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-rw-r--r--src/f32/coresimd/mat2.rs52
1 files changed, 36 insertions, 16 deletions
diff --git a/src/f32/coresimd/mat2.rs b/src/f32/coresimd/mat2.rs
index 200aa52..f8c0f91 100644
--- a/src/f32/coresimd/mat2.rs
+++ b/src/f32/coresimd/mat2.rs
@@ -1,24 +1,25 @@
// Generated from mat.rs.tera template. Edit the template, not the generated file.
-use crate::{swizzles::*, DMat2, Mat3, Mat3A, Vec2};
+use crate::{f32::math, 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};
-use core::simd::{Which::*, *};
+use core::simd::*;
-#[cfg(feature = "libm")]
-#[allow(unused_imports)]
-use num_traits::Float;
-
-/// Creates a 2x2 matrix from column vectors.
+/// Creates a 2x2 matrix from two column vectors.
#[inline(always)]
+#[must_use]
pub const fn mat2(x_axis: Vec2, y_axis: Vec2) -> Mat2 {
Mat2::from_cols(x_axis, y_axis)
}
/// A 2x2 column major matrix.
+///
+/// SIMD vector types are used for storage on supported platforms.
+///
+/// This type is 16 byte aligned.
#[derive(Clone, Copy)]
#[repr(transparent)]
pub struct Mat2(pub(crate) f32x4);
@@ -35,12 +36,14 @@ impl Mat2 {
#[allow(clippy::too_many_arguments)]
#[inline(always)]
+ #[must_use]
const fn new(m00: f32, m01: f32, m10: f32, m11: f32) -> Self {
Self(f32x4::from_array([m00, m01, m10, m11]))
}
/// Creates a 2x2 matrix from two column vectors.
#[inline(always)]
+ #[must_use]
pub const fn from_cols(x_axis: Vec2, y_axis: Vec2) -> Self {
Self(f32x4::from_array([x_axis.x, x_axis.y, y_axis.x, y_axis.y]))
}
@@ -49,6 +52,7 @@ impl Mat2 {
/// If your data is stored in row major you will need to `transpose` the returned
/// matrix.
#[inline]
+ #[must_use]
pub const fn from_cols_array(m: &[f32; 4]) -> Self {
Self(f32x4::from_array(*m))
}
@@ -56,6 +60,7 @@ impl Mat2 {
/// Creates a `[f32; 4]` array storing data in column major order.
/// If you require data in row major order `transpose` the matrix first.
#[inline]
+ #[must_use]
pub const fn to_cols_array(&self) -> [f32; 4] {
unsafe { *(self as *const Self as *const [f32; 4]) }
}
@@ -64,6 +69,7 @@ impl Mat2 {
/// If your data is in row major order you will need to `transpose` the returned
/// matrix.
#[inline]
+ #[must_use]
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]))
}
@@ -71,6 +77,7 @@ impl Mat2 {
/// 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]
+ #[must_use]
pub const fn to_cols_array_2d(&self) -> [[f32; 2]; 2] {
unsafe { *(self as *const Self as *const [[f32; 2]; 2]) }
}
@@ -78,6 +85,7 @@ impl Mat2 {
/// Creates a 2x2 matrix with its diagonal set to `diagonal` and all other entries set to 0.
#[doc(alias = "scale")]
#[inline]
+ #[must_use]
pub const fn from_diagonal(diagonal: Vec2) -> Self {
Self::new(diagonal.x, 0.0, 0.0, diagonal.y)
}
@@ -85,26 +93,30 @@ impl Mat2 {
/// Creates a 2x2 matrix containing the combining non-uniform `scale` and rotation of
/// `angle` (in radians).
#[inline]
+ #[must_use]
pub fn from_scale_angle(scale: Vec2, angle: f32) -> Self {
- let (sin, cos) = angle.sin_cos();
+ let (sin, cos) = math::sin_cos(angle);
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]
+ #[must_use]
pub fn from_angle(angle: f32) -> Self {
- let (sin, cos) = angle.sin_cos();
+ let (sin, cos) = math::sin_cos(angle);
Self::new(cos, sin, -sin, cos)
}
/// Creates a 2x2 matrix from a 3x3 matrix, discarding the 2nd row and column.
#[inline]
+ #[must_use]
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]
+ #[must_use]
pub fn from_mat3a(m: Mat3A) -> Self {
Self::from_cols(m.x_axis.xy(), m.y_axis.xy())
}
@@ -115,6 +127,7 @@ impl Mat2 {
///
/// Panics if `slice` is less than 4 elements long.
#[inline]
+ #[must_use]
pub const fn from_cols_slice(slice: &[f32]) -> Self {
Self::new(slice[0], slice[1], slice[2], slice[3])
}
@@ -138,6 +151,7 @@ impl Mat2 {
///
/// Panics if `index` is greater than 1.
#[inline]
+ #[must_use]
pub fn col(&self, index: usize) -> Vec2 {
match index {
0 => self.x_axis,
@@ -166,6 +180,7 @@ impl Mat2 {
///
/// Panics if `index` is greater than 1.
#[inline]
+ #[must_use]
pub fn row(&self, index: usize) -> Vec2 {
match index {
0 => Vec2::new(self.x_axis.x, self.y_axis.x),
@@ -177,25 +192,28 @@ impl Mat2 {
/// 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]
+ #[must_use]
pub fn is_finite(&self) -> bool {
self.x_axis.is_finite() && self.y_axis.is_finite()
}
/// Returns `true` if any elements are `NaN`.
#[inline]
+ #[must_use]
pub fn is_nan(&self) -> bool {
self.x_axis.is_nan() || self.y_axis.is_nan()
}
/// Returns the transpose of `self`.
- #[must_use]
#[inline]
+ #[must_use]
pub fn transpose(&self) -> Self {
Self(simd_swizzle!(self.0, [0, 2, 1, 3]))
}
/// Returns the determinant of `self`.
#[inline]
+ #[must_use]
pub fn determinant(&self) -> f32 {
let abcd = self.0;
let dcba = simd_swizzle!(abcd, [3, 2, 1, 0]);
@@ -211,8 +229,8 @@ impl Mat2 {
/// # Panics
///
/// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
- #[must_use]
#[inline]
+ #[must_use]
pub fn inverse(&self) -> Self {
const SIGN: f32x4 = f32x4::from_array([1.0, -1.0, -1.0, 1.0]);
let abcd = self.0;
@@ -228,6 +246,7 @@ impl Mat2 {
/// Transforms a 2D vector.
#[inline]
+ #[must_use]
pub fn mul_vec2(&self, rhs: Vec2) -> Vec2 {
let abcd = self.0;
let xxyy = f32x4::from_array([rhs.x, rhs.x, rhs.y, rhs.y]);
@@ -239,6 +258,7 @@ impl Mat2 {
/// Multiplies two 2x2 matrices.
#[inline]
+ #[must_use]
pub fn mul_mat2(&self, rhs: &Self) -> Self {
let abcd = self.0;
let xxyy0 = simd_swizzle!(rhs.0, [0, 0, 1, 1]);
@@ -249,27 +269,26 @@ impl Mat2 {
let cydyaxbx1 = simd_swizzle!(axbxcydy1, [2, 3, 0, 1]);
let result0 = axbxcydy0 + cydyaxbx0;
let result1 = axbxcydy1 + cydyaxbx1;
- Self(simd_swizzle!(
- result0,
- result1,
- [First(0), First(1), Second(0), Second(1)]
- ))
+ Self(simd_swizzle!(result0, result1, [0, 1, 4, 5]))
}
/// Adds two 2x2 matrices.
#[inline]
+ #[must_use]
pub fn add_mat2(&self, rhs: &Self) -> Self {
Self(self.0 + rhs.0)
}
/// Subtracts two 2x2 matrices.
#[inline]
+ #[must_use]
pub fn sub_mat2(&self, rhs: &Self) -> Self {
Self(self.0 - rhs.0)
}
/// Multiplies a 2x2 matrix by a scalar.
#[inline]
+ #[must_use]
pub fn mul_scalar(&self, rhs: f32) -> Self {
Self(self.0 * f32x4::splat(rhs))
}
@@ -284,6 +303,7 @@ impl Mat2 {
/// For more see
/// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
#[inline]
+ #[must_use]
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)
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-31 23:28:37 +0000