qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult

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

Recursive Eigen Optimizer Result.

Constructs an instance of the result class.

Parâmetros

• 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.

Parâmetros

• 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.
samples	Returns the list of solution samples
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.

Tipo de retorno

float

Retorna

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.

Tipo de retorno

Tuple[List[MinimumEigenOptimizationResult], OptimizationResult]

property raw_results

Return the original results object from the optimization algorithm.

Currently a dump for any leftovers.

Tipo de retorno

Any

Retorna

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.

Tipo de retorno

Dict[str, Tuple[str, int]]

property samples

Returns the list of solution samples

Tipo de retorno

List[SolutionSample]

Retorna

The list of solution samples.

property status

Returns the termination status of the optimization algorithm.

Tipo de retorno

OptimizationResultStatus

Retorna

The termination status of the algorithm.

property variable_names

Returns the list of variable names of the optimization problem.

Tipo de retorno

List[str]

Retorna

The list of variable names of the optimization problem.

property variables

Returns the list of variables of the optimization problem.

Tipo de retorno

List[Variable]

Retorna

The list of variables.

property variables_dict

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

Tipo de retorno

Dict[str, float]

Retorna

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.

Tipo de retorno

Optional[ndarray]

Retorna

The optimal value found in the optimization.