scikit-sparse

This scikit-sparse a companion to the scipy.sparse library for sparse matrix manipulation in Python. It provides routines that are not suitable for inclusion in scipy.sparse proper, usually because they are GPL'ed.

For more details on usage see the docs.

Installation

With pip

For pip installs of scikit-sparse depend on the suite-sparse library which can be installed via:

# mac
brew install suite-sparse

# debian
sudo apt-get install libsuitesparse-dev

Then, scikit-sparse can be installed via pip:

pip install scikit-sparse

If you suite-sparse library is installed in a non-standard place and you get errors when installing with pip you can use the environment variables:

• SUITESPARSE_INCLUDE_DIR
• SUITESPARSE_LIBRARY_DIR

at runtime so the compiler can find them. For example, lets say your suite-sparse installation is in /opt/local then you can run

SUITESPARSE_INCLUDE_DIR=/opt/local/include SUITESPARSE_LIBRARY_DIR=/opt/local/lib pip install scikit-sparse

With conda

The conda package comes with suite-sparse packaged as a dependency so all you need to do is:

conda install -c conda-forge scikit-sparse

Windows installation

This was tested with a Anaconda 3 installation and Python 3.8

0. Install requirements

   • conda install -c conda-forge cython - tested with v0.29.32
   • conda install -c conda-forge suitesparse - tested with v5.4.0
   • optional (included in the build dependencies of scikit-sparse):
     • conda install -c conda-forge numpy - tested with v1.23.2
     • conda install -c conda-forge scipy - tested with v1.9.1

1. Download Microsoft Build Tools for C++ from https://visualstudio.microsoft.com/de/visual-cpp-build-tools/ (tested with 2022, should work with 2015 or newer)

2. Install Visual Studio Build Tools

   1. Choose Workloads
   2. Check "Desktop development with C++"
   3. Keep standard settings

3. Run in a Powershell

   • $env:SUITESPARSE_INCLUDE_DIR='C:/Anaconda3/envs/<YOUR ENVIRONMENT NAME HERE>/Library/include/suitesparse'
   • $env:SUITESPARSE_LIBRARY_DIR='C:/Anaconda3/envs/<YOUR ENVIRONMENT NAME HERE>/Library/lib'
   • pip install scikit-sparse

4. Test from sksparse.cholmod import cholesky

License

The wrapper code contained in this package is released under a 2-clause BSD license, as per below. However, this applies only to the original code contained in this package, and NOT to the libraries (e.g., CHOLMOD) which it uses. These libraries are generally licensed under less permissive licenses, such as the GNU GPL or LGPL, and users of this package are responsible for determining what requirements these licenses impose on their usage. (The intent here is that if you, for example, buy a license to use CHOLMOD in a commercial product, then you can also go ahead and use our wrapper code with your commercial license.)

Copyright (c) 2009-2017, the scikit-sparse developers

scikits-sparse
Copyright (c) 2009-2017, the scikit-sparse developers
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