/Game-Clustering

Game Clustering

Primary LanguagePython

Game-Clustering

Game Clustering Dr. CHAN Chung
Ali Al-Bashabsheh
Handason Tam
And big thanks to Zhao Chao
And thanks also to the implementation of Incremental Breadth-First Search
"Maximum Flows By Incremental Breadth-First Search" A.V. Goldberg, S.Hed, H. Kaplan, R.E. Tarjan, and R.F. Werneck

Run Experiment

$ git clone https://github.com/handasontam/Game-Clustering.git
$ conda create --name gameclustering python=3.5  # create virtual conda environment
$ source activate gameclustering
$ pip install -r requirements.txt
$ python run_experiment.py --cpu 2 --data data/example_graph.txt --output /tmp --undirected --unweighted --beta 0.5  # example

Usage

$ python run_experiment.py -h                                                                                    
usage: run_experiment.py [-h] --cpu CPU --data DATA
                                             --output OUTPUT [--directed]
                                             [--undirected] [--weighted]
                                             [--unweighted] --beta BETA


optional arguments:
  -h, --help       show this help message and exit
  --cpu CPU        number of cpu core to run the algorithm in parallel
  --data DATA      the file path of the graph data
  --output OUTPUT  the output directory
  --directed
  --undirected
  --weighted
  --unweighted
  --beta BETA      the beta value to use, range: [0,1]

Example Usage

# data/example_graph.txt
1 2 1
3 4 1
4 5 1
5 3 1

$ python run_experiment.py --cpu 2 --data data/example_graph.txt --output /tmp --undirected --weighted --beta 0.5