1. © 2014, Selventa. All Rights Reserved. Scalable Networks with Graph-tool April 2014

2. © 2014, Selventa. All Rights Reserved. Scalable Networks with Graph-tool

3. © 2014, Selventa. All Rights Reserved. What is graph-tool? 3

4. © 2014, Selventa. All Rights Reserved. What is graph-tool? A Python library – E.g.: >>> g = Graph(directed=False) Innards written in C/C++ – Efficient use of memory – Excellent speed on consumer-grade hardware – Leverages multi-core capabilities through OpenMP Features – Lots of built-in algorithms (50+) – Does input/output in GraphML, Graphviz DOT, and GML – Allow “on-the-fly” filtering of graph components 4

5. © 2014, Selventa. All Rights Reserved. Memory Estimates 5

6. © 2014, Selventa. All Rights Reserved. How does it compare? Using the BEL large corpus for reference – 100k vertices – 160k edges In Java… – Using the popular TinkerPop graph stack – 360 MB is used In Python… – Using graph-tool – 55 MB is used 6

7. © 2014, Selventa. All Rights Reserved. Filtering Example “On-the-fly” filtering of graphs is easy! – E.g.: >>> vfilter = g.new_vertex_filter(’bool’) >>> for v in g.vertices():... # include vertex ‘v’... vfilter[v] = True... # alternatively, exclude with False... >>> g.set_vertex_filter(vfilter) >>> # clear previous filter >>> g.set_vertex_filter(None) 7