Bipartite graph series#

And now, well the first thing I'm going to do is I'm going to add the nodes, and to add the notes I'm going to use the function add nodes from rather than add nodes, and what this allows me to do, is to add a set of nodes from a list. Like I said, there's no separate class for bipartite graphs. So, to construct these bipartite graph, what I'm going to do is I'm going to use the class graph. NetworkX does not have a separate class for bipartite graph, but it does have a set of algorithms that allow us to study them and to analyze them and to do things with them, and so for that we would import bipartite to get that set of algorithms. And so in this particular example the two sets would be the sets of fans, this will be L, and the set of basketball teams which would be R. So, no edge connects a node from L to another node in L, and no edge connects a node in R to another node in R. So, just to be a little bit more specific, a graph is a bipartite graph if it has two sets of nodes which we call L and R, and every single edge connects a node from L to R. And that's exactly what a bipartite graphs is. In this case, one set of nodes is fans and the other set of nodes is basketball teams. So this graph has a particular structure that all the edges go from one set of nodes to another set of nodes. So, one aspect of this graph is that you couldn't imagine that it would make sense to add an edge between the fans, right? Because fans are not fans of other fans, are fans of teams, or edges between the basketball teams, because basketball teams have fans, they're not really fans of other teams. And here the edges represent the fact that a particular fan is a fan of a particular team. So the nodes on green A, B, C, D and E, are people who are fans of basketball teams, 1, 2, 3, and 4. So, here's an example of fans of specific basketball teams. So before I tell you what the actual definition of a bipartite graphs, let me give you a little sense for, in what kinds of cases they are important, or just a particular example of what describes bipartite graph. We haven't looked at a particular type of graph that is very interesting and useful for certain types of applications, and these are called bipartite graphs. We've looked at undirected graphs, directed graphs, multi graphs, signed graphs, weighted graphs and so on. R-release (arm64): bipartite_2.17.tgz, r-oldrel (arm64): bipartite_2.17.tgz, r-release (x86_64): bipartite_2.17.tgz, r-oldrel (x86_64): bipartite_2.17.So, in the past videos we've looked at different types of graphs. R-devel: bipartite_2.17.zip, r-release: bipartite_2.17.zip, r-oldrel: bipartite_2.17.zip Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology. It focuses on webs consisting of only two levels (bipartite), e.g.

Bipartite graph series#

Bipartite: Visualising Bipartite Networks and Calculating Some (Ecological)įunctions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs.