Struct vek::mat::repr_simd::column_major::mat3::Mat3

#[repr(C)]
pub struct Mat3<T> {
    pub cols: CVec3<Vec3<T>>,
}

3x3 matrix.

Fields

cols: CVec3<Vec3<T>>

Methods

impl<T> Mat3<T>

pub fn identity() -> Self where
    T: Zero + One, 

The identity matrix, which is also the default value for square matrices.

assert_eq!(Mat4::<f32>::default(), Mat4::<f32>::identity());

pub fn zero() -> Self where
    T: Zero, 

The matrix with all elements set to zero.

pub fn apply<F>(&mut self, f: F) where
    T: Copy,
    F: FnMut(T) -> T, 

Applies the function f to each element of this matrix, in-place.

For an example, see the map() method.

pub fn apply2<F, S>(&mut self, other: Mat3<S>, f: F) where
    T: Copy,
    F: FnMut(T, S) -> T, 

Applies the function f to each element of this matrix, in-place.

For an example, see the map2() method.

pub fn numcast<D>(self) -> Option<Mat3<D>> where
    T: NumCast,
    D: NumCast, 

Returns a memberwise-converted copy of this matrix, using NumCast.

let m = Mat4::<f32>::identity();
let m: Mat4<i32> = m.numcast().unwrap();
assert_eq!(m, Mat4::identity());

pub fn broadcast_diagonal(val: T) -> Self where
    T: Zero + Copy, 

Initializes a new matrix with elements of the diagonal set to val and the other to zero.

In a way, this is the same as single-argument matrix constructors in GLSL and GLM.

assert_eq!(Mat4::broadcast_diagonal(0), Mat4::zero());
assert_eq!(Mat4::broadcast_diagonal(1), Mat4::identity());
assert_eq!(Mat4::broadcast_diagonal(2), Mat4::new(
    2,0,0,0,
    0,2,0,0,
    0,0,2,0,
    0,0,0,2,
));

pub fn with_diagonal(d: Vec3<T>) -> Self where
    T: Zero + Copy, 

Initializes a matrix by its diagonal, setting other elements to zero.

pub fn diagonal(self) -> Vec3<T>

Gets the matrix's diagonal into a vector.

assert_eq!(Mat4::<u32>::zero().diagonal(), Vec4::zero());
assert_eq!(Mat4::<u32>::identity().diagonal(), Vec4::one());

let mut m = Mat4::zero();
m[(0, 0)] = 1;
m[(1, 1)] = 2;
m[(2, 2)] = 3;
m[(3, 3)] = 4;
assert_eq!(m.diagonal(), Vec4::new(1, 2, 3, 4));
assert_eq!(m.diagonal(), Vec4::iota() + 1);

pub fn trace(self) -> T where
    T: Sum, 

The sum of the diagonal's elements.

assert_eq!(Mat4::<u32>::zero().trace(), 0);
assert_eq!(Mat4::<u32>::identity().trace(), 4);

pub fn mul_memberwise(self, m: Self) -> Self where
    T: Mul<Output = T>, 

Multiply elements of this matrix with another's.

let m = Mat4::new(
    0, 1, 2, 3,
    1, 2, 3, 4,
    2, 3, 4, 5,
    3, 4, 5, 6,
);
let r = Mat4::new(
    0, 1, 4, 9,
    1, 4, 9, 16,
    4, 9, 16, 25,
    9, 16, 25, 36,
);
assert_eq!(m.mul_memberwise(m), r);

pub fn row_count(&self) -> usize

Convenience for getting the number of rows of this matrix.

pub fn col_count(&self) -> usize

Convenience for getting the number of columns of this matrix.

pub const ROW_COUNT: usize

Convenience constant representing the number of rows for matrices of this type.

pub const COL_COUNT: usize

Convenience constant representing the number of columns for matrices of this type.

pub fn is_packed(&self) -> bool

Are all elements of this matrix tightly packed together in memory ?

This might not be the case for matrices in the repr_simd module (it depends on the target architecture).

impl<T> Mat3<T>

pub fn map_cols<D, F>(self, f: F) -> Mat3<D> where
    F: FnMut(Vec3<T>) -> Vec3<D>, 

Returns a column-wise-converted copy of this matrix, using the given conversion closure.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<f32>::new(
    0.25, 1.25, 5.56, 8.66,
    8.53, 2.92, 3.86, 9.36,
    1.02, 0.28, 5.52, 6.06,
    6.20, 7.01, 4.90, 5.26
);
let m = m.map_cols(|col| col.map(|x| x.round() as i32));
assert_eq!(m, Mat4::new(
    0, 1, 6, 9,
    9, 3, 4, 9,
    1, 0, 6, 6,
    6, 7, 5, 5
));

pub fn into_col_array(self) -> [T; 9]

Converts this matrix into a fixed-size array of elements.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
    0, 4, 8, 12,
    1, 5, 9, 13,
    2, 6, 10, 14,
    3, 7, 11, 15
];
assert_eq!(m.into_col_array(), array);

pub fn into_col_arrays(self) -> [[T; 3]; 3]

Converts this matrix into a fixed-size array of fixed-size arrays of elements.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
    [ 0, 4,  8, 12, ],
    [ 1, 5,  9, 13, ],
    [ 2, 6, 10, 14, ],
    [ 3, 7, 11, 15, ],
];
assert_eq!(m.into_col_arrays(), array);

pub fn from_col_array(array: [T; 9]) -> Self

Converts a fixed-size array of elements into a matrix.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
    0, 4, 8, 12,
    1, 5, 9, 13,
    2, 6, 10, 14,
    3, 7, 11, 15
];
assert_eq!(m, Mat4::from_col_array(array));

pub fn from_col_arrays(array: [[T; 3]; 3]) -> Self

Converts a fixed-size array of fixed-size arrays of elements into a matrix.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
    [ 0, 4,  8, 12, ],
    [ 1, 5,  9, 13, ],
    [ 2, 6, 10, 14, ],
    [ 3, 7, 11, 15, ],
];
assert_eq!(m, Mat4::from_col_arrays(array));

pub fn into_row_array(self) -> [T; 9]

Converts this matrix into a fixed-size array of elements.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
];
assert_eq!(m.into_row_array(), array);

pub fn into_row_arrays(self) -> [[T; 3]; 3]

Converts this matrix into a fixed-size array of fixed-size arrays of elements.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
    [  0,  1,  2,  3, ],
    [  4,  5,  6,  7, ],
    [  8,  9, 10, 11, ],
    [ 12, 13, 14, 15, ],
];
assert_eq!(m.into_row_arrays(), array);

pub fn from_row_array(array: [T; 9]) -> Self

Converts a fixed-size array of elements into a matrix.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
];
assert_eq!(m, Mat4::from_row_array(array));

pub fn from_row_arrays(array: [[T; 3]; 3]) -> Self

Converts a fixed-size array of fixed-size array of elements into a matrix.

use vek::mat::repr_c::column_major::Mat4;

let m = Mat4::<u32>::new(
     0,  1,  2,  3,
     4,  5,  6,  7,
     8,  9, 10, 11,
    12, 13, 14, 15
);
let array = [
    [  0,  1,  2,  3, ],
    [  4,  5,  6,  7, ],
    [  8,  9, 10, 11, ],
    [ 12, 13, 14, 15, ],
];
assert_eq!(m, Mat4::from_row_arrays(array));

pub fn as_col_ptr(&self) -> *const T

Gets a const pointer to this matrix's elements.

Panics

Panics if the matrix's elements are not tightly packed in memory, which may be the case for matrices in the repr_simd module.
You may check this with the is_packed() method.

pub fn as_mut_col_ptr(&mut self) -> *mut T

Gets a mut pointer to this matrix's elements.

Panics

Panics if the matrix's elements are not tightly packed in memory, which may be the case for matrices in the repr_simd module.
You may check this with the is_packed() method.

pub fn as_col_slice(&self) -> &[T]

View this matrix as an immutable slice.

Panics

Panics if the matrix's elements are not tightly packed in memory, which may be the case for matrices in the repr_simd module.
You may check this with the is_packed() method.

pub fn as_mut_col_slice(&mut self) -> &mut [T]

View this matrix as a mutable slice.

Panics

Panics if the matrix's elements are not tightly packed in memory, which may be the case for matrices in the repr_simd module.
You may check this with the is_packed() method.

impl<T> Mat3<T>

pub fn gl_should_transpose(&self) -> bool

Gets the transpose parameter to pass to OpenGL glUniformMatrix*() functions.

The return value is a plain bool which you may directly cast to a GLboolean.

This takes &self to prevent surprises when changing the type of matrix you plan to send.

pub const GL_SHOULD_TRANSPOSE: bool

The transpose parameter to pass to OpenGL glUniformMatrix*() functions.

impl<T> Mat3<T>

pub fn map<D, F>(self, f: F) -> Mat3<D> where
    F: FnMut(T) -> D, 

Returns an element-wise-converted copy of this matrix, using the given conversion closure.

use vek::mat::repr_c::row_major::Mat4;

let m = Mat4::<f32>::new(
    0.25, 1.25, 5.56, 8.66,
    8.53, 2.92, 3.86, 9.36,
    1.02, 0.28, 5.52, 6.06,
    6.20, 7.01, 4.90, 5.26
);
let m = m.map(|x| x.round() as i32);
assert_eq!(m, Mat4::new(
    0, 1, 6, 9,
    9, 3, 4, 9,
    1, 0, 6, 6,
    6, 7, 5, 5
));

pub fn map2<D, F, S>(self, other: Mat3<S>, f: F) -> Mat3<D> where
    F: FnMut(T, S) -> D, 

Applies the function f to each element of two matrices, pairwise, and returns the result.

use vek::mat::repr_c::row_major::Mat4;

let a = Mat4::<f32>::new(
    0.25, 1.25, 2.52, 2.99,
    0.25, 1.25, 2.52, 2.99,
    0.25, 1.25, 2.52, 2.99,
    0.25, 1.25, 2.52, 2.99
);
let b = Mat4::<i32>::new(
    0, 1, 0, 0,
    1, 0, 0, 0,
    0, 0, 1, 0,
    0, 0, 0, 1
);
let m = a.map2(b, |a, b| a.round() as i32 + b);
assert_eq!(m, Mat4::new(
    0, 2, 3, 3,
    1, 1, 3, 3,
    0, 1, 4, 3,
    0, 1, 3, 4
));

pub fn transposed(self) -> Self

The matrix's transpose.

For orthogonal matrices, the transpose is the same as the inverse. All pure rotation matrices are orthogonal, and therefore can be inverted faster by simply computing their transpose.

use std::f32::consts::PI;

let m = Mat3::new(
    0, 1, 2,
    4, 5, 6,
    8, 9, 0
);
let t = Mat3::new(
    0, 4, 8,
    1, 5, 9,
    2, 6, 0 
);
assert_eq!(m.transposed(), t);
assert_eq!(m, m.transposed().transposed());

let m = Mat3::rotation_x(PI/7.);
assert_relative_eq!(m * m.transposed(), Mat3::identity());
assert_relative_eq!(m.transposed() * m, Mat3::identity());

pub fn transpose(&mut self)

Transpose this matrix.

let mut m = Mat3::new(
    0, 1, 2,
    4, 5, 6,
    8, 9, 0
);
let t = Mat3::new(
    0, 4, 8,
    1, 5, 9,
    2, 6, 0
);
m.transpose();
assert_eq!(m, t);

pub fn determinant(self) -> T where
    T: Copy + Mul<T, Output = T> + Sub<T, Output = T> + Add<T, Output = T>, 

Get this matrix's determinant.

A matrix is invertible if its determinant is non-zero.

pub fn mul_point_2d<V: Into<Vec2<T>> + From<Vec3<T>>>(self, rhs: V) -> V where
    T: Real + MulAdd<T, T, Output = T>, 

Shortcut for self * Vec3::from_point_2d(rhs).

pub fn mul_direction_2d<V: Into<Vec2<T>> + From<Vec3<T>>>(self, rhs: V) -> V where
    T: Real + MulAdd<T, T, Output = T>, 

Shortcut for self * Vec3::from_direction_2d(rhs).

pub fn translate_2d<V: Into<Vec2<T>>>(&mut self, v: V) where
    T: Real + MulAdd<T, T, Output = T>, 

Translates this matrix in 2D.

pub fn translated_2d<V: Into<Vec2<T>>>(self, v: V) -> Self where
    T: Real + MulAdd<T, T, Output = T>, 

Returns this matrix translated in 2D.

pub fn translation_2d<V: Into<Vec2<T>>>(v: V) -> Self where
    T: Zero + One, 

Creates a 2D translation matrix.

pub fn scale_3d<V: Into<Vec3<T>>>(&mut self, v: V) where
    T: Real + MulAdd<T, T, Output = T>, 

Scales this matrix in 3D.

pub fn scaled_3d<V: Into<Vec3<T>>>(self, v: V) -> Self where
    T: Real + MulAdd<T, T, Output = T>, 

Returns this matrix scaled in 3D.

pub fn scaling_3d<V: Into<Vec3<T>>>(v: V) -> Self where
    T: Zero, 

Creates a 3D scaling matrix.

pub fn rotate_x(&mut self, angle_radians: T) where
    T: Real + MulAdd<T, T, Output = T>, 

Rotates this matrix around the X axis.

pub fn rotated_x(self, angle_radians: T) -> Self where
    T: Real + MulAdd<T, T, Output = T>, 

Returns this matrix rotated around the X axis.

pub fn rotation_x(angle_radians: T) -> Self where
    T: Real, 

Creates a matrix that rotates around the X axis.

pub fn rotate_y(&mut self, angle_radians: T) where
    T: Real + MulAdd<T, T, Output = T>, 

Rotates this matrix around the Y axis.

pub fn rotated_y(self, angle_radians: T) -> Self where
    T: Real + MulAdd<T, T, Output = T>, 

Returns this matrix rotated around the Y axis.

pub fn rotation_y(angle_radians: T) -> Self where
    T: Real, 

Creates a matrix that rotates around the Y axis.

pub fn rotate_z(&mut self, angle_radians: T) where
    T: Real + MulAdd<T, T, Output = T>, 

Rotates this matrix around the Z axis.

pub fn rotated_z(self, angle_radians: T) -> Self where
    T: Real + MulAdd<T, T, Output = T>, 

Returns this matrix rotated around the Z axis.

pub fn rotation_z(angle_radians: T) -> Self where
    T: Real, 

Creates a matrix that rotates around the Z axis.

pub fn rotate_3d<V: Into<Vec3<T>>>(&mut self, angle_radians: T, axis: V) where
    T: Real + MulAdd<T, T, Output = T> + Sum, 

Rotates this matrix around a 3D axis.
The axis is not required to be normalized.

pub fn rotated_3d<V: Into<Vec3<T>>>(self, angle_radians: T, axis: V) -> Self where
    T: Real + MulAdd<T, T, Output = T> + Sum, 

Returns this matrix rotated around a 3D axis.
The axis is not required to be normalized.

pub fn rotation_3d<V: Into<Vec3<T>>>(angle_radians: T, axis: V) -> Self where
    T: Real + Sum, 

Creates a matrix that rotates around a 3D axis.
The axis is not required to be normalized.

use std::f32::consts::PI;

let angles = 32;
for i in 0..angles {
    let theta = PI * 2. * (i as f32) / (angles as f32);

    assert_relative_eq!(Mat3::rotation_x(theta), Mat3::from(Quaternion::rotation_x(theta)), epsilon = 0.000001);
    assert_relative_eq!(Mat3::rotation_y(theta), Mat3::from(Quaternion::rotation_y(theta)), epsilon = 0.000001);
    assert_relative_eq!(Mat3::rotation_z(theta), Mat3::from(Quaternion::rotation_z(theta)), epsilon = 0.000001);

    assert_relative_eq!(Mat3::rotation_x(theta), Mat3::rotation_3d(theta, Vec3::unit_x()));
    assert_relative_eq!(Mat3::rotation_y(theta), Mat3::rotation_3d(theta, Vec3::unit_y()));
    assert_relative_eq!(Mat3::rotation_z(theta), Mat3::rotation_3d(theta, Vec3::unit_z()));

    assert_relative_eq!(Mat3::rotation_x(theta), Mat3::from(Mat4::rotation_3d(theta, Vec3::unit_x())));
    assert_relative_eq!(Mat3::rotation_y(theta), Mat3::from(Mat4::rotation_3d(theta, Vec3::unit_y())));
    assert_relative_eq!(Mat3::rotation_z(theta), Mat3::from(Mat4::rotation_3d(theta, Vec3::unit_z())));

    assert_relative_eq!(Mat4::rotation_x(theta), Mat4::from(Mat3::rotation_3d(theta, Vec3::unit_x())));
    assert_relative_eq!(Mat4::rotation_y(theta), Mat4::from(Mat3::rotation_3d(theta, Vec3::unit_y())));
    assert_relative_eq!(Mat4::rotation_z(theta), Mat4::from(Mat3::rotation_3d(theta, Vec3::unit_z())));

    // See what rotating unit vectors do for most angles between 0 and 2*PI.
    // It's helpful to picture this as a right-handed coordinate system.

    let v = Vec3::unit_y();
    let m = Mat3::rotation_x(theta);
    assert_relative_eq!(m * v, Vec3::new(0., theta.cos(), theta.sin()));

    let v = Vec3::unit_z();
    let m = Mat3::rotation_y(theta);
    assert_relative_eq!(m * v, Vec3::new(theta.sin(), 0., theta.cos()));

    let v = Vec3::unit_x();
    let m = Mat3::rotation_z(theta);
    assert_relative_eq!(m * v, Vec3::new(theta.cos(), theta.sin(), 0.));
}

pub fn rotation_from_to_3d<V: Into<Vec3<T>>>(from: V, to: V) -> Self where
    T: Real + Sum, 

Creates a matrix that would rotate a from direction to to.

let (from, to) = (Vec3::<f32>::unit_x(), Vec3::<f32>::unit_z());
let m = Mat3::<f32>::rotation_from_to_3d(from, to);
assert_relative_eq!(m * from, to);

let (from, to) = (Vec3::<f32>::unit_x(), -Vec3::<f32>::unit_x());
let m = Mat3::<f32>::rotation_from_to_3d(from, to);
assert_relative_eq!(m * from, to);

impl<T> Mat3<T>

pub fn new(
    m00: T,
    m01: T,
    m02: T,
    m10: T,
    m11: T,
    m12: T,
    m20: T,
    m21: T,
    m22: T
) -> Self

Creates a new 3x3 matrix from elements in a layout-agnostic way.

The parameters are named mij where i is the row index and j the column index. Their order is always the same regardless of the matrix's layout.

Trait Implementations

impl<T: Display> Display for Mat3<T>

Displays this matrix using the following format:

(i being the number of rows and j the number of columns)

( m00 ... m0j
  ... ... ...
  mi0 ... mij )

Note that elements are not comma-separated.
This format doesn't depend on the matrix's storage layout.

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<T: Debug> Debug for Mat3<T>

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<T> Div<Mat3<T>> for Mat3<T> where
    T: Div<Output = T>, 

type Output = Self

The resulting type after applying the / operator.

fn div(self, rhs: Self) -> Self::Output

Performs the / operation.

impl<T> Div<T> for Mat3<T> where
    T: Copy + Div<Output = T>, 

type Output = Self

The resulting type after applying the / operator.

fn div(self, rhs: T) -> Self::Output

Performs the / operation.

impl<T> Rem<Mat3<T>> for Mat3<T> where
    T: Rem<Output = T>, 

type Output = Self

The resulting type after applying the % operator.

fn rem(self, rhs: Self) -> Self::Output

Performs the % operation.

impl<T> Rem<T> for Mat3<T> where
    T: Copy + Rem<Output = T>, 

type Output = Self

The resulting type after applying the % operator.

fn rem(self, rhs: T) -> Self::Output

Performs the % operation.

impl<T: PartialEq> PartialEq<Mat3<T>> for Mat3<T>

fn eq(&self, other: &Mat3<T>) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Mat3<T>) -> bool

This method tests for !=.

impl<T: Eq> Eq for Mat3<T>

impl<T> Add<Mat3<T>> for Mat3<T> where
    T: Add<Output = T>, 

type Output = Self

The resulting type after applying the + operator.

fn add(self, rhs: Self) -> Self::Output

Performs the + operation.

impl<T> Add<T> for Mat3<T> where
    T: Copy + Add<Output = T>, 

type Output = Self

The resulting type after applying the + operator.

fn add(self, rhs: T) -> Self::Output

Performs the + operation.

impl<T> Sub<Mat3<T>> for Mat3<T> where
    T: Sub<Output = T>, 

type Output = Self

The resulting type after applying the - operator.

fn sub(self, rhs: Self) -> Self::Output

Performs the - operation.

impl<T> Sub<T> for Mat3<T> where
    T: Copy + Sub<Output = T>, 

type Output = Self

The resulting type after applying the - operator.

fn sub(self, rhs: T) -> Self::Output

Performs the - operation.

impl<T> Mul<T> for Mat3<T> where
    T: Copy + Zero + Add<Output = T> + Mul<Output = T>, 

type Output = Self

The resulting type after applying the * operator.

fn mul(self, rhs: T) -> Self::Output

Performs the * operation.

impl<T: MulAdd<T, T, Output = T> + Mul<Output = T> + Copy> Mul<Mat3<T>> for Vec3<T>

Multiplies a row vector with a column-major matrix, giving a row vector.

use vek::mat::column_major::Mat4;
use vek::vec::Vec4;

let m = Mat4::new(
    0, 1, 2, 3,
    4, 5, 6, 7,
    8, 9, 0, 1,
    2, 3, 4, 5
);
let v = Vec4::new(0, 1, 2, 3);
let r = Vec4::new(26, 32, 18, 24);
assert_eq!(v * m, r);

type Output = Self

The resulting type after applying the * operator.

fn mul(self, rhs: Mat3<T>) -> Self::Output

Performs the * operation.

impl<T: MulAdd<T, T, Output = T> + Mul<Output = T> + Copy> Mul<Vec3<T>> for Mat3<T>

Multiplies a column-major matrix with a column vector, giving a column vector.

With SIMD vectors, this is the most efficient way.

use vek::mat::column_major::Mat4;
use vek::vec::Vec4;

let m = Mat4::new(
    0, 1, 2, 3,
    4, 5, 6, 7,
    8, 9, 0, 1,
    2, 3, 4, 5
);
let v = Vec4::new(0, 1, 2, 3);
let r = Vec4::new(14, 38, 12, 26);
assert_eq!(m * v, r);

type Output = Vec3<T>

The resulting type after applying the * operator.

fn mul(self, v: Vec3<T>) -> Self::Output

Performs the * operation.

impl<T: MulAdd<T, T, Output = T> + Mul<Output = T> + Copy> Mul<Mat3<T>> for Mat3<T>

Multiplies a column-major matrix with another.

use vek::mat::column_major::Mat4;

let m = Mat4::<u32>::new(
    0, 1, 2, 3,
    4, 5, 6, 7,
    8, 9, 0, 1,
    2, 3, 4, 5
);
let r = Mat4::<u32>::new(
    26, 32, 18, 24,
    82, 104, 66, 88,
    38, 56, 74, 92,
    54, 68, 42, 56
);
assert_eq!(m * m, r);
assert_eq!(m, m * Mat4::<u32>::identity());
assert_eq!(m, Mat4::<u32>::identity() * m);

type Output = Self

The resulting type after applying the * operator.

fn mul(self, rhs: Self) -> Self::Output

Performs the * operation.

impl<T: MulAdd<T, T, Output = T> + Mul<Output = T> + Copy> Mul<Mat3<T>> for Mat3<T>

Multiplies a column-major matrix with a row-major matrix.

use vek::mat::row_major::Mat4 as Rows4;
use vek::mat::column_major::Mat4 as Cols4;

let m = Cols4::<u32>::new(
    0, 1, 2, 3,
    4, 5, 6, 7,
    8, 9, 0, 1,
    2, 3, 4, 5
);
let b = Rows4::from(m);
let r = Rows4::<u32>::new(
    26, 32, 18, 24,
    82, 104, 66, 88,
    38, 56, 74, 92,
    54, 68, 42, 56
);
assert_eq!(m * b, r);
assert_eq!(m * Rows4::<u32>::identity(), m.into());
assert_eq!(Cols4::<u32>::identity() * b, m.into());

type Output = Transpose<T>

The resulting type after applying the * operator.

fn mul(self, rhs: Transpose<T>) -> Self::Output

Performs the * operation.

impl<T: MulAdd<T, T, Output = T> + Mul<Output = T> + Copy> Mul<Mat3<T>> for Mat3<T>

Multiplies a row-major matrix with a column-major matrix, producing a column-major matrix.

use vek::mat::row_major::Mat4 as Rows4;
use vek::mat::column_major::Mat4 as Cols4;

let m = Rows4::<u32>::new(
    0, 1, 2, 3,
    4, 5, 6, 7,
    8, 9, 0, 1,
    2, 3, 4, 5
);
let b = Cols4::from(m);
let r = Cols4::<u32>::new(
    26, 32, 18, 24,
    82, 104, 66, 88,
    38, 56, 74, 92,
    54, 68, 42, 56
);
assert_eq!(m * b, r);
assert_eq!(m * Cols4::<u32>::identity(), m.into());
assert_eq!(Rows4::<u32>::identity() * b, m.into());

type Output = Transpose<T>

The resulting type after applying the * operator.

fn mul(self, rhs: Transpose<T>) -> Self::Output

Performs the * operation.

impl<T> Mul<QuadraticBezier2<T>> for Cols3<T> where
    T: Real + MulAdd<T, T, Output = T>, 

type Output = QuadraticBezier2<T>

The resulting type after applying the * operator.

fn mul(self, rhs: QuadraticBezier2<T>) -> QuadraticBezier2<T>

Performs the * operation.

impl<T> Mul<QuadraticBezier3<T>> for Cols3<T> where
    T: Real + MulAdd<T, T, Output = T>, 

type Output = QuadraticBezier3<T>

The resulting type after applying the * operator.

fn mul(self, rhs: QuadraticBezier3<T>) -> QuadraticBezier3<T>

Performs the * operation.

impl<T> Mul<CubicBezier2<T>> for Cols3<T> where
    T: Real + MulAdd<T, T, Output = T>, 

type Output = CubicBezier2<T>

The resulting type after applying the * operator.

fn mul(self, rhs: CubicBezier2<T>) -> CubicBezier2<T>

Performs the * operation.

impl<T> Mul<CubicBezier3<T>> for Cols3<T> where
    T: Real + MulAdd<T, T, Output = T>, 

type Output = CubicBezier3<T>

The resulting type after applying the * operator.

fn mul(self, rhs: CubicBezier3<T>) -> CubicBezier3<T>

Performs the * operation.

impl<T> Neg for Mat3<T> where
    T: Neg<Output = T>, 

type Output = Self

The resulting type after applying the - operator.

fn neg(self) -> Self::Output

Performs the unary - operation.

impl<T: Add<Output = T> + Copy> AddAssign<Mat3<T>> for Mat3<T>

fn add_assign(&mut self, rhs: Self)

Performs the += operation.

impl<T: Add<Output = T> + Copy> AddAssign<T> for Mat3<T>

fn add_assign(&mut self, rhs: T)

Performs the += operation.

impl<T: Sub<Output = T> + Copy> SubAssign<Mat3<T>> for Mat3<T>

fn sub_assign(&mut self, rhs: Self)

Performs the -= operation.

impl<T: Sub<Output = T> + Copy> SubAssign<T> for Mat3<T>

fn sub_assign(&mut self, rhs: T)

Performs the -= operation.

impl<T> MulAssign<Mat3<T>> for Mat3<T> where
    T: Copy + Zero + Add<Output = T> + Mul<Output = T> + MulAdd<T, T, Output = T>, 

fn mul_assign(&mut self, rhs: Self)

Performs the *= operation.

impl<T> MulAssign<T> for Mat3<T> where
    T: Copy + Zero + Add<Output = T> + Mul<Output = T>, 

fn mul_assign(&mut self, rhs: T)

Performs the *= operation.

impl<T: Div<Output = T> + Copy> DivAssign<Mat3<T>> for Mat3<T>

fn div_assign(&mut self, rhs: Self)

Performs the /= operation.

impl<T: Div<Output = T> + Copy> DivAssign<T> for Mat3<T>

fn div_assign(&mut self, rhs: T)

Performs the /= operation.

impl<T: Rem<Output = T> + Copy> RemAssign<Mat3<T>> for Mat3<T>

fn rem_assign(&mut self, rhs: Self)

Performs the %= operation.

impl<T: Rem<Output = T> + Copy> RemAssign<T> for Mat3<T>

fn rem_assign(&mut self, rhs: T)

Performs the %= operation.

impl<T> Index<(usize, usize)> for Mat3<T>

Index this matrix in a layout-agnostic way with an (i, j) (row index, column index) tuple.

Matrices cannot be indexed by Vec2s because that would be likely to cause confusion: should x be the row index (because it's the first element) or the column index (because it's a horizontal position) ?

type Output = T

The returned type after indexing.

fn index(&self, t: (usize, usize)) -> &Self::Output

Performs the indexing (container[index]) operation.

impl<T> IndexMut<(usize, usize)> for Mat3<T>

fn index_mut(&mut self, t: (usize, usize)) -> &mut Self::Output

Performs the mutable indexing (container[index]) operation.

impl<T: Hash> Hash for Mat3<T>

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given [Hasher].

fn hash_slice<H>(data: &[Self], state: &mut H) where
    H: Hasher, 

Feeds a slice of this type into the given [Hasher].

impl<T: Copy> Copy for Mat3<T>

impl<T> From<Mat3<T>> for Mat4<T> where
    T: Zero + One, 

fn from(m: Mat3<T>) -> Self

Performs the conversion.

impl<T> From<Mat3<T>> for Mat3<T>

fn from(m: Transpose<T>) -> Self

Performs the conversion.

impl<T> From<Mat4<T>> for Mat3<T>

fn from(m: Mat4<T>) -> Self

Performs the conversion.

impl<T> From<Mat2<T>> for Mat3<T> where
    T: Zero + One, 

fn from(m: Mat2<T>) -> Self

Performs the conversion.

impl<T> From<Quaternion<T>> for Mat3<T> where
    T: Copy + Zero + One + Mul<Output = T> + Add<Output = T> + Sub<Output = T>, 

fn from(q: Quaternion<T>) -> Self

Performs the conversion.

impl<T> From<Mat3<T>> for Mat2<T>

fn from(m: Mat3<T>) -> Self

Performs the conversion.

impl<T> From<Mat3<T>> for Mat3<T>

fn from(m: Transpose<T>) -> Self

Performs the conversion.

impl<T: Clone> Clone for Mat3<T>

fn clone(&self) -> Mat3<T>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T: Zero + One> Default for Mat3<T>

The default value for a square matrix is the identity.

assert_eq!(Mat4::<f32>::default(), Mat4::<f32>::identity());

fn default() -> Self

Returns the "default value" for a type.

impl<T: Zero + PartialEq> Zero for Mat3<T>

fn zero() -> Self

Returns the additive identity element of Self, 0. # Purity

fn is_zero(&self) -> bool

Returns true if self is equal to the additive identity.

fn set_zero(&mut self)

Sets self to the additive identity element of Self, 0.

impl<T: Zero + One + Copy + MulAdd<T, T, Output = T>> One for Mat3<T>

fn one() -> Self

Returns the multiplicative identity element of Self, 1.

fn set_one(&mut self)

Sets self to the multiplicative identity element of Self, 1.

fn is_one(&self) -> bool where
    Self: PartialEq<Self>, 

Returns true if self is equal to the multiplicative identity.

impl<T: ApproxEq> ApproxEq for Mat3<T> where
    T::Epsilon: Copy, 

type Epsilon = T::Epsilon

Used for specifying relative comparisons.

fn default_epsilon() -> T::Epsilon

The default tolerance to use when testing values that are close together.

fn default_max_relative() -> T::Epsilon

The default relative tolerance for testing values that are far-apart.

fn default_max_ulps() -> u32

The default ULPs to tolerate when testing values that are far-apart.

fn relative_eq(
    &self,
    other: &Self,
    epsilon: T::Epsilon,
    max_relative: T::Epsilon
) -> bool

A test for equality that uses a relative comparison if the values are far apart.

fn ulps_eq(&self, other: &Self, epsilon: T::Epsilon, max_ulps: u32) -> bool

A test for equality that uses units in the last place (ULP) if the values are far apart.

fn relative_ne(
    &self,
    other: &Self,
    epsilon: Self::Epsilon,
    max_relative: Self::Epsilon
) -> bool

The inverse of ApproxEq::relative_eq.

fn ulps_ne(&self, other: &Self, epsilon: Self::Epsilon, max_ulps: u32) -> bool

The inverse of ApproxEq::ulps_eq.