crates/glam/src/f32/sse2/mat3a.rs - platform/external/rust/android-crates-io - Git at Google

 // Generated from mat.rs.tera template. Edit the template, not the generated file.

 use crate::{f32::math, swizzles::*, DMat3, EulerRot, Mat2, Mat3, Mat4, Quat, Vec2, Vec3, Vec3A};
 #[cfg(not(target_arch = "spirv"))]
 use core::fmt;
 use core::iter::{Product, Sum};
 use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};

 #[cfg(target_arch = "x86")]
 use core::arch::x86::*;
 #[cfg(target_arch = "x86_64")]
 use core::arch::x86_64::*;

 /// Creates a 3x3 matrix from three column vectors.
 #[inline(always)]
 #[must_use]
 pub const fn mat3a(x_axis: Vec3A, y_axis: Vec3A, z_axis: Vec3A) -> Mat3A {
     Mat3A::from_cols(x_axis, y_axis, z_axis)
 }

 /// A 3x3 column major matrix.
 ///
 /// This 3x3 matrix type features convenience methods for creating and using linear and
 /// affine transformations. If you are primarily dealing with 2D affine transformations the
 /// [`Affine2`](crate::Affine2) type is much faster and more space efficient than
 /// using a 3x3 matrix.
 ///
 /// Linear transformations including 3D rotation and scale can be created using methods
 /// such as [`Self::from_diagonal()`], [`Self::from_quat()`], [`Self::from_axis_angle()`],
 /// [`Self::from_rotation_x()`], [`Self::from_rotation_y()`], or
 /// [`Self::from_rotation_z()`].
 ///
 /// The resulting matrices can be use to transform 3D vectors using regular vector
 /// multiplication.
 ///
 /// Affine transformations including 2D translation, rotation and scale can be created
 /// using methods such as [`Self::from_translation()`], [`Self::from_angle()`],
 /// [`Self::from_scale()`] and [`Self::from_scale_angle_translation()`].
 ///
 /// The [`Self::transform_point2()`] and [`Self::transform_vector2()`] convenience methods
 /// are provided for performing affine transforms on 2D vectors and points. These multiply
 /// 2D inputs as 3D vectors with an implicit `z` value of `1` for points and `0` for
 /// vectors respectively. These methods assume that `Self` contains a valid affine
 /// transform.
 #[derive(Clone, Copy)]
 #[repr(C)]
 pub struct Mat3A {
     pub x_axis: Vec3A,
     pub y_axis: Vec3A,
     pub z_axis: Vec3A,
 }

 impl Mat3A {
     /// A 3x3 matrix with all elements set to `0.0`.
     pub const ZERO: Self = Self::from_cols(Vec3A::ZERO, Vec3A::ZERO, Vec3A::ZERO);

     /// A 3x3 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
     pub const IDENTITY: Self = Self::from_cols(Vec3A::X, Vec3A::Y, Vec3A::Z);

     /// All NAN:s.
     pub const NAN: Self = Self::from_cols(Vec3A::NAN, Vec3A::NAN, Vec3A::NAN);

     #[allow(clippy::too_many_arguments)]
     #[inline(always)]
     #[must_use]
     const fn new(
         m00: f32,
         m01: f32,
         m02: f32,
         m10: f32,
         m11: f32,
         m12: f32,
         m20: f32,
         m21: f32,
         m22: f32,
     ) -> Self {
         Self {
             x_axis: Vec3A::new(m00, m01, m02),
             y_axis: Vec3A::new(m10, m11, m12),
             z_axis: Vec3A::new(m20, m21, m22),
         }
     }

     /// Creates a 3x3 matrix from three column vectors.
     #[inline(always)]
     #[must_use]
     pub const fn from_cols(x_axis: Vec3A, y_axis: Vec3A, z_axis: Vec3A) -> Self {
         Self {
             x_axis,
             y_axis,
             z_axis,
         }
     }

     /// Creates a 3x3 matrix from a `[f32; 9]` array stored in column major order.
     /// 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; 9]) -> Self {
         Self::new(m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8])
     }

     /// Creates a `[f32; 9]` 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; 9] {
         let [x_axis_x, x_axis_y, x_axis_z] = self.x_axis.to_array();
         let [y_axis_x, y_axis_y, y_axis_z] = self.y_axis.to_array();
         let [z_axis_x, z_axis_y, z_axis_z] = self.z_axis.to_array();

         [
             x_axis_x, x_axis_y, x_axis_z, y_axis_x, y_axis_y, y_axis_z, z_axis_x, z_axis_y,
             z_axis_z,
         ]
     }

     /// Creates a 3x3 matrix from a `[[f32; 3]; 3]` 3D array stored in column major order.
     /// 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; 3]; 3]) -> Self {
         Self::from_cols(
             Vec3A::from_array(m[0]),
             Vec3A::from_array(m[1]),
             Vec3A::from_array(m[2]),
         )
     }

     /// Creates a `[[f32; 3]; 3]` 3D 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; 3]; 3] {
         [
             self.x_axis.to_array(),
             self.y_axis.to_array(),
             self.z_axis.to_array(),
         ]
     }

     /// Creates a 3x3 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: Vec3) -> Self {
         Self::new(
             diagonal.x, 0.0, 0.0, 0.0, diagonal.y, 0.0, 0.0, 0.0, diagonal.z,
         )
     }

     /// Creates a 3x3 matrix from a 4x4 matrix, discarding the 4th row and column.
     #[inline]
     #[must_use]
     pub fn from_mat4(m: Mat4) -> Self {
         Self::from_cols(m.x_axis.into(), m.y_axis.into(), m.z_axis.into())
     }

     /// Creates a 3D rotation matrix from the given quaternion.
     ///
     /// # Panics
     ///
     /// Will panic if `rotation` is not normalized when `glam_assert` is enabled.
     #[inline]
     #[must_use]
     pub fn from_quat(rotation: Quat) -> Self {
         glam_assert!(rotation.is_normalized());

         let x2 = rotation.x + rotation.x;
         let y2 = rotation.y + rotation.y;
         let z2 = rotation.z + rotation.z;
         let xx = rotation.x * x2;
         let xy = rotation.x * y2;
         let xz = rotation.x * z2;
         let yy = rotation.y * y2;
         let yz = rotation.y * z2;
         let zz = rotation.z * z2;
         let wx = rotation.w * x2;
         let wy = rotation.w * y2;
         let wz = rotation.w * z2;

         Self::from_cols(
             Vec3A::new(1.0 - (yy + zz), xy + wz, xz - wy),
             Vec3A::new(xy - wz, 1.0 - (xx + zz), yz + wx),
             Vec3A::new(xz + wy, yz - wx, 1.0 - (xx + yy)),
         )
     }

     /// Creates a 3D rotation matrix from a normalized rotation `axis` and `angle` (in
     /// radians).
     ///
     /// # Panics
     ///
     /// Will panic if `axis` is not normalized when `glam_assert` is enabled.
     #[inline]
     #[must_use]
     pub fn from_axis_angle(axis: Vec3, angle: f32) -> Self {
         glam_assert!(axis.is_normalized());

         let (sin, cos) = math::sin_cos(angle);
         let (xsin, ysin, zsin) = axis.mul(sin).into();
         let (x, y, z) = axis.into();
         let (x2, y2, z2) = axis.mul(axis).into();
         let omc = 1.0 - cos;
         let xyomc = x * y * omc;
         let xzomc = x * z * omc;
         let yzomc = y * z * omc;
         Self::from_cols(
             Vec3A::new(x2 * omc + cos, xyomc + zsin, xzomc - ysin),
             Vec3A::new(xyomc - zsin, y2 * omc + cos, yzomc + xsin),
             Vec3A::new(xzomc + ysin, yzomc - xsin, z2 * omc + cos),
         )
     }

     /// Creates a 3D rotation matrix from the given euler rotation sequence and the angles (in
     /// radians).
     #[inline]
     #[must_use]
     pub fn from_euler(order: EulerRot, a: f32, b: f32, c: f32) -> Self {
         let quat = Quat::from_euler(order, a, b, c);
         Self::from_quat(quat)
     }

     /// Creates a 3D rotation matrix from `angle` (in radians) around the x axis.
     #[inline]
     #[must_use]
     pub fn from_rotation_x(angle: f32) -> Self {
         let (sina, cosa) = math::sin_cos(angle);
         Self::from_cols(
             Vec3A::X,
             Vec3A::new(0.0, cosa, sina),
             Vec3A::new(0.0, -sina, cosa),
         )
     }

     /// Creates a 3D rotation matrix from `angle` (in radians) around the y axis.
     #[inline]
     #[must_use]
     pub fn from_rotation_y(angle: f32) -> Self {
         let (sina, cosa) = math::sin_cos(angle);
         Self::from_cols(
             Vec3A::new(cosa, 0.0, -sina),
             Vec3A::Y,
             Vec3A::new(sina, 0.0, cosa),
         )
     }

     /// Creates a 3D rotation matrix from `angle` (in radians) around the z axis.
     #[inline]
     #[must_use]
     pub fn from_rotation_z(angle: f32) -> Self {
         let (sina, cosa) = math::sin_cos(angle);
         Self::from_cols(
             Vec3A::new(cosa, sina, 0.0),
             Vec3A::new(-sina, cosa, 0.0),
             Vec3A::Z,
         )
     }

     /// Creates an affine transformation matrix from the given 2D `translation`.
     ///
     /// The resulting matrix can be used to transform 2D points and vectors. See
     /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
     #[inline]
     #[must_use]
     pub fn from_translation(translation: Vec2) -> Self {
         Self::from_cols(
             Vec3A::X,
             Vec3A::Y,
             Vec3A::new(translation.x, translation.y, 1.0),
         )
     }

     /// Creates an affine transformation matrix from the given 2D rotation `angle` (in
     /// radians).
     ///
     /// The resulting matrix can be used to transform 2D points and vectors. See
     /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
     #[inline]
     #[must_use]
     pub fn from_angle(angle: f32) -> Self {
         let (sin, cos) = math::sin_cos(angle);
         Self::from_cols(
             Vec3A::new(cos, sin, 0.0),
             Vec3A::new(-sin, cos, 0.0),
             Vec3A::Z,
         )
     }

     /// Creates an affine transformation matrix from the given 2D `scale`, rotation `angle` (in
     /// radians) and `translation`.
     ///
     /// The resulting matrix can be used to transform 2D points and vectors. See
     /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
     #[inline]
     #[must_use]
     pub fn from_scale_angle_translation(scale: Vec2, angle: f32, translation: Vec2) -> Self {
         let (sin, cos) = math::sin_cos(angle);
         Self::from_cols(
             Vec3A::new(cos * scale.x, sin * scale.x, 0.0),
             Vec3A::new(-sin * scale.y, cos * scale.y, 0.0),
             Vec3A::new(translation.x, translation.y, 1.0),
         )
     }

     /// Creates an affine transformation matrix from the given non-uniform 2D `scale`.
     ///
     /// The resulting matrix can be used to transform 2D points and vectors. See
     /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
     ///
     /// # Panics
     ///
     /// Will panic if all elements of `scale` are zero when `glam_assert` is enabled.
     #[inline]
     #[must_use]
     pub fn from_scale(scale: Vec2) -> Self {
         // Do not panic as long as any component is non-zero
         glam_assert!(scale.cmpne(Vec2::ZERO).any());

         Self::from_cols(
             Vec3A::new(scale.x, 0.0, 0.0),
             Vec3A::new(0.0, scale.y, 0.0),
             Vec3A::Z,
         )
     }

     /// Creates an affine transformation matrix from the given 2x2 matrix.
     ///
     /// The resulting matrix can be used to transform 2D points and vectors. See
     /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
     #[inline]
     pub fn from_mat2(m: Mat2) -> Self {
         Self::from_cols((m.x_axis, 0.0).into(), (m.y_axis, 0.0).into(), Vec3A::Z)
     }

     /// Creates a 3x3 matrix from the first 9 values in `slice`.
     ///
     /// # Panics
     ///
     /// Panics if `slice` is less than 9 elements long.
     #[inline]
     #[must_use]
     pub const fn from_cols_slice(slice: &[f32]) -> Self {
         Self::new(
             slice[0], slice[1], slice[2], slice[3], slice[4], slice[5], slice[6], slice[7],
             slice[8],
         )
     }

     /// Writes the columns of `self` to the first 9 elements in `slice`.
     ///
     /// # Panics
     ///
     /// Panics if `slice` is less than 9 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.x_axis.z;
         slice[3] = self.y_axis.x;
         slice[4] = self.y_axis.y;
         slice[5] = self.y_axis.z;
         slice[6] = self.z_axis.x;
         slice[7] = self.z_axis.y;
         slice[8] = self.z_axis.z;
     }

     /// Returns the matrix column for the given `index`.
     ///
     /// # Panics
     ///
     /// Panics if `index` is greater than 2.
     #[inline]
     #[must_use]
     pub fn col(&self, index: usize) -> Vec3A {
         match index {
             0 => self.x_axis,
             1 => self.y_axis,
             2 => self.z_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 2.
     #[inline]
     pub fn col_mut(&mut self, index: usize) -> &mut Vec3A {
         match index {
             0 => &mut self.x_axis,
             1 => &mut self.y_axis,
             2 => &mut self.z_axis,
             _ => panic!("index out of bounds"),
         }
     }

     /// Returns the matrix row for the given `index`.
     ///
     /// # Panics
     ///
     /// Panics if `index` is greater than 2.
     #[inline]
     #[must_use]
     pub fn row(&self, index: usize) -> Vec3A {
         match index {
             0 => Vec3A::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
             1 => Vec3A::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
             2 => Vec3A::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
             _ => 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]
     #[must_use]
     pub fn is_finite(&self) -> bool {
         self.x_axis.is_finite() && self.y_axis.is_finite() && self.z_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() || self.z_axis.is_nan()
     }

     /// Returns the transpose of `self`.
     #[inline]
     #[must_use]
     pub fn transpose(&self) -> Self {
         unsafe {
             let tmp0 = _mm_shuffle_ps(self.x_axis.0, self.y_axis.0, 0b01_00_01_00);
             let tmp1 = _mm_shuffle_ps(self.x_axis.0, self.y_axis.0, 0b11_10_11_10);

             Self {
                 x_axis: Vec3A(_mm_shuffle_ps(tmp0, self.z_axis.0, 0b00_00_10_00)),
                 y_axis: Vec3A(_mm_shuffle_ps(tmp0, self.z_axis.0, 0b01_01_11_01)),
                 z_axis: Vec3A(_mm_shuffle_ps(tmp1, self.z_axis.0, 0b10_10_10_00)),
             }
         }
     }

     /// Returns the determinant of `self`.
     #[inline]
     #[must_use]
     pub fn determinant(&self) -> f32 {
         self.z_axis.dot(self.x_axis.cross(self.y_axis))
     }

     /// 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.
     #[inline]
     #[must_use]
     pub fn inverse(&self) -> Self {
         let tmp0 = self.y_axis.cross(self.z_axis);
         let tmp1 = self.z_axis.cross(self.x_axis);
         let tmp2 = self.x_axis.cross(self.y_axis);
         let det = self.z_axis.dot(tmp2);
         glam_assert!(det != 0.0);
         let inv_det = Vec3A::splat(det.recip());
         Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose()
     }

     /// Transforms the given 2D vector as a point.
     ///
     /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
     ///
     /// This method assumes that `self` contains a valid affine transform.
     ///
     /// # Panics
     ///
     /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
     #[inline]
     #[must_use]
     pub fn transform_point2(&self, rhs: Vec2) -> Vec2 {
         glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
         Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
     }

     /// Rotates the given 2D vector.
     ///
     /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
     ///
     /// This method assumes that `self` contains a valid affine transform.
     ///
     /// # Panics
     ///
     /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
     #[inline]
     #[must_use]
     pub fn transform_vector2(&self, rhs: Vec2) -> Vec2 {
         glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
         Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
     }

     /// Transforms a 3D vector.
     #[inline]
     #[must_use]
     pub fn mul_vec3(&self, rhs: Vec3) -> Vec3 {
         self.mul_vec3a(rhs.into()).into()
     }

     /// Transforms a [`Vec3A`].
     #[inline]
     #[must_use]
     pub fn mul_vec3a(&self, rhs: Vec3A) -> Vec3A {
         let mut res = self.x_axis.mul(rhs.xxx());
         res = res.add(self.y_axis.mul(rhs.yyy()));
         res = res.add(self.z_axis.mul(rhs.zzz()));
         res
     }

     /// Multiplies two 3x3 matrices.
     #[inline]
     #[must_use]
     pub fn mul_mat3(&self, rhs: &Self) -> Self {
         Self::from_cols(
             self.mul(rhs.x_axis),
             self.mul(rhs.y_axis),
             self.mul(rhs.z_axis),
         )
     }

     /// Adds two 3x3 matrices.
     #[inline]
     #[must_use]
     pub fn add_mat3(&self, rhs: &Self) -> Self {
         Self::from_cols(
             self.x_axis.add(rhs.x_axis),
             self.y_axis.add(rhs.y_axis),
             self.z_axis.add(rhs.z_axis),
         )
     }

     /// Subtracts two 3x3 matrices.
     #[inline]
     #[must_use]
     pub fn sub_mat3(&self, rhs: &Self) -> Self {
         Self::from_cols(
             self.x_axis.sub(rhs.x_axis),
             self.y_axis.sub(rhs.y_axis),
             self.z_axis.sub(rhs.z_axis),
         )
     }

     /// Multiplies a 3x3 matrix by a scalar.
     #[inline]
     #[must_use]
     pub fn mul_scalar(&self, rhs: f32) -> Self {
         Self::from_cols(
             self.x_axis.mul(rhs),
             self.y_axis.mul(rhs),
             self.z_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]
     #[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)
             && self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
     }

     #[inline]
     pub fn as_dmat3(&self) -> DMat3 {
         DMat3::from_cols(
             self.x_axis.as_dvec3(),
             self.y_axis.as_dvec3(),
             self.z_axis.as_dvec3(),
         )
     }
 }

 impl Default for Mat3A {
     #[inline]
     fn default() -> Self {
         Self::IDENTITY
     }
 }

 impl Add<Mat3A> for Mat3A {
     type Output = Self;
     #[inline]
     fn add(self, rhs: Self) -> Self::Output {
         self.add_mat3(&rhs)
     }
 }

 impl AddAssign<Mat3A> for Mat3A {
     #[inline]
     fn add_assign(&mut self, rhs: Self) {
         *self = self.add_mat3(&rhs);
     }
 }

 impl Sub<Mat3A> for Mat3A {
     type Output = Self;
     #[inline]
     fn sub(self, rhs: Self) -> Self::Output {
         self.sub_mat3(&rhs)
     }
 }

 impl SubAssign<Mat3A> for Mat3A {
     #[inline]
     fn sub_assign(&mut self, rhs: Self) {
         *self = self.sub_mat3(&rhs);
     }
 }

 impl Neg for Mat3A {
     type Output = Self;
     #[inline]
     fn neg(self) -> Self::Output {
         Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
     }
 }

 impl Mul<Mat3A> for Mat3A {
     type Output = Self;
     #[inline]
     fn mul(self, rhs: Self) -> Self::Output {
         self.mul_mat3(&rhs)
     }
 }

 impl MulAssign<Mat3A> for Mat3A {
     #[inline]
     fn mul_assign(&mut self, rhs: Self) {
         *self = self.mul_mat3(&rhs);
     }
 }

 impl Mul<Vec3A> for Mat3A {
     type Output = Vec3A;
     #[inline]
     fn mul(self, rhs: Vec3A) -> Self::Output {
         self.mul_vec3a(rhs)
     }
 }

 impl Mul<Mat3A> for f32 {
     type Output = Mat3A;
     #[inline]
     fn mul(self, rhs: Mat3A) -> Self::Output {
         rhs.mul_scalar(self)
     }
 }

 impl Mul<f32> for Mat3A {
     type Output = Self;
     #[inline]
     fn mul(self, rhs: f32) -> Self::Output {
         self.mul_scalar(rhs)
     }
 }

 impl MulAssign<f32> for Mat3A {
     #[inline]
     fn mul_assign(&mut self, rhs: f32) {
         *self = self.mul_scalar(rhs);
     }
 }

 impl Mul<Vec3> for Mat3A {
     type Output = Vec3;
     #[inline]
     fn mul(self, rhs: Vec3) -> Vec3 {
         self.mul_vec3a(rhs.into()).into()
     }
 }

 impl From<Mat3> for Mat3A {
     #[inline]
     fn from(m: Mat3) -> Self {
         Self {
             x_axis: m.x_axis.into(),
             y_axis: m.y_axis.into(),
             z_axis: m.z_axis.into(),
         }
     }
 }

 impl Sum<Self> for Mat3A {
     fn sum<I>(iter: I) -> Self
     where
         I: Iterator<Item = Self>,
     {
         iter.fold(Self::ZERO, Self::add)
     }
 }

 impl<'a> Sum<&'a Self> for Mat3A {
     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 Mat3A {
     fn product<I>(iter: I) -> Self
     where
         I: Iterator<Item = Self>,
     {
         iter.fold(Self::IDENTITY, Self::mul)
     }
 }

 impl<'a> Product<&'a Self> for Mat3A {
     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 Mat3A {
     #[inline]
     fn eq(&self, rhs: &Self) -> bool {
         self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
     }
 }

 #[cfg(not(target_arch = "spirv"))]
 impl fmt::Debug for Mat3A {
     fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
         fmt.debug_struct(stringify!(Mat3A))
             .field("x_axis", &self.x_axis)
             .field("y_axis", &self.y_axis)
             .field("z_axis", &self.z_axis)
             .finish()
     }
 }

 #[cfg(not(target_arch = "spirv"))]
 impl fmt::Display for Mat3A {
     fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
         write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
     }
 }
	// Generated from mat.rs.tera template. Edit the template, not the generated file.

	use crate::{f32::math, swizzles::*, DMat3, EulerRot, Mat2, Mat3, Mat4, Quat, Vec2, Vec3, Vec3A};
	#[cfg(not(target_arch = "spirv"))]
	use core::fmt;
	use core::iter::{Product, Sum};
	use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};

	#[cfg(target_arch = "x86")]
	use core::arch::x86::*;
	#[cfg(target_arch = "x86_64")]
	use core::arch::x86_64::*;

	/// Creates a 3x3 matrix from three column vectors.
	#[inline(always)]
	#[must_use]
	pub const fn mat3a(x_axis: Vec3A, y_axis: Vec3A, z_axis: Vec3A) -> Mat3A {
	Mat3A::from_cols(x_axis, y_axis, z_axis)
	}

	/// A 3x3 column major matrix.
	///
	/// This 3x3 matrix type features convenience methods for creating and using linear and
	/// affine transformations. If you are primarily dealing with 2D affine transformations the
	/// [`Affine2`](crate::Affine2) type is much faster and more space efficient than
	/// using a 3x3 matrix.
	///
	/// Linear transformations including 3D rotation and scale can be created using methods
	/// such as [`Self::from_diagonal()`], [`Self::from_quat()`], [`Self::from_axis_angle()`],
	/// [`Self::from_rotation_x()`], [`Self::from_rotation_y()`], or
	/// [`Self::from_rotation_z()`].
	///
	/// The resulting matrices can be use to transform 3D vectors using regular vector
	/// multiplication.
	///
	/// Affine transformations including 2D translation, rotation and scale can be created
	/// using methods such as [`Self::from_translation()`], [`Self::from_angle()`],
	/// [`Self::from_scale()`] and [`Self::from_scale_angle_translation()`].
	///
	/// The [`Self::transform_point2()`] and [`Self::transform_vector2()`] convenience methods
	/// are provided for performing affine transforms on 2D vectors and points. These multiply
	/// 2D inputs as 3D vectors with an implicit `z` value of `1` for points and `0` for
	/// vectors respectively. These methods assume that `Self` contains a valid affine
	/// transform.
	#[derive(Clone, Copy)]
	#[repr(C)]
	pub struct Mat3A {
	pub x_axis: Vec3A,
	pub y_axis: Vec3A,
	pub z_axis: Vec3A,
	}

	impl Mat3A {
	/// A 3x3 matrix with all elements set to `0.0`.
	pub const ZERO: Self = Self::from_cols(Vec3A::ZERO, Vec3A::ZERO, Vec3A::ZERO);

	/// A 3x3 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
	pub const IDENTITY: Self = Self::from_cols(Vec3A::X, Vec3A::Y, Vec3A::Z);

	/// All NAN:s.
	pub const NAN: Self = Self::from_cols(Vec3A::NAN, Vec3A::NAN, Vec3A::NAN);

	#[allow(clippy::too_many_arguments)]
	#[inline(always)]
	#[must_use]
	const fn new(
	m00: f32,
	m01: f32,
	m02: f32,
	m10: f32,
	m11: f32,
	m12: f32,
	m20: f32,
	m21: f32,
	m22: f32,
	) -> Self {
	Self {
	x_axis: Vec3A::new(m00, m01, m02),
	y_axis: Vec3A::new(m10, m11, m12),
	z_axis: Vec3A::new(m20, m21, m22),
	}
	}

	/// Creates a 3x3 matrix from three column vectors.
	#[inline(always)]
	#[must_use]
	pub const fn from_cols(x_axis: Vec3A, y_axis: Vec3A, z_axis: Vec3A) -> Self {
	Self {
	x_axis,
	y_axis,
	z_axis,
	}
	}

	/// Creates a 3x3 matrix from a `[f32; 9]` array stored in column major order.
	/// 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; 9]) -> Self {
	Self::new(m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8])
	}

	/// Creates a `[f32; 9]` 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; 9] {
	let [x_axis_x, x_axis_y, x_axis_z] = self.x_axis.to_array();
	let [y_axis_x, y_axis_y, y_axis_z] = self.y_axis.to_array();
	let [z_axis_x, z_axis_y, z_axis_z] = self.z_axis.to_array();

	[
	x_axis_x, x_axis_y, x_axis_z, y_axis_x, y_axis_y, y_axis_z, z_axis_x, z_axis_y,
	z_axis_z,
	]
	}

	/// Creates a 3x3 matrix from a `[[f32; 3]; 3]` 3D array stored in column major order.
	/// 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; 3]; 3]) -> Self {
	Self::from_cols(
	Vec3A::from_array(m[0]),
	Vec3A::from_array(m[1]),
	Vec3A::from_array(m[2]),
	)
	}

	/// Creates a `[[f32; 3]; 3]` 3D 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; 3]; 3] {
	[
	self.x_axis.to_array(),
	self.y_axis.to_array(),
	self.z_axis.to_array(),
	]
	}

	/// Creates a 3x3 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: Vec3) -> Self {
	Self::new(
	diagonal.x, 0.0, 0.0, 0.0, diagonal.y, 0.0, 0.0, 0.0, diagonal.z,
	)
	}

	/// Creates a 3x3 matrix from a 4x4 matrix, discarding the 4th row and column.
	#[inline]
	#[must_use]
	pub fn from_mat4(m: Mat4) -> Self {
	Self::from_cols(m.x_axis.into(), m.y_axis.into(), m.z_axis.into())
	}

	/// Creates a 3D rotation matrix from the given quaternion.
	///
	/// # Panics
	///
	/// Will panic if `rotation` is not normalized when `glam_assert` is enabled.
	#[inline]
	#[must_use]
	pub fn from_quat(rotation: Quat) -> Self {
	glam_assert!(rotation.is_normalized());

	let x2 = rotation.x + rotation.x;
	let y2 = rotation.y + rotation.y;
	let z2 = rotation.z + rotation.z;
	let xx = rotation.x * x2;
	let xy = rotation.x * y2;
	let xz = rotation.x * z2;
	let yy = rotation.y * y2;
	let yz = rotation.y * z2;
	let zz = rotation.z * z2;
	let wx = rotation.w * x2;
	let wy = rotation.w * y2;
	let wz = rotation.w * z2;

	Self::from_cols(
	Vec3A::new(1.0 - (yy + zz), xy + wz, xz - wy),
	Vec3A::new(xy - wz, 1.0 - (xx + zz), yz + wx),
	Vec3A::new(xz + wy, yz - wx, 1.0 - (xx + yy)),
	)
	}

	/// Creates a 3D rotation matrix from a normalized rotation `axis` and `angle` (in
	/// radians).
	///
	/// # Panics
	///
	/// Will panic if `axis` is not normalized when `glam_assert` is enabled.
	#[inline]
	#[must_use]
	pub fn from_axis_angle(axis: Vec3, angle: f32) -> Self {
	glam_assert!(axis.is_normalized());

	let (sin, cos) = math::sin_cos(angle);
	let (xsin, ysin, zsin) = axis.mul(sin).into();
	let (x, y, z) = axis.into();
	let (x2, y2, z2) = axis.mul(axis).into();
	let omc = 1.0 - cos;
	let xyomc = x * y * omc;
	let xzomc = x * z * omc;
	let yzomc = y * z * omc;
	Self::from_cols(
	Vec3A::new(x2 * omc + cos, xyomc + zsin, xzomc - ysin),
	Vec3A::new(xyomc - zsin, y2 * omc + cos, yzomc + xsin),
	Vec3A::new(xzomc + ysin, yzomc - xsin, z2 * omc + cos),
	)
	}

	/// Creates a 3D rotation matrix from the given euler rotation sequence and the angles (in
	/// radians).
	#[inline]
	#[must_use]
	pub fn from_euler(order: EulerRot, a: f32, b: f32, c: f32) -> Self {
	let quat = Quat::from_euler(order, a, b, c);
	Self::from_quat(quat)
	}

	/// Creates a 3D rotation matrix from `angle` (in radians) around the x axis.
	#[inline]
	#[must_use]
	pub fn from_rotation_x(angle: f32) -> Self {
	let (sina, cosa) = math::sin_cos(angle);
	Self::from_cols(
	Vec3A::X,
	Vec3A::new(0.0, cosa, sina),
	Vec3A::new(0.0, -sina, cosa),
	)
	}

	/// Creates a 3D rotation matrix from `angle` (in radians) around the y axis.
	#[inline]
	#[must_use]
	pub fn from_rotation_y(angle: f32) -> Self {
	let (sina, cosa) = math::sin_cos(angle);
	Self::from_cols(
	Vec3A::new(cosa, 0.0, -sina),
	Vec3A::Y,
	Vec3A::new(sina, 0.0, cosa),
	)
	}

	/// Creates a 3D rotation matrix from `angle` (in radians) around the z axis.
	#[inline]
	#[must_use]
	pub fn from_rotation_z(angle: f32) -> Self {
	let (sina, cosa) = math::sin_cos(angle);
	Self::from_cols(
	Vec3A::new(cosa, sina, 0.0),
	Vec3A::new(-sina, cosa, 0.0),
	Vec3A::Z,
	)
	}

	/// Creates an affine transformation matrix from the given 2D `translation`.
	///
	/// The resulting matrix can be used to transform 2D points and vectors. See
	/// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
	#[inline]
	#[must_use]
	pub fn from_translation(translation: Vec2) -> Self {
	Self::from_cols(
	Vec3A::X,
	Vec3A::Y,
	Vec3A::new(translation.x, translation.y, 1.0),
	)
	}

	/// Creates an affine transformation matrix from the given 2D rotation `angle` (in
	/// radians).
	///
	/// The resulting matrix can be used to transform 2D points and vectors. See
	/// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
	#[inline]
	#[must_use]
	pub fn from_angle(angle: f32) -> Self {
	let (sin, cos) = math::sin_cos(angle);
	Self::from_cols(
	Vec3A::new(cos, sin, 0.0),
	Vec3A::new(-sin, cos, 0.0),
	Vec3A::Z,
	)
	}

	/// Creates an affine transformation matrix from the given 2D `scale`, rotation `angle` (in
	/// radians) and `translation`.
	///
	/// The resulting matrix can be used to transform 2D points and vectors. See
	/// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
	#[inline]
	#[must_use]
	pub fn from_scale_angle_translation(scale: Vec2, angle: f32, translation: Vec2) -> Self {
	let (sin, cos) = math::sin_cos(angle);
	Self::from_cols(
	Vec3A::new(cos * scale.x, sin * scale.x, 0.0),
	Vec3A::new(-sin * scale.y, cos * scale.y, 0.0),
	Vec3A::new(translation.x, translation.y, 1.0),
	)
	}

	/// Creates an affine transformation matrix from the given non-uniform 2D `scale`.
	///
	/// The resulting matrix can be used to transform 2D points and vectors. See
	/// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
	///
	/// # Panics
	///
	/// Will panic if all elements of `scale` are zero when `glam_assert` is enabled.
	#[inline]
	#[must_use]
	pub fn from_scale(scale: Vec2) -> Self {
	// Do not panic as long as any component is non-zero
	glam_assert!(scale.cmpne(Vec2::ZERO).any());

	Self::from_cols(
	Vec3A::new(scale.x, 0.0, 0.0),
	Vec3A::new(0.0, scale.y, 0.0),
	Vec3A::Z,
	)
	}

	/// Creates an affine transformation matrix from the given 2x2 matrix.
	///
	/// The resulting matrix can be used to transform 2D points and vectors. See
	/// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
	#[inline]
	pub fn from_mat2(m: Mat2) -> Self {
	Self::from_cols((m.x_axis, 0.0).into(), (m.y_axis, 0.0).into(), Vec3A::Z)
	}

	/// Creates a 3x3 matrix from the first 9 values in `slice`.
	///
	/// # Panics
	///
	/// Panics if `slice` is less than 9 elements long.
	#[inline]
	#[must_use]
	pub const fn from_cols_slice(slice: &[f32]) -> Self {
	Self::new(
	slice[0], slice[1], slice[2], slice[3], slice[4], slice[5], slice[6], slice[7],
	slice[8],
	)
	}

	/// Writes the columns of `self` to the first 9 elements in `slice`.
	///
	/// # Panics
	///
	/// Panics if `slice` is less than 9 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.x_axis.z;
	slice[3] = self.y_axis.x;
	slice[4] = self.y_axis.y;
	slice[5] = self.y_axis.z;
	slice[6] = self.z_axis.x;
	slice[7] = self.z_axis.y;
	slice[8] = self.z_axis.z;
	}

	/// Returns the matrix column for the given `index`.
	///
	/// # Panics
	///
	/// Panics if `index` is greater than 2.
	#[inline]
	#[must_use]
	pub fn col(&self, index: usize) -> Vec3A {
	match index {
	0 => self.x_axis,
	1 => self.y_axis,
	2 => self.z_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 2.
	#[inline]
	pub fn col_mut(&mut self, index: usize) -> &mut Vec3A {
	match index {
	0 => &mut self.x_axis,
	1 => &mut self.y_axis,
	2 => &mut self.z_axis,
	_ => panic!("index out of bounds"),
	}
	}

	/// Returns the matrix row for the given `index`.
	///
	/// # Panics
	///
	/// Panics if `index` is greater than 2.
	#[inline]
	#[must_use]
	pub fn row(&self, index: usize) -> Vec3A {
	match index {
	0 => Vec3A::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
	1 => Vec3A::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
	2 => Vec3A::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
	_ => 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]
	#[must_use]
	pub fn is_finite(&self) -> bool {
	self.x_axis.is_finite() && self.y_axis.is_finite() && self.z_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() \|\| self.z_axis.is_nan()
	}

	/// Returns the transpose of `self`.
	#[inline]
	#[must_use]
	pub fn transpose(&self) -> Self {
	unsafe {
	let tmp0 = _mm_shuffle_ps(self.x_axis.0, self.y_axis.0, 0b01_00_01_00);
	let tmp1 = _mm_shuffle_ps(self.x_axis.0, self.y_axis.0, 0b11_10_11_10);

	Self {
	x_axis: Vec3A(_mm_shuffle_ps(tmp0, self.z_axis.0, 0b00_00_10_00)),
	y_axis: Vec3A(_mm_shuffle_ps(tmp0, self.z_axis.0, 0b01_01_11_01)),
	z_axis: Vec3A(_mm_shuffle_ps(tmp1, self.z_axis.0, 0b10_10_10_00)),
	}
	}
	}

	/// Returns the determinant of `self`.
	#[inline]
	#[must_use]
	pub fn determinant(&self) -> f32 {
	self.z_axis.dot(self.x_axis.cross(self.y_axis))
	}

	/// 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.
	#[inline]
	#[must_use]
	pub fn inverse(&self) -> Self {
	let tmp0 = self.y_axis.cross(self.z_axis);
	let tmp1 = self.z_axis.cross(self.x_axis);
	let tmp2 = self.x_axis.cross(self.y_axis);
	let det = self.z_axis.dot(tmp2);
	glam_assert!(det != 0.0);
	let inv_det = Vec3A::splat(det.recip());
	Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose()
	}

	/// Transforms the given 2D vector as a point.
	///
	/// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
	///
	/// This method assumes that `self` contains a valid affine transform.
	///
	/// # Panics
	///
	/// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
	#[inline]
	#[must_use]
	pub fn transform_point2(&self, rhs: Vec2) -> Vec2 {
	glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
	Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
	}

	/// Rotates the given 2D vector.
	///
	/// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
	///
	/// This method assumes that `self` contains a valid affine transform.
	///
	/// # Panics
	///
	/// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
	#[inline]
	#[must_use]
	pub fn transform_vector2(&self, rhs: Vec2) -> Vec2 {
	glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
	Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
	}

	/// Transforms a 3D vector.
	#[inline]
	#[must_use]
	pub fn mul_vec3(&self, rhs: Vec3) -> Vec3 {
	self.mul_vec3a(rhs.into()).into()
	}

	/// Transforms a [`Vec3A`].
	#[inline]
	#[must_use]
	pub fn mul_vec3a(&self, rhs: Vec3A) -> Vec3A {
	let mut res = self.x_axis.mul(rhs.xxx());
	res = res.add(self.y_axis.mul(rhs.yyy()));
	res = res.add(self.z_axis.mul(rhs.zzz()));
	res
	}

	/// Multiplies two 3x3 matrices.
	#[inline]
	#[must_use]
	pub fn mul_mat3(&self, rhs: &Self) -> Self {
	Self::from_cols(
	self.mul(rhs.x_axis),
	self.mul(rhs.y_axis),
	self.mul(rhs.z_axis),
	)
	}

	/// Adds two 3x3 matrices.
	#[inline]
	#[must_use]
	pub fn add_mat3(&self, rhs: &Self) -> Self {
	Self::from_cols(
	self.x_axis.add(rhs.x_axis),
	self.y_axis.add(rhs.y_axis),
	self.z_axis.add(rhs.z_axis),
	)
	}

	/// Subtracts two 3x3 matrices.
	#[inline]
	#[must_use]
	pub fn sub_mat3(&self, rhs: &Self) -> Self {
	Self::from_cols(
	self.x_axis.sub(rhs.x_axis),
	self.y_axis.sub(rhs.y_axis),
	self.z_axis.sub(rhs.z_axis),
	)
	}

	/// Multiplies a 3x3 matrix by a scalar.
	#[inline]
	#[must_use]
	pub fn mul_scalar(&self, rhs: f32) -> Self {
	Self::from_cols(
	self.x_axis.mul(rhs),
	self.y_axis.mul(rhs),
	self.z_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]
	#[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)
	&& self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
	}

	#[inline]
	pub fn as_dmat3(&self) -> DMat3 {
	DMat3::from_cols(
	self.x_axis.as_dvec3(),
	self.y_axis.as_dvec3(),
	self.z_axis.as_dvec3(),
	)
	}
	}

	impl Default for Mat3A {
	#[inline]
	fn default() -> Self {
	Self::IDENTITY
	}
	}

	impl Add<Mat3A> for Mat3A {
	type Output = Self;
	#[inline]
	fn add(self, rhs: Self) -> Self::Output {
	self.add_mat3(&rhs)
	}
	}

	impl AddAssign<Mat3A> for Mat3A {
	#[inline]
	fn add_assign(&mut self, rhs: Self) {
	*self = self.add_mat3(&rhs);
	}
	}

	impl Sub<Mat3A> for Mat3A {
	type Output = Self;
	#[inline]
	fn sub(self, rhs: Self) -> Self::Output {
	self.sub_mat3(&rhs)
	}
	}

	impl SubAssign<Mat3A> for Mat3A {
	#[inline]
	fn sub_assign(&mut self, rhs: Self) {
	*self = self.sub_mat3(&rhs);
	}
	}

	impl Neg for Mat3A {
	type Output = Self;
	#[inline]
	fn neg(self) -> Self::Output {
	Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
	}
	}

	impl Mul<Mat3A> for Mat3A {
	type Output = Self;
	#[inline]
	fn mul(self, rhs: Self) -> Self::Output {
	self.mul_mat3(&rhs)
	}
	}

	impl MulAssign<Mat3A> for Mat3A {
	#[inline]
	fn mul_assign(&mut self, rhs: Self) {
	*self = self.mul_mat3(&rhs);
	}
	}

	impl Mul<Vec3A> for Mat3A {
	type Output = Vec3A;
	#[inline]
	fn mul(self, rhs: Vec3A) -> Self::Output {
	self.mul_vec3a(rhs)
	}
	}

	impl Mul<Mat3A> for f32 {
	type Output = Mat3A;
	#[inline]
	fn mul(self, rhs: Mat3A) -> Self::Output {
	rhs.mul_scalar(self)
	}
	}

	impl Mul<f32> for Mat3A {
	type Output = Self;
	#[inline]
	fn mul(self, rhs: f32) -> Self::Output {
	self.mul_scalar(rhs)
	}
	}

	impl MulAssign<f32> for Mat3A {
	#[inline]
	fn mul_assign(&mut self, rhs: f32) {
	*self = self.mul_scalar(rhs);
	}
	}

	impl Mul<Vec3> for Mat3A {
	type Output = Vec3;
	#[inline]
	fn mul(self, rhs: Vec3) -> Vec3 {
	self.mul_vec3a(rhs.into()).into()
	}
	}

	impl From<Mat3> for Mat3A {
	#[inline]
	fn from(m: Mat3) -> Self {
	Self {
	x_axis: m.x_axis.into(),
	y_axis: m.y_axis.into(),
	z_axis: m.z_axis.into(),
	}
	}
	}

	impl Sum<Self> for Mat3A {
	fn sum<I>(iter: I) -> Self
	where
	I: Iterator<Item = Self>,
	{
	iter.fold(Self::ZERO, Self::add)
	}
	}

	impl<'a> Sum<&'a Self> for Mat3A {
	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 Mat3A {
	fn product<I>(iter: I) -> Self
	where
	I: Iterator<Item = Self>,
	{
	iter.fold(Self::IDENTITY, Self::mul)
	}
	}

	impl<'a> Product<&'a Self> for Mat3A {
	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 Mat3A {
	#[inline]
	fn eq(&self, rhs: &Self) -> bool {
	self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
	}
	}

	#[cfg(not(target_arch = "spirv"))]
	impl fmt::Debug for Mat3A {
	fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
	fmt.debug_struct(stringify!(Mat3A))
	.field("x_axis", &self.x_axis)
	.field("y_axis", &self.y_axis)
	.field("z_axis", &self.z_axis)
	.finish()
	}
	}

	#[cfg(not(target_arch = "spirv"))]
	impl fmt::Display for Mat3A {
	fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
	write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
	}
	}