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PyMetis: A Python Wrapper for METIS
===================================

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PyMetis is a Python wrapper for the `Metis
<http://glaros.dtc.umn.edu/gkhome/views/metis>`_ graph partititioning software
by George Karypis, Vipin Kumar and others. It includes version 5.1.0 of Metis
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and wraps it using the `Pybind11 <https://pybind11.readthedocs.io/en/stable/>`_
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wrapper generator library. So far, it only wraps the most basic graph
partitioning functionality (which is enough for my current use), but extending
it in case you need more should be quite straightforward. Using PyMetis to
partition your meshes is really easy--essentially all you need to pass into
PyMetis is an adjacency list for the graph and the number of parts you would
like.

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Links
-----

* `Documentation <https://documen.tician.de/pymetis>`__ (read how things work)
* `Conda Forge <https://anaconda.org/conda-forge/pymetis>`_ (download binary packages for Linux, macOS, Windows)
* `Python package index <https://pypi.python.org/pypi/pymetis>`_ (download releases)
* `C. Gohlke's Windows binaries <https://www.lfd.uci.edu/~gohlke/pythonlibs/#pymetis>`_ (download Windows binaries)
* `Github <https://github.com/inducer/pymetis>`_ (get latest source code, file bugs)

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------------

The following line should do the job::

    pip install pymetis
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-----------

This graph, adapted from Figure 2 of the Metis
`manual <http://glaros.dtc.umn.edu/gkhome/fetch/sw/metis/manual.pdf>`_ to
use zero-based indexing,

.. image:: doc/_static/tiny_01.png

can be defined and partitioned into two graphs with

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.. code:: python

    import numpy as np
    adjacency_list = [np.array([4, 2, 1]),
                      np.array([0, 2, 3]),
                      np.array([4, 3, 1, 0]),
                      np.array([1, 2, 5, 6]),
                      np.array([0, 2, 5]),
                      np.array([4, 3, 6]),
                      np.array([5, 3])]
    n_cuts, membership = pymetis.part_graph(2, adjacency=adjacency_list)
    # n_cuts = 3
    # membership = [1, 1, 1, 0, 1, 0, 0]

    nodes_part_0 = np.argwhere(np.array(membership) == 0).ravel() # [3, 5, 6]
    nodes_part_1 = np.argwhere(np.array(membership) == 1).ravel() # [0, 1, 2, 4]

.. image:: doc/_static/tiny_01_partitioned.png
Configuration
=============

METIS has a number of configuration options that can be specified using the `pymetis.Options` class

.. code:: python
   import pymetis
   options = pymetis.Options()
   options.contig = 1     # Require contiguous partitions
   options.seed   = 1234  # Random seed for partitioning

   ...

   n_cuts, membership = pymetis.part_graph(n_parts, adjacency=adjacency_list, options=options) 

The following options are available. For a description of the options see the
METIS documentation.

    options.ncuts:      METIS_OPTION_NCUTS
    options.nseps:      METIS_OPTION_NSEPS
    options.numbering:  METIS_OPTION_NUMBERING
    options.niter:      METIS_OPTION_NITER
    options.minconn:    METIS_OPTION_MINCONN
    options.no2hop:     METIS_OPTION_NO2HOP
    options.seed:       METIS_OPTION_SEED
    options.contig:     METIS_OPTION_CONTIG
    options.compress:   METIS_OPTION_COMPRESS
    options.ccorder:    METIS_OPTION_CCORDER
    options.pfactor:    METIS_OPTION_PFACTOR
    options.ufactor:    METIS_OPTION_UFACTOR