partition_graph_color#

m4opt.utils.optimization.partition_graph_color(graph, partition, **kwargs)[source] [edit on github]#

Find a coloring for a partition of a graph.

Parameters:

graph (Graph) – A graph in the form of a networkx.Graph object.
partition (ndarray) – Partition assignments of the nodes in the graphs as returned by partition_graph().
**kwargs – Any additional arguments to pass to networkx.algorithms.coloring.greedy_color.

Returns:

An integer-valued array of color assignments for each partition. The color for node i in the original graph is color[partition[i]].

Return type:

ndarray

Example

from matplotlib import pyplot as plt
from m4opt.utils.optimization import partition_graph, partition_graph_color
import networkx as nx

graph = nx.triangular_lattice_graph(20, 40)
part = partition_graph(graph, 20, seed=42)
color = partition_graph_color(
    graph, part, strategy="connected_sequential", interchange=True)
ax = plt.axes(aspect=1)
nx.draw(
    graph,
    ax=ax,
    pos=nx.get_node_attributes(graph, "pos"),
    node_size=50,
    node_color=color[part],
    cmap="cool",
)

(Source code)

../_images/m4opt-utils-optimization-partition_graph_color-1.svg