{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#from collections import defaultdict\n",
    "\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from Bio.PopGen.GenePop import Controller as gpc\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "my_pops = [l.rstrip() for l in open('hapmap10_auto_noofs_2.pops')]\n",
    "num_pops = len(my_pops)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ctrl = gpc.GenePopController()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "(multi_fis, multi_fst, multi_fit), f_iter = ctrl.calc_fst_all('hapmap10_auto_noofs_2.gp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.0004, 0.1078, 0.1082)\n"
     ]
    }
   ],
   "source": [
    "print(multi_fis, multi_fst, multi_fit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fst_vals = []\n",
    "fis_vals = []\n",
    "fit_vals = []\n",
    "for f_case in f_iter:\n",
    "    name, fis, fst, fit, qinter, qintra = f_case\n",
    "    fst_vals.append(fst)\n",
    "    fis_vals.append(fis)\n",
    "    fit_vals.append(fit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.1, 0.4)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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CqkD6A7rOMxPHkuluwJ3vH7gRt7ETnbsEJw88zkIOhyM1HtbpxNlpXKzD4ew0\nFtXAMBzp51P7G0Z3esPYOBxOnI7U+ZzOY+tBc8TQaprmd4EvAvs6bZsKfLXT41LgW8AppBrDXzVN\n8wXgG8C7lmXdaprmZcANwFXHVKWIiIh0S3cDXKaCnmEYBAIBAoHAUSfjSCQS7N69m+3bt3fcPqj+\ngJ07a9hf3Qikgqx7SADv0BDuQQM7wGZjq2A21iTSzo4nUzMItyQ6Jl1qn3Ap2ZaAttSasYm2eJdj\nOg2HgdfnIxDwEwwGCQ8KEw6F8Pv9eDyegyY9OvSr0+nsmA34cLMId0yw1Gnm4M4TIHV+3D5xksvl\nOjABU6f7nR93nsm4cw0nSlVVVY+POVpL6ybgn4CHAEzTLAJ+RCp83pfe53RgpWVZMSBmmuYmYBIw\nC2j/aHYJcGOPq5MBJwrs3HJsbbUjRozQ4tAiMqANHz6cP/zhD5/Y/uqrrx70+LbbbjtRJR0Xp9NJ\naWkppaWlnHbaaR3bbdumvr6edevWdazR2rqlMbVG65AA3mHBAbdGKygYikCqW2wymjioZbQjiKaX\nt7HbkiRb4iTjn1zWxuF0EsoLUZBfRGFZEcVFgw5arzUSiRAOhzuWtvH5BvaHZSfKEUOrZVmLTNMc\nAWCapgP4DXAN0NpptzygodPjJlKTSOcBjYdsEzminQAXXtjj47YAWBaVlT3tzCwiIrnGMAwKCgqY\nM2cOc+bMobW1ldWrV7Ns+TJWr15Na3U6wJb68Q4L4S72649KOSZqKc4s27ZTXW6jSZLRRCqMpu/b\nsfS2tlRAtaPpJWqinxgtD4DL7SIcyaOwsJSSQcUUDyqmsLDwoFtBQQHBYFC/L7JQTyZiOgUYAywE\nfMB40zTvBF4Bwp32CwP1pAJr+JBtR3UszcXSM919j7du3crEPq7lcI5lHC3AunXraGpq6u1yJIvp\n94X0B/o+Pn4+n4/Zs2cze/ZsWltbqaqqYvmKFaxa9RYNW5twF/oITRmEK8+b6VIlxyis9j47nky3\nfKZbQKMHuuPaHWNGOwXQrrrlGgZev49IXpiC4nwKCwopLCgkPz+/o0U0Eol03FcYzW3dDq2WZa2C\nVIYxTbMC+INlWdekx7T+yDRNL6kwOw5YB6wELgZWARcBy7tznVNOOaVHL0B6pqqqqtvvcTgcPvpO\nWWTixIlqaR1AevK9LJKtcuH7ONdCtc/nY9asWcyaNYu2tjZWrFjBffffR90rOwmMjRAwCzCOcSKQ\nbKdWQcmfxVjDAAAgAElEQVQGdjxJojlOojlGMv010RzHbo6TbImTaDt8S6jX7yOcFyK/qIDCwgIK\n8wvJy8sjHA53fO18PxgMnvCxmJI53Q2th37GYbRvsyzrI9M07wZWAA7gOsuy2kzTXAg8YJrmCqAN\n+Hwv1SwiIiJyVF6vl3PPPZfTTjuN++6/j2VLlxGtaSY4eRCe4v63kKLCqpwotm2TbE2QaIoSb4yS\naIqSaEqH1Nb4Qfs6XU4KigoZUjGEYUOGMnjwYAoLCztaQPPz88nLy8Ptdmfo1UguOGpotSyrGph5\npG2WZd0P3H/IPi3AZ3ujSBEREZFjFYlEuPbb13LuOefy8wV3sXdlDb7yMMGJRVr7tY/lepAe6K3X\ntm2TbIkTb4qSaIylwum+WCqgxg60mPoCfkaUlVNRXsGQ0lJKSkooTX/Nz89Xi6gct56MaRURERHJ\nWVOmTOHXC+/lD3/4A4ueWETs4xYCJxfiHRbSWDc5rIESVm3bTi3t0nhwy2miKUoydmCG3UA4yIiy\nEYw6YxTl5eWUl5dTVlZGfn5+BquXgUChVURERAYMn8/HP//zPzNv3jzuvOtOqldX07ZtH6HJg3AG\nc7t74kBvFZTuScaSqW69DW2pgNqY7trbadZdf9DPqPIKRp8xmhEjRnSE07y8vAxWLgOZQquIiIgM\nOCNHjuSuO+/i6aef5ncPPED90p2Epw/GMyh3x7oqrEpntm2T2B8j0ZBqPY03Rkk2xojvj3bs4/F5\nKS8bzphTx1BRUUFFRQXl5eVqOZWso9AqIiIiA5LT6WT+/PlMnz6d6268nt2vf0T41BK8Q4KZLk2y\nRK60Xtu2TbI5TqyujXhdK/H6NuL1UexEqmuvYRgMKhnEmMljGD1qNCNHjmTEiBEUFxera7zkBIVW\nERERGdAGDx7MnT/5GTf84Aaq36omPLUEX3luLfsmfSNbw2qyrT2gtqUDahvJ9FIyTpeT8hEVTJg5\nntGjUt17y8rK8Hq1TrHkLoVWERERGfAikQh33HYHt/znrWx4ez3JaILAmNzqIpmNrYLZWFOusW2b\nRGOUWG0rsb2tJOraiO+PAakW1MFDS5kwZwJmZSWVlZVUVFTgculPfOlf9B0tIiIiAgQCAX54639y\n+x2389abb2FHkwTGFeRM90kFw/4hGUsSr2s9KKQm46luvsFwiMknT2PCuPFUVlYyevRo/P7cHYct\n0l0KrSIiIiJpbreb675/Hffccw8vvvgiyWiC0ORBORNcpXediJbiZCxBbE8rsd0txGtbiTW0AalW\n1CHDhjD5vMmMHz+ecePGUVJSou9FGZAUWkVEREQ6cTqdXHHFFYTz8nhi0SLsWJLwKSUYDoWFgaYv\nwqqdSBLbmwqpsd2txOpbwQaX20WlaTLlksmMGzeOyspKAoFAr19fJBcptIqIiIgcwjAMvvqVr5CX\nF+aB3z2AHUuQd3ophsuR6dK6pPGj2cm2beINUWK7monubiG+txU7YWM4DEaMGslp553KlClTOOmk\nk3C7c3utYJG+otAqIiIi0oVLP30peeE87rnnHhpe+5C8M0pxeJyZLuuwFFazh520idW20Fazn9hH\nLSRaUhMnDRk2hFMvToXUiRMnqiVVpJsUWkVERESO4PzzzyccDnP7HXfQsKKGvDNKcQbVItYduR6k\ne9J6bceTRHc10/bhfmIft5CMJnC6nEyZMpU5s2czbdo0CgoK+rpkkX5JoVVERETkKGbMmMGPf/Qj\nbrn1FhqW1xCePhh3oS/TZUkfO1pYTUYTRD/an2pR3d2KnUji8/uYM3MOs2bOZOrUqfh8+j4ROV4K\nrSIiIiLdMGHCBH5+58+5/sYb2LuyhvC0ErzDQpkuq4PGtJ4YyViS6If7adu5j9juFuykTV5BhPMu\nPIsZM2YwYcIErZMq0sv0EyUiIiLSTcOGDWPBz+/ipltuYvOqzQSb4/jHRLJiGRKF1b5jx5O0fdSc\nCqofN2MnbSIF+Vw8/3zmzJnD2LFjs+J7QKS/UmgVERER6YFIJMIdt93BT3/2U954/Q0SzTFCJw/S\nkjj9jJ1IUvfKDpLRBCRTwTWUF+b8iy9h3rx5VFZW4nBk72zSIv2JQquIiIhID3m9Xr7/ve/zuwd+\nxxOLniDZHCd86mAcboWYXGYnkkR3tXS0qCZjSQKhAHNnz2Xu3LmMHz8epzM7Z48W6c8UWkVERESO\ngcPh4Ktf+SpDSoewcOFCGlfWEJ5eitOfmT+vsnFMazbWdCg7YRPdne76+1ELyVgCX8DP2fPOZu7c\nuUyaNElBVSTDFFpFREREjsNFF11EcXExP779NhqW15B3xmBcEe8JryObg2G2sZN2anmazkHV7+Os\neWcyd04qqGoyJZHsoZ9GERERkeN06qmn8rOf/JQbfnAD9ctr8I+NEBiTj+FSd+Fs0dGiWrOf2EfN\nJKMJvH4fZ86Z19Gi6nZr/V2RbKTQKiIiItILRo4cyd133c3Cexfy5htv0rZ1H4FxBXjLQppZNkM6\nxqjWHGhR9fq8zJk5hzPnzWPy5MkKqiI5QKFVREREpJcUFRVxw/U3sH79ehb+eiFb395K65ZGAhMK\n8Qzy9+m1c2H86IlgJ5JEP04H1fRkSr50i+qcOXMUVEVykEKriIiISC+bMGECd991N0uXLuU3v/0N\nDa/W4BkaJDShCGewbwLTQA6rtm0T291C67amVNffeBJfwM9Z885izuw56vorkuMUWkVERET6gMPh\n4Oyzz2bmzJksemIRjz76GHUvbcc3KkLAzMfh7v8z0vZ1kE7sj9G6rYm27ftINMfw+X2cc9Y5zJ49\nW5MpifQj+kkWERER6UM+n4/Pf+7zXHD+BTzwwAO88sortG3fh39MBF9FGIen/4fX3mQnkrR9uJ+2\nrU1Ed7cAMHHSRC6+8GKmT5+Ox+PJcIUi0tsUWkVEREROgKKiIq655hrmz5/Pf9//37y//n2arTq8\nZSH8oyO4QscXtvrzmFbbtok3RGnd2kh0536S0QT5RQVc+vl/5JxzzqGkpCTTJYpIH1JoFRERETmB\nxowZw3/d/l9s3ryZxU8uZvny5bRuacQzOIB/TAT3IP8xzTbcX8NqtGY/LZsaiNW14nQ5mTljBhde\ncCEnn3wyDoeWFBIZCBRaRURERDJg9OjRfPuab/PVr3yVp595mj//5c80rPwQV54X36g8fGUhDOfA\nDGV2PEnrtiZaP2gkvi9KUXERl/7blznzzDMJhUKZLk9ETjCFVhEREZEMKigo4Itf+CKf/cxnWb58\nOY8+/hg17+yk5f06vBUhfBV5fTbjcLZJtiVo+aCBtuomEm1xRo4eyWXfvIwzzjgDp1Njf0UGKoVW\nERERkSzg8Xg499xzOeecc1i7di2PP7GIt1dX0byxHk+xH29FGO+QYJetr9k4prW7NSX2xWjeXE/b\ntibshM3UU6Zx2Wc+y/jx44+pq7SI9C8KrSIiIiJZxDAMJk2axKRJk9i1axcvvfQSzyx5lvrVu9jv\nduIZHsRXkYc733vQcdkUVrvDtm1iu1po2dpItGY/DqeDs848i0s/fSllZWWZLk9EsohCq4iIiEiW\nKikp4XOf+xyXXXYZ7733HkueW8Ibb7xB65ZG3PlevOVhvMNDObVsTmJfjNZtjbRt30+iJbW26qc/\n/Wnmz59PYWFhpssTkSyk0CoiIiKS5RwOB1OmTGHKlCk0NTWxfPly/vLM0+x4bzv719XiLvbjLvLh\nLvLhyvdhOLOrS60dT9K2cx+t2/YRq23BMAxOnjyJiy64kOnTp+N2D4wxuyJybBRaRURERHJIOBzm\nkksu4ZJLLmHz5s288OKLvLX6LXZv2AWA4TBwFXjTIdaPq9CLw33iW2Jt2yYZS5JsS1C7ZCt2PMmg\nkkFcdPmlnHPOORQVFZ3wmkQkNym0ioiIiOSo0aNHM3r0aL7+b/9GQ0MDGzZsYP369bzz3jts27SN\n5o31YIA74sVZ4MUZcOPwO3H4XDj9Lhw+13G3ytq2TbI1QaIpSrwxSqIpSqIpRqIpRjKWwDAMzj7n\nbM4/73zGjRuniZVEpMcUWkVERET6gUgkwowZM5gxYwYAra2tWJbFhg0bWPPuO2zetInWtsZPHOf0\nuXD4nBg+Jw6/C8PlwDAAw4D0146c2b7Ntknsix0UTtv5An5GlJUzZvpoTjrpJGbOnInP5+vz1y8i\n/ZdCq4iIiEg/5PP5mDx5MpMnT+Zzn/scAM3NzezZs4c9e/awd+/ejvsf7fqIXbt3UfdxHW1tUeyk\njW3bRz5/p3BaXl7ecYtEImpNFZFepdAqIiIiMkAEAoGOcHk0tp0Krslk8hM3wzAIBAIKpyJyQii0\nioiIiMgnGIaBYRg4HI5MlyIiA5x+C4mIiIiIiEjWUmgVERERERGRrKXQKiIiIiIiIllLoVVERERE\nRESylkKriIiIiIiIZC2FVhEREREREclaCq0iIiIiIiKStRRaRUREREREJGsptIqIiIiIiEjWUmgV\nERERERGRrKXQKiIiIiIiIllLoVVERERERESylkKriIiIiIiIZC2FVhEREREREclaCq0iIiIiIiKS\ntRRaRUREREREJGu5jraDaZrTgdstyzrLNM0pwN1AAmgDvmRZ1i7TNL8G/CsQB35oWdbTpmn6gf8F\nioEm4MuWZe3pqxciIiIiIiIi/c8RW1pN0/wucB/gTW+6C/imZVlnAYuA/zBNczDwLWAmcAFwm2ma\nHuAbwLuWZc0FHgRu6JuXICIiIiIiIv3V0boHbwL+CTDSj/+PZVnvpe+7gRbgdGClZVkxy7Ia08dM\nAmYBS9L7LgHO7c3CRUREREREpP87Yvdgy7IWmaY5otPjjwBM05wJ/DswB7gQaOh0WBMQAfKAxkO2\niYiIiPR7LS0tvP/++6xfv56CggLmzp1LXl5epssSEclJRx3TeijTNC8DrgMutiyr1jTNRiDcaZcw\nUE8qsIYP2XZUVVVVPS1Jeqi77/HWrVuZ2Me19KZ169bR1NSU6TLkBNLvC+kP9H3cPzQ3N7NhwwbW\nrVvH6rffYVv1Fmw7Saqzms1999/P6aedzoUXXsCUKVNwOp2ZLllEJGf0KLSapvlFUhMunWlZVl16\n81vAj0zT9AI+YBywDlgJXAysAi4ClnfnGqecckpPSpIeqqqq6vZ7HA6Hj75TFpk4cSKVlZWZLkNO\nkJ58L4tkq1z4PlaoPrz2kLp27Vqq3n6HbVurUyHVcODyF+IpMnEGimndvQHsBK7AIN5a/TZvvPE6\n4bx8Ljj/XM477zyGDh2a6ZciIpL1uhtabdM0HcACYCuwyDRNgKWWZd1imubdwApSY2SvsyyrzTTN\nhcADpmmuIDXT8Od7v3wRERGRE6ehoYEFC+5m9epV2LZ9UEh1BYpxBoowHAf+vGrb8z4YLvylU7AH\nTyLeVENLfTWPPfY4jz32GGPGVnLJxRcxa9Ys/H5/Bl+ZiEj2OmpotSyrmtTMwABFXexzP3D/Idta\ngM8eZ30iIiIiWeG9997j9tv/i3379uEprMQVKsXpLzwopB6JYThw5w3HnTecZKyFWMNWtmyrZsGC\nBfzqVwuZPXs2n/nMpZSVlfXxKxERyS09HtMqko2iwM4tW475+BEjRuDxeHqvIBER6TcSiQS///3v\n+dOf/oTTGyY48mycvvzjOqfD7cc76CQ8RSaJllqi9dUsXb6cFStW8LWv/QsXXXQRhmEc/UQiIgOA\nQqv0CzsBLrzwmI7dAmBZGg8rIiKfsGvXLm67/Q42/W0j7vwR+EundrtltTsMw8AVGIQrMIhkbAIt\nNatYuHAhb61azdVXXUkkosUXREQUWqXfGAkodoqISG95/fXXufPOu4jGYviHTccTKe/T6zncfgLl\nc4ju/RtvV1Xx9W/8O//x3WuZMmVKn15XRCTbKbSKiIiIdBKNRrnvvvtZsuRZXP5CAiPn4fSEjulc\noRFn9mh/wzDwFlXiCpbQsvNNbrzxRj71qX/kS1+6HLfbfUw1iIjkOkemCxARERHJFtu3b+dbV1zF\nkiXP4imsJDDirGMOrMfD6csnOPIcPAWjWLz4Ca686hp27NhxwusQEckGCq0iIiIy4Nm2zfPPP88V\nV17JRx/vJlA2G3/pZAwjc38qGQ4X/iGnEBg+k501NXzriit47rnnUkvtiIgMIOoeLCIiIgNaNBpl\nwYK7Wb58Ga5gCcGhp+NwZ8+aqe68YTj9hbTUvMU999zDm2+t4uqrriQcDme6NBGRE0ItrSIiIjJg\n1dbW8u1rv8Py5cvwFk8gUD43qwJru9QkTXPxlUxi9apVfP0b/4/3338/02WJiJwQCq0iIiIyIG3c\nuJFvfetKtm7dRmD4THzF47N6bVTDMIjt+xDDm8f+1jjf//51LFu2LNNliYj0OXUPFhERkQFn6dKl\n3HXXAnB6CY44G6cvtR7qvuqlQM9n/e1Kb5+v/TzJeBstO17jpz/9KTt37uRzn/tcVgduEZHjodAq\nIiIiA0YikeCBBx/kiUWLcAWK8Q+fgcPl7Xi+t8JlX3O4vATK59LyYRWPPPIIO3bWcPVVV2pZHBHp\nlxRaRUREZEBobm7mttvv4J01b+MpGIWvdGpGZwc+XobDiX/oaTg8YVYsX8ZHH33ETT+4kUgkkunS\nRER6Ve7+phYRERHpppqaGq648mreeWcNvtJp+IeckpOBdV/10o4ux5Aa5+orHod/2HQ2/W0TV151\ntdZzFZF+J/d+W4uIiIj0wLvvvsuVV13N7j21BMvn4i0c3eW+h4bCbBMaceZhuzB7IuUEKuZRV9/E\n1dd8m7Vr15744kRE+ohCq4iIiPRLtm3z5z//mRtv/AFx201wxNm4giVHPKarUJgLXIEigiPOJma7\nuP6GG3jhhRcyXZKISK/QmFYRERHpdxKJBAsX3stzzy3BFR5KYOjpGM4TP0nRiQ7ADk+QYMVZNO94\ng7vvvpudO2v40pcux+FQO4WI5C6FVhEREelXWlpa+PFtt/POmrfxFpl4S07uN8vBdGcJHcPpIVA+\nm9YP1/D444+xY+cOvnPttXi93i6PERHJZvrYTURERPqNuro6rv3Od3lnzRp8Q6bhGzypR4E1V8e0\nHsowHB2v/8033uDb136XvXv39n2BIiJ9QKFVRERE+oXt27dzxZVXs337DgJls/AWdD3hUldyeUzr\noQzDwFtkEiibybZt2/jWFVexefPmTJclItJjCq0iIiKS89atW8fV13ybxn37CVaciTs8JNMlZQ13\neBjBEWexv6WNa7/zHV5//fVMlyQi0iMKrSIiIpLTli1bxvU33JCaIbjibJz+gkyX1GeOtfuy05dP\nYMQ54Arz4x//mEcffQzbtnu/QBGRPqCJmERERCQn2bbNY489zoMPPoArWExg+EwMp+e4ztmdiY4y\neb7jOY/D5SNQcSYtNat48MEH2LptG1de8S3c7hM/q7KISE8otIqIiEjOSSQS/GrhvTz/3BLceWX4\nh56G4XAe93n7y3jWrhgOJ/5h03F4wyxb+go1NTXc9IMbiUQimS5NRKRL6h4sIiIiOaWlpYWbb7mV\n559bgrfoJPzDpvdKYB0oDMPAVzwB/7DpbNq0iSuuuIqtW7dmuiwRkS4ptIqIiEjOqK2tPbCkTek0\nfIP7zxqs3dGbS/J4IuUEyudR37SPa759LVVVVb1yXhGR3qbQKiIiIlnPtm1efvll/u3r30gvaTMT\nb2HPl7Q5mv6yTmt3uQJFBEecQ8Lwccstt/DUU09pgiYRyToa0yoiIiJZbe/evdy14G7WvF2FKzCI\n4KjTcHpCfXKt/j6m9XAc7gDBEWfRvPNN7rvvPl56eSn/8n+/wsknn5zp0kREAIVWERERyVK2bbNs\n2TJ++auFtLW14Rs8GU/h2JzqDpwrIdhwuAgMn0msfgvV2zZw3XXXMfHkSfzfr36FMWPGZLo8ERng\nFFpFREQk69TV1bHg7l9QtXpVqgvryLk4veFMl5Vxvb2ETmeGYeApGIU7UkG0bhMb3re4+uqrOX36\nGfzzl79EWVlZr19TRKQ7FFpFREQka9i2zfLly7nnl7+irbUN3+BJeAorT1jral+Gwt5wIuoyHE68\nRSae/FG01W5k1erVrHrrTc486yy++IUvUFJS0uc1iIh0ptAqIiIiWaG+vp67f3EPq956E1egkOCo\nOTi9eSe0hmwNq5lgON34SibgKRxD2573WfrKMpYtW8bFF13MZZd9lvz8/EyXKCIDhEKriIiIZJRt\n26xcuZK7f3EPrS2t+EpOxlNk5tTY1f7M4fLiL52Ct6iS1t0b+Mtf/sJzzz3Hpz71Kf7u7y6hsLAw\n0yWKSD+n0CoiIiIZEYvFWLFiBY89/gTbt1Xj8hcSHDX7hLeu5pJMdl92uAMEhp5Kosikbfc6Hn30\nTzz2+GOcdtrp/P3fXcKkSZNwOLSaooj0PoVWEREROaFqa2t55pln+MvTz9C8fx9OXx6+IdPw5I/E\nMDIbeno7FPb2+bKh+7LTGyYwfAaJ6D6idR+wumoNb735BkXFJcz/u0s499xzycvTBw8i0nsUWkVE\nRKTP2bbNX//6VxY/+SSvv/46djKJKzSUYPk0nMGSrOkKnA2hMFc4PSH8gydhF08g1rSDhroP+O1v\nf8uDDz7EzFmz+LtLLmbcuHFZ8/9WRHKXQquIiIj0mUO7ADucbtz5Y/AWjsbhCWW6POkFhsOJJ1KB\nJ1JBorWBaN0HrFz5GiuWL6N0yDA+9Q9/z5lnnkkwGMx0qSKSoxRaRUREpFclEgk2bdrEm2++xdPP\ndOoCXDoNT34FhkN/fhyrbF+Sx+mL4B8yFXvwycQatrG7/gPuvfde/vu/72PkqFFMmzqFiRMnMm7c\nOPx+f6bLFZEcoX81RERE5Lgkk0mqq6t57733qKpaw/oN64lF2wCysgvwkWR7KMzWug5lOFx4Ckbh\nKRhFvGUvscYdbN25m82bH+PRRx/FMByUV4xg2tTJnHzyyYwfP14tsSLSJYVWERGRfmLHjh3Mnz+f\nCRMmdGw744wzeOSRR3j11VdpbW3l5ptvZvfu3bS0tDBo0CBuvfXWHq+3ads227dvZ+3atbz99hre\nW7uW1pZmIDVJjzM4DH9xCa5gMQ6Xr1dfY1/LlVCYS1z+Qlz+1LI4djJOvLmWRPNudu7azbbFT/LE\nE09gGAZDh5UxbepkKisrKSwsJD8/n/z8fMLhcE584CEifUehVUREpB8ZO3YsDz300EHbHnnkEQAe\nf/xxiouLuf322wF44IEH+OUvf8n1119/xHO++OKL1NXVUV9fz8e7drNu3Tr272sCwOkJ4AiU4C8o\nwRUsweFWl8/OFIIPZjhcuEODcYcGA2AnEyRaaok37+bjut385elnsP/850OOcRAIhohE8ikqLGBQ\nUWFHqI1EIoRCIcLhMKFQqOPmculPXJH+RD/RIiIiA0RxcTGPP/4406ZN47TTTuPyyy/Htu2jHrdg\nwQIADKcLh8uPw1uAf4iJK1iM4Q6qFewEyvbuyz1lOJy4gqkPPCAVYpOx/djxVpLxVux4G3a8lWii\nlV31rXxcuw3++jcSsVawk12e1+3x4vcHCIVC5OXlkZcXJhgI4Ha7cLvduFyujlv7Y6fTedD9Q78e\nbpvL5cIwjIN+Brp63H5zOBxd3tqfdzqd2LZNMpnEtu2D7h+6rf0aRztn+32RXKTQKiIi0o9s2rSJ\nyy+/HEj9IfuTn/yk47nzzz8fwzB47LHH+N73vkdlZSU33ngjlZWVRzxneMzFGC7vgJhAKdtDYbbW\n1VsMhxOnNw+8R17n1bZtSMZIxtuwE9HULRk7cD8RpSXexv76Nj6u3QnJGHYyAXYS204CduprNz60\nEZHedfPNN/f4mP7/r4+IiMgAMmbMmE90D263Zs0aZsyYwXnnnYdt2yxevJjvfe97LFq06IjnjNZ9\nkAqtLh8Olw+nrwDD6e6L8jOuv4fCXGXbyY5W12Qi9TV1P3pQUCXZfj+GnYwfxxUNDIcDh8PAMBzp\nVtL0Y4cDh9F5O59owTQADAPs9gdgYICR2gzpltf0zh33DxxN+ynbc7Xd/t/2x7adumvb6esbHccY\nRvpaHafsfP7DvFrDwP7/7d15mGVlfSfwb/VS1Vs1dCOrgtXE1BHSLNJN0AbaJSyFEcEJOijuKJNI\nTMZoApKAMy4BR5HFKFEYQ2IS9dEkziijcUQUJEzAEoGWeBCtbqAVZeumq7fa7vxR1f000NRyu6ru\nqarP53n6oe65573nV4e3btX3vu95z87XyVO+Ho3RzNh4+vGe3n6kbTuOsaPWp3+962vvuu3p+9dz\nTBpPaAWAGeKGG27IkiVLcv7556epqSnt7e1paWkZsV3PE/elNrDLVMympsyZvySz5++X2Qv3y5wF\n+8yIUVgmTq1Wy0Dv5vRveST92zYOTQ/enqaB7RkY+np3Zs+ek3nzF2ThwoVZvHhpFi9uzd57Lc7i\nxYt3Xt+643rXlpaWzJ079xnTg3dMEd4x3XfHlF9gYnR2do65jd8wADCNDPfH9nve85586EMfypln\nnpn58+dnwYIF+chHPjLia371X/4l3d3d2bBhQx599NH8+Mc/zg8670xX132pPfaTpGlW5szfJ7MX\n7Js5C/fL7PlL0zRr9nh+Wwyp+vTl0arVahno2ZS+LY+kf/MjGdj6WPp7B1egnjO3Oa2ti7Nk372z\nz9Kl2WefpVmyZMnO1YR3/FuyZIl7vcIMIbQCwDTxvOc9L1/84hefsf373/9+kmThwoU7Vw4ei1mz\nZg0tZrM4hxxySI455pi86U1vytatW3Pvvffmrrvuyg8678yDD/xHtj967+B1ifP3yeyF+6d5r+dP\nqRWFxzsUjvfrTdWwWqvVMrB9Y/q2PJq+zY9kYOujGejbliRZ1Lo4R/72i3LUkUdm+fLlOfjgg410\nAk8htDLj9SRZ39VVV9u2trY0NzePb0EAU8T8+fOzYsWKrFixIm9/e9Ld3Z01a9bk7rvvzh0/+GEe\n/qqoQzgAACAASURBVOU92f7ImsxtfW6al/5mZs/fp/JhZKqGwqrq3/pEep74efq61++c4rt4ryU5\n+vjjcuQRR+SII47IgQceWPl+ATSW0MqMtz5JOjrG3K4rScpyxFU3AWaKRYsW5cUvfnFe/OIX57zz\nkocffjg33HBDvvHNf83mtQ9l9vwlaV7ygsxdfLDpw9NYbaAvvU8+mN4nfp6+rY9nzpy5OX7Vqqw4\n5kVZvnx59t9//0aXCEwxQiskWZZE9AQYXwcccEDOPffcnHPOObnpppvyT//81fzqF3dk+6/vzty9\nD03zkt+YUlOHq6DK17T2b39ycFR147oM9Pdkv/0PzBlvfGde8YpXZNGiRY0uD5jChFYAYELNmzcv\np512Wjo6OnL33XfnX/7lf6Wz8wfZ/thPKjd1uMqhMKleXbWB/vRuWj84qrrlkcyaNTsveclL8qpX\n/W5+67d+qxL/T4GpT2gFACZFU1NTjjrqqBx11FHPmDo8Z/6StOz/osxZsE9Da6xaKKyqgd6t6Xn8\n/vRu7MpA3/YsWfqcvPq1b8lJJ52Uvffeu9HlAdOM0AoATLqnTx3++3/4Qp5ce1Na9inSsu/h0+aa\n1+kWgmv9Pdn+aJmeJ36a1AayYuXKnP6qV+Xoo4/OrFmzGl0eME0JrQBAw+yYOrx69epce+11ufHG\nb6dv8y8z78CVmTN/aaPLq5xGTV+uDfRl+2M/Te/jZQb6e3PCiavzpjeek4MOOmhS6wBmJqEVAGi4\nhQsX5r/+1z/OCSccnyuuuCpPrv1OWvZ5YVqec9ikjrq6pvWpagP96dnw8/Q89pMM9G7Li45Zkbe9\n9S1ZtmzZpNYBzGxCKwBQGStXrsxnPnNNPvPZz+a7N92Uvu5fZP6Bx2b2/CWTcvyqhtXJVqvV0rtx\nXXoevTf9PZtTFIfl3HPflsMOO6zRpQEz0IihtSiK45JcVpbly4uieEGS65MMJFmT5PyyLGtFUbwz\nyXlJ+pJ8uCzLG4qimJ/k75Psm2RTkreUZfnoBH0fAMA0sWjRorz3T/4kq088MZ+44qp0r70xLfsc\nlpZ9D0tTk+smJ1KtVkvfpvXZ/uiP07/tyRx8yPPzjnP/LC960YusBAw0zLDv/EVR/FmSa5O0DG36\nRJKLyrJcnaQpyRlFURyQ5N1JViU5NcmlRVE0J/mDJHcN7ft3Sf5iYr4FAGA6OvbYY3PtZ/86q09c\nne2P3pvNXTemf9uGRpfVUN1rv7tzCvN469/+ZLas/U62PHRbli5ekAsvvDCf+qtP5phjjhFYgYYa\naaT1/iT/Kcnnhx4fU5blzUNffyPJKUn6k9xalmVvkt6iKO5PcmSS45N8dGjfbya5eDwLBwCmv0WL\nFuVP//R9Wb36xFx51dXp7vp2Wp5z+OC1rhMQpMb7mtbxfr2Jmr7c1/2rbF1/W+bNa8m7/uiP8opX\nvCKzZ0+PFZyBqW/YkdayLP85g1N+d9j1t8OmJHslWZxk47Nsf/Jp2wAAxuy4447LZ/76mhx//AnZ\n/siPs+Wh/5faQP+4H2dR28tm3HWt2x//WTY/eEv233+/XH3VlTn55JMFVqBSxroQ08AuXy9OsiGD\nwbR1l+2tu9m+Y9uIOjs7x1gSYzXac7xu3bosn+Bapro1a9Zk06ZNjS5jxvJ+wXSgH4/e4sWLc8Gf\n/Wm+2v6b+dznPpctD2zL/Oetyqw5LSM35hlqtYFs+9Vd6Xn8/hz9omPy/gsvyIIFCxpdFsAzjDW0\n3lkUxUvLsvxektOS3Jjk9iQfKYqiJcm8JIdlcJGmW5O8MskdQ/vevPuXfKoVK1aMsSTGorOzc9Tn\nuLW1deSdZrjly5envb290WXMSGPpy1BVU6EfVy1UNzU15TWveU323XfffPzjl2fLupsy/+ATMrt5\nUaNLmxTjNd241t+bLetvS1/3r3L66a/Ouee+3egqUFmjDa21of++N8m1Qwst3ZvkK0OrB1+d5JYM\nTje+qCzL7UVRXJPkb4uiuCXJ9iRvGOfaAYAZ6oQTTsjSpUvzgf/237Nl7U2Z/7xVmbNgnz1+3Zlw\nn9aBnu5seejWDPR05/zzz09HR8eeFwYwgUYMrWVZrs3gysApy/KnSV62m32uS3Ld07ZtTfK68SgS\nAODpDj/88Fx5xSdy0Z9fnCce+F7mP/e4zG197h69ZlXD6njp2/xItq6/Lc1zZ+fiD30oRx55ZKNL\nAhiRm50BAFPWc5/73Fx15Sfy/Oe3ZcuD/5btj9/f6JKeokoLO/VsWJstD9ycfZbunauuvEJgBaYM\noRUAmNL23nvvfOx/XJYVK4/NtofvzNaH70qtVhu54RRUz31aa7Vatv3q7mz9xR057PDDc/VVV+ag\ngw6amAIBJoDQCgBMefPmzcvFf/HnOe2Vr0zP4/dl6/r6bolTTyicTGMdua0N9GXLQ/+W7Y+VOeXU\njnzkwx/KokUzY9EqYPoY6+rBAACVNHv27PzB7/9+DjzggHzuc59LrW/st8SpylTe8TDQuzVbH7o1\n/ds25B3veEde/epXp6mpqdFlAYyZkVYAYNrYcUucCy64ILXtG7Jl3U3p3z7z7qfdv21Dtqz9Tpr6\nt+Tiiy/OGWecIbACU5bQCgBMOyeccEL+8i8/kpY5tWxZe2N6ux9udEnjYjTTl3s3/SKb196UhQta\ncvnHP5Zjjz12cooDmCBCKwAwLR1++OH55NVX5cADD8yWB76f7Y+VIy7QNN7XtI736w13TWutVsv2\nx36aLQ/+Ww4++Hn55NVXZtmyZeN2bIBGEVoBgGlrv/32y5VXXJ7fPu64nSvoDrdAU5VuUTMWtdpA\ntj18Z7b96kc59thjc/nHP5alS5c2uiyAcSG0AgDT2rx58/LnF70/r3/969O7cV22PPC9DPRubXRZ\n46bW35stD96anid+ljPPfE3+4i/+PPPmzWt0WQDjRmgFAKa9WbNm5Q1veEMuvPDCpPfJbFn7nfRt\nfbzRZY3Z06cbD/RsHlxsavOvc/755+fcc9+eWbP8eQdML255AwDMGMcff3wOOuigXPKB/5aN676b\neQeuTPNeh+x8fkcgrOoU4V3r6tv6eLY+dGvmzko+8MH/nqOPPrpxhQFMIB/FAQAzyrJly/LJq6/K\nC17wgmxd/+/Z9ut7di7QNFWuae198qFsWffd7N26KFdc8QmBFZjWhFYAYMbZe++989HLLs1JJ52U\n7Y/+JFse/LfU+nvH/TjjHYJrA/3Z+vCd2fLQbTl02aG56qorcvDBB4/b6wNUkenBAMCMNHfu3PzR\nH/1RDj300Fx77XXZvO47mX/QizN73l6NLm23+rdtTHfXjUmtP7/7u6/K29/+tjQ3Nze6LIAJJ7QC\nADNWU1NTTj/99BxyyCG59LKPpvvn30rT3EVpfUFHmpqaGl1eksH7r/Y88bNs//XdWbhgQd73vj/J\nypUrG10WwKQxPRgAmPGOOuqoXPPpT+WII45Krbc7Wx66LbX+nkaXlYG+7dny4K3Z9vCdOfKII3LN\nNZ8SWIEZR2gFAEiyZMmSfPjDH8xb3/q29G/+ZTZ3fTt9Wx5tWD293Q9nc9f/TW3rIznvvPPyoQ99\nMEuWLGlYPQCNIrQCAAyZNWtWfu/3/lM+/rGPZa/W+dm87rvZ9sh/7FxdeDIMLrb0o2x54Jbs95yl\nufLKK3L66adXZroywGQTWgEAnqa9vT2f/tRf5SUveUm2P7ImWx64OQO9W8f8Ot1rv7vz3q+j0b/9\nyWxe+530PP7TnPbKV+avPnlV2traxnxcgOlEaAUA2I2FCxfm/RdemD/8wz9Mtj+RzV3/N72bfjkh\nx6r192b7Y/dlc9e30zyrNxdffHHe9Qd/kJaWlgk5HsBUYvVgAIBn0dTUlFNPPTWHH354PvyRS/OL\nB7+f5qXtmbf/EWlq2rPP/mu1Wvq3PJqeDWvTt+mh1Ab6csQRR+VP//S9rl0F2IXQCgAwgoMPPjhX\nX3VFrrvuf+ab3/xG+jY9kNnz983sBftmzsJ9M6u5ddTXnA70bknPhnXpe3Jt+rd3Z25zS37nFS/P\nKaecnBe+8IWuXQV4GqEVAGAUWlpacv7578pxx/12brzxO/nRXXen++EHkySz5s7L7PnPyewF++02\nxNYG+tO76Rfp3diVvu5fJ6mleOFheeVpHVm1alXmzZvXoO8KoPqEVgCAMVi5cmVWrlyZWq2WX/7y\nl7nnnnty191350c/uiubHn4oSTJrzrzMXvCcwcWban3p/unXM9Dfk8V7LUnH616Xk08+KQcccECD\nvxOAqUFoBQCoQ1NTUw466KAcdNBBOfXUU1Or1fLwww/vDLF33nlXNvV2Z/bsOXnxS16SU085OUce\neWRmz57d6NIBphShFQBgHDQ1NeXAAw/MgQcemFNOOSW1Wi2PPPJIFixYkEWLFjW6PIApS2gFAJgA\nTU1N2W+//RpdBsCU5z6tAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAA\nVJbQCgAAQGUJrQAAAFTWnEYXAABUW2dnZ6NLAGAGE1oBgGe1YsWKRpfAFNDZ2amvMC3oyxOvng9C\nTQ8GAACgsoRWAAAAKktoBQAAoLKEVgAAACpLaAUAAKCyhFYAYKdt27bl3e9+d84555ycd955efzx\nx3e73+OPP55TTz01PT09k1xhdQ0MDOSSSy7J2WefnTe96U154IEHnvL8d77znZx11lk5++yz8+Uv\nf7lBVVbbSOcwSbZu3Zqzzz47P//5zxtQYfWNdA6//vWv53Wve11e//rX5wMf+EBqtVqDKq2ukc7h\nv/7rv+ass87Ka1/72vzd3/1dg6qsttH8LCdJURSfLYri0pFeT2gFAHb6whe+kKIo8g//8A8588wz\nc8011zxjn1tuuSVvf/vb89hjjzWgwur69re/nd7e3nzxi1/M+973vlx22WU7n+vt7c1ll12Wv/mb\nv8nnP//5fOlLX3L+dmO4c5gk99xzT84555w89NBDaWpqalCV1TbcOdy2bVuuuuqqfP7zn88XvvCF\ndHd356abbmpgtdU03Dns7+/PJz7xiVx//fX50pe+lH/8x3/Mhg0bGlhtNY30s5wkRVH8lyTLk4z4\nyYnQCgDs9MMf/jCrV69Okpx44om57bbbnrHP7Nmzc/3112fx4sWTXV6l/fCHP8yJJ56YJDnqqKOy\nZs2anc/97Gc/yyGHHJLW1tbMnTs3K1asyB133NGoUitruHOYDIb/T3/601m2bFkjypsShjuHLS0t\n+dKXvpSWlpYkSV9fX+bNm9eQOqtsuHM4e/bsfOMb38iiRYvy+OOPZ2BgIHPnzm1UqZU10s9yURSr\nkvx2ks8kGfETqDkTUCMAMAV8+ctffsbUtn322ScLFy5MkixcuDCbNm16RrtVq1ZNSn1TTXd3dxYt\nWrTz8ezZszMwMJBZs2alu7s7ra2tO597tnM70w13DpPkmGOOaVRpU8Zw57CpqSlLly5Nknz+85/P\n1q1b/Tzvxkj9cNasWfnWt76VD37wg3n5y1+e+fPnN6rUyhruHD7xxBNJckmS1yT5z6N5PSOtADBD\nvfa1r83Xvva1p/xrbW3N5s2bkySbN282mjoGixYt2nnukjzlj9xdz2syeG732muvSa+x6oY7h4zO\nSOdwYGAgH/3oR3Pbbbflk5/8ZCNKrLzR9MNTTjklt9xyS3p6evLVr351skusvOHO4e23354kz0ny\nf5JckOQNRVG8ebjX8y4AAOx0zDHH5Oabb06S3HzzzVm5cmWDK5o6dj13P/rRj1IUxc7nDj300Kxb\nty4bN25MT09P7rjjjhx99NGNKrWyhjuHjM5I5/CSSy5JT09PPvWpT+2cJsxTDXcOu7u788Y3vjE9\nPT1pamrK/PnzfbCyG8Odw1NPPTVlWa4sy/LlSS5L8o9lWQ67opXpwQDATq9//etzwQUX5A1veEOa\nm5tz+eWXJ0muv/76HHLIIXnFK16xc18L4TzVySefnFtvvTVnn312kuTSSy/N17/+9WzZsiWve93r\ncuGFF+bcc8/NwMBAzjrrrOy3334Nrrh6RjqHjGy4c7h8+fL80z/9U1auXJk3v3lwYOstb3lLTjrp\npEaWXDkj9cNXv/rVeeMb35g5c+bkhS98Yc4444wGV1w9w53D3/iN33j67iMuxNRUpWWuOzs7aytW\nrGh0GdNaZ2dnRnuO77vvvqQo0j7GY/xrkmXJmNvtSdtGHPO+JCnLtLfXc1T21Fj6MlSVfsx0oS8z\nXejLE2/oHI/pU09j2QAAAFSW0AoAAEBlCa0AAABUltAKAABAZY159eCiKGYluS6D69YMJHlnkv4k\n1w89XpPk/LIsa0VRvDPJeUn6kny4LMsbxqluAAAAZoB6RlpPSbKwLMsTknwwyV8muTzJRWVZrk7S\nlOSMoigOSPLuJKuSnJrk0qIomsenbAAAAGaCeu7TujXJXkVRNCXZK0lPkuPKsrx56PlvZDDY9ie5\ntSzL3iS9RVHcn+TIJD/Y87IBAACYCeoJrbcmmZfkJ0n2SXJ6ktW7PL8pg2F2cZKNu9kOAAAAo1JP\naP2zDI6g/nlRFM9LclOSubs8vzjJhiRPJmndZXtrkidGevHOzs46SmIsRnuO161bl+UTXMtUt2bN\nmmzatKnRZcxY3i+YDvRjpgt9melCX66eekLrwgwG0mQwhM5JcmdRFC8ty/J7SU5LcmOS25N8pCiK\nlgyOzB6WwUWahrVixYo6SmK0Ojs7R32OW1tbR95phlu+fHna29sbXcaMNJa+DFWlHzNd6MtMF/ry\nxKvnQ4F6QuvHkvxNURS3ZHCE9f1JOpNcO7TQ0r1JvjK0evDVSW7J4IJPF5Vl2VPH8QAAAJihxhxa\ny7LckOQ1u3nqZbvZ97oM3h4Hpp2eJOu7uupu39bWluZmC2oDAMBw6hlpBZKsT5KOjrradiVJWZpa\nDAAAIxBaYQ8sSyJ2AgDAxJnV6AIAAADg2QitAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABU\nltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAA\nQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0A\nAABUltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQ\nCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZc1pdAFMvP+4665s7e5OkpQ/+Umatm0bVbt1\nDz6Y35rIwgAAAEYgtM4APzzvvLzs9tuTJPuPod23nvMcoRUAAGgooXUGWDxnTp5bR7u9Z5k9DgAA\nNJZUAgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZVk9GBqgJ8n6rq662ra1taW5uXl8CwIA\ngIoSWqEB1idJR8eY23UlSVmmvb19nCsCAIBqElqhQZYlET0BAGB4rmkFAACgsoRWAAAAKktoBQAA\noLKEVgAAACpLaAUAAKCy6lo9uCiK9yc5PcncJH+V5NYk1ycZSLImyfllWdaKonhnkvOS9CX5cFmW\nN4xH0QAAAMwMYx5pLYriZUleUpblqiQvS3JoksuTXFSW5eokTUnOKIrigCTvTrIqyalJLi2Konmc\n6gYAAGAGqGd68ClJ7imK4qtJvpbkfydZUZblzUPPfyPJSUmOTXJrWZa9ZVk+meT+JEeOQ80AAADM\nEPVMD943ycFJXpXBUdavZXB0dYdNSfZKsjjJxt1sH1ZnZ2cdJTGc7u7uutr19PWNcyWMhzVr1mTT\npk2NLqMSvF8wHejHTBf6MtOFvlw99YTWR5P8R1mWfUnuK4piW5Ln7vL84iQbkjyZpHWX7a1Jnhjp\nxVesWFFHSQznF4sW1dWueU5dlzwzwZYvX5729vZGl9FwnZ2d3i+Y8vRjpgt9melCX5549XwoUM/0\n4O8n6UiSoigOSrIgyY1FUbx06PnTktyc5PYkJxZF0VIUxV5JDsvgIk0AAAAwKmMeSivL8oaiKFYX\nRXF7BkPvu5KsTXLt0EJL9yb5ytDqwVcnuWVov4vKsuwZv9IBAACY7uqa/1mW5QW72fyy3ex3XZLr\n6jkGAAAA1DM9GAAAACaF0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVFZdqwcDjdGTZH1XV93t29ra\n0tzcPH4FAQDABBNaYQpZnyQdHXW17UqSskx7e/s4VgQAABNLaIUpZlkSsRMAgJnCNa0AAABUltAK\nAABAZQmtAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAAQGUJ\nrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABU\nltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAA\nQGUJrQAAAFSW0AoAAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFTWnEYXAEyOniTr\nu7rqatvW1pbm5ubxLQgAAEZBaIUZYn2SdHSMuV1XkpRl2tvbx7kiAAAYmdAKM8iyJKInAABTiWta\nAQAAqCyhFQAAgMoSWgEAAKgsoRUAAIDKEloBAACoLKEVAACAyhJaAQAAqCyhFQAAgMqaU2/Doij2\nS9KZ5HeSDCS5fui/a5KcX5ZlrSiKdyY5L0lfkg+XZXnDHlcMAADAjFHXSGtRFHOTfCbJ5iRNST6R\n5KKyLFcPPT6jKIoDkrw7yaokpya5tCiK5nGpGgAAgBmh3unBH0tyTZJfDj0+pizLm4e+/kaSk5Ic\nm+TWsix7y7J8Msn9SY7ck2IBAACYWcYcWouieGuSR8qy/NbQpqahfztsSrJXksVJNu5mOwAAAIxK\nPde0vi1JrSiKk5IcneRvk+y7y/OLk2xI8mSS1l22tyZ5YqQX7+zsrKMkhtPd3V1Xu56+vnGuhKlq\nzZo12bRpU6PLeAbvF0wH+jHThb7MdKEvV8+YQ2tZli/d8XVRFDcl+f0kHyuK4qVlWX4vyWlJbkxy\ne5KPFEXRkmReksMyuEjTsFasWDHWkhjBLxYtqqtd85y61+limlm+fHna29sbXcZTdHZ2er9gytOP\nmS70ZaYLfXni1fOhwHikklqS9ya5dmihpXuTfGVo9eCrk9ySwWnIF5Vl2TMOxwMAAGCG2KPQWpbl\ny3d5+LLdPH9dkuv25BgAAADMXOZ/AsPqSbK+q6vu9m1tbWludrcrAADqI7QCw1qfJB0ddbXtSpKy\nrNz1sAAATB1CKzCiZUnETgAAGmHM92kFAACAySK0AgAAUFlCKwAAAJUltAIAAFBZQisAAACVJbQC\nAABQWUIrAAAAlSW0AgAAUFlCKwAAAJUltAIAAFBZQisAAACVJbQCAABQWUIrAAAAlSW0AgAAUFlC\nKwAAAJUltAIAAFBZQisAAACVJbQCAABQWUIrAAAAlSW0AgAAUFlCKwAAAJUltAIAAFBZQisAAACV\nJbQCAABQWUIrAAAAlTWn0QUA01dPkvVdXXW1bWtrS3Nz8/gWBADAlCO0AhNmfZJ0dIy5XVeSlGXa\n29vHuSIAAKYaoRWYUMuSiJ4AANTLNa0AAABUltAKAABAZQmtAAAAVJbQCgAAQGVZiAmonNHcKmfd\nunVpbW3d7XNulwMAMH0IrUDljOZWOcufZbvb5QAATC9CK1BJbpUDAEDimlYAAAAqTGgFAACgsoRW\nAAAAKktoBQAAoLKEVgAAACpLaAUAAKCyhFYAAAAqS2gFAACgsoRWAAAAKktoBQAAoLKEVgAAACpL\naAUAAKCyhFYAAAAqS2gFAACgsoRWAAAAKktoBQAAoLKEVgAAACprzlgbFEUxN8nnkjw/SUuSDyf5\njyTXJxlIsibJ+WVZ1oqieGeS85L0JflwWZY3jFPdAAAAzAD1jLSek+SRsixXJ+lI8qkklye5aGhb\nU5IziqI4IMm7k6xKcmqSS4uiaB6fsgEAAJgJxjzSmuTLSb4y9PWsJL1JjinL8uahbd9IckqS/iS3\nlmXZm6S3KIr7kxyZ5Ad7VjIAAAAzxZhDa1mWm5OkKIrWDAbYv0jy8V122ZRkrySLk2zczXYAAAAY\nlXpGWlMUxcFJ/jnJp8qy/EJRFP9jl6cXJ9mQ5Mkkrbtsb03yxEiv3dnZWU9JDKO7u7uudj19feNc\nCUyONWvWZNOmTY0uA0bF7z2mC32Z6UJfrp56FmLaP8m3kryrLMubhjbfWRTFS8uy/F6S05LcmOT2\nJB8piqIlybwkh2VwkaZhrVixYqwlMYJfLFpUV7vmOXV9pgENt3z58rS3tze6DBhRZ2en33tMC/oy\n04W+PPHq+VCgnlRyUQan+V5SFMUlQ9v+OMnVQwst3ZvkK0OrB1+d5JYMXvt6UVmWPXUcDwAAgBmq\nnmta/ziDIfXpXrabfa9Lct3YywIAAID6bnkDAAAAk8JFi8C00pNkfVdXXW3b2trS3Ox20gAAVSK0\nAtPK+iTp6Bhzu64kKUsLOAEAVIzQCkw7y5KIngAA04NrWgEAAKgsoRUAAIDKEloBAACoLKEVAACA\nyhJaAQAAqCyhFQAAgMoSWgEAAKgs92kFSNKTZH1XV93t29ra0tzcPH4FAQCQRGgFSJKsT5KOjrra\ndiVJWaa9vX0cKwIAIBFaAXZalkTsBACoFqEVYA/tydRi04oBAIYntALsoXqnFptWDAAwMqEVYByY\nWgwAMDHc8gYAAIDKEloBAACoLKEVAACAyhJaAQAAqCyhFQAAgMoSWgEAAKgsoRUAAIDKEloBAACo\nrDmNLgBgpupJsr6rq+72bW1taW5uHr+CAAAqSGgFaJD1SdLRUVfbriQpy7S3t49jRQAA1SO0UjEZ\nyQAACARJREFUAjTQsiRiJwDAs3NNKwAAAJVlpBVgCtqT62FdCwsATCVCK8AUVO/1sK6FBQCmGqEV\nYIpyPSwAMBO4phUAAIDKEloBAACoLKEVAACAyhJaAQAAqCyhFQAAgMoSWgEAAKgst7wBmEF6kqzv\n6qq7fVtbW5qbm8evIACAEQitADPI+iTp6KirbVeSlGXa290dFgCYPEIrwAyzLInYCQBMFa5pBQAA\noLKMtAIwKq6HBQAaQWgFYFRcDwsANILQCsCouR4WAJhsQisAE25PphabVgwAM5vQCsCEq3dqsWnF\nAIDQCsCkmOypxT09PVm7dm1dbY3uAkB1CK0AVNaeTCvu6upKOjqybKztEqO7AFAhQisAlbUnKxY/\nlOTEjH10tydDgbcOPT09STLqUdp169altbV1zO2ezsgwANOZ0ApApdU7rbjeO8ruSVD+9yTPS0Y9\nuru8zna7MjIMwHQntALA0+xJUK6nbb3tAGAmEFoBYApzOyEApjuhFQCmMLcTAmC6E1oBYIoztRiA\n6WxCQ2tRFLOSfDrJkUm2J3lHWZY/m8hjAgAj25NpxfWudmyVZADqMdEjrWcmaS7LclVRFMcluXxo\nGwDQQJO5SvKetkuS+5J0ffObWbZs7K3rDbs9PT1Zu3btmNvtyTEBeKaJDq3HJ/lmkpRl+e9FUayc\n4OMBAKM0lVZJ7krqCtl7Ena7urqSjo4xh+w9OWZSX+Ddk4A9HiPnO+45PBaCPY0w0s/KSH1Zv22M\niQ6ti5M8ucvj/qIoZpVlOTDBx2UX98+bl68demiSZNv27ZnX0jKqdj9OsuzXvx7z8R4ac4s9b+uY\njumY1T3mnrR1TMfcte3z6mj3qyR9HR3praPtD5McN8nHXJ+krY7A29XVlbUdHXluHcf8YZL9kzG3\n3bVdcwbD+mjV+33CnhrpZ2W4vrw+ycstYNcQTbVabcJevCiKy5P8v7Isvzz0+MGyLA9+tv07Ozsn\nrhgAAAAabsWKFU1j2X+iR1pvTXJ6ki8XRfHiJHcPt/NYiwcAAGB6m+jQ+i9JTi6K4tahx2+b4OMB\nAAAwjUzo9GAAAADYE7MaXQAAAAA8G6EVAACAyhJaAQAAqKyJXoiJBimKYlaSTyc5Msn2JO8oy/Jn\nuzx/epKLk/Ql+VxZltc1pFAYxij68euT/HEG+/E9Sd5VlqUL9amckfryLvt9NsljZVm+f5JLhBGN\n4j352CSXJ2nK4C0t31yWZU8jaoXhjKIvvybJRUlqGfw7+a8bUig7GWmdvs5M0lyW5aokF2bwl0iS\npCiKuUk+keTkJC9Ncl5RFPs1pEoY3nD9eH6SDyV5WVmWJyTZK8mrGlIljOxZ+/IORVH8lyTLM/hH\nElTRcO/JTUk+m+StZVmemOTGJMsaUiWMbKT35B1/Jx+f5L1FUew1yfXxNELr9HV8km8mSVmW/55k\n5S7PHZbk/rIsN5Zl2Zvk+0lWT36JMKLh+vG2JC8py3Lb0OM5SbZObnkwasP15RRFsSrJbyf5TAZH\nqaCKhuvH7UkeS/InRVF8N8neZVmWk14hjM6w78lJepPsnWR+Bt+TfZjYYELr9LU4yZO7PO4fmgqx\n47mNuzy3KYOjVFA1z9qPy7KslWX5SJIURfHuJAvLsvx2A2qE0XjWvlwUxYFJLknyhxFYqbbh/rZ4\nTpJVST6Z5KQkv1MUxcsnuT4YreH6cjI48tqZZE2Sr5Vlueu+NIDQOn09maR1l8ezyrIcGPp649Oe\na03yxGQVBmMwXD9OURSziqL4eJLfSfJ7k10cjMFwffmsDP7B/3+SXJDkDUVRvHmS64PRGK4fP5bB\nWVxlWZZ9GRzFevroFVTFs/bloigOyeCHiM9P0pZk/6Iozpr0CnkKoXX6ujXJK5OkKIoXJ7l7l+d+\nkuQ3i6JYUhRFcwanBt82+SXCiIbrx8ngVMqWJK/ZZZowVNGz9uWyLD9ZluXKsixfnuSyJP9YluXf\nNaZMGNZw78k/T7KoKIrfGHp8YgZHqaCKhuvL85L0J9k+FGR/ncGpwjRQU61mivZ0NLQgwo5V0ZLk\nbUlWJFlUluW1RVG8KoPT0WYl+Z9lWV7TmErh2Q3Xj5P8YOjfzbs0uaosy69OapEwCiO9J++y31uS\nFGVZXjT5VcLwRvG3xY4PXpqS3FqW5XsaUykMbxR9+T1J3pDB9TPuT/LOoRkENIjQCgAAQGWZHgwA\nAEBlCa0AAABUltAKAABAZQmtAAAAVJbQCgAAQGUJrQAAAFTWnEYXAADTUVEUbUnuS/LjXTbXkpyZ\n5IIkq5MMJNmQ5L1lWf6gKIpPJVmVpDnJC5LcO9TuyrIs/3aSSgeAShFaAWDirC/L8kW7biiK4oIk\nTWVZHjH0eFWS/10UxcFlWZ4/tO35Sb779LYAMBOZHgwAk2v/JM1FUcxNkrIs/y3JW/PUD5KbGlAX\nAFSSkVYAmDgHFUVx5y6P/z7JVUluSPJIURTfTXJjkr8ty3J7A+oDgMoTWgFg4vziWab4Li+K4tgk\nJyV5c5L3FEXxorIsN05ueQBQfUIrAEyioiguS3JVWZZ3JLkjyaVFUXw/gwH2nxpaHABUkGtaAWBy\nHZDk4qIo5iRJURRLk+yb5J6GVgUAFSW0AsDEqe1m2x8mmZ3kp0VRrEny7SQXlGV53yjaAsCM01Sr\n+Z0IAABANRlpBQAAoLKEVgAAACpLaAUAAKCyhFYAAAAqS2gFAACgsoRWAAAAKktoBQAAoLKEVgAA\nACrr/wMzlVl2FfKTMgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f43bc5ffe50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "fig = plt.figure(figsize=(16, 9))\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "ax.hist(fst_vals, 50, color='r')\n",
    "ax.set_title('FST, FIS and FIS distributions')\n",
    "ax.set_xlabel('FST')\n",
    "ax = fig.add_subplot(2, 2, 2)\n",
    "sns.violinplot([fis_vals, fit_vals], ax=ax, vert=False)\n",
    "ax.set_yticklabels(['FIS', 'FIT'])\n",
    "ax.set_xlim(-.1, 0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fpair_iter, avg = ctrl.calc_fst_pair('hapmap10_auto_noofs_2.gp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "min_pair = min(avg.values())\n",
    "max_pair = max(avg.values())\n",
    "arr = np.ones((num_pops - 1, num_pops - 1, 3), dtype=float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.text.Text at 0x7f43bbff81d0>,\n",
       " <matplotlib.text.Text at 0x7f43bc33d1d0>,\n",
       " <matplotlib.text.Text at 0x7f43bc24ec10>,\n",
       " <matplotlib.text.Text at 0x7f43bc255150>,\n",
       " <matplotlib.text.Text at 0x7f43bc255850>,\n",
       " <matplotlib.text.Text at 0x7f43bc23af10>,\n",
       " <matplotlib.text.Text at 0x7f43bc255cd0>,\n",
       " <matplotlib.text.Text at 0x7f43bc25e450>,\n",
       " <matplotlib.text.Text at 0x7f43bc25eb90>,\n",
       " <matplotlib.text.Text at 0x7f43bc268310>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fwNTo8RAXksPucGCYOZo8nrYmBKBbfDyN9fVt+z2TlcWyxYu5+tZbgS8+NB5b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\nCTE3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f43bbff71d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"white\")\n",
    "fig = plt.figure(figsize=(16,9))\n",
    "ax = fig.add_subplot(111)\n",
    "for row in range(num_pops - 1):\n",
    "    for col in range(row + 1, num_pops):\n",
    "        val = avg[(col, row)]\n",
    "        norm_val = (val - min_pair) / (max_pair - min_pair)\n",
    "        ax.text(col - 1, row, '%.3f' % val, ha='center')\n",
    "        if norm_val == 0.0:\n",
    "            arr[row, col - 1, 0] = 1\n",
    "            arr[row, col - 1, 1] = 1\n",
    "            arr[row, col - 1, 2] = 0\n",
    "        elif norm_val == 1.0:\n",
    "            arr[row, col - 1, 0] = 1\n",
    "            arr[row, col - 1, 1] = 0\n",
    "            arr[row, col - 1, 2] = 1\n",
    "        else:\n",
    "            arr[row, col - 1, 0] = 1 - norm_val\n",
    "            arr[row, col - 1, 1] = 1\n",
    "            arr[row, col - 1, 2] = 1\n",
    "ax.imshow(arr, interpolation='none')\n",
    "ax.set_title('Multilocus Pairwise FST')\n",
    "ax.set_xticks(range(num_pops - 1))\n",
    "ax.set_xticklabels(my_pops[1:])\n",
    "ax.set_yticks(range(num_pops - 1))\n",
    "ax.set_yticklabels(my_pops[:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pop_ceu = my_pops.index('CEU')\n",
    "pop_yri = my_pops.index('YRI')\n",
    "start_pos = 136261886  # b36\n",
    "end_pos = 136350481\n",
    "all_fsts = []\n",
    "inside_fsts = []\n",
    "for locus_pfst in fpair_iter:\n",
    "    name = locus_pfst[0]\n",
    "    pfst = locus_pfst[1]\n",
    "    pos = int(name.split('/')[-1])  # dependent\n",
    "    my_fst = pfst[(pop_yri, pop_ceu)]\n",
    "    if my_fst == '-':  # Can be this\n",
    "        continue\n",
    "    all_fsts.append(my_fst)\n",
    "    if pos >= start_pos and pos <= end_pos:\n",
    "        inside_fsts.append(my_fst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.1346, 0.6703, 0.7317, 0.1432, 0.2485]\n",
      "0.08/0.13/0.33\n"
     ]
    }
   ],
   "source": [
    "print(inside_fsts)\n",
    "print('%.2f/%.2f/%.2f' % (np.median(all_fsts), np.mean(all_fsts), np.percentile(all_fsts, 90)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.03660950413223141"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "100 * (end_pos - start_pos) / 242000000.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}