Labeling edges in networkx

Question

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) 

the blue points (imagine them on all edges) are where i want to add a label onto the edges, but i dont know how to do it. Its supposed to work for any reasonable net size, i.e. it shoudl also work for 4, 3 and 2 neurons in the resprective layers.

Answer 1

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()  

Answer 2

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() 

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()