def getMaxGreedy_2(nodes_set, N, curr_nodes):
result = []
max_node = None
max_influence = 0
for i in nodes_set:
tmp = influence_function(N, curr_nodes + [i], 4)
if tmp > max_influence:
max_node = i
max_influence = tmp
return max_node
def calculateSK(nodes_set, N, K):
# Perform getMaxGreedy for three times to get the solution for S3
opt = []
curr_nodes = []
for i in range(K):
tmp = getMaxGreedy_2(nodes_set, N, curr_nodes)
curr_nodes = curr_nodes + [tmp]
nodes_set.remove(tmp)
max_influence = influence_function(N, curr_nodes, 4)
#print curr_nodes
return (curr_nodes, max_influence)
