{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e1dfc1f4",
   "metadata": {},
   "source": [
    "# $\\mathrm{Co_3O_4}$  Project EQCM"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cdbac84",
   "metadata": {},
   "source": [
    "## Analyze EQCM Data and Model the Anodic Current Shape + Mass per Transferred Electron Profiles"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c4fcfbb",
   "metadata": {},
   "source": [
    "### Load EQCM Data and Pstat Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "07b2f521",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/leppin/Documents/SYNC/People/Christian/Electroresponsivity_Co3O4/Folder_For_DataBase/FastEQCM-D/SmallLoadingRepeat4/pristine/2025-06-16 CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1/CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1_dfc_by_n.txt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1699: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return math.isfinite(val)\n",
      "/opt/homebrew/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1345: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return np.asarray(x, float)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "66b6536ccb934c188237f794722be5a3",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' 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       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3993821204.py:46: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data = pd.read_csv(master_fname, skiprows = 0, delimiter = \"\\t\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   flags      time/s  control/V     Ewe/V    <I>/mA  cycle number  \\\n",
      "0     22  347.444591   0.099981  0.099663  0.001343           1.0   \n",
      "1     22  347.554591   0.100530  0.100190  0.000523           1.0   \n",
      "2     22  347.754491   0.101530  0.101217  0.000539           1.0   \n",
      "3      6  347.954391   0.102529  0.102226  0.000545           1.0   \n",
      "4     22  348.154291   0.103529  0.103236  0.000564           1.0   \n",
      "\n",
      "       (Q-Qo)/C  I Range   Rcmp/Ohm  \n",
      "0  0.000000e+00       40  10.199999  \n",
      "1  1.050036e-07       40  10.199995  \n",
      "2  3.003250e-07       40  10.199995  \n",
      "3  5.014687e-07       40  10.199995  \n",
      "4  7.043355e-07       40  10.199996  \n",
      "B\n",
      "/Users/leppin/Documents/SYNC/People/Christian/Electroresponsivity_Co3O4/Folder_For_DataBase/FastEQCM-D/SmallLoadingRepeat4/after_1930mV/2025-06-17 CL20250617_001_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_1p0V_MSE_eq_1p93V_RHEseq1/CL20250617_001_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_1p0V_MSE_eq_1p93V_RHE_seq1_dfc_by_n.txt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1699: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return math.isfinite(val)\n",
      "/opt/homebrew/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1345: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return np.asarray(x, float)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dbc8552ea34f4de4827ee33fa7b9f2f6",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3993821204.py:46: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data = pd.read_csv(master_fname, skiprows = 0, delimiter = \"\\t\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   flags     time/s  control/V     Ewe/V    <I>/mA  cycle number  \\\n",
      "0     22  376.74979   0.099976  0.099603  0.006317           1.0   \n",
      "1     22  376.85979   0.100526  0.100173  0.005683           1.0   \n",
      "2     22  377.05969   0.101525  0.101155  0.005627           1.0   \n",
      "3      6  377.25959   0.102525  0.102166  0.005661           1.0   \n",
      "4     22  377.45949   0.103524  0.103175  0.005672           1.0   \n",
      "\n",
      "       (Q-Qo)/C  I Range   Rcmp/Ohm  \n",
      "0  0.000000e+00       40  10.199999  \n",
      "1  6.758066e-07       40  10.199995  \n",
      "2  1.888296e-06       40  10.199995  \n",
      "3  3.100557e-06       40  10.199995  \n",
      "4  4.312209e-06       40  10.199996  \n",
      "B\n",
      "/Users/leppin/Documents/SYNC/People/Christian/Electroresponsivity_Co3O4/Folder_For_DataBase/FastEQCM-D/SmallLoadingRepeat4/after_1730mV/2025-06-16 CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1/CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1_dfc_by_n.txt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1699: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return math.isfinite(val)\n",
      "/opt/homebrew/anaconda3/lib/python3.12/site-packages/matplotlib/cbook.py:1345: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return np.asarray(x, float)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a4e13ca117364938808faacc1cc5fad9",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' 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       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3993821204.py:46: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data = pd.read_csv(master_fname, skiprows = 0, delimiter = \"\\t\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   flags     time/s  control/V     Ewe/V    <I>/mA  cycle number  \\\n",
      "0      6  383.43179   0.099952  0.099610  0.004874           1.0   \n",
      "1      6  383.54179   0.100502  0.100162  0.004314           1.0   \n",
      "2     22  383.74169   0.101501  0.101181  0.004275           1.0   \n",
      "3     22  383.94159   0.102501  0.102160  0.004299           1.0   \n",
      "4     22  384.14149   0.103500  0.103173  0.004297           1.0   \n",
      "\n",
      "       (Q-Qo)/C  I Range   Rcmp/Ohm  \n",
      "0  0.000000e+00       40  10.199999  \n",
      "1  5.121120e-07       40  10.199995  \n",
      "2  1.434043e-06       40  10.199995  \n",
      "3  2.354975e-06       40  10.199995  \n",
      "4  3.276124e-06       40  10.199996  \n",
      "B\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time (s)</th>\n",
       "      <th>cycle</th>\n",
       "      <th>potential (V)</th>\n",
       "      <th>current (mA)</th>\n",
       "      <th>df/n 3 (Hz)</th>\n",
       "      <th>dG/n 3 (Hz)</th>\n",
       "      <th>df/n 5 (Hz)</th>\n",
       "      <th>dG/n 5 (Hz)</th>\n",
       "      <th>df/n 7 (Hz)</th>\n",
       "      <th>dG/n 7 (Hz)</th>\n",
       "      <th>df/n 9 (Hz)</th>\n",
       "      <th>dG/n 9 (Hz)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fname</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>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1_05_CV_C01.mpr</th>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.099663</td>\n",
       "      <td>0.001343</td>\n",
       "      <td>7.826193</td>\n",
       "      <td>-4.057380</td>\n",
       "      <td>5.409493</td>\n",
       "      <td>-3.547316</td>\n",
       "      <td>3.313979</td>\n",
       "      <td>-2.209374</td>\n",
       "      <td>2.338771</td>\n",
       "      <td>-0.373380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1_05_CV_C01.mpr</th>\n",
       "      <td>0.02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.099759</td>\n",
       "      <td>0.001194</td>\n",
       "      <td>7.827216</td>\n",
       "      <td>-4.052558</td>\n",
       "      <td>5.409419</td>\n",
       "      <td>-3.552090</td>\n",
       "      <td>3.315482</td>\n",
       "      <td>-2.206367</td>\n",
       "      <td>2.341522</td>\n",
       "      <td>-0.372834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1_05_CV_C01.mpr</th>\n",
       "      <td>0.04</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.099855</td>\n",
       "      <td>0.001045</td>\n",
       "      <td>7.826109</td>\n",
       "      <td>-4.052185</td>\n",
       "      <td>5.413488</td>\n",
       "      <td>-3.555189</td>\n",
       "      <td>3.315500</td>\n",
       "      <td>-2.205362</td>\n",
       "      <td>2.341467</td>\n",
       "      <td>-0.372347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1_05_CV_C01.mpr</th>\n",
       "      <td>0.06</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.099951</td>\n",
       "      <td>0.000896</td>\n",
       "      <td>7.825959</td>\n",
       "      <td>-4.053920</td>\n",
       "      <td>5.415014</td>\n",
       "      <td>-3.555546</td>\n",
       "      <td>3.320772</td>\n",
       "      <td>-2.203898</td>\n",
       "      <td>2.340575</td>\n",
       "      <td>-0.373041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_seq1_05_CV_C01.mpr</th>\n",
       "      <td>0.08</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.100046</td>\n",
       "      <td>0.000747</td>\n",
       "      <td>7.825414</td>\n",
       "      <td>-4.058414</td>\n",
       "      <td>5.414339</td>\n",
       "      <td>-3.551727</td>\n",
       "      <td>3.321379</td>\n",
       "      <td>-2.199409</td>\n",
       "      <td>2.342829</td>\n",
       "      <td>-0.373292</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1_05_CV_C01.mpr</th>\n",
       "      <td>1300.36</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.100280</td>\n",
       "      <td>-0.004678</td>\n",
       "      <td>5.653582</td>\n",
       "      <td>2.191772</td>\n",
       "      <td>4.889552</td>\n",
       "      <td>0.898783</td>\n",
       "      <td>3.457220</td>\n",
       "      <td>0.930342</td>\n",
       "      <td>1.267458</td>\n",
       "      <td>2.783443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1_05_CV_C01.mpr</th>\n",
       "      <td>1300.38</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.100177</td>\n",
       "      <td>-0.004670</td>\n",
       "      <td>5.654773</td>\n",
       "      <td>2.191437</td>\n",
       "      <td>4.887597</td>\n",
       "      <td>0.898933</td>\n",
       "      <td>3.455297</td>\n",
       "      <td>0.929887</td>\n",
       "      <td>1.266482</td>\n",
       "      <td>2.781992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1_05_CV_C01.mpr</th>\n",
       "      <td>1300.40</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.100073</td>\n",
       "      <td>-0.004662</td>\n",
       "      <td>5.656745</td>\n",
       "      <td>2.192022</td>\n",
       "      <td>4.886552</td>\n",
       "      <td>0.903915</td>\n",
       "      <td>3.458903</td>\n",
       "      <td>0.926533</td>\n",
       "      <td>1.266993</td>\n",
       "      <td>2.780718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1_05_CV_C01.mpr</th>\n",
       "      <td>1300.42</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.099970</td>\n",
       "      <td>-0.004654</td>\n",
       "      <td>5.653910</td>\n",
       "      <td>2.188616</td>\n",
       "      <td>4.888818</td>\n",
       "      <td>0.908662</td>\n",
       "      <td>3.458443</td>\n",
       "      <td>0.922935</td>\n",
       "      <td>1.267225</td>\n",
       "      <td>2.780397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA_1h_at_0p8V_MSE_eq_1p73V_RHE_seq1_05_CV_C01.mpr</th>\n",
       "      <td>1300.44</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.099866</td>\n",
       "      <td>-0.004646</td>\n",
       "      <td>5.651496</td>\n",
       "      <td>2.195009</td>\n",
       "      <td>4.885380</td>\n",
       "      <td>0.908669</td>\n",
       "      <td>3.454114</td>\n",
       "      <td>0.925120</td>\n",
       "      <td>1.264227</td>\n",
       "      <td>2.779672</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>195071 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    time (s)  cycle  \\\n",
       "fname                                                                 \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.00    1.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.02    1.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.04    1.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.06    1.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.08    1.0   \n",
       "...                                                      ...    ...   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...   1300.36    5.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...   1300.38    5.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...   1300.40    5.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...   1300.42    5.0   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...   1300.44    5.0   \n",
       "\n",
       "                                                    potential (V)  \\\n",
       "fname                                                               \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...       0.099663   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...       0.099759   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...       0.099855   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...       0.099951   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...       0.100046   \n",
       "...                                                           ...   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...       0.100280   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...       0.100177   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...       0.100073   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...       0.099970   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...       0.099866   \n",
       "\n",
       "                                                    current (mA)  df/n 3 (Hz)  \\\n",
       "fname                                                                           \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.001343     7.826193   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.001194     7.827216   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.001045     7.826109   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.000896     7.825959   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...      0.000747     7.825414   \n",
       "...                                                          ...          ...   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     -0.004678     5.653582   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     -0.004670     5.654773   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     -0.004662     5.656745   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     -0.004654     5.653910   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     -0.004646     5.651496   \n",
       "\n",
       "                                                    dG/n 3 (Hz)  df/n 5 (Hz)  \\\n",
       "fname                                                                          \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -4.057380     5.409493   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -4.052558     5.409419   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -4.052185     5.413488   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -4.053920     5.415014   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -4.058414     5.414339   \n",
       "...                                                         ...          ...   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.191772     4.889552   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.191437     4.887597   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.192022     4.886552   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.188616     4.888818   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.195009     4.885380   \n",
       "\n",
       "                                                    dG/n 5 (Hz)  df/n 7 (Hz)  \\\n",
       "fname                                                                          \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -3.547316     3.313979   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -3.552090     3.315482   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -3.555189     3.315500   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -3.555546     3.320772   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -3.551727     3.321379   \n",
       "...                                                         ...          ...   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.898783     3.457220   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.898933     3.455297   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.903915     3.458903   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.908662     3.458443   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.908669     3.454114   \n",
       "\n",
       "                                                    dG/n 7 (Hz)  df/n 9 (Hz)  \\\n",
       "fname                                                                          \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -2.209374     2.338771   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -2.206367     2.341522   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -2.205362     2.341467   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -2.203898     2.340575   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -2.199409     2.342829   \n",
       "...                                                         ...          ...   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.930342     1.267458   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.929887     1.266482   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.926533     1.266993   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.922935     1.267225   \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     0.925120     1.264227   \n",
       "\n",
       "                                                    dG/n 9 (Hz)  \n",
       "fname                                                            \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -0.373380  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -0.372834  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -0.372347  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -0.373041  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_initial_...    -0.373292  \n",
       "...                                                         ...  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.783443  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.781992  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.780718  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.780397  \n",
       "CL20250616_003_#18_Co3O4Nps_CV_5mVpers_after_CA...     2.779672  \n",
       "\n",
       "[195071 rows x 12 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy.optimize import curve_fit\n",
    "from numba import jit\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib widget\n",
    "from scipy import interpolate\n",
    "from galvani import BioLogic\n",
    "from scipy import stats\n",
    "from scipy.signal import savgol_filter\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def load_data_pstat_binary(master_fname: str) -> tuple[np.ndarray[float], np.ndarray[float], np.ndarray[float]]:\n",
    "    mpr_file = BioLogic.MPRfile(master_fname)\n",
    "    data = pd.DataFrame(mpr_file.data)\n",
    "    print(data.head())\n",
    "    data.to_csv(f'{master_fname[:-4]}.txt', sep = '\\t')\n",
    "    #data = np.array(data)\n",
    "    voltage    = pd.Series(data['Ewe/V']); \n",
    "    current    = pd.Series(data['<I>/mA'])\n",
    "    time          = pd.Series(data['time/s']- data['time/s'].iloc[0])\n",
    "    cycle      = pd.Series(data['cycle number'])\n",
    "    fnames     = pd.Series(np.full(np.shape(time), os.path.basename(master_fname)))\n",
    "    return time, voltage, current, cycle, fnames\n",
    "\n",
    "def discard_points(y: np.ndarray[float], trsh: int) -> np.ndarray[float]: \n",
    "    y[np.abs(y)>trsh]=np.nan\n",
    "    y = pd.Series(y).interpolate().to_numpy()\n",
    "    return y\n",
    "\n",
    "\n",
    "\n",
    "def load_QCM_data(master_fname: str) -> np.ndarray[float]:\n",
    "    data = pd.read_csv(master_fname, skiprows = 0, delimiter = \"\\t\")\n",
    "    data = np.array(data)\n",
    "    time = data[:,0]/1000\n",
    "    dfc_by_n = np.zeros((np.shape(data)[0], (np.shape(data)[1]-1)//2), dtype = complex)\n",
    "    dfc_by_n.real = data[:, 1::2]\n",
    "    dfc_by_n.imag = data[:, 2::2]\n",
    "    return time, dfc_by_n\n",
    "\n",
    "def load_trigger_data(master_fname: str) -> np.ndarray[float]: \n",
    "    data = pd.read_csv(master_fname, skiprows = 0, delimiter = \"\\t\")\n",
    "    trigger = np.array(data)[:,-1]\n",
    "    return trigger \n",
    "\n",
    "def interpol(old_x: np.ndarray[float], old_y: np.ndarray[float], new_x: np.ndarray[float]) -> np.ndarray[float]:\n",
    "    f = interpolate.interp1d(old_x, old_y, fill_value = 'extrapolate')\n",
    "    new_y = f(new_x)\n",
    "    return new_y\n",
    "\n",
    "def correct_drift(x: np.ndarray[float], y: np.ndarray[float], positions: np.ndarray[int])-> np.ndarray[float]:\n",
    "    print('positions: ', y[positions])\n",
    "    slope, intercept, r_value, p_value, std_err = stats.linregress(x[positions],y[positions].real)\n",
    "    y.real = y.real - slope*x\n",
    "    f_drift = slope*x\n",
    "    print('slope: ', slope)\n",
    "    slope, intercept, r_value, p_value, std_err = stats.linregress(x[positions],y[positions].imag)\n",
    "    y.imag = y.imag - slope*x \n",
    "    return y, f_drift + 1j*slope*x\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "AllEQCMData = pd.DataFrame()\n",
    "EQCM_files = []\n",
    "PSTAT_files = []\n",
    "TRIGGER_files = []\n",
    "root = os.getcwd()\n",
    "###Put it in the fodler Fast EQCM-D -> Small_Loading_Repeat4\n",
    "if __name__ == \"__main__\":\n",
    "    for dirpath, dirnames, filenames in os.walk(root):\n",
    "        for file in filenames:\n",
    "            if file.endswith('.mpr') and file.__contains__('05_CV_C') and file.__contains__('seq1'):\n",
    "                PSTAT_files.append(os.path.join(dirpath, file))\n",
    "            if file.endswith('.txt') and file.__contains__('_dfc'):#eqcm\n",
    "                EQCM_files.append(os.path.join(dirpath, file))\n",
    "            if file.endswith('.txt') and file.__contains__('ResonaceCurves_1'):#trigger\n",
    "                TRIGGER_files.append(os.path.join(dirpath, file))\n",
    "    \n",
    "    ####check here\n",
    "    for i_file, (EQCM_file, PSTAT_file, TRIGGER_file) in enumerate(zip(EQCM_files, PSTAT_files, TRIGGER_files)): \n",
    "        print(EQCM_file)\n",
    "        time, dfc_by_n = load_QCM_data(master_fname =EQCM_file)\n",
    "        n_ovt = len(dfc_by_n[0,:])\n",
    "        ns = np.array([3, 5, 7, 9, 11, 13])\n",
    "        for iovt in range(n_ovt):\n",
    "            dfc_by_n[:,iovt] = discard_points(dfc_by_n[:,iovt], 150)\n",
    "            dfc_by_n.real[:,iovt] = savgol_filter(dfc_by_n.real[:,iovt], window_length = 53, polyorder = 1 )\n",
    "            dfc_by_n.imag[:,iovt] = savgol_filter(dfc_by_n.imag[:,iovt], window_length = 53, polyorder = 1 )\n",
    "        fig, ax = plt.subplots()\n",
    "        plt.plot(time, dfc_by_n); plt.show()\n",
    "        trigger = load_trigger_data(master_fname = TRIGGER_file)\n",
    "        i_Trigs = np.zeros(0, dtype = int)\t# finds data points, where the trigger signal jumps\n",
    "        for i in range(2,len(trigger)-1):\n",
    "            if (trigger[i]-trigger[i-1] > 0.5) and \\\n",
    "            (trigger[i]-trigger[i-1] > trigger[i-1]-trigger[i-2]) and \\\n",
    "            (trigger[i]-trigger[i-1] > trigger[i+1]-trigger[i]) :\n",
    "                i_Trigs = np.append(i_Trigs,i)\n",
    "\n",
    "        time -= time[i_Trigs[0]]\n",
    "        time = time[i_Trigs[0]:]\n",
    "        dfc_by_n = dfc_by_n[i_Trigs[0]:, :]\n",
    "        i_Trigs -= i_Trigs[0]\n",
    "\n",
    "        time_iv, voltage, current, cycle, fnames = load_data_pstat_binary(PSTAT_file)\n",
    "\n",
    "        if time_iv.iloc[-1] > time[-1]:\n",
    "            print('A')\n",
    "            i_end_time =  np.argmin(np.abs(time_iv-time[-1]))\n",
    "            time_iv = time_iv[:i_end_time]\n",
    "            voltage = voltage[:i_end_time]\n",
    "            current = current[:i_end_time]\n",
    "            cycle = cycle[:i_end_time]\n",
    "            #print(time_iv)\n",
    "        elif time[-1] > time_iv.iloc[-1]:\n",
    "            print('B')\n",
    "            i_end_time =  np.argmin(np.abs(time-time_iv.iloc[-1]))\n",
    "            time= time[:i_end_time]\n",
    "            dfc_by_n= dfc_by_n[:i_end_time, :]\n",
    "\n",
    "        voltage_dfG = interpol(old_x = time_iv, old_y = voltage, new_x = time)\n",
    "        current_dfG = interpol(old_x = time_iv, old_y = current, new_x = time)\n",
    "        cycle_dfG   = interpol(old_x = time_iv, old_y = cycle,   new_x = time)\n",
    "\n",
    "        #construc a data frame usinf pandas data structures. \n",
    "        EQCMData = {'time (s)': time, \n",
    "                    'cycle':    cycle_dfG,\n",
    "                    'potential (V)': voltage_dfG, \n",
    "                    'current (mA)': current_dfG, \n",
    "                    'fname': np.full(np.shape(time), fnames[0])}\n",
    "        for i_ovt in range(n_ovt): \n",
    "            EQCMData[f'df/n {ns[i_ovt]} (Hz)'] = dfc_by_n[:, i_ovt].real\n",
    "            EQCMData[f'dG/n {ns[i_ovt]} (Hz)'] = dfc_by_n[:, i_ovt].imag\n",
    "        EQCMData = pd.DataFrame(EQCMData)\n",
    "        AllEQCMData = pd.concat([AllEQCMData, EQCMData])\n",
    "    AllEQCMData_indexed = AllEQCMData.set_index(['fname'])\n",
    "    #AllEQCMData_indexed = AllEQCMData_indexed.sort_index()\n",
    "AllEQCMData_indexed"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "448a2334",
   "metadata": {},
   "source": [
    "## Plot of the Single Measurement as Figure 1 (Left)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0687f0c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:77: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:77: SyntaxWarning: invalid escape sequence '\\m'\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/2274702176.py:77: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  ax2.set_ylabel('$\\mathrm{mass_{geo}}$ ($\\mathrm{\\mu g \\ cm^{-2}}$)', fontsize=7)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8a2625feeb074b178e0af9882560e2c7",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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0oIgbu7G7fNhquzs+ev/3+P3Y7X4cDjcOB1Onv+Ohx4nM5/vO5/Lp3r7urC3d2Np7v7H3/9r3kDYh64OjpwdXTQUV0dsm7G1FSy588ne948cubPJ2vuXIxRyPjSrxAOHTpEqCxwg8Xj8ZCZmYnT6ZQdNFUqlZzuTq/XYzabATh69Cg73n+fzmefxeNwMP7GG7l540Z0JtOFfLaQqFQq9HFx6OPiiBui4WWo+LxePHY77q4unFbrP1qmc+foOHMGa1UV7adPYz19ms6aGhytrVS9/z5V778vXyN1yhRy/OKIz80l5bLLSL300rDWs18h7Nmzh1BZ4AaDlBlNSoFz5ZVXkpubKx8XQtDR0cHRo0epr6/HaDTifu89nM3NGMaN44a//CXsIog2ao2mZ/AaHz+g6DxOJy1HjlD/2Wc0fPZZz+D49GlaT5yg9cQJjq5fD0BCfj4Pnz0b3nr2d3Cwmd46Ozvp6OiQH1IImMOHD6PT6fB6vXR2dsqp7iRUKhVJSUksXLiQO+64gziHA+vWrQBkPPww23bsoK6ubtgfcrSgUqnw2O3YW1roPHuWzpqaPs8zRKCr6LdFGGymt6lTpwY9l7K8Wa1WhBC0tbXh8/loamrqda6ESqVCXVYGPh+GGTMwTJmCSqVi//79VFdXM3/+/K9d0G4hBM2HDnFm2zbObN9O3c6duLuCh61xWVnkFBX1PBYsYMysWT0D3Qvg0yeeoH7PHpIKCrjutdfQ+Md7lZs39y+EoqIi1q1b12cWuECOHz8e1ORLWd4WL15MW1sbn332GT6fD7vdHrIsr8vF0ddeA+CGn/0M3axZlJWVYTQaaW1t5eOPP2bevHmjPp6jq6uLs9u3c3rLFk6/9x62+vqg46YxYxi7ZAnjli5l7JIlJE2YEJZZRNOhQ9jq6li9cyefPf88pzZuZIq/mx8za1b/QigsLCQzM5Pi4mLGjh3LY4891ud5CQkJIW9QSkoK+fn5VFVV4fP58Pl8fS6I1JSW4mhtxZyRwYTly1FrNKSnp/PBBx+g0+lwOByUlpYyfvx4ZsyYMdTvIaa4urqo3LSJE6+/zpmPPgqaSeji4si/+mr55qdPnx4Re0P9nj0U+Md7Bddfz9H162UhJI4dO/D08Ve/+tWwKzF+/HgqKysBaG5ulpevAyn/3/8F4JJbbkHt7wLi4uK444472L59O1arFZ1OR01NDUIIZs6cOex6RZrWkyfZ/+KLHPvzn/F0d8uvJxYUMHHFCibedBN5ixejDciaO1Q8TmfwFLWzs8/zHG1txPm3ChiSknCcN96LSr6GuLg4vF4varWa+vr6PoVQ/eGHAEy85ZZex5YuXUpVVRW7d+8mKSmJM2fOUF1dzaJFi/rNUBsrrNXV7HzySb7asEF+LXniRCbfcw+X3XUX6dOmhc1o9PkvfsHef/7nAc8zJCfj8o/3nFYrxvO+t6jZPCVDVFtbW69jnXV1WKuqUKnV5BUX9/n+8ePHs2LFCs6dOwf0DC63b9/e77gj2vg8Hvb+7Ge8NnmyLIKJK1Zw1yef8FB5OYuefZYx06eH1XI470c/4hGrVX7cc/x4n+flFhVxZts2oOdHlxsw3nN1dkZPCElJSQB93ri6nTsByCgsxNDPYDApKYnVq1dTWVmJ2+3GaDTy0UcfcfDgwYjUeSh01NSwYdEidv/0p3idTsYuWcK9X37JbZs2MbakJGJmY63BgCExUX7oExL6PC+jsBBzZiYbios5d+wYk26/na0PPwzA/hdfjF4qn8zMTKxWa59Z4mv9QsgN0RoEYjAYePTRR3nppZfIysrCbDZTW1uLzWajqKgoJptoLQcO8M7y5XQ1NGBISmLpb3/LlHvuGXErmyXnjfeW/f73ACz46U+j1yLk5eXJ+xLONyw1fvEFADkLFgz6et/73veYOnUqzc3N+Hw+2tra2Lx5c9TjGTcfPcpbS5bQ1dBA2rRp3HfoEFO/8Y0RJ4KBiJoQ4uLi5NagPmDu7PN6aTlyBOhpvobCjBkzuP3227FYLHg8HtRqNX//+985ffp02OrdH521tfz1uutwtreTs2ABq3ftImncuKiUHW5iskAeOGBsr6zEY7ejNZlIvuSSIV8rKSmJNWvWoNfr6e7uRq1W89VXX3H06NFwVrkXPo+HLatWYauvJ23aNFa+915UVgkjRVSFoNfrAegOmFM3HzoEQPr06bL94EJYvnw5Y8aMoa2tDa/XS1VVlZxOMBLsefZZ6nbvRp+YyG2bNmFMSYlIOdEiqkKQ9iO4XC75NUkIY2bNGvb1lyxZws033ywLrb6+nv379+P1eod97UCajx6l7Be/AHoGXMnnbaoZjYRFCCUlJYNK7pXgn9oEzhzOnTgBQPq0aeGoCsnJydx22200NTXh8/loaGjggw8+CFvLIIRg2//5P/g8Hi655RYmr1oVluvGmrAIobS0lOPHj/Od73yn3/PS09Pl/6Ub03bqFAApl10WjqoAPV3QN7/5TTo7O/H5fAghKCsrC4sYvnrjDep27UJrNrPk178OQ21HBlHtGjIzM+Ub09bWhvD5aK+oACAlzDtuDAYD3/zmN+nu7paXwD/77LNhicHrdrP7pz8Feix6iWPHhqu6MSeqQjAYDHK30NLSQmdtLR6HA7VWS1JBQUTKXLVqFQ6HA6/XS0tLC6WlpRcshqOvvUZ7ZSXmjAyuePTR8FY0xsRsf3V7eztt5eVAz4KMeigu3ENApVJx11130draitfrxWazXVA34bbb2fvsswDM/8lP0MfHR6K6MSPqQpB89ru7u/8xPpg0KaJlqlQq7r//fpqamvB6vTQ3N/PVV18N6RpH16/HVl9PwtixzFy7NkI1jR1RF4K0e8npdNLmHx9ciCFpqGg0Gh566CEaGhoQQlBVVUVzc/Og3uvzePji3/4NgLk/+MGw9g+MVKIuBJN/V7LX65X39ydFaR6u0Wi49957aW9vx+v1cuDAgUHZGE698w7W06cxpaUx/cEHo1DT6BN1IcQH9K2yECI0UAxV/pVXXklnZydOp3PAmYQQgn0vvADA5Y88gs7vg/F1I+pCSPGbYoUQWM+cASAxygs1U6ZMQaPR4PV6aW1tlTe79MXZjz/G8uWXaM1mLv/ud6NYy+gSUgjV1dWMGTOGkpISSkpKBt2fDsSYMWPw+Xx4bDYc/hsQbSEA3HbbbfIq6JEjR/B4PH2eV+ZvDWY89BCmtLSo1S/a9DtnW7x4MRs3bgxrgdL+RZ9fWJKberTR6/UsXLhQnj0cP36814ZYy4EDnPnoI1QaDVf+v/8X9TpGk367ht27d1NcXMyTTz4Z1lU8IQTupiYguuOD85k1axYajQYhBPX19UGrogD7/Dt6Jt99d0zrGQ1CCiE7O5uKigp27NhBU1MT77zzTsiLhHJ5C1moWo3b7+4ei24hkGuvvZbW1lbcbjeHDx+WBd9eVcXJt94CYM7jj8eyilFB3djYKI8DAh9tbW3ExcWhUqlYuXIlh/zLxX0xdepUkpKS5Mcv/Eu0odBoNLj9XUNijH9pSUlJ5OXl4XK5OHfunOzfuX/dOoTXS8GyZUPeOTUa0WZlZVFaWtrrQGeAo8TOnTuZMmVKyIuEcnkLhU6nk1uEkdDkLlmyhPXr15ORkcHRo0e5cupUjrz6KgBzn3gixrWLDiG7hl27dnHFFVdQXFxMXV0d99xzT8iLSC5v0mMgIRgMBjz+MUKsWwTo6apmzpxJd3c3HR0d7P6Xf8Fjt5N5xRXkX311rKsXFULOGm644QZuuOGGiBQaFxcnDxZjPUaQuOKKK9i3bx9GjYbj//mfAMz5wQ9G3W7kCyUmq49GtRqv3/0qYYSs6avVambMmEHTe+/hsVpJKChg0sqVsa5WWPn0iSfYUFzM+/fei9cfsQag9dSp2AhB748BoI6LQz+C3NwXzJuHdfNmANJXrkT1NYrHEOgWnzp5MqcC7EMJeXmxEYLa7+Ciy8jAZrPFogp9UvHOO3DuHOqEBPRFRSEjxIxGzneLr9u9Wz6mM5tjIwS737Sry8jo0yk2Fvi8Xvb4N55oFy8GvZ6KiooRHzXW43Ti7OiQH/25xUutb8zc4s/H6l911GVk0NUVjQiHA/PVhg20njiBMSWFyQ8/THNnJxqNBpvNJu++HomMOrf4QKTlZ21GRi+zbizwut3s8X+Zcx5/nJLrr5f3LJSXl4/oViEcbvEQIyEEtgjRdlrti+N//jPtFRWYxozh8kceQavVkpOTQ1dXFy0tLTgcjlhXMSThcIt3tLXFpmvo8O9D0GVkyIE3Y4XLZmP3U08BMO+HP5Q3pS5YsIC33nqLuLg4amtrueSSS0a9TSGUW7wxJSX6LYLbbpfjK+syMvqMlxBNPv/5z7HV15M8cSKF//RP8usZGRkkJCRgt9uprKwcES1XJImqyxv8ozXQmM2o4+MRQsSsD26rqJA3pZasW4fWaAw6fu2119LU1ITb7aa6unpEjxWGS1i6htLS0kHndJKEYMrNRQgRcmdQpBFC8Mn3v4/X5aLguuuYuGJFr3NycnIQQuBwOKivr2fixIlDCko+moh61yDNGBLHjcPtduP1emMihq/eeIPTW7ag1um4+sUXQ/b/t912Gy0tLXR1dVFXV/e1bRWiLgRpxpB2ySW4XC58Pl/UbQldjY1s929EXfDUU6RNnhzy3Ly8PDnVwNmzZ2M+uI0U0W8R/F1D6iWXyF9qNE25wudj69q1OFpbybj88kHtN1i0aBENDQ10dHTQ2NgY8wFuJIhZ15BUUCA3x9FsEcr+5V+o3LwZjV7P9evXy4Gp++Oyyy5Dq9VitVqpqamJ2bgmksSsa0gcN04WQrSmZme2b2fXj38MwNL/+A8yBhmlRaVSUVRURFNTE62trVgslrBHYYk1URWCx+mkq6EB6NmZJI3A3W53xAdhzYcPs+n22xE+H9MeeIAZ3/72kN4/c+ZMtFotjY2NVFVV4XQ6v1YDx6gKodOfdUQXF4cpLY3ExETcbnfEv9T2qio2XncdTquV3EWLuObll4dsJdRoNFx77bWcO3eOhoYGamtr8Xg8XxsxRFUI53cLY8aMoaurC5fLFbGmtquxkY3LltHV2Ej6jBnctmnTBacHmjx5MmlpadTV1VFdXU1nZ+fXpotQQ08k1Llz5xIfHx8Un/Dtt9+mqKiIpUuXUltbO+zCpBmDtGE1KyuLzs5OPB5PRBZ2OuvqeLOkhPaKChILCrjj738fdhi8W265BYfDQUVFBZWVlREVcTRRA5jNZt577z3uuOMO+YDH42HdunWUlpby7LPP8txzzw27MCkwhhSOLj09XRaCzWYLazNrra7mjauuovXkSRLGjuXOjz4iPidn2NfNyMjg0ksvxWazceLECaqqqnC73aO+m1BDj5/BmDFjgg6Ul5czZcoU2Ufw8OHDIS8yWE8nKZReqt9HwmQyodFo6O7uDhmw+0JoKy/njauuwnr6NEkTJrBqxw5SwhiM46abbsJgMNDY2MipU6eora3F6XTi8XhGrY0h5BghMMMb0G/zN1hPp1a/ENICnGUSExOx2WzYbLawNLE1n37KX+bPp7OmhtTLLmPVjh1hj49sMpkoKSnB5XJRXl7OoUOHaGhowOFw4PF4cLvdo04Q2pKSEt544w2ysrKCDgRmeAP6zbA2GE8nj8OBtaoKCBZCWloa1dXVdHd343A40Gq1Fxxq/8j69Xz08MP43G6y5szhts2bI5bgc+bMmVgsFsrKyuTuYfLkyWRlZZGcnIwQoidznVqNWq0e8XsZtH25uwFceumlnDhxApfLxRdffNFvDqX+kntJtJWXI3w+DElJmANuTnZ2NidOnKC5uZmuri5MJtOQhSB8PnY++aQcy2DSnXdyw5/+FNHkoSqViquvvpry8nIsFgtnz57FarWSnZ3NxIkTycvLw2g0IoTA6/WOeFHIy9A33ngjBw8e5OTJkzz88MM88MADPProo5SUlGA0GvnTn/40rIJa/XEIUv35HCUyMjIQQmCxWLBarSQnJ6PRaAYtBpfNxgf33ScnB5v/k5+w8J//OSqZ2XU6HWvXrmXLli0cPHhQjufodrtpb28nNzcXs9mM0WjEYDDIogBkQYwUYchCeD8gF7HE3Xffzd133x2Wgs75N1WmnrfSl56ejslkoqOjQ84Ap9Fo0Ol0A35B7ZWVvHvrrbQcPYpGr2fZf/0X0+69Nyz1HSw6nY4VK1bQ3NyMzWajoaFBHvM0NzdjNptJTEwkKSmJtLQ04uLi0Ol08hhCai2AoFYj2kRtz6Jl/36gd3KO5ORk0tPTOXPmDLW1tYwbNw6z2YzX60Wj0YQUQ/VHH7Hl7rt70thlZXHzX/9KblFRpD9Gn2i1WtauXcvJkycpLS2lvb2diooKtFot48aNw2az0djYiFarJSUlhbS0NPR6PXq9HpPJRFxcHGq1GiGELBCVStXnI2KfIWJXDkAIQUNZGQDZc+f2Oj5hwgRqamro7Oykrq6OhIQEOaT/+WIQQvDFunXs+MEPED4fWXPncss775AQMFiNFZdddhkTJ05kx44dnDp1CpfLRUVFBSqVCpPJRE5ODi6XKygeVV5eHklJSWg0GuLj41Gr1fJfyS4hbeeTnms0Gjn3RbiIihA6a2rotlhQa7WM6SPoxNixYzEajbS1tWGxWMjMzMRgMKDVavH5fPKYweNwsHXNGk785S8ATH/wQa55+eVeew1jiVarZcmSJSxatIg9e/Zwym9EczgcchLUzMxM9Ho9SUlJ1NbWUldXJ8+W8vLyZCGYzWb0er0crVb6QUTCcBUVITTu2wdA+owZfY7kc3NzSU5O5syZMzgcDiwWCxqNhqysLFQqFV6vl/aqKt676y6aDhxApdFQsm4dl3/3u6hUKnmqBgN/SYP5EsPxRWs0GoqLi1m4cCGffPIJnZ2d5Obm9oQN8i+0uVwuNBoNSUlJ6HQ6DAYD3d3dstOPTqcjMTERnU4n2yfcbjcZGRl9JlEdDlERguRhEyqLm06nY+LEiXLoGqPRSEJCAm63m+zsbCx79vD+PffgaGnBmJ7ODX/5C/klJaNmg0hJSQnQk7Ckvb2dpqYmmvzxIaRxQVNTk7xuIYTAbDZjMpmoqanB6XTi8/lwuVy4XC4mTpxIRkZGWMcMEReCEILTW7YAMOGmm0KeN2nSJMrLy2loaCAvL4/KykomTpzIzp//nGMvvIDwehlTWMhNb78d9pgK53+hHo9Hfk0KzCmN5KUb5/P50Gq1CCFwuVzyLKev86QFtY6ODlJSUsjJySElJYX29nbZvG6322WLpMvlor6+Ho/HI083DQYDRqMRlUpFVVWVLK6h8OkTT1C/Zw9JBQVc99pr8u4sn9cbeSGc/fhjOmtr0cXFMbafMDTSoMnlclFVVcUlubnsWrsW2969PcdvvplZzz3HOZ+Pc9XVqFQq4uPj5VhP8fHx+Hw+nE4nWq0Wp9NJWloaDocjaCucZCGVvmCNRiOP1CO1aCTVC5B/3U6nE41Gw7lz50hISCA/P5+mpiZZHFI91Wq1PL5wuVw4HI4LEkFgfITPnn+eUxs3ytniT2/ZElkhHP3jH/nEn+Bi+re+NeCg7uqrr+Zvf/sb9mPHOPXcc3jPnUOl1ZJ2//0Yli/H4fUibDa0Wi1GozEo4JfNZguamwshOHv2LDqdDrVaLffJer2eM/7l8MzMTLq6uvD5fH064+p0urDtWpbGMuejVqs5d+6c3LokJCSg0+no7OyktbWVs2fP4vV6ZXuDwWDA5XLJLdZgs8WfHx/h6Pr1shDq9uyJrBC0RiNOq5WUSZOY/5OfDHh+glqNecsWOvxRS3TZ2Yz78Y8xX3ppzxS0oUHOEKdWq/tc2AkcNEpTMKnJlmwTOp0OIQTnzp2T5+eB6yPSa9I1AqdygccCkcoJHLg6nU70ej3t7e3Y7Xbi4uIQQtDd3U11dbXcKul0OvR6PWq1GpvNRnx8PCkpKZjNZtlxKC0tjYKCAoQQzJ49Wy53sG7xjrY24rKzgd7xEZzhcoItKSlBr9fzne98JyjBlzEtjbzFi8mZP5/Wr77CnJ7ep+nXVl/Pl7/5DQd+8xvc/mZcd9VVGG+/HdMll8g3UKvVylOpoSDdHLfbLScJ9Xg8civgcrlwOp2cO3cuyARsNBpxuVxBg1IphLDL5cJgMOB0OklISEAIgd1ux2AwoNPpcDqddHd3o9VqMZlMmEwmOTqMWq0mOztbvkbgGCUlJQWTyYTdbictLY0pU6YwadKkkJ973o9+FBQe+FxdHa9PndrrvP7iIxiSkyPr8tZeWUntp59S++mnlL3wAvE5OUy6806y585FpVbTVl5OTWkpZz/5BPy/sMzZs5n3i19wrKuL5uZmuRmPi4vD4/GQkJAgtwbV1dXEx8fT1dWFRqNh0qRJnDhxAoPBEPQrhp7uQq/X4/P5elnpVCoVRqMxaAX1QkgOyAQ7mOAaEyZMkAODT58+ncsvv1zOZzFYtAZDUCIRfcCKcSC5RUV8sW4d0+67r1d8hJyiIlRiGCOk2tpa8vPzqamp6VMIzYcPU/Xhh7QcOULlpk04z0sOHlTRRYuY+4MfMOGmm+SbdPz4cU6fPh2USzpchOpa+iMtLY3c3Fw6Ozsxm81UVlaSk5ODyWSiq6sLr9dLWloaSUlJxMXFkZGRQWtrKxkZGVFbP2ipreWP+fk8UFND+nn3pPTxx2n47DMSx47l+vXr2f7IIyz7/e/xeTyRFUIgHqeTM1u3UvG3v9FeWQkqFfE5OWTPm8eE5cv7zaYqBcyuq6ujrq4Om82G2Wymu7ubgoICHA4HdrsdlUolN9VNTU1MnToVlUrFuHHjUKvVJCYmolar0Wq1YTfRjhT6E0J/RG3RSWswMHHFij69jgcix7/X8JIo5H66WAl7e+V0OnnmmWci6r0UjTK+juX0ixgGNTU1AhA1NTXya1arVQDCarUO59L9Eo0yRms5zTU14lcgmgPuyWCI6g6IUBFV+ou0MpgoLEo5YWA46htqizBlypQ+rxPq9VDHBvoFXczlXGiLMKzBojT9avA7tsI/8jzU1dUF7YKGHsNNXx5ToV4Pday/Mi72clobGnDA0LfTD0k251FWViYA5TECH4fKyoZ0L4dlR/B4PBw4cIDMzMyYbLhU6I3P56PdYmHq5ZcPyRw/LCEofH1QfsYKgCIEBT+KEBQARQgKfhQhKACKEBT8KEJQABQhKPhRhKAAKEJQ8KMIQQFQhKDgRxGCAqAIQcHPsHco1dfXk5CQMCIigyn0uPd1dnaSk5MzpD0iwxJCfX09+fn5w7mEQoQYjNNRIMMSguTfV1NTM2DATYXo0NHRQX5+/pATmw9LCFJ3kJiYqAhhhDHUrloZLCoAihAU/ChCUABGoBCUTdWxIWpu8QMhhAgKXCXFMVCIDiOmRZDiC1osFjktjsvlUlqIKDGihNDW1gZAY2MjR48exeVyRSU5qMIAQigrK2PBggVcddVVrF69OmKZ0oUQtLe3097ezsGDBzl27Bher5djx47JMYgVMUSWfoWQn5/Pxx9/zI4dOygoKOBvf/tbRCohhKC+vj4ooWZDQwNOpxOLxYLFYgl7OkCFYPodjWX7AzQCckDISOB0OnE4HHLoGClQVmtrKx6PR7aZS6H7FYfb8DOob/TMmTNs3bqVFSECYQXmfOwv72MopPgALpcLs9kMIP/t6Oigra0Nj8eDxWJRBpARYkAhdHR0cO+99/LHP/5Rzu5+Pvn5+YPK+xgKqTvweDwkJSVx7bXXAsjBJxsaGjhx4gQWi4Xm5mbcbrciiDDTb9fg8XhYtWoVTz/9NJdddlnI885ffewr72MohD/MvcTs2bNRqVQUFxdz8OBBVCoV3d3duFwuOjo6SE9PlxN7pKenA4rNIRz02yJs2LCBzz//nOeee46SkhLefPPNPs+TVh+lx1CFIA0S1Wq13OqYTCYWLFjA0qVL5VyQHR0dHDp0SI5y2tHRgdfrlW0Qoy376khiWIEyOjo6SEpKwmq1XvAytMfjYf/+/bjdbrq6urjuuut6nePz+di2bVtQKP3ExEQuvfRSoEc0geVLOaAuxl1TF3pPYj78liKfB+Y/PB+1Ws1VV12F2WyWW4yOjg72799PTU0NNpsNi8UiJ+iQknCO5qTd0SbmLUJrayvl5eV0d3djNps5dOiQfOyhhx4Kyknt9XrZvn07QK9EGykpKUzwx3MeM2ZMrynmYBKKfh0YtS2CNFCUAnMF8uqrrwY912g0XHPNNUDP9DJwLNLW1sbZs2fZv38/Bw8epL6+npqaGnlmIc00zn8oLUYPMR9qS12D3W7v01D0hz/8gZkzZzJ//nwAOaOKlA9Ssjd0d3fLiTUbGxs5d+6cnEDj/P17ganyApNyaLVaVCoVHo9H/v9iIeZdQ3V1NRaLhbKyMvkXPmXKFE6cONHr3LVr18r/NzY24nA45ASb0NN19GXMSk9PR6fTkZWV1UtsRqORpKSkkPULTL45GoRxofdkxLQIgU10cXExbW1tNDY2Bp177Ngxpk2bBkBWVhYABQUFeDwePv74Y7mFkBJlSrS0tAD/iBArnSPNOhwOB2azmfj4+D5T//WFSqWS0xWPBoEMREzHCEII2Q4gWRdvv/12AG6++Wbi4+ODzt+9e3ef19FqtSzzZzCDnoFh4AzjfLq7u3G73Rw/fpyamhr279/PkSNHaGxspLm5WV7oslgs2O32Pi2YQgh5ZTRwzCFlZBttVs+Ydg1CCPbt20d3dzeff/45KSkpQc2/xHvvvUddXZ38PD4+nnvuuafPa7rdbj755JOQ5dnt9gHrlZqaikajweFwMH78+JCCSkpKwm63k5SUNGDLEJg17vzE5+Fk1HYN0s2RsqX2xfLly/nDH/4gP7fZbHz++efMmzev17k6nS6odTh58iRWq5X29nY5iZeUxRV6T0OhZ0orcfjwYVJSUkhLS5NzM0oGKylfY2D2d+gRqpS1VUIam0jZYQPrC0P3Qwg3MRWCz+dDrVbT1dVFcnJykM1gIA4dOsRXX33F/fffT3NzMy0tLUyZMqXXeYFrJJIdQq1Wk5OTQ319PWazWU7fJzWOer0+yBjV1tYm756SGD9+PFVVVaSmppKZmSm3CIGzjvNJT08Psnh2dnZiMpnQarX4fL5eaYWjScyFAMh5Hfvz1UtJSel1M5xOZ1BLYbFY+k2Xq9FoglqLrKwsvvzySzQaTa80e9KNFELITTr0dD1er5eqqiqgp/UIbEEkJkyYgNFoxOFwoNPp0Gq11NTUoNfrgwQf2CKpVCoyMjJ61XkoP5ALJaZCCBwoqtXqPn/REnfeeSfNzc1oNBo++eQTzp071+ucU6dOkZeXN+gkYOnp6UHC8Xq9nDx5Us7kDr2njTqdLmjMILUikmCk6evp06f7LDMnJ0fOD6lWq4OMYkIIWlpa8Hq9JCQkyK2V1+uN+IacsAwWJ02ahEaj6ZUJdjDvP378OKdOncJut/Pggw8OOg3ftm3bQn7ZACtXrsRoNMozD6kbGiznJxH/7LPP5EyuQyWUfUNi8uTJcipgs9ksC2/MmDG0traSmJgotyQDLaZd6GAxprOGlpYWTp48yalTp9BoNNx3331Der/H4+G1117r95xp06bR2tpKQ0MDt912G2PGjBlyPSWcTic6nY5t27YN+b1ut1vOQislHw9lo5DIzc2V7SUpKSl4PB65RQr1gxmVQmhoaKC8vJxTp06RkZHBzTfffKFV4dSpU5SWlg543qpVq+S6Sk1xenr6BY/aOzs75eTf0NOCbN26ddDvF/681ee3GgaDgdTUVFJTU+UBpURSUlLI1MGjcvooDbx8Pp+8ZnChTJo0CZvNxhdffNHveW+88QZFRUXk5eXx1ltvAT0m7aKiogsalPUVh+Daa68NGmBKVFVVUV5eHvSaJECNRiNniQ9sKaSM9nq9Hr1ej8lkQggx5BzSAxFTIUiWOWnqNFxmz57N7Nmz8Xg8vPXWWyH79D179gQ9P3HiBCdOnJAXswoLCzl8+DArVqwgPT19yAIJZVwqKCjA7Xaj0WjIz8+XP/P+/fuDpo06nQ6XyyVfw+Px4PV6qaysxOfzkZ2dHbTDPBzEfNYgtQjhnCJptVrZ8tjZ2cm+ffuoqKgY8H3SdPbgwYMA/fpxTJkyhSuvvHJIv0yv18vEiRPlrkBaD5k5cyZ2ux2n0xlk/LJYLHIWt5SUFLq7u9FqtfJezXAScyEIIfD5fBH5cNDTdC9ZsoQlS5bg8/n4r//6r7BcV2pFtFotixYt4tJLLw05zpAE3xcdHR2y2VsaJ0jdTaB9QrKh2O12Pvzww36n2hdCzIQgCUD6PzU1NeJlqtVqvvGNb9Dc3ExGRgZOp5O2tjZKS0sHHMGHwuPxUFpaSmlpKePGjePMmTNAzwqqTqejurqaOXPmUFNTQ3p6Oqmpqbjd7qCbLHWRx48fD7q2TqcjJycHrVaLVqvlq6++uvAPPwAxHyNIv5bhDhYHS1xcHHFxcUDPcnTgFjdAbp5NJhOHDx/m2LFjg762JIL8/PygRTJpAGuxWGhpacHtdjN9+nTMZjOnT58Ouc5yvvHKYDDgdDqHNbsKxYgQglqtjpoQBsJgMMhm3oULF7Jw4cI+zztw4AD79u3r9XrgIDCQ6upqXC6X7NVVX1+PSqUiOTmZtrY2Jk6ciNFolI1GfTFx4kSuueaaiFgYY9o1uFwuPB4PBoNh1PkzXn755Vx++eXy89bWVrZv395rNdFut9PY2Ijb7ZZFIOHz+WhoaMDlcnHgwAH5F5+Tk8Mll1zC7NmzSU9Px+fzYbPZIhq5LqZCiHa3EEmSk5O56aab5Kb/9OnTNDU10d3dLe9Z6OzsRKPR9Fo8C2Ts2LFATwuSm5uLWq2OSvjCfoVgtVq59tprOX78OJ999hnTp08PW8GSCDwez6gXgvRZWlpa8Pl8eDwejEYjZrNZ/mwmk0k2F1dVVVFTUyO/Py8vr88WMXBH1tKlSxk/fjy1tbUhzx8O/QrBbDbz3nvv8fjjj4e1UEDeSu7xeOTB22hE2rcgmYetVivnzp3DarUCvQd8V199NQUFBWg0Gvlv4FJ6KLZv305bWxtHjhxh3rx5PPLII2H9HP0KQafTDWuRpj+kjSDSr2c0IgmgtbUVr9fL4cOH5SmxWq3u9blmzpyJTqdj0qRJQa+vXbuWmpoaMjMz0ev1sr3D7XZTW1uLRqOhurpaPv/zzz+PrhAGS0dHR9Bzg8EwoCOsw+GQv7ShOM2OJDweD62trbINQPo853d1gZthQhEY3DzQxpKdnU1ZWVnQuffee+9wq96LsAjh/AjtTz/9NM8880y/75HWGEbrYFFq0ZxOJxUVFbJBKtDknJGR0W84gYaGBjZv3szq1auJi4sLsnpKjjw6nY65c+cGiUHy9gonYRHChcRHkNYY3G73qBOCJODDhw8DyNvRAscCS5YsCRmzobW1lY0bN8rPN2zY0G95RqOR2bNn43a7KS4ujsjWtQGFcOONN3Lw4EFOnjzJww8/zAMPPNDrnAuZ3sTCqhguPB6P3GdLTjPSTe+vG7Db7fz3f//3kMpKTEyUo9ZEarwGgxDC+++/H/ZCpSir0tbu0TRrkOrc0dEhm4a1Wi1ms5ni4uKgc9vb2+U9D4Nl8eLFpKSkYLfbGTduXNjqPRAxMyjZbDZ5RW40tQiSCOAfK4I6na6XKXowU0KAm266idTUVPR6PV6vNyz7Mi6EmAhBmjZ6PB55981oQAhBd3c3LS0tsp1gxYoV8obSjo4O3njjjQGvM3HiRJYuXdrr9Via2WNuYj7fv3Ek4/P5OHHihCwIyX0N+m8Bli5dSlZWFi6Xi6SkpBG5rhITIQRaFaU9/iMdIYS8W0gK7iHNjjZt2hTyfQ8++KDc3I/ksVBMhOBwOGTP4b4cVUYiUoBwgK6uLkwmE4WFhezfv7+X+35SUhJ6vZ5bb7015j6NgyVmQpCmj6MBKWi4tKvI4/EwdepUampq+PLLL4POXb58Obm5ubGo5rCIiRC6u7vRaDQ4nU7mzJkTiyoMifPtBnFxcVRXV1NZWRl03s033yyvMI42YjJqkfwZpMHTSEcyGkkbS/Ly8nqJYPXq1aNWBBDDrkGaM4/0fJHSPgPosQwmJCSwc+fOoHPuu+++UbuCKhGTFkFaeXS73UPOWBpt2tvb5UGi1+uVYzhJrF27dtSLAGIgBMl+AD3Tr5H8JXo8HtkxpqOjgwkTJgRNFVetWhWrqoWdqHcN0sqdEGLEtwaBIf46OjqorKwMMgaN9G5tKISlRZgzZw5Tp07lt7/97YDndnd3yxncUlJSwlF8RHC73XI0k3PnztHY2BgkgrvuuitWVYsIYWkR9u3bN+hfx5dffinnXxjJO5PO32kcuBj0dRgcnk/UxwjSMq7T6RyxQvB6vfIu49bW1qCp4qJFi752IoAYCEH6ZQkhmDp1arSLHxSnT58OSh8QKNiRWufhElUhnB+dbCQOtioqKmRTclNTU1DE+KKiolhVK+JEVQhOpzMoQspIW451uVxBi2AVFRVB4e7C6eAz0ojqnbDZbLS3t+NyuUbcZhSfzxf066+urg6KcBbo5/h1JKp2BOmLdjqdIyphRnt7e1Bso/b2diwWizwozM3NHRWLY8Mhai2C0+mUI4/Z7faQyURjwf79++X/3W43X3zxRdDMYPny5bGoVlSJmhCOHDkib+symUwjxpi0b98+UlNT8fl8crT4wG3ja9asiWHtokfUuoby8nJ5f+JImIefPn2a06dPk5aWJudaaGxsJCEhQe621qxZM2p2GA2XqLQIx44dk1fwPB5PzNftq6urKS8vx2w2y65r9fX1WK1WWQS33HLLRSMCiEKL4PV6qa+vl7sCn88X8/n4qVOnMBqNctSW1tZWOjs75THMpEmTghKAXQwMKIQnnniCPXv2UFBQwGuvvTZkBwyLxSK3BiqVivz8/KjbDzweD2VlZXR1dSGEICUlBa/XS3NzMyaTSU68IYToM4PMxUC/Qjh06BB1dXXs3LmT559/no0bN7J69eohFbBp0yZSU1MxGAyoVKqomWj7CncrxTC0WCxyGNszZ87I3cHX1Xw8GPr9ae7Zs0d26rz++utDJtfq6OgIekjRQzZs2EBGRgbjxo3D4XBQUVFBbW2tbFjqL3T9YKisrKShoYGtW7eydetW+YZu3bo1SARS4OvA2QH0eHEH7qS+4oorhlWf0Uy/LUJbW5sc8zcpKanPTCUQOj5CYE7F3Nxcqqur2bVrFxkZGZSVlcnRw2bMmIFer2f//v1BsQCuvvpqzpw5g81mY+rUqQNGX5fC5wdGPI+Li8NgMNDU1CQ7rZrNZhoaGoJSAgJhD3Q9muhXCMnJybLDp9VqDRkdNVR8BLfbLXv32O12pk6dSltbm3yj6+vrqa+vD7pWWVkZQgh27tzJjh07KC4uRqVSBWVVgX/cbAmHw4Hb7aahoYFJkybJv3rJRxF6brRKpaKqqgqfzyePB6RQ+xcz/QqhqKiIdevWcd999/Hhhx+GDD4ZKj6CyWTCYrEERU5LSUlh3rx5uN1uKioq6OzsZPfu3Xi9XhITE+WkFkajEaPRyN69e4mLiyMtLS1orSI9PZ3c3FxUKpUcn1CtVjNu3DicTidarRa9Xo9Op5MTXpw9e1ZuBb797W/L9RzpW+aiQb9CKCwsJDMzk+LiYsaOHctjjz02pItL3kBut1sOAyNt/9LpdEMOLN1foIhAI5X0y3c4HDQ1NcnjAGkM8Y1vfGPErXzGmohncJF2JEmDtKNHj9LW1ibPIkIFnzSZTAMm6zQYDLLZWnKaMRqNnD17Vr750gaYoqKii8JANGIzuEhBoSSmTZvG2bNngZ5fsdPplPcpSL9kCZ/Ph8lk6vXrNRgMskm4L7F861vfUn7xQyTq29mNRqM8mDtz5gyXXnopCQkJJCYmyskzu7u7SUhIkH/tNptNHjCOGzcOtVrNoUOHmD59epAF0G63xyyB5mgnpsm9FMLPhd6TsP90nE4nzzzzzLCNRbEu4+tYTr+IYWC1WgUgrFZrv6+Fm2iUMVrLudBrRbUzDeUJ1Z+H1GC8p5RywkC41defIqdMmdLndUK9HurYQKq/mMu50BZhWLMG4R9nBgbllv4/P1A39OxNGMrroY71V8bFXo70XAxxDjCsWUNtbW2vBSeFkUFNTQ15eXmDPn9YQvD5fNTX15OQkHBRWO1GA0IIOjs7ycnJGZI9ZVhCUPj6oJjgFABFCAp+hiUEq9XK3LlziY+P5+jRo0HHvF4v3/rWtyguLubRRx8dTjH9lrN582bmzZvHokWL+N73vhexciR++ctfcuWVV0asjDfeeIMlS5ZQUlLC3r17L7icoTIsIUhZ4O64445ex7Zs2UJOTg47d+6kq6trWB+qv3JmzZrF7t272bVrF01NTXL63XCXAz07mY4cOXLB1x+ojPr6ev72t7+xfft2SktLWbBgwbDKGgrDEkJ/WeAGu/F1uOWMHTtWzp6i1+uHtfI4UFa7l156ie9+97sXfP2Byvj73/+OwWDg2muv5d5778Vmsw2rrKEQsTFCW1ubvPrV38bXcLFv3z6ampqYPXt2RK5vtVo5cuRIRH+lUhLxjz76iAULFvAf//EfESvrfCImhMFufA0HtbW1PProo/zpT3+KWBkvvvhi2HMtnk9ycjJXX301KpWKpUuXDilT/XCJmBCKiork7eX9bXwdLp2dnaxatYrf//73QdFNwk1FRQU/+9nPuP766ykvL+f5558PexkLFy7k4MGDABw8eJAJEyaEvYyQDGllog9uuOEGkZ2dLebPny/Wr18v1q5dK4QQwu12i/vvv18sWrRIPPLII8MtJmQ5zz77rMjJyRGLFy8WixcvFqWlpREpJ5ArrrgiYmX86Ec/EosXLxbLli0Tzc3NwypnKCiWRQVAMSgp+FGEoAAoQlDwowhBAVCEoOBHEYICoAhBwU9YhaDVaiksLGT69OnceeedsudzX7z77rucOnXqgssqLS2V4ywAPPXUU72Sbp1PQUFBWBdyCgoKmDlzJjNnzmTx4sWcOXNGPpaenh507mOPPcYf//hHAB544AEmTJhAYWEhhYWFIVc733rrLf7t3/6N0tJSlixZEnSsqamJ3NxcnE4nS5YskaPJXyhhFUJycjIHDx7k6NGj6PV6fve734U8N9xCePbZZykuLr7g610oe/bs4fDhwxQXF/Ozn/1s0O/79a9/zcGDBzl48CAbN27s85x169axZs0arrrqKsrLy7FYLPKxjRs3cuutt2IwGLjmmmt4++23h/U5ItY1FBcXU1FRQUtLCytWrGDmzJmUlJRQXV3N559/zqZNm/i///f/UlhYSFNTE5WVlVx33XVceeWVLFmyRE64WVJSwhNPPMGVV17J9OnTOXbsGDU1Nfzud7/jl7/8JYWFhRw8eJAHHniALVu2AD2he+bMmcP06dP5/ve/3289X3nlFZ566in5+bPPPsu///u/U19fz8KFC5k1axYzZ87k8OHD/V5n0aJFcu7ocHD8+HFSUlJITExErVZz22238c4778jH33rrLe6++26gJ/Hohg0bhldgOO3VaWlpQoiedYabb75ZvPzyy+I73/mOeOGFF4QQQrzxxhtixYoVQggh7r//frF582b5vcuWLRNVVVVCCCG2b98u7rjjDiGEEIsXLxY//vGPhRBCvPrqq+Jb3/qWEEKIp59+WvzmN7+R3x94vXPnzgkhhPD5fGLlypVi165dQgghxo0bJzo7O4Pq3NjYKKZNmyY/nzlzpqipqRH/+q//Kp588kn583R1dfX6vIHXe+SRR8TLL78sH9NoNGLWrFnyY8yYMWL9+vVyXcePHy8fe/TRR3td+9VXX5XLF0KIXbt2iZKSEiGEEA0NDSI/P194vV4hhBBer1fk5ub2usZQCKtbfHt7O4WFhQBcddVVPPTQQ8ydO5f3338f6EmI1dd2MpvNxs6dO7n11lslcQbFNLrtttuAnqhnf/nLXwasx/bt2/nVr34lR0y5/vrrQ65+ZmZmMmbMGLk7i4uLIy8vjzlz5nDfffeh1Wq54447mDFjRp/vLyoqoqWlBZPJFNQ1SN2kxPnRZn79619z0003hfwMjY2NQRtYioqKqKqqwmKxsHHjRlauXClvwlGr1QghcLvdQ46DKRFWIZz/4fuiL/8Hn89HZmZmyPdKwbk0Gs2AicUdDgePPvooX3zxBdnZ2Tz22GMDehnfddddvP322+j1eu68806gR8i7d+9my5YtrF69mp///OfcfPPNvd67Z88eDAYDq1ev5plnnmHdunX9ljVYjEajHAUOer6322+/nb/+9a+89dZbvPDCC0HnS5l1L5SITx8XLVrE66+/DvQMcObOnQv0BLCSci0nJiaSmZnJ5s2bgZ4PFWrzqETg+wNxOByoVCrS0tKwWq28++67A9Zx5cqVvPPOO/z1r3+VhXDmzBmysrJ4+OGHuffee/sdI+h0Ol566SX+9Kc/hQwFNFQmT54sJx+VuPvuu3nllVeoqalh/vz58uttbW3D3osRcSE888wzlJaWMnPmTH7729/y0ksvAT1ZVJ977jl5sPj666/zm9/8hlmzZjFjxgy2b9/e73VXrFjBhg0b5MGiRHJyMvfffz9Tp05lxYoVQV9YKDIzM0lPT8doNMpuYqWlpcyaNYvLL7+cv//970FR2PoiNzeX1atX88orrwxYHiAPlAsLC7n66qt7HS8uLu61EXfu3Ll0dXVxxx13BLWsn376Kddff/2gyg3JsEYYChHl4YcfFnv37h3wvLvvvlucPHlyWGUplsURzFNPPUV7e3u/53g8HpYvX86kSZOGVZayQ0kBUNYaFPwoQlAAFCEo+FGEoAAoQlDwowhBAVCEoOBHEYICoAhBwY8iBAVAEYKCH0UICoAiBAU//x8B4lKzawD9/QAAAABJRU5ErkJggg==' width=130.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "from matplotlib import cm\n",
    "from scipy.ndimage import gaussian_filter1d\n",
    "from matplotlib.ticker import AutoMinorLocator\n",
    "\n",
    "n_cycle = 3\n",
    "\n",
    "def convert_potential(E_old, pH=13, Eref_old = 0.165): \n",
    "    E_new = E_old + Eref_old + 0.059*pH\n",
    "    return E_new\n",
    "\n",
    "def CalcSauerbreyMass(df_by_n: np.ndarray, Filter: bool = True) -> np.ndarray: \n",
    "    Zq = 8.8e6\n",
    "    f0 = 5e6\n",
    "    MassDensity = -df_by_n * Zq / (2*f0**2) * 1e5  # conversion of kg/m2 in ug/cm2\n",
    "    return gaussian_filter1d(MassDensity, 150, axis=0) if Filter else MassDensity\n",
    "\n",
    "def discard_points(y: np.ndarray, trsh: int) -> np.ndarray: \n",
    "    y[np.abs(y) > trsh] = np.nan\n",
    "    return pd.Series(y).interpolate().to_numpy()\n",
    "\n",
    "labels = ['15 MHz', '25 MHz', '35 MHz', '45 MHz']\n",
    "lines  = ['-', '--', '-']\n",
    "\n",
    "SelectedData = AllEQCMData_indexed[AllEQCMData_indexed['cycle'].isin([n_cycle])]\n",
    "def sample_sort_key(s):\n",
    "    if \"initial\" in s:\n",
    "        return 0\n",
    "    elif \"at_0\" in s:\n",
    "        return 1\n",
    "    elif \"at_1\" in s or \"at_1V\" in s:\n",
    "        return 2\n",
    "    else:\n",
    "        return 3  # fallback\n",
    "samples = set(SelectedData.index.get_level_values('fname'))\n",
    "samples = [sorted(samples, key=sample_sort_key)[0]]\n",
    "\n",
    "\n",
    "fig, axs = plt.subplots(nrows=3, ncols=1, sharex=True, figsize=[1.3,4])\n",
    "axs[0].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    len_anodic_wave = len(df['df/n 3 (Hz)']) // 2\n",
    "\n",
    "    # Plot current\n",
    "    axs[0].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), df['current (mA)'].iloc[:len_anodic_wave],\n",
    "                       linestyle=lines[i_sample], color='black')\n",
    "    axs[0].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), df['current (mA)'].iloc[len_anodic_wave:],\n",
    "                       linestyle=lines[i_sample], color='black')\n",
    "axs[0].set_ylabel(r'$i_{\\mathrm{geo}} \\ \\mathrm{(mA \\ cm^{-2}})$', fontsize=7)\n",
    "axs[0].set_ylim(bottom = -0.08)\n",
    "\n",
    "ovt_keys_f = SelectedData.keys()[4::2]\n",
    "axs[1].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    for i_ovt, ovt_key in enumerate(ovt_keys_f):\n",
    "        axs[1].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), (df[ovt_key]-df[ovt_key].iloc[0]).iloc[:len_anodic_wave],\n",
    "                           linestyle=lines[i_sample], color=cm.gray(i_ovt*80), alpha = 0.4)\n",
    "        axs[1].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), (df[ovt_key]-df[ovt_key].iloc[0]).iloc[len_anodic_wave:],\n",
    "                           linestyle=lines[i_sample], color=cm.gray(i_ovt*80), alpha=0.4)\n",
    "axs[1].set_ylabel(r\"$\\Delta f/n$ (Hz)\", fontsize=7)\n",
    "\n",
    "ax2 = axs[1].twinx()\n",
    "sec_axs = ax2\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    SauerbreyMass = CalcSauerbreyMass(df['df/n 3 (Hz)'] - df['df/n 3 (Hz)'].iloc[0])\n",
    "    ax2.plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), SauerbreyMass[:len_anodic_wave],\n",
    "                    linestyle=lines[i_sample], color='darkred')\n",
    "    ax2.plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), SauerbreyMass[len_anodic_wave:],\n",
    "                    linestyle=lines[i_sample], color='darkred')\n",
    "ax2.set_ylabel('$\\mathrm{mass_{geo}}$ ($\\mathrm{\\mu g \\ cm^{-2}}$)', fontsize=7)\n",
    "ax2.spines['right'].set_color('darkred')\n",
    "ax2.yaxis.label.set_color('darkred')\n",
    "ax2.tick_params(which='both', labelsize=6, labelright=True, colors = 'darkred', direction = 'in')\n",
    "\n",
    "\n",
    "\n",
    "ovt_keys_g = SelectedData.keys()[5::2]\n",
    "axs[2].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    for i_ovt, ovt_key in enumerate(ovt_keys_g):\n",
    "        if i_sample == 0: \n",
    "            axs[2].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), (df[ovt_key] - df[ovt_key].iloc[0]).iloc[:len_anodic_wave],\n",
    "                            linestyle=lines[i_sample], color=cm.gray(i_ovt*80), label=labels[i_ovt], alpha = 0.4)\n",
    "        else: \n",
    "            axs[2].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), (df[ovt_key] - df[ovt_key].iloc[0]).iloc[:len_anodic_wave],\n",
    "                linestyle=lines[i_sample], color=cm.gray(i_ovt*80), alpha = 0.4)\n",
    "        axs[2].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), (df[ovt_key] - df[ovt_key].iloc[0]).iloc[len_anodic_wave:],\n",
    "                           linestyle=lines[i_sample], color=cm.gray(i_ovt*80), alpha = 0.4)\n",
    "axs[2].set_ylabel(r'$\\Delta \\Gamma/n$ (Hz)', fontsize=7)\n",
    "axs[2].set_xlabel('Potential vs RHE (V)',    fontsize=7)\n",
    "\n",
    "\n",
    "\n",
    "for iax, ax in enumerate(axs):\n",
    "    if iax == 1:\n",
    "        ax.yaxis.set_label_coords(-0.2, 0.55)\n",
    "    else:\n",
    "        ax.yaxis.set_label_coords(-0.2, 0.5) \n",
    "    \n",
    "    ax.margins(x=0.1, y=0.1)\n",
    "    ax.set_xticks([1.0, 1.2, 1.4, 1.6])\n",
    "    ax.yaxis.set_minor_locator(AutoMinorLocator(n = 2))\n",
    "    ax.xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "\n",
    "sec_axs.yaxis.set_label_coords(1.2, 0.5)\n",
    "sec_axs.margins(x=0.1, y=0.1)\n",
    "#fig.legend(bbox_to_anchor=(0.9, 0.05), ncol = 4, fontsize = 13)\n",
    "plt.savefig(fname=f\"result_cycle{n_cycle}_left.tif\", dpi=600, pil_kwargs={\"compression\": \"tiff_lzw\"}, bbox_inches='tight', transparent = True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61282c19",
   "metadata": {},
   "source": [
    "## Plot of the Single Measurement as Figure 1 (Right)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "16965105",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:86: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:106: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:86: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:106: SyntaxWarning: invalid escape sequence '\\m'\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3083076582.py:86: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs[2].set_ylabel('Mass per electron \\n ($\\mathrm{g \\ mol^{-1}}$)', fontsize=7)\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3083076582.py:106: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs[1].set_ylabel('$d/dt(\\mathrm{mass_{geo}})$ \\n ($\\mathrm{ ng \\ cm^{-2} \\ s^{-1}}$)', fontsize=7)\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3083076582.py:63: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  rate = np.abs((np.roll(SauerbreyMass, -1) - SauerbreyMass) / (time[1] - time[0])/1000)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e4b571d6f29348ad898ee6a3177043a5",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=130.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "from matplotlib import cm\n",
    "from scipy.ndimage import gaussian_filter1d\n",
    "\n",
    "n_cycle = 3\n",
    "\n",
    "def convert_potential(E_old, pH=13, Eref_old = 0.165): \n",
    "    E_new = E_old + Eref_old + 0.059*pH\n",
    "    return E_new\n",
    "\n",
    "def CalcSauerbreyMass(df_by_n: np.ndarray, Filter: bool = True) -> np.ndarray: \n",
    "    Zq = 8.8e6\n",
    "    f0 = 5e6\n",
    "    MassDensity = -df_by_n * Zq / (2*f0**2) * 1e5  # conversion of kg/m2 in ug/cm2\n",
    "    return gaussian_filter1d(MassDensity, 150, axis=0) if Filter else MassDensity\n",
    "\n",
    "def discard_points(y: np.ndarray, trsh: int) -> np.ndarray: \n",
    "    y[np.abs(y) > trsh] = np.nan\n",
    "    return pd.Series(y).interpolate().to_numpy()\n",
    "\n",
    "labels = ['15 MHz', '25 MHz', '35 MHz', '45 MHz']\n",
    "lines  = ['-', '--', '-']\n",
    "\n",
    "SelectedData = AllEQCMData_indexed[AllEQCMData_indexed['cycle'].isin([n_cycle])]\n",
    "def sample_sort_key(s):\n",
    "    if \"initial\" in s:\n",
    "        return 0\n",
    "    elif \"at_0\" in s:\n",
    "        return 1\n",
    "    elif \"at_1\" in s or \"at_1V\" in s:\n",
    "        return 2\n",
    "    else:\n",
    "        return 3  # fallback\n",
    "\n",
    "\n",
    "\n",
    "samples = set(SelectedData.index.get_level_values('fname'))\n",
    "samples = [sorted(samples, key=sample_sort_key)[0]]\n",
    "fig, axs = plt.subplots(nrows=3, ncols=1, sharex=True, figsize=[1.3,4])\n",
    "axs[0].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    \n",
    "    df = SelectedData.loc[(sample)]\n",
    "    len_anodic_wave = len(df['df/n 3 (Hz)']) // 2\n",
    "\n",
    "    # Plot current\n",
    "    axs[0].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), df['current (mA)'].iloc[:len_anodic_wave],\n",
    "                       linestyle=lines[i_sample], color='black')\n",
    "    axs[0].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), df['current (mA)'].iloc[len_anodic_wave:],\n",
    "                       linestyle=lines[i_sample], color='black')\n",
    "axs[0].set_ylabel(r'$i_{\\mathrm{geo}} \\ \\mathrm{(mA \\ cm^{-2}})$', fontsize=7)\n",
    "\n",
    "\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    SauerbreyMass = CalcSauerbreyMass(df['df/n 3 (Hz)'] - df['df/n 3 (Hz)'].iloc[0])\n",
    "    time = df['time (s)']\n",
    "\n",
    "    rate = np.abs((np.roll(SauerbreyMass, -1) - SauerbreyMass) / (time[1] - time[0])/1000)\n",
    "    MPE = 96485 * rate / (df['current (mA)'] / 1.17)\n",
    "    potential = df['potential (V)'].values\n",
    "\n",
    "    # Identify the index of the turning point (max potential)\n",
    "    turning_idx = np.argmax(potential)\n",
    "\n",
    "    # Split forward and backward scan\n",
    "    fwd_pot = potential[:turning_idx+1]\n",
    "    fwd_MPE = MPE[:turning_idx+1]\n",
    "    bwd_pot = potential[turning_idx:]\n",
    "    bwd_MPE = MPE[turning_idx:]\n",
    "\n",
    "    # Apply masking\n",
    "    fwd_mask = fwd_pot >= 0.145  # Keep data from 0.14 V onward\n",
    "    bwd_mask = (bwd_pot <= 0.22) & (bwd_pot >= 0.1)\n",
    "\n",
    "    # Plot masked data\n",
    "    axs[2].plot(convert_potential(fwd_pot[fwd_mask]), fwd_MPE[fwd_mask], linestyle=lines[i_sample], color='darkred', linewidth = 0.75)\n",
    "    axs[2].plot(convert_potential(bwd_pot[bwd_mask]), bwd_MPE[bwd_mask], linestyle=lines[i_sample], color='darkred', linewidth = 0.75)\n",
    "    axs[2].plot(convert_potential(fwd_pot), fwd_MPE, linestyle=lines[i_sample], color='darkred', linewidth = 0.75, alpha = 0.3)\n",
    "    axs[2].plot(convert_potential(bwd_pot), bwd_MPE, linestyle=lines[i_sample], color='darkred', linewidth = 0.75, alpha = 0.3)\n",
    "\n",
    "axs[2].set_ylabel('Mass per electron \\n ($\\mathrm{g \\ mol^{-1}}$)', fontsize=7)\n",
    "\n",
    "axs[2].tick_params(which='both', labelsize=6, direction = 'in')\n",
    "axs[2].set_ylim(bottom = -99, top = 99)\n",
    "\n",
    "\n",
    "axs[2].set_xlabel('Potential vs RHE (V)', fontsize=7)\n",
    "\n",
    "\n",
    "axs[1].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    SauerbreyMass = CalcSauerbreyMass(df['df/n 3 (Hz)'] - df['df/n 3 (Hz)'].iloc[0])\n",
    "    time = df['time (s)'].to_numpy()\n",
    "    rate = (np.roll(SauerbreyMass, -1) - SauerbreyMass) / (time[1] - time[0])*1000\n",
    "    rate_clean = discard_points(rate[5:-5], 20)\n",
    "    axs[1].plot(convert_potential(df['potential (V)'].iloc[5:-5].iloc[:len_anodic_wave]), rate_clean[:len_anodic_wave],\n",
    "                       linestyle=lines[i_sample], color='darkred')\n",
    "    axs[1].plot(convert_potential(df['potential (V)'].iloc[5:-5].iloc[len_anodic_wave:]), rate_clean[len_anodic_wave:],\n",
    "                       linestyle=lines[i_sample], color='darkred')\n",
    "axs[1].set_ylabel('$d/dt(\\mathrm{mass_{geo}})$ \\n ($\\mathrm{ ng \\ cm^{-2} \\ s^{-1}}$)', fontsize=7)\n",
    "for ax in axs:\n",
    "    ax.yaxis.set_label_coords(-0.3, 0.5)\n",
    "    ax.set_xlim(left = 0.95, right=1.55)\n",
    "    ax.margins(x=0.1, y=0.1)\n",
    "    ax.set_xticks([1.0, 1.2, 1.4])\n",
    "    ax.yaxis.set_minor_locator(AutoMinorLocator(n = 2))\n",
    "    ax.xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "#fig.legend(bbox_to_anchor=(0.9, 0.05), ncol = 4, fontsize = 13)\n",
    "axs[0].set_ylim(bottom = -0.04, top=0.025)\n",
    "\n",
    "plt.savefig(fname=f\"result_cycle{n_cycle}_right.tif\", dpi=600, pil_kwargs={\"compression\": \"tiff_lzw\"}, bbox_inches='tight', transparent = True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eba21b97",
   "metadata": {},
   "source": [
    "## Compare Samples 2x2 Plot (As Figure 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "afbbf6f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:68: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:98: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:68: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:98: SyntaxWarning: invalid escape sequence '\\m'\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/4090277336.py:68: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs[0,1].set_ylabel('$\\mathrm{mass_{geo}}$ \\n ($\\mathrm{\\mu g \\ cm^{-2}}$)', fontsize=7)\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/4090277336.py:98: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs[1,0].set_ylabel('$d/dt(\\mathrm{mass_{geo}})$ \\n ($\\mathrm{ ng \\ cm^{-2} \\ s^{-1}}$)', fontsize=7)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "748c98c836d04e63b67528822b68c52e",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=350.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "from matplotlib import cm\n",
    "from scipy.ndimage import gaussian_filter1d\n",
    "\n",
    "def convert_potential(E_old, pH=13, Eref_old = 0.165): \n",
    "    E_new = E_old + Eref_old + 0.059*pH\n",
    "    return E_new\n",
    "\n",
    "\n",
    "n_cycle = 3\n",
    "\n",
    "def CalcSauerbreyMass(df_by_n: np.ndarray, Filter: bool = True) -> np.ndarray: \n",
    "    Zq = 8.8e6\n",
    "    f0 = 5e6\n",
    "    MassDensity = -df_by_n * Zq / (2*f0**2) * 1e5  # conversion of kg/m2 in ug/cm2\n",
    "    return gaussian_filter1d(MassDensity, 150, axis=0) if Filter else MassDensity\n",
    "\n",
    "def discard_points(y: np.ndarray, trsh: int) -> np.ndarray: \n",
    "    y[np.abs(y) > trsh] = np.nan\n",
    "    return pd.Series(y).interpolate().to_numpy()\n",
    "\n",
    "\n",
    "\n",
    "labels = ['Pristine', '1 h at 1.73 V', '1 h at 1.93 V']\n",
    "lines  = ['-', '-', '-']\n",
    "\n",
    "SelectedData = AllEQCMData_indexed[AllEQCMData_indexed['cycle'].isin([n_cycle])]\n",
    "def sample_sort_key(s):\n",
    "    if \"initial\" in s:\n",
    "        return 0\n",
    "    elif \"at_0\" in s:\n",
    "        return 1\n",
    "    elif \"at_1\" in s or \"at_1V\" in s:\n",
    "        return 2\n",
    "    else:\n",
    "        return 3  # fallback\n",
    "\n",
    "samples = set(SelectedData.index.get_level_values('fname'))\n",
    "samples = sorted(samples, key=sample_sort_key)\n",
    "fig, axs = plt.subplots(nrows=2, ncols=2, sharex=True, figsize=[3.5,2.5], constrained_layout = True)\n",
    "axs[0,0].tick_params(which='both', direction=\"in\", labelsize=7)\n",
    "def colors(i):\n",
    "    colors = cm.YlGnBu_r((i)*90)#cm.PuRd_r((i)*90)\n",
    "    return colors\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    len_anodic_wave = len(df['df/n 3 (Hz)']) // 2\n",
    "\n",
    "    # Plot current\n",
    "    axs[0,0].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), df['current (mA)'].iloc[:len_anodic_wave],\n",
    "                       linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1, label=labels[i_sample])\n",
    "    axs[0,0].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), df['current (mA)'].iloc[len_anodic_wave:],\n",
    "                       linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "axs[0,0].set_ylabel(r'$i_{\\mathrm{geo}} \\ \\mathrm{(mA \\ cm^{-2}})$', fontsize=7)\n",
    "\n",
    "ovt_keys_f = [SelectedData.keys()[4::2][0]]\n",
    "axs[0,1].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    SauerbreyMass = CalcSauerbreyMass(df['df/n 3 (Hz)'] - df['df/n 3 (Hz)'].iloc[0])\n",
    "    axs[0,1].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), SauerbreyMass[:len_anodic_wave],\n",
    "                    linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "    axs[0,1].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), SauerbreyMass[len_anodic_wave:],\n",
    "                    linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "axs[0,1].set_ylabel('$\\mathrm{mass_{geo}}$ \\n ($\\mathrm{\\mu g \\ cm^{-2}}$)', fontsize=7)\n",
    "axs[0,1].tick_params(which='both', labelsize=6, direction = 'in')\n",
    "\n",
    "\n",
    "\n",
    "ovt_keys_g = [SelectedData.keys()[5::2][0]]\n",
    "axs[1,1].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    for i_ovt, ovt_key in enumerate(ovt_keys_g):\n",
    "        axs[1,1].plot(convert_potential(df['potential (V)'].iloc[:len_anodic_wave]), (df[ovt_key] - df[ovt_key].iloc[0]).iloc[:len_anodic_wave],\n",
    "                            linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "        axs[1,1].plot(convert_potential(df['potential (V)'].iloc[len_anodic_wave:]), (df[ovt_key] - df[ovt_key].iloc[0]).iloc[len_anodic_wave:],\n",
    "                           linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "\n",
    "axs[1,1].set_ylabel(r'$(\\Delta \\Gamma/n)_{15 \\ \\mathrm{MHz}}$ (Hz)', fontsize=7)\n",
    "axs[1,1].set_xlabel('Potential vs RHE (V)', fontsize=7)\n",
    "axs[1,0].set_xlabel('Potential vs RHE (V)', fontsize=7)\n",
    "\n",
    "axs[1,0].tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    SauerbreyMass = CalcSauerbreyMass(df['df/n 3 (Hz)'] - df['df/n 3 (Hz)'].iloc[0])\n",
    "    time = df['time (s)'].to_numpy()\n",
    "    rate = (np.roll(SauerbreyMass, -1) - SauerbreyMass) / (time[1] - time[0])*1000\n",
    "    rate_clean = discard_points(rate[5:-5], 20)\n",
    "    axs[1,0].plot(convert_potential(df['potential (V)'].iloc[5:-5].iloc[:len_anodic_wave]), rate_clean[:len_anodic_wave],\n",
    "                       linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "    axs[1,0].plot(convert_potential(df['potential (V)'].iloc[5:-5].iloc[len_anodic_wave:]), rate_clean[len_anodic_wave:],\n",
    "                       linestyle=lines[i_sample], color=colors(i = i_sample), alpha = 1)\n",
    "axs[1,0].set_ylabel('$d/dt(\\mathrm{mass_{geo}})$ \\n ($\\mathrm{ ng \\ cm^{-2} \\ s^{-1}}$)', fontsize=7)\n",
    "\n",
    "for ax in np.ravel(axs):\n",
    "    ax.margins(x=0.1, y=0.1)\n",
    "    ax.set_xticks([1.0, 1.2, 1.4, 1.6])\n",
    "    ax.yaxis.set_minor_locator(AutoMinorLocator(n = 2))\n",
    "    ax.xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[0,0].legend( fontsize = 6, frameon = False, handlelength=0.75)\n",
    "plt.savefig(fname=f\"result_{n_cycle}_conditioning.tif\", dpi=600, pil_kwargs={\"compression\": \"tiff_lzw\"}, bbox_inches='tight', transparent = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a0df705",
   "metadata": {},
   "source": [
    "## Check the MPE\n",
    "the differential MPE suffers from poles (division by zero)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "494c7915",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:51: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:51: SyntaxWarning: invalid escape sequence '\\m'\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/398479949.py:51: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs.set_ylabel('Mass per electron ($\\mathrm{g \\ mol^{-1}}$)', fontsize = 7)\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/398479949.py:30: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
      "  rate = np.abs((np.roll(SauerbreyMass, -1) - SauerbreyMass) / (time[1] - time[0])/1000)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "71fe99c33dd947cd83a67c63ca0493a1",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img src='data:image/png;base64,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' width=170.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import AutoMinorLocator\n",
    "\n",
    "labels = ['Pristine', '1 h at 1.73 V', '1 h at 1.93 V']\n",
    "\n",
    "def colors(i):\n",
    "    colors = cm.YlGnBu_r((i)*90)#cm.PuRd_r((i)*90)\n",
    "    return colors\n",
    "\n",
    "def sample_sort_key(s):\n",
    "    if \"initial\" in s:\n",
    "        return 0\n",
    "    elif \"at_0\" in s:\n",
    "        return 1\n",
    "    elif \"at_1\" in s or \"at_1V\" in s:\n",
    "        return 2\n",
    "    else:\n",
    "        return 3  # fallback\n",
    "\n",
    "samples = set(SelectedData.index.get_level_values('fname'))\n",
    "samples = [sorted(samples, key=sample_sort_key)[0]]\n",
    "\n",
    "fig, axs = plt.subplots(figsize=[1.7,1.7])\n",
    "for i_sample, sample in enumerate(samples):\n",
    "    df = SelectedData.loc[(sample)]\n",
    "    SauerbreyMass = CalcSauerbreyMass(df['df/n 3 (Hz)'] - df['df/n 3 (Hz)'].iloc[0])\n",
    "    time = df['time (s)']\n",
    "\n",
    "    rate = np.abs((np.roll(SauerbreyMass, -1) - SauerbreyMass) / (time[1] - time[0])/1000)\n",
    "    MPE = 96485 * rate / (df['current (mA)'] / 1.17)\n",
    "    potential = df['potential (V)'].values\n",
    "\n",
    "    # Identify the index of the turning point (max potential)\n",
    "    turning_idx = np.argmax(potential)\n",
    "\n",
    "    # Split forward and backward scan\n",
    "    fwd_pot = potential[:turning_idx+1]\n",
    "    fwd_MPE = MPE[:turning_idx+1]\n",
    "    bwd_pot = potential[turning_idx:]\n",
    "    bwd_MPE = MPE[turning_idx:]\n",
    "\n",
    "    # Apply masking\n",
    "    fwd_mask = fwd_pot >= 0.142  # Keep data from 0.14 V onward\n",
    "    bwd_mask = (bwd_pot <= 0.22) & (bwd_pot >= 0.1)\n",
    "\n",
    "    # Plot masked data\n",
    "    axs.plot(convert_potential(fwd_pot[fwd_mask]), fwd_MPE[fwd_mask], color = colors(i_sample), label=f\"{labels[i_sample]}\")\n",
    "    axs.plot(convert_potential(bwd_pot[bwd_mask]), bwd_MPE[bwd_mask], color = colors(i_sample))\n",
    "\n",
    "axs.set_ylabel('Mass per electron ($\\mathrm{g \\ mol^{-1}}$)', fontsize = 7)\n",
    "axs.tick_params(which='both', direction=\"in\", labelsize=6)\n",
    "for ax in np.ravel(axs):\n",
    "    ax.margins(x=0.17, y=0.17)\n",
    "for label in axs.get_xticklabels():\n",
    "    label.set_horizontalalignment('right')\n",
    "axs.set_xlabel('Potential vs RHE (V)', fontsize=7)\n",
    "ax.yaxis.set_minor_locator(AutoMinorLocator(n = 2))\n",
    "ax.xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "fig.legend(bbox_to_anchor=(1, 0.5), loc=\"center left\", ncol = 1, fontsize = 6, frameon = False)\n",
    "plt.savefig(fname=f\"MPE.tif\", dpi=600, pil_kwargs={\"compression\": \"tiff_lzw\"}, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2da8af37",
   "metadata": {},
   "source": [
    "# Pseudocapacitive Temkin analysis and MPE modeling\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9ab9fa5f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:209: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:232: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:209: SyntaxWarning: invalid escape sequence '\\m'\n",
      "<>:232: SyntaxWarning: invalid escape sequence '\\m'\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3875835699.py:209: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs[2].set_ylabel('Fractional conversion $\\mathrm{\\\\theta}$')\n",
      "/var/folders/f2/krn3py8536556jbm969hx5380000gn/T/ipykernel_34848/3875835699.py:232: SyntaxWarning: invalid escape sequence '\\m'\n",
      "  axs[0].set_ylabel('Fractional conversion $\\mathrm{\\\\theta}$')\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[Fit Statistics]]\n",
      "    # fitting method   = least_squares\n",
      "    # function evals   = 21\n",
      "    # data points      = 2399\n",
      "    # variables        = 2\n",
      "    chi-square         = 0.44125066\n",
      "    reduced chi-square = 1.8408e-04\n",
      "    Akaike info crit   = -20629.6777\n",
      "    Bayesian info crit = -20618.1121\n",
      "[[Variables]]\n",
      "    E0:  1.39120585 +/- 1.3714e-04 (0.01%) (init = 1.399952)\n",
      "    g:   0.66269145 +/- 0.00972043 (1.47%) (init = 1)\n",
      "[[Correlations]] (unreported correlations are < 0.100)\n",
      "    C(E0, g) = -0.9105\n",
      "[[Model]]\n",
      "    Model(mpe_model)\n",
      "[[Fit Statistics]]\n",
      "    # fitting method   = least_squares\n",
      "    # function evals   = 60\n",
      "    # data points      = 2399\n",
      "    # variables        = 4\n",
      "    chi-square         = 101510.498\n",
      "    reduced chi-square = 42.3843417\n",
      "    Akaike info crit   = 8992.51947\n",
      "    Bayesian info crit = 9015.65070\n",
      "    R-squared          = 0.75234377\n",
      "[[Variables]]\n",
      "    lam:      21886.8172 +/- 1125.03423 (5.14%) (init = 10000)\n",
      "    theta_c:  0.44835486 +/- 0.00240293 (0.54%) (init = 0.5)\n",
      "    M_lo:     30.0000000 +/- 0.63675247 (2.12%) (init = 30)\n",
      "    dM:       33.0910906 +/- 0.59023657 (1.78%) (init = 30)\n",
      "[[Correlations]] (unreported correlations are < 0.100)\n",
      "    C(lam, M_lo)     = +0.9359\n",
      "    C(M_lo, dM)      = -0.8214\n",
      "    C(lam, dM)       = -0.6467\n",
      "    C(lam, theta_c)  = -0.2661\n",
      "    C(theta_c, M_lo) = -0.2568\n",
      "    C(theta_c, dM)   = +0.2291\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cf0d6e6a435d41f7b7ec0d18d2545c06",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' 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       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3819a6b0e38f4da2aec228c6ba0f711d",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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8zjrrIuLi5OXbkHqF69OsePH7diRNYhyxWpOLJskYylGt9TZp0/D6dOQa1a0KEDODtbOyKbYcznjVVmsrWUkSNHEhISIlsYLei7AQO00ly+g+1V7kGZyi4kJERmuTBAwTkvhBBkZWVZKRrrkeWKVBxZtkiSge7ehSFDwN8fnn0WOneGwEBISLB2ZHbNoSv4MTExxMXFMW7cOGuHUiZ0UihYpbH9LjA/f92WKvegfNwVFxdHTEyMtUOxG23btmXixIlcu3aNq1ev8tprr9G2bVtrh2VxslyRiiPLFkkywL170KMHrF+vvT8xEcLC4Nw5q4TlCIzqogPKHM1///23Vqte7dq1TRKUqZT5x10W1KZGDXbwOFvOF8Cc/HVbq9yDbXWvsBeLFi1i8uTJtGrVCoVCQf/+/fn444+tHZbFyXJFKo4sWyTJABMngmrGek9PmDABduyAkychLQ0iI5XrlSpZN047ZFQFf9WqVbz++uuUL18eJyflQwCFQsHNmzdNGpxkJx494pN//kHVO3sX8Er+epMmTawUlGRqbm5ufPXVV9YOQ5IkSXIEmzfDN98o111dYf9+Zdec6dOhUydlf/zz52HOHJg7t5gLSboY1UVnzpw5HD9+nNTUVG7dusWtW7fKdOX+rbfeIiAgAIVCweXLlwH48MMPSzjLcSytVIk2+euXgWEos+UAcqCZg/n111/59ttv+eabb9SLZB/GjBnDtm3bAOWkZcVZsmSJ1viKko6XpLLuypUrhIeH07RpUwIDA3nw4AHHjh0jICAAPz8/3n//fWuHaFuysuCttx5vf/qpsnIPysr+mjWgmj198WJITrZ8jHbOqAp+9erVady4saljsVurVq3izJkzCCFo0KABUHYq+CNdXXktfz0TiAJU82TaYtccyXgTJkzg2WefZcOGDWzdupWtW7eqK4yS9eTm5hp8zr59+4p9vWAFv6TjJamsGzNmDO+//z7nzp3jwIEDVKxYkVdffZXvvvuO33//nR07dnDmzBlrh2k7PvsMLl1SroeFwYgR2q83bQqvvqpcz8yULfhGMKqC/8wzz7BkyRJu3rxJenq6erE1iYmJxMfHc+PGDbO9x8CBA0lLS6Nly5a0bt2as2fPMnPmTO7cuUNwcDDjx48323tbXUoKi+7fV29OAk7lr9t65f7GjRvEx8fLJwwG2LNnD+fOnWPjxo2sX7+e9evXs27dOmuHZXGWKFdUrl69SlBQEEOGDMHf35/Ro0eTk5ND3bp1efvtt2nRogU//fQTq1evplWrVjRv3pwpU6aoz589ezaNGzemS5cu/PPPP+r91atXV6/PnTuXwMBAgoKC+Pjjj/nPf/5DcnIy7du3V8/AqzpeCMHkyZNp1qwZwcHB7NmzB1A2cgwZMoTu3bvj5+fHokWaubTKFlm2lD2//fYb5cuXp2PHjgB4enpy8+ZNcnJyCAoKwtnZmWHDhskGEZWsLFi48PH2okWgUBQ+bsYMqFpVub5yJdy+bZn4HIUwgkKhKLQ4OTkZcymziIuLE4B6iY6OLnxQSIgQPj76LyEhRb6fl5eXEEKIzp07izNnzmjtc2TfghD5y2aN37eLi4u1QytRdHS01j0SFxdn7ZBsXseOHUVeXp61w7AaS5crQghx5coVoVAoxPHjx4UQQjz77LNi5cqVok6dOmLZsmVCCCHOnTsnIiMjRXZ2thBCiFGjRolt27aJY8eOidDQUJGZmSmSk5OFu7u72Lp1qxDicfm0fft20aVLF5GZmSmEECI1NVUIIUSdOnXEvXv31HGojl+/fr3o06ePyM3NFVeuXBF16tQRGRkZYuXKlaJx48bi3r17Ii0tTTzxxBPi0aNHRv6m7ZssW8qeTZs2iQEDBoi+ffuKFi1aiLlz54rjx4+LPn36qI9Zt26dePXVV3WerypbvL29hY+Pj9ayaNEiS/0YlrNqlbruIAYMKP7Y1157fOyCBRYJz1YsWrSo0P3g7e2td7li1CDbvLy8Un6tsIxiZ4X7+29ISrJ8UA7iZS8vPs9fTwU0Ewbeu3fPChEZxphZ4cq6Nm3aEBUVxdChQ6mkkdFA1cpbVli6XPHz8yM0NBSAYcOGERsbC8DgwYMB2Lt3L0ePHlUf8/DhQ0JCQrh48SIDBw6kYsWK1KxZky5duhS69p49e3j++eepWFGZ/8rT07PYWH755ReGDx+Ok5MTdevWpVGjRvz+++8AdO/eHRcXFwBq1arFP//8w1NPPWWC34B9kWVL2ZOTk8PBgwc5deoUTzzxBBEREZQvX97g69y6davQPlvsHVEqQsBHHz3e1uyHr8trr8GyZcrzPv0U3nwTnBw6w7taeno6SaX4PDE6TSZAcv6gh1q1apXmMmZTbDq7GjUMu5ihxzuye/eYrfGobCKgevi/ZcsWq4RkKJnKznAnTpwA4LPPPlPvU6XLLEssXa4oNB5dKxQK9XaVKlUAZYPL2LFjiY6O1jpvyZIlWueam+pLAoCzs7NRYwMcgSxbyh4fHx9CQ0PVX2h79+7Nw4cPtSpnSUlJJdaVvL29qaAaWJrPzc3N9AFb0759cPascr1dO+WMtVBsWbUD6AVw7RocOABlZNC/m5sbPj4+WvuysrJ0fhHUxaivQYmJiQQEBKiXwMBAzp8/b8ylrOfECbh+Xf8lv3KjL0f+gFvk5oaqmIoF1uavly9fvsxV9sqSffv2FVp++uknq8Y0cOBAPDw8iIqKUu9LTU1lwIABNGnShKZNm6ozW12+fJnQ0FD8/PwYP368epxISkoK4eHhNGzYkEGDBpGZmWl8QGYoVy5evEh8fDwA33//PU8//bTW6127duX7778nNTUVgJs3b3Ljxg2efvppNm/eTFZWFn///bfOgbLdunVj5cqVPHr0CIDb+V/cXV1ddT6Je/rpp1m7di1CCK5du8bFixdlwgWpzGvVqhU3b94kLS2NvLw8fv75Z0JCQnB2diYhIYHc3FzWrl1Lv379ir3Orl27uH79utaiOabGIaxc+Xh90iRcXV1LbIhYpbmu40mko5oyZUqh+2HXrl16n29UBf+VV15h5syZpKWlkZaWxsyZM5kwYYIxl3JYo0ePJjAw0OEG2f60bBmv569noBxYq6KZdUNyTNnZ2Vy4cIGEhAT1Yk2TJk0qlKpz0qRJDB06lPPnz3PixAlq5LeST58+ndmzZ3Pp0iVSUlLYvn07AB988AGRkZFcvHiR+vXrs2LFCov/HMVp1qwZCxYswN/fHycnJ4YPH671ekBAADNnzqRr164EBQXRp08fbt++TWhoKL169SIwMJDhw4frnHW4d+/ehIWF0bJlS4KDg1m9ejUAY8eOJTw8vNAX9kGDBlG/fn0CAwMZMGAAX3zxhVZ3LUkqi8qVK8e8efPo1KkTQUFBNGzYkL59+7Js2TKeffZZGjVqREREBIGqNJBl1d278MMPynUPDyoNG8Z9jUQdRYkF7uSvRwFV859kurq6milQB2FMx//mzZvrtc9aVANW5OAmE8vLE3s1Bta+qzGQLCoqytrRGUXeK/rbunWrqFGjhqhYsaLw9PQUCoVC1K1b19phiX379onIyEghhBB37twRjRs3LnRMXl6eqFmzpnqQ8KZNm8TLL78shBCiYcOG4s6dO0IIIU6ePCl69Oih832sca9cuXJFhJQwEFeyTbJskfRVZu6VL75Q1x+WadQf9FmWa9Q9RhR4rSwx5F4xqgXf2dmZc+fOqbfPnTuHs7OzMZcyK0umsysLPnj6aVQPx/4ANDP9r1+/3goRGU+msjPcrFmzOHr0KP7+/qSmpvLNN99odY2xBVeuXKF69eqMGDGCFi1a8MYbb5CTk0Nqaiqenp7qR8E+Pj7q/rF3797F3d290P6iRERE4Ovrq7UsXrzYvD+YZNMWL15c6J6IiIiwdliSZFtWrVKvriz6KJ1iNNYLfuooFAp18gHpMaMG2Wo+ihJCcPbsWdasWWPq2EpNlcEgOjqa2bNnWzcYe5ebS9/Dh9Wbb6Kc2ApsP+e9LsuXL+e9996zdhh2xcnJiTp16pCTo5yneOTIkXz88ccGXePevXscPHiQ69evU7lyZZo3b05QUJDJYszJyeHYsWMsW7aMoKAgnnvuOVauXMnAgQNN9h6WzHRRt25d9eBmyXaVNtuFJDm8Cxfg0CEAzgJxRRwWFRWl1WCoapQ5BNwAagIRgAug2blnwIABbNmyRY4D1GBUBb9nz54kJiby66+/AtC2bVutiVNsRbHp7CSDzPD1ZX7++hFgU/66vfa/lansDKdK++br68umTZuoW7cuaWlpep177do13n33XXbu3ElgYCA1atQgMzOT+fPnk5eXx7Rp03jhhRdKHaOPjw/16tUjODgYUBb6+/fv56WXXuL27dsIIVAoFFoZLdzd3dWt+DLThWSM0ma7kCSH9/XX6tWiWu91NRaq9nl5ebHx9m1eBSoBvYGC0ywOGDDALhsczcWgCv6DBw+oWrUq6enpVKxYkU6dOqlfS09Pt7kPuWLT2Un6y8xkwt9/qzff1ngpIyPD8vGYgExlZ7hJkyaRlpbGv//9b4YNG8adO3dYsmSJXueOGjWKN998ky+//JJy5bSLnatXr7J8+XKWLVvGxIkTSxVjzZo1eeKJJ7hy5Qr16tVj//79+Pv7o1AoaNu2Ldu3b6dv376sWbOG5557DoC+ffuyevVqJk6cSExMjF6ZLmS5ImmaMmVKoWwn8fHxhISEWCkiSbIhublcnzcPXyAHKNjfw9PTU50FrCipqanKFJv5WXSiKFzBB6hcubLd1ktMzaA++KppmKtVq4aHh4d6UW3ra9u2bTRu3JiGDRsWylhx7949goOD1Yu7u7u6EjF79mx8fX3Vrx08eNCQ8CUjfVCnDrXz17cDP+evqya1kcqG7t274+HhoZ5E6datW/Ts2VOvc3/++Wf69+9fqHIPym4o8+fPN6py361bNwYPHsyOHTvw9fXlyJEjfPzxx0RGRhIYGEh6ejpjx44FYMGCBURHR9OgQQM8PDzo06cPADNmzGD9+vX4+flx6dIlXnrpJYPjkCTJvty7d48dO3bw+eefs3r1aqtnBHNkfStXxjd/fQeP580BZZeckir3ah07grc3oGzBr6LjkMzMTNkfP59BLfiqXMylmck2JyeHKVOmsG/fPtzd3QkJCWHgwIF4eXkByvzLp06dApSPZurWrcuAAQPU57/99tulbuWTDJCRwZibNwHIA2ZovGQPM9ZKptOjRw91GVDcPk2ZmZk4OTlpdWm5ceOGyZ6e7NmzR+d+XTE1bNiQuLjCPT+9vb05cOCASeIxtatXrxIVFVWqfvizZ8+mevXqNlVumuLnkiRjWKq7oDFUSR8c7QnziOxs9foqjf0KhcKwBB3lysHAgfD551QFBru48LWONJuO2FXnxo0b3Lhxw6DEIKWe7/fu3bucVc1Kpodjx44REBCAj48PLi4u9OrVix9//FHnsUeOHKFGjRrUq1fPqNhktovSm1OvHqq5Nn8AzuSvlzSlvS2SmS6Mk5WVRXp6Orm5udy7d4/09HTS09P566+/ePDgQZHnffzxx/Tu3Zu+ffsyYcIE9WPTESNGWCp0syhL2bkcdbI+c5IZumzbqFGjiIyMJDk5mb1797JmzRp++OEHzp07x65du7h48SLLli2zSmwjR44kJCSE5cuXW+X9zaGaQoEqxUEKsE3jNaMaiyMj1aurihlQO3PmTMOvbcOWL19OSEiIQWMGjargR0REcOfOHe7fv0/z5s3p27cv7777rl7nJicnaw1GKi4t3bp16xg6dKjWvsWLFxMUFMSECRNKnCDh1q1bJCUlaS3mynbhkLKyGPPP44dpczVe0vuRmg1RZbrQXOQguJLNnz+fatWqcfbsWdzd3alWrRrVqlUjMDCw2MLmhx9+4KeffuLHH39k0KBB9OvXj4sXL1owcvOw9IdwVlYWQ4YMwd/fn9GjR5OTk0N0dDStWrWiWbNmvPHGG+pjf/31V9q2bUvz5s0JCwsrdK0PP/yQUaNGkZuby5YtW2jUqBGtWrXixRdf5M033wQgLCyMyZMnExoayurVq1m9ejWBgYE0a9aMhQsXAsoW+NDQUPV133zzTVblp8CrW7cus2fPJjg4mFatWqm/CF26dIlWrVoRFBTEJ598YqbflvUZ80EsWY65uguaQkxMDHFxcYwbN84q729qvr6+DEM5KBaUfe9VbflGt7CHhUG1asr1bdsQ+bNwFzRv3jzjrm+jxo0bR1xcHDExMSUfnM+oCv4///xDtWrV2LFjBwMGDODixYts2rSp5BMNIITghx9+YMiQIep9EyZM4OLFi5w8eZIqVaqUmObQ29sbHx8frcXWBgLbsv+2a8dT+euxwOn8dXtsvYfHmS40F+/8/nxS0aKjo8nLy+Pll18mLy9Pvdy5c4dZs2YVeV5ubq46pWb37t1ZtWoVr7zyChcuXLBU6GZR1IewEPDggWGLPp9xZ8+eZdq0aSQmJpKdnU1MTAyTJk3i+PHjnDlzhj///JNDhw6RlZXFiBEjWLFiBadPn2bjxo1a15k/fz5nz57l66+/Jisri9dff52ffvqJI0eOcPnyZa1jy5cvz4kTJ+jevTuzZ8/mwIEDnDhxgu+++05nN6eCfH19OXXqFL169VKPs5o8eTIzZswgISFBnZHJERnzQSxZh+Z8PrZAlRjEUbrnJCUlMUZjW5U9p1TdZypUAFUihPR0+OmnIscDdujQwfj3sTE1a9akZcuW+Pv7632OURX87Pz+VD///DPdu3enfPnyOr8N61KrVi2tFvui0tL98ssv1KlTB19fX/W+J598EmdnZ5ydnXnhhRc4fvx4se+1a9curl+/rrUUzHQgFSEnhx4a/Zj/rfGSPbbegzLTRcH7YdeuXdYOy2589tlnBh3/0UcfkZKSot729fVl+/bt/Pvf/y7mLNtX1Ifww4fg4mLY8vBhye/n5+enbi0fNmwYv/zyC3v37qV169Y0b96cQ4cOce7cOc6fP0/dunVp1qwZoP1F/PPPP+fkyZOsWrUKJycnfv/9d5o0aYKvry/lypUjUuOxN8DgwYMBOH78OF27dsXT05NKlSoRFRXFL7/8UmLMqnkHQkJCuHr1qvpaqv323k2rOMZ8EEvWMXnyZGuH4LC8vLxoArTN3z6FspHQyanUPcNh0KDH6xs3Fjke8LDG3D1lkVG/6WbNmtGrVy+2bdtGly5deKjPp1S+1q1bc/bsWZKSkrh//z47d+7UmYlDV/cczT6vW7ZsISAgwJjwJT18HxVF/fz13YDqq5TMnFP2dO7cGQAPDw88PT3Vi2q7KB06dKBGjRrq7Q8//JAKFSowZswYc4fsUFQTvajWFQoFkydPZsuWLSQkJDBy5EgeFfGYWqV58+b8/vvv3MwfMF9SC1qVKrryUzxWrlw5rf6zBd+/YsWKgHLWc1U/fs2fQ5Isyc3NjR49etC9e3d69OihXj958qS1Q3NYt2/f1tl6b5JxPT16gKqM2rwZcnNp3769zkMdqRXfUAZX8HNzc6lduzbjxo1j3759VKlShbS0NObPn1/yySg/GBYtWkR4eDjBwcFMnToVLy8vevfuTXJyMqAceLFp0yaiorQnJJ42bRqBgYEEBQURHx/PnDlzDA1f0ocQ+G3Zot7U7MkmM+eUPWvXrgXg1KlTnDx5Ur2otvXl6E9LqlSB+/cNW0qoRwNw8eJFdVag77//nqeffhqFQoGXlxd3795l8+bNADRp0oSrV6+qkx7cvn1bfY02bdqwcOFC+vbtS1paGk2aNOH8+fMkJSWRm5tbqDuPSuvWrdm7dy9paWk8evSIjRs30rFjR5544gmSk5O5d+8e9+/f53//+1+JP0doaChb8suVb7/9tuQfXJJMpFGjRqxbt47//e9//Pjjj/z444/873//U0+IJ5mWQqGgHDA6fzsL+BbUf/+lVqUKqBJk3LoFhw5xKH+W3ILKciu+wTPZOjs7s3//fj788EP1PlV/Zn3179+/0HTCO3bsUK87OTlx/fr1QuetXr3a0HAlYxw8iGp6ljge572311lrpdJRdUVRKBQ88cQT6vsgMzPToEHKjpa2rCCFAqpWNf11mzVrxoIFC0hISKBVq1YMHz6cCxcu0LRpU2rVqkXbtsqH4BUqVCAmJoYXXniBR48e4eXlxU8//aS+To8ePbh79y79+/dn9+7dLFmyhPDwcNzd3WnSpInO8Um1atUiOjqaTp06IYRg9OjR6km+pk2bRosWLahduzaBgYEl/hxLlizh2WefJTo6mq5du5rotyNJJfvf//6Hq6urzv2Saam690WAOgPfVpQZdArW+0pl0CBQNUxs2gSdOtG+fXudFfrBgwcblo7TQSiEEZ+6s2fPpnz58jz//PNaXTZsZQCragbBmJgY/P39HS6nrLltVih4Jn99BMpv3uBYFTTNnLIjR44kLi5Ozk5agtatW/Pzzz+rK/gZGRmEhYXx66+/6nV+ly5dtCqc9sbRypX79+/j4uJCbm4ugwYNYuzYsfTt29faYdk9WbZIhlKVLY5wr6i64m0EdXrMPsCd9u2LbGU3yp078MQTkJ0NtWvD1auQ34VRF0epvxhyrxjVB//9999n1qxZ+Pr6GjWTraU4Yk5Zs7t0CdV37CRA9Z3X2dnZSgGZh0xlZ7isrCytpziVK1cuse+3JkcpYB2lXPnss88IDg6mWbNm1K5dWz2zr1Q6smyxfZo9ECTTUVWuvQFVU0Ey8FO5cqat3IMyVabqSeCff0J+N8YmTZroPFz1ZKEsMaqCr5kqLzc3V/2vrXG0nLKW8FmTJuqbYimPc9aq0h06CpnKznAKhUI9SBPg77//NqjS/umnn5ojLItzlHLlrbfe4tSpUyQmJrJ06VI5CNZEZNli+xx9PJC1jQRUiXC/BjI0ZrI1qQLZdIAiJ5jbsGGDeWKwYQb3wVe5ceMGv//+O2FhYeTk5JCXl6c1Hb0tUKWzk/SUlsao/C9qD4DPrRuNWdl79wpreP3112nXrh2jRo0ClBXd6Ohovc93lLSBslyRiiPLFttnq08TVZVTe7yHNBsIXtTY39qcDTv9+8O4ccoJRTZuhLnK6ThdXFx0ToQaGxtr2nEAFqTZ9U9fRrXgb9iwgbZt26rT3f32228888wzxlxKsiH/8vFBNaJiFZCWv26yke+SXXv++ef58ssvefjwIQ8fPmTlypXqyr6+fv75Z1q3bo2npydubm64urrazNgdyQhCwO3bcPeufrN2SZINsNWnVfba/U/z99keUCUw/0WhoOuECeZ74yefhKefVq6fPw/5ld+isv2p5uGwR8Z0/TOqBX/+/PnEx8fTrVs3QJlj+dq1a8ZcSrIVQjA8I0O9uVTjJXv9xiuZXlhYGGFhYUafP3bsWObOnUvr1q0dblxHmRIfD4sXw/btysFuoPywHTAApk6FRo2sGp4kFcdWW/A1B/Dbi4KTnE7UWH961SrzBzBoEBw8qFzftAnynxSXL19ePSmriubcHfZm3Lhx9O/fXz14Xx9GVfCdnZ3x8vLS2mdr3XMkwzxbty7f5a//DPyev15wLgKp7MrIyGDp0qWcOnWKzMxM9f6icqjr4ubmJu8pe/bwIUyeDF98Ufi1f/6Bzz+HFStgxgyIjoby5QsfJ0lWZqvjgeyt+5+Xl5fW+MsagKp0T3V2xmvIEPMHMXAgvPGGcn3jRnjnHUCZFELXkxovLy9SU1PNH5eJGdNty6guOq6urvzzzz/qX97evXuLndHSWhITE4mPj9eaAVfSrceff6rXV2jsd9TcsTdu3CA+Pt6g/mxl3dixY7l69SqHDx8mPDyca9euUadOHYOuERkZyerVq8nKyjJTlOZXZsuVf/6B9u21K/fu7spZJcPDH8/alZen7AvbqxeUwYnxZNli29LT0/Hx8SE9PV3nIulPczI9gLE8HlzrNW0aWGLunDp1ICR/5p64OCihN0nBmB2aMMLx48dFixYthLu7u+jQoYOoVauWOHnypDGXMou4uDgBqJfo6Ghrh2TTnhswQNxX9qAVd0BUzv+9NWnSxNqhmU10dLTWPRIXF2ftkGxes2bNhBBCBAYGCiGESE9PFx07djToGps3bxYuLi7CyclJODk5CYVCIZycnEweqzmU6XLlxg0hmjQRIr+cEFWqCLFkiRCZmY+PSU8XIjpaiHLlHh/Xtq0Q9+9bLWxrkGWLbVOVOQqFotBirbJIVbbY072ieY8DohyIJNXfvZOTENeuWS6Yf//7cZnz8cfq3e3bty8UJyCioqIsF5uJGXKvGNVFJzQ0lH379nH48GGEELRv355q1aoZ9w3DjOyxP5s1VNqyBdUEnGsAVU98R26BMqY/W1lXuXJlQNnn8sGDB7i6uho0ky3AG2+8wZYtWwgNDbXbPvhlrlzJyFBmqzh/Xrlduzbs3AlNmwKFByz2dHVll7Ozsm/+0aMwfLjy0bmd/n8bSpYtts2e+2HbCl1dX54Faqk2BgxQlhOWMmgQ/OtfyvWNG5XdCIFDhw7pjLWspMw0qoKfmpqKl5cXvXr1MnU8JmVv/dms5SWNddXDd1vscmVK9piGzNo8PT1JS0ujd+/e9OzZk+rVq+Pr62vQNZ544gm6dOlipggto0yVK0Io09AdP67cfuopOHAA6talQ4cOOqeF333vHs1RjuVxB4iNhXffVaewc3SybLEvycnJANSqVauEIyWg0PhLAAXwtuYOVZ94S/H3hyZNlI0Qv/yi7E745JOA8nOrTHXL0WBUH/xGjRoxePBgduzYIb8N27lW5cvTKn89DjiVv26Pg1Ak89q+fTseHh7MmTOHCRMm0K1bN3744QeDrtG/f3+WLVvGzZs3TdLvdeDAgXh4eGgN3A0LC6NJkyYEBwcTHBxMRn52qJSUFMLDw2nYsCGDBg1SDxTOzMxk0KBBNGzYkPDwcFJSUoyOx+HExMDq1cr1KlVg61aoWxeFQqGzcq+SAETyeKI85s+HffvMHKwk6S8xMZGAgAD1EhgYyHnVUyqpSLoqy/2BpqqNp5+Gjh0tGZKSatIrIZSNCvmKqsuUhcQwRlXw//zzT/r06cOHH35InTp1mDFjBhcuXDB1bJIFPKcxQ61qcG15mflC0sHZ2ZkHDx5w6NAh6taty/PPP29wDvt//etfvP7669SoUQMPDw+qVauGh4eH0TFNmjSJb775ptD+DRs2cOrUKU6dOqXuWvTBBx8QGRnJxYsXqV+/PitWKO/4FStWUL9+fS5evEhkZCQffPCB0fE4lL/+gtdeU28OefgQRXCw3jnE9wKzVBtCwKhRynz5kmQDXnnlFWbOnElaWhppaWnMnDmTCebM2e4Aivrbn6G1MUPnMWanOavtunVaLzk5Fa7qFkyh6YiMquBXrVqVMWPGsH//fn7++WdSU1MdZpbKssTH0xNVD9GHoE6Tac8ZTiTz2bt3L/Xr1+e1115j4sSJNGjQgH0Gtsrm5eWpl9zcXPW/xgoLC8PV1VWvY2NjY9UTc40cOZKtW7cWu79MEwLGjlVXyFcDxuTT+hBlRR+ApCSYOdM08UlSKaWlpTF8+HD19rBhw0hLSyvmjLKtqBbvPkAb1Ubz5srsWdbQsiXUr69c37sXNDIDbtq0yToxWZlRFXxQfvv54YcfmDhxIps3b7bJb75lNp2dnsLT0lC1na4HylLbmkxlZ7jJkycTGxvLyZMnOXnyJLGxsbz++uvWDkun4cOH06JFCxYvXqzed/fuXdzd3QHw8fEhKSkJUPbB9fHxAaBatWrcUU3cVISIiAh8fX21Fs33cQibN8Pu3QBcB4z9XxbAC8AD1Y5PP4Vjx0obnc1ZvHhxoXsiIiLC2mFJxXB2dubcuXPq7XPnzll94L8t11l0tXg7AZ/kPyEFlGNtrDVLsEIBY8Yo14UAjSe7RU3WWVkzdhtnTJ3FqAr+a6+9xlNPPcWKFSsYPXo0169fZ9myZcZcyqzsddpnSxg8eLDOwbVlZRIiY6Z9LuucnJxo00bdVmPUbLRbt27VqkCnpaWxfft2U4UIwJo1a0hISGD//v1s2bLF5Ne/desWSUlJWotD5c/OyOCaRjnwOnCnhFPeeecdhBC4uLgUeu1P4F3VhhAwYYIyV74DSU9PL3RPGJphSrKsefPm0alTJ7p06UKXLl3o3Lkz8+fPt2pMtlpnKaprziigfv4YJ9q2VU46ZU2jRz/+grFqlbK8yaerbNKcsNHWGVNnMSqLTs2aNTlx4oTBGTQsrcylszPA6Q0bCMtfPw8cyl931ImtCpKp7AzXo0cPVq1axejRowFYvXo1PXr0MOgas2bN4tSpU+rtatWqMWvWLPr06WOyOFWt8e7u7gwZMoTjx4/Tp08f3N3d1a34SUlJ6qwZtWrVIikpierVq3Pnzp0SU/56e3sXelxt6FgEWzbfy4sZ+RXw/wHFPdyuVq0ar7zyCnPzM+Tcy5/YqmCF4P9QVgaCAeLj4dtvwYH+7tzc3NT3nUpWVpas5Nuwnj17kpiYyK+//gpA27ZtqV69ulVjssU6S7lyuquJLsAqHx9l1zuABQus13qvUrs2dO0Ke/bA5ctw8CB06gQoyyZ9xw/ZImPqLEZV8N955x3y8vJITk4mR2OQZm1L5j3VQ5lKZ2egFzTWVYNrC35AOTKZys5wK1as4O7du4wbNw5QPrJ1d3fniy++QKFQGJWKTKFQlKoPfkE5OTncuXOH6tWrk5WVxc6dO9VfSPr27cvq1auZOHEiMTEx9OvXT2t/8+bNiYmJoW/fvsW+x65duxyyXHF1daXq/fv8kb+dDUzScZzQaBUrihBC68M0F5gC/JS/fW3UKGZs3Mi3GzeWLmgbMWXKFKZMmaK1Lz4+nhDVDJuSTfL29i7x792SbLHOUlT5fKpfP2VWLYB+/dQVaat7/nllBR/gyy9LjMvV1VXdMGHLjKmzGFXB//rrr3nttdcoX768enSyQqHg5s2bxlxOsjDXSpW4mL+eDah6ql2/ft1KEUn2QLPl3Viurq4cPnyY9u3bA8qJSPQdJKtLt27dOH36NA8ePMDX15fvv/+e119/nezsbHJzc+nXr5+629mMGTOIiopiyZIlNGvWjDlz5gAwduxYnn32Wfz8/PDx8Skzk6Co+Pr6qscjzAWq5O//DCjY21Ofyr3msZqV/H3ADqA3UAfw3bQJhUJBVFRUmXlyKNmOn3/+mTfffJNLly6Rk5Ojvl8dqrtdKRXV4h2iUNBA1fWxcmX4v/+zYFQlGDgQqlVTTrS3di0sXAhPPAHozol///59y8doIUZV8N9//32OHz9O48aNTR2PZAHdHj2iRv76FuAWutNISZKmOnXqlPoaH374IQMHDqRJkyYAXLx4sVQZDvaoWmo0xMXF6TzW29ubAwcOFNpfuXJlNm/ebHQM9kyzcv8UMC5//wOUlX1NhlTuNc/RrCRMA3oCzihT6y1HmdJ08ODBspIvWdTYsWOZO3euUWOJyoIOHTro3F8RONGsGZw5o9zx7rtQr57lAitJ5crw0kvw0UeQlQXLl8MsZcLe1NRUu+6mYyijKvjVq1eXlXs71aFDB97R2FYNri2raaQk/d28eZPo6GhOnz6tNTgpPj5e72u0a9eOxMREjhw5AkD79u1L7PMumY+qcg/KnPUV89c/AVTPYytVqqSeLMwYzs7O6sf8v6F8Yvg84AG8hvKLRFl7aiJZn5ubW5lJKmGMoiayO9e3L2zbptwIDIQCXdNswsSJsHixcjD/p5/C9OlQzMRWvr6+DtmDwahm22eeeYYlS5aYbDZKc7HllFPW8ufhw6iSt10DVO2fRaWRclQyTabhXnzxRerWrUtKSgrvvfcetWrVMmpwrIeHB71796Z37952Wbl3lHJFs9WyAcpKNyjT5S7UOK40lXtQjovQfK9/A6qRW1MAVQctW0/aoC9ZttiHyMhIVq9eLed90aGoJ/rPAPVVlfuKFZWD5W1xRtg6deCZZ5Trf/+tNfGVp6dnocM1GzociVEV/JkzZzJlyhRq1KhBtWrVSj0bpbnYasopaxqD8vE4wFdAHmVrcK2KTJNpuL/++ovp06dTsWJF+vXrx8aNG3V2kXF0jlCuxMbGkqeRqnIGjx/nLgLSUJYLxnTL0UXVx9nT05M/gJj8/Z4oW/FB+SE7ePBgk7yfNcmyxT74+/vzyiuvULlyZZydnXFycpJddfLp+rtvDmyqWvXxjkWLoFkzywVlqEkaKQLmzoX8p4ipqalWCsjyjKrga85GqTkrpa2JiYkhLi5OnfWjrKtYvjwv5q/nASvz1x3x0VRJxo0bR1xcHDExMSUfLAGPZzKsVKkSqamplCtXjpSUFCtHZXn2Xq7ExsYyYMAA9XYtlCksQZnvfgnKD3hzlAupqakIIYpsxXeErjqybLEPb7zxBlu2bCEtLY309HTu3btX6p4IDx8+pE6dOrz55psAHDt2jICAAPz8/Hj//fdNEbbZ6fqS8xSwzckJHuRPWTdsGLzyimUDM1THjvD008r18+fh+++LPbw0yR5sValGViYnJ5OcnGyqWExOlXJKpkNU6pyTQ9389d3AXygra2VRzZo1admyJf7+/tYOxW40atSI1NRURo4cSZs2bQgNDS2TaQDtvVzRrNwDTAZUD9k/BdJN1GpfnEtCsCZ/3QvQnAe9qMF99kKWLfbhiSeeoEuXLri5uVG1alX1Uhpz586lbdu26u1XX32V7777jt9//50dO3ZwRjUw1YblFZiEzhdlBixf1f42beCrr6yf874kCgXMnv14+/331a34ugbaOmI2HaMq+ImJiQQEBKiXwMBAzp8/r/f527Zto3HjxjRs2JAVK1YUej0sLIwmTZoQHBxMcHCwug9oSkoK4eHhNGzYkEGDBtnVLGTW5u/vrzVzreq3Xtr+tVLZERMTg5eXF5MmTeLrr7/m/fff17uV8uWXX1avb9myxVwhSiUoWOmsBozPX88E/rBgTvDRv/+OqioxmcdfMooa3CdJptS/f3+WLVtmsrGEFy9e5Pz58/Tq1QtAPU9QUFAQzs7ODBs2jG2q/utFiIiIwNfXV2tZvHix0TEZqmDFtzFwAOUYHQAaNYItW5SZauxBly7KlnyA33+H/PrmjBkzrBiU/hYvXlzofoiIiCj5xHxGVfBfeeUVZs6cSVpaGmlpacycOZMJEyaUfCLKvphTpkzhp59+4uTJkyxcuFBnn6gNGzZw6tQpTp06ReX8m+mDDz4gMjKSixcvUr9+fZ1fDiTdUs6f55n89X+ArVaMRbJPx48fV08I0qFDBzp16qR3bvwTJ06o19977z1zhCfpoWBDzAQed4/5uX59Vmy1YMnQqBFb8gfz1eRxNyFwzMflkm3517/+xeuvv06NGjXw8PAo9VjCN998k/nz56u3k5OTtca3+fj4lDiY89atWyQlJWktlkpgUnCQe1fgCFBftcPPD376CZ580iLxmIRCoex/rzJzJty+rZ55uyBbe+qWnp5e6H4wZHZsoyr4aWlpDB8+XL09bNgw0tLS9DpX1SfNx8cHFxcXevXqxY8//qjXubGxsYwapfwYGDlyJFst+WFkx2JjYxnF4xayr1FOcKWabEiS9DFu3DiqVKmi3q5SpQrjx48v5gzdTDVwUyqdSmjMVOvkRA89y2FTGnj0qHr9LUDVfuiIj8sl21JwDGFpxhJu2bKFRo0a0ahRo1LF5O3tjY+Pj9bi5uZWqmvqS/XlozwwD/gRZSpbAJo3h/37wR4TcnTsqBwzAJCaqs6JX7FixUKHGtITxRLc3NwK3Q/e3t56n29UHnxnZ2fOnTtH06ZNATh37pzeo8/1/VY7fPhwnJ2dGTVqlHoK8Lt37+Lu7l7seZoiIiLUAwNVdE0p7ugGPvMMmj3/vsz/99ChQ9YIx2oWL15c6HGnTJGmv7y8PK2/83LlypGTk1PMGY9lZGRw5swZhBBkZmaq11WCgoJMHq+5qNIfGjN1uDUVLKPHAOq2uKgoaNAAi2vViv0KBWFC0BgYAGzOfyk2NtYu0/feuHGDGzduyDSZZcjRo0dZu3Yt69ev5/79+2RnZ+Pm5qZVR0lKSqJWrVrFXmfXrl20bNnS3OEWoiobOqOcA0OrNO7TB777Duz5qdrChRAbCw8fwmefwZAhTJ06lXnz5lk7smLpqq/Gx8frPfbNqAr+vHnz6NSpk/pD+cyZM6xZs6aEs/S3Zs0afHx8uHv3Lv3796dx48ZG5dvW9SjDFvP1m1tbIWiav/4zcAFwcXGxYkTWoXrcJRmnQoUKXLx4kYYNGwJw4cIFypcvr9e5GRkZWpU1zXWFQsEff/xh2mDNSJX+MDo6mtmag7hsnObgOWfgTc0Xp0+3dDhqYTt2QH6/5ek8ruAPHz7cLlvyly9fLruhlTHz589Xd89ZtWoVZ8+e5d133yU2NpaEhAQCAgJYu3YtX3zxRQlXsrzBgwfTIi+PmcBAjf1ZQIUFC2DqVLD39KG+vjBnjvJnEQKee465CQk6K/iONOmVURX8nj17kpiYyK+//gpA27ZtqV69ul7n1qpVq9C32tatW2sdo2rhd3d3Z8iQIRw/fpw+ffrg7u6ubsXX59uwt7d3oRZ8Sz3ushVeXl58pLGtGrWg6ktdlqged2nKysoyqE9bWRYdHc3TTz+tHkS2e/duVq5cWcJZSlevXjVjZJYVExODv7+/XbXez5w5U2s7Eo2Bc927gxVaDdV69uSskxPN8vJoC3QEDgIPVCn57My4cePo378/iYmJMhd+Gbds2TKeffZZMjMzGTVqFIGBgdYO6bHMTNiyhfEbNtC1wEsngHVdu/LhtGnWiMw8Jk1StuIfOAB//gkvvoizQkFugS6jDtUIKIwQGxsr0tLS1Nu3b98W27Zt0+vc7Oxs4efnJ65fvy7u3bsnGjVqJFJSUrRev3XrlhBCiEePHok+ffqIdevWCSGEeOONN8TSpUuFEEJMnTpVfPLJJzrfIy4uTgAiLi7OmB/PobiBuK/8zirSQFQGYeR/u0OS94phLly4IP7zn/+I//znP+LSpUsGn3/t2jWt5fLly6J79+5miNT07PleIf/vXrXE5ZcJAoTYs8fa4QmxerU6nq0acfr4+Fg7MqPZ8/1SFhQsi65duybu3r1rlVgsdq+kpQmxbp0Qzz8vhLv74zIgf0kG8TwIhaPWEa5eFcLNTf3z7unYsVDZaOv1I0PuFaNa8GfNmqWVPaNatWrMmjVLr2405cqVY9GiRYSHh5OXl8e0adPw8vKid+/erFixAnd3d3r27El2dja5ubn069ePqKgoQJnaKCoqiiVLltCsWTPmzJljTPhlxuDBgxkGqDL7rgEyQP37lCRDNWzYUN1FxxghISEoFAqEEGRnZ3Pv3j369etnwgilknQH1O31ISHKVHLWNnQo10aNog7QFwgAfsPBWtMkmxISEsLt27fV3Qyzs7NxcXHB19eXNWvWEBwcbN0ASysrCy5dghMn4Ngx5RIfr84Fr+kSsBBlAo5HOHAihDp14NtvoV8/EIKuBw/yIo/HJarMnDmzyEw79sSoCn5BCoXCoNHn/fv3LzR4aseOHer1uLg4ned5e3tz4MAB44IsgzZs2MAxjW1V95z169dbIxxJKtQd6vDhwyxZssQ6wZQRBXNba/W2f/tt25iwpnx5/s/JicX54wSmAaOtG5Hk4F588UWaNGnC6NGjEUIQExPD2bNn6dChAxMnTuSXX36xdoj6y86GL76ACxceL1ev6qzMq9wHNgDfAPtRNl0DhbqxOpw+feCDD9Tjjj5H+bN/pXHI/PnzHaKCb1SaTFdXV63JSA4dOmSTeYsTExOJj4/nxo0b1g7FKpoDrfLX44BTgKenp9XisSU3btwgPj5eZrqwsvbt23PlyhVrh2EQeypXCva9D4HH/W0bNoSBAwueYjWL09NRzYjyLPBU/rquWSdtmSxb7MPu3bsZM2YMCoUCJycnnnvuOfbs2cOAAQO4e/eutcMzTLlyMG0a/N//wc6dcPmy7sq9vz9MnkwPoDrwPMpZajXb6x1lgGmx3npLOeAWZSX4S+A9HqfpdZQnGEZV8D/88EMGDRpEWFgYYWFhDBkyxKKzrelr5MiRhISEsHz5cmuHYnGVK1fWOXOtrknFyqLly5cTEhIiB8FZmOaMkXfv3mX37t0EBARw7949u8lwZU/lSsEsEVqt92++aVvZMapWZWn+anlAMzlcwS8qtkyWLfbh0aNHXLx4Ub198eJFMjMzgcIpZW2eQqH8wq7i4qIcOD90KMybB3v2QFoanDuHYskS/oeyK05BjlKxLZFCoUyd+cYb6l3vAluAJ/K3O3ToYI3ITMqoLjrt2rUjMTGRI0eOAMpWuGrVqpkyLpOwx2wXJpOZierj5SHwLfbXEmZOMtOF/mJjY4t93ZBc5dWqVVP3wdf0zTffGNzVz1rspVwpODOlH8rsOYByNsrnnrN0SCX6oUYNpv39N1WAscAc4DbKLyoLFizQe94Fa5Jli32YP38+7dq1o3nz5gAkJCSwYsUK7t+/z9ChQ60cnRE++gjKl1dW9GvUKNT1rkOHDlo9LwoqcxNfKhSwaBE89RS5U6bgDPQDzqJMIby6mN+VvTC6D76Hhwe9e/c2ZSwm5+/vb5VJI6zN39+fSKBa/vY6IB3YsnmztUKyOfY2SZE1ffzxx0W+plAoDKrga+Zit1f2UK506NCh0ADVN9F4ZDt5MlSqZOGoSnbmxg0+USh4HWVygInA+/mv5ebmUqFCBZufnE6WLfZhwIABtG/fnqP5sym3bdtWPUvojBkzrBJTqSbR61ow2aWSl5cXt2/fLvZUFxeXMjfxJaCs5L/xBm998QXTExN5EvBGOdh4MsDmzcoBuTbwRMeYCfRMMshWsi3nz5/nvxrbqu459jgrpGR9+/btK/U1fv31V9q0aVPk6xkZGVy5ckU9O7ZUOgVb6p5EY9CqqyuMH2/pkPT2+pUr5NSrRzngNeAjlE8hQZnpRJJMxdvb26ayeJlyEr3BgwezYcOGEo9zcnIqk/PiaFp87hzeCgWfAaocgy1AOUapQQMYN07Z3al2bavFaMwEekb1wZds18yZM2mEcsppgPPAIaBJkybWC0pyGNnZ2Vy4cIGEhAT1oo9FixbRvXt3Vq5cyblz50hNTSUpKYmffvqJadOm0a5dO/755x+D4xk4cCAeHh6FUr/m5eXRpk0brf2XL18mNDQUPz8/xo8fr+4mlJKSQnh4OA0bNmTQoEHqfrj2ysvLq9C+SYC6vX78eLDBLpVqdetSbsQIQDkQ8AXrRiM5GNUEnUXJyMjg3LlzFopGW0xMDHFxcYwbN65U11EoFHpV7gG76BZpCSnAYKALEK/5wuXLygHMdepA+/Ywezb8/DM80jWKwXzGjRtHXFwcMTExep9jUAVfc4CcrkWyvvnz5zNWY/vz/H9lRgeptLZt20bt2rUJCgoiPDyc4OBgBgwYoNe569atY968eRw6dIj+/fvj4+NDUFAQc+bMoXbt2hw6dIjw8HCDY5o0aRLffPNNof1ffvkldevW1do3ffp0Zs+ezaVLl0hJSWH79u0AfPDBB0RGRnLx4kXq16/PihUrCl3PnhR8HO8KTFBtVKig7J5j66Y/Hg48Fe1HzXIskVQa5mpsMAVV9z9ju3gpFAq9/z48PT3LzqBaPajGIOwDQoHewP8KHnTkCLz3HnTuDG5uynlEXnwRPvlEmb3o/HnlDMFmULNmTVq2bIm/v7/e5xjURUfXADnVti0OkCtVfzY7VV4IxuSvP0KZ49bFxcV6AdkoY/qzlXWzZs3i6NGjPPPMM5w8eZKYmBhOnz6t9/mtWrWiVatWJR9ogLCwMPbv36+17/bt26xdu5Z33nmHzz77DFBmhzh8+LB6DoiRI0eydetW+vbtS2xsLMePH1fvnz59OhMnTizyPSMiIqhQoYLWvilTpjBlypQizrAcXa3343g8HodRo6BWLQtGZKTAQOjdG3bsoC4wFOVEfSq+vr42lc5v8eLFhTLJ2fpYgbJq3bp1HD9+nOXLlzN37lyuX79O1apVCQoKIjIykkOHDlG1atWSL2RjDPniKyv2hR06dEj9OxTAzvxlYkQES59+GtauhbNnH5+QlaWcOCw+vvDFatZUDnT29oYnnlD+6+0Nnp7g66vMxW8BBlXw7W2AnCn7s9kDV1dXBqJ8rA3wA5AKiDLev04XY/qzlXVOTk7UqVNHnclk5MiRxQ7AtZaZM2cya9YsrX2pqal4enqqC3AfHx/1INS7d+/i7u5eaH9RCk7WBdjEE8zBgwcXar2vQP5gMVAOKHvzTQtHVQrTp0P+BIjT0K7g29oMt+np6TYXk1Q0czQ22ANZsTfcsl27WLpzJ8ycCX/9Bfv2wd69cPw4/P476KoX37ihXHRp2dI2K/j2xl7S2ZnK/fv3eVlj+/Mij5RkKjvDqaZ09/X1ZdOmTdStW5e0tDQrR6Xt5MmTpKWl6WzZNxVvb+9CLfhubm5meS9D/PDDD4X2vQio56UcMADsaSxOx47Qti0cPUoQ0Atli5qKrnSr1uLm5lZoBtCsrCydXwYlydJs5e/E1jVp0oTz588XfcBTTynTC6tSDD98qGzVP3MGrlxRLn/8Adeuwa1boCutrwXHPxlVwb958ybR0dGcPn1aa0BavK5HFVZkD+nsTMXf3x8/lANEAC4AB4B33nnHekHZsLLUbctUJk2aRFpaGv/+978ZNmwYd+7cYcmSJdYOS8vRo0c5ePAgdevWJTMzk3v37vHyyy+zfPlybt++re5OmJSURK38riru7u7qVnzN/UXZtWuXTZYrBT/EKwBayf4KPNWweQqFshU/f7bdf6FdwQflUwtVtytr0tVFKz4+npCQECtFJJU1qrJNk4+Pj011ZbN1iYmJOrs6dejQQXca0SpVoHVr5VKQEHDnDty8qazs37ql3NbRjdJcjMqi8+KLL1K3bl1SUlJ47733qFWrFn0s9MhB0u38+fNaM9eqWu/nzp1rjXAkB/Tss8/i4eFBSEgIFy9e5NatW4zIz3ZiKyZMmEBSUhJXr15l7dq19OrVi88//xyFQkHbtm3VA2vXrFmjTo/Xt29fVq9eDSif+tlS2jx96fpQegF4SrXRr5/y0bC96d8fAgIAaA/0LPCyvplCJKksEEJoLbJybxrFTRBWJIUCPDygcWN4+mllQ8XzzyvLNAsxqoL/119/MX36dCpWrEi/fv3YuHEje/bsMXVskp5mzpxJeeD5/O0slBM1yNSYkikcOHAAUM5oq2sxxL1799ixYweff/45q1ev1jvNZlG6devG4MGD2bFjB76+vurZtXVZsGAB0dHRNGjQAA8PD3WjxIwZM1i/fj1+fn5cunSJl156qchr2CJdA2srAFrP7qKjLRWOaTk5KbNW5Juj4xBHmFJespzffvtNvf6oQKpDVVknlV2OVG8yqouOqv9ppUqVSE1NxcPDg5SUFJMGJulv3rx5RAFP5G9vQpnT9ZbMECOZQExMDJ07d9Y5oFbfmWyvXbvGu+++y86dOwkMDKRGjRpkZmYyf/588vLymDZtGi+8YHjG8+IaFsLCwggLC1NvN2zYkLi4uELHeXt72/UHu65ZKp9Ho/W+b19lOjd7NXAgNG8Op0/TCugLbNN42ajWNanMGjVqlLo7cbt27bS6Fr/xxhs219VYsiyDu+nYMKMq+I0aNSI1NZWRI0fSpk0b3NzcbLKvYVlKk/mqxvoXyNSYJZFpMvX3xRdfAKWb0XbUqFG8+eabfPnll5Qrp13sXL16leXLl7Ns2bJi01PaClsqVwr+LkE5odW/NHfYa+u9iqoV/5lnAHgf2I4ylZ3KzJkzbaY7oixbbJvmWJWC41asPRjVlsoWSZu1GxKMKldEKf3yyy9i69atIjs7u7SXMpm4uDiBsvwXgIiOjrZ2SGZTqVIlEagcziEEiEQQitL/tzq86OhorXskLi7O2iHZvFatWum1z1HZYrmiGY9qeUujPBB9+lg7RNPIyxMiJET9cw3S8XPbClm22LYWLVroXNe1bSm2WLaUZe3bt9dZtlqTMeWKUX3wQZkTPzk5maeeeoqgoCCSk5ONvZTZmGraZ1uWmZmp1Xq/DO2WLUk3Y6Z9LutyCqT8ys7O5p6ecyx07dpVvW7v3flsuVzxBGaqHi87OcEHH1g1HpNRKOD999Wb84HyBQ4ZPHiwRUMqiixbbFtGRgZnzpwhISFBa121bU22XLaUJUV1xfH19bVwJI8ZU64Y1UVn1apVvP7665QvXx4nJ+V3BIVCwc2bN425nNk4eppMX19fqgGqLO7pKAfXytSYJZOPQPW3YMECPvjgA+7fv4+np6d6f0ZGBs+p8gGXQLOfeI8ePbT6ub7//vu8++67pgvYzGylXNHVT/QdwF3VzWD0aGjWzLJBmVOvXsrc+AcP0ggYDyzVeFnXPADWIMsW25aRkaE1bkhz3ZDZYM3BVsoWCZydncnNzdXaZ83J7IwpV4yq4M+ZM4fjx4/TuHFjY06XTCQpKYkpgGpS7a+B+8jUmJJpjR8/nqFDhzJhwgT++9//qve7ubnh4eFh8PVEgX6umzdvtqsKvi3QVRGpA6hHMFSqpNXi7RAUCli8GPJnIJ0NxACqqdYK3leSpMvVq1etHYJkBzZu3MiAAQOsHUapGFXBr169uqzcW1mHDh1wAl7R2LcMaN++vZUikhyVu7s77u7u7NxZcJoh/WlWSAtWTmXFzDQWARVVG5MngxUfJ5tNaCiMGgWrV+MJzAI0p5fS1eomSQWdPXuWCxcuEBwcTP369a0djmSDisoO5+rqqnfXVGszqg/+M888w5IlS7h58ybp6enqRbKcw4cP0wtokL+9G+XstfaWxkmyH/Hx8URERNCoUSPq169PvXr19P5wvHDhAiNGjGDJkiU8ePBAawZsaz8WtzczZ84stK8nEKnaePJJePttS4ZkWfPmQeXKgPKJhb/GS3l5eTbTF1+yTZ9++ilPP/00CxYsoGXLlmzatMnaIUk2ysfHp9C++/fvWyES4xjVgq/6gNGcmluhUNhcy4mjppxS/f4na+xbBlr9o6XiyVR2hhs9ejQTJ06kXbt2ODs7G3Tunj17iIuLIz4+nsqVK1OtWjV8fX1p1qyZ3c22aO1yZd68eVrbFVH+/astXAju7pYMybJ8feGtt+D99ykPLAc68zi5wIYNG6yaNlOWLbbt008/JSEhgdq1a3PmzBkmTJjAwIEDrR2WZIOuX7+uswHK19fXLj63jKrg5+XlmToOsxg5Ujn8NDo6mtmzZ1s3GBOaN28eLYFu+dsXgR1Abmqq9YKyM8uXL+c9jRkypZI5Ozsbnd2hbdu2tG3bVr396NEjEhISiI+P54knnijmTNtjzXJFV+v0NMBPtdGxI4wcWegYh/P22/Dtt3DpEh2BF4EVGi+rvgRZo5IvyxbbVr58eWrXrg1AYGAgDx8+tHJEkr2x5mBbQxidJhMgOTnZJtNjqjhyyqm3NNY/AipUqmStUOySTGVnuA4dOnDixAmjzv3111+1titWrEirVq0YN24cn3/+ORkZGZw7d84UYZqdNcuVgt0JAtGY1MrZGf7zH+VgVEdXuTJoDPj+EHiywCEfffSRRUNSkWWLbcvMzCyUGlNzW5I0RUVF6dzfoUMHC0diOKNa8BMTE4mKilJX7n19fVm/fj1NmjQxaXCl5Ygpp8qVK0c9QNWOdxP4Bqyev9feOFq3LUv4+eef+eKLL/Dz86OSxhdKfaZ2X7RoEWlpaQwfPpw2bdrw5JNPkpmZye+//87u3bvZvXs3H3/8MU2bNjXnj2AS1ixXNLtBlkeZOauCase0aRAYaIWorKRrV/WAWw/gc0Az50VWVpZVwpJli20rmCYTHg+oVCgU/PHHH9YIS7JR69ev19lNx9oz2+rDqAr+K6+8wsyZMxk+fDgAa9euZcKECXpPZb9t2zamTp1KXl4e06dP56WXXlK/9vDhQyIjI7ly5QrOzs6MHz+e1157DYDZs2ezYsUKqlevDsDSpUvp2LGjMT+C3crNzeUNQNUD+hMgt3zBKV8kyfSWLVtW8kFFWLduHcePH2f58uXMnTuX69evU7VqVYKCgoiMjOTQoUNUrVq15AuVYQW758wEWqg2mjWD6GhLh2R9ixbBrl1w6xb9gZdRVvRV/P39ZV94SYstp8m09vgeSTdPT0+tuVyswZixPUZV8FUtcSrDhg3jAz1nTMzJyWHKlCns27cPd3d3QkJCGDhwIF5eXupj3n77bTp37sz9+/cJDQ2lV69e+Pn5qV+bOHFiUZd3aBUqVMALZX9TgAfAp1ivpUoqWzp37kx2djZ//vknDRo0KPmEAlq1akWr/BzmkuE2bNigXg9Do2tOuXLw9ddQsaKOsxyctzd89RX06wfAx8AB4Pf8l8+fP2+tyCQbpZkcRJfFixdbKJLCHHXcoL1LTU3V2YpvybS8xoztMaoPvrOzs1Z/2XPnzumdVePYsWMEBATg4+ODi4sLvXr14scff1S/XqVKFTp37gyAi4sLjRs35saNG8aE6XCys7N5A6iSv/0Fjyd5kSRz279/P3Xq1CE8PByA48ePqz+QSrJlyxa++eYbc4bn0GJjY9XrNYG1PH6KR3Q0OFhXRIP07QuvKGcEqQKs5/Hkf5JU0JIlSzh06BCurq7qOT40F2ty5HGD9q68jp4Slkw4Y8zYHqNa8OfNm0enTp0ICgpCCMHZs2dZs2aNXucmJydr5Rb18fEpckTyX3/9RUJCglZ/18WLF/P555/ToUMHFi5ciIuLS5HvFRERQYUKFbT2TZkypcRv8LbI1dUVT+D1/O0sYDHKipOkn8WLFxdqnZFPP/T39ttvc/DgQfWgo1atWnHy5Em9zv3ggw90lhGbN2/G29vbLgYsqVjjMbrqd14eZeVePaC0Rw945x2LxGDTFi7k0ooV+GVlEQis4vE4JYVCYdHJ1GSaTNu2d+9evvrqK7799luGDBnCCy+8YNQTSXNwxHGDjiIrK0tnK76Tk5NFKvrGfN4Y1YLfs2dPEhMTmTJlClOnTiUxMZEePXoYc6kiPXr0iKFDh7Jw4UJ139wJEyZw8eJFTp48SZUqVUp8XHHr1i2SkpK0FnudkOv+/ftMBVzzt78E/qLo2dakwtLT0wvdD7du3bJ2WHYjNze30AdhwS/QRXn06JHOSbH8/f159913TRKfpYwcOZKQkBCWL19usffMzs4GlE/tOuXv+wsgJgacSpUMzTFUqYJfQgJ38zej0OjChDIRhKUsX76ckJAQvZ9uSZYVHh7O6tWriYuLo3bt2owYMYLw8PBCmb4kqSBdPVWEEFpPWG2JQS34Dx48oGrVqqSnp1OxYkU6deqkfi09PR03N7cSr1GrVi2tFvukpCRat26tdYwQgueee47evXtrpSh68snHidBeeOEFXn311WLfy9vbu1AFRJ8YbY2rqytewGv524+AecA7suXOIG5uboVmpsvKypKVfD1VqlSJ+/fvq1sxzpw5Q+X8GUVLkpOTo3N/48aNbTrVri4xMTH4+/tbrPVeNT7pXWB0/r4M4KmjR5V90CWlxo3ZPGQIo9atwwmYA9xA2RhiybzV48aNo3///iQmJspKvg1zc3NjwIAB3L59m08++YTz58/Tpk0ba4cl2bCcnBydrfgDBgyw6FNCfRnU9KPKWFOtWjU8PDzUi2pbH61bt+bs2bMkJSVx//59du7cSc+ePbWOmTFjBlWqVOFf//qX1n7NvvhbtmwhICCg2PfatWsX169f11rssXtOwdb7FcB1rDOJiz2bMmVKofth165d1g7LbsyaNYsePXqQlJTEyJEj6d69O//+97/1OtfPz4+dO3fqfK2inQ0OVT1Gt1QF//bt20wGVM8r84CRALIyUsjo779njUaq0OVAZP66q6urznNMrWbNmrRs2RJ/f3+LvJ9kmNzcXDZt2kTfvn3p3r07zs7OxMfHM3r06JJPlsq8osab6pqE0NoMquCr8l3n5eWRm5urXlTb+ihXrhyLFi0iPDyc4OBgpk6dipeXF7179yY5OZnr16+zYMECjh07RnBwMMHBwezevRuAadOmERgYSFBQEPHx8cyZM8fAH9f++Pr6UguYlL/9CJgPtG/f3npBSWWOEILAwEDWrFnD7Nmzad++PYcOHaJLly56nf/ee+/x8ssv891332m1dBw/frzYcTQlGThwIB4eHlpP+jp16kTz5s1p2rQp77//vnr/5cuXCQ0Nxc/Pj/Hjx6vjSElJITw8nIYNGzJo0CAyMzONjsccJqPMDqPyFuBUxOQrEow6fRrVFFfOwHfAEJQNJZLk4+PD/Pnz6dOnD2vWrCEiIoJbt27Jia4kvRT1NFozy5nNEEa4deuWXvusJS4uTgAiLi7O2qGUGiBWgBD5y8cgjPxvk3RwpHvFnPLy8kRAQECprnH06FHh5+cnnnrqKfHMM8+I/v37C09PT7Fv3z6jr7lv3z4RGxsrIiMj1fvu3r0rhBAiOztbtGnTRsTHxwshhIiMjBRbt24ttD516lSxdOnSQusFWfxeycsT85yc1H/7AsS78u9fL+3btdMqN3NBvJz/u2vfvr2oXLmyaN++vVljkGWLbapTp46oW7euqFu3rqhXr556XbVtjD///FN07txZ+Pv7i8DAQLFu3TohhBCXLl0SISEhokGDBmLcuHEiLy9P5/nyXrEvlSpVEuSXJ5qLj4+P2d/bkHvFqNFZugbUmnqQrSkkJiYSHx9vt2k2vby8CASez9++g7Jfqa3NGGyPbty4QXx8vMx0oSeFQoGvry8pKSlGX6NNmzacP3+e//znP4SEhNClSxd+/fVXwsLCjL5mWFhYoa4XqnE22dnZZGdnq7OoHD58mD59+gDKgbJbt24FlCkoR40aVWh/USIiIvD19dVaTJ47OzMTRoxghkZ2hmjg/aLPkDQcOnyYl1EOSgblo+rlwEfAr4cPk5GRweHDh03WbWfx4sWF7omIiAiTXFsyratXr3LlyhWuXLnCH3/8oV5XbRujXLlyLFmyhHPnzvHjjz8yefJkHjx4wPTp05k9ezaXLl0iJSWF7du3m/inkawhIyND535LjvXRh0GDbLOyssjMzCQ3N5d79+6pH3HfvXuXBw8emCXA0rD3SSNu377NtzzuR/Vv4DaQKiulpWbMpBFlnYuLC8HBwfTu3VurW40hlVtnZ2f69etHv/yJicylffv2nDlzhldeeYXg4GBSUlLw9PRUD5DSTM979+5ddf7r4tL2qugalG3S7FyJiTBsGOR3F8gD3kA5azXI7nn6atSkCS+fP08aMC1/31SgJfAs8A/KbjsdOnTg0KFDpXovVYYuqWzSTGFYo0YNqlevzu3btzl8+DDr168HHjce9O3b15qhSiZS1Oy2lk7LWxyDKvjz589XV4o0J4Rwc3Nj6tSppo3MBCyd7cKUvLy86Auohh9fAZYhP9xNRWa6MFxgYCCBGgMYbdnhw4e5d+8eUVFRnD17lho1apjs2mbLzpWbC//9L0ybBg8fAsrZqp8FNJ8plLYyWlYkJibi5OTEdCG4AvwfUAEIB34DJqKcU+Dw4cOlfi+ZoUtSiYuLIzc3l8qVKxfZqFAUR5q7R+XEiRN8//33LFy40GzvsWrVKnr37s0TTzxhtvcoqKjZbQGTNBpA6efuMaiCHx0dTXR0NBMmTOCzzz4z5FSrsOdJIzJv32aZxvYMlANs5Ye7aVhykiJHER0dbe0QDOLq6krXrl3ZtWsXU6dO5fbt2wghUCgUJCUlUatWLUDZWKFqxdfcX5Rdu3aZvlyJi4MJE+D4cfWu31AODj2ncVilSpVM+74OLi8vjwoVKvDf7GxOAxuAWoAXysG3I4E3edzq1qFDB3WF38fHh+vXr+v1ProqYfHx8YSEhJjuh5Fs3u3bt3nuuef44osvSj5YB7M/HbSw3NxcQkNDCQ0NNev7rFq1itDQUItW8EHZ4KqrgcAUjQZQ+ieDRvXB7927N3fu3FFvp6Wlyb5lJlS5cmVmAXXyt/cA3yP73kvW9ddff9G3b1+Cg4MBOHXqFB9//HHxJ1nY3bt31R+Sjx49Yvfu3TRp0gSFQkHbtm3V5dSaNWvU3YT69u3L6tWrAeVTP3N3H9Ly228QFQWhoVqV+88VClqhXbmHovt+SkXLysrinXfe4QgQhLLVXqUPcAb4DKinUGh9MCclJVl0gizJvj169IhnnnmGt99+m/bt2+Pl5aVuVAD0ajzw9vbGx8dHazHX3D2rV6+mVatWNG/enClTpvD999/zzDPPAPDbb78REBDAw4cPmT17NmPGjKFNmzY0atSIdevWqa+xYMECWrVqRVBQEB99pMxdtX//frp06ULv3r3p0KED+/fvV2c5mz17Ni+88AJPP/009erVY9euXUyYMIGmTZtqPUnfvXs37dq1o0WLFowcOVLdal29enXefPNNAgMD6dq1Kw8ePGDTpk2cOHGCqKgos3+RKKi4BteiWvcNoXoyqLl4GzL3iTGjeJs3b661nZeXJ1q0aGHMpczC3kekB4DIys/+kAmiocycYTb2fq9YUq9evcTq1atFUFCQEEKZpaZZs2ZWjalr166ievXqonLlysLHx0fs379fhISEiMDAQBEQECDee+899bEXLlwQLVu2FPXr1xdjx44Vubm5Qgghbt68KTp16iQaNGggBgwYIB4+fKjzvUx2r+TkCLF1qxAREVoZcgQI4e8vxIEDOjM0yDKg9JycnAQgIkH8WeB3nwPiOxDtTPQ7l2VL2ZGXlyeGDRsmoqOjtfYPHDhQna0rKipKxMbG6jzfmHtly5YtYvLkyWLLli0Gx3vu3DkRGRkpsrOzhRBCjBo1Smzbtk1ERkaKr7/+WrRt21YcOHBACCFEdHS0CAkJEZmZmeLvv/8WtWvXFnfv3hW7d+8WEydOFHl5eSInJ0eEh4eLM2fOiH379gk3NzeRlJQkhFBmOlNlOYuOjhZdunQROTk54pdffhFVq1YVv/76q8jLyxPt2rUT8fHx4tatW6Jr167qcnjWrFli2bJlQghlVsH//e9/6pi/+eYbIYQQnTt3FmfOnDH492AqRZXXCoXC5O9lyL1iUBedoigUCr3z4EvFq6hQcBgon789D7iI7HsvWd/NmzcZOXIkixYtApSZI8qVM0kRYrQ9e/YU2nfixAmdxzZs2JC4uLhC+729vTlw4IDJY9Np7VqYMQOuXtXe/+ST8M47MH48g0eM0HlqlMx9X2qqzymFQsEOlIOX30Y5iaAzMCx/OYey7F1jnTAlO3Po0CG+//57goKC2Lx5M6BsIV+wYAHDhg1j0qRJdO3aVZ3Fq7RiY2MZMGAAtWrVYsmSJWzZsoX+/fvrff7evXs5evSousX74cOHhISE8OmnnxIQEMDQoUPp1KmT+vhBgwZRsWJFnnzySUJCQkhISODHH39k+/btHDx4EIB79+5x4cIFPD096dChQ5FPK3r37o2zszOBgYG4urrSunVrAJo1a8bVq1dJSkoiISGBdu3aAconI6rfm4uLC926dQMgJCSEqwXLUSspasCtEILKlStb7cmrUZ/Orq6uHD58WF3pPHTokMVmCTSEKgWivfS3njlzJv8CVL02E4EF+euy771p3bhxgxs3bsg0mQYoV66cVnaAtLQ0m8kWYEmlKldyc7Ur93XqwGuvKfvfV6kCFD1hiiobh1R6In8sxjyU3XMmoJxMUNWDtylQAwoNnNWHLFvKnqeffpo8jZS2mnQ1KpTWvn37qFWrFtevX8fX15f9+/cbVMHPy8tj7NixhcZVnThxgvLlyxdKLa7Z3UShUKBQKMjLyyM6OrrQDMD79++nSn5Zpotq5nInJyetWcydnJzIzc3F2dmZPn36sHLlyiLPBWVGNltpWC5uwG1mZib+/v5WKQ+M6oP/4YcfMmjQIMLCwggLC2PIkCGmzwNtAiNHjiQkJITly5dbOxS97J03j3fy17NRDgB7BLzzzjtFnyQZZfny5YSEhMgMOgYYPHgw48aNIz09nRUrVtC9e3deeukla4dlcaUqV6KilK31EREQGwuXL8PUqerKfVFkGWB6qjFNaShb6+sAzwEHgCzgfzVq6D3IVpMsWyRzCw8PJzk5GV9fX5KTkw2eS6Rr1658//33pKamAsqns9euXePll19mx44dZGVlafW137RpE1lZWdy8eZO4uDgCAwPp0aMHK1as4GF+xq+rV69y9+7dUv9s7dq1Y9++fVy7dg1QDjS9cuVKsee4urpy7969Ur93aRTX2HX+/HliY2MtGI2SUS347dq1IzExkSNHjgDK7iPVqlUzZVwmYU9pMv08PPgfysfEAO8B8fnrc+fOtU5QDkymyTTc1KlT+e6777h79y4//vgjU6ZMYfjw4dYOy+JKVa5UrAgXLoCBA+dkGWB6iYmJuLq6cv/+fQAygdX5i7hxg9NGplaVZYtkbv3792fLli3s37+fsLAwg1rvAQICApg5cyZdu3YlLy+PihUrUrduXfr06UNwcDDLly8nPDycLl26qI/v2LEjaWlpfPjhh7i5uREREcG5c+do27YteXl5VKtWjR9++KHUP5u3tzdffPEFkZGRZGVl4eTkxJIlS6hXr16R54wZM4YxY8bg6upaZBdNS1A9GdRlwIABFn/irRAO+IxdlZ4sLi7OPtJk5uayq1w5VPMeHgY6AbkU/61QKj27u1esIDIykh9++IEPP/yQadOmlXyCgzLVvbJ5M+Tk6H5t0aJFHD16RGufk5Mz33//vdHvJxVP83fu4uLCypWrABg0CJyMesatJMsWSV+2fK/Mnj2b6tWrM3HiRGuHYjeKy6BT2jqdIfeKUS34N2/eJDo6mtOnT5OZman1xpLh5pQrx6z89Zsoc1/nohy4IUnW9vvvvyOEYO3atWW6gm8qo0dD0amtC08YmJcHgwebNaQy7vHv/P79x7/rR4+gwJxDkiRJJSquJd+SM90aVcF/8cUXefrpp9m7dy+LFi1i+fLltGjRwtSxlQlTPDxQjV7IBYYCqmkNVP3jJMma2rRpg6urK48ePdL60qkqxHRlD5CK1qEDPHhQeP/BgwcRovBAvYCAALy8qlsgMkmTCdJYS5Ldmz17trVDsEtRUVFFJkyoUKGCQTPSGsuoCv5ff/3F9OnT1ZPC9OzZk86dOzNnzhxTx+fYdu7kQ40Jw94C9uevy0F1kq348ssvmTdvHl26dGHHjh3WDsfuFfUrVCg66dx/9qzspidJZYG9Zf6TirZ+/XoqVKhAdnZ2odd07SuJMdm5jKrgV8h/blmpUiVSU1Px8PAgJSXFmEuZlU3/sezdy4Pevamav7kEUM0J6uzsLAfVmZlMZac/VR/85557jjp16pR8goMzR7lSVIYFOQbH/siyRTKWalB2dHS0bDl3AFlZWSaZ0RaU2bnee+89g84xaghRo0aNSE1NZeTIkbRp04bQ0FBCQkJKPtHCbDZN5u7dZHTrpq7crwemaLycU9QIPMlkZCo7/an64MuBnkrmKFfGjBljsmtJ1iXLFslYMTExxMXFMW7cOGuHIpmIrkYaZ2dnHUcWb9y4ccTFxRETE6P3OQa34Ofm5uLj44OXlxeTJk0iNDSUtLQ0IiIiSj7ZwmwyTWZMDNmjR1M5f3Mzynz3qltgy5YtVgmrrJGp7PQn++BrM0e5kpaWVmhf+fLldRwp2TpZtkjG8vf3t7ksOlLpCSEoV66ceiIvYxpxjXlibHAF39nZmX379qm3O3ToYOglLMam/ljy8uDdd2HuXFQf2+uB4YDqv7pSpUoG57OVjGOT3bZslOyDr83U5UrlypV17rfEICzJ9GTZItm6t956ix07dnDu3DkuXbpEgwYNynwaZHOzRs8Mo/rg9+7dm7lz5/L888/j4uKi3u9m4OQtZcaNG/Dcc7Bnj3rXf4GJKDPnqGRkZFg6MknSy5NPPsnhw4dxd3e3digORzPVsCRJkrmtWrWKf/75ByeNiR5kBd/xGFXBf//99wGYNWuWOqenQqEgNze3hDPLGCFgwwZ45RXIH4Sci7K//SeFDpWD6STbtGjRIqZOnVrkAJ/Fixfr3C+VzNfXV+d+2T1HkiRzGDhwIGlpabRs2ZIKFSrw1Vdf8d1333Hnzh2Cg4Np27Yt//3vf60dpmQCRlXw8/IK52qWCrhwAV57DX78Ub0rGRgF/FTgUJkSU7Jlqqd0svXetDp06EBSUpLO12T3HEmStISGwt9/63dsjRpw4oTOlzZt2kT16tU5deoUYWFhAMydO5fly5dz6tQp08Qq2QSDKvgvv/wyn3/+OaAcDDpgwACzBGUqVkmT+ccf8O9/wzffgMYTjc3AS0DBqatcXFxkSkwrkKns9KfK6BAdHW3lSGyDqcqVI0eO6NxvqrRqknXIskUyi7//hiIaBCRJF4PSZJ7Q+EZoaD5Oa7BYmkwh4KeflHOcN2oEK1eqK/d/AgPzF13z0t67d8+8sUk6yVR2hjl+/DhDhw6lWbNmNGvWjGHDhmmVB2WJqcqVorrltWvXrlTXlaxLli2SWdSoAT4++i01alg7WskGGNVFB+yjz7hZ02QKASdPwg8/wPr1cPGi9uvVqvHunTssAh4WeQnb/x06KpnKTn9Hjhyhd+/ejB8/nmeffRYhBMeOHaNHjx7s3LmTNm3aWDtEizJFuVJcHuRDhw4ZfV3J+mTZIpmFmRtUnJ2d1WkcJcdgUAU/IyODM2fOIIQgMzNTva4SFBRk8gBLo7Tp7JydncnLy8PJyYncnBy4ehUOHID9+2HfPvjzz8InPfkkexo1IurgQe4Wc21ZubcumcpOfx9++CFfffUVAwcOVO8bOHAgbdu2Zf78+WzevNl6wVmBKdJkFjWOSZYL9k+WLZKxrNKtON/o0aMJDAykU6dOcpCtDTKm659BXXQyMjLo378/AwYMIDMzU70+YMAAnnnmGb2vs23bNho3bkzDhg1ZsWJFodePHTtGQEAAfn5+6ow9AJcvXyY0NBQ/Pz/Gjx9v1g/DFk5OPJeXx8fAnrw8bjs5Qf368Pzz8PXX2pV7hQLCw2HtWir88w/dZeVeciC//fabVuVeZcCAAZw7d84KET02cOBAPDw8iIqKAuDhw4f06tWLJk2aEBAQwNKlS9XHpqSkEB4eTsOGDRk0aJA6PWVmZiaDBg2iYcOGhIeHk5Kf8crSfHx8rPK+kiTZBkt1K1aVcfv376dZs2aAsiHn3LlzsnJvo4zp+mdQBf/q1atcuXJF5/LHH3/odY2cnBymTJnCTz/9xMmTJ1m4cCGpqdq901999VW+++47fv/9d3bs2MGZM2cAmD59OrNnz+bSpUukpKSwfft2Q8I3yJdCsBKYDIQDngVezwDo0QP++1+eFALFvn0ohg0ju4Trysq9ZG+qVKlS5GtVq1a1YCSFTZo0iW+++UZr39tvv8358+f59ddf+c9//sOlS5cA+OCDD4iMjOTixYvUr19f3biwYsUK6tevz8WLF4mMjOSDDz4wa8xFDaK9fv26Wd9XkiTbFhMTQ1xcnDqxgSSpjBs3jri4OGJiYvQ+x6AKvimoWud9fHxwcXGhV69e/KiZSjI5mZycHIKCgnB2dmbYsGFs27YNIQSHDx+mT58+gPKb7tatW80W5+kC28nATmAW0BGoBih+/BHF+PHc1POasnIv2aNHjx5x5swZEhISCi3WnqQpLCwMV1dX9XaVKlXo3LkzoMxQ1bhxY27cuAFAbGwso0aNArTLj6L2W5Ls0iFJkqr7nywPpIJq1qxJy5Yt8ff31/scowfZGis5OVnrUbSPj49WLmhdrx84cIDU1FQ8PT3VrV8Fz9MlIiKCChUqaO2bMmUKU6ZMKTHO7S4unL1/n9MoK/uleWjv6elZ6CmFZHmLFy8uNCmTzDdeMlXXPF1sOaXjX3/9RUJCgrq//N27d9W5/DXLD80yp1q1aty5c6fY65amXCl4nop8LG7fZNkiSZKtsXgF35Ju3bpVaF96erpe5264dw8vLy9u375dqhhkq73tSE9PL/FLoVTY1atXrR2CwR49esTQoUNZuHChybsRlaZcyc4u3IlPoVAU+QVKsg+ybJEkydZYvIJfq1YtrYIwKSmJ1q1bF/t6rVq11JVtIQQKhUK9vzje3t6FWszc3Nz0jlXV6u7q6sr9+/f1Pg+gffv2NpfubvHixaSnp+Pm5qZXa6M1mSNWNze3QgMZs7KydFbYJPslhOC5556jd+/e6sG3oJyJV9WKr1l+qMqc6tWrc+fOHapVq1bs9UtTrpQvX75QJT8yMrLQcWX9b9VczBWrLFskeyD/Vs3HJuMVFpadnS38/PzE9evXxb1790SjRo1ESkqK1jEhISHi9OnTIicnR7Rp00YkJCQIIYQYOHCg2Lp1qxBCiKioKBEbG6vzPeLi4gQg4uLiTB6/p6enAHQuPj4+Jn8/U/Lx8bGLOIWwXKzmvFcky9i3b5+IjIxUb0+fPl2MGTOm0HFvvPGGWLp0qRBCiKlTp4pPPvlECCHE//3f/4mpU6cKIYRYunSpmDJlis73MdW9Ur58eXWZERUVpfMY+bdqHpaMVZYtkr4sda/Iv1XzscU6i8UH2ZYrV45FixYRHh5OcHAwU6dOxcvLi969e5OcnAzAsmXLePbZZ2nUqBEREREEBgYCsGDBAqKjo2nQoAEeHh7qAbeWlJqaihACIYS6xcbHxwchhMyCIUkW1q1bNwYPHsyOHTvw9fXl4MGDLFiwgGPHjhEcHExwcDC7d+8GYMaMGaxfvx4/Pz8uXbrESy+9BMDYsWO5dOkSfn5+rF+/nrffftusMWdlZanLkPXr15v1vSRJkqSyyeIVfID+/ftz4cIFLl26xMsvvwzAjh071I/M27Zty2+//cbly5eZPXu2+ryGDRsSFxfH5cuX+fzzz3Fy0j/8GzduMHv2bHVGDVMda+33L+ux2koMknXs2bOHW7du8fDhQ65fv07Hjh0RQvDbb79x6tQpTp06Rc+ePQFl15oDBw5w6dIlNm/eTOXKlQGoXLkymzdv5tKlSxw4cABvb2+9398W7j19r2tPsZrzWH1Z+/2lsssW7j35t2r9322p39+szxKsRNcjDEMea+h7rCGPZMzx/oYeq2+89hRraWOQj9ElfVmqXBHCPPe/PcVqrmMtGassWyR9leZzSf6tWj9Wc8Vb2nLFIbPoZGRkAMqnAomJiVSvXl09c5s+0/yqjinpWFUatKysLOLj401yTXMeq2+89hSrsTEcPnyYxMRErly5Ajy+ZySpKJYqV8A897+9/q3aW5l969YtUlJSZNki6U11jxS85+Tfqn3ECpYrs1Xr+pQrCiEcL4/jmjVrDJrOV5JiYmIYMWKEtcOQbJgsVyRjyLJFKoksWyRD6VOuOGQFPyUlhbVr11KlShUqVqxI9erVDepXKzk+VSvbo0ePePjwIcOGDaN69erWDkuyYbJckfQhyxbJUCkpKezevZu6deuqxwZJki4ZGRlcvXqVnj17lliuOGQFX5IkSZIkSZLKKqtk0ZEkSZIkSZIkyTxkBV+SJEmSJEmSHIis4Otp4MCBeHh4EBUVpfP1Tp060bx5c5o2bcr7779v4ei0lRQrQF5eHm3atCn2GEsoKdawsDCaNGminrRIZqSQHIksV8xHli1SWSbLFvOwp3JFVvD1NGnSJL755psiX9+2bRunT58mISGBHTt2cPLkSQtGp62kWAG+/PJL6tata5mAiqFPrBs2bFBPWiQHIEmORJYr5iPLFqksk2WLedhTuSIr+HoKCwvD1dW1yNfd3NwAyM7OJjs7G4VCYanQCikp1tu3b7N27Vr1LMLWVFKskuTIZLliPrJskcoyWbaYhz2VK7KCb0Lt27fniSeeoFu3bgQHB1s7nCLNnDmTWbNm4ezsbO1Q9DJ8+HBatGjB4sWLrR2KJFmcLFfMR5YtUlkmyxbzsJVyRVbwTejw4cMkJydz6tQpzp49a+1wdDp58iRpaWmEhYVZOxS9rFmzhoSEBPbv38+WLVvYvn27tUOSJIuS5Yp5yLJFKutk2WJ6tlSuyAq+ibm6utK1a1d27dpl7VB0Onr0KAcPHqRu3boMGzaMnTt32sRjr6L4+PgA4O7uzpAhQzh+/LiVI5Iky5PliunJskWSZNliarZUrsgKvgncvXuXW7duAfDo0SN2795NkyZNrByVbhMmTCApKYmrV6+ydu1aevXqxeeff27tsHTKyckhJSUFgKysLHbu3ElAQICVo5Iky5DlivnIskUqy2TZYh62Vq7ICr6eunXrxuDBg9mxYwe+vr4cOXKE3r17k5yczJ07d+jVqxdBQUGEhITQuXNn+vbta5Ox2priYn306BE9e/YkKCiIFi1a0KxZM6unyJIkU5LlivnIskUqy2TZYh72VK4ohBDCau8uSZIkSZIkSZJJyRZ8SZIkSZIkSXIgsoIvSZIkSZIkSQ5EVvAlSZIkSZIkyYHICr4kSZIkSZIkORBZwZckSZIkSZIkByIr+JIkSZIkSZLkQGQFX5IkSZIkSZIciKzgS5IkSZIkSZIDKfMV/Lp169K4cWOCg4Np2rQp//nPf0o8Z/bs2WRmZpb6vXVdJzg4mHv37pV4rkKh4M6dO4X2HzlyhKpVqxIcHKxewsPDSx2rLpq/u8aNG/PBBx9ovXbq1Cmt48PCwti8ebPO81XLmTNndL7X4MGDOXLkCAC9e/dm2bJlhY5p3rw5GzdupGPHjly5cqX0P6AkGUmWK8aT5YokFU2WLcYrc2WLKOPq1KkjTp48KYQQ4urVq8LNzU2cPn262HMAkZaWVur3Ls11ijp36dKlYtiwYaULTE+av7vr168LNzc38euvvxZ6TaVz585i06ZNOs8vzq+//iq6dOmi3t6wYYNo2bKl1jHHjx8X3t7eIisrS2zatEmMGjXKqJ9JkkxBlivGk+WKJBVNli3GK2tlS5lvwddUp04dGjduzIULF9i9ezctW7YkKCiIzp07c+7cOQDGjx8PQMeOHQkODubmzZscP36cLl26EBoaSosWLVi/fr36mgqFgnnz5tG6dWvq1avHypUri7yO6njVt9wRI0YQGhpKUFAQffr04e+//y7xZ4iPj6dVq1YlHjd37lwmTpyo3r5//z6enp789ddfDB06lKZNm9K8eXN69Oihx28OfHx8aNKkCdeuXdPreEMsX76c4cOHq7f79+/PX3/9RUJCgnrfV199xXPPPUf58uXp06cPO3fu5O7duyaPRZIMJcsVWa5IkjnIskWWLcUy+VcGO6P5jSwhIUG4urqKo0ePCk9PT5GQkCCEECImJkb4+/uLvLw8IYT2N9G0tDQRHBwskpOThRBC3Lp1Szz11FPi+vXr6mM/+ugjIYQQiYmJwsXFRWRnZxe6jormvps3b6r3z58/X4wbN07ncZqCgoKEn5+faN68uXr5559/Ch33559/Cm9vb5GZmSmEEOKrr74SgwYNEhs3bhQ9evRQH5eamqrX7y4xMVE0aNBAHXOdOnVEo0aNtOKoWrVqoW/DBY95+PBhofepX7++OHPmjNa+KVOmiEmTJgkhhMjIyBDVqlUT586dU78eHh4utm7dWmTskmROslyR5YokmYMsW2TZoi9Zwdf4D2vXrp1Yv369iI2NFZ07d9Y6zt3dXfz1119CCO0bdfv27cLNzU3rP/ypp54Se/fuVR9748YN9XWqVaum8zoqmvuWLFkiQkJCREBAgGjQoIFo06aNzuNUMjIyRIUKFcT9+/f1+tl79Ogh1q1bJ4QQolOnTmLr1q3i8uXL4qmnnhITJkwQa9euFenp6SX+7po0aSIUCoVYsmSJ1mumetxVoUIFrYJDCCF+++03Ub16dfHo0SOxZs0a0a5dO63Xn332WfHZZ5+VeG1JMgdZrshyRZLMQZYtsmzRVznTPg+wT99//z3BwcHq7a1bt+p9rhCCgIAADh8+XOQxlSpVUq87OzuTk5NT4nV/+eUXPvnkE44cOcITTzxBbGws7777brHnJCQk4OPjQ9WqVfWK/YUXXmDlypWEhIRw6dIlIiIiKFeuHOfOneOnn35iz549TJs2jVOnTuHh4aHzGqrf3Z49e+jXrx9dunQhMDBQr/fXV5UqVQoN7GnatCl+fn5s3bqVr776ihdffFHr9czMTCpXrmzSOCTJELJckeWKJJmDLFtk2aIP2Qdfh7Zt23LmzBnOnj0LwNq1a/Hx8cHHxwcAV1dXdV+p9u3bc+XKFfbs2aM+/9SpU2RlZZX4PprXKSgtLQ1XV1e8vLzIyspi+fLlJV4vPj6eZs2alXicyjPPPMPx48eZP38+I0eOpFy5cly/fh2FQkH//v356KOPEELw119/lXitbt26MWHCBP71r3/p/f76CgoK4vfffy+0/8UXX2TevHkcO3aMoUOHar2WmJhI8+bNTR6LJBlLliuyXJEkc5BliyxbdJEVfB28vb1Zs2YNzz33HEFBQXz22WesX78ehUIBwNSpU+nevTvBwcFkZ2ezfft25s2bR/PmzWnatClvv/02eXl5Jb6P5nVUA1ZUIiIiaNy4MY0bN1YPailJXFwchw8f1krhNHv27CKPr1ixIkOGDGHFihU8//zzAJw5c4YOHTrQvHlzWrRowahRowgKCirxvQFmzZrFL7/8QlxcnF7HAwwdOlQr3n379hU6Jioqit27d+s89/fff2fw4MG4uLio91+9epXc3Fz5QSzZFFmuyHJFksxBli2ybNFFIYQQJr2iJJnY/fv3ad++vTpfbknefvtt/Pz8eOmllywQnSRJ9kiWK5IkmYOtlC2yBV+yeS4uLnz88cd6TwRRq1YtXnjhBTNHJUmSPZPliiRJ5mArZYtswZckSZIkSZIkByJb8CVJkiRJkiTJgcgKviRJkiRJkiQ5EFnBlyRJkiRJkiQHIiv4kiRJkiRJkuRAZAVfkiRJkiRJkhyIrOBLkiRJkiRJkgORFXxJkiRJkiRJciCygi9JkiRJkiRJDkRW8CVJkiRJkiTJgcgKviRJkiRJkiQ5kP8HeRP/ZBPbEL0AAAAASUVORK5CYII=' width=800.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import lmfit as lf\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import root_scalar\n",
    "from lmfit import Model\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "\n",
    "\n",
    "# Constants\n",
    "R  = 8.314462618\n",
    "F  = 96485.33212\n",
    "T  = 298.15\n",
    "z  = 1.0\n",
    "\n",
    "\n",
    "\n",
    "def temkin_E(theta, E0, g):\n",
    "    \"\"\"Temkin (Frumkin) isotherm E(theta).\"\"\"\n",
    "    th = np.clip(theta, 1e-9, 1-1e-9)\n",
    "    return E0 + R*T/(z*F)*(np.log(th/(1.0-th)) + g*th)\n",
    "\n",
    "def temkin_dtheta_dE(theta, g):\n",
    "    \"\"\"Temkin derivative dθ/dE (shape of pseudocapacitance).\"\"\"\n",
    "    th = np.clip(theta, 1e-9, 1-1e-9)\n",
    "    denom = (1.0/th) + (1.0/(1.0-th)) + g\n",
    "    return z*F/(R*T) / denom\n",
    "\n",
    "def invert_temkin_thetas(E_arr, E0, g):\n",
    "    \"\"\"\n",
    "    Solve ln(theta/(1-theta)) + g*theta - zF/RT*(E - E0) = 0\n",
    "    for each E in E_arr with Brent's method.\n",
    "    Returns theta(E) in (0,1); NaN on failures.\n",
    "    \"\"\"\n",
    "    E_arr = np.asarray(E_arr, dtype=float).ravel()\n",
    "    thetas = np.full_like(E_arr, np.nan, dtype=float)\n",
    "    for i, Ei in enumerate(E_arr):\n",
    "        def f(theta):\n",
    "            th = np.clip(theta, 1e-12, 1-1e-12)\n",
    "            return np.log(th/(1.0-th)) + g*th - (z*F)/(R*T)*(Ei - E0)\n",
    "        try:\n",
    "            sol = root_scalar(f, bracket=[1e-9, 1.0-1e-9], method='brentq')\n",
    "            if sol.converged:\n",
    "                thetas[i] = sol.root\n",
    "        except Exception:\n",
    "            pass\n",
    "    return thetas\n",
    "\n",
    "\n",
    "def residuals_temkin_theta(pars, E, Theta_abs):\n",
    "    \"\"\"\n",
    "    Fit theta only:\n",
    "    theta_model(E; E0,g)  vs  Θ_abs(E)\n",
    "    theta_abs is interpreted theta_rel in [0,1] (full 0 -> 1 transition).\n",
    "    \"\"\"\n",
    "    E0 = pars['E0'].value\n",
    "    g  = pars['g'].value\n",
    "\n",
    "    # Keep E(theta) invertible/monotone: g > -4\n",
    "    if g <= -3.99:\n",
    "        return 1e6*np.ones_like(E, dtype=float)\n",
    "\n",
    "    E         = np.asarray(E).ravel()\n",
    "    Theta_abs = np.asarray(Theta_abs).ravel()\n",
    "\n",
    "    theta_model = invert_temkin_thetas(E, E0, g)\n",
    "    m = np.isfinite(theta_model) & np.isfinite(Theta_abs)\n",
    "    if m.sum() < 5:\n",
    "        return 1e6*np.ones_like(E)\n",
    "\n",
    "    r = theta_model[m] - Theta_abs[m]\n",
    "    return r\n",
    "\n",
    "\n",
    "def mpe_model(theta, lam, theta_c, M_lo, dM):\n",
    "    # M(θ) = M_lo + dM * exp( -lam*(θ - theta_c)^2 / (R*T) )\n",
    "    return M_lo + dM * np.exp(-lam * (theta - theta_c)**2 / (R*T))\n",
    "\n",
    "###Pretreatment###\n",
    "# Select window (adjust bounds as needed)\n",
    "istart = np.argmin(np.abs(convert_potential(fwd_pot[fwd_mask]) - 1.28))\n",
    "istop  = np.argmin(np.abs(convert_potential(fwd_pot[fwd_mask]) - 1.52))\n",
    "E = convert_potential(fwd_pot[fwd_mask][istart:istop]).astype(float)\n",
    "\n",
    "# Current -> differential capacitance\n",
    "sweep_rate = 5e-3  # V/s (5 mV/s)\n",
    "current_density = (df['current (mA)'][:turning_idx+1][fwd_mask][istart:istop].to_numpy() / 1.17) * 1e-3  # A\n",
    "C_raw = current_density / sweep_rate  # F\n",
    "\n",
    "# Background (DL) capacitance estimate from window edges\n",
    "edge = max(5, len(C_raw)//10)\n",
    "Cdl_est = 0.5*(np.median(C_raw[:edge]) + np.median(C_raw[-edge:]))\n",
    "C_background = np.full_like(C_raw, Cdl_est)\n",
    "C = C_raw - C_background  # pseudocapacitance\n",
    "\n",
    "# Integrate C(E) -> Q(E)\n",
    "dE = np.diff(E)\n",
    "Q = np.zeros_like(E, dtype=float)\n",
    "Q[1:] = np.cumsum(0.5*(C[1:] + C[:-1]) * dE)   # C cm-2 (per area)\n",
    "\n",
    "# Assume the window covers the full 0 ->1 transition -> treat theta_rel as absolute theta\n",
    "Qmin, Qmax = np.nanmin(Q), np.nanmax(Q)\n",
    "Theta_rel = (Q - Qmin) / (Qmax - Qmin)   # used as theta_abs in fit\n",
    "\n",
    "\n",
    "mask = np.isfinite(E) & np.isfinite(Theta_rel)\n",
    "E_fitdat, Th_fitdat = np.asarray(E)[mask], np.asarray(Theta_rel)[mask]\n",
    "\n",
    "params = lf.Parameters()\n",
    "params.add('E0', value=float(np.median(E_fitdat)), min=float(E_fitdat.min()-1.0), max=float(E_fitdat.max()+1.0))\n",
    "params.add('g',  value=1.0,                        min=-3.9,                      max=5.0)  # keep > -4\n",
    "\n",
    "mini = lf.Minimizer(\n",
    "    residuals_temkin_theta, params,\n",
    "    fcn_args=(E_fitdat, Th_fitdat),\n",
    "    nan_policy='omit'\n",
    ")\n",
    "result = mini.minimize(method='least_squares', loss='soft_l1', f_scale=1.0)\n",
    "lf.report_fit(result)\n",
    "\n",
    "# Reconstruct model coverage on E-grid\n",
    "E0 = result.params['E0'].value\n",
    "g  = result.params['g'].value\n",
    "theta_fit = invert_temkin_thetas(E_fitdat, E0, g)\n",
    "\n",
    "#compute C(E) from theta(E) (NOT considered for fitting)\n",
    "\n",
    "Cshape = temkin_dtheta_dE(theta_fit, g)  # shape-only pseudocapacitance\n",
    "# Comparison of C(E) to measured C:\n",
    "if np.isfinite(C).any():\n",
    "    C_fitdat = np.asarray(C)[mask]\n",
    "    num = np.nansum(C_fitdat * Cshape)\n",
    "    den = np.nansum(Cshape * Cshape)\n",
    "    Aopt = num/den if (den > 0 and np.isfinite(den)) else 0.0\n",
    "    C_model = Aopt * Cshape\n",
    "else:\n",
    "    Aopt = np.nan\n",
    "    C_model = np.full_like(Cshape, np.nan)\n",
    "\n",
    "\n",
    "#obtain MPE from theta\n",
    "MPEmodel = Model(mpe_model)\n",
    "experimental_MPE = fwd_MPE[fwd_mask][istart:istop]\n",
    "\n",
    "MPEmodel.set_param_hint('lam',     value=1.0e4)  # J/mol\n",
    "MPEmodel.set_param_hint('theta_c', value=0.5,   min=0.0,   max=1.0)\n",
    "MPEmodel.set_param_hint('M_lo',    value=30, min = 30, vary = True)                  # unbounded\n",
    "MPEmodel.set_param_hint('dM',      value=30, min=0.0)           # non-negative\n",
    "params_mpe = MPEmodel.make_params()\n",
    "result_mpe = MPEmodel.fit(experimental_MPE, params_mpe, theta=theta_fit, method='least_squares', nan_policy='omit')\n",
    "print(result_mpe.fit_report())\n",
    "MPE_model = result_mpe.best_fit\n",
    "\n",
    "#plot the results\n",
    "plt.rcParams['figure.dpi'] = 100\n",
    "plt.rcParams['font.size'] = 7\n",
    "plt.rcParams['axes.labelsize'] = 8\n",
    "plt.rcParams['axes.titlesize'] = 8\n",
    "plt.rcParams['legend.fontsize'] = 7\n",
    "plt.rcParams['xtick.labelsize'] = 7\n",
    "plt.rcParams['ytick.labelsize'] = 7\n",
    "plt.rcParams['xtick.direction'] = 'in'\n",
    "plt.rcParams['ytick.direction'] = 'in'\n",
    "plt.rcParams['xtick.major.size'] = 4\n",
    "plt.rcParams['ytick.major.size'] = 4\n",
    "plt.rcParams['xtick.major.width'] = 2\n",
    "plt.rcParams['ytick.major.width'] = 2\n",
    "plt.rcParams['xtick.minor.size'] = 2\n",
    "plt.rcParams['ytick.minor.size'] = 2\n",
    "plt.rcParams['xtick.minor.width'] = 1\n",
    "plt.rcParams['ytick.minor.width'] = 1\n",
    "plt.rcParams['xtick.top'] = True\n",
    "plt.rcParams['ytick.right'] = True\n",
    "plt.rcParams['axes.linewidth'] = 1.0\n",
    "plt.rcParams['lines.linewidth'] = 1.5\n",
    "plt.rcParams['lines.markersize'] = 6\n",
    "plt.rcParams['legend.loc'] = 'upper left'\n",
    "plt.rcParams['legend.frameon'] = False\n",
    "plt.rcParams['savefig.dpi'] = 300\n",
    "plt.rcParams['savefig.bbox'] = 'tight'\n",
    "\n",
    "fig, axs  = plt.subplots(nrows = 1, ncols = 3, figsize=(8, 2))\n",
    "fig.subplots_adjust(left=0.08, right=0.95, bottom=0.2, top=0.95, wspace=1, hspace=1)\n",
    "\n",
    "# current density\n",
    "axs[0].plot(E_fitdat, current_density[mask] * 1e6, '.', fillstyle='none', linestyle='none', ms=4, color='black')\n",
    "axs[0].set_xlabel('Potential $E$ vs RHE (V)')\n",
    "axs[0].set_ylabel('Current density $i (E)$ ($\\\\mathrm{\\\\mu A\\\\ cm^{-2}}$)')\n",
    "axs[0].legend(frameon=False)\n",
    "axs[0].yaxis.set_major_locator(MaxNLocator(nbins=5))\n",
    "axs[0].yaxis.set_minor_locator(AutoMinorLocator(n = 5))\n",
    "axs[0].xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "\n",
    "\n",
    "# charge density\n",
    "axs[1].plot(E_fitdat, Q[mask] * 1e6, '.', fillstyle='none', linestyle='none', ms=4, color='black')\n",
    "axs[1].set_xlabel('Potential $E$ vs RHE (V)')\n",
    "axs[1].set_ylabel('Amount of transferred charge \\n $Q(E)$ ($\\\\mathrm{\\\\mu C\\\\ cm^{-2}}$)')\n",
    "axs[1].legend(frameon=False)\n",
    "axs[1].yaxis.set_major_locator(MaxNLocator(nbins=5))\n",
    "axs[1].yaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[1].xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "\n",
    "\n",
    "\n",
    "# theta vs E (fitted)\n",
    "axs[2].plot(E_fitdat, Th_fitdat, '.', ms=4, label='experiment', color='black', fillstyle = 'none')\n",
    "axs[2].plot(E_fitdat, theta_fit, '-', lw=2, label='fit', color='red')\n",
    "axs[2].set_xlabel('Potential $E$ vs RHE (V)')\n",
    "axs[2].set_ylabel('Fractional conversion $\\mathrm{\\\\theta}$')\n",
    "axs[2].legend(frameon=False, handlelength=1)\n",
    "axs[2].yaxis.set_major_locator(MaxNLocator(nbins=5))\n",
    "axs[2].yaxis.set_minor_locator(AutoMinorLocator(n = 5))\n",
    "axs[2].xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[2].set_ylim(bottom = -0.15, top = 1.05)\n",
    "\n",
    "\n",
    "for ax in np.ravel(axs):\n",
    "    ax.margins(x=0.17, y=0.2)\n",
    "plt.savefig(fname=\"Temkin_theta.tif\", dpi=600,\n",
    "            pil_kwargs={\"compression\": \"tiff_lzw\"},\n",
    "            bbox_inches='tight', transparent=True)\n",
    "plt.show()\n",
    "\n",
    "\n",
    "fig, axs  = plt.subplots(nrows = 1, ncols = 3, figsize=(8, 2))\n",
    "fig.subplots_adjust(left=0.08, right=0.95, bottom=0.2, top=0.95, wspace=1, hspace=1)\n",
    "\n",
    "# theta vs E (fitted)\n",
    "axs[0].plot(E_fitdat, Th_fitdat, '.', ms=4, label='experiment', color='black', fillstyle = 'none')\n",
    "axs[0].plot(E_fitdat, theta_fit, '-', lw=2, label='fit', color='red')\n",
    "axs[0].set_xlabel('Potential $E$ vs RHE (V)')\n",
    "axs[0].set_ylabel('Fractional conversion $\\mathrm{\\\\theta}$')\n",
    "axs[0].legend(frameon=False, handlelength=1)\n",
    "axs[0].yaxis.set_major_locator(MaxNLocator(nbins=5))\n",
    "axs[0].yaxis.set_minor_locator(AutoMinorLocator(n = 5))\n",
    "axs[0].xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[0].set_ylim(bottom = -0.05, top = 1.05)\n",
    "\n",
    "# differential capacitances\n",
    "axs[1].plot(E_fitdat, (C[mask] + C_background[mask]) * 1e6, '.', fillstyle='none', linestyle='none',\n",
    "          ms=4, label='experiment', color='black')\n",
    "if np.isfinite(C_model).any():\n",
    "    axs[1].plot(E_fitdat, (C_model + C_background[mask]) * 1e6, '-', lw=2, label='prediction', color='red')\n",
    "axs[1].plot(E_fitdat,  C_background[mask] * 1e6, '-', ms=4, label='background', color='blue')\n",
    "axs[1].set_xlabel('Potential $E$ vs RHE (V)')\n",
    "axs[1].set_ylabel('Differential capacitance \\n $C(E)$ ($\\\\mathrm{\\\\mu F\\\\ cm^{-2}}$)')\n",
    "handles, labels = axs[1].get_legend_handles_labels()\n",
    "order = ['experiment', 'prediction', 'background']   # put your labels here, in the order you want\n",
    "idx = [labels.index(l) for l in order if l in labels]\n",
    "axs[1].legend([handles[i] for i in idx], [labels[i] for i in idx], frameon=False, handlelength=1, ncols = 1)\n",
    "axs[1].yaxis.set_major_locator(MaxNLocator(nbins=6))\n",
    "axs[1].yaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[1].xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[1].set_ylim(1175, 1725)\n",
    "\n",
    "# Panel 5: MPE vs potential (fitted MPE with theta(E) as input)\n",
    "axs[2].plot(E, fwd_MPE[fwd_mask][istart:istop], marker='.', fillstyle='none', ms = 4,\n",
    "                linestyle='none', label='experiment', color='black')\n",
    "\n",
    "axs[2].plot(E_fitdat, MPE_model, '-', lw=2, color='red', label='fit')\n",
    "axs[2].set_xlabel('Potential $E$ vs RHE (V)')\n",
    "axs[2].set_ylabel('MPE (g mol$^{-1}$)')\n",
    "axs[2].legend(frameon=False, handlelength=1, loc = 'lower left')\n",
    "axs[2].yaxis.set_major_locator(MaxNLocator(nbins=4))\n",
    "axs[2].yaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "axs[2].xaxis.set_minor_locator(AutoMinorLocator(n = 4))\n",
    "\n",
    "for ax in np.ravel(axs):\n",
    "    ax.margins(x=0.17, y=0.2)\n",
    "plt.savefig(fname=\"Temkin_theta_MPE.tif\", dpi=600,\n",
    "            pil_kwargs={\"compression\": \"tiff_lzw\"},\n",
    "            bbox_inches='tight', transparent=True)\n",
    "plt.show()\n"
   ]
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