import random import networkx as nx import matplotlib.pyplot as plt from matplotlib import animation class Node: def __init__(self, is_infected=False): self.id = random.randint(1, 2000000) self.is_infected = is_infected def as_tuple(self): return self.id, self.is_infected def __repr__(self): return f'id: {self.id}, infected: {self.is_infected}' class Edge: def __init__(self, node_a: Node, node_b: Node, weight: float): self.node_a = node_a self.node_b = node_b self.weight = weight def as_tuple(self): return self.node_a, self.node_b, {'weight': self.weight} class Graph: def __init__(self): self.edges = [] def add_edge(self, edge: Edge): self.edges.append(edge) def add_edges(self, edges: [Edge]): [self.edges.append(e) for e in edges] def get_nodes(self) -> [Node]: nodes = set() for edge in self.edges: nodes.add(edge.node_a) nodes.add(edge.node_b) return nodes def update(num, layout, g_repr, ax, our_graph: Graph): """ This function is called every 'step', so if you wish to update the graph, do it here """ ax.clear() for n in our_graph.get_nodes(): n.is_infected = bool(random.getrandbits(1)) colors = ['red' if n.is_infected else 'blue' for n in g_repr] nx.draw_networkx(g_repr, ax=ax, pos=layout, node_color=colors, with_labels=False) def do_graph_animation(output_file_name: str, in_graph: Graph, frame_count: int): g_repr = nx.Graph() # Convert our graph class into tuples understood by networkx g_repr.add_edges_from([e.as_tuple() for e in in_graph.edges]) layout = nx.spring_layout(g_repr) fig, ax = plt.subplots() anim = animation.FuncAnimation(fig, update, frames=frame_count, fargs=(layout, g_repr, ax, in_graph)) anim.save(output_file_name) plt.show() def main(): network = Graph() nodes = [Node(True), Node(), Node(), Node(True), Node()] network.add_edges([ Edge(nodes[1], nodes[0], 0.02), Edge(nodes[1], nodes[2], 0.2), Edge(nodes[2], nodes[0], 0.7), Edge(nodes[3], nodes[2], 0.2), Edge(nodes[3], nodes[1], 0.2), Edge(nodes[4], nodes[3], 0.2) ]) do_graph_animation('test.gif', network, 5) if __name__ == "__main__": main()