QuadraticObjective#

class QuadraticObjective(quadratic_program, constant=0.0, linear=None, quadratic=None, sense=ObjSense.MINIMIZE)[fuente]#

Representation of quadratic objective function of the form: constant + linear * x + x * quadratic * x.

Constructs a quadratic objective function.

Parámetros:

quadratic_program (Any) – The parent quadratic program.
constant (float) – The constant offset of the objective.
linear (ndarray | spmatrix | List[float] | Dict[int | str, float] | None) – The coefficients of the linear part of the objective.
quadratic (ndarray | spmatrix | List[List[float]] | Dict[Tuple[int | str, int | str], float] | None) – The coefficients of the quadratic part of the objective.
sense (ObjSense) – The optimization sense of the objective.

Attributes

constant#

Returns the constant part of the objective function.

linear#

Returns the linear part of the objective function.

quadratic#

Returns the quadratic part of the objective function.

quadratic_program#

Returns the parent QuadraticProgram.

sense#

Returns the sense of the objective function.

Methods

evaluate(x)[fuente]#

Evaluate the quadratic objective for given variable values.

Parámetros:: x (ndarray | List | Dict[int | str, float]) – The values of the variables to be evaluated.
Devuelve:: The value of the quadratic objective given the variable values.
Muestra:: QiskitOptimizationError – if the shape of the objective function does not match with the number of variables.
Tipo del valor devuelto:: float

evaluate_gradient(x)[fuente]#

Evaluate the gradient of the quadratic objective for given variable values.

Parámetros:: x (ndarray | List | Dict[int | str, float]) – The values of the variables to be evaluated.
Devuelve:: The value of the gradient of the quadratic objective given the variable values.
Muestra:: QiskitOptimizationError – if the shape of the objective function does not match with the number of variables.
Tipo del valor devuelto:: ndarray