molsim

Simulation tools for radio molecular spectra

molsim is a Python 3 package that provides an object-oriented interface for analyzing molecular spectra in high resolution astronomical observations and laboratory data. Key features of molsim include:

1. Line profile simulation
2. Velocity stacking
3. Interface to emcee for MCMC analysis
4. Matched filter analysis

For details about the methodology, particularly with respect to MCMC simulations, please refer to Loomis et al. 2020

If you use molsim for your analysis, please cite the Zenodo entry:

Setup instructions

For science-ready code, we recommend downloading one of the releases—these are verified to the best of our ability to be accurate. If there are any indications otherwise, please submit an issue!

For the latest build, either for testing or for contributing, please clone the development branch of this repository.

We recommend using conda for maintaining Python environments. Once you have acquired the code either from downloading a release or cloning the repository, you can create a new conda environment (called molsim) by running the following in the molsim directory:

conda env create -n molsim -f conda.yml

followed by:

conda activate molsim

to change the Anaconda environment, and then

pip install .

which will then install molsim into your Anaconda/Python installation.

For developers/testers, you should make a fork of this repository, and make changes to the development branch. To separate science/production and development environments, make a new conda environment with the following command:

conda env create -n molsim-dev -f conda.yml

followed by:

pip install -e .\[dev\]

The backslashes are required to escape the [] characters for zsh, although you may not have that issue on other shells/OS'. This will install molsim as a softlink so that changes are updated on the fly, while the [dev] option installs additional packages such as pytest, and black for formatting.

Use with notebook environments

A common way to interact with notebook environments is to have a base environment installation of jupyter. To use the Python kernel installed as part of the molsim environment with the base environment, using these steps:

1. conda activate molsim
2. python -m ipykernel install --user --name molsim --display-name "molsim-jupyter"

This links the IPython kernel with the jupyter installation. You'll then be able to start a notebook with the environment called "molsim-jupyter".

Contributions

The large majority of molsim was written by @bmcguir2, building on top of earlier code (simulate_lte).

The mcmc module was written by @laserkelvin, based heavily on earlier code by @ryanaloomis (see his repo here), which was used for the DR1 GOTHAM data analysis. The radex module was written by @cixue, implemented based on the RADEX non-LTE radiative transfer code, and accelerated with Numba to provide the high performance required for MCMC analysis.

Any issues, please submit an issue, reporting what you think should happen and what actually happens.