how to draw directed graphs using networkx in python?

directed-graph, graph, networkx, plot, python

Solution

Fully fleshed out example with arrows for only the red edges:

import networkx as nx
import matplotlib.pyplot as plt

G = nx.DiGraph()
G.add_edges_from(
    [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),
     ('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')])

val_map = {'A': 1.0,
           'D': 0.5714285714285714,
           'H': 0.0}

values = [val_map.get(node, 0.25) for node in G.nodes()]

# Specify the edges you want here
red_edges = [('A', 'C'), ('E', 'C')]
edge_colours = ['black' if not edge in red_edges else 'red'
                for edge in G.edges()]
black_edges = [edge for edge in G.edges() if edge not in red_edges]

# Need to create a layout when doing
# separate calls to draw nodes and edges
pos = nx.spring_layout(G)
nx.draw_networkx_nodes(G, pos, cmap=plt.get_cmap('jet'), 
                       node_color = values, node_size = 500)
nx.draw_networkx_labels(G, pos)
nx.draw_networkx_edges(G, pos, edgelist=red_edges, edge_color='r', arrows=True)
nx.draw_networkx_edges(G, pos, edgelist=black_edges, arrows=False)
plt.show()

Problem

I have some nodes coming from a script that I want to map on to a graph. In the below, I want to use Arrow to go from A to D and probably have the edge colored too in (red or something). This is basically, like a path from A to D when all other nodes are present. you can imagine each nodes as cities and traveling from A to D requires directions (with arrow heads). This code below builds the graph ``` import networkx as nx import numpy as np import matplotlib.pyplot as plt G = nx.Graph() G.add_edges_from( [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'), ('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')]) val_map = {'A': 1.0, 'D': 0.5714285714285714, 'H': 0.0} values = [val_map.get(node, 0.25) for node in G.nodes()] nx.draw(G, cmap = plt.get_cmap('jet'), node_color = values) plt.show() ``` but I want something like shown in the image. Arrow heads of the first image and the edges in red color onto the second image.

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