pg-rad/docs/pg-rad-in-python.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5e30f59a",
   "metadata": {},
   "source": [
    "# Using PG-RAD as a module\n",
    "\n",
    "This discusses the overall design of the code to understand how different parts interact, doing so by an interactive notebook demo. For specific usage of functions and classes, consult the API documentation in the side bar (relevant API documentation sections will also be hyperlinked in the below explanation)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f18912e5",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "415fdd25",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from pg_rad.dataloader import load_data\n",
    "from pg_rad.path import path_from_RT90\n",
    "from pg_rad.landscape import Landscape\n",
    "from pg_rad.sources import PointSource\n",
    "\n",
    "from pg_rad.isotope import Isotope\n",
    "from pg_rad.logger import setup_logger\n",
    "\n",
    "setup_logger(log_level = \"INFO\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5a0e470a",
   "metadata": {},
   "outputs": [],
   "source": [
    "FILENAME = \"B10_NaIR_MGS_ROI_CPS_IPL.CSV\"\n",
    "df = load_data(FILENAME)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "baa7aba8",
   "metadata": {},
   "source": [
    "## Demo: Path regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2ec97553",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2026-01-28 15:53:22,182 - INFO: Piecewise regression reduced path from 105 to 4 segments.\n"
     ]
    },
    {
     "data": {
      "image/png": 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oc1y/fv2M7t27G4ZhGCNHjjRCQ0NtykeMGGEAxrlz5wzDMIzRo0cb9evXt6nz4YcfGhUrVrT+HhwcbLzyyisZxrlhwwbDz8/PSEpKstl/8803G59++qlhGIYRFhZmPPPMMzbljRs3Tnfeq61Zs8YAjDlz5lj3nTlzxihatKjxv//9z+5xbdu2NYYNG2b9/d577zWee+65DNv+5ZdfrPuWLFliADaflatl9Fm6Iqvf33qy40gNGsDYsZlW6cEs3uIVAAbzMYtoZ1vhqafg4kUHBSgiIhlp1qwZkZGRbN68md69e9O3b1+6dOkCmItRJyYmcv/99+Pr62vdvv76aw4fPgzA3r17rYtXXxEWlrX1E6+IiYnh1KlTNG/ePMPyP/74g4SEBEqVKmUTx5EjR3IljqvrlSxZkho1arD33+4VqampvPnmm9StW5eSJUvi6+vLihUrOH78eJbavrLsE/y33mWMAwfmOHUG5ULh+edh2TJYvdpulZcZy1Eq8QX96cYc1nEvtxFhFu7ZAy++CB9/nEcBi4g4ho9P1udNXb8e2rS5fr2lS+Gee7J27uwoVqyY9XXR9OnTqV+/Pl9++SX9+vUj4d+LWLJkCTfddJPNcdlZl9HNzQ3jmvdrV14TARQtWjTT4xMSEggKCmLt2rXpygICArIcR068++67TJo0iYkTJ1K3bl2KFSvGkCFDuHTpUpaO9/T0tP7ZYjH7rKal2Vtq6cbpyY6jubnBzJlQooTdKhbgE56hJctJpBjtWMxRKv5XYfJk8/9oEZF8zGKBYsWytj3wAJQvbx5jr62QELNeVtqz105WuLm58fLLL/Pqq69y8eJFQkND8fb25vjx41StWtVmu9IvpVatWtb+K1ds2rTJ5vcyZcoQHR1tk/BERkZa/1y8eHEqVarEqlWrMozr1ltvJTo6Gg8Pj3RxlC5d2hrH5s2bM43DnqvrnTt3jgMHDlCrVi0AfvvtNzp06MBjjz1G/fr1qVKlCgcOHLA53svLi1RHzxOQRUp28kL58td9neVJCnN5mPpEcppA2rCUcwT8V6FvXzh92rFxioi4CHd3mDTJ/PO1icqV3ydONOvlhYceegh3d3emTJlC8eLFeeGFFxg6dCgzZ87k8OHD/P7773z88cfMnDkTgKeffpqDBw8yfPhw9u/fz6xZs5gxY4ZNm02bNuXvv/9mwoQJHD58mClTprBs2TKbOmPGjOH999/no48+4uDBg9bzALRo0YKwsDA6duzIzz//zNGjR9m4cSOvvPIK27ZtA+C5555j+vTpfPXVVxw4cIDRo0eze/fuLF3zG2+8wapVq9i1axd9+vShdOnSdOzYEYBq1aqxcuVKNm7cyN69e3nqqac4fc13VKVKldi8eTNHjx7ln3/+ceiTm+vKtEdPIeGwDspXu3TJMKpXv24vupMEG+U5boBh3MsaIwmv/8pbtDCMlBTHxSgikksy61SaHd9/bxjly9v+VRkSYu53lN69exsdOnRIt3/cuHFGmTJljISEBCMtLc2YOHGiUaNGDcPT09MoU6aM0bJlS2PdunXW+osWLTKqVq1qeHt7G02aNDGmT59u00HZMAxj6tSpRkhIiFGsWDGjV69exttvv23TQdkwDGPatGnW8wQFBRmDBw+2lsXHxxuDBw82goODDU9PTyMkJMTo0aOHcfz4cWudt99+2yhdurTh6+tr9O7d23jxxRez1EF50aJFRu3atQ0vLy+jUaNGxh9//GGtc+bMGaNDhw6Gr6+vUbZsWePVV181evXqZXPf9u/fb9xxxx1G0aJFDcA4cuSIte2r78H27dut5RnJjQ7KFsO4kQF5BUN8fDz+/v7ExcXh5+fnuBMtWAD/dnDLzA7qcje/ch4/evAt39Dzv1l4xowBTWwlIi4uKSmJI0eOULlyZYoUKXJDbaWmwoYNEBUFQUHQpEnePdEpjNauXUuzZs04d+6cw/v+ZEVmn6Wsfn/rNVZe6tQJstALvh47+Z4ueHCZ73iM13jzv8LXX4dffnFgkCIirsXdHZo2he7dzZ9KdCS7lOzkJYvFHFWVhf9T7+cXPuNJAN7mVb6gn1lgGOac6ddOKSoiIiIZUrKT1xo2hFGjslS1LzN4jTcAeJpprOABs+Dvv6FdOzh/3lFRiohIIdW0aVMMw3CJV1i5RcmOM7z8Mtx5Z5aqvs5oevI1qXjQlflEUt8s+OMP6NYNUlIcGKiIiEj+p2THGTw84NtvoXjx61a1AF/wBPexigSK05YlnKC8Wbh0qbk4jPqYi4iL0hgYuVG58RlSsuMslSubkwVmgReX+Z4u1GYXp7iJtiwhjn97nX/yiWZXFhGXc2WG3MTERCdHIvndlc/Q1bMuZ5eGnpOHQ8+vZRjQpw98/XWWqh+jAnewiWiCuJ+fWUJbPEkxOzyvWAF21k8REXGGqKgoYmNjKVu2LD4+PtZlAUSywjAMEhMTiYmJISAgwLqG1tWy+v2tZAcnJjsAFy5Ao0bmGlhZ8Du3cA/ruYAvfZnOl/Qz5+ApWRK2bTOfGImIuADDMIiOjiY2NtbZoUg+FhAQQGBgYIbJspKdbHBqsgOwdy/cdhtk8XHvUlrTnkWk4c7rjGLUlXl46tWD334DX18HBisikj2pqak2C1yKZJWnpyfumUzXomQnG5ye7IDZYblnzyxX/5QneZpPAZhJL3rxjVnQuDH88AMEBjogSBEREdehGZTzm8ceg0GDslz9KT5jBOMB6MeXrKaZWbB5M9x+O/z+uyOiFBERyXeU7LiSDz+ENm2yXH0sL9ON2aTgSWcWsJtQs+DkSbj7bpg/30GBioiI5B9KdlyJhwfMmQP162epuhsGX9GXu9lAHAG0Zhmn+Le3+sWL8NBD8Mor5ip6IiIihZSSHVdTvDgsXgzBwVmqXoRkfqQDNdjHCSrQjsUkUOy/CmPHmk+LzpxxUMAiIiKuTcmOKypfHhYtgqJFs1S9JOdYShvKEMN2buUR/kcKV/Ve//lnc00u9eMREZFCSMmOq7r1VvjyyyxXr8IRFtOOoiSylLYMYjI2w+yOHTPX41q4MNdDFRERcWVKdlxZ9+4wfHiWqzdiK7PpjoU0PuVpJvCibYXkZHj4YViyJJcDFRERcV1KdlzduHHQsmWWq3fgJyYyBICXeIc5PGJbISUFHn0UDh7MxSBFRERcl5IdV+fuDrNnQ4MGWT7kWT5mKB8A0JuZrKeJbYX4eOjQARIScjFQERER16RkJz8oUQJ++QXuuSfLh7zHC3Tmey7hTUd+YB81bCvs3QshIRqlJSIiBZ6SnfyiVClYuRKeeCJL1d0w+JbHuINwzlGSNizlNGVtK8XGQtmyMHEiXLqU6yGLiIi4AiU7+YmXF3z2GUyaBG7X/09XlCR+4kFu5hBHqMKD/EQi1wxnT0uDoUOhbl1YscJBgYuIiDiPU5OdqVOnUq9ePfz8/PDz8yMsLIxly5ZZy5OSkhg4cCClSpXC19eXLl26cPr0aZs2jh8/Ttu2bfHx8aFs2bIMHz6clJSUvL6UvGOxwLPPwtKl4O9/3epl+IeltKEkZ9hCYx5lFqkZ/Wc/cABatTJHf2ltWBERKUCcmuyUL1+e8ePHExERwbZt27jvvvvo0KEDu3fvBmDo0KEsWrSIefPmsW7dOk6dOkXnzp2tx6emptK2bVsuXbrExo0bmTlzJjNmzGDUqFHOuqS807IlbNsGdepct2p1DvITD+JNEj/SkaF8iN105r334PXXczVUERERpzJcTIkSJYwvvvjCiI2NNTw9PY158+ZZy/bu3WsARnh4uGEYhrF06VLDzc3NiI6OttaZOnWq4efnZyQnJ9s9R1JSkhEXF2fdTpw4YQBGXFyc4y7MURISDKN7d8Mwn8dkus2lq/XXDxhiv67FYhirVjn7ykRERDIVFxeXpe9vl+mzk5qaypw5c7hw4QJhYWFERERw+fJlWrRoYa1Ts2ZNKlSoQHh4OADh4eHUrVuXcuXKWeu0bNmS+Ph469OhjIwbNw5/f3/rFhIS4rgLc7RixeC778xOxtfxEPN5lxcAGMb7fE/njCsaBvTqBWfP5mKgIiIizuH0ZGfnzp34+vri7e3N008/zcKFCwkNDSU6OhovLy8CAgJs6pcrV47o6GgAoqOjbRKdK+VXyuwZOXIkcXFx1u3EiRO5e1F5zWKB556DLLy+G8b7PMMUDNx4jG8J546MK/71F3TqpP47IiKS7zk92alRowaRkZFs3ryZAQMG0Lt3b/bs2ePQc3p7e1s7RV/ZCoTRo80VzjNhASbxHO1YRBJFeZCfOMTNGVdevx7uv9+chFBERCSfcnqy4+XlRdWqVWnYsCHjxo2jfv36TJo0icDAQC5dukRsbKxN/dOnTxMYGAhAYGBgutFZV36/UqdQcXODb7+FKlUyreZBKnPoRkO28Q9laM0y/qFUxpVXrTIXJY2IcEDAIiIijuf0ZOdaaWlpJCcn07BhQzw9PVm1apW1bP/+/Rw/fpywsDAAwsLC2LlzJzExMdY6K1euxM/Pj9DQ0DyP3SWUKAGLFpmTEGaiGIksph0VOcohqtGBH7lIkYwrHz4MYWEwZYoDAhYREXEspyY7I0eOZP369Rw9epSdO3cycuRI1q5dS48ePfD396dfv348//zzrFmzhoiICPr27UtYWBh33GH2M3nggQcIDQ2lZ8+e/PHHH6xYsYJXX32VgQMH4u3t7cxLc67QUPMVVP36mVYL5DTLaE0A59jIXfRmJmlYMq58+TIMGmT2C1I/HhERyUecmuzExMTQq1cvatSoQfPmzdm6dSsrVqzg/vvvB+DDDz+kXbt2dOnShXvuuYfAwEAWLFhgPd7d3Z3Fixfj7u5OWFgYjz32GL169eKNN95w1iW5jtBQ2LoVPvrIfNpjRy328QMd8eQS83iYEbyTebtvvgnTpuVysCIiIo5jMQz9Mz0+Ph5/f3/i4uIKTmflq509CwMGwNy5dqt8x6M8xncATGYgA/nEfnseHmZfnmwsTCoiIpLbsvr97XJ9dsQBSpaE//0PXn7ZbpUezOItXgHgWT5iEe3st5eSAl27wvHjuR2piIhIrlOyU5i89RZ07Gi3+GXG8gSfk4Y73ZjDNhrab+vvv815eBITcz9OERGRXKRkpzCxWODzzyEoKONi4BOeoSXLSaQY7VjMUSrab+/33+Hxx9VhWUREXJqSncKmdGlzxXQ7nZY9SWEeD1GfSE4TSBuWco4A++39739aOFRERFyakp3CqEEDWLkSbropw+LiJLCEtpTnBHsJpRMLScbLfnuvvw5z5jgmVhERkRukZKewatgQIiOhbdsMi2/iFEtoS3HiWUdTHme6/Tl4APr2hS1bHBOriIjIDVCyU5iVLg0//QTvvWcOJ79GPXbyPV3w4DKz6MFrvGm/raQk6NwZzpxxYMAiIiLZp2SnsHNzg2HDYPVqyGDW6fv5hc/pD8BYXuFznrDf1l9/Qb9+6rAsIiIuRcmOmJo0gU8/zbCoDzMZhdkJeQBTWU5L++38+CNMneqICEVERHJEyY78p3dveO65DIvGMIZezCQVDx5iHpFksu7W889rlXQREXEZSnbE1nvvwX33pdttAT6nP/exigSK05YlnKB8xm0kJ0PTpuYQdxERESdTsiO2PDxg3jyoVi1dkReX+Z4u1GYXp7iJNiwlDjtrkSQkQPv2MGWKgwMWERHJnJIdSa9kSVi8GAIC0hUFEMdS2hDEKXZRl67M5zLpR3IBkJYGgwbBkCGQmurQkEVEROxRsiMZq14d5s8Hd/d0RRU4wRLaUowEfuF+nuQzMh1/NWkS9OwJly87LFwRERF7lOyIfc2bw0cfZVh0C5HM5WHcSWEGfXmT1zJva/Zsc+HQixcdEKiIiIh9SnYkcwMGQNeuGRa1YRlTGAjAaN5gJr0yb2vJEmjVCuLjcztKERERu5TsSOYsFvjsM6hQIcPip/iMEYwH4Am+YBXpR3LZWL8ewsJg69bcjlRERCRDSnbk+kqUgFmzzNmWMzCWl+nGbFLwpDML2EXtzNvbswfuuANeeslcZkJERMSBlOxI1tx1F7z9doZFbhjMoA9NWE88/rRhKacIyry9tDR45x245RYID3dAwCIiIiYlO5J1I0bA0KEZFnlziR/oSA32cYIKtGMxCRS7fpv79sHdd8MHH2hNLRERcQglO5J1Fgu8/745y7LFkq64JOdYShvKEMN2buVh5pJC+qHr6aSlmYuRjhyphEdERHKdkh3JHovFTEy+/x6KFk1XXIUjLKYdRUlkGW0YyJTM5+C52jvvmGtzpaXlasgiIlK4KdmRnOnUyRxZFRiYrqgRW5lNdyyk8RlP8Q4jst7uxx+bbavjsoiI5BIlO5Jzt90GmzZluI5WB35iEuYK6iMZz2y6Zb3dn34yh7rPnKllJkRE5IYp2ZEbU7EibNgA9eqlKxrMZIbyAQB9mMF6mmS93b//hj59oG5dc9mKlJRcClhERAobJTty48qVg7VrzckCr/EeL9CZ77mENx35gX3UyF7be/fCQw9B+fJmf57Nm9WJWUREskXJjuSOEiVg5Upo2dJmtxsG3/IYdxDOOUrSmmWcpmz22z992lyn6447oGpVeO012L07l4IXEZGCzGIY+mdyfHw8/v7+xMXF4efn5+xw8rfUVHjzTXMCwqtePf1NacII5zBVuZ0t/EJzfqchUQQRRBRN2IA7ORiFVbs2PPywudWsmYsXIiIiri6r399KdlCy4xDbt0PfvvDHH9ZdB6lKGOGcoTRFuEgS/w1dL88JJvEcnVmY83PWrQv33mu+Vitb9r+fgYEQEgIeHjdyRSIi4mKU7GSDkh0HuXQJxo83n/T8+5RnLC/xCmMB20kJLf8+1ZlP1xtLeOzx9jZHj911l7ndeSeULp375xERkTyjZCcblOw42LZt0Lo1qf+cpRJHOUl5rk12wEx4ynOSI1TO2Sut7KpRw0x6WrSA+++HMmUcf04REck1SnayQclOHti9m7VNXqPZuQXXrXorETRiC9U4aN2q8CdeXHZcfBaL+eSnVStza9RIr71ERFyckp1sULKTN2Z/GMWjz19nNXQ73EilIsdsEqArWyWO4kkuz8Pj5gZ+fuDvb7v5+ppbsWK2m4+P+aqsSBHz55U/Fy1qTpAYGJjhemIiIpJzWf3+1j9dJc8E3ZK1RGcE4/EgxSalSaA4R6jCEarwM7bD291JoTJHqMqhdIlQRY7hQQ5mYU5Lg9hYc8sNZcpAs2bQvLm5Vami5EdEJI/oyQ56spNXUlOhUiX46y8Dw8h6nx0DOE25DJ7pVOMQVUmkmN1zenKJyhzJ8IlQCCfypm9QRipUMJOfkBAoVQpKlvzvZ0CA+UTo2idF7llYQV5EpBDRa6xsULKTdxYsgK5dzT9f/cnL6WgsAzhFcIaJ0GFuthnefi0vkrmZw1TjYLqnQuU5iVvW12vPGx4eGb8q8/Y2X7lVqmQu21G/vrmpw7WIFHD5ItkZN24cCxYsYN++fRQtWpQ777yTd955hxo1/ltSoGnTpqxbt87muKeeeopp06ZZfz9+/DgDBgxgzZo1+Pr60rt3b8aNG4dHFjuYKtnJWwsWmCs/nDz5376Qon8z8eJTuTrsPA0Lf3GT3UToEt52jy3CRWsidO0WzKkMxpK5oKAgM+mpW9cceVa9uvmzTBm9QhORAiFfJDutWrWiW7du3H777aSkpPDyyy+za9cu9uzZQ7Fi5quJpk2bUr16dd544w3rcT4+PtaLSk1NpUGDBgQGBvLuu+8SFRVFr1696N+/P2PHjs1SHEp28l5qqrl+aFSU+Z3cpAm4R2yBCRPMVc8vO3DkFZCKGycIyTAR+pMqpOBp91gfLtg8Cbr6z4FEu34i5O9vJj41a8Itt0DDhubP4sWdHZmISLbki2TnWn///Tdly5Zl3bp13HPPPYCZ7DRo0ICJEydmeMyyZcto164dp06doly5cgBMmzaNESNG8Pfff+Pl5ZXumOTkZJKTk62/x8fHExISomTHVZw5A99/D7NmwTVP9fJCCu4co6K1T9DVidARKpOaSb9+X85n2FG6Ggcpw9+umwhZLGYC1LChOQS/UyfztZiIiAvLl8nOoUOHqFatGjt37qROnTqAmezs3r0bwzAIDAykffv2vPbaa/j4+AAwatQofvrpJyIjI63tHDlyhCpVqvD7779zyy23pDvPmDFjeP3119PtV7Ljgk6cgDlzzMTnqv/GznIZD45SKcMnQseoSBr2OxH7EZfuqCuJUSnOuF4i1LQpjB5t/hQRcUH5LtlJS0vjwQcfJDY2ll9//dW6/7PPPqNixYoEBwezY8cORowYQaNGjViwwJyc7sknn+TYsWOsWLHCekxiYiLFihVj6dKltG7dOt259GQnnzpwAObNg7lzYccOZ0eTTjJeHKFyhonQCUIwcLN7bADnMnwaVI2DlCA27y4iIw8+aL5evKovnYiIK8h3yc6AAQNYtmwZv/76K+XLl7dbb/Xq1TRv3pxDhw5x88035yjZuZb67ORD+/aZic/335uJj2t8jO1Kwps/qZJhOnOSkEyPLcU/GSZBVTmEP/G5El8qbmygif1V6D084OmnzSc9WlNMRFxEvppUcNCgQSxevJj169dnmugANG7cGMCa7AQGBrJlyxabOqdPnwYgMDDQMQGL89WsCa+9Zm7nz5tPfWJizO306f9+7t1rvv5KzcHEgrmoCMmEspdQ9qYrS6Qoh7k5w0QoimDOUJozlGYTYemOLUOM3SdCvlzIUmwL6MRzTLJJutKtQp+SApMnw9dfw1tvwcCB5izTIiL5gFOTHcMwGDx4MAsXLmTt2rVUrlz5usdc6ZsTFGTOxhsWFsbbb79NTEwMZcuWBWDlypX4+fkRGhrqsNjFhRQvbnastSchAbZsgd9+M7eNG80EyUX4cJG67KIuu9KVJVDM2kn62s7Spwnkb8ryN2XZyF3pjg0kyu4TIR8uAmai05X56WYU+oub6Mr89PMexcfDs8+arxKnT4dq1XLzVoiIOIRTX2M988wzzJo1ix9//NFmbh1/f3+KFi3K4cOHmTVrFm3atKFUqVLs2LGDoUOHUr58eevcO1eGngcHBzNhwgSio6Pp2bMnTzzxhIaeS8YuX4bNm2H5cnOLiHB2RDkST/F0CdCV7R8yn1AwmL+oykEiuI0LFCNHq9AXKQJvv21OmqTZnUXECfJFnx2LnYnNvvrqK/r06cOJEyd47LHH2LVrFxcuXCAkJIROnTrx6quv2lzUsWPHGDBgAGvXrqVYsWL07t2b8ePHa1JByZqYGPj5Z1i7FnbvNl9/xcWZm5Nff+VULP52Xm5V4xwls9XWGprSlEymAAgLg6++UgdmEclz+SLZcRVKdiRDhgGJif8lPufPw4UL6beEBEhKguRk25+xseZrs7//dvaV2DhLCQ5Sja/pxScMvG79WXSnO3Myr+TjA5MmQb9+mp1ZRPJMvuqgLOKSLBYoVszcgoNz1oZhwK5dsGoVrF5tPj1ycn+hkpyjMVu4SNEsJTveJF2/0cRE6N/ffC342WfmgqYiIi5CT3bQkx3JQykp8OefcPQonD1rzhZ99c+zZ83E4dqnRFf/TE6GS5duOJRU3KjEUf7iJjtzABmABX/O8Q4v0Z/Ps7Y4avny8O23cO+9NxyjiEhm9BorG5TsSL6TlmYmPMnJZqK0cyf88Ye5RUaaCVUWXBmNBdgkPBbSMIDKHOUIVQBozCam8TQN+CNrMfbrB2PHwr+jJEVEcpuSnWxQsiMFTny8OfHigQPmtn//f39OTLSpmtE8OyEcZyJDeJCf+IRneJW3OI8fbqTyHJN4ndEUJ+H6cfj7w5tvwoAB5sSEIiK5SMlONijZkUIjLQ2OHTOH21/ZVq687gzKpwhiKB8yl0cAuImT/046uCBra3rVrQtTppjL24uI5BIlO9mgZEcKNcOAb74x58w5cCDTqit4gGf4hD+5GYA2LGEyg6jM0eufx2KBESPMGZg1L4+I5IKsfn9rvneRws5igV69zFFjH30EpUrZrdqSn9lFHV7jDTy5xFLaEsoexjKSS3hmfh7DgPHjoVMnp49IE5HCRcmOiJg8PWHwYDh0CJ56ym61oiTxBqPZSV3uYxVJFOUVxtKASNaShRFYixbBnXeaI9JERPKAkh0RsRUQANOmwS+/QKVKdqvV4AC/0IJv6UFZTrOXUJqxlt7MIOY6y1Wwaxfcfjv8+muuhi4ikhElOyKSsebNzSHtA+1PPGgBejCLfdTkaaZiIY2v6U1N9vEZ/UnLrPvyP/+Y55hzndmZRURukJIdEbHP1xcmTzZngL7pJrvVShDLVJ4hnDAasJ1zlOQpPuNufuUP6tlv/9Il6N4dJkww+/SIiDiAkh0Rub777jMnLOzYMdNqjdnCVm7nQ4bgy3nCuZOGRDCM90igmP0DR4yAQYPy7cKrIuLalOyISNaUKgULFsDUqVCkiN1qHqQyhEnsoyZdmUcqHnzAMGqxl4V0tL/gxCefQOfO6SY9FBG5UUp2RCTrLBZ4+mlzMsJGjTKtehOnmMfDLKU1lfmTk4TQmYW0ZxFHqJTxQT/9BC1amGuEiYjkEiU7IpJ9oaEQHg5ffAGlS2datTXL2UUdXuEtPLnEEtpRm92MZ0TGc/OEh8Pdd8OJEw4KXkQKGyU7IpIzbm7mYp8HDpjz87jZ/+vEh4u8xWv8QX2asoaL+DCS8dzCdtaTwRISe/eac/Hs2ePACxCRwkLJjojcmBIlzJmXt2+H2rUzrVqLfazmPr6mJ2WIYQ+1uZf19GU6f3PNE6KTJ81XZZMmqeOyiNwQJTsikjvq1YONG6Ft20yrWYCefMs+avIU0wCYQV9qso8v6Gc7N8+FCzBkCNx1lzkRoYhIDijZEZHc4+cHP/4IL7xw3aolOcc0BhDOHdQnkrOUoj9f0IQN7KSObeXNm+HWW2HYMDhyxEHBi0hBpWRHRHKXuzu8+y5Mnw4eHtetfgeb2cZtfMBQipHARu7iFrYznAm2c/NcvgwffAA33wzt28Py5ZCW5sALEZGCQsmOiDhG376wdCkUL37dqh6kMpSJ7KUWnfmeVDx4j+GEsocfedC2smHA4sXQujXUqGHO8Jyc7KCLEJGCQMmOiDjO/ffDhg0QHJyl6iGc5Hu6spi2VOIIJ6hAR37kQX7kGBXSH3DokDkSrE4dWL8+l4MXkYJCyY6IOFb9+rBpk5mQZFFblrKb2oxkLJ5cYhEPEsoeJjCcy2TwauzQIbj3XjPxSUjIxeBFpCBQsiMijhcSYj7hueeeLB/iw0XG8gqRNOAe1pFIMUYwgVvYzgbuzvigyZPNUWGrV+dS4CJSECjZEZG8ERAAK1ZAp07ZOiyUvaylKTPoTWn+Zjd1uIcNPM6X/EOp9AccOQLNm8PAgVpnS0QAJTsikpeKFIF58+DJJ7N1mAXozdfsoyb9+QyAr3icGuxnOn1t5+a54pNP4JZbYOvWXAhcRPIzJTsikrfc3WHaNHj99WwfWoqzfMZT/Mad1GUHZylFP6ZzL+vYRQazNx84YC478dZbkJKSC8GLSH6kZEdE8p7FAqNGmUPTy5fP9uF3Ek4EDXmPYRQjgV9pwi1sZwTjuYCPbeWUFHjtNbO/0J9/5tIFiEh+omRHRJyndWvYvRueeSbbh3qSwjA+YA+hdGQhKXgygRGEsoefaJ/+gPBwuO02WLkyFwIXkfxEyY6IOJefH0yZYo7WqlEj24dX4AQL6cxPtKciRzlORTrwEx1ZyHFCbCufOwetWsF775mTE4pIoaBkR0Rcw913Q2QkvPFGlmZdvlZ7FrOb2rzEODy4zI90pBZ7eZcXbOfmSUuD4cPhjjtg//7ci19EXJaSHRFxHUWKmP1rTpyASZOgevVsHV6MRMbxMpE0oAnrSaQYL/Iut/I7v3GnbeUtW6BmTWjaFL78EmJjc+0yRMS1WAxDz3Lj4+Px9/cnLi4OPz8/Z4cjIlekpcGqVeZrrkWLsrXwpwHMpDcv8B5nKA1AP77gHUZQirPpD/D2NvsQtW0LbdpkeYkLEXGerH5/K9lByY5IvrBnDzz+OGzenK3DzlCSEbzDlzwBQCn+4T1eoDczM5qd5z8NGvyX+DRubA6ZFxGXktXvb73GEpH8ITQUfvvN7FxcpEiWDyvFWb6gP79yF3XYyRlK05cZ3Ms6dhNq/8DISHj7bbjrLrj5Znj/fbh48cavQ0TynFOTnXHjxnH77bdTvHhxypYtS8eOHdl/TYfBpKQkBg4cSKlSpfD19aVLly6cPn3aps7x48dp27YtPj4+lC1bluHDh5OiCcRECh53dxg2DP74w0xCsuEuNvI7tzKB4fhwgQ3cQwMiGclYEima+cHHjsELL0Dt2rB48Q1cgIg4g1OTnXXr1jFw4EA2bdrEypUruXz5Mg888AAXLlyw1hk6dCiLFi1i3rx5rFu3jlOnTtG5c2dreWpqKm3btuXSpUts3LiRmTNnMmPGDEaNGuWMSxKRvFC9OqxbB+PGgadnlg/zJIXhvMceQunAD6TgyXhGEsoeFtP2+g0cOQLt20PHjuafRSR/MFxITEyMARjr1q0zDMMwYmNjDU9PT2PevHnWOnv37jUAIzw83DAMw1i6dKnh5uZmREdHW+tMnTrV8PPzM5KTk7N03ri4OAMw4uLicvFqRCRPREQYRq1ahmHOnJOt7UfaGxU4at3Vie+N45TPehvNmxvGxx8bxp49hpGW5uw7IVLoZPX726X67MTFxQFQsmRJACIiIrh8+TItWrSw1qlZsyYVKlQgPDwcgPDwcOrWrUu5cuWsdVq2bEl8fDy7d+/O8DzJycnEx8fbbCKST916K0REwODB2T70QRaxh1Be5B08uMxCOlOLvbzP87Zz89izapV53tBQc9mLnj3h++8hOTkHFyIijuIyyU5aWhpDhgzhrrvuok6dOgBER0fj5eVFQECATd1y5coRHR1trXN1onOl/EpZRsaNG4e/v791CwkJybCeiOQTRYvCRx/B3Lng43P9+lcpRiLv8BK/cyt38SsX8OUF3uc2thHOHVlv6NQp+PZb6NoVKleGiRMhMTF71yEiDuEyyc7AgQPZtWsXc+bMcfi5Ro4cSVxcnHU7ceKEw88pInngoYdg40aoVCnbh9ZlF+u5hy95nJKcYQf1uZNwnuRTzlIie41FRcHQoWbS8+67kJCQ7XhEJPe4RLIzaNAgFi9ezJo1ayh/1QrIgYGBXLp0idhrZjY9ffo0gYGB1jrXjs668vuVOtfy9vbGz8/PZhORAqJ+fdi2De67L9uHumHwOF+xnxo8zpcAfM6T1GA/X9OTbE9KFhMDL75oJl/jxsFVgy9EJO9kKdm5tn9LVrasMAyDQYMGsXDhQlavXk3lypVtyhs2bIinpyerVq2y7tu/fz/Hjx8nLCwMgLCwMHbu3ElMTIy1zsqVK/Hz8yM0NJM5NESk4CpVClasMJ+q5OAfM6U5w5c8wXqaUJtd/EMZevM1zVjDXmpmP54zZ+Dll6FqVfj0U7h8OfttiEiOZWkGZTc3NyyWTOcatW3UYuHAgQNUqVIl03rPPPMMs2bN4scff6TGVasd+/v7U7SoOe/FgAEDWLp0KTNmzMDPz4/B/3ZC3LhxI2AOPW/QoAHBwcFMmDCB6OhoevbsyRNPPMHYsWOzFK9mUBYpwP7+Gz75xOxPc+hQtg+/hCcfMpTXGc1FfPDkEi/wHq/yFj7kcJLB6tVh7Fjo3Bmy8XeriNjK1eUi3Nzc+P77762jpDJjGAZt2rRh165d10127CVQX331FX369AHMSQWHDRvG7NmzSU5OpmXLlnzyySc2r6iOHTvGgAEDWLt2LcWKFaN3796MHz8eD48sjKZAyY5IoWAY5uKf334Lc+bAP/9k6/CjVGQwH7OY9gBU4ghTGEgbluU8psaNzY7Md2SjI7SIWOVqslO5cmW2bdtGqVKlsnTyOnXqsGzZsnwzyknJjkghc/kyLF8OCxbA0qVm35osMIAf6cCzfMQJKgDQhflMZAjl+StnsVgs8Pzz8NZb2VoGQ0S0EGi2KNkRKcTS0uD332HJEjPx2brVfAqUiQSK8Tqj+ZChpOKBL+d5g1EM5mM8SM1ZHLVqwddfw2235ex4kUJIC4GKiGSFm5uZYIweba6ofuCAudJ5Jny5wLu8yO/cShgbSaA4z/Mht7GNTTTOWRx795qvs8aMUQdmkVyWoyc7W7duZc2aNcTExJCWlmZT9sEHH+RacHlFT3ZExIZhwA8/wHPPwXXm4UrDwnQe50UmcI6SWEjjST5jHCMpQWzOzl+7Nnz8MTRrlrPjRQoJh73GGjt2LK+++io1atSgXLlyNp2MLRYLq1evznnUTqJkR0QydOECjB8PU6bAuXOZVv2b0rzIBGbQF4AyxPABz9OD78jxeKuHHoL33oMKFXLagkiB5rBkp1y5crzzzjvW0VIFgZIdEclUYqLZmfnnn831sE6dslt1HfcwgKnsxZznqxmr+YRnqMn+nJ27aFF46SUYPtz8s4hYOazPjpubG3fdddcNBScikq/4+MBjj5kdiE+ehH37zKc9nTqBp6dN1XtZTyQNGMdLFCWRNdxHPXbwKm9ykRyMtrp40exPFBoKP/543c7TIpJetpOdoUOHMmXKFEfEIiLi+iwWqFEDnnnGfNpz6JD5Zy8vaxUvLvMS77Cb2rRhCZfx4m1epQ67WE7LnJ336FHo2BFat4b9OXxKJFJIZfs1VlpaGm3btuXAgQOEhobiec2/ahYsWJCrAeYFvcYSkRv2118wYQJ89hkkJVl3G8BCOvEckziJOfdYV+YxkSHchP3XYZny9DQXGn3tNfD1zYXgRfInh73GevbZZ1mzZg3Vq1enVKlS+Pv722wiIoXSTTfBpEnmk57+/c0h7YAF6MxC9hDK87yPOynM5yFqso9JPEsK7tk/1+XLZmLVoAFERubmVYgUSNl+slO8eHHmzJlD27ZtHRVTntOTHRHJdXv3mot//vCDze4/qMfTTGMT5mLGDdjOpzxFI7bm7DxFi8JXX8Ejj9xgwCL5j8Oe7JQsWZKbb775hoITESnwatWChQvht9/g1lutu+uzg9+4i095khKcJZJbuINNPMMUYsnB0/GLF6FbN3PEVmoOZ28WKeCyneyMGTOG0aNHk5iY6Ih4REQKljvvhE2b4PXX4d/Fid0weJLP2UdNejETAzem8gw12M93PEqOxlu98w60b3/d+YBECqNsv8a65ZZbOHz4MIZhUKlSpXQdlH///fdcDTAv6DWWiOSJ33+HXr1g926b3WtoyjN8wj5qAXAfq/iEZ6jBgeyfo2JFc1V3raQuhUBWv789sttwx44dbyQuEZHC69ZbISICRo2C99+3vnZqxlr+oD7v8QJv8hqraU49djCCdxjJOIqSdJ2Gr3LsGDRpAm+/DS+8YO0oLVKYadVz9GRHRJxg50549llYu9Zm959UZhCTWYa5GOnNHGIKA2nJz9k/R6tWMHMmlC2bCwGLuB6tei4i4srq1oXVq2HuXAgJse6uwhGW0Jb5dCGYvzhMVVqxgkeYwymCsneO5cvNRUVnzdLMy1KoZSnZKVmyJP/880+WG61QoQLHjh3LcVAiIoWCxWIu9rl3L7z6Knh7m7uBLixgHzUZwoe4kcpcHqEm+/iIwaRm59+p//wDPXpAu3Zw/LhjrkPExWXpNZabmxszZ87M8qSB3bt3Z+fOnVSpUuWGA8wLeo0lIi7hzz/NmZF/+slm93Ya8DTT2EJjAG4lgmk8ze1sy177xYrBuHEwcKD68kiBkKurnrvl4H+KQ4cOKdkREcmJ5cvhuefgwH+jsVJx43P6M5JxxFICC2k8wye8xasEEJe99h94AGbPhpIlczlwkbyVq3120tLSsr3ll0RHRMTltGpldmB+6y3rExh30niaT9lHTR7jGwzcmMIgarKP2XTL3tw8P/8Mt99unkOkENBzTBERV+TlBa+8AitWQIkS1t3liOEberGK+6jOfk4TyKPM5gF+5iBVs97+n39CWBh8/70DghdxLUp2RERcWYsWsG0b1Kljs/s+1rCDerzJq3iTxC/cTx12MYbRJOGdtbYvXICuXc2kKiXFAcGLuAYlOyIirq5KFQgPNxOTq3hziVd5m93UpiXLuYQ3rzOGuuxkJS2y3v7YsXDXXXDwYC4HLuIaspzsnDp1ypFxiIhIZnx9zTl5Jk82X3Fd5Wb+ZBmtmctDBHGKQ1TjAVbSnVlEEZi19rdsgQYN4LPPNCePFDhZTnZq167NrFmzHBmLiIhkxmIxh41v2gTVqtkWAQ8xn33U5Dkm4kYqc+hOTfYxmYFZm5snMRGeego6dIC//nLMNYg4QZaTnbfffpunnnqKhx56iLNnzzoyJhERycwtt5hrbPXoka7Ij/NMZChbuZ3b2UI8/gxmMo3ZTAS3Zq39RYugZk344AO4fDmXgxfJe1lOdp555hl27NjBmTNnCA0NZdGiRY6MS0REMlO8OHzzDXz9tc1orStuZTvhhDGFZ/AnlghuoxFbGMxHxJGF+cQSEmDYMHPx0g0bHHABInknRwuBTp48maFDh1KrVi08PGwXTv/9999zLbi8okkFRSRfO33anITwf//LsDiacgzjfWZhPgkKJIqJDOFh5mLJ6jl69YJ339WiouJScnUG5asdO3aMvn37smvXLp566ql0yc7o0aNzFrETKdkRkQLhp5/gmWfs9rdZxX0MYCoHqQ7A/fzMJzxDVQ5nrf2AAHj7bbNfj7t7LgUtknMOSXY+//xzhg0bRosWLfj0008pU6ZMrgTrbEp2RKTAiI83k5E5czIsTsKbCbzIWF4mmSJ4k8TLjGUE7+DNpaydo2FDmDrVnIVZxIlydbkIgFatWjFixAgmT57MggULCkyiIyJSoPj5waxZ8M475uitaxQhmVG8yS7qcD8/k0wRRvMGddnJLzTP2jkiIqBxYxgwwEyuRFxclpOd1NRUduzYQa9evRwZj4iI3CiLBV58EZYuNV89ZaAqh1lBS+bwCIFEcZDq3M8v9OBboil3/XMYBkybBvXqwZo1uRu/SC7LcrKzcuVKypcv78hYREQkN7VqZU4WeM1SE1dYgEeYyz5qMpiPcCOVWfSgJvv4hAFZm5vn2DG47z6zg3RiYu7GL5JLtFyEiEhBVq0abN0KQ4bYreJPPB/xHJtpTEO2EUcAA/mEMML5nVuydp6PPjLn/9m0KXfiFslFSnZERAq6IkXgww9h5UoIDrZb7TYi2ExjJjMQP+LYSiNuZyvPMZF4il//PAcOmGtsjR8PaWm5eAEiN0bJjohIYdGiBezcCQ8/bLeKO2kM5BP2UZNuzCYNdz7iOWqyj7k8xHWH76alwciR5pITmm1fXIRTk53169fTvn17goODsVgs/PDDDzblffr0wWKx2GytWrWyqXP27Fl69OiBn58fAQEB9OvXj4SEhDy8ChGRfKRkSXNY+pw5EBRkt1oQ0czmUX7mfqpykCiCeYS5tGYZh6ly/fMsXmzOvrx1ay4GL5IzTk12Lly4QP369ZkyZYrdOq1atSIqKsq6zZ4926a8R48e7N69m5UrV7J48WLWr1/Pk08+6ejQRUTyL4sFHnkE9u2DoUMznSDwfn5hJ3UZzRi8SGYFrajDLt7iFZLxsnscYHZevvtuc9SWiBPlaLkIR7BYLCxcuJCOHTta9/Xp04fY2Nh0T3yu2Lt3L6GhoWzdupXbbrsNgOXLl9OmTRtOnjxJcCbvpq+mSQVFpFDbscOcefm33zKtdoBqDGQKv3A/ADXYxyc8w31kYej5s8+aC4tq5mXJRbk+qaCzrF27lrJly1KjRg0GDBjAmTNnrGXh4eEEBARYEx2AFi1a4ObmxubNm+22mZycTHx8vM0mIlJo1asH69fDV19BJhPGVucgP/MAs+lGOaLZT02as5qefM1prrNm1kcfQceO5gKjInnMpZOdVq1a8fXXX7Nq1Sreeecd1q1bR+vWrUlNTQUgOjqastcsSufh4UHJkiWJjo622+64cePw9/e3biEhIQ69DhERl+fmBn36wP795szIGcy+DObcPN34H/uoyUAmYyGNb+lJTfYxjadIy2xp0cWLoUkTOHnSIZcgYo9LJzvdunXjwQcfpG7dunTs2JHFixezdetW1q5de0Ptjhw5kri4OOt24sSJ3AlYRCS/K1ECPvkENm+Gq56aXyuAOCYzmM005lYiiKUEA5hGGOFsp4H99iMjzfl45s41Z2EWyQMunexcq0qVKpQuXZpDhw4BEBgYSExMjE2dlJQUzp49S2BgoN12vL298fPzs9lEROQqt99uThA4caI5T4+9amxjC434iMEUJ54tNOY2tjGUDziPb8YH/fOP2UG6a1c4fdox8YtcJV8lOydPnuTMmTME/TtcMiwsjNjYWCIiIqx1Vq9eTVpaGo0bN3ZWmCIiBYO7u7kMRGSkufCnvWqkMZjJ7KMmjzCHNNyZyFBqsZf5dLE/N8+CBRAaai5cqqc84kBOTXYSEhKIjIwkMjISgCNHjhAZGcnx48dJSEhg+PDhbNq0iaNHj7Jq1So6dOhA1apVadmyJQC1atWiVatW9O/fny1btvDbb78xaNAgunXrluWRWCIich01asCvv8LYseDpabdaMFHMoTvLacnNHOIvyvMQ82nLEv6kcsYHnT0LPXrAE0/ApUsOugAp9AwnWrNmjQGk23r37m0kJiYaDzzwgFGmTBnD09PTqFixotG/f38jOjrapo0zZ84Y3bt3N3x9fQ0/Pz+jb9++xvnz57MVR1xcnAEYcXFxuXl5IiIFT2SkYVSvbhjmsxi7WyJFjNd43fAiyQDDKEKi8RYvG0l42T+ubVvDuHjR2Vco+UhWv79dZp4dZ9I8OyIi2RAfD/37m52Mr2M/1XmGT1hNcwBqspepDKAp6zI+oHlz+PFHKFYsNyOWAqrAzLMjIiIuxs/PXG7i448zfa0FUIMD/EILvuNRynKafdSiGWvpxUxiyGBOn1WroFUrM6ESySVKdkREJPssFhg0CDZsgExGv4I5N8+jzGYfNRnAJ1hI4xt6UZN9fEb/9HPz/PqruWjpP/84Ln4pVJTsiIhIzjVubM7JU7fudauWIJZPGMgm7uAWfuccJXmKz7iL3/iDeraVt24119U6dsxBgUthomRHRERuTIUK5tOYVq2yVL0RW9lCIybyHMWJZxNhNCSCYbxnOzfP/v1w552wc6eDApfCQsmOiIjcOD8/WLTIXFA0CzxI5Tk+Yi+1eIi5pOLBBwwjlD0soNN/c/OcOmUuMbEmC4uNitihZEdERHKHhwdMmQLffmsuO5EFN3GKuTzCUlpTmT85SQhdWEB7FnGESmaluDhzlNbIkZqLR3JEyY6IiOSuHj1g927o0CHLh7RmObupzau8iSeXWEI7arObcbzEJTzBMEgdP4G1tQcy+92TrF0L/64JLXJdmmcHzbMjIuIQhmEOUR80yJwpOYv2UYMBTGUtzQCoxR66M4vPeIqThFjrlS9vMGmShc6dcz1yySey+v2tZAclOyIiDhUVBS1bZqujsQF8Rw+e5wP+puxVe/8bpm4hDSwW5s9XwlNYaVJBERFxDUFBZgfjhg2zfIgFeIzv2EMtipHAtYkOgIEbGAZDnkggNaXQ/7tdMqFkR0REHK9UKXN25DvvzNZhu6jLBXy5NtG5wsCNE+d82XD3SPMJkkgGlOyIiEje8PeHFSvMkVVZFEVQ1uptPgYNGkB4eA6Dk4JMyY6IiOQdX19YsgQefjhL1YPI2tOaIKIgJgaaNcvSAqVSuCjZERGRvOXtDbNnm6O0rqMJGyjPCbMzcoYMyhFFEzaYvyYnwyOPwNix5mgwEZTsiIiIM7i5wUcfwdtvZ1rNnTQm8RxABgmP2Wn5Mp6cIti26JVX4PHHNQmhAEp2RETEWSwWePllmDkTihSxW60zC5lPV27iL5v9N/EX5TnOWUrTmmXE4m974IwZ0LmzEh5RsiMiIk7WqxdERJgdjO3ozEKOUok1NGUW3VlDU45Rkd+4myBOsZs6dGIhyXjZHnilf9Dly469BnFpSnZERMT5QkNh82Z46SXziU8G3EmjKevozhyasg530qjACZbShuLEs5Zm9GEGadcOU//xR+jeXQlPIaZkR0REXIOXF4wbB+vWQcWKWT6sAX/wPV3w4DJz6M5IxqWv9P338NhjkJKSiwFLfqFkR0REXEuTJrBjh9nBOIvu5xemY9afwAgmMzB9pblzoV07iI/PrUgln1CyIyIirsfPD778EhYtgsDALB3Sk295m5cBeJaPWEjH9JVWrIC77oJjx3IxWHF1SnZERMR1tWsHu3ZBt25Zqj6ScTzFNAzceJRZbCQsfaVdu6BxY9i6NZeDFVelZEdERFxbqVLmJISffQbu7plWtQCTGUQ7FpFEUdqziP1UT1/x9Gm4915zvS4p8JTsiIhI/tC/PyxbZr7iyoQHqcyhG7ezhbOUojXLOE3Z9BUvXoQHH4Q//nBQwOIqlOyIiEj+cf/9sHHjdUdrFSORxbSjCoc5QhXasoQEiqWvmJgIHTvCmTOOiVdcgpIdERHJX2rXhk2boGbNTKuV5W+W04rS/E0Et/EI/yOFDF6DHT1qTjyoYekFlpIdERHJfwIDYfVqqJ5Bf5yrVOMQi2lHURJZSlue4RMyXB509Wp46iktLVFAKdkREZH8KSjITFJuvjnTao3Zwhy64UYqn/Mkb/NKxhWnTzeHpR8+7IBgxZmU7IiISP51002wZg1UrpxptQdZxGQGAfAabzGD3hlX3LYNbr3VnIBQCgwlOyIikr+FhMCGDXDLLZlWG8A0Xvp3KYn+fM4KHsi4Ynw8PPIIDB6sfjwFhJIdERHJ/266Cdavh/btM632Nq/Qg29JwZOuzGc7DexXnjzZnMxQ/XjyPSU7IiJSMPj6wsKFMGSI3SpuGEznce5jFQkUpw1LOUYF+21+/z107gxJSbkfr+QZJTsiIlJwuLvDhx/C22/breLFZRbQmbrsIJogWrOMs5Sw3+aSJeYTowsXHBCw5AUlOyIiUvCMHAmPPmq32J94ltKG8pxgL6F05AeS8Lbf3i+/QOvWSnjyKSU7IiJS8Fgs8PnnmXZaLs9fLKM1/sSygXvoxdekYbHf5oYNZh+etDQHBCyOpGRHREQKJh8f+OEHKFPGbpU67GYhnfDkEvN4mBd4L/M2Fy+GN9/M3TjF4Zya7Kxfv5727dsTHByMxWLhhx9+sCk3DINRo0YRFBRE0aJFadGiBQcPHrSpc/bsWXr06IGfnx8BAQH069ePhISEPLwKERFxWRUqmBMPlitnt0oz1jKDPgB8yPN8yJDM2xwzxkx6JN9warJz4cIF6tevz5QpUzIsnzBhAh999BHTpk1j8+bNFCtWjJYtW5J0Va/4Hj16sHv3blauXMnixYtZv349Tz75ZF5dgoiIuLo6dcy1tBo1slvlUWbzDi8CMIz3mUfXzNt87DE4dCg3oxRHMlwEYCxcuND6e1pamhEYGGi8++671n2xsbGGt7e3MXv2bMMwDGPPnj0GYGzdutVaZ9myZYbFYjH++usvu+dKSkoy4uLirNuJEycMwIiLi8v9CxMREdeQnGwYL7xgGJDhlgbGQD42wDC8uWis5267dQ0wjEqVDOPQIWdfVaEWFxeXpe9vl+2zc+TIEaKjo2nRooV1n7+/P40bNyY8PByA8PBwAgICuO2226x1WrRogZubG5s3b7bb9rhx4/D397duISEhjrsQERFxDV5e8O675lDyUqXSFVuASTxHRxaSTBE68CN7yWRl9aNH4e67Ydcuh4UsucNlk53o6GgAyl3znrVcuXLWsujoaMqWLWtT7uHhQcmSJa11MjJy5Eji4uKs24kTJ3I5ehERcVlt2sDvv2e4Yro7acziUcLYyDlK0pplRBFov63oaLjnHtiyxYEBy41y2WTHkby9vfHz87PZRESkEKlQwVxeok6ddEVFSeInHqQaBzhGJdqyhPP42m/r3Dlo3lwJjwtz2WQnMNDMpE+fPm2z//Tp09aywMBAYmJibMpTUlI4e/astY6IiEiGypWDtWvNVc6vUZozLKcVZTnNdm7lIeZxGQ/7bSUkmLMsR0U5Ll7JMZdNdipXrkxgYCCrVq2y7ouPj2fz5s2EhYUBEBYWRmxsLBEREdY6q1evJi0tjcaNG+d5zCIiks+UKgWrVkGtWumKqnCExbTDhwusoBVP8hlGZm3FxEDfvpp00AU5NdlJSEggMjKSyMhIwOyUHBkZyfHjx7FYLAwZMoS33nqLn376iZ07d9KrVy+Cg4Pp2LEjALVq1aJVq1b079+fLVu28NtvvzFo0CC6detGcHCw8y5MRETyj4AAcwHR4sXTFd3ONubyMG6kMoO+jGFM5m2tWGGuli6uJY9Gh2VozZo1BpBu6927t2EY5vDz1157zShXrpzh7e1tNG/e3Ni/f79NG2fOnDG6d+9u+Pr6Gn5+fkbfvn2N8+fPZyuOrA5dExGRAmzhQrvDzD+lv/XXz+mX+ZB0b2/D2LHD2VdTKGT1+9tiGEamT+UKg/j4ePz9/YmLi1NnZRGRwuzVV+2umP4ab/AWr+FOCj/xIG1YZr+doCBYvhzq1XNQoAJZ//522T47IiIiee71183FPjPwBqPozQxS8eAh5rGNhvbbiYoyh6SvW+egQCU7lOyIiIhc4e4O33wDvXqlK7IAn9Of+/mZRIrRliX8SWX7bcXFQcuWsGCB4+KVLFGyIyIicjUPD/jqKxg8OF2RJynMpysN2E4M5WjNMv4h/WzMVsnJ8NBDSnicTMmOiIjItdzcYNIkGDUqXZEf51lCWypwjAPU4EF+4iJF7LeVlgY9esAffzgwYMmMkh0REZGMWCxmH56ePdMVBRPFMloTwDnCuZMefEdqZl+pSUnmE574eAcGLPYo2REREcnM5MlQOX3fnFD28iMd8CKZhXRmCBMzn3Tw4EF44glzgLrkKSU7IiIimfHzMzstu6X/yryHDXyD+eRnMoN5n2GZtzVvniYddAIlOyIiItdz110wZkyGRQ8zjw8YCsBw3mMOj2Te1pAhMGtW7sYnmVKyIyIikhWvvmqufZWBoUxkCB8C0JuZrOVe++2kpZn9gObOdUSUkgElOyIiIllhscAXX8Czz2ZY/D7D6Mo8LuFNR35gF7Xtt5WWBo8+Ct9/76Bg5WpKdkRERLLKzQ0mToRx49IXYfANPbmbDcQRQGuW8ReZLEqdmmrO1rx0qePiFUDJjoiISPZYLPDSS/Dll+k6LRchmR/pQE32cpIQ2rCUODJZczElBR5+GCIjHRtzIadkR0REJCcefxzGjk23uyTnWEZrAoliB/XpwvdcwtN+OxcuQNu2cPKkA4Mt3JTsiIiI5NTw4Waico1KHGMJbfHlPKtoQT++zHwOnlOnoH17OH/eYaEWZkp2REREcsrNDWbOhAoV0hXdynbm0xV3UviWnrzKW5m3FRlp9uFJSXFMrIWYkh0REZEbUaqUOYzc2ztdUUt+5nP6AzCWV5jGU5m3tXQpPP20ZlnOZUp2REREblTjxjBnjrli+jX6MoPXMRcUHcgUfqJ95m19+aW5JpfkGiU7IiIiuaFjR5g9G9zd0xW9xpv04wvScKcbc9hMo8zbev11+Owzx8RZCCnZERERyS1du8J336Ubkm4BpjKA1izlIj60YzGHuDnztgYMgCVLHBdrIaJkR0REJDc98gh8/bU5H89VPElhLg9zKxH8QxlasZy/KW2/nbQ0eOwxOHrUsfEWAkp2REREcluPHvD+++l2+3KBJbSlEkc4TFXasZhEitpvJzbWnHTw0iXHxVoIKNkRERFxhCFD4Jln0u0O5DTLaUVJzrCFxnRjDimk7+djtXWrOZ+P5JiSHREREUewWGDSJGjdOl1RDQ6wiPYU4SKLeJDBfJz5pIMffWS+GpMcUbIjIiLiKB4e8L//Qf366YruJJzv6IGFNKYxgPG8lHlbffqYw9Il25TsiIiIOFLx4uZkgRnMstyZhUziOQBeZhzf8Jj9dgwDnngCPv7YUZEWWEp2REREHC04GJYvhxIl0hUNZjIv8C4AjzOdX2ieeVvPPgsTJjgiygJLyY6IiEheqFULFi+GIkXSFb3DCB5hDil40pkF/EG9zNsaMQKmTXNQoAWPkh0REZG8cued8O236Xa7YTCT3tzLWs7jRxuWcoLymbc1eDCsX++gQAsWJTsiIiJ5qUsXeP75dLu9ucQPdKQ2uzjFTbRmGbH4228nJcWcsfn4cQcGWzAo2REREclr48fDHXek2x1AHEtpQzB/sZs6dOQHkvGy387ff5trciUmOi7WAkDJjoiISF7z9DSHpJcsma6oAidYShuKE886mtKHGaRhyaCRf23fbg5LT011XLz5nJIdERERZ6hQAebMMefiuUZ9drCAznhwmTl05yXGZ97WvHnw3HPm8HRJR8mOiIiIs9x/P8yenWHC04JVTOdxAN7lRT5mUOZtTZkCb77piCjzPSU7IiIiztS1KyxcCF7p++b05Fve5mUAnmMSC+mYeVujR8PUqQ4IMn9TsiMiIuJs7dqZc/AUTb8C+kjG8RTTMHDjUWaxkbDM2xo4EH7+2UGB5k8uneyMGTMGi8Vis9WsWdNanpSUxMCBAylVqhS+vr506dKF06dPOzFiERGRHLr/fnOWZW9vm90WYDKDaM9PJFGU9ixiP9Xtt2MY0LMnxMQ4Nt58xKWTHYDatWsTFRVl3X799Vdr2dChQ1m0aBHz5s1j3bp1nDp1is6dOzsxWhERkRtwzz3w2WfpdnuQymy604jNnKUUrVlGNOXstxMTA48/rg7L/3L5ZMfDw4PAwEDrVrp0aQDi4uL48ssv+eCDD7jvvvto2LAhX331FRs3bmTTpk1OjlpERCSHevWCIUPS7S5GIotoz80c4ghVaMdiEihmv50lS7SkxL9cPtk5ePAgwcHBVKlShR49enD835kiIyIiuHz5Mi1atLDWrVmzJhUqVCA8PDzTNpOTk4mPj7fZREREXMa770Lz9AuCluVvltOK0vxNBLfxMHNJwd1+O88/D5GRjoszn3DpZKdx48bMmDGD5cuXM3XqVI4cOUKTJk04f/480dHReHl5ERAQYHNMuXLliI6OzrTdcePG4e/vb91CQkIceBUiIiLZ5OFhTjpYPX3fnKocZjHtKEoiy2jDAKZi92VVUhK0agWHDjk0XFfn0slO69ateeihh6hXrx4tW7Zk6dKlxMbGMnfu3Btqd+TIkcTFxVm3EydO5FLEIiIiuaRUKVixAoKD0xU1Zgtz6IYbqXxBf97iVfvtnD5tdn7+6y8HBuvaXDrZuVZAQADVq1fn0KFDBAYGcunSJWJjY23qnD59msDAwEzb8fb2xs/Pz2YTERFxOZUqmQlPiRLpih5kEZP/nWhwFG8yg9722zl6FFq2hLNnHROni8tXyU5CQgKHDx8mKCiIhg0b4unpyapVq6zl+/fv5/jx44SFXWcOAhERkfyiTh27c/AMYBojGQtAfz5nBQ/Yb2f3bujc2VwtvZBx6WTnhRdeYN26dRw9epSNGzfSqVMn3N3d6d69O/7+/vTr14/nn3+eNWvWEBERQd++fQkLC+OODFaSFRERybfuvBM+/TTDord5hcf4hhQ86cp8fucW++2sWwfvvOOgIF2XSyc7J0+epHv37tSoUYOHH36YUqVKsWnTJsqUKQPAhx9+SLt27ejSpQv33HMPgYGBLFiwwMlRi4iIOMBjj0G3bul2W4Av6UdzfiGB4rRlCUepaL+dN96AffscF6cLshiGZhyKj4/H39+fuLg49d8RERHXFRsL9epBBgNr4vCjCRvYST1qspffuIuSnMu4nTvvhA0bwM2ln3lcV1a/v/P3VYqIiBQmAQHwzTdgsaQr8ieepbShPCfYRy068CNJeKdvA2DjRnOV9EJCyY6IiEh+cu+9dvvdlOcvltEaf2L5lSb05BvSSJ8YAfDiixAR4cBAXYeSHRERkfzmhRdg6NAMi+qwm4V0wotk5vMQL/Bexm0kJUGnToViwVAlOyIiIvmNxQLvvQe9M55bpxlrmUEfAD7keT5kSMbtnDgBXbvCpUuOidNFKNkRERHJj9zc4IsvoEOHDIu7M4cJDAdgGO8zj64Zt7Nhg7mGVgGmZEdERCS/8vCAWbOgatUMi1/gPQbxMQZuPMa3rKdJxu1MmWLO1FxAKdkRERHJz3x84PPPMyyyABMZQkcWcglvOvAje6iVcTtDhhTY2ZWV7IiIiOR3TZvCU09lWOROGrN4lDA2EksJWrOMUwSlr7hvn92kKb9TsiMiIlIQvPMO3HRThkVFSeInHqQaBzhORdqyhPP4pq84ejTExzs40LynZEdERKQg8PeH774Dd/cMi0tzhuW0oiynieQWujKfy3jYVvr7b+jRo8CNzlKyIyIiUlDcey98+KHd4iocYQlt8eECP9OSJ/mMdGtGLV5srsF1+bJDQ81LSnZEREQKkkGDoG9fu8W3EcE8HsKdFGbQl9G8nr7SwoXmE54C0mFZyY6IiEhBYrHAJ59A48Z2q7RhGVMZAMCbjOJznkhfad48s9NzAVgvXMmOiIhIQVOkCHz1ld3+OwD9+YLXeAOAAUxlCW3SV5o+vUCM0FKyIyIiUhDVqgX9+2da5XVG05sZpOLBw8xlGw3TVxo6FPbvd1CQeUPJjoiISEE1Zgz4ZjDE/F8W4HP6cz8/k0gx2rKEP6lsWykxMd+P0FKyIyIiUlCVKwevvpppFU9S+J4uNGA7MZSjFcv5h1K2lSIiYMSIfNt/R8mOiIhIQfbCC9CsWaZVipPAUtpQgWMcpDoP8hOJFLWtNHEiPPsspKU5LlYHUbIjIiJSkLm7w//+B6GhmVYLIprltCKAc4RzJz34jtRr04TJk6F7d0hOdmDAuU/JjoiISEFXpgysXg01a2ZarRb7+IkH8SKZH+jEc0xKP+ng3LnQtm2+WlZCyY6IiEhhUK6cmfBUq5ZptSb8yrc8BsAUBvEeL6SvtGqV+Wrs9GlHRJrrlOyIiIgUFkFBsGaN3QVDr3iI+XzAUABe5F1m0y19pd9/h7vugsOHHRFprlKyIyIiUpjcdBN8840503ImhjKRIZjrbPVmJmtomr7S4cNw552wfbsDAs09SnZEREQKm2bNzFFa1/E+w+jKPC7jRScWsova6SvFxJgLkK5dm/tx5hIlOyIiIoXRm2/CLbdkWsUNg2/oyd1sII4AWrOMk2TwCuz8eWjdGpYvd1CwN0bJjoiISGHk7Q1z5kDJkplWK0IyP9KBmuzlJCG0YSlx+KWvmJQEDz4IP/zgmHhvgJIdERGRwqp6dViyBPz9M61WknMsozWBRLGTenRmAZfwTF/x8mXo2tVMolyIkh0REZHC7I47YMMGCA7OtFoljrGUNvhyntU053Gmp5+DByA1FR591JzI0EUo2RERESns6taFjRuhRo1Mq91CJPPpijspfMdjvMLbGVc0DOjVy1xTywUo2RERERGoWBF+/RUaNcq0Wkt+5nP6AzCOl5nK0xlXvHQJHnoIYmNzOdDsU7IjIiIiptKlzVmWW7XKtFpfZvA6owAYxGR+on3GFY8cMZ/wOHm1dCU7IiIi8p9ixeCnn+CxxzKt9hpv8gSfk4Y73ZjDJhpnXHHRIujQwamLhyrZEREREVuenjBzJgwbZreKBZjKANqwhIv40J5FHKRqxpUXLYLGjWH3bsfEex1KdkRERCQ9Nzd47z2YMMFuFQ9S+R+P0JBt/EMZWrOMGMpkXPmPP6BhQ5g4EdLSHBOzHUp2RERExL7hw+GTT+wW+3KBJbSlMn9ymKq0YzEX8Mm4cnIyDB0KLVvCX385KOD0lOyIiIhI5gYMgBkzzKc9GShHDMtoTUnOsJVGdGMOKbjbb++XX8zh7nPnOibeaxSYZGfKlClUqlSJIkWK0LhxY7Zs2eLskERERAqO3r1h9mxwzziJqcEBFtGeIlxkMe0ZxGRScGMt9zKbbqzlXlKvTjvOnYNHHoGePSEuzqGhF4hk53//+x/PP/88o0eP5vfff6d+/fq0bNmSmJgYZ4cmIiJScDz8MLz7rt3iOwlnFo9iIY1PeZpSnKEZa3mU2TRjLZU4ygI62R707bdQrx6sW+ewsAtEsvPBBx/Qv39/+vbtS2hoKNOmTcPHx4fp06c7OzQREZGCZcgQ6NjRbnEnfuBxvgQgngCbsr+4ia7MT5/wHD8O+/fnbpxXyffJzqVLl4iIiKBFixbWfW5ubrRo0YLw8PAMj0lOTiY+Pt5mExERkSywWOCrr6By5QyLU3FjBa0gg5WzjH/TjiFMtH2l1a4d9O/viGiBApDs/PPPP6SmplKuXDmb/eXKlSM6OjrDY8aNG4e/v791CwkJyYtQRURECoaAAJg/H3x90xVtoAknCcGciSc9AzdOUIENNDF3lCkDX3xhJlEOku+TnZwYOXIkcXFx1u3EiRPODklERCR/ufVWWLkS/P1tdkcRlKXDrfW+/BKueWCR2/J9slO6dGnc3d05ffq0zf7Tp08TGBiY4THe3t74+fnZbCIiIpJNd9wBmzaZkwX+K4ioLB0aRJT56qq9nXW1clG+T3a8vLxo2LAhq1atsu5LS0tj1apVhIWFOTEyERGRQqBmTdi4EV55BdzcaMIGynMCCxnPkmwhjRCO0+TmKPjggzwJMd8nOwDPP/88n3/+OTNnzmTv3r0MGDCACxcu0LdvX2eHJiIiUvB5ecFbb8H69bhXrsgkngNIl/Bc+X2i2/O4f/d1hn1+HKFAJDuPPPII7733HqNGjaJBgwZERkayfPnydJ2WRURExIHuugsiI+ncx5/5dOUmbJeEKM9J5tOVzq/VMRcGzSMWwzDSjw0rZOLj4/H39ycuLk79d0RERHLDggWkPvEUG87VJooggoiiCRtwb3Qb/PqrubL6Dcrq97fHDZ9JRERE5FqdO+N+xx00ffxxWDHH3OfjY86YnAuJTnYUiNdYIiIi4oKCg2HZMvj4YyhSBD78EKpVy/Mw9GRHREREHMdigUGDzCHmFSo4JQQlOyIiIuJ4FSs67dR6jSUiIiIFmpIdERERKdCU7IiIiEiBpmRHRERECjQlOyIiIlKgKdkRERGRAk1Dz4ErK2bEx8c7ORIRERHJqivf29db+UrJDnD+/HkAQkJCnByJiIiIZNf58+fx9/e3W66FQIG0tDROnTpF8eLFsVgsudZufHw8ISEhnDhxotAuMKp7oHsAugege1DYrx90DyD374FhGJw/f57g4GDc3Oz3zNGTHcDNzY3y5cs7rH0/P79C+8G+QvdA9wB0D0D3oLBfP+geQO7eg8ye6FyhDsoiIiJSoCnZERERkQJNyY4DeXt7M3r0aLy9vZ0ditPoHugegO4B6B4U9usH3QNw3j1QB2UREREp0PRkR0RERAo0JTsiIiJSoCnZERERkQJNyY6IiIgUaEp2HGjKlClUqlSJIkWK0LhxY7Zs2eLskBxizJgxWCwWm61mzZrW8qSkJAYOHEipUqXw9fWlS5cunD592okR37j169fTvn17goODsVgs/PDDDzblhmEwatQogoKCKFq0KC1atODgwYM2dc6ePUuPHj3w8/MjICCAfv36kZCQkIdXcWOudw/69OmT7nPRqlUrmzr5+R6MGzeO22+/neLFi1O2bFk6duzI/v37bepk5bN//Phx2rZti4+PD2XLlmX48OGkpKTk5aXkWFbuQdOmTdN9Dp5++mmbOvn5HkydOpV69epZJ8kLCwtj2bJl1vKC/hmA698DV/gMKNlxkP/97388//zzjB49mt9//5369evTsmVLYmJinB2aQ9SuXZuoqCjr9uuvv1rLhg4dyqJFi5g3bx7r1q3j1KlTdO7c2YnR3rgLFy5Qv359pkyZkmH5hAkT+Oijj5g2bRqbN2+mWLFitGzZkqSkJGudHj16sHv3blauXMnixYtZv349Tz75ZF5dwg273j0AaNWqlc3nYvbs2Tbl+fkerFu3joEDB7Jp0yZWrlzJ5cuXeeCBB7hw4YK1zvU++6mpqbRt25ZLly6xceNGZs6cyYwZMxg1apQzLinbsnIPAPr372/zOZgwYYK1LL/fg/LlyzN+/HgiIiLYtm0b9913Hx06dGD37t1Awf8MwPXvAbjAZ8AQh2jUqJExcOBA6++pqalGcHCwMW7cOCdG5RijR4826tevn2FZbGys4enpacybN8+6b+/evQZghIeH51GEjgUYCxcutP6elpZmBAYGGu+++651X2xsrOHt7W3Mnj3bMAzD2LNnjwEYW7dutdZZtmyZYbFYjL/++ivPYs8t194DwzCM3r17Gx06dLB7TEG7BzExMQZgrFu3zjCMrH32ly5dari5uRnR0dHWOlOnTjX8/PyM5OTkvL2AXHDtPTAMw7j33nuN5557zu4xBe0eGIZhlChRwvjiiy8K5Wfgiiv3wDBc4zOgJzsOcOnSJSIiImjRooV1n5ubGy1atCA8PNyJkTnOwYMHCQ4OpkqVKvTo0YPjx48DEBERweXLl23uRc2aNalQoUKBvRdHjhwhOjra5pr9/f1p3Lix9ZrDw8MJCAjgtttus9Zp0aIFbm5ubN68Oc9jdpS1a9dStmxZatSowYABAzhz5oy1rKDdg7i4OABKliwJZO2zHx4eTt26dSlXrpy1TsuWLYmPj7f5V3F+ce09uOK7776jdOnS1KlTh5EjR5KYmGgtK0j3IDU1lTlz5nDhwgXCwsIK5Wfg2ntwhbM/A1oI1AH++ecfUlNTbf7DAZQrV459+/Y5KSrHady4MTNmzKBGjRpERUXx+uuv06RJE3bt2kV0dDReXl4EBATYHFOuXDmio6OdE7CDXbmujP77XymLjo6mbNmyNuUeHh6ULFmywNyXVq1a0blzZypXrszhw4d5+eWXad26NeHh4bi7uxeoe5CWlsaQIUO46667qFOnDkCWPvvR0dEZfk6ulOUnGd0DgEcffZSKFSsSHBzMjh07GDFiBPv372fBggVAwbgHO3fuJCwsjKSkJHx9fVm4cCGhoaFERkYWms+AvXsArvEZULIjN6x169bWP9erV4/GjRtTsWJF5s6dS9GiRZ0YmThTt27drH+uW7cu9erV4+abb2bt2rU0b97ciZHlvoEDB7Jr1y6bvmqFjb17cHUfrLp16xIUFETz5s05fPgwN998c16H6RA1atQgMjKSuLg45s+fT+/evVm3bp2zw8pT9u5BaGioS3wG9BrLAUqXLo27u3u6HvenT58mMDDQSVHlnYCAAKpXr86hQ4cIDAzk0qVLxMbG2tQpyPfiynVl9t8/MDAwXWf1lJQUzp49W2DvS5UqVShdujSHDh0CCs49GDRoEIsXL2bNmjWUL1/euj8rn/3AwMAMPydXyvILe/cgI40bNwaw+Rzk93vg5eVF1apVadiwIePGjaN+/fpMmjSpUH0G7N2DjDjjM6BkxwG8vLxo2LAhq1atsu5LS0tj1apVNu8wC6qEhAQOHz5MUFAQDRs2xNPT0+Ze7N+/n+PHjxfYe1G5cmUCAwNtrjk+Pp7NmzdbrzksLIzY2FgiIiKsdVavXk1aWpr1L4KC5uTJk5w5c4agoCAg/98DwzAYNGgQCxcuZPXq1VSuXNmmPCuf/bCwMHbu3GmT9K1cuRI/Pz/rKwBXdr17kJHIyEgAm89Bfr4HGUlLSyM5OblQfAbsuXIPMuKUz0CudHOWdObMmWN4e3sbM2bMMPbs2WM8+eSTRkBAgE1v84Ji2LBhxtq1a40jR44Yv/32m9GiRQujdOnSRkxMjGEYhvH0008bFSpUMFavXm1s27bNCAsLM8LCwpwc9Y05f/68sX37dmP79u0GYHzwwQfG9u3bjWPHjhmGYRjjx483AgICjB9//NHYsWOH0aFDB6Ny5crGxYsXrW20atXKuOWWW4zNmzcbv/76q1GtWjWje/fuzrqkbMvsHpw/f9544YUXjPDwcOPIkSPGL7/8Ytx6661GtWrVjKSkJGsb+fkeDBgwwPD39zfWrl1rREVFWbfExERrnet99lNSUow6deoYDzzwgBEZGWksX77cKFOmjDFy5EhnXFK2Xe8eHDp0yHjjjTeMbdu2GUeOHDF+/PFHo0qVKsY999xjbSO/34OXXnrJWLdunXHkyBFjx44dxksvvWRYLBbj559/Ngyj4H8GDCPze+AqnwElOw708ccfGxUqVDC8vLyMRo0aGZs2bXJ2SA7xyCOPGEFBQYaXl5dx0003GY888ohx6NAha/nFixeNZ555xihRooTh4+NjdOrUyYiKinJixDduzZo1BpBu6927t2EY5vDz1157zShXrpzh7e1tNG/e3Ni/f79NG2fOnDG6d+9u+Pr6Gn5+fkbfvn2N8+fPO+Fqciaze5CYmGg88MADRpkyZQxPT0+jYsWKRv/+/dMl+/n5HmR07YDx1VdfWetk5bN/9OhRo3Xr1kbRokWN0qVLG8OGDTMuX76cx1eTM9e7B8ePHzfuueceo2TJkoa3t7dRtWpVY/jw4UZcXJxNO/n5Hjz++ONGxYoVDS8vL6NMmTJG8+bNrYmOYRT8z4BhZH4PXOUzYDEMw8idZ0QiIiIirkd9dkRERKRAU7IjIiIiBZqSHRERESnQlOyIiIhIgaZkR0RERAo0JTsiIiJSoCnZERERkQJNyY6IiIgUaEp2RKRAqVSpEhaLBYvFkm4Bxuxq2rSpta0r6/mISP6jZEdEXE5qaip33nknnTt3ttkfFxdHSEgIr7zySqbHv/HGG0RFReHv739DcSxYsIAtW7bcUBsi4nxKdkTE5bi7uzNjxgyWL1/Od999Z90/ePBgSpYsyejRozM9vnjx4gQGBmKxWG4ojpIlS1KmTJkbakNEnE/Jjoi4pOrVqzN+/HgGDx5MVFQUP/74I3PmzOHrr7/Gy8srW23NmDGDgIAAFi9eTI0aNfDx8aFr164kJiYyc+ZMKlWqRIkSJXj22WdJTU110BWJiLN4ODsAERF7Bg8ezMKFC+nZsyc7d+5k1KhR1K9fP0dtJSYm8tFHHzFnzhzOnz9P586d6dSpEwEBASxdupQ///yTLl26cNddd/HII4/k8pWIiDMp2RERl2WxWJg6dSq1atWibt26vPTSSzlu6/Lly0ydOpWbb74ZgK5du/LNN99w+vRpfH19CQ0NpVmzZqxZs0bJjkgBo9dYIuLSpk+fjo+PD0eOHOHkyZM5bsfHx8ea6ACUK1eOSpUq4evra7MvJibmhuIVEdejZEdEXNbGjRv58MMPWbx4MY0aNaJfv34YhpGjtjw9PW1+t1gsGe5LS0vLcbwi4pqU7IiIS0pMTKRPnz4MGDCAZs2a8eWXX7JlyxamTZvm7NBEJJ9RsiMiLmnkyJEYhsH48eMBc7LA9957jxdffJGjR486NzgRyVeU7IiIy1m3bh1Tpkzhq6++wsfHx7r/qaee4s4777yh11kiUvhYDP2NISIFSKVKlRgyZAhDhgzJlfaOHj1K5cqV2b59Ow0aNMiVNkUkb+nJjogUOCNGjMDX15e4uLgbaqd169bUrl07l6ISEWfRkx0RKVCOHTvG5cuXAahSpQpubjn/N91ff/3FxYsXAahQoUK2Z24WEdegZEdEREQKNL3GEhERkQJNyY6IiIgUaEp2REREpEBTsiMiIiIFmpIdERERKdCU7IiIiEiBpmRHRERECjQlOyIiIlKg/R9gBbWQG6TkkwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p1 = path_from_RT90(df, east_col = \"East\", north_col = \"North\", path_simplify = False)\n",
    "p2 = path_from_RT90(df, east_col = \"East\", north_col = \"North\", path_simplify = True)\n",
    "\n",
    "p1.plot(color='r', linestyle='-', linewidth = 10, label = \"Full path\")\n",
    "p2.plot(color='b', linestyle='-', marker = 'o', label = \"Reduced path\")\n",
    "\n",
    "plt.xlabel(\"X [m]\")\n",
    "plt.ylabel(\"Y [m]\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da8620fa",
   "metadata": {},
   "source": [
    "## Landscape\n",
    "\n",
    "The [Landscape](/API/landscape/landscape) is the starting point for the model. It is essentially an empty data structure which represents a cuboid space\n",
    "\n",
    "$$\n",
    "C = [0, x_{\\max}] \\times [0, y_{\\max}] \\times [0, z_{\\max}] \\subset \\mathbb{R}^3\n",
    "$$\n",
    "\n",
    "where $x_{\\max}, y_{\\max}, z_{\\max}$ are defined by the user upon creating the landscape object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "24f1159d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_landscape = Landscape(size = (500, 500, 500), scale = 'meters')\n",
    "fig, ax = my_landscape.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a285a2b6",
   "metadata": {},
   "source": [
    "Not much to see here, but we created the backbone of our simulation now."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "035b4f42",
   "metadata": {},
   "source": [
    "## Point sources\n",
    "\n",
    "A [PointSource](/API/sources/point_source) can be added to `my_landscape` in the following way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "91019da5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[PointSource(name=Source 2, pos=(100, 100, 0), isotope=Cs137, A=100 MBq)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cs137 = Isotope(name = \"Cs137\", E = 662.66, b = 0.851)\n",
    "my_source = PointSource(x = 100, y = 100, z = 0, activity = 100, isotope = cs137)\n",
    "my_landscape.add_sources(my_source)\n",
    "\n",
    "my_landscape.sources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7913fe1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>,\n",
       " <Axes: xlabel='X [meters]', ylabel='Y [meters]'>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_landscape.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "df4715c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>,\n",
       " <Axes: xlabel='X [meters]', ylabel='Y [meters]'>)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_landscape.set_path(p2)\n",
    "my_landscape.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17fec32f",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}