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 a part of SuiteSparse.
References
Installation
Releases of scikit-umfpack can be installed from source using pip, or with a package manager like conda . To install from source, first ensure the dependencies described in the next section are installed, then run:
pip install scikit-umfpack
To install scikit-umfpack from its source code directory, run in the root of a clone of the Git repository:
pip install .
Dependencies
scikit-umfpack depends on NumPy, SciPy, and SuiteSparse.
To build scikit-umfpack, the following are needed: - a C compiler - a BLAS library with CBLAS symbols (e.g., OpenBLAS, Accelerate on macOS, or reference BLAS) - NumPy - SuiteSparse (which contains UMFPACK) - SWIG
pkg-config is an optional dependency, if it’s installed it may be used to detect a BLAS library.
SuiteSparse cannot be installed from PyPI, however it will likely be available from your package manager of choice. E.g., installing on Ubuntu 22.04 can be achieved with:
sudo apt-get install libsuitesparse-dev
or from Conda-forge on any supported OS with:
conda install suitesparse
SuiteSparse can also be built from source, see the instructions in the README of the SuiteSparse repository.
Detection of UMFPACK
During the build, scikit-umfpack tries to automatically detect the UMFPACK shared library and headers. In case SuiteSparse is installed in a non-standard location, this autodetection may fail. If that happens, it is possible to provide the paths to the library and include directories in a config file (a Meson machine file). This file should contain absolute paths. For example, for a conda env on Windows, it may look like:
[properties]
umfpack-libdir = 'C:\Users\micromamba\envs\scikit-umfpack-dev\Library\lib'
umfpack-includedir = 'C:\Users\micromamba\envs\scikit-umfpack-dev\Library\include\suitesparse'If that file is named nativefile.ini, then the pip invocation should look like (note that $PWD ensures an absolute path to the native file is used):
pip install . -Csetup-args=--native-file=$PWD/nativefile.ini
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 git@github.com: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 pytest package installed):
pip install pytest pytest --pyargs scikits.umfpack
1 maintainer
Metadata
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Release files for scikit-umfpack 0.4.2
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