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RADIS

RADIS is a fast line-by-line code for high resolution infrared molecular spectra (emission / absorption, equilibrium / non-LTE) based on HITRAN/HITEMP/ExoMol. Atomic spectra from the NIST and Kurucz databases are also available.

RADIS includes post-processing tools to compare experimental spectra and spectra calculated with RADIS or other spectral codes.

Full user documentation (advanced install and examples) are available on the RADIS Website.

Getting Started

Install

Assuming you have Python installed with the Anaconda distribution you can use pip:

pip install radis

or mamba or conda via the conda-forge channel:

conda install radis -c conda-forge

That's it! You can now run your first example below. If you encounter any issue, or to upgrade the package later, please refer to the detailed installation procedure.

Quick Start

Calculate a CO equilibrium spectrum from the HITRAN database:

from radis import calc_spectrum
s = calc_spectrum(1900, 2300,         # cm-1
                  molecule='CO',
                  isotope='1,2,3',
                  pressure=1.01325,   # bar
                  Tgas=700,           # K
                  mole_fraction=0.1,
                  path_length=1,      # cm
                  databank='hitran'   # or 'hitemp'
                  )
s.apply_slit(0.5, 'nm')       # simulate an experimental slit
s.plot('radiance')

CO spectrum

Advanced use

The Quick Start examples automatically download the line databases from HITRAN-2016, which is valid for temperatures below 700 K. For high temperature cases, you may need to use other line databases such as HITEMP-2010 (typically T < 2000 K) or CDSD-4000 (T < 5000 K). HITEMP can also be downloaded automatically, or can be downloaded manually and described in a ~/radis.json Configuration file.

More complex examples will require to use the SpectrumFactory class, which is the core of RADIS line-by-line calculations. calc_spectrum is a wrapper to SpectrumFactory for the simple cases.

Compare with experiments

Experimental spectra can be loaded using the experimental_spectrum function and compared with the plot_diff function. For instance:

from numpy import loadtxt
from radis import experimental_spectrum, plot_diff
w, I = loadtxt('my_file.txt').T    # assuming 2 columns
sexp = experimental_spectrum(w, I, Iunit='mW/cm2/sr/nm')
plot_diff(sexp, s)    # comparing with spectrum 's' calculated previously

Typical output of plot_diff:

comparison

Refer to the Examples section for more examples, and to the Spectrum page for more post-processing functions.

GPU Acceleration

RADIS supports GPU acceleration for super-fast computation of spectra. Refer to GPU Spectrum Calculation on RADIS for more details on GPU acceleration.

Try online (no installation needed!)

🌱 Radis-app

A simple web-app for RADIS under development - GitHub

Radis-app

🔬 RADIS-lab

An online environment for advanced spectrum processing and comparison with experimental data:

  • no need to install anything
  • use pre-configured line databases (HITEMP)
  • upload your data files, download your results !

RADIS-lab

See more on GitHub


Cite

Articles are available at Article Spectral Synthesis Algorithm

For reproducibility, do not forget to cite the line database used, and the spectroscopic constants if running nonequilibrium calculations. See How to cite?


Developer Guide

Contribute

Want to contribute to RADIS? Join the Slack community and we'll help you through the process. Want to get started immediately? Nice. Have a look at the Developer Guide.

Contributors Slack

RADIS internals are also described in the full documentation

License

The code is available on this repository under GNU LESSER GENERAL PUBLIC LICENSE (v3) License


References

Links

  • Documentation: Documentation Status

  • Help: Gitter Slack Q&A forum

  • Articles: Article Spectral Synthesis Algorithm

  • Source Code: GitHub Contributors License

  • Test Status: Tests Coverage Benchmarks

  • PyPI Repository: PyPI Downloads

  • Interactive Examples: radis_examples Examples Binder

  • Fitroom (for advanced multidimensional fitting).

Other Spectroscopic tools

See awesome-spectra awesome-spectra


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