qiskit.optimization.algorithms.GroverOptimizationResult
class GroverOptimizationResult(x, fval, variables, operation_counts, n_input_qubits, n_output_qubits, intermediate_fval, threshold, status)
A result object for Grover Optimization methods.
Constructs a result object with the specific Grover properties.
Parameters
- x (
Union[List[float],ndarray]) – The solution of the problem - fval (
float) – The value of the objective function of the solution - variables (
List[Variable]) – A list of variables defined in the problem - operation_counts (
Dict[int,Dict[str,int]]) – The counts of each operation performed per iteration. - n_input_qubits (
int) – The number of qubits used to represent the input. - n_output_qubits (
int) – The number of qubits used to represent the output. - intermediate_fval (
float) – The intermediate value of the objective function of the solution, that is expected to be identical withfval. - threshold (
float) – The threshold of Grover algorithm. - status (
OptimizationResultStatus) – the termination status of the optimization algorithm.
__init__
__init__(x, fval, variables, operation_counts, n_input_qubits, n_output_qubits, intermediate_fval, threshold, status)
Constructs a result object with the specific Grover properties.
Parameters
- x (
Union[List[float],ndarray]) – The solution of the problem - fval (
float) – The value of the objective function of the solution - variables (
List[Variable]) – A list of variables defined in the problem - operation_counts (
Dict[int,Dict[str,int]]) – The counts of each operation performed per iteration. - n_input_qubits (
int) – The number of qubits used to represent the input. - n_output_qubits (
int) – The number of qubits used to represent the output. - intermediate_fval (
float) – The intermediate value of the objective function of the solution, that is expected to be identical withfval. - threshold (
float) – The threshold of Grover algorithm. - status (
OptimizationResultStatus) – the termination status of the optimization algorithm.
Methods
__init__(x, fval, variables, …) | Constructs a result object with the specific Grover properties. |
Attributes
fval | Returns the optimal function value. |
intermediate_fval | Getter of the intermediate fval |
n_input_qubits | Getter of n_input_qubits |
n_output_qubits | Getter of n_output_qubits |
operation_counts | Get the operation counts. |
raw_results | Return the original results object from the optimization algorithm. |
status | Returns the termination status of the optimization algorithm. |
threshold | Getter of the threshold of Grover 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.
intermediate_fval
Getter of the intermediate fval
Return type
float
Returns
The intermediate value of fval before interpret.
n_input_qubits
Getter of n_input_qubits
Return type
int
Returns
The number of qubits used to represent the input.
n_output_qubits
Getter of n_output_qubits
Return type
int
Returns
The number of qubits used to represent the output.
operation_counts
Get the operation counts.
Return type
Dict[int, Dict[str, int]]
Returns
The counts of each operation performed per iteration.
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.
status
Returns the termination status of the optimization algorithm.
Return type
OptimizationResultStatus
Returns
The termination status of the algorithm.
threshold
Getter of the threshold of Grover algorithm.
Return type
float
Returns
The threshold of Grover 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.