Concuss

- Basic patterns
- User can specify common patterns by name instead of needing a pattern file.
- Supports cliques, wheels, cycles, paths, stars, and bicliques of any size.
- Multiple patterns
- Can return counts for a set of patterns in a single run of CONCUSS.
- Compatible with basic patterns and custom pattern files
- BEAVr integration
- Compatible with visualization software [BEAVr](github.com/TheoryInPractice/BEAVr)
- Supports exporting archive of a single run to file for import by BEAVr

Initial release of CONCUSS: Combatting Network Complexity Using Structural Sparsity. CONCUSS is a Python software tool for large scale graph analytics whose efficiency and scalability come from exploiting the underlying "structural sparsity" of the data. Current modules use low-treedepth colorings (guaranteed in graph classes of bounded expansion) and allow users to count the number of occurences of a specific pattern within a graph (i.e. subgraph isomorphism counting).