gwemopt 0.4.2

A python package for GW-EM Followup Optimization

gwemopt

Gravitational-wave Electromagnetic Optimization

Citing gwemopt

When utilizing this code for a publication, kindly make a reference to the package by its name, gwemopt, and a citation to the software papers Optimizing searches for electromagnetic counterparts of gravitational wave triggers and Teamwork Makes the Dream Work: Optimizing Multi-Telescope Observations of Gravitational-Wave Counterparts. The BibTeX entry for the papers are:

@article{Coughlin:2018lta,
    author = "Coughlin, Michael W. and others",
    title = "{Optimizing searches for electromagnetic counterparts of gravitational wave triggers}",
    eprint = "1803.02255",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.IM",
    doi = "10.1093/mnras/sty1066",
    journal = "Mon. Not. Roy. Astron. Soc.",
    volume = "478",
    number = "1",
    pages = "692--702",
    year = "2018"
}

and

@article{Coughlin:2019qkn,
    author = "Coughlin, Michael W. and others",
    title = "{Optimizing multitelescope observations of gravitational-wave counterparts}",
    eprint = "1909.01244",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.IM",
    doi = "10.1093/mnras/stz2485",
    journal = "Mon. Not. Roy. Astron. Soc.",
    volume = "489",
    number = "4",
    pages = "5775--5783",
    year = "2019"
}

and for the ability to balance field exposures Dynamic scheduling: target of opportunity observations of gravitational wave events.

@article{Almualla:2020hbs,
    author = {Almualla, Mouza and Coughlin, Michael W and Anand, Shreya and Alqassimi, Khalid and Guessoum, Nidhal and Singer, Leo P},
    title = {Dynamic scheduling: target of opportunity observations of gravitational wave events},
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {495},
    number = {4},
    pages = {4366-4371},
    year = {2020},
    month = {06},
    issn = {0035-8711},
    doi = {10.1093/mnras/staa1498},
    url = {https://doi.org/10.1093/mnras/staa1498},
    eprint = {https://academic.oup.com/mnras/article-pdf/495/4/4366/33371783/staa1498.pdf},
}

Setting up the environment

If you want the latest version, we recommend creating a clean environment:

conda create -n gwemopt python=3.11
git clone [e-mail]:skyportal/gwemopt.git
cd gwemopt
pip install -e .
pre-commit install

or if you just want the latest version released on PyPI:

pip install gwemopt

If you run into dependency issues, you can try installing dependencies via conda:

conda install numpy scipy matplotlib astropy h5py shapely
conda install -c astropy astroquery
conda install -c conda-forge voeventlib astropy-healpix python-ligo-lw igwn-segments ligo.skymap ffmpeg

And then run pip install -e . again.

Usage

Once installed, You can use gwemopt via the command line:

gwemopt-run ....

where ... corresponds to the various arguments.

Tests

To run the tests, you'll first need to install gwemopt with the testing dependencies:

pip install -e ".[test]"

Then you can run the tests using:

coverage run -m pytest -v -s