GraphOptimizationApplication#

class GraphOptimizationApplication(graph)[source]#

Bases: OptimizationApplication

An abstract class for graph optimization applications.

Parameters:: graph (Graph | ndarray | List) – A graph representing a problem. It can be specified directly as a NetworkX graph, or as an array or list format suitable to build out a NetworkX graph.

Attributes

graph#

Getter of the graph

Returns:: A graph for a problem

Methods

draw(result=None, pos=None)[source]#

Draw a graph with the result. When the result is None, draw an original graph without colors.

Parameters:

result (OptimizationResult | ndarray | None) – The calculated result for the problem
pos (Dict[int, ndarray] | None) – The positions of nodes

abstract interpret(result)#

Convert the calculation result of the problem (OptimizationResult or a binary array using np.ndarray) to the answer of the problem in an easy-to-understand format.

Parameters:: result (OptimizationResult | ndarray) – The calculated result of the problem

static sample_most_likely(state_vector)#

Compute the most likely binary string from state vector.

Parameters:: state_vector (QuasiDistribution | Statevector | ndarray | Dict) – state vector or counts or quasi-probabilities.
Returns:: binary string as numpy.ndarray of ints.
Raises:: ValueError – if state_vector is not QuasiDistribution, Statevector, np.ndarray, or dict.
Return type:: ndarray

abstract to_quadratic_program()#

Convert a problem instance into a QuadraticProgram

Return type:: QuadraticProgram