Library to handle radiative opacities from various sources for atmospheric applications
Project description
Exo_k
Author: Jeremy Leconte (CNRS/LAB/Univ. Bordeaux)
Exo_k
is a Python 3 based library to handle radiative opacities from various sources for atmospheric applications.
It enables you to:
-
Interpolate efficiently and easily in correlated-k and cross section tables.
-
Convert easily correlated-k and cross section tables from one format to another (hdf5, LMDZ GCM, Exomol, Nemesis, PetitCode, TauREx, ExoREM, ARCIS, etc.).
-
Adapt precomputed correlated-k tables to your needs by changing:
- the resolution and quadrature (g) grid,
- the pressure/temperature grid.
-
Create tables for a mix of gases using tables for individual gases.
-
Create your own tables from high-resolution spectra (for example from K-spectrum, Helios-K, etc.).
-
Use your data in an integrated radiative transfer framework to simulate planetary atmospheres.
For a complete online documentation, checkout: http://perso.astrophy.u-bordeaux.fr/~jleconte/exo_k-doc/index.html
In this repository, you'll find a tutorial jupyter notebook that will show you how to do all that with concrete examples that you can run on your own machine. Many important concepts and options are presented along the way.
Enjoy!
J. Leconte
Acknowledgements
If you use this library in your research, please acknowledge it by citing Leconte (2021):
- Spectral binning of precomputed correlated-k coefficients. Astronomy and Astrophysics 645. Leconte, J. 2021. doi:10.1051/0004-6361/202039040
This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 679030/WHIPLASH).
The framework for this documentation has been developped by Aurelien Falco using Sphinx.
last release (see past releases below)
v1.0.2 (June 2021): Adds a few missing dependencies. Enables computation of thermal emission spectra with scattering through the two-stream method (full documentation pending). Enables creating Xtables for a mix of gases (CIA can be added as well). Solves some issues with the 2018 Hitran CIA format.
Installation
Exo_k can be installed using pip (without cloning the repository; dependencies should be downloaded automatically):
pip install exo_k
Or by running the setup.py script in the cloned repository:
python setup.py install
Usage
To learn how to use exo_k
, you can follow the tutorial jupyter notebook.
Have fun!
Links
- Project homepage: http://perso.astrophy.u-bordeaux.fr/~jleconte/
- Code repository: https://forge.oasu.u-bordeaux.fr/jleconte/exo_k-public
- Documentation: http://perso.astrophy.u-bordeaux.fr/~jleconte/exo_k-doc/index.html
- Contact: jeremy.leconte at u-bordeaux.fr
past releases
v1.0.1 (Jan 2021): Solves a binary/string conversion issue introduced by version 3 of h5py. Enables linear interpolation in pressure (default is log). Enables creation of empty tables to be filled later and extension of the spectral range of existing tables.
v1.0.0 (Dec 2020): Finally our first official version. Creation of a
'examples' notebook with fully worked out use cases for the Exo_k
.
v0.0.5 (Oct 2020): Ensures compatibility with latest Exomol correlated-k and cross-section tables.
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