create python script for directed graph

2023-round-2/achluma/nx_tutorial_script.py

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+import networkx as nx
+import matplotlib.pyplot as plt
+
+# Create a NetworkX DiGraph graph object
+G = nx.DiGraph()
+
+# Add nodes of multiple type
+G.add_node(1, node_type='int')
+G.add_node('A', node_type='str')
+G.add_node((2, 3), node_type='tuple')
+G.add_node('B', node_type='str')
+G.add_node(4, node_type='int')
+G.add_node('C', node_type='str')
+G.add_node('D', node_type='str')
+G.add_node((5, 6), node_type='tuple')
+G.add_node('E', node_type='str')
+G.add_node(7, node_type='int')
+
+# Add multiple edges between these nodes
+G.add_edge(1, 'A')
+G.add_edge('A', (2, 3))
+G.add_edge('A', 'B')
+G.add_edge('B', 4)
+G.add_edge('B', 'C')
+G.add_edge('C', 'D')
+G.add_edge('C', (5, 6))
+G.add_edge('C', 'E')
+G.add_edge((5, 6), 7)
+G.add_edge(7, 1)
+
+# Find the shortest path between all pairs of nodes in the graph
+shortest_paths = dict(nx.all_pairs_shortest_path(G))
+
+# Print shortest paths
+for source_node, paths in shortest_paths.items():
+    for target_node, path in paths.items():
+        if source_node != target_node:
+            print(f"Shortest path from {source_node} to {target_node}: {path}")
+
+# Plot the graph using networkx.draw
+pos = nx.spring_layout(G, seed=42)  
+node_colors = {'int': 'red', 'str': 'blue', 'tuple': 'green'}
+node_colors_list = [node_colors[data['node_type']] for _, data in G.nodes(data=True)]
+nx.draw(G, pos, with_labels=True, node_color=node_colors_list)
+plt.show()