QuadraticObjective¶

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

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

Constructs a quadratic objective function.

Parameters:

quadratic_program (Any) – The parent quadratic program.
constant (float) – The constant offset of the objective.
linear (ndarray | spmatrix | list[float] | dict[str | int, 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)[source]¶

Evaluate the quadratic objective for given variable values.

Parameters:: x (ndarray | list | dict[int | str, float]) – The values of the variables to be evaluated.
Returns:: The value of the quadratic objective given the variable values.
Raises:: QiskitOptimizationError – if the shape of the objective function does not match with the number of variables.
Return type:: float

evaluate_gradient(x)[source]¶

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

Parameters:: x (ndarray | list | dict[int | str, float]) – The values of the variables to be evaluated.
Returns:: The value of the gradient of the quadratic objective given the variable values.
Raises:: QiskitOptimizationError – if the shape of the objective function does not match with the number of variables.
Return type:: ndarray