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 details, 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 | |||||
| Incoherent Network |
Check out Usage and Examples!
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