This repository is for the project of the course MPRI 2.29.2: Graph Mining. The goal is to implement the Fully Dynamic k-center Clustering algorithm.
This implementation was tested on Python 3.5, but it should be able to run on Python 3.4+ without any problem. Additional packages can be installed using the command pip3 install -r requirements.txt.
The script can be run via CLI: python3 main.py [OPTIONS]
-h, --help show this help message and exit
-p PROC, --proc PROC The number of parallel processes to run the algorithm.
Default: os.cpu_count() = 8.
-l LIMIT, --limit LIMIT
The total number of points to be inserted in the
algorithm. Default: 1000.
-w WINDOW, --window WINDOW
The size of the sliding window. Default: 60.
The results will be saved in the file results_{limit}_{window}.json. The relevant plots can be obtained from the notebook report.ipynb. This notebook uses the seaborn library to obtain cleaner plots, but it is easy to remove the usage of seaborn if necessary.