Task: Python3
Description: Python 3 packages for astronomy
 This metapackage will install Python 3 packages for astronomy. The packages
 can be used for interactive analysis, or to create specific programs.

Depends: python3, ipython3

Depends: python3-numpy, python3-scipy, python3-matplotlib, python3-healpy

Depends: python3-astropy, python3-pyfits, python3-pyds9
Why: Generic Python packages for astronomy

Depends: python3-astropy-affiliated

Depends: python3-astroscrappy, python3-astroplan, python3-astroquery,
    	 python3-ccdproc, python3-gwcs, python3-montage-wrapper,
    	 python3-naima, python3-photutils, python3-pydl, python3-sncosmo,
	 python3-spectral-cube, python3-wcsaxes, python3-specutils

Depends: python3-aplpy, python3-astroml, python3-galpy, python3-gammapy,
	 python3-ginga, python3-imexam, python3-omnifit, python3-pyregion,
	 python3-cpl, python3-pyvo, python3-reproject,
	 python3-spherical-geometry
Why: Astropy affiliated packages

Depends: python3-pyavm

Depends: python3-astlib

Depends: python3-yt

Depends: python3-gyoto

Depends: python3-sherpa
WNPP: 795370
Pkg-Description: Modeling and fitting in Python 3
 Sherpa is a Python package for modeling and fitting. It enables the user to
 construct complex models from simple definitions and fit those models to
 data, using a variety of statistics and optimization methods.
 .
 It was originally developed by the Smithsonian Astrophysical Observatory /
 Chandra X-Ray Center as part of the larger CIAO package for X-ray data
 analysis
Homepage: http://cxc.cfa.harvard.edu/sherpa/

Depends: python3-sncosmo
WNPP: 757096
Pkg-Description: Python 3 library for high-level supervova cosmology analysis
 SNCosmo is a Python library for high-level supernova cosmology analysis. It
 aims to make such analysis both as flexible and clear as possible. It is
 built on NumPy, SciPy and AstroPy. Package Features:
 .
  * SN models: Synthesize supernova spectra and photometry from SN models.
  * Fitting and sampling: Functions for fitting and sampling SN model
    parameters given photometric light curve data.
  * Dust laws: Fast implementations of several commonly used extinction laws;
    can be used to construct SN models that include dust.
  * I/O: Convenience functions for reading and writing peculiar data formats
    used in other packages and getting dust values from SFD (1998) maps.
  * Built-in supernova models such as SALT2, MLCS2k2, Hsiao, Nugent, PSNID,
    SNANA and Whalen models, as well as a variety of built-in bandpasses and
    magnitude systems.
  * Extensible: New models, bandpasses, and magnitude systems can be defined,
    using an object-oriented interface.
Homepage: https://sncosmo.github.io/
