qiskit_addon_opt_mapper.solvers.SolverResult¶

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

Bases: object

A base class for optimization results.

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

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

Examples

>>> from qiskit_addon_opt_mapper import OptimizationProblem
>>> from qiskit_addon_opt_mapper.solvers import CplexSolver
>>> problem = OptimizationProblem()
>>> _ = 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 = CplexSolver()
>>> 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 OptimizationProblem should maintain the order when generating a new SolverResult object.

Init method.

Parameters:

x (list[float] | np.ndarray | None) – the variable values found in the optimization, or possibly None in case of FAILURE.
fval (float) – the objective function value.
variables (list[Variable]) – the list of variables of the optimization problem.
raw_results (Any | None) – the original results object from the optimization algorithm.
status (SolverResultStatus) – the termination status of the optimization algorithm.
samples (list[SolutionSample] | None) – the solution samples.

Raises:

OptimizationError – if sizes of x and variables do not match or one of (fval, samples) is not provided.

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

Init method.

Parameters:

x (list[float] | ndarray | None) – the variable values found in the optimization, or possibly None in case of FAILURE.
fval (float) – the objective function value.
variables (list[Variable]) – the list of variables of the optimization problem.
raw_results (Any | None) – the original results object from the optimization algorithm.
status (SolverResultStatus) – the termination status of the optimization algorithm.
samples (list[SolutionSample] | None) – the solution samples.

Raises:

OptimizationError – if sizes of x and variables do not match or one of (fval, samples) is not provided.

Return type:

None

Methods

`__init__`(x, fval, variables, status[, ...])	Init method.
`get_correlations`()	Get <Zi x Zj> correlation matrix from the samples.
`prettyprint`()	Returns a pretty printed string of this optimization result.

Attributes

`fval`	Returns the objective 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 variable values as a dictionary of the variable name and corresponding value.
`x`	Returns the variable values found in the optimization or None in case of FAILURE.

property fval: float | None¶

Returns the objective function value.

Returns:: The function value corresponding to the objective function value found in the optimization.

get_correlations()[source]¶

Get <Zi x Zj> correlation matrix from the samples.

Returns:: A correlation matrix.
Return type:: ndarray

prettyprint()[source]¶

Returns a pretty printed string of this optimization result.

Returns:: A pretty printed string representing the result.
Return type:: str

property raw_results: Any¶

Return the original results object from the optimization algorithm.

Currently a dump for any leftovers.

Returns:: Additional result information of the optimization algorithm.

property samples: list[SolutionSample]¶

Returns the list of solution samples.

Returns:: The list of solution samples.

property status: SolverResultStatus¶

Returns the termination status of the optimization algorithm.

Returns:: The termination status of the algorithm.

property variable_names: list[str]¶

Returns the list of variable names of the optimization problem.

Returns:: The list of variable names of the optimization problem.

property variables: list[Variable]¶

Returns the list of variables of the optimization problem.

Returns:: The list of variables.

property variables_dict: dict[str, float]¶

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

Returns:: The variable values as a dictionary of the variable name and corresponding value.

property x: ndarray | None¶

Returns the variable values found in the optimization or None in case of FAILURE.

Returns:: The variable values found in the optimization.