PyMolFit

PyMolFit is an independent pure-Python package for modelling and correcting telluric absorption in astronomical spectra. It is based on the concepts, workflow, and radiative-transfer approach of the original ESO Molecfit, with a Python API for both spectrum files and wavelength-flux arrays.

PyMolFit does not import or run Molecfit and is not affiliated with or endorsed by ESO.

Installation

python -m pip install pymolfit

Install plotting support for the tutorial notebooks:

python -m pip install "pymolfit[plot]" ipympl

PyMolFit supports Python 3.10 and newer.

Correct A Spectrum File

The main API is correct():

from pymolfit import correct

result = correct(
    input_path="spectrum.fits",
    wavelength_medium="air",
)

wavelength = result.corrected.wavelength
corrected_flux = result.corrected.flux

Use wavelength_medium="vacuum" for vacuum wavelengths. The argument may be omitted only when the FITS metadata declares the wavelength medium unambiguously.

Results remain in memory unless an output is requested:

from pymolfit import save_corrected_txt, save_fit_product_ecsv

save_corrected_txt(result, "corrected_spectrum.txt")
save_fit_product_ecsv(result, "fit_product.ecsv")

The text file contains a compact corrected spectrum. The ECSV product also contains the fitted transmission, model, masks, metadata, and provenance.

Correct Wavelength And Flux Arrays

Arrays do not have a FITS header, so observing metadata is supplied with an Observation:

from pymolfit import Observation, correct

observation = Observation(
    time="2025-09-28T07:44:51",
    latitude_deg=-24.627,
    longitude_deg=-70.404,
    altitude_m=2635.0,
    airmass=1.18,
    resolving_power=140_000,
    wavelength_frame="observatory",
    instrument="ESPRESSO",
)

result = correct(
    wavelength=wavelength,
    flux=flux,
    wavelength_unit="angstrom",
    wavelength_medium="air",
    observation=observation,
)

wavelength_medium states whether the numbers are air or vacuum wavelengths. wavelength_frame separately states their velocity reference frame. Supported frames are observatory, barycentric, and heliocentric.

Tutorials

The runnable notebooks in tutorials/ cover:

1. Correcting part of a spectrum
2. Correcting a full spectrum
3. Expert parameters
4. Correcting wavelength-flux arrays

Start with Tutorial 1 for a short example or Tutorial 2 for a complete one-dimensional echelle spectrum.

Molecular And Atmospheric Data

The standard workflow automatically obtains the versioned AER molecular line catalogue, verifies its checksum, and caches it under ~/.cache/pymolfit/aer. It is not bundled in the Python wheel, and the normal workflow does not require a HITRAN API key.

Users may instead provide their own HITRAN .par files or other supported line and continuum data.

Scientific Basis And References

PyMolFit builds on the methods and scientific data developed by several projects. Publications using PyMolFit should cite the relevant upstream resources:

• ESO Molecfit: Smette et al. 2015, A&A 576, A77 and Kausch et al. 2015, A&A 576, A78
• AER LBLRTM line-by-line radiative-transfer methods and data
• AER MT_CKD atmospheric continuum model
• HITRAN molecular spectroscopic data
• MIPAS atmospheric reference profiles
• NOAA GDAS meteorological profiles

PyMolFit uses NumPy, SciPy, and Astropy.

Development

git clone https://github.com/nikolasvalsamidis97/PyMolFit.git
cd PyMolFit
python -m pip install -e ".[dev,plot]"
python -m pytest

Report problems through the GitHub issue tracker.

Licensing And Third-Party Data

PyMolFit's original Python code is available under the BSD 3-Clause License. Scientific datasets and derived coefficient tables retain their upstream terms and attribution requirements. See THIRD_PARTY_NOTICES.md for the included and automatically downloaded data.