bw2analyzer.page_rank#

Module Contents#

Classes#

PageRank

exception bw2analyzer.page_rank.ConvergenceError[source]#

Bases: Exception

Inheritance diagram of bw2analyzer.page_rank.ConvergenceError

Common base class for all non-exit exceptions.

Initialize self. See help(type(self)) for accurate signature.

class bw2analyzer.page_rank.PageRank(database)[source]#
calculate()[source]#
page_rank(technosphere, alpha=0.85, max_iter=100, tol=1e-06)[source]#

Return the PageRank of the nodes in the graph.

Adapted from http://networkx.lanl.gov/svn/networkx/trunk/networkx/algorithms/link_analysis/pagerank_alg.py

PageRank computes a ranking of the nodes in the graph G based on the structure of the incoming links. It was originally designed as an algorithm to rank web pages.

The eigenvector calculation uses power iteration with a SciPy sparse matrix representation.

Parameters

  • technosphere (*) – The technosphere matrix.

  • alpha (*) – Damping parameter for PageRank, default=0.85

Returns

  • Dictionary of nodes (activity codes) with value as PageRank

References

1

A. Langville and C. Meyer, “A survey of eigenvector methods of web information retrieval.” http://citeseer.ist.psu.edu/713792.html

2

Page, Lawrence; Brin, Sergey; Motwani, Rajeev and Winograd, Terry, The PageRank citation ranking: Bringing order to the Web. 1999 http://dbpubs.stanford.edu:8090/pub/showDoc.Fulltext?lang=en&doc=1999-66&format=pdf