{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ce9d2ed1-3fba-416f-971c-a7babaf4425a",
   "metadata": {},
   "source": [
    "# Propagating uncertainties in fluid inclusion barometry\n",
    "- This notebook shows how to propagate uncertainty when performing fluid inclusion barometry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fd37aa53-66e7-4f06-b3ef-a048433ae784",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.0.1'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import DiadFit as pf\n",
    "pf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e4a04f0-47bb-4129-865f-5275b1216358",
   "metadata": {},
   "source": [
    "### Load in the data\n",
    "- You can call your column headings whatever you want, just swap the text when it references them later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4f32d34a-ccfd-40d0-a963-298dbe168be4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sample</th>\n",
       "      <th>Density_g_cm3</th>\n",
       "      <th>T_C</th>\n",
       "      <th>XH2O</th>\n",
       "      <th>Host_Fo_content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>1048.898738</td>\n",
       "      <td>0.086258</td>\n",
       "      <td>0.897797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>1015.924767</td>\n",
       "      <td>0.085212</td>\n",
       "      <td>0.831850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>1041.589916</td>\n",
       "      <td>0.085462</td>\n",
       "      <td>0.883180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>1034.935183</td>\n",
       "      <td>0.085167</td>\n",
       "      <td>0.869870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>1034.820102</td>\n",
       "      <td>0.085708</td>\n",
       "      <td>0.869640</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Sample  Density_g_cm3          T_C      XH2O  Host_Fo_content\n",
       "0    FI1       0.458055  1048.898738  0.086258         0.897797\n",
       "1    FI2       0.492947  1015.924767  0.085212         0.831850\n",
       "2    FI4       0.484594  1041.589916  0.085462         0.883180\n",
       "3    FI5       0.494431  1034.935183  0.085167         0.869870\n",
       "4    FI7       0.476416  1034.820102  0.085708         0.869640"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get from here - https://github.com/PennyWieser/DiadFit/blob/main/docs/Examples/EOS_calculations/Fluid_Inclusion_Densities_Example1.xlsx\n",
    "df=pd.read_excel('Fluid_Inclusion_Densities_Example1.xlsx', sheet_name='Diff_Temps')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60800584-aede-44bd-8820-a33f85dec089",
   "metadata": {},
   "source": [
    "## Propagating uncertainty in temperature\n",
    "- Lets say the uncertainty in temperature is +-50K. So this is an absolute error, and we want temperature distributed normally\n",
    "- We want to use a single step profile initially to convert pressure to depth\n",
    "- We want to make 1000 duplicates per FI with temperature varying by 1 sigma=50K\n",
    "- It outputs MC_Av, which is the average for each fluid inclusion, and MC_All, which contains rows for each of the N duplicates you asked for appended end-on-end\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "417d7a41",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are not using multiprocessing based on your selected EOS. You can override this by setting multiprocess=True in the function, but for SP94 and SW96 it might actually be slower\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing: 100%|██████████| 60/60 [00:01<00:00, 32.92it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>CO2_dens_gcm3</th>\n",
       "      <th>SingleCalc_D_km</th>\n",
       "      <th>SingleCalc_P_kbar</th>\n",
       "      <th>Mean_MC_P_kbar</th>\n",
       "      <th>Med_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar_from_percentile</th>\n",
       "      <th>Mean_MC_D_km</th>\n",
       "      <th>Med_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km_from_percentile</th>\n",
       "      <th>T_K_input</th>\n",
       "      <th>error_T_K</th>\n",
       "      <th>CO2_dens_gcm3_input</th>\n",
       "      <th>error_CO2_dens_gcm3</th>\n",
       "      <th>crust_dens_kgm3_input</th>\n",
       "      <th>error_crust_dens_kgm3</th>\n",
       "      <th>model</th>\n",
       "      <th>EOS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>6.357853</td>\n",
       "      <td>1.684004</td>\n",
       "      <td>1.685286</td>\n",
       "      <td>1.685877</td>\n",
       "      <td>0.072431</td>\n",
       "      <td>0.071137</td>\n",
       "      <td>6.362691</td>\n",
       "      <td>6.364923</td>\n",
       "      <td>0.273457</td>\n",
       "      <td>0.268572</td>\n",
       "      <td>1322.048738</td>\n",
       "      <td>50</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>6.918818</td>\n",
       "      <td>1.832587</td>\n",
       "      <td>1.831854</td>\n",
       "      <td>1.832474</td>\n",
       "      <td>0.086385</td>\n",
       "      <td>0.087010</td>\n",
       "      <td>6.916050</td>\n",
       "      <td>6.918390</td>\n",
       "      <td>0.326140</td>\n",
       "      <td>0.328502</td>\n",
       "      <td>1289.074767</td>\n",
       "      <td>50</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>6.891995</td>\n",
       "      <td>1.825483</td>\n",
       "      <td>1.822461</td>\n",
       "      <td>1.821793</td>\n",
       "      <td>0.082639</td>\n",
       "      <td>0.082694</td>\n",
       "      <td>6.880586</td>\n",
       "      <td>6.878064</td>\n",
       "      <td>0.311999</td>\n",
       "      <td>0.312206</td>\n",
       "      <td>1314.739916</td>\n",
       "      <td>50</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>7.071963</td>\n",
       "      <td>1.873151</td>\n",
       "      <td>1.874001</td>\n",
       "      <td>1.874879</td>\n",
       "      <td>0.080538</td>\n",
       "      <td>0.082679</td>\n",
       "      <td>7.075173</td>\n",
       "      <td>7.078488</td>\n",
       "      <td>0.304065</td>\n",
       "      <td>0.312150</td>\n",
       "      <td>1308.085183</td>\n",
       "      <td>50</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>6.670854</td>\n",
       "      <td>1.766909</td>\n",
       "      <td>1.767672</td>\n",
       "      <td>1.766460</td>\n",
       "      <td>0.079613</td>\n",
       "      <td>0.077064</td>\n",
       "      <td>6.673735</td>\n",
       "      <td>6.669158</td>\n",
       "      <td>0.300574</td>\n",
       "      <td>0.290949</td>\n",
       "      <td>1307.970102</td>\n",
       "      <td>50</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Filename  CO2_dens_gcm3  SingleCalc_D_km  SingleCalc_P_kbar  Mean_MC_P_kbar  \\\n",
       "0      FI1       0.458055         6.357853           1.684004        1.685286   \n",
       "1      FI2       0.492947         6.918818           1.832587        1.831854   \n",
       "2      FI4       0.484594         6.891995           1.825483        1.822461   \n",
       "3      FI5       0.494431         7.071963           1.873151        1.874001   \n",
       "4      FI7       0.476416         6.670854           1.766909        1.767672   \n",
       "\n",
       "   Med_MC_P_kbar  std_dev_MC_P_kbar  std_dev_MC_P_kbar_from_percentile  \\\n",
       "0       1.685877           0.072431                           0.071137   \n",
       "1       1.832474           0.086385                           0.087010   \n",
       "2       1.821793           0.082639                           0.082694   \n",
       "3       1.874879           0.080538                           0.082679   \n",
       "4       1.766460           0.079613                           0.077064   \n",
       "\n",
       "   Mean_MC_D_km  Med_MC_D_km  std_dev_MC_D_km  \\\n",
       "0      6.362691     6.364923         0.273457   \n",
       "1      6.916050     6.918390         0.326140   \n",
       "2      6.880586     6.878064         0.311999   \n",
       "3      7.075173     7.078488         0.304065   \n",
       "4      6.673735     6.669158         0.300574   \n",
       "\n",
       "   std_dev_MC_D_km_from_percentile    T_K_input  error_T_K  \\\n",
       "0                         0.268572  1322.048738         50   \n",
       "1                         0.328502  1289.074767         50   \n",
       "2                         0.312206  1314.739916         50   \n",
       "3                         0.312150  1308.085183         50   \n",
       "4                         0.290949  1307.970102         50   \n",
       "\n",
       "   CO2_dens_gcm3_input  error_CO2_dens_gcm3  crust_dens_kgm3_input  \\\n",
       "0             0.458055                    0                   2700   \n",
       "1             0.492947                    0                   2700   \n",
       "2             0.484594                    0                   2700   \n",
       "3             0.494431                    0                   2700   \n",
       "4             0.476416                    0                   2700   \n",
       "\n",
       "   error_crust_dens_kgm3 model   EOS  \n",
       "0                    0.0  None  SW96  \n",
       "1                    0.0  None  SW96  \n",
       "2                    0.0  None  SW96  \n",
       "3                    0.0  None  SW96  \n",
       "4                    0.0  None  SW96  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MC_Av_Tonly, MC_All_Tonly, fig=pf.propagate_FI_uncertainty(T_K=df['T_C']+273.15,\n",
    "error_T_K=50, error_type_T_K='Abs', error_dist_T_K='normal',\n",
    "                        CO2_dens_gcm3=df['Density_g_cm3'],\n",
    "                        sample_ID=df['Sample'],\n",
    "                        crust_dens_kgm3=2700, EOS='SW96',\n",
    "                        N_dup=1000, fig_i=0, plot_figure=True)\n",
    "MC_Av_Tonly.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72ee685a-1dc4-4515-982a-d03459e3dd2c",
   "metadata": {},
   "source": [
    "### Plot each FI and its 1 sigma error\n",
    "-  Lets plot the pressure of the inputted FI (SingleFI_P_kbar), and then the standard deviation of the MC simulation against the Fo content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eea38908",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>CO2_dens_gcm3</th>\n",
       "      <th>SingleCalc_D_km</th>\n",
       "      <th>SingleCalc_P_kbar</th>\n",
       "      <th>Mean_MC_P_kbar</th>\n",
       "      <th>Med_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar_from_percentile</th>\n",
       "      <th>Mean_MC_D_km</th>\n",
       "      <th>Med_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km_from_percentile</th>\n",
       "      <th>T_K_input</th>\n",
       "      <th>error_T_K</th>\n",
       "      <th>CO2_dens_gcm3_input</th>\n",
       "      <th>error_CO2_dens_gcm3</th>\n",
       "      <th>crust_dens_kgm3_input</th>\n",
       "      <th>error_crust_dens_kgm3</th>\n",
       "      <th>model</th>\n",
       "      <th>EOS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>6.357853</td>\n",
       "      <td>1.684004</td>\n",
       "      <td>1.685286</td>\n",
       "      <td>1.685877</td>\n",
       "      <td>0.072431</td>\n",
       "      <td>0.071137</td>\n",
       "      <td>6.362691</td>\n",
       "      <td>6.364923</td>\n",
       "      <td>0.273457</td>\n",
       "      <td>0.268572</td>\n",
       "      <td>1322.048738</td>\n",
       "      <td>50</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>6.918818</td>\n",
       "      <td>1.832587</td>\n",
       "      <td>1.831854</td>\n",
       "      <td>1.832474</td>\n",
       "      <td>0.086385</td>\n",
       "      <td>0.087010</td>\n",
       "      <td>6.916050</td>\n",
       "      <td>6.918390</td>\n",
       "      <td>0.326140</td>\n",
       "      <td>0.328502</td>\n",
       "      <td>1289.074767</td>\n",
       "      <td>50</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>6.891995</td>\n",
       "      <td>1.825483</td>\n",
       "      <td>1.822461</td>\n",
       "      <td>1.821793</td>\n",
       "      <td>0.082639</td>\n",
       "      <td>0.082694</td>\n",
       "      <td>6.880586</td>\n",
       "      <td>6.878064</td>\n",
       "      <td>0.311999</td>\n",
       "      <td>0.312206</td>\n",
       "      <td>1314.739916</td>\n",
       "      <td>50</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>7.071963</td>\n",
       "      <td>1.873151</td>\n",
       "      <td>1.874001</td>\n",
       "      <td>1.874879</td>\n",
       "      <td>0.080538</td>\n",
       "      <td>0.082679</td>\n",
       "      <td>7.075173</td>\n",
       "      <td>7.078488</td>\n",
       "      <td>0.304065</td>\n",
       "      <td>0.312150</td>\n",
       "      <td>1308.085183</td>\n",
       "      <td>50</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>6.670854</td>\n",
       "      <td>1.766909</td>\n",
       "      <td>1.767672</td>\n",
       "      <td>1.766460</td>\n",
       "      <td>0.079613</td>\n",
       "      <td>0.077064</td>\n",
       "      <td>6.673735</td>\n",
       "      <td>6.669158</td>\n",
       "      <td>0.300574</td>\n",
       "      <td>0.290949</td>\n",
       "      <td>1307.970102</td>\n",
       "      <td>50</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>0</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Filename  CO2_dens_gcm3  SingleCalc_D_km  SingleCalc_P_kbar  Mean_MC_P_kbar  \\\n",
       "0      FI1       0.458055         6.357853           1.684004        1.685286   \n",
       "1      FI2       0.492947         6.918818           1.832587        1.831854   \n",
       "2      FI4       0.484594         6.891995           1.825483        1.822461   \n",
       "3      FI5       0.494431         7.071963           1.873151        1.874001   \n",
       "4      FI7       0.476416         6.670854           1.766909        1.767672   \n",
       "\n",
       "   Med_MC_P_kbar  std_dev_MC_P_kbar  std_dev_MC_P_kbar_from_percentile  \\\n",
       "0       1.685877           0.072431                           0.071137   \n",
       "1       1.832474           0.086385                           0.087010   \n",
       "2       1.821793           0.082639                           0.082694   \n",
       "3       1.874879           0.080538                           0.082679   \n",
       "4       1.766460           0.079613                           0.077064   \n",
       "\n",
       "   Mean_MC_D_km  Med_MC_D_km  std_dev_MC_D_km  \\\n",
       "0      6.362691     6.364923         0.273457   \n",
       "1      6.916050     6.918390         0.326140   \n",
       "2      6.880586     6.878064         0.311999   \n",
       "3      7.075173     7.078488         0.304065   \n",
       "4      6.673735     6.669158         0.300574   \n",
       "\n",
       "   std_dev_MC_D_km_from_percentile    T_K_input  error_T_K  \\\n",
       "0                         0.268572  1322.048738         50   \n",
       "1                         0.328502  1289.074767         50   \n",
       "2                         0.312206  1314.739916         50   \n",
       "3                         0.312150  1308.085183         50   \n",
       "4                         0.290949  1307.970102         50   \n",
       "\n",
       "   CO2_dens_gcm3_input  error_CO2_dens_gcm3  crust_dens_kgm3_input  \\\n",
       "0             0.458055                    0                   2700   \n",
       "1             0.492947                    0                   2700   \n",
       "2             0.484594                    0                   2700   \n",
       "3             0.494431                    0                   2700   \n",
       "4             0.476416                    0                   2700   \n",
       "\n",
       "   error_crust_dens_kgm3 model   EOS  \n",
       "0                    0.0  None  SW96  \n",
       "1                    0.0  None  SW96  \n",
       "2                    0.0  None  SW96  \n",
       "3                    0.0  None  SW96  \n",
       "4                    0.0  None  SW96  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MC_Av_Tonly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7fe0eb92-6471-498b-b462-3c97fd024ee4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10,5))\n",
    "\n",
    "ax1.errorbar(df['Host_Fo_content'], \n",
    "             MC_Av_Tonly['SingleCalc_P_kbar'],\n",
    "             xerr=0, yerr=MC_Av_Tonly['std_dev_MC_P_kbar'],\n",
    "             fmt='d', ecolor='grey', elinewidth=0.8, mfc='cyan', ms=5, mec='k', capsize=5)\n",
    "\n",
    "ax1.set_xlabel('Fo content')\n",
    "ax1.set_ylabel('Pressure (kbar)')\n",
    "\n",
    "ax2.errorbar(df['Host_Fo_content'], \n",
    "             MC_Av_Tonly['SingleCalc_D_km'],\n",
    "             xerr=0, yerr=MC_Av_Tonly['std_dev_MC_D_km'],\n",
    "             fmt='d', ecolor='grey', elinewidth=0.8, mfc='cyan', ms=5, mec='k', capsize=5)\n",
    "ax2.set_xlabel('Fo content')\n",
    "ax2.set_ylabel('Depth (km)')\n",
    "\n",
    "\n",
    "ax1.set_ylim([0, 2.5])\n",
    "ax2.set_ylim([0, 8])\n",
    "ax1.invert_yaxis()\n",
    "ax2.invert_yaxis()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbc71b13-b6a5-43c0-a869-1d107a987b78",
   "metadata": {},
   "source": [
    "## Propagating uncertainty in CO2 Density\n",
    "- Lets say the uncertainty in CO2 density is +-10%, in reality, this will vary greatly between instruments, as well with the absolute density (e.g. more like +-20% for the very weakest diads, more like +-5% for the densest)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ca22d273-51b7-414f-9b78-49b2e5292178",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are not using multiprocessing based on your selected EOS. You can override this by setting multiprocess=True in the function, but for SP94 and SW96 it might actually be slower\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing: 100%|██████████| 60/60 [00:01<00:00, 35.32it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>CO2_dens_gcm3</th>\n",
       "      <th>SingleCalc_D_km</th>\n",
       "      <th>SingleCalc_P_kbar</th>\n",
       "      <th>Mean_MC_P_kbar</th>\n",
       "      <th>Med_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar_from_percentile</th>\n",
       "      <th>Mean_MC_D_km</th>\n",
       "      <th>Med_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km_from_percentile</th>\n",
       "      <th>T_K_input</th>\n",
       "      <th>error_T_K</th>\n",
       "      <th>CO2_dens_gcm3_input</th>\n",
       "      <th>error_CO2_dens_gcm3</th>\n",
       "      <th>crust_dens_kgm3_input</th>\n",
       "      <th>error_crust_dens_kgm3</th>\n",
       "      <th>model</th>\n",
       "      <th>EOS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>6.357853</td>\n",
       "      <td>1.684004</td>\n",
       "      <td>1.698304</td>\n",
       "      <td>1.678897</td>\n",
       "      <td>0.261998</td>\n",
       "      <td>0.253055</td>\n",
       "      <td>6.411839</td>\n",
       "      <td>6.338570</td>\n",
       "      <td>0.989156</td>\n",
       "      <td>0.955393</td>\n",
       "      <td>1322.048738</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>10</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>6.918818</td>\n",
       "      <td>1.832587</td>\n",
       "      <td>1.854009</td>\n",
       "      <td>1.842078</td>\n",
       "      <td>0.285182</td>\n",
       "      <td>0.275894</td>\n",
       "      <td>6.999695</td>\n",
       "      <td>6.954650</td>\n",
       "      <td>1.076688</td>\n",
       "      <td>1.041619</td>\n",
       "      <td>1289.074767</td>\n",
       "      <td>0</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>10</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>6.891995</td>\n",
       "      <td>1.825483</td>\n",
       "      <td>1.842121</td>\n",
       "      <td>1.824761</td>\n",
       "      <td>0.281790</td>\n",
       "      <td>0.279376</td>\n",
       "      <td>6.954811</td>\n",
       "      <td>6.889269</td>\n",
       "      <td>1.063880</td>\n",
       "      <td>1.054768</td>\n",
       "      <td>1314.739916</td>\n",
       "      <td>0</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>10</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>7.071963</td>\n",
       "      <td>1.873151</td>\n",
       "      <td>1.886170</td>\n",
       "      <td>1.861636</td>\n",
       "      <td>0.300329</td>\n",
       "      <td>0.298863</td>\n",
       "      <td>7.121114</td>\n",
       "      <td>7.028488</td>\n",
       "      <td>1.133874</td>\n",
       "      <td>1.128338</td>\n",
       "      <td>1308.085183</td>\n",
       "      <td>0</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>10</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>6.670854</td>\n",
       "      <td>1.766909</td>\n",
       "      <td>1.789624</td>\n",
       "      <td>1.780613</td>\n",
       "      <td>0.280114</td>\n",
       "      <td>0.282397</td>\n",
       "      <td>6.756614</td>\n",
       "      <td>6.722593</td>\n",
       "      <td>1.057553</td>\n",
       "      <td>1.066171</td>\n",
       "      <td>1307.970102</td>\n",
       "      <td>0</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>10</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Filename  CO2_dens_gcm3  SingleCalc_D_km  SingleCalc_P_kbar  Mean_MC_P_kbar  \\\n",
       "0      FI1       0.458055         6.357853           1.684004        1.698304   \n",
       "1      FI2       0.492947         6.918818           1.832587        1.854009   \n",
       "2      FI4       0.484594         6.891995           1.825483        1.842121   \n",
       "3      FI5       0.494431         7.071963           1.873151        1.886170   \n",
       "4      FI7       0.476416         6.670854           1.766909        1.789624   \n",
       "\n",
       "   Med_MC_P_kbar  std_dev_MC_P_kbar  std_dev_MC_P_kbar_from_percentile  \\\n",
       "0       1.678897           0.261998                           0.253055   \n",
       "1       1.842078           0.285182                           0.275894   \n",
       "2       1.824761           0.281790                           0.279376   \n",
       "3       1.861636           0.300329                           0.298863   \n",
       "4       1.780613           0.280114                           0.282397   \n",
       "\n",
       "   Mean_MC_D_km  Med_MC_D_km  std_dev_MC_D_km  \\\n",
       "0      6.411839     6.338570         0.989156   \n",
       "1      6.999695     6.954650         1.076688   \n",
       "2      6.954811     6.889269         1.063880   \n",
       "3      7.121114     7.028488         1.133874   \n",
       "4      6.756614     6.722593         1.057553   \n",
       "\n",
       "   std_dev_MC_D_km_from_percentile    T_K_input  error_T_K  \\\n",
       "0                         0.955393  1322.048738          0   \n",
       "1                         1.041619  1289.074767          0   \n",
       "2                         1.054768  1314.739916          0   \n",
       "3                         1.128338  1308.085183          0   \n",
       "4                         1.066171  1307.970102          0   \n",
       "\n",
       "   CO2_dens_gcm3_input  error_CO2_dens_gcm3  crust_dens_kgm3_input  \\\n",
       "0             0.458055                   10                   2700   \n",
       "1             0.492947                   10                   2700   \n",
       "2             0.484594                   10                   2700   \n",
       "3             0.494431                   10                   2700   \n",
       "4             0.476416                   10                   2700   \n",
       "\n",
       "   error_crust_dens_kgm3 model   EOS  \n",
       "0                    0.0  None  SW96  \n",
       "1                    0.0  None  SW96  \n",
       "2                    0.0  None  SW96  \n",
       "3                    0.0  None  SW96  \n",
       "4                    0.0  None  SW96  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Jkydne/2Z3c70ea8uVculpKRkO5acuHbtGsqVK4dZs2bh/v37Wd4i+eHDB63F8vbtWwCfklFZcXBwkFtGmczqHvhf/aeve319fRw4cABubm4AgCtXrmDixImoW7cuChcujObNm2Pz5s1a/cw+36+s6iOtLtIvl15a28+JyZMno1+/fpDJZIiIiMCyZcvQoUMH2Nvbw93dHVOnTsWrV6+ULqvJtqbqZ5vdNpBeVr2e0j4jIQSioqIyLZsmKSkpWz0qc9qjjYiIiHKOPauIiEgjDA0N0bdvXzg5OUlP3tu9ezdWrlyp1acG5mWJiYno0qUL3rx5A319fYwYMQJt27ZFmTJlYGlpKd1C9+jRI2lsIE2M95UVVXqYaDuO8uXL49atWzhw4AAOHDiAs2fP4uHDh/jw4QOOHj2Ko0ePYv78+Th8+HCWiYycyqo+VK0LXV3dHMeir6+PVatWYcyYMdiyZQtOnTqFq1evIjExUbqVb/78+di4cSPatm0rLZdX25qqNPUZfO7zBFmXLl1ylDxXxYsXL1ROpGXE1NQUxYsX11BERERE+ReTVUREpFFNmzaFs7Mznj17hqioKLx580al25e+tM8TaKmpqZmWff/+fba2cerUKWmsnmXLlmHgwIFKy+X0H1xVWVlZISwsTKXbnNJ672R2K1hO6erqol27dmjXrh2AT73xjhw5guXLl+PatWu4du0aBg0ahD179mh825/vV1b18XlPJm3Wx+fKly+PGTNmYMaMGfjw4QMuXryIzZs3Y/369YiLi0P37t3x8OFD6TbbvNbW1PXq1SulA/6niYiIAPApqaVqDzYjIyOYmJggPj4e7969Q8WKFTUSa0YmTZqEdevW5WgdXl5eOHPmjGYCIiIiyscK5k/dRESkVU5OTtLfebVX1ecDamf2D/ybN2+yPY7UnTt3pL+7deuWYbm0cXUyoupYO1lJ+2f9xo0bSEpKyrBcREQEnjx5IrfMl+Do6Ih+/fohKCgI1apVAwAcPHhQK7dGfr5fly9fzrTs33//rXS5L8XY2BiNGzfG6tWrMW/ePACfbuE7ePCgVEZTbS23XLlyRaX5pUuXVmtMs6pVqwIALl68yNv7iIiI8pG8+R8EERHlW/Hx8bh79y4AwNzc/Iv1RFGXpaWlNEh0Zv/Ab9myJdvbSE5Olv7O6B/l1NRUrFy5MtP1GBkZSX8nJCRkO57GjRsDAN69e4ddu3ZlWG7VqlXSbVdpy3xJ+vr68PLyAvCpDrXxJEcnJydpzKwdO3ZkOAB4SkoK1q5dC+BTm0lLouWWRo0aSX9/nkTVVFvLLZn1SLp69ao0IL667bFNmzYAPvWOXLZsWfYDVMHatWshhMjRi72qiIiIPmGyioiIshQXFwdPT08cPHgw01vmUlNTMWLECOkf/zZt2misV5A2pD2qft++fXj48KHC/JCQEEyZMiXb6y9durT0d0b/jE+YMAHXr1/PdD2fP1FRWZyq6tu3rzQg9pgxY/Ds2TOFMv/88w/8/f0BfHq6Wdotepp0/vx5/PfffxnOT0xMxNmzZwEAhQoV0tptpMOGDQMAvH79GiNGjFA6LtK0adOk5OvAgQOlsZ+04e3bt9i/f3+m4zMdP35c+vvzsY001dZyy/79+7F9+3aF6XFxcfj+++8BfOqlOWjQILXWO3jwYNjY2AD4NHj9kSNHMi1/8eJFnDt3Tq1tEBERkeZxzCoiIlLJ33//jdatW0sJjNq1a8PFxQVmZmZ49+4dbty4gdWrV+PWrVsAAAsLC8yYMSOXo87c0KFDsX//fnz48AENGjSAn58fqlatiri4OJw4cQKLFi2CnZ0d9PT08Pr1a7XX37RpU9jZ2SEiIgKTJk3CkydP0KZNG9jY2OC///7Dn3/+iZMnT6Ju3bq4ePFihuupU6eO9PeoUaMwadIkODo6SolAV1dX6Oll/ZVua2uLefPmYdiwYXj58iU8PDwwfvx41KlTBykpKThx4gTmzZuHuLg4yGQyrFy5Evr6+mrvd1ZOnjyJGTNmoH79+mjZsiUqVaoEW1tbfPjwAffv38eKFSukpMqAAQNU2rfsGDx4MDZt2oSgoCCsW7cOT548wbBhw1CiRAmEhYVh9erV2L17NwCgZMmSWh+gOyYmBm3btoWrqys6dOgAT09PuLi4QE9PD2FhYThw4AD++usvAEDRokXRunVraVlNtbXc4uHhgR49euDs2bPo1KkTzM3NcfPmTcyZMwf37t0D8Cm5WKlSJbXWa25uji1btqB58+ZISEhAq1at0LFjR3Ts2FEaaD4sLAzXrl3Dnj17cPPmTSxZskRKZJO8o0ePyo3x9u+//0p/BwcHS70QgU+J5k6dOn3J8IiI6CvCZBUREWVJT08PDg4OCA8Px4sXL7Bs2bJMb6kpXbo0tmzZAldX1y8XZDY0bdoUP/zwAxYvXoznz59jwIABcvOdnZ2xb98+tGjRIlvrNzU1xfr169GuXTt8/PgRy5cvx/Lly+XKNGjQAEuXLs10LKRSpUqhS5cu2L59O44fPy7XuwYAHj9+rHJdDx06FO/evcPkyZMRERGB0aNHK5QxNDTEypUrs73fqkhNTcXZs2elHlTKdOjQAbNmzdJaDLq6ujh48CDatGmDixcv4syZM0pvw3Jzc8ORI0dQqFAhrcXyudDQUMyfPz/D+UWKFMH+/fthamoqTdNUW8st27dvR6NGjZTGDQAdO3bMtE4y07hxYxw7dgw9e/ZEeHg4duzYgR07dmRY3tzcPFvbKQhmz56d4TG7b98+7Nu3T3rv4uLCZBUREWUbk1VERJQlIyMjvHjxApcuXcKJEydw6dIl3Lt3D69evcLHjx9hamoKJycnVK5cGW3btkXHjh3VGgQ5Ny1atAi1atXCihUrEBwcjKSkJBQrVgzt27fH2LFjYW1tnaP1N23aFFevXsXs2bNx6tQpvH79GoULF0b58uXRs2dP9O/fH0+fPs1yPRs3boSHhwd27tyJe/fuITY2NsunGGZk4sSJaNWqFZYuXYpTp07h5cuX0NHRQbFixdCkSRP4+vpqNdE4btw4eHp6IiAgAEFBQXj58qX0tDcHBwd4enriu+++02qyLI2VlRXOnTuHzZs3Y9OmTbhx4wbevn0Lc3NzuLu7o1OnThg4cOAXac8uLi4IDg5GQECA9HS/V69eIS4uDoULF0aFChXQunVrfP/993IPCEijqbaWG4oXL45r167h119/xZ49e/DkyRPo6+ujcuXK+P7779GzZ88crf/bb7/Fw4cPsWbNGhw8eBD//PMP3rx5Ax0dHdja2sLNzQ1eXl7o2LEjypYtq6G9IiIiouySicwGRiAiIiIi0gI/Pz9MmzYNADIdp4uIiIgKHg6wTkREREREREREeQaTVURERERERERElGcwWUVERERERERERHkGk1VERERERERERJRnMFlFRERERERERER5Bp8GSEREREREREREeQZ7VhERERERERERUZ7BZBUREREREREREeUZTFYREREREREREVGewWQVERERERERERHlGUxWERERERERERFRnsFkFRERERERERER5RlMVhERERERERERUZ7BZBUREREREREREeUZTFYREREREREREVGewWQVERERERERERHlGUxWERERERERERFRnsFkFRERERERERER5RlMVhERERERERERUZ7BZBUREREREREREeUZTFYREREREREREVGewWRVPrV27VrIZDJcvXo1t0OR+Pv7Y+/evTlaR2hoKGQyGdauXStN8/Pzg0wmU2s98fHx8PPzw5kzZ9RaTtm2XF1d0apVK7XWk5XNmzdj4cKFSufJZDL4+flpdHtZkclkKr3Urc+8xNXVFTKZDIMHD1aYd+bMGchkMuzcuTMXIss5ZcdN2jkiNDRU69tP32azu+3snEOUbatBgwaoWLGiWuvJyuHDh7V2XDZo0AANGjTI1rLPnz+Hr68vvLy8ULhwYYV2kBckJSVh2rRpcHV1haGhIcqVK4clS5aotGxG33WRkZHw8PBAoUKFEBAQoI2wKRvy2rVJYGAg/Pz88O7duxytR9m1QXbOc9mJR9l20uKJjIxUeT05ie1Lfp8oc/PmTfTt2xfFixeHkZERChUqhGrVqmHu3Ll4+/atQvlLly6hc+fOcHR0hIGBARwcHNCpUycEBQVpNc7sXK9qg7LPS1PHgjrbNzIywpMnTxTma+M7+ktSVr9f6hjJzXORsm196XNRTuXkGI2NjcW4cePQpEkT2Nra5sr/a1lRJ8a4uDj4+vrCyckJRkZGqFKlCrZu3apQ7tmzZ2jRogXMzc3h5uaGffv2KZTZsWMHrK2t8fr1a03vEpNVpDmaSFYpM2DAALUvMOLj4zFt2jS1kyvZ2VZ2ZJasCgoKwoABA7QeQ/ptfv5q0aIFjI2NFaZXq1bti8alDatWrcK9e/dyO4yvWsuWLREUFARHR0e1lsvOOSS721LX4cOHMW3aNK1uIzv+++8/bNq0CQYGBmjRokVuh6PU0KFDMWvWLAwbNgzHjh1D+/btMXLkSPj7+2drfc+fP0f9+vXx6NEjnDhxAt7e3hqOmL4WgYGBmDZtmlb+6cnOuSc78Xypc1xmsX2pGJT5888/Ub16dVy5cgU//vgjjh49ij179qBz585YsWIF+vfvL1d+yZIlqFu3Lp4/f465c+fixIkT+PXXX/HixQvUq1cPS5cu/eL78KUp+7y0eSxkJCEhAT///PMX215B9aXORdndlrpyo62q4s2bN1i5ciUSEhLQrl273A5HKXVi7NChA9atW4epU6fiyJEjqFGjBrp3747NmzfLlfPx8UF0dDR27tyJ9u3bo0uXLnj48KE0Pzo6GiNHjsSvv/4KW1tbje+TnsbXSKRhRYsWRdGiRbW6jfj4eJiYmHyRbWWlVq1aub5NW1tb6Ojo5Eos2lS7dm3cvXsXEydOxK5du7S2nQ8fPsDIyChP/MKaG2xtbbXyhfW5tDr+EtvKy7755hvpl6yrV69iy5YtuRyRvDt37mDVqlX45Zdf8OOPPwL49Kv6mzdvMHPmTAwePBhWVlYqr+/Bgwdo3LgxkpKScPbsWbi7u2srdKJMafvck3ZdkhfOcbkVQ1BQEIYMGQJvb2/s3bsXhoaG0jxvb2+MGTMGR48elaZdvHgRvr6+aNGiBfbs2QM9vf/9m9OtWzcpUV61alXUrVv3i+7Ll5QX2gwANGvWDJs3b8bYsWNRuXJlrW0n7VgpqL7E552Xzke5xcXFBVFRUVJPsr/++iu3Q1KgaoyHDx9GQEAANm/ejO7duwMAGjZsiCdPnuDHH39E165doauri/j4eJw5cwYXL15E7dq10aRJE+zcuRMBAQEoWbIkAOCnn35C2bJl0bdvX63sE3tWfUX69OmDQoUK4b///kOLFi1QqFAhODs7Y8yYMUhISJDKpd0yNHfuXPzyyy8oVqwYjIyM4OHhgZMnTyqs09XVVWFb6btRymQyvH//HuvWrZNuGcvqtpaXL1+iS5cuMDMzg4WFBbp27Yrw8PAstwUAp06dQoMGDWBtbQ1jY2MUK1YMHTt2RHx8PEJDQ6UT6bRp06R4+vTpI7e+69evo1OnTrC0tJQOuMy6h+7ZsweVKlWCkZERSpQogcWLF8vNz6gbbtotZmm9vBo0aIBDhw7hyZMncrfYfV6X6bts3r59G23btoWlpaXUVXPdunVKt7NlyxZMmjQJTk5OMDc3R+PGjTXSkygxMREzZ85EuXLlYGhoCFtbW/Tt21ehy2fabZMHDx5E1apVYWxsDDc3Nxw8eFCqJzc3N5iamqJmzZoKt4ukteM7d+6gUaNGMDU1ha2tLYYPH474+Pgc7YOVlRXGjx+P3bt349KlS1mWv3DhAho1agQzMzOYmJigTp06OHTokFyZtM/9+PHj6NevH2xtbWFiYoKEhASpq3tQUBDq1KkDY2NjuLq6Ys2aNQCAQ4cOoVq1ajAxMYG7u7vcRTfwqddM3759Ubp0aZiYmKBIkSJo3bo1bt26pfa+z5gxA3p6enj27JnCvH79+sHa2hofP37MdB0xMTEYOHAgrK2tUahQITRr1gz3799XKKfsWLhx4wZatWoFOzs7GBoawsnJCS1btsTz588BZH4OyayOM+v+fv78edSqVQvGxsYoUqQIJk+ejJSUFGl++mMzTfrbKvv06YNly5ZJcaa90rYphMDy5ctRpUoVGBsbw9LSEp06dcKjR4/k1iuEwNy5c+Hi4gIjIyNUq1YNR44cybTOs6Kjo/rX+MuXL9G7d284OjpCV1dX4TZfbXRn37t3L4QQChcxffv2xYcPHxTafGaCg4NRr1496Onp4cKFC0xU5QNp36l37txB9+7dYWFhAXt7e/Tr1w/R0dFKy964cQMdOnSAubk5LCws0KtXL4XvGVWuTfz8/KQEafHixVW+nf3QoUOoUqUKDA0NUbx4cfz6669Ky6U/97x+/Rrff/89nJ2dpe/IunXr4sSJE1nGk9l1SWbnuGfPnmVaV6pew2VVV8piUOX7UZ3PXxl/f3/IZDKsXLlSLlGVxsDAAG3atJHez5o1CzKZDL///rtcogoA9PT0sHz5cshkMsyePTvLbWdF1XYCfEqy9+jRQ/r+c3Nzk75T0qhTV1m1NWW3amX0+Z4/f166dkxv/fr1kMlkuHLlSrbqaNy4cbC2tsZPP/2kUnl12lRm1/A3b95E586dYWFhASsrK4wePRrJycm4d+8emjVrBjMzM7i6umLu3Lly69bkNZcm6jW75yIg8zaS1fGenfNRVuciQHPnbVWOJ3XqT1Xp/1/Lyvr166VrfGVDq2iDquves2cPChUqhM6dO8tN79u3L16+fInLly8D+PS/nxACpqamUplChQpJ/y8EBgZi/fr1+OOPPzS4F/KYrPrKJCUloU2bNmjUqBH27duHfv36YcGCBZgzZ45C2aVLl+Lo0aNYuHAhNm7cCB0dHTRv3jxbt8EFBQXB2NgYLVq0kG4ZW758eYblP3z4gMaNG+P48eOYNWsWduzYAQcHB3Tt2jXLbYWGhqJly5YwMDDA6tWrcfToUcyePRumpqZITEyEo6Oj9A9Q//79pXgmT54st54OHTqgVKlS2LFjB1asWJHpNoODg+Hr64tRo0Zhz549qFOnjtTlUV3Lly9H3bp14eDgIHeLXUbu3buHOnXq4M6dO1i8eDF2796N8uXLo0+fPgpftAAwceJEPHnyBH/99RdWrlyJBw8eoHXr1nL/pKsrNTUVbdu2xezZs9GjRw8cOnQIs2fPRkBAABo0aIAPHz7Ilf/nn38wYcIE/PTTT9i9ezcsLCzQoUMHTJ06FX/99Rf8/f2xadMmREdHo1WrVgrLJyUloUWLFmjUqBH27t2L4cOH448//lBoH2lfcOrc7jly5EgUKVIE48aNy7Tc2bNn8e233yI6OhqrVq3Cli1bYGZmhtatW2Pbtm0K5fv16wd9fX1s2LABO3fuhL6+PgAgPDwcffv2xYABA7Bv3z64u7ujX79+mD59OiZMmIBx48Zh165dKFSoENq1a4eXL19K63z58iWsra0xe/ZsHD16FMuWLYOenh48PT3VTkAOGjQIenp6Cl8ob9++xdatW9G/f38YGRlluLwQAu3atcOGDRswZswY7NmzB7Vq1ULz5s2z3Pb79+/h7e2NV69eYdmyZQgICMDChQtRrFgxxMbGAlDtHJJRHSsTHh6Obt26oWfPnti3bx86deqEmTNnYuTIkVnGm97kyZPRqVMnKc60V1o3+EGDBsHX1xeNGzfG3r17sXz5cty5cwd16tTBq1evpPVMmzYNP/30k9RLYMiQIRg4cOAXuS01MTER3t7e2L59O4YOHYpjx45h0aJFsLCwgJ6eHsaPH49vvvkm03UkJyer9BJCSMvcvn0btra2cHBwkFtXpUqVpPmquHDhAho0aAA7OztcuHABJUqUULMGKDd17NgRZcqUwa5duzB+/Hhs3rwZo0aNUlq2ffv2KFWqFHbu3Ak/Pz/s3bsXTZs2RVJSklrbHDBgAEaMGAEA2L17t0q3s588eRJt27aFmZkZtm7dinnz5mH79u3SDwyZ6d27N/bu3YspU6bg+PHj+Ouvv9C4cWO8efNG5XjUuS4Bcq+u1P1+VOfzT5OSkoJTp06hevXqcHZ2znIfUlJScPr0aXh4eGTYQ97Z2RnVq1fHqVOncnRNpE47uXv3LmrUqIHbt2/jt99+w8GDB9GyZUv88MMPSm8tV6Wusmpr6WX2+davXx9Vq1ZV+s/+0qVLUaNGDdSoUQMAVPoh+nNmZmb4+eefcezYMZw6dSrTsuq2qcyOlS5duqBy5crYtWsXBg4ciAULFmDUqFFo164dWrZsiT179uDbb7+VrlHTaPKaS516VSYn5yIg8zai6vGuzvnoS52LVD2eclp/ObVp0yb4+PjA2NgY69evx/79+9G6dWsAn3rET5o0KdPlhRAqX3Nlx+3bt+Hm5qaQ1E9/bVa4cGGUK1cOv/32G6KiorB37178888/qFOnDpKSkvD9999jwoQJKFOmTLbiUImgfGnNmjUCgLhy5Yo0zcfHRwAQ27dvlyvbokULUbZsWen948ePBQDh5OQkPnz4IE2PiYkRVlZWonHjxnLrdHFxUdj+1KlTRfrmY2pqKnx8fFSK//fffxcAxL59++SmDxw4UAAQa9asyXBbO3fuFABEcHBwhut//fq1ACCmTp2aYexTpkxRab9cXFyETCZT2J63t7cwNzcX79+/F0L87zN5/PixXLnTp08LAOL06dPStJYtWyqtVyGEQtzdunUThoaG4unTp3LlmjdvLkxMTMS7d+/kttOiRQu5ctu3bxcARFBQkNLtKePj4yNMTU2l91u2bBEAxK5du+TKXblyRQAQy5cvl6a5uLgIY2Nj8fz5c2lacHCwACAcHR2l+hJCiL179woAYv/+/XLbBiAWLVokt61ffvlFABAXLlyQpk2bNk3o6uqKM2fOZLlPLi4uomXLlkIIIf78808BQBw4cEAI8b+627Fjh1S+Vq1aws7OTsTGxkrTkpOTRcWKFUXRokVFamqqEOJ/n/t3332nsE0vLy8BQFy9elWa9ubNG6GrqyuMjY3FixcvFOpo8eLFGe5DcnKySExMFKVLlxajRo2Spqcd058fN8rao4+Pj7CzsxMJCQnStDlz5ggdHR2FdpvekSNHMv1cPm+z6bd99epVAUDs3bs3021kdA7JrI6V7WdavSs7v+jo6IgnT54IIZQfm0Ior89hw4YpnBuEECIoKEgAEL/99pvc9GfPngljY2Mxbtw4IYQQUVFRwsjISLRv316u3MWLFwUA4eXlpbBudaUdj5/HnWbbtm0CgFi4cKHc9N27dwsAYtOmTVmuH4BKr8+37+3tLff98zkDAwPx/fffZ7rNtM8XgLCwsBARERFZxkm5J/21Sdp36ty5c+XKDR06VBgZGUnn0c/Lfn5uE0KITZs2CQBi48aN0jRVr03mzZun9Hs5I56enhleG6U//tOfewoVKiR8fX0zXX9G8WR2XaLsHKdqXalzDZdZXaWPQdXvR3U+//TCw8MFANGtW7cMy2SnfNeuXQUA8erVK/Hx40fRp08fUbRoUWFmZiY8PT3FxYsXs9yWOu2kadOmomjRoiI6Olpu+vDhw4WRkZF4+/atEEK9usqqrSlrM6p8vjdu3JCm/f333wKAWLdunTRNV1dXfPvttxluN/36rly5IhISEkSJEiWEh4eHtA9eXl6iQoUKcsuo26Yyu4ZP/31cpUoVAUDs3r1bmpaUlCRsbW1Fhw4dMtyPjK65lNVvZtOyqldlcnIuEiLrNpJZe1DnfPSlz9uqHk/q1F92ZPZ/phBCuLm5CUdHRxEfHy9NS01NFZUrVxZly5bN9NwnxP+uT1V5ZfT9llmMpUuXFk2bNlWY/vLlSwFA+Pv7S9MuXrwoHBwcBACho6MjtYsZM2aI8uXLy/1PoQ3sWfWVkclkUuY2TaVKlZQ+jaNDhw5yPSnSfsE4d+5cjn5xUsXp06dhZmYm130bAHr06JHlslWqVIGBgQG+//57rFu3TuFWG1V17NhR5bIVKlRQuN++R48eiImJwfXr17O1fVWdOnUKjRo1UvhlsU+fPoiPj1folZW+TtOy5MragKoOHjyIwoULo3Xr1nLZ/CpVqsDBwUGhZ1OVKlVQpEgR6b2bmxuAT7dAfj6uQNp0ZbH17NlT7n1a2zh9+rQ0bcqUKUhOToaXl5da+9O3b1+UL18e48ePR2pqqsL89+/f4/Lly+jUqRMKFSokTdfV1UXv3r3x/PlzhV/ZMmpPjo6OqF69uvTeysoKdnZ2qFKlCpycnKTpyuoiOTkZ/v7+KF++PAwMDKCnpwcDAwM8ePAAISEhau0z8KlXWUREBHbs2AHgU4+533//HS1btpS6ZqekpMh9xmn1k1bvGX0umSlVqhQsLS3x008/YcWKFbh7967asQPqHbMZnV9SU1Nx7ty5bG1fmYMHD0Imk6FXr15y9ebg4IDKlStLx0ZQUBA+fvyoUH916tSBi4uLxuLJSNptr7169ZKb3q5dO5iamkq3j2TmypUrKr3Sfwdl1iVd1a7wbdq0QXR0NHx9fbX+/USap+x76ePHj4iIiFAom/4Y6dKlC/T09OTO/drw/v17XLlyJcNro6zUrFkTa9euxcyZM3Hp0iW1exQA6p3jgNypq+x8P6rz+Wub+P+enzKZDMnJyShevDguXryId+/eYciQIWjTpk2mQw6o004+fvyIkydPon379jAxMZH7jmjRogU+fvyoMCSBKnWlibb2ue7du8POzk6uF9CSJUtga2sr16M9OTlZYbiQrBgYGGDmzJm4evUqtm/frrSMJq+5ACg8wdvNzQ0ymUyuJ7ienh5KlSql1WsuVepVWc/knJ6LgC9/PvoS5yJVjydN1F9OxMTEICQkBB07doSxsbE0XSaToWfPnrh3757SITk+l/ZQCVVen/8voQ5Vr83q1KmDp0+f4t9//8Xbt28xbdo0PHjwAP7+/vjjjz+gp6eHqVOnolixYnBwcMDw4cOzHFZEHUxWfWVMTEwUbuUxNDRU2mjS35aRNi0xMRFxcXFaixH49LQCe3t7lWJKr2TJkjhx4gTs7OwwbNgwlCxZEiVLlsSiRYvUikGdJ1lkVFcAMux2rSlv3rxRGmvaySn99q2treXep43zkP5WO3W8evUK7969g4GBAfT19eVe4eHhCo+sTT9gsoGBQabT07dPPT09hf3QZH3r6urC398fd+7cURj7CwCioqIghFCr3jNqT8oGjzYwMFCpLkaPHo3JkyejXbt2OHDgAC5fvowrV66gcuXK2fo8q1ativr160sXTgcPHkRoaCiGDx8ulWnUqJHc59uvXz9pfzP7XDJjYWGBs2fPokqVKpg4cSIqVKgAJycnTJ06Va0LKHWO2czOL5o8Zl+9egUhBOzt7RWOjUuXLknHRto2MzuXaFNsbKzSz08mk8HBwQEvXrzIch1VqlRR6fV527a2tlZa3+/fv0diYqLKg6tPnjwZU6ZMwebNm9GrVy8mrPIZdb6X0h8Pae1W29+1UVFRSE1NzfYxum3bNvj4+OCvv/5C7dq1YWVlhe+++07pWJwZUfcJW7lRV9n5fszOdYmNjQ1MTEzw+PFjleJStXxoaChMTExgZWUFU1NTTJkyBcWKFYOOjg58fHyQmpqKBw8eZLi8Ou3kzZs3SE5OxpIlSxS+H9Ke3pr++kmVutJEW0u/jUGDBmHz5s149+4dXr9+je3bt2PAgAFKxwpTV7du3VCtWjVMmjRJ6Xe+Jq+5AOXXmsr+PzIwMNDqNVdW9RoaGqrQLs6ePZvjcxHw5c9HX+JcpOrxpIn6y4m04S2UbSutTrO65ipUqJDK11xp/z+oI6PP5u3btwAUjyF9fX2ULVsWFhYWAIDBgwejd+/eqFevHtasWYM1a9bg5MmTuHHjBs6fP49Zs2apHVNG+DTAAkzZCSs8PBwGBgbSLxtGRkZyg7OnSf/lqi5ra2v8/fffKsWkTP369VG/fn2kpKTg6tWrWLJkCXx9fWFvb49u3bqptA51BrfLqK6A/11YpH0Jpq8vTdRVWFiYwvS0sY1sbGxytH5V2NjYwNraOsPBkM3MzDS6veTkZLx580buoi19fedU27ZtUbduXUydOhUrV66Um2dpaQkdHR216l0bgyVu3LgR3333Hfz9/eWmR0ZGonDhwtla5w8//IDOnTvj+vXrWLp0KcqUKQNvb29p/h9//CF90QL/209ra+tMP5esuLu7Y+vWrRBC4ObNm1i7di2mT58OY2NjjB8/XqV1qFPHn48VlT5WTR6zNjY2kMlkOH/+vNKL+rRpadvM6FyibNBRTbKzs0NycjIiIiJgZ2cnTU9NTcXLly9Rs2bNLNeR2Rhhn1uzZo30QIu0zz08PFzuwi1twNqKFSuqvA9pD8yYNm0aUlNTsWnTJoXxFij/Cw8Pl+uZq+y8o41rE0tLS8hksky/7zNjY2ODhQsXYuHChXj69Cn279+P8ePHIyIiQuUHCaj7PZJVXWmrntT9fswOXV1dNGrUCEeOHMHz58+zfFKzrq4uGjZsiKNHj2ZY/vnz57h27RqaN28OXV1dhfn//vsvPnz4IA0mrYw67cTS0lLqHTRs2DCl6ytevHim+6WMJtpaekOGDMHs2bOxevVqfPz4EcnJyRg8eHC21pWeTCbDnDlz4O3trXC9BXzd11yZ1auTk5PCIOtly5aFjo5Ojs5FwJc/H32J87aqx1Pa07hzUn85YW1tDV1dXaUJqbSHCmX1v8zZs2fRsGFDlbb3+PFjta8h3d3dsWXLFiQnJ8tdR6lybbZ27VrcvXtXeqr6kSNH0LlzZ5QuXRrAp/GiN2zYoHRMvuxgz6oCbPfu3XK/KMTGxuLAgQOoX7++9CXu6uqKiIgIuX/8EhMTcezYMYX1GRoaqvzLQ8OGDREbG4v9+/fLTd+8ebNa+6CrqwtPT0+pp0jaLXma6E30uTt37uCff/6Rm7Z582aYmZlJg/6lnShu3rwpVy79PqbFp2psjRo1wqlTp+QG3gY+PWXCxMQEtWrVUnU3sq1Vq1Z48+YNUlJS4OHhofAqW7asxre5adMmufdpbUOdwT2zMmfOHDx79kzhyY6mpqbw9PTE7t275T6n1NRUbNy4EUWLFtXuYIL/TyaTKSRADh06pFIvmIy0b98exYoVw5gxY3DixAkMHTpU7oKkbNmycp9tWrtO+9LM6HNRlUwmQ+XKlbFgwQIULlxY7jZadY6LrGR0ftHR0ZEGElf3mAUUzymtWrWCEAIvXrxQemykPbGuVq1aMDIyUqi/wMDAHN2iq6omTZoA+HTe+Nz27dulB15kJTu3AbZt2xYymUyhB+PatWthbGyMZs2aqbUffn5+mDZtGrZv344ePXpke3BRyrvSHyPbt29HcnKy3Llf1WsTda4F0p5Qm9G1kTqKFSuG4cOHw9vbW+Ecp2o8qsiqrtS9hlMlti/5/ThhwgQIITBw4EAkJiYqzE9KSpL7bNLKDx06VKH3ZUpKCoYMGQIhBCZMmKCwrvj4ePTu3Rs///yz3K1o6anTTkxMTNCwYUPcuHEDlSpVUvodkdMf4DJqa+ll9fk6Ojqic+fOWL58OVasWIHWrVujWLFiOYrtc40bN4a3tzemT5+ucPfG13zNlVm9GhgYKLQHMzMzjZ6LAOVt5Eufi4Ccn7dVPZ40XX/qMjIyQv369bFr1y68f/9emp6SkoKNGzeiWLFiUmInI9q+DbB9+/aIi4uTEk5p1q1bBycnJ3h6eipdLjIyEmPHjsWiRYukBG7aratp4uLi5B60k1P8SbIA09XVhbe3N0aPHo3U1FTMmTMHMTExcpnQrl27YsqUKejWrRt+/PFHfPz4EYsXL1Z6C4a7uzvOnDmDAwcOwNHREWZmZhkmMb777jssWLAA3333HX755ReULl0ahw8fVnoBld6KFStw6tQptGzZEsWKFcPHjx+xevVqAJD+4TIzM4OLiwv27duHRo0awcrKCjY2NtnuveDk5IQ2bdrAz88Pjo6O2LhxIwICAjBnzhxpDKYaNWqgbNmyGDt2LJKTk2FpaYk9e/bgwoULSutq9+7d+P3331G9enXo6OjAw8ND6banTp2KgwcPomHDhpgyZQqsrKywadMmHDp0CHPnzpW6ZGpTt27dsGnTJrRo0QIjR45EzZo1oa+vj+fPn+P06dNo27Yt2rdvr7HtGRgY4LfffkNcXBxq1KiBwMBAzJw5E82bN0e9evWkctOnT8f06dNx8uRJtcetAoC6deuibdu22Ldvn8K8WbNmwdvbGw0bNsTYsWNhYGCA5cuX4/bt29iyZYvWHjv7uVatWmHt2rUoV64cKlWqhGvXrmHevHlZ/sKcGV1dXQwbNgw//fQTTE1NpR4wWWnSpAm++eYbjBs3Du/fv4eHhwcuXryIDRs2ZLnswYMHsXz5crRr1w4lSpSAEAK7d+/Gu3fv5Hp1qXMOyYq1tTWGDBmCp0+fokyZMjh8+DD+/PNPDBkyRLpQdHBwQOPGjTFr1ixYWlrCxcUFJ0+elHs60OexAZ8SnGm/yleqVAl169bF999/j759++Lq1av45ptvYGpqirCwMFy4cAHu7u4YMmQILC0tMXbsWMycORMDBgxA586d8ezZM/j5+SntKt6gQQOcPXtWpS/8nTt3AoA0ft/Vq1elf7bSnmLo5eWF9u3bY+LEiYiLi0PdunVx8+ZNTJ06FVWrVlUYb0KZjM5RmalQoQL69++PqVOnQldXFzVq1MDx48excuVKzJw5U+XbAD83ZcoU6OjoYPLkyRBCYMuWLexh9RXZvXs39PT04O3tjTt37mDy5MmoXLkyunTpIpVR9dok7bhdtGgRfHx8pFsZMuoNPGPGDDRr1gze3t4YM2YMUlJSMGfOHJiamkq3RygTHR2Nhg0bokePHihXrhzMzMxw5coVHD16FB06dMgyHm3VlbrXcKrW1Zf6fqxduzZ+//13DB06FNWrV8eQIUNQoUIFJCUl4caNG1i5ciUqVqwoJcjr1q2LhQsXwtfXF/Xq1cPw4cNRrFgxPH36FMuWLcPly5excOFC1KlTR247SUlJ6NKlC8qXL4+JEydmGZc67WTRokWoV68e6tevjyFDhsDV1RWxsbH477//cODAgSyfkpeeqm0tPVU+35EjR0r/pCp7apqenh68vLzUHrcqzZw5c1C9enVERESgQoUKcvO+1msuIOt6VSa75yJAtTai7rkxK1/qvK3q8aRu/clkMnh5eWX5dPEjR47g/fv30h0Id+/ela7BWrRoIf1POGfOHHzzzTdo2LAhfvzxR6k93717F1u3bs2yPZuZmWXrmkvVGJs3bw5vb28MGTIEMTExKFWqFLZs2YKjR49i48aNSnueAp9ulfX09JT7XJs2bYoxY8agdu3aKFSoEBYvXowBAwZkK3altDp8O2lNRk8D/PwJbmnSP2Uh7UlXc+bMEdOmTRNFixYVBgYGomrVquLYsWMKyx8+fFhUqVJFGBsbixIlSoilS5cqfZJMcHCwqFu3rjAxMVHp6VbPnz8XHTt2FIUKFRJmZmaiY8eOIjAwUOFpUum3FRQUJNq3by9cXFyEoaGhsLa2Fl5eXnJPlBNCiBMnToiqVasKQ0NDAUB6ylja+l6/fp1lXQnxv6fI7dy5U1SoUEEYGBgIV1dXMX/+fIXl79+/L5o0aSLMzc2Fra2tGDFihDh06JDCE8fevn0rOnXqJAoXLixkMpncNqHkyQ23bt0SrVu3FhYWFsLAwEBUrlxZ4Ylfyp5oJ4TyJ5tlRVlbSkpKEr/++quoXLmyMDIyEoUKFRLlypUTgwYNEg8ePFCor/QAiGHDhimNbd68eQrbvnnzpmjQoIEwNjYWVlZWYsiQISIuLk5u+bTPK/3T3JTJKK67d+8KXV1dpXV3/vx58e233wpTU1NhbGwsatWqJT1BMI2yYzGNsifeZBZL+jqKiooS/fv3F3Z2dsLExETUq1dPnD9/Xnh5eckdX6o+DTBNaGioACAGDx6sMC8z7969E/369ROFCxcWJiYmwtvbW/z7779ZPg3w33//Fd27dxclS5YUxsbGwsLCQtSsWVOsXbtWbv0ZnUMyq+OMngZYoUIFcebMGeHh4SEMDQ2Fo6OjmDhxokhKSpJbPiwsTHTq1ElYWVkJCwsL0atXL+nphZ/XZ0JCghgwYICwtbWVjtnPt7l69Wrh6ekptZWSJUuK7777Tu5JkKmpqWLWrFnC2dlZGBgYiEqVKokDBw4ofJ5CCFG9enXh4OCQ9YciMn9K3+cSEhLEpEmThKurq9DX1xeOjo5i6NChIioqSqXtZFdiYqKYOnWqKFasmDAwMBBlypTJ9KmXn8vss097EmWHDh1EYmKipsOmbMjoaYDpv28ze8LdtWvXROvWraVrg+7du4tXr14pbEvVa5MJEyYIJycnoaOjo9L3xf79+0WlSpWEgYGBKFasmJg9e7bS9X6+Dx8/fhSDBw8WlSpVEubm5sLY2FiULVtWTJ06Ve4JuBnFk9l1SU7rStV6yqyulMWgyvejOp9/ZoKDg4WPj490DjE1NRVVq1YVU6ZMUfqE0KCgINGpUydhb28v9PT0hJ2dnejQoYMIDAxUKJuSkiK6desm2rRpo/D9kBlV24kQn76j+/XrJ4oUKSL09fWFra2tqFOnjpg5c6ZURtW6UqWtZVS/qhwLrq6uws3NTek+q3Jt//n2lZ23e/ToIQAovTbKSZvKbF5G/x+lv0ZT9ZpL1acBfi6zes1Ids5FQqjWRoTIuD2ocz7KjfO2KseTOvUXGxsroOKTR11cXFR+Kl9QUJBo3LixXHs+ePBgltvIKVVjjI2NFT/88INwcHCQrkm3bNmS4XpPnDghTE1NRWhoqNz05ORk8dNPPwkHBwdhZWUlBg4cKPcUxJySCaHBflqUL4SGhqJ48eKYN28exo4dm9vhEMnp06cPdu7cqfVB/guyJUuW4IcffsDt27cVft2k3BcbGwsrKyssXLgww3EZiL42abd4vn79+ouMxUgEAAMHDsSDBw9w9OhRhQG4C5qbN2+icuXKWLZsGYYOHZrb4Xw1WK952+HDh9GqVSv8888/Uq8uyjvYb56IqIC4ceMGHj9+jOnTp6Nt27ZMVOVR586dQ5EiRTBw4MDcDoWI6Kv15MkT/PXXXzAyMpJLkB45cgT169fPxci+rIcPH+LJkyeYOHEiHB0dVR4egDLHes0fTp8+jW7dujFRlUcxWUVEVEC0b98e4eHhqF+/PlasWJHb4VAGWrZsiZYtW+Z2GEREXzUXFxeNDgScX82YMQMbNmyAm5sbduzYIY27QznDes0f5s2bl9shUCZ4GyAREREREREREeUZOrkdABERERERERERURomq4iIiIiIiIiIKM/gmFUqSk1NxcuXL2FmZgaZTJbb4RAREVEeIoRAbGwsnJycoKPz9f8WyOsiIiIiykxOr42YrFLRy5cv4ezsnNthEBERUR727NkzFC1aNLfD0DpeFxEREZEqsnttxGSViszMzAB8qmhzc/NcjoaIiIjykpiYGDg7O0vXC187XhcRERFRZnJ6bcRklYrSuribm5vzooyIiIiUKii3xPG6iIiIiFSR3Wujr39QBSIiIiIiIiIiyjdynKxKSUlBcHAwoqKi1F723LlzaN26NZycnCCTybB37165+UII+Pn5wcnJCcbGxmjQoAHu3LkjVyYhIQEjRoyAjY0NTE1N0aZNGzx//lyuTFRUFHr37g0LCwtYWFigd+/eePfundrxEhERERERERGRdqmdrPL19cWqVasAfEpUeXl5oVq1anB2dsaZM2fUWtf79+9RuXJlLF26VOn8uXPnYv78+Vi6dCmuXLkCBwcHeHt7IzY2Vi6ePXv2YOvWrbhw4QLi4uLQqlUrpKSkSGV69OiB4OBgHD16FEePHkVwcDB69+6t7q4TEREREREREZGWyYQQQp0FihYtir1798LDwwN79+7FsGHDcPr0aaxfvx6nT5/GxYsXsxeITIY9e/agXbt2AD71qnJycoKvry9++uknAJ96Udnb22POnDkYNGgQoqOjYWtriw0bNqBr164A/vd0msOHD6Np06YICQlB+fLlcenSJXh6egIALl26hNq1a+Pff/9F2bJlVYovJiYGFhYWiI6O5tgMRAWdEEB8/Ke/TUyAAjJGDRFlrKBdJxS0/SUiIiL15PRaQe0B1iMjI+Hg4AAAOHz4MDp37owyZcqgf//+WLx4sdoBZOTx48cIDw9HkyZNpGmGhobw8vJCYGAgBg0ahGvXriEpKUmujJOTEypWrIjAwEA0bdoUQUFBsLCwkBJVAFCrVi1YWFggMDAww2RVQkICEhISpPcxMTEa2zciyufi44FChT79HRcHmJrmbjxERET0VXj69CkiIyNzO4xss7GxQbFixXI7DCL6CqidrLK3t8fdu3fh6OiIo0ePYvny5QCA+Ph46Orqaiyw8PBwaXvpt//kyROpjIGBASwtLRXKpC0fHh4OOzs7hfXb2dlJZZSZNWsWpk2blqN9ICIiIiIiUsXTp0/h5uaG+LTe2/mQiYkJQkJCmLAiohxTO1nVt29fdOnSBY6OjpDJZPD29gYAXL58GeXKldN4gOkfcyiEyPLRh+nLKCuf1XomTJiA0aNHS+9jYmLg7OysathEREREREQqi4yMRHx8PDZu3Ag3N7fcDkdtISEh6NWrFyIjI5msIqIcUztZ5efnh4oVK+LZs2fo3LkzDA0NAQC6uroYP368xgJLu9UwPDwcjo6O0vSIiAipt5WDgwMSExMRFRUl17sqIiICderUkcq8evVKYf2vX79W6LX1OUNDQ2nfiIiIiIiIvgQ3NzdUq1Ytt8MgIspVaj8NEAA6deqEUaNGwcbGRprm4+ODtm3baiyw4sWLw8HBAQEBAdK0xMREnD17VkpEVa9eHfr6+nJlwsLCcPv2balM7dq1ER0djb///lsqc/nyZURHR0tliIiIiIiIiIgob1A7WZWSkoIZM2agSJEiKFSoEB49egQAmDx5MlatWqXWuuLi4hAcHIzg4GAAnwZVDw4OxtOnTyGTyeDr6wt/f3/s2bMHt2/fRp8+fWBiYoIePXoAACwsLNC/f3+MGTMGJ0+exI0bN9CrVy+4u7ujcePGAD79MtGsWTMMHDgQly5dwqVLlzBw4EC0atVK5ScBEhERERERERHRl6F2suqXX37B2rVrMXfuXBgYGEjT3d3d8ddff6m1rqtXr6Jq1aqoWrUqAGD06NGoWrUqpkyZAgAYN24cfH19MXToUHh4eODFixc4fvw4zMzMpHUsWLAA7dq1Q5cuXVC3bl2YmJjgwIEDcoO9b9q0Ce7u7mjSpAmaNGmCSpUqYcOGDeruOhERERERERERaZlMCCHUWaBUqVL4448/0KhRI5iZmeGff/5BiRIl8O+//6J27dqIiorSVqy5KiYmBhYWFoiOjoa5uXluh0NEuen9e6BQoU9/x8UBpqa5Gw8R5bqCdp1Q0PaX6Eu4fv06qlevjmvXruXLMavye/xEpFk5vVZQu2fVixcvUKpUKYXpqampSEpKUjsAIiIiIiIiIiKiNGonqypUqIDz588rTN+xY4d0Ox8REREREREREVF26Km7wNSpU9G7d2+8ePECqamp2L17N+7du4f169fj4MGD2oiRiIiIiIiIiIgKCLV7VrVu3Rrbtm3D4cOHIZPJMGXKFISEhODAgQPw9vbWRoxERERERERERFRAqN2zCgCaNm2Kpk2bajoWIiIiIiIiIiIq4NTuWUVERERERERERKQtKvWssrS0hEwmU2mFb9++zVFARERERERERERUcKmUrFq4cKGWwyAiIiIiIiIiIlIxWeXj46PtOIiIiIiIiIiIiLI3wHpKSgr27NmDkJAQyGQyuLm5oW3bttDTy9bqiIiIiIiIiIiIAGQjWXX79m20bdsW4eHhKFu2LADg/v37sLW1xf79++Hu7q7xIImIiIiIiIiIqGBQ+2mAAwYMQIUKFfD8+XNcv34d169fx7Nnz1CpUiV8//332oiRiIiIiIiIiIgKCLV7Vv3zzz+4evUqLC0tpWmWlpb45ZdfUKNGDY0GR0REREREREREBYvayaqyZcvi1atXqFChgtz0iIgIlCpVSmOBERERERERUf4SEhKS2yFki42NDYoVK5bbYRDR/1M7WeXv748ffvgBfn5+qFWrFgDg0qVLmD59OubMmYOYmBiprLm5ueYiJSIiIiIiojwpLCwMOjo66NWrV26Hki0mJiYICQlhwoooj1A7WdWqVSsAQJcuXSCTyQAAQggAQOvWraX3MpkMKSkpmoqTiIiIiIgoS0+fPkVkZGRuh6G2/NojKc27d++QmpqKjRs3ws3NLbfDUUtISAh69eqFyMhIJquI8gi1k1WnT5/WRhxEREREREQ58vTpU7i5uSE+Pj63Qymw3NzcUK1atdwOg4jyObWTVV5eXtqIg4iIiIiIKEciIyMRHx+fL3v3HD58GJMnT87tMIiI8gS1k1UA8PHjR9y8eRMRERFITU2Vm9emTRuNBEZERERERJQd+bF3T36/DZCISJPUTlYdPXoU3333ndL7wDlOFRERERERERER5YSOugsMHz4cnTt3RlhYGFJTU+VeTFQREREREREREVFOqJ2sioiIwOjRo2Fvb6+NeIiIiIgoA7NmzUKNGjVgZmYGOzs7tGvXDvfu3ZMrI4SAn58fnJycYGxsjAYNGuDOnTtyZRISEjBixAjY2NjA1NQUbdq0wfPnz7/krhARERFlSO1kVadOnXDmzBkthEJEREREmTl79iyGDRuGS5cuISAgAMnJyWjSpAnev38vlZk7dy7mz5+PpUuX4sqVK3BwcIC3tzdiY2OlMr6+vtizZw+2bt2KCxcuIC4uDq1atWIveSIiIsoT1B6zaunSpejcuTPOnz8Pd3d36Ovry83/4YcfNBYcEREREf3P0aNH5d6vWbMGdnZ2uHbtGr755hsIIbBw4UJMmjQJHTp0AACsW7cO9vb22Lx5MwYNGoTo6GisWrUKGzZsQOPGjQEAGzduhLOzM06cOIGmTZt+8f0iIiIi+pzayarNmzfj2LFjMDY2xpkzZyCTyaR5MpmMySoiIiKiLyQ6OhoAYGVlBQB4/PgxwsPD0aRJE6mMoaEhvLy8EBgYiEGDBuHatWtISkqSK+Pk5ISKFSsiMDBQabIqISEBCQkJ0vuYmBht7RIRERGR+rcB/vzzz5g+fTqio6MRGhqKx48fS69Hjx5pI0YiIiIiSkcIgdGjR6NevXqoWLEiACA8PBwAFMYWtbe3l+aFh4fDwMAAlpaWGZZJb9asWbCwsJBezs7Omt4dIiIiIonayarExER07doVOjpqL5otrq6ukMlkCq9hw4YBAPr06aMwr1atWnLr4CCiRERE9LUZPnw4bt68iS1btijM+7znO/ApsZV+WnqZlZkwYQKio6Ol17Nnz7IfOBEREVEW1M44+fj4YNu2bdqIRakrV64gLCxMegUEBAAAOnfuLJVp1qyZXJnDhw/LrYODiBIREdHXZMSIEdi/fz9Onz6NokWLStMdHBwAQKGHVEREhNTbysHBAYmJiYiKisqwTHqGhoYwNzeXexERERFpi9pjVqWkpGDu3Lk4duwYKlWqpDDA+vz58zUWHADY2trKvZ89ezZKliwJLy8vaZqhoaF0cZYeBxElIiKir4UQAiNGjMCePXtw5swZFC9eXG5+8eLF4eDggICAAFStWhXAp17xZ8+exZw5cwAA1atXh76+PgICAtClSxcAQFhYGG7fvo25c+d+2R0iIiIiUkLtZNWtW7eki5/bt2/Lzcuqe3lOJSYmYuPGjRg9erTcts6cOQM7OzsULlwYXl5e+OWXX2BnZwcA2RpEFOBAokRERJT3DBs2DJs3b8a+fftgZmYm9aCysLCAsbExZDIZfH194e/vj9KlS6N06dLw9/eHiYkJevToIZXt378/xowZA2tra1hZWWHs2LFwd3eXftgjIiIiyk1qJ6tOnz6tjThUsnfvXrx79w59+vSRpjVv3hydO3eGi4sLHj9+jMmTJ+Pbb7/FtWvXYGhomK1BRIFPA4lOmzZNW7tCREREpLbff/8dANCgQQO56WvWrJGuj8aNG4cPHz5g6NChiIqKgqenJ44fPw4zMzOp/IIFC6Cnp4cuXbrgw4cPaNSoEdauXQtdXd0vtStEREREGVI7WZWbVq1ahebNm8PJyUma1rVrV+nvihUrwsPDAy4uLjh06BA6dOiQ4bqyGmh0woQJGD16tPQ+JiaGT74hIiKiXCWEyLKMTCaDn58f/Pz8MixjZGSEJUuWYMmSJRqMjoiIiEgzspWsunLlCnbs2IGnT58iMTFRbt7u3bs1Elh6T548wYkTJ7Jcv6OjI1xcXPDgwQMA8oOIft67KiIiAnXq1MlwPYaGhjA0NNRM8EREREREREREpBK1nwa4detW1K1bF3fv3sWePXuQlJSEu3fv4tSpU7CwsNBGjAA+dW+3s7NDy5YtMy335s0bPHv2DI6OjgDkBxFNkzaIaGbJKiIiIiIiIiIi+vLUTlb5+/tjwYIFOHjwIAwMDLBo0SKEhISgS5cuKFasmDZiRGpqKtasWQMfHx/o6f2vM1hcXBzGjh2LoKAghIaG4syZM2jdujVsbGzQvn17APKDiJ48eRI3btxAr169OIgoEREREREREVEepHay6uHDh1LvJkNDQ7x//x4ymQyjRo3CypUrNR4gAJw4cQJPnz5Fv3795Kbr6uri1q1baNu2LcqUKQMfHx+UKVMGQUFBCoOItmvXDl26dEHdunVhYmKCAwcOcBBRIiIiIiIiIqI8Ru0xq6ysrBAbGwsAKFKkCG7fvg13d3e8e/cO8fHxGg8QAJo0aaJ0QFFjY2McO3Ysy+U5iCgRERERERERUf6gdrKqfv36CAgIgLu7O7p06YKRI0fi1KlTCAgIQKNGjbQRIxERERERERERFRBqJ6uWLl2Kjx8/AgAmTJgAfX19XLhwAR06dMDkyZM1HiARERERERERERUc2boNMI2Ojg7GjRuHcePGaTQoIiIiIiIiIiIqmNQeYP369eu4deuW9H7fvn1o164dJk6ciMTERI0GR0REREREREREBYvayapBgwbh/v37AIBHjx6ha9euMDExwY4dO9jDioiIiIiIiIiIckTtZNX9+/dRpUoVAMCOHTvg5eWFzZs3Y+3atdi1a5em4yMiIiIiIiIiogJE7WSVEAKpqakAgBMnTqBFixYAAGdnZ0RGRmo2OiIiIiIiIiIiKlDUTlZ5eHhg5syZ2LBhA86ePYuWLVsCAB4/fgx7e3uNB0hERERERERERAWH2smqhQsX4vr16xg+fDgmTZqEUqVKAQB27tyJOnXqaDxAIiIiIiIiIiIqOPTUXaBSpUpyTwNMM2/ePOjq6mokKCIiIiIiIiIiKpjUTlZlxMjISFOrIiIiIiIiIiKiAkrt2wCJiIiIiIiIiIi0hckqIiIiIiIiIiLKM5isIiIiIiIiIiKiPIPJKiIiIiIiIiIiyjPUTlZ16tQJs2fPVpg+b948dO7cWSNBERERERERERFRwaR2surs2bNo2bKlwvRmzZrh3LlzGgmKiIiIiIiIiIgKJrWTVXFxcTAwMFCYrq+vj5iYGI0ERUREREREREREBZPayaqKFSti27ZtCtO3bt2K8uXLayQoIiIiIiIiIiIqmPTUXWDy5Mno2LEjHj58iG+//RYAcPLkSWzZsgU7duzQeIBERERERERERFRwqJ2satOmDfbu3Qt/f3/s3LkTxsbGqFSpEk6cOAEvLy9txEhERERERERERAWE2skqAGjZsqXSQdaJiIiIiIiIiIhyQu0xq4iIiIiIiIiIiLRFpZ5VVlZWuH//PmxsbGBpaQmZTJZh2bdv32osOCIiIiIiIiIiKlhUSlYtWLAAZmZm0t+ZJauIiIiIiIiIiIiyS6VklY+Pj/R3nz59tBULEREREREREREVcGqPWaWrq4uIiAiF6W/evIGurq5Ggkrj5+cHmUwm93JwcJDmCyHg5+cHJycnGBsbo0GDBrhz547cOhISEjBixAjY2NjA1NQUbdq0wfPnzzUaJxERERERERERaYbaySohhNLpCQkJMDAwyHFA6VWoUAFhYWHS69atW9K8uXPnYv78+Vi6dCmuXLkCBwcHeHt7IzY2Virj6+uLPXv2YOvWrbhw4QLi4uLQqlUrpKSkaDxWIiIiIiIiIiLKGZVuAwSAxYsXAwBkMhn++usvFCpUSJqXkpKCc+fOoVy5cpoPUE9PrjdVGiEEFi5ciEmTJqFDhw4AgHXr1sHe3h6bN2/GoEGDEB0djVWrVmHDhg1o3LgxAGDjxo1wdnbGiRMn0LRpU43HS0RERERERERE2adysmrBggUAPiWJVqxYIXfLn4GBAVxdXbFixQqNB/jgwQM4OTnB0NAQnp6e8Pf3R4kSJfD48WOEh4ejSZMmUllDQ0N4eXkhMDAQgwYNwrVr15CUlCRXxsnJCRUrVkRgYGCmyaqEhAQkJCRI72NiYjS+b0REREREREREJE/lZNXjx48BAA0bNsTu3bthaWmptaDSeHp6Yv369ShTpgxevXqFmTNnok6dOrhz5w7Cw8MBAPb29nLL2Nvb48mTJwCA8PBwGBgYKMRqb28vLZ+RWbNmYdq0aRrcGyIiIiIiIiIiyoraY1adPn0alpaWSExMxL1795CcnKyNuAAAzZs3R8eOHeHu7o7GjRvj0KFDAD7d7pdGJpPJLSOEUJiWniplJkyYgOjoaOn17NmzbO4FERERERERERGpSu1k1YcPH9C/f3+YmJigQoUKePr0KQDghx9+wOzZszUe4OdMTU3h7u6OBw8eSONYpe8hFRERIfW2cnBwQGJiIqKiojIskxFDQ0OYm5vLvYiIiIiIiIiISLvUTlaNHz8e//zzD86cOQMjIyNpeuPGjbFt2zaNBpdeQkICQkJC4OjoiOLFi8PBwQEBAQHS/MTERJw9exZ16tQBAFSvXh36+vpyZcLCwnD79m2pDBERERERERER5R0qj1mVZu/evdi2bRtq1aoldytd+fLl8fDhQ40GN3bsWLRu3RrFihVDREQEZs6ciZiYGPj4+EAmk8HX1xf+/v4oXbo0SpcuDX9/f5iYmKBHjx4AAAsLC/Tv3x9jxoyBtbU1rKysMHbsWOm2QiIiIiIiIiIiylvUTla9fv0adnZ2CtPfv3+f5ThQ6nr+/Dm6d++OyMhI2NraolatWrh06RJcXFwAAOPGjcOHDx8wdOhQREVFwdPTE8ePH4eZmZm0jgULFkBPTw9dunTBhw8f0KhRI6xdu1buaYZERERERERERJQ3qJ2sqlGjBg4dOoQRI0YA+N8A53/++Sdq166t0eC2bt2a6XyZTAY/Pz/4+fllWMbIyAhLlizBkiVLNBobERERERERERFpntrJqlmzZqFZs2a4e/cukpOTsWjRIty5cwdBQUE4e/asNmIkIiIiIiIiIqICQu0B1uvUqYOLFy8iPj4eJUuWxPHjx2Fvb4+goCBUr15dGzESEREREREREVEBoXbPKgBwd3fHunXrNB0LEREREREREREVcNlKVqWmpuK///5DREQEUlNT5eZ98803GgmMiIiIiIiIiIgKHrWTVZcuXUKPHj3w5MkTCCHk5slkMqSkpGgsOCIiIiIiIiIiKljUTlYNHjwYHh4eOHToEBwdHaWnARIREREREREREeWU2smqBw8eYOfOnShVqpQ24iEiIiIiIiIiogJM7WSVp6cn/vvvPyariIiIiIi+Qk+fPkVkZGRuh5EtISEhuR0CERFpgErJqps3b0p/jxgxAmPGjEF4eDjc3d2hr68vV7ZSpUqajZCIiIiIiL6Ip0+fws3NDfHx8bkdCtEXl5+TnTY2NihWrFhuh0GkMSolq6pUqQKZTCY3oHq/fv2kv9PmcYB1IiIiIu06d+4c5s2bh2vXriEsLAx79uxBu3btpPlCCEybNg0rV65EVFQUPD09sWzZMlSoUEEqk5CQgLFjx2LLli348OEDGjVqhOXLl6No0aK5sEeUl0RGRiI+Ph4bN26Em5tbboejtsOHD2Py5Mm5HQblM2FhYdDR0UGvXr1yO5RsMzExQUhICBNW9NVQKVn1+PFjbcdBRERERCp4//49KleujL59+6Jjx44K8+fOnYv58+dj7dq1KFOmDGbOnAlvb2/cu3cPZmZmAABfX18cOHAAW7duhbW1NcaMGYNWrVrh2rVr0NXV/dK7RHmQm5sbqlWrltthqC0/94yh3PPu3Tukpqbm2yRtSEgIevXqhcjISCar6KuhUrLKxcVF+vvcuXOoU6cO9PTkF01OTkZgYKBcWSIiIiLSrObNm6N58+ZK5wkhsHDhQkyaNAkdOnQAAKxbtw729vbYvHkzBg0ahOjoaKxatQobNmxA48aNAQAbN26Es7MzTpw4gaZNmyqsNyEhAQkJCdL7mJgYLewZEVHuyq9JWqKvkY66CzRs2BBv375VmB4dHY2GDRtqJCgiIiIiUt/jx48RHh6OJk2aSNMMDQ3h5eWFwMBAAMC1a9eQlJQkV8bJyQkVK1aUyqQ3a9YsWFhYSC9nZ2ft7ggREREVaGonq9LGpkrvzZs3MDU11UhQRERERKS+8PBwAIC9vb3cdHt7e2leeHg4DAwMYGlpmWGZ9CZMmIDo6Gjp9ezZMy1ET0RERPSJSrcBApC6kstkMvTp0weGhobSvJSUFNy8eRN16tTRfIREREREpJb0Pyxm9GOjqmUMDQ3lrv2IiIiItEnlZJWFhQWATxcyZmZmMDY2luYZGBigVq1aGDhwoOYjJCIiIiKVODg4APjUe8rR0VGaHhERIfW2cnBwQGJiIqKiouR6V0VERPCHRyIiIsoTVE5WrVmzBgDg6uqKsWPH8pY/IiIiojymePHicHBwQEBAAKpWrQoASExMxNmzZzFnzhwAQPXq1aGvr4+AgAB06dIFwKfHtt++fRtz587NtdiJiIiI0qicrEozdepUbcRBRERERCqIi4vDf//9J71//PgxgoODYWVlhWLFisHX1xf+/v4oXbo0SpcuDX9/f5iYmKBHjx4APvWW79+/P8aMGQNra2tYWVlh7NixcHd3l54OSERERJSb1E5WvXr1CmPHjsXJkycREREBIYTc/JSUFI0FR0RERETyrl69KvcE5tGjRwMAfHx8sHbtWowbNw4fPnzA0KFDERUVBU9PTxw/fhxmZmbSMgsWLICenh66dOmCDx8+oFGjRli7di10dXW/+P4QERERpad2sqpPnz54+vQpJk+eDEdHxywH6yQiIiIizWnQoIHCj4Wfk8lk8PPzg5+fX4ZljIyMsGTJEixZskQLERIRERHljNrJqgsXLuD8+fOoUqWKFsIhIiIiIiIiIqKCTEfdBZydnTP9NY+IiIiIiIiIiCi71E5WLVy4EOPHj0doaKgWwiEiIiIiIiIiooJM7dsAu3btivj4eJQsWRImJibQ19eXm//27VuNBUdERERERERERAWL2smqBQsWcFB1IiIiIiIiIiLSimw9DZCIiIiIiIiIiEgb1B6zqkGDBli/fj0+fPigjXjkzJo1CzVq1ICZmRns7OzQrl073Lt3T65Mnz59IJPJ5F61atWSK5OQkIARI0bAxsYGpqamaNOmDZ4/f671+ImIiIiIiIiISD1qJ6uqV6+OcePGwcHBAQMHDsSlS5e0ERcA4OzZsxg2bBguXbqEgIAAJCcno0mTJnj//r1cuWbNmiEsLEx6HT58WG6+r68v9uzZg61bt+LChQuIi4tDq1atkJKSorXYiYiIiIiIiIhIfWonq3777Te8ePEC69evx+vXr/HNN9+gfPny+PXXX/Hq1SuNBnf06FH06dMHFSpUQOXKlbFmzRo8ffoU165dkytnaGgIBwcH6WVlZSXNi46OxqpVq/Dbb7+hcePGqFq1KjZu3Ihbt27hxIkTGo2XiIiIiIiIiIhyRu1kFQDo6uqibdu22Lt3L168eIEePXpg8uTJcHZ2Rrt27XDq1ClNxwngU+IJgFwyCgDOnDkDOzs7lClTBgMHDkRERIQ079q1a0hKSkKTJk2kaU5OTqhYsSICAwMz3FZCQgJiYmLkXkREREREREREpF3ZSlal+fvvvzFlyhT8+uuvsLOzw4QJE2BnZ4fWrVtj7NixmooRACCEwOjRo1GvXj1UrFhRmt68eXNs2rQJp06dwm+//YYrV67g22+/RUJCAgAgPDwcBgYGsLS0lFufvb09wsPDM9zerFmzYGFhIb2cnZ01uj9ERERERERERKRI7acBRkREYMOGDVizZg0ePHiA1q1bY+vWrWjatClkMhkAoEuXLmjXrh1+/fVXjQU6fPhw3Lx5ExcuXJCb3rVrV+nvihUrwsPDAy4uLjh06BA6dOiQ4fqEEFK8ykyYMAGjR4+W3sfExDBhRURERERERESkZWonq4oWLYqSJUuiX79+6NOnD2xtbRXK1KxZEzVq1NBIgAAwYsQI7N+/H+fOnUPRokUzLevo6AgXFxc8ePAAAODg4IDExERERUXJ9a6KiIhAnTp1MlyPoaEhDA0NNbMDRERERERERESkErVvAzx58iRCQkLw448/Kk1UAYC5uTlOnz6d4+CEEBg+fDh2796NU6dOoXjx4lku8+bNGzx79gyOjo4APj29UF9fHwEBAVKZsLAw3L59O9NkFRERERERERERfXlq96zy8PBAfHw8TExMAABPnjzBnj17UL58eblBzDVh2LBh2Lx5M/bt2wczMzNpjCkLCwsYGxsjLi4Ofn5+6NixIxwdHREaGoqJEyfCxsYG7du3l8r2798fY8aMgbW1NaysrDB27Fi4u7ujcePGGo2XiIiIiIiIiIhyRu1kVdu2bdGhQwcMHjwY7969g6enJ/T19REZGYn58+djyJAhGgvu999/BwA0aNBAbvqaNWvQp08f6Orq4tatW1i/fj3evXsHR0dHNGzYENu2bYOZmZlUfsGCBdDT00OXLl3w4cMHNGrUCGvXroWurq7GYiUiIiIiIiIiopxTO1l1/fp1LFiwAACwc+dO2Nvb48aNG9i1axemTJmi0WSVECLT+cbGxjh27FiW6zEyMsKSJUuwZMkSTYVGRERERERERERaoPaYVfHx8VKvpePHj6NDhw7Q0dFBrVq18OTJE40HSEREREREREREBYfayapSpUph7969ePbsGY4dOyaNUxUREQFzc3ONB0hERERERERERAWH2smqKVOmYOzYsXB1dYWnpydq164N4FMvq6pVq2o8QCIiIiIiIiIiKjjUHrOqU6dOqFevHsLCwlC5cmVpeqNGjaQn8BEREREREREREWWH2skqAHBwcICDg4PctJo1a2okICIiIiIiIiIiKrjUvg2QiIiIiIiIiIhIW5isIiIiIiIiIiKiPIPJKiIiIiIiIiIiyjNUSlZVq1YNUVFRAIDp06cjPj5eq0EREREREREREVHBpFKyKiQkBO/fvwcATJs2DXFxcVoNioiIiIiIiIiICiaVngZYpUoV9O3bF/Xq1YMQAr/++isKFSqktOyUKVM0GiARERERERERZS4kJCS3Q8gWGxsbFCtWLLfDoDxGpWTV2rVrMXXqVBw8eBAymQxHjhyBnp7iojKZjMkqIiIiIiIioi8kLCwMOjo66NWrV26Hki0mJiYICQlhworkqJSsKlu2LLZu3QoA0NHRwcmTJ2FnZ6fVwIiIiIiI8qunT58iMjIyt8NQW37tmUFUkL179w6pqanYuHEj3NzccjsctYSEhKBXr16IjIxksorkqJSs+lxqaqo24iAiIiIi+io8ffoUbm5ufCgREX1Rbm5uqFatWm6HQaQRaierAODhw4dYuHAhQkJCIJPJ4ObmhpEjR6JkyZKajo+IiIiIKF+JjIxEfHx8vuzlcPjwYUyePDm3wyAiogJO7WTVsWPH0KZNG1SpUgV169aFEAKBgYGoUKECDhw4AG9vb23ESURERESUr+THXg68DZCIiPICtZNV48ePx6hRozB79myF6T/99BOTVURERERERERElG066i4QEhKC/v37K0zv168f7t69q5GgiIiIiIiIiIioYFI7WWVra4vg4GCF6cHBwXxCIBERERERERER5YjatwEOHDgQ33//PR49eoQ6depAJpPhwoULmDNnDsaMGaONGImIiIiIiIiIqIBQO1k1efJkmJmZ4bfffsOECRMAAE5OTvDz88MPP/yg8QCJiIiIiIiIiKjgUDtZJZPJMGrUKIwaNQqxsbEAADMzM40HRkREREREREREBY/ayarPMUlFRERERERERESapPYA60RERERERERERNrCZBUREREREREREeUZTFYREREREREREVGeUaCSVcuXL0fx4sVhZGSE6tWr4/z587kdEhERERERERERfSZbyarhw4fj7du3mo5Fq7Zt2wZfX19MmjQJN27cQP369dG8eXM8ffo0t0MjIiIiIiIiIqL/p3Ky6vnz59LfmzdvRlxcHADA3d0dz54903xkGjZ//nz0798fAwYMgJubGxYuXAhnZ2f8/vvvuR0aERERERERERH9P5WTVeXKlYOLiwt69OiBjx8/Sgmq0NBQJCUlaS1ATUhMTMS1a9fQpEkTuelNmjRBYGCg0mUSEhIQExMj9yIiIiIiIiIiIu3SU7VgdHQ0rl27hvPnz2P37t1o0aIF7O3tkZCQgGPHjqF9+/ZwcHDQZqzZFhkZiZSUFNjb28tNt7e3R3h4uNJlZs2ahWnTpn2J8IiIiIgonadPnyIyMjK3w8iWkJCQ3A6BiIgoX1M5WZWUlISaNWuiZs2amDlzJq5du4awsDA0btwYq1evxtixY1G0aFHcu3dPm/HmiEwmk3svhFCYlmbChAkYPXq09D4mJgbOzs5ajY+I8gkTE+D/b4WGiUnuxkJE9BV6+vQp3NzcEB8fn9uhEBHRF5Cfk/w2NjYoVqxYbofx1VE5WWVubo6qVauibt26SExMRHx8POrWrQs9PT1s27YNRYsWxd9//63NWLPNxsYGurq6Cr2oIiIiFHpbpTE0NIShoeGXCI+I8huZDDA1ze0oiIi+WpGRkYiPj8fGjRvh5uaW2+Go7fDhw5g8eXJuh0FElOeFhYVBR0cHvXr1yu1Qss3ExAQhISFMWGmYysmqly9fIigoCIGBgUhOToaHhwdq1KiBxMREXL9+Hc7OzqhXr542Y802AwMDVK9eHQEBAWjfvr00PSAgAG3bts3FyIiIiIgoI25ubqhWrVpuh6G2/NxDgIjoS3r37h1SU1Pz7Y8TISEh6NWrFyIjI5ms0jCVk1U2NjZo3bo1WrdujRUrVuDcuXMICQnBd999h7Fjx6J3796oWbMmzp49q814s2306NHo3bs3PDw8ULt2baxcuRJPnz7F4MGDczs0IiIiolyxfPlyzJs3D2FhYahQoQIWLlyI+vXr53ZYRERUwOTXHydIe1ROVqVnYWGBLl26oH///jh16hRMTEzybKIKALp27Yo3b95g+vTpCAsLQ8WKFXH48GG4uLjkdmhEREREX9y2bdvg6+uL5cuXo27duvjjjz/QvHlz3L17l78OExERqSG/9qjNy+NtZStZdfPmTRQpUgQA4OLiAn19fTg4OKBr164aDU7Thg4diqFDh2ZrWSEEgE8DrRMRERF9Lu36IO16IT+YP38++vfvjwEDBgAAFi5ciGPHjuH333/HrFmz5MomJCQgISFBeh8dHQ1Ae9dFcf//EItr165Jf+cnaf+05Mf483PsQP6OPz/HDuTv+PNz7ED+jj8/xw4AQUFBkMlk+XbMLWNjY1y5ckUrD5PL6bWRTOSnq6pc9Pz5cz4NkIiIiDL17NkzFC1aNLfDyFJiYiJMTEywY8cOufE8R44cieDgYIXe8n5+fpg2bdqXDpOIiIjyuexeG2X7NsCCxsnJCc+ePYOZmRlkMlluh5OnxMTEwNnZGc+ePYO5uXluh1OgsO5zD+s+97Ducw/rPmNCCMTGxsLJySm3Q1FJZGQkUlJSFJ6KbG9vr/D0ZACYMGECRo8eLb1PTU3F27dvYW1tzesi8NjILtZb9rHuso91lz2st+wrqHWX02sjJqtUpKOjky9+Kc1N5ubmBergy0tY97mHdZ97WPe5h3WvnIWFRW6HoLb0iSYhhNLkk6GhIQwNDeWmFS5cWJuh5Us8NrKH9ZZ9rLvsY91lD+st+wpi3eXk2khHg3EQERERUT5gY2MDXV1dhV5UERERCr2tiIiIiL40JquIiIiIChgDAwNUr14dAQEBctMDAgJQp06dXIqKiIiI6BPeBkg5ZmhoiKlTpyrcHkDax7rPPaz73MO6zz2s+6/L6NGj0bt3b3h4eKB27dpYuXIlnj59isGDB+d2aPkOj43sYb1lH+su+1h32cN6yz7WXfbwaYBEREREBdTy5csxd+5chIWFoWLFiliwYAG++eab3A6LiIiICjgmq4iIiIiIiIiIKM/gmFVERERERERERJRnMFlFRERERERERER5BpNVRERERERERESUZzBZRUREREREREREeQaTVZSlqKgo9O7dGxYWFrCwsEDv3r3x7t27TJcRQsDPzw9OTk4wNjZGgwYNcOfOnQzLNm/eHDKZDHv37tX8DuRj2qj7t2/fYsSIEShbtixMTExQrFgx/PDDD4iOjtby3uRty5cvR/HixWFkZITq1avj/PnzmZY/e/YsqlevDiMjI5QoUQIrVqxQKLNr1y6UL18ehoaGKF++PPbs2aOt8PM1Tdf9n3/+ifr168PS0hKWlpZo3Lgx/v77b23uQr6ljXafZuvWrZDJZGjXrp2GoybSLHWOgwsXLqBu3bqwtraGsbExypUrhwULFsiVWbt2LWQymcLr48eP2d5uXpXdfbh48SL09PRQpUoVhXmqfHey7hTrju1OuTNnziitl3///VeuXEFod5quN7a5jCUkJGDSpElwcXGBoaEhSpYsidWrV8uVKQhtLscEURaaNWsmKlasKAIDA0VgYKCoWLGiaNWqVabLzJ49W5iZmYldu3aJW7duia5duwpHR0cRExOjUHb+/PmiefPmAoDYs2ePlvYif9JG3d+6dUt06NBB7N+/X/z333/i5MmTonTp0qJjx45fYpfypK1btwp9fX3x559/irt374qRI0cKU1NT8eTJE6XlHz16JExMTMTIkSPF3bt3xZ9//in09fXFzp07pTKBgYFCV1dX+Pv7i5CQEOHv7y/09PTEpUuXvtRu5QvaqPsePXqIZcuWiRs3boiQkBDRt29fYWFhIZ4/f/6lditf0EbdpwkNDRVFihQR9evXF23bttXynhBln7rHwfXr18XmzZvF7du3xePHj8WGDRuEiYmJ+OOPP6Qya9asEebm5iIsLEzulZPt5kXZ3Yd3796JEiVKiCZNmojKlSvLzVPlu5N1p7zu2O6U78Pp06cFAHHv3j25eklOTpbKFIR2p416Y5vLeB/atGkjPD09RUBAgHj8+LG4fPmyuHjxojS/ILQ5TWCyijJ19+5dAUDuwAkKChIAxL///qt0mdTUVOHg4CBmz54tTfv48aOwsLAQK1askCsbHBwsihYtKsLCwpisSkfbdf+57du3CwMDA5GUlKS5HchHatasKQYPHiw3rVy5cmL8+PFKy48bN06UK1dObtqgQYNErVq1pPddunQRzZo1kyvTtGlT0a1bNw1F/XXQRt2nl5ycLMzMzMS6detyHvBXRFt1n5ycLOrWrSv++usv4ePjw2QV5WnqHgfKtG/fXvTq1Ut6v2bNGmFhYaH17ea27O5D165dxc8//yymTp2qkHBR5buTdae87tjulO9DWtIlKioqw3UWhHanjXpjm1O+D0eOHBEWFhbizZs3Ga6zILQ5TeBtgJSpoKAgWFhYwNPTU5pWq1YtWFhYIDAwUOkyjx8/Rnh4OJo0aSJNMzQ0hJeXl9wy8fHx6N69O5YuXQoHBwft7UQ+pc26Ty86Ohrm5ubQ09PT3A7kE4mJibh27ZpcnQFAkyZNMqyzoKAghfJNmzbF1atXkZSUlGmZzD6HgkZbdZ9efHw8kpKSYGVlpZnAvwLarPvp06fD1tYW/fv313zgRBqUneMgvRs3biAwMBBeXl5y0+Pi4uDi4oKiRYuiVatWuHHjhka3m9uyuw9r1qzBw4cPMXXqVKXzs/ruZN1lXHcA211mqlatCkdHRzRq1AinT5+Wm/e1tztt1RvANqfM/v374eHhgblz56JIkSIoU6YMxo4diw8fPkhlvvY2pylMVlGmwsPDYWdnpzDdzs4O4eHhGS4DAPb29nLT7e3t5ZYZNWoU6tSpg7Zt22ow4q+HNuv+c2/evMGMGTMwaNCgHEacP0VGRiIlJUWtOgsPD1daPjk5GZGRkZmWyWidBZG26j698ePHo0iRImjcuLFmAv8KaKvuL168iFWrVuHPP//UTuBEGpSd4yBN0aJFYWhoCA8PDwwbNgwDBgyQ5pUrVw5r167F/v37sWXLFhgZGaFu3bp48OBBjrebV2RnHx48eIDx48dj06ZNGf44ltV3J+su47pju1O+D46Ojli5ciV27dqF3bt3o2zZsmjUqBHOnTsnlfna25226o1tTvk+PHr0CBcuXMDt27exZ88eLFy4EDt37sSwYcOkMl97m9OUgteNggAAfn5+mDZtWqZlrly5AgCQyWQK84QQSqd/Lv38z5fZv38/Tp06JZd9Lyhyu+4/FxMTg5YtW6J8+fKZ/lJXEKhaZ5mVTz9d3XUWVNqo+zRz587Fli1bcObMGRgZGWkg2q+LJus+NjYWvXr1wp9//gkbGxvNB0ukJdk5V58/fx5xcXG4dOkSxo8fj1KlSqF79+4APvWCrlWrllS2bt26qFatGpYsWYLFixfnaLt5jar7kJKSgh49emDatGkoU6ZMjtfJulPEdqd8H8qWLYuyZctK72vXro1nz57h119/xTfffKPWOvN73Wm63tjmlO9DamoqZDIZNm3aBAsLCwDA/Pnz0alTJyxbtgzGxsYqr/NrqLucYLKqgBo+fDi6deuWaRlXV1fcvHkTr169Upj3+vVrhUxvmrRb+sLDw+Ho6ChNj4iIkJY5deoUHj58iMKFC8st27FjR9SvXx9nzpxRY2/yl9yu+zSxsbFo1qwZChUqhD179kBfX1/dXfkq2NjYQFdXV+FXCmV1lsbBwUFpeT09PVhbW2daJqN1FkTaqvs0v/76K/z9/XHixAlUqlRJs8Hnc9qo+zt37iA0NBStW7eW5qempgIA9PT0cO/ePZQsWVLDe0KUfdk5DtIUL14cAODu7o5Xr17Bz89PSlalp6Ojgxo1aki9DXKy3bxC3X2IjY3F1atXcePGDQwfPhzAp/ODEAJ6eno4fvw4vv322yy/O1l3Gdddemx3GatVqxY2btwovf/a25226i09trlPHB0dUaRIESlRBQBubm4QQuD58+coXbr0V9/mNIW3ARZQNjY2KFeuXKYvIyMj1K5dG9HR0XKPfb98+TKio6NRp04dpesuXrw4HBwcEBAQIE1LTEzE2bNnpWXGjx+PmzdvIjg4WHoBwIIFC7BmzRrt7XgekNt1D3zqUdWkSRMYGBhg//79BbrHiYGBAapXry5XZwAQEBCQYT3Xrl1bofzx48fh4eEhJf0yKpPROgsibdU9AMybNw8zZszA0aNH4eHhofng8zlt1H25cuVw69YtufN6mzZt0LBhQwQHB8PZ2Vlr+0OUHdk5DpQRQiAhISHT+cHBwdKPSJrabm5Sdx/Mzc0Vzg+DBw9G2bJlERwcLI3PmdV3J+su47pLj+0uYzdu3JD7Ufdrb3faqrf02OY+qVu3Ll6+fIm4uDhp2v3796Gjo4OiRYsC+PrbnMZofQh3yveaNWsmKlWqJIKCgkRQUJBwd3cXrVq1kitTtmxZsXv3bun97NmzhYWFhdi9e7e4deuW6N69u3B0dBQxMTEZbgd8GqACbdR9TEyM8PT0FO7u7uK///7L8HG0BUnao2FXrVol7t69K3x9fYWpqakIDQ0VQggxfvx40bt3b6n8o0ePhImJiRg1apS4e/euWLVqldDX1xc7d+6Uyly8eFHo6uqK2bNni5CQEDF79myFR9KSdup+zpw5wsDAQOzcuVOufcfGxn7x/cvLtFH36fFpgJTXqXscLF26VOzfv1/cv39f3L9/X6xevVqYm5uLSZMmSWX8/PzE0aNHxcOHD8WNGzdE3759hZ6enrh8+bLK280P1K279JQ90U6V707WnfK6Y7tTXncLFiwQe/bsEffv3xe3b98W48ePFwDErl27pDIFod1po97Y5pTXXWxsrChatKjo1KmTuHPnjjh79qwoXbq0GDBggFSmILQ5TWCyirL05s0b0bNnT2FmZibMzMxEz549FR5jCkCsWbNGep+amiqmTp0qHBwchKGhofjmm2/ErVu3Mt0Ok1WKtFH3aY+iVfZ6/Pjxl9mxPGjZsmXCxcVFGBgYiGrVqomzZ89K83x8fISXl5dc+TNnzoiqVasKAwMD4erqKn7//XeFde7YsUOULVtW6Ovri3Llysl9wdP/aLruXVxclLbvqVOnfoG9yV+00e4/x2QV5QfqHAeLFy8WFSpUECYmJsLc3FxUrVpVLF++XKSkpEhlfH19RbFixYSBgYGwtbUVTZo0EYGBgWptN79Q9xzyOWUJFyFU++5k3SnWHdvdJ+nrbs6cOaJkyZLCyMhIWFpainr16olDhw4prLMgtDtN1xvb3CfKjteQkBDRuHFjYWxsLIoWLSpGjx4t4uPj5coUhDaXUzIh/n90VCIiIiIiIiIiolzGMauIiIiIiIiIiCjPYLKKiIiIiIiIiIjyDCariIiIiIiIiIgoz2CyioiIiIiIiIiI8gwmq4iIiIiIiIiIKM9gsoqIiIiIiIiIiPIMJquIiIiIiIiIiCjPYLKKiIiIiIiIiIjyDCariIiy4c2bN7Czs0NoaKjKy0RERMDW1hYvXrzQXmBERERERET5HJNVRFRgyWSyTF99+vTJcNlZs2ahdevWcHV1BQCEhoZCJpMhODhYKhMbG4sGDRqgXLlyePbsGezs7NC7d29MnTpVuztGRERERFoVGxuLGjVqoEqVKnB3d8eff/6Z2yERfVVkQgiR20EQEeWG8PBw6e9t27ZhypQpuHfvnjTN2NgYFhYWCst9+PABTk5OOHz4MGrXrg3gU7KqePHiuHHjBqpUqYLXr1+jefPmAICjR4/CxsYGAHDr1i3UrFkTL1++hKWlpTZ3j4iIiIi0JCUlBQkJCTAxMUF8fDwqVqyIK1euwNraOrdDI/oqsGcVERVYDg4O0svCwgIymUxhmjJHjhyBnp6elKhK79mzZ6hfvz7MzMxw+vRpKVEFAO7u7nBwcMCePXu0sk9EREREX1qDBg3g6+ur8fVmZ9iFL0VXVxcmJiYAgI8fPyIlJQVp/UA6deqE+fPn52Z4RPkek1VERGo6d+4cPDw8lM67d+8e6tati3LlyuHo0aMwMzNTKFOzZk2cP39e22ESERGRloWHh2PEiBEoUaIEDA0N4ezsjNatW+PkyZNSmWfPnqF///5wcnKCgYEBXFxcMHLkSLx58ybb2+3Tp480bIG+vj7s7e3h7e2N1atXIzU1VRO7ppbdu3djxowZADSbuEo/7IK6+vTpg/Hjx2skFmXevXuHypUro2jRohg3bpz0A+WUKVPwyy+/ICYmRmvbJvraMVlFRKSm0NBQODk5KZ333XffoWTJkti1axcMDQ2VlilSpEie/IWQiIiIVBcaGorq1avj1KlTmDt3Lm7duoWjR4+iYcOGGDZsGADg0aNH8PDwwP3797Flyxb8999/WLFiBU6ePInatWvj7du32d5+s2bNEBYWhtDQUBw5cgQNGzbEyJEj0apVKyQnJ2tqN1ViZWWl9Ae6nPjw4QNWrVqFAQMGZGv51NRUHDp0CG3bttVoXJ8rXLgw/vnnHzx+/BibN2/Gq1evAACVKlWCq6srNm3apLVtE33tmKwiIlLThw8fYGRkpHRe27ZtceHCBezatSvD5Y2NjREfH6+t8IiIiOgLGDp0KGQyGf7++2906tQJZcqUQYUKFTB69GhcunQJADBs2DAYGBjg+PHj8PLyQrFixdC8eXOcOHECL168wKRJk7K9fUNDQzg4OKBIkSKoVq0aJk6ciH379uHIkSNYu3atVE4Igblz56JEiRIwNjZG5cqVsXPnTrl1NWjQAD/88APGjRsHKysrODg4wM/PT5q/c+dOuLu7w9jYGNbW1mjcuDHev38vt7yvry/69OmDs2fPYtGiRVLPr9DQUKxfvx7W1tZISEiQ227Hjh3x3XffKd2/jIZdiI2NRc+ePWFqagpHR0csWLBAaW+uixcvQkdHB56enkhNTcWcOXNQqlQpGBoaolixYvjll1/k4h8xYgR8fX1haWkJe3t7rFy5Eu/fv0ffvn1hZmaGkiVL4siRI0pjtbe3R6VKlXDu3DlpWps2bbBlyxal5Ykoa0xWERGpycbGBlFRUUrnTZw4EVOnTkXPnj2xbds2pWXevn0LW1tbbYZIREREWvT27VscPXoUw4YNg6mpqcL8woUL4+3btzh27BiGDh0KY2NjufkODg7StYImn3f17bffonLlyti9e7c07eeff8aaNWvw+++/486dOxg1ahR69eqFs2fPyi27bt06mJqa4vLly5g7dy6mT5+OgIAAhIWFoXv37ujXrx9CQkJw5swZdOjQQWncixYtQu3atTFw4ECEhYUhLCwMzs7O6Ny5M1JSUrB//36pbGRkJA4ePIi+ffsq3ZeMhl0YPXo0Ll68iP379yMgIADnz5/H9evXFcrt378frVu3ho6ODiZMmIA5c+Zg8uTJuHv3LjZv3gx7e3uF/bexscHff/+NESNGYMiQIejcuTPq1KmD69evo2nTpujdu7f0g+OrV6+k2/xiYmJw7tw5lC1bVlpfzZo18ffffysk6IhINXq5HQARUX5TtWpVbNy4McP5P//8M/T09NCzZ0+kpqaie/fucvNv376NBg0aaDlKIiIi0pb//vsPQgiUK1cuwzIPHjyAEAJubm5K57u5uSEqKgqvX7+GnZ2dxmIrV64cbt68CQB4//495s+fj1OnTkk9lEqUKIELFy7gjz/+gJeXl7RcpUqVMHXqVABA6dKlsXTpUpw8eRLW1tZITk5Ghw4d4OLiAuDTA2OUsbCwgIGBAUxMTODg4CBNNzY2Ro8ePbBmzRp07twZALBp0yYULVo0w2siZcMuxMbGYt26ddi8eTMaNWoEAFizZo3S4Rn279+PX3/9FbGxsVi0aBGWLl0KHx8fAEDJkiVRr149ufKVK1fGzz//DACYMGECZs+eDRsbGwwcOBDAp3Gofv/9d9y8eRO1atXC8+fP0b9/fwghIITA8OHDUalSJWl9RYoUQUJCAsLDw6V6IyLVMVlFRKSmpk2bYsKECYiKioKlpaXSMuPHj4euri569+6N1NRU9OzZEwAQHx+Pa9euwd/f/0uGTERERBqU1qtIJpNpZB3Pnj1D7969ERERAT09PUyePFlK6mRnvWlx3b17Fx8/foS3t7dcmcTERFStWlVu2ueJFgBwdHREREQEKleujEaNGsHd3R1NmzZFkyZN0KlTpwyvgTIycOBA1KhRAy9evECRIkWwZs0aaaB4ZZQNu/Do0SMkJSWhZs2a0jQLCwu5Hk0AEBISgufPn6Nx48a4desWEhISpORWRj7ff11dXVhbW8sl5dJ6YkVERAAAqlevjuDg4AzXl9abjkM/EGUPbwMkIlKTu7s7PDw8sH379kzL/fjjj5g7dy58fHywYcMGAMC+fftQrFgx1K9f/0uESkRERFpQunRpyGQyhISEZFimVKlSkMlkuHv3rtL5//77LywtLWFjYwM9PT0sXLgQd+/exYkTJzBq1Ci5MaHUERISguLFiwOA9GTAQ4cOITg4WHrdvXtXYdwqfX19ufcymQypqanQ1dVFQEAAjhw5gvLly2PJkiUoW7YsHj9+rFZcVatWReXKlbF+/Xpcv34dt27dQp8+fTIsr2zYhYyShOlvSdy/fz+8vb1hbGyscAtmRpTt/+fT0rap6tMW0wbP59APRNnDZBURET492vjdu3cql588eTIWLVokXbC4urpCCIEqVarIlRs9ejSSk5PRu3dvAMCCBQswZcoUTYVNREREucDKygpNmzbFsmXLlCaV3r17B2tra3h7e2P58uX48OGD3Pzw8HBs2rQJXbt2hUwmg6Ojo3QNYWdnBysrq2w9KfDUqVO4desWOnbsCAAoX748DA0N8fTpU5QqVUru5ezsrPJ6ZTIZ6tati2nTpuHGjRswMDDAnj17lJY1MDBASkqK0nkDBgzAmjVrsHr1ajRu3DjTGKpWraqQ6CtZsiT09fXx999/S9NiYmLw4MEDuXL79u1DmzZtAHxKLBobG+PkyZMq7aum3L59G0WLFoWNjc0X3S7R14LJKiKibGjRogUGDRqEFy9eqLxMREQEOnXqpDCGFREREeU/y5cvR0pKCmrWrIldu3bhwYMHCAkJweLFi6XxoZYuXYqEhAQ0bdoU586dw7Nnz3D06FF4e3ujSJEick+kS3P16lWkpqZmmUxKGw/pxYsXuH79Ovz9/dG2bVu0atVKesKemZkZxo4di1GjRmHdunV4+PAhbty4gWXLlmHdunUq7efly5fh7++Pq1ev4unTp9i9ezdev36d4Vhcrq6uuHz5MkJDQxEZGSnXE6lnz5548eIF/vzzT/Tr1y/T7TZt2hR37tyR611lZmYGHx8f/Pjjjzh9+jTu3LmDfv36QUdHR+r5FBERgStXrqBVq1YAACMjI/z0008YN24c1q9fj4cPH+LSpUtYtWqVSvufXefPn0eTJk20ug2irxnHrCIiyqaRI0eqVd7Ozg7jxo3TUjRERET0JRUvXhzXr1/HL7/8gjFjxiAsLAy2traoXr06fv/9dwCfevVcvXoVfn5+6Nq1K968eQMHBwe0a9cOU6dOhZWVldw637x5g++++w5//fVXlts/evQoHB0doaenB0tLS1SuXBmLFy+Gj48PdHT+1ydhxowZsLOzw6xZs/Do0SMULlwY1apVw8SJE1XaT3Nzc5w7dw4LFy5ETEwMXFxc8Ntvv6F58+ZKy48dOxY+Pj4oX748Pnz4gMePH8PV1VVaV8eOHXHo0P+xd9/xUVT7/8ffS3ogiQkhDUPvEEBQugalSxUpimJQxHIFqZcLKkVUUERAREFRKSLCBSkqSG8iRS6ItAiKIKAEDCUBAgkk5/cHv+yXJQlkwy6b8no+HvN4ZGfOnvOZyS758JmZM0vVoUOHm457/bQLzz//vHX9+PHj9cILL6hNmzby9/fX4MGDdezYMev8Vt9++63q1q1rM2n9sGHD5O7uruHDh+vvv/9WeHi4XnjhhWztf05cvnxZixYt0ooVK5w2BpDfWYwjn5UKAAAAALBbcnKymjVrpl69elmnD8iPmjVrpsqVK2vSpEm3bLts2TINGjRIe/futSnAXe/ixYsqXry43nvvPfXs2VPt2rVTo0aNXHqC8MMPP9SSJUu0cuVKl8UA5HVcWQUAAAAALmSMUY8ePfTQQw/l20LVmTNntHLlSq1du1aTJ0/O1nsefvhh/fbbb/rrr7+st0X+/PPP+vXXX1WnTh0lJCRo1KhRkqT27dtLkho1auTyKRc8PDz0wQcfuDQGIK/jyioAAAAAcKFNmzbpgQceUPXq1a3rvvjiC0VFRbkwKscqVaqUzp49q2HDhmnQoEE57ufnn3/Ws88+qwMHDsjT01O1a9fW+PHj89WxAkCxCgAAAAAAALkITwMEAAAAAABArkGxCgAAAAAAALkGxSoAAAAAAADkGhSrAAAAAAAAkGtQrAIAAAAAAECuQbEKAAAAAAAAuQbFKgAAAAAAAOQaFKsAAAAAAACQa1CsAgAAAAAAQK5BsQoAAAAAAAC5BsUqAAAAAAAA5BoUqwAAAAAAAJBrUKwCAAAAAABArkGxCgAAAAAAALkGxSoAAAAAAADkGhSrAAAAAAAAkGtQrAIAAAAAAECuQbEKAAAAAAAAuQbFKgAAANzSjBkzZLFY9L///c/VoViNHj1aixcvznZ7i8ViXdzc3BQYGKgaNWro+eef19atWzO0P3LkiCwWi2bMmGFXXHPmzNHEiRPtek9mY40cOVIWi0Xx8fF29XUz+/fv18iRI3XkyJEM23r06KFSpUo5bKzs2rBhgwoVKqRXXnklw7ZDhw6pSJEi6tSpk3Vdjx49VKRIkSz7K1KkiHr06GF9ffDgQQ0aNEi1a9fWXXfdpaCgIDVs2FALFizIso/ly5erdevWKlasmLy8vBQZGamYmBjt378/Zzv5/zVu3FgWi0UtW7bMsC39MzBu3LjbGsOVLBaLRo4caX29fv16WSwWrV+/3uljlypVyub3ntOxP/roI7u/85mNdavPaU5s3rxZI0eO1Llz5xzar3R73//z589r8ODBat68uYoVK5bhc5BbfPDBB6pUqZK8vLxUunRpvf7667py5YpLYsnp35eChGIVAAAA8iR7i1WS1KlTJ23ZskWbNm3S3Llz9dRTT2nr1q2qX7+++vbta9M2PDxcW7ZsUevWre0aIyfFqpyOZa/9+/fr9ddfz7RYNWzYMC1atMip42cmOjpaL7/8ssaOHauffvrJuj4tLU0xMTHy9fXVlClTctz/ypUrtXTpUj366KOaP3++vvzyS5UvX16dO3fWqFGjMrQfPHiwWrVqpbS0NH300UdatWqVRowYoe3bt6tWrVpauHBhjmNJt2LFCq1du/a2+0HWatWqpS1btqhWrVp2vS8nxaqcjmWvzZs36/XXX3dKsep2nD59Wp988omSk5PVoUMHV4eTqbfeekt9+/ZVx44dtWLFCv3rX//S6NGj9dJLL7k6NGTB3dUBAAAAAHdKaGio6tWrZ33dokUL9evXT88995wmTZqkSpUq6cUXX5QkeXl52bR1htTUVF29evWOjHUrZcuWddnYY8aM0ffff6+YmBj9/PPP8vb21rhx4/Tjjz/q66+/VrFixXLc92OPPaaXXnpJFovFuq5Vq1aKj4/XO++8o//85z/y8vKSJH311Vd699139eKLL+qjjz6ytn/ggQf0+OOPKzo6Wt27d1fNmjVVpkyZHMVToUIFXb16VYMHD9b27dtt4nKkK1euyGKxyN29YP6Xz9/f3+nfqfRjfCfGys1Kliyps2fPWq8E/fTTT10dko3Tp0/rzTffVK9evTR69GhJ165yvHLlil577TX169dPVapUcXGUt8eZ3/ekpCT5+vo6vN9b4coqAAAA5Ej6bS6///67Hn74YRUpUkSRkZEaOHCgkpOTre3Sb3cYO3as3nrrLZUoUULe3t669957tWbNmgx9ZnYrSvotceksFosuXryomTNnWm/ta9y4cY72w83NTZMnT1ZwcLDefffdDHFff5XFP//8o+eee06RkZHy8vJSsWLF1LBhQ61evVrStf8ALV26VH/++afNbYc3Hoc333xTpUuXlpeXl9atW3fTW0KOHTumjh07yt/fXwEBAXryySf1zz//2LTJ6rab62+NmjFjhjp37ixJevDBB62xpY+Z2bG/fPmyhg4dqtKlS8vT01PFixfXSy+9lOHKjlKlSqlNmzZavny5atWqJR8fH1WqVEmff/75LY7+NT4+PpoxY4YOHjyoV155RXv37tXw4cP1xBNPqGPHjtnqIyvBwcGZFoTq1KmjpKQknTlzxrrurbfeUmBgYKa34hUuXFgffPCBkpKSNGHChBzH4+Hhobfeeks7duzQvHnzbtl+7969at++vQIDA+Xt7a2aNWtq5syZNm3Sb0P74osvNHDgQBUvXlxeXl76/fffrd/TX3/9VS1atFDhwoUVHh6ut99+W5K0detWNWrUSIULF1aFChUy9P3PP//oX//6l6pUqaIiRYooJCREDz30kH744Qe79/2LL76QxWLRli1bMmwbNWqUPDw89Pfff9+0jytXrmjw4MEKCwuTr6+vGjVqZHNF3o3H5Ppb8/744w899thjioiIkJeXl0JDQ9WkSRPt2rVL0rXP8b59+7Rhwwbr9yP9O3GzY3yzWw737dunJk2aqHDhwipWrJh69+6tpKQk6/abffev/16PHDlS//73vyVJpUuXtsZ3/Zjz5s1T/fr1VbhwYRUpUkQtWrTQzz//nKHfGTNmqGLFivLy8lLlypU1a9asmx7zW7n+37lbSUxM1EsvvaQSJUrIw8PD5t9Ji8VicyunoyxfvlyXL1/W008/bbP+6aefljHG5grd2/2+SNn7zmbm999/19NPP63y5cvL19dXxYsXV9u2bbVnzx6bdjf7LGbGnr/B6X9rd+7cqU6dOikwMNB6IsPevweLFi1S9erV5e3trTJlymjSpEm3PAbXo1gFAACAHLty5YratWunJk2aaMmSJXrmmWc0YcIEvfPOOxnaTp48WcuXL9fEiRM1e/ZsFSpUSK1atcr0P663smXLFvn4+Ojhhx/Wli1btGXLFpsrYezl4+Ojpk2b6vDhwzp+/HiW7bp3767Fixdr+PDhWrlypT799FM1bdpUp0+flnTtFqKGDRsqLCzMGteN+zdp0iStXbtW48aN0/fff69KlSrdNLZHHnlE5cqV04IFCzRy5EgtXrxYLVq0sHuuldatW1uvKvjwww+tsWV166ExRh06dNC4cePUvXt3LV26VAMGDNDMmTP10EMP2RQkJemXX37RwIED1b9/fy1ZskTVq1dXz549tXHjxmzFV79+fQ0aNEjvv/++2rVrp6JFi+qDDz7Isv3Vq1czXbJr3bp1KlasmEJCQiRJJ06c0L59+9S8efMsryKoX7++QkJCtGrVKuu69Pnc7Ll1rGvXrqpdu7Zee+21m/4eDxw4oAYNGmjfvn2aNGmSFi5cqCpVqqhHjx4aO3ZshvZDhw7V0aNHNXXqVH377bfWfbty5Yo6duyo1q1ba8mSJWrVqpWGDh2qV155RTExMXrmmWe0aNEiVaxYUT169NCOHTusfaYX80aMGKGlS5dq+vTpKlOmjBo3bmz3fFBdu3ZVWFiYPvzwQ5v1V69e1ccff6xHHnlEERERN+2jV69eGjdunJ566iktWbJEjz76qDp27KizZ8/ecvyHH35YO3bs0NixY7Vq1SpNmTJF99xzj/U/24sWLVKZMmV0zz33WL8fN94am9UxzsyVK1f08MMPq0mTJlq8eLF69+6tjz/+WF27dr1lrDd69tln1adPH0nSwoULrfGl33o4evRoPf7446pSpYr++9//6osvvtD58+d1//3328y1NmPGDD399NOqXLmyvv76a7322mt644037thtqY8++qimTJmizp07a+nSpfr000+tv/M+ffqoXbt2N31/+tWot1rS0tKs79m7d68kKSoqyqav8PBwBQcHW7enu53vi73f2ev9/fffKlq0qN5++20tX75cH374odzd3VW3bl0dOHAgQ3t7PouSfX+DO3bsqHLlymn+/PmaOnWq3X8Pdu3apX79+ql///5atGiRGjRooL59+9o3J58BAAAAbmH69OlGktm+fbt1XUxMjJFk/vvf/9q0ffjhh03FihWtrw8fPmwkmYiICHPp0iXr+sTERBMUFGSaNm1q02fJkiUzjD9ixAhzY+pauHBhExMTk+19kGReeumlLLf/5z//MZLMtm3bbOKePn26tU2RIkVMv379bjpO69atM92H9P7Kli1rUlJSMt12/Vjp+9y/f3+btl9++aWRZGbPnm2zbyNGjMgwZsmSJW2O0fz5840ks27dugxtbzz2y5cvN5LM2LFjbdrNmzfPSDKffPKJzTje3t7mzz//tK67dOmSCQoKMs8//3yGsbJy6dIlExAQYCSZBQsWZNom/XN3s+VWn4tp06YZSeb999+3rtu6dauRZIYMGXLT99atW9f4+PhYX8+cOdO4ubmZmTNn3nL/oqOjTdWqVY0xxqxevdpIMh988IEx5v8+A++++661/WOPPWa8vLzM0aNHbfpp1aqV8fX1NefOnTPGGLNu3TojyTzwwAMZxkw/Xl9//bV13ZUrV0yxYsWMJLNz507r+tOnTxs3NzczYMCALPfh6tWr5sqVK6ZJkybmkUcesdl24+cwPa7rP28jRowwnp6e5uTJk9Z16Z+pDRs2ZDmuMcbExsbe9Dtx/e/9xrHj4+ONJDNx4sSbjlG1alUTHR2dYf3NjnFm+5l+3K//jBljzFtvvWUkmU2bNhljMv/up7vxeL777rtGkjl8+LBNu6NHjxp3d3fTp08fm/Xnz583YWFhpkuXLsYYY1JTU01ERISpVauWSUtLs7Y7cuSI8fDwyPTfLXv9888/Wf57tG3bNiMpw7+hO3bsMJLMW2+9dcv+S5Ysecvv/43j9+rVy3h5eWXaX4UKFUzz5s2tr2/3+5Ld7+zNfu/prl69alJSUkz58uVtPvM3+yxmxp6/wel/d4YPH27Th71/DywWi9m1a5dN22bNmhl/f39z8eLFbMXNlVUAAADIMYvForZt29qsq169uv78888MbTt27Chvb2/raz8/P7Vt21YbN25Uamqq02O9FWPMLdvUqVNHM2bM0JtvvqmtW7fm6ElS7dq1k4eHR7bbP/HEEzavu3TpInd3d61bt87use2RfqXFjbfldO7cWYULF85w+0jNmjVVokQJ62tvb29VqFAh089CVqZPn66EhAQVKlTI5uqlG/n4+Gj79u2ZLj4+Pjcd4/vvv9dLL72kTp06Wa9UsYcxxuaWp6eeekpXr17VU089ZVc/TZo0UfPmzTVq1CidP38+0zZr165VkyZNFBkZabO+R48eSkpKynBFxKOPPpppPxaLRQ8//LD1tbu7u8qVK6fw8HDdc8891vVBQUEKCQnJ8DubOnWqatWqJW9vb7m7u8vDw0Nr1qxRbGysXfssyTon3LRp06zrJk+erKioKD3wwAOSrk2uf/1VMun/PqR/5rP6TtxMUFCQypYtq3fffVfjx4/Xzz//bHP1TXZldYyzcmOs3bp1kySHfn9XrFhh/Qxef9y8vb0VHR1tvQLuwIED+vvvv9WtWzebz3DJkiXVoEEDh8WTlfSnrj755JM262vVqqUqVapYb6e+mW+//TbL7/71y3PPPWfzvpvdpnjjttv5vtj7nb3e1atXNXr0aFWpUkWenp5yd3eXp6enfvvtt0y/a/Z+Fu35G3xj3/b+Pahatapq1Khhs65bt25KTEzUzp07sxUvxSoAAADkmK+vr03yK12bmPzy5csZ2oaFhWW6LiUlRRcuXHBajNmV/h+Om92GNG/ePMXExOjTTz9V/fr1FRQUpKeeekpxcXHZHic8PNyuuG48bu7u7ipatKj11kNnOX36tNzd3TNMbm6xWBQWFpZh/KJFi2bow8vLS5cuXcrWeH/88Yf+/e9/65FHHtGwYcP08ccfZ/mf10KFCunee+/NdClUKOv/4qxYsUIdO3ZUs2bN9OWXX9r8JzW90Hb48OGbxvnnn39m+I9oTr3zzjuKj4/P8taY06dPZ/p5Sf+M3vg7yOqzldn31NPTU0FBQRnaenp62nx/x48frxdffFF169bV119/ra1bt2r79u1q2bJltn+31wsNDVXXrl318ccfKzU1Vbt379YPP/yg3r17W9s888wz8vDwsC5NmjSx2d+svhM3Y7FYtGbNGrVo0UJjx45VrVq1VKxYMb388stZFgszY8/3N7O40mN35Pf35MmTkqT77rvP5rh5eHho3rx5io+Ptxkzq3+LnS39OGc2Vnh4uP76669b9lGlShXVrFnzlsv1YxQtWlSXL1+2mSss3ZkzZzJ8D27n+2Lvd/Z6AwYM0LBhw9ShQwd9++232rZtm7Zv364aNWpk+l273b8l6esy+xt8Y9/2/j242Wcsu5/9gvloCAAAANxxmRV04uLi5OnpqSJFiki6djXOjXNfSLL+Z8tZLl26pNWrV6ts2bK6++67s2wXHBysiRMnauLEiTp69Ki++eYbDRkyRKdOndLy5cuzNZa9T3+Li4tT8eLFra+vXr2q06dP2/wn2MvLK9Pjdjv/IS5atKiuXr2qf/75x+Y/KMYYxcXF6b777stx3zcyxujpp5+Wj4+Ppk6dqsDAQC1evFjPPvus9uzZIz8/v9seY8WKFerQoYOio6P19ddfy9PT02Z7eHi4qlatqpUrV2b59KstW7bo5MmT1onqb1fNmjX1+OOPa/z48TZXcqQrWrSoTpw4kWF9+iTkwcHBNuud8WTB2bNnq3HjxpoyZYrNensKPDfq27evvvjiCy1ZskTLly/XXXfdZXMF0siRI22KV+m///TPfFbfiVspWbKkPvvsM0nSwYMH9d///lcjR45USkqKpk6dmq3Y7TnGmX1X0/8dTF+XXhS58ftrz3c3/XOwYMEClSxZMst21x+/G9lTcM+p9DmV/vrrL5vfnyQdP378lgVH6dpTS7NzteaIESOsk9Onz1W1Z88e1a1b19omLi5O8fHxqlatWnZ34Zbs/c5eb/bs2Xrqqaescwumi4+P11133ZWhfU7+lmS27vq/wVn1be/fg5t9xrLze5a4sgoAAAB3yMKFC23OQJ8/f17ffvut7r//frm5uUm69hShU6dOWa8UkKSUlBStWLEiQ3/2XLVzM6mpqerdu7dOnz6t//znP9l+X4kSJdS7d281a9bM5rYGR8WV7ssvv7R5/d///ldXr161efphqVKltHv3bpt2a9euzXC23MvLS5KyFV/61SyzZ8+2Wf/111/r4sWL1u2O8P7772vjxo2aMmWKQkJC5OHhoRkzZujvv/+2PgHtdqxcuVIdOnRQo0aNtHjxYutxuNGrr76qs2fPatCgQRm2Xbx4US+//LJ8fX3Vv3//244p3ZtvvqmUlBS9/vrrGbY1adJEa9euzfCEvFmzZsnX11f16tVzWBxZsVgsGY7X7t27c/RghHS1a9dWgwYN9M477+jLL79Ujx49VLhwYev2UqVK2VwtV7FiRUmyfuaz+k7Yo0KFCnrttdcUFRV1R7+/c+bMkfR/+xIaGipvb+8M398lS5Zk6Cur72+LFi3k7u6uQ4cOZXnFoSRVrFhR4eHh+uqrr2xue/7zzz+1efPm29vRbGjatKkKFSqU4emD27Zt04EDB9S0adNb9pGT2wBbtmwpb2/vDA9BSH84QocOHRyxe5Ju7zub2Xdt6dKl2briLDuy8zc4K/b+Pdi3b59++eUXm3Vz5syRn5+f9aEAt8KVVQAAALgj3Nzc1KxZMw0YMEBpaWl65513lJiYaPOf9K5du2r48OF67LHH9O9//1uXL1/WpEmTMp3TKioqSuvXr9e3336r8PBw+fn5Wf9Tm5WTJ09q69atMsbo/Pnz2rt3r2bNmqVffvlF/fv3V69evbJ8b0JCgh588EF169ZNlSpVkp+fn7Zv367ly5erY8eONnEtXLhQU6ZMUe3ata23rOXUwoUL5e7urmbNmmnfvn0aNmyYatSooS5duljbdO/eXcOGDdPw4cMVHR2t/fv3a/LkyQoICLDpK/0Kgk8++UR+fn7y9vZW6dKlMz3T3axZM7Vo0UL/+c9/lJiYqIYNG2r37t0aMWKE7rnnHnXv3j3H+3S9gwcP6pVXXtFjjz2mTp06WdfXrFlTr7zyil5//XV16tQpW/+RzcymTZvUoUMHhYWF6ZVXXtGuXbtstlepUkX+/v6SpMcff1w7d+7UuHHjdOTIET3zzDMKDQ3VgQMHNGHCBB06dEhz5sxRmTJlrO+fNWuWnnnmGX3++ed2z1slSaVLl9aLL76o999/P8O2ESNG6LvvvtODDz6o4cOHKygoSF9++aWWLl2qsWPHZvj9OkObNm30xhtvaMSIEYqOjtaBAwc0atQolS5d2u4C0fX69u2rrl27ymKx6F//+le23lO5cmU9+eSTmjhxojw8PNS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",
      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MC_Av_rhoonly, MC_All_rhoonly, fig=pf.propagate_FI_uncertainty(T_K=df['T_C']+273.15,\n",
    "error_CO2_dens=10, error_type_CO2_dens='Perc', error_dist_CO2_dens='normal',\n",
    "                        CO2_dens_gcm3=df['Density_g_cm3'],\n",
    "                        sample_ID=df['Sample'],\n",
    "                        crust_dens_kgm3=2700,\n",
    "                        N_dup=1000, fig_i=0, plot_figure=True)\n",
    "MC_Av_rhoonly.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4d82c7d-3045-4270-bd29-9092a35ee75c",
   "metadata": {},
   "source": [
    "## Simulation varying both temperature and CO$_2$ density\n",
    "- Lets say you think you have +-30K uncertainty in temp, and +-0.02 g/cm3 in density"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6d28a559-37b2-46e1-a7f4-5a55a0227ba9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are not using multiprocessing based on your selected EOS. You can override this by setting multiprocess=True in the function, but for SP94 and SW96 it might actually be slower\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing: 100%|██████████| 60/60 [00:01<00:00, 35.79it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>CO2_dens_gcm3</th>\n",
       "      <th>SingleCalc_D_km</th>\n",
       "      <th>SingleCalc_P_kbar</th>\n",
       "      <th>Mean_MC_P_kbar</th>\n",
       "      <th>Med_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar_from_percentile</th>\n",
       "      <th>Mean_MC_D_km</th>\n",
       "      <th>Med_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km_from_percentile</th>\n",
       "      <th>T_K_input</th>\n",
       "      <th>error_T_K</th>\n",
       "      <th>CO2_dens_gcm3_input</th>\n",
       "      <th>error_CO2_dens_gcm3</th>\n",
       "      <th>crust_dens_kgm3_input</th>\n",
       "      <th>error_crust_dens_kgm3</th>\n",
       "      <th>model</th>\n",
       "      <th>EOS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>6.357853</td>\n",
       "      <td>1.684004</td>\n",
       "      <td>1.688554</td>\n",
       "      <td>1.686840</td>\n",
       "      <td>0.119360</td>\n",
       "      <td>0.116826</td>\n",
       "      <td>6.375029</td>\n",
       "      <td>6.368558</td>\n",
       "      <td>0.450637</td>\n",
       "      <td>0.441071</td>\n",
       "      <td>1322.048738</td>\n",
       "      <td>30</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>6.918818</td>\n",
       "      <td>1.832587</td>\n",
       "      <td>1.829419</td>\n",
       "      <td>1.823433</td>\n",
       "      <td>0.126059</td>\n",
       "      <td>0.125995</td>\n",
       "      <td>6.906858</td>\n",
       "      <td>6.884256</td>\n",
       "      <td>0.475929</td>\n",
       "      <td>0.475686</td>\n",
       "      <td>1289.074767</td>\n",
       "      <td>30</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>6.891995</td>\n",
       "      <td>1.825483</td>\n",
       "      <td>1.821729</td>\n",
       "      <td>1.820861</td>\n",
       "      <td>0.131336</td>\n",
       "      <td>0.131174</td>\n",
       "      <td>6.877825</td>\n",
       "      <td>6.874546</td>\n",
       "      <td>0.495852</td>\n",
       "      <td>0.495238</td>\n",
       "      <td>1314.739916</td>\n",
       "      <td>30</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>7.071963</td>\n",
       "      <td>1.873151</td>\n",
       "      <td>1.874064</td>\n",
       "      <td>1.866136</td>\n",
       "      <td>0.125095</td>\n",
       "      <td>0.124611</td>\n",
       "      <td>7.075411</td>\n",
       "      <td>7.045478</td>\n",
       "      <td>0.472290</td>\n",
       "      <td>0.470461</td>\n",
       "      <td>1308.085183</td>\n",
       "      <td>30</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>6.670854</td>\n",
       "      <td>1.766909</td>\n",
       "      <td>1.770078</td>\n",
       "      <td>1.767223</td>\n",
       "      <td>0.125171</td>\n",
       "      <td>0.121619</td>\n",
       "      <td>6.682818</td>\n",
       "      <td>6.672038</td>\n",
       "      <td>0.472575</td>\n",
       "      <td>0.459166</td>\n",
       "      <td>1307.970102</td>\n",
       "      <td>30</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Filename  CO2_dens_gcm3  SingleCalc_D_km  SingleCalc_P_kbar  Mean_MC_P_kbar  \\\n",
       "0      FI1       0.458055         6.357853           1.684004        1.688554   \n",
       "1      FI2       0.492947         6.918818           1.832587        1.829419   \n",
       "2      FI4       0.484594         6.891995           1.825483        1.821729   \n",
       "3      FI5       0.494431         7.071963           1.873151        1.874064   \n",
       "4      FI7       0.476416         6.670854           1.766909        1.770078   \n",
       "\n",
       "   Med_MC_P_kbar  std_dev_MC_P_kbar  std_dev_MC_P_kbar_from_percentile  \\\n",
       "0       1.686840           0.119360                           0.116826   \n",
       "1       1.823433           0.126059                           0.125995   \n",
       "2       1.820861           0.131336                           0.131174   \n",
       "3       1.866136           0.125095                           0.124611   \n",
       "4       1.767223           0.125171                           0.121619   \n",
       "\n",
       "   Mean_MC_D_km  Med_MC_D_km  std_dev_MC_D_km  \\\n",
       "0      6.375029     6.368558         0.450637   \n",
       "1      6.906858     6.884256         0.475929   \n",
       "2      6.877825     6.874546         0.495852   \n",
       "3      7.075411     7.045478         0.472290   \n",
       "4      6.682818     6.672038         0.472575   \n",
       "\n",
       "   std_dev_MC_D_km_from_percentile    T_K_input  error_T_K  \\\n",
       "0                         0.441071  1322.048738         30   \n",
       "1                         0.475686  1289.074767         30   \n",
       "2                         0.495238  1314.739916         30   \n",
       "3                         0.470461  1308.085183         30   \n",
       "4                         0.459166  1307.970102         30   \n",
       "\n",
       "   CO2_dens_gcm3_input  error_CO2_dens_gcm3  crust_dens_kgm3_input  \\\n",
       "0             0.458055                 0.02                   2700   \n",
       "1             0.492947                 0.02                   2700   \n",
       "2             0.484594                 0.02                   2700   \n",
       "3             0.494431                 0.02                   2700   \n",
       "4             0.476416                 0.02                   2700   \n",
       "\n",
       "   error_crust_dens_kgm3 model   EOS  \n",
       "0                    0.0  None  SW96  \n",
       "1                    0.0  None  SW96  \n",
       "2                    0.0  None  SW96  \n",
       "3                    0.0  None  SW96  \n",
       "4                    0.0  None  SW96  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MC_Av_rho_T, MC_All_rho_T, fig=pf.propagate_FI_uncertainty(\n",
    "T_K=df['T_C']+273.15,\n",
    "error_CO2_dens=0.02, error_type_CO2_dens='Abs', error_dist_CO2_dens='normal',\n",
    "error_T_K=30, error_type_T_K='Abs', error_dist_T_K='normal',\n",
    "CO2_dens_gcm3=df['Density_g_cm3'],\n",
    "sample_ID=df['Sample'],\n",
    "crust_dens_kgm3=2700,\n",
    "N_dup=1000, fig_i=0, plot_figure=True)\n",
    "MC_Av_rho_T.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d50a0cf9-ef85-4311-8a26-ac226770f1df",
   "metadata": {},
   "source": [
    "## Uncertainty in Temp, CO2 and Crustal density\n",
    "- Here we also add a 5% uncertainty in crustal density."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6c4ce815-29ea-4a95-8a49-ec8134037d7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We are not using multiprocessing based on your selected EOS. You can override this by setting multiprocess=True in the function, but for SP94 and SW96 it might actually be slower\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing: 100%|██████████| 60/60 [00:01<00:00, 37.12it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MC_Av_rho_T_CD, MC_All_rho_T_CD, fig=pf.propagate_FI_uncertainty(T_K=df['T_C']+273.15,\n",
    "error_CO2_dens=0.02, error_type_CO2_dens='Abs', error_dist_CO2_dens='normal',\n",
    "error_T_K=30, error_type_T_K='Abs', error_dist_T_K='normal',\n",
    "crust_dens_kgm3=2700,\n",
    "error_crust_dens=5, error_type_crust_dens='Perc', error_dist_crust_dens='normal',                                            \n",
    "CO2_dens_gcm3=df['Density_g_cm3'],\n",
    "sample_ID=df['Sample'],\n",
    "N_dup=1000, fig_i=0, plot_figure=True )\n",
    "\n",
    "\n",
    "fig.savefig('MonteCarlo_Sample1_png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7d54aa97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>CO2_dens_gcm3</th>\n",
       "      <th>SingleCalc_D_km</th>\n",
       "      <th>SingleCalc_P_kbar</th>\n",
       "      <th>Mean_MC_P_kbar</th>\n",
       "      <th>Med_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar_from_percentile</th>\n",
       "      <th>Mean_MC_D_km</th>\n",
       "      <th>Med_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km</th>\n",
       "      <th>std_dev_MC_D_km_from_percentile</th>\n",
       "      <th>T_K_input</th>\n",
       "      <th>error_T_K</th>\n",
       "      <th>CO2_dens_gcm3_input</th>\n",
       "      <th>error_CO2_dens_gcm3</th>\n",
       "      <th>crust_dens_kgm3_input</th>\n",
       "      <th>error_crust_dens_kgm3</th>\n",
       "      <th>model</th>\n",
       "      <th>EOS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>6.357853</td>\n",
       "      <td>1.684004</td>\n",
       "      <td>1.690564</td>\n",
       "      <td>1.686960</td>\n",
       "      <td>0.125152</td>\n",
       "      <td>0.121030</td>\n",
       "      <td>6.397435</td>\n",
       "      <td>6.360036</td>\n",
       "      <td>0.584467</td>\n",
       "      <td>0.557955</td>\n",
       "      <td>1322.048738</td>\n",
       "      <td>30</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>6.918818</td>\n",
       "      <td>1.832587</td>\n",
       "      <td>1.837438</td>\n",
       "      <td>1.838429</td>\n",
       "      <td>0.134013</td>\n",
       "      <td>0.133324</td>\n",
       "      <td>6.950017</td>\n",
       "      <td>6.934502</td>\n",
       "      <td>0.612384</td>\n",
       "      <td>0.599707</td>\n",
       "      <td>1289.074767</td>\n",
       "      <td>30</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>6.891995</td>\n",
       "      <td>1.825483</td>\n",
       "      <td>1.820464</td>\n",
       "      <td>1.817220</td>\n",
       "      <td>0.127858</td>\n",
       "      <td>0.130603</td>\n",
       "      <td>6.888725</td>\n",
       "      <td>6.887654</td>\n",
       "      <td>0.595282</td>\n",
       "      <td>0.597282</td>\n",
       "      <td>1314.739916</td>\n",
       "      <td>30</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>7.071963</td>\n",
       "      <td>1.873151</td>\n",
       "      <td>1.878002</td>\n",
       "      <td>1.873677</td>\n",
       "      <td>0.135345</td>\n",
       "      <td>0.129115</td>\n",
       "      <td>7.084029</td>\n",
       "      <td>7.066155</td>\n",
       "      <td>0.622443</td>\n",
       "      <td>0.602472</td>\n",
       "      <td>1308.085183</td>\n",
       "      <td>30</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>6.670854</td>\n",
       "      <td>1.766909</td>\n",
       "      <td>1.766453</td>\n",
       "      <td>1.764747</td>\n",
       "      <td>0.126029</td>\n",
       "      <td>0.122503</td>\n",
       "      <td>6.685152</td>\n",
       "      <td>6.686630</td>\n",
       "      <td>0.579506</td>\n",
       "      <td>0.572458</td>\n",
       "      <td>1307.970102</td>\n",
       "      <td>30</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>SW96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Filename  CO2_dens_gcm3  SingleCalc_D_km  SingleCalc_P_kbar  Mean_MC_P_kbar  \\\n",
       "0      FI1       0.458055         6.357853           1.684004        1.690564   \n",
       "1      FI2       0.492947         6.918818           1.832587        1.837438   \n",
       "2      FI4       0.484594         6.891995           1.825483        1.820464   \n",
       "3      FI5       0.494431         7.071963           1.873151        1.878002   \n",
       "4      FI7       0.476416         6.670854           1.766909        1.766453   \n",
       "\n",
       "   Med_MC_P_kbar  std_dev_MC_P_kbar  std_dev_MC_P_kbar_from_percentile  \\\n",
       "0       1.686960           0.125152                           0.121030   \n",
       "1       1.838429           0.134013                           0.133324   \n",
       "2       1.817220           0.127858                           0.130603   \n",
       "3       1.873677           0.135345                           0.129115   \n",
       "4       1.764747           0.126029                           0.122503   \n",
       "\n",
       "   Mean_MC_D_km  Med_MC_D_km  std_dev_MC_D_km  \\\n",
       "0      6.397435     6.360036         0.584467   \n",
       "1      6.950017     6.934502         0.612384   \n",
       "2      6.888725     6.887654         0.595282   \n",
       "3      7.084029     7.066155         0.622443   \n",
       "4      6.685152     6.686630         0.579506   \n",
       "\n",
       "   std_dev_MC_D_km_from_percentile    T_K_input  error_T_K  \\\n",
       "0                         0.557955  1322.048738         30   \n",
       "1                         0.599707  1289.074767         30   \n",
       "2                         0.597282  1314.739916         30   \n",
       "3                         0.602472  1308.085183         30   \n",
       "4                         0.572458  1307.970102         30   \n",
       "\n",
       "   CO2_dens_gcm3_input  error_CO2_dens_gcm3  crust_dens_kgm3_input  \\\n",
       "0             0.458055                 0.02                   2700   \n",
       "1             0.492947                 0.02                   2700   \n",
       "2             0.484594                 0.02                   2700   \n",
       "3             0.494431                 0.02                   2700   \n",
       "4             0.476416                 0.02                   2700   \n",
       "\n",
       "   error_crust_dens_kgm3 model   EOS  \n",
       "0                    5.0  None  SW96  \n",
       "1                    5.0  None  SW96  \n",
       "2                    5.0  None  SW96  \n",
       "3                    5.0  None  SW96  \n",
       "4                    5.0  None  SW96  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MC_Av_rho_T_CD.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b255cdcb",
   "metadata": {},
   "source": [
    "## Uncertainty in Temp, CO2 density, crustal density and XH2O\n",
    "- If XH2O is not None, the function will use the EOS of Duan and Zhang (2006) to propagate this additional source of uncertainty. Note, these calculations are an order of magnitude slower, so it may take several minutes to run. We are using multiprocessing to speed it up. \n",
    "- Here we consider XH2O=0.1, with a uniformly distributed error of +-0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "92840374-b595-46d9-910c-68419b9e761a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You have entered a value for XH2O, so we are now using the EOS of Duan and Zhang 200 regardless of what model you selected. If you dont want this, specify XH2O=None\n",
      "Please note, the DZ2006 EOS is about 5-40X slower to run than the SP94 and SW94 EOS\n",
      "We are using multiprocessing based on your selected EOS. You can override this by setting multiprocess=False in the function, but it might slow it down a lot\n",
      "Number of processors:  8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\penny\\box\\berkeley_new\\diadfit_outer\\src\\DiadFit\\error_propagation.py:747: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value 'DZ06' has dtype incompatible with float64, please explicitly cast to a compatible dtype first.\n",
      "  df_step.at[i, key] = value\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Filename</th>\n",
       "      <th>i</th>\n",
       "      <th>CO2_density_input</th>\n",
       "      <th>SingleCalc_D_km</th>\n",
       "      <th>SingleCalc_P_kbar</th>\n",
       "      <th>Mean_MC_P_kbar</th>\n",
       "      <th>Med_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar</th>\n",
       "      <th>std_dev_MC_P_kbar_from_percentile</th>\n",
       "      <th>Mean_MC_D_km</th>\n",
       "      <th>...</th>\n",
       "      <th>T_K_input</th>\n",
       "      <th>error_T_K</th>\n",
       "      <th>CO2_dens_gcm3_input</th>\n",
       "      <th>error_CO2_dens_gcm3</th>\n",
       "      <th>crust_dens_kgm3_input</th>\n",
       "      <th>error_crust_dens_kgm3</th>\n",
       "      <th>model</th>\n",
       "      <th>EOS</th>\n",
       "      <th>XH2O_input</th>\n",
       "      <th>error_XH2O</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FI1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>7.291610</td>\n",
       "      <td>1.931329</td>\n",
       "      <td>1.946028</td>\n",
       "      <td>1.935574</td>\n",
       "      <td>0.192155</td>\n",
       "      <td>0.182582</td>\n",
       "      <td>7.374642</td>\n",
       "      <td>...</td>\n",
       "      <td>1322.048738</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.458055</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DZ06</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FI2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>7.905409</td>\n",
       "      <td>2.093906</td>\n",
       "      <td>2.121787</td>\n",
       "      <td>2.098956</td>\n",
       "      <td>0.212000</td>\n",
       "      <td>0.205083</td>\n",
       "      <td>8.040700</td>\n",
       "      <td>...</td>\n",
       "      <td>1289.074767</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.492947</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DZ06</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FI4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>7.869712</td>\n",
       "      <td>2.084451</td>\n",
       "      <td>2.112670</td>\n",
       "      <td>2.089794</td>\n",
       "      <td>0.210073</td>\n",
       "      <td>0.202420</td>\n",
       "      <td>8.006136</td>\n",
       "      <td>...</td>\n",
       "      <td>1314.739916</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.484594</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DZ06</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FI5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>8.089363</td>\n",
       "      <td>2.142630</td>\n",
       "      <td>2.170117</td>\n",
       "      <td>2.148561</td>\n",
       "      <td>0.216681</td>\n",
       "      <td>0.209704</td>\n",
       "      <td>8.223869</td>\n",
       "      <td>...</td>\n",
       "      <td>1308.085183</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.494431</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DZ06</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FI7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>7.601455</td>\n",
       "      <td>2.013397</td>\n",
       "      <td>2.043449</td>\n",
       "      <td>2.019502</td>\n",
       "      <td>0.202435</td>\n",
       "      <td>0.195015</td>\n",
       "      <td>7.743774</td>\n",
       "      <td>...</td>\n",
       "      <td>1307.970102</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.476416</td>\n",
       "      <td>0.02</td>\n",
       "      <td>2700.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DZ06</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Filename    i  CO2_density_input  SingleCalc_D_km  SingleCalc_P_kbar  \\\n",
       "0      FI1  0.0           0.458055         7.291610           1.931329   \n",
       "1      FI2  1.0           0.492947         7.905409           2.093906   \n",
       "2      FI4  2.0           0.484594         7.869712           2.084451   \n",
       "3      FI5  3.0           0.494431         8.089363           2.142630   \n",
       "4      FI7  4.0           0.476416         7.601455           2.013397   \n",
       "\n",
       "   Mean_MC_P_kbar  Med_MC_P_kbar  std_dev_MC_P_kbar  \\\n",
       "0        1.946028       1.935574           0.192155   \n",
       "1        2.121787       2.098956           0.212000   \n",
       "2        2.112670       2.089794           0.210073   \n",
       "3        2.170117       2.148561           0.216681   \n",
       "4        2.043449       2.019502           0.202435   \n",
       "\n",
       "   std_dev_MC_P_kbar_from_percentile  Mean_MC_D_km  ...    T_K_input  \\\n",
       "0                           0.182582      7.374642  ...  1322.048738   \n",
       "1                           0.205083      8.040700  ...  1289.074767   \n",
       "2                           0.202420      8.006136  ...  1314.739916   \n",
       "3                           0.209704      8.223869  ...  1308.085183   \n",
       "4                           0.195015      7.743774  ...  1307.970102   \n",
       "\n",
       "   error_T_K  CO2_dens_gcm3_input  error_CO2_dens_gcm3  crust_dens_kgm3_input  \\\n",
       "0       30.0             0.458055                 0.02                 2700.0   \n",
       "1       30.0             0.492947                 0.02                 2700.0   \n",
       "2       30.0             0.484594                 0.02                 2700.0   \n",
       "3       30.0             0.494431                 0.02                 2700.0   \n",
       "4       30.0             0.476416                 0.02                 2700.0   \n",
       "\n",
       "   error_crust_dens_kgm3  model   EOS  XH2O_input  error_XH2O  \n",
       "0                    5.0    NaN  DZ06         0.1        0.05  \n",
       "1                    5.0    NaN  DZ06         0.1        0.05  \n",
       "2                    5.0    NaN  DZ06         0.1        0.05  \n",
       "3                    5.0    NaN  DZ06         0.1        0.05  \n",
       "4                    5.0    NaN  DZ06         0.1        0.05  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x800 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "MC_Av_rho_T_CDH, MC_All_rho_T_CDH, fig=pf.propagate_FI_uncertainty(T_K=df['T_C']+273.15,\n",
    "error_CO2_dens=0.02, error_type_CO2_dens='Abs', error_dist_CO2_dens='normal',\n",
    "error_T_K=30, error_type_T_K='Abs', error_dist_T_K='normal',\n",
    "crust_dens_kgm3=2700,\n",
    "error_crust_dens=5, error_type_crust_dens='Perc', error_dist_crust_dens='normal',                                            \n",
    "CO2_dens_gcm3=df['Density_g_cm3'],\n",
    "XH2O=0.1, error_XH2O=0.05, error_type_XH2O='Abs', error_dist_XH2O='normal',  \n",
    "sample_ID=df['Sample'],\n",
    "N_dup=1000, fig_i=0, plot_figure=True )\n",
    "MC_Av_rho_T_CDH.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "16bace83",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig('MC for paper.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2b4cbd1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}