6e9a58b20848646f37fcf24179fc29f28cabda3d,qiskit/optimization/algorithms/minimum_eigen_optimizer.py,MinimumEigenOptimizer,solve,#MinimumEigenOptimizer#Any#,158

Before Change

            samples = [(x_str, offset, 1.0)]

        // translate result back to integers
        result = OptimizationResult(x=x, fval=fval, variables=problem_.variables,
                                    status=OptimizationResultStatus.SUCCESS)

        result = self._interpret(result, self._converters)

        if result.fval is None or result.x is None:
            // if not function value is given, then something went wrong, e.g., a
            // NumPyMinimumEigensolver has been configured with an infeasible filter criterion.
            return MinimumEigenOptimizationResult(x=None, fval=None,
                                                  variables=result.variables,
                                                  status=OptimizationResultStatus.FAILURE,
                                                  samples=None,
                                                  min_eigen_solver_result=eigen_result)

        return MinimumEigenOptimizationResult(x=result.x, fval=result.fval,
                                              variables=result.variables,
                                              status=self._get_feasibility_status(problem,
                                                                                  result.x),
                                              samples=samples, min_eigen_solver_result=eigen_result)

After Change

                                                  samples=None,
                                                  min_eigen_solver_result=eigen_result)
        // translate result back to integers
        return cast(MinimumEigenOptimizationResult,
                    self._interpret(x=x, converters=self._converters, problem=problem,
                                    result_class=MinimumEigenOptimizationResult,
                                    samples=samples,
                                    min_eigen_solver_result=eigen_result))


def _eigenvector_to_solutions(eigenvector: Union[dict, np.ndarray, StateFn],
                              qubo: QuadraticProgram,

Instances