| Name | nuance JSON |
| Version |
0.7.1
JSON |
| download |
| home_page | None |
| Summary | Transit signals detection among correlated noises |
| upload_time | 2024-05-28 10:55:30 |
| 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
from nuance import Nuance, utils
import numpy as np
(time, flux, error), X, gp = utils.simulated()
nu = Nuance(time, flux, gp=gp, X=X)
# linear search
epochs = time.copy()
durations = np.linspace(0.01, 0.2, 15)
nu.linear_search(epochs, durations)
# periodic search
periods = np.linspace(0.3, 5, 2000)
search = nu.periodic_search(periods)
t0, D, P = search.best
```
## 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 .
```
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"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\nfrom nuance import Nuance, utils\nimport numpy as np\n\n(time, flux, error), X, gp = utils.simulated()\n\nnu = Nuance(time, flux, gp=gp, X=X)\n\n# linear search\nepochs = time.copy()\ndurations = np.linspace(0.01, 0.2, 15)\nnu.linear_search(epochs, durations)\n\n# periodic search\nperiods = np.linspace(0.3, 5, 2000)\nsearch = nu.periodic_search(periods)\n\nt0, D, P = search.best\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",
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