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Network Validation using the Spatial Coherence Framework.

Project description

Network Spatial Coherence

How good is your network? This package measures the spatial coherence of a network—how closely it resembles a physical network—. Additionally, it can reconstruct the network's original positions in space using the STRND algorithm. Networks can be simulated (if you don't have any) or imported, and weighted and bipartite networks are supported. For detailed methodologies, see Spatial Coherence and STRND papers.

Features

  • Analyze the spatial coherence of a network
  • Reconstruct images from purely network information - like drawing a country by only knowing which train stations are connected
  • Efficient graph loading and processing (sparse matrices)
  • Handles simulated graphs, custom graphs, unweighted graphs, weighted graphs, bipartite graphs

Install

Python 3.11 is reccomended, although older versions should work. See requirements.txt for dependencies.

pip install network_spatial_coherence

Example Results

OG Image SP Constant Net Dim Gram Mat REC Image
Coherent Network OG Image SP Constant Net Dim Gram Mat REC Image
Incoherent Network OG Image SP Constant Net Dim Gram Mat REC Image

Further information

Contact

[dfb@kth.se]

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