{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2e. Calculate closed-system degassing paths for different volatile systems.\n",
"\n",
"These are some examples where the volatiles aren't C, H, and S. These types of calculations can be done for open- and closed-system, re- and degassing paths as described in Examples 2a-d, but we'll just show them for closed-system degassing paths where the inputted composition represents the bulk composition of the system."
]
},
{
"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. Remove the # from line below to do this (don't remove the # from this line!).\n",
"# pip install VolFe"
]
},
{
"cell_type": "code",
"execution_count": 2,
"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": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'0.4.1'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# VolFe version\n",
"vf.__version__"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Define the inputs\n",
"\n",
"For the volatile-free melt composition, we'll use Sari15-04-33 from Brounce et al. (2014) with the updated Fe3+/FeT from Cottrell et al. (2021) at 1200 °C as before, but we will specify different volatile concentrations. \n",
"\n",
"First, we'll model CHOAr degassing - i.e., carbon, hydrogen, and argon are the volatiles of interest (no sulfur - at the moment it isn't possible to run CHOS and a noble gas).\n",
"\n",
"In this case the initial volatile content is 500 ppm CO2, 2 wt% H2O, and 10 ppm Ar.\n",
"\n",
"The Ar amount is inputted for the \"X\" species."
]
},
{
"cell_type": "code",
"execution_count": 4,
"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",
" 'H2O': 2., # wt%\n",
" 'CO2ppm': 500., # ppm\n",
" 'STppm': 0., # ppm\n",
" 'Xppm': 10., # ppm <<< treating this as Ar\n",
" 'Fe3FeT': 0.177}\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, but the important options for noble gas modelling are:\n",
"\n",
"**species X** where the default is Ar (*Ar*)\n",
"\n",
"**species X solubility** where the default is for Ar in basalt (*Ar_Basalt_Hughes25*)\n",
"\n",
"Both these defaults are fine for this example, but you can change them to Ar in rhyolite (*Ar_Rhyolite_Hughes25*) or Ne (*Ne*) for basalt (*Ne_Basalt_Hughes25*) or rhyolite (*Ne_Rhyolite_Hughes25*).\n",
"\n",
"## Run the calculation\n",
"\n",
"### Ar in basalt"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|█████████▉| 1399.0/1400 [00:51<00:00, 27.29it/s] \n"
]
}
],
"source": [
"degas1 = vf.calc_gassing(my_analysis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Ne in basalt\n",
"\n",
"Next for Ne in basalt"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|█████████▉| 1399.0/1400 [00:54<00:00, 25.51it/s] \n"
]
}
],
"source": [
"# choose the options I want - everything else will use the default options\n",
"my_models = [['species X','Ne'],['species X solubility','Ne_Basalt_Hughes25']]\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 calculation\n",
"degas2 = vf.calc_gassing(my_analysis,models=my_models)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Ar in rhyolite\n",
"\n",
"Or Ar in rhyolite"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|█████████▉| 1299.0/1300 [00:47<00:00, 27.58it/s] \n"
]
}
],
"source": [
"# choose the options I want - everything else will use the default options\n",
"my_models = [['species X solubility','Ar_Rhyolite_Hughes25']]\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 calculation\n",
"degas3 = vf.calc_gassing(my_analysis,models=my_models)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plotting\n",
"\n",
"And plot for comparison."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(1500.0, 0.0)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(12,4))\n",
"\n",
"data1 = degas1 # Ar in basalt\n",
"data2 = degas2 # Ne in basalt\n",
"data3 = degas3 # Ar in rhyolite\n",
"\n",
"# Plotting results\n",
"ax1.plot(data1['CO2T-eq_ppmw'], data1['P_bar'], '-k')\n",
"ax1.plot(data2['CO2T-eq_ppmw'], data2['P_bar'], ':k')\n",
"ax1.plot(data3['CO2T-eq_ppmw'], data3['P_bar'], '--k')\n",
"ax2.plot(data1['H2OT-eq_wtpc'], data1['P_bar'], '-k')\n",
"ax2.plot(data2['H2OT-eq_wtpc'], data2['P_bar'], ':k')\n",
"ax2.plot(data3['H2OT-eq_wtpc'], data3['P_bar'], '--k')\n",
"ax3.plot(data1['X_ppmw'], data1['P_bar'], '-k')\n",
"ax3.plot(data2['X_ppmw'], data2['P_bar'], ':k')\n",
"ax3.plot(data3['X_ppmw'], data3['P_bar'], '--k')\n",
"\n",
"ax1.set_ylabel('P (bar)')\n",
"ax1.set_xlabel('CO2,T-eq (ppmw)')\n",
"ax2.set_xlabel('H2OT-eq (wt%)')\n",
"ax3.set_xlabel('XT (ppmw)')\n",
"ax1.set_ylim([1500,0])\n",
"ax2.set_ylim([1500,0])\n",
"ax3.set_ylim([1500,0])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### HSO system\n",
"\n",
"Alternatively, we could just look at degassing in the HSO system (i.e., no CO2 or X)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"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",
" 'H2O': 2., # wt%\n",
" 'CO2ppm': 0., # ppm\n",
" 'STppm': 1000., # ppm\n",
" 'Xppm': 0., # ppm\n",
" 'Fe3FeT': 0.177}\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": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|█████████▉| 299.0/300 [00:06<00:00, 43.82it/s] \n"
]
}
],
"source": [
"degas4 = vf.calc_gassing(my_analysis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### CSO system\n",
"\n",
"Or CSO system"
]
},
{
"cell_type": "code",
"execution_count": 11,
"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",
" 'H2O': 0., # wt%\n",
" 'CO2ppm': 500., # ppm\n",
" 'STppm': 1000., # ppm\n",
" 'Xppm': 0., # ppm\n",
" 'Fe3FeT': 0.177}\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": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|█████████▉| 999.0/1000 [00:13<00:00, 71.53it/s] \n"
]
}
],
"source": [
"degas5 = vf.calc_gassing(my_analysis)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plotting\n",
"\n",
"And compare!"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(1200.0, 0.0)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(12,4))\n",
"\n",
"data1 = degas4 # HSO\n",
"data2 = degas5 # CSO\n",
"\n",
"# Plotting results\n",
"ax1.plot(data2['CO2T-eq_ppmw'], data2['P_bar'], ':k')\n",
"ax2.plot(data1['H2OT-eq_wtpc'], data1['P_bar'], '-k')\n",
"ax3.plot(data1['ST_ppmw'], data1['P_bar'], '-k')\n",
"ax3.plot(data2['ST_ppmw'], data2['P_bar'], ':k')\n",
"\n",
"ax1.set_ylabel('P (bar)')\n",
"ax1.set_xlabel('CO2,T-eq (ppmw)')\n",
"ax2.set_xlabel('H2OT-eq (wt%)')\n",
"ax3.set_xlabel('ST (ppmw)')\n",
"ax1.set_ylim([1200,0])\n",
"ax2.set_ylim([1200,0])\n",
"ax3.set_ylim([1200,0])"
]
}
],
"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
}