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Python client for Carpyncho VVV dataset collection.

Project description

Carpyncho client for Python

Python client for Carpyncho VVV dataset collection.

QuatroPe CI DOI Python 3 BSD-3 Documentation Status PyPI ascl:2005.007

Logo

This library access as a Pandas DataFrame all the data of the web version of Carpyncho https://carpyncho.github.io/.

Code

The entire source code of is hosted in GitHub https://github.com/carpyncho/carpyncho-py/

License

Carpyncho is under The BSD-3 License

The BSD 3-clause license allows you almost unlimited freedom with the software so long as you include the BSD copyright and license notice in it (found in Fulltext).

Citation

If you use Carpyncho in a scientific publication, we would appreciate citations to the following paper:

Cabral, J. B., Ramos, F., Gurovich, S., & Granitto, P. (2020). Automatic Catalog of RRLyrae from ∼ 14 million VVV Light Curves: How far can we go with traditional machine-learning? https://arxiv.org/abs/2005.00220

Bibtex entry

@ARTICLE{2020A&A...642A..58C,
       author = {{Cabral}, J.~B. and {Ramos}, F. and {Gurovich}, S. and {Granitto}, P.~M.},
        title = "{Automatic catalog of RR Lyrae from {\ensuremath{\sim}}14 million VVV light curves: How far can we go with traditional machine-learning?}",
      journal = {\aap},
     keywords = {methods: data analysis, methods: statistical, surveys, catalogs, stars: variables: RR Lyrae, Galaxy: bulge, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Computer Science - Machine Learning, Statistics - Machine Learning},
         year = 2020,
        month = oct,
       volume = {642},
          eid = {A58},
        pages = {A58},
          doi = {10.1051/0004-6361/202038314},
archivePrefix = {arXiv},
       eprint = {2005.00220},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020A&A...642A..58C},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Installation

This is the recommended way to install carpyncho.

Installing with pip

Make sure that the Python interpreter can load carpyncho code. The most convenient way to do this is to use virtualenv, virtualenvwrapper, and pip.

After setting up and activating the virtualenv, run the following command:

$ pip install carpyncho
...

That should be it all.

Installing the development version

If you’d like to be able to update your carpyncho code occasionally with the latest bug fixes and improvements, follow these instructions:

Make sure that you have Git installed and that you can run its commands from a shell. (Enter git help at a shell prompt to test this.)

Check out carpyncho main development branch like so:

$ git clone https://github.com/carpyncho/carpyncho-py.git carpyncho
...

This will create a directory carpyncho in your current directory.

Then you can proceed to install with the commands

$ cd carpyncho
$ pip install -e .
...

Documentation

The full documentation of the project are available in https://carpyncho-py.readthedocs.io/

Contact

For bugs or question please contact

Juan B. Cabral: jbcabral@unc.edu.ar

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