Trait ndarray::linalg::Dot [−][src]
Matrix Multiplication
For two-dimensional arrays, the dot method computes the matrix multiplication.
Associated Types
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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,
[src]
S: Data<Elem = A>,
S2: Data<Elem = A>,
A: LinalgScalar,
type Output = A
fn dot(&self, rhs: &ArrayBase<S2, Ix1>) -> A
[src]
Compute the dot product of one-dimensional arrays.
The dot product is a sum of the elementwise products (no conjugation of complex operands, and thus not their inner product).
Panics if the arrays are not of the same length.
Note: If enabled, uses blas dot
for elements of f32, f64
when memory
layout allows.
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,
[src]
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.
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,
[src]
S: Data<Elem = A>,
S2: Data<Elem = A>,
A: LinalgScalar,
type Output = Array<A, Ix1>
fn dot(&self, rhs: &ArrayBase<S2, Ix2>) -> Array<A, Ix1>
[src]
Perform the matrix multiplication of the row vector self
and
rectangular matrix rhs
.
The array shapes must agree in the way that
if self
is M, then rhs
is M × N.
Return a result array with shape N.
Panics if shapes are incompatible.
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,
[src]
S: Data<Elem = A>,
S2: Data<Elem = A>,
A: LinalgScalar,