Uses of Class
de.labathome.trustconstr.ScalarFunction.ScalarFunctionFactory

Packages that use ScalarFunction.ScalarFunctionFactory

Package	Description
de.labathome.trustconstr

Uses of ScalarFunction.ScalarFunctionFactory in de.labathome.trustconstr

Fields in de.labathome.trustconstr declared as ScalarFunction.ScalarFunctionFactory

Modifier and Type	Field	Description
static final ScalarFunction.ScalarFunctionFactory	ScalarFunction.FACTORY	Default ScalarFunction.ScalarFunctionFactory; create one and call build().

Methods in de.labathome.trustconstr that return ScalarFunction.ScalarFunctionFactory

Modifier and Type	Method	Description
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.args(Object args)	Provide any additional fixed parameters needed to specify the scalar function (the args argument forwarded to fun/grad/hess).
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.epsilon(Matrix epsilon)	Absolute step size for FD gradient/Hessian, taking precedence over the relative step.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.finiteDiffBounds(FiniteDifferenceBounds finiteDiffBounds)	Bounds within which FD perturbations must stay.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.finiteDiffRelStep(Matrix finiteDiffRelStep)	Per-component relative step size for the FD gradient/Hessian.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.fun(ToDoubleBiFunction<Matrix,Object> fun)	Set the objective function to optimize.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.grad(FiniteDifferenceMethod grad)	Compute the gradient by finite differences instead of analytically.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.grad(BiFunction<Matrix,Object,Matrix> grad)	Provide an analytic gradient grad(x, args) -> gradf(x).
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.hess(FiniteDifferenceMethod hess)	Compute the Hessian by finite differences instead of analytically.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.hess(HessianUpdateStrategy hess)	Approximate the Hessian via a quasi-Newton update strategy (e.g.
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.hess(BiFunction<Matrix,Object,Matrix> hess)	Provide an analytic Hessian hess(x, args) -> grad^2f(x).
ScalarFunction.ScalarFunctionFactory	ScalarFunction.ScalarFunctionFactory.x0(Matrix x0)	Provide the initial point for evaluating fun.