src/matplotlib_histogram.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `matplotlib` histogram\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import random"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data\n",
    "\n",
    "Generate fake distribution for height and weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DATA\n",
    "nr = 2000  # sample size\n",
    "data_height = [\n",
    "    random.normalvariate(mu=176,sigma=4)\n",
    "    for _ in range(nr)\n",
    "]\n",
    "data_weight = [\n",
    "    random.normalvariate(mu=90,sigma=3)\n",
    "    for _ in range(nr)\n",
    "]\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot histogram of heights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "ax.hist(\n",
    "    data_height,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\"  # GNOME purple 2\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot1.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot histogram of heights with custom bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "ax.hist(\n",
    "    data_height,\n",
    "    bins=15,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\"  # GNOME purple 2\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot2.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot histogram of heights with custom bins - return n, bins, and patches and use it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "n, bins, patches = ax.hist(\n",
    "    data_height,\n",
    "    bins=15,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\"  # GNOME purple 2\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.bar_label(\n",
    "    patches,\n",
    "    fontsize=16,\n",
    "    color=\"#613583\",  # GNOME purple 5,\n",
    ")\n",
    "\n",
    "# set ticks\n",
    "ax.set_xticks(bins)\n",
    "ax.set_xticklabels([f\"{value:.1f}\" for value in bins])\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot3.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Normalized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "n, bins, patches = ax.hist(\n",
    "    data_height,\n",
    "    bins=10,\n",
    "    density=True,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\"  # GNOME purple 2\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.bar_label(\n",
    "    patches,\n",
    "    fontsize=16,\n",
    "    color=\"#613583\",  # GNOME purple 5\n",
    "    fmt=\"{:,.3f}\"\n",
    ")\n",
    "\n",
    "# set ticks\n",
    "ax.set_xticks(bins)\n",
    "ax.set_xticklabels([f\"{value:.1f}\" for value in bins])\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot4.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cummulative"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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22+bUU0/Nq6++usav9f4o+++/f1Vo9d///d9p3rx5ysvL07Zt25x//vk5/vjjc/DBB6/23saNG+fmm29Oq1at8vLLL2ePPfZIixYt0qxZsxx44IFp3rx5zjrrrCRJo0aNatx/0kkn5ec//3lKSkpyxRVXpFu3blXPb968efbaa69cdtllVQdbbwitWrXKPffck+233z5vvPFGBg0alBYtWqR169Zp2rRpOnXqlKFDh+bZZ59d6993SUlJRo0alY4dO+btt9/OQQcdlGbNmqVFixbp27dvZs+enfPPPz/J6n9Pn8aXv/zlqoCwQ4cOadeuXTp37pzOnTuv0+cAAGtPwAMAtWRVSLPttttW7Yj4OKuCoNGjR1d7PaakpKRaoLP33nt/5NdnJ8luu+2Wl156Kb/+9a+zxx57pHnz5pkzZ06aNm2a3r1757vf/W4eeOCB9O/f/xOu7H033nhjfvWrX2X77bdPgwYNUllZmT333DPXXHNNrrjiio+8d+edd85zzz2Xr3/969l8882zbNmybL755jnllFPyxBNPVJ0B06pVq9Xef+aZZ+a5557LkCFDss0222TlypVZsGBB2rVrlwMOOCDnnnvuejufZk223nrrPPPMM/nDH/6QffbZJ2VlZXnvvfdSWlqanXbaKUOGDMldd92VwYMHr/WcHTt2zNNPP53vfve76dixY1asWJFWrVrlm9/8Zp566qmqXVJr+j39p1q3bp37778/X/nKV9KmTZvMmDEjr7/+elVgCQBseCWVTscDAArm2GOPzahRo/KTn/wkZ599dm23U2edddZZ+cUvfpHjjjsuV199dW23AwCsR3bwAACF8tprr+XWW29N8u+zfqhp9uzZ+eMf/5jE7wkANgYCHgCgzrnjjjvy3//935k4cWLV4c9LlizJHXfckX333TeLFi1Knz59sueee9Zyp7Xr73//e0466aRMmDCh6kyh5cuXZ9y4cdlnn33y9ttvp3Pnzmt1xhMAUGxe0QIA6pwrrrgi3/zmN5Mk9erVS6tWrTJ37twsX748SdKpU6fcd9992WqrrWqzzVr3t7/9rdrunLKysixYsCBLly5NkpSXl2fMmDHZfffda6tFAGADEfAAAHXOlClTcsUVV2TcuHF5/fXXM3PmzDRu3Dhbb711DjnkkHzve99b5wcHF9HMmTPzP//zP/nrX/+a1157LdOnT09paWk6d+6cAQMG5NRTT/3Yw7YBgM8GAQ8AAABAwTmDBwAAAKDgBDwAAAAABSfgAQAAACg4Ac9aGjBgQG23AAAAALBaAp61NHPmzNpuAQAAAGC1BDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKrrS2GwAAAADWnwn3vZi/3zsxU158K3MrFqa8bcvsus92+dLX9kyTZo2q6hbMXZSbLrovzzzwcpYuWZ6tdmyfo07ePx223qzafMuWLM9t/zM+j415IQvnL07Hbdrmqyfum269OlWrW7myMmOufTTjb3s6782an807bppDTuiX3vtuv0HWvbGxgwcAAAA+w8Ze93hK6pXkK8P2ySkXHpV9Dt8199/6VH5z0p+zcmVlkqSysjIXnnpjXnj81Rz9gwPynV9/NSuWr8y53/5TZr87t9p8V/3iL3ng9mdy2NC98r3fDMomrZvngu9dnzf++U61utsuG587Ln8wXziid07+3VHZasf2uXT4rfnHI69ssLVvTOzgAQAAYL2a/e7cjLn20Ux58e28+a93s3TJ8px7+4lpvUWranUzplXkpovvy6QnJmfF8pXp2n2LHHHSF9Jlhy2q1c2bszA3X3xfnn3oX1myaGk6bL1Zvjykf3r03apa3a+/dW1efvqNGv0cefIXs/9Rn1vn66yrvvub/0rLsmZVn7v16pRmLZvkjz8dnZefmpLtd+uSZx/8Z155bmpO+8PgbN+7c5Jkqx3b50eH/T5j/vRYjvnBAUmSN/75bh6/Z2K+ftbB6Tdw56r5zjzystz+Pw/ku78ZlCSZO3tB7rnu8Rx03B4ZMLhvkmT73p0z/c2K3HLJuOy059Yb7hewkbCDBwAAgPVq+tTZefK+F9O0ZeNss3PH1dbMn7MwI4Zcm2mvzshxww/Kt875cpLk3GGj8tbkmVV1y5Yuz3nDRuX5x17NESftm+/8+qspb9syF55yY156akqNeTtsvVnO+OPXqv187ovd18s666oPhjurrArNKmbMS5I88+A/06pNi6pwJ0maNm+cnp/fJs8++HLV2LMP/TP1S+tl9w/8DuuX1svn9u+eFx5/LcuWLk+SvPD4q1m+bEX6Dtix2nP7HNgjU1+ZnhnTKtbZ+nifgAcAAID1attdOuV3Y0/Oyb87Krt9YfXnr9x/61OZO3t+vv/bQdn9i92zc79t870LBqVR4wa5feQDVXUT7nsxU1+ZnqE/Pyz9Bu6cnfbYOsNGHJ52XVrn5ovH1Zi3cbOG2WrHDtV+NmndfL2ttShefvr1JEm7zq2TJG9Nnpn2XdvUqGvftU1mvTM3ixcufb/utRlpvUWrNGrcoFrdFl3aZPmyFZn+5vvBzbTXZqa0Yf1stmVZjflWPY91S8ADAADAelWvXsnH1rz6wrS03bI8m3Uorxpr1KRhttl5y/zj4X9lxfKVVXUNG5Vmu107V9WVlJSk++e6ZvKkt1Ixfe6Hp+ZDKqbPze0jH8gOu3ep2smz4L1FadaycY3aZi2bJEkWzlv0ft3cRVVj1eo2aVx1fdWfTZs3TklJ9X/2q+5dVce64wweAAAAal29+vVSv7R+jfEGDepn6ZLlmT6tIu06bZp69UpWW1fa4P2xaa/OSNlmLavG33j53Xxnn/OydPGytOvSOvsN2i17HbrL+ltIHbd44dJc9IObU69+vXzjrIG13Q7rkIAHAACAWrd5x00z6e+vZf6chWneqmmS979m+7VJbyV5f4dJkmzeadMsWrAkb02emS26tK66/9XnpyZJ5n9gZ8i2u3RMnwE9snnHTbNw3uI8evfzufqcu/LezPkZeHy/DbW0OmPp4mW56NQbM/Otivzosv+X8rb/DsKatmycBXMX17hn1U6bpi2aVP058+33ata99/69q3boNGvROAvnL05lZWW1XTyr5lvdLiA+Ha9oAQAAUOv2PrxXVlZW5oqfjs70qbMzZ+a8/Pk392TmW3OSJCX/95pXnwN6pHmrpvnjT0dn6ivTM2/Owtx51cP557Pvf1vWB18H+/LQvdP/sF7p1qtTdunfLd/59VezS/9uufPqR6rOlNlYLF++In8Yfmsmv/h2vv/bI9Nh682qXW/ftU3emjyjxn1vTZ6ZTTdvmcZNG/5fXevMfGtOlixe9qG6GSlt8O8zd7bo2ibLl67I9KkVNeZLUi2cY93YoAHPLbfcksMPPzydOnVKkyZN0q1btwwfPjzz5s2rVldRUZETTjghrVu3TrNmzbLffvvl+eefrzHf4sWLc9ppp6Vdu3Zp0qRJ+vbtmwcffLBG3cqVKzNixIh07tw5jRs3Ts+ePXPrrbeut3UCAADwyWzWvixDfnZYprz4dk7/yh9yykEX5tXnp1Z9nXmr/zsYuWmLxjnx11/NvDkL8+OjR+Z7+1+Qh//yXA49Ya8kySabfvQByp/bv3uWLVmeqa9MX78LqkNWrqzMyLNuz4sTpuSkc4/IVjt2qFGzc79tUzF9XtXhy0myaP6SPPvQv7Jzv22rxnr22zYrlq/MhL9NqhpbsXxlnvzbpHT/XNc0aPj+i0I79t0q9Uvr5fGxL1R7zmNjnk/7rdqkTfvqhy/z6W3QV7TOP//8dOzYMb/85S/ToUOHPPPMMzn77LNz//3359FHH029evVSWVmZgQMHZsqUKbn44otTVlaWESNGZJ999smzzz6bDh3+/S/i8ccfn7vuuivnnXdeunbtmksuuSQHHHBAHnvssey8885VdWeddVbOP//8nHPOOdl1111zww035Igjjsidd96Zgw46aEP+CgAAAFiD3vtun179u+WdN2antEG9bNahPNf+6u6Ut22ZTTffpKpu21065te3fSfT36zIypUr07bjphn7p8fSsFFpOm/fbq2eVfLx5z5/Zow6d0wm3PdiDv76nmnUpEHV62xJUrZZy5S3bZmd99o2W+3YISN/fHv+67v7pVmLxrnrmkeSVObA/9e3qr5Tt82z+xd3yPW//WtWLF+Z1lu0yv3/+1RmvDUnQ352WFVdy/Jm2f/oPrnrmkfSuGnDdNpu8zzx10l5acKUnHT+oA24+o1HSWVlZeWGetiMGTPSpk31r1279tprc9xxx+W+++7LvvvumzvuuCOHHXZYxo0bl3322SdJ8t5776VLly4ZPHhwLrrooiTJc889l5133jlXXnllvv71rydJli9fnu7du6dbt24ZPXp0kmT69OnZcsstc/rpp+enP/1p1XO/8IUvZMaMGfnHP/6xVr337t07EyZM+NS/AwAAgI3Zg7c/k6t/eVfOvf3EtN6i1UfWVsyYlx8f9T8ZMLhvvvS1PddYt3jh0pw9+PJsv1vnHDf8Sx8550U/uCmT/v5aLrz3lDRq0vA/WULhnHboxZm1mnNzkuSQE/rlsCH9kyTz31uUmy76W5554OUsW7I8W+3YIYO+/8V03LZttXuWLl6W/710fB6/54UsnL84W27TNkecuG+1bzZLkpUrVuauqx/Jg3c8k/dmLcjmnTbNIcf3S+8vbL9e1rmx26A7eD4c7iTJbrvtliSZNm1akmT06NHZYostqsKdJNlkk00ycODA3HHHHVUBz+jRo9OgQYMMGvTv5K+0tDRHHnlkfvWrX2XJkiVp1KhR7rnnnixdujSDBw+u9tzBgwfnG9/4RiZPnpwuXbqs87UCAAB1w+x352bMtY9myotv581/vZulS5avNlyYMa0iN118XyY9MTkrlq9M1+5b5IiTvlD1NdIfVDF9bm77nwfyj0deycJ5i9OqdfPsvn/3fPU7+yZJXnpqSs799qg19nTGH7+22tdkPssm3PdikmTKS28nSZ5/9NW0KGuaFmVN061XpyxfviI3X3RfuvXqlCbNGmbaazNz1zWPZIsubXLAMX2qzXXLJePSebt2ad6qSaa/WZExox5L/dJ6OXzYvlU1/3zmjdx97aPptXe3tG7XKosWLMkjd/0jzz74z3z1O/tuNOFOkpx3x0lrVdd8kybvf7PWx3y7VsPGDXLkyV/MkSd/8SPr6tWvl4HH99soD7SuDbX+LVoPPPBAkmT77d9P8CZOnJgePXrUqOvevXuuvfbazJ8/P82bN8/EiRPTpUuXNG3atEbd0qVL88orr6R79+6ZOHFiGjVqlK233rpGXZJMmjRJwAMAAJ9h06fOzpP3vZhO222ebXbumIl/f61Gzfw5CzNiyLVp3LRhjht+UBo2bpB7//z3nDtsVM666hvVDoSd+dac/PKb16T1Fpvk6FMPyCabNsvMt+bk3Q8cJtupW7uc8cev1XjOVb+4MwvmLl5taPRZ94fh1c9B/dO5Y5Ik3Xp1zI8u+38pSUnefXN2/n7vxCyctzhlm7VIv4E986Wvf77qK9BXmTt7Qa7/7b2ZO3tBWpY3S6/+3XLokP5pvsm/v5lpk9bNs3JlZW4f+WDmz1mY+qX10mHrthny88PS54Ca/5sTiq5WA55p06blxz/+cfbbb7/07t07STJ79ux07ty5Rm15eXmS9w9gbt68eWbPnp2yspqHMq2qmz17dtWfrVq1qva1bKurAwAAPpu23aVTfjf25CTvvx60uoDn/lufytzZ83P6/3w7m3V4/38rbN+7c3705Uty+8gHMmzE4VW11/7q7pS1aZEfXnpsSkvfDx669epUbb4mzRvV2KEz8+05eXvKzBxwTJ/Uq7/xfaHxlU+c+ZHX65fWy/d/e+RazfWNj9lhkiRttyzPKRcetVbzwWdBrQU88+fPz6GHHprS0tJcddVVtdXGRxo5cmRGjhyZ5P3zgwAAgOL54Ndmr8mrL0xL2y3Lq8KdJGnUpGG22XnL/OPhf2XF8pWpX1ov06fOzguPv5YTzj6kKtxZW4/d/XwqK5M9vrTTJ14Dnx2nHnRhKmbO+/hC1ouy1i3ym7u/V9ttrBe1EvAsWrQoAwcOzGuvvZYHHnig2jdjlZWVpaKiosY9q3barNq1U1ZWltdff32Ndat26JSVlWXOnDmprKystovnw3WrM2TIkAwZMiRJqnYYAQAAnz316tdL/dUENg0a1M/SJcszfVpF2nXaNP967v1vH2rYqEHOP/G6/POZN9KwcYP0/Pw2OerkL6Z5q6Y15ljl0bufT6ftNk+HrTZbb+ug7quYOS/H9RhQ221stK55YWxtt7DebPCAZ9myZfnqV7+aCRMm5K9//Wt23HHHate7d++ee++9t8Z9kyZNSseOHdO8efOquttuuy0LFy6sdg7PpEmT0rBhw6ozd7p3754lS5bk1VdfrXYOz6RJk5IkO+ywwzpfIwAAUCybd9w0k/7+WubPWVgV0qxcWZnXJr2VJFnw3qIkyZz/23lx5S/+kr4H7pgvHbdH3p1akVsvuT9vTZ6Zs67+xmp3DL3yj6l5983ZOerU/TfQilbP7hH47NqgAc/KlStzzDHHZNy4cbnzzjvTp0+fGjWHHHJIrrrqqjzwwAPp3//9r2qbO3du/vKXv+Too4+uqhs4cGB+8pOf5Oabb85xxx2X5P2vSb/xxhuz//77p1GjRkmSAQMGpEGDBrnuuuvyk5/8pOr+UaNGpUePHg5YBgAAsvfhvfK3m57IFT8dnaNP3T8NGzfInVc9kplvzUmSlPxfaFO5sjJJsl2vTjn2hwcmSbbfrUuaNm+Uy864LS88/mp22mPrGvM/etc/Ur+0Xq0f7mv3SO37LO8goXZt0IDnO9/5Tm6++eacccYZadasWR5//PGqax06dEiHDh1yyCGHpG/fvhk8eHDOO++8lJWVZcSIEamsrMwPf/jDqvpddtklgwYNyve///0sW7YsXbp0yaWXXprJkyfnuuuuq6rbbLPNcsopp2TEiBFp0aJFevXqlRtvvDHjxo3L6NGjN+TyAQCAOmqz9mUZ8rPDMurcsTn9K39IknTabvPsf9TnMnbU42nV+v03CVZ9S9MOu3etdn/3z73/+Y2X36kR8CxbujxP3jcpO+25TVp8xCtcAJ/GBg14xox5/2vwzjnnnJxzzjnVrv3kJz/J2WefnXr16uXOO+/MD37wgwwbNiyLFy9O3759c//992fLLbesds9VV12VM844I2eeeWbmzJmTnj17ZuzYsenVq1e1unPOOSfNmzfPhRdemHfeeSfdunXLTTfdlIMPPnj9LhgAACiM3vtun179u+WdN2antEG9bNahPNf+6u6Ut22ZTTffJEmyRdc2HzlHyWpez3r2wX9mwdzF2dPhysB6tEEDnilTpqxVXXl5ea688spceeWVH1nXpEmTXHDBBbngggs+sq5+/fo588wzc+aZH/21fAAAwMatXv162aJL6yRJxYx5efJvkzJgcN+q61v16JBNNm2eFx5/NfsN2q1q/PnHXk2SdNl+ixpzPnLXP9K8VdPs9Pmar24BrCu19jXpAAAAG8qE+15Mkkx56e0kyfOPvpoWZU3ToqxpuvXqlOXLV+Tmi+5Lt16d0qRZw0x7bWbuuuaRbNGlTQ445t9nh9YvrZevfmef/PFnf8m1I+5Or326ZfrUivzvpeOz3a6dsv1unas9d+7sBZn4+GvZ+/BdP/HXqgN8EgIeAADgM+8Pw2+t9vlP575/fES3Xh3zo8v+X0pSknffnJ2/3zsxC+ctTtlmLdJvYM986eufT2mD6sHMngf3TEm9koy59rE8fOdzadaySfoO6JHDv7NvSkqqv6L1+NgXsmLFSq9nAeudgAcAAPjMu/KJjz6uoX5pvXz/t0eu9Xx7HLRT9jjo40Ob/Y/+XPY/+nNrPS/Af6pebTcAAAAAwKcj4AEAAAAoOK9oAQAAG8SpB12YipnzarsNgM8kAQ8AALBBVMycl+N6DKjtNjZq17wwtrZbANYTr2gBAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwpbXdAAAAfJbNfnduxlz7aKa8+Hbe/Ne7Wbpkec69/cS03qJVtbpZ77yX2y4bn5eeej3z5ixM+WYts9t+2+dLX9szjZo0rKp75M7n8uxD/8qUF9/KrHfmZs8v7ZTjf3JIjefePvKBjL7ioRrju+y1bU46/7/W+ToBqF0CHgAAWI+mT52dJ+97MZ222zzb7NwxE//+Wo2aJYuW5vzvXJcVy1fky0P7p3zzTTJl0lu5/fIH8+6bFfn2L79SVfvY2Bcyr2Jhdti9aybc9+LHPn/45celXr2Sqs/NWjZZNwsDoE4R8AAAwHq07S6d8ruxJydJHrz9mdUGPP967s28++bsnHLRUenRZ6skyfa9O2f+3MW557rHsmTxsjRq3CBJcspFR1cFNi88/urHPr9r9/apX+pkBoDPOv9JDwAA69EHd8+syfJlK5MkTZo1qjbetEWjVK6sTCorP9F8AGx87OABAIBa1n33Lmm7ZXlu/v24HPujA7Pp5ptk8sRp+dsNT2bvr+xa7QyeT+oHAy/K3IoFKd+sRXb/Yvcc+s290vD/dgMB8Nkh4AEAgFrWoFFphl9+XC750S0568j/qRrf69Cdc8xpA/6jOdtuWZ6vfmffdOzWNiUlJZn499dy7/V/z+svv5Mf/P6YddU6AHWEgAcAAGrZsiXLc9kZ/5u5FQvyzZ8emvK2LTN50lsZ/ceHUq9+vfy/0w/6xHP2PXDHap+7f65ryjZrmesvuDcTn3gt3Xfvuq7aB6AOcAYPAADUsgdHP5uXnno9J//uyPQ9cMd069UpAwb3zaDv7Zfx//t03vjnu+vkOZ/bv3uSZMqkt9fJfADUHQIeAACoZdNemZ5mLRtnsw7l1ca77NA+SfL2lJnr9oHOaQb4zBHwAABALWu5abMsmLs47745u9r4axOnJUnK2rRYJ895fOwLSZKuO2yxTuYDoO5wBg8AAKxnE+57MUky5aX3X416/tFX06KsaVqUNU23Xp3y+YN75t7r/57fff+GHPz1PVO++SaZ8uLb+cuVD6XTdu2ydc8tq+aa9tqMvD35/R09Sxcvz6x33quaf9teHdOyrFmS5OzBl2ePg3bK5p02TUqSSX+fnPtuejI9+m6V7XfrsiGXD8AGIOABAID17A/Db632+U/njkmSdOvVMT+67P+l9RatcsYfv547Ln8w/3vZ+Mx/b1HKN2uZ/of1ysFf3zP16v37naon/zYpo694qOrzS0+9npeeej1J8sNLB6flru8HPJt32jT33fxk3ps5PysrK9OmfVkGntAvBx7bd30vF4BaIOABAID17MonzvzYmvZd22TYiMM/tu6wIf1z2JD+H1v3rXO+sla9AfDZ4AweAAAAgIKzgwcAgI3CqQddmIqZ82q7DQBYLwQ8AABsFCpmzstxPQbUdhsbtWteGFvbLQB8ZnlFCwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABTcBg94pk6dmpNOOil9+/ZN06ZNU1JSkilTplSrOfvss1NSUrLan8aNG1er7dy582rrbr/99hrPvvzyy7PddtulUaNG6datWy677LL1uFIAAACADaN0Qz/wlVdeyU033ZRdd901/fr1y7333luj5oQTTsiAAQOqjS1YsCADBgzIIYccUqP+gAMOyNlnn11trFu3btU+X3755Rk6dGiGDx+e/fbbL/fdd1+GDRuWysrKfPvb3/70CwMAAACoJRs84Nlrr73y7rvvJkmuuOKK1QY8HTp0SIcOHaqN/elPf8ry5ctz3HHH1ahv3bp1+vTps8ZnLl++PGeccUaOPfbYnHPOOUmSffbZJ2+99VbOOuusnHDCCWnQoMGnWRYAAABArdngr2jVq/efPfKaa65J27Ztc8ABB3ziex977LHMmDEjgwcPrjZ+7LHHZtasWXn44Yf/o54AAAAA6oJCHLL85ptv5v77788xxxyT0tKam47+8pe/pGnTpmnUqFH69OlT4/ydiRMnJkl69OhRbbx79+5JkkmTJq2fxgEAAAA2gEIEPKNGjcrKlStX+3rWwIEDc/HFF+eee+7Jddddl8aNG+fLX/5yRo0aVVUze/bsJElZWVm1e8vLy6tdBwAAACiiDX4Gz3/i2muvzS677JKddtqpxrWLL7642ucvf/nL6dOnT4YPH17jlaxPauTIkRk5cmSSZMaMGZ9qLgAAAID1pc7v4HniiSfy0ksvrXb3zurUr18/RxxxRKZOnZq33347yb937lRUVFSrXbVzZ9VOng8bMmRIJkyYkAkTJqRNmzb/6RIAAAAA1qs6H/Bcc801adCgQY4++uhPfG9JSUmSf5+1s+osnlVWnb2zww47fMouAQAAAGpPnQ54li5dmhtuuCEHHnjgWu+gWb58eW688cZ07Ngxm2++eZKkb9++ad26da677rpqtaNGjUp5eXn23HPPdd47AAAAwIZSK2fw3HLLLUmSp556KkkyZsyYtGnTJm3atEn//v2r6u68887Mnj17ja9nXX/99bnjjjty0EEHZcstt8y7776bSy65JE8//XSuv/76qroGDRrk5z//eYYNG5b27dtnv/32y7hx43LllVfm4osvTsOGDdfjagEAAADWr1oJeI444ohqn4cNG5Yk6d+/f8aPH181fs0116S8vDwHH3zwaufp0qVLpk+fntNOOy2zZ89Os2bN0rt374wdOzYHHHBAtdpvfetbKSkpyW9+85ucd9556dixY37/+99XPRsAAACgqGol4KmsrFyrujvuuOMjr/fp0yfjxo1b6+cOHTo0Q4cOXet6AAAAgCKo02fwAAAAAPDxBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgILb4AHP1KlTc9JJJ6Vv375p2rRpSkpKMmXKlBp1JSUlq/159tlnq9WtXLkyI0aMSOfOndO4ceP07Nkzt95662qfffnll2e77bZLo0aN0q1bt1x22WXrYYUAAAAAG9YGD3heeeWV3HTTTSkrK0u/fv0+svZrX/taHnvssWo/2267bbWas846K2effXZOPPHEjBkzJn369MkRRxyRu+++u1rd5ZdfnqFDh+bwww/P2LFjc8QRR2TYsGG59NJL1/kaAQAAADak0g39wL322ivvvvtukuSKK67Ivffeu8ba9u3bp0+fPmu8Pn369Jx//vk5/fTT84Mf/CBJss8+++SVV17J6aefnoMOOihJsnz58pxxxhk59thjc84551TVvfXWWznrrLNywgknpEGDButqiQAAAAAb1AbfwVOv3rp75D333JOlS5dm8ODB1cYHDx6c559/PpMnT06SPPbYY5kxY0aNumOPPTazZs3Kww8/vM56AgAAANjQ6vQhy5deemkaNWqUpk2bZt99981DDz1U7frEiRPTqFGjbL311tXGu3fvniSZNGlSVV2S9OjR4yPrAAAAAIqozgY8gwcPzh/+8If87W9/y8iRIzNr1qzsu+++GT9+fFXN7Nmz06pVq5SUlFS7t7y8vOr6B/8sKyv7yLoPGzlyZHr37p3evXtnxowZ62RdAAAAAOvaBj+DZ2396U9/qvp7v379cuihh6ZHjx4588wzN9grVUOGDMmQIUOSJL17994gzwQAAAD4pOrsDp4Pa9GiRb70pS/lySefrBorKyvLnDlzUllZWa121Y6cVTt0Vu3cqaio+Mg6AAAAgCIqTMCzygdfx+revXuWLFmSV199tVrNqjN1dthhh6q65N9n8aypDgAAAKCIChPwzJ07N3feeWd23333qrEBAwakQYMGue6666rVjho1Kj169EiXLl2SJH379k3r1q1XW1deXp4999xz/S8AAAAAYD2plTN4brnlliTJU089lSQZM2ZM2rRpkzZt2qR///45//zz8/LLL2efffbJFltskddffz3nn39+3nnnnWohzWabbZZTTjklI0aMSIsWLdKrV6/ceOONGTduXEaPHl1V16BBg/z85z/PsGHD0r59++y3334ZN25crrzyylx88cVp2LDhhv0FAAAAAKxDtRLwHHHEEdU+Dxs2LEnSv3//jB8/Pt26dcttt92W2267Le+9915atmyZPffcM3/84x+r7eBJknPOOSfNmzfPhRdemHfeeSfdunXLTTfdlIMPPrha3be+9a2UlJTkN7/5Tc4777x07Ngxv//976ueDQAAAFBUtRLwfPhQ5A8bOHBgBg4cuFZz1a9fP2eeeWbOPPPMj60dOnRohg4dulbzAgAAABRFYc7gAQAAAGD1BDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwpbXdAAAA69fsd+dmzLWPZsqLb+fNf72bpUuW59zbT0zrLVqt8Z67rnkkt15yf7bu2SH/ffnXql1bubIyY659NONvezrvzZqfzTtumkNO6Jfe+25fY54Hbn8691z398x8a042bbdJ9j/qc9nn8F3X8QoBADt4AAA+46ZPnZ0n73sxTVs2zjY7d/z4+mkVufPKh9OyvNlqr9922fjccfmD+cIRvXPy747KVju2z6XDb80/HnmlWt0Dtz+da0fcnV332S4nX3hUdvvC9hl17pjcf8tT62RdAMC/2cEDAPAZt+0unfK7sScnSR68/ZlM/PtrH1n/p1+NSZ8BPfLO67OyYsXKatfmzl6Qe657PAcdt0cGDO6bJNm+d+dMf7Mit1wyLjvtuXWSZMXylfnfS8en74E75vBh+1TVzZk5P7f9z/j0O2znlJbWX9dLBYCNlh08AACfcfXqlax17eNjX8jrL7+Tw4ftu9rrLzz+apYvW5G+A3asNt7nwB6Z+sr0zJhWkSR59fmpmVexMH0PrF7X98AdM/+9RfnXs29+wlUAAB9FwAMAQJJkwdxFueF3f80RJ+2b5ps0WW3NtNdmprRh/Wy2ZVm18fZd2yRJ3po88//qZrw/vlWbj6wDANYNAQ8AAEmSmy66L223LM/nD+65xpoFcxelafPGKSmpviuoWcsmVdc/+GezFk0+sg4AWDcEPAAA5J/PvJFH7/5Hjj39wBrhDQBQ9wl4AADINb+6O/0O2Tnlm7XMwnmLs3De4qxYsTKVKyqzcN7iLFu6PEnSrEXjLJy/OJWVldXur9qx8387dFbt3Fkwb9FH1gEA64Zv0QIAIG9Pnpm3J8/M+P99usa1E79wfo48+YvZ/6jPZYuubbJ86YpMn1qRtluWV9WsOlNniy6t3/+z6/t/TnttRlq1bvGBuhnV6gCAdUPAAwBAfnjp4Bpj11/w16xcuTLH/OCAbNbh/TBnx75bpX5pvTw+9oUc+s29qmofG/N82m/VJm3av3/48lY7dUjzVk3z+NgX0n33rh+oeyHNWjbJNj23XM8rAoCNi4AHAGAjMOG+F5MkU156O0ny/KOvpkVZ07Qoa5puvTplu10717inaYtGWbFiZbVrLcubZf+j++Suax5J46YN02m7zfPEXyflpQlTctL5g6rqSkvr58tD+2fUuWNS1qZFdti9S16cMCUP/+XZHP2DASltUH+9rhcANjYCHgCAjcAfht9a7fOfzh2TJOnWq2N+dNn/+0RzHf7tvdO4SYP87cYn8t6sBdm806b59i8Pz879tqlWt8/hu6akJLnnur9n7KjHU755yxxz2oDs+9Xen24xAEANAh4AgI3AlU+c+YnvWVPwU69+vQw8vl8GHt/vY+fY+yu7Zu+v7PqJnw0AfDK+RQsAAACg4AQ8AAAAAAXnFS0AgA3k1IMuTMXMebXdBgDwGSTgAQDYQCpmzstxPQbUdhsbrWteGFvbLQDAeuMVLQAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKboMHPFOnTs1JJ52Uvn37pmnTpikpKcmUKVOq1UyYMCFDhgzJdtttl6ZNm6Zjx4455phjMnny5Brzde7cOSUlJTV+br/99hq1l19+ebbbbrs0atQo3bp1y2WXXbaeVgkAAACw4ZRu6Ae+8soruemmm7LrrrumX79+uffee2vU3HDDDZk4cWK++93vpnv37pk2bVp+/vOfp3fv3nn22Wez5ZZbVqs/4IADcvbZZ1cb69atW7XPl19+eYYOHZrhw4dnv/32y3333Zdhw4alsrIy3/72t9f5OgEAAAA2lA0e8Oy111559913kyRXXHHFagOeH/3oR2nTpk21sT333DNdunTJ5Zdfnp/97GfVrrVu3Tp9+vRZ4zOXL1+eM844I8cee2zOOeecJMk+++yTt956K2eddVZOOOGENGjQ4NMuDQAAAKBWbPBXtOrV+/hHfjjcSZJOnTqlTZs2mTZt2id+5mOPPZYZM2Zk8ODB1caPPfbYzJo1Kw8//PAnnhMAAACgrijMIcsvvvhipk+fnu23377Gtb/85S9p2rRpGjVqlD59+tQ4f2fixIlJkh49elQb7969e5Jk0qRJ66dpAAAAgA2gEAHP8uXL861vfStt2rTJ8ccfX+3awIEDc/HFF+eee+7Jddddl8aNG+fLX/5yRo0aVVUze/bsJElZWVm1e8vLy6td/7CRI0emd+/e6d27d2bMmLEulwQAAACwzmzwM3j+EyeeeGIeffTR3HXXXTVCmosvvrja5y9/+cvp06dPhg8fXuOVrE9qyJAhGTJkSJKkd+/en2ouAAAAgPWlzu/gOf300zNy5MhceeWV2X///T+2vn79+jniiCMyderUvP3220n+vXOnoqKiWu2qnTurdvIAAAAAFFGdDnjOOeec/PrXv85FF12UY4899hPfX1JSkuTfZ+2sOotnlVVn7+ywww6fslMAAACA2lNnA56LLrooZ555Zs4555yceOKJa33f8uXLc+ONN6Zjx47ZfPPNkyR9+/ZN69atc91111WrHTVqVMrLy7Pnnnuu094BAAAANqRaOYPnlltuSZI89dRTSZIxY8akTZs2adOmTfr3758bbrgh3//+9zNgwIDsu+++efzxx6vubdmyZdWOm+uvvz533HFHDjrooGy55ZZ59913c8kll+Tpp5/O9ddfX3VPgwYN8vOf/zzDhg1L+/bts99++2XcuHG58sorc/HFF6dhw4YbcPUAAAAA61atBDxHHHFEtc/Dhg1LkvTv3z/jx4/P2LFjU1lZmbFjx2bs2LHValfVJEmXLl0yffr0nHbaaZk9e3aaNWuW3r17Z+zYsTnggAOq3fetb30rJSUl+c1vfpPzzjsvHTt2zO9///uqZwMAAAAUVa0EPJWVlR95/eqrr87VV1/9sfP06dMn48aNW+vnDh06NEOHDl3regAAAIAiqLNn8AAAAACwdgQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACm6tA56uXbvmueeeW+21F154IV27dl1nTQEAAACw9tY64JkyZUqWLFmy2muLFy/O66+/vs6aAgAAAGDtfaJXtEpKSlY7PmHChLRq1Wpd9AMAAADAJ1T6URd/+9vf5re//W2S98OdgQMHpmHDhtVqFi1alNmzZ+fII49cf10CAAAAsEYfGfB07do1X/jCF5Ik11xzTXr37p02bdpUq2nUqFF22GGHnHDCCeuvSwAAAADW6CMDnkMPPTSHHnpo1ecf//jH6dKly3pvCgAAAIC195EBzwddddVV67MPAAAAAP5Dax3wJMlrr72Wm266KW+88UYWL15c7VpJSUn++Mc/rtPmAAAAAPh4ax3w3H777fmv//qvrFy5MptttlkaNWpU7fqavmELAAAAgPVrrQOes846K3vvvXeuu+66GgctAwAAAFB71jrgee211/Kb3/xGuAMAAABQx9Rb28Ltttsus2bNWp+9AAAAAPAfWOuA59xzz80vf/nLvPbaa+uzHwAAAAA+obV+Revss8/OrFmzsv3222ebbbZJeXl5teslJSV54IEH1nmDAAAAAHy0tQ546tevn27duq3PXgAAAAD4D6x1wDN+/Pj12AYAAAAA/6m1PoMHAAAAgLpprXfwPPjggx9bs9dee32qZgAAAAD45NY64Nl7771TUlLykTUrVqz41A0BAAAA8MmsdcBz//331xibNWtW7rzzzjzwwAP5/e9/v04bAwAAAGDtrHXA079//9WOf+UrX8nJJ5+cv/zlLznwwAPXWWMAAAAArJ11csjyl770pdx0003rYioAAAAAPqF1EvC8/PLLqVfPF3IBAAAA1Ia1fkXr2muvrTG2dOnSvPDCC/njH/+Yr3zlK+u0MQAAAADWzloHPF/72tdWO96oUaMMGjQoF1544brqCQAAAIBPYK0DnsmTJ9cYa9y4cdq2bbtOGwIAAADgk1nrgKdTp07rsw8AAAAA/kNrHfCscuedd+aBBx7I7NmzU15enr333jtf+tKX1kdvAAAAAKyFtQ545s2bl4MPPjgPPfRQSktLs+mmm2bWrFm54IIL0q9fv9x5551p3rz5+uwVAAAAgNVY6+82/+///u88/fTT+dOf/pRFixbl7bffzqJFi3Lttdfm6aefzn//93+vzz4BAAAAWIO1DnhuvfXW/OIXv8gxxxyT+vXrJ0nq16+fY445Jj//+c9z6623rrcmAQAAAFiztQ54Zs2alR122GG113bYYYfMmjVrnTUFAAAAwNpb64CnS5cuufPOO1d77e67706XLl3WWVMAAAAArL21DniGDh2aiy++OMcff3zGjRuXF198Mffff3+GDh2aiy66KN/61rfWap6pU6fmpJNOSt++fdO0adOUlJRkypQpNeoWL16c0047Le3atUuTJk3St2/fPPjggzXqVq5cmREjRqRz585p3LhxevbsucbXxS6//PJst912adSoUbp165bLLrtsbZcPAAAAUGetdcBz8skn5/TTT891112XL37xi+nRo0e+8IUv5Jprrsnpp5+e733ve2s1zyuvvJKbbropZWVl6dev3xrrjj/++Fx++eX52c9+ljvvvDPt2rXLAQcckGeffbZa3VlnnZWzzz47J554YsaMGZM+ffrkiCOOyN13312t7vLLL8/QoUNz+OGHZ+zYsTniiCMybNiwXHrppWv7KwAAAACok9b6a9KT5Je//GVOO+20PP7445k9e3bKy8vTp0+flJWVrfUce+21V959990kyRVXXJF77723Rs1zzz2XP//5z7nyyivz9a9/PUnSv3//dO/ePT/+8Y8zevToJMn06dNz/vnn5/TTT88PfvCDJMk+++yTV155JaeffnoOOuigJMny5ctzxhln5Nhjj80555xTVffWW2/lrLPOygknnJAGDRp8kl8FAAAAQJ2x1jt4fv3rX+ekk05KWVlZDjzwwBxzzDE58MADU1ZWlu9+97s577zz1u6B9T7+kaNHj06DBg0yaNCgqrHS0tIceeSRueeee7JkyZIkyT333JOlS5dm8ODB1e4fPHhwnn/++UyePDlJ8thjj2XGjBk16o499tjMmjUrDz/88Fr1DgAAAFAXrXXAc9VVV2WnnXZa7bWePXvmqquuWmdNTZw4MV26dEnTpk2rjXfv3j1Lly7NK6+8UlXXqFGjbL311jXqkmTSpElVdUnSo0ePj6wDAAAAKKK1DnjeeOONbLPNNqu9ttVWW+X1119fZ03Nnj17ta99lZeXV11f9WerVq1SUlLysXVJasz54ToAAACAIlrrM3iaNm2aadOmrfba1KlT06hRo3XWVF0xcuTIjBw5MkkyY8aMWu4GAAAAYPXWegdPv379ct5551Wdf7PKkiVL8pvf/OYjvxHrkyorK0tFRUWN8VU7bVbtvCkrK8ucOXNSWVn5sXVJasz54boPGzJkSCZMmJAJEyakTZs2/+lyAAAAANartd7Bc/bZZ2ePPfbItttum8GDB6d9+/aZNm1aRo0alVmzZuXqq69eZ0117949t912WxYuXFjtHJ5JkyalYcOGVWfudO/ePUuWLMmrr75a7RyeVWfq7LDDDlV1yftn8bRr126NdQAAAABFtNY7eHr27Jn7778/nTp1yq9//euceOKJ+fWvf50uXbpk/Pjx6dmz5zprauDAgVm2bFluvvnmqrHly5fnxhtvzP7771/1OtiAAQPSoEGDXHfdddXuHzVqVHr06JEuXbokSfr27ZvWrVuvtq68vDx77rnnOusdAAAAYENb6x08SbL77rvnwQcfzKJFi1JRUZGysrI0adLkEz/0lltuSZI89dRTSZIxY8akTZs2adOmTfr3759ddtklgwYNyve///0sW7YsXbp0yaWXXprJkydXC2k222yznHLKKRkxYkRatGiRXr165cYbb8y4ceMyevToqroGDRrk5z//eYYNG5b27dtnv/32y7hx43LllVfm4osvTsOGDT/xGgAAAADqik8U8KzSpEmT/yjYWeWII46o9nnYsGFJkv79+2f8+PFJ3v9a9jPOOCNnnnlm5syZk549e2bs2LHp1atXtXvPOeecNG/ePBdeeGHeeeeddOvWLTfddFMOPvjganXf+ta3UlJSkt/85jc577zz0rFjx/z+97+vejYAAABAUf1HAc+n9eFDkVenSZMmueCCC3LBBRd8ZF39+vVz5pln5swzz/zYOYcOHZqhQ4eudZ8AAAAARbDWZ/AAAAAAUDcJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgSmu7AQBg4/Lrb12bl59+Y7XXevTpmlMuOjpJ8sY/38ktvx+Xfz33ZkrqlWS7Xp0y6PtfTNsty6vdc+sfxmXKi29nyovvZMHcRfnGjwfm8wf3XO/rAACoSwQ8AMAGNfiHB2bxgiXVxl59flpu+N1fs/Ne2yZJ3n1jdkYMuTYdurbJkJ8dlhUrVmb0FQ/lV0OvzU9HfTMty5tV3fu3myak4zZt0/PzW+fRu5/foGsBAKgrBDwAwAbVvmubGmMP3P5MShvUz+5f7J4kufvaR1OvXklOvvCoNG3ROEnStXv7nH74JRk76vH813e/UHXvJeNOS716JXn3zdkCHgBgo+UMHgCgVi1ZvCwTxr2Ynv22SfNNmiRJXnthWrbasUNVuJMk5W1bpn3XzfL0Ay9Vu79evZIN2i8AQF0k4AEAatXT41/K4gVLs+eXdqoaK6lXktIG9WvUNmhYPzOmVmTZkuUbskUAgDpPwAMA1KpH73o+LcubZce+W1eNbd5p07z+0ttZvnxF1diiBUsy7bUZqaxMFsxbVButAgDUWQIeAKDWVMyYl0lPTk6fA3qkfum//8+S/Qbtlorp83LtiLtTMX1uZr49J1f+/C9ZsmhpkqSkxGtZAAAf5JBlAKDWPD7m+VSurMweH3g9K0m23bljBv9wQG695P48/JfnkiQ77N4lexy0Ux4f+0Ka/d9ZPQAAvE/AAwDUmkfu+ke23KZtOm7btsa1fb/aO/0O2TnT36xIk+YNU952k1zwvevTtfsWKS2teT4PAMDGzCtaAECtmDzprbw1eWa1w5U/rEHD0rTfqk3K226Sqa9Mz4tPTM7eh++6AbsEACgGO3gAgFrx6N3Pp379eukzoEeNa7PfnZv7b30qW+/UIaUN62fKi2/n7qsfTa99tkufA6rXv/z065lXsTDvzZqfJJny4ttp3KRhkqT3F7Zf/wsBAKgDBDwAwAa3fPmK/P3eienRd6u0LG9W43r90np5beK0PHDb01m8cGnadCjLwBP65YuDdq9Re/vIB/Ly029UfR5384SMu3lCkuTKJ85cf4sAAKhDBDwAwAZXWlo/F917yhqvb7Jp85x2yeC1mutHl/2/ddUWAEBhOYMHAAAAoOAEPAAAAAAF5xUtANhInHrQhamYOa+22wAAYD0Q8ADARqJi5rwc12NAbbexUbvmhbG13QIA8BnlFS0AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKrs4GPHvvvXdKSkpW+zNgwIAkyZQpU9ZYM2fOnGrzLV68OKeddlratWuXJk2apG/fvnnwwQdrYWUAAAAA61ZpbTewJn/4wx8yd+7camOPPfZYTjnllBxyyCHVxocPH15jrEWLFtU+H3/88bnrrrty3nnnpWvXrrnkkktywAEH5LHHHsvOO++8XtYAAAAAsCHU2YBnhx12qDF2+eWXp2HDhjnyyCOrjXft2jV9+vRZ41zPPfdc/vznP+fKK6/M17/+9SRJ//7907179/z4xz/O6NGj123zAAAAABtQnX1F68MWLlyYm2++OQMHDkx5efknunf06NFp0KBBBg0aVDVWWlqaI488Mvfcc0+WLFmyrtsFAAAA2GAKE/DcdtttmTdvXo477rga14YPH57S0tJssskmOeSQQ/L8889Xuz5x4sR06dIlTZs2rTbevXv3LF26NK+88sp67R0AAABgfaqzr2h92LXXXpvNNtssBx54YNVYo0aNMnTo0Oy///5p06ZNXnrppfzyl7/MHnvskSeeeCLbb799kmT27NkpKyurMeeqnUCzZ8/eMIsAAAAAWA8KEfC89dZb+dvf/pbvfe97KS39d8vt2rXLZZddVvW5X79+GTBgQLp3755zzjkno0aN+lTPHTlyZEaOHJkkmTFjxqeaCwAAAGB9KcQrWqNGjcrKlStX+3rWh2255Zb5/Oc/nyeffLJqrKysLBUVFTVqV+3cWdOZPkOGDMmECRMyYcKEtGnT5j/sHgAAAGD9KkTAc80116Rnz57p2bPnWt9TUlJS9ffu3btn8uTJWbhwYbWaSZMmpWHDhtl6663XWa8AAAAAG1qdD3gmTJiQSZMmrdXunSR544038vDDD2f33XevGhs4cGCWLVuWm2++uWps+fLlufHGG7P//vunUaNG67xvAAAAgA2lzp/Bc+2116a0tDTHHHNMjWunnnpqVq5cmb59+6ZNmzZ5+eWXM2LEiNSrVy9nnHFGVd0uu+ySQYMG5fvf/36WLVuWLl265NJLL83kyZNz3XXXbcjlAAAAAKxzdTrgWbZsWa6//voMGDAgm222WY3r3bt3z6WXXpqrr7468+fPz6abbpp99903P/nJT9KtW7dqtVdddVXOOOOMnHnmmZkzZ0569uyZsWPHplevXhtqOQAAAADrRZ0OeBo0aPCR3171jW98I9/4xjfWaq4mTZrkggsuyAUXXLCu2gMAAACoE+r8GTwAAAAAfDQBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4OpswDN+/PiUlJTU+GnVqlW1uoqKipxwwglp3bp1mjVrlv322y/PP/98jfkWL16c0047Le3atUuTJk3St2/fPPjggxtoNQAAAADrT2ltN/BxLrroouy2225Vn0tL/91yZWVlBg4cmClTpuTiiy9OWVlZRowYkX322SfPPvtsOnToUFV7/PHH56677sp5552Xrl275pJLLskBBxyQxx57LDvvvPOGXBIAAADAOlXnA57tt98+ffr0We210aNH55FHHsm4ceOyzz77JEn69u2bLl265Nxzz81FF12UJHnuuefy5z//OVdeeWW+/vWvJ0n69++f7t2758c//nFGjx69YRYDAAAAsB7U2Ve01sbo0aOzxRZbVIU7SbLJJptk4MCBueOOO6rVNWjQIIMGDaoaKy0tzZFHHpl77rknS5Ys2aB9AwAAAKxLdT7gOeaYY1K/fv1suummOfroo/PGG29UXZs4cWJ69OhR457u3bvnjTfeyPz586vqunTpkqZNm9aoW7p0aV555ZX1uwgAAACA9ajOvqK1ySab5NRTT03//v3TsmXLPPPMM/nlL3+Zvn375plnnslmm22W2bNnp3PnzjXuLS8vT/L+AczNmzfP7NmzU1ZWtsa62bNnr7aHkSNHZuTIkUmSGTNmrKOVAQAAAKxbdTbg2WWXXbLLLrtUfe7fv3/22muv7L777rnooovyi1/8Yr33MGTIkAwZMiRJ0rt37/X+PAAAAID/RJ1/ReuDevXqlW233TZPPvlkkqSsrCwVFRU16lbtyFm1a+fj6lbt5AEAAAAookIFPKuUlJQkef8MnYkTJ9a4PmnSpHTs2DHNmzevqps8eXIWLlxYo65hw4bZeuut13/TAAAAAOtJoQKeCRMm5OWXX87uu++eJDnkkEMybdq0PPDAA1U1c+fOzV/+8pcccsghVWMDBw7MsmXLcvPNN1eNLV++PDfeeGP233//NGrUaMMtAgAAAGAdq7Nn8BxzzDHp0qVLevXqlVatWuWZZ57JiBEj0r59+3z3u99N8n7A07dv3wwePDjnnXdeysrKMmLEiFRWVuaHP/xh1Vy77LJLBg0alO9///tZtmxZunTpkksvvTSTJ0/OddddV1tLBAAAAFgn6mzA06NHj1x//fW5+OKLs3Dhwmy++eb5yle+kp/+9Kdp3bp1kqRevXq5884784Mf/CDDhg3L4sWL07dv39x///3Zcsstq8131VVX5YwzzsiZZ56ZOXPmpGfPnhk7dmx69epVG8sDAAAAWGfqbMAzfPjwDB8+/GPrysvLc+WVV+bKK6/8yLomTZrkggsuyAUXXLCuWgQAAACoEwp1Bg8AAAAANQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIrre0GAGBDm3Dfi/n7vRMz5cW3MrdiYcrbtsyu+2yXL31tzzRp1qiq7o1/vpNbfj8u/3ruzZTUK8l2vTpl0Pe/mLZblleb7xu7/2K1zzl71AnpuO3m63UtAACQCHgA2AiNve7xlLdtma8M2yflm7XM6y+/kzsufzAvPfV6/vuKr6VevZK8+8bsjBhybTp0bZMhPzssK1aszOgrHsqvhl6bn476ZlqWN6s2554H75S9v9yr2ljbjptuyGUBALARE/AAsNH57m/+Ky3L/h3QdOvVKc1aNskffzo6Lz81Jdvv1iV3X/to6tUryckXHpWmLRonSbp2b5/TD78kY0c9nv/67heqzVnWpkW22rHDBl0HAACs4gweADY6Hwx3VumywxZJkooZ85Ikr70wLVvt2KEq3EmS8rYt077rZnn6gZc2TKMAALCW7OABgCQvP/16kqRd59ZJkpJ6JSltUL9GXYOG9fPGyxVZtmR5GjT693+N3n/r0xk76vHUq1eSrj3a57Ah/bPtLh03TPMAAGz0BDwAbPQqps/N7SMfyA67d6naybN5p03z6vNTs3z5ipSWvh/0LFqwJNNem5HKymTBvEVp1ahFkqTvgT3S8/PbpFXrFpn1znsZ86fHct6wUTn190dnu10719ayAADYiHhFC4CN2uKFS3PRD25Ovfr18o2zBlaN7zdot1RMn5drR9ydiulzM/PtObny53/JkkVLkyQlJSVVtd/86WHZ/Yvds+0uHdP3wB0z/PLj0qpN8/zvZeM39HIAANhICXgA2GgtXbwsF516Y2a+VZFTLzo65W1bVl3bdueOGfzDAXlq3Es59eCL8sNDf59F85dkj4N2SmmD+mm2SZM1ztukWaPstOc2mTLp7Q2xDAAA8IoWABun5ctX5A/Db83kF9/ODy4+Oh223qxGzb5f7Z1+h+yc6W9WpEnzhilvu0ku+N716dp9i6rXtj5SyceXAADAumAHDwAbnZUrKzPyrNvz4oQpOencIz7y680bNCxN+63apLztJpn6yvS8+MTk7H34rh85/6L5S/Lcw/9K1/87zwcAANY3O3gA2OiMOndMJtz3Yg7++p5p1KRBXn1+atW1ss1aprxty8x+d27uv/WpbL1Th5Q2rJ8pL76du69+NL322S59DuhRVT921GN55/VZ2W7XzmnVpnlmvf1exl73eN6bNT9DfnZYLawOAICNkYAHgI3O84+9miS586pHcudVj1S7dsgJ/XLYkP6pX1ovr02clgduezqLFy5Nmw5lGXhCv3xx0O7V6jfvtGmeHv9ynh7/chbNX5LGzRplm54d8vUzD07X7u032JoAANi4CXgA2Oicd8dJH1uzyabNc9olgz+2bud+22bnftuui7YAAOA/5gweAAAAgIIT8AAAAAAUnFe0ANggTj3owlTMnFfbbQAAwGeSgAeADaJi5rwc12NAbbexUbvmhbG13QIAAOuJV7QAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKrs4GPLfccksOP/zwdOrUKU2aNEm3bt0yfPjwzJs3r6pmypQpKSkpWe3PnDlzqs23ePHinHbaaWnXrl2aNGmSvn375sEHH9zAqwIAAABY90pru4E1Of/889OxY8f88pe/TIcOHfLMM8/k7LPPzv33359HH3009er9O5saPnx4DjnkkGr3t2jRotrn448/PnfddVfOO++8dO3aNZdcckkOOOCAPPbYY9l55503xJIAAAAA1os6G/D85S9/SZs2bao+9+/fP+Xl5TnuuOMyfvz47LvvvlXXunbtmj59+qxxrueeey5//vOfc+WVV+brX/961Xzdu3fPj3/844wePXr9LQQAAABgPauzr2h9MNxZZbfddkuSTJs27RPNNXr06DRo0CCDBg2qGistLc2RRx6Ze+65J0uWLPl0zQIAAADUojob8KzOAw88kCTZfvvtq40PHz48paWl2WSTTXLIIYfk+eefr3Z94sSJ6dKlS5o2bVptvHv37lm6dGleeeWV9ds4AAAAwHpUZ1/R+rBp06blxz/+cfbbb7/07t07SdKoUaMMHTo0+++/f9q0aZOXXnopv/zlL7PHHnvkiSeeqAqCZs+enbKyshpzlpeXV10HAAAAKKpCBDzz58/PoYcemtLS0lx11VVV4+3atctll11W9blfv34ZMGBAunfvnnPOOSejRo36VM8dOXJkRo4cmSSZMWPGp5oLAAAAYH2p869oLVq0KAMHDsxrr72We+65Jx06dPjI+i233DKf//zn8+STT1aNlZWVpaKiokbtqp07q3byfNiQIUMyYcKETJgwYbVnAgEAAADUBXU64Fm2bFm++tWvZsKECbn77ruz4447rvW9JSUlVX/v3r17Jk+enIULF1armTRpUho2bJitt956nfUMAAAAsKHV2YBn5cqVOeaYYzJu3LjcfvvtH/k16B/0xhtv5OGHH87uu+9eNTZw4MAsW7YsN998c9XY8uXLc+ONN2b//fdPo0aN1nn/AAAAABtKnT2D5zvf+U5uvvnmnHHGGWnWrFkef/zxqmsdOnRIhw4dcuqpp2blypXp27dv2rRpk5dffjkjRoxIvXr1csYZZ1TV77LLLhk0aFC+//3vZ9myZenSpUsuvfTSTJ48Odddd11tLA8AAABgnamzAc+YMWOSJOecc07OOeecatd+8pOf5Oyzz0737t1z6aWX5uqrr878+fOz6aabZt99981PfvKTdOvWrdo9V111Vc4444yceeaZmTNnTnr27JmxY8emV69eG2xNAAAAAOtDnQ14pkyZ8rE13/jGN/KNb3xjreZr0qRJLrjgglxwwQWfsjMAAACAuqXOnsEDAAAAwNoR8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHACHgAAAICCE/AAAAAAFJyABwAAAKDgBDwAAAAABSfgAQAAACg4AQ8AAABAwQl4AAAAAApOwAMAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBCXgAAAAACk7AAwAAAFBwAh4AAACAghPwAAAAABScgAcAAACg4AQ8AAAAAAUn4AEAAAAoOAEPAAAAQMEJeAAAAAAKTsADAAAAUHCltd0AAMmvv3VtXn76jdVe69Gna0656OgkyRv/fCe3/H5c/vXcmympV5LtenXKoO9/MW23LN+Q7QIAAHWMgAegDhj8wwOzeMGSamOvPj8tN/zur9l5r22TJO++MTsjhlybDl3bZMjPDsuKFSsz+oqH8quh1+ano76ZluXNaqN1AACgDhDwANQB7bu2qTH2wO3PpLRB/ez+xe5JkruvfTT16pXk5AuPStMWjZMkXbu3z+mHX5Kxox7Pf333Cxu0ZwAAoO5wBg9AHbRk8bJMGPdievbbJs03aZIkee2Fadlqxw5V4U6SlLdtmfZdN8vTD7xUW60CAAB1gIAHoA56evxLWbxgafb80k5VYyX1SlLaoH6N2gYN62fG1IosW7J8Q7YIAADUIQIegDro0bueT8vyZtmx79ZVY5t32jSvv/R2li9fUTW2aMGSTHttRiorkwXzFtVGqwAAQB0g4AGoYypmzMukJyenzwE9Ur/03/8xvd+g3VIxfV6uHXF3KqbPzcy35+TKn/8lSxYtTZKUlJTUVssAAEAtc8gyQB3z+JjnU7myMnt84PWsJNl2544Z/MMBufWS+/PwX55Lkuywe5fscdBOeXzsC2n2f2f1AAAAGx8BD0Ad88hd/8iW27RNx23b1ri271d7p98hO2f6mxVp0rxhyttukgu+d326dt8ipaU1z+cBAAA2Dl7RAqhDJk96K29NnlntcOUPa9CwNO23apPytptk6ivT8+ITk7P34btuwC4BAIC6xg4egDrk0bufT/369dJnQI8a12a/Ozf33/pUtt6pQ0ob1s+UF9/O3Vc/ml77bJc+B9SsBwAANh4CHoA6YvnyFfn7vRPTo+9WaVnerMb1+qX18trEaXngtqezeOHStOlQloEn9MsXB+1eC90CAAB1iYAHoI4oLa2fi+49ZY3XN9m0eU67ZPAG7AgAACgKZ/AAAAAAFJyABwAAAKDgvKIFbDROPejCVMycV9ttAAAArHMCHmCjUTFzXo7rMaC229hoXfPC2NpuAQAAPrO8ogUAAABQcAIeAAAAgIIT8AAAAAAUnIAHAAAAoOAEPAAAAAAFJ+ABAAAAKDgBDwAAAEDBldZ2A0DdMPvduRlz7aOZ8uLbefNf72bpkuU59/YT03qLVtXqvrH7L1Z7/9mjTkjHbTffAJ0CAADwYQIeIEkyfersPHnfi+m03ebZZueOmfj319ZYu+fBO2XvL/eqNta246bru0UAAADWQMADJEm23aVTfjf25CTJg7c/85EBT1mbFtlqxw4bqjUAAAA+hjN4gCRJvXoltd0CAAAA/yE7eKizXnjs1dx97aN5a/LMLJy3OC3KmmarHTvk0G/ulfZd29R2exu1+299OmNHPZ569UrStUf7HDakf7bdpWNttwUAALDREvBQZ82fuyidt2+Xfb/aOy3KmmbWO+/l7msezTnHX5Wf/XlIWrdrVdstbpT6HtgjPT+/TVq1bpFZ77yXMX96LOcNG5VTf390ttu1c223BwAAsFES8FBn9TmgR/oc0KPaWJfu7XPGEZdmwriXMuCYPrXU2cbtmz897P+3d+dhTV15H8C/kSUBNyKLoiUsCirgriNjVQT3DetY6tQNarVaR0vdWnEpCrTOTNXH1qm78xbBusxoXRiQ0RbGOoUq1NYFXKAqal0QtL64IjnvH76kDYEQkuiF5Pt5Hp7HnNx787u/H/dcPDn3Xq3Xnfv64YPXN2DP+gws3BQpSUxERERERETWjvfgoXqlUVMHAICNDX916wqHhnJ0fNkXl3KvSx0KERERERGR1eIMHqrz1OVqqNUCxdd/wT8/+xpNnRuh56AAqcOiyniPZiIiIiIiIslwgIfqvLg3/geXzz6bHeLmocT8tRPQpFlDiaOiCg9LH+PHoxfg499S6lCIiIiIiIisFgd4qM6bumwUHt5/jKJrd5C2LQsrZ21D9MYIuLR0kjo0i5P9VR4A4NL/D6id+rYAjZWOaKx0RNuunjiYlIkbl4vRrpsXnFwbofj6Lzi4LQu/FJfirdhXJIyciIiIiIjIunGAh+q8lt4uAIDWga3QsVcbzB+1BikJ32JS9DCJI7M8a6N3a71O/GsqAKBtVxXeXz8JLTyd8X3GOXyfcQ4PSx9D0VAO304v4Y3FI+AT0EqKkImIiIiIiAgc4KF6xrGxAm4vNcPNqyVSh2KR/n5ssd73O/fxQ+c+fi8oGiIiIiIiIjIUH0VE9covxaW4cfk23F5SSh0KERERERERUZ1hVTN4rly5gtmzZ+PQoUMQQmDAgAFYvXo1VCqV1KFRFdbM/wc827WARxs3KBrKcbOwGP/efgwNbBpg8LggqcOrtbnDPsGd2/8rdRhERERERERkgaxmgOfBgwcIDQ2FXC5HQkICZDIZFi9ejJCQEJw8eRING/KpTHVN68BWOP5VLtK2ZaG8rBzK5k3Qrpsnhke8XC9vsHzn9v8iInCI1GFYtYTTB6UOgYiIiIiI6LmwmgGeTZs24aeffsK5c+fQpk0bAEDHjh3h6+uLDRs2YM6cORJHSJUNi+iFYRG9pA6DiIiIiIiIqM6zmnvw7N+/H0FBQZrBHQDw9vbGyy+/jH379kkYGRERERERERGRaaxmgOfMmTMIDAzUaQ8ICEBubq4EERERERERERERmYfVXKJVUlICpVL3yUvNmjXDnTt3JIjoxeINfomIiIiIiIgsl9UM8Bhj48aN2LhxIwDg7Nmz6N69u8QRGa+oqAiurq5Sh2HVioqKcFK9V+owrBprIC3mX3qsgfRYA2kx/9JjDaTHGkiPNZBWUVERunffK3UYJnFxccHBg7oPkLGaAR6lUlnlTJ3qZvYAwFtvvYW33nrreYf2QnTv3h3Z2dlSh2HVWAPpsQbSYv6lxxpIjzWQFvMvPdZAeqyB9FgDaVly/q3mHjwBAQE4c+aMTntubi78/f0liIiIiIiIiIiIyDysZoAnLCwMWVlZ+OmnnzRtly5dwn//+1+EhYVJGBkRERERERERkWmsZoBn6tSp8PLywqhRo7Bv3z7s378fo0aNgoeHB6ZNmyZ1eM+dpVxqVp+xBtJjDaTF/EuPNZAeayAt5l96rIH0WAPpsQbSsuT8y4QQQuogXpTCwkLMnj0bhw4dghAC/fv3x+rVq+Hl5SV1aERERERERERERrOqAR4iIiIiIiIiIktkNZdo1SdXr17FrFmz8Pvf/x6Ojo6QyWS4dOmSznIymazKnx9++EFrudu3b2Py5MlwdXWFg4MDevbsibS0NINiKS8vR1xcHLy9vSGXy+Hr64vVq1ebvpN1nKE1AIC8vDyEh4fDxcUFDg4OaNu2LT755BPN++fPn0dUVBQ6duyIRo0awd3dHWFhYfjxxx8NisUaa2DO/AOAl5dXlcfK3r17a4zFGvMPmL8GpvRDALB371506dIFCoUCnp6eiI+PR3l5uSm7WOcZUoOlS5dWey5QKBSa5UzthwDWwNQaAKb1RYD11cDc+S8uLkZUVBR8fHzg4OAAb29vzJw5E0VFRTXGcvToUURGRiIwMBC2trZWM/vb0HNBYWEhIiIioFKp4ODgAD8/PyxevBj379/XWi4hIQFjxoyBp6cnZDIZIiMjDY7l9OnTmDZtGrp16wZ7e3vIZDIT965+MHcNfuvbb79FgwYNIJPJ8PTp0xpjscbjwJz5z8jIqLa/kslkyMrK0huLNeYfMLwGFy9exKuvvgonJyc0bNgQISEhVT4pS61WY/ny5fDy8oJCoUCnTp2we/fuGuO4d+8eYmNj0atXLzg7O8PJyQm9evUy+Bz+onCApw7Kz8/Hrl27oFQq0adPH73LRkZGIjMzU+vHz89P8/7jx48RGhqKgwcP4q9//Sv27NkDDw8PjBgxAhkZGTXGMmPGDMTHx+PNN99EcnIywsPDMW/ePMTHx5u6m3WaoTXIzs5Gz5498fjxY2zevBkpKSmYO3eu1h/c//73v5Geno6IiAgcOHAAa9euRVFREYKCgpCTk1NjLNZYA3Pmv8LgwYN1jpXg4OAaY7HG/APmrYGp/VBaWhrGjBmDHj16IDU1FVFRUYiPj8fChQvNsat1liE1mDJlis7v9eHDh2Fra6v1AAFT+yHWwPQaVDC2L7LGGpgz/0IIhIWF4YsvvsD8+fORmpqK+fPnY8eOHRg5ciRqmtD+1Vdf4ZtvvkFAQADat29v1v2sywypwf379zFgwAAcOXIEcXFxSElJwZQpU7By5UpMnjxZa9mkpCQUFBRg4MCBaNKkSa1iycnJQUpKClQqFbp37270PtU35q5BhbKyMkybNg3Nmzc3OBZrPA7Mmf+uXbvq9FeZmZnw9/dHixYt0KNHD72xWGP+AcNqUFxcjN69e+P06dPYsGEDduzYAQAICQlBXl6e1rJLlizB0qVLMXPmTKSmpiIoKAjh4eFISUnRG0dhYSHWrl2L4OBgJCUlYefOnfDz88Po0aPx2WefmWdnzUFQnVNeXq7596ZNmwQAcfHiRZ3lAIhFixbp3VZiYqIAINLT0zVtarVadOjQQfTo0UPvupcvXxYNGjQQMTExWu1/+tOfhEKhEMXFxTXuS31lSA3Ky8tF+/btxSuvvKJ3W0VFRUKtVmu13b17Vzg5OYmJEyfqXddaa2DO/AshhKenpxg/fnyt47DW/Ath3hqY0g8JIUTnzp1F3759tdqWLVsm7OzsxPXr12vemXrK0HNBZVu3bhUARHJysqbNlH5ICNZACNNrIITxfZEQ1lkDc+b/3LlzAoDYsGGD1rLr1q0TAMTZs2cNjmX8+PHC09PTsJ2o5wypQVpamgAg0tLStNrff/99YWNjI+7fv1/l9lq1aiUiIiKMimXRokXCWv4bY+4aVPjwww9FQECAWLhwoQAgysrKahWLtRwHzyv/FS5duiRkMpmYN29erWKxlvwLYVgN4uLihI2NjcjPz9e0lZaWCjc3NxEeHq5pu3nzprC3txcffPCB1vqhoaGiQ4cOeuMoLS2tspahoaHCw8OjNrv0XHEGTx3UoIH5ypKVlQUHBwf069dP0yaTyTBo0CAcP34c165dq3bdY8eOQa1WY+jQoVrtQ4YMwaNHj5Cammq2OOsaQ2qQkZGBvLw8zJkzR+9yLi4uOtOImzZtCj8/P735B6y3BubMvymsNf+AeWtgSj905coV/PDDD5gwYYJW+8SJE1FWVmb1NahKQkICmjdvjsGDB2vaTOmHWIPaq6oGprDWGpgz/0+ePAEAnVkjTk5OAJ5N2X8esdR3huy3vtyq1Wqt2VGm5JE1qF5tagAABQUFiI+Px9q1a2FnZ2fWWCzN88j/byUmJkIIgYiICLPEYokM2e+srCz4+vqidevWmraGDRuiT58+SE5O1lyCmJaWhidPnuicTydMmIBTp07h4sWL1X5Gw4YN4ejoqNPevXt3/Pzzz4buznNnnb8lFmTdunWQy+VwdHREaGgovvnmG633bWxsquy45XI5gGfXM1fHxsYGAGBvb1/rda3B0aNHAQCPHj1CUFAQ7Ozs4ObmhnfeeQcPHz7Uu25JSQlOnz5d4/RK1qB6tc3/gQMH4OjoCLlcjqCgIIOul2X+9TO0Bqb0Q2fOnAEABAYGarV7e3vD0dERubm5Ju+HJbly5QrS09Mxfvx42Nra6l3W0H6INaidmmpgTF/EGhiuuvwHBASgb9++iIuLQ3Z2NkpLS3Hs2DHExsZi6NChVnW5g7kNGDAAvr6+eP/995Gbm4vS0lJ8/fXX+OSTTzB9+nQ0bNhQ6hAtXm1rMH36dISHh6Nv374SRWxZTDkGtm7diq5du+r071Q7NjY2On+vA8/+1nz48CEKCgoAPDufyuVytGnTRmu5gIAAADDqfHrkyBG0a9fOiKifDw7w1GMTJkzA2rVrcfjwYWzcuBHFxcUIDQ3VuqdF27Ztce/ePZ1rDzMzMwE8+wO/Om3btgUAnRt+GbKuNagYqR07diwGDRqEQ4cO4b333sPmzZsxbtw4vevOmjULQgi8++67epdjDapXm/yPHDkSa9asQVpaGrZt2waFQoHRo0cjKSlJ72cw//oZWgNT+qGK95RKpc57SqXS6mtQWVJSEtRqtUHfBBraD7EGtaOvBsb2RayB4arLv0wmQ0pKCtq2bYsePXqgcePG6NmzJ3x8fAy6uSZVT6FQ4OjRo1Cr1QgICEDjxo3Rv39/jBgxAn/729+kDs8q1KYGSUlJyMnJwccffyxRtJbH2GMgMzMTFy5cMOicTfq1bdsWFy5cQHFxsaZNrVbj2LFjAH49j5aUlMDJyUlnVnOzZs20ljPUxo0bkZWVhejoaFPCNyv9X+9RnZaYmKj5d58+fTBq1CgEBgZi8eLFmm/Wx40bh5iYGERERGDLli1wd3fHxo0bceTIEQD6p7z5+/tjwIABiImJgY+PD3r27In09HTNE4SsdZpghYrp3BMmTEBsbCwAoF+/figvL8eCBQuQl5dX5TeCy5cvxxdffIEtW7bojB5XxhpUrzb5X7Nmjda6o0ePRlBQEKKjo3WmaP4W86+foTUwpR+i2tm6dSu6dOmCjh076l2uNv0Q1Y6+GhjbF5Hh9OV/6tSpyMrKwvr169G+fXvk5eUhJiYGr776Kg4cOMC+yEiPHj3C2LFjcevWLSQmJkKlUmlmR9na2mLdunVSh2jxDK1BSUkJ5syZg48++ghubm4SR205jD0GEhISYGdnV+MXw1Sz6dOn49NPP8WkSZPw6aefwtHRER9++KHmkqvn0b9nZGTgnXfewaRJkzB+/Hizb99YPJNZkMaNG2P48OE4fvy4ps3JyQl79uzB7du30bFjR7i6uuLvf/87li5dCgBwd3fXu83PP/8c/v7+GDJkCJRKJSIjI7F8+XKD1rV0zs7OAICBAwdqtQ8aNAgAcOLECZ111q9fj4ULFyI+Pr7apxpUxhpUzZj8V7CxsUF4eDiuXr2K69ev6/0c5r96htbAlH6oYsbCnTt3dN67c+eO5hsXenbPqLNnz9b4TWBt+yHWwHCG1qCCoX0Ra2AYffn/17/+he3btyMxMRHTpk1D3759MW3aNCQmJiIlJQUHDhyQIGLLsGXLFmRkZCAlJQUTJkxA3759MW/ePKxcuRLr16/Hjz/+KHWIFs/QGixevBju7u547bXXcPfuXdy9exePHj0CAPzyyy96H6lO1TPmGHj8+DF27dqF4cOHw8XFRYKoLYuPjw+2bduGnJwctGnTBi1btkRmZiZmz54N4Ne/NZVKJe7evatzX6SKmTuGnk+PHz+OsLAwhIaGYvPmzWbcE9NxgMcCVZ5y1qdPHxQUFOD8+fPIy8vD+fPnYWdnBwcHB3Tr1k3vtlq1aoWMjAxcu3YNp06dwo0bN9C5c2cAQO/evZ/XLtQLFddqVqfySHFiYiJmzJiBuXPnYtGiRQZ/DmtQtdrmvzqVj5fKmP/q1aYGxvZDFZ9RcQ+SCpcuXcKDBw/g7+9vwh5YFkO+CTSmH2INDGfKt7H6+iLWwDD68n/q1CkA0HkM8e9+9zsA0LmElAx36tQpKJVKrZubAszti2RoDXJzc3Hy5Ek4OztDqVRCqVTiL3/5C4BnN+OvS7MQ6hNjjoH9+/fjzp07vDzLjMaMGYNr164hNzcX+fn5yMnJQWlpKTw8PKBSqQA8O58+fvxYc0+eChX33jHkfHrq1CkMHjwYnTt3xu7du2t1o/IXgQM8FuTevXtITk7WdCa/JZPJ4Ovri3bt2uHBgwfYtGkTJk6caPCN71q2bInAwEAoFAqsXr0a7dq103oijjUaOnQo5HI50tLStNoPHjwI4Nkd1St8+eWXeOONNzBlyhSsWLHCqM9jDbTVJv+VPX36FDt37oRKpUKLFi0M+jzmX1dta2BMP6RSqdCpUyds27ZNqz0pKQl2dnY6TzizVk+ePMGOHTswdOhQuLq6VrmMsf0Qa2AYQ2pQmaF9EWtQs5ryX5HfivsxVPjuu+8APBvMJ+O0aNECd+7cQX5+vlY7c/viGFqD1atXIz09XeunYoDh8OHDiI+Pf7GBWwhjjoGEhAS4uLhg+PDhLyRGa2FjY4P27dujdevW+Pnnn7Fz5068/fbbmveHDBkCOzu7Ks+ngYGB8Pb21rv9CxcuYODAgfDx8UFycjIcHByey36YgvfgqaP++c9/AgBycnIAAKmpqXB1dYWrqyuCg4OxYsUKnDt3DiEhIWjZsiUuX76MFStW4MaNGzq/sNHR0ejWrRtcXFyQn5+Pjz/+GHZ2dprLTCr0798fly9f1uqc1q1bB4VCAW9vb9y4cQMJCQk4evQovvrqK4u/Vr2mGjg7OyM6OhpxcXFo0qQJQkNDkZ2djdjYWERERGjua3HkyBG8/vrr6NSpEyIjI7Vu2CuXy9GlSxfNa9bgV+bK//bt27Fv3z4MGzYMHh4euHnzJj777DN8//332L59u9ZnMv/azFUDwLR+6KOPPsKIESMwbdo0vP766zhx4gTi4+MRFRVl8ABdfVVTDSokJyejpKSk2m8CTe2HWAPTa2BqX2StNTBX/v/whz9g0aJFmDRpEpYsWYJ27drh7NmzWLZsGTw8PDB69GjNsm+++SYSEhI0j9UFgKKiIvznP/8BABQWFuLBgwea2Pz9/S16FlVNNYiMjMSqVaswbNgwLFq0CCqVCtnZ2YiLi0O3bt3w8ssva7aVm5ur+ab84cOHuHz5smb7wcHBmsG52NhYxMbGoqCgAJ6engCABw8eICUlBQBw9uxZrdi8vLz0frFT35mrBhUzkH+r4uEswcHBWk+e43HwK3MeAwBw69YtpKWl4e2336529gfzr62mGpSVleG9995DcHAwmjRpgjNnzmD58uUICAjA3LlzNdtxc3PDnDlzsHz5cjRu3Bhdu3bFzp078fXXX2P//v1an1n5XHzr1i0MHDgQT548wbJly3SeuNWlSxfNE2IlJahOAlDlT3BwsBBCiP3794tevXoJZ2dnYWtrK5o1ayZGjhwpvvvuO51tvfHGG6JVq1bCzs5OtGrVSsycOVMUFxfrLBccHCw8PT212tasWSP8/PyEXC4XSqVSjB49Wpw+ffp57HKdU1MNhBBCrVaLlStXitatWws7OzuhUqnEkiVLxJMnTzTLxMTEVLutyvlmDX5lrvxnZmaKkJAQ4ebmJmxtbUXTpk1F//79xcGDB3U+k/nXZq4aCGFaPySEELt37xYdO3YU9vb2wsPDQyxbtkw8ffrU3Ltc5xhSAyGECAsLE82aNROPHz+ucjum9kNCsAam1sDUvkgI66yBufIvhBCFhYVi8uTJwsvLS8jlcuHl5SWmTJkirl69qrVcRESEqPwncnp6erWxxMTEmGt36yRDanDmzBkRHh4uXnrpJaFQKISvr6+YO3euKCkp0dqWvr4oPT1dZ7mLFy9q2i5evFjtuhEREc83CRIzZw0qq8h1WVmZVjuPg1+ZO/+rVq0SAER2dna1n8n8a6upBmVlZWL48OHCzc1N2NvbCx8fH7Fo0SJx//59nW09ffpUxMXFCZVKJezt7UWHDh3EP/7xD53lKp+L9eW/cn8lJZkQle4wRERERERERERE9YplX19ARERERERERGQFOMBDRERERERERFTPcYCHiIiIiIiIiKie4wAPEREREREREVE9xwEeIiIiIiIiIqJ6jgM8RERERERERET1HAd4iIiIiGph6dKlkMlkePr0abXLZGRkQCaTISMj48UFRkRERFbNVuoAiIiIiCxN165dkZmZCX9/f6lDISIiIivBAR4iIiIiM2vSpAmCgoKkDoOIiIisCC/RIiIiIjJCXl4eQkJC4OjoCHd3d3zwwQdQq9UAqr5Eq1+/fujduzcOHz6Mrl27wtHREYGBgfjyyy+1tnv+/HmMHj0abm5uUCgUUKlUCA8P13tJGBEREREHeIiIiIiM8Morr2DAgAHYu3cvxo0bh7i4OMTGxupdp6CgAFFRUZgzZw727NkDd3d3hIeHIz8/X7PM8OHDce3aNaxbtw5paWn485//DLlcrhk8IiIiIqoKL9EiIiIiMsLUqVOxYMECAMCgQYNw7949rFy5Eu+++26169y+fRtHjhyBr68vgGf36nF3d8euXbuwcOFC3L59G/n5+di3bx/CwsI0640bN+657gsRERHVf5zBQ0RERGSE1157Tev1H//4R5SWluL06dPVruPr66sZ3AEANzc3uLm5obCwEADg7OwMHx8fLFiwAJs2bcKFCxeeT/BERERkcTjAQ0RERGSE5s2bV/n62rVr1a7TrFkznTa5XI5Hjx4BAGQyGQ4dOoTu3bsjOjoafn5+8PHxwbp168wYOREREVkiDvAQERERGeHmzZtVvm7VqpVJ2/Xx8cHWrVtRVFSEEydOIDQ0FDNmzEBqaqpJ2yUiIiLLxgEeIiIiIiPs2rVL6/WOHTvQqFEjdOjQwSzbl8lk6Ny5M1atWgUAei/9IiIiIuJNlomIiIiMsGnTJqjVavTo0QNpaWnYvHkzli5diqZNmxq9zZMnTyIqKgpjx45FmzZtUF5ejs8//xy2trYIDQ01Y/RERERkaTjAQ0RERGSEffv2YdasWYiLi0PTpk2xePFiLFmyxKRttmjRAiqVCqtWrcLVq1ehUCjQoUMHJCcno1u3bmaKnIiIiCyRTAghpA6CiIiIiIiIiIiMx3vwEBERERERERHVcxzgISIiIiIiIiKq5zjAQ0RERERERERUz3GAh4iIiIiIiIionuMADxERERERERFRPccBHiIiIiIiIiKieo4DPERERERERERE9RwHeIiIiIiIiIiI6jkO8BARERERERER1XP/B9sMdUB2niZyAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "n, bins, patches = ax.hist(\n",
    "    data_height,\n",
    "    bins=10,\n",
    "    cumulative=True,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\"  # GNOME purple 2\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.bar_label(\n",
    "    patches,\n",
    "    fontsize=16,\n",
    "    color=\"#613583\",  # GNOME purple 5\n",
    ")\n",
    "\n",
    "# set ticks\n",
    "ax.set_xticks(bins)\n",
    "ax.set_xticklabels([f\"{value:.1f}\" for value in bins])\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot5.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Two histograms"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data for 2nd histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_height_2 = [\n",
    "    random.normalvariate(mu=168,sigma=3.5)\n",
    "    for _ in range(nr)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "ax.hist(\n",
    "    data_height,\n",
    "    bins=10,\n",
    "    density=True,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\",  # GNOME purple 2\n",
    "    alpha = 0.8\n",
    ")\n",
    "ax.hist(\n",
    "    data_height_2,\n",
    "    bins=10,\n",
    "    density=True,\n",
    "    edgecolor=\"#26a269\",  # GNOME green 5,\n",
    "    facecolor =\"#57e389\",  # GNOME green 2\n",
    "    alpha = 0.8\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot6.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Two histograms with different styles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Average height\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "ax.hist(\n",
    "    data_height,\n",
    "    bins=10,\n",
    "    density=True,\n",
    "    edgecolor=\"#613583\",  # GNOME purple 5,\n",
    "    facecolor =\"#c061cb\",  # GNOME purple 2\n",
    "    alpha = 0.5,\n",
    "    histtype=\"stepfilled\"\n",
    ")\n",
    "ax.hist(\n",
    "    data_height_2,\n",
    "    bins=10,\n",
    "    density=True,\n",
    "    edgecolor=\"#26a269\",  # GNOME green 5,\n",
    "    facecolor =\"#57e389\",  # GNOME green 2\n",
    "    alpha = 0.5,\n",
    "    histtype=\"stepfilled\"\n",
    ")\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"bins\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"count\",\n",
    "    fontsize=16\n",
    ")\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot7.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2D histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Q3377LQDAzc0N3t7eiI6OVngJxKNHj3Dq1CksXbq0yUkGQPJNsrOzQ2Zmpgot6vooNrJRXOSj2MhGcZGPYiMbxUU+io18FBvZKC7yUWxko7jIZ2dn195V4FxycnJ7V0FpxsbGuH//vvj3Bw8ewNjYmPPzdIqlE5GRkRgxYgRGjBgh9Zq/vz+ePHmC7Oxs5Ofn4+TJk3j48CHGjh0LPp+v0PGjo6PR0NBAyyYIIYQQQgghhHRZY8aMQW5uLu7cuYPa2lrExcVhxowZnJ+nw9/RkJmZiZycHIklEy8TCAQYNmwYACArKwunTp1CVFSUwueIioqCjY0NbG1tW1pdQgghhBBCCCGkQ1JXV8eePXswZcoUNDQ0YP78+eL/S3N6Hs6PyLGoqCioq6tjzpw5Uq89ePAAX3/9NcaPHw+BQIDMzExs2bIFb731ltQjKtXV1eHt7Y1Dhw5JpF+9ehXZ2dnYvn270nUTLaEg0ig2slFc5KPYyEZxkY9iIxvFRT6KjXwUG9koLvJRbGSjuMhHsek4pk2bhmnTprXqOTr0ZpB1dXXo27cv7O3tcezYManXHz9+jDlz5uCPP/5AeXk5Bg0ahAULFmD58uVSey3weDx4e3sjIiJCIn358uUIDw/HgwcPFN44khBCCCGEEEIIIbJ16IkGQgghhBBCCCGEdC6dYjNILjx48ABLly7FuHHjoKWlBR6Ph7t370rl4/F4Mn/++OMPiXxPnz7F/PnzYWhoCE1NTYwdOxYpKSkK1aWhoQGhoaEwNTWFQCCAubk5du7c2fJGqkDRuADAjRs34OXlBQMDA2hqasLS0hK7du0Sv37r1i0sX74cNjY26NGjB1577TXMmDED//nPf5Su119//SWuT15enqrNaxEuY/OyuLg48Hg89OvXT6G6dKQ+A3Abm4iICLmfOx6Ph8LCwibr4uPjI7PcihUrOGyxYhSJS1BQkNy2CoVCibyNjY3YsmULBg4cCKFQiBEjRuCnn35SuD5HjhzByJEjIRQKMWDAAGzatAkNDQ1cNFVpXMampWNNV+4zAwcOlJnvyJEjCtWnq/aZlo4zwD+PCgsKCoK5uTkEAgF69+4NT09P1NbWct30Jik6/ubn58Pb2xsmJibQ1NSEhYUFPv30U1RUVEjlPXDgAKysrCAQCGBpaYl9+/YpVJf09HT4+PjA2toa6urqGDhwYAtb1zJcxubRo0cIDAyEnZ0ddHV1YWhoCFdXV5w7d07h+jQ0NGDnzp2wtraGUCiEvr4+3Nzc8OjRIy6aqzCu+4yTk5PMz5Ei1yVduc+kpaU1Oc5cuHChybo0VXbr1q1cN71Zisbmzp07eOedd6Crq4vu3bvD2dlZ5lM3VL2mKSsrQ0hICMaPHw99fX3o6upi/PjxCv9dI+2nw+/RwJW8vDz88MMPGD16NBwcHHDixAm5eX18fLBkyRKJNAsLC/G/a2pq4OLigqdPn+KLL75Anz59cOjQIXh6euLkyZNwcnJqsi7+/v6IiIjAhg0bMHbsWKSmpmLNmjV4/vw5Pv300xa1U1mKxiUzMxMuLi5wcnLCwYMHoaOjg9zcXDx//lyc58SJE0hNTYW3tzdGjRqF0tJSfPHFF7C3t0d6ejpGjx6tcL38/f2ho6ODqqqqFrdRVVzG5kWlpaVYsWIF+vTpo3BdOlKfAbiNjYeHBzIyMiTKMcYwffp0mJmZKRQnQ0NDJCYmSqS99tprKrSsZRSJy8KFC+Hu7i6RVlFRAXd3d6kdfzds2ICwsDBs3rwZo0ePRlxcHLy8vJCUlNTsurqUlBS8/fbbWLBgAXbs2IFr165h3bp1KC8vx7Zt21reWCVxGRsuxpqu2mcAYMqUKQgKCpJIs7S0bLYuXbnPtHScqaurw9SpU3Hnzh0EBgZi6NChKCoqwsmTJ9t8IkaRuFRUVMDNzQ11dXUIDQ2FiYkJLl++jI0bNyI3Nxfx8fHivAcOHMCSJUsQGBgINzc3nD59Gv7+/mCMwc/Pr8m6nD59GufPn4ednR14PB7Ky8s5b68yuIzNlStXEB8fD19fX9jb26O2thbh4eFwcnJCYmIiPD09m63PvHnzkJKSgnXr1sHOzg5///03zp49i+rqas7b3hSu+wwA2NjY4JtvvpFIU2TSoCv3mVGjRkmNMwCwYMECPHv2DGPGjGmyLrLK7t27F9HR0a3yRIDmKBKb4uJiTJgwAdra2vjmm2+gpaWFHTt2wNnZGZcuXcKQIUPEeVW9psnPz0d4eDh8fX2xYcMGdOvWDbGxsZg1axb27NmDDz/8sFXaTzjAXhENDQ3ifx84cIABYHfu3JHKB4CtX7++yWMdPnyYAWCpqanitMbGRjZ8+HA2ZsyYJsveu3ePdevWjW3cuFEi/cMPP2RCoZAVFxc32xYuKRKXhoYGNmTIEPbmm282eayioiLW2NgokVZaWsp0dXXZvHnzFK5TTEwMMzIyYl999RUDwHJzcxUuyyUuY/OiRYsWscmTJzNvb29mbGzcbP6O1mcYa73YiJw7d44BYHv27Gk2r6JxbAuKjjMvi4qKYgBYUlKSOO3x48dMQ0ODffbZZxJ5XVxc2PDhw5s9pq2tLZs4caJEWnBwMOPz+ezRo0fNlucal7Fp6VjTVfsMY4wNGDCAzZkzR6W6dOU+I4sy48yWLVuYtrY2y8/PbzZva1MkLikpKQwAS0lJkUhfu3YtU1NTYxUVFYwxxurq6pihoSH797//LZHP19eX6evrs9raWoXrMmfOHDZgwAAVWsQdLmNTUlLC6urqJPLU1dUxCwsL5uDg0GxdYmNjmZqaGsvMzFSxNdzhMi6MMebo6MjeeOONFtelq/UZWe7evct4PB5bs2aNSvUbNGgQs7OzU6lsSykSm9DQUKampsby8vLEac+fP2dGRkbMy8tLnNaSa5rnz5/LjLGLiwvr37+/Mk0ibeyVWTrRrRt3Tb1w4QI0NTUl7lzg8XiYPHkyLl++jIKCArllL126hMbGRkydOlUi3d3dHdXV1fj11185q6ciFIlLWloabty4gVWrVjWZz8DAADweTyJNR0cHFhYWTcbkRSUlJVi1ahXCwsKgq6urUJnWwmVsRH777TdER0dj7969Ctejo/UZoHVi86LIyEhoaGhIPT2mo1N1nImMjETv3r0xZcoUcVpKSgpqa2sxd+5cibxz585FVlYW7ty5I/d49+/fxx9//CFVdt68eairq+uwfUYWWbHhYqzpKLiMS0t09T4jL5+i40x4eDi8vLzQv39/lerEJUXiIlrO0bNnT4l0XV1dNDY2gv3/9lwZGRkoKiqS+b4XFxcjPT29xXVpS1zGRldXV2pjcXV1ddja2io0zoSHh8PR0VGpuzlbC5dxaYu6tKXWjs3hw4fBGIO3t7fSdUtPT8ft27dVKssFRWJz4cIFmJubY9CgQeK07t27w8HBAUlJSaivrwfQsmua7t27Q0tLSyrdzs4ODx8+VLQ5pB10rE97B/H1119DIBBAS0sLLi4uOH/+vMTrampq4PP5UuUEAgEAIDs7W+6x1dTUAAAaGhpKl20voguN6upq2Nvbg8/nw8jICMuWLWt2acOzZ8+QnZ0tcetUUwICAmBlZYV58+a1uN5tQZnY1NXVYfHixfj4448xePBghc/RGfsMoHq/qaqqQkJCAjw9PdGrVy+FzvXkyRMYGBhAXV0dFhYW2LZtW7utK1fW/fv3kZqaijlz5khc1F6/fh0CgUCqr4iec5yTkyP3mNevXwcAWFtbS6SbmppCS0urybIdibzYyKLsWNMV+4zIsWPHoKWlBYFAAHt7e4XWsb5qfUaZcSY/Px/379+HmZkZFi1ahJ49e0IoFMLV1VVq/6aOws3NDebm5li7di1ycnLw/PlznDlzBrt27cIHH3yA7t27A5D/visyznRWisZGltraWmRkZDQ7ztTV1eHixYsYNmwYAgICYGBgAD6fj7Fjx+LMmTNcN4kTysbl2rVr0NHRAZ/Ph42NjdTj47uSlvSZqKgojBo1SuozpojO8KWLmpqa1PUp8M81alVVFW7fvg2gZdc08pw7dw5WVlYq1Jq0FZpoeMncuXMRHh6OU6dOYf/+/SguLoaLiwvS0tLEeSwtLVFWVoYbN25IlBWtrXr27Jnc44vWyb68IYwiZduLaLbwvffew+TJk3Hy5EkEBATg4MGDmD17dpNlly5dCsaYQpusnT9/HlFRUQgPD+ei2m1Cmdhs27YNNTU1CAwMVOocnbHPAKr3myNHjqCsrEzhGXxbW1ts374dP/zwAxITE+Ho6IjAwECpfVY6qujoaDQ2Nkq199mzZ9DV1ZX65l70n6Km3nfRa3p6elKv6enpddg+8zJ5sZFFmbGmq/YZAJg+fTp2796NlJQUxMTEQCgUYtasWYiOjm7ymK9an1FmnBGNZdu2bcNff/2FuLg4xMbGoqioCE5OTsjPz+ek7lwSCoVIT09HY2Mjhg0bBm1tbbi6usLT0xN79uwR55P3visyznRWisZGlqCgIDx48ABr165tMl9xcTFqa2sRERGBEydO4MCBAzh69Ci0tLTg7u4uc6O89qZMXCZOnIidO3ciMTERP/74I8zNzbFw4UJs2rSpnWrfulTtMxkZGcjNzVXpjoTq6mokJCTAw8MD+vr6Lal+q7K0tERubi6Ki4vFaY2Njbh06RKA/40hLbmmkWX//v24cOGC0tfUpI2147KNdqPMWs+ysjJmYmIisRatpKSEGRgYsDFjxrD//ve/rKioiG3evJmpqakxACwuLq7JY7q5uTFDQ0OWnJzMSkpK2M8//8z09PQYAPbBBx+0tHkqkxeXRYsWMQBs6dKlEulbt25lAFhOTo7M433++ecMADt06FCz566pqWFDhgxha9euFad999137bpHw4taGpvc3FwmFArZr7/+Ks6jzDrxjtpnGOO+30yZMoUZGRlJrY1VxooVKxgAduvWLZWP0VKKjjNWVlZs5MiRUumLFi1ivXv3lkrPzc1lAFhUVJTcY8bExDAA7MaNG1KvGRsbs/nz5zffgFbU0ti8TJmxRp6u0Gdkqa+vZ3Z2dqxfv35N5nvV+owy48xvv/3GALDevXtLrBPOz89nGhoaLCAgoNljtBZ5camqqmJOTk7MwsKCHT58mJ09e5Z9+eWXTFtbW+JvxubNmxkAVlVVJVG+rq6OAWAhISEK16UjrLd/UUtj87KYmBjG4/Gk1pjLUlBQwAAwoVDICgoKxOnl5eXM0NCQvfvuuyq3q6W4jovIm2++yYRCISsvL1e4Ll29zyxZsoTx+XxWVFSkdF1iY2MZAHb06FGly7YGebG5ffs2EwgEbNq0aSwvL489fPiQffjhh+L/E124cIEx1rJrmpelpqYygUAgtbcM6XjojoZmaGtrw8PDA5cvXxan6erq4ueff8bTp09hY2MDQ0NDfPvtt+JdvpvbuTwiIgJDhw6Fu7s79PT04OPjgy1btihUtj2IZlInTZokkT558mQA/9w+97J9+/Zh3bp12LRpE+bPn9/sOXbu3ImSkhIsW7YMpaWlKC0tRWVlJQCgvLy83XcllkfR2CxbtgwuLi6wt7cXt6+2thaMMZSWlja7BKWz9RlAtX7z6NEjnDp1CrNnz272VvmmiG4z7IjfGr3o0qVLuHnzpsxvO/T09FBaWiq19lM069/U7d6ibydLSkqkXispKVF4SUp7aio2L1J2rJGnK/QZWdTU1ODl5YUHDx40+Ui9V6nPKDvOiMayN954Q2KdcP/+/WFlZSVzLGtvhw4dQlpaGo4fP465c+di4sSJWLNmDbZv3459+/aJHwUr731XZJzprBSNzYuOHTsGHx8fLFiwAMHBwc2eQ09PDzweD0OHDkXfvn3F6T169MC4ceM6dZ+R5/3330d1dTWysrLaqMZtR5XY1NTU4IcffoCHhwcMDAyUPmdUVBQMDQ2l9ufqaMzMzBATE4MrV65g8ODB6Nu3LzIyMrBy5UoA/7tGbck1zYsuX76MGTNmwMXFBQcPHuSwJaQ10ESDgl6+1cfBwQG3b9/GrVu3cOPGDdy6dQt8Ph+amprNbvxjbGyMtLQ0FBQUICsrC4WFhbC1tQUATJgwobWaoDLR+il5Xt4s5vDhw/D398fq1auxfv16hc6Rk5ODwsJCGBsbQ09PD3p6euLH1YwaNQoODg6qVb6VKRqbnJwcHD9+XNw2PT09xMbG4uHDh9DT02v21q/O1mcA5fsN8M9tzw0NDZxtfPTy57ajiYyMBJ/Pl7mUZNiwYaipqRGvbxQRrWMcOnSo3OOKYi9afy1y9+5dVFZWNlm2o2gqNiKqjDXN6cx9pjlNte1V6TOA8uOMmZkZNDU15b7e0Ta3A4CsrCzo6elJbNAGAK+//joAiJd+ynvfFRlnOitFYyNy+vRpeHl5YdasWVKPc5RHU1MTZmZmcl/vzH2mOR19DFWFKrFJTExESUmJStczhYWFOHHiBGbPni1zT7iO5u2330ZBQQFycnKQl5eHK1eu4Pnz5+jfvz9MTEwAtOyaRiQrKwtTpkyBra0tfvrpp04Rm1ddxxvpOpiysjIkJSWJB5MX8Xg8mJubw8rKCpWVlThw4ADmzZvX5KYwL+rbty+sra0hFAqxc+dOWFlZSTzJoqOYOnUqBAIBUlJSJNKTk5MB/LPrq8gvv/wCX19fLFy4EGFhYQqf45NPPkFqaqrEj2gNZHR0dIedtVQ0NnFxcVLtmzJlCgwMDJCamoqPPvpIofN1lj4DKNdvRKKiomBjYyOeRFFVTEwMeDxes8+sbk+1tbWIi4vD1KlTYWhoKPW6u7s7+Hw+YmJiJNKjo6NhbW0NU1NTucc2MTHBiBEjZJbl8/kd/huS5mIDqD7WyNMV+ows9fX1iI+Ph4mJCfr06SM336vQZ0SUHWf4fD48PDyQnp6OiooKcXp+fj5u3rzZIftMnz59UFJSgry8PIn0ixcvAvhn8hoAxo0bBwMDA5nve69evfDGG2+0TYXbkKKxAf5ZYz9z5ky4uroiOjpaqQmCWbNm4fr16xJPqCgvL8fvv//eqfuMPDExMdDU1MTw4cNbrY7tRZXYREZGwsDAAB4eHkqfj+svXdqCmpoahgwZgkGDBuHhw4eIj4+Hn5+f+PWWXNMAQG5uLiZNmgQzMzMkJSU1OflLOg7V703uhH788UcAwJUrVwAAv/76KwwNDWFoaAhHR0eEhYXhzz//hLOzM/r27Yt79+4hLCwMhYWFUh+MwMBAjB49GgYGBsjLy8OXX34JPp8vvp1dxNXVFffu3ZMYnL7++msIhUKYmpqisLAQkZGRSE9Px+nTp9tllru5uOjr6yMwMBChoaHo2bMnXFxckJmZiZCQEHh7e4t3kD137hzef/99jBgxAj4+PhKbFwoEAowcOVL8+8txsbKykto59u7duwCAsWPHKvWUBi5xFRt7e3upY0dEREAgEEhNFHSGPgNwFxuRq1evIjs7G9u3b5d7zpdjc+/ePcybNw//+te/MHjwYNTU1OCXX35BREQElixZIvXtQ1toLi4iSUlJePbsmdwLCSMjI6xatQpbtmyBtrY2Ro0ahfj4eJw5cwaJiYkSeWX1mc8//xyenp5YsmQJ3n//fVy7dg2bNm3C8uXLm/wPZ2viKjYtGWu6cp+JjY3F0aNHMW3aNPTv3x+PHz/G3r17cfXqVcTGxkrkfdX6jIgq4wwABAcH4/XXX4eHhwdWr16N6upqBAcHQ1dXV+GJYi41FxcfHx/s2LED06ZNw/r162FiYoLMzEyEhoZi9OjR4gkEPp+P0NBQ+Pv7w9jYGG5ubjhz5gy+/fZb7N69W2I3+QULFiAyMlL8uDoAKCoqwtmzZwH8M/FSWVkprtvQoUPb5Y4IrmJz8+ZN8W3vH3/8sfh4Ii/+XZcVmzVr1uDw4cOYOnUqPvvsM2hoaCAsLAyVlZX45JNPWjsMUriKy/nz57F161a89dZbGDhwIP7++29ERkYiMTERW7dulfiy7VXrMyJPnjxBSkoK/Pz85H7rLis2IlFRURg+fLjE37L20lxs6urqEBAQAEdHR/Ts2RPXr1/Hli1bMGzYMKxevVp8nJZc0zx58gSTJk1CbW0tgoODpZ5QMXLkSPGT2EgH0857RLQpADJ/HB0dGWOMJSYmsvHjxzN9fX2mrq7OevXqxaZPn84uXrwodSxfX19mbGzM+Hw+MzY2Zh999BErLi6Wyufo6Ci10c3u3buZhYUFEwgETE9Pj82aNYtlZ2e3RpMV0lxcGGOssbGRbd++nQ0aNIjx+XxmYmLCNmzYwGpra8V5Nm7cKPdYL8dAVlxe1hE2g+QqNrLI2wyyM/QZxriPzbJly5i6ujorLCyUe86XY1NcXMxmzpzJTExMmEAgYJqammzkyJFs9+7drKGhgcvmKkyRuDDG2IwZM1ivXr1YTU2N3GPV19ez0NBQZmJiwjQ0NNjw4cNZQkKCVD55n6effvqJ2djYMA0NDda/f38WHBzM6uvrW9pElXEVm5aMNV25z2RkZDBnZ2dmZGTE1NXVmY6ODnN1dWXJyclSeV+1PiOiyjgjcvHiRebk5MQ0NTVZz5492cyZM9vt75Micbl+/Trz8vJi/fr1Y0KhkJmbm7PVq1ezZ8+eSR1v3759zNzcnGloaLDBgwezvXv3SuXx9vZmL182pqamyq3Lxo0buW62QriKjegaRN7Pi2TFhjHG/vzzT+bp6cl69OjBtLS0mKurK7t8+XKrtb0pXMUlNzeXubu7s759+zINDQ3WvXt3Nm7cOPb9999LnfNV6zMiO3bsYABYZmam3HPK6zNXr15lAFhYWBgnbWup5mJTV1fHPDw8mJGREdPQ0GBmZmZs/fr1Ehvniqh6TdNUn4GMDSpJx8Fj7KVdOQghhBBCCCGEEEJURHs0EEIIIYQQQgghhDM00UAIIYQQQgghhBDO0EQDIYQQQgghhBBCOEMTDYQQQgghhBBCCOEMTTQQQgghhBBCCCGEMzTRQAghhBBCCCGEEM7QRAMhhBDSioKCgsDj8VBfX9/iY0VERIDH4+Hu3btKl/Xx8UG/fv2azZeWloagoCA0NjaqUENCCCGEEJpoIIQQQjoNDw8PZGRk4LXXXmu1c6SlpSE4OJgmGgghhBCiMvX2rgAhhBBCFGNoaAhDQ8P2rgYhhBBCSJPojgZCCCGkDdy5cwceHh7o0aMHBgwYgJCQEIm7BoqKivDBBx/A2NgYAoEAVlZW2L9/v8QxZC2dqKyshJ+fH/T19dGjRw/MmjULv//+O3g8HiIiIqTqce3aNTg4OEBLSwvm5ubYt2+f+LWgoCAEBwcDAPh8Png8Hng8HgCgvr4eGzZswKBBgyAUCmFgYIAJEyYgPT2dwygRQgghpCugOxoIIYSQNjBr1iz4+vpi5cqVOHbsGDZu3Ij+/fvD19cXZWVlmDBhAqqqqhAUFARTU1OkpKTAz88PNTU1WLp0qdzjLl68GAkJCQgKCoKdnR1Onz6NOXPmyMxbVlaG2bNnY8WKFfjss8/w3Xffwc/PD5aWlnB2dsbChQvx4MEDHDp0COnp6VBTUxOX3bZtG7766its3rwZtra2KCsrQ2ZmJp49e8Z5rAghhBDSudFEAyGEENIGVq9eDV9fXwCAm5sbzpw5g9jYWPj6+mLXrl24d+8esrKyYG5uLs5TWlqK4OBg+Pn5QV1d+k/2n3/+ie+//x5bt25FQEAAAGDSpEmorKzE7t27pfKXl5cjPDwczs7OAICJEyciJSUFsbGxcHZ2Rr9+/cQbRo4dO1binBkZGZg8eTKWL18uTps+fTpH0SGEEEJIV0JLJwghhJA24OHhIfG7tbU18vPzAQDJyckYO3YsTE1NUV9fL/6ZMmUKiouLkZOTI/OYFy9eBGMMXl5eEunvvPOOzPxaWlriSQYAEAgEsLCwENejKWPGjMHx48exfv16pKeno7a2ttkyhBBCCHk10R0NhBBCSBvo1auXxO8CgQDV1dUAgCdPniAvLw98Pl9m2eLiYpnpjx49AgAYGRlJpPfu3Vtmfj09Pam0F+vRlHXr1kEoFCI6Ohqff/45evTogXfeeQdffvklDAwMmi1PCCGEkFcHTTQQQggh7UxfXx9GRkbYtWuXzNctLS1lposec/nkyROYmpqK0x8/fsx5Hfl8PtauXYu1a9eisLAQSUlJWLVqFSorKxEfH8/5+QghhBDSedFEAyGEENLO3N3dsXv3bpiYmEjdndCU119/HTweDwkJCeI9GgAgISFB5boIBAIAQFVVFbS1tWXm6dOnDxYuXIjjx48jOztb5XMRQgghpGuiiQZCCCGkna1cuRLx8fFwcHDAypUrYWlpiYqKCty8eRPnz5/H0aNHZZazsrLC7NmzsWHDBjQ2NmL06NE4c+YMjh07BgDo1k35rZiGDh0KANi+fTumTp0KNTU12NnZYebMmRgxYgRGjRoFPT09XLt2DcnJyViyZInqDSeEEEJIl0QTDYQQQkg709HRwe+//46QkBBs27YNBQUF0NXVhaWlJd5+++0my+7fvx/a2tr44osvUFtbCxcXF+zduxeenp7Q0dFRui6enp7w9/dHeHg4QkJCwBgDYwwTJ05EQkIC9u7di8rKSpiYmCAgIADr169XtdmEEEII6aJ4jDHW3pUghBBCCHfCwsIQEBCAu3fvwsTEpL2rQwghhJBXDN3RQAghhHRiSUlJyM7Ohq2tLbp164bz588jLCwM7777Lk0yEEIIIaRd0B0NhBBCSCd29uxZrF27Fjdv3kRFRQWMjY3x3nvvITg4GEKhsL2rRwghhJBXEE00EEIIIYQQQgghhDPKb0dNCCGEEEIIIYQQIgdNNBBCCCGEEEIIIYQzNNFACCGEEEIIIYQQztBEAyGEEEIIIYQQQjhDEw2EEEIIIYQQQgjhDE00EEIIIYQQQgghhDP/Bxfriqq8TFcGAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1152x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(16,12),\n",
    "    facecolor=\"white\"\n",
    ")\n",
    "fig.suptitle(\n",
    "    \"Weight - height relationship [MADE UP]\",\n",
    "    fontsize=24,\n",
    ")\n",
    "\n",
    "h, xedges, yedges, img = ax.hist2d(\n",
    "    data_height,\n",
    "    data_weight,\n",
    "    bins=[12, 8],\n",
    "    edgecolor=\"white\",\n",
    "    cmap=\"plasma\"\n",
    ")\n",
    "fig.colorbar(img)\n",
    "\n",
    "# set ticks\n",
    "ax.set_xticks(xedges)\n",
    "ax.set_xticklabels([f\"{value:.1f}\" for value in xedges])\n",
    "ax.set_yticks(yedges)\n",
    "ax.set_yticklabels([f\"{value:.1f}\" for value in yedges])\n",
    "\n",
    "# labels\n",
    "ax.set_xlabel (\n",
    "    \"heights\",\n",
    "    fontsize=16\n",
    ")\n",
    "ax.set_ylabel(\n",
    "    \"weights\",\n",
    "    fontsize=16\n",
    ")\n",
    "\n",
    "# Update font size of the 'x' and 'y' axis labels\n",
    "ax.tick_params(\n",
    "    axis=\"both\",\n",
    "    labelsize=16\n",
    ")\n",
    "\n",
    "# Remove spines\n",
    "for position in [\"top\", \"right\"]:\n",
    "    ax.spines[position].set_visible(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.savefig(\n",
    "    fname=\"plot8.png\",\n",
    "    format=\"png\",\n",
    "    dpi=125\n",
    ");"
   ]
  }
 ],
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