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this package aims to contain Influence Maximization tools as much as possible.

So far, with the following algorithm models, it will continue to expand in the future:

• IMRank
• IC based on Monte Carlo
• IC based on LT
• Greedy based on IC

• IMRank: My blog
• IC based on Monte Carlo: My blog
• IC based on LT: My blog
• Greedy based on IC: My blog
• Simulated burst: My blog

this repository is a Influence Maximization tools kit, including Classic methods and algorithms for papers in recent years. Hopes to fill the gap in Maximizing Impact Problem in github.

## test based on IMRank
data = np.loadtxt('./graph.txt')
data = list(data)
IMRank(data)

 ## test Greedy based on IC
source = [0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,2,3,4,5]
target = [2,3,4,5,6,7,8,9,2,3,4,5,6,7,8,9,6,7,8,9]
g = Graph(directed=True)
g.add_vertices(range(10))
g.add_edges(zip(source, target))
greed_res = greedy(g, 2, p=0.2, mc=1000)
print(greed_res)