pymcfost is a python package that provides an interface to the 3D radiative transfer code mcfost.
pymcfost offers (or will offer) the following functionalities:
- set up continuum and line models
- read a single model or library of models
- plot basic quantities, e.g. density structures, temperature maps
- plot observables : SEDs, image (with convolution), polarisation maps, visibilities, channels maps (with spatial and spectral convolution), moment maps.
- convert units, e.g. W.m-2 to Jy or brightness temperature
- provides an interface to the ALMA CASA simulator
- consistent interface with the casa python package to compare observations with models (ask C. Pinte)
- (TBD) read and plot dust models
- (TBD) direct interface to the Mie, DHS and aggregates dust properties calculations
- (TBD) direct interface to the ML chemical predictions
- (TBD) direct interface to the Voronoi mesh interface (available via fits files only so far)
- (TBD) consistent interface with PLONK (Phantom/splash python interface)
pymcfost was born as an attempt to port in python the functions that were available in the yorick-mcfost code. The goal is to provide a simple and light interface to explore a single (or a few) model(s).
The fitting routines of the yorick interface are yet to be ported into pymcfost. An alternative python distribution is available at https://github.com/swolff9/mcfost-python . It is more tailored towards handling large grid of models and model fitting.
git clone https://github.com/cpinte/pymcfost.git
cd pymcfost
python3 setup.py install
If you don't have the sudo rights, use python3 setup.py install --user.
To install in developer mode: (i.e. using symlinks to point directly at this directory, so that code changes here are immediately available without needing to repeat the above step):
python3 setup.py develop
- python >= 3.6 vs python 2.x
- only parameter file >= 3.0
- handles parameter files with mutiple zones, dust population, molecules, stars, etc. Parameter files are stored in objects rather than dicts, allowing more flexibility.
- does not and will not handle observational data, only models