{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)\n",
    "from glob import glob\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_bin_eval(dfx,col,eval_method='rmse'):\n",
    "    g=dfx.groupby(\n",
    "            by=[\n",
    "                'Dataset',\n",
    "                'Eval_Method',\n",
    "                'Sampling',\n",
    "               ])\n",
    "    bin_err=0\n",
    "    metric=0\n",
    "    eq=0\n",
    "    first=True\n",
    "    for gname,group in g:\n",
    "        if first:\n",
    "            first=False\n",
    "            prev=group[col]['mean'].mean()\n",
    "        else:\n",
    "            first=True\n",
    "            if prev<group[col]['mean'].mean() and eval_method=='r2':\n",
    "                bin_err+=1\n",
    "            elif prev>group[col]['mean'].mean() and eval_method=='rmse':\n",
    "                bin_err+=1\n",
    "            elif prev==group[col]['mean'].mean():\n",
    "                eq+=1\n",
    "            else:\n",
    "                metric+=1\n",
    "    print(f'PDF:{bin_err},Random:{metric}, Equal:{eq}')\n",
    "    return bin_err,  metric, eq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_eval(dfx):\n",
    "    g=dfx[['Selector', 'Ratio','Dataset', 'Eval_Method', 'PDF_Test', 'Sampling']].groupby(\n",
    "            by=[\n",
    "                'Dataset',\n",
    "                'Sampling',\n",
    "                'Eval_Method',\n",
    "               ])\n",
    "    bin_err=0\n",
    "    metric=0\n",
    "    eq=0\n",
    "    first=True\n",
    "    check=[]\n",
    "    c=0\n",
    "    out={1:0,2:0,3:0,4:0}\n",
    "    for gname,group in g:\n",
    "        print(gname, group.Selector.mean())\n",
    "        check.append(group.Selector.mean())\n",
    "        if len(check):\n",
    "            if len(check)%4==0:\n",
    "                out[np.argmin(check)+1]+=1\n",
    "                check=[]\n",
    "        \n",
    "    print(f'PDF-Bin_Err:{out[1]},PDF-Metric:{out[2]},Random-Bin_Err:{out[3]},Random-Metric:{out[4]}')\n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df11_0=pd.read_pickle('R2_0.pickle')\n",
    "df11_10=pd.read_pickle('R2_10.pickle')\n",
    "df11_100=pd.read_pickle('R2_100.pickle')\n",
    "df11_1k=pd.read_pickle('R2_1k.pickle')\n",
    "df10_0=pd.read_pickle('RMSE_0.pickle')\n",
    "df10_10=pd.read_pickle('RMSE_10.pickle')\n",
    "df10_100=pd.read_pickle('RMSE_100.pickle')\n",
    "df10_1k=pd.read_pickle('RMSE_1k.pickle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((252, 21),\n",
       " (252, 21),\n",
       " (252, 21),\n",
       " (252, 21),\n",
       " (252, 21),\n",
       " (252, 21),\n",
       " (252, 21),\n",
       " (252, 21))"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df11_0.shape, df11_10.shape, df11_100.shape, df11_1k.shape, df10_100.shape, df10_10.shape, df10_1k.shape, df10_0.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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></th>\n",
       "      <th></th>\n",
       "      <th>Seed</th>\n",
       "      <th>Stack</th>\n",
       "      <th>Bins</th>\n",
       "      <th>Ratio</th>\n",
       "      <th>SML_Vanilla</th>\n",
       "      <th>R2_1000</th>\n",
       "      <th>Diff</th>\n",
       "      <th>Diff_Perc</th>\n",
       "      <th>Test_Eval</th>\n",
       "      <th>Train_Model</th>\n",
       "      <th>Train_Group_Mean</th>\n",
       "      <th>Train_Group_Sum</th>\n",
       "      <th>KL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eval_Method</th>\n",
       "      <th>Flag</th>\n",
       "      <th>Sampling</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Metric</th>\n",
       "      <th>True</th>\n",
       "      <th>Random</th>\n",
       "      <td>185.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.779481</td>\n",
       "      <td>0.843424</td>\n",
       "      <td>0.063943</td>\n",
       "      <td>14.046018</td>\n",
       "      <td>0.845552</td>\n",
       "      <td>4.631989</td>\n",
       "      <td>5.609311</td>\n",
       "      <td>67.311730</td>\n",
       "      <td>8.434242e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PDF Energy</th>\n",
       "      <th>True</th>\n",
       "      <th>PDF</th>\n",
       "      <td>185.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.779481</td>\n",
       "      <td>0.846794</td>\n",
       "      <td>0.067312</td>\n",
       "      <td>14.648705</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.020123</td>\n",
       "      <td>4.977813</td>\n",
       "      <td>59.733752</td>\n",
       "      <td>-1.555432e+16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Seed  Stack    Bins  Ratio  SML_Vanilla   R2_1000  \\\n",
       "Eval_Method Flag Sampling                                                       \n",
       "Metric      True Random    185.0    3.0  1000.0    0.3     0.779481  0.843424   \n",
       "PDF Energy  True PDF       185.0    3.0  1000.0    0.3     0.779481  0.846794   \n",
       "\n",
       "                               Diff  Diff_Perc  Test_Eval  Train_Model  \\\n",
       "Eval_Method Flag Sampling                                                \n",
       "Metric      True Random    0.063943  14.046018   0.845552     4.631989   \n",
       "PDF Energy  True PDF       0.067312  14.648705   0.000000     5.020123   \n",
       "\n",
       "                           Train_Group_Mean  Train_Group_Sum            KL  \n",
       "Eval_Method Flag Sampling                                                   \n",
       "Metric      True Random            5.609311        67.311730  8.434242e-01  \n",
       "PDF Energy  True PDF               4.977813        59.733752 -1.555432e+16  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df11_1k.groupby(['Eval_Method', 'Flag', 'Sampling']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "r2_0=df11_0[['R2_0', 'Ratio','Bins','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'R2_0': ['mean', 'std']})\n",
    "r2_10=df11_10[['R2_10', 'Ratio','Bins','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'R2_10': ['mean', 'std']})\n",
    "r2_100=df11_100[['R2_100', 'Ratio','Bins','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'R2_100': ['mean', 'std']})\n",
    "r2_1k=df11_1k[['R2_1000', 'Ratio','Bins','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'R2_1000': ['mean', 'std']})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14,)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10_100.Dataset.unique().shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['361072', '361073', '361078', '361080', '361081', '361082',\n",
       "       '361083', '361085', '361086', '361087', '361088', '361089',\n",
       "       '361090', '42570'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10_0.Dataset.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Table Stratum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: cannot create directory ‘paper’: File exists\r\n"
     ]
    }
   ],
   "source": [
    "!mkdir paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/1491377064.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  bins=df10_0.groupby(['Dataset','Seed'])['Dataset','Bins'].agg({'Bins':'mean'})\n"
     ]
    }
   ],
   "source": [
    "bins=df10_0.groupby(['Dataset','Seed'])['Dataset','Bins'].agg({'Bins':'mean'})\n",
    "df_bins=pd.DataFrame(bins.Bins.astype(int))\n",
    "df_bins.columns=['Stratum']\n",
    "df_bins.to_pickle('paper/tbl_stratum_optimal_stratified.pkl')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/3985421369.py:2: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
      "  wf.write(df_bins.to_latex())\n"
     ]
    }
   ],
   "source": [
    "with open(\"paper/tbl_stratum_optimal_stratified.pkl.tex\", 'w') as wf:\n",
    "    wf.write(df_bins.to_latex())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_agg_std(df, sel='RMSE_100',):\n",
    "    df=df[[sel, 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "            'Ratio',\n",
    "           ]).agg({'sel': ['mean', 'std']})\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_agg(df, sel='RMSE_100',):\n",
    "    df_mean=df[[sel, 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "            'Ratio',\n",
    "           ]).agg('mean')#'{sel: ['mean', 'std']})\n",
    "    \n",
    "    df_std=df[[sel, 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "            'Ratio',\n",
    "           ]).agg('std')\n",
    "    \n",
    "    return df_mean, df_std\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x1000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "from matplotlib import ticker\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import matplotlib.pylab as plt\n",
    "plt.rcParams[\"figure.figsize\"] = (10,7)\n",
    "fig = matplotlib.pyplot.gcf()\n",
    "fig.set_size_inches(10, 10, forward=True)\n",
    "fig.set_dpi(100)\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (10, 10),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':'large',\n",
    "         'ytick.labelsize':'large'}\n",
    "plt.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_kl_pdf(df, col, ratio=None):\n",
    "    df[df.KL<0]=np.nan\n",
    "    dr=None\n",
    "    if ratio is not None:\n",
    "        df=df[(df.Sampling=='PDF') & (df.Ratio==ratio)]\n",
    "        \n",
    "    else:\n",
    "        df=df[(df.Sampling=='PDF')]\n",
    "        \n",
    "    df.to_pickle(f'paper/df_KL_PDF_{col}_{ratio}.pkl')\n",
    "    df.to_pickle(f'paper/df_KL_PDF_{col}_{ratio}.csv')\n",
    "    \n",
    "    _pdf=round(df[col].mean(),3)\n",
    "    _pdf_std=round(df[col].std(),3)\n",
    "    _kl=round(df.KL.mean(),3)\n",
    "    _kl_std=round(df.KL.std(),3)\n",
    "    \n",
    "    dr_mean, dr_std =get_agg(df,col)\n",
    "    \n",
    "    dr_mean=dr_mean.reset_index()\n",
    "    dr_std=dr_std.reset_index()\n",
    "\n",
    "    dr_mean=dr_mean.groupby(['Dataset']).mean()\n",
    "    dr_std=dr_std.groupby(['Dataset']).std()\n",
    "    \n",
    "    bins=int(dr_mean.Bins.mean())\n",
    "    \n",
    "    drr=dr_mean[[col,'KL']]\n",
    "    drr_s=dr_std[[col,'KL']]\n",
    "    \n",
    "    drr.columns=['PDF','KL']\n",
    "    drr_s.columns=['PDF','KL']\n",
    "\n",
    "    drr.to_pickle('paper/'+f'{col}_{(ratio if ratio else 0)*100}.jpg'+'.pkl')\n",
    "    drr.to_csv('paper/'+f'{col}_{(ratio if ratio else 0)*100}.jpg'+'.csv')\n",
    "    ax=drr.plot(rot=75, style=['b*-','r-','g^-'], linewidth=2.0, )\n",
    "    plt.fill_between(drr.index, drr['KL']-drr_std['KL'], drr['KL']+drr_std['KL'], alpha=0.2, label=None, color='red')\n",
    "    plt.fill_between(drr.index, drr['PDF']-drr_s['PDF'], drr['PDF']+drr_s['PDF'], alpha=0.2, label=None, color='blue')\n",
    "\n",
    "\n",
    "    PDF='{PDF}'\n",
    "    KL='{KL}'\n",
    "    OB='{'\n",
    "    CB='}'\n",
    "    if bins>9:\n",
    "        _title=f'$\\\\beta={bins},\\ \\\\overline{PDF}={_pdf}\\pm{_pdf_std},\\  \\\\overline{KL}={_kl}\\pm{_kl_std}$'\n",
    "        \n",
    "    else:\n",
    "        BETA='{\\\\beta}'\n",
    "        _title=f'$\\\\overline{BETA}={bins}\\  \\ \\\\overline{PDF}={_pdf}\\pm{_pdf_std},\\  \\\\overline{KL}={_kl}\\pm{_kl_std}$'\n",
    "    if ratio:\n",
    "        _title=f'$\\\\rho={ratio}$, '+_title\n",
    "    ax.set_title(_title, fontsize=20)\n",
    "    plt.xlabel('Dataset', fontsize=20)\n",
    "    plt.ylabel('R2', fontsize=20)\n",
    "    ax.xaxis.set_minor_locator(ticker.LinearLocator(14))\n",
    "    ax.xaxis.set_major_locator(ticker.LinearLocator(14))\n",
    "    ax.set_xticklabels(drr.index)\n",
    "    plt.legend(fontsize=20)\n",
    "    plt.grid(visible=True, which='major', color='0.65', linestyle='-')\n",
    "    if ratio is None:\n",
    "        ratio=0\n",
    "    plt.savefig(f'{col}_{ratio*100}_v2.jpg')\n",
    "    plt.show()\n",
    "    return plt,df, drr, drr_std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_729041/609560072.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax.set_xticklabels(drr.index)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for exp in [\n",
    "            (df11_10,'R2_10'),\n",
    "            (df11_100,'R2_100'),\n",
    "            (df11_1k,'R2_1000'),\n",
    "            (df11_0,'R2_0')\n",
    "           ]:\n",
    "    for ratio in [.2,.3,.4]:\n",
    "        a,b, drr, drr_std = get_kl_pdf(exp[0], exp[1], ratio=ratio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "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>PDF</th>\n",
       "      <th>KL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dataset</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>361072</th>\n",
       "      <td>0.000832</td>\n",
       "      <td>0.000097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361073</th>\n",
       "      <td>0.077607</td>\n",
       "      <td>0.001583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361078</th>\n",
       "      <td>0.004505</td>\n",
       "      <td>0.003338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361080</th>\n",
       "      <td>0.000281</td>\n",
       "      <td>0.001705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361081</th>\n",
       "      <td>0.004052</td>\n",
       "      <td>0.002421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361082</th>\n",
       "      <td>0.004192</td>\n",
       "      <td>0.067439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361083</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361085</th>\n",
       "      <td>0.016288</td>\n",
       "      <td>0.042169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361086</th>\n",
       "      <td>0.000269</td>\n",
       "      <td>0.000119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361087</th>\n",
       "      <td>0.002772</td>\n",
       "      <td>0.000583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361088</th>\n",
       "      <td>0.000790</td>\n",
       "      <td>0.010203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361089</th>\n",
       "      <td>0.000835</td>\n",
       "      <td>0.002780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361090</th>\n",
       "      <td>0.006512</td>\n",
       "      <td>0.002590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42570</th>\n",
       "      <td>0.009131</td>\n",
       "      <td>0.020882</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              PDF        KL\n",
       "Dataset                    \n",
       "361072   0.000832  0.000097\n",
       "361073   0.077607  0.001583\n",
       "361078   0.004505  0.003338\n",
       "361080   0.000281  0.001705\n",
       "361081   0.004052  0.002421\n",
       "361082   0.004192  0.067439\n",
       "361083   0.000000  0.000862\n",
       "361085   0.016288  0.042169\n",
       "361086   0.000269  0.000119\n",
       "361087   0.002772  0.000583\n",
       "361088   0.000790  0.010203\n",
       "361089   0.000835  0.002780\n",
       "361090   0.006512  0.002590\n",
       "42570    0.009131  0.020882"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drr_std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 853,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmse_0=df10_0[['RMSE_0', 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "            \n",
    "           ]).agg({'RMSE_0': ['mean', 'std']})\n",
    "rmse_10=df10_10[['RMSE_10', 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'RMSE_10': ['mean', 'std']})\n",
    "rmse_100=df10_100[['RMSE_100', 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'RMSE_100': ['mean', 'std']})\n",
    "\n",
    "rmse_1k=df10_1k[['RMSE_1000', 'Bins','Ratio','Dataset', 'Eval_Method','Sampling','KL']].groupby(\n",
    "        by=[\n",
    "            'Dataset',\n",
    "            'Sampling',\n",
    "            'Eval_Method',\n",
    "           ]).agg({'RMSE_1000': ['mean', 'std']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 854,
   "metadata": {},
   "outputs": [],
   "source": [
    "dx=rmse_0.join(r2_0).join(r2_10).join(rmse_10).join(r2_100).join(rmse_100).join(rmse_1k).join(r2_1k)\n",
    "dx_bk=dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 855,
   "metadata": {},
   "outputs": [],
   "source": [
    "out={'RMSE':{'mean':{},\n",
    "             'std':{}},\n",
    "     'R2':{'mean':{},\n",
    "             'std':{}}\n",
    "    }\n",
    "for metric in out.keys():\n",
    "    for t in out[metric].keys():\n",
    "        for i in dx.index:\n",
    "            if 'Random' in i:\n",
    "                for j in dx.loc[i].index:\n",
    "                    if metric in j[0] and t in j[1]:\n",
    "                        out[metric][t][i[0]]=out[metric][t].get(i[0],0)+dx.loc[i,j]/4      \n",
    "                        \n",
    "dx.loc[('361072', 'Random',     'Metric')][(   'RMSE_0', 'mean')]=0\n",
    "\n",
    "for metric in out:\n",
    "    for t in out[metric]:\n",
    "        for i in dx.index:\n",
    "            for j in dx.loc[i].index:\n",
    "                if metric in j[0] and t==j[1] and i[1]=='Random':\n",
    "                    #print(i,j,out[metric][t][i[0]])\n",
    "                    dx.loc[i][j]=out[metric][t][i[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 856,
   "metadata": {},
   "outputs": [],
   "source": [
    "dx.to_pickle('paper/dx_rmse_r2_pdf_vs_sampling.pkl')\n",
    "dx.to_csv('paper/dx_rmse_r2_pdf_vs_sampling.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 857,
   "metadata": {},
   "outputs": [],
   "source": [
    "def join_mean_std(dx, del_org=True):\n",
    "    dx['_R2_10']=dx.apply(lambda x: ('$'+str(round(x['R2_10']['mean'],4))+\n",
    "                                  ' \\pm '+\n",
    "                                  str(round(x['R2_10']['std'],3))+'$'),\n",
    "                       axis=1)\n",
    "    dx['_RMSE_10']=dx.apply(lambda x: '$'+(str(round(x['RMSE_10']['mean'],4))+\n",
    "                                   ' \\pm '+\n",
    "                                   str(round(x['RMSE_10']['std'],3))+'$'), \n",
    "                         axis=1)\n",
    "    dx['_R2_100']=dx.apply(lambda x: ('$'+str(round(x['R2_100']['mean'],4))+\n",
    "                                  ' \\pm '+\n",
    "                                  str(round(x['R2_100']['std'],3))+'$'),\n",
    "                       axis=1)\n",
    "    dx['_RMSE_100']=dx.apply(lambda x: '$'+(str(round(x['RMSE_100']['mean'],4))+\n",
    "                                   ' \\pm '+\n",
    "                                   str(round(x['RMSE_100']['std'],3))+'$'), \n",
    "                         axis=1)\n",
    "    dx['_R2_1000']=dx.apply(lambda x: ('$'+str(round(x['R2_1000']['mean'],4))+\n",
    "                                  ' \\pm '+\n",
    "                                  str(round(x['R2_1000']['std'],3))+'$'),\n",
    "                       axis=1)\n",
    "\n",
    "    dx['_RMSE_1000']=dx.apply(lambda x: '$'+(str(round(x['RMSE_1000']['mean'],4))+\n",
    "                                   ' \\pm '+\n",
    "                                   str(round(x['RMSE_1000']['std'],3))+'$'), \n",
    "                         axis=1)\n",
    "    dx['_R2_0']=dx.apply(lambda x: '$'+(str(round(x['R2_0']['mean'],4))+\n",
    "                                   ' \\pm '+\n",
    "                                   str(round(x['R2_0']['std'],3))+'$'), \n",
    "                         axis=1)\n",
    "    dx['_RMSE_0']=dx.apply(lambda x: '$'+(str(round(x['RMSE_0']['mean'],4))+\n",
    "                                   ' \\pm '+\n",
    "                                   str(round(x['RMSE_0']['std'],3))+'$'), \n",
    "                         axis=1)\n",
    "    if del_org:\n",
    "        dx=del_non_paper(dx)\n",
    "    return dx\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 858,
   "metadata": {},
   "outputs": [],
   "source": [
    "dx=join_mean_std(dx,False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 859,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_10</th>\n",
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       "      <th colspan=\"2\" halign=\"left\">RMSE_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_1000</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_1000</th>\n",
       "      <th>_R2_10</th>\n",
       "      <th>_RMSE_10</th>\n",
       "      <th>_R2_100</th>\n",
       "      <th>_RMSE_100</th>\n",
       "      <th>_R2_1000</th>\n",
       "      <th>_RMSE_1000</th>\n",
       "      <th>_R2_0</th>\n",
       "      <th>_RMSE_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dataset</th>\n",
       "      <th>Sampling</th>\n",
       "      <th>Eval_Method</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361072</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>2.285418</td>\n",
       "      <td>0.100470</td>\n",
       "      <td>0.984469</td>\n",
       "      <td>0.002246</td>\n",
       "      <td>0.985745</td>\n",
       "      <td>0.001963</td>\n",
       "      <td>2.190370</td>\n",
       "      <td>0.074086</td>\n",
       "      <td>0.983909</td>\n",
       "      <td>0.003078</td>\n",
       "      <td>2.320368</td>\n",
       "      <td>0.136334</td>\n",
       "      <td>2.255595</td>\n",
       "      <td>0.133364</td>\n",
       "      <td>0.984800</td>\n",
       "      <td>0.002932</td>\n",
       "      <td>$0.9857 \\pm 0.002$</td>\n",
       "      <td>$2.1904 \\pm 0.074$</td>\n",
       "      <td>$0.9839 \\pm 0.003$</td>\n",
       "      <td>$2.3204 \\pm 0.136$</td>\n",
       "      <td>$0.9848 \\pm 0.003$</td>\n",
       "      <td>$2.2556 \\pm 0.133$</td>\n",
       "      <td>$0.9845 \\pm 0.002$</td>\n",
       "      <td>$2.2854 \\pm 0.1$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>2.255033</td>\n",
       "      <td>0.054383</td>\n",
       "      <td>0.984932</td>\n",
       "      <td>0.001562</td>\n",
       "      <td>0.984932</td>\n",
       "      <td>0.001562</td>\n",
       "      <td>2.255033</td>\n",
       "      <td>0.054383</td>\n",
       "      <td>0.984932</td>\n",
       "      <td>0.001562</td>\n",
       "      <td>2.255033</td>\n",
       "      <td>0.054383</td>\n",
       "      <td>2.255033</td>\n",
       "      <td>0.054383</td>\n",
       "      <td>0.984932</td>\n",
       "      <td>0.001562</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361073</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>7.787946</td>\n",
       "      <td>7.280729</td>\n",
       "      <td>0.938506</td>\n",
       "      <td>0.102860</td>\n",
       "      <td>0.988413</td>\n",
       "      <td>0.001283</td>\n",
       "      <td>4.501045</td>\n",
       "      <td>0.248430</td>\n",
       "      <td>0.971971</td>\n",
       "      <td>0.002034</td>\n",
       "      <td>7.006527</td>\n",
       "      <td>0.242512</td>\n",
       "      <td>6.991734</td>\n",
       "      <td>0.261632</td>\n",
       "      <td>0.972084</td>\n",
       "      <td>0.002177</td>\n",
       "      <td>$0.9884 \\pm 0.001$</td>\n",
       "      <td>$4.501 \\pm 0.248$</td>\n",
       "      <td>$0.972 \\pm 0.002$</td>\n",
       "      <td>$7.0065 \\pm 0.243$</td>\n",
       "      <td>$0.9721 \\pm 0.002$</td>\n",
       "      <td>$6.9917 \\pm 0.262$</td>\n",
       "      <td>$0.9385 \\pm 0.103$</td>\n",
       "      <td>$7.7879 \\pm 7.281$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>4.500983</td>\n",
       "      <td>0.427056</td>\n",
       "      <td>0.988351</td>\n",
       "      <td>0.002250</td>\n",
       "      <td>0.988351</td>\n",
       "      <td>0.002250</td>\n",
       "      <td>4.500983</td>\n",
       "      <td>0.427056</td>\n",
       "      <td>0.988351</td>\n",
       "      <td>0.002250</td>\n",
       "      <td>4.500983</td>\n",
       "      <td>0.427056</td>\n",
       "      <td>4.500983</td>\n",
       "      <td>0.427056</td>\n",
       "      <td>0.988351</td>\n",
       "      <td>0.002250</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361078</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.220044</td>\n",
       "      <td>0.006596</td>\n",
       "      <td>0.850595</td>\n",
       "      <td>0.007950</td>\n",
       "      <td>0.851884</td>\n",
       "      <td>0.005652</td>\n",
       "      <td>0.219117</td>\n",
       "      <td>0.004809</td>\n",
       "      <td>0.853217</td>\n",
       "      <td>0.005896</td>\n",
       "      <td>0.218125</td>\n",
       "      <td>0.004974</td>\n",
       "      <td>0.218092</td>\n",
       "      <td>0.005036</td>\n",
       "      <td>0.853256</td>\n",
       "      <td>0.006053</td>\n",
       "      <td>$0.8519 \\pm 0.006$</td>\n",
       "      <td>$0.2191 \\pm 0.005$</td>\n",
       "      <td>$0.8532 \\pm 0.006$</td>\n",
       "      <td>$0.2181 \\pm 0.005$</td>\n",
       "      <td>$0.8533 \\pm 0.006$</td>\n",
       "      <td>$0.2181 \\pm 0.005$</td>\n",
       "      <td>$0.8506 \\pm 0.008$</td>\n",
       "      <td>$0.22 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.219382</td>\n",
       "      <td>0.006101</td>\n",
       "      <td>0.851484</td>\n",
       "      <td>0.007593</td>\n",
       "      <td>0.851484</td>\n",
       "      <td>0.007593</td>\n",
       "      <td>0.219382</td>\n",
       "      <td>0.006101</td>\n",
       "      <td>0.851484</td>\n",
       "      <td>0.007593</td>\n",
       "      <td>0.219382</td>\n",
       "      <td>0.006101</td>\n",
       "      <td>0.219382</td>\n",
       "      <td>0.006101</td>\n",
       "      <td>0.851484</td>\n",
       "      <td>0.007593</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361080</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.236615</td>\n",
       "      <td>0.002581</td>\n",
       "      <td>0.945512</td>\n",
       "      <td>0.001174</td>\n",
       "      <td>0.946005</td>\n",
       "      <td>0.000959</td>\n",
       "      <td>0.235549</td>\n",
       "      <td>0.002595</td>\n",
       "      <td>0.945651</td>\n",
       "      <td>0.001858</td>\n",
       "      <td>0.236279</td>\n",
       "      <td>0.002878</td>\n",
       "      <td>0.237668</td>\n",
       "      <td>0.003062</td>\n",
       "      <td>0.945017</td>\n",
       "      <td>0.001660</td>\n",
       "      <td>$0.946 \\pm 0.001$</td>\n",
       "      <td>$0.2355 \\pm 0.003$</td>\n",
       "      <td>$0.9457 \\pm 0.002$</td>\n",
       "      <td>$0.2363 \\pm 0.003$</td>\n",
       "      <td>$0.945 \\pm 0.002$</td>\n",
       "      <td>$0.2377 \\pm 0.003$</td>\n",
       "      <td>$0.9455 \\pm 0.001$</td>\n",
       "      <td>$0.2366 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.245571</td>\n",
       "      <td>0.007037</td>\n",
       "      <td>0.941395</td>\n",
       "      <td>0.003407</td>\n",
       "      <td>0.941395</td>\n",
       "      <td>0.003407</td>\n",
       "      <td>0.245571</td>\n",
       "      <td>0.007037</td>\n",
       "      <td>0.941395</td>\n",
       "      <td>0.003407</td>\n",
       "      <td>0.245571</td>\n",
       "      <td>0.007037</td>\n",
       "      <td>0.245571</td>\n",
       "      <td>0.007037</td>\n",
       "      <td>0.941395</td>\n",
       "      <td>0.003407</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361081</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.068299</td>\n",
       "      <td>0.032262</td>\n",
       "      <td>0.991214</td>\n",
       "      <td>0.007269</td>\n",
       "      <td>0.986533</td>\n",
       "      <td>0.010035</td>\n",
       "      <td>0.084016</td>\n",
       "      <td>0.041159</td>\n",
       "      <td>0.985932</td>\n",
       "      <td>0.011924</td>\n",
       "      <td>0.085687</td>\n",
       "      <td>0.042495</td>\n",
       "      <td>0.082649</td>\n",
       "      <td>0.037941</td>\n",
       "      <td>0.987250</td>\n",
       "      <td>0.009615</td>\n",
       "      <td>$0.9865 \\pm 0.01$</td>\n",
       "      <td>$0.084 \\pm 0.041$</td>\n",
       "      <td>$0.9859 \\pm 0.012$</td>\n",
       "      <td>$0.0857 \\pm 0.042$</td>\n",
       "      <td>$0.9872 \\pm 0.01$</td>\n",
       "      <td>$0.0826 \\pm 0.038$</td>\n",
       "      <td>$0.9912 \\pm 0.007$</td>\n",
       "      <td>$0.0683 \\pm 0.032$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.080185</td>\n",
       "      <td>0.042063</td>\n",
       "      <td>0.987352</td>\n",
       "      <td>0.011227</td>\n",
       "      <td>0.987352</td>\n",
       "      <td>0.011227</td>\n",
       "      <td>0.080185</td>\n",
       "      <td>0.042063</td>\n",
       "      <td>0.987352</td>\n",
       "      <td>0.011227</td>\n",
       "      <td>0.080185</td>\n",
       "      <td>0.042063</td>\n",
       "      <td>0.080185</td>\n",
       "      <td>0.042063</td>\n",
       "      <td>0.987352</td>\n",
       "      <td>0.011227</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361082</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>104.037535</td>\n",
       "      <td>3.800579</td>\n",
       "      <td>0.669927</td>\n",
       "      <td>0.021896</td>\n",
       "      <td>0.662916</td>\n",
       "      <td>0.020850</td>\n",
       "      <td>105.133282</td>\n",
       "      <td>3.342916</td>\n",
       "      <td>0.675929</td>\n",
       "      <td>0.022423</td>\n",
       "      <td>103.074698</td>\n",
       "      <td>3.567029</td>\n",
       "      <td>104.601624</td>\n",
       "      <td>3.162918</td>\n",
       "      <td>0.666179</td>\n",
       "      <td>0.022590</td>\n",
       "      <td>$0.6629 \\pm 0.021$</td>\n",
       "      <td>$105.1333 \\pm 3.343$</td>\n",
       "      <td>$0.6759 \\pm 0.022$</td>\n",
       "      <td>$103.0747 \\pm 3.567$</td>\n",
       "      <td>$0.6662 \\pm 0.023$</td>\n",
       "      <td>$104.6016 \\pm 3.163$</td>\n",
       "      <td>$0.6699 \\pm 0.022$</td>\n",
       "      <td>$104.0375 \\pm 3.801$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>107.276317</td>\n",
       "      <td>3.316033</td>\n",
       "      <td>0.648812</td>\n",
       "      <td>0.024293</td>\n",
       "      <td>0.648812</td>\n",
       "      <td>0.024293</td>\n",
       "      <td>107.276317</td>\n",
       "      <td>3.316033</td>\n",
       "      <td>0.648812</td>\n",
       "      <td>0.024293</td>\n",
       "      <td>107.276317</td>\n",
       "      <td>3.316033</td>\n",
       "      <td>107.276317</td>\n",
       "      <td>3.316033</td>\n",
       "      <td>0.648812</td>\n",
       "      <td>0.024293</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361083</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.648337</td>\n",
       "      <td>0.090280</td>\n",
       "      <td>0.351565</td>\n",
       "      <td>0.039796</td>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6483 \\pm 0.09$</td>\n",
       "      <td>$0.3516 \\pm 0.04$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.338191</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.678404</td>\n",
       "      <td>0.001914</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361085</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.031774</td>\n",
       "      <td>0.018239</td>\n",
       "      <td>0.641823</td>\n",
       "      <td>0.306866</td>\n",
       "      <td>0.477815</td>\n",
       "      <td>0.229302</td>\n",
       "      <td>0.039400</td>\n",
       "      <td>0.012013</td>\n",
       "      <td>0.883703</td>\n",
       "      <td>0.034511</td>\n",
       "      <td>0.019340</td>\n",
       "      <td>0.004794</td>\n",
       "      <td>0.019340</td>\n",
       "      <td>0.004794</td>\n",
       "      <td>0.883703</td>\n",
       "      <td>0.034511</td>\n",
       "      <td>$0.4778 \\pm 0.229$</td>\n",
       "      <td>$0.0394 \\pm 0.012$</td>\n",
       "      <td>$0.8837 \\pm 0.035$</td>\n",
       "      <td>$0.0193 \\pm 0.005$</td>\n",
       "      <td>$0.8837 \\pm 0.035$</td>\n",
       "      <td>$0.0193 \\pm 0.005$</td>\n",
       "      <td>$0.6418 \\pm 0.307$</td>\n",
       "      <td>$0.0318 \\pm 0.018$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.020685</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>0.865283</td>\n",
       "      <td>0.047684</td>\n",
       "      <td>0.865283</td>\n",
       "      <td>0.047684</td>\n",
       "      <td>0.020685</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>0.865283</td>\n",
       "      <td>0.047684</td>\n",
       "      <td>0.020685</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>0.020685</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>0.865283</td>\n",
       "      <td>0.047684</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361086</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.084504</td>\n",
       "      <td>0.002723</td>\n",
       "      <td>0.977709</td>\n",
       "      <td>0.001351</td>\n",
       "      <td>0.979168</td>\n",
       "      <td>0.000376</td>\n",
       "      <td>0.081717</td>\n",
       "      <td>0.000592</td>\n",
       "      <td>0.978913</td>\n",
       "      <td>0.001084</td>\n",
       "      <td>0.082192</td>\n",
       "      <td>0.001929</td>\n",
       "      <td>0.082264</td>\n",
       "      <td>0.001558</td>\n",
       "      <td>0.978884</td>\n",
       "      <td>0.000786</td>\n",
       "      <td>$0.9792 \\pm 0.0$</td>\n",
       "      <td>$0.0817 \\pm 0.001$</td>\n",
       "      <td>$0.9789 \\pm 0.001$</td>\n",
       "      <td>$0.0822 \\pm 0.002$</td>\n",
       "      <td>$0.9789 \\pm 0.001$</td>\n",
       "      <td>$0.0823 \\pm 0.002$</td>\n",
       "      <td>$0.9777 \\pm 0.001$</td>\n",
       "      <td>$0.0845 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.085796</td>\n",
       "      <td>0.002569</td>\n",
       "      <td>0.977018</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.977018</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.085796</td>\n",
       "      <td>0.002569</td>\n",
       "      <td>0.977018</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>0.085796</td>\n",
       "      <td>0.002569</td>\n",
       "      <td>0.085796</td>\n",
       "      <td>0.002569</td>\n",
       "      <td>0.977018</td>\n",
       "      <td>0.001366</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361087</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.152191</td>\n",
       "      <td>0.005796</td>\n",
       "      <td>0.928885</td>\n",
       "      <td>0.005403</td>\n",
       "      <td>0.933776</td>\n",
       "      <td>0.005480</td>\n",
       "      <td>0.146841</td>\n",
       "      <td>0.005367</td>\n",
       "      <td>0.935413</td>\n",
       "      <td>0.001680</td>\n",
       "      <td>0.145124</td>\n",
       "      <td>0.002119</td>\n",
       "      <td>0.146271</td>\n",
       "      <td>0.003300</td>\n",
       "      <td>0.934376</td>\n",
       "      <td>0.002705</td>\n",
       "      <td>$0.9338 \\pm 0.005$</td>\n",
       "      <td>$0.1468 \\pm 0.005$</td>\n",
       "      <td>$0.9354 \\pm 0.002$</td>\n",
       "      <td>$0.1451 \\pm 0.002$</td>\n",
       "      <td>$0.9344 \\pm 0.003$</td>\n",
       "      <td>$0.1463 \\pm 0.003$</td>\n",
       "      <td>$0.9289 \\pm 0.005$</td>\n",
       "      <td>$0.1522 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.145906</td>\n",
       "      <td>0.002920</td>\n",
       "      <td>0.934689</td>\n",
       "      <td>0.002550</td>\n",
       "      <td>0.934689</td>\n",
       "      <td>0.002550</td>\n",
       "      <td>0.145906</td>\n",
       "      <td>0.002920</td>\n",
       "      <td>0.934689</td>\n",
       "      <td>0.002550</td>\n",
       "      <td>0.145906</td>\n",
       "      <td>0.002920</td>\n",
       "      <td>0.145906</td>\n",
       "      <td>0.002920</td>\n",
       "      <td>0.934689</td>\n",
       "      <td>0.002550</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361088</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>10.045855</td>\n",
       "      <td>0.458113</td>\n",
       "      <td>0.914604</td>\n",
       "      <td>0.008210</td>\n",
       "      <td>0.913125</td>\n",
       "      <td>0.011120</td>\n",
       "      <td>10.125706</td>\n",
       "      <td>0.618858</td>\n",
       "      <td>0.915239</td>\n",
       "      <td>0.007387</td>\n",
       "      <td>10.010129</td>\n",
       "      <td>0.407764</td>\n",
       "      <td>10.010129</td>\n",
       "      <td>0.407764</td>\n",
       "      <td>0.915239</td>\n",
       "      <td>0.007387</td>\n",
       "      <td>$0.9131 \\pm 0.011$</td>\n",
       "      <td>$10.1257 \\pm 0.619$</td>\n",
       "      <td>$0.9152 \\pm 0.007$</td>\n",
       "      <td>$10.0101 \\pm 0.408$</td>\n",
       "      <td>$0.9152 \\pm 0.007$</td>\n",
       "      <td>$10.0101 \\pm 0.408$</td>\n",
       "      <td>$0.9146 \\pm 0.008$</td>\n",
       "      <td>$10.0459 \\pm 0.458$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>10.163004</td>\n",
       "      <td>0.587097</td>\n",
       "      <td>0.912474</td>\n",
       "      <td>0.010639</td>\n",
       "      <td>0.912474</td>\n",
       "      <td>0.010639</td>\n",
       "      <td>10.163004</td>\n",
       "      <td>0.587097</td>\n",
       "      <td>0.912474</td>\n",
       "      <td>0.010639</td>\n",
       "      <td>10.163004</td>\n",
       "      <td>0.587097</td>\n",
       "      <td>10.163004</td>\n",
       "      <td>0.587097</td>\n",
       "      <td>0.912474</td>\n",
       "      <td>0.010639</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361089</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.133728</td>\n",
       "      <td>0.002153</td>\n",
       "      <td>0.857686</td>\n",
       "      <td>0.003428</td>\n",
       "      <td>0.857258</td>\n",
       "      <td>0.005862</td>\n",
       "      <td>0.133920</td>\n",
       "      <td>0.003375</td>\n",
       "      <td>0.858721</td>\n",
       "      <td>0.002397</td>\n",
       "      <td>0.133246</td>\n",
       "      <td>0.001880</td>\n",
       "      <td>0.134945</td>\n",
       "      <td>0.004059</td>\n",
       "      <td>0.854991</td>\n",
       "      <td>0.008456</td>\n",
       "      <td>$0.8573 \\pm 0.006$</td>\n",
       "      <td>$0.1339 \\pm 0.003$</td>\n",
       "      <td>$0.8587 \\pm 0.002$</td>\n",
       "      <td>$0.1332 \\pm 0.002$</td>\n",
       "      <td>$0.855 \\pm 0.008$</td>\n",
       "      <td>$0.1349 \\pm 0.004$</td>\n",
       "      <td>$0.8577 \\pm 0.003$</td>\n",
       "      <td>$0.1337 \\pm 0.002$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.003105</td>\n",
       "      <td>0.856776</td>\n",
       "      <td>0.006424</td>\n",
       "      <td>0.856776</td>\n",
       "      <td>0.006424</td>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.003105</td>\n",
       "      <td>0.856776</td>\n",
       "      <td>0.006424</td>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.003105</td>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.003105</td>\n",
       "      <td>0.856776</td>\n",
       "      <td>0.006424</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361090</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.774765</td>\n",
       "      <td>0.010520</td>\n",
       "      <td>0.673214</td>\n",
       "      <td>0.009003</td>\n",
       "      <td>0.686704</td>\n",
       "      <td>0.003095</td>\n",
       "      <td>0.758662</td>\n",
       "      <td>0.003703</td>\n",
       "      <td>0.684825</td>\n",
       "      <td>0.002794</td>\n",
       "      <td>0.760934</td>\n",
       "      <td>0.003209</td>\n",
       "      <td>0.761963</td>\n",
       "      <td>0.003628</td>\n",
       "      <td>0.683970</td>\n",
       "      <td>0.003196</td>\n",
       "      <td>$0.6867 \\pm 0.003$</td>\n",
       "      <td>$0.7587 \\pm 0.004$</td>\n",
       "      <td>$0.6848 \\pm 0.003$</td>\n",
       "      <td>$0.7609 \\pm 0.003$</td>\n",
       "      <td>$0.684 \\pm 0.003$</td>\n",
       "      <td>$0.762 \\pm 0.004$</td>\n",
       "      <td>$0.6732 \\pm 0.009$</td>\n",
       "      <td>$0.7748 \\pm 0.011$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.781211</td>\n",
       "      <td>0.024629</td>\n",
       "      <td>0.667505</td>\n",
       "      <td>0.021057</td>\n",
       "      <td>0.667505</td>\n",
       "      <td>0.021057</td>\n",
       "      <td>0.781211</td>\n",
       "      <td>0.024629</td>\n",
       "      <td>0.667505</td>\n",
       "      <td>0.021057</td>\n",
       "      <td>0.781211</td>\n",
       "      <td>0.024629</td>\n",
       "      <td>0.781211</td>\n",
       "      <td>0.024629</td>\n",
       "      <td>0.667505</td>\n",
       "      <td>0.021057</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">42570</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>9.262296</td>\n",
       "      <td>0.451748</td>\n",
       "      <td>0.503583</td>\n",
       "      <td>0.027106</td>\n",
       "      <td>0.489164</td>\n",
       "      <td>0.028370</td>\n",
       "      <td>9.217702</td>\n",
       "      <td>0.619747</td>\n",
       "      <td>0.493155</td>\n",
       "      <td>0.018303</td>\n",
       "      <td>9.160692</td>\n",
       "      <td>0.623823</td>\n",
       "      <td>9.154491</td>\n",
       "      <td>0.611918</td>\n",
       "      <td>0.496105</td>\n",
       "      <td>0.014031</td>\n",
       "      <td>$0.4892 \\pm 0.028$</td>\n",
       "      <td>$9.2177 \\pm 0.62$</td>\n",
       "      <td>$0.4932 \\pm 0.018$</td>\n",
       "      <td>$9.1607 \\pm 0.624$</td>\n",
       "      <td>$0.4961 \\pm 0.014$</td>\n",
       "      <td>$9.1545 \\pm 0.612$</td>\n",
       "      <td>$0.5036 \\pm 0.027$</td>\n",
       "      <td>$9.2623 \\pm 0.452$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>9.290604</td>\n",
       "      <td>0.545377</td>\n",
       "      <td>0.490130</td>\n",
       "      <td>0.023668</td>\n",
       "      <td>0.490130</td>\n",
       "      <td>0.023668</td>\n",
       "      <td>9.290604</td>\n",
       "      <td>0.545377</td>\n",
       "      <td>0.490130</td>\n",
       "      <td>0.023668</td>\n",
       "      <td>9.290604</td>\n",
       "      <td>0.545377</td>\n",
       "      <td>9.290604</td>\n",
       "      <td>0.545377</td>\n",
       "      <td>0.490130</td>\n",
       "      <td>0.023668</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  RMSE_0                R2_0            \\\n",
       "                                    mean       std      mean       std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     2.285418  0.100470  0.984469  0.002246   \n",
       "        Random   Metric         2.255033  0.054383  0.984932  0.001562   \n",
       "361073  PDF      PDF Energy     7.787946  7.280729  0.938506  0.102860   \n",
       "        Random   Metric         4.500983  0.427056  0.988351  0.002250   \n",
       "361078  PDF      PDF Energy     0.220044  0.006596  0.850595  0.007950   \n",
       "        Random   Metric         0.219382  0.006101  0.851484  0.007593   \n",
       "361080  PDF      PDF Energy     0.236615  0.002581  0.945512  0.001174   \n",
       "        Random   Metric         0.245571  0.007037  0.941395  0.003407   \n",
       "361081  PDF      PDF Energy     0.068299  0.032262  0.991214  0.007269   \n",
       "        Random   Metric         0.080185  0.042063  0.987352  0.011227   \n",
       "361082  PDF      PDF Energy   104.037535  3.800579  0.669927  0.021896   \n",
       "        Random   Metric       107.276317  3.316033  0.648812  0.024293   \n",
       "361083  PDF      PDF Energy     0.338191  0.001142  0.678404  0.001914   \n",
       "        Random   Metric         0.338191  0.001142  0.678404  0.001914   \n",
       "361085  PDF      PDF Energy     0.031774  0.018239  0.641823  0.306866   \n",
       "        Random   Metric         0.020685  0.005476  0.865283  0.047684   \n",
       "361086  PDF      PDF Energy     0.084504  0.002723  0.977709  0.001351   \n",
       "        Random   Metric         0.085796  0.002569  0.977018  0.001366   \n",
       "361087  PDF      PDF Energy     0.152191  0.005796  0.928885  0.005403   \n",
       "        Random   Metric         0.145906  0.002920  0.934689  0.002550   \n",
       "361088  PDF      PDF Energy    10.045855  0.458113  0.914604  0.008210   \n",
       "        Random   Metric        10.163004  0.587097  0.912474  0.010639   \n",
       "361089  PDF      PDF Energy     0.133728  0.002153  0.857686  0.003428   \n",
       "        Random   Metric         0.134125  0.003105  0.856776  0.006424   \n",
       "361090  PDF      PDF Energy     0.774765  0.010520  0.673214  0.009003   \n",
       "        Random   Metric         0.781211  0.024629  0.667505  0.021057   \n",
       "42570   PDF      PDF Energy     9.262296  0.451748  0.503583  0.027106   \n",
       "        Random   Metric         9.290604  0.545377  0.490130  0.023668   \n",
       "\n",
       "                                 R2_10               RMSE_10            \\\n",
       "                                  mean       std        mean       std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   0.985745  0.001963    2.190370  0.074086   \n",
       "        Random   Metric       0.984932  0.001562    2.255033  0.054383   \n",
       "361073  PDF      PDF Energy   0.988413  0.001283    4.501045  0.248430   \n",
       "        Random   Metric       0.988351  0.002250    4.500983  0.427056   \n",
       "361078  PDF      PDF Energy   0.851884  0.005652    0.219117  0.004809   \n",
       "        Random   Metric       0.851484  0.007593    0.219382  0.006101   \n",
       "361080  PDF      PDF Energy   0.946005  0.000959    0.235549  0.002595   \n",
       "        Random   Metric       0.941395  0.003407    0.245571  0.007037   \n",
       "361081  PDF      PDF Energy   0.986533  0.010035    0.084016  0.041159   \n",
       "        Random   Metric       0.987352  0.011227    0.080185  0.042063   \n",
       "361082  PDF      PDF Energy   0.662916  0.020850  105.133282  3.342916   \n",
       "        Random   Metric       0.648812  0.024293  107.276317  3.316033   \n",
       "361083  PDF      PDF Energy   0.678404  0.001914    0.338191  0.001142   \n",
       "        Random   Metric       0.678404  0.001914    0.338191  0.001142   \n",
       "361085  PDF      PDF Energy   0.477815  0.229302    0.039400  0.012013   \n",
       "        Random   Metric       0.865283  0.047684    0.020685  0.005476   \n",
       "361086  PDF      PDF Energy   0.979168  0.000376    0.081717  0.000592   \n",
       "        Random   Metric       0.977018  0.001366    0.085796  0.002569   \n",
       "361087  PDF      PDF Energy   0.933776  0.005480    0.146841  0.005367   \n",
       "        Random   Metric       0.934689  0.002550    0.145906  0.002920   \n",
       "361088  PDF      PDF Energy   0.913125  0.011120   10.125706  0.618858   \n",
       "        Random   Metric       0.912474  0.010639   10.163004  0.587097   \n",
       "361089  PDF      PDF Energy   0.857258  0.005862    0.133920  0.003375   \n",
       "        Random   Metric       0.856776  0.006424    0.134125  0.003105   \n",
       "361090  PDF      PDF Energy   0.686704  0.003095    0.758662  0.003703   \n",
       "        Random   Metric       0.667505  0.021057    0.781211  0.024629   \n",
       "42570   PDF      PDF Energy   0.489164  0.028370    9.217702  0.619747   \n",
       "        Random   Metric       0.490130  0.023668    9.290604  0.545377   \n",
       "\n",
       "                                R2_100              RMSE_100            \\\n",
       "                                  mean       std        mean       std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   0.983909  0.003078    2.320368  0.136334   \n",
       "        Random   Metric       0.984932  0.001562    2.255033  0.054383   \n",
       "361073  PDF      PDF Energy   0.971971  0.002034    7.006527  0.242512   \n",
       "        Random   Metric       0.988351  0.002250    4.500983  0.427056   \n",
       "361078  PDF      PDF Energy   0.853217  0.005896    0.218125  0.004974   \n",
       "        Random   Metric       0.851484  0.007593    0.219382  0.006101   \n",
       "361080  PDF      PDF Energy   0.945651  0.001858    0.236279  0.002878   \n",
       "        Random   Metric       0.941395  0.003407    0.245571  0.007037   \n",
       "361081  PDF      PDF Energy   0.985932  0.011924    0.085687  0.042495   \n",
       "        Random   Metric       0.987352  0.011227    0.080185  0.042063   \n",
       "361082  PDF      PDF Energy   0.675929  0.022423  103.074698  3.567029   \n",
       "        Random   Metric       0.648812  0.024293  107.276317  3.316033   \n",
       "361083  PDF      PDF Energy   0.648337  0.090280    0.351565  0.039796   \n",
       "        Random   Metric       0.678404  0.001914    0.338191  0.001142   \n",
       "361085  PDF      PDF Energy   0.883703  0.034511    0.019340  0.004794   \n",
       "        Random   Metric       0.865283  0.047684    0.020685  0.005476   \n",
       "361086  PDF      PDF Energy   0.978913  0.001084    0.082192  0.001929   \n",
       "        Random   Metric       0.977018  0.001366    0.085796  0.002569   \n",
       "361087  PDF      PDF Energy   0.935413  0.001680    0.145124  0.002119   \n",
       "        Random   Metric       0.934689  0.002550    0.145906  0.002920   \n",
       "361088  PDF      PDF Energy   0.915239  0.007387   10.010129  0.407764   \n",
       "        Random   Metric       0.912474  0.010639   10.163004  0.587097   \n",
       "361089  PDF      PDF Energy   0.858721  0.002397    0.133246  0.001880   \n",
       "        Random   Metric       0.856776  0.006424    0.134125  0.003105   \n",
       "361090  PDF      PDF Energy   0.684825  0.002794    0.760934  0.003209   \n",
       "        Random   Metric       0.667505  0.021057    0.781211  0.024629   \n",
       "42570   PDF      PDF Energy   0.493155  0.018303    9.160692  0.623823   \n",
       "        Random   Metric       0.490130  0.023668    9.290604  0.545377   \n",
       "\n",
       "                               RMSE_1000             R2_1000            \\\n",
       "                                    mean       std      mean       std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     2.255595  0.133364  0.984800  0.002932   \n",
       "        Random   Metric         2.255033  0.054383  0.984932  0.001562   \n",
       "361073  PDF      PDF Energy     6.991734  0.261632  0.972084  0.002177   \n",
       "        Random   Metric         4.500983  0.427056  0.988351  0.002250   \n",
       "361078  PDF      PDF Energy     0.218092  0.005036  0.853256  0.006053   \n",
       "        Random   Metric         0.219382  0.006101  0.851484  0.007593   \n",
       "361080  PDF      PDF Energy     0.237668  0.003062  0.945017  0.001660   \n",
       "        Random   Metric         0.245571  0.007037  0.941395  0.003407   \n",
       "361081  PDF      PDF Energy     0.082649  0.037941  0.987250  0.009615   \n",
       "        Random   Metric         0.080185  0.042063  0.987352  0.011227   \n",
       "361082  PDF      PDF Energy   104.601624  3.162918  0.666179  0.022590   \n",
       "        Random   Metric       107.276317  3.316033  0.648812  0.024293   \n",
       "361083  PDF      PDF Energy     0.338191  0.001142  0.678404  0.001914   \n",
       "        Random   Metric         0.338191  0.001142  0.678404  0.001914   \n",
       "361085  PDF      PDF Energy     0.019340  0.004794  0.883703  0.034511   \n",
       "        Random   Metric         0.020685  0.005476  0.865283  0.047684   \n",
       "361086  PDF      PDF Energy     0.082264  0.001558  0.978884  0.000786   \n",
       "        Random   Metric         0.085796  0.002569  0.977018  0.001366   \n",
       "361087  PDF      PDF Energy     0.146271  0.003300  0.934376  0.002705   \n",
       "        Random   Metric         0.145906  0.002920  0.934689  0.002550   \n",
       "361088  PDF      PDF Energy    10.010129  0.407764  0.915239  0.007387   \n",
       "        Random   Metric        10.163004  0.587097  0.912474  0.010639   \n",
       "361089  PDF      PDF Energy     0.134945  0.004059  0.854991  0.008456   \n",
       "        Random   Metric         0.134125  0.003105  0.856776  0.006424   \n",
       "361090  PDF      PDF Energy     0.761963  0.003628  0.683970  0.003196   \n",
       "        Random   Metric         0.781211  0.024629  0.667505  0.021057   \n",
       "42570   PDF      PDF Energy     9.154491  0.611918  0.496105  0.014031   \n",
       "        Random   Metric         9.290604  0.545377  0.490130  0.023668   \n",
       "\n",
       "                                          _R2_10              _RMSE_10  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   $0.9857 \\pm 0.002$    $2.1904 \\pm 0.074$   \n",
       "        Random   Metric       $0.9849 \\pm 0.002$     $2.255 \\pm 0.054$   \n",
       "361073  PDF      PDF Energy   $0.9884 \\pm 0.001$     $4.501 \\pm 0.248$   \n",
       "        Random   Metric       $0.9884 \\pm 0.002$     $4.501 \\pm 0.427$   \n",
       "361078  PDF      PDF Energy   $0.8519 \\pm 0.006$    $0.2191 \\pm 0.005$   \n",
       "        Random   Metric       $0.8515 \\pm 0.008$    $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy    $0.946 \\pm 0.001$    $0.2355 \\pm 0.003$   \n",
       "        Random   Metric       $0.9414 \\pm 0.003$    $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy    $0.9865 \\pm 0.01$     $0.084 \\pm 0.041$   \n",
       "        Random   Metric       $0.9874 \\pm 0.011$    $0.0802 \\pm 0.042$   \n",
       "361082  PDF      PDF Energy   $0.6629 \\pm 0.021$  $105.1333 \\pm 3.343$   \n",
       "        Random   Metric       $0.6488 \\pm 0.024$  $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy   $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$   \n",
       "        Random   Metric       $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$   \n",
       "361085  PDF      PDF Energy   $0.4778 \\pm 0.229$    $0.0394 \\pm 0.012$   \n",
       "        Random   Metric       $0.8653 \\pm 0.048$    $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy     $0.9792 \\pm 0.0$    $0.0817 \\pm 0.001$   \n",
       "        Random   Metric        $0.977 \\pm 0.001$    $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy   $0.9338 \\pm 0.005$    $0.1468 \\pm 0.005$   \n",
       "        Random   Metric       $0.9347 \\pm 0.003$    $0.1459 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   $0.9131 \\pm 0.011$   $10.1257 \\pm 0.619$   \n",
       "        Random   Metric       $0.9125 \\pm 0.011$    $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy   $0.8573 \\pm 0.006$    $0.1339 \\pm 0.003$   \n",
       "        Random   Metric       $0.8568 \\pm 0.006$    $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy   $0.6867 \\pm 0.003$    $0.7587 \\pm 0.004$   \n",
       "        Random   Metric       $0.6675 \\pm 0.021$    $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy   $0.4892 \\pm 0.028$     $9.2177 \\pm 0.62$   \n",
       "        Random   Metric       $0.4901 \\pm 0.024$    $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                         _R2_100             _RMSE_100  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   $0.9839 \\pm 0.003$    $2.3204 \\pm 0.136$   \n",
       "        Random   Metric       $0.9849 \\pm 0.002$     $2.255 \\pm 0.054$   \n",
       "361073  PDF      PDF Energy    $0.972 \\pm 0.002$    $7.0065 \\pm 0.243$   \n",
       "        Random   Metric       $0.9884 \\pm 0.002$     $4.501 \\pm 0.427$   \n",
       "361078  PDF      PDF Energy   $0.8532 \\pm 0.006$    $0.2181 \\pm 0.005$   \n",
       "        Random   Metric       $0.8515 \\pm 0.008$    $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy   $0.9457 \\pm 0.002$    $0.2363 \\pm 0.003$   \n",
       "        Random   Metric       $0.9414 \\pm 0.003$    $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy   $0.9859 \\pm 0.012$    $0.0857 \\pm 0.042$   \n",
       "        Random   Metric       $0.9874 \\pm 0.011$    $0.0802 \\pm 0.042$   \n",
       "361082  PDF      PDF Energy   $0.6759 \\pm 0.022$  $103.0747 \\pm 3.567$   \n",
       "        Random   Metric       $0.6488 \\pm 0.024$  $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy    $0.6483 \\pm 0.09$     $0.3516 \\pm 0.04$   \n",
       "        Random   Metric       $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$   \n",
       "361085  PDF      PDF Energy   $0.8837 \\pm 0.035$    $0.0193 \\pm 0.005$   \n",
       "        Random   Metric       $0.8653 \\pm 0.048$    $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy   $0.9789 \\pm 0.001$    $0.0822 \\pm 0.002$   \n",
       "        Random   Metric        $0.977 \\pm 0.001$    $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy   $0.9354 \\pm 0.002$    $0.1451 \\pm 0.002$   \n",
       "        Random   Metric       $0.9347 \\pm 0.003$    $0.1459 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   $0.9152 \\pm 0.007$   $10.0101 \\pm 0.408$   \n",
       "        Random   Metric       $0.9125 \\pm 0.011$    $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy   $0.8587 \\pm 0.002$    $0.1332 \\pm 0.002$   \n",
       "        Random   Metric       $0.8568 \\pm 0.006$    $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy   $0.6848 \\pm 0.003$    $0.7609 \\pm 0.003$   \n",
       "        Random   Metric       $0.6675 \\pm 0.021$    $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy   $0.4932 \\pm 0.018$    $9.1607 \\pm 0.624$   \n",
       "        Random   Metric       $0.4901 \\pm 0.024$    $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                        _R2_1000            _RMSE_1000  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   $0.9848 \\pm 0.003$    $2.2556 \\pm 0.133$   \n",
       "        Random   Metric       $0.9849 \\pm 0.002$     $2.255 \\pm 0.054$   \n",
       "361073  PDF      PDF Energy   $0.9721 \\pm 0.002$    $6.9917 \\pm 0.262$   \n",
       "        Random   Metric       $0.9884 \\pm 0.002$     $4.501 \\pm 0.427$   \n",
       "361078  PDF      PDF Energy   $0.8533 \\pm 0.006$    $0.2181 \\pm 0.005$   \n",
       "        Random   Metric       $0.8515 \\pm 0.008$    $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy    $0.945 \\pm 0.002$    $0.2377 \\pm 0.003$   \n",
       "        Random   Metric       $0.9414 \\pm 0.003$    $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy    $0.9872 \\pm 0.01$    $0.0826 \\pm 0.038$   \n",
       "        Random   Metric       $0.9874 \\pm 0.011$    $0.0802 \\pm 0.042$   \n",
       "361082  PDF      PDF Energy   $0.6662 \\pm 0.023$  $104.6016 \\pm 3.163$   \n",
       "        Random   Metric       $0.6488 \\pm 0.024$  $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy   $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$   \n",
       "        Random   Metric       $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$   \n",
       "361085  PDF      PDF Energy   $0.8837 \\pm 0.035$    $0.0193 \\pm 0.005$   \n",
       "        Random   Metric       $0.8653 \\pm 0.048$    $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy   $0.9789 \\pm 0.001$    $0.0823 \\pm 0.002$   \n",
       "        Random   Metric        $0.977 \\pm 0.001$    $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy   $0.9344 \\pm 0.003$    $0.1463 \\pm 0.003$   \n",
       "        Random   Metric       $0.9347 \\pm 0.003$    $0.1459 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   $0.9152 \\pm 0.007$   $10.0101 \\pm 0.408$   \n",
       "        Random   Metric       $0.9125 \\pm 0.011$    $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy    $0.855 \\pm 0.008$    $0.1349 \\pm 0.004$   \n",
       "        Random   Metric       $0.8568 \\pm 0.006$    $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy    $0.684 \\pm 0.003$     $0.762 \\pm 0.004$   \n",
       "        Random   Metric       $0.6675 \\pm 0.021$    $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy   $0.4961 \\pm 0.014$    $9.1545 \\pm 0.612$   \n",
       "        Random   Metric       $0.4901 \\pm 0.024$    $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                           _R2_0               _RMSE_0  \n",
       "                                                                        \n",
       "Dataset Sampling Eval_Method                                            \n",
       "361072  PDF      PDF Energy   $0.9845 \\pm 0.002$      $2.2854 \\pm 0.1$  \n",
       "        Random   Metric       $0.9849 \\pm 0.002$     $2.255 \\pm 0.054$  \n",
       "361073  PDF      PDF Energy   $0.9385 \\pm 0.103$    $7.7879 \\pm 7.281$  \n",
       "        Random   Metric       $0.9884 \\pm 0.002$     $4.501 \\pm 0.427$  \n",
       "361078  PDF      PDF Energy   $0.8506 \\pm 0.008$      $0.22 \\pm 0.007$  \n",
       "        Random   Metric       $0.8515 \\pm 0.008$    $0.2194 \\pm 0.006$  \n",
       "361080  PDF      PDF Energy   $0.9455 \\pm 0.001$    $0.2366 \\pm 0.003$  \n",
       "        Random   Metric       $0.9414 \\pm 0.003$    $0.2456 \\pm 0.007$  \n",
       "361081  PDF      PDF Energy   $0.9912 \\pm 0.007$    $0.0683 \\pm 0.032$  \n",
       "        Random   Metric       $0.9874 \\pm 0.011$    $0.0802 \\pm 0.042$  \n",
       "361082  PDF      PDF Energy   $0.6699 \\pm 0.022$  $104.0375 \\pm 3.801$  \n",
       "        Random   Metric       $0.6488 \\pm 0.024$  $107.2763 \\pm 3.316$  \n",
       "361083  PDF      PDF Energy   $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$  \n",
       "        Random   Metric       $0.6784 \\pm 0.002$    $0.3382 \\pm 0.001$  \n",
       "361085  PDF      PDF Energy   $0.6418 \\pm 0.307$    $0.0318 \\pm 0.018$  \n",
       "        Random   Metric       $0.8653 \\pm 0.048$    $0.0207 \\pm 0.005$  \n",
       "361086  PDF      PDF Energy   $0.9777 \\pm 0.001$    $0.0845 \\pm 0.003$  \n",
       "        Random   Metric        $0.977 \\pm 0.001$    $0.0858 \\pm 0.003$  \n",
       "361087  PDF      PDF Energy   $0.9289 \\pm 0.005$    $0.1522 \\pm 0.006$  \n",
       "        Random   Metric       $0.9347 \\pm 0.003$    $0.1459 \\pm 0.003$  \n",
       "361088  PDF      PDF Energy   $0.9146 \\pm 0.008$   $10.0459 \\pm 0.458$  \n",
       "        Random   Metric       $0.9125 \\pm 0.011$    $10.163 \\pm 0.587$  \n",
       "361089  PDF      PDF Energy   $0.8577 \\pm 0.003$    $0.1337 \\pm 0.002$  \n",
       "        Random   Metric       $0.8568 \\pm 0.006$    $0.1341 \\pm 0.003$  \n",
       "361090  PDF      PDF Energy   $0.6732 \\pm 0.009$    $0.7748 \\pm 0.011$  \n",
       "        Random   Metric       $0.6675 \\pm 0.021$    $0.7812 \\pm 0.025$  \n",
       "42570   PDF      PDF Energy   $0.5036 \\pm 0.027$    $9.2623 \\pm 0.452$  \n",
       "        Random   Metric       $0.4901 \\pm 0.024$    $9.2906 \\pm 0.545$  "
      ]
     },
     "execution_count": 859,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 860,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_1000</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_1000</th>\n",
       "      <th>_R2_10</th>\n",
       "      <th>_RMSE_10</th>\n",
       "      <th>_R2_100</th>\n",
       "      <th>_RMSE_100</th>\n",
       "      <th>_R2_1000</th>\n",
       "      <th>_RMSE_1000</th>\n",
       "      <th>_R2_0</th>\n",
       "      <th>_RMSE_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dataset</th>\n",
       "      <th>Sampling</th>\n",
       "      <th>Eval_Method</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361072</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>2.2854</td>\n",
       "      <td>0.1005</td>\n",
       "      <td>0.9845</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.9857</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>2.1904</td>\n",
       "      <td>0.0741</td>\n",
       "      <td>0.9839</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>2.3204</td>\n",
       "      <td>0.1363</td>\n",
       "      <td>2.2556</td>\n",
       "      <td>0.1334</td>\n",
       "      <td>0.9848</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>\\pmb{$0.9857 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.1904 \\pm 0.074$}</td>\n",
       "      <td>$0.9839 \\pm 0.003$</td>\n",
       "      <td>$2.3204 \\pm 0.136$</td>\n",
       "      <td>$0.9848 \\pm 0.003$</td>\n",
       "      <td>$2.2556 \\pm 0.133$</td>\n",
       "      <td>$0.9845 \\pm 0.002$</td>\n",
       "      <td>$2.2854 \\pm 0.1$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>\\pmb{$0.9849 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.255 \\pm 0.054$}</td>\n",
       "      <td>\\pmb{$0.9849 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.255 \\pm 0.054$}</td>\n",
       "      <td>\\pmb{$0.9849 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.255 \\pm 0.054$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361073</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>7.7879</td>\n",
       "      <td>7.2807</td>\n",
       "      <td>0.9385</td>\n",
       "      <td>0.1029</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.2484</td>\n",
       "      <td>0.9720</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>7.0065</td>\n",
       "      <td>0.2425</td>\n",
       "      <td>6.9917</td>\n",
       "      <td>0.2616</td>\n",
       "      <td>0.9721</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.248$}</td>\n",
       "      <td>$0.972 \\pm 0.002$</td>\n",
       "      <td>$7.0065 \\pm 0.243$</td>\n",
       "      <td>$0.9721 \\pm 0.002$</td>\n",
       "      <td>$6.9917 \\pm 0.262$</td>\n",
       "      <td>$0.9385 \\pm 0.103$</td>\n",
       "      <td>$7.7879 \\pm 7.281$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361078</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.2200</td>\n",
       "      <td>0.0066</td>\n",
       "      <td>0.8506</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>0.8519</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.2191</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.8532</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.2181</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.2181</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.8533</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>\\pmb{$0.8519 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.2191 \\pm 0.005$}</td>\n",
       "      <td>\\pmb{$0.8532 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.2181 \\pm 0.005$}</td>\n",
       "      <td>\\pmb{$0.8533 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.2181 \\pm 0.005$}</td>\n",
       "      <td>$0.8506 \\pm 0.008$</td>\n",
       "      <td>$0.22 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>\\pmb{$0.8515 \\pm 0.008$}</td>\n",
       "      <td>\\pmb{$0.2194 \\pm 0.006$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361080</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.2366</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9455</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>0.9460</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>0.2355</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9457</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.2363</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.2377</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.9450</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>\\pmb{$0.946 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.2355 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.9457 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.2363 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.945 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.2377 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.9455 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.2366 \\pm 0.003$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361081</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0683</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.9912</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.9865</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0840</td>\n",
       "      <td>0.0412</td>\n",
       "      <td>0.9859</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>0.0857</td>\n",
       "      <td>0.0425</td>\n",
       "      <td>0.0826</td>\n",
       "      <td>0.0379</td>\n",
       "      <td>0.9872</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>$0.9865 \\pm 0.01$</td>\n",
       "      <td>$0.084 \\pm 0.041$</td>\n",
       "      <td>$0.9859 \\pm 0.012$</td>\n",
       "      <td>$0.0857 \\pm 0.042$</td>\n",
       "      <td>$0.9872 \\pm 0.01$</td>\n",
       "      <td>$0.0826 \\pm 0.038$</td>\n",
       "      <td>\\pmb{$0.9912 \\pm 0.007$}</td>\n",
       "      <td>\\pmb{$0.0683 \\pm 0.032$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>\\pmb{$0.9874 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$0.0802 \\pm 0.042$}</td>\n",
       "      <td>\\pmb{$0.9874 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$0.0802 \\pm 0.042$}</td>\n",
       "      <td>\\pmb{$0.9874 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$0.0802 \\pm 0.042$}</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361082</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>104.0375</td>\n",
       "      <td>3.8006</td>\n",
       "      <td>0.6699</td>\n",
       "      <td>0.0219</td>\n",
       "      <td>0.6629</td>\n",
       "      <td>0.0208</td>\n",
       "      <td>105.1333</td>\n",
       "      <td>3.3429</td>\n",
       "      <td>0.6759</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>103.0747</td>\n",
       "      <td>3.5670</td>\n",
       "      <td>104.6016</td>\n",
       "      <td>3.1629</td>\n",
       "      <td>0.6662</td>\n",
       "      <td>0.0226</td>\n",
       "      <td>\\pmb{$0.6629 \\pm 0.021$}</td>\n",
       "      <td>\\pmb{$105.1333 \\pm 3.343$}</td>\n",
       "      <td>\\pmb{$0.6759 \\pm 0.022$}</td>\n",
       "      <td>\\pmb{$103.0747 \\pm 3.567$}</td>\n",
       "      <td>\\pmb{$0.6662 \\pm 0.023$}</td>\n",
       "      <td>\\pmb{$104.6016 \\pm 3.163$}</td>\n",
       "      <td>\\pmb{$0.6699 \\pm 0.022$}</td>\n",
       "      <td>\\pmb{$104.0375 \\pm 3.801$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361083</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6483</td>\n",
       "      <td>0.0903</td>\n",
       "      <td>0.3516</td>\n",
       "      <td>0.0398</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>$0.6483 \\pm 0.09$</td>\n",
       "      <td>$0.3516 \\pm 0.04$</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361085</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.0182</td>\n",
       "      <td>0.6418</td>\n",
       "      <td>0.3069</td>\n",
       "      <td>0.4778</td>\n",
       "      <td>0.2293</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.8837</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.8837</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>$0.4778 \\pm 0.229$</td>\n",
       "      <td>$0.0394 \\pm 0.012$</td>\n",
       "      <td>\\pmb{$0.8837 \\pm 0.035$}</td>\n",
       "      <td>\\pmb{$0.0193 \\pm 0.005$}</td>\n",
       "      <td>\\pmb{$0.8837 \\pm 0.035$}</td>\n",
       "      <td>\\pmb{$0.0193 \\pm 0.005$}</td>\n",
       "      <td>$0.6418 \\pm 0.307$</td>\n",
       "      <td>$0.0318 \\pm 0.018$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>\\pmb{$0.8653 \\pm 0.048$}</td>\n",
       "      <td>\\pmb{$0.0207 \\pm 0.005$}</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>\\pmb{$0.8653 \\pm 0.048$}</td>\n",
       "      <td>\\pmb{$0.0207 \\pm 0.005$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361086</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0845</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.9777</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.9792</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0817</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.0822</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0823</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>\\pmb{$0.9792 \\pm 0.0$}</td>\n",
       "      <td>\\pmb{$0.0817 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.9789 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.0822 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.9789 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.0823 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.9777 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.0845 \\pm 0.003$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361087</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0.9289</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.9338</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.1468</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.9354</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.1463</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0.9344</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>$0.9338 \\pm 0.005$</td>\n",
       "      <td>$0.1468 \\pm 0.005$</td>\n",
       "      <td>\\pmb{$0.9354 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.1451 \\pm 0.002$}</td>\n",
       "      <td>$0.9344 \\pm 0.003$</td>\n",
       "      <td>$0.1463 \\pm 0.003$</td>\n",
       "      <td>$0.9289 \\pm 0.005$</td>\n",
       "      <td>$0.1522 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>\\pmb{$0.9347 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1459 \\pm 0.003$}</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>\\pmb{$0.9347 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1459 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.9347 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1459 \\pm 0.003$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361088</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>10.0459</td>\n",
       "      <td>0.4581</td>\n",
       "      <td>0.9146</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>0.9131</td>\n",
       "      <td>0.0111</td>\n",
       "      <td>10.1257</td>\n",
       "      <td>0.6189</td>\n",
       "      <td>0.9152</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>10.0101</td>\n",
       "      <td>0.4078</td>\n",
       "      <td>10.0101</td>\n",
       "      <td>0.4078</td>\n",
       "      <td>0.9152</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>\\pmb{$0.9131 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$10.1257 \\pm 0.619$}</td>\n",
       "      <td>\\pmb{$0.9152 \\pm 0.007$}</td>\n",
       "      <td>\\pmb{$10.0101 \\pm 0.408$}</td>\n",
       "      <td>\\pmb{$0.9152 \\pm 0.007$}</td>\n",
       "      <td>\\pmb{$10.0101 \\pm 0.408$}</td>\n",
       "      <td>\\pmb{$0.9146 \\pm 0.008$}</td>\n",
       "      <td>\\pmb{$10.0459 \\pm 0.458$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361089</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.1337</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.8577</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8573</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.1339</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8587</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.1332</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.1349</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>0.8550</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>\\pmb{$0.8573 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.1339 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.8587 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.1332 \\pm 0.002$}</td>\n",
       "      <td>$0.855 \\pm 0.008$</td>\n",
       "      <td>$0.1349 \\pm 0.004$</td>\n",
       "      <td>\\pmb{$0.8577 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1337 \\pm 0.002$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>\\pmb{$0.8568 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.1341 \\pm 0.003$}</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361090</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.7748</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.6732</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.6867</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.7587</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.6848</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.7609</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.7620</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.6840</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>\\pmb{$0.6867 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.7587 \\pm 0.004$}</td>\n",
       "      <td>\\pmb{$0.6848 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.7609 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.684 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.762 \\pm 0.004$}</td>\n",
       "      <td>\\pmb{$0.6732 \\pm 0.009$}</td>\n",
       "      <td>\\pmb{$0.7748 \\pm 0.011$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">42570</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>9.2623</td>\n",
       "      <td>0.4517</td>\n",
       "      <td>0.5036</td>\n",
       "      <td>0.0271</td>\n",
       "      <td>0.4892</td>\n",
       "      <td>0.0284</td>\n",
       "      <td>9.2177</td>\n",
       "      <td>0.6197</td>\n",
       "      <td>0.4932</td>\n",
       "      <td>0.0183</td>\n",
       "      <td>9.1607</td>\n",
       "      <td>0.6238</td>\n",
       "      <td>9.1545</td>\n",
       "      <td>0.6119</td>\n",
       "      <td>0.4961</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>$0.4892 \\pm 0.028$</td>\n",
       "      <td>\\pmb{$9.2177 \\pm 0.62$}</td>\n",
       "      <td>\\pmb{$0.4932 \\pm 0.018$}</td>\n",
       "      <td>\\pmb{$9.1607 \\pm 0.624$}</td>\n",
       "      <td>\\pmb{$0.4961 \\pm 0.014$}</td>\n",
       "      <td>\\pmb{$9.1545 \\pm 0.612$}</td>\n",
       "      <td>\\pmb{$0.5036 \\pm 0.027$}</td>\n",
       "      <td>\\pmb{$9.2623 \\pm 0.452$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>\\pmb{$0.4901 \\pm 0.024$}</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                RMSE_0            R2_0           R2_10  \\\n",
       "                                  mean     std    mean     std    mean   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     2.2854  0.1005  0.9845  0.0022  0.9857   \n",
       "        Random   Metric         2.2550  0.0544  0.9849  0.0016  0.9849   \n",
       "361073  PDF      PDF Energy     7.7879  7.2807  0.9385  0.1029  0.9884   \n",
       "        Random   Metric         4.5010  0.4271  0.9884  0.0023  0.9884   \n",
       "361078  PDF      PDF Energy     0.2200  0.0066  0.8506  0.0080  0.8519   \n",
       "        Random   Metric         0.2194  0.0061  0.8515  0.0076  0.8515   \n",
       "361080  PDF      PDF Energy     0.2366  0.0026  0.9455  0.0012  0.9460   \n",
       "        Random   Metric         0.2456  0.0070  0.9414  0.0034  0.9414   \n",
       "361081  PDF      PDF Energy     0.0683  0.0323  0.9912  0.0073  0.9865   \n",
       "        Random   Metric         0.0802  0.0421  0.9874  0.0112  0.9874   \n",
       "361082  PDF      PDF Energy   104.0375  3.8006  0.6699  0.0219  0.6629   \n",
       "        Random   Metric       107.2763  3.3160  0.6488  0.0243  0.6488   \n",
       "361083  PDF      PDF Energy     0.3382  0.0011  0.6784  0.0019  0.6784   \n",
       "        Random   Metric         0.3382  0.0011  0.6784  0.0019  0.6784   \n",
       "361085  PDF      PDF Energy     0.0318  0.0182  0.6418  0.3069  0.4778   \n",
       "        Random   Metric         0.0207  0.0055  0.8653  0.0477  0.8653   \n",
       "361086  PDF      PDF Energy     0.0845  0.0027  0.9777  0.0014  0.9792   \n",
       "        Random   Metric         0.0858  0.0026  0.9770  0.0014  0.9770   \n",
       "361087  PDF      PDF Energy     0.1522  0.0058  0.9289  0.0054  0.9338   \n",
       "        Random   Metric         0.1459  0.0029  0.9347  0.0026  0.9347   \n",
       "361088  PDF      PDF Energy    10.0459  0.4581  0.9146  0.0082  0.9131   \n",
       "        Random   Metric        10.1630  0.5871  0.9125  0.0106  0.9125   \n",
       "361089  PDF      PDF Energy     0.1337  0.0022  0.8577  0.0034  0.8573   \n",
       "        Random   Metric         0.1341  0.0031  0.8568  0.0064  0.8568   \n",
       "361090  PDF      PDF Energy     0.7748  0.0105  0.6732  0.0090  0.6867   \n",
       "        Random   Metric         0.7812  0.0246  0.6675  0.0211  0.6675   \n",
       "42570   PDF      PDF Energy     9.2623  0.4517  0.5036  0.0271  0.4892   \n",
       "        Random   Metric         9.2906  0.5454  0.4901  0.0237  0.4901   \n",
       "\n",
       "                                       RMSE_10          R2_100          \\\n",
       "                                 std      mean     std    mean     std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   0.0020    2.1904  0.0741  0.9839  0.0031   \n",
       "        Random   Metric       0.0016    2.2550  0.0544  0.9849  0.0016   \n",
       "361073  PDF      PDF Energy   0.0013    4.5010  0.2484  0.9720  0.0020   \n",
       "        Random   Metric       0.0023    4.5010  0.4271  0.9884  0.0023   \n",
       "361078  PDF      PDF Energy   0.0057    0.2191  0.0048  0.8532  0.0059   \n",
       "        Random   Metric       0.0076    0.2194  0.0061  0.8515  0.0076   \n",
       "361080  PDF      PDF Energy   0.0010    0.2355  0.0026  0.9457  0.0019   \n",
       "        Random   Metric       0.0034    0.2456  0.0070  0.9414  0.0034   \n",
       "361081  PDF      PDF Energy   0.0100    0.0840  0.0412  0.9859  0.0119   \n",
       "        Random   Metric       0.0112    0.0802  0.0421  0.9874  0.0112   \n",
       "361082  PDF      PDF Energy   0.0208  105.1333  3.3429  0.6759  0.0224   \n",
       "        Random   Metric       0.0243  107.2763  3.3160  0.6488  0.0243   \n",
       "361083  PDF      PDF Energy   0.0019    0.3382  0.0011  0.6483  0.0903   \n",
       "        Random   Metric       0.0019    0.3382  0.0011  0.6784  0.0019   \n",
       "361085  PDF      PDF Energy   0.2293    0.0394  0.0120  0.8837  0.0345   \n",
       "        Random   Metric       0.0477    0.0207  0.0055  0.8653  0.0477   \n",
       "361086  PDF      PDF Energy   0.0004    0.0817  0.0006  0.9789  0.0011   \n",
       "        Random   Metric       0.0014    0.0858  0.0026  0.9770  0.0014   \n",
       "361087  PDF      PDF Energy   0.0055    0.1468  0.0054  0.9354  0.0017   \n",
       "        Random   Metric       0.0026    0.1459  0.0029  0.9347  0.0026   \n",
       "361088  PDF      PDF Energy   0.0111   10.1257  0.6189  0.9152  0.0074   \n",
       "        Random   Metric       0.0106   10.1630  0.5871  0.9125  0.0106   \n",
       "361089  PDF      PDF Energy   0.0059    0.1339  0.0034  0.8587  0.0024   \n",
       "        Random   Metric       0.0064    0.1341  0.0031  0.8568  0.0064   \n",
       "361090  PDF      PDF Energy   0.0031    0.7587  0.0037  0.6848  0.0028   \n",
       "        Random   Metric       0.0211    0.7812  0.0246  0.6675  0.0211   \n",
       "42570   PDF      PDF Energy   0.0284    9.2177  0.6197  0.4932  0.0183   \n",
       "        Random   Metric       0.0237    9.2906  0.5454  0.4901  0.0237   \n",
       "\n",
       "                              RMSE_100         RMSE_1000         R2_1000  \\\n",
       "                                  mean     std      mean     std    mean   \n",
       "Dataset Sampling Eval_Method                                               \n",
       "361072  PDF      PDF Energy     2.3204  0.1363    2.2556  0.1334  0.9848   \n",
       "        Random   Metric         2.2550  0.0544    2.2550  0.0544  0.9849   \n",
       "361073  PDF      PDF Energy     7.0065  0.2425    6.9917  0.2616  0.9721   \n",
       "        Random   Metric         4.5010  0.4271    4.5010  0.4271  0.9884   \n",
       "361078  PDF      PDF Energy     0.2181  0.0050    0.2181  0.0050  0.8533   \n",
       "        Random   Metric         0.2194  0.0061    0.2194  0.0061  0.8515   \n",
       "361080  PDF      PDF Energy     0.2363  0.0029    0.2377  0.0031  0.9450   \n",
       "        Random   Metric         0.2456  0.0070    0.2456  0.0070  0.9414   \n",
       "361081  PDF      PDF Energy     0.0857  0.0425    0.0826  0.0379  0.9872   \n",
       "        Random   Metric         0.0802  0.0421    0.0802  0.0421  0.9874   \n",
       "361082  PDF      PDF Energy   103.0747  3.5670  104.6016  3.1629  0.6662   \n",
       "        Random   Metric       107.2763  3.3160  107.2763  3.3160  0.6488   \n",
       "361083  PDF      PDF Energy     0.3516  0.0398    0.3382  0.0011  0.6784   \n",
       "        Random   Metric         0.3382  0.0011    0.3382  0.0011  0.6784   \n",
       "361085  PDF      PDF Energy     0.0193  0.0048    0.0193  0.0048  0.8837   \n",
       "        Random   Metric         0.0207  0.0055    0.0207  0.0055  0.8653   \n",
       "361086  PDF      PDF Energy     0.0822  0.0019    0.0823  0.0016  0.9789   \n",
       "        Random   Metric         0.0858  0.0026    0.0858  0.0026  0.9770   \n",
       "361087  PDF      PDF Energy     0.1451  0.0021    0.1463  0.0033  0.9344   \n",
       "        Random   Metric         0.1459  0.0029    0.1459  0.0029  0.9347   \n",
       "361088  PDF      PDF Energy    10.0101  0.4078   10.0101  0.4078  0.9152   \n",
       "        Random   Metric        10.1630  0.5871   10.1630  0.5871  0.9125   \n",
       "361089  PDF      PDF Energy     0.1332  0.0019    0.1349  0.0041  0.8550   \n",
       "        Random   Metric         0.1341  0.0031    0.1341  0.0031  0.8568   \n",
       "361090  PDF      PDF Energy     0.7609  0.0032    0.7620  0.0036  0.6840   \n",
       "        Random   Metric         0.7812  0.0246    0.7812  0.0246  0.6675   \n",
       "42570   PDF      PDF Energy     9.1607  0.6238    9.1545  0.6119  0.4961   \n",
       "        Random   Metric         9.2906  0.5454    9.2906  0.5454  0.4901   \n",
       "\n",
       "                                                        _R2_10  \\\n",
       "                                 std                             \n",
       "Dataset Sampling Eval_Method                                     \n",
       "361072  PDF      PDF Energy   0.0029  \\pmb{$0.9857 \\pm 0.002$}   \n",
       "        Random   Metric       0.0016        $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy   0.0022  \\pmb{$0.9884 \\pm 0.001$}   \n",
       "        Random   Metric       0.0023  \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy   0.0061  \\pmb{$0.8519 \\pm 0.006$}   \n",
       "        Random   Metric       0.0076        $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy   0.0017   \\pmb{$0.946 \\pm 0.001$}   \n",
       "        Random   Metric       0.0034        $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy   0.0096         $0.9865 \\pm 0.01$   \n",
       "        Random   Metric       0.0112  \\pmb{$0.9874 \\pm 0.011$}   \n",
       "361082  PDF      PDF Energy   0.0226  \\pmb{$0.6629 \\pm 0.021$}   \n",
       "        Random   Metric       0.0243        $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   0.0019  \\pmb{$0.6784 \\pm 0.002$}   \n",
       "        Random   Metric       0.0019  \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy   0.0345        $0.4778 \\pm 0.229$   \n",
       "        Random   Metric       0.0477  \\pmb{$0.8653 \\pm 0.048$}   \n",
       "361086  PDF      PDF Energy   0.0008    \\pmb{$0.9792 \\pm 0.0$}   \n",
       "        Random   Metric       0.0014         $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy   0.0027        $0.9338 \\pm 0.005$   \n",
       "        Random   Metric       0.0026  \\pmb{$0.9347 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy   0.0074  \\pmb{$0.9131 \\pm 0.011$}   \n",
       "        Random   Metric       0.0106        $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   0.0085  \\pmb{$0.8573 \\pm 0.006$}   \n",
       "        Random   Metric       0.0064        $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   0.0032  \\pmb{$0.6867 \\pm 0.003$}   \n",
       "        Random   Metric       0.0211        $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   0.0140        $0.4892 \\pm 0.028$   \n",
       "        Random   Metric       0.0237  \\pmb{$0.4901 \\pm 0.024$}   \n",
       "\n",
       "                                                _RMSE_10  \\\n",
       "                                                           \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy     \\pmb{$2.1904 \\pm 0.074$}   \n",
       "        Random   Metric                $2.255 \\pm 0.054$   \n",
       "361073  PDF      PDF Energy      \\pmb{$4.501 \\pm 0.248$}   \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}   \n",
       "361078  PDF      PDF Energy     \\pmb{$0.2191 \\pm 0.005$}   \n",
       "        Random   Metric               $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2355 \\pm 0.003$}   \n",
       "        Random   Metric               $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy            $0.084 \\pm 0.041$   \n",
       "        Random   Metric         \\pmb{$0.0802 \\pm 0.042$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$105.1333 \\pm 3.343$}   \n",
       "        Random   Metric             $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy     \\pmb{$0.3382 \\pm 0.001$}   \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}   \n",
       "361085  PDF      PDF Energy           $0.0394 \\pm 0.012$   \n",
       "        Random   Metric         \\pmb{$0.0207 \\pm 0.005$}   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0817 \\pm 0.001$}   \n",
       "        Random   Metric               $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy           $0.1468 \\pm 0.005$   \n",
       "        Random   Metric         \\pmb{$0.1459 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy    \\pmb{$10.1257 \\pm 0.619$}   \n",
       "        Random   Metric               $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy     \\pmb{$0.1339 \\pm 0.003$}   \n",
       "        Random   Metric               $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy     \\pmb{$0.7587 \\pm 0.004$}   \n",
       "        Random   Metric               $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy      \\pmb{$9.2177 \\pm 0.62$}   \n",
       "        Random   Metric               $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                               _R2_100  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy         $0.9839 \\pm 0.003$   \n",
       "        Random   Metric       \\pmb{$0.9849 \\pm 0.002$}   \n",
       "361073  PDF      PDF Energy          $0.972 \\pm 0.002$   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy   \\pmb{$0.8532 \\pm 0.006$}   \n",
       "        Random   Metric             $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy   \\pmb{$0.9457 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy         $0.9859 \\pm 0.012$   \n",
       "        Random   Metric       \\pmb{$0.9874 \\pm 0.011$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6759 \\pm 0.022$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy          $0.6483 \\pm 0.09$   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy   \\pmb{$0.8837 \\pm 0.035$}   \n",
       "        Random   Metric             $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy   \\pmb{$0.9789 \\pm 0.001$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy   \\pmb{$0.9354 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9152 \\pm 0.007$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   \\pmb{$0.8587 \\pm 0.002$}   \n",
       "        Random   Metric             $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   \\pmb{$0.6848 \\pm 0.003$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   \\pmb{$0.4932 \\pm 0.018$}   \n",
       "        Random   Metric             $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                               _RMSE_100  \\\n",
       "                                                           \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy           $2.3204 \\pm 0.136$   \n",
       "        Random   Metric          \\pmb{$2.255 \\pm 0.054$}   \n",
       "361073  PDF      PDF Energy           $7.0065 \\pm 0.243$   \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}   \n",
       "361078  PDF      PDF Energy     \\pmb{$0.2181 \\pm 0.005$}   \n",
       "        Random   Metric               $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2363 \\pm 0.003$}   \n",
       "        Random   Metric               $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy           $0.0857 \\pm 0.042$   \n",
       "        Random   Metric         \\pmb{$0.0802 \\pm 0.042$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$103.0747 \\pm 3.567$}   \n",
       "        Random   Metric             $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy            $0.3516 \\pm 0.04$   \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}   \n",
       "361085  PDF      PDF Energy     \\pmb{$0.0193 \\pm 0.005$}   \n",
       "        Random   Metric               $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0822 \\pm 0.002$}   \n",
       "        Random   Metric               $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy     \\pmb{$0.1451 \\pm 0.002$}   \n",
       "        Random   Metric               $0.1459 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    \\pmb{$10.0101 \\pm 0.408$}   \n",
       "        Random   Metric               $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy     \\pmb{$0.1332 \\pm 0.002$}   \n",
       "        Random   Metric               $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy     \\pmb{$0.7609 \\pm 0.003$}   \n",
       "        Random   Metric               $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy     \\pmb{$9.1607 \\pm 0.624$}   \n",
       "        Random   Metric               $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                              _R2_1000  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy         $0.9848 \\pm 0.003$   \n",
       "        Random   Metric       \\pmb{$0.9849 \\pm 0.002$}   \n",
       "361073  PDF      PDF Energy         $0.9721 \\pm 0.002$   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy   \\pmb{$0.8533 \\pm 0.006$}   \n",
       "        Random   Metric             $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy    \\pmb{$0.945 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy          $0.9872 \\pm 0.01$   \n",
       "        Random   Metric       \\pmb{$0.9874 \\pm 0.011$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6662 \\pm 0.023$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   \\pmb{$0.6784 \\pm 0.002$}   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy   \\pmb{$0.8837 \\pm 0.035$}   \n",
       "        Random   Metric             $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy   \\pmb{$0.9789 \\pm 0.001$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy         $0.9344 \\pm 0.003$   \n",
       "        Random   Metric       \\pmb{$0.9347 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9152 \\pm 0.007$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy          $0.855 \\pm 0.008$   \n",
       "        Random   Metric       \\pmb{$0.8568 \\pm 0.006$}   \n",
       "361090  PDF      PDF Energy    \\pmb{$0.684 \\pm 0.003$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   \\pmb{$0.4961 \\pm 0.014$}   \n",
       "        Random   Metric             $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                              _RMSE_1000  \\\n",
       "                                                           \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy           $2.2556 \\pm 0.133$   \n",
       "        Random   Metric          \\pmb{$2.255 \\pm 0.054$}   \n",
       "361073  PDF      PDF Energy           $6.9917 \\pm 0.262$   \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}   \n",
       "361078  PDF      PDF Energy     \\pmb{$0.2181 \\pm 0.005$}   \n",
       "        Random   Metric               $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2377 \\pm 0.003$}   \n",
       "        Random   Metric               $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy           $0.0826 \\pm 0.038$   \n",
       "        Random   Metric         \\pmb{$0.0802 \\pm 0.042$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$104.6016 \\pm 3.163$}   \n",
       "        Random   Metric             $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy     \\pmb{$0.3382 \\pm 0.001$}   \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}   \n",
       "361085  PDF      PDF Energy     \\pmb{$0.0193 \\pm 0.005$}   \n",
       "        Random   Metric               $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0823 \\pm 0.002$}   \n",
       "        Random   Metric               $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy           $0.1463 \\pm 0.003$   \n",
       "        Random   Metric         \\pmb{$0.1459 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy    \\pmb{$10.0101 \\pm 0.408$}   \n",
       "        Random   Metric               $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy           $0.1349 \\pm 0.004$   \n",
       "        Random   Metric         \\pmb{$0.1341 \\pm 0.003$}   \n",
       "361090  PDF      PDF Energy      \\pmb{$0.762 \\pm 0.004$}   \n",
       "        Random   Metric               $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy     \\pmb{$9.1545 \\pm 0.612$}   \n",
       "        Random   Metric               $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                                 _R2_0  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy         $0.9845 \\pm 0.002$   \n",
       "        Random   Metric       \\pmb{$0.9849 \\pm 0.002$}   \n",
       "361073  PDF      PDF Energy         $0.9385 \\pm 0.103$   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy         $0.8506 \\pm 0.008$   \n",
       "        Random   Metric       \\pmb{$0.8515 \\pm 0.008$}   \n",
       "361080  PDF      PDF Energy   \\pmb{$0.9455 \\pm 0.001$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy   \\pmb{$0.9912 \\pm 0.007$}   \n",
       "        Random   Metric             $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6699 \\pm 0.022$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   \\pmb{$0.6784 \\pm 0.002$}   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy         $0.6418 \\pm 0.307$   \n",
       "        Random   Metric       \\pmb{$0.8653 \\pm 0.048$}   \n",
       "361086  PDF      PDF Energy   \\pmb{$0.9777 \\pm 0.001$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy         $0.9289 \\pm 0.005$   \n",
       "        Random   Metric       \\pmb{$0.9347 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9146 \\pm 0.008$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   \\pmb{$0.8577 \\pm 0.003$}   \n",
       "        Random   Metric             $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   \\pmb{$0.6732 \\pm 0.009$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   \\pmb{$0.5036 \\pm 0.027$}   \n",
       "        Random   Metric             $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                                 _RMSE_0  \n",
       "                                                          \n",
       "Dataset Sampling Eval_Method                              \n",
       "361072  PDF      PDF Energy             $2.2854 \\pm 0.1$  \n",
       "        Random   Metric          \\pmb{$2.255 \\pm 0.054$}  \n",
       "361073  PDF      PDF Energy           $7.7879 \\pm 7.281$  \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}  \n",
       "361078  PDF      PDF Energy             $0.22 \\pm 0.007$  \n",
       "        Random   Metric         \\pmb{$0.2194 \\pm 0.006$}  \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2366 \\pm 0.003$}  \n",
       "        Random   Metric               $0.2456 \\pm 0.007$  \n",
       "361081  PDF      PDF Energy     \\pmb{$0.0683 \\pm 0.032$}  \n",
       "        Random   Metric               $0.0802 \\pm 0.042$  \n",
       "361082  PDF      PDF Energy   \\pmb{$104.0375 \\pm 3.801$}  \n",
       "        Random   Metric             $107.2763 \\pm 3.316$  \n",
       "361083  PDF      PDF Energy     \\pmb{$0.3382 \\pm 0.001$}  \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}  \n",
       "361085  PDF      PDF Energy           $0.0318 \\pm 0.018$  \n",
       "        Random   Metric         \\pmb{$0.0207 \\pm 0.005$}  \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0845 \\pm 0.003$}  \n",
       "        Random   Metric               $0.0858 \\pm 0.003$  \n",
       "361087  PDF      PDF Energy           $0.1522 \\pm 0.006$  \n",
       "        Random   Metric         \\pmb{$0.1459 \\pm 0.003$}  \n",
       "361088  PDF      PDF Energy    \\pmb{$10.0459 \\pm 0.458$}  \n",
       "        Random   Metric               $10.163 \\pm 0.587$  \n",
       "361089  PDF      PDF Energy     \\pmb{$0.1337 \\pm 0.002$}  \n",
       "        Random   Metric               $0.1341 \\pm 0.003$  \n",
       "361090  PDF      PDF Energy     \\pmb{$0.7748 \\pm 0.011$}  \n",
       "        Random   Metric               $0.7812 \\pm 0.025$  \n",
       "42570   PDF      PDF Energy     \\pmb{$9.2623 \\pm 0.452$}  \n",
       "        Random   Metric               $9.2906 \\pm 0.545$  "
      ]
     },
     "execution_count": 860,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def make_bold(dx, cols,metric):\n",
    "    for col in cols:\n",
    "        #print(col,dx.columns[col])\n",
    "        first=True\n",
    "        for i in dx.index:\n",
    "            if first:\n",
    "                prev=i\n",
    "                first=False\n",
    "                continue\n",
    "            #print(i,dx.loc[i,dx.columns[col]],prev,dx.loc[prev,dx.columns[col]])\n",
    "            if dx.loc[i,dx.columns[col]]==dx.loc[prev,dx.columns[col]]:\n",
    "                dx.loc[i, ('_'+dx.columns[col][0],'')]='\\pmb{'+dx.loc[i,('_'+dx.columns[col][0],'')]+'}'\n",
    "                dx.loc[prev, ('_'+dx.columns[col][0],'')]='\\pmb{'+dx.loc[prev,('_'+dx.columns[col][0],'')]+'}'\n",
    "            elif ((dx.loc[i,dx.columns[col]]<dx.loc[prev,dx.columns[col]] and metric=='rmse') or \n",
    "                  (dx.loc[i,dx.columns[col]]>dx.loc[prev,dx.columns[col]] and metric=='r2')):\n",
    "                dx.loc[i, ('_'+dx.columns[col][0],'')]='\\pmb{'+dx.loc[i,('_'+dx.columns[col][0],'')]+'}'\n",
    "            else:# dx.loc[i,dx.columns[col]]>dx.loc[prev,dx.columns[col]] and metric=='rmse':\n",
    "                dx.loc[prev, ('_'+dx.columns[col][0],'')]='\\pmb{'+dx.loc[prev,('_'+dx.columns[col][0],'')]+'}'\n",
    "            \n",
    "            first=True\n",
    "    return dx\n",
    "dx=dx.round(4)\n",
    "dx1=make_bold(dx.copy(),rmse_col,'rmse')\n",
    "dx2=make_bold(dx1,r2_col,'r2')\n",
    "dx2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 861,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_latex(df):\n",
    "    return str(df.to_latex().replace('\\$','$').replace('\\\\textbackslash ','\\\\').replace('\\{','{').replace('\\}','}'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 862,
   "metadata": {},
   "outputs": [],
   "source": [
    "def del_non_paper(dx):\n",
    "    del dx['R2_0']\n",
    "    del dx['R2_10']\n",
    "    del dx['R2_100']\n",
    "    del dx['R2_1000']\n",
    "    del dx['RMSE_0']\n",
    "    del dx['RMSE_10']\n",
    "    del dx['RMSE_100']\n",
    "    del dx['RMSE_1000']\n",
    "    return dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 863,
   "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 tr th {\n",
       "        text-align: left;\n",
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>_R2_10</th>\n",
       "      <th>_RMSE_10</th>\n",
       "      <th>_R2_100</th>\n",
       "      <th>_RMSE_100</th>\n",
       "      <th>_R2_1000</th>\n",
       "      <th>_RMSE_1000</th>\n",
       "      <th>_R2_0</th>\n",
       "      <th>_RMSE_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dataset</th>\n",
       "      <th>Sampling</th>\n",
       "      <th>Eval_Method</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361072</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.9857 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.1904 \\pm 0.074$}</td>\n",
       "      <td>$0.9839 \\pm 0.003$</td>\n",
       "      <td>$2.3204 \\pm 0.136$</td>\n",
       "      <td>$0.9848 \\pm 0.003$</td>\n",
       "      <td>$2.2556 \\pm 0.133$</td>\n",
       "      <td>$0.9845 \\pm 0.002$</td>\n",
       "      <td>$2.2854 \\pm 0.1$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>\\pmb{$0.9849 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.255 \\pm 0.054$}</td>\n",
       "      <td>\\pmb{$0.9849 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.255 \\pm 0.054$}</td>\n",
       "      <td>\\pmb{$0.9849 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$2.255 \\pm 0.054$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361073</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.248$}</td>\n",
       "      <td>$0.972 \\pm 0.002$</td>\n",
       "      <td>$7.0065 \\pm 0.243$</td>\n",
       "      <td>$0.9721 \\pm 0.002$</td>\n",
       "      <td>$6.9917 \\pm 0.262$</td>\n",
       "      <td>$0.9385 \\pm 0.103$</td>\n",
       "      <td>$7.7879 \\pm 7.281$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "      <td>\\pmb{$0.9884 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$4.501 \\pm 0.427$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361078</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.8519 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.2191 \\pm 0.005$}</td>\n",
       "      <td>\\pmb{$0.8532 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.2181 \\pm 0.005$}</td>\n",
       "      <td>\\pmb{$0.8533 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.2181 \\pm 0.005$}</td>\n",
       "      <td>$0.8506 \\pm 0.008$</td>\n",
       "      <td>$0.22 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>\\pmb{$0.8515 \\pm 0.008$}</td>\n",
       "      <td>\\pmb{$0.2194 \\pm 0.006$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361080</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.946 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.2355 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.9457 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.2363 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.945 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.2377 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.9455 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.2366 \\pm 0.003$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361081</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>$0.9865 \\pm 0.01$</td>\n",
       "      <td>$0.084 \\pm 0.041$</td>\n",
       "      <td>$0.9859 \\pm 0.012$</td>\n",
       "      <td>$0.0857 \\pm 0.042$</td>\n",
       "      <td>$0.9872 \\pm 0.01$</td>\n",
       "      <td>$0.0826 \\pm 0.038$</td>\n",
       "      <td>\\pmb{$0.9912 \\pm 0.007$}</td>\n",
       "      <td>\\pmb{$0.0683 \\pm 0.032$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>\\pmb{$0.9874 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$0.0802 \\pm 0.042$}</td>\n",
       "      <td>\\pmb{$0.9874 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$0.0802 \\pm 0.042$}</td>\n",
       "      <td>\\pmb{$0.9874 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$0.0802 \\pm 0.042$}</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361082</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.6629 \\pm 0.021$}</td>\n",
       "      <td>\\pmb{$105.1333 \\pm 3.343$}</td>\n",
       "      <td>\\pmb{$0.6759 \\pm 0.022$}</td>\n",
       "      <td>\\pmb{$103.0747 \\pm 3.567$}</td>\n",
       "      <td>\\pmb{$0.6662 \\pm 0.023$}</td>\n",
       "      <td>\\pmb{$104.6016 \\pm 3.163$}</td>\n",
       "      <td>\\pmb{$0.6699 \\pm 0.022$}</td>\n",
       "      <td>\\pmb{$104.0375 \\pm 3.801$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361083</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>$0.6483 \\pm 0.09$</td>\n",
       "      <td>$0.3516 \\pm 0.04$</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.6784 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.3382 \\pm 0.001$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361085</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>$0.4778 \\pm 0.229$</td>\n",
       "      <td>$0.0394 \\pm 0.012$</td>\n",
       "      <td>\\pmb{$0.8837 \\pm 0.035$}</td>\n",
       "      <td>\\pmb{$0.0193 \\pm 0.005$}</td>\n",
       "      <td>\\pmb{$0.8837 \\pm 0.035$}</td>\n",
       "      <td>\\pmb{$0.0193 \\pm 0.005$}</td>\n",
       "      <td>$0.6418 \\pm 0.307$</td>\n",
       "      <td>$0.0318 \\pm 0.018$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>\\pmb{$0.8653 \\pm 0.048$}</td>\n",
       "      <td>\\pmb{$0.0207 \\pm 0.005$}</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>\\pmb{$0.8653 \\pm 0.048$}</td>\n",
       "      <td>\\pmb{$0.0207 \\pm 0.005$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361086</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.9792 \\pm 0.0$}</td>\n",
       "      <td>\\pmb{$0.0817 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.9789 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.0822 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.9789 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.0823 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.9777 \\pm 0.001$}</td>\n",
       "      <td>\\pmb{$0.0845 \\pm 0.003$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361087</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>$0.9338 \\pm 0.005$</td>\n",
       "      <td>$0.1468 \\pm 0.005$</td>\n",
       "      <td>\\pmb{$0.9354 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.1451 \\pm 0.002$}</td>\n",
       "      <td>$0.9344 \\pm 0.003$</td>\n",
       "      <td>$0.1463 \\pm 0.003$</td>\n",
       "      <td>$0.9289 \\pm 0.005$</td>\n",
       "      <td>$0.1522 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>\\pmb{$0.9347 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1459 \\pm 0.003$}</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>\\pmb{$0.9347 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1459 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.9347 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1459 \\pm 0.003$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361088</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.9131 \\pm 0.011$}</td>\n",
       "      <td>\\pmb{$10.1257 \\pm 0.619$}</td>\n",
       "      <td>\\pmb{$0.9152 \\pm 0.007$}</td>\n",
       "      <td>\\pmb{$10.0101 \\pm 0.408$}</td>\n",
       "      <td>\\pmb{$0.9152 \\pm 0.007$}</td>\n",
       "      <td>\\pmb{$10.0101 \\pm 0.408$}</td>\n",
       "      <td>\\pmb{$0.9146 \\pm 0.008$}</td>\n",
       "      <td>\\pmb{$10.0459 \\pm 0.458$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361089</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.8573 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.1339 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.8587 \\pm 0.002$}</td>\n",
       "      <td>\\pmb{$0.1332 \\pm 0.002$}</td>\n",
       "      <td>$0.855 \\pm 0.008$</td>\n",
       "      <td>$0.1349 \\pm 0.004$</td>\n",
       "      <td>\\pmb{$0.8577 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.1337 \\pm 0.002$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>\\pmb{$0.8568 \\pm 0.006$}</td>\n",
       "      <td>\\pmb{$0.1341 \\pm 0.003$}</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361090</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>\\pmb{$0.6867 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.7587 \\pm 0.004$}</td>\n",
       "      <td>\\pmb{$0.6848 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.7609 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.684 \\pm 0.003$}</td>\n",
       "      <td>\\pmb{$0.762 \\pm 0.004$}</td>\n",
       "      <td>\\pmb{$0.6732 \\pm 0.009$}</td>\n",
       "      <td>\\pmb{$0.7748 \\pm 0.011$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">42570</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>$0.4892 \\pm 0.028$</td>\n",
       "      <td>\\pmb{$9.2177 \\pm 0.62$}</td>\n",
       "      <td>\\pmb{$0.4932 \\pm 0.018$}</td>\n",
       "      <td>\\pmb{$9.1607 \\pm 0.624$}</td>\n",
       "      <td>\\pmb{$0.4961 \\pm 0.014$}</td>\n",
       "      <td>\\pmb{$9.1545 \\pm 0.612$}</td>\n",
       "      <td>\\pmb{$0.5036 \\pm 0.027$}</td>\n",
       "      <td>\\pmb{$9.2623 \\pm 0.452$}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>\\pmb{$0.4901 \\pm 0.024$}</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                _R2_10  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy   \\pmb{$0.9857 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy   \\pmb{$0.9884 \\pm 0.001$}   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy   \\pmb{$0.8519 \\pm 0.006$}   \n",
       "        Random   Metric             $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy    \\pmb{$0.946 \\pm 0.001$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy          $0.9865 \\pm 0.01$   \n",
       "        Random   Metric       \\pmb{$0.9874 \\pm 0.011$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6629 \\pm 0.021$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   \\pmb{$0.6784 \\pm 0.002$}   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy         $0.4778 \\pm 0.229$   \n",
       "        Random   Metric       \\pmb{$0.8653 \\pm 0.048$}   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.9792 \\pm 0.0$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy         $0.9338 \\pm 0.005$   \n",
       "        Random   Metric       \\pmb{$0.9347 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9131 \\pm 0.011$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   \\pmb{$0.8573 \\pm 0.006$}   \n",
       "        Random   Metric             $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   \\pmb{$0.6867 \\pm 0.003$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy         $0.4892 \\pm 0.028$   \n",
       "        Random   Metric       \\pmb{$0.4901 \\pm 0.024$}   \n",
       "\n",
       "                                                _RMSE_10  \\\n",
       "                                                           \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy     \\pmb{$2.1904 \\pm 0.074$}   \n",
       "        Random   Metric                $2.255 \\pm 0.054$   \n",
       "361073  PDF      PDF Energy      \\pmb{$4.501 \\pm 0.248$}   \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}   \n",
       "361078  PDF      PDF Energy     \\pmb{$0.2191 \\pm 0.005$}   \n",
       "        Random   Metric               $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2355 \\pm 0.003$}   \n",
       "        Random   Metric               $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy            $0.084 \\pm 0.041$   \n",
       "        Random   Metric         \\pmb{$0.0802 \\pm 0.042$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$105.1333 \\pm 3.343$}   \n",
       "        Random   Metric             $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy     \\pmb{$0.3382 \\pm 0.001$}   \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}   \n",
       "361085  PDF      PDF Energy           $0.0394 \\pm 0.012$   \n",
       "        Random   Metric         \\pmb{$0.0207 \\pm 0.005$}   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0817 \\pm 0.001$}   \n",
       "        Random   Metric               $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy           $0.1468 \\pm 0.005$   \n",
       "        Random   Metric         \\pmb{$0.1459 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy    \\pmb{$10.1257 \\pm 0.619$}   \n",
       "        Random   Metric               $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy     \\pmb{$0.1339 \\pm 0.003$}   \n",
       "        Random   Metric               $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy     \\pmb{$0.7587 \\pm 0.004$}   \n",
       "        Random   Metric               $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy      \\pmb{$9.2177 \\pm 0.62$}   \n",
       "        Random   Metric               $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                               _R2_100  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy         $0.9839 \\pm 0.003$   \n",
       "        Random   Metric       \\pmb{$0.9849 \\pm 0.002$}   \n",
       "361073  PDF      PDF Energy          $0.972 \\pm 0.002$   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy   \\pmb{$0.8532 \\pm 0.006$}   \n",
       "        Random   Metric             $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy   \\pmb{$0.9457 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy         $0.9859 \\pm 0.012$   \n",
       "        Random   Metric       \\pmb{$0.9874 \\pm 0.011$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6759 \\pm 0.022$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy          $0.6483 \\pm 0.09$   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy   \\pmb{$0.8837 \\pm 0.035$}   \n",
       "        Random   Metric             $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy   \\pmb{$0.9789 \\pm 0.001$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy   \\pmb{$0.9354 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9152 \\pm 0.007$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   \\pmb{$0.8587 \\pm 0.002$}   \n",
       "        Random   Metric             $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   \\pmb{$0.6848 \\pm 0.003$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   \\pmb{$0.4932 \\pm 0.018$}   \n",
       "        Random   Metric             $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                               _RMSE_100  \\\n",
       "                                                           \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy           $2.3204 \\pm 0.136$   \n",
       "        Random   Metric          \\pmb{$2.255 \\pm 0.054$}   \n",
       "361073  PDF      PDF Energy           $7.0065 \\pm 0.243$   \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}   \n",
       "361078  PDF      PDF Energy     \\pmb{$0.2181 \\pm 0.005$}   \n",
       "        Random   Metric               $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2363 \\pm 0.003$}   \n",
       "        Random   Metric               $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy           $0.0857 \\pm 0.042$   \n",
       "        Random   Metric         \\pmb{$0.0802 \\pm 0.042$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$103.0747 \\pm 3.567$}   \n",
       "        Random   Metric             $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy            $0.3516 \\pm 0.04$   \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}   \n",
       "361085  PDF      PDF Energy     \\pmb{$0.0193 \\pm 0.005$}   \n",
       "        Random   Metric               $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0822 \\pm 0.002$}   \n",
       "        Random   Metric               $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy     \\pmb{$0.1451 \\pm 0.002$}   \n",
       "        Random   Metric               $0.1459 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    \\pmb{$10.0101 \\pm 0.408$}   \n",
       "        Random   Metric               $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy     \\pmb{$0.1332 \\pm 0.002$}   \n",
       "        Random   Metric               $0.1341 \\pm 0.003$   \n",
       "361090  PDF      PDF Energy     \\pmb{$0.7609 \\pm 0.003$}   \n",
       "        Random   Metric               $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy     \\pmb{$9.1607 \\pm 0.624$}   \n",
       "        Random   Metric               $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                              _R2_1000  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy         $0.9848 \\pm 0.003$   \n",
       "        Random   Metric       \\pmb{$0.9849 \\pm 0.002$}   \n",
       "361073  PDF      PDF Energy         $0.9721 \\pm 0.002$   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy   \\pmb{$0.8533 \\pm 0.006$}   \n",
       "        Random   Metric             $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy    \\pmb{$0.945 \\pm 0.002$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy          $0.9872 \\pm 0.01$   \n",
       "        Random   Metric       \\pmb{$0.9874 \\pm 0.011$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6662 \\pm 0.023$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   \\pmb{$0.6784 \\pm 0.002$}   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy   \\pmb{$0.8837 \\pm 0.035$}   \n",
       "        Random   Metric             $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy   \\pmb{$0.9789 \\pm 0.001$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy         $0.9344 \\pm 0.003$   \n",
       "        Random   Metric       \\pmb{$0.9347 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9152 \\pm 0.007$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy          $0.855 \\pm 0.008$   \n",
       "        Random   Metric       \\pmb{$0.8568 \\pm 0.006$}   \n",
       "361090  PDF      PDF Energy    \\pmb{$0.684 \\pm 0.003$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   \\pmb{$0.4961 \\pm 0.014$}   \n",
       "        Random   Metric             $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                              _RMSE_1000  \\\n",
       "                                                           \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy           $2.2556 \\pm 0.133$   \n",
       "        Random   Metric          \\pmb{$2.255 \\pm 0.054$}   \n",
       "361073  PDF      PDF Energy           $6.9917 \\pm 0.262$   \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}   \n",
       "361078  PDF      PDF Energy     \\pmb{$0.2181 \\pm 0.005$}   \n",
       "        Random   Metric               $0.2194 \\pm 0.006$   \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2377 \\pm 0.003$}   \n",
       "        Random   Metric               $0.2456 \\pm 0.007$   \n",
       "361081  PDF      PDF Energy           $0.0826 \\pm 0.038$   \n",
       "        Random   Metric         \\pmb{$0.0802 \\pm 0.042$}   \n",
       "361082  PDF      PDF Energy   \\pmb{$104.6016 \\pm 3.163$}   \n",
       "        Random   Metric             $107.2763 \\pm 3.316$   \n",
       "361083  PDF      PDF Energy     \\pmb{$0.3382 \\pm 0.001$}   \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}   \n",
       "361085  PDF      PDF Energy     \\pmb{$0.0193 \\pm 0.005$}   \n",
       "        Random   Metric               $0.0207 \\pm 0.005$   \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0823 \\pm 0.002$}   \n",
       "        Random   Metric               $0.0858 \\pm 0.003$   \n",
       "361087  PDF      PDF Energy           $0.1463 \\pm 0.003$   \n",
       "        Random   Metric         \\pmb{$0.1459 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy    \\pmb{$10.0101 \\pm 0.408$}   \n",
       "        Random   Metric               $10.163 \\pm 0.587$   \n",
       "361089  PDF      PDF Energy           $0.1349 \\pm 0.004$   \n",
       "        Random   Metric         \\pmb{$0.1341 \\pm 0.003$}   \n",
       "361090  PDF      PDF Energy      \\pmb{$0.762 \\pm 0.004$}   \n",
       "        Random   Metric               $0.7812 \\pm 0.025$   \n",
       "42570   PDF      PDF Energy     \\pmb{$9.1545 \\pm 0.612$}   \n",
       "        Random   Metric               $9.2906 \\pm 0.545$   \n",
       "\n",
       "                                                 _R2_0  \\\n",
       "                                                         \n",
       "Dataset Sampling Eval_Method                             \n",
       "361072  PDF      PDF Energy         $0.9845 \\pm 0.002$   \n",
       "        Random   Metric       \\pmb{$0.9849 \\pm 0.002$}   \n",
       "361073  PDF      PDF Energy         $0.9385 \\pm 0.103$   \n",
       "        Random   Metric       \\pmb{$0.9884 \\pm 0.002$}   \n",
       "361078  PDF      PDF Energy         $0.8506 \\pm 0.008$   \n",
       "        Random   Metric       \\pmb{$0.8515 \\pm 0.008$}   \n",
       "361080  PDF      PDF Energy   \\pmb{$0.9455 \\pm 0.001$}   \n",
       "        Random   Metric             $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy   \\pmb{$0.9912 \\pm 0.007$}   \n",
       "        Random   Metric             $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   \\pmb{$0.6699 \\pm 0.022$}   \n",
       "        Random   Metric             $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   \\pmb{$0.6784 \\pm 0.002$}   \n",
       "        Random   Metric       \\pmb{$0.6784 \\pm 0.002$}   \n",
       "361085  PDF      PDF Energy         $0.6418 \\pm 0.307$   \n",
       "        Random   Metric       \\pmb{$0.8653 \\pm 0.048$}   \n",
       "361086  PDF      PDF Energy   \\pmb{$0.9777 \\pm 0.001$}   \n",
       "        Random   Metric              $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy         $0.9289 \\pm 0.005$   \n",
       "        Random   Metric       \\pmb{$0.9347 \\pm 0.003$}   \n",
       "361088  PDF      PDF Energy   \\pmb{$0.9146 \\pm 0.008$}   \n",
       "        Random   Metric             $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   \\pmb{$0.8577 \\pm 0.003$}   \n",
       "        Random   Metric             $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   \\pmb{$0.6732 \\pm 0.009$}   \n",
       "        Random   Metric             $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   \\pmb{$0.5036 \\pm 0.027$}   \n",
       "        Random   Metric             $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                                 _RMSE_0  \n",
       "                                                          \n",
       "Dataset Sampling Eval_Method                              \n",
       "361072  PDF      PDF Energy             $2.2854 \\pm 0.1$  \n",
       "        Random   Metric          \\pmb{$2.255 \\pm 0.054$}  \n",
       "361073  PDF      PDF Energy           $7.7879 \\pm 7.281$  \n",
       "        Random   Metric          \\pmb{$4.501 \\pm 0.427$}  \n",
       "361078  PDF      PDF Energy             $0.22 \\pm 0.007$  \n",
       "        Random   Metric         \\pmb{$0.2194 \\pm 0.006$}  \n",
       "361080  PDF      PDF Energy     \\pmb{$0.2366 \\pm 0.003$}  \n",
       "        Random   Metric               $0.2456 \\pm 0.007$  \n",
       "361081  PDF      PDF Energy     \\pmb{$0.0683 \\pm 0.032$}  \n",
       "        Random   Metric               $0.0802 \\pm 0.042$  \n",
       "361082  PDF      PDF Energy   \\pmb{$104.0375 \\pm 3.801$}  \n",
       "        Random   Metric             $107.2763 \\pm 3.316$  \n",
       "361083  PDF      PDF Energy     \\pmb{$0.3382 \\pm 0.001$}  \n",
       "        Random   Metric         \\pmb{$0.3382 \\pm 0.001$}  \n",
       "361085  PDF      PDF Energy           $0.0318 \\pm 0.018$  \n",
       "        Random   Metric         \\pmb{$0.0207 \\pm 0.005$}  \n",
       "361086  PDF      PDF Energy     \\pmb{$0.0845 \\pm 0.003$}  \n",
       "        Random   Metric               $0.0858 \\pm 0.003$  \n",
       "361087  PDF      PDF Energy           $0.1522 \\pm 0.006$  \n",
       "        Random   Metric         \\pmb{$0.1459 \\pm 0.003$}  \n",
       "361088  PDF      PDF Energy    \\pmb{$10.0459 \\pm 0.458$}  \n",
       "        Random   Metric               $10.163 \\pm 0.587$  \n",
       "361089  PDF      PDF Energy     \\pmb{$0.1337 \\pm 0.002$}  \n",
       "        Random   Metric               $0.1341 \\pm 0.003$  \n",
       "361090  PDF      PDF Energy     \\pmb{$0.7748 \\pm 0.011$}  \n",
       "        Random   Metric               $0.7812 \\pm 0.025$  \n",
       "42570   PDF      PDF Energy     \\pmb{$9.2623 \\pm 0.452$}  \n",
       "        Random   Metric               $9.2906 \\pm 0.545$  "
      ]
     },
     "execution_count": 863,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del_non_paper(dx2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 864,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_tex_dx(dx):\n",
    "    return str(dx.to_latex().replace('\\$',\n",
    "                             '$').replace('\\\\textbackslash ',\n",
    "                                          '\\\\').replace('\\{',\n",
    "                                                        '{').replace('\\}',\n",
    "                                                                     '}').replace('3610',\n",
    "                                                                                  '\\hline 3610'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 865,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_140334/2852109057.py:2: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
      "  return str(dx.to_latex().replace('\\$',\n"
     ]
    }
   ],
   "source": [
    "with open('paper/dx_rmse_r2_pdf_vs_sampling.tex','w') as f:\n",
    "    f.write(get_tex_dx(dx2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 866,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lllllllllll}\n",
      "\\toprule\n",
      "      &        &        &                    \\_R2\\_10 &                    \\_RMSE\\_10 &                   \\_R2\\_100 &                   \\_RMSE\\_100 &                  \\_R2\\_1000 &                  \\_RMSE\\_1000 &                     \\_R2\\_0 &                     \\_RMSE\\_0 \\\\\n",
      "      &        &        \\\\\n",
      "Dataset & Sampling & Eval\\_Method &                           &                             &                           &                             &                           &                             &                           &                             \\\\\n",
      "\\midrule\n",
      "\\hline 361072 & PDF & PDF Energy &  \\pmb{$0.9857 \\pm 0.002$} &    \\pmb{$2.1904 \\pm 0.074$} &        $0.9839 \\pm 0.003$ &          $2.3204 \\pm 0.136$ &        $0.9848 \\pm 0.003$ &          $2.2556 \\pm 0.133$ &        $0.9845 \\pm 0.002$ &            $2.2854 \\pm 0.1$ \\\\\n",
      "      & Random & Metric &        $0.9849 \\pm 0.002$ &           $2.255 \\pm 0.054$ &  \\pmb{$0.9849 \\pm 0.002$} &     \\pmb{$2.255 \\pm 0.054$} &  \\pmb{$0.9849 \\pm 0.002$} &     \\pmb{$2.255 \\pm 0.054$} &  \\pmb{$0.9849 \\pm 0.002$} &     \\pmb{$2.255 \\pm 0.054$} \\\\\n",
      "\\hline 361073 & PDF & PDF Energy &  \\pmb{$0.9884 \\pm 0.001$} &     \\pmb{$4.501 \\pm 0.248$} &         $0.972 \\pm 0.002$ &          $7.0065 \\pm 0.243$ &        $0.9721 \\pm 0.002$ &          $6.9917 \\pm 0.262$ &        $0.9385 \\pm 0.103$ &          $7.7879 \\pm 7.281$ \\\\\n",
      "      & Random & Metric &  \\pmb{$0.9884 \\pm 0.002$} &     \\pmb{$4.501 \\pm 0.427$} &  \\pmb{$0.9884 \\pm 0.002$} &     \\pmb{$4.501 \\pm 0.427$} &  \\pmb{$0.9884 \\pm 0.002$} &     \\pmb{$4.501 \\pm 0.427$} &  \\pmb{$0.9884 \\pm 0.002$} &     \\pmb{$4.501 \\pm 0.427$} \\\\\n",
      "\\hline 361078 & PDF & PDF Energy &  \\pmb{$0.8519 \\pm 0.006$} &    \\pmb{$0.2191 \\pm 0.005$} &  \\pmb{$0.8532 \\pm 0.006$} &    \\pmb{$0.2181 \\pm 0.005$} &  \\pmb{$0.8533 \\pm 0.006$} &    \\pmb{$0.2181 \\pm 0.005$} &        $0.8506 \\pm 0.008$ &            $0.22 \\pm 0.007$ \\\\\n",
      "      & Random & Metric &        $0.8515 \\pm 0.008$ &          $0.2194 \\pm 0.006$ &        $0.8515 \\pm 0.008$ &          $0.2194 \\pm 0.006$ &        $0.8515 \\pm 0.008$ &          $0.2194 \\pm 0.006$ &  \\pmb{$0.8515 \\pm 0.008$} &    \\pmb{$0.2194 \\pm 0.006$} \\\\\n",
      "\\hline 361080 & PDF & PDF Energy &   \\pmb{$0.946 \\pm 0.001$} &    \\pmb{$0.2355 \\pm 0.003$} &  \\pmb{$0.9457 \\pm 0.002$} &    \\pmb{$0.2363 \\pm 0.003$} &   \\pmb{$0.945 \\pm 0.002$} &    \\pmb{$0.2377 \\pm 0.003$} &  \\pmb{$0.9455 \\pm 0.001$} &    \\pmb{$0.2366 \\pm 0.003$} \\\\\n",
      "      & Random & Metric &        $0.9414 \\pm 0.003$ &          $0.2456 \\pm 0.007$ &        $0.9414 \\pm 0.003$ &          $0.2456 \\pm 0.007$ &        $0.9414 \\pm 0.003$ &          $0.2456 \\pm 0.007$ &        $0.9414 \\pm 0.003$ &          $0.2456 \\pm 0.007$ \\\\\n",
      "\\hline 361081 & PDF & PDF Energy &         $0.9865 \\pm 0.01$ &           $0.084 \\pm 0.041$ &        $0.9859 \\pm 0.012$ &          $0.0857 \\pm 0.042$ &         $0.9872 \\pm 0.01$ &          $0.0826 \\pm 0.038$ &  \\pmb{$0.9912 \\pm 0.007$} &    \\pmb{$0.0683 \\pm 0.032$} \\\\\n",
      "      & Random & Metric &  \\pmb{$0.9874 \\pm 0.011$} &    \\pmb{$0.0802 \\pm 0.042$} &  \\pmb{$0.9874 \\pm 0.011$} &    \\pmb{$0.0802 \\pm 0.042$} &  \\pmb{$0.9874 \\pm 0.011$} &    \\pmb{$0.0802 \\pm 0.042$} &        $0.9874 \\pm 0.011$ &          $0.0802 \\pm 0.042$ \\\\\n",
      "\\hline 361082 & PDF & PDF Energy &  \\pmb{$0.6629 \\pm 0.021$} &  \\pmb{$105.1333 \\pm 3.343$} &  \\pmb{$0.6759 \\pm 0.022$} &  \\pmb{$103.0747 \\pm 3.567$} &  \\pmb{$0.6662 \\pm 0.023$} &  \\pmb{$104.6016 \\pm 3.163$} &  \\pmb{$0.6699 \\pm 0.022$} &  \\pmb{$104.0375 \\pm 3.801$} \\\\\n",
      "      & Random & Metric &        $0.6488 \\pm 0.024$ &        $107.2763 \\pm 3.316$ &        $0.6488 \\pm 0.024$ &        $107.2763 \\pm 3.316$ &        $0.6488 \\pm 0.024$ &        $107.2763 \\pm 3.316$ &        $0.6488 \\pm 0.024$ &        $107.2763 \\pm 3.316$ \\\\\n",
      "\\hline 361083 & PDF & PDF Energy &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} &         $0.6483 \\pm 0.09$ &           $0.3516 \\pm 0.04$ &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} \\\\\n",
      "      & Random & Metric &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} &  \\pmb{$0.6784 \\pm 0.002$} &    \\pmb{$0.3382 \\pm 0.001$} \\\\\n",
      "\\hline 361085 & PDF & PDF Energy &        $0.4778 \\pm 0.229$ &          $0.0394 \\pm 0.012$ &  \\pmb{$0.8837 \\pm 0.035$} &    \\pmb{$0.0193 \\pm 0.005$} &  \\pmb{$0.8837 \\pm 0.035$} &    \\pmb{$0.0193 \\pm 0.005$} &        $0.6418 \\pm 0.307$ &          $0.0318 \\pm 0.018$ \\\\\n",
      "      & Random & Metric &  \\pmb{$0.8653 \\pm 0.048$} &    \\pmb{$0.0207 \\pm 0.005$} &        $0.8653 \\pm 0.048$ &          $0.0207 \\pm 0.005$ &        $0.8653 \\pm 0.048$ &          $0.0207 \\pm 0.005$ &  \\pmb{$0.8653 \\pm 0.048$} &    \\pmb{$0.0207 \\pm 0.005$} \\\\\n",
      "\\hline 361086 & PDF & PDF Energy &    \\pmb{$0.9792 \\pm 0.0$} &    \\pmb{$0.0817 \\pm 0.001$} &  \\pmb{$0.9789 \\pm 0.001$} &    \\pmb{$0.0822 \\pm 0.002$} &  \\pmb{$0.9789 \\pm 0.001$} &    \\pmb{$0.0823 \\pm 0.002$} &  \\pmb{$0.9777 \\pm 0.001$} &    \\pmb{$0.0845 \\pm 0.003$} \\\\\n",
      "      & Random & Metric &         $0.977 \\pm 0.001$ &          $0.0858 \\pm 0.003$ &         $0.977 \\pm 0.001$ &          $0.0858 \\pm 0.003$ &         $0.977 \\pm 0.001$ &          $0.0858 \\pm 0.003$ &         $0.977 \\pm 0.001$ &          $0.0858 \\pm 0.003$ \\\\\n",
      "\\hline 361087 & PDF & PDF Energy &        $0.9338 \\pm 0.005$ &          $0.1468 \\pm 0.005$ &  \\pmb{$0.9354 \\pm 0.002$} &    \\pmb{$0.1451 \\pm 0.002$} &        $0.9344 \\pm 0.003$ &          $0.1463 \\pm 0.003$ &        $0.9289 \\pm 0.005$ &          $0.1522 \\pm 0.006$ \\\\\n",
      "      & Random & Metric &  \\pmb{$0.9347 \\pm 0.003$} &    \\pmb{$0.1459 \\pm 0.003$} &        $0.9347 \\pm 0.003$ &          $0.1459 \\pm 0.003$ &  \\pmb{$0.9347 \\pm 0.003$} &    \\pmb{$0.1459 \\pm 0.003$} &  \\pmb{$0.9347 \\pm 0.003$} &    \\pmb{$0.1459 \\pm 0.003$} \\\\\n",
      "\\hline 361088 & PDF & PDF Energy &  \\pmb{$0.9131 \\pm 0.011$} &   \\pmb{$10.1257 \\pm 0.619$} &  \\pmb{$0.9152 \\pm 0.007$} &   \\pmb{$10.0101 \\pm 0.408$} &  \\pmb{$0.9152 \\pm 0.007$} &   \\pmb{$10.0101 \\pm 0.408$} &  \\pmb{$0.9146 \\pm 0.008$} &   \\pmb{$10.0459 \\pm 0.458$} \\\\\n",
      "      & Random & Metric &        $0.9125 \\pm 0.011$ &          $10.163 \\pm 0.587$ &        $0.9125 \\pm 0.011$ &          $10.163 \\pm 0.587$ &        $0.9125 \\pm 0.011$ &          $10.163 \\pm 0.587$ &        $0.9125 \\pm 0.011$ &          $10.163 \\pm 0.587$ \\\\\n",
      "\\hline 361089 & PDF & PDF Energy &  \\pmb{$0.8573 \\pm 0.006$} &    \\pmb{$0.1339 \\pm 0.003$} &  \\pmb{$0.8587 \\pm 0.002$} &    \\pmb{$0.1332 \\pm 0.002$} &         $0.855 \\pm 0.008$ &          $0.1349 \\pm 0.004$ &  \\pmb{$0.8577 \\pm 0.003$} &    \\pmb{$0.1337 \\pm 0.002$} \\\\\n",
      "      & Random & Metric &        $0.8568 \\pm 0.006$ &          $0.1341 \\pm 0.003$ &        $0.8568 \\pm 0.006$ &          $0.1341 \\pm 0.003$ &  \\pmb{$0.8568 \\pm 0.006$} &    \\pmb{$0.1341 \\pm 0.003$} &        $0.8568 \\pm 0.006$ &          $0.1341 \\pm 0.003$ \\\\\n",
      "\\hline 361090 & PDF & PDF Energy &  \\pmb{$0.6867 \\pm 0.003$} &    \\pmb{$0.7587 \\pm 0.004$} &  \\pmb{$0.6848 \\pm 0.003$} &    \\pmb{$0.7609 \\pm 0.003$} &   \\pmb{$0.684 \\pm 0.003$} &     \\pmb{$0.762 \\pm 0.004$} &  \\pmb{$0.6732 \\pm 0.009$} &    \\pmb{$0.7748 \\pm 0.011$} \\\\\n",
      "      & Random & Metric &        $0.6675 \\pm 0.021$ &          $0.7812 \\pm 0.025$ &        $0.6675 \\pm 0.021$ &          $0.7812 \\pm 0.025$ &        $0.6675 \\pm 0.021$ &          $0.7812 \\pm 0.025$ &        $0.6675 \\pm 0.021$ &          $0.7812 \\pm 0.025$ \\\\\n",
      "42570 & PDF & PDF Energy &        $0.4892 \\pm 0.028$ &     \\pmb{$9.2177 \\pm 0.62$} &  \\pmb{$0.4932 \\pm 0.018$} &    \\pmb{$9.1607 \\pm 0.624$} &  \\pmb{$0.4961 \\pm 0.014$} &    \\pmb{$9.1545 \\pm 0.612$} &  \\pmb{$0.5036 \\pm 0.027$} &    \\pmb{$9.2623 \\pm 0.452$} \\\\\n",
      "      & Random & Metric &  \\pmb{$0.4901 \\pm 0.024$} &          $9.2906 \\pm 0.545$ &        $0.4901 \\pm 0.024$ &          $9.2906 \\pm 0.545$ &        $0.4901 \\pm 0.024$ &          $9.2906 \\pm 0.545$ &        $0.4901 \\pm 0.024$ &          $9.2906 \\pm 0.545$ \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_140334/2852109057.py:2: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
      "  return str(dx.to_latex().replace('\\$',\n"
     ]
    }
   ],
   "source": [
    "print(get_tex_dx(dx2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 867,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_1000</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_1000</th>\n",
       "      <th>_R2_10</th>\n",
       "      <th>_RMSE_10</th>\n",
       "      <th>_R2_100</th>\n",
       "      <th>_RMSE_100</th>\n",
       "      <th>_R2_1000</th>\n",
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       "      <th>_RMSE_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
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       "      <th>std</th>\n",
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       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
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       "      <th>std</th>\n",
       "      <th>mean</th>\n",
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       "      <th>Sampling</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361072</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>2.2854</td>\n",
       "      <td>0.1005</td>\n",
       "      <td>0.9845</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.9857</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>2.1904</td>\n",
       "      <td>0.0741</td>\n",
       "      <td>0.9839</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>2.3204</td>\n",
       "      <td>0.1363</td>\n",
       "      <td>2.2556</td>\n",
       "      <td>0.1334</td>\n",
       "      <td>0.9848</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>$0.9857 \\pm 0.002$</td>\n",
       "      <td>$2.1904 \\pm 0.074$</td>\n",
       "      <td>$0.9839 \\pm 0.003$</td>\n",
       "      <td>$2.3204 \\pm 0.136$</td>\n",
       "      <td>$0.9848 \\pm 0.003$</td>\n",
       "      <td>$2.2556 \\pm 0.133$</td>\n",
       "      <td>$0.9845 \\pm 0.002$</td>\n",
       "      <td>$2.2854 \\pm 0.1$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361073</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>7.7879</td>\n",
       "      <td>7.2807</td>\n",
       "      <td>0.9385</td>\n",
       "      <td>0.1029</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.2484</td>\n",
       "      <td>0.9720</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>7.0065</td>\n",
       "      <td>0.2425</td>\n",
       "      <td>6.9917</td>\n",
       "      <td>0.2616</td>\n",
       "      <td>0.9721</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>$0.9884 \\pm 0.001$</td>\n",
       "      <td>$4.501 \\pm 0.248$</td>\n",
       "      <td>$0.972 \\pm 0.002$</td>\n",
       "      <td>$7.0065 \\pm 0.243$</td>\n",
       "      <td>$0.9721 \\pm 0.002$</td>\n",
       "      <td>$6.9917 \\pm 0.262$</td>\n",
       "      <td>$0.9385 \\pm 0.103$</td>\n",
       "      <td>$7.7879 \\pm 7.281$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361078</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.2200</td>\n",
       "      <td>0.0066</td>\n",
       "      <td>0.8506</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>0.8519</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.2191</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.8532</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.2181</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.2181</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.8533</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>$0.8519 \\pm 0.006$</td>\n",
       "      <td>$0.2191 \\pm 0.005$</td>\n",
       "      <td>$0.8532 \\pm 0.006$</td>\n",
       "      <td>$0.2181 \\pm 0.005$</td>\n",
       "      <td>$0.8533 \\pm 0.006$</td>\n",
       "      <td>$0.2181 \\pm 0.005$</td>\n",
       "      <td>$0.8506 \\pm 0.008$</td>\n",
       "      <td>$0.22 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361080</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.2366</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9455</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>0.9460</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>0.2355</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9457</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.2363</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.2377</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.9450</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>$0.946 \\pm 0.001$</td>\n",
       "      <td>$0.2355 \\pm 0.003$</td>\n",
       "      <td>$0.9457 \\pm 0.002$</td>\n",
       "      <td>$0.2363 \\pm 0.003$</td>\n",
       "      <td>$0.945 \\pm 0.002$</td>\n",
       "      <td>$0.2377 \\pm 0.003$</td>\n",
       "      <td>$0.9455 \\pm 0.001$</td>\n",
       "      <td>$0.2366 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361081</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0683</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.9912</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.9865</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0840</td>\n",
       "      <td>0.0412</td>\n",
       "      <td>0.9859</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>0.0857</td>\n",
       "      <td>0.0425</td>\n",
       "      <td>0.0826</td>\n",
       "      <td>0.0379</td>\n",
       "      <td>0.9872</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>$0.9865 \\pm 0.01$</td>\n",
       "      <td>$0.084 \\pm 0.041$</td>\n",
       "      <td>$0.9859 \\pm 0.012$</td>\n",
       "      <td>$0.0857 \\pm 0.042$</td>\n",
       "      <td>$0.9872 \\pm 0.01$</td>\n",
       "      <td>$0.0826 \\pm 0.038$</td>\n",
       "      <td>$0.9912 \\pm 0.007$</td>\n",
       "      <td>$0.0683 \\pm 0.032$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361082</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>104.0375</td>\n",
       "      <td>3.8006</td>\n",
       "      <td>0.6699</td>\n",
       "      <td>0.0219</td>\n",
       "      <td>0.6629</td>\n",
       "      <td>0.0208</td>\n",
       "      <td>105.1333</td>\n",
       "      <td>3.3429</td>\n",
       "      <td>0.6759</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>103.0747</td>\n",
       "      <td>3.5670</td>\n",
       "      <td>104.6016</td>\n",
       "      <td>3.1629</td>\n",
       "      <td>0.6662</td>\n",
       "      <td>0.0226</td>\n",
       "      <td>$0.6629 \\pm 0.021$</td>\n",
       "      <td>$105.1333 \\pm 3.343$</td>\n",
       "      <td>$0.6759 \\pm 0.022$</td>\n",
       "      <td>$103.0747 \\pm 3.567$</td>\n",
       "      <td>$0.6662 \\pm 0.023$</td>\n",
       "      <td>$104.6016 \\pm 3.163$</td>\n",
       "      <td>$0.6699 \\pm 0.022$</td>\n",
       "      <td>$104.0375 \\pm 3.801$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361083</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6483</td>\n",
       "      <td>0.0903</td>\n",
       "      <td>0.3516</td>\n",
       "      <td>0.0398</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6483 \\pm 0.09$</td>\n",
       "      <td>$0.3516 \\pm 0.04$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361085</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.0182</td>\n",
       "      <td>0.6418</td>\n",
       "      <td>0.3069</td>\n",
       "      <td>0.4778</td>\n",
       "      <td>0.2293</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.8837</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.8837</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>$0.4778 \\pm 0.229$</td>\n",
       "      <td>$0.0394 \\pm 0.012$</td>\n",
       "      <td>$0.8837 \\pm 0.035$</td>\n",
       "      <td>$0.0193 \\pm 0.005$</td>\n",
       "      <td>$0.8837 \\pm 0.035$</td>\n",
       "      <td>$0.0193 \\pm 0.005$</td>\n",
       "      <td>$0.6418 \\pm 0.307$</td>\n",
       "      <td>$0.0318 \\pm 0.018$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361086</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0845</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.9777</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.9792</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0817</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.0822</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0823</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>$0.9792 \\pm 0.0$</td>\n",
       "      <td>$0.0817 \\pm 0.001$</td>\n",
       "      <td>$0.9789 \\pm 0.001$</td>\n",
       "      <td>$0.0822 \\pm 0.002$</td>\n",
       "      <td>$0.9789 \\pm 0.001$</td>\n",
       "      <td>$0.0823 \\pm 0.002$</td>\n",
       "      <td>$0.9777 \\pm 0.001$</td>\n",
       "      <td>$0.0845 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361087</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0.9289</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.9338</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.1468</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.9354</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.1463</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0.9344</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>$0.9338 \\pm 0.005$</td>\n",
       "      <td>$0.1468 \\pm 0.005$</td>\n",
       "      <td>$0.9354 \\pm 0.002$</td>\n",
       "      <td>$0.1451 \\pm 0.002$</td>\n",
       "      <td>$0.9344 \\pm 0.003$</td>\n",
       "      <td>$0.1463 \\pm 0.003$</td>\n",
       "      <td>$0.9289 \\pm 0.005$</td>\n",
       "      <td>$0.1522 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361088</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>10.0459</td>\n",
       "      <td>0.4581</td>\n",
       "      <td>0.9146</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>0.9131</td>\n",
       "      <td>0.0111</td>\n",
       "      <td>10.1257</td>\n",
       "      <td>0.6189</td>\n",
       "      <td>0.9152</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>10.0101</td>\n",
       "      <td>0.4078</td>\n",
       "      <td>10.0101</td>\n",
       "      <td>0.4078</td>\n",
       "      <td>0.9152</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>$0.9131 \\pm 0.011$</td>\n",
       "      <td>$10.1257 \\pm 0.619$</td>\n",
       "      <td>$0.9152 \\pm 0.007$</td>\n",
       "      <td>$10.0101 \\pm 0.408$</td>\n",
       "      <td>$0.9152 \\pm 0.007$</td>\n",
       "      <td>$10.0101 \\pm 0.408$</td>\n",
       "      <td>$0.9146 \\pm 0.008$</td>\n",
       "      <td>$10.0459 \\pm 0.458$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361089</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.1337</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.8577</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8573</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.1339</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8587</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.1332</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.1349</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>0.8550</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>$0.8573 \\pm 0.006$</td>\n",
       "      <td>$0.1339 \\pm 0.003$</td>\n",
       "      <td>$0.8587 \\pm 0.002$</td>\n",
       "      <td>$0.1332 \\pm 0.002$</td>\n",
       "      <td>$0.855 \\pm 0.008$</td>\n",
       "      <td>$0.1349 \\pm 0.004$</td>\n",
       "      <td>$0.8577 \\pm 0.003$</td>\n",
       "      <td>$0.1337 \\pm 0.002$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361090</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.7748</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.6732</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.6867</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.7587</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.6848</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.7609</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.7620</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.6840</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>$0.6867 \\pm 0.003$</td>\n",
       "      <td>$0.7587 \\pm 0.004$</td>\n",
       "      <td>$0.6848 \\pm 0.003$</td>\n",
       "      <td>$0.7609 \\pm 0.003$</td>\n",
       "      <td>$0.684 \\pm 0.003$</td>\n",
       "      <td>$0.762 \\pm 0.004$</td>\n",
       "      <td>$0.6732 \\pm 0.009$</td>\n",
       "      <td>$0.7748 \\pm 0.011$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">42570</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>9.2623</td>\n",
       "      <td>0.4517</td>\n",
       "      <td>0.5036</td>\n",
       "      <td>0.0271</td>\n",
       "      <td>0.4892</td>\n",
       "      <td>0.0284</td>\n",
       "      <td>9.2177</td>\n",
       "      <td>0.6197</td>\n",
       "      <td>0.4932</td>\n",
       "      <td>0.0183</td>\n",
       "      <td>9.1607</td>\n",
       "      <td>0.6238</td>\n",
       "      <td>9.1545</td>\n",
       "      <td>0.6119</td>\n",
       "      <td>0.4961</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>$0.4892 \\pm 0.028$</td>\n",
       "      <td>$9.2177 \\pm 0.62$</td>\n",
       "      <td>$0.4932 \\pm 0.018$</td>\n",
       "      <td>$9.1607 \\pm 0.624$</td>\n",
       "      <td>$0.4961 \\pm 0.014$</td>\n",
       "      <td>$9.1545 \\pm 0.612$</td>\n",
       "      <td>$0.5036 \\pm 0.027$</td>\n",
       "      <td>$9.2623 \\pm 0.452$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                RMSE_0            R2_0           R2_10  \\\n",
       "                                  mean     std    mean     std    mean   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     2.2854  0.1005  0.9845  0.0022  0.9857   \n",
       "        Random   Metric         2.2550  0.0544  0.9849  0.0016  0.9849   \n",
       "361073  PDF      PDF Energy     7.7879  7.2807  0.9385  0.1029  0.9884   \n",
       "        Random   Metric         4.5010  0.4271  0.9884  0.0023  0.9884   \n",
       "361078  PDF      PDF Energy     0.2200  0.0066  0.8506  0.0080  0.8519   \n",
       "        Random   Metric         0.2194  0.0061  0.8515  0.0076  0.8515   \n",
       "361080  PDF      PDF Energy     0.2366  0.0026  0.9455  0.0012  0.9460   \n",
       "        Random   Metric         0.2456  0.0070  0.9414  0.0034  0.9414   \n",
       "361081  PDF      PDF Energy     0.0683  0.0323  0.9912  0.0073  0.9865   \n",
       "        Random   Metric         0.0802  0.0421  0.9874  0.0112  0.9874   \n",
       "361082  PDF      PDF Energy   104.0375  3.8006  0.6699  0.0219  0.6629   \n",
       "        Random   Metric       107.2763  3.3160  0.6488  0.0243  0.6488   \n",
       "361083  PDF      PDF Energy     0.3382  0.0011  0.6784  0.0019  0.6784   \n",
       "        Random   Metric         0.3382  0.0011  0.6784  0.0019  0.6784   \n",
       "361085  PDF      PDF Energy     0.0318  0.0182  0.6418  0.3069  0.4778   \n",
       "        Random   Metric         0.0207  0.0055  0.8653  0.0477  0.8653   \n",
       "361086  PDF      PDF Energy     0.0845  0.0027  0.9777  0.0014  0.9792   \n",
       "        Random   Metric         0.0858  0.0026  0.9770  0.0014  0.9770   \n",
       "361087  PDF      PDF Energy     0.1522  0.0058  0.9289  0.0054  0.9338   \n",
       "        Random   Metric         0.1459  0.0029  0.9347  0.0026  0.9347   \n",
       "361088  PDF      PDF Energy    10.0459  0.4581  0.9146  0.0082  0.9131   \n",
       "        Random   Metric        10.1630  0.5871  0.9125  0.0106  0.9125   \n",
       "361089  PDF      PDF Energy     0.1337  0.0022  0.8577  0.0034  0.8573   \n",
       "        Random   Metric         0.1341  0.0031  0.8568  0.0064  0.8568   \n",
       "361090  PDF      PDF Energy     0.7748  0.0105  0.6732  0.0090  0.6867   \n",
       "        Random   Metric         0.7812  0.0246  0.6675  0.0211  0.6675   \n",
       "42570   PDF      PDF Energy     9.2623  0.4517  0.5036  0.0271  0.4892   \n",
       "        Random   Metric         9.2906  0.5454  0.4901  0.0237  0.4901   \n",
       "\n",
       "                                       RMSE_10          R2_100          \\\n",
       "                                 std      mean     std    mean     std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   0.0020    2.1904  0.0741  0.9839  0.0031   \n",
       "        Random   Metric       0.0016    2.2550  0.0544  0.9849  0.0016   \n",
       "361073  PDF      PDF Energy   0.0013    4.5010  0.2484  0.9720  0.0020   \n",
       "        Random   Metric       0.0023    4.5010  0.4271  0.9884  0.0023   \n",
       "361078  PDF      PDF Energy   0.0057    0.2191  0.0048  0.8532  0.0059   \n",
       "        Random   Metric       0.0076    0.2194  0.0061  0.8515  0.0076   \n",
       "361080  PDF      PDF Energy   0.0010    0.2355  0.0026  0.9457  0.0019   \n",
       "        Random   Metric       0.0034    0.2456  0.0070  0.9414  0.0034   \n",
       "361081  PDF      PDF Energy   0.0100    0.0840  0.0412  0.9859  0.0119   \n",
       "        Random   Metric       0.0112    0.0802  0.0421  0.9874  0.0112   \n",
       "361082  PDF      PDF Energy   0.0208  105.1333  3.3429  0.6759  0.0224   \n",
       "        Random   Metric       0.0243  107.2763  3.3160  0.6488  0.0243   \n",
       "361083  PDF      PDF Energy   0.0019    0.3382  0.0011  0.6483  0.0903   \n",
       "        Random   Metric       0.0019    0.3382  0.0011  0.6784  0.0019   \n",
       "361085  PDF      PDF Energy   0.2293    0.0394  0.0120  0.8837  0.0345   \n",
       "        Random   Metric       0.0477    0.0207  0.0055  0.8653  0.0477   \n",
       "361086  PDF      PDF Energy   0.0004    0.0817  0.0006  0.9789  0.0011   \n",
       "        Random   Metric       0.0014    0.0858  0.0026  0.9770  0.0014   \n",
       "361087  PDF      PDF Energy   0.0055    0.1468  0.0054  0.9354  0.0017   \n",
       "        Random   Metric       0.0026    0.1459  0.0029  0.9347  0.0026   \n",
       "361088  PDF      PDF Energy   0.0111   10.1257  0.6189  0.9152  0.0074   \n",
       "        Random   Metric       0.0106   10.1630  0.5871  0.9125  0.0106   \n",
       "361089  PDF      PDF Energy   0.0059    0.1339  0.0034  0.8587  0.0024   \n",
       "        Random   Metric       0.0064    0.1341  0.0031  0.8568  0.0064   \n",
       "361090  PDF      PDF Energy   0.0031    0.7587  0.0037  0.6848  0.0028   \n",
       "        Random   Metric       0.0211    0.7812  0.0246  0.6675  0.0211   \n",
       "42570   PDF      PDF Energy   0.0284    9.2177  0.6197  0.4932  0.0183   \n",
       "        Random   Metric       0.0237    9.2906  0.5454  0.4901  0.0237   \n",
       "\n",
       "                              RMSE_100         RMSE_1000         R2_1000  \\\n",
       "                                  mean     std      mean     std    mean   \n",
       "Dataset Sampling Eval_Method                                               \n",
       "361072  PDF      PDF Energy     2.3204  0.1363    2.2556  0.1334  0.9848   \n",
       "        Random   Metric         2.2550  0.0544    2.2550  0.0544  0.9849   \n",
       "361073  PDF      PDF Energy     7.0065  0.2425    6.9917  0.2616  0.9721   \n",
       "        Random   Metric         4.5010  0.4271    4.5010  0.4271  0.9884   \n",
       "361078  PDF      PDF Energy     0.2181  0.0050    0.2181  0.0050  0.8533   \n",
       "        Random   Metric         0.2194  0.0061    0.2194  0.0061  0.8515   \n",
       "361080  PDF      PDF Energy     0.2363  0.0029    0.2377  0.0031  0.9450   \n",
       "        Random   Metric         0.2456  0.0070    0.2456  0.0070  0.9414   \n",
       "361081  PDF      PDF Energy     0.0857  0.0425    0.0826  0.0379  0.9872   \n",
       "        Random   Metric         0.0802  0.0421    0.0802  0.0421  0.9874   \n",
       "361082  PDF      PDF Energy   103.0747  3.5670  104.6016  3.1629  0.6662   \n",
       "        Random   Metric       107.2763  3.3160  107.2763  3.3160  0.6488   \n",
       "361083  PDF      PDF Energy     0.3516  0.0398    0.3382  0.0011  0.6784   \n",
       "        Random   Metric         0.3382  0.0011    0.3382  0.0011  0.6784   \n",
       "361085  PDF      PDF Energy     0.0193  0.0048    0.0193  0.0048  0.8837   \n",
       "        Random   Metric         0.0207  0.0055    0.0207  0.0055  0.8653   \n",
       "361086  PDF      PDF Energy     0.0822  0.0019    0.0823  0.0016  0.9789   \n",
       "        Random   Metric         0.0858  0.0026    0.0858  0.0026  0.9770   \n",
       "361087  PDF      PDF Energy     0.1451  0.0021    0.1463  0.0033  0.9344   \n",
       "        Random   Metric         0.1459  0.0029    0.1459  0.0029  0.9347   \n",
       "361088  PDF      PDF Energy    10.0101  0.4078   10.0101  0.4078  0.9152   \n",
       "        Random   Metric        10.1630  0.5871   10.1630  0.5871  0.9125   \n",
       "361089  PDF      PDF Energy     0.1332  0.0019    0.1349  0.0041  0.8550   \n",
       "        Random   Metric         0.1341  0.0031    0.1341  0.0031  0.8568   \n",
       "361090  PDF      PDF Energy     0.7609  0.0032    0.7620  0.0036  0.6840   \n",
       "        Random   Metric         0.7812  0.0246    0.7812  0.0246  0.6675   \n",
       "42570   PDF      PDF Energy     9.1607  0.6238    9.1545  0.6119  0.4961   \n",
       "        Random   Metric         9.2906  0.5454    9.2906  0.5454  0.4901   \n",
       "\n",
       "                                                  _R2_10  \\\n",
       "                                 std                       \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy   0.0029  $0.9857 \\pm 0.002$   \n",
       "        Random   Metric       0.0016  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy   0.0022  $0.9884 \\pm 0.001$   \n",
       "        Random   Metric       0.0023  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy   0.0061  $0.8519 \\pm 0.006$   \n",
       "        Random   Metric       0.0076  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy   0.0017   $0.946 \\pm 0.001$   \n",
       "        Random   Metric       0.0034  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy   0.0096   $0.9865 \\pm 0.01$   \n",
       "        Random   Metric       0.0112  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   0.0226  $0.6629 \\pm 0.021$   \n",
       "        Random   Metric       0.0243  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   0.0019  $0.6784 \\pm 0.002$   \n",
       "        Random   Metric       0.0019  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy   0.0345  $0.4778 \\pm 0.229$   \n",
       "        Random   Metric       0.0477  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy   0.0008    $0.9792 \\pm 0.0$   \n",
       "        Random   Metric       0.0014   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy   0.0027  $0.9338 \\pm 0.005$   \n",
       "        Random   Metric       0.0026  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   0.0074  $0.9131 \\pm 0.011$   \n",
       "        Random   Metric       0.0106  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   0.0085  $0.8573 \\pm 0.006$   \n",
       "        Random   Metric       0.0064  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   0.0032  $0.6867 \\pm 0.003$   \n",
       "        Random   Metric       0.0211  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   0.0140  $0.4892 \\pm 0.028$   \n",
       "        Random   Metric       0.0237  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                          _RMSE_10             _R2_100  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     $2.1904 \\pm 0.074$  $0.9839 \\pm 0.003$   \n",
       "        Random   Metric          $2.255 \\pm 0.054$  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy      $4.501 \\pm 0.248$   $0.972 \\pm 0.002$   \n",
       "        Random   Metric          $4.501 \\pm 0.427$  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy     $0.2191 \\pm 0.005$  $0.8532 \\pm 0.006$   \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy     $0.2355 \\pm 0.003$  $0.9457 \\pm 0.002$   \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy      $0.084 \\pm 0.041$  $0.9859 \\pm 0.012$   \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   $105.1333 \\pm 3.343$  $0.6759 \\pm 0.022$   \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy     $0.3382 \\pm 0.001$   $0.6483 \\pm 0.09$   \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy     $0.0394 \\pm 0.012$  $0.8837 \\pm 0.035$   \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy     $0.0817 \\pm 0.001$  $0.9789 \\pm 0.001$   \n",
       "        Random   Metric         $0.0858 \\pm 0.003$   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy     $0.1468 \\pm 0.005$  $0.9354 \\pm 0.002$   \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    $10.1257 \\pm 0.619$  $0.9152 \\pm 0.007$   \n",
       "        Random   Metric         $10.163 \\pm 0.587$  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy     $0.1339 \\pm 0.003$  $0.8587 \\pm 0.002$   \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy     $0.7587 \\pm 0.004$  $0.6848 \\pm 0.003$   \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy      $9.2177 \\pm 0.62$  $0.4932 \\pm 0.018$   \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                         _RMSE_100            _R2_1000  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     $2.3204 \\pm 0.136$  $0.9848 \\pm 0.003$   \n",
       "        Random   Metric          $2.255 \\pm 0.054$  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy     $7.0065 \\pm 0.243$  $0.9721 \\pm 0.002$   \n",
       "        Random   Metric          $4.501 \\pm 0.427$  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy     $0.2181 \\pm 0.005$  $0.8533 \\pm 0.006$   \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy     $0.2363 \\pm 0.003$   $0.945 \\pm 0.002$   \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy     $0.0857 \\pm 0.042$   $0.9872 \\pm 0.01$   \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   $103.0747 \\pm 3.567$  $0.6662 \\pm 0.023$   \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy      $0.3516 \\pm 0.04$  $0.6784 \\pm 0.002$   \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy     $0.0193 \\pm 0.005$  $0.8837 \\pm 0.035$   \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy     $0.0822 \\pm 0.002$  $0.9789 \\pm 0.001$   \n",
       "        Random   Metric         $0.0858 \\pm 0.003$   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy     $0.1451 \\pm 0.002$  $0.9344 \\pm 0.003$   \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    $10.0101 \\pm 0.408$  $0.9152 \\pm 0.007$   \n",
       "        Random   Metric         $10.163 \\pm 0.587$  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy     $0.1332 \\pm 0.002$   $0.855 \\pm 0.008$   \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy     $0.7609 \\pm 0.003$   $0.684 \\pm 0.003$   \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy     $9.1607 \\pm 0.624$  $0.4961 \\pm 0.014$   \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                        _RMSE_1000               _R2_0  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     $2.2556 \\pm 0.133$  $0.9845 \\pm 0.002$   \n",
       "        Random   Metric          $2.255 \\pm 0.054$  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy     $6.9917 \\pm 0.262$  $0.9385 \\pm 0.103$   \n",
       "        Random   Metric          $4.501 \\pm 0.427$  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy     $0.2181 \\pm 0.005$  $0.8506 \\pm 0.008$   \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy     $0.2377 \\pm 0.003$  $0.9455 \\pm 0.001$   \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy     $0.0826 \\pm 0.038$  $0.9912 \\pm 0.007$   \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   $104.6016 \\pm 3.163$  $0.6699 \\pm 0.022$   \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy     $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy     $0.0193 \\pm 0.005$  $0.6418 \\pm 0.307$   \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy     $0.0823 \\pm 0.002$  $0.9777 \\pm 0.001$   \n",
       "        Random   Metric         $0.0858 \\pm 0.003$   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy     $0.1463 \\pm 0.003$  $0.9289 \\pm 0.005$   \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    $10.0101 \\pm 0.408$  $0.9146 \\pm 0.008$   \n",
       "        Random   Metric         $10.163 \\pm 0.587$  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy     $0.1349 \\pm 0.004$  $0.8577 \\pm 0.003$   \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy      $0.762 \\pm 0.004$  $0.6732 \\pm 0.009$   \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy     $9.1545 \\pm 0.612$  $0.5036 \\pm 0.027$   \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                           _RMSE_0  \n",
       "                                                    \n",
       "Dataset Sampling Eval_Method                        \n",
       "361072  PDF      PDF Energy       $2.2854 \\pm 0.1$  \n",
       "        Random   Metric          $2.255 \\pm 0.054$  \n",
       "361073  PDF      PDF Energy     $7.7879 \\pm 7.281$  \n",
       "        Random   Metric          $4.501 \\pm 0.427$  \n",
       "361078  PDF      PDF Energy       $0.22 \\pm 0.007$  \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  \n",
       "361080  PDF      PDF Energy     $0.2366 \\pm 0.003$  \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  \n",
       "361081  PDF      PDF Energy     $0.0683 \\pm 0.032$  \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  \n",
       "361082  PDF      PDF Energy   $104.0375 \\pm 3.801$  \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  \n",
       "361083  PDF      PDF Energy     $0.3382 \\pm 0.001$  \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  \n",
       "361085  PDF      PDF Energy     $0.0318 \\pm 0.018$  \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  \n",
       "361086  PDF      PDF Energy     $0.0845 \\pm 0.003$  \n",
       "        Random   Metric         $0.0858 \\pm 0.003$  \n",
       "361087  PDF      PDF Energy     $0.1522 \\pm 0.006$  \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  \n",
       "361088  PDF      PDF Energy    $10.0459 \\pm 0.458$  \n",
       "        Random   Metric         $10.163 \\pm 0.587$  \n",
       "361089  PDF      PDF Energy     $0.1337 \\pm 0.002$  \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  \n",
       "361090  PDF      PDF Energy     $0.7748 \\pm 0.011$  \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  \n",
       "42570   PDF      PDF Energy     $9.2623 \\pm 0.452$  \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  "
      ]
     },
     "execution_count": 867,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 868,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PDF:8,Random:4, Equal:2\n",
      "PDF:9,Random:3, Equal:2\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "((8, 4, 2), (9, 3, 2))"
      ]
     },
     "execution_count": 868,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_bin_eval(dx,'R2_10','r2'), get_bin_eval(dx,'RMSE_10','rmse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 869,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PDF:10,Random:4, Equal:0\n",
      "PDF:10,Random:4, Equal:0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "((10, 4, 0), (10, 4, 0))"
      ]
     },
     "execution_count": 869,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_bin_eval(dx,'R2_100','r2'), get_bin_eval(dx,'RMSE_100','rmse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 870,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PDF:8,Random:5, Equal:1\n",
      "PDF:8,Random:5, Equal:1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "((8, 5, 1), (8, 5, 1))"
      ]
     },
     "execution_count": 870,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_bin_eval(dx,'R2_1000','r2'), get_bin_eval(dx,'RMSE_1000','rmse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 871,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PDF:8,Random:5, Equal:1\n",
      "PDF:8,Random:5, Equal:1\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "((8, 5, 1), (8, 5, 1))"
      ]
     },
     "execution_count": 871,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_bin_eval(dx,'R2_0','r2'), get_bin_eval(dx,'RMSE_0','rmse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 872,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PDF:8,Random:5, Equal:1\n",
      "RMSE_0 (8, 5, 1)\n",
      "PDF:9,Random:3, Equal:2\n",
      "RMSE_10 (9, 3, 2)\n",
      "PDF:10,Random:4, Equal:0\n",
      "RMSE_100 (10, 4, 0)\n",
      "PDF:8,Random:5, Equal:1\n",
      "RMSE_1000 (8, 5, 1)\n"
     ]
    }
   ],
   "source": [
    "for col in ['RMSE_0','RMSE_10','RMSE_100','RMSE_1000']:\n",
    "    print(col, get_bin_eval(dx,col,'rmse'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 873,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmse_col=[0,6,10,12]      \n",
    "r2_col=[2,4,8,14]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 874,
   "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",
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       "\n",
       "    .dataframe thead tr th {\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_1000</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_1000</th>\n",
       "      <th>_R2_10</th>\n",
       "      <th>_RMSE_10</th>\n",
       "      <th>_R2_100</th>\n",
       "      <th>_RMSE_100</th>\n",
       "      <th>_R2_1000</th>\n",
       "      <th>_RMSE_1000</th>\n",
       "      <th>_R2_0</th>\n",
       "      <th>_RMSE_0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dataset</th>\n",
       "      <th>Sampling</th>\n",
       "      <th>Eval_Method</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361072</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>2.2854</td>\n",
       "      <td>0.1005</td>\n",
       "      <td>0.9845</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.9857</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>2.1904</td>\n",
       "      <td>0.0741</td>\n",
       "      <td>0.9839</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>2.3204</td>\n",
       "      <td>0.1363</td>\n",
       "      <td>2.2556</td>\n",
       "      <td>0.1334</td>\n",
       "      <td>0.9848</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>$0.9857 \\pm 0.002$</td>\n",
       "      <td>$2.1904 \\pm 0.074$</td>\n",
       "      <td>$0.9839 \\pm 0.003$</td>\n",
       "      <td>$2.3204 \\pm 0.136$</td>\n",
       "      <td>$0.9848 \\pm 0.003$</td>\n",
       "      <td>$2.2556 \\pm 0.133$</td>\n",
       "      <td>$0.9845 \\pm 0.002$</td>\n",
       "      <td>$2.2854 \\pm 0.1$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>2.2550</td>\n",
       "      <td>0.0544</td>\n",
       "      <td>0.9849</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "      <td>$0.9849 \\pm 0.002$</td>\n",
       "      <td>$2.255 \\pm 0.054$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361073</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>7.7879</td>\n",
       "      <td>7.2807</td>\n",
       "      <td>0.9385</td>\n",
       "      <td>0.1029</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.2484</td>\n",
       "      <td>0.9720</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>7.0065</td>\n",
       "      <td>0.2425</td>\n",
       "      <td>6.9917</td>\n",
       "      <td>0.2616</td>\n",
       "      <td>0.9721</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>$0.9884 \\pm 0.001$</td>\n",
       "      <td>$4.501 \\pm 0.248$</td>\n",
       "      <td>$0.972 \\pm 0.002$</td>\n",
       "      <td>$7.0065 \\pm 0.243$</td>\n",
       "      <td>$0.9721 \\pm 0.002$</td>\n",
       "      <td>$6.9917 \\pm 0.262$</td>\n",
       "      <td>$0.9385 \\pm 0.103$</td>\n",
       "      <td>$7.7879 \\pm 7.281$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>4.5010</td>\n",
       "      <td>0.4271</td>\n",
       "      <td>0.9884</td>\n",
       "      <td>0.0023</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "      <td>$0.9884 \\pm 0.002$</td>\n",
       "      <td>$4.501 \\pm 0.427$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361078</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.2200</td>\n",
       "      <td>0.0066</td>\n",
       "      <td>0.8506</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>0.8519</td>\n",
       "      <td>0.0057</td>\n",
       "      <td>0.2191</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.8532</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.2181</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.2181</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.8533</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>$0.8519 \\pm 0.006$</td>\n",
       "      <td>$0.2191 \\pm 0.005$</td>\n",
       "      <td>$0.8532 \\pm 0.006$</td>\n",
       "      <td>$0.2181 \\pm 0.005$</td>\n",
       "      <td>$0.8533 \\pm 0.006$</td>\n",
       "      <td>$0.2181 \\pm 0.005$</td>\n",
       "      <td>$0.8506 \\pm 0.008$</td>\n",
       "      <td>$0.22 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.2194</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.8515</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "      <td>$0.8515 \\pm 0.008$</td>\n",
       "      <td>$0.2194 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361080</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.2366</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9455</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>0.9460</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>0.2355</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9457</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.2363</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.2377</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.9450</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>$0.946 \\pm 0.001$</td>\n",
       "      <td>$0.2355 \\pm 0.003$</td>\n",
       "      <td>$0.9457 \\pm 0.002$</td>\n",
       "      <td>$0.2363 \\pm 0.003$</td>\n",
       "      <td>$0.945 \\pm 0.002$</td>\n",
       "      <td>$0.2377 \\pm 0.003$</td>\n",
       "      <td>$0.9455 \\pm 0.001$</td>\n",
       "      <td>$0.2366 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.2456</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.9414</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "      <td>$0.9414 \\pm 0.003$</td>\n",
       "      <td>$0.2456 \\pm 0.007$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361081</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0683</td>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.9912</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.9865</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0840</td>\n",
       "      <td>0.0412</td>\n",
       "      <td>0.9859</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>0.0857</td>\n",
       "      <td>0.0425</td>\n",
       "      <td>0.0826</td>\n",
       "      <td>0.0379</td>\n",
       "      <td>0.9872</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>$0.9865 \\pm 0.01$</td>\n",
       "      <td>$0.084 \\pm 0.041$</td>\n",
       "      <td>$0.9859 \\pm 0.012$</td>\n",
       "      <td>$0.0857 \\pm 0.042$</td>\n",
       "      <td>$0.9872 \\pm 0.01$</td>\n",
       "      <td>$0.0826 \\pm 0.038$</td>\n",
       "      <td>$0.9912 \\pm 0.007$</td>\n",
       "      <td>$0.0683 \\pm 0.032$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.0802</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.9874</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "      <td>$0.9874 \\pm 0.011$</td>\n",
       "      <td>$0.0802 \\pm 0.042$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361082</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>104.0375</td>\n",
       "      <td>3.8006</td>\n",
       "      <td>0.6699</td>\n",
       "      <td>0.0219</td>\n",
       "      <td>0.6629</td>\n",
       "      <td>0.0208</td>\n",
       "      <td>105.1333</td>\n",
       "      <td>3.3429</td>\n",
       "      <td>0.6759</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>103.0747</td>\n",
       "      <td>3.5670</td>\n",
       "      <td>104.6016</td>\n",
       "      <td>3.1629</td>\n",
       "      <td>0.6662</td>\n",
       "      <td>0.0226</td>\n",
       "      <td>$0.6629 \\pm 0.021$</td>\n",
       "      <td>$105.1333 \\pm 3.343$</td>\n",
       "      <td>$0.6759 \\pm 0.022$</td>\n",
       "      <td>$103.0747 \\pm 3.567$</td>\n",
       "      <td>$0.6662 \\pm 0.023$</td>\n",
       "      <td>$104.6016 \\pm 3.163$</td>\n",
       "      <td>$0.6699 \\pm 0.022$</td>\n",
       "      <td>$104.0375 \\pm 3.801$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>107.2763</td>\n",
       "      <td>3.3160</td>\n",
       "      <td>0.6488</td>\n",
       "      <td>0.0243</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "      <td>$0.6488 \\pm 0.024$</td>\n",
       "      <td>$107.2763 \\pm 3.316$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361083</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6483</td>\n",
       "      <td>0.0903</td>\n",
       "      <td>0.3516</td>\n",
       "      <td>0.0398</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6483 \\pm 0.09$</td>\n",
       "      <td>$0.3516 \\pm 0.04$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.3382</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.6784</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "      <td>$0.6784 \\pm 0.002$</td>\n",
       "      <td>$0.3382 \\pm 0.001$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361085</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.0182</td>\n",
       "      <td>0.6418</td>\n",
       "      <td>0.3069</td>\n",
       "      <td>0.4778</td>\n",
       "      <td>0.2293</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0120</td>\n",
       "      <td>0.8837</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.8837</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>$0.4778 \\pm 0.229$</td>\n",
       "      <td>$0.0394 \\pm 0.012$</td>\n",
       "      <td>$0.8837 \\pm 0.035$</td>\n",
       "      <td>$0.0193 \\pm 0.005$</td>\n",
       "      <td>$0.8837 \\pm 0.035$</td>\n",
       "      <td>$0.0193 \\pm 0.005$</td>\n",
       "      <td>$0.6418 \\pm 0.307$</td>\n",
       "      <td>$0.0318 \\pm 0.018$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.8653</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "      <td>$0.8653 \\pm 0.048$</td>\n",
       "      <td>$0.0207 \\pm 0.005$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361086</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.0845</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.9777</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.9792</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0817</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.0822</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.0823</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>$0.9792 \\pm 0.0$</td>\n",
       "      <td>$0.0817 \\pm 0.001$</td>\n",
       "      <td>$0.9789 \\pm 0.001$</td>\n",
       "      <td>$0.0822 \\pm 0.002$</td>\n",
       "      <td>$0.9789 \\pm 0.001$</td>\n",
       "      <td>$0.0823 \\pm 0.002$</td>\n",
       "      <td>$0.9777 \\pm 0.001$</td>\n",
       "      <td>$0.0845 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "      <td>$0.977 \\pm 0.001$</td>\n",
       "      <td>$0.0858 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361087</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.1522</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>0.9289</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.9338</td>\n",
       "      <td>0.0055</td>\n",
       "      <td>0.1468</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.9354</td>\n",
       "      <td>0.0017</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.1463</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0.9344</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>$0.9338 \\pm 0.005$</td>\n",
       "      <td>$0.1468 \\pm 0.005$</td>\n",
       "      <td>$0.9354 \\pm 0.002$</td>\n",
       "      <td>$0.1451 \\pm 0.002$</td>\n",
       "      <td>$0.9344 \\pm 0.003$</td>\n",
       "      <td>$0.1463 \\pm 0.003$</td>\n",
       "      <td>$0.9289 \\pm 0.005$</td>\n",
       "      <td>$0.1522 \\pm 0.006$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.1459</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.9347</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "      <td>$0.9347 \\pm 0.003$</td>\n",
       "      <td>$0.1459 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361088</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>10.0459</td>\n",
       "      <td>0.4581</td>\n",
       "      <td>0.9146</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>0.9131</td>\n",
       "      <td>0.0111</td>\n",
       "      <td>10.1257</td>\n",
       "      <td>0.6189</td>\n",
       "      <td>0.9152</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>10.0101</td>\n",
       "      <td>0.4078</td>\n",
       "      <td>10.0101</td>\n",
       "      <td>0.4078</td>\n",
       "      <td>0.9152</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>$0.9131 \\pm 0.011$</td>\n",
       "      <td>$10.1257 \\pm 0.619$</td>\n",
       "      <td>$0.9152 \\pm 0.007$</td>\n",
       "      <td>$10.0101 \\pm 0.408$</td>\n",
       "      <td>$0.9152 \\pm 0.007$</td>\n",
       "      <td>$10.0101 \\pm 0.408$</td>\n",
       "      <td>$0.9146 \\pm 0.008$</td>\n",
       "      <td>$10.0459 \\pm 0.458$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>10.1630</td>\n",
       "      <td>0.5871</td>\n",
       "      <td>0.9125</td>\n",
       "      <td>0.0106</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "      <td>$0.9125 \\pm 0.011$</td>\n",
       "      <td>$10.163 \\pm 0.587$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361089</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.1337</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.8577</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8573</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>0.1339</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8587</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>0.1332</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>0.1349</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>0.8550</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>$0.8573 \\pm 0.006$</td>\n",
       "      <td>$0.1339 \\pm 0.003$</td>\n",
       "      <td>$0.8587 \\pm 0.002$</td>\n",
       "      <td>$0.1332 \\pm 0.002$</td>\n",
       "      <td>$0.855 \\pm 0.008$</td>\n",
       "      <td>$0.1349 \\pm 0.004$</td>\n",
       "      <td>$0.8577 \\pm 0.003$</td>\n",
       "      <td>$0.1337 \\pm 0.002$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.1341</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.8568</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "      <td>$0.8568 \\pm 0.006$</td>\n",
       "      <td>$0.1341 \\pm 0.003$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">361090</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>0.7748</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.6732</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.6867</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.7587</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.6848</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.7609</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.7620</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.6840</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>$0.6867 \\pm 0.003$</td>\n",
       "      <td>$0.7587 \\pm 0.004$</td>\n",
       "      <td>$0.6848 \\pm 0.003$</td>\n",
       "      <td>$0.7609 \\pm 0.003$</td>\n",
       "      <td>$0.684 \\pm 0.003$</td>\n",
       "      <td>$0.762 \\pm 0.004$</td>\n",
       "      <td>$0.6732 \\pm 0.009$</td>\n",
       "      <td>$0.7748 \\pm 0.011$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.7812</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>0.6675</td>\n",
       "      <td>0.0211</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "      <td>$0.6675 \\pm 0.021$</td>\n",
       "      <td>$0.7812 \\pm 0.025$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">42570</th>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>9.2623</td>\n",
       "      <td>0.4517</td>\n",
       "      <td>0.5036</td>\n",
       "      <td>0.0271</td>\n",
       "      <td>0.4892</td>\n",
       "      <td>0.0284</td>\n",
       "      <td>9.2177</td>\n",
       "      <td>0.6197</td>\n",
       "      <td>0.4932</td>\n",
       "      <td>0.0183</td>\n",
       "      <td>9.1607</td>\n",
       "      <td>0.6238</td>\n",
       "      <td>9.1545</td>\n",
       "      <td>0.6119</td>\n",
       "      <td>0.4961</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>$0.4892 \\pm 0.028$</td>\n",
       "      <td>$9.2177 \\pm 0.62$</td>\n",
       "      <td>$0.4932 \\pm 0.018$</td>\n",
       "      <td>$9.1607 \\pm 0.624$</td>\n",
       "      <td>$0.4961 \\pm 0.014$</td>\n",
       "      <td>$9.1545 \\pm 0.612$</td>\n",
       "      <td>$0.5036 \\pm 0.027$</td>\n",
       "      <td>$9.2623 \\pm 0.452$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>9.2906</td>\n",
       "      <td>0.5454</td>\n",
       "      <td>0.4901</td>\n",
       "      <td>0.0237</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "      <td>$0.4901 \\pm 0.024$</td>\n",
       "      <td>$9.2906 \\pm 0.545$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                RMSE_0            R2_0           R2_10  \\\n",
       "                                  mean     std    mean     std    mean   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     2.2854  0.1005  0.9845  0.0022  0.9857   \n",
       "        Random   Metric         2.2550  0.0544  0.9849  0.0016  0.9849   \n",
       "361073  PDF      PDF Energy     7.7879  7.2807  0.9385  0.1029  0.9884   \n",
       "        Random   Metric         4.5010  0.4271  0.9884  0.0023  0.9884   \n",
       "361078  PDF      PDF Energy     0.2200  0.0066  0.8506  0.0080  0.8519   \n",
       "        Random   Metric         0.2194  0.0061  0.8515  0.0076  0.8515   \n",
       "361080  PDF      PDF Energy     0.2366  0.0026  0.9455  0.0012  0.9460   \n",
       "        Random   Metric         0.2456  0.0070  0.9414  0.0034  0.9414   \n",
       "361081  PDF      PDF Energy     0.0683  0.0323  0.9912  0.0073  0.9865   \n",
       "        Random   Metric         0.0802  0.0421  0.9874  0.0112  0.9874   \n",
       "361082  PDF      PDF Energy   104.0375  3.8006  0.6699  0.0219  0.6629   \n",
       "        Random   Metric       107.2763  3.3160  0.6488  0.0243  0.6488   \n",
       "361083  PDF      PDF Energy     0.3382  0.0011  0.6784  0.0019  0.6784   \n",
       "        Random   Metric         0.3382  0.0011  0.6784  0.0019  0.6784   \n",
       "361085  PDF      PDF Energy     0.0318  0.0182  0.6418  0.3069  0.4778   \n",
       "        Random   Metric         0.0207  0.0055  0.8653  0.0477  0.8653   \n",
       "361086  PDF      PDF Energy     0.0845  0.0027  0.9777  0.0014  0.9792   \n",
       "        Random   Metric         0.0858  0.0026  0.9770  0.0014  0.9770   \n",
       "361087  PDF      PDF Energy     0.1522  0.0058  0.9289  0.0054  0.9338   \n",
       "        Random   Metric         0.1459  0.0029  0.9347  0.0026  0.9347   \n",
       "361088  PDF      PDF Energy    10.0459  0.4581  0.9146  0.0082  0.9131   \n",
       "        Random   Metric        10.1630  0.5871  0.9125  0.0106  0.9125   \n",
       "361089  PDF      PDF Energy     0.1337  0.0022  0.8577  0.0034  0.8573   \n",
       "        Random   Metric         0.1341  0.0031  0.8568  0.0064  0.8568   \n",
       "361090  PDF      PDF Energy     0.7748  0.0105  0.6732  0.0090  0.6867   \n",
       "        Random   Metric         0.7812  0.0246  0.6675  0.0211  0.6675   \n",
       "42570   PDF      PDF Energy     9.2623  0.4517  0.5036  0.0271  0.4892   \n",
       "        Random   Metric         9.2906  0.5454  0.4901  0.0237  0.4901   \n",
       "\n",
       "                                       RMSE_10          R2_100          \\\n",
       "                                 std      mean     std    mean     std   \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy   0.0020    2.1904  0.0741  0.9839  0.0031   \n",
       "        Random   Metric       0.0016    2.2550  0.0544  0.9849  0.0016   \n",
       "361073  PDF      PDF Energy   0.0013    4.5010  0.2484  0.9720  0.0020   \n",
       "        Random   Metric       0.0023    4.5010  0.4271  0.9884  0.0023   \n",
       "361078  PDF      PDF Energy   0.0057    0.2191  0.0048  0.8532  0.0059   \n",
       "        Random   Metric       0.0076    0.2194  0.0061  0.8515  0.0076   \n",
       "361080  PDF      PDF Energy   0.0010    0.2355  0.0026  0.9457  0.0019   \n",
       "        Random   Metric       0.0034    0.2456  0.0070  0.9414  0.0034   \n",
       "361081  PDF      PDF Energy   0.0100    0.0840  0.0412  0.9859  0.0119   \n",
       "        Random   Metric       0.0112    0.0802  0.0421  0.9874  0.0112   \n",
       "361082  PDF      PDF Energy   0.0208  105.1333  3.3429  0.6759  0.0224   \n",
       "        Random   Metric       0.0243  107.2763  3.3160  0.6488  0.0243   \n",
       "361083  PDF      PDF Energy   0.0019    0.3382  0.0011  0.6483  0.0903   \n",
       "        Random   Metric       0.0019    0.3382  0.0011  0.6784  0.0019   \n",
       "361085  PDF      PDF Energy   0.2293    0.0394  0.0120  0.8837  0.0345   \n",
       "        Random   Metric       0.0477    0.0207  0.0055  0.8653  0.0477   \n",
       "361086  PDF      PDF Energy   0.0004    0.0817  0.0006  0.9789  0.0011   \n",
       "        Random   Metric       0.0014    0.0858  0.0026  0.9770  0.0014   \n",
       "361087  PDF      PDF Energy   0.0055    0.1468  0.0054  0.9354  0.0017   \n",
       "        Random   Metric       0.0026    0.1459  0.0029  0.9347  0.0026   \n",
       "361088  PDF      PDF Energy   0.0111   10.1257  0.6189  0.9152  0.0074   \n",
       "        Random   Metric       0.0106   10.1630  0.5871  0.9125  0.0106   \n",
       "361089  PDF      PDF Energy   0.0059    0.1339  0.0034  0.8587  0.0024   \n",
       "        Random   Metric       0.0064    0.1341  0.0031  0.8568  0.0064   \n",
       "361090  PDF      PDF Energy   0.0031    0.7587  0.0037  0.6848  0.0028   \n",
       "        Random   Metric       0.0211    0.7812  0.0246  0.6675  0.0211   \n",
       "42570   PDF      PDF Energy   0.0284    9.2177  0.6197  0.4932  0.0183   \n",
       "        Random   Metric       0.0237    9.2906  0.5454  0.4901  0.0237   \n",
       "\n",
       "                              RMSE_100         RMSE_1000         R2_1000  \\\n",
       "                                  mean     std      mean     std    mean   \n",
       "Dataset Sampling Eval_Method                                               \n",
       "361072  PDF      PDF Energy     2.3204  0.1363    2.2556  0.1334  0.9848   \n",
       "        Random   Metric         2.2550  0.0544    2.2550  0.0544  0.9849   \n",
       "361073  PDF      PDF Energy     7.0065  0.2425    6.9917  0.2616  0.9721   \n",
       "        Random   Metric         4.5010  0.4271    4.5010  0.4271  0.9884   \n",
       "361078  PDF      PDF Energy     0.2181  0.0050    0.2181  0.0050  0.8533   \n",
       "        Random   Metric         0.2194  0.0061    0.2194  0.0061  0.8515   \n",
       "361080  PDF      PDF Energy     0.2363  0.0029    0.2377  0.0031  0.9450   \n",
       "        Random   Metric         0.2456  0.0070    0.2456  0.0070  0.9414   \n",
       "361081  PDF      PDF Energy     0.0857  0.0425    0.0826  0.0379  0.9872   \n",
       "        Random   Metric         0.0802  0.0421    0.0802  0.0421  0.9874   \n",
       "361082  PDF      PDF Energy   103.0747  3.5670  104.6016  3.1629  0.6662   \n",
       "        Random   Metric       107.2763  3.3160  107.2763  3.3160  0.6488   \n",
       "361083  PDF      PDF Energy     0.3516  0.0398    0.3382  0.0011  0.6784   \n",
       "        Random   Metric         0.3382  0.0011    0.3382  0.0011  0.6784   \n",
       "361085  PDF      PDF Energy     0.0193  0.0048    0.0193  0.0048  0.8837   \n",
       "        Random   Metric         0.0207  0.0055    0.0207  0.0055  0.8653   \n",
       "361086  PDF      PDF Energy     0.0822  0.0019    0.0823  0.0016  0.9789   \n",
       "        Random   Metric         0.0858  0.0026    0.0858  0.0026  0.9770   \n",
       "361087  PDF      PDF Energy     0.1451  0.0021    0.1463  0.0033  0.9344   \n",
       "        Random   Metric         0.1459  0.0029    0.1459  0.0029  0.9347   \n",
       "361088  PDF      PDF Energy    10.0101  0.4078   10.0101  0.4078  0.9152   \n",
       "        Random   Metric        10.1630  0.5871   10.1630  0.5871  0.9125   \n",
       "361089  PDF      PDF Energy     0.1332  0.0019    0.1349  0.0041  0.8550   \n",
       "        Random   Metric         0.1341  0.0031    0.1341  0.0031  0.8568   \n",
       "361090  PDF      PDF Energy     0.7609  0.0032    0.7620  0.0036  0.6840   \n",
       "        Random   Metric         0.7812  0.0246    0.7812  0.0246  0.6675   \n",
       "42570   PDF      PDF Energy     9.1607  0.6238    9.1545  0.6119  0.4961   \n",
       "        Random   Metric         9.2906  0.5454    9.2906  0.5454  0.4901   \n",
       "\n",
       "                                                  _R2_10  \\\n",
       "                                 std                       \n",
       "Dataset Sampling Eval_Method                               \n",
       "361072  PDF      PDF Energy   0.0029  $0.9857 \\pm 0.002$   \n",
       "        Random   Metric       0.0016  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy   0.0022  $0.9884 \\pm 0.001$   \n",
       "        Random   Metric       0.0023  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy   0.0061  $0.8519 \\pm 0.006$   \n",
       "        Random   Metric       0.0076  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy   0.0017   $0.946 \\pm 0.001$   \n",
       "        Random   Metric       0.0034  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy   0.0096   $0.9865 \\pm 0.01$   \n",
       "        Random   Metric       0.0112  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   0.0226  $0.6629 \\pm 0.021$   \n",
       "        Random   Metric       0.0243  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy   0.0019  $0.6784 \\pm 0.002$   \n",
       "        Random   Metric       0.0019  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy   0.0345  $0.4778 \\pm 0.229$   \n",
       "        Random   Metric       0.0477  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy   0.0008    $0.9792 \\pm 0.0$   \n",
       "        Random   Metric       0.0014   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy   0.0027  $0.9338 \\pm 0.005$   \n",
       "        Random   Metric       0.0026  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy   0.0074  $0.9131 \\pm 0.011$   \n",
       "        Random   Metric       0.0106  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy   0.0085  $0.8573 \\pm 0.006$   \n",
       "        Random   Metric       0.0064  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy   0.0032  $0.6867 \\pm 0.003$   \n",
       "        Random   Metric       0.0211  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy   0.0140  $0.4892 \\pm 0.028$   \n",
       "        Random   Metric       0.0237  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                          _RMSE_10             _R2_100  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     $2.1904 \\pm 0.074$  $0.9839 \\pm 0.003$   \n",
       "        Random   Metric          $2.255 \\pm 0.054$  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy      $4.501 \\pm 0.248$   $0.972 \\pm 0.002$   \n",
       "        Random   Metric          $4.501 \\pm 0.427$  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy     $0.2191 \\pm 0.005$  $0.8532 \\pm 0.006$   \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy     $0.2355 \\pm 0.003$  $0.9457 \\pm 0.002$   \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy      $0.084 \\pm 0.041$  $0.9859 \\pm 0.012$   \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   $105.1333 \\pm 3.343$  $0.6759 \\pm 0.022$   \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy     $0.3382 \\pm 0.001$   $0.6483 \\pm 0.09$   \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy     $0.0394 \\pm 0.012$  $0.8837 \\pm 0.035$   \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy     $0.0817 \\pm 0.001$  $0.9789 \\pm 0.001$   \n",
       "        Random   Metric         $0.0858 \\pm 0.003$   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy     $0.1468 \\pm 0.005$  $0.9354 \\pm 0.002$   \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    $10.1257 \\pm 0.619$  $0.9152 \\pm 0.007$   \n",
       "        Random   Metric         $10.163 \\pm 0.587$  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy     $0.1339 \\pm 0.003$  $0.8587 \\pm 0.002$   \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy     $0.7587 \\pm 0.004$  $0.6848 \\pm 0.003$   \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy      $9.2177 \\pm 0.62$  $0.4932 \\pm 0.018$   \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                         _RMSE_100            _R2_1000  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     $2.3204 \\pm 0.136$  $0.9848 \\pm 0.003$   \n",
       "        Random   Metric          $2.255 \\pm 0.054$  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy     $7.0065 \\pm 0.243$  $0.9721 \\pm 0.002$   \n",
       "        Random   Metric          $4.501 \\pm 0.427$  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy     $0.2181 \\pm 0.005$  $0.8533 \\pm 0.006$   \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy     $0.2363 \\pm 0.003$   $0.945 \\pm 0.002$   \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy     $0.0857 \\pm 0.042$   $0.9872 \\pm 0.01$   \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   $103.0747 \\pm 3.567$  $0.6662 \\pm 0.023$   \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy      $0.3516 \\pm 0.04$  $0.6784 \\pm 0.002$   \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy     $0.0193 \\pm 0.005$  $0.8837 \\pm 0.035$   \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy     $0.0822 \\pm 0.002$  $0.9789 \\pm 0.001$   \n",
       "        Random   Metric         $0.0858 \\pm 0.003$   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy     $0.1451 \\pm 0.002$  $0.9344 \\pm 0.003$   \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    $10.0101 \\pm 0.408$  $0.9152 \\pm 0.007$   \n",
       "        Random   Metric         $10.163 \\pm 0.587$  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy     $0.1332 \\pm 0.002$   $0.855 \\pm 0.008$   \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy     $0.7609 \\pm 0.003$   $0.684 \\pm 0.003$   \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy     $9.1607 \\pm 0.624$  $0.4961 \\pm 0.014$   \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                        _RMSE_1000               _R2_0  \\\n",
       "                                                                         \n",
       "Dataset Sampling Eval_Method                                             \n",
       "361072  PDF      PDF Energy     $2.2556 \\pm 0.133$  $0.9845 \\pm 0.002$   \n",
       "        Random   Metric          $2.255 \\pm 0.054$  $0.9849 \\pm 0.002$   \n",
       "361073  PDF      PDF Energy     $6.9917 \\pm 0.262$  $0.9385 \\pm 0.103$   \n",
       "        Random   Metric          $4.501 \\pm 0.427$  $0.9884 \\pm 0.002$   \n",
       "361078  PDF      PDF Energy     $0.2181 \\pm 0.005$  $0.8506 \\pm 0.008$   \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  $0.8515 \\pm 0.008$   \n",
       "361080  PDF      PDF Energy     $0.2377 \\pm 0.003$  $0.9455 \\pm 0.001$   \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  $0.9414 \\pm 0.003$   \n",
       "361081  PDF      PDF Energy     $0.0826 \\pm 0.038$  $0.9912 \\pm 0.007$   \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  $0.9874 \\pm 0.011$   \n",
       "361082  PDF      PDF Energy   $104.6016 \\pm 3.163$  $0.6699 \\pm 0.022$   \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  $0.6488 \\pm 0.024$   \n",
       "361083  PDF      PDF Energy     $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  $0.6784 \\pm 0.002$   \n",
       "361085  PDF      PDF Energy     $0.0193 \\pm 0.005$  $0.6418 \\pm 0.307$   \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  $0.8653 \\pm 0.048$   \n",
       "361086  PDF      PDF Energy     $0.0823 \\pm 0.002$  $0.9777 \\pm 0.001$   \n",
       "        Random   Metric         $0.0858 \\pm 0.003$   $0.977 \\pm 0.001$   \n",
       "361087  PDF      PDF Energy     $0.1463 \\pm 0.003$  $0.9289 \\pm 0.005$   \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  $0.9347 \\pm 0.003$   \n",
       "361088  PDF      PDF Energy    $10.0101 \\pm 0.408$  $0.9146 \\pm 0.008$   \n",
       "        Random   Metric         $10.163 \\pm 0.587$  $0.9125 \\pm 0.011$   \n",
       "361089  PDF      PDF Energy     $0.1349 \\pm 0.004$  $0.8577 \\pm 0.003$   \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  $0.8568 \\pm 0.006$   \n",
       "361090  PDF      PDF Energy      $0.762 \\pm 0.004$  $0.6732 \\pm 0.009$   \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  $0.6675 \\pm 0.021$   \n",
       "42570   PDF      PDF Energy     $9.1545 \\pm 0.612$  $0.5036 \\pm 0.027$   \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  $0.4901 \\pm 0.024$   \n",
       "\n",
       "                                           _RMSE_0  \n",
       "                                                    \n",
       "Dataset Sampling Eval_Method                        \n",
       "361072  PDF      PDF Energy       $2.2854 \\pm 0.1$  \n",
       "        Random   Metric          $2.255 \\pm 0.054$  \n",
       "361073  PDF      PDF Energy     $7.7879 \\pm 7.281$  \n",
       "        Random   Metric          $4.501 \\pm 0.427$  \n",
       "361078  PDF      PDF Energy       $0.22 \\pm 0.007$  \n",
       "        Random   Metric         $0.2194 \\pm 0.006$  \n",
       "361080  PDF      PDF Energy     $0.2366 \\pm 0.003$  \n",
       "        Random   Metric         $0.2456 \\pm 0.007$  \n",
       "361081  PDF      PDF Energy     $0.0683 \\pm 0.032$  \n",
       "        Random   Metric         $0.0802 \\pm 0.042$  \n",
       "361082  PDF      PDF Energy   $104.0375 \\pm 3.801$  \n",
       "        Random   Metric       $107.2763 \\pm 3.316$  \n",
       "361083  PDF      PDF Energy     $0.3382 \\pm 0.001$  \n",
       "        Random   Metric         $0.3382 \\pm 0.001$  \n",
       "361085  PDF      PDF Energy     $0.0318 \\pm 0.018$  \n",
       "        Random   Metric         $0.0207 \\pm 0.005$  \n",
       "361086  PDF      PDF Energy     $0.0845 \\pm 0.003$  \n",
       "        Random   Metric         $0.0858 \\pm 0.003$  \n",
       "361087  PDF      PDF Energy     $0.1522 \\pm 0.006$  \n",
       "        Random   Metric         $0.1459 \\pm 0.003$  \n",
       "361088  PDF      PDF Energy    $10.0459 \\pm 0.458$  \n",
       "        Random   Metric         $10.163 \\pm 0.587$  \n",
       "361089  PDF      PDF Energy     $0.1337 \\pm 0.002$  \n",
       "        Random   Metric         $0.1341 \\pm 0.003$  \n",
       "361090  PDF      PDF Energy     $0.7748 \\pm 0.011$  \n",
       "        Random   Metric         $0.7812 \\pm 0.025$  \n",
       "42570   PDF      PDF Energy     $9.2623 \\pm 0.452$  \n",
       "        Random   Metric         $9.2906 \\pm 0.545$  "
      ]
     },
     "execution_count": 874,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 875,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_1000</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_1000</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sampling</th>\n",
       "      <th>Eval_Method</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>9.675650</td>\n",
       "      <td>0.869543</td>\n",
       "      <td>0.825436</td>\n",
       "      <td>0.036200</td>\n",
       "      <td>0.816921</td>\n",
       "      <td>0.023314</td>\n",
       "      <td>9.514671</td>\n",
       "      <td>0.355629</td>\n",
       "      <td>0.843914</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>9.543200</td>\n",
       "      <td>0.362964</td>\n",
       "      <td>9.645350</td>\n",
       "      <td>0.331579</td>\n",
       "      <td>0.845307</td>\n",
       "      <td>0.008436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        RMSE_0                R2_0               R2_10  \\\n",
       "                          mean       std      mean       std      mean   \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   9.675650  0.869543  0.825436  0.036200  0.816921   \n",
       "Random   Metric       9.681214  0.358929  0.841764  0.011843  0.841764   \n",
       "\n",
       "                                 RMSE_10              R2_100            \\\n",
       "                           std      mean       std      mean       std   \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   0.023314  9.514671  0.355629  0.843914  0.014693   \n",
       "Random   Metric       0.011843  9.681214  0.358929  0.841764  0.011843   \n",
       "\n",
       "                      RMSE_100           RMSE_1000             R2_1000  \\\n",
       "                          mean       std      mean       std      mean   \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   9.543200  0.362964  9.645350  0.331579  0.845307   \n",
       "Random   Metric       9.681214  0.358929  9.681214  0.358929  0.841764   \n",
       "\n",
       "                                \n",
       "                           std  \n",
       "Sampling Eval_Method            \n",
       "PDF      PDF Energy   0.008436  \n",
       "Random   Metric       0.011843  "
      ]
     },
     "execution_count": 875,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dx_summary=dx.groupby(['Sampling', 'Eval_Method']).mean()\n",
    "dx_summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 876,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead tr:last-of-type th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_100</th>\n",
       "      <th colspan=\"2\" halign=\"left\">RMSE_1000</th>\n",
       "      <th colspan=\"2\" halign=\"left\">R2_1000</th>\n",
       "      <th>_R2_10</th>\n",
       "      <th>_RMSE_10</th>\n",
       "      <th>_R2_100</th>\n",
       "      <th>_RMSE_100</th>\n",
       "      <th>_R2_1000</th>\n",
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       "      <th>_R2_0</th>\n",
       "      <th>_RMSE_0</th>\n",
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       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sampling</th>\n",
       "      <th>Eval_Method</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PDF</th>\n",
       "      <th>PDF Energy</th>\n",
       "      <td>9.675650</td>\n",
       "      <td>0.869543</td>\n",
       "      <td>0.825436</td>\n",
       "      <td>0.036200</td>\n",
       "      <td>0.816921</td>\n",
       "      <td>0.023314</td>\n",
       "      <td>9.514671</td>\n",
       "      <td>0.355629</td>\n",
       "      <td>0.843914</td>\n",
       "      <td>0.014693</td>\n",
       "      <td>9.543200</td>\n",
       "      <td>0.362964</td>\n",
       "      <td>9.645350</td>\n",
       "      <td>0.331579</td>\n",
       "      <td>0.845307</td>\n",
       "      <td>0.008436</td>\n",
       "      <td>$0.8169 \\pm 0.023$</td>\n",
       "      <td>$9.5147 \\pm 0.356$</td>\n",
       "      <td>$0.8439 \\pm 0.015$</td>\n",
       "      <td>$9.5432 \\pm 0.363$</td>\n",
       "      <td>$0.8453 \\pm 0.008$</td>\n",
       "      <td>$9.6453 \\pm 0.332$</td>\n",
       "      <td>$0.8254 \\pm 0.036$</td>\n",
       "      <td>$9.6757 \\pm 0.87$</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Random</th>\n",
       "      <th>Metric</th>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>9.681214</td>\n",
       "      <td>0.358929</td>\n",
       "      <td>0.841764</td>\n",
       "      <td>0.011843</td>\n",
       "      <td>$0.8418 \\pm 0.012$</td>\n",
       "      <td>$9.6812 \\pm 0.359$</td>\n",
       "      <td>$0.8418 \\pm 0.012$</td>\n",
       "      <td>$9.6812 \\pm 0.359$</td>\n",
       "      <td>$0.8418 \\pm 0.012$</td>\n",
       "      <td>$9.6812 \\pm 0.359$</td>\n",
       "      <td>$0.8418 \\pm 0.012$</td>\n",
       "      <td>$9.6812 \\pm 0.359$</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        RMSE_0                R2_0               R2_10  \\\n",
       "                          mean       std      mean       std      mean   \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   9.675650  0.869543  0.825436  0.036200  0.816921   \n",
       "Random   Metric       9.681214  0.358929  0.841764  0.011843  0.841764   \n",
       "\n",
       "                                 RMSE_10              R2_100            \\\n",
       "                           std      mean       std      mean       std   \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   0.023314  9.514671  0.355629  0.843914  0.014693   \n",
       "Random   Metric       0.011843  9.681214  0.358929  0.841764  0.011843   \n",
       "\n",
       "                      RMSE_100           RMSE_1000             R2_1000  \\\n",
       "                          mean       std      mean       std      mean   \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   9.543200  0.362964  9.645350  0.331579  0.845307   \n",
       "Random   Metric       9.681214  0.358929  9.681214  0.358929  0.841764   \n",
       "\n",
       "                                            _R2_10            _RMSE_10  \\\n",
       "                           std                                           \n",
       "Sampling Eval_Method                                                     \n",
       "PDF      PDF Energy   0.008436  $0.8169 \\pm 0.023$  $9.5147 \\pm 0.356$   \n",
       "Random   Metric       0.011843  $0.8418 \\pm 0.012$  $9.6812 \\pm 0.359$   \n",
       "\n",
       "                                 _R2_100           _RMSE_100  \\\n",
       "                                                               \n",
       "Sampling Eval_Method                                           \n",
       "PDF      PDF Energy   $0.8439 \\pm 0.015$  $9.5432 \\pm 0.363$   \n",
       "Random   Metric       $0.8418 \\pm 0.012$  $9.6812 \\pm 0.359$   \n",
       "\n",
       "                                _R2_1000          _RMSE_1000  \\\n",
       "                                                               \n",
       "Sampling Eval_Method                                           \n",
       "PDF      PDF Energy   $0.8453 \\pm 0.008$  $9.6453 \\pm 0.332$   \n",
       "Random   Metric       $0.8418 \\pm 0.012$  $9.6812 \\pm 0.359$   \n",
       "\n",
       "                                   _R2_0             _RMSE_0  \n",
       "                                                              \n",
       "Sampling Eval_Method                                          \n",
       "PDF      PDF Energy   $0.8254 \\pm 0.036$   $9.6757 \\pm 0.87$  \n",
       "Random   Metric       $0.8418 \\pm 0.012$  $9.6812 \\pm 0.359$  "
      ]
     },
     "execution_count": 876,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latex_summary=join_mean_std(dx_summary, del_org=False)\n",
    "latex_summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 877,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{llllllllll}\n",
      "\\toprule\n",
      "       &        &                    \\_R2\\_10 &                  \\_RMSE\\_10 &                   \\_R2\\_100 &                 \\_RMSE\\_100 &                  \\_R2\\_1000 &                \\_RMSE\\_1000 &                     \\_R2\\_0 &                  \\_RMSE\\_0 \\\\\n",
      "       &        \\\\\n",
      "Sampling & Eval\\_Method &                           &                           &                           &                           &                           &                           &                           &                          \\\\\n",
      "\\midrule\n",
      "PDF & PDF Energy &        $0.8169 \\pm 0.023$ &  \\pmb{$9.5147 \\pm 0.356$} &  \\pmb{$0.8439 \\pm 0.015$} &  \\pmb{$9.5432 \\pm 0.363$} &  \\pmb{$0.8453 \\pm 0.008$} &  \\pmb{$9.6453 \\pm 0.332$} &        $0.8254 \\pm 0.036$ &  \\pmb{$9.6757 \\pm 0.87$} \\\\\n",
      "Random & Metric &  \\pmb{$0.8418 \\pm 0.012$} &        $9.6812 \\pm 0.359$ &        $0.8418 \\pm 0.012$ &        $9.6812 \\pm 0.359$ &        $0.8418 \\pm 0.012$ &        $9.6812 \\pm 0.359$ &  \\pmb{$0.8418 \\pm 0.012$} &       $9.6812 \\pm 0.359$ \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_140334/983800386.py:2: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
      "  return str(df.to_latex().replace('\\$','$').replace('\\\\textbackslash ','\\\\').replace('\\{','{').replace('\\}','}'))\n"
     ]
    }
   ],
   "source": [
    "latex_summary_rmse=make_bold(latex_summary,rmse_col,'rmse')\n",
    "latex_summary_final=make_bold(latex_summary_rmse,r2_col,'r2')\n",
    "latex_summary_final=del_non_paper(latex_summary_final)\n",
    "with open('paper/dx_rmse_r2_pdf_vs_sampling_summary.tex','w') as f:\n",
    "    f.write(get_latex(latex_summary_final))\n",
    "print(get_latex(latex_summary_final))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 3500x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pylab as plt\n",
    "plt.rcParams[\"figure.figsize\"] = (35,20)\n",
    "fig = matplotlib.pyplot.gcf()\n",
    "fig.set_size_inches(35, 20, forward=True)\n",
    "fig.set_dpi(100)\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (35, 20),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':12,\n",
    "         'ytick.labelsize':12}\n",
    "plt.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PDF vs KL "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1168,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Model selection "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1171,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_pdf_vs_KL_stack(df=df11_100, col='R2_100', B=100, ratio=None, ax=None):\n",
    "    if ratio:\n",
    "        df=df[(df.Sampling=='PDF') & (df.Ratio==ratio)]\n",
    "    else:\n",
    "        df=df[(df.Sampling=='PDF')]\n",
    "    df['PDF']=df.apply(lambda r: r.SML_Vanilla if r.SML_Vanilla>r[col] else r[col], axis=1)\n",
    "    df.reset_index(drop=True, inplace=True)\n",
    "    df_n=df.groupby(by=['Dataset']).count()\n",
    "    df_n['KL Wins']=None\n",
    "    df_n['PDF Wins']=None\n",
    "    df_n['Equal']=None\n",
    "    df_n=df_n.T\n",
    "    df_n.keys()\n",
    "    for i,g in df[(df.PDF>df.KL)].groupby(by=['Dataset'])['Dataset'].count().iteritems():\n",
    "        df_n[i]['PDF Wins']=g\n",
    "    for i,g in df[(df.PDF<df.KL)].groupby(by=['Dataset'])['Dataset'].count().iteritems():\n",
    "        df_n[i]['KL Wins']=g\n",
    "    for i,g in df[(df.PDF==df.KL)].groupby(by=['Dataset'])['Dataset'].count().iteritems():\n",
    "        df_n[i]['Equal']=g\n",
    "    df_n.fillna(0, inplace=True)\n",
    "    df_n=df_n.T\n",
    "    #df_n=df_n[['TS','PDF Wins', 'KL_Wins', 'PDF_KL_Eq']]\n",
    "    #labels=['TS','PDF Wins', 'KL Wins', 'Equal']\n",
    "    #df_n.columns=labels\n",
    "    fig1 = plt.figure(figsize=(10,5),dpi=300)\n",
    "    bx = fig1.add_subplot(111)\n",
    "    ax=df_n[['PDF Wins', 'KL Wins', 'Equal']].plot(kind='bar', \n",
    "                                                      stacked=True, \n",
    "                                                       rot=55,\n",
    "                                                       ax=bx\n",
    "                                                      )\n",
    "    ax.set_label(labels)\n",
    "    bars = ax.patches\n",
    "    patterns =('/', '////', '\\\\\\\\\\\\','/','//','O','o','\\\\','\\\\\\\\')\n",
    "    hatches = [p for p in patterns for i in range(len(df_n))]\n",
    "    for bar, hatch in zip(bars, hatches):\n",
    "        bar.set_hatch(hatch)\n",
    "    _ratio=f'\\\\rho={ratio}' if ratio else '\\\\rho \\\\in [.2,.3,.4]'\n",
    "    ax.set_title(f'Number of champions (highest R2 score); $ \\\\beta={B},{_ratio},T={df_n.sum().TS} $', fontsize=14)\n",
    "    plt.xlabel(\"Dataset\", fontsize=14)\n",
    "    plt.ylabel(\"Total Number of Wins\", fontsize=12)\n",
    "    plt.legend(bbox_to_anchor=(1, 1.05),fontsize=12)\n",
    "    plt.grid()\n",
    "    plt.savefig(f'paper/tab_pdf_kl_wins_{ratio}_{B}.jpg', bbox_inches=\"tight\")\n",
    "    df_n.to_csv(f'paper/tab_pdf_kl_wins_{ratio}_{B}.jpg_df_n.csv')\n",
    "    df.to_csv(f'paper/tab_pdf_kl_wins_{ratio}_{B}.jpg_df.csv')\n",
    "    df_n.to_pickle(f'paper/tab_pdf_kl_wins_{ratio}_{B}.jpg_df_n.pkl')\n",
    "    df.to_pickle(f'paper/tab_pdf_kl_wins_{ratio}_{B}.jpg_df.pkl')\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1173,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_140334/2166303040.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['PDF']=df.apply(lambda r: r.SML_Vanilla if r.SML_Vanilla>r[col] else r[col], axis=1)\n",
      "/tmp/ipykernel_140334/2166303040.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['PDF']=df.apply(lambda r: r.SML_Vanilla if r.SML_Vanilla>r[col] else r[col], axis=1)\n",
      "/tmp/ipykernel_140334/2166303040.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['PDF']=df.apply(lambda r: r.SML_Vanilla if r.SML_Vanilla>r[col] else r[col], axis=1)\n",
      "/tmp/ipykernel_140334/2166303040.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df['PDF']=df.apply(lambda r: r.SML_Vanilla if r.SML_Vanilla>r[col] else r[col], axis=1)\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 3000x1500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x1500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rRPZIaAfKTDmfsJXaOpC+qL/zjx+Vn4R2tisUEzergNZv5qIwSGp/G0ntyAQjrQCpkfwWL/xYDqTG/gGkxvE8XmivgNTYP4DUOJ7HC+0ViqnUcnHKfR3l5K677ur+/ve//6C6urrqpuX9+vXbM3v27CWTJk3aHlVsxXbcccft6NGjR7Mevp9//vnOGzdubDN/d9asWc2Sz5smnk+dOrVZEvqCBQvSSmgPS3xPTo4vpPr6ep111lnDbrjhhv3r6+vTXu6FF17o9I53vGPU5s2b08p7Xrt2bfWJJ544aubMmT2yjRXFldHTCgBKT7mcsJXaOpC+OHznbY7fk4d15MO188t7mCmkj5tVADdzi6m6c7Xqt719I6ExqX3IF4eoqn1hn5FuTGpf/rPl2vbCtn3ljUntQ68YKg0raAiSgqR2KUhib6rx/8b5QCqMtAKE48fyeOH8CkiN/QNIjeN5vNBeAamxfwCpcTyPF9orFFOp5eKU+zrKyU033dTz4osvHpbc6/aQIUN2zZgxY+nIkSN3RxVbFKqqqnTCCSdsnT59es/Gsvr6es2YMaPrOeecs7m1ZefNm9cs+fykk07al3g+cODAvcOGDdv52muvdZCkN954o93zzz/fbvTo0a1+vvPnz2+R0J6cHF9Il1566cB//vOfvRr/79+//+6TTz558+GHH76jT58+e+vq6qpeeOGFjv/+9797rlq1qlkvpcuWLetwySWXHPCHP/xhRVvr+dznPjdo6dKlHZPLhwwZsmvChAlbDj744J29e/fe26FDh4atW7dWb9q0qXrp0qUdXnzxxY5PP/105927d6fsNR6FQUI7UMbK5YSt1NaB9JXLd17MdZDQXjnqnpklHXVSi3JuVgHczC22oVcM1bKrl8U2qb3fd/pJ3QoagiSS2pFftFcAI63EDedXQGqMtAKkRvJbvHA8B1Jj/wBS43geL7RXKKZSzZko13WUk6uvvrrvN77xjcENDc1HfD744IN3zJo1a+nAgQP3pli0rE2aNKlZQrskzZkzp9WE9oaGBi1atGhf8rmZacqUKXVNXzN27NitjQntkjRjxoyuo0ePXp+qzhUrVtQsW7asQ9OyAw44YFexHjJYu3Zt7Y033thfkjp37txw1VVXrbzsssvW1dS0TGXetWvXqi9/+csDfv3rXzcbTvvPf/5z36uuuuqNYcOG7Um1npdffrn2nnvu6d20rGfPnnt/+ctfLjv33HNbfYhAkrZs2VL1j3/8o9stt9zSp6qqytN+g8hJYTMPAESmXE7YSm0dSF+5fOdc0KAQtiy8h55cgRS4mVt8HYd01NArhqq6c7PRAPcltTfsakixZP40JrV3PqRzs/L6bfVafcvqgq+/UZ939lH/c/q3KF9z1xqtu39d0eJAaaO9Ajiexw3fB9A6rs+BcDycFi8cz4HU2D+A1EhmjxfaKxRbOeRMlNM6ysXXv/71/l/72tdaJLOPGTOm7uGHH15SqcnskjRlypQWPaA//PDDLXpKb2rBggUdN2/evO9H2uHDh+8cMGBAs89w0qRJzRLc586d22pXYNOmTWuxzvHjxxetd/Y9e/aYu6t79+71M2fOfPErX/lKaDK7JLVv395/9atfrfrwhz/c7IfY+vp63Xjjja32Nva3v/2th3vzPPQ//vGPr6STzC5J3bp1azjvvPM2zZkz5+U//elPy9NZBrkjoR0oQ+V0wlZK60D6yuU7J5kdhZDqZlW348/iZhUqHjdzoxPrpPYd9SmWKAyS2pGOumdmhZbTXgEcz+OG7wPIHPsHwPEjbvg+gNQYaQVIjWT2eOF4jlJV7nkZpbaOqD355JOdf/KTnwxMLp88efLmuXPnLu3du3dxf9SLmTFjxuzs3bt3s2T0F198sdP69eurUy0za9asZsnnY8eObZF4PnXq1GZlCxYsaDVJfu7cuS3mT548uWgJ7Y1+9atfvTZu3Lgd6bz2Zz/72evt27dvlp0+e/bsVhP3X3311WY71pAhQ3a9+93vrkv1+tZ07dq18D+GQxIJ7UDZKbWTqXJZB9JXLt85yewohNZuHnY5/NQiRwPECzdzoxfnpPZiI6kdrWGkFSA1jufxwvcBZI79A+D4ETd8H0DruD4HwjHSSrxwPEepKve8jFJbRxzs2bPHkstOPvnkTTNmzHi5S5cuHrZMpUlOSK+vr9eMGTO6pHr9vHnzmiWfn3TSSS0Sz4cOHbpn8ODB+zawN998s/bZZ59NuWHNnz+/RSL46aefXtSE9uOOO67uox/9aFo9pUtSv3796idNmtTs9S+++GKn+vrUz0jU1dU1+1G7R48eFTs6QCkhoR0oM6V0MnX7k7s5Kaww5XIhQDI7CoGeMIDUuJkbH6WQ1L5z9c6CxyCR1I5wjLQCpMbxPF74PoDUGGkFSI3jR7zwfQCZY/8AOH7EDd8HSlW552WU2jri7Mknn+zy1FNPdYg6jriYNGnSluSyOXPmhPaoXl9fr0WLFjWbd9ppp4Umno8bN65Z+YwZM0LrXL58ee3y5ctb9Fw+bNiwPW3Fnk+f+MQn1ma6zLHHHrut6f/bt2+veu2112pTvb5Xr17NEtiXLl3asbXe8BEPJLQDaKFYJ1PXzN9d0HVU+klh3JTLhUDU60B5IpkdSI2bufET96T21bes1o7laY1OlzOS2tEUI60AqXE8jxe+DyA1RloBUuP4ES98H0Dm2D8Ajh9xw/eBUhV1zgTriK/OnTs3mDXvpH3Dhg01U6ZMGbVw4cKOEYUVK1OnTm2RkP7II4+EJp8vWLCg45YtW/b9IHvggQfuHDRoUGgv4xMnTmxW79y5c0PrnDZtWovy8ePHt0iyL7QpU6Zk3CP8iBEjWuxMGzduTJmgPnbs2GYJ8Dt27Kh6//vff+Cbb75JUnuMkdAOoJkoT6Y4KSxf5XIhUC7rQLy01pMrUOm4mRtfcUpq73hg8/tf9TvqtezqZSS1o6h4OA1IjeN5vPB9AKkx0gqQGsePeOH7AFJjpBUgNY4f8cL3gVJVLjkT5bKOuBk9evT2H//4xyuSk9o3btxYM3Xq1JGPPfZYxSe1H3HEEbv222+/Zr2hv/jii53WrVvXIsl61qxZzZLPx44dmzIJPDlBfMGCBaEJ7fPmzWtRftJJJ2WcXJ6L9u3b+/DhwzPuEb5Hjx71yWWtJbS///3v39y3b99m63nooYe6jRgx4vDzzjtv8H333dd1165dlmp5RIOEdgD7kMyOQimHC4FyWQfipbWbVfTkikrHzdz4i0tS+4DzBrQor99GUjuKh2R2IDWO5/HC9wGkxkgrQGocP+KF7wNIjZFWgNQ4fsQL3wdKVbnkTJTLOuLqiiuuWHvNNdcsT05q37RpU83pp58+8tFHH634pPbkxPSGhgZNnz69S/Lr5s2b163p/5MnT06ZeD5ixIg9AwcO3N34/9q1a2uffvrpFhvb/PnzWyS0n3766UVNaO/WrVtoL/Ntqa2t9eSy3bt3p8x/7tKli19zzTUtHrCoq6urvuOOO/qeeeaZI3v06HHU+PHjR15yySUD//SnP3Vfu3YtvbdHjIR2AJKKczJ1+5O7Q8s5Kaw8pfadl8s6EC/crAJSY/8oHbFIam8XfllLUjuKgZFWgNQ4nscL3weQGg+nAalx/IgXvg8gNUZaAVLj+BEvfB8oVeWSM1Eu64i7r3zlK+uuvfba0KT2d77znaMeeeSRik5qD0tMf+CBB5olr9fX12vRokXNktynTp3aauJ5cqL89OnTmyWvL1u2rHb58v9n797j7Crre/F/VwKThIRwMWBEIakKgkqbFkWN9YLiBdFaUQ+1rc1P29NTT1vF04a2WtvTY609xLZorW2PR09TTy/0KGovokK9QA013qKooHhJAGnEcAu5MSGzfn9Mhrlknp09k733ep613+/Xa14wa2b2sybf9X2emWd/Zq9t0y7CRz3qUftOPfXUeQXM52u2YHq/rFu37p53vetd312yZMmsT1rv27dvwfXXX3/sO9/5zpU/+7M/++iVK1euefzjH3/WG9/4xpXf+ta3jh7UeTJJoB0Y2A9sGzYdGmj3Q+HwKa3mbRmDvNisgjT9UZ4cQu0pQu30kzutQJr1PC/qAWnC7JBm/ciLekCaO61AmvUjL+pBqdqSmWjLGKV4/etfv+NP/uRPti5YMD2eeu+99y688MILH/Nv//ZvxzR0ao173vOet3PmsZmvnH799dcfc9999z345Ovq1av3nXbaaR2D509/+tOnBdqvvfbaaY/50Y9+9JBXZ1+7du1AX529Cb/0S79019e+9rWv/uzP/uwPli1bdqDT546NjcXXvva1Y/7gD/7g4WedddbZF1988arbb7/9qEGdKwLtMPSa/IFt/doRPxQOmdJ+EWjLGOTFZhWk6Y9y5RRqX/LI6S/qkFOonfYwX0Ga/siLekCaO61AmvUjL+oBaf44DdKsH3lRD0rVlsxEW8Yozete97o7L7/88lSo/Yxrr712KEPtj33sY0dPOeWUaa8K+41vfGPJ97///QefaL366qunhc+f8pSn7Drc4z73uc+dFk7/93//92mP8alPfeqQQPuznvWsQ8L1bfRDP/RD+9/3vvfd8h//8R9f3rhx47d/7ud+7o7HPOYxexcuXJj8mgceeKD6h3/4hxU/8iM/8thh/gOMQRNohyHW5A9sERHr1oz0dYxh/qEwR6X9ItCWMciLzSpI0x/lyyXUfsorT4mlZy2ddiyXUDvtYL6CNP2RH/WA2bnTCqRZz/OiHpAmzA5p1o+8qAelaktmoi1jlOpXf/VX73zHO97x3Zmh9p07dy584QtfeManP/3poQwKP/nJT54WPq/rOj7+8Y8/GDi/7rrrpoXPn/GMZxz2ldTPPPPM0ZUrVz4YlN+xY8fRX/rSlxZPvH/99ddPe8yqquJ5z3veYYPybbJs2bL6537u5+7ZuHHjrTfddNPX77zzzi998IMf/ObrX//6//jhH/7h3TOv04jxf8eXvOQlj96+fXs6/U7PCLTDkGo6zN4rfigsQ2m/CGzcMuoXGnrOZhWk6Y/2yCHUvmBkQay6ZJVQO31hvoI0/VEG9QDzFXSiP/KjHjA7d1qBNOt5XtSDUrUlBN6WMUr3y7/8y3e9853v/O7MV8O+7777Fr7whS884xOf+MTSxJe21jOf+cxDAuqf+MQnjo2IOHDgQHzuc59bNvVjz3ve8w4baI+IeNKTnjQtoD4Rkt+6devRt9xyy7QL8vTTT9/7sIc97IG5nnubHHfccWM/+ZM/ed8f//Ef3/7lL3/5pm9+85tf+eVf/uXtixYtqqd+3o4dO47+vd/7PU/8DoBAOwwhYXYGrbRfBDZsGj3kmF9oOBI2qyBNf7RPFqH2RULt9J75CtL0RxnUA8xX0In+KIN6gDutQCfW87yoB6VqSwi8LWO0xWte85pZQ+27du1a+OIXv/j0f/3Xfx2qUPvzn//8QwLqmzZtOvbgf4/ZtWvXg/9Qq1atun/16tX7u3ncpz/96dMe99prrz02IuKqq646dubnPvWpT+0qJD9MHvWoR+1/5zvf+b0PfehD35x5rf7Lv/zLCQ2d1lARaIch0+QPbOvXjvTk8TuN4YfC9mqy5n6h4UjYrII0/dFeQu2ThNrbwXwFafqjDOoB5ivoRH+UQT3AfAWd6I/8qAclaksIvC1jtM0v/dIv3fXnf/7n30mE2s+4+uqrhybUfvrpp48+4hGPmHYB3XzzzUu2b9++8Oqrr54WPn/yk5/cdfD8uc997rTP/fd///djIyI+9alPHRJof9azniXQnvD85z9/13nnnXfP1GO33nrrovvuu0/eus/8A8MQafoHtnVrehNoH9T3QT6E2SmVzUNI0x/tJ9Q+Sai9bOYrSNMfZVAPMF9BJ/qjDOoB5ivoRH+UQT3IXdOZImMMh//8n//z3X/xF3/xnYULF9ZTj+/evXvBS17ykjM+/vGPD02ofe3atdMC5XVdx8c+9rFjr7vuumnh82c84xldB88f//jH33/SSSc9+Grud91111Ff+MIXFl9//fXTHnPBggXxvOc9T6C9gzPOOGPfzGN33XXXwtk+l94RaIch0ZYf2Jocg2YMouYbt4zOery0a5e82DyENP0xPITaJ624YMVAxqG3zFeQpj/KoB5gvoJO9EcZ1APMV9CJ/iiDepC7tud9Shuj7X7hF37h7ne/+93fTYXaP/rRjy5r6twG6ZnPfOYhgfKrr756+ec///lp3//MV10/nCc96UnTPv///J//85Bbb7112sV55pln7jnppJMOzOVxh8327duPnvp+VVWxcuXKB5o6n2Eh0A5DoC0/sAmzD59B1XzDpkMD7aVdu+TF5iGk6Y/hI9ROqcxXkKY/yqEeDDvzFaTpjzKoB5ivoBP9UQb1IHdtz/uUNsaweNWrXnX3e97znu8cddRR00Lte/bsWXDRRRedftVVV7U+1H7BBRccElT/4Ac/+JBdu3Y9+KTqqaeeev+jHvWo/TM/r5OnP/3pMwPtJ8/8nKc+9amtf3X2//bf/tspn/jEJ+b1iv/f+ta3jv74xz9+/NRjj3zkI/ctWrSoTnwJPSLQDi3Xlh/YhNmHT5M1X792pKhrl7zYPIQ0/TG8hNopjfkK0vQHUArzFaTpj3KoB8POfAVp+qMM6kHu2p73KW2MYbNu3bp73vve9x4Sat+7d++Cl770paf/8z//87FNndsgrF69ev+qVaumXVR79uyZlud98pOfPOfg+fnnn7+r02NGRDzrWc9qfaD9Ix/5yPHPfvazz/yRH/mRM9/85jeffPPNN49083VXX3310mc/+9mPmfqHBRERL3/5y+/sz5ky1VFNnwDQP235gU2Yffg0XfN1a0Yi9vVvDL/QtJfNQ0jTH0yE2rdetjUO7J68g91EqH3VJatiwaL+/s31RKh92+XbYveNux88PhFqX33p6liyaklfz4H8ma8gTX8ApTBfQZr+AEphvoI0/VEG9SB3bc/7lDbGsHrlK195z4IFC779qle96lH79++vJo7v3bt3wctf/vJHX3HFFd/6iZ/4ia7D13/913990kc+8pHjj/S8NmzYcOuLXvSivoe+165du3Pbtm0npT7+jGc8Y87n8KM/+qP7HvKQhzxw5513zpoNXrhwYTz3uc9tfaB9wle+8pWlX/nKV5b+zu/8zqmrV6/e97jHPW7v4x73uD0nnXTSA8cff/yBiIh77rln4Te/+c3Fn/nMZ479+te/fszMx1i1atX9b3jDG+4Y/NkPH4F2aKm2/MDWdLCZwWtLzf1CM3xsHkKa/mCCUDu5M19Bmv4ASmG+gjT9AZTCfAVp+qMc6kHu2pz3KXGMX+vJI5XpZ37mZ+5dsGDBt9etWzct1L5v374FF1988aP//u///lsvfvGLuwpg33nnnUelgtxzcc899yw8/GcdufPOO+++v/u7v0sG2p/73OfuSn2sk3PPPfe+q6666oTZPvbYxz5294knntj/22dnaOvWrYu3bt26+F/+5V9m/beZzUMf+tD973//+7917LHHDuW/2aD1NykANKJNP7A1OQaDJ8xOqWweQpr+YKaJUPvCpdP3gSZC7WP3938vYCLUvvSspdOOT4Ta927b2/dzID/mK0jTH0ApzFeQpj+AUpivIE1/AP3UprxPG8YYNq94xSvu/eu//utvj4yM1FOP79u3b8FP/dRPPfqDH/zg8qbOrZ9e8IIXJIP6D3/4w0dPP/300fk87tOe9rTk4/74j//4ULw6+0knnbT/SB/jvPPOu/f666+/8QlPeMK+XpwTh+cV2qFl2v4DW2lj0L0ma75+7UhPHr/TGK6r9rJ5CGn6gxSv1E5uzFeQpj+AUpivIE1/AKUwX0Ga/gB6ra7rL/TrsX/t4Fs/GaN9fuqnfureBQsWfOuVr3zlo0dHR6e9UvsrXvGKR//N3/zNt1760pfubPIce+3hD3/4A4961KP2ffvb314882NPfvKT5x08P//88+97wxveMOvHnvWsZw1FoP266667+Utf+tLiD33oQ8ddd911x37pS19aes899xw2L71s2bIDz33uc+/5hV/4hR0XXHDBvF4hn/kTaIeWaUMIvC1j0L2ma75uzUh8ss9juK7ayeYhpOkPDkeonVyYryBNfwClMF9Bmv4ASmG+gjT9AUBuHvOYx4z2448i/tN/+k87/9N/+k9f7OZzX/va19752te+9s5en8Ogfetb3/parx/ziU984r5e12e+/94f+MAHtkbE1iMd/4UvfOF9c/2efvRHf3Tfj/7oj+6LiO9HRNx8880jN91006LvfOc7I/fcc8/C3bt3Lzz66KPr5cuXH3joQx+6/8d+7Mf2Pu5xj7t/4cKFh3lk+kWgHVqutBB4W8ageznUvBd/vjmo78Nf5ubD5iGk6Q+6JdRO08xXkKY/gFKYryBNfwClMF9Bmv4AAOiN008/ffT0008fbfo8SOtvMgBoVGkh8LaMQffaUvMmx6AZNg8hTX8wVxOh9oVLp/+l+0Sofez+sb6fw0SofelZS6cdnwi17922t+/nwOCZryBNfwClMF9Bmv4ASmG+gjT9AQDAMBFoh5ZqS1i3tDHoXltqLsw+fGweQpr+YL6E2hk08xWk6Q+gFOYrSNMfQCnMV5CmPwAAGDYC7dBCbQnrljYG3WtLzYXZh4/NQ0jTH+2146odAxlHqJ1BMV9Bmv6AtJ2br2z6FJjCfAVp+gMohfkK0vQHAADDSKAdWqYtYd3SxqB7bam5MPvwsXkIafqj3bZfsV2oPYTa28J8BWn6A9JS/UEzzFeQpj+AUpivIE1/AAAwrATaoWVKCutu3DLaitAx3Wt70FyYvb1sHkKa/hgOQu3jhNrLZr6CNP0BacLseTFfQZr+gDR3WsmL+QrS9AcAAMNMoB04xKBC4Bs2jfZ1DGH2vLQ9aD6oMRg8m4eQtuuGa/THEBFqHyfUXibrOaTpD0gTZs+L+QrS9AekWc/zYr6CNP0BAMCwE2gHpmkyBF5a6JjuNR0CNwbzZfMQOpvt1a30R7sJtY8Tai+L9RzS9AekCb/lxXwFafoD0qzneTFfQZr+gDR3WgGA4SHQDjxImJ1+aUMIvC1j0D2bhzB3+mM4CLWPE2ovg/Uc0txpBdKE3/JiPYc0/QFp1vO8mK8gTX9AmvUcAIaLQDsQEYMJ0m7cMjrrcYHg4VNazdsyBt2zeQhzpz/aa+XFKw85llWofVSondlZz6Ezd1qB2XVaPxg86zmk6Q9IE37Li/kK0vQHpFnPAWD4CLQDAwvrbth0aKBdIHj4lFbztoxB92weQtquG66Z9bj+aLcVF6zIOtR++/tuH8g5CLWXxXoOc6c/wPqRG/WANHdagTTht7xYzyFNf0Ca9RwAhpNAOwy5JsO669eOCAQPmdJC4G0Zg+7ZPIS0nZuv9EquQyznUPve7wwuSC7UXgbrOcyd/gDrR27UAzrz+znMzp1W8mI9hzT9AWnC7AAwvATaYYg1GdaNiFi3ZqSvYwgE56W0EHhbxqB7Ng8hLdUfy8+9SH8MkZxD7YMk1J436zmkudMKpFk/8qIeMHf6A6wfuVEPSHOnFUgTZgeA4SbQDkOq6TB7rwgEl6G0EPjGLaPC7EPG5jqkddo8XHb2+QM+G5pWQqh9bHSs7+cg1J4n6zmkudMKpFk/8qIeMHf6A6wfuVEP6Mzv5zA7d1oBAATaYQgJszNopYXAN2wa7esYrt282FyHNK+EwWxyD7Xf/r7bY+x+ofZhYz2HNHdagTTrR17UA9LcaQXSrB95UQ+YO/0B1g8AYJxAOwyZJsPs69eO9OTxO40hENxeTdZcmL29bI5AmjA7nWQVal8yPdS+9zt7Y9vl24Tah4j1HNLcaQXSrB95UQ9Ic6cVSLN+5EU9YO70B1g/AIBJAu0wRJoMs7/tOYti3ZreBNoH9X2QD2F2+sHmCKR1eiVXmJBLqP2UV59yyPHdN+4Wah8S1nNI88dpkGb9yIt6QJo7rUCa9SMv6gFp7rQCadYPAGAqgXYYEk2H2dswBs0YRM03bhmd9Xhp1y5zY3MEZtdp89AruTJTDqH2xacsnvW4UHv7ebID0oTZIc36kRf1gDR3WoE060de1APS3GkF0qwfAMBMAu0wBNoeNBdmb69B1XzDpkMD7aVduxw5myNg85D5ySHUniLU3l7mK0hzpxVIs37kRT0gzR+nQZr1Iy/qAWnutAJp1g8AYDYC7dBybQ+aC7O3V5M1X792pKhrlyNncwRsHnJkcgq1L1yycNr7OYXa6R3zFczOnVYgzc+7eVEPSBNmhzTrR17UA9LcaQXSrB8AQIpAO7RY24Pmwuzt1XTN160Z6esYwux5sTkCNg/pjVxC7ae8+pRYuDTPUDv9Y74C6zl0oj/yox4wO3dagTTreV7UA9L8cRqkWT8AgE4E2qGl2h40F2Zvr7bUXJi9DDZHwOYhvZVDqH3xKYtj9aWrswy10x/mK7CeQyf6owzqAe60Ap1Yz/OiHpAmzA5p1g8A4HAE2qGF2h40H9QYDJ4wO4NkcwRsHtIfOYTal6xaItQ+JMxXYD2HTvRHGdQDzFfQif7Ij3rA7NxpBdKs5wBANwTaoWWaDoEbg/lqsubr14705PE7jeG6yo/NEYadzUP6Sah9nFB7f5mvwHoOneiPMqgHmK+gE/1RBvUAd1qBTqznAEC3BNqhZdoQAm/LGHSv6ZqvW9ObQLvrCiiFzUMGQah9nFB7f5ivwHoOneiPMqgHmK+gE/1RBvUA8xV0oj8AgLkQaIeWKy0E3pYx6F5baj6oMQCOlM1DBkmofdxEqJ3eMV8x7KznkKY/yqAeYL6CTvRHGdQDzFfQif4AAOZKoB1arMSwbhvGoHttqXmTYwDMhc1DmiDUPm7BIr9+A71hPYc0/VEO9WDYma8gTX+UQT3AfAWd6A8AYD48ow4t1Zawbmlj0L221FyYHSiFzUOaJNQO0BvWc0jTH0ApzFeQpj/KoB5gvoJO9AcAMF8C7dBCbQnrljYG3WtLzYXZgVLYPCQHQu0AR8Z6Dmn6AyiF+QrS9Ec51INhZ76CNP0BABwJgXZombaEdUsbg+61pebC7EApbB6SE6F2gPmxnkOa/gBKYb6CNP0BlMJ8BWn6AwA4UgLt0DIlhXU3bhltReiY7rU9aC7MDuTG5iE5EmoHmBvrOaTpD6AU5itI0x9AKcxXkKY/AIBeEGgHDjGoEPiGTaN9HUOYPS9tD5oPagyAbtk8JGdC7QDdsZ5Dmv4ASmG+gjT9AZTCfAVp+gMA6BWBdmCaJkPgpYWO6V7TIXBjAMPG5iElEGoH6Mx6Dmn6AyiF+QrS9AdQCvMVpOkPAKCXBNqBBwmz0y9tCIG3ZQyg/WweUhKhdoDZWc8hTX8ApTBfQZr+AEphvoI0/QEwfF760peurqrqnIm3hz/84Wc3fU60i0A7EBGDCdJu3DI663GB4OFTWs3bMgb0w87NVzZ9Ckxh85ASCbUDTGc9hzT9AZTCfAVp+gMohfkK0vQHANAPRzV9AkDzBhXWfftNo/Gnr+jvGALB+Sut5m0ZA/phcrPqPU2fCmHzkLKtuGBFRIyH2KeaeH/i4/00EWrfetnWOLD7wIPHJ0Ltqy5ZFQsW+ZtwoL+s55CmP4BSmK8gTX8ApTBfQZr+ACZ84xvfGDnzzDP78grdy5YtO3Dfffdt6cdjA/kSaIchN8iw7qmnTj++fu1I/OqZAsHDpLQQeFvGgH5IbVbRDJuH9NPebXtjyaolfR9HqB0Gb/xOKxc2fRocZD2HNP0BlMJ8BWn6AyiF+QrS9Ee7VFV1TkTE0rOWDuz5j7H7x2Lb5dti9427px1fuHRhrL509UCej4qI2HHVjkOej4qIWHnxyoE8HxUx/vzb1Oej6rr+wkAGBsiYZ+JhiDUZ1o2IWLdmpK9jCATnpbQQeFvGgH4QZs+LzUP6betlW2Pvtr0DGWvFBSti5cUrDzm+/YrtseOqHQM5h4lQ+8KlC6cdnwi1j90/NpDzgH6znufFeg5p+gPSxv84jVyYryBNfwClMF9Bmv5or0E+/7Fg0YJYdcmqWHrW0mnHD+w+4PkoALxCOwyrpsPsvSIQXIbSQuAbt4wKs0OC8FtebB4yCBObiIN6ZQyv1A79Zz3Pi/Uc0vQHpE32x3uaPhXCfAWd6A+gFOYrSNMf7TfI5z8mQu0zX6l92J+PaoslS5aMnXbaaUccFlu6dOmBw38W0DYC7TCEhNkZtNJC4Bs2jfZ1DNcupRJ+y4vNQwZp2DcRhdppE+t5XqznkKY/IM16nhfzFaTpD0gbv9PKhU2fBgeZryBNf7TXwqULG3v+Q6h90sTzUW3x+Mc/fs/mzZu/0fR5AGXy7DsMmSbD7OvXjvTk8TuNIRDcXk3WXJgdOm9WMXg2D2mC2z1OGuTtN6GXhN/yYj2HNP0BadbzvJivIE1/QJr1PC/mK0jTH+3W9PMfE6H2pWctnXZ8WJ+PAkCgHYZKk2H2tz1nUaxb05tA+6C+D/IhzA7NslmVF/WgScO6idj0pi70gifL82I9hzT9AWnW87yYryBNf0Ca9Twv5itI0x/tl8PzH0LtAEwl0A5DoukwexvGoBmDqPnGLaOzHi/t2oV+sFmVF/WgCTYR89jUhSPhTit5sZ5D2q4brtEfkCD8lhfrOaTpD0iznufFfAVp+mN45PD8h1A7ABOOavoEgP5re9BcmL29BlXzt980Gn/6iv6OIcxOiWxW5UU9aMqqS1bFtsu3xe4bdz94bGITcfWlqwdyG8QVF6yIiPFNw6m2X7E9Hrb8YREX9v0UHtzU3XrZ1jiw+8CDxyc2dVddsioWLPI34+TH+pEX9YDOdm6+8pBj+gP8cVpurOeQpj8gTZg9L+YrSNMfwyeH5z8mQu05Px819ePk6957711wzTXXLLvllltGvv/97x+1aNGi+mEPe9j+c889d8+P/diP7Wv6/PplbGwsbr755pEbbrhh8datW0d27ty5cHR0tDr++OMPnHDCCQfOOOOMfT/+4z++5+ijj276VKEjgXZoubYHzYXZ22uQNT/11OnH168diV89s5xrF/rBZlVe1IMm5b6JuOOjOwYSaI/IY1MX5sL6kRf1gLnTH2D9yI16QJo7rUCaMHterOeQpj+GVw7Pf+T+fJRQe94++9nPLvnd3/3dh336058+bt++fbNerI94xCPu/8Vf/MU7Lr300h8sWrSojoh46UtfuvrKK698yMTnnHLKKaPf+973bug01jve8Y6HvO51r1s99dhNN910w2Me85jRuZ53VVXnTH3/9a9//X/88R//8e3dfO23v/3to//u7/7uhE9+8pPHfv7znz92586dCzt9/uLFi8ee+MQn7nrd6173/Ze+9KU753quMAieaYcWa3vQXJi9vZqu+bo1I30dQ5id3Nmsyot6kIPcb/c4SDncfhO6Yf3Ii3rA3OkPsH7kRj2gM3dagdm500perOeQpj/I4fmP3J+P2n7F9thx1Y6BnAPdOXDgQPzKr/zKw5/61Kee9bGPfeyEVJg9IuK2225b9Du/8zunnn322Wd9/etf700wqCHnnHPOY04//fQfftOb3nTqJz7xieMPF2aPiNi3b9+C6667bvnLXvay03/sx37szG9/+9terp3sCLRDS7U9aC7M3l5tqbkwO6WyWZUX9SAnuW8iDlIOm7rQifUjL+oBabtuuGbW4/oDrB+5UQ+YO/0B1o/cqAekudMKE3J4/iP356OE2vNx4MCBeNnLXrb6z/7sz1YeOHCg6vbrbr755iXPeMYzzvzGN75RbKj9i1/84rK6ruf99V/60peWPulJT3rs9ddf3//bHsAcHNX0CQC91/ag+aDGYPCE2aFZNnPzoh7kKPfbPUZE3H3d3RFP7fspZHH7TZiN9SMv6gFpOzdfGWPfujriledNO64/wPqRG/WAudMfYP3IjXpAZ+60wlQ5PP+R+/NRE+9PfJxm/PzP//ypH/rQhx4y8/gxxxwz9uxnP/ueJz7xibtXrly5/95771148803L/7IRz5y/G233bYoImLHjh1Hv+QlL3nU6aefvm/wZ95bIyMj9eMf//jdZ5xxxr4zzjhj3wknnPDA8uXLx/bv31/de++9C2+66abFmzdvXva1r33tmKlfd+eddx518cUXP2rLli1fP/HEE71aF1kQaIeWaToEbgzmq8mar1/buz+6dF1RKpu5eVEPcpbbJmJsmn58x0d3xP6d+weyiZjDpi5MZf3Ii3pA2kR/LDv11GnHl597USx49HMaOivIg/UjL+oBabtuuCZizXmHHNcfYP3IjXrA3OkPcnj+I7fno4Ta8/JP//RPx/71X//1yTOPv+QlL7nzL//yL2896aSTDsz82NjY2G1/9Ed/tOL3fu/3Tt29e/eCG2+88Zjvfve7iwdzxr21ePHisRe84AV3//RP//Rdz3ve8+5btmzZYV+u/fOf//zi173udadu2rRp+cSxW2+9ddEll1zyiL/+67++pb9nDN3xzDq0TBtC4G0Zg+41XfN1a3oTaHddUSqbuXlRD0qQ0+0eVzz/0I3CQd7uMYfbb0KE9SM36gFpqf6IiFh29vkDPhvIi/UjL+oBaTs3X+mVXCHB+pEX9YC50x9MyOH5j5yej1p58cpDjg/y+SgmHThwIH7lV35lVV1Pz3D/4i/+4vevvPLKrbOF2SMiFixYEOvXr9/xgQ984ObFixePRUTs27evyPzsbbfd9pUPfOADW1/60pfu7CbMHhHxhCc8Yd+1115788tf/vJpF+3/+3//7yE/+MEPFqa+DgapyIYEuldaCLwtY9C9ttR8UGNAr9nMzYt6UJJcNhFPeNoJsx4XameYWD/yoh6Q1inMDsPO+pEX9YC0VH8sP/ci/cHQs37kRT0gbdcN18x6XH8wUw7Pf+TyfJRQe3e++tWvHnPmmWc+9kjfvvzlLyeDNldcccVxt9xyy7SPn3POObv+8i//8rZuzvF5z3verje/+c23Hun32qSHPOQhs4b2D2fhwoXxV3/1V7esXLlydOLYvn37FrznPe85sXdnB/Mn0A4tVmJYtw1j0L221LzJMeBI2MzNj3pQmlw2EVOE2hkG1vO8qAekCbNDmvUjL+oBae60AmnWj7yoB6S50wpzlcPzH7k8HyXUfnh79+5d8I1vfGPJkb7t3r07mWv9X//rf50089if/umf3jKX83z961+/4zGPeUyzT2Q25Jhjjqlf+MIX3j312Gc+85llTZ0PTCXQDi3VlrBuaWPQvbbUXJidUtnMLYN6UIJcNhFTcgq1Q69Zz/OiHpDW6ZVcYdhZP/KiHpDmj9MgzfqRF/WANHdaYb6E2icJtTfr/vvvr/793/99+dRjZ5999u6nPOUpc7oAFi5cGOvWrftBb8+uHKeffvq0ENKXvvQlgXaycFTTJwD0XlvCuqWNQffaUnNhdkplM7cM6kFJJjYRt12+LXbfuPvB4xObiKsvXR1LVi0ZyLmseP6KuPXd0+8SuP2K7eMfu2BF38ef2NTdetnWOLB78m5/U/9doBes5/lRD5hdp/lq/JVc53V3XGgF63le1APShNkhzfqRF/WAtMPdaWXXUL5OMXPR6fmPbZdvi1WXrIoFi/r72rq5PB818XzTxPNPEwb5fNSw2rRp05L777+/mnrsRS960T3zeayf/umfvucNb3jDaT05sYZt37594dVXX33sV77ylSU33XTT4nvvvfeo3bt3L9izZ8/Cuq4P+fx777134YyvP3pgJwsdCLRDy7QlrFvaGHSvLTUXZqdUNnPLoB6UKJdNxBOedkKs3Lmy0U3E1KYu9Ir1vAzqAd3MV4c+mQLDwnqeH/WA2bnTCqRZz/OiHpDmj9PoFaH2SULts3viE5+4a/Pmzd/o1+Nv3rx56cxjT3ziE+f1qlKrVq3af9JJJ+3/wQ9+UGyY+8Mf/vCxb3/72x963XXXLX/ggQeqw3/F7A4cOFDde++9C4477rj+324BOujvCgIMXElh3Y1bRlsROqZ7bQ+aC7OTO5u5ZVAPSuZ2j5NSt9+EI2U9L4N6gPkKOtEfZVAP6OZOKzC8rOd5UQ9IE2an11LPf0yE2sfu738e1vNRw+uOO+445AWcH//4x++b7+M98pGPnPfXNumuu+5acOGFFz7yJ3/yJ8/45Cc/edyRhNmnPKYnNWmcQDtwiEGFwDdsGu3rGMLseWl70HxQY8B82cwtg3rQBjYRJwm102vW8zKoB5ivoBP9UQb1APMVdKI/8qMeMDt3WqFfhNon5fB81DC55557Dgm0n3jiifO+XfKxxx5b3K2W77rrrgXPetazzvjIRz5yQi8fd3R09IhD8XCkBNqBaZoMgZcWOqZ7TYfAjcGws7leDvWgLWwiThJqp1es52VQDzBfQSf6owzqAeYr6ER/lEE9wJ1W6D+h9kk5PB81LHbt2nVI3nX58uXzvtiOOeaY/l+oPfaa17zm1C9/+ctLZx5ftWrV/T//8z///fe85z3f+dSnPnXj1q1bv3LnnXd+ae/evV+s6/oLU9/e/va3b23g1OGwBNqBBwmz0y9tCIG3ZQyGj811oCk2ESdNbOrCfFnPy6AeYL6CTvRHGdQDzFfQif4og3qA+YrBEWqflMPzUcNg2bJlh1xUO3funHcGds+ePUXlZzdv3rzk/e9//4qpx4455pixd73rXd/9zne+89X//b//922vfvWr737GM56xZ9WqVftPPPHEscWLF9czH2fv3r1Ffd8MDxcmEBGDCdJu3DI663GB4OFTWs3bMgbDx2YV0DSbiJOWrFoykHFoH+t5OdSDYWe+gjT9UQb1APMVdKI/yqAeYL5i8ITaJ+XwfFTbHX/88Q/MPHbXXXfN+zbJ9913X2O3WL7//vuruX7N//2///eEsbHpPfWud73ru695zWvuWrCg+yjwkfybQT8JtAMDC+tu2HRooF0gePiUVvO2jMHwsVkF5MImIsyf9RwohfkK0vRHOdSDYWe+gjT9UQb1APMVzRFqn+T5qP46+eSTDwm0f/WrX10838f7zne+M+evPfroow95xfPR0dE5h9O///3vzzlU/qlPfWr51Pcf/ehH71u3bt09c32c7373u8JIZEmgHYZck2Hd9WtHBIKHTGkh8LaMwfCxWQXkxiYizJ31HCiF+QrS9AdQCvMVpOmPMqgHmK9onlD7JM9H9c+55567e+axz33uc0tn+9zDueWWW476wQ9+cPRcv+644447MPPYPffcM+dw+o033jjnMP327dtHpr5/7rnn3jfXx4iI+MIXvrBsPl8H/SbQDkOsybBuRMS6NSOzHu/VGALBeSktBN6WMRg+NquAXNlEhO5Zz4FSmK8gTX8ApTBfQZr+KId6MOzMV+RCqH2S56P6Y+3atXsXLVo07RXS//mf//n4+TzW3/zN35wwn6878cQTDwm033zzzXMO+XziE5+Yc6j87rvvPupw53I4mzdvXjKfV6aHQRBohyHVdJi9VwSCy1BaCHzjllFhdopkswrInU1EODzrOVAK8xWk6Q+gFOYrSNMfQCnMV+RGqH2S56N6b9GiRfWTn/zknVOPfeUrX1m6efPmJXN5nLGxsXjf+963Yj7ncPbZZ++beeyzn/3snF4l/oEHHoi//du/nfP4S5YsmdZAd95551Gpz0257LLLHjrXr4FBEWiHISTMzqCVFgLfsGm0r2O4dukHm1VAKWwiQpr1HCiF+QrS9AdQCvMVpOkPoBTmK3Il1D7J81G994u/+Is/mHnsV3/1V0+dy2NcfvnlK2688cZj5jP+wx/+8Ace+tCH7p967J/+6Z9OeOCBB7p+jD/8wz88+bbbbptzQOikk06aNu5111137IED3b9I+4c+9KFjr7zyyofMdVwYFIF2GDJNhtnXrx3pyeN3GkMguL2arLkwO7mzWQWUxiYiHMp6DpTCfAVp+gMohfkK0vQHUArzFbkTap/k+ajeuvjii+897bTTpgVvNm/efOwv//IvP7ybr7/mmmuW/vZv//acAvAznXfeefdOff8//uM/Rt785jd39crnH/7wh49985vf/Ij5jPukJz1p19T3b7vttkUbNmw4qZuv/bd/+7djXvWqVz2yruv5DA0DIdAOQ6TJMPvbnrMo1q3pTaB9UN8H+RBmhzSbVUCpbCLCJOs5UArzFaTpD6AU5itI0x9AKcxXlEKofZLno3pn4cKF8c53vnNbVVXTjr/rXe9a+fKXv3z1D37wg4Wzfd3Y2Fj88R//8YqXvOQlp+/du3dBRMTixYvndRHO9irxb3nLWx6xYcOGFWNjsz/knj17qje+8Y0rX/ayl50+OjpaLVq0aM7J8osvvviumcd++7d/+9Q//MM/PCk17gMPPBBvfetbT7rgggvOuOeee46KiFi2bFn3L+sOA3RU0ycADEbTYfZfW7sodg5gjF6YGOPXevJoHKlB1HzjltE47axDjwuzkzubVUDpJjYRt12+LXbfuPvB4xObiKsvXR1LVi3p+3msuGBFRIxvGk418f7Ex6EfrOdAKcxXkKY/gFKYryBNfwClMF/RKzuu2jGQ5z8mQu1bL9saB3ZPZmgnQu2rLlkVCxb19zV5i3g+6u/7PvxAfPWrXz3mzDPPfGwvHutNb3rT937mZ37m3tk+9qIXvei+n/u5n7tj48aNJ089/v73v/8hV1111QnPfvaz7zn33HN3n3zyyfvvu+++hd/85jcXf+QjHzn+1ltvfTCgc+aZZ+4944wz9v7jP/7jiXM9t/POO2/Ps5/97Hv+9V//9fiJYwcOHIhLL7101bvf/e6TL7zwwnse/ehH7xsZGal/8IMfHPXFL35x6Sc/+cnj7rrrrgfzum9+85tvufTSS1fNZdwXv/jF9z3hCU/Y9fnPf37ZlHGr3/qt3zrtL/7iLx76ghe84O7HPvax+4455pixO+6446ivfvWrSz7+8Y8f/4Mf/ODoic9/yEMe8sBrXvOa7b//+78/r1eJh34SaIchkEOYvfQxaMagav72m0bjT1/R3zGE2ek1m1WQtnPzlRFxYdOnQZeK2EQMoXb6w3oOlMJ8BWn6AyiF+QrS9AdQCvMVvTTI5z+E2ielno9qi7179y74xje+0ZN/yDvvvLNjtvU973nPrXffffdRMwPpu3fvXvCP//iPJ3YKqj/kIQ954IMf/OC33vjGN54y3/N773vfu+0JT3jC0qlh8YiIm2++ecnll1/e8d/gv/yX//L99evX75hroD0i4m//9m+/+5SnPOWsmf8+27ZtW/Tnf/7nh94GYIply5Yd+OAHP3jzl770pf5f7DAP/V0JgMa1PWguzN5eTdZ8/dqRoq5dho/NKkhL9Qfz53aPbvdIf1jPgVKYryBNfwClMF9Bmv4ASmG+oh8G+fzHRKh94dKF045PhNo9H8VcLVy4MD7wgQ9897/+1/+6feHChXW3X/eoRz1q36c//embzjzzzNEjGf+000574Nprr73ptNNO6zpsdvTRR9e/8zu/c9tf/MVf3DbfcU8//fTRj33sY99YvXr1vrl83erVq/d98pOfvOlpT3vanvmODf0m0A4t1vaguTB7ezVd83VrRvo6hjA7R8JmFaQJs/eHTcRxQu30kvUc0sbvtEIuzFeQpj+AUpivIE1/AKUwX9FPQu3jcnk+irk56qij4s/+7M++d91119343Oc+955FixYlg+2nnHLK6Jve9KbbvvrVr379cY97XE9CYmeeeebo1772ta/95m/+5vdOOumk/anPO/roo+sLL7zw7uuvv/7rv/d7v/f9Ix33nHPO2bdly5Ybf+M3fuN7K1asSI4bEfHIRz5y3+///u/feuONN379CU94wpxC8DBoHW/LAJSr7UFzYfb2akvNhdnpB5tVkCbM3j9u9zhpkLffpL2s55A22R/vafpUCPMVdKI/IG38j9MubPo0OMh8BWn6AyiF+Yp+qev6C40N/juNjTzpF5s+gYhYFxF/3/RJzN9jHvOY0Uavoyme8pSn7P3Yxz727bvvvnvBv/7rvy675ZZbRu64446jjj766PqUU07Z/8QnPnFPv8Lcy5Ytq9/61rduf+tb37r9s5/97JLPf/7zS3bs2HHUnj17Fhx33HEHzjrrrPuf9axn7TruuOMO+YuNI/n3O+6448b+8A//cPsf/MEfbP/c5z63ZPPmzcfs2LHjqL179y449thjD6xevXr03HPP3fOYxzzmkFeif+1rX3vna1/72jvnOuYHPvCBrRGxdb7nDIcj0A4t1Pag+aDGYPCE2SFt1w3X2KyCBGH2/hNqnyTUzpHw5BOkWc/zYr6CNP0Baf44LS/mK0jTH0ApzFcAc3PCCSeMvexlL9vZ1PhPetKT9j7pSU8azMv8H7RgwYJGxoV+6G8SARi4pkPgxmC+mqz5+rUjPXn8TmO4rjhS469uNZ3NKhB+GyS3e5w0yNtv0h6efII063lezFeQpj8gzXqeF/MVpOkPSJvtuSiaY74CAIaNQDu0TBtC4G0Zg+41XfN1a3oTaHddMUg2q6DzZi79IdQ+SaiduXCnFUgTfsuLJ8shTX9AmvU8L+YrSNMfkGY9z4v5CgAYRgLt0HKlhcDbMgbda0vNBzUGRNisggibuYO0cOnCae8LtU8Saqdb7rQCs/NkeV78fAVp+gPSrOd5MV9Bmv6ANOt5XsxXAMCwEmiHFisxrNuGMeheW2re5Bi0164brpn1uM0qsJk7aKsvXZ11qH3f7fv6fg4RQu30lvkK3GklN36+gjR3WoE04be8WM8hTX9AmvU8L+YrAGCYCbRDS7UlrFvaGHSvLTUXZqcfdm6+0iu5QoLN3MFbsmpJ1qH22997e9/HnyDUTi+Yr8B6nhv1gM78fg6z88dpebGeQ5r+gDRh9ryYrwCAYSfQDi3UlrBuaWPQvbbUXJidfkhtVi0/9yKbVQw9m7nNyTrUvvdA38eeSqidbrjTCqRZz/OiHjB3+gOsH7lRD0hzpxVIE2bPi/UcAECgHVqnLWHd0sage22puTA7/dBp83DZ2ecP+GwgLzZzm5dzqH3QhNrpxJ1WIM16nhf1gLnTH2D9yI16QGd+P4fZudNKXqznAADjBNqhZUoK627cMtqK0DHda3vQXJidI+GVMCDNZm4+Sgi177t9X9/PIUKondm50wqkWc/zoh6Q5k4rkGb9yIt6wNzpD7B+5EY9AAAmCbQDhxhUCHzDptG+jiHMnpe2B80HNQbtJMwOaTZz85N7qP32994ee7ft7fs5RAi1M507rUCa9Twv6gFp7rQCadaPvKgHzJ3+AOtHbtQDoHkf+MAHttZ1/YWJt+9973s3NH1OMMwE2oFpmgyBlxY6pntNh8CNQc46vZIrDDubufnKKdS+5JFLph0/sPdAbL1sq1A7A+WP0yDNep4X9YA0d1qBNOtHXtQD0txpBdKsH3lRDwCAQwm0Aw8SZqdf2hACb8sY5KXTZpVXcmXY2czNXy6h9lNeecohxw/sFmpncITZIc16nhf1gDR3WoE060de1APS3GkF0qwfeVEPAIDZCbQDETGYIO3GLaOzHhcIHj6l1bwtY5AXm1WQpj/KkUWofWT2X2uF2hkEd1qBNOt5XtQD0vxxGqRZP/KiHpDmTiuQZv3Ii3oAAKQJtAMDC+tu2HRooF0gePiUVvO2jEFebFZBmv4oTw6h9hShdvrJnVYgzXqeF/WANGF2SLN+5EU9IM2dViDN+pEX9QAA6EygHYZck2Hd9WtHBIKHTGkh8LaMQV5sVkGa/ihXTqH2JY9cMu39nELttIf5CtL0R17UA9LcaQXSrB95UQ9I88dpkGb9yIt6AAAcnkA7DLEmw7oREevWjPR1DIHgvJQWAm/LGOTFZhWk6Y/y5RJqP+WVp8TSs5ZOO5ZLqJ12MF9Bmv7Ij3rA7NxpBdKs53lRD0gTZoc060de1AMAoDsC7TCkmg6z94pAcBlKC4Fv3DIqzE7P2ayCNP3RHjmE2heMLIhVl6wSaqcvzFeQpj/KoB5gvoJO9Ed+1ANm504rkGY9z4t6AAB0T6AdhpAwO4NWWgh8w6bRvo7h2h0+NqsgTX+0Txah9kVC7fSe+QrS9EcZ1APMV9CJ/iiDeoA7rUAn1vO8qAcAwNwItMOQaTLMvn7tSE8ev9MYAsHt1WTNhdk5EjarIE1/tJdQ+ySh9nYwX0Ga/iiDeoD5CjrRH2VQDzBfQSf6Iz/qAQAwNwLtMESaDLO/7TmLYt2a3gTaB/V9kA9hdkpl8xDS9Ef7CbVPEmovm/kK0vRHGdQDzFfQif4og3qA+Qo60R9lUA/maf+U/68jIsbGxuT9AOiLKWtMPeXw6KDGt8DBkGg6zN6GMWjGIGq+ccvs625p1y55sXkIafpjeAi1T1pxwYqBjENvma8gTX+UQT3AfAWd6I8yqAeYr6AT/VEG9eAI7ImIsYiIuq4PREQcOHBA3g+AvphYYybWnBhfg/YManwLHAyBtgfNhdnba1A137Dp0EB7adcuebF5CGn6Y/gItVMq8xWk6Y9yqAfDznwFafqjDOoB5ivoRH+UQT04Euecc85YROyMiKjren9ExJ49e5Y0elIAtNaePXuOiZhccyLi3nPOOafu8CU9JdAOLdf2oLkwe3s1WfP1a0eKunbJi81DSNMfw0uondKYryBNfwClMF9Bmv4oh3ow7MxXkKY/yqAe9MjnIiLGxsbui4i47777ljd7OgC01c6dO4+NmFxz4uAaNCgC7dBibQ+aC7O3V9M1X7dmpK9jCLO3l81DSNMfCLVTCvMVpOkPoBTmK0jTH0ApzFeQpj/KoB700NUREQcOHNgZEbFnz56l+/fvX9j5SwBgbvbv379w7969SyMm15yIuGaQ5yDQDi3V9qC5MHt7taXmwuzDx+YhpOkPJgi1kzvzFaTpD6AU5itI0x9AKcxXkKY/yqEe9NCmiNhX1/X+uq73RkTcdtttDx8bG6saPi8AWmJsbKy67bbbHh4RUdf13rqu90fE3oj4zCDPQ6AdWqjtQfNBjcHgCbNTKpuHkKY/mEmonVyZryBNfwClMF9Bmv4ASmG+gjT9AcPpnHPO2RcR10ZE7N+///sRMbZnz56l27ZtO9UrtQNwpPbv379w27Ztp+7Zs2dpRIwdXGsiIq4755xzBvoqwUcNcjCg/5oOgRuD+Wqy5uvXjvTk8TuN4bpqL5uHkKY/SJkItW+9bGsc2H3gweMTofZVl6yKBYv6+/fXE6H2bZdvi9037n7w+ESoffWlq2PJqiV9PQfyYb6CNP0BlMJ8BWn6AyiF+QrS9AcMvb+KiKeMjY3F6OjoLSMjI6ft2bNn6Te/+c0zlixZsnv58uX3HXPMMXsWLlw4tmDBgv6/chAAxRobG1tw4MCBBXv27Dlm586dx+7du3fiVeDGRkdHbxkbG9sbEffF+NozUALt0DJtCIG3ZQy613TN160ZiU/2eQzXVTvZPIQ0/cHhCLWTC/MVpOkPoBTmK0jTH0ApzFeQpj+Ac84555tf+MIXfjki/mwi1H700Uc/tKqqJXv37l06JYwIAHNW1/Xe/fv3f39KmP2XzznnnG8O+jz6mw4AGldaCLwtY9C9ttR8UGOQD5uHkKY/6NZEqH3h0ul3xJwItY/d3/8XEZkItS89a/pe70Sofe+2vX0/B5pjvoI0/QGUwnwFafoDKIX5CtL0BzDhnHPO+XpE/HJE3Dc2Nrb3/vvv33r//fd/64EHHrhjbGxsb13XD0RE3fBpApC/uq7rB8bGxvY+8MADd9x///3fuv/++7fOCLN/vYkT8wrt0GIlhnXbMAbda0vNBznGr/Xk0ThSNg8hTX8wV16pnaaYryBNfwClMF9Bmv4ASmG+gjT9Acx0zjnnfP0LX/jCf4mI/y8inlbXdTzwwAN3RsSdzZ4ZAIXbGxHXRcRfNfHK7BO8Qju0VKlh3dLHoHttqXmTY9AMm4eQpj+YL6/UzqCZryBNfwClMF9Bmv4ASmG+gjT9AaScc8453zznnHPeEBHPiYhLI+LjEXF3RPT/yRQA2mIsxteOj8f4WnL+Oeec84Ymw+wRXqEdWqktYd3SxqB7bam5MPvwsXkIafqjvXZctSNWXLCi7+N4pXYGxXwFafoD0nZuvjIiLmz6NDjIfAVp+gMohfkK0vQH0I1zzjlnX0R84uBbfOELX6gi4piIGGnyvADI3mhE7DnnnHPqpk9kJoF2aJm2hHVLG4PutaXmwuzDx+YhpOmPdtt+xfaICKF2ofZWMF9Bmv6AtMn+eE/Tp0KYr6AT/QGUwnwFafoDmK+DwcTdB98AoDj9TQIAA1dSWHfjltFWhI7pXtuD5sLs7WXzENL0x3DYfsX22HHVjoGMNRFqX7h04bTjE6H2sfv7f8fMiVD70rOWTjs+EWrfu21v38+B3jNfQZr+gLRUf9AM8xWk6Q9IG7/TCrkwX0Ga/gAAYJgJtAOHGFQIfMOm0b6OIcyel7YHzQc1BoNn8xDSdt1wjf4YIkLt44Tay2Q9hzT9AWnC7HkxX0Ga/oA063lezFeQpj8AABh2Au3ANE2GwEsLHdO9pkPgxmC+bB5CZ7O9upX+aDeh9nFC7WWxnkOa/oA04be8mK8gTX9AmvU8L+YrSNMfkOZOKwAwPATagQcJs9MvbQiBt2UMumfzEOZOfwwHofZxQu1lsJ5DmjutQJrwW16s55CmPyDNep4X8xWk6Q9Is54DwHARaAciYjBB2o1bRmc9LhA8fEqreVvGoHs2D2Hu9Ed7rbx45SHHsgq1jwq1MzvrOXTmTiswu07rB4NnPYc0/QFpwm95MV9Bmv6ANOs5AAwfgXZgYGHdDZsODbQLBA+f0mreljHons1DSNt1wzWzHtcf7bbighVZh9pvf9/tAzkHofayWM9h7vQHWD9yox6Q5k4rkCb8lhfrOaTpD0izngPAcBJohyHXZFh3/doRgeAhU1oIvC1j0D2bh5C2c/OVXsl1iOUcat/7ncEFyYXay2A9h7nTH2D9yI16QGd+P4fZudNKXqznkKY/IE2YHQCGl0A7DLEmw7oREevWjPR1DIHgvJQWAm/LGHTP5iGkpfpj+bkX6Y8hknOofZCE2vNmPYc0d1qBNOtHXtQD5k5/gPUjN+oBae60AmnC7AAw3ATaYUg1HWbvFYHgMpQWAt+4ZVSYfcjYXIe0TpuHy84+f8BnQ9NKCLWPjY71/RyE2vNkPYc0d1qBNOtHXtQD5k5/gPUjN+oBnfn9HGbnTisAgEB7AaqqOrWqqudXVfULVVX9elVVb6iq6jVVVf1UVVVrqqpq7uUJKZIwO4NWWgh8w6bRvo7h2s2LzXVI80oYzCb3UPvt77s9xu4Xah821nNIc6cVSLN+5EU9IM2dViDN+pEX9YC50x9g/QAAxgm0Z6iqqjOrqnpdVVUfrqrq7oi4JSKuioh3R8SGiHhLRLwrIv4uIr4UEfdWVfXPVVW9sKqqxmpaVdXWqqrqHr39ZlPfR9s1GWZfv3akJ4/faQyB4PZqsubC7O1lcwTShNnpJKtQ+5Lpofa939kb2y7fJtQ+RKznkOZOK5Bm/ciLekCaO61AmvUjL+oBc6c/wPoBAEwSaM9EVVVLqqp6U1VVN0TEjRFxeUT8REQc38WXL42ICyPinyLiK1VVPaFf50nZmgyzv+05i2Ldmt4E2gf1fZAPYXb6weYIpHV6JVeYkEuo/ZRXn3LI8d037hZqHxLWc0jzx2mQZv3Ii3pAmjutQJr1Iy/qAWnutAJp1g8AYCqB9nw8NCL+R0Q8/ggf53ERcX1VVb9y5KdEmzQdZm/DGDRjEDXfuGV01uOlXbvMjc0RmF2nzUOv5MpMOYTaF5+yeNbjQu3t58kOSBNmhzTrR17UA9LcaQXSrB95UQ9Ic6cVSLN+AAAzHdX0CdCVb0XEpyPi5oi4IyJ2R8SJEbEmIl4QEafO+PyjIuJPq6oarev6fw3wPGe6OyJumefXfr+XJzLs2h40F2Zvr0HV/O03jcafvqK/Ywiz58/mCHSzeVgP/qTI3ooLVkTEeIh9qon3Jz7ehIlQ+6pLVsWCRf39e+6JUPu2y7fF7ht3P3h8ItS++tLVfR1/2HiyA9LcaQXSrB95UQ9I88dpkGb9yIt6QNpEfyw7dXqcY/m5F8WCRz+nobOCPFg/AIDZCLTn6+sR8VcR8bd1XX8v9UlVVR0VEa+KiD+OiGUzPvynVVV9qq7rb/btLDv7x7qu/7+GxuagtgfNhdnba5A1n7GPFOvXjsSvnlnOtcuRszkCNg85MjmF2hcuWTjt/ZxC7fE7fR1+qJivYHaHv9PKgcGfFGTCz7t5UQ9IE2aHNOtHXtQD0g53p5VdbujIELN+AAAp/X02n/n4ZEQ8o67rx9V1vaFTmD0ioq7rB+q6fndEPDUi7pnx4ZGI+KP+nCYlaHvQXJi9vZqu+bo1I30dQ5g9LzZHwOYhvbHighWx8uKVhxzffsX22HHVjoGdxymvPiUWLp091D52/1jfx58ItS89a+m04wd2C5H2k/kKrOfQif7Ij3rA7NxpBdKs53lRD0jzx2mQZv0AADoRaM/HvRHxzLqun1XX9bVz/eK6rr8SEb8wy4cuqKpqcC+HSDbaHjQXZm+vttRcmL0MNkfA5iG9lUOoffEpi2P1pauzDLXTH+YrsJ5DJ/qjDOoB3dxpBYaX9Twv6gFpwuyQZv0AAA5HoD0TdV3fXdf1p4/wMT4QEV+ZcXhhRFxwJI9LedoeNB/UGAyeMDuDZHMEbB7SHzmE2pesWiLUPiTMV2A9h070RxnUA8xX0In+yI96wOzcaQXSrOcAQDcE2tvnqlmOPXLgZ0Fjmg6BG4P5arLm69eO9OTxO43husqPzRGGnc1D+kmofZxQe3+Zr8B6Dp3ojzKoB5ivoBP9UQb1AHdagU6s5wBAtwTa2+eWWY4dmiShtdoQAm/LGHSv6ZqvW9ObQLvrCiiFzUMGQah9nFB7f5ivwHoOneiPMqgHmK+gE/1RBvUA8xV0oj8AgLkQaG+fY2Y5tnfgZ0E2SguBt2UMuteWmg9qDIAjZfOQQRJqHzcRaqd3zFcMO+s5pOmPMqgHmK+gE/1RBvUA8xV0oj8AgLkSaG+fR89y7D8GfhZkocSwbhvGoHttqXmTYwDMhc1DmiDUPm7BIr9+A71hPYc0/VEO9WDYma8gTX+UQT3AfAWd6A8AYD48o94iVVUdFREvnuVDnxv0uRz0qKqq/rCqqmurqrqlqqq9VVXtPvj/X6qq6q+qqnp1VVWnNnR+rdaWsG5pY9C9ttRcmB0ohc1DmiTUDtAb1nNI0x9AKcxXkKY/yqAeYL6CTvQHADBfAu3t8hMRMTMlcldE/FsD5xIR8eMR8RsR8bSIODUiFkfEMQf/f01ErIuI90TEd6uq+ruqqtY0c5rt05awbmlj0L221FyYHSiFzUNyINQOcGSs55CmP4BSmK8gTX+UQz0YduYrSNMfAMCREGhviaqqFkfEW2f50P+p6/qBQZ/PHC2MiJ+KiM9XVfXGqqqqpk+oZG0J65Y2Bt1rS82F2YFS2DwkJ0LtAPNjPYc0/QGUwnwFafoDKIX5CtL0BwBwpI5q+gTombdGxBkzjt0dEf+zgXOZaiwi7oiInQf//yEH32b7Y4qFEfH7EfGEqqpeVtf1gV6fTFVVJ0fESXP8skdNfWfXrl2xc+fO3p1Uj/3nZz0yenF2G7eMxttvGo1TT51+fP3akVi3ZmReY+weOXna+3/7nRPi7Ted3NMxZjqi7yPjOhdn8cMjoj/X1UzzGWPmtTnz/V6MMVepMXKef0qzcknd9Cl0tGJx3fH9nLgue6fX1+WuG66JsW9dHctmTCbLz70olp19fkTMbTzX5XA6eUHndXHOj3fhyfGw5Q+LHR+dEWDfFHH08qPjhKedMKfHO3HBiR3fn9UPRTz0TQ+N2997exzYO+XXjl0RD/ztA3HKK0+JBSO9//tv12XvWMd7x3XZO/26Lnu1nrsuh1Pb58te/7x7OK7N3sn52ixpvoxwXfZSP6/LI52vXJfDaxjmy0Gt567L3hmG63JQXJe9M4jrcr7zletyeA3TfNnv9Tzn63LXrl1NnwIAtEZV1/n+AEV3qqp6aUS8f5YP/Xxd14f++WP/zmNrRDwiIj4dEVdFxKci4ut1Xe+Z8XnHR8RTI+L/i4iLYvZw+5/Xdf1f+3CO/z0ifvdIHuMd73hHnHbaab05IQAAAAAAAAAAoDi33HJLvPa1r5166PF1XX+tqfMBgJJ5hfbCVVX1YxGxcZYPfWCQYfaDNkTEP9Z1fWunT6rr+p6I+JeI+Jeqqn44Iq6IiDNnfNprqqr617quP9CXMwUAAAAAAAAAAAAAGtf7e6gzMFVVPTLGg+FLZ3zopoh41aDPp67rPztcmH2Wr/lKRJwbEV+e5cNvqapqYU9ODgAAAAAAAAAAAADIjldoL1RVVQ+PiGsiYuWMD90WEc+v6/q+wZ/V/NR1fV9VVS+KiBtjejj/MRHxooj4UA+He1dE/L85fs2jIuLDE++ce+65cdZZZ/XwlHrsXU+e15dt3DIaGzaNHnJ8/dqRWLdm5EjPKiIi/vY7J8TDLrz0wfff8pa3xPbt23s6Rk+/j//67z05JyIe//jHT3s/t5rvHjk5Nj/q9Q++f+63/ySWjt7R0zEOp+sxXJc989w/ubbpU+hoxeI6/vOZYw++/+6bFsSOfVWDZzS7XTdcE5ve+z+aPo3WONLrctcN18TOzVcecnz5uRfFsrPPP6LHjijnuoyI+Pjrn970KbTGSz78kr6Pcfd1d8eOj+445PiK56+IE552QsevPXHBifGzy372wff/767/G3eN3TXnc9h3+764/b23x4G9B6YdX/LIJXHKK0+JBSNH/vfgH3zxB4/4MRhnHe8d82Xv9Oq67Nd67rocTm2bL/v98+7huDZ7J+drs6T5MsJ12Uu9vC57PV+5LodXG+fLptZz12XvtPG6bIrrsnf6cV32ar5yXQ6vNs+Xg17Pc74ub7zxxqZPAQBaQ6C9QFVVnRzjYfYfmvGh70fEs+u63jb4szoydV3fWlXV5RHxxhkfuiB6GGiv6/qOiLjjsJ84RVVN/6F92bJlsXz58l6dUu/t+96cv+SPNt0fv371/Yccf9tzFsWvnrkoYt+Rn9Yfbbo/3n7TyfGnF04e2759e7zuzDt6OkZPv4+c61yYW2+dvHlDr6+rfly7S0fviOUHe2lQ/dH1GK7Lntm+N9/Nwtns2Fdld847N18Zd3/yvbH8/Zc3fSqtcSQ1nqjHTCec9+pY8OjnxK69R3Jms8vxupyQ9c9rhbljbE4/Ps/PUyP279wf26/YPu3wre++NVbuXBkrLljR9UPdNXbX/M55ZcTCn1kYt152axzYPSXUfmvE9+74Xqy6ZFUsWHRkoXbXZe/kOvekmC+HQy9qPMj13HU5HHKtcUqn67KJn3dncm32TknXZs7zZYTrspd6VedBzFeuy+GRc51n6ua6bHI9d132Ttuuyya5Lnun13Xu53zluhweOdd5prlcl02s5zlfl8uWLWv6FACgNY78JeYYqKqqHhLjYfYzZ3xoR4yH2b85+LPqmb+d5dizB34WQ6ZTkPbX1i7q6xjr1470fYxefh8cuUFcV8aAwUhtVtGMTpuHy8+9qIEzok32bhtAOiwiVlywIlZePPMGVBHbr9geO6469NXb+2HJqiWx+tLVsXDpwmnHd9+4O7Zdvi3G7h9LfCWUabZXUaI51nNI0x9AKcxXkKY/gFKYryBNfwAA/STQXpCqqk6IiKsj4uwZH7orIs6v6/prgz+r3qnr+usR8YMZh09t4lyGRZNh3YiIdWtG+jqGQHBeSguBt2UM6Adh9rzYPKTftl62Vag9hNppH+t5XqznkKY/IM0fp+XFfAVp+gMohfkK0vQHANBvAu2FqKrquBgPs//ojA/dExHPrev6ywM/qf74jxnvjxz83umxpsPsvSIQXIbSQuAbt4wKs0OC8FtebB4yCAd2HxBqP0ionbawnufFeg5p+gPSrOd5MV9Bmv4ASmG+gjT9AQAMgkB7AaqqWh4RH4+Ic2Z8aGdEPK+u6y8M/qz6Zvcsx5YM/CxaTpidQSstBL5h02hfx3DtUipPlufF5iGDJNQ+Said0lnP82I9hzT9AWnW87yYryBNf0CaO63kxXwFafoDABgUgfbMVVV1bER8LCLOnfGh+2I8zL558GfVVyfNcuzOgZ9FizUZZl+/dqQnj99pDIHg9mqy5sLs0HmzisGzeUgThNonCbVTKuG3vFjPIU1/QJr1PC/mK0jTH5BmPc+L+QrS9AcAMEgC7RmrqmpZRHw0Ip4840O7IuKCuq7/ffBn1T9VVS2NiNNmHL6nruv9TZxPGzUZZn/bcxbFujW9CbQP6vsgH8Ls0CybVXlRD5ok1D5JqJ3SeLI8L9ZzSNMfkGY9z4v5CtL0B6RZz/NivoI0/QEADJpAe6YOhrs/EhFrZ3xod0S8oK7rzwz+rPru2RExM/H85SZOpI2aDrO3YQyaMYiab9wyOuvx0q5d6AebVXlRD5qw9Kyl094Xap8k1E4p3GklL9ZzSNt1wzX6AxKE3/JiPYc0/QFp1vO8mK8gTX8AAE0QaM9QVVXHRMQ/R8TTZnxoT0RcWNf1dYM/q4H4jVmOXTXws2ihtgfNhdnba1A137Dp0EB7adcu9IPNqryoB01ZdcmqrEPtd19390DOQaidUlk/8qIe0NnOzVceckx/gD9Oy431HNL0B6QJs+fFfAVp+gMAaIpAe2aqqlocER+OiGfO+NDeiHhRXdefHvhJDUBVVb8ch74a/VhEfLCB02mVtgfNhdnbq8mar187UtS1C/1gsyov6kGTFixakHWofcdHB/Mq7RFC7ZTH+pEX9YC50x9g/ciNekCaO61AmjB7XqznkKY/AIAmCbRnpKqqkYi4MiLOn/GhiTD7J/o8/qeqqqpnvP1/XXzdc6uqev4RjPuqiHj7LB/aWNf1N+f7uLQ/aC7M3l5N13zdmpG+jiHMTu5sVuVFPchB7qH2QRJqpxTWj7yoB8yd/gDrR27UAzpzpxWYnTut5MV6Dmn6AwBomkB7JqqqOioi/iEiLpjxoX0R8ZN1Xf/r4M+qa4+NiKuqqvpiVVWvrarq4d18UVVVj62q6oqIeG9ELJzx4Tsj4k09Ps+h0vaguTB7e7Wl5sLslMpmVV7Ug5wItU8Said31o+8qAek7brhmlmP6w+wfuRGPWDu9AdYP3KjHpDmTisAQA6OavoEeNDFEfHiWY7vi4jLqqq67Age+/N1Xf/CEXx9t3704NvlVVXdGBFfjoivRcSOiLg3IuqIODEiHh0RT4uIJ0RENcvj7ImIC+u6/t4AzrmV2h40H9QYDJ4wOzTLZm5e1IMcTYTat12+LXbfuPvB4xOh9tWXro4lq5b0/TxWXLAiIiK2X7H9kI/dfd3dEU/t+yk8GGrfetnWOLD7wIPHJ0Ltqy5ZFQsW+RtyBs/6kRf1gLSdm6+MsW9dHfHK86Yd1x9g/ciNesDc6Q+wfuRGPaAzd1oBAHIg0J6PoxPHjz/4diTuOcKvn6sqxl+1/bHz+NrbIuJn6rr+bG9PaXg0HQI3BvPVZM3Xrx3pyeN3GsN1Re5s5uZFPchZbqH22DT9+I6P7oj9O/dPfryPhNrJjfUjL+oBaRP9sezUU6cdX37uRbHg0c9p6KwgD9aPvKgHpO264ZqINecdclx/gPUjN+oBc6c/AIAmeGadXDwQEX8dET9c1/W1TZ9MydoQAm/LGHSv6ZqvW9ObQLvrilLZzM2LelCCiVD70rOWTjs+EWrfu23vQM5jxQUrYsXzDw2ub79ie+y4asdAzmEi1L5w6cJpxydC7WP3jw3kPMD6kRf1gLRUf0RELDv7/AGfDeTF+pEX9YC0nZuv9EqukGD9yIt6wNzpDwCgKQLt9MJ7IuInIuKPI+L6iNjd+dMfNBYRN0TE70fE6rqu19V1fXd/TnF4lRYCb8sYdK8tNR/UGNBrNnPzoh6UJJdQ+wlPO2HW40LtDBPrR17UA9I6hdlh2Fk/8qIekJbqj+XnXqQ/GHrWj7yoB6TtuuGaWY/rDwCgSUc1fQKMq+v6ryLirxo+h2fO8+vui4h/OvgWVVUtiIgfiohVEXFqRJwQEccc/PR7I+LuiLg9Ij5f1/WuIztrOikxrNuGMeheW2o+yDF+rSePBuNs5uZHPSjNRKh92+XbYveNk3/XOhFqX33p6liyaklj57f9iu0RMf5K7v02EWrfetnWOLD7wIPHJ0Ltqy5Z1fdzYDhZz/OiHpAmzA5p1o+8qAekHe5OK7sG87ftkCXrR17UA9J2br4yxr51dcQrz5t2XH8AAE0TaKfn6roei4hvH3yjIaWGdUsfg+61peZNjgFHwmZuGdSDEgi1TzpcqD1+se+nwJCxnudFPSCt0yu5wrCzfuRFPSDNH6dBmvUjL+oBaRP9sezUU6cdX37uRbHg0c9p6KwAAMYtaPoEgN5rS1i3tDHoXltqLsxOqWzmlkE9KMlEqH3pWUunHZ8Ite/dNriXaFvx/EOD69uv2B47rtoxkPEnQu0Lly6cdnxq2B96wXqeH/WA2XWar5adfX4DZwT5sJ7nRT0gTZgd0qwfeVEPSDvcnVYAAJom0A4t05awbmlj0L221FyYnVLZzC2DelCiXELtJzzthFh58cpDjucQaodesZ6XQT3AfAWd6I/8qAfMzp1WIM16nhf1gDR/nAYAlECgHVqmpLDuxi2jrQgd0722B82F2cmdzdwyqAclyyXUvuKCFULttJb1vAzqAeYr6ER/lEE9wJ1WoBPreV7UA9KE2QGAUgi0A4cYVAh8w6bRvo4hzJ6XtgfNBzUGzJfN3DKoB20g1D5JqJ1es56XQT3AfAWd6I8yqAeYr6AT/ZEf9YDZudMKAFASgXZgmiZD4KWFjule0yFwYzDsbK6XQz1oC6H2SULt9Ir1vAzqAeYr6ER/lEE9wHwFneiPMqgHuNMKAFAegXbgQcLs9EsbQuBtGYPhY3MdaIpQ+6SJUDvMl/W8DOoB5ivoRH+UQT3AfAWd6I8yqAeYrwCAMgm0AxExmCDtxi2jsx4XCB4+pdW8LWMwfGxWAU0Tap+0ZNWSgYxD+1jPy6EeDDvzFaTpjzKoB5ivoBP9UQb1APMVAFAugXZgYGHdDZsODbQLBA+f0mreljEYPjargFwItcP8Wc+BUpivIE1/lEM9GHbmK0jTH2VQDzBfAQBlE2iHIddkWHf92hGB4CFTWgi8LWMwfGxWAbkRaoe5s54DpTBfQZr+AEphvoI0/VEG9QDzFQBQPoF2GGJNhnUjItatGenrGALBeSktBN6WMRg+NquAXAm1Q/es50ApzFeQpj+AUpivIE1/lEM9GHbmKwCgDQTaYUg1HWbvFYHgMpQWAt+4ZVSYnSLZrAJyJ9QOh2c9B0phvoI0/QGUwnwFafoDKIX5CgBoC4F2GELC7AxaaSHwDZtG+zqGa5d+sFkFlEKoHdKs50ApzFeQpj+AUpivIE1/AKUwXwEAbSLQDkOmyTD7+rUjPXn8TmMIBLdXkzUXZid3NquA0gi1w6Gs50ApzFeQpj+AUpivIE1/AKUwXwEAbSPQDkOkyTD7256zKNat6U2gfVDfB/kQZoc0m1VAqYTaYZL1HCiF+QrS9AdQCvMVpOkPoBTmKwCgjQTaYUg0HWZvwxg0YxA137hldNbjpV27DB+bVUDphNrBeg6Uw3wFafoDKIX5CtL0B1AK8xUA0FYC7TAE2h40F2Zvr0HVfMOmQwPtpV27DB+bVZC2c/OVTZ8CcyDUzjCzngOlMF9Bmv4ASmG+gjT9AZTCfAUAtJlAO7Rc24Pmwuzt1WTN168dKeraZfjYrIK0VH8wf2P3j/V9DKF2hpH1HCiF+QrS9AdQCvMVpOkPoBTmKwCg7QTaocXaHjQXZm+vpmu+bs1IX8cQZudI2KyCNGH2/th2+Tah9hBqp7es55DmTit5MV9Bmv4ASmG+gjT9AZTCfAUADAOBdmiptgfNhdnbqy01F2anH2xWQZowe//svnG3UPtBQu30gvUc0qzneTFfQZr+gDR/nJYX8xWk6Q+gFOYrAGBYCLRDC7U9aD6oMRg8YXZI23XDNTarIEH4rf+E2icJtXMkPPkEadbzvJivIE1/QJr1PC/mK0jTH0ApzFcAwDARaIeWaToEbgzmq8mar1870pPH7zSG64ojNdurW9msAk+WD5JQ+yShdubDk0+QZj3Pi/kK0vQHpFnP82K+gjT9AWnutJIX8xUAMGwE2qFl2hACb8sYdK/pmq9b05tAu+uKQbJZBZ03c+kPofZJQu3MhTutQJrwW148WQ5p+gPSrOd5MV9Bmv6ANOt5XsxXAMAwEmiHlistBN6WMeheW2o+qDEgwmYVRNjMHaSFSxdOe1+ofZJQO91ypxWYnSfL8+LnK0jTH5BmPc+L+QrS9AekWc/zYr4CAIaVQDu0WIlh3TaMQffaUvMmx6C9dt1wzazHbVaBzdxBW33p6qxD7ftu39f3c4gQaqe3zFfgTiu58fMVpLnTCqQJv+XFeg5p+gPSrOd5MV8BAMNMoB1aqi1h3dLGoHttqbkwO/2wc/OVXskVEmzmDt6SVUuyDrXf/t7b+z7+BKF2esF8Bdbz3KgHdOb3c5idP07Li/Uc0vQHpAmz58V8BQAMO4F2aKG2hHVLG4PutaXmwuz0Q2qzavm5F9msYujZzG1O1qH2vQf6PvZUQu10w51WIM16nhf1gLnTH2D9yI16QJo7rUCaMHterOcAAALt0DptCeuWNgbda0vNhdnph06bh8vOPn/AZwN5sZnbvJxD7YMm1E4n7rQCadbzvKgHzJ3+AOtHbtQDOvP7OczOnVbyYj0HABgn0A4tU1JYd+OW0VaEjule24PmwuwcCa+EAWk2c/NRQqh93+37+n4OEULtzM6dViDNep4X9YA0d1qBNOtHXtQD5k5/gPUjN+oBADBJoB04xKBC4Bs2jfZ1DGH2vLQ9aD6oMWgnYXZIs5mbn9xD7be/9/bYu21v388hQqid6dxpBdKs53lRD0hzpxVIs37kRT1g7vQHWD9yox4AANMJtAPTNBkCLy10TPeaDoEbg5x1eiVXGHY2c/OVU6h9ySOXTDt+YO+B2HrZVqF2Bsofp0Ga9Twv6gFp7rQCadaPvKgHpLnTCqRZP/KiHgAAhxJoBx4kzE6/tCEE3pYxyEunzSqv5Mqws5mbv1xC7ae88pRDjh/YLdTO4AizQ5r1PC/qAWnutAJp1o+8qAekudMKpFk/8qIeAACzE2gHImIwQdqNW0ZnPS4QPHxKq3lbxiAvNqsgTX+UI4tQ+8jsv9YKtTMI7rQCadbzvKgHpPnjNEizfuRFPSDNnVYgzfqRF/UAAEgTaAcGFtbdsOnQQLtA8PApreZtGYO82KyCNP1RnhxC7SlC7fSTO61AmvU8L+oBacLskGb9yIt6QJo7rUCa9SMv6gEA0JlAOwy5JsO669eOCAQPmdJC4G0Zg7zYrII0/VGunELtSx65ZNr7OYXaaQ/zFaTpj7yoB6S50wqkWT/yoh6Q5o/TIM36kRf1AAA4PIF2GGJNhnUjItatGenrGALBeSktBN6WMciLzSpI0x/lyyXUfsorT4mlZy2ddiyXUDvtYL6CNP2RH/WA2bnTCqRZz/OiHpAmzA5p1o+8qAcAQHcE2mFINR1m7xWB4DKUFgLfuGVUmJ2es1kFafqjPXIItS8YWRCrLlkl1E5fmK8gTX+UQT3AfAWd6I/8qAfMzp1WIM16nhf1AADonkA7DCFhdgattBD4hk2jfR3DtTt8bFZBmv5onyxC7YuE2uk98xWk6Y8yqAeYr6AT/VEG9QB3WoFOrOd5UQ8AgLkRaIch02SYff3akZ48fqcxBILbq8maC7NzJGxWQZr+aC+h9klC7e1gvoI0/VEG9QDzFXSiP8qgHmC+gk70R37UAwBgbgTaYYg0GWZ/23MWxbo1vQm0D+r7IB/C7JTK5iGk6Y/2E2qfJNReNvMVpOmPMqgHmK+gE/1RBvUA8xV0oj/KoB4AAJ0JtMOQaDrM3oYxaMYgar5xy+isx0u7dsmLzUNI0x/DQ6h90ooLVgxkHHrLfAVp+qMM6gHmK+hEf5RBPcB8BZ3ojzKoBwDA4Qm0wxBoe9BcmL29BlXzDZsODbSXdu2SF5uHkKY/ho9QO6UyX0Ga/iiHejDszFeQpj/KoB5gvoJO9EcZ1AMAoDsC7dBybQ+aC7O3V5M1X792pKhrl7zYPIQ0/TG8hNopjfkK0vQHUArzFaTpj3KoB8POfAVp+qMM6gEA0D2BdmixtgfNhdnbq+mar1sz0tcxhNnby+YhpOkPhNophfkK0vQHUArzFaTpD6AU5itI0x9lUA8AgLkRaIeWanvQXJi9vdpSc2H24WPzENL0BxOE2smd+QrS9AdQCvMVpOkPoBTmK0jTH+VQDwCAuRFohxZqe9B8UGMweMLslMrmIaTpD2YSaidX5itI0x9AKcxXkKY/gFKYryBNfwAA0GYC7dAyTYfAjcF8NVnz9WtHevL4ncZwXbWXzUNI0x+kCLWTG/MVpOkPoBTmK0jTH0ApzFeQpj8AAGg7gXZomTaEwNsyBt1ruubr1vQm0O66Gj42DyFNf3A4Qu3kwnwFafoDKIX5CtL0B1AK8xWk6Q8AAIaBQDu0XGkh8LaMQffaUvNBjUE+bB5Cmv6gW0LtNM18BWn6AyiF+QrS9AdQCvMVpOkPAACGResD7VVVLaiqam1VVb9UVdVvVFX16qqqzmn6vGAQSgzrtmEMuteWmjc5Bs2weQhp+oO5EmqnKeYrSNMfQCnMV5CmP4BSmK8gTX8AADBMigi0V1U1MvVtDl/3iojYGhHXRcSfRcQfRMS7I2JzVVVfr6rqWX05YchAW8K6pY1B99pSc2H24WPzENL0B/Ml1M6gma8gTX8ApTBfQZr+AEphvoI0/QEAwLDJPtBeVdWPRMTeKW/fq6rqsAnBqqreEBH/NyIeERHVLG9nRsTHq6r61T6dOjSmLWHd0sage22puTD78LF5CGn6o712XLVjIOMItTMo5itI0x+QtnPzlU2fAlOYryBNfwClMF9Bmv4AAGAYZR9oj4iXx2QIPSLiPXVdd0z2VVX1zIh488GvqTu8LYiIP6mq6gX9OHFoQlvCuqWNQffaUnNh9uFj8xDS9Ee7bb9iu1B7CLW3hfkK0vQHpKX6g2aYryBNfwClMF9Bmv4AAGBYlRBoPz/Gw+cTrujiay6LyTB7xOyv0B4xGWp/Z1VVIz05W2hYSWHdjVtGWxE6pnttD5oLs7eXzUNI0x/DQah9nFB72cxXkKY/IE2YPS/mK0jTH5DmTit5MV9Bmv4AAGCYZR1or6pqUUSsmXJoe13XXzrM1zw9Ip4Q42H1ieD6lyLiJyPizIg4LyI+NOVjERGrIuLnenHO0AaDCoFv2DTa1zGE2fPS9qD5oMZg8GweQtquG67RH0NEqH2cUHuZrOeQpj8gTZg9L+YrSNMfkGY9z4v5CtL0BwAAwy7rQHtEnBERE6+cXkfEZ7v4mlfMeP+bEfG0uq7/sa7rb9Z1/em6ri+KiPfF9Fdx/5lenDCUrskQeGmhY7rXdAjcGMyXzUPobLZXt9If7SbUPk6ovSzWc0jTH5Am/JYX8xWk6Q9Is57nxXwFafoD0txpBQCGR+6B9tUz3v9aF1/z4ph8dfY6Iv57Xdd7Zvm8/xYRE+mDKiJ+vKqqJfM8T2gFYXb6pQ0h8LaMQfdsHsLc6Y/hINQ+Tqi9DNZzSHOnFUgTfsuL9RzS9AekWc/zYr6CNP0BadZzABguuQfaTzn43+rgf2/p9MlVVZ0RESunHNoZEbP+qV5d13dGxNVTHntBRJw97zOFwg0iSLtxy+isxwWCh09pNW/LGHTP5iHMnf5or5UXrzzkWFah9lGhdmZnPYfO3GkFZtdp/WDwrOeQpj8gTfgtL+YrSNMfkGY9B4Dhk3ugfemM9+87zOc/bcr/1xHx8bqu93f4/M/NeP+Mbk8M2mRQYd0Nmw4NtAsED5/Sat6WMeiezUNI23XDNbMe1x/ttuKCFVmH2m9/3+0DOQeh9rJYz2Hu9AdYP3KjHpDmTiuQJvyWF+s5pOkPSLOeA8Bwyj3QvmTG+4em/aZ74sH/Trzq+icP8/nbZrx/fBfnBK3SZFh3/doRgeAhU1oIvC1j0D2bh5C2c/OVXsl1iOUcat/7ncEFyYXay2A9h7nTH2D9yI16QGd+P4fZudNKXqznkKY/IE2YHQCGV+6B9pkJv5mv2D7T2hh/ZfYJ1x3m8/cc/O/E1xzb5XlBKzQZ1o2IWLdmpK9jCATnpbQQeFvGoHs2DyEt1R/Lz71IfwyRnEPtgyTUnjfrOaS50wqkWT/yoh4wd/oDrB+5UQ9Ic6cVSBNmB4DhlnugfefB/04Ezk9NfWJVVQ+JiMdN/dq6rr92mMef+QrwB+Z2elCupsPsvSIQXIbSQuAbt4wKsw8Zm+uQ1mnzcNnZ5w/4bGhaCaH2sdGxvp+DUHuerOeQ5k4rkGb9yIt6wNzpD7B+5EY9oDO/n8Ps3GkFAMg90P69Ge+v6fC5L4iI6uD/1xHx7108/vEH/zvxdbu6PTEomTA7g1ZaCHzDptG+juHazYvNdUjzShjMJvdQ++3vuz3G7hdqHzbWc0hzpxVIs37kRT0gzZ1WIM36kRf1gLnTH2D9AADG5R5o//KU/68i4jlVVS1NfO7PTvm8iIhru3j802a8f8cczg2K1GSYff3akZ48fqcxBILbq8maC7O3l80RSBNmp5OsQu1Lpofa935nb2y7fJtQ+xCxnkOaO61AmvUjL+oBae60AmnWj7yoB8yd/gDrBwAwKetAe13Xt0XE1imHjouI35n5eVVV/XhEPCfGX5l9wke7GGLNjPe/M7czhLI0GWZ/23MWxbo1vQm0D+r7IB/C7PSDzRFI6/RKrjAhl1D7Ka8+5ZDju2/cLdQ+JKznkOaP0yDN+pEX9YA0d1qBNOtHXtQD0txpBdKsHwDAVFkH2g/6+xh/1fX64H9/vaqq/11V1ZOrqjq9qqpXRcTMl6b4Rl3XX+r0oFVVVRHxYzEZgq8j4ubenjrko+kwexvGoBmDqPnGLaOzHi/t2mVubI7A7DptHnolV2bKIdS++JTFsx4Xam8/T3ZAmjA7pFk/8qIekOZOK5Bm/ciLekCaO61AmvUDAJiphED7OyJi18H/nwi1vyoiPhMRN0XE/46IFVM+VkfEH3fxuGsj4iFT3r+pruv7enTOkJW2B82F2dtrUDXfsOnQQHtp1y5HzuYI2DxkfnIItacItbeX+QrS3GkF0qwfeVEPSPPHaZBm/ciLekCaO61AmvUDAJhN9oH2uq63R8RvxXhYPWIyuD71beqrrH8pIrrZ5Zv6E1AdEZt6cb6Qm7YHzYXZ26vJmq9fO1LUtcuRszkCNg85MjmF2hcuWTjt/ZxC7fSO+Qpm504rkObn3byoB6QJs0Oa9SMv6gFp7rQCadYPACAl+0B7RERd138WEW85+O5EgH3q28Tx70bES+u67phUqKpqJCJ+JibD8RER1/T4tKFxbQ+aC7O3V9M1X7dmpK9jCLPnxeYI2DykN3IJtZ/y6lNi4dI8Q+30j/kKrOfQif7Ij3rA7NxpBdKs53lRD0jzx2mQZv0AADopItAeEVHX9Zsi4tkR8YmIGIvpr9B+d0RcHhHn1nW9rYuH++mIODkmw+wPRMRHe3zK0Ki2B82F2durLTUXZi+DzRGweUhv5RBqX3zK4lh96eosQ+30h/kKrOfQif4og3qAO61AJ9bzvKgHpAmzQ5r1AwA4nGIC7RERdV1/qq7r8yPixIj44Yh4akScGREn1XX93+q6vqvLh7ozIl4/5e3n67re2Y9zhia0PWg+qDEYPGF2BsnmCNg8pD9yCLUvWbVEqH1ImK/Aeg6d6I8yqAeYr6AT/ZEf9YDZudMKpFnPAYBuHNX0CcxHXdf3RcRXj+Dr/6mHpwNZaToEbgzmq8mar1870pPH7zSG6yo/NkcYdjYP6acVF6yIiPEQ+1QT7098vJ8mQu1bL9saB3YfePD4RKh91SWrYsGi/v6N90Sofdvl22L3jbv7OtYwMl+B9Rw60R9lUA8wX0En+qMM6gHd3GnlwKFfBEPCeg4AdKuoV2gHDq8NIfC2jEH3mq75ujW9CbS7roBS2DxkELxS+ziv1N4f5iuwnkMn+qMM6gHmK+hEf5RBPcB8BZ3oDwBgLgTaoeVKC4G3ZQy615aaD2oMgCNl85BBEmofNxFqp3fMVww76zmk6Y8yqAeYr6AT/VEG9QDzFXSiPwCAuRJohxYrMazbhjHoXltq3uQYAHNh85AmCLWPW7DIr99Ab1jPIU1/lEM9GHbmK0jTH2VQDzBfQSf6AwCYD8+oQ0u1Jaxb2hh0ry01F2YHSmHzkCYJtQP0hvUc0vQHUArzFaTpjzKoB5ivoBP9AQDMl0A7tFBbwrqljUH32lJzYXagFDYPyYFQO8CRsZ5Dmv4ASmG+gjT9UQ71YNiZryBNfwAAR+Kopk9gvqqq+qGIOCciHhMRxx18O/oIHrKu6/rne3Fu0KS2hHVLG4PutaXmwuxAKWwekpMVF6yIiPEQ+1QT7098vJ8mQu1bL9saB3YfePD4RKh91SWrYsEif/sN5MV6Dmn6AyiF+QrS9AdQCvMVpOkPAOBIFRVor6rq2Ih4TUT8fEQ8upcPHRH1wceFopUU1t24ZbQVoWO61/aguTA7kBubh+RIqB1gbqznkKY/gFKYryBNfwClMF9Bmv4AAHqhmGfoq6p6bkR8LSLeGhGnx3gIvRdvwAyDCoFv2DTa1zGE2fPS9qD5oMYA6JbNQ3K24oIVsfLilYcc337F9thx1Y6BnMNEqH3h0oXTjk+E2sfuHxvIeQB0Yj2HNP0BlMJ8BWn6AyiF+QrS9AcA0CtFBNqrqnpRRPxTRDw8Jl9NvVdvwBRNhsBLCx3TvaZD4MYAho3NQ0og1A7QmfUc0vQHUArzFaTpD6AU5itI0x8AQC8d1fQJHE5VVY+IiL+PiKNjegh96qur746IeyNi/2DPDtpFmJ1+aUMIvC1jAO1n85CSrLhgRUSMh9inmnh/4uP9NBFq33rZ1jiw+8CDxydC7asuWRULFhXxt+BAi1jPIU1/AKUwX0Ga/gBKYb6CNP0BAPRa9oH2iPgfEbEkpgfZ64j4h4j4vxHx2bquf9DQuUFrDCJIu3HLaJx21qHHBYKHT2k1b8sY0A87N18ZERc2fRocZPOQEgm1A0xnPYc0/QGUwnwFafoDKIX5CtL0BwDQD1k/I19V1dER8fKYHma/MyKeVtf1T9V1/c/C7HDkBhXW3bBptO9jCATnr7Sat2UM6IfUZhXNsHlIyVZcsCJWXrzykOPbr9geO67aMZBzmAi1L1y6cNrxiVD72P1jAzkPYLhZzyFNfwClMF9Bmv4ASmG+gjT9AQD0S9aB9ohYGxFLD/7/xCuzX1TX9abmTgnapcmw7vq1IwLBQ6a0EHhbxoB+EGbPi81D+mnvtr0DGUeoHQZv/E4r5MJ6Dmn6AyiF+QrS9AdQCvMVpOkPAKCfcg+0P3LK/9cR8a91XV/X1MlA2zQZ1o2IWLdmpK9jCATnpbQQeFvGgH4QZs+LzUP6betlW4XaQ6id9rGe58V6Dmn6A9L8cVpezFeQpj+AUpivIE1/AAD9lnugfcXB/1YH//vxpk4E2qbpMHuvCASXobQQ+MYto8LskCD8lhebhwzCgd0HhNoPEmqnLaznebGeQ5r+gDTreV7MV5CmP4BSmK8gTX8AAIOQe6C9mvH+rY2cBbSMMDuDVloIfMOm0b6O4dqlVJ4sz4vNQwZJqH2SUDuls57nxXoOafoD0qzneTFfQZr+gDR3WsmL+QrS9AcAMCi5B9rvmPH+UY2cBbRIk2H29WtHevL4ncYQCG6vJmsuzA6dN6sYPJuHNEGofZJQO6USfsuL9RzS9AekWc/zYr6CNP0BadbzvJivIE1/AACDlHug/YaD/60P/vfQNAPQtSbD7G97zqJYt6Y3gfZBfR/kQ5gdmmWzKi/qQZOE2icJtVMaT5bnxXoOafoD0qzneTFfQZr+gDTreV7MV5CmPwCAQcs90P7FiPj+lPef3tSJQOmaDrO3YQyaMYiab9wyOuvx0q5d6AebVXlRD5qw9Kyl094Xap8k1E4p3GklL9ZzSNt1wzX6AxKE3/JiPYc0/QFp1vO8mK8gTX8AAE3IOtBe13UdEf8rIqqDb8+uquqhzZ4VlKftQXNh9vYaVM03bDo00F7atQv9YLMqL+pBU1ZdsirrUPvd1909kHMQaqdU1o+8qAd0tnPzlYcc0x/gj9NyYz2HNP0BacLseTFfQZr+AACaknWg/aC3RcT3IqKOiCUR8YfNng6Upe1Bc2H29mqy5uvXjhR17UI/2KzKi3rQpAWLFmQdat/x0cG8SnuEUDvlsX7kRT1g7vQHWD9yox6Q5k4rkCbMnhfrOaTpDwCgSdkH2uu6vi8ifiYiHjh46OeqqvqtBk8JitH2oLkwe3s1XfN1a0b6OoYwO7mzWZUX9SAHuYfaB0monVJYP/KiHjB3+gOsH7lRD+jMnVZgdu60khfrOaTpNpdekQABAABJREFUDwCgadkH2iMi6rq+NiJeGhH3R0QVEb9fVdU/VFX1Q82eGeSr7UFzYfb2akvNhdkplc2qvKgHORFqnyTUTu6sH3lRD0jbdcM1sx7XH2D9yI16wNzpD7B+5EY9IM2dVgCAHBzV9AkcTlVVTz/4vzsj4rci4q0RsTjGA+4vqarqExHx6Yi4OSLuioj98x3rYHAeitf2oPmgxmDwhNmhWTZz86Ie5Ggi1L7t8m2x+8bdDx6fCLWvvnR1LFm1pO/nseKCFRERsf2K7Yd87O7r7o54at9P4cFQ+9bLtsaB3QcePD4Ral91yapYsKiIvyGnZawfeVEPSNu5+coY+9bVEa88b9px/QHWj9yoB8yd/gDrR27UAzpzpxUAIAfZB9oj4lMRUc84Vsf4K7UvjIjzD74dqTrK+PeAjpoOgRuD+Wqy5uvXjvTk8TuN4boidzZz86Ie5Cy3UHtsmn58x0d3xP6d+yc/3kdC7eTG+pEX9YC0if5Yduqp044vP/eiWPDo5zR0VpAH60de1APSdt1wTcSa8w45rj/A+pEb9YC50x8AQBNKema9mvFWx2SwvVdvULw2hMDbMgbda7rm69b0JtDuuqJUNnPzoh6UYCLUvvSspdOOT4Ta927bO5DzWHHBiljx/EOD69uv2B47rtoxkHOYCLUvXLpw2vGJUPvY/WMDOQ+wfuRFPSAt1R8REcvO7sXrlkC5rB95UQ9I27n5Sq/kCgnWj7yoB8yd/gAAmlJSoL2e8ZY6Pp83aK3SQuBtGYPutaXmgxoDes1mbl7Ug5LkEmo/4WknzHpcqJ1hYv3Ii3pAWqcwOww760de1APSUv2x/NyL9AdDz/qRF/WAtF03XDPrcf0BADSplEB7L1+F3SuzMzRKDOu2YQy615aaNzkGHAmbuflRD0qTS6g9RaidYWA9z4t6QJowO6RZP/KiHpDmTiuQZv3Ii3pAmjutAAC5OqrpE+jCeU2fAJSoLWHd0sage22puTA7pbKZWwb1oAQTofZtl2+L3TfufvD4RKh99aWrY8mqJY2d3/YrtkdExIoLVvR9rIlQ+9bLtsaB3QcePD4Rao9f7PspMGSs53lRD0jr9EquMOysH3lRD0jzx2mQZv3Ii3pA2kR/LDv11GnHl597USx49HMaOisAgHHZB9rruv500+cApWlLWLe0MeheW2ouzE6pbOaWQT0oSU6h9hXPXxG3vvvWacdyCbVDL1nP86MeMLtO89X4K7keOPSLYEhYz/OiHpAmzA5p1o+8qAekHe5OK7uaveEqAEAsaPoEgN5qS1i3tDHoXltqLsxOqWzmlkE9KNFEqH3pWUunHZ8Ite/dNpjd8BOedkKsvHjlIce3X7E9dly1YyDnMBFqX7h04UDGY/hYz8ugHmC+gk70R37UA2bnTiuQZj3Pi3pAmj9OAwBKINAOLVNSWHfjltFWhI7pXtuD5sLs5M5mbhnUg5LlEmpfccEKoXZay3peBvUA8xV0oj/KoB7QzZ1WYHhZz/OiHpAmzA4AlEKgHTjEoELgGzaN9nUMYfa8tD1oPqgxYL5s5pZBPWgDofZJQu30mvW8DOoB5ivoRH+UQT3AfAWd6I/8qAfMzp1WAICSCLQD0zQZAi8tdEz3mg6BG4NhZ3O9HOpBWwi1TxJqp1es52VQDzBfQSf6owzqAeYr6ER/lEE9wJ1WAIDyCLQDDxJmp1/aEAJvyxgMH5vrQFOE2idNhNphvqznZVAPMF9BJ/qjDOoB5ivoRH+UQT3AfAUAlEmgHYiIwQRpN24ZnfW4QPDwKa3mbRmD4WOzCmiaUPukJauWDGQc2sd6Xg71YNiZryBNf5RBPcB8BZ3ojzKoB5ivAIByCbQDAwvrbth0aKBdIHj4lFbztozB8LFZBeRCqB3mz3oOlMJ8BWn6oxzqwbAzX0Ga/iiDeoD5CgAo21FNDFpV1e/Mdryu6//R7ef2w2zjQ9sNMqx76qnTj69fOxK/eqZA8DApLQTeljEYPjargNxMhNq3Xb4tdt+4+8HjE6H21ZeuHsgrmK+4YEVEjIfYp5p4f+LjkAPrOVAK8xWk6Q+gFOYrSNMfZVAPMF8BAOVrJNAeEf89IupZjs8WKE99bj8ItDNUmgzrRkSsWzMSsa9/YwgE56W0EHhbxmD42KwCciXUDt2zngOlMF9Bmv4ASmG+gjT9UQ71YNiZrwCANljQ8PjVlLe5fG4/3mCoNB1m7xWB4DKUFgLfuGVUmJ0i2awCcjcRal961tJpxydC7Xu37R3Ieay4YEWsvHjlIce3X7E9dly1YyDnACnWc6AU5itI0x9AKcxXkKY/gFKYrwCAtmg60F5H96++XvfxDYaKMDuDVloIfMOm0b6O4dqlH2xWAaUQaoc06zlQCvMVpOkPoBTmK0jTH0ApzFcAQJs0GWj36uzQgCbD7OvXjvTk8TuNIRDcXk3WXJid3NmsAkoj1A6Hsp4DpTBfQZr+AEphvoI0/QGUwnwFALRNI4H2uq4XzPK2cA6f24+3WceHNmkyzP625yyKdWt6E2gf1PdBPoTZIc1mFVAqoXaYZD0HSmG+gjT9AZTCfAVp+gMohfkKAGijJl+hHRigpsPsbRiDZgyi5hu3jM56vLRrl+FjswoonVA7WM+BcpivIE1/AKUwX0Ga/gBKYb4CANpKoB2GQNuD5sLs7TWomm/YdGigvbRrl+FjswrSdm6+sulTYA6E2hlm1nOgFOYrSNMfQCnMV5CmP4BSmK8AgDYTaIeWa3vQXJi9vZqs+fq1I0Vduwwfm1WQluoP5m/s/rG+jyHUzjCyngOlMF9Bmv4ASmG+gjT9AZTCfAUAtJ1AO7RY24Pmwuzt1XTN160Z6esYwuwcCZtVkCbM3h/bLt8m1B5C7fSW9RzS3GklL+YrSNMfQCnMV5CmP4BSmK8AgGHQaKC9qqo/rKrqeVVVLT38ZwNz0faguTB7e7Wl5sLs9IPNKkgTZu+f3TfuFmo/SKidXrCeQ5r1PC/mK0jTH5Dmj9PyYr6CNP0BlMJ8BQAMi6Zfof3SiPhIRNxVVdVnqqr6/aqqnl1V1eKGzwuK1vag+aDGYPCE2SFt1w3X2KyCBOG3/hNqnyTUzpHw5BOkWc/zYr6CNP0BadbzvJivIE1/AKUwXwEAw6TpQPuEoyPiyRHxWxHx8Yi4p6qqT1dV9d+rqnpGVVUjzZ4elKPpELgxmK8ma75+be+WGdcV/TLbq1vZrAJPlg+SUPskoXbmw5NPkGY9z4v5CtL0B6RZz/NivoI0/QFp7rSSF/MVADBscgm01xFRTXkbiYgfj4g3RcQnYjzg/q9VVf12VVVPrarqqOZOFfLWhhB4W8age03XfN2a3gTaXVcMks0q6LyZS38ItU8Samcu3GkF0oTf8uLJckjTH5BmPc+L+QrS9AekWc/zYr4CAIZRLoH2iPFQ+9S3qQH3xRHxzIj4vYi4NsYD7h+rquo3q6p6UlVVC5s5ZchfaSHwtoxB99pS80GNARE2qyDCZu4gLVw6/dctofZJQu10y51WYHaeLM+Ln68gTX9AmvU8L+YrSNMfkGY9z4v5CgAYVk0H2n8jIq6KiPtieoA9onPA/ZiIOD8i3hIRmyLi7qqq/qWqql+vquqcqqqqAIoM67ZhDLrXlpo3OQbtteuGa2Y9brMKbOYO2upLV2cdat93+76+n0OEUDu9Zb4Cd1rJjZ+vIM2dViBN+C0v1nNI0x+QZj3Pi/kKABhmjQba67reUNf1CyPixIg4NyYD7rtibgH3ZRHx/Ij4nxGxOSLuqqrqw1VVXVJV1Y8M7juCfLQlrFvaGHSvLTUXZqcfdm6+0iu5QoLN3MFbsmpJ1qH22997e9/HnyDUTi+Yr8B6nhv1gM78fg6z88dpebGeQ5r+gDRh9ryYrwCAYdf0K7RHRERd12N1XX/+YMD9wog4ISKeFBG/GREfjbkH3I+LiBdGxB9FxBerqtpRVdUHqqr6laqqHjfAbw0a0Zawbmlj0L221FyYnX5IbVYtP/cim1UMPZu5zck61L73QN/HnkqonW640wqkWc/zoh4wd/oDrB+5UQ9Ic6cVSBNmz4v1HAAgk0D7TAcD7p+r6/qyuq5fEOOv4P7kiPitiPhYROyOuQXcT4yIn4yIt0fEV6qq+n5VVVdUVfVLVVU9ZnDfGfRfW8K6pY1B99pSc2F2+qHT5uGys88f8NlAXmzmNi/nUPugCbXTiTutQJr1PC/qAXOnP8D6kRv1gM78fg6zc6eVvFjPAQDGZRlon6mu6wN1XW+u6/p/1nV9QYy/gvtTIuINEfHxiNgTcwu4nxQRL4uIP4uIr1dVdXtVVX8zwG8J+qaksO7GLaOtCB3TvbYHzYXZORJeCQPSbObmo4RQ+77b9/X9HCKE2pmdO61AmvU8L+oBae60AmnWj7yoB8yd/gDrR27UAwBgUhGB9pkOBtw/W9f1H9Z1/fyIOD4i1kbEGyPi6ph7wH1lRPzUIL8HyNmgQuAbNo32dQxh9ry0PWg+qDFoJ2F2SLOZm5/cQ+23v/f22Lttb9/PIUKonencaQXSrOd5UQ9Ic6cVSLN+5EU9YO70B1g/cqMeAADTFRlon+lgwP3f67p+a13Xz4vxV3D/8Yj47Yi4JiL2xvQAexXTw+3AQU2GwEsLHdO9pkPgxiBnnV7JFYadzdx85RRqX/LIJdOOH9h7ILZetlWonYHyx2mQZj3Pi3pAmjutQJr1Iy/qAWnutAJp1o+8qAcAwKFaEWifqa7rB+q63lTX9R/Udf3cGH8F96dFxJsi4l9jPOAOzCDMTr+0IQTeljHIS6fNKq/kyrCzmZu/XELtp7zylEOOH9gt1M7gCLNDmvU8L+oBae60AmnWj7yoB6S50wqkWT/yoh4AALNrZaB9Fosi4tiDb8dFxEizpwP5GUSQduOW0VmPCwQPn9Jq3pYxyIvNKkjTH+XIItQ+MvuvtULtDII7rUCa9Twv6gFp/jgN0qwfeVEPSHOnFUizfuRFPQAA0loZaK+q6piqqp5bVdUfVFV1fUTcHRH/EhHrI+KcaOn3DfM1qLDuhk2HBtoFgodPaTVvyxjkxWYVpOmP8uQQak8Raqef3GkF0qzneVEPSBNmhzTrR17UA9LcaQXSrB95UQ8AgM5aEeyuqmpxVVXPrqrq96uq+kyMB9iviojfiIhzI+KoiKgOvj34ZVPeDkTEFwZ71pCHJsO669eOCAQPmdJC4G0Zg7zYrII0/VGunELtSx65ZNr7OYXaaQ/zFaTpj7yoB6S50wqkWT/yoh6Q5o/TIM36kRf1AAA4vCID7VVVLaqq6ryqqv5HVVXXRsQ9EfHxiPitiHhyRBwd0wPs9dQvj/EA+2cj4rKIuDAiTqzr+twBnT5ko8mwbkTEujUjfR1DIDgvpYXA2zIGebFZBWn6o3y5hNpPeeUpsfSspdOO5RJqpx3MV5CmP/KjHjA7d1qBNOt5XtQD0oTZIc36kRf1AADoThGB9qqqRqqqekZVVf+9qqpPxXiA/ZqIeGNEPDUiRqJzgH1/RHwmIv4gIp4XEcfXdf2Uuq5/s67rq+q6vm8w3wnko+kwe68IBJehtBD4xi2jwuz0nM0qSNMf7ZFDqH3ByIJYdckqoXb6wnwFafqjDOoB5ivoRH/kRz1gdu60AmnW87yoBwBA97IMtFdVdXRVVU+rqup3qqr6RIwH2D8REW+KiKdFxKLoHGAfjYhrI+LNEXF+RJxQ1/XT6rr+7bqur67res+AvhXIkjA7g1ZaCHzDptG+juHaHT42qyBNf7RPFqH2RULt9J75CtL0RxnUA8xX0In+KIN6gDutQCfW87yoBwDA3GQRaK+q6qiqqp5aVdVvV1V1TYwH2D8VEb8bEc+IiMXROcC+L8YD778bEc+M8Vdgf2Zd179b1/Un6roeTFoBCtBkmH392pGePH6nMQSC26vJmguzcyRsVkGa/mgvofZJQu3tYL6CNP1RBvUA8xV0oj/KoB5gvoJO9Ed+1AMAYG4aDbRXVfVbVVV9PMYD7NdGxO9FxHkRsSQ6B9j3RMTVEfHbEfHjMR5gP7+u6zfXdX1tXdf9fVloKFSTYfa3PWdRrFvTm0D7oL4P8iHMTqlsHkKa/mg/ofZJQu1lM19Bmv4og3qA+Qo60R9lUA8wX0En+qMM6gEA0FnTr9D+loh4dkQcE50D7PdFxFUR8ZsR8ZQYD7A/r67rP6jrelNd1/sHeM5QpKbD7G0Yg2YMouYbt4zOery0a5e82DyENP0xPITaJ624YMVAxqG3zFeQpj/KoB5gvoJO9EcZ1APMV9CJ/iiDegAAHF7TgfYJ9ZS3KiLujYh/johfj4gnRsSJdV1fWNf1ZXVdf7au6wPNnSqUp+1Bc2H29hpUzTdsOjTQXtq1S15sHkKa/hg+Qu2UynwFafqjHOrBsDNfQZr+KIN6gPkKOtEfZVAPAIDuHNX0CUxRRcQDEfE3EfH2uq63NHs6+aiq6tSIeFxEPCIijo+IkYi4++DbTRFxQ+4h/6qqHh0RayLi1IhYGhF7I+L2iPhKXddfa/DUWq/tQXNh9vYaZM1PPXX68fVrR+JXzyzn2iUvNg8hTX8Mr4lQ+9bLtsaB3ZO/ukyE2lddsioWLOrv31tPhNq3Xb4tdt+4+8HjE6H21ZeujiWrlvT1HCiH+QrS9AdQCvMVpOmPcqgHw858BWn6owzqAQDQvZwC7XVELIyIn4uIn6uq6u6IuC4iPh0RnxqmgHtVVWdGxPMi4lkR8fQYD7F3sruqqk9FxF9ExEfquu7/Sxx2oaqqJRHxmoj4pYg4vcPn3RYR74mIy+u6vmcwZzcc2h40F2Zvr6Zrvm7NSMS+/o0hzN5eNg8hTX8g1E4pzFeQpj+AUpivIE1/AKUwX0Ga/iiDegAAzE1/0wLdqQ6+zXz/xIj4iYj4o4j4QlVVd1VV9eGqqv5bVVU/VlVVNctjFauqqiVVVb2pqqobIuLGiLg8xr//47v48qURcWFE/FNEfKWqqif06zy7VVXVU2P8+/ij6BBmP+gREfG7EfHNqqp+ot/nNizaHjQXZm+vttRcmH342DyENP3BhIlQ+8KlC6cdnwi1j93f/7/NnQi1Lz1r6bTjE6H2vdv29v0cyJf5CtL0B1AK8xWk6Q+gFOYrSNMf5VAPAIC5aTrQ/hMR8ccR8cUYf4X2iZB6ffAtYjLgfnxEvDAiNkTE5yLirqqq/qmqql+vquoJVVU1/b0cqYdGxP+IiMcf4eM8LiKur6rqV478lOanqqqLIuKTEbFqjl96UkR8qKqq/9r7sxoubQ+aD2oMBk+YnVLZPIQ0/cFMQu3kynwFafoDKIX5CtL0B1AK8xWk6Q8AANqs0RB4Xdf/XNf1r9d1/YSIeEhEvDgi/iQitsThA+7HRcQLIuJ/RsRnI+Luqqr+paqqS6uqOreqqunpiLJ9KyLeExG/GRGvjoiLI+I1EfGXEXHrLJ9/VET8aVVVvziwMzyoqqq1EfH3EXH0jA+NRcQ/RsSlEfGKiHhtjH9Pe2Y+RES8s6qql/T5VFur6RC4MZivJmu+fu1ITx6/0xiuq/ayeQhp+oMUoXZyY76CNP0BlMJ8BWn6AyiF+QrS9AcAAG13VNMnMKGu63sj4p8OvkVVVcdFxDMi4pkH3344JgP49ZQvnQi9HxsRzz/4FhGxu6qqz0TEpyPiUxHxubquD/TtG+i9r0fEX0XE39Z1/b3UJ1VVdVREvCrGX+l+2YwP/2lVVZ+q6/qbfTvL6eeyNCL+Lg4Ns38jIl5S1/WNs3zNpRHxf2L81fofPBwR/6eqquvrut7er/NtqzaEwNsyBt1ruubr1ozEJ/s8huuqnWweQpr+4HAmQu1bL9saB3ZP/qo2EWpfdcmqWLCov3+DPRFq33b5tth94+4Hj0+E2ldfujqWrFrS13OgeeYrSNMfQCnMV5CmP4BSmK8gTX8AADAMGn2F9k7qur63rut/rOv6v9V1/WMRsSIiXhIRb4+Irxz8tE6v4L4sIp4bEW+JiM9ExD1VVX2sqqo3VFW19mAQPEefjIhn1HX9uLquN3QKs0dE1HX9QF3X746Ip0bEPTM+PBIRf9Sf05zVGyLitBnHbo6ItbOF2SMi6rq+KyIuiogPzPjQcTH+6vscodJC4G0Zg+61peaDGoN82DyENP1Bt7xSO00zX0Ga/gBKYb6CNP0BlMJ8BWn6AwCAYZFtoH2muq7vqev6w3Vdv76u6x+N8YD7RRHxjoi44eCndQq4L42I8yPizRFxXYwH3K+uquq3q6r68aqqZr6q+KDdGxHPrOv6WXVdXzvXL67r+isR8QuzfOiCqqpWHPHZHUZVVcdHxK/MODwWEa8+GFpPOvjK+f8lIr4/40M/U1XVI3t2kkOoxLBuG8age22peZNj0Aybh5CmP5groXaaYr6CNP0BlMJ8BWn6AyiF+QrS9AcAAMOkmED7THVd313X9Yfqur6krus1EXFSRLw0Iv40Ir568NM6BdyPiYhnRcTvRcSnI+LuAZ36rA5+P58+wsf4QEy+ev2EhRFxwZE8bpd+JiKWzzj2L3Vd/1s3X1zX9Z0RsWHG4YUR8Z97cG5DqS1h3dLGoHttqbkw+/CxeQhp+oP5Empn0MxXkKY/gFKYryBNfwClMF9Bmv4AAGDYFBton6mu67vquv5gXdevq+v6R2I84P6yiHhnRHzt4KdVU78kJsPtVUQsGeT59tFVsxwbxKuc/9Qsx/5ijo/xVxExM7H5inmdzZBrS1i3tDHoXltqLsw+fGweQpr+aK8dV+0YyDhC7QyK+QrS9Aek7dx8ZdOnwBTmK0jTH0ApzFeQpj8AABhGrQm0z3Qw4H5lXdevrev6hyPi5Ih4eUT8eUTsmvi0mHzl9ra4ZZZjK/s5YFVVx0XEU2Yc3hURH5vL4xx8lfZPzTi8qqqqs+Z/dsOnLWHd0sage22puTD78LF5CGn6o922X7FdqD2E2tvCfAVp+gPSUv1BM8xXkKY/gFKYryBNfwAAMKxaG2ifqqqqH4mIVx58e0VETCQTquQXleuYWY71O3HxlIhYOOPY9XVdH5jHY103y7GnzeNxhlZJYd2NW0ZbETqme20Pmguzt5fNQ0jTH8NBqH2cUHvZzFeQpj8gTZg9L+YrSNMfkOZOK3kxX0Ga/gAAYJi1MtBeVdXZVVW9tqqqK6uq2hERX4yIP4qIF0XE8TEeZG9jmD0i4tGzHPuPPo95zizHrp/nY23q8vHpo0GFwDdsGu3rGMLseWl70HxQYzB4Ng8hbdcN1+iPISLUPk6ovUzWc0jTH5AmzJ4X8xWk6Q9Is57nxXwFafoDAIBh14pAe1VVj6uq6perqnp/VVU/iIgtEfEnEfHiiDgxJgPsVUTUM95ao6qqo2L8e57pc30e+sxZjn1rno/17VmOPWaej8U8NBkCLy10TPeaDoEbg/myeQidzfbqVvqj3YTaxwm1l8V6Dmn6A9KE3/JivoI0/QFp1vO8mK8gTX9AmjutAMDwKDLQXlXVWVVVvaaqqn+oqur7EfGViHhHRLwkIh4Shw+wT/34roi4KiJ+Y6DfRH/8RESsnHHsroj4tz6Pu3qWY9vm+Vjfi4gDM449cp6PxRwJs9MvbQiBt2UMumfzEOZOfwwHofZxQu1lsJ5DmjutQJrwW16s55CmPyDNep4X8xWk6Q9Is54DwHApItBeVdVjqqr6L1VV/X1VVf8REV+NiHdGxEsj4qSYW4B9b0RcHRFviIinRMSJdV1fWNf12wb4LfVcVVWLI+Kts3zo/9R1/UCfh58Zoo+IuHU+D1TX9YGI+I8Zhx86n8dibgYRpN24ZXTW4wLBw6e0mrdlDLpn8xDmTn+018qLD/1xP6tQ+6hQO7OznkNn7rQCs+u0fjB41nNI0x+QJvyWF/MVpOkPSLOeA8DwOarpE5hNVVWnR8QzI+K8iHhGTA9MVzM+vY5DTf2cfRFxfUR88uDbZwcQ8G7CWyPijBnH7o6I/zmAsU+c5diuI3i8mV87UlXVsrquj+QxIyKiqqqTY/yPIObiUVPf2bVrV+zcufNIT6V/Fj98zl+ycctovP2m0Tj11OnH168diXVrRqIX3+3GLaPxvu+cGG+ccmzlypU9H6On30fOdS7MqVOKkmPNd4+cnHx/UP3R9Riuy55ZuWS2HyHGX6ly7FtXx7IZBVl+7kWx7OzzY/YfPXpvxeK64/s5yXpdLEzquszFMbdsiljzpAffX7ly/Mf0QfdHN1yXvfPYCx8bD1v+sNjx0RkB9k0RRy8/Ok542gn9P4kfinjomx4at7/39jiwd8oNnXZFHPjIgYifmzx04oLZfj3pgSURJ//ayXH7+26Pvd+ZHmA/8DcHYvmrl8fiUxZ3fAjXZe8cbr5sej23jg+n3NfxmdfhxDo+Iaf13HXZO6Vdl03Pl4dbP1ybvdPNtdnUep7bdXk4rsveyXnOnHkdHnPLpliWwf5Viuuyd0q6LnOZL1Prh+uyd+ZyXQ56Pc/1ukxxXfZOifNl0/tXKa7L3inxuszFzP7I+brcteuIo0wAwEFVXTf/Q0lVVY+KyQD7MyPiYVM/POPTDxdgH42Iz8ZkgP36uq5nf1nolqiq6qUR8f5ZPvTzdV33/c8Vq6raFxEzXz742PkG0Kuq+mJE/OiMww+t6/qO+TzejMf+7xHxu0fyGO94xzvitNNOO9JTAQAAAAAAAAAACnXLLbfEa1/72qmHHl/X9deaOh8AKFmjr9BeVdXGGA+xT31J6bkG2B+IiM/FZID9M3Vd7+vleeasqqofi4iNs3zoA4MIsx909CzHjqQGe2c5NnIEjwcAAAAAAAAAAAAAZKjRQHtEvDLGA+tTA+qHC7AfiIgvxmSA/d/qut7dtzPMWFVVj4yIf4mIpTM+dFNEvGrwZzTNkbz0/+GuAQAAAAAAAAAAAACgBZoOtE+YGWCeGl4ei4gtMRlgv7au6/sGdF7Zqqrq4RFxTUSsnPGh2yLi+QP+N9ofEYtmHFsSEbvm+XhLZjk2Os/HmuldEfH/5vg1j4qID0+8c+6558ZZZ53Vo9Ppg3c9+bCfsnHLaGzYdOg/6fq1I7FuTW9eDH+2MVauXBlvfOMbH3z/3G//SSwdvaOnY0T08Pv4r/9+5I9BREQ890+ubfoUOlqxuI7/fObYg++/+6YFsWNf//6OZtcN18TOzVcecnz5uRfFsrPP7/i1H3/90/t1WkNn4ro8knr006CvyyPhuuyd3ObLmf0xcy13XQ6Hxz/+8X3/OTFi/j/D7R45OTY/6vUPvn/ut/8k3r/5tkZ+3j3sGH6+7JmZ82Vu67l1fDjlto5PmOiPmev42//xs7HntLUNnlma67J3cr0uJzQ9X851/XBt9s5s12Yu63nT1+VcuS57J+c585hbNsXrfuJJD77/lre8JbZv3974/lWK67J3cr4uc5kvu10/XJe90+m6bHo9z+W67JbrsndKmi8n1vEJua3nrsveKem6bHq+PNz6kfN1eeONNzZ9CgDQGrkE2iMmQ+x1RNwQkwH2T9d1fU9TJ5WjqqpOjvEw+w/N+ND3I+LZdV1vG/Ap7Yn+B9p78ir8dV3fERFzSlBX1fQf2pctWxbLly/vxen0x77vdfzwH226P3796vsPOf625yyKXz1zUcS+Iz+F1Bjr104P9iwdvSOWH+Z85zpGL7+PyLnOhdm+N9/Nwtns2Ff17Zx3br4y7v7kew85fsJ5r44Fj35O7Nrb+euznn8Ks31vdcT1GKR+XpdHynXZOznVONUfU7kuh8Przryj7z8n9vJnuPdvvi1ee8W3+zrGvL8P12XPTJ17SljPzZfDIccad1rP95y2NstzjnBd9lKuNU4Z5Hw5n/XDtdk7M+uc83qe8zoe4brspVzrvHPzlbHsW1dHTAm0b9++PXY9+jmN90eK67J3cr0uZ9PEfDmX9cN12TupOue4nlvHh0fOdZ5p+/btceutt0ZEHj/vzuS67J2Srssm58tu1o+cr8tly5Y1fQoA0BoLmj6BGA+y3xTjr5z98og4ua7rH6nr+pK6rj8szD5dVVUPifEw+5kzPrQjxsPs3xz8WcWdsxw7kp/YZn7taF3X8w3HM0Wn4M2vrZ35Nwm9H6NXr4Y5qO8Deq3TL+PLz72ogTMabuoBaan+0BvDaRA/J/ZqjIiY9VXTB/Xzbi+/D7pjPYe0bv44DYaV9SMv6gFpnX4/1x8MO+tHXtQD0nbdcM2sx/UHWD8AgOmaDrS/IiJW1nX9uLquf6Wu6w/UdT1bOJqIqKrqhIi4OiLOnvGhuyLi/Lquvzb4s4qI8VeGn+kR83mgqqoWRsTDunh85qjpMHsbxoAj4Zfx/KgHzK7TfJXTbU8pS5Mh8NJ+FqV7fr6CNGF2SLN+5EU9IK3Teu73c4ad9SMv6gFpOzdfGTs3X3nIcf0B1g8A4FCNBtrrur6irus7mjyHUlRVdVyMh9l/dMaH7omI59Z1/eWBn9Sk785ybNU8H+uUiDiqi8dnDtoeNBdmJ3d+GS+DeoD5iv4QZqcfzFeQ5k4rkGb9yIt6QJo/ToM060de1APS3Gnl/2fv38Ms28r60P87mk0J0myBIGp04wWi4M+treiOtlFBwaOiyclOPIlJSMfb8W5MSJv7MTEhXrZG0WguBrUTo56j6WgSNZEtKCStaZW0tggq3hAVAQWa5mLL3uP3R1XT1dU1VtdlrTXHmOvzeZ56qmt11Ryz91jvO+ac+1tzQpv1AwDYz9R3aOcASil3JvnRJE/Z81dXkvwftdafXf9e3eSX9nntiUfc1hP2ee3lR9wWmX/QXJid3jkZH4P5AP2K1VjHMdy5S9f2fX20Y1EOR7+C/XnSCrQ53u2L+YA2YXZos370xXxAmyetQJv1AwBoEWjvXCnlkUn+e5J79vzVm7IdZr+4/r26xX6B+o864rZO7/PaS464rY0396C5MDu9czI+BvMB+hWrsa5juPsu3BpoH+1YlOPTr8B6Douoj/6YD9ifJ61Am/W8L+YD2vxyGrRZPwCARQTaO1ZKOZnkvyX5yD1/dTXJJ9daf2r9e7WvC0ke2PPaR5VSHnKEbf2pfV570RG2s/HmHjQXZqd3TsbHYD5Av2I1pjyGO3t6a6hjUY5PvwLrOSyiPsZgPsCTVmAR63lfzAe0CbNDm/UDALgdgfZOlVIekeSHc+sdy9+c5FNqrf9z/Xu1v1rrG5PsDdc/MskzDrOdUspjkjxtz8uvrLW+7Bi7t5HmHjRf1xhwVE7Gx2A+QL9iNab+hcQzp7ZWOoYwe1/0K7CewyLqYwzmA/QrWER99Md8wP48aQXarOcAwEEItHeolPLOSf5rko/Z81dvSfLMWuuL179Xt/W9+7z2+YfcxpkkD9vz2vccbXc219QhcGOw6ZyMj8N8sOn0K1Zh6jD7sjhOHIN+BdZzWER9jMF8gH4Fi6iPMZgP8KQVWMR6DgAclEB7Z0opD0vyg0meuuev3prk02qtP7H2nTqY70rypj2vfVopZe8d5vdVSnl0krN7Xn4gybctYd82yhxC4HMZg83jZBwYhX7FKgizs076FVjPYRH1MQbzAfoVLKI+xmA+QL+CRdQHAHAYAu0dKaVsJTmfZO+v6F4Ps79gxeP/eCml7vn4awf52VrrG5J8y56XTyT5jp2w+qJxTyT510neY89ffU+t9VcPtve0jBYCn8sYbB4n48Ao9CtWYcpjuLOnt5ay/UVjOE7sj37FprOeQ5v6GIP5AP0KFlEfYzAfoF/BIuoDADgsgfZOlFLuSPL/JfnkPX/1tiT/Z631x9a/V4f2nCSv2vPa+ye5UEp50n4/sBN2P5/k0/f81ZUkf3vpe7hhRguBz2UMNo+TcWAU+hWrMPUx3JlTywm0O04ERmE9hzb1MQ7zwabTr6BNfYzBfIB+BYuoDwDgKO6Yegd4h7+Q5M/s8/rbknxtKeVrj7Htn6m1fs4xfv5Aaq1XSyl/KckLcvN760lJXlpK+S9JXpzkt5M8NsmHJPmMJI/YZ3OfXWv9nRXv8qyNFgKfyxhsHifjwCj0K1ahh2O4K2sYYxm+/sIf5tlL2RKwyazn0KY+gFHoV9CmPsZgPkC/gkXUBwBwVALt/Xho4/VH7XwcxxuO+fMHVmt98U6o/btz8/vrRLYD+/uF9m/aRJIvq7V+/4p2cSOMFgKfyxhsHifjwCj0K1ZhLsdw6xxDoB04Dus5tKkPYBT6FbSpj3GYDzadfgVt6gMAOI4TU+8A81Nr/b4kH5/klYf80dclubfW+k3L36vNMWq4Z/Qx2DxOxoFR6FeswlyO4aYcA+AwrOfQpj6AUehX0KY+gFHoV9CmPgCA4xJoZyVqrS9O8uQkZ5O84jbf/ttJ/kmS96+1/sCKd232Rgr3nLt0bRYhJTaPk3FgFPoVqzD3oLkwO9Ab6zm0qQ9gFPoVtKkPYBT6FbSpDwBgGe6YegfYVmv9ziTfOfE+PHXJ23tLkq9L8nWllD+R5EOT3JXknZO8LcnvJPn5WuvlZY7L8a0rBH7fhWsrHUOYnVVwMg6MQr9iFeYeNBdmB3pjPYc29QGMQr+CNvUBjEK/gjb1AQAsi0A7a1Fr/ZUkvzL1fnB7U4bARwspsXmcjAOj0K9YhbkHzYXZgd5Yz6FNfQCj0K+gTX0Ao9CvoE19AADLdGLqHQD6IcwObU7GgVHoV6zC3IPm6xoD4KCs59CmPoBR6FfQpj6AUehX0KY+AIBlmyTQXkr5g10fPz7FPgA3W0e459yla/u+PlpIic3jZBzarlw8P/UusIt+xSpMHQI3BrBprOfQpj6AUehX0KY+gFHoV9CmPgCAVZjqDu2P2vVx56JvLKW8YNfHv1n9rsHmWVe4574LtwbaBYjonZNxaGvVB9PQr1iVOYTA5zIGMH/Wc2hTH8Ao9CtoUx/AKPQraFMfAMCq3DHh2DVJOcD3PXXne5PtADywROsM99x1182vnz29lS95kgAR/XIyDm3C7H3Rr1in0ULgcxkDVmH7SSvPnHo32GE9hzb1AYxCv4I29QGMQr+CNvUBAKzSVHdoP4qDhN+BQ5gy3JMkZ05trXQMASKOw8k4tAmz90W/Yp1GC4HPZQxYBet5X6zn0KY+oG37l9PohX4FbeoDGIV+BW3qAwBYtakC7Q90sA+w0aYOsy+LABGrcPXy/U7GoUH4rS8uHrJOo4XA5zIGrIL1vC/Wc2hTH9BmPe+LfgVt6gMYhX4FbeoDAFiHqcLkb9j158dMtA+wsYTZYbH97m7lZBz8z/LeuHjIOo0WAp/LGLAK1vO+WM+hTX1Am/W8L/oVtKkPaPOklb7oV9CmPgCAdZkq0P7aXX9+z1LKe0y0H7Bxpgz3nD29tZTtLxpDgIhVcDIOiy9WsX4uHrJOo4XAz126JswODcJvfbGeQ5v6gDbreV/0K2hTH9BmPe+LfgVt6gMAWKepAu0/m6Ts+vofT7QfsFGmvlPlmVPLCbSv698BiZNxSFys6o35YN1GC4Hfd+HaSscQZmdU/md5X6zn0KY+oM163hf9CtrUB7RZz/uiX0Gb+gAA1u2Oica9P8lfTlKzHWz/7FLK3Un+vyS/lOTNO3+318lSyseuaqdqrS9a1bZhalOH2Z99+p1yZQ1jLMP1MZ69lK0xgquX709OPe2W152Mg4tVvTEfjGrKELgwO3jSSm+s59B29fL96gMahN/6Yj2HNvUBbdbzvuhX0KY+AIApTBVo/94kX5vksbkRar9n52M/1+/m/oQkL1zRPtVM998DVqqHMPvoYzBfVy6ez4OveH7yrJsD7U7GwcWq3pgPRiXMDtOyfvTFfMBiVy6ev+U19QF+Oa031nNoUx/QJszeF/0K2tQHADCVE1MMWmv9wySflxtB9et3Yy/7fOy2398v8wNmZ+5Bc2F2jqN1Mn7nPfc6GWfjuVjVF/PBqNZxDHfu0rV9Xx/tWBRWwfrRF/MBh6c+wPrRG/MBbZ60Am3C7H2xnkOb+gAApjRJoD1Jaq0/kORMkrfm5mD73o+bfmxFHzBLcw+aC7NzHIsuHp68++lr3hvoi4tVfTEfjGpdx3D3Xbg10D7asSisgvWjL+YDDk99gPWjN+YDFvOkFdifJ630xXoObeoDAJjaZIH2JKm1/vsk75/kq5K8LNvh8inu0A6zM/eguTA7x+FOGNDmYlVfzAejmvIY7uzpraGORWEVrB99MR/QdvXy/fu+rj7A+tEb8wGHpz7A+tEb8wFtnrQCAPTgjql3oNb6O0n+fpK/X0o5meS9krxLkodlO2z+gtwIur8iyedOtKswjLkHzdc1BvMkzA5tLub2xXwwqql/IfHMqa3kbasbQ5id3lk/+mI+oO3KxfN58BXPT571tJteVx9g/eiN+YDDUx9g/eiN+YDFPGkFAOjB5IH23WqtV5O8fPdrpdx0A/WrtdafWOtOwWCmDoEbg561LlY5EQcXc3tjPhjV1GH2ZXGcyKisH30xH9B2vT5O3nXXTa/fec+9OfHEZ0y0V9AH60dfzAe0Xb18f3Lqabe8rj7A+tEb8wGHpz4AgCmcmHoHDqFOvQMwgjmEwOcyBn1ZdLHq5N1Pn2CPoB8u5vbFfDAqYXaYlvWjL+YD2hY9Oc35OZvO+tEX8wFtVy6edydXaLB+9MV8wOGpDwBgKqME2svOB3BIo4XA5zIGfXGxCtrUR1/MB6Oa8hju7OmtpWx/0RiOE+md9aMv5gPaFoXZYdNZP/piPqBt0ZNQ1QebzvrRF/MBbVcv37/v6+oDAJjSHVPvwAH8411/fvVkewEDGi0EPpcx6IuLVdCmPvpjPhjR1MdwZ05t5YUrHsNxIj2znvfFfECbMDu0WT/6Yj6g7XZPWrn61jXvEHTE+tEX8wFtVy6ez4OveH7yrKfd9Lr6AACm1n2gvdb6j2//XcBeo4XA5zIGfXGxCtrUxxjMB73r4RjuyhrGWIavv/CHefZStgQ3WM/7Yj6gbdGdXGHTWT/6Yj6gzS+nQZv1oy/mA9qu18fJu+666fU777k3J574jIn2CgBg24mpdwBYvtFC4HMZg764WAVt6mMM5oPezeUYbsox4Dis5/0xH7C/Rf3q5N1Pn2CPoB/W876YD2gTZoc260dfzAe03e5JKwAAUxNoh5mZS7hntDHoi4tV0KY+xmA+6N1cjuGE2RmV9XwM5gP0K1hEffTHfMD+PGkF2qznfTEf0OaX0wCAEdwx9Q4cVymlJPmQJB+W5LFJHpPkkUnelOQPkrwuyc8m+flaa51qP2FdRgr3nLt0bRYhJfriYhW0qY8xmA96N/eguTA7vbOej8F8gH4Fi6iPMZgPOMiTVh5Y/05BJ6znfTEf0CbMDgCMYthAeynl6Um+OMnTkpw8wI9cLaX8WJJvrrW+cKU7B4NbVwj8vgvXVjqGMPvmcbEK2tTHGMwHvZt70FyYnd5Zz8dgPkC/gkXUxxjMBxykX7mPGJvLet4f8wH786QVAGAkJ6begcMqpXxYKeVSkv+e5NOyfTf2coCPRyb5M0nuL6W8pJTyoevfe+jflCHw0UJK9MXFQ2hTH+MwH/Rs7kFzYXZ6Zz0fg/kA/QoWUR9jMB+gX8Ei6mMM5gMO8qQVAIC+DBVoL6X8zSQXktydG0H1eoiP6z9zKslPllL+xnr/BdA3YXZG5eIhtKkPYBnmHjRf1xhwVNbzMZgP0K9gEfUxBvMB+hUsoj7GYD5AvwIAxjRMoL2U8reSfF2SrdwcZE8Odof25OZw+1aSr9vZLmy8dYR7zl26tu/ro4WU6IuTcWhTH8AyTB0CNwabzno+DvPBptOvoE19jMF8gH4Fi6iPMZgP0K8AgHHdMfUOHEQp5f9M8jW5EWB/x18l+YMk/znJTyf5xSSvT/LmJI9I8qgkH5jkI5L86SR/bNc2rt+x/atLKb9Sa/3Blf4joGPrCvc89+XX8s2fsdoxBIg2i5NxaFMfwLLMIQQ+lzHYPNZzYBT6FbSpj3GYDzadfgVt6mMM5gP0KwBgbN0H2kspW0m+MTfuyp6dP786yd9J8r211v1v+7ztRUn+VSnloUn+YpKvTvIeuXGn9hNJnltK+ZHbbAdmaZ3hnrvuuvn1s6e38iVPEiDiaJyMQ5v6AFZptBD4XMZg81jPgVHoV9CmPoBR6FfQpj7GYD5AvwIAxndi6h04gC9K8vjcuKN6SfKCJE+qtf67g4bQa61/VGv990melOT+ne1cd1eSL1jqXsMApgz3JMmZU1srHUOAaL6cjEOb+gBWabQQ+FzGYPNYz4FR6FfQpj6AUehX0KY+xmE+2HT6FQAwByME2j9j159rkp9M8im11itH2Vit9U1JPnVnO9fv+l6S/OVj7icMZeow+7IIEG0eJ+PQpj6AVRotBD6XMdg81nNgFPoVtKkPYBT6FbSpD2AU+hUAMBddB9pLKY9N8pTcCJ0/kOSzDnpX9padn//sJG/f9fKH7YwHsyfMzqicjEOb+gBWabQQ+FzGYPNYz4FR6FfQpj6AUehX0KY+gFHoVwDAnHQdaE/yEdkOsifbofYX1lp/aRkbrrW+PMkLdm2/7IwHszZluOfs6a2lbH/RGAJE8+VkHNrUB7BKo4XAz126JszOkKznwCj0K2hTH8Ao9CtoUx/AKPQrAGBueg+0P27P189f8vbv3/P1uy15+9CVqe9UeebUcgLt6/p30A8n49CmPoBVGy0Eft+FWx/oJcxO76znwCj0K2hTH8Ao9CtoUx/AKPQrAGCORgm0X7+L+m8vefvXt1d3Pr/rkrcP3Zg6zD6HMZiGk3FoUx/AKKYMgY92LMrmsZ4Do9CvoE19AKPQr6BNfQCj0K8AgLnqPdD+wJ6v71jy9h+y8/l6YH7veDALcw+aC7PPl5NxaFMf0Hbl4vmpd4FdhNmhzXoOjEK/gjb1AYxCv4I29QGMQr8CAOas90D7a3c+X7+D+l1L3v7e7b123++Cgc09aC7MPl9OxqFNfUBbqz6YxjqO4c5durbv66Mdi7J5rOfAKPQraFMfwCj0K2hTH8Ao9CsAYO56D7S/es/Xn7zk7X/Snq9/b8nbh0nNPWguzD5fTsahTX1AmzB7X9Z1DHffhVsD7aMdi7J5rOfQ5kkrfdGvoE19AKPQr6BNfQCj0K8AgE3Qe6D9YpIHdv5cknxUKeUpy9hwKeVDk3x0btz9/YEkP7WMbUMP5h40F2afLyfj0KY+oE2YvS9THsOdPb011LEom8d6Dm3W877oV9CmPqDNL6f1Rb+CNvUBjEK/AgA2RdeB9lrrG5P8ZLbD7DXb+/u8Usojj7PdUsrJJM/LjX9/TfJTtdYrx9ku9GLuQfN1jcH6ORmHtquX71cf0CD81pepfyHxzKmtlY4hzM5xON6FNut5X/QraFMf0GY974t+BW3qAxiFfgUAbJKuA+07/v2er+9Ocn8p5d2PsrFSyrsl+dEkp7IdZC87f/XvjrqD0JOpQ+DG4KicjMNi+93dSn2A/1nem6nD7MviOJFVcLwLbdbzvuhX0KY+oM163hf9CtrUB7R50kpf9CsAYNOMEGj/9iS/vPPn6wH0j0jy8lLK3yylPOogGymlPKqU8jeSvCzJn9z1V3Vn+66yMQtzCIHPZQwOzsk4HJ76gMXrB+snzA5tnrQCbcJvfXF+Dm3qA9qs533Rr6BNfUCb9bwv+hUAsInumHoHbqfW+kAp5YuS/EiSh+RGqP3OJPcleU4p5QVJfibbYfU3JHlzkkckeVSSJyf58CRPS/JOuXFH9uvb+aMkX1RrfXA9/yJYr9FC4HMZg4NzMg6Hpz7A+tGbKY/hzp7eWsr2F43hOJHj8qQV2J//Wd4Xx1fQpj6gzXreF/0K2tQHtFnP+6JfAQCbqvtAe5LUWn+slPJ5SZ6X7SB63fmrku2Q+iftfCyyO8i+++vPq7W+YIm7C90YLQQ+lzE4OCfj0Hb18v3Jqafd8rr6AOtHb6Y+hjtzaisvXPEYjhNZNv0KPGmlN46voM2TVqBN+K0v1nNoUx/QZj3vi34FAGyyE1PvwEHVWr8jyZls3319dzj9+p3Wb/exNwj/piR/tdb6nev5F8B6jRYCn8sYHJyTcWi7cvG8O7lCg/WjL3M5hlvXGJDoV5BYz3tjPmAx5+ewP7+c1hfrObSpD2gTZu+LfgUAbLphAu1JUmv990k+LMn9uRFUT26E1Rd9ZNfP/GiSD621ftfadh7WaMRwzxzG4OCcjENbqz7uvOde9cHGs370ZS7HcFOOwXxdvXz/vq/rV2A97435gMNTH2D96I35gDZPWoE2Yfa+WM8BAAYLtCdJrfUVtdZPTHJ3kn+T5NdzsDu0/3qSf5nkg2qtn1Rr/bUJdh9Wbi7hntHG4OCcjEPboouHJ+9++pr3Bvpi/ejLXI7hhNlZBU9agTbreV/MBxye+gDrR2/MByzm/Bz250krfbGeAwBsu2PqHTiqWutLk3x+kpRSHpfkKUkem+TRSR6Z5E1JXp/ktUleUmt9zUS7Cms1Urjn3KVrswgpcXBOxqHNnTCgzfrRl7kHzYXZOY7r/erkXXfd9Pqd99ybE098xkR7BX2wnvfFfEDb1cv3J6eedsvr6gOsH70xH3B46gOsH70xHwAANwwbaN9tJ6z+I1PvB8zFukLg9124ttIxhNn74mQc2oTZoc360Ze5B82F2TmO2z1p5epb17xD0BHreV/MB7RduXg+D77i+cmzbg60qw+wfvTGfMDhqQ+wfvTGfAAA3OzE1DsA9GXKEPhoISUOzsk4tLXqQ22A9aM3cw+aC7NzHH45Ddqs530xH9C26PxcfbDprB99MR/QdvXy/fu+rj7A+tEb8wEAcCuBduAdhNlZFSfjsL9FF6tO3v30CfYI+uFibl/mHjRf1xjMkzA7tFnP+2I+oO12T1qBTWb96Iv5gLYrF8/nysXzt7yuPsD60RvzAQCwP4F2IMl6wj3nLl3b9/XRQkocn5NxcLEKFlEffZk6BG4MeuZJK9BmPe+L+YA2v5wGbdaPvpgPaPOkFWizfvTFfAAAtAm0A2sL99x34dZAuwDR5nEyDi5WwSLqoz9zCIHPZQz64kkr0GY974v5gDZhdmizfvTFfECbJ61Am/WjL+YDAGAxgXbYcFOGe86e3hIg2jBOxsHFKlhEfYxhtBD4XMagL/oVtKmPvpgPaPOkFWizfvTFfECbX06DNutHX8wHAMDtCbTDBpsy3JMkZ05trXQMAaK+OBkHF6tgEfUxhtFC4HMZg77oV9CmPvpjPmB/nrQCbdbzvpgPaBNmhzbrR1/MBwDAwQi0w4aaOsy+LAJEY3AyDi5WwSLqYwyjhcDnMgZ90a+gTX2MwXyAfgWLqI/+mA/YnyetQJv1vC/mAwDg4ATaYQMJs7NuTsbZdC5WQZv6GMNoIfC5jEFf9CtoUx9jMB+gX8Ei6mMM5gM8aQUWsZ73xXwAAByOQDtsmCnDPWdPby1l+4vGECACeuNiFbSpjzGMFgI/d+maMDtLp19Bm/oYg/kA/QoWUR9jMB+gX8Ei6qM/5gMA4HAE2mGDTH2nyjOnlhNoX9e/A+C4XDyENvUxjtFC4PdduLbSMYTZN49+BW3qYwzmA/QrWER9jMF8gH4Fi6iPMZgPAIDFBNphQ0wdZp/DGACH4eIhtKmPzTNlCHy0Y1H6ol9Bm/oYg/kA/QoWUR9jMB+gX8Ei6mMM5gMA4PYE2mEDzD1oLswO9MbFQ2hTH5tHmJ1R6VfQpj7GYT7YdPoVtKmPMZgP0K9gEfUxBvMBAHAwAu0wc3MPmguzA71x8RDa1MfmWccx3LlL1/Z9fbRjUfqiX0Gb+gBGoV9Bm/oYh/lg0+lX0KY+xmA+AAAOTqAdZmzuQXNhdqA3Lh5Cm/rYPOs6hrvvwq2B9tGORemLfgVt6gMYhX4FbeoDGIV+BW3qYwzmAwDgcATaYabmHjQXZgd64+IhtKmPzTPlMdzZ01tDHYvSF/0K2tQHMAr9CtrUBzAK/Qra1Mc4zAcAwOEItMMMzT1ovq4xAA7KxUNoUx+bZ+pfSDxzamulYwizz5d+BW3qAxiFfgVt6gMYhX4FbeoDAIA5E2iHmZk6BG4MYNO4eAht6mPzTB1mXxbHiZtHv4I29QGMQr+CNvUBjEK/gjb1AQDA3N0x9Q4sUkr5+CT/YNdL15L86VrrtYl2Cbo3hxD4XMYA5s/FQ2hTH5tHmJ1R6VfQpj6AUehX0KY+gFHoV9CmPgAA2AS936H9g5M8NcnH7XxcFWaHwxktBD6XMWAVrlw8P/UusIuLh9CmPjbPlMdwZ09vLWX7i8ZwnDhf+hW0qQ9gFPoVtKkPYBT6FbSpDwAANkXvgfZH7HwuO5//11Q7AiMaLQQ+lzFgFVoXq5iGi4fQpj42z9THcGdOLSfQ7jhx8+hX0KY+gFHoV9CmPoBR6FfQpj4AANgkvQfa37bn61dNshcwoNFC4HMZA1ZBmL0vLh5Cm/rYPHM5hlvXGPRDv4I29QGMQr+CNvUBjEK/gjb1AQDApuk90P57e76+Y5K9gMGMGO6ZwxiwCsLsfXHxENrUx+aZyzHclGMwDf0K2tQHtF25eH7qXWAX/Qra1AcwCv0K2tQHAACbqPdA+y/ufK47n999qh2BUcwl3DPaGLAKwux9cfEQ2tTH5pnLMZww++bRr6BNfUCb8/O+6FfQpj6AUehX0KY+AADYVL0H2i8lef2ur586zW7AOEYK95y7dG0WISVYBf+zvC8uHkKb+tg8cw+aC7PPl34FbeoD2pyf90W/gjb1AW2etNIX/Qra1AcAAJus60B7rfXBJN+TpOx8PK2U8p7T7hXM37pC4PdduLbSMYTZGdWii1Wsn4uH0Hb18v3qY8PMPWguzD5f1nNoUx/QJszeF/0K2tQHtFnP+6JfQZv6AABg03UdaN/xNUnekqQmeack/3za3YF5mzIEPlpICVbBxaq+mA9YbL+7W6mP+Zp70FyYfb6s59CmPqBN+K0v+hW0qQ9os573Rb+CNvUBbZ60AgCbo/tAe631t5L89WzfoT1J/nwp5RtKKWXBjwFHIMwO03Kxqi/mAw5PfczX3IPm6xqD9bOeQ5snrUCb8FtfrOfQpj6gzXreF/0K2tQHtFnPAWCzdB9oT5Ja6/OS/O2dL0uSL03yP0spHz3dXsG8rCPcc+7StX1fHy2kBKvgYlVfzAccnvqYr6lD4MbgqKznsJgnrcD+Fq0frJ/1HNrUB7QJv/VFv4I29QFt1nMA2Dx3TL0Dt1NK+didP/6vJF+d5MuTPCTJRyZ5USnlV5L8eJKXJHlNkitJ3n6UsWqtLzru/sKI1hXuee7Lr+WbP2O1YwgQMSIXq/piPqDt6uX7k1NPu+V19TFvcwiBz2UMDs56DoenPsD60RvzAW2etAJtwm99sZ5Dm/qANus5AGym7gPt2Q6r1z2v1Wzfqb0kef8kf2IJ49SM8d8Dlmqd4Z677rr59bOnt/IlTxIgYrO5WNUX8wFtVy6ez4OveH7yrJsD7epj84wWAp/LGByc9RwOT32A9aM35gMW86QV2J8nrfTFeg5t6gPahNkBYHOdmHoHDqHs+ai7Pvb+3VE/YKNMGe5JkjOntlY6hgARvXOxqi/mA9pa9XHnPfeqjw0zWgh8LmNwcNZzaLt6+f59X1cfYP3ojfmAw1MfYP3ojfmANk9agTZhdgDYbCMF2uuej0V/d9gP2DhTh9mXRYCIUbmY2xfzAW2LLh6evPvpa94bpjRaCHwuY3Bw1nNou3LxvDu5QoP1oy/mAw5PfYD1ozfmAxZzfg7786QVAGCUQPuy7sDuzuwQYXaYmou5fTEf0OZOGFw3Wgh8LmNwcNZzaPOkFWizfvTFfECbJ61Am/WjL+YDDk99gPUDANh2x9Q7cABPm3oHYE6mDPecPb21lO0vGkOAiN45Ge+L+YA2YXauGy0Efu7SNWH2DWM9h7bbPWnl6lvXvEPQEetHX8wHtF25eD4PvuL5ybNu/t9l6gOsH70xH3B46gOsHwDADd0H2mutPzH1PsBcTH2nyjOntvLCFY+xzH/Hs5eyJbjByXhfzAe0LbqTK5tntBD4fReurXQMYfa+WM+hzS+nQZv1oy/mA9qu18fJu+666fU777k3J574jIn2Cvpg/eiL+YC2q5fvT07deh9H9QHWDwDgZiem3gFgPaYOs89hDDgOJ+P9MR+wv0X96uTdT59gj5iDKUPgox2LcnCOr6BNmB3arB99MR/QdrsnrcAms370xXxA25WL53Pl4vlbXlcfYP0AAG4l0A4bYO5Bc2F2eudkfAzmA/QrVkOYnVXQr6DNk1agzfrRF/MBbX45DdqsH30xH9C26PxcfbDprB8AwH4E2mHm5h40F2and07Gx2A+QL9iNdZxDHfu0rV9Xx/tWJTD0a9gf560Am2Od/tiPqBNmB3arB99MR/Q5kkr0Gb9AABaBNphxuYeNBdmp3dOxsdgPkC/YjXWdQx334VbA+2jHYtyfPoVWM9hEfXRH/MB+/OkFWiznvfFfECbX06DNusHALCIQDvM1NyD5sLs9M7J+BjMB+hXrMaUx3BnT28NdSzK8elXYD2HRdTHGMwHeNIKLGI974v5gDZhdmizfgAAt3PH1DtwHKWUrSR/MsmHJnlskj+W5OFJaq31s6fcN5jS3IPm6xoDjsrJ+BjMB+hXrMbUv5B45tRW8rbVjSHM3hf9CqznsIj6GIP5gIP0q7r+nYJOWM/7Yz5gf560Am3WcwDgIIYMtJdSPiLJ30nyyUn2JglKtq/sNQPtpZQvS/J+u1764Vrrf1vybsIkpg6BG4NN52R8HOaDTadfsQpTh9mXxXHiGPQrsJ7DIupjDOYD9CtYRH2MwXzAQZ608sD6dwo6YT0HAA5qqEB7KeWRSb49yfUjmnLETb05yRfnxi0t7kki0M4szCEEPpcx2DxOxoFR6FesgjA766RfgfUcFlEfYzAfoF/BIupjDOYDPGkFFrGeAwCHcWLqHTioUsqfSPKz2Q6zl9y4E/vej4M4l+TV1zed5CNKKU9a6g5DJ0YLgc9lDDaPk3FgFPoVqzDlMdzZ01tL2f6iMRwn9ke/YtNZz6FNfYzBfIB+BYuojzGYD9CvYBH1AQAc1hCB9lLKo5P81yRPzM1B9uvB9itJ3n7Q7dVaryX57tx8h/c/s6z9hV6MFgKfyxhsHifjwCj0K1Zh6mO4M6eWE2h3nAiMwnoObepjHOaDTadfQZv6GIP5AP0KFlEfAMBRDBFoT/LtSf5Ebg6yvzzJs5L8sVrro5P84iG3+f/tfL5+V/enL2E/oRujhcDnMgabx8k4MAr9ilWYyzHcusYAOC7rObSpD2AU+hW0qY8xmA/Qr2AR9QEAHFX3gfZSyp/M9t3TrwfZk+Q7knxIrfU/1Fpff5Tt1lovJnnt9WGSnC6llAU/AsMYMdwzhzHYPE7GgVHoV6zCXI7hphwD4DCs59CmPoBR6FfQpj7GYT7YdPoVtKkPAOA4ug+0J/nbu/5ck/z3Wutn11rfvoRt/0xuhOQfluT9lrBNmNRcwj2jjcHmcTIOjEK/YhXmcgwnzA6MwnoObeoDGIV+BW3qAxiFfgVt6gMAOK6uA+2llDuSPD037s7+QJIvWuIQ/3vP1x+wxG3DJEYK95y7dG0WISU2j5NxYBT6Fasw96C5MDvQG+s5tKkPYBT6FbSpD2AU+hW0qQ8AYBm6DrQn+YgkJ3f+XJP8WK3115e4/d/d8/UfX+K2YVjrCoHfd+HaSscQZmcVnIwDo9CvWIW5B82F2YHeWM+hTX0Ao9CvoE19AKPQr6BNfQAAy9J7oP199nz9E0ve/hv2fP3IJW8fhjNlCHy0kBKbx8k4MAr9ilWYe9BcmB3ojfUc2tQHMAr9CtrUBzAK/Qra1AcAsEy9B9rfdedz2fn8qiVv/3rCoO58fviStw9DEWaHNifjwCj0K1Zh7kHzdY0BcFDWc2hTH8Ao9CtoUx/AKPQraFMfAMCy9R5of+c9X791ydt/9M7n64H5Ny55+zCMdYR7zl26tu/ro4WU2DxOxqHtysXzU+8Cu+hXrMLUIXBjAJvGeg5t6gMYhX4FbeoDGIV+BW3qAwBYhd4D7b+/5+tHLXn773Wb8WAjrCvcc9+FWwPtAkT0zsk4tLXqg2noV6zKHELgcxkDmD/rObSpD2AU+hW0qQ9gFPoVtKkPAGBVeg+0v2bnc935/L5L3v7HNsaDjTFluOfs6S0BIrrmZBzahNn7ol+xTqOFwOcyBqyCJ630xXoObeoDGIV+BW3qAxiFfgVt6gMAWKXeA+2v2PP16WVtuJTybkk+KjfC8g8k+ellbR9GMGW4J0nOnNpa6RgCRByHk3FoE2bvi37FOo0WAp/LGLAK1vO+WM+hTX1Am19O64t+BW3qAxiFfgVt6gMAWLWuA+211pcm+Z2dL0uSjymlvNeSNv/sJLvTtP+71vqmJW0bujd1mH1ZBIhYhauX73cyDg3Cb31x8ZB1Gi0EPpcxYBWs532xnkOb+oA263lf9CtoUx/AKPQraFMfAMA6dB1o3/Gj2Q6z12zv71ccd4OllI9J8mU727y+7f963O3CKITZYbH97m7lZBz8z/LeuHjIOo0WAp/LGLAK1vO+WM+hTX1Am/W8L/oVtKkPaPOklb7oV9CmPgCAdRkh0P4N2Q6cJ9vh888qpfzFo26slHI6yfcnuWPXy29O8i1H3kMYyJThnrOnt/b57uWOIUDEKjgZh8UXq1g/Fw9Zp9FC4OcuXRNmhwbht75Yz6FNfUCb9bwv+hW0qQ9os573Rb+CNvUBAKxT94H2WuvlJN+bG3dSL0n+XSnlb5VSykG3U0p5l1LKVyZ5QZJ3zc13Z//XtdY/WPrOQ2emvlPlmVPLCbSv698BiZNxSFys6o35YN1GC4Hfd+HaSscQZmdU/md5X6zn0KY+oM163hf9CtrUB7RZz/uiX0Gb+gAA1q37QPuOZyf57Z0/12zfXf1rkvxKKeXvl1I+PslNyYFSyiNLKR9cSvkrpZT/kOQ3k/z9JFu5ccf3muQXkvzDNfwbYFJTh9nnMAbzdfXy/fu+7mQcXKzqjflgVFOGwEc7FoVV8KSVvljPoe3q5fvVBzQIv/XFeg5t6gParOd90a+gTX0AAFO4Y+odOIha66tLKZ+a5MVJHpEbd1d/vyRfuetby67Pb9izmet/V/d8z7211rctf6+hH3MPmguzcxxXLp7Pg694fvKsp930upNxcLGqN+aDUQmzw7SsH30xH7DYlYvnb3lNfYBfTuuN9Rza1Ae0CbP3Rb+CNvUBAExllDu0p9b6c0k+Pskrsx1Gr7kRbL/+sVvZ83H9+6//3a8n+Zha66+ufOdhQnMPmguzcxytk/E777nXyTgbz8WqvpgPRrWOY7hzl67t+/pox6KwCtaPvpgPODz1AdaP3pgPaPOkFWgTZu+L9Rza1AcAMKVhAu1JUmv9mSQfmuR7cyPMXg/4kdwIt//HJB9Ra33pOvcf1m3uQXNhdo5j0cXDk3c/fc17A31xsaov5oNRresY7r4LtwbaRzsWhVWwfvTFfMDhqQ+wfvTGfMBinrQC+/Oklb5Yz6FNfQAAUxsq0J4ktdY31Fr/UpIPTPLtSd6QW+/Gvt/HW7IdZP+wWuun11r/YP17D+sz96C5MDvH4U4Y0OZiVV/MB6Oa8hju7OmtoY5FYRWsH30xH9B29fL9+76uPsD60RvzAYenPsD60RvzAW2etAIA9OCOqXfgqGqtv5zkc5J8Tinlg5N8dJL3SvLHkjw6yVuTvC7J7yW5mORCrfWPJtpdWKu5B83XNQbzJMwObS7m9sV8MKqpfyHxzKmt5G2rG0OYnd5ZP/piPqDtysXzefAVz0+e9bSbXlcfYP3ojfmAw1MfYP3ojfmAxTxpBQDowbCB9t1qrT+f5Oen3g/owdQhcGPQs9bFKifi4GJub8wHo5o6zL4sjhMZlfWjL+YD2q7Xx8m77rrp9TvvuTcnnviMifYK+mD96Iv5gLarl+9PTj3tltfVB1g/emM+4PDUBwAwhRNT7wCwXHMIgc9lDPqy6GLVybufPsEeQT9czO2L+WBUwuwwLetHX8wHtC16cprzczad9aMv5gParlw8706u0GD96Iv5gMNTHwDAVATaYeZGC4HPZQz64mIVtKmPvpgPRjXlMdzZ01tL2f6iMRwn0jvrR1/MB7QtCrPDprN+9MV8QNuiJ6GqDzad9aMv5gParl6+f9/X1QcAMCWBdpix0ULgcxmDvrhYBW3qoz/mgxFNfQx35tRyAu2OExmV9bwv5gPahNmhzfrRF/MBbZ60Am3Wj76YD2jzpBUAoFcC7TBTo4XA5zIGfXGxCtrUxxjMB72byzHcusaAZbOe98V8QNuiO7nCprN+9MV8QJtfToM260dfzAe0edIKANCzO6begeMqpbxnko9M8pQkj0vyqCSPTPKmJG9I8pokP5vkp2qtvz3NXsJ6jRjumcMY9MXFKmhTH2MwH/RuLsdw6xzj2UvZGmyznvfHfMD+FvWr7Tu5PrD+nYJOWM/7Yj6gTZgd2qwffTEf0Ha7J61cfeuadwgAYI8hA+2llEcmeVaSz0/y/zvEz700yb9M8l211jetaPdgUqOGe0Yfg764WAVt6mMM5oPezeUYbsox4Dis52MwH3CQflXXv1PQCet5f8wH7M+TVqDNet4X8wFtfjkNABjBial34LBKKc9K8utJvjnJByUph/j4oCT/Ismvl1L+ytp3HtZgpHDPuUvXZhFSoi8uVkGb+hiD+aB3cw+aC7PTO+v5GMwH6FewiPoYg/mAgzxpBTaX9bwv5gPahNkBgFEME2gvpbxTKeU/JfnOJI/JdkA92b6Nz0E/svNzj0lyrpRyvpQi0Qp7rCsEft+FaysdQ5h987hYBW3qYwzmg97NPWguzE7vrOdjMB+gX8Ei6mMM5gP0K1hEffTHfMD+PGkFABjJEIH2UsrDkvyXJH8624H03SH1/e7Ensbre3/uzyT5z0LtcMOUIfDRQkr0xcVDaFMf4zAf9GzuQXNhdnpnPR+D+QD9ChZRH2MwH6BfwSLqYwzmAzxpBQAYzxCB9iTfnOT60dTuO62XJD+Z5GyST0jynklO1lofkuTkztcfv/P3P5mbA+/XQ+1P39k+bDxhdkbl4iG0qQ9gGeYeNF/XGHBU1vMxmA/Qr2AR9TEG8wH6FSyiPsZgPkC/AgDG1H2gvZTysUk+KzeC7Ml2EP3Hk9xda/3oWuvX11pfWGv93VrrW5Kk1vqWna9/fOfvPzrJ3UlemFtD7Z9dSvmYdf2boEfrCPecu3Rt39dHCynRFyfj0KY+gGWYOgRuDDad9Xwc5oNNp19Bm/oYg/kA/QoWUR9jMB+gXwEA4+o+0J7k7+RGAP3656+utX58rfWlh9lQrfWltdZPSPLPdm1r9ziwkdYV7rnvwq2BdgEijsPJOLSpD2BZ5hACn8sYbB7rOTAK/Qra1Mc4zAebTr+CNvUxBvMB+hUAMLauA+2llEcn+YTcuJN6TfLttda/d5zt1lr/QZJ/u2ubJcnTd8aDjTJluOfs6S0BIo7MyTi0qQ9glUYLgc9lDDaP9RwYhX4FbeoDGIV+BW3qYwzmA/QrAGB8XQfak3xUkofu+vpKkr+5pG3/rSRv3PX1HTvjwcaYMtyTJGdOba10DAGi+XIyDm3qA1il0ULgcxmDzWM9B0ahX0Gb+gBGoV9Bm/oYh/lg0+lXAMAc9B5of89df65JfrDW+qZlbLjWeiXJD2b77uz7jQezNnWYfVkEiDaPk3FoUx/AKo0WAp/LGGwe6zkwCv0K2tQHMAr9CtrUBzAK/QoAmIveA+3vuvP5euj8Z5a8/Z/e8/Vjl7x96JIwO6NyMg5t6gNYpdFC4HMZg81jPQdGoV9Bm/oARqFfQZv6AEahXwEAc9J7oP2te77+vSVv/zU7n+vO57ctefvQnSnDPWdPby1l+4vGECCaLyfj0KY+gFUaLQR+7tI1YXaGZD0HRqFfQZv6AEahX0Gb+gBGoV8BAHPTe6D9t/Z8/aglb//69q7fAf5VS94+dGXqO1WeObWcQPu6/h30w8k4tKkPYNVGC4Hfd+HaSscQZmcVrOfAKPQraFMfwCj0K2hTH8Ao9CsAYI56D7T/7M7n63dQf/KSt/+kxngwO1OH2ecwBtNwMg5t6gMYxZQh8NGORdk81nNgFPoVtKkPYBT6FbSpD2AU+hUAMFddB9prrb+e5PLOlyXJvaWUsuBHDmxnO38u22H5muRltdZfW8a2oTdzD5oLs8+Xk3FoUx/QduXi+al3gV2E2aHNeg6MQr+CNvUBjEK/gjb1AYxCvwIA5qzrQPuOb8x2mL0muSvJly1pu389yeN3tp0k37Ck7UJX5h40F2afLyfj0KY+oK1VH0xjHcdw5y5d2/f10Y5F2TzWc2AU+hW0qQ9gFPoVtKkPYBT6FQAwd90H2mut35Hkf2Q7eF6SPKeU8snH2WYp5ZOS/LPcuDv7hVrr8467r9CbuQfNhdnny8k4tKkPaBNm78u6juHuu3BroH20Y1E2j/Uc2jxppS/6FbSpD2AU+hW0qQ9gFPoVALAJug+07/hzSX5p588PS/IDpZR/UErZOsxGSikPLaX8/SQ/sLOdkuSXkzi6Y3bmHjQXZp8vJ+PQpj6gTZi9L1Mew509vTXUsSibx3oObdbzvuhX0KY+oM0vp/VFv4I29QGMQr8CADbFEIH2Wutrk3xUkh/aeemhSf5xkleUUv5pKeUjWuH2UspWKeXDSyn/NMkrknxlkq1s35n9h5J81M72YTbmHjRf1xisn5NxaLt6+X71AQ3Cb32Z+hcSz5w61O89H3oMYXaOw/EutFnP+6JfQZv6gDbreV/0K2hTH8Ao9CsAYJPcMcWgpZQXHOPH35bknbJ9d/X3SvJ3dz7eXkp5ZZI3JnlzkkckeZckj8+Nf2fZ+Vx3tvOIJOdLKUlSa62fcIz9gi5MHQI3BkflZBwW2+/uVuoD/M/y3kwdZl8Wx4msguNdaLOe90W/gjb1AW3W877oV9CmPqBt+/9FPXPq3WCHfgUAbJpJAu1JnprtUPlxXP/56yH1hyZ5wq6/K7f8xM1jPizJx+3axnH3B7owhxD4XMbg4JyMw+GpD1i8frB+wuzQ5kkr0Cb81hfn59CmPqDNet4X/Qra1Ae03aiP5029K0S/AgA201SB9qPaL3jeCqIfJKAuyM7sjRYCn8sYHJyTcTg89QHWj95MeQx39vTWUra/aAzHiRyXJ63A/oTf+uL4CtrUB7RZz/uiX0Gb+oA263lf9CsAYFOdmHj8csiPo/zMQbbXrVLKY0opn1hK+XullPOllN8spdS9H1PvZ5KUUn5jv3074sffmfrfMwejhcDnMgYH52Qc2q5evn/f19UHWD96M/Ux3JlTywm0O05knfQr8KSV3ji+gjZPWoE24be+WM+hTX1Am/W8L/oVALDJprpD+4vizuj7KqV8UJJnJnlKkg9P8r7T7hGjGi0EPpcxODgn49B25eL5PPiK5yfPetpNr6sPsH70podjuCtrGGMZvv7CH+bZS9kSo9OvwHreG/MBi3nSCuzPL6f1xXoObeoD2oTZ+6JfAQCbbpJAe631qVOMO4jPSfLXp94JxjZaCHwuY3BwTsah7Xp9nLzrrptev/Oee3Piic+YaK+gD9aPvszlGG6dYwi0b46rl+9PTj3tltf1K7Ce98Z8wOGpD7B+9MZ8QJsnrUCbMHtfrOcAANPdoZ3N8Pokrzziz/7eMndkk4wa7hl9DA7OyTi0Lbp4ePLup+fqW9e8Q9AR60df5nIMN+UYzJcnrUCb9bwv5gMOT32A9aM35gMW86QV2J8nrfTFeg4AsE2gfRzXkvxCkp9J8n8ledSke3Mw/7nW+tem3olNM1K459yla7MIKXFwTsahzZ0woM360Ze5B82F2TkOT1qBNut5X8wHtHnSCrRZP/piPuDw1AdYP3pjPgAAbhBo79Pbk/xitsPr1z9+rtZ6LUlKKf9Hxgi0M6h1hcDvu3BtpWMIs/fFyTi0CbNDm/WjL3MPmguzcxyetAJt1vO+mA9o86QVaLN+9MV8wOGpD7B+9MZ8AADcTKC9P1+T5O/WWv2vbiYxZQh8tJASB+dkHNpa9aE2wPrRm7kHzYXZOQ6/nAZt1vO+mA9o86QVaLN+9MV8QJsnrUCb9aMv5gMA4FYnpt4BblZr/V1hdqYizM6qOBmH/S26WHXy7qdPsEfQDxdz+zL3oPm6xmCehNmhzXreF/MBbbd70gpsMutHX8wHtF25eD5XLp6/5XX1AdaP3pgPAID9CbQDSdYT7jl36dq+r48WUuL4nIyDi1WwiProy9QhcGPQM09agTbreV/MB7T55TRos370xXxA26Lzc/XBprN+9MV8AAC0CbQDawv33Hfh1kC7ANHmcTIOLlbBIuqjP3MIgc9lDPriSSvQZj3vi/mANmF2aLN+9MV8QJsnrUCb9aMv5gMAYLE7pt6BoyqlbCW5O8kHJHlUkndJ8tDjbLPW+pXH3zMYyzrDPXfddfPrZ09v5UueJEC0SZyMg4tVsIj6GMNoIfC5jEFfbt+v6vp3CjphPe+L+YA2T1qBNutHX8wHtPnlNGizfvTFfAAA3N5QgfZSyokkn57kM5M8Lcvff4F2NsqU4Z4kOXNqK3nb6sYQIOqLk3FwsQoWUR9jGC0EPpcx6It+BW3qoz/mA/Z3+yetPLD+nYJOWM/7Yj6gTZgd2qwffTEfAAAHM0ygvZTylCTfluRDrr+05CHcPm35nlBK+eokp5O8T5J3TfJgkt/f+fi5JC9K8vxa629NtZObauow+7IIEI3ByTi4WAWLqI8xjBYCn8sY9EW/gjb1MQbzAZ60AotYz/tjPmB/nrQCbdbzvpgPAICDGyLQXkr5hCQ/mOThuRFkX+ZV5WWH49n2p3Y+9nrnJHclOZXkTJIHSinfl+Rraq2X1rZ3G0yYnXVzMs6mc7EK2tTHGEYLgc9lDPqiX0Gb+hiD+QD9ChZRH2MwH+BJK7CI9bwv5gMA4HC6D7SXUu5K8gPZDkEnN4LsQujz8ZAkfzHJp5dSviLJP6u1ruQ2OKWUx2X7TvGH8YTdX1y9ejVXrlxZ3k4t28Pec+Ffn7t0Lc99+bXcddfNr589vZUzp7ayjH9Za4y/90k3v/DmrcctfYxl/jvS8zwP5t0f3vedrR77sLrw65503X8Gs6735dXL9+fBVzw/J/c0rDvvuXfn4vr+++F9uZk2rV8etT4Owvtyeb7pLzxh5ceJxzmG23tM+d2/9ug89+WPm+R497ZjeF8uzbr75WH7lXV8M23aOn7dKtZz78vluWtnXpZxfLUKI/XLxHtzmabomQftV96Xm6vntXzV78tlr+fel8tz16456W091y8315T98nb9yvtyc23yOn7dstZz78vlObmi//+xDPrl8ly9enXqXQCA2Sgryg0vTSnle5L8hdwaZP9vSb4/yf9O8htJ3lRrffvad3ACpZTfSPLeu1+rtU4e8N9vv5I8mOQ1Sa7s/PmP7XycWLCpH0jy52utS//1+VLKP0ryFcfZxjd90zfl8Y9//HJ2CAAAAAAAAAAAGM4rX/nKfOmXfunulz6o1vrSqfYHAEbW9R3aSymPTPJnc3OY/TVJ/lyt9X9OtmMs8kCSn0jyI0l+PMkv1lrfsvsbSimPSvLRSf5akntza7j9/0zyzUm+cKV7CgAAAAAAAAAAAABMqutAe5KPS7KV7UB7yXZY+lNqrS+ZdK9ouS/Jf661/taib6q1viHJDyX5oVLKByf5f5M8ac+3fUEp5cdqrf9xJXsKAAAAAAAAAAAAAEyu90D7e+36c812WFqYvVO11m85ws/8fCnlniQvTvIhe/76OaWUH6i1PrCUHdz2rUm+75A/84QkP3j9i3vuuSdPfvKTl7hLS/atH3nTl+cuXct9F67d8m1nT2/lzKmtpQx50DHevPW4XHzC33jH1/f86jfkEddes9QxjmPvGL/wC7+wlO2SfOI3vGjqXVjosQ+r+dwnPfiOr7/t5SfyureVCfeo7Uf/xsdOvQuzsar35dXL9+fKxfO3vH7nPffm5N1PP/B2vC8309z75bLq4yC8L5doz/HlYazjGO67f+3ReY9nfvk7vn7Oc56TV7/61ZMc797WF/7UUvaH1ffL4/Yr6/hmmvs6ft061nPvy+XZlPflunhvLs863ptH7Vfel5ur55657Pflqtdz78vl2aT35ap5Xy7POt+Xh+1X3pebaxP75arWc+/L5fmgD/qglfz/j2XQL5fnZS972dS7AACz0Xug/TE7n0u2A+0vmHBfWJFa65tKKZ+W5GVJHrHrrz4gyacl+YEljvWaJAdLUO8o5eaD9pMnT+bOO+9c1i4t39t++x1//PoLf5i/9fw/vOVbvu4Z75QvedI7JW87/nDHGeMR116TO3ft7yrGOKj9xuh6ngfz6rf2e/K7n9e9rXS7z96Xy7OKOb5y8Xxe/8Jvv+X1Rz/ts3Liic/I1bcefdvel5uh1zluOcz7cpX1sR/vyyU6wPHaftZ1DPfclz8u3/zMG6+9+tWvzl9/0mu6ON69hffl0qyyX66iX1nHN0Ovc9xylPflutZz78vl2YT35Tp5by7Pqud5mf3K+3Jz9DzPex3nfbmO9dz7cnk25X25Dt6Xy7OueV5Gv/K+3Bw9z/Ney3hfrnI9975cnqtPfMZK/v/HKuiXR3fy5MmpdwEAZuPE1DtwG1f3fP17k+wFK1dr/a0k37jPX33ymndlNhYFb559+p2McYAxAA5j0cXDO++5d4I9gn6oj80z5THc2dNbQx2L0hf9CtrUBzAK/Qra1AcwCv0K2tTHOMwHAMDh9B5o/409Xz9yip1gbb57n9c+Ye17MQNzD5qvawyAg3LxENrUx+aZ+hcSz5zaWukYwuzzpV9Bm/oARqFfQZv6AEahX0Gb+gAAYM56D7T/dJK685Ek7zvhvrBitdZfTPLaPS/fNcW+jGzqELgxgE3j4iG0qY/NM3WYfVkcJ24e/Qra1AcwCv0K2tQHMAr9CtrUBwAAc9d1oL3W+rtJLiQpOy990oS7w3r87p6vt0op7zLJngxqDiHwuYwBzJ+Lh9CmPjaPMDuj0q+gTX0Ao9CvoE19AKPQr6BNfQAAsAm6DrTv+NqdzyXJU0opT51uV1iDN+/z2sPXvhczMloIfC5jwCpcuXh+6l1gFxcPoU19bJ4pj+HOnt5ayvYXjeE4cb70K2hTH8Ao9CtoUx/AKPQraFMfAABsiu4D7bXW/5LkP+166dtKKY+dan9YuXfd57XfX/tezMRoIfC5jAGr0LpYxTRcPIQ29bF5pj6GO3NqOYF2x4mbR7+CNvUBjEK/gjb1AYxCv4I29QEAwCbpPtC+4zOTvCTbd2l/vyQ/Vkr5gGl3iWUrpTwiyeP3vPyGWusfTbE/oxstBD6XMWAVhNn74uIhtKmPzTOXY7h1jUE/9CtoUx/AKPQraFMfwCj0K2hTHwAAbJohAu211itJPiHJj2Y71H53kpeUUv5lKeUjSilD/Du4rU9Isvf2ij83xY6MbsRwzxzGgFUQZu+Li4fQpj42z1yO4aYcg2noV9CmPqDtysXzU+8Cu+hX0KY+gFHoV9CmPgAA2ER3TL0DB1VrfWMp5ZOTfFmSr0zyiCT/987HW0opv5nk9UmOejfvWmv9hGXsK0f2t/d57UfWvheDm0u4Z7QxYBWE2fvi4iG0qY/NM5djOGH2zaNfQZv6gLYb9fG8qXeF6FewiPoARqFfQZv6AABgUw0TaN/xXkk+INt3aa87n5PtcPsH7rx2FNe3x0RKKV+U5PSelx9M8p8m2J2hjRTuOXfp2ixCSrAKwux9cfEQ2tTH5pl70FyYfb70K2hTH9Dm/Lwv+hW0qQ9o237SyjOn3g126FfQpj4AANhkJ6begYMqpXxOkpcl+dwkD995ue754BhKKT9eSql7Pv7aAX7uE0spn3SMcT8zyXP3+atztdZfPup2Obp1hcDvu3BtpWMIszOqRRerWD8XD6Ht6uX71ceGmXvQXJh9vqzn0KY+oE2YvS/6FbSpD2iznvdFv4I29QEAwKYbItBeSnl2kn+d5J1z467sN33LMT84ng9M8iOllJeUUr60lPKeB/mhUsoHllL+3yTfnuQhe/7695P8wyXvJwcwZQh8tJASrIKLVX0xH7DY9t2tbqY+5mvuQXNh9vmynkOb+oA24be+6FfQpj6gzXreF/0K2tQHtO33/6IAgHm6Y+oduJ1Syp9M8rU7X+6+C/v1IPobk7wyyZuS/NEad21lSik/nOSPL/iWW/6ulHLpNpv9lFrr7xxnvw7gQ3c+vrGU8rIkP5fkpUlel+15qkkek+SJST4myYdn/18oeEuSZ9Zaf3vF+8sewuwwLRer+mI+4PDUx3zNPWi+rjFYP+s5tHnSCrQJv/XFeg5t6gParOd90a+gTX1A2436eN7UuwIArEH3gfYkX53t0PP1MHtJ8pokX5fkP9Zaf32qHVuhD0zy3of8mQ+5zd9vHXFfjqJk+9/wgUf42Vcl+cu11v+13F3idtYR7jl36Voe/+RbXx8tpASr4GJVX8wHHJ76mK+pQ+DG4Kis57CYJ63A/hatH6yf9Rza1Ae0CbP3Rb+CNvUBbdZzANg8J6begUVKKY9P8nHZDrNfv5P3/0jyAbXWr5tpmH1TvT3Jv0vywbXWF029M5tmXeGe+y5cW/kYAkSMyMWqvpgPaLt6+f59X1cf8zaHEPhcxuDgrOdweOoDrB+9MR/Q5kkr0Cb81hfrObSpD2izngPAZuo60J7ko/Z8fSXJn6u1vnGKnaHpeUn+dJJ/nuQnk7z5gD/3YJLLSf5pkveptZ6ptb5+NbtIy5ThnrOntwSI2HguVvXFfEDblYvn3cmVJOOFwOcyBgdnPYfDUx9g/eiN+YDFnJ/D/jxppS/Wc2hTH9AmzA4Am+uOqXfgNt5z159rku+rtb52qp1Zl1rr+0w07lOP+HNvSvJfdj5SSjmR5H2TvHeSu5I8Osk773z7G5O8PsnvJPmZWuvV4+01xzFluCdJzpzaSt62ujEEiOidi1V9MR/Qdr0+Tt51102v33nPvTnxxGdMtFdMYbQQ+FzG4OCs59B29fL9yamn3fK6+gDrR2/MBxye+gDrR2/MB7R50gq0CbMDwGbrPdD+sJ3PJduB9v814b5wQLXWB5P86s4HnZo6zL4sAkSMysXcvpgPaFt08fDk3U/P1beueYeYzGgh8LmMwcFZz6HtysXzefAVz0+edXOgXX2A9aM35gMOT32A9aM35gMW86QV2J8nrQAAJ6begdt4456v3zDFTsDcCLPDtFzM7Yv5gDZ3wuC60ULgcxmDg7OeQ1urPu685171wcazfvTFfEDb1cv37/u6+gDrR2/MBxye+gDrBwCwrfdA+6/sfK47nx8z1Y7AXEwZ7jl7emsp2180hgARvXMy3hfzAW3C7Fw3Wgj83KVrwuwbxnoObbd70gpsMutHX8wHtF25eN6dXKHB+tEX8wGHpz7A+gEA3NB7oP2nkrx919cfNNWOwBxMfafKM6eWE2hf178Dls3JeF/MB7QtupMrm2e0EPh9F66tdAxh9r5Yz6HNL6dBm/WjL+YD2jxpBdqsH30xH9DmSSvQZv0AAHbrOtBea72S5EeSlJ2PTyullGn3CsY0dZh9DmPAcTgZ74/5gP0t6lfu5MpRTRkCH+1YlINzfAVtwuzQZv3oi/mANk9agTbrR1/MB7R50gq0WT8AgL26DrTv+KdJHkxSk7x3ks+ZdndgPHMPmguz0zsn42MwH6BfsRrC7KyCfgVtnrQCbdaPvpgPaPPLadBm/eiL+YA2T1qBNusHALCf7gPttdafTvJV2b5De5L881LKPRPuEgxl7kFzYXZ652R8DOYD9CtWYx3HcOcuXdv39dGORTkc/Qr250kr0OZ4ty/mA9qE2aHN+tEX8wFtnrQCbdYPAKCl+0B7ktRa/2GSb8t2qP0RSX6slPJZ0+4V9G/uQXNhdnrnZHwM5gP0K1ZjXcdw9124NdA+2rEox6dfgfUcFlEf/TEfsD9PWoE263lfzAe0+eU0aLN+AACLDBFoT5Ja6+cl+bIkf5jtUPu3lVJeVkr58lLKR5ZSHltKecikOwkdmXvQXJid3jkZH4P5AP2K1ZjyGO7s6a2hjkU5Pv0KrOewiPoYg/kAT1qBRaznfTEf0CbMDm3WDwDgdu6Yegdup5TywD4v12zfrf0DknzVnu8/6lC11tr9fw84iLkHzdc1BhyVk/ExmA/Qr1iNqX8h8cypreRtqxtDmL0v+hVYz2ER9TEG8wEH6Vd1/TsFnbCe98d8wP48aQXarOcAwEGMEODeL6Fec+Pq3ZET7DBHU4fAjcGmczI+DvPBptOvWIWpw+zL4jhxDPoVWM9hEfUxBvMB+hUsoj7GYD7gIE9a2e8+jrAZrOcAwEGNEGhPFt96Yhm3pRCKZzbmEAKfyxhsHifjwCj0K1ZBmJ110q/Aeg6LqI8xmA/Qr2AR9TEG8wGetAKLWM8BgMMYJdAucA5HNFoIfC5jsHmcjAOj0K9YhSmP4c6e3lrK9heN4TixP/oVm856Dm3qYwzmA/QrWER9jMF8gH4Fi6gPAOCwRgi0/+OpdwBGNVoIfC5jsHmcjAOj0K9YhamP4c6c2soLVzyG40SgJ9ZzaFMf4zAfbDr9CtrUxxjMB+hXsIj6AACOovtAe61VoB2OYLQQ+FzGYPM4GQdGoV+xCj0cw11ZwxjL8PUX/jDPXsqWgE1mPYc29QGMQr+CNvUxBvMB+hUsoj4AgKM6MfUOAMs3Wgh8LmOweZyMA6PQr1iFuRzDTTkGwGFYz6FNfQCj0K+gTX2Mw3yw6fQraFMfAMBxCLTDzMwl3DPaGGweJ+PAKPQrVmEux3DC7MAorOfQpj6AUehX0KY+gFHoV9CmPgCA4xJoh5kZKdxz7tK1WYSU2DxOxoFR6FeswtyD5sLsQG+s59CmPoBR6FfQpj6AUehX0KY+AIBlEGgHbrGuEPh9F66tdAxhdlbByTgwCv2KVZh70FyYHeiN9Rza1AcwCv0K2tQHMAr9CtrUBwCwLALtwE2mDIGPFlJi8zgZB0ahX7EKcw+aC7MDvbGeQ5v6AEahX0Gb+gBGoV9Bm/oAAJZJoB14B2F2aHMyDoxCv2IV5h40X9cYAAdlPYc29QGMQr+CNvUBjEK/gjb1AQAsm0A7kGQ94Z5zl67t+/poISU2j5NxaLty8fzUu8Au+hWrMHUI3BjAprGeQ5v6AEahX0Gb+gBGoV9Bm/oAAFbhjql34HZKKf/PusaqtX7lusaCnqwr3PPcl1/LN3/GascQIGLZnIxD2436eN7Uu0L0K1ZnDiHwuYwBzJ/1HNrUBzAK/Qra1AcwCv0K2tQHALAq3Qfak/yjJHVNYwm0s3HWGe65666bXz97eitf8iQBIvrlZBzaWvXBNPQr1mm0EPhcxoBV2H7SyjOn3g12WM+hTX0Ao9CvoE19AKPQr6BNfQAAq3Ri6h04hLLiD9g4U4Z7kuTMqa2VjiFAxHE4GYc2Yfa+6Fes02gh8LmMAatgPe+L9Rza1Ae0bf9yGr3Qr6BNfQCj0K+gTX0AAKs2UqC9rvADNs7UYfZlESBiFa5evt/JODQIv/XFxUPWabQQ+FzGgFWwnvfFeg5t6gParOd90a+gTX0Ao9CvoE19AADrMEqgfRV3YXd3djaWMDsstt/drZyMg/9Z3hsXD1mn0ULgcxkDVsF63hfrObSpD2iznvdFv4I29QFtnrTSF/0K2tQHALAu3Qfaa60njvqRZCvJeyT5mCT/IMmv50aA/a1JPm/X9z9kmn8hrNeU4Z6zp7eWsv1FYwgQsQpOxmHxxSrWz8VD1mm0EPi5S9eE2aFB+K0v1nNoUx/QZj3vi34FbeoD2qznfdGvoE19AADr1H2g/ThqrW+vtf5erfV/1lr/WZL3T/JlSa4leViSf1VK+aop9xHWaeo7VZ45tZxA+7r+HZA4GYfExaremA/WbbQQ+H0Xrq10DGF2RuV/lvfFeg5t6gParOd90a+gTX1Am/W8L/oVtKkPAGDdZh1o36vW+mCt9ZuSfGqSt2f7bu1fXkr5skl3DNZg6jD7HMZgvq5evn/f152Mg4tVvTEfjGrKEPhox6KwCp600hfrObRdvXy/+oAG4be+WM+hTX1Am/W8L/oVtKkPAGAKGxVov67W+mNJ/p+dL0uSryqlPGnCXYKVmnvQXJid47hy8XyuXDx/y+tOxsHFqt6YD0YlzA7Tsn70xXzAYs7PYX9+Oa0v1nNoUx/QJszeF/0K2tQHADCVjQy07/jGJK9JUpNsJfmHk+4NrMjcg+bC7BxH62T8znvudTLOxnOxqi/mg1Gt4xju3KVr+74+2rEorIL1oy/mAw5PfYD1ozfmA9o8aQXahNn7Yj2HNvUBAExpYwPttdY/TPLD2b5De0lybynlnafdK1iuuQfNhdk5jkUXD0/e/fQ17w30xcWqvpgPRrWuY7j7LtwaaB/tWBRWwfrRF/MBh6c+wPrRG/MBi3nSCuzPk1b6Yj2HNvUBAExtYwPtO35215+3knzUVDsCyzb3oLkwO8fhThjQ5mJVX8wHo5ryGO7s6a2hjkVhFawffTEf0Hb18v37vq4+wPrRG/MBh6c+wPrRG/MBbZ60AgD0YNMD7a/d8/UHTLIXsGRzD5qvawzmSZgd2lzM7Yv5YFRT/0LimVNbKx1DmJ3eWT/6Yj6g7crF8+7kCg3Wj76YDzg89QHWj96YD1jM+TkA0INND7RfTzrUnc/vMtWOwLJMHQI3Bj1rXaxyIg4u5vbGfDCqqcPsy+I4kVFZP/piPqBt0fm5+mDTWT/6Yj6gzZNWoM360RfzAYenPgCAKWx6oP2JO5/Lzue3TLUjsCxzCIHPZQz6suhi1cm7nz7BHkE/XMzti/lgVMLsMC3rR1/MB7QtenKa83M2nfWjL+YD2jxpBdqsH30xH3B46gMAmMqmB9r/bG7cnT1JXjfVjsCqjBYCn8sY9MXFKmhTH30xH4xqymO4s6e39vnu5Y7hOJHeWT/6Yj6gbVGYHTad9aMv5gPaPGkF2qwffTEf0OZJKwBAjzY20F5K+b+T3L3n5Z+bYl9gVUYLgc9lDPriYhW0qY/+mA9GNPUx3JlTywm0O05kVNbzvpgPaBNmhzbrR1/MB7R50gq0WT/6Yj6gzZNWAIBebVygvWz7G0n+RW6+O/vv1lp/YaLdgqUbLQQ+lzHoi4tV0KY+xmA+6N1cjuHWNQYsm/W8L+YD2hbdyRU2nfWjL+YD2vxyGrRZP/piPqDNk1YAgJ7dMfUO3E4p5fHH3MRDk9yZ5P2S3JPk/0ry+CQl24H265+/+ZjjQDdGDPfMYQz64mIVtKmPMZgPejeXY7h1jvHspWwNtlnP+2M+YH+L+tX2nVwfWP9OQSes530xH9AmzA5t1o++mA9ou92TVq6+dc07BACwR/eB9iS/kZvvpH5cZefz7m2+Isk3LnEMmMyo4Z7Rx6AvLlZBm/oYg/mgd3M5hptyDDgO6/kYzAccpF8t87IvjMV63h/zAfvzpBVos573xXxAm19OAwBGMEKgPbkRQl+G3f+XpCT5nSSfWGuVMGAWRgr3nLt0bRYhJfriYhW0qY8xmA96N/eguTA7vbOej8F8gH4Fi6iPMZgP8KQVWMR63hfzAW3C7ADAKE5MvQMHVJf4kWwH2UuSH0zylFrrb67rHwIjWFcI/L4L11Y6hjD75nGxCtrUxxjMB72be9BcmJ3eWc/HYD5Av4JF1McYzAfoV7CI+uiP+YD9edIKADCSTbxD+6uS/EiSf1tr/eklbhdmYcoQ+GghJfri4iG0qY9xmA96NveguTA7vbOej8F8gH4Fi6iPMZgP0K9gEfUxBvMBnrQCAIxnhED7Zx7z5/8oyZUkb0jyS7XW1x57j2CmhNkZlYuH0KY+gGWYe9B8XWPAUVnPx2A+QL+CRdTHGMwH6FewiPoYg/mAg/Sruv6dAgC4je4D7bXWc1PvA2yCdYR7zl26lsc/+dbXRwsp0RcXD6FNfQDLMHUI3BhsOuv5OMwHm06/gjb1MQbzAfoVLKI+xmA+QL8CAMZ1YuodAKa3rnDPfReurXwMAaLN4mQc2tQHsCxzCIHPZQw2j/UcGIV+BW3qYxzmg02nX0Gb+hiD+QD9CgAYm0A7bLgpwz1nT28JEHFkTsahTX0AqzRaCHwuY7B5rOfAKPQraFMfwCj0K2hTH2MwH6BfAQDjE2iHDTZluCdJzpzaWukYAkTz5WQc2tQHsEqjhcDnMgabx3oOjEK/gjb1AYxCv4I29TEO88Gm068AgDkQaIcNNXWYfVkEiDaPk3FoUx/AKo0WAp/LGGwe6zkwCv0K2tQHMAr9CtrUBzAK/QoAmAuBdthAwuyMysk4tKkPYJVGC4HPZQw2j/UcGIV+BW3qAxiFfgVt6gMYhX4FAMyJQDtsmCnDPWdPby1l+4vGECCaLyfj0KY+gFUaLQR+7tI1YXaGZD0HRqFfQZv6AEahX0Gb+gBGoV8BAHMj0A4bZOo7VZ45tZxA+7r+HfTDyTi0qQ9g1UYLgd934dpKxxBmZxWs58Ao9CtoUx/AKPQraFMfwCj0KwBgju6YcvBSyv8z5fh71Vq/cup9gFWZOsz+7NPvlCtrGGMZro/x7KVsjeNyMg5t6gMYxZQhcGF2emc9B0ahX0Gb+gBGoV9Bm/oARqFfAQBzNWmgPck/SlIn3ofdBNqZpR7C7KOPwTScjEOb+oC2KxfPJ3nm1LvBDmF2aLOeA6PQr6BNfQCj0K+gTX0Ao9CvAIA5OzH1DuwoHXzALM09aC7MPl9OxqFNfUBbqz6YxjqO4c5durbv66Mdi7J5rOfAKPQraFMfwCj0K2hTH8Ao9CsAYO56CbTXiT9gluYeNBdmny8n49CmPqBNmL0v6zqGu+/CrYH20Y5F2TzWc2jbftIKvdCvoE19AKPQr6BNfQCj0K8AgE3QQ6DdndlhBeYeNBdmny8n49CmPqBNmL0vUx7DnT29NdSxKJvHeg5t1vO+6FfQpj6gzS+n9UW/gjb1AYxCvwIANsUdE4//MWsebyvJFyT589m+M7tAO7M096D5usZg/ZyMQ9vVy/erD2gQfuvL1L+QeObUVvK21Y0hzM5xON6FNut5X/QraFMf0HajPp439a4Q/QoWUR/AKPQrAGCTTBpor7X+z3WNVUr5i0n+aZL3zY0we13X+LAuU4fAjcFRORmHxfa7u5X6AOG33kwdZl8Wx4msguNdaLOe90W/gjb1AW3W877oV9CmPqBt+/9FPXPq3WCHfgUAbJoTU+/AqpVSPqGU8jNJ/kOS98uNu7JfD7OXJK9K8tkT7B4s3RxC4HMZg4NzMg6Hpz5g8frB+gmzQ5snrUCb8FtfnJ9Dm/qANut5X/QraFMf0GY974t+BQBsoknv0L5KpZRTSb4mydOvv7TzeXeQ/Q1JvirJN9VaV5uKgImMFgKfyxgcnJNxODz1AdaP3kx5DHf29NZStr9oDMeJHJcnrcD+/M/yvji+gjb1AW3W877oV9CmPqDNet4X/QoA2FSzu0N7KeV9SinfleRnsh1mLzsfdeejJPnDJF+X5P1qrfcJszNXo4XA5zIGB+dkHNquXr5/39fVB1g/ejP1MdyZU8sJtDtOZJ30K/Ckld44voI2T1qBNuG3vljPoU19QJv1vC/6FQCwyWYTaC+lPKaU8g1JXpbkM7L9b9sbZK9JziV5/1rrl9da3zDR7sLKjRYCn8sYHJyTcWi7cvG8O7lCg/WjL3M5hlvXGJDoV5BYz3tjPmAx5+ewP7+c1hfrObSpD2gTZu+LfgUAbLrhA+2llIeXUv5ekl9L8qVJ3im3BtlLkh9OcqrW+pm11ldNtb+wDiOGe+YwBgfnZBzaWvVx5z33qg82nvWjL3M5hptyDObLk1agzXreF/MBh6c+wPrRG/MBbZ60Am3C7H2xngMADBxoL6WcKKV8bpJXJPknSe7M/kH2i0meWmv91FrrL0y1v7Aucwn3jDYGB+dkHNoWXTw8effT17w30BfrR1/mcgwnzM4qeNIKtFnP+2I+4PDUB1g/emM+YDHn57A/T1rpi/UcAGDbkIH2UsqfTfLSJP8qyXvk5iB7dr7+lSSfXmv9yFrriybZUZjASOGec5euzSKkxME5GYc2d8KANutHX+YeNBdm5zg8aQXarOd9MR/Q5kkr0Gb96Iv5gMNTH2D96I35AAC4YahAeynlT5VS/meS70/yAdk/yP6aJF+Y5ANrrf9xkh2Fwa0rBH7fhWsrHUOYvS9OxqFNmB3arB99mXvQXJid4/CkFWiznvfFfECbJ61Am/WjL+YDDk99gPWjN+YDAOBmQwTaSylPLqX8YJKfSPKR2T/IfjXJVyR5Qq31X9VaH5hkZ2FwU4bARwspcXBOxqFt0Z1cYdNZP/oy96C5MDvH4ZfToM163hfzAW2etAJt1o++mA9o86QVaLN+9MV8AADcqutAeynlj5dS/m2Sn0/yqdkOrl8Ps2fnz29P8i+yHWT/J7XWt0yyszADwuysipNx2N+ii1Xu5MqmczG3L3MPmq9rDOZJmB3arOd9MR/Q5kkr0Gb96Iv5gDZPWoE260dfzAcAwP66DLSXUt6llPLVSX4lyWcmeUhuvit72fnW/zfJk2utX1prfd0kOwszsY5wz7lL1/Z9fbSQEsfnZBxcrIJF1Edfpg6BG4OeedIKtFnP+2I+oM0vp0Gb9aMv5gPaPGkF2qwffTEfAABtXQXaSylbpZRnJ/nVJGeTPDy3BtlLkh9L8hG11s+otf7aVPsLc7GucM99F24NtAsQbR4n4+BiFSyiPvozhxD4XMagL560Am3W876YD2gTZoc260dfzAe0edIKtFk/+mI+AAAW6ybQXkr5q0l+OcnXJnlMbg6yZ+frS0k+qdb6jFrrS6bYT5ibKcM9Z09vCRBtGCfj4GIVLKI+xjBaCHwuY9AX/Qra1EdfzAe0edIKtFk/+mI+oM0vp0Gb9aMv5gMA4PbumHoHSimfnOSrktyd7dB6ciPEnp3XfiPJP6y1/of17h3M25ThniQ5c2oredvqxhAg6ouTcXCxChZRH2MYLQQ+lzHoi34FbeqjP+YD9nf7J608sP6dgk5Yz/tiPqBNmB3arB99MR8AAAczaaC9lPKCJB93/cvcGmT//STPSfIttdY/WvPuwaxNHWZfFgGiMTgZBxerYBH1MYbRQuBzGYO+6FfQpj7GYD7gIP2q3vpDsCGs5/0xH7A/T1qBNut5X8wHAMDBTX2H9qdm++rw7jB7SfLmJM9N8jW11jdNs2swX8LsrJuTcTadi1XQpj7GMFoIfC5j0Bf9CtrUxxjMB+hXsIj6GIP5AE9agUWs530xHwAAhzN1oP263WH2muQnkjwuydeXUta2D7XWz1vXYDCVKcM9Z09vLWX7i8YQIAJ642IVtKmPMYwWAj936ZowO0unX0Gb+hiD+QD9ChZRH2MwH+BJK7CI9bw/5gMA4HB6CbSXPX/+5AnGr0kE2pm1qe9UeebUVl644jGW+e949lK2BGwyFw+hTX2MY7QQ+H0Xrq10DGH2zaNfQZv6GIP5AP0KFlEfYzAfoF/BIupjDOYDAGCxE1PvQENZ8wfM3tRh9jmMAXAYLh5Cm/rYPFOGwEc7FqUv+hW0qY8xmA/Qr2AR9TEG8wH6FSyiPsZgPgAAbq+XO7RP/ewvoXZmbe5Bc2F2oDcuHkKb+tg8wuyMSr+CNvUxDvPBptOvoE19jMF8gH4Fi6iPMZgPAICD6eEO7eu+G7s7tLNR5h40F2YHeuPiIbSpj82zjmO4c5eu7fv6aMei9EW/gjb1AYxCv4I29TEO88Gm06+gTX2MwXwAABzc1Hdof9+Jx4dZm3vQXJgd6I2Lh9CmPjbPuo7hnvvya/nmz1jtGMLsm0W/gjb1AYxCv4I29QGMQr+CNvUxBvMBAHA4kwbaa62/OeX4MGdzD5oLswO9cfEQ2tTH5lnnMdxdd938+tnTW/mSJ41zLEpf9CtoUx/AKPQraFMfwCj0K2hTH+MwHwAAh3Ni6h0Alm/uQfN1jQFwUC4eQpv62DxT/0LimVNbKx1DmH2+9CtoUx/AKPQraFMfwCj0K2hTHwAAzJlAO8zM1CFwYwCbxsVDaFMfm2fqMPuyOE7cPPoVtKkPYBT6FbSpD2AU+hW0qQ8AAOZOoB1mZg4h8LmMAcyfi4fQpj42jzA7o9KvoE19AKPQr6BNfQCj0K+gTX0AALAJBNph5kYLgc9lDFiFKxfPT70L7OLiIbSpj80z5THc2dNbS9n+ojEcJ86XfgVt6gMYhX4FbeoDGIV+BW3qAwCATSHQDjM2Wgh8LmPAKrQuVjENFw+hTX1snqmP4c6cWk6g3XHi5tGvoE19AKPQr6BNfQCj0K+gTX0AALBJBNphpkYLgc9lDFgFYfa+uHgIbepj88zlGG5dY9AP/Qra1AcwCv0K2tQHMAr9CtrUBwAAm0agHWZoxHDPHMaAVRBm74uLh9CmPjbPXI7hphyDaehX0KY+oO3KxfNT7wK76FfQpj6AUehX0KY+AADYRALtMDNzCfeMNgasgjB7X1w8hDb1sXnmcgwnzL559CtoUx/Q5vy8L/oVtKkPYBT6FbSpDwAANpVAO8zMSOGec5euzSKkBKvgf5b3xcVDaFMfm2fuQXNh9vnSr6BNfUCb8/O+6FfQpj6gzZNW+qJfQZv6AABgkwm0A7dYVwj8vgvXVjqGMDujWnSxivVz8RDarl6+X31smLkHzYXZ58t6Dm3qA9qE2fuiX0Gb+oA263lf9CtoUx8AAGw6gXbgJlOGwEcLKcEquFjVF/MBi+13dyv1MV9zD5oLs8+X9Rza1Ae0Cb/1Rb+CNvUBbdbzvuhX0KY+oM2TVgBgcwi0A+8gzA7TcrGqL+YDDk99zNfcg+brGoP1s55DmyetQJvwW1+s59CmPqDNet4X/Qra1Ae0Wc8BYLMItANJ1hPuOXfp2r6vjxZSglVwsaov5gMOT33M19QhcGNwVNZzWMyTVmB/i9YP1s96Dm3qA9qE3/qiX0Gb+oA26zkAbB6BdmBt4Z77LtwaaBcgAheremM+oO3q5fv3fV19zNscQuBzGYODs57D4akPsH70xnxAmyetQJvwW1+s59CmPqDNeg4Am0mgHTbclOGes6e3BIjYeC5W9cV8QNuVi+fdyZUk44XA5zIGB2c9h8NTH2D96I35gMWcn8P+PGmlL9ZzaFMf0CbMDgCbS6AdNtiU4Z4kOXNqa6VjCBDROxer+mI+oK1VH3fec6/62DCjhcDnMgYHZz2HNk9agTbrR1/MBxye+gDrR2/MB7R50gq0CbMDwGYTaIcNNXWYfVkEiBiVi7l9MR/Qtuji4cm7n77mvWFKo4XA5zIGB2c9hzZPWoE260dfzAccnvoA60dvzAcs5vwc9udJKwCAQDtsIGF2mJaLuX0xH9DmThhcN1oIfC5jcHDWc2jzpBVos370xXxAmyetQJv1oy/mAw5PfYD1AwDYJtAOG2bKcM/Z01tL2f6iMQSI6J2T8b6YD2gTZue60ULg5y5dE2bfMNZzaPOkFWizfvTFfECbJ61Am/WjL+YDDk99gPUDALhBoB02yNR3qjxzajmB9nX9O2DZnIz3xXxA26I7ubJ5RguB33fh2krHEGbvi/Uc2vxyGrRZP/piPqDNk1agzfrRF/MBbZ60Am3WDwBgN4F22BBTh9nnMAYch5Px/pgP2N+ifuVOrhzVlCHw0Y5FOTjHV9AmzA5t1o++mA9o86QVaLN+9MV8QJsnrUCb9QMA2EugHTbA3IPmwuz0zsn4GMwH6FeshjA7q6BfQZsnrUCb9aMv5gPa/HIatFk/+mI+oM2TVqDN+gEA7EegHWZu7kFzYXZ652R8DOYD9CtWYx3HcOcuXdv39dGORTkc/Qr250kr0OZ4ty/mA9qE2aHN+tEX8wFtnrQCbdYPAKDljikGLaX81SnGvZ1a67+beh9gmeYeNBdmp3dOxsdgPkC/YjXWdQz33Jdfyzd/xmrHEGbvn34FB1nP6/p3CjrheLc/5gP250kr0GY974v5gDa/nAZt1g8AYJFJAu1JvjN9/l80gXZmY+5Bc2F2eudkfAzmA/QrVmOdx3B33XXz62dPb+VLnjTOsSjHp1+B9RwWUR9jMB9wkCetPLD+nYJOWM/7Yj6gTZgd2qwfAMDtTBVov65MPP5uPQbs4UjmHjRf1xhwVE7Gx2A+QL9iNab+hcQzp7aSt61uDGH2vuhXYD2HRdTHGMwHeNIKLGI974/5gP150gq0Wc8BgIOYOtDeyxW4noL1cCxTh8CNwaZzMj4O88Gm069YhanD7MviOHEM+hVYz2ER9TEG8wH6FSyiPsZgPsCTVmAR6zkAcFBTBtqFyGEF5hACn8sYbB4n48Ao9CtWQZidddKvwHoOi6iPMZgP0K9gEfUxBvMBnrQCi1jPAYDDmCrQ/r4TjQsbZ7QQ+FzGYPM4GQdGoV+xClMew509vbWU7S8aw3Fif/QrNp31HNrUxxjMB+hXsIj6GIP5AP0KFlEfAMBhTRJor7X+5hTjwqYZLQQ+lzHYPE7GgVHoV6zC1MdwZ05t5YUrHsNxItAT6zm0qY9xmA82nX4FbepjDOYD9CtYRH0AAEdxYuodAFZjtBD4XMZg8zgZB0ahX7EKczmGW9cYAMdlPYc29QGMQr+CNvUxBvMB+hUsoj4AgKMSaIcZGjHcM4cx2DxOxoFR6FeswlyO4aYcA+AwrOfQpj6AUehX0KY+xmE+2HT6FbSpDwDgOATaYWbmEu4ZbQw2j5NxYBT6Faswl2M4YXZgFNZzaFMfwCj0K2hTH8Ao9CtoUx8AwHEJtMPMjBTuOXfp2ixCSmweJ+PAKPQrVmHuQXNhdqA31nNoUx/AKPQraFMfwCj0K2hTHwDAMgi0A7dYVwj8vgvXVjqGMDur4GQcGIV+xSrMPWguzA70xnoObeoDGIV+BW3qAxiFfgVt6gMAWBaBduAmU4bARwspsXmcjAOj0K9YhbkHzYXZgd5Yz6FNfQCj0K+gTX0Ao9CvoE19AADLJNAOvIMwO7Q5GQdGoV+xCnMPmq9rDICDsp5Dm/oARqFfQZv6AEahX0Gb+gAAlu2OqXfgOEopT0zykUken+RRSd4lyUOPuLlaa/3sJe0aDGcd4Z5zl67l8U++9fXRQkpsHifj0Hbl4vkkz5x6N9ihX7EKU4fAjQFsGus5tKkPYBT6FbSpD2AU+hW0qQ8AYBWGC7SXUt4jyRcl+ewkj1vWZpPUnW3CxllXuOe5L7+Wb/6M1Y4hQMSyORmHthv18bypd4XoV6zOHELgcxkDmD/rObSpD2AU+hW0qQ9gFPoVtKkPAGBVTky9A4dRSvn8JL+a5O8mebdsB9GP+wEbbcpwz9nTWwJEdM3JOLS16oNp6Fes02gh8LmMAauw/aQVemE9hzb1AYxCv4I29QGMQr+CNvUBAKzSMIH2Usq3JPmWJA/LjTuqH+cDNt6U4Z4kOXNqa6VjCBBxHE7GoU2YvS/6Fes0Wgh8LmPAKljP+2I9hzb1AW1+Oa0v+hW0qQ9gFPoVtKkPAGDVhgi0l1K+MMkX5OYg+/W7q78myduvf+vO51cmee3O6627sb85yW/ufO/1z7Axpg6zL4sAEatw9fL9TsahQfitLy4esk6jhcDnMgasgvW8L9ZzaFMf0GY974t+BW3qAxiFfgVt6gMAWIfuA+2llD+W5Gtzc5D9TUm+OMmja63vkeQXd/9MrfV9a63vXmt9pySPT/IXkpxP8mBuhNu3kvzbne9931rr+67r3wRTE2aHxfa7u5WTcfA/y3vj4iHrNFoIfC5jwCpYz/tiPYc29QFt1vO+6FfQpj6gzZNW+qJfQZv6AADWpftAe5IvTfLOO38uSd6Y5GNqrd9aa71yux+utb6q1vp9tdY/n+RJSV6881d3JPnKUsp3rmCfoVtThnvOnt5ayvYXjSFAxCo4GYfFF6tYPxcPWafRQuDnLl0TZocG4be+WM+hTX1Am/W8L/oVtKkPaLOe90W/gjb1AQCs0wiB9r+UG3dmr0n+Qa318lE2VGv91SRPTfK83LhT+7NKKV+5nF2Fvk19p8ozp5YTaF/XvwMSJ+OQuFjVG/PBuo0WAr/vwrWVjiHMzqj8z/K+WM+hTX1Am/W8L/oVtKkPaLOe90W/gjb1AQCsW9eB9lLKuyV5wq6X3pjk3xxnm7XWmuT/TnL/9WGS/J1Syt3H2S70buow+xzGYL6uXr5/39edjIOLVb0xH4xqyhD4aMeisAqetNIX6zm0Xb18v/qABuG3vljPoU19QJv1vC/6FbSpDwBgCl0H2pN8+K4/1yT/vdb6R8fd6E6o/YuTvH1nuw9Jcva424VezT1oLszOcVy5eD5XLp6/5XUn4+BiVW/MB6MSZodpWT/6Yj5gMefnsD+/nNYX6zm0qQ9oE2bvi34FbeoDAJhK74H2x+35+tJBfqiU8rDbfU+t9ZeTvDjbd2gvSf5sKeWhh91B6N3cg+bC7BxH62T8znvudTLOxnOxqi/mg1Gt4xju3KVr+74+2rEorIL1oy/mAw5PfYD1ozfmA9o8aQXahNn7Yj2HNvUBAEyp90D7o3c+l53Pv9P4vr13bT9oouD5u/78zkk+4oA/B0OYe9BcmJ3jWHTx8OTdT1/z3kBfXKzqi/lgVOs6hrvvwq2B9tGORWEVrB99MR9weOoDrB+9MR+wmCetwP48aaUv1nNoUx8AwNR6D7TvTQdcbXzfldwIvSfJux5w+7+95+sPOODPQffmHjQXZuc43AkD2lys6ov5YFRTHsOdPb011LEorIL1oy/mA9quXr5/39fVB1g/emM+4PDUB1g/emM+oM2TVgCAHvQeaH/Tnq8ffsDvu+uA23/bzue68/mxB/w56Nrcg+brGoN5EmaHNhdz+2I+GNXUv5B45tTWSscQZqd31o++mA9ou3LxvDu5QoP1oy/mAw5PfYD1ozfmAxZzfg4A9KD3QPvv7/n6kY3ve9Wer+8+4Pbffefz9bu733HAn4NuTR0CNwY9a12sciIOLub2xnwwqqnD7MviOJFRWT/6Yj6gbdH5ufpg01k/+mI+oM2TVqDN+tEX8wGHpz4AgCn0Hmj/5Z3P1++g/l6N77u85/s+9oDb/1N7vn79AX8OujWHEPhcxqAviy5Wnbz76RPsEfTDxdy+mA9GJcwO07J+9MV8QNuiJ6c5P2fTWT/6Yj6gzZNWoM360RfzAYenPgCAqfQeaH95boTUk+QDG9/3s7v+XJJ8ainl3RZtuJTy+CR/Zs/2X3mUnYSejRYCn8sY9MXFKmhTH30xH4xqymO4s6e3lrL9RWM4TqR31o++mA9oWxRmh01n/eiL+YA2T1qBNutHX8wHtHnSCgDQo64D7bXWN2f77utl5+NDG9/3s0l+Y9dLD03yvFLKQ/b7/lLKySTfm2R38uHBJP/j+HsN/RgtBD6XMeiLi1XQpj76Yz4Y0dTHcGdOLSfQ7jiRUVnP+2I+oE2YHdqsH30xH9DmSSvQZv3oi/mANk9aAQB61XWgfceP7/rze5dSntD4vu/Kdui97nz+5CQ/VUr5s6WUdy2lPKSU8m6llGdl+47uf3LX99Yk/73WemVV/whYt9FC4HMZg764WAVt6mMM5oPezeUYbl1jwLJZz/tiPqBt0Z1cYdNZP/piPqDNL6dBm/WjL+YD2jxpBQDo2R1T78AB/FCSL8126DzZDqr/i32+7+uSfG6Sx+VGUP0pSb5/n+8tO5/rrs//dEn7yz5KKU9McirJXUkekeStSX4nyc/XWl864a7N0ojhnjmMQV9crII29TEG80Hv5nIMt84xnr2UrcE263l/zAfsb1G/2r6T6wPr3ynohPW8L+YD2oTZoc360RfzAW23e9LK1beueYcAAPYYIdD+giSvS/LYna8/J/sE2mutV0opn5/tAPuJ3Ai1l73fmxtB9ut/fk6t9aeWudPLUkp5TJIP3/XxlCSP3/t9tdb9/p2TKqU8PMkXJPn8JH9iwfe9KsnzknxjrfUN69m7+Ro13DP6GPTFxSpoUx9jMB/0bi7HcFOOAcdhPR+D+YCD9Kt66w/BhrCe98d8wP48aQXarOd9MR/Q5pfTAIARdB9or7U+UEr5oiQfeP21Usoja61v2ud7f7CU8leTfHuSd8ri/yNyPQD+1bXWr1jmPh9HKeWDkjwz28H1D0/yvtPu0dGUUj46yX9I8t4H+Pb3SvIVSb6wlPI5tdb/vNKdm7mRwj3nLl2bRUiJvrhYBW3qYwzmg97NPWguzE7vrOdjMB+gX8Ei6mMM5gM8aQUWsZ73xXxAmzA7ADCK7gPtSVJr/b5DfO/3lFL+V5KvSfKp2Q627+d/JPmKWusLl7CLy/Q5Sf761DtxHKWUe5N8b5KHHvJH3zXJD5RSvrjW+q3L3zMOal0h8PsuXFvpGMLsm8fFKmhTH2MwH/Ru7kFzYXZ6Zz0fg/kA/QoWUR9jMB/gSSuwiPW8P+YD9udJKwDASIYItB9WrfXXknx6KeWdk3xskruSPDbJm5P8bpIX11pfPeEuzlYp5XT2D7M/mOS/ZvsXCX4r2+H1D0nyGUneefcmkvyLUsrv1lr/0+r3mL2mDIGPFlKiLy4eQpv6GIf5oGdzD5oLs9M76/kYzAfoV7CI+hiD+QD9ChZRH2MwH+BJKwDAeGYZaL+u1vqWJP9t6v1YkmtJfiHJzyT5v5I8atK92Ucp5RFJvie3htl/KcmfrbW+bJ+f+fIk35HkT+9+Ocl3lFJ+0i8erJcwO6Ny8RDa1AewDHMPmq9rDDgq6/kYzAfoV7CI+hiD+QD9ChZRH2MwH+BJKwDAmE5MvQPs6+1Jfj7Jtyf5wiT3JHlkrfUptdbPS/LGKXdugb+X5PF7XvuVJKf3C7MnSa31D5Lcm+Q/7vmrd0nyNUvfQ5rWEe45d+navq+PFlKiLy4eQpv6AJZh6hC4Mdh01vNxmA82nX4FbepjDOYD9CtYRH2MwXyAfgUAjEugvT9fk+TOWuuH1Fo/u9b6L2utP11r3T8J3IlSyqOSfPGelx9M8lk7ofWmWusDST4vye/t+au/XEp5v6XtJE3rCvfcd+HWt7EAEcfhZBza1AewLHMIgc9lDDaP9RwYhX4FbepjHOaDTadfQZv6GIP5AP0KABhb94H2UsrH7vr4sCVv+8N2b3+Z2z6qWuvv1lrfOvV+HMFfTnLnntd+qNb6Pw7yw7XW309y356XH5Lkc5ewbywwZbjn7OktASKOzMk4tKkPYJVGC4HPZQw2j/UcGIV+BW3qAxiFfgVt6mMM5gP0KwBgfHdMvQMH8ONJ6s6ffy7JMkPtz0vywTt/rhnjv0ev/uI+r/2rQ27jO5M8J8nuxMdnJPm7R9wnbmPKcE+SnDm1lbxtdWMIEM2Xk3FoUx/AKo0WAp/LGGwe6zkwCv0K2tQHMAr9CtrUxzjMB5tOvwIA5qD7O7TvKDsfq9z2qrY/e6WUd0nyUXtevprkvx9mOzt3af/xPS+/dynlyUffO1qmDrMviwDR5nEyDm3qA1il0ULgcxmDzWM9B0ahX0Gb+gBGoV9Bm/oARqFfAQBzMUqgvebGXdpXsW2O56OSPGTPaz9Za33gCNt68T6vfcwRtsMCwuyMysk4tKkPYJVGC4HPZQw2j/UcGIV+BW3qAxiFfgVt6gMYhX4FAMzJKIH2xB3Ue/aUfV77ySNu68IBt88RTRnuOXt6aynbXzSGANF8ORmHNvUBrNJoIfBzl64JszMk6zkwCv0K2tQHMAr9CtrUBzAK/QoAmJuRAu2rsDsk/+BkezG+J+3z2iuOuK1f3ee1Dzjitthj6jtVnjm1nED7uv4d9MPJOLSpD2DVRguB33fh2krHEGZnFaznwCj0K2hTH8Ao9CtoUx/AKPQrAGCONj3Q/ohdf37LZHsxvvfZ57XfPOK2fjvJA3tee78jbotdpg6zz2EMpuFkHNrUBzCKKUPgox2Lsnms58Ao9CtoUx/AKPQraFMfwCj0KwBgrjY20F5KuSPJXbteujLVvszAu+/z2m8dZUO11geS/O6el9/tKNvihrkHzYXZ58vJOLSpD2i7cvH81LvALsLs0GY9B0ahX0Gb+gBGoV9Bm/oARqFfAQBzdsfUOzChT0mylaTufPzatLsztMfs89rVY2xv789ulVJO1lqPs80kSSnlcUne9ZA/9oTdX1y9ejVXrnT8+w8Pe8+bvjx36Vqe+/Jrueuum7/t7OmtnDm1tZTf5DjoGG/eetxNf7/362WMcRx7x+h6ngfz7g+vh/6Zq5fvz4OveH5O7pn0O++5Nyfvfnq2W/dyPPZhdeHXPfG+XJ6jvC/XadH7cp31cRDel8sz8vuyF9frw/tyifYcXx7GOo7hvvvXHp33ePKNr9/93d996WMs7d/hfbk0c+iXvazn+uXyzOF92Qvvy+VZxvtylf1qpPdl4r25TD33zMO8L3tYz70vl2cu78seeF8uz7Lel6voV96Xm2tu/XLK9dz7cnnm9r6ckvfl8iz7fbnMfuV9uTxXrx47ygQA7Ci19n1QUkp5MNtHXSXJpVrrhx1ze++S7TD712f7zt9lZ/vfWmv9kmPu7lqUUn4jyXvvfq3WWqbZm6SU8rYke29J+MijBtBLKS9J8qF7Xn63WutrjrK9Pdv+R0m+4jjb+KZv+qY8/vGPP+6uAAAAAAAAAAAAg3rlK1+ZL/3SL9390gfVWl861f4AwMgmv0N7KeUwd0b/wEN+/24PSXIyyaOuD52bfz3xvx5xuyQP3ee1tx1je2/d57WtY2wPAAAAAAAAAAAAAOjQ5IH2JO+TG3dgb7n+d1s7378MddfnVyT50SVtl23HufX/fj872R3oAQAAAAAAAAAAAIDV6CHQfl0rAF0O8D1HVZK8OclfrbUue9ub5I+SvNOe1x6e5OoRt/fwfV67dsRt7fWtSb7vkD/zhCQ/eP2Le+65J09+8pOXtDvL94nf8KKpd6HpsQ+r+dwnPfiOr7/t5SfyurdN97sKVy/fnysXz9/y+p333JuTdz89P/o3PnaCvZqng7wvbzcfq9Tbe3MR78vl6blfJre+L5/znOfk1a9+9U3fs476OAjvy+UZ7X3ZQ79srR+/8Au/MMHezNNh3pdTrOc9vi9b9MvlGbFf/sZP/9hkx7uLeF8uz4jvy1765d71wzq+PEd5X65zPe/5fbkfPXN5eu6Zi96XU16/avG+XJ5R35e92F0f1vLlOer7ch39aoT35W765fKM3i97Ws+9L5dn9PdlL65evj8Xvv0rp96N2Tju+3KV/Wqk92XSd7982cteNvUuAMBs9BJoP+hR0TKPnh5M8iNJztZaHV0cz1uy+kD7m4+4rZvUWl+T5DWH+ZlSbn7bnTx5MnfeeecydmclXv3Wfk8y9nrd28pk+3vl4vm8/oXffsvrj37aZ+XEE5+Rq29N1/M8mtvN80HmY52mfG/ejvfl8vQ6xy2vfvWr81u/9Vvv+Hqq+tiP9+XyjPa+nLpfLlo/vC+X56Bz3Mt6PvX7chHvy+XpdY5bfuOnfywv/Y/PveX1HtZz78vlGe192Uu/3G/98L5cnsPO8dTreS/vyxbvzeXpeZ73uv6+nLo+Wrwvl2fE92Uv9taH9+XyHGWep+pXvb0v9/K+XJ6e53mvve/L3tZz78vlGfl92Yvr9XHn93/j1LsyG8eZ53X3q17fl9f13C9Pnjw59S4AwGz0EGg/d5u/P5PtO7OXJH+Q5L8ccZy3J3lTktcnuZzkp2qtr178IxzQ7yd59J7XTiZ57RG3t/do71qt9ajheLjFwvDbPfdOsEebzXzA4akPsH70xnzAYvvdSUl9QHv9YBrWc2hTH9BmPe+LfgVt6gParOd90a8AgE01eaC91vqZi/6+lHJm15evvN33M4nfS/LEPa+9V5JfP+yGSikPSfIe+2wflsLJX1/MB7RdvXx/cuppt7yuPsD60RvzAYenPmDx+sH6Wc+h7erl+9UHNAi/9cV6Dm3qA9qs533RrwCATXZi6h04hDr1DtC0X3D9vY+4rT+eW3/R4tDBeNiPk7++mA9ou3LxvDu5QoP1oy/mAw5PfYD1ozfmAxZzfg7788tpfbGeQ5v6gDZh9r7oVwDAphsh0P7KXR+/M/G+sL9f2ue1vXdsP6gn7PPay4+4LXgHJ399MR/Q1qqPO++5V32w8awffTEf0Hb18v37vq4+wPrRG/MBh6c+wPrRG/MBbZ60Am3C7H2xngMA3Hon7O7UWt9n6n3gtn52n9c+6ojbOr3Pay854rYgiZO/3pgPaFt08fDk3U/P1beueYegI9aPvpgPaLty8XwefMXzk2c97abX1QdYP3pjPuDw1AdYP3pjPmAxT1qB/XnSSl+s5wAA20a4Qzv9u5DkgT2vfVQp5SFH2Naf2ue1Fx1hO5DEyV9vzAe0uRMGtFk/+mI+oM2TVqDN+tEX8wFtnrQCbdaPvpgPODz1AdaP3pgPAIAbBNo5tlrrG5P81J6XH5nkGYfZTinlMUmetuflV9ZaX3aM3WODOfnri/mANmF2aLN+9MV8QNvtnrQCm8z60RfzAW1XLp53J1dosH70xXzA4akPsH70xnwAANxMoJ1l+d59Xvv8Q27jTJKH7Xnte462O2w6J399MR/QtuhOrrDprB99MR/Q5pfToM360RfzAW2etAJt1o++mA9o86QVaLN+9MV8AADcauhAeynlXUspn15K+cZSyotKKb9YSnl1KeXNO59/cef1b9j5vsdOvc8z9l1J3rTntU8rpZw+yA+XUh6d5Oyelx9I8m1L2Dc2jJO//pgP2N+ifuVOrmw663lfzAe0CbNDm/WjL+YD2jxpBdqsH30xH9DmSSvQZv3oi/kAANjfkIH2UsqHlVK+K8lvZfvO4F+S5KOTPCnJ45I8fOfzk3Ze/9Kd73tVKeVcKeVDJ9nxzpVSfryUUvd8/LWD/Gyt9Q1JvmXPyyeSfMdOWH3RuCeS/Osk77Hnr76n1vqrB9t72ObkbwzmA/QrWER99MV8QJsnrUCb9aMv5gPa/HIatFk/+mI+oM2TVqDN+tEX8wEA0DZUoL2U8tBSytcnuZjkM5JsJSm7Puo+H7v/fivJX0ny06WU+0opD137P2LenpPkVXtee/8kF0opT9rvB3bC7ueTfPqev7qS5G8vfQ+ZNSd/YzAfoF/BIuqjP+YD9udJK9BmPe+L+YA2YXZos370xXxAmyetQJv1oy/mAwBgsTum3oGDKqU8Ksnzk3xYtsPpyXZg/ZZv3fXnus/3XA+3/80kH1dKeUat9Y3L3dvjKaX8cJI/vuBbbvm7Usql22z2U2qtv3Oc/bqdWuvVUspfSvKC3PzeelKSl5ZS/kuSFyf57SSPTfIh2f7FhEfss7nPXvX+Mi9O/sZgPkC/gkXUxxjMBxykX+13uQI2g/W8L+YD2jxpBdqsH30xH9Dml9OgzfrRF/MBAHB7QwTaSylbSX4wyVN2Xtr9f4avB9gfTPJbSV6f5M3ZDkk/Ksnjc+NO9LsD7mVnez9YSvnEWuu1Ve3/EXxgkvc+5M98yG3+fuuI+3IotdYX74Tavzs3v79OJPkzOx8LN5Hky2qt37+iXWSGnPyNwXyAfgWLqI8xmA/Qr2AR9dEf8wH7u/2TVh5Y/05BJ6znfTEf0CbMDm3Wj76YDwCAgzlx+2/pwtcm+ZjcGkh/Q5JvTfLUJO9Sa33fWuuH1Vo/Zufz+yW5M8nHJfmWbIfdd9/dvexs92vW9O/YCLXW70vy8UleecgffV2Se2ut37T8vWKunPyNwXyAfgWLqI8xmA/Qr2AR9TEG8wH6FSyiPvpjPmB/nrQCbdbzvpgPAICD6z7QXkp5vyRfkJuD7CXJv0ryfrXWL661vqjW+ub9fr7W+pZa64trrV+S5P2yHYB/x1/vbOsLSinvu7J/xAaqtb44yZOTnE3yitt8+28n+SdJ3r/W+gMr3jVmxMnfOMwHm06/gjb1MQbzAfoVLKI+xmA+QL+CRdTHGMwHHORJK7C5rOd9MR8AAIdzx9Q7cAB/O8lDcyN8/kCSL6y1ftthN1RrvZLki0spL0nyb3Ljbu0PTfLl2Q7OT67W+j4TjfvUJW/vLUm+LsnXlVL+RJIPTXJXkndO8rYkv5Pk52utl5c5LpvByR8wCv0K2tTHGMwH6FewiPoYg/kA/QoWUR9jMB9wkH5Vb/0h2BDW8/6YDwCAwxkh0P7M3Aiz1yRff5Qw+2611m/fCVj/7V3b/rR0Emifo1rrryT5lan3g3lwMg6MQr+CNvUxDvPBptOvoE19jMF8gH4Fi6iPMZgP0K9gEfUxBvMBALDYial3YJFSygcl+eO7Xvr9JF+xpM3/oySv2/X1e+yMB3TMyTgwCv0K2tQHMAr9CtrUxxjMB+hXsIj6GIP5AP0KFlEfYzAfAAC313WgPcn77/pzTfKfaq1/uIwN72znP2X77uz7jQd0xsk4MAr9CtrUBzAK/Qra1Mc4zAebTr+CNvUxBvMB+hUsoj7GYD4AAA6m90D7u+58vh46/7klb//Snq8ft+TtA0viZBwYhX4FbeoDGIV+BW3qAxiFfgVt6mMc5oNNp19Bm/oYg/kAADi43gPtj9nz9WuWvP3X7XyuO58fteTtA0vgZBwYhX4FbeoDGIV+BW3qAxiFfgVt6gMYhX4FbepjDOYDAOBweg+0v3HP13sD7sf1qJ3P1+8Af2XJ2weOyck4MAr9CtrUBzAK/Qra1AcwCv0K2tQHMAr9CtrUxzjMBwDA4fQeaH/tzufrd1B/8pK3v3d7r933u4BJOBkHRqFfQZv6AEahX0Gb+gBGoV9Bm/oARqFfQZv6AABgznoPtP/6rj+XJPeWUkrrmw9jZzv35kZYPkl+YxnbBo7PyTgwCv0K2tQHMAr9CtrUBzAK/Qra1AcwCv0K2tQHAABz13ug/SVJ/mDX1++V5EuWtO0vTPL4XV+/PsnPLGnbwDE4GQdGoV9Bm/oARqFfQZv6AEahX0Gb+gBGoV9Bm/oAAGATdB1or7U+mOT52b47e935/M9KKU89znZLKR+b5Kt3bbMm+dFaa134g8DKORmHtisXz0+9C+yiX0Gb+gBGoV9Bm/oARqFfQZv6AEahX0Gb+gAAYFNMGmgvpbxg18e/aXzb12U7cJ6dz++c5IdKKV94xDE/P8kPJ3nErpfrzjjAhJyMQ1urPpiGfgVt6gMYhX4FbeoDGIV+BW3qAxiFfgVt6gMAgE0y9R3an5rk43Y+Pny/b6i1/myS78v2ndST7fD5w5N8cynlUinl80spj1s0SCnlXUspX1BK+d9JviXbofjdd2f/vlrrS5bw7wGOyMk4tAmz90W/gjb1AW2etNIX/Qra1AcwCv0K2tQHMAr9CtrUBwAAm+aOqXdgR7nN339Rkg9L8oSdr6+H0T842wH1bymlvCrJy5K8Icmbs30H9kcleXKS99ozzu47vv9Kki8+7j8AODon49AmzN4X/Qra1Ae03aiP5029K0S/gkXUB7Rt/3LaM6feDXboV9CmPoBR6FfQpj4AANhEvQTaF6q1/n4p5ZOS/I8k757tIPr1UPv1kPpduRFc321vWL7uev13k3xSrfX3l77TwIE4GYc2Yfa+6FfQpj6gzXreF/0K2tQHtPnltL7oV9CmPoBR6FfQpj4AANhUJ6begYOqtf5akg9J8t9y853Wd3+UfT5a3/PDSU7VWn9jbf8I4CZXL9/vZBwahN/64uIhtKkPaLOe90W/gjb1AW3W877oV9CmPqBt+0kr9EK/gjb1AQDAJhsm0J4ktdbX1lo/JclfSfKS3BxcT24Nr+++G/v1j59J8pdqrZ9aa33t/5+9+46zNK/qxP/59vQMaRiSIIoEJRgWFBXGgKyiYPi5GMaAgjmtrllXV8UAiBF1zVlx17ioo5iRUVkDyAiyMgIGEAQMIBiGJkzq7++P596p2zX33K7qrq76PnXf79eLV0/fqnvrac5zzqnvc899vod4+MAu6y4gWozD5otVHD4XD6Hmw2lQM/w2Fv0cavIDavr5WNQrqMkPqOnnY1GvoCY/AADYdieP+gDORe/955L8XGvtvZI8KsnDkrxHkjsnuWjlW29K8vpMw+/PTvKM3vufHfLhAntkMQ4uVo1GPGAzH06D9bxZPhb9HGryA2r6+VjUK6jJD6jp52NRr6AmP6A2vRf14Ud9GADAIZjlQPtS7/25SZ67+lhr7bIkt0/yht77tUdyYMC+WYyDi1WjEQ/YP/kBdloZjX4ONTutQM3w21j0c6jJD6jp52NRr6AmP6C2kx8/cdSHAgAcghNHfQAHrfd+be/9Hwyzw3hOXXPV2sctxsHFqtGIB+yf/AD9YzTiAZvZaQXW8+G0sejnUJMfUDPMPhb1CmryA2r6OQBsn2M30A6M6dqrr/RmORRcrBqLeEDNh9Ogpn+MRTxg/+QH6B+jEQ+o2WkFaobfxqKfQ01+QE0/B4DtZKAduOCqxcZll19hMc7Wc7FqLOIBNR9Og5r+MRbxgP2TH6B/jEY8YDPrc1jPTitj0c+hJj+gZpgdALaXgXbggtq02Lj0QY885KOBsbhYNRbxgJoPp0FN/xiLeEDNTitQ0z/GIh6wf/ID9I/RiAfU7LQCNcPsALDdDLQDF4zFBtRczB2LeEDNh9Ogpn+MRTygZqcVqOkfYxEP2D/5AfrHaMQDNrM+h/XstAIAnDzqA1hxv9ba7x/hz++99w86wp8Px4phdqi5mDsW8YCafg41/WMs4gG1ZX5ces97nvH4ZZdfkRP3e9QRHRWMQf8Yi3hA7dQ1VyUPfsQtHpcfoH+MRjxg/+QH6B8AwGSkgfbbJXn/I/rZLUk/op8Nx0612LDQAIvx0YgH1AyzQ03/GIt4QO1sO62cevMhHxAMRP8Yi3hA7dqrr8zplz4z+eQzB9rlB+gfoxEP2D/5AfoHALDjxFEfwIp2RP8DDtCmxcalD3rkERwRjMNifCziATUfToOa/jEW8YCaD6dBTf8Yi3hAbdP6XH6w7fSPsYgH1E5dc9Xax+UH6B8AwJlGGmjvR/Q/4IBYbEBNfoxHPGA9H06Dmn4+FvGAmmF2qOkfYxEPqJ1tpxXYZvrHWMQDatdefWWuvfrKWzwuP0D/AABu6eRRH8AKd0uHGbPYgJr8mAfxgL3UK58HZXvp52MRD6jZaQVq+sdYxANqPpwGNf1jLOIBtWV+XHrPe57x+GWXX5ET93vUER0VjEH/AADWGWmg/aVJPvuoDwLYP4sNqMmPeRAPUK9gE/kxHvGA9c6+08pNh39QMAj9fCziATXD7FDTP8YiHlA7204rp958yAcEA9E/AIDKSAPtp3rv//eoDwLYH4sNqMmPeRAPUK9gE/kxD+IBdlqBTfTz8YgHrGenFajp52MRD6j5cBrU9A8AYJMTR30AwHxZbEBNfsyDeIB6BZvIj3kQD1CvYBP5MQ/iAXvZaQW2l34+FvGAmmF2qOkfAMDZGGgHzonFBtTkxzyIB6hXsIn8mAfxAPUKNpEf8yAeoF7BJvJjPOIB69lpBWr6OQCwFwbagX2z2ICa/JgP8WDbqVdQkx/zIB6gXsEm8mMexAPUK9hEfsyDeICdVmAT/RwA2CsD7cC+WGxATX4Ac6FeQU1+zIN4gHoFm8iPeRAPUK9gE/kxD+IB6hVsIj8AgP0w0A7smcUG1OQHMBfqFdTkx3yIB9tOvYKa/JgH8QD1CjaRH/MgHqBewSbyAwDYLwPtwJ5YbEBNfgBzoV5BTX4Ac6FeQU1+zId4sO3UK6jJj3kQD1CvYBP5AQCcCwPtwFlZbEBNfgBzoV5BTX4Ac6FeQU1+AHOhXkFNfsyDeIB6BZvIDwDgXBloBzay2ICa/ADmQr2CmvwA5kK9gpr8AOZCvYKa/JgP8WDbqVdQkx8AwPkw0A6ULDagJj+AuVCvoCY/gLlQr6AmP4C5UK+gJj+AuVCvoCY/AIDzNcpAez/qAwDOZLEBNfkBzIV6BTX5AcyFegU1+QHMhXoFNfkBzIV6BTX5AQAchJNHfQBJ2lEfAHAmiw2oyQ9gLtQrqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPAOCgHPVA+9uv/Pf1R3YUwM0sNqAmP4C5UK+gJj+AuVCvoCY/gLlQr6AmP4C5UK+gJj8AgIN0pAPtvfe/P8qfD5zJYgNq8gOYC/UKavIDmAv1CmryA5gL9Qpq8gOYC/UKavIDADhoJ476AIAxWGxATX5A7dqrrzzqQ2CFegU1+QHMhXoFNfkBzIV6BTX5AcyFegU1+QEAXAgG2gGLDdhAfkCtyg+OhnoFNfkBzIV6BTX5AcyFegU1+QHMhXoFNfkBAFwoBtphy1lsQE1+QM0w+1jUK6jJD6jZaWUs6hXU5AcwF+oV1OQHMBfqFdTkBwBwIRlohy1msQE1+QE1w+xjUa+gJj+gpp+PRb2CmvyAmg+njUW9gpr8AOZCvYKa/AAALjQD7bClLDagduqaq+QHFAy/jUU/h5r8gJp+Phb1CmryA2r6+VjUK6jJD2Au1CuoyQ8A4DAYaIctZLEBm627u5X8AG+Wj0Y/h5r8gJp+Phb1CmryA2r6+VjUK6jJD6jZaWUs6hXU5AcAcFgMtMOWsdiA/ZMfsLl/cPj0c6jZaQVqht/Gop9DTX5ATT8fi3oFNfkBNf18LOoV1OQHAHCYDLTDFrHYgP2TH6B/jEY8YDM7rcB63iwfi34ONfkBNf18LOoV1OQH1PTzsahXUJMfAMBhM9AOW8JiA2qnrrlq7ePyA/SP0YgH7J/8ADutjEY/h5qdVqBm+G0s+jnU5AfU9POxqFdQkx8AwFEw0A5bwGIDatdefaU7uUJB/xiLeMD+yQ/QP0YjHrCZ9Tms58NpY9HPoSY/oGaYfSzqFdTkBwBwVAy0wzFnsQG1Kj8uu/wK+cHW0z/GIh5Qs9MK1PSPsYgH7J/8AP1jNOIBNTutQM0w+1j0c6jJDwDgKBloh2PMYgNqmy4eXvqgRx7y0cBY9I+xiAfU7LQCNf1jLOIB+yc/QP8YjXjAZtbnsJ6dVsain0NNfgAAR81AOxxTFhtQcycMqOkfYxEPqNlpBWr6x1jEA2p2WoGa/jEW8YD9kx+gf4xGPKBmpxUAYAQG2uEYshiHmmF2qOkfYxEPqNlpBWr6x1jEA2p2WoGa/jEW8YD9kx+gf4xGPGAz63MAYAQG2uGYsRiH2qY7ucK20z/GIh5Q8+E0qOkfYxEPqNlpBWr6x1jEA2p2WoGa/jEW8YD9kx8AwFEw0A7HjMU4rLfpYpU7ubLtXMwdi3hAzTA71PSPsYgH1Oy0AjX9YyziATU7rUBN/xiLeMD+yQ8A4KgYaIdjzmIDXKyCTeTHWMQDanZagZr+MRbxgJoPp0FN/xiLeEDNTitQ0z/GIh5Qs9MKADAiA+1wjFlsgItVsIn8GI94wHp2WoGafj4W8YCaYXao6R9jEQ+o2WkFavrHWMQDanZaAQBGZaAdjimLDXCxCjaRH/MgHqBewSbyYyziATU7rUBN/xiLeEDNh9Ogpn+MRTygZqcVAGBkBtrhGLIYBxerYBP5MQ/iAeoVbCI/xiMesJ6dVqCmn49FPKBmmB1q+sdYxANqdloBAEZnoB2OGYtxcLEKNpEf8yAeoF7BJvJjHsQD1CvYRH6MRzxgPTutQE0/H4t4QM2H0wCAOTDQDseMxTjbzsUqqMmPeRAPUK9gE/kxD+IB6hVsIj/mQTzATiuwiX4+FvGAmmF2AGAuDLQDcGy4WAU1+TEP4gHqFWwiP+ZBPEC9gk3kxzyIB6hXsIn8GI94wHp2WgEA5sRAOwDHgouHUJMf8yEebDv1CmryYx7EA9Qr2ER+zIN4gHoFm8iPeRAPsNMKADA/BtoBmD0XD6EmP4C5UK+gJj/mQTxAvYJN5Mc8iAeoV7CJ/JgH8QD1CgCYJwPtAMyaxTjU5AcwF+oV1OTHfIgH2069gpr8mAfxAPUKNpEf8yAeoF4BAPNloB2A2bIYh5r8AOZCvYKa/ADmQr2CmvyYD/Fg26lXUJMf8yAeoF4BAPNmoB2AWbIYh5r8AOZCvYKa/ADmQr2CmvwA5kK9gpr8mAfxAPUKAJg/A+0AzI7FONTkBzAX6hXU5AcwF+oV1OQHMBfqFdTkx3yIB9tOvQIAjgMD7QDMisU41OQHMBfqFdTkBzAX6hXU5AcwF+oV1OQHMBfqFQBwXBhoB2A2LMahJj+AuVCvoCY/gLlQr6AmP4C5UK+gJj+AuVCvAIDjxEA7ALNgMQ41+QHMhXoFNfkBzIV6BTX5AcyFegU1+QHMhXoFABw3BtoB1rj26iuP+hBYYTEONfkBzIV6BTX5AcyFegU1+QHMhXoFNfkBzIV6BQAcRwbaAXapFn8cDYtxqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPYC7UKwDguDLQDrDCMPtYLMahJj+gZqeVsahXUJMfwFyoV1CTH8BcqFdQkx/AXKhXAMBxZqAdYMEw+1gsxqEmP6Cmn49FvYKa/ADmQr2CmvwA5kK9gpr8AOZCvQIAjjsD7QAx/DYai3GoyQ+o6edjUa+gJj+gZqeVsahXUJMfwFyoV1CTH8BcqFcAwDYw0A5sPcNvY7EYh5r8gJp+Phb1CmryA2r6+VjUK6jJD6j5cNpY1CuoyQ9gLtQrAGBbGGgHttqmxR+Hz2IcaqeuuUp+QMHw21j0c6jJD6jp52NRr6AmP6Cmn49FvYKa/ADmQr0CALaJgXZga1n8jUU8YLN1d7eSH+DN8tHo51CTH1DTz8eiXkFNfkBNPx+LegU1+QE1O62MRb0CALaNgXZgK1n8jUU8YP/kB9hpZTT6OdTstAI1w29j0c+hJj+gpp+PRb2CmvyAmn4+FvUKANhGBtqBrWPxNxbxgP2TH6B/jEY8YDM7rcB63iwfi34ONfkBNf18LOoV1OQH1PTzsahXAMC2MtAObBWLv7GIB9ROXXPV2sflB+gfoxEP2D/5AXZaGY1+DjU7rUDN8NtY9HOoyQ+o6edjUa8AgG1moB3YGhZ/YxEPqF179ZXu5AoF/WMs4gH7Jz9A/xiNeMBm1uewng+njUU/h5r8gJph9rGoVwDAtjPQDmwFi7+xiAfUqvy47PIr5AdbT/8Yi3hAzU4rUNM/xiIesH/yA/SP0YgH1Oy0AjXD7GPRzwEADLQDW8DibyziAbVNFw8vfdAjD/loYCz6x1jEA2p2WoGa/jEW8YD9kx+gf4xGPGAz63NYz04rY9HPAQAmBtqBY83ibyziATV3woCa/jEW8YCanVagpn+MRTygZqcVqOkfYxEP2D/5AfrHaMQDAGCHgXbg2LL4G4t4QM0wO9T0j7GIB9TstAI1/WMs4gE1O61ATf8Yi3jA/skP0D9GIx4AAGcy0A4cSxZ/YxEPqG26kytsO/1jLOIBNR9Og5r+MRbxgJqdVqCmf4xFPKBmpxWo6R9jEQ8AgFsy0A4cOxZ/4xEPWG9TvXInV7adfj4W8YCaYXao6R9jEQ+o2WkFavrHWMQDanZagZr+MRbxAABYz0A7cKxY/M2DeIB6BZvIj7GIB9TstAI1/WMs4gE1H06Dmv4xFvGAmp1WoKZ/jEU8AABqBtqBY8Pibx7EA9Qr2ER+jEc8YD07rUBNPx+LeEDNMDvU9I+xiAfU7LQCNf1jLOIBALCZgXbgWLD4mwfxAPUKNpEf8yAeoF7BJvJjLOIBNTutQE3/GIt4QM2H06Cmf4xFPAAAzs5AOzB7Fn/zIB6gXsEm8mMexAPUK9hEfoxHPGA9O61ATT8fi3hAzTA71PSPsYgHAMDeGGgHZs3ibx7EA9Qr2ER+zIN4gHoFm8iPeRAPUK9gE/kxHvGA9ey0AjX9fCziAQCwdwbagdmy+JsP8WDbqVdQkx/zIB6gXsEm8mMexAPUK9hEfsyDeICdVmAT/Xws4gEAsD8G2oFZsvgD5kK9gpr8mAfxAPUKNpEf8yAeoF7BJvJjHsQD1CvYRH6MRzwAAPbHQDswOxbjwFyoV1CTH/MhHmw79Qpq8mMexAPUK9hEfsyDeIB6BZvIj3kQDwCAzQy0A7NiMQ7MhXoFNfkBzIV6BTX5MQ/iAeoVbCI/5kE8QL2CTeTHPIgHAMDZGWgHZsNiHJgL9Qpq8gOYC/UKavJjPsSDbadeQU1+zIN4gHoFm8iPeRAPAIC9MdAOzILFODAX6hXU5AcwF+oV1OQHMBfqFdTkx3yIB9tOvYKa/JgH8QAA2DsD7cDwLMaBuVCvoCY/gLlQr6AmP4C5UK+gJj+AuVCvoCY/5kE8AAD2x0A7MDSLcWAu1CuoyQ9gLtQrqMkPYC7UK6jJD2Au1CuoyY/5EA8AgP0x0A4My2IcmAv1CmryA5gL9Qpq8gOYC/UKavIDmAv1CmryAwCA48xAOzAki3FgLtQrqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPAACOOwPtwHAsxoG5UK+gJj+AuVCvoCY/gLlQr6AmP4C5UK+gJj8AANgGBtqBoViMQ+3aq6886kNghXoFNfkBzIV6BTX5AcyFegU1+QHMhXoFNfkBAMC2MNAODMNiHGpVfnA01CuoyQ9gLtQrqMkPYC7UK6jJD2Au1CuoyQ8AALaJgXZgCBbjUDPMPhb1CmryA2p2WhmLegU1+QHMhXoFNfkBzIV6BTX5AQDAtjHQDhw5i3GoGWYfi3oFNfkBNf18LOoV1OQH1Hw4bSzqFdTkBzAX6hXU5AcAANvIQDtwpCzGoWb4bSzqFdTkB9T087GoV1CTH1DTz8eiXkFNfgBzoV5BTX4AALCtDLQDR+bUNVdZjEPBm+VjcfEQavIDavr5WNQrqMkPqOnnY1GvoCY/oGanlbGoV1CTHwAAbDMD7cCRWXcB0WIcNl+s4vC5eAg1H06DmuG3sejnUJMfUNPPx6JeQU1+QE0/H4t6BTX5AQDAtjPQDgzDYhxcrBqNeMBmPpwG63mzfCz6OdTkB9T087GoV1CTH1DTz8eiXkFNfkDNTisAsD0MtANDsBgHF6tGIx6wf/ID7LQyGv0canZagZrht7Ho51CTH1DTz8eiXkFNfkBNPweA7WKgHTg0p665au3jFuPgYtVoxAP2T36A/jEa8YDN7LQC6/lw2lj0c6jJD6gZfhuLegU1+QE1/RwAto+BduBQXHv1ld4sh4KLVWMRD6j5cBrU9I+xiAfsn/wA/WM04gE1O61AzfDbWPRzqMkPqOnnALCdDLQDF1y12Ljs8issxtl6LlaNRTyg5sNpUNM/xiIesH/yA/SP0YgHbGZ9DuvZaWUs+jnU5AfUDLMDwPYy0A5cUJsWG5c+6JGHfDQwFherxiIeUPPhNKjpH2MRD6jZaQVq+sdYxAP2T36A/jEa8YCanVagZpgdALabgXbggrHYgJqLuWMRD6j5cBrU9I+xiAfU7LQCNf1jLOIB+yc/QP8YjXjAZtbnsJ6dVgAAA+3ABWGYHWou5o5FPKCmn0NN/xiLeEDNTitQ0z/GIh5Qs9MK1PSPsYgH7J/8AP0DAJgYaAcO3KY3y2HbWYyPRTygZpgdavrHWMQDanZagZr+MRbxgJqdVqCmf4xFPGD/5AfoHwDADgPtwIHatNjwZjnbzmJ8LOIBNR9Og5r+MRbxgJoPp0FN/xiLeEDNTitQ0z/GIh5Qs9MK1PQPAGCVgXbgwFhsQE1+jEc8YD0fToOafj4W8YCaYXao6R9jEQ+o2WkFavrHWMQDanZagZr+AQDsZqAdOBAWG1CTH/MgHqBewSbyYyziATU7rUBN/xiLeEDNh9Ogpn+MRTygZqcVqOkfAMA6BtqB82axATX5MQ/iAeoVbCI/xiMesJ6dVqCmn49FPKBmmB1q+sdYxANqdlqBmv4BAFQMtAPnxWIDavJjHsQD1CvYRH7Mg3iAegWbyI/xiAesZ6cVqOnnYxEPqPlwGtT0DwBgEwPtwDmz2ICa/JgH8QD1CjaRH/MgHqBewSbyYx7EA+y0Apvo52MRD6gZZoea/gEAnI2BduCcWGxATX7Mg3iAegWbyI95EA9Qr2AT+TEP4gHqFWwiP8YjHrCenVagpp8DAHthoB3YN4sNqMmP+RAPtp16BTX5MQ/iAeoVbCI/5kE8QL2CTeTHPIgH2GkFNtHPAYC9MtAO7IvFBtTkBzAX6hXU5Mc8iAeoV7CJ/JgH8QD1CjaRH/MgHqBewSbyAwDYDwPtwJ5ZbEBNfgBzoV5BTX7Mh3iw7dQrqMmPeRAPUK9gE/kxD+IB6hVsIj8AgP0y0A7sicUG1OQHMBfqFdTkBzAX6hXU5Md8iAfbTr2CmvyYB/EA9Qo2kR8AwLkw0A6clcUG1OQHMBfqFdTkBzAX6hXU5AcwF+oV1OTHPIgHqFewifwAAM6VgXZgI4sNqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMmP+RAPtp16BTX5AQCcDwPtQMliA2ryA5gL9Qpq8gOYC/UKavIDmAv1CmryA5gL9Qpq8gMAOF8G2oG1LDagJj+AuVCvoCY/gLlQr6AmP4C5UK+gJj+AuVCvoCY/AICDYKAduAWLDajJD2Au1CuoyQ9gLtQrqMkPYC7UK6jJD2Au1CuoyQ8A4KAYaAfOYLEBNfkBzIV6BTX5AcyFegU1+QHMhXoFNfkBzIV6BTX5AQAcpJNHfQDsXWvtrkkemuS+SS5LckOS1yd5cZLn9d5vOMLD4xiw2ICa/ADmQr2CmvwA5kK9gpr8AOZCvYKa/ADmQr2CmvwAAA6agfYZaK19bJIvTvKwJK34tje01p6W5Nt7739zaAe3orX2iiT3PqCX++re+7ce0GuxBxYbUJMfULv26iuTfPhRHwYL6hXU5AcwF+oV1OQHMBfqFdTkBzAX6hXU5AcAcCGcOOoDoNZau0dr7VlJfjHJ+6UeZk+S2yf5zCTXtNa+rrW26XvhDBYbUJMfUKvyg6OhXkFNfgBzoV5BTX4Ac6FeQU1+AHOhXkFNfgAAF4qB9kG11h6Q5M+SvP8+n3pJkicl+dnW2kUHfmAcOxYbUJMfUDPMPhb1CmryA2rTTiuMQr2CmvwA5kK9gpr8AOZCvYKa/AAALqSTR30A3FJr7S5JnpnkbdZ8+flJnp7k5Uluk+QBSR6b5G13fd8nJnltki+5YAd6dv+W5JXn+NzXHOSBsJ7FBtTkB9QMs49FvYKa/IDaTn78xFEfClGvYBP5AbXpw2kfftSHwYJ6BTX5AcyFegU1+QEAXGgG2sf0o0nuteuxNyT55N7703d/c2vta5J8TZIn7PrSF7fWntF7/+0LcpRn92u99087op/NWVhsQO3UNVfJDygYZh+Lfg41+QE1/Xws6hXU5AfUfDhtLOoV1OQHMBfqFdTkBwBwGE4c9QFwptbao5Ls/m3v+iQfuG6YPUl67zf03p+Y9Xdj/77Wmg8ucAaLDdhsurvVmeQHGH4bjX4ONfkBNf18LOoV1OQH1PTzsahXUJMfUFv3XhRHR72CmvwAAA6LgfbxfN2ax57Ye3/e2Z7Ye/+eJM/c9fB9kzz2IA6M48FiA/ZPfsDm/sHh08+hZqcVqBl+G4t+DjX5ATX9fCzqFdTkB9T087GoV1CTHwDAYTLQPpDW2rskefiuh1+X5Dv38TJfveaxzzvng+JYsdiA/ZMfoH+MRjxgMzutwHreLB+Lfg41+QE1/Xws6hXU5AfU9POxqFdQkx8AwGEz0D6WT1zz2FN779ft9QV6789P8vxdD793a+3tz+vImD2LDaiduuaqtY/LD9A/RiMesH/yA+y0Mhr9HGp2WoGa4bex6OdQkx9Q08/Hol5BTX4AAEfBQPtYPnTNY790Dq+z7jnrXpstYbEBtWuvvtKdXKGgf4xFPGD/5AfoH6MRD9jM+hzW8+G0sejnUJMfUDPMPhb1CmryAwA4KgbaB9Fau12S99j18JuSvOAcXu6P1jz28HN4HY4Biw2oVflx2eVXyA+2nv4xFvGAmp1WoKZ/jEU8YP/kB+gfoxEPqNlpBWqG2cein0NNfgAAR8lA+zgenFvG43m99xvO4bX+LMnu573nuRwU82axAbVNFw8vfdAjD/loYCz6x1jEA2p2WoGa/jEW8YD9kx+gf4xGPGAz63NYz04rY9HPoSY/AICjZqB9HO+05rGXnssL9d6vT/LqXQ/ft7V28lxe7zzct7X2ra21P2ytvbK19ubW2hsX//2C1tpPtdY+o7V2z0M+rq1gsQE1d8KAmv4xFvGAmp1WoKZ/jEU8oGanFajpH2MRD9g/+QH6x2jEA2p2WgEARmCgfRz3WfPY35/H671y198vSnKv83i9c/F+Sf5HkocnuWeSWye57eK/H5zkU5P8RJKXt9Z+vrX24EM+vmPLYhxqhtmhpn+MRTygZqcVqOkfYxEPqNlpBWr6x1jEA/ZPfoD+MRrxgM2szwGAERhoH8fd1zz2qvN4vXXPfevzeL0L6aIkn5Dkea21x7fW2lEf0JxZjENt051cYdvpH2MRD6j5cBrU9I+xiAfU7LQCNf1jLOIBNTutQE3/GIt4wP7JDwDgKJw86gPgZnde89ip83i9dc+9y3m83rk6neS1Sa5d/PddFv9b92GKi5I8OclDWmsf23u/6aAPprV2tyR33efT7rv6l1OnTuXaa689uIM6YJe+9Jm59J73POOxyy6/YnGnyn40B7XwVrfuG/8+mpHjPDd3v83Rx/rUNVfldJEf93noB2UqUZORz03n5cEZ4bzc5DBr5qb82Ev/cF4enLvfpp93PC6kOfVy5+XBGalersuPu9/9zM8GOy+3w0jn5TpHUS/PtX84Lw/O6nk5Yj/Xx7fTiPVyNT929/H7PPSD8rq3jHfMS87NgzPiubl0lPXyXPqH8/Lg7D4vR+rnc+rjifPyII1aL09dc1Vu+8pnJ3nEzY/d/e53H+L6VcV5eXBGPS+TMerlfvqH8/LgVOflCP18hPNyP5yXB2dO9XJ1fT5iPx/5vDx16nxGuwCAVa33cX4B2Wattd9J8iG7Hn507/03zvH1vivJl+56+DG996edy+vt8We+IsnbJfm/SX47ybOSvLj3/qZd33fHJA9L8mlJrsj64fYf6r3/twtwjE9I8g3n8xrf+73fm3vd614Hc0AAAAAAAAAAAMDsvPKVr8wXfdEXrT70wN77i47qeABgztyhfRwXr3nsLefxem9e89gl5/F6e/GUJL/We3/Vpm/qvf97kt9M8puttXdN8n+SvNOub/u81trv9d5/+YIcKQAAAAAAAAAAAABw5NbdGZtxnM/t89c9t53H6539B/b+A2cbZl/znBcmuTzJX6z58je11i46kIMDAAAAAAAAAAAAAIbjDu3juGHNY7c5j9db99zrz+P1Lpje+xtaa49O8pIkt1v50jsmeXSSXz3AH/eDSX5xn8+5b5KnL/9y+eWX553f+Z0P8JAO1gMf+MBcdvkVufRBjzzqQ7mFt7p1z2e/0+mb//5jf3Uir3vLBf2cxXn53S/9z0d9CMfGB//PPzz0n3nqmqty7dVX3uLxdfkxp3PTeXlwjuK83I8LeV7uJz/2wnl5cB74wAfe/N8j9nP1cjsdZb3cS71yXm6nbe7jSwfVz52XB2e1jy+N1M/Vy+00Qr3cVK/u89APms15mTg3D9II52blMOvlQfRz5+XBed/P+PoDvV5ykObUxxPn5UEapV6uq1d3v/vd8/jHP/7mvzsvt8co5+U6R1Evz6efOy8PzvK8POj3Pw6CPr69RquXq/mhjx+cl7zkJUd9CABwbBhoH8eb1jx20APtbzyP17ugeu+vaq19d5LH7/rSh+UAB9p7769N8tr9PKe1M39pv/TSS3PZZZcd1CEduFP3e1RO3O9ROfXmoz6Ss3vdW1r++c3jLopGjvPcHHacr736yvzbH/zkLR6/0yM+Y0/5MfK56bw8OKPGuHJQ5+X55sc6zsuD86pXTZvdnE88DpN6uR2OKsbnWq+cl9th1BhXDvq8PMh+7rw8OMs+vjR6P1cvt8NRx/hs9ep1bzlzk8mRz8vEuXmQRo7zbhfqvDyofu68PDgv+uXvucVjo/Zz9XJ7jBDnql5ddvkVZ/zdebk9Ro7zbhf6vDzffu68PDj//OZ2Qd7/uBDUy+0xUpyr/FhyXp67Sy+99KgPAQCOjRNHfQDc7PVrHjuf33rWPXfdzxjJz6157IMO/ShmbvcFRNg2my5WyQ+2nfyYB/EA9Qo2kR/zIB6gXsEm8mMexAM216uj3rkAjpp+PhbxgNrZhtkBAEZhoH0cr1nz2Nudx+vdc48/Yxi99xcn+ZddD6/7dwCs5WIV1OTHPIgHqFewifyYB/EA9Qo2kR/zIB6gXsEm8mM84gHr7XWnFQCAERhoH8fL1zx27/N4vXvt+vtNSV55Hq93WP5p198vaa3d4UiOBJgVFw+hJj/mQzzYduoV1OTHPIgHqFewifyYB/EA9Qo2kR/zIB5gpxUAYH4MtI/jr9c8dr9zeaHW2iW55Z3NX9Z7v/FcXu+QvXHNY7c59KMAZsXFQ6jJD2Au1CuoyY95EA9Qr2AT+TEP4gHqFWwiP+ZBPEC9AgDmyUD7OF6Q5PSuxx7SWjt5Dq/1kCQX73rsz8/pqA7fXdc89vpDPwpgNizGoSY/gLlQr6AmP+ZDPNh26hXU5Mc8iAeoV7CJ/JgH8QD1CgCYLwPtg+i9vzHTUPuq2yV593N4ufdb89gfnsPrHKrW2u2S3GvXw//ee7/hKI4HGJ/FONTkBzAX6hXU5AcwF+oV1OTHfIgH2069gpr8mAfxAPUKAJg3A+1j+Z01j33MObzOx+7xtUfzQUku2fXYXxzFgQDjsxiHmvwA5kK9gpr8AOZCvYKa/ADmQr2CmvyYB/EA9QoAmD8D7WP5+TWPfXprbfeQd6m19u5JHrrr4ef23l9+Xkd2OP7Hmsd++9CPAhiexTjU5AcwF+oV1OQHMBfqFdTkBzAX6hXU5Md8iAfbTr0CAI4DA+0D6b2/KMkf73r4bkm+dB8v881rHvuhcz6oQ9Ja+/wk77vr4dNJfuUIDgcYmMU41OQHMBfqFdTkBzAX6hXU5AcwF+oV1OQHMBfqFQBwXBhoH8+T1zz2xNbae5ztia21L0jyobsefnmSn9vLD26tPau11nf979P28LwPbq3t/rl71lr79CTfs+ZL/6v3/jfn+rrA8WMxDjX5AcyFegU1+QHMhXoFNfkBzIV6BTX5AcyFegUAHCcG2gfTe39GkqfvevhWSf6gtfbodc9prV3cWvu6JN+75stf1Hu/4YAPc7d3SfLbrbU/b619UWvtHnt5UmvtXVpr/yfJTya5aNeXX5/k6w74OIEZsxiHmvwA5kK9gpr8AOZCvYKa/ADmQr2CmvwA5kK9AgCOm5NHfQCs9VlJ3jPJ2608dlmSX2utPS/TwPvLk9wmyf2TPC7JuiHy7++9/8YFPtZV777433e31l6S5C+SvCjJ65L8R5Ke5M5J7pfk4UkekqSteZ03Jfnw3vs/HMZBwzrXXn1lkg8/6sNgwWIcavIDmAv1CmryA5gL9Qpq8gOYC/UKavIDmAv1CgA4jgy0D6j3/rrW2gcn+f0kd9/15Ycs/nc2T0vyJQd8aHvVMt21/V3O4bmvTvK43vtzD/aQYO92Fn8/cdSHQizGYRP5AcyFegU1+QHMhXoFNfkBzIV6BTX5AcyFegUAHFcnjvoAWK/3/pIkD03yR/t86g1JnpDkE3vvNx30cV1ANyb530netff+h0d9MGyvavHH0bAYh5r8gNq00wqjUK+gJj+AuVCvoCY/gLlQr6AmP4C5UK8AgOPMQPvAeu+vTvL+SR6T5NlJ+oZvP5XkqUke1Ht/Yu/99CEc4tJPJPmIJN+V5DlJ3rjH551Ock2SJye5T+/9U3vv/3ZhDhHOzjD7WCzGoSY/oKafj0W9gpr8AOZCvYKa/ADmQr2CmvwA5kK9AgCOu5NHfQBs1nvvSZ6W5GmttbsluTzJOyS5LNNdzV+X5CVJ/qz3fv15/qwPOMfnvSHJry/+l9baiSRvn+TeSe6Z5E5Jbrv49v9I8m9J/jHJ83rvp87nmOGgGH4bi8U41OQH1PTzsahXUJMfUJt2Wvnwoz4MFtQrqMkPYC7UK6jJD2Au1CsAYBsYaJ+R3vtrk/zGUR/H2SzuDv+yxf9geIbfxmIxDjX5ATX9fCzqFdTkB9R28uMnjvpQiHoFm8gPqPlw2ljUK6jJD2Au1CsAYFucOOoDADhKmxZ/HD6LcaiduuYq+QEFw+xj0c+hJj+gpp+PRb2CmvyAmn4+FvUKavIDmAv1CgDYJgbaga1l8TcW8YDNprtbnUl+gDfLR6OfQ01+QE0/H4t6BTX5ATX9fCzqFdTkB9TWvRfF0VGvAIBtY6Ad2EoWf2MRD9g/+QF2WhmNfg41O61AzfDbWPRzqMkPqOnnY1GvoCY/oKafj0W9AgC2kYF2YOtY/I1FPGD/5AfoH6MRD9jMTiuwnjfLx6KfQ01+QE0/H4t6BTX5ATX9fCzqFQCwrQy0A1vF4m8s4gG1U9dctfZx+QH6x2jEA/ZPfoCdVkajn0PNTitQM/w2Fv0cavIDavr5WNQrAGCbGWgHtobF31jEA2rXXn2lO7lCQf8Yi3jA/skP0D9GIx6wmfU5rOfDaWPRz6EmP6BmmH0s6hUAsO0MtANbweJvLOIBtSo/Lrv8CvnB1tM/xiIeULPTCtT0j7GIB+yf/AD9YzTiATU7rUDNMPtY9HMAAAPtwBaw+BuLeEBt08XDSx/0yEM+GhiL/jEW8YCanVagpn+MRTxg/+QH6B+jEQ/YzPoc1rPTylj0cwCAiYF24Fiz+BuLeEDNnTCgpn+MRTygZqcVqOkfYxEPqNlpBWr6x1jEA/ZPfoD+MRrxAADYYaAdOLYs/sYiHlAzzA41/WMs4gE1O61ATf8Yi3hAzU4rUNM/xiIesH/yA/SP0YgHAMCZDLQDx5LF31jEA2qb7uQK207/GIt4QM2H06Cmf4xFPKBmpxWo6R9jEQ+o2WkFavrHWMQDAOCWDLQDx47F33jEA9bbVK/cyZVtp5+PRTygZpgdavrHWMQDanZagZr+MRbxgJqdVqCmf4xFPAAA1jPQDhwrFn/zIB6gXsEm8mMs4gE1O61ATf8Yi3hAzYfToKZ/jEU8oGanFajpH2MRDwCAmoF24Niw+JsH8QD1CjaRH+MRD1jPTitQ08/HIh5QM8wONf1jLOIBNTutQE3/GIt4AABsZqAdOBYs/uZBPEC9gk3kxzyIB6hXsIn8GIt4QM1OK1DTP8YiHlDz4TSo6R9jEQ8AgLMz0A7MnsXfPIgHqFewifyYB/EA9Qo2kR/jEQ9Yz04rUNPPxyIeUDPMDjX9YyziAQCwNwbagVmz+JsH8QD1CjaRH/MgHqBewSbyYx7EA9Qr2ER+jEc8YD07rUBNPx+LeAAA7J2BdmC2LP7mQzzYduoV1OTHPIgHqFewifyYB/EA9Qo2kR/zIB5gpxXYRD8fi3gAAOyPgXZgliz+gLlQr6AmP+ZBPEC9gk3kxzyIB6hXsIn8mAfxAPUKNpEf4xEPAID9MdAOzI7FODAX6hXU5Md8iAfbTr2CmvyYB/EA9Qo2kR/zIB6gXsEm8mMexAMAYDMD7cCsWIwDc6FeQU1+AHOhXkFNfsyDeIB6BZvIj3kQD1CvYBP5MQ/iAQBwdgbagdmwGAfmQr2CmvwA5kK9gpr8mA/xYNupV1CTH/MgHqBewSbyYx7EAwBgbwy0A7NgMQ7MhXoFNfkBzIV6BTX5AcyFegU1+TEf4sG2U6+gJj/mQTwAAPbOQDswPItxYC7UK6jJD2Au1CuoyQ9gLtQrqMkPYC7UK6jJj3kQDwCA/THQDgzNYhyYC/UKavIDmAv1CmryA5gL9Qpq8gOYC/UKavJjPsQDAGB/DLQDw7IYB+ZCvYKa/ADmQr2CmvwA5kK9gpr8AOZCvYKa/AAA4Dgz0A4MyWIcmAv1CmryA5gL9Qpq8gOYC/UKavIDmAv1CmryAwCA485AOzAci3FgLtQrqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPAAC2gYF2YCgW41C79uorj/oQWKFeQU1+AHOhXkFNfgBzoV5BTX4Ac6FeQU1+AACwLQy0A8OwGIdalR8cDfUKavIDmAv1CmryA5gL9Qpq8gOYC/UKavIDAIBtYqAdGILFONQMs49FvYKa/ICanVbGol5BTX4Ac6FeQU1+AHOhXkFNfgAAsG0MtANHzmIcaobZx6JeQU1+QE0/H4t6BTX5ATUfThuLegU1+QHMhXoFNfkBAMA2MtAOHCmLcagZfhuLegU1+QE1/Xws6hXU5AfU9POxqFdQkx/AXKhXUJMfAABsKwPtwJE5dc1VFuNQ8Gb5WFw8hJr8gJp+Phb1CmryA2r6+VjUK6jJD6jZaWUs6hXU5AcAANvMQDtwZNZdQLQYh80Xqzh8Lh5CzYfToGb4bSz6OdTkB9T087GoV1CTH1DTz8eiXkFNfgAAsO0MtAPDsBgHF6tGIx6wmQ+nwXreLB+Lfg41+QE1/Xws6hXU5AfU9POxqFdQkx9Qs9MKAGwPA+3AECzGwcWq0YgH7J/8ADutjEY/h5qdVqBm+G0s+jnU5AfU9POxqFdQkx9Q088BYLsYaAcOzalrrlr7uMU4uFg1GvGA/ZMfoH+MRjxgMzutwHo+nDYW/Rxq8gNqht/Gol5BTX5ATT8HgO1joB04FNdefaU3y6HgYtVYxANqPpwGNf1jLOIB+yc/QP8YjXhAzU4rUDP8Nhb9HGryA2r6OQBsJwPtwAVXLTYuu/wKi3G2notVYxEPqPlwGtT0j7GIB+yf/AD9YzTiAZtZn8N6dloZi34ONfkBNcPsALC9DLQDF9SmxcalD3rkIR8NjMXFqrGIB9R8OA1q+sdYxANqdlqBmv4xFvGA/ZMfoH+MRjygZqcVqBlmB4DtZqAduGAsNqDmYu5YxANqPpwGNf1jLOIBNTutQE3/GIt4wP7JD9A/RiMesJn1OaxnpxUAwEA7cEEYZoeai7ljEQ+o6edQ0z/GIh5Qs9MK1PSPsYgH1Oy0AjX9YyziAfsnP0D/AAAmBtqBA7fpzXLYdhbjYxEPqBlmh5r+MRbxgJqdVqCmf4xFPKBmpxWo6R9jEQ/YP/kB+gcAsMNAO3CgNi02vFnOtrMYH4t4QM2H06Cmf4xFPKDmw2lQ0z/GIh5Qs9MK1PSPsYgH1Oy0AjX9AwBYZaAdODAWG1CTH+MRD1jPh9Ogpp+PRTygZpgdavrHWMQDanZagZr+MRbxgJqdVqCmfwAAuxloBw6ExQbU5Mc8iAeoV7CJ/BiLeEDNTitQ0z/GIh5Q8+E0qOkfYxEPqNlpBWr6BwCwjoF24LxZbEBNfsyDeIB6BZvIj/GIB6xnpxWo6edjEQ+oGWaHmv4xFvGAmp1WoKZ/AAAVA+3AebHYgJr8mAfxAPUKNpEf8yAeoF7BJvJjPOIB69lpBWr6+VjEA2o+nAY1/QMA2MRAO3DOLDagJj/mQTxAvYJN5Mc8iAeoV7CJ/JgH8QA7rcAm+vlYxANqhtmhpn8AAGdjoB04JxYbUJMf8yAeoF7BJvJjHsQD1CvYRH7Mg3iAegWbyI/xiAesZ6cVqOnnAMBeGGgH9s1iA2ryYz7Eg22nXkFNfsyDeIB6BZvIj3kQD1CvYBP5MQ/iAXZagU30cwBgrwy0A/tisQE1+QHMhXoFNfkxD+IB6hVsIj/mQTxAvYJN5Mc8iAeoV7CJ/AAA9sNAO7BnFhtQkx/AXKhXUJMf8yEebDv1CmryYx7EA9Qr2ER+zIN4gHoFm8gPAGC/DLQDe2KxATX5AcyFegU1+QHMhXoFNfkxH+LBtlOvoCY/5kE8QL2CTeQHAHAuDLQDZ2WxATX5AcyFegU1+QHMhXoFNfkBzIV6BTX5MQ/iAeoVbCI/AIBzZaAd2MhiA2ryA5gL9Qpq8gOYC/UKavIDmAv1CmryYz7Eg22nXkFNfgAA58NAO1Cy2ICa/ADmQr2CmvwA5kK9gpr8AOZCvYKa/ADmQr2CmvwAAM6XgXZgLYsNqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPYC7UK6jJDwDgIBhoB27BYgNq8gOYC/UKavIDmAv1CmryA5gL9Qpq8gOYC/UKavIDADgoBtqBM1hsQE1+AHOhXkFNfgBzoV5BTX4Ac6FeQU1+AHOhXkFNfgAAB8lAO3Aziw2oyQ9gLtQrqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPAOCgGWgHklhswCbyA2rXXn3lUR8CK9QrqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPAOBCMNAOWGzABvIDalV+cDTUK6jJD2Au1CuoyQ9gLtQrqMkPYC7UK6jJDwDgQjHQDlvOYgNq8gNqhtnHol5BTX5AzU4rY1GvoCY/gLlQr6AmP4C5UK+gJj8AgAvJQDtsMYsNqMkPqBlmH4t6BTX5ATX9fCzqFdTkB9R8OG0s6hXU5AcwF+oV1OQHAHChGWiHLWWxAbVT11wlP6Bg+G0s+jnU5AfU9POxqFdQkx9Q08/Hol5BTX4Ac6FeQU1+AACHwUA7bCGLDdhs3d2t5Ad4s3w0+jnU5AfU9POxqFdQkx9Q08/Hol5BTX5AzU4rY1GvoCY/AIDDYqAdtozFBuyf/IDN/YPDp59DzU4rUDP8Nhb9HGryA2r6+VjUK6jJD6jp52NRr6AmPwCAw2SgHbaIxQbsn/wA/WM04gGb2WkF1vNm+Vj0c6jJD6jp52NRr6AmP6Cmn49FvYKa/AAADpuBdtgSFhtQO3XNVWsflx+gf4xGPGD/5AfYaWU0+jnU7LQCNcNvY9HPoSY/oKafj0W9gpr8AACOgoF22AIWG1C79uor3ckVCvrHWMQD9k9+gP4xGvGAzazPYT0fThuLfg41+QE1w+xjUa+gJj8AgKNioB2OOYsNqFX5cdnlV8gPtp7+MRbxgJqdVqCmf4xFPGD/5AfoH6MRD6jZaQVqhtnHop9DTX4AAEfJQDscYxYbUNt08fDSBz3ykI8GxqJ/jEU8oGanFajpH2MRD9g/+QH6x2jEAzazPof17LQyFv0cavIDADhqBtrhmLLYgJo7YUBN/xiLeEDNTitQ0z/GIh5Qs9MK1PSPsYgH7J/8AP1jNOIBNTutAAAjMNAOx5DFONQMs0NN/xiLeEDNTitQ0z/GIh5Qs9MK1PSPsYgH7J/8AP1jNOIBm1mfAwAjMNAOx4zFONQ23ckVtp3+MRbxgJoPp0FN/xiLeEDNTitQ0z/GIh5Qs9MK1PSPsYgH7J/8AACOgoF2OGYsxmG9TRer3MmVbedi7ljEA2qG2aGmf4xFPKBmpxWo6R9jEQ+o2WkFavrHWMQD9k9+AABHxUA7HHMWG+BiFWwiP8YiHlCz0wrU9I+xiAfUfDgNavrHWMQDanZagZr+MRbxgJqdVgCAERloh2PMYgNcrIJN5Md4xAPWs9MK1PTzsYgH1AyzQ03/GIt4QM1OK1DTP8YiHlCz0woAMCoD7XBMWWyAi1WwifyYB/EA9Qo2kR9jEQ+o2WkFavrHWMQDaj6cBjX9YyziATU7rQAAIzPQDseQxTi4WAWbyI95EA9Qr2AT+TEe8YD17LQCNf18LOIBNcPsUNM/xiIeULPTCgAwOgPtcMxYjIOLVbCJ/JgH8QD1CjaRH/MgHqBewSbyYzziAevZaQVq+vlYxANqPpwGAMyBgXY4ZizG2XYuVkFNfsyDeIB6BZvIj3kQD1CvYBP5MQ/iAXZagU3087GIB9QMswMAc2GgHYBjw8UqqMmPeRAPUK9gE/kxD+IB6hVsIj/mQTxAvYJN5Md4xAPWs9MKADAnBtoBOBZcPISa/JgP8WDbqVdQkx/zIB6gXsEm8mMexAPUK9hEfsyDeICdVgCA+THQDsDsuXgINfkBzIV6BTX5MQ/iAeoVbCI/5kE8QL2CTeTHPIgHqFcAwDwZaAdg1izGoSY/gLlQr6AmP+ZDPNh26hXU5Mc8iAeoV7CJ/JgH8QD1CgCYLwPtAMyWxTjU5AcwF+oV1OQHMBfqFdTkx3yIB9tOvYKa/JgH8QD1CgCYNwPtAMySxTjU5AcwF+oV1OQHMBfqFdTkBzAX6hXU5Mc8iAeoVwDA/BloB2B2LMahJj+AuVCvoCY/gLlQr6AmP4C5UK+gJj/mQzzYduoVAHAcGGgHYFYsxqEmP4C5UK+gJj+AuVCvoCY/gLlQr6AmP4C5UK8AgOPCQDsAs2ExDjX5AcyFegU1+QHMhXoFNfkBzIV6BTX5AcyFegUAHCcG2gGYBYtxqMkPYC7UK6jJD2Au1CuoyQ9gLtQrqMkPYC7UKwDguDHQDrDGtVdfedSHwAqLcajJD2Au1CuoyQ9gLtQrqMkPYC7UK6jJD2Au1CsA4Dgy0A6wS7X442hYjENNfgBzoV5BTX4Ac6FeQU1+AHOhXkFNfgBzoV4BAMeVgXaAFYbZx2IxDjX5ATU7rYxFvYKa/ADmQr2CmvwA5kK9gpr8AOZCvQIAjjMD7QALhtnHYjEONfkBNf18LOoV1OQHMBfqFdTkBzAX6hXU5AcwF+oVAHDcGWgHiOG30ViMQ01+QE0/H4t6BTX5ATU7rYxFvYKa/ADmQr2CmvwA5kK9AgC2gYF2YOsZfhuLxTjU5AfU9POxqFdQkx9Q08/Hol5BTX5AzYfTxqJeQU1+AHOhXgEA28JAO7DVNi3+OHwW41A7dc1V8gMKht/Gop9DTX5ATT8fi3oFNfkBNf18LOoV1OQHMBfqFQCwTQy0A1vL4m8s4gGbrbu7lfwAb5aPRj+HmvyAmn4+FvUKavIDavr5WNQrqMkPqNlpZSzqFQCwbQy0A1vJ4m8s4gH7Jz/ATiuj0c+hZqcVqBl+G4t+DjX5ATX9fCzqFdTkB9T087GoVwDANjLQDmwdi7+xiAfsn/wA/WM04gGb2WkF1vNm+Vj0c6jJD6jp52NRr6AmP6Cmn49FvQIAtpWBdmCrWPyNRTygduqaq9Y+Lj9A/xiNeMD+yQ+w08po9HOo2WkFaobfxqKfQ01+QE0/H4t6BQBsMwPtwNaw+BuLeEDt2quvdCdXKOgfYxEP2D/5AfrHaMQDNrM+h/V8OG0s+jnU5AfUDLOPRb0CALadgXZgK1j8jUU8oFblx2WXXyE/2Hr6x1jEA2p2WoGa/jEW8YD9kx+gf4xGPKBmpxWoGWYfi34OAGCgHdgCFn9jEQ+obbp4eOmDHnnIRwNj0T/GIh5Qs9MK1PSPsYgH7J/8AP1jNOIBm1mfw3p2WhmLfg4AMDHQDhxrFn9jEQ+ouRMG1PSPsYgH1Oy0AjX9YyziATU7rUBN/xiLeMD+yQ/QP0YjHgAAOwy0A8eWxd9YxANqhtmhpn+MRTygZqcVqOkfYxEPqNlpBWr6x1jEA/ZPfoD+MRrxAAA4k4F24Fiy+BuLeEBt051cYdvpH2MRD6j5cBrU9I+xiAfU7LQCNf1jLOIBNTutQE3/GIt4AADckoF24Nix+BuPeMB6m+qVO7my7fTzsYgH1AyzQ03/GIt4QM1OK1DTP8YiHlCz0wrU9I+xiAcAwHoG2oFjxeJvHsQD1CvYRH6MRTygZqcVqOkfYxEPqPlwGtT0j7GIB9TstAI1/WMs4gEAUDPQDhwbFn/zIB6gXsEm8mM84gHr2WkFavr5WMQDaobZoaZ/jEU8oGanFajpH2MRDwCAzQy0A8eCxd88iAeoV7CJ/JgH8QD1CjaRH2MRD6jZaQVq+sdYxANqPpwGNf1jLOIBAHB2BtqB2bP4mwfxAPUKNpEf8yAeoF7BJvJjPOIB69lpBWr6+VjEA2qG2aGmf4xFPAAA9sZAOzBrFn/zIB6gXsEm8mMexAPUK9hEfsyDeIB6BZvIj/GIB6xnpxWo6edjEQ8AgL0z0A7MlsXffIgH2069gpr8mAfxAPUKNpEf8yAeoF7BJvJjHsQD7LQCm+jnYxEPAID9MdAOzJLFHzAX6hXU5Mc8iAeoV7CJ/JgH8QD1CjaRH/MgHqBewSbyYzziAQCwPwbagdmxGAfmQr2CmvyYD/Fg26lXUJMf8yAeoF7BJvJjHsQD1CvYRH7Mg3gAAGxmoB2YFYtxYC7UK6jJD2Au1CuoyY95EA9Qr2AT+TEP4gHqFWwiP+ZBPAAAzs5AOzAbFuPAXKhXUJMfwFyoV1CTH/MhHmw79Qpq8mMexAPUK9hEfsyDeAAA7I2BdmAWLMaBuVCvoCY/gLlQr6AmP4C5UK+gJj/mQzzYduoV1OTHPIgHAMDeGWgHhmcxDsyFegU1+QHMhXoFNfkBzIV6BTX5AcyFegU1+TEP4gEAsD8G2oGhWYwDc6FeQU1+AHOhXkFNfgBzoV5BTX4Ac6FeQU1+zId4AADsj4F2YFgW48BcqFdQkx/AXKhXUJMfwFyoV1CTH8BcqFdQkx8AABxnBtqBIVmMA3OhXkFNfgBzoV5BTX4Ac6FeQU1+AHOhXkFNfgAAcNwZaAeGYzEOzIV6BTX5AcyFegU1+QHMhXoFNfkBzIV6BTX5AQDANjDQDgzFYhxq11595VEfAivUK6jJD2Au1CuoyQ9gLtQrqMkPYC7UK6jJDwAAtoWBdmAYFuNQq/KDo6FeQU1+AHOhXkFNfgBzoV5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\n",
      "text/plain": [
       "<Figure size 3000x1500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3000x1500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for r in [None, .2, .3, .4]:\n",
    "    draw_pdf_vs_KL_stack(df=df11_100, col='R2_100', B=100, ratio=r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TS    23\n",
       "dtype: int64"
      ]
     },
     "execution_count": 1174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_sum=pd.DataFrame(df[df.Diff<0].groupby(by=['Dataset']).count()['TS']).sum()\n",
    "_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TS    126\n",
       "dtype: int64"
      ]
     },
     "execution_count": 1183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_sum=pd.DataFrame(df.groupby(by=['Model_Selector']).count()['TS']).sum()\n",
    "_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pylab as plt\n",
    "fig = matplotlib.pyplot.gcf()\n",
    "fig.set_dpi(150)\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (15, 5),\n",
    "         'axes.labelsize': 'x-large',\n",
    "         'axes.titlesize':'x-large',\n",
    "         'xtick.labelsize':12,\n",
    "         'ytick.labelsize':12}\n",
    "plt.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1309,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_model_stat(df,c='KL_Model',B=100):\n",
    "    df_model=df.groupby(by=['Dataset',\n",
    "                       c]).count()['TS'].unstack(c)\n",
    "    col_rev={'<catboost.core.CatBo':'Catboost',\n",
    "            'BaggingRegressor()':'BaggingRegressor',\n",
    "            'DecisionTreeRegresso':'DecisionTreeRegressor',\n",
    "            'ExtraTreesRegressor':'ExtraTreesRegressor',\n",
    "            'GradientBoostingRegr':'GradientBoostingRegressor',\n",
    "            'LGBMRegressor()':'LGBMRegressor',\n",
    "            'LinearRegression()':'LinearRegression',\n",
    "            'RandomForestRegresso':'RandomForestRegressor',\n",
    "            'StackingRegressor(cv':'StackingRegressor(Dynamic)',\n",
    "            'XGBRegressor(base_sc':'XGBRegressor',\n",
    "             'ExtraTreesRegressor(':'ExtraTreesRegressor',\n",
    "             '<catboost.core.':'Catboost',\n",
    "             'Stacking_SGDRegresso':'StackingSGDRegressor'\n",
    "            }\n",
    "    df_model.columns = [col_rev[c] for c in df_model.columns]\n",
    "\n",
    "    ax=df_model.plot(kind='bar',rot=65,width = .9, stacked=True)\n",
    "    bars = ax.patches\n",
    "    patterns =('/', '////', '\\\\\\\\\\\\','/','//','||','o','\\\\','\\\\\\\\')\n",
    "    hatches = [p for p in patterns for i in range(len(df_n))]\n",
    "    for bar, hatch in zip(bars, hatches):\n",
    "        bar.set_hatch(hatch)\n",
    "    plt.xlabel(\"Dataset\", fontsize=14)\n",
    "    plt.ylabel(\"Total Number of Wins\", fontsize=14)\n",
    "    _type='KL Model Selection' if 'KL' in c else 'PDF Model Selection'\n",
    "    ax.set_title(f'{_type} ($T={len(df)}, \\\\beta={B}$)',fontsize=18)\n",
    "    plt.grid()\n",
    "    plt.legend(bbox_to_anchor=(1, .5),fontsize=10)\n",
    "    ax.set_xlim([0, 10])\n",
    "    df_model.to_csv(f'paper/df_model_{c}_{B}.jpg')\n",
    "    plt.savefig(f'paper/df_model_{c}_{B}.jpg', bbox_inches=\"tight\")\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1310,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=draw_model_stat(df,c='Model_Selector',B=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1311,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=draw_model_stat(df,c='KL_Model',B=100)"
   ]
  }
 ],
 "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}