This is a Python script to perform a basic graph analysis on simple, undirected graphs.
The original aim of this script is to quickly generate solutions for the exercises of the Network complexity course taught in Politecnico di Milano by prof. Carlo Piccardi.
The script computes the following metrics:
- Diameter of the network
- Average distance
- Clustering coefficient (global and local)
- Efficiency of the network
- Degree of each node
- Closeness centrality
- Betweenness centrality
- k-core decomposition of nodes
This script requires Python 3 and the NetworkX package.
If you have already installed Python 3, you can install NetworkX with pip:
pip3 install networkx
To use the script, you'll need to provide a graph in a file as an adjacency list.
See the reference of the package for the syntax and the 20150204_es5.txt file for an example.
Usage:
python3 analyze.py <input_file>
Example:
python3 analyze.py 20150204_es5.txt
Sample output:
$ python3 analyze.py 20150204_es5.txt
Diameter: 4
Average shortest path: 2.3485
Average clustering: 0.5694
Efficiency of the network: 0.5518
Clustering for each node:
Node 1: 0.6667
Node 2: 0.3333
Node 3: 0.6667
Node 4: 0.3333
Node 5: 1.0000
Node 6: 0.3333
Node 7: 0.3333
Node 8: 1.0000
Node 9: 0.5000
Node 10: 0.6667
Node 11: 0.6667
Node 12: 0.3333
Node degrees:
Node 1: 3
Node 2: 3
Node 3: 3
Node 4: 3
Node 5: 2
Node 6: 3
Node 7: 3
Node 8: 3
Node 9: 4
Node 10: 4
Node 11: 4
Node 12: 3
Closeness centrality of nodes:
Node 1: 0.4231
Node 2: 0.4074
Node 3: 0.4231
Node 4: 0.4400
Node 5: 0.3667
Node 6: 0.4231
Node 7: 0.4400
Node 8: 0.3929
Node 9: 0.4583
Node 10: 0.4583
Node 11: 0.4583
Node 12: 0.4400
Betweenness centrality of nodes (not normalized):
Node 1: 3.6667
Node 2: 9.6667
Node 3: 3.6667
Node 4: 13.1667
Node 5: 0.0000
Node 6: 9.8333
Node 7: 11.8333
Node 8: 0.0000
Node 9: 14.1667
Node 10: 5.1667
Node 11: 5.1667
Node 12: 12.6667
k-core decomposition for each node:
Node 1: 2-core
Node 2: 2-core
Node 3: 2-core
Node 4: 2-core
Node 5: 2-core
Node 6: 2-core
Node 7: 2-core
Node 8: 3-core
Node 9: 3-core
Node 10: 3-core
Node 11: 3-core
Node 12: 2-core