- libjs-mathjax
- libjs-sphinxdoc (>= 1.0)
- sphinx-rtd-theme-common (>= 0.4.2+dfsg)
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.
Installed Size: 2.9 MB
Architectures: all