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 git@github.com: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
Metadata
Release files for gwemopt 0.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gwemopt-0.4.2.tar.gz | 119.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gwemopt-0.4.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 239.8 MB
Release files / gwemopt-0.4.2.tar.gz
| Download URL | gwemopt-0.4.2.tar.gz |
|---|---|
| Size | 119.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.20
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Release files / gwemopt-0.4.2-py3-none-any.whl
| Download URL | gwemopt-0.4.2-py3-none-any.whl |
|---|---|
| Size | 120.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.20
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