Type Alias VectorSum

pub type VectorSum<T, R1, R2> = Matrix<T, <ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, Const<1>, <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<Const<1>, Const<1>>>::Representative>>::Buffer<T>>;

The type of the result of a matrix sum.

Aliased Type

struct VectorSum<T, R1, R2> {
    pub data: <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<Const<1>, Const<1>>>::Representative>>::Buffer<T>,
    /* private fields */
}

Fields

data: <DefaultAllocator as Allocator<<ShapeConstraint as SameNumberOfRows<R1, R2>>::Representative, <ShapeConstraint as SameNumberOfColumns<Const<1>, Const<1>>>::Representative>>::Buffer<T>

The data storage that contains all the matrix components. Disappointed?

Well, if you came here to see how you can access the matrix components, you may be in luck: you can access the individual components of all vectors with compile-time dimensions <= 6 using field notation like this: vec.x, vec.y, vec.z, vec.w, vec.a, vec.b. Reference and assignation work too:

let mut vec = Vector3::new(1.0, 2.0, 3.0);
vec.x = 10.0;
vec.y += 30.0;
assert_eq!(vec.x, 10.0);
assert_eq!(vec.y + 100.0, 132.0);

Similarly, for matrices with compile-time dimensions <= 6, you can use field notation like this: mat.m11, mat.m42, etc. The first digit identifies the row to address and the second digit identifies the column to address. So mat.m13 identifies the component at the first row and third column (note that the count of rows and columns start at 1 instead of 0 here. This is so we match the mathematical notation).

For all matrices and vectors, independently from their size, individual components can be accessed and modified using indexing: vec[20], mat[(20, 19)]. Here the indexing starts at 0 as you would expect.