RecursiveMinimumEigenOptimizationResult
class RecursiveMinimumEigenOptimizationResult(x, fval, variables, status, replacements, history)
Bases: qiskit.optimization.algorithms.optimization_algorithm.OptimizationResult
Recursive Eigen Optimizer Result.
Constructs an instance of the result class.
Parameters
- x (
Union[List[float],ndarray]) – the optimal value found in the optimization. - fval (
float) – the optimal function value. - variables (
List[Variable]) – the list of variables of the optimization problem. - status (
OptimizationResultStatus) – the termination status of the optimization algorithm. - replacements (
Dict[str,Tuple[str,int]]) – a dictionary of substituted variables. Key is a variable being substituted, value is a tuple of substituting variable and a weight, either 1 or -1. - history (
Tuple[List[MinimumEigenOptimizationResult],OptimizationResult]) – a tuple containing intermediate results. The first element is a list ofMinimumEigenOptimizerResultobtained by invokingMinimumEigenOptimizeriteratively, the second element is an instance ofOptimizationResultobtained at the last step via min_num_vars_optimizer.
Attributes
fval
Returns the optimal function value.
Return type
float
Returns
The function value corresponding to the optimal value found in the optimization.
history
Returns intermediate results. The first element is a list of MinimumEigenOptimizerResult obtained by invoking MinimumEigenOptimizer iteratively, the second element is an instance of OptimizationResult obtained at the last step via min_num_vars_optimizer.
Return type
Tuple[List[MinimumEigenOptimizationResult], OptimizationResult]
raw_results
Return the original results object from the optimization algorithm.
Currently a dump for any leftovers.
Return type
Any
Returns
Additional result information of the optimization algorithm.
replacements
Returns a dictionary of substituted variables. Key is a variable being substituted, value is a tuple of substituting variable and a weight, either 1 or -1.
Return type
Dict[str, Tuple[str, int]]
samples
Returns the list of solution samples
Return type
List[SolutionSample]
Returns
The list of solution samples.
status
Returns the termination status of the optimization algorithm.
Return type
OptimizationResultStatus
Returns
The termination status of the algorithm.
variable_names
Returns the list of variable names of the optimization problem.
Return type
List[str]
Returns
The list of variable names of the optimization problem.
variables
Returns the list of variables of the optimization problem.
Return type
List[Variable]
Returns
The list of variables.
variables_dict
Returns the optimal value as a dictionary of the variable name and corresponding value.
Return type
Dict[str, float]
Returns
The optimal value as a dictionary of the variable name and corresponding value.
x
Returns the optimal value found in the optimization or None in case of FAILURE.
Return type
Optional[ndarray]
Returns
The optimal value found in the optimization.