pyIRoGlass 0.4.2

PyIRoGlass

PyIRoGlass

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.

Preprint

Find the preprint on EarthArXiv on for a more detailed description of the development and validation of the method.

Documentation

Read the documentation for a run-through of the PyIRoGlass code.

Run on the Cloud

If you do not have Python installed locally, run PyIRoGlass on 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. 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