Metadata-Version: 2.4
Name: zap
Version: 2.2
Summary: ZAP (the Zurich Atmosphere Purge) is a high precision sky subtraction tool
Author-email: Kurt Soto <sotok@phys.ethz.ch>, Simon Conseil <simon.conseil@univ-lyon1.fr>
License-Expression: MIT
Project-URL: documentation, https://zap.readthedocs.io
Project-URL: github, https://github.com/musevlt/zap
Keywords: astronomy,astrophysics,science,muse,vlt,sky subtraction
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.11
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: astropy
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scipy
Provides-Extra: all
Requires-Dist: matplotlib; extra == "all"
Provides-Extra: docs
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Provides-Extra: tests
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Requires-Dist: mpdaf; extra == "tests"
Dynamic: license-file

ZAP (the Zurich Atmosphere Purge)
---------------------------------

Tired of sky subtraction residuals? ZAP them!

ZAP is a high precision sky subtraction tool which can be used as complete sky
subtraction solution, or as an enhancement to previously sky-subtracted MUSE
data.  The method uses PCA to isolate the residual sky subtraction features and
remove them from the observed datacube. ZAP was designed for MUSE data and has
been used sucessfully on KCWI and Subaru/FOCAS data.

The last stable release of ZAP can be installed simply with pip::

    pip install zap

Or into the user path with::

    pip install --user zap

Links
~~~~~

- `documentation <http://zap.readthedocs.io/en/latest/>`_

- `git repository <https://github.com/musevlt/zap>`_

- `changelog <https://github.com/musevlt/zap/blob/master/CHANGELOG>`_

- `pypi <https://pypi.org/project/zap/>`_

Citation
~~~~~~~~

The paper describing the original method can be found here:
http://adsabs.harvard.edu/abs/2016MNRAS.458.3210S

Please cite ZAP as::

\bibitem[Soto et al.(2016)]{2016MNRAS.458.3210S} Soto, K.~T., Lilly, S.~J., Bacon, R., Richard, J., \& Conseil, S.\ 2016, \mnras, 458, 3210
