Count or list the cliques in a graph using the Pivoter algorithm.
Project description
PyPivoter
Purpose
The purpose of this package is to count and/or list the cliques, or maximally-connected subgraphs, within a graph using the fast Pivoter algorithm developed by Shweta Jain and C. Seshadhri.
Installation
From a repository checkout
make install
or
CYTHONIZE=1 pip install --user .
Use
The two main functions available to the user are countCliques and enumerateCliques, which can be imported as follows:
>> from pivoter.pivoter import countCliques, enumerateCliques
Both take two arguments. The first is an m x 2 NumPy array of integer indices of vertex pairs that comprise the edges of a graph, with no repeated or reversed pairs or self-adjacency. The second is an integer, the maximum clique size to output. If the second argument is 0, all sizes will be output.
Example output from countCliques is:
>> import numpy as np
>> from pypivoter import countCliques
>> tetrahedron = np.array([[0, 1], [0, 2], [0, 3], [1, 2], [1, 3], [2, 3]])
>> countCliques(tetrahedron, 0)
[1 4 6 4 1]
Example output from enumerateCliques is:
>> import numpy as np
>> from pypivoter import enumerateCliques
>> tetrahedron = np.array([[0, 1], [0, 2], [0, 3], [1, 2], [1, 3], [2, 3]])
>> enumerateCliques(tetrahedron, 0)
[array([], shape=(0, 0), dtype=int32), array([[0],
[1],
[2],
[3]], dtype=int32), array([[1, 0],
[2, 0],
[2, 1],
[3, 1],
[3, 0],
[3, 2]], dtype=int32), array([[2, 0, 1],
[3, 1, 0],
[3, 1, 2],
[3, 0, 2]], dtype=int32), array([[3, 1, 0, 2]], dtype=int32)]
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