Plotting directed graphs in Python in a way that show all edges separately

Question

I'm using Python to simulate a process that takes place on directed graphs. I would like to produce an animation of this process.

The problem that I've run into is that most Python graph visualization libraries combine pairs of directed edges into a single edge. For example, NetworkX draws only two edges when displaying the following graph, whereas I would like to display each of the four edges separately:

import networkx as nx
import matplotlib.pyplot as plt 

G = nx.MultiDiGraph()

G.add_edges_from([
    (1, 2),
    (2, 3),
    (3, 2),
    (2, 1),
])

plt.figure(figsize=(8,8))
nx.draw(G)

I would like to display something like this, with each parallel edge drawn separately:

The question R reciprocal edges in igraph in R seems to deal with the same issue, but the solution there is for the R igraph library, not the Python one.

Is there an easy way to produce this style of plot using an existing Python graph visualization library? It would be a bonus if it could support multigraphs.

I'm open to solutions that invoke an external program to produce the images. I'd like to generate a whole series of animation frames, so the solution must be automated.

Answer 1

The Graphviz tools appear to display distinct edges.

For example, giving this:

digraph G {   A -> B;   A -> B;   A -> B;   B -> C;    B -> A;   C -> B; } 

to dot produces:

Graphviz's input language is pretty simple so you can generate it on your own, though searching for "python graphviz" does turn up a couple of libraries including a graphviz module on PyPI.

Here's python that generates the above graph using the graphviz module:

from graphviz import Digraph  dot = Digraph() dot.node('A', 'A') dot.node('B', 'B') dot.node('C', 'C') dot.edges(['AB', 'AB', 'AB', 'BC', 'BA', 'CB'])  print(dot.source) dot.render(view=True) 

Answer 2

Using NetworkX, a possible workaround which avoids file I/O and uses dot via pydot for layout is:

import networkx as nx import matplotlib.pyplot as plt import matplotlib.image as mpimg from io import BytesIO  g = nx.dodecahedral_graph() d = nx.drawing.nx_pydot.to_pydot(g)     # `d` is a `pydot` graph object,     # `dot` options can be easily set     # attributes get converted from `networkx`,     # use set methods to control     # `dot` attributes after creation png_str = d.create_png() sio = BytesIO() # file-like string, appropriate for imread below sio.write(png_str) sio.seek(0) img = mpimg.imread(sio) imgplot = plt.imshow(img) plt.show()  # added to make the script wait before exiting 

for why seek(0) is needed, see How to create an image from a string in python

If within the IPython (qt)console, then the above will print inline and a more direct approach is:

import networkx as nx from IPython.display import Image  g = nx.dodecahedral_graph() d = nx.drawing.nx_pydot.to_pydot(g)  png_str = d.create_png() Image(data=png_str) 

Answer 3

Maybe I am a little late but I found another solution to you issue. I am posting it so that it can be helpful if somebody has the same problem.

It is possible to plot directed graphs with networkx using matplotlib in a way that the edges appear separately, by passing the argument connectionstyle to the function networkx.drawing.nx_pylab.draw:

import matplotlib.pyplot as plt
import networkx as nx


# create a directed multi-graph
G = nx.MultiDiGraph()
G.add_edges_from([
    (1, 2),
    (2, 3),
    (3, 2),
    (2, 1),
])
# plot the graph
plt.figure(figsize=(8,8))
nx.draw(G, connectionstyle='arc3, rad = 0.1')
plt.show()  # pause before exiting

Here you see the result:

See also the documentation of matplotlib.patches.ConnectionStyle about the argument connectionstyle.