A Python graph library based on numpy and scipy with some machine learning features
It can create and modify user defined and/or random generated graphs, find shortest paths, and can write graphs to Pajek files for visualization.
- Write to Pajek, and simple CSV files
- Some machine learning features - date preprocessing, kernels, wrappers for LibSVM, and some mlpy learning algorithms
- Unit tested using the Python unittest framework
- Directed, undirected and multigraphs designed under a hierarchical class structure
- Sparse and Dense graph structures using numpy and scipy for fast linear algebra computations
- Many operations on graphs such as subgraphs, search, Floyd-Warshall, Dijkstras algorithm
- Erdos-Renyi, Small-World and Albert-Barabasi random graphs
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