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*************
Matrix Market
*************
The `Matrix Market`_ exchange format is a text-based file format described by
NIST.
Matrix Market supports both a **coordinate format** for sparse matrices and
an **array format** for dense matrices.
The :mod:`scipy.io` module provides the `scipy.io.mmread` and `scipy.io.mmwrite`
functions to read and write data in Matrix Market format, respectively.
These functions work with either `numpy.ndarray` or `scipy.sparse.coo_matrix`
objects depending on whether the data is in **array** or **coordinate** format.
These functions can be combined with those of NetworkX's `~networkx.convert_matrix`
module to read and write Graphs in Matrix Market format.
.. _Matrix Market: https://math.nist.gov/MatrixMarket/formats.html
Examples
========
Reading and writing graphs using Matrix Market's **array format** for dense
matrices::
>>> import scipy as sp
>>> import io # Use BytesIO as a stand-in for a Python file object
>>> fh = io.BytesIO()
>>> G = nx.complete_graph(5)
>>> a = nx.to_numpy_array(G)
>>> print(a)
[[0. 1. 1. 1. 1.]
[1. 0. 1. 1. 1.]
[1. 1. 0. 1. 1.]
[1. 1. 1. 0. 1.]
[1. 1. 1. 1. 0.]]
>>> # Write to file in Matrix Market array format
>>> sp.io.mmwrite(fh, a)
>>> print(fh.getvalue().decode('utf-8')) # file contents
%%MatrixMarket matrix array real symmetric
%
5 5
0.0000000000000000e+00
1.0000000000000000e+00
1.0000000000000000e+00
1.0000000000000000e+00
1.0000000000000000e+00
0.0000000000000000e+00
1.0000000000000000e+00
1.0000000000000000e+00
1.0000000000000000e+00
0.0000000000000000e+00
1.0000000000000000e+00
1.0000000000000000e+00
0.0000000000000000e+00
1.0000000000000000e+00
0.0000000000000000e+00
>>> # Read from file
>>> fh.seek(0)
>>> H = nx.from_numpy_array(sp.io.mmread(fh))
>>> H.edges() == G.edges()
True
Reading and writing graphs using Matrix Market's **coordinate format** for
sparse matrices::
>>> import scipy as sp
>>> import io # Use BytesIO as a stand-in for a Python file object
>>> fh = io.BytesIO()
>>> G = nx.path_graph(5)
>>> m = nx.to_scipy_sparse_array(G)
>>> print(m)
(0, 1) 1
(1, 0) 1
(1, 2) 1
(2, 1) 1
(2, 3) 1
(3, 2) 1
(3, 4) 1
(4, 3) 1
>>> sp.io.mmwrite(fh, m)
>>> print(fh.getvalue().decode('utf-8')) # file contents
%%MatrixMarket matrix coordinate integer symmetric
%
5 5 4
2 1 1
3 2 1
4 3 1
5 4 1
>>> # Read from file
>>> fh.seek(0)
>>> H = nx.from_scipy_sparse_array(sp.io.mmread(fh))
>>> H.edges() == G.edges()
True
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