import Thermobar as pt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from pickle import dump
import pickle
Shea2022_Cali_out=pt.import_excel('Calibration_Datasets.xlsx',
sheet_name='Shea_2022')
Shea2022_Cali_Ol=Shea2022_Cali_out['Ols']
Shea2022_Cali_Liqs=Shea2022_Cali_out['Liqs']
Shea2022_Cali_input=Shea2022_Cali_out['my_input']
from pickle import dump
import pickle
Shea2022_Cali_input.to_pickle("Shea2022_Cali_input.pkl")
Ridolfi_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Ridolfi21_Cali')
Ridolfi_Cali_Amp=Ridolfi_Cali_out['Amps']
Ridolfi_Cali_input=Ridolfi_Cali_out['my_input']
sites=pt.calculate_sites_ridolfi(amp_comps=Ridolfi_Cali_Amp)
Combo=pd.concat([Ridolfi_Cali_input, sites], axis=1)
Combo.to_pickle("Ridolfi_Cali_input.pkl")
Ridolfi_Cali_Amp.to_pickle("Ridolfi_Cali_Amp.pkl")
Mutch_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Mutch2016_Amp')
Mutch_Cali_Amp=Mutch_Cali_out['Amps']
Mutch_Cali_input=Mutch_Cali_out['my_input']
sites=pt.calculate_sites_ridolfi(amp_comps=Mutch_Cali_Amp)
Combo=pd.concat([Mutch_Cali_input, sites], axis=1)
Combo.to_pickle("Mutch_Cali_input.pkl")
Mutch_Cali_Amp.to_pickle("Mutch_Cali_Amp.pkl")
Putirka16_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Putirka16_Cali')
Putirka16_Cali_Amp=Putirka16_Cali_out['Amps']
Putirka16_Cali_input=Putirka16_Cali_out['my_input']
sites=pt.calculate_sites_ridolfi(amp_comps=Putirka16_Cali_Amp)
Combo=pd.concat([Putirka16_Cali_input, sites], axis=1)
Combo.to_pickle("Putirka16_Cali_input.pkl")
Putirka16_Cali_Amp.to_pickle("Putirka16_Cali_Amp.pkl")
Zhang17_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Zhang2017_Cali')
Zhang17_Cali_Amp=Zhang17_Cali_out['Amps']
Zhang17_Cali_input=Zhang17_Cali_out['my_input']
sites=pt.calculate_sites_ridolfi(amp_comps=Zhang17_Cali_Amp)
Combo=pd.concat([Zhang17_Cali_input, sites], axis=1)
Combo.to_pickle("Zhang17_Cali_input.pkl")
Zhang17_Cali_Amp.to_pickle("Zhang17_Cali_Amp.pkl")
Jorgenson2022_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Jorgenson2022_Cali')
Jorgenson2022_Cali_Cpx=Jorgenson2022_Cali_out['Cpxs']
Jorgenson2022_Cali_Liqs=Jorgenson2022_Cali_out['Liqs']
Jorgenson2022_Cali_input=Jorgenson2022_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=Jorgenson2022_Cali_Cpx, liq_comps=Jorgenson2022_Cali_Liqs)
cpx_comps_Pet['P_kbar']=Jorgenson2022_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=Jorgenson2022_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("Jorgenson2022_Cali_input.pkl")
Jorgenson2022_Cali_Cpx.to_pickle("Jorgenson2022_Cali_Cpx.pkl")
C:\Users\penny\anaconda3\lib\site-packages\pandas\core\arraylike.py:364: RuntimeWarning: divide by zero encountered in log result = getattr(ufunc, method)(*inputs, **kwargs)
NeavePutirka_2017_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='NeavePutirka_2017_Cali')
NeavePutirka_2017_Cali_Cpx=NeavePutirka_2017_Cali_out['Cpxs']
NeavePutirka_2017_Cali_Liqs=NeavePutirka_2017_Cali_out['Liqs']
NeavePutirka_2017_Cali_input=NeavePutirka_2017_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=NeavePutirka_2017_Cali_Cpx, liq_comps=NeavePutirka_2017_Cali_Liqs)
cpx_comps_Pet['P_kbar']=NeavePutirka_2017_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=NeavePutirka_2017_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("NeavePutirka_2017_Cali_input.pkl")
NeavePutirka_2017_Cali_Cpx.to_pickle("NeavePutirka_2017_Cali_Cpx.pkl")
Masotta_2013_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Masotta_2013_Cali_Cpx')
Masotta_2013_Cali_Cpx=Masotta_2013_Cali_out['Cpxs']
Masotta_2013_Cali_Liqs=Masotta_2013_Cali_out['Liqs']
Masotta_2013_Cali_input=Masotta_2013_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=Masotta_2013_Cali_Cpx, liq_comps=Masotta_2013_Cali_Liqs)
cpx_comps_Pet['P_kbar']=Masotta_2013_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=Masotta_2013_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("Masotta_2013_Cali_input.pkl")
Masotta_2013_Cali_Cpx.to_pickle("Masotta_2013_Cali_Cpx.pkl")
Wang21_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Wang21_Cali_Cpx')
Wang21_Cali_Cpx=Wang21_Cali_out['Cpxs']
Wang21_Cali_Liqs=Wang21_Cali_out['Liqs']
Wang21_Cali_input=Wang21_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=Wang21_Cali_Cpx, liq_comps=Wang21_Cali_Liqs)
cpx_comps_Pet['P_kbar']=Wang21_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=Wang21_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("Wang21_Cali_input.pkl")
Wang21_Cali_Cpx.to_pickle("Wang21_Cali_Cpx.pkl")
Brugman_2019_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Brugman19_Cali')
Brugman_2019_Cali_Cpx=Brugman_2019_Cali_out['Cpxs']
Brugman_2019_Cali_Liqs=Brugman_2019_Cali_out['Liqs']
Brugman_2019_Cali_input=Brugman_2019_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=Brugman_2019_Cali_Cpx, liq_comps=Brugman_2019_Cali_Liqs)
cpx_comps_Pet['P_kbar']=Brugman_2019_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=Brugman_2019_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("Brugman_2019_Cali_input.pkl")
Brugman_2019_Cali_Cpx.to_pickle("Brugman_2019_Cali_Cpx.pkl")
Petrelli20_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Petrelli20_Cali')
Petrelli20_Cali_Cpx=Petrelli20_Cali_out['Cpxs']
Petrelli20_Cali_Liqs=Petrelli20_Cali_out['Liqs']
Petrelli20_Cali_input=Petrelli20_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=Petrelli20_Cali_Cpx, liq_comps=Petrelli20_Cali_Liqs)
cpx_comps_Pet['P_kbar']=Petrelli20_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=Petrelli20_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("Petrelli20_Cali_input.pkl")
Petrelli20_Cali_Cpx.to_pickle("Petrelli20_Cali_Cpx.pkl")
Putirka2008_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Putirka2008_CpxLiq')
Putirka2008_Cali_Cpx=Putirka2008_Cali_out['Cpxs']
Putirka2008_Cali_Liqs=Putirka2008_Cali_out['Liqs']
Putirka2008_Cali_input=Putirka2008_Cali_out['my_input']
# Calculating Cpx components to also save.
cpx_comps_Pet=pt.calculate_clinopyroxene_liquid_components(cpx_comps=Putirka2008_Cali_Cpx, liq_comps=Putirka2008_Cali_Liqs)
cpx_comps_Pet['P_kbar']=Putirka2008_Cali_input['P_kbar']
cpx_comps_Pet['T_K']=Putirka2008_Cali_input['T_K']
from pickle import dump
import pickle
cpx_comps_Pet.to_pickle("Putirka2008_Cali_input.pkl")
Putirka2008_Cali_Cpx.to_pickle("Putirka2008_Cali_Cpx.pkl")
C:\Users\penny\anaconda3\lib\site-packages\pandas\core\arraylike.py:364: RuntimeWarning: divide by zero encountered in log result = getattr(ufunc, method)(*inputs, **kwargs)
Waters_Lange2015_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Waters_Lange2015_Cali')
Waters_Lange2015_Cali_Amp=Waters_Lange2015_Cali_out['Plags']
Waters_Lange2015_Cali_input=Waters_Lange2015_Cali_out['my_input']
from pickle import dump
import pickle
Waters_Lange2015_Cali_input.to_pickle("Waters_Lange2015_Cali_input.pkl")
Waters_Lange2015_Cali_Amp.to_pickle("Waters_Lange2015_Cali_Amp.pkl")
Masotta2019_Cali_out=pt.import_excel('Calibration_Datasets.xlsx', sheet_name='Masotta2019_PlagLiq_Cali')
Masotta2019_Cali_Amp=Masotta2019_Cali_out['Plags']
Masotta2019_Cali_input=Masotta2019_Cali_out['my_input']
from pickle import dump
import pickle
Masotta2019_Cali_input.to_pickle("Masotta2019_Cali_input.pkl")
Masotta2019_Cali_Amp.to_pickle("Masotta2019_Cali_Amp.pkl")