This release is a pre-release and may not be stable for production use.
bilby NR
This Python package incorporates model accuracy into gravitational wave Bayesian analyses via the bilby Python package.
Installation
bilby_nr is currently available via PyPI and can be installed with:
$ pip install bilby_nr
Once bilby_nr has been installed, a custom version of bilby_pipe needs to
be installed with:
$ pip install 'bilby_pipe @ git+https://git.ligo.org/charlie.hoy/bilby_pipe.git@input_class'
This version needs to be installed because we are waiting for required code to
be merged into the main bilby_pipe code base. Please see the following merge
request for details:
* `bilby_pipe!583 <https://git.ligo.org/lscsoft/bilby_pipe/-/merge_requests/583>`_
For full installation instructions, see our documentation.
Usage in bilby_pipe
The functionality in bilby_nr can be used with bilby_pipe as you would with any other frequency domain source model. It simply requires the following options to be specified in your configuration file:
analysis_executable_parser=bilby_nr.bilby_pipe.create_parser
waveform-approximant=IMRPhenomXPHMST,IMRPhenomTPHM,SEOBNRv5PHM
frequency-domain-source-model = bilby_nr.source.multi_model_binary_black_hole
waveform-arguments-dict={'match_interpolant': 'bilby_nr.match.match_from_pade_pade_interpolant'}
Citing
If you find bilby_nr useful in your work please cite the following papers:
@article{Hoy:2024vpc,
author = "Hoy, Charlie and Akcay, Sarp and Mac Uilliam, Jake and Thompson, Jonathan E.",
title = "{Incorporation of model accuracy in gravitational wave Bayesian inference}",
eprint = "2409.19404",
archivePrefix = "arXiv",
primaryClass = "gr-qc",
reportNumber = "LIGO-P2400393",
doi = "10.1038/s41550-025-02579-7",
journal = "Nature Astron.",
volume = "9",
number = "8",
pages = "1256--1267",
year = "2025"
}
@article{Hoy:2022tst,
author = "Hoy, Charlie",
title = "{Accelerating multimodel Bayesian inference, model selection, and systematic studies for gravitational wave astronomy}",
eprint = "2208.00106",
archivePrefix = "arXiv",
primaryClass = "gr-qc",
reportNumber = "LIGO-P2200228",
doi = "10.1103/PhysRevD.106.083003",
journal = "Phys. Rev. D",
volume = "106",
number = "8",
pages = "083003",
year = "2022"
}
Metadata
Release files for bilby-nr 0.1.0a3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| bilby_nr-0.1.0a3.tar.gz | 33.0 kB | Without provenance | Details for bilby_nr-0.1.0a3.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| bilby_nr-0.1.0a3-py3-none-any.whl | Python 3 | none | any | Details for bilby_nr-0.1.0a3-py3-none-any.whl |
Total release size: 65.0 kB
Release files / bilby_nr-0.1.0a3.tar.gz
| Download URL | bilby_nr-0.1.0a3.tar.gz |
|---|---|
| Size | 33.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.13
|
Release files / bilby_nr-0.1.0a3-py3-none-any.whl
| Download URL | bilby_nr-0.1.0a3-py3-none-any.whl |
|---|---|
| Size | 32.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.13
|
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