NOESIS for Python

Official Python API for NOESIS, an open source framework for network data mining that provides a large collection of network analysis techniques, including the analysis of network structural properties, community detection methods, link scoring, and link prediction, as well as network visualization algorithms.


From source:

git clone https://github.com/fvictor/noesis-python.git
cd noesis-python
python setup.py install

From PyPi:

pip install noesis

Getting started

NOESIS for Python provides simple and unified interfaces for most of the implemented techniques. The following example loads a network from a GML file and detects its communities using the Kernighan–Lin algorithm:

from noesis import Noesis

ns = Noesis()

network_reader = ns.create_network_reader('GML')
network = network_reader.read('my_network.gml')

community_detector = ns.create_community_detector('KernighanLin')
communities = community_detector.compute(network)

for node in range(network.nodes()):
        print('Node {} belongs to community {}'.format(node, communities[node]))


The following example generates a network of 20 nodes and 100 links using the Erdös–Rényi model and computes the PageRank score of each node:

from noesis import Noesis

ns = Noesis()

network = ns.create_network_from_model('ErdosRenyi', 20, 100)

pagerank_scorer = ns.create_node_scorer('PageRank', 0.9)
scores = pagerank_scorer.compute(network)

for node in range(network.nodes()):
        print('Node {} has a PageRank score of {}'.format(node, scores[node]))


Always remember to call the end method of Noesis class to properly terminate the NOESIS session and finish the execution of your program.

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