Overview¶
Introduction¶
The scikit-sparse
package (previously known as scikits.sparse
)
is a companion to the scipy.sparse
library for sparse matrix
manipulation in Python. All scikit-sparse
routines expect and
return scipy.sparse
matrices (usually in CSC format). The intent
of scikit-sparse
is to wrap GPL’ed code such as SuiteSparse, which cannot be
included in SciPy proper.
Currently our coverage is rather… sparse, with only a wrapper for the CHOLMOD routines for sparse Cholesky decomposition, but we hope that this will expand over time. Contributions of new wrappers are very welcome, especially if you can follow the style of the existing interfaces.
Download¶
The current release may be downloaded from the Python Package index at
Or from the homepage at
Or the latest development version may be found in our Git repository:
$ git clone git://github.com/scikit-sparse/scikit-sparse.git
Requirements¶
Installing scikit-sparse
requires:
- Python
- NumPy
- SciPy
- Cython
- CHOLMOD (included in SuiteSparse)
Test versions are: * Python: 3.7, 3.6 * NumPy: 1.15, 1.14, 1.13 * SciPy: 1.1, 1.0, 0.19 * SuiteSparse: 5.2 (Other versions may work but are untested.)
On Debian/Ubuntu systems, the following command should suffice:
$ sudo apt-get install python-scipy libsuitesparse-dev
On Arch Linux, run:
$ sudo pacman -S suitesparse
Installation¶
As usual,
$ pip install --user scikit-sparse
or with conda
$ conda install -c conda-forge scikit-sparse
Contact¶
Post your suggestions and questions directly to our bug tracker.
Developers¶
- 2008 David Cournapeau
- 2009-2015 Nathaniel Smith
- 2010 Dag Sverre Seljebotn
- 2014 Leon Barrett
- 2015 Yuri
- 2016-2017 Antony Lee
- 2016 Alex Grigorievskiy
- 2016-2018 Joscha Reimer