SpectralClustering.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "%config InlineBackend.figure_format='retina'\n",
    "\n",
    "from SuchTree import SuchTree, SuchLinkedTrees\n",
    "import seaborn\n",
    "import pandas\n",
    "import dendropy\n",
    "import numpy\n",
    "from scipy.stats import pearsonr, kendalltau\n",
    "from os import listdir\n",
    "from itertools import combinations\n",
    "\n",
    "from scipy.cluster.hierarchy import ClusterWarning\n",
    "from warnings import simplefilter\n",
    "simplefilter(\"ignore\", ClusterWarning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3 µs, sys: 1 µs, total: 4 µs\n",
      "Wall time: 5.96 µs\n"
     ]
    }
   ],
   "source": [
    "%time\n",
    "\n",
    "forest = {}\n",
    "for t in listdir( 'data/ncldv' ) :\n",
    "    forest[t] = SuchTree( 'data/ncldv/' + t )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dendropy\n",
    "from dendropy.simulate import treesim\n",
    "\n",
    "# generate coalescent trees\n",
    "for name,T in forest.items() :\n",
    "    taxa = dendropy.TaxonNamespace( T.leafs )\n",
    "    tree = treesim.pure_kingman_tree( taxon_namespace=taxa, pop_size=10000 )\n",
    "    tree.write_to_path( 'data/simulated/kingman_' + name, schema='newick' )\n",
    "    \n",
    "for name,T in forest.items() :\n",
    "    tree = treesim.birth_death_tree( 0.4, 0.1, num_extant_tips=T.n_leafs )\n",
    "    tree.write_to_path( 'data/simulated/bd_' + name, schema='newick' )\n",
    "\n",
    "for t in listdir( 'data/simulated/') :\n",
    "    forest[t] = SuchTree( 'data/simulated/' + t )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 249,
       "width": 394
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.linalg import eigvals\n",
    "from scipy.stats import skew, entropy, gaussian_kde, kurtosis\n",
    "import pyprind\n",
    "\n",
    "spectra = {}\n",
    "for a in forest.keys() :\n",
    "    L = forest[a].laplacian()['laplacian']\n",
    "    spectra[a] = L\n",
    "    plot( linspace( 0, 1, len(L) ), eigvals( L ).real )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/ck9h1OlzyemrpW8iIhJ7lEwCaKxtN2UbKjFeL6jhoohIRHjzzTc5+uij/UuxWrQsWUtOTm4z/6c//Ynvf//7/mRMfX09v//97wE4//zz/cedf/753HTTTdxwww0ceOCB7XoXeb1ePvroI2bMmAFAbm4uZ555Jk888QRXXXVVu7u5VVdX4/F4/BVP2dm+BTMbN25k2LBhe/2+W+J56KGHOOecc/zvf9OmTfzxj3/c6+uJhJMxhgOufJXtW9ax+OsvOWbyzLDFMmH6MTRNOZJl7z5K0vYvSHWBq/94UieewrTMfv7jRp1xHtuKT+DDJ6/msNLncBhLgnFzSMkz1Nz3Mu/mn82QE3/H0P75eL2W9Zs2Uvz1G8QXL8NZW4y3qQ48TbiMF6fDQW18Dp78/Rl68Mnk9B8etvcvIiLSHUomATRWt5sy1uubT0zv4AQREelpZ555JomJiRx66KEUFhZirWX+/PksWLCAyZMnc/TRR7c5fsyYMYwbN47TTjuNuLg4XnrpJdauXcsJJ5zQpmIpOzub5557jpNPPpmDDjqIo446inHjxuFwONi4cSOffvoppaWl1NfX+8+55557WLZsGf/3f//HBx98wKxZs4iPj2fdunXMmzePl19+2Z98Ouqoo7jtttu48MILOe2000hNTSUzM5PLLrusS+972rRpHH744Xz00UdMnTqVmTNnsmPHDl555RVmzZrVYcWSSERzOMgfOIz8gXufXA22uLg49jv2p8BPd3tcQW4OBZf/i7WLzsb7xjWMaFoBQIqp56gdD7Lz/mf4NGE8fRq3MtJuZGjz0rhOlb4My29kjWskJYNm4c0Zgys1i4TkNPpkZNA3J5vEzAL1ZhIRkYilZBJAU/vKJAAaKpVMEhGJELfccgvz5s1j0aJFvP766yQmJjJ48GBuvfVWLr74YuLi4toc/8wzz/CnP/2Jxx9/nK1bt9K/f3/mzp3L1Vdf3a4/0VFHHcWSJUu4/fbbmTdvHvPnzyc+Pp5+/foxc+bMNsvnwLf07JNPPuHOO+/k6aef5v7778fpdDJw4EB+8pOfMHZsay+VWbNm8de//pUHHniAO+64g8bGRgYPHtzlZBLASy+9xG9+8xteeukl7r77bkaMGMFf/vIXjjnmGJ55puNeLyISfMMmzcRO+ISl7z1F+ic3M9i7EYA+pprpjb47Q7IX+Z8R7tWM+G41fNd+XzXJbIofSkX2ASQNOYiB+88gK39Q+wNFRETCwFi7h7+chJkxZuGkSZMmLVy4MHQv8vk/4Y3ftp+/+BPoOy50rysi0gUrVvj+Aj5mzJgwRxIdZsyYwYcffkik//sWC7r6szt58mQWLVq0yFo7uSfikq7pkc9gUcx63Hz77kNkfnE7ue7t/nk3Dr5LGEtRzjTc6QNJSEojIT6eBuukqbERZ+V6Ujd/xNj6xV2+61yLCptCnUmi3iTgdiTgdqXQmJiDNzkPm5oLKX0hNY+41D4kuwzJcYaEzAIyB47FqHWDiIjsojufwVSZBB0ucwPUhFtEREREOmScLkYccyEc/RO2r/iUks2ryM4tIH/soYxMTGfkHs4vK9nBmo+exrX5M1LqdxDnqcblqcfpqSfNW0mGaV85n2FqyKAGLOBpfjQAe/jIutX0peSAi9nv+5fhcMV1eIy7oY7ysiKcDoPTgMthcDosroYKHE4XJmsYuOK78JUREZFYoGQSYBtqO65IVjJJRERERHbH4SR/3KHkjzt0r07LyunLtFMuBy5vt6/J7WHLlnUUrfqM+nWfkl7yFUMb15BkGvcpxH52B/2+nsv6pQ9RPP0P1BZMw1P8LQnbvyR52xf0r/qaPG8xObu5RgWprB12HhPPmotRUklEJOYpmQR43fU4O9qhZJKIiIiI9LA4l5P+g4fTf/Bw4McAuJsaqaoqpaG2isa6WmprqqjYWUJt2TYaK7YTV1dMQkMpKY0lxHlqabIGj9dS6NlIhqkBoNCzgcKPL9inmDKoZtLae/nmto/JPf9xcvMHBuvtiohIFFIyCbBN9R3vUDJJRCTqfPDBB+EOQUQk6Fxx8aRlFZCWVbBX51WUl/Phc7cwZdODpJiGTo9zWweVJhUPTlpazlmg0iaTaarJNb7PxWMbFrP9/47g7f5ngqeBzLpNWFciOeO/x9DDzgKnfr0QEYkF+r89vsqkFqU2jWxT5duorwxTRCIiIiIi3ZeRmckRF9xC0ZaLWPHf6yksm0+mt5wqVxZbU8ZSmTuF5BGHMmjsQWSlJbc7vy9Q39DAh49ex2GbH8BhLPmUkr/l3rYHfvAS2+b/mZ0HX8uoGWdjAa8FpwGnU82/RUR6GyWTANyt689LbEZAMqk8PPGIiIiIiARRXv9C8i57xL/dp/nRFYkJCRxx4W188+E0+r9/BRl0fPOaAs9WCuZfyo6PrqUJF+nUkm5qqSSVkoQBVKaPxJM3juRBE+g7bCJ9snJ1lzkRkSilZBJtl7mV2AxGsdk3X1/RcWNuEREREZEYM/aI06jc73AWvf1PkirWYuNTqEsrpHT7RqYVP+/vzdTXlLc5L51q0htWQvFKKH4Zlvvma20C5Y4+VMZlU5eQgycpB1LycKXnkZiZT2p2P9Jz+5OWOwjjSujhdysiIrujZBJgPa3rx0vI8I/dteV0fPNUEREREZHYk56dx6Qz/9BufsuW37H8xRs4oPhlUuikH+kukk0DyXY7/Rq3QyNQ1fFx9TaO7+JHUdtvGjkHHM/gA47AOPUpXUQknJRMAmgKSCbZ1mRSU81OJZNERERERPagf/8B9L/0AfD8A8o3gMMJCenUmGQ2bdpA2YZluLcsJrFsBbk1qylwbyHRNHXp2ommibFNy2DDMtjwb6pfTmZV8iSqcyeRVjCM5LwhJGX0JblPXzIzMohTjyYRkZBTMgnA03EyyVunu7mJiIiIiHSZ0wXZw/ybKcDokaNg5CjgVP+89XrZWV7GzqJNVBVvpm7nNtyV27FVxTjrikloKCWlqYw+nlL6mp1tXiKVWibXfgwbPoYNbV++1iZQYtKpjMumNrEvdQl5eF1JGKcLl9NJQpyLhPg4bNYw+k/5Phl9cnb7dmqqKqgs3kx8QxlOVxzOPgNIze6PMWqGISKxTckkaNuAm/TWed3NTUREREQk6IzDQZ+sHPpk5cDoiZ0eZ62lZMcmvl3wNp417zK08jMKKO30+GTTQDLFFDQVQ9PKTpfOAdR8/Fs+zTmB/GOvZMiI/aisb+LblcuoXfE2qVvnU1j9NZm2kpRdzttsCtiafyTZ085i6P6Hqom4iMSkkCSTjDHnAI82b15orf1XKF4nWIyndV13qW1NJjkbd/Ovj4iIiIiIhJQxhpz8QeTM/inwU9xuD+u/XULF8rdp2rEKV+Um0puKSPNWkmEriMfd5WunmAaml76A57H/sswxnAxPOZMcxXs8b4DdxoBtT8CLT1D6YgZVzkzcziSqEwtg5LHsP+snOOLiu/GuRUQiX9CTScaYgcDdQDWQGuzrh4QnoDIpYJlbnLvj256KiIiIiEjPc7mcFI6e2HE1k7U01lZQvGMLZds3UlO8gbiaHXg9jVh3E01uN41NbjxNdQyr+JwhXt8aOaex7GfXQAcFRg3WRZnpQ5nJwGndFNq2vZ6yqSDbUwEeoHElfPk+2xbdQcn0a9jvqHNUtSQivVZQk0nGt3j4IaAUeAG4KpjXDxXjbq1MqiCFJuskznhw2UZwN4BuRSoiIiIiEtmMIT4lk/5DM+k/dNxuD7VeLys+eQXv/+5iXN2X/vk6ElmfOoHq/oeRMvZohoyeQkGCi4Lm/fV1tSz63yu4lzzPmIqPSDN17a5d4N1Owf8u59tP/0aRySHbU0o+RWAc1MRlszN7Ep7hxzDy4BNJTNp1EZ2ISHQIdmXS5cBMYEbzc1QwAZVJDTaOKpLIorkqqb4SUnPDFJmIiIiIiASbcTgYc+gP4NAfULplLdXbVpPfN5+kgnGMcXW+RC0xKZlJR58BR59BU2MDW7eup7K8lOrKndSu/oD9Nz1OpqkBYLh3PcNZ33qyhYzGKvptWw/bXqDqo1+xKO0QKDycVE85yWUr8LgbacifzMgTLicxOa37b9RaULNwEQmBoCWTjDFjgFuAv1trPzLG7FUyyRizsJNdo7sd3J5eOyCZZF0JVNlkskxzMqlBySQRERERkd4qu/8wsvsP2/OBu4iLT6Bf4Sj6tUwcfgLFRb/mk2evZ0rRc8Qbz27PTzN1HFz9Dix7p+2O0nfZvvJRks5/mYwBo/Yqprr6RlYufA/PitcZXPIhufXrqXZmsDLvOMadfQtJaX326noiIp0JSjLJGOMC/gNsBK4JxjV7kvE0+Md90tOoqk5u3VlfEYaIREREREQk2uTmFZB76f1UFF/PtjWfkeD0Ep9RAH0Gs2lnPcXrlpCw/j2GFb1DP7u90+vke7ZT9O/j2PyjlxgwfDxVdY2sXTAP13fvkFC9BY+7kTobh9uRgNuZhNcRj6tqEyNqv2aiaXsToVRPBVO2PcWmexYy4Iq3MMlZof4yiEgMCFZHuP8HTATmWGvbLxzuAmvt5I4ewMogxdipwMqkPmkpVNGaTHLXKZkkIhJJnnnmGQ4//HAyMjJISkpi/Pjx3HzzzTQ0+P4wUF9fT2ZmJnl5ebjdHd/V56KLLsIYw2uvvdZmfuXKlcyZM4eBAweSkJBA3759Ofvss1m1alW7a8yZMwdjDN999x133303+++/P0lJScyYMQPw3c76kUce4eCDDyY3N5fExEQGDhzIrFmzePrpp9tcq7CwkMLCQioqKrjsssvo378/iYmJjB07lrvuugtrbbvXf/jhhzn11FMZOnQoSUlJpKenc8ghh/DYY491+rUrKyvj2muvZb/99iM5OZmMjAwOOOAArr76ampqatod+/vf/54xY8aQlJRERkYGRx11FG+99Van1xcREZ+M3P4MPvhU8qedTtboQ8nqO5ADRo/g6ONO5bCL76Xf/1vJ1h++ydeFP2FR6hH8L/NEXh34G94suIh6GwdAni0l4bHZPHbrpWy9eRIT3vsx+61/mBElbzO6/EMmVrzDgTtfY3rJcxxS9ATT6uaTZTq/G/XAhjVsfXiOb+mbiEg3dbsyyRgzFV810l+ttZ92P6QeZi0O2/rLhtOVQIMzBZr/H1tVXoaKQUVEIsM111zDzTffTE5ODmeffTapqam88cYbXHPNNcybN4+3336bxMREzjjjDO6//37eeOMNZs+e3eYaDQ0NPPPMM/Tt25dZs2b55998801OOeUUmpqamD17NsOHD2fz5s288MILvPbaa7z//vtMmjSpXUxXXHEF8+fP54QTTuD444/H6XQCcO2113LzzTczZMgQfvjDH5KRkcG2bdtYsGABzz77LGeccUab6zQ2NnL00UdTXl7OmWeeSWNjI88//zxXXHEFq1at4t57721z/MUXX8zYsWM5/PDDKSgooLS0lNdff51zzjmHVatW8ac//anN8evWrePII49kw4YNTJ48mYsvvhiv18vq1au54447uOiii0hJ8TWC3bBhAzNmzGD9+vUcdthhHHvssdTU1PDqq69y7LHH8s9//pMLL7xw37+RIiKxzhj6jZ1Ov7HT2+36/N2D2P+jn5FkGsllJz+ue2yvSgBKTR/WZx1Kcb+Z7Mw7CJY8xVnFfwegf9GHbH/vXvKPuixY70REYlS3kkkBy9tWA38ISkQ9zdN6a88m68TpdNDkSoPm6eqKEiWTREQiwKeffsrNN9/MwIED+eKLL8jPzwfg5ptv5uSTT+bVV1/ltttu45prrmHOnDncf//9PPLII+2SSS+//DI7d+7k17/+NS6X75/BnTt3ctZZZ5GcnMxHH33E2LFj/ccvX76cadOmccEFF7Bo0aJ2cS1atIivvvqKIUOGtJn/5z//Sf/+/Vm2bBnJyclt9pWUlLS7zrZt2xg6dCjLli0jIcF3F9EbbriBAw88kPvuu48zzjiDww8/3H/8smXLGDasbY+PxsZGjjvuOG655RYuuugi+vfv79/34x//mA0bNvDnP/+Z3//+9+3iSU1N9W+fd955bNiwgSeffJIzzzzTP19eXs6MGTO4/PLLOfHEE+nbt2+79yEiIt0z7aiTWZ2WRL/X55BK66KPOhJZnH0sxZkTiE9MIdXlxumpx9FUh/HUY1LzGDxuGrnDppDtaM0+1U27nudv38CpjS8CkD7/T9SOP4HkvCG7vrSISJd1tzIpFRjZPK43Hd8p4AFjzAP4GnP/spuvF3ze1mSSGycuh8EmpPuTSXVVO8MUmIhIF83NCHcEXTd335cOP/jggwBcd911/kQSgMvl4q9//Suvv/46//rXv7jmmmuYPn06I0eO5JVXXqGsrIysrNb+EI888gjgS5i0ePTRRykvL+eee+5pk0gCGDduHBdeeCF33nkn33zzTbv9v/3tb9slklrExcX5K5UC5eTkdHj8zTff7E8kAWRlZfGHP/yB888/n4ceeqhNMmnXRBJAfHw8l156Ke+99x7vvvsu5557LgALFy7kk08+YcKECfzud7/bbTyLFy/mww8/5LTTTmuTSALIzMzkhhtu4KSTTuL555/nkksu6fB9iIhI94yceizF/ebz3Tv3kW0qyRoygaQDf8xBSXv/Z+6keCcT5tzOt/9cwHCzhWTq+eahnzLkl2+RlNDxr4PehlrWL/2YxtoKcvsPJWvgaEx8Snffloj0It1NJjUA/+5k3yR8fZQ+BlYBkbkELqBfUhNOnA6DSUyH5pu5NVaXhycuERFpo6UqaObM9jcLHTlyJAMGDGDdunWUl5eTmZnJeeedx7XXXstTTz3lT3rs2LGDefPmMXHiRPbff3//+Z9+6vsnavHixcydO7fd9VevXg3AihUr2iWTpk6d2mG8P/rRj7j77rsZN24cp59+OkcccQTTp08nI6Pj5J/L5eLggw9uN9/Sg+mrr75qM79x40ZuvfVW3n33XTZu3EhdXduWhVu2bPGPP/vsMwBmzZqFw7H7tRItX4uKiooOvxbFxcWA72shIiKhkztgBLlz7gjKtYb1y+W9w25j6Pwf4TCWsXULuffOazn2J39gWK6vMrXJ7WHVl+/QsOAxRpW+w1Bq/ed7rGGrqz9F8QPxuFLxxiXjTMkmt18h/fY/kvh+46HjwgIR6aW6lUxqbrZ9QUf7jDFz8SWTHrHW/qs7rxNSntZ+SU24cDkNzuTWD/pNteVhCEpERHZVUeGraiooKOhwf0FBARs3bqSiooLMzEzOPfdc/vCHP/DII4/4k0mPP/44bre7TVUSQGlpKQAPPPDAbmOorq5uNxdYJRXojjvuYNiwYTz44IPccsst3HLLLbhcLo4//nj++te/Mnz48DbH5+TkdFjF1HL9lvcP8N133zF16lR27tzJYYcdxjHHHENGRgZOp5P169fzyCOP+BuSg295GtBm2VtnWr4Wb7/9Nm+//Xanx3X0tRARkcg18+gT+GTVGRxc/BQAF9f+kyfuWc+SoQcRV/IN4ys/Yj/T8R3mnMYy0LOZgXWbWyfLgE3A57DFNYgd065m0vd+FPo3IiIRodsNuKPeLsvcnA4H8Smt5aPe+spwRCUi0nXdWDoWTVoqerZv397hEq9t27a1OW7AgAHMnDmTd955h5UrVzJ69GgeeeQR4uLiOPvsszu89uLFi9tULHVFJ0u8cTqdXHHFFVxxxRUUFRXx8ccf89RTT/Hss8+yfPlyli9f3mZJW0lJCR6Pp11Cafv27W1iBPjb3/5GaWkpDz30EHPmzGlz/JNPPulfytciMzMTaFut1JmW1/n73//O5ZdfvsfjRUQkeky/8G/svPsr+lStwmEsP+ZNWPemb+cu/5xtJo/iuP5kNm1nsN2Ow3R+F7j+7o30/98lfLj0DUafdxd9s7Morazl6w9fIGfNc+R5izApOTB0BlmHnE98qrrSikS7vbgvQC8V2IAbFy6HISEt2z/nqi8LR1QiIrKLiRMnAvDBBx+02/ftt9+yefNmhgwZ4k+cAP5EyyOPPMLXX3/NkiVLOO6448jNzW1z/kEHHQTA/PnzQxJ7Xl4ep5xyCs888wwzZ85k7dq1LFu2rM0xbrebTz75pN25Le+35f2D7/0CnHrqqe2O//DDD9vNtby/efPm4fV6dxtrqL8WIiISPiY+hT4Xv0lNwbQO91eTzILs2Sw55mnyr1vJxGs/oPD6FZRe8R0rv/9flh16N4sm38wXY37PO3nn877zYKpskv/8Iypfofbug3n19guo+esBHLXwUg6ofJ+C6uXk7/iQ/E9voPb2/Vg+r7NOKWDLN7Hq3xew5s8H8e1DF2LL1gX96yAi3ReyZJK1dq611kT0EjcAb+syN7f19UxKz25dspDQqAbcIiKR4Cc/+QkAN954o79vD4DH4+Gqq67C6/Xy05/+tM05p5xyCunp6Tz22GM8/PDDAO0qeQDOP/98f3PpL774ot1+r9fbYRKrMw0NDbz77rtY2/avuE1NTZSV+f5Isesd3gB+//vft1meVlZWxo033uiPsUVhYSHQPrE2b948/vWv9v/sTp48mYMPPpivv/6aW2+9td3+0tJS6uvrAZgyZQqHHXYYL7zwgr/p+a6WLl1KUVFRh/tERCTCJWeR8rN51J76Hxb1PZWlmUfy7dBzKPn+Q6Re+x0H/uIx9j/4WFwuX6WsMYbcrCxGT5nJfkefy6TZlzD1jKs5+pI7OfIPb1B90UKWZszwX34I2/h+9bMMMh3/O5FJNeM+/TWL/vULbEDLEYD6LcuouvswRm16lhGNKxi+4Rka7z6I6sWvhOzLISL7RsvcPO3v5paVN8A/l+xWMklEJBIcfPDB/Pa3v+Uvf/kL++23H6eddhopKSm88cYbLFu2jEMPPZTf/OY3bc5JSkri9NNP59///jf33Xcf2dnZnHDCCe2unZ2dzXPPPcfJJ5/MQQcdxFFHHcW4ceNwOBxs3LiRTz/9tE3CZU/q6uo4+uijKSwsZNq0aQwePJj6+nrefvttVqxYwYknnsiYMWPanFNQUEBDQwP77bcfJ554Ik1NTTz33HNs27aNSy65pM2d3C655BIeeughTj/9dE499VT69+/PsmXLePPNN/nhD3/I008/3S6mxx57jBkzZnDNNdfw/PPPM2PGDKy1rFmzhrfeeouVK1f6k1RPPPEEM2fO5Kc//Sl33XUX06ZNIzMzk82bN7NkyRKWLVvGp59+Sl5eXpe+HiIiEmGMIXn8iUwaf2K3L1VQ0J+CX77It2/9H/0+nUsyrf9WVplU1vY/iRWp03EXr+ao0ifoh+8PQpM2P8qSv60h7vQHyM7Oxbv9GxKfOIlM23b5foKtx/nfc/lm662MmnUhTocafYtEAiWTOribW3ZeP/9cpq2kpsFNSie3zRQRkZ5z6623MnHiRO655x4effRRmpqaGDZsGDfeeCNXXnkl8fHx7c6ZM2cO//73v2lqauKss87q8BiAo446iiVLlnD77bczb9485s+fT3x8PP369WPmzJkdLinrTEpKCrfeeivvv/8+n3zyCS+++CJpaWkMGzaMf/zjH/4qq0Dx8fG88847XHPNNTz11FOUlJQwdOhQrr76an7xi1+0OXb//ffn/fff57rrruP111/H7XZzwAEH8MILL5CZmdlhMmnIkCEsWrSIv/zlL7z44ovcc889JCYmUlhYyJVXXtkmMTRgwAAWLlzI3XffzfPPP8/jjz+Ox+MhPz+fsWPH8otf/ILx48d3+eshIiK9nDEMn3Ux9VO+z5dv/ou4xgoGjJtO9sQTmRCXxITmw0rLruDLf57FlIbPAdi/5lPWP3gUL3in8kPn+2Qa380dqmwST6Wdx6zK5xnkKMaFl7Gf/4Y3P3+Bsuwp9B0whOz8QfTpO4i+/QaTmJgYnvctEsPMriX4kcYYs3DSpEmTFi5cGJoX2LIQHvDdZnqJdwjPT36MG2aPxf3HbFz4+kqs+dlaRvTLCc3ri4jsQcst2HetZJHeo6UiaP369WGNI9i6+rM7efJkFi1atMhaO7kn4pKuCflnMBGJSU1NTXz+wOUcWvREh/urbBL/m34/xx57IvMXLSP/5bMYwcZOr+e1hp0mg5qEXOozhmNHH8/ww8/C6Yrrckylaxexac1iBo2aRFbh/tByc43GWtzbllDnyiCtvz6HSe/Tnc9gKrcJWKfbcjc3HA6qHRlken1L3Iq2b1UySUREREREpJvi4uI49JJ/8NVrkxj15f8j2db69xWbbLYf/y+Oner7Y/9hk/ajuP9bLH/8AsZVftzh9RzGkk052Q3lULQGit5g3f/+iuP0Bxk8eve/HzeWbWL7fy5k0M5PyQb4DL6LG8HW0XNIr1nP8PVPkOytIQ1Y1ecIRl38FMS373koEouUTPLucjc3py8LXReXSWaDL5m0s3gLsHe3ihYREREREZGOTTzhQjjyVFj8FOxchyd9ILlTziM3MaPNcbl9C8j99WvYLV9RunQepZtX4y7fSlJ9EZnuErKoaHftIZ711D15LB+P/wOHnPoLTHOlUX1jExXVNVQ0GqoXv8zQz65hkK1sc+7QpjUMXXptu2uO2vkh2x77OQXnP9pauSQSw5RMCmzA3Xw3NwB3YjY0+G5DWV22IyyhiYiIiIiI9FrJWTD9EgCcezjU9J9ITv+J7LpepKmxge/Wf8em71Zj1r7LIUVPkGiaSDKNHLrsDyxZ/jiVJNPPu53+FNHXuOm7yzU81rDcMZKR3u9INE1t9pXaNLJNFQAFG1+mauHTpE05c9/fs0gvoWRSB3dzAyAll5Ykd32FkkkiIhI6va1XkoiISE+Ji09g1MgxjBo5BvgB333zY1zPnc8g72YA9rcrfQd2UkxUZPvw5YG3c8xxp1BWvIVVb91FypaPqXWkUTriVPpMPo2PH76QH9h3AXC/cQ12/AmYhLQeeHcikUvJpIBlbo24/JVJcWm5/nlPVUmPhyUiIiIiIiJ7Z+jYqdRf+QmLH7qY8cWv4zBtbzjlxokLD5UmnVXZMyk8/WaO7+u7m3de/kDyzr2t3TWrTrmN4ueOJNdU0MdTyqpnr2fUj//WI+9HJFIpmdRJZVJSn9biR1OrZJKIiIiIiEg0SEzJ4IDLnqB82zpq1n1OUkI8SXlDScwdiisxHTxNpDtcHNjF3keHjR/Gs19cxumbbgJgyJqHuezvBzK0bzqHuFYzMLGenH6FxI+YCWm7LqIT6Z2UTPJ2cDc3IDVngH8+011EfZOHxLg9reQVERERAGvtng8SEREJocyCIWQWDGm/wxm319c6/ke/ZOlfnme8dyXxxsM9Oy+CnW2PacLFkr4nM/bcO0hK0TI46d2UTPLscje35sokZ5/B/vmBpogt5XUMy03t8fBERIwxWGvxer04mhPeIpGuJZlkdMcbERHpBVIS40k95U4an5tNPE0dHhOHm8k7nmXdXxcQd+6zDCgc6d+3dc1XNH71NHHFy3A31FGWOIA+k0+lcOps3R1OopKSSZ5G/9BtnThaGnC3SSYVs3qnkkkiEh4JCQnU19dTU1NDWpr+yiXRoaamBvD9/IqIiPQGQ/abDqkv4n71KlwlK6hzZbAmYRwrG3MZ1vANkx1rfMd511P08DG8d/j9FNV46L/kLg5r+qTNtQZXfglvvMj6D8eTeeqdZA6bEo63JLLPlEzydlyZRMZAvDhw4CXf7OSDknIYmdvxNUREQigtLY36+nq2b98OQEpKCsYYVXxIxLHWYq2lpqbG//OqBKiIiPQqhYfiuuwzcDeQ5Epgf2B/oLq+ic9euYvJy24iznjIYyczPzp9z5erXUrTf47hi5G/5MAzr8U41FpFooOSSZ7WnklNAQ24ccZRnZBHeoPvw3B10XfAiDAEKCKxLisri5qaGmpra9m8eXO4wxHpsuTkZLKyssIdhoiISPC52lbepibGcdDpV7J20Ghy37iQdGranbIw8SBW5s4iJa0PyRs/YEbVK8QbD3F4mLr6ryy//WOGXvifNjeDEolUSiYFVCZ5cJLoaP1Lf33KAH8yqalkXY+HJiIC4HA4GDhwIGVlZVRVVdHQ0KDmxhKxjDEkJCSQlpZGVlaW+nyJiEhMGTbtBMoL3mb1Excxsn4JjSaekvzDyTzuOiYPmsjk5uOsncNnCz6nz5uXMtr7LQDjaj9n+92HUfWjZ8gbNiFs70GkK5RM8nr8wyacOAOSSWQOhrIvAXBWbOzpyERE/BwOBzk5OeTk5IQ7FBERERHZjcxB48i8ej401RHvjKdfB0vXjDFMn3oQjQf8j/n//hWHFT0BQL53B1X/OY5Vxz/MqKmz2pxTX72TbUs/ok9KAhnDpmBScsBaKPoGqrZB/gGQqtYs0jOUTPK2LnPz4sDlbE0mxecOhe9849QaJZNEREQkMhljfg+cAowCGoDPgN9ba5eFNTARkVgWl7THQ+ITEjnskn/wwcvTOHDhb0kxDaRRy4DXzuH9in9z5PdmA7D05b9TuOgWhlDrP3ersx9Jto4+3p0ANOJi1f5XM/6U34Tm/YgEUDLJev1DDw6cAeX4qf3H+Md9mzbT6PYS71K5voiIiEScGcB9wALAAH8E3jHGjLXWloUzMBER2bMZJ85hccFQ+r12DrmUk2IamPLxhTxc9ncGFb3HzNKn2p3Tz7O1zXY8bsYvuZHakWNI3u/7PRW6xChlRgIqkzw4WhtwA668kf7xULOVbRV1PRqaiIiISFdYa2dZax+y1i6z1i4FzgFygUPCHJqIiHTRAQceTtOPXqLcZACQZuqYs+JnbRJJO8hisR1Bk21dOrfTprLBm+ffdr9yFTS2VjCJhIKSSQE9kzzW0bZnUtYw/3CgKWZrSUVPRiYiIiIRyhhzmjHmbmPMfGNMpTHGGmMe28M5A4wxDxpjthpjGowx640xdxpj+oQgxDR8n/N2huDaIiISIv1GTCDuJ69S5Uhvt29p6iEk/uor9p+7gJ2/WMOyWU+zZPbrlF68nM+Pfo4ymwpAesM26r54uIcjl1ijZJINSCbhbFOZRHwyZS7fbRldxkv5ltU9HZ2IiIhEpuuAy4AJwJY9HWyMGQYsBM4HvgDuwNeZ8QrgU2NMdpDj+zvwNfBpkK8rIiIhljJwf1IueI2yxEFAcy+kMZcx/tevkJGRiTGGvJxs9pt+LPtPPoTh+Zmccsh4Hk84y3+Nho/vBa+3s5cQ6TYlk3ZZ5tamMgmoTBnsHzcWKZkkIiIiAPwKGAmkAxd34fj7gDzgcmvtSdbaq621M/EllUYBNwUebIy5sbnaaXePGR29kDHmb8ChwKnWBvzVTEREooaj3/5k/XYxFRcuwPz2O0adcRN0cFe4Fi6ng8Lv/YwKmwxAZv1mapa/0VPhSgxSMikgW+vGgcvR9kvSkNm61M1Z9m2PhSUiIiKRy1r7vrV2jbXW7ulYY8xQ4BhgPXDvLruvB2qAc4wxKQHzdwJj9vD4ooPXugM4C5hprf1u796ViIhEFIeDjP4jiUvO6NLhx08ewZvxx/i3t793X6giE9Hd3AIrk7wdVCY5c0bABt84pWpdT0YmIiIivcPM5ue3rLVt1hxYa6uMMf/Dl2w6CHi3eb4EKNmbFzHG/B04E5hhrV25F+ct7GTX6L15fRERCS+nw5Az4yJ4+0UAhpT9j6JNa8gbOKL9wU11UF8JqXlgTLvdtrqYlc/eQFV5CUOOvoDc8UeHOHqJNqpMatMzyYHL2fY/pOT+Y/zjnPoNPRaWiIiI9Bqjmp87Wy+/pvl5ZCf798gYcy++fkxnATuNMfnNj9R9vaaIiESfGdMPYqFzAgAOY3n38duoqm/y79+wciHLbz8W70394K8jqb9tLJWfPdr2Ig1VVP3fMYzZ8B+mVrxB1vOnw3cf9uC7kGigZFKbnknOdpVJWYPH+ccDvFtwe9TETERERPZKy/qEzm4L2zKf2Y3XuATfHdzeBbYFPK7a04nW2skdPYAuVzeJiEhkcDoMqYf+zL99dN2b/PI/n9Dk8fLJa4+S8+RxjKv+FAe+32sTa7eS/uYvmP/v39Gycrt63p9Ir25dKe3ES/1Lv2pzJ3QRJZO8u1Qm7ZJMSuwzkDoSAOhjqinasccbtoiIiIjsjZYPH3vsv9QZa63p5DE3OCGKiEi0GHX4D6lLyAMg11Rw6IZ7efzWSzh4wS9IMQ3+49y2NR1wyMZ/8sTTj+Ot2Eb8oofaXTOxYi1890HIY5fooWTSLsmkXSuTcDjY5uzv36zcrD/SiYiIyF5pqTzqrINq+i7HiYiI7DtnHEmz/uDfPN81jzmNT/q3t5q+vDD1KW4a/yaLXeMB35K4GSv+H/P/cRnxNAKw2DuUf7uP859X/+VjPfQGJBoomRTYM8m2v5sbQEnCAP+4qVRNuEVERGSvrGp+7qwnUktn1M56KomIiOydCT/GDjmi3fS3yRPIuHw+pxx/HNefNo0xlz5DlcP3N43+ppQj6t/xH7tq9KUsyf2+f9u1+jVoqA597BIVlEwKqExyd9AzCaAuMb/18IqtPRKWiIiI9BrvNz8fY4xp89nLGJMGHALUAZ/1dGAiItJLORyYMx/HO+Ec6p2pFDlyWTzmSob9+m1S+vT1Hxbfpx+JJ/293elLnWM58bQ5zDh8Biu8AwFweRvwfPtej70FiWxKJgU04PZ20DMJwJ3S+h+bqdrWI2GJiIhI72CtXQu8BRQCl+6y+wYgBXjUWlvTw6GJiEhvlpCG46R7SPzDFvL+37cccMb/w7ji2x0Wt/8peA44279db+NImn0rifEujh9fwP+cU/37tn3xQo+ELpHPFe4Aws7uuTLJphX4x67aHT0SloiIiEQuY8xJwEnNmy0lzNONMQ83j0ustYF3UrsE+AS4yxhzFLACmAYciW9527UhDllERKRTzh/ci3fYTDau/hrn/qczfOQEABJcThL3mw1LnwcgfdN7vtU9DmcYo5VIoGRSwDI3L6bDZJIzozWZlFRf1CNhiYiISESbAJy3y9zQ5gfABsCfTLLWrjXGTAH+CBwLHA9sA+4CbrDWloU6YBERkU45HDj2P53C/U9vt+uoo45hx5JM+ppy0r0VLP70bQ445NgwBCmRRMvcdrmbW0fL3BL6tDbgTm0s6ZGwREREJHJZa+daa81uHoUdnLPJWnu+tbbAWhtvrR1srb1CiSQREYlkBZkprMk8zL/91TtPsLW8LowRSSRQMimgZ5Knk2VuqTmtyaRMTyl4vT0SmoiIiIiIiEi47XfkGf7xTM8nXPbYAhrcnt2cIb2dkkl218qk9l+SPpmZVNpkAOJwQ53+gCgiIiIiIiKxIXPc0bjjMwAY5CjmwG1P8OdXl4c5KgknJZO8uzTgdravTMpKiWe77ePftpVbeiQ0ERERERERkbCLS8I1/SL/5u/jnuTcRT/ki9ceCmNQEk5KJgU24LYd90xKjndSQmsyqWHn9h4JTURERERERCQiHPJLbN9x/s1hjm1MXfBLtr/3jzAGJeGiZJINrExydNgzyRhDtas1mVSjZJKIiIiIiIjEkvhkzJzXaDzwYqpJ9k/nfnQNNWs/CWNgEg4xn0yyAQ24vThwmvbJJID6+Ez/uK6iKNRhiYiIiIiIiESWpD7En3AL2+d8xlI7FAAnXmqf/Am2oSrMwUlPivlkUuAyN2scODqoTAJoSsj2j92VO0IeloiIiIiIiEgkGl44mG2z/um/UVWuexvfPPrrMEclPSnmk0mBlUnWuDo9zpPUmkzy1pSENCYRERERERGRSHbMwVN5p/BK//a4Lc+w5vPXwhiR9KSYTyYFVibhcHZ6mEnJaT2stjSUEYmIiIiIiIhEvO//+FcsiJ/m385+8xLqSzaEMSLpKTGfTLJtkkmdVyY503L947h6JZNEREREREQktsXHOel3zj/ZadMAyLLllP37dGisDXNkEmoxn0wiYJkbjs6/HIkZef5xQuPOUEYkIiIiIiIiEhX6DxzC19P/TpP1rfTpV7eK7c/8KsxRSagpmdTFyqSkPgX+cYq7PIQBiYiIiIiIiESPGbNO4cmcX/i38799iqqNS8MYkYSakkkBySSzm55JGX1y/JnWJFsLTfUhD01EREREREQk0hljOO683/MxE/1z375yexgjklBTMskGJpM6r0zKTk1gJ2mtE7W6o5uIiIiIiIgIQG56Ip5DWpe3jSh5BzxNYYxIQknJpDY9kzqvTMpKiafUBiSTapRMEhEREREREWmRN+4IttosAFJtNWxZGOaIJFSUTApc5mY6TyalJrioCKhMaqgqC2lYIiIiIiIiItEkLSmejzz7t06s+yh8wUhIKZkUsMwNZ+fL3Iwx1DnT/dvV5UWhjEpEREREREQkqqQlxvGFd3TrhCqTei0lk9rcza3zyiSA+rgM/7iuUsvcRERERERERFqkJrhYbIf5t+2WRWGMRkIp5pNJJrAyaTcNuAHcCZn+cWNlaYgiEhEREREREYk+TodhR9wAam0CAKamCGrVIqY3ivlkUmBlkmMPlUk2MdM/dtcomSQiIiIiIiISKDUxge9sQetE8arwBSMhE/PJpMDKJLOHZBLJWf6hVXZVREREREREpI20RBff2n6tEyVKJvVGsZ1MsrZNMsmxh2VurtTWZJKpLw9VVCIiIiIiIiJRKS3RxQab3zpRvjF8wUjIxHgyyesfeq3B4dx9ZVJ8arZ/HNdYHqqoRERERERERKJSamIcW2zr786UbwpfMBIysZ1MCuiX5MaBy2l2e3hSRq5/nNBUEbKwRERERERERKJRWqKLLTandaJCyaTeKMaTSe7WIQ6cjt0nk1IzW5NJSe6qkIUlIiIiIiIiEo3S2yWTNocvGAmZ2E4m2cDKJCeuPSSTMrLy/OM0WwnWhiw0ERERERERkWiTlhhHke3TOlFTrN+de6HYTibtZWVSn4x0am0CAC480Fgd0vBEREREREREoklagotaEqiz8b4Jd71+d+6FYjyZ1NqA24MDl2P3X470RBcVpPi366tKQxaaiIiIiIiISLRJS3QBhlLSWydrisMWj4RGjCeTWiuT3F2oTDLGUG3S/NtVZTtCFpqIiIiIiIhItElNjAOgxAYmk1SI0dvEdjIpoGeSF8ceeyYB1Lgy/OPqcmVXRURERERERFr4KpOgrE0yqShM0UioxHYyydu2AfeeKpMAGuNa/4OoqygJSVgiIiIiIiIi0aglmbST1NbJ+oowRSOhEuPJpIAG3NaBy7nnZFJTfKZ/3FilZJKIiIiIiIhIi/TmZW41Nql1sqEqTNFIqMR2Msm2NuDuSs8kAG9i6y0O3dVlIQlLREREREREJBq1VCbVkNg6qWRSrxPbyaTAyqQu3M0NwCS3JpNsrZJJIiIiIiIiIi1SE3zJpOrAyqTG6jBFI6ES48mkve+Z5ErJ8o9NfXkoohIRERERERGJSmkty9zaVCYpmdTbxHgyadfKpD0nk+LTsv1jZ6OaiImIiIiIiIi0iHc5SHA52iaTVJnU68R2Msm2ViZ5utgzKSk9xz9OaFIySURERERERCRQWmJc22VutWXgaQpfQBJ0sZ1MarPMrWvJpJTM1mRSsqcyJGGJiIiIiIiIRKv0RBfVBCST1syDmwpg7XvhC0qCSsmklmEXk0lpmXn+cYpXHelFREREREREAqUluqixiW0nvU3wzg3hCUiCLraTSbZtA+6u9ExK65PrH6fbatxuz26OFhEREREREYktqYkuGohvv2Pb11C1vcfjkeCL7WTSLg24nY49fzlciSnU4+tOn2DcVFSqb5KIiIiIiIhIi7SEODydpRtK1vRsMBISMZ5MCqhMsl27mxtAtUnzj6t2Fgc9LBEREREREZFolZbo6jyZVPZdzwYjIRGUZJIx5lZjzLvGmE3GmDpjTJkx5itjzPXGmOxgvEZI7EPPJIAaZ7p/XFWuZJKIiIiIiIhIi7TEOLx08vt12dqeDUZCIliVSb8CUoC3gb8DjwNuYC6wxBgzMEivE1wBPZM8OHA5u5ZMqne1JpPqKpRMEhEREREREWmx28qkav0O3Ru4gnSddGtt/a6TxpibgGuA3wOXBOm1giegZ5IbZ5crk5riMqD53TZUlYUiMhEREREREZGolJbowttZMqlOv0P3BkGpTOookdTsmebnEcF4naDbZZlbV3smeRIz/WN3TWmwoxIRERERERGJWrtNJtXqd+jeIFiVSZ2Z3fy8ZE8HGmMWdrJrdPDC2UXAMjd3F+/mBkBSpn/ordkZ5KBEREREREREoldaYhwe21kySZVJvUFQk0nGmKuAVCADmAIcii+RdEswXydo9rEyySS39hQ39UomiYiIiIiIiLTYbc8kLXPrFYJdmXQV0Ddg+01gjrV2jx22rLWTO5pvrliaFJzwduENrExydjmZFJea5R87G8qDHZWIiIiIiIhI1PLdza2zZFK573dxh7NHY5LgCtbd3ACw1uZbaw2QD5wCDAW+MsaEJhnUXTawMsl0OZmUkJbjH8c1VgQ9LBEREREREZFo5euZ1Nnv1xYWPwUN1T0akwRXUJNJLay1O6y1/wWOAbKBR0PxOt1mvf6h1zq6fDe35IzWZFKiuzLoYYmIiIiIiIhEq7SE3SxzA3jpErj/CGis7bmgJKhCkkxqYa3dAHwDjDPG5Ozp+B63a88kZ9eSSSmZua1jj5JJIiIiIiIiIi12u8ytRem3sOz5nglIgi6kyaRm/ZqfPbs9KhwCKpM8mC7fzS01szUvlkY19U2R99ZEREREREREwiExzoHpSk+kzV+EPhgJiW4nk4wxo40x+R3MO4wxNwF5wCfW2si77VlAMsnuzd3cklobcGdSQ3ltU9BDExEREREREYlGxhiSE+L2fODWr0Mei4RGMO7mdixwmzHmI2AtUIrvjm5H4GvAvR24MAivE3yBPZMwXe6ZRHwKTbiIw02yaWBDRSX5GYkhClJEREREREQkuiQnJkDdHg6q2NwjsUjwBWOZ2zvA/fgabZ8C/AY4FSgDbgDGWWu/CcLrBN8uyaSuViZhDDWONP9mVXlJsCMTERER6TJjzFxjjN3lsT3ccYmISOxKTojf80F1ZWrCHaW6XZlkrV0GXBqEWHpem2RS1+/mBlDnSiez0bdyr6aiOOihiYiIiOylVcCMgG01dRQRkbBJSexCMgmgcivkDA9tMBJ0wVjmFr26kUxqcKVDo29cX1ka7MhERERE9pbbWqtqJBERiQhpSV1MJlUpmRSNeuJubpFrX3smAZ6ETP+4sUrJJBERkVhijDnNGHO3MWa+MaayeVnZY3s4Z4Ax5kFjzFZjTIMxZr0x5k5jTJ8ghTXUGLPFGLPOGPOUMWZokK4rIiKy19ITu1i7Ulce0jgkNGK7MsnbWv3t65nU9dyaNzGzdVxbFsyoREREJPJdBxwAVAObgdG7O9gYMwz4BN9dbl8CVgJTgSuAY40xh1hru/PXqc+BOc3XzWuO7xNjzLhuXldERGSfpHU1mVRfEdpAJCRUmdRsb5e5meSs1svU7gxqWCIiIhLxfgWMBNKBi7tw/H34kjyXW2tPstZeba2dCdwBjAJuCjzYGHNjBw21d33MaDneWvuGtfYZa+0Sa+07wPfxfc47LxhvVkREZG+ldjWZ1FAZ2kAkJGK7Mmlf7+YGuFJak0mOBiWTREREYom19v2WsTG7//zQvNzsGGA9cO8uu68HfgacY4y50lpb0zx/J7DbZXPAxt3EV22MWQ6M2MM1REREQiItMa5rB6oyKSrFeDLJ+od7W5kUn5btH8c16IdfREREOjWz+fktawP+kgVYa6uMMf/Dl2w6CHi3eb4EKNnXFzTGJOJbevd+F45d2Mmu3S7dExER2Z2uL3NTZVI0ivFlbrv0THJ2PZmUmJ7jHye4lUwSERGRTo1qfl7dyf41zc8j9/UFjDG3G2OOMMYMMcZMA54DUoBH9vWaIiIi3dHlyqSd66BKNyONNjFemRSwzM3uXWVSSkZrMinJXYW1do9l7iIiIhKTMpqfO/vrU8t8ZjdeYwDwJJADFAOfAQdZazfs6URr7eSO5psrliZ1IyYREYlhXa5MWv0m3DEOznwCRs4KbVASNDFembRrz6SufzkSApa5pVNFTaNnN0eLiIiIdKrlr1F2t0fthrX2TGttP2ttvLW2v7X2VGvtN0GKT0REZK+l75pMKjigdXzYlW33ed3wyi/btKKRyKZkUrO97ZlEUh//sI+pZmdNYzAjExERkd6jpfIoo5P96bscJyIiEvVSE3ZZ5jb4ULj4E99j6Iz2J1Rt1XK3KBLbySRvazWR3cu7uZGS6x/mUkFZdUMwIxMREZHeY1Xzc2c9kVruuNZZTyUREZGo026ZmzHQd5zv4ehkCVzxitAHJkER28mkgMokz95WJiWkUm8SfUPTREVFWbCjExERkd6h5Y5qxxhj2nz2MsakAYcAdfj6HImIiPQKu+2Z1FkyqWhlaIKRoFMyqZl3byuTgGpXln9cv3Nb0MISERGR3sNauxZ4CygELt1l9w347rr2qLW2podDExERCZmU+LYJI29gPySHs+OTKreEMCIJppi+m5u1Xn/HSy9m7yqTgLr4LGjaCkBjuZJJIiIiscIYcxJwUvNmfvPzdGPMw83jEmvtVQGnXAJ8AtxljDkKWAFMA47Et7zt2hCHLCIi0qMcu/x+3ej2kujf2UkqoqY4pDFJ8MR2Msnr8SeTMA6M2btkUkNiLjT/DdFTXRTU2ERERCSiTQDO22VuaPMDYAPgTyZZa9caY6YAfwSOBY4HtgF3ATdYa7VeXkREerUGtxeXx4vTYTCdJZP0e3XUiOlkktfrbV3nZzops9sNT3IOlDafrh96ERGRmGGtnQvM3ctzNgHnhyIeERGRSPf0l5v582dvUJCRyH3HJDOxo4NqSno6LNlHMd0zyQbczQ2z918Kk5LnH7tqVY4nIiIiIiIisjvbKup5/qvtHe+sUZFGtIjpZJLX29qAG8fefymc6X3944SG0mCEJCIiIiIiItKrVbs72VG3s0fjkH0X08mkwMoksw+VSQl98v3jpCa1OhARERERERHpyPHjC/xjL520mfE0gqezTJNEEiWTWsb70DMpOauff5zp1tpOERERERERkT3x7O7376aangtE9llsJ5Ns6zK3vb2TG0Ba36H+cT+7A6/XBiUuERERERERkd6l9XfuTiuTAJ7+MXx6bw/EI90R28kkb2Ayae8rk+Iy+lFHPACZpoaqcjXhFhEREREREdkd7+5SEes+gnnXwLr5PReQ7LUYTyYF3M1tHxpwYwzbTGvfpMqtq4MQlYiIiIiIiEjvtdtlbi2WPR/6QGSfxXgyKeBubvvQgBtgZ0J//7h4k5JJIiIiIiIiIrsK7FO822VuLbYsDGE00l2xnUwK7Jm0L5VJgCdzsH9cvU3JJBEREREREREADrvK9+yMZ+uY8/3Tnq4Uc5R+C4EFIBJRXOEOIJzaLHPbh55JAIl9h8P25uuVrgtCVCIiIiIiIiK9wOG/gb5jIXcMTZU5wFoAPF2pTGqqhcotkDkwtDHKPonpyiQCkkn7WpmUO2isf5xT8y3W6o5uIiIiIiIiIsQlwn6n+hJKAWxXUxEVm0MQlARDTCeTApe54di3yqS+o6f7xyPtOorKyrsZlYiIiIiIiEgvZkzXjqtpf8f0iuItLHnoCnb864d4/ncPNNUHOTjpihhf5taaTHLsYwNuR0oWm50DGeDZRJzxsGn5J/Q9/IRghSgiIiIiIiLSyxmgg1U+NUW7bJfSeP/R7N+01be9eR7lH/8fnpPuJ6Fwqm/OejHVO8DdkmQKSFz5k1hmD9tdPL6DOdvumD29lml7ePsNAFxx8SQmpbSbD5fYTia1qUza9yKt4sz9GVC6CYD67z4FJZNEREREREREuiYxA+rL289Xt61M8r5zPbktiaRmmXWb8D5xPIvtMFKoY5ApItE0hTDY8Pg8+wdM+8Wj4Q7DL6aXuQX2TNrXyiQAT/8D/eO0ogXdCklEREREREQkpiRmdDwfuMytajvm6yf9m895DqfSJgHgMJaJjm8Z6djSKxNJkSimK5MIQs8kgMyxM2HJXACG1S4Bjxucsf2lFREREREREemSxPSO52tLW8fLX8RYNwALvCN5c/j1pA1z0+/D3zK+aXGb08ptKpX4loSZ5uVzrc90OE8n83s6Ppiv0dn1AawjvsP5cInpjEfgMjdHN5a5DR6+H9ttFvmmjFRqqVy3kPTh04IRooiIiIiIiEjvltBJZVJjdet49Rv+4X89h3HQ0CxmHToUDv0Idm6A8g2QkAZ9hpCZlElmaCPucQeFO4BdxPgyt9ZkkulGZVKcy8mKxAP822XL3+lWWCIiIiIiIiIxIyGt4/nGGt+zxw2bWlvKvO+ZwOTBfVqP6zMYhhwO/SZCUmbo4hS/2E4m2daeScbsezIJoCxnqn/s3fxlt64lIiIiIiIiEjNcCR3Pt1QmFa+AJl9iaavNotSVy7h+nVQzSY+I6WRS4DI34+xeMilx8GT/OGPn8m5dS0RERERERCRmOOM6nm9oTiYVrfBPLfUO5YABGcS7YjqdEXax/dUPUs8kgP6jJtFgfS2ost07oL6iW9cTERERERERiQnZIzqeb1nmVrLaP/Wt7cekwCVuEhaxnUxq0zOpe1+K0f2y2GDz/dt121Z263oiIiIiIiIiMSGtL8z+Oww9Es56unW+ZZlbyRr/1HfefkwepGRSuMV2MimgZ1J3K5MS45wUxQ/0b2/7bmm3riciIiIiIiISMybPgXNfhBHHAMY311QLXg/eik3+wzbYPFUmRYAYTyYFVia5un25hoyh/nHlltW7OVJEREREREQkhmW0FmNQeFjr2OGA+JTW7cYamsq3+zfjMwvISe2kYbf0mO5nUKKZtf5hd5e5ASTlDIJS37ihbEu3ryciIiIiIiLSK/3oOfj4bzDkcMge1nZffGrrErfHTyehpvX360GDh/RgkNKZGE8mBTbg7t7d3ADS8gbBKt84oW5Ht68nIiIiIiIi0ivljYZT7u94nyu+dbzpM/+wyiYxfki/EAcmXRHTy9xMEHsmAaTmDGgdN5V0+3oiIiIiIiIiscZDx8UexTaDyeqXFBFiOpnUtmdS9yuTMvoO9o+zvEomiYiIiIiIiOyt4lpPh/NVJo0ReWk9HI10JMaTSa09k4KxzC0zpz8e6+s6n0UVdbW13b6miIiIiIiISCxp8JgO5+OSUnA6Ot4nPSvGk0mBPZO6/6VwuFyUmdaSu7LtG7p9TREREREREZFY4u4kVTGwb24PRyKdielkUtueScHpRb7TleMfVxRvCso1RURERERERHqLgEVCHeqsZ1JaWkYIopF9EdvJJAIqk5zdX+YGUJPQmimtK1UySURERERERGRveG0nS9niU3o2EOlUTCeT2vRMcgbnS9GY1Nc/birfGpRrioiIiIiIiEQzsxetjjotXFIyKWLEeDIpsGdScCqTSGmtTPJUFwfnmiIiIiIiIiIxwna2Di4uuWcDkU7FdDLJEeQG3ACutDz/2FlTEpRrioiIiIiIiMQKVSZFvphOJhHQM8npDE4D7oTM1mVucQ2lQbmmiIiIiIiISMzorDJJyaSIEdPJJBOCZW4pWf384+SmsqBcU0RERERERCRWmM5qk5RMihixnUwK+AF1BimZlJnbmkxK8+wMyjVFREREREREYkZnlUkJaT0bh3QqtpNJ1uMfB+tubhnZBf5xlq2krtGzm6NFREREREREJFCnPZNS8jrbIz0sxpNJrT+iDldweiY5kjJoIA6AZNNAcZmWuomIiIiIiIh0XSfppIC7p0t4xXYyKbABd5Du5oYxVDoy/ZvlxVuCc10RERERERGRGNDZKjdSlUyKFDGeTAromeQMTs8kgBpXH/+4snRr0K4rIiIiIiIi0pt5vbbzBtwJ6T0bjHQqtpNJgT2TgtSAG6AhMds/rtu5o+1Oa2H9x7BzfdBeT0RERERERKQ38HRalgQY03OByG7FdjKpTWVScHomAXiScvzjpsrtrTushed+Ag+fAHdNhG9eCtprioiIiIiIiEQ7j9fSLmXUfwr86LlwhCOdiO1kkm3tmWSCuMzNpAZ0mK8uaR2v+wiWv+AbWy+8cTV4moL2uiIiIiIiIiLRzN3RMrcL34UR3wtPQNKhmE4mOQJ+QF3BasANxKW3JpMcdQHJpKXPtD2waits/jJorysiIiIiIiISzTweS6d3c5OIEePJpNbKJEcQK5OSMvP944T60tYdmxe2P3jjJ0F7XREREREREZFo5vZ693yQhJ2SSc1cQeyZlJpd4B+nuMsAaKqvxlu8qv3BW78K2uuKiIiIiIiIRLMOeyZJxIndZNIuHeKdzuB9KdKyWpNJGd4K6ps8zP/4ozbJK7/i1UF7XREREREREZFo5vZqiVs0iOFkUmtix2NNUHsmOdJaeyblmAqKKhvYuvIz/9zbnkmtr126Vk24RURERERERGipTFJCKdLFbjLJ62kd4sDpCGIhXXKOf9iHajaUVBBftNQ/96Udww6bCYDTutmxeW3wXltEREREREQkSqkyKTrEbjIpoDLJiwOXM4jJJKeLakc6AA5jmbfgG0azzr/7nJNPpMTRWr1UunVdu0uIiIiIiIiIxBq3x6vKpCigZBLgxQS3Mgmojcvyj5evWMkos8m/PWDMVBqS+/q368o2B/W1RURERERERKKRWw24o4KSSfiSSa4gJ5MaEluXuk1lKQnG7ZtPHQDJWTQm5/v3u3duCepri4iIiIiIiEQj9UyKDjGcTAphzyTAndrPP/6ec6F/HD9gou81U1vv+Gaqtgb1tUVERERERESikXomRYcYTibtWpkU3C+FyRzgH09xrG6dLzgAAEdmf/9cfO32oL62iIiIxBZjjNMY8ydjzDpjTH3z843GGFe4YxMREdkbHq+XFz2HtE6MmBW+YKRTsfsBw7ZmO0NRmRSfNajjHc3JpKSs1mRTcn1RUF9bREREYs7vgEuB84ClwP7AI0AD8KcwxiUiIrJX3B7LA54TKHTsYHByEwfO/nu4Q5IOxHAyKbQ9k1L6Du14R3MyKTWvNdmU4S4O6muLiIhIzDkYeMVa+0rz9npjzMvAtDDGJCIistc8XksD8VzVdBHTs7N5Mr1gzydJj4vdZW7ewJ5JBqczuMmktAH7tZ9M7w9pvru4ZfUd7J/O9pa1iUdEREQimzHmNGPM3caY+caYSmOMNcY8todzBhhjHjTGbDXGNBhj1htj7jTG9AlCSB8DRxpjRje/1lhgJvB6EK4tIiLSYwJ7JrmC/Hu6BI8qk/Atcwt2ZZIjox+VpJJOdevkoIP8w8yMdCpsChmmBpfxUltRRHKfDjKu7gaaFj9DXZ/RpA89MKgxioiIyD67DjgAqAY2A6N3d7AxZhjwCZAHvASsBKYCVwDHGmMOsdaWdiOeW4E04BtjjAffZ7ybrLX3deOaIiIiIWF302PbE5BMCnY7GgmeblcmGWOyjTEXGGP+a4z51hhTZ4ypMMZ8bIz5qTEmMqufdkkmBf2H1Bi2pI5rOzf86IDdhp2OTP/2zh1bOrxM/XMXEffKZaQ88j2WvP9ccGMUERGRffUrYCSQDlzchePvw5dIutxae5K19mpr7UzgDmAUcFPgwc3Ns+0eHjMCTjkDOBc4G5jUPL7EGPPTbr5PERGRHtWmMknJpIgVjETP6cAD+Nbkfw7cCTwP7Af8C3jGGBN5PwEhvpsbwLDjrmjdSM6BMSe22V/tyvKPK0s6SCaVfEviyhcAcBpL8hdqPCYiIhIJrLXvW2vXWLu7v636GGOGAscA64F7d9l9PVADnGOMSQmYvxMYs4fHFwHH3wbcbq19ylq71Fr7H+BvwO/3/t2JiIiEj8fb+ru6KpMiVzCWua0GTgRes7Y1Q2OMuQbfh5xTgVPwJZgihtfj9mfSLIZQ/IzGjzsBPP+CsrUw/nRISG2zvz4+G5p847ry7e0v8N37bTYH130DTfUQlxj8YEVERCRUZjY/vxX4WQnAWltljPkfvmTTQcC7zfMlQMlevEYysGsDRg9d+MOhMWZhJ7t2u3RPRERkb3T1V+62lUmRudBJglCZZK19z1r7SgcfjrYD/9e8OaO7rxNsgdlOLw5CVjy1/+kw42rIHtZulzs5xz9urOggmbTp8zabcbhhx/KghygiIiIhNar5eXUn+9c0P4/sxmu8AlxtjDnBGFNojDkZ+DXw325cU0REpMepZ1J0CHUD7ua6G9whfp295m1zN7cwZTtT8qDYN7TVRe12e4vXtIvMU7IG54DJoY9NREREgiWj+bmik/0t85ndeI1fAH+itTfTNnxtCP64pxOttR1+sGiuWJrUjZhERET2mtujnknRIGTJJGOMC1/zR4A3u3B8j5ZYuz0eEprHtssFd8HlSs/zj501xW13Wost+67dObXbVpI2IcSBiYiISE9q+SCyx/5LnbHWVgG/bH6IiIhELVUmRYdQluTcgq8J9+vW2nkhfJ194nW3VibZMN1wLjGzwD+Ob9jlbsB1O3E2VrY7p6l4bajDEhERkeBqqTzK6GR/+i7HiYiIxKymgJY0LqeSSZEqJJVJxpjLgSuBlcA5XTmnp0usPZ7WlXfhWuaWlt3PP05p2iWZ1EFVEoCt2BrKkERERCT4VjU/d9YTaUTzc2c9lURERGKGRw24o0LQvzPGmEuBvwPfAEdaa8uC/RrB4LEBlUlhWuaWmdvfP87wlLfdGZBMWu1tPS6upoNG3SIiIhLJWm7PeowxbcuhjTFpwCFAHfBZTwcmIiISaQJ7JmmZW+QKajLJGPNL4B5gGb5EUsRmPrye1tK5cC1zS89trUzKooLahkb/tqekdTnb594x/nFyQxHYfW6pICIiIj3MWrsWeAsoBC7dZfcNQArwqLW2podDExERiThtK5OUTIpUQVvmZoz5Hb4+SV8D37PWlgTr2qEQuMzNhmmZm4lLoppkUqnFZbxsLdrOoIGDAKjettrfWGG5LaTKJpFm6nDZRqjbCclZYYlZREREwBhzEnBS82Z+8/N0Y8zDzeMSa+1VAadcAnwC3GWMOQpYAUwDjsS3vO3aEIcsIiISFdyBDbjVMyliBSWLYoz5A75E0kLgqEhPJEFkVCYBVDj7+MflxVv8Y3dAZdLOhAFstwHJo8rW40RERCQsJgDnNT9mNc8NDZg7LfDg5uqkKcDD+JJIVwLDgLuA6dbaXZonioiIxCZPYANuVSZFrG5XJhljzgP+CHiA+cDlxrT7hq+31j7c3dcKJo83/D2TAGrjssDjSw5Vl23zzydWbfCPBw/fj+0r+jCC5iRS5TbIH9+jcYqIiEgra+1cYO5enrMJOD8U8YiIiPQWbSqT1IA7YgVjmduQ5mcn8MtOjvkQ31/iIkakVCY1JuZAvW9cv7M5mVRfQYq7HIAGG8ek8ePYsaK1MqmpfBNxPRyniIiIiIiISKipZ1J06HYWxVo711pr9vCYEYRYg8rrbfKPw9UzCcCTnNs6rioCwFvaeie3jTaPAwb1oSo+zz9XW7y55wIUERERERER6SFtK5OUTIpUMVszFimVSc601iSRqfYlk0o2rvTPbXUUkJ+eSGNSX/9cffnWngtQREREREREpIeoMik6xGwyKbBnEmFMJsVl5PvHrjpf3/KyTa3JpNrUQRhjMGmtySRv1faeC1BERERERESkh7g9qkyKBjGbTPIGdIgP5zK3lD4F/nFio+9GLo3F3/rnnDnDAIjPbE06OWqKeyg6ERERERERkZ6ju7lFh9hNJrndrRvt7z7XY9Jz+/nHae6dAMRXtt7JLb3/KACSs/r75xLqlUwSERERERGR3qdNzyRnzKYsIl7MfmfaVCYZZ9jiSM1uTSZls5OvN5WTWd/aYHvgsP0AyAxIOqU2lYFt/Q9MREREREREpDdQz6ToEMPJpNaeSeFswG3S++PF9x9IHuX88en55BtfhZIbF/0HjwCgb3YWVTYJABduqNsZnoBFREREREREQqRJPZOigpJJENZlbjjjKHf0AcBhLP3KPvfvcmcNA6cLgILMRIptRut56pskIiIiIiIivYx6JkWHmE0mGeOkmiRqbQJeR0JYY6mIa71T2xGOxf5xYsFY/zgnJYFSMv3bDTu39UhsIiIiIiIiIj0lsGeSSz2TIpYr3AGEywEzT4eZpwMwMcyx1CYVQMMKAI5yLmrdkTvGP3Q4DFVxWdBcUFVevJm+I3syShEREREREZHQUs+k6KA0XwSoSy/0j7NMdeuOvNFtjmtIyPGPa0q3hjosERERERERkR7V5m5uSiZFLCWTIkH28I7nAyqTADzJef5xY4WWuYmIiIiIiEjvosqk6KBkUgQYvf+U9pMJ6ZA9rM2UI721t5K3akeowxIRERERERHpUapMig5KJkWA1IETsXHJbScHTQeHs81UQmaBf+yqLeqJ0ERERERERER6TNu7uSllEan0nYkErnjM4EPazo2Z3e6w1Oz+/nFCQ2mooxIRERERERHpUW6PKpOigZJJkeKI34EzwTcumADjT2t3SGZeazIpzV3WQ4GJiIiIiIiIBI/FdrqvTc8kp5JJkcoV7gCk2cAD4WcfQNl3MHQGxCW1OySv7wD/OMNbgfW4MU59C0VERERERKR3UM+k6KDKpEjSdyyM+T4kpHa4OzMtmTKbBoDTWKrKtvdkdCIiIiIiIiL7pot5Id3NLToomRRFjDGUO7P828XbNoUxGhEREREREZHgUmVSdFAyKcrUxmf7xzuLlEwSERERERGR3kN3c4sO+s5EGXdSrn9cU7IljJGIiIiIiIiIBJfu5hYdlEyKMia9wD9uKlcySURERERERHoPt3omRQUlk6JMXNYg/9hVpWSSiIiIiIiI9B5tGnA7lUyKVEomRZm0vEL/OLl+W/gCEREREREREQkyt3omRQV9Z6JMTv9h/nGWu6hN1lZEREREREQkmnl0N7eooGRSlEnKHewf96OEHRV1YYxGREREREREJHjUMyk6KJkUbRIzqTNJACSbBrZu2xrmgERERERERESCwxN4Nzf1TIpYSiZFG2Moj+vr3yzb9l0YgxEREREREREJHlUmRQclk6JQfXKBf1xXtC6MkYiIiIiIiIgEj3omRQclk6KQJ2OQf2zLlEwSERERERGR3kF3c4sO+s5EIVfucP84sXpDGCMRERERERERCQ6v1xJ4w3IVJkUuJZOiUFq/Uf5xn/pNYYxEREREREREJDg8tm2/JGOUTYpUSiZFocwBo/3j/t5t1DS4wxiNiIiIiIiISPepX1L0UDIpCjmzCvE0f+v6Ucrm4rIwRyQiIiIiIiLSPbqTW/RQMikauRIoc+YB4DCWkk1rwhyQiIiIiIiISPe4Pa3Nt1WZFNmUTIpSFckD/eOabavDGImIiIiIiIhI97WpTHIqXRHJ9N2JUo3phf6xt3Rt+AIRERERERERCQKPlrlFDSWTopTJHu4fx1WsD18gIiIiIiIiIkGgnknRQ8mkKJVSMMI/zqzbEMZIRERERERERLrP4wm4m5tTyaRIpmRSlMoaPNY/7ufejDcggysiIiIiIiISbdze1gbcLofSFZFM350oldp3OE24ACgwZRSVloY5IhEREREREZF9F9gzSXdzi2xKJkUrZxzbnQX+zeL1y8MYjIiIiIiIiEj3qGdS9FAyKYqVJQ32j2u2rghjJCIiIiIiIiLdo8qk6KFkUhSrSx/aulG8OnyBiIiIiIiIiHSTKpOih5JJUczkjvKP48q/DWMkIiIiIiIiIt3jCWjArcqkyKZkUhTLHjzOP86o2RDGSERERERERES6xnZyM3K3J7AySemKSKbvThQbOGJ//3iAdwsV1fVhjEZERERERERk36lnUvRQMimKJaRls9NkApBomljzrZpwi4iIiIiISOQx7Dk51KZnklPJpEjmCncA0j07kwfTp6YcgB3fLYUJEzs8zlO5nU2L5lFQtZwEGmDcKTD0iB6MVERERERERKRzqkyKHkomRTlP1gioWQxA3baV7Q8oXkXTK1cRt/EjCgPnFz4M378DpvykB6IUERERERER2b0mT2sDbt3NLbJpmVuUS+k3xj+O37nLHd12bsDz4LHEbfyow3Pdr/2OuhI17hYREREREZHwU2VS9FAyKcrlFO7nH+c1bqSyvsm/Xf3Sb3DWlQHgtYbPvaO5y30Sa70FALhsI4tfvKNnAxYRERERERHpQNueSUpXRDJ9d6JcfN9R/vFQs41lWyoAX/+k1PXz/PvO8VxH0an/ZfRZt/JUeuvStv5b3+r8vowiIiIiIiIiPSSwMknL3CKbkknRLnMQTSYegDxTzur1mwFY+faD/kPes1O4ZM4cZh/Qj2PG5fOriy+m2iYCMNC7haJvF/V83CIiIiIiIiIB3FrmFjWUTIp2DifVKYP8myUbllPX6CF32/v+udyDf8whw3P828kpaSxJme7f3rbgvz0Tq4iIiOw1Y8zhxpiXjTFbjDHWGDNnX44RERGJdB6vGnBHCyWTegGTM9I/du9YxdtffM1Y1vm2cTLusJPbndNYeJR/nLBxfuiDFBERkX2VCiwDrgDqunGMiIhIRGtbmaR0RSTTd6cXSB0w1j/OqVnNt/97wb+9I3MSjuTMducMPvA4/3ho3TIa66pDGqOIiIjsG2vt69baa6y1zwHefT1GREQk0qlnUvRQMqkXcA080D+e5FjDftWf+rczJ8zu8JzCwmGsMwMBiDduvv3yndAGKSIiEiWMMacZY+42xsw3xlQ2Lxt7bA/nDDDGPGiM2WqMaTDGrDfG3GmM6dNTcYuIiEQ7t0c9k6KFkkm9wYDAZNK3HONc6N9O2e+EDk8xxrAte5p/u+Kbt0MXn4iISHS5DrgMmABs2dPBxphhwELgfOAL4A7gO3xLzj41xmSHLFIREZFeRJVJ0UPJpN4gJZuK5MHtpmszR0HO8E5PSx59tH+cU/Rpp8eJiIjEmF8BI4F04OIuHH8fkAdcbq09yVp7tbV2Jr6k0ijgpsCDjTE3Nlc77e4xI6jvSEREJAq06ZnkVDIpkimZ1Eu4+x/Ybi5pwim7PWfktFm4re9HYJj7O7Zv3+MfX0VERHo9a+371to11lq7p2ONMUOBY4D1wL277L4eqAHOMcakBMzfCYzZw+OL7r0LERGR6KO7uUUPV7gDkOBIm3AKrHnOv20xmP1O3e05yWlZrE4YzcjGb3AYy7efv0H+Dy4IdagiIiK9yczm57estW0aX1trq4wx/8OXbDoIeLd5vgQo6dEod8MYs7CTXaN7NBAREYl5uptb9NB3p5eIHz2L7+JH+rcbJ5wLOSP2eF51v0P8Y/vteyGJTUREpBcb1fy8upP9a5qfR3ayf4+MManGmAnGmAn4PrsNat4etDfHiIiIRDr1TIoeSib1Fk4XWT9/jcUjr6Bo5t9ImP23Lp2WN/E4/3h85QfcPW8JtY3uUEUpIiLS22Q0P1d0sr9lPrMbrzEF+Kr5kQTc0Dz+414e0yFr7eSOHsDKbsQsIiKy15p0N7eooWVuvUhmdh6ZZ+/xM2Mb/cfPYPuLeeTbIjJNDSM+/jX3fDGRQw+cyPTvnY5xxoUoWhERkZjQ8kl4j/2XOmOt/SDgOvt8jIiISKRTz6ToocqkGGccThyH/cq/faxzAb/13M/Bn11MyR2HQNX2MEYnIiIS8VoqjzI62Z++y3EiIiLSicCeSS6n0hWRTN8dIW/Gz7Gjv99uPrd6FTX/ng0N1WGISkREJCqsan7urCdSSwPDznoqiYiISDP1TIoeSiYJOJyYH/4HTn+YxmmX8UHS0bit70cjpXw1tfP2bumciIhIDHm/+fkYY0ybz1XGmDTgEKAO+KynAxMREYk2be/mpmRSJFMySXwcDhh3MvHH3cTYix/nFueF/l2Jix7AvUM9OEVERHZlrV0LvAUUApfusvsGIAV41Fpb08OhiYiIRB2PR5VJ0ULJJGknLz2RmWf9hk+84wBw4GXVs9eHOSoREZGeYYw5yRjzsDHmYeDq5unpLXPGmNt3OeUSoAi4yxjzojHmZmPMe8Cv8C1vu7bHghcREYliqkyKHkomSYcOHpHL5olX+bdHF89j8zpVJ4mISEyYAJzX/JjVPDc0YO60wIObq5OmAA8D04ArgWHAXcB0a21pTwQtIiIS7drczc2pZFIkUzJJOnXaD05mSfwEAJzGsu71O8Maj4iISE+w1s611prdPAo7OGeTtfZ8a22BtTbeWjvYWnuFtbYsDG9BREQkKrWtTFK6IpLpuyOdcjgMroNb2z/sX/QyJWX6TCwiIiIiIiLBp7u5RQ8lk2S3xhx+Klsd/QDIMDV89co/whyRiIiIiIiI9EbqmRQ9lEyS3TIOJzv3m+PfHrbucWrqm8IXkIiIiIiIiPRKqkyKHkomyR6NPu4iakgCYChb+OjNZ8IckYiIiIiIiEQr28m8KpOih5JJskfOpAw2DT7Fv523+D4am9xhjEhERERERESiielCbqjN3dzUgDuiBeW7Y4w5zRhztzFmvjGm0hhjjTGPBePaEhmGnPBrPM0/LpPtMubdeiZPPPUoK75Zgg34D15ERERERERkXzR5VJkULVxBus51wAFANbAZGB2k60qESMgbzlcDf8zETY8CMNv9Nqx8G1bC6oRxDDzvXyT1GxvmKEVERERERCRatemZ5FQyKZIFq27sV8BIIB24OEjXlAgz5uxbWZsyqd38yIbluB84htqNX4UhKhEREREREekN3GrAHTWCkkyy1r5vrV1jre2sj5b0AolJyQz79ds0nfwvthWexLrEsXit7z/wNFtF00M/oHrryjBHKSIiIiIiItFIPZOih747snecLuIOOJ2COY8w5OpPeenA/1BhkwHIsBXU/OtEtm1eF+YgRUREREREJNq41TMpakRMMskYs7CjB+q/FNFO/v5sPjrwPupsPAB9vTuofGA2f/3vJ+ysrod1H8GXD0Lp2jBHKiIiIiIiIpFMPZOiR7AacEsMm/39k3nHU82MRZfjMl5GmU0UfH0qdV8nginzHeSIg9MfgjGzwxusiIiIiIiIRKTAZJIqkyJbxFQmWWsnd/QA1IQnChz9g3PYcOht/u10U0vflkQSgLeJxhcuxdaV93xwIiIiIiIiEvHUgDt6REwySaLfsO9dgD37GeqSCvxz5TbFP45vqmDRqw+EIzQRERERERGJcKpMih5a5iZBZUbOIuk3y3FvXcKitVt4aH0WeWue4QbXQwAkrX0d+E14gxQREREREZGI49bd3KKGkkkSfA4nrgETmTpgIlOPgFWr+8ATvmTS0PqleBrrccYnhjlIERERERERiSSqTIoeSvVJyI0cMZoN+Ja+JdLExiUfhjkiERERERERiTTqmRQ9glKZZIw5CTipeTO/+Xm6Mebh5nGJtfaqYLyWRB9jDBszpjC44hUAype/A1NmhTkqERERERERiSQeT0BlklPJpEgWrGVuE4Dzdpkb2vwA2AAomRTLBh8CS3zJpITtX4Y5GBEREREREYk0qkyKHkFZ5matnWutNbt5FAbjdSR69R9/hH88qG4FXre76yfX7YT3boTXfwOblYgSERERERHpjdQzKXqoAbf0iCHDRlNMJrmUk0od61Z/xZCxB7Y9yONm1cu3YVa8jI1Po2LI8eSNmsbg9y7DlH3rO2bhI3Dhu5A/vuffhIiIiIiIiIRMk+7mFjWUTJIeYRwOtqSMI7fmfwBsWz6/bTLJWsofP59R373s224Eln4OS3e5kKeBTS9cx8BLXuqRuEVERERERCT0vF6LbS1MQoVJkU2pPukxTf2mtG5s+qLNvobP/kVmSyJpD/rumE9tZWkwQxMREREREZEwCuyXFOc0GKNsUiRTMkl6TM7oQ/3jvpVLsS1p5+pi7Nt/8O97yR7Gx0N+yZb4IQCs9/bl5IYbWOYtBCDeeNi85IOeCltERERERERCTP2SoouWuUmPGbTfIbhfceDCyzA2s27LVoYM6M/aF+YyzFsHwLfeftjZf+fQA4eBnQtNtQx2JfGU1/L5vYth53oAqtd+BoeeGr43IyIiIiIiIkHjVr+kqKLvkPQYZ0IKW+KH+bfXfvUBr330GYPWPumfe3/QLzjpwOZjjIH4FIzDQYLLiWNga4+lxB1f9VjcIiIiIiIiElqqTIouqkySHlWdNwk2rwFg7eevk2vKiXN6AFjiGMOZP7qg03NzRx0CS3zjAbUrwFpfwklERERERESiWmDPJJeSSRFPlUnSo5LHzvKPf+56lVOcH/u3U0/4E2lJ8Z2eO3TUfuy0aQCkU03ZllWhC1RERERERER6jCqToouSSdKjBk46liqS2803jTyBoZO/t9tz41xONsQP929v/uaL3RwtIiIiIiIi0UKVSdFFySTpUa7EFMrGntt2Mi6FuONv6dL5NVlj/ePajYuCGZqIiIiIiIiEiccTUJnkVDIp0imZJD1u8Mk3wLiTfRtpBXDWk5A5qEvnJgw4wD9OLPkmFOGJiIiIiIhID9Pd3KKLGnBLz4tLhNMfhpPvB1fnPZI6UjB6GixsHtevwVqLURNuERERERGRqKaeSdFF6T4Jn71MJAH0G7ofdfjO60sZGzdvCnZUIiIiIiIiEkq2/ZR6JkUXJZMkqhini63xQ/3bm7/5PIzRiIiIiIiISDCoMim6KJkkUaemT2sT7pqNX4UxEhEREREREemKPaWHmjyBPZOUTIp0SiZJ1EkYGNiEe1kYIxEREREREZFgUGVSdFEySaJO/sgD/eP+9WtodHvZ8c3HrHn/P9TWVIYxMhEREREREdkXbXomOZWqiHT6DknUySiciBsnAMPMVp7+8xz6PnMCIz68jB13HoltrAlzhCIiIiIiIrI3PGrAHVWUTJLoE5/MuqT9/JvneF/yj4c0fcvWeXeEIyoRERERERHZR24tc4sqSiZJVKocNrvTfQlLnwTbwb0mRUREREREJCJ5vGrAHU2UTJKodMDsSylLH+3frsg/mEbrW/qW07iZ+nWfhis0ERERERER2UtuT2BlklIVkU7fIYlKroRksi59F068G858gvSfvcrb8TP9+zfPfyyM0YmIiIiIiMjeUM+k6OIKdwAi+ywhFSadC4ABPGNOhiVvA5Cx8W3fUjej/wmJiIiIiIhEujY9k5z6PS7SqTJJeo1pR55IpU0GINdTxPbVC8IckYiIiIiIiHSFKpOii5JJ0mv07ZPG8pSD/NvrPn4mjNGIiIiIiIhIV+lubtFFySTpVRLGn+gf9938Jt/uqGT55lI2rFyIrSkJY2QiIiIiIiLSGd3NLboomSS9yrjDT6aOeACG2k18cfe5pNw/ncFPzcR72wiqXvwNeJrCHKWIiIiIiIgEaluZpFRFpFMDbulVElIyWZg9i8mlrwBwtut9/z4nXtK+vp/SHSvI/slzEJcYrjBFRER6Fa/XS1lZGVVVVTQ0NGCt3fNJImFijCEhIYG0tDSysrJw6JdWkYignknRRf/nlF5n2Ok3UmNSO92fvW0+3917Eu6G2h6MSkREpHfyer1s2rSJ4uJi6uvrlUiSiGetpb6+nuLiYjZt2oQ3YGmNiIRPk0c9k6KJKpOk18nML4Sfz4P3/ww1xTDyGL7u90O+evKPnO95DoCh5Z+y8K8n0vfCZxiQmxXegEVERKJYWVkZtbW1uFwu8vPzSUlJUaWHRDSv10tNTQ3bt2+ntraWsrIycnJywh2WSMxTz6Toon/ppXfK3w/OegIueBsO/w0Thg/mB7+6j/+m/8h/yOTGBdTdezj/++DNMAYqIiIS3aqqqgDIz88nLS1NiSSJeA6Hg7S0NPLz84HWn2ERCa/Ankkup/4tiXT6DknMyEpN4MQr7uGLQRf450awiUM+OIOvb53Fog9fwuPxhDFCERGR6NPQ0ABASkpKmCMR2TstP7MtP8MiEl4ej3omRRMlkySmOJ0Opp5/Oxum30gdCf75CXWfMen9c9l+4xg+feh3bFm3KoxRioiIRI+WHkmqSJJoY4zvl1X1+RKJDG3v5qZkUqTTv/oSe4xh8Kxf4P75xyxKn4nXtv6Pqr/dwfQN/0f/R6ay9KZDmf/03yjfWRLGYEVEREQkFFqSSSISGXQ3t+iiZJLErLSCkUz69X/Z/qP3WJh3GpW0Lc8f37SUw1bcQOLfR7Pm3tNp2LosTJGKiIiIiIj0bm0qk5xKJkU6JZMk5vUbOYnJl/yb+N+u5sspt7E06UA8AdVKiTQxovgtnPcfxpJnbsTq9rEiItKDjDGHG2NeNsZsMcZYY8ycPRx/TfNx9/RQiCIiIt2mu7lFFyWTRJolJqcy5fs/Y/zv3qH60iUsGn0VaxxD/PtdeNn/m9v48pHfhjFKERGJQanAMuAKoG53BxpjDgIuBJb0QFwiIiJB07ZnklIVkU7fIZEOZOQNYtKZf6Dw2kW8Nv0pljLCv+/ADQ+w5OW7whidiIjEEmvt69baa6y1zwGdlscaYzKAx4GfAjt7Kj6JbnPmzMEYw/r168MdiojEOPVMii5KJonsRpzTwQmzjmPobz7k64TJ/vkxC+fy7eevhTEyEREJFWPMacaYu40x840xlc1Lxh7bwzkDjDEPGmO2GmMajDHrjTF3GmP69FTcwP3Ac9ba93rwNUVERIJCd3OLLkomiXRBSkoKhRc951/2Fmc85L7xM7avWx7myEREJASuAy4DJgBb9nSwMWYYsBA4H/gCuAP4Dt+ytE+NMdkhi7Q1hguB4cAfQv1aIiIioeDxqDIpmiiZJNJFmX2ySDj3WYrw/ZE5g2oaHzmVBV8tDnNkIiISZL8CRgLpwMVdOP4+IA+43Fp7krX2amvtTHxJpVHATYEHG2NubK522t1jRleDNcaMAv4M/Mha29jV8yT4Xn75ZY466igKCgpISEigX79+HHHEEdx3333+Y2bMmIExhoaGBq677jqGDBlCQkICw4YN44YbbqCxseNv4cqVK5kzZw4DBw4kISGBvn37cvbZZ7Nq1aoOj6+treXWW29lypQppKWlkZqaypgxY7j88svZsWMHAMYYHnnkEQCGDBmCMQZjDIWFhe3ibWxs5I9//COjRo0iISGBOXPmADB37lyMMXzwwQftYli/fj3GGP+xLVqW1q1bt4577rmHsWPHkpiYSGFhIX/+85+x1vcL5bPPPsvUqVNJSUkhLy+Pyy67jPr6+q58K0QkCqkyKbq4wh2ASDQZVDiCZcc/SPprPyTRNDGIbSS9OJunl/6OH5z5cxLj9Z+UiEi0s9a+3zI2ZvcfZo0xQ4FjgPXAvbvsvh74GXCOMeZKa21N8/ydwG6XzQEbux4x04EcYFlAvE7gcGPMRUCKtbZhL64n++D+++/n5z//Ofn5+cyePZucnByKiopYsmQJDz30EJdcckmb43/4wx+yYMECTjvtNOLi4njppZeYO3cuX375JS+//HKbn70333yTU045haamJmbPns3w4cPZvHkzL7zwAq+99hrvv/8+kyZN8h+/c+dOjjzySBYvXsyoUaP4yU9+Qnx8PGvXruXBBx/klFNOoW/fvlx//fW8+OKLLF68mCuuuILMzEwA/3OgU089lQULFnDcccdx0kknkZeX1+2v2VVXXcUHH3zA7NmzOeaYY3j55Ze59tpraWxsJCsri6uvvpqTTjqJww47jLfffpt7770Xj8fDP/7xj26/tohEnjZ3c3MqmRTp9JuvyF7ab+pMllbeyeiPryAON7mmgjO+u4bNN9/Fxj4H4Rg0nYLxhzNoyGiM7kIgItLbzWx+fsta26Y5trW2yhjzP3zJpoOAd5vnS4CSIMbwIvDlLnMPAWvwVSypWqkH/POf/yQ+Pp7Fixe3S7SUlLT/dq9YsYLly5fTp4+v4vmmm27iyCOP5NVXX+Wxxx7jnHPOAXyJobPOOovk5GQ++ugjxo4d67/G8uXLmTZtGhdccAGLFi3yz1966aUsXryYiy66iHvvvRdHwOeRqqoqvM2/sM2dO5f169ezePFifvnLX7apSNrVhg0bWLZsGTk5OXv/xenEwoULWbJkCf379/fHM3z4cG677TaSk5NZuHAhY8aMAaChoYGJEyfy4IMPcsMNNwQlmSUi4WOx7eaadDe3qKJkksg+GH/0jynvPwDns+eS5q0AYIDdzoCyF6HsRfga1jsGUzzuJ4w//kISk1LCGa6IiITOqObn1Z3sX4MvmTSS5mTS3jLGpOLrhwS+FgWDjDETgDJr7UZrbTlQvss5Nc37l/3/9u47Pqoq7+P458xMeiUJHSQUka4UAenFBxQfXQsKNgSVXcsqrriuojwLiy6goqygawVxrWAvKJalLrgiKBgFRCA0Q0sDQspk5jx/TBIJSSDCZJIJ3/frdV/D3HvumXNP7mvuj9+ce24l6l9TwaY2J9PeYyXfFzwPrEiddtEp7e9yuQgJCSmzvrwEzMSJE0sSSQDh4eFMnTqVgQMHMmfOnJJk0ssvv0xWVlbJ7WBHa9++PWPHjmXmzJn8+OOPtGvXjn379vHmm2/SsGFDHnvssVKJJICYmJiTOrYpU6b4NZEEvj4oTiSBb0TUJZdcwty5cxk/fnxJIgkgLCyMESNGMGnSJDZs2KBkkkgQOtFoX82ZFFyUTBI5SfFtB2DHf8vGBf9H021vEWVK38Of7N1O8vd/JfP7x/gm8QKy63YlIjaJhEgHLeIcxIaHQLNeEJlQTUcgIiJ+EFf0ml3B9uL18afwGd2AxUe9n1y0zANGn0K94kfXXnst48ePp3379owYMYL+/fvTu3dv6tatW275/v37l1nXt29fXC4X3377bcm6VatWAbBu3TomTZpUZp+ffvLlMTds2EC7du1YvXo1Xq+Xfv36ERXlvx+zunfv7re6inXr1q3MukaNGgHQtWvXMtuKE0+7du3ye1tEpPppzqTgomSSyCkwUYm0Gf0UebmPsnHt5xz6aQWRe9fQPDeFSOObnqIOh+iTvgDSF5TZv8CEsavzeFpc8pcTflZhxg6cu1djCvOgcReo1/aE+4iISLUrjobLjuevJGvtkqPqqew+A35D2bL/a6dkxFKX8rZJWXfffTdJSUk8/fTTPPnkk8ycORNjDP379+fRRx8tkzipX79+mTqcTieJiYns27evZF16ejoAzz///HE///DhwwBkZWUBlBrx4w8NGjTwa30AcXFxZda5XK4TbnO73X5vi4hUv6PnTArRnEk1npJJIn4QHhFJm96/g96/AyA7Yz9fffQkyVtfpwH7K9wv1ObTYu3f+dodRvcr7ipbwOth15I55K96jpbu0ndQ/BjTmyY3/YvY+Cp/4rSIiFSseORR2f/5+sQeU+60c6q3jgWTUaNGMWrUKLKysli5ciXvvvsuc+bMYejQoWVuzdq7dy9nnHFGqf09Hg/p6enExsaWrCtOqqxbt45OnTqdsA3Fk2fv3r3bD0f0q4puTym+ja6wsLDMtuLElohIZRRqzqSgor+QSBWIS6hLz1FTqPvgBr4f8CIpzUbxc3wffo7szLrQznzp7Uqq99dfJDutf4jNP5SeOzVj67f88kgPmiy7p0wiCaDdof9wYPb5HMry5xyuIiLyGxU/l711BdvPLHqtaE4lqYXi4+MZNmwYzz//PKNHjyYjI4Ply5eXKrN06dIy+y1fvpzCwkI6d+5csq5nz54l2yqje/fuOBwOli1bRk5OzgnLO51OwJfIOhnF8z7t3LmzzLZvvjl2XngRkYp5vJozKZgomSRShZyuEDoOGE6HMbNoddfHtLp3CWdPWELviZ+TPmox2xzNAAg3bgrevo1DR/LweC0LP34H17xhNMrbXFJXvg1hhac9Sz2//irZonArO576HYdzDgf82EREBPh1LqMhxphScZUxJgboDeQCXwW6YRJYn376abmjc4pvWYuMjCy1fsqUKWRmZpa8z8vL4/777wdgzJgxJevHjBlDfHw8kydP5uuvvy5Tv9frZcmSJSXv69aty8iRI0lLS+Oee+4peXJbscOHD5Od/etAucRE3wjnHTt2VPZQSymeS2nu3Lmljn/nzp387W9/O6k6ReT0pDmTgotucxOpBuEhTrq2aszOq+bgfn0IIcZDe+8m3nh+Ihs8TfhL9sMlcy7l2lA+jR/JOcPv5dyGjTiUV8iKhU/R58fJALR3p/DfJ4fT6ua5JNZtWJ2HJSJy2rHWbjHGfIbviW23A7OO2jwZiAKetdaeeIiIBLWRI0cSHh5Onz59SE5OxlrL8uXLWb16NV27duX8888vVb5t27a0b9+e4cOHExISwvvvv8+WLVu46KKLSp7kBr5kz1tvvcVll11Gz549GTx4MO3bt8fhcLBjxw5WrVpFeno6eXm/Pghk9uzZpKSk8Mwzz7BkyRKGDh1KaGgo27ZtY9GiRXzwwQcMGDAAgMGDB/Poo48yduxYhg8fTnR0NPHx8fzxj3+s1HH36NGDfv36sWzZMrp3786gQYPYu3cvH374IUOHDi13xJKISHk0Mim4KJkkUo2atunGhra30Xaj7/8eIzOf820o+u7MMHH8fMG/uKznr098CYt20uequ/nm1YN02/wEAD3yV8FTbcglnKzwxuR0H0erQTcE9FhERGoLY8ylwKVFb4tnHT7PGPNS0b8PWGvvOWqX24CVwJPGmMHABqAHMBDf7W0PVHGTpQaYNm0aixYtYu3atSxcuJDw8HCaNWvG9OnTufXWWwkJCSlVfv78+UyZMoVXX32VX375hcaNGzNp0iTuu+++MvMTDR48mPXr1/PYY4+xaNEili9fTmhoKI0aNWLQoEFcccUVpcrXqVOHlStXMnPmTN58802ee+45nE4nTZs25cYbb6Rdu3YlZYcOHcqMGTN4/vnneeKJJygoKKBZs2aVTiYBvP/++/z5z3/m/fffZ9asWZx55pk88sgjDBkyhPnz559Eb4rI6Ugjk4KLsfakHy4SEMaYNV26dOmyZs2a6m6KSNXwuPnlsV40yi09ncahsPqE3fghofXPKn8/a/l+7h103PGvcjd/d84kzrn0T/5urYiI33Xt2pW1a9eureipYoFmjJkE/PU4RbZba5OP2acp8DfgAiARSAPeAyZbazOqpKFVrLIx2IYNGwDfSBs5sQEDBrB06VJqegx+utD5KxI4X2/L4KpnVwFwbnIdFtzSq9T2/521nJTdBwH48I996NikomdbiL+cSgymOZNEqpszhISb32J7SIuSVUea9CXm9iUVJ5IAjKHjmFmsO2cym12tKbClBxq2/fZhdm8sO7eCiIgcn7V2krXWHGdJLmefndbaMdbahtbaUGttM2vtuGBNJImIiARaoUcjk4KJbnMTqQHCE5txxn2rydn5LVGRMUTWPQsqeARvKcZw9qV3waV3kVdQyDc//Uz8OyNo5U0lzLjJW/AH8u9dRVhYeJUfg4iIiIiIyMkqNWeSU8mkmk4jk0RqCON0EZV8LtRrU7lE0jHCQ11069AGz+VzybO+eRlaerayct6DgO/Lef/+veTv+xncecerSkREREREJKA8mjMpqGhkkkgtc1aHLny97g66b34cgN675/CvKQdo4d5MT/MDTmMpMOEcbn0ZCRdPgei61dxiERGR08eSJUuquwkiIjVSoZ7mFlQ0MkmkFjp35ANsCfNNJBlqPFzveZfejhScxvcFHWrzSNj0OtkzurB2xcLqbKqIiIiIiIhGJgUZJZNEaiHjdFH3hn+x1ySV2ZZho0v+HWcP0v7z63nt2Wlk5hT4Vu79ETYuhIO/BKq5IiIiIiJymnN7vCX/djmUqqjpdJubSC0V2+hMHOP+y64VLxDj3k9kwza42g5jS0Y4b/37La7Y8RCJ5iBhppBr0qay5NEvaB6ZS7MjKQAU4iTlnImcc+mfqvlIRERERESkttPIpOCiZJJILRYdn0T0/95Xat25cXDuTX8gc9dA0l6+koYFqQAMYDUc+bWcCw8dv51MWuseNGzX6+QakJsJK2bi/WkRHk8heR2uJWbAONAvDSIiIiIicpSj50wK0dPcajz9j07kNFWnSWsajl/BviZDSq0vsE4O2FgAnMaS/+4dWE/hb6o7313I8nefIfORc+A/M3Hs30BIxmZilk1izdy7/HMAIiIiIiJSa2hkUnDRyCSR01lYDPVumk/O1q/YsuoDshzxeM4ahrMwl+4LhxFu3CS7f2bth0/T5dI7f90vJx3PthUczD7AAU80BRH1IbYhIeER7Fy3lNhvn6OvXV/uR56z42Uyto4hoUXnAB2kiIiIiIjUdIVezZkUTJRMEjndGUNUy/Po1PK8UquXfDeKAWkvAtD0u8fJ7H8d2zLdHPzoQfpkvI0LD3WAOsdU1/qY92k2gRmekVzlXEx3swGnsWR+cD8Jd31aZYckIiIiIiLBRSOTgovSfSJSrm7X/JX9RamiumTy339cg/OlCxiQMR8XnhPu78HBD42vImzcNzw65e8UDHkEr/VdFFpmreLQjnVV2n4REREREQkeR8+Z5FIyqcZTMklEyhUdE8f+bn8ueX8BqzjbsbXk/ffeZD42/VkT0pVUV3MOmliOEMF2ZzO+b3ot7ltX037s8yQkJGKModd5fVkR0rNk/10fPxrQ4xERERERkZrJ67XYolySMeBQMqnG021uIlKhdsNu4eeU12mV933JukLjYs+593Hm+X+iY2jZr5BmFdTlcBg8Pe+AFasAaLX3E3LTdxGR2KQqmi4iIiIiIkFCo5KCj0YmiUjFHE6a3P4hPzQZSVZ0K9ytL8L1h6U0GfZnwstJJJ1In4EXss60ASCEQjZ/OMPfLRYRERERkSCj+ZKCj0YmichxhcfUof3Nz/qlrhCng4yz/wDf/QmA5NQ3OXTw/4iJPXYa79K8Bbk4QsJ9Y15FRERERKRW0ZPcgo+SSSISUOddeB3bv3uEZqQRSw4vPfUAg37/GGckRpYqt2vjNxxY8gzN93xKHIc4Qjh7wpLJju9Ibt2OuKKTCIuKIaZOfZqdkYwzpp6STSIiIiIiQUgjk4KPUn4iElDhYaHs73Bzyfvr8l7nn7OnsmzTPlZ+v5lP/vUIGx/qQZM3BnPOngXEcQiASPJokb+RznsX0Cvl/+j+1W2c/eX1tHhrCM7HW3Pg4bPYMOdW9u7cXF2HJiIiwvz58+nXrx9xcXFERETQsWNHpk6dSn5+PgB5eXnEx8dTr149CgsLy63jlltuwRjDxx9/XGr9xo0bGT16NE2bNiUsLIz69etzzTXXsGnTpjJ1jB49GmMMW7duZdasWXTq1ImIiAgGDBgAgLWWefPm0atXL+rWrUt4eDhNmzZl6NChvPnmm6XqSk5OJjk5mezsbP74xz/SuHFjwsPDadeuHU8++STW2jKf/9JLL3HFFVfQokULIiIiiI2NpXfv3rzyyisV9l1GRgYPPPAAHTp0IDIykri4OM4++2zuu+8+cnJyypS9//77adu2LREREcTFxTF48GA+++yzCusXkZpLcyYFH41MEpGA63bZONJ3f0Bi5jpcxstU+yS5rz1DhCkot7zXGhymbKB6tKTCvSTteI28FxawtNkf6Hb1RKIiwgHIzXezZe2XxGZvIjEumqjkc6FBR41kEhERv5owYQJTp04lKSmJa665hujoaD755BMmTJjAokWL+PzzzwkPD2fEiBE899xzfPLJJ1x88cWl6sjPz2f+/PnUr1+foUOHlqz/9NNPufzyy3G73Vx88cW0atWKXbt28c477/Dxxx+zePFiunTpUqZN48aNY/ny5Vx00UUMGzYMp9MJwAMPPMDUqVNp3rw5V111FXFxcaSlpbF69WoWLFjAiBEjStVTUFDA+eefT1ZWFiNHjqSgoIC3336bcePGsWnTJp566qlS5W+99VbatWtHv379aNiwIenp6SxcuJDrr7+eTZs2MWXKlFLlt23bxsCBA9m+fTtdu3bl1ltvxev18tNPP/HEE09wyy23EBUVBcD27dsZMGAAqamp9O3blwsuuICcnBw++ugjLrjgAp599lnGjh178n9IEQk4jUwKPkomiUjgOUNIHP0aeS8MI/zQdoAyiaQC62RddF+8XUbT5rxh7PllFwe2rMa7cw0xh7bidB/GVXiYsIIs6tv9RBnfL77hxk3/HbPZ+MhCtre6HvfeTZyT/QUdzIFS9W93JZPdawKdBl5VflLJWval/JvtX39ETHwirQePxhGvJ8+JiEj5Vq1axdSpU2natClff/01DRo0AGDq1KlcdtllfPTRRzz66KNMmDCB0aNH89xzzzFv3rwyyaQPPviAzMxM7r77blwuX6iemZnJ1VdfTWRkJMuWLaNdu3Yl5X/44Qd69OjBzTffzNq1a8u0a+3atXz77bc0b9681Ppnn32Wxo0bk5KSQmRk6VvNDxwofc0ESEtLo0WLFqSkpBAWFgbA5MmTOffcc3n66acZMWIE/fr1KymfkpJCy5YtS9VRUFDAhRdeyLRp07jlllto3LhxybbrrruO7du38/e//53777+/THuio6NL3t9www1s376d119/nZEjR5asz8rKYsCAAdx5551ccskl1K9fv8xxiEjN5PYcPWeSkknBQMkkEakecU0Iv20phz/9G3b9fGLsYTw4SItsy6GWw2jYdzTn1vs1eRPXqiVntWoJjCxVjbWWLXsy2fb1Qlqun0ELz1YA2tittNk82VeonOtRs8JUWPZ71n/zIvVGzKJBs7NKtuVnpZH28s0kZ6ygHsBOcH//BDvb/54zfjcRExpZtkIRESnfpLjqbkHlTco+6V3nzJkDwIMPPliSSAJwuVzMmDGDhQsX8sILLzBhwgTOO+88WrduzYcffkhGRgYJCQkl5efNmwf4EibFXn75ZbKyspg9e3apRBJA+/btGTt2LDNnzuTHH38ss/3ee+8tk0gqFhISUjJS6WhJSUnllp86dWpJIgkgISGBiRMnMmbMGObOnVsqmXRsIgkgNDSU22+/nX//+998+eWXjBo1CoA1a9awcuVKzjnnHP7yl78ctz3r1q1j6dKlDB8+vFQiCSA+Pp7Jkydz6aWX8vbbb3PbbbeVexwiUv2OvTu21Mgkp5JJwUDJJBGpPhF1iL7sCezvZuDOO0hIWDRNnL/ta8kYQ6uGCbT63XV4h13F9+/8ndYbZhOGu1S5g0TzTUg3Cgpy6ct3JSOZOh35L7lz+vBp0tVsqTuYMzzb6f3zDJJtVqn9Qyik2Q9Ps2fju6xteTtRTTvStGF9kurWJyYmHqOnToiInNaKRwUNGjSozLbWrVvTpEkTtm3bRlZWFvHx8dxwww088MADvPHGGyVJj71797Jo0SI6d+5Mp06dSvZftWoV4EukTJo0qUz9P/30EwAbNmwok0zq3r17ue299tprmTVrFu3bt+fKK6+kf//+nHfeecTFlZ/8c7lc9OrVq8z64jmYvv3221Lrd+zYwfTp0/nyyy/ZsWMHubm5pbbv3r275N9fffUVAEOHDsVxgutpcV9kZ2eX2xf79+8HfH0hIjXL8WaYOHrOpBDF1UFBySQRqXbG4SAkMv6U63GEhNJxxCRy0q4m5cOZhGX+TEhCExLOuZi6nS9ikCsMr9eS9stOvn97At0zPsJhLBGmgAvS50H6vDJ1Lnb1IcGdxtlmCwANPGkM++lB+OnXMm7r5KCJJstRh5zQJAoi6uGNbkjEWYNo22MorpCQE7bdU5DHlv9+RObWNYSERRLbpC0Nz+xCRGJTDuzcSPbWteQezqReh4E0aHn2KfeViIj4V3a2b1RTw4YNy93esGFDduzYQXZ2NvHx8YwaNYqJEycyb968kmTSq6++SmFhYalRSQDp6ekAPP/888dtw+HDh8usO3qU1NGeeOIJWrZsyZw5c5g2bRrTpk3D5XIxbNgwZsyYQatWrUqVT0pKKncUU3H9xccPsHXrVrp3705mZiZ9+/ZlyJAhxMXF4XQ6SU1NZd68eSUTkoPv9jSg1G1vFSnui88//5zPP/+8wnLl9YWI1FyaMyn4KJkkIrVOVMOz6Pr7f5a7zeEwNG5yBo3HvcKGr78k7NO7aeFNLVPuAHF823Uagy66mvRDuby3YAYDd/6TOJNTpmyI8ZBINonebMhLhTwgE9j5Ivu+SGBTvQuIaDsU6wzDFuRg8w9CwRHfveHuPML2rKZN9gpac+TXSjcCX/gmH69nrO92O4Bv/8qGxCE0H/UU4XH1jm2KiEjNcwq3jgWT4hE9e/bsKfcWr7S0tFLlmjRpwqBBg/jiiy/YuHEjbdq0Yd68eYSEhHDNNdeUW/e6detKjViqDFPBUACn08m4ceMYN24c+/btY8WKFbzxxhssWLCAH374gR9++KHULW0HDhzA4/GUSSjt2bOnVBsBHn/8cdLT05k7dy6jR48uVf71118vuZWvWHx8PFB6tFJFij/nH//4B3feeecJy4tIcCj0KJkUbPw2fswY08QYM8cY84sxJt8Yk2qMmWmMqeOvzxAR8ae23Qdzxv2r2dTrCX6p15+DEU3ZF3UW3zW7EW5dyf9cfA1Oh6FeXCSX3jyRnLEr2dBqLDtiOrMrJJm9JpEjNuy4n1GPDPrue41uS2/g3H+PpPuKm+ix+k/0WPcAfVIm0mfTw5yb/RkxRyeSjlLeU+zapn/G4ZndWfvFm2w/cJiMnALchR7wesupQUREAqFz584ALFmypMy2n3/+mV27dtG8efOSxAlQkmiZN28e3333HevXr+fCCy+kbt26pfbv2bMnAMuXL6+StterV4/LL7+c+fPnM2jQILZs2UJKSkqpMoWFhaxcubLMvsXHW3z84DtegCuuuKJM+aVLl5ZZV3x8ixYtwnuCa1lV94WIVI+jRya5NGdSUPDLyCRjTEtgJVAPeB/fb+rdgXHABcaY3tbadH98loiIP7lCQjlryI0w5EYAYoGKxvs0apJMo+seK7M+P+8IhzL2kr1/J4f27yY3YzeOvSmcmf4lCRysdFt2U4/UhN54vV5iD22haWEqCeYw+4lnR0hLnNbNOYXrAUiymSSt+D0HlsfiC7tzwHgoxEmWieWX0ObkxLfB1bQr9Vp3x+OKIDsrk9ysfXgO78eZl05IXiYerxdXbD2i67cgKbkjiQ2TNf+TiMhJuPHGG3nxxRd56KGHuOSSS0oSQh6Ph3vuuQev18tNN91Uap/LL7+c2NhYXnnllZI5hY4dyQMwZswYHn744ZKnpx07D5LX62XZsmUl8xedSH5+PitWrGDQoEGlRi653W4yMjIAyjzhDeD+++/nyy+/LBmxlJGRwUMPPVTSxmLJycmAL9F09NPqFi1axAsvvFCm3q5du9KrVy9WrlzJ9OnTyzzNLT09naioKMLDw+nWrRt9+/blnXfeYc6cOdx4441l6vv++++pX78+9eppBK9IsCg8KpHsVCwaFPx1m9vT+P7/dae1dlbxSmPM48CfgIeBW/z0WSIiNUpYeCRhjZqT1Kj003I87gI2rPqAI9+9S8zhrTiMpdCEUeCKxu2MxOFw4HA4yI1JJvHsC2nZqQ+Nnb9ePAvcHg7l5VA3Jpa6gNdrWfLxq3RcM4FEfLeNJJnSySoXHl+iKT8T9q6Fva/BN5U/lsM2gt2uJmRENCcvvhWOemcR26g19Zu2JDLUScaBvRzav5u8zDRCPIdxuMIwoRHgDMdtQnE7wvA6Q2lSL5EzmrfGuI4/cktEpLbo1asX9957L4888ggdOnRg+PDhREVF8cknn5CSkkKfPn3485//XGqfiIgIrrzySl588UWefvppEhMTueiii8rUnZiYyFtvvcVll11Gz549GTx4MO3bt8fhcLBjxw5WrVpFeno6eXl5lWprbm4u559/PsnJyfTo0YNmzZqRl5fH559/zoYNG7jkkkto27ZtqX0aNmxIfn4+HTp04JJLLsHtdvPWW2+RlpbGbbfdVupJbrfddhtz587lyiuv5IorrqBx48akpKTw6aefctVVV/Hmm2+WadMrr7zCgAEDmDBhAm+//TYDBgzAWsvmzZv57LPP2LhxY0mS6rXXXmPQoEHcdNNNPPnkk/To0YP4+Hh27drF+vXrSUlJYdWqVUomiQSRUiOTdJtbUDjlZJIxpgUwBEgFnjpm81+B3wPXG2PGW2vLTjYiIlJLOUNCadtvOPQbflL7h4Y4CQ2JLXnvcBgGXHwdB87tzzfz76ddxhdEknucGn67aJPLWZ7NcHgzHP4MdgFrf90e/xvqyieEnWFnkp3QiZzEjoRGJxARHoYtOEJh3mE8+UewngKc1oNxOPCExkJEHUKj4gmPjMEUHCYv8xcKDu7Fm3sQV1Q8UYlnENe4FXUatSYsOh6Hgg0RqUGmT59O586dmT17Ni+//DJut5uWLVvy0EMPMX78eEJDQ8vsM3r0aF588UXcbjdXX311uWUABg8ezPr163nsscdYtGgRy5cvJzQ0lEaNGjFo0KBybymrSFRUFNOnT2fx4sWsXLmS9957j5iYGFq2bMk///nPckf7hIaG8sUXXzBhwgTeeOMNDhw4QIsWLbjvvvu44447SpXt1KkTixcv5sEHH2ThwoUUFhZy9tln88477xAfH19uMql58+asXbuWRx55hPfee4/Zs2cTHh5OcnIy48ePL5UYatKkCWvWrGHWrFm8/fbbvPrqq3g8Hho0aEC7du2444476NixY6X7Q0SqX6Em4A46xtqy83H8pgqMuRl4HnjOWvuHcrYvwpdsOt9a++VJ1L+mS5cuXdasWXNK7RQRqXU8hXB4Lzic2PA4cjwuDuXkkHdgO9mp35G3Yy1R6d9TP28bDmNxOyI44oonPzSe3JAE8kPjMQYcOfuJPbKDRoU7iCN4cv5HbBhuXBTiotA4KSQEj3HiMS4sDjzGidc48eJ7tcaJB9+rt2jBOABT8qja4z2yVnzc4Un0+ONcv9bZtWtX1q5du9Za29WvFcspqWwMVvwI9mNHskjtUTwiKDU1tVrbURV0/ooEzurUDK58ZhUA3ZrV4a1be5Vs+8/PB7j2hf8C0KtlIq+N7VktbTzdnEoM5o/b3M4qev2pgu2b8SWTWgMVJpOMMRVFKm1OvmkiIrWY0wVxvscoGyA6BKLD4yExHs46G7jhODuXZb1esvbv5kDq9+Ts/hG7fxMRB7cQk5dGHU86HuvgiCOSQ64EckLrkuuIwul14/TmE2LzCbFuQm0BITYfl/sQDajaqfIiTT6QX3qlLVqkyuzOqV/dTRAREZFaRiOTgo8/kknFzwGt6Lmvxevj/fBZIiJSRYzDQXz9psTXbwoMK7dMNBVPUH40ay2pO7azK2U5rrS1RB/ahnHnYD1u3M5wPM5IrCsc6wzFjQtjPYQVHiLcnY2rMIcQzxHyTARHQhMpjEjEGxaHPZJJ+JE0Egp+oZHdR5hx+/PwRURERKSaHH3HlNFQ8aDgrwm4j6f4TDjub8UVDasqGrHUxd+NEhGRqmOMIblZMsnNkoHr/f8BXi+24DAF7gIKCvIpyMunwJ1PQX4+Hk8BtrAQ6ynE6/Xg9RSC1+17LVpni9d5vXitxVo4xbu+Txuu8CgaV3cjRERERKRa+SOZVDzyKK6C7bHHlBMRETk1DgcmPJawcNDz4kREqlZtnCtJREROjePERU5oU9Fr6wq2n1n0WtGcSiIiIiIiIiIiEiT8kUxaXPQ6xBhTqj5jTAzQG8gFvvLDZ4mIiIiIiIiISDU65WSStXYL8BmQDNx+zObJQBTwsrU2eJ43LSIiIiIitZrVZHkiIifNXxNw3wasBJ40xgwGNgA9gIH4bm97wE+fIyIiIiI1iDEGay1erxeHwx+D3kUCoziZpCdHiYj8dn654heNTuoGvIQviTQeaAk8CZxnrU33x+eIiIiISM0SFuabBj8nR4PQJbgUn7PF57CIiFSev0YmYa3dCYzxV30iIiIiUvPFxMSQl5fHnj17AIiKisIYo9EeUiNZa7HWkpOTU3LOxsTEVHOrRESCj9+SSSIiIiJy+klISCAnJ4cjR46wa9eu6m6OyG8SGRlJQkJCdTdDRCToKJkkIiIiIifN4XDQtGlTMjIyOHToEPn5+ZrYWGo0YwxhYWHExMSQkJCgub5ERE6CkkkiIiIickocDgdJSUkkJSVVd1NEREQkAJSGFxERERERERGRSlMySUREREREREREKk3JJBERERERERERqTQlk0REREREREREpNKUTBIRERERERERkUpTMklERERERERERCpNySQREREREREREak0Y62t7jYclzEmPSIiIqFt27bV3RQRERGpAhs2bCA3NzfDWptY3W2RXykGExERfzpS4GHr/sMARIa6aFE3qmTbobxCtqfnABAd7iI5MarcOsS/TiUGC4Zk0jYgFkitgurbFL1urIK6pSz1d+CpzwNL/R1Y6u/Aqsr+TgYOWmubV0HdcpIUg9Uq6u/AUn8Hnvo8sNTfgVUjY7Aan0yqSsaYNQDW2q7V3ZbTgfo78NTngaX+Diz1d2Cpv8WfdD4Flvo7sNTfgac+Dyz1d2DV1P7WnEkiIiIiIiIiIlJpSiaJiIiIiIiIiEilKZkkIiIiIiIiIiKVpmSSiIiIiIiIiIhUmpJJIiIiIiIiIiJSaaf109xEREREREREROS30cgkERERERERERGpNCWTRERERERERESk0pRMEhERERERERGRSlMySUREREREREREKk3JJBERERERERERqTQlk0REREREREREpNKUTBIRERERERERkUqrdckkY0wTY8wcY8wvxph8Y0yqMWamMaZOddRT251qPxljEo0xNxtj3jXG/GyMyTXGZBtjVhhjbjLG1Lpz9FRUxXlpjLneGGOLlpv92d5g58/+Nsb0Nca8bYxJK6orzRjzmTFmWFW0PVj58Tv8oqL+3VX0vbLVGLPAGHNeVbU92BhjhhtjZhljlhtjDhZ9B7xyknXpmnmaU/wVeIrBAksxWGApBgssxV+BU5viL2OtDcTnBIQxpiWwEqgHvA9sBLoDA4FNQG9rbXqg6qnt/NFPxphbgH8CacBiYAdQH7gciAPeBq60telEPUlVcV4aY5oC3wNOIBoYa619wZ/tDlb+7G9jzIPAFOAA8BG+8z0J6Awsttbe6/cDCEJ+/A6fDtwLpAPv4ev3VsAlgAsYZa09qYt2bWKM+Q44GzgM7ALaAK9aa6/7jfXomnmaU/wVeIrBAksxWGApBgssxV+BVaviL2ttrVmARYAF7jhm/eNF658JZD21ffFHPwGDgIsBxzHrG+ALaixwRXUfa01Y/H1eAgb4AtgCPFpUx83VfZw1ZfHj98mVReU/B2LK2R5S3cdaUxY/fac0ADzAHqDeMdsGFtWztbqPtSYsRf1xZtF3wYCivnmlOv5uWoJ7UfwVnH2uGCyw/X3MforBAtDfisEC19+Kv35Tf9ea+KvaO9OPf5QWRZ22rZyLYgy+zF8OEBWIemr7Eoh+AiYUfcas6j7e6l6qor+BcYAX6AdMUiDj//7Gdyvx1qKydav7uGry4sc+71FUz/sVbD8IHKru461py8kGM7pmalH8Fbx9foLPUAxWhf2tGKzq+1sxWMD7W/HXyfV/UMdftele6EFFr59Za71Hb7DWHgL+A0QCPQNUT20XiH5yF70WnkIdtYVf+9sY0xaYBvzDWrvMnw2tJfzV372A5sBCILPoPvK/GGPG6d7xMvzV55uBAqC7MSbp6A3GmH74LrBf+KXFArpmiuKv6qAYLLAUgwWWYrDAUvwVnGrENbM2JZPOKnr9qYLtm4teWweontquSvvJGOMCRhW9/fRk6qhl/NbfRX37L3xD2CecetNqJX/197lFr3uBtfju1Z8GzARWGmOWGmPqnkI7axO/9Lm1NgP4C755P340xjxnjJlqjJkPfIZvqPsf/NBe8dE1UxR/BZ5isMBSDBZYisECS/FXcKoR10xXVVYeYHFFr9kVbC9eHx+gemq7qu6naUAHYKG1dtFJ1lGb+LO//w/fpIN9rLW5p9iu2spf/V2v6PUWfMNQzwf+CzQDZgBDgQX4hrie7vx2jltrZxpjUoE5wNijNv0MvGSt3XeSbZSydM0UxV+BpxgssBSDBZZisMBS/BWcasQ1szaNTDoRU/Rqa0g9td1J95Mx5k5gPL4Z6a/3Z6NqsUr1tzGmO75fwmZYa1dVeatqr8qe386jyg+31n5prT1srf0BuAzfExz6a7h1pVT6O8UYcy/wFvAS0BKIArrimzvhVWPMI1XURilL10xR/BV4isECSzFYYCkGCyzFX8EpINfM2pRMKs6+xVWwPfaYclVdT21XJf1kjLkd+AfwIzCwaMik+KG/jxpa/RMw0X9Nq5X8dX5nFr1utdauO3pD0S+Sxb/4dv/NLax9/NLnxpgBwHTgA2vt3dbardbaI9batfiCx93AeGNMi1NvsqBrpij+qg6KwQJLMVhgKQYLLMVfwalGXDNrUzJpU9FrRfcFnln0WtF9hf6up7bzez8ZY+4CZgMp+IKYPSfdutrHH/0dXbR/WyDPGGOLF+CvRWWeL1o381QbHOT8/X2SVcH24kAnonLNqtX81ef/W/S6+NgN1tojwNf4rn2df2sDpVy6Zorir8BTDBZYisECSzFYYCn+Ck414ppZm+ZMKj5xhxhjHEfPam6MiQF6A7nAVwGqp7bzaz8ZY/6C7x7974D/sdYe8G9zg54/+jsfeLGCbV3wfbmvwPfldLoPv/bX+b0M35NwzjTGhFprC47Z3qHoNfXUmxz0/NXnYUWvFU2qWbz+2L+FnBxdM0XxV+ApBgssxWCBpRgssBR/Baeacc201taaBd9wRQvcccz6x4vWP3PUuhCgDdDyVOo5nRc/9vfEovLfAAnVfVw1dfFXf1dQ96SiOm6u7uOsKYsfz+9Xiso/dMz6/wG8+H4xi6/u460Jiz/6HLiqqOweoPEx2y4s6vNcILG6j7cmLfgmILXAKxVs1zVTy/HOH8VfwdvnisEC2N8V1K0YrIr6WzFY4Ppb8ddJ931Qx1+m6ANrBWNMS2Alvtn73wc2AD2AgfiGePWy1qYXlU3GN7P/dmtt8snWczrzR38bY27AN0mbB5hF+fd1plprX6qiwwga/jq/K6h7Er5h1mOttS9UQfODjh+/T+oB/wFaAcvxDfNthu/+cQtcY61dUPVHVPP56TvFge/iej5wCHgXX2DTFt8QbAPcZa39R0AOqgYzxlwKXFr0tgG+J9tsxXeeAhyw1t5TVDYZXTOlAoq/Ak8xWGApBgssxWCBpfgrsGpV/FXd2bgqyO41BeYCafiG0W3HN5lgwjHlkvF9iaSeSj2n+3Kq/c2vv8Ycb1lS3cdZUxZ/nd/l1Fv8d9CvYlXQ30ACvl8JthXVk47vS79ndR9jTVv80ef4fsW5C9/Q3oP4hrnvAz4ChlT3MdaUpRLfv6lHldU1U8uJzifFX0HW55X4DlAM5sf+Pk69xX8HxWBV0N8oBgtYf6P4q7J9faLv3tSjytboa2atGpkkIiIiIiIiIiJVqzY9zU1ERERERERERKqYkkkiIiIiIiIiIlJpSiaJiIiIiIiIiEilKZkkIiIiIiIiIiKVpmSSiIiIiIiIiIhUmpJJIiIiIiIiIiJSaUomiYiIiIiIiIhIpSmZJCIiIiIiIiIilaZkkoiIiIiIiIiIVJqSSSIiIiIiIiIiUmlKJomIiIiIiIiISKUpmSQiIiIiIiIiIpWmZJKIiIiIiIiIiFSakkkiIiIiIiIiIlJpSiaJiIiIiIiIiEilKZkkIiIiIiIiIiKVpmSSiIiIiIiIiIhU2v8DDYAW/U+nqZkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 248,
       "width": 585
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy import interpolate\n",
    "\n",
    "figure( figsize=( 10, 4 ) )\n",
    "\n",
    "def overspace( spectrum, N=1000 ) :\n",
    "    '''\n",
    "    Project the spectrum into a higher or lower space of density N. \n",
    "    '''\n",
    "    x = linspace( 0, 1, len( spectrum ) )\n",
    "    s = interpolate.InterpolatedUnivariateSpline( x, spectrum )\n",
    "    # numerical instability at small scalees is a problem, so let's keep things positive\n",
    "    return sqrt( s( linspace( 0, 1, N ) )**2 )\n",
    "\n",
    "L = list( forest.values() )[7].laplacian()['laplacian']\n",
    "\n",
    "subplot( 1, 2, 1 )\n",
    "N = 1000\n",
    "plot( linspace( 0, 1, len(L) ), eigvals(L).real, label='spectrum' )\n",
    "plot( linspace( 0, 1, N ), overspace( eigvals(L).real, N=N ), label='overspace' )\n",
    "legend()\n",
    "\n",
    "subplot( 1, 2, 2 )\n",
    "N = 1000\n",
    "plot( linspace( 0, 1, len(L) ), eigvals(L).real, label='spectrum' )\n",
    "plot( linspace( 0, 1, N ), overspace( eigvals(L).real, N=N ), label='overspace' )\n",
    "legend()\n",
    "semilogy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pdd( a, b ) :\n",
    "    '''Jensen-Shannon distance'''\n",
    "    return ( 0.5 * entropy( a, b ) + 0.5 * entropy( b, a ) )**(0.5)\n",
    "\n",
    "jsd = numpy.zeros( ( len(spectra), len(spectra) ) ) \n",
    "\n",
    "for i,a in enumerate( spectra.keys() ) :\n",
    "    for j,b in enumerate( spectra.keys() ) :\n",
    "        L1 = forest[a].laplacian()['laplacian']\n",
    "        L2 = forest[b].laplacian()['laplacian']\n",
    "        \n",
    "        E1 = eigvals( L1 ).real\n",
    "        E2 = eigvals( L2 ).real\n",
    "        \n",
    "        O1 = overspace( E1, 1000 )\n",
    "        O2 = overspace( E2, 1000 )\n",
    "    \n",
    "        jsd[i,j] = pdd( O1, O2 )\n",
    "        \n",
    "names  = [ name.split('-final.')[0] for name in forest.keys() ]\n",
    "jsdist = pandas.DataFrame( jsd, columns=names, index=names )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x7f51983859d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 713,
       "width": 713
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seaborn.clustermap( jsdist, cmap='viridis' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dnapol</th>\n",
       "      <th>vltf3</th>\n",
       "      <th>primase</th>\n",
       "      <th>rnapol2</th>\n",
       "      <th>capsid</th>\n",
       "      <th>rnapol1</th>\n",
       "      <th>packaging</th>\n",
       "      <th>tf2s</th>\n",
       "      <th>bd_packaging</th>\n",
       "      <th>kingman_packaging</th>\n",
       "      <th>...</th>\n",
       "      <th>bd_rnapol2</th>\n",
       "      <th>bd_rnapol1</th>\n",
       "      <th>kingman_rnapol1</th>\n",
       "      <th>bd_primase</th>\n",
       "      <th>kingman_primase</th>\n",
       "      <th>kingman_dnapol</th>\n",
       "      <th>kingman_capsid</th>\n",
       "      <th>kingman_rnapol2</th>\n",
       "      <th>bd_dnapol</th>\n",
       "      <th>kingman_tf2s</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>dnapol</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.144687</td>\n",
       "      <td>0.109859</td>\n",
       "      <td>0.151885</td>\n",
       "      <td>0.189734</td>\n",
       "      <td>0.101359</td>\n",
       "      <td>0.121295</td>\n",
       "      <td>0.108646</td>\n",
       "      <td>0.225400</td>\n",
       "      <td>0.570519</td>\n",
       "      <td>...</td>\n",
       "      <td>0.278555</td>\n",
       "      <td>0.244786</td>\n",
       "      <td>0.650479</td>\n",
       "      <td>0.205494</td>\n",
       "      <td>0.556278</td>\n",
       "      <td>0.346783</td>\n",
       "      <td>0.782643</td>\n",
       "      <td>0.295743</td>\n",
       "      <td>0.197951</td>\n",
       "      <td>0.703659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>vltf3</th>\n",
       "      <td>0.144687</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.158261</td>\n",
       "      <td>0.177856</td>\n",
       "      <td>0.155239</td>\n",
       "      <td>0.118080</td>\n",
       "      <td>0.113465</td>\n",
       "      <td>0.150145</td>\n",
       "      <td>0.332095</td>\n",
       "      <td>0.499262</td>\n",
       "      <td>...</td>\n",
       "      <td>0.410454</td>\n",
       "      <td>0.351467</td>\n",
       "      <td>0.572438</td>\n",
       "      <td>0.311857</td>\n",
       "      <td>0.481983</td>\n",
       "      <td>0.307753</td>\n",
       "      <td>0.710775</td>\n",
       "      <td>0.263235</td>\n",
       "      <td>0.307119</td>\n",
       "      <td>0.638893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>primase</th>\n",
       "      <td>0.109859</td>\n",
       "      <td>0.158261</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.139659</td>\n",
       "      <td>0.181204</td>\n",
       "      <td>0.100752</td>\n",
       "      <td>0.107248</td>\n",
       "      <td>0.104142</td>\n",
       "      <td>0.250981</td>\n",
       "      <td>0.556721</td>\n",
       "      <td>...</td>\n",
       "      <td>0.294951</td>\n",
       "      <td>0.260248</td>\n",
       "      <td>0.651945</td>\n",
       "      <td>0.229378</td>\n",
       "      <td>0.544933</td>\n",
       "      <td>0.343956</td>\n",
       "      <td>0.793200</td>\n",
       "      <td>0.297654</td>\n",
       "      <td>0.208403</td>\n",
       "      <td>0.712814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rnapol2</th>\n",
       "      <td>0.151885</td>\n",
       "      <td>0.177856</td>\n",
       "      <td>0.139659</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.172058</td>\n",
       "      <td>0.136753</td>\n",
       "      <td>0.173896</td>\n",
       "      <td>0.134871</td>\n",
       "      <td>0.256272</td>\n",
       "      <td>0.554112</td>\n",
       "      <td>...</td>\n",
       "      <td>0.311947</td>\n",
       "      <td>0.264315</td>\n",
       "      <td>0.617367</td>\n",
       "      <td>0.230667</td>\n",
       "      <td>0.543083</td>\n",
       "      <td>0.333924</td>\n",
       "      <td>0.764027</td>\n",
       "      <td>0.273529</td>\n",
       "      <td>0.218448</td>\n",
       "      <td>0.678382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>capsid</th>\n",
       "      <td>0.189734</td>\n",
       "      <td>0.155239</td>\n",
       "      <td>0.181204</td>\n",
       "      <td>0.172058</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.160154</td>\n",
       "      <td>0.171870</td>\n",
       "      <td>0.178269</td>\n",
       "      <td>0.316797</td>\n",
       "      <td>0.441048</td>\n",
       "      <td>...</td>\n",
       "      <td>0.400612</td>\n",
       "      <td>0.348821</td>\n",
       "      <td>0.506281</td>\n",
       "      <td>0.310714</td>\n",
       "      <td>0.422956</td>\n",
       "      <td>0.238404</td>\n",
       "      <td>0.642678</td>\n",
       "      <td>0.225406</td>\n",
       "      <td>0.288221</td>\n",
       "      <td>0.567764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rnapol1</th>\n",
       "      <td>0.101359</td>\n",
       "      <td>0.118080</td>\n",
       "      <td>0.100752</td>\n",
       "      <td>0.136753</td>\n",
       "      <td>0.160154</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.103380</td>\n",
       "      <td>0.125304</td>\n",
       "      <td>0.238828</td>\n",
       "      <td>0.511965</td>\n",
       "      <td>...</td>\n",
       "      <td>0.288121</td>\n",
       "      <td>0.260309</td>\n",
       "      <td>0.593759</td>\n",
       "      <td>0.240581</td>\n",
       "      <td>0.498692</td>\n",
       "      <td>0.297676</td>\n",
       "      <td>0.732617</td>\n",
       "      <td>0.238404</td>\n",
       "      <td>0.207269</td>\n",
       "      <td>0.652676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>packaging</th>\n",
       "      <td>0.121295</td>\n",
       "      <td>0.113465</td>\n",
       "      <td>0.107248</td>\n",
       "      <td>0.173896</td>\n",
       "      <td>0.171870</td>\n",
       "      <td>0.103380</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.117484</td>\n",
       "      <td>0.305569</td>\n",
       "      <td>0.536346</td>\n",
       "      <td>...</td>\n",
       "      <td>0.392808</td>\n",
       "      <td>0.319458</td>\n",
       "      <td>0.632538</td>\n",
       "      <td>0.285890</td>\n",
       "      <td>0.518076</td>\n",
       "      <td>0.341713</td>\n",
       "      <td>0.772890</td>\n",
       "      <td>0.298856</td>\n",
       "      <td>0.290192</td>\n",
       "      <td>0.700649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tf2s</th>\n",
       "      <td>0.108646</td>\n",
       "      <td>0.150145</td>\n",
       "      <td>0.104142</td>\n",
       "      <td>0.134871</td>\n",
       "      <td>0.178269</td>\n",
       "      <td>0.125304</td>\n",
       "      <td>0.117484</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.275260</td>\n",
       "      <td>0.569913</td>\n",
       "      <td>...</td>\n",
       "      <td>0.372920</td>\n",
       "      <td>0.289173</td>\n",
       "      <td>0.655767</td>\n",
       "      <td>0.240008</td>\n",
       "      <td>0.553122</td>\n",
       "      <td>0.366118</td>\n",
       "      <td>0.799090</td>\n",
       "      <td>0.318359</td>\n",
       "      <td>0.267720</td>\n",
       "      <td>0.722943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_packaging</th>\n",
       "      <td>0.225400</td>\n",
       "      <td>0.332095</td>\n",
       "      <td>0.250981</td>\n",
       "      <td>0.256272</td>\n",
       "      <td>0.316797</td>\n",
       "      <td>0.238828</td>\n",
       "      <td>0.305569</td>\n",
       "      <td>0.275260</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.619526</td>\n",
       "      <td>...</td>\n",
       "      <td>0.198122</td>\n",
       "      <td>0.140247</td>\n",
       "      <td>0.686372</td>\n",
       "      <td>0.162696</td>\n",
       "      <td>0.607214</td>\n",
       "      <td>0.381653</td>\n",
       "      <td>0.811064</td>\n",
       "      <td>0.343196</td>\n",
       "      <td>0.166807</td>\n",
       "      <td>0.723584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_packaging</th>\n",
       "      <td>0.570519</td>\n",
       "      <td>0.499262</td>\n",
       "      <td>0.556721</td>\n",
       "      <td>0.554112</td>\n",
       "      <td>0.441048</td>\n",
       "      <td>0.511965</td>\n",
       "      <td>0.536346</td>\n",
       "      <td>0.569913</td>\n",
       "      <td>0.619526</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.638743</td>\n",
       "      <td>0.665360</td>\n",
       "      <td>0.230396</td>\n",
       "      <td>0.666839</td>\n",
       "      <td>0.081589</td>\n",
       "      <td>0.282217</td>\n",
       "      <td>0.365979</td>\n",
       "      <td>0.342277</td>\n",
       "      <td>0.571332</td>\n",
       "      <td>0.323011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_tf2s</th>\n",
       "      <td>0.221639</td>\n",
       "      <td>0.337032</td>\n",
       "      <td>0.241735</td>\n",
       "      <td>0.250196</td>\n",
       "      <td>0.332940</td>\n",
       "      <td>0.253368</td>\n",
       "      <td>0.317528</td>\n",
       "      <td>0.282534</td>\n",
       "      <td>0.161827</td>\n",
       "      <td>0.653376</td>\n",
       "      <td>...</td>\n",
       "      <td>0.185740</td>\n",
       "      <td>0.164593</td>\n",
       "      <td>0.719050</td>\n",
       "      <td>0.167884</td>\n",
       "      <td>0.647232</td>\n",
       "      <td>0.407934</td>\n",
       "      <td>0.843453</td>\n",
       "      <td>0.381163</td>\n",
       "      <td>0.164653</td>\n",
       "      <td>0.753223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_vltf3</th>\n",
       "      <td>0.200414</td>\n",
       "      <td>0.318167</td>\n",
       "      <td>0.221088</td>\n",
       "      <td>0.234497</td>\n",
       "      <td>0.315809</td>\n",
       "      <td>0.229614</td>\n",
       "      <td>0.293631</td>\n",
       "      <td>0.256544</td>\n",
       "      <td>0.145825</td>\n",
       "      <td>0.655197</td>\n",
       "      <td>...</td>\n",
       "      <td>0.209891</td>\n",
       "      <td>0.156025</td>\n",
       "      <td>0.718180</td>\n",
       "      <td>0.130028</td>\n",
       "      <td>0.645132</td>\n",
       "      <td>0.410888</td>\n",
       "      <td>0.840895</td>\n",
       "      <td>0.377229</td>\n",
       "      <td>0.163393</td>\n",
       "      <td>0.755811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_capsid</th>\n",
       "      <td>0.257350</td>\n",
       "      <td>0.376430</td>\n",
       "      <td>0.271699</td>\n",
       "      <td>0.288271</td>\n",
       "      <td>0.368429</td>\n",
       "      <td>0.274929</td>\n",
       "      <td>0.351998</td>\n",
       "      <td>0.313594</td>\n",
       "      <td>0.154964</td>\n",
       "      <td>0.667430</td>\n",
       "      <td>...</td>\n",
       "      <td>0.200823</td>\n",
       "      <td>0.172900</td>\n",
       "      <td>0.729669</td>\n",
       "      <td>0.144669</td>\n",
       "      <td>0.660053</td>\n",
       "      <td>0.425649</td>\n",
       "      <td>0.847432</td>\n",
       "      <td>0.397084</td>\n",
       "      <td>0.166591</td>\n",
       "      <td>0.762238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_vltf3</th>\n",
       "      <td>0.514348</td>\n",
       "      <td>0.461157</td>\n",
       "      <td>0.518290</td>\n",
       "      <td>0.477842</td>\n",
       "      <td>0.377004</td>\n",
       "      <td>0.464618</td>\n",
       "      <td>0.514661</td>\n",
       "      <td>0.525715</td>\n",
       "      <td>0.533221</td>\n",
       "      <td>0.236500</td>\n",
       "      <td>...</td>\n",
       "      <td>0.556800</td>\n",
       "      <td>0.580900</td>\n",
       "      <td>0.201115</td>\n",
       "      <td>0.574519</td>\n",
       "      <td>0.232482</td>\n",
       "      <td>0.212081</td>\n",
       "      <td>0.327520</td>\n",
       "      <td>0.287842</td>\n",
       "      <td>0.488610</td>\n",
       "      <td>0.254469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_rnapol2</th>\n",
       "      <td>0.278555</td>\n",
       "      <td>0.410454</td>\n",
       "      <td>0.294951</td>\n",
       "      <td>0.311947</td>\n",
       "      <td>0.400612</td>\n",
       "      <td>0.288121</td>\n",
       "      <td>0.392808</td>\n",
       "      <td>0.372920</td>\n",
       "      <td>0.198122</td>\n",
       "      <td>0.638743</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.228401</td>\n",
       "      <td>0.706773</td>\n",
       "      <td>0.229398</td>\n",
       "      <td>0.638405</td>\n",
       "      <td>0.407669</td>\n",
       "      <td>0.832771</td>\n",
       "      <td>0.377729</td>\n",
       "      <td>0.178017</td>\n",
       "      <td>0.743707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_rnapol1</th>\n",
       "      <td>0.244786</td>\n",
       "      <td>0.351467</td>\n",
       "      <td>0.260248</td>\n",
       "      <td>0.264315</td>\n",
       "      <td>0.348821</td>\n",
       "      <td>0.260309</td>\n",
       "      <td>0.319458</td>\n",
       "      <td>0.289173</td>\n",
       "      <td>0.140247</td>\n",
       "      <td>0.665360</td>\n",
       "      <td>...</td>\n",
       "      <td>0.228401</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.734569</td>\n",
       "      <td>0.175090</td>\n",
       "      <td>0.657598</td>\n",
       "      <td>0.426109</td>\n",
       "      <td>0.860650</td>\n",
       "      <td>0.379615</td>\n",
       "      <td>0.201359</td>\n",
       "      <td>0.771026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_rnapol1</th>\n",
       "      <td>0.650479</td>\n",
       "      <td>0.572438</td>\n",
       "      <td>0.651945</td>\n",
       "      <td>0.617367</td>\n",
       "      <td>0.506281</td>\n",
       "      <td>0.593759</td>\n",
       "      <td>0.632538</td>\n",
       "      <td>0.655767</td>\n",
       "      <td>0.686372</td>\n",
       "      <td>0.230396</td>\n",
       "      <td>...</td>\n",
       "      <td>0.706773</td>\n",
       "      <td>0.734569</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.723921</td>\n",
       "      <td>0.227479</td>\n",
       "      <td>0.337805</td>\n",
       "      <td>0.210725</td>\n",
       "      <td>0.415044</td>\n",
       "      <td>0.640560</td>\n",
       "      <td>0.155619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_primase</th>\n",
       "      <td>0.205494</td>\n",
       "      <td>0.311857</td>\n",
       "      <td>0.229378</td>\n",
       "      <td>0.230667</td>\n",
       "      <td>0.310714</td>\n",
       "      <td>0.240581</td>\n",
       "      <td>0.285890</td>\n",
       "      <td>0.240008</td>\n",
       "      <td>0.162696</td>\n",
       "      <td>0.666839</td>\n",
       "      <td>...</td>\n",
       "      <td>0.229398</td>\n",
       "      <td>0.175090</td>\n",
       "      <td>0.723921</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.656468</td>\n",
       "      <td>0.422765</td>\n",
       "      <td>0.840616</td>\n",
       "      <td>0.394858</td>\n",
       "      <td>0.179934</td>\n",
       "      <td>0.757348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_primase</th>\n",
       "      <td>0.556278</td>\n",
       "      <td>0.481983</td>\n",
       "      <td>0.544933</td>\n",
       "      <td>0.543083</td>\n",
       "      <td>0.422956</td>\n",
       "      <td>0.498692</td>\n",
       "      <td>0.518076</td>\n",
       "      <td>0.553122</td>\n",
       "      <td>0.607214</td>\n",
       "      <td>0.081589</td>\n",
       "      <td>...</td>\n",
       "      <td>0.638405</td>\n",
       "      <td>0.657598</td>\n",
       "      <td>0.227479</td>\n",
       "      <td>0.656468</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.274578</td>\n",
       "      <td>0.366655</td>\n",
       "      <td>0.335816</td>\n",
       "      <td>0.569660</td>\n",
       "      <td>0.325166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_dnapol</th>\n",
       "      <td>0.346783</td>\n",
       "      <td>0.307753</td>\n",
       "      <td>0.343956</td>\n",
       "      <td>0.333924</td>\n",
       "      <td>0.238404</td>\n",
       "      <td>0.297676</td>\n",
       "      <td>0.341713</td>\n",
       "      <td>0.366118</td>\n",
       "      <td>0.381653</td>\n",
       "      <td>0.282217</td>\n",
       "      <td>...</td>\n",
       "      <td>0.407669</td>\n",
       "      <td>0.426109</td>\n",
       "      <td>0.337805</td>\n",
       "      <td>0.422765</td>\n",
       "      <td>0.274578</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.472224</td>\n",
       "      <td>0.167653</td>\n",
       "      <td>0.334257</td>\n",
       "      <td>0.388266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_capsid</th>\n",
       "      <td>0.782643</td>\n",
       "      <td>0.710775</td>\n",
       "      <td>0.793200</td>\n",
       "      <td>0.764027</td>\n",
       "      <td>0.642678</td>\n",
       "      <td>0.732617</td>\n",
       "      <td>0.772890</td>\n",
       "      <td>0.799090</td>\n",
       "      <td>0.811064</td>\n",
       "      <td>0.365979</td>\n",
       "      <td>...</td>\n",
       "      <td>0.832771</td>\n",
       "      <td>0.860650</td>\n",
       "      <td>0.210725</td>\n",
       "      <td>0.840616</td>\n",
       "      <td>0.366655</td>\n",
       "      <td>0.472224</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.564135</td>\n",
       "      <td>0.764671</td>\n",
       "      <td>0.147171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_rnapol2</th>\n",
       "      <td>0.295743</td>\n",
       "      <td>0.263235</td>\n",
       "      <td>0.297654</td>\n",
       "      <td>0.273529</td>\n",
       "      <td>0.225406</td>\n",
       "      <td>0.238404</td>\n",
       "      <td>0.298856</td>\n",
       "      <td>0.318359</td>\n",
       "      <td>0.343196</td>\n",
       "      <td>0.342277</td>\n",
       "      <td>...</td>\n",
       "      <td>0.377729</td>\n",
       "      <td>0.379615</td>\n",
       "      <td>0.415044</td>\n",
       "      <td>0.394858</td>\n",
       "      <td>0.335816</td>\n",
       "      <td>0.167653</td>\n",
       "      <td>0.564135</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.309935</td>\n",
       "      <td>0.486142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bd_dnapol</th>\n",
       "      <td>0.197951</td>\n",
       "      <td>0.307119</td>\n",
       "      <td>0.208403</td>\n",
       "      <td>0.218448</td>\n",
       "      <td>0.288221</td>\n",
       "      <td>0.207269</td>\n",
       "      <td>0.290192</td>\n",
       "      <td>0.267720</td>\n",
       "      <td>0.166807</td>\n",
       "      <td>0.571332</td>\n",
       "      <td>...</td>\n",
       "      <td>0.178017</td>\n",
       "      <td>0.201359</td>\n",
       "      <td>0.640560</td>\n",
       "      <td>0.179934</td>\n",
       "      <td>0.569660</td>\n",
       "      <td>0.334257</td>\n",
       "      <td>0.764671</td>\n",
       "      <td>0.309935</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.679557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kingman_tf2s</th>\n",
       "      <td>0.703659</td>\n",
       "      <td>0.638893</td>\n",
       "      <td>0.712814</td>\n",
       "      <td>0.678382</td>\n",
       "      <td>0.567764</td>\n",
       "      <td>0.652676</td>\n",
       "      <td>0.700649</td>\n",
       "      <td>0.722943</td>\n",
       "      <td>0.723584</td>\n",
       "      <td>0.323011</td>\n",
       "      <td>...</td>\n",
       "      <td>0.743707</td>\n",
       "      <td>0.771026</td>\n",
       "      <td>0.155619</td>\n",
       "      <td>0.757348</td>\n",
       "      <td>0.325166</td>\n",
       "      <td>0.388266</td>\n",
       "      <td>0.147171</td>\n",
       "      <td>0.486142</td>\n",
       "      <td>0.679557</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>24 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     dnapol     vltf3   primase   rnapol2    capsid   rnapol1  \\\n",
       "dnapol             0.000000  0.144687  0.109859  0.151885  0.189734  0.101359   \n",
       "vltf3              0.144687  0.000000  0.158261  0.177856  0.155239  0.118080   \n",
       "primase            0.109859  0.158261  0.000000  0.139659  0.181204  0.100752   \n",
       "rnapol2            0.151885  0.177856  0.139659  0.000000  0.172058  0.136753   \n",
       "capsid             0.189734  0.155239  0.181204  0.172058  0.000000  0.160154   \n",
       "rnapol1            0.101359  0.118080  0.100752  0.136753  0.160154  0.000000   \n",
       "packaging          0.121295  0.113465  0.107248  0.173896  0.171870  0.103380   \n",
       "tf2s               0.108646  0.150145  0.104142  0.134871  0.178269  0.125304   \n",
       "bd_packaging       0.225400  0.332095  0.250981  0.256272  0.316797  0.238828   \n",
       "kingman_packaging  0.570519  0.499262  0.556721  0.554112  0.441048  0.511965   \n",
       "bd_tf2s            0.221639  0.337032  0.241735  0.250196  0.332940  0.253368   \n",
       "bd_vltf3           0.200414  0.318167  0.221088  0.234497  0.315809  0.229614   \n",
       "bd_capsid          0.257350  0.376430  0.271699  0.288271  0.368429  0.274929   \n",
       "kingman_vltf3      0.514348  0.461157  0.518290  0.477842  0.377004  0.464618   \n",
       "bd_rnapol2         0.278555  0.410454  0.294951  0.311947  0.400612  0.288121   \n",
       "bd_rnapol1         0.244786  0.351467  0.260248  0.264315  0.348821  0.260309   \n",
       "kingman_rnapol1    0.650479  0.572438  0.651945  0.617367  0.506281  0.593759   \n",
       "bd_primase         0.205494  0.311857  0.229378  0.230667  0.310714  0.240581   \n",
       "kingman_primase    0.556278  0.481983  0.544933  0.543083  0.422956  0.498692   \n",
       "kingman_dnapol     0.346783  0.307753  0.343956  0.333924  0.238404  0.297676   \n",
       "kingman_capsid     0.782643  0.710775  0.793200  0.764027  0.642678  0.732617   \n",
       "kingman_rnapol2    0.295743  0.263235  0.297654  0.273529  0.225406  0.238404   \n",
       "bd_dnapol          0.197951  0.307119  0.208403  0.218448  0.288221  0.207269   \n",
       "kingman_tf2s       0.703659  0.638893  0.712814  0.678382  0.567764  0.652676   \n",
       "\n",
       "                   packaging      tf2s  bd_packaging  kingman_packaging  ...  \\\n",
       "dnapol              0.121295  0.108646      0.225400           0.570519  ...   \n",
       "vltf3               0.113465  0.150145      0.332095           0.499262  ...   \n",
       "primase             0.107248  0.104142      0.250981           0.556721  ...   \n",
       "rnapol2             0.173896  0.134871      0.256272           0.554112  ...   \n",
       "capsid              0.171870  0.178269      0.316797           0.441048  ...   \n",
       "rnapol1             0.103380  0.125304      0.238828           0.511965  ...   \n",
       "packaging           0.000000  0.117484      0.305569           0.536346  ...   \n",
       "tf2s                0.117484  0.000000      0.275260           0.569913  ...   \n",
       "bd_packaging        0.305569  0.275260      0.000000           0.619526  ...   \n",
       "kingman_packaging   0.536346  0.569913      0.619526           0.000000  ...   \n",
       "bd_tf2s             0.317528  0.282534      0.161827           0.653376  ...   \n",
       "bd_vltf3            0.293631  0.256544      0.145825           0.655197  ...   \n",
       "bd_capsid           0.351998  0.313594      0.154964           0.667430  ...   \n",
       "kingman_vltf3       0.514661  0.525715      0.533221           0.236500  ...   \n",
       "bd_rnapol2          0.392808  0.372920      0.198122           0.638743  ...   \n",
       "bd_rnapol1          0.319458  0.289173      0.140247           0.665360  ...   \n",
       "kingman_rnapol1     0.632538  0.655767      0.686372           0.230396  ...   \n",
       "bd_primase          0.285890  0.240008      0.162696           0.666839  ...   \n",
       "kingman_primase     0.518076  0.553122      0.607214           0.081589  ...   \n",
       "kingman_dnapol      0.341713  0.366118      0.381653           0.282217  ...   \n",
       "kingman_capsid      0.772890  0.799090      0.811064           0.365979  ...   \n",
       "kingman_rnapol2     0.298856  0.318359      0.343196           0.342277  ...   \n",
       "bd_dnapol           0.290192  0.267720      0.166807           0.571332  ...   \n",
       "kingman_tf2s        0.700649  0.722943      0.723584           0.323011  ...   \n",
       "\n",
       "                   bd_rnapol2  bd_rnapol1  kingman_rnapol1  bd_primase  \\\n",
       "dnapol               0.278555    0.244786         0.650479    0.205494   \n",
       "vltf3                0.410454    0.351467         0.572438    0.311857   \n",
       "primase              0.294951    0.260248         0.651945    0.229378   \n",
       "rnapol2              0.311947    0.264315         0.617367    0.230667   \n",
       "capsid               0.400612    0.348821         0.506281    0.310714   \n",
       "rnapol1              0.288121    0.260309         0.593759    0.240581   \n",
       "packaging            0.392808    0.319458         0.632538    0.285890   \n",
       "tf2s                 0.372920    0.289173         0.655767    0.240008   \n",
       "bd_packaging         0.198122    0.140247         0.686372    0.162696   \n",
       "kingman_packaging    0.638743    0.665360         0.230396    0.666839   \n",
       "bd_tf2s              0.185740    0.164593         0.719050    0.167884   \n",
       "bd_vltf3             0.209891    0.156025         0.718180    0.130028   \n",
       "bd_capsid            0.200823    0.172900         0.729669    0.144669   \n",
       "kingman_vltf3        0.556800    0.580900         0.201115    0.574519   \n",
       "bd_rnapol2           0.000000    0.228401         0.706773    0.229398   \n",
       "bd_rnapol1           0.228401    0.000000         0.734569    0.175090   \n",
       "kingman_rnapol1      0.706773    0.734569         0.000000    0.723921   \n",
       "bd_primase           0.229398    0.175090         0.723921    0.000000   \n",
       "kingman_primase      0.638405    0.657598         0.227479    0.656468   \n",
       "kingman_dnapol       0.407669    0.426109         0.337805    0.422765   \n",
       "kingman_capsid       0.832771    0.860650         0.210725    0.840616   \n",
       "kingman_rnapol2      0.377729    0.379615         0.415044    0.394858   \n",
       "bd_dnapol            0.178017    0.201359         0.640560    0.179934   \n",
       "kingman_tf2s         0.743707    0.771026         0.155619    0.757348   \n",
       "\n",
       "                   kingman_primase  kingman_dnapol  kingman_capsid  \\\n",
       "dnapol                    0.556278        0.346783        0.782643   \n",
       "vltf3                     0.481983        0.307753        0.710775   \n",
       "primase                   0.544933        0.343956        0.793200   \n",
       "rnapol2                   0.543083        0.333924        0.764027   \n",
       "capsid                    0.422956        0.238404        0.642678   \n",
       "rnapol1                   0.498692        0.297676        0.732617   \n",
       "packaging                 0.518076        0.341713        0.772890   \n",
       "tf2s                      0.553122        0.366118        0.799090   \n",
       "bd_packaging              0.607214        0.381653        0.811064   \n",
       "kingman_packaging         0.081589        0.282217        0.365979   \n",
       "bd_tf2s                   0.647232        0.407934        0.843453   \n",
       "bd_vltf3                  0.645132        0.410888        0.840895   \n",
       "bd_capsid                 0.660053        0.425649        0.847432   \n",
       "kingman_vltf3             0.232482        0.212081        0.327520   \n",
       "bd_rnapol2                0.638405        0.407669        0.832771   \n",
       "bd_rnapol1                0.657598        0.426109        0.860650   \n",
       "kingman_rnapol1           0.227479        0.337805        0.210725   \n",
       "bd_primase                0.656468        0.422765        0.840616   \n",
       "kingman_primase           0.000000        0.274578        0.366655   \n",
       "kingman_dnapol            0.274578        0.000000        0.472224   \n",
       "kingman_capsid            0.366655        0.472224        0.000000   \n",
       "kingman_rnapol2           0.335816        0.167653        0.564135   \n",
       "bd_dnapol                 0.569660        0.334257        0.764671   \n",
       "kingman_tf2s              0.325166        0.388266        0.147171   \n",
       "\n",
       "                   kingman_rnapol2  bd_dnapol  kingman_tf2s  \n",
       "dnapol                    0.295743   0.197951      0.703659  \n",
       "vltf3                     0.263235   0.307119      0.638893  \n",
       "primase                   0.297654   0.208403      0.712814  \n",
       "rnapol2                   0.273529   0.218448      0.678382  \n",
       "capsid                    0.225406   0.288221      0.567764  \n",
       "rnapol1                   0.238404   0.207269      0.652676  \n",
       "packaging                 0.298856   0.290192      0.700649  \n",
       "tf2s                      0.318359   0.267720      0.722943  \n",
       "bd_packaging              0.343196   0.166807      0.723584  \n",
       "kingman_packaging         0.342277   0.571332      0.323011  \n",
       "bd_tf2s                   0.381163   0.164653      0.753223  \n",
       "bd_vltf3                  0.377229   0.163393      0.755811  \n",
       "bd_capsid                 0.397084   0.166591      0.762238  \n",
       "kingman_vltf3             0.287842   0.488610      0.254469  \n",
       "bd_rnapol2                0.377729   0.178017      0.743707  \n",
       "bd_rnapol1                0.379615   0.201359      0.771026  \n",
       "kingman_rnapol1           0.415044   0.640560      0.155619  \n",
       "bd_primase                0.394858   0.179934      0.757348  \n",
       "kingman_primase           0.335816   0.569660      0.325166  \n",
       "kingman_dnapol            0.167653   0.334257      0.388266  \n",
       "kingman_capsid            0.564135   0.764671      0.147171  \n",
       "kingman_rnapol2           0.000000   0.309935      0.486142  \n",
       "bd_dnapol                 0.309935   0.000000      0.679557  \n",
       "kingman_tf2s              0.486142   0.679557      0.000000  \n",
       "\n",
       "[24 rows x 24 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jsdist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "        0.10135884, 0.12129471, 0.10864586, 0.22959132, 0.51426633,\n",
       "        0.2016781 , 0.22674701, 0.19395793, 0.6285069 , 0.21456739,\n",
       "        0.19136234, 0.66647204, 0.22295154, 0.48519189, 0.46940338,\n",
       "        0.66215848, 0.69257046, 0.21571131, 0.57925208],\n",
       "       [0.14468745, 0.        , 0.15826069, 0.1778562 , 0.15523944,\n",
       "        0.11807988, 0.11346501, 0.15014471, 0.35293355, 0.45126023,\n",
       "        0.29940271, 0.33478743, 0.29878774, 0.55746334, 0.32964462,\n",
       "        0.27208089, 0.59681562, 0.30530502, 0.43005249, 0.4138846 ,\n",
       "        0.58812415, 0.61961449, 0.3183376 , 0.51752927],\n",
       "       [0.10985873, 0.15826069, 0.        , 0.13965854, 0.18120359,\n",
       "        0.10075215, 0.10724773, 0.10414181, 0.2516558 , 0.5198063 ,\n",
       "        0.21049182, 0.2478213 , 0.21184046, 0.63116001, 0.22925143,\n",
       "        0.20707734, 0.67162855, 0.23252907, 0.482037  , 0.46889672,\n",
       "        0.66922265, 0.69935401, 0.23040461, 0.56039756],\n",
       "       [0.15188482, 0.1778562 , 0.13965854, 0.        , 0.17205845,\n",
       "        0.13675346, 0.17389613, 0.13487139, 0.26157105, 0.51575402,\n",
       "        0.21152562, 0.24578296, 0.21562252, 0.59123435, 0.24676795,\n",
       "        0.19483412, 0.64315901, 0.24404803, 0.45685337, 0.45500269,\n",
       "        0.64610092, 0.67453775, 0.24911153, 0.57443183],\n",
       "       [0.18973392, 0.15523944, 0.18120359, 0.17205845, 0.        ,\n",
       "        0.16015365, 0.17186983, 0.17826924, 0.34164975, 0.3954448 ,\n",
       "        0.29465806, 0.31838669, 0.29316984, 0.47788886, 0.32407045,\n",
       "        0.26159585, 0.52651487, 0.27313178, 0.34911446, 0.34715331,\n",
       "        0.52222505, 0.55368527, 0.28953931, 0.45963749],\n",
       "       [0.10135884, 0.11807988, 0.10075215, 0.13675346, 0.16015365,\n",
       "        0.        , 0.10337969, 0.12530412, 0.25395283, 0.46624395,\n",
       "        0.23393594, 0.2357117 , 0.19936214, 0.57362769, 0.23325263,\n",
       "        0.18263893, 0.61211367, 0.21693967, 0.43531182, 0.41557735,\n",
       "        0.60998448, 0.64165843, 0.2348404 , 0.52227143],\n",
       "       [0.12129471, 0.11346501, 0.10724773, 0.17389613, 0.17186983,\n",
       "        0.10337969, 0.        , 0.11748408, 0.33219718, 0.49732237,\n",
       "        0.27327786, 0.31707328, 0.28365821, 0.61576587, 0.30137271,\n",
       "        0.2656872 , 0.65339284, 0.28871973, 0.4757397 , 0.45914277,\n",
       "        0.64443989, 0.67758097, 0.29230291, 0.54417866],\n",
       "       [0.10864586, 0.15014471, 0.10414181, 0.13487139, 0.17826924,\n",
       "        0.12530412, 0.11748408, 0.        , 0.29993835, 0.53524323,\n",
       "        0.22900066, 0.28967333, 0.26931624, 0.63465141, 0.26387357,\n",
       "        0.23799018, 0.68029903, 0.26503031, 0.4927885 , 0.48985203,\n",
       "        0.67507787, 0.7061125 , 0.25880868, 0.57982908],\n",
       "       [0.22959132, 0.35293355, 0.2516558 , 0.26157105, 0.34164975,\n",
       "        0.25395283, 0.33219718, 0.29993835, 0.        , 0.58156146,\n",
       "        0.16957613, 0.15835598, 0.174073  , 0.6788071 , 0.13559958,\n",
       "        0.16171302, 0.71892085, 0.19580107, 0.53357777, 0.5247596 ,\n",
       "        0.72175672, 0.74310957, 0.16121431, 0.64568858],\n",
       "       [0.51426633, 0.45126023, 0.5198063 , 0.51575402, 0.3954448 ,\n",
       "        0.46624395, 0.49732237, 0.53524323, 0.58156146, 0.        ,\n",
       "        0.59011602, 0.54888627, 0.51367176, 0.19463572, 0.58271545,\n",
       "        0.51270504, 0.20938457, 0.47451198, 0.1606087 , 0.13007092,\n",
       "        0.18893793, 0.23089908, 0.53973834, 0.23037502],\n",
       "       [0.2016781 , 0.29940271, 0.21049182, 0.21152562, 0.29465806,\n",
       "        0.23393594, 0.27327786, 0.22900066, 0.16957613, 0.59011602,\n",
       "        0.        , 0.17244493, 0.17194131, 0.68833276, 0.15994382,\n",
       "        0.17896873, 0.7299049 , 0.19420498, 0.5386935 , 0.53462468,\n",
       "        0.73303642, 0.74891596, 0.16882662, 0.65139944],\n",
       "       [0.22674701, 0.33478743, 0.2478213 , 0.24578296, 0.31838669,\n",
       "        0.2357117 , 0.31707328, 0.28967333, 0.15835598, 0.54888627,\n",
       "        0.17244493, 0.        , 0.16376431, 0.63998065, 0.15934449,\n",
       "        0.14859608, 0.68209001, 0.15378287, 0.49817559, 0.48708256,\n",
       "        0.6870221 , 0.70988718, 0.15087814, 0.60748781],\n",
       "       [0.19395793, 0.29878774, 0.21184046, 0.21562252, 0.29316984,\n",
       "        0.19936214, 0.28365821, 0.26931624, 0.174073  , 0.51367176,\n",
       "        0.17194131, 0.16376431, 0.        , 0.61379877, 0.15939157,\n",
       "        0.1505337 , 0.65722657, 0.16763765, 0.46473996, 0.4604257 ,\n",
       "        0.65146005, 0.67442964, 0.1870812 , 0.58447424],\n",
       "       [0.6285069 , 0.55746334, 0.63116001, 0.59123435, 0.47788886,\n",
       "        0.57362769, 0.61576587, 0.63465141, 0.6788071 , 0.19463572,\n",
       "        0.68833276, 0.63998065, 0.61379877, 0.        , 0.67872946,\n",
       "        0.60184654, 0.13821862, 0.57016683, 0.1941565 , 0.20278606,\n",
       "        0.14191104, 0.18607285, 0.63760128, 0.27383849],\n",
       "       [0.21456739, 0.32964462, 0.22925143, 0.24676795, 0.32407045,\n",
       "        0.23325263, 0.30137271, 0.26387357, 0.13559958, 0.58271545,\n",
       "        0.15994382, 0.15934449, 0.15939157, 0.67872946, 0.        ,\n",
       "        0.16458384, 0.7239818 , 0.17301498, 0.53075009, 0.52381422,\n",
       "        0.72328113, 0.74555384, 0.14042912, 0.63632432],\n",
       "       [0.19136234, 0.27208089, 0.20707734, 0.19483412, 0.26159585,\n",
       "        0.18263893, 0.2656872 , 0.23799018, 0.16171302, 0.51270504,\n",
       "        0.17896873, 0.14859608, 0.1505337 , 0.60184654, 0.16458384,\n",
       "        0.        , 0.64731503, 0.16551076, 0.46251394, 0.45269365,\n",
       "        0.64598541, 0.67554317, 0.16206654, 0.57560656],\n",
       "       [0.66647204, 0.59681562, 0.67162855, 0.64315901, 0.52651487,\n",
       "        0.61211367, 0.65339284, 0.68029903, 0.71892085, 0.20938457,\n",
       "        0.7299049 , 0.68209001, 0.65722657, 0.13821862, 0.7239818 ,\n",
       "        0.64731503, 0.        , 0.61226566, 0.23625379, 0.23261522,\n",
       "        0.11574647, 0.12746792, 0.67597215, 0.27057896],\n",
       "       [0.22295154, 0.30530502, 0.23252907, 0.24404803, 0.27313178,\n",
       "        0.21693967, 0.28871973, 0.26503031, 0.19580107, 0.47451198,\n",
       "        0.19420498, 0.15378287, 0.16763765, 0.57016683, 0.17301498,\n",
       "        0.16551076, 0.61226566, 0.        , 0.42292605, 0.41817166,\n",
       "        0.61529242, 0.63620353, 0.14537945, 0.52405485],\n",
       "       [0.48519189, 0.43005249, 0.482037  , 0.45685337, 0.34911446,\n",
       "        0.43531182, 0.4757397 , 0.4927885 , 0.53357777, 0.1606087 ,\n",
       "        0.5386935 , 0.49817559, 0.46473996, 0.1941565 , 0.53075009,\n",
       "        0.46251394, 0.23625379, 0.42292605, 0.        , 0.14356891,\n",
       "        0.23235045, 0.26114341, 0.49196203, 0.23448501],\n",
       "       [0.46940338, 0.4138846 , 0.46889672, 0.45500269, 0.34715331,\n",
       "        0.41557735, 0.45914277, 0.48985203, 0.5247596 , 0.13007092,\n",
       "        0.53462468, 0.48708256, 0.4604257 , 0.20278606, 0.52381422,\n",
       "        0.45269365, 0.23261522, 0.41817166, 0.14356891, 0.        ,\n",
       "        0.23275788, 0.26747919, 0.47970472, 0.24113125],\n",
       "       [0.66215848, 0.58812415, 0.66922265, 0.64610092, 0.52222505,\n",
       "        0.60998448, 0.64443989, 0.67507787, 0.72175672, 0.18893793,\n",
       "        0.73303642, 0.6870221 , 0.65146005, 0.14191104, 0.72328113,\n",
       "        0.64598541, 0.11574647, 0.61529242, 0.23235045, 0.23275788,\n",
       "        0.        , 0.13392114, 0.67925502, 0.27686039],\n",
       "       [0.69257046, 0.61961449, 0.69935401, 0.67453775, 0.55368527,\n",
       "        0.64165843, 0.67758097, 0.7061125 , 0.74310957, 0.23089908,\n",
       "        0.74891596, 0.70988718, 0.67442964, 0.18607285, 0.74555384,\n",
       "        0.67554317, 0.12746792, 0.63620353, 0.26114341, 0.26747919,\n",
       "        0.13392114, 0.        , 0.70135979, 0.31380153],\n",
       "       [0.21571131, 0.3183376 , 0.23040461, 0.24911153, 0.28953931,\n",
       "        0.2348404 , 0.29230291, 0.25880868, 0.16121431, 0.53973834,\n",
       "        0.16882662, 0.15087814, 0.1870812 , 0.63760128, 0.14042912,\n",
       "        0.16206654, 0.67597215, 0.14537945, 0.49196203, 0.47970472,\n",
       "        0.67925502, 0.70135979, 0.        , 0.59058967],\n",
       "       [0.57925208, 0.51752927, 0.56039756, 0.57443183, 0.45963749,\n",
       "        0.52227143, 0.54417866, 0.57982908, 0.64568858, 0.23037502,\n",
       "        0.65139944, 0.60748781, 0.58447424, 0.27383849, 0.63632432,\n",
       "        0.57560656, 0.27057896, 0.52405485, 0.23448501, 0.24113125,\n",
       "        0.27686039, 0.31380153, 0.59058967, 0.        ]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jsd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.14468745, 0.10985873, 0.15188482, 0.18973392, 0.10135884,\n",
       "       0.12129471, 0.10864586, 0.22959132, 0.51426633, 0.2016781 ,\n",
       "       0.22674701, 0.19395793, 0.6285069 , 0.21456739, 0.19136234,\n",
       "       0.66647204, 0.22295154, 0.48519189, 0.46940338, 0.66215848,\n",
       "       0.69257046, 0.21571131, 0.57925208, 0.15826069, 0.1778562 ,\n",
       "       0.15523944, 0.11807988, 0.11346501, 0.15014471, 0.35293355,\n",
       "       0.45126023, 0.29940271, 0.33478743, 0.29878774, 0.55746334,\n",
       "       0.32964462, 0.27208089, 0.59681562, 0.30530502, 0.43005249,\n",
       "       0.4138846 , 0.58812415, 0.61961449, 0.3183376 , 0.51752927,\n",
       "       0.13965854, 0.18120359, 0.10075215, 0.10724773, 0.10414181,\n",
       "       0.2516558 , 0.5198063 , 0.21049182, 0.2478213 , 0.21184046,\n",
       "       0.63116001, 0.22925143, 0.20707734, 0.67162855, 0.23252907,\n",
       "       0.482037  , 0.46889672, 0.66922265, 0.69935401, 0.23040461,\n",
       "       0.56039756, 0.17205845, 0.13675346, 0.17389613, 0.13487139,\n",
       "       0.26157105, 0.51575402, 0.21152562, 0.24578296, 0.21562252,\n",
       "       0.59123435, 0.24676795, 0.19483412, 0.64315901, 0.24404803,\n",
       "       0.45685337, 0.45500269, 0.64610092, 0.67453775, 0.24911153,\n",
       "       0.57443183, 0.16015365, 0.17186983, 0.17826924, 0.34164975,\n",
       "       0.3954448 , 0.29465806, 0.31838669, 0.29316984, 0.47788886,\n",
       "       0.32407045, 0.26159585, 0.52651487, 0.27313178, 0.34911446,\n",
       "       0.34715331, 0.52222505, 0.55368527, 0.28953931, 0.45963749,\n",
       "       0.10337969, 0.12530412, 0.25395283, 0.46624395, 0.23393594,\n",
       "       0.2357117 , 0.19936214, 0.57362769, 0.23325263, 0.18263893,\n",
       "       0.61211367, 0.21693967, 0.43531182, 0.41557735, 0.60998448,\n",
       "       0.64165843, 0.2348404 , 0.52227143, 0.11748408, 0.33219718,\n",
       "       0.49732237, 0.27327786, 0.31707328, 0.28365821, 0.61576587,\n",
       "       0.30137271, 0.2656872 , 0.65339284, 0.28871973, 0.4757397 ,\n",
       "       0.45914277, 0.64443989, 0.67758097, 0.29230291, 0.54417866,\n",
       "       0.29993835, 0.53524323, 0.22900066, 0.28967333, 0.26931624,\n",
       "       0.63465141, 0.26387357, 0.23799018, 0.68029903, 0.26503031,\n",
       "       0.4927885 , 0.48985203, 0.67507787, 0.7061125 , 0.25880868,\n",
       "       0.57982908, 0.58156146, 0.16957613, 0.15835598, 0.174073  ,\n",
       "       0.6788071 , 0.13559958, 0.16171302, 0.71892085, 0.19580107,\n",
       "       0.53357777, 0.5247596 , 0.72175672, 0.74310957, 0.16121431,\n",
       "       0.64568858, 0.59011602, 0.54888627, 0.51367176, 0.19463572,\n",
       "       0.58271545, 0.51270504, 0.20938457, 0.47451198, 0.1606087 ,\n",
       "       0.13007092, 0.18893793, 0.23089908, 0.53973834, 0.23037502,\n",
       "       0.17244493, 0.17194131, 0.68833276, 0.15994382, 0.17896873,\n",
       "       0.7299049 , 0.19420498, 0.5386935 , 0.53462468, 0.73303642,\n",
       "       0.74891596, 0.16882662, 0.65139944, 0.16376431, 0.63998065,\n",
       "       0.15934449, 0.14859608, 0.68209001, 0.15378287, 0.49817559,\n",
       "       0.48708256, 0.6870221 , 0.70988718, 0.15087814, 0.60748781,\n",
       "       0.61379877, 0.15939157, 0.1505337 , 0.65722657, 0.16763765,\n",
       "       0.46473996, 0.4604257 , 0.65146005, 0.67442964, 0.1870812 ,\n",
       "       0.58447424, 0.67872946, 0.60184654, 0.13821862, 0.57016683,\n",
       "       0.1941565 , 0.20278606, 0.14191104, 0.18607285, 0.63760128,\n",
       "       0.27383849, 0.16458384, 0.7239818 , 0.17301498, 0.53075009,\n",
       "       0.52381422, 0.72328113, 0.74555384, 0.14042912, 0.63632432,\n",
       "       0.64731503, 0.16551076, 0.46251394, 0.45269365, 0.64598541,\n",
       "       0.67554317, 0.16206654, 0.57560656, 0.61226566, 0.23625379,\n",
       "       0.23261522, 0.11574647, 0.12746792, 0.67597215, 0.27057896,\n",
       "       0.42292605, 0.41817166, 0.61529242, 0.63620353, 0.14537945,\n",
       "       0.52405485, 0.14356891, 0.23235045, 0.26114341, 0.49196203,\n",
       "       0.23448501, 0.23275788, 0.26747919, 0.47970472, 0.24113125,\n",
       "       0.13392114, 0.67925502, 0.27686039, 0.70135979, 0.31380153,\n",
       "       0.59058967])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.spatial.distance import squareform\n",
    "\n",
    "squareform(jsd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "s = '(A:0.1,B:0.2,(C:0.3,D:0.4):0.5);'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.count('(') == s.count(')') and s.count('(') >= 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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