SpringRank is a method for ranking the nodes in a directed network or from a set of pairwise comparisons.
In this repo, we provide three implementations of the SpringRank model described in:
- [1] C. De Bacco, D. B. Larremore and C. Moore, A physical model for efficient ranking in networks, Science Advances, Vol 4, 7, eaar8260, 2018. Science Advances PDF. arXiv PDF and here.
If you use this code please cite [1].
python: Python code and a test script.matlab: MATLAB code and a test script.r: R code and a test script.iml_sas:SAS/IML code.data: Contains sample adjacency files to test the code and a sample result.
Haskell: by Jon Zingale github.com/jonzingale/Haskell/.Python: Fast Sparse alternative code by Larremore Lab on PyPI github.com/LarremoreLab/SpringRank
Need to make a directory called data at the same level of the python folder.
To make one, just type from the command line, inside that folder:
mkdir data
The directed adjacency matrix should be formatted as an edge list with 3 columns:
node1 node2 3
The first and second columns are the source and target nodes of that edge, respectively; the third is the edge weigth (must be integer). In this example the edge node1 --> node2 exists with weight 3.
One file will be generated inside the data folder containg the SpringRank scores ordered from highest to lowest. The output file will be inside data folder with names:
networkname_SpringRank_a0.0_l0_1.0_l1_1.0.datfor the casealpha=0andl_0=l_1=1.0.
The first column is the node id, the second column is the SpringRank score.
Copyright (c) 2017 Caterina De Bacco and Daniel B Larremore
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