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": 5,
   "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"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8431d39b",
   "metadata": {},
   "source": [
    "## Loading a file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": 7,
   "id": "2ec97553",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2026-01-28 13:31:03,130 - 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/cnL6WgsAzhFcIaJ0GFuthnefi0vkrmZw1TjYLqnQuU5iVvW12vPGx4etsnP1cmQn5+ZSdarB/Xrm5s6XItIAZcvkp1x48axYMEC9u3bR9GiRbnzzjt55513qFHjvyUFmjZtyrp162yOe+qpp5g2bZr19+PHjzNgwADWrFmDr68vvXv3Zty4cXhksYOpkp28tWCBufLDyZP/7Qsp+jcTLz6Vq8PO07DwFzfZTYQu4W332CJctCZC127BnMpgLJkLCgoyk566dc2RZ9Wrmz/LlNErNBEpEPJFstOqVSu6devG7bffTkpKCi+//DK7du1iz549FCtmvppo2rQp1atX54033rAe5+PjY72o1NRUGjRoQGBgIO+++y5RUVH06tWL/v37M3bs2CzFoWQn76WmmuuHRkWZ38lNmoB7xBaYMMFc9fyyA0deAam4cYKQDBOhP6lCCp52j/Xhgs2ToKv/HEi06ydC/v5m4lOzJtxyCzRsaP4sXtzZkYmIZEu+SHau9ffff1O2bFnWrVvHPffcA5jJToMGDZg4cWKGxyxbtox27dpx6tQpypUrB8C0adMYMWIEf//9N15eXumOSU5OJjk52fp7fHw8ISEhSnZcxZkz8P33MGsWXPNULy+k4M4xKlr7BF2dCB2hMqmZ9Ov35XyGHaWrcZAy/O26iZDFYiZADRuaQ/A7dTJfi4mIuLB8mewcOnSIatWqsXPnTurUqQOYyc7u3bsxDIPAwEDat2/Pa6+9ho+PDwCjRo3ip59+IjIy0trOkSNHqFKlCr///ju33HJLuvOMGTOG119/Pd1+JTsu6MQJmDPHTHyu+m/sLJfx4CiVMnwidIyKpGG/E7EfcemOupIYleKM6yVCTZvC6NHmTxERF5Tvkp20tDQefPBBYmNj+fXXX637P/vsMypWrEhwcDA7duxgxIgRNGrUiAULzMnpnnzySY4dO8aKFSusxyQmJlKsWDGWLl1K69at051LT3byqQMHYN48mDsXduxwdjTpJOPFESpnmAidIAQDN7vHBnAuw6dB1ThICWLz7iIy8uCD5uvFq/rSiYi4gnyX7AwYMIBly5bx66+/Ur58ebv1Vq9eTfPmzTl06BA333xzjpKda6nPTj60b5+Z+Hz/vZn4uMbH2K4kvPmTKhmmMycJyfTYUvyTYRJUlUP4E58r8aXixgaa2F+F3sMDnn7afNKjNcVExEXkq0kFBw0axOLFi1m/fn2miQ5A48aNAazJTmBgIFu2bLGpc/r0aQACAwMdE7A4X82a8Npr5nb+vPnUJybG3E6f/u/n3r3m66/UHEwsmIuKkEwoewllb7qyRIpymJszTISiCOYMpTlDaTYRlu7YMsTYfSLky4UsxbaATjzHJJukK90q9CkpMHkyfP01vPUWDBxozjItIpIPODXZMQyDwYMHs3DhQtauXUvlypWve8yVvjlBQeZsvGFhYbz99tvExMRQtmxZAFauXImfnx+hoaEOi11cSPHiZsdaexISYMsW+O03c9u40UyQXIQPF6nLLuqyK11ZAsWsnaSv7Sx9mkD+pix/U5aN3JXu2ECi7D4R8uEiYCY6XZmfbkahv7iJrsxPP+9RfDw8+6z5KnH6dKhWLTdvhYiIQzj1NdYzzzzDrFmz+PHHH23m1vH396do0aIcPnyYWbNm0aZNG0qVKsWOHTsYOnQo5cuXt869c2XoeXBwMBMmTCA6OpqePXvyxBNPaOi5ZOzyZdi8GZYvN7eICGdHlCPxFE+XAF3Z/iHzCQWD+YuqHCSC27hAMXK0Cn2RIvD22+akSZrdWUScIF/02bHYmdjsq6++ok+fPpw4cYLHHnuMXbt2ceHCBUJCQujUqROvvvqqzUUdO3aMAQMGsHbtWooVK0bv3r0ZP368JhWUrImJgZ9/hrVrYfdu8/VXXJy5Ofn1V07F4m/n5VY1zlEyW22toSlNyWQKgLAw+OordWAWkTyXL5IdV6FkRzJkGJCY+F/ic/48XLiQfktIgKQkSE62/Rkba742+/tvZ1+JjbOU4CDV+JpefMLA69afRXe6MyfzSj4+MGkS9Oun2ZlFJM/kqw7KIi7JYoFixcwtODhnbRgG7NoFq1bB6tXm0yMn9xcqyTkas4WLFM1SsuNN0vUbTUyE/v3N14KffWYuaCoi4iL0ZAc92ZE8lJICf/4JR4/C2bPmbNFX/zx71kwcrn1KdPXP5GS4dOmGQ0nFjUoc5S9usjMHkAFY8Occ7/AS/fk8a4ujli8P334L9957wzGKiGRGr7GyQcmO5DtpaWbCk5xsJko7d8Iff5hbZKSZUGXBldFYgE3CYyENA6jMUY5QBYDGbGIaT9OAP7IWY79+MHYs/DtKUkQktynZyQYlO1LgxMebEy8eOGBu+/f/9+fERJuqGc2zE8JxJjKEB/mJT3iGV3mL8/jhRirPMYnXGU1xEq4fh78/vPkmDBhgTkwoIpKLlOxkg5IdKTTS0uDYMXO4/ZVt5crrzqB8iiCG8iFzeQSAmzj576SDC7K2plfdujBlirm8vYhILlGykw1KdqRQMwz45htzzpwDBzKtuoIHeIZP+JObAWjDEiYziMocvf55LBYYMcKcgVnz8ohILsjq97fmexcp7CwW6NXLHDX20UdQqpTdqi35mV3U4TXewJNLLKUtoexhLCO5hGfm5zEMGD8eOnVy+og0ESlclOyIiMnTEwYPhkOH4Kmn7FYrShJvMJqd1OU+VpFEUV5hLA2IZC1ZGIG1aBHceac5Ik1EJA8o2RERWwEBMG0a/PILVKpkt1oNDvALLfiWHpTlNHsJpRlr6c0MYq6zXAW7dsHtt8Ovv+Zq6CIiGVGyIyIZa97cHNI+0P7EgxagB7PYR02eZioW0via3tRkH5/Rn7TMui//8495jjnXmZ1ZROQGKdkREft8fWHyZHMG6JtuslutBLFM5RnCCaMB2zlHSZ7iM+7mV/6gnv32L12C7t1hwgSzT4+IiAMo2RGR67vvPnPCwo4dM63WmC1s5XY+ZAi+nCecO2lIBMN4jwSK2T9wxAgYNCjfLrwqIq5NyY6IZE2pUrBgAUydCkWK2K3mQSpDmMQ+atKVeaTiwQcMoxZ7WUhH+wtOfPIJdO6cbtJDEZEbpWRHRLLOYoGnnzYnI2zUKNOqN3GKeTzMUlpTmT85SQidWUh7FnGEShkf9NNP0KKFuUaYiEguUbIjItkXGgrh4fDFF1C6dKZVW7OcXdThFd7Ck0ssoR212c14RmQ8N094ONx9N5w44aDgRaSwUbIjIjnj5mYu9nnggDk/j5v9v058uMhbvMYf1Kcpa7iIDyMZzy1sZz0ZLCGxd685F8+ePQ68ABEpLJTsiMiNKVHCnHl5+3aoXTvTqrXYx2ru42t6UoYY9lCbe1lPX6bzN9c8ITp50nxVNmmSOi6LyA1RsiMiuaNePdi4Edq2zbSaBejJt+yjJk8xDYAZ9KUm+/iCfrZz81y4AEOGwF13mRMRiojkgJIdEck9fn7w44/wwgvXrVqSc0xjAOHcQX0iOUsp+vMFTdjATurYVt68GW69FYYNgyNHHBS8iBRUSnZEJHe5u8O778L06eDhcd3qd7CZbdzGBwylGAls5C5uYTvDmWA7N8/ly/DBB3DzzdC+PSxfDmlpDrwQESkolOyIiGP07QtLl0Lx4tet6kEqQ5nIXmrRme9JxYP3GE4oe/iRB20rGwYsXgytW0ONGuYMz8nJDroIESkIlOyIiOPcfz9s2ADBwVmqHsJJvqcri2lLJY5wggp05Ece5EeOUSH9AYcOmSPB6tSB9etzOXgRKSiU7IiIY9WvD5s2mQlJFrVlKbupzUjG4sklFvEgoexhAsO5TAavxg4dgnvvNROfhIRcDF5ECgIlOyLieCEh5hOee+7J8iE+XGQsrxBJA+5hHYkUYwQTuIXtbODujA+aPNkcFbZ6dS4FLiIFgZIdEckbAQGwYgV06pStw0LZy1qaMoPelOZvdlOHe9jA43zJP5RKf8CRI9C8OQwcqHW2RARQsiMiealIEZg3D558MluHWYDefM0+atKfzwD4isepwX6m09d2bp4rPvkEbrkFtm7NhcBFJD9TsiMiecvdHaZNg9dfz/ahpTjLZzzFb9xJXXZwllL0Yzr3so5dZDB784ED5rITb70FKSm5ELyI5EdKdkQk71ksMGqUOTS9fPlsH34n4UTQkPcYRjES+JUm3MJ2RjCeC/jYVk5JgddeM/sL/flnLl2AiOQnSnZExHlat4bdu+GZZ7J9qCcpDOMD9hBKRxaSgicTGEEoe/iJ9ukPCA+H226DlStzIXARyU+U7IiIc/n5wZQp5mitGjWyfXgFTrCQzvxEeypylONUpAM/0ZGFHCfEtvK5c9CqFbz3njk5oYgUCkp2RMQ13H03REbCG29kadbla7VnMbupzUuMw4PL/EhHarGXd3nBdm6etDQYPhzuuAP278+9+EXEZSnZERHXUaSI2b/mxAmYNAmqV8/W4cVIZBwvE0kDmrCeRIrxIu9yK7/zG3faVt6yBWrWhKZN4csvITY21y5DRFyLxTD0LDc+Ph5/f3/i4uLw8/NzdjgickVaGqxaZb7mWrQoWwt/GsBMevMC73GG0gD04wveYQSlOJv+AG9vsw9R27bQpk2Wl7gQEefJ6ve3kh2U7IjkC3v2wOOPw+bN2TrsDCUZwTt8yRMAlOIf3uMFejMzo9l5/tOgwX+JT+PG5pB5EXEpWf3+1mssEckfQkPht9/MzsVFimT5sFKc5Qv68yt3UYednKE0fZnBvaxjN6H2D4yMhLffhrvugptvhvffh4sXb/w6RCTPOTXZGTduHLfffjvFixenbNmydOzYkf3XdBhMSkpi4MCBlCpVCl9fX7p06cLp06dt6hw/fpy2bdvi4+ND2bJlGT58OCmaQEyk4HF3h2HD4I8/zCQkG+5iI79zKxMYjg8X2MA9NCCSkYwlkaKZH3zsGLzwAtSuDYsX38AFiIgzODXZWbduHQMHDmTTpk2sXLmSy5cv88ADD3DhwgVrnaFDh7Jo0SLmzZvHunXrOHXqFJ07d7aWp6am0rZtWy5dusTGjRuZOXMmM2bMYNSoUc64JBHJC9Wrw7p1MG4ceHpm+TBPUhjOe+whlA78QAqejGckoexhMW2v38CRI9C+PXTsaP5ZRPIHw4XExMQYgLFu3TrDMAwjNjbW8PT0NObNm2ets3fvXgMwwsPDDcMwjKVLlxpubm5GdHS0tc7UqVMNPz8/Izk5OUvnjYuLMwAjLi4uF69GRPJERIRh1KplGObMOdnafqS9UYGj1l2d+N44Tvmst9G8uWF8/LFh7NljGGlpzr4TIoVOVr+/XarPTlxcHAAlS5YEICIigsuXL9OiRQtrnZo1a1KhQgXCw8MBCA8Pp27dupQrV85ap2XLlsTHx7N79+4Mz5OcnEx8fLzNJiL51K23QkQEDB6c7UMfZBF7COVF3sGDyyykM7XYy/s8bzs3jz2rVpnnDQ01l73o2RO+/x6Sk3NwISLiKC6T7KSlpTFkyBDuuusu6tSpA0B0dDReXl4EBATY1C1XrhzR0dHWOlcnOlfKr5RlZNy4cfj7+1u3kJCQDOuJSD5RtCh89BHMnQs+Ptevf5ViJPIOL/E7t3IXv3IBX17gfW5jG+HckfWGTp2Cb7+Frl2hcmWYOBESE7N3HSLiEC6T7AwcOJBdu3YxZ84ch59r5MiRxMXFWbcTJ044/Jwikgceegg2boRKlbJ9aF12sZ57+JLHKckZdlCfOwnnST7lLCWy11hUFAwdaiY9774LCQnZjkdEco9LJDuDBg1i8eLFrFmzhvJXrYAcGBjIpUuXiL1mZtPTp08TGBhorXPt6Kwrv1+pcy1vb2/8/PxsNhEpIOrXh23b4L77sn2oGwaP8xX7qcHjfAnA5zxJDfbzNT3J9qRkMTHw4otm8jVuHFw1+EJE8k6Wkp1r+7dkZcsKwzAYNGgQCxcuZPXq1VSuXNmmvGHDhnh6erJq1Srrvv3793P8+HHCwsIACAsLY+fOncTExFjrrFy5Ej8/P0JDM5lDQ0QKrlKlYMUK86lKDv4xU5ozfMkTrKcJtdnFP5ShN1/TjDXspWb24zlzBl5+GapWhU8/hcuXs9+GiORYlmZQdnNzw2LJdK5R20YtFg4cOECVKlUyrffMM88wa9YsfvzxR2pctdqxv78/RYua814MGDCApUuXMmPGDPz8/Bj8byfEjRs3AubQ8wYNGhAcHMyECROIjo6mZ8+ePPHEE4wdOzZL8WoGZZEC7O+/4ZNPzP40hw5l+/BLePIhQ3md0VzEB08u8QLv8Spv4UMOJxmsXh3GjoXOnSEbf7eKiK1cXS7Czc2N77//3jpKKjOGYdCmTRt27dp13WTHXgL11Vdf0adPH8CcVHDYsGHMnj2b5ORkWrZsySeffGLziurYsWMMGDCAtWvXUqxYMXr37s348ePx8MjCaAqU7IgUCoZhLv757bcwZw7880+2Dj9KRQbzMYtpD0AljjCFgbRhWc5jatzY7Mh8RzY6QouIVa4mO5UrV2bbtm2UKlUqSyevU6cOy5YtyzejnJTsiBQyly/D8uWwYAEsXWr2rckCA/iRDjzLR5ygAgBdmM9EhlCev3IWi8UCzz8Pb72VrWUwREQLgWaLkh2RQiwtDX7/HZYsMROfrVvNp0CZSKAYrzOaDxlKKh74cp43GMVgPsaD1JzFUasWfP013HZbzo4XKYS0EKiISFa4uZkJxujR5orqBw6YK51nwpcLvMuL/M6thLGRBIrzPB9yG9vYROOcxbF3r/k6a8wYdWAWyWU5erKzdetW1qxZQ0xMDGlpaTZlH3zwQa4Fl1f0ZEdEbBgG/PADPPccXGcerjQsTOdxXmQC5yiJhTSe5DPGMZISxObs/LVrw8cfQ7NmOTtepJBw2GussWPH8uqrr1KjRg3KlStn08nYYrGwevXqnEftJEp2RCRDFy7A+PEwZQqcO5dp1b8pzYtMYAZ9AShDDB/wPD34jhyPt3roIXjvPahQIactiBRoDkt2ypUrxzvvvGMdLVUQKNkRkUwlJpqdmX/+2VwP69Qpu1XXcQ8DmMpezHm+mrGaT3iGmuzP2bmLFoWXXoLhw80/i4iVw/rsuLm5cdddd91QcCIi+YqPDzz2mNmB+ORJ2LfPfNrTqRN4etpUvZf1RNKAcbxEURJZw33UYwev8iYXycFoq4sXzf5EoaHw44/X7TwtIullO9kZOnQoU6ZMcUQsIiKuz2KBGjXgmWfMpz2HDpl/9vKyVvHiMi/xDrupTRuWcBkv3uZV6rCL5bTM2XmPHoWOHaF1a9ifw6dEIoVUtl9jpaWl0bZtWw4cOEBoaCie1/yrZsGCBbkaYF7QaywRuWF//QUTJsBnn0FSknW3ASykE88xiZOYc491ZR4TGcJN2H8dlilPT3Oh0ddeA1/fXAheJH9y2GusZ599ljVr1lC9enVKlSqFv7+/zSYiUijddBNMmmQ+6enf3xzSDliAzixkD6E8z/u4k8J8HqIm+5jEs6Tgnv1zXb5sJlYNGkBkZG5ehUiBlO0nO8WLF2fOnDm0bdvWUTHlOT3ZEZFct3evufjnDz/Y7P6DejzNNDZhLmbcgO18ylM0YmvOzlO0KHz1FTzyyA0GLJL/OOzJTsmSJbn55ptvKDgRkQKvVi1YuBB++w1uvdW6uz47+I27+JQnKcFZIrmFO9jEM0whlhw8Hb94Ebp1M0dspeZw9maRAi7byc6YMWMYPXo0iYmJjohHRKRgufNO2LQJXn8d/l2c2A2DJ/mcfdSkFzMxcGMqz1CD/XzHo+RovNU770D79tedD0ikMMr2a6xbbrmFw4cPYxgGlSpVStdB+ffff8/VAPOCXmOJSJ74/Xfo1Qt277bZvYamPMMn7KMWAPexik94hhocyP45KlY0V3XXSupSCGT1+9sjuw137NjxRuISESm8br0VIiJg1Ch4/33ra6dmrOUP6vMeL/Amr7Ga5tRjByN4h5GMoyhJ12n4KseOQZMm8Pbb8MIL1o7SIoWZVj1HT3ZExAl27oRnn4W1a212/0llBjGZZZiLkd7MIaYwkJb8nP1ztGoFM2dC2bK5ELCI69Gq5yIirqxuXVi9GubOhZAQ6+4qHGEJbZlPF4L5i8NUpRUreIQ5nCIoe+dYvtxcVHTWLM28LIValpKdkiVL8s8//2S50QoVKnDs2LEcByUiUihYLOZin3v3wquvgre3uRvowgL2UZMhfIgbqczlEWqyj48YTGp2/p36zz/Qowe0awfHjzvmOkRcXJZeY7m5uTFz5swsTxrYvXt3du7cSZUqVW44wLyg11gi4hL+/NOcGfmnn2x2b6cBTzONLTQG4FYimMbT3M627LVfrBiMGwcDB6ovjxQIubrquVsO/qc4dOiQkh0RkZxYvhyeew4O/DcaKxU3Pqc/IxlHLCWwkMYzfMJbvEoAcdlr/4EHYPZsKFkylwMXyVu52mcnLS0t21t+SXRERFxOq1ZmB+a33rI+gXEnjaf5lH3U5DG+wcCNKQyiJvuYTbfszc3z889w++3mOUQKAT3HFBFxRV5e8MorsGIFlChh3V2OGL6hF6u4j+rs5zSBPMpsHuBnDlI16+3/+SeEhcH33zsgeBHXomRHRMSVtWgB27ZBnTo2u+9jDTuox5u8ijdJ/ML91GEXYxhNEt5Za/vCBeja1UyqUlIcELyIa1CyIyLi6qpUgfBwMzG5ijeXeJW32U1tWrKcS3jzOmOoy05W0iLr7Y8dC3fdBQcP5nLgIq4hy8nOqVOnHBmHiIhkxtfXnJNn8mTzFddVbuZPltGauTxEEKc4RDUeYCXdmUUUgVlrf8sWaNAAPvtMc/JIgZPlZKd27drMmjXLkbGIiEhmLBZz2PimTVCtmm0R8BDz2UdNnmMibqQyh+7UZB+TGZi1uXkSE+Gpp6BDB/jrL8dcg4gTZDnZefvtt3nqqad46KGHOHv2rCNjEhGRzNxyi7nGVo8e6Yr8OM9EhrKV27mdLcTjz2Am05jNRHBr1tpftAhq1oQPPoDLl3M5eJG8l+Vk55lnnmHHjh2cOXOG0NBQFi1a5Mi4REQkM8WLwzffwNdf24zWuuJWthNOGFN4Bn9iieA2GrGFwXxEHFmYTywhAYYNMxcv3bDBARcgkndytBDo5MmTGTp0KLVq1cLDw3bh9N9//z3XgssrmlRQRPK106fNSQj/978Mi6MpxzDeZxbmk6BAopjIEB5mLpasnqNXL3j3XS0qKi4lV2dQvtqxY8fo27cvu3bt4qmnnkqX7IwePTpnETuRkh0RKRB++gmeecZuf5tV3McApnKQ6gDcz898wjNU5XDW2g8IgLffNvv1uLvnUtAiOeeQZOfzzz9n2LBhtGjRgk8//ZQyZcrkSrDOpmRHRAqM+HgzGZkzJ8PiJLyZwIuM5WWSKYI3SbzMWEbwDt5cyto5GjaEqVPNWZhFnChXl4sAaNWqFSNGjGDy5MksWLCgwCQ6IiIFip8fzJoF77xjjt66RhGSGcWb7KIO9/MzyRRhNG9Ql538QvOsnSMiAho3hgEDzORKxMVlOdlJTU1lx44d9OrVy5HxiIjIjbJY4MUXYelS89VTBqpymBW0ZA6PEEgUB6nO/fxCD74lmnLXP4dhwLRpUK8erFmTu/GL5LIsJzsrV66kfPnyjoxFRERyU6tW5mSB1yw1cYUFeIS57KMmg/kIN1KZRQ9qso9PGJC1uXmOHYP77jM7SCcm5m78IrlEy0WIiBRk1arB1q0wZIjdKv7E8xHPsZnGNGQbcQQwkE8II5zfuSVr5/noI3P+n02bcidukVykZEdEpKArUgQ+/BBWroTgYLvVbiOCzTRmMgPxI46tNOJ2tvIcE4mn+PXPc+CAucbW+PGQlpaLFyByY5TsiIgUFi1awM6d8PDDdqu4k8ZAPmEfNenGbNJw5yOeoyb7mMtDXHf4bloajBxpLjmh2fbFRTg12Vm/fj3t27cnODgYi8XCDz/8YFPep08fLBaLzdaqVSubOmfPnqVHjx74+fkREBBAv379SEhIyMOrEBHJR0qWNIelz5kDQUF2qwURzWwe5WfupyoHiSKYR5hLa5ZxmCrXP8/ixebsy1u35mLwIjnj1GTnwoUL1K9fnylTptit06pVK6Kioqzb7Nmzbcp79OjB7t27WblyJYsXL2b9+vU8+eSTjg5dRCT/sljgkUdg3z4YOjTTCQLv5xd2UpfRjMGLZFbQijrs4i1eIRkvu8cBZuflu+82R22JOFGOlotwBIvFwsKFC+nYsaN1X58+fYiNjU33xOeKvXv3EhoaytatW7ntttsAWL58OW3atOHkyZMEZ/Ju+mqaVFBECrUdO8yZl3/7LdNqB6jGQKbwC/cDUIN9fMIz3EcWhp4/+6y5sKhmXpZclOuTCjrL2rVrKVu2LDVq1GDAgAGcOXPGWhYeHk5AQIA10QFo0aIFbm5ubN682W6bycnJxMfH22wiIoVWvXqwfj189RVkMmFsdQ7yMw8wm26UI5r91KQ5q+nJ15zmOmtmffQRdOxoLjAqksdcOtlp1aoVX3/9NatWreKdd95h3bp1tG7dmtTUVACio6Mpe82idB4eHpQsWZLo6Gi77Y4bNw5/f3/rFhIS4tDrEBFxeW5u0KcP7N9vzoycwezLYM7N043/sY+aDGQyFtL4lp7UZB/TeIq0zJYWXbwYmjSBkycdcgki9rh0stOtWzcefPBB6tatS8eOHVm8eDFbt25l7dq1N9TuyJEjiYuLs24nTpzInYBFRPK7EiXgk09g82a46qn5tQKIYzKD2UxjbiWCWEowgGmEEc52GthvPzLSnI9n7lxzFmaRPODSyc61qlSpQunSpTl06BAAgYGBxMTE2NRJSUnh7NmzBAYG2m3H29sbPz8/m01ERK5y++3mBIETJ5rz9Nirxja20IiPGExx4tlCY25jG0P5gPP4ZnzQP/+YHaS7doXTpx0Tv8hV8lWyc/LkSc6cOUPQv8Mlw8LCiI2NJSIiwlpn9erVpKWl0bhxY2eFKSJSMLi7m8tAREaaC3/aq0Yag5nMPmryCHNIw52JDKUWe5lPF/tz8yxYAKGh5sKlesojDuTUZCchIYHIyEgiIyMBOHLkCJGRkRw/fpyEhASGDx/Opk2bOHr0KKtWraJDhw5UrVqVli1bAlCrVi1atWpF//792bJlC7/99huDBg2iW7duWR6JJSIi11GjBvz6K4wdC56edqsFE8UcurOcltzMIf6iPA8xn7Ys4U8qZ3zQ2bPQowc88QRcuuSgC5BCz3CiNWvWGEC6rXfv3kZiYqLxwAMPGGXKlDE8PT2NihUrGv379zeio6Nt2jhz5ozRvXt3w9fX1/Dz8zP69u1rnD9/PltxxMXFGYARFxeXm5cnIlLwREYaRvXqhmE+i7G7JVLEeI3XDS+SDDCMIiQab/GykYSX/ePatjWMixedfYWSj2T1+9tl5tlxJs2zIyKSDfHx0L+/2cn4OvZTnWf4hNU0B6Ame5nKAJqyLuMDmjeHH3+EYsVyM2IpoArMPDsiIuJi/PzM5SY+/jjT11oANTjAL7TgOx6lLKfZRy2asZZezCSGDOb0WbUKWrUyEyqRXKJkR0REss9igUGDYMMGyGT0K5hz8zzKbPZRkwF8goU0vqEXNdnHZ/RPPzfPr7+ai5b+84/j4pdCRcmOiIjkXOPG5pw8detet2oJYvmEgWziDm7hd85Rkqf4jLv4jT+oZ1t561ZzXa1jxxwUuBQmSnZEROTGVKhgPo1p1SpL1RuxlS00YiLPUZx4NhFGQyIYxnu2c/Ps3w933gk7dzoocCkslOyIiMiN8/ODRYvMBUWzwINUnuMj9lKLh5hLKh58wDBC2cMCOv03N8+pU+YSE2uysNioiB1KdkREJHd4eMCUKfDtt+ayE1lwE6eYyyMspTWV+ZOThNCFBbRnEUeoZFaKizNHaY0cqbl4JEeU7IiISO7q0QN274YOHbJ8SGuWs5vavMqbeHKJJbSjNrsZx0tcwhMMg9TxE1hbeyCz3z3J2rXw75rQIteleXbQPDsiIg5hGOYQ9UGDzJmSs2gfNRjAVNbSDIBa7KE7s/iMpzhJiLVe+fIGkyZZ6Nw51yOXfCKr399KdlCyIyLiUFFR0LJltjoaG8B39OB5PuBvyl61979h6hbSwGJh/nwlPIWVJhUUERHXEBRkdjBu2DDLh1iAx/iOPdSiGAlcm+gAGLiBYTDkiQRSUwr9v9slE0p2RETE8UqVMmdHvvPObB22i7pcwJdrE50rDNw4cc6XDXePNJ8giWRAyY6IiOQNf39YscIcWZVFUQRlrd7mY9CgAYSH5zA4KciU7IiISN7x9YUlS+Dhh7NUPYisPa0JIgpiYqBZsywtUCqFi5IdERHJW97eMHu2OUrrOpqwgfKcMDsjZ8igHFE0YYP5a3IyPPIIjB1rjgYTQcmOiIg4g5sbfPQRvP12ptXcSWMSzwFkkPCYnZYv48kpgm2LXnkFHn9ckxAKoGRHREScxWKBl1+GmTOhSBG71TqzkPl05Sb+stl/E39RnuOcpTStWUYs/rYHzpgBnTsr4RElOyIi4mS9ekFEhNnB2I7OLOQolVhDU2bRnTU05RgV+Y27CeIUu6lDJxaSjJftgVf6B12+7NhrEJemZEdERJwvNBQ2b4aXXjKf+GTAnTSaso7uzKEp63AnjQqcYCltKE48a2lGH2aQdu0w9R9/hO7dlfAUYkp2RETENXh5wbhxsG4dVKyY5cMa8Aff0wUPLjOH7oxkXPpK338Pjz0GKSm5GLDkF0p2RETEtTRpAjt2mB2Ms+h+fmE6Zv0JjGAyA9NXmjsX2rWD+PjcilTyCSU7IiLievz84MsvYdEiCAzM0iE9+Za3eRmAZ/mIhXRMX2nFCrjrLjh2LBeDFVenZEdERFxXu3awaxd065al6iMZx1NMw8CNR5nFRsLSV9q1Cxo3hq1bczlYcVVKdkRExLWVKmVOQvjZZ+DunmlVCzCZQbRjEUkUpT2L2E/19BVPn4Z77zXX65ICT8mOiIjkD/37w7Jl5iuuTHiQyhy6cTtbOEspWrOM05RNX/HiRXjwQfjjDwcFLK5CyY6IiOQf998PGzded7RWMRJZTDuqcJgjVKEtS0igWPqKiYnQsSOcOeOYeMUlKNkREZH8pXZt2LQJatbMtFpZ/mY5rSjN30RwG4/wP1LI4DXY0aPmxIMall5gKdkREZH8JzAQVq+G6hn0x7lKNQ6xmHYUJZGltOUZPiHD5UFXr4anntLSEgWUkh0REcmfgoLMJOXmmzOt1pgtzKEbbqTyOU/yNq9kXHH6dHNY+uHDDghWnEnJjoiI5F833QRr1kDlyplWe5BFTGYQAK/xFjPonXHFbdvg1lvNCQilwFCyIyIi+VtICGzYALfckmm1AUzjpX+XkujP56zggYwrxsfDI4/A4MHqx1NAKNkREZH876abYP16aN8+02pv8wo9+JYUPOnKfLbTwH7lyZPNyQzVjyffU7IjIiIFg68vLFwIQ4bYreKGwXQe5z5WkUBx2rCUY1Sw3+b330PnzpCUlPvxSp5RsiMiIgWHuzt8+CG8/bbdKl5cZgGdqcsOogmiNcs4Swn7bS5ZYj4xunDBAQFLXlCyIyIiBc/IkfDoo3aL/YlnKW0ozwn2EkpHfiAJb/vt/fILtG6thCefUrIjIiIFj8UCn3+eaafl8vzFMlrjTywbuIdefE0aFvttbthg9uFJS3NAwOJISnZERKRg8vGBH36AMmXsVqnDbhbSCU8uMY+HeYH3Mm9z8WJ4883cjVMczqnJzvr162nfvj3BwcFYLBZ++OEHm3LDMBg1ahRBQUEULVqUFi1acPDgQZs6Z8+epUePHvj5+REQEEC/fv1ISEjIw6sQERGXVaGCOfFguXJ2qzRjLTPoA8CHPM+HDMm8zTFjzKRH8g2nJjsXLlygfv36TJkyJcPyCRMm8NFHHzFt2jQ2b95MsWLFaNmyJUlX9Yrv0aMHu3fvZuXKlSxevJj169fz5JNP5tUliIiIq6tTx1xLq1Eju1UeZTbv8CIAw3ifeXTNvM3HHoNDh3IzSnEkw0UAxsKFC62/p6WlGYGBgca7775r3RcbG2t4e3sbs2fPNgzDMPbs2WMAxtatW611li1bZlgsFuOvv/6ye66kpCQjLi7Oup04ccIAjLi4uNy/MBERcQ3JyYbxwguGARluaWAM5GMDDMObi8Z67rZb1wDDqFTJMA4dcvZVFWpxcXFZ+v522T47R44cITo6mhYtWlj3+fv707hxY8LDwwEIDw8nICCA2267zVqnRYsWuLm5sXnzZrttjxs3Dn9/f+sWEhLiuAsRERHX4OUF775rDiUvVSpdsQWYxHN0ZCHJFKEDP7KXTFZWP3oU7r4bdu1yWMiSO1w22YmOjgag3DXvWcuVK2cti46OpmzZsjblHh4elCxZ0lonIyNHjiQuLs66nThxIpejFxERl9WmDfz+e4YrpruTxiweJYyNnKMkrVlGFIH224qOhnvugS1bHBiw3CiXTXYcydvbGz8/P5tNREQKkQoVzOUl6tRJV1SUJH7iQapxgGNUoi1LOI+v/bbOnYPmzZXwuDCXTXYCA81M+vTp0zb7T58+bS0LDAwkJibGpjwlJYWzZ89a64iIiGSoXDlYu9Zc5fwapTnDclpRltNs51YeYh6X8bDfVkKCOctyVJTj4pUcc9lkp3LlygQGBrJq1Srrvvj4eDZv3kxYWBgAYWFhxMbGEhERYa2zevVq0tLSaNy4cZ7HLCIi+UypUrBqFdSqla6oCkdYTDt8uMAKWvEkn2Fk1lZMDPTtq0kHXZBTk52EhAQiIyOJjIwEzE7JkZGRHD9+HIvFwpAhQ3jrrbf46aef2LlzJ7169SI4OJiOHTsCUKtWLVq1akX//v3ZsmULv/32G4MGDaJbt24EBwc778JERCT/CAgwFxAtXjxd0e1sYy4P40YqM+jLGMZk3taKFeZq6eJa8mh0WIbWrFljAOm23r17G4ZhDj9/7bXXjHLlyhne3t5G8+bNjf3799u0cebMGaN79+6Gr6+v4efnZ/Tt29c4f/58tuLI6tA1EREpwBYutDvM/FP6W3/9nH6ZD0n39jaMHTucfTWFQla/vy2GYWT6VK4wiI+Px9/fn7i4OHVWFhEpzF591e6K6a/xBm/xGu6k8BMP0oZl9tsJCoLly6FePQcFKpD172+X7bMjIiKS515/3VzsMwNvMIrezCAVDx5iHttoaL+dqChzSPq6dQ4KVLJDyY6IiMgV7u7wzTfQq1e6IgvwOf25n59JpBhtWcKfVLbfVlwctGwJCxY4Ll7JEiU7IiIiV/PwgK++gsGD0xV5ksJ8utKA7cRQjtYs4x/Sz8ZslZwMDz2khMfJlOyIiIhcy80NJk2CUaPSFflxniW0pQLHOEANHuQnLlLEfltpadCjB/zxhwMDlswo2REREcmIxWL24enZM11RMFEsozUBnCOcO+nBd6Rm9pWalGQ+4YmPd2DAYo+SHRERkcxMngyV0/fNCWUvP9IBL5JZSGeGMDHzSQcPHoQnnjAHqEueUrIjIiKSGT8/s9OyW/qvzHvYwDeYT34mM5j3GZZ5W/PmadJBJ1CyIyIicj133QVjxmRY9DDz+IChAAznPebwSOZtDRkCs2blbnySKSU7IiIiWfHqq+baVxkYykSG8CEAvZnJWu61305amtkPaO5cR0QpGVCyIyIikhUWC3zxBTz7bIbF7zOMrszjEt505Ad2Udt+W2lp8Oij8P33DgpWrqZkR0REJKvc3GDiRBg3Ln0RBt/Qk7vZQBwBtGYZf5HJotSpqeZszUuXOi5eAZTsiIiIZI/FAi+9BF9+ma7TchGS+ZEO1GQvJwmhDUuJI5M1F1NS4OGHITLSsTEXckp2REREcuLxx2Hs2HS7S3KOZbQmkCh2UJ8ufM8lPO23c+ECtG0LJ086MNjCTcmOiIhITg0fbiYq16jEMZbQFl/Os4oW9OPLzOfgOXUK2reH8+cdFmphpmRHREQkp9zcYOZMqFAhXdGtbGc+XXEnhW/pyau8lXlbkZFmH56UFMfEWogp2REREbkRpUqZw8i9vdMVteRnPqc/AGN5hWk8lXlbS5fC009rluVcpmRHRETkRjVuDHPmmCumX6MvM3gdc0HRgUzhJ9pn3taXX5prckmuUbIjIiKSGzp2hNmzwd09XdFrvEk/viANd7oxh800yryt11+Hzz5zTJyFkJIdERGR3NK1K3z3Xboh6RZgKgNozVIu4kM7FnOImzNva8AAWLLEcbEWIkp2REREctMjj8DXX5vz8VzFkxTm8jC3EsE/lKEVy/mb0vbbSUuDxx6Do0cdG28hoGRHREQkt/XoAe+/n263LxdYQlsqcYTDVKUdi0mkqP12YmPNSQcvXXJcrIWAkh0RERFHGDIEnnkm3e5ATrOcVpTkDFtoTDfmkEL6fj5WW7ea8/lIjinZERERcQSLBSZNgtat0xXV4ACLaE8RLrKIBxnMx5lPOvjRR+arMckRJTsiIiKO4uEB//sf1K+fruhOwvmOHlhIYxoDGM9LmbfVp485LF2yTcmOiIiIIxUvbk4WmMEsy51ZyCSeA+BlxvENj9lvxzDgiSfg448dFWmBpWRHRETE0YKDYflyKFEiXdFgJvMC7wLwONP5heaZt/XsszBhgiOiLLCU7IiIiOSFWrVg8WIoUiRd0TuM4BHmkIInnVnAH9TLvK0RI2DaNAcFWvAo2REREckrd94J336bbrcbBjPpzb2s5Tx+tGEpJyifeVuDB8P69Q4KtGBRsiMiIpKXunSB559Pt9ubS/xAR2qzi1PcRGuWEYu//XZSUswZm48fd2CwBYOSHRERkbw2fjzccUe63QHEsZQ2BPMXu6lDR34gGS/77fz9t7kmV2Ki42ItAJTsiIiI5DVPT3NIesmS6YoqcIKltKE48ayjKX2YQRqWDBr51/bt5rD01FTHxZvPKdkRERFxhgoVYM4ccy6ea9RnBwvojAeXmUN3XmJ85m3NmwfPPWcOT5d0lOyIiIg4y/33w+zZGSY8LVjFdB4H4F1e5GMGZd7WlCnw5puOiDLfU7IjIiLiTF27wsKF4JW+b05PvuVtXgbgOSaxkI6ZtzV6NEyd6oAg8zclOyIiIs7Wrp05B0/R9Cugj2QcTzENAzceZRYbCcu8rYED4eefHRRo/uTSyc6YMWOwWCw2W82aNa3lSUlJDBw4kFKlSuHr60uXLl04ffq0EyMWERHJofvvN2dZ9va22W0BJjOI9vxEEkVpzyL2U91+O4YBPXtCTIxj481HXDrZAahduzZRUVHW7ddff7WWDR06lEWLFjFv3jzWrVvHqVOn6Ny5sxOjFRERuQH33AOffZZutwepzKY7jdjMWUrRmmVEU85+OzEx8Pjj6rD8L5dPdjw8PAgMDLRupUuXBiAuLo4vv/ySDz74gPvuu4+GDRvy1VdfsXHjRjZt2uTkqEVERHKoVy8YMiTd7mIksoj23MwhjlCFdiwmgWL221myREtK/Mvlk52DBw8SHBxMlSpV6NGjB8f/nSkyIiKCy5cv06JFC2vdmjVrUqFCBcLDwzNtMzk5mfj4eJtNRETEZbz7LjRPvyBoWf5mOa0ozd9EcBsPM5cU3O238/zzEBnpuDjzCZdOdho3bsyMGTNYvnw5U6dO5ciRIzRp0oTz588THR2Nl5cXAQEBNseUK1eO6OjoTNsdN24c/v7+1i0kJMSBVyEiIpJNHh7mpIPV0/fNqcphFtOOoiSyjDYMYCp2X1YlJUGrVnDokEPDdXUuney0bt2ahx56iHr16tGyZUuWLl1KbGwsc+fOvaF2R44cSVxcnHU7ceJELkUsIiKSS0qVghUrIDg4XVFjtjCHbriRyhf05y1etd/O6dNm5+e//nJgsK7NpZOdawUEBFC9enUOHTpEYGAgly5dIjY21qbO6dOnCQwMzLQdb29v/Pz8bDYRERGXU6mSmfCUKJGu6EEWMfnfiQZH8SYz6G2/naNHoWVLOHvWMXG6uHyV7CQkJHD48GGCgoJo2LAhnp6erFq1ylq+f/9+jh8/TljYdeYgEBERyS/q1LE7B88ApjGSsQD053NW8ID9dnbvhs6dzdXSCxmXTnZeeOEF1q1bx9GjR9m4cSOdOnXC3d2d7t274+/vT79+/Xj++edZs2YNERER9O3bl7CwMO7IYCVZERGRfOvOO+HTTzMseptXeIxvSMGTrsznd26x3866dfDOOw4K0nW5dLJz8uRJunfvTo0aNXj44YcpVaoUmzZtokyZMgB8+OGHtGvXji5dunDPPfcQGBjIggULnBy1iIiIAzz2GHTrlm63BfiSfjTnFxIoTluWcJSK9tt54w3Yt89xcbogi2FoxqH4+Hj8/f2Ji4tT/x0REXFdsbFQrx5kMLAmDj+asIGd1KMme/mNuyjJuYzbufNO2LAB3Fz6mcd1ZfX7O39fpYiISGESEADffAMWS7oif+JZShvKc4J91KIDP5KEd/o2ADZuNFdJLySU7IiIiOQn995rt99Nef5iGa3xJ5ZfaUJPviGN9IkRAC++CBERDgzUdSjZERERyW9eeAGGDs2wqA67WUgnvEhmPg/xAu9l3EZSEnTqVCgWDFWyIyIikt9YLPDee9A747l1mrGWGfQB4EOe50OGZNzOiRPQtStcuuSYOF2Ekh0REZH8yM0NvvgCOnTIsLg7c5jAcACG8T7z6JpxOxs2mGtoFWBKdkRERPIrDw+YNQuqVs2w+AXeYxAfY+DGY3zLeppk3M6UKeZMzQWUkh0REZH8zMcHPv88wyILMJEhdGQhl/CmAz+yh1oZtzNkSIGdXVnJjoiISH7XtCk89VSGRe6kMYtHCWMjsZSgNcs4RVD6ivv22U2a8jslOyIiIgXBO+/ATTdlWFSUJH7iQapxgONUpC1LOI9v+oqjR0N8vIMDzXtKdkRERAoCf3/47jtwd8+wuDRnWE4rynKaSG6hK/O5jIdtpb//hh49CtzoLCU7IiIiBcW998KHH9otrsIRltAWHy7wMy15ks9It2bU4sXmGlyXLzs01LykZEdERKQgGTQI+va1W3wbEczjIdxJYQZ9Gc3r6SstXGg+4SkgHZaV7IiIiBQkFgt88gk0bmy3ShuWMZUBALzJKD7nifSV5s0zOz0XgPXCleyIiIgUNEWKwFdf2e2/A9CfL3iNNwAYwFSW0CZ9penTC8QILSU7IiIiBVGtWtC/f6ZVXmc0vZlBKh48zFy20TB9paFDYf9+BwWZN5TsiIiIFFRjxoBvBkPM/2UBPqc/9/MziRSjLUv4k8q2lRIT8/0ILSU7IiIiBVW5cvDqq5lW8SSF7+lCA7YTQzlasZx/KGVbKSICRozIt/13lOyIiIgUZC+8AM2aZVqlOAkspQ0VOMZBqvMgP5FIUdtKEyfCs89CWprjYnUQJTsiIiIFmbs7/O9/EBqaabUgollOKwI4Rzh30oPvSL02TZg8Gbp3h+RkBwac+5TsiIiIFHRlysDq1VCzZqbVarGPn3gQL5L5gU48x6T0kw7OnQtt2+arZSWU7IiIiBQG5cqZCU+1aplWa8KvfMtjAExhEO/xQvpKq1aZr8ZOn3ZEpLlOyY6IiEhhERQEa9bYXTD0ioeYzwcMBeBF3mU23dJX+v13uOsuOHzYEZHmKiU7IiIihclNN8E335gzLWdiKBMZgrnOVm9msoam6SsdPgx33gnbtzsg0NyjZEdERKSwadbMHKV1He8zjK7M4zJedGIhu6idvlJMjLkA6dq1uR9nLlGyIyIiUhi9+SbcckumVdww+Iae3M0G4gigNcs4SQavwM6fh9atYflyBwV7Y5TsiIiIFEbe3jBnDpQsmWm1IiTzIx2oyV5OEkIblhKHX/qKSUnw4IPwww+OifcGKNkREREprKpXhyVLwN8/02olOccyWhNIFDupR2cWcAnP9BUvX4auXc0kyoUo2RERESnM7rgDNmyA4OBMq1XiGEtpgy/nWU1zHmd6+jl4AFJT4dFHzYkMXYSSHRERkcKubl3YuBFq1Mi02i1EMp+uuJPCdzzGK7ydcUXDgF69zDW1XICSHREREYGKFeHXX6FRo0yrteRnPqc/AON4mak8nXHFS5fgoYcgNjaXA80+JTsiIiJiKl3anGW5VatMq/VlBq8zCoBBTOYn2mdc8cgR8wmPk1dLV7IjIiIi/ylWDH76CR57LNNqr/EmT/A5abjTjTlsonHGFRctgg4dnLp4qJIdERERseXpCTNnwrBhdqtYgKkMoA1LuIgP7VnEQapmXHnRImjcGHbvdky816FkR0RERNJzc4P33oMJE+xW8SCV//EIDdnGP5ShNcuIoUzGlf/4Axo2hIkTIS3NMTHboWRHRERE7Bs+HD75xG6xLxdYQlsq8yeHqUo7FnMBn4wrJyfD0KHQsiX89ZeDAk5PyY6IiIhkbsAAmDHDfNqTgXLEsIzWlOQMW2lEN+aQgrv99n75xRzuPneuY+K9RoFJdqZMmUKlSpUoUqQIjRs3ZsuWLc4OSUREpODo3Rtmzwb3jJOYGhxgEe0pwkUW055BTCYFN9ZyL7PpxlruJfXqtOPcOXjkEejZE+LiHBp6gUh2/ve///H8888zevRofv/9d+rXr0/Lli2JiYlxdmgiIiIFx8MPw7vv2i2+k3Bm8SgW0viUpynFGZqxlkeZTTPWUomjLKCT7UHffgv16sG6dQ4Lu0AkOx988AH9+/enb9++hIaGMm3aNHx8fJg+fbqzQxMRESlYhgyBjh3tFnfiBx7nSwDiCbAp+4ub6Mr89AnP8eOwf3/uxnmVfJ/sXLp0iYiICFq0aGHd5+bmRosWLQgPD8/wmOTkZOLj4202ERERyQKLBb76CipXzrA4FTdW0AoyWDnL+DftGMJE21da7dpB//6OiBYoAMnOP//8Q2pqKuXKlbPZX65cOaKjozM8Zty4cfj7+1u3kJCQvAhVRESkYAgIgPnzwdc3XdEGmnCSEMyZeNIzcOMEFdhAE3NHmTLwxRdmEuUg+T7ZyYmRI0cSFxdn3U6cOOHskERERPKXW2+FlSvB399mdxRBWTrcWu/LL+GaBxa5Ld8nO6VLl8bd3Z3Tp0/b7D99+jSBgYEZHuPt7Y2fn5/NJiIiItl0xx2waZM5WeC/gojK0qFBRJmvrtrbWVcrF+X7ZMfLy4uGDRuyatUq6760tDRWrVpFWFiYEyMTEREpBGrWhI0b4ZVXwM2NJmygPCewkPEsyRbSCOE4TW6Ogg8+yJMQ832yA/D888/z+eefM3PmTPbu3cuAAQO4cOECffv2dXZoIiIiBZ+XF7z1Fqxfj3vlikziOYB0Cc+V3ye6PY/7d19n2OfHEQpEsvPII4/w3nvvMWrUKBo0aEBkZCTLly9P12lZREREHOiuuyAyks59/JlPV27CdkmI8pxkPl3p/Fodc2HQPGIxDCP92LBCJj4+Hn9/f+Li4tR/R0REJDcsWEDqE0+x4VxtoggiiCiasAH3RrfBr7+aK6vfoKx+f3vc8JlERERErtW5M+533EHTxx+HFXPMfT4+5ozJuZDoZEeBeI0lIiIiLig4GJYtg48/hiJF4MMPoVq1PA9DT3ZERETEcSwWGDTIHGJeoYJTQlCyIyIiIo5XsaLTTq3XWCIiIlKgKdkRERGRAk3JjoiIiBRoSnZERESkQFOyIyIiIgWakh0REREp0DT0HLiyYkZ8fLyTIxEREZGsuvK9fb2Vr5TsAOfPnwcgJCTEyZGIiIhIdp0/fx5/f3+75VoIFEhLS+PUqVMUL14ci8WSa+3Gx8cTEhLCiRMnCu0Co7oHugegewC6B4X9+kH3AHL/HhiGwfnz5wkODsbNzX7PHD3ZAdzc3ChfvrzD2vfz8yu0H+wrdA90D0D3AHQPCvv1g+4B5O49yOyJzhXqoCwiIiIFmpIdERERKdCU7DiQt7c3o0ePxtvb29mhOI3uge4B6B6A7kFhv37QPQDn3QN1UBYREZECTU92REREpEBTsiMiIiIFmpIdERERKdCU7IiIiEiBpmTHgaZMmUKlSpUoUqQIjRs3ZsuWLc4OySHGjBmDxWKx2WrWrGktT0pKYuDAgZQqVQpfX1+6dOnC6dOnnRjxjVu/fj3t27cnODgYi8XCDz/8YFNuGAajRo0iKCiIokWL0qJFCw4ePGhT5+zZs/To0QM/Pz8CAgLo168fCQkJeXgVN+Z696BPnz7pPhetWrWyqZOf78G4ceO4/fbbKV68OGXLlqVjx47s37/fpk5WPvvHjx+nbdu2+Pj4ULZsWYYPH05KSkpeXkqOZeUeNG3aNN3n4Omnn7apk5/vwdSpU6lXr551krywsDCWLVtmLS/onwG4/j1whc+Akh0H+d///sfzzz/P6NGj+f3336lfvz4tW7YkJibG2aE5RO3atYmKirJuv/76q7Vs6NChLFq0iHnz5rFu3TpOnTpF586dnRjtjbtw4QL169dnypQpGZZPmDCBjz76iGnTprF582aKFStGy5YtSUpKstbp0aMHu3fvZuXKlSxevJj169fz5JNP5tUl3LDr3QOAVq1a2XwuZs+ebVOen+/BunXrGDhwIJs2bWLlypVcvnyZBx54gAsXLljrXO+zn5qaStu2bbl06RIbN25k5syZzJgxg1GjRjnjkrItK/cAoH///jafgwkTJljL8vs9KF++POPHjyciIoJt27Zx33330aFDB3bv3g0U/M8AXP8egAt8BgxxiEaNGhkDBw60/p6ammoEBwcb48aNc2JUjjF69Gijfv36GZbFxsYanp6exrx586z79u7dawBGeHh4HkXoWICxcOFC6+9paWlGYGCg8e6771r3xcbGGt7e3sbs2bMNwzCMPXv2GICxdetWa51ly5YZFovF+Ouvv/Is9txy7T0wDMPo3bu30aFDB7vHFLR7EBMTYwDGunXrDMPI2md/6dKlhpubmxEdHW2tM3XqVMPPz89ITk7O2wvIBdfeA8MwjHvvvdd47rnn7B5T0O6BYRhGiRIljC+++KJQfgauuHIPDMM1PgN6suMAly5dIiIighYtWlj3ubm50aJFC8LDw50YmeMcPHiQ4OBgqlSpQo8ePTh+/DgAERERXL582eZe1KxZkwoVKhTYe3HkyBGio6Ntrtnf35/GjRtbrzk8PJyAgABuu+02a50WLVrg5ubG5s2b8zxmR1m7di1ly5alRo0aDBgwgDNnzljLCto9iIuLA6BkyZJA1j774eHh1K1bl3LlylnrtGzZkvj4eJt/FecX196DK7777jtKly5NnTp1GDlyJImJidaygnQPUlNTmTNnDhcuXCAsLKxQfgauvQdXOPszoIVAHeCff/4hNTXV5j8cQLly5di3b5+TonKcxo0bM2PGDGrUqEFUVBSvv/46TZo0YdeuXURHR+Pl5UVAQIDNMeXKlSM6Oto5ATvYlevK6L//lbLo6GjKli1rU+7h4UHJkiULzH1p1aoVnTt3pnLlyhw+fJiXX36Z1q1bEx4ejru7e4G6B2lpaQwZMoS77rqLOnXqAGTpsx8dHZ3h5+RKWX6S0T0AePTRR6lYsSLBwcHs2LGDESNGsH//fhYsWAAUjHuwc+dOwsLCSEpKwtfXl4ULFxIaGkpkZGSh+QzYuwfgGp8BJTtyw1q3bm39c7169WjcuDEVK1Zk7ty5FC1a1ImRiTN169bN+ue6detSr149br75ZtauXUvz5s2dGFnuGzhwILt27bLpq1bY2LsHV/fBqlu3LkFBQTRv3pzDhw9z880353WYDlGjRg0iIyOJi4tj/vz59O7dm3Xr1jk7rDxl7x6Ehoa6xGdAr7EcoHTp0ri7u6frcX/69GkCAwOdFFXeCQgIoHr16hw6dIjAwEAuXbpEbGysTZ2CfC+uXFdm//0DAwPTdVZPSUnh7NmzBfa+VKlShdKlS3Po0CGg4NyDQYMGsXjxYtasWUP58uWt+7Py2Q8MDMzwc3KlLL+wdw8y0rhxYwCbz0F+vwdeXl5UrVqVhg0bMm7cOOrXr8+kSZMK1WfA3j3IiDM+A0p2HMDLy4uGDRuyatUq6760tDRWrVpl8w6zoEpISODw4cMEBQXRsGFDPD09be7F/v37OX78eIG9F5UrVyYwMNDmmuPj49m8ebP1msPCwoiNjSUiIsJaZ/Xq1aSlpVn/IihoTp48yZkzZwgKCgLy/z0wDINBgwaxcOFCVq9eTeXKlW3Ks/LZDwsLY+fOnTZJ38qVK/Hz87O+AnBl17sHGYmMjASw+Rzk53uQkbS0NJKTkwvFZ8CeK/cgI075DORKN2dJZ86cOYa3t7cxY8YMY8+ePcaTTz5pBAQE2PQ2LyiGDRtmrF271jhy5Ijx22+/GS1atDBKly5txMTEGIZhGE8//bRRoUIFY/Xq1ca2bduMsLAwIywszMlR35jz588b27dvN7Zv324AxgcffGBs377dOHbsmGEYhjF+/HgjICDA+PHHH40dO3YYHTp0MCpXrmxcvHjR2karVq2MW265xdi8ebPx66+/GtWqVTO6d+/urEvKtszuwfnz540XXnjBCA8PN44cOWL88ssvxq233mpUq1bNSEpKsraRn+/BgAEDDH9/f2Pt2rVGVFSUdUtMTLTWud5nPyUlxahTp47xwAMPGJGRkcby5cuNMmXKGCNHjnTGJWXb9e7BoUOHjDfeeMPYtm2bceTIEePHH380qlSpYtxzzz3WNvL7PXjppZeMdevWGUeOHDF27NhhvPTSS4bFYjF+/vlnwzAK/mfAMDK/B67yGVCy40Aff/yxUaFCBcPLy8to1KiRsWnTJmeH5BCPPPKIERQUZHh5eRk33XST8cgjjxiHDh2yll+8eNF45plnjBIlShg+Pj5Gp06djKioKCdGfOPWrFljAOm23r17G4ZhDj9/7bXXjHLlyhne3t5G8+bNjf3799u0cebMGaN79+6Gr6+v4efnZ/Tt29c4f/68E64mZzK7B4mJicYDDzxglClTxvD09DQqVqxo9O/fP12yn5/vQUbXDhhfffWVtU5WPvtHjx41WrdubRQtWtQoXbq0MWzYMOPy5ct5fDU5c717cPz4ceOee+4xSpYsaXh7extVq1Y1hg8fbsTFxdm0k5/vweOPP25UrFjR8PLyMsqUKWM0b97cmugYRsH/DBhG5vfAVT4DFsMwjNx5RiQiIiLietRnR0RERAo0JTsiIiJSoCnZERERkQJNyY6IiIgUaEp2REREpEBTsiMiIiIFmpIdERERKdCU7IiIiEiBpmRHRAqUSpUqYbFYsFgs6RZgzK6mTZta27qyno+I5D9KdkTE5aSmpnLnnXfSuXNnm/1xcXGEhITwyiuvZHr8G2+8QVRUFP7+/jcUx4IFC9iyZcsNtSEizqdkR0Rcjru7OzNmzGD58uV899131v2DBw+mZMmSjB49OtPjixcvTmBgIBaL5YbiKFmyJGXKlLmhNkTE+ZTsiIhLql69OuPHj2fw4MFERUXx448/MmfOHL7++mu8vLyy1daMGTMICAhg8eLF1KhRAx8fH7p27UpiYiIzZ86kUqVKlChRgmeffZbU1FQHXZGIOIuHswMQEbFn8ODBLFy4kJ49e7Jz505GjRpF/fr1c9RWYmIiH330EXPmzOH8+fN07tyZTp06ERAQwNKlS/nzzz/p0qULd911F4888kguX4mIOJOSHRFxWRaLhalTp1KrVi3q1q3LSy+9lOO2Ll++zNSpU7n55psB6Nq1K9988w2nT5/G19eX0NBQmjVrxpo1a5TsiBQweo0lIi5t+vTp+Pj4cOTIEU6ePJnjdnx8fKyJDkC5cuWoVKkSvr6+NvtiYmJuKF4RcT1KdkTEZW3cuJEPP/yQxYsX06hRI/r164dhGDlqy9PT0+Z3i8WS4b60tLQcxysirknJjoi4pMTERPr06cOAAQNo1qwZX375JVu2bGHatGnODk1E8hklOyLikkaOHIlhGIwfPx4wJwt87733ePHFFzl69KhzgxORfEXJjoi4nHXr1jFlyhS++uorfHx8rPufeuop7rzzzht6nSUihY/F0N8YIlKAVKpUiSFDhjBkyJBcae/o0aNUrlyZ7du306BBg1xpU0Tylp7siEiBM2LECHx9fYmLi7uhdlq3bk3t2rVzKSoRcRY92RGRAuXYsWNcvnwZgCpVquDmlvN/0/31119cvHgRgAoVKmR75mYRcQ1KdkRERKRA02ssERERKdCU7IiIiEiBpmRHRERECjQlOyIiIlKgKdkRERGRAk3JjoiIiBRoSnZERESkQFOyIyIiIgXa/wFgDbWQ/HgWGgAAAABJRU5ErkJggg==",
      "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": 8,
   "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": 9,
   "id": "91019da5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[PointSource(name=Source 1, pos=(100, 100, 0), isotope=Cs137, A=100 MBq)]"
      ]
     },
     "execution_count": 9,
     "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": 10,
   "id": "7913fe1e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>,\n",
       " <Axes: xlabel='X [meters]', ylabel='Y [meters]'>)"
      ]
     },
     "execution_count": 10,
     "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": 11,
   "id": "df4715c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>,\n",
       " <Axes: xlabel='X [meters]', ylabel='Y [meters]'>)"
      ]
     },
     "execution_count": 11,
     "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
}