Labeling edges in networkx

user_5524637 0
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I'm programming a basic neural network and want to plot it as a picture. For that, I created all the nodes and edges I need.

    for l, j in zip(self.layers, range(len(self.layers))):
        for n, i in zip(l.neurons, range(len(l.neurons))):
            fixed_positions[n.identifier] = (j, i)
    for l in self.layers:
        for n in l.neurons:
            for c, w in zip(n.inconnections, n.inconnectionweights):
               g.add_edge(n.identifier, c.identifier)
    fixed_nodes = fixed_positions.keys()
    pos = nx.spring_layout(g, pos=fixed_positions, fixed=fixed_nodes)

enter image description here

the blue points (imagine them on all edges) are where I want to add a label onto the edges, but I don't know how to do it. It's supposed to work for any reasonable net size, i.e. it should also work for 4, 3 and 2 neurons in the respective layers.

networkx python
3 Answers

Here is an example for ploting edge label in networkx, hope it will help you.

import matplotlib.pyplot as plt
import networkx as nx

edges = [['A', 'B'], ['B', 'C'], ['B', 'D']]
G = nx.Graph()
G.add_edges_from(edges)
pos = nx.spring_layout(G)
plt.figure()
nx.draw(
    G, pos, edge_color='black', width=1, linewidths=1,
    node_size=500, node_color='pink', alpha=0.9,
    labels={node: node for node in G.nodes()}
)
nx.draw_networkx_edge_labels(
    G, pos,
    edge_labels={('A', 'B'): 'AB', 
                 ('B', 'C'): 'BC', 
                 ('B', 'D'): 'BD'},
    font_color='red'
)
plt.axis('off')
plt.show()

edge label

user_87433280

You can use draw_networkx_edge_labels(edge_labels) to draw label between edges.

  • If edge_labels is not given, the attributes of edge is used.
  • edge_labels should be a dictionary keyed by edge two-tuple of text labels. Only labels for the keys in the dictionary are drawn.

To iterate through the edges of graph, you can use G.edges.

  • G.edges returns a list of (node1, node2), where node1 and node2 are two nodes of the edge.
  • G.edges(data=True) returns a list of (node1, node2, ddict), where ddict is edge attribute dict.
  • G.edges(data=attr) returns a list of (node1, node2, ddict[attr])
import matplotlib.pyplot as plt
import networkx as nx

G = nx.DiGraph()

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

pos = nx.spring_layout(G)

nx.draw_networkx(G, pos)

edge_labels = dict([((n1, n2), f'{n1}->{n2}')
                    for n1, n2 in G.edges])

nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels)

plt.show()

enter image description here

With G.edges(data=True)

import matplotlib.pyplot as plt
import networkx as nx

G = nx.Graph()
G.add_edge(1, 2, weight=3)
G.add_edge(2, 3, weight=5)

pos = nx.spring_layout(G)

nx.draw(G, pos, with_labels=True)

edge_labels = dict([((n1, n2), d['weight'])
                    for n1, n2, d in G.edges(data=True)])

nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels, label_pos=0.9,
                             font_color='red', font_size=16, font_weight='bold')

plt.show()

enter image description here

user_103151630

you can use the edge attributes of G

nx.draw(G, with_labels=True, node_color='skyblue', edge_cmap=plt.cm.Blues, pos = pos)
edge_labels = nx.get_edge_attributes(G,'edge') # key is edge, pls check for your case
formatted_edge_labels = {(elem[0],elem[1]):edge_labels[elem] for elem in edge_labels} # use this to modify the tuple keyed dict if it has > 2 elements, else ignore
nx.draw_networkx_edge_labels(G,pos,edge_labels=formatted_edge_labels,font_color='red')
plt.show()
user_59096980
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