SpectralRadex makes use of numpy's F2PY compiler to create a python module. Run RADEX from within your python scripts with no subprocesses, no input files, and no fuss. We've even updated the base code to modern fortran to remove COMMON blocks and prevent any multiprocessing concerns. Use Python dictionaries to set parameters and receive results as pandas dataframes. Check our readthedocs for an API guide to the functions we built around the core RADEX functionality.
RADEX calculates the excitation temperature of every transition and the optical depth at line centre. SpectralRadex uses this output to generate model spectra by assuming the line profiles are Gaussian with a FWHM given by the linewidth parameter used by RADEX. By simply suppling the frequency values of your spectra, you can fit your data directly without assuming LTE.
History Independent Tracers
A lot of UCLCHEM work revolves around interpreting molecular observations to understand the underlying physical conditions of some gas. In our HITs paper, we describe a method for determining which observations will most constrain parameter of interest.
As a result of this work, you can use our HITs website to plan your own observations. Simply specify the parameter you'd like to measure and it will suggest the molecular transitions that will most constrain that parameter when you try to model it with RADEX and UCLCHEM.