THE SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND "WITH ALL
FAULTS". THE AUTHOR MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND
CONCERNING THE QUALITY, SAFETY OR SUITABILITY OF THE SOFTWARE, EITHER
EXPRESSED OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR
PySparse extends the Python interpreter by a set of sparse matrix
types holding double precision values. PySparse also includes modules
- iterative methods for solving linear systems of equations
- a set of standard preconditioners
- an interface to a direct solver for sparse linear systems of
- a Jacobi-Davidson eigenvalue solver for the symmetric, generalised
matrix eigenvalue problem (JDSYM)
All these modules are implemented as C extension modules for maximum
PySparse uses NumPy for handling dense vectors and matrices and makes use of
UMFPACK and SuperLU for factorising sparse matrices.
1. Install NumPy
- Download NumPy from http://www.numpy.org/
PySparse was tested with NumPy up to version 2.0
- Unpack and Install the NumPy package
Refer to the documentation provided in the NumPy package for
2. Customise the site.cfg file
PySparse is needs to link against the BLAS and LAPACK libraries,
which must be available on your system.
3. Install PySparse
Run 'python setup.py install' to install PySparse into the default
directory of your Python installation. Refer to the Python
documentation, if you have advanced installation needs.
Some systems will require usage of a Fortran compiler to link the BLAS
and/or LAPACK libraries. The Fortran compiler that was used to compile those
libraries should normally be used. It can be specified at build time using:
python setup.py config_fc --fcompiler=gfortran build
(replace gfortran with your compiler; see 'python setup.py config_fc --help'
for more information.)
Testing support is only rudimentary.
Run the scripts in the examples and test directories. Check if the results
are meaningful :-;
PySparse was successfully tested on many UNIX brands, including
Linux, OSX, Solaris (SunOS 5.6), Digital UNIX (OSF1 V4.0) and HP-UX
11.11, and Windows XP (MinGW).
PySparse was tested using Python version 2.6.
Some documentation is located in the doc subdirectory.
Major parts of this work was done while I was working as a PhD student at
Institute of Scientific Computing
CH-8092 Zurich, Switzerland
and while I was working as a postdoc at
Paul Scherrer Institute
CH-5232 Villigen, Switzerland
I would like thank the developers of the SuperLU and Umfpack
packages. Both SuperLU and Umfpack are incorporated into the PySparse
For comments, questions, bug reports, etc. please consult the pysparse-users
mailing list. See http://pysparse.sf.net.
Thank you for using PySparse!