Ol-Liq, Ol-Sp Functions

Thermobar.olivine_liquid_olivine_spinel_thermometry.H_Gavr2016(*, CaO_Liq, MgO_Liq, CaO_Ol)[source]

Olivine-Liquid hygrometer of Gavrilenko et al. (2016).

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Beatt93_ol(P, *, Den_Beat93)[source]

Olivine-Liquid thermometer: Beattie (1993). Putirka (2008) suggest this is the best olivine-liquid thermometer for anhydrous conditions at relatively low pressures.

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Beatt93_ol_HerzCorr(P, *, Den_Beat93)[source]

Olivine-Liquid thermometer: Beattie (1993) with correction of Herzberg and O’Hara (2002), eliminating systematic error at higher pressures Anhydrous SEE=±44°C Hydrous SEE=±53°C

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Coogan2014(P=None, *, Cr_No_sp, Al2O3_Ol, Al2O3_Sp)[source]

Aluminum-in-olivine thermometer from Coogan et al. 2014. doi: 10.1016/j.chemgeo.2014.01.004 Uses the Al2O3 content in Olivine, Al2O3 content of Spinel, and the Cr number of the spinel

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Pu2017(P=None, *, NiO_Ol_mol_frac, FeOt_Liq_mol_frac, MnO_Liq_mol_frac, MgO_Liq_mol_frac, CaO_Liq_mol_frac, NiO_Liq_mol_frac, Al2O3_Liq_mol_frac, TiO2_Liq_mol_frac, SiO2_Liq_mol_frac)[source]

Olivine-Liquid thermometer: Pu et al. (2017). Uses D Ni (ol-melt) rather than D Mg (ol-melt), meaning this thermometer has far less sensitivity to H2O or pressure at 0-1 GPa. SEE=±29°C

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Pu2021(P, *, NiO_Ol_mol_frac, FeOt_Liq_mol_frac, MnO_Liq_mol_frac, MgO_Liq_mol_frac, CaO_Liq_mol_frac, NiO_Liq_mol_frac, Al2O3_Liq_mol_frac, TiO2_Liq_mol_frac, SiO2_Liq_mol_frac)[source]

Olivine-Liquid thermometer: Pu et al. (2017), with the pressure correction of Pu et al. (2021). Uses D Ni (ol-melt) rather than D Mg (ol-melt), meaning this thermometer has far less sensitivity to melt H2O than other olivine-liquid thermometers. SEE=±45°C (for the 2017 expression).

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Put2008_eq19(P, *, DMg_Meas, CNML, CSiO2L, NF)[source]

Olivine-Liquid thermometer originally from Beattie, (1993), form from Putirka (2008)

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Put2008_eq21(P, *, DMg_Meas, Na2O_Liq, K2O_Liq, H2O_Liq)[source]

Olivine-Liquid thermometer: Putirka (2008), equation 21 (originally Putirka et al., 2007, Eq 2). Recalibration of Beattie (1993) to account for the pressures sensitivity noted by Herzberg and O’Hara (2002), and esliminates the systematic error of Beattie (1993) for hydrous compositions. Anhydrous SEE=±53°C Hydrous SEE=±36°C

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Put2008_eq22(P, *, DMg_Meas, CNML, CSiO2L, NF, H2O_Liq)[source]

Olivine-Liquid thermometer: Putirka (2008), equation 22 (originally Putirka et al., 2007, Eq 4). Recalibration of Beattie (1993) to account for the pressures sensitivity noted by Herzberg and O’Hara (2002), and esliminates the systematic error of Beattie (1993) for hydrous compositions. Putirka (2008) suggest this is the best olivine-liquid thermometer for hydrous melts. Anhydrous SEE±45°C Hydrous SEE±29°C

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Sisson1992(P, *, KdMg_TSG1992)[source]

Olivine-Liquid thermometer: Sisson and Grove (1992). Putirka (2008) suggests this thermometer is best in peridotitic systems containing 2-25 wt% CO2.

Thermobar.olivine_liquid_olivine_spinel_thermometry.T_Wan2008(P=None, *, Cr_No_sp, Al2O3_Ol, Al2O3_Sp)[source]

Aluminum-in-olivine thermometer from Wan et al. (2008) - doi: 10.2138/am.2008.2758 Uses the Al2O3 content in Olivine, Al2O3 content of Spinel, and the Cr number of the spinel

Thermobar.olivine_liquid_olivine_spinel_thermometry.calculate_ol_liq_hygr(*, liq_comps=None, ol_comps=None, equationH=None, eq_tests=False, P=None, T=None, meltmatch=None, equationT=None, Fe3Fet_Liq=None)[source]

Olivine-liquid hygrometer. Returns the estimated H2O content in wt%

Parameters
liq_comps: pandas.DataFrame

liquid compositions with column headings SiO2_Liq, MgO_Liq etc.

ol_comps: pandas.DataFrame

Olivine compositions with column headings SiO2_Ol, MgO_Ol etc.

equationH: str

H_Gavr2016 (P-independent, H2O_independent)

eq_tests: bool

if true, calculates Kd for olivine-liquid pairs. Other inputs for these tests:

P: int, flt, pandas.Series (needed for Toplis Kd calculation). If nothing inputted, P set to 1 kbar

T: int, flt, pandas.Series (needed for Toplis KD calculation). Can also specify equationT=”” to calculate temperature using an olivine-liquid thermometer, using the calculated H2O content from the hygrometer

Fe3Fet_Liq: int, flt, pandas.Series. As Kd calculated using only Fe2 in the Liq.

pandas.core.series.Series

H2O content in wt%.

Thermobar.olivine_liquid_olivine_spinel_thermometry.calculate_ol_liq_hygr_matching(*, liq_comps, ol_comps, equationH, eq_tests=False, T=None, equationT=None, P=None, Fe3Fet_Liq=None, iterations=30)[source]

Evaluates all possible Ol-liq pairs for H2O returns H2O and equilibrium test values.

Parameters:
  • ol_comps (pandas.DataFrame) – Panda DataFrame of Ol compositions with column headings SiO2_Ol, CaO_Ol etc.

  • liq_comps (pandas.DataFrame) – Panda DataFrame of liq compositions with column headings SiO2_Liq etc.

  • EquationH (str) –

    Choose from:

    H_Gavr2016 (P-independent, T-independent)

iterations: int

number of times to iterate temperature and H2O. Default 30.

Returns:

H2O (wt%) for all posible ol-liq matches, along with equilibrium tests, components and input mineral compositions

Return type:

pandas.DataFrame

Thermobar.olivine_liquid_olivine_spinel_thermometry.calculate_ol_liq_temp(*, equationT, liq_comps=None, ol_comps=None, meltmatch=None, P=None, NiO_Ol_Mol=None, H2O_Liq=None, Fe3Fet_Liq=None, eq_tests=False)[source]

Olivine-liquid thermometers. Returns the temperature in Kelvin, along with calculations of Kd-Fe-Mg equilibrium tests.

Parameters
liq_comps: pandas.DataFrame

liquid compositions with column headings SiO2_Liq, MgO_Liq etc.

ol_comps: pandas.DataFrame

Olivine compositions with column headings SiO2_Ol, MgO_Ol etc.

equationT: str

T_Beatt93_ol (P-dependent, H2O_independent) T_Beatt93_ol_HerzCorr (P-dependent, H2O_independent) T_Put2008_eq21 (P-dependent, H2O-dependent) T_Put2008_eq22 (P-dependent, H2O-dependent) T_Sisson1992 (P-dependent, H2O_independent) T_Pu2017 (P-independent, H2O_independent) T_Pu2021 (P-dependent, H2O_independent)

P: float, int, pandas.Series, str (“Solve”)

Pressure in kbar Only needed for P-sensitive thermometers. If enter P=”Solve”, returns a partial function Else, enter an integer, float, or panda series

H2O_Liq: optional.

If None, uses H2O_Liq column from input. If int, float, pandas.Series, uses this instead of H2O_Liq Column

pandas.core.series.Series

Temperatures in kelvin.

Thermobar.olivine_liquid_olivine_spinel_thermometry.calculate_ol_liq_temp_matching(*, liq_comps, ol_comps, eq_tests=False, equationT=None, P=None, H2O_Liq=None, Fe3Fet_Liq=None, iterations=30)[source]

Evaluates all possible Ol-liq pairs for temperature, and calculates equilibrium tests

Parameters:
  • ol_comps (pandas.DataFrame) – Panda DataFrame of Ol compositions with column headings SiO2_Ol, CaO_Ol etc.

  • liq_comps (pandas.DataFrame) – Panda DataFrame of liq compositions with column headings SiO2_Liq etc.

  • equationT (str) – T_Beatt93_ol (P-dependent, H2O_independent) T_Beatt93_ol_HerzCorr (P-dependent, H2O_independent) T_Put2008_eq21 (P-dependent, H2O-dependent) T_Put2008_eq22 (P-dependent, H2O-dependent) T_Sisson1992 (P-dependent, H2O_independent) T_Pu2017 (P-independent, H2O_independent) T_Pu2021 (P-dependent, H2O_independent)

  • P (float, int, pandas.Series, str ("Solve")) – Pressure in kbar Only needed for P-sensitive thermometers. If enter P=”Solve”, returns a partial function Else, enter an integer, float, or panda series

  • H2O_Liq (optional.) – If None, uses H2O_Liq column from input. If int, float, pandas.Series, uses this instead of H2O_Liq Column

iterations: int

number of times to iterate temperature and H2O. Default 30.

Returns:

Temp (K) for all posible ol-liq matches, along with equilibrium tests, components and input mineral compositions

Return type:

pandas.DataFrame

Thermobar.olivine_liquid_olivine_spinel_thermometry.calculate_ol_sp_temp(ol_comps, sp_comps, equationT)[source]

calculates temperatures from olivine-spinel pairs.

Parameters
ol_comps: pandas.DataFrame

liquid compositions with column headings SiO2_Ol, MgO_Ol etc

sp_comps: pandas.DataFrame

spinel compositions with column headings SiO2_Sp, MgO_Sp etc

equationT: str
Equation choices:
T_Wan2008
T_Coogan2014
pandas series

Temperature in K