Created
May 24, 2019 09:06
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Recreating Graph Visualization in Randomly Wired Neural Network
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| import networkx as nx | |
| def to_directed(graph): | |
| G = nx.DiGraph(source=[], sink=[]) | |
| for node in range(graph.number_of_nodes()): | |
| neighbors = list(graph.neighbors(node)) | |
| neighbors.sort() | |
| if node < neighbors[0]: # input nodes | |
| G.graph['source'].append(node) | |
| G.add_node(node, node_type=0, fillcolor='deepskyblue1') | |
| elif node > neighbors[-1]: # output nodes | |
| G.graph['sink'].append(node) | |
| G.add_node(node, node_type=1, fillcolor='firebrick3') | |
| else: # intermediate nodes | |
| G.add_node(node, node_type=-1, fillcolor='white') | |
| for neighbor in neighbors[::-1]: | |
| if node >= neighbor: | |
| break | |
| G.add_edge(node, neighbor) | |
| return G | |
| def draw_graph(graph, filename): | |
| A = nx.nx_agraph.to_agraph(graph) # convert to a graphviz graph | |
| A.node_attr.update(label=" ", shape='circle', style='filled') # label = " " ensures label to be white | |
| A.add_subgraph(graph.graph['source'], rank='source') | |
| A.add_subgraph(graph.graph['sink'], rank='sink') | |
| A.draw(filename, format='png', prog='dot') | |
| if __name__ == "__main__": | |
| n = 32 | |
| K = 4 | |
| P = 0.75 | |
| G = nx.random_graphs.connected_watts_strogatz_graph(n, K, P, tries=200) | |
| D = to_directed(G) | |
| draw_graph(D, "directed.png") |
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