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This project is archived. Current development moved to GitLab:

https://gitlab.com/rgarcia-herrera/pyveplot

Pyveplot

A nice way of visualizing complex networks are Hiveplots.

This library uses svgwrite to programmatically create images like this one:

https://github.com/CSB-IG/pyveplot/raw/master/example.png

A short example

Create a plot from a network, randomly selecting whichever axis to place 50 nodes.:

from pyveplot import *
import networkx, random

# a network
g = networkx.barabasi_albert_graph(50, 2)

# our hiveplot object
h = Hiveplot( 'short_example.svg')
            # start      end
axis0 = Axis( (200,200), (200,100), stroke="grey")
axis1 = Axis( (200,200), (300,300), stroke="blue")
axis2 = Axis( (200,200), (10,310),  stroke="black")

h.axes = [ axis0, axis1, axis2 ]

# randomly distribute nodes in axes
for n in g.nodes():
    node = Node(n)
    random.choice( h.axes ).add_node( node, random.random() )

for e in g.edges():
    if (e[0] in axis0.nodes) and (e[1] in axis1.nodes):       # edges from axis0 to axis1
        h.connect(axis0, e[0], 45,
                  axis1, e[1], -45,
                  stroke_width='0.34', stroke_opacity='0.4',
                  stroke='purple')
    elif (e[0] in axis0.nodes) and (e[1] in axis2.nodes):     # edges from axis0 to axis2
        h.connect(axis0, e[0], -45,
                  axis2, e[1], 45,
                  stroke_width='0.34', stroke_opacity='0.4',
                  stroke='red')
    elif (e[0] in axis1.nodes) and (e[1] in axis2.nodes):     # edges from axis1 to axis2
        h.connect(axis1, e[0], 15,
                  axis2, e[1], -15,
                  stroke_width='0.34', stroke_opacity='0.4',
                  stroke='magenta')

h.save()

https://github.com/CSB-IG/pyveplot/raw/master/short_example.png

The more elaborate example.py shows how to use shapes for nodes, placement of the control points and attributes of edges, and the attributes of axes.

Installation

Install library, perhaps within a virtualenv:

$ pip install pyveplot