Displays the input graph in a "hierarchical" layout.
Displays the Gomory Hu tree of the graph. Here you can see possible clusters and choose
the best cut.
The label- or weight-attributes of edges are used for the calcultation of the minimal cuts. When both label and weight attributes are present and both can be converted to floating point numbers the weight-attributes take priority. If only a label attribute is present it is copied into a weight attribute. Note that the weight attribute is also used by the lay-out algorithm in the sense that it tries to shorten edges with high weight values. The weight values must be positive numbers.
Note that a graph with many equal weights may have many equal minimal cuts. So if you choose a node pair the program will show just one of these cuts! There may be quite different cuts with the same cut-weight that you wo'nt see. A solution is to add small different offsets to the equal weights (e.g. 1.01, 1.02, 1.03 instead of 1, 1, 1) and experiment with different distributions of these offsets.
The graph is divided into two clusters. The split is along the
minimal cut between the first two nodes specified in the text area
(A5 and A1 in the example graph on the left). If you want the split calculated between two different nodes
you have to move these nodes to the top in the text area.
See here for an explanation of minimal cut, modularity and centrality score.