1. Finding cliques (I)
Good work there! I hope you're now feeling proficient in making rational network visualizations with nxviz! In this next set of exercises, we're going to revise the concept of cliques. Are you able to recall
2. Cliques
the definition of a clique? Pause for a moment, and test yourself to see if it's still there in memory. Recall that a clique is a group of nodes that are fully connected to one another. The simplest clique is an edge, and the simplest "complex" clique is a triangle. There was one other concept that we introduced earlier,
3. Maximal cliques
and that's the idea of "maximal cliques". Are you able to recall the definition here as well? Try again by pausing the video for one moment. Did you get it? A maximal clique is a clique that cannot be extended by adding another node in the graph. Okay! Now that we've got the definitions recalled,
4. Finding cliques
let's quickly revise the NetworkX functions that are used for identifying cliques in a graph. What does the code look like for finding a clique? Let's go to the IPython terminal to play around. If I have a graph G, say, generated using one of NetworkX's graph generators, I can use the NetworkX find_cliques function, and iterate over all of the maximal cliques that it finds.
5. Let's practice!
With that little bit of revision, I think you're ready to go on to the exercises. Have fun!