW1MM4Lz3wvr+Kzo++8+5hgGGA0b2AEZ3htsGmW6CWrdYr1FFAaXWxSj5IASW+RXFvCVA9DHbrk61WuMAmgekdTtOEBITUNSFgbLKAUqcMeMk9ryg3YLz/b6KX2nfnywwwDDAMMKJ3im1Q2AL5inteNZHehcqZzh1GSqldimCxK1o1vQUwxpw868xOYIpstTsdmaSEpVgtpT0Zm18pVdgQdRuWGjAuOC898P53RC+t706XGmAYYBhgRO8U26CwBdYloESaegJGgx5GoGkys9tJtNLLCCVat7BSqrAxgg3LDRjnpwc++M7oZfXdYa8BhgGGAUb0TrENClugqYexsoh0/lDVw5ifRaqAUe9hqAgWQ1LmYRS2/aluSMXNAx96V/Tnfbe72ADDAMMAI3qn2AaFLdCYw2DSmzmMJWD+EFImvGcPAQSLRZbY+hyGhqSGhpxqImnNsxwGBZSmfA7DU5wL87CFpAoPTIsN997tLsUA47Z7DDAMMAwwOnHT2T6cBRrKaskftUZGV/ZgUEDJV0mJd+GpwPl9miJRinqKYLGsVlT3djrVRFZJDQy7pLeSSZawSqrZPCh1SIqA8eG/j07hvnMvNMAwwDDAiN4ptkFhCzQVUGIfhuhFUEBpzjXuiW4E6UF8HwY7vaUPY8wp7qmA0ti0o6snYBBUQvbhLWjcK2yMbslhEDA+8g/Ry+q7zd0MMLoUMChUQi3c8wFQoOT64Dooi/hEACcAPAPAv8RmQlk7vWPnbd+XzwL5Akosr/U8UsxlSKe3igxRl33NVUnRY6AHwcY94ZGi6h6pQYKmPamQ8lK7mySg1Akrl97D+Mh7opfZd5sLDDC6FDAIFCcBkDGMMocKGHcB8G4PImcB+BSAO3nwaHqpBhjRe8U2KGiB7aiHUfDSW25WbsC4a3rgY/8Yvcy+s+9igNGlgKGnTZm8EDDqRdfpXdAT+VKr6zTAiN4rtsE6LNDAJ6UKdaqLcWINQnOeEQ+ecNQgwlZL8ashCU0lGa25F8Bil3em5d1dqonlB4z3Rke47+zzDTC2GWBQZ/HLALSomoxi/wyg5WwwwIjeK7bBOizQKDZE4SsnLiRiQ6QL8eJCqYgPMXrqmYb7+pGoSJJK6/L/IeGgap10ER1MqQHjQnoY74uOcN+tzzPAKDFgMJx0Rs75vQDAP/m/13sYb/LeRAgYHwOQNxueDIBvnHP22Xtv/tbXohPGNjALFLVAPmh4cMi0I7wUr1KCC2lkqJzoFRNFFKvfeSCBtkmZOKRidik9YPxzAcC4lQFGbJxLSRYWnLSFpGIjaN9viQVylRNFM8KDhP5bdE78KQpeBKBBgAhBokvBgldXfsB4f3Se9N3qzuZhlNjDiA4ggHrAuCsAtmyycopJ708DuKMlvYuY0rbptAXyxYYIGl6JTj0LHph/U1r6EDS8rG4GJH6bbvIuyg8YF6QH/uUD0eHvO/OOBhhdChi/AOANAHYDmAVwI4Cr/LUwZPUEL67+TJ/DaHmZlsOI3iu2wSlaoKnYUL3QUM3+VTUx8Di6FCj0ssrtYRAwPhgd4b4z72CA0aWAER3c9WxggLEea9m2p2KBRuAQt6LFrnw0eJuIYZUeMD6hadHmQ9J3xu0NMAwwrNP7VBZA+82pW6Be+KrVnrot9NTsWsoPGB+KDmjfGbczwDDAMMCI3im2gVmgTQuUGjAuult64BMFAOP02xpgGGAYYLS5FtjPzQJRC5QeMD754eg19J12rgGGAYYBRvROsQ3MAm1aoOyAcf2nPhq9wmT3OQYYBhgGGNE7xTYwC7RpgdIDxqfZ39v6lew62wAjZqOYEbfD91YltR1G0a6hzBYoN2BcmF5fCDBubYBhgGEeRpkXGju37WGBYqn36gAACEdJREFU0gPGZ0g5F/Ewdt7KACNmo5gRt8P35mFsh1G0ayizBUoNGHsuTK//zMej5kt2nGWAYYBhHkb0TrENzAJtWqD8gBHVWUOy40wDDAMMA4w21wL7uVkgaoHSA8Y1n4heQzJ9hgGGAYYBRvROsQ3MAm1aoNyAcVF6fSHAON0AwwDDAKPNtcB+bhaIWqD0gPG5T0avIZk6zQDDAMMAI3qn2AZmgTYtUGrAuPii9PrPUa+t9SuZ3G2AEbNRzIjb4XurktoOo2jXUGYLlB8wKJ0TA4xdRQDjgQBeB6AfwFsBvKxur6Qh5vcPBrAM4FcBfCV27G75vuyKex2xowFGR8xoOzELNLVAuQFjT3r95z8THb1kfEcMMAgS3wZwfwDfB3AAwKMAfDPYOYHi6R4wLvPgwc9t8TLA2BbDaBdhFthaC5QfMD4bNVAyPhMDjHsAeGEg5vY8v9OXBjt/i1cKfbf/238AuALAD6Mn0AUbGGB0wSDZKZoFym6B0gPGF6j2HAlJjU3HAOOhABiSepLf02MB0Ht4WrDnj/gw1Rf83xgLew6A62PH74bvewIwANwC4OYNGJBdAA5uwH43YpfddK68/m463246142y7W28pPJGzN1298k2b45R7DUMYDXY6GoAfOvrYd67CAHjUh+C0m1Ii0uPIwSMZwMgGHX9q1cAY6MGik8Nl2zUzju83246V156N51vN51rt9m2w7dBW7uzkFRb5rMfd9NC0U3n2m2Lmtm2N9aCik963xfAD3zS+9EAvhFc/kN8iIrJb4arXg+AXsi2eJmH0d4wdtNC0U3naoDR3ryM/brb5kLsejbzewLBa31Z7dsBvBjAU/wJvBkA19Q3+lwHy2ofv13yF7xGA4z2ptqT62Kc7e1tY3/dTedKS3TT+XbTuXabbTf2rrC9r8sCBhjrMpdtbBYwC5gFetcCBhi9O/Z25WYBs4BZYF0WMMBYl7lkY5bWsXnnfJ/MCuur2cjzRAAnADwDQJyEf/3Hb+cXPO9f82XG3M/zAcTFjts54vp/G6NeWP8eN/YX3wWw4Mf8eAmr5hhn/2kAPwZwgTfFDgD/AOBcADz/hwM4srFmsr1vBwsYYKx/FAkUJwGwo/N3g4TWXQCwu5MVEWcBINvZnfxCsv6jbMwvCBiLAF61Mbtve69FqBfaPkiHd8AFl6XVZe3HudyP+TsCwHgFgMO+wey5AGZ8c1mHTWO7224WMMA49RFl62gIGPU0AfQuuEB/6dQP0fFflh0witS5d9wobe6w7IDBy6MnwQ5k9TBCuoozPZXFndu0g/28ByxggHHqg1wPGCyl+zKAd/pdvg0Aleffe+qH6PgvCRhkz5z3ntGzShaKKEK90HGjtLnD73gbpt7rDDuD29x1x35eDxizAKaDvTMcRS/DXmaBlhYwwMg3D8NJZ+R89QIA/+T/Xg8Yb/LeRAgYzA+8b5PnYKtzJ6AxdMLF7U8A8OnyCZt8fq0OV4R6oUSnK6fC8OP/AjgNAFV6yFR6bclO0gCjZAPSradjgHHqI9eNIanwausXkVO3ROd+2Y0hqfDqyxrys5BU5+ZoT+/JAOPUh78eMO4K4F1B0psslXcsWdKbHoXSLP+2py545KmboOO/LEK90PGDtrHDMQB9vkqK/6aH8SIAJLsr06seMF4J4FCQ9GbVFAny7GUWaGkBA4z1T5BfAPAGz8zJWPCNAT8+Q1YM8bC88pk+h7H+I2zcL/4WwB4fkmKy9tdLyNOfR72wcRZpb8+3A/ABvwuCHR8YSBVRphcr96jHQLbWHwH4IwAfBPAeAOcA+J4vFWfVlL3MAgYYNgfMAmYBs4BZoH0LmIfRvg1tD2YBs4BZoCcsYIDRE8NsF2kWMAuYBdq3gAFG+za0PZgFzAJmgZ6wgAFGTwyzXaRZwCxgFmjfAgYY7dvQ9mAWMAuYBXrCAgYYPTHMdpFmAbOAWaB9CxhgtG9D24NZwCxgFugJCxhg9MQw20WaBcwCZoH2LWCA0b4NbQ9mAbOAWaAnLGCA0RPDbBdpFjALmAXat4ABRvs2tD2YBcwCZoGesIABRk8Ms12kWcAsYBZo3wIGGO3b0PZgFjALmAV6wgIGGD0xzHaRZgGzgFmgfQsYYLRvQ9uDWcAsYBboCQsYYPTEMNtFmgXMAmaB9i1ggNG+DW0PZgGzgFmgJyxggNETw2wXaRYwC5gF2reAAUb7NrQ9mAXMAmaBnrCAAUZPDLNdpFnALGAWaN8CBhjt29D2YBYwC5gFesICBhg9Mcx2kWYBs4BZoH0LGGC0b0Pbg1nALGAW6AkLGGD0xDDbRZoFzAJmgfYtYIDRvg1tD2YBs4BZoCcsYIDRE8NsF2kWMAuYBdq3gAFG+za0PZgFzAJmgZ6wgAFGTwyzXaRZwCxgFmjfAgYY7dvQ9mAWMAuYBXrCAgYYPTHMdpFmAbOAWaB9CxhgtG9D24NZwCxgFugJCxhg9MQw20WaBcwCZoH2LWCA0b4NbQ9mAbOAWaAnLGCA0RPDbBdpFjALmAXat4ABRvs2tD2YBcwCZoGesIABRk8Ms12kWcAsYBZo3wIGGO3b0PZgFjALmAV6wgIGGD0xzHaRZgGzgFmgfQsYYLRvQ9uDWcAsYBboCQsYYPTEMNtFmgXMAmaB9i1ggNG+DW0PZgGzgFmgJyxggNETw2wXaRYwC5gF2reAAUb7NrQ9mAXMAmaBnrCAAUZPDLNdpFnALGAWaN8CBhjt29D2YBYwC5gFesICBhg9Mcx2kWYBs4BZoH0LGGC0b0Pbg1nALGAW6AkLGGD0xDDbRZoFzAJmgfYtYIDRvg1tD2YBs4BZoCcs8P8BSp1Os/GCCMQAAAAASUVORK5CYII=\" width=\"359.9999921972103\">"
      ],
      "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": 12,
   "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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\" width=\"359.9999921972103\">"
      ],
      "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": 13,
   "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": 14,
   "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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\" width=\"359.9999921972103\">"
      ],
      "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
}