RecursiveMinimumEigenOptimizationResult¶
-
class
RecursiveMinimumEigenOptimizationResult(x, fval, variables, status, replacements, history)[source]¶ Bases:
qiskit.optimization.algorithms.optimization_algorithm.OptimizationResultRecursive 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
MinimumEigenOptimizerResultobtained by invokingMinimumEigenOptimizeriteratively, the second element is an instance ofOptimizationResultobtained 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.