Skip to main content

SVG Hiveplot Python API

Project description

A nice way of visualizing complex networks are Hiveplots.

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

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,
                  fill='none', stroke_width='0.34', stroke_opacity='0.4',
    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,
                  fill='none', stroke_width='0.34', stroke_opacity='0.4',
    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,
                  fill='none', stroke_width='0.34', stroke_opacity='0.4',

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


Install library, perhaps within a virtualenv:

$ pip install pyveplot

Project details

Download files

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

Source Distribution

pyveplot-0.4.tar.gz (3.1 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page