solver_test_swe.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyro import Pyro\n",
    "solver = \"swe\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Acoustic pulse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "problem_name = \"acoustic_pulse\"\n",
    "param_file = \"inputs.acoustic_pulse\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the acoustic pulse problem...\u001b[0m\n",
      "cc data: nx = 8, ny = 8, ng = 4\n",
      "         nvars = 4\n",
      "         variables:\n",
      "          height: min:    1.4000000000    max:    1.4977377908\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "      x-momentum: min:    0.0000000000    max:    0.0000000000\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "      y-momentum: min:    0.0000000000    max:    0.0000000000\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "            fuel: min:    1.3086402787    max:    1.4977377908\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:3285: UserWarning: Attempting to set identical bottom==top results\n",
      "in singular transformations; automatically expanding.\n",
      "bottom=0.0, top=0.0\n",
      "  'bottom=%s, top=%s') % (bottom, top))\n"
     ]
    },
    {
     "data": {
      "image/png": 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XwSTaSdLT0xEQEACFQoHg4GAcOXLEbHxaWhq6dOmC5s2bw9fXF7Nnz8Yvv/zipNESkS10AHSQWCgPFBUVQavViiUhIaFOxnDp0iXMmzcPW7duhUxm+kvGuXPnYsKECejatSuaNWuGp556CnFxcZgwYUKdjIGIyJVwOYcT7NixA3FxcUhPT0fv3r2xdu1aREZG4ty5c/Dz8zOK37p1K+bNm4eNGzciPDwcFy9exKRJkwAA77//vpNHT0SW/Ham2VwMACiVSiiVyjo9v06nQ1RUFBYvXownnnii1rgdO3Zgy5Yt2LZtG/74xz+ioKAAcXFx8PHxwcSJE+t0TERETR2TaCdITU3F5MmTMWXKFAAPZpn37duH1atXm/wqNycnB71790ZUVBSAB+sWJ0yYgJMnT9Z6joqKClRUVIifH153SUSOU9/7RN+5cwcajQb5+fmYMWMGAECv10MQBMhkMmRlZeH555/HX/7yF8ybNw/jx48HAHTv3h3Xrl1DcnKyQ5Jo3peIqCnjcg4Hq6ysRF5eHiIiIgzqIyIicPz4cZN9nn32WeTl5YlJ8/fff4+9e/eKDwOZkpycbLDO0tfXt+4ugojMqhakqLJQqi08eGgPpVKJs2fPoqCgQCwxMTHo0qULCgoKEBoaCgC4f/8+3NwMb/tSqdRhW9zxvkRETRlnoh3s5s2b0Ol08PLyMqj38vJCSUmJyT7jx4/HjRs38Oyzz0IQBFRXV+ONN97AvHnzaj1PQkIC4uPjxc/l5eX8hUXkJNbsA23rPtF3797Fd999J36+cuUKCgoK0LZtW/j5+SEhIQHXr1/H5s2b4ebmhqCgIIP+np6eUCgUBvUjRozAkiVL4Ofnhz/+8Y/Iz89HamoqXnvtNZvGZi3el4ioKWMS7SQSieEvUEEQjOpqHDx4EEuWLEF6ejpCQ0Px3XffYdasWWjfvj0WLlxosk9t22QRkeM54o2FGo0G/fv3Fz/XJKMTJ05ERkYGiouLUVhYaNMxV65ciYULFyI2NhalpaXw8fHBtGnT8O6779p0HGvxvkRETRmTaAfz8PCAVCo1mnUuLS01mp2usXDhQqjVanENdffu3XHv3j28/vrrmD9/vtHXsURUvxwxE92vXz8Iv+4tbUpGRobZ/omJiUhMTDSoa9WqFdLS0pCWlmbTWIiIyBizMQdzd3dHcHAwsrOzDeqzs7MRHh5usk9t6xYFQTD7S5WI6of+1zcSWipERNR0cCbaCeLj46FWqxESEoKwsDCsW7cOhYWFiImJAQBER0ejQ4cO4k4dI0aMQGpqKp566ilxOcfChQsxcuRISKWOeziJiB6NTpBAZ2Gm2VI7ERE1LkyinWDcuHG4desWkpKSUFxcjKCgIOzduxf+/v4AgMLCQoOZ5wULFkAikWDBggW4fv06fve734kPBBFRw6PTS1GtN/8PXJ2DdsAgIqL6wSTaSWJjYxEbG2uy7eDBgwafZTIZFi1aVOure4moYal5K6GlGCIiajqYRBMR2UkvWH5wUM/HGYiImhQm0UREdrLltd9ERNQ0MImmRkXaWuW0c/3c6wmnncuZmudedMp5dLe1TjlPQ6CHBHoLyzUstRMRUePCJJqIyE5VeikkFh4srLLQTkREjQuTaCIiO+lhxctWOBNNRNSkMIkmIrKTYMVyDoFJNBFRk8IkmojITo547TcRETVsTKKJiOzE3TmIiFwPk2giIjtVC26QWEiSq5lEExE1KUyiiYjsxOUcRESuh1MjRER2qkmiLRUiosYuPT0dAQEBUCgUCA4OxpEjR8zG79q1C926dYNcLke3bt2we/dug3ZBEJCYmAgfHx80b94c/fr1w7fffmsQU1ZWBrVaDZVKBZVKBbVajdu3b5s833fffYdWrVqhdevW9l2oFZhEExHZiUk0EbmCHTt2IC4uDvPnz0d+fj769OmDyMhIFBYWmozPycnBuHHjoFarcebMGajVaowdOxYnTpwQY1JSUpCamopVq1bh1KlT8Pb2xqBBg3Dnzh0xJioqCgUFBcjMzERmZiYKCgqgVquNzldVVYUJEyagT58+dX/xJjCJJiKyE5NoInIFqampmDx5MqZMmYLAwECkpaXB19cXq1evNhmflpaGQYMGISEhAV27dkVCQgIGDBiAtLQ0AA9modPS0jB//ny8+OKLCAoKwscff4z79+9j27ZtAIDz588jMzMTH330EcLCwhAWFob169fjq6++woULFwzOt2DBAnTt2hVjx4517A/iV0yiiYjspBMkqBbczBYdk2giaoDKy8sNSkVFhcm4yspK5OXlISIiwqA+IiICx48fN9knJyfHKH7w4MFi/JUrV1BSUmIQI5fL0bdvXzEmJycHKpUKoaGhYkyvXr2gUqkMznvgwAHs3LkTH374oQ1Xbx8m0UREduJMNBE1Vr6+vuJaY5VKheTkZJNxN2/ehE6ng5eXl0G9l5cXSkpKTPYpKSkxG1/zp6UYT09Po2N7enqKMbdu3cKkSZOQkZEBpVJp6ZLrDHfnICKyE3fnIKLGqqioyCDxlMvlZuMlEsN7mSAIRnW2xluKMXX838ZMnToVUVFReO6558yOva5xJpqIyE6ciSaixkqpVBqU2pJoDw8PSKVSo1nn0tJSo5nkGt7e3mbjvb29AcBizI8//mh07Bs3bogxBw4cwIoVKyCTySCTyTB58mRotVrIZDJs3LjR0o/gkTGJJiKykyBIrCpERI2Vu7s7goODkZ2dbVCfnZ2N8PBwk33CwsKM4rOyssT4gIAAeHt7G8RUVlbi0KFDYkxYWBi0Wi1Onjwpxpw4cQJarVaMycnJQUFBgViSkpLQqlUrFBQU4IUXXrD/4mvB5RxERHaqFtwAvrGQiJq4+Ph4qNVqhISEICwsDOvWrUNhYSFiYmIAANHR0ejQoYO4rnrWrFl47rnnsGzZMowaNQqff/459u/fj6NHjwJ4sEwjLi4OS5cuRefOndG5c2csXboULVq0QFRUFAAgMDAQQ4YMwdSpU7F27VoAwOuvv47hw4ejS5cuYsxvaTQauLm5ISgoyKE/DybRRER2smammTPRRNTYjRs3Drdu3UJSUhKKi4sRFBSEvXv3wt/fHwBQWFgIN7f/mzAIDw/H9u3bsWDBAixcuBCPP/44duzYYbDTxttvv42ff/4ZsbGxKCsrQ2hoKLKystCqVSsxZuvWrZg5c6a4i8fIkSOxatUqJ1117SSCIAj1PQiqe+Xl5VCpVOiHUZBJmtX3cOqMtLXKaef6udcTTjuXMzXPveiU8+hua51yHmeqFqpwEJ9Dq9VCqVSKf89C/hEHWUvzD+NU36uA5sU0sa8raqr3JaL6VNt9ydK9xto4qh1noomI7MSZaCIi18MkmojIToIVu28wiSYialqYRBMR2UkHCWAhSdaBSTQRUVPCJJqIyE5czkFE5HqYRBMR2UkvSCDhGwuJiFwKk2giIjsJwoNiKYaIiJoOJtFERHbicg4iItfDV2gREdlJp3ezqtji8OHDGDFiBHx8fCCRSLBnzx6r+x47dgwymQw9e/Y0art+/TpeeeUVtGvXDi1atEDPnj2Rl5dn09iIiIgz0VRXJM6ZZXPmC1D+tXG9087lTP1fm+qU87jv0zjlPADqfa2EI5Zz3Lt3Dz169MCrr76KMWPGWN1Pq9UiOjoaAwYMwI8//mjQVlZWht69e6N///745z//CU9PT1y+fBmtW7e2bXBERMQkmojIXg+SaEvLOWw7ZmRkJCIjI20ey7Rp0xAVFQWpVGo0e71s2TL4+vpi06ZNYl3Hjh1tPgcREXE5h9Okp6cjICAACoUCwcHBOHLkiNn427dvY/r06Wjfvj0UCgUCAwOxd+9eJ42WiGxRsybaUgEevGr3t6WioqLOxrFp0yZcvnwZixYtMtn+xRdfICQkBH/+85/h6emJp556CuvXN81vXIiIHI1JtBPs2LEDcXFxmD9/PvLz89GnTx9ERkaisLDQZHxlZSUGDRqEq1ev4rPPPsOFCxewfv16dOjQwckjJyJrCFYWAPD19YVKpRJLcnJynYzh0qVLmDdvHrZu3QqZzPSXjN9//z1Wr16Nzp07Y9++fYiJicHMmTOxefPmOhkDEZEr4XIOJ0hNTcXkyZMxZcoUAEBaWhr27duH1atXm/wFunHjRvz00084fvw4mjVrBgDw9/d36piJyHqCXgJBb2E5x6/tRUVFUCqVYr1cLrf7/DqdDlFRUVi8eDGeeKL25wb0ej1CQkKwdOlSAMBTTz2Fb7/9FqtXr0Z0dLTd4yAiciWciXawyspK5OXlISIiwqA+IiICx48fN9nniy++QFhYGKZPnw4vLy8EBQVh6dKl0Ol0tZ6noqLC6GtiInISa5Zy/LqcQ6lUGpS6SKLv3LkDjUaDGTNmQCaTQSaTISkpCWfOnIFMJsOBAwcAAO3bt0e3bt0M+gYGBtb6rZi9eF8ioqaMM9EOdvPmTeh0Onh5eRnUe3l5oaSkxGSf77//HgcOHMDLL7+MvXv34tKlS5g+fTqqq6vx7rvvmuyTnJyMxYsX1/n4iciy+n7ZilKpxNmzZw3q0tPTceDAAXz22WcICAgAAPTu3RsXLlwwiLt48aLDvunifYmImjIm0U4ieWgLOEEQjOpq6PV6eHp6Yt26dZBKpQgODsYPP/yA5cuX15pEJyQkID4+XvxcXl4OX1/fursAIqqVI162cvfuXXz33Xfi5ytXrqCgoABt27aFn58fEhIScP36dWzevBlubm4ICgoy6O/p6QmFQmFQP3v2bISHh2Pp0qUYO3YsTp48iXXr1mHdunU2jc1avC8RUVPGJNrBPDw8IJVKjWadS0tLjWana7Rv3x7NmjWDVCoV6wIDA1FSUoLKykq4u7sb9ZHL5XXytTARPYLfLNcwG2MDjUaD/v37i59rktGJEyciIyMDxcXFNi/D+NOf/oTdu3cjISEBSUlJCAgIQFpaGl5++WWbjmMt3peIqCljEu1g7u7uCA4ORnZ2Nl544QWxPjs7G6NGjTLZp3fv3ti2bRv0ej3c3B4sW7948SLat29vMoEmovol6B8USzG26NevHwQza0AyMjLM9k9MTERiYqJR/fDhwzF8+HDbBkNEREb4YKETxMfH46OPPsLGjRtx/vx5zJ49G4WFhYiJiQEAREdHIyEhQYx/4403cOvWLcyaNQsXL17E119/jaVLl2L69On1dQlEZIYt+0QTEVHTwJloJxg3bhxu3bqFpKQkFBcXIygoCHv37hUf5iksLBRnnIEH+8hmZWVh9uzZePLJJ9GhQwfMmjULc+fOra9LICJL6vfN40RE5GRMop0kNjYWsbGxJtsOHjxoVBcWFobc3FwHj4qI6oIjHiwkIqKGjUk0EZG9fvtKQnMxRETUZDCJJiKylwN25yAiooaNSTQRkb04E01E5HKYRBMR2Ysz0URELodJNBGRner7td9EROR8TKKJiOzF5RxERC6HSTQRkZ0kegkkevPLNSy1ExFR48IkmojIXpyJJiJyOUyiiYjsxQcLiYhcDpNoIiJ7cSaaiMjlMIkmIrIXk2giIpfjVt8DICJq9AQrCxFRI5eeno6AgAAoFAoEBwfjyJEjZuN37dqFbt26QS6Xo1u3bti9e7dBuyAISExMhI+PD5o3b45+/frh22+/NYgpKyuDWq2GSqWCSqWCWq3G7du3DWLOnj2Lvn37onnz5ujQoQOSkpIgOHhvUSbRtZg0aRIOHz5c38MgokagZncOS4WIqDHbsWMH4uLiMH/+fOTn56NPnz6IjIxEYWGhyficnByMGzcOarUaZ86cgVqtxtixY3HixAkxJiUlBampqVi1ahVOnToFb29vDBo0CHfu3BFjoqKiUFBQgMzMTGRmZqKgoABqtVpsLy8vx6BBg+Dj44NTp05h5cqVWLFiBVJTUx33wwCXc9Tqzp07iIiIgK+vL1599VVMnDgRHTp0qO9hEVFDxOUcRNTAjFJFQyZpVmt7tVAF4EEC+ltyuRxyudxkn9TUVEyePBlTpkwBAKSlpWHfvn1YvXo1kpOTjeLT0tIwaNAgJCQkAAASEhJw6NAhpKWl4dNPP4UgCEhLS8P8+fPx4osvAgA+/vhjeHl5Ydu2bZg2bRrOnz+PzMxICf2EAAAgAElEQVRM5ObmIjQ0FACwfv16hIWF4cKFC+jSpQu2bt2KX375BRkZGZDL5QgKCsLFixeRmpqK+Ph4SCSOmcTgTHQtdu3ahevXr2PGjBnYuXMnOnbsiMjISHz22Weoqqqq7+ERERER2c3X11dcJqFSqUwmwwBQWVmJvLw8REREGNRHRETg+PHjJvvk5OQYxQ8ePFiMv3LlCkpKSgxi5HI5+vbtK8bk5ORApVKJCTQA9OrVCyqVyiCmb9++Bsn/4MGD8cMPP+Dq1atW/iRsxyTajHbt2mHWrFnIz8/HyZMn8Yc//AFqtRo+Pj6YPXs2Ll26VN9DJKIGQAJAIlgo9T1IIiITioqKoNVqxVIza/ywmzdvQqfTwcvLy6Dey8sLJSUlJvuUlJSYja/501KMp6en0bE9PT0NYkwd47fncAQu57BCcXExsrKykJWVBalUiqFDh+Lbb79Ft27dkJKSgtmzZ9f3EImoPnGfaCJqYD7XboZSqay1vby8HCqVCkql0mzcwx5eGiEIgtnlEtbEW4oxdXxLMTUPFTpqKQfAmehaVVVVYdeuXRg+fDj8/f2xc+dOzJ49G8XFxfj444+RlZWFTz75BElJSfU9VCKqb3orCxFRI+Xh4QGpVGo0s1taWmo0C1zD29vbbLy3tzcA49nih2N+/PFHo2PfuHHDIMbUMQDjWe66xCS6Fu3bt8fUqVPh7++PkydPQqPRICYmBq1atRJjBg8ejNatW9fjKImoIbC4lOPXQkTUWLm7uyM4OBjZ2dkG9dnZ2QgPDzfZJywszCg+KytLjA8ICIC3t7dBTGVlJQ4dOiTGhIWFQavV4uTJk2LMiRMnoNVqDWIOHz6MyspKg/P4+PigY8eOj37RFnA5Ry3ef/99/PnPf4ZCoag1pk2bNrhy5YoTR0VEDRJ35yAiFxAfHw+1Wo2QkBCEhYVh3bp1KCwsRExMDAAgOjoaHTp0EB9OnDVrFp577jksW7YMo0aNwueff479+/fj6NGjAB4stYiLi8PSpUvRuXNndO7cGUuXLkWLFi0QFRUFAAgMDMSQIUMwdepUrF27FgDw+uuvY/jw4ejSpQuAB1vgLV68GJMmTcI777yDS5cuYenSpXj33XcdupyDSXQtfrv/IBGRWUyiicgFjBs3Drdu3UJSUhKKi4sRFBSEvXv3wt/fHwBQWFgIN7f/W+QQHh6O7du3Y8GCBVi4cCEef/xx7Nixw2Cnjbfffhs///wzYmNjUVZWhtDQUGRlZRl8879161bMnDlT3MVj5MiRWLVqldiuUqmQnZ2N6dOnIyQkBG3atEF8fDzi4+Md+vNgEk1EZCdrlmtwOQcRNQWxsbGIjY012Xbw4EGjupdeegkvvfRSrceTSCRITExEYmJirTFt27bFli1bzI6re/fuTn9JHpNoIiJ76SUPiqUYIiJqMphEExHZiTPRRESuh0k0EZG9uCaaiMjlMIkmIrKXNVvYMYkmImpSmEQTEdmLM9FERC6HSTQRkZ0k+gfFUgwRETUdfGMhEREREZGNOBNNRGQvLucgInI5nIkmIrJTzRZ3lootDh8+jBEjRsDHxwcSiQR79uyxuu+xY8cgk8nQs2fPWmOSk5PFV+4SEZHtmEQTEdUFwUKx0b1799CjRw+DV9taQ6vVIjo6GgMGDKg15tSpU1i3bh2efPJJ2wdGREQAmEQ7TXp6OgICAqBQKBAcHIwjR45Y1W/79u2QSCQYPXq0g0dIRI+q5sFCS8UWkZGReO+99/Diiy/a1G/atGmIiopCWFiYyfa7d+/i5Zdfxvr169GmTRvbBkVERCIm0U6wY8cOxMXFYf78+cjPz0efPn0QGRmJwsJCs/2uXbuGOXPmoE+fPk4aKRE9Ekuz0L+ZjS4vLzcoFRUVdTaMTZs24fLly1i0aFGtMdOnT8ewYcMwcODAOjsvEZErYhLtBKmpqZg8eTKmTJmCwMBApKWlwdfXF6tXr661j06nw8svv4zFixejU6dOThwtEdnKljXRvr6+UKlUYklOTq6TMVy6dAnz5s3D1q1bIZOZfmZ8+/btOH36dJ2dk4jIlXF3DgerrKxEXl4e5s2bZ1AfERGB48eP19ovKSkJv/vd7zB58mSrln5UVFQYzGiVl5c/+qCJyDY27M5RVFQEpVIpVsvlcrtPr9PpEBUVhcWLF+OJJ54wGVNUVIRZs2YhKysLCoXC7nNag/clImrKmEQ72M2bN6HT6eDl5WVQ7+XlhZKSEpN9jh07hg0bNqCgoMDq8yQnJ2Px4sV2jZWIHpENSbRSqTRIouvCnTt3oNFokJ+fjxkzZgAA9Ho9BEGATCZDVlYWysvLUVpaiuDgYLGfTqfD4cOHsWrVKlRUVEAqldbpuHhfIqKmjEm0k0gkEoPPgiAY1QEPfhm+8sorWL9+PTw8PKw+fkJCAuLj48XP5eXl8PX1ffQBE5HV6vuNhUqlEmfPnjWoS09Px4EDB/DZZ58hICAAer3eKObVV19F165dMXfu3DpPoAHel4ioaWMS7WAeHh6QSqVGs86lpaVGs9MAcPnyZVy9ehUjRowQ6/T6B799ZTIZLly4gMcff9yon1wur5OvhYnoETjgZSt3797Fd999J36+cuUKCgoK0LZtW/j5+SEhIQHXr1/H5s2b4ebmhqCgIIP+np6eUCgUBvUPx7Rs2RLt2rUzqq8rvC8RUVPGJNrB3N3dERwcjOzsbLzwwgtifXZ2NkaNGmUU37VrV6PZogULFuDOnTv4+9//zlkcogbImpep2PqyFY1Gg/79+4ufa2Z0J06ciIyMDBQXF1vc4YeIiByHSbQTxMfHQ61WIyQkBGFhYVi3bh0KCwsRExMDAIiOjkaHDh2QnJxsNHMEAK1btwZgPIvUoAjOeadx89yLTjkPAPR/barTzuVMzvoZ6pz030SD4ICZ6H79+kEw8zPMyMgw2z8xMRGJiYlmYw4ePGjboIiISMQk2gnGjRuHW7duISkpCcXFxQgKCsLevXvh7+8PACgsLISbG3cbJGqsHDETTUREDRuTaCeJjY1FbGysyTZLs0GWZpyIqJ7pfy2WYoiIqMlgEk1EZCfJr8VSDBERNR1MoomI7OWANdFERNSwMYkmIrIT10QTEbkeJtFERPbiTDQRkcthEk1EZCeJYMUbC5lEExE1KUyiiYjsxZloIiKXwySaiMhOXBNNROR6mEQTEdmLM9FERC6HSTQRkZ04E01E5HqYRBMR2YtvLCQicjlMoomI7MSZaCIi1+NW3wMgImr0BCsLEZGLKCsrg1qthkqlgkqlglqtxu3bt832qaiowJtvvgkPDw+0bNkSI0eOxP/+9z+DmMLCQowYMQItW7aEh4cHZs6cicrKSoOYQ4cOITg4GAqFAp06dcKaNWtqPWdycjIkEgni4uJsvkYm0UREdpIIglWFiMhVREVFoaCgAJmZmcjMzERBQQHUarXZPnFxcdi9eze2b9+Oo0eP4u7duxg+fDh0Oh0AQKfTYdiwYbh37x6OHj2K7du3Y9euXXjrrbfEY1y5cgVDhw5Fnz59kJ+fj3feeQczZ87Erl27jM536tQprFu3Dk8++eQjXSOXcxAR2Yu7cxBRI1VeXm7wWS6XQy6X23XM8+fPIzMzE7m5uQgNDQUArF+/HmFhYbhw4QK6dOli1Eer1WLDhg345JNPMHDgQADAli1b4Ovri/3792Pw4MHIysrCuXPnUFRUBB8fHwDA3/72N0yaNAlLliyBUqnEmjVr4Ofnh7S0NABAYGAgNBoNVqxYgTFjxojnu3v3Ll5++WWsX78e77333iNdJ2eiiYjsJNFbV4iIGhpfX19xyYVKpUJycrLdx8zJyYFKpRITaADo1asXVCoVjh8/brJPXl4eqqqqEBERIdb5+PggKChI7JOTk4OgoCAxgQaAwYMHo6KiAnl5eWLMb49RE6PRaFBVVSXWTZ8+HcOGDRMT9kfBmWgiIjvxwUIiaqyKioqgVCrFz/bOQgNASUkJPD09jeo9PT1RUlJSax93d3e0adPGoN7Ly0vsU1JSAi8vL4P2Nm3awN3d3WyMl5cXqqurcfPmTbRv3x7bt2/H6dOncerUqUe+RoAz0URE9uODhUTUSCmVSoNiLolOTEyERCIxWzQaDQBAIpEY9RcEwWS9OQ/3sea4D8cIvz6TIpFIUFRUhFmzZmHLli1QKBQ2jeVhnIkmIrITZ6KJyBXMmDED48ePNxvTsWNH/Pvf/8aPP/5o1Hbjxg2jWeIa3t7eqKysRFlZmcFsdGlpKcLDw8WYEydOGPQrKytDVVWVeFxvb2+j2e7S0lLIZDK0a9cOX3/9NUpLSxEcHCy263Q6HD58GKtWrUJFRQWkUqnZa6zBJJqIyF58sJCIXICHhwc8PDwsxoWFhUGr1eLkyZN45plnAAAnTpyAVqsVE+KHBQcHo1mzZsjOzsbYsWMBAMXFxfjPf/6DlJQU8bhLlixBcXEx2rdvDwDIysqCXC4Xk+KwsDB8+eWXBsfOyspCSEgImjVrhgEDBuDs2bMG7a+++iq6du2KuXPnWp1AA1zOQURUJ2pmo2srRESuIjAwEEOGDMHUqVORm5uL3NxcTJ06FcOHDxd35rh+/Tq6du2KkydPAgBUKhUmT56Mt956C9988w3y8/PxyiuvoHv37uLDfxEREejWrRvUajXy8/PxzTffYM6cOZg6daq4rjsmJgbXrl1DfHw8zp8/j40bN2LDhg2YM2cOAKBVq1YICgoyKC1btkS7du0QFBRk03UyiSYispNEL1hViIhcxdatW9G9e3dEREQgIiICTz75JD755BOxvaqqChcuXMD9+/fFuvfffx+jR4/G2LFj0bt3b7Ro0QJffvmlODsslUrx9ddfQ6FQoHfv3hg7dixGjx6NFStWiMcICAjA3r17cfDgQfTs2RN//etf8cEHHxhsb1dXuJyDiMheXM5BRGSgbdu22LJlS63tHTt2FB/4q6FQKLBy5UqsXLmy1n5+fn746quvzJ67b9++OH36tNVjPXjwoNWxv8UkmojITtbsA819oomImhYm0URE9uJMNBGRy2ESTY2K7rbWaedy36dx2rmcSScwm6tr3OKOiMj1MIkmIrKTNQ8O8sFCIqKmhUk0EZG9uJyDiMjlMIkmIrITl3MQEbkeJtFERPYShAfFUgwRETUZTKKJiOzEmWgiItfDJJqIyE7cJ5qIyPXwtd9ERPbSC9YVGxw+fBgjRoyAj48PJBIJ9uzZY3XfY8eOQSaToWfPngb1ycnJ+NOf/oRWrVrB09MTo0ePxoULF2waFxERPcAk2knS09MREBAAhUKB4OBgHDlypNbY9evXo0+fPmjTpg3atGmDgQMH4uTJk04cLRHZRLCy2ODevXvo0aMHVq1aZVM/rVaL6OhoDBgwwKjt0KFDmD59OnJzc5GdnY3q6mpERETg3r17tg2OiIi4nMMZduzYgbi4OKSnp6N3795Yu3YtIiMjce7cOfj5+RnFHzx4EBMmTEB4eDgUCgVSUlIQERGBb7/9Fh06dKiHKyAicySwYk20jceMjIxEZGSkzWOZNm0aoqKiIJVKjWavMzMzDT5v2rQJnp6eyMvLw3PPPWfzuYiIXBlnop0gNTUVkydPxpQpUxAYGIi0tDT4+vpi9erVJuO3bt2K2NhY9OzZE127dsX69euh1+vxzTffOHnkRGSVmt05LBUA5eXlBqWioqLOhrFp0yZcvnwZixYtsipeq33wBtC2bdvW2RiIiFwFk2gHq6ysRF5eHiIiIgzqIyIicPz4cauOcf/+fVRVVZn9RVdRUWH0y5mInKPmwUJLBQB8fX2hUqnEkpycXCdjuHTpEubNm4etW7dCJrP8JaMgCIiPj8ezzz6LoKCgOhnDw3hfIqKmjMs5HOzmzZvQ6XTw8vIyqPfy8kJJSYlVx5g3bx46dOiAgQMH1hqTnJyMxYsX2zVWIno0EkGAxMI+0DXtRUVFUCqVYr1cLrf7/DqdDlFRUVi8eDGeeOIJq/rMmDED//73v3H06FG7z18b3peIqCnjTLSTSCSGKyIFQTCqMyUlJQWffvop/vGPf0ChUNQal5CQAK1WK5aioiK7x0xEVtJbWQAolUqDUhdJ9J07d6DRaDBjxgzIZDLIZDIkJSXhzJkzkMlkOHDggEH8m2++iS+++AL/+te/8Pvf/97u89eG9yUiaso4E+1gHh4ekEqlRrPOpaWlRrPTD1uxYgWWLl2K/fv348knnzQbK5fL6+SXMRHZzpaZaEdQKpU4e/asQV16ejoOHDiAzz77DAEBAQAe/OP9zTffxO7du3Hw4EGx3lF4XyKipoxJtIO5u7sjODgY2dnZeOGFF8T67OxsjBo1qtZ+y5cvx3vvvYd9+/YhJCTEGUMlokdlzRZ2NubQd+/exXfffSd+vnLlCgoKCtC2bVv4+fkhISEB169fx+bNm+Hm5ma0rtnT0xMKhcKgfvr06di2bRs+//xztGrVSvzHvUqlQvPmzW0bIBGRi2MS7QTx8fFQq9UICQlBWFgY1q1bh8LCQsTExAAAoqOj0aFDB/EBo5SUFCxcuBDbtm1Dx44dxV90jz32GB577LF6uw4iMk2iFyCx8DIVS+0P02g06N+/v/g5Pj4eADBx4kRkZGSguLgYhYWFNh2zZkegfv36GdRv2rQJkyZNsulYRESujkm0E4wbNw63bt1CUlISiouLERQUhL1798Lf3x8AUFhYCDe3/1uenp6ejsrKSrz00ksGx1m0aBESExOdOXQissZvtrAzG2ODfv36QTDTJyMjw2z/xMREo/uFueMREZFtmEQ7SWxsLGJjY022HTx40ODz1atXHT8gIqozv93CzlwMERE1HUyiiYjs5YCZaCIiatiYRBMR2csBDxYSEVHDxiSaiMhOEr0eEr359RqW2omIqHFhEk1EZC8B4stUzMYQEVGTwSSaiMhO9f2yFSIicj4m0URE9hJgxYOFThkJERE5CZNoIiJ7cXcOIiKXwySaiMhOEp0AiYWpZomOSTQRUVPCJJqoNpw5JGtxJpqIyOUwiSYisheTaCIil+NW3wMgImr0apJoS4WIyEWUlZVBrVZDpVJBpVJBrVbj9u3bZvtUVFTgzTffhIeHB1q2bImRI0fif//7n0FMYWEhRowYgZYtW8LDwwMzZ85EZWWlQcyhQ4cQHBwMhUKBTp06Yc2aNQbt1dXVWLBgAQICAtC8eXN06tQJSUlJ0Nu4nz+TaCIie+mtLERELiIqKgoFBQXIzMxEZmYmCgoKoFarzfaJi4vD7t27sX37dhw9ehR3797F8OHDodPpAAA6nQ7Dhg3DvXv3cPToUWzfvh27du3CW2+9JR7jypUrGDp0KPr06YP8/Hy88847mDlzJnbt2iXGLFu2DGvWrMGqVatw/vx5pKSkYPny5Vi5cqVN18jlHEREdpLo9ZBI+MZCIiIAOH/+PDIzM5Gbm4vQ0FAAwPr16xEWFoYLFy6gS5cuRn20Wi02bNiATz75BAMHDgQAbNmyBb6+vti/fz8GDx6MrKwsnDt3DkVFRfDx8QEA/O1vf8OkSZOwZMkSKJVKrFmzBn5+fkhLSwMABAYGQqPRYMWKFRgzZgwAICcnB6NGjcKwYcMAAB07dsSnn34KjUZj03VyJpqIyF56wbpCRNTAlJeXG5SKigq7j5mTkwOVSiUm0ADQq1cvqFQqHD9+3GSfvLw8VFVVISIiQqzz8fFBUFCQ2CcnJwdBQUFiAg0AgwcPRkVFBfLy8sSY3x6jJkaj0aCqqgoA8Oyzz+Kbb77BxYsXAQBnzpzB0aNHMXToUJuukzPRRET24oOFRNRI+fr6GnxetGgREhMT7TpmSUkJPD09jeo9PT1RUlJSax93d3e0adPGoN7Ly0vsU1JSAi8vL4P2Nm3awN3d3WyMl5cXqqurcfPmTbRv3x5z586FVqtF165dIZVKodPpsGTJEkyYMMGm62QSTURkN2seHGQSTUQNT1FREZRKpfhZLpfXGpuYmIjFixebPd6pU6cAABKJxKhNEAST9eY83Mea4z4cI/x6f66p37FjB7Zs2YJt27bhj3/8IwoKChAXFwcfHx9MnDjR6rExiSYishdnoomokVIqlQZJtDkzZszA+PHjzcZ07NgR//73v/Hjjz8atd24ccNolriGt7c3KisrUVZWZjAbXVpaivDwcDHmxIkTBv3KyspQVVUlHtfb29totru0tBQymQzt2rUDAPzlL3/BvHnzxGvp3r07rl27huTkZCbRREROpdMBgs58jN5COxFRA+fh4QEPDw+LcWFhYdBqtTh58iSeeeYZAMCJEyeg1WrFhPhhwcHBaNasGbKzszF27FgAQHFxMf7zn/8gJSVFPO6SJUtQXFyM9u3bAwCysrIgl8sRHBwsxnz55ZcGx87KykJISAiaNWsGALh//z7c3AwfC5RKpdzijojI6bhPNBGRKDAwEEOGDMHUqVORm5uL3NxcTJ06FcOHDxd35rh+/Tq6du2KkydPAgBUKhUmT56Mt956C9988w3y8/PxyiuvoHv37uJuHREREejWrRvUajXy8/PxzTffYM6cOZg6dao4mx4TE4Nr164hPj4e58+fx8aNG7FhwwbMmTNHHN+IESOwZMkSfP3117h69Sp2796N1NRUvPDCCzZdJ2eiiYjspRdgcc0zd+cgIheydetWzJw5U9wpY+TIkVi1apXYXlVVhQsXLuD+/fti3fvvvw+ZTIaxY8fi559/xoABA5CRkQGpVArgwWzx119/jdjYWPTu3RvNmzdHVFQUVqxYIR4jICAAe/fuxezZs/Hhhx/Cx8cHH3zwgbi9HQCsXLkSCxcuRGxsLEpLS+Hj44Np06bh3XfftekaJYLA6ZGmqLy8HCqVCv0wCjJJs/oeDlGTUC1U4SA+h1arhVKpFP+eDfSZBplb7Q/jAEC1vgL7f1gr9nVFvC8R1b3a7kuW7jXWxlHtOBNNRGQvAVY8WOiUkRARkZMwiSYishcfLCQicjlMoomI7MUt7oiIXA6TaCIiezGJJiJyOUyiiYjsxd05iIhcDpNoIiI7CYIegmB+k35L7URE1LgwiSYispdeD1hKkplEExE1KUyiiYjspdcDEibRRESuhEk0EZG9BCvWRPPBQiKiJoVJNBGRnQS9HoKFmWiuiSYialqYRBMR2Ysz0URELsetvgfgKtLT0xEQEACFQoHg4GAcOXLEbPyuXbvQrVs3yOVydOvWDbt373bSSInIZnrBumKDw4cPY8SIEfDx8YFEIsGePXus7nvs2DHIZDL07NnTqM3WexEREZnGJNoJduzYgbi4OMyfPx/5+fno06cPIiMjUVhYaDI+JycH48aNg1qtxpkzZ6BWqzF27FicOHHCySMnImsIOj0Enc5CsW05x71799CjRw+sWrXKpn5arRbR0dEYMGCAUZut9yIiIqqdRBD4HaOjhYaG4umnn8bq1avFusDAQIwePRrJyclG8ePGjUN5eTn++c9/inVDhgxBmzZt8Omnn5o8R0VFBSoqKsTPWq0Wfn5+eBZDIUOzOrwaItdVjSocxV7cvn0bKpUKWq0WrVu3Rh+3EZBJzP89qxaqcET/JQoLC6FSqcR6uVwOuVxutq9EIsHu3bsxevRoi2McP348OnfuDKlUij179qCgoEBss/VeZC/el4gcr7b7UlFREZRKZa39ysvL4evrK/ajRyCQQ1VUVAhSqVT4xz/+YVA/c+ZM4bnnnjPZx9fXV0hNTTWoS01NFfz8/Go9z6JFi2oWZbKwsDi4XL58WRAEQSgqKrL7WIsWLbJ4HwEg7N6922Lcxo0bhZCQEKGqqkpYtGiR0KNHD7HtUe5F9uJ9iYXFeeVR70tFRUUO+fvvCvhgoYPdvHkTOp0OXl5eBvVeXl4oKSkx2aekpMSmeABISEhAfHy8+Pn27dvw9/c3mvVqaGr+JWzpX8wNAcfqGI1prDUzqW3btgUA+Pj4oKioCK1atYJEIjHbVxAE3Lp1C23btoWb2/+tpLM0C22tS5cuYd68eThy5AhkMuNb+6Pci+zF+5LjcayO0ZjG+qj3JUEQcOfOHfj4+DhrqE0Ok2gnefg/ZEEQzP7HbWt8bV8Jq1SqBn8DAAClUtkoxglwrI7SmMZakwS7ubnh97//vdX9HJU46nQ6REVFYfHixXjiiSfMxtp6b7EH70vOw7E6RmMa66PclxryP2YbAybRDubh4QGpVGo001NaWmo0I1TD29vbpngicm137tyBRqNBfn4+ZsyYAQDQ6/UQBAEymQxZWVl49tlnbb4XERFR7bg7h4O5u7sjODgY2dnZBvXZ2dkIDw832ScsLMwoPisrq9Z4InJtSqUSZ8+eRUFBgVhiYmLQpUsXFBQUIDQ09JHuRUREVDtpYmJiYn0PoqlTKpVYuHAhOnToAIVCgaVLl+Jf//oXNm3ahNatWyM6OhonT57EwIEDAQAdOnTAggULIJfL4eHhgQ0bNuCjjz7CunXrbPrqWCqVol+/fibXRzYkjWWcAMfqKByrsbt37+LcuXMoKSnB2rVrERoaiubNm6OyshIqlQoJCQnYvHkzXnjhBUgkEnh6ehqUU6dO4bvvvsO7774Ld3d3AJbvRc7QWP6/bizjBDhWR+FYyaL6fKrRlXz44YeCv7+/4O7uLjz99NPCoUOHxLa+ffsKEydONIjfuXOn0KVLF6FZs2ZC165dhV27djl5xOQoS5YsEQAIp0+fNmpTq9WCVCoVvvrqq3oYGTUk//rXv0w+SV9zr5g4caLQt2/fWvs/vDtHDXP3ImqcnnjiCat2YWjZsqVQXl7ukDEkJCQIAITvv//eZHtAQIAQFhbmkHMT1RfuE03kZOXl5fD398fAgQOxc+dOsf7dd9/FX//6V6Snp+ONN96oxxESUWOSkpKCuXPnYtq0aejatatR+82bN7FkyRJMnjwZH330kUPGMGTIEJw8eRI//fSTUfd7dBgAACAASURBVFtZWRnatm2LGTNmYOXKlQ45P1F94Lw/kZMplUq8+eabWLJkCf773/+ia9eu2LRpE/7617/i7bffZgJNRDaZNGkSFixYAJlMhri4OKP2999/HwAwdepUk/3Ly8tx7NgxREZGmmz/6quv0L9/f7Rs2bLWMZw+fRrBwcEm2zQaDQDU2k7UWPHBQqJ6EBcXhxYtWiA5ORn79+/HtGnTMHbsWPy///f/6ntoRNTIeHp6YsSIEdi2bZvBGyJrbNy4Ed27d0doaKjJ/h999BGGDx+Ojz/+2Kht7dq1GDlyJDZv3lzr+QsLC3Hjxg2EhISYbM/LywPAJJqaHibRRPWgbdu2eOONN7Bt2zaMGTMGoaGh2Lx5s8P26yWipm3q1KkoKyvD7t27DepPnDiB//znP5gyZUqtfePj4xEXF4dXX30Va9euFev//ve/IyYmBgkJCWa/IbOUJGs0GigUCgQGBtpySUQNHpdzENWTCRMmYPny5Xjsscfw+eef19mb64jI9URERMDPzw8bNmzA+PHjxfqNGzdCoVBArVab7f+3v/0NCoUCMTEx+OWXX/DLL79g3rx5SEpKwsKFC832PX36NACYnYnu0aMHd46gJof/RRPVg/Lycrz66qsAHjz0c//+ffGVrUREtnJzc8Nrr72GxYsX49q1a/D398f9+/exfft2jBkzBm3atLF4jCVLlkChUIjrqpcvX445c+ZY7JeXl4e2bduiY8eORm0//fQTrl69iqFDh9p8TUQNHZdzEDlZVVUVxowZg++//x579uyBXq/H8uXL63tYRNTIvfbaa5BIJMjIyAAA7Ny5E+Xl5bU+UGiKVqsVl5Xdvn3bqj75+fno0aOHybbc3FwAwDPPPGP1GIgaCybRRE42ZcoUHDx4EDt37sSoUaPwyiuvYP369SgtLa3voRH9f/buPi7KKu8f+GfkYQYVRhN53FGR5RaIHgw2HVzUtgTFp7TyqcZ0lSJsFck1EdyIbuGlKVIZqKxaoaa/jVVrYxF0b0lXRCVwS83afBhyIdLFAZ9gmLl+fxhXjgPMjAMjMJ/3/Tov7znX97quc/FaTl/OnOsc6sIUCgWioqKwdetWCIKAzZs3IyAgAKNGjTJ5riAIePXVV7Fu3Tps3rwZ2dnZSEtLMzkSrdPpUF1djX79+rV4fM+ePXBwcEBkZOQ9PRNRZ8YkmsiGkpOT8dFHH2HDhg2IiooCACxfvhyNjY3iMlRERPdq/vz5uHjxIjZs2IBDhw61+UJhM71ej5iYGGzcuBHbt2/H3LlzERsbi61btyIzMxMLFixAa1tKODg4wN3dHeXl5dBqtQbHysvL8eGHH2LGjBnw9vZul+cj6ky42QqRjWzatAkvv/wykpOT8dZbbxkcmzlzJvLz83Hx4kWbbb9MRN2PVquFQqHA1atXodfr8cMPP8DDw6PNc9asWYOkpCTs2rULTz/9tMGxXbt24YUXXsC6devw6quvtnj+ypUrkZycjN/97ndQqVRwdnbGiRMnkJ2djUGDBuHQoUNwd3dvt2ck6iyYRBPZQH5+PiZNmoSZM2ciNzfX6PjXX3+Nhx9+GCkpKfjTn/50H1pIRN1FYmIi3n77bUydOhX/7//9P5PxN2/eREVFBZRKZYvH//nPf+I3v/kNnJ2dW73Gtm3b8O677+Ls2bNobGzEr3/9a0ydOhVLliyBq6vrPT8LUWfGJJqIiIiIyEKcE01EREREZCEm0UREREREFmISTURERERkISbRHeyLL77AxIkT4ePjA4lEgj179pg8p7i4GKGhoZDJZBg8eDA2bNhgg5YSERERkbmYRHew69ev45FHHsH69evNij9//jyio6MRERGB8vJyLF++HAsXLkReXl4Ht5SIiIiIzMXVOWxIIpFg9+7dRutw3un111/Hp59+ijNnzoh1sbGxOHnyJEpKSmzRTCIiIiIywfF+N4AMlZSUGG2PGhUVhc2bN0Or1cLJyanF8xoaGtDQ0CB+1uv1+O9//4t+/fpBIpF0aJuJ7IUgCKivr4ePjw969OgBvV6P//znP3B1dTX5e3b3ufaA/RJRx7vXfske+6T2xiS6k6muroanp6dBnaenJ5qamnD58uVWt05NT0/Hm2++aYsmEtm9yspK/OpXv8J//vMfKBSKezrXHrBfIrKde+2X7KlPam9Mojuhu/9ybJ5x09ZflImJiUhISBA/azQaDBgwAL9FNBzR8ug1EVmmCVocRr64A1vzvxe/HAS33m2P5NRd02PgYxfsavc29ktEHa+1fqmyshJubm6tnldXVweFQmFXfVJ7YxLdyXh5eaG6utqgrqamBo6OjujXr1+r50mlUkilUqN6RzjBUcL/WBG1i5/fIGn+g7b5X5deAlx6t/16idaMP4a7G/ZLRDbQSr/k5ubWZhLdzJ76pPbGSTCdjFKpRFFRkUFdYWEhwsLCWp0PTUT3lx6CWYWIiLoPJtEd7Nq1a6ioqEBFRQWA20vYVVRUQK1WA7j9defs2bPF+NjYWFy8eBEJCQk4c+YMtmzZgs2bN2PJkiX3pf1EZJrezP8jIqLug9M5OtiJEyfwxBNPiJ+b5we++OKL+OCDD1BVVSUm1ADg5+eH/Px8LF68GO+//z58fHzw7rvv4plnnrF524nIPDpBgM7EaqGmjhMRUdfCJLqDjR49Gm0txf3BBx8Y1Y0aNQpffvllB7aKiNqTOdM1OJ2DiKh7YRJNRGSlJuihNSOGiIi6DybRRERW4nQOIiL7wySaiMhK+p+LqRgiIuo+mEQTEVlJBwE6E3OeTR0nIqKuhUk0EZGVdMLtYiqGiIi6DybRRERWaoIEWrS961eTieNERNS1MIkmIrKSXrhdTMUQEVH3wSSaiMhKOkigMzHSbOo4ERF1LUyiiYisxCSaiMj+MIkmIrKSXpBAL7SdJJs6TkREXUuP+90AIqKurhEOZhUioq4uKysLfn5+kMlkCA0NxaFDh9qMz8vLQ3BwMKRSKYKDg7F7926D44IgICUlBT4+PnBxccHo0aNx6tQpg5ja2lqoVCrI5XLI5XKoVCpcvXrVIGbfvn0YPnw4XF1d0b9/fzzzzDM4f/58+zx0K5hEExFZSfh5JLqtInAkmoi6uF27diE+Ph5JSUkoLy9HREQExo0bB7Va3WJ8SUkJpk+fDpVKhZMnT0KlUmHatGkoLS0VY1avXo2MjAysX78ex48fh5eXF8aMGYP6+noxZtasWaioqEBBQQEKCgpQUVEBlUolHj937hwmT56M3/3ud6ioqMC+fftw+fJlTJ06teN+GAAkgsC9aLujuro6yOVyjMZkOEqc7ndziLqFJkGLg9gLjUYDNzc38fes8KuB6OXa9pjE9Xo9Ih+6KJ5rj9gvEbW/1volU32NuXF3GjZsGB577DFkZ2eLdUFBQXj66aeRnp5uFD99+nTU1dXh73//u1g3duxY9O3bFx9//DEEQYCPjw/i4+Px+uuvAwAaGhrg6emJVatW4eWXX8aZM2cQHByMo0ePYtiwYQCAo0ePQqlU4ptvvsGQIUPwySefYObMmWhoaECPHrf74s8++wyTJ09GQ0MDnJw6pr/hSDQRkZV0Qg+zChFRZ1NXV2dQGhoaWoxrbGxEWVkZIiMjDeojIyNx5MiRFs8pKSkxio+KihLjz58/j+rqaoMYqVSKUaNGiTElJSWQy+ViAg0Aw4cPh1wuF2PCwsLg4OCArVu3QqfTQaPRIDc3F5GRkR2WQANMoomIrKaHBHr0MFE4nYOIOh+FQiHONZbL5S2OKAPA5cuXodPp4OnpaVDv6emJ6urqFs+prq5uM775X1MxHh4eRtf28PAQYwYNGoTCwkIsX74cUqkUffr0wQ8//ICdO3eaenyrMIkmIrJSo+BgViEi6mwqKyuh0WjEkpiY2Ga8RGI4ICAIglGdpfGmYlq6/p0x1dXVmD9/Pl588UUcP34cxcXFcHZ2xrPPPouOnLXMJe6IiKx0eyTaxBJ3HIkmok7Izc3NrDnR7u7ucHBwMBp1rqmpMRpJbubl5dVmvJeXF4DbSbC3t3erMT/++KPRtX/66Scx5v3334ebmxtWr14tHt+2bRsUCgVKS0sxfPhwk893LzgSTURkJT16QGei6NndElEX5uzsjNDQUBQVFRnUFxUVITw8vMVzlEqlUXxhYaEY7+fnBy8vL4OYxsZGFBcXizFKpRIajQbHjh0TY0pLS6HRaMSYGzduwMHB8Nu+5s96vf5eHtcsHIkmIrKSOS8O6rgQEhF1cQkJCVCpVAgLC4NSqcSmTZugVqsRGxsLAJg9ezZ8fX3FedWLFi3CyJEjsWrVKkyePBl79+7F/v37cfjwYQC3p2nEx8cjLS0NAQEBCAgIQFpaGnr27IlZs2YBuL36x9ixYxETE4ONGzcCAF566SVMmDABQ4YMAQCMHz8e69atQ2pqKmbOnIn6+nosX74cAwcOxNChQzvs58Ekmqg1bczx6tKYzLU7vRkjzXrw505EXdv06dNx5coVpKamoqqqCiEhIcjPz8fAgQMBAGq1WlxiDgDCw8Oxc+dOJCcnY8WKFfD398euXbsMVtpYunQpbt68ibi4ONTW1mLYsGEoLCyEq6urGLN9+3YsXLhQXMVj0qRJWL9+vXj8d7/7HXbs2IHVq1dj9erV6NmzJ5RKJQoKCuDi4tJhPw+uE91NcT3WdsAkmu7S2nqsH5Q/gp6ubb84eKNehzlDT3KdaPZLRO3KlutEkyGORBMRWUkv9IDexHQOPf94ISLqVvimCxGRlUy9VNhcLJWVlQU/Pz/IZDKEhobi0KFDrcZqtVqkpqbC398fMpkMjzzyCAoKCgxi6uvrER8fj4EDB8LFxQXh4eE4fvy4QYwgCEhJSYGPjw9cXFwwevRonDp1yuK2ExF1d0yiiYispAegEyRtFkvfD9+1axfi4+ORlJSE8vJyREREYNy4cVCr1S3GJycnY+PGjXjvvfdw+vRpxMbGYsqUKSgvLxdj5s+fj6KiIuTm5uKrr75CZGQknnrqKVy6dEmMWb16NTIyMrB+/XocP34cXl5eGDNmDOrr6+/hJ0NE1H0xiSYispLp3Qp/efHQ3C12MzIyMG/ePMyfPx9BQUHIzMyEQqFAdnZ2i/G5ublYvnw5oqOjMXjwYLzyyiuIiorC2rVrAQA3b95EXl4eVq9ejZEjR+LXv/41UlJS4OfnJ15TEARkZmYiKSkJU6dORUhICD788EPcuHEDO3bs6ICfHBFR18UkmojISlrBwawCmLfFbmNjI8rKysQ30ZtFRkbiyJEjLbahoaEBMpnMoM7FxUVcSqqpqQk6na7NmPPnz6O6utrgvlKpFKNGjWr1vkRE9oovFhIRWcm8daJvH6+srDR4E14qlRrFXr58GTqdzmgXME9PT6Pdv5pFRUUhIyMDI0eOhL+/Pw4cOIC9e/dCp9MBAFxdXaFUKvHWW28hKCgInp6e+Pjjj1FaWoqAgAAAEK/d0n0vXrzY5vMREdkbjkQTEVnJkhcLm7fYbS4tJdHNJHctsygIglFds3feeQcBAQEIDAyEs7MzXn31VcydO9dgF6/c3FwIggBfX19IpVK8++67mDVrltFOX5bcl4jIXjGJJiKykl6QmFXM5e7uDgcHB6NR55qaGqNR4mb9+/fHnj17cP36dVy8eBHffPMNevfuDT8/PzHG398fxcXFuHbtGiorK3Hs2DFotVoxxsvLCwAsui8Rkb1iEk1EZCW9GaPQpnY0vJOzszNCQ0NRVFRkUF9UVITw8PA2z5XJZPD19UVTUxPy8vIwefJko5hevXrB29sbtbW12Ldvnxjj5+cHLy8vg/s2NjaiuLjY5H2JiOwN50QTEVlJKzjAQWh7x0KthZutJCQkQKVSISwsDEqlEps2bYJarUZsbCwAYPbs2fD19RVfTCwtLcWlS5fw6KOP4tKlS0hJSYFer8fSpUvFa+7btw+CIGDIkCH497//jT/+8Y8YMmQI5s6dC+D2NI74+HikpaUhICAAAQEBSEtLQ8+ePTFr1iyL2k9E1N0xiSYispJ5OxZa9sXf9OnTceXKFaSmpqKqqgohISHIz8/HwIEDAQBqtRo9evxyzVu3biE5ORnnzp1D7969ER0djdzcXPTp00eM0Wg0SExMxA8//IAHHngAzzzzDFauXAknp1+24F66dClu3ryJuLg41NbWYtiwYSgsLISrq6tF7Sci6u4kgsC9aG0hKysLb7/9NqqqqvDggw8iMzMTERERrcZnZmYiOzsbarUa7u7uePbZZ5Genm60PFVr6urqIJfLMRqT4ShxMn0CGeuuL1LxV/6eNQlaHMReaDQauLm5ib9nfyp9CrLebf+e3bqmReqw/eK59oj9ElH7a61fMtXXmBtHreNItA007zyWlZWFESNGYOPGjRg3bhxOnz6NAQMGGMVv374dy5Ytw5YtWxAeHo5vv/0Wc+bMAQCsW7fOxq0nIlM6YiSaiIg6NybRNnDnzmPA7VHmffv2ITs7u8WNFkpKSjBixAhxDuKgQYMwc+ZMHDt2rNV7NDQ0GOx8VldX185PQUStsWSdaHvCfomIujP769Vt7F52Hvvtb3+LsrIyMWk+d+4c8vPzMX78+Fbvk56ebrALmkKhaL+HIKI2NZmxW2GTiRcPuyP2S0TUnTGJ7mD3svPYjBkz8NZbb+G3v/0tnJyc4O/vjyeeeALLli1r9T6JiYnQaDRiqaysbNfnIKLWtfc60d0F+yUi6s44ncNGLNkB7ODBg1i5ciWysrIwbNgw/Pvf/8aiRYvg7e2NFStWtHiOVCptc+czIuo4d+5I2FaMvWG/RETdGZPoDnYvO4+tWLECKpVKnEP90EMP4fr163jppZeQlJRksKwVEd1/5ow02+NINBFRd8ZsrIPdy85jN27cMEqUHRwcIAgCuCIhUeej/3lHQlOFiIi6D45E24ClO49NnDgRGRkZGDp0qDidY8WKFZg0aRIcHOzv5SSizk4nSKAzMdJs6jgREXUtTKJtwNKdx5KTkyGRSJCcnIxLly6hf//+mDhxIlauXHm/HoGI2qDTO6BJ3/YfuDq93katISIiW2ASbSNxcXGIi4tr8djBgwcNPjs6OuKNN97AG2+8YYOWEZG1dJBABxMj0SaOExFR18IkmojISnrB9IuDer7OQETUrTCJJiKyErf9JiKyP0yiiYispIcEehPTNUwdJyKiroVJNHUpDn3kNrvXzeH/Y7N72ZLL0W9tch/dVY1N7tMZaPUOkJh4sVBr4jgREXUtTKKJiKykhxmbrXAkmoioW2ESTURkJcGM6RwCk2giom6FSTQRkZW47TcRkf1hEk1EZCWuzkFEZH+YRBMRWalJ6AGJiSS5iUk0EVG3wiSaiMhKnM5BRGR/ODRCRGSl5iTaVCEi6uqysrLg5+cHmUyG0NBQHDp0qM34vLw8BAcHQyqVIjg4GLt37zY4LggCUlJS4OPjAxcXF4wePRqnTp0yiKmtrYVKpYJcLodcLodKpcLVq1dbvN+///1vuLq6ok+fPtY9qBmYRBMRWYlJNBHZg127diE+Ph5JSUkoLy9HREQExo0bB7Va3WJ8SUkJpk+fDpVKhZMnT0KlUmHatGkoLS0VY1avXo2MjAysX78ex48fh5eXF8aMGYP6+noxZtasWaioqEBBQQEKCgpQUVEBlUpldD+tVouZM2ciIiKi/R++BUyiiYisxCSaiOxBRkYG5s2bh/nz5yMoKAiZmZlQKBTIzs5uMT4zMxNjxoxBYmIiAgMDkZiYiCeffBKZmZkAbo9CZ2ZmIikpCVOnTkVISAg+/PBD3LhxAzt27AAAnDlzBgUFBfjzn/8MpVIJpVKJnJwc/O1vf8PZs2cN7pecnIzAwEBMmzatY38QP2MSTURkJZ0gQZPQo82iYxJNRJ1QXV2dQWloaGgxrrGxEWVlZYiMjDSoj4yMxJEjR1o8p6SkxCg+KipKjD9//jyqq6sNYqRSKUaNGiXGlJSUQC6XY9iwYWLM8OHDIZfLDe77j3/8A3/5y1/w/vvvW/D01mESTURkJY5EE1FXpVAoxLnGcrkc6enpLcZdvnwZOp0Onp6eBvWenp6orq5u8Zzq6uo245v/NRXj4eFhdG0PDw8x5sqVK5gzZw4++OADuLm5mXrkdsPVOYiIrMTVOYioq6qsrDRIPKVSaZvxEolhXyYIglGdpfGmYlq6/p0xMTExmDVrFkaOHNlm29sbR6KJiKzEkWgi6qrc3NwMSmtJtLu7OxwcHIxGnWtqaoxGkpt5eXm1Ge/l5QUAJmN+/PFHo2v/9NNPYsw//vEPrFmzBo6OjnB0dMS8efOg0Wjg6OiILVu2mPoR3DMm0UREVhIEiVmFiKircnZ2RmhoKIqKigzqi4qKEB4e3uI5SqXSKL6wsFCM9/Pzg5eXl0FMY2MjiouLxRilUgmNRoNjx46JMaWlpdBoNGJMSUkJKioqxJKamgpXV1dUVFRgypQp1j98Kzidg4jISk1CD4A7FhJRN5eQkACVSoWwsDAolUps2rQJarUasbGxAIDZs2fD19dXnFe9aNEijBw5EqtWrcLkyZOxd+9e7N+/H4cPHwZwe5pGfHw80tLSEBAQgICAAKSlpaFnz56YNWsWACAoKAhjx45FTEwMNm7cCAB46aWXMGHCBAwZMkSMudOJEyfQo0cPhISEdOjPg0k0EZGVzBlp5kg0EXV106dPx5UrV5CamoqqqiqEhIQgPz8fAwcOBACo1Wr06PHLgEF4eDh27tyJ5ORkrFixAv7+/ti1a5fBShtLly7FzZs3ERcXh9raWgwbNgyFhYVwdXUVY7Zv346FCxeKq3hMmjQJ69evt9FTt04iCIJwvxtB7a+urg5yuRyjMRmOEqf73Zx249BHbrN73Rz+Pza7ly25HP3WJvfRXdXY5D621CRocRB7odFo4ObmJv6ehf01Ho692n4Zp+l6A05MzRTPtUfdtV8iup9a65dM9TXmxlHrOBJNRGQljkQTEdkfJtFERFYSzFh9g0k0EVH3wiSaiMhKOkgAE0myDkyiiYi6EybRRERW4nQOIiL7wySaiMhKekECCXcsJCKyK0yiiYisJAi3i6kYIiLqPphEExFZidM5iIjsD7fQIiKykk7fw6xiqaysLPj5+UEmkyE0NBSHDh1qNVar1SI1NRX+/v6QyWR45JFHUFBQYBAzaNAgSCQSo7JgwQIxZvTo0UbHZ8yYYXHbiYi6O45EU/uQ2GaUzZYboPzflhyb3cuWnvh9jE3u47zvhE3uA+C+z5XoiOkcu3btQnx8PLKysjBixAhs3LgR48aNw+nTpzFgwACj+OTkZGzbtg05OTkIDAzEvn37MGXKFBw5cgRDhw4FABw/fhw6nU485+uvv8aYMWPw3HPPGVwrJiYGqamp4mcXFxfLGk9EZAc4Ek1EZKXbSbTERLkdW1dXZ1AaGhpavGZGRgbmzZuH+fPnIygoCJmZmVAoFMjOzm4xPjc3F8uXL0d0dDQGDx6MV155BVFRUVi7dq0Y079/f3h5eYnlb3/7G/z9/TFq1CiDa/Xs2dMgTi633U6hRERdBZNoG7Hka1kAuHr1KhYsWABvb2/IZDIEBQUhPz/fRq0lIkuYTqB/mTOtUCggl8vFkp6ebnS9xsZGlJWVITIy0qA+MjISR44cabENDQ0NkMlkBnUuLi44fPhwi/GNjY3Ytm0bfv/730Ny1zdJ27dvh7u7Ox588EEsWbIE9fX1Zv8siIjsBadz2IClX8s2NjZizJgx8PDwwCeffIJf/epXqKyshKur631oPRGZIvxcTMUAQGVlJdzc3MR6qVRqFHv58mXodDp4enoa1Ht6eqK6urrF60dFRSEjIwMjR46Ev78/Dhw4gL179xpM37jTnj17cPXqVcyZM8eg/vnnn4efnx+8vLzw9ddfIzExESdPnkRRUZGJJyQisi9Mom3gzq9lASAzMxP79u1DdnZ2i6NQW7ZswX//+18cOXIETk5OAICBAwfatM1EZD5BL4GgN7E6x8/H3dzcDJLottw9QiwIglFds3feeQcxMTEIDAyERCKBv78/5s6di61bt7YYv3nzZowbNw4+Pj4G9TExv8yZDwkJQUBAAMLCwvDll1/iscceM6vdRET2gNM5Oti9fC376aefQqlUYsGCBfD09ERISAjS0tJaHVECbn+Ve/dcSyKyEXOmcliwxJ27uzscHByMRp1ramqMRqeb9e/fH3v27MH169dx8eJFfPPNN+jduzf8/PyMYi9evIj9+/eLf9i35bHHHoOTkxO+++47s9vfjP0SEXVnTKI72L18LXvu3Dl88skn0Ol0yM/PR3JyMtauXYuVK1e2ep/09HSDeZYKhaJdn4OIWte8OoepYi5nZ2eEhoYaTaEoKipCeHh4m+fKZDL4+vqiqakJeXl5mDx5slHM1q1b4eHhgfHjx5tsy6lTp6DVauHt7W3+A/yM/RIRdWdMom3Ekq9l9Xo9PDw8sGnTJoSGhmLGjBlISkpq9a18AEhMTIRGoxFLZWVlu7afiFpnyYuF5kpISMCf//xnbNmyBWfOnMHixYuhVqsRGxsLAJg9ezYSExPF+NLSUvz1r3/FuXPncOjQIYwdOxZ6vR5Lly41uK5er8fWrVvx4osvwtHRcEbf999/j9TUVJw4cQIXLlxAfn4+nnvuOQwdOhQjRoyw+OfCfomIujPOie5g9/K1rLe3N5ycnODg4CDWBQUFobq6Go2NjXB2djY6RyqVtviCEhHZgDnTNSxMoqdPn44rV64gNTUVVVVVCAkJQX5+vvh+hFqtRo8ev4yD3Lp1C8nJyTh37hx69+6N6Oho5Obmok+fPgbX3b9/P9RqNX7/+98b3dPZ2RkHDhzAO++8g2vXrkGhUGD8+PF44403DPojc7FfIqLujEl0B7vza9kpU6aI9UVFRS1+zQoAI0aMwI4dO6DX68X/SH777bfwsF1o4QAAIABJREFU9vZuMYEmovtL0N8upmIsFRcXh7i4uBaPHTx40ODzqFGjcPr0aZPXjIyMhNDK3BKFQoHi4mKL20lEZI84ncMGLP1a9pVXXsGVK1ewaNEifPvtt/j888+RlpZmsDUvEXUeHTGdg4iIOjeORNuApV/LKhQKFBYWYvHixXj44Yfh6+uLRYsW4fXXX79fj0BEptzfnceJiMjGmETbiCVfywKAUqnE0aNHO7hVRNQezBlp5kg0EVH3wiSaiMhalmxZSERE3QKTaCIia3XA6hxERNS5MYkmIrIWR6KJiOwOk2giImtxJJqIyO4wiSYispI523pbsu03ERF1fkyiiYisxekcRER2h0k0EZGVJHoJJPq2p2uYOk5ERF0Lk2giImtxJJqIyO4wiSYishZfLCQisjtMoomIrMWRaCIiu8MkmojIWkyiiYjsTo/73QAioi5PMLMQEXVxWVlZ8PPzg0wmQ2hoKA4dOtRmfF5eHoKDgyGVShEcHIzdu3cbHBcEASkpKfDx8YGLiwtGjx6NU6dOGcTU1tZCpVJBLpdDLpdDpVLh6tWrBjFfffUVRo0aBRcXF/j6+iI1NRVCB68tyiS6FXPmzMEXX3xxv5tBRF1A8+ocpgoRUVe2a9cuxMfHIykpCeXl5YiIiMC4ceOgVqtbjC8pKcH06dOhUqlw8uRJqFQqTJs2DaWlpWLM6tWrkZGRgfXr1+P48ePw8vLCmDFjUF9fL8bMmjULFRUVKCgoQEFBASoqKqBSqcTjdXV1GDNmDHx8fHD8+HG89957WLNmDTIyMjruhwFO52hVfX09IiMjoVAoMHfuXLz44ovw9fW9380ios6I0zmIqJOZLJ8NR4lTq8ebBK3F18zIyMC8efMwf/58AEBmZib27duH7OxspKenG8VnZmZizJgxSExMBAAkJiaiuLgYmZmZ+PjjjyEIAjIzM5GUlISpU6cCAD788EN4enpix44dePnll3HmzBkUFBTg6NGjGDZsGAAgJycHSqUSZ8+exZAhQ7B9+3bcunULH3zwAaRSKUJCQvDtt98iIyMDCQkJkEg6ZhCDI9GtyMvLw6VLl/Dqq6/iL3/5CwYNGoRx48bhk08+gVZr+f/wiIiIiDqburo6g9LQ0NBiXGNjI8rKyhAZGWlQHxkZiSNHjrR4TklJiVF8VFSUGH/+/HlUV1cbxEilUowaNUqMKSkpgVwuFxNoABg+fDjkcrlBzKhRoyCVSg3u85///AcXLlww8ydhOSbRbejXrx8WLVqE8vJyHDt2DL/+9a+hUqng4+ODxYsX47vvvrvfTSSiTkACQCKYKPe7kURELVAoFOJcY7lc3uKIMgBcvnwZOp0Onp6eBvWenp6orq5u8Zzq6uo245v/NRXj4eFhdG0PDw+DmJaucec9OgKnc5ihqqoKhYWFKCwshIODA6Kjo3Hq1CkEBwdj9erVWLx48f1uIhHdT1wnmog6mb2aj+Dm5tbq8bq6OsjlclRWVhrE3Tma25K7p0YIgtDmdAlz4k3FtHR9UzHNLxV21FQOgCPRrdJqtcjLy8OECRMwcOBA/OUvf8HixYtRVVWFDz/8EIWFhcjNzUVqaur9bioR3W96MwsRUSfj5uZmUFpLot3d3eHg4GA0sltTU2M0CtzMy8urzXgvLy8AxqPFd8f8+OOPRtf+6aefDGJaugZgPMrdnphEt8Lb2xsxMTEYOHAgjh07hhMnTiA2Nhaurq5iTFRUFPr06XMfW0lEnYHJqRw/FyKirsrZ2RmhoaEoKioyqC8qKkJ4eHiL5yiVSqP4wsJCMd7Pzw9eXl4GMY2NjSguLhZjlEolNBoNjh07JsaUlpZCo9EYxHzxxRdobGw0uI+Pjw8GDRp07w9tAqdztGLdunV47rnnIJPJWo3p27cvzp8/b8NWEVGnxNU5iMgOJCQkQKVSISwsDEqlEps2bYJarUZsbCwAYPbs2fD19RXnVS9atAgjR47EqlWrMHnyZOzduxf79+/H4cOHAdyeahEfH4+0tDQEBAQgICAAaWlp6NmzJ2bNmgUACAoKwtixYxETE4ONGzcCAF566SVMmDABQ4YMAXB7Cbw333wTc+bMwfLly/Hdd98hLS0Nf/rTnzp0OgeT6Fbcuf4gEVGbmEQTkR2YPn06rly5gtTUVFRVVSEkJAT5+fkYOHAgAECtVqNHj18mOYSHh2Pnzp1ITk7GihUr4O/vj127dhmstLF06VLcvHkTcXFxqK2txbBhw1BYWGjwzf/27duxcOFCcRWPSZMmYf369eJxuVyOoqIiLFiwAGFhYejbty8SEhKQkJDQoT8PJtFERFYyZ7oGp3MQUXcQFxeHuLi4Fo8dPHjQqO7ZZ5/Fs88+2+r1JBIJUlJSkJKS0mrMAw88gG3btrXZroceesjmm+QxiSYispZecruYiiEiom6DSTQRkZU4Ek1EZH+YRBMRWYtzoomI7A6TaCIia5mzhB2TaCKiboVJNBGRtTgSTURkd5hEExFZSaK/XUzFEBFR98EdC4mIiIiILMSRaCIia3E6BxGR3WESTURkJS5xR0Rkf5hEExG1BybJRER2hXOibSQrKwt+fn6QyWQIDQ3FoUOHzDpv586dkEgkePrppzu4hUR0r5pfLDRViIio+2ASbQO7du1CfHw8kpKSUF5ejoiICIwbNw5qtbrN8y5evIglS5YgIiLCRi0lonsimFmIiKjbYBJtAxkZGZg3bx7mz5+PoKAgZGZmQqFQIDs7u9VzdDodnn/+ebz55psYPHiwDVtLRJZqnhNtqhARUffBJLqDNTY2oqysDJGRkQb1kZGROHLkSKvnpaamon///pg3b55Z92loaEBdXZ1BISIb6aCRaEumgWm1WqSmpsLf3x8ymQyPPPIICgoKjOIuXbqEF154Af369UPPnj3x6KOPoqys7JdHEQSkpKTAx8cHLi4uGD16NE6dOmV548F+iYi6NybRHezy5cvQ6XTw9PQ0qPf09ER1dXWL5/zzn//E5s2bkZOTY/Z90tPTIZfLxaJQKKxqNxFZoAOSaEungSUnJ2Pjxo147733cPr0acTGxmLKlCkoLy8XY2prazFixAg4OTnh73//O06fPo21a9eiT58+Yszq1auRkZGB9evX4/jx4/Dy8sKYMWNQX19v2QOA/RIRdW9Mom1EIpEYfBYEwagOAOrr6/HCCy8gJycH7u7uZl8/MTERGo1GLJWVlVa3mYjM0xEvFlo6DSw3NxfLly9HdHQ0Bg8ejFdeeQVRUVFYu3atGLNq1SooFAps3boVjz/+OAYNGoQnn3wS/v7+AG73S5mZmUhKSsLUqVMREhKCDz/8EDdu3MCOHTss/rmwXyKi7oxJdAdzd3eHg4OD0ahzTU2N0eg0AHz//fe4cOECJk6cCEdHRzg6OuKjjz7Cp59+CkdHR3z//fct3kcqlcLNzc2gEJGNWDASfff0hoaGBqPL3cs0sIaGBshkMoM6FxcXHD58WPz86aefIiwsDM899xw8PDwwdOhQg2+8zp8/j+rqaoP7SqVSjBo1qs3pZ61hv0RE3RmT6A7m7OyM0NBQFBUVGdQXFRUhPDzcKD4wMBBfffUVKioqxDJp0iQ88cQTqKio4NehRJ2QJS8WKhQKgykO6enpRte7l2lgUVFRyMjIwHfffQe9Xo+ioiLs3bsXVVVVYsy5c+eQnZ2NgIAA7Nu3D7GxsVi4cCE++ugjABCvbcl9iYjsFTdbsYGEhASoVCqEhYVBqVRi06ZNUKvViI2NBQDMnj0bvr6+SE9Ph0wmQ0hIiMH5zfMV764nok7Cgm2/KysrDUZkpVJpq6eYOw0MAN555x3ExMQgMDAQEokE/v7+mDt3LrZu3SrG6PV6hIWFIS0tDQAwdOhQnDp1CtnZ2Zg9e/Y93ZeIyF4xibaB6dOn48qVK0hNTUVVVRVCQkKQn5+PgQMHAgDUajV69OjiXwoItlm/y+Xotza5DwA88fsYm93Llmz1M9TZ6H8TnYEl236bM63B0mlgANC/f3/s2bMHt27dwpUrV+Dj44Nly5bBz89PjPH29kZwcLDBeUFBQcjLywMAeHl5Abg9Iu3t7W3WfYmI7BWTaBuJi4tDXFxci8cOHjzY5rkffPBB+zeIiNqP/udiKsZMd04DmzJlilhfVFSEyZMnt3muTCaDr68vtFot8vLyMG3aNPHYiBEjcPbsWYP4b7/9VvyD3s/PD15eXigqKsLQoUMB3J6fXVxcjFWrVpn/AEREdoBJNBGRlSQ/F1MxlrBkGhgAlJaW4tKlS3j00Udx6dIlpKSkQK/XY+nSpeI1Fy9ejPDwcKSlpWHatGk4duwYNm3ahE2bNt1uo0SC+Ph4pKWlISAgAAEBAUhLS0PPnj0xa9YsC5+AiKh7YxJNRGQtC+ZEm8vSaWC3bt1CcnIyzp07h969eyM6Ohq5ubkGa0D/5je/we7du5GYmIjU1FT4+fkhMzMTzz//vBizdOlS3Lx5E3FxcaitrcWwYcNQWFgIV1dXyx6AiKibkwiCHU1ctCN1dXWQy+UYjclwlDjd7+a0G4c+cpvd6+bw/7HZvWzJZnOir2psch9bahK0OIi90Gg0cHNzE3/PHoxNg4NU1ua5uoZbOLVhuXiuPequ/RLR/dRav2SqrzE3jlrHkWgiImt1wEg0ERF1bkyiiYisJBFM70hoavUOIiLqWphEExFZiyPRRER2h0k0EZGVLFknmoiIugcm0URE1uJINBGR3WESTURkJY5EExHZHybRRETWaucdC4mIqPNjEk1EZCWORBMR2Z8epkOIiKhNgpmFiMhO1NbWQqVSQS6XQy6XQ6VS4erVq22e09DQgD/84Q9wd3dHr169MGnSJPzwww8GMWq1GhMnTkSvXr3g7u6OhQsXorGx0SCmuLgYoaGhkMlkGDx4MDZs2NDqPdPT0yGRSBAfH2/xMzKJJiKykkQQzCpERPZi1qxZqKioQEFBAQoKClBRUQGVStXmOfHx8di9ezd27tyJw4cP49q1a5gwYQJ0Oh0AQKfTYfz48bh+/ToOHz6MnTt3Ii8vD6+99pp4jfPnzyM6OhoREREoLy/H8uXLsXDhQuTl5Rnd7/jx49i0aRMefvjhe3pGTucgIrIWV+cgoi6qrq7O4LNUKoVUKrXqmmfOnEFBQQGOHj2KYcOGAQBycnKgVCpx9uxZDBkyxOgcjUaDzZs3Izc3F0899RQAYNu2bVAoFNi/fz+ioqJQWFiI06dPo7KyEj4+PgCAtWvXYs6cOVi5ciXc3NywYcMGDBgwAJmZmQCAoKAgnDhxAmvWrMEzzzwj3u/atWt4/vnnkZOTg//93/+9p+fkSDQRkZUkevMKEVFno1AoxCkXcrkc6enpVl+zpKQEcrlcTKABYPjw4ZDL5Thy5EiL55SVlUGr1SIyMlKs8/HxQUhIiHhOSUkJQkJCxAQaAKKiotDQ0ICysjIx5s5rNMecOHECWq1WrFuwYAHGjx8vJuz3giPRRERW4ouFRNRVVVZWws3NTfxs7Sg0AFRXV8PDw8Oo3sPDA9XV1a2e4+zsjL59+xrUe3p6iudUV1fD09PT4Hjfvn3h7OzcZoynpyeamppw+fJleHt7Y+fOnfjyyy9x/Pjxe35GgCPRRETW44uFRNRFubm5GZS2kuiUlBRIJJI2y4kTJwAAEonE6HxBEFqsb8vd55hz3btjhJ/fSZFIJKisrMSiRYuwbds2yGQyi9pyN45EExFZiSPRRGQPXn31VcyYMaPNmEGDBuFf//oXfvzxR6NjP/30k9EocTMvLy80NjaitrbWYDS6pqYG4eHhYkxpaanBebW1tdBqteJ1vby8jEa7a2pq4OjoiH79+uHzzz9HTU0NQkNDxeM6nQ5ffPEF1q9fj4aGBjg4OLT5jM2YRBMRWYsvFhKRHXB3d4e7u7vJOKVSCY1Gg2PHjuHxxx8HAJSWlkKj0YgJ8d1CQ0Ph5OSEoqIiTJs2DQBQVVWFr7/+GqtXrxavu3LlSlRVVcHb2xsAUFhYCKlUKibFSqUSn332mcG1CwsLERYWBicnJzz55JP46quvDI7PnTsXgYGBeP31181OoAFO5yAiahfNo9GtFSIiexEUFISxY8ciJiYGR48exdGjRxETE4MJEyaIK3NcunQJgYGBOHbsGABALpdj3rx5eO2113DgwAGUl5fjhRdewEMPPSS+/BcZGYng4GCoVCqUl5fjwIEDWLJkCWJiYsR53bGxsbh48SISEhJw5swZbNmyBZs3b8aSJUsAAK6urggJCTEovXr1Qr9+/RASEmLRczKJJiKykkQvmFWIiOzF9u3b8dBDDyEyMhKRkZF4+OGHkZubKx7XarU4e/Ysbty4IdatW7cOTz/9NKZNm4YRI0agZ8+e+Oyzz8TRYQcHB3z++eeQyWQYMWIEpk2bhqeffhpr1qwRr+Hn54f8/HwcPHgQjz76KN566y28++67BsvbtRdO5yAishancxARGXjggQewbdu2Vo8PGjRIfOGvmUwmw3vvvYf33nuv1fMGDBiAv/3tb23ee9SoUfjyyy/NbuvBgwfNjr0Tk2giIiuZsw4014kmIupemEQTEVmLI9FERHaHSTQRkZW4xB0Rkf1hEk1diu6qxmb3ct53wmb3siWdwGyuvZnz4iBfLCQi6l6YRBMRWYvTOYiI7A6TaCIiK3E6BxGR/WESTURkLUG4XUzFEBFRt8EkmojIShyJJiKyP0yiiYisxHWiiYjsD5NoIiJr6YXbxVQMERF1Gz3udwPsRVZWFvz8/CCTyRAaGopDhw61GpuTk4OIiAj07dsXffv2xVNPPYVjx47ZsLVEZBHBzEJERN0Gk2gb2LVrF+Lj45GUlITy8nJERERg3LhxUKvVLcYfPHgQM2fOxP/93/+hpKQEAwYMQGRkJC5dumTjlhOROST4ZV50q+V+N5KIiNoVk2gbyMjIwLx58zB//nwEBQUhMzMTCoUC2dnZLcZv374dcXFxePTRRxEYGIicnBzo9XocOHDAxi0nIrM0r85hqhARUbfBOdEdrLGxEWVlZVi2bJlBfWRkJI4cOWLWNW7cuAGtVosHHnig1ZiGhgY0NDSIn+vq6u6twURkMb5Y2DL2S0TUnXEkuoNdvnwZOp0Onp6eBvWenp6orq426xrLli2Dr68vnnrqqVZj0tPTIZfLxaJQKKxqNxGZTyIIZhV7w36JiLozJtE2IpEYzogUBMGoriWrV6/Gxx9/jL/+9a+QyWStxiUmJkKj0YilsrLS6jYTkZn0ZhY7w36JiLozTufoYO7u7nBwcDAada6pqTEanb7bmjVrkJaWhv379+Phhx9uM1YqlUIqlVrdXiKynDkjzfY4Es1+iYi6M45EdzBnZ2eEhoaiqKjIoL6oqAjh4eGtnvf222/jrbfeQkFBAcLCwjq6mURkDS5xR0RkdzgSbQMJCQlQqVQICwuDUqnEpk2boFarERsbCwCYPXs2fH19kZ6eDuD2FI4VK1Zgx44dGDRokDiK3bt3b/Tu3fu+PQcRtUyiFyAxsZmKqeNERNS1cCTaBqZPn47MzEykpqbi0UcfxRdffIH8/HwMHDgQAKBWq1FVVSXGZ2VlobGxEc8++yy8vb3FsmbNmvv1CETUlg5a4s6STZq0Wi1SU1Ph7+8PmUyGRx55BAUFBa3Gp6enQyKRID4+3qB+9OjRkEgkBmXGjBkWt52IqLvjSLSNxMXFIS4ursVjBw8eNPh84cKFjm8QEbWbjljirnmTpqysLIwYMQIbN27EuHHjcPr0aQwYMMAoPjk5Gdu2bUNOTg4CAwOxb98+TJkyBUeOHMHQoUMNYo8fP45Nmza1+q5FTEwMUlNTxc8uLi6WNZ6IyA5wJJqIyFodMBJt6SZNubm5WL58OaKjozF48GC88soriIqKwtq1aw3irl27hueffx45OTno27dvi9fq2bMnvLy8xCKXyy1qOxGRPWASTURkLQteLKyrqzMod25G0qx5k6bIyEiD+rY2aWpoaDBaBtPFxQWHDx82qFuwYAHGjx/f5rrz27dvh7u7Ox588EEsWbIE9fX1bTw8EZF94nQOIiIrSfR6SPRtz9doPn73hiNvvPEGUlJSDOruZZOmqKgoZGRkYOTIkfD398eBAwewd+9e6HQ6MWbnzp348ssvcfz48Vbb+fzzz8PPzw9eXl74+uuvkZiYiJMnTxqtMEREZO+YRBMRWUuA6c1Ufh6JrqyshJubm1jd1jrKlmzS9M477yAmJgaBgYGQSCTw9/fH3LlzsXXrVvG+ixYtQmFhYZsbN8XExIj/f0hICAICAhAWFoYvv/wSjz32mImHJCKyH5zOQURkJUu2/XZzczMoLSXR97JJU//+/bFnzx5cv34dFy9exDfffIPevXvDz88PAFBWVoaamhqEhobC0dERjo6OKC4uxrvvvgtHR0eDEes7PfbYY3BycsJ3331nzY+IiKjbYRJNRGQtAWa8WGj+5e51kyYAkMlk8PX1RVNTE/Ly8jB58mQAwJNPPomvvvoKFRUVYgkLC8Pzzz+PiooKODg4tHi9U6dOQavVwtvb2/wHICKyA5zOQURkLXNW37BwdQ5LN2kqLS3FpUuX8Oijj+LSpUtISUmBXq/H0qVLAQCurq4ICQkxuEevXr3Qr18/sf7777/H9u3bER0dDXd3d5w+fRqvvfYahg4dihEjRljUfiKi7o5JNBGRlSQ6ARITQ80SnWVJ9PTp03HlyhWkpqaiqqoKISEhRps09ejxy5eJt27dQnJyMs6dO4fevXsjOjoaubm56NOnj9n3dHZ2xoEDB/DOO+/g2rVrUCgUGD9+PN54441WR6qJiOwVk2ii1tzDDnNkpzpgJBqwbJOmUaNG4fTp0xZd/+5rKBQKFBcXW3QNIiJ7xSSaiMhaHZREExFR58UXC4mIrNUBOxYSEXVltbW1UKlUkMvlkMvlUKlUuHr1apvnNDQ04A9/+APc3d3Rq1cvTJo0CT/88INBjFqtxsSJE9GrVy+4u7tj4cKFaGxsNIgpLi5GaGgoZDIZBg8ejA0bNhgcb2pqQnJyMvz8/ODi4oLBgwcjNTUVehPr/d+NSTQRkbX0ZhYiIjsxa9YsVFRUoKCgAAUFBaioqIBKpWrznPj4eOzevRs7d+7E4cOHce3aNUyYMEFcglOn02H8+PG4fv06Dh8+jJ07dyIvLw+vvfaaeI3z588jOjoaERERKC8vx/Lly7Fw4ULk5eWJMatWrcKGDRuwfv16nDlzBqtXr8bbb7+N9957z6Jn5HQOIiIrSfR6SCTm7VhIRNTdnTlzBgUFBTh69CiGDRsGAMjJyYFSqcTZs2cxZMgQo3M0Gg02b96M3NxcPPXUUwCAbdu2QaFQYP/+/YiKikJhYSFOnz6NyspK+Pj4AADWrl2LOXPmYOXKlXBzc8OGDRswYMAAZGZmAgCCgoJw4sQJrFmzBs888wwAoKSkBJMnT8b48eMBAIMGDcLHH3+MEydOWPScHIkmIrKWXjCvEBF1MnV1dQaloaHB6muWlJRALpeLCTQADB8+HHK5HEeOHGnxnLKyMmi1WkRGRop1Pj4+CAkJEc8pKSlBSEiImEADQFRUFBoaGlBWVibG3HmN5pgTJ05Aq9UCAH7729/iwIED+PbbbwEAJ0+exOHDhxEdHW3Rc3IkmojIWnyxkIi6KIVCYfD5jTfeQEpKilXXrK6uhoeHh1G9h4eH0U6sd57j7OyMvn37GtR7enqK51RXVxvt2tq3b184Ozu3GePp6YmmpiZcvnwZ3t7eeP3116HRaBAYGAgHBwfodDqsXLkSM2fOtOg5mUQTEVnNnBcHmUQTUedTWVkJNzc38bNUKm01NiUlBW+++Wab1zt+/DgAQCKRGB0TBKHF+rbcfY451707Rvi5f26u37VrF7Zt24YdO3bgwQcfREVFBeLj4+Hj44MXX3zR7LYxiSYishZHoomoi3JzczNIotvy6quvYsaMGW3GDBo0CP/617/w448/Gh376aefjEaJm3l5eaGxsRG1tbUGo9E1NTUIDw8XY0pLSw3Oq62thVarFa/r5eVlNNpdU1MDR0dH9OvXDwDwxz/+EcuWLROf5aGHHsLFixeRnp7OJJqIyKZ0OkDQtR2jN3GciKiTc3d3h7u7u8k4pVIJjUaDY8eO4fHHHwcAlJaWQqPRiAnx3UJDQ+Hk5ISioiJMmzYNAFBVVYWvv/4aq1evFq+7cuVKVFVVwdvbGwBQWFgIqVSK0NBQMeazzz4zuHZhYSHCwsLg5OQEALhx44bBjq8A4ODgwCXuiIhsjutEExGJgoKCMHbsWMTExODo0aM4evQoYmJiMGHCBHFljkuXLiEwMBDHjh0DAMjlcsybNw+vvfYaDhw4gPLycrzwwgt46KGHxNU6IiMjERwcDJVKhfLychw4cABLlixBTEyMOJoeGxuLixcvIiEhAWfOnMGWLVuwefNmLFmyRGzfxIkTsXLlSnz++ee4cOECdu/ejYyMDEyZMsWi5+RINBGRtfQCTM555uocRGRHtm/fjoULF4orZUyaNAnr168Xj2u1Wpw9exY3btwQ69atWwdHR0dMmzYNN2/exJNPPokPPvgADg4OAG6PFn/++eeIi4vDiBEj4OLiglmzZmHNmjXiNfz8/JCfn4/Fixfj/fffh4+PD959911xeTsAeO+997BixQrExcWhpqYGPj4+ePnll/GnP/3JomeUCAKHR7qjuro6yOVyjMZkOEqc7ndziLqFJkGLg9gLjUYDNzc38ffsKZ+X4dij9ZdxAKBJ34D9/9konmuP2C8Rtb/W+iVTfY25cdQ6jkQTEVlLgBkvFtqkJUREZCNMoomIrMUXC4mI7A6TaCIia3GJOyIiu8MkmojIWkyiiYjsDpNoIiJrcXUOIiK7wySaiMhKgqCHILS9SL+p40RE1LUwiSYispZeD5hKkplEExF1K0yiiYispdcDEibRREQ5PurOAAAPFUlEQVT2hEk0EZG1BDPmRPPFQiKiboVJNBGRlQS9HoKJkWjOiSYi6l6YRBMRWYsj0UREdqfH/W6AvcjKyoKfnx9kMhlCQ0Nx6NChNuPz8vIQHBwMqVSK4OBg7N6920YtJSKL6QXzChERdRtMom1g165diI+PR1JSEsrLyxEREYFx48ZBrVa3GF9SUoLp06dDpVLh5MmTUKlUmDZtGkpLS23cciIyh6DTQ9DpTBRO5yAi6k6YRNtARkYG5s2bh/nz5yMoKAiZmZlQKBTIzs5uMT4zMxNjxoxBYmIiAgMDkZiYiCeffBKZmZk2bjkRmUXQm1eIiKjb4JzoDtbY2IiysjIsW7bMoD4yMhJHjhxp8ZySkhIsXrzYoC4qKqrNJLqhoQENDQ3iZ41GAwDIrVwPNze3e20+Ed2hrq4OCsVeCD/Pb27+V6trhCBpe7pGk6A1OMcesF8i6nit9Ut1dXUmz7sznizHJLqDXb58GTqdDp6engb1np6eqK6ubvGc6upqi+IBID09HW+++aZRvUKhuIdWE1Fbrly5Arlcjvr6egDAYfzN5HuFzerr6yGXyzuwdZ0H+yUi27m7XzL398ye+qT2xiTaRiQSicFnQRCM6qyJT0xMREJCgvj56tWrGDhwINRqdaf+5bj9F7QClZWVnX5kim3tGF2prRqNBgMGDMADDzwAAPDx8UFlZSVcXV3b/P0Ebv8O19fXw8fHxxZN7RTYL3U8trVjdKW23mu/ZI99UntjEt3B3N3d4eDgYDSKXFNTYzTa3MzLy8uieACQSqWQSqVG9XK5vNN3AADg5ubWJdoJsK0dpSu1tUePHuK/v/rVr8w+rzMnjh2B/ZLtsK0doyu19V76JXvrk9obXyzsYM7OzggNDUVRUZFBfVFREcLDw1s8R6lUGsUXFha2Gk9EREREtsWRaBtISEiASqVCWFgYlEolNm3aBLVajdjYWADA7Nmz4evri/T0dADAokWLMHLkSKxatQqTJ0/G3r17sX//fhw+fPh+PgYRERER/cwhJSUl5X43orsLCQlBv379kJaWhjVr1uDmzZvIzc3FI488AgB455134OjoiKeffhrA7ZcBgoODkZGRgbS0NKjVamRnZ2PMmDEW3dfBwQGjR4+Go2Pn/lupq7QTYFs7CttqP7rKz6+rtBNgWzsK20qmSASubUJEREREZBHOiSYiIiIishCTaCIiIiIiCzGJJiIiIiKyEJNoIiIiIiILMYnuorKysuDn5weZTIbQ0FAcOnSozfi8vDwEBwdDKpUiODgYu3fvtlFLLWtrTk4OIiIi0LdvX/Tt2xdPPfUUjh071inbeqedO3dCIpGIK6zYgqVtvXr1KhYsWABvb2/IZDIEBQUhPz+/U7Y1MzMTQ4YMgYuLCxQKBRYvXoxbt251aBu/+OILTJw4ET4+PpBIJNizZ4/Jc4qLixEaGgqZTIbBgwdjw4YNHdrGzo790v1v653YL7VvW9kvkRGBupydO3cKTk5OQk5OjnD69Glh0aJFQq9evYSLFy+2GH/kyBHBwcFBSEtLE86cOSOkpaUJjo6OwtGjRztdW2fNmiW8//77Qnl5uXDmzBlh7ty5glwuF3744YdO19ZmFy5cEHx9fYWIiAhh8uTJHd7Oe2lrQ0ODEBYWJkRHRwuHDx8WLly4IBw6dEioqKjodG3dtm2bIJVKhe3btwvnz58X9u3bJ3h7ewvx8fEd2s78/HwhKSlJyMvLEwAIu3fvbjP+3LlzQs+ePYVFixYJp0+fFnJycgQnJyfhk08+6dB2dlbslzpHW5uxX2rftrJfopYwie6CHn/8cSE2NtagLjAwUFi2bFmL8dOmTRPGjh1rUBcVFSXMmDGjw9rYzNK23q2pqUlwdXUVPvzww45onoF7aWtTU5MwYsQI4c9//rPw4osv2uw/Vpa2NTs7Wxg8eLDQ2Nhoi+YZsLStCxYs+P/t3W1Ilfcfx/GPHr2yZYtu5tFCavNBJ6jobjVLcEarB1H0aARNFGrVMuhuDVdkw0rshmiMTVj4YPQg6OZJhIRFGUxlq1ARGlmZa0NPNxAlFXj324Ph+f/VU//z8+/ldey8X3AedPk7+rE63/Px8neuY5YuXdrn2M6dO01WVpZrGfuL5Mnqm2++MYFAoM+xTZs2mU8++cTNaFGLueQO5pI7mEsYCmznGGE6Ojp069YtLV++vM/x5cuXq6amJux9amtrB6xfsWLFG9cPlcFk7e/Vq1fq7OzUhAkT3IgYMtisxcXF+uCDD7R+/XpX8/23wWS9cOGCMjMzVVBQIL/fr5kzZ6qkpETd3d1RlzUrK0u3bt0K/bq8ublZFRUVWrlypatZbb3pcXXz5k11dnZ6lMobzCV3MJeiJytzCeHw1jYjzNOnT9Xd3S2/39/nuN/vVzAYDHufYDBotX6oDCZrf4WFhZoyZYqWLVvmRsSQwWStrq5WeXm56uvrXc3W32CyNjc36+rVq1q3bp0qKip09+5dFRQUqKurS0VFRVGVde3atXry5ImysrJkjFFXV5e++uorFRYWupZzMN70uOrq6tLTp0+VlpbmUbLhx1xyB3MperIylxAOJXqEiouL6/NnY8yAY//P+qE02K995MgRnT59WlVVVUpKSnIrXh+RZm1vb9cXX3yhkydPatKkScOSrT+bv9eenh6lpKTo559/ls/n0/z589Xa2qqjR4+6+mQ1mKxVVVU6dOiQfvrpJy1atEj37t3Ttm3blJaWpn379rme1Ua47yvc8VjBXHIHc8n7rMwlhEOJHmEmTZokn8834Kflx48fD/jps1dqaqrV+qEymKy9jh07ppKSEl25ckWzZ892M6Yk+6z3799XS0uLVq1aFTrW09MjSUpISNCdO3eUkZERFVklKS0tTYmJifL5fKFjM2bMUDAYVEdHhxzHiZqs+/btU25urjZs2CBJmjVrll6+fKmNGzdq7969io+Pjl1ob3pcJSQkaOLEiR6l8gZzyR3MJeaSLebS8IqOf3VEzHEczZ8/X5cvX+5z/PLly1q8eHHY+2RmZg5YX1lZ+cb1Q2UwWSXp6NGjOnDggC5duqQFCxa4mrGXbdZAIKDGxkbV19eHbqtXr1ZOTo7q6+uVnp4eNVklacmSJbp3717oCVWSmpqalJaW5toT1WCzvnr1asATks/nk/n3hdCuZbX1psfVggULlJiY6FEqbzCX3MFcip6szCWENbyvY8RQ6L00T3l5ubl9+7bZvn27GTNmjGlpaTHGGJObm9vnFcbV1dXG5/OZ0tJS88cff5jS0tJhv5RUpFkPHz5sHMcx586dM21tbaFbe3t71GXtbzhfBW+b9eHDhyY5Odls3brV3Llzx1y8eNGkpKSYgwcPRl3W/fv3m7Fjx5rTp0+b5uZmU1lZaTIyMsznn3/uas729nZTV1dn6urqjCRz/PhxU1dXF7rkVWFhocnNzQ2t772U1I4dO8zt27dNeXl5TF9KirkUHVn7Yy4NTVbmEsKhRI9QP/74o5k6dapxHMfMmzfPXL9+PfSx7Oxsk5eX12f92bNnzfTp001iYqIJBALm/PnzUZl16tSpRtKA2/79+6Mua3/D+WRljH3Wmpoas2jRIjNq1Cjz0UcfmUOHDpmurq6oy9rZ2Wm+++47k5GRYZKSkkx6errZsmWLefbsmasZr127Fvb/Xm+2vLw8k52d3ec+VVVVZu7cucZxHDNt2jRTVlbmasZox1zyPmt/zKWhycpcQjhxxkTR7yEAAACAEYA90QAAAIAlSjQAAABgiRINAAAAWKJEAwAAAJYo0QAAAIAlSjQAAABgiRINAAAAWKJEAwAAAJYo0QAAAIAlSjQAAABgiRINAAAAWKJEAx548uSJUlNTVVJSEjr222+/yXEcVVZWepgMQKxiLgF24owxxusQQCyqqKjQmjVrVFNTo0AgoLlz52rlypU6ceKE19EAxCjmEhA5SjTgoYKCAl25ckUff/yxGhoadOPGDSUlJXkdC0AMYy4BkaFEAx56/fq1Zs6cqb/++ks3b97U7NmzvY4EIMYxl4DIsCca8FBzc7NaW1vV09OjP//80+s4AMBcAiLEmWjAIx0dHVq4cKHmzJmjQCCg48ePq7GxUX6/3+toAGIUcwmIHCUa8Mju3bt17tw5NTQ0KDk5WTk5ORo7dqwuXrzodTQAMYq5BESO7RyAB6qqqnTixAmdOnVK77//vuLj43Xq1Cn9+uuvKisr8zoegBjEXALscCYaAAAAsMSZaAAAAMASJRoAAACwRIkGAAAALFGiAQAAAEuUaAAAAMASJRoAAACwRIkGAAAALFGiAQAAAEuUaAAAAMASJRoAAACwRIkGAAAALFGiAQAAAEuUaAAAAMASJRoAAACwRIkGAAAALFGiAQAAAEtWJfrTTz/V9u3b3coyYjQ2Nio7O1ujR4/WlClTVFxcLGOM17EAAAAwTBK8DjDSvHjxQp999plycnJ048YNNTU1KT8/X2PGjNGuXbu8jgcAAIBhEGciPIWan5+vX375pc+xBw8eaNq0aW7kilplZWX69ttv9ejRI40aNUqSVFpaqh9++EF///234uLiPE4IAAAAt0W8neP7779XZmamvvzyS7W1tamtrU3p6elh127evFnJyclvvT18+HDIvonhVFtbq+zs7FCBlqQVK1aotbVVLS0t3gUDAADAsIl4O8e4cePkOI7ee+89paamvnVtcXGxvv7667eumTx5cqRfOqoEg8EBZ9/9fn/oYx9++KEHqQAAADCcXNkTnZKSopSUFDc+dVTov2Wjd0cMWzkAAABigyuXuHuXt3OkpqYqGAz2Ofb48WNJ/zkjDQAAgHeb1Zlox3HU3d39P9e9y9s5MjMztWfPHnV0dMhxHElSZWWlJk+eHHMvsgQAAIhVEV+dQ5I2btyo+vp6nTlzRsnJyZowYYLi42Pr/VqeP3+u6dOna+nSpdqzZ4/u3r2r/Px8FRUVcYk7AACAGGFVopuampSXl6eGhga9fv06Ji9xJ/37ZisFBQX6/fffNX78eG3evFlFRUXsiQYAAIgRViUaAAAAgEsvLAQAAADeZZRoAAAAwBIlGgAAALBEiQYAAAAsUaIBAAAAS5RoAAAAwBIlGgAAALBEiQYAAAAsUaIBAAAAS5RoAAAAwBIlGgAAALD0D+ZEaZs4sAqCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe053310400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.00082    0.00082\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe05a9b3748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "\u001b[33mparameter swe.cvisc never used\u001b[0m\n",
      "main:  1.5110516548156738\n",
      "   evolve:  0.003922462463378906\n",
      "      unsplitFluxes:  0.003696441650390625\n",
      "         limiting:  0.0026841163635253906\n",
      "         interfaceStates:  7.510185241699219e-05\n",
      "         riemann:  0.00016427040100097656\n",
      "         transverse flux addition:  0.0004930496215820312\n",
      "   vis:  0.5120527744293213\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<swe.simulation.Simulation at 0x7fe053310d68>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a82a6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       1.4       1.4       1.4       1.4       1.4       1.4       1.4       1.4 \n",
      "       1.4       1.4    1.4001    1.4007    1.4007    1.4001       1.4       1.4 \n",
      "       1.4    1.4001    1.4043    1.4219    1.4219    1.4043    1.4001       1.4 \n",
      "       1.4    1.4007    1.4219    1.4973    1.4973    1.4219    1.4007       1.4 \n",
      "       1.4    1.4007    1.4219    1.4973    1.4973    1.4219    1.4007       1.4 \n",
      "       1.4    1.4001    1.4043    1.4219    1.4219    1.4043    1.4001       1.4 \n",
      "       1.4       1.4    1.4001    1.4007    1.4007    1.4001       1.4       1.4 \n",
      "       1.4       1.4       1.4       1.4       1.4       1.4       1.4       1.4 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "p = pyro_sim.sim.cc_data.get_var(\"height\")\n",
    "p.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "problem_name = \"advect\"\n",
    "param_file = \"inputs.advect\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\", \"swe.riemann=HLLC\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the advect problem...\u001b[0m\n",
      "cc data: nx = 8, ny = 8, ng = 4\n",
      "         nvars = 4\n",
      "         variables:\n",
      "          height: min:    1.0000000001    max:    1.6257840096\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "      x-momentum: min:    1.0000000001    max:    1.6257840096\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "      y-momentum: min:    1.0000000001    max:    1.6257840096\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "            fuel: min:    0.6150878556    max:    1.6257840096\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:3285: UserWarning: Attempting to set identical bottom==top results\n",
      "in singular transformations; automatically expanding.\n",
      "bottom=1.4142135623730951, top=1.4142135623730951\n",
      "  'bottom=%s, top=%s') % (bottom, top))\n",
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:3285: UserWarning: Attempting to set identical bottom==top results\n",
      "in singular transformations; automatically expanding.\n",
      "bottom=0.0, top=0.0\n",
      "  'bottom=%s, top=%s') % (bottom, top))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a7e8cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.00096    0.00096\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04ab4a7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "\u001b[33mparameter swe.cvisc never used\u001b[0m\n",
      "main:  1.2293202877044678\n",
      "   evolve:  0.0036513805389404297\n",
      "      unsplitFluxes:  0.003047466278076172\n",
      "         limiting:  0.0008172988891601562\n",
      "         interfaceStates:  0.00014591217041015625\n",
      "         riemann:  0.00019502639770507812\n",
      "         transverse flux addition:  0.0012941360473632812\n",
      "   vis:  0.5489068031311035\n",
      "\n",
      "          \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<swe.simulation.Simulation at 0x7fe04a7e8588>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a85b4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         1         1   0.99998   0.99985   0.99985   0.99998         1         1 \n",
      "         1         1    1.0003     1.002     1.002    1.0003         1         1 \n",
      "         1    1.0003    1.0151    1.0996    1.1005     1.016    1.0003   0.99998 \n",
      "         1    1.0021    1.0945    1.6239    1.6298    1.1005     1.002   0.99985 \n",
      "         1     1.002    1.0936     1.618    1.6239    1.0996     1.002   0.99985 \n",
      "         1    1.0003    1.0142    1.0936    1.0945    1.0151    1.0003   0.99998 \n",
      "         1         1    1.0003     1.002    1.0021    1.0003         1         1 \n",
      "         1         1         1         1         1         1         1         1 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "p = pyro_sim.sim.cc_data.get_var(\"x-momentum\")\n",
    "p.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "problem_name = \"dam\"\n",
    "param_file = \"inputs.dam.x\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=16\",  \"mesh.ny=4\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the dam problem...\u001b[0m\n",
      "cc data: nx = 16, ny = 4, ng = 4\n",
      "         nvars = 4\n",
      "         variables:\n",
      "          height: min:    0.1250000000    max:    1.0000000000\n",
      "                  BCs: -x: outflow      +x: outflow      -y: reflect-even +y: reflect-even\n",
      "      x-momentum: min:    0.0000000000    max:    0.0000000000\n",
      "                  BCs: -x: outflow      +x: outflow      -y: reflect-even +y: reflect-even\n",
      "      y-momentum: min:    0.0000000000    max:    0.0000000000\n",
      "                  BCs: -x: outflow      +x: outflow      -y: reflect-odd  +y: reflect-odd \n",
      "            fuel: min:    0.0000000000    max:    1.0000000000\n",
      "                  BCs: -x: outflow      +x: outflow      -y: reflect-even +y: reflect-even\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:2961: UserWarning: Attempting to set identical left==right results\n",
      "in singular transformations; automatically expanding.\n",
      "left=0.0, right=0.0\n",
      "  'left=%s, right=%s') % (left, right))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a9c79b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.00010    0.00010\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a672c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "\u001b[33mparameter swe.cvisc never used\u001b[0m\n",
      "main:  1.1560947895050049\n",
      "   evolve:  0.004359245300292969\n",
      "      unsplitFluxes:  0.0036864280700683594\n",
      "         limiting:  0.0018572807312011719\n",
      "         interfaceStates:  9.846687316894531e-05\n",
      "         riemann:  0.00026535987854003906\n",
      "         transverse flux addition:  0.0010950565338134766\n",
      "   vis:  0.5056569576263428\n",
      "\n",
      "          The script analysis/dam_compare.py can be used to compare\n",
      "          this output to the exact solution.\n",
      "          \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<swe.simulation.Simulation at 0x7fe04a9c7240>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a9f6e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0 \n",
      "         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0         0 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "p = pyro_sim.sim.cc_data.get_var(\"y-momentum\")\n",
    "p.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kelvin-Helmholtz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "problem_name = \"kh\"\n",
    "param_file = \"inputs.kh\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=16\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[33mwarning, key: driver.splitting not defined\u001b[0m\n",
      "\u001b[33mwarning, key: io.tplot not defined\u001b[0m\n",
      "\u001b[1minitializing the Kelvin-Helmholtz problem...\u001b[0m\n",
      "cc data: nx = 16, ny = 8, ng = 4\n",
      "         nvars = 4\n",
      "         variables:\n",
      "          height: min:    1.0000000000    max:    1.0000000000\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "      x-momentum: min:   -0.4997234578    max:    0.4997234578\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "      y-momentum: min:   -0.0092387953    max:    0.0092387953\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "            fuel: min:    0.0002765422    max:    0.9997234578\n",
      "                  BCs: -x: periodic     +x: periodic     -y: periodic     +y: periodic    \n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:3285: UserWarning: Attempting to set identical bottom==top results\n",
      "in singular transformations; automatically expanding.\n",
      "bottom=1.0, top=1.0\n",
      "  'bottom=%s, top=%s') % (bottom, top))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04aa1aa20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.00033    0.00033\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04aa2e128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "\u001b[33mparameter swe.cvisc never used\u001b[0m\n",
      "main:  1.2434208393096924\n",
      "   evolve:  0.0065517425537109375\n",
      "      unsplitFluxes:  0.00631260871887207\n",
      "         limiting:  0.005168437957763672\n",
      "         interfaceStates:  0.00012350082397460938\n",
      "         riemann:  0.00015425682067871094\n",
      "         transverse flux addition:  0.0005147457122802734\n",
      "   vis:  0.5764517784118652\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<swe.simulation.Simulation at 0x7fe04aa1a9e8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04ae144e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972 \n",
      "   0.95895   0.95893   0.95893   0.95895   0.95896   0.95896   0.95896   0.95896   0.95895   0.95893   0.95893   0.95895   0.95896   0.95896   0.95896   0.95896 \n",
      "  0.041042   0.04104   0.04104  0.041042  0.041052  0.041065  0.041065  0.041052  0.041042   0.04104   0.04104  0.041042  0.041052  0.041065  0.041065  0.041052 \n",
      "0.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.00027654 \n",
      "0.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.000276540.00027654 \n",
      "  0.041052  0.041065  0.041065  0.041052  0.041042   0.04104   0.04104  0.041042  0.041052  0.041065  0.041065  0.041052  0.041042   0.04104   0.04104  0.041042 \n",
      "   0.95896   0.95896   0.95896   0.95896   0.95895   0.95893   0.95893   0.95895   0.95896   0.95896   0.95896   0.95896   0.95895   0.95893   0.95893   0.95895 \n",
      "   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972   0.99972 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "f = pyro_sim.sim.cc_data.get_var(\"fuel\")\n",
    "f.pretty_print(show_ghost=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "problem_name = \"quad\"\n",
    "param_file = \"inputs.quad\"\n",
    "other_commands = [\"driver.max_steps=1\", \"mesh.nx=8\",  \"mesh.ny=8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mpyro ...\u001b[0m\n",
      "\u001b[1minitializing the quadrant problem...\u001b[0m\n",
      "cc data: nx = 8, ny = 8, ng = 4\n",
      "         nvars = 4\n",
      "         variables:\n",
      "          height: min:    0.1379928315    max:    1.4000000000\n",
      "                  BCs: -x: outflow      +x: outflow      -y: outflow      +y: outflow     \n",
      "      x-momentum: min:    0.0000000000    max:    0.6419273788\n",
      "                  BCs: -x: outflow      +x: outflow      -y: outflow      +y: outflow     \n",
      "      y-momentum: min:    0.0000000000    max:    0.6419273788\n",
      "                  BCs: -x: outflow      +x: outflow      -y: outflow      +y: outflow     \n",
      "            fuel: min:    0.0000000000    max:    1.4000000000\n",
      "                  BCs: -x: outflow      +x: outflow      -y: outflow      +y: outflow     \n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/alice/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py:3285: UserWarning: Attempting to set identical bottom==top results\n",
      "in singular transformations; automatically expanding.\n",
      "bottom=0.0, top=0.0\n",
      "  'bottom=%s, top=%s') % (bottom, top))\n"
     ]
    },
    {
     "data": {
      "image/png": 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65v1YzUp3Q1wCwoeYZD+mc4SIw+H7P6thGH51zXbt2qUVK1aouLhYo0eP1gcffKB58+Zp0KBBWrJkSYvnxMTE2PbkMwBtC+aJhd0JcQkIH55YaD+SaJvFx8fL6XT6jTqfOHHCb3S62ZIlS5Sbm+udQ33FFVfo7Nmz+sEPfqBFixYpKor/8YFIEswTCwEgFHhiof3IxmwWHR2ttLQ0lZaW+tSXlpYqMzOzxXPOnTvnlyg7nU4ZhtHman0A4eFRVEAFAEKFmGQ/RqJDIC8vT7m5uUpPT1dGRobWrl2ryspKzZ49W5I0ffp0JSUleXfqyMnJUWFhoUaNGuWdzrFkyRJNmjRJTicLAYBI4zYccpuM6pgdB4COZBaXiEnWkUSHwJQpU3Tq1CktX75c1dXVGjFihEpKSpSSkiJJqqys9Bl5Xrx4sRwOhxYvXqyPPvpI/fv3V05OjlasWBGuWwDQBrfHqSZP23/guj2eEPUGAMzjEjHJOpLoEJkzZ47mzJnT4rGvPiShR48eWrp0qZYuXRqCngGwqvkJYGZtACBUzOISMck6kmgAsMhjmC/S8bCcAUAImcUlYpJ1JNEAYJEdj/0GACt47Lf9SKK7uL4v7lcPR89wdwPd0Ld0b7i70OHcDV9IWuRX75FDHpOvRs2OdyevXFoqVx8+wBEeN/73jeHuQocyztZLLTzQ2CwuEZOsI4kGAIsaPU45TBYWNpocB4COZBaXiEnWkUQDgEUeBfCwFUZ9AISQWVwiJllHEg0AFhkBTOcw+MACEEJmcYmYZB1JNABYxGO/AUQaHvttP5JoALCI3TkARBp257AfSTQAWNRkRMlh8oHUxAcWgBAyi0vEJOv4CQKARc1fm5oVAAgVO2LS7t27lZOTo8TERDkcDm3durXN9q+++qomTJig/v37y+VyKSMjQzt27GjvLUUckmgAsIgkGkCksSMmnT17ViNHjtSTTz4ZUPvdu3drwoQJKikpUVlZma677jrl5OSovLw86GtHIqZzAIBFLCwEEGnsWFiYnZ2t7OzsgNsXFRX5vF65cqW2bdumN954Q6NGjQr6+pGGJBoALCKJBhBpAk2i6+rqfOpjYmIUExNjT588Hp05c0b9+vWz5f1DjekcAGCR23CoyYhqs7hJogGEkFlcao5JycnJiouL85aCggLb+vTYY4/p7Nmzmjx5sm3XCCVGogHAIkaiAUSaQEeiq6qq5HK5vPV2jUJv3LhRy5Yt07Zt2zRgwABbrhFqJNEAYBFJNIBIE2gS7XK5fJJoO2zatEkzZ87U5s2bdf3119t6rVAiiQYAi0iiAUSaSHli4caNG3X33Xdr48aNuummm0JyzVAhiQYAiwzDIcPkA8nsOAB0JLO41J6Y9Pnnn+uDDz7wvj527JgqKirUr18/DR48WPn5+froo4/0/PPPSzqfQE+fPl0/+9nPdPXVV6umpkaS1KtXL8XFxQV9/UjDwkIAsMhsUWFzAYBQsSMmHThwQKNGjfJuT5eXl6dRo0bpoYcekiRVV1ersrLS237NmjVqamrS3LlzNWjQIG+ZN29ex9xkmDESDQAWMRININLYMRI9fvx4GYbR6vENGzb4vN61a1fQ1+hMSKIBwCLmRAOINJEyJ7orI4kGAIsYiQYQaewYiYYvkmgAsMgIYCSaDywAoWQWl4hJ1pFEA4BFbjkkkw8kt/jAAhA6ZnGJmGQdSTQAWMR0DgCRhukc9iOJBgCLPIZDDhYWAoggZnGJmGQdSTQAWGQY54tZGwAIFbO4REyyjiQaACxiOgeASMN0DvuRRAOARW5PlORp++lfbpPjANCRzOISMck6kmgAsIjpHAAiDdM57EcSDQAWnf+wMpvOEaLOAIDM4xIxyTrG8kOkuLhYqampio2NVVpamvbs2dNm+9OnT2vu3LkaNGiQYmNjNXz4cJWUlISotwCC0Tz30KwEK5i40djYqOXLl2vo0KGKjY3VyJEjtX37diu3BaATsyMmwRdJdAhs2rRJ8+fP16JFi1ReXq6xY8cqOztblZWVLbZvaGjQhAkT9OGHH+qVV17R+++/r6efflpJSUkh7jmAQBgBlmAEGzcWL16sNWvW6Oc//7kOHTqk2bNn61//9V9VXl7e7vsC0Hl1dEyCP5LoECgsLNTMmTM1a9YsDR8+XEVFRUpOTtbq1atbbL9+/Xp9+umn2rp1q8aMGaOUlBRdc801GjlyZIh7DiAQhscRUJGkuro6n1JfX9/iewYbN1544QU9+OCDuvHGG3XxxRfr3nvv1cSJE/XYY4/Zdt8AIlegMQntRxJts4aGBpWVlSkrK8unPisrS3v37m3xnNdff10ZGRmaO3euEhISNGLECK1cuVJut7vV69TX1/t9OAMIkUC+Nv3HV6fJycmKi4vzloKCAr+3a0/cqK+vV2xsrE9dr1699NZbb3XQTQaPuASEUYAxCe3HwkKbnTx5Um63WwkJCT71CQkJqqmpafGco0eP6ve//71uv/12lZSU6M9//rPmzp2rpqYmPfTQQy2eU1BQoIcffrjD+w/AXDC7c1RVVcnlcnnrY2Ji/Nq2J25MnDhRhYWFuvbaazV06FD97ne/07Zt29r849tuxCUgfNidw36MRIeIw+H7F59hGH51zTwejwYMGKC1a9cqLS1Nt912mxYtWtTq17iSlJ+fr9raWm+pqqrq0P4DaF0wCwtdLpdPaSmJbhZM3PjZz36mSy+9VMOGDVN0dLTuu+8+zZgxQ06ns+NuNEjEJSB8WFhoP0aibRYfHy+n0+k3enTixAm/UaZmgwYNUs+ePX0+/IYPH66amho1NDQoOjra75yYmJg2P4wB2CiQr0aD+MBqT9zo37+/tm7dqi+++EKnTp1SYmKiFi5cqNTU1ICv29GIS0AYmcUlkmjLGIm2WXR0tNLS0lRaWupTX1paqszMzBbPGTNmjD744AN5PB5v3ZEjRzRo0KAWE2gA4WV4AiuBak/caBYbG6ukpCQ1NTVpy5Ytuvnmm9tzSwA6uY6MSWgZSXQI5OXl6ZlnntH69et1+PBhLViwQJWVlZo9e7Ykafr06crPz/e2v/fee3Xq1CnNmzdPR44c0a9//WutXLlSc+fODdctAGiDHftEBxs33nnnHb366qs6evSo9uzZoxtuuEEej0c//vGPO/ReAXQOTOewH9M5QmDKlCk6deqUli9frurqao0YMUIlJSVKSUmRJFVWVioq6p9/zyQnJ2vnzp1asGCBrrzySiUlJWnevHl64IEHwnULAMx08CKdYOPGF198ocWLF+vo0aPq3bu3brzxRr3wwgvq27dvx3YMQOfB4kFbkUSHyJw5czRnzpwWj+3atcuvLiMjQ2+//bbNvQLQEQIZ1WnPqE8wcWPcuHE6dOhQ0NcA0DWZxSVGoq0jiQYAqwJ5/BcjQgBCySwuEZMsI4kGAKs6eHcOALCM3TlsRxINAFYxEg0g0jASbTuSaACwipFoAJGGkWjbkUQDgEXBPPYbAEKBx37bjyQaAKxiOgeASMN0DtuRRAOARQ6PQw5P21+Nmh0HgI5kFpeISdaRRAOAVYxEA4g0jETbjiQaAKxiYSGASMPCQtuRRAOAVYxEA4g0jETbjiQaAKwiiQYQaUiibUcSDQBWkUQDiDQk0baLCncHItVdd92l3bt3h7sbADqB5lXwZgUAQoWYZD+S6FacOXNGWVlZuvTSS7Vy5Up99NFH4e4SgEhlBFgAIFSISbYjiW7Fli1b9NFHH+m+++7T5s2bNWTIEGVnZ+uVV15RY2NjuLsHAACAMCKJbsOFF16oefPmqby8XPv379cll1yi3NxcJSYmasGCBfrzn/8c7i4CiAAOSQ7DpIS7kwC6FdO4FO4OdgEk0QGorq7Wzp07tXPnTjmdTt14443605/+pMsvv1yPP/54uLsHINya92M1KwAQKsQk25FEt6KxsVFbtmzRd7/7XaWkpGjz5s1asGCBqqur9dxzz2nnzp164YUXtHz58nB3FUC4eQIsABAqNsWk4uJipaamKjY2VmlpadqzZ0+b7YuKinTZZZepV69eSk5O1oIFC/TFF1+07+IRhi3uWjFo0CB5PB5NnTpV+/fv1ze/+U2/NhMnTlTfvn3D0DsAkaT561GzNgAQKmZxqT0xadOmTZo/f76Ki4s1ZswYrVmzRtnZ2Tp06JAGDx7s1/7FF1/UwoULtX79emVmZurIkSO66667JKlLfJNPEt2Kxx9/XP/2b/+m2NjYVttccMEFOnbsWAh7BSAisU80gEhjwz7RhYWFmjlzpmbNmiXp/Cjzjh07tHr1ahUUFPi137dvn8aMGaNp06ZJkoYMGeIdnOwKmM7Ritzc3DYTaADwYos7AJEmwJhUV1fnU+rr61t8u4aGBpWVlSkrK8unPisrS3v37m3xnGuuuUZlZWXepPno0aMqKSnRTTfdZP3+IgAj0QBgEdM5AESaQKdzJCcn+9QvXbpUy5Yt82t/8uRJud1uJSQk+NQnJCSopqamxWvcdttt+uSTT3TNNdfIMAw1NTXp3nvv1cKFC4O6l0hFEg0AVnkc54tZGwAIFbO49I9jVVVVcrlc3uqYmJg239bh8H1PwzD86prt2rVLK1asUHFxsUaPHq0PPvhA8+bN06BBg7RkyZIAbyRykUQDgEWMRAOINIGORLtcLp8kujXx8fFyOp1+o84nTpzwG51utmTJEuXm5nrnUF9xxRU6e/asfvCDH2jRokWKiurcs4o7d+8BIBIwJxpApOngmBQdHa20tDSVlpb61JeWliozM7PFc86dO+eXKDudThmGIcPo/EGRkWgAsCqAkWiSaAAhZRaX2hGT8vLylJubq/T0dGVkZGjt2rWqrKzU7NmzJUnTp09XUlKSd6eOnJwcFRYWatSoUd7pHEuWLNGkSZPkdDrbcVORhSQaAKxiizsAkcaGLe6mTJmiU6dOafny5aqurtaIESNUUlKilJQUSVJlZaXPyPPixYvlcDi0ePFiffTRR+rfv79ycnK0YsWK4C8egUiiAcAih+d8MWsDAKFiFpfaG5PmzJmjOXPmtHhs165dPq979OihpUuXaunSpe27WIRjTjQAAAAQJEaiAcAqpnMAiDQ2TOeAL5JoALCILe4ARJpAt7hD+5FEA0BH4AMJQKQhLtmKOdEhUlxcrNTUVMXGxiotLU179uwJ6LyXX35ZDodDt9xyi809BNBezQt4zAoAhAoxyX4k0SGwadMmzZ8/X4sWLVJ5ebnGjh2r7OxsVVZWtnne8ePHdf/992vs2LEh6imAduFhKwAiDTHJdiTRIVBYWKiZM2dq1qxZGj58uIqKipScnKzVq1e3eo7b7dbtt9+uhx9+WBdffHEIewsgWM1zD80KAIQKMcl+JNE2a2hoUFlZmbKysnzqs7KytHfv3lbPW758ufr376+ZM2cGdJ36+nrV1dX5FAAhwkh0i4hLQBgRk2xHEm2zkydPyu12KyEhwac+ISFBNTU1LZ7zhz/8QevWrdPTTz8d8HUKCgoUFxfnLcnJyZb6DSAIJNEtIi4BYURMsh1JdIg4HA6f14Zh+NVJ0pkzZ3THHXfo6aefVnx8fMDvn5+fr9raWm+pqqqy3GcAgWFhYcuIS0D4EJPsxxZ3NouPj5fT6fQbdT5x4oTf6LQk/eUvf9GHH36onJwcb53Hc/7/9B49euj999/X0KFD/c6LiYlRTExMB/ceQEB42EqLiEtAGPGwFdsxEm2z6OhopaWlqbS01Ke+tLRUmZmZfu2HDRumP/7xj6qoqPCWSZMm6brrrlNFRQVfhwIRyK6FhcFujXn69GnNnTtXgwYNUmxsrIYPH66SkpJ23hWAzoyFhfZjJDoE8vLylJubq/T0dGVkZGjt2rWqrKzU7NmzJUnTp09XUlKSCgoKFBsbqxEjRvic37dvX0nyqwcQIWwYiW7eGrO4uFhjxozRmjVrlJ2drUOHDmnw4MF+7RsaGjRhwgQNGDBAr7zyii666CJVVVWpT58+wV0YQNfASLTtSKJDYMqUKTp16pSWL1+u6upqjRgxQiUlJUpJSZEkVVZWKiqKLwWAzsqOx35/eWtMSSoqKtKOHTu0evVqFRQU+LVfv369Pv30U+3du1c9e/aUJG+MAdD98Nhv+5FIwJYhAAAgAElEQVREh8icOXM0Z86cFo/t2rWrzXM3bNjQ8R0C0HE8/yhmbSS/bd5amjfcvDXmwoULferb2hrz9ddfV0ZGhubOnatt27apf//+mjZtmh544AE5nc5g7gZAV2AWl1hYaBnDnwBgkSPAIknJyck+2761NKrcnq0xjx49qldeeUVut1slJSVavHixHnvsMa1YsaKD7hJAZxJoTEL7MRINAFYFMSe6qqpKLpfLW93W7hWBbo0pnd/FZ8CAAVq7dq2cTqfS0tL08ccf69FHH9VDDz0UyF0A6EqYE207kmgAsCiYOdEul8sniW5JsFtjStKgQYPUs2dPn6kbw4cPV01NjRoaGhQdHW1+IwC6DOZE24/pHABgVQc/sTDYrTElacyYMfrggw+8+8pL0pEjRzRo0CASaKA74omFtiOJBgCLHEYATwcL8gMrLy9PzzzzjNavX6/Dhw9rwYIFfltj5ufne9vfe++9OnXqlObNm6cjR47o17/+tVauXKm5c+d25K0C6CRM4xJJtGVM5wAAq2zYJzrYrTGTk5O1c+dOLViwQFdeeaWSkpI0b948PfDAA8FdGEDXwJxo25FEA4BFduwTLQW/NWZGRobefvvt4C8EoMthTrT9SKIBwCobRqIBwBJGom1HEg0AFtk1Eg0A7cVItP1IogHAqiCeWAgAIcETC21HEg0AFjESDSDSMBJtP5JoALCKOdEAIg1zom1HEg0AFjkMQw6j7U8ks+MA0JHM4hIxyTqSaACwipFoAJGGkWjbkUQDgEXNTwAzawMAoWIWl4hJ1pFEA4BFLCwEEGlYWGg/kmgAsIrpHAAiDdM5bEcSDQAWMRININIwEm0/kmgAsIqRaACRhpFo25FEA0AHYFQHQKQhLtmLJBoALHJ4DDk8JvtEmxwHgI5kFpeISdaRRAOAVUznABBpmM5hO5JoALCIfaIBRBr2ibYfSTQAWMVINIBIw0i07UiiAcAitrgDEGnY4s5+UeHuAAB0ds0LeMwKAISKXTGpuLhYqampio2NVVpamvbs2RPQeS+//LIcDoduueWWdl03EpFEA4BVRoAFAELFhpi0adMmzZ8/X4sWLVJ5ebnGjh2r7OxsVVZWtnne8ePHdf/992vs2LHBXzSCkUQDgEXNX5uaFQAIlUBjUl1dnU+pr69v9T0LCws1c+ZMzZo1S8OHD1dRUZGSk5O1evXqVs9xu926/fbb9fDDD+viiy/u6NsMK5JoALDKMAIrABAqAcak5ORkxcXFeUtBQUGLb9fQ0KCysjJlZWX51GdlZWnv3r2tdmP58uXq37+/Zs6c2XH3FiFYWAgAFrGwEECkCXRhYVVVlVwul7c+JiamxfYnT56U2+1WQkKCT31CQoJqampaPOcPf/iD1q1bp4qKiuA630mQRAOARewTDSDSBLpPtMvl8kmiTd/X4fB5bRiGX50knTlzRnfccYeefvppxcfHB/z+nQlJNABY5THOF7M2ABAqZnEpyJgUHx8vp9PpN+p84sQJv9FpSfrLX/6iDz/8UDk5Of+8pOd85t6jRw+9//77Gjp0aFB9iDTMiQ6RYLaEefrppzV27FhdcMEFuuCCC3T99ddr//79IewtgKCwOweASNPBMSk6OlppaWkqLS31qS8tLVVmZqZf+2HDhumPf/yjKioqvGXSpEm67rrrVFFRoeTk5PbcVURhJDoEmreEKS4u1pgxY7RmzRplZ2fr0KFDGjx4sF/7Xbt2aerUqcrMzFRsbKxWrVqlrKws/elPf1JSUlIY7gBAWxwKYE50SHoCAOeZxaX2xKS8vDzl5uYqPT1dGRkZWrt2rSorKzV79mxJ0vTp05WUlKSCggLFxsZqxIgRPuf37dtXkvzqOyuS6BD48pYwklRUVKQdO3Zo9erVLa6CffHFF31eP/3003rllVf0u9/9TtOnTw9JnwEEIZDdN9idA0AomcWldsSkKVOm6NSpU1q+fLmqq6s1YsQIlZSUKCUlRZJUWVmpqKjuM8mBJNpmzVvCLFy40KfebEuYLzt37pwaGxvVr1+/VtvU19f77O1YV1fXvg4DCBoLC1tGXALCJ9CFhcGaM2eO5syZ0+KxXbt2tXnuhg0b2nfRCNV9/lwIk/ZsCfNVCxcuVFJSkq6//vpW2xQUFPjs89gV5hoBnYXDMAIq3Q1xCQgfYpL9SKJDJNAtYb5q1apV2rhxo1599VXFxsa22i4/P1+1tbXeUlVVZbnPAALkCbB0M8QlIIyISbZjOofNgt0S5st++tOfauXKlfrtb3+rK6+8ss22MTExrW6QDsBegYzqdMdRH+ISED5mcak7xqSOxki0zYLdEqbZo48+qkceeUTbt29Xenq63d0EYAVb3AGINMQk2zESHQLBbAkjnZ/CsWTJEr300ksaMmSIdxS7d+/e6t27d9juA0DLHB5DDpMHF5gdB4COZBaXiEnWkUSHQLBbwhQXF6uhoUHf//73fd5n6dKlWrZsWSi7DiAQbHEHINLYsMUdfJFEh0gwW8J8+OGH9ncIQIdhizsAkcauLe7wTyTRAGAVI9EAIg0j0bYjiQYAqwJZpMPnFYBQMotLxCTLSKIBwCKHxyOHp+3vRs2OA0BHMotLxCTrSKIBwCpD5g8uYNQHQCiZxSVikmXsEw0AFtn12O/i4mKlpqYqNjZWaWlp2rNnT6ttX331VaWnp6tv3776+te/rm9+85t64YUXrNwWgE6Mx37bjyQaAKwy9M9FPK2W4N5y06ZNmj9/vhYtWqTy8nKNHTtW2dnZqqysbLF9v379tGjRIu3bt0//8z//oxkzZmjGjBnasWOH9fsD0PmYxqVwd7DzI4kGAKtME+gAdu/4isLCQs2cOVOzZs3S8OHDVVRUpOTkZK1evbrF9uPHj9e//uu/avjw4Ro6dKjmzZunK6+8Um+99VZH3CGAzqaDYxL8kUQDgEUOtxFQkaS6ujqfUl9f7/d+DQ0NKisrU1ZWlk99VlaW9u7da9ofwzD0u9/9Tu+//76uvfbajrlJAJ1KoDEJ7UcSDQBWBTESnZycrLi4OG8pKCjwe7uTJ0/K7XYrISHBpz4hIUE1NTWtdqO2tla9e/dWdHS0brrpJv385z/XhAkTOvZeAXQOjETbjt05AMCqIB62UlVVJZfL5a2OiYlp9RSHw/GVtzD86r6sT58+qqio0Oeff67f/e53ysvL08UXX6zx48eb3wOAroWHrdiOJBoArAoiiXa5XD5JdEvi4+PldDr9Rp1PnDjhNzr9ZVFRUbrkkkskSd/85jd1+PBhFRQUkEQD3RFJtO2YzgEAVnkCLAGKjo5WWlqaSktLfepLS0uVmZkZ8PsYhtHinGsA3UAHxiS0jJFoALDI4fHI4ejYJxbm5eUpNzdX6enpysjI0Nq1a1VZWanZs2dLkqZPn66kpCTvnOqCggKlp6dr6NChamhoUElJiZ5//vlWd/MA0LWZxSWeWGgdSTQAWOUxJIfJV6Oe4L46nTJlik6dOqXly5erurpaI0aMUElJiVJSUiRJlZWVior655eJZ8+e1Zw5c/TXv/5VvXr10rBhw/TLX/5SU6ZMCfp2AHQBZnEpyJgEfyTRAGBVEHOigzFnzhzNmTOnxWO7du3yef2Tn/xEP/nJT4K+BoAuijnRtiOJBgDLAtkuig8sAKFkFpeISVaRRAOAVTaNRANAuzESbTuSaACwyu2WDHfbbTwmxwGgI5nFJWKSZSTRAGAVI9EAIg0j0bYjiQYAqzyGTOcXshIeQCiZxSVikmUk0QBgFSPRACINI9G2I4kGAKsMBZBEh6QnAHCeWVwiJllGEg0AVrGwEECkYWGh7UiiAcAqpnMAiDRM57AdSTQAWEUSDSDSkETbjiQaAKxidw4AkYbdOWxHEg0AFhmGR4bhMW0DAKFiFpeISdaRRAOAVR6PZPaBxAcWgFAyi0vEJMtIogHAKo9HcpBEA4ggZnGJmGQZSTQAWGUEMCeaRTwAQsksLhGTLCOJBgCLDI9HhslINPMPAYSSWVwiJllHEg0AVjESDSDSMBJtu6hwd6C7KC4uVmpqqmJjY5WWlqY9e/a02X7Lli26/PLLFRMTo8svv1yvvfZaiHoKIGgeI7ACAKFiU0win/knkugQ2LRpk+bPn69FixapvLxcY8eOVXZ2tiorK1tsv2/fPk2ZMkW5ubl67733lJubq8mTJ+udd94Jcc8BBMJwe2S43SaFr04BhI55XAo+JpHP+HIYBuP5dhs9erSuuuoqrV692ls3fPhw3XLLLSooKPBrP2XKFNXV1ek3v/mNt+6GG27QBRdcoI0bN7Z4jfr6etXX13tf19bWavDgwbpGN6qHenbg3QCBOX37t8LdhQ7nbvxCf/yvR3T69GnFxcWptrZWffv21dioHPVwtP171mQ0ao/nDe+53UFrcen4wSFy9WYMB+Hx/T9PCHcXOlTTuQa9+W/PBh2XmmNSZWWlT0yKiYlRTExMi+eEIp/pVAzYqr6+3nA6ncarr77qU/+jH/3IuPbaa1s8Jzk52SgsLPSpKywsNAYPHtzqdZYuXdo8+YlCodhc/vKXvxiGYRhVVVVBn1tVVWUxqnQexCUKJXTFSlz6clm6dGmLv8+hymc6ExYW2uzkyZNyu91KSEjwqU9ISFBNTU2L59TU1ATVXpLy8/OVl5fnfX369GmlpKT4/YUZaerq6pScnKyqqiq5XK5wd6dN9NUenamvzSOp/fr1kyQlJiaqqqpKffr0kcPhaPNcwzB05swZJSYmhqKrEYG4ZD/6ao/O1Nf2xiXDMHTq1Cn169dPUVH//GaotVHoUOUznQlJdIh89X9kwzDa/J872Patff0SFxcX8QFAklwuV6fop0Rf7dKZ+tr8gRMVFaWLLroo4PMiOXG0A3EpdOirPTpTX9sTl9oTk+zOZzoTJqXZLD4+Xk6n0++vrhMnTvj9ddZs4MCBQbUHAACwE/mMP5Jom0VHRystLU2lpaU+9aWlpcrMzGzxnIyMDL/2O3fubLU9AACAnchn/DmXLVu2LNyd6OpcLpeWLFmipKQkxcbGauXKlfrv//5vPfvss+rbt6+mT5+u/fv36/rrr5ckJSUlafHixYqJiVF8fLzWrVunZ555RmvXrg3qq2On06nx48erR4/InrXTWfop0Ve70Nfuo7P8/DpLPyX6ahf66i9c+UzECueqxu7kqaeeMlJSUozo6GjjqquuMt58803vsXHjxhl33nmnT/vNmzcbl112mdGzZ09j2LBhxpYtW0LcY9hlxYoVhiTj4MGDfsdyc3MNp9Np/OpXvwpDzwB0Rt/4xjcC2nXh61//ulFXV2dLH/Lz8w1JxtGjR1s8npqaamRkZNhybYQW+cw/sU80EGJ1dXVKSUnR9ddfr82bN3vrH3roIT3yyCMqLi7WvffeG8YeAuhMVq1apQceeEA//OEPNWzYML/jJ0+e1IoVKzRz5kw988wztvThhhtu0P79+/Xpp5/6Hfvss8/Ur18/3Xffffr5z39uy/WBcIj87yiALsblcunf//3ftWLFCv3f//2fhg0bpmeffVaPPPKIfvzjH5NAAwjKXXfdpcWLF6tHjx6aP3++3/HHH39cknTPPfe0eH5dXZ3+8Ic/KDs7u8Xjv/rVr3Tdddfp61//eqt9OHjwoNLS0lo8duDAAUlq9TjQWbGwEAiD+fPn62tf+5oKCgr029/+Vj/84Q81efJk/cd//Ee4uwagkxkwYIBycnL00ksv+Twhstn69et1xRVXaPTo0S2e/8wzz+i73/2unnvuOb9ja9as0aRJk/T888+3ev3Kykp98sknSk9Pb/F4WVmZJJJodD0k0UAY9OvXT/fee69eeukl3XrrrRo9erSef/75LrN3JoDQuueee/TZZ5/ptdde86l/55139L//+7+aNWtWq+fm5eVp/vz5mjFjhtasWeOt/9nPfqbZs2crPz+/zW/IzJLkAwcOKDY2VsOHDw/mloCIx3QOIEymTp2qRx99VL1799a2bdtafUoUAJjJysrS4MGDtW7dOt12223e+vXr1ys2Nla5ubltnv/YY48pNjZWs2fP1hdffKEvvvhCCxcu1PLly7VkyZI2zz148KAktTkSPXLkyE6xywUQDP6PBsKgrq5OM2bMkHR+0c+5c+e8j2wFgGBFRUXp7rvv1sMPP6zjx48rJSVF586d08svv6xbb71VF1xwgel7rFixQrGxsd551Y8++qjuv/9+0/PKysrUr18/DRkyxO/Yp59+qg8//FA33nhj0PcERDqmcwAh1tjYqFtvvVVHjx7V1q1b5fF49Oijj4a7WwA6ubvvvlsOh0MbNmyQJG3evFl1dXWtLihsSW1trXda2enTpwM6p7y8XCNHjmzx2Ntvvy1J+ta3vhVwH4DOgiQaCLFZs2Zp165d2rx5s26++Wbdcccdevrpp3XixIlwdw1AJ5acnKyJEyfq2WeflWEYWrdunS699FKNGzfO9FzDMHTffffp8ccf17p167R69WqtXLnSdCTa7XarpqZGF154YYvHt27dKqfTqaysrHbdExDJSKKBEFq8eLGef/55/eIXv9DEiRMlSQ8++KAaGhq821ABQHvNmjVLx48f1y9+8Qvt2bOnzQWFzTwej+655x6tWbNGL774ombMmKHZs2fr2WefVVFRkebOnavWHinhdDoVHx+v8vJyNTY2+hwrLy/Xc889p9tuu02DBg3qkPsDIgkPWwFCZO3atfrhD3+oxYsX65FHHvE5NnXqVJWUlOj48ePq27dvmHoIoLNrbGxUcnKyTp8+LY/Ho7/+9a8aMGBAm+f89Kc/1aJFi7Rp0ybdcsstPsc2bdqkO+64Q48//rjuu+++Fs9fsWKFFi9erG9/+9vKzc1VdHS0Dhw4oNWrV2vIkCHas2eP4uPjO+wegUhBEg2EQElJiSZNmqSpU6fqhRde8Dv+v//7v7ryyiu1bNkyPfTQQ2HoIYCuIj8/X48++qi+973v6b/+679M2//9739XRUWFMjIyWjz+hz/8Qf/yL/+i6OjoVt/jl7/8pZ544gm9//77amho0CWXXKLvfe97uv/++9WnT5923wsQyUiiAQAAgCAxJxoAAAAIEkk0AAAAECSSaAAAACBIJNE22717t3JycpSYmCiHw6GtW7eanvPmm28qLS1NsbGxuvjii/WLX/wiBD0FEEmIHQAQ2UiibXb27FmNHDlSTz75ZEDtjx07phtvvFFjx45VeXm5HnzwQf3oRz/Sli1bbO4pgEhC7ACAyMbuHCHkcDj02muv+e3D+WUPPPCAXn/9dR0+fNhbN3v2bL333nvat29fKLoJIMIQOwAg8vQIdwfga9++fX6PR504caLWrVunxsZG9ezZs8Xz6uvrVV9f733t8Xj06aef6sILL5TD4bC1z0B3YRiGzpw5o8TEREVFRcnj8ejjjz9Wnz59TH/PDMPQqVOn1K9fP0VF/fNLwJiYGMXExFjuW3tjh52IS4D92huXvnoegkcSHWFqamqUkJDgU5eQkKCmpiadPHmy1UenFhQU6OGHHw5FF4Fur6qqShdddJE+/vhjJScnW3qvpUuXatmyZZb71N7YYSfiEhA67Y1LzecheCTREeirfzk2z7hp6y/K/Px85eXleV/X1tZq8ODBukY3qodCPwIFvHbkj+HuQoer+9yjlKs+9D6Brfnf4weHyNW77ZGc5nMrKysVFxfnre+IUehm7YkddiIuAfZrUqPeUolfXKqqqpLL5Wr1vLq6OiUnJ/NESQtIoiPMwIEDVVNT41N34sQJ9ejRQxdeeGGr57X2lXAP9VQPBx9WCD1Xn6779WBzUtr8b6+vG+rVu+3lJY3/SGjj4uLa/GBrr/bGDjsRl4AQ+Efo+WpccrlcAcUapla1X9f9lOukMjIyVFpa6lO3c+dOpaenh2VOIwBzHhkBFTsROwAgtEiibfb555+roqJCFRUVks5vQ1VRUaHKykpJ57/unD59urf97Nmzdfz4ceXl5enw4cNav3691q1bp/vvvz8s/QdgzhPgf8EgdgBAZGM6h80OHDig6667zvu6eX7gnXfeqQ0bNqi6utr7oShJqampKikp0YIFC/TUU08pMTFRTzzxhG699daQ9x1AYNyGIbfJbqFmx7+K2AEAkY0k2mbjx49XW1txb9iwwa9u3LhxOnjwoI29AtCRApmuEex0DmIHAEQ2kmgAsKhJHjUG0AYA0HWQRAOARXZM5wAARDaSaACwyPOPYtYGANB1kEQDgEVuGXKbzHk2Ow4A6FxIogHAIrdxvpi1AQB0HSTRAGBRkxxqVNtP/WoyOQ4A6FxIogHAIo9xvpi1AQB0HSTRAGCRWw65TUaazY4DADoXkmgAsIgkGgC6H5JoALDIYzjkMdpOks2OAwA6l6hwdwAAOrsGOQMqANDZFRcXKzU1VbGxsUpLS9OePXvabL9lyxZdfvnliomJ0eWXX67XXnvN57hhGFq2bJkSExPVq1cvjR8/Xn/605982nz22WfKzc1VXFyc4uLilJubq9OnT/u02bFjh66++mr16dNH/fv316233qpjx451zE23giQaACwy/jES3VYxGIkG0Mlt2rRJ8+fP16JFi1ReXq6xY8cqOztblZWVLbbft2+fpkyZotzcXL333nvKzc3V5MmT9c4773jbrFq1SoWFhXryySf17rvvauDAgZowYYLOnDnjbTNt2jRVVFRo+/bt2r59uyoqKpSbm+s9fvToUd1888369re/rYqKCu3YsUMnT57U9773Pft+GJIchsGzaLuiuro6xcXFabxuVg9Hz3B3B93Qjo8rwt2FDld3xqMLvnFUtbW1crlc3t+znX9M0df7tD0mcfaMR1lXHPee2x0Rl4CO12Q0ape2+cUls1gTaLsvGz16tK666iqtXr3aWzd8+HDdcsstKigo8Gs/ZcoU1dXV6Te/+Y237oYbbtAFF1ygjRs3yjAMJSYmav78+XrggQckSfX19UpISNB//ud/6oc//KEOHz6syy+/XG+//bZGjx4tSXr77beVkZGh//u//9Nll12mV155RVOnTlV9fb2ios7H4jfeeEM333yz6uvr1bOnPfGGkWgAsMhtRAVUACDS1NXV+ZT6+voW2zU0NKisrExZWVk+9VlZWdq7d2+L5+zbt8+v/cSJE73tjx07ppqaGp82MTExGjdunLfNvn37FBcX502gJenqq69WXFyct016erqcTqeeffZZud1u1dbW6oUXXlBWVpZtCbREEg0AlnnkkEdRJoXpHAAiT3JysneucVxcXIsjypJ08uRJud1uJSQk+NQnJCSopqamxXNqamrabN/8r1mbAQMG+L33gAEDvG2GDBminTt36sEHH1RMTIz69u2rv/71r3r55ZfNbt8SkmgAsKjBcAZUACDSVFVVqba21lvy8/PbbO9w+A4IGIbhVxdse7M2Lb3/l9vU1NRo1qxZuvPOO/Xuu+/qzTffVHR0tL7//e/LzlnLbHEHABadH4k22eKOkWgAEcjlcgU0Jzo+Pl5Op9Nv1PnEiRN+I8nNBg4c2Gb7gQMHSjqfBA8aNKjVNn/729/83vuTTz7xtnnqqafkcrm0atUq7/Ff/vKXSk5O1jvvvKOrr77a9P7ag5FoALDIoyi5TYqHcAugE4uOjlZaWppKS0t96ktLS5WZmdniORkZGX7td+7c6W2fmpqqgQMH+rRpaGjQm2++6W2TkZGh2tpa7d+/39vmnXfeUW1trbfNuXPn5HT6ftvX/Nrj8bTndgPCSDQAWBTIwkE3GyEB6OTy8vKUm5ur9PR0ZWRkaO3ataqsrNTs2bMlSdOnT1dSUpJ3XvW8efN07bXX6j//8z918803a9u2bfrtb3+rt956S9L5aRrz58/XypUrdemll+rSSy/VypUr9bWvfU3Tpk2TdH73jxtuuEH33HOP1qxZI0n6wQ9+oO9+97u67LLLJEk33XSTHn/8cS1fvlxTp07VmTNn9OCDDyolJUWjRo2y7edBEg0AFnkCGGn2iCQaQOc2ZcoUnTp1SsuXL1d1dbVGjBihkpISpaSkSJIqKyu9W8xJUmZmpl5++WUtXrxYS5Ys0dChQ7Vp0yafnTZ+/OMf6+9//7vmzJmjzz77TKNHj9bOnTvVp08fb5sXX3xRP/rRj7y7eEyaNElPPvmk9/i3v/1tvfTSS1q1apVWrVqlr33ta8rIyND27dvVq1cv234e7BPdRbEfK8KtO+0TvaF8pL7Wp+2Fg+fOuHXXqPfYJ5q4BHSoUO4TDV+MRAOARR4jSh6T6RwexisAoEshiQYAi5oXD7bdhiQaALoSkmgAsMgjyW2YbXEHAOhKSKIBwKLAFhayxR0AdCUk0QBgUaPhVA+TJxI2MicaALoUkmgAsCiwfaIZiQaAroQkGgAsCmxhIUk0AHQlJNEAYJHHcMhjtrDQ5DgAoHMhiQYAizwBjESzsBAAuhaSaACwqNFwysnCQgDoVkiiAcCiwJ5YyEg0AHQlRPUQKS4uVmpqqmJjY5WWlqY9e/a02b6oqEiXXXaZevXqpeTkZC1YsEBffPFFiHoLIBhuSW45TErwiBsAELkYiQ6BTZs2af78+SouLtaYMWO0Zs0aZWdn69ChQxo8eLBf+xdffFELFy7U+vXrlZmZqSNHjuiuu+6SJD3++OMh7j0AM3aMRBM3ACCykUSHQGFhoWbOnKlZs2ZJOj9atGPHDq1evVoFBQV+7fft26cxY8Zo2rRpkqQhQ4Zo6tSp2r9/f6vXqK+vV319vfd1XV1dB98FgNYEs0/0V383Y2JiFBMT49c+FHHDbsQlAF0Z0zls1tDQoLKyMmVlZfnUZ2Vlae/evS2ec80116isrMz74Xf06FGVlJTopptuavU6BQUFiouL85bk5OSOuwkAbWoynGo0KU3/WHiYnJzs87vaUkIcqrhhN+ISgK6MkWibnTx5Um63WwkJCT71CQkJqo1ag14AACAASURBVKmpafGc2267TZ988omuueYaGYahpqYm3XvvvVq4cGGr18nPz1deXp73dV1dHR9YQIgEs090VVWVXC6Xt76lUehQxQ27EZcAdGUk0SHicPh+wBqG4VfXbNeuXVqxYoWKi4s1evRoffDBB5o3b54GDRqkJUuWtHhOa18JA7BfME8sdLlcPkl0W+yOG3YjLgHoykiibRYfHy+n0+k3enTixAm/UaZmS5YsUW5urncu5BVXXKGzZ8/qBz/4gRYtWqSoKGbhAJGko59YSNwAgMhHVLVZdHS00tLSVFpa6lNfWlqqzMzMFs85d+6c3wee0+mUYRgyeGADEHE8igqoBIq4AQCRj5HoEMjLy1Nubq7S09OVkZGhtWvXqrKyUrNnz5YkTZ8+XUlJSd4FRjk5OSosLNSoUaO8X8suWbJEkyZNktPZ9lPRAISe23DIbTLSbHb8q4gbABDZSKJDYMqUKTp16pSWL1+u6upqjRgxQiUlJUpJSZEkVVZW+owgLV68WA6HQ4sXL9ZHH32k/v37KycnRytWrAjXLQBog9vjVJOn7UTV7fEE9Z7EDQCIbA6D7/m6pLq6OsXFxWm8blYPR89wdwfd0I6PK8LdhQ5Xd8ajC75xVLW1tXK5XN7fs5lvTlZ077Z/zxo+b9S6cf/lPbc7Ii4BHa/JaNQubfOLS2axJtB2aB0j0QBgkccwXzjoYbgCALoUkmgAsMiOx34DACIbSTQAWOSRQx6ZjESbHAcAdC4k0V3ca0f+KFcfRsAQehMTvxnuLnS4JqNR0lG/+kaPUw6ThYWNJscBAJ0LSTQAWORRAA9bYSQaALoUkmgAsMgIYDqHQRINAF0KSTQAWNTRj/0GAEQ+kmgAsIjdOQCg+yGJBgCLmowoOUyS5CaSaADoUkiiAcAipnMAQPfD0AgAWNScRJsVAOjsiouLlZqaqtjYWKWlpWnPnj1ttt+yZYsuv/xyxcTE6PLLL9drr73mc9wwDC1btkyJiYnq1auXxo8frz/96U8+bT777DPl5uYqLi5OcXFxys3N1enTp1u83gcffKA+ffqob9++1m40ACTRAGARSTSA7mDTpk2aP3++Fi1apPLyco0dO1bZ2dmqrKxssf2+ffs0ZcoU5ebm6r333lNubq4mT56sd955x9tm1apVKiws1JNPPql3331XAwcO1IQJE3TmzBlvm2nTpqmiokLbt2/X9u3bVVFRodzcXL/rNTY2aurUqRo7dmzH33wLSKIBwCKSaADdQWFhoWbOnKlZs2Zp+PDhKioqUnJyslavXt1i+6KiIk2YMEH5+fkaNmyY8vPz9Z3vfEdFRUWSzo9CFxUVadGiRfre976nESNG6LnnntO5c+f00ksvSZIOHz6s7du365lnnlFGRoYyMjL09NNP61e/+pXef/99n+stXrxYw4YN0+TJk+39QfwDSTQAWOQ2HGoyotosbpJoABGorq7Op9TX17fYrqGhQWVlZcrKyvKpz8rK0t69e1s8Z9++fX7tJ06c6G1/7Ngx1dTU+LSJiYnRuHHjvG327dunuLg4jR492tvm6quvVlxcnM91f//732vz5s166qmngrh7a0iiAcAiRqIBdFbJycneucZxcXEqKChosd3JkyfldruVkJDgU5+QkKCampoWz6mpqWmzffO/Zm0GDBjg994DBgzwtjl16pTuuusubdiwQS6Xy+yWOwy7cwCARezOAaCzqqqq8kk8Y2Ji2mzvcPjGMsMw/OqCbW/WpqX3/3Kbe+65R9OmTdO1117bZt87GiPRAGARI9EAOiuXy+VTWkui4+Pj5XQ6/UadT5w44TeS3GzgwIFtth84cKAkmbb529/+5vfen3zyibfN73//e/30pz9Vjx491KNHD82cOVO1tbXq0aOH1q9fb/YjaDeSaACwyDAcARUA6Kyio6OVlpam0tJSn/rS0lJlZma2eE5GRoZf+507d3rbp6amauDAgf+/vXuPjqo+9z/+mdwRyDSQ5tpwPS4IJ3KsyREDUrTFBOTan+eARQdwIZqChRCpgghiLIkgIi0ICMV1/IEFjvDjUCWlCZ6CYMK1CaWFA1ouiZoY4YQEBXPdvz9sRofcZhjmksz7tdZeXfnO893zTOw8efjOd++xiampqdH+/futMcnJyaqsrNSRI0esMYcPH1ZlZaU1pqCgQEVFRdYjMzNTXbt2VVFRkX760586/+JbwHYOAHBSneEn8Y2FADq4jIwMWSwWJSUlKTk5WevXr1dxcbHS0tIkSZMnT1ZsbKx1X/Xs2bP1ox/9SEuXLtW4ceO0a9cu7d27VwcPHpT0zTaN9PR0ZWVl6fbbb9ftt9+urKws3XbbbZo0aZIkKT4+XiNGjND06dP1xhtvSJKeeOIJjR49Wv369bPGfNexY8fk5+enhIQEl/4+aKIBwEn2rDSzEg2gvZs4caIuX76szMxMlZaWKiEhQTk5OerZs6ckqbi4WH5+3y4YDB48WFu3btXzzz+vhQsXqm/fvtq2bZvNnTaeeeYZXb9+XTNmzFBFRYUGDRqk3Nxcde3a1Rrz9ttva9asWda7eIwdO1arV69206tumckwDMPTSeDWq6qqktlsVsXZPgrtygoY3C815k5Pp3DL1Rm12qddqqysVGhoqPV9lvT/0hXQufWLceq+qtax/7PSOtcXNf6+7tM4BZgCPZ0O0CG0VJfaqjX2xqFlrEQDgJNYiQYA30MTDQBOMuy4+wZNNAB0LDTRAOCkepmkNprketFEA0BHQhMNAE5iOwcA+B6aaABwUoNhkolvLAQAn0ITDQBOMoxvjrZiAAAdB000ADiJ7RwA4HtoogHASfUNflJD6/djr2/jcQBA+0ITDQBOYjsHAPgemmgAcNI3TXRb2znclAwAwC34fNFN1qxZo969eyskJESJiYk6cOBAq/FXrlzRzJkzFR0drZCQEMXHxysnJ8dN2QJwROOe6LYOR1E3AMB7sRLtBtu2bVN6errWrFmjIUOG6I033tDIkSN16tQp9ejRo0l8TU2NHnjgAUVERGj79u36wQ9+oJKSEnXt2tUD2QNoi/GPo60YR1A3AMC70US7wYoVKzRt2jQ9/vjjkqSVK1fqj3/8o9auXavs7Owm8W+++ab+93//V/n5+QoMDJQk9ezZ0605A7Cf0WCS0dDGdo42Hr8RdQMAvBvbOVyspqZGx48fV0pKis14SkqK8vPzm53z+9//XsnJyZo5c6YiIyOVkJCgrKws1dfXt/g81dXVqqqqsjkAuIk9Wzn+sZ3jxvdpdXV1k9O5q264GnUJQEdGE+1ily5dUn19vSIjI23GIyMjVVZW1uycc+fOafv27aqvr1dOTo6ef/55vfrqq1qyZEmLz5OdnS2z2Ww94uLibunrANCyxrtztHVIUlxcnM17tblVZXfVDVejLgHoyNjO4SYmk+1HuYZhNBlr1NDQoIiICK1fv17+/v5KTEzUZ599pldeeUWLFi1qds78+fOVkZFh/bmqqoo/WICbOPJlKyUlJQoNDbWOBwcHtzjH1XXD1ahLADoymmgXCw8Pl7+/f5PVo/Ly8iarTI2io6MVGBgof39/61h8fLzKyspUU1OjoKCgJnOCg4Nb/WMMwIW+s12j1RhJoaGhNk10c9xVN1yNugSgI2M7h4sFBQUpMTFReXl5NuN5eXkaPHhws3OGDBmijz/+WA0NDdaxs2fPKjo62iN/CAG0zmiw77AXdQMAvB9NtBtkZGTot7/9rd58802dPn1ac+bMUXFxsdLS0iRJkydP1vz5863xP//5z3X58mXNnj1bZ8+e1e7du5WVlaWZM2d66iUAaIUr7hNN3QAA78Z2DjeYOHGiLl++rMzMTJWWliohIUE5OTnW208VFxfLz+/bf8/ExcUpNzdXc+bM0cCBAxUbG6vZs2fr2Wef9dRLANCWW/yNhNQNAPBuJsPgy2g7oqqqKpnNZlWc7aPQrnzgAPdLjbnT0ynccnVGrfZplyorKxUaGmp9n8W98YL8OoW0Orfh+tcqefJF61xf1Pj7uk/jFGAK9HQ6QIfQUl1qq9bYG4eWsRINAM5yxVcWAgC8Gk00ADjLgbtzAAA6BppoAHAWK9EA4HNoogHAWaxEA4DPoYkGACd992u9W4sBAHQcNNEA4Cy2cwCAz6GJBgAnmRpMMjW0vl2jrccBAO0LTTQAOIuVaADwOTTRAOAsLiwEAJ9DEw0AzmIlGgB8Dk00ADiLJhoAfI6fpxMAgHbPsPMAgHZuzZo16t27t0JCQpSYmKgDBw60Gr9jxw4NGDBAwcHBGjBggHbu3GnzuGEYWrx4sWJiYtSpUyfdd999+tvf/mYTU1FRIYvFIrPZLLPZLIvFoitXrtjEnDx5UsOGDVOnTp0UGxurzMxMGS6+tyhNdAumTp2qDz74wNNpAGgHGu/O0dYBAO3Ztm3blJ6ergULFqiwsFBDhw7VyJEjVVxc3Gx8QUGBJk6cKIvFohMnTshisWjChAk6fPiwNWbZsmVasWKFVq9eraNHjyoqKkoPPPCArl69ao2ZNGmSioqKtGfPHu3Zs0dFRUWyWCzWx6uqqvTAAw8oJiZGR48e1apVq7R8+XKtWLHCdb8MSSbD1W16O/XQQw9p9+7diouL02OPPaYpU6YoNjbW02nZraqqSmazWRVn+yi0K/9Wgvulxtzp6RRuuTqjVvu0S5WVlQoNDbW+z3os/ZX8OoW0Orfh+tcqfvZ561xf1Pj7uk/jFGAK9HQ6QIfQUl1q63124zx7DBo0SHfddZfWrl1rHYuPj9f48eOVnZ3dJH7ixImqqqrSH/7wB+vYiBEjFBYWpi1btsgwDMXExCg9PV3PPvusJKm6ulqRkZFaunSpnnzySZ0+fVoDBgzQoUOHNGjQIEnSoUOHlJycrP/5n/9Rv379tHbtWs2fP1+ff/65goODJUkvv/yyVq1apU8++UQmk2sWMeiuWrBjxw59+umneuqpp/TOO++oV69eGjlypLZv367a2lpPpwcAAOC0qqoqm6O6urrZuJqaGh0/flwpKSk24ykpKcrPz292TkFBQZP41NRUa/z58+dVVlZmExMcHKxhw4ZZYwoKCmQ2m60NtCTdc889MpvNNjHDhg2zNtCNz/PZZ5/pwoULdv4mHEcT3Yru3btr9uzZKiws1JEjR/RP//RPslgsiomJ0Zw5c/TRRx95OkUAXsAkyWS0cXg6SQBoRlxcnHWvsdlsbnZFWZIuXbqk+vp6RUZG2oxHRkaqrKys2TllZWWtxjf+b1sxERERTc4dERFhE9PcOb77HK7A3TnsUFpaqtzcXOXm5srf318PPvig/va3v2nAgAFatmyZ5syZ4+kUAXgS94kG4GV2Vf7fVrdpNG77KCkpsYn77mpuc27cGmEYRqvbJeyJbyumufO3FdO4W9lVWzkkVqJbVFtbqx07dmj06NHq2bOn3nnnHc2ZM0elpaV66623lJubq02bNikzM9PTqQLwtAY7DwDwMqGhoTZHS010eHi4/P39m6zslpeXN1kFbhQVFdVqfFRUlKSmq8U3xnz++edNzv3FF1/YxDR3DqnpKvetRBPdgujoaE2fPl09e/bUkSNHdOzYMaWlpalr167WmNTUVH3ve9/zYJYAvEGbWzn+cQBAexUUFKTExETl5eXZjOfl5Wnw4MHNzklOTm4Sn5uba43v3bu3oqKibGJqamq0f/9+a0xycrIqKyt15MgRa8zhw4dVWVlpE/PBBx+opqbG5nliYmLUq1evm3/RbWA7Rwtee+01/fu//7tCQlq+4j4sLEznz593Y1YAvBJftgLAB2RkZMhisSgpKUnJyclav369iouLlZaWJkmaPHmyYmNjrfuqZ8+erR/96EdaunSpxo0bp127dmnv3r06ePCgpG+2WqSnpysrK0u33367br/9dmVlZem2227TpEmTJH1z948RI0Zo+vTpeuONNyRJTzzxhEaPHq1+/fpJ+uYWeC+++KKmTp2q5557Th999JGysrK0aNEil27noIluwXfvPwgAraKJBuADJk6cqMuXLyszM1OlpaVKSEhQTk6OevbsKUkqLi6Wn9+3mxwGDx6srVu36vnnn9fChQvVt29fbdu2zeZOG88884yuX7+uGTNmqKKiQoMGDVJubq7NJ/9vv/22Zs2aZb2Lx9ixY7V69Wrr42azWXl5eZo5c6aSkpIUFhamjIwMZWRkuPT3wX2iOyjuEw1P86X7RPfOXCK/Vj61kqSGr7/W+UULuE8094kGbqmW6lJbtcbeOLSMlWgAcFaD6ZujrRgAQIdBEw0ATrLnwkEuLASAjoUmGgCcxZ5oAPA5NNEA4Cx7bmFHEw0AHQpNNAA4i5VoAPA5NNEA4CRTwzdHWzEAgI6De58BAAAADmIlGgCcxXYOAPA5NNEA4CRucQcAvocmGgBuBZpkAPAp7Il2kzVr1qh3794KCQlRYmKiDhw4YNe8rVu3ymQyafz48S7OEMDNarywsK3DUdQNAPBeNNFusG3bNqWnp2vBggUqLCzU0KFDNXLkSBUXF7c67+LFi5o7d66GDh3qpkwB3BTDzsMB1A0A8G400W6wYsUKTZs2TY8//rji4+O1cuVKxcXFae3atS3Oqa+v1yOPPKIXX3xRffr0cWO2ABzVuCe6rcMR1A0A8G400S5WU1Oj48ePKyUlxWY8JSVF+fn5Lc7LzMzU97//fU2bNs2u56murlZVVZXNAcBNHFiJvvF9Wl1d3eR07qobrkZdAtCR0US72KVLl1RfX6/IyEib8cjISJWVlTU758MPP9TGjRu1YcMGu58nOztbZrPZesTFxTmVNwAHONBEx8XF2bxXs7Ozm5zOXXXD1ahLADoymmg3MZlMNj8bhtFkTJKuXr2qRx99VBs2bFB4eLjd558/f74qKyutR0lJidM5A7CPIxcWlpSU2LxX58+f3/J5XVw3XI26BKAj4xZ3LhYeHi5/f/8mq0fl5eVNVpkk6e9//7suXLigMWPGWMcaGr756xsQEKAzZ86ob9++TeYFBwcrODj4FmcPwC4OfNlKaGioQkNDWw11V91wNeoSgI6MlWgXCwoKUmJiovLy8mzG8/LyNHjw4Cbx/fv318mTJ1VUVGQ9xo4dq/vvv19FRUV8HAp4oVt9YSF1AwC8HyvRbpCRkSGLxaKkpCQlJydr/fr1Ki4uVlpamiRp8uTJio2NVXZ2tkJCQpSQkGAz/3vf+54kNRkH4CVc8LXf1A0A8G400W4wceJEXb58WZmZmSotLVVCQoJycnLUs2dPSVJxcbH8/PhQAGivXPG139QNAPBuJsMw+LLaDqiqqkpms1kVZ/sotCt/aOF+qTF3ejqFW67OqNU+7VJlZaVCQ0Ot77P4GVnyDw5pdW599dc6veY561xf1Pj7uk/jFGAK9HQ6QIfQUl1qq9bYG4eWsRINAE4y/eNoKwYA0HHQRAOAs1ywJxoA4N1oogHASa7YEw0A8G400QDgLFaiAcDn0EQDgJNMxrffSNhaDACg46CJBgBnsRINAD6HJhoAnMSeaADwPTTRAOAsVqIBwOfQRAOAk1iJBgDfQxMNAM5q+MfRVgwAoMOgiQYAJ7ESDQC+x8/TCQBAu2fYeQCAj6ioqJDFYpHZbJbZbJbFYtGVK1danVNdXa1f/OIXCg8PV+fOnTV27Fh98sknNjHFxcUaM2aMOnfurPDwcM2aNUs1NTU2Mfv371diYqJCQkLUp08frVu3rsXnzM7OlslkUnp6usOvkSYaAJxkMgy7DgDwFZMmTVJRUZH27NmjPXv2qKioSBaLpdU56enp2rlzp7Zu3aqDBw/qyy+/1OjRo1VfXy9Jqq+v16hRo/TVV1/p4MGD2rp1q3bs2KGnn37aeo7z58/rwQcf1NChQ1VYWKjnnntOs2bN0o4dO5o839GjR7V+/XoNHDjwpl4j2zkAwFncnQNAO1VVVWXzc3BwsIKDg5065+nTp7Vnzx4dOnRIgwYNkiRt2LBBycnJOnPmjPr169dkTmVlpTZu3KhNmzZp+PDhkqTNmzcrLi5Oe/fuVWpqqnJzc3Xq1CmVlJQoJiZGkvTqq69q6tSpWrJkiUJDQ7Vu3Tr16NFDK1eulCTFx8fr2LFjWr58uR566CHr83355Zd65JFHtGHDBv3qV7+6qdfJSjQAOMnUYN8BAN4mLi7OuuXCbDYrOzvb6XMWFBTIbDZbG2hJuueee2Q2m5Wfn9/snOPHj6u2tlYpKSnWsZiYGCUkJFjnFBQUKCEhwdpAS1Jqaqqqq6t1/Phxa8x3z9EYc+zYMdXW1lrHZs6cqVGjRlkb9pvBSjQAOIkLCwG0VyUlJQoNDbX+7OwqtCSVlZUpIiKiyXhERITKyspanBMUFKSwsDCb8cjISOucsrIyRUZG2jweFhamoKCgVmMiIyNVV1enS5cuKTo6Wlu3btWf//xnHT169KZfo8RKNAA4jwsLAbRToaGhNkdrTfTixYtlMplaPY4dOyZJMplMTeYbhtHseGtunGPPeW+MMf5xTYrJZFJJSYlmz56tzZs3KyQkxKFcbsRKNAA4iZVoAL7gqaee0sMPP9xqTK9evfSXv/xFn3/+eZPHvvjiiyarxI2ioqJUU1OjiooKm9Xo8vJyDR482Bpz+PBhm3kVFRWqra21njcqKqrJand5ebkCAgLUvXt37d69W+Xl5UpMTLQ+Xl9frw8++ECrV69WdXW1/P39W32NjWiiAcBZXFgIwAeEh4crPDy8zbjk5GRVVlbqyJEjuvvuuyVJhw8fVmVlpbUhvlFiYqICAwOVl5enCRMmSJJKS0v117/+VcuWLbOed8mSJSotLVV0dLQkKTc3V8HBwdamODk5We+++67NuXNzc5WUlKTAwED95Cc/0cmTJ20ef+yxx9S/f389++yzdjfQEts5AOCWaFyNbukAAF8RHx+vESNGaPr06Tp06JAOHTqk6dOna/To0dY7c3z66afq37+/jhw5Ikkym82aNm2ann76ab3//vsqLCzUo48+qjvuuMN68V9KSooGDBggi8WiwsJCvf/++5o7d66mT59u3dedlpamixcvKiMjQ6dPn9abb76pjRs3au7cuZKkrl27KiEhwebo3LmzunfvroSEBIdeJ000ADjJ1GDYdQCAr3j77bd1xx13KCUlRSkpKRo4cKA2bdpkfby2tlZnzpzRtWvXrGOvvfaaxo8frwkTJmjIkCG67bbb9O6771pXh/39/bV7926FhIRoyJAhmjBhgsaPH6/ly5dbz9G7d2/l5ORo3759uvPOO/XSSy/pN7/5jc3t7W4VtnMAgLPYzgEANrp166bNmze3+HivXr2sF/w1CgkJ0apVq7Rq1aoW5/Xo0UPvvfdeq889bNgw/fnPf7Y713379tkd+1000QDgJHvuA819ogGgY6GJBgBnsRINAD6HJhoAnMQt7gDA99BEA4CT7LlwkAsLAaBjoYkGAGexnQMAfA5NNAA4ie0cAOB7aKIBwFmG8c3RVgwAoMOgiQYAJ7ESDQC+hyYaAJzEfaIBwPfQRAOAsxqMb462YgAAHYafpxPwFWvWrFHv3r0VEhKixMREHThwoMXYDRs2aOjQoQoLC1NYWJiGDx+uI0eOuDFbAA4x7DwcRN0AAO9FE+0G27ZtU3p6uhYsWKDCwkINHTpUI0eOVHFxcbPx+/bt089+9jP96U9/UkFBgXr06KGUlBR9+umnbs4cgD1M+nZfdIuHg+ekbgCAdzMZBpeMu9qgQYN01113ae3atdax+Ph4jR8/XtnZ2W3Or6+vV1hYmFavXq3Jkyfb9ZxVVVUym82qONtHoV35txLcLzXmTk+ncMvVGbXap12qrKxUaGio9X025CeLFRAQ0vrcuq/14fuLrXPb4om64WqNv6/7NE4BpkBPpwN0CC3VpbZqjb1xaBl7ol2spqZGx48f17x582zGU1JSlJ+fb9c5rl27ptraWnXr1q3FmOrqalVXV1t/rqqqurmEATjMkQsLb3xvBgcHKzg42GbMXXXD1ahLADoylihd7NKlS6qvr1dkZKTNeGRkpMrKyuw6x7x58xQbG6vhw4e3GJOdnS2z2Ww94uLinMobgP1MhmHXIUlxcXE279XmVpXdVTdcjboEoCNjJdpNTCbbHZGGYTQZa86yZcu0ZcsW7du3TyEhLX9cPH/+fGVkZFh/rqqq4g8W4C4N/zjaipFUUlJi89HpjavQ3+XquuFq1CUAHRlNtIuFh4fL39+/yepReXl5k1WmGy1fvlxZWVnau3evBg4c2Gpscx8JA3CP7640txYjSaGhoW3uP3RX3XA16hKAjoztHC4WFBSkxMRE5eXl2Yzn5eVp8ODBLc575ZVX9NJLL2nPnj1KSkpydZoAnHGLb3FH3QAA78dKtBtkZGTIYrEoKSlJycnJWr9+vYqLi5WWliZJmjx5smJjY617I5ctW6aFCxfqd7/7nXr16mVdjerSpYu6dOnisdcBoHmmBkOmNr5Mpa3Hb0TdAADvRhPtBhMnTtTly5eVmZmp0tJSJSQkKCcnRz179pQkFRcXy8/v2w8F1qxZo5qaGv3bv/2bzXleeOEFLV682J2pA7CHYXxztBXjAOoGAHg3mmg3mTFjhmbMmNHsY/v27bP5+cKFC65PCMAt48gt7hxB3QAA70UTDQDOcsFKNADAu9FEA4Cz7LlwkB4aADoUmmgAcJKpoUGmhtb3a7T1OACgfaGJBgBnGWr7y1ZYiQaADoUmGgCc5MiXrQAAOgaaaABwliE7Lix0SyYAADehiQYAZ3F3DgDwOTTRAOAkU70hUxtLzaZ6mmgA6EhoogHAWaxEA4DPoYkGAGfRRAOAz/HzdAIA0O41NtFtHQDgIyoqKmSxWGQ2m2U2m2WxWHTlypVW51RXV+sXv/iFwsPD1blzZ40dO1affPKJTUxxcbHGjBmjzp07Kzw8XLNmzVJNTY1NzP79+5WYmKiQDxoY5QAAFU9JREFUkBD16dNH69ats3m8rq5Ozz//vHr37q1OnTqpT58+yszMVIOD9/OniQYAZzXYeQCAj5g0aZKKioq0Z88e7dmzR0VFRbJYLK3OSU9P186dO7V161YdPHhQX375pUaPHq36+npJUn19vUaNGqWvvvpKBw8e1NatW7Vjxw49/fTT1nOcP39eDz74oIYOHarCwkI999xzmjVrlnbs2GGNWbp0qdatW6fVq1fr9OnTWrZsmV555RWtWrXKodfIdg4AcJKpoUEmE99YCACSdPr0ae3Zs0eHDh3SoEGDJEkbNmxQcnKyzpw5o379+jWZU1lZqY0bN2rTpk0aPny4JGnz5s2Ki4vT3r17lZqaqtzcXJ06dUolJSWKiYmRJL366quaOnWqlixZotDQUK1bt049evTQypUrJUnx8fE6duyYli9froceekiSVFBQoHHjxmnUqFGSpF69emnLli06duyYQ6+TlWgAcFaDYd8BAF6mqqrK5qiurnb6nAUFBTKbzdYGWpLuuecemc1m5efnNzvn+PHjqq2tVUpKinUsJiZGCQkJ1jkFBQVKSEiwNtCSlJqaqurqah0/ftwa891zNMYcO3ZMtbW1kqR7771X77//vs6ePStJOnHihA4ePKgHH3zQodfJSjQAOIsLCwG0U3FxcTY/v/DCC1q8eLFT5ywrK1NEREST8YiICJWVlbU4JygoSGFhYTbjkZGR1jllZWWKjIy0eTwsLExBQUGtxkRGRqqurk6XLl1SdHS0nn32WVVWVqp///7y9/dXfX29lixZop/97GcOvU6aaABwmj0XDtJEA/A+JSUlCg0Ntf4cHBzcYuzixYv14osvtnq+o0ePSpJMJlOTxwzDaHa8NTfOsee8N8YY/6jPjePbtm3T5s2b9bvf/U7//M//rKKiIqWnpysmJkZTpkyxOzeaaABwFivRANqp0NBQmya6NU899ZQefvjhVmN69eqlv/zlL/r888+bPPbFF180WSVuFBUVpZqaGlVUVNisRpeXl2vw4MHWmMOHD9vMq6ioUG1trfW8UVFRTVa7y8vLFRAQoO7du0uSfvnLX2revHnW13LHHXfo4sWLys7OpokGALeqr5eM+tZjGtp4HAC8XHh4uMLDw9uMS05OVmVlpY4cOaK7775bknT48GFVVlZaG+IbJSYmKjAwUHl5eZowYYIkqbS0VH/961+1bNky63mXLFmi0tJSRUdHS5Jyc3MVHBysxMREa8y7775rc+7c3FwlJSUpMDBQknTt2jX5+dleFujv788t7gDA7bhPNABYxcfHa8SIEZo+fboOHTqkQ4cOafr06Ro9erT1zhyffvqp+vfvryNHjkiSzGazpk2bpqefflrvv/++CgsL9eijj+qOO+6w3q0jJSVFAwYMkMViUWFhod5//33NnTtX06dPt66mp6Wl6eLFi8rIyNDp06f15ptvauPGjZo7d641vzFjxmjJkiXavXu3Lly4oJ07d2rFihX66U9/6tDrZCUaAJzVYKjNPc/cnQOAD3n77bc1a9Ys650yxo4dq9WrV1sfr62t1ZkzZ3Tt2jXr2GuvvaaAgABNmDBB169f109+8hP9x3/8h/z9/SV9s1q8e/duzZgxQ0OGDFGnTp00adIkLV++3HqO3r17KycnR3PmzNHrr7+umJgY/eY3v7He3k6SVq1apYULF2rGjBkqLy9XTEyMnnzySS1atMih12gyDJZHOqKqqiqZzWZVnO2j0K584AD3S42509Mp3HJ1Rq32aZcqKysVGhpqfZ8Nj3lSAX4tX4wjSXUN1dr72RvWub6o8fd1n8YpwBTo6XSADqGlutRWrbE3Di1jJRoAnGXIjgsL3ZIJAMBNaKIBwFlcWAgAPocmGgCcxS3uAMDn0EQDgLNoogHA59BEA4CzuDsHAPgcmmgAcJJhNMgwWr9Jf1uPAwDaF5poAHBWQ4PUVpNMEw0AHQpNNAA4q6FBMtFEA4AvoYkGAGcZduyJ5sJCAOhQaKIBwElGQ4OMNlai2RMNAB0LTTQAOIuVaADwOX6eTsBXrFmzRr1791ZISIgSExN14MCBVuN37NihAQMGKDg4WAMGDNDOnTvdlCkAhzUY9h0Oom4AgPeiiXaDbdu2KT09XQsWLFBhYaGGDh2qkSNHqri4uNn4goICTZw4URaLRSdOnJDFYtGECRN0+PBhN2cOwB5GfYOM+vo2Dse2c1A3AMC7mQyDzxhdbdCgQbrrrru0du1a61h8fLzGjx+v7OzsJvETJ05UVVWV/vCHP1jHRowYobCwMG3ZssWu56yqqpLZbFbF2T4K7cq/leB+qTF3ejqFW67OqNU+7VJlZaVCQ0Ot77P7/f+PAkyBbc79U/3/s85tiyfqhqs1/r7u07g2f18A7NNSXWqr1tgbh5axJ9rFampqdPz4cc2bN89mPCUlRfn5+c3OKSgo0Jw5c2zGUlNTtXLlyhafp7q6WtXV1dafKysrJUlfdtovv9t4c8D9dlzxdAa3XlVVleLidqlx7aHxf2vra2SYWl+PqDNqJX373mwUHBys4OBgmzF31Q1Xa6kubSpZzR9t4BZpqS5VVVW1Oe+78XAcTbSLXbp0SfX19YqMjLQZj4yMVFlZWbNzysrKHIqXpOzsbL344otNxuPi4m4iawCtuXz5ssxms65evSpJOqj32ryusFGPHj1sfn7hhRe0ePFimzF31Q1Xoy4B7nNjXbL3fXb16lWZzWZXptZh0US7iclksvnZMIwmY87Ez58/XxkZGdafr1y5op49e6q4uNir3xzf/As6TiUlJV6/MkWurtGecq2srFSPHj3UrVs3SVJMTIxKSkrUtWvXVt+f0jfv4cuXL6tbt27y8/t2i9WNq9Df5eq64WrUJdcjV9doT7nebF0yDENXr15VTEyMu1LtcGiiXSw8PFz+/v5NVoPKy8ubrBo1ioqKciheav4jYUkym81eXwAkKTQ0tF3kKZGrq7SnXBubYD8/P/3gBz+we569jaO76oarUZfch1xdoz3lejN1yZv/MdsecMWZiwUFBSkxMVF5eXk243l5eRo8eHCzc5KTk5vE5+bmthgPoGOhbgCA92Ml2g0yMjJksViUlJSk5ORkrV+/XsXFxUpLS5MkTZ48WbGxsdYr7mfPnq0f/ehHWrp0qcaNG6ddu3Zp7969OnjwoCdfBgA3om4AgHfzX3zjFS245RISEtS9e3dlZWVp+fLlun79ujZt2qR/+Zd/kST9+te/VkBAgMaPHy/pm4sBBgwYoBUrVigrK0vFxcVau3atHnjgAYee19/fX/fdd58CArz730rtJU+JXF2FXJvyVN1wtfby37q95CmRq6uQK9rCfaIBAAAAB7EnGgAAAHAQTTQAAADgIJpoAAAAwEE00QAAAICDaKLbqTVr1qh3794KCQlRYmKiDhw40Gr8jh07NGDAAAUHB2vAgAHauXOnmzJ1LNcNGzZo6NChCgsLU1hYmIYPH64jR454Za7ftXXrVplMJuudEtzB0VyvXLmimTNnKjo6WiEhIYqPj1dOTo5X5rpy5Ur169dPnTp1UlxcnObMmaOvv/7apTl+8MEHGjNmjGJiYmQymfRf//Vfbc7Zv3+/EhMTFRISoj59+mjdunUuzdHbUZc8n+t3UZduba7UJTRhoN3ZunWrERgYaGzYsME4deqUMXv2bKNz587GxYsXm43Pz883/P39jaysLOP06dNGVlaWERAQYBw6dMjrcp00aZLx+uuvG4WFhcbp06eNxx57zDCbzcYnn3zidbk2unDhghEbG2sMHTrUGDdunMvzvJlcq6urjaSkJOPBBx80Dh48aFy4cME4cOCAUVRU5HW5bt682QgODjbefvtt4/z588Yf//hHIzo62khPT3dpnjk5OcaCBQuMHTt2GJKMnTt3thp/7tw547bbbjNmz55tnDp1ytiwYYMRGBhobN++3aV5eivqknfk2oi6dGtzpS6hOTTR7dDdd99tpKWl2Yz179/fmDdvXrPxEyZMMEaMGGEzlpqaajz88MMuy7GRo7neqK6uzujatavx1ltvuSI9GzeTa11dnTFkyBDjt7/9rTFlyhS3/bFyNNe1a9caffr0MWpqatyRng1Hc505c6bx4x//2GYsIyPDuPfee12W443s+WP1zDPPGP3797cZe/LJJ4177rnHlal5LeqSa1CXXIO6hFuB7RztTE1NjY4fP66UlBSb8ZSUFOXn5zc7p6CgoEl8ampqi/G3ys3keqNr166ptrZW3bp1c0WKVjeba2Zmpr7//e9r2rRpLs3vu24m19///vdKTk7WzJkzFRkZqYSEBGVlZam+vt7rcr333nt1/Phx68fl586dU05OjkaNGuXSXB3V0vvq2LFjqq2t9VBWnkFdcg3qkvfkSl1Cc/hqm3bm0qVLqq+vV2RkpM14ZGSkysrKmp1TVlbmUPytcjO53mjevHmKjY3V8OHDXZGi1c3k+uGHH2rjxo0qKipyaW43uplcz507p//+7//WI488opycHH300UeaOXOm6urqtGjRIq/K9eGHH9YXX3yhe++9V4ZhqK6uTj//+c81b948l+V5M1p6X9XV1enSpUuKjo72UGbuR11yDeqS9+RKXUJzaKLbKZPJZPOzYRhNxpyJv5Vu9rmXLVumLVu2aN++fQoJCXFVejbszfXq1at69NFHtWHDBoWHh7sltxs58nttaGhQRESE1q9fL39/fyUmJuqzzz7TK6+84tI/VjeT6759+7RkyRKtWbNGgwYN0scff6zZs2crOjpaCxcudHmujmjudTU37iuoS65BXfJ8rtQlNIcmup0JDw+Xv79/k38tl5eXN/nXZ6OoqCiH4m+Vm8m10fLly5WVlaW9e/dq4MCBrkxTkuO5/v3vf9eFCxc0ZswY61hDQ4MkKSAgQGfOnFHfvn29IldJio6OVmBgoPz9/a1j8fHxKisrU01NjYKCgrwm14ULF8pisejxxx+XJN1xxx366quv9MQTT2jBggXy8/OOXWgtva8CAgLUvXt3D2XlGdQl16AuUZccRV1yL+/4rw67BQUFKTExUXl5eTbjeXl5Gjx4cLNzkpOTm8Tn5ua2GH+r3EyukvTKK6/opZde0p49e5SUlOTSHBs5mmv//v118uRJFRUVWY+xY8fq/vvvV1FRkeLi4rwmV0kaMmSIPv74Y+sfVEk6e/asoqOjXfaH6mZzvXbtWpM/SP7+/jK+uRDaZbk6qqX3VVJSkgIDAz2UlWdQl1yDuuQ9uVKX0Cz3XseIW6Hx1jwbN240Tp06ZaSnpxudO3c2Lly4YBiGYVgsFpsrjD/88EPD39/fePnll43Tp08bL7/8sttvJWVvrkuXLjWCgoKM7du3G6Wlpdbj6tWrXpfrjdx5FbyjuRYXFxtdunQxnnrqKePMmTPGe++9Z0RERBi/+tWvvC7XF154wejatauxZcsW49y5c0Zubq7Rt29fY8KECS7N8+rVq0ZhYaFRWFhoSDJWrFhhFBYWWm95NW/ePMNisVjjG28lNWfOHOPUqVPGxo0bffpWUtQl78j1RtSlW5MrdQnNoYlup15//XWjZ8+eRlBQkHHXXXcZ+/fvtz42bNgwY8qUKTbx77zzjtGvXz8jMDDQ6N+/v7Fjxw6vzLVnz56GpCbHCy+84HW53sidf6wMw/Fc8/PzjUGDBhnBwcFGnz59jCVLlhh1dXVel2ttba2xePFio2/fvkZISIgRFxdnzJgxw6ioqHBpjn/605+a/f9eY25Tpkwxhg0bZjNn3759xg9/+EMjKCjI6NWrl7F27VqX5ujtqEuez/VG1KVbkyt1Cc0xGYYXfQ4BAAAAtAPsiQYAAAAcRBMNAAAAOIgmGgAAAHAQTTQAAADgIJpoAAAAwEE00QAAAICDaKIBAAAAB9FEAwAAAA6iiQYAAAAcRBMNAAAAOIgmGgAAAHAQTTTgAV988YWioqKUlZVlHTt8+LCCgoKUm5vrwcwA+CrqEuAYk2EYhqeTAHxRTk6Oxo8fr/z8fPXv318//OEPNWrUKK1cudLTqQHwUdQlwH400YAHzZw5U3v37tW//uu/6sSJEzp69KhCQkI8nRYAH0ZdAuxDEw140PXr15WQkKCSkhIdO3ZMAwcO9HRKAHwcdQmwD3uiAQ86d+6cPvvsMzU0NOjixYueTgcAqEuAnViJBjykpqZGd999t+688071799fK1as0MmTJxUZGenp1AD4KOoSYD+aaMBDfvnLX2r79u06ceKEunTpovvvv19du3bVe++95+nUAPgo6hJgP7ZzAB6wb98+rVy5Ups2bVJoaKj8/Py0adMmHTx4UGvXrvV0egB8EHUJcAwr0QAAAICDWIkGAAAAHEQTDQAAADiIJhoAAABwEE00AAAA4CCaaAAAAMBBNNEAAACAg2iiAQAAAAfRRAMAAAAOookGAAAAHEQTDQAAADiIJhoAAABwEE00AAAA4CCaaAAAAMBBNNEAAACAg2iiAQAAAAfRRAMAAAAOcqiJvu+++5Senu6qXNqNkydPatiwYerUqZNiY2OVmZkpwzA8nRYAAADcJMDTCbQ3VVVVeuCBB3T//ffr6NGjOnv2rKZOnarOnTvr6aef9nR6AAAAcAOTYecS6tSpU/XWW2/ZjJ0/f169evVyRV5ea+3atZo/f74+//xzBQcHS5JefvllrVq1Sp988olMJpOHMwQAAICr2b2d49e//rWSk5M1ffp0lZaWqrS0VHFxcc3GpqWlqUuXLq0excXFt+xFuFNBQYGGDRtmbaAlKTU1VZ999pkuXLjgucQAAADgNnZv5zCbzQoKCtJtt92mqKioVmMzMzM1d+7cVmNiYmLsfWqvUlZW1mT1PTIy0vpY7969PZAVAAAA3Mkle6IjIiIUERHhilN7hRu3bDTuiGErBwAAgG9wyS3uOvJ2jqioKJWVldmMlZeXS/p2RRoAAAAdm0Mr0UFBQaqvr28zriNv50hOTtZzzz2nmpoaBQUFSZJyc3MVExPjcxdZAgAA+Cq7784hSU888YSKior0n//5n+rSpYu6desmPz/f+r6WyspK9evXTz/+8Y/13HPP6aOPPtLUqVO1aNEibnEHAADgIxxqos+ePaspU6boxIkTun79uk/e4k765stWZs6cqSNHjigsLExpaWlatGgRe6IBAAB8hENNNAAAAAAXXVgIAAAAdGQ00QAAAICDaKIBAAAAB9FEAwAAAA6iiQYAAAAcRBMNAAAAOIgmGgAAAHAQTTQAAADgIJpoAAAAwEE00QAAAICDaKIBAAAAB/1/thwQ961H6VgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a939128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    1    0.00052    0.00052\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04ad91518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33moutputting...\u001b[0m\n",
      "\u001b[33mparameter particles.n_particles never used\u001b[0m\n",
      "\u001b[33mparameter particles.particle_generator never used\u001b[0m\n",
      "\u001b[33mparameter swe.cvisc never used\u001b[0m\n",
      "main:  1.2175016403198242\n",
      "   evolve:  0.004194974899291992\n",
      "      unsplitFluxes:  0.00395655632019043\n",
      "         limiting:  0.0027303695678710938\n",
      "         interfaceStates:  7.748603820800781e-05\n",
      "         riemann:  0.00019359588623046875\n",
      "         transverse flux addition:  0.0006589889526367188\n",
      "   vis:  0.5826215744018555\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<swe.simulation.Simulation at 0x7fe04a9396d8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe04a9a4860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pyro_sim = Pyro(solver)\n",
    "pyro_sim.initialize_problem(problem_name, param_file, other_commands=other_commands)\n",
    "pyro_sim.run_sim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0.53226   0.53226   0.53226   0.53226   0.53226   0.53434    1.4006       1.4 \n",
      "   0.53261   0.53261   0.53261   0.53261   0.53261   0.53469    1.4011    1.4006 \n",
      "   0.13833   0.13833   0.13833   0.13833   0.13833   0.13868   0.53469   0.53434 \n",
      "   0.13799   0.13799   0.13799   0.13799   0.13799   0.13833   0.53261   0.53226 \n",
      "   0.13799   0.13799   0.13799   0.13799   0.13799   0.13833   0.53261   0.53226 \n",
      "   0.13799   0.13799   0.13799   0.13799   0.13799   0.13833   0.53261   0.53226 \n",
      "   0.13799   0.13799   0.13799   0.13799   0.13799   0.13833   0.53261   0.53226 \n",
      "   0.13799   0.13799   0.13799   0.13799   0.13799   0.13833   0.53261   0.53226 \n",
      "\n",
      "         ^ y\n",
      "         |\n",
      "         +---> x\n",
      "        \n"
     ]
    }
   ],
   "source": [
    "p = pyro_sim.sim.cc_data.get_var(\"height\")\n",
    "p.pretty_print(show_ghost=False)"
   ]
  }
 ],
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