qiskit.optimization.algorithms.SlsqpOptimizationResult
class SlsqpOptimizationResult(x, fval, variables, status, fx=None, its=None, imode=None, smode=None)
SLSQP optimization result, defines additional properties that may be returned by the optimizer.
Constructs a result object with properties specific to SLSQP.
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 - fx (
Optional[ndarray]) – The value of the objective function being optimized, may be different fromfval - its (
Optional[int]) – The number of iterations. - imode (
Optional[int]) – The exit mode from the optimizer (see the documentation ofscipy.optimize.fmin_slsqp). - smode (
Optional[str]) – Message describing the exit mode from the optimizer. - status (
OptimizationResultStatus) – the termination status of the optimization algorithm.
__init__
__init__(x, fval, variables, status, fx=None, its=None, imode=None, smode=None)
Constructs a result object with properties specific to SLSQP.
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 - fx (
Optional[ndarray]) – The value of the objective function being optimized, may be different fromfval - its (
Optional[int]) – The number of iterations. - imode (
Optional[int]) – The exit mode from the optimizer (see the documentation ofscipy.optimize.fmin_slsqp). - smode (
Optional[str]) – Message describing the exit mode from the optimizer. - status (
OptimizationResultStatus) – the termination status of the optimization algorithm.
Methods
__init__(x, fval, variables, status[, fx, …]) | Constructs a result object with properties specific to SLSQP. |
Attributes
fval | Returns the optimal function value. |
fx | Returns the final value of the objective function being actually optimized. |
imode | Returns the exit mode from the optimizer. |
its | Returns the number of iterations |
raw_results | Return the original results object from the optimization algorithm. |
smode | Returns message describing the exit mode from the optimizer. |
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.
fx
Returns the final value of the objective function being actually optimized.
Return type
Optional[ndarray]
imode
Returns the exit mode from the optimizer.
Return type
Optional[int]
its
Returns the number of iterations
Return type
Optional[int]
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.
smode
Returns message describing the exit mode from the optimizer.
Return type
Optional[str]
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.