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pymatsolver

pymatsolver: Matrix Solvers for Python

  • 0.3.1
  • PyPI
  • Socket score

Maintainers
4

pymatsolver


.. image:: https://img.shields.io/pypi/v/pymatsolver.svg :target: https://pypi.python.org/pypi/pymatsolver :alt: Latest PyPI version

.. image:: https://img.shields.io/badge/license-MIT-blue.svg :target: https://github.com/simpeg/pymatsolver/blob/master/LICENSE :alt: MIT license.

.. image:: https://codecov.io/gh/simpeg/pymatsolver/branch/main/graph/badge.svg?token=8uQoxzxf3r :target: https://codecov.io/gh/simpeg/pymatsolver :alt: Coverage status

A (sparse) matrix solver for python.

Solving Ax = b should be as easy as:

.. code-block:: python

Ainv = Solver(A)
x = Ainv * b

In pymatsolver we provide a number of wrappers to existing numerical packages. Nothing fancy here.

Solvers Available

All solvers work with :code:scipy.sparse matricies, and a single or multiple right hand sides using :code:numpy:

  • L/U Triangular Solves
  • Wrapping of SciPy matrix solvers (direct and indirect)
  • Pardiso solvers
  • Mumps solvers

Installing Solvers

Often, there are faster solvers available for your system than the default scipy factorizations available. pymatsolver provides a consistent interface to both MKL's Pardiso routines and the MUMPS solver package. To make use of these we use intermediate wrappers for the libraries that must be installed separately.

Pardiso

The Pardiso interface is recommended for Intel processor based systems. The interface is enabled by the pydiso python package, which can be installed through conda-forge as:

.. code::

conda install -c conda-forge pydiso

Mumps

Mumps is available for all platforms. The mumps interface is enabled by installing the python-mumps wrapper package. This can easily be installed through conda-forge with:

.. code::

conda install -c conda-forge python-mumps

Code: https://github.com/simpeg/pymatsolver

Tests: https://github.com/simpeg/pymatsolver/actions

Bugs & Issues: https://github.com/simpeg/pymatsolver/issues

License: MIT

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