Skip to main content

Equitable coloring for networkX graphs.

Project description

Equitable coloring for networkX graphs.

From Wikipedia:

In graph theory [..] an equitable coloring is an assignment of colors to the vertices of an undirected graph, in such a way that

  • No two adjacent vertices have the same color, and
  • The numbers of vertices in any two color classes differ by at most one.

Kierstead et. al. have provided a fast polynomial time algorithm for uncovering an equitable coloring using r + 1 colors for a graph with maximum degree r. This package is an implementation of the algorithm for networkX graphs.

  • Free software: MIT license


pip install equitable-coloring


To use equitable-coloring:

>>> import networkx as nx
>>> from equitable_coloring import equitable_color
>>> from equitable_coloring.utils import is_equitable
>>> G = nx.cycle_graph(4)
>>> d = equitable_color(G, num_colors=3)
>>> is_equitable(G, d)


To run the all tests run:

pip install pytest-cov  # Needed the first time.
python test

Or, you can use tox.


0.1.2 (2018-06-30)

  • Update README and usage instructions.

0.1.1 (2018-06-30)

  • Initial version with tests.

0.1.0 (2018-06-11)

  • First commit.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for equitable-coloring, version 0.1.2
Filename, size File type Python version Upload date Hashes
Filename, size equitable_coloring-0.1.2-py2.py3-none-any.whl (15.6 kB) File type Wheel Python version py2.py3 Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page