{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dfeba988-6a50-456a-b419-bca6b50c6224",
   "metadata": {},
   "source": [
    "# Simulation Results\n",
    "\n",
    "This notebook will teach how to viasualize and extract results from the MobsPy simulation object.\n",
    "\n",
    "We start with a simple model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "df8e675d-5966-49be-898b-6c5fbb8f8369",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Compiling model\n",
      "Starting Simulator\n",
      "Running simulation in parallel\n",
      "Simulation is Over\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mobspy import *\n",
    "\n",
    "Color, Disease = BaseSpecies()\n",
    "\n",
    "Color.blue, Color.red, Color.yellow\n",
    "Disease.not_sick, Disease.sick\n",
    "\n",
    "Disease.not_sick >> Disease.sick [1]\n",
    "\n",
    "Tree = Color*Disease\n",
    "\n",
    "Tree.yellow(20), Tree.red(20), Tree.blue(20)\n",
    "\n",
    "S = Simulation(Tree)\n",
    "S.method = 'stochastic'\n",
    "S.repetitions = 3\n",
    "S.step_size = 0.25\n",
    "S.duration = 3\n",
    "S.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "611f87ec-b356-49cd-bc01-95964c544eb7",
   "metadata": {},
   "source": [
    "The previous plot did not show much as the number of Trees remains constant throughout the simulation.\n",
    "However, MobsPy provides tools to better viasualize the results. Firstly, one can use the plot_stochastic() function with perform string queries to plot the counts from specific states."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9b28c8e6-8cd6-43a7-8956-863095d4bd18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZwAAAEcCAYAAADz8QLhAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAB1eklEQVR4nO2dZ3hU1daA3zUphJAGSYAA0ntHmoqigAIqdgEbAupFr4qggqJ+KqKi3uvlgmDDAtYrYsUuXUWlhN57SagJkN5nfT/OZEggZQKZmUyy3+c5z8wpe591AnvW2WuvIqqKwWAwGAzuxuZtAQwGg8FQNTAKx2AwGAwewSgcg8FgMHgEo3AMBoPB4BGMwjEYDAaDRzAKx2AwGAwewa0KR0QiROQLEdkqIltE5EIRqSUi80Vkh+OzpjtlMBgMBkPFwN0znGnAz6raGugEbAEmAAtVtQWw0LFvMBgMhkqOuCvwU0TCgHVAUy1wExHZBlymqodEJAZYoqqtSuorKipKGzdu7BY5DYbTiY2NTVDVaG/LUV6Y8WPwNMWNIX833rMpcAyYJSKdgFhgDFBHVQ8BOJRO7aIai8goYBRAw4YNWbVqlRtFNRhOISL7yrm/McAsIAV4F+gCTFDVX0tpF+G4vj2gwF3ANmAO0BjYCwxR1RMl9dO4cWMzfgwepbgx5E6Tmj9wPvCmqnYB0iiD+UxVZ6pqN1XtFh1daV42DVWTu1Q1GegPRAMjgZddaGdM0oZKhTtnOHFAnKoud+x/gTU4johITAGT2lE3ymDwIbJys9iXtI/dJ3ZzKOUQSvmbe7Nys9ieuJ2a1WvyzKXPlHv/xSCOz6uAWaq6TkSkxAaWSbo3MAJAVbOBbBG5DrjMcdkHwBLg8bOSas8euP56+OYbaNLkrLowGMqC2xSOqh4WkQMi0kpVtwH9gM2ObTjWG95w4Ft3yWCoWKgqCekJ7D6xm90ndrPrxC7n990ndhOXHOcWJVMU4dXCPalwYkXkV6AJ8ISIhAL2UtqUq0m6SN56C9avh2uugY0by/5UBkMZcZvTAICIdMayQQcCu7FMCTbgc6AhsB8YrKrHS+qnW7duamzQvkFWbhZ7T+4tpEh2nzz1PTU7tdD1MSExNK3Z1Lk1q9mMpjWbUi+0Hn42vzLfX1XZfWI3fxz4gz/2/8GfB/4kNTsVQYiuEU3NoJoIQrd63fjoxo+K7ENEYlW121n9AYruzwZ0Bnar6kkRiQTqq+r6Etp0A/4GeqnqchGZBiQDo1U1osB1J1S1xNCCEsePvz/k5UFcHNSvX8YnMxiKprgx5E6TGqq6Fihq4PZz530N7kVVWXdkHZuPbS6kWHad2EV8cnyhWUqQfxBNazalSUQTLmt0maVUallKpXFEY4IDgs/o/3DKYeZtn0eePc9lmfac3MNv+35j07FNTqUmiFMWRTmadhR/m79TBg8yX1Wd/+dVNVFEPqfkceAZk/SIEfDee3DttRAbe05dGQyl4VaFY6hcnMg4wcfrP2bm6plsPHrKBFMvtB5Nazalb5O+NI1oWmjGUjekLqUsV5Cdl83fcX/z6YZP+XbbtxxOPXzWMvqJHzEhMbSNbkuH2h0KydI4ojHVA6qfdd9lRUSCgGAgyhHgnP+HCAPqldTWYybpN9+EWbNg9WrYtw8aNTqn7gyGkjAKx1AiqsqfB/5k5uqZfL7pczJzM+lerztvD3qbixteXOwspbQ+Nx7dyILdC/h5588s2beE7LxswJqVtI1uy/Wtrie0WqjLfdYNqcsVTa+gXmi9UhWcB7kXGIulXGI5pXCSgdddaD8a+EREzjBJi8jdOEzS5yRhQIA1u/nmGxgyBJYvL7WJwXC2GIVjKJITGSf4aP1HzIydyaZjmwgNDGVEpxGM6jqKLjFdytxfXHIcC3YvYP7u+SzcvZAjaUcAsIkNu9qJCYnhn93+yX3d7iO6RuVwg1fVacA0ERmtqtPPov1aPGGSfvddS+GsWAGbNkG7duXavcGQj1E4BifFzWbeveZdhrYfSkhgSJn6y8rN4uutXzMzdiaL9y4GIDQwlGr+1QAIsAVwU9ubGHX+KC5rfFlFmpmUK6o6XUQuwgrW9C9w/EOvCVWQyEi4+GL44w+46y4zyzG4DaNwDEXOZkZ2Hsk/zv/HWc1mtiduZ2bsTGavnU1iRiJ1a9TlgvoXsOnYJlKyU4gJjWFCrwnc2enOSjObKQkR+QhoBqwF8j0hFKgYCgfg7betmc2KFfDnn3DRRd6WqEKSmJhIv37WBPPw4cP4+fmRH5i+YsUKAgMDPS7T1KlTGTVqFMHBZTNtP/PMM/Tu3ZvLL7+8yPOzZ89m1apVzJgxozzEBFxQOCLSC1irqmkicgdW9oBpqlqu6T8MniV/NvN27NvM3TyXzNxMetTvcU6zma+2fMXbsW+zdN9SbGIjsnokAbYADqcd5njmcW5qcxOjuo7i0kaXVtrZTDF0A9qqO2MQzpW2baFNG9iyBe6/H9asgYr+bzR2LKxdW759du4MU6cWezoyMpK1jntOnDiRkJAQxo0b5zyfm5uLv79n3+OnTp3KHXfcUWaFM2nSJDdJVDyupLZ5E0h3BJ89BuyjIr2ZGcrEiYwTTPt7Gu3fbM/Fsy7mm63fMLLzSNbcu4bl9yzn7vPvLpOy2XpsK3d/ezeR/4rktq9u4/f9vwNY6zKhMYzuMZqfbv+J448d59ObPq3UprMS2AjU9bYQpfLqq9bnunXw44/elcWHGDFiBI888gh9+vTh8ccfZ9euXQwcOJCuXbtyySWXsHXrVgCOHTvGTTfdRPfu3enevTvLli07o68lS5Zw2WWXcfPNN9O6dWtuv/128t9TFi5cSJcuXejQoQN33XUXWVlZvPbaaxw8eJA+ffrQp0+fIuXLy8tjxIgRtG/fng4dOvDf//7XKfcXX3wBwMqVK7nooovo1KkTPXr0ICUlpVAfP/zwAxdeeCEJCQnn9LdyRRXnqqo6UmpMU9X3RGT4Od3V4FFUlWUHljEzdmah2cx7177H0HZDqRFYw+V+EjMS2XpsK//b+D++2vpVIRfm6OBorm55Nf2b9qdvk77UCanjrkfyNaKAzSKyAsjKP6iq13pPpCK48kqoUweOHIGHH4aBA8Gv7MG3HqOEmYin2b59OwsWLMDPz49+/frx1ltv0aJFC5YvX87999/PokWLGDNmDA8//DAXX3wx+/fvZ8CAAWzZsuWMvtasWcOmTZuoV68evXr1YtmyZXTr1o0RI0awcOFCWrZsyZ133smbb77J2LFjmTJlCosXLyYqKqpI2dauXUt8fDwbHdkkTp48Weh8dnY2Q4cOZc6cOXTv3p3k5GSqVz8VPvD1118zZcoUfvzxR2rWPLfyZa4onBQReQK4A+gtIn5AwDnd1eARjmcc56N1HzFz9Uw2H9tMWLUw7up8F//o+g861+1cZJvsvGz2ndxXZKaAncd3FsoUYBMbbaPbMqzjMG5scyMtarWoirMXV5jobQFcQgT+7/9g9GjYsQM++QTuvNPbUvkEgwcPxs/Pj9TUVP78808GDz7lrZ6VZb1jLFiwgM2bNzuPJycnk5KSQmhoYff/Hj160KBBAwA6d+7M3r17CQ0NpUmTJrRs2RKA4cOH8/rrrzN27NhSZWvatCm7d+9m9OjRXH311fTv37/Q+W3bthETE0P37t0BCAsLc55bvHgxq1at4tdffy10/GxxReEMBW4D7nYEozUE/n3Odza4jZSsFJ5c+CTvrH6HrLwsetbvyfvXvs+QdkMIDggmMSORFfErCisVx3Yg+QB2PZXmq5pfNSKDI8nMzSQ1OxWb2LigwQWM6DSC4Z2HE+jn+UVSX0NVl3pbBpcZNQoefxzS0+HJJ63YnKAgb0tV4alRw7IS2O12IiIinOs8BbHb7fz111+FZg9FUa1aNed3Pz8/cnNzOZflv5o1a7Ju3Tp++eUXXn/9dT7//HPef/9953lVLfZFMV9Zbd++nW7dzj3bkysK52FVdWajVdX9ImIc9SsoC3cv5K5v72J/8n4GNhtIl5guZOdl893275i2fBq7T+wmJbuwfbZuSF2aRDThkkaXODMF+Nn8+G3fb3yx+QsOphykac2mPHbRY4zoPMKYysqIiKSAM99PIJaFIE1Vz/2VsbwJDIT77oMpUyA+3spE8PDD3pbKZwgLC6NJkybMnTuXwYMHo6qsX7+eTp060b9/f2bMmMH48eMBy9TVuXNnl/pt3bo1e/fuZefOnTRv3pyPPvqISy+9FIDQ0FBSUlKKNaklJCQQGBjITTfdRLNmzRgxYsQZfR88eJCVK1fSvXt3UlJSnEqxUaNGvPrqq9xwww3MnTuXducYo+WKwrmCM9OfX1nEMYOHyF9L2X1iN7uOWxmXtyZuZdHuRRxMPei87uddP/Pzrp+p5lfNmd6ld6PehdK9NIlo4lzDyczN5MvNXzJz9Ux+2/cb/jZ/bmh9A6O6jqJvk77YxN0VySsnqlrIZiIi1wM9vCONCzz5JEybBnY7vPCCFZsTHu5tqXyGTz75hH/+85+88MIL5OTkcMstt9CpUydee+01HnjgATp27Ehubi69e/fmrbfeYtWqVbz11lu8++67xfYZFBTErFmzGDx4MLm5uXTv3p377rsPgFGjRnHllVcSExPD4sWLz2gbHx/PyJEjsdsty8VLL71U6HxgYCBz5sxh9OjRZGRkUL16dRYsWOA836pVKz755BMGDx7Md999R7NmZ5+HsNhs0SLyT+B+rDTpuwqcCgX+VNXbz/quZaSqZ4vOs+fxyYZP+GbrN07T1+mzlPyI/bZRbbmu9XW0jmpNk4gmNKvVjLohdYtVFslZySzdu5Rfdv3C/zb+j+MZx2lWsxn/OP8fVXY2U97Zoou5x9+qeoE775HPWY2fm2+GL7+0vv/f/8Hzz5e/YIZKy9lki/4U+Al4icJVBVNKKydgKB9Ule+2f8eTC59k07FNNIloQtvotvRu1JtmNS1F8sXmL/hiyxe0qNWCWdfN4sLzLiyxz5y8HP6O+5sFuxewYM8ClsctJ0/zqO5fnUEtB3Fv13vp06SPmc2UIyJyY4FdG1ZcTsWNyQFrZvPll5aX2pQpVmxOTIy3pTL4OMUqHFVNApKAWx2eaXUc14eISIiq7veQjFWS3/f9zoSFE/jzwJ+0qNWCOTfP4ea2NzsVwfxd87nnu3uIS45j3IXjmNRnUpGZkFWVTcc2WQpm9wKW7lvqXPzvXq87Ey6ewOVNL+fCBhc6U84Yyp1rCnzPBfYC13lHFBdp3Rp69rTS3GRkWDOcN97wtlSGUujZs6fTKy6fjz76iA4dOnhJosK4kmngQSy3ziOcqlKoQEf3iVV1WX9kPU8sfIIfd/xITEgMbw96m5GdRxLgZ3miJ2clM+7Xcbyz+h1aRbbij5F/nDGriU+Od85gFuxe4IyVaVGrBXd2vJPLm17OZY0vo2b1c/OpN7iGqo70tgxnxaRJMGAAVKsG77xjOQ+0aOFtqQwlsLyC58FzxWlgLNBKVRPdLEuVZveJ3Tyz+Bk+3fAp4UHhvNzvZUb3HF0o9f+vu37lnnn3EJ8Sz/iLxvPcZc9RPaA6SZlJLN231JmNeWuCFdkcHRzN5U0v5/Kml9OvST8aRZhaJ95ARBoA04FeWC9rfwBjVDXOq4KVxhVXWPVx9u2zvNf+7/9gzhxvS2XwYVxROAewTGsGN3Ak9Qgv/PYCb8e+jb/Nn8d7Pc5jvR4rNPvIycth3K/jeG3Fa7SKbMWS4UtQlJf+eIkFuxewIn4FeZpHcEAwvRv15p4u93B508vpUKeDWYupGMzCWhPNjwa8w3HsCq9J5Aoi8NRTVmxO9erw+efw2GPQtau3JTP4KK4onN3AEhH5gcJpOaa4TaoqQFJmEv/56z9M+WsKmbmZ3HP+PTxz6TPUCy1cCPJI6hGGfDGE3/b9xiUNLyE4IJgrP7mStJw0bGKjR/0ePHHxE1ze9HIuaHCBWYepmESr6qwC+7NFZKy3hCkTw4bBo49CUhKEhcGECTB/vrelMvgoriic/Y4t0LEZzoHM3EzeWPkGk3+fTGJGIkPaDeH5Ps/TMrLlGdeujF/JDXNu4GjaUYIDgvl9/++0imzFiM4jnOswEUERnn8IQ1lJcGRa/59j/1bAN0zUQUHw0EPw4ouWwlmwAF5/HR54wNuSGXyQUhWOqj7nCUEqO7n2XD5a9xHPLnmWA8kH6N+sP5P7TqZrvaLNE7PXzube7+7Fz+ZHjj2H7vW7884179A2uq2HJTeUA3cBM4D/Yq3h/Ok45huMHg0vvwxxcVadnDFjoGVLa43HYCgDrnipLaaImAFV7esWiSoZqsq3277lyYVPsiVhC93rdWf29bPp26ToP19OXg4P//wwr696HX+bPzZsTOk/hYd6PoSfrQJn7jUUiyOEoGJlhi4LderAbbfBRx9ZM542bWDwYMtlulUrb0tn8CFcMamNK/A9CLgJK5bAUApL9i5hwoIJLI9fTqvIVnwx+AtubHNjsYnyjqQe4dr/XcuKgysA6FG/B7Ovm02LSOOK6ouIyL+A3ar61mnHHwbqFsxRWOEZP95SOIsWWWlvXngBrrkG/v4batXytnQGH6FUFyZVjS2wLVPVR4Cert5ARPxEZI2IfO/YryUi80Vkh+Oz0gWDrDm0his/uZI+H/QhLjmOd695l433b+SmtjcVq2yWxy2nzettWHFwBQG2AKb0n8JvI34zysa3GQTMLOL4NOBqD8tybnToAH36WO7RjzxiORLs22fNdHJyvC2dwUcoVeE4FET+FiUiAyhb9cIxQMEqQxOAharaAlhI4bQ5Ps3O4zu59ctbOX/m+SyPW86/r/g3O0bv4O7z78bfVvxkcspfU7jovYs4kXmCznU7s+n+TTx84cPGhOb7qGqBWg+nDtoB3yscNGECZGdbKW4mTrQCQRctspwKKnD1bEPFwRWTWizWGo5gmdL2AHe70rkj4O1q4EXgEcfh64DLHN8/AJZQCTJPL96zmAEfDyDAL4AnL36S8b3Gl+pBlpWbxVWfXMWivYuwiY3nL3ueJy5+wiiaykO6iLRQ1R0FD4pICyDDSzKdPf37W1VBly2Dhg0tb7Vhw+Ctt6BdO3jwQW9LaKjguOKl1uQc+p8KPIaVYTqfOqp6yNH3IRGpXVRDERkFjAJo2LDhOYjgfg6nHubWL2+lWa1mLLpzETGhpSc53Hh0I71n9eZE5gnqh9Zn/rD5tIlu4wFpDR7kGeAnEXkB68UNrMSdT2Bl8CgVRx7DVUC8qg4SkVrAHKAxVk62Iap6onzFLoEpUyzzWvfu8Oef8P33lqkt33PttGqSBkNBXDGpBYjIQyLyhWN7UERKLTEtIoOAo6oaW9q1RaGqM1W1m6p2i46OPpsuPEKePY/bv7qd5Kxk5g6eW6qyUVVmrZlFl7e7cCLzBMM6DmPf2H1G2VRCVPUn4HqgDzDbsV0G3KSqP7rYTcUySbdubc1kPv0UXnvN8lrbvNnKsTZkCGzd6lFxDL6FK3lP3gS6Am84tq6OY6XRC7hWRPYCnwF9ReRj4IiIxAA4Po+ehdwVhhd+e4FFexbx+lWv0752+xKvjU+O55r/XcNd8+4i157LC31e4MMbPjQmtEqMqm5U1eGq2tWxDVfVDa60LWCSLliZ6zosUzSOz+vLVWBXeOYZiIyEV1+FX36xnAbS0iAgAAYNgkTfiGk1eB5XFE53xyBZ5NhGAt1La6SqT6hqA1VtDNwCLFLVO4B5wHDHZcOBb89Sdq+zaM8inlv6HHd2upMRnUcUe52q8sHaD2j3Rjvm75qPINzW4TaevORJzwlr8EWmYpmkCzoeFDJJA8WapEVklYisOnbsWPlKVbOm5Ra9dCls2wY//wwnT0JICBw4YBVvM55rhiJwReHkiYizpqiINAXyzuGeLwNXiMgOrOSFL59DX17jcOphbvvyNlpHteaNq94o1t05PjmeQf8bxIhvR9A6qjXhQeG0jGzJ24PeLraNwVDhTdL33AMdO8K4cdC+PXz3HRw6BPXqwZIlltnNeK4ZTsMVhTMeWCwiS0RkKbAIeLQsN1HVJao6yPE9UVX7qWoLx6fPVQ/Ns+dx25e3OddtagTWOOMaVWX22tm0e6Mdi/cs5r8D/ktIYAgp2SnMHTyXkMAQL0hu8AaOhf7Tj5XmjFOxTdJ+flYA6L598J//wGWXwRdfWOlvzjsPZs6E6dO9Ipqh4uJK4OdCoAXwkGNrpaqL3S1YReb5355n8d7FvHH1G7Sr3e6M8/mzmpHfjqRjnY6s/+d6UrJSWLhnITOunEGHOhWj+p7BY3wnImH5OyLSFviupAY+YZK+7DLLfPbSS5aiGTQIPvzQMqvVqWPF6fz8s9fEM1RAVLXIDatmx7Aijv8DuK24du7YunbtqhWFBbsWqEwUHf718DPO2e12nbVmloa/FK7BLwbra3+/pnn2PF20e5HanrPpHV/doXa73fNCG8oEsErL8f8v1sL/UiAEy+lmE9C5DO0vA753fI/E8k7b4fisVVp7t46fPXtUq1VTvf32U8feeksVVCMiVIODVT//3H33N1RIihtDJf0nXwOEFnE8DIgtrp07toqicA6lHNI6/66jbWa00dSs1ELnkjKT9KpPrlImor1n9dadiTtVVfVwymGt+2pdbT2jtaZkpXhDbEMZKW+FY3XJ9VhZojcALcq7/5I2t4+fp56yfkr+/PPUsVdesY7VqWN9TpigmpvrXjkMFYbixlBJJjU/VU0pYkaUDJQah1PZyF+3yV+DKbhuo6qM+m4Uv+z8hWkDp7F4+GKa1WrmjNFJykwy6zZVEBGZLiKvichrQF+sl7U9wGjHscrBhAmWs8CYMWB3ONQ99pi1HTkCl15qlTe4+mo47nNLtoZypCSFEyAiZ6yGi0goVbAQ26Slk6x1m6vOXLd5O/Zt5myawwt9X+Chng85yzq/+PuL1rrNVTNKjdExVEpWYWUYyN/+DXxZYL9yEBICr7wCK1daGaXzmTwZ+vWzyhg884yVd617d9jgUhiSoTJS1LTHmhExDvgJaFzgWGPgB2B8ce3csXnbpDZ/13yViaIjvhlxxrnVB1drteer6ZUfX6l59jzn8YW7F6pMFB321TCzbuNjUP5rODWwLAb5+35AcHneo6TNI+MnL0/1ggtU69ZVTU4+dfzwYetY69aqCxaoxsRY6zpz5rhfJoPXKG4MFTvDUdVXsTxglopIoogkYC18fq+q/3aT/qtwHEo5xO1f3U6b6DbMuHJGoXPJWckMnjuYqOAoPrzhQ+fMJj9Gp1VUK964uvgYHUOVYSFQvcB+dWCBl2RxDzab5SZ9+LA1s8mnTh0rDc727TB7NqxaBZ07w9Chliku71xC+gy+Rolu0ar6lqo2AhoBTVS1kaq6ktamUpBrz+W2r24jNTu1yHWbf3z3D/ae3MtnN39GVHAUYK313PHVHc4YHbNuYwCCVDU1f8fxPdiL8riHHj3gzjutBJ+7dp063qcPPPssfPwx/PQTLF4M995rmeHMuk6VwpXAT1Q1VYtwIKjsTFo6iSV7l/DGVW/QNrptoXNvrXqLzzd9zot9X+Tihhc7j7/w2wss3LPQpdxqhipDmoicn78jIl3xxfIErvDSS1ZOtXHjCh9/6im4/HIrA8G2bVZJg5kzLeVj1nWqDkXZ2Sra5o01nNUHVxcbbxN7MFYDnw8sdt3mzq/vNOs2Pgzlv4bTHdgF/O7YdgJdy/MeJW0eHz+TJ6uC6vz5hY/nr+e0aqWa4ggR+Osvs65TCSluDLk0wzkdEalWTvquQqKqjPl5DFHBUUwdOLXQuaTMJIbMHULtGrULrdtsT9zuUm41Q9VDVVcCrYF/AvcDbfQsc6T5BA8/DE2awNixkJt76nj+es6OHfDPf1q51i64AGJjT63rPP+8t6Q2eABX6uG8f9p+COBqLQ+fZO7mufy+/3de6PtCoaqdWnDd5qZT6zbfbfuO7u90J0/zis2tZqh6iEhfx+eNwDVAS6w0Udc4jlVOgoKs/GqbNllms4L06WOVp/74Y3jf8dMSE2OZ1oYNs9ynv/XZBPKGUnBlhhMvIm8CiEhN4FfgY7dK5UXSc9IZP388nep04u4uhStpv7nqTeZunsvkfpPp1bAXdrUzaekkrv3sWprXak7sqNgic6sZqiyXOj6vKWIb5C2hPML110Pfvtbazb59hc89+SRccYW1nrN+vXUsMBDeeQe6doURI2DvXg8LbPAIRdnZTt+AV4C3gJVY1Qor7RrOc0ueUyaiS/YsKXR8VfwqDXw+UK/65CrNs+dpUmaSXve/65SJ6J1f36np2ekek9HgXnBDahtvbl6LY9uxQzU01IrPyc4ufO7IEWvtpmXLwnE7u3aphoWp9uihmpXlWXkN5UZxY6jYGY6I3Ji/ASuAC7Dyq2llNQccSDrAy3+8zOC2g7m08aXO40mZSQz5wlq3+eD6D9ieuJ2e7/bk++3fM23gNGZfN5vqAdVL6NlQlRGRMSISJhbvishqEenvbbncTvPm8N578Pff8MQThc/Vrm2t5+zcCffdd6p2TtOmlqltxQorTsdQqSjJpHb69H8NVg61SmsOmLBwAoryryv+5Tymqtzz3T3sO7mPOTfP4c8Df9LjnR4kpiey8M6FPNTzIeMgYCiNu9TKQdgfq0LnSHy08GCZGTwYHnjAWtOZN6/wucsug+eesxTPe++dOn7TTTB6NPz3v2Y9p7JR1LSnom2eMAn8se8PZSL69KKnCx2fsXyGMhF9+feXdeLiicpEtOvbXXXfyX1ul8ngHSh/t+j1js9pwA2O72vK8x4lbd5ODaUZGarnn69as6bq3r2Fz+XlqV5xhWpQkOq6daeOZ2aqdutmlTjYs8ej4hrOneLGkCteah+ISESB/Zqne675Ona1M+bnMdQPrc/jvR53Ho89GMsjvz5C/6b9WXZgGROXTmR4p+H8PvJ3GoY39KLEBh8jVkR+Ba4CfnEkwLV7WSbPERQEn39upbEZOhSys0+ds9ksj7WaNa3ZUIojvrxaNZgzxzK1nd7G4LO44qXWUVVP5u+o6gmgi9sk8gIfrP2A2EOx/OuKfzldmo+kHmHw3MHUDKrJ7pO7+XHHj7w28DVmXTfLrNcYysrdwASgu6qmY2VbH5l/UkQqv2tjs2bw7rtW5ugnnyx8rnZt+N//rPWcIUPg2DHreMH1nMcfP7NPg8/hisKxOdyhAWd9dn/3ieRZkrOSeWLhE1zY4EJubX8rACczTzLg4wHEJ8eTkp1CUmYSC+9cyOieo816jaHMqKpdVVfnv7ipaqKqri9wyUdFt6xklLSec+ml8MYbsHAhtGsHX3xhHb/xRnjoIZg6Fb75xtMSG8oZVxTOf4A/ReR5EXkeq2rhv0pp4zO8+NuLHEk7wrSB0xAR0rLTuPrTq9l4dCO5mkvb6LbEjoot5LVmMJQzVect5j//gfPPh+HDz4y1ufdeWL0aGjWylFP+bOdf/4Ju3WDkSNizxytiG8qHUhWOqn4I3AQcAY4CN6pqpXgj23l8J1OXT2VE5xF0r9+drNwsbvz8Rv468BeBfoF0qtOJJcOXcF74ed4W1VC5UW8L4DGqVbPWc+x2uOWWM9dm2reHv/6yShx8+y20bWvNhj7/3KznVAJKisMJc3zWAg4DnwKfAIcdx0pERM4TkcUiskVENonImPz+RGS+iOxwfNYsrS93Me7XcQT6BTK572Ry7bnc/tXt/LrrVyKDIwkPCmferfNMmhqDobxp1sxyg16+/Mz4HAB/f+t4bCw0bmzNdB57zDKrrVxpfTf4JCXNcD51fMZilcrN3/L3SyMXeFRV22AFjT4gIm2xFk8XqmoLrMJUXonumr9rPt9u+5b/u+T/qBNSh3989w++3PIlTSKakJqdyre3fEuDsAbeEM1Q9ah6r+w332yltpkypfhYm4KznXnzYPx4uPJKq9Db1197Vl5D+VCUr7Q7NqzqoVcA24AYx7EYYFtpbcs7jiAnL0fbvt5Wm01rphnZGfrQjw8pE9HOb3VWJqKfrv+0XO9n8C0o/zicha4cc9fm9Tic4sjMVO3a1bVYm40brbgcsOJ5wsJUd+/2iJiGslPcGHIlDqeXiNRwfL9DRKaISJmCUESkMZYr9XKgjqoecii7Q1iR10W1GSUiq0Rk1bF8N8ly4q1Vb7H52Gb+0/8/vLzsZV5b8RqXNLyEtYfX8nTvp7m1w63lej9D1UREghzm5yhH/Fotx9YYqFdK2wpvkj5nCq7nlLY2067dqdlOaqoVr3PFFZCV5Tl5DeeMK15qbwLpItIJeAzYRxncOB3lDL4ExqqV3sMlVHWmqnZT1W7R0dGuNiuVxPREnln8DJc3vZxdx3fx3NLnuLzJ5fyx/w9uanMTEy+bWG73MlR57sUyQbcGVju+x2LN9l8vpW2FNkmXG2XJnZa/trNmjbUOtGuX9WkyS/sMriicXMcU6TpgmqpOA0Jd6VxEArCUzSeq+pXj8BERiXGcj8HyfPMYE5dMJCkriUsaXsKj8x/l8iaX83f833SJ6cIH13/gLKhmMJwrqjpNVZsA41S1SYGtk6rOKKXtIVVd7fieAmwB6mONww8cl30AXO++J/AQBXOnff556de3awdbtljrOfHxVpLQ6dNPJQA1VFhc+XVNEZEngDuAH0TEDyuJZ4mIFSH5HrBFVacUODUPGO74Phzrbc8jbDy6kTdXvckVTa/guaXP0adxH3Yc30FoYCjf3vKt8UgzuIu3ReQhEfnCsT3oeBlziYpmknYL//43dO9umdauuw42biz5en9/+PFHePNNa/+hh6zg0SNH3C+r4axxReEMBbKAu1X1MNZb1r9daNcLGAb0FZG1ju0qrCy5V4jIDiwnAo9lzX3010epHlCdhbsX0rN+TzJzMzmSdsR4pBnczRtAV8dn/vc3XWlY0UzSbqNaNavq54svwpIl0LGjVYjt9OJtp3PffbBhg5Ue5/ffLRPdZ5+Z2U5FpShPgoq2lYeXzeqDq5WJqP8kf+30Zie97YvblInoZxs+O+e+DZULyt9LbZ0rx4q4JgD4BXikwDGve3m6nYQE1XHjVKtVUw0MVB07VvXo0ZLbJCdbWactVaN63XWqhw97RFzDmRQ3hs5qwUJEZpZ+VcXi1T9fRRAahTfi+tbX8+nGT3mm9zMMbT/U26IZKj95ItIsf0dEmgJ5JTWoiCZpjxEZaZnYduyAYcPgtdesmctzz53KJn06oaHwyy8waZK1P28etGljZjsVjaK0UGkb0PVs2p3tdq5vaAeTD6rfc37KRHTyb5NVJooO/nyw5tnzzqlfQ+WE8p/h9AP2A0uApcBeoE8pbS7GSnmzHljr2K4CIrG803Y4PmuVdn+fm+GczubNqjfeaM1coqNVp02zYniK48cfrdLWfn5WmxtvNLMdD1PcGHJ5hpMfi+NQUrHnoOM8zvQV08nTPFpFtmLyH5M5P+Z8Zl8/23ikGTyCqi4EWgAPObZWqrq4lDZ/qKqoakdV7ezYflQr03Q/VW3h+DzuiWfwKm3awJdfWqlw2reHMWOgdWv46COrxs7pXHmllQS0VSsQsWY7bdtaJRDMbMeruBL4eZGIbMZyy0REOonIG26XrJxIz0ln+orpAKRkpTg90oIDgr0smaGK0RVoD3QChorInV6Wx/fo0cMqX/DLL1bBtjvvhM6d4bvvzlQkzZtbCuqmmyA31zp2221WJuq77rLKWhuPNo/jyiv+f4EBQCKAqq4DertTqPLkw3UfkpqdSq3qtTiYepB3r32X+mH1vS2WoQohIh8Br2KZybo7tm5eFcpXEYH+/WHVKmt9JjMTrr0WLrkE/vij8LUhIVZcz0svwfHj0KCBNdP55hu4/XaoWxc6dYJHH4WffoK0NK88UlXCJZuSqh447VCJC54VBbvaefH3FwHIycvh0kaXcmXzK70slaEK0g3opar3q+pox/aQt4XyaWw2K2Zn82Z46y3YvdtSOtdcY7lJ5yNiZTDIVyhLl8JTT8Hff1uKKDoaXn8drrrKmjVddhm88IJ1Pn9mZCg3XFE4B0TkIkBFJFBExuEwr1V0ftn5C3HJcQT5B5GSncIrl79iKnYavMFGoK63haiUBARYhdt27rQUyO+/W7OWO+8sXKxt4EArmPTyy2HcOGtWc+ONsGABnDgBv/4KDz9secE98wxceCFERcENN1gKads2s/5TDriicO4DHsAK+IwDOjv2KzzPLnkWALvdzo1tbqRng55elshQRYkCNovILyIyL3/ztlCViuBgayaze7dVxmDuXMtp4KGH4Kgje1a9epYDwYcfwqZNlmL6738hMNBKBPrKK1YNnqNHLVPckCGwdq1VRqF1a2jY0Ko6+sknZv3nLBH1Aa3drVs3XbXKlRI8p9h4dCMd3uyAv/hjx86m+zfROqq1myQ0VCZEJFZVy22NRUSKrE+uqkvL6x4lcTbjx+eJj7dict57D4KCrBnNo49CWJh1/uBBa2b0/fdw0UUwaxa0bFl0X7t3WzOhBQssp4XjDsfADh2sGdPll0Pv3taakQEofgyVqnBEpCVWGo46qtpeRDoC16rqC+4R9UzOZsDcNOcmvtr6FTZs3H3+3cy8xudiVQ1eorwVjrepkgonn23b4OmnrRlPZKS1RtO0qZVlukkTWL/eWrPJyrLS6owZA35+xfeXlwfr1sH8+ZYC+v13q62/P1x8sTUDGjwYqlf32CNWRM5F4SwFxgNvq2oXx7GNqtreLZIWQVkHzNG0o8T8JwZVpZp/NXaO3mk80wwu4wmFIyIzVXWUO++RT5VWOPmsWmWZzDZssNZ2CtbesdmsXG4ZGVZOtttvh549LaXUtKnlTFDc2m9GBvz5p6V8vvoKtm+HiAgrQ8KoUVbcUBWkuDHk70LbYFVdcdpie4V233j5j5exqx2AMT3HGGVjqIi87W0BqhTdulmzHLAKvh08aJnKCm7Ll1s1dv7738Jtw8MtxVPU1rAh9OtnbZMnW15wM2fC229bJRMuushSPEOGVPlZD7imcBIceaAUQERuBg65VapzICs3i7dXWWM5vFo4j/d63MsSVX4SExPp168fAIcPH8bPz4/8DMUrVqwgMDDQLfe96qqr+PTTT4mIiCjy/IgRIxg0aBA333yzW+5fVkSkhqqmge9l66hU2GxWTE6DBtbaS0EOHYJ77rFKH7RqZZ0PDLRmRZs2WWs+BauM2mxw3nmnZkNNm1rlFUaOtCqUfvyxlfV67NgqP+sB1xTOA8BMoLWIxAN7gNvdKtU58Hbs26TnpgPw1CVPUbO671bg9RUiIyNZu3YtABMnTiQkJIRx48Y5z+fm5uLv78p/tbLx448/lnuf7sARVvAuEAI0dFTPvVdV7/euZIYziImxlMqnn8Ijj8A771izmHvusb7XrWsppV27zpwhzZt3yiMun7AwK+tBZqblXj19upWqZ/hwq7RCeLh3ntNLlOgW7Si29k9VvRyIBlqr6sWqWkqRCu+gqrz4mxXoWadGHR7s8aCXJaq6jBgxgkceeYQ+ffrw+OOPs2vXLgYOHEjXrl255JJL2Lp1KwDHjh3jpptuonv37nTv3p1ly5ad0dehQ4fo3bs3nTt3pn379vz+++8ANG7cmISEBAA+/PBDOnbsSKdOnRg2bNgZfTz99NOMGDECu93uxqcuFp/O1lHlELHWcQ4csNyjW7a0YnMaNrRid9avh169rJnLpEnWLObPPy1X6ZQUa53om29gyhQrHqhlS8uDLcBRc2/LFsuFOyLCSrUzfrzliOCd/5sepdjXThHxV9VcEekKkG8KqMj8sP0HjqZbbxiT+02mekDVs5mO/Xksaw+vLdc+O9ftzNSBU8vcbvv27SxYsAA/Pz/69evHW2+9RYsWLVi+fDn3338/ixYtYsyYMTz88MNcfPHF7N+/nwEDBrBlS+G44k8//ZQBAwbw1FNPkZeXR3p6eqHzmzZt4sUXX2TZsmVERUVxPN9t1cFjjz1GUlISs2bN8lrgr6oeOO3ePpGto0oTGGh5nA0ebAWWvvuu5T797benZj133QX1C6wRh4RYJrOizGZ2+6nZ0U8/nXIyePVVawsNhQEDrOSjl19u3aOSUZKdYwVwPrDGEaQ2F3AqHVX9ys2ylZnHFjwGQMPwhtzZyeRG9DaDBw/Gz8+P1NRU/vzzTwYPHuw8l+Wwgy9YsIDNmzc7jycnJ5OSkkJoaKjzWPfu3bnrrrvIycnh+uuvp3PnzoXus2jRIm6++WaioqIAqFWrlvPc888/T8+ePZk506tu8YWydWBljPaJbB0GB82bw8svWzOaefMsp4BnnrFq9AwaZK3NDBhQsku1zWYpp/r1rbWhl16ChATLzDZzJhw+bGXF/uIL6/oWLU7F+fTpY3nL+TiuGNZrYZkC+mI5Dojjs0IpnI1HNrIlwRrD0wZOw99W/msGvsDZzETcRY0aVkULu91ORESEc52nIHa7nb/++ovqJXjw9O7dm99++40ffviBYcOGMX78eO6889QLhaoWO3Pp3r07sbGxHD9+vJAi8jD3AdM4la3jV3wkW4fhNAID4eabrW3XLmvW8/77Jc96SiIqylJaEydaMT1vvWV50+XmWspo1ix4801LWfXuDf/4h2XWCwpy62O6i5LWcGqLyCNYeaA2OD43OT43ekC2MvHAj9b4bRnZkutaXedlaQwFCQsLo0mTJsx1uKWqKuvWrQOgf//+zJgxw3ltUUpp37591K5dm3/84x/cfffdrF69utD5fv368fnnn5OYmAhQyKQ2cOBAJkyYwNVXX01KcdUi3YyqJqjq7apaR1Vrq+odqproFWEM5UezZtYs5cABa1bSqtWptZ7rrrM83Yqq11MUIpZC+fRTa6YzZYoVE5SZCTVqQNeuVgXU22+3lNkjj4BjHdSXKEnh+GF51YQAoQW+528VhmNpx/ht/28AvDPoHZOgswLyySef8N5779GpUyfatWvHt99alZFfe+01Vq1aRceOHWnbti1vvfUWAKtWreKee+4BYMmSJXTu3JkuXbrw5ZdfMmbMmEJ9t2vXjqeeeopLL72UTp068cgjjxQ6P3jwYP7xj39w7bXXkpGR4YGnLYyItBSRhSKy0bHfUUT+z+OCGNxDYKBVd+fXX61Zz+OPWzE9V19tZTOYNMlKteMqkZFWItEtW6y4nuuvtxwV4uMt5VO9OkybZnm7XXqpldstM9Ntj1euFFUG1JF9YHVx5zy9lVYi9+bPb1Ymoq1ntC7xOoPBFSj/EtNLgR7AmgLHNpbnPUrafL7EtC+Sna36xReq/ftbZa5tNtVrr1X9/nvV3Nyy95eYqPrZZ6r33KPaqJHVJ6j6+1ufISGq995rleOuABQ3hopNbSMia9SRysbblJSaIzs3m+qTq2NXO2tGraFzTGfPCmeodLgheedKVe1ecEyJyFpV7Vxe9ygJk9rGy+zefWqt58gRK1D0nnvgllusGVC+u7SrqFozqQULrJxuv/4Kqamnztevb1U37dXL9T5tNiudT+3aZZOlGMqcS01EamkFqZde0oAZ/eNoZqycQevI1mx50Dj+GM4dNyicn4AHgbmqer4jW8fdquqRaoBG4VQQcnKscthvv20pCbC82ho2LJypoODmimdaXh6sWQNffw1z5ljK6GwJCIA6dazKqJ07F5brvPNcVo5nnbzTHYjIQCyvHT/gXVV9uaTrixswqkq1F6qRY89hywNbTPkBQ7ngBoXTFCtbx0XACRzZOtRDAdRG4VRA9uyBxYutz/xMBbt2wbFjha+LiChaETVrVrwCSE21ZlT797suT1aWVftn0yZISir6mtOV46OPFlvS4VySd5YrjuwFrwNXYLmIrhSReaq6ueSWZzJp6SRy7Dk0q9nMKBtDhaRgtg4RqQHYVNU77nKGikOTJtZ2OikphZVQ/rZ+vRX/UzDLdb4CKEohDRt2qvZPWdm3z1KG+TWA8r0+IyKse+7bZ82o7r23zF17I1ilB7BTVXcDiMhnwHVAmRXOy39YE6N5t5jiiYaKhy9m6zB4mdBQ6NjR2k7Hbrc81U5XRrt3W3FAp+dxK28SE60tn2XL4Pzzy9SFNxROfeBAgf044IzazyIyChgF0LCYFA/Xtb6OuOQ42tZu6wYxDYZzxm3ZOspqljZUAvIzU593nuUOfTqnz47cEQKQm2vFHe3aBX37lrm5NxROUUEyZywkqepMLLs33bp1K3Kh6bObPytfyQwG91Cu2TrK0yxtqESUNDuqIHhD4cQB5xXYbwAc9IIcBoO7KZitI1/R5HMu3jrlZpY2GDxJieUJ3MRKoIWINHEkMrwFMIswhsqIu7J1FGWWLpS8S0RGicgqEVl17HTPJ4PBS3h8huNYRH0Q+AVrQL6vqptKahMbG5sgIsW5kEYBCeUspqfwZdnBt+UvSfZG5XSPQ6o6qZz6KkipZumCJmkROVbC+IHK++9Y0anMshc5hrySUllVfwRcLteoqtHFnRORVeUZM+FJfFl28G35PSS7u5L6lcksXdL4AfPv6C2qouzeMKkZDFWFfm7q15ilDT5J1SwaYzB4AHelhjobs7TBUBGoDArHq6UczxFflh18W35flr3MZulS8OW/hZHdO5yV7F7JpWYwGAyGqodZwzEYDAaDRzAKx2AwGAwewWcVjogMFJFtIrJTRCZ4W56yICLvi8jR/JLDvoSInCcii0Vki4hsEpExpbeqOIhIkIisEJF1Dvmf87ZM3sKMIe/gy2PoXMePT67hOHJJbadALingVl/JJSUivYFU4ENVbe9tecqCiMQAMaq6WkRCgVjgeh/62wtQQ1VTRSQA+AMYo6p/e1k0j2LGkPfw5TF0ruPHV2c4zlxSqpoN5OeS8glU9TegQlRTLSuqekhVVzu+pwBbOC2tSkXGUXI9vx5vgGPzvbeuc8eMIS/hy2PoXMePryqcUnNJGdyPiDQGugDLvSxKmRARPxFZCxwF5quqT8lfTpgxVAHwxTF0LuPHVxWOSyUODO5DREKAL4GxqprsbXnKgqrmqWpnrJQwPUTEp0wy5YQZQ17GV8fQuYwfX1U4psSBF3HYbr8EPjmXImLeRlVPAkuAgd6VxCuYMeRFKsMYOpvx46sKx+SS8hKORcP3gC2qOsXb8pQVEYkWkQjH9+rA5cBWrwrlHcwY8hK+PIbOdfz4pMJR1VwgP5fUFuBzX8olJSL/A/4CWolInIjc7W2ZykAvYBjQV0TWOrarvC1UGYgBFovIeqwf3fmq+r2XZfI4Zgx5FV8eQ+c0fnzSLdpgMBgMvodPznAMBoPB4HsYhWMwGAwGj2AUjsFgMBg8glE4BoPBYPAIRuEYDAaDwSMYhWMwGAwGj2AUTgVDRCIL+OYfFpF4x/dUEXmjHO8z1ZFxt7jzD4rIyPK6n8HgKcwYqriYOJwKjIhMBFJV9dVy7rcW8KOqXlDCNcHAMlXtUp73Nhg8iRlDFQszw/ERROQyEfne8X2iiHwgIr+KyF4RuVFE/iUiG0TkZ0eeJkSkq4gsFZFYEfnFUYcD4Gbg5wJ9vywim0VkvYi8CqCq6cBeEenh4Uc1GNyCGUPexygc36UZcDVWDZOPgcWq2gHIAK52DJjpwM2q2hV4H3jR0bYXVtGn/De1G4B2qtoReKHAPVYBl3jgWQwGb2DGkIfx97YAhrPmJ1XNEZENgB+n3rY2AI2BVkB7YL6VKxA/4JDjmhjgmON7MpAJvCsiPwAF8yIdBVq78RkMBm9ixpCHMQrHd8kCUFW7iOToqcU4O9a/qwCbVPXCItpmAEGO9rmOKX8/rIzBDwJ9HdcFOa41GCojZgx5GGNSq7xsA6JF5EKw6m+ISDvHuS1Ac8fxECBcVX8ExgKdC/TREtjoKYENhgqGGUPljFE4lRRHnfqbgVdEZB2wFrjIcfoH4DLH91Dge0e68aXAwwW66QUs8IS8BkNFw4yh8se4RVdRROQPYJCjal9R57sAj6jqMI8KZjD4CGYMlR2jcKooItITyFDV9cWcvwLYoap7PSqYweAjmDFUdozCMRgMBoNHMGs4BoPBYPAIblU4IhIhIl+IyFYR2SIiF4pILRGZLyI7HJ813SmDwWAwGCoGbjWpicgHwO+q+q6IBALBwJPAcVV9WUQmADVV9fGS+omKitLGjRu7TU6DoSCxsbEJqhrtbTnKCzN+DJ6muDHktsBPEQkDegMjwOlimC0i13HKnfADYAlQosJp3Lgxq1atcpeoBkMhRGSft2UoT8z4MXia4saQO01qTbFSP8wSkTUi8q6I1ADqqOohAMdn7aIai8goEVklIquOHTtW1CUGg08gImNEJEws3hOR1SLS34V2xiRtqFS4U+H4A+cDbzrSc6cBE1xtrKozVbWbqnaLjq401g1D1eQuVU0G+gPRwEjgZRfaTQN+VtXWQCes6PYJwEJVbQEspAxjqkiys8+pucFQFtypcOKAOFVd7tj/AksBHclP8e34POpGGQyGQtjtdg4mHWRnwk5P3lYcn1cBs1R1XYFjRTc4ZZJ+DyyTtCPA8DosUzSOz+vPWqrly9HzzsO+fHnp1xoM5YDb1nBU9bCIHBCRVqq6DSux3WbHNhzrDW848K27ZDD4HqpKbm4umZmZ5OXllaltXl4eubm5pGamsvfkXvac3MO+5H3sS97HgdQDxKXFEZ8eT0ZeBhdGX8if9//ppqc4g1gR+RVoAjwhIqFYCSJLoqBJuhNWKvwxnGaSFpFiTdLAKICGDRsWfYc2bdCsLNKffpqQX38t+1MZDGXE3dmiRwOfODzUdmOZEmzA5yJyN7AfGOxmGQwVEFUlJyeHzMxMMjIySE9PJyMjg30n97H86HK2p2ynLB6UablpToVyNLPwpLmarRr1a9SnQXADukd1p35wfZqHNi/vRyqJu7ESOu5W1XQRicQaCyWRb5IerarLRWQaZTRJAzMBunXrVvQfMiwMRo8m5IUXSF+xguAepk6Ywb24VeGo6lqgWxGn+rnzvoaKRU5OTiGlkp6eTlZWFgApOSmsTFjJimMrWJ6wnP1p+wGo7ledAFuAy/cI8guifnB9ekT1oH5w/UJbdPVoRARVpXr16tSoUYOwsDC3PGsxzFdV5/95VU0Ukc8peRwUZZKegMMk7ZjdnLNJ2jZ2LPYpU8h9/nn47rtz6cpgKBVTD8dQbtjtdjIyMpxKJS0tjczMTFQVm82G3W4nKzeL9SfWszxhOSsSVrDl5Bbs2KnuV52ukV25udHN9IjqQbPQZjiKXpUJm82GqiIiVK9enZCQEGrUqEFwcDCBgYFn1efZIiJBWLFnUQ5vsvybhwH1SmrrMZN0ZCT2e+8ldNo0UteuJaRz53PqzmAoCaNwDGdFbm4uqampTsWSkZFBTk4ONpvlh2K3W0sUdrWzPXk7KxJWsCJhBWsS15Blz8JP/Ggf0Z67W9xNz+ietIto55zR2Gw2/P39CQoKKpNMwcHBTuUSEBDgUeVSDPdi1Ueph7UGky9QMvC6C+09YpL2Hz8e++uvk/PCC+jcuRXh72aopBiFY3AZu93OyZMnSUhIIDU1FRFxKpaC18Snx7Pi2AqnkknKSQKgaWhTbmx0Iz2ietClVhdCAkKc7Ww2GyJCrVq1iIqKIjg42KPP5g5UdRowTURGq+r0s2i/Fk+YpGNiyB0+nPBZs0jZvJmwdu1Kb2MwnAVG4RhKRFVJTk4mISGBpKSkQkomf1H/ZPZJViWscprJ4tPjAYiuFs0ldS6hR1QPukd1JzqocDxVvvkrLCyM2rVrExoaWinfrlV1uohcBDSmwJhT1Q+9JtRpBD71FDprFtkvvYR+9FGl/HcweJ9SFY6I9ALWqmqaiNyB5TkzTVUrVfoPwylUlbS0NBISEjhx4gRAISWTY89hzfE1LD9mKZitSVtRlBr+Nega2ZVbm9zKBdEX0KhGozN+uPL3q1evTnR0NDVr1sTPz8+zD+hhROQjoBlWxch8X28FKozCoVEjsgcPptYXX3Dy6aep2aqVtyWqsuzdu5eBAwdy8cUX8/fff9OpUydGjhzJs88+y9GjR/nkk09o164do0ePZsOGDeTm5jJx4kSuu+469u7dy7Bhw0hLSwNgxowZXHTRRSxZsoSJEycSFRXFxo0b6dq1Kx9//LHHXyxcmeG8CXRyxAI8hhWI9iFwqTsFM3gWVSUjI4PExEQSExNR1ULmstScVP489idLDy9l2dFlpOam4i/+dKzZkXtb3kuP6B60DW+Lv63o/1I2mw0/Pz+ioqKIiooiMDDQU49WEegGtNUKXnwq8Jln4LPPyPnXv9B33zWznLFjYe3a8u2zc2eYOrXUy3bu3MncuXOZOXMm3bt359NPP+WPP/5g3rx5TJ48mbZt29K3b1/ef/99Tp48SY8ePbj88supXbs28+fPJygoiB07dnDrrbc68+itWbOGTZs2Ua9ePXr16sWyZcu4+OKLy/f5SsEVhZOrqupIujlNVd8TkeHuFszgfvJnMsePH+fEiRPY7fZCSuZoxlF+O/IbS48sZWXCSnI1l5qBNekb05dL61xK96juBPsXv9ZScF0mMjKS4ODgqvojthGoCxzytiAlIa1bk3nNNUTOmcPxJ54gsrlHY5UMBWjSpAkdOnQAoF27dvTr1w8RoUOHDuzdu5e4uDjmzZvHq6++CkBmZib79++nXr16PPjgg6xduxY/Pz+2b9/u7LNHjx40aNAAgM6dO7N3794KqXBSROQJ4A6gt4j4Aa4HSBgqFHa7neTkZI4fP05SUpLzGFgKaHfqbpYcXsLSw0vZnLQZgPOCz+PWJrdyad1L6VCzA35SvAksf10mIiKCqKioSrsuU0aigM0isgLIyj+oqtd6T6SiCXj2WfzmzSP7v//FPn260+uwSuLCTMRdVKtWzfndZrM59202G7m5ufj5+fHll1/S6jTT58SJE6lTpw7r1q3DbrcX8vQs2Kefnx+5ublufoozcUXhDAVuA+52xAY0BP7tXrEM5Ulubi5JSUkcP36clJSUQgv/6bnprE5czYqEFfx25Dfi0uMAaBfRjgdaP8CldS6lSUiTEpVGvpIJDQ0lKiqK8PDwqv1DdSYTvS2Aq/idfz4Z/foR/cknJI4bR3STJt4WyVAEAwYMYPr06UyfPh0RYc2aNXTp0oWkpCQaNGiAzWbjgw8+KHN6KHfjisJ5uGCBNFXdLyLGb7KCk5OTw4kTJ0hMTCQjI8OpZHLtuWw6ucnpsrz+xHryNI9AWyDdIrsxrNkwetfpfYZH2enkK5mqtPh/tqjqUm/LUBb8nnkG/0svJXv6dOyvvmpeHiogTz/9NGPHjqVjx46oKo0bN+b777/n/vvv56abbmLu3Ln06dOHGjVqeFvUQpRa8VNEVqvq+acdW6+qHd0qWQG6deumpoBU6eTl5XHixAkSEhJIT08HLHPZntQ9rEiwUsesTlxNWm4agtAmvA09onrQI7oHHWt2JMiv+EBLEXHOckJDQ6lZsyZhYWEEBFQ+66qIxKpqUfEvZ9tfCpZXGkAglkk6TVU9kl/nbMZP+oUXErBjBwkrVxJjZjmGMlLcGCp2hiMi/wTuB5qKyPoCp0IBj6XZNZRM/ppMQkICycnJiAjpOen8duQ3/jjyBysSVpCQlQBYazED6w+kR1QPukV2IzwwvMS+82cxwcHBREREEB4eTlBQkFmTKSOqGlpwX0SuByp0pkz5v/8jYNAgct95h7znnzezV0O5UJJJ7VPgJ+AlCmepTVHV426VylAiRcXJZOdmszJhJT/F/8SSw0tIz0snIjDCmsE4tnrBJabvciqYwMBAIiIiCAsLIyQkxJhUyhlV/UZEzq1wmpupftVVpHfqRO3Zszn0j3/QwMxyDOVAsQpHVZOAJOBWh2daHcf1ISISoqr7PSSjwUFmZibHjh3j+PHj2O128vLy2HRyEz/F/8T8g/M5nn2c0IBQ+tfrz8D6A+kS2aVYj7J8E5mqUq1aNUJDQ52bv79JQFGeiMiNBXZtWHE5FTomBxHsEyYQfOut5H30ETlPPFEpzacGz+JKpoEHsbxsjnCqaJQCHlvDqerk5OQQFxfHiRMnUFX2pu7l5/if+Tn+Z+LS4wi0BXJJnUsYWG8gvWr3ItDvzKDK/NmLn58fNWrUIDQ0lJCQEKpXr25mMO7nmgLfc4G9WJU7KzQ1hgwh49lnqfP++xwaNoyGZpZjOEdceZUdC7RS1UQ3y2I4DbvdzpEjRzh8+DAnMk/wfdz3/Bz/M1uStiAI3aO6c1eLu+hbt2+hRJhQ2IssX7nUqFHDvKV6AVUtrdhahURsNrIefZSIe+8l9/PPyX744aqWIcJQzriicA5gmdYMHkJVSUpKYv/+/eTl5bEwfiEvbXiJ49nHaRPehofbPkz/ev2LTYZZo0YNoqOjiYiIMLOXCoCINACmA72wrAN/AGNUNc6rgrlA6IgRZL70EnXff5/4wYNp0rSpt0Uy+DCuKJzdwBIR+YHCUdJT3CZVFSYjI4N9+/aRkZHB8czj/Gvjv/j14K+0CmvFaz1fo3V460LX53uMBQUFOeNhzBpMhWMWlhNOfu2aOxzHrvCaRC7iFxjIyQcfJHLcOPK++46s++4rFLFe2Vm3bl25RuT7+/vTqVOnMrebOnUqo0aNKrJsx+zZs1m1ahUzZsxwub8RI0YwaNAgbr755jLLci648vq7H5iPFT8QWmAzlCO5ubns27ePLVu2kJaWxvz4+QxeMphFhxZxX6v7+ODiDwopG5vNRmBgIDExMbRv3562bdsSHR1tlE3FJFpVZ6lqrmObDZQcWVuBCL3vPrJiYqj7/vvEHTjgbXE8Snmnfznb/qZOneqMrfNlSv11UtXnPCFIVUVVOXbsGPHx8aiqc1Yz/9B8Woe35s0L3qR5mJVE0WazYbPZnEXKqlev7mXpDS6S4Cjt8T/H/q2Az6yJBtaowdF776X2xIkcXLiQ9Hr1KkWBvIpIWloaQ4YMIS4ujry8PJ5++mmOHDnCwYMH6dOnD1FRUSxevJhZs2bx0ksvERMTQ8uWLUuddaoqo0ePZtGiRTRp0sRZywogNjaWRx55hNTUVKKiopg9ezYnT55k+PDhrFixArBKJlx77bWsX7++uFu4hCteaospwoVTVfue050NJCcns2/fPnJzc7Hb7Sw4uICXN75Mak4q/2z1T4Y3G+5M9y8i1K9fn+joaBN46XvcBcwA/os1lv50HPMZajz4IDkzZlD3/ffZccEFtGnTxjgQuIGff/6ZevXq8cMPPwCQlJREeHg4U6ZMYfHixURFRXHo0CGeffZZYmNjCQ8Pp0+fPnTp0qXEfr/++mu2bdvGhg0bOHLkCG3btuWuu+4iJyeH0aNH8+233xIdHc2cOXN46qmneP/998nOzmb37t00bdqUOXPmMGTIkHN+PlfsL+MKfA8CbsJy7TScJRkZGezfv5/09HTsdjvHs47zysZXWHhoIW3C2/DsBc86ZzUigr+/P82bNzdvlT6KI2atwmWGLgs1IiM5PHIkdf/9b0J++YWtIrRt29aYcMuZDh06MG7cOB5//HEGDRrEJZdccsY1y5cv57LLLiM62rLKDh06tFAZgqL47bffuPXWW/Hz86NevXr07WvNF7Zt28bGjRu54gprOTEvL4+YmBgAhgwZwueff86ECROYM2cOc+bMOefnc8WkFnvaoWUi4nIyQkfQ6CogXlUHiUgtYA5Wud29wBBVPeGyxD5MTk4O8fHxHD9+HFVFVZl/aD6vbHiF9Lx0Hmj9AMOaDnPOamw2G6GhoTRp0sSkFvFBRORfwG5Vfeu04w8DdQsmxfUFqj36KGk//UTjSZPY3KoV2/z8aN26tfm/WY60bNmS2NhYfvzxR5544gn69+/PM888c8Z1Z2PlKKqNqtKuXTv++uuvM84NHTqUwYMHc+ONNyIitGjRosz3PJ1SnQZEpFaBLUpEBmAVk3KVMcCWAvsTgIWq2gJYSOG0OZUSu93OwYMH2bhxo1PZnMw+yWOxj/Hk6iepH1yfjy/5mJHNR55hQmvWrJkZ0L7LIGBmEcenAVd7WJZzJqJ2bfa98gpqs9F0wgSyk5PZsWNHoaJ9hnPj4MGDBAcHc8cddzBu3DhWr14NWAlzU1JSAOjZsydLliwhMTGRnJwc5s6dW2q/vXv35rPPPiMvL49Dhw6xePFiAFq1asWxY8ecCicnJ4dNmzYBOH97nn/+eYYOHVouz+fKfDgWy+4sWKa0PcDdrnTuiD+4GngReMRx+DrgMsf3D4AlgE+96bmKqpKYmEhcXBx2u925ULcnZQ9jV47laOZRHmz9IHc0vaOQojEmtEqDquoZv8aqahcfXIgTEWr36MG+SZNo9vDD1P/vf4mbMIFdu3bRvHnzSrm26O/vX+5u0SWxYcMGxo8fj81mIyAggDfffBOAUaNGceWVVxITE8PixYuZOHEiF154ITExMZx//vnOujfz5s1j1apVTJo0qVC/N9xwA4sWLaJDhw60bNmSSy+9FIDAwEC++OILHnroIZKSksjNzWXs2LG0a2dVoBk6dCjjx49nz5495fL8pZYnOKfORb7ASv4ZCoxzmNROqmpEgWtOqGrNItqOAkYBNGzYsOu+ffvcJqc7SElJYd++feTk5BR6A/z72N9MiJ1AoC2Q/3T/Dx1qdnCeMya0ikF5lScQkZXAbaq647TjLYD/uXKP8jBJl2d5D1Vl27Zt1HzhBep88gm7X3qJk/37U7NmTRo3blwplY6h7BQ3hlwxqQWIyEMi8oVje1BESs2PIiKDgKNFrAG5hKrOVNVuqtotf3HMF8jMzGT79u3s2LGDrKysQspm7t65jFkxhrrV6/LBxR8UUjbGhFYpeQb4SURGiEgHxzYS+MFxzhUqlElaRGjSpAnxo0eT2qEDjV54gcB9+zh58iRxcRU+cYLBy7gS+Pkm0BV4w7F1dRwrjV7AtSKyF/gM6CsiHwNHRCQGwPF59CzkrpAcPXqUzZs3k5KSUsjPPdeey783/ptXNr7CRdEX8V6v94gJtjxB8k1orVu3pnbt2uYNsRKhqj8B1wN9gNmO7TLgJlX9sbT2BUzS7xY4fB2WKRrH5/XlJK7LVKtWjZiGDdnz0kuonx9NJ0xAMzJISEjg0KFDnhbH4EO4onC6q+pwVV3k2EYC3UtrpKpPqGoDVW0M3AIsUtU7gHnAcMdlw4Fvz1L2CkVaWhpxcXGcbqJMzUnl4ZUPM2fvHO5oegevdn+VGv5W2VcRITQ0lPbt25v1mkqKqm50jJ+ujm24qm5wsflU4DFOZWkHqKOqhxx9HwJqF9VQREaJyCoRWXXs2LFzeYQiqVu3LtKoEXufe47g7ds5b8oU7HY7hw4dIiEhodzvZ6gcuKJw8kSkWf6OiDQF8s7hni8DV4jIDqxcUi+fQ18VgtzcXHbu3HmGsolLi+OuZXexImEFT3V4irFtxzrr04gIYWFhNG/e3JjQDGdQ0U3S+aa15N69OTxsGNFffknNn39GVdm/f7+zMKDBUBBXvNTGA4tFZDeWp1ojoEzp1lV1CZY3Go4yB/3KJGUFRlXZvXu300skn7XH1zJu1Tjsauf1nq/TLerU+pmIUL16dZo2bWpMaIbiyDdJX4UVcB1W0CStqoe8bZKuUaMGkZGRHHzgAULWraPR5Mmkt2lDVqNG7NmzB39/f0JDTdpFwylKneGo6kKgBfCQY2ulqovdLZivcOTIEdLS0grNbr6P+55//v1PwgLCmN1rdiFlAxAQEECLFi1M6YAqgsOz7PRjJVYz8xWTdIMGDfALCmL35MloQABNJ0xAMjNRVXbu3FkpEk4ayo9if/FE5A4RGQagqlmqul5V1wF3ishtHpOwApOWlsbBgwednmh2tfP61teZuHYinWt2Znav2TQMaViojZ+fH61atTIpQaoW34lIWP6OiLQFvjvLviqUSdrPz49GjRqRV68eeyZNInjHDs77z38AK+B5+/btZGRkeFNEQwWipFfsR4Fvijg+x3GuSnP6uk1WXhaPxz7OrJ2zuKHhDUzvOZ2wwLBCbWw2G61atTJJD6sek7GUToiIdAXmYtXEcQlVXaKqgxzfE1W1n6q2cHwed5PMLhMREUFoaCjJvXpxaMQIor/+mlo//QRYubm2bt1qZjoGoGSF46eqKacfVNVkoErXKVZV9uzZ41y3saudiesmsvjwYh5u+zBPdnjSmTkgHxGhefPmpqRAFURVf8DKFP0rlmv09aq61psylTeNGjXCZrNx8L77SOncmYaTJ1Nt717Amuls27aNtLQ07wpp8DolKZwAEalx+kERCcUqxlZlOXbsGKmpqc7ZzRtb32D+wfmMbj2a25vefoYjgIjQqFEjs4BaxRCR6SLymoi8BvQFwrBSQ412HKs0BAQEcN5552ELDGTP5MnYq1Wj2eOPI5mZwCnzWmpqqpclNXiTkhTOe8AXItI4/4Dj+2eOc1WS9PR0Z240gK/2fcXsXbO5qdFN3NnszjOuFxHq1atHZGSkp0U1eJ9VWLkI87d/A18W2K9UREZGEhQURE7t2ux9/nmq79pFw1deAceLmd1uZ8eOHSQnJ3tZUoO3KHblWlVfFZFUYKmIhGAl8EwDXlZVVzINVDry8vIKrdssO7rMmT1gfLvxRc5sIiMjqVu3LMm1DZUFVf0AwGEpyFTVPMe+H1ByiUYfJD82Z/PmzSRfeCGH7r6bmPfeI7NpU44MGwZYSmfXrl00adKEiIgI7wps8Dgl+uWq6luq2ggr9qaJqjaqqsomf90mP3PstqRtPBH7BM1Dm/NS15eKXLMJCwujYcOGRXVnqFosBAou3lUHFnhJFrcSFBRkZSEQ4eC993L88stpMG0aEQtOPa7dbmf37t0mOLQK4lIgiKqmFuVAUJU4duyYM0fakYwjjF0xltCAUKb2mOpMVVMQE9hpKECQqjoXLxzfK20uo5iYGAICAsBmY+/EiaR27EiTZ56hxrp1zmvyX+ASExO9KKnB05jIQxcouG6TmpPK2BVjSc9LZ1qPaUQHnZk2JDAw0AR2GgqSJiLn5+84XKMrbXCKiDhftjQoiJ1TppBdpw7NH3mEagcOOK9TVfbt22dyr1UhzuoXUUQqnf25OAqu2+Tac5mwegK7U3fzStdXaB7W/IzrTWCnoQjGAnNF5HcR+R0rlu1B74rkXvLT3ogIeRER7Jw2DYDmDz2E38mTzuvyc68dPVppksYbSsCVejjvn7YfApSaWr0yUHDdRlV5ecPL/H3sb57s8CQXRF9wxvX5ysYEdhoKoqorgdbAP4H7gTZnm5TTl2jQoIEzMW1Ww4bs/M9/CDxyhOaPPopkZTmvU1Xi4uI4fPiwt0Q1eAhXZjjxIvImgIjUxApe+9itUlUQEhMTnes2s3bO4psD33B3i7u5ruF1Z1zr5+dH69atTWCnwYmI9HV83ghcA7TEykt4jeNYpcbPz6/QOmZa587smTSJkHXraDxxIhQoTqiqHDx4kIMHD3pJWoMncCV559NAsoi8haVs/qOqs9wumZfJycnhwIED2O12fo7/mTe2vcGV9a/kvpb3nXGtv78/bdq0ISgoyAuSGiowlzo+ryliG+QtoTxJaGgodevWda5nnrz8cuIeeoha8+dT//XXC12rqhw5coQjR454Q1SDByh2oeG0N7AVwNOOTxWRG1X1K3cL503279+P3W5ndeJqnlv3HOfXOp+nOz59htdZQEAArVu3NmY0wxmo6rOOzzKV86hsxMTEkJyc7Extc2TYMKrFx1P3gw/IqlePhJtucl5rt9uJj48nMDCQmjVrektkg5soaYZz+tvYGqwcapX+7SwpKYnk5GT2pu5l3Kpx1A+uz6vdXiXQr7BSCQwMpE2bNkbZGEpERMaISJhYvCsiq0Wkv7fl8hQiQrNmzU4VGhRh//jxJPXqRcNXXiHsjz8KXa+q7N2716TBqYQUq3BUdWQJ212eFNKT5OXlsXfvXk5knmDMijH4iz/Tekw7I/NztWrVaNOmjRVvYDCUzF2OpLf9sUpCj6QSVLotCwEBATRr1uyUhcDfn90vvURGixY0feIJqm/dWuj6/DQ4mY5cbIbKgSteah+ISESB/Zqne65VJuLj48nNzeW5dc9xJOMI/+n+H+oH13eeFxGCgoJo3bq1cX02uEq+HfYqYJajrlSViwjOX8/JVzr24GB2Tp1KXlgYzR9+mIDTvNTys0zn5OR4Q1yDG3DFS62jqp7M31HVE0AXt0nkRdLS0khISODjXR/z25HfGNNmDB1qdnCeN8rGcJbEisivWArnF0fGdXspbSolMTExBAefSrKQEx3NjmnT8EtPp8WYMdhOM6Pl5uaybdu2M0q4G3wTVxSOzeEODTjL5Va6X9v8mJt1x9cxfet0+tTtwy1NbnGeFxGCg4Np1arVKVu0weAadwMTgO6qmo5V3sPpSCAi7bwlmKc5Yz0HyGzenF3/+hdBe/fS/OGH8UtKKtQmOzubHTt2ODO0G3wXVxTOf4A/ReR5EXke+BP4l3vF8jyHDx/mWNoxnoh9grrV6/JMp2ecU38RoUaNGrRs2dIoG0OZUVW7qq7OtxQ4qnauL3DJR96RzDsEBASckWcwpWdP9jz/PDU2bqT1yJFU27fPeU5VSU9PZ+/evc5M7QbfxJU4nA+Bm4AjwFHgRlWtVAMkKyuL+IPxPLP6GY5nH+el818iNMAqliYihIaGmtxoBndS5dZzwsLCqF27dqExdaJ/f7a/+SZ+ycm0HjGC0BUrnOdUlZMnTxIfH+8NcQ3lRLG/oCIS5visBRwGPgU+AQ47jlUK8k1pH+36iD+O/sHYNmNpG9EWOFVioHnz5kbZGNxJlXxtr1+//hnB0mmdO7P1gw/IiY6mxejRRH11KtxPVTl27JjJu+bDlPQr+qnjMxarcmH+lr9fIiJynogsFpEtIrJJRMY4jtcSkfkissPx6dXorsTERP6K+4vXt75Ov5h+DGk8JF9+atSoYUoMGAxuQkRo3rz5GWbq7Pr12fr++yT37EmjyZNpMGUKOJwG7HY7cXFxppaOj1JSHM4gx2cTVW1aYGuiqk1d6DsXeFRV2wAXAA+ISFusxdOFqtoCqzDVhHN/jLMjNzeX9TvXMyF2AjHVYwplEggKCjJmNIOnyPa2AN4iICCAJk2anPFSZw8JYeeUKRy55RbqfPopzR591OnBZgJDfRdX4nB6OUrkIiJ3iMgUESm1jKWqHlLV1Y7vKcAWoD5wHfCB47IPgOvPUvZzZs/ePTy9+mlOZJ/g5a4vExIQAlgZBFq2bGmUjaFcEJGFJR1T1TNTj1chwsPDz1jPAcDfn7hx49g3YQLhf/1F67vvJtCR3NMEhvomrvyivgmki0gn4DFgH2X0qhGRxlixO8uBOqp6CCylhBV5XVSbUSKySkRWHTt2rCy3c4nk5GRei32NP4/9ySNtH6F1eGvASsRp4mwM5YGIBDnWO6McAdO1HFtjoF4pbX3CJF1eFLWek0/CzTezY9o0Ao4cofWIEdRYbzn42e12tm7damY6PoQrCidXLV/E64BpqjoNCHX1Bo76OV8CYx3pPVxCVWeqajdV7RYdfWZVzXPBbrfz5coveXPbm1xR7wpubnQzcKrEgElXYygn7sVa82wNrHZ8jwW+BV4voR34gEm6PMmPz/H39y9yzTTlggvYOns2ecHBtLzvPmr+/DNgpaLavn07hw8fNi7TPoArCidFRJ4A7gB+EBE/rCSepSIiAVjK5pMC2aWPiEiM43wMlqu1R1m3cx2Pr3qcetXr8VSHpxARbDYbLVu2pFq1KlPM1OBmVHWaqjYBxjnWPvO3Tqo6o5S2Fd4kXd4EBgbSvn17ateuXaTSyWrcmK2zZ5PWvj1N/+//iHnrLbDbUVUOHTrEjh07yM3N9YLkBldxReEMBbKAu1X1MNZ/+n+X1kis/zHvAVtUdUqBU/OA4Y7vw7He9jxGaloq9y+4n6TsJOe6jc1mo0WLFoVSbhgM5cjbIvKQiHzh2B50vIy5REU0SbsLPz8/GjRoQPv27alZs+YZiicvIoIdr79OwrXXUu/dd2n2yCMEHDuG3W4nNTWVTZs2OcsgGCoe4q5pqIhcDPwObOBU3qgnsQbN50BDYD8wWFWPl9RXt27ddNWqUj2xS0VVGfPlGKZvms4THZ7gpkY3ISI0bdqUiIiIc+7fUDkQkVhV7VaO/b2LZRXIn5kMA/JU9R4X2oYAS4EXVfUrETmpqhEFzp9Q1RLXccpr/HiD9PR09u/fT0ZGRuHUNqpEz5lDg+nTsQcGcuDRRzl+9dUggohQr1496tSpY0IavERxY+isVsZFZKaqjirpGlX9g+IjqPudzX3Ple82fMfrm15nQL0B3NjwRkSERo0aVVplM/bnsaw9vLZc++xctzNTB04t8Zq9e/cycOBALr74Yv7++286derEyJEjefbZZzl69CiffPIJ7dq1Y/To0WzYsIHc3FwmTpzIddddx969exk2bJjzLXXGjBlcdNFFLFmyhIkTJxIVFcXGjRvp2rUrH3/8sa/8oHRX1U4F9heJyLrSGpVkklbVQ94ySXuS/PyFycnJ7Nu3j7y8PEvxiHDslltIvugiGk2aRJOJE6k1fz77nnqKnNq1OXToEMnJyTRt2tQ4AFUgztbv9+1ylcIDZOdlc98v99GgRgOe7Pgkfn5+1KtXj8jISG+LVinZuXMnY8aMYf369WzdupVPP/2UP/74g1dffZXJkyfz4osv0rdvX1auXMnixYsZP348aWlp1K5dm/nz57N69WrmzJnDQw895OxzzZo1TJ06lc2bN7N7926WLVvmxScsE3ki0ix/R0SaAiWmP66oJmlvICKEh4fToUMH6tevj5+fn/NFI6thQ7bPnMn+ceMIXbWKtkOGEPndd9jz8oyJrQLisuoXkRqqmgagqrHuE8k9vLPiHQ6lH+K1Hq8RGhhKdHQ0devW9bZYbqW0mYg7adKkCR06WKUd2rVrR79+/RAROnTowN69e4mLi2PevHm8+uqrAGRmZrJ//37q1avHgw8+yNq1a/Hz82P79u3OPnv06EGDBg0A6Ny5M3v37uXiiy/2/MOVnfHAYhHZjTXrb0SBbNHF0AvL9LZBRNY6jj2JVbjtcxG5G4dJ2i0SV0BEhNq1axMZGcmhQ4c4evSo5Zlms1mznV69aPT88zR+7jlq5s926tRh27ZtxsRWQShV4YjIRcC7QAjQ0BGPc6+q3u9u4cqLXHsu//7z37QJb0OvOr2oWbMm9evXL72h4awp6O1ns9mc+zabjdzcXPz8/Pjyyy9p1apVoXYTJ06kTp06rFu3DrvdXig2o2Cffn5+PuORpKoLRaQF0ApL4WxV1axS2lQ4k3RFId+xoHbt2hw4cICkpCRUlazzzmP7W28R/fnn1J8xg3ZDhnDgkUdIvPZaDh06REpKCk2aNDEmNi/iikntv8AAIBHAUa2wtzuFKm8+Xfcp+1L3MbL5SIKDg2nUqJF50/EyAwYMYPr06c7YiTVr1gCQlJRETEwMNpuNjz76qDIV3uoKtAc6AUNF5E4vy+PzBAYG0qxZM1q2bElQUJCVqcAx29n82Wekt2pF4+efp/lDD+F38CApKSls2LCBPXv2kJKSYuJ2vIBLaziqeuC0Qz7zK2BXO5N/m0zTkKb0ielDw4YNjbKpADz99NPk5OTQsWNH2rdvz9NPPw3A/fffzwcffMAFF1zA9u3bqVGjhpclPXdE5CPgVeBioLtjKzcvuKpOSEgIbdu25bzzznOu72Q3aMD2t95i/2OPEbJ2Le2GDqXW119jz8vj+PHj7Ny5k3Xr1rF//37S09ON8vEQpbpFi8gXwBRgBlbE80NAN1W9pcSG5ci5uHV+vflrbpx7I5M6T+KWtrfQokWLcpbOUNlwg1v0FqCteulXzZfdostKXl4eBw8e5NixY04lEhgXR+Pnnyc0NpasmBiODxzI8YEDyWxm+XHYbDb8/PyIiooiMjLSBH+XA+fiFn0fMA0r4DMO+BV4oHzFcw+qyqQlk6gfXJ8B9Qc4F5wNBg+zEagLHPK2IJUdPz8/zjvvPGrXrs3+/ftJTU21ZjtvvknN+fOJ/P576n74ITGzZpHesiXHBwzg+IAB5NSty+HDhzl8+DDVqlUjOjqaWrVqmfWecqbUv6aqJgC3e0CWcmf+rvmsPbaWJzs8SWTNSKpXr+5tkQxVkyhgs4iswMraAYCqXus9kSo31apVo0WLFs74ndzcXE4MGMCJAQPwT0yk5vz51Pr5ZxpMn079GTNI7dKF4wMHcqJfPzLDw4mPjycuLo6goCBCQ0MJCQkhJCTE5Fk8R1wxqbXEyhhdR1Xbi0hH4FpVfcETAsLZmwQufvdidiTu4Nu+39KlYxczVTa4hBtMapcWdVxVl5bXPUqiKpnUiiK/Umh8fDyqWmi9ptqBA9T85Rcif/qJoH37sPv7k9yrF8cHDuTkJZegDi9Jm82GqmKz2ahRo4ZTCQUHB5syJkVwLia1d7DiCN4GUNX1IvIp4DGFczYs27+MZfHLeKTtI9SNrmuUjcFreEqxGIomP36nVq1aJCQkkJCQQHZ2ttOV+vA993D47rupvm0bkT/9RM1ffiFi6VLygoNJ6daN5B49SOnZk8zGjclTJTk5mZSUFEQEVSUwMJDQ0FCnEgoMDPT2I1dYXFE4waq64jTPrgofADFpySQiAiO4sdGNJubGUOFwJT2UoXzx9/enbt261K1bl4yMDI4fP05CQgJ2ux273U5G69bEtW5N3EMPEbp6NTXnzyd0xQoifvsNgOzoaFJ69LAUUI8e5DjKpmRlZZGVlcXx48dRVfz9/QkPDyc8PJzQ0NAzSmhXZVxROAmOtBwKICI3U8EXP1cfWs2ve37l/lb30zCmobG7GioiPpceqjJRvXp16tevT7169UhLSyMxMZHjx60cwnYgpXt3Urp3ByAwPp7QlSsJW76csGXLiPzhBwAymjZ1Kp+U88/HHmJVDM7JySEhIcGpgIKCgoiIiCA8PJzg4OAqHZbhisJ5AJgJtBaReGAPFdyJ4IWlLxDiH8KQJkOIiYnxtjheZd26deUake/v70+nTp1Kv/A0pk6dyqhRo4osATF79mxWrVrFjBkllogpxIgRIxg0aBA333xzmWXxFr6eHqoyIiJOh4CGDRuSnJxMQkICSUlJiAh2u53s+vVJrF+fxOuvB7ud6jt2ELZiBaHLlxP99dfU+ewz1M+PtPbtOdm7NycvvZSsxo2d2a0zMjLIyMjgyJEjANSoUcOpgKqaqb9EheMotvZPVb1cRGoANkcxqArLlmNb+GbbN4xsPpLmDZpXebfG8k7/crb9TZ06lTvuuKNK1hyqDOmhqgL5SULDw8Ox2+2cPHmSxMRE53qN3W4Hm42MVq3IaNWKI8OGIVlZ1NiwgbDlywn/808aTJ9Og+nTyWjcmKRLL+XkZZeR1q4d2GxOBZSSkkJqaipxcXEEBAQ4XbCrwtpPsb/GIuKvqrki0hUg/82sojP598lU86vG7c1ur/TJOSsiaWlpDBkyhLi4OPLy8nj66ac5cuQIBw8epE+fPkRFRbF48WJmzZrFSy+9RExMjEuVVlWV0aNHs2jRIpo0aVLI0yg2NpZHHnmE1NRUoqKimD17NidPnmT48OGsWLECsEomXHvttaxfv96tz18M+emh5jmeZZ2I+FR6qKqGzWajVq1a1KpVC7vdTnJyMsePHycpKQnAqTy0WjVSu3UjtVs3Dj7wAAGHDxOxdCkRS5dS5+OPqfvBB+RERjpnPindu6PVqjn//2ZnZ3Pw4EEOHjxIUFAQ0dHR1KxZs9K+KJf0VCuA84E1IjIPmAs4lU6B+hwVht0ndvO/jf9jaOOhtGnUxizWeYGff/6ZevXq8YPDzp2UlER4eDhTpkxh8eLFREVFcejQIZ599lliY2MJDw+nT58+dOnSpcR+v/76a7Zt28aGDRs4cuQIbdu25a677iInJ4fRo0fz7bffEh0dzZw5c3jqqad4//33yc7OZvfu3TRt2pQ5c+YwZMgQT/wJikRVD5xmu/eZ9FBVHZvNRkREBBEREagqaWlpHD9+nBMnTjgdDvLJqVuXY0OHcmzoUPxSUghbtoyIpUup9csvRH/9NXnVq5N84YWcvOwyknr1Ii883Kl8MjIyiIuL48CBA4SEhBAVFUVERESlcrt2RY3Wwkrc2RfLcUAcnxVO4byy7BVsYmN4i+HUqVPH2+JUSTp06MC4ceN4/PHHGTRoEJdccskZ1yxfvpzLLruMaIeXz9ChQwuVISiK3377jVtvvdVZx6hv374AbNu2jY0bN3LFFVcAVmqT/HW7IUOG8PnnnzNhwgTmzJnDnDlzyvNRy8IBh1lNRSQQKz3UFm8JYzh7Cq75nHfeeWRmZnLixAmOHz9OdnY2gFOB5IWGcmLgQE4MHIhkZxO6ahURS5YQ/ttv1Fy0CLXZSG/dmuSePUnp0YPUjh2xO2b6KSkppKWlsXfvXsLDw4mKiiIsLMznHQ5KUji1ReQRrLQc+YomnwqX6S4+OZ7Za2ZzTYNr6Nysc6V6K/AlWrZsSWxsLD/++CNPPPEE/fv355lnnjnjurMZOEW1UVXatWvHX3/9dca5oUOHMnjwYG680aru6sU8ej6bHspQPCJC9erVqV69OvXq1SMrK4sTJ05w7NgxcnJyCpl9NTCQ5IsuIvmii2DCBII3byb8zz8JXbHCmWrHXq0aqZ07k9yjB8k9e5LRsiXYbJw8eZLk5GQAatWqRXR0NNWrV/dJ5VOSwvHDWuQs6qkqnMJ59c9XydM87m51N1FRUd4Wp8py8OBBatWqxR133EFISAizZ88GIDQ0lJSUFKKioujZsydjxowhMTGRsLAw5s6dW6rnW+/evXn77be58847OXr0KIsXL+a2226jVatWHDt2jL/++osLL7yQnJwctm/fTrt27WjWrBl+fn48//zzDB061ANPXzS+nB7K4DrVqlUrMc7Hic1Gevv2pLdvz6FRo7ClpRGyZo3ldr1iBQ2mT4fp08kNDye5e3dn7E92gwZOd2s/Pz+io6OJjIz0KWeDkhTOIVWd5DFJzoGE9ARmxs5kQL0B9GjZw8xuCuDv71/ubtElsWHDBsaPH4/NZiMgIIA333wTgFGjRnHllVcSExPD4sWLmThxIhdeeCExMTGcf/75zro38+bNY9WqVUyaVPi/3g033MCiRYvo0KEDLVu25NJLrWwxgYGBfPHFFzz00EMkJSWRm5vL2LFjadeuHWDNcsaPH8+ePXvK7W9QVipCeiiDZykY55Oenu6M81HVwsoHsNeoQfLFF5PsqF7rn5BA2MqVhK5YQdjy5dRasACArPr1nXE/yd27cyg3l0OHDhEcHExUVBQ1a9as8OvWxeZSE5E1qlrySq6HKC0X1P8t+j8m/z6Zry//mmsvutYnp5qGioMbcqktxZEeKn9MichGVW1fXvcoiaqeS62ioKqkpKSQmJjIyZMnAc5QPkU0otq+fYQtX07oypWErlqFf2oqAOmtWjnNb+ldumAPCiI8PJzo6GhCQ0O9+jt4NrnUfKKMbVJmEjNWzKBP3T70btvbKBtDRcQn00MZyhcRISwsjLCwMOx2u9MxIDU1lczMTHJycpzWGaciEiGrcWOONW7MsaFDITeX4K1bnea32v/7H3U/+gh7QACpnTqR0qMHhy64gN1t2xJeq1aZrD3+/v7UqFGD4OBgAgIC3PJbWqzCUdXj5X43ByIyEGsR1Q94V1VfPtu+Xl/5OklZSfyz3T+JiIgoLxENhvLE59JDGdyLzWZzBpnmY7fbnVkJ0tLSSE9PJzMzE1U9FXjq7+9c/zl8993YMjIIWbPGMr+tWEH9N96AN94gNySEnNq1yyRTTnQ02Q0acKx+fbIbNICmTQls3ZrgevUIDg4mMDDwnJWQx6OLHNkLXgeuwPLYWSki81R1c1n7SstO479//5detXvRv2N/M7sxVFR8Lj2UwfPklz6oUaOG0/FJVcnNzSU9PZ2MjAzS09NJT093umBTo4bT+y0e8D9+/JTpzeHZ5hJ2O4FHjxK+cCEBDnNfPrlhYWTXr8/J+vXJa9QIadEC/5YtqXHppfjXqlWmZ/RGOGsPYKeq7gYQkc+A64AyK5x3Vr9DQnoC0y6YRmhoaDmLaTCcO76YHspQcRARAgICzpgNqSo5OTnOGVG+QsqKjOTkwIEkXXklxa3Pl4SqYktNpdrBg1SLjycwPp5qjq369u0ELlmCzeGElPjNN0Red12Z+veGwqkPHCiwHwf0PP0iERkFjAJo2LBhkR0t2rOIblHduLaLcRQwVDzcmR6qPM3SBt9DRAgMDCQwMLBIRZSZmUlWVlYJPZxJ/mwqJyeHnPr1yenShcy8PPIcm91uR+x2AhMSCIyLI9zhCVoWvKFwXIrrUdWZWGYIunXrVqSq/vaWbzmacpQQR1pwg6GC4Zb0UOVpljZULgoqovIm36U7NzeX3NxcghzVUMuCNxROHHBegf0GwMGz6UhEqBNmUtgYKjzlnR6q3MzSBoOriAh+fn74+fmddVkFbyiclUALEWkCxAO3ALd5QQ6Dwd24Kz1UqWZpV0zSBoOn8bjCcdi0HwR+wbI/v6+qmzwth8HgAdyVHqrU/lwxSRsMnqbYTAMVCRE5Buwr5nQUkOBBccoTX5YdfFv+kmRvpKrR53oDEVmtquefaz9F9HshMFFVBzj2nwBQ1ZeKub6k8QOV99+xolOZZS9yDPlElZ+SBr+IrCrPNCSexJdlB9+W30Oyu8t1skxm6dKUp/l39A5VUXafUDgGg4/ilvRQxixt8FWMwjEY3IQ700Op6o/Aj+7q32BwB5Uhj/9MbwtwDviy7ODb8vuy7OWNL/8tjOze4axk9wmnAYPBYDD4PpVhhmMwGAwGH8AoHIPBYDB4BJ9VOCIyUES2ichOEZngbXnKgoi8LyJHRWSjt2UpKyJynogsFpEtIrJJRMZ4W6ayICJBIrJCRNY55H/O2zJ5CzOGvIMvj6FzHT8+uYbjSF64nQLJC4FbfSV5oYj0BlKBDz1VZri8EJEYIEZVV4tIKBALXO9Df3sBaqhqqogEAH8AY1T1by+L5lHMGPIevjyGznX8+OoMx5m8UFWzgfzkhT6Bqv4GuM1l1p2o6iFVXe34ngJswcrt5ROoRapjN8Cx+d5b17ljxpCX8OUxdK7jx1cVTlHJC33iH6wyISKNgS7Aci+LUiZExE9E1gJHgfmq6lPylxNmDFUAfHEMncv48VWFU97JEA1lRERCgC+Bsapahlq23kdV81S1M1ZpjB4i4lMmmXLCjCEv46tj6FzGj68qnHKrqWMoOw7b7ZfAJ2dbRKwioKongSXAQO9K4hXMGPIilWEMnc348VWF40xeKCKBWMkL53lZpiqBY9HwPWCLqk7xtjxlRUSiRSTC8b06cDmw1atCeQczhryEL4+hcx0/PqlwVDUXyE9euAX43JeSF4rI/4C/gFYiEicid3tbpjLQCxgG9BWRtY7tKm8LVQZigMUish7rR3e+qn7vZZk8jhlDXsWXx9A5jR+fdIs2GAwGg+/hkzMcg8FgMPgeRuEYDAaDwSMYhWMwGAwGj2AUjsFgMBg8glE4BoPBYPAIRuFUMEQksoCr5GERiXd8TxWRN8rxPlMdCRCLO/+giIwsr/sZDJ7CjKGKi3GLrsCIyEQgVVVfLed+awE/quoFJVwTDCxT1S7leW+DwZOYMVSxMDMcH0FELhOR7x3fJ4rIByLyq4jsFZEbReRfIrJBRH52pM1ARLqKyFIRiRWRXxxp0QFuBn4u0PfLIrJZRNaLyKsAqpoO7BWRHh5+VIPBLZgx5H2MwvFdmgFXY6WU/xhYrKodgAzgaseAmQ7crKpdgfeBFx1te2HV4Mh/U7sBaKeqHYEXCtxjFXCJB57FYPAGZgx5GH9vC2A4a35S1RwR2QD4ceptawPQGGgFtAfmW6mb8AMOOa6JAY45vicDmcC7IvIDUDBNxVGgtRufwWDwJmYMeRijcHyXLABVtYtIjp5ajLNj/bsKsElVLyyibQYQ5Gif65jy98NK4Pgg0NdxXZDjWoOhMmLGkIcxJrXKyzYgWkQuBCsduoi0c5zbAjR3HA8BwlX1R2As0LlAHy0Bn6sZbzCUE2YMlTNG4VRSHGWDbwZeEZF1wFrgIsfpH4DLHN9Dge8d2V+XAg8X6KYXsMAT8hoMFQ0zhsof4xZdRRGRP4BBjiJKRZ3vAjyiqsM8KpjB4COYMVR2jMKpoohITyBDVdcXc/4KYIeq7vWoYAaDj2DGUNkxCsdgMBgMHsGs4RgMBoPBIxiFYzAYDAaPYBSOwWAwGDyCUTgGg8Fg8AhG4RgMBoPBI/w/ANVrW6FcOicAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "S.plot_stochastic(Tree.not_sick, Tree.sick)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d829ee2-9eac-4556-b3c3-0474b36cb8e0",
   "metadata": {},
   "source": [
    "Plot stochastic generates two figures for each species. The figures above refer to the runs, while the figures bellow refer to an average of the runs with the standard deviation.\n",
    "\n",
    "If one wishes to see all species together, one can use the plot function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0f198b63-0238-4c20-b5e1-6cdfb81f17bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "S.plot(Tree.not_sick, Tree.sick)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcb9ad8f-ac4a-400f-a6b8-e0a739832459",
   "metadata": {},
   "source": [
    "One can also access the data directly using either the meta-species objects or strings. \n",
    "Similarly to the plotting function you can perform queries in the result data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a35e7f4e-67c5-4d09-99cd-29eba06af496",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tree: \n",
      " [[60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0], [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0], [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0]]\n",
      "Tree.not_sick: \n",
      " [[60.0, 44.0, 36.0, 26.0, 21.0, 15.0, 10.0, 7.0, 4.0, 3.0, 2.0, 2.0, 2.0], [60.0, 46.0, 37.0, 31.0, 21.0, 16.0, 14.0, 12.0, 9.0, 6.0, 4.0, 4.0, 3.0], [60.0, 43.0, 30.0, 20.0, 16.0, 12.0, 11.0, 10.0, 9.0, 7.0, 4.0, 4.0, 2.0]]\n",
      "Tree.sick: \n",
      " [[0.0, 16.0, 24.0, 34.0, 39.0, 45.0, 50.0, 53.0, 56.0, 57.0, 58.0, 58.0, 58.0], [0.0, 14.0, 23.0, 29.0, 39.0, 44.0, 46.0, 48.0, 51.0, 54.0, 56.0, 56.0, 57.0], [0.0, 17.0, 30.0, 40.0, 44.0, 48.0, 49.0, 50.0, 51.0, 53.0, 56.0, 56.0, 58.0]]\n",
      "Tree.sick.blue: \n",
      " [[0.0, 6.0, 9.0, 13.0, 15.0, 18.0, 19.0, 19.0, 20.0, 20.0, 20.0, 20.0, 20.0], [0.0, 4.0, 8.0, 9.0, 12.0, 12.0, 14.0, 14.0, 15.0, 17.0, 19.0, 19.0, 20.0], [0.0, 2.0, 5.0, 8.0, 10.0, 13.0, 14.0, 15.0, 15.0, 15.0, 16.0, 16.0, 18.0]]\n"
     ]
    }
   ],
   "source": [
    "R = S.results\n",
    "print('Tree: \\n', R[Tree])\n",
    "print('Tree.not_sick: \\n', R[Tree.not_sick])\n",
    "print('Tree.sick: \\n', R['Tree.sick'])\n",
    "print('Tree.sick.blue: \\n', R['Tree.sick.blue'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23ef615c-b3cc-4c77-b6f7-72d33d80eba1",
   "metadata": {},
   "source": [
    "If the simulation has more than one repetition the results requested for a species will yield all runs packed in a list. However, if a simulation has only one run it will return a single list. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1dd86359-8cc3-4c7d-af7c-5b9c14aaa3b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Compiling model\n",
      "Starting Simulator\n",
      "Running simulation in parallel\n",
      "Simulation is Over\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEGCAYAAABiq/5QAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAkWUlEQVR4nO3deXQUdb7+8fcnIWFfEgiLLEIQEFQEDNsIAkIUxQFEdNARkHHgquAYneM9jHfG0fF6r3pd0Bmcn6isCo6iLIqIYRVUloAICigQiShb2EEkQPj+/kibiQihCamuXp7XOX16q0o/RR2erq6u+rY55xARkdgR53cAEREJLRW/iEiMUfGLiMQYFb+ISIxR8YuIxJgyfgcIRo0aNVzDhg39jiEiElFWrly52zmXcurjEVH8DRs2JCsry+8YIiIRxcxyTve4dvWIiMQYFb+ISIxR8YuIxBgVv4hIjFHxi4jEGE+L38yqmdlUM9tgZuvNrKOZJZtZppltDFwneZlBRER+zust/ueBD5xzFwOXA+uBkcA851wTYF7gvoiIhIhnxW9mVYCrgFcBnHPHnHP7gT7AhMBkE4C+XmWYlz2PJ5Y84dWfFxGJSF5u8acCucA4M/vMzF4xs4pALefcdoDAdc3TzWxmw8wsy8yycnNzSxRgzuY5/Hn+n/n2wLclXAQREf9NmzYNM2PDhg2l8ve8LP4yQBvgn8651sAPnMNuHefcGOdcmnMuLSXlF2ccB2VEuxEAjF4+ukTzi4iEgylTptCpUyfeeOONUvl7Xhb/d8B3zrllgftTKXgj2GlmdQAC17u8CtCgagP6Ne/HmFVj+OHYD169jIiIZw4fPszHH3/Mq6++WmrF79lYPc65HWa21cyaOee+AroD6wKXwcATgesZXmUAyOiQwVvr3mLi5xO5u+3dXr6UiESxjA8yWL1jdan+zVa1WzGq56hip5k+fTo9e/akadOmJCcns2rVKtq0aXNer+v1UT33Aq+b2RqgFfA/FBR+upltBNID9z3TsV5H2l7QlueXPc9Jd9LLlxIRKXVTpkxhwIABAAwYMIApU6ac99+0SPix9bS0NHc+o3NOXjuZ377zW96/7X2ua3JdKSYTEfHOnj17qFevHjVr1sTMyM/Px8zIycnBzM46v5mtdM6lnfp4TJy5279Ffy6ofAHPLX3O7ygiIkGbOnUqgwYNIicnhy1btrB161YaNWrEkiVLzuvvxkTxJ8YnMrztcDKzM/ly15d+xxERCcqUKVO48cYbf/bYTTfdxOTJk8/r78bErh6A3Ud2U/+5+gxsOZAxvx5TSslERMJXTO/qAahRoQYDWw5k0ppJ7D6y2+84IiK+iZniB7iv/X0cPXGUMSu1xS8isSumiv+SmpeQnprO6BWjOZZ/zO84IiK+iKnih4ITurYd2sbUdVP9jiIi4ouYK/6eF/WkWfVmPLf0OSLhi20RkdIWc8UfZ3Hc1/4+srZl8el3n/odR0Qk5GKu+AEGXT6IauWqMWrpKL+jiIiEXEwWf8XEigxrM4y3179Nzv4cv+OIiIRUTBY/wPB2wzGM0Ss0Vr+IxJaYLf4GVRtwU4ubeHnVyxw+dtjvOCIiIROzxQ+Q0T6D/Uf3M/HziX5HEREJmZgu/g71OtCubjuN1S8iMSWmi9/MyGifwdd7vuaDTR/4HUdEJCRiuvhBY/WLSOyJ+eJPiE9gRNsRzM2eyxe7vvA7joiI52K++AGGXTGMcmXK8fzS5/2OIiLiORU/UL1CdQa1HMSkNZPI/SHX7zgiIp5S8Qfc1+E+8vLzNFa/iEQ9FX9Ai5QWXNP4Go3VLyJRT8VfREb7DLYf3s5bX77ldxQREc+o+Iu49qJraVa9GaOWjdJY/SIStVT8RcRZHBkdMsjalsUnWz/xO46IiCc8LX4z22Jma81stZllBR5LNrNMM9sYuE7yMsO5GthyIEnlkhi1bJTfUUREPBGKLf5uzrlWzrm0wP2RwDznXBNgXuB+2KiYWJFhVwzjnfXvaKx+EYlKfuzq6QNMCNyeAPT1IUOxhrctGKv/H8v/4XcUEZFS53XxO+BDM1tpZsMCj9Vyzm0HCFzXPN2MZjbMzLLMLCs3N7QnVdWvWp/+LfprrH4RiUpeF/+Vzrk2wHXAcDO7KtgZnXNjnHNpzrm0lJQU7xKeQUaHDA7kHWDC6glnn1hEJIJ4WvzOuW2B613ANKAdsNPM6gAErnd5maGkOtTrQPu67TVWv4hEHc+K38wqmlnln24D1wBfADOBwYHJBgMzvMpwvjI6ZLBx70Zmb5ztdxQRkVLj5RZ/LWCJmX0OLAdmOec+AJ4A0s1sI5AeuB+Wbmp+E3Ur19WhnSISVcp49Yedc9nA5ad5fA/Q3avXLU0J8QmMaDeCP837E2t3ruWyWpf5HUlE5LzpzN2zGNpmKOXLlOf5ZRqrX0Sig4r/LKpXqM6gywfx2prXNFa/iEQFFX8Q/tD+D+Tl5/HSypf8jiIict5U/EFokdKCaxtfq7H6RSQqqPiDlNEhgx2Hd/Dml2/6HUVE5Lyo+IN0TeNruLjGxTy39DmN1S8iEU3FH6Q4i+O+9vexavsqPt76sd9xRERKTMV/DgZdPqhgrP6lo/yOIiJSYir+c1AhoQL/ccV/MG3DNLbs3+J3HBGRElHxn6Ph7TRWv4hENhX/OapXpR43X3Izr6x6hUN5h/yOIyJyzlT8JZDRPjBW/+caq19EIo+KvwTa12tPh3odNFa/iEQkFX8JZbTPYNPeTby/8X2/o4iInBMVfwn1a96PelXq6dBOEYk4Kv4SSohPYETbEcz7Zh5rdq7xO46ISNBU/Odh6BWBsfqXaqx+EYkcKv7zkFw+mcGXD+b1ta+z8/BOv+OIiARFxX+e7u94PyfdSTLmZPgdRUQkKCr+89S0elMe7vIwb3zxBlPXTfU7jojIWan4S8HITiNJuyCNu2fdza4fdvkdR0SkWCr+UlAmrgwT+k7gUN4h7nrvLo3XLyJhTcVfSlqktOCxbo8xbcM0Jq+d7HccEZEzUvGXogc6PsCv6v+KEbNH8P3B7/2OIyJyWir+UhQfF8/4PuPJO5HH0HeHapePiIQlz4vfzOLN7DMzey9wP9nMMs1sY+A6yesModSkehOe7PEkszfNZuxnY/2OIyLyC6HY4r8PWF/k/khgnnOuCTAvcD+qDG83nG4Nu3H/nPvJ2Z/jdxwRkZ/xtPjNrB7QC3ilyMN9gJ8Gsp8A9PUygx/iLI6xfcbicPxu5u80dLOIhBWvt/hHAf8JFG2+Ws657QCB65qnm9HMhplZlpll5ebmehyz9DWs1pBnrnmG+d/M558r/ul3HBGRQp4Vv5ndAOxyzq0syfzOuTHOuTTnXFpKSkoppwuNoW2Gcm3ja/nPuf/Jpr2b/I4jIgJ4u8V/JdDbzLYAbwBXm9lrwE4zqwMQuI7aU13NjFd6v0JCXAJDZgwh/2S+35FERLwrfufcn5xz9ZxzDYEBwHzn3O3ATGBwYLLBwAyvMoSDelXq8cJ1L7Dk2yU8v0zDN4uI//w4jv8JIN3MNgLpgftRbWDLgfRu1puH5j3Eht0b/I4jIjEuJMXvnFvonLshcHuPc667c65J4HpvKDL4ycx46YaXqJhYkcHTB3Pi5Am/I4lIDNOZuyFSu1JtXrz+RZZ/v5ynPn7K7zgiEsNU/CH0m0t/wy2X3MIjCx/R7/SKiG9U/CE2+vrRJJVPYvD0wRzLP+Z3HBGJQSr+EKtRoQZjbhjD6h2refyjx/2OIyIxSMXvgz4X92Fgy4E8vvhxVm4r0fltIiIlpuL3yfM9n6dWpVoMmj6IoyeO+h1HRGKIit8nSeWTeLX3q6zLXcdfF/zV7zgiEkNU/D7qeVFPhrYZytOfPs2nWz/1O46IxAgVv8+eueYZ6lepz+Dpgzly/IjfcUQkBqj4fVa5bGXG9RnHxr0beWjeQ37HEZEYcM7Fb2ZJZtbSizCxqlujboxoO4Lnlz3Pwi0L/Y4jIlEuqOI3s4VmVsXMkoHPgXFm9qy30WLLEz2e4KLkixgyYwiH8g75HUdEoliwW/xVnXMHgX7AOOfcFUAP72LFnoqJFRnfZzw5+3N4MPNBv+OISBQLtvjLBH405RbgPQ/zxLQrG1zJHzv+kZdWvsSHmz/0O46IRKlgi/9RYA6wyTm3wsxSgY3exYpdj139GM1rNOfOmXey/+h+v+OISBQKtvi3O+daOufuAXDOZQPax++BcmXKMaHvBLYf2k7GBxl+xxGRKBRs8f89yMekFLSt25aRnUYy4fMJzPxqpt9xRCTKlCnuSTPrCPwKSDGzB4o8VQWI9zJYrHu4y8O8+/W7DHt3GFfWv5LqFar7HUlEosTZtvgTgUoUvEFULnI5CPT3NlpsS4xPZGLfiez9cS8jZo/wO46IRJFit/idc4uARWY23jmXE6JMEnB57ct5uMvD/GXBX+h3cT9uvuRmvyOJSBQIdh9/WTMbY2Yfmtn8ny6eJhMARnYaSdoFadw96252Ht7pdxwRiQLBFv9bwGfAn4EHi1zEY2XiyjCh7wQOHztM/7f6czDvoN+RRCTCBVv8J5xz/3TOLXfOrfzp4mkyKdQipQUTb5zI0u+W0n1id3Yf2e13JBGJYMEW/7tmdo+Z1TGz5J8uniaTn7nlkluY/pvpfLHrC7qM78K2Q9v8jiQiESrY4h9Mwa6dT4CVgUuWV6Hk9Ho17cXs387m2wPf0mlsJ7L3ZfsdSUQiUFDF75xrdJpLanHzmFk5M1tuZp+b2Zdm9mjg8WQzyzSzjYHrpNJYkFjRtWFX5g+az4G8A3Qe15l1uev8jiQiESbYYZkHne5yltnygKudc5cDrYCeZtYBGAnMc841AeYF7ss5aFu3LYvuWIRzjqvGXUXWNn34EpHgBburp22RS2fgEaB3cTO4AocDdxMCFwf0ASYEHp8A9D2nxALApTUvZfGQxVQuW5mrJ1zNRzkf+R1JRCJEsLt67i1yGQq0puCs3mKZWbyZrQZ2AZnOuWVALefc9sDf3Q7UPMO8w8wsy8yycnNzg1yc2NI4uTFLhiyhXpV6XPvatby/8X2/I4lIBCjpb+4eAZqcbSLnXL5zrhVQD2hnZpcG+wLOuTHOuTTnXFpKSkoJY0a/ulXqsuiORbRIaUGfN/rw5pdv+h1JRMJcsUM2/MTM3qVgNw0UDM7WHAi6YZxz+81sIdAT2GlmdZxz2wM/7rLr3CLLqVIqpjB/0Hx+PeXX3Pr2rRzKO8Sdbe70O5aIhKmgih94usjtE0COc+674mYwsxTgeKD0y1PwU41PAjMpODz0icD1jHNOLb9QtVxVPrj9A2568yZ+/+7vOZh3kPs73u93LBEJQ8Hu418EbKBgZM4k4FgQs9UBFpjZGmAFBfv436Og8NPNbCOQHrgvpaBCQgVmDJjBzS1u5oEPH+CvC/6Kc+7sM4pITAl2V88twP8BCwED/m5mDzrnpp5pHufcGgq+BD718T1A9xKllbNKjE9kyk1TqJxYmb999DcO5B3g2WufJc5K+nWOiESbYHf1/BfQ1jm3Cwp348wFzlj84p/4uHhe7v0yVcpWYdSyURzMO8jLv36Z+Dj9do6IBF/8cT+VfsAeSn5EkIRAnMXx7LXPUrVcVR5d9CiHjh3i9X6vkxh/1qNwRSTKBVv8H5jZHGBK4P5vAB00HubMjEe6PkLVslV54MMHOHzsMG/f8jYVEir4HU1EfFTsVruZXWRmVzrnHgReAloClwOfAmNCkE9Kwf0d7+fV3q/y4eYPufa1azlw9IDfkUTER2fbXTMKOATgnHvHOfeAc+5+Crb2R3kbTUrT71r/jjdueoNl3y3j6olXk/uDzoYWiVVnK/6GgaNzfsY5lwU09CSReObmS25mxoAZrMtdx1Xjr+L7g9/7HUlEfHC24i9XzHPlSzOIhMZ1Ta5jzu1z+P7g93Qa14nNezf7HUlEQuxsxb/CzIae+qCZ3UnBj7FIBLrqwqtYMHgBh/IO0XlcZ77Y9YXfkUQkhKy4MzvNrBYwjYIzdX8q+jQKRua80Tm3w/OEQFpamsvK0pjzpW1d7jrSJ6Vz9MRRZv92Nu3qtvM7koiUIjNb6ZxLO/XxYrf4nXM7nXO/Ah4FtgQujzrnOoaq9MU7LVJasGTIEqqVq0b3id1ZuGWh35FEJASCHatngXPu74HLfK9DSeg0SmrE4iGLaVC1AT1f68m7X73rdyQR8ZjOvhUuqHwBi+5YxGW1LqP3G70ZMHUAm/Zu8juWiHhExS8A1KhQgwWDF/Dnzn/m3a/fpfno5gyfNZwdh7VHTyTaqPilUKXESjx29WNsuncTQ9sM5aWVL3HRCxfx8IKHOZh30O94IlJKVPzyC3Uq1+HFXi+yfvh6ejXtxWMfPUbjFxrz/NLnyTuR53c8ETlPKn45oybVm/Cv/v9ixdAVtKzVkow5GVw8+mJeW/MaJ91Jv+OJSAmp+OWs0i5IY+7Aucy5fQ7VylVj4LSBtHmpDR9s+kC/8CUSgVT8EhQz45rG17By2Eom95vMwbyDXPf6dVw98WqWf7/c73gicg5U/HJO4iyOWy+7lQ0jNvD36/7Ol7u+pP0r7en/Zn++2v2V3/FEJAgqfimRxPhERrQbweY/bOavXf7KnM1zuOTFS7jrvbvYfmi73/FEpBgqfjkvlctW5pGuj7D5D5u5p+09jP1sLI1faMx/zfsv/eCLSJhS8UupqFmxJi9c9wLrh6+n78V9+Z8l/0PqC6k8++mzHD1x1O94IlKEil9KVePkxky+aTIrh60k7YI0/vjhH2n2j2ZMWD2B/JP5fscTEVT84pE2ddow5/Y5zB04l5QKKdwx4w5avdSKWV/P0iGgIj5T8Yunuqd2Z/nQ5fyr/784euIoN0y5gS7ju+gIIBEfeVb8ZlbfzBaY2Xoz+9LM7gs8nmxmmWa2MXCd5FUGCQ9xFsctl9zCunvW8c9e/2T97vW0e6Ud7339nt/RRGKSl1v8J4A/OueaAx2A4WbWAhgJzHPONQHmBe5LDEiIT+CutLtYOWwlFyVfRO8pvfnvj/5bwz+IhJhnxe+c2+6cWxW4fQhYD9QF+gATApNNAPp6lUHCU4OqDVgyZAm3XXYbf1nwF25+62YOHzvsdyyRmBGSffxm1hBoDSwDajnntkPBmwNQMxQZJLyUTyjPpBsn8cw1zzB9w3Q6vtqRzXs3+x1LJCZ4XvxmVgl4G8hwzgU9qLuZDTOzLDPLys3N9S6g+MbMeKDjA8y5fQ7bDm2j7cttydyc6XcskajnafGbWQIFpf+6c+6dwMM7zaxO4Pk6wK7TzeucG+OcS3POpaWkpHgZU3zWI7UHK4auoF6VevR8vSdPf/K0DvkU8ZCXR/UY8Cqw3jn3bJGnZgKDA7cHAzO8yiCRIzUplU/u/IR+zfvxYOaD3D7tdo4cP+J3LJGo5OUW/5XAQOBqM1sduFwPPAGkm9lGID1wX4RKiZV4s/+bPH7140xZO4VOYzuRsz/H71giUcci4SN1Wlqay8rK8juGhNCsr2dx2zu3kRifyFs3v0XXhl39jiQSccxspXMu7dTHdeauhKVeTXux/PfLqVGhBj0m9uAfy/+h/f4ipUTFL2GrWY1mLL1zKdc3uZ57Z9/L72f+XiN9ipQCFb+EtarlqjJ9wHT+ctVfGLt6LF3Hd2XboW1+xxKJaCp+CXtxFsffuv2Nt295my92fcEVY67g062f+h1LJGKp+CVi9Gvej6W/X0qFhAp0Gd+FV1a94nckkYik4peIcmnNS1kxdAXdGnVj6LtDGT5rOMfyj/kdSySiqPgl4iSXT+b9297nwV89yItZL9JjYg92Ht7pdyyRiKHil4gUHxfPU+lPMbnfZLK2ZZH2chpZ23Suh0gwVPwS0W697FY+/t3HxFkcncd1ZtLnk/yOJBL2VPwS8VrXaU3W0Cw61OvAoOmDeGDOA5w4ecLvWCJhS8UvUSGlYgof3v4h97a7l+eWPkfP13qy58gev2OJhCUVv0SNhPgEXrjuBcb2HsvibxfT8dWOfHvgW79jiYQdFb9EnSGthzB/0Hx2/bCLTmM78fWer/2OJBJWVPwSla5scCULBi/g6ImjdB7Xmc93fO53JJGwoeKXqNW6Tms+GvIRifGJdJ3QVcM8iASo+CWqXVzjYpYMWUKNCjVIn5TO3Oy5fkcS8Z2KX6LehdUuZPGQxTRKakSvyb2YvmG635FEfKXil5hQu1JtFt2xiNa1W9P/zf460UtimopfYkZy+WQyB2bSpWEXBk0fxIsrXvQ7kogvVPwSUyqXrcys22bx66a/Zvj7w/nfxf/rdySRkFPxS8wpV6Ycb9/yNrdddhsPzX+IkXNH6vd8JaaU8TuAiB8S4hOYdOMkqiRW4cmPn+TA0QOM7jWaONO2kEQ/Fb/ErDiL48VeL1KlbBWe+uQpDh47yPg+40mIT/A7moinVPwS08yMJ9OfpFq5ajw0/yEOHzvMv/r/i3JlyvkdTcQz+lwrAvyp858Yff1oZn41k16Te3Eo75DfkUQ841nxm9lYM9tlZl8UeSzZzDLNbGPgOsmr1xc5V/e0vYdJN05i0ZZFpE9KZ++Pe/2OJOIJL7f4xwM9T3lsJDDPOdcEmBe4LxI2bm95O1NvmcpnOz6j6/iu7Di8w+9IIqXOs+J3zn0EnLrJ1AeYELg9Aejr1euLlFTfi/sy67ZZbN63mc7jOpOzP8fvSCKlKtT7+Gs557YDBK5rhvj1RYLSI7UHcwfOZfeR3XQa14mvdn/ldySRUhO2X+6a2TAzyzKzrNzcXL/jSAzqWL8jCwcv5Fj+MTqP68zqHav9jiRSKkJd/DvNrA5A4HrXmSZ0zo1xzqU559JSUlJCFlCkqMtrX87iIYspV6YcXcd35ZOtn/gdSeS8hbr4ZwKDA7cHAzNC/Poi56xp9aYs+d0SalasSfqkdDI3Z/odSeS8eHk45xTgU6CZmX1nZncCTwDpZrYRSA/cFwl7Dao2YPGQxVyUfBE3TLmBaeun+R1JpMQsEganSktLc1lZWX7HEGHfj/u4fvL1LP9+OWN7j2Vwq8Fnn0nEJ2a20jmXdurjYfvlrkg4SiqfRObATLo17MYdM+7gmU+e4cfjP/odS+ScaItfpASOnjjKgKkDmPHVDMrGl6VTg06kp6aT3jidVrVbaZRPCQtn2uJX8YuUUP7JfDKzM8ncnElmdiZrd60FoHr56nRP7V7wRpCazoXVLvQ5qcQqFb+Ix3Yc3sHc7LmFbwbbD28HoElyE9JT0+mR2oNujbpRrVw1f4NKzFDxi4SQc471u9cXfhpYuGUhPxz/gTiLo13ddoWfBtrXa09ifKLfcSVKqfhFfHQs/xhLv1ta+Ilg+ffLOelOUimxEl0u7FL4/UDzGs0xM7/jSpRQ8YuEkf1H97PgmwVkZmcyN3suG/duBOCCyhcU7hbqkdqD2pVq+5xUIpmKXySM5ezPKfhuIDuTednz2PPjHgAuq3kZPVJ7UKtiLc8z1KpUi+6NulO/an3PX0tCQ8UvEiFOupOs3rG68PuBJd8uIS8/L2Sv37R608LvILo16kaVslVC9tpSulT8IhHqxMkTHM8/7ulrOByb924u/NTxUc5HHDl+hHiLp3299oW7n9rXba8fo48gKn4RCVreiTw+/e7Twk8dWduycDgqJ1ama8OuhV9GN6veTF9GhzEVv4iU2N4f9xZ+GZ2ZnUn2vmwA6lWpR4/UHoWfCGpW1G8rhRMVv4iUmux92YWHps7Lnse+o/sAaFmrZeH3A50v7EyFhAo+J41tKn4R8UT+yXxWbV9VeGjqx1s/5lj+MRLjE/89hlFqOq3rtNYYRiGm4heRkPjh2A8s/nYxmZszmfvNXNbsXANAcvlkujbsSvMazUlNSiU1KZXGSY2pW6Wu3hA8ouIXEV/sOLyDednzCg9N3bJ/C/kuv/D5xPhEGlVr9LM3g9SkVBonN6ZRtUZUTKzoY/rIpuIXkbBwPP84Ww9uJXtfNpv3bi643vfv64N5B382fa2KtWic3Phnbwo/3a5dqbaOKiqGil9Ewp5zjr0/7iV7X/Yv3hCy92Wz9cBWHP/urPJlyhe+ERR9Y6hctrLnWSskVCA1KZWkcklh++ZzpuIv40cYEZHTMTOqV6hO9QrVaVu37S+ezzuRR86BnH+/MezdTPb+guv538znh+M/hDxz1bJVC3dNpVZL/dmnk/pV61MmLvxqNvwSiYicQdkyZWlavSlNqzf9xXPOOXKP5JK9L5sjx494nuVg3kG+2fdN4aeRtTvXMvOrmRzLP1Y4TbzFc2G1C//9vUXRXVXJjX0bDkPFLyJRwcyoWbGmryeR5Z/MZ9uhbYVvBkV3U01dN7Vw8L2fVC9fvfATQtFPC6lJqdStXJf4uHhPcmofv4hIiBw4eoBv9n9T+KV20TeGnAM5nDh5onDaxPhEGlZryEs3vETXhl1L9Hraxy8i4rOq5arSqnYrWtVu9YvnTpw8wdYDW3/2ZpC9L5saFWqUeg4Vv4hIGCgTV4ZGSY1olNSI7nT39LV0upyISIxR8YuIxBhfit/MeprZV2a2ycxG+pFBRCRWhbz4zSweGA1cB7QAbjWzFqHOISISq/zY4m8HbHLOZTvnjgFvAH18yCEiEpP8KP66wNYi978LPPYzZjbMzLLMLCs3Nzdk4UREop0fxX+60Yx+cRaZc26Mcy7NOZeWkpISglgiIrHBj+L/Dqhf5H49YJsPOUREYlLIh2wwszLA10B34HtgBXCbc+7LYubJBXJK+JI1gN0lnDfcaFnCT7QsB2hZwtX5LMuFzrlf7DIJ+Zm7zrkTZjYCmAPEA2OLK/3APCXe12NmWacbqyISaVnCT7QsB2hZwpUXy+LLkA3OufeB9/14bRGRWKczd0VEYkwsFP8YvwOUIi1L+ImW5QAtS7gq9WWJiPH4RUSk9MTCFr+IiBSh4hcRiTFRU/xnG/HTCrwQeH6NmbXxI2cwgliWrmZ2wMxWBy4P+5HzbMxsrJntMrMvzvB8RKyTIJYjItYHgJnVN7MFZrbezL40s/tOM02krJdgliXs142ZlTOz5Wb2eWA5Hj3NNKW7TpxzEX+h4HyAzUAqkAh8DrQ4ZZrrgdkUDBnRAVjmd+7zWJauwHt+Zw1iWa4C2gBfnOH5SFknZ1uOiFgfgax1gDaB25UpOJkyUv+vBLMsYb9uAv/OlQK3E4BlQAcv10m0bPEHM+JnH2CiK7AUqGZmdUIdNAhRM3qpc+4jYG8xk0TEOgliOSKGc267c25V4PYhYD2/HCQxUtZLMMsS9gL/zocDdxMCl1OPuinVdRItxR/MiJ9BjQoaBoLN2THw0XC2mV0SmmilLlLWSTAibn2YWUOgNQVbmEVF3HopZlkgAtaNmcWb2WpgF5DpnPN0nUTLj60HM+JnUKOChoFgcq6iYAyOw2Z2PTAdaOJ1MA9Eyjo5m4hbH2ZWCXgbyHDOHTz16dPMErbr5SzLEhHrxjmXD7Qys2rANDO71DlX9DulUl0n0bLFH8yIn5EyKuhZczrnDv700dAVDH+RYGY1Qhex1ETKOilWpK0PM0ugoChfd869c5pJIma9nG1ZIm3dOOf2AwuBnqc8VarrJFqKfwXQxMwamVkiMACYeco0M4FBgW/HOwAHnHPbQx00CGddFjOrbWYWuN2OgvW4J+RJz1+krJNiRdL6COR8FVjvnHv2DJNFxHoJZlkiYd2YWUpgSx8zKw/0ADacMlmprpOo2NXjzjDip5ndFXj+/1EwKNz1wCbgCDDEr7zFCXJZ+gN3m9kJ4EdggAt89R9OzGwKBUdV1DCz74C/UvDFVUStkyCWIyLWR8CVwEBgbWCfMsBDQAOIrPVCcMsSCeumDjDBCn6PPA540zn3npf9pSEbRERiTLTs6hERkSCp+EVEYoyKX0Qkxqj4RURijIpfRCTGqPglJplZ9SIjNu4ws+8Dtw+b2Yul+DqjzOyqYp4fYWbherikRCkdzikxz8weAQ47554u5b+bDLzvnOtQzDQVgI+dc61L87VFiqMtfpEiAuO3vxe4/YiZTTCzD81si5n1M7OnzGytmX0QGC4AM7vCzBaZ2Uozm1Nk1MT+wAdF/vYTZrbOCsZTfxrAOXcE2BI4q1QkJFT8IsVrDPSiYFjc14AFzrnLKDgLtFeg/P8O9HfOXQGMBR4PzHslsBIKt/5vBC5xzrUE/rvIa2QBnUOwLCJAlAzZIOKh2c6542a2loIhNH7agl8LNASaAZcCmYEhYeKBn8ZQqQPkBm4fBI4Cr5jZLOC9Iq+xC7jYw2UQ+RkVv0jx8gCccyfN7HiRcV5OUvD/x4AvnXMdTzPvj0C5wPwnArtzulMw8N4I4OrAdOUC04qEhHb1iJyfr4AUM+sIBcMEF/mxj/XARYHHKwFVA0MDZwCtivyNpsBpf89XxAsqfpHzEPh5zP7Ak2b2ObAa+FXg6VkUjOoJBb8J+56ZrQEWAfcX+TNXAnNDkVcEdDiniKfMbAlwQ+AHNk73fGvgAefcwJAGk5im4hfxkJm1B350zq05w/PpwEbn3JaQBpOYpuIXEYkx2scvIhJjVPwiIjFGxS8iEmNU/CIiMUbFLyISY/4/b4sdxh5U8ocAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "A = BaseSpecies()\n",
    "\n",
    "A >> Zero [1]\n",
    "\n",
    "A(60)\n",
    "S_one_run = Simulation(A)\n",
    "S_one_run.method = 'stochastic'\n",
    "S_one_run.step_size = 0.25\n",
    "S_one_run.duration = 3\n",
    "S_one_run.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "da58e142-f4fe-4991-b644-077c5b86df3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[60.0, 43.0, 32.0, 25.0, 21.0, 15.0, 8.0, 6.0, 6.0, 4.0, 3.0, 3.0, 2.0]\n"
     ]
    }
   ],
   "source": [
    "print(S_one_run.results[A])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "080e650e-ef49-4699-8ce7-24ac12f4d0e5",
   "metadata": {},
   "source": [
    "## Looping over data\n",
    "\n",
    "Looping through results changes for simulations with multiple repetitions and simulations with a single repetition.\n",
    "If there is a single repetition a loop through the results will yield all the meta-species and if there are multiple repetations a loop through the results will yield each time-series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5389fda9-ed11-4425-b3b4-67777fa83818",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Single repetition: \n",
      "A\n",
      "Time\n",
      "\n",
      "Multiple repetitions: \n",
      "{'Tree.red.not_sick': [20.0, 17.0, 15.0, 10.0, 9.0, 6.0, 2.0, 2.0, 1.0, 0.0, 0.0, 0.0, 0.0], 'Tree.yellow.not_sick': [20.0, 13.0, 10.0, 9.0, 7.0, 7.0, 7.0, 4.0, 3.0, 3.0, 2.0, 2.0, 2.0], 'Tree.blue.not_sick': [20.0, 14.0, 11.0, 7.0, 5.0, 2.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0], 'Tree.yellow.sick': [0.0, 7.0, 10.0, 11.0, 13.0, 13.0, 13.0, 16.0, 17.0, 17.0, 18.0, 18.0, 18.0], 'Tree.red.sick': [0.0, 3.0, 5.0, 10.0, 11.0, 14.0, 18.0, 18.0, 19.0, 20.0, 20.0, 20.0, 20.0], 'Tree.blue.sick': [0.0, 6.0, 9.0, 13.0, 15.0, 18.0, 19.0, 19.0, 20.0, 20.0, 20.0, 20.0, 20.0], 'Tree': [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0], 'Time': [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0]}\n",
      "{'Tree.red.not_sick': [20.0, 12.0, 10.0, 6.0, 5.0, 4.0, 4.0, 3.0, 2.0, 2.0, 2.0, 2.0, 2.0], 'Tree.yellow.not_sick': [20.0, 18.0, 15.0, 14.0, 8.0, 4.0, 4.0, 3.0, 2.0, 1.0, 1.0, 1.0, 1.0], 'Tree.blue.not_sick': [20.0, 16.0, 12.0, 11.0, 8.0, 8.0, 6.0, 6.0, 5.0, 3.0, 1.0, 1.0, 0.0], 'Tree.yellow.sick': [0.0, 2.0, 5.0, 6.0, 12.0, 16.0, 16.0, 17.0, 18.0, 19.0, 19.0, 19.0, 19.0], 'Tree.red.sick': [0.0, 8.0, 10.0, 14.0, 15.0, 16.0, 16.0, 17.0, 18.0, 18.0, 18.0, 18.0, 18.0], 'Tree.blue.sick': [0.0, 4.0, 8.0, 9.0, 12.0, 12.0, 14.0, 14.0, 15.0, 17.0, 19.0, 19.0, 20.0], 'Tree': [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0], 'Time': [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0]}\n",
      "{'Tree.red.not_sick': [20.0, 13.0, 10.0, 5.0, 3.0, 2.0, 2.0, 2.0, 2.0, 2.0, 0.0, 0.0, 0.0], 'Tree.yellow.not_sick': [20.0, 12.0, 5.0, 3.0, 3.0, 3.0, 3.0, 3.0, 2.0, 0.0, 0.0, 0.0, 0.0], 'Tree.blue.not_sick': [20.0, 18.0, 15.0, 12.0, 10.0, 7.0, 6.0, 5.0, 5.0, 5.0, 4.0, 4.0, 2.0], 'Tree.yellow.sick': [0.0, 8.0, 15.0, 17.0, 17.0, 17.0, 17.0, 17.0, 18.0, 20.0, 20.0, 20.0, 20.0], 'Tree.red.sick': [0.0, 7.0, 10.0, 15.0, 17.0, 18.0, 18.0, 18.0, 18.0, 18.0, 20.0, 20.0, 20.0], 'Tree.blue.sick': [0.0, 2.0, 5.0, 8.0, 10.0, 13.0, 14.0, 15.0, 15.0, 15.0, 16.0, 16.0, 18.0], 'Tree': [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0], 'Time': [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0]}\n"
     ]
    }
   ],
   "source": [
    "print('Single repetition: ')\n",
    "for e in S_one_run.results:\n",
    "    print(e)\n",
    "print()\n",
    "\n",
    "print('Multiple repetitions: ')\n",
    "for e in S.results:\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2d06b66-b378-4cf7-9d94-91b1da88d429",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
