# Combinatorial Optimization Generators tools

Generators used to solve combinatorial problems could return a parsed result. This parsed result is a class containing:

class qat.opt.results.GraphPartitioningResult(graph, *args, **kwargs)

Class describing a graph partitioning. This class allows for the representation of a solution of a graph combinatorial optimization problem under the form of a networkx graph to provide a visual display to the solution

display(with_figure=False, figsize=(6.4, 4.8), node_size=300, font_size=12, **kwargs)

Display the partitions using the draw_networkx method from networkx

Parameters
• with_figure (bool, optional) – wrap the displayed in a matplotlib.pyplot figure

• figsize (tuple, optional) – the size of the matplotlib.pyplot figure, only used if with_figure is True

• node_size (int, optional) – the size of the node in the diagram passed to the draw_networkx function

• font_size (int, optional) – the font size in the diagram passed to the draw_networkx function

## K-Clique result

Generator `KCliqueGenerator` will cast the `Result` returned by the QPU into a `KCliqueResult` (which is a subclass of `GraphPartitioningResult`)

class qat.opt.results.KCliqueResult(graph, *args, **kwargs)

Result of a KClique problem. This class adds an attribute clique used to extract the clique found

property clique

Extract the nodes in the graph that forms the clique

## Vertex cover result

Generator `VertexCoverGenerator` will cast the `Result` returned by the QPU into a `VertexCoverResult` (which is a subclass of `GraphPartitioningResult`)

class qat.opt.results.VertexCoverResult(graph, *args, **kwargs)

Result of a VertexCover problem. This class adds an attribute cover used to extract the vertex cover

property cover

Extract the nodes in the graph that forms the cover