src/f64/dmat2.rs - platform/external/rust/crates/glam - Gitiles

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

 use crate::{f64::math, swizzles::*, DMat3, DVec2, Mat2};
 #[cfg(not(target_arch = "spirv"))]
 use core::fmt;
 use core::iter::{Product, Sum};
 use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};

 /// Creates a 2x2 matrix from two column vectors.
 #[inline(always)]
 #[must_use]
 pub const fn dmat2(x_axis: DVec2, y_axis: DVec2) -> DMat2 {
     DMat2::from_cols(x_axis, y_axis)
 }

 /// A 2x2 column major matrix.
 #[derive(Clone, Copy)]
 #[cfg_attr(feature = "cuda", repr(align(16)))]
 #[repr(C)]
 pub struct DMat2 {
     pub x_axis: DVec2,
     pub y_axis: DVec2,
 }

 impl DMat2 {
     /// A 2x2 matrix with all elements set to `0.0`.
     pub const ZERO: Self = Self::from_cols(DVec2::ZERO, DVec2::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(DVec2::X, DVec2::Y);

     /// All NAN:s.
     pub const NAN: Self = Self::from_cols(DVec2::NAN, DVec2::NAN);

     #[allow(clippy::too_many_arguments)]
     #[inline(always)]
     #[must_use]
     const fn new(m00: f64, m01: f64, m10: f64, m11: f64) -> Self {
         Self {
             x_axis: DVec2::new(m00, m01),
             y_axis: DVec2::new(m10, m11),
         }
     }

     /// Creates a 2x2 matrix from two column vectors.
     #[inline(always)]
     #[must_use]
     pub const fn from_cols(x_axis: DVec2, y_axis: DVec2) -> Self {
         Self { x_axis, y_axis }
     }

     /// Creates a 2x2 matrix from a `[f64; 4]` 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: &[f64; 4]) -> Self {
         Self::new(m[0], m[1], m[2], m[3])
     }

     /// Creates a `[f64; 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) -> [f64; 4] {
         [self.x_axis.x, self.x_axis.y, self.y_axis.x, self.y_axis.y]
     }

     /// Creates a 2x2 matrix from a `[[f64; 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]
     #[must_use]
     pub const fn from_cols_array_2d(m: &[[f64; 2]; 2]) -> Self {
         Self::from_cols(DVec2::from_array(m[0]), DVec2::from_array(m[1]))
     }

     /// Creates a `[[f64; 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) -> [[f64; 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]
     #[must_use]
     pub const fn from_diagonal(diagonal: DVec2) -> 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]
     #[must_use]
     pub fn from_scale_angle(scale: DVec2, angle: f64) -> Self {
         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: f64) -> Self {
         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: DMat3) -> 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]
     #[must_use]
     pub const fn from_cols_slice(slice: &[f64]) -> 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 [f64]) {
         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]
     #[must_use]
     pub fn col(&self, index: usize) -> DVec2 {
         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 DVec2 {
         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]
     #[must_use]
     pub fn row(&self, index: usize) -> DVec2 {
         match index {
             0 => DVec2::new(self.x_axis.x, self.y_axis.x),
             1 => DVec2::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]
     #[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`.
     #[inline]
     #[must_use]
     pub fn transpose(&self) -> Self {
         Self {
             x_axis: DVec2::new(self.x_axis.x, self.y_axis.x),
             y_axis: DVec2::new(self.x_axis.y, self.y_axis.y),
         }
     }

     /// Returns the determinant of `self`.
     #[inline]
     #[must_use]
     pub fn determinant(&self) -> f64 {
         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.
     #[inline]
     #[must_use]
     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]
     #[must_use]
     pub fn mul_vec2(&self, rhs: DVec2) -> DVec2 {
         #[allow(clippy::suspicious_operation_groupings)]
         DVec2::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]
     #[must_use]
     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]
     #[must_use]
     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]
     #[must_use]
     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]
     #[must_use]
     pub fn mul_scalar(&self, rhs: f64) -> 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]
     #[must_use]
     pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f64) -> 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_mat2(&self) -> Mat2 {
         Mat2::from_cols(self.x_axis.as_vec2(), self.y_axis.as_vec2())
     }
 }

 impl Default for DMat2 {
     #[inline]
     fn default() -> Self {
         Self::IDENTITY
     }
 }

 impl Add<DMat2> for DMat2 {
     type Output = Self;
     #[inline]
     fn add(self, rhs: Self) -> Self::Output {
         self.add_mat2(&rhs)
     }
 }

 impl AddAssign<DMat2> for DMat2 {
     #[inline]
     fn add_assign(&mut self, rhs: Self) {
         *self = self.add_mat2(&rhs);
     }
 }

 impl Sub<DMat2> for DMat2 {
     type Output = Self;
     #[inline]
     fn sub(self, rhs: Self) -> Self::Output {
         self.sub_mat2(&rhs)
     }
 }

 impl SubAssign<DMat2> for DMat2 {
     #[inline]
     fn sub_assign(&mut self, rhs: Self) {
         *self = self.sub_mat2(&rhs);
     }
 }

 impl Neg for DMat2 {
     type Output = Self;
     #[inline]
     fn neg(self) -> Self::Output {
         Self::from_cols(self.x_axis.neg(), self.y_axis.neg())
     }
 }

 impl Mul<DMat2> for DMat2 {
     type Output = Self;
     #[inline]
     fn mul(self, rhs: Self) -> Self::Output {
         self.mul_mat2(&rhs)
     }
 }

 impl MulAssign<DMat2> for DMat2 {
     #[inline]
     fn mul_assign(&mut self, rhs: Self) {
         *self = self.mul_mat2(&rhs);
     }
 }

 impl Mul<DVec2> for DMat2 {
     type Output = DVec2;
     #[inline]
     fn mul(self, rhs: DVec2) -> Self::Output {
         self.mul_vec2(rhs)
     }
 }

 impl Mul<DMat2> for f64 {
     type Output = DMat2;
     #[inline]
     fn mul(self, rhs: DMat2) -> Self::Output {
         rhs.mul_scalar(self)
     }
 }

 impl Mul<f64> for DMat2 {
     type Output = Self;
     #[inline]
     fn mul(self, rhs: f64) -> Self::Output {
         self.mul_scalar(rhs)
     }
 }

 impl MulAssign<f64> for DMat2 {
     #[inline]
     fn mul_assign(&mut self, rhs: f64) {
         *self = self.mul_scalar(rhs);
     }
 }

 impl Sum<Self> for DMat2 {
     fn sum<I>(iter: I) -> Self
     where
         I: Iterator<Item = Self>,
     {
         iter.fold(Self::ZERO, Self::add)
     }
 }

 impl<'a> Sum<&'a Self> for DMat2 {
     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 DMat2 {
     fn product<I>(iter: I) -> Self
     where
         I: Iterator<Item = Self>,
     {
         iter.fold(Self::IDENTITY, Self::mul)
     }
 }

 impl<'a> Product<&'a Self> for DMat2 {
     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 DMat2 {
     #[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<[f64; 4]> for DMat2 {
     #[inline]
     fn as_ref(&self) -> &[f64; 4] {
         unsafe { &*(self as *const Self as *const [f64; 4]) }
     }
 }

 #[cfg(not(target_arch = "spirv"))]
 impl AsMut<[f64; 4]> for DMat2 {
     #[inline]
     fn as_mut(&mut self) -> &mut [f64; 4] {
         unsafe { &mut *(self as *mut Self as *mut [f64; 4]) }
     }
 }

 #[cfg(not(target_arch = "spirv"))]
 impl fmt::Debug for DMat2 {
     fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
         fmt.debug_struct(stringify!(DMat2))
             .field("x_axis", &self.x_axis)
             .field("y_axis", &self.y_axis)
             .finish()
     }
 }

 #[cfg(not(target_arch = "spirv"))]
 impl fmt::Display for DMat2 {
     fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
         write!(f, "[{}, {}]", self.x_axis, self.y_axis)
     }
 }
	// Generated from mat.rs.tera template. Edit the template, not the generated file.

	use crate::{f64::math, swizzles::*, DMat3, DVec2, Mat2};
	#[cfg(not(target_arch = "spirv"))]
	use core::fmt;
	use core::iter::{Product, Sum};
	use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};

	/// Creates a 2x2 matrix from two column vectors.
	#[inline(always)]
	#[must_use]
	pub const fn dmat2(x_axis: DVec2, y_axis: DVec2) -> DMat2 {
	DMat2::from_cols(x_axis, y_axis)
	}

	/// A 2x2 column major matrix.
	#[derive(Clone, Copy)]
	#[cfg_attr(feature = "cuda", repr(align(16)))]
	#[repr(C)]
	pub struct DMat2 {
	pub x_axis: DVec2,
	pub y_axis: DVec2,
	}

	impl DMat2 {
	/// A 2x2 matrix with all elements set to `0.0`.
	pub const ZERO: Self = Self::from_cols(DVec2::ZERO, DVec2::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(DVec2::X, DVec2::Y);

	/// All NAN:s.
	pub const NAN: Self = Self::from_cols(DVec2::NAN, DVec2::NAN);

	#[allow(clippy::too_many_arguments)]
	#[inline(always)]
	#[must_use]
	const fn new(m00: f64, m01: f64, m10: f64, m11: f64) -> Self {
	Self {
	x_axis: DVec2::new(m00, m01),
	y_axis: DVec2::new(m10, m11),
	}
	}

	/// Creates a 2x2 matrix from two column vectors.
	#[inline(always)]
	#[must_use]
	pub const fn from_cols(x_axis: DVec2, y_axis: DVec2) -> Self {
	Self { x_axis, y_axis }
	}

	/// Creates a 2x2 matrix from a `[f64; 4]` 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: &[f64; 4]) -> Self {
	Self::new(m[0], m[1], m[2], m[3])
	}

	/// Creates a `[f64; 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) -> [f64; 4] {
	[self.x_axis.x, self.x_axis.y, self.y_axis.x, self.y_axis.y]
	}

	/// Creates a 2x2 matrix from a `[[f64; 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]
	#[must_use]
	pub const fn from_cols_array_2d(m: &[[f64; 2]; 2]) -> Self {
	Self::from_cols(DVec2::from_array(m[0]), DVec2::from_array(m[1]))
	}

	/// Creates a `[[f64; 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) -> [[f64; 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]
	#[must_use]
	pub const fn from_diagonal(diagonal: DVec2) -> 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]
	#[must_use]
	pub fn from_scale_angle(scale: DVec2, angle: f64) -> Self {
	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: f64) -> Self {
	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: DMat3) -> 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]
	#[must_use]
	pub const fn from_cols_slice(slice: &[f64]) -> 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 [f64]) {
	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]
	#[must_use]
	pub fn col(&self, index: usize) -> DVec2 {
	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 DVec2 {
	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]
	#[must_use]
	pub fn row(&self, index: usize) -> DVec2 {
	match index {
	0 => DVec2::new(self.x_axis.x, self.y_axis.x),
	1 => DVec2::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]
	#[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`.
	#[inline]
	#[must_use]
	pub fn transpose(&self) -> Self {
	Self {
	x_axis: DVec2::new(self.x_axis.x, self.y_axis.x),
	y_axis: DVec2::new(self.x_axis.y, self.y_axis.y),
	}
	}

	/// Returns the determinant of `self`.
	#[inline]
	#[must_use]
	pub fn determinant(&self) -> f64 {
	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.
	#[inline]
	#[must_use]
	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]
	#[must_use]
	pub fn mul_vec2(&self, rhs: DVec2) -> DVec2 {
	#[allow(clippy::suspicious_operation_groupings)]
	DVec2::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]
	#[must_use]
	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]
	#[must_use]
	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]
	#[must_use]
	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]
	#[must_use]
	pub fn mul_scalar(&self, rhs: f64) -> 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]
	#[must_use]
	pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f64) -> 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_mat2(&self) -> Mat2 {
	Mat2::from_cols(self.x_axis.as_vec2(), self.y_axis.as_vec2())
	}
	}

	impl Default for DMat2 {
	#[inline]
	fn default() -> Self {
	Self::IDENTITY
	}
	}

	impl Add<DMat2> for DMat2 {
	type Output = Self;
	#[inline]
	fn add(self, rhs: Self) -> Self::Output {
	self.add_mat2(&rhs)
	}
	}

	impl AddAssign<DMat2> for DMat2 {
	#[inline]
	fn add_assign(&mut self, rhs: Self) {
	*self = self.add_mat2(&rhs);
	}
	}

	impl Sub<DMat2> for DMat2 {
	type Output = Self;
	#[inline]
	fn sub(self, rhs: Self) -> Self::Output {
	self.sub_mat2(&rhs)
	}
	}

	impl SubAssign<DMat2> for DMat2 {
	#[inline]
	fn sub_assign(&mut self, rhs: Self) {
	*self = self.sub_mat2(&rhs);
	}
	}

	impl Neg for DMat2 {
	type Output = Self;
	#[inline]
	fn neg(self) -> Self::Output {
	Self::from_cols(self.x_axis.neg(), self.y_axis.neg())
	}
	}

	impl Mul<DMat2> for DMat2 {
	type Output = Self;
	#[inline]
	fn mul(self, rhs: Self) -> Self::Output {
	self.mul_mat2(&rhs)
	}
	}

	impl MulAssign<DMat2> for DMat2 {
	#[inline]
	fn mul_assign(&mut self, rhs: Self) {
	*self = self.mul_mat2(&rhs);
	}
	}

	impl Mul<DVec2> for DMat2 {
	type Output = DVec2;
	#[inline]
	fn mul(self, rhs: DVec2) -> Self::Output {
	self.mul_vec2(rhs)
	}
	}

	impl Mul<DMat2> for f64 {
	type Output = DMat2;
	#[inline]
	fn mul(self, rhs: DMat2) -> Self::Output {
	rhs.mul_scalar(self)
	}
	}

	impl Mul<f64> for DMat2 {
	type Output = Self;
	#[inline]
	fn mul(self, rhs: f64) -> Self::Output {
	self.mul_scalar(rhs)
	}
	}

	impl MulAssign<f64> for DMat2 {
	#[inline]
	fn mul_assign(&mut self, rhs: f64) {
	*self = self.mul_scalar(rhs);
	}
	}

	impl Sum<Self> for DMat2 {
	fn sum<I>(iter: I) -> Self
	where
	I: Iterator<Item = Self>,
	{
	iter.fold(Self::ZERO, Self::add)
	}
	}

	impl<'a> Sum<&'a Self> for DMat2 {
	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 DMat2 {
	fn product<I>(iter: I) -> Self
	where
	I: Iterator<Item = Self>,
	{
	iter.fold(Self::IDENTITY, Self::mul)
	}
	}

	impl<'a> Product<&'a Self> for DMat2 {
	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 DMat2 {
	#[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<[f64; 4]> for DMat2 {
	#[inline]
	fn as_ref(&self) -> &[f64; 4] {
	unsafe { &(self as const Self as *const [f64; 4]) }
	}
	}

	#[cfg(not(target_arch = "spirv"))]
	impl AsMut<[f64; 4]> for DMat2 {
	#[inline]
	fn as_mut(&mut self) -> &mut [f64; 4] {
	unsafe { &mut (self as mut Self as *mut [f64; 4]) }
	}
	}

	#[cfg(not(target_arch = "spirv"))]
	impl fmt::Debug for DMat2 {
	fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
	fmt.debug_struct(stringify!(DMat2))
	.field("x_axis", &self.x_axis)
	.field("y_axis", &self.y_axis)
	.finish()
	}
	}

	#[cfg(not(target_arch = "spirv"))]
	impl fmt::Display for DMat2 {
	fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
	write!(f, "[{}, {}]", self.x_axis, self.y_axis)
	}
	}