Overview ======== Introduction ------------ The :mod:`scikit-sparse` package (previously known as :mod:`scikits.sparse`) is a companion to the :mod:`scipy.sparse` library for sparse matrix manipulation in Python. All :mod:`scikit-sparse` routines expect and return :mod:`scipy.sparse` matrices (usually in CSC format). The intent of :mod:`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 https://pypi.python.org/pypi/scikit-sparse/ Or from the `homepage `_ at https://github.com/scikit-sparse/scikit-sparse/releases Or the latest *development version* may be found in our `Git repository `_:: $ git clone git://github.com/scikit-sparse/scikit-sparse.git Requirements ------------ Installing :mod:`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 `_