Metadata-Version: 2.4
Name: PyIRoGlass
Version: 0.6.5
Summary: PyIRoGlass
Home-page: https://github.com/sarahshi/PyIRoGlass
Author: Sarah Shi
Author-email: sarah.c.shi@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: mc3
Requires-Dist: pykrige
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
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# PyIRoGlass
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[![Python 3.8](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/release/python-380/)
[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
[![DOI](https://zenodo.org/badge/406815894.svg)](https://zenodo.org/doi/10.5281/zenodo.10883628)

PyIRoGlass is a Bayesian MCMC-founded Python algorithm, written in the open-source language Python3, for determining $\mathrm{H_2O}$ and $\mathrm{CO_2}$ species concentrations in the transmission FTIR spectra of basaltic to andesitic glasses. We leverage a database of naturally degassed melt inclusions and back-arc basin basalts to delineate the fundamental shape and variability of the baseline underlying the $\mathrm{CO_{3}^{2-}}$ and $\mathrm{H_2O_{m, 1635}}$ peaks, in the mid-infrared region. PyIRoGlass employs Bayesian inference and Markov Chain Monte Carlo sampling to fit all probable baselines and peaks, solving for best-fit parameters and capturing covariance to offer robust uncertainty estimates.

## Manuscript
Find the [PyIRoGlass manuscript](https://doi.org/10.30909/vol.07.02.471501) published at Volcanica on for a more detailed description of the development and validation of the method. If you use this package in your work, please cite: 

```console
Shi, S., Towbin, W. H., Plank, T., Barth, A., Rasmussen, D., Moussallam, Y., Lee, H. J. and Menke, W. (2024) “PyIRoGlass: An open-source, Bayesian MCMC algorithm for fitting baselines to FTIR spectra of basaltic-andesitic glasses”, Volcanica, 7(2), pp. 471–501. doi: 10.30909/vol.07.02.471501.
```

```
@article{Shietal2024,
    doi       = {10.30909/vol.07.02.471501},
    url       = {https://doi.org/10.30909/vol.07.02.471501},
    year      = {2024},
    volume    = {7},
    number    = {2},
    pages     = {471-501},
    author    = {Shi, Sarah C. and Towbin, W. Henry and Plank, Terry and Barth, Anna and Rasmussen, Daniel and Moussallam, Yves and Lee, Hyun Joo and Menke, William},
    title     = {PyIRoGlass: An open-source, Bayesian MCMC algorithm for fitting baselines to FTIR spectra of basaltic-andesitic glasses},
    journal   = {Volcanica}
}
```

## Documentation
Read the [documentation](https://pyiroglass.readthedocs.io/en/latest/) for a run-through of the PyIRoGlass code. 

## Run on the Cloud 
If you do not have Python installed locally or if you use a Windows computer (without Linux), please run PyIRoGlass on [VICTOR (Volcanology Infrastructure for Computational Tools and Resources)](https://hub.victorproject.org/hub/login?next=%2Fhub%2F) or on [Google Colab](https://colab.research.google.com/github/SarahShi/PyIRoGlass/blob/main/PyIRoGlass_RUN_colab.ipynb).

To run PyIRoGlass on VICTOR, use the ```victor setup``` command in the command line and select option 15 for PyIRoGlass. This will create an instance of PyIRoGlass in your local working directory. The VICTOR option will allow for more rapid processing than Google Colab. 

## Run and Install Locally
Obtain a version of Python between 3.8 and 3.12 if you do not already have it installed. PyIRoGlass can be installed with one line on Mac and Linux. Open terminal and type the following:

```
pip install PyIRoGlass
```

Make sure that you keep up with the latest version of PyIRoGlass. To upgrade to the latest version of PyIRoGlass, open terminal and type the following: 

```
pip install PyIRoGlass --upgrade
```
