1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
|
"""
.. _tutorials-dag:
======================
Directed Acyclic Graph
======================
This example demonstrates how to create a random directed acyclic graph (DAG), which is useful in a number of contexts including for Git commit history.
"""
import igraph as ig
import matplotlib.pyplot as plt
import random
# %%
# First, we set a random seed for reproducibility.
random.seed(0)
# %%
# First, we generate a random undirected graph with a fixed number of edges, without loops.
g = ig.Graph.Erdos_Renyi(n=15, m=30, directed=False, loops=False)
# %%
# Then we convert it to a DAG *in place*. This method samples DAGs with a given number of edges and vertices uniformly.
g.to_directed(mode="acyclic")
# %%
# We can print out a summary of the DAG.
ig.summary(g)
# %%
# Finally, we can plot the graph using the Sugiyama layout from :meth:`igraph.Graph.layout_sugiyama`:
fig, ax = plt.subplots()
ig.plot(
g,
target=ax,
layout="sugiyama",
vertex_size=15,
vertex_color="grey",
edge_color="#222",
edge_width=1,
)
plt.show()
|
