Lagrangian |
The LagrangianFunction type exposes the following members.
Name | Description | |
---|---|---|
LagrangianFunction | Constructs a LagrangianFunction for the given objective function and constraints. |
Name | Description | |
---|---|---|
CentralDifferenceDelta |
Gets and sets the delta used in the centeral difference method
for approximating the gradient with respect to the parameters.
(Inherited from DoubleParameterizedFunctional) | |
XDimension |
Gets and sets the dimension of the domain of the functional.
(Inherited from DoubleParameterizedFunctional) |
Name | Description | |
---|---|---|
Clone |
Returns a deep copy of the base. Deriving classes must override this method.
(Inherited from DoubleParameterizedFunctional) | |
Evaluate(DoubleVector, DoubleVector) |
Evaluates the parameterized function for the given parameter values at the
given point.
(Overrides DoubleParameterizedFunctionalEvaluate(DoubleVector, DoubleVector)) | |
Evaluate(DoubleVector, DoubleMatrix, DoubleVector) |
Evaluates the parameterized function for the given parameter values at the
given set of points.
(Inherited from DoubleParameterizedFunctional) | |
GradientWithRespectToParams |
Method for calculating the gradient with respect to the parameters while keeping x
fixed at the specified value.
(Inherited from DoubleParameterizedFunctional) | |
GradientWithRespectToX(DoubleVector, DoubleVector) | Evaluates the gradient with respect to x at the given point. | |
GradientWithRespectToX(DoubleVector, DoubleVector, DoubleVector) | Evaluates the gradient with respect to x at the given point. | |
HessianWithRespectToX | Calcuates the Hessian matrix with respect to x. |