{
 "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",
      "If using the Green et al. (2025) or Weller et al. (2024) thermodynamic models please run `ptt.activate_petthermotools_env()` prior to any calculations.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'0.4.6'"
      ]
     },
     "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",
      "    615.7 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-5919-c725-0476-cd0238baa5be 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",
      "   1162.7 ms  ? MAGEMinCalc\n",
      "[ Info: Precompiling MAGEMinCalc [dd69d18c-a947-4316-a873-d8ea006ff1b2] (cache misses: wrong dep version loaded (4), mismatched flags (2))\n",
      "┌ Warning: Module PythonCall with build ID fafbfcfd-5919-c725-0476-cd0238baa5be 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 3:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 5:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 2:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "      From worker 4:\tUsing libMAGEMin.dylib from MAGEMin_jll\n",
      "Julia Environment Ready. MAGEMinCalc v0.6.1 detected\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: 0:00:09\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",
      "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: 0:00:09\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"
     ]
    }
   ],
   "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": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 500x400 with 1 Axes>,\n",
       " <Axes: xlabel='P (bars)', ylabel='T ($\\\\degree$C)'>)"
      ]
     },
     "execution_count": 6,
     "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": 7,
   "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": []
  }
 ],
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