DGSD (Distributed Graph Statistical Distances)

DGSD is a statistical graph descriptor that computes a feature vector from graph which can be used for many downstream machine learning tasks.

Quick start

import dgsd
import multiprocessing
import networkx as nx


g = nx.erdos_renyi_graph(100, 0.2) # create a random graph with 100 nodes
descriptor = dgsd.DGSD().get_descriptor(g,bins = 50, workers = 1) # compute the descriptor with given number of worker machines. Number of workers can be increased for fast and parallel processing

That's it!

Requirements

• numpy
• networkx
• multiprocessing

Installation

simply pip install DGSD

Citing

Please cite DGSD if you use this code in your own work:

@article{said2021dgsd,

title={DGSD: Distributed graph representation via graph statistical properties},

author={Said, Anwar and Hassan, Saeed-Ul and Tuarob, Suppawong and Nawaz, Raheel and Shabbir, Mudassir},

journal={Future Generation Computer Systems},

year={2021},

publisher={Elsevier}

}

Link to the paper: https://www.sciencedirect.com/science/article/abs/pii/S0167739X21000571