1_E_pair_interactions.py.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "21516a12",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "# from numba import jit\n",
    "from tqdm import tqdm\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import sklearn \n",
    "from sklearn.metrics import matthews_corrcoef\n",
    "\n",
    "from scipy.optimize import minimize\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as colors \n",
    "from matplotlib import cm\n",
    "\n",
    "from my_utilities.constants import AMINOACIDS, aminoacid_name_from_1l\n",
    "from my_utilities.svd import SVD_representation\n",
    "from my_utilities.pair_contacts import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "02392d70",
   "metadata": {},
   "outputs": [],
   "source": [
    "DIR_PATH = \"./cg_contacts/\"\n",
    "DAA_CONTACT_CUTOFF = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d649eafa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████| 6442/6442 [00:12<00:00, 514.24it/s]\n"
     ]
    }
   ],
   "source": [
    "df = load_data(DIR_PATH)\n",
    "df[\"aa_contact\"] = df.apply(lambda row: row[\"daa\"] < DAA_CONTACT_CUTOFF, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9c41e26c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "aas = df[\"aa1\"].unique()\n",
    "aas.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "92f9a2d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfg = df.groupby([\"aa1\",\"aa2\"])\n",
    "dfnrg = {}\n",
    "for g in dfg: #dfgg.keys():\n",
    "    g_key, g_df = g\n",
    "    if (g_key[1],g_key[0]) not in dfnrg.keys():\n",
    "        dfnrg[g_key] = pd.concat([dfg.get_group(g_key), dfg.get_group((g_key[1],g_key[0]))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "43629d99",
   "metadata": {},
   "outputs": [],
   "source": [
    "d2vals = {}\n",
    "for p in dfnrg:\n",
    "    d2vals[p] = get_optimal_d2(dfnrg[p])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "649209f6",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "171"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(d2vals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7c21f3b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_contact_hists(dfx, N_BINS=100, plot_mcc_curve=False, save_to=None):\n",
    "    \"\"\"\n",
    "    \"\"\"\n",
    "    aac_hist, aac_edges = np.histogram(dfx[dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "    aac_rdf = aac_hist / ((3/4)*(np.pi)*aac_edges[1:]**3)\n",
    "\n",
    "    aanc_hist, aanc_edges = np.histogram(dfx[~dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "    aanc_rdf = aanc_hist / ((3/4)*(np.pi)*aanc_edges[1:]**3)\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(aac_edges[1:], aac_rdf, label=\"contact\")\n",
    "    ax.plot(aanc_edges[1:], aanc_rdf, label=\"no contact\")\n",
    "    ax.tick_params(direction=\"in\")\n",
    "    ax.set_xlabel(\"d [Å]\")\n",
    "    ax.set_ylabel(\"n\")\n",
    "    ax.legend()\n",
    "\n",
    "    if plot_mcc_curve:\n",
    "        rs, mccs = [], []\n",
    "        for r in tqdm(np.linspace(min(aac_edges[0], aanc_edges[0]),\n",
    "                                  max(aac_edges[-1], aanc_edges[-1]), 100)):\n",
    "            rs.append(r)\n",
    "            mccs.append(\n",
    "                sklearn.metrics.matthews_corrcoef(dfx[\"aa_contact\"], dfx[\"dcg\"] < r)\n",
    "            )\n",
    "        ax1 = ax.twinx()\n",
    "        ax1.plot(rs, mccs, color=\"red\",linestyle=\"dashed\")\n",
    "        ax1.tick_params(axis='y', labelcolor=\"red\")\n",
    "        ax1.set_ylabel('MCC', color=\"red\")\n",
    "\n",
    "    if save_to is None:\n",
    "        plt.show()\n",
    "    else:\n",
    "        plt.savefig(save_to)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fdcd253f",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_contact_hists(dfnrg['L','V'], N_BINS=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3ee43b90",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████| 100/100 [00:08<00:00, 11.77it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_contact_hists(dfnrg['L','V'], N_BINS=100, plot_mcc_curve=True, save_to=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b99dd924",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('C',\n",
       "  'C'):      aa1 aa2 dij    dcg    daa  aa_contact\n",
       " 4350   C   C   1  8.253  8.253       False\n",
       " 4368   C   C   3  7.273  7.273       False\n",
       " 4369   C   C   2  9.528  9.528       False\n",
       " 1104   C   C   4  7.035  7.035       False\n",
       " 521    C   C  37  4.232  4.232        True\n",
       " ...   ..  ..  ..    ...    ...         ...\n",
       " 393    C   C   3  3.885  3.885        True\n",
       " 129    C   C  23  2.176  2.176        True\n",
       " 958    C   C   1  7.695  7.695       False\n",
       " 3820   C   C   5  1.995  1.995        True\n",
       " 544    C   C  68  1.991  1.991        True\n",
       " \n",
       " [17716 rows x 6 columns],\n",
       " ('C',\n",
       "  'D'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1377   C   D    7   7.337  6.899       False\n",
       " 3757   C   D   18   6.507  6.238       False\n",
       " 4343   C   D    1   7.052  6.709       False\n",
       " 4349   C   D    2   8.193  7.716       False\n",
       " 4358   C   D   56  10.486  9.470       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 807    D   C  115   4.555  3.690        True\n",
       " 1391   D   C    3   6.374  5.650       False\n",
       " 2926   D   C    2   9.291  9.076       False\n",
       " 3693   D   C    3   4.472  3.692        True\n",
       " 4440   D   C   56   6.672  6.380       False\n",
       " \n",
       " [17965 rows x 6 columns],\n",
       " ('C',\n",
       "  'E'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2084   C   E   46  10.163  8.905       False\n",
       " 2087   C   E   42   8.627  7.532       False\n",
       " 3751   C   E  113   9.286  8.486       False\n",
       " 3754   C   E   36   8.707  7.881       False\n",
       " 3755   C   E   34  10.166  9.360       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3576   E   C   20   8.583  8.370       False\n",
       " 933    E   C    1   4.769  4.001        True\n",
       " 951    E   C    3   6.582  5.705       False\n",
       " 1389   E   C    2   4.995  4.492        True\n",
       " 4398   E   C   53   8.665  7.776       False\n",
       " \n",
       " [17826 rows x 6 columns],\n",
       " ('C',\n",
       "  'F'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 1204   C   F  40   7.842  7.247       False\n",
       " 1206   C   F  38   9.639  8.932       False\n",
       " 1372   C   F  55   9.419  8.220       False\n",
       " 2082   C   F  50  11.228  9.950       False\n",
       " 2083   C   F  47   5.768  4.894        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 2671   F   C  53  10.007  8.951       False\n",
       " 3059   F   C  86   6.927  5.943       False\n",
       " 3206   F   C  31   9.435  8.062       False\n",
       " 3727   F   C   8   8.523  7.328       False\n",
       " 4041   F   C  31  10.486  9.396       False\n",
       " \n",
       " [25020 rows x 6 columns],\n",
       " ('C',\n",
       "  'H'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1378   C   H    5   9.670  9.481       False\n",
       " 5520   C   H   89   9.374  8.243       False\n",
       " 1096   C   H   21  10.462  9.353       False\n",
       " 1106   C   H    1   7.789  6.650       False\n",
       " 2370   C   H    3  10.047  9.387       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5391   H   C    1   5.155  4.498        True\n",
       " 5740   H   C    8   5.544  4.527        True\n",
       " 737    H   C  106   9.173  8.496       False\n",
       " 3249   H   C    2   4.969  3.970        True\n",
       " 2601   H   C   46  10.538  9.400       False\n",
       " \n",
       " [11650 rows x 6 columns],\n",
       " ('C',\n",
       "  'I'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 173    C   I   5  10.165  9.436       False\n",
       " 1205   C   I  39   8.469  8.191       False\n",
       " 2081   C   I  71   8.510  8.428       False\n",
       " 2088   C   I  40   8.576  7.399       False\n",
       " 2090   C   I  36  10.657  9.424       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 2710   I   C  55   9.802  9.001       False\n",
       " 2762   I   C  58   5.570  4.661        True\n",
       " 2968   I   C   4   6.901  5.722       False\n",
       " 3115   I   C  17   8.001  7.544       False\n",
       " 3265   I   C  35   9.753  9.490       False\n",
       " \n",
       " [32148 rows x 6 columns],\n",
       " ('C',\n",
       "  'K'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1201   C   K   44   5.154  4.890        True\n",
       " 2095   C   K    1   6.815  5.315       False\n",
       " 3760   C   K   15  10.406  9.349       False\n",
       " 3761   C   K    3   9.024  7.826       False\n",
       " 4327   C   K   43   9.650  7.902       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1769   K   C  200   5.564  5.200       False\n",
       " 4676   K   C  150   9.677  8.887       False\n",
       " 354    K   C   50   8.199  7.547       False\n",
       " 1419   K   C    8   7.640  6.983       False\n",
       " 5428   K   C  117  10.043  8.382       False\n",
       " \n",
       " [14704 rows x 6 columns],\n",
       " ('C',\n",
       "  'L'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 172    C   L  12   9.785  9.017       False\n",
       " 175    C   L   3   5.718  5.148       False\n",
       " 1202   C   L  42   5.237  4.349        True\n",
       " 1380   C   L   2   9.648  9.130       False\n",
       " 4329   C   L  41   4.361  3.681        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 1399   L   C   4   8.928  8.676       False\n",
       " 2526   L   C  40   9.371  8.113       False\n",
       " 2617   L   C  47   6.193  5.771       False\n",
       " 2947   L   C   3   7.979  7.273       False\n",
       " 4078   L   C  32  10.035  8.828       False\n",
       " \n",
       " [47482 rows x 6 columns],\n",
       " ('C',\n",
       "  'M'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 549    C   M   33   9.854  9.356       False\n",
       " 3947   C   M   94   8.261  7.019       False\n",
       " 3318   C   M    1   4.440  4.103        True\n",
       " 1150   C   M    2   5.199  5.165       False\n",
       " 2421   C   M    3   7.505  7.009       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 963    M   C    2   9.288  8.943       False\n",
       " 964    M   C    1   7.550  6.717       False\n",
       " 1399   M   C   39   8.239  7.726       False\n",
       " 1748   M   C  199   7.850  7.050       False\n",
       " 852    M   C  121  10.248  9.716       False\n",
       " \n",
       " [10366 rows x 6 columns],\n",
       " ('C',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 177    C   N    1   6.867  6.535       False\n",
       " 4370   C   N    1   8.716  8.333       False\n",
       " 5184   C   N  118   7.009  6.534       False\n",
       " 5188   C   N  114   7.832  6.977       False\n",
       " 1039   C   N   76   8.525  8.110       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 782    N   C  112  10.284  9.941       False\n",
       " 1987   N   C   15  10.194  9.299       False\n",
       " 4046   N   C    2   9.421  8.672       False\n",
       " 112    N   C   11   8.680  8.489       False\n",
       " 125    N   C   14   9.885  9.533       False\n",
       " \n",
       " [14914 rows x 6 columns],\n",
       " ('C',\n",
       "  'P'):      aa1 aa2  dij    dcg    daa  aa_contact\n",
       " 1208   C   P    2  9.635  9.432       False\n",
       " 1374   C   P   15  8.951  8.832       False\n",
       " 4511   C   P   40  9.086  8.518       False\n",
       " 5183   C   P  442  7.011  6.966       False\n",
       " 172    C   P   32  4.745  4.287        True\n",
       " ...   ..  ..  ...    ...    ...         ...\n",
       " 1654   P   C  190  7.854  7.632       False\n",
       " 1914   P   C    3  8.322  8.259       False\n",
       " 3816   P   C    2  7.271  6.805       False\n",
       " 3824   P   C    7  9.992  9.345       False\n",
       " 3827   P   C    2  9.408  8.821       False\n",
       " \n",
       " [17255 rows x 6 columns],\n",
       " ('C',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 176    C   Q   2   9.511  8.483       False\n",
       " 1203   C   Q  41   6.035  5.007       False\n",
       " 1379   C   Q   4   7.348  6.684       False\n",
       " 4342   C   Q   2   9.686  9.069       False\n",
       " 4348   C   Q   3   4.232  3.173        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 224    Q   C   6   9.597  9.133       False\n",
       " 5426   Q   C   3   8.472  7.038       False\n",
       " 5730   Q   C   6   9.858  8.963       False\n",
       " 4184   Q   C  31   9.345  8.669       False\n",
       " 942    Q   C   2  10.464  9.533       False\n",
       " \n",
       " [12966 rows x 6 columns],\n",
       " ('C',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2093   C   R    3   8.682  7.429       False\n",
       " 4328   C   R   42   6.515  4.126        True\n",
       " 4365   C   R   45  10.214  8.395       False\n",
       " 4515   C   R    2   9.874  7.597       False\n",
       " 5182   C   R  443   7.682  6.465       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2281   R   C   44   9.423  8.676       False\n",
       " 4267   R   C   36   6.297  5.470       False\n",
       " 73     R   C    1   9.255  7.582       False\n",
       " 982    R   C    8  10.703  9.946       False\n",
       " 4093   R   C   33   7.159  6.290       False\n",
       " \n",
       " [18682 rows x 6 columns],\n",
       " ('C',\n",
       "  'S'):      aa1 aa2  dij    dcg    daa  aa_contact\n",
       " 1207   C   S    3  9.347  9.347       False\n",
       " 1209   C   S    1  4.850  4.850        True\n",
       " 1373   C   S   16  8.963  8.963       False\n",
       " 1376   C   S    9  7.278  7.278       False\n",
       " 3750   C   S  115  8.580  8.580       False\n",
       " ...   ..  ..  ...    ...    ...         ...\n",
       " 2787   S   C   59  6.679  6.679       False\n",
       " 3130   S   C   89  9.634  9.634       False\n",
       " 3154   S   C   19  8.326  8.326       False\n",
       " 3708   S   C    6  7.147  7.147       False\n",
       " 4137   S   C   35  9.470  9.470       False\n",
       " \n",
       " [21699 rows x 6 columns],\n",
       " ('C',\n",
       "  'T'):      aa1 aa2  dij    dcg    daa  aa_contact\n",
       " 2091   C   T    5  9.281  8.282       False\n",
       " 2094   C   T    2  9.200  9.135       False\n",
       " 3749   C   T  117  8.930  8.420       False\n",
       " 4338   C   T    8  8.235  7.803       False\n",
       " 555    C   T   25  9.980  9.472       False\n",
       " ...   ..  ..  ...    ...    ...         ...\n",
       " 3814   T   C    1  6.543  6.393       False\n",
       " 689    T   C   82  9.579  8.475       False\n",
       " 697    T   C   14  9.843  8.810       False\n",
       " 2727   T   C   56  4.455  3.589        True\n",
       " 3681   T   C    1  5.425  4.566        True\n",
       " \n",
       " [23233 rows x 6 columns],\n",
       " ('C',\n",
       "  'V'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 1375   C   V  12   5.768  5.064       False\n",
       " 2085   C   V  44  10.513  9.663       False\n",
       " 2089   C   V  39   7.164  6.066       False\n",
       " 3756   C   V  33   9.605  8.557       False\n",
       " 3758   C   V  17   5.842  5.610       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 4034   V   C   1   6.895  5.836       False\n",
       " 97     V   C   7   5.773  5.567       False\n",
       " 647    V   C  77   9.317  8.671       False\n",
       " 652    V   C   9   9.479  8.924       False\n",
       " 2919   V   C   1   7.330  6.470       False\n",
       " \n",
       " [38096 rows x 6 columns],\n",
       " ('C',\n",
       "  'W'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 2086   C   W  43   4.150  3.467        True\n",
       " 4336   C   W  14   5.834  3.807        True\n",
       " 4345   C   W  15   9.815  9.221       False\n",
       " 4366   C   W  17   8.984  7.019       False\n",
       " 1046   C   W  41  10.636  9.382       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 636    W   C   8   9.749  7.820       False\n",
       " 2457   W   C  36  11.459  9.343       False\n",
       " 2663   W   C  52  10.217  8.754       False\n",
       " 4122   W   C  34   8.097  6.585       False\n",
       " 4382   W   C  52   8.867  7.673       False\n",
       " \n",
       " [9645 rows x 6 columns],\n",
       " ('C',\n",
       "  'Y'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 174    C   Y   4   4.527  4.188        True\n",
       " 1381   C   Y   1   6.227  4.729        True\n",
       " 3752   C   Y  93   7.916  6.446       False\n",
       " 5193   C   Y  85   7.846  6.537       False\n",
       " 5195   C   Y  75   6.328  5.757       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 4287   Y   C  37   7.956  6.782       False\n",
       " 589    Y   C  72   8.720  7.044       False\n",
       " 598    Y   C   4   9.275  8.006       False\n",
       " 2169   Y   C   1  10.315  8.715       False\n",
       " 2747   Y   C  57   9.021  7.465       False\n",
       " \n",
       " [19753 rows x 6 columns],\n",
       " ('D',\n",
       "  'D'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 21     D   D    6   9.644  7.939       False\n",
       " 37     D   D    3   6.903  5.458       False\n",
       " 406    D   D    2   9.532  8.827       False\n",
       " 853    D   D    1   7.093  5.659       False\n",
       " 1759   D   D    3   9.042  7.779       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5071   D   D  497  11.019  9.437       False\n",
       " 5075   D   D  470   5.755  4.733        True\n",
       " 5557   D   D  544  10.903  9.697       False\n",
       " 5560   D   D  122   8.757  6.940       False\n",
       " 5565   D   D    2   9.827  9.270       False\n",
       " \n",
       " [80712 rows x 6 columns],\n",
       " ('D',\n",
       "  'E'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 38     D   E    2  11.388  9.669       False\n",
       " 394    D   E    8  10.617  9.116       False\n",
       " 1733   D   E    4   5.339  4.164        True\n",
       " 3471   D   E   71   9.257  7.329       False\n",
       " 3476   D   E   16   6.020  4.402        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4400   E   D   50   8.723  7.962       False\n",
       " 4897   E   D  398  11.538  9.708       False\n",
       " 4997   E   D  493   7.061  5.376       False\n",
       " 5000   E   D  466   8.678  7.252       False\n",
       " 5654   E   D    7  11.294  9.477       False\n",
       " \n",
       " [79360 rows x 6 columns],\n",
       " ('D',\n",
       "  'F'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 0      D   F    1   6.693  6.319       False\n",
       " 39     D   F    1   7.688  5.871       False\n",
       " 666    D   F    2   6.054  4.416        True\n",
       " 825    D   F    4   8.247  6.753       False\n",
       " 850    D   F  132  11.117  9.442       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4486   F   D  377   7.303  5.164       False\n",
       " 4495   F   D  247  10.854  8.817       False\n",
       " 4502   F   D   21   9.314  7.584       False\n",
       " 4514   F   D    2   9.230  8.257       False\n",
       " 4723   F   D   35  10.859  9.678       False\n",
       " \n",
       " [75030 rows x 6 columns],\n",
       " ('D',\n",
       "  'H'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 663    D   H   23   9.843  8.130       False\n",
       " 2609   D   H    1   4.537  4.208        True\n",
       " 4007   D   H  236   9.264  7.331       False\n",
       " 4008   D   H  232  10.638  9.803       False\n",
       " 4398   D   H   24  10.917  9.671       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2596   H   D   69   3.913  2.628        True\n",
       " 3364   H   D   54  11.759  9.781       False\n",
       " 3367   H   D   22   3.993  3.403        True\n",
       " 3477   H   D   30  10.261  8.731       False\n",
       " 3481   H   D   25   3.935  2.751        True\n",
       " \n",
       " [42980 rows x 6 columns],\n",
       " ('D',\n",
       "  'I'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 26     D   I    1   4.973  3.432        True\n",
       " 36     D   I    4   7.405  6.126       False\n",
       " 395    D   I    5  11.053  8.728       False\n",
       " 400    D   I   41  10.558  9.160       False\n",
       " 824    D   I  121  10.427  9.708       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5615   I   D  125   6.567  4.979        True\n",
       " 5625   I   D    3   6.799  5.438       False\n",
       " 5691   I   D   56  10.113  8.442       False\n",
       " 5743   I   D  530  11.489  9.303       False\n",
       " 5749   I   D   60   8.067  7.041       False\n",
       " \n",
       " [96619 rows x 6 columns],\n",
       " ('D',\n",
       "  'K'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 201    D   K   27  11.438  9.627       False\n",
       " 202    D   K   23  11.098  9.220       False\n",
       " 396    D   K    4   5.017  3.849        True\n",
       " 402    D   K    6  10.296  9.177       False\n",
       " 1231   D   K   14   3.828  1.609        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5430   K   D  114   6.564  4.375        True\n",
       " 5513   K   D  118   9.662  8.259       False\n",
       " 5709   K   D  554   8.394  6.506       False\n",
       " 5714   K   D  527   8.546  7.671       False\n",
       " 5723   K   D   57   4.770  3.225        True\n",
       " \n",
       " [83605 rows x 6 columns],\n",
       " ('D',\n",
       "  'L'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 203    D   L    6  10.440  9.690       False\n",
       " 1730   D   L   38  11.149  9.426       False\n",
       " 1731   D   L   37   6.313  4.859        True\n",
       " 2596   D   L  205   5.283  3.394        True\n",
       " 3474   D   L   41  11.078  9.586       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4539   L   D   22   9.707  8.871       False\n",
       " 4541   L   D    3   9.032  8.151       False\n",
       " 4866   L   D  397  10.179  9.490       False\n",
       " 5579   L   D    3   6.633  4.784        True\n",
       " 5581   L   D    1   9.017  8.297       False\n",
       " \n",
       " [142151 rows x 6 columns],\n",
       " ('D',\n",
       "  'M'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 22     D   M    5   9.924  9.305       False\n",
       " 398    D   M    2  10.919  8.719       False\n",
       " 404    D   M    4   8.989  7.841       False\n",
       " 823    D   M  125   9.936  9.103       False\n",
       " 1232   D   M   11   8.307  7.523       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3433   M   D    1   9.551  8.305       False\n",
       " 3455   M   D   27  11.312  9.826       False\n",
       " 3458   M   D   22   8.621  7.060       False\n",
       " 3460   M   D   18  11.575  9.787       False\n",
       " 3465   M   D    4   9.455  8.231       False\n",
       " \n",
       " [30134 rows x 6 columns],\n",
       " ('D',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 23     D   N    4   6.353  5.555       False\n",
       " 204    D   N    5   9.109  7.729       False\n",
       " 205    D   N    3  11.115  9.783       False\n",
       " 827    D   N    2   9.835  9.243       False\n",
       " 847    D   N    6   8.669  7.688       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5134   N   D    2   9.168  8.468       False\n",
       " 5661   N   D  551   8.263  6.930       False\n",
       " 5668   N   D   54  10.628  9.113       False\n",
       " 5770   N   D  531   7.377  6.243       False\n",
       " 5777   N   D   61   6.625  6.040       False\n",
       " \n",
       " [66381 rows x 6 columns],\n",
       " ('D',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 665    D   P   20   5.057  4.173        True\n",
       " 848    D   P    2   9.789  8.695       False\n",
       " 1237   D   P    1   7.959  7.078       False\n",
       " 1323   D   P    1   5.558  4.266        True\n",
       " 2492   D   P   30   8.746  7.968       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4599   P   D  381  10.926  9.486       False\n",
       " 4609   P   D  251  10.594  9.802       False\n",
       " 4610   P   D   25   9.761  9.042       False\n",
       " 4813   P   D  395   5.758  4.513        True\n",
       " 5407   P   D  103  10.989  9.456       False\n",
       " \n",
       " [67645 rows x 6 columns],\n",
       " ('D',\n",
       "  'Q'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1225   D   Q   44   8.243  6.437       False\n",
       " 1727   D   Q   44  11.097  9.483       False\n",
       " 2595   D   Q  206  11.879  9.926       False\n",
       " 3852   D   Q  329  10.854  9.530       False\n",
       " 4013   D   Q   19   9.500  8.158       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 936    Q   D   95   4.554  2.851        True\n",
       " 1270   Q   D  125   4.458  3.541        True\n",
       " 1936   Q   D    4   8.763  7.710       False\n",
       " 3947   Q   D   47   8.478  6.721       False\n",
       " 3948   Q   D   46  10.370  9.000       False\n",
       " \n",
       " [53691 rows x 6 columns],\n",
       " ('D',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 24     D   R    3   8.902  5.583       False\n",
       " 397    D   R    3  11.412  8.141       False\n",
       " 403    D   R    5   5.897  4.509        True\n",
       " 826    D   R    3   8.345  5.622       False\n",
       " 828    D   R    1   3.935  2.632        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5393   R   D  111   8.743  6.225       False\n",
       " 5534   R   D  543  10.384  9.456       False\n",
       " 5540   R   D  536   9.001  6.786       False\n",
       " 5546   R   D  121   3.595  2.765        True\n",
       " 5555   R   D    1  11.114  8.203       False\n",
       " \n",
       " [96179 rows x 6 columns],\n",
       " ('D',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1227   D   S   40   8.823  8.213       False\n",
       " 1234   D   S    4   6.677  5.783       False\n",
       " 1236   D   S    2   8.552  7.770       False\n",
       " 1318   D   S   46   7.261  6.316       False\n",
       " 1322   D   S    2   2.935  2.089        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4668   S   D    1   7.298  6.500       False\n",
       " 4763   S   D  393   9.457  9.067       False\n",
       " 5488   S   D   68  10.015  9.778       False\n",
       " 5628   S   D  548  10.027  9.580       False\n",
       " 5636   S   D    4   7.225  6.852       False\n",
       " \n",
       " [82145 rows x 6 columns],\n",
       " ('D',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 206    D   T    1   7.483  6.800       False\n",
       " 315    D   T    1   5.068  4.105        True\n",
       " 667    D   T    1   5.523  4.421        True\n",
       " 1233   D   T    7  10.807  9.632       False\n",
       " 1736   D   T    1   5.913  4.508        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4780   T   D  394   4.724  4.382        True\n",
       " 5582   T   D  546   8.830  7.542       False\n",
       " 5588   T   D  124   7.182  6.321       False\n",
       " 5603   T   D    4   8.717  7.080       False\n",
       " 5605   T   D    2   9.227  8.495       False\n",
       " \n",
       " [87838 rows x 6 columns],\n",
       " ('D',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 25     D   V    2   8.794  8.114       False\n",
       " 314    D   V    2   8.834  8.091       False\n",
       " 399    D   V    1   4.947  3.882        True\n",
       " 405    D   V    3  10.351  9.937       False\n",
       " 664    D   V   21   9.306  8.536       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1217   V   D   89   9.936  9.348       False\n",
       " 1259   V   D  124  10.246  9.514       False\n",
       " 4225   V   D  229   8.492  7.281       False\n",
       " 4308   V   D  366   6.400  5.106       False\n",
       " 5498   V   D  114   9.533  9.071       False\n",
       " \n",
       " [114929 rows x 6 columns],\n",
       " ('D',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 4401   D   W   19  10.664  8.678       False\n",
       " 88     D   W    2   6.462  3.508        True\n",
       " 15     D   W    2  10.521  9.121       False\n",
       " 381    D   W   55   9.134  6.563       False\n",
       " 807    D   W   29  11.036  9.609       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4124   W   D   31  11.708  8.764       False\n",
       " 4199   W   D  358  12.192  9.469       False\n",
       " 4215   W   D  228   8.472  6.605       False\n",
       " 4218   W   D    2   6.195  5.702       False\n",
       " 4381   W   D  239  11.114  8.359       False\n",
       " \n",
       " [34210 rows x 6 columns],\n",
       " ('D',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 401    D   Y    8  11.472  9.334       False\n",
       " 1228   D   Y   20   8.758  7.314       False\n",
       " 1728   D   Y   41   4.890  2.672        True\n",
       " 2491   D   Y   34   8.395  5.933       False\n",
       " 2603   D   Y   29  11.347  9.793       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4342   Y   D  238   9.221  8.009       False\n",
       " 4343   Y   D  236  10.723  8.638       False\n",
       " 4575   Y   D  380   4.872  2.615        True\n",
       " 4753   Y   D    7  11.201  8.397       False\n",
       " 5328   Y   D  131   8.085  7.052       False\n",
       " \n",
       " [74109 rows x 6 columns],\n",
       " ('E',\n",
       "  'E'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 42     E   E    3   8.637  6.716       False\n",
       " 233    E   E    1   5.690  4.835        True\n",
       " 340    E   E    2  10.602  8.619       False\n",
       " 669    E   E   82   9.608  8.190       False\n",
       " 700    E   E   85  10.151  7.838       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5001   E   E  465   8.672  7.108       False\n",
       " 5017   E   E    4   7.670  6.387       False\n",
       " 5216   E   E  349  10.285  8.962       False\n",
       " 5446   E   E   66   8.039  6.750       False\n",
       " 5653   E   E    8  10.984  9.925       False\n",
       " \n",
       " [95230 rows x 6 columns],\n",
       " ('E',\n",
       "  'F'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 43     E   F    2  11.499  9.580       False\n",
       " 678    E   F    3   9.207  7.825       False\n",
       " 702    E   F    6  10.744  8.935       False\n",
       " 1653   E   F    4   8.615  6.919       False\n",
       " 1656   E   F    1   8.351  6.006       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4030   F   E  278  10.401  9.077       False\n",
       " 4718   F   E  285   4.687  3.583        True\n",
       " 5808   F   E   44  10.657  9.206       False\n",
       " 5849   F   E   58  10.630  9.103       False\n",
       " 5857   F   E    1   9.359  7.207       False\n",
       " \n",
       " [79101 rows x 6 columns],\n",
       " ('E',\n",
       "  'H'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 218    E   H   33   9.306  7.323       False\n",
       " 674    E   H   24  10.200  8.538       False\n",
       " 2990   E   H  337  10.795  9.239       False\n",
       " 3956   E   H  256  11.063  9.541       False\n",
       " 4186   E   H  281  10.315  8.469       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1841   H   E   63  11.566  9.893       False\n",
       " 3047   H   E    9   5.246  3.986        True\n",
       " 3053   H   E    1   7.314  5.936       False\n",
       " 3365   H   E   53   5.813  4.456        True\n",
       " 3369   H   E   20   4.803  2.707        True\n",
       " \n",
       " [41519 rows x 6 columns],\n",
       " ('E',\n",
       "  'I'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 30     E   I    2   9.552  8.342       False\n",
       " 670    E   I   81   8.131  7.686       False\n",
       " 2361   E   I    6  10.952  8.090       False\n",
       " 2652   E   I  257  10.031  8.772       False\n",
       " 2653   E   I  237  11.035  9.633       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5621   I   E   54  11.085  9.698       False\n",
       " 5704   I   E    4   6.435  4.960        True\n",
       " 5758   I   E   41  11.550  8.979       False\n",
       " 5862   I   E  419   8.796  7.400       False\n",
       " 5875   I   E    2  10.476  8.933       False\n",
       " \n",
       " [104014 rows x 6 columns],\n",
       " ('E',\n",
       "  'K'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 114    E   K    5  11.389  9.672       False\n",
       " 118    E   K    1   8.771  5.853       False\n",
       " 220    E   K   29   4.496  3.043        True\n",
       " 223    E   K   25   7.079  5.101       False\n",
       " 227    E   K   30   8.804  7.209       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5254   K   E    6   9.468  8.096       False\n",
       " 5435   K   E  102  10.802  9.232       False\n",
       " 5436   K   E   64   9.396  7.801       False\n",
       " 5711   K   E  533   6.116  4.699        True\n",
       " 5721   K   E   61   7.040  5.629       False\n",
       " \n",
       " [93823 rows x 6 columns],\n",
       " ('E',\n",
       "  'L'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 222    E   L  26   5.935  3.970        True\n",
       " 224    E   L  22  10.702  9.395       False\n",
       " 228    E   L  27  10.102  8.712       False\n",
       " 321    E   L   5   9.883  8.649       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 4952   L   E  66  10.354  9.304       False\n",
       " 4968   L   E   2   9.759  8.934       False\n",
       " 5307   L   E   2  11.254  9.427       False\n",
       " 5578   L   E   4   6.834  6.248       False\n",
       " 5892   L   E   4   8.482  6.962       False\n",
       " \n",
       " [160335 rows x 6 columns],\n",
       " ('E',\n",
       "  'M'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 111    E   M  14  11.000  9.456       False\n",
       " 707    E   M   1   8.511  5.992       False\n",
       " 2362   E   M   5  10.043  7.775       False\n",
       " 2365   E   M   1   9.542  7.633       False\n",
       " 2807   E   M  43  12.221  9.987       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 1563   M   E   4   7.053  5.647       False\n",
       " 2850   M   E   3  11.490  9.194       False\n",
       " 3162   M   E  30   7.370  5.946       False\n",
       " 3420   M   E  28  10.410  8.427       False\n",
       " 3452   M   E  31  11.697  9.805       False\n",
       " \n",
       " [32076 rows x 6 columns],\n",
       " ('E',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 672    E   N   77  10.263  8.856       False\n",
       " 2012   E   N    2   7.272  6.435       False\n",
       " 3880   E   N    6   8.502  7.281       False\n",
       " 4240   E   N  232   9.256  8.361       False\n",
       " 4276   E   N    1   7.140  6.077       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5732   N   E  534  11.147  9.946       False\n",
       " 5734   N   E  409  11.316  9.099       False\n",
       " 5767   N   E  537   9.736  8.091       False\n",
       " 5772   N   E  412   8.759  8.256       False\n",
       " 5789   N   E  413  10.063  8.053       False\n",
       " \n",
       " [64013 rows x 6 columns],\n",
       " ('E',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 226    E   P    1   6.681  6.071       False\n",
       " 232    E   P    2   7.598  6.016       False\n",
       " 320    E   P    6   8.654  7.058       False\n",
       " 676    E   P   21   8.991  8.037       False\n",
       " 677    E   P    4  11.588  9.970       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4482   P   E    4   9.578  8.318       False\n",
       " 4613   P   E   21  10.467  9.875       False\n",
       " 4617   P   E   17  10.523  9.587       False\n",
       " 5236   P   E    3   9.031  7.520       False\n",
       " 5409   P   E  100   8.161  7.143       False\n",
       " \n",
       " [66610 rows x 6 columns],\n",
       " ('E',\n",
       "  'Q'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 112    E   Q    8   9.203  7.422       False\n",
       " 115    E   Q    4   6.072  5.164       False\n",
       " 219    E   Q   30   9.380  8.045       False\n",
       " 221    E   Q   28  10.645  9.235       False\n",
       " 1687   E   Q   40  11.108  9.149       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1344   Q   E    3   7.848  6.519       False\n",
       " 1647   Q   E    5   9.311  7.490       False\n",
       " 2100   Q   E  102   6.460  4.599        True\n",
       " 2245   Q   E   66   8.381  6.987       False\n",
       " 2488   Q   E   68  10.154  7.655       False\n",
       " \n",
       " [56974 rows x 6 columns],\n",
       " ('E',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 28     E   R    4   6.767  5.008       False\n",
       " 40     E   R    7  13.055  9.807       False\n",
       " 1239   E   R   20   9.376  7.775       False\n",
       " 1654   E   R    3   8.872  6.532       False\n",
       " 2812   E   R   31  11.372  9.881       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5069   R   E    3   6.347  3.342        True\n",
       " 5549   R   E  118   7.987  6.232       False\n",
       " 5554   R   E    2  13.038  9.501       False\n",
       " 5684   R   E    3   4.303  2.821        True\n",
       " 5823   R   E  416   5.091  2.929        True\n",
       " \n",
       " [104653 rows x 6 columns],\n",
       " ('E',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1238   E   S   40  10.423  9.376       False\n",
       " 2364   E   S    2   8.253  7.801       False\n",
       " 2654   E   S  236   5.974  5.194       False\n",
       " 2656   E   S  234   4.354  3.724        True\n",
       " 2657   E   S  233   7.889  7.258       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5486   S   E   71   4.437  3.455        True\n",
       " 5489   S   E    5   7.752  7.581       False\n",
       " 5634   S   E    7   9.159  8.189       False\n",
       " 5877   S   E  420  10.758  9.745       False\n",
       " 5883   S   E    3   7.723  6.408       False\n",
       " \n",
       " [79370 rows x 6 columns],\n",
       " ('E',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 116    E   T    3   5.995  5.499       False\n",
       " 230    E   T    4  11.093  9.215       False\n",
       " 323    E   T    3   4.006  2.581        True\n",
       " 337    E   T    5  10.193  8.130       False\n",
       " 668    E   T   85  10.706  9.241       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4703   T   E    7  10.851  9.519       False\n",
       " 4785   T   E  288   9.831  8.803       False\n",
       " 5591   T   E  121   5.341  3.980        True\n",
       " 5602   T   E    5  11.909  9.707       False\n",
       " 5903   T   E    5  11.588  9.282       False\n",
       " \n",
       " [86477 rows x 6 columns],\n",
       " ('E',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 29     E   V    3   6.793  6.026       False\n",
       " 113    E   V    7   8.699  6.695       False\n",
       " 322    E   V    4   5.139  3.887        True\n",
       " 325    E   V    1   6.382  5.057       False\n",
       " 339    E   V    3   5.872  4.823        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1582   V   E   43   8.336  7.747       False\n",
       " 4318   V   E    2  10.309  9.157       False\n",
       " 5499   V   E  111   8.541  7.242       False\n",
       " 5500   V   E   73   8.396  7.058       False\n",
       " 5503   V   E    7   7.732  6.087       False\n",
       " \n",
       " [121235 rows x 6 columns],\n",
       " ('E',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1686   E   W    1   4.581  3.526        True\n",
       " 1694   E   W    2  10.839  9.155       False\n",
       " 4200   E   W    1  10.994  8.262       False\n",
       " 4272   E   W    8  11.599  9.943       False\n",
       " 442    E   W   57   9.724  7.978       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2661   W   E   60   9.218  5.796       False\n",
       " 2667   W   E    4  12.017  9.195       False\n",
       " 4107   W   E  281  12.118  9.838       False\n",
       " 4146   W   E  283  11.894  9.801       False\n",
       " 4158   W   E  249   7.619  4.448        True\n",
       " \n",
       " [33975 rows x 6 columns],\n",
       " ('E',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 319    E   Y   28   7.864  5.955       False\n",
       " 1683   E   Y   36  12.641  9.688       False\n",
       " 1688   E   Y   37   5.546  3.898        True\n",
       " 2664   E   Y    4  10.785  8.867       False\n",
       " 2999   E   Y    2   5.150  3.688        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4752   Y   E    9   4.910  2.613        True\n",
       " 5189   Y   E  346   8.967  6.915       False\n",
       " 5345   Y   E    4   5.682  4.266        True\n",
       " 5469   Y   E  445   8.708  6.970       False\n",
       " 5472   Y   E    3  11.223  9.000       False\n",
       " \n",
       " [73492 rows x 6 columns],\n",
       " ('F',\n",
       "  'F'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 776    F   F  121   8.305  6.987       False\n",
       " 781    F   F    4   5.197  3.889        True\n",
       " 784    F   F  123  11.050  9.232       False\n",
       " 791    F   F  114   5.014  3.386        True\n",
       " 799    F   F    2  11.967  9.632       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4031   F   F  277   6.061  3.676        True\n",
       " 4046   F   F   23  11.663  9.727       False\n",
       " 4047   F   F   13  11.470  9.617       False\n",
       " 4496   F   F   50  11.175  9.775       False\n",
       " 5855   F   F    4  10.927  8.655       False\n",
       " \n",
       " [113326 rows x 6 columns],\n",
       " ('F',\n",
       "  'H'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1571   F   H   15  11.027  8.718       False\n",
       " 1623   F   H    2  10.729  9.120       False\n",
       " 2844   F   H   24   7.650  6.800       False\n",
       " 3552   F   H  387   9.416  6.970       False\n",
       " 3718   F   H   93  11.523  9.378       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2591   H   F   75  10.076  8.511       False\n",
       " 2595   H   F   70   6.660  4.722        True\n",
       " 2602   H   F    7  10.205  8.647       False\n",
       " 2604   H   F    3   6.942  4.711        True\n",
       " 3042   H   F   32   8.910  6.774       False\n",
       " \n",
       " [42429 rows x 6 columns],\n",
       " ('F',\n",
       "  'I'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 33     F   I    3   7.782  6.411       False\n",
       " 238    F   I   26   9.637  8.482       False\n",
       " 594    F   I   33   6.798  4.523        True\n",
       " 600    F   I   22  10.360  8.318       False\n",
       " 603    F   I   13   4.816  3.178        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5108   I   F   57  10.161  8.292       False\n",
       " 5610   I   F  546   6.507  4.162        True\n",
       " 5619   I   F  119  10.156  8.336       False\n",
       " 5686   I   F  125   8.967  7.425       False\n",
       " 5876   I   F    1   7.176  5.274       False\n",
       " \n",
       " [141901 rows x 6 columns],\n",
       " ('F',\n",
       "  'K'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 234    F   K   32   9.499  7.666       False\n",
       " 237    F   K   28   7.387  5.944       False\n",
       " 595    F   K   32   7.065  4.734        True\n",
       " 608    F   K    1   9.082  6.786       False\n",
       " 1282   F   K   42  11.104  8.364       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4979   K   F  328   9.210  7.056       False\n",
       " 4988   K   F   10   9.220  6.440       False\n",
       " 5376   K   F   95  10.055  7.324       False\n",
       " 5434   K   F  109  10.230  8.555       False\n",
       " 5511   K   F  539   9.907  9.074       False\n",
       " \n",
       " [64184 rows x 6 columns],\n",
       " ('F',\n",
       "  'L'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 236    F   L   29   4.568  3.420        True\n",
       " 239    F   L   25   4.440  3.345        True\n",
       " 240    F   L   24  10.273  8.579       False\n",
       " 242    F   L   16   7.431  6.516       False\n",
       " 244    F   L   11   5.081  3.443        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4953   L   F   63  11.787  9.454       False\n",
       " 4958   L   F   50   5.228  3.834        True\n",
       " 5360   L   F   94   4.707  3.877        True\n",
       " 5570   L   F  117   7.537  6.130       False\n",
       " 5893   L   F    3   5.899  3.771        True\n",
       " \n",
       " [211881 rows x 6 columns],\n",
       " ('F',\n",
       "  'M'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 597    F   M   30   9.301  7.467       False\n",
       " 745    F   M    7  10.264  8.242       False\n",
       " 785    F   M  121   8.998  7.292       False\n",
       " 793    F   M  111  10.712  8.643       False\n",
       " 1079   F   M   57   6.868  4.313        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1560   M   F   37   5.424  3.608        True\n",
       " 1734   M   F   43   5.650  4.118        True\n",
       " 1736   M   F   38  11.432  9.377       False\n",
       " 2579   M   F    5  10.557  9.685       False\n",
       " 2583   M   F    1   8.851  7.377       False\n",
       " \n",
       " [44140 rows x 6 columns],\n",
       " ('F',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 245    F   N   10   9.251  7.143       False\n",
       " 246    F   N    8  10.916  9.232       False\n",
       " 786    F   N  120  10.501  8.805       False\n",
       " 831    F   N    3   9.473  7.362       False\n",
       " 1092   F   N    3   8.150  6.610       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2694   N   F    1   7.749  6.394       False\n",
       " 3020   N   F   27   5.284  3.794        True\n",
       " 4293   N   F  367  10.824  9.028       False\n",
       " 5455   N   F  441  10.234  7.937       False\n",
       " 5456   N   F  112  10.099  8.785       False\n",
       " \n",
       " [62089 rows x 6 columns],\n",
       " ('F',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 248    F   P    4   6.421  5.547       False\n",
       " 593    F   P   35  10.389  8.832       False\n",
       " 607    F   P    2   8.109  7.203       False\n",
       " 644    F   P   18   4.857  3.728        True\n",
       " 648    F   P    1   9.801  8.443       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4423   P   F   46   6.621  5.616       False\n",
       " 4468   P   F   49   8.698  6.862       False\n",
       " 4619   P   F    4   6.858  5.791       False\n",
       " 4811   P   F  397  11.169  9.971       False\n",
       " 5410   P   F   97   4.530  3.659        True\n",
       " \n",
       " [68974 rows x 6 columns],\n",
       " ('F',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 235    F   Q  31  12.376  9.811       False\n",
       " 241    F   Q  21  10.870  9.218       False\n",
       " 748    F   Q   2  12.058  9.524       False\n",
       " 795    F   Q   8  11.509  9.546       False\n",
       " 866    F   Q   1   9.470  7.510       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 2108   Q   F   2   7.931  7.189       False\n",
       " 2251   Q   F  42  12.402  9.661       False\n",
       " 2487   Q   F  69   5.478  3.613        True\n",
       " 2489   Q   F  67   7.349  5.646       False\n",
       " 3956   Q   F   8  10.504  8.768       False\n",
       " \n",
       " [52505 rows x 6 columns],\n",
       " ('F',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 596    F   R   31  12.762  8.943       False\n",
       " 782    F   R    3  10.049  7.920       False\n",
       " 797    F   R    5  12.556  9.040       False\n",
       " 830    F   R    4   7.231  3.963        True\n",
       " 832    F   R    2  10.168  8.535       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5396   R   F   96   7.345  4.605        True\n",
       " 5535   R   F  542   6.753  4.406        True\n",
       " 5542   R   F  454  11.720  8.989       False\n",
       " 5673   R   F  124  10.729  8.299       False\n",
       " 5833   R   F    2  11.050  8.877       False\n",
       " \n",
       " [75890 rows x 6 columns],\n",
       " ('F',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 604    F   S   12   8.161  7.029       False\n",
       " 606    F   S    6  10.623  9.902       False\n",
       " 646    F   S   15   7.776  6.547       False\n",
       " 1086   F   S   25   7.512  7.267       False\n",
       " 1280   F   S   44   4.258  2.938        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4775   S   F    2   6.900  5.578       False\n",
       " 5480   S   F  445   9.929  9.142       False\n",
       " 5482   S   F  116   6.971  6.453       False\n",
       " 5630   S   F  120   9.404  8.299       False\n",
       " 5884   S   F    2   9.869  8.844       False\n",
       " \n",
       " [85299 rows x 6 columns],\n",
       " ('F',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 642    F   T   23  11.266  9.914       False\n",
       " 746    F   T    4   7.074  5.202       False\n",
       " 778    F   T    8  11.647  9.409       False\n",
       " 783    F   T    2  10.545  9.426       False\n",
       " 794    F   T  110   8.309  7.251       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4796   T   F   17   7.942  6.076       False\n",
       " 4801   T   F    3   9.718  8.171       False\n",
       " 5583   T   F  545  11.528  9.855       False\n",
       " 5592   T   F  118   5.036  4.161        True\n",
       " 5904   T   F    4   4.737  3.683        True\n",
       " \n",
       " [95329 rows x 6 columns],\n",
       " ('F',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 32     F   V    4   7.972  6.885       False\n",
       " 598    F   V   29   3.879  3.295        True\n",
       " 602    F   V   16  10.155  8.620       False\n",
       " 643    F   V   19   7.039  5.860       False\n",
       " 777    F   V  116  11.394  9.767       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1586   V   F   23  11.555  9.362       False\n",
       " 4307   V   F  368   8.266  6.622       False\n",
       " 4310   V   F   39  11.201  9.469       False\n",
       " 5493   V   F  447  11.446  9.377       False\n",
       " 5495   V   F  118   9.180  7.087       False\n",
       " \n",
       " [162233 rows x 6 columns],\n",
       " ('F',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2847   F   W   16  11.590  9.140       False\n",
       " 2982   F   W   25  10.379  7.370       False\n",
       " 4436   F   W   22  10.607  8.341       False\n",
       " 4734   F   W   49   9.637  6.442       False\n",
       " 467    F   W   60   7.017  4.540        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4127   W   F   26  10.186  7.072       False\n",
       " 4128   W   F    3  11.899  8.690       False\n",
       " 4147   W   F  282   6.107  3.497        True\n",
       " 4169   W   F    5  11.963  9.173       False\n",
       " 4385   W   F   44   9.623  6.985       False\n",
       " \n",
       " [41097 rows x 6 columns],\n",
       " ('F',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1090   F   Y    5   4.810  3.118        True\n",
       " 1288   F   Y   24   6.965  4.406        True\n",
       " 1564   F   Y   50   8.958  5.365       False\n",
       " 1572   F   Y    2   6.817  4.754        True\n",
       " 1642   F   Y   31   9.538  7.291       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3898   Y   F    4   6.063  3.778        True\n",
       " 3934   Y   F    7   8.865  7.368       False\n",
       " 4573   Y   F  382  11.072  7.691       False\n",
       " 4594   Y   F    3   5.168  3.757        True\n",
       " 4758   Y   F    1   7.928  6.209       False\n",
       " \n",
       " [86014 rows x 6 columns],\n",
       " ('H',\n",
       "  'H'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1608   H   H   30  10.948  8.685       False\n",
       " 1611   H   H    4   7.670  6.066       False\n",
       " 4878   H   H  309  11.222  9.594       False\n",
       " 1061   H   H    1   6.531  5.467       False\n",
       " 1079   H   H    2   9.341  7.786       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1055   H   H    3   7.749  6.784       False\n",
       " 365    H   H   32  10.684  8.847       False\n",
       " 4353   H   H    4   5.403  3.418        True\n",
       " 1638   H   H    5   9.282  7.633       False\n",
       " 1845   H   H   56   8.606  7.690       False\n",
       " \n",
       " [28314 rows x 6 columns],\n",
       " ('H',\n",
       "  'I'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1385   H   I   57   6.414  4.587        True\n",
       " 1397   H   I   12   4.616  3.360        True\n",
       " 2460   H   I   27  10.505  9.001       False\n",
       " 2581   H   I  180  11.377  9.921       False\n",
       " 2589   H   I   24   5.859  4.079        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3383   I   H    1   8.406  6.372       False\n",
       " 3628   I   H   21  11.522  9.868       False\n",
       " 3747   I   H  418   8.388  6.641       False\n",
       " 4549   I   H  303  10.840  9.178       False\n",
       " 5309   I   H  133  12.271  9.386       False\n",
       " \n",
       " [50383 rows x 6 columns],\n",
       " ('H',\n",
       "  'K'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 477    H   K   54  10.575  9.279       False\n",
       " 1341   H   K   47  10.044  8.269       False\n",
       " 2462   H   K    3   5.102  3.731        True\n",
       " 4870   H   K  425  11.224  9.811       False\n",
       " 4887   H   K    4   9.558  7.061       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4354   K   H  243   7.973  5.978       False\n",
       " 4679   K   H  386   7.682  6.823       False\n",
       " 4918   K   H  488  10.404  8.873       False\n",
       " 5374   K   H  137   7.630  5.703       False\n",
       " 5426   K   H  144  11.128  9.347       False\n",
       " \n",
       " [28450 rows x 6 columns],\n",
       " ('H',\n",
       "  'L'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1382   H   L   60   7.759  5.585       False\n",
       " 1402   H   L    3   6.702  4.773        True\n",
       " 1586   H   L   23  10.756  9.573       False\n",
       " 1609   H   L   27   5.949  3.756        True\n",
       " 1610   H   L   23   9.028  8.324       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3552   L   H    6   7.943  6.160       False\n",
       " 4268   L   H  360   6.244  5.021       False\n",
       " 4521   L   H  302  11.214  9.733       False\n",
       " 5357   L   H  136   6.954  5.482       False\n",
       " 5567   L   H  159   9.274  7.939       False\n",
       " \n",
       " [77653 rows x 6 columns],\n",
       " ('H',\n",
       "  'M'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 479    H   M  12   9.147  7.683       False\n",
       " 2590   H   M  23   9.923  8.634       False\n",
       " 1058   H   M   2   5.607  4.409        True\n",
       " 1078   H   M   4   9.885  7.908       False\n",
       " 183    H   M   4   6.121  4.732        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 917    M   H  91   9.879  8.852       False\n",
       " 1730   M   H  59   9.889  8.483       False\n",
       " 1735   M   H  39   9.523  7.562       False\n",
       " 3427   M   H   8  10.242  8.685       False\n",
       " 3430   M   H   5  11.148  8.998       False\n",
       " \n",
       " [17788 rows x 6 columns],\n",
       " ('H',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 69     H   N    2   9.882  8.571       False\n",
       " 478    H   N   53   9.149  7.596       False\n",
       " 2456   H   N   32   5.158  4.140        True\n",
       " 242    H   N    2   5.674  4.348        True\n",
       " 844    H   N   19   9.638  8.641       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1497   N   H    7  10.015  8.603       False\n",
       " 1633   N   H    4  10.047  8.381       False\n",
       " 3393   N   H    1   5.755  3.831        True\n",
       " 3968   N   H   40  11.954  9.933       False\n",
       " 5417   N   H  140   9.214  8.055       False\n",
       " \n",
       " [30319 rows x 6 columns],\n",
       " ('H',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 481    H   P    5   6.982  5.668       False\n",
       " 1343   H   P    3  10.365  9.567       False\n",
       " 1394   H   P   16   8.110  7.016       False\n",
       " 2461   H   P    4  10.272  9.146       False\n",
       " 4120   H   P    2   8.337  7.305       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4412   P   H  462  10.678  9.169       False\n",
       " 4459   P   H  300   9.206  8.369       False\n",
       " 4601   P   H  378  10.370  9.425       False\n",
       " 4805   P   H  484   6.137  4.926        True\n",
       " 5404   P   H  139   8.031  7.319       False\n",
       " \n",
       " [34348 rows x 6 columns],\n",
       " ('H',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 1383   H   Q  59   6.743  5.181       False\n",
       " 4889   H   Q   2   9.411  7.755       False\n",
       " 1054   H   Q  18  10.179  7.838       False\n",
       " 58     H   Q   1   9.248  7.043       False\n",
       " 129    H   Q  14  10.550  9.367       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 1644   Q   H  51   8.367  6.352       False\n",
       " 1650   Q   H   1   9.359  7.015       False\n",
       " 2244   Q   H  67   4.204  3.482        True\n",
       " 3518   Q   H   2  10.992  8.818       False\n",
       " 3944   Q   H  50   7.025  4.784        True\n",
       " \n",
       " [25698 rows x 6 columns],\n",
       " ('H',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 68     H   R    3  11.251  9.272       False\n",
       " 2464   H   R    1   7.715  6.184       False\n",
       " 2580   H   R  196   8.001  5.754       False\n",
       " 4886   H   R    5  11.063  9.369       False\n",
       " 1057   H   R    3   8.421  6.956       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4826   R   H  485   8.128  6.263       False\n",
       " 5385   R   H  141  11.546  8.723       False\n",
       " 5388   R   H  138   5.452  3.879        True\n",
       " 5536   R   H  541   9.747  7.222       False\n",
       " 5672   R   H  166  11.950  8.841       False\n",
       " \n",
       " [39609 rows x 6 columns],\n",
       " ('H',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1340   H   S   48   9.975  9.002       False\n",
       " 1342   H   S    4   8.106  7.636       False\n",
       " 1387   H   S   55  10.317  9.538       False\n",
       " 1388   H   S   54   9.930  9.194       False\n",
       " 1391   H   S   19   6.175  5.409       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3765   S   H  419   8.102  7.190       False\n",
       " 3814   S   H  422   9.381  9.421       False\n",
       " 4133   S   H  278   8.526  7.477       False\n",
       " 4660   S   H  383   9.462  8.610       False\n",
       " 5349   S   H  135  10.206  9.216       False\n",
       " \n",
       " [41159 rows x 6 columns],\n",
       " ('H',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 480    H   T    7  10.831  9.539       False\n",
       " 482    H   T    2  10.471  9.085       False\n",
       " 2576   H   T  207   9.816  8.528       False\n",
       " 2591   H   T   22  10.688  9.077       False\n",
       " 4111   H   T  317  10.909  9.327       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1603   T   H   42   8.505  7.010       False\n",
       " 2732   T   H   10   9.778  8.533       False\n",
       " 3590   T   H    8  10.216  8.566       False\n",
       " 3734   T   H  417   7.022  5.409       False\n",
       " 4777   T   H  483   9.208  8.141       False\n",
       " \n",
       " [43551 rows x 6 columns],\n",
       " ('H',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1345   H   V    1   7.400  5.825       False\n",
       " 1396   H   V   13   5.320  3.716        True\n",
       " 1401   H   V    7   8.009  7.015       False\n",
       " 1587   H   V    3   8.510  7.248       False\n",
       " 1607   H   V   31  10.826  9.000       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5416   V   H  111   9.932  8.238       False\n",
       " 5421   V   H   56  11.493  9.923       False\n",
       " 5485   V   H   59  10.590  9.986       False\n",
       " 657    V   H    2   5.241  3.397        True\n",
       " 4300   V   H  455  10.863  9.928       False\n",
       " \n",
       " [59662 rows x 6 columns],\n",
       " ('H',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2457   H   W   31   9.096  6.106       False\n",
       " 977    H   W    4   9.962  7.533       False\n",
       " 1143   H   W   23   9.714  7.942       False\n",
       " 4331   H   W    1   7.712  5.782       False\n",
       " 4488   H   W   18   9.585  7.669       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4150   W   H  279   9.707  6.609       False\n",
       " 4201   W   H  282   9.473  8.410       False\n",
       " 4209   W   H  262  11.665  8.849       False\n",
       " 4375   W   H  295  11.044  8.762       False\n",
       " 4377   W   H  245  11.880  8.744       False\n",
       " \n",
       " [18834 rows x 6 columns],\n",
       " ('H',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1389   H   Y   35   9.462  7.509       False\n",
       " 1403   H   Y    2  11.768  9.280       False\n",
       " 2458   H   Y   30   5.641  3.341        True\n",
       " 2582   H   Y  158  11.614  9.106       False\n",
       " 2583   H   Y  110  11.015  8.907       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4364   Y   H  244   9.729  7.624       False\n",
       " 4567   Y   H  469  10.585  8.311       False\n",
       " 4578   Y   H  377   9.543  7.817       False\n",
       " 4738   Y   H  389   4.325  3.336        True\n",
       " 5327   Y   H  134  11.057  8.636       False\n",
       " \n",
       " [37513 rows x 6 columns],\n",
       " ('I',\n",
       "  'I'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 363    I   I   34  11.049  9.505       False\n",
       " 431    I   I   45   6.109  3.896        True\n",
       " 437    I   I   11   5.555  3.535        True\n",
       " 507    I   I   20   5.817  3.586        True\n",
       " 512    I   I    9   8.943  6.824       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5750   I   I   59   9.334  7.892       False\n",
       " 5757   I   I   42   5.396  3.759        True\n",
       " 5760   I   I   38   6.709  4.932        True\n",
       " 5763   I   I    4   6.905  4.432        True\n",
       " 5860   I   I  540   9.516  7.994       False\n",
       " \n",
       " [213456 rows x 6 columns],\n",
       " ('I',\n",
       "  'K'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 123    I   K   2  10.351  8.719       False\n",
       " 438    I   K  10  10.609  9.276       False\n",
       " 508    I   K  19  10.649  8.591       False\n",
       " 623    I   K   2   5.100  3.285        True\n",
       " 1145   I   K   2  10.846  8.320       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 5177   K   I   7   9.228  7.760       False\n",
       " 5178   K   I   4   4.858  3.808        True\n",
       " 5724   K   I  56  11.849  9.565       False\n",
       " 5727   K   I   7  10.859  8.177       False\n",
       " 5730   K   I   1   9.241  7.157       False\n",
       " \n",
       " [90177 rows x 6 columns],\n",
       " ('I',\n",
       "  'L'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 366    I   L    4   6.143  4.836        True\n",
       " 434    I   L   15   8.833  7.283       False\n",
       " 513    I   L    8  10.971  9.201       False\n",
       " 610    I   L   38   8.020  6.838       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5358   L   I  115  10.862  8.648       False\n",
       " 5362   L   I   92  11.211  9.845       False\n",
       " 5369   L   I   24  10.755  8.636       False\n",
       " 5371   L   I    3   7.706  5.998       False\n",
       " 5894   L   I    2   9.661  8.510       False\n",
       " \n",
       " [292716 rows x 6 columns],\n",
       " ('I',\n",
       "  'M'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 440    I   M    8   4.090  3.229        True\n",
       " 509    I   M   17   6.278  5.180       False\n",
       " 613    I   M   31  10.246  8.971       False\n",
       " 841    I   M  128  10.480  9.336       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3459   M   I   20  10.238  9.639       False\n",
       " 3461   M   I   17   5.670  3.892        True\n",
       " 3463   M   I   15   5.896  4.067        True\n",
       " 3464   M   I   10   9.185  7.798       False\n",
       " 5210   M   I    7   9.706  8.152       False\n",
       " \n",
       " [55967 rows x 6 columns],\n",
       " ('I',\n",
       "  'N'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 151    I   N   4   8.858  7.956       False\n",
       " 430    I   N  49   9.572  8.763       False\n",
       " 433    I   N  41  11.580  9.475       False\n",
       " 844    I   N   5   4.100  3.071        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 5669   N   I   4   8.427  6.402       False\n",
       " 5739   N   I   2   9.681  9.288       False\n",
       " 5783   N   I   5  11.105  9.791       False\n",
       " 5786   N   I   1   6.655  4.777        True\n",
       " 5796   N   I   2   9.295  8.937       False\n",
       " \n",
       " [80209 rows x 6 columns],\n",
       " ('I',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 368    I   P    2   7.952  7.088       False\n",
       " 435    I   P   13   8.446  8.141       False\n",
       " 444    I   P    1   6.800  6.526       False\n",
       " 515    I   P    4  10.362  9.330       False\n",
       " 517    I   P    2   8.849  7.888       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4603   P   I  301   8.270  7.882       False\n",
       " 4620   P   I    2   7.602  6.290       False\n",
       " 4814   P   I  394   7.799  6.888       False\n",
       " 4815   P   I  393   4.840  3.908        True\n",
       " 4821   P   I   16  11.923  9.859       False\n",
       " \n",
       " [85486 rows x 6 columns],\n",
       " ('I',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 120    I   Q   7   9.786  8.018       False\n",
       " 870    I   Q   2   3.721  3.084        True\n",
       " 896    I   Q   2   7.696  5.258       False\n",
       " 1136   I   Q  59  10.971  8.615       False\n",
       " 1256   I   Q  47   5.908  4.174        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 2494   Q   I   5  11.309  9.203       False\n",
       " 2496   Q   I   3   6.344  5.038       False\n",
       " 3940   Q   I  57   8.962  8.068       False\n",
       " 3942   Q   I  52   4.594  3.347        True\n",
       " 3955   Q   I  29   6.845  4.914        True\n",
       " \n",
       " [66944 rows x 6 columns],\n",
       " ('I',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 19     I   R    2  10.448  7.981       False\n",
       " 439    I   R    9   5.578  3.447        True\n",
       " 843    I   R    6   8.664  7.233       False\n",
       " 1138   I   R   56   4.325  3.119        True\n",
       " 1141   I   R   50  10.614  7.794       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5386   R   I  140   6.261  3.956        True\n",
       " 5391   R   I  117   9.105  8.069       False\n",
       " 5677   R   I   33  10.224  8.801       False\n",
       " 5822   R   I  439   9.552  6.714       False\n",
       " 5830   R   I    5  11.102  9.564       False\n",
       " \n",
       " [96318 rows x 6 columns],\n",
       " ('I',\n",
       "  'S'):      aa1 aa2  dij    dcg    daa  aa_contact\n",
       " 152    I   S    2  9.763  8.426       False\n",
       " 443    I   S    2  5.822  5.007       False\n",
       " 620    I   S   13  3.606  3.170        True\n",
       " 622    I   S   11  7.336  6.176       False\n",
       " 1146   I   S    1  5.553  4.939        True\n",
       " ...   ..  ..  ...    ...    ...         ...\n",
       " 5354   S   I    2  7.796  7.437       False\n",
       " 5475   S   I  457  6.604  6.245       False\n",
       " 5483   S   I  114  5.095  4.001        True\n",
       " 5639   S   I    1  6.772  5.991       False\n",
       " 5885   S   I    1  6.243  5.363       False\n",
       " \n",
       " [107719 rows x 6 columns],\n",
       " ('I',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 121    I   T    4   5.850  3.652        True\n",
       " 514    I   T    7   9.799  7.613       False\n",
       " 617    I   T   21   8.249  7.311       False\n",
       " 895    I   T   70  11.714  9.465       False\n",
       " 1134   I   T   61  11.076  9.285       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4705   T   I    3  11.218  9.605       False\n",
       " 4781   T   I  393   7.254  5.638       False\n",
       " 4782   T   I  392   6.858  6.195       False\n",
       " 4798   T   I   15   7.133  6.027       False\n",
       " 5905   T   I    3   7.125  6.418       False\n",
       " \n",
       " [128597 rows x 6 columns],\n",
       " ('I',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 20     I   V    1   6.208  3.823        True\n",
       " 119    I   V    8  11.534  9.639       False\n",
       " 365    I   V    9   9.710  8.469       False\n",
       " 441    I   V    7   9.477  7.784       False\n",
       " 510    I   V   16   4.200  3.439        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4305   V   I  380  11.372  8.682       False\n",
       " 4309   V   I  365   8.370  6.488       False\n",
       " 4312   V   I   37   9.251  7.285       False\n",
       " 5492   V   I  459   9.270  8.270       False\n",
       " 5496   V   I  116   7.119  4.787        True\n",
       " \n",
       " [232066 rows x 6 columns],\n",
       " ('I',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1709   I   W    3   8.755  6.497       False\n",
       " 1744   I   W    7  11.429  8.903       False\n",
       " 2045   I   W   39   6.173  4.071        True\n",
       " 2178   I   W    4  11.539  9.272       False\n",
       " 2693   I   W    1   8.786  6.992       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4164   W   I  239  11.989  8.889       False\n",
       " 4168   W   I  190   9.398  8.029       False\n",
       " 4200   W   I  357  10.792  9.572       False\n",
       " 4204   W   I  278   5.392  3.637        True\n",
       " 4208   W   I  272  12.722  9.631       False\n",
       " \n",
       " [47374 rows x 6 columns],\n",
       " ('I',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 364    I   Y   33  10.666  9.390       False\n",
       " 369    I   Y    1   8.467  5.909       False\n",
       " 432    I   Y   44   9.884  8.645       False\n",
       " 436    I   Y   12   5.866  3.582        True\n",
       " 897    I   Y    1   6.341  5.723       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5182   Y   I  478  10.746  9.386       False\n",
       " 5344   Y   I    5  10.017  8.420       False\n",
       " 5348   Y   I    1   5.600  4.092        True\n",
       " 5463   Y   I  455   5.774  3.816        True\n",
       " 5470   Y   I  112  10.993  8.913       False\n",
       " \n",
       " [105353 rows x 6 columns],\n",
       " ('K',\n",
       "  'K'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 107    K   K    4   4.448  2.789        True\n",
       " 253    K   K   33   9.211  8.066       False\n",
       " 255    K   K   29  10.965  9.342       False\n",
       " 1121   K   K    4   9.954  8.474       False\n",
       " 3042   K   K  313  10.430  9.056       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4993   K   K    2  10.492  8.626       False\n",
       " 5180   K   K    2  11.353  9.107       False\n",
       " 5251   K   K   10  11.136  9.394       False\n",
       " 5720   K   K   64   8.675  6.191       False\n",
       " 5725   K   K   54   7.835  6.390       False\n",
       " \n",
       " [69340 rows x 6 columns],\n",
       " ('K',\n",
       "  'L'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 139    K   L   2  10.602  8.750       False\n",
       " 140    K   L   1   6.989  6.309       False\n",
       " 254    K   L  30   7.384  6.357       False\n",
       " 256    K   L  26  11.225  9.653       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 5201   L   K   4   8.059  6.454       False\n",
       " 5202   L   K   2  11.533  9.144       False\n",
       " 5244   L   K   4  12.296  9.641       False\n",
       " 5573   L   K  22   6.205  4.501        True\n",
       " 5888   L   K  60  12.032  9.544       False\n",
       " \n",
       " [125866 rows x 6 columns],\n",
       " ('K',\n",
       "  'M'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 1122   K   M   1   9.249  7.446       False\n",
       " 1950   K   M   2  10.254  8.837       False\n",
       " 5358   K   M  10  11.156  9.731       False\n",
       " 286    K   M   1  10.228  8.308       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 914    M   K  94   9.683  8.269       False\n",
       " 202    M   K   3   9.716  7.337       False\n",
       " 3166   M   K  23  10.796  8.309       False\n",
       " 3467   M   K   2  10.635  9.255       False\n",
       " 5212   M   K   3   7.141  4.379        True\n",
       " \n",
       " [25381 rows x 6 columns],\n",
       " ('K',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 1103   K   N    4   9.690  8.990       False\n",
       " 1105   K   N    2  10.470  9.602       False\n",
       " 2255   K   N  166   8.379  6.924       False\n",
       " 2266   K   N    2   7.942  7.323       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5448   N   K  524  11.300  8.585       False\n",
       " 5666   N   K   61  11.261  8.910       False\n",
       " 5740   N   K    1   8.105  7.074       False\n",
       " 5778   N   K   58   5.062  3.931        True\n",
       " 5784   N   K    4   6.348  4.325        True\n",
       " \n",
       " [58550 rows x 6 columns],\n",
       " ('K',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 371    K   P    3   7.651  6.611       False\n",
       " 580    K   P   34  10.287  8.892       False\n",
       " 591    K   P    1   9.969  8.402       False\n",
       " 1104   K   P    3   9.185  8.616       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4479   P   K    7  10.840  9.353       False\n",
       " 4597   P   K  401  10.252  9.519       False\n",
       " 4808   P   K  454   7.580  6.114       False\n",
       " 5237   P   K    2   8.561  7.113       False\n",
       " 5414   P   K    2   9.746  7.611       False\n",
       " \n",
       " [51493 rows x 6 columns],\n",
       " ('K',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 90     K   Q   1  10.166  7.960       False\n",
       " 106    K   Q   7   9.999  8.586       False\n",
       " 108    K   Q   3   5.397  3.256        True\n",
       " 252    K   Q  34  11.108  9.623       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 1937   Q   K   3   8.600  6.645       False\n",
       " 2249   Q   K  51  10.382  8.818       False\n",
       " 2483   Q   K  75   8.456  7.299       False\n",
       " 3515   Q   K   7  10.569  8.457       False\n",
       " 3950   Q   K  44   6.506  5.172       False\n",
       " \n",
       " [45783 rows x 6 columns],\n",
       " ('K',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 1120   K   R   54  12.336  9.374       False\n",
       " 2073   K   R   67   7.616  5.418       False\n",
       " 2079   K   R    2  13.518  9.650       False\n",
       " 2254   K   R  167  10.837  8.336       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5539   R   K  537  10.637  9.065       False\n",
       " 5541   R   K  511  13.367  9.670       False\n",
       " 5553   R   K    3   6.414  5.052       False\n",
       " 5681   R   K   29   6.153  3.885        True\n",
       " 5828   R   K    8  11.526  9.487       False\n",
       " \n",
       " [58094 rows x 6 columns],\n",
       " ('K',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 587    K   S    9   4.391  3.881        True\n",
       " 588    K   S    8   9.402  8.785       False\n",
       " 590    K   S    5   7.398  6.371       False\n",
       " 882    K   S    2   8.920  7.757       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3197   S   K   32   8.690  8.260       False\n",
       " 3337   S   K  111   9.475  8.038       False\n",
       " 4667   S   K    2  11.352  9.592       False\n",
       " 5264   S   K    2  10.317  8.581       False\n",
       " 5632   S   K   25   8.709  7.604       False\n",
       " \n",
       " [66234 rows x 6 columns],\n",
       " ('K',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 136    K   T    7  11.478  9.406       False\n",
       " 575    K   T   40   9.086  8.603       False\n",
       " 583    K   T   19  11.761  9.933       False\n",
       " 589    K   T    6   9.888  8.714       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4691   T   K  292   9.194  7.514       False\n",
       " 4697   T   K  285   9.896  9.122       False\n",
       " 4706   T   K    1   8.462  6.753       False\n",
       " 5596   T   K   56  10.656  9.147       False\n",
       " 5900   T   K   61   9.822  8.506       False\n",
       " \n",
       " [71970 rows x 6 columns],\n",
       " ('K',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 574    K   V   41   8.829  7.759       False\n",
       " 577    K   V   38   9.973  8.800       False\n",
       " 1100   K   V    7  10.575  9.832       False\n",
       " 1753   K   V    4   6.213  4.416        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 194    V   K    2   5.445  3.846        True\n",
       " 1223   V   K   27   9.722  8.210       False\n",
       " 2918   V   K    3   8.523  6.484       False\n",
       " 4301   V   K  386  10.930  9.602       False\n",
       " 5502   V   K    9   9.168  7.902       False\n",
       " \n",
       " [99585 rows x 6 columns],\n",
       " ('K',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 2076   K   W   42  10.656  8.157       False\n",
       " 2410   K   W   28  10.956  8.388       False\n",
       " 5348   K   W  221  11.196  8.952       False\n",
       " 85     K   W    1   8.782  6.495       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1917   W   K    1  11.098  8.145       False\n",
       " 2651   W   K   74  10.863  8.154       False\n",
       " 2668   W   K    2   4.428  3.531        True\n",
       " 4157   W   K  250  12.640  9.655       False\n",
       " 4391   W   K    2   8.447  7.101       False\n",
       " \n",
       " [25023 rows x 6 columns],\n",
       " ('K',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 1101   K   Y    6   9.449  7.433       False\n",
       " 2263   K   Y   81  10.117  6.971       False\n",
       " 2411   K   Y   27  10.104  7.975       False\n",
       " 2414   K   Y    3   9.146  6.196       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5193   Y   K    1  11.622  8.330       False\n",
       " 5329   Y   K  128   4.587  3.851        True\n",
       " 5340   Y   K   18  11.295  9.536       False\n",
       " 5342   Y   K    8   9.729  7.846       False\n",
       " 5461   Y   K  526  11.811  8.933       False\n",
       " \n",
       " [62240 rows x 6 columns],\n",
       " ('L',\n",
       "  'L'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 126    L   L    4   5.087  3.707        True\n",
       " 131    L   L    5  10.511  9.511       False\n",
       " 135    L   L    1   8.752  7.841       False\n",
       " 156    L   L   13   9.812  8.468       False\n",
       " 158    L   L    9   5.365  4.286        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5370   L   L    4   9.173  8.333       False\n",
       " 5572   L   L   23   8.238  7.547       False\n",
       " 5886   L   L  417  10.390  8.813       False\n",
       " 5887   L   L   63  10.909  8.797       False\n",
       " 5891   L   L   56   7.523  6.928       False\n",
       " \n",
       " [479542 rows x 6 columns],\n",
       " ('L',\n",
       "  'M'):      aa1 aa2  dij    dcg    daa  aa_contact\n",
       " 461    L   M    9  7.898  6.994       False\n",
       " 724    L   M    4  4.311  3.560        True\n",
       " 740    L   M  104  9.847  8.559       False\n",
       " 1967   L   M    3  5.181  3.639        True\n",
       " 1985   L   M    4  5.646  4.481        True\n",
       " ...   ..  ..  ...    ...    ...         ...\n",
       " 3422   M   L   20  9.545  8.199       False\n",
       " 3426   M   L   10  9.820  8.684       False\n",
       " 3457   M   L   23  5.222  4.079        True\n",
       " 5208   M   L   71  5.762  4.369        True\n",
       " 5214   M   L    1  8.183  6.866       False\n",
       " \n",
       " [82706 rows x 6 columns],\n",
       " ('L',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 159    L   N    6   6.488  5.236       False\n",
       " 181    L   N   11   9.846  8.517       False\n",
       " 186    L   N    3  10.356  9.048       False\n",
       " 445    L   N   50   9.755  8.938       False\n",
       " 449    L   N   42   9.971  7.795       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5780   N   L   54   8.295  6.481       False\n",
       " 5781   N   L   40  10.739  9.467       False\n",
       " 5790   N   L  411   8.745  7.346       False\n",
       " 5791   N   L   55  11.013  9.755       False\n",
       " 5792   N   L   41   9.149  8.080       False\n",
       " \n",
       " [109550 rows x 6 columns],\n",
       " ('L',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 304    L   P    1   7.357  6.836       False\n",
       " 331    L   P    7  10.513  9.599       False\n",
       " 452    L   P   23  11.034  9.897       False\n",
       " 457    L   P   14   7.224  6.775       False\n",
       " 684    L   P   22   9.211  8.176       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4809   P   L  416   4.908  4.008        True\n",
       " 4820   P   L   17  10.886  9.434       False\n",
       " 5234   P   L    5  10.293  8.989       False\n",
       " 5403   P   L  144   8.022  7.686       False\n",
       " 5413   P   L    3   7.838  7.118       False\n",
       " \n",
       " [134487 rows x 6 columns],\n",
       " ('L',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 102    L   Q   4   9.032  8.466       False\n",
       " 104    L   Q   2   9.842  8.316       False\n",
       " 130    L   Q   7   8.905  7.213       False\n",
       " 160    L   Q   5   9.673  7.386       False\n",
       " 182    L   Q  10   9.675  8.531       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 1277   Q   L   2   9.990  9.039       False\n",
       " 2107   Q   L   8   7.636  6.157       False\n",
       " 2493   Q   L   7   9.453  7.097       False\n",
       " 3941   Q   L  55   8.704  6.859       False\n",
       " 3960   Q   L   2  10.328  8.927       False\n",
       " \n",
       " [106412 rows x 6 columns],\n",
       " ('L',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 460    L   R   10   8.599  7.658       False\n",
       " 1984   L   R    7   9.308  7.053       False\n",
       " 2016   L   R   60   9.230  8.182       False\n",
       " 2153   L   R   58  12.966  9.468       False\n",
       " 2194   L   R   81   8.135  7.283       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5682   R   L    7   8.752  7.128       False\n",
       " 5824   R   L  414   4.471  3.987        True\n",
       " 5825   R   L  412  10.368  7.869       False\n",
       " 5826   R   L   58  10.909  8.892       False\n",
       " 5827   R   L   51  12.600  9.775       False\n",
       " \n",
       " [158574 rows x 6 columns],\n",
       " ('L',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 161    L   S    4   9.007  8.140       False\n",
       " 525    L   S    1   8.536  8.206       False\n",
       " 686    L   S   19   7.199  6.173       False\n",
       " 1359   L   S   14   9.283  8.114       False\n",
       " 1409   L   S   18  10.124  9.552       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5631   S   L   26   9.760  8.664       False\n",
       " 5637   S   L    3   5.070  4.189        True\n",
       " 5878   S   L  418   9.699  9.232       False\n",
       " 5879   S   L  416  10.140  9.996       False\n",
       " 5880   S   L   55  10.064  9.616       False\n",
       " \n",
       " [158612 rows x 6 columns],\n",
       " ('L',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 105    L   T    1   7.982  7.383       False\n",
       " 125    L   T    5  10.327  8.451       False\n",
       " 333    L   T    4   7.502  6.649       False\n",
       " 682    L   T   27   8.833  8.451       False\n",
       " 690    L   T    3   6.824  5.952       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5606   T   L    1   7.039  5.803       False\n",
       " 5897   T   L  418   7.280  6.221       False\n",
       " 5899   T   L   64  10.308  8.163       False\n",
       " 5902   T   L   57  10.314  8.390       False\n",
       " 5907   T   L    1   5.123  3.343        True\n",
       " \n",
       " [185791 rows x 6 columns],\n",
       " ('L',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 303    L   V    2   9.018  7.346       False\n",
       " 330    L   V    8  11.202  9.278       False\n",
       " 332    L   V    5   3.583  3.454        True\n",
       " 335    L   V    2   9.489  8.971       False\n",
       " 451    L   V   24  10.957  8.915       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1587   V   L   11   7.081  6.611       False\n",
       " 2917   V   L    4   7.866  6.650       False\n",
       " 4303   V   L  383   8.719  8.109       False\n",
       " 4306   V   L  371   9.412  7.444       False\n",
       " 4317   V   L    3   9.686  7.973       False\n",
       " \n",
       " [344364 rows x 6 columns],\n",
       " ('L',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2111   L   W   46   7.724  7.197       False\n",
       " 2157   L   W   52   9.451  8.023       False\n",
       " 2163   L   W    3   5.302  3.379        True\n",
       " 2201   L   W   56  10.569  8.781       False\n",
       " 2207   L   W    7   8.605  6.044       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4154   W   L  255  10.709  7.690       False\n",
       " 4156   W   L  251   7.319  4.782        True\n",
       " 4167   W   L  192  11.902  9.691       False\n",
       " 4211   W   L  258  10.151  7.347       False\n",
       " 4213   W   L  254  11.602  9.975       False\n",
       " \n",
       " [74182 rows x 6 columns],\n",
       " ('L',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 163    L   Y    1   6.683  3.886        True\n",
       " 183    L   Y    6   8.860  7.091       False\n",
       " 300    L   Y   23  10.420  7.843       False\n",
       " 327    L   Y   29   6.383  5.133       False\n",
       " 447    L   Y   45   5.525  3.598        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4734   Y   L  413  11.519  9.547       False\n",
       " 4747   Y   L   29   5.695  4.092        True\n",
       " 5185   Y   L  353   5.394  4.129        True\n",
       " 5335   Y   L   86   7.397  6.105       False\n",
       " 5347   Y   L    2  10.189  8.765       False\n",
       " \n",
       " [153259 rows x 6 columns],\n",
       " ('M',\n",
       "  'M'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1107   M   M   61   9.108  6.700       False\n",
       " 2358   M   M    4   8.923  7.501       False\n",
       " 5104   M   M  238  10.638  8.755       False\n",
       " 928    M   M   19   8.219  7.389       False\n",
       " 1034   M   M   77   9.938  8.559       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3160   M   M   32   6.599  4.961        True\n",
       " 3164   M   M   27   6.738  4.277        True\n",
       " 3418   M   M   31  11.597  9.961       False\n",
       " 3450   M   M   34   9.069  7.935       False\n",
       " 3466   M   M    3   5.231  3.657        True\n",
       " \n",
       " [22972 rows x 6 columns],\n",
       " ('M',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 273    M   N   13   8.864  8.146       False\n",
       " 383    M   N   41   9.703  7.618       False\n",
       " 5107   M   N  121  11.000  8.967       False\n",
       " 935    M   N    2   6.502  5.329       False\n",
       " 535    M   N   40   8.598  7.812       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4014   N   M   48  11.141  9.430       False\n",
       " 4015   N   M   45  10.852  9.494       False\n",
       " 5125   N   M  298  10.522  9.423       False\n",
       " 5258   N   M    8  10.026  9.064       False\n",
       " 5294   N   M   12  10.406  9.418       False\n",
       " \n",
       " [25045 rows x 6 columns],\n",
       " ('M',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 275    M   P    7  10.460  9.856       False\n",
       " 693    M   P   23  11.319  9.764       False\n",
       " 1919   M   P   74   7.436  6.740       False\n",
       " 1028   M   P  142  10.004  9.002       False\n",
       " 562    M   P   24   9.224  8.204       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5559   P   M   50   8.400  7.281       False\n",
       " 5031   P   M   23  10.552  9.628       False\n",
       " 5064   P   M   28   6.294  5.020       False\n",
       " 5297   P   M    1   5.290  4.572        True\n",
       " 5235   P   M    4  10.561  9.020       False\n",
       " \n",
       " [27413 rows x 6 columns],\n",
       " ('M',\n",
       "  'Q'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1113   M   Q   33   6.557  4.803        True\n",
       " 1923   M   Q   63  10.689  8.954       False\n",
       " 5108   M   Q  105  10.777  9.672       False\n",
       " 5119   M   Q   15   4.986  3.667        True\n",
       " 916    M   Q  114  10.676  9.122       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 941    Q   M    3   7.956  6.064       False\n",
       " 3514   Q   M    8  10.875  9.638       False\n",
       " 3516   Q   M    5  10.233  8.975       False\n",
       " 3949   Q   M   45   4.657  3.165        True\n",
       " 3952   Q   M   42   9.358  7.849       False\n",
       " \n",
       " [21744 rows x 6 columns],\n",
       " ('M',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 388    M   R    1   8.636  6.807       False\n",
       " 1111   M   R   53  10.158  7.443       False\n",
       " 1938   M   R    3   8.837  6.272       False\n",
       " 2101   M   R    4   6.046  3.386        True\n",
       " 2329   M   R  173  10.948  9.551       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3507   R   M    7   9.515  7.627       False\n",
       " 3508   R   M    4   5.632  3.523        True\n",
       " 4086   R   M  242  12.335  9.840       False\n",
       " 5062   R   M  295   8.867  7.798       False\n",
       " 5390   R   M  133  10.254  8.023       False\n",
       " \n",
       " [31340 rows x 6 columns],\n",
       " ('M',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 279    M   S    1   4.064  3.693        True\n",
       " 1918   M   S   75   9.700  8.975       False\n",
       " 1921   M   S   68   9.742  8.779       False\n",
       " 1928   M   S   55   6.314  5.630       False\n",
       " 1936   M   S    5  10.633  9.402       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3342   S   M   18   9.977  8.584       False\n",
       " 3715   S   M  216  10.731  9.481       False\n",
       " 3906   S   M   42  10.149  9.241       False\n",
       " 4770   S   M  283   8.051  7.480       False\n",
       " 5261   S   M    9  10.523  9.733       False\n",
       " \n",
       " [33355 rows x 6 columns],\n",
       " ('M',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 695    M   T    4  11.441  9.695       False\n",
       " 1108   M   T   58   9.601  7.410       False\n",
       " 1939   M   T    2  10.355  9.158       False\n",
       " 2102   M   T    3   6.853  5.689       False\n",
       " 2359   M   T    3   9.918  8.039       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3614   T   M   15   9.686  7.919       False\n",
       " 3615   T   M   12  10.891  9.351       False\n",
       " 3986   T   M   47   5.781  3.712        True\n",
       " 3988   T   M   44   8.423  6.191       False\n",
       " 4786   T   M  284  10.534  9.123       False\n",
       " \n",
       " [38445 rows x 6 columns],\n",
       " ('M',\n",
       "  'V'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 45     M   V   7  10.060  8.926       False\n",
       " 1115   M   V  10   8.138  6.794       False\n",
       " 1920   M   V  71   6.645  6.103       False\n",
       " 1935   M   V   7  11.650  9.750       False\n",
       " 1937   M   V   4   6.447  4.625        True\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 252    V   M   7   9.323  8.309       False\n",
       " 270    V   M  10   5.448  3.940        True\n",
       " 977    V   M  95   4.795  3.987        True\n",
       " 2915   V   M  12   5.530  3.958        True\n",
       " 2916   V   M   7   9.081  7.742       False\n",
       " \n",
       " [64249 rows x 6 columns],\n",
       " ('M',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2096   M   W   44   5.918  3.498        True\n",
       " 566    M   W    3   5.190  3.784        True\n",
       " 2505   M   W  160  11.355  9.120       False\n",
       " 4422   M   W   10   5.962  4.142        True\n",
       " 643    M   W   14   6.436  3.765        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 221    W   M    1   8.259  6.054       False\n",
       " 418    W   M   34   5.990  3.327        True\n",
       " 1912   W   M   21   5.087  3.354        True\n",
       " 2646   W   M   94  12.082  9.569       False\n",
       " 4162   W   M  245   6.764  4.167        True\n",
       " \n",
       " [16245 rows x 6 columns],\n",
       " ('M',\n",
       "  'Y'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
       " 385    M   Y   4   9.906  7.734       False\n",
       " 1116   M   Y   9   7.491  6.017       False\n",
       " 1924   M   Y  60   8.577  7.275       False\n",
       " 2339   M   Y   5  10.946  8.233       False\n",
       " 2341   M   Y   3   8.075  6.431       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 3641   Y   M  48  10.473  8.255       False\n",
       " 3652   Y   M  17  10.759  8.990       False\n",
       " 3892   Y   M  41   8.200  6.669       False\n",
       " 3931   Y   M  44   9.602  7.393       False\n",
       " 5341   Y   M  15   7.892  6.273       False\n",
       " \n",
       " [33500 rows x 6 columns],\n",
       " ('N',\n",
       "  'N'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 197    N   N    2   8.114  6.838       False\n",
       " 1055   N   N    4   7.882  6.737       False\n",
       " 1077   N   N    2   4.778  3.144        True\n",
       " 2921   N   N  237   6.543  4.852        True\n",
       " 3264   N   N  274   7.424  5.384       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5782   N   N    7  10.365  8.864       False\n",
       " 5785   N   N    3   7.576  6.516       False\n",
       " 5793   N   N    8  10.762  9.917       False\n",
       " 5795   N   N    4   4.338  3.722        True\n",
       " 5797   N   N    1   7.825  6.963       False\n",
       " \n",
       " [60962 rows x 6 columns],\n",
       " ('N',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 988    N   P   73   8.027  7.532       False\n",
       " 1000   N   P    7   8.386  7.408       False\n",
       " 1044   N   P   77   8.856  7.027       False\n",
       " 1069   N   P   79  11.596  9.816       False\n",
       " 1078   N   P    1   5.608  5.153       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4414   P   N  388   6.774  5.892       False\n",
       " 4428   P   N    8   9.856  8.456       False\n",
       " 4608   P   N  278   9.748  8.833       False\n",
       " 4614   P   N   20   7.945  6.452       False\n",
       " 4807   P   N  456   9.272  8.950       False\n",
       " \n",
       " [52101 rows x 6 columns],\n",
       " ('N',\n",
       "  'Q'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 171    N   Q    1   4.697  3.672        True\n",
       " 190    N   Q   11   7.847  7.206       False\n",
       " 193    N   Q   23  11.368  9.255       False\n",
       " 196    N   Q   13   9.001  7.555       False\n",
       " 998    N   Q   15   6.093  4.274        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2495   Q   N    4   4.636  2.709        True\n",
       " 3511   Q   N  240   8.347  7.121       False\n",
       " 3943   Q   N   51   9.370  8.066       False\n",
       " 3945   Q   N   49  11.062  9.278       False\n",
       " 3951   Q   N   43   9.922  8.526       False\n",
       " \n",
       " [43870 rows x 6 columns],\n",
       " ('N',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 67     N   R    1   8.172  5.831       False\n",
       " 810    N   R    1   8.233  7.135       False\n",
       " 1058   N   R    1  11.432  8.573       False\n",
       " 1075   N   R   48  12.033  9.900       False\n",
       " 2245   N   R   84   8.248  6.857       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5685   R   N    1   8.920  6.020       False\n",
       " 5819   R   N  542   9.962  7.105       False\n",
       " 5829   R   N    7   7.538  5.009       False\n",
       " 5831   R   N    4   6.664  5.727       False\n",
       " 5832   R   N    3   5.158  3.006        True\n",
       " \n",
       " [57913 rows x 6 columns],\n",
       " ('N',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 990    N   S   70   7.992  6.834       False\n",
       " 997    N   S   18   8.176  7.727       False\n",
       " 1794   N   S    1   5.052  4.811        True\n",
       " 2121   N   S    1   8.467  8.058       False\n",
       " 2707   N   S   13   5.564  4.676        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5474   S   N  458   7.442  6.337       False\n",
       " 5478   S   N  453   8.511  8.037       False\n",
       " 5490   S   N    4   4.092  4.030        True\n",
       " 5509   S   N   13   7.222  6.443       False\n",
       " 5881   S   N    7  10.543  9.870       False\n",
       " \n",
       " [67074 rows x 6 columns],\n",
       " ('N',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 710    N   T   89   8.548  7.785       False\n",
       " 714    N   T    6   9.849  9.252       False\n",
       " 996    N   T   47  10.446  9.617       False\n",
       " 1002   N   T    4   6.919  6.461       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3473   T   N    3   6.464  5.305       False\n",
       " 4003   T   N    1   7.386  6.915       False\n",
       " 4695   T   N  287   7.328  5.730       False\n",
       " 5600   T   N   20  11.117  9.785       False\n",
       " 5896   T   N  419   8.597  7.496       False\n",
       " \n",
       " [71963 rows x 6 columns],\n",
       " ('N',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 987    N   V   74   9.788  8.964       False\n",
       " 1001   N   V    6   8.383  7.801       False\n",
       " 1056   N   V    3   7.455  6.666       False\n",
       " 1076   N   V    5  10.784  9.457       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1265   V   N    2   8.262  6.157       False\n",
       " 4304   V   N  381   9.835  8.276       False\n",
       " 4315   V   N    5  10.160  8.985       False\n",
       " 4319   V   N    1   6.377  5.123       False\n",
       " 5504   V   N    6   5.182  4.578        True\n",
       " \n",
       " [89850 rows x 6 columns],\n",
       " ('N',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2925   N   W   21  11.218  8.550       False\n",
       " 3268   N   W   58  10.044  7.189       False\n",
       " 894    N   W  102   8.680  6.762       False\n",
       " 713    N   W   18  11.047  8.625       False\n",
       " 714    N   W    6   9.737  6.889       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2655   W   N   69  10.568  9.377       False\n",
       " 4155   W   N  252   5.371  2.875        True\n",
       " 4161   W   N  246  11.347  9.608       False\n",
       " 4166   W   N  195  10.472  8.665       False\n",
       " 4212   W   N  255   7.371  5.002       False\n",
       " \n",
       " [27330 rows x 6 columns],\n",
       " ('N',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 1057   N   Y    2  10.824  8.902       False\n",
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       " 2701   N   Y   40  11.256  9.587       False\n",
       " 2702   N   Y   38   7.852  5.856       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5343   Y   N    7   9.208  7.280       False\n",
       " 5346   Y   N    3   7.155  4.599        True\n",
       " 5462   Y   N  456   7.902  6.375       False\n",
       " 5465   Y   N  451   5.675  3.713        True\n",
       " 5473   Y   N    2   6.107  4.485        True\n",
       " \n",
       " [60407 rows x 6 columns],\n",
       " ('P',\n",
       "  'P'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 488    P   P    6   3.557  3.416        True\n",
       " 504    P   P    2   8.382  7.576       False\n",
       " 634    P   P   19  10.329  9.383       False\n",
       " 636    P   P   17   9.709  8.908       False\n",
       " 937    P   P   66   7.816  7.770       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4483   P   P    3   8.506  7.804       False\n",
       " 4615   P   P   19   3.905  3.501        True\n",
       " 4812   P   P  396   7.229  6.606       False\n",
       " 4819   P   P   63   5.824  4.794        True\n",
       " 5406   P   P  110   4.147  3.929        True\n",
       " \n",
       " [64204 rows x 6 columns],\n",
       " ('P',\n",
       "  'Q'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 572    P   Q   3  10.095  8.741       False\n",
       " 940    P   Q   8   7.725  5.890       False\n",
       " 1064   P   Q  20   9.237  7.691       False\n",
       " 1183   P   Q  39   9.087  8.453       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
       " 434    Q   P  67   7.997  7.312       False\n",
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       " 935    Q   P  96  11.050  9.807       False\n",
       " 940    Q   P   4   9.268  8.755       False\n",
       " \n",
       " [45562 rows x 6 columns],\n",
       " ('P',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 573    P   R    1   4.445  3.718        True\n",
       " 835    P   R    5  10.055  7.601       False\n",
       " 837    P   R    3   9.263  7.259       False\n",
       " 1067   P   R    2  10.486  8.045       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 5058   R   P  341   9.583  7.980       False\n",
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       " 5550   R   P   18  11.599  8.429       False\n",
       " \n",
       " [68431 rows x 6 columns],\n",
       " ('P',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 422    P   S   46  10.415  9.662       False\n",
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       " 571    P   S    4   6.925  6.516       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
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       " 5487   S   P   70   4.890  4.355        True\n",
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       " 5633   S   P   23   9.051  8.962       False\n",
       " \n",
       " [66896 rows x 6 columns],\n",
       " ('P',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 345    P   T    6   9.687  8.153       False\n",
       " 428    P   T    2   7.749  6.346       False\n",
       " 486    P   T    8   6.879  5.744       False\n",
       " 490    P   T    3  10.071  8.869       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4800   T   P   13  10.087  8.370       False\n",
       " 5586   T   P  131   4.743  4.235        True\n",
       " 5589   T   P  123  10.351  9.095       False\n",
       " 5599   T   P   21   4.466  3.247        True\n",
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       " \n",
       " [74338 rows x 6 columns],\n",
       " ('P',\n",
       "  'V'):      aa1 aa2 dij     dcg    daa  aa_contact\n",
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       " 505    P   V   1   5.041  4.337        True\n",
       " 566    P   V  37  10.441  9.520       False\n",
       " ...   ..  ..  ..     ...    ...         ...\n",
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       " 5501   V   P  72  10.115  8.732       False\n",
       " \n",
       " [105406 rows x 6 columns],\n",
       " ('P',\n",
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       " 680    P   W    7  10.309  8.277       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
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       " 2660   W   P   61   5.912  3.574        True\n",
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       " 4202   W   P  281  10.801  9.806       False\n",
       " \n",
       " [31291 rows x 6 columns],\n",
       " ('P',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " ...   ..  ..  ...     ...    ...         ...\n",
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       " 5468   Y   P  447   3.785  3.407        True\n",
       " 5471   Y   P   68  11.143  9.618       False\n",
       " \n",
       " [64309 rows x 6 columns],\n",
       " ('Q',\n",
       "  'Q'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 94     Q   Q    2  11.361  9.526       False\n",
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       " 5430   Q   Q  407   3.761  3.180        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1026   Q   Q    4   8.037  6.028       False\n",
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       " 2098   Q   Q  104   4.063  2.857        True\n",
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       " 3513   Q   Q  238  11.060  9.615       False\n",
       " \n",
       " [42298 rows x 6 columns],\n",
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       " 4311   Q   R   40  11.578  9.963       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
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       " \n",
       " [54269 rows x 6 columns],\n",
       " ('Q',\n",
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       " 1348   Q   S    5   6.705  6.344       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
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       " \n",
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       " ('Q',\n",
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       " ...   ..  ..  ...     ...    ...         ...\n",
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       " \n",
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       " ('Q',\n",
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       " ...   ..  ..  ...     ...    ...         ...\n",
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       " 1584   V   Q   40   4.645  4.165        True\n",
       " \n",
       " [78648 rows x 6 columns],\n",
       " ('Q',\n",
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       " ...   ..  ..  ...     ...    ...         ...\n",
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       " \n",
       " [23726 rows x 6 columns],\n",
       " ('Q',\n",
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       " 3666   Q   Y    5   3.672  3.327        True\n",
       " 4830   Q   Y  220   7.260  5.619       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
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       " \n",
       " [48518 rows x 6 columns],\n",
       " ('R',\n",
       "  'R'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 2757   R   R  210   7.854  5.716       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
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       " \n",
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       " ('R',\n",
       "  'S'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " ...   ..  ..  ...     ...    ...         ...\n",
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       " 5882   S   R    4   8.500  6.566       False\n",
       " \n",
       " [77570 rows x 6 columns],\n",
       " ('R',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 819    R   T    7  10.869  8.647       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3674   T   R  332   3.701  3.108        True\n",
       " 3990   T   R   40   9.488  7.750       False\n",
       " 4694   T   R  289   9.703  8.081       False\n",
       " 5598   T   R   22  10.140  7.723       False\n",
       " 5604   T   R    3   8.590  6.104       False\n",
       " \n",
       " [82751 rows x 6 columns],\n",
       " ('R',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
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       " 1627   R   V    4   5.409  3.738        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 758    V   R   45   9.594  8.678       False\n",
       " 1261   V   R   34   5.348  3.479        True\n",
       " 1589   V   R    7  12.055  9.206       False\n",
       " 1590   V   R    2  12.138  8.358       False\n",
       " 4221   V   R  277   8.379  6.549       False\n",
       " \n",
       " [119685 rows x 6 columns],\n",
       " ('R',\n",
       "  'W'):      aa1 aa2  dij     dcg     daa  aa_contact\n",
       " 2055   R   W   40   6.596   3.862        True\n",
       " 4411   R   W   20  12.366   9.345       False\n",
       " 4629   R   W   42  13.006   9.842       False\n",
       " 5170   R   W   70  11.436   8.586       False\n",
       " 132    R   W   11   5.116   3.799        True\n",
       " ...   ..  ..  ...     ...     ...         ...\n",
       " 4160   W   R  247  12.149  10.000       False\n",
       " 4170   W   R    3  11.342   8.689       False\n",
       " 4205   W   R  276   7.876   5.354       False\n",
       " 4373   W   R  383   7.392   4.766        True\n",
       " 4386   W   R   19  10.074   8.280       False\n",
       " \n",
       " [33533 rows x 6 columns],\n",
       " ('R',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 375    R   Y   35  12.086  9.292       False\n",
       " 380    R   Y    3   5.800  3.922        True\n",
       " 1043   R   Y    1   9.990  6.374       False\n",
       " 1798   R   Y   50   5.680  4.570        True\n",
       " 2442   R   Y   29   6.684  4.814        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4334   Y   R  380  11.785  9.340       False\n",
       " 4336   Y   R  286  11.105  8.883       False\n",
       " 4360   Y   R  382   9.388  7.460       False\n",
       " 5183   Y   R  386  11.281  8.900       False\n",
       " 5464   Y   R  453  13.704  9.805       False\n",
       " \n",
       " [68822 rows x 6 columns],\n",
       " ('S',\n",
       "  'S'):      aa1 aa2  dij    dcg    daa  aa_contact\n",
       " 528    S   S    2  8.854  8.854       False\n",
       " 532    S   S    1  5.041  5.041       False\n",
       " 548    S   S    4  9.337  9.337       False\n",
       " 880    S   S    1  7.020  7.020       False\n",
       " 1199   S   S    2  8.862  8.862       False\n",
       " ...   ..  ..  ...    ...    ...         ...\n",
       " 4139   S   S   28  7.014  7.014       False\n",
       " 4761   S   S  416  9.472  9.472       False\n",
       " 5477   S   S  454  9.176  9.176       False\n",
       " 5484   S   S  113  9.038  9.038       False\n",
       " 5629   S   S  124  9.774  9.774       False\n",
       " \n",
       " [89172 rows x 6 columns],\n",
       " ('S',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 420    S   T    1   7.048  6.718       False\n",
       " 521    S   T    8   9.839  9.300       False\n",
       " 540    S   T   35   7.383  6.609       False\n",
       " 549    S   T    1   7.233  7.183       False\n",
       " 902    S   T   71   8.735  7.632       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4803   T   S    1   4.983  4.748        True\n",
       " 5587   T   S  125   9.627  9.340       False\n",
       " 5590   T   S  122   4.769  3.931        True\n",
       " 5601   T   S    7  10.506  9.334       False\n",
       " 5906   T   S    2   9.147  8.680       False\n",
       " \n",
       " [92423 rows x 6 columns],\n",
       " ('S',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 417    S   V    5   9.320  8.842       False\n",
       " 520    S   V   17   9.622  8.920       False\n",
       " 522    S   V    4   7.840  7.633       False\n",
       " 539    S   V   36  10.600  9.933       False\n",
       " 542    S   V   33   3.920  3.317        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 982    V   S   82   9.770  9.431       False\n",
       " 2188   V   S    2   4.413  3.591        True\n",
       " 4223   V   S  231   9.731  8.663       False\n",
       " 5497   V   S  115   8.701  7.736       False\n",
       " 5506   V   S    2   6.921  6.107       False\n",
       " \n",
       " [126919 rows x 6 columns],\n",
       " ('S',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 5627   S   W   89  10.199  9.336       False\n",
       " 96     S   W    7  10.572  9.458       False\n",
       " 543    S   W    1   7.494  5.238       False\n",
       " 691    S   W   14  10.831  9.024       False\n",
       " 692    S   W    2   7.604  5.716       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4171   W   S    1   8.488  7.215       False\n",
       " 4374   W   S  382   7.326  6.248       False\n",
       " 4379   W   S  243   6.551  4.433        True\n",
       " 4384   W   S   46  11.193  9.883       False\n",
       " 4388   W   S   17   9.825  9.159       False\n",
       " \n",
       " [35742 rows x 6 columns],\n",
       " ('S',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 412    S   Y   10   9.659  8.212       False\n",
       " 906    S   Y    2   6.654  6.031       False\n",
       " 1194   S   Y   16   8.771  8.550       False\n",
       " 1216   S   Y   18  10.488  9.803       False\n",
       " 1435   S   Y    5  10.031  9.174       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4591   Y   S   13  11.417  9.690       False\n",
       " 4733   Y   S  415   8.839  7.580       False\n",
       " 4740   Y   S  387  10.149  8.992       False\n",
       " 4754   Y   S    6   6.886  5.518       False\n",
       " 5467   Y   S  449   6.539  5.421       False\n",
       " \n",
       " [75550 rows x 6 columns],\n",
       " ('T',\n",
       "  'T'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 653    T   T   24   7.310  6.309       False\n",
       " 771    T   T  106   8.750  7.735       False\n",
       " 911    T   T   72  11.268  9.304       False\n",
       " 977    T   T    2   4.177  3.279        True\n",
       " 985    T   T    3   5.436  4.460        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 3994   T   T   32   6.213  5.613       False\n",
       " 3996   T   T    9  10.851  9.156       False\n",
       " 4779   T   T  412  10.104  8.242       False\n",
       " 4788   T   T   66   7.869  7.028       False\n",
       " 5593   T   T  117   8.974  7.304       False\n",
       " \n",
       " [107506 rows x 6 columns],\n",
       " ('T',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 98     T   V    4   5.696  3.749        True\n",
       " 313    T   V    1   5.871  5.163       False\n",
       " 408    T   V    4   9.690  8.823       False\n",
       " 534    T   V   32  10.341  8.831       False\n",
       " 656    T   V   20   5.407  3.277        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4219   V   T  377   9.083  7.704       False\n",
       " 4220   V   T  280   9.180  8.488       False\n",
       " 4226   V   T   31   9.945  9.157       False\n",
       " 4302   V   T  384   4.257  3.801        True\n",
       " 4311   V   T   38   4.254  4.059        True\n",
       " \n",
       " [155054 rows x 6 columns],\n",
       " ('T',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1722   T   W    5  10.613  8.820       False\n",
       " 2031   T   W   38  11.484  8.672       False\n",
       " 2067   T   W   41  10.478  8.449       False\n",
       " 4259   T   W    6  11.271  8.660       False\n",
       " 123    T   W   10   8.485  7.146       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4123   W   T   33   8.297  6.885       False\n",
       " 4152   W   T  276  11.837  9.543       False\n",
       " 4203   W   T  279   6.149  4.214        True\n",
       " 4216   W   T   30  13.073  9.972       False\n",
       " 4383   W   T   51   5.476  3.480        True\n",
       " \n",
       " [37908 rows x 6 columns],\n",
       " ('T',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 311    T   Y   25  10.500  8.664       False\n",
       " 468    T   Y   46  10.440  9.380       False\n",
       " 471    T   Y   14  11.310  9.455       False\n",
       " 913    T   Y    3   7.071  4.305        True\n",
       " 969    T   Y   10  12.322  9.525       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4581   Y   T   52   6.357  3.943        True\n",
       " 4757   Y   T    2   9.151  8.943       False\n",
       " 5190   Y   T  345  10.154  7.444       False\n",
       " 5331   Y   T  124   8.442  5.957       False\n",
       " 5339   Y   T   82  10.892  9.643       False\n",
       " \n",
       " [81416 rows x 6 columns],\n",
       " ('V',\n",
       "  'V'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 308    V   V    3   9.194  7.502       False\n",
       " 316    V   V    3   9.633  8.613       False\n",
       " 495    V   V   13   8.596  6.483       False\n",
       " 918    V   V   79   5.719  5.247       False\n",
       " 925    V   V   66   8.099  6.215       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 1209   V   V  125   8.541  7.905       False\n",
       " 1264   V   V    4   9.774  8.333       False\n",
       " 2185   V   V   61   9.823  9.606       False\n",
       " 2912   V   V   68  10.358  9.281       False\n",
       " 4314   V   V    7   6.215  5.550       False\n",
       " \n",
       " [289378 rows x 6 columns],\n",
       " ('V',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1717   V   W    4   6.038  3.911        True\n",
       " 2864   V   W   18  11.187  9.321       False\n",
       " 4287   V   W   10  10.946  8.305       False\n",
       " 4644   V   W   43   6.860  5.680       False\n",
       " 4669   V   W   44   9.825  7.333       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 2451   W   V   93   6.471  3.831        True\n",
       " 2461   W   V   32   8.041  7.061       False\n",
       " 2645   W   V  114  10.584  9.657       False\n",
       " 4163   W   V  240  10.647  9.677       False\n",
       " 4389   W   V   12  10.433  7.525       False\n",
       " \n",
       " [56745 rows x 6 columns],\n",
       " ('V',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 282    V   Y   21   6.261  4.137        True\n",
       " 305    V   Y   24   5.318  3.987        True\n",
       " 930    V   Y    6  10.490  9.703       False\n",
       " 958    V   Y    8   6.667  4.834        True\n",
       " 1331   V   Y   28  10.977  8.985       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4349   Y   V    2  10.881  8.835       False\n",
       " 4370   Y   V   11  11.888  9.683       False\n",
       " 4584   Y   V   21   9.064  7.553       False\n",
       " 4590   Y   V   14   5.712  3.192        True\n",
       " 5186   Y   V  352   7.624  6.549       False\n",
       " \n",
       " [119512 rows x 6 columns],\n",
       " ('W',\n",
       "  'W'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 2129   W   W   49   6.171  3.247        True\n",
       " 670    W   W   12   5.866  3.690        True\n",
       " 854    W   W   25  11.612  8.500       False\n",
       " 932    W   W   29   8.917  6.549       False\n",
       " 600    W   W    8  12.400  9.097       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4148   W   W  281  11.872  8.411       False\n",
       " 4165   W   W  199  11.258  7.282       False\n",
       " 4217   W   W    3   9.078  6.904       False\n",
       " 4376   W   W  247  10.910  8.305       False\n",
       " 4387   W   W   18   5.720  3.485        True\n",
       " \n",
       " [20568 rows x 6 columns],\n",
       " ('W',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 1676   W   Y   35  11.908  9.100       False\n",
       " 2678   W   Y  166  12.091  9.491       False\n",
       " 2681   W   Y   34  11.855  8.035       False\n",
       " 2685   W   Y    6   9.281  6.748       False\n",
       " 983    W   Y   12   7.450  5.088       False\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4369   Y   W   17  10.997  7.703       False\n",
       " 4583   Y   W   22   8.148  5.745       False\n",
       " 4744   Y   W   34  10.607  8.485       False\n",
       " 5181   Y   W  479   6.518  3.794        True\n",
       " 5333   Y   W   89  11.782  9.345       False\n",
       " \n",
       " [35455 rows x 6 columns],\n",
       " ('Y',\n",
       "  'Y'):      aa1 aa2  dij     dcg    daa  aa_contact\n",
       " 352    Y   Y   32   6.634  4.845        True\n",
       " 1535   Y   Y   48  12.891  9.874       False\n",
       " 2281   Y   Y   82   4.921  3.582        True\n",
       " 2313   Y   Y   84   7.524  5.353       False\n",
       " 2319   Y   Y    2   6.432  4.208        True\n",
       " ...   ..  ..  ...     ...    ...         ...\n",
       " 4741   Y   Y  309  10.147  7.415       False\n",
       " 4742   Y   Y  308   9.952  7.030       False\n",
       " 4750   Y   Y   12   8.693  5.759       False\n",
       " 5334   Y   Y   88  10.974  9.193       False\n",
       " 5336   Y   Y   85   6.564  4.214        True\n",
       " \n",
       " [74462 rows x 6 columns]}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfnrg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fb681f66",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "('A', 'L')",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[20], line 8\u001b[0m\n\u001b[1;32m      5\u001b[0m ax\u001b[38;5;241m.\u001b[39mset_xlabel(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124md [Å]\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      6\u001b[0m ax\u001b[38;5;241m.\u001b[39mlegend()\n\u001b[0;32m----> 8\u001b[0m dfx \u001b[38;5;241m=\u001b[39m \u001b[43mdfnrg\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mA\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mL\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m     10\u001b[0m aac_hist, aac_edges \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mhistogram(dfx[dfx[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maa_contact\u001b[39m\u001b[38;5;124m\"\u001b[39m]][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdcg\u001b[39m\u001b[38;5;124m\"\u001b[39m], N_BINS)\n\u001b[1;32m     11\u001b[0m aac_rdf \u001b[38;5;241m=\u001b[39m aac_hist \u001b[38;5;241m/\u001b[39m ((\u001b[38;5;241m3\u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m4\u001b[39m)\u001b[38;5;241m*\u001b[39m(np\u001b[38;5;241m.\u001b[39mpi)\u001b[38;5;241m*\u001b[39maac_edges[\u001b[38;5;241m1\u001b[39m:]\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m3\u001b[39m)\n",
      "\u001b[0;31mKeyError\u001b[0m: ('A', 'L')"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "N_BINS = 100\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.tick_params(direction=\"in\")\n",
    "ax.set_xlabel(\"d [Å]\")\n",
    "ax.legend()\n",
    "\n",
    "dfx = dfnrg['A','L']\n",
    "\n",
    "aac_hist, aac_edges = np.histogram(dfx[dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "aac_rdf = aac_hist / ((3/4)*(np.pi)*aac_edges[1:]**3)\n",
    "\n",
    "aanc_hist, aanc_edges = np.histogram(dfx[~dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "aanc_rdf = aanc_hist / ((3/4)*(np.pi)*aanc_edges[1:]**3)\n",
    "\n",
    "rs, mccs = [], []\n",
    "for r in tqdm(np.linspace(min(aac_edges[0], aanc_edges[0]),\n",
    "                          max(aac_edges[-1], aanc_edges[-1]), 100)):\n",
    "    rs.append(r)\n",
    "    mccs.append(\n",
    "        sklearn.metrics.matthews_corrcoef(dfx[\"aa_contact\"], dfx[\"dcg\"] < r)\n",
    "    )\n",
    "\n",
    "ax.plot(rs, mccs)\n",
    "ax.set_ylabel('MCC') # , color=\"red\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "562797fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['C', 'D', 'E', 'F', 'H', 'I', 'K', 'L', 'M', 'N', 'P', 'Q', 'R',\n",
       "       'S', 'T', 'V', 'W', 'Y'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1eeddb23",
   "metadata": {},
   "outputs": [],
   "source": [
    "N = aas.shape[0]\n",
    "d2vals_arr = np.zeros((N,N))\n",
    "for i in range(N):\n",
    "    for j in range(i,N):\n",
    "        ni, nj = aas[i], aas[j]\n",
    "        d2vals_arr[i,j] = d2vals[ni,nj]\n",
    "        d2vals_arr[j,i] = d2vals[ni,nj]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "65fa256c",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"./d2vals.txt\", \"w\") as f:\n",
    "    f.write(str(d2vals))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8b24e735",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{('C', 'C'): 4.999043806942041,\n",
       " ('C', 'D'): 5.357762026439511,\n",
       " ('C', 'E'): 5.7731360936500105,\n",
       " ('C', 'F'): 6.1614431587892815,\n",
       " ('C', 'H'): 5.923183024288514,\n",
       " ('C', 'I'): 6.074561570903881,\n",
       " ('C', 'K'): 5.667076648255435,\n",
       " ('C', 'L'): 5.7923127475499765,\n",
       " ('C', 'M'): 5.772447898454652,\n",
       " ('C', 'N'): 5.500139099343675,\n",
       " ('C', 'P'): 5.524386773960173,\n",
       " ('C', 'Q'): 6.016821707360994,\n",
       " ('C', 'R'): 6.3964550753386,\n",
       " ('C', 'S'): 4.999218879205529,\n",
       " ('C', 'T'): 5.717701414454972,\n",
       " ('C', 'V'): 5.813139827144093,\n",
       " ('C', 'W'): 6.518099513651693,\n",
       " ('C', 'Y'): 6.404380891806739,\n",
       " ('D', 'D'): 6.2757599923561065,\n",
       " ('D', 'E'): 6.540752481951831,\n",
       " ('D', 'F'): 6.6116609943887585,\n",
       " ('D', 'H'): 6.49632865853111,\n",
       " ('D', 'I'): 6.541152663279169,\n",
       " ('D', 'K'): 6.483229850260708,\n",
       " ('D', 'L'): 6.264225339318206,\n",
       " ('D', 'M'): 6.3170137412290135,\n",
       " ('D', 'N'): 6.16718427131295,\n",
       " ('D', 'P'): 6.021165141987643,\n",
       " ('D', 'Q'): 6.471280909474635,\n",
       " ('D', 'R'): 6.771547128988349,\n",
       " ('D', 'S'): 5.671040993482821,\n",
       " ('D', 'T'): 6.145898034764737,\n",
       " ('D', 'V'): 6.145898034764737,\n",
       " ('D', 'W'): 7.069927392042977,\n",
       " ('D', 'Y'): 6.862513007178355,\n",
       " ('E', 'E'): 6.771815981360528,\n",
       " ('E', 'F'): 7.0118160773806615,\n",
       " ('E', 'H'): 6.772614205982921,\n",
       " ('E', 'I'): 6.731280772537552,\n",
       " ('E', 'K'): 6.641862243267594,\n",
       " ('E', 'L'): 6.563290855869866,\n",
       " ('E', 'M'): 6.579464526891192,\n",
       " ('E', 'N'): 6.48650935594802,\n",
       " ('E', 'P'): 6.285865402150542,\n",
       " ('E', 'Q'): 6.78345300395935,\n",
       " ('E', 'R'): 7.076714683883031,\n",
       " ('E', 'S'): 5.909148529906093,\n",
       " ('E', 'T'): 6.534117959104065,\n",
       " ('E', 'V'): 6.581529505363305,\n",
       " ('E', 'W'): 7.358073267091544,\n",
       " ('E', 'Y'): 7.1425884658236996,\n",
       " ('F', 'F'): 7.197671663039268,\n",
       " ('F', 'H'): 6.906948326429636,\n",
       " ('F', 'I'): 7.099203237984641,\n",
       " ('F', 'K'): 6.900032486347389,\n",
       " ('F', 'L'): 6.898375115332731,\n",
       " ('F', 'M'): 6.8324903551812435,\n",
       " ('F', 'N'): 6.607710192333349,\n",
       " ('F', 'P'): 6.61918654436962,\n",
       " ('F', 'Q'): 6.8686883786534665,\n",
       " ('F', 'R'): 7.354240724176094,\n",
       " ('F', 'S'): 6.151389023070029,\n",
       " ('F', 'T'): 6.7505508499021385,\n",
       " ('F', 'V'): 6.85605012331145,\n",
       " ('F', 'W'): 7.647982101636175,\n",
       " ('F', 'Y'): 7.368702369390544,\n",
       " ('H', 'H'): 6.787065971616172,\n",
       " ('H', 'I'): 6.785501790960626,\n",
       " ('H', 'K'): 6.627865422946,\n",
       " ('H', 'L'): 6.5827504403508055,\n",
       " ('H', 'M'): 6.678115462812152,\n",
       " ('H', 'N'): 6.452115503857021,\n",
       " ('H', 'P'): 6.27217370423688,\n",
       " ('H', 'Q'): 6.791300968509975,\n",
       " ('H', 'R'): 7.104324969085007,\n",
       " ('H', 'S'): 5.892815923483962,\n",
       " ('H', 'T'): 6.596699245411482,\n",
       " ('H', 'V'): 6.359097128844767,\n",
       " ('H', 'W'): 7.331892939826454,\n",
       " ('H', 'Y'): 7.164016241847652,\n",
       " ('I', 'I'): 6.989033185971462,\n",
       " ('I', 'K'): 6.912568614309436,\n",
       " ('I', 'L'): 6.721342633559915,\n",
       " ('I', 'M'): 6.905821849601819,\n",
       " ('I', 'N'): 6.55419294374426,\n",
       " ('I', 'P'): 6.281014223927016,\n",
       " ('I', 'Q'): 6.789764814199899,\n",
       " ('I', 'R'): 7.244009202669449,\n",
       " ('I', 'S'): 5.889449131762694,\n",
       " ('I', 'T'): 6.560240002738315,\n",
       " ('I', 'V'): 6.760182722579183,\n",
       " ('I', 'W'): 7.65271951320031,\n",
       " ('I', 'Y'): 7.273596442107247,\n",
       " ('K', 'K'): 6.585431659402318,\n",
       " ('K', 'L'): 6.698399885406227,\n",
       " ('K', 'M'): 6.630176068450377,\n",
       " ('K', 'N'): 6.503471225288056,\n",
       " ('K', 'P'): 6.466046730499123,\n",
       " ('K', 'Q'): 6.702994870079713,\n",
       " ('K', 'R'): 7.079929844510838,\n",
       " ('K', 'S'): 5.826011095982237,\n",
       " ('K', 'T'): 6.592668043547567,\n",
       " ('K', 'V'): 6.616604239551839,\n",
       " ('K', 'W'): 7.302342014999208,\n",
       " ('K', 'Y'): 7.154808143385852,\n",
       " ('L', 'L'): 6.833653857313883,\n",
       " ('L', 'M'): 6.559267591688002,\n",
       " ('L', 'N'): 6.316790347002464,\n",
       " ('L', 'P'): 6.140341636741269,\n",
       " ('L', 'Q'): 6.6496784582156705,\n",
       " ('L', 'R'): 7.0391753476862515,\n",
       " ('L', 'S'): 5.381966025156,\n",
       " ('L', 'T'): 6.313675673487518,\n",
       " ('L', 'V'): 6.358547274258883,\n",
       " ('L', 'W'): 7.505960452006895,\n",
       " ('L', 'Y'): 7.195889744661709,\n",
       " ('M', 'M'): 6.621033096436403,\n",
       " ('M', 'N'): 6.271113867455356,\n",
       " ('M', 'P'): 6.145898034764737,\n",
       " ('M', 'Q'): 6.702078651303757,\n",
       " ('M', 'R'): 7.222453565403264,\n",
       " ('M', 'S'): 5.651021229497889,\n",
       " ('M', 'T'): 6.476292104214179,\n",
       " ('M', 'V'): 6.604551132695353,\n",
       " ('M', 'W'): 7.4291541218865484,\n",
       " ('M', 'Y'): 7.085717481836081,\n",
       " ('N', 'N'): 6.201626127181895,\n",
       " ('N', 'P'): 6.014202362840141,\n",
       " ('N', 'Q'): 6.438885662910663,\n",
       " ('N', 'R'): 6.870863886700917,\n",
       " ('N', 'S'): 5.653216173661824,\n",
       " ('N', 'T'): 6.20043988240693,\n",
       " ('N', 'V'): 6.25306831716496,\n",
       " ('N', 'W'): 7.077598491316402,\n",
       " ('N', 'Y'): 6.872037789307629,\n",
       " ('P', 'P'): 5.84078476664752,\n",
       " ('P', 'Q'): 6.145898034764737,\n",
       " ('P', 'R'): 6.663939050128348,\n",
       " ('P', 'S'): 5.438110838128187,\n",
       " ('P', 'T'): 6.036110688995548,\n",
       " ('P', 'V'): 6.089173373794797,\n",
       " ('P', 'W'): 6.964098490999158,\n",
       " ('P', 'Y'): 6.812012739783208,\n",
       " ('Q', 'Q'): 6.750439069883684,\n",
       " ('Q', 'R'): 7.1010385372020135,\n",
       " ('Q', 'S'): 5.9110100783752815,\n",
       " ('Q', 'T'): 6.462733927102822,\n",
       " ('Q', 'V'): 6.5412016763691145,\n",
       " ('Q', 'W'): 7.368801644968533,\n",
       " ('Q', 'Y'): 7.111815202445311,\n",
       " ('R', 'R'): 7.513585573785119,\n",
       " ('R', 'S'): 6.3078356170823175,\n",
       " ('R', 'T'): 6.964713526913423,\n",
       " ('R', 'V'): 6.954665226394165,\n",
       " ('R', 'W'): 7.822458943469966,\n",
       " ('R', 'Y'): 7.56798185220042,\n",
       " ('S', 'S'): 4.9991279904019414,\n",
       " ('S', 'T'): 5.711041719878457,\n",
       " ('S', 'V'): 5.7332048822123856,\n",
       " ('S', 'W'): 6.620137193976818,\n",
       " ('S', 'Y'): 6.145898034764737,\n",
       " ('T', 'T'): 6.16718427131295,\n",
       " ('T', 'V'): 6.3004142527708575,\n",
       " ('T', 'W'): 7.16722828787032,\n",
       " ('T', 'Y'): 6.868452035636638,\n",
       " ('V', 'V'): 6.453528150053509,\n",
       " ('V', 'W'): 7.247158010634773,\n",
       " ('V', 'Y'): 6.970072163124451,\n",
       " ('W', 'W'): 8.201626133986842,\n",
       " ('W', 'Y'): 7.845791614385846,\n",
       " ('Y', 'Y'): 7.474383840508412}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d2vals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "11264dd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from  matplotlib.cm import ScalarMappable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b726c421",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.savetxt(\"contact_d2_data.csv\", d2vals_arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "64f04aeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.imshow(d2vals_arr)\n",
    "ax.set_xticks(range(len(aas)), aas)\n",
    "ax.tick_params(top=True, labeltop=True, bottom=False, labelbottom=False, length=0)\n",
    "ax.set_yticks(range(len(aas)), aas)\n",
    "\n",
    "scmap = ScalarMappable(norm=None)\n",
    "scmap.set_array(d2vals_arr)\n",
    "scmap.autoscale()\n",
    "fig.colorbar(scmap, cmap=None, ax=ax)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c0aab768",
   "metadata": {},
   "outputs": [],
   "source": [
    "u, s, vh = np.linalg.svd(d2vals_arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ba26cf28",
   "metadata": {},
   "outputs": [],
   "source": [
    "s1 = s[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6235b851",
   "metadata": {},
   "outputs": [],
   "source": [
    "u1 = u[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1711ce5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "vh1 = vh[0,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b75eb28d",
   "metadata": {},
   "outputs": [],
   "source": [
    "m1 = np.zeros((18,18))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "9d0f0c44",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(18):\n",
    "    for j in range(18):\n",
    "        m1[i][j] = u1[i]*s1*vh1[j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d8ef9d76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f4c7ad987c0>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SMmzf/a2y/Txc9iH7MSYG2M2JJAWbbfMkKdhqm+ey7McYOWz/7QzhRtu81sH2+8/RvIGmeSMOxU3zJClyOGyalwzb7z9/PDzUNO/IJ18wzUseOz3VwhEYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEuhnh5AZ4JHWxUMBszyshtzzbIk6fhAu7GdkMy2zQw3mcZJkgJJ2zGGmk3jJEnBVtu8ZNA2T5LCjfaZ2U1J07xwo/2GxxttX3KCsZhpniSFGwea5iXDpnGSpKjx61nAeK4DxzLwpOkAR2AAAC9RYAAAL1FgAAAvUWAAAC9RYAAAL6VdYFu2bNHMmTNVXFysQCCgtWvXtrvfOae7775bI0aMUG5urioqKrRnzx6r8QIAIOkUCqypqUllZWVavnx5h/c/+OCD+ulPf6qVK1fqtdde08CBAzV9+nS1tLR87sECAHBC2h/KqKysVGVlZYf3Oee0bNky/dM//ZNmzZolSfr5z3+uwsJCrV27VjfeeOPnGy0AAP/H9G9gtbW1qq+vV0VFReq2/Px8lZeXa+vWrR0+Jh6PKxaLtbsAANAd0wKrr6+XJBUWFra7vbCwMHXfp1VXVys/Pz91KSkpsRwSAKCP6vF3IVZVVSkajaYudXV1PT0kAIAHTAusqKhIknTw4MF2tx88eDB136dFIhENGjSo3QUAgO6YFtiYMWNUVFSkDRs2pG6LxWJ67bXXNHnyZMtVAQD6ubTfhdjY2Ki9e/emrtfW1mrXrl0qKChQaWmpFi5cqH/+53/WWWedpTFjxmjJkiUqLi7W7NmzLccNAOjn0i6w7du3a9q0aanrixYtkiTNnTtXq1at0j/8wz+oqalJt912m44cOaLLL79c69atU05Ojt2oAQD9XtoFNnXqVDnnOr0/EAjo3nvv1b333vu5BgYAQFd6/F2IAACcCgoMAOAlCgwA4KW0/wZ2ujT+5SCFwnZv/IiNse3qlqKEaZ4khQpsT3jceMj+jTMu13a7A81B0zxJyooHTPOc/RDVOtj+d8dwo+1AG8fa7+NDRx02zWs8a7BpniTFxtrmJTPwKvvFsftM894ZXNj9QmlINMV1Ok5JwREYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEsUGADASxQYAMBLFBgAwEuhnh5AZ46ODCoYCZrlHRvVapYlScOKYqZ5knTWkI9M8/bknWGaJ0kFuc2meR83DzDNk6SW1rBpXjCYNM2TpKN5A80z4422T+ehow6b5knS1SVvm+Y9W/pl0zxJOj7qmGleMGS//8w94xXTvM2540zz4o1tqjFN7BhHYAAAL1FgAAAvUWAAAC9RYAAAL1FgAAAvpV1gW7Zs0cyZM1VcXKxAIKC1a9em7mtra9PixYs1YcIEDRw4UMXFxfr617+uAwcOWI4ZAID0C6ypqUllZWVavnz5Sfc1NzerpqZGS5YsUU1NjX7zm99o9+7duvbaa00GCwDACWl/cKSyslKVlZUd3pefn6/169e3u+1nP/uZLr30Ur333nsqLS09tVECAPApGf8gczQaVSAQ0ODBgzu8Px6PKx6Pp67HYvYfEAYA9D0ZfRNHS0uLFi9erJtuukmDBg3qcJnq6mrl5+enLiUlJZkcEgCgj8hYgbW1ten666+Xc04rVqzodLmqqipFo9HUpa6uLlNDAgD0IRn5L8QT5bV//3799re/7fToS5IikYgikUgmhgEA6MPMC+xEee3Zs0cbN27U0KFDrVcBAED6BdbY2Ki9e/emrtfW1mrXrl0qKCjQiBEj9Nd//deqqanR888/r0Qiofr6eklSQUGBsrOz7UYOAOjX0i6w7du3a9q0aanrixYtkiTNnTtXP/jBD/Tcc89Jki644IJ2j9u4caOmTp166iMFAODPpF1gU6dOlXOu0/u7ug8AACucCxEA4CUKDADgJQoMAOClgOtlf7SKxWLKz8/X1KzrFAqE7YIvOc8uS9KxEbmmeZLUMiRompdzOGGaJ0nHc21/5wk3JU3zJCmr1TbTBQOmeZIUORTvfqE0BWMtpnmNZw02zZOkWKntJ3cKH37VNE+SkpdfYJrnwvbHCR98Occ0L3LINE6JeIv+sPL/KRqNdvk54M+LIzAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAl0I9PYDOJC8br2Qoxyzvo4m5ZlmSdGy4M82TpLaCpGle+FDQNE+SErm22x08Zj/GYNx2t3b2Q1TkcNg8M9w40DQvNtY0TpJ0fNQx07wzLr/ANE+SDpYPMM1L2k+1BpcfNM1r+GSQaV6yucU0rzMcgQEAvESBAQC8RIEBALxEgQEAvESBAQC8lHaBbdmyRTNnzlRxcbECgYDWrl3b6bLf/va3FQgEtGzZss8xRAAATpZ2gTU1NamsrEzLly/vcrk1a9Zo27ZtKi4uPuXBAQDQmbQ/MFNZWanKysoul/nggw/0ne98Ry+++KJmzJhxyoMDAKAz5h9kTiaTuvnmm3XnnXdq/Pjx3S4fj8cVj8dT12OxmPWQAAB9kPmbOB544AGFQiHdcccdn2n56upq5efnpy4lJSXWQwIA9EGmBbZjxw79y7/8i1atWqVAIPCZHlNVVaVoNJq61NXVWQ4JANBHmRbY7373OzU0NKi0tFShUEihUEj79+/X97//fY0ePbrDx0QiEQ0aNKjdBQCA7pj+Dezmm29WRUVFu9umT5+um2++WfPmzbNcFQCgn0u7wBobG7V3797U9draWu3atUsFBQUqLS3V0KFD2y0fDodVVFSkc8455/OPFgCA/5N2gW3fvl3Tpk1LXV+0aJEkae7cuVq1apXZwAAA6EraBTZ16lQ599m/E+p//ud/0l0FAADd4lyIAAAvUWAAAC9RYAAAL5mfSspKIpylQMiuX5NhsyhJkjPO+9/MpHGe/e8n1j/HrOO2eZKUtP0xygU/+998P6tk+LN90D+9TOO8DLw6BEPW+3jQNE/KwM/RfogaEG4zzQuGEqZ5AeO8znAEBgDwEgUGAPASBQYA8BIFBgDwEgUGAPASBQYA8BIFBgDwEgUGAPASBQYA8BIFBgDwEgUGAPASBQYA8BIFBgDwEgUGAPASBQYA8BIFBgDwEgUGAPASBQYA8BIFBgDwEgUGAPBSqKcH0JkPp2QrKyfbLG/AxENmWZI0pfAD0zxJuijvPdO8N2KjTPMkaWTOEdO891sGm+ZJ0pHWAaZ52VnHTfMk6Y+Hh5pnRhtzTfO+OHafaZ4kzT3jFdO823d/2zRPkgaXHzTNGxBuM82TpA3nPWeat6XFNE5NR5O6xjayQxyBAQC8RIEBALxEgQEAvESBAQC8RIEBALyUdoFt2bJFM2fOVHFxsQKBgNauXXvSMu+8846uvfZa5efna+DAgZo0aZLee8/2HXYAgP4t7QJrampSWVmZli9f3uH9+/bt0+WXX65x48Zp06ZN+v3vf68lS5YoJyfncw8WAIAT0v4cWGVlpSorKzu9/x//8R919dVX68EHH0zdduaZZ57a6AAA6ITp38CSyaReeOEFnX322Zo+fbqGDx+u8vLyDv+b8YR4PK5YLNbuAgBAd0wLrKGhQY2Njbr//vt11VVX6b/+67/01a9+Vdddd502b97c4WOqq6uVn5+fupSUlFgOCQDQR5kfgUnSrFmz9L3vfU8XXHCB7rrrLl1zzTVauXJlh4+pqqpSNBpNXerq6iyHBADoo0zPhThs2DCFQiGdd9557W4/99xz9fLLL3f4mEgkokgkYjkMAEA/YHoElp2drUmTJmn37t3tbn/33Xc1apT9iWUBAP1X2kdgjY2N2rt3b+p6bW2tdu3apYKCApWWlurOO+/UDTfcoC996UuaNm2a1q1bp3//93/Xpk2bLMcNAOjn0i6w7du3a9q0aanrixYtkiTNnTtXq1at0le/+lWtXLlS1dXVuuOOO3TOOefo17/+tS6//HK7UQMA+r20C2zq1KlyznW5zC233KJbbrnllAcFAEB3OBciAMBLFBgAwEsUGADAS6afA7MUORxQMBIwyzvy8RfMsiTp7VCRaZ4ktSWDpnnvHj7DNE+SGnLzTPMOHRtgmidJzfFs07xwMGGaJ0lHPrHdHyUp0Gi7/7wzuNA0T5I2544zzYscMo2TJDV8Msg0Lxiy33+2tBjnNdrOS0tTm6Q/mmZ2hCMwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXKDAAgJcoMACAlygwAICXQj09gE9zzkmSEq0tprnJY62meYnmuGmeJLVl9/4xHk/aZiZagqZ5kpSIO9O8rGDCNE+Sksfsn3qBY7Y/y0ST/f4Tb2wzzUvEbV8nJCnZbJsZCNnvP01Hk6Z5LU228xJvOi7pT6/nmRJwmV5Dmt5//32VlJT09DAAAJ/Tvn37NHbs2Izl97oCSyaTOnDggPLy8hQIBLpcNhaLqaSkRHV1dRo0aNBpGmFmsC29V1/aHral9+pL2xONRlVaWqrDhw9r8ODBGVtPr/svxKysLI0cOTKtxwwaNMj7CT+Bbem9+tL2sC29V1/anqyszL7NgjdxAAC8RIEBALzkdYFFIhEtXbpUkUikp4fyubEtvVdf2h62pffqS9tzural172JAwCAz8LrIzAAQP9FgQEAvESBAQC8RIEBALzU6wts+fLlGj16tHJyclReXq7XX3+9y+V/9atfady4ccrJydGECRP0H//xH6dppJ2rrq7WpEmTlJeXp+HDh2v27NnavXt3l49ZtWqVAoFAu0tOTs5pGnHXfvCDH5w0tnHjxnX5mN44L5I0evTok7YlEAho/vz5HS7fm+Zly5YtmjlzpoqLixUIBLR27dp29zvndPfdd2vEiBHKzc1VRUWF9uzZ021uus85K11tT1tbmxYvXqwJEyZo4MCBKi4u1te//nUdOHCgy8xT2VctdDc33/jGN04a11VXXdVtbk/MTXfb0tHzJxAI6Mc//nGnmVbz0qsL7Omnn9aiRYu0dOlS1dTUqKysTNOnT1dDQ0OHy7/66qu66aab9M1vflM7d+7U7NmzNXv2bL311luneeTtbd68WfPnz9e2bdu0fv16tbW16corr1RTU1OXjxs0aJA+/PDD1GX//v2nacTdGz9+fLuxvfzyy50u21vnRZLeeOONdtuxfv16SdLXvva1Th/TW+alqalJZWVlWr58eYf3P/jgg/rpT3+qlStX6rXXXtPAgQM1ffp0tbR0frLadJ9zlrranubmZtXU1GjJkiWqqanRb37zG+3evVvXXnttt7np7KtWupsbSbrqqqvajevJJ5/sMrOn5qa7bfnzbfjwww/12GOPKRAI6K/+6q+6zDWZF9eLXXrppW7+/Pmp64lEwhUXF7vq6uoOl7/++uvdjBkz2t1WXl7uvvWtb2V0nOlqaGhwktzmzZs7Xebxxx93+fn5p29QaVi6dKkrKyv7zMv7Mi/OOffd737XnXnmmS6ZTHZ4f2+dF0luzZo1qevJZNIVFRW5H//4x6nbjhw54iKRiHvyySc7zUn3OZcpn96ejrz++utOktu/f3+ny6S7r2ZCR9syd+5cN2vWrLRyesPcfJZ5mTVrlvvKV77S5TJW89Jrj8BaW1u1Y8cOVVRUpG7LyspSRUWFtm7d2uFjtm7d2m55SZo+fXqny/eUaDQqSSooKOhyucbGRo0aNUolJSWaNWuW3n777dMxvM9kz549Ki4u1tixYzVnzhy99957nS7ry7y0trbqF7/4hW655ZYuTyTdm+flhNraWtXX17f7uefn56u8vLzTn/upPOd6UjQaVSAQ6PZksensq6fTpk2bNHz4cJ1zzjm6/fbb9cknn3S6rC9zc/DgQb3wwgv65je/2e2yFvPSawvs448/ViKRUGFhYbvbCwsLVV9f3+Fj6uvr01q+JySTSS1cuFBTpkzR+eef3+ly55xzjh577DE9++yz+sUvfqFkMqnLLrtM77///mkcbcfKy8u1atUqrVu3TitWrFBtba2++MUv6ujRox0u78O8SNLatWt15MgRfeMb3+h0md48L3/uxM82nZ/7qTznekpLS4sWL16sm266qcsT36a7r54uV111lX7+859rw4YNeuCBB7R582ZVVlYqkej4u8N8mZvVq1crLy9P1113XZfLWc1LrzsbfV83f/58vfXWW93+f+/kyZM1efLk1PXLLrtM5557rh555BHdd999mR5mlyorK1P/njhxosrLyzVq1Cg988wzn+k3r97q3/7t31RZWani4uJOl+nN89JftLW16frrr5dzTitWrOhy2d66r954442pf0+YMEETJ07UmWeeqU2bNumKK67osXF9Xo899pjmzJnT7RubrOal1x6BDRs2TMFgUAcPHmx3+8GDB1VUVNThY4qKitJa/nRbsGCBnn/+eW3cuDHtr4wJh8O68MILtXfv3gyN7tQNHjxYZ599dqdj6+3zIkn79+/XSy+9pL/9279N63G9dV5O/GzT+bmfynPudDtRXvv379f69evT/tqR7vbVnjJ27FgNGzas03H5MDe/+93vtHv37rSfQ9Kpz0uvLbDs7GxdfPHF2rBhQ+q2ZDKpDRs2tPsN+M9Nnjy53fKStH79+k6XP12cc1qwYIHWrFmj3/72txozZkzaGYlEQm+++aZGjBiRgRF+Po2Njdq3b1+nY+ut8/LnHn/8cQ0fPlwzZsxI63G9dV7GjBmjoqKidj/3WCym1157rdOf+6k8506nE+W1Z88evfTSSxo6dGjaGd3tqz3l/fff1yeffNLpuHr73Ej/+z8YF198scrKytJ+7CnPy+d+G0gGPfXUUy4SibhVq1a5P/zhD+62225zgwcPdvX19c45526++WZ31113pZZ/5ZVXXCgUcj/5yU/cO++845YuXerC4bB78803e2oTnHPO3X777S4/P99t2rTJffjhh6lLc3NzaplPb8s999zjXnzxRbdv3z63Y8cOd+ONN7qcnBz39ttv98QmtPP973/fbdq0ydXW1rpXXnnFVVRUuGHDhrmGhgbnnD/zckIikXClpaVu8eLFJ93Xm+fl6NGjbufOnW7nzp1OknvooYfczp07U+/Ku//++93gwYPds88+637/+9+7WbNmuTFjxrhjx46lMr7yla+4hx9+OHW9u+dcT21Pa2uru/baa93IkSPdrl272j2P4vF4p9vT3b7aE9ty9OhR9/d///du69atrra21r300kvuoosucmeddZZraWnpdFt6am6628+ccy4ajboBAwa4FStWdJiRqXnp1QXmnHMPP/ywKy0tddnZ2e7SSy9127ZtS9335S9/2c2dO7fd8s8884w7++yzXXZ2ths/frx74YUXTvOITyapw8vjjz+eWubT27Jw4cLUdhcWFrqrr77a1dTUnP7Bd+CGG25wI0aMcNnZ2e4v/uIv3A033OD27t2but+XeTnhxRdfdJLc7t27T7qvN8/Lxo0bO9yvTow3mUy6JUuWuMLCQheJRNwVV1xx0jaOGjXKLV26tN1tXT3nemp7amtrO30ebdy4sdPt6W5f7YltaW5udldeeaU744wzXDgcdqNGjXK33nrrSUXUW+amu/3MOeceeeQRl5ub644cOdJhRqbmha9TAQB4qdf+DQwAgK5QYAAAL1FgAAAvUWAAAC9RYAAAL1FgAAAvUWAAAC9RYAAAL1FgAAAvUWAAAC9RYAAAL1FgAAAv/X8UPOdI/uI9PgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(m1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "e0486c2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "118.60291744656233"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "584d5210",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['C', 'D', 'E', 'F', 'H', 'I', 'K', 'L', 'M', 'N', 'P', 'Q', 'R',\n",
       "       'S', 'T', 'V', 'W', 'Y'], dtype=object)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "a70b91d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.20799844, -0.22740109, -0.23795322, -0.24646996, -0.23788943,\n",
       "       -0.24242963, -0.23765508, -0.23471991, -0.23597267, -0.22783849,\n",
       "       -0.22252034, -0.2380431 , -0.25284067, -0.20691224, -0.23006163,\n",
       "       -0.23219535, -0.2629743 , -0.25338989])"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vh1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "3595a9db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C & -0.20799844 & -0.20799844 \\\\\n",
      "D & -0.22740109 & -0.22740109 \\\\\n",
      "E & -0.23795322 & -0.23795322 \\\\\n",
      "F & -0.24646996 & -0.24646996 \\\\\n",
      "H & -0.23788943 & -0.23788943 \\\\\n",
      "I & -0.24242963 & -0.24242963 \\\\\n",
      "K & -0.23765508 & -0.23765508 \\\\\n",
      "L & -0.23471991 & -0.23471991 \\\\\n",
      "M & -0.23597267 & -0.23597267 \\\\\n",
      "N & -0.22783849 & -0.22783849 \\\\\n",
      "P & -0.22252034 & -0.22252034 \\\\\n",
      "Q & -0.23804310 & -0.23804310 \\\\\n",
      "R & -0.25284067 & -0.25284067 \\\\\n",
      "S & -0.20691224 & -0.20691224 \\\\\n",
      "T & -0.23006163 & -0.23006163 \\\\\n",
      "V & -0.23219535 & -0.23219535 \\\\\n",
      "W & -0.26297430 & -0.26297430 \\\\\n",
      "Y & -0.25338989 & -0.25338989 \\\\\n"
     ]
    }
   ],
   "source": [
    "n = vh1.shape[0]\n",
    "\n",
    "for aa, x, y in zip(aas, u1, vh1):\n",
    "    print(f\"{aa} & {x:.8f} & {y:.8f} \\\\\\\\\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ce514c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ae9b4fd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a681f85",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9820c5dd",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "svda_d1 = SVD_representation(d2vals_arr, 1)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.imshow(svda_d1)\n",
    "ax.set_xticks(range(len(aas)), aas)\n",
    "ax.tick_params(top=True, labeltop=True, bottom=False, labelbottom=False, length=0)\n",
    "ax.set_yticks(range(len(aas)), aas)\n",
    "\n",
    "scmap = ScalarMappable(norm=None)\n",
    "scmap.set_array(svda_d1)\n",
    "scmap.autoscale()\n",
    "fig.colorbar(scmap, cmap=None, ax=ax)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0cc5377b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "M = d2vals_arr - svda_d1\n",
    "# M = np.absolute(d2vals_arr - svda_d1)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "M_axr = ax.imshow(M, cmap=\"bwr\")\n",
    "ax.set_xticks(range(len(aas)), aas)\n",
    "ax.tick_params(top=True, labeltop=True, bottom=False, labelbottom=False, length=0)\n",
    "ax.set_yticks(range(len(aas)), aas)\n",
    "\n",
    "# scmap = ScalarMappable(norm=None)\n",
    "# scmap.set_array(M)\n",
    "# scmap.autoscale()\n",
    "fig.colorbar(M_axr, cmap=\"bwr\", ax=ax)\n",
    "# fig.colorbar(scmap, ax=ax)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c5e592bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  2.,   2.,   4.,  18.,  74., 107.,  81.,  29.,   6.,   1.]),\n",
       " array([-0.37815341, -0.31039692, -0.24264043, -0.17488394, -0.10712744,\n",
       "        -0.03937095,  0.02838554,  0.09614203,  0.16389853,  0.23165502,\n",
       "         0.29941151]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(M.flatten(), bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1c8663d0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9b58ba0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13, 7)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(aas == 'S'), np.argmax(aas == 'L')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "09030dc3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.3781534131457933"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M[13,7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "05ebd58d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0649342995173075"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.absolute(M).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c05b1525",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(139, -0.3781534131457951)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.argmin(), M.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6f84f4c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "dvals = np.arange(1,18)\n",
    "errs = []\n",
    "for d in dvals:\n",
    "    svda1 = SVD_representation(d2vals_arr, d)\n",
    "    errs.append(np.mean(np.abs(d2vals_arr - svda1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "29c37578",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(dvals, errs)\n",
    "ax.set_ylabel(\"MAE [Å]\")\n",
    "ax.set_xlabel(\"d\")\n",
    "ax.tick_params(direction=\"in\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "id": "2fcfdc86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bottom = -1.5\n",
    "left = 0\n",
    "\n",
    "d1 = 20\n",
    "d2 = 50\n",
    "maxval = 100\n",
    "bins = 500\n",
    "factor = bins/maxval\n",
    "\n",
    "X = np.linspace(0,100,bins)\n",
    "Y = np.zeros(bins)\n",
    "\n",
    "Y[:round(factor*d1)] = 4\n",
    "Y[round(factor*d1):round(factor*d2)] = -1\n",
    "\n",
    "\n",
    "plt.figure(figsize=(4,4))\n",
    "\n",
    "plt.plot(X,Y, color=\"orange\", label=\"E\")\n",
    "plt.vlines(d1,bottom,-1, color=\"red\", linestyle=\"dashed\", label=\"$d_1$\")\n",
    "plt.vlines(d2,bottom,-1, color=\"green\", linestyle=\"dashed\", label=\"$d_2$\")\n",
    "plt.hlines(0,0,d2, linestyle=\"dotted\")\n",
    "\n",
    "plt.xlim(left,maxval)\n",
    "plt.ylim(bottom,5)\n",
    "\n",
    "plt.xticks([d1,d2], labels=[\"$d_1$\",\"$d_2$\"])\n",
    "plt.yticks([-1,0,4], labels=[\"$E_-$\",0,\"$E_+$\"])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a8c75dd",
   "metadata": {},
   "source": [
    "DIR_PATH = \"./cg_contacts/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "03be5af9",
   "metadata": {},
   "outputs": [],
   "source": [
    "fnames = os.listdir(DIR_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2dce4ba6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 58%|█████████████████████████████                     | 3749/6443 [00:06<00:04, 613.29it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Problem with file: runme.sh\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████| 6443/6443 [00:10<00:00, 589.16it/s]\n"
     ]
    }
   ],
   "source": [
    "dfs = []\n",
    "for fname in tqdm(fnames):\n",
    "    try:\n",
    "        dfs.append(\n",
    "            pd.read_csv(DIR_PATH + fname,\n",
    "                        delim_whitespace=True,\n",
    "                        index_col=False,\n",
    "                        names=[\"aa1\", \"aa2\", \"dij\", \"dcg\", \"daa\"],\n",
    "                        skiprows=1)\n",
    "        )\n",
    "        \n",
    "    except:\n",
    "        print(f\"Problem with file: {fname}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "45381a2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat(dfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "744ef081",
   "metadata": {},
   "outputs": [],
   "source": [
    "N_BINS = 100\n",
    "DAA_CONTACT_CUTOFF = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "795b1788",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"aa_contact\"] = df.apply(lambda row: row[\"daa\"] < DAA_CONTACT_CUTOFF, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "8cceacdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11818010"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "130990b6",
   "metadata": {
    "scrolled": true
   },
   "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>aa1</th>\n",
       "      <th>aa2</th>\n",
       "      <th>dij</th>\n",
       "      <th>dcg</th>\n",
       "      <th>daa</th>\n",
       "      <th>aa_contact</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>6.693</td>\n",
       "      <td>6.319</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>7.283</td>\n",
       "      <td>5.421</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M</td>\n",
       "      <td>D</td>\n",
       "      <td>1</td>\n",
       "      <td>6.490</td>\n",
       "      <td>5.718</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>N</td>\n",
       "      <td>F</td>\n",
       "      <td>3</td>\n",
       "      <td>10.526</td>\n",
       "      <td>9.412</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>N</td>\n",
       "      <td>D</td>\n",
       "      <td>2</td>\n",
       "      <td>5.950</td>\n",
       "      <td>4.843</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  aa1 aa2 dij     dcg    daa  aa_contact\n",
       "0   D   F   1   6.693  6.319       False\n",
       "1   M   F   2   7.283  5.421       False\n",
       "2   M   D   1   6.490  5.718       False\n",
       "3   N   F   3  10.526  9.412       False\n",
       "4   N   D   2   5.950  4.843        True"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "8183ddd8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='aa1'>"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(\"aa1\").count().sort_values(\"aa2\", ascending=False)[\"aa2\"].plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "id": "cb30c1ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfgg = df.groupby([\"aa1\",\"aa2\"]).groups"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b427358",
   "metadata": {},
   "source": [
    "### Groups without repetitions (a,b) is joined with (b,a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "e7cecd7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfnrg = {}\n",
    "for k in dfgg.keys():\n",
    "    if (k[1],k[0]) not in dfnrg.keys():\n",
    "        dfnrg[k] = pd.concat([dfg.get_group(k), dfg.get_group((k[1],k[0]))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5a73ab83",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "7aefcf0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_contact_hists(dfx, N_BINS=100):\n",
    "    aac_hist, aac_edges = np.histogram(dfx[dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "    aac_rdf = aac_hist / ((3/4)*(np.pi)*aac_edges[1:]**3)\n",
    "\n",
    "    aanc_hist, aanc_edges = np.histogram(dfx[~dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "    aanc_rdf = aanc_hist / ((3/4)*(np.pi)*aanc_edges[1:]**3)\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(aac_edges[1:], aac_rdf, label=\"contact\")\n",
    "    ax.plot(aanc_edges[1:], aanc_rdf, label=\"no contact\")\n",
    "    ax.tick_params(direction=\"in\")\n",
    "    ax.set_xlabel(\"d [Å]\")\n",
    "    ax.set_ylabel(\"n\")\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68f92d52",
   "metadata": {},
   "source": [
    "## Specific case, Threonine & Tryptophane ('cause not that many cases?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "b8cd37f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_TW = dfnrg[(\"T\",\"W\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "66b1f90c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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iRYv46quveOyxx3yCnRtvvJG5c+cC8Pvf/56nnnqK9evXM2vWLPfz9u3bl+TkZPdjrrrqKp+xrFy5kj59+rBjxw7Gjh170rHFx8djNpvJzMzs8vfvVOka7KSnp2Mymdql6EpKSjr94o1Go/sblpeXx86dO1m6dKk72Glr8ODBpKens2/fvg6DnSNHjvhsES9ZnY412ux896nPaLDZGZCq+iZGZiawq7iWeleDsneGZ3dJHQNSY3yeo6PMTksXp557gp1Y0lzBjmR2gkRLExzxpNA50c1gp3y3OtYcU83HFldvjneDMngFO67MTmszFG1W53X+JzgIobfx432znFlZWe4JOTt37iQnJ8fnj+/Ro0eTnJzMzp07/QY7W7ZsYeLEie5goq2dO3dy8803+9x27rnn8uSTT3Y4rri4OBITEzucKKTZu3cvixcvZt26dZSXl7uzSYWFhYwdO/akYwskXYMdi8XCpEmTKCgoYPbs2QA4HA4KCgpYuHBhl5/H4XDQ3NzxG93Ro0epqKggKyurw2sSExN9gh3RsbLaZncgUlipUsczx2Syq7gWm92BrdXhE+zsL6sjOsq3Pex0p54fPaFmYg1IjSUlVpWxJLMTJI6uh9Ymz+fdzeyU7/WcnzjkWUBQW1AwVitjacGOq2fn+Ddgd/0M1HtKqyICRMWqDIter92dy6OifD43GAzuIOFUaCWl03Uq47rssssYOHAgK1asIDs7G4fDwdixY7HZbD06tp6g+2ysRYsWsWLFClatWsXOnTtZsGAB9fX1zJ8/H4B58+Zx9913u69funQpH374IQcOHGDnzp08/vjjvPTSS1x33XWAql/efvvtfPXVVxw6dIiCggKuuOIKhg4dysyZM3X5GsNNdWMLAMmxUcw9K4cZI/pw/dSB7vvrm1upa/IEO7ZWB98WqZ4orbTd4dTzLjYoV7rW1EmLs7ozO3XNrTSdZKd0EQBaCUtrIK4q7N7jfYKdg57ztpmdeFewo83G8s4mNVerDJOIDAaDKiXp8dGNfp2TGTVqFEeOHOHIkSPu23bs2EFVVRWjR4/2+5jx48ezZcsWKisrO3zOL774wue2L774osPn88diUX9Q2u2e368VFRXs3r2be+65hwsvvJBRo0Zx4sSJbo3NYrH4PGdv0r1nZ86cOZSVlbF48WKKi4vJy8tj9erV7qblwsJCjEZPTFZfX88tt9zC0aNHiYmJYeTIkbz88svMmTMHAJPJxDfffMOqVauoqqoiOzubiy++mAceeEBKUz2kpkkFO30TrCz9vif1aTUbaXZldeqaW3weo2Vy+iZYKalp7rBnxzsIamyx43A4MRp9f5k02uw0uoKa1HgLCVYzFpMRm91BeV0z/VO695eW6GFasDNhLnyxTJWxnM6uvyl4BzuV3sGO6xdmTAeZnaNtFiOtL4Nk3148IYJZfn4+48aN49prr2XZsmW0trZyyy23MH36dCZPnuz3MXPnzuX3v/89s2fPZunSpWRlZbF582ays7OZOnUqt99+O1dffTUTJ04kPz+ff/3rX/zzn/90NwV3xcCBAzEYDLz77rt897vfJSYmhpSUFNLS0njuuefIysqisLCQu+66q1tjy83N5eDBg2zZsoX+/fuTkJDQa+/Tumd2ABYuXMjhw4dpbm5m3bp1TJkyxX3fmjVrfKajPfjgg+zdu5fGxkYqKyv58ssv3YEOqLTZBx98QGlpKTabjUOHDvHcc8+1m/ElTp2W2UmK8U17xruakOttrdQ2+W8uzkpSac0Oe3bsvjuXN7W2j/q1aexRJgMJVjMGg4E094wsKWXpqrkWjm1U5xNVtpWWek9W5mRsDVDt+auWygOe88a2ZSxXWbq2RAVTR9oGO9K3I0KLwWDg7bffJiUlhfPPP5/8/HwGDx7MG2+80eFjLBYL//nPf+jbty/f/e53GTduHA899JB75vHs2bN58skneeyxxxgzZgx/+tOfeP755zvscfWnX79+/Pa3v+Wuu+4iIyODhQsXYjQaef3119m4cSNjx47lF7/4BY8++mi3xnbVVVcxa9YsLrjgAvr06dOri//qntkRoUcLdhKjfYOdOKuZinqbKmM1tw92okwG9zTxjqee+wY3DTY7sRbfH1OthJUaZ8HgyhakxVs4Xt0ka+3o7fBacLRCSi6kD1MBSe1x1bcTl37yx1fuB7wCXr9lLC3Ycf0B01wN5XvU6xjNaiuJ8j3StyOCjr/p42+99ZbP5wMGDODtt9/u1vMOHDiQv//97x3ev2DBAhYsWNDh/U6ns91tbVdLvvfee7n33nt9bsvPz2fHjh2dPldnY7NarZ2OuycFRWZHhJaOMjtxrsxOXbPd3bNjMXt+xNLirFjNKqJvG9Ro2mZ2/DUpV7iDHU+6M909I0syO7o6+Ik6DnIt8pns6uXq6owsrYRlUkGxO7Nja/A0PWs9O96rKO9UC6CROR6SB6hzmZElhHCRYEd0W42W2WlXxlKBjHdmZ1w/zyJRafEWd/DT4To7bTI+/pqUK+u05mSL57ldgU+ZZHb0pfXrDJqujimuYKerM7K0YCd3mutxR8De4snqGKPAEq/ODQZP384OV7CTcxbE9VXnUsYSQrhIsCO67eSZHU/PzojMBGKiVBCUHm9171DelannAA1+Fhb0LmNp0hOkZ0d3DZVQvE2dn2pmp0ILds4DczQ47aqHx3tBQe9GZ21GVvE36phzFsT3UedSxhJCuEiwI7qtuoPMjhbseGd2EqOjGJah/hL3yex0YbsIOFkZyyvYiZP9sXR36DPACX1GQbwru6KVlLo6/bx8jzr2GQEpg9R55YH2/TqahDaLj/Y/C+JcwY6UsYQQLhLsiG6rcWVt2s3GsngFO65rEqLNDM9Qu5L3ibe6g53mDnc9P3kZ60R9+zKWO7NTL8GObtwlLK9NebtTxnI6oXyfOk8bBqlasHPQa0HBNN/HeAc7CdmQ1F/KWEKIdiTYEd3WpQZlV2Yn3mrmxnNyuXh0Bj+Y1L/LmR2tUuFvM1B3Zie+fc9Oea2UsXRzoE1zMnjKWFWFcLJVYmuK1DR1o1kFOqmD1e0+wU4nmZ2cM127oWuZHdkfK5z5m0Ekwk9P/TtLsCO6rabDdXY8Dcq1zZ7Mzth+STw3bzLDMhJO2rOjZXYSXIGTv81AK13ZG58GZW2dnXoJdnRRfUz12xiMnuZiUJt5GkxqGwdtpWNQwcumF9V+VhqtXyclF0xR6ghq+nnbHc81CV5bwOS41udyZ3Yk2AlH2rYGDQ067XIuAkr7d267nUV3yTo7ots8PTu+Pz4+PTuuVZbj2+x23tXMTnKshZqmVv+zsTqZel5Z3+x31WXRy7Qp59kTISbZc7vJDEn9VGanqhASXTtTf/Ab2Pqqaly+0LV2hzYTK324OnpndpL6q/O2Zax4r8VC3cGOK7PTUAH2VjUGETZMJhPJycnuTSpjY2Pd622J8OF0OmloaKC0tJTk5GT3QoSnSn4LiG5xOp0dZna8Z2O5y1jRvj9i1pNNPXets6M9t79gx1+DsrYZqMMJVY0tPveJAHCXsKa3vy95oAp0ThyGAWerqeS7/63u2/IqXPBrMJo8wU7aUHXUenZOHIS+o9R52zKWFgSZo9UaO+AKiAyAUwU8CbJ6erjJzFTly5Ptyi1CX3Jysvvf+3RIsCO6pcFmp9XhG5Bo/G0XkWD1vebkmR0V3CTHqse1nY1la3W4n9u7jGUxG0mKiaK6sYWKumYJdgLJ6fRkdgb7CXZSBqqZWlqTcuFX0FStzmuLYP/HMCzfMxNLy+wkDVD9O61NUOpapbVtZidtCFx0v5r1ZXb9m5vM6rqGctWkLMFO2DEYDGRlZdG3b19aWlpO/gARkqKiok47o6ORYEd0i1bCijIZ3OvnaPytoNw2s3Pynh0VSCV2kNk50aCyOiajoV2wlRZvobqxhfI6G8Pk/S1wyveqrRpMVk8pyVtyrjpqwc7u99XRYFLr6Gx52RXsaGWsYepoMkNSjsrslO1Wt7Xt2QE499b2t8X3dQU70rcTzkwmU4+9GYrwJg3Kolu898VqWyePs6hfOnVNLdTZPLOxvJ10BWXX7cmuQKaxxbdBWVs0MCU2ql1fjrbWjkw/DzAtqzNgCkTFtL9fW2tH2/1893vq8/N+qY67/q0anGuOqs+1zA54+na0/bLaZnY6EtfBjKx9BXBgTdeeQwgRNiTYEd3SUb8OeDI7pbXNaLMFE9pmdrR1dvxkduwOJ3ZH5z07/lZP1sjO5zrRgofBM/zf773WTtlulakxWVVGJmOcmqn1yUPqmphU374crW9HE5vStTFpwY73WjuNJ+DVOfDyD2R1ZSEijAQ7ols6Wj0ZPMGO1lNjNhrcDcmazspY3gsKaj07bYMdLWvTebAjmZ2AcdhdKycDg2b4v0Zba6f6GOz8lzofPB2s8TDxWvX55pfV0TurA55VlDVdzezE+5l+XvItOFrUx97/dO15hBBhQYId0S0dLSgI7UtW8dHmdqWuzhqUvUtb2vO3bVCudK+ebKUt98KCstZO4BzfopqNrUmQnef/mvgMlclx2mHj8+q2EZeo47ir1eaeTte/ffpQ38e6y1ioZmVrYtfG5a+MVbrTc66V0oQQEUGCHdEtnWd2fBsF2wY/0HnPTktr+2Cn7UagnZWx0iWzE3jalPPcaWr6uD9GIyTnqPOaY+o4fJY6xqXBiFmea9tmdrzLWDGpvpuAdsad2fEqY5V86znf919oaeracwkhQp4EOxHgn5uO8pNVG6hvbr8acXd59sVqH8jEWdpkdvwEO9YuZHaiTAZiXc/VvozVWc+Oq0FZenYCp7Mp5960UhaohQe1xQUB8q7znKcN832ctooydL2EBf43A/XO7LTUe8pvQoiwJ8FOBFj5xUE+2lnK+oOVHV7zn2+LOe+R//LhjpJOn6uzBmWj0UCsxfPXfdvmZACLa5qo356dVtWcHGUyup+nsc3eWJWuQCYt3k+wEydbRvS4w1/Ch4t9t3XQtDSpNXPA/2KC3lK8gp3hl/jeNzRfBUMmK2RN8L0vKkZt8AntFxTsjLtB2dWI7HR6gp2cs9VRmwLfkdKdcHRj119TCBG0JNiJAM0tKrBoGzh4e3V9IUcqG7n19c3sLq71uW/n8RqWvr+TuubWTnt2wNOkDN0vY9nsdvc1Ma5gp3uzsVw9O1LG6jmr74YvnoQ9q9vfd3S9WvAvPhP6jOj8ebTp5+Dp19GYzPCj1fC/n6itJdrS+na6E+x4Nyg7nVB9FJqrVd/PuT9X9+1+HzraZLC5FlbOhBe+C/UVXX9dIURQkmAnAmiBRVMHwY7D4WRzYRWggoubX/qa6gbPqqR/+O9e/vTJAV5fX+izzo4/3gFOvJ9rOm1Q9snsaBuBdn02ltazU9vUSnNrx4Gd6CKH3ZMNqdjX/v7jW9VxwNkn76XRApbE/pA5rv39idmeLSHaPTZXHf0tKNgRLbPjaFFTzrWvI20YDLkQouLU6s3a19DWjrdV43Vrk2eDUiFEyJJgJwJojb/+1rYBOFBeR3VjC1azkX7JMRyuaOCBf+9w36/1wGwurOq0jAW+Tcp+y1hd6NmxeJWxGmytOL3++u5sNlZidBRm10KDlVLKOn2VB8HuypJVHvBzv+u29GHt72tr+CUwZQFc8YeuNxlrhs1Ue18NOr/rjzFb1QwxUKWsUldzcsZoiIqGIReozzsqZW1+xXNeebB74xVCBB0JdiLAyTI7mw5XATAhJ5n7Lh8DwNYjVe77tXVzNheeOHkZy6tJOcFfGcvkKWM525QQtHV2vMtYDqcnSLM7nFS5Xt9fZsdoNLhvlyblHlDm1dBbeaj9/RX71dF7enhHzBa45CEY8p3uj2P05XD3MRj3g+49Lt5rYUEts6Nlj0Z8Vx33+Al2KvZD4Zeez08c6t7rCiGCjgQ7EUDLojS1+M/sbCo8AcAZA1LISooGoKbJU8aqbVbnRdVNFFY2AP6nnkObMlYnPTvQvm9HG6fFZCTWa98trZR1osHmbrFIifX/+tK304O8Zy/5zey4Mh6pQ3p/LKZT2MYvztW3U1cKJa5MZV8VzDN8JmBQZazqY76P2/qa7+cS7AgR8iTYiQBaUNFRH8vGw1qwk+zuxdGyOW3PtSxLlxqU/ZSxvFdUblvKck89Nxswm4zuLFCDKyNV5doENDHajNnk/0c3XbaM6DnewU5tEbQ0ej5vaYLqI+q8K5kdPWiZndrjUO7aSFTL7MSlezYt9c7uOBywxRXsjLpcHU9IGUuIUCfBTgTQdhL3l9mpbmxhb2kdAGcMTHH32TTY7LS4Sk3ewY6mo8zOSWdjeQUp2rg03pkdwF3KanQtLKit8dPRa4P39HPJ7Jy2sl2+n3tnOKoOA061onFceiBH1XVak3LhV2r/rag43/V+tMUMv3jSk905+InakDQ6Cab+VN0mmR0hQp4EO2HOe3NNfz07W1y9OQPTYkmPt/o0Fdc1tdLYYnc/XmMw+O/HAYg/SYOy0WhwNxG3zey0uBcVVD+WsW2mn2tBV0IHM8HA/8KCVQ02frLqa97fdrzDx4k27C1Q7pqFpAUN3qUsd7/OoO43HAeKVsbSFg/sO0qt5qyZOE8tWlhVCKu+BzXHYcur6r6xP/BMp68rAVtDwIYthOh5EuyEOe/NNf3Nxtp02NOvA2D2mglV09RCnb+sTnQURqP/NzjfzI7/oKSjGVnuzI7ZN7PjCXZU75C/IErj3gzUazbWx7tL+WhnCc9/cajDx4k2KvaraduWeBh4rrrNe1ZSpRbsBKBf51RpZaxG9TPebmp7XBrc8K5aA6jygAp4tI1KJ14LMSkqwwOS3REixEmwE+a8A5xmP5kdd3PywBT3bd59OzXubIqZRFeQkehnqwhN/El6dsB7YUE79c2tfHWgArvD6ZmN1Saz09gms5PYSbCTHqdldjxlrPJaFfjU9sB2GRFDm4nVZySkuQIa78yOdh6s/TrgyexoMsa0vyY5RwU8STlqLaHWRvU1Z5+h7td2XZdgR4iQJsFOmPPO7DT5aVDeU6JWSx6b7dlNWsuc1DS2uLMpidFR5LmyPx01J8PJe3bAE8w0tzp49IPdXPPcV7y//Xi7zI62sGCdK0jxZHY6K2O1z+xoM7PabioqOuGeqj3SE9B4N+pqZay0IM7saOU3TUeLFqYMhBv+pRY8BJh4vac0p+3NJcGOECHtFOZzilBi88nstC9jaSUi7wBCawCuaWql1dWvkxBtZmJOMp/uKetysNNRucm7jHWgvB6AwxUNRLumm2s9O1qGSZsGX+uVZeqIv56dMlewU98sqyp3mTvYGe3JbvhkdrRp50Gc2YlvG+z4yexoUgfBTz6C/f+F8Vd7bncHOzIjS4hQJpmdMHeyzI5W5oqO8vwouDM7TS1epaMoLpuQTb/kGL47LqvD1/NuUO4ws+MV7GiLFNY0tbTL7GhBlXZNl4Id12ys8rpm96KFWuDTE7u+R4xSrzKWFtBUHVGNyz7TzoM5s+NVxopNbx/8tJWYpXp1TF7BfKqUsYQIB5LZCXOdZXYcDqf7/mivRfy8e3YcXpmdoX3j+eKuzlfA1VZQNhjw2QHdm/cqytWutXNqGlvdj9UyO22DnZpulLGaWx3U2+zEW83uMpY2s8zUQXO1cGlt9mRx+o6ChEwwx6h+lqpCcLQS9NPOAazxEBULLQ1qm4hTIWUsIcKCZHbCnHeDctvMjvd93sGOb8/OybMp3rQyVrzVjKGDKcnWk2R2tPuTXask13QjsxNrMbuDrLJaFeR4r6bc2c7vwqV8LzjtaiZSQpaKXLUMR+XB0Jh2rtGCsb6nG+wcVgsOCiFCUlAEO8888wy5ublER0czZcoU1q9f3+G1//znP5k8eTLJycnExcWRl5fHSy+95HON0+lk8eLFZGVlERMTQ35+Pnv3RubOxT5lrDaZHe91d6K9Vjb29Oy0dKkp2NvwjASmDk7j2ikDO7xGK1M1ewc7jS1e6+yoN1Ats1PVoAU7XRtLpmvLi+PVjTidTp/+nQYpZZ2cu4Q1yqtRVyvnHPSaiRXEJSxNfIY6nmqwk9gfjGa1IWqtrNMkRKjSPdh54403WLRoEUuWLGHTpk1MmDCBmTNnUlpa6vf61NRUfvOb37B27Vq++eYb5s+fz/z58/nggw/c1zzyyCM89dRTLF++nHXr1hEXF8fMmTNpamoK1JcVNHzKWG0yO1qmx2w0+Gy/oGVO2k497wqL2chrN5/NXZeM7PQaUDuTa+sV1jS1ujNNp9OzA9AvOQaAoqomqhtb3E3W4JnZJTpR1mbTTPDK7BzwWmMniJuTNef8XO24PvryU3u8yaympYNvKWvXv2HZODj0xWkPUQjR+3QPdp544gluuukm5s+fz+jRo1m+fDmxsbGsXLnS7/UzZszgyiuvZNSoUQwZMoRbb72V8ePH8/nnnwMqq7Ns2TLuuecerrjiCsaPH8+LL75IUVERb731VgC/suDgvSVD+8xO+34d8JoF5VPG6lpmpyu0nh2tzARQ65PZ6TzY6WydHYDsJC3YaWy3Iag2+0x0otS1TYTfYOdgaEw714y+HP7ndbVA4Kny17fz2eOqf2nN0tMZnRAiQHQNdmw2Gxs3biQ/P999m9FoJD8/n7Vr15708U6nk4KCAnbv3s35558PwMGDBykuLvZ5zqSkJKZMmdKl5ww3Nrvnzb3tdhHa594zscA3s9OVVYu7S8vclHkFIn5nY8W2DXa6VsbKTvYOdnw3BJUZWV1Qqu0Q7h3suLI4lQdCY9p5T2o7/byqEI5tVOeHPvMEf0KIoKXrbKzy8nLsdjsZGRk+t2dkZLBr164OHgXV1dX069eP5uZmTCYTf/zjH7nooosAKC4udj9H2+fU7vOnpqbG53Or1YrVau3W1xOMbK2ezE7b7SK0YMdqbpPZ8erZ0Vo2ejbYUa9XWuMV7DS2unc9t/jJ7HhvSHqysWQnq56dY34yO/WysGDnbA2eDEYfr2DHu2fHroLOkOjZ6Qltp5/veNv3/s0vQ/6SgA5JCNE9upexTkVCQgJbtmxhw4YN/O53v2PRokWsWbPmtJ4zJyeHpKQk98fSpeGRnrZ5NSjbWh3uqeTgXcby/TFI9MnsdK9npyvcZSyvQMRmd7hfq23PTm1TK/U2u9cCh51ndvp5ZXYq2mV2pIzVqfLdgBNi03zXpUnKcTXq2tT9loTgnnbek9qWsb59Sx0Hz1DHLa94AkAhRFDSNbOTnp6OyWSipKTE5/aSkhIyMzM7fJzRaGTo0KEA5OXlsXPnTpYuXcqMGTPcjyspKSEry7P4XUlJCXl5eR0+55EjR0hM9GyZEA5ZHYCWNtmc5laHe4NNrUG5w56dphaM7sxOD/bsuIKZ8lrfrIu2n1Xbnh1QgQuoyUFxHazfo8nyalBu37MjmZ1Oea+c7M1khuSBnubktMHBP+28p2jBTuVBtbDisa8BA1z+NKy4QO2Kvvc/MPJSPUcphOiErpkdi8XCpEmTKCgocN/mcDgoKChg6tSpXX4eh8NBc7N6Uxs0aBCZmZk+z1lTU8O6des6fc7ExESfj3AJdrwzO+A7I6u5pYNgxyuj0huZHW0dnbI2wY7WX6NlfqJMRndgc/REA9D5+j2aLNfU88YWO3tL6nzuk8xOJ5xO+No1MaDfGe3v18o5EDn9OuAJdhrKYcur6nzgOWoT0bz/UZ9vXKXL0IQQXaN7GWvRokWsWLGCVatWsXPnThYsWEB9fT3z588HYN68edx9993u65cuXcqHH37IgQMH2LlzJ48//jgvvfQS1113HQAGg4HbbruNBx98kHfeeYdt27Yxb948srOzmT17th5foq5a7P5nYHmfW83+G5TtDqd7Q83eyOy0DcS0LEyU13i07M7REyqzk9iFcURHmUh3raS87Vg1gDtDdSoNyq12B/e8tY23Nh/r9mNDyq5/w9ENatXhs29pf793gBMp/TqgFleMSVXn6/+kjqNnq+PEeeq470OoDvOfDyFCmO7bRcyZM4eysjIWL15McXExeXl5rF692t1gXFhYiNHoefOrr6/nlltu4ejRo8TExDBy5Ehefvll5syZ477mjjvuoL6+nptvvpmqqiqmTZvG6tWriY6ODvjXpzdbB03J3udtMzsxUSbMRoPP+jS90bPTlnudHa/7E2OiKKpu4khlQ7fGkZ0cQ3mdjWOu8ldWUgzHqhqpP8nUc6fTyeP/2cOGQ5WsuGEyidFRrD1QwctfFfLpnnJmT+zXpdcPOfZWKLhfnZ+9QG0R0VZKhGZ2QGV3GiuhoQIweNbtSR8KA8+Fw1+orM/02/UcpRCiA7oHOwALFy5k4cKFfu9r23j84IMP8uCDD3b6fAaDgfvvv5/777+/p4YYstqXsbwzO/6nnhsMBhKizZxwrVxsMEC8ped+VKI6CHY0FrOnTNU2s9PlYCcphm+OVrs/H5gWy7Gqxk57dpxOJ7/91w5e+PIQAGt2l3H5hGx2Hlcz9bSp72Fp62uqOTkmBc691f813gFOKKyx05NScqFokzofMNU3GDzjBhXsbH4RzvslGHVPmAsh2pD/lWGu08yOtgmouX3Db6JXc3C8xYyxBzfPtJhPEuyYPOPR9sfyBDtdK6dpa+1oBqbFAp2voPzQ+7vcgQ7At0UqWNpVXAuEcb9PS6NncbzzfqXKNv749OxEWLDj/bWPme173+jLwZqk1t8p2nzy53LYobm2R4cnhOicBDthrm3Pjr/MjjWqfbDjnUHpyRIWtA92tP4ajbY3FnhndrpbxvItWQ5IjQOgoYOA5UBZHX/6VO35NG2omlK9o0hldHYdV29MNrvDHTzuK63j/n/taNdkHZLWPwc1x9Q+UGf+pOPrUodA5jgYOC1ypp1rtCZlgFGX+d4XFQM5Z6lzLfvTEYcdXvkBPDJEFiMUIoAk2AlznWV2tMCnbRkLfBuBe7I5GdoHOzmpsR3erwU7Wkmtq8FOP6/MTnSUkT4JanZdR4sKfnWgEoCzB6dy+8wRAHxbVEOL3cG+Us+MLq0M9pfPD7Dyi4O8uflol8YTtGz18NkT6vyCX0NUJ31tJjP872dw47uRM+1c0/8sMJhg+CxIzG5/f/ZEdSza0vnzrH0G9v9XbSy698MeH6YQwj8JdsKc995Y0LUGZejdzI61Tc9OTopvsOPd0+O91o4aS/fLWGlxVuKt6mvsaG+s9QcrAJgyKI0RmQmYjAYq6218daDCp+9Ja3CudM1S07ayCFllu6GpCmLTYcI1J7/eYIi8QAeg70i4dQv8wP+efWTnqWNnZaySHfDfBzyfH93Q/hp7K2x6CWo7Xu1dCNF9EuyEubZbRPiWsTrp2fHJ7PRuGat/im9/jfdU+KRY3xJXd2ZjadITrMRZ1eP8TT13Op2sO6gyO1MGpRIdZWJon3gA/rHRN3OjPV7r3wn5Pp4GFeSRmA3GzhdrjHjJA8AS5/8+LbNTtlNtudFWqw3evFmtQJ08UN12dH376zb8Gd5ZCB/d1yNDFkIoEuyEufbr7PhbVLD9j0GCjmWsnsjspMVZ3K+THmch1jWbzF8Z6+iJRo5XNxFlMjBxgNode0y2Wk179be+f2FrwU6t6xjyKzLXl6ljXJ/OrxOdS8iC+AxwOqBke/v7P3kYirep9XqufxMwqIbmWt/V49nnKm0d/6bXhyxEJJFgJ8y169nxzux0sF0EQGJMLzYoewUzsRYTaXG+2Rt/PTvucXVxLEajgWzXSsrp8VbitDKWn0yMltUZ3z/ZvZXGaFew470II3jKYHWuaegnW7cn6Emw0zMMBq++nTalrGMb4XNXX9T3/k9N29e24/AuZbXa4PCX6rxin2pmFkL0CAl2wly72Vg+PTsdNygHKrOTFBPlM80dTpbZ6XrgpZWy0uItxLkyO/6mnq87oEo5Zw1Kdd82Jtt3+rXZNfW+rk0Zq+EUVmQOKu5gJ8JmV/WGjoKddc+pjM+Y73umrfefrI7ewc6xr6HFVQKzN6vMjxCiR0iwE+a0zI7WU+p/UUF/PTuBmXqeFBPVbguIzjI73Qm8Rmep7MywjHh3z05zq4PWNgHg+kMqs+Md7GiZHY1W1tLKVm2DnpBVX66OEuycPn/BTqsNdr+vzs+62XN7/zPV0TvYOfCJ7/OV7+35MQoRoSTYCXPaTKJ415u9v9lYVj8Nyt5BRVdLR13VPrPj+/zeZa7k08js/PLiEfzt/03l8gn9iPXaKb3B63tQXN3E4YoGjAaYPDDFZ1w5qSozlJ0UTVaSOq9rtuNwON29Px1NZQ8ZUsbqOVl56li2G5pdyxUc+hSaq1U/T84Uz7XaujzHNqkZWAAHXcGOyVXWLd/T60MWIlJIsBPmtMyOlj3xOxvL3zo7XgFIfC/27CTFRLXL1ngHQ21LXN3J7MRYTJyZm4rJaMBqNmJylaK8+3a+cpWwxmQntXvuMVmqlDUyK5FYd89PKw0tdpyuGf0dTWUPGe7MjgQ7py0hAxKyAScUuxqMd7yjjiMv9d1GIm2YWqm6tVE1NDfXebI82iajEuwI0WMk2AlzWs+OlhHx3S6iszKWV8+OtWd7dqxtMjsJVrO7zGY04A5KQJ0nWE+/pGYwGIhzZXe8+3ZWb1ezraYNa1/G+c6ovgBMH97H3fNT39xKXZPn8aeyi3pQkTJWz/IuZTnsaid5gFGX+15nNEI/r76dwrXgaFXT24ddrG6XMpYQPUaCnTBnaxPsNHvNLmp2Z3b0W2cnOTYKo9HgLrP52zdLy+6c7oakWt+O1ndT09TCf3eXAnDZ+Par4v5wUn8+vf0Crj97oGedHpvdJ1gK6cyO0yllrJ7mHewUroWGcohOhtxp7a/17ts5sEadD5oO6cPUuWR2hOgxQbHrueg9bctYWjYHOt71HNpOPe/d2Vja+GqbWv3uiJ4cG8WxqsbT3pBU69vRmoo//LYEW6uDIX3iGJWV0O56g8HAANcGonHux7b6BDv1tlacTieGUFxVuLlWzfoBtYKyOH3ewU6Mq+F95KVg8vN/KMcr2NEWKxw8A9KGqvOGcmiohNjU9o8VQnSLZHbCnLZdhN8ylhbs+GlQju+B0lFH2vbsgCd7Y/WT2dGuOd1xxLfJ7LyztQiAyyf0O2mw4pPZ8SpjOZ3t1+IJGVpWJyoOLLGdXyu6Rts2omIffPtPdd5241BNv0nqWHlALTgIMOh8sMarTVmhfSnrwCew/+MeHbIQkUCCnTCnZXYS/DUot3ZcxjKbjPxwUn+mD+/js6lmT7D42Q5Cm/HlL7PjCXZOL8MU67XWTkVdM5/vU/0ql03IOuljtUUJ22Z2IIRnZEm/Ts+LS4ekAeq8vgws8TD4Av/XxqRA+gjP531HQ7zqE3OXsiq8gp36cnj5KnjpSjXjSwjRZRLshLm2PTtaNqfF7sDuUFkff2UsgEd/OIFVPzrrtEpH/vgtY7mO/np2eiqzE+e1Gej724uxO5yM7ZfIYNc+WJ0/1qtBuU2w429V5pDQIDOxeoWW3QEYPrPzneS1vh1Q/Tqa9OHq6N23s68AHC2AEz57vCdGKkTEkGAnzLXN7GglF+9ylr91dnqT3zKWa3x+MzuxPRPsxHrNqPpwh9qTyF9jsj9xXntraVtFaEI3syPNyb3CO9jpqISlyfEKdgZ7Bztak7JXZmfvB57zbX+Div2nPEQhIo0EO2Gu7dRzrYzl3Wfir0+mNxkMBnc2KaVNIGPxE+ykuEpdbVdT7i5PdsbOt0XVAEwZnNatxzY029vthxWym4HKVhG9Q2tSNkfD0Is6v7a/a3FBoxkGnuu5ve2MLHuryuyA2jXd6fDstyWEOCmZjRXmPJkdbeq5eqNuds3KspiNPV6m6opbLxzO0RMNDHDteK6VsaL8BF7fG5/FlsIqrp868LReU5tRdbiinvI6G0YDjMhoPwvLn1ivNXpqm9r07IRqGUt6dnrHoOkw5f9B5njVbNyZjNEwc6nKrkV7bVGilbEqD6otJ45thKYq1efz/edg5UzY+jqcfweknN7/CyEigQQ7YczhcNLq6stxTz13BTvu1ZMDnNXRLJgxxOdzrUHZ6iez0z8lluXXTzrt14x1ZWc2Fp4AIDc9zr3L+cl4ZnLZ2y0kGPqZHSlj9SijCS55uOvXT72l/W0JWaq52VYHJw7C3v+o24fmw4Cz1RT1A2vg8/+Dy5b5f96aIrW8QJ8R/u8XIoJIGSuM2bw2vNTWzfGUsTpePVkPWonK2kGzdE+It2qZHbWz9KjMxM4u96FtF1Fva6W2bc9OyGZ2JNgJWgaDbylLC3a01ZXPv0Mdt7wC1cf8P8fzl8Cfzldr9QgR4STYCWMtXsFOQpvMTnMnW0Xo4Tsj+3LBiD5cd3bvpeRj26y+7G8hwY5omR2nE8rrbD73hW5mR+0LJmWsIKWVsg6sUftnYYAhF6rbcs9VPT52G6x9uv1jm2rgxCFobZKVmIVAgp2wZvNaU0d7s27boNzRtPNAS4u38vz8s5g5JrPXXkObeq4ZldX1zE5MlMm9f1dJTRPgaaZu27AcMiSzE9y0zM6WV9Wx/5kQ59VQf9ZN6nj4y/aPrT7qOa8q7J3xCRFCguOdTvQKbfVks9HgbrBtdThptTuCrowVCO0zO10PdtRGourxxa5gp2+iFVA7oYcch0PW2Ql2WmanRZVd3SUsTZorGPIXzPgEO4d7fmxChBgJdsKYltmxmI0+QU1Tq8OrQTlygh3vLTASo81kJXWy2JsfWsCozcbqm6CCnZDM7DSeUNOXAWK7Nv1eBJgW7GiGtwl2knPUsbESmut876s+4jmXzI4QEuyEM61BOcpk9Fm/prnF7s7s9GZDcLCJ9Zp5NSorsdubd3oHSwAZiSpYCsmeHa2EFZ3sf5NKob/UwWBw/f+Mz1RT2b1FJ6kP8A1uQMpYQrQROe90Ecg7s2M0GtxbMTS1Oty7n0dSGSvOK1jpTglLE9um50cLdkJyNpb06wQ/sxVSctX5sIvAX3Cu7cNV1Vmw0+Y+ISKQBDthTJuNpWV1tJWSm1rsXg3KkRrsdH0mlqZtz08fVxkrJDM70q8TGnLPU8dxP/B/f7IW7LTpy/EOdqqPqB4tISKYBDthTCtjaRkdLbBpbvFqUNZpUUE9xLUpY3VXR2Ws0MzsyOrJIWHWQ/CzTWoRQX+0vp3Oylh2G9SV9MrwhAgVkfNOF4FaWrWeHZX+1qaZN7Xa3dtGRFJmJ95qJj3eQmqcheFd3CbCm3fPj8VkdO/rFZKZHSljhQZLLKQN6fj+JFew412qctihxrXQoDnGdb/07YjIJttFhLHmNpkdbXfzphY7Ta3Btc5OIJhNRt77+Xk4ObUgzzuzE2c1eXZRD8XZWBLshAd3GcsrmKktBqddbS6anQeFa9X9A6boMkQhgkHkvNNFIE9mRytjqWNza2SuswPQNzHaXX7qLu+enfhos3uRwpBcZ0d2PA8P/spYWgkrMRtSBqlzWWtHRDgJdsKYrU2DsramjvfU80gLdk5HvNdsrHhrVIhndmSriLCQ7Npepa4EWtRil+7AJynHk/lp29MjRIQJimDnmWeeITc3l+joaKZMmcL69es7vHbFihWcd955pKSkkJKSQn5+frvrb7zxRgwGg8/HrFmzevvLCDotbctYPpkddZ81ghqUT1esVxkr3mryZHZcPTvLPtrD7/69Q5exdZuUscJDTApExalzLaOjHZP6+y9zCRGBdH+ne+ONN1i0aBFLlixh06ZNTJgwgZkzZ1JaWur3+jVr1jB37lw+/vhj1q5dS05ODhdffDHHjvnu/Dtr1iyOHz/u/njttdcC8eUEFfc6O20yO00t9qDbCDQUxPkEO2Z3ZqfF7qSirpllH+1lxWcHqay3dfQUwUOCnfBgMLSffi7BjhDt6B7sPPHEE9x0003Mnz+f0aNHs3z5cmJjY1m5cqXf61955RVuueUW8vLyGDlyJH/+859xOBwUFBT4XGe1WsnMzHR/pKSkBOLLCSo2195YWs+OltlpanFE5Do7p8t76np8dJTP7Kwdx2vc50E/O6vVBk1V6lyCndDXtm/Hp4zlNVtL1toREUzXYMdms7Fx40by8/PdtxmNRvLz81m7dm2XnqOhoYGWlhZSU1N9bl+zZg19+/ZlxIgRLFiwgIqKih4deyjwXkEZvHp2Wr22i5AyVpfFtSljRZmM7u/tjiJPsKMFkkGrwfV/wWBS20WI0NZ2+rk7s5MDif3UlhP2Zqj3ny0XIhLoOvW8vLwcu91ORkaGz+0ZGRns2rWrS89x5513kp2d7RMwzZo1i+9///sMGjSI/fv38+tf/5pLLrmEtWvXYjL5z2TU1NT4fG61WrFard38ioJLi913NpY1SitjObymnktmp6viLL5lLHWbCVurwyezowWSQUsrYcWmgVGC3ZDXtlTlzuz0V/ueJfZTt1UdgYRMfcYohM5C+jfdQw89xOuvv86bb75JdLRnOvE111zD5Zdfzrhx45g9ezbvvvsuGzZsYM2aNR0+V05ODklJSe6PpUuXBuAr6Dk7j9fwxId7fEoobTM73ttFeBYVDOkfgYCK85qNpWV5tL4d78xOY7AHO7JVRHjxLmM11UBTtfo8qZ/r/g62lBAiguia2UlPT8dkMlFS4ruUeUlJCZmZnf8F8thjj/HQQw/x0UcfMX78+E6vHTx4MOnp6ezbt48LL7zQ7zVHjhwhMdGzhUCoZXWWvr+LT/eU0T8lhqsnq19+ngZlbQVlrYwVuevsnI62DcrqNvX9219W574v+DM7slVEWNGmn1cVelZOjk4Gq2uV8OQBcPgLaVIWEU3XP+stFguTJk3yaS7Wmo2nTp3a4eMeeeQRHnjgAVavXs3kyZNP+jpHjx6loqKCrKysDq9JTEz0+Qi1YGenq4xypLLBfVvbqedag21lvc3ToGyWYKervIOdhGjfzI7D6bmuMdjX3ZGZWOFF69mpPQ6VB3xvA5mRJQRBUMZatGgRK1asYNWqVezcuZMFCxZQX1/P/PnzAZg3bx533323+/qHH36Ye++9l5UrV5Kbm0txcTHFxcXU1am/rOvq6rj99tv56quvOHToEAUFBVxxxRUMHTqUmTNn6vI19rYT9TbKapsBKKpqct/e3GYF5fE5yQCsO1BBU6uUsbrLezZWXJvMjjetHypoSbATXuL6gMkKTgccWaduS+rvuV+CHSH03xtrzpw5lJWVsXjxYoqLi8nLy2P16tXupuXCwkKMXk2Uzz77LDabjR/84Ac+z7NkyRLuu+8+TCYT33zzDatWraKqqors7GwuvvhiHnjggZDL1nTVnpJa93lRVaP7vG1m58zcFCwmI0XVnoBIylhdF+unQdn7Nk1TyGR2pIwVFoxG1bdTsQ8Ou2axegc77tlaEuyIyKV7sAOwcOFCFi5c6Pe+tk3Fhw4d6vS5YmJi+OCDD3poZKHBO9g5Xu0JdmxtMjuxFjMTBySz7mCl+xqrZHa6zGI2YjEZsdkd7jKWd7ZHo2XNgla9NCiHnSRXsFO02fW5n8xO9RFwOtVChEJEGHmnCwN7SjzNsUXVTTidqoFEy+x4r6UzbajvX/OS2eme5NgoAFJiLYDvFhKa4O/ZkQblsKMFNI4WdfQOdrS1dlqbPFk9ISKMBDthYLdXZsfW6qDCtV2BrU0ZC+CctsGONCh3y++uHMevvzuSwX3igQ4yO8G+qKA2Yyc+o/PrROhIzvH93LtB2WyBhGx1LqUsEaEk2AlxTqfTp4wFnr4dW6vvdhEAE/onuftNjAaIMklKuzsuGp3BzecPcX/u3bOTHq96woJ6nZ2GSjVrB6DPCH3HInqONv1c453ZAVlrR0Q8CXZCXFldM1UNLRgNMDJTrauhzchyZ3a8gh2zycjZg9XWGtFRJgxSvz8t3rOxRmWp739Qr7NT8q06Jg/0rMMiQp93Jsdgar9SsszIEhFOgp0Qt6dY9evkpsUxuE8c4MnstGgNym32vzrXVcqSfp3T553ZGZERQsFOxlh9xyF6lncZK7EfGE3+79f2zxIiwkiwE+K0fp1hGfFkJ8UAnhlZ/jI7ABeM6IvZaKB/SkwARxqetMxOcmwUmUlqy5LgDna2q2PGGH3HIXpWQhYYXYF32xIWSGZHRLygmHouTt1eV7AzIiOBJNcMIa2M5Vlnx7dUlZsex3u3nkdanCWAIw1PqXGqT2don3j3RqtB3bNTukMdJdgJL0aTyuhUHfYf7KTkqmPF3oAOS4hgIcFOiNMyO8MzEzAbVVBTpGV23HtjtS9XDc+Qfo2ecM6QNO65dBTnDEl373wetLOxHHYo3anOJdgJP8kDOg52Ml37B544BHVlEC9rLInIImWsEOZ0OtnrWmNneEYCWa4ylns2ll1bVFCakHtLlMnIT84bzOjsRPfWG0Gb2TlxCFoawBwNqYP1Ho3oaf3PdB397BcYkwx9RqrzY18HbEhCBAsJdkJYY4uduuZWAPolx5CdrIKd0tpmWuwOT2bHLP/MgRCj7SofrMGO1q/Td1T7BlYR+r5zD9y6FUZe6v9+LQg6sj5wYxIiSMi7YAirbVKBjsloINZiIi3OgsVkxOmE4uomd89OlEn+mQMhOth7dtwzsaSEFZaMJk9vjj/9z1LHoxsCMhwhgom8C4aw2ia1NHy81YzBYMBoNJCVrGYEHa9ucmd2rJLZCQgt2Ananh2Zdh7ZtDLXsU1gb9V3LEIEmLwLhrAaV2ZH25QSIMs1/bmoqpEWe/sVlEXvCfqeHS3Y6Tta33EIffQZCdZEaKmHsp2dX1uyA2qOB2ZcQgSAvAuGsFp3sBPlvk3r2ymqbpSenQCLcWd2gjDYaa6DEwfVuZSxIpPRCP3OUOed9e2U74U/nQ8rZ4K9JTBjE6KXybtgCNPKWN6ZnWyvGVk26dkJqOhgDna0KefxmbLbeSTrSt/Ot2+q3dOrDsOOtwMzLiF6mbwLhjAts5PoFewMSldbRry/rdh9m2R2AkPL7LTYnbTag6xvR1ZOFuDp2+ks2Nn5jud87TPgdPbumIQIAHkXDGGezI6njHXp+CxGZCRQUW9z39Z2uwjRO7z3GmtqDbJgR1ZOFuCZfl6xDxoq299feRCKt6nNRE1WKNokU9VFWJB3wRBW66dBOTrKxFNzJ/rMwJLMTmB4f8+DrpQl084FQGwqpA1T50f9LC646111zD0Xxl+tzr96JjBjE6IXybtgCPMX7ACMyEzgnktHAaq0YjLKCsqBYDQa3AFPoy2Igh2nU8pYwsNdyvKTsdn5L3UcdTmcvcBzm2wgKkKc7I0Vwmr8lLE01509ELvDSVq8NdDDimgxFhPNrY7gyuzUHIOmarUrdvpwvUcj9JZzJmx9tX3fTm0xHFmnzkdeConZMHgGHFgD65+Dix8M9EiF6DGS2QlhHWV2AAwGAzeeO4jLJmQHelgRLdochAsLaiWs9OFgluA34rkzOxvV5rAaLavT/0wV6ACcfYs6bnxRLV8gRIiSYCeE+WtQFvqKsQThlhHHNqqjlLAEqEUlo+LAVgtluzy3e5ewNEMvgrSh0FwNW14N7DiF6EES7ISwzjI7Qh9az07QlLGqCtX0YYBB0/UdiwgORpNnccGvV0JLk5qZdehzdduo73lda4Qzb1Ln2/4a2HEK0YMk2Alh/tbZEfoKqsyO0wnv/BxsdTBgKuRdq/eIRLDQsjcb/gxPnwkf/AacdsgYB6mDfa8dfQVgUD0+1ccCPlQheoIEOyFMyljBx9OzEwTBzuaX4MDHYI6GK55Rf6ULAXDmT2D2ckjIhupC1bAMMOqy9tcmZsGAs9W5VuoSIsTIb78Q5XQ6pYwVhLTMju7BTvUx9dc6wHfugbQh+o5HBBejEfLmws82qp8PSzyYY2DsVf6v1zJBsn2ECFES7ISophYHrQ61jLtkdoKHtvO5rrOxnE74163QXKNm1mgzaoRoyxIL598Ov/hWBT7pQ/1fp2V8CtdCbUngxidED5FgJ0RpJSyjAeIsppNcLQJF2zJC156dI+tg34dquf8rnlENqUJ0JiYZkvp1fH9yDvSbDDhhl5SyROiRYCdE1bhKWPFWMwaDrJAcLGKCYedzbVbNiFnQZ4R+4xDhZfQV6iilLBGCJNgJUdKcHJyCJrMDagaWED1ltKtv59AXUF+u71iE6CYJdkKUNCcHJy2z06xXz47D4Ql2cqboMwYRnlJyIWuCmqK+6996j0aIbpFgJ0R51tiRzE4w0RqUddsItGyX2gcrKg4yx+szBhG+pJQlQpQEOyHKU8aSzE4w0cpYTa06BTtHvlLH/pPAJD8booeNcgU7Bz+BxhP6jkWIbpBgJ0RJGSs4uXt29MrsFLqCnZyz9Xl9Ed7Sh6q9tRytsPcjvUcjRJcFRbDzzDPPkJubS3R0NFOmTGH9+vUdXrtixQrOO+88UlJSSElJIT8/v931TqeTxYsXk5WVRUxMDPn5+ezdu7e3v4yAkgbl4OSejdWqU8+OFuwMkGBH9JKh+ep44GN9xyFEN+ge7LzxxhssWrSIJUuWsGnTJiZMmMDMmTMpLS31e/2aNWuYO3cuH3/8MWvXriUnJ4eLL76YY8c8e7Y88sgjPPXUUyxfvpx169YRFxfHzJkzaWpqCtSX1etqJLMTlNxlrN7O7DTXqSnmTqfntprjUHUYDEa1mKAQvWHIBeq4/2Pfnz8hgpjuwc4TTzzBTTfdxPz58xk9ejTLly8nNjaWlStX+r3+lVde4ZZbbiEvL4+RI0fy5z//GYfDQUFBAaCyOsuWLeOee+7hiiuuYPz48bz44osUFRXx1ltvBfAr612eMpZkdoJJjMW1gnJv9+x8+gi8cCl8+qjnNq1fp+8YiE7s3dcXkWvAVLVgZW0RlO/RezRCdImuwY7NZmPjxo3k5+e7bzMajeTn57N27douPUdDQwMtLS2kpqYCcPDgQYqLi32eMykpiSlTpnT5OUOBNCgHJ20j0EabneqGFha/vZ1vjlb1/AuVud5kvngS6srUeaG2vo6UsEQvioqBga41nPZLKUuEBl2DnfLycux2OxkZGT63Z2RkUFxc3KXnuPPOO8nOznYHN9rjuvucNTU1Ph/Nzc3d+VICThqUg1O0xTMb6++bjvLi2sM8VbCv51+osVIdbXWe7E6hK5iXYEf0tsGuUpb07YgQoXsZ63Q89NBDvP7667z55ptER0ef1nPl5OSQlJTk/li6dGkPjbJ31DarzI6ssxNcPJkdB3uKawE4eqKh51+oodJz/vVKKPkWirepz2UxQdHbtL6dQ5+DvUXfsQjRBbqmBdLT0zGZTJSU+O6iW1JSQmZmZqePfeyxx3jooYf46KOPGD/es3ia9riSkhKysrJ8njMvL6/D5zty5AiJiZ4+B6vV2p0vJeAksxOcYizaCsp29paqYKeoqrHnX0jL7KQMghMH4Y3r1cq2if3Vpo1C9KaMcRCbDg3lcHQDDDxH7xEJ0SldMzsWi4VJkya5m4sBd7Px1Kkd7+vzyCOP8MADD7B69WomT57sc9+gQYPIzMz0ec6amhrWrVvX6XMmJib6fIROsCOZnWCiraDc0GJnb2kdoGbO1TWrf6/DFfW8t+04ztOZxeJweBZ0u+QRdazcr44DJKsjAsBohMHT1bn07YgQoHsZa9GiRaxYsYJVq1axc+dOFixYQH19PfPnzwdg3rx53H333e7rH374Ye69915WrlxJbm4uxcXFFBcXU1en3lgMBgO33XYbDz74IO+88w7btm1j3rx5ZGdnM3v2bD2+xB7ndDqlQTlIaevs2B1Od0AKcNyV3fnV37Zyyyub2HDoNFafbaoCp2sdn8EzYOwPPPfJYoIiUKRvR4QQ3d8p58yZQ1lZGYsXL6a4uJi8vDxWr17tbjAuLCzEaPTEZM8++yw2m40f/OAHPs+zZMkS7rvvPgDuuOMO6uvrufnmm6mqqmLatGmsXr36tPt6gkVzq4MWu8oMSLATXLR1dto6VtXI0L7x7CiqAWB/WR1nDUo9tRfRsjqWeDBb4Dv3qL2KHC1SThCBo/XtHNsIjVUQk6znaIToVFC8Uy5cuJCFCxf6vW/NmjU+nx86dOikz2cwGLj//vu5//77e2B0wafGldUxGCDOEhT/hMLFavafLD1e3URZXTP1rsUGj59OH4/WnBzjCpZSB8E1r0Dtccgce+rPK0R3JPWHtGFQsRcOfQajLtN7REJ0SPcyluie2qYWd3kk3mrGaDToPCLhzWAwuPt2vBVVNXKwrN79+bGq01jNW2tOjk3x3DZ8Jky68dSfU4hT4b2ashBBTIKdEPL8FwcZd99/WPTXrYBMOw9WMV6lrNFZaobfsapGDpZ7gp3j1T2Y2RFCL1rfzv7/ytYRIqhJsBNCNh5WvRpbj1QB0q8TrLz7dmaM6AO4Mjs+wU5PZHYk2BE6G3QeRMWq5Q8OfqL3aITokAQ7IaS6UfXq9E1Q0+IHpsXqORzRAS2zYzIaOHdoOqCCmwNewU5RVeOpTz+XzI4IFtYEmHi9Ov98ma5DEaIzp5waKCgooKCggNLSUhwOh899HW3iKU7PiQYbAA9dNY60OCuD+8TpPCLhj9UV7OSmxboD0uNVTZi9+quaWx1U1ttIiz+F9ZwksyOCydSfwoY/qynox7dC1gS9RyREO6eU2fntb3/LxRdfTEFBAeXl5Zw4ccLnQ/SOqgaV2UmOtTAhJ1kWFAxSMa4G5eEZCWQkRmM0gM3uYL+rQVkLek65lCWZHRFMUgbCmCvV+RdP6TsWITpwSpmd5cuX88ILL3D99df39HhEJ7RgJyXWovNIRGe0np1hfeOJMhnJSIx2BzYWk5ERmQlsO1bNsapGxvZL6v4LNFSoY2xaTw1ZiNNz7s9h+9/h2zfhwnshJVfvEQnh45QyOzabjXPOkcXLAqnF7nBvOZAcIxmdYDa0bzwAZw9WwUhWkmcxy4FpsfRPiQFOY60dbVFB76nnQugpawIM+Y7an23tH/UejRDtnFKw85Of/IRXX321p8ciOqE1JxsMkCjBTlBb/L3RrPnVDM5xNSdnJ8e47xuUHkdWkivYkTKWCCfn3qqOm16E+gp9xyJEG6dUxmpqauK5555z7zgeFeX75vvEE0/0yOCER5WrOTkxOgqTLCQY1MwmI7npnubxft7BTp84+riako+dcmZHGpRFEBo0XWV4jm+Fdc+qbUyECBKnFOx888035OXlAbB9+3af+wwGeSPuDZ7mZMnqhBrvzM7g9Dh3Y/kpZXZsDdDqepxkdkQwMRhg2iL42w3wxZOqaTljjN6jEgI4xWDn449lafBAO+E1E0uEFt8yVjxRJtdsrFPJ7GhZHaNZrXEiRDAZfQUMvwT2vA9v/j/4SYHarFYIncmigiFCK2NJc3Lo8W5QHpQe5w5+imuaaLU7OnqYf979OpJFFcHGYIDLnoSYFCj+Bj57TO8RCQFIsBMyPNPOJdgJNYPS40iMNpObFkt6vIU+8VaiTAYcTiitbe7ek0m/jgh2CRlwqatv89PHoGizvuMRAgl2QkZVoyuzI2WskBNnNfPfX83gnZ9Nw2AwYDQayEhU2Z6i7payZCaWCAVjv696dpx2Vc5qOY294IToARLshAgts5MkZayQlB5v9dmlPts1/byou03KktkRoeK7j0NcXyjbBTve0ns0IsJJsBMipIwVXrKSVWan203KDRLsiBARlwbjr1bnxzbpOxYR8STYCRFSxgovWpOylLFEWMscr47Ht+o7DhHxJNgJESfqZZ2dcKIFO8eqpIwlwpi2A3rxNnB0c+ahED1Igp0QoW0XIZmd8NDfHexIZkeEsfRhYI6Blnqo3K/3aEQEk2AnRMg6O+Gln2sz0GMnGrr3QMnsiFBiNEHmWHUupSyhIwl2QoCt1UG9zQ5AimR2woJWxqppaqW2qaXrD5TMjgg10rcjgoAEOyFAa042GiAh+pR2+BBBJt5qdi8j0K1SlmR2RKjJcgU7xd/oOw4R0STYCQHea+wYZcfzsNGvuzOy7K3QVK3OJbMjQoXWpHx8Kzid+o5FRCwJdkJAlWwCGpY8fTtdDHaaqjznMSk9PyAhekPf0Wrj2sYTUH1U79GICCXBTghwNyfLtPOwomV2jnY1s6P161iTwCTlTBEizFboM0qdSylL6ESCnSDldDr582cH+HJfuSezIzOxwkr/7mZ2GirUUfp1RKjJkiZloS8JdoLU9mM1PPjvnfy/lzdSWqsWnpMyVnjJ7u5aO9KcLEKVu29HMjtCHxLsBKniGhXg1DS18taWIkDKWOGm2w3KMu1chCqZfi50JsFOkDpRb3Of7yutAyA5RjI74URrUC6tbcbW2oWl9CWzI0JV5ljAALVFUFem92hEBJJgJ0hVNtja3ZYSJ5mdcJIWZyE6yojTCceru5DdkcyOCFXWBEgbos6LJbsjAk+CnSDlndnRJEmDclgxGAyevp2uNClLZkeEMunbETqSYCdIVda3n24uDcrhp9Pp5xX7oWyP53N3ZkfW2BEhSPp2hI4k2AlSJ1xlrDln5rhvS5EG5bDTYZOyvQX+chH86XyoKlS3NZ5QR8nsiFAk20YIHeke7DzzzDPk5uYSHR3NlClTWL9+fYfXfvvtt1x11VXk5uZiMBhYtmxZu2vuu+8+DAaDz8fIkSN78SvoHSdca+tMzEnmf6YMYPLAFEZkJug8KtHT+nVUxqoqVOvqtDbC58vUbdKzI0JZpquMVXkAmmr0HYuIOLoGO2+88QaLFi1iyZIlbNq0iQkTJjBz5kxKS0v9Xt/Q0MDgwYN56KGHyMzM7PB5x4wZw/Hjx90fn3/+eW99Cb1G69lJibXw+yvH8fcF52A1m3Qelehp7i0j2mZ2Thz0nG9+CWqKpGdHhLa4NEjsr85LvtV3LCLi6BrsPPHEE9x0003Mnz+f0aNHs3z5cmJjY1m5cqXf688880weffRRrrnmGqxWa4fPazabyczMdH+kp6f31pfQa7TZWKlx0qcTzvp1tLDgiUOec7tNZXfcKyinBWRsQvS4zHHqWLxN33GIiKNbsGOz2di4cSP5+fmewRiN5Ofns3bt2tN67r1795Kdnc3gwYO59tprKSwsPN3hBlSr3UF1oypjpUiwE9ZyUmMBVcayO7x2hK50ZXa0N4evV4KjVZ1LGUuEKnewI307IrB0C3bKy8ux2+1kZGT43J6RkUFxcfEpP++UKVN44YUXWL16Nc8++ywHDx7kvPPOo7a2ttPH1dTU+Hw0Nzef8hhOV3VjC07X+57shxXeMhKjsZiMtDqcvk3KWmZn4vXQ/yxwqOAXczRYYgM+TiF6hGR2hE50b1DuaZdccgk//OEPGT9+PDNnzuS9996jqqqKv/71r50+Licnh6SkJPfH0qVLAzTi9rSZWEkxUZhNYfdPJLyYjAb6p6pS1pHKBs8dWrCTMgim3+G5XbI6IpRpwU7pTjXjUIgAMev1wunp6ZhMJkpKSnxuLykp6bT5uLuSk5MZPnw4+/bt6/S6I0eOkJiY6P68s56g3lZZr34JSL9OZBiQGsuBsnoOVzZwDoDT6SljpQ6CtKGQPRGKNktzsghtyQPBmgjNNVC+FzJG6z0iESF0SxtYLBYmTZpEQUGB+zaHw0FBQQFTp07tsdepq6tj//79ZGVldXpdYmKiz4e+wY42E0tKWJFgoKtvp1DL7NSXQUs9YIDkAWAwwHfuAYPRswqtEKHIaISMsepcSlkigHStkSxatIgVK1awatUqdu7cyYIFC6ivr2f+/PkAzJs3j7vvvtt9vc1mY8uWLWzZsgWbzcaxY8fYsmWLT9bmV7/6FZ988gmHDh3iyy+/5Morr8RkMjF37tyAf32n6oTMxIooWpNyYYUr2NFKWIn9wOwKuofmw8+3wKVPBHx8QvQoaVIWOtCtjAUwZ84cysrKWLx4McXFxeTl5bF69Wp303JhYSFGoyceKyoqYuLEie7PH3vsMR577DGmT5/OmjVrADh69Chz586loqKCPn36MG3aNL766iv69OkT0K/tdFR6rbEjwt/AtDjAK7PjXcLyljIwgKMSopdIk7LQga7BDsDChQtZuHCh3/u0AEaTm5uL0+n0e63m9ddf76mhBcTyT/aTGmvhaq9tIbQFBSWzExkGuDI7hyvq1Q3agoIpufoMSIje5B3sOJ2qTCtEL9M92Ilkx6sbeej9XRgMMG1YunsHbG1BQVljJzJowU5NUyvVDS0kuWdi5eo2JiF6TZ+RYDSrFcFriiCpn94jEhFA5jXrqL5ZLRLndMI/Nh513+7O7EgZKyLEWEz0SVC9OYcr6zsuYwkRDqKiIX2EOpdSlggQCXZ01NzqcJ//beNRHK4VdCsbZPXkSOMzI8tdxpJgR4Qp6dsRASbBjo68g53CygbWHVQbPXp6dmTqeaTQSlnHSiugTq09ta1R1tQRYUpmZIkAk2BHRzavYAfgr18fAXx3PBeRYUCaCnaqi/aqozOW9/c16TkkIXqPZHZEgEmwoyMtsxMdpf4Z3tt2nIq6ZmpdvTwyGytyaJmdg3u+BaDQ2de9GawQYUcLdk4chKYafcciIoIEOzpqbrEDMDIzkWF942ludfD8F4cAMBogMVrKWJFioCuzk+1Um+AedmZQJcGOCFexqZDYX52XfKvvWEREkGBHRza7yuxYzUb+Z8oAAFZ9eQhQJSyjUdafiBTaKsoDDKpfp9CZQY0EOyKcSSlLBJAEOzpqbnEFO1Emvn9Gf2KiTO4SlszEiix94q3ERJkYaCgFVBmrqkGCHRHG3MHOVn3HISKCBDs60jI7FpORpJgoLp+Q7b5P1tiJLAaDgRvOyWW4pRzQylg2nUclRC/qd4Y67ngHqo7oOxYR9iTY0ZHWs2N1NShfd7Zn76MUmXYece6aOYxspyuz4+hLtWR2RDgbehH0Pwuaa+CtBeBwnPwxQpwiCXZ05O7ZMal/hnH9k5jQPwmQmVgRqeYYOFpwGqM4Tho1Ta3YHZ3vBSdEyDKZ4crlEBULhz6Ddcv1HpEIYxLs6MjTs+P5Z7h95kiyk6K5eEymXsMSetH2xEoegMP1X1OalEVYSxsCFz+ozj+6D0p36TocEb4k2NGRts6OxeT5Z5g2LJ0v776QC0b01WtYQi+uPbEMqYOIs5gAZK0dEf4m/wiG5oO9Gd78X7DLz7zoeRLs6Mhdxooy6TwSERTce2LlkuxqUJe1dkTYMxjg8qchJgWOb4HNL+k9IhGGJNjRkbtB2Sz/DAKoPKCOKYNIilEN6lUNMiNLRIDELDj3VnW++319xyLCkrzL6sh76rmIcA47HPpcnWeNdwc7UsYSEWPYxep48DNokX3hRM+Sd1kd+WtQFhHqyDpoqIDoZBgwleRYCXZEhOk7GhKyoLURCr/UezQizMi7rI6aJbMjNLv+rY7DZ4IpyhPsyFo7IlIYDDD0QnW+9yN9xyLCjrzL6sh7uwgRwZxOT7Az4rsAJGo9O5LZEZFk6EXquE+CHdGzJNjRUXOralCWzE6EK9ulZmKZrO6/bJNjXLOxJLMjIsngGWAwQfluqCrUezQijMi7rI5srdKzI/BkdQZPB2sCgDQoi8gUkwz9z1Tn+wp0HYoIL/IuqyNtUUGrWcpYEW33e+roKmEBXg3KMvVcRJih+eoopSzRgyTY0ZGW2bHIOjuRq+Y4HNuozkdc4r452b3OjsrstNod7rKnEGFNa1I+8Am0SrAveoa8y+pIe/OSRQUjmJbV6X8mJHj2Q0v0KmM5nU6ueOYLvvPYJzS1SMAjwlxWHsSmg60Wjq7XezQiTMi7rI7ciwpKsBO5/JSwwFPGqmps4Xh1E98W1XCsqpFDFfWBHqEQgWU0erI7UsoSPUTeZXXknnouwU5kaq6Fg5+q85GX+tyl7Y1la3WwubDKffuxE42BGp0Q+tH6dmS9HdFD5F1WR54GZflniEj7/wt2G6QOgfThPnfFWUyYjAYAvjpQ4b79WJUEOyICDPkOYICSbZ4944Q4DfIuqyObzMaKbMe/UcdB56nVY70YDAZ3k/Ja72BHMjsiEsSluwIeYM3D+o5FhAUJdnQkDcoRrmyXOvYZ6ffuJFffzr7SOvdtRyWzIyLFd+5Rx2/egJJv9R2LCHnyLquTVrsDh1OdS4NyhCrfo45tSlgabWFBb5LZERGj3xkw+grACf99UO/RiBAn77I60fp1QMpYEcne4ulF6DPC7yXJ/oIdyeyISHLBPWAwqlmLR2Qaujh1EuzoxOYV7EhmJwJVHgBHK1jiIbGf30u8MztjshMBKKttlrV2ROToMxzy/kedf/RbtWmuEKdA3mV1omV2zEaDe9aNiCBav0768HbNyRpt+jnAOUPSiHbtoXa8uqnXhydE0Jh+l9ok9/DnsF/2yxKnRvdg55lnniE3N5fo6GimTJnC+vUdpyq//fZbrrrqKnJzczEYDCxbtuy0n1Mv7h3PJasTmcpc/TodlLDAN7MzKiuRfskxgPTtiAiTnANn/kSdf/KovmMRIUvXd9o33niDRYsWsWTJEjZt2sSECROYOXMmpaWlfq9vaGhg8ODBPPTQQ2RmZvq9prvPqRebrLET2cp3q2MHzcngJ9hJiQXgWFVDrw5NiKBz9gJ1PLoemmr0HYsISbq+0z7xxBPcdNNNzJ8/n9GjR7N8+XJiY2NZuXKl3+vPPPNMHn30Ua655hqsVmuPPKdeZMfzCFfmCnY6yexoW0ZEmQwM6RPvyexUSRlLRJjkHEgeCE4HHFmn92hECNIt2LHZbGzcuJH8/HzPYIxG8vPzWbt2bdA8Z29plh3PI5fDAeV71XkHa+wA9E2IBmBEZgIWs5H+KVLGEhEsd5o6Hv5C33GIkGTW64XLy8ux2+1kZGT43J6RkcGuXbsC/pw1Nb6pUavV2mH2qCfIgoIRrLoQWhvBZFF/rXbg7MGp3HPpKKYMSgPwyuxIGUtEoIHnwJZX4PCXeo9EhCB5p3XJyckhKSnJ/bF06dJefT2bZHYil9acnDYUTB3/vWE2GfnJeYMZ1z8JgH5aZkfW2hGRaOC56nhsE9gk4Bfdo1tmJz09HZPJRElJic/tJSUlHTYf9+ZzHjlyhMTERPfnvZnVAdkENKJ1oTnZHy2zc7yqCbvDKUsWiMiSkgsJ2VBbBEc3wODpeo9IhBDd3mktFguTJk2ioMCzboLD4aCgoICpU6cG/DkTExN9PgIV7EhmJwJ1oTnZn4zEaMxGA60OJ6W10qQsIozBALmu7I707Yhu0vWddtGiRaxYsYJVq1axc+dOFixYQH19PfPnzwdg3rx53H333e7rbTYbW7ZsYcuWLdhsNo4dO8aWLVvYt29fl58zWMiO5xHsFIMdk9FAZpJqWpYmZRGRBp6jjtK3I7pJtzIWwJw5cygrK2Px4sUUFxeTl5fH6tWr3Q3GhYWFGI2eeKyoqIiJEye6P3/sscd47LHHmD59OmvWrOnScwYLaVCOUE6nVxmre8EOqFLW0RON7Dhew+Tc1B4enBBBbqBrRtbRDdDaDObezcCL8KFrsAOwcOFCFi5c6Pc+LYDR5Obm4uzC3iidPWewkAblCFVXCk3VanPDtKHdfvj5w/uw7mAlj67ezfThfRiYFtcLgxQiSKUPg7g+UF+mGpUHnlrLg4g88k6rE1lUMEJpWZ3kgRAV3e2H33z+YCYPTKG2uZVbXtkkm4KKyGIweJWyPtd3LCKkSLCjE8nsRKhT7NfRRJmM/OF/JpIaZ+HbohqeKtjbg4MTIgRoU9Clb0d0g7zT6kR6diJU2alNO/eWlRTDvd8bBcB/dwXXnm9C9Dot2ClcB/YWfcciQoa80+qkuUXW2YlIWhmrk20iuuLswWpV5b2ldVLKEpGl72iIToaWejj+jd6jESFC3ml1YrNLsBNx7K2e1ZNPsYylyUyMJi3Ogt3hZFdxbQ8MTogQYTR6+nbevx12/RscEvCLzuk+GytSuTM7UdKgHHYcdqjYD8XfQMl2KN2pPj9xEByt6pr0Yaf1EgaDgTH9kvh0TxnfFlWTl5N8+uMWIlSc+RPY8wEc2wiv/w8kD4Bpv4DJP9J7ZCJISbCjEy2zYzFJZiesHP4SXr0Gmqv932+OgfFXQ3TSab/U2OxEPt1TxvZjNSe/WIhwMvRCuHUrfP0X2PgCVBXCu79QsxyHXqj36EQQkmBHJ+4G5SgJdsLKzn+pQMccA5ljIWMsZIxRmZy0oWpvH2PP/JuP7acCpm+LOgishAhnyTmQfx9MvxPe+Rls+xtseVWCHeGXBDs6cU89l8xOeKk8oI6zft/rKfWx2SrY2XW8lha7gyj5WRKRKCoGzr5FBTu73lWLdvZA5lSEF/ntqBP3ooKS2QkvWrCTOrjXXyonNYaEaDM2u4O9JXW9/npCBK3siWr7ldYm2PG23qMRQUjeaXWiNShbTNKgHDYcdjhxSJ0HINgxGAzu7M52KWWJSGYwQN5cdb7lNX3HIoKSBDs6aZap5+Gn+ijYbWCyQGK/gLzk2H6JAHx7TIIdEeHGXQ0YoPBLqDyo92hEkJF3Wp00t0iDctjRSlgpuWAMTMZOa1LeXiQzskSES+oHg2eo82/e0HUoIvjIO61OZOp5GHL36wwJ2EuOcZWxdhTV4HA4A/a6QgSlCa5S1tbXwCn/H4SHvNPqRBYVDEMBbE7WDEiNBaCxxc6JBlvAXleIoDTqe2CJV71zhV/pPRoRRCTY0UmzTD0PP+5gZ1DAXtJiNpIebwGguKYpYK8rRFCyxMHoK9T5VmlUFh7yTqsTmywqGH50yOwAZCRGA1AiwY4QnlLWjrdkzyzhJu+0OpHMTphxODwzQAIc7GS6gp3i6uaAvq4QQWngOWBNUosLHt+i92hEkJB3Wh04nU7PrueS2QkPtUVgbwZjFCTlBPSlM5JcwY5kdoRQMyEHnafOD3yi71hE0JB3Wh202J3uiQJWszQoh4WK/eqYMhBMgd2FRcvslFRLsCMEAIOmq+OBNboOQwQPCXZ0oGV1QBYVDBs69euAVxnLldmxO5xsPFxJU4v0K4gINdgV7BR+BS2N+o5FBAV5p9VBs9ebkPTshAkdgx2tjKU1KP/t6yNc9exanirYG/CxCBEU0odDQpYqLR9Zp/doRBCQd1odaM3JUSYDRqNB59GIHhFEmZ2vD58A4JujsoWEiFAGg1cpS/p2hAQ7urBpO55Lv074cM/ECtzqyRot2KlqaKGpxc7eUrUD+qGK+oCPRYigoW0dIX07Agl2dOGedi79OuHB4dBlQUFNYoyZaNesvuLqJvaV1AJQVNVIc6v07YgIpfXtHN8CjSd0HYrQn7zb6sCT2ZFvf1ioK4bWRjCYIHlAwF/eYDC4szubj5yg3qYCHIcTjlRKc6aIUInZkDYMnA449LneoxE6k3dbHWh/bUuwEya0rE7yADBF6TIEbRXlz/aW+9x+qFxKWSKCuUtZ0rcT6eTdVgc2KWOFFx2bkzWZSR0EO9K3IyKZVso6KMFOpJN3Wx00S4NyeNGCnbTANydrtDJWWa3aMkJb0kCCHRHRcqeBwQjle6CmSO/RCB1JsKMDrYwlmZ0woa2erGNmRytjac4ZmgbA4YoGPYYjRHCISYGsPHUupayIJu+2OmiWBuXwotMGoN60MpbmotEZAByUnh0R6bS+nb0f6DoMoS95t9WBTD0PI05nUPTseGd2zEYDF4zoC8j0cyEYfbk67n5f7YQuIpK82+pApp6HkbpSaKlXfQE6TDvXeGd2ctPjyEqKJs5ikunnQmTlQZ+R0NoEO97WezRCJ/Juq4OtR6qA9n0WIgQVbVLH1MFgtuo2jL4JVgyunUeG9Y3HYDAwMC0OkOnnIsIZDDDhGnW+9XV9xyJ0ExTBzjPPPENubi7R0dFMmTKF9evXd3r93/72N0aOHEl0dDTjxo3jvffe87n/xhtvxGAw+HzMmjWrN7+ELmu02Xlv23EAvjc+W+fRiNOmLUWv7cOjkyiTkbQ4FWwNy0gAYFC6K9iRGVki0o27GjDA4S/gxCG9RyN0oHuw88Ybb7Bo0SKWLFnCpk2bmDBhAjNnzqS0tNTv9V9++SVz587lxz/+MZs3b2b27NnMnj2b7du3+1w3a9Ysjh8/7v547bXXAvHlnNR/dhRTb7OTkxrD5IEpeg9HnK79H6uj1gSpo34pMQCMcAU7A9NiAQl2hCCpn2fNnW/+qu9YhC50D3aeeOIJbrrpJubPn8/o0aNZvnw5sbGxrFy50u/1Tz75JLNmzeL2229n1KhRPPDAA5xxxhk8/fTTPtdZrVYyMzPdHykpwRFY/HPTMQCunNhfdjwPdTVFUL4bMMCg8/QeDXfNGslPpg0if7RqTs51ZXZk+rkQwIS56rj1NTWxQEQUXYMdm83Gxo0byc/Pd99mNBrJz89n7dq1fh+zdu1an+sBZs6c2e76NWvW0LdvX0aMGMGCBQuoqKjo+S+gm0prmvhsbxkAV07sp/NoxGnT1u3InqjW89DZ1CFp3PO90e7FKnNdPTt7S+pwyi93EelGfg+i4tTsyaMb9B6NCDBdg53y8nLsdjsZGRk+t2dkZFBcXOz3McXFxSe9ftasWbz44osUFBTw8MMP88knn3DJJZdgt3c8Bbempsbno7m5+TS+Mv/e2VqEwwlnDEh291OIEKb16wRBCcufMdmJxESZKK5pYutRmXIrIpw13jMNfWtwtDWIwNG9jNUbrrnmGi6//HLGjRvH7Nmzeffdd9mwYQNr1qzp8DE5OTkkJSW5P5YuXdrj4/pkj8rqXD5BGpNDntMZ9MFOnNXMxWPUHwZvbT6m82iECALarKzt/4TWnv+DVgQvXYOd9PR0TCYTJSUlPreXlJSQmZnp9zGZmZnduh5g8ODBpKens2/fvg6vOXLkCNXV1e6Pu+++uxtfSdecaLABMMDVOCpCWNluqCsGcwzkTNF7NB2a7SqX/mtrES12h86jEUJnuedBYj9oqoJ1y/UejQggXYMdi8XCpEmTKCgocN/mcDgoKChg6tSpfh8zdepUn+sBPvzwww6vBzh69CgVFRVkZWV1eE1iYqLPh9Xa82umVDe2AJAUE9Xjzy0C7IBrFtbAqRAVvOslnTc0nbQ4CxX1Nj7fV37yBwgRzowmOP92dV5wPxzdqO94RMDoXsZatGgRK1asYNWqVezcuZMFCxZQX1/P/PnzAZg3b55PluXWW29l9erVPP744+zatYv77ruPr7/+moULFwJQV1fH7bffzldffcWhQ4coKCjgiiuuYOjQocycOVOXr1FT3SDBTtgI8hKWxmwycpmrbCqlLCGASTfC6CvA0Qp/ny9bSEQI3YOdOXPm8Nhjj7F48WLy8vLYsmULq1evdjchFxYWcvz4cff155xzDq+++irPPfccEyZM4O9//ztvvfUWY8eOBcBkMvHNN99w+eWXM3z4cH784x8zadIkPvvss17J1nSVw+GktrkVgEQJdkKbvQUOfa7OgzzYAU8p64Nvi6l3/QwKEbEMBrjsKbW9S9VheOfnMhU9AhicET4ntaamhqSkJKqrq0lMTOy116lubGHCb/8DwK4HZhEdZeq11xK9rPArWDkTYlLh9v1g1P1vhk45nU5mPLaGwxUNPHf9JC4e03F/mxAR4+hGWHmxyvB87/9g8o/0HpHopu68fwf3b+kwUuPq17GajRLohDp3CWt60Ac6AAaDgfOGpQPwhfTtCKH0nwQXLlHnH/xGyllhLvh/U4cJaU4OI/v/q44hUMLSnDvEFezs139xTSGCxtSFakf0lgY1HV2ELQl2AkSCnTBRsR+OrAMMMDT/pJcHi6lD0jAYYF9pHSU1TXoPR4jgYDRC3rXqfPPL+o5F9CoJdgJEgp0w8bVrz7ZhF0NSf33H0g3JsRbGZKua9pf7pZQlhNuEa8BggmNfQ+kuvUcjeokEOwEiwU4YaGmCLa+o8xBsZnSXsvZJKUsIt/i+MNy1LMkWye6EKwl2AqRGgp3Qt+MtaDwBSTkw7CK9R9Nt5wxVwc6X+8plY1AhvGmlrK1vqKUlRNiRYCdAtMyOrLETwrQS1qQb1EqsIebM3BSiTAaKqps4VNGg93CECB7DZ0JcH6gvhX0f6T0a0Qsk2AkQKWOFuOLtqjHZaIaJ8/QezSmJtZiZOCAFQLaOEMKbKQrGz1Hn0qgcliTYCRDJ7IQ4Lasz8nuQkKHvWE7DNFcp64u9EuwI4UMrZe1ZDXVl+o5F9DgJdgJEMjshrLkWvnlDnYdgY7K384f3AeCL/eW0yi7oQnhkjIbsM9SKytr/dxE2JNgJEGlQDmHrnwNbHaQNhUHn6z2a0zKuXxJJMVHUNrWy9aisGCuEj4nXqePGF2S/rDAjwU6ASGYnRH31LBTcr87PXqA2EQxhJqPBXcr6dI+k6oXwMf5qsCRAxV7PtjAiLEiwEyAS7ISgTx+D1Xep83Nvhck/1nc8PUTbJ+uzvSrY2X6smrWyjYQQYE2AvLnqfP1z+o5F9CgJdgLA6XRS09QKSLATMgoegP8+oM5n/BryfxvyWR3Nea6+nS1HqvhkTxnf/+OXXPvnrzhcUa/zyIQIAmfepI6734cTh/Udi+gxEuwEQL3Njt2h6r8S7ISAQ1/AZ4+p84segBl3hk2gA9AvOYYhfeJwOOEnqzZgsztwOOG9bcV6D00I/fUZDoMvAJzw9V/0Ho3oIRLsBIBWwrKYjERHybc86O18Rx3Hz4Fzf67vWHrJecNUdqfF7sRqVj+Tq7cf13NIQgSPs25Wx00vQkujvmMRPULeeQOgukFbY8eMIYwyBGHJ6VTpa4BRl+k7ll50wci+ACRGm3n1pikYDLD1aDXHquQXuxAMnwlJA9T2MNv/ofdoRA+QYCcAZEHBEFK2C6oOg8niSmWHp/OHpbNsTh7/WHAOkwamcmZuKgCrt0spSwiMJjjTNSFh3Z9kGnoYkGAnAGQmVgjZs1odB50P1nh9x9KLDAYDsyf2Y1hGAgCXjM0EpJQlhNsZ88AcDcXfwKHP9B6NOE0S7ASALCgYQna7gp3hs/QdR4DNcgU7Xx8+QWltk86jESIIxKbCBNc09Ld+Cg2V+o5HnBYJdgKgpkmCnZBQXwFH16vzCAt2spJiyMtJxumEu/+xjQZbq95DEkJ/F/0WUnKhuhDe/qmUs0KYBDsBIGWsIOR0tv9Lbe9/wOmAjHGQnKPPuHT0y4uHYzUbKdhVypw/fSUZHiGik+CHL6gevt3vqRXVRUiSYCcAJNgJQv99EB4ZDGuf8dy2xzULa0RkZXU05w3rw6s3nU1qnIVtx6q54+/f6D0kIfSXPREu/p06/3AxHN2o73jEKZFgJwAk2Aky9hb4eiXghA9+DVtfh1Yb7Puvun/4JboOT0+TBqbw+s1nA7BmdxlHKhsAePmrw/xw+ZeU1TbrOTwh9HHWTTDqcnC0wN9uhDrZVy7USLATAO6p59ES7ASFfQXQWAm41jx6+6dQ8Fuw1UJ8hvpLLoINz0hwbxb6xoYjHK9u5P53d7Dh0An+uemozqMTQgcGA1zxNKQMUv07r80Bm2yvEkok2AkAWWcnyHzzhjpO+V+1SrKjFdY+rW4bdjEY5b/F3LMGAPC3jUd44j97sLU6APh8X7mewxJCP9FJcO3fICYFjm2Ef/wEHHa9RyW6SH6rB4CUsYJIU41qNASYcA1c8QwMzffcPyJyS1jeLhqdQVqchZKaZv620ZPNWX+wkqYW+QUvIlT6MJj7Opis6vfI+3fIDK0QIcFOL2mwtbK58ATNrXZZZyeY7PwXtDZB+nDIygNTFFz9Igz5jvp8yHf0HmFQsJiNXDWpv/vz74zsS0aileZWB18fOqHjyITQ2YCz4aoVgAE2/Nl3koMIWhLs9JKNh09w5R+/ZOySDyivswGQFCvBju60Etb4qz07mVvi4Po34X8/gagY/cYWZK450zP9/lcXj+BcVx/PZ/tUc2ajzY7DIX/Vigg0+gqY+Xt1/tF9UPKtrsMRJyfBTi+prLeRGmehxa7eDOIsJtLiLDqPKsLVFMHBT9X5uB/qO5YQMLhPPM9eewbLr5vE6OxEzhumgp0v9pWz83gN5z78X2Yu+5TialmPR0SgsxfAiEvVDK23bgG7LMQZzAxOZ2QXHGtqakhKSqK6uprExMQefW6n08nRE41sPVrFwNQ4xvVP6tHnF9305R/gP/fAgKnwo9V6jybklNY2cdbvCjAYICsxmiJXkDM4PY7Xbz6bvonROo9QiACrLYZnpkBTFVy4GM77pd4jiijdef+WzE4vMhgM5KTG8r3x2RLoBAPvEpbotr4J0YzMTMDphKLqJgakxtIvOYYD5fX8z5/XUdVg03uIQgRWQibMekidr3kISnephuU9H8DKS+CPU+HwWn3HKAAJdkSkKFwHxdvAGAWjZ+s9mpClrb8TbzXzlxsm89pNZ5OVFM2+0jpue2OL9PCIyDPhGrVkhd0Gf/8RLJ8Gr14NhV9C6Q544bvw39+pxUyFbiTYEaGrbDf8515PH05Hjm6EV109OqMvV7sZi1Pyo2mD+N74LP58w2SGZSQwIC2Wv9xwJlazkTW7y3iyYK/eQxQisAwG+N4ysCZC6bdQsh0s8XDOz9Wu6U4HfPoIrJwFlQf0Hm3ECopg55lnniE3N5fo6GimTJnC+vXrO73+b3/7GyNHjiQ6Oppx48bx3nvv+dzvdDpZvHgxWVlZxMTEkJ+fz9698ks4bNQWwzs/hz+eDV8+BasuU39R1Rxvf23hOnjxCmiqhpyz1S8lccqyk2N4+n/O4OzBae7bRmcn8vsrxwHwZMFeCnaW6DU8IfSR1A9mPwuZ4+CC38AvtsPFD8CVy+EHK8GaBMe+hj9Nhx3v6D3aiKR7sPPGG2+waNEilixZwqZNm5gwYQIzZ86ktLTU7/Vffvklc+fO5cc//jGbN29m9uzZzJ49m+3bt7uveeSRR3jqqadYvnw569atIy4ujpkzZ9LUJLNGQlpzrUoHPzURNq1SfzH1mwwGI2z/Bzx9JnzyKHzzN9jxNmx+GV66Um0DkXseXPcPiO7ZJnShXDWpP9efPRCAW1/fwr7SWr/XOZ1OvjlaRV2zzFwRYWbU9+D/fQ7T71CrLGvGXgULvlB/bDXXwF+vhw9+I2WtANN9NtaUKVM488wzefpptVy/w+EgJyeHn/3sZ9x1113trp8zZw719fW8++677tvOPvts8vLyWL58OU6nk+zsbH75y1/yq1/9CoDq6moyMjJ44YUXuOaaa3yerzdnY4kedugLVf8G6H+W+stpwNlQtAX+/Uv1l5M/gy+Aa14FS2zAhhqJbK0OrvvzOtYfqiQ3LZbfXDqaL/aV09xq5/xhfUiOtfDYf3az8fAJBqTGsvLGyQztm6D3sIUIDHuLWpNH25pmwDkw5WbIGAupg8Fo0nV4oag779+6Bjs2m43Y2Fj+/ve/M3v2bPftN9xwA1VVVbz99tvtHjNgwAAWLVrEbbfd5r5tyZIlvPXWW2zdupUDBw4wZMgQNm/eTF5envua6dOnk5eXx5NPPunzfBLshJj374SB58KoyzyLAgI4HLDlFdj1LrQ0qmbB1mboNwkufhCiZFp0IJTXNXPF019wrKrxpNcmRJu5feaIHl1ZvMXuZOfxGjYVnqC8Tu3QbsCAwQBGg4Hzh6Xz2yvG9tjrCdFtO95R6/LYvLKf5mi1qnvKQEgeCCm56vdbfQU0lENjFVjjITYd4tIhKhYaT0BDhfoAiE1T98Wkgqk31nRzun6vNkFLE9ib1euYo9VirCYL7s2VcargrrVJ/R5ubVJbbYy6rEdH1J33b3OPvnI3lZeXY7fbycjI8Lk9IyODXbt2+X1McXGx3+uLi4vd92u3dXSNPzU1NT6fW61WrFZr174QETiXPOz/dqMRzrhefQjdpMdbeW7eJK7/y3qizUamj+hLrMXEf3eVcqSyge+f0Y8bzxnEkne2s+HQCRa/HdiVZ0dkSCZJ6Gz05ZAxRq37VfwNlO6ElgZ1XvyN3qPrPWOu7PFgpzt0DXaCSU5Ojs/nS5Ys4b777tNnMEKEsDHZSWy69yKcTicGV/bt3u+NxuFwYjSqz1/+yRSeKtjL1iPVPfraBgPkpsVxxsBkBqbFAdo+jU4cTkiRLVtEMEgbApctU+cOB5w4COV74MRhqDqsjgaDJ1sTnQy2OqgvV5keW4OaVRqb5pld2lCp7m+sBEcv9cSZLGC2gjkGzBaVvWlpVJkbe5t1toxRrmujVWY9+4zeGVMX6RrspKenYzKZKCnxnb1RUlJCZmam38dkZmZ2er12LCkpISsry+ca77JWW0eOHPFJg0lWR4jTY/AuM4I70AGwmk3cPnNkoIckRPAxGlXwkzZE75GENV1nY1ksFiZNmkRBQYH7NofDQUFBAVOnTvX7mKlTp/pcD/Dhhx+6rx80aBCZmZk+19TU1LBu3boOnxMgMTHR50OCHSGEECI86F7GWrRoETfccAOTJ0/mrLPOYtmyZdTX1zN//nwA5s2bR79+/Vi6dCkAt956K9OnT+fxxx/n0ksv5fXXX+frr7/mueeeA9Rfk7fddhsPPvggw4YNY9CgQdx7771kZ2f7NEELIYQQIjLoHuzMmTOHsrIyFi9eTHFxMXl5eaxevdrdYFxYWIjR6ElAnXPOObz66qvcc889/PrXv2bYsGG89dZbjB3rmWFxxx13UF9fz80330xVVRXTpk1j9erVREfLjBwhhBAi0ui+zo7eZOq5EEIIEXpk13MhhBBCCBcJdoQQQggR1iTYEUIIIURYk2BHCCGEEGFNgh0hhBBChDUJdkJYc3Mz9913H83NzXoPJeTI9+7Uyffu1Mn37tTJ9+7UyfdOpp6H9NTzUB673uR7d+rke3fq5Ht36uR7d+rC9XsnU8+FEEIIIVwk2BFCCCFEWNN9uwi9aVW8mpoanUfSfdqYQ3HsepPv3amT792pk+/dqZPv3akL1++d9vV0pRsn4nt2jh49Sk5Ojt7DEEIIIcQpOHLkCP379+/0mogPdhwOB0VFRSQkJGAwGPQejhBCCCG6wOl0UltbS3Z2ts+G4f5EfLAjhBBCiPAmDcpCCCGECGsS7AghhBAirEmwI4QQQoiwJsFOiHvooYcwGAzcdttteg8lJBw7dozrrruOtLQ0YmJiGDduHF9//bXewwp6drude++9l0GDBhETE8OQIUN44IEHujTlMxJ9+umnXHbZZWRnZ2MwGHjrrbd87nc6nSxevJisrCxiYmLIz89n7969+gw2yHT2vWtpaeHOO+9k3LhxxMXFkZ2dzbx58ygqKtJvwEHkZD933v7f//t/GAwGli1bFrDx6UmCnRC2YcMG/vSnPzF+/Hi9hxISTpw4wbnnnktUVBTvv/8+O3bs4PHHHyclJUXvoQW9hx9+mGeffZann36anTt38vDDD/PII4/whz/8Qe+hBaX6+nomTJjAM8884/f+Rx55hKeeeorly5ezbt064uLimDlzJk1NTQEeafDp7HvX0NDApk2buPfee9m0aRP//Oc/2b17N5dffrkOIw0+J/u507z55pt89dVXZGdnB2hkQcApQlJtba1z2LBhzg8//NA5ffp056233qr3kILenXfe6Zw2bZrewwhJl156qfNHP/qRz23f//73nddee61OIwodgPPNN990f+5wOJyZmZnORx991H1bVVWV02q1Ol977TUdRhi82n7v/Fm/fr0TcB4+fDgwgwoRHX3vjh496uzXr59z+/btzoEDBzr/7//+L+Bj04NkdkLUT3/6Uy699FLy8/P1HkrIeOedd5g8eTI//OEP6du3LxMnTmTFihV6DysknHPOORQUFLBnzx4Atm7dyueff84ll1yi88hCz8GDBykuLvb5v5uUlMSUKVNYu3atjiMLTdXV1RgMBpKTk/UeStBzOBxcf/313H777YwZM0bv4QRUxG8XEYpef/11Nm3axIYNG/QeSkg5cOAAzz77LIsWLeLXv/41GzZs4Oc//zkWi4UbbrhB7+EFtbvuuouamhpGjhyJyWTCbrfzu9/9jmuvvVbvoYWc4uJiADIyMnxuz8jIcN8nuqapqYk777yTuXPnhtVu3r3l4Ycfxmw28/Of/1zvoQScBDsh5siRI9x66618+OGHREdH6z2ckOJwOJg8eTK///3vAZg4cSLbt29n+fLlEuycxF//+ldeeeUVXn31VcaMGcOWLVu47bbbyM7Olu+d0EVLSwtXX301TqeTZ599Vu/hBL2NGzfy5JNPsmnTpojcLUDKWCFm48aNlJaWcsYZZ2A2mzGbzXzyySc89dRTmM1m7Ha73kMMWllZWYwePdrntlGjRlFYWKjTiELH7bffzl133cU111zDuHHjuP766/nFL37B0qVL9R5ayMnMzASgpKTE5/aSkhL3faJzWqBz+PBhPvzwQ8nqdMFnn31GaWkpAwYMcL93HD58mF/+8pfk5ubqPbxeJ5mdEHPhhReybds2n9vmz5/PyJEjufPOOzGZTDqNLPide+657N692+e2PXv2MHDgQJ1GFDoaGhra7T1jMplwOBw6jSh0DRo0iMzMTAoKCsjLywPU7s3r1q1jwYIF+g4uBGiBzt69e/n4449JS0vTe0gh4frrr2/X4zlz5kyuv/565s+fr9OoAkeCnRCTkJDA2LFjfW6Li4sjLS2t3e3C1y9+8QvOOeccfv/733P11Vezfv16nnvuOZ577jm9hxb0LrvsMn73u98xYMAAxowZw+bNm3niiSf40Y9+pPfQglJdXR379u1zf37w4EG2bNlCamoqAwYM4LbbbuPBBx9k2LBhDBo0iHvvvZfs7Gxmz56t36CDRGffu6ysLH7wgx+wadMm3n33Xex2u7vPKTU1FYvFotewg8LJfu7aBoZRUVFkZmYyYsSIQA818PSeDiZOn0w977p//etfzrFjxzqtVqtz5MiRzueee07vIYWEmpoa56233uocMGCAMzo62jl48GDnb37zG2dzc7PeQwtKH3/8sRNo93HDDTc4nU41/fzee+91ZmRkOK1Wq/PCCy907t69W99BB4nOvncHDx70ex/g/Pjjj/Ueuu5O9nPXViRNPZddz4UQQggR1qRBWQghhBBhTYIdIYQQQoQ1CXaEEEIIEdYk2BFCCCFEWJNgRwghhBBhTYIdIYQQQoQ1CXaEEBHF4XBw8803k5WVxc0334ysviFE+JNgRwgRUT744AP27NnD+++/z65du1i9erXeQxJC9DIJdoQQIWfGjBncdtttHd5/3333YTAYMBgMLFu2zOe+pKQkUlJSGDp0KKmpqaSmpvrc/8ILL7gf29lrCCFChwQ7QoiwNGbMGI4fP87NN9/sc/s555yDzWYjKSkJu93OlClTfO6fM2cOx48fZ+rUqYEcrhCiF0mwI4QIS2azmczMTGJjY31ub2lpYcOGDdxxxx1s2LCB1tZWn/tjYmLIzMyM+E0lhQgnEuwIIYJafX098+bNIz4+nqysLB5//PHTer5///vfWCwW7r//fkwmE++9914PjVQIEawk2BFCBLXbb7+dTz75hLfffpv//Oc/rFmzhk2bNp3y8z3//PPMnTuXqKgo5s6dy/PPP9+DoxVCBCOz3gMQQoiO1NXV8Ze//IWXX36ZCy+8EIBVq1bRv3//U3q+kpIS3nvvPe6//34ArrvuOs466yzKysro06dPj41bCBFcJLMjhAha+/fvx2az+TQRp6amMmLEiFN6vpdffpmRI0cyYcIEAPLy8hg+fDivvPJKj4xXCBGcJNgRQkSM559/nm+//Raz2ez+2LFjBy+88ILeQxNC9CIpYwkhgtaQIUOIiopi3bp1DBgwAIATJ06wZ88epk+f3q3n2rBhAzt27GDNmjU+a+tUVVVx/vnns3nzZiZOnNij4xdCBAcJdoQQQSs+Pp4f//jH3H777aSlpdG3b19+85vfYDR2Pyn9/PPPc9ZZZ3H++ee3u2/q1Kk8//zzEuwIEaakjCWECGqPPvoo5513Hpdddhn5+flMmzaNSZMmdes5mpqaeO2117jqqqv83n/VVVfx6quvYrPZemLIQoggY3DKLnhCiDBz33338dZbb7Fly5ZTfo4ZM2aQl5fXbrsJIUTokcyOECIsbdu2jfj4eP74xz9263GvvPIK8fHxfPbZZ700MiFEoElmRwgRdiorK6msrASgT58+JCUldfmxtbW1lJSUAJCcnEx6enqvjFEIETgS7AghhBAirEkZSwghhBBhTYIdIYQQQoQ1CXaEEEIIEdYk2BFCCCFEWJNgRwghhBBhTYIdIYQQQoQ1CXaEEEIIEdYk2BFCCCFEWJNgRwghhBBhTYIdIYQQQoS1/w/28LvhANS5rAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_contact_hists(df_TW)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "1bab405c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████| 100/100 [00:00<00:00, 121.26it/s]\n"
     ]
    }
   ],
   "source": [
    "rs = []\n",
    "mccs = []\n",
    "\n",
    "for r in tqdm(np.linspace(1, 10, 100)):\n",
    "    rs.append(r)\n",
    "    mccs.append(\n",
    "        sklearn.metrics.matthews_corrcoef(df_TW[\"aa_contact\"], df_TW[\"dcg\"] < r)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "809a65bf",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfx = df_TW\n",
    "\n",
    "aac_hist, aac_edges = np.histogram(dfx[dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "aac_rdf = aac_hist / ((3/4)*(np.pi)*aac_edges[1:]**3)\n",
    "\n",
    "aanc_hist, aanc_edges = np.histogram(dfx[~dfx[\"aa_contact\"]][\"dcg\"], N_BINS)\n",
    "aanc_rdf = aanc_hist / ((3/4)*(np.pi)*aanc_edges[1:]**3)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(aac_edges[1:], aac_rdf, label=\"contact\")\n",
    "ax.plot(aanc_edges[1:], aanc_rdf, label=\"no contact\")\n",
    "ax.tick_params(direction=\"in\")\n",
    "ax.set_xlabel(\"d [Å]\")\n",
    "ax.set_ylabel(\"n\")\n",
    "\n",
    "ax1 = ax.twinx()\n",
    "ax1.plot(rs, mccs, color=\"red\",linestyle=\"dashed\")\n",
    "ax1.tick_params(axis='y', labelcolor=\"red\")\n",
    "ax1.set_ylabel('MCC', color=color)\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "c098d119",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 0.6399067884183385,\n",
       " 0.6219460496129536,\n",
       " 0.601699461198225,\n",
       " 0.583652765247771,\n",
       " 0.5654759988727025,\n",
       " 0.5493308091038163,\n",
       " 0.5325812633436008,\n",
       " 0.5163973020994154,\n",
       " 0.5008802438679064,\n",
       " 0.4846108542151995,\n",
       " 0.46965092972371325,\n",
       " 0.45494208182446655,\n",
       " 0.4392500234612168,\n",
       " 0.42577693201660866,\n",
       " 0.41160532923849696,\n",
       " 0.39766113608932324]"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mccs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "801bda03",
   "metadata": {},
   "outputs": [],
   "source": [
    "realvals = df_TW[\"aa_contact\"].to_numpy()\n",
    "dcgs = df_TW[\"dcg\"].to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "3f0de0e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fun(r,realvals,dcgs):\n",
    "#     preds =\n",
    "    return -sklearn.metrics.matthews_corrcoef(realvals, dcgs < r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "1c989d28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.8735173403727619"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fun(7,realvals,dcgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "id": "d55ed0e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "minres = minimize(fun,5,args=(realvals,dcgs), tol=0.005,method=\"Powell\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "id": "d0d6abf6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.16722828787032"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minres.x[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5342ad7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "e39fa8bd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0       True\n",
       " 1       True\n",
       " 2       True\n",
       " 3       True\n",
       " 4       True\n",
       "         ... \n",
       " 5903    True\n",
       " 5904    True\n",
       " 5905    True\n",
       " 5906    True\n",
       " 5907    True\n",
       " Name: dcg, Length: 11818010, dtype: bool,\n",
       " 0       False\n",
       " 1       False\n",
       " 2       False\n",
       " 3       False\n",
       " 4        True\n",
       "         ...  \n",
       " 5903    False\n",
       " 5904     True\n",
       " 5905    False\n",
       " 5906    False\n",
       " 5907     True\n",
       " Name: aa_contact, Length: 11818010, dtype: bool)"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"dcg\"] > 4, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe0293ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e77907dc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eba5d335",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72ddae5c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "b79ee804",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "daas = dfc[\"daa\"].to_numpy()\\\n",
    "\n",
    "hist, edges = np.histogram(daas, N_BINS)\n",
    "rdf = hist / ((3/4)*(np.pi)*edges[1:]**3)\n",
    "plt.plot(edges[1:], rdf)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "2ec8cba5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "daas = df[\"dcg\"].to_numpy()\\\n",
    "\n",
    "hist, edges = np.histogram(daas, N_BINS)\n",
    "rdf = hist / ((3/4)*(np.pi)*edges[1:]**3)\n",
    "plt.plot(edges[1:], rdf)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "bab76ec9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.00000e+00, 3.00000e+00, 0.00000e+00, 0.00000e+00, 1.00000e+00,\n",
       "        0.00000e+00, 1.00000e+00, 2.00000e+00, 6.00000e+00, 8.00000e+00,\n",
       "        8.00000e+00, 1.90000e+01, 4.10000e+01, 1.05900e+03, 1.05000e+03,\n",
       "        3.02000e+02, 5.67000e+02, 8.11000e+02, 2.41300e+03, 8.14000e+03,\n",
       "        2.02990e+04, 2.79130e+04, 3.38860e+04, 2.87310e+04, 2.07870e+04,\n",
       "        1.89450e+04, 2.55900e+04, 3.97080e+04, 6.26300e+04, 9.18190e+04,\n",
       "        1.25571e+05, 1.52327e+05, 1.72147e+05, 1.75041e+05, 1.69494e+05,\n",
       "        1.54400e+05, 1.41978e+05, 1.27817e+05, 1.13925e+05, 1.03918e+05,\n",
       "        9.73240e+04, 9.00890e+04, 8.68230e+04, 8.27860e+04, 8.13510e+04,\n",
       "        7.85730e+04, 7.75130e+04, 7.46370e+04, 7.51020e+04, 7.36730e+04,\n",
       "        7.34060e+04, 7.23550e+04, 7.42310e+04, 7.52470e+04, 8.03430e+04,\n",
       "        8.51640e+04, 9.47160e+04, 1.04523e+05, 1.19641e+05, 1.30783e+05,\n",
       "        1.39994e+05, 1.43661e+05, 1.50343e+05, 1.52705e+05, 1.58803e+05,\n",
       "        1.61592e+05, 1.68344e+05, 1.70942e+05, 1.75829e+05, 1.76612e+05,\n",
       "        1.78737e+05, 1.75286e+05, 1.77452e+05, 1.75454e+05, 1.80086e+05,\n",
       "        1.80686e+05, 1.85288e+05, 1.88040e+05, 1.97132e+05, 2.02159e+05,\n",
       "        2.13256e+05, 2.16533e+05, 2.19295e+05, 2.16460e+05, 2.21177e+05,\n",
       "        2.25276e+05, 2.36170e+05, 2.41201e+05, 2.49553e+05, 2.47700e+05,\n",
       "        2.51754e+05, 2.48634e+05, 2.53352e+05, 2.53990e+05, 2.57005e+05,\n",
       "        2.54174e+05, 2.56401e+05, 2.53188e+05, 2.57498e+05, 2.56610e+05]),\n",
       " array([ 0.75  ,  0.8425,  0.935 ,  1.0275,  1.12  ,  1.2125,  1.305 ,\n",
       "         1.3975,  1.49  ,  1.5825,  1.675 ,  1.7675,  1.86  ,  1.9525,\n",
       "         2.045 ,  2.1375,  2.23  ,  2.3225,  2.415 ,  2.5075,  2.6   ,\n",
       "         2.6925,  2.785 ,  2.8775,  2.97  ,  3.0625,  3.155 ,  3.2475,\n",
       "         3.34  ,  3.4325,  3.525 ,  3.6175,  3.71  ,  3.8025,  3.895 ,\n",
       "         3.9875,  4.08  ,  4.1725,  4.265 ,  4.3575,  4.45  ,  4.5425,\n",
       "         4.635 ,  4.7275,  4.82  ,  4.9125,  5.005 ,  5.0975,  5.19  ,\n",
       "         5.2825,  5.375 ,  5.4675,  5.56  ,  5.6525,  5.745 ,  5.8375,\n",
       "         5.93  ,  6.0225,  6.115 ,  6.2075,  6.3   ,  6.3925,  6.485 ,\n",
       "         6.5775,  6.67  ,  6.7625,  6.855 ,  6.9475,  7.04  ,  7.1325,\n",
       "         7.225 ,  7.3175,  7.41  ,  7.5025,  7.595 ,  7.6875,  7.78  ,\n",
       "         7.8725,  7.965 ,  8.0575,  8.15  ,  8.2425,  8.335 ,  8.4275,\n",
       "         8.52  ,  8.6125,  8.705 ,  8.7975,  8.89  ,  8.9825,  9.075 ,\n",
       "         9.1675,  9.26  ,  9.3525,  9.445 ,  9.5375,  9.63  ,  9.7225,\n",
       "         9.815 ,  9.9075, 10.    ]),\n",
       " <BarContainer object of 100 artists>)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df[\"daa\"].to_numpy(), bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "e637d8ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[\"daa\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b220402c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e1acadd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db3e3c9f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "id": "54105d75",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfg = df.groupby([\"aa1\",\"aa2\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "id": "10435518",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('C', 'C')\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "Interrupted by user",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[304], line 4\u001b[0m\n\u001b[1;32m      2\u001b[0m g_key, g_df \u001b[38;5;241m=\u001b[39m g\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28mprint\u001b[39m(g_key)\n\u001b[0;32m----> 4\u001b[0m \u001b[38;5;28;43minput\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/surpass2/lib/python3.10/site-packages/ipykernel/kernelbase.py:1191\u001b[0m, in \u001b[0;36mKernel.raw_input\u001b[0;34m(self, prompt)\u001b[0m\n\u001b[1;32m   1189\u001b[0m     msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraw_input was called, but this frontend does not support input requests.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1190\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m StdinNotImplementedError(msg)\n\u001b[0;32m-> 1191\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_input_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1192\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mprompt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1193\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_parent_ident\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mshell\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1194\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_parent\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mshell\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1195\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpassword\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   1196\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/surpass2/lib/python3.10/site-packages/ipykernel/kernelbase.py:1234\u001b[0m, in \u001b[0;36mKernel._input_request\u001b[0;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[1;32m   1231\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyboardInterrupt\u001b[39;00m:\n\u001b[1;32m   1232\u001b[0m     \u001b[38;5;66;03m# re-raise KeyboardInterrupt, to truncate traceback\u001b[39;00m\n\u001b[1;32m   1233\u001b[0m     msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInterrupted by user\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1234\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyboardInterrupt\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1235\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m   1236\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlog\u001b[38;5;241m.\u001b[39mwarning(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid Message:\u001b[39m\u001b[38;5;124m\"\u001b[39m, exc_info\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: Interrupted by user"
     ]
    }
   ],
   "source": [
    "for g in dfg:\n",
    "    g_key, g_df = g\n",
    "    print(g_key)\n",
    "    input()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2eaf3f36",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6a672b3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42e6df61",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "628ddbf6",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('C', 'C')\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "Interrupted by user",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[48], line 5\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28minput\u001b[39m()\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28mtype\u001b[39m(d))\n\u001b[0;32m----> 5\u001b[0m \u001b[38;5;28;43minput\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/surpass2/lib/python3.10/site-packages/ipykernel/kernelbase.py:1191\u001b[0m, in \u001b[0;36mKernel.raw_input\u001b[0;34m(self, prompt)\u001b[0m\n\u001b[1;32m   1189\u001b[0m     msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mraw_input was called, but this frontend does not support input requests.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1190\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m StdinNotImplementedError(msg)\n\u001b[0;32m-> 1191\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_input_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1192\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mstr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mprompt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1193\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_parent_ident\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mshell\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1194\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_parent\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mshell\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1195\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpassword\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   1196\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/surpass2/lib/python3.10/site-packages/ipykernel/kernelbase.py:1234\u001b[0m, in \u001b[0;36mKernel._input_request\u001b[0;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[1;32m   1231\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyboardInterrupt\u001b[39;00m:\n\u001b[1;32m   1232\u001b[0m     \u001b[38;5;66;03m# re-raise KeyboardInterrupt, to truncate traceback\u001b[39;00m\n\u001b[1;32m   1233\u001b[0m     msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInterrupted by user\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1234\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyboardInterrupt\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1235\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m:\n\u001b[1;32m   1236\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlog\u001b[38;5;241m.\u001b[39mwarning(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid Message:\u001b[39m\u001b[38;5;124m\"\u001b[39m, exc_info\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: Interrupted by user"
     ]
    }
   ],
   "source": [
    "for aapair, d in dfg:\n",
    "    print(aapair)\n",
    "    input()\n",
    "    print(type(d))\n",
    "    input()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a928840a",
   "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>aa1</th>\n",
       "      <th>aa2</th>\n",
       "      <th>dij</th>\n",
       "      <th>dcg</th>\n",
       "      <th>daa</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D</td>\n",
       "      <td>F</td>\n",
       "      <td>1</td>\n",
       "      <td>6.693</td>\n",
       "      <td>6.319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>7.283</td>\n",
       "      <td>5.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M</td>\n",
       "      <td>D</td>\n",
       "      <td>1</td>\n",
       "      <td>6.490</td>\n",
       "      <td>5.718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>N</td>\n",
       "      <td>F</td>\n",
       "      <td>3</td>\n",
       "      <td>10.526</td>\n",
       "      <td>9.412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>N</td>\n",
       "      <td>D</td>\n",
       "      <td>2</td>\n",
       "      <td>5.950</td>\n",
       "      <td>4.843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5716</th>\n",
       "      <td>T</td>\n",
       "      <td>D</td>\n",
       "      <td>75</td>\n",
       "      <td>10.889</td>\n",
       "      <td>9.611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5717</th>\n",
       "      <td>T</td>\n",
       "      <td>K</td>\n",
       "      <td>60</td>\n",
       "      <td>11.738</td>\n",
       "      <td>9.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5718</th>\n",
       "      <td>T</td>\n",
       "      <td>Y</td>\n",
       "      <td>3</td>\n",
       "      <td>7.714</td>\n",
       "      <td>5.734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5719</th>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>2</td>\n",
       "      <td>9.535</td>\n",
       "      <td>8.242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5720</th>\n",
       "      <td>T</td>\n",
       "      <td>S</td>\n",
       "      <td>1</td>\n",
       "      <td>6.283</td>\n",
       "      <td>5.723</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5721 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     aa1 aa2  dij     dcg    daa\n",
       "0      D   F    1   6.693  6.319\n",
       "1      M   F    2   7.283  5.421\n",
       "2      M   D    1   6.490  5.718\n",
       "3      N   F    3  10.526  9.412\n",
       "4      N   D    2   5.950  4.843\n",
       "...   ..  ..  ...     ...    ...\n",
       "5716   T   D   75  10.889  9.611\n",
       "5717   T   K   60  11.738  9.825\n",
       "5718   T   Y    3   7.714  5.734\n",
       "5719   T   F    2   9.535  8.242\n",
       "5720   T   S    1   6.283  5.723\n",
       "\n",
       "[5721 rows x 5 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(fname, delim_whitespace=True, index_col=False, names=[\"aa1\", \"aa2\", \"dij\", \"dcg\", \"daa\"], skiprows=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4908a186",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['#aaij dij    dcg    d_aa\\n', 'D F    1   6.693   6.319\\n', 'M F    2   7.283   5.421\\n', 'M D    1   6.490   5.718\\n', 'N F    3  10.526   9.412\\n', 'N D    2   5.950   4.843\\n', 'N M    1   5.124   4.179\\n', 'R F    4  10.574   9.486\\n', 'R D    3   5.646   4.977\\n', 'R M    2  11.283   9.898\\n', 'R N    1   8.869   7.027\\n', 'V F    5   6.835   5.454\\n', 'V D    4   7.676   6.674\\n', 'V M    3   8.576   6.077\\n', 'V N    2   9.395   8.058\\n', 'V R    1   8.319   7.725\\n', 'I F    6  10.468   7.593\\n', 'I D    5   9.004   7.615\\n', 'I M    4   6.820   5.034\\n', 'I N    3   6.219   5.033\\n', 'I R    2  10.448   7.981\\n', 'I V    1   6.208   3.823\\n', 'D D    6   9.644   7.939\\n', 'D M    5   9.924   9.305\\n', 'D N    4   6.353   5.555\\n', 'D R    3   8.902   5.583\\n', 'D V    2   8.794   8.114\\n', 'D I    1   4.973   3.432\\n', 'E D    7  10.475   9.036\\n', 'E R    4   6.767   5.008\\n', 'E V    3   6.793   6.026\\n', 'E I    2   9.552   8.342\\n', 'E D    1   8.363   6.790\\n', 'F V    4   7.972   6.885\\n', 'F I    3   7.782   6.411\\n', 'F D    2  10.521   8.719\\n', 'F E    1  10.217   8.253\\n', 'D I    4   7.405   6.126\\n', 'D D    3   6.903   5.458\\n', 'D E    2  11.388   9.669\\n', 'D F    1   7.688   5.871\\n', 'E R    7  13.055   9.807\\n', 'E D    4   8.204   6.953\\n', 'E E    3   8.637   6.716\\n', 'E F    2  11.499   9.580\\n', 'E D    1   7.442   6.883\\n', 'M V    7  10.060   8.926\\n', 'M E    4   8.670   7.656\\n', 'M F    3   6.079   4.498\\n', 'M D    2  10.586   9.418\\n', 'M E    1  10.258   7.609\\n', 'T I    7   9.884   9.279\\n', 'T D    6  10.956   9.472\\n', 'T F    4   4.356   3.639\\n', 'T D    3   5.831   4.216\\n', 'T E    2   9.287   7.425\\n', 'T M    1   6.142   5.204\\n', 'R D    7  11.266   9.304\\n', 'R F    5  11.085   8.457\\n', 'R D    4   5.266   4.275\\n', 'R E    3   7.685   6.035\\n', 'R M    2  12.133   8.595\\n', 'R T    1   7.309   4.232\\n', 'N E    7  10.932   9.371\\n', 'N D    5   9.845   8.621\\n', 'N E    4   5.487   3.395\\n', 'N M    3   8.306   6.636\\n', 'N T    2   8.448   7.218\\n', 'N R    1   8.172   5.831\\n', 'H R    3  11.251   9.272\\n', 'H N    2   9.882   8.571\\n', 'Q E    7   9.848   7.590\\n', 'Q M    6   9.609   7.696\\n', 'Q N    3   5.100   3.037\\n', 'Q H    1  10.428   8.282\\n', 'V F   10  10.150   9.717\\n', 'V E    8  11.122   9.240\\n', 'V M    7   4.885   4.523\\n', 'V T    6   8.266   7.455\\n', 'V R    5  12.385   9.255\\n', 'V N    4   6.788   5.697\\n', 'V H    2   9.256   7.361\\n', 'V Q    1   6.161   5.514\\n', 'Q M    8   8.947   7.480\\n', 'Q T    7  10.659   9.351\\n', 'Q H    3   8.200   6.466\\n', 'Q Q    2  10.906   9.207\\n', 'Q V    1   5.956   5.115\\n', 'K H    4   9.324   7.472\\n', 'K Q    3   9.024   6.918\\n', 'K V    2  10.498   8.997\\n', 'K Q    1  10.166   7.960\\n', 'Q N    7  10.518   8.490\\n', 'Q Q    4   5.495   4.029\\n', 'Q V    3   8.454   6.888\\n', 'Q Q    2  11.361   9.526\\n', 'Q K    1   6.855   5.899\\n', 'T M   11   8.410   6.891\\n', 'T Q    5   9.733   8.401\\n', 'T V    4   5.696   3.749\\n', 'T Q    3   5.700   4.827\\n', 'T K    2  10.353   8.375\\n', 'T Q    1   8.418   6.766\\n', 'L Q    4   9.032   8.466\\n', 'L K    3   7.364   5.758\\n', 'L Q    2   9.842   8.316\\n', 'L T    1   7.982   7.383\\n', 'K Q    7   9.999   8.586\\n', 'K K    4   4.448   2.789\\n', 'K Q    3   5.397   3.256\\n', 'K T    2   9.525   7.977\\n', 'K L    1   6.081   5.437\\n', 'E M   14  11.000   9.456\\n', 'E Q    8   9.203   7.422\\n', 'E V    7   8.699   6.695\\n', 'E K    5  11.389   9.672\\n', 'E Q    4   6.072   5.164\\n', 'E T    3   5.995   5.499\\n', 'E L    2  10.276   8.623\\n', 'E K    1   8.771   5.853\\n', 'I V    8  11.534   9.639\\n', 'I Q    7   9.786   8.018\\n', 'I T    4   5.850   3.652\\n', 'I L    3   6.849   5.867\\n', 'I K    2  10.351   8.719\\n', 'I E    1   7.849   6.456\\n', 'L T    5  10.327   8.451\\n', 'L L    4   5.087   3.707\\n', 'L K    3   8.632   8.022\\n', 'L E    2  10.918   8.982\\n', 'L I    1   6.093   3.967\\n', 'L Q    7   8.905   7.213\\n', 'L L    5  10.511   9.511\\n', 'L K    4   7.832   6.603\\n', 'L E    3   7.963   6.091\\n', 'L I    2  10.403   9.536\\n', 'L L    1   8.752   7.841\\n', 'K T    7  11.478   9.406\\n', 'K E    4   7.430   6.221\\n', 'K I    3   8.901   6.623\\n', 'K L    2  10.602   8.750\\n', 'K L    1   6.989   6.309\\n', 'N I    4   9.116   7.087\\n', 'N L    3   7.717   6.950\\n', 'N K    1   8.777   7.573\\n', 'Q L    4   9.298   7.907\\n', 'Q L    3   6.740   4.377\\n', 'Q K    2   9.856   9.173\\n', 'Q N    1   8.403   6.137\\n', 'S L    4  10.504   9.578\\n', 'S N    2   5.705   4.865\\n', 'S Q    1   5.060   4.075\\n', 'I N    4   8.858   7.956\\n', 'I S    2   9.763   8.426\\n', 'Y L    8  10.895   9.173\\n', 'Y N    5  11.184   9.489\\n', 'Y I    1   8.678   6.115\\n', 'L L   13   9.812   8.468\\n', 'L I   10   9.974   7.873\\n', 'L L    9   5.365   4.286\\n', 'L N    6   6.488   5.236\\n', 'L Q    5   9.673   7.386\\n', 'L S    4   9.007   8.140\\n', 'L I    2   8.831   7.641\\n', 'L Y    1   6.683   3.886\\n', 'Q S    5  10.466   9.617\\n', 'Q I    3   6.740   4.953\\n', 'Q Y    2  10.931   9.165\\n', 'Q L    1   9.847   8.575\\n', 'N I    4   6.612   5.650\\n', 'N Y    3   7.498   5.506\\n', 'N L    2   9.345   8.485\\n', 'N Q    1   4.697   3.672\\n', 'C L   12   9.785   9.017\\n', 'C I    5  10.165   9.436\\n', 'C Y    4   4.527   4.188\\n', 'C L    3   5.718   5.148\\n', 'C Q    2   9.511   8.483\\n', 'C N    1   6.867   6.535\\n', 'L L   18   9.019   7.398\\n', 'L I   15  11.781   9.396\\n', 'L L   14   5.871   3.467\\n', 'L N   11   9.846   8.517\\n', 'L Q   10   9.675   8.531\\n', 'L Y    6   8.860   7.091\\n', 'L L    5   4.107   3.495\\n', 'L Q    4  10.535   8.489\\n', 'L N    3  10.356   9.048\\n', 'L C    2   5.609   4.529\\n', 'N L   15  10.970   9.245\\n', 'N L   14  11.310   9.350\\n', 'N Q   11   7.847   7.206\\n', 'N L    6  10.750   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5.101\\n', 'E L   22  10.702   9.395\\n', 'E D    2  10.359   9.217\\n', 'E P    1   6.681   6.071\\n', 'E K   30   8.804   7.209\\n', 'E L   27  10.102   8.712\\n', 'E K   26  11.046   8.707\\n', 'E T    4  11.093   9.215\\n', 'E D    3   7.435   5.790\\n', 'E P    2   7.598   6.016\\n', 'E E    1   5.690   4.835\\n', 'F K   32   9.499   7.666\\n', 'F Q   31  12.376   9.811\\n', 'F L   29   4.568   3.420\\n', 'F K   28   7.387   5.944\\n', 'F I   26   9.637   8.482\\n', 'F L   25   4.440   3.345\\n', 'F L   24  10.273   8.579\\n', 'F Q   21  10.870   9.218\\n', 'F L   16   7.431   6.516\\n', 'F C   13   9.577   8.441\\n', 'F L   11   5.081   3.443\\n', 'F N   10   9.251   7.143\\n', 'F N    8  10.916   9.232\\n', 'F D    5   8.586   7.778\\n', 'F P    4   6.421   5.547\\n', 'F E    3   7.970   5.650\\n', 'F E    2   9.645   8.577\\n', 'K H   37  11.943   9.229\\n', 'K Q   34  11.108   9.623\\n', 'K K   33   9.211   8.066\\n', 'K L   30   7.384   6.357\\n', 'K K   29  10.965   9.342\\n', 'K L   26  11.225   9.653\\n', 'K D    6  10.659   9.947\\n', 'K P    5   9.426   8.887\\n', 'K E    4   4.741   3.475\\n', 'K E    3   5.108   4.271\\n', 'K F    1   8.303   6.015\\n', 'S L   13   9.117   8.889\\n', 'S D    7   6.487   5.691\\n', 'S P    6   9.984   9.648\\n', 'S E    5  10.693   9.443\\n', 'S E    4   7.201   6.588\\n', 'S F    2   8.527   7.524\\n', 'S K    1   8.079   6.910\\n', 'M L   28  11.656   9.843\\n', 'M L   19  10.718   9.550\\n', 'M C   16   8.404   7.523\\n', 'M L   14   6.875   5.780\\n', 'M N   13   8.864   8.146\\n', 'M D    8   6.568   5.169\\n', 'M P    7  10.460   9.856\\n', 'M E    5  10.441   9.376\\n', 'M F    3   8.214   6.515\\n', 'M K    2  11.184   9.184\\n', 'M S    1   4.064   3.693\\n', 'V L   33   9.232   8.356\\n', 'V L   29   7.591   6.483\\n', 'V Y   21   6.261   4.137\\n', 'V L   20   5.699   5.164\\n', 'V N   18  10.499   9.946\\n', 'V C   17   3.701   3.570\\n', 'V L   15   4.782   3.687\\n', 'V F    4   6.756   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8.191\\n', 'L S   96   8.436   7.284\\n', 'L S   95  10.756   9.508\\n', 'L Y   94   4.954   3.673\\n', 'L I   93  10.583   9.395\\n', 'L D   92   8.518   8.350\\n', 'L F   81   8.129   5.912\\n', 'L R   38   9.051   6.932\\n', 'L I   28  10.972   9.788\\n', 'L C    9  10.068   8.893\\n', 'L V    8   5.201   3.473\\n', 'L K    7  11.311   9.425\\n', 'L P    6   8.319   7.660\\n', 'L S    5   9.404   9.234\\n', 'L N    4   7.644   6.825\\n', 'L K    2  11.190   9.257\\n', 'L V    1   7.491   6.611\\n', 'Q P  465  10.794   9.410\\n', 'Q I  463  10.074   9.368\\n', 'Q S  462  10.066   9.595\\n', 'Q F  447   8.610   7.244\\n', 'Q S  410   7.350   6.561\\n', 'Q K  408   9.358   7.581\\n', 'Q Q  407   3.761   3.180\\n', 'Q Y  406   9.247   6.411\\n', 'Q I  405   8.222   6.281\\n', 'Q S  404  10.456   9.944\\n', 'Q V  400  11.275   9.517\\n', 'Q P  399   7.728   6.108\\n', 'Q V  398   7.112   5.921\\n', 'Q T  396   6.285   4.768\\n', 'Q T  394   8.251   5.949\\n', 'Q T  393   4.133   3.163\\n', 'Q N  392   4.044   3.032\\n', 'Q V  391  10.643   8.686\\n', 'Q Y  390  11.167   8.985\\n', 'Q R  389   7.463   6.594\\n', 'Q N  388  10.771   9.226\\n', 'Q P  387  11.294   9.757\\n', 'Q F  366  10.321   8.779\\n', 'Q S  227  10.697   9.748\\n', 'Q K   30  10.754   9.287\\n', 'Q I   29  11.842   9.686\\n', 'Q K    3   9.373   7.964\\n', 'Q L    1   9.299   7.663\\n', 'I L  462   9.347   8.960\\n', 'I F  412  10.302   8.941\\n', 'I S  411   7.474   6.915\\n', 'I S  410   8.638   8.256\\n', 'I K  409   5.148   3.487\\n', 'I Q  408   9.641   7.806\\n', 'I Y  407  11.708   9.751\\n', 'I V  399  11.245   9.507\\n', 'I T  397   3.923   3.027\\n', 'I T  395   5.130   3.648\\n', 'I T  394   5.384   3.541\\n', 'I N  393   9.522   8.617\\n', 'I V  392  12.006   9.897\\n', 'I Y  391  10.255   8.760\\n', 'I R  390  10.158   9.361\\n', 'I F  367  11.224   9.525\\n', 'I V  363   7.983   7.049\\n', 'I S   98   9.967   9.109\\n', 'I F   83   9.523   7.435\\n', 'I E   81  10.306   8.200\\n', 'I V   38   7.909   6.299\\n', 'I T   34   4.805   3.415\\n', 'I F   33   8.515   7.428\\n', 'I R   32  10.377   9.349\\n', 'I K   31   4.505   3.392\\n', 'I I   30   6.070   4.250\\n', 'I E   28  10.887   9.215\\n', 'I H   27   8.041   6.033\\n', 'I F   26  10.820   9.435\\n', 'I K    4   7.871   5.857\\n', 'I V    3   6.345   5.461\\n', 'I L    2   9.902   9.121\\n', 'I Q    1   7.320   5.777\\n', 'L L  463  10.557   8.534\\n', 'L F  452  11.518   9.694\\n', 'L K  410   7.989   6.315\\n', 'L Y  408   4.675   3.354\\n', 'L I  407  10.303   9.071\\n', 'L T  405  10.625   9.614\\n', 'L V  400   8.816   7.758\\n', 'L T  398  10.645   9.292\\n', 'L S   99   8.127   7.174\\n', 'L S   98   9.806   8.799\\n', 'L Y   97   5.526   4.204\\n', 'L D   95   7.853   6.948\\n', 'L H   88   9.592   8.458\\n', 'L F   84   4.779   3.270\\n', 'L E   43   8.316   7.748\\n', 'L R   41   4.971   3.854\\n', 'L V   39   8.282   6.904\\n', 'L T   35   9.456   8.526\\n', 'L F   34  10.873   9.518\\n', 'L C   12  10.826   9.624\\n', 'L V   11   7.093   5.117\\n', 'L P    9  11.345   9.931\\n', 'L N    7  11.151   9.814\\n', 'L V    4   7.935   6.525\\n', 'L L    3   4.649   3.508\\n', 'L Q    2   9.861   8.007\\n', 'L I    1   8.999   7.702\\n', 'C K  411   8.475   7.596\\n', 'C Q  410  10.625   9.701\\n', 'C Y  409   4.661   3.409\\n', 'C I  408   8.370   7.906\\n', 'C V  401  10.593   9.842\\n', 'C Y   98   8.270   7.595\\n', 'C D   96   8.042   7.137\\n', 'C S   94  10.000  10.000\\n', 'C H   89   9.374   8.243\\n', 'C F   85   7.916   6.790\\n', 'C E   44   7.287   6.668\\n', 'C R   42   4.873   4.677\\n', 'C V   40   9.774   8.587\\n', 'C L    4   8.201   7.916\\n', 'C Q    3  10.295   8.944\\n', 'C L    1   4.585   3.429\\n', 'E S  414  10.688   9.551\\n', 'E S  413   7.001   6.481\\n', 'E K  412   7.981   5.858\\n', 'E Q  411   7.712   5.397\\n', 'E Y  410  10.151   7.991\\n', 'E I  409   9.501   8.023\\n', 'E T  397   9.606   7.809\\n', 'E R  393   6.648   4.488\\n', 'E F  370  10.618   8.939\\n', 'E S  369  10.294   9.269\\n', 'E P  368   6.346   4.744\\n', 'E D  367  11.369   9.266\\n', 'E V  308  10.360   9.158\\n', 'E S  306  10.212   9.236\\n', 'E V   41  11.465   9.846\\n', 'E Q    4   9.651   7.535\\n', 'E I    3  11.340   9.627\\n', 'E L    2  10.295   8.556\\n', 'E C    1   6.961   6.694\\n', 'N F  416   8.054   6.467\\n', 'N S  415   8.435   8.219\\n', 'N S  414   2.464   2.052\\n', 'N K  413   3.638   3.069\\n', 'N Q  412  10.552   8.637\\n', 'N T  399  10.603   9.394\\n', 'N T  398   8.416   7.927\\n', 'N R  394   8.076   5.721\\n', 'N V  373  10.790   9.972\\n', 'N I  372  10.793   9.187\\n', 'N F  371   9.231   7.643\\n', 'N S  370   6.236   5.959\\n', 'N P  369   5.554   4.640\\n', 'N D  368   7.115   6.170\\n', 'N V  367   4.093   3.134\\n', 'N H  366   8.487   7.069\\n', 'N Q  365   9.854   9.463\\n', 'N V  309   8.560   7.900\\n', 'N S  307   9.730   8.951\\n', 'N V  306  10.066   9.587\\n', 'N V   42   7.042   6.265\\n', 'N K   40  12.206   9.951\\n', 'N T   38   7.285   5.433\\n', 'N K   35   7.241   5.384\\n', 'N I    4   7.765   6.350\\n', 'N E    1   7.229   5.635\\n', 'V S  415   9.485   9.070\\n', 'V K  414   7.388   6.083\\n', 'V Y  412  10.279   8.647\\n', 'V P  370   8.706   7.098\\n', 'V D  369  10.845   9.702\\n', 'V V  310  10.202   8.589\\n', 'V H   92  11.626   9.793\\n', 'V F   88   8.475   6.344\\n', 'V E   79  10.732   9.797\\n', 'V E   47   7.076   5.171\\n', 'V L   46  10.916   9.544\\n', 'V R   45   6.284   4.008\\n', 'V V   44   9.112   8.624\\n', 'V V   43   7.617   5.709\\n', 'V T   39  10.834   9.997\\n', 'V L    4   8.258   6.868\\n', 'V C    3   5.681   5.306\\n', 'V E    2   6.827   5.479\\n', 'V N    1   7.836   7.203\\n', 'V S  416   8.883   7.636\\n', 'V K  415   7.743   6.279\\n', 'V S  372   8.509   7.520\\n', 'V P  371   8.774   7.717\\n', 'V D  370   6.634   5.593\\n', 'V V  369   7.929   6.353\\n', 'V H  368   4.399   3.475\\n', 'V Q  367   6.528   5.593\\n', 'V T  312   8.036   6.894\\n', 'V V  311   8.040   6.620\\n', 'V V  308  11.144   9.789\\n', 'V L  115  11.269   9.793\\n', 'V F   89  10.611   9.781\\n', 'V W   88  11.861   9.882\\n', 'V I   86   8.253   6.817\\n', 'V E   83   9.798   7.891\\n', 'V T   82  10.286   8.355\\n', 'V E   80   9.303   6.853\\n', 'V L   77   7.941   5.849\\n', 'V L   47  10.207   9.190\\n', 'V R   46  11.643   9.430\\n', 'V V   45   5.458   3.708\\n', 'V V   44   6.186   5.779\\n', 'V K   42  10.254   8.646\\n', 'V T   40   9.160   7.551\\n', 'V K   37  11.632   9.480\\n', 'V E    3  11.391   9.626\\n', 'V N    2   6.858   5.319\\n', 'V V    1   7.229   7.150\\n', 'S H  369   8.339   7.490\\n', 'S Q  368   9.808   8.480\\n', 'S T  313   9.003   8.463\\n', 'S V  312  10.857   9.632\\n', 'S L  116   9.479   9.312\\n', 'S F   90  10.861   9.661\\n', 'S W   89  10.199   9.336\\n', 'S I   87   8.980   7.920\\n', 'S E   84  10.342   9.272\\n', 'S T   83   8.614   7.918\\n', 'S N   82   9.633   9.034\\n', 'S E   81   4.396   3.187\\n', 'S V   79   9.865   8.746\\n', 'S L   78   4.553   3.585\\n', 'S Q   77   9.377   8.894\\n', 'S C   75   9.986   9.986\\n', 'S E   49   9.774   9.112\\n', 'S L   48   7.008   6.740\\n', 'S R   47  10.573   8.105\\n', 'S V   46   3.743   3.783\\n', 'S V   45   8.548   8.237\\n', 'S V    2   7.594   7.471\\n', 'S V    1   5.070   3.951\\n', 'S K  417  11.142   9.800\\n', 'S D  102  10.606   9.516\\n', 'S H   95   8.183   7.473\\n', 'S F   91   8.345   7.025\\n', 'S E   82   8.683   8.305\\n', 'S Q   78   9.768   8.912\\n', 'S C   75   9.665   9.665\\n', 'S L   51  10.223   9.131\\n', 'S E   50   3.029   2.017\\n', 'S L   49   8.214   7.648\\n', 'S R   48   4.636   3.282\\n', 'S V   47   8.701   8.159\\n', 'S V   46   9.524   8.541\\n', 'S L    7   9.104   8.809\\n', 'S C    6   7.364   7.364\\n', 'S V    3   4.841   4.227\\n', 'S V    2   9.644   9.306\\n', 'S S    1   7.196   7.196\\n', 'Y N   84   9.576   8.207\\n', 'Y E   83   3.641   3.246\\n', 'Y D   82   9.194   7.734\\n', 'Y L   80   8.318   6.667\\n', 'Y Q   79   5.632   3.053\\n', 'Y C   76   8.528   6.899\\n', 'Y N   75  10.545   9.053\\n', 'Y E   51   9.156   7.239\\n', 'Y L   50   9.393   7.442\\n', 'Y R   49  11.618   8.312\\n', 'Y V   48   9.244   7.119\\n', 'Y V    4   9.769   8.563\\n', 'Y V    3  10.782   8.649\\n', 'Y S    2   6.192   4.919\\n', 'Y S    1   7.086   5.936\\n', 'F Y  106  12.565   9.958\\n', 'F D  104  10.158   7.884\\n', 'F T  101   9.099   7.479\\n', 'F H   97   6.385   4.932\\n', 'F F   93  11.935   9.761\\n', 'F E   84  10.415   9.241\\n', 'F Q   80   8.749   6.776\\n', 'F C   77   8.984   7.939\\n', 'F D   73  11.030   9.459\\n', 'F R   61  12.354   9.658\\n', 'F L   53  10.126   8.288\\n', 'F E   52   4.043   3.172\\n', 'F L   51  10.533   9.666\\n', 'F R   50   7.282   5.807\\n', 'F C    8  10.254   9.081\\n', 'F V    5   9.306   7.990\\n', 'F S    2   4.911   4.365\\n', 'F Y    1   7.688   5.827\\n', 'S Q   81   5.735   4.478\\n', 'S D   80   9.639   8.792\\n', 'S C   78   3.812   3.812\\n', 'S N   77   3.560   2.457\\n', 'S L   75   9.823   9.108\\n', 'S D   74   4.858   4.144\\n', 'S R   73   7.935   6.890\\n', 'S Y   66  10.257   9.196\\n', 'S R   62   7.615   6.011\\n', 'S K   59   8.943   7.520\\n', 'S L   54   8.180   7.623\\n', 'S E   53  11.149   9.890\\n', 'S L   52   9.629   9.060\\n', 'S Y    2  10.733   9.222\\n', 'S F    1   9.750   8.423\\n', 'T E   86   9.218   7.611\\n', 'T D   85   8.636   7.136\\n', 'T Q   82   4.075   2.959\\n', 'T D   81   9.146   7.393\\n', 'T C   79   7.157   6.150\\n', 'T N   78   6.516   5.428\\n', 'T D   75  10.889   9.611\\n', 'T K   60  11.738   9.825\\n', 'T Y    3   7.714   5.734\\n', 'T F    2   9.535   8.242\\n', 'T S    1   6.283   5.723\\n']\n"
     ]
    }
   ],
   "source": [
    "with open(fname, \"r\") as f:\n",
    "    print(f.readlines())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a4a0add",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}