Type Alias nalgebra::base::Matrix1

pub type Matrix1<T> = Matrix<T, U1, U1, ArrayStorage<T, 1, 1>>;

A stack-allocated, column-major, 1x1 square matrix.

Because this is an alias, not all its methods are listed here. See the Matrix type too.

Aliased Type

struct Matrix1<T> {
    pub data: ArrayStorage<T, 1, 1>,
    /* private fields */
}

Fields

data: ArrayStorage<T, 1, 1>

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.

Implementations

impl<T> Matrix1<T>

pub fn into_scalar(self) -> T

Convert this 1x1 matrix into a scalar.

As opposed to indexing, using this provides type-safety when flattening dimensions.

Example

let v = Vector3::new(0., 0., 1.);
let inner_product: f32 = (v.transpose() * v).into_scalar();
assert_eq!(inner_product, 1.);

 let v = Vector3::new(0., 0., 1.);
 let mut inner_product: f32 = (v * v.transpose()).into_scalar();