Welcome to opac_mixer’s documentation!

There is a pressing need for fast opacity mixing in the correlated-k approximation. This python package builds a framework for machine learning on grids of k-tables.

To get the most out of this code, start by installing the code (see Installation). Once installed, head over to Tutorial: Quick Start to see a quick explanation of how to use the code.

Finally, if you want to couple the code to your own radiative transfer, you might need to read in your own k-tables. Thats easy, and its explained in Tutorial: Add custom k-tables. You also need to write a short code passage to deploy the mixing in the radiative transfer solver (see Deployment in code).

If you find this work useful, please consider to cite the following paper: Schneider et al. (in review)

WARNING: The paper is not yet published, please do not use this code, before it is published

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