{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4c. Calculate pure solubility of CO<sub>2</sub> and H<sub>2</sub>O\n",
    "\n",
    "This allows you to calculate the pure solubility for H<sub>2</sub>O and CO<sub>2</sub> for a given melt composition."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python set-up\n",
    "You need to install VolFe once on your machine, if you haven't yet. Then we need to import a few Python packages (including VolFe). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install VolFe on your machine. Don't remove the # from this line!\n",
    "# pip install VolFe # Remove the first # in this line if you have not installed VolFe on your machine before.\n",
    "\n",
    "# import python packages\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import VolFe as vf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the inputs\n",
    "\n",
    "This composition is from Brounce et al. (2014) with the updated Fe<sup>3+</sup>/Fe<sub>T</sub> from Cottrell et al. (2021)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the melt composition, fO2 estimate, and T as a dictionary.\n",
    "my_analysis = {'Sample':'Sari15-04-33',\n",
    "           'T_C': 1200., # Temperature in 'C\n",
    "           'SiO2': 47.89, # wt%\n",
    "           'TiO2': 0.75, # wt%\n",
    "           'Al2O3': 16.74, # wt%\n",
    "           'FeOT': 9.43, # wt%\n",
    "           'MnO': 0.18, # wt%\n",
    "           'MgO': 5.92, # wt%\n",
    "           'CaO': 11.58, # wt%\n",
    "           'Na2O': 2.14, # wt%\n",
    "           'K2O': 0.63, # wt%\n",
    "           'P2O5': 0.17, # wt%\n",
    "           'Fe3FeT': 0.177,\n",
    "           'initial_P': 5000.} # bar\n",
    "\n",
    "# Turn the dictionary into a pandas dataframe, setting the index to 0.\n",
    "my_analysis = pd.DataFrame(my_analysis, index=[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll use the default options"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            option\n",
      "type                              \n",
      "COH_species     yes_H2_CO_CH4_melt\n",
      "H2S_m                         True\n",
      "species X                       Ar\n",
      "Hspeciation                   none\n",
      "fO2                       Kress91A\n",
      "...                            ...\n",
      "error                          0.1\n",
      "print status                 False\n",
      "output csv                    True\n",
      "setup                        False\n",
      "high precision               False\n",
      "\n",
      "[78 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "# print default options in VolFe\n",
    "print(vf.default_models)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the calculation\n",
    "\n",
    "And this runs the calculation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "pure_sol1 = vf.calc_pure_solubility(my_analysis)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change the solubility models\n",
    "\n",
    "And we can change the solubility models..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# choose the options I want - everything else will use the default options\n",
    "my_models = [['water','Rhyolite_HughesIP'],['carbon dioxide','Rhyolite_Blank93']]\n",
    "\n",
    "# turn to dataframe with correct column headers and indexes    \n",
    "my_models = vf.make_df_and_add_model_defaults(my_models)\n",
    "\n",
    "# run calculations\n",
    "pure_sol2 = vf.calc_pure_solubility(my_analysis,models=my_models)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting\n",
    "\n",
    "And we can plot them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000.0, 0.0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12,4))\n",
    "\n",
    "data1 = pure_sol1 # basalt\n",
    "data2 = pure_sol2 # rhyolite\n",
    "\n",
    "# Plotting results\n",
    "ax1.plot(data1['H2O_wtpc'], data1['P_bar'], '-k')\n",
    "ax1.plot(data2['H2O_wtpc'], data2['P_bar'], '--k')\n",
    "ax2.plot(data1['CO2_ppmw'], data1['P_bar'], '-k')\n",
    "ax2.plot(data2['CO2_ppmw'], data2['P_bar'], '--k')\n",
    "\n",
    "ax1.set_ylabel('P (bar)')\n",
    "ax1.set_xlabel('H2O (wt%)')\n",
    "ax2.set_xlabel('CO2 (ppmw)')\n",
    "ax1.set_ylim([5000,0])\n",
    "ax2.set_ylim([5000,0])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "volfe-dev",
   "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": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}