Trait ndarray::linalg::Dot

pub trait Dot<Rhs> {
    type Output;

    // Required method
    fn dot(&self, rhs: &Rhs) -> Self::Output;
}

Matrix Multiplication

For two-dimensional arrays, the dot method computes the matrix multiplication.

Required Associated Types

type Output

The result of the operation.

For two-dimensional arrays: a rectangular array.

Required Methods

fn dot(&self, rhs: &Rhs) -> Self::Output

Implementors

impl<A, S, S2> Dot<ArrayBase<S2, Dim<[usize; 1]>>> for ArrayBase<S, Ix1>where S: Data<Elem = A>, S2: Data<Elem = A>, A: LinalgScalar,

type Output = A

impl<A, S, S2> Dot<ArrayBase<S2, Dim<[usize; 1]>>> for ArrayBase<S, Ix2>where S: Data<Elem = A>, S2: Data<Elem = A>, A: LinalgScalar,

Perform the matrix multiplication of the rectangular array self and column vector rhs.

The array shapes must agree in the way that if self is M × N, then rhs is N.

Return a result array with shape M.

Panics if shapes are incompatible.

type Output = ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>

impl<A, S, S2> Dot<ArrayBase<S2, Dim<[usize; 2]>>> for ArrayBase<S, Ix1>where S: Data<Elem = A>, S2: Data<Elem = A>, A: LinalgScalar,

type Output = ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>

impl<A, S, S2> Dot<ArrayBase<S2, Dim<[usize; 2]>>> for ArrayBase<S, Ix2>where S: Data<Elem = A>, S2: Data<Elem = A>, A: LinalgScalar,

type Output = ArrayBase<OwnedRepr<A>, Dim<[usize; 2]>>