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Topological sorting
This example demonstrates how to get a topological sorting on a directed acyclic graph (DAG). A topological sorting of a directed graph is a linear ordering based on the precedence implied by the directed edges. It exists iff the graph doesn’t have any cycle. In igraph
, we can use igraph.GraphBase.topological_sorting()
to get a topological ordering of the vertices.
import igraph as ig
import matplotlib.pyplot as plt
First off, we generate a directed acyclic graph (DAG):
g = ig.Graph(
edges=[(0, 1), (0, 2), (1, 3), (2, 4), (4, 3), (3, 5), (4, 5)],
directed=True,
)
We can verify immediately that this is actually a DAG:
assert g.is_dag
A topological sorting can be computed quite easily by calling
igraph.GraphBase.topological_sorting()
, which returns a list of vertex IDs.
If the given graph is not DAG, the error will occur.
results = g.topological_sorting(mode='out')
print('Topological sort of g (out):', *results)
Topological sort of g (out): 0 1 2 4 3 5
In fact, there are two modes of igraph.GraphBase.topological_sorting()
,
'out'
'in'
. 'out'
is the default and starts from a node with
indegree equal to 0. Vice versa, 'in'
starts from a node with outdegree
equal to 0. To call the other mode, we can simply use:
results = g.topological_sorting(mode='in')
print('Topological sort of g (in):', *results)
Topological sort of g (in): 5 3 1 4 2 0
We can use igraph.Vertex.indegree()
to find the indegree of the node.
for i in range(g.vcount()):
print('degree of {}: {}'.format(i, g.vs[i].indegree()))
# %
# Finally, we can plot the graph to make the situation a little clearer.
# Just to change things up a bit, we use the matplotlib visualization mode
# inspired by `xkcd <https://xkcd.com/>_:
with plt.xkcd():
fig, ax = plt.subplots(figsize=(5, 5))
ig.plot(
g,
target=ax,
layout='kk',
vertex_size=25,
edge_width=4,
vertex_label=range(g.vcount()),
vertex_color="white",
)
degree of 0: 0
degree of 1: 1
degree of 2: 1
degree of 3: 2
degree of 4: 1
degree of 5: 2
Total running time of the script: (0 minutes 0.176 seconds)