scikit-umfpack 0.2.1

Python interface to UMFPACK sparse direct solver.

scikit-umfpack

scikit-umfpack provides wrapper of UMFPACK sparse direct solver to SciPy.

Usage:

>>> from scikits.umfpack import spsolve, splu
>>> lu = splu(A)
>>> x = spsolve(A, b)

Installing scikits.umfpack also enables using UMFPACK solver via some of the scipy.sparse.linalg functions, for SciPy >= 0.14.0. Note you will need to have installed UMFPACK before hand. UMFPACK is parse of SuiteSparse.

Dependencies

scikit-umfpack depends on NumPy, SciPy, SuiteSparse, and swig is a build-time dependency.

Building SuiteSparse

SuiteSparse may be available from your package manager or as a prebuilt shared library. If that is the case use that if possible. Installation on Ubuntu 14.04 can be achieved with

sudo apt-get install libsuitesparse-dev

Otherwise, you will need to build from source. Unfortunately, SuiteSparse’s makefiles do not support building a shared library out of the box. You may find Stefan Fürtinger instructions helpful.

Furthmore, building METIS-4.0, an optional but important compile time dependency of SuiteSparse, has problems on newer GCCs. This patch and instructions from Nadir Soualem are helpful for getting a working METIS build.

Otherwise, I commend you to the documentation.

Install

This package uses distutils, which is the default way of installing python modules. In the directory scikit-umfpack (the same as the file you are reading now) do:

python setup.py install

or for a local installation:

python setup.py install --root=<DIRECTORY>

Development

Code

You can check the latest sources with the command:

git clone https://github.com/scikit-umfpack/scikit-umfpack.git

or if you have write privileges:

git clone [e-mail]:scikit-umfpack/scikit-umfpack.git

Testing

After installation, you can launch the test suite from outside the source directory (you will need to have the nose package installed):

nosetests -v scikits.umfpack