qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult

class RecursiveMinimumEigenOptimizationResult(x, fval, variables, status, replacements, history)

Recursive Eigen Optimizer Result.

Constructs an instance of the result class.

パラメータ

• 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 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.

__init__(x, fval, variables, status, replacements, history)

Constructs an instance of the result class.

パラメータ

• 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 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.

Methods

__init__(x, fval, variables, status, …)

Constructs an instance of the result class.

Attributes

fval	Returns the optimal function value.
history	Returns intermediate results.
raw_results	Return the original results object from the optimization algorithm.
replacements	Returns a dictionary of substituted variables.
status	Returns the termination status of the optimization algorithm.
variable_names	Returns the list of variable names of the optimization problem.
variables	Returns the list of variables of the optimization problem.
variables_dict	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.

property fval

Returns the optimal function value.

戻り値の型

float

戻り値

The function value corresponding to the optimal value found in the optimization.

property 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.

戻り値の型

Tuple[List[MinimumEigenOptimizationResult], OptimizationResult]

property raw_results

Return the original results object from the optimization algorithm.

Currently a dump for any leftovers.

戻り値の型

Any

戻り値

Additional result information of the optimization algorithm.

property 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.

戻り値の型

Dict[str, Tuple[str, int]]

property status

Returns the termination status of the optimization algorithm.

戻り値の型

OptimizationResultStatus

戻り値

The termination status of the algorithm.

property variable_names

Returns the list of variable names of the optimization problem.

戻り値の型

List[str]

戻り値

The list of variable names of the optimization problem.

property variables

Returns the list of variables of the optimization problem.

戻り値の型

List[Variable]

戻り値

The list of variables.

property variables_dict

Returns the optimal value as a dictionary of the variable name and corresponding value.

戻り値の型

Dict[str, float]

戻り値

The optimal value as a dictionary of the variable name and corresponding value.

property x

Returns the optimal value found in the optimization or None in case of FAILURE.

戻り値の型

Optional[ndarray]

戻り値

The optimal value found in the optimization.