bleh

scripts/Strategies.py

@@ -1,8 +1,10 @@
 import random
+import networkx as nx
 
 from CityGraph import CityGraph
 from Attack import Attack, print_suppression_edge
 
+
 # Juste pour test pour l'instant
 ville="Saints"
 
@@ -98,6 +100,12 @@ def moving_attack(graph : CityGraph, nbTimes : int, budget : int) -> Attack :
 		for edge_idx in range(graph.nb_edges()) :
 			if nb_people_on_edges[edge_idx] > 0 :
 				# Move the people
+
+				# If there are no neighbours, stay on the edge
+				if len(neighbours[edge_idx]) == 0 :
+					attacks.add_attack(time, edge_idx)
+					continue
+
 				edge_idx2 = random.choice(list(neighbours[edge_idx]))
 				nb_people_on_edges[edge_idx] -= graph.get_nb_lanes_of_edge(edge_idx)
 				nb_people_on_edges[edge_idx2] += graph.get_nb_lanes_of_edge(edge_idx)
@@ -117,6 +125,46 @@ def moving_attack(graph : CityGraph, nbTimes : int, budget : int) -> Attack :
 
 	return attacks
 
+def is_bridge(graph : CityGraph, node0 : int, node1 : int) -> bool :
+	"""Returns True if the edge is a bridge"""
+	# TODO : ca marche pas pour les graphes orientes car networkx veut me rendre malheureux	
+	# Remove the edge
+	graph.graph.remove_edge(node0, node1)
+	# Check if the graph is still connected
+	is_connected = nx.is_connected(graph.graph)
+	# Add the edge back
+	graph.graph.add_edge(node0, node1)
+	return not is_connected
+
+
+def connex_attack(graph : CityGraph, nbTimes : int, budget : int) -> Attack :
+	"""We remove edges which cut the graph into two parts recursively
+	Algorithm reference : https://stackoverflow.com/questions/11218746/bridges-in-a-connected-graph"""
+
+	attacks = Attack(graph)
+	edges = list(graph.edges())
+
+	# Find the bridge with the highest betweenness centrality
+	# Then remove it
+	for time in range(nbTimes) :
+		# Find the bridge with the highest betweenness centrality
+		bridge = None
+		max_betweenness = 0
+		for edge_idx in range(graph.nb_edges()) :
+			edge = graph.get_edge_at(edge_idx)
+			if is_bridge(graph, edge[0], edge[1]) :
+				betweenness = graph.get_edge_betweenness_centrality(edge_idx)
+				if betweenness > max_betweenness :
+					bridge = edge_idx
+					max_betweenness = betweenness
+		if bridge is not None :
+			attacks.add_attack(time, bridge)
+		else :
+			break
+
+		print_suppression_edge(graph, bridge)
+
+	return attacks
 
 graph = CityGraph(ville)
 graph.print_stats()
@@ -131,4 +179,6 @@ def moving_attack(graph : CityGraph, nbTimes : int, budget : int) -> Attack :
 # a = betweenness_centralities_attack(graph, 10, 10)
 # a.write_to_file("test_betweenness_centralities_attack.txt")
 a = moving_attack(graph, 10, 100)
-a.write_to_file("test_moving_attack.txt")
+a.write_to_file("test_moving_attack.txt")
+a = connex_attack(graph, 10, 10)
+a.write_to_file("test_connex_attack.txt")

test_connex_attack.txt

@@ -0,0 +1 @@
+0

test_moving_attack.txt

@@ -1,153 +1,149 @@
-152
-1 20 2 4 9
-5 1 3 0 6 10
-5 30 9 0 1 2 3 5 6 7 8 10
+148
+0 1 2 0 10
+0 5 3 4 5 9
+1 20 9 1 2 3 4 5 6 7 8 9
+2 3 2 0 10
+2 7 6 1 2 5 6 8 9
+3 4 11 0 1 2 3 4 5 6 7 8 9 10
+5 1 3 0 4 10
+5 30 4 1 2 6 9
 6 63 2 0 10
-8 15 3 2 3 5
-8 26 8 0 1 3 4 7 8 9 10
-8 31 3 5 6 9
-9 26 4 0 3 9 10
-9 60 4 1 3 4 6
-9 61 3 4 5 8
-10 23 3 0 1 10
-10 33 4 2 4 6 7
-10 42 7 0 1 3 4 5 8 10
-11 12 7 0 1 3 4 6 7 10
-11 50 3 2 8 10
-12 11 6 0 2 5 6 9 10
-12 13 8 0 1 2 3 4 5 7 10
-12 55 8 0 3 4 6 7 8 9 10
-13 12 6 0 1 5 6 9 10
-13 14 7 0 3 4 6 7 8 10
-13 55 11 0 1 2 3 4 5 6 7 8 9 10
-14 13 4 1 2 3 7
-14 51 5 3 4 5 8 9
-14 56 5 0 2 5 7 10
-15 8 1 3
-15 16 4 0 2 4 10
-15 82 4 2 7 8 9
-16 15 6 0 1 5 6 9 10
-16 17 8 0 2 3 4 5 7 8 10
-16 57 7 0 1 3 4 6 8 10
-17 16 5 0 4 7 9 10
-17 26 7 0 1 3 5 6 7 10
-17 61 7 1 2 3 4 6 7 9
-18 19 7 0 1 2 4 7 8 10
-18 36 5 0 1 2 5 10
-19 18 6 1 5 6 7 8 9
-19 75 6 0 3 4 7 9 10
-20 19 5 1 2 5 7 8
-20 75 2 0 10
-21 48 2 0 10
-21 50 2 0 10
-22 23 5 1 3 6 7 10
-22 39 5 0 5 8 9 10
-22 45 4 3 4 9 10
-23 10 4 1 2 6 9
-23 22 3 7 8 9
-23 60 7 0 2 3 4 5 7 10
-24 25 1 9
-24 40 2 1 6
-25 24 3 0 3 10
-25 37 5 2 5 7 8 9
-25 81 5 3 4 5 7 8
-26 8 7 0 1 2 3 6 7 10
-26 9 6 0 5 7 8 9 10
-26 17 9 1 2 3 4 5 6 7 8 9
-27 28 2 7 9
-27 67 4 1 3 4 6
-28 27 2 0 10
-28 29 1 2
-28 73 2 5 8
-29 28 1 9
-29 30 1 4
-30 5 5 4 5 6 8 9
-30 29 6 0 1 3 8 9 10
-30 63 8 0 1 2 3 5 7 8 10
-31 8 4 0 4 8 10
-31 32 5 0 2 6 7 10
-31 37 3 0 2 10
-32 31 8 1 2 3 4 5 6 7 9
-32 34 8 0 3 4 5 7 8 9 10
-32 62 6 0 1 2 5 8 10
-34 32 4 0 2 7 10
-34 35 5 3 4 5 6 9
-35 34 3 0 9 10
-35 36 4 1 4 8 9
-35 65 4 3 4 7 8
-36 18 4 0 1 2 10
-36 35 8 0 3 4 5 6 7 8 10
-36 70 4 3 5 6 9
-37 25 6 0 3 5 7 9 10
-37 31 4 1 2 6 8
-38 39 4 1 5 6 10
-38 43 7 0 1 2 3 6 9 10
-38 47 7 2 3 4 5 8 9 10
-39 22 8 0 1 4 6 7 8 9 10
-39 38 6 0 2 3 4 8 9
-39 76 4 0 3 5 10
-42 10 9 1 2 3 4 5 6 7 8 9
-42 42 4 0 3 8 10
-43 38 3 6 7 8
-44 46 8 0 1 2 3 5 6 8 9
-44 48 6 1 2 3 5 7 10
-44 56 7 0 3 5 6 7 8 10
-45 22 5 0 1 2 8 9
-45 46 6 0 1 2 5 7 10
-45 53 5 1 5 6 8 10
-46 44 4 0 3 4 6
-46 45 4 2 4 7 9
-46 53 8 0 2 3 4 7 8 9 10
-47 38 3 3 4 7
-48 21 5 2 4 7 8 10
-48 44 6 0 1 3 5 6 10
-48 51 6 4 5 6 8 9 10
-49 51 1 7
-50 11 7 3 4 5 6 7 9 10
-50 21 3 2 3 8
-50 55 3 1 9 10
-51 14 6 0 5 7 8 9 10
-51 48 5 1 3 4 6 9
-51 49 9 0 2 3 4 5 6 8 9 10
-51 52 5 1 2 4 5 6
-52 51 2 0 10
-53 45 4 1 3 4 8
-53 46 2 2 9
-53 54 3 4 5 7
-55 12 4 1 2 6 9
-55 13 4 1 4 7 8
-55 50 2 0 5
-56 14 4 1 4 8 9
-56 44 2 6 9
-56 80 2 2 6
-57 16 1 7
-57 59 7 0 4 5 6 8 9 10
-57 68 4 1 2 6 9
-59 57 4 0 5 7 10
-59 58 7 1 3 4 6 7 8 9
-59 60 3 1 5 6
-60 9 3 3 5 8
-60 23 3 2 3 4
-60 59 3 0 5 10
-61 9 1 6
-61 17 2 0 10
-61 69 3 4 5 8
-62 32 4 2 4 7 9
-63 6 6 2 3 4 6 8 9
-63 30 6 0 4 5 8 9 10
-63 71 6 1 2 3 4 6 7
-64 65 2 0 10
-65 35 3 2 3 5
-65 64 6 1 2 4 6 7 9
-65 66 5 1 5 6 8 9
-66 65 2 0 10
-71 63 2 4 6
-71 72 1 3
-71 73 2 2 8
-72 71 3 0 4 10
-72 73 7 1 2 5 6 7 8 9
-72 74 3 1 3 5
-74 72 2 0 10
-75 2 6 2 3 4 6 8 9
-76 39 3 2 6 7
-76 77 1 8
+7 3 2 0 10
+8 15 7 0 1 4 6 7 9 10
+8 26 3 1 6 8
+8 31 6 0 3 4 5 9 10
+9 26 7 0 2 3 5 6 7 10
+9 60 9 0 1 2 4 5 7 8 9 10
+9 61 9 0 2 4 5 6 7 8 9 10
+10 23 6 0 1 2 8 9 10
+10 33 6 0 3 6 7 9 10
+10 42 7 1 2 3 4 5 6 7
+11 12 1 4
+11 50 1 10
+12 11 5 0 1 3 5 7
+12 13 4 0 2 3 10
+12 55 4 1 2 4 9
+13 12 2 4 6
+13 14 5 1 2 5 7 8
+13 55 2 2 8
+14 13 6 0 1 3 4 8 10
+14 51 3 3 5 9
+14 56 6 0 4 6 7 9 10
+15 8 5 0 2 3 6 10
+15 16 5 1 2 7 8 9
+15 82 9 0 1 2 3 4 5 6 7 10
+16 15 2 0 10
+16 17 1 9
+16 57 2 5 7
+17 16 4 3 4 7 8
+17 26 4 4 6 8 9
+17 61 1 1
+18 19 8 1 2 3 4 6 7 8 9
+18 36 7 0 1 3 6 7 9 10
+19 18 8 0 1 2 3 5 6 9 10
+19 75 7 0 3 4 5 7 9 10
+20 19 7 0 2 4 5 6 7 10
+20 75 3 0 8 10
+22 23 5 0 4 8 9 10
+22 39 4 2 3 5 10
+22 45 6 0 2 4 6 7 10
+23 10 2 1 3
+23 22 6 0 1 2 3 4 8
+23 60 4 2 5 7 8
+25 24 3 1 3 9
+25 37 2 0 10
+25 81 3 2 4 5
+26 8 3 0 7 10
+26 9 8 0 1 2 3 4 5 9 10
+26 17 6 0 5 6 7 8 10
+28 27 7 1 2 4 5 7 8 9
+28 29 7 0 3 5 7 8 9 10
+28 73 5 0 2 3 4 10
+29 28 5 1 3 4 7 9
+29 30 3 5 6 8
+30 5 4 0 1 2 10
+30 29 6 0 4 5 6 8 10
+30 63 7 1 2 3 6 7 8 9
+31 8 3 1 3 8
+31 32 6 1 3 4 5 7 9
+31 37 7 0 2 3 5 7 9 10
+32 31 4 3 5 8 9
+32 34 4 0 5 6 10
+32 62 4 1 2 4 7
+33 10 10 0 1 2 3 4 6 7 8 9 10
+33 41 9 0 2 3 4 5 7 8 9 10
+34 32 7 0 1 3 6 7 8 10
+34 35 5 0 1 2 4 10
+35 34 5 1 3 6 7 9
+35 36 8 1 2 3 4 5 6 7 8
+35 65 5 0 2 5 9 10
+36 18 9 0 1 2 3 5 6 8 9 10
+36 35 8 0 2 4 5 6 8 9 10
+36 70 6 1 2 4 5 7 8
+37 25 3 6 7 8
+37 31 4 0 2 6 10
+38 39 6 0 2 4 5 6 9
+38 43 7 1 2 3 4 6 8 10
+38 47 7 0 1 3 4 7 8 10
+39 22 6 2 4 5 8 9 10
+39 38 5 0 5 6 9 10
+39 76 7 0 2 3 6 8 9 10
+41 33 6 0 3 5 6 9 10
+42 10 11 0 1 2 3 4 5 6 7 8 9 10
+42 42 3 0 4 10
+43 38 5 0 1 5 7 9
+44 46 5 1 2 3 4 9
+44 48 6 0 2 3 6 9 10
+44 56 9 0 1 3 5 6 7 8 9 10
+45 22 2 4 10
+45 46 2 4 6
+45 53 10 0 1 2 3 4 5 7 8 9 10
+46 44 5 0 3 6 7 10
+46 45 3 2 4 10
+46 53 6 4 5 6 8 9 10
+47 38 3 1 5 7
+48 21 4 2 3 5 9
+48 44 4 0 3 4 10
+48 51 5 0 6 7 8 10
+49 51 2 0 10
+50 11 2 6 9
+50 21 1 7
+50 55 2 8 10
+51 14 9 0 1 2 3 4 6 7 8 10
+51 48 2 1 2
+51 49 5 2 5 7 8 9
+51 52 6 1 4 5 6 8 9
+53 45 4 3 4 5 8
+53 54 3 6 7 9
+55 12 2 0 10
+55 13 2 7 8
+55 50 4 3 6 8 9
+56 14 4 1 3 5 9
+56 44 5 2 4 5 6 8
+56 80 6 0 1 3 4 7 10
+57 16 3 2 7 8
+57 59 7 1 2 3 4 5 7 9
+57 68 5 0 6 8 9 10
+60 9 3 0 9 10
+60 23 4 3 4 6 8
+60 59 4 1 4 6 8
+61 9 8 0 2 3 5 6 7 8 10
+61 17 5 0 1 4 8 10
+61 69 3 1 6 7
+63 6 4 3 5 6 8
+63 30 5 0 1 4 7 10
+63 71 4 2 3 5 9
+65 35 2 2 5
+65 66 2 4 9
+68 57 5 0 4 5 6 10
+70 36 2 0 10
+73 28 4 0 6 9 10
+73 71 2 2 8
+73 72 3 1 5 6
+75 2 7 1 3 4 6 7 8 9
+76 39 3 1 5 7
+76 77 1 3
+80 56 2 2 4
+80 82 2 5 7
+82 15 1 4
+82 81 2 5 6