pygmtools.multi_graph_solvers
Classic (learningfree) multigraph matching solvers. These multigraph matching solvers are recommended to solve the joint matching problem of multiple graphs.
Note
Multigraph matching means jointly matching \(\geq\) 3 graphs. It is different from twograph matching because multigraph matching is a more challenging problem and requires different solvers.
What makes multigraph matching more challenging is the socalled cycleconsistency constraint: a multigraph
matching solution has to be cycleconsistent, meaning that any pairwise matching result should be the same as
the result propagated from a third graph. For example, denote \(\mathbf{X}_{i,j}\) as the matching matrix
between graph i
and graph j
, it requires
\(\forall i,j,k, \mathbf{X}_{i,j} = \mathbf{X}_{i,k} \mathbf{X}_{k,j}\).
Such an extra constraint offers an extra source of information, but makes the problem itself more challenging
to solve.
Functions
Composition based Affinity Optimization (CAO) solver for multigraph matching. 

Graduated Assignmentbased multigraph matching solver. 

MultiGraph Matching based on Floyd shortest path algorithm. 