blob: 9c4c25308a3d9e23c7aa97fcf1853dffe314b1a6 [file] [log] [blame]
// Generated from mat.rs.tera template. Edit the template, not the generated file.
use crate::{swizzles::*, DMat2, Mat3, Mat3A, Vec2};
#[cfg(not(target_arch = "spirv"))]
use core::fmt;
use core::iter::{Product, Sum};
use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
#[cfg(feature = "libm")]
#[allow(unused_imports)]
use num_traits::Float;
/// Creates a 2x2 matrix from column vectors.
#[inline(always)]
pub const fn mat2(x_axis: Vec2, y_axis: Vec2) -> Mat2 {
Mat2::from_cols(x_axis, y_axis)
}
/// A 2x2 column major matrix.
#[derive(Clone, Copy)]
#[cfg_attr(
not(any(feature = "scalar-math", target_arch = "spirv")),
repr(align(16))
)]
#[cfg_attr(feature = "cuda", repr(align(8)))]
#[repr(C)]
pub struct Mat2 {
pub x_axis: Vec2,
pub y_axis: Vec2,
}
impl Mat2 {
/// A 2x2 matrix with all elements set to `0.0`.
pub const ZERO: Self = Self::from_cols(Vec2::ZERO, Vec2::ZERO);
/// A 2x2 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
pub const IDENTITY: Self = Self::from_cols(Vec2::X, Vec2::Y);
/// All NAN:s.
pub const NAN: Self = Self::from_cols(Vec2::NAN, Vec2::NAN);
#[allow(clippy::too_many_arguments)]
#[inline(always)]
const fn new(m00: f32, m01: f32, m10: f32, m11: f32) -> Self {
Self {
x_axis: Vec2::new(m00, m01),
y_axis: Vec2::new(m10, m11),
}
}
/// Creates a 2x2 matrix from two column vectors.
#[inline(always)]
pub const fn from_cols(x_axis: Vec2, y_axis: Vec2) -> Self {
Self { x_axis, y_axis }
}
/// Creates a 2x2 matrix from a `[f32; 4]` array stored in column major order.
/// If your data is stored in row major you will need to `transpose` the returned
/// matrix.
#[inline]
pub const fn from_cols_array(m: &[f32; 4]) -> Self {
Self::new(m[0], m[1], m[2], m[3])
}
/// Creates a `[f32; 4]` array storing data in column major order.
/// If you require data in row major order `transpose` the matrix first.
#[inline]
pub const fn to_cols_array(&self) -> [f32; 4] {
[self.x_axis.x, self.x_axis.y, self.y_axis.x, self.y_axis.y]
}
/// Creates a 2x2 matrix from a `[[f32; 2]; 2]` 2D array stored in column major order.
/// If your data is in row major order you will need to `transpose` the returned
/// matrix.
#[inline]
pub const fn from_cols_array_2d(m: &[[f32; 2]; 2]) -> Self {
Self::from_cols(Vec2::from_array(m[0]), Vec2::from_array(m[1]))
}
/// Creates a `[[f32; 2]; 2]` 2D array storing data in column major order.
/// If you require data in row major order `transpose` the matrix first.
#[inline]
pub const fn to_cols_array_2d(&self) -> [[f32; 2]; 2] {
[self.x_axis.to_array(), self.y_axis.to_array()]
}
/// Creates a 2x2 matrix with its diagonal set to `diagonal` and all other entries set to 0.
#[doc(alias = "scale")]
#[inline]
pub const fn from_diagonal(diagonal: Vec2) -> Self {
Self::new(diagonal.x, 0.0, 0.0, diagonal.y)
}
/// Creates a 2x2 matrix containing the combining non-uniform `scale` and rotation of
/// `angle` (in radians).
#[inline]
pub fn from_scale_angle(scale: Vec2, angle: f32) -> Self {
let (sin, cos) = angle.sin_cos();
Self::new(cos * scale.x, sin * scale.x, -sin * scale.y, cos * scale.y)
}
/// Creates a 2x2 matrix containing a rotation of `angle` (in radians).
#[inline]
pub fn from_angle(angle: f32) -> Self {
let (sin, cos) = angle.sin_cos();
Self::new(cos, sin, -sin, cos)
}
/// Creates a 2x2 matrix from a 3x3 matrix, discarding the 2nd row and column.
#[inline]
pub fn from_mat3(m: Mat3) -> Self {
Self::from_cols(m.x_axis.xy(), m.y_axis.xy())
}
/// Creates a 2x2 matrix from a 3x3 matrix, discarding the 2nd row and column.
#[inline]
pub fn from_mat3a(m: Mat3A) -> Self {
Self::from_cols(m.x_axis.xy(), m.y_axis.xy())
}
/// Creates a 2x2 matrix from the first 4 values in `slice`.
///
/// # Panics
///
/// Panics if `slice` is less than 4 elements long.
#[inline]
pub const fn from_cols_slice(slice: &[f32]) -> Self {
Self::new(slice[0], slice[1], slice[2], slice[3])
}
/// Writes the columns of `self` to the first 4 elements in `slice`.
///
/// # Panics
///
/// Panics if `slice` is less than 4 elements long.
#[inline]
pub fn write_cols_to_slice(self, slice: &mut [f32]) {
slice[0] = self.x_axis.x;
slice[1] = self.x_axis.y;
slice[2] = self.y_axis.x;
slice[3] = self.y_axis.y;
}
/// Returns the matrix column for the given `index`.
///
/// # Panics
///
/// Panics if `index` is greater than 1.
#[inline]
pub fn col(&self, index: usize) -> Vec2 {
match index {
0 => self.x_axis,
1 => self.y_axis,
_ => panic!("index out of bounds"),
}
}
/// Returns a mutable reference to the matrix column for the given `index`.
///
/// # Panics
///
/// Panics if `index` is greater than 1.
#[inline]
pub fn col_mut(&mut self, index: usize) -> &mut Vec2 {
match index {
0 => &mut self.x_axis,
1 => &mut self.y_axis,
_ => panic!("index out of bounds"),
}
}
/// Returns the matrix row for the given `index`.
///
/// # Panics
///
/// Panics if `index` is greater than 1.
#[inline]
pub fn row(&self, index: usize) -> Vec2 {
match index {
0 => Vec2::new(self.x_axis.x, self.y_axis.x),
1 => Vec2::new(self.x_axis.y, self.y_axis.y),
_ => panic!("index out of bounds"),
}
}
/// Returns `true` if, and only if, all elements are finite.
/// If any element is either `NaN`, positive or negative infinity, this will return `false`.
#[inline]
pub fn is_finite(&self) -> bool {
self.x_axis.is_finite() && self.y_axis.is_finite()
}
/// Returns `true` if any elements are `NaN`.
#[inline]
pub fn is_nan(&self) -> bool {
self.x_axis.is_nan() || self.y_axis.is_nan()
}
/// Returns the transpose of `self`.
#[must_use]
#[inline]
pub fn transpose(&self) -> Self {
Self {
x_axis: Vec2::new(self.x_axis.x, self.y_axis.x),
y_axis: Vec2::new(self.x_axis.y, self.y_axis.y),
}
}
/// Returns the determinant of `self`.
#[inline]
pub fn determinant(&self) -> f32 {
self.x_axis.x * self.y_axis.y - self.x_axis.y * self.y_axis.x
}
/// Returns the inverse of `self`.
///
/// If the matrix is not invertible the returned matrix will be invalid.
///
/// # Panics
///
/// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
#[must_use]
#[inline]
pub fn inverse(&self) -> Self {
let inv_det = {
let det = self.determinant();
glam_assert!(det != 0.0);
det.recip()
};
Self::new(
self.y_axis.y * inv_det,
self.x_axis.y * -inv_det,
self.y_axis.x * -inv_det,
self.x_axis.x * inv_det,
)
}
/// Transforms a 2D vector.
#[inline]
pub fn mul_vec2(&self, rhs: Vec2) -> Vec2 {
#[allow(clippy::suspicious_operation_groupings)]
Vec2::new(
(self.x_axis.x * rhs.x) + (self.y_axis.x * rhs.y),
(self.x_axis.y * rhs.x) + (self.y_axis.y * rhs.y),
)
}
/// Multiplies two 2x2 matrices.
#[inline]
pub fn mul_mat2(&self, rhs: &Self) -> Self {
Self::from_cols(self.mul(rhs.x_axis), self.mul(rhs.y_axis))
}
/// Adds two 2x2 matrices.
#[inline]
pub fn add_mat2(&self, rhs: &Self) -> Self {
Self::from_cols(self.x_axis.add(rhs.x_axis), self.y_axis.add(rhs.y_axis))
}
/// Subtracts two 2x2 matrices.
#[inline]
pub fn sub_mat2(&self, rhs: &Self) -> Self {
Self::from_cols(self.x_axis.sub(rhs.x_axis), self.y_axis.sub(rhs.y_axis))
}
/// Multiplies a 2x2 matrix by a scalar.
#[inline]
pub fn mul_scalar(&self, rhs: f32) -> Self {
Self::from_cols(self.x_axis.mul(rhs), self.y_axis.mul(rhs))
}
/// Returns true if the absolute difference of all elements between `self` and `rhs`
/// is less than or equal to `max_abs_diff`.
///
/// This can be used to compare if two matrices contain similar elements. It works best
/// when comparing with a known value. The `max_abs_diff` that should be used used
/// depends on the values being compared against.
///
/// For more see
/// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
#[inline]
pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f32) -> bool {
self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
&& self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
}
#[inline]
pub fn as_dmat2(&self) -> DMat2 {
DMat2::from_cols(self.x_axis.as_dvec2(), self.y_axis.as_dvec2())
}
}
impl Default for Mat2 {
#[inline]
fn default() -> Self {
Self::IDENTITY
}
}
impl Add<Mat2> for Mat2 {
type Output = Self;
#[inline]
fn add(self, rhs: Self) -> Self::Output {
self.add_mat2(&rhs)
}
}
impl AddAssign<Mat2> for Mat2 {
#[inline]
fn add_assign(&mut self, rhs: Self) {
*self = self.add_mat2(&rhs);
}
}
impl Sub<Mat2> for Mat2 {
type Output = Self;
#[inline]
fn sub(self, rhs: Self) -> Self::Output {
self.sub_mat2(&rhs)
}
}
impl SubAssign<Mat2> for Mat2 {
#[inline]
fn sub_assign(&mut self, rhs: Self) {
*self = self.sub_mat2(&rhs);
}
}
impl Neg for Mat2 {
type Output = Self;
#[inline]
fn neg(self) -> Self::Output {
Self::from_cols(self.x_axis.neg(), self.y_axis.neg())
}
}
impl Mul<Mat2> for Mat2 {
type Output = Self;
#[inline]
fn mul(self, rhs: Self) -> Self::Output {
self.mul_mat2(&rhs)
}
}
impl MulAssign<Mat2> for Mat2 {
#[inline]
fn mul_assign(&mut self, rhs: Self) {
*self = self.mul_mat2(&rhs);
}
}
impl Mul<Vec2> for Mat2 {
type Output = Vec2;
#[inline]
fn mul(self, rhs: Vec2) -> Self::Output {
self.mul_vec2(rhs)
}
}
impl Mul<Mat2> for f32 {
type Output = Mat2;
#[inline]
fn mul(self, rhs: Mat2) -> Self::Output {
rhs.mul_scalar(self)
}
}
impl Mul<f32> for Mat2 {
type Output = Self;
#[inline]
fn mul(self, rhs: f32) -> Self::Output {
self.mul_scalar(rhs)
}
}
impl MulAssign<f32> for Mat2 {
#[inline]
fn mul_assign(&mut self, rhs: f32) {
*self = self.mul_scalar(rhs);
}
}
impl Sum<Self> for Mat2 {
fn sum<I>(iter: I) -> Self
where
I: Iterator<Item = Self>,
{
iter.fold(Self::ZERO, Self::add)
}
}
impl<'a> Sum<&'a Self> for Mat2 {
fn sum<I>(iter: I) -> Self
where
I: Iterator<Item = &'a Self>,
{
iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
}
}
impl Product for Mat2 {
fn product<I>(iter: I) -> Self
where
I: Iterator<Item = Self>,
{
iter.fold(Self::IDENTITY, Self::mul)
}
}
impl<'a> Product<&'a Self> for Mat2 {
fn product<I>(iter: I) -> Self
where
I: Iterator<Item = &'a Self>,
{
iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
}
}
impl PartialEq for Mat2 {
#[inline]
fn eq(&self, rhs: &Self) -> bool {
self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis)
}
}
#[cfg(not(target_arch = "spirv"))]
impl AsRef<[f32; 4]> for Mat2 {
#[inline]
fn as_ref(&self) -> &[f32; 4] {
unsafe { &*(self as *const Self as *const [f32; 4]) }
}
}
#[cfg(not(target_arch = "spirv"))]
impl AsMut<[f32; 4]> for Mat2 {
#[inline]
fn as_mut(&mut self) -> &mut [f32; 4] {
unsafe { &mut *(self as *mut Self as *mut [f32; 4]) }
}
}
#[cfg(not(target_arch = "spirv"))]
impl fmt::Debug for Mat2 {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(stringify!(Mat2))
.field("x_axis", &self.x_axis)
.field("y_axis", &self.y_axis)
.finish()
}
}
#[cfg(not(target_arch = "spirv"))]
impl fmt::Display for Mat2 {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "[{}, {}]", self.x_axis, self.y_axis)
}
}