{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MELTS geobarometry part 3 - multi-phase saturation in mafic magmas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alphaMELTS for Python files successfully located.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'0.3.23'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import petthermotools as ptt\n",
    "\n",
    "ptt.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Julia environment detected.\n",
      "Detected IPython. Loading juliacall extension. See https://juliapy.github.io/PythonCall.jl/stable/compat/#IPython\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  Activating project at `~/.petthermotools_julia_env`\n",
      "Precompiling MAGEMinCalc...\n",
      "    568.0 ms  ? PythonCall\n",
      "Info Given MAGEMinCalc was explicitly requested, output will be shown live \u001b[0K\n",
      "\u001b[0KUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "\u001b[0K┌ Warning: Module PythonCall with build ID fafbfcfd-3501-17ed-0393-e686105ae5fb is missing from the cache.\n",
      "\u001b[0K│ This may mean PythonCall [6099a3de-0909-46bc-b1f4-468b9a2dfc0d] does not support precompilation but is imported by a module that does.\n",
      "\u001b[0K└ @ Base loading.jl:2541\n",
      "   1132.4 ms  ? MAGEMinCalc\n",
      "[ Info: Precompiling MAGEMinCalc [dd69d18c-a947-4316-a873-d8ea006ff1b2] (cache misses: wrong dep version loaded (2), mismatched flags (2))\n",
      "┌ Warning: Module PythonCall with build ID fafbfcfd-3501-17ed-0393-e686105ae5fb is missing from the cache.\n",
      "│ This may mean PythonCall [6099a3de-0909-46bc-b1f4-468b9a2dfc0d] does not support precompilation but is imported by a module that does.\n",
      "└ @ Base loading.jl:2541\n",
      "┌ Info: Skipping precompilation due to precompilable error. Importing MAGEMinCalc [dd69d18c-a947-4316-a873-d8ea006ff1b2].\n",
      "└   exception = Error when precompiling module, potentially caused by a __precompile__(false) declaration in the module.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using libMAGEMin.dylib from MAGEMin_jll\n",
      "Using libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 2:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 3:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 5:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 4:\tUsing libMAGEMin.dylib from MAGEMin_jll\n"
     ]
    }
   ],
   "source": [
    "ptt.activate_petthermotools_env()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To demonstrate how PetThermoTools can be used to estimate the pressure of storage for any magma saturated in multiple solid phases we'll use the compsition of an olivine, clinopyroxene, and plagioclase saturated melt from experiment Y0174-12 of Neave et al. (2019). We'll also perform these minimizations using the Green et al. (2025) thermodynamic model implemented through MAGEMin (see installation instructions for how to run MAGEMin calculations)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "bulk = {'SiO2_Liq': 49.47,\n",
    "       'TiO2_Liq': 1.09,\n",
    "       'Al2O3_Liq': 15.58,\n",
    "       'FeOt_Liq': 12.60,\n",
    "       'MgO_Liq': 7.56,\n",
    "       'CaO_Liq': 11.63,\n",
    "       'Na2O_Liq': 1.84,\n",
    "       'K2O_Liq': 0.13,\n",
    "       'H2O_Liq': 1.0,\n",
    "       'Fe3Fet_Liq': 0.18}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we run the barometry calculations there are several other things that need to be specified:\n",
    "- The oxygen fugacity of the system. **At the moment we cannot run these calculations at an fO2 buffer, instead the Fe redox state can be specified in the `bulk` variable above. This is due to a small bug that I'm trying to fix as soon as possible**\n",
    "- The water content (also set in the `bulk` variable above).\n",
    "- The pressure range and number of steps.\n",
    "- The phases of interest.\n",
    "- The thermodynamic model we want to use for the calculations.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fO2_offset = 0.8 # offset from FMQ buffer\n",
    "P_bar = np.linspace(250.0,7500.0,24) #bars\n",
    "phases = ['olivine1', 'plagioclase1', 'clinopyroxene1']\n",
    "Model = \"Green2025\" # calculations performed using the rhyolite-MELTS v1.0.2 thermodynamic model as in Harmon et al. (2018)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use these parameters to calculate pressure. Note, with a natural glass data the H$_2$O content and oxygen fugacity may not be known, which leads to additional uncertainty in the calculation as these parameters have a notable influence on the saturation curves investigated here.\n",
    "\n",
    "Notably, in the example below we'll also specify a maximum temperaure interval on 50 degrees Celsius below the liquidus and a temperature step for each calculatio of 1 degree Celsius."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Limiting calculations to 4 processes due to limitations in available memory\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:08\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:08\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:08\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:10\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:10\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:10\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:10\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:09\u001b[K\n",
      "Computing 51 points... 100%|█████████████████████████████| Time: 0:00:10\u001b[K\n"
     ]
    }
   ],
   "source": [
    "minimum, xstal = ptt.mineral_cosaturation(bulk = bulk, \n",
    "                                   Model = Model,\n",
    "                                   phases = phases,\n",
    "                                   P_bar = P_bar, \n",
    "                                   T_initial_C = 1150.0,\n",
    "                                   dt_C = 1.0, # temperature interval for each calculation\n",
    "                                   T_maxdrop_C = 50.0, # maximum temperature below the liquidus the code will search for 3 phase saturation\n",
    "                                   timeout = 300,\n",
    "                                   T_cut_C = 25.0) \n",
    "                                    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To investigate the results, we can use in-built plotting functions to look at the position of the saturation curves in P-T space:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 500x400 with 1 Axes>,\n",
       " <Axes: xlabel='P (bars)', ylabel='T ($\\\\degree$C)'>)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptt.plot_surfaces(Results = minimum, P_bar = P_bar, phases = phases)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also investigate the temperature residual between the curves using the plottin function below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ptt.residualT_plot(Results = minimum, P_bar = P_bar, phases = phases, interpolate = True, ylim = [0, 100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}