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