examples/palettes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Yellowbrick Palettes\n",
    "\n",
    "This notebook demonstrates every Yellowbrick palette."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline \n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from yellowbrick.style.palettes import PALETTES, SEQUENCES, color_palette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCIICADCCoAAAjPgTx6jyl5wys04AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11225e650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1122f08d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nVuUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112385f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112424e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11249c1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnwEenqM+E4h2YQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11252ea10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1125a3790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1126426d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1126b8190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nj9xJegHsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11274af50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1127c1890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112861690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1128d8090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1129911d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQJIkAf8Bmf6js2GU5HcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1129f3390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112a5d750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACP5JREFUeJzt3WtMVGcex/HvIDOA3KXMZleozYoEQ62tWI14wXgL1jbR\neIlK2MgLCSXGVhpaE6WrhazRqAkqdRk0TarUGGvjG6NR04TiXTdqUrMNDRS6q/Wyii6D2w44Z18Y\npw5KmVnHZ1b8fV4xZ54z58+bL4czZ8BmWZaFiIgYERHuAUREXiSKroiIQYquiIhBiq6IiEGKroiI\nQYquiIhBz0V0CwsL+eCDD4Leb8qUKWzevDmkx9m7dy+1tbVBzyIiAhAZ7gGepU8//ZTk5OSQvmZt\nbS1vv/12SF9TRF4c/Tq6WVlZ4R5BRMRPQJcXLly4wKJFi3jjjTcYN24cK1eu5M6dO1y5coWsrCwa\nGhpYsmQJI0eOZMqUKezdu9dvf5fLxbRp0xgxYgT5+fnU19cHPWh3dzeVlZXk5OQwYcIEqqur8Xq9\nAL45du3aRV5eHmPHjqWtre2xywvffvstixcv5vXXX2fWrFk0NjaSnZ3NuXPn/I6zfv16xo0bR05O\nDuXl5bjdbuDB5YqffvoJl8vF1KlTg/4eRET6jK7b7aakpIT09HRqa2upqKjgxIkTfPLJJ741q1at\nIjc3F5fLxahRo1izZg3Nzc0AHDhwgG3btlFcXMxnn31Gfn4+VVVVNDY2BjXosWPH+P7779m8eTNF\nRUXU1dWxdetWvzUul4uKigpWrVrFkCFD/J67efMmRUVFxMTEUF1dzfz581mxYoUv3A8dPXqUH374\ngU2bNlFWVsahQ4fYsmULADU1NaSkpDB79mxqamqCml9EBAK4vNDc3Mzdu3cpKChg5MiRAMTFxdHS\n0uJbM3fuXIqLiwF47bXXOHz4MI2NjQwdOpQLFy6QlpbGggULABg9ejQOh4OYmJigBk1ISMDlchEd\nHU1eXh53795l9+7dlJaW+tbMmzePadOmPXH/3bt3ExUVxfbt23E4HOTl5WFZFhs2bPBbl5qayrZt\n24iMjCQ3N5dz585x/vx5AIYPH47D4cDpdOrShYj8T/o8083IyCAxMZGSkhKqqqo4deoU48ePZ8mS\nJb41I0aM8H0dExNDQkIC9+7dAx5EtqWlhXnz5rFz505aW1spLS1l9OjRQQ2am5tLdHS07/HkyZNx\nu900NTX5tr3yyiu97n/27FnGjx+Pw+HwbcvPz6fn3/vJzs4mMvLXn0WDBw+mo6MjqFlFRHrTZ3Rj\nY2Opr69nzJgx7N+/n6KiIiZNmsRXX33lW/NoDAEiIiJ8v7a/8847rFu3Dsuy2LhxI/n5+SxatIi2\ntragBk1JSfF7nJycjGVZfkHsueZR7e3tDBo06DdfE3jsDPzR70VE5GkF9EZaRkYG1dXVnD17lrq6\nOoYNG0ZFRQXXrl0L6CBz5sxh//79fPPNN6xZs4a2tjYqKyuDGrTn2eatW7ew2WyPhbQ3TqeTW7du\n+W1rb28PagYRkafVZ3RPnz5Nbm4u7e3t2O12Jk6cSFlZGV6vl6ioqD4PsHbtWt577z3gwfXShQsX\nMmPGDK5fvx7UoGfOnOH+/fu+x0eOHCEpKYmMjIyA9s/JyeHkyZN4PB7ftq+//hqbzRbUHAMGDAhq\nvYjIo/qM7quvvkpERATLly+noaGBhoYGNmzYQHp6OvHx8X0e4M033+TIkSO+M+V9+/Zx8OBBpk+f\nHtSgt2/fZsWKFZw6dYqamhq++OILSktLiYgI7EN1hYWFeDwe3n33XRoaGqivr/fdThZMeOPj47l0\n6RKXLl0Kan4REQggunFxcdTV1WG32ykvL6esrIy4uDh27txJZGRkn8F66623WL16NYcPH2bp0qXU\n1NRQUFDAsmXLAh7SZrMxZ84cEhISKC0tZd++fZSXl1NYWOi35kn7PTRo0CB27NiB2+1m+fLl7Nmz\nh48++gjLshg4cGDAsyxdupTvvvuO4uJiXesVkaDZXpR/13Px4kU8Hg9jxozxbTt+/DjFxcWcOXMm\noLN2EZGnFdaPAXu93sdu2eopVNdQW1tb+fjjj/nwww/Jysri6tWrbNmyhZkzZyq4ImJMWM90CwsL\n/T6C25PNZmPdunXMnj07JMerq6vjyy+/5Nq1ayQlJTFr1izef/99v3t3RUSepbBGt7W1lc7Ozt9c\nk5aWRmJioqGJRESerV6j6/V66ezsxG63B31blYjIi8qyLLq6uoiNjX3i3VW9XtPt7Oz0+4itiIgE\nLjMz84nvF/UaXbvdDsCmA4Npuhr4LVXPC2eih8qCNv780ufciLwT7nFCztmdxNp//Ymkiioib9wM\n9zgh1+1M5U7lai7/NZ5f2p+Lf4ASsKhkL9klHQzxVOCwboR7nJDz2Jy0OSqpcAzhhq3/vZ+SYnXx\nF0+rr6E99Rrdh5cUmq4O5G/NCc9mujB6+aWfAbgc3cY/7P0vSuldqQBEXf479h//GeZpQq/r5TQA\n/t1i5z/X+9ff4o/5XTcAcdZloq0fwzxN6P3MywBcHhDHjxHRfax+/vze+wvQ+4eu+tcpgojI/zlF\nV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdE\nxCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQg\nRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVX\nRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExCBFV0TE\nIEVXRMQgRVdExCBFV0TEIEVXRMQgRVdExKDI3p6wLAuAzD/cMzaMSc5EDwDZPw8htTsxzNOEnrM7\nCYBfsodzP/WlME8Tet3OVAAS/thFVPL9ME8TWlHJXgDctmw8pIZ5mtDz2JwAZN93k+r1hHma0Eux\nuoBfG9qTzerlmY6ODpqamp7dZCIi/VhmZibx8fGPbe81ul6vl87OTux2Ozab7ZkPKCLSH1iWRVdX\nF7GxsUREPH4Ft9foiohI6OmNNBERgxRdERGDFF0REYMUXRERg/4LOsWVxsYoUHgAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112b0d690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ['blue', 'green', 'red', 'maroon', 'yellow', 'cyan']\n",
    "for palette in PALETTES.keys():\n",
    "    color_palette(palette).plot()\n",
    "    plt.title(palette, loc='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/site-packages/matplotlib/pyplot.py:524: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  max_open_warning, RuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwuGomXA4aiac/wIl79p1L+txfwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112cb2f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112e746d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112f0b5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112f6e110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113000450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112dbc3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1128c9ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112cbdcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112c81110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKJQjUQvlSNRCORK1UM6/AUxUhX1Z6rk1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1124c0f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfwNDQ3Zuh8x4hwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11231bcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIqEwSkQklP8AmvygSax2eToAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112a52410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1124a6d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1128e3e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1126cbfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAQAAIBAAAAARCAAAgKT/Afii4uWEGuYNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1125c6b50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1126d8c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112782ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112955310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1127b1e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x112625150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11281c190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1125f1550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11274d890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACRxJREFUeJzt3W1sVFUex/HvTJ+oUyjdQlkLSDCBFFoFAg0hSnhMX6wR\njbramCBoN1WByBvEKJIIJmvU+NCaKE3RQkSjghijQRMFQ8Q0PrC6UYKBKFEe11DbAi0wQ+fui8rE\nUjo8DUxav59kXsyZc8/5n0Jyf71ze08oCIIASZL0lxZOdwGSJCn9DASSJMlAIEmSDASSJAkDgSRJ\nwkAgSZK4gECwadMm5s6dy8SJE5k0aRKVlZVs3LjxvI597733KCkp6fIaM2YM5eXlzJ07l2+++Sbp\n8V999RUlJSXs2bPnfMvtUUNDA7NmzWLcuHFUVlbS2Nh4yWNKktTbZZ5PpxUrVrB+/Xruuusuqqur\nCYfDfPHFF6xYsYKtW7fy4osvEgqFko4RCoVYt24dWVlZAMTjcQ4cOEBdXR33338/H330EUVFRUmP\nv1Rr1qzhmWee4Z577mH69Ol89913LFiwgFWrVjF58uRLHl+SpN7qnIHg/fff5+233+bll19m+vTp\nifYbbriBadOmcd9997FmzRruvffec0523XXXkZ2dnXg/fvx4ysrKqKio4NNPP+Xuu+++uFWcp7q6\nOu644w4effRRAKZMmcLx48d5+umnz/tqhyRJfdE5vzJYvXo1s2bN6hIGTps8eTJz5szh1VdfTbTN\nnDmTF154gdtuu40JEybwwQcfJB0/Eol0a9u+fTt33nkn48ePp7Kykr17957HUpJrbm6mubmZG2+8\nsUv7xIkT2blzJ62trZc8hyRJvVXSQPD777+ze/fubifRP6uoqKCpqYkffvgh0dbQ0MAtt9zCs88+\n2+VSfEdHR+IVjUb56aefWLZsGbm5ucyYMQOAffv2UVVVxaBBg3jppZeYOnUqK1euvNR1kp+fT3Z2\nNgcPHuzSfjpsHDhw4JLnkCSpt0r6lcH+/fsBKC4u7rHPsGHDCIKAQ4cOUVZWBkBZWRnz5s3r0i8I\nAiZMmNClLRwOc/3119PQ0MDVV18NwOuvv05+fj61tbVkZmYydepUmpubeeONNy58dWfMddNNN/HK\nK68wYsQIysvL+f7773nttdcAaG9vv6TxJUnqzZIGgtP7HmVm9twtIyOjS1+AkSNHdusXCoV46623\nyMzMpKWlheeee45YLEZNTQ1DhgxJ9Pv222+ZMmVKlzlnz56dNBDE4/Eu85+u6UzLli2jvb2dBQsW\nEAQBxcXFLFy4kMcff5zc3Nwex5ckqa9LGgiGDh0KJL+cvn//fkKhUOI3fIDCwsKz9h0zZkzipsKx\nY8dy8803U11dzYYNGxJ/fdDa2kpBQUGX4wYNGpR0EbNnz07UGAqFeOqpp7j11lu79cvLy6OmpoYj\nR45w+PBhRo4cyZdffglA//79k84hSVJfljQQFBYWMnbsWDZv3sztt99+1j6bN2+msLCQ0tLSC5q4\noKCApUuXsnTpUlavXs2DDz4IwMCBA2lqaurSt6WlJelYdXV1RKPRxPthw4adtd+WLVsoLi6mpKSE\nAQMGAPDjjz8SiUQYPnz4BdUvSVJfcs6/MnjggQf47LPP+Pjjj7t9tn37djZs2MD8+fMv6jkBc+bM\nYdy4cdTX1ydCQHl5Odu2bePkyZOJfp9//nnScUaNGkVpaWnilZ+ff9Z+69atY9WqVYn30WiUd999\nl2nTpl1w7ZIk9SXnDAQVFRXMnz+fJUuWsHLlSrZt20ZjYyPPP/88VVVVzJw5k6qqqosu4OGHH6a9\nvZ2amhoA5s2bR0dHB9XV1WzdupX6+nrefPPNix7/zyorK/nkk0+or6+nsbGRRYsWcfDgQRYuXJiS\n8SVJ6q3O69HFjzzyCLW1tezZs4clS5bw0EMP8fXXX/PEE09QW1vb5erAhV4pmDRpEjNmzGDjxo38\n/PPPDB48mLVr1xKPx1m8eDEffvghy5cvv7BV9aCiooLHHnuMd955h0WLFhGNRlm7di3XXnttSsaX\nJKm3CgV/vj1fkiT9JbnboSRJMhBIkiQDgSRJIslzCOLxOG1tbWRlZaVk62FJkpQ+QRAQi8WIRCKE\nw92vB/QYCNra2ti1a9dlLU6SJF1Zo0ePPuvTeXsMBKcfJTy0aCBX5eZcvsrSJBo7xS8Hmrhm4Cmy\nkz6vsXeKnoJfWzIZnvkL2aFT6S4n5aJBJntPjWD4sf+SHT+R7nJSKhrux968cQzfuYmsk8fSXU7K\nxXLy2DvmHwzasp6stiPpLiflYpEBHJ75T7JX1xBqbjr3Ab1MUFBI9F+LaV6+nI7ffkt3OSmXUVRE\nwZNP8p/lyznRx9aXU1jIxH//O3F+P1OPp8LTXxNclZvDgLy+t/HPiZMxAPJyoN/Zfza92onO5ZEX\nPk6/cDR5517oRLxzT4y8jlb6xfvWTpUngqsAiBw9RL/jzWmuJvVO5HbuVZL72z6yW/veCTOa37mX\nS8ae3YT/d/AcvXuf+JDOfWtiO3bQ8euvaa4m9eLXXANAy44dtPWx9eX+sedQT7cBeFOhJEkyEEiS\nJAOBJEnCQCBJkjAQSJIkDASSJAkDgSRJwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIk\nCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIk\nCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIk\nCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIk\nCQOBJEnCQCBJkoDMnj4IggCA9uMnr1gxV1I0dgqAYych2pHmYi6DaOfyOBbPJRpkpbeYyyAadP7X\nPZaRTzSUk+ZqUisa7gdAW/+/E83OS3M1qRfL6VzT8aJhnIoMSHM1qRf7Y00dI0cRH/i3NFeTekFB\nIQBZpaWEBw9OczWpl1FUBMDA0lL69bH15RR2/tudPr+fKRT08MnRo0fZtWvX5atMkiRdcaNHj6Z/\n//7d2nsMBPF4nLa2NrKysgiFQpe9QEmSdPkEQUAsFiMSiRAOd79joMdAIEmS/jq8qVCSJBkIJEmS\ngUCSJGEgkCRJwP8B9J92G2pYaLoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11306f590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1130e1ed0>"
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     "metadata": {},
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     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113191f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niBIAo/wfp37pDdNN09IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112fbb710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nABhEdAHAIKILAAYRXQAw6D+U/B4IT8SUZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1132435d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1132bc350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11334ce90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1133c2d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nahKHUZM4jJrE+Rv1kc+41u6cJAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11346a110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1134de690>"
      ]
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     "metadata": {},
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     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113566ed0>"
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     "metadata": {},
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     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1135df2d0>"
      ]
     },
     "metadata": {},
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    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11367d4d0>"
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1136e7e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113784cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113805590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1138a0950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEQmFUSIiofwBEUkqlJ6TuhIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11390e6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nENEFAIP+AzDuUrnozUeEAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113998910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113a0e910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113aad550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nISQNGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113b22c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113bbef10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnQAAABXCAYAAACNzth+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAACGI+gAAAAMR9ABAAAY7t9OQFVtcb58kAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113c47c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLPSl/fdQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113ceebd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1132869d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113dcc590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113e30910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113ecd0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x113f3ab50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113fe3390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmDKwrU+8NfcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114053810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1140f1c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11415ea50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1141e6c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11425eed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1142fcf90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJMlAIEmSDASSJAn4P2thZL4YVJkkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11437d1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11441c3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1144a6150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAB45JREFUeJzt3E9MU1sCx/FfLy2V0j5SwGocFHhgBQmjhobERNDEuCGR\nEDEx/sF/wYBgxoGYiBqjUBcaF1IV48Yx0cR/kVFjArowAWVhgm4mY4xFHwstDk5GGW0Z6Z97ZsFr\n59VS4dFiz+jvk7jouX96bmK+uT3cViOEECAikoSS6AkQEf0Wo0REUmGUiEgqjBIRSYVRIiKpMEpE\nJBXtZDvU1NSgv78/9Fqj0cBgMMBqtaKhoQFlZWUAgAMHDmBwcBDXrl3D1q1b8fz5c9y7dw8ZGRlh\n5/N6vaioqEB6ejquX78OjUYDAHjz5g0uXryIR48eYXh4GLNmzcKyZctQW1sLm80Wl4utra1FX19f\n2FhmZmbEGBEljmay55RqamqQnJyMvXv3AgCEEHC73bh06RL6+vpw8+ZNFBYW4vXr1/B6vcjLy8Pg\n4CAqKytRUVGBEydOhJ2vvb0dFy5cwK1bt5Cfnw8AePLkCRoaGjB//nxs2rQJ2dnZ+PDhAzo7O/Hw\n4UM4HA6sWbMm5otduXIlqqqqsHr16tCYTqdDYWFhzOcmojgRk9iyZYtobm6OGP/8+bMoLS0VR44c\nmfA4h8MhCgoKRH9/f2hscHBQFBcXizNnzoTG3G63WLVqldi5c6fw+/0R59m3b58oKysTqqpONtWv\nGhkZEYsWLRJPnz6N6TxENLOmvaak1+uRk5ODoaEhAEBLSws2bNgQ2l5fX48FCxagra0N4tebMbvd\njuzsbNTV1YX2u3v3LoaHh9Ha2oqkpKSI92loaEBJSQlGRkamO1UAgNPphEajwcKFC2M6DxHNrGlH\nKRAIwOVyISsrC8D4WlNwfQgAkpOTcfToUQwMDODGjRt48OABHj9+jGPHjkGn04X26+3tRWFhYeg8\nX8rNzcWpU6dgNpunO1UA41EyGAyw2+0oLS1FSUkJDh06hNHR0ZjOS0TxNelCNzC+jhQIBAAAqqri\n7du3OH/+PN6/f4/169dHPW758uWorKzE6dOnYTQasXnzZixZsiRsH5fLhby8vIhjg+8XNNFd1O/x\n4sULjI6OYs6cOTh37hwGBgbQ3t4Ot9sNh8MR07mJKH6mFKWuri50dXWFjWVkZKCtrQ2LFy/+6rH7\n9+9HT08PfD4fmpqaIraLCdbZe3p6UF9fHzbW2toa9vEwSFXVsHMoihJ2xxa0Y8cOVFZWhv6SZ7PZ\nYDab0dTUhJcvX4YW3YkosaYUpRUrVqC5uRlCCCiKApPJFPXj1pfS09NhtVphsViQkpISsX3u3Lmh\ndakgm82Gzs7O0Ovq6uqo59+2bVvokQWNRoPGxkbs2bMnYr/c3Fzk5uZGXJcQAk6nk1EiksSUopSW\nljbpHdF0lZeX4/jx43j37h0sFgsAwGg0oqioaErH2+12eDye0OvgOb7U3d0Ni8WCkpKS0NjY2BgA\nwGAwTHf6RBRnCX+iu6qqCpmZmTh8+DC8Xm/E9levXn31+JycHBQVFYX+zZ49e8L9rly5gpMnT4aN\n3b9/H3q9HsXFxdO/ACKKqyndKc0kk8kEh8OBxsZGrFu3Dhs3bkR+fj7cbjd6e3tx+/ZtZGVlRSyQ\n/167du1CXV0dDh48iLVr1+LZs2c4e/Ystm/fHvHUORElTsKjBABLly7FnTt3cPnyZVy9ehUulwta\nrRYFBQVoaWlBdXU19Hp9TO9RXl6Ojo4OdHR0oLu7G2azGbt37w57ZoqIEm/Sr5kQEX1LCV9TIiL6\nLUaJiKTCKBGRVKIudKuqCo/HA51ON+ET0kRE0yGEgM/nQ2pqKhQl8r4oapQ8Hg+cTueMTo6IflxW\nqxUmkyliPGqUQt/k/8sAlF/cMzaxRBGZeog/L4bl33ro1O/vU6xPUfEubQzz5s0L+1WG74XP58PQ\n0BA+Gv8GVRlL9HTiSlH1+Mn9R/z1n+fw0f+vRE8n7oxJaVhv+VPU/5dRoxT8yKb84oby99h+y0hG\nYl4KAgBS/FokB2L7BQIZeZMCAMZgMBhifsZLRsGvCPl1H6Fqv6+fn1H84197co29xHv/PxI8m/hL\n02YCQNRloe/vFoGI/q8xSkQkFUaJiKTCKBGRVBglIpIKo0REUmGUiEgqjBIRSYVRIiKpMEpEJBVG\niYikwigRkVQYJSKSCqNERFJhlIhIKowSEUmFUSIiqTBKRCQVRomIpMIoEZFUGCUikgqjRERSYZSI\nSCqMEhFJhVEiIqkwSkQkFUaJiKTCKBGRVBglIpIKo0REUmGUiEgqjBIRSYVRIiKpMEpEJBVGiYik\nwigRkVQYJSKSCqNERFJhlIhIKowSEUmFUSIiqTBKRCQVRomIpMIoEZFUGCUikgqjRERSYZSISCqM\nEhFJhVEiIqkwSkQkFUaJiKTCKBGRVLTRNgghAADqz8ZvNplvSWTqAQD/0frhV9QEzyb+fL9e0+jo\nKHw+X4JnE3/Ba9L6foIa0Cd4NvGlqOPX8wd9PkxJ5gTPJv6MSWkA/teYL2lElC2fPn2C0+mcuZkR\n0Q/NarXCZDJFjEeNkqqq8Hg80Ol00Gg0Mz5BIvoxCCHg8/mQmpoKRYlcQYoaJSKiROBCNxFJhVEi\nIqkwSkQkFUaJiKTyX3FPWcetyDS3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11452d050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAGAQ0QUAg4guABhEdAHAoP8DqzdLXZEflwwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114598c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1146390d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1146ad850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZKA/wHKf1oJoBMdsgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11474ab10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1147cb490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114866ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAdByseTZnTKwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11456f490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11493fd50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhPI/qx5FloaVZP8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1149af2d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngVpvXlY8tgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114a42050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114abb410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114b584d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114bcc6d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114c69a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114cf3690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/BcKVCdvDDaH0wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114d7e690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114df6190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114e89550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114ef4c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nOwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114f9ae10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11501b990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1150b6e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11512eb50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1151cd490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x115230950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1152d7c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115342cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1153e8e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1150f0910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n6ZMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11548c4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11538f350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMt5+Ar3FMMsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115596490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1155cd790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1156a96d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11566e0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1157ba890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1157ea750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1158b0850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTMoDAIwgKAAAIwgKAMAIggIAMOI/vhw5qJY9iCUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11590ba90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1159c7410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQCBJkjAQSJIk4L/BRpa1ZVhnTAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115a28650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjwAAABXCAYAAAAAo58qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ae3190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x115b24c10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x115bfad50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAB7ZJREFUeJzt3G9IU/8Cx/HP2ZzWRL26exkyQ6ibDhO1UBJaQoXlRQIr\n0HEhH4mSZf0MsWEa/UHKECHCwrAooh5UQ5NIfoWWig/qiRmFZUV/flldKDFq+nNr53sfeB2tOZ3l\nn9/X+3lB6Pmes/PnwXs75+yYIoQQICJpaOZ7B4hoehgtkWQYLZFkGC2RZBgtkWQYLZFkJo3WZrMh\nMTERz549m3C+1WrFhg0bMDIyApvNBqvV6rNMe3s7CgsLYbFYkJSUhMzMTBw9ehSDg4PT2tGBgQGY\nzWavf8nJycjJyUFLS8u01jVT3rx5g5SUFDQ3N8/L9un/U9BkM/ft24e7d+/i8OHDuHjxote8q1ev\nore3F42NjVi8eDEURfF5fU1NDS5cuICtW7fCarUiPDwcT58+xdmzZ9He3g673Y7w8PBp7fD+/fuR\nnJwMIQQcDgc6OztRXl6OyMhIrF27dlrr+lUHDhzA6OjonG6TCGIK165dE2azWVy/ft0zNjQ0JNLT\n04XNZvOM2Ww2kZeX55m+ffu2iI+PF01NTT7r/Pjxo1i9erWora2davMeb9++FfHx8aKrq8tnXl5e\nnti9e3fA65oJdrtdZGRkCLPZPOExEs2WKa9pt23bhtTUVBw/fhwOhwMAUFtbC61WC5vN5vd1jY2N\nSEtLQ05Ojs88g8GA4uJiREREeMbMZjNaWlpQUlKClStXwmKxoL6+PqA3nrCwMK/p9evXo66uzmts\n7969yM/PD2h9U/n06RNqampQVVUFwQfKaI4FdCPq4MGD+Pz5MxoaGvDkyRPY7XZUVlZ6Rfe9oaEh\n9Pb2Iisry+868/PzUVBQ4DVWXV2N2NhYnD59GtnZ2Th58iS6urq8llFVFW63G263G1+/fsWNGzdw\n79495ObmBnIoM6K6uhoWiwUZGRlztk2icZNe045btmwZCgoKcO7cOXR3d2PdunWTBvnu3TsIIbBk\nyRKvcSEEVFX1GtNqtZ7fLRYLysrKAADp6elobW1FR0eH17VqUVGR16eboijYvHkz1qxZE8ih/LKO\njg50d3ejtbV1TrZH9KOAogWAHTt24ObNm3j9+jVOnTo16bI/hjluz549uHXrltfYw4cPERwcDABI\nSkrymmc0GjEyMuI1VllZiZSUFADAyMgIHjx4gPr6ehw5cgRVVVWBHo4Pt9vtNf39m8m44eFhHDp0\nCGVlZYiKioLT6fzp7RH9rICjDQ4OxqpVq/Dy5UsYjcZJl42OjgYw9on7vfLychQVFQEA7ty543PN\numjRIq9pjUbj8wYQGxuLFStWeKZTU1OhqipOnDiB4uJiGAyGQA/J4/79+8jPz4eiKBBCQFEU9PX1\n+SxXV1cHo9GILVu2wO1249u3bwDG3qRUVYVGw6+9afYFHO10GAwGJCQkoK2tzeu725iYGMTExAAA\n+vv7Z2x78fHxUFUVAwMDMBgMUBTF55NzeHjY7+sTExNht9un3E57ezvev3+PxMREz5iiKKioqEB9\nfT3a2tp+/iCIAjQr0QJAYWEhSktL0dzcPOEd5OfPn8/Yth4/fgxFUWAymQAAer0eHz588Mx3Op14\n9OgRli5dOuHr9Xq916e3Pw0NDV6nxC6XC1arFSUlJdi4ceMvHgVRYGYt2qysLPT19aGiogKdnZ3Y\ntGkToqKi8OrVKzQ1NaGnpweZmZme69lAvXjxwvMVj6qq6O3txZkzZ5Cdne05NbZYLLh8+TKuXLkC\nk8mE8+fPe05lf8Xy5cu9pscDNplMPvOIZsusRQsApaWlsFgsuHTpkufRxcjISKSmpqK0tBRpaWme\nZRVF8XmqaqLpY8eOeaa1Wi2io6Oxfft27Nq1yzO+c+dODA4OoqamBiEhIcjNzUVCQgJ6enpm/Bgn\nehKMaDYpgk8HEEmFtzuJJMNoiSTDaIkk4/dGlKqqcDgc0Ol0vNlCNIeEEHC5XAgNDZ3wgR2/0Toc\njhl9AIKIpicuLs7nL9iASaLV6XQAAJMJ0Otnb8fmi9MJvH4NvA0ZgkvjnvoFktGpWsSM/g2XPzvx\nWV14XxBEaBT8OyIYJ3//gMGvv/4d/F9JhF6L3/4V7WnwR36jHT8l1uuBaf7nElL488+xnyNBLji1\nCy/aYLcKjAJ/fBP46F540f79f3/P8fw/o3g/5JrfnZlh/wgby9LfZSlvRBFJhtESSYbREkmG0RJJ\nhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG\n0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbR\nEkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtESSYbREkmG0RJJhtES\nSYbREkmG0RJJhtESSYbREkmG0RJJJsjfDCEEAGB4eM72ZU45nWM/F3/TIUhdeO9dOlULAFgSpCB8\n4R0eIjQKAOCfxhBEhWrneW9mVoR+7HjGG/yRIvzM+fLlC/r7+2dvz4hoUnFxcQgLC/MZ9xutqqpw\nOBzQ6XRQFGXWd5CIxggh4HK5EBoaCo3G9zTJb7RE9Ne0AK92iBY2RkskGUZLJBlGSySZ/wKtKKlF\nuVRCoQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115b96c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x115d10750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIKILAAb9F2W2lOwCinjsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115d3da10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACLxJREFUeJzt3WtoVGcCh/H/yZiLiSZNppJmExHXy2RVvBGr0AheWhSk\nQbSYsGg+iDRotV1FdNR0sS2iFpGVoKLYoogipiEqQdle0npD4ofVWDXVjdvIRteim8bLmDRx5t0P\n0Vlnk4mT9o3R2ecHgZz3zJzzHgbmycyZOXGMMUYAAPxGMT09AQBAdCAoAAArCAoAwAqCAgCwgqAA\nAKwgKAAAK3p1ttLr9aqiokLl5eUaMmRIu/UFBQW6ffu2Kioq9NFHH6murk4HDhwIuU1lZaUOHDig\ny5cv6969e0pPT9eUKVNUVFSktLS0iCd648YNTZ06NWQsPj5eAwcO1Pz585WXlxfxtn6t8vJyrVq1\nqsN1WVlZ+vrrr7t9DgDwouo0KCtXrtR3332njz/+WHv37g1ZV1paqurqau3atUu9e/eW4zjt7r9x\n40bt2bNHs2bNUkFBgZKTk3XlyhV99tlnqqysVFlZmZKTk7s04TVr1mjUqFEyxsjn8+nEiRNasWKF\nUlNTNXHixC5tq6smTZqkgwcPhozV1dXJ6/XqnXfe6dZ9A8ALzzzDF198YbKzs83hw4eDY42NjWbC\nhAnG6/UGx7xer8nPzw8uf/XVV8bj8Zjy8vJ227xz544ZP3682bRp07N2H1RfX288Ho85efJku3X5\n+fnm/fffj3hbNuXn55u5c+f2yL4B4EXyzHMos2fPVk5Ojj799FP5fD5J0qZNm+RyueT1esPeb9eu\nXRo3bpxmzpzZbp3b7daiRYuUkpISHMvOztaRI0e0ZMkSjRkzRrm5udq6dWtEUezbt2/I8pQpU7R5\n8+aQsWXLlqmwsDCi7UXqyJEj+v7771VcXGx1uwDwMoropPzatWt19+5d7dixQz/88IPKyspUXFwc\nEoSnNTY2qrq6WtOnTw+7zcLCQi1YsCBkbN26dRowYIC2b9+uGTNmqKSkRCdPngy5TSAQkN/vl9/v\n14MHD1RRUaGqqirNmTMnkkOxxhijkpIS5eXlyePxPNd9A8CLqNNzKE8MGjRICxYs0Oeff67Tp09r\n8uTJncbi5s2bMsaof//+IePGGAUCgZAxl8sV/D03N1fLly+XJE2YMEHHjh3T8ePHQ86NFBUVyTx1\n+THHcfT222/rjTfeiORQrKmsrFR9fb22b9/+XPcLAC+qiIIiSQsXLtTRo0d1/fp1bdu2rdPb/m80\nnvjggw/05ZdfhoxduHBBcXFxkqSRI0eGrEtPT1dTU1PIWHFxsUaPHi1Jampq0vnz57V161Z98skn\n+vDDDyM9nHb8fn/I8tOh60hpaalef/11DR48+FfvEwCiScRBiYuL09ixY/Xjjz8qPT2909tmZGRI\nanul8rQVK1aoqKhIkvTtt9+2O0eSkJAQshwTE9MuTgMGDNDw4cODyzk5OQoEAtqyZYsWLVokt9sd\n6SEFnT17VoWFhXIcR8YYOY6jmpqasLdvbm7WmTNntGbNmi7vCwCiVcRB6Qq3261hw4bpm2++UUFB\nQXA8KytLWVlZkqSrV69a25/H41EgENCNGzfkdrvlOE67VxwPHz4Me/8RI0aorKws4v1VVVWppaVF\nb7755q+eMwBEm277pvy7776rU6dO6dChQx2ur62ttbavS5cuyXEcZWZmSpISExN169at4PqWlhZd\nvHgx7P0TExM1fPjwkJ/OXLx4UVlZWV36YiYARLtueYUiSdOnT1dNTY1Wr16tEydOaNq0aUpLS1Nd\nXZ3Ky8t17tw5vfXWW8HzJ5G6du1a8GPCgUBA1dXV2rlzp2bMmBF8uys3N1f79+/XwYMHlZmZqd27\nd+vRo0fWjq22tlYDBw60tj0AiAbdFhRJWrp0qXJzc7Vv3z6tX79eDQ0NSk1NVU5OjpYuXapx48YF\nb+s4Trtv23e0vGHDhuCyy+VSRkaG5s2bp8WLFwfH33vvPTU0NGjjxo2Kj4/XnDlzNGzYMJ07d87K\ncTU0NKhfv35WtgUA0cIxhn8BDAD47bjaMADACoICALCCoAAArAh7Uj4QCMjn8yk2NrbDS9MDAP7/\nGGPU2tqqpKQkxcSEviYJGxSfz2f1y4cAgOgxdOjQdld6DxuU2NhYSVJmppSY2L0T6wktLdL161Jr\naqPk8j/7Di8bv0uxP7+iv+mBmtXxtdVeZgmK0Vj10f67LbobiK4PKqbEOPpjSpz+cqVJ/26JrmOT\nJHecoz95eqvkr7fU8MDe98NeFGl9emnJtNe0bke1bv/c3NPTsS4tJU5/Xjgm2IinhQ3Kk7e5EhOl\nLv5TxZdC85PHOb5Vio3CoLS2RaRRfvmc6AtK0uNPu//zkdEdf3Q96b76+Lqkf38Q0M3m6Do2Sfpd\nQttzS+1Pv+hfja09PBv7Ml5pe6Kt+cdd1f8U/pJPL6vXXu0tqf33BCVOygMALCEoAAArCAoAwAqC\nAgCwgqAAAKwgKAAAKwgKAMAKggIAsIKgAACsICgAACsICgDACoICALCCoAAArCAoAAArCAoAwAqC\nAgCwgqAAAKwgKAAAKwgKAMAKggIAsIKgAACsICgAACsICgDACoICALCCoAAArCAoAAArCAoAwAqC\nAgCwgqAAAKwgKAAAKwgKAMAKggIAsIKgAACsICgAACsICgDACoICALCCoAAArCAoAAArCAoAwAqC\nAgCwgqAAAKwgKAAAKwgKAMAKggIAsIKgAACsICgAACsICgDACoICALCCoAAArCAoAAArCAoAwAqC\nAgCwole4FcYYSdLDh89tLs9VS8vjX36JlR5FYVf9LknSK3IpwTg9PBn7Eh7/LdS/l6PkKHv4UmLa\nHq8hfWKUFmd6eDb2uePajm9werzSklw9PBv70vq0Pa3+4fcpejU1vodnY19aSpyk/zbiaY7paFTS\n/fv3dfXq1e6dGQDgpTR06FD17ds3ZCxsUAKBgHw+n2JjY+U40fcXLgCg64wxam1tVVJSkmJiQt8e\nCBsUAAC6IsrefQYA9BSCAgCwgqAAAKwgKAAAK/4DOdlZdyG1JWMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115e1b310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x115e52390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115f2d490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ef0c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116041650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noTBKRCSU/wMiX3+2kgcI6gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1160703d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116136650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1161918d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11624a250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzQwn4UFjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1162ac490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116329590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnQAAABXCAYAAACNzth+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLqOkGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1163cdbd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11644c990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116496f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116557390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1165dff90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1166566d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1166e9b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nU5FZ8OMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116769850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjwAAABXCAYAAAAAo58qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nj8ADAACM939Px5qx0vQwWwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116807690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnQAAABXCAYAAACNzth+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYLj/Ao3AZd0eEBEUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1168833d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1168fa890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1169a4f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKEoiYhRFSUSM8l+K8F443osJ9AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1169fd910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nM+OFipcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116a9de90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116b32f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJgAABghMAAAM/B/0H6Vj/3SrqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116ba8e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACeBJREFUeJzt3VtslNXex/HvlB6mlJazbLbUE5G0FohTLMXQIBDDhckb\nE2MiJFbqIaG8akVSg0h2aogSaJVqqduamGhKUKpW46H1Qi88RI0JWy7EpCFR2VsEBG3ZttOhTGdm\nXxT6vqXtTqmFgfr9JHPxrFnzPP9FAvObtRbPE0gkEgkkSdKfWkqyC5AkSclnIJAkSQYCSZJkIJAk\nSRgIJEkSBgJJksQIAkFpaSl5eXn9r/z8fBYtWsSaNWv4/PPPL0aN5OXl0dTUdFGu9d/09vayc+dO\nli1bRigU4t577+W7775LdlmSJP1hqSPptHTpUh555BEAEokEXV1dNDY2Ul5ezltvvUV+fv4FLfJS\nsWPHDvbu3Ut5eTmFhYV89tlnlJaW8uabbzJ37txklydJ0qiNKBBMmTKFhQsXDmi76aabWLZsGU1N\nTTz55JMXorZLSldXF3v27KGiooLy8nIAbr75Zo4fP87zzz9PXV1dkiuUJGn0Rr2HICMjg2uuuYYj\nR44A8Pjjj7N69eoBfV5//XXy8vL6j1euXEltbS133HEHoVCI999/n82bN1NRUUFDQwNLliyhuLiY\nrVu3cvr06WGv/f333/PAAw8QCoVYsmQJTz31FD09Pf3vnzhxgocffpji4mJCoRD33XcfbW1tox0q\nAIcOHSKRSFBSUjKgvbCwkC+//PIPnVuSpGQbdSCIxWL8/PPPzJkzB4BAIDCoTyAQGNT+yiuvcPvt\nt1NTU0NxcTEAX331Fe+99x5PP/00GzZs4J133qGqqmrI6x4/fpy7776bSCRCbW0tmzZtoqWlhU2b\nNvX3qays5OjRo1RXV1NfX08kEmHdunXE4/HRDpeZM2eSSCQ4evTogPbDhw8TDof5/fffR31uSZKS\nbURLBolEglgsBkA8Hufo0aM0NDTQ3t7OnXfeeV4XnD9/PmvXrh3QFolEeOmll8jNze2/xrZt26is\nrGT69OkD+r766qukpKTw8ssvk5mZCcDs2bMpKyujra2NvLw89u/fz0MPPcQtt9wCQG5uLs3NzXR3\ndzNp0qTzqvesWbNmsXjxYrZv386UKVPIz8/niy++4O233+4fQ05OzqjOLUlSso1ohqC1tZWCggIK\nCgpYsGABq1at4tNPP2Xr1q3ccMMN53XBa6+9dlDb/Pnz+8MAwK233kosFmP//v2D+u7bt49FixaR\nnp5OLBYjFotRWFhIMBjk66+/Bvr2N9TV1VFZWUlrayvTpk3j0UcfHTYMnD3P2ddwampquPLKK7nn\nnnsoKiqivr6eBx98EIBgMHhefw6SJF1KRjRDUFJSwsaNG0kkEqSkpJCdnd2/VHC+zv3FD33T8f/f\n1KlTAYachj958iTffvstBQUFA9oDgQAnTpwA4LnnnmPXrl18+OGHtLS0kJ6ezl133cUTTzwxZE0F\nBQUEAgESiQSBQIDGxkaKiooG9Zs1axaNjY20t7fT2dnJ1VdfTXNzM4FAYNQzD5IkXQpGFAgmT548\nopmAc39dd3d3j6iIkydPDjhub28Hhg4P2dnZrFq1inXr1nHuk5tnzJgBQE5ODlu2bGHLli0cOHCA\n5uZmdu/ezY033shtt9026JzNzc0DjoeaxQD44IMPWLhwIVdddRXTpk0DoK2tjblz5zJhwoQRjVWS\npEvRmN2pMCsri19++WVA2759+0b02QMHDtDR0dF//NFHH5GamkooFBrUNxQK8cMPP5Cfn9+/jDFz\n5kyeffZZDh06RFdXFytXruTjjz8G+pYjqqqqCAaDHDt2bMjrnz3P2dfEiROH7Ldr1y7eeOON/uOO\njg5aW1tZsWLFiMYpSdKlakQzBCNRUlLCnj172L59OytWrOCTTz7hm2++GdFne3p6WL9+PeXl5Rw+\nfJidO3dSWlo65Ca9srIy3n33XdavX8+aNWuIRqO88MIL/Pbbb+Tl5TFp0iSuu+46tm3bRiQS4Yor\nrqClpYXe3t7+TYajtXr1aurq6sjNzWX27NnU19eTlpZGWVnZHzqvJEnJNmaBYPny5VRUVPDaa6/R\n1NTE8uXLqaqqYuPGjf19hvqviQALFixg6dKlPPbYYwSDQe6///7+zXrnfm7OnDns3r2bmpoaNmzY\nQHp6OkVFRdTW1jJ58mQAqqurqa6uZseOHXR2dnL99dfT0NDwh+8muHbtWsLhMC+++CLhcJjFixfz\nzDPP9C8fSJJ0uQokzl2Iv8g2b97Mjz/+yN69e5NZhiRJf2o+7VCSJBkIJEnSJbBkIEmSkm/YTYXx\neJxwOExaWtqwmwElSdLlIZFIEI1GycrKIiVl8ALBsIEgHA5z8ODBC1qcJEm6uObNm0d2dvag9mED\nQVpaGtD34KDMzKFv1HM5i0ZP89NPPzFjxl9IS01LdjljLtob5ddfj5GRMZ2UlPF3F8V4PEZPz2+E\nw5nEE+NrK0xKIE5WVoR//thLbzTZ1Yy91DS4+tpU9v+jk1OR8bdiGcwMEFqUzafv/ky4szfZ5Yy5\nrOxUbrn9St7/exu/tw//mPrLVc60dP7nf/PY87d/8O/jkWSXM6ayp2dQuq2o//v9XMMGgrPLBJmZ\nE8nJHn9P8TvVcwqAzOBE0tMyklzN2Dsd7QEgNTWDCRPGX+CJxaL09EAsnko8Pr4CTyKl7xbgkW44\n3ZPkYi6A9DN/3U52xAiHR/9I8ktVVlZfQD1x5NS4/cIEOPJ9Fx3HxtcXJsDUv/Q9Rfdf33Xw67/C\nSa5mbE2d3Te24bYBjK+fVpIkaVQMBJIkyUAgSZIMBJIkCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJ\nwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIkCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJ\nwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIkCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJ\nwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIkCQOBJEnCQCBJkjAQSJIkDASSJAkDgSRJ\nwkAgSZIwEEiSJAwEkiQJA4EkScJAIEmSMBBIkiQMBJIkCUgd7o1EIgFAJNJ90Yq5mKLR0wBETnXT\n2xtNcjVjL3pmTL29PcTjvUmuZuzF4zEAJqT0EgjEk1zN2Eo5M57MiZCWluRiLoDUM2OaMnUCweD4\n+00SzAwAMPOvQSZmD/tP7GUr68yY/jp3EpOmpie5mrGXM61vTFcVTGXyzGCSqxlb2dMzgP/7fj9X\nIDHMO52dnRw8ePDCVSZJki66efPmkZ2dPah92EAQj8cJh8OkpaURCAQueIGSJOnCSSQSRKNRsrKy\nSEkZPDs3bCCQJEl/HuNvAU+SJJ03A4EkSTIQSJIkA4EkSQL+A9zzyBygdgddAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116c51310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116cc4f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmP8C9ysvMAxd8AEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116d3ab90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niITyL31wTCOT42e1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116dcdb90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116e6f0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116ecead0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAGCCYAAAb+C9e6mQ2vwPHCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116f6f050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116fe3750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11707e7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n0mHUJJ1/AXbjouMYcfTUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1170fdcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1171b7590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11721b190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1172af4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11731d590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1173b8710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11742f1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1174cd210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAB+BJREFUeJzt3H1IU3scx/HPZhN1LtEe7EmhMqG0plBKPiGG/pGmpn9o\nGWUkYZoFZZSmgaFBLlqFCiJqBv0TTCLRwKgwsCREE4xIeiAjJezBoUtrbrt/SLtNneve1O137+cF\nEjvn7Phd8N45Ox4mMZlMJhCRMKT2HoCI/hlGSyQYRkskGEZLJBhGSyQYRkskmN+OtrOzE8ePH0d0\ndDQ2b96M6OhoFBUV4cOHD/M534Lq7+9HUFAQbt++be9RiKz6rWgbGhqwf/9+mEwmFBYWor6+Hnl5\neejp6UFqairev38/33MuiHPnzuH79+/2HoNoVjaj7e3tRXl5OXJycnDt2jXExcVh69atSE1Nxa1b\nt+Dp6Qm1Wr0Qs86rxsZGvH371t5jENlkM9q6ujqsWbMGR44cmbbO1dUVeXl58Pb2Ni+LiYmBWq1G\nSkoKgoOD0dTUBADo7u7G3r17oVQqERUVhYqKCvNzrl+/ji1btkCn01nsf9++fTh79qz5+Xv27EFw\ncDC2b9+OM2fOYHh4+N+96ik+f/6Mixcvori4GLxBjBydzWgfPXqEmJgYODk5zbh+586dOH36tMWy\n+vp6JCUlQaVSITQ0FC9fvkRmZia8vLxQUVGBw4cPo7a2FiqVCgCQkJAAo9GIe/fumffx8eNHdHV1\nITExEaOjo8jOzoaPjw+qq6tRXFyM9vZ2nD9//k9eu1lZWRkiIiIQFRU1J/sjmk+LZlup1WoxOjoK\nX19fi+UmkwlGo9Fi2a9RBwYG4sCBA+bHZWVl8PX1NR9dIyMj4eLigpKSEhw6dAhLly5FaGgoWlpa\nkJycDABoaWkxL+/p6YFWq0VGRgaUSiUAwN3dHW/evPmDlz6pra0N7e3tuHv37h/vi2ghzHqknRrm\nT+Xl5QgICLD4+fXz4Nq1ay227+zsRHh4OAwGg/knIiICer0eXV1dAICkpCQ8fvwYWq0WANDc3Iz4\n+HgAgJ+fHzw8PJCdnY3S0lI8efIE4eHhyMzMtDr7r7/LYDDMuM23b99QUlKC/Px8eHl5zfZfQeQw\nZo3W09MTLi4uGBgYsFiemZkJjUYDjUaDkpISSCQSi/VLliyxeDw8PIyGhgaLyKOjoyGRSDA0NAQA\niI2NhUwmQ2trK/r7+9Hb24vExEQAgFwux82bNxESEgKNRoODBw8iKioKjY2NM8799OlTBAQEIDAw\n0PzvTC5fvgxvb2/s3r0bBoMBExMTACbfrKy9YRHZ26ynx8DkqezDhw9x8uRJ8zJvb2/zxaepF49m\nolAokJCQgJSUlGkXelauXAlg8qJWbGwsWltbodVqsW7dOmzcuNG8nZ+fH65evQq9Xo+Ojg7U1tai\nuLgY4eHhFhfCgMnTc41GY3OuBw8eYHBw0CJqiUSCwsJCVFZW4v79+zb3QbTQbEablZWFjIwMVFZW\nIjc3d9r6V69e2fwlwcHBePfuHTZt2mRe9uLFC1y6dAkFBQXmU9PExETk5ubi69evSEhIMG/b0dGB\nEydOoLm5GZ6enoiMjISHhwfS0tIwNDQ0LVo3NzcEBATYnKu6uho/fvwwP9br9UhPT0deXh7i4uJs\nPp/IHmxGq1QqUVRUhNLSUnR3dyMpKQkrVqzA4OAgmpub0dbWhpCQECxbtszqPrKzs5GRkYGCggLE\nx8djeHgYV65cgZubm8Xn37CwMCgUCjx//tzib7+BgYGQSqU4duwYsrKyAAA1NTXw8fGxOBr/Uxs2\nbLB4/DPg1atXT1tH5ChsRgsA6enpCAoKwo0bN6BWq/Hp0ycsXrwYSqUSVVVViImJMW879fMtMBl+\nXV0d1Go1jh49CrlcjsjISOTn51tcdZZKpQgLC0N/fz98fHzMy93d3VFTUwOVSoVTp07BYDBg27Zt\nuHDhgtU/Rf1bM81P5EgkjvR1MxMTE9ixYwdycnKQlpZm73GIHNJvHWnnm8FgQFVVFZ49e4bx8XHs\n2rXL3iMROSyHiNbJyQlNTU0YGxuDSqWCm5ubvUciclgOdXpMRLZZPdIajUbodDrIZDJenCFaQCaT\nCXq9HnK5HFLp9PufrEar0+nQ19c3r8MRkXX+/v5QKBTTlluNViaTAQCWL18OV1fX+ZvMTvR6/bTb\nM/+LXr9+bXEDyX+Fs7Mz1q9fjzt37mBkZMTe48wpuVyO5ORkc4NTWY325ymxq6sr3N3d52c6O/q/\nfEOFTqfD+Pi4vceYcy4uLgCAgYEBfPnyxc7TzC0PDw8A1u8Z4Be7EQmG0RIJhtESCYbREgmG0RIJ\nhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG\n0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbR\nEgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtESCYbREgmG0RIJhtES\nCYbREgmG0RIJhtESCYbREglmkbUVJpMJADA2NrZgwywkvV5v7xEWhFwuh0wms/cYc87Z2RkAsGrV\nKigUCjtPM7fkcjmAvxucSmKysmZkZAR9fX3zNxkRzcrf33/GNySr0RqNRuh0OshkMkgkknkfkIgm\nmUwm6PV6yOVySKXTP8FajZaIHBMvRBEJhtESCYbREgmG0RIJ5i9zMFfUdLow7QAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117549690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAfCWjr8TvNjYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1175e04d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x116b4b850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAQAivCpBJ26AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11768ca90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAMDA30J24nTO94I5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1177037d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n2Pn01D08tq0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11779f650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117814ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1178bc190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11791dd50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUnRFRAxSdEVEDFJ0RUQM+h9d37G38IfrhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1179b3150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAIwgUAAARhAoAAAj/gcB4HwMznh0VAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117a2a4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x117ac6590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nihkEkiTJIJAkSQaBJEkC/h8A/dryfQC3BQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117b3b790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjwAAABXCAYAAAAAo58qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117bd7ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnQAAABXCAYAAACNzth+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117c61750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFDXhDkVNuENRE+78F7eA2SPJOX00AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117d096d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noSUSDENLJBiGlkgw/wX9DVFLyenrXgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117d8f350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x117e0ef50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nc83mAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117e87610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117f24750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/Ado5aiBAN6ZzQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117f9e0d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAACAQAAEIEAAABI+i9kv79Z/oWhOAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11802cf50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nadRECxUvFEkcRk3iMGoSh1GTOP8BMIhy5qPo0kkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1180ac750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118147bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1181b5950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118240b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElBoAAAjCBQAABGECgAACP+D22K/rr1WbwYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1182b6b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1183547d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1183c9fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjwAAABXCAYAAAAAo58qAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUNseA3cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118471090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1184eded0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nngAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118593e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRkskDKMlEobREgnzL7Pv31MHaBtyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11861da10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1186a8850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118712d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n8kgiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1187b2ed0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTAAADBBMAAAMEEwAAAz8D9foN3MRAhR6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118828890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1188c8710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118938f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAO0AAABXCAYAAADoHMKcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1189e3250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118a500d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118ad8410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGydIonR0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118b4f4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118bed650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nA4EkSQL+B6EGijunaZO/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118a11c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABXCAYAAABC3wQgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118c71450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x118cf63d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAABXCAYAAABC+lMJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118d83110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAABXCAYAAACnZJZlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118da6f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAABXCAYAAAAjzrMOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118e81f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcwAAABXCAYAAACJDXWyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118ebae10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgQAAABXCAYAAAB7h13mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEAAAEAgAAACBAAAAiEAAAAAk/Q+qtNV65v1W4wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118fa1190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for name, maps in SEQUENCES.items():\n",
    "    for num, palette in maps.items():\n",
    "        color_palette(palette).plot()\n",
    "        plt.title(\"{} - {}\".format(name, num), loc='left')"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:bigleaf]",
   "language": "python",
   "name": "conda-env-bigleaf-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}