| Name | star-privateer JSON |
| Version |
1.2.0
JSON |
| download |
| home_page | None |
| Summary | Module for stellar surface rotation and activity analysis |
| upload_time | 2024-11-22 09:58:40 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | Copyright (C) 2024 Sylvain Breton Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
stellar physics
stellar rotation
stellar activity
solar-type stars
light curves
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# star-privateer
The present module provides a complete API to implement
tools for stellar surface rotation and activity analysis
in photometric light curves collected by space missions
such as NASA/*Kepler*, NASA/TESS or, in a near future,
[ESA/PLATO](https://platomission.com/).
Several tutorials are included in order to help
new users that would like to discover the code.
## Getting Started
### Prerequisites
The module is written in Python 3.
The following Python packages are necessary to use it:
- numpy
- scipy
- pandas
- matplotlib
- astropy
- tqdm
- scikit-learn
- scikit-image
- ssqueezepy
- pycwt
- pywavelets
### Installing
The simplest way to install the module is through PyPi
`pip install star-privateer`
You can also install the most recent version of the module by cloning the GitLab repository
`git clone https://gitlab.com/sybreton/star_privateer.git`
and installing it directly by going to the root of the cloned repository
`pip install .`
Some of the tutoriels notebook require additional datasets to be properly run, you can access them through an auxiliary repository
`git clone https://gitlab.com/sybreton/plato_msap4_demonstrator_datasets.git`
that you will also have to install through
`pip install .`
In the future, we plan to provide packaged versions of the pipeline through conda-forge.
### Documentation
API Documentation and tutorials are available [here](https://star-privateer.readthedocs.io/en/latest/).
## Authors
* **Sylvain N. Breton** - Maintainer & head developer - (INAF-OACT, Catania, Italy)
Active contributors:
* **Antonino F. Lanza** - Responsible PLATO WP122 - (INAF-OACT, Catania, Italy)
* **Sergio Messina** - Responsible PLATO WP122300 - (INAF-OACT, Catania, Italy)
* **Rafael A. García** (CEA Saclay, France)
* **S. Mathur** (IAC Tenerife, Spain)
* **Angela R.G. Santos** (Universidade do Porto, Portugal)
* **L. Bugnet** (ISTA Vienna, Austria)
* **E. Corsaro** (INAF-OACT, Catania, Italy)
* **D.B. Palakkatharappil** (CEA Saclay, France)
* **E. Panetier** (CEA Saclay, France)
* **O. Roth** (LESIA, Observatoire de Paris, France)
* **M.B. Nielsen** (University of Birmingham, United Kingdom)
Former contributors:
* **Emile Carinos** (CEA Saclay, France)
* **Yassine Dhifaoui** (CEA Saclay/Université Clermont-Auvergne, France)
## Acknowledgements
If you use this module in your work, please provide a link to
the GitLab repository.
You will find references for most of the methods implemented in this module in
[Breton et al. 2021](https://ui.adsabs.harvard.edu/abs/2021A%26A...647A.125B/abstract) and
in [Santos et al. 2019](https://ui.adsabs.harvard.edu/abs/2019ApJS..244...21S/abstract), if you
make use of the code in view of a scientific publication, please take a look at these two papers
in order to provide the relevant citations.
The [*Kepler*](https://www.nasa.gov/mission_pages/kepler/overview/index.html) light curves
included in the datasets were calibrated with the KEPSEISMIC
method, if you use them, please cite [García et al. 2011](https://ui.adsabs.harvard.edu/abs/2011MNRAS.414L...6G/abstract),
[García et al. 2014](https://ui.adsabs.harvard.edu/abs/2014A%26A...568A..10G/abstract)
and [Pires et al. 2015](https://ui.adsabs.harvard.edu/abs/2015A%26A...574A..18P/abstract).
The PLATO simulated light curves included in the datasets were produced and detrended
by Suzanne Aigrain and Oscar Barragán. If you make any use of these light curves,
please acknowledge them and cite [Aigrain et al. 2015](https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.3211A/abstract).
For more information about the light curves, a readme file written by S. Aigrain is included.
## License and copyright
The current version of the module is licensed under [MIT
License](https://opensource.org/license/mit).
All source code copyright belongs to Sylvain Breton, unless specified
differently in the header source files.
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"description": "# star-privateer\n\nThe present module provides a complete API to implement\ntools for stellar surface rotation and activity analysis\nin photometric light curves collected by space missions\nsuch as NASA/*Kepler*, NASA/TESS or, in a near future,\n[ESA/PLATO](https://platomission.com/). \nSeveral tutorials are included in order to help \nnew users that would like to discover the code. \n\n## Getting Started\n\n### Prerequisites\n\nThe module is written in Python 3.\nThe following Python packages are necessary to use it: \n- numpy\n- scipy\n- pandas\n- matplotlib\n- astropy\n- tqdm\n- scikit-learn\n- scikit-image \n- ssqueezepy\n- pycwt\n- pywavelets\n\n### Installing\n\nThe simplest way to install the module is through PyPi \n\n`pip install star-privateer`\n\nYou can also install the most recent version of the module by cloning the GitLab repository\n\n`git clone https://gitlab.com/sybreton/star_privateer.git`\n\nand installing it directly by going to the root of the cloned repository\n\n`pip install .` \n\nSome of the tutoriels notebook require additional datasets to be properly run, you can access them through an auxiliary repository\n\n`git clone https://gitlab.com/sybreton/plato_msap4_demonstrator_datasets.git`\n\nthat you will also have to install through\n\n`pip install .`\n\nIn the future, we plan to provide packaged versions of the pipeline through conda-forge.\n\n### Documentation\n\nAPI Documentation and tutorials are available [here](https://star-privateer.readthedocs.io/en/latest/).\n\n## Authors\n\n* **Sylvain N. Breton** - Maintainer & head developer - (INAF-OACT, Catania, Italy)\n\nActive contributors:\n\n* **Antonino F. Lanza** - Responsible PLATO WP122 - (INAF-OACT, Catania, Italy)\n* **Sergio Messina** - Responsible PLATO WP122300 - (INAF-OACT, Catania, Italy)\n* **Rafael A. Garc\u00eda** (CEA Saclay, France) \n* **S. Mathur** (IAC Tenerife, Spain) \n* **Angela R.G. Santos** (Universidade do Porto, Portugal) \n* **L. Bugnet** (ISTA Vienna, Austria) \n* **E. Corsaro** (INAF-OACT, Catania, Italy) \n* **D.B. Palakkatharappil** (CEA Saclay, France)\n* **E. Panetier** (CEA Saclay, France)\n* **O. Roth** (LESIA, Observatoire de Paris, France)\n* **M.B. Nielsen** (University of Birmingham, United Kingdom)\n\nFormer contributors:\n\n* **Emile Carinos** (CEA Saclay, France)\n* **Yassine Dhifaoui** (CEA Saclay/Universit\u00e9 Clermont-Auvergne, France)\n\n## Acknowledgements \n\nIf you use this module in your work, please provide a link to\nthe GitLab repository. \n\nYou will find references for most of the methods implemented in this module in \n[Breton et al. 2021](https://ui.adsabs.harvard.edu/abs/2021A%26A...647A.125B/abstract) and\nin [Santos et al. 2019](https://ui.adsabs.harvard.edu/abs/2019ApJS..244...21S/abstract), if you\nmake use of the code in view of a scientific publication, please take a look at these two papers \nin order to provide the relevant citations. \n\nThe [*Kepler*](https://www.nasa.gov/mission_pages/kepler/overview/index.html) light curves \nincluded in the datasets were calibrated with the KEPSEISMIC\nmethod, if you use them, please cite [Garc\u00eda et al. 2011](https://ui.adsabs.harvard.edu/abs/2011MNRAS.414L...6G/abstract),\n[Garc\u00eda et al. 2014](https://ui.adsabs.harvard.edu/abs/2014A%26A...568A..10G/abstract) \nand [Pires et al. 2015](https://ui.adsabs.harvard.edu/abs/2015A%26A...574A..18P/abstract).\n\nThe PLATO simulated light curves included in the datasets were produced and detrended\nby Suzanne Aigrain and Oscar Barrag\u00e1n. If you make any use of these light curves,\nplease acknowledge them and cite [Aigrain et al. 2015](https://ui.adsabs.harvard.edu/abs/2015MNRAS.450.3211A/abstract).\nFor more information about the light curves, a readme file written by S. Aigrain is included.\n\n## License and copyright\n\nThe current version of the module is licensed under [MIT\nLicense](https://opensource.org/license/mit).\n\nAll source code copyright belongs to Sylvain Breton, unless specified\ndifferently in the header source files.\n",
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