Metadata-Version: 2.1
Name: muse-origin
Version: 3.2
Summary: Blind detection of faint emission line galaxies in MUSE datacubes
Home-page: https://github.com/musevlt/origin
Author: Simon Conseil
Author-email: simon.conseil@univ-lyon1.fr
License: MIT License
Description: .. image:: https://travis-ci.org/musevlt/origin.svg?branch=master
          :target: https://travis-ci.org/musevlt/origin
        
        .. image:: https://codecov.io/gh/musevlt/origin/branch/master/graph/badge.svg
          :target: https://codecov.io/gh/musevlt/origin
        
        
        ORIGIN is a software to perform blind detection of faint emitters in MUSE
        datacubes.
        
        The algorithm is tuned to efficiently detects faint spatial-spectral emission
        signatures, while  allowing for a stable false detection rate over the data cube
        and providing in the same time an automated and reliable estimation of the
        purity.
        
        The algorithm implements :
        
        1. A nuisance removal part based on a continuum subtraction  combining
        a Discrete Cosine Transform and an iterative Principal Component Analysis,
        
        2. A detection part based on the local maxima of Generalized Likelihood
        Ratio test  statistics obtained for a set of spatial-spectral profiles of
        emission line emitters,
        
        3. A purity estimation part, where the proportion of true emission lines
        is estimated from the data itself:  the distribution of the local maxima in
        the noise only configuration is estimated from that of the local minima.
        
        
        Citation
        --------
        ORIGIN is presented in the following paper:
        `Mary et al., A&A, 2020, in press <https://doi.org/10.1051/0004-6361/201937001>`_
        
        
        Links
        -----
        
        - `Documentation <https://muse-origin.readthedocs.io/>`_
        - `PyPI <https://pypi.org/project/muse-origin/>`_
        - `Github <https://github.com/musevlt/origin>`_
        
Keywords: astronomy,astrophysics,science,muse,vlt
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
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: >=3.6
Provides-Extra: docs
