qiskit.optimization.algorithms.OptimizationResult¶

class OptimizationResult(x, fval, variables, status, raw_results=None, samples=None)[source]¶

A base class for optimization results.

The optimization algorithms return an object of the type OptimizationResult with the information about the solution obtained.

OptimizationResult allows users to get the value of a variable by specifying an index or a name as follows.

Exemples

>>> from qiskit.optimization import QuadraticProgram
>>> from qiskit.optimization.algorithms import CplexOptimizer
>>> problem = QuadraticProgram()
>>> _ = problem.binary_var('x1')
>>> _ = problem.binary_var('x2')
>>> _ = problem.binary_var('x3')
>>> problem.minimize(linear={'x1': 1, 'x2': -2, 'x3': 3})
>>> print([var.name for var in problem.variables])
['x1', 'x2', 'x3']
>>> optimizer = CplexOptimizer()
>>> result = optimizer.solve(problem)
>>> print(result.variable_names)
['x1', 'x2', 'x3']
>>> print(result.x)
[0. 1. 0.]
>>> print(result[1])
1.0
>>> print(result['x1'])
0.0
>>> print(result.fval)
-2.0
>>> print(result.variables_dict)
{'x1': 0.0, 'x2': 1.0, 'x3': 0.0}

Note

The order of variables should be equal to that of the problem solved by optimization algorithms. Optimization algorithms and converters of QuadraticProgram should maintain the order when generating a new OptimizationResult object.

Paramètres

x (Union[List[float], ndarray, None]) – the optimal value found in the optimization, or possibly None in case of FAILURE.
fval (float) – the optimal function value.
variables (List[Variable]) – the list of variables of the optimization problem.
raw_results (Optional[Any]) – the original results object from the optimization algorithm.
status (OptimizationResultStatus) – the termination status of the optimization algorithm.
samples (Optional[List[SolutionSample]]) – the solution samples.

Lève

QiskitOptimizationError – if sizes of x and variables do not match.

__init__(x, fval, variables, status, raw_results=None, samples=None)[source]¶

Paramètres

x (Union[List[float], ndarray, None]) – the optimal value found in the optimization, or possibly None in case of FAILURE.
fval (float) – the optimal function value.
variables (List[Variable]) – the list of variables of the optimization problem.
raw_results (Optional[Any]) – the original results object from the optimization algorithm.
status (OptimizationResultStatus) – the termination status of the optimization algorithm.
samples (Optional[List[SolutionSample]]) – the solution samples.

Lève

QiskitOptimizationError – if sizes of x and variables do not match.

Methods

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

type x: Union[List[float], ndarray, None]

Attributes

`fval`	Returns the optimal function value.
`raw_results`	Return the original results object from the optimization algorithm.
`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.

Type renvoyé: float
Renvoie: The function value corresponding to the optimal value found in the optimization.

property raw_results¶

Return the original results object from the optimization algorithm.

Currently a dump for any leftovers.

Type renvoyé: Any
Renvoie: Additional result information of the optimization algorithm.

property samples¶

Returns the list of solution samples

Type renvoyé: List[SolutionSample]
Renvoie: The list of solution samples.

property status¶

Returns the termination status of the optimization algorithm.

Type renvoyé: OptimizationResultStatus
Renvoie: The termination status of the algorithm.

property variable_names¶

Returns the list of variable names of the optimization problem.

Type renvoyé: List[str]
Renvoie: The list of variable names of the optimization problem.

property variables¶

Returns the list of variables of the optimization problem.

Type renvoyé: List[Variable]
Renvoie: The list of variables.

property variables_dict¶

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

Type renvoyé: Dict[str, float]
Renvoie: 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.

Type renvoyé: Optional[ndarray]
Renvoie: The optimal value found in the optimization.