I've just started doing graphs in networkx and I want to follow the evolution of a graph in time: how it changed, what nodes/edges are in the graph at a specified time t.
Here is my code:
import networkx as nx
import matplotlib.pyplot as plt
G=nx.Graph()
G.add_node(1,id=1000,since='December 2008')
G.add_node(2,id=2000,since='December 2008')
G.add_node(3,id=3000,since='January 2010')
G.add_node(4,id=2000,since='December 2016')
G.add_edge(1,2,since='December 2008')
G.add_edge(1,3,since='February 2010')
G.add_edge(2,3,since='March 2014')
G.add_edge(2,4,since='April 2017')
nx.draw_spectral(G,with_labels=True,node_size=3000)
plt.show()
This shows the graph with all the nodes and edges.
So, my question is:
How to design a time-based filter that will extract only the relevant nodes/edges on my graph G graph at time t, say for example 'July 2014'. When it is done, how do I update the graph with matplotlib?
Thank you in advance for your help
You may select nodes by conditions with list comprehension with G.nodes()
method:
selected_nodes = [n for n,v in G.nodes(data=True) if v['since'] == 'December 2008']
print (selected_nodes)
Out: [1, 2]
To select edges use G.edges_iter
or G.edges
methods:
selected_edges = [(u,v) for u,v,e in G.edges(data=True) if e['since'] == 'December 2008']
print (selected_edges)
Out: [(1, 2)]
To plot selected nodes call G.subgraph()
H = G.subgraph(selected_nodes)
nx.draw(H,with_labels=True,node_size=3000)
To plot selected edges with attributes you may construct new graph:
H = nx.Graph(((u, v, e) for u,v,e in G.edges(data=True) if e['since'] == 'December 2008'))
nx.draw(H,with_labels=True,node_size=3000)
plt.show()
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