Source: pysph
Priority: optional
Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Uploaders:
 Anton Gladky <gladk@debian.org>
Build-Depends:
 cython,
 debhelper (>= 9),
 python-dev (>=2.6.6-3~),
 python-enthoughtbase,
 python-mako,
 python-nose,
 python-numpy,
 python-sphinx (>= 1.0.7+dfsg),
 python-traits,
 python-setuptools
X-Python-Version: >= 2.7
Standards-Version: 3.9.6
Section: science
XS-Testsuite: autopkgtest
Homepage: http://pysph.googlecode.com
Vcs-Git: git://anonscm.debian.org/debian-science/packages/pysph.git
Vcs-Browser: http://anonscm.debian.org/gitweb/?p=debian-science/packages/pysph.git

Package: python-pysph
Section: python
Architecture: any
Depends:
 cython,
 python (<<2.8),
 python (>= 2.7),
 python-mako,
 python-nose,
 python-numpy,
 ${misc:Depends},
 ${python:Depends},
 ${shlibs:Depends},
 ${sphinxdoc:Depends}
Recommends:
 pysph-viewer
Description:  open source framework for Smoothed Particle Hydrodynamics 
 It is implemented in Python and the performance critical parts are 
 implemented in Cython.
 .
 PySPH is implemented in a way that allows a user to specify the entire 
 SPH simulation in pure Python. High-performance code is generated from 
 this high-level Python code, compiled on the fly and executed. PySPH also 
 features optional automatic parallelization using mpi4py and Zoltan.

Package: pysph-viewer
Section: python
Architecture: any
Depends:
 mayavi2,
 python-pysph,
 ${misc:Depends},
 ${python:Depends},
 ${shlibs:Depends},
Description: viewer for PySPH - framework for Smoothed Particle Hydrodynamics
 It is implemented in Python and the performance critical parts are 
 implemented in Cython.
 .
 PySPH is implemented in a way that allows a user to specify the entire 
 SPH simulation in pure Python. High-performance code is generated from 
 this high-level Python code, compiled on the fly and executed. PySPH also 
 features optional automatic parallelization using mpi4py and Zoltan. 
 The package contains viewer for PySPH.

Package: pysph-doc
Section: doc
Architecture: all
Depends:
 libjs-mathjax,
 ${sphinxdoc:Depends},
 ${misc:Depends},
Recommends:
 python-pysph
Description: documentation and examples for PySPH 
 It is implemented in Python and the performance critical parts are 
 implemented in Cython.
 .
 PySPH is implemented in a way that allows a user to specify the entire 
 SPH simulation in pure Python. High-performance code is generated from 
 this high-level Python code, compiled on the fly and executed. PySPH also 
 features optional automatic parallelization using mpi4py and Zoltan. 
 The package contains documentation and examples for PySPH.
