GraVE Documentation

import networkx as nx
from networkx.algorithms.centrality import closeness_centrality
import matplotlib.pyplot as plt

from grave import plot_network, use_attributes

toy_network = nx.barbell_graph(10, 14)
toy_centrality = closeness_centrality(toy_network)
max_centrality = max(toy_centrality.values())

for u, v, edge_attributes in toy_network.edges.data():
    c = (toy_centrality[u] +
         toy_centrality[v]) / 2
    color_idx = (c / max_centrality)
    cmap = plt.get_cmap()
    edge_attributes['color'] = cmap(color_idx)
    edge_attributes['width'] = 2

for node, node_attributes in toy_network.nodes.data():
    node_attributes['size'] = (1 - (toy_centrality[node] /
                                max_centrality) + .1) * 100


def edge_style(edge_attributes):
    return {'linewidth': edge_attributes.get('weight', 1)}

fig, ax = plt.subplots()
plot_network(toy_network,
             layout='spring',
             node_style=use_attributes(),
             edge_style=use_attributes('color'))
plt.show()

Total running time of the script: ( 0 minutes 0.154 seconds)