Exo_k¶
About Exo_k¶
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 spectral and quadrature (g) grids,
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.
On this website, you’ll find a ‘Getting Started’ section that will show you how to do all that with concrete examples that you can run on your own machine through the tutorial jupyter notebook provided in the repository. Many important concepts and options are presented along the way.
The API reference section also lists systematically all the classes and methods available in the library and details the necessary inputs and available options for each of them. This documentation is searchable with the search bar in the top left corner.
Enjoy!
Leconte
Recent releases¶
v1.0.1 (Jan 2021): Solves a binary/string conversion issue on some platforms. Enables linear interpolation in pressure (default is log). Enables creation of empty tables to filled later and spectral extension of existing tables.
v1.0.0 (Dec 2020): Finally our first official version. Creation of a ‘Neat examples’ section 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 (Chubb et al. 2020).
Doc Contents¶
- Getting exo_k
- Basic principles and objects
- Notes on units and formats
- Getting started
- First steps with
exo_k
- Dealing with
Ktable()
objects - Dealing with mixes: The
Kdatabase()
object - Loading and creating correlated-k tables to use with LMDZ GCM
- Creating corr-k from
High_resolution
spectra - Dealing with cross sections:
Xtable()
objects - Dealing with continua:
Cia_table()
andCIAdatabase()
objects - How to use
exo_k
as an opacity interpolator inside your code: TheGas_mix
object - The
Atm
class: An integrated atmospheric radiative-transfer model
- First steps with
- Where to find data to use with Exo_k?
- Neat examples
- Some worked out use-cases for
exo_k
- Loading ExoMol files and changing their resolution before saving them in different formats
- Creating k-coefficients for a new species not in ExoMol from high-resolution spectra from the petitRADTRANS database
- Modelling transit spectra: sampled cross sections vs. k-coefficients (Leconte, A&A, 2020)
- Some worked out use-cases for
- API reference
- Looking for a function? (Index)
- How to contribute
- Building the documentation
Other 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
Acknowledgements¶
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.