Repository for the network science project deliveries (MEIC-A 2017/2018)
The goal of this project was the exploration of the functionalities provided by the Networkx Python package and constructing a report of feedback (dificulties, strong points, neat tricks, etc.)
For this project we developed 3 modules with examples and utilities for analysing a dataset in the Networkx environment:
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basicstats.py
- functions to import the datasets in GML and JSON formats
- functions to return basic details on the dataset such as number of nodes/edges and is_type_X questions (is directed/connected/weighted/etc?)
- functions to print and draw information related to clustering metrics: triangles, clustering coeffcients and transitivity
-
cliques.py
- functions to calculate metrics related to cliques
- visualization utility functions to draw different types of graphs
-
assortativity.py
- functions to describe and calculate metrics of assortativity
There is also a datasets folder which contains the datasets we used during development to test our examples.