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

use crate::{Mat2, Mat3, Mat3A, Vec2, Vec3A};
use core::ops::{Deref, DerefMut, Mul};

/// A 2D affine transform, which can represent translation, rotation, scaling and shear.
#[derive(Copy, Clone)]
#[repr(C)]
pub struct Affine2 {
    pub matrix2: Mat2,
    pub translation: Vec2,
}

impl Affine2 {
    /// The degenerate zero transform.
    ///
    /// This transforms any finite vector and point to zero.
    /// The zero transform is non-invertible.
    pub const ZERO: Self = Self {
        matrix2: Mat2::ZERO,
        translation: Vec2::ZERO,
    };

    /// The identity transform.
    ///
    /// Multiplying a vector with this returns the same vector.
    pub const IDENTITY: Self = Self {
        matrix2: Mat2::IDENTITY,
        translation: Vec2::ZERO,
    };

    /// All NAN:s.
    pub const NAN: Self = Self {
        matrix2: Mat2::NAN,
        translation: Vec2::NAN,
    };

    /// Creates an affine transform from three column vectors.
    #[inline(always)]
    pub const fn from_cols(x_axis: Vec2, y_axis: Vec2, z_axis: Vec2) -> Self {
        Self {
            matrix2: Mat2::from_cols(x_axis, y_axis),
            translation: z_axis,
        }
    }

    /// Creates an affine transform from a `[f32; 6]` array stored in column major order.
    #[inline]
    pub fn from_cols_array(m: &[f32; 6]) -> Self {
        Self {
            matrix2: Mat2::from_cols_slice(&m[0..4]),
            translation: Vec2::from_slice(&m[4..6]),
        }
    }

    /// Creates a `[f32; 6]` array storing data in column major order.
    #[inline]
    pub fn to_cols_array(&self) -> [f32; 6] {
        let x = &self.matrix2.x_axis;
        let y = &self.matrix2.y_axis;
        let z = &self.translation;
        [x.x, x.y, y.x, y.y, z.x, z.y]
    }

    /// Creates an affine transform from a `[[f32; 2]; 3]`
    /// 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 fn from_cols_array_2d(m: &[[f32; 2]; 3]) -> Self {
        Self {
            matrix2: Mat2::from_cols(m[0].into(), m[1].into()),
            translation: m[2].into(),
        }
    }

    /// Creates a `[[f32; 2]; 3]` 2D array storing data in
    /// column major order.
    /// If you require data in row major order `transpose` the matrix first.
    #[inline]
    pub fn to_cols_array_2d(&self) -> [[f32; 2]; 3] {
        [
            self.matrix2.x_axis.into(),
            self.matrix2.y_axis.into(),
            self.translation.into(),
        ]
    }

    /// Creates an affine transform from the first 6 values in `slice`.
    ///
    /// # Panics
    ///
    /// Panics if `slice` is less than 6 elements long.
    #[inline]
    pub fn from_cols_slice(slice: &[f32]) -> Self {
        Self {
            matrix2: Mat2::from_cols_slice(&slice[0..4]),
            translation: Vec2::from_slice(&slice[4..6]),
        }
    }

    /// Writes the columns of `self` to the first 6 elements in `slice`.
    ///
    /// # Panics
    ///
    /// Panics if `slice` is less than 6 elements long.
    #[inline]
    pub fn write_cols_to_slice(self, slice: &mut [f32]) {
        self.matrix2.write_cols_to_slice(&mut slice[0..4]);
        self.translation.write_to_slice(&mut slice[4..6]);
    }

    /// Creates an affine transform that changes scale.
    /// Note that if any scale is zero the transform will be non-invertible.
    #[inline]
    pub fn from_scale(scale: Vec2) -> Self {
        Self {
            matrix2: Mat2::from_diagonal(scale),
            translation: Vec2::ZERO,
        }
    }

    /// Creates an affine transform from the given rotation `angle`.
    #[inline]
    pub fn from_angle(angle: f32) -> Self {
        Self {
            matrix2: Mat2::from_angle(angle),
            translation: Vec2::ZERO,
        }
    }

    /// Creates an affine transformation from the given 2D `translation`.
    #[inline]
    pub fn from_translation(translation: Vec2) -> Self {
        Self {
            matrix2: Mat2::IDENTITY,
            translation,
        }
    }

    /// Creates an affine transform from a 2x2 matrix (expressing scale, shear and rotation)
    #[inline]
    pub fn from_mat2(matrix2: Mat2) -> Self {
        Self {
            matrix2,
            translation: Vec2::ZERO,
        }
    }

    /// Creates an affine transform from a 2x2 matrix (expressing scale, shear and rotation) and a
    /// translation vector.
    ///
    /// Equivalent to
    /// `Affine2::from_translation(translation) * Affine2::from_mat2(mat2)`
    #[inline]
    pub fn from_mat2_translation(matrix2: Mat2, translation: Vec2) -> Self {
        Self {
            matrix2,
            translation,
        }
    }

    /// Creates an affine transform from the given 2D `scale`, rotation `angle` (in radians) and
    /// `translation`.
    ///
    /// Equivalent to `Affine2::from_translation(translation) *
    /// Affine2::from_angle(angle) * Affine2::from_scale(scale)`
    #[inline]
    pub fn from_scale_angle_translation(scale: Vec2, angle: f32, translation: Vec2) -> Self {
        let rotation = Mat2::from_angle(angle);
        Self {
            matrix2: Mat2::from_cols(rotation.x_axis * scale.x, rotation.y_axis * scale.y),
            translation,
        }
    }

    /// Creates an affine transform from the given 2D rotation `angle` (in radians) and
    /// `translation`.
    ///
    /// Equivalent to `Affine2::from_translation(translation) * Affine2::from_angle(angle)`
    #[inline]
    pub fn from_angle_translation(angle: f32, translation: Vec2) -> Self {
        Self {
            matrix2: Mat2::from_angle(angle),
            translation,
        }
    }

    /// The given `Mat3` must be an affine transform,
    #[inline]
    pub fn from_mat3(m: Mat3) -> Self {
        use crate::swizzles::Vec3Swizzles;
        Self {
            matrix2: Mat2::from_cols(m.x_axis.xy(), m.y_axis.xy()),
            translation: m.z_axis.xy(),
        }
    }

    /// The given [`Mat3A`] must be an affine transform,
    #[inline]
    pub fn from_mat3a(m: Mat3A) -> Self {
        use crate::swizzles::Vec3Swizzles;
        Self {
            matrix2: Mat2::from_cols(m.x_axis.xy(), m.y_axis.xy()),
            translation: m.z_axis.xy(),
        }
    }

    /// Transforms the given 2D point, applying shear, scale, rotation and translation.
    #[inline]
    pub fn transform_point2(&self, rhs: Vec2) -> Vec2 {
        self.matrix2 * rhs + self.translation
    }

    /// Transforms the given 2D vector, applying shear, scale and rotation (but NOT
    /// translation).
    ///
    /// To also apply translation, use [`Self::transform_point2()`] instead.
    #[inline]
    pub fn transform_vector2(&self, rhs: Vec2) -> Vec2 {
        self.matrix2 * rhs
    }

    /// 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.matrix2.is_finite() && self.translation.is_finite()
    }

    /// Returns `true` if any elements are `NaN`.
    #[inline]
    pub fn is_nan(&self) -> bool {
        self.matrix2.is_nan() || self.translation.is_nan()
    }

    /// 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 3x4 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.matrix2.abs_diff_eq(rhs.matrix2, max_abs_diff)
            && self.translation.abs_diff_eq(rhs.translation, max_abs_diff)
    }

    /// Return the inverse of this transform.
    ///
    /// Note that if the transform is not invertible the result will be invalid.
    #[must_use]
    #[inline]
    pub fn inverse(&self) -> Self {
        let matrix2 = self.matrix2.inverse();
        // transform negative translation by the matrix inverse:
        let translation = -(matrix2 * self.translation);

        Self {
            matrix2,
            translation,
        }
    }
}

impl Default for Affine2 {
    #[inline(always)]
    fn default() -> Self {
        Self::IDENTITY
    }
}

impl Deref for Affine2 {
    type Target = crate::deref::Cols3<Vec2>;
    #[inline(always)]
    fn deref(&self) -> &Self::Target {
        unsafe { &*(self as *const Self as *const Self::Target) }
    }
}

impl DerefMut for Affine2 {
    #[inline(always)]
    fn deref_mut(&mut self) -> &mut Self::Target {
        unsafe { &mut *(self as *mut Self as *mut Self::Target) }
    }
}

impl PartialEq for Affine2 {
    #[inline]
    fn eq(&self, rhs: &Self) -> bool {
        self.matrix2.eq(&rhs.matrix2) && self.translation.eq(&rhs.translation)
    }
}

#[cfg(not(target_arch = "spirv"))]
impl core::fmt::Debug for Affine2 {
    fn fmt(&self, fmt: &mut core::fmt::Formatter<'_>) -> core::fmt::Result {
        fmt.debug_struct(stringify!(Affine2))
            .field("matrix2", &self.matrix2)
            .field("translation", &self.translation)
            .finish()
    }
}

#[cfg(not(target_arch = "spirv"))]
impl core::fmt::Display for Affine2 {
    fn fmt(&self, f: &mut core::fmt::Formatter<'_>) -> core::fmt::Result {
        write!(
            f,
            "[{}, {}, {}]",
            self.matrix2.x_axis, self.matrix2.y_axis, self.translation
        )
    }
}

impl<'a> core::iter::Product<&'a Self> for Affine2 {
    fn product<I>(iter: I) -> Self
    where
        I: Iterator<Item = &'a Self>,
    {
        iter.fold(Self::IDENTITY, |a, &b| a * b)
    }
}

impl Mul for Affine2 {
    type Output = Affine2;

    #[inline]
    fn mul(self, rhs: Affine2) -> Self::Output {
        Self {
            matrix2: self.matrix2 * rhs.matrix2,
            translation: self.matrix2 * rhs.translation + self.translation,
        }
    }
}

impl From<Affine2> for Mat3 {
    #[inline]
    fn from(m: Affine2) -> Mat3 {
        Self::from_cols(
            m.matrix2.x_axis.extend(0.0),
            m.matrix2.y_axis.extend(0.0),
            m.translation.extend(1.0),
        )
    }
}

impl Mul<Mat3> for Affine2 {
    type Output = Mat3;

    #[inline]
    fn mul(self, rhs: Mat3) -> Self::Output {
        Mat3::from(self) * rhs
    }
}

impl Mul<Affine2> for Mat3 {
    type Output = Mat3;

    #[inline]
    fn mul(self, rhs: Affine2) -> Self::Output {
        self * Mat3::from(rhs)
    }
}

impl From<Affine2> for Mat3A {
    #[inline]
    fn from(m: Affine2) -> Mat3A {
        Self::from_cols(
            Vec3A::from((m.matrix2.x_axis, 0.0)),
            Vec3A::from((m.matrix2.y_axis, 0.0)),
            Vec3A::from((m.translation, 1.0)),
        )
    }
}

impl Mul<Mat3A> for Affine2 {
    type Output = Mat3A;

    #[inline]
    fn mul(self, rhs: Mat3A) -> Self::Output {
        Mat3A::from(self) * rhs
    }
}

impl Mul<Affine2> for Mat3A {
    type Output = Mat3A;

    #[inline]
    fn mul(self, rhs: Affine2) -> Self::Output {
        self * Mat3A::from(rhs)
    }
}