plot_13_arcdiagram.rst

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Note

Click here <sphx_glr_download_sphinx_gallery_output_plot_13_arcdiagram.py> to download the full example code

sphx-glr-example-title

Arc Diagrams

import matplotlib.pyplot as plt
import networkx as nx

from netgraph import ArcDiagram

# Create a modular graph.
partition_sizes = [5, 6, 7]
g = nx.random_partition_graph(partition_sizes, 1, 0.1)

# Create a dictionary that maps nodes to the community they belong to,
# and set the node colors accordingly.
node_to_community = dict()
node = 0
for community_id, size in enumerate(partition_sizes):
    for _ in range(size):
        node_to_community[node] = community_id
        node += 1

community_to_color = {
    0 : 'tab:blue',
    1 : 'tab:orange',
    2 : 'tab:green',
}
node_color = {node: community_to_color[community_id] for node, community_id in node_to_community.items()}

ArcDiagram(g, node_size=1, node_color=node_color, node_edge_width=0, edge_alpha=1., edge_width=0.1)
plt.show()

/sphinx_gallery_output/images/sphx_glr_plot_13_arcdiagram_001.png

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Out:

/home/paul/src/netgraph/netgraph/_node_layout.py:847: UserWarning: Maximum number of iterations reached. Aborting further node layout optimisations.
  warnings.warn("Maximum number of iterations reached. Aborting further node layout optimisations.")

By default, ArcDiagram optimises the node order such that the number of edge crossings is minimised. For larger graphs, this process can take a long time. The node order can be set explicitly using the node_order argument. In this case, no optimisation is attempted.

ArcDiagram(g, node_order=range(len(g)), node_size=1, node_color=node_color, node_edge_width=0, edge_alpha=1., edge_width=0.1)

/sphinx_gallery_output/images/sphx_glr_plot_13_arcdiagram_002.png

sphx-glr-script-out

Out:

<netgraph._arcdiagram.ArcDiagram object at 0x7f034f543d30>

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Total running time of the script: ( 1 minutes 0.919 seconds)

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Gallery generated by Sphinx-Gallery