test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Looking at GAMBIT scan outputs\n",
    "\n",
    "This is a small test notebook for looking a t GAMBIT test outputs. It contains a few examples for how to read `hdf5` files and make plots and is in no way complete!\n",
    "\n",
    "## Open file with scan results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keys:  ['WC', 'metadata']\n",
      "Key: #B2mumu_LogLikelihood_Atlas @FlavBit::HEPLike_B2mumu_LogLikelihood_Atlas\n",
      "Key: #B2mumu_LogLikelihood_Atlas @FlavBit::HEPLike_B2mumu_LogLikelihood_Atlas_isvalid\n",
      "Key: #B2mumu_LogLikelihood_CMS @FlavBit::HEPLike_B2mumu_LogLikelihood_CMS\n",
      "Key: #B2mumu_LogLikelihood_CMS @FlavBit::HEPLike_B2mumu_LogLikelihood_CMS_isvalid\n",
      "Key: #B2mumu_LogLikelihood_LHCb @FlavBit::HEPLike_B2mumu_LogLikelihood_LHCb\n",
      "Key: #B2mumu_LogLikelihood_LHCb @FlavBit::HEPLike_B2mumu_LogLikelihood_LHCb_isvalid\n",
      "Key: #StandardModel_Higgs_parameters @StandardModel_Higgs::primary_parameters::mH\n",
      "Key: #StandardModel_Higgs_parameters @StandardModel_Higgs::primary_parameters::mH_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_A\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_A_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_etabar\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_etabar_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_lambda\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_lambda_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_rhobar\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_rhobar_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::GF\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::GF_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alpha1\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alpha1_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alpha2\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alpha2_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alphaS\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alphaS_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alphainv\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::alphainv_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::delta13\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::delta13_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mBmB\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mBmB_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mCmC\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mCmC_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mD\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mD_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mE\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mE_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mMu\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mMu_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mNu1\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mNu1_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mNu2\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mNu2_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mNu3\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mNu3_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mS\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mS_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mT\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mT_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mTau\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mTau_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mU\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mU_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mZ\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::mZ_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::theta12\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::theta12_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::theta13\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::theta13_isvalid\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::theta23\n",
      "Key: #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::theta23_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaC10\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaC10_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaC7\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaC7_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaC9\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaC9_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaCQ1\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaCQ1_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaCQ2\n",
      "Key: #WC_parameters @WC::primary_parameters::Im_DeltaCQ2_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaC10\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaC10_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaC7\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaC7_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaC9\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaC9_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaCQ1\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaCQ1_isvalid\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaCQ2\n",
      "Key: #WC_parameters @WC::primary_parameters::Re_DeltaCQ2_isvalid\n",
      "Key: #b2sgamma_LogLikelihood @FlavBit::HEPLike_b2sgamma_LogLikelihood\n",
      "Key: #b2sgamma_LogLikelihood @FlavBit::HEPLike_b2sgamma_LogLikelihood_isvalid\n",
      "Key: LogLike\n",
      "Key: LogLike_isvalid\n",
      "Key: MPIrank\n",
      "Key: MPIrank_isvalid\n",
      "Key: ModifiedLogLike\n",
      "Key: ModifiedLogLike_isvalid\n",
      "Key: pointID\n",
      "Key: pointID_isvalid\n",
      "Key: scanID\n",
      "Key: scanID_isvalid\n",
      "[-119.73873928 -158.0929235   -10.3239199  ...   -1.32523466   -1.32514564\n",
      "   -1.32522438]\n"
     ]
    }
   ],
   "source": [
    "import h5py\n",
    "import os\n",
    "\n",
    "# Open h5py file with scan results\n",
    "hdf = h5py.File(os.getcwd()+'/runs/WC_lite/samples/WC.hdf5', 'r')\n",
    "\n",
    "# Print top-level keys\n",
    "print(\"Keys: \", list(hdf.keys()))\n",
    "\n",
    "# Extract dataset with scan data\n",
    "dataset = hdf['WC']\n",
    "\n",
    "# Can e.g. loop over keys and print them:\n",
    "for key in dataset.keys():\n",
    "    print(\"Key:\", key)\n",
    "    \n",
    "# Can extract contents of dataset's entries with:\n",
    "print(dataset['LogLike'][:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract contents into python dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "datadict = {}\n",
    "for key in dataset.keys():\n",
    "    datadict[key] = dataset[key][:]\n",
    "    if \"MSSM7\" in key:\n",
    "        print(\"Key:\", key)\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read dict into pandas dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#B2mumu_LogLikelihood_Atlas @FlavBit::HEPLike_B2mumu_LogLikelihood_Atlas</th>\n",
       "      <th>#B2mumu_LogLikelihood_Atlas @FlavBit::HEPLike_B2mumu_LogLikelihood_Atlas_isvalid</th>\n",
       "      <th>#B2mumu_LogLikelihood_CMS @FlavBit::HEPLike_B2mumu_LogLikelihood_CMS</th>\n",
       "      <th>#B2mumu_LogLikelihood_CMS @FlavBit::HEPLike_B2mumu_LogLikelihood_CMS_isvalid</th>\n",
       "      <th>#B2mumu_LogLikelihood_LHCb @FlavBit::HEPLike_B2mumu_LogLikelihood_LHCb</th>\n",
       "      <th>#B2mumu_LogLikelihood_LHCb @FlavBit::HEPLike_B2mumu_LogLikelihood_LHCb_isvalid</th>\n",
       "      <th>#StandardModel_Higgs_parameters @StandardModel_Higgs::primary_parameters::mH</th>\n",
       "      <th>#StandardModel_Higgs_parameters @StandardModel_Higgs::primary_parameters::mH_isvalid</th>\n",
       "      <th>#StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_A</th>\n",
       "      <th>#StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_A_isvalid</th>\n",
       "      <th>...</th>\n",
       "      <th>LogLike</th>\n",
       "      <th>LogLike_isvalid</th>\n",
       "      <th>MPIrank</th>\n",
       "      <th>MPIrank_isvalid</th>\n",
       "      <th>ModifiedLogLike</th>\n",
       "      <th>ModifiedLogLike_isvalid</th>\n",
       "      <th>pointID</th>\n",
       "      <th>pointID_isvalid</th>\n",
       "      <th>scanID</th>\n",
       "      <th>scanID_isvalid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0.814</td>\n",
       "      <td>1</td>\n",
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       "      <td>-119.738739</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-119.738739</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>133053841</td>\n",
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       "    <tr>\n",
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       "      <td>-47.122478</td>\n",
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       "      <td>125.09</td>\n",
       "      <td>1</td>\n",
       "      <td>0.814</td>\n",
       "      <td>1</td>\n",
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       "      <td>-158.092924</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-158.092924</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>133053841</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
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       "      <td>-0.591055</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.314953</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.744503</td>\n",
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       "      <td>125.09</td>\n",
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       "      <td>0.814</td>\n",
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       "      <td>-10.323920</td>\n",
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       "      <td>-10.323920</td>\n",
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       "      <td>1</td>\n",
       "      <td>133053841</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>-25.880368</td>\n",
       "      <td>1</td>\n",
       "      <td>125.09</td>\n",
       "      <td>1</td>\n",
       "      <td>0.814</td>\n",
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       "      <td>-42.173662</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>-42.173662</td>\n",
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       "      <td>133053841</td>\n",
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       "      <td>1</td>\n",
       "      <td>-0.430827</td>\n",
       "      <td>1</td>\n",
       "      <td>125.09</td>\n",
       "      <td>1</td>\n",
       "      <td>0.814</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.325224</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.325224</td>\n",
       "      <td>1</td>\n",
       "      <td>7600</td>\n",
       "      <td>1</td>\n",
       "      <td>133053841</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7600 rows × 92 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      #B2mumu_LogLikelihood_Atlas @FlavBit::HEPLike_B2mumu_LogLikelihood_Atlas  \\\n",
       "0                                            -27.698807                          \n",
       "1                                            -37.957563                          \n",
       "2                                             -0.591055                          \n",
       "3                                             -3.188283                          \n",
       "4                                            -20.027890                          \n",
       "...                                                 ...                          \n",
       "7595                                          -0.851461                          \n",
       "7596                                          -0.875610                          \n",
       "7597                                          -0.851899                          \n",
       "7598                                          -0.849640                          \n",
       "7599                                          -0.853545                          \n",
       "\n",
       "      #B2mumu_LogLikelihood_Atlas @FlavBit::HEPLike_B2mumu_LogLikelihood_Atlas_isvalid  \\\n",
       "0                                                     1                                  \n",
       "1                                                     1                                  \n",
       "2                                                     1                                  \n",
       "3                                                     1                                  \n",
       "4                                                     1                                  \n",
       "...                                                 ...                                  \n",
       "7595                                                  1                                  \n",
       "7596                                                  1                                  \n",
       "7597                                                  1                                  \n",
       "7598                                                  1                                  \n",
       "7599                                                  1                                  \n",
       "\n",
       "      #B2mumu_LogLikelihood_CMS @FlavBit::HEPLike_B2mumu_LogLikelihood_CMS  \\\n",
       "0                                            -44.902319                      \n",
       "1                                            -57.710037                      \n",
       "2                                             -0.314953                      \n",
       "3                                             -4.578417                      \n",
       "4                                             -8.924414                      \n",
       "...                                                 ...                      \n",
       "7595                                          -0.041472                      \n",
       "7596                                          -0.034082                      \n",
       "7597                                          -0.041338                      \n",
       "7598                                          -0.042033                      \n",
       "7599                                          -0.040832                      \n",
       "\n",
       "      #B2mumu_LogLikelihood_CMS @FlavBit::HEPLike_B2mumu_LogLikelihood_CMS_isvalid  \\\n",
       "0                                                     1                              \n",
       "1                                                     1                              \n",
       "2                                                     1                              \n",
       "3                                                     1                              \n",
       "4                                                     1                              \n",
       "...                                                 ...                              \n",
       "7595                                                  1                              \n",
       "7596                                                  1                              \n",
       "7597                                                  1                              \n",
       "7598                                                  1                              \n",
       "7599                                                  1                              \n",
       "\n",
       "      #B2mumu_LogLikelihood_LHCb @FlavBit::HEPLike_B2mumu_LogLikelihood_LHCb  \\\n",
       "0                                            -45.546427                        \n",
       "1                                            -47.122478                        \n",
       "2                                             -1.744503                        \n",
       "3                                            -25.880368                        \n",
       "4                                            -30.074185                        \n",
       "...                                                 ...                        \n",
       "7595                                          -0.432215                        \n",
       "7596                                          -0.416195                        \n",
       "7597                                          -0.431923                        \n",
       "7598                                          -0.433430                        \n",
       "7599                                          -0.430827                        \n",
       "\n",
       "      #B2mumu_LogLikelihood_LHCb @FlavBit::HEPLike_B2mumu_LogLikelihood_LHCb_isvalid  \\\n",
       "0                                                     1                                \n",
       "1                                                     1                                \n",
       "2                                                     1                                \n",
       "3                                                     1                                \n",
       "4                                                     1                                \n",
       "...                                                 ...                                \n",
       "7595                                                  1                                \n",
       "7596                                                  1                                \n",
       "7597                                                  1                                \n",
       "7598                                                  1                                \n",
       "7599                                                  1                                \n",
       "\n",
       "      #StandardModel_Higgs_parameters @StandardModel_Higgs::primary_parameters::mH  \\\n",
       "0                                                125.09                              \n",
       "1                                                125.09                              \n",
       "2                                                125.09                              \n",
       "3                                                125.09                              \n",
       "4                                                125.09                              \n",
       "...                                                 ...                              \n",
       "7595                                             125.09                              \n",
       "7596                                             125.09                              \n",
       "7597                                             125.09                              \n",
       "7598                                             125.09                              \n",
       "7599                                             125.09                              \n",
       "\n",
       "      #StandardModel_Higgs_parameters @StandardModel_Higgs::primary_parameters::mH_isvalid  \\\n",
       "0                                                     1                                      \n",
       "1                                                     1                                      \n",
       "2                                                     1                                      \n",
       "3                                                     1                                      \n",
       "4                                                     1                                      \n",
       "...                                                 ...                                      \n",
       "7595                                                  1                                      \n",
       "7596                                                  1                                      \n",
       "7597                                                  1                                      \n",
       "7598                                                  1                                      \n",
       "7599                                                  1                                      \n",
       "\n",
       "      #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_A  \\\n",
       "0                                                 0.814                                 \n",
       "1                                                 0.814                                 \n",
       "2                                                 0.814                                 \n",
       "3                                                 0.814                                 \n",
       "4                                                 0.814                                 \n",
       "...                                                 ...                                 \n",
       "7595                                              0.814                                 \n",
       "7596                                              0.814                                 \n",
       "7597                                              0.814                                 \n",
       "7598                                              0.814                                 \n",
       "7599                                              0.814                                 \n",
       "\n",
       "      #StandardModel_SLHA2_parameters @StandardModel_SLHA2::primary_parameters::CKM_A_isvalid  \\\n",
       "0                                                     1                                         \n",
       "1                                                     1                                         \n",
       "2                                                     1                                         \n",
       "3                                                     1                                         \n",
       "4                                                     1                                         \n",
       "...                                                 ...                                         \n",
       "7595                                                  1                                         \n",
       "7596                                                  1                                         \n",
       "7597                                                  1                                         \n",
       "7598                                                  1                                         \n",
       "7599                                                  1                                         \n",
       "\n",
       "      ...     LogLike  LogLike_isvalid  MPIrank  MPIrank_isvalid  \\\n",
       "0     ... -119.738739                1        0                1   \n",
       "1     ... -158.092924                1        0                1   \n",
       "2     ...  -10.323920                1        0                1   \n",
       "3     ...  -42.173662                1        0                1   \n",
       "4     ...  -65.594049                1        0                1   \n",
       "...   ...         ...              ...      ...              ...   \n",
       "7595  ...   -1.325430                1        0                1   \n",
       "7596  ...   -1.325892                1        0                1   \n",
       "7597  ...   -1.325235                1        0                1   \n",
       "7598  ...   -1.325146                1        0                1   \n",
       "7599  ...   -1.325224                1        0                1   \n",
       "\n",
       "      ModifiedLogLike  ModifiedLogLike_isvalid  pointID  pointID_isvalid  \\\n",
       "0         -119.738739                        1        1                1   \n",
       "1         -158.092924                        1        2                1   \n",
       "2          -10.323920                        1        3                1   \n",
       "3          -42.173662                        1        4                1   \n",
       "4          -65.594049                        1        5                1   \n",
       "...               ...                      ...      ...              ...   \n",
       "7595        -1.325430                        1     7596                1   \n",
       "7596        -1.325892                        1     7597                1   \n",
       "7597        -1.325235                        1     7598                1   \n",
       "7598        -1.325146                        1     7599                1   \n",
       "7599        -1.325224                        1     7600                1   \n",
       "\n",
       "         scanID  scanID_isvalid  \n",
       "0     133053841               1  \n",
       "1     133053841               1  \n",
       "2     133053841               1  \n",
       "3     133053841               1  \n",
       "4     133053841               1  \n",
       "...         ...             ...  \n",
       "7595  133053841               1  \n",
       "7596  133053841               1  \n",
       "7597  133053841               1  \n",
       "7598  133053841               1  \n",
       "7599  133053841               1  \n",
       "\n",
       "[7600 rows x 92 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "scan = pd.DataFrame(datadict)\n",
    "\n",
    "scan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the available keys, we can see that the scan parameters are stored under `#WC_parameters @WC::primary_parameters::...`. Let's look at the part of out dataframe which contains these:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>#WC_parameters @WC::primary_parameters::Im_DeltaC10</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Im_DeltaC7</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Im_DeltaC9</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Im_DeltaCQ1</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Im_DeltaCQ2</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Re_DeltaC10</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Re_DeltaC7</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Re_DeltaC9</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Re_DeltaCQ1</th>\n",
       "      <th>#WC_parameters @WC::primary_parameters::Re_DeltaCQ2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.470887</td>\n",
       "      <td>-0.035139</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.529395</td>\n",
       "      <td>0.088759</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.723627</td>\n",
       "      <td>0.063279</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.233892</td>\n",
       "      <td>0.066664</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.927405</td>\n",
       "      <td>0.058579</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7595</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.404574</td>\n",
       "      <td>-0.001471</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7596</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.388371</td>\n",
       "      <td>-0.001831</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7597</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.404279</td>\n",
       "      <td>-0.001674</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7598</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.405801</td>\n",
       "      <td>-0.001725</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7599</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.403170</td>\n",
       "      <td>-0.001777</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7600 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      #WC_parameters @WC::primary_parameters::Im_DeltaC10  \\\n",
       "0                                                   0.0     \n",
       "1                                                   0.0     \n",
       "2                                                   0.0     \n",
       "3                                                   0.0     \n",
       "4                                                   0.0     \n",
       "...                                                 ...     \n",
       "7595                                                0.0     \n",
       "7596                                                0.0     \n",
       "7597                                                0.0     \n",
       "7598                                                0.0     \n",
       "7599                                                0.0     \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Im_DeltaC7  \\\n",
       "0                                                   0.0    \n",
       "1                                                   0.0    \n",
       "2                                                   0.0    \n",
       "3                                                   0.0    \n",
       "4                                                   0.0    \n",
       "...                                                 ...    \n",
       "7595                                                0.0    \n",
       "7596                                                0.0    \n",
       "7597                                                0.0    \n",
       "7598                                                0.0    \n",
       "7599                                                0.0    \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Im_DeltaC9  \\\n",
       "0                                                   0.0    \n",
       "1                                                   0.0    \n",
       "2                                                   0.0    \n",
       "3                                                   0.0    \n",
       "4                                                   0.0    \n",
       "...                                                 ...    \n",
       "7595                                                0.0    \n",
       "7596                                                0.0    \n",
       "7597                                                0.0    \n",
       "7598                                                0.0    \n",
       "7599                                                0.0    \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Im_DeltaCQ1  \\\n",
       "0                                                   0.0     \n",
       "1                                                   0.0     \n",
       "2                                                   0.0     \n",
       "3                                                   0.0     \n",
       "4                                                   0.0     \n",
       "...                                                 ...     \n",
       "7595                                                0.0     \n",
       "7596                                                0.0     \n",
       "7597                                                0.0     \n",
       "7598                                                0.0     \n",
       "7599                                                0.0     \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Im_DeltaCQ2  \\\n",
       "0                                                   0.0     \n",
       "1                                                   0.0     \n",
       "2                                                   0.0     \n",
       "3                                                   0.0     \n",
       "4                                                   0.0     \n",
       "...                                                 ...     \n",
       "7595                                                0.0     \n",
       "7596                                                0.0     \n",
       "7597                                                0.0     \n",
       "7598                                                0.0     \n",
       "7599                                                0.0     \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Re_DeltaC10  \\\n",
       "0                                             -2.470887     \n",
       "1                                             -2.529395     \n",
       "2                                              0.723627     \n",
       "3                                              2.233892     \n",
       "4                                             -1.927405     \n",
       "...                                                 ...     \n",
       "7595                                           0.404574     \n",
       "7596                                           0.388371     \n",
       "7597                                           0.404279     \n",
       "7598                                           0.405801     \n",
       "7599                                           0.403170     \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Re_DeltaC7  \\\n",
       "0                                             -0.035139    \n",
       "1                                              0.088759    \n",
       "2                                              0.063279    \n",
       "3                                              0.066664    \n",
       "4                                              0.058579    \n",
       "...                                                 ...    \n",
       "7595                                          -0.001471    \n",
       "7596                                          -0.001831    \n",
       "7597                                          -0.001674    \n",
       "7598                                          -0.001725    \n",
       "7599                                          -0.001777    \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Re_DeltaC9  \\\n",
       "0                                                   0.0    \n",
       "1                                                   0.0    \n",
       "2                                                   0.0    \n",
       "3                                                   0.0    \n",
       "4                                                   0.0    \n",
       "...                                                 ...    \n",
       "7595                                                0.0    \n",
       "7596                                                0.0    \n",
       "7597                                                0.0    \n",
       "7598                                                0.0    \n",
       "7599                                                0.0    \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Re_DeltaCQ1  \\\n",
       "0                                                   0.0     \n",
       "1                                                   0.0     \n",
       "2                                                   0.0     \n",
       "3                                                   0.0     \n",
       "4                                                   0.0     \n",
       "...                                                 ...     \n",
       "7595                                                0.0     \n",
       "7596                                                0.0     \n",
       "7597                                                0.0     \n",
       "7598                                                0.0     \n",
       "7599                                                0.0     \n",
       "\n",
       "      #WC_parameters @WC::primary_parameters::Re_DeltaCQ2  \n",
       "0                                                   0.0    \n",
       "1                                                   0.0    \n",
       "2                                                   0.0    \n",
       "3                                                   0.0    \n",
       "4                                                   0.0    \n",
       "...                                                 ...    \n",
       "7595                                                0.0    \n",
       "7596                                                0.0    \n",
       "7597                                                0.0    \n",
       "7598                                                0.0    \n",
       "7599                                                0.0    \n",
       "\n",
       "[7600 rows x 10 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scan.filter(regex='^#WC_parameters @WC::primary_parameters(?!.*_isvalid)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this we can see that only the two parameters `Re_DeltaC10` and `Re_DeltaC7` actually contribute. Next, we'll make some plots for these. The dataset contains an `_isvalid` column for each parameter. This is necessary to filter out bad points which occured during the scan. Do this with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "validlogs = scan[ scan['LogLike_isvalid'] == 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use these to plot the (maximum) [negative LogLikelihood](https://www.sciencedirect.com/topics/computer-science/negative-log-likelihood#:~:text='Negative%20Log%20Likelihood'%20is%20defined,method%20to%20determine%20model%20parameters.):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12eb1af10>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot(validlogs['LogLike'], label = 'LogLike')\n",
    "plt.scatter(validlogs['LogLike'].idxmax(), validlogs['LogLike'].max(), label = 'max. LogLike')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.40797556197302143"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print the max. LokLike (i.e. best fit point:)\n",
    "validlogs.loc[ validlogs['LogLike'].idxmax(), \"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute the profile Likelihood ratio:\n",
    "\n",
    "The Likelihood is related to the negative Log-Likelihood by: $L(\\theta) = \\exp{(\\mathrm{NLL}(\\theta))}$. Thus, the profile likelihood ratio can be computed with: $L(\\theta)/L_{\\mathrm{max}} = \\exp{(\\mathrm{NLL}(\\theta) - \\mathrm{NLL}_\\mathrm{max}(\\theta))} $"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12ebe2f70>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Make new column in dataframe:\n",
    "validlogs['ProfLikeRatio'] = np.exp( (validlogs['LogLike']-validlogs['LogLike'].max()))\n",
    "\n",
    "# plot:\n",
    "plt.plot(validlogs['ProfLikeRatio'], label = 'Profile Likelihood Ratio')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using this, we can plot a histogram of `Re_DeltaC10` with the best fit point indicated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12eca4910>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.hist(validlogs[\"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"], label = 'Valid Re_DeltaC10')\n",
    "ax.axvline(x=validlogs.loc[ validlogs['ProfLikeRatio'].idxmax(),\n",
    "                           \"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"],\n",
    "                            c='r',\n",
    "                            label = 'Max Loglike')\n",
    "ax.set_xlabel('Re_DeltaC10')\n",
    "ax.set_ylabel('Counts')\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or we can plot the profile likelihood ratio directly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12ed2f940>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ktk79wdtCRK6IxQ0Rua3iSq3oCNDp2X1DZG0sbojIbYX4iL0tBQAf7z8jOgKRy2FxQ0Ruq1pnEB0BZ0o5HZzI2ljcEJHbKq7UiY6ASxsxEJE1sbghIrdkMMqo1IrvuenYJlB0BCKXw+KGiNxSem6Z6AgAgPLaetERiFyO8OJm6dKliI+Ph5eXF5KTk7F79+5rnr927Vrcdttt8PHxQWRkJB555BGUlnLzOSKyTFFFregIAIACB8lB5EqEFjcbNmzAtGnT8MILL+DIkSPo1asXBg8ejLy8vCbP37NnD8aOHYsJEybg+PHj+O9//4uDBw/iscces3NyInJ2FxxgGjgAbMw4JzoCkcsRWtzMnz8fEyZMwGOPPYaEhAQsXLgQ0dHRWLZsWZPnHzhwAHFxcUhNTUV8fDzuvPNOPPHEEzh06JCdkxORs8sqdIytDzR1BhiMHFRMZE3CihudToeMjAwMGDCgwfEBAwZg3759TT4nJSUF586dw5YtWyDLMv744w98/vnnGDp06FXb0Wq10Gg0DR5ERFVavegIJgdO89Y6kTUJK25KSkpgMBgQHh7e4Hh4eDiKioqafE5KSgrWrl2LUaNGQaVSISIiAkFBQXj33Xev2s68efMQGBhoekRHR1v1dRCRcwr1U4mOYLLz92LREYhcivABxZIkNfhcluVGxy7LyspCamoqXnrpJWRkZGDr1q3Izc3FxIkTr3r9WbNmoaKiwvTIz8+3an4ick41DjAN/LIfspr+g46ImsdDVMOhoaFQKpWNemmKi4sb9eZcNm/ePPTs2RPPPvssAKBjx47w9fVFr1698NprryEyMrLRc9RqNdRqtfVfABE5tfPljjNL6WKNIywmSOQ6hPXcqFQqJCcnIy0trcHxtLQ0pKSkNPmcmpoaKBQNIyuVl/aGkWUOyCMi86k9hXdcm/g6UBYiVyD0X9SMGTOwYsUKrFy5EtnZ2Zg+fTry8vJMt5lmzZqFsWPHms4fNmwYNm3ahGXLliEnJwd79+5FamoqunXrhqioKFEvg4icUCtfx+nR7RARIDoCkUsRdlsKAEaNGoXS0lK8+uqrKCwsRFJSErZs2YLY2FgAQGFhYYM1b8aPH4/KykosXrwYTz/9NIKCgnDPPffgjTfeEPUSiMhJZRVWiI5golSI352cyJVIspvdz9FoNAgMDERFRQUCAvjXEpE70umN6PCv76x2PW9dHbIX/AMAkDD9c9SqvCx6fs92rbD28e5Wy0Pkiiz5/c0bvUTkdlbvzRUdoYFAL/bcEFkTixsicjuONvV6DxfxI7IqFjdE5HaMDrbdgabOAJ3eKDoGkctgcUNEbifI11N0hEZW7s4RHYHIZbC4ISK3ExnoIzpCI5uOcHdwImthcUNEbieula/oCI1o6hxnI08iZ8fihojcTocwP9ERGvFUNL2nHhFZjsUNEbmdT34+KzpCI39o6mBwsIHORM6KxQ0RuRWDUcb234pFx2hEZwTSc8tExyByCSxuiMitHMgphaN2kBRX1omOQOQSWNwQkVvZd6pEdISrCvFWiY5A5BJY3BCRWzlfXis6wlX9WuA4m3kSOTMWN0TkVqKCvEVHuKqvMs+LjkDkEljcEJFb6dk+VHSEq9LqDaIjELkEFjdE5Fa6xoWIjnBV7Vo73uKCRM6IxQ0RuZWfcxx3B+7BSVGiIxC5BBY3RORW3v3xpOgIV9Um2PH2vCJyRixuiMhtGIwyjuSXi45xVZ2ig0RHIHIJLG6IyG2k55ah3uCgK/gB+NQBt4UgckYsbojIbRRcrBEd4ZpW7c0VHYHIJTSruNm5cyeGDRuG9u3b48Ybb8Tw4cOxe/dua2cjIrKqQ2cvio5wTefK61Cr43RwopayuLj55JNP0K9fP/j4+CA1NRVTpkyBt7c3+vbti08//dQWGYmIrCLDwYsbAHh9S5boCEROz8PSJ8ydOxdvvvkmpk+fbjr21FNPYf78+ZgzZw5Gjx5t1YBERNZSbzSKjnBdOReqREcgcnoW99zk5ORg2LBhjY4PHz4cubm8X0xEjuuOeMddwO+y8w4+LojIGVhc3ERHR2P79u2Njm/fvh3R0dFWCUVEZAsDEyNER7iuM2V1MBgdd0YXkTOw+LbU008/jdTUVGRmZiIlJQWSJGHPnj1YvXo13nnnHVtkJCKyioNOMOYGAPadLEGvm1qLjkHktCwubiZNmoSIiAi8/fbb+OyzzwAACQkJ2LBhA0aMGGH1gERE1lJQXis6glk+O5zH4oaoBSwubgDg3nvvxb333mvtLERENtUmyFt0BLOcKOSgYqKW4CJ+ROQ2UtqHio5gFj8vpegIRE7NrJ6bkJAQ/P777wgNDUVwcDAkSbrquWVlZVYLR0RkTRU1OtERzHJTeIDoCEROzaziZsGCBfD39zd9fK3ihojIERmMMp7/8pjoGGYJ9lGJjkDk1MwqbsaNG2f6ePz48bbKQkRkMwdySlFeUy86hlkUHDBA1CIW/xNSKpUoLi5udLy0tBRKJe8TE5Fj2n+6VHQEs/W4wTnGBhE5KouLG1luenEprVYLlYpdqUTkqJxjYTwfTwW6t2slOgaRUzN7KviiRYsAAJIkYcWKFfDz8zN9zWAwYNeuXbj55putn5CIyAp63BCKxTtOi45xXUltAqFUcFwjUUuYXdwsWLAAwKWem/fee6/BLSiVSoW4uDi899571k9IRGQF3du1go9KgRqdY2+eqdUbREcgcnpmFzeXN8Xs06cPNm3ahODgYJuFIiKyDcfvETl9oQoGo8zeG6IWsHjMzY4dO1jYEJHTOXC6FDU6x+8VqdIakZ7L9cKIWqJZ2y+cO3cOmzdvRl5eHnS6hotizZ8/3yrBiIisae/pC6IjmK24sk50BCKnZnFxs337dgwfPhzx8fE4ceIEkpKScObMGciyjM6dO9siIxFRixWUO0/BkHuhWnQEIqdm8W2pWbNm4emnn8axY8fg5eWFjRs3Ij8/H71798Z9991ni4xERC0WFegcm2YCwEf7z8BgdI6p60SOyOLiJjs727RisYeHB2pra+Hn54dXX30Vb7zxhtUDEhFZwx9OdKvnYk09x90QtYDFxY2vry+0Wi0AICoqCqdP/7luRElJifWSERFZicEoY8uvhaJjWITjboiaz+IxN927d8fevXuRmJiIoUOH4umnn8avv/6KTZs2oXv37rbISETUIgdySlFb79jr21wpzN9LdAQip2VxcTN//nxUVVUBAF5++WVUVVVhw4YNaN++vWmhPyIiR7LvtPP1KifHcskNouayqLgxGAzIz89Hx44dAQA+Pj5YunSpTYIREVnL2VLnm310MLcMPW/kBppEzWHRmBulUomBAweivLzcRnGIiKwv90KV6AgW23PSedblIXI0Fg8ovvXWW5GTk2OLLERENuHo+0k15ej5CtERiJyWxcXN3Llz8cwzz+Cbb75BYWEhNBpNgwcRkaOJCnKeNW4uq6t3/K0iiByVxQOKBw0aBAAYPnw4JOnPjd1kWYYkSTAY+A+SiBzL/+t1A/aeLhUdwyJqD4v/9iSi/7G4uNmxY4ctchAR2Uy1Ti86gsU6RgeKjkDktCwubnr37m2LHERENmEwynjm86OiY1isRxxnShE1F/s9icil7TtZghqd890uP1FcKToCkdNicUNELu3zw/miIzTLwbPcW4qouVjcEJFLyyp0zinVtVrn620ichQsbojItcnS9c9xQLe25YBiouYSXtwsXboU8fHx8PLyQnJyMnbv3n3N87VaLV544QXExsZCrVajXbt2WLlypZ3SEpGzaR2gFh2hWe5s31p0BCKnZdZsqdtvv73BmjbXcvjwYbMb37BhA6ZNm4alS5eiZ8+eWL58OQYPHoysrCzExMQ0+Zz7778ff/zxBz788EO0b98excXF0Oudb5onEdlHxzZB2HfaucaveHko0L1dK9ExiJyWWcXNyJEjTR/X1dVh6dKlSExMRI8ePQAABw4cwPHjxzF58mSLGp8/fz4mTJiAxx57DACwcOFCfP/991i2bBnmzZvX6PytW7di586dyMnJQUhICAAgLi7OojaJyL208lOJjmAxoyyLjkDk1MwqbmbPnm36+LHHHkNqairmzJnT6Jz8fPNnJeh0OmRkZGDmzJkNjg8YMAD79u1r8jmbN29Gly5d8Oabb+Ljjz+Gr68vhg8fjjlz5sDbu+nl1bVaLbRarelzbhFB5F5C/b1ER7CYziDjwOlS7gpO1EwWj7n573//i7FjxzY6/vDDD2Pjxo1mX6ekpAQGgwHh4eENjoeHh6OoqKjJ5+Tk5GDPnj04duwYvvjiCyxcuBCff/45nnzyyau2M2/ePAQGBpoe0dHRZmckIucXEeB8xQ0A7M8pER2ByGlZXNx4e3tjz549jY7v2bMHXl6W/xC5cizP5T2qmmI0GiFJEtauXYtu3bphyJAhmD9/PlavXo3a2tomnzNr1ixUVFSYHpb0LhGR8yup0l7/JIfknLO8iByBxdsvTJs2DZMmTUJGRga6d+8O4NKYm5UrV+Kll14y+zqhoaFQKpWNemmKi4sb9eZcFhkZiTZt2iAw8M8pkgkJCZBlGefOncONN97Y6DlqtRpqtXPOliCiljEYZcz+6rjoGM1yR3yI6AhETsvinpuZM2dizZo1OHLkCFJTU5GamoojR45g9erVjcbPXItKpUJycjLS0tIaHE9LS0NKSkqTz+nZsycKCgpQVVVlOvb7779DoVCgbdu2lr4UInJx6bllKKvRiY7RLBlnL4qOQOS0mrXOzf3334+9e/eirKwMZWVl2Lt3L+6//36LrzNjxgysWLECK1euRHZ2NqZPn468vDxMnDgRwKVbSn8d3zN69Gi0atUKjzzyCLKysrBr1y48++yzePTRR686oJiI3FeRpk50hGZbve8MDEbOmiJqDotvS12WkZGB7OxsSJKExMRE3H777RZfY9SoUSgtLcWrr76KwsJCJCUlYcuWLYiNjQUAFBYWIi8vz3S+n58f0tLSMHXqVHTp0gWtWrXC/fffj9dee625L4OIXFhJpbOOtwHKa+uRnluGHlzvhshiFhc3xcXFeOCBB/DTTz8hKCgIsiyjoqICffr0wfr169G6tWWrak6ePPmq6+OsXr260bGbb7650a0sIqKmXHTSW1KXFVc6b88TkUgW35aaOnUqNBoNjh8/jrKyMly8eBHHjh2DRqNBamqqLTISETWTc9/WCfFxvgUIiRyBxcXN1q1bsWzZMiQkJJiOJSYmYsmSJfjuu++sGo6IqCWCfZx7puTx8865ozmRaBYXN0ajEZ6eno2Oe3p6wmg0WiUUEZE1hPo7d3Gz7bc/REcgckoWFzf33HMPnnrqKRQUFJiOnT9/HtOnT0ffvn2tGo6IqCWcdXXiy5z7phqROBYXN4sXL0ZlZSXi4uLQrl07tG/fHvHx8aisrMS7775ri4xERM3SKTpIdIQWuSncT3QEIqdk8Wyp6OhoHD58GGlpafjtt98gyzISExPRr18/W+QjImq2f315VHSEFrk9Olh0BCKn1Ox1bvr374/+/ftbMwsRkdUYjDK+ziy4/okOTFOnFx2ByCk1a4XinTt3YtiwYWjfvj1uvPFGDB8+HLt377Z2NiKiZkvPLYPOyec4BHo3nrxBRNdncXHzySefoF+/fvDx8UFqaiqmTJkCb29v9O3bF59++qktMhIRWcwVFsD75Vy56AhETsni21Jz587Fm2++ienTp5uOPfXUU5g/fz7mzJmD0aNHWzUgEVFzhPk790wpImo+i3tucnJyMGzYsEbHhw8fjtzcXKuEIiJqqW7xIQj2afawQocQE+IrOgKRU7K4uImOjsb27dsbHd++fTuio6OtEoqIqKWUCglzR94qOkaL3BzhLzoCkVOy+M+ap59+GqmpqcjMzERKSgokScKePXuwevVqvPPOO7bISETULEM6RuHx/HJ8sNs5e5XLnHzjTyJRLC5uJk2ahIiICLz99tv47LPPAAAJCQnYsGEDRowYYfWAREQt4ad23hlHHDdE1DzNuiF977334t5777V2FiIiq9p6rBALtv0uOkazXazWio5A5JSaPdpOp9OhuLi40WaZMTExLQ5FRNRSBqOMV77OEh2jRZ75/BcMTIqEUiGJjkLkVCwubk6ePIlHH30U+/bta3BclmVIkgSDwWC1cEREzZWeW4bCCude66ZGZ8S+kyXodVNr0VGInIrFxc348ePh4eGBb775BpGRkZAk/kVBRI6nsLxWdASr+PxwPosbIgtZXNxkZmYiIyMDN998sy3yEBFZxZH8i1a9XpCPJ14fmYTnvzyG8pp6q177Ws67SJFGZE8Wr3OTmJiIkpISW2QhIrIa2crX8/ZUYmBSJP79d/uundMmyMeu7RG5ArOKG41GY3q88cYb+Oc//4mffvoJpaWlDb6m0WhsnZeIyCzxray7um9hRR3Sc8vQPzECQT72m16eGBVgt7aIXIVZt6WCgoIajK2RZRl9+/ZtcA4HFBORIxnTIw5zvs226jWLK+uw+MeTdr0tFWLHQorIVZhV3OzYscPWOYiIrErlocDQWyPw7a9FVrvmmZJqLNh20mrXM8fXRwtxX1cusUFkCbOKm969e9s6BxGR1S16sDO2ZW+FVm+8/snXERnohXXpeVZIZZkDOaUwGGWudUNkAbOKm6NHjyIpKQkKhQJHjx695rkdO3a0SjAiopZSKiSMT4nF8l0t31uqZ7tW+PzweSuksozOIOPA6VL0vDHU7m0TOSuziptOnTqhqKgIYWFh6NSpEyRJgiw3novAMTdE5Ei2HivE+1YobAAIKWwu23v6AosbIguYVdzk5uaidevWpo+JiBzd5e0XrD0lXISCcudeaZnI3swqbmJjY5v8mIjIUbnC9guXtQn2Fh2ByKmYVdxs3rzZ7AsOHz682WGIiKyluNI1ChsASGnHW1JEljCruBk5cqRZF+OYGyJyFGH+XqIjWEWwjye639BKdAwip2JWcWM0tnwaJRGRPXWLD4HaQ2GVaeAizfv7rZwGTmQhi/eW+qu6Otfp9iUi1/Ld0UKnL2wAYOPhc6IjEDkdi4sbg8GAOXPmoE2bNvDz80NOTg4A4MUXX8SHH35o9YBERJYyGGXM+vJX0TGsIi2rGLU63u4nsoTFxc3cuXOxevVqvPnmm1CpVKbjt956K1asWGHVcEREzZGeW4bKOr3oGFYz55tjoiMQORWLi5s1a9bg/fffx0MPPQSlUmk63rFjR/z2229WDUdE1ByuNFMKAPadLhMdgcipWFzcnD9/Hu3bt2903Gg0or7efjvlEhFdjavMlLpMz1moRBaxuLi55ZZbsHv37kbH//vf/+L222+3SigiopboFh+CyEDXKXD8vTxFRyByKmZNBf+r2bNnY8yYMTh//jyMRiM2bdqEEydOYM2aNfjmm29skZGIyCJKhYTht0VaZcNMR+Djqbz+SURkYnHPzbBhw7BhwwZs2bIFkiThpZdeQnZ2Nr7++mv079/fFhmJiCyy9VihyxQ2AKBQtmjVDiK3Y3HPTX5+PgYOHIiBAwc2+tqBAwfQvXt3qwQjImoOg1HGzE2uMQ38sqwCDQxGmYv5EZnJ4j8H+vfvj9LS0kbH9+7di0GDBlklFBFRcx3IKUV5jfUnN4gsK6p1BhzIafxzl4iaZnFx06tXLwwYMACVlZWmY7t27cKQIUMwe/Zsq4YjIrLUvtMlNrluiK8KyTGBNrm2Ofaess3rInJFFhc377//PuLj4zF06FDU1dVhx44dGDp0KF599VVMnz7dFhmJiMx2/mKt1a7l7/XnQN7Sah2O5FdY7dqWKrDi6yJydRYXN5IkYd26dfDy8kLfvn0xfPhwzJs3D0899ZQt8hERWcSaU8Ar6xquL2OUrXZpy3G4DZHZzBpQfPTo0UbHZs+ejQcffBAPP/ww7rrrLtM5HTt2tG5CIiILhPiqrn+SE4oK9BYdgchpmFXcdOrUCZIkQZb//LPl8ufLly/H+++/D1mWIUkSDFxJk4gECvFVi45gE4E+Fk9uJXJbZv1ryc11nfUiiMi1ldfoREewibJq13xdRLZgVnETGxtr6xxERFYR4ueaPTfHzmtERyByGmYVN5s3b8bgwYPh6emJzZs3X/Pc4cOHWyUYEVFzRAS4zp5Sf1VU4Vo7nRPZklnFzciRI1FUVISwsDCMHDnyqudxzA0RidYtPgQhviqXu41z7mINVykmMpNZU8GNRiPCwsJMH1/twcKGiERTKiSM7BQlOobVaQ0y0nPLRMcgcgrcjY2IXE7/xAjREWyiuJK3pojMYdZtqUWLFpl9wdTU1GaHISKyhm7xIYgM9EKhmeNUgn08MWf4LUjdkCl2ob7rCPN3zfFERNZmVnGzYMECsy4mSRKLGyISTqmQMHtYIiZ9chgAcL16Ze7IW1FYUevQhQ0AdIoOEh2ByClwnRsickmDkiKx7OHOeOXrrKv24EQGemH4bZF49ZvjKNJo7ZzQcmv2n8ETvduJjkHk8LjkJRG5JJ3eiPMXa3HPTa1RXKlFWIAXYkJ8IMnAuYpaxIb4INzfC1PWH7H42kHeHiiv1dsg9bWlZRWxuCEyg/DiZunSpXjrrbdQWFiIW265BQsXLkSvXr2u+7y9e/eid+/eSEpKQmZmpu2DEpHTmLclCx/szr3ubabmTqoWUdgQkfmEzpbasGEDpk2bhhdeeAFHjhxBr169MHjwYOTl5V3zeRUVFRg7diz69u1rp6RE5CzmbcnC8l3XL2yA64/FcTQDXHQWGJG1CS1u5s+fjwkTJuCxxx5DQkICFi5ciOjoaCxbtuyaz3viiScwevRo9OjRw05JicgZ6PRGfLDbdccIju8ZLzoCkVMQVtzodDpkZGRgwIABDY4PGDAA+/btu+rzVq1ahdOnT2P27NlmtaPVaqHRaBo8iMg1fbz/jMPPeGoulVLi6sREZmpWcbN79248/PDD6NGjB86fPw8A+Pjjj7Fnzx6zr1FSUgKDwYDw8PAGx8PDw1FUVNTkc06ePImZM2di7dq18PAwb7jQvHnzEBgYaHpER0ebnZGInMvO34tFR7AZHVcoJjKbxcXNxo0bMXDgQHh7e+PIkSPQai9Nn6ysrMTrr79ucQBJaviXiCzLjY4BgMFgwOjRo/HKK6+gQ4cOZl9/1qxZqKioMD3y8/MtzkhEjs9glLHnZKnoGDZVpOEKxUTmsLi4ee211/Dee+/hgw8+gKenp+l4SkoKDh8+bPZ1QkNDoVQqG/XSFBcXN+rNAS4VT4cOHcKUKVPg4eEBDw8PvPrqq/jll1/g4eGBH3/8scl21Go1AgICGjyIyPXsO1UCo+gQ19HKV4WlozvD36t5E1XLqhx/LR4iR2BxcXPixAncddddjY4HBASgvLzc7OuoVCokJycjLS2twfG0tDSkpKQ0ef1ff/0VmZmZpsfEiRNx0003ITMzE3fccYelL4WIXMjGw+dER7iuUV3bYmBSBDrHBDXr+WfLqq0biMhFWfznQ2RkJE6dOoW4uLgGx/fs2YMbbrjBomvNmDEDY8aMQZcuXdCjRw+8//77yMvLw8SJEwFcuqV0/vx5rFmzBgqFAklJSQ2eHxYWBi8vr0bHicj91Ogcf+2ZpT/l4IsjBYht5dOs5395pACzhyVxYDHRdVhc3DzxxBN46qmnsHLlSkiShIKCAuzfvx/PPPMMXnrpJYuuNWrUKJSWluLVV19FYWEhkpKSsGXLFsTGxgIACgsLr7vmDRERAHSNa4Ufshx/QHFhRZ3ZG3peSVOnR3puGXq0a2XlVESuRZJl2eKJky+88AIWLFiAurpL/0DVajWeeeYZzJkzx+oBrU2j0SAwMBAVFRUcf0PkQmp1BiS8tFVI2966OmQv+AcAIGH656hV2W737nce6IQRndrY7PpEjsqS39/NGtU2d+5cvPDCC8jKyoLRaERiYiL8/PyaFZaIyBoy88tFR7CLMH/bFU5ErqLZe0v5+PigS5cu1sxCRNRsxZWuP006yMcT3eJDRMcgcnhmFTd///vfzb7gpk2bmh2GiKi53KFHo1ZnEB2ByCmYVdwEBgbaOgcRUYskxwZDgvNthmkJrd6IfadK0KtDa9FRiByaWcXNqlWrbJ2DiKhFMs5edOnC5rKNh8+xuCG6DqG7ghMRWYuIMTciVps5d7FWQKtEzsWsnpvOnTtj+/btCA4Oxu23397k3k+XWbIFAxGRtdhzzM2jPePQPzECybHBWLT9JD78/pjd2la4Rf8UUcuYVdyMGDECarUaADBy5Ehb5iEiapZu8SEI8vFEeU29zdoI8vHEv/9+KwYlRZqO9Wwfig+/t1mTjRwr1MBglLlKMdE1mFXcBAcHQ6G4dAfrkUceQdu2bU2fExG5iyUPdkbPG0MbHOsWH4KIQLXdMtTojDhwurRRDiL6k1kVyowZM6DRaAAA8fHxKCkpsWkoIiJLpeeW2bTXBgAqahtfX6mQMHPgzTZt90r7c/gzmOhazOq5iYqKwsaNGzFkyBDIsoxz586Ztl64UkxMjFUDEhGZo0hj+wHFc77NwsCkiAa3hLYcLcRr32ZhoM1b/yvekiK6FrOKm3/961+YOnUqpkyZAkmS0LVr10bnyLIMSZJgMHCRKSKyv5JKrc3bKKyow4K0E+jZvjW6xYfgza3ZWL4rF9462/YYXYkbZxJdm1nFzf/7f/8PDz74IM6ePYuOHTti27ZtaNWK/7iIyHGUVtu+uAGAxTtOY/GO0zYfvHw1wT6e6H4Df/4SXYvZe0v5+/sjKSkJq1atQs+ePU2zp4iIHEFRhfm3pRQSYGzhjGoRhQ0AjE+J50wpouuweOPMcePGAQAyMjKQnZ0NSZKQkJCAzp07Wz0cEZG52gR5m33uhDvjofZQYvGOUzZMZBsVtTrREYgcnsXzuYuLi3HPPfega9euSE1NxZQpU9ClSxf07dsXFy5csEVGIqLrSmlv/tToFbtz4al0zt6Pzw6dg6Gl3U5ELs7i4mbq1KnQaDQ4fvw4ysrKcPHiRRw7dgwajQapqam2yEhEdF3db2gFX5XSrHNlAOvS8xAR4OV0846qtHocyCkVHYPIoVlc3GzduhXLli1DQkKC6VhiYiKWLFmC7777zqrhiIgsYZTN79Eo0mjxYDfnXLpi/2kWN0TXYnFxYzQa4enp2ei4p6cnjEajVUIREVnqqfVHUFtv2c+guFAf/L+74m2UyJZ4W4roWiwubu655x489dRTKCgoMB07f/48pk+fjr59+1o1HBGRObYcLcQ3Rwstfl6orxqbf7H8eaL1uIFbLxBdi8XFzeLFi1FZWYm4uDi0a9cO7du3R3x8PCorK/Huu+/aIiMR0VUZjDL+9ZXlu3K38lUB0qWF+ZxN1/gQ0RGIHJrFU8Gjo6Nx+PBhpKWl4bfffoMsy0hMTES/fv1skY+I6JrSc8tQVm359Og5I5JQUmWfhf+s7enPjuDd0cmiYxA5LIuKG71eDy8vL2RmZqJ///7o37+/rXIREZmlOXtKPXFXPIZ0jMQ7207aIJHtfXO0CG/fb4TKw+LOdyK3YNG/DA8PD8TGxnL/KCJyGGUW9r4E+Xjin4MSYDDKWJeeZ6NUtiUD+Hj/GdExiByWxWX/v/71L8yaNQtlZWW2yENEZJEQX5VF55fX1CM9twzpuWVW20lcxFo5Z8tqBLRK5BwsHnOzaNEinDp1ClFRUYiNjYWvr2+Drx8+fNhq4YiIrifM38vi5xRXWncQsYiJ2dHBPgJaJXIOFhc3I0aMgCQ525qeROSymvHjqKRSi5sjA6yfxY5uDvcXHYHIYVlc3Lz88ss2iEFE1DzNmfE059tsBHp7QJIACxY1dihl3ECT6KrMHnNTU1ODJ598Em3atEFYWBhGjx6NkpISW2YjIrquUD91s55XUat32sIGAM6UcMwN0dWYXdzMnj0bq1evxtChQ/HAAw8gLS0NkyZNsmU2IqLrc+ICpSXWH8zj7uBEV2H2balNmzbhww8/xAMPPAAAePjhh9GzZ08YDAYolebtxEtEZG0l1c65EF9LFVbUIT23DD3atRIdhcjhmN1zk5+fj169epk+79atGzw8PBrsMUVEZG/NmS1ljhG3RdrkutZk7VlfRK7C7OLGYDBApWq4noSHhwf0er3VQxERmatbfAgiA61f4Gz/rdjq17Q2WxV2RM7O7NtSsixj/PjxUKv/HLxXV1eHiRMnNljrZtOmTdZNSER0DUqFhNnDEjHxE+uusVWldeyV2CUJSI4NFh2DyCGZXdyMGzeu0bGHH37YqmGIiJpjUFIkpve7EQucdK+o5pBl4GBuGXreGCo6CpHDMbu4WbVqlS1zEBG1yJR7bsS69HyrbangDPaevsDihqgJ3FKWiFyCUiHhpb8l2OTavirHnBH6w/E/REcgckgsbojIZQT7Nm9Bv+u5KdzX4g067eHUhWro9EbRMYgcDosbInIZ27KKbHLdw/ka3Ht7G0gQswP4tXy8/4zoCEQOh8UNEbmErccK8eHeMza7/qc/52HJ6NsRYYNp5y1xtozbMBBdicUNETk9g1HGy5uP27SN2noDVuzOwX/uuw0fP9oNQd6eNm3PXLEhPqIjEDkci3cFJyJyNIt/PIUije23YTicX4GHVvyMEF8Vymvrbd7e9UgAxvSIEx2DyOGw54aInNrWY4VYsO13u7ZZVq2za3tXc3tMIFQe/DFOdCX+qyAip2Uwypi56VfRMYTJuVDDncGJmsDihoic1uIfT6K8RvztIVHKa+uRnlsmOgaRw2FxQ0ROyWCUsXJPrugYwqXZaPo7kTNjcUNETik9twwVdXrRMRDsI3bW1FeZBbw1RXQFFjdE5JSKK8XvIeWn9oBKKfbHaGm1jremiK7AqeBE5JTC/MUvplel1aNKq4e34BzutFkokTnYc0NETulite3XtbkWldJxNmIoqRT7XhA5GhY3ROR0DEYZc77NFppBZ3CccS6HzvK2FNFfsbghIqeTnluGwgoxt2IkAEGCBxFfac/JCxxUTPQXLG6IyOmIHmPySEq80PavVK0zclAx0V+wuCEipyNqjEmAlweWjO6MKfe0R2SgFxxn1I1jzB4jchQsbojI6VysEVPcaOr0eP6LX7H4x5N4cWgCADhMgRPqpxYdgchhcCo4ETkdSRJXUpTX1mPBtpMI8vHE/7srHpt/KUT5BQfoNeGQGyIT4T03S5cuRXx8PLy8vJCcnIzdu3df9dxNmzahf//+aN26NQICAtCjRw98//33dkxLRI4gyFslOgLKa+rx/q5cvDg0Easf6Wo6HuYvJpvocUhEjkRocbNhwwZMmzYNL7zwAo4cOYJevXph8ODByMvLa/L8Xbt2oX///tiyZQsyMjLQp08fDBs2DEeOHLFzciISKcDbMTqdZQBzvs1Cl7gQ07F/DU0UkuVwHgcUE10mybIsrDPzjjvuQOfOnbFs2TLTsYSEBIwcORLz5s0z6xq33HILRo0ahZdeesms8zUaDQIDA1FRUYGAgIBm5SYisYa/uxtHz2tExzDZ8NCtuKNj7KVPqqqwNVeD5zYeRUVtw72vgnw88frIJAT7qlGkqcOFijq88+PvqNYZW5yhY5sAbJ7aq8XXIXJUlvz+Fvbnj06nQ0ZGBmbOnNng+IABA7Bv3z6zrmE0GlFZWYmQkJDrn0xELsFglHG8wHEKGwC4UNV4gLO3p0eD4ibEV4XXRiRhSMdI07H9p0utUtgAQHZRJQxGGUqFowxxJhJH2G2pkpISGAwGhIeHNzgeHh6OoqIis67x9ttvo7q6Gvfff/9Vz9FqtdBoNA0eROS8DpwuhQMtDgwAaP2XmUppx4sw6ZPDjcbAlFXrMPnTw9h6rNB0rKii1moZ6g0yDpwutdr1iJyZ8AHFV856kGXZrJkQ69atw8svv4wNGzYgLCzsqufNmzcPgYGBpkd0dHSLMxOROPtzSkRHMJEARAZ6NRhz8/p32decuDRz068wGGVsPVaIF786btU8+047zntDJJKw4iY0NBRKpbJRL01xcXGj3pwrbdiwARMmTMBnn32Gfv36XfPcWbNmoaKiwvTIz89vcXYiEskxbrtcTjF7WGKDW0FFFddeg6e8ph5PrT+CiZ8cRpVWf81zLVVQbr2eICJnJqy4UalUSE5ORlpaWoPjaWlpSElJuerz1q1bh/Hjx+PTTz/F0KFDr9uOWq1GQEBAgwcROa874m03xu7K4SqRgV5YOvp2TO/XAUHeDfeTigj0wrKHO6N/YgR+zrHsdtC3vxZe/6RmiAr2tsl1iZyN0PmUM2bMwJgxY9ClSxf06NED77//PvLy8jBx4kQAl3pdzp8/jzVr1gC4VNiMHTsW77zzDrp3727q9fH29kZgYKCw10FEdmTD8TaX544+2jMO/RMj0C0+xNQrM+We9kjPLUNxZR3C/L3QLT4EaVlFuPONH1F+oRyW7FFuqzmqHhxMTARAcHEzatQolJaW4tVXX0VhYSGSkpKwZcsWxMZemlJZWFjYYM2b5cuXQ6/X48knn8STTz5pOj5u3DisXr3a3vGJSIB1B8/a7NoyLt1u+u5YEV4Y2vB2k1IhoUe7VqbPtx4rxKRPDkMG4Cj9JZ8eOIPUvh04Y4rcnvCVsCZPnozJkyc3+bUrC5affvrJ9oGIyGEZjDK2/3bBpm3IAAor6pCeW4Ye7VrBYJQb9dgAwCtfZzncjgcXqvWm3ETuTHhxQ0RkrgOnS6HVW2ddmOvZe6oE27KK8EXmeZRV15uORwSo0bN9KxRWOOZ2B9wdnIjFDRE5EXtOA1+841STx4s0Wmw8XGC3HJYK8/cSHYFIOOHr3BARmUvcZjHWE+zjCbXSdmNikmODbXZtImfB4oaInEaQj/jdwFtCAvDqiCTobLjEcsbZiza7NpGzYHFDRE6joLxGdIRmi/zfujjFmjqbDkROyzJv+xoiV8bihoicgsEo47OMc6JjNMuTfdphz3P3YFBSJHb+XmzTtr7MLIDB6AL374hagMUNETmFxT+eRLXWIDpGs4T4qKBUSDAYZRw8Y9vbRmXVOqTnltm0DSJHx+KGiByewShj1d4zVr2mr0rZ4POIADWCfDxtsnPV5a0b0nPLUFtv+6nsnA5O7o5TwYnI4aXnlqG8tv76J1rgvYeT4aFUoKiiFmXVOoT4qZFXWo0F205atR0AmPvdb/D18rDbGj2hfmq7tEPkqFjcEJHDK9JYvyeisk4PhQJ48/sTDRbkkyTrTzkvq9Zh0ieHMa1fB+te+CqMNpyNReQMWNwQkcMrqdRa/ZovfPkrLtY07g2y5Vo66w/mISJAjSKN9V/PX3168Cx63dTapm0QOTKOuSEih3exxvrFQFOFjS1d3rPqwW4xNhnX81fbsoo5Y4rcGosbInJ4Csl1flTFhfpi2cOdERnYcJsEfy8lHkmJxchOUS1uo94o493t1h87ROQseFuKiBzeHfEhWLxDdArrCPVTo2f7UPRPjGi027hSIWHSxwet0s7iHScxte+NUCps3U9E5Hhc588hInJZChf6Bf30Z5nYeqwQSoWEHu1aYUSnNujRrhWUCglbjhZi63HrLPKnNwL7Ttlvo1EiR8KeGyJyeCVVth2Aa09/aLSY9MlhLBndGcG+KlPPzcVqHSZ/etiqbW06fA69OnBgMbkfFjdE5PC2udB+SZeH+T756eEGe0xJNuicqtLqrX9RIifA21JE5NB0eiO+Puo6xc1lV85lssUU9Nb+XMyP3BOLGyJyaB/tyxUdwWkFeatERyASgsUNETm0b44WCmu7+w0hwtq2htySStERiIRgcUNEDstglJFdqBHW/oEc595d+8cTF7iYH7klFjdE5LAO5JRCx32Smk2rl3HgdKnoGER2x+KGiBzWXq7T0mKf/HxGdAQiu2NxQ0QOq6C8VnQEp8d9psgdsbghIodVq+M6LS1Vb5Sx7yR7wMi9sLghIodkMMrYy/EiVvHfjDzREYjsisUNETmk9NwyVGkNomO4hMP55aIjENkVixsickgrdp8WHcFlVNbWi45AZFcsbojI4Ww5WoDtv10QHcNlVNQZOKiY3AqLGyJyKAajjH99dUx0DJez53cWi+Q+WNwQkUNJzy1DWTVvo1jbrC9+FR2ByG5Y3BCRQzlXVi06gksqqKjDFoH7dBHZE4sbInIoHx84KzqCy3rxq2Mce0NugcUNETkMg1HGb0VVomO4rNJqHdJznXszUCJzsLghIoeRnlsGncEoOoYwkYFeCPLxhGTDNoor62x4dSLH4CE6ABHRZUUa9/vF+/fb28Aoy8gvq4GXhwJ+3h74/ngxJAC2uIG0Zt8ZjOjUxgZXJnIcLG6IyGGUVGpFR7C7TUfO27W9jLxy1OoM8FYp7doukT3xthQROYxvjhaIjuAwbDns97Vvjtvw6kTisbghIoeg0xvxy7kK0THcwqfp+aIjENkUixsicggf7TsjOoLbkAH8bdFu0TGIbIbFDRE5hPd3WW+jzK5xwVa7lqs6VqBBVZ1edAwim2BxQ0TC1eoMuFCls8q1grw9sfax7gjy8bTK9VzZ6A/2i45AZBMsbohIuP7zf7LatR7pGQeVhwKjurS12jVd1a/nNVyxmFwSixsiEqpWZ8C5cuutb9Mu1BdbjxVi+a5cq13TVckAnlp/RHQMIqvjOjdEJNSd/95u1eulbshEgBd/tJnr26OFmH+/ESoP/q1LroPfzUQkTFWdHqU19Va9plEGyms5UNZcMjhTjVwPixsiEmbahsOiIxCA9DOloiMQWRWLGyIS5rdC7gDuCPadKhEdgciqWNwQkTCFFbWiIxCAap0Rr32dJToGkdWwuCEiIYa8sxMGzkJ2GCv25kKnN4qOQWQVLG6IyO7+tmgXsnhLyuE8899M0RGIrILFDRHZ1aOr0nGsoFJ0DJvzUSlFR7DY5l8KUasziI5B1GIsbojIbl7+6lf8eOKC6Bh2UeOkRULCS1sx91uOvyHnxpWuiMjmqur0uPutH1FSbd01bcg2Ptidi50nivFN6l1c3I+cEosbIrIZnd6IO/+9DcVVLGqcze/F1ejwr+8Q7O2BJ3q3w6N33sBCh5wGixsiaraqOj0mf5KOvacvwiADXgpAkoA6w6WVb8n5XazV499bT+DfW08AANRKINjXEz6eHpAlCT1uaIUX/3YLvJ1wjBG5LuHFzdKlS/HWW2+hsLAQt9xyCxYuXIhevXpd9fydO3dixowZOH78OKKiovDPf/4TEydOtGPiphmMMtJzy1CkqUNZlRZB3p4oq6lHaZUWR8+Vo7Zej4vV9YAERPirEd/aH/UGGT8cL4BGa4QCQIivEomRgSiprkdlnR4dwn3xcLc4lNfVo6xahxA/NUJ9Vcgu0ODg2VJUaw2QAdQbjGgT5IORt0XheGEFPvn5LIo0OlO2G1v7oK7egIraenh6KOGrUsJHpUR5jRYXKvWABLTy9cRdN4ZC6aHAiaJKFFVoIUOGj4cC1Vo9qnUG6Awy9MZLv7S8lEB8az+ktGuFnAuVyCqqRr3eiAh/NeJCvXG2tA6lNTp4KAB/tQd0eiMq6vRQKACDwYjaeiO0ehlqDwWSYwIQFeiHrD808PfyQNtgb5RV6VBQXoPyGj0qtXooJCDczxPF1XpUa/UwGAFPBeDnpURrPzUqdUYopUu/bOvq9ag3AhIAgxFQKgAftRJ+nkqU1tRDq5dhxKWve0iAryegkyUoFRIMBhkyZBhkCd4eEqKCvBHoo0JtvQGF5bWo0xvhIQGSJKFKq4feeOkaPmolIMvQ6o0wyoAsA0Zc+q+HAvDyVELCpa8rFEooFECQtyf81ArkXKiB1gAoJMBXpYBCAur+dx2lQoF2rbxRrKlDcc2fYzi8FICPSkK9EajTy6j/ywxetQLQGS8NqPNUAPVG4MrRHxIAb08JkC891/C/55veFwVM/68tUceZxC5PawCKNPUALvXG5ZbU4NP0/CbPlWDZ95ACgI8KqNU1/J5VAvDyAGr01iuaPSRA7aEAjEZUX2V4VGyQGs8OSMAn6Wfw63kNav/3D02pAJSSBAky6gx/Zg/0VkKSFPBVKyFJMgrKtQ3/bSqBIB8VUuKC8PPZChRXak3LIVz5uoK9JNQbZGgN//t5IgOeSuDmyAD06tAKmzLO42KNHp4KCR5KCUoJl87XG2GUZSgkCZ4eCgR5eSAi0AvFmlrklesgy4BKCQy5NQIl1fX4+XQpdP/7eenlIcHLU4GoQDUKK3SXfmZLgGS89H9bxqXn+qmUMMoSlAogxFeFmyL84aP2QGZeBbT1etQbZfiqPRDXyhcLRt0OPwF7vUmyLAv7A2vDhg0YM2YMli5dip49e2L58uVYsWIFsrKyEBMT0+j83NxcJCUl4fHHH8cTTzyBvXv3YvLkyVi3bh3+7//+z6w2NRoNAgMDUVFRgYCAAKu8jq3HCvHK11korLDezsZE5Dy8dXXIXvAPAEDC9M9Rq/ISnIjIcXRsG4DNU67eaWEuS35/Cy1u7rjjDnTu3BnLli0zHUtISMDIkSMxb968Ruc/99xz2Lx5M7Kzs03HJk6ciF9++QX79+83q01rFzdbjxVi0ieH2QVP5MZY3BBdmzUKHEt+fwsbHabT6ZCRkYEBAwY0OD5gwADs27evyefs37+/0fkDBw7EoUOHUF9v/wGLBqOMV77OYmFDRER0DUfPaVBVp7dbe8KKm5KSEhgMBoSHhzc4Hh4ejqKioiafU1RU1OT5er0eJSVNb/ym1Wqh0WgaPKwlPbeMt6KIiIjMMH3DEbu1JXxenyRJDT6XZbnRseud39Txy+bNm4fAwEDTIzo6uoWJ/1RcycKGiIjIHHkX7bdRrrDiJjQ0FEqlslEvTXFxcaPemcsiIiKaPN/DwwOtWrVq8jmzZs1CRUWF6ZGf3/So/uYI8+d9dSIiInPEBHvbrS1hxY1KpUJycjLS0tIaHE9LS0NKSkqTz+nRo0ej83/44Qd06dIFnp6eTT5HrVYjICCgwcNausWHIDLQC1fvZyIiIiIAWDDqdru1JfS21IwZM7BixQqsXLkS2dnZmD59OvLy8kzr1syaNQtjx441nT9x4kScPXsWM2bMQHZ2NlauXIkPP/wQzzzzjJD8SoWE2cMShbRNRETkLDq2DbDrejdCF/EbNWoUSktL8eqrr6KwsBBJSUnYsmULYmNjAQCFhYXIy8sznR8fH48tW7Zg+vTpWLJkCaKiorBo0SKz17ixhUFJkVj2cGeuc0NERNQEa61zYwmh69yIYItF/ACuUMwVit13hWK14tKTDMZLq6jKuLSirEICFAoJKg8FdHqDaSVXpQQEeyvho/aAwQjojTK8PBVoH+aHrnGtYNDL+PKXcyiproePpwIB3p7w9lQiPFCNEwUaFGi0MMqAWinBW6XEjWF+eKxXO6g8lCip1iLEW4WsIg0OnilDXb0BSVGBCPFVoaK2HvVGIw6cKsbvxTWQZSDY1wMR/l7wUCrRLtwPtXV6FGi0iAr0gpenAkfyLqJKa0B8a1+M6xKL//5yDr8VVUKhACRZhl6WEOanQkqkN579R1cAwMIvMqBT+6C8VocLlVr4qj2QGBmA1v7qS+P0JOCPijr8nFuCPadKoa03QKWU4OGhgEqpgJ/aA2VVWpTX6RHi44nu7UIRE+yDw3kXcb6iFmWVtbhQbYBRvvT/WKUAwgK9cEOoL0qqdZf+HxiNqK03wMtDgSKNFpo6A4wAvJQSDEYZ9X/5H+ujBAJ9Vais0ZlWAPZQAK19lLhQa4TBIEPtIcFPBehlJTwVgBESyqrrcb0FqblCMVcotuYKxU6ziJ8ItipuiMiNVVcDfn6XPq6qAnx9xeYhckFOsYgfERERkS2wuCEiIiKXwuKGiIiIXAqLGyIiInIpLG6IiIjIpbC4ISIiIpfC4oaIiIhcCosbIiIiciksboiIiMilCN1bSoTLCzJrNBrBSYjIZVRX//mxRgMYrrKePxE12+Xf2+ZsrOB2xU1lZSUAIDo6WnASInJJUVGiExC5tMrKSgQGBl7zHLfbW8poNKKgoAD+/v6QJMlq19VoNIiOjkZ+fj73rDID3y/z8b0yH98r8/G9sgzfL/PZ6r2SZRmVlZWIioqCQnHtUTVu13OjUCjQtm1bm10/ICCA3/gW4PtlPr5X5uN7ZT6+V5bh+2U+W7xX1+uxuYwDiomIiMilsLghIiIil8LixkrUajVmz54NtVotOopT4PtlPr5X5uN7ZT6+V5bh+2U+R3iv3G5AMREREbk29twQERGRS2FxQ0RERC6FxQ0RERG5FBY3NjJ8+HDExMTAy8sLkZGRGDNmDAoKCkTHcjhnzpzBhAkTEB8fD29vb7Rr1w6zZ8+GTqcTHc0hzZ07FykpKfDx8UFQUJDoOA5n6dKliI+Ph5eXF5KTk7F7927RkRzSrl27MGzYMERFRUGSJHz55ZeiIzmkefPmoWvXrvD390dYWBhGjhyJEydOiI7lsJYtW4aOHTua1rfp0aMHvvvuOyFZWNzYSJ8+ffDZZ5/hxIkT2LhxI06fPo1//OMfomM5nN9++w1GoxHLly/H8ePHsWDBArz33nt4/vnnRUdzSDqdDvfddx8mTZokOorD2bBhA6ZNm4YXXngBR44cQa9evTB48GDk5eWJjuZwqqurcdttt2Hx4sWiozi0nTt34sknn8SBAweQlpYGvV6PAQMGoPqve4mRSdu2bfHvf/8bhw4dwqFDh3DPPfdgxIgROH78uN2zcLaUnWzevBkjR46EVquFp6en6DgO7a233sKyZcuQk5MjOorDWr16NaZNm4by8nLRURzGHXfcgc6dO2PZsmWmYwkJCRg5ciTmzZsnMJljkyQJX3zxBUaOHCk6isO7cOECwsLCsHPnTtx1112i4ziFkJAQvPXWW5gwYYJd22XPjR2UlZVh7dq1SElJYWFjhoqKCoSEhIiOQU5Ep9MhIyMDAwYMaHB8wIAB2Ldvn6BU5GoqKioAgD+fzGAwGLB+/XpUV1ejR48edm+fxY0NPffcc/D19UWrVq2Ql5eHr776SnQkh3f69Gm8++67mDhxougo5ERKSkpgMBgQHh7e4Hh4eDiKiooEpSJXIssyZsyYgTvvvBNJSUmi4zisX3/9FX5+flCr1Zg4cSK++OILJCYm2j0HixsLvPzyy5Ak6ZqPQ4cOmc5/9tlnceTIEfzwww9QKpUYO3Ys3OUuoKXvFQAUFBRg0KBBuO+++/DYY48JSm5/zXmvqGmSJDX4XJblRseImmPKlCk4evQo1q1bJzqKQ7vpppuQmZmJAwcOYNKkSRg3bhyysrLsnsPtdgVviSlTpuCBBx645jlxcXGmj0NDQxEaGooOHTogISEB0dHROHDggJAuOnuz9L0qKChAnz590KNHD7z//vs2TudYLH2vqLHQ0FAolcpGvTTFxcWNenOILDV16lRs3rwZu3btQtu2bUXHcWgqlQrt27cHAHTp0gUHDx7EO++8g+XLl9s1B4sbC1wuVprjco+NVqu1ZiSHZcl7df78efTp0wfJyclYtWoVFAr36lBsyfcVXaJSqZCcnIy0tDTce++9puNpaWkYMWKEwGTkzGRZxtSpU/HFF1/gp59+Qnx8vOhITkeWZSG/91jc2EB6ejrS09Nx5513Ijg4GDk5OXjppZfQrl07t+i1sURBQQHuvvtuxMTE4D//+Q8uXLhg+lpERITAZI4pLy8PZWVlyMvLg8FgQGZmJgCgffv28PPzExtOsBkzZmDMmDHo0qWLqQcwLy+P47eaUFVVhVOnTpk+z83NRWZmJkJCQhATEyMwmWN58skn8emnn+Krr76Cv7+/qWcwMDAQ3t7egtM5nueffx6DBw9GdHQ0KisrsX79evz000/YunWr/cPIZHVHjx6V+/TpI4eEhMhqtVqOi4uTJ06cKJ87d050NIezatUqGUCTD2ps3LhxTb5XO3bsEB3NISxZskSOjY2VVSqV3LlzZ3nnzp2iIzmkHTt2NPl9NG7cONHRHMrVfjatWrVKdDSH9Oijj5r+/bVu3Vru27ev/MMPPwjJwnVuiIiIyKW41+AGIiIicnksboiIiMilsLghIiIil8LihoiIiFwKixsiIiJyKSxuiIiIyKWwuCEiIiKXwuKGiIiIXAqLGyJyKXFxcVi4cKHoGEQkEIsbIrqu8ePHQ5IkSJIEDw8PxMTEYNKkSbh48aJVrn/52pIkwdfXFzfeeCPGjx+PjIwMq1z7yy+/bNZzT506hUceeQRt27aFWq1GfHw8HnzwQRw6dMh0zty5c5GSkgIfHx8EBQU1eZ28vDwMGzYMvr6+CA0NRWpqKnQ6XbMyEdH1sbghIrMMGjQIhYWFOHPmDFasWIGvv/4akydPttr1V61ahcLCQhw/fhxLlixBVVUV7rjjDqxZs8ZqbVji0KFDSE5Oxu+//47ly5cjKysLX3zxBW6++WY8/fTTpvN0Oh3uu+8+TJo0qcnrGAwGDB06FNXV1dizZw/Wr1+PjRs3NrgGEVmZkB2tiMipjBs3Th4xYkSDYzNmzJBDQkJMn69cuVK++eabZbVaLd90003ykiVLzL4+APmLL75odHzs2LGyv7+/XFZWZjq2d+9euVevXrKXl5fctm1beerUqXJVVZXp67GxsfKCBQtMH+MvGx7GxsbKsizLp06dkocPHy6HhYXJvr6+cpcuXeS0tDTTNYxGo3zLLbfIycnJssFgaJTr4sWLjY6tWrVKDgwMbHR8y5YtskKhkM+fP286tm7dOlmtVssVFRXXeWeIqDnYc0NEFsvJycHWrVvh6ekJAPjggw/wwgsvYO7cucjOzsbrr7+OF198ER999FGL2pk+fToqKyuRlpYGAPj1118xcOBA/P3vf8fRo0exYcMG7NmzB1OmTGny+QcPHgTwZ6/Q5c+rqqowZMgQbNu2DUeOHMHAgQMxbNgw5OXlAQAyMzNx/PhxPP3001AoGv+YvNrtp6bs378fSUlJiIqKMh0bOHAgtFqtVW67EVFjHqIDEJFz+Oabb+Dn5weDwYC6ujoAwPz58wEAc+bMwdtvv42///3vAID4+HhkZWVh+fLlGDduXLPbvPnmmwEAZ86cAQC89dZbGD16NKZNmwYAuPHGG7Fo0SL07t0by5Ytg5eXV4Pnt27dGsClYiQiIsJ0/LbbbsNtt91m+vy1117DF198gc2bN2PKlCk4efJkg/ZboqioCOHh4Q2OBQcHQ6VSoaioqMXXJ6LGWNwQkVn69OmDZcuWoaamBitWrMDvv/+OqVOn4sKFC8jPz8eECRPw+OOPm87X6/UIDAxsUZuyLAO4NCgYADIyMnDq1CmsXbu2wTlGoxG5ublISEgw67rV1dV45ZVX8M0336CgoAB6vR61tbWmnpsr222ppq4jy7LVrk9EDbG4ISKz+Pr6on379gCARYsWoU+fPnjllVdMt4Q++OAD3HHHHQ2eo1QqW9RmdnY2gEs9QQBgNBrxxBNPIDU1tdG5MTExZl/32Wefxffff4///Oc/aN++Pby9vfGPf/zDNIOpQ4cOpvY7derUotcQERGBn3/+ucGxixcvor6+vlGPDhFZB4sbImqW2bNnY/DgwZg0aRLatGmDnJwcPPTQQ1ZtY+HChQgICEC/fv0AAJ07d8bx48dNRZY5PD09YTAYGhzbvXs3xo8fj3vvvRfApTE4l299AUCnTp2QmJiIt99+G6NGjWo07qa8vNzscTc9evTA3LlzUVhYiMjISADADz/8ALVajeTkZLNfBxGZj8UNETXL3XffjVtuuQWvv/46Xn75ZaSmpiIgIACDBw+GVqvFoUOHcPHiRcyYMcOs65WXl6OoqAhardY0/frLL7/EmjVrTIXEc889h+7du+PJJ5/E448/Dl9fX2RnZyMtLQ3vvvtuk9eNi4vD9u3b0bNnT6jVagQHB6N9+/bYtGkThg0bBkmS8OKLL8JoNJqeI0kSVq1ahX79+uGuu+7C888/j5tvvhlVVVX4+uuv8cMPP2Dnzp0ALq1hU1ZWhry8PBgMBmRmZgIA2rdvDz8/PwwYMACJiYkYM2YM3nrrLZSVleGZZ57B448/joCAgOb/DyCiqxM7WYuInEFTU8FlWZbXrl0rq1QqOS8vT167dq3cqVMnWaVSycHBwfJdd90lb9q0yazr4y/Ttb28vOR27drJ48aNkzMyMhqdm56eLvfv31/28/OTfX195Y4dO8pz5841ff2vU8FlWZY3b94st2/fXvbw8DBNBc/NzZX79Okje3t7y9HR0fLixYvl3r17y0899VSDtk6cOCGPHTtWjoqKklUqlRwbGys/+OCD8uHDhxu8N3/Nf/mxY8cO0zlnz56Vhw4dKnt7e8shISHylClT5Lq6OrPeGyKynCTL/xs5R0REROQCuM4NERERuRQWN0RkU6+//jr8/PyafAwePFh0PCJyQbwtRUQ2VVZWhrKysia/5u3tjTZt2tg5ERG5OhY3RERE5FJ4W4qIiIhcCosbIiIiciksboiIiMilsLghIiIil8LihoiIiFwKixsiIiJyKSxuiIiIyKWwuCEiIiKX8v8BI9XcsVxPPb4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(x=validlogs[\"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"],\n",
    "           y=validlogs[\"ProfLikeRatio\"]\n",
    "           )\n",
    "ax.axvline(x=validlogs.loc[ validlogs['ProfLikeRatio'].idxmax(),\n",
    "                           \"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"],\n",
    "                            c='r',\n",
    "                            label = 'Max Loglike')\n",
    "ax.set_xlabel('Re_DeltaC10')\n",
    "ax.set_ylabel('Profile likelihood ratio')\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this plot, we can see that one value of `Re_DeltaC10` can bring multiple different likelihood values. This is because we are also scanning `Re_DeltaC7`, so we're looking at a 1D projection. Let's plot the profile likelihood for both parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x12ed3b9a0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Create a meshgrid for contour plot\n",
    "x = validlogs[\"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"]\n",
    "y = validlogs[\"#WC_parameters @WC::primary_parameters::Re_DeltaC7\"]\n",
    "z = validlogs[\"ProfLikeRatio\"]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# plot all points\n",
    "t = ax.scatter(x, y, c=z)\n",
    "# make contour plot\n",
    "ax.tricontour(x, y, z, levels=3, linewidths=1., colors='w')\n",
    "# add marker for best fit point\n",
    "ax.scatter(x=validlogs.loc[ validlogs['ProfLikeRatio'].idxmax(), \"#WC_parameters @WC::primary_parameters::Re_DeltaC10\"],\n",
    "           y=validlogs.loc[ validlogs['ProfLikeRatio'].idxmax(), \"#WC_parameters @WC::primary_parameters::Re_DeltaC7\"],\n",
    "           c='r',\n",
    "           s=10,\n",
    "           label='best fit point'\n",
    "           )\n",
    "\n",
    "\n",
    "ax.set_xlabel('Re_DeltaC7')\n",
    "ax.set_ylabel('Re_DeltaC10')\n",
    "fig.colorbar(t, label='Profile likelihood ratio')\n",
    "fig.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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