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.. image:: https://travis-ci.org/musevlt/mpdaf.svg?branch=master
  :target: https://travis-ci.org/musevlt/mpdaf

.. image:: https://codecov.io/gh/musevlt/mpdaf/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/musevlt/mpdaf

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MPDAF, the *MUSE Python Data Analysis Framework*, is an open-source (BSD
licensed) Python package, developed and maintained by `CRAL
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<https://cral.univ-lyon1.fr/>`_ and partially funded by the ERC advanced grant
339659-MUSICOS (see `Authors and Credits
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<http://mpdaf.readthedocs.io/en/stable/credits.html>`_ for more details).  It
has been developed and used in the `MUSE Consortium
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<http://muse-vlt.eu/science/>`_ for several years, and is available freely for
the community.
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It provides tools to work with MUSE-specific data (raw data, pixel tables,
etc.), and with more general data like spectra, images and data cubes. Although
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its main use is to work with MUSE data, it is also possible to use it with other
data, for example HST images.

MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in
a datacube, and a format to gather all the information on a source in one FITS
file.
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Bug reports, comments, and help with development are very welcome.
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MPDAF 3.0 requires Python 3.5 or later.  It is the first version that supports
only Python 3. `Older versions <https://pypi.org/project/mpdaf/#history>`_ can
be installed for users that still need Python 2.
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Links
-----
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- `Documentation <http://mpdaf.readthedocs.io//en/stable/>`_.
- Source, issues and pull requests on
  `Github <https://github.com/musevlt/mpdaf/>`_ and on a
  `Gitlab <https://git-cral.univ-lyon1.fr/MUSE/mpdaf>`_ instance.
- Releases on `PyPI <https://pypi.org/project/mpdaf/>`_.
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- `Mailing list <mpdaf-support@osulistes.univ-lyon1.fr>`_ to get help or
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  discuss issues.
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Reporting Issues
----------------

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If you have found a bug in MPDAF please `create an issue on Github
<https://github.com/musevlt/mpdaf/issues/new>`_.
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Citing
------

MPDAF can be cited with the `ASCL <http://ascl.net/1611.003>`_ reference (`ADS
<http://adsabs.harvard.edu/abs/2016ascl.soft11003B>`__, `BibTeX
<http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2016ascl.soft11003B&data_type=BIBTEX&db_key=AST&nocookieset=1>`__),
and was also presented at ADASS XXVI, for which the proceedings is on the
`arXiv <https://arxiv.org/abs/1710.03554>`_ (`ADS
<http://adsabs.harvard.edu/abs/2017arXiv171003554P>`__, `BibTeX
<http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2017arXiv171003554P&data_type=BIBTEX&db_key=PRE&nocookieset=1>`__).