Fig8_MC_Neave-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d21affcd-2b70-4a8c-993d-7588ff26cce7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "from matplotlib import cm\n",
    "import warnings as w\n",
    "pd.options.display.max_columns = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b0d37c5d-1f9f-4434-9c94-1605b237a69a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Note \n",
      "----- in \n",
      "Plots spidergrams for trace elements data. Additional arguments are typically forwarded\n",
      "to respective :mod:`matplotlib` functions :func:`~matplotlib.pyplot.plot` and... in the docstring of spider in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\spider.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Method for plotting histograms (mode='hist2d'|'hexbin') or kernel density\n",
      "esitimates from point data. Convenience access function to... in the docstring of density in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Note \n",
      "----- in \n",
      "Creates diagramatic representation of data density and/or frequency for either\n",
      "binary diagrams (X-Y) or ternary plots.... in the docstring of density in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\density\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Create a :func:`pyrolite.plot.parallel.parallel`. coordinate plot from\n",
      "the columns of the :class:`~pandas.DataFrame`.... in the docstring of parallel in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Create a parallel coordinate plot across dataframe columns, with\n",
      "individual lines for each row.... in the docstring of parallel in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\parallel.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Todo \n",
      "------ in \n",
      "Create a parallel coordinate plot across dataframe columns, with\n",
      "individual lines for each row.... in the docstring of parallel in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\parallel.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "------------ in \n",
      "Pass the pandas object to :func:`pyrolite.plot.spider.REE_v_radii`.\n",
      "... in the docstring of REE in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Note \n",
      "----- in \n",
      "Creates an axis for a REE diagram with ionic radii along the x axis.\n",
      "... in the docstring of REE_v_radii in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\spider.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Convenience method for scatter plots using the pyroplot API. See\n",
      "further parameters for `matplotlib.pyplot.scatter` function below.... in the docstring of scatter in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Convenience method for line plots using the pyroplot API. See\n",
      "further parameters for `matplotlib.pyplot.scatter` function below.... in the docstring of plot in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Method for spider plots. Convenience access function to\n",
      ":func:`~pyrolite.plot.spider.spider` (see `Other Parameters`, below), where... in the docstring of spider in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Todo \n",
      "----- in \n",
      "Method for spider plots. Convenience access function to\n",
      ":func:`~pyrolite.plot.spider.spider` (see `Other Parameters`, below), where... in the docstring of spider in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Method for creating stem plots. Convenience access function to\n",
      ":func:`~pyrolite.plot.stem.stem` (see `Other Parameters`, below), where... in the docstring of stem in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Parameters \n",
      "----------- in \n",
      "Create a stem (or 'lollipop') plot, with optional orientation.\n",
      "... in the docstring of stem in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\stem.py.\n",
      "  warn(msg)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\numpydoc\\docscrape.py:449: UserWarning: potentially wrong underline length... \n",
      "Note \n",
      "----- in \n",
      "Convenience method for scatter plots using the pyroplot API. See\n",
      "further parameters for `matplotlib.pyplot.scatter` function below.... in the docstring of scatter in C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pyrolite\\plot\\__init__.py.\n",
      "  warn(msg)\n"
     ]
    }
   ],
   "source": [
    "## Uncomment once per computer\n",
    "#!pip install pyrolite\n",
    "#!pip install Thermobar\n",
    "#!pip install \"https://github.com/PennyWieser/Thermobar_onnx/archive/refs/tags/0.02.zip\"\n",
    "import Thermobar as pt\n",
    "import pyrolite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8c11c135-aa43-4738-84db-3ce286497234",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use(\"seaborn-colorblind\")\n",
    "plt.rcParams[\"font.family\"] = 'arial'\n",
    "plt.rcParams[\"font.size\"] =12\n",
    "plt.rcParams[\"mathtext.default\"] = \"regular\"\n",
    "plt.rcParams[\"mathtext.fontset\"] = \"dejavusans\"\n",
    "plt.rcParams['patch.linewidth'] = 1\n",
    "plt.rcParams['axes.linewidth'] = 1\n",
    "plt.rcParams[\"xtick.direction\"] = \"in\"\n",
    "plt.rcParams[\"ytick.direction\"] = \"in\"\n",
    "plt.rcParams[\"ytick.direction\"] = \"in\"\n",
    "plt.rcParams[\"xtick.major.size\"] = 6 # Sets length of ticks\n",
    "plt.rcParams[\"ytick.major.size\"] = 4 # Sets length of ticks\n",
    "plt.rcParams[\"ytick.labelsize\"] = 12 # Sets size of numbers on tick marks\n",
    "plt.rcParams[\"xtick.labelsize\"] = 12 # Sets size of numbers on tick marks\n",
    "plt.rcParams[\"axes.titlesize\"] = 14 # Overall title\n",
    "plt.rcParams[\"axes.labelsize\"] = 14 # Axes labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffed5c49-948b-44a6-b731-17bec2501a20",
   "metadata": {},
   "source": [
    "## Loading in Davids microprobe error data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "844e20f1-a85f-4e87-a1a5-d90d87a1ad1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Neave_18=pd.read_excel('Supporting_Data_3.xlsx', \n",
    "                       sheet_name='Neave19_20180718_Python')\n",
    "#Neave_19=pd.read_excel('Kraw_2013_Calibration_Errors.xlsx', sheet_name='083006_Analyses')\n",
    "\n",
    "Neave_sigma=pt.import_excel('Supporting_Data_3.xlsx', \n",
    "                            sheet_name='Neave19_20180718_Python', suffix=\"_Cpx\")\n",
    "Neave_sigma_in=Neave_sigma['my_input']\n",
    "Neave_sigma_Cpx=Neave_sigma['Cpxs']\n",
    "Neave_conv=pt.convert_oxide_percent_to_element_weight_percent(df=Neave_sigma_Cpx, suffix='_Cpx', without_oxygen=True)\n",
    "\n",
    "Pec_Err_Neave_Na=100*Neave_sigma_in['Na_sig']/Neave_conv['Na_wt_noO2']\n",
    "Pec_Err_Neave_Al=100*Neave_sigma_in['Al_sig']/Neave_conv['Al_wt_noO2']\n",
    "Pec_Err_Neave_Ti=100*Neave_sigma_in['Ti_sig']/Neave_conv['Ti_wt_noO2']\n",
    "Pec_Err_Neave_Ca=100*Neave_sigma_in['Ca_sig']/Neave_conv['Ca_wt_noO2']\n",
    "Pec_Err_Neave_Fe=100*Neave_sigma_in['Fe_sig']/Neave_conv['Fe_wt_noO2']\n",
    "Pec_Err_Neave_Mn=100*Neave_sigma_in['Mn_sig']/Neave_conv['Mn_wt_noO2']\n",
    "Pec_Err_Neave_Mg=100*Neave_sigma_in['Mg_sig']/Neave_conv['Mg_wt_noO2']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03576d17-6ce6-4466-8502-3aa4fb7e0b43",
   "metadata": {},
   "source": [
    "## Real compositions from Neave's experiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "943a58e7-fe4e-43d7-9952-e227481d1009",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    }
   ],
   "source": [
    "out_2nd_NExp=pt.import_excel('Supporting_Data_5.xlsx', \n",
    "                             sheet_name='Neave_Cpx', suffix=\"_Cpx\") \n",
    "Cpxs_2nd_NExp=out_2nd_NExp['Cpxs']\n",
    "input_2nd_NExp=out_2nd_NExp['my_input']\n",
    "cpx_comp_2nd_NExp=pt.calculate_clinopyroxene_components(cpx_comps=Cpxs_2nd_NExp)\n",
    "All_NExp=pt.calculate_cpx_only_press_all_eqs(cpx_comps=Cpxs_2nd_NExp)\n",
    "All_NExp['P_kbar_x']=input_2nd_NExp['Pressure(MPa)']/100\n",
    "All_NExp_9=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0188-9\"]\n",
    "All_NExp_2=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0201-2\"]\n",
    "All_NExp_8=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0187-8\"]\n",
    "All_NExp_4=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0183-4\"]\n",
    "All_NExp_1=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0167-1\"]\n",
    "All_NExp_10=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0184-10\"]\n",
    "All_NExp_Y2=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0205-2\"]\n",
    "All_NExp_Y3=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0200-3\"]\n",
    "All_NExp_Y1=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0272-1\"]\n",
    "All_NExp_Y7=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0287-1\"]\n",
    "All_NExp_043=All_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0204-3\"]\n",
    "\n",
    "Cpxs_Exp9=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0188-9\"]\n",
    "Cpxs_Exp2=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0201-2\"]\n",
    "Cpxs_Exp8=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0187-8\"]\n",
    "Cpxs_Exp4=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0183-4\"]\n",
    "Cpxs_Exp1=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0167-1\"]\n",
    "Cpxs_Exp10=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"B0184-10\"]\n",
    "Cpxs_ExpY2=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0205-2\"]\n",
    "Cpxs_ExpY3=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0200-3\"]\n",
    "Cpxs_ExpY1=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0272-1\"]\n",
    "Cpxs_ExpY27=Cpxs_2nd_NExp.loc[input_2nd_NExp['ExperimentID']==\"Y0272-2\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "451ff6a6-477d-4bd5-aad6-fb573922115c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading in the glass data, and getting it for ExpY1\n",
    "out_av_glass=pt.import_excel('Supporting_Data_5.xlsx', \n",
    "                             sheet_name='Neave_Liqs',\n",
    "                             suffix=\"_Liq\")\n",
    "av_all=out_av_glass['my_input']\n",
    "av_glass=out_av_glass['Liqs']\n",
    "# Doesnt exist\n",
    "Glass_ExpY1=av_glass.loc[av_all['Comment']==\"Y272-1_gl01\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9dc779c2-70a4-4acf-932b-0b515224882b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating the mean Cpx and std deviation for each experiment\n",
    "Cpxs_Exp9_Mean=Cpxs_Exp9.mean(axis=0).to_frame().T\n",
    "Cpxs_Exp9_Std=Cpxs_Exp9.std(axis=0).to_frame().T\n",
    "Prec_Exp9=100*Cpxs_Exp9_Std/Cpxs_Exp9_Mean\n",
    "\n",
    "Cpxs_Exp2_Mean=Cpxs_Exp2.mean(axis=0).to_frame().T\n",
    "Cpxs_Exp2_Std=Cpxs_Exp2.std(axis=0).to_frame().T\n",
    "Prec_Exp2=100*Cpxs_Exp2_Std/Cpxs_Exp2_Mean\n",
    "\n",
    "Cpxs_Exp8_Mean=Cpxs_Exp8.mean(axis=0).to_frame().T\n",
    "Cpxs_Exp8_Std=Cpxs_Exp8.std(axis=0).to_frame().T\n",
    "Prec_Exp8=100*Cpxs_Exp8_Std/Cpxs_Exp8_Mean\n",
    "\n",
    "Cpxs_Exp4_Mean=Cpxs_Exp4.mean(axis=0).to_frame().T\n",
    "Cpxs_Exp4_Std=Cpxs_Exp4.std(axis=0).to_frame().T\n",
    "Prec_Exp4=100*Cpxs_Exp4_Std/Cpxs_Exp4_Mean\n",
    "\n",
    "Cpxs_Exp1_Mean=Cpxs_Exp1.mean(axis=0).to_frame().T\n",
    "Cpxs_Exp1_Std=Cpxs_Exp1.std(axis=0).to_frame().T\n",
    "Prec_Exp1=100*Cpxs_Exp1_Std/Cpxs_Exp1_Mean\n",
    "\n",
    "Cpxs_Exp10_Mean=Cpxs_Exp10.mean(axis=0).to_frame().T\n",
    "Cpxs_Exp10_Std=Cpxs_Exp10.std(axis=0).to_frame().T\n",
    "Prec_Exp10=100*Cpxs_Exp10_Std/Cpxs_Exp10_Mean\n",
    "\n",
    "Cpxs_ExpY2_Mean=Cpxs_ExpY2.mean(axis=0).to_frame().T\n",
    "Cpxs_ExpY2_Std=Cpxs_ExpY2.std(axis=0).to_frame().T\n",
    "Prec_ExpY2=100*Cpxs_ExpY2_Std/Cpxs_ExpY2_Mean\n",
    "\n",
    "Cpxs_ExpY3_Mean=Cpxs_ExpY3.mean(axis=0).to_frame().T\n",
    "Cpxs_ExpY3_Std=Cpxs_ExpY3.std(axis=0).to_frame().T\n",
    "Prec_ExpY3=100*Cpxs_ExpY3_Std/Cpxs_ExpY3_Mean\n",
    "\n",
    "Cpxs_ExpY1_Mean=Cpxs_ExpY1.mean(axis=0).to_frame().T\n",
    "Cpxs_ExpY1_Std=Cpxs_ExpY1.std(axis=0).to_frame().T\n",
    "Prec_ExpY1=100*Cpxs_ExpY1_Std/Cpxs_ExpY1_Mean#\n",
    "\n",
    "Cpxs_ExpY27_Mean=Cpxs_ExpY27.mean(axis=0).to_frame().T\n",
    "Cpxs_ExpY27_Std=Cpxs_ExpY27.std(axis=0).to_frame().T\n",
    "Prec_ExpY27=100*Cpxs_ExpY27_Std/Cpxs_ExpY27_Mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f85f4d13-9230-4312-8485-5ae53dce1234",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compiling the # precision nad the mean content for different experiments\n",
    "Neave_Exp_Prec=pd.concat([Prec_Exp9, Prec_Exp2, Prec_Exp8, Prec_Exp4, Prec_Exp1, Prec_Exp10, Prec_ExpY2, Prec_ExpY3, Prec_ExpY1])\n",
    "Neave_Exp_Mean=pd.concat([Cpxs_Exp9_Mean, Cpxs_Exp2_Mean, Cpxs_Exp8_Mean, Cpxs_Exp4_Mean, Cpxs_Exp1_Mean,\n",
    "                          Cpxs_Exp10_Mean, Cpxs_ExpY2_Mean, Cpxs_ExpY3_Mean, Cpxs_ExpY1_Mean])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa690c8a-d594-49b7-af2b-f7734ee4b8fa",
   "metadata": {},
   "source": [
    "# Neave Monte Carlo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67dc543f-f499-4766-bc7a-20482bf56363",
   "metadata": {},
   "source": [
    "### Calculating Neave Cpx Errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "be6479f2-2d8b-4b09-ac10-843cfbd3bf8a",
   "metadata": {},
   "outputs": [
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       "      <th>SiO2_Cpx_Err</th>\n",
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       "      <th>Al2O3_Cpx_Err</th>\n",
       "      <th>FeOt_Cpx_Err</th>\n",
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      ],
      "text/plain": [
       "   SiO2_Cpx_Err  TiO2_Cpx_Err  Al2O3_Cpx_Err  FeOt_Cpx_Err  MnO_Cpx_Err  \\\n",
       "0      1.062405      4.571841       3.676167      2.303602    22.023084   \n",
       "\n",
       "   MgO_Cpx_Err  CaO_Cpx_Err  Na2O_Cpx_Err  Cr2O3_Cpx_Err  K2O_Cpx_Err  \n",
       "0      1.42239     2.028583     21.665442      96.375765            0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ExpY1_Cpx_Err"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "db69b8a7-1d48-4774-a102-048552e9e8c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "Neave_sigma_in_ExpY1=Neave_sigma_in.loc[Neave_sigma_in['Exp']==\"Y272-1\"]\n",
    "Neave_conv_ExpY1=Neave_conv.loc[Neave_sigma_in['Exp']==\"Y272-1\"]\n",
    "\n",
    "# Get the error for each element for one specific experiment\n",
    "Pec_Err_Neave_Na_ExpY1=100*Neave_sigma_in_ExpY1['Na_sig']/Neave_conv_ExpY1['Na_wt_noO2']\n",
    "Pec_Err_Neave_Si_ExpY1=100*Neave_sigma_in_ExpY1['Si_sig']/Neave_conv_ExpY1['Si_wt_noO2']\n",
    "Pec_Err_Neave_Cr_ExpY1=100*Neave_sigma_in_ExpY1['Cr_sig']/Neave_conv_ExpY1['Cr_wt_noO2']\n",
    "Pec_Err_Neave_Al_ExpY1=100*Neave_sigma_in_ExpY1['Al_sig']/Neave_conv_ExpY1['Al_wt_noO2']\n",
    "Pec_Err_Neave_Ti_ExpY1=100*Neave_sigma_in_ExpY1['Ti_sig']/Neave_conv_ExpY1['Ti_wt_noO2']\n",
    "Pec_Err_Neave_Ca_ExpY1=100*Neave_sigma_in_ExpY1['Ca_sig']/Neave_conv_ExpY1['Ca_wt_noO2']\n",
    "Pec_Err_Neave_Fe_ExpY1=100*Neave_sigma_in_ExpY1['Fe_sig']/Neave_conv_ExpY1['Fe_wt_noO2']\n",
    "Pec_Err_Neave_Mn_ExpY1=100*Neave_sigma_in_ExpY1['Mn_sig']/Neave_conv_ExpY1['Mn_wt_noO2']\n",
    "Pec_Err_Neave_Mg_ExpY1=100*Neave_sigma_in_ExpY1['Mg_sig']/Neave_conv_ExpY1['Mg_wt_noO2']\n",
    "\n",
    "Pec_Err_Neave_Cr_ExpY1.replace([np.inf, -np.inf], np.nan, inplace=True)\n",
    "\n",
    "ExpY1_Mean_Cpx=Cpxs_ExpY1.mean(axis=0).to_frame().T\n",
    "\n",
    "# Making a dataframe of the percentage errors for this one experiment (e.g. the average)\n",
    "ExpY1_Cpx_Err=pd.DataFrame(data={'SiO2_Cpx_Err': np.nanmean(Pec_Err_Neave_Si_ExpY1),\n",
    "                            'TiO2_Cpx_Err':np.nanmean(Pec_Err_Neave_Ti_ExpY1),\n",
    "                             'Al2O3_Cpx_Err':np.nanmean(Pec_Err_Neave_Al_ExpY1),\n",
    "                             'FeOt_Cpx_Err':np.nanmean(Pec_Err_Neave_Fe_ExpY1),\n",
    "                            'MnO_Cpx_Err':np.nanmean(Pec_Err_Neave_Mn_ExpY1),\n",
    "                            'MgO_Cpx_Err':np.nanmean(Pec_Err_Neave_Mg_ExpY1),\n",
    "                            'CaO_Cpx_Err':np.nanmean(Pec_Err_Neave_Ca_ExpY1),\n",
    "                            'Na2O_Cpx_Err':np.nanmean(Pec_Err_Neave_Na_ExpY1),\n",
    "                            'Cr2O3_Cpx_Err':np.nanmean(Pec_Err_Neave_Cr_ExpY1),\n",
    "                               'K2O_Cpx_Err': 0}, index=[0])\n",
    "\n",
    "## This bit actually makes the distributions of compositions, the previous bit was formatting\n",
    "\n",
    "# 5000 compositions, normally distributed, variation for all elements, for Cpx\n",
    "ExpY1_noise1=pt.add_noise_sample_1phase(phase_comp=ExpY1_Mean_Cpx, \n",
    "                                        phase_err=ExpY1_Cpx_Err,\n",
    "                                  phase_err_type=\"Perc\", duplicates=5000, \n",
    "                                  err_dist=\"normal\", positive=False)\n",
    "# 500 compositions, normally distributed, variation for all elements\n",
    "\n",
    "ExpY1_noise1_500=pt.add_noise_sample_1phase(phase_comp=ExpY1_Mean_Cpx, \n",
    "                                            phase_err=ExpY1_Cpx_Err,\n",
    "                         phase_err_type=\"Perc\", duplicates=500, \n",
    "                         err_dist=\"normal\", positive=False)\n",
    "# 500 compositions, normally distributed,just Na variation\n",
    "\n",
    "ExpY1_noise1_500_JustNa=pt.add_noise_sample_1phase(phase_comp=ExpY1_Mean_Cpx, \n",
    "                                                   variable=\"Na2O\",\n",
    "                                variable_err=Pec_Err_Neave_Na_ExpY1,\n",
    "                                             variable_err_type=\"Perc\", duplicates=500, \n",
    "                                        err_dist=\"normal\", positive=False)\n",
    "\n",
    "Cpx_ExpY1_Syn=pt.calculate_cpx_only_press_all_eqs(cpx_comps=ExpY1_noise1)\n",
    "Cpx_ExpY1_Calc=pt.calculate_cpx_only_press_all_eqs(cpx_comps=Cpxs_ExpY1.reset_index(drop=True))\n",
    "Cpx_ExpY1_Calc_100=pt.calculate_cpx_only_press_all_eqs(cpx_comps=ExpY1_noise1_500)\n",
    "Cpx_ExpY1_Calc_100_JustNa=pt.calculate_cpx_only_press_all_eqs(cpx_comps=ExpY1_noise1_500_JustNa)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2a2c8c2-b30f-4c6c-8a58-c0daf3bdee0a",
   "metadata": {},
   "source": [
    "## How do the cations look"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2625d48c-f645-4fb3-97f5-eb65352aab65",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    }
   ],
   "source": [
    "cpx_components=pt.calculate_clinopyroxene_components(cpx_comps=ExpY1_noise1)\n",
    "cpx_components_all_Cpx=pt.calculate_clinopyroxene_components(cpx_comps=Cpxs_2nd_NExp)\n",
    "cpx_comps_ExpY1=pt.calculate_clinopyroxene_components(cpx_comps=Cpxs_ExpY1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "02332129-6107-44c5-b642-68493ad18c0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(5,8), sharex=True)\n",
    "bins=[3.96, 3.965, 3.97, 3.975, 3.98, 3.985, 3.99, 3.995, 4, 4.005, 4.01,\n",
    "      4.015, 4.02, 4.025,  4.03, 4.035, 4.04, 4.045, 4.05]\n",
    "ax1.set_title('a) Synthetic Cpx from Exp Y1')\n",
    "ax2.set_title('b) Measured Cpx (Exp Y1)')\n",
    "ax3.set_title('c) All Cpx (Neave et al. 2019)')\n",
    "\n",
    "ax1.hist(cpx_components['Cation_Sum_Cpx'], bins=bins, fc='red', ec='k', density=True);\n",
    "ax3.hist(cpx_components_all_Cpx['Cation_Sum_Cpx'].loc[cpx_components_all_Cpx['Cation_Sum_Cpx'].between(3.9, 4.2)],\n",
    "       fc=None, bins=bins, ec='k', density=True);\n",
    "    \n",
    "ax2.hist(cpx_comps_ExpY1['Cation_Sum_Cpx'].loc[cpx_components_all_Cpx['Cation_Sum_Cpx'].between(3.9, 4.2)],\n",
    "       fc=None,bins=bins, ec='k', density=True);    \n",
    "\n",
    "ax1.set_xlim([3.95, 4.05])\n",
    "lw1=3\n",
    "ax1.plot([4, 4], [0, 45], '-k', lw=lw1)\n",
    "ax2.plot([4, 4], [0, 85], '-k', lw=lw1)\n",
    "ax3.plot([4, 4], [0, 35], '-k', lw=lw1)\n",
    "ax1.xaxis.set_tick_params(which='both', labelbottom=True)\n",
    "ax2.xaxis.set_tick_params(which='both', labelbottom=True)\n",
    "ax3.xaxis.set_tick_params(which='both', labelbottom=True)\n",
    "\n",
    "ax1.grid(color = 'k', linestyle = '--', linewidth = 1, alpha = 0.1)\n",
    "\n",
    "ax1.set_xticks([3.95, 3.96, 3.97, 3.98, 3.99, 4, 4.01, 4.02, 4.03, 4.04, 4.05]);\n",
    "ax1.set_xlabel('Cation sum')\n",
    "ax2.set_xlabel('Cation sum')\n",
    "ax3.set_xlabel('Cation sum')\n",
    "fig.tight_layout()\n",
    "fig.savefig('Synthetic_Cations.png', dpi=200)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2098965-dca1-4951-9137-1e12cbf0e2f2",
   "metadata": {},
   "source": [
    "### Neave Liquid calculations\n",
    "- We dont have precision for Neave in the liquid - so we just make an average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fcdadc8c-7d3b-44c2-b9e6-39d966443306",
   "metadata": {},
   "outputs": [],
   "source": [
    "Mean_Glass_ExpY1=Glass_ExpY1.mean(axis=0).to_frame().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3ac32044-237e-4923-bdc1-747373983f5c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=16 Cpx & N=12 Liqs, which is a total of N=192 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=192 Cpx-Liq matches using the specified filter. N=16 Cpx out of the N=16 Cpx that you input matched to 1 or more liquids\n"
     ]
    }
   ],
   "source": [
    "# Working out all measured pairs - e.g. Cpx we measured Liq we measure\n",
    "Y1_Cpx_AvLiq_32c_eq33_Liq=pt.calculate_cpx_liq_press_temp_matching(\n",
    "cpx_comps=Cpxs_ExpY1,\n",
    "liq_comps=Glass_ExpY1,\n",
    "H2O_Liq=0,\n",
    "equationT=\"T_Put2008_eq33\",\n",
    "equationP=\"P_Put2008_eq32c\",\n",
    "return_all_pairs=True\n",
    ").get('All_PTs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "45ef4a50-f4ec-40fa-964e-6c6a4cd1862d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=5000 Cpx & N=12 Liqs, which is a total of N=60000 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=60000 Cpx-Liq matches using the specified filter. N=5000 Cpx out of the N=5000 Cpx that you input matched to 1 or more liquids\n"
     ]
    }
   ],
   "source": [
    "# 5000 Synthetic Cpxs, measured glasses. \n",
    "Y1_Cpx_AvLiq_32c_eq33_Liq_Syn=pt.calculate_cpx_liq_press_temp_matching(\n",
    "cpx_comps=ExpY1_noise1,\n",
    "liq_comps=Glass_ExpY1,\n",
    " H2O_Liq=0,\n",
    "equationT=\"T_Put2008_eq33\",\n",
    "equationP=\"P_Put2008_eq32c\",\n",
    "return_all_pairs=True\n",
    ").get('All_PTs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "16ee02e8-87a9-41d4-8c05-d4c277bb87b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x20b74e3b160>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(Y1_Cpx_AvLiq_32c_eq33_Liq_Syn['Al2O3_Cpx'], Y1_Cpx_AvLiq_32c_eq33_Liq_Syn['P_kbar_calc'], '.k')\n",
    "plt.plot(Y1_Cpx_AvLiq_32c_eq33_Liq['Al2O3_Cpx'], Y1_Cpx_AvLiq_32c_eq33_Liq['P_kbar_calc'], 'or')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db70ebe4-ca50-4df4-8e4e-2d9582fa2569",
   "metadata": {},
   "source": [
    "### Synthetic Calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d403a059-0447-42f5-9d0e-ad474124c206",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=5000 Cpx & N=1 Liqs, which is a total of N=5000 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=5000 Cpx-Liq matches using the specified filter. N=5000 Cpx out of the N=5000 Cpx that you input matched to 1 or more liquids\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=5000 Cpx & N=1 Liqs, which is a total of N=5000 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=5000 Cpx-Liq matches using the specified filter. N=5000 Cpx out of the N=5000 Cpx that you input matched to 1 or more liquids\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=5000 Cpx & N=1 Liqs, which is a total of N=5000 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=5000 Cpx-Liq matches using the specified filter. N=5000 Cpx out of the N=5000 Cpx that you input matched to 1 or more liquids\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:2120: FutureWarning: In a future version, the Index constructor will not infer numeric dtypes when passed object-dtype sequences (matching Series behavior)\n",
      "  new_ix = Index(new_ix)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=5000 Cpx & N=1 Liqs, which is a total of N=5000 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Youve selected a P-independent function\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator StandardScaler from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreeRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreesRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Youve selected a T-independent function\n",
      "Youve selected a T-independent function\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator StandardScaler from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreeRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreesRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=5000 Cpx-Liq matches using the specified filter. N=5000 Cpx out of the N=5000 Cpx that you input matched to 1 or more liquids\n"
     ]
    }
   ],
   "source": [
    "# 5000 synthetic Cpxs, mean glass compositions, different PT equations\n",
    "Y1_Cpx_AvLiq_N17_eq33_Liq_Syn=pt.calculate_cpx_liq_press_temp_matching(\n",
    "cpx_comps=ExpY1_noise1,\n",
    "liq_comps=Mean_Glass_ExpY1,\n",
    "H2O_Liq=0,\n",
    "equationT=\"T_Put2008_eq33\",\n",
    "equationP=\"P_Neave2017\",\n",
    "return_all_pairs=True\n",
    ").get('All_PTs')\n",
    "\n",
    "Y1_Cpx_AvLiq_31_eq33_Liq_Syn=pt.calculate_cpx_liq_press_temp_matching(\n",
    "cpx_comps=ExpY1_noise1,\n",
    "liq_comps=Mean_Glass_ExpY1,\n",
    "H2O_Liq=0,\n",
    "equationT=\"T_Put2008_eq33\",\n",
    "equationP=\"P_Put2008_eq31\",\n",
    "return_all_pairs=True\n",
    ").get('All_PTs')\n",
    "\n",
    "Y1_Cpx_AvLiq_30_eq33_Liq_Syn=pt.calculate_cpx_liq_press_temp_matching(\n",
    "cpx_comps=ExpY1_noise1,\n",
    "liq_comps=Mean_Glass_ExpY1,\n",
    "H2O_Liq=0,\n",
    "equationT=\"T_Put2008_eq33\",\n",
    "equationP=\"P_Put2008_eq30\",\n",
    "return_all_pairs=True\n",
    ").get('All_PTs')\n",
    "\n",
    "Y1_Cpx_AvLiq_Pet_Liq_Syn=pt.calculate_cpx_liq_press_temp_matching(\n",
    "cpx_comps=ExpY1_noise1,\n",
    "liq_comps=Mean_Glass_ExpY1,\n",
    "H2O_Liq=0,\n",
    "equationT=\"T_Petrelli2020_Cpx_Liq\",\n",
    "equationP=\"P_Petrelli2020_Cpx_Liq\",\n",
    "return_all_pairs=True\n",
    ").get('All_PTs')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebe7e8f0-110b-4428-89ac-83812e35fc59",
   "metadata": {},
   "source": [
    "### Calculations using measured pairs for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3f34852b-7759-46ef-81c0-a0f864973fe5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Considering N=16 Cpx & N=12 Liqs, which is a total of N=192 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=192 Cpx-Liq matches using the specified filter. N=16 Cpx out of the N=16 Cpx that you input matched to 1 or more liquids\n",
      "Considering N=16 Cpx & N=12 Liqs, which is a total of N=192 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=192 Cpx-Liq matches using the specified filter. N=16 Cpx out of the N=16 Cpx that you input matched to 1 or more liquids\n",
      "Considering N=16 Cpx & N=12 Liqs, which is a total of N=192 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=192 Cpx-Liq matches using the specified filter. N=16 Cpx out of the N=16 Cpx that you input matched to 1 or more liquids\n",
      "Considering N=16 Cpx & N=12 Liqs, which is a total of N=192 Liq-Cpx pairs, be patient if this is >>1 million!\n",
      "No equilibrium filters applied\n",
      "Youve selected a P-independent function\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator StandardScaler from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreeRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreesRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator StandardScaler from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n",
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreeRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Youve selected a T-independent function\n",
      "Youve selected a T-independent function\n",
      "Finished calculating Ps and Ts, now just averaging the results. Almost there!\n",
      "Done!!! I found a total of N=192 Cpx-Liq matches using the specified filter. N=16 Cpx out of the N=16 Cpx that you input matched to 1 or more liquids\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\penny\\anaconda3\\lib\\site-packages\\sklearn\\base.py:329: UserWarning: Trying to unpickle estimator ExtraTreesRegressor from version 1.0.2 when using version 1.1.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:\n",
      "https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "Y1_Cpx_Liq_N17_eq33_Liq=pt.calculate_cpx_liq_press_temp_matching(\n",
    "liq_comps=Glass_ExpY1, cpx_comps=Cpxs_ExpY1.reset_index(drop=True),\n",
    "H2O_Liq=0, equationT=\"T_Put2008_eq33\", equationP=\"P_Neave2017\", \n",
    "return_all_pairs=True).get('All_PTs')\n",
    "\n",
    "Y1_Cpx_Liq_30_eq33_Liq=pt.calculate_cpx_liq_press_temp_matching(\n",
    "liq_comps=Glass_ExpY1, cpx_comps=Cpxs_ExpY1.reset_index(drop=True),\n",
    "H2O_Liq=0, equationT=\"T_Put2008_eq33\", equationP=\"P_Put2008_eq30\", \n",
    "return_all_pairs=True).get('All_PTs')\n",
    "\n",
    "Y1_Cpx_Liq_31_eq33_Liq=pt.calculate_cpx_liq_press_temp_matching(\n",
    "liq_comps=Glass_ExpY1, cpx_comps=Cpxs_ExpY1.reset_index(drop=True),\n",
    "H2O_Liq=0, equationT=\"T_Put2008_eq33\", equationP=\"P_Put2008_eq31\", \n",
    "return_all_pairs=True).get('All_PTs')\n",
    "\n",
    "Y1_Cpx_Liq_Pet_Liq=pt.calculate_cpx_liq_press_temp_matching(\n",
    "liq_comps=Glass_ExpY1, cpx_comps=Cpxs_ExpY1.reset_index(drop=True),\n",
    "H2O_Liq=0, equationT=\"T_Petrelli2020_Cpx_Liq\", \n",
    "equationP=\"P_Petrelli2020_Cpx_Liq\", return_all_pairs=True ).get('All_PTs')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52f282cf-1249-446a-b9c2-f59756173622",
   "metadata": {},
   "source": [
    "## 6 part figure for noise paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "05878245-037f-432e-9d75-a0de7490ee0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1300 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig, ((ax1, ax2), (ax3, ax4), (ax5, ax6))  = plt.subplots(3, 2, figsize=(10,13))\n",
    "###################\n",
    "extent1=(-1, 5, 1300, 1500)\n",
    "Cpx_ExpY1_Syn=Cpx_ExpY1_Syn.fillna(0)\n",
    "#ax1.set_title('Exp B0184-10- Neave et al. (2019)')\n",
    "ax1.errorbar(np.mean(Cpx_ExpY1_Calc['P_Put_Teq32d_Peq32b']),\n",
    "             np.mean(Cpx_ExpY1_Calc['T_Put_Teq32d_Peq32b']),\n",
    "             xerr=2.6, yerr=58,\n",
    "             fmt='.', ecolor='k', elinewidth=0.8, mfc='k', ms=1, mec='k')\n",
    "\n",
    "# h=ax1.hist2d(Cpx_ExpY1_Syn['Jd'], Cpx_ExpY1_Syn['P_Put_Teq32d_Peq32b'], bins=(50, 50), cmap=plt.cm.BuPu, \n",
    "#            label='Simulated EPMA errors', vmin=0, vmax=500)\n",
    "ax1.hexbin(Cpx_ExpY1_Syn['P_Put_Teq32d_Peq32b'].loc[Cpx_ExpY1_Syn['P_Put_Teq32d_Peq32b']!=0],\n",
    "           Cpx_ExpY1_Syn['T_Put_Teq32d_Peq32b'].loc[Cpx_ExpY1_Syn['P_Put_Teq32d_Peq32b']!=0]\n",
    "           , cmap=plt.cm.BuPu, \n",
    "            linewidths=0.2, bins=50)\n",
    "ax1.plot(Cpx_ExpY1_Calc['P_Put_Teq32d_Peq32b'],\n",
    "         Cpx_ExpY1_Calc['T_Put_Teq32d_Peq32b'],\n",
    "          'ok', mfc='yellow',  ms=4,label='Meas Cpx')\n",
    "ax1.plot(Cpx_ExpY1_Calc['P_Put_Teq32d_Peq32b'].loc[Cpx_ExpY1_Calc['Jd_from 0=Na, 1=Al']==1],\n",
    "         Cpx_ExpY1_Calc['T_Put_Teq32d_Peq32b'].loc[Cpx_ExpY1_Calc['Jd_from 0=Na, 1=Al']==1],\n",
    "          'or', mfc='red',  ms=4, label='Meas Cpx')\n",
    "#ax1.plot(8, 1505, '*k', ms=20,  mfc='yellow') # Note, temperature is actually 1323.15\n",
    "\n",
    "Cpx_ExpY1_Syn.loc[Cpx_ExpY1_Syn['P_Put_Teq32d_Peq32b']!=0, \n",
    "[\"P_Put_Teq32d_Peq32b\", \"T_Put_Teq32d_Peq32b\"]].pyroplot.density(ax=ax1, contours=[0.67, 0.95], colors=['m', 'k'],\n",
    "                                                                                      extent=extent1,\n",
    "                                                                    cmap=\"viridis\", bins=100, label_contours=False)\n",
    "ax1.set_ylim([1360, 1500])\n",
    "ax1.set_xlim([-1, 5])\n",
    "ax1.plot(1, 1140+273.15, '*k', mfc='yellow', ms=20)\n",
    "\n",
    "\n",
    "########### ax2# ###############\n",
    "extent2=(-3, 3, 1375, 1475)\n",
    "ax2.errorbar(np.mean(Cpx_ExpY1_Calc['P_Wang21_eq1']),\n",
    "             np.mean(Cpx_ExpY1_Calc['T_Wang21_eq2']),\n",
    "             xerr=1.52, yerr=35.2,\n",
    "             fmt='.', ecolor='k', elinewidth=0.8, mfc='k', ms=1)\n",
    "ax2.hexbin(Cpx_ExpY1_Syn['P_Wang21_eq1'].loc[Cpx_ExpY1_Syn['P_Wang21_eq1']!=0],\n",
    "           Cpx_ExpY1_Syn['T_Wang21_eq2'].loc[Cpx_ExpY1_Syn['P_Wang21_eq1']!=0]\n",
    "           , cmap=plt.cm.BuPu, \n",
    "            linewidths=0.2, bins=50)\n",
    "ax2.plot(Cpx_ExpY1_Calc['P_Wang21_eq1'],\n",
    "         Cpx_ExpY1_Calc['T_Wang21_eq2'],\n",
    "         'ok', mfc='yellow',  ms=4, label='Meas Cpx')\n",
    "ax2.plot(Cpx_ExpY1_Calc['P_Wang21_eq1'].loc[Cpx_ExpY1_Calc['Jd_from 0=Na, 1=Al']==1],\n",
    "         Cpx_ExpY1_Calc['T_Wang21_eq2'].loc[Cpx_ExpY1_Calc['Jd_from 0=Na, 1=Al']==1],\n",
    "         'or', mfc='red',  ms=4, label='Meas Cpx')\n",
    "Cpx_ExpY1_Syn.loc[Cpx_ExpY1_Syn['P_Wang21_eq1']!=0, \n",
    "[\"P_Wang21_eq1\", \"T_Wang21_eq2\"]].pyroplot.density(ax=ax2, contours=[0.67, 0.95], colors=['m', 'k'],\n",
    "                                                                                      extent=extent2,\n",
    "                                                                    cmap=\"viridis\", bins=50, label_contours=False)\n",
    "ax2.set_ylim([1370, 1460])\n",
    "ax2.set_xlim([-2, 3.5])\n",
    "ax2.plot(1, 1140+273.15, '*k', mfc='yellow', ms=20)\n",
    "\n",
    "################ ax3 ##################\n",
    "extent2=(-3, 3, 1330, 1460)\n",
    "ax3.errorbar(np.mean(Cpx_ExpY1_Calc['P_Petrelli20']),\n",
    "             np.mean(Cpx_ExpY1_Calc['T_Petrelli20']),\n",
    "             xerr=3.1, yerr=51,\n",
    "             fmt='.', ecolor='k', elinewidth=0.8, mfc='k', ms=1)\n",
    "ax3.hexbin(Cpx_ExpY1_Syn['P_Petrelli20'].loc[Cpx_ExpY1_Syn['P_Petrelli20']!=0],\n",
    "           Cpx_ExpY1_Syn['T_Petrelli20'].loc[Cpx_ExpY1_Syn['P_Petrelli20']!=0]\n",
    "           , cmap=plt.cm.BuPu, \n",
    "            linewidths=0.2, bins=50)\n",
    "ax3.plot(Cpx_ExpY1_Calc['P_Petrelli20'],\n",
    "         Cpx_ExpY1_Calc['T_Petrelli20'],\n",
    "          'ok', mfc='yellow',  ms=4, label='Meas Cpx')\n",
    "ax3.plot(Cpx_ExpY1_Calc['P_Petrelli20'].loc[Cpx_ExpY1_Calc['Jd_from 0=Na, 1=Al']==1],\n",
    "         Cpx_ExpY1_Calc['T_Petrelli20'].loc[Cpx_ExpY1_Calc['Jd_from 0=Na, 1=Al']==1],\n",
    "         'or', mfc='red',  ms=4, label='Meas Cpx')\n",
    "Cpx_ExpY1_Syn.loc[Cpx_ExpY1_Syn['P_Petrelli20']!=0, \n",
    "[\"P_Petrelli20\", \"T_Petrelli20\"]].pyroplot.density(ax=ax3, contours=[0.67, 0.95], colors=['m', 'k'],\n",
    "                                                          extent=extent2,\n",
    "                                                        cmap=\"viridis\", bins=50, label_contours=False)\n",
    "ax3.set_xlim([-3, 5])\n",
    "ax3.set_ylim([1320, 1440])\n",
    "ax3.plot(1, 1140+273.15, '*k', mfc='yellow', ms=20)\n",
    "### ax4 ################\n",
    "## Cpx=Liq\n",
    "Y1_Cpx_Liq_N17_eq33_Liq_100=Y1_Cpx_Liq_N17_eq33_Liq#.sample(n=100)\n",
    "extent4=(-8, 6, 1350, 1500)\n",
    "ax4.plot(Y1_Cpx_Liq_N17_eq33_Liq_100['P_kbar_calc'].loc[Y1_Cpx_Liq_N17_eq33_Liq_100['Jd_from 0=Na, 1=Al']==1],\n",
    "         Y1_Cpx_Liq_N17_eq33_Liq_100['T_K_calc'].loc[Y1_Cpx_Liq_N17_eq33_Liq_100['Jd_from 0=Na, 1=Al']==1],\n",
    "         'or', mfc='red',  ms=2,label='Meas Cpx', alpha=0.8)\n",
    "ax4.plot(Y1_Cpx_Liq_N17_eq33_Liq_100['P_kbar_calc'].loc[Y1_Cpx_Liq_N17_eq33_Liq_100['Jd_from 0=Na, 1=Al']==0],\n",
    "         Y1_Cpx_Liq_N17_eq33_Liq_100['T_K_calc'].loc[Y1_Cpx_Liq_N17_eq33_Liq_100['Jd_from 0=Na, 1=Al']==0],\n",
    "         'ok', mfc='yellow', ms=2, label='Meas Cpx', alpha=0.8,  mew=0.5)\n",
    "ax4.hexbin(Y1_Cpx_AvLiq_N17_eq33_Liq_Syn['P_kbar_calc'],\n",
    "           Y1_Cpx_AvLiq_N17_eq33_Liq_Syn['T_K_calc'],\n",
    "            cmap=plt.cm.BuPu, \n",
    "            linewidths=0.2, bins=50)\n",
    "ax4.errorbar(np.mean(Y1_Cpx_AvLiq_N17_eq33_Liq_Syn['P_kbar_calc']),\n",
    "           np.mean(Y1_Cpx_AvLiq_N17_eq33_Liq_Syn['T_K_calc']),\n",
    "             xerr=1.4, yerr=45,\n",
    "             fmt='.', ecolor='k', elinewidth=0.8, mfc='k', ms=1)\n",
    "\n",
    "Y1_Cpx_AvLiq_N17_eq33_Liq_Syn.loc[:, \n",
    "[\"P_kbar_calc\", \"T_K_calc\"]].pyroplot.density(ax=ax4, contours=[0.67, 0.95], colors=['m', 'grey'],\n",
    "                                                          extent=extent4,\n",
    "                                                        cmap=\"viridis\", bins=100, label_contours=False, zorder=100)\n",
    "ax4.set_xlim([-7, 4])\n",
    "ax4.set_ylim([1340, 1455])\n",
    "ax4.plot(1, 1140+273.15, '*k', mfc='yellow', ms=20)\n",
    "\n",
    "\n",
    "## ax5\n",
    "Y1_Cpx_Liq_30_eq33_Liq_100=Y1_Cpx_Liq_30_eq33_Liq#.sample(n=100)\n",
    "extent4=(-3, 7, 1370, 1480)\n",
    "\n",
    "ax5.errorbar(np.mean(Y1_Cpx_AvLiq_30_eq33_Liq_Syn['P_kbar_calc']),\n",
    "           np.mean(Y1_Cpx_AvLiq_30_eq33_Liq_Syn['T_K_calc']),\n",
    "             xerr=3.6, yerr=45,\n",
    "             fmt='.', ecolor='k', elinewidth=0.8, mfc='k', ms=1)\n",
    "\n",
    "ax5.plot(Y1_Cpx_Liq_30_eq33_Liq_100['P_kbar_calc'].loc[Y1_Cpx_Liq_30_eq33_Liq_100['Jd_from 0=Na, 1=Al']==1],\n",
    "         Y1_Cpx_Liq_30_eq33_Liq_100['T_K_calc'].loc[Y1_Cpx_Liq_30_eq33_Liq_100['Jd_from 0=Na, 1=Al']==1],\n",
    "         'or', mfc='red',  ms=2,label='Meas Cpx', alpha=0.8,  mew=0.5)\n",
    "ax5.plot(Y1_Cpx_Liq_30_eq33_Liq_100['P_kbar_calc'].loc[Y1_Cpx_Liq_30_eq33_Liq_100['Jd_from 0=Na, 1=Al']==0],\n",
    "         Y1_Cpx_Liq_30_eq33_Liq_100['T_K_calc'].loc[Y1_Cpx_Liq_30_eq33_Liq_100['Jd_from 0=Na, 1=Al']==0],\n",
    "         'ok', mfc='yellow', ms=2, label='Meas Cpx', alpha=0.8,   mew=0.5)\n",
    "ax5.hexbin(Y1_Cpx_AvLiq_30_eq33_Liq_Syn['P_kbar_calc'],\n",
    "           Y1_Cpx_AvLiq_30_eq33_Liq_Syn['T_K_calc'],\n",
    "            cmap=plt.cm.BuPu, \n",
    "            linewidths=0.2, bins=50)\n",
    "\n",
    "\n",
    "Y1_Cpx_AvLiq_30_eq33_Liq_Syn.loc[:, \n",
    "[\"P_kbar_calc\", \"T_K_calc\"]].pyroplot.density(ax=ax5, contours=[0.67, 0.95], colors=['m', 'grey'],\n",
    "                                                          extent=extent4,\n",
    "                                                        cmap=\"viridis\", bins=100, label_contours=False, zorder=100)\n",
    "ax5.set_xlim([-3, 6])\n",
    "ax5.set_ylim([1370, 1470])\n",
    "ax5.plot(1, 1140+273.15, '*k', mfc='yellow', ms=20)\n",
    "\n",
    "### ax6\n",
    "\n",
    "\n",
    "Y1_Cpx_Liq_Pet_Liq_100=Y1_Cpx_Liq_Pet_Liq#.sample(n=100)\n",
    "extent4=(-3, 7, 1370, 1480)\n",
    "\n",
    "ax6.errorbar(np.mean(Y1_Cpx_AvLiq_Pet_Liq_Syn['P_kbar_calc']),\n",
    "           np.mean(Y1_Cpx_AvLiq_Pet_Liq_Syn['T_K_calc']),\n",
    "             xerr=3.6, yerr=45,\n",
    "             fmt='.', ecolor='k', elinewidth=0.8, mfc='k', ms=1)\n",
    "\n",
    "ax6.plot(Y1_Cpx_Liq_Pet_Liq_100['P_kbar_calc'].loc[Y1_Cpx_Liq_Pet_Liq_100['Jd_from 0=Na, 1=Al']==1],\n",
    "         Y1_Cpx_Liq_Pet_Liq_100['T_K_calc'].loc[Y1_Cpx_Liq_Pet_Liq_100['Jd_from 0=Na, 1=Al']==1],\n",
    "         'or', mfc='red',  ms=2,label='Meas Cpx', alpha=0.8,   mew=0.5)\n",
    "ax6.plot(Y1_Cpx_Liq_Pet_Liq_100['P_kbar_calc'].loc[Y1_Cpx_Liq_Pet_Liq_100['Jd_from 0=Na, 1=Al']==0],\n",
    "         Y1_Cpx_Liq_Pet_Liq_100['T_K_calc'].loc[Y1_Cpx_Liq_Pet_Liq_100['Jd_from 0=Na, 1=Al']==0],\n",
    "         'ok', mfc='yellow', ms=2, label='Meas Cpx', alpha=0.8,   mew=0.5)\n",
    "ax6.hexbin(Y1_Cpx_AvLiq_Pet_Liq_Syn['P_kbar_calc'],\n",
    "           Y1_Cpx_AvLiq_Pet_Liq_Syn['T_K_calc'],\n",
    "            cmap=plt.cm.BuPu, \n",
    "            linewidths=0.2, bins=50)\n",
    "\n",
    "\n",
    "Y1_Cpx_AvLiq_Pet_Liq_Syn.loc[:, \n",
    "[\"P_kbar_calc\", \"T_K_calc\"]].pyroplot.density(ax=ax6, contours=[0.67, 0.95], colors=['m', 'grey'],\n",
    "                                                          extent=extent4,\n",
    "                                                        cmap=\"viridis\", bins=100, label_contours=False, zorder=100)\n",
    "ax6.set_xlim([-4, 6])\n",
    "ax6.set_ylim([1360, 1470])\n",
    "ax6.plot(1, 1140+273.15, '*k', mfc='yellow', ms=20, zorder=101)\n",
    "\n",
    "ax1.annotate(\"a) Cpx-only\", xy=(0.02, 0.95), xycoords=\"axes fraction\", fontsize=14)\n",
    "ax2.annotate(\"b) Cpx-only\", xy=(0.02, 0.95), xycoords=\"axes fraction\", fontsize=14)\n",
    "ax3.annotate(\"c) Cpx-only\", xy=(0.02, 0.95), xycoords=\"axes fraction\", fontsize=14)\n",
    "ax4.annotate(\"d) Cpx-Liq\", xy=(0.02, 0.95), xycoords=\"axes fraction\", fontsize=14)\n",
    "ax5.annotate(\"e) Cpx-Liq\", xy=(0.02, 0.95), xycoords=\"axes fraction\", fontsize=14)\n",
    "ax6.annotate(\"f) Cpx-Liq\", xy=(0.02, 0.95), xycoords=\"axes fraction\", fontsize=14)\n",
    "\n",
    "ax1.set_xlabel('Calc P (kbar), Putirka (2008) eq32d-32b')\n",
    "ax1.set_ylabel('Calc T (K), Putirka (2008) eq32d-32b')\n",
    "ax2.set_xlabel('Calc P (kbar), Wang et al. (2021) eq1')\n",
    "ax2.set_ylabel('Calc T (K), Wang et al. (2021)  eq2')\n",
    "ax3.set_xlabel('Calc P (kbar), Petrelli et al. (2020)')\n",
    "ax3.set_ylabel('Calc T (K), Petrelli et al. (2020)')\n",
    "\n",
    "ax4.set_xlabel('Calc P (kbar), Putirka (2008) eq 33, \\n Neave et al. (2017)')\n",
    "ax4.set_ylabel('Calc T (K), Putirka (2008) eq 33, \\n Neave et al. (2017)')\n",
    "ax5.set_xlabel('Calc P (kbar), Putirka (2008) eq 33-30')\n",
    "ax5.set_ylabel('Calc T (K), Putirka (2008) eq 33-30')\n",
    "ax6.set_xlabel('Calc P (kbar), Petrelli et al. (2020)')\n",
    "ax6.set_ylabel('Calc T (K), Petrelli et al. (2020)')\n",
    "ax3.plot(8, 1050+273.15, '*k', mfc='yellow', ms=20)\n",
    "ax6.plot(8, 1050+273.15, '*k', mfc='yellow', ms=20)\n",
    "plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=None, hspace=0.3)\n",
    "fig.savefig('Neave_Cpx_Cpx_Liq_Y272.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "873e7a77-073a-429d-9109-56d6338dec6f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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