star_topology

network_attack_propagation.py

@@ -1,6 +1,8 @@
 import random
-import networkx as nx
+from statistics import mean
+
 import matplotlib.pyplot as plt
+import networkx as nx
 from matplotlib import animation
 
 
@@ -73,12 +75,36 @@ def do_graph_animation(output_file_name: str, in_graph: Graph, frame_count: int)
 def bus_network(n=30) -> Graph:
     network = Graph()
     nodes = [Node() for _ in range(n)]
-    edges = [Edge(nodes[i], nodes[i+1], 1.0) for i in range(n-1)]
+    edges = [Edge(nodes[i], nodes[i + 1], 1.0) for i in range(n - 1)]
 
     network.add_edges(edges)
     return network
 
 
+def rank_avg(edges, digits=2):
+    ranks = {}
+    for e in edges:
+        ranks[e.node_a] = ranks.get(e.node_a, 0) + 1
+        ranks[e.node_b] = ranks.get(e.node_b, 0) + 1
+    return round(mean(ranks.values()), digits)
+
+
+def star_network(cluster_count=5, starsize=6) -> tuple[Graph, float]:
+    node_count = cluster_count + cluster_count * starsize + 1
+    nodes = [Node() for _ in range(node_count)]
+
+    edges = []
+    for x in range(cluster_count):
+        center_node = x * starsize + x
+        edges += [Edge(nodes[center_node], nodes[i], 1.0) for i in range(center_node + 1, center_node + starsize + 1)]
+        edges.append(Edge(nodes[-1], nodes[center_node], 1.0))
+
+    network = Graph()
+    network.add_edges(edges)
+
+    return network, rank_avg(edges)
+
+
 def main():
     network = Graph()
     nodes = [Node(True), Node(), Node(), Node(True), Node()]
@@ -97,6 +123,9 @@ def main():
     bus = bus_network()
     do_graph_animation('bus.gif', bus, 5)
 
+    star, star_avg_rank = star_network()
+    do_graph_animation('star.gif', star, 5)
+
 
 if __name__ == "__main__":
     main()