<<<<<<< HEAD
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)