Metadata-Version: 2.4
Name: thermobar
Version: 1.0.67
Summary: Thermobar
Home-page: https://github.com/PennyWieser/Thermobar
Author: Penny Wieser et al. 
Author-email: penny.wieser@gmail.com
License: MIT (with GUI use clause, see LICENSE file)
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: python-ternary
Requires-Dist: matplotlib
Requires-Dist: scikit-learn>=1.3
Requires-Dist: scipy
Requires-Dist: tqdm
Requires-Dist: statsmodels
Requires-Dist: openpyxl
Requires-Dist: pathlib
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Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
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[![PyPI](https://badgen.net/pypi/v/Thermobar)](https://pypi.org/project/Thermobar/)
[![Build Status](https://github.com/PennyWieser/Thermobar/actions/workflows/main.yml/badge.svg?branch=main)](https://github.com/PennyWieser/Thermobar/actions/workflows/main.yml)
[![codecov](https://codecov.io/gh/PennyWieser/Thermobar/branch/main/graph/badge.svg)](https://codecov.io/gh/PennyWieser/Thermobar/branch/main)

Thermobar is a python tool for thermobarometry, chemometry and mineral equilibrium.
Thermobar allows users to easily choose between more than 100 popular parameterizations involving liquid, olivine-liquid, olivine-spinel, 
pyroxene only, pyroxene-liquid, two pyroxene, feldspar-liquid, two feldspar, amphibole and amphibole-liquid, garnet and biotite equilibrium. 

It can be downloaded via pip, on Github (you are here!), and extensive documentation and 
example videos and Jupyter Notebooks are available at https://thermobar.readthedocs.io/en/latest/index.html

If you want to use Machine learning models, you will need to pip install a separate package (the pkl and onnx files are too big for one release). Please see the instructions here:
https://thermobar.readthedocs.io/en/latest/Examples/Cpx_Cpx_Liq_Thermobarometry/MachineLearning_Cpx_Liq_Thermobarometry.html


Find more information in Volcanica - and please make sure you cite this work!!!
https://www.jvolcanica.org/ojs/index.php/volcanica/article/view/161
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Want your model in Thermobar?
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Getting your model into Thermobar will hopefully help to increase usage. 
I am happy to help you with this. You will need to supply me with your scripts or excel spreadsheet showing how the model works, 
your calibration dataset, and some example calculations for benchmarking. 

For Machine Learning models, please see the read the docs page. 
