Metadata-Version: 2.1
Name: mpdaf
Version: 3.2
Summary: MUSE Python Data Analysis Framework is a python framework in view of the analysis of MUSE data in the context of the GTO.
Home-page: https://git-cral.univ-lyon1.fr/MUSE/mpdaf
Maintainer: Laure Piqueras
Maintainer-email: laure.piqueras@univ-lyon1.fr
License: BSD
Keywords: astronomy,astrophysics,science,muse,vlt,cube,image,spectrum
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: C
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.5
Provides-Extra: all
Requires-Dist: numpy (>=1.10.0)
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: astropy (>=1.0)
Provides-Extra: all
Requires-Dist: numexpr; extra == 'all'
Requires-Dist: fitsio; extra == 'all'
Requires-Dist: adjustText; extra == 'all'
Requires-Dist: joblib; extra == 'all'
Requires-Dist: tqdm; extra == 'all'

MPDAF, the *MUSE Python Data Analysis Framework*, is an open-source (BSD
licensed) Python package, developed and maintained by `CRAL
<https://cral.univ-lyon1.fr/>`_ and partially funded by the ERC advanced grant
339659-MUSICOS (see `Authors and Credits
<http://mpdaf.readthedocs.io/en/stable/credits.html>`_ for more details).

It has been developed and used in the `MUSE Consortium
<http://muse-vlt.eu/science/>`_ for several years, and is available freely for
the community.

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
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.

Bug reports, comments, and help with development are very welcome.

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.

Links
-----

- `Documentation <http://mpdaf.readthedocs.io//en/stable/>`_
- Source, issues and pull requests on a
  `Gitlab <https://git-cral.univ-lyon1.fr/MUSE/mpdaf>`_ instance
- Releases on `PyPI <https://pypi.org/project/mpdaf/>`_
- `Mailing list <mpdaf-support@osulistes.univ-lyon1.fr>`_ to get help or
  discuss issues

Reporting Issues
----------------

If you have found a bug in MPDAF please report it.

The preferred way is to create a new issue on `the MPDAF gitlab issue page
<https://git-cral.univ-lyon1.fr/MUSE/mpdaf/issues>`_ .  This requires creating
a account on `git-cral <https://git-cral.univ-lyon1.fr>`_ if you don't have
one.  To create an account, please send email to
`mpdaf-support@osulistes.univ-lyon1.fr
<mailto:mpdaf-support@osulistes.univ-lyon1.fr?subject=Account%20creation>`_

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>`__).


