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Python Notebook Download

CHOMPI calculations

  • This notebook shows how to perform CHOMPI calculations following Blundy (2022)- JPET

  • Specifically, this method calculates P, T and XH2O for samples saturated in CHOMPI - Cpx, Hornblende, Opx, Ilmenite-Magnetite, and Plagioclase

  • It also includes a test of how likely it is the liquid was actually CHOMPI saturated

  • Here, we show how to perform calculations using the Cascade liquids from the Blundy paper.

If you havent already, import or upgrade Thermobar. Only in v1.0.25 onwards

[1]:

#!pip install --upgrade Thermobar

[6]:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import Thermobar as pt
pt.__version__
pd.set_option('display.max_columns', None)

[7]:

# Load in the data, dont worry about normalizing, the code will do it for you!
out=pt.import_excel('Cascade_Liqs.xlsx', sheet_name='Sheet1')
Liq=out['Liqs']
all=out['my_input']

[8]:

df_out=pt.calculate_CHOMPI(liq_comps=Liq,  deltaNNO=all['∆NNO (log units)'],
                            T_K_guess=all['T erupt (°C)']+273.15, N_rep=100)
df_out.head()

[8]:
final_assessment SSR In Cali Range? T_K_calc T_K_residual P_kbar_calc XH2O_mol_calc XCO2XH2O SiO2_calc TiO2_calc Al2O3_calc FeOt_calc MgO_calc CaO_calc Na2O_calc K2O_calc CHOMPI (SSI<6?) Pass_Cali_test_SiO2? Pass_Cali_test_Al2O3? Pass_Cali_test_MgO? Pass_Cali_test_Na2O? Pass_Cali_test_K2O? SiO2_Liq TiO2_Liq Al2O3_Liq FeOt_Liq MgO_Liq CaO_Liq Na2O_Liq K2O_Liq Fe3Fet_Liq Sample_ID_Liq NiO_Liq CoO_Liq CO2_Liq H2O_Liq
0 Strong_positive 0.890216 True 1173.709528 100.559528 3.504459 0.725600 0.378169 69.893687 0.401833 16.037467 2.756033 0.959862 3.431091 3.841899 2.678127 True True True True True True 69.299930 0.379375 15.675434 2.805987 1.408777 3.599436 4.258715 2.572347 0.0 0 0.0 0.0 0.0 0.0
1 Permissive_positive 14.786599 True 1276.842769 3.692769 4.881374 0.539418 0.853850 59.635015 0.940393 19.167929 4.871097 2.992865 5.856037 4.394051 2.142614 True True True True True True 62.700096 0.598123 17.082901 4.360429 3.670163 6.234633 4.140009 1.213647 0.0 1 0.0 0.0 0.0 0.0
2 Strong_positive 1.483696 True 1121.009366 -12.140634 2.267972 0.732973 0.364307 72.840975 0.262233 14.364388 2.023597 0.252214 1.611477 4.526237 4.118879 True True True True True True 73.812642 0.284803 13.799921 1.924439 0.362842 1.399290 4.134659 4.281403 0.0 2 0.0 0.0 0.0 0.0
3 Permissive_positive 8.305913 True 1289.833057 66.683057 5.757290 0.407235 1.455582 57.456685 1.030918 19.591490 5.720371 3.308518 6.313887 4.546906 2.031226 True True True True True True 59.888020 0.778866 18.175961 5.804112 3.697594 6.364292 4.139059 1.152095 0.0 3 0.0 0.0 0.0 0.0
4 Strong_positive 0.799768 True 1110.734404 -12.415596 1.259607 0.814489 0.227763 72.458598 0.246746 14.493137 2.238104 0.226659 1.587819 5.066988 3.681950 True True True True True True 73.034776 0.234337 14.569193 2.082972 0.196227 0.948193 4.900449 4.033852 0.0 4 0.0 0.0 0.0 0.0 
[9]:

## What about using a fixed value of T_K_guess if you dont know?
df_out=pt.calculate_CHOMPI(liq_comps=Liq,  deltaNNO=all['∆NNO (log units)'],
                            T_K_guess=1200+273.15, N_rep=100)
df_out.head()

[9]:
final_assessment SSR In Cali Range? T_K_calc T_K_residual P_kbar_calc XH2O_mol_calc XCO2XH2O SiO2_calc TiO2_calc Al2O3_calc FeOt_calc MgO_calc CaO_calc Na2O_calc K2O_calc CHOMPI (SSI<6?) Pass_Cali_test_SiO2? Pass_Cali_test_Al2O3? Pass_Cali_test_MgO? Pass_Cali_test_Na2O? Pass_Cali_test_K2O? SiO2_Liq TiO2_Liq Al2O3_Liq FeOt_Liq MgO_Liq CaO_Liq Na2O_Liq K2O_Liq Fe3Fet_Liq Sample_ID_Liq NiO_Liq CoO_Liq CO2_Liq H2O_Liq
0 Strong_positive 0.890216 True 1173.709528 -299.440472 3.504459 0.725600 0.378169 69.893687 0.401833 16.037467 2.756033 0.959862 3.431091 3.841899 2.678127 True True True True True True 69.299930 0.379375 15.675434 2.805987 1.408777 3.599436 4.258715 2.572347 0.0 0 0.0 0.0 0.0 0.0
1 Permissive_positive 14.786599 True 1276.842769 -196.307231 4.881374 0.539418 0.853850 59.635015 0.940393 19.167929 4.871097 2.992865 5.856037 4.394051 2.142614 True True True True True True 62.700096 0.598123 17.082901 4.360429 3.670163 6.234633 4.140009 1.213647 0.0 1 0.0 0.0 0.0 0.0
2 Strong_positive 1.483696 True 1121.009366 -352.140634 2.267972 0.732973 0.364307 72.840975 0.262233 14.364388 2.023597 0.252214 1.611477 4.526237 4.118879 True True True True True True 73.812642 0.284803 13.799921 1.924439 0.362842 1.399290 4.134659 4.281403 0.0 2 0.0 0.0 0.0 0.0
3 Permissive_positive 8.305913 True 1289.833057 -183.316943 5.757290 0.407235 1.455582 57.456685 1.030918 19.591490 5.720371 3.308518 6.313887 4.546906 2.031226 True True True True True True 59.888020 0.778866 18.175961 5.804112 3.697594 6.364292 4.139059 1.152095 0.0 3 0.0 0.0 0.0 0.0
4 Strong_positive 0.799768 True 1110.734404 -362.415596 1.259607 0.814489 0.227763 72.458598 0.246746 14.493137 2.238104 0.226659 1.587819 5.066988 3.681950 True True True True True True 73.034776 0.234337 14.569193 2.082972 0.196227 0.948193 4.900449 4.033852 0.0 4 0.0 0.0 0.0 0.0 
[12]:

## What about using a fixed value deltaNNO - lets try 0 and 2 to see how much they differ
df_out_NNO0=pt.calculate_CHOMPI(liq_comps=Liq,  deltaNNO=0,
                            T_K_guess=1200+273.15, N_rep=100)
display(df_out_NNO0.head())

df_out_NNO2=pt.calculate_CHOMPI(liq_comps=Liq,  deltaNNO=2,
                            T_K_guess=1200+273.15, N_rep=100)
display(df_out_NNO2.head())
final_assessment SSR In Cali Range? T_K_calc T_K_residual P_kbar_calc XH2O_mol_calc XCO2XH2O SiO2_calc TiO2_calc Al2O3_calc FeOt_calc MgO_calc CaO_calc Na2O_calc K2O_calc CHOMPI (SSI<6?) Pass_Cali_test_SiO2? Pass_Cali_test_Al2O3? Pass_Cali_test_MgO? Pass_Cali_test_Na2O? Pass_Cali_test_K2O? SiO2_Liq TiO2_Liq Al2O3_Liq FeOt_Liq MgO_Liq CaO_Liq Na2O_Liq K2O_Liq Fe3Fet_Liq Sample_ID_Liq NiO_Liq CoO_Liq CO2_Liq H2O_Liq
0 Strong_positive 0.933310 True 1173.709528 -299.440472 3.504459 0.725600 0.378169 69.893687 0.425833 16.037467 2.756033 0.915862 3.431091 3.841899 2.698127 True True True True True True 69.299930 0.379375 15.675434 2.805987 1.408777 3.599436 4.258715 2.572347 0.0 0 0.0 0.0 0.0 0.0
1 Permissive_positive 14.865142 True 1276.842769 -196.307231 4.881374 0.539418 0.853850 59.635015 0.964393 19.167929 4.871097 2.948865 5.856037 4.394051 2.162614 True True True True True True 62.700096 0.598123 17.082901 4.360429 3.670163 6.234633 4.140009 1.213647 0.0 1 0.0 0.0 0.0 0.0
2 Strong_positive 1.494860 True 1121.009366 -352.140634 2.267972 0.732973 0.364307 72.840975 0.286233 14.364388 2.023597 0.208214 1.611477 4.526237 4.138879 True True True True True True 73.812642 0.284803 13.799921 1.924439 0.362842 1.399290 4.134659 4.281403 0.0 2 0.0 0.0 0.0 0.0
3 Permissive_positive 8.354762 True 1289.833057 -183.316943 5.757290 0.407235 1.455582 57.456685 1.054918 19.591490 5.720371 3.264518 6.313887 4.546906 2.051226 True True True True True True 59.888020 0.778866 18.175961 5.804112 3.697594 6.364292 4.139059 1.152095 0.0 3 0.0 0.0 0.0 0.0
4 Strong_positive 0.800198 True 1110.734404 -362.415596 1.259607 0.814489 0.227763 72.458598 0.270746 14.493137 2.238104 0.182659 1.587819 5.066988 3.701950 True True True True True True 73.034776 0.234337 14.569193 2.082972 0.196227 0.948193 4.900449 4.033852 0.0 4 0.0 0.0 0.0 0.0
final_assessment SSR In Cali Range? T_K_calc T_K_residual P_kbar_calc XH2O_mol_calc XCO2XH2O SiO2_calc TiO2_calc Al2O3_calc FeOt_calc MgO_calc CaO_calc Na2O_calc K2O_calc CHOMPI (SSI<6?) Pass_Cali_test_SiO2? Pass_Cali_test_Al2O3? Pass_Cali_test_MgO? Pass_Cali_test_Na2O? Pass_Cali_test_K2O? SiO2_Liq TiO2_Liq Al2O3_Liq FeOt_Liq MgO_Liq CaO_Liq Na2O_Liq K2O_Liq Fe3Fet_Liq Sample_ID_Liq NiO_Liq CoO_Liq CO2_Liq H2O_Liq
0 Strong_positive 0.852145 True 1173.709528 -299.440472 3.504459 0.725600 0.378169 69.893687 0.377833 16.037467 2.756033 1.003862 3.431091 3.841899 2.658127 True True True True True True 69.299930 0.379375 15.675434 2.805987 1.408777 3.599436 4.258715 2.572347 0.0 0 0.0 0.0 0.0 0.0
1 Permissive_positive 14.713079 True 1276.842769 -196.307231 4.881374 0.539418 0.853850 59.635015 0.916393 19.167929 4.871097 3.036865 5.856037 4.394051 2.122614 True True True True True True 62.700096 0.598123 17.082901 4.360429 3.670163 6.234633 4.140009 1.213647 0.0 1 0.0 0.0 0.0 0.0
2 Strong_positive 1.477556 True 1121.009366 -352.140634 2.267972 0.732973 0.364307 72.840975 0.238233 14.364388 2.023597 0.296214 1.611477 4.526237 4.098879 True True True True True True 73.812642 0.284803 13.799921 1.924439 0.362842 1.399290 4.134659 4.281403 0.0 2 0.0 0.0 0.0 0.0
3 Permissive_positive 8.262088 True 1289.833057 -183.316943 5.757290 0.407235 1.455582 57.456685 1.006918 19.591490 5.720371 3.352518 6.313887 4.546906 2.011226 True True True True True True 59.888020 0.778866 18.175961 5.804112 3.697594 6.364292 4.139059 1.152095 0.0 3 0.0 0.0 0.0 0.0
4 Strong_positive 0.804362 True 1110.734404 -362.415596 1.259607 0.814489 0.227763 72.458598 0.222746 14.493137 2.238104 0.270659 1.587819 5.066988 3.661950 True True True True True True 73.034776 0.234337 14.569193 2.082972 0.196227 0.948193 4.900449 4.033852 0.0 4 0.0 0.0 0.0 0.0 
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