Trait Gradients 

pub trait Gradients: Dim
where
    DefaultAllocator: Allocator<Self>,
{
    type Dual<T: DualNum<F> + Copy, F: DualNumFloat>: DualNum<F, Inner = T> + Copy;
    type Dual2<T: DualNum<F> + Copy, F: DualNumFloat>: DualNum<F, Inner = T> + Copy;
    type HyperDual<T: DualNum<F> + Copy, F: DualNumFloat>: DualNum<F, Inner = T> + Copy;

    // Required methods
    fn gradient<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual<T, F>, F>>(
        g: G,
        x: &OVector<T, Self>,
        args: &A::Inner,
    ) -> (T, OVector<T, Self>)
       where G: Fn(OVector<Self::Dual<T, F>, Self>, &A) -> Self::Dual<T, F>;
    fn hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual2<T, F>, F>>(
        g: G,
        x: &OVector<T, Self>,
        args: &A::Inner,
    ) -> (T, OVector<T, Self>, OMatrix<T, Self, Self>)
       where G: Fn(OVector<Self::Dual2<T, F>, Self>, &A) -> Self::Dual2<T, F>,
             DefaultAllocator: Allocator<Self, Self>;
    fn partial_hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::HyperDual<T, F>, F>>(
        g: G,
        x: &OVector<T, Self>,
        y: T,
        args: &A::Inner,
    ) -> (T, OVector<T, Self>, T, OVector<T, Self>)
       where G: Fn(OVector<Self::HyperDual<T, F>, Self>, Self::HyperDual<T, F>, &A) -> Self::HyperDual<T, F>;
    fn jacobian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual<T, F>, F>>(
        g: G,
        x: &OVector<T, Self>,
        args: &A::Inner,
    ) -> (OVector<T, Self>, OMatrix<T, Self, Self>)
       where G: Fn(OVector<Self::Dual<T, F>, Self>, &A) -> OVector<Self::Dual<T, F>, Self>,
             DefaultAllocator: Allocator<Self, Self>;
}

Evaluation of gradients, hessians, and partial (Nx1) hessians that is generic over the dimensionality of the input vector.

Required Associated Types

type Dual<T: DualNum<F> + Copy, F: DualNumFloat>: DualNum<F, Inner = T> + Copy

type Dual2<T: DualNum<F> + Copy, F: DualNumFloat>: DualNum<F, Inner = T> + Copy

type HyperDual<T: DualNum<F> + Copy, F: DualNumFloat>: DualNum<F, Inner = T> + Copy

Required Methods

fn gradient<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual<T, F>, F>>( g: G, x: &OVector<T, Self>, args: &A::Inner, ) -> (T, OVector<T, Self>)

where G: Fn(OVector<Self::Dual<T, F>, Self>, &A) -> Self::Dual<T, F>,

fn hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual2<T, F>, F>>( g: G, x: &OVector<T, Self>, args: &A::Inner, ) -> (T, OVector<T, Self>, OMatrix<T, Self, Self>)

where G: Fn(OVector<Self::Dual2<T, F>, Self>, &A) -> Self::Dual2<T, F>, DefaultAllocator: Allocator<Self, Self>,

fn partial_hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::HyperDual<T, F>, F>>( g: G, x: &OVector<T, Self>, y: T, args: &A::Inner, ) -> (T, OVector<T, Self>, T, OVector<T, Self>)

where G: Fn(OVector<Self::HyperDual<T, F>, Self>, Self::HyperDual<T, F>, &A) -> Self::HyperDual<T, F>,

fn jacobian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual<T, F>, F>>( g: G, x: &OVector<T, Self>, args: &A::Inner, ) -> (OVector<T, Self>, OMatrix<T, Self, Self>)

where G: Fn(OVector<Self::Dual<T, F>, Self>, &A) -> OVector<Self::Dual<T, F>, Self>, DefaultAllocator: Allocator<Self, Self>,

Dyn Compatibility

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.

Implementations on Foreign Types

impl Gradients for Dyn

type Dual<T: DualNum<F> + Copy, F: DualNumFloat> = Dual<T, F>

type Dual2<T: DualNum<F> + Copy, F: DualNumFloat> = HyperDual<T, F>

type HyperDual<T: DualNum<F> + Copy, F: DualNumFloat> = HyperDual<T, F>

fn gradient<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Dual<T, F>, F>>( g: G, x: &DVector<T>, args: &A::Inner, ) -> (T, DVector<T>)

where G: Fn(OVector<Dual<T, F>, Dyn>, &A) -> Dual<T, F>,

fn hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<HyperDual<T, F>, F>>( g: G, x: &DVector<T>, args: &A::Inner, ) -> (T, DVector<T>, DMatrix<T>)

where G: Fn(DVector<HyperDual<T, F>>, &A) -> HyperDual<T, F>,

fn partial_hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<HyperDual<T, F>, F>>( g: G, x: &DVector<T>, y: T, args: &A::Inner, ) -> (T, DVector<T>, T, DVector<T>)

where G: Fn(DVector<HyperDual<T, F>>, HyperDual<T, F>, &A) -> HyperDual<T, F>,

fn jacobian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual<T, F>, F>>( g: G, x: &OVector<T, Self>, args: &A::Inner, ) -> (OVector<T, Self>, OMatrix<T, Self, Self>)

where G: Fn(OVector<Dual<T, F>, Self>, &A) -> OVector<Dual<T, F>, Self>, DefaultAllocator: Allocator<Self, Self>,

impl<const N: usize> Gradients for Const<N>

type Dual<T: DualNum<F> + Copy, F: DualNumFloat> = DualVec<T, F, Const<N>>

type Dual2<T: DualNum<F> + Copy, F: DualNumFloat> = Dual2Vec<T, F, Const<N>>

type HyperDual<T: DualNum<F> + Copy, F: DualNumFloat> = HyperDualVec<T, F, Const<N>, Const<1>>

fn gradient<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<DualSVec<T, F, N>, F>>( g: G, x: &SVector<T, N>, args: &A::Inner, ) -> (T, SVector<T, N>)

where G: Fn(SVector<DualSVec<T, F, N>, N>, &A) -> DualSVec<T, F, N>,

fn hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual2<T, F>, F>>( g: G, x: &OVector<T, Self>, args: &A::Inner, ) -> (T, OVector<T, Self>, OMatrix<T, Self, Self>)

where G: Fn(OVector<Self::Dual2<T, F>, Self>, &A) -> Self::Dual2<T, F>,

fn partial_hessian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::HyperDual<T, F>, F>>( g: G, x: &OVector<T, Self>, y: T, args: &A::Inner, ) -> (T, OVector<T, Self>, T, OVector<T, Self>)

where G: Fn(OVector<Self::HyperDual<T, F>, Self>, Self::HyperDual<T, F>, &A) -> Self::HyperDual<T, F>,

fn jacobian<G, T: DualNum<F> + Copy, F: DualNumFloat, A: DualStruct<Self::Dual<T, F>, F>>( g: G, x: &OVector<T, Self>, args: &A::Inner, ) -> (OVector<T, Self>, OMatrix<T, Self, Self>)

where G: Fn(OVector<DualVec<T, F, Self>, Self>, &A) -> OVector<DualVec<T, F, Self>, Self>,

Implementors