文件列表:

communities.py (13764, 2015-12-02)
input.txt (157, 2015-12-02)
input_test.txt (35, 2015-12-02)
output.txt (44, 2015-12-02)

# Community-Detection Implement a community detection algorithm using a divisive hierarchical clustering (Girvan-Newman algorithm) ## Overview Implement a community detection algorithm using a divisive hierarchical clustering (Girvan-Newman algorithm). It will make use of 2 python libraries called networkx and community. The networkx is a python library which can be installed on your machines. The assignment will require making use of the betweenness function and the modularity function which are a part of the networkx and the community libraries respectively. The matplotlib library will be used for plotting the communities. ## Main Steps - Read the input file into a graph using Networkx. - Use the betweenness of the edges as a measure to break communities into smaller - communities in divisive clustering. - The result should be the set of communities that have the highest modularity. - Use the modularity function in the community API - Use the betweenness function from networkx - After the best set of communities are obtained, use matplotlib and networkx functions to plot the communities with different colors. ## Execution Details The python code should take in two parameters, namely input file containing the graph and the output image with the community structure. For example: Python communities.py input.txt image.png ## Input Parameters ### input.txt This file consists of the representation of the graph. All graphs tested will be undirected graphs. Each line in the input file is of the format: 1 2 where 1 and 2 are the nodes and each line represents an edge between the two nodes. The nodes are separated by one space. ### image.png This will be a visualization of the communities detected by your algorithm. You should represent each communities in a unique color. Each node should contain a label representing the node numbers in the input file. ## Output The Python code should output the communities in the form of a dictionary to standard output (the console). Each community should be an array representing nodes in that community. In each array, the nodes should be sorted lexicographically. For example: [1,2,3,4] [5,6,7,8] [9] [10] These 4 arrays represent the 4 communities.

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