| Name | nuance JSON |
| Version |
0.8.1
JSON |
| download |
| home_page | None |
| Summary | Transit signals detection among correlated noises |
| upload_time | 2024-07-31 00:34:00 |
| maintainer | None |
| docs_url | None |
| author | Lionel Garcia |
| requires_python | >=3.9 |
| license | None |
| keywords |
astronomy
exoplanets
jax
transit
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# nuance
Efficient detection of planets transiting quiet or active stars
<p align="center">
<img src="docs/_static/illu_readme.png" height="350" style="margin:50px">
</p>
*nuance* uses linear models and Gaussian processes (using the [JAX](https://github.com/google/jax)-based [tinygp](https://github.com/dfm/tinygp)) to simultaneously **search for planetary transits while modeling correlated noises** (e.g. stellar variability) in a tractable way. See [the paper](https://arxiv.org/abs/2402.06835) for more details.
When to use *nuance*?
- To detect single or periodic transits
- When correlated noises are present in the data (e.g. stellar variability or instrumental systematics)
- For space-based or sparse ground-based observations
- To effectively find transits in light curves from multiple instruments
- To use GPUs for fast transit searches
Documentation at [nuance.readthedocs.io](https://nuance.readthedocs.io)
## Example
```python
import numpy as np
from nuance import linear_search, periodic_search, core
# linear search
epochs = time.copy()
durations = np.linspace(0.01, 0.2, 15)
ls = linear_search(time, flux, gp=gp)(epochs, durations)
# periodic search
periods = np.linspace(0.3, 5, 2000)
snr_function = jax.jit(core.snr(time, flux, gp=gp))
ps_function = periodic_search(epochs, durations, ls, snr_function)
snr, params = ps_function(periods)
t0, D, P = params[np.argmax(snr)]
```
## Installation
`nuance` is written for python 3 and can be installed using pip
```shell
pip install nuance
```
or from sources
```shell
git clone https://github.com/lgrcia/nuance
cd nuance
pip install -e .
```
## Citation
If you find *nuance* useful for your research, cite [Garcia et. al 2024](https://ui.adsabs.harvard.edu/abs/2024AJ....167..284G). The BibTeX entry for the paper is:
```
@ARTICLE{2024AJ....167..284G,
author = {{Garcia}, Lionel J. and {Foreman-Mackey}, Daniel and {Murray}, Catriona A. and {Aigrain}, Suzanne and {Feliz}, Dax L. and {Pozuelos}, Francisco J.},
title = "{nuance: Efficient Detection of Planets Transiting Active Stars}",
journal = {\aj},
keywords = {Exoplanet detection methods, Stellar activity, Time series analysis, Gaussian Processes regression, Computational methods, GPU computing, 489, 1580, 1916, 1930, 1965, 1969, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},
year = 2024,
month = jun,
volume = {167},
number = {6},
eid = {284},
pages = {284},
doi = {10.3847/1538-3881/ad3cd6},
archivePrefix = {arXiv},
eprint = {2402.06835},
primaryClass = {astro-ph.EP},
adsurl = {https://ui.adsabs.harvard.edu/abs/2024AJ....167..284G},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
```
Raw data
{
"_id": null,
"home_page": null,
"name": "nuance",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.9",
"maintainer_email": null,
"keywords": "astronomy, exoplanets, jax, transit",
"author": "Lionel Garcia",
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/52/fe/4b20fe32ebd8f78b6154dd45e521f4c0a79b2bc9e2fc994e28f9338f6399/nuance-0.8.1.tar.gz",
"platform": null,
"description": "# nuance\nEfficient detection of planets transiting quiet or active stars\n\n<p align=\"center\">\n <img src=\"docs/_static/illu_readme.png\" height=\"350\" style=\"margin:50px\">\n</p>\n\n*nuance* uses linear models and Gaussian processes (using the [JAX](https://github.com/google/jax)-based [tinygp](https://github.com/dfm/tinygp)) to simultaneously **search for planetary transits while modeling correlated noises** (e.g. stellar variability) in a tractable way. See [the paper](https://arxiv.org/abs/2402.06835) for more details.\n\nWhen to use *nuance*?\n- To detect single or periodic transits\n- When correlated noises are present in the data (e.g. stellar variability or instrumental systematics)\n- For space-based or sparse ground-based observations\n- To effectively find transits in light curves from multiple instruments\n- To use GPUs for fast transit searches\n\nDocumentation at [nuance.readthedocs.io](https://nuance.readthedocs.io)\n\n## Example\n\n```python\nimport numpy as np\nfrom nuance import linear_search, periodic_search, core\n\n# linear search\nepochs = time.copy()\ndurations = np.linspace(0.01, 0.2, 15)\nls = linear_search(time, flux, gp=gp)(epochs, durations)\n\n# periodic search\nperiods = np.linspace(0.3, 5, 2000)\nsnr_function = jax.jit(core.snr(time, flux, gp=gp))\nps_function = periodic_search(epochs, durations, ls, snr_function)\nsnr, params = ps_function(periods)\n\nt0, D, P = params[np.argmax(snr)]\n```\n\n## Installation\n\n`nuance` is written for python 3 and can be installed using pip\n\n```shell\npip install nuance\n```\n\nor from sources\n \n```shell\ngit clone https://github.com/lgrcia/nuance\ncd nuance\npip install -e .\n```\n\n## Citation\n\nIf you find *nuance* useful for your research, cite [Garcia et. al 2024](https://ui.adsabs.harvard.edu/abs/2024AJ....167..284G). The BibTeX entry for the paper is:\n\n```\n@ARTICLE{2024AJ....167..284G,\n author = {{Garcia}, Lionel J. and {Foreman-Mackey}, Daniel and {Murray}, Catriona A. and {Aigrain}, Suzanne and {Feliz}, Dax L. and {Pozuelos}, Francisco J.},\n title = \"{nuance: Efficient Detection of Planets Transiting Active Stars}\",\n journal = {\\aj},\n keywords = {Exoplanet detection methods, Stellar activity, Time series analysis, Gaussian Processes regression, Computational methods, GPU computing, 489, 1580, 1916, 1930, 1965, 1969, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics},\n year = 2024,\n month = jun,\n volume = {167},\n number = {6},\n eid = {284},\n pages = {284},\n doi = {10.3847/1538-3881/ad3cd6},\narchivePrefix = {arXiv},\n eprint = {2402.06835},\n primaryClass = {astro-ph.EP},\n adsurl = {https://ui.adsabs.harvard.edu/abs/2024AJ....167..284G},\n adsnote = {Provided by the SAO/NASA Astrophysics Data System}\n}\n```",
"bugtrack_url": null,
"license": null,
"summary": "Transit signals detection among correlated noises",
"version": "0.8.1",
"project_urls": null,
"split_keywords": [
"astronomy",
" exoplanets",
" jax",
" transit"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "ebd73e3dc916b9c1e89932d0c08fb5f28a290c1c9066ea8f81bd8f2808d708c8",
"md5": "f73149905cf1171731d30e6f1b9fac7b",
"sha256": "5a655352168777df01d4a99421a8d707c52978a5c07f731b9b26d73b3aba625c"
},
"downloads": -1,
"filename": "nuance-0.8.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "f73149905cf1171731d30e6f1b9fac7b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.9",
"size": 13789,
"upload_time": "2024-07-31T00:33:58",
"upload_time_iso_8601": "2024-07-31T00:33:58.729711Z",
"url": "https://files.pythonhosted.org/packages/eb/d7/3e3dc916b9c1e89932d0c08fb5f28a290c1c9066ea8f81bd8f2808d708c8/nuance-0.8.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "52fe4b20fe32ebd8f78b6154dd45e521f4c0a79b2bc9e2fc994e28f9338f6399",
"md5": "7a2f6189cfc426b6376a16081c1d5a3a",
"sha256": "8f64075d28ada298b225dc26bf1061ae25ee0d295f18c821435ed8822736274d"
},
"downloads": -1,
"filename": "nuance-0.8.1.tar.gz",
"has_sig": false,
"md5_digest": "7a2f6189cfc426b6376a16081c1d5a3a",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.9",
"size": 2388898,
"upload_time": "2024-07-31T00:34:00",
"upload_time_iso_8601": "2024-07-31T00:34:00.169228Z",
"url": "https://files.pythonhosted.org/packages/52/fe/4b20fe32ebd8f78b6154dd45e521f4c0a79b2bc9e2fc994e28f9338f6399/nuance-0.8.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-07-31 00:34:00",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "nuance"
}
