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README.rst

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:target: https://github.com/simpeg/pymatsolver/blob/master/LICENSE
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:alt: MIT license.
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.. image:: https://codecov.io/gh/simpeg/pymatsolver/branch/master/graph/badge.svg
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.. image:: https://codecov.io/gh/simpeg/pymatsolver/branch/main/graph/badge.svg?token=8uQoxzxf3r
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:target: https://codecov.io/gh/simpeg/pymatsolver
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:alt: Coverage status
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* L/U Triangular Solves
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* Wrapping of SciPy matrix solvers (direct and indirect)
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* Pardiso solvers now that MKL comes with conda!
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* Mumps solver with nice error messages
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* Pardiso solvers
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* Mumps solvers
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Installing Mumps
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================
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Installing Solvers
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==================
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Often, there are faster solvers available for your system than the default scipy factorizations available.
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pymatsolver provides a consistent interface to both MKL's ``Pardiso`` routines and the ``MUMPS`` solver package. To
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make use of these we use intermediate wrappers for the libraries that must be installed separately.
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We have not been able to get the pip install to work because of multiple dependencies on fortran libraries.
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However, the linux and mac installs are relatively easy. Note that you must have mumps pre-installed,
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currently we have only got this working for the sequential version, so when you are installing,
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you will need to point to that one. You can also look at the `.travis.yml` file for how to get it working on TravisCI.
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Pardiso
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-------
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The Pardiso interface is recommended for Intel processor based systems. The interface is enabled by
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the ``pydiso`` python package, which can be installed through conda-forge as:
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Linux
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-----
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From a clean install on Ubuntu:
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.. code-block:: bash
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apt-get update
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apt-get -y install gcc gfortran git libopenmpi-dev libmumps-seq-dev libblas-dev liblapack-dev
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# Install all the python you need!
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wget http://repo.continuum.io/miniconda/Miniconda-3.8.3-Linux-x86_64.sh -O miniconda.sh;
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chmod +x miniconda.sh
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./miniconda.sh -b
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export PATH=/root/anaconda/bin:/root/miniconda/bin:$PATH
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conda update --yes conda
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conda install --yes numpy scipy matplotlib cython ipython pytest coverage
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git clone https://github.com/rowanc1/pymatsolver.git
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cd pymatsolver
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make mumps
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.. code::
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Mac
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---
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conda install -c conda-forge pydiso
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This assumes that you have Brew and some python installed (numpy, scipy):
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.. code-block:: bash
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brew install mumps --with-scotch5 --without-mpi
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git clone https://github.com/rowanc1/pymatsolver.git
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cd pymatsolver
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make mumps_mac
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If you have problems you may have to go into the Makefile and update the pointers to Lib and Include for the various libraries.
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Mumps
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-----
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Mumps is available for all platforms. The mumps interface is enabled by installing the ``python-mumps``
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wrapper package. This can easily be installed through conda-forge with:
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This command is helpful for finding dependencies. You should also take note of have happens when brew installs mumps.
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.. code::
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.. code-block:: bash
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conda install -c conda-forge python-mumps
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mpicc --showme
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Code:
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https://github.com/simpeg/pymatsolver
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Tests:
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https://travis-ci.org/simpeg/pymatsolver
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https://github.com/simpeg/pymatsolver/actions
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Bugs & Issues:

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