qiskit.optimization.algorithms.MinimumEigenOptimizationResult
class MinimumEigenOptimizationResult(x, fval, variables, status, samples, min_eigen_solver_result=None)
Minimum Eigen Optimizer Result.
Parameters
- x (
Union[List[float],ndarray]) – the optimal value found byMinimumEigensolver. - 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. - samples (
List[Tuple[str,float,float]]) – the basis state as bitstring, the QUBO value, and the probability of sampling. - min_eigen_solver_result (
Optional[MinimumEigensolverResult]) – the result obtained from the underlying algorithm.
__init__
__init__(x, fval, variables, status, samples, min_eigen_solver_result=None)
Parameters
- x (
Union[List[float],ndarray]) – the optimal value found byMinimumEigensolver. - 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. - samples (
List[Tuple[str,float,float]]) – the basis state as bitstring, the QUBO value, and the probability of sampling. - min_eigen_solver_result (
Optional[MinimumEigensolverResult]) – the result obtained from the underlying algorithm.
Methods
__init__(x, fval, variables, status, samples) | type xUnion[List[float], ndarray] |
get_correlations() | Get <Zi x Zj> correlation matrix from samples. |
Attributes
fval | Returns the optimal function value. |
min_eigen_solver_result | Returns a result object obtained from the instance of MinimumEigensolver. |
raw_results | Return the original results object from the optimization algorithm. |
samples | Returns 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. |
fval
Returns the optimal function value.
Return type
float
Returns
The function value corresponding to the optimal value found in the optimization.
get_correlations
get_correlations()
Get <Zi x Zj> correlation matrix from samples.
Return type
ndarray
min_eigen_solver_result
Returns a result object obtained from the instance of MinimumEigensolver.
Return type
MinimumEigensolverResult
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.
samples
Returns samples.
Return type
List[Tuple[str, float, float]]
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.