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The triangle count algorithm counts the number of triangles (triplet of nodes which all pairwise share a link) that each vertex is a member of, from which additionally the global graph triangle count and clustering coefficient can be realised.
A connected component of an undirected graph is a set of vertices all of which are connected by paths to each other. This algorithm calculates the number of connected components in the graph and the size of each, and returns some statisics of these.
Returns the communities of the constructed graph as detected by synchronous label propagation.
In the previous entry, you learnt how to write your own spout and router to ingest the data. In here, you are to learn how to write an analyser that will run algorithms that you want to test with your data. Depending on the type of algorithm that you want to implement, a set of these modules are to be defined:
In this section, you’re going to go through the steps to have Raphtory up and running on your local machine. To make it as easy as possible, an example Raphtory project is available here.
Now that you have a working version of Raphtory on your machine, the first step to getting your first temporal graph analysis up and running is to tell Raphtory how to read in your datafile and how to build it into a graph. This is done by the Spout and Graph Builder classes respectively. Once these are build they can be passed to a
RaphtoryGraph which will use the both components to build up the temporal graph.