revier_glam/f32/
mat3.rs

1// Generated from mat.rs.tera template. Edit the template, not the generated file.
2
3use crate::{f32::math, swizzles::*, DMat3, EulerRot, Mat2, Mat3A, Mat4, Quat, Vec2, Vec3, Vec3A};
4#[cfg(not(target_arch = "spirv"))]
5use core::fmt;
6use core::iter::{Product, Sum};
7use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
8
9/// Creates a 3x3 matrix from three column vectors.
10#[inline(always)]
11pub const fn mat3(x_axis: Vec3, y_axis: Vec3, z_axis: Vec3) -> Mat3 {
12    Mat3::from_cols(x_axis, y_axis, z_axis)
13}
14
15/// A 3x3 column major matrix.
16///
17/// This 3x3 matrix type features convenience methods for creating and using linear and
18/// affine transformations. If you are primarily dealing with 2D affine transformations the
19/// [`Affine2`](crate::Affine2) type is much faster and more space efficient than
20/// using a 3x3 matrix.
21///
22/// Linear transformations including 3D rotation and scale can be created using methods
23/// such as [`Self::from_diagonal()`], [`Self::from_quat()`], [`Self::from_axis_angle()`],
24/// [`Self::from_rotation_x()`], [`Self::from_rotation_y()`], or
25/// [`Self::from_rotation_z()`].
26///
27/// The resulting matrices can be use to transform 3D vectors using regular vector
28/// multiplication.
29///
30/// Affine transformations including 2D translation, rotation and scale can be created
31/// using methods such as [`Self::from_translation()`], [`Self::from_angle()`],
32/// [`Self::from_scale()`] and [`Self::from_scale_angle_translation()`].
33///
34/// The [`Self::transform_point2()`] and [`Self::transform_vector2()`] convenience methods
35/// are provided for performing affine transforms on 2D vectors and points. These multiply
36/// 2D inputs as 3D vectors with an implicit `z` value of `1` for points and `0` for
37/// vectors respectively. These methods assume that `Self` contains a valid affine
38/// transform.
39#[derive(Clone, Copy)]
40#[repr(C)]
41pub struct Mat3 {
42    pub x_axis: Vec3,
43    pub y_axis: Vec3,
44    pub z_axis: Vec3,
45}
46
47impl Mat3 {
48    /// A 3x3 matrix with all elements set to `0.0`.
49    pub const ZERO: Self = Self::from_cols(Vec3::ZERO, Vec3::ZERO, Vec3::ZERO);
50
51    /// A 3x3 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
52    pub const IDENTITY: Self = Self::from_cols(Vec3::X, Vec3::Y, Vec3::Z);
53
54    /// All NAN:s.
55    pub const NAN: Self = Self::from_cols(Vec3::NAN, Vec3::NAN, Vec3::NAN);
56
57    #[allow(clippy::too_many_arguments)]
58    #[inline(always)]
59    const fn new(
60        m00: f32,
61        m01: f32,
62        m02: f32,
63        m10: f32,
64        m11: f32,
65        m12: f32,
66        m20: f32,
67        m21: f32,
68        m22: f32,
69    ) -> Self {
70        Self {
71            x_axis: Vec3::new(m00, m01, m02),
72            y_axis: Vec3::new(m10, m11, m12),
73            z_axis: Vec3::new(m20, m21, m22),
74        }
75    }
76
77    /// Creates a 3x3 matrix from three column vectors.
78    #[inline(always)]
79    pub const fn from_cols(x_axis: Vec3, y_axis: Vec3, z_axis: Vec3) -> Self {
80        Self {
81            x_axis,
82            y_axis,
83            z_axis,
84        }
85    }
86
87    /// Creates a 3x3 matrix from a `[f32; 9]` array stored in column major order.
88    /// If your data is stored in row major you will need to `transpose` the returned
89    /// matrix.
90    #[inline]
91    pub const fn from_cols_array(m: &[f32; 9]) -> Self {
92        Self::new(m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8])
93    }
94
95    /// Creates a `[f32; 9]` array storing data in column major order.
96    /// If you require data in row major order `transpose` the matrix first.
97    #[inline]
98    pub const fn to_cols_array(&self) -> [f32; 9] {
99        [
100            self.x_axis.x,
101            self.x_axis.y,
102            self.x_axis.z,
103            self.y_axis.x,
104            self.y_axis.y,
105            self.y_axis.z,
106            self.z_axis.x,
107            self.z_axis.y,
108            self.z_axis.z,
109        ]
110    }
111
112    /// Creates a 3x3 matrix from a `[[f32; 3]; 3]` 3D array stored in column major order.
113    /// If your data is in row major order you will need to `transpose` the returned
114    /// matrix.
115    #[inline]
116    pub const fn from_cols_array_2d(m: &[[f32; 3]; 3]) -> Self {
117        Self::from_cols(
118            Vec3::from_array(m[0]),
119            Vec3::from_array(m[1]),
120            Vec3::from_array(m[2]),
121        )
122    }
123
124    /// Creates a `[[f32; 3]; 3]` 3D array storing data in column major order.
125    /// If you require data in row major order `transpose` the matrix first.
126    #[inline]
127    pub const fn to_cols_array_2d(&self) -> [[f32; 3]; 3] {
128        [
129            self.x_axis.to_array(),
130            self.y_axis.to_array(),
131            self.z_axis.to_array(),
132        ]
133    }
134
135    /// Creates a 3x3 matrix with its diagonal set to `diagonal` and all other entries set to 0.
136    #[doc(alias = "scale")]
137    #[inline]
138    pub const fn from_diagonal(diagonal: Vec3) -> Self {
139        Self::new(
140            diagonal.x, 0.0, 0.0, 0.0, diagonal.y, 0.0, 0.0, 0.0, diagonal.z,
141        )
142    }
143
144    /// Creates a 3x3 matrix from a 4x4 matrix, discarding the 4th row and column.
145    pub fn from_mat4(m: Mat4) -> Self {
146        Self::from_cols(m.x_axis.xyz(), m.y_axis.xyz(), m.z_axis.xyz())
147    }
148
149    /// Creates a 3D rotation matrix from the given quaternion.
150    ///
151    /// # Panics
152    ///
153    /// Will panic if `rotation` is not normalized when `glam_assert` is enabled.
154    #[inline]
155    pub fn from_quat(rotation: Quat) -> Self {
156        glam_assert!(rotation.is_normalized());
157
158        let x2 = rotation.x + rotation.x;
159        let y2 = rotation.y + rotation.y;
160        let z2 = rotation.z + rotation.z;
161        let xx = rotation.x * x2;
162        let xy = rotation.x * y2;
163        let xz = rotation.x * z2;
164        let yy = rotation.y * y2;
165        let yz = rotation.y * z2;
166        let zz = rotation.z * z2;
167        let wx = rotation.w * x2;
168        let wy = rotation.w * y2;
169        let wz = rotation.w * z2;
170
171        Self::from_cols(
172            Vec3::new(1.0 - (yy + zz), xy + wz, xz - wy),
173            Vec3::new(xy - wz, 1.0 - (xx + zz), yz + wx),
174            Vec3::new(xz + wy, yz - wx, 1.0 - (xx + yy)),
175        )
176    }
177
178    /// Creates a 3D rotation matrix from a normalized rotation `axis` and `angle` (in
179    /// radians).
180    ///
181    /// # Panics
182    ///
183    /// Will panic if `axis` is not normalized when `glam_assert` is enabled.
184    #[inline]
185    pub fn from_axis_angle(axis: Vec3, angle: f32) -> Self {
186        glam_assert!(axis.is_normalized());
187
188        let (sin, cos) = math::sin_cos(angle);
189        let (xsin, ysin, zsin) = axis.mul(sin).into();
190        let (x, y, z) = axis.into();
191        let (x2, y2, z2) = axis.mul(axis).into();
192        let omc = 1.0 - cos;
193        let xyomc = x * y * omc;
194        let xzomc = x * z * omc;
195        let yzomc = y * z * omc;
196        Self::from_cols(
197            Vec3::new(x2 * omc + cos, xyomc + zsin, xzomc - ysin),
198            Vec3::new(xyomc - zsin, y2 * omc + cos, yzomc + xsin),
199            Vec3::new(xzomc + ysin, yzomc - xsin, z2 * omc + cos),
200        )
201    }
202
203    #[inline]
204    /// Creates a 3D rotation matrix from the given euler rotation sequence and the angles (in
205    /// radians).
206    pub fn from_euler(order: EulerRot, a: f32, b: f32, c: f32) -> Self {
207        let quat = Quat::from_euler(order, a, b, c);
208        Self::from_quat(quat)
209    }
210
211    /// Creates a 3D rotation matrix from `angle` (in radians) around the x axis.
212    #[inline]
213    pub fn from_rotation_x(angle: f32) -> Self {
214        let (sina, cosa) = math::sin_cos(angle);
215        Self::from_cols(
216            Vec3::X,
217            Vec3::new(0.0, cosa, sina),
218            Vec3::new(0.0, -sina, cosa),
219        )
220    }
221
222    /// Creates a 3D rotation matrix from `angle` (in radians) around the y axis.
223    #[inline]
224    pub fn from_rotation_y(angle: f32) -> Self {
225        let (sina, cosa) = math::sin_cos(angle);
226        Self::from_cols(
227            Vec3::new(cosa, 0.0, -sina),
228            Vec3::Y,
229            Vec3::new(sina, 0.0, cosa),
230        )
231    }
232
233    /// Creates a 3D rotation matrix from `angle` (in radians) around the z axis.
234    #[inline]
235    pub fn from_rotation_z(angle: f32) -> Self {
236        let (sina, cosa) = math::sin_cos(angle);
237        Self::from_cols(
238            Vec3::new(cosa, sina, 0.0),
239            Vec3::new(-sina, cosa, 0.0),
240            Vec3::Z,
241        )
242    }
243
244    /// Creates an affine transformation matrix from the given 2D `translation`.
245    ///
246    /// The resulting matrix can be used to transform 2D points and vectors. See
247    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
248    #[inline]
249    pub fn from_translation(translation: Vec2) -> Self {
250        Self::from_cols(
251            Vec3::X,
252            Vec3::Y,
253            Vec3::new(translation.x, translation.y, 1.0),
254        )
255    }
256
257    /// Creates an affine transformation matrix from the given 2D rotation `angle` (in
258    /// radians).
259    ///
260    /// The resulting matrix can be used to transform 2D points and vectors. See
261    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
262    #[inline]
263    pub fn from_angle(angle: f32) -> Self {
264        let (sin, cos) = math::sin_cos(angle);
265        Self::from_cols(Vec3::new(cos, sin, 0.0), Vec3::new(-sin, cos, 0.0), Vec3::Z)
266    }
267
268    /// Creates an affine transformation matrix from the given 2D `scale`, rotation `angle` (in
269    /// radians) and `translation`.
270    ///
271    /// The resulting matrix can be used to transform 2D points and vectors. See
272    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
273    #[inline]
274    pub fn from_scale_angle_translation(scale: Vec2, angle: f32, translation: Vec2) -> Self {
275        let (sin, cos) = math::sin_cos(angle);
276        Self::from_cols(
277            Vec3::new(cos * scale.x, sin * scale.x, 0.0),
278            Vec3::new(-sin * scale.y, cos * scale.y, 0.0),
279            Vec3::new(translation.x, translation.y, 1.0),
280        )
281    }
282
283    /// Creates an affine transformation matrix from the given non-uniform 2D `scale`.
284    ///
285    /// The resulting matrix can be used to transform 2D points and vectors. See
286    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
287    ///
288    /// # Panics
289    ///
290    /// Will panic if all elements of `scale` are zero when `glam_assert` is enabled.
291    #[inline]
292    pub fn from_scale(scale: Vec2) -> Self {
293        // Do not panic as long as any component is non-zero
294        glam_assert!(scale.cmpne(Vec2::ZERO).any());
295
296        Self::from_cols(
297            Vec3::new(scale.x, 0.0, 0.0),
298            Vec3::new(0.0, scale.y, 0.0),
299            Vec3::Z,
300        )
301    }
302
303    /// Creates an affine transformation matrix from the given 2x2 matrix.
304    ///
305    /// The resulting matrix can be used to transform 2D points and vectors. See
306    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
307    #[inline]
308    pub fn from_mat2(m: Mat2) -> Self {
309        Self::from_cols((m.x_axis, 0.0).into(), (m.y_axis, 0.0).into(), Vec3::Z)
310    }
311
312    /// Creates a 3x3 matrix from the first 9 values in `slice`.
313    ///
314    /// # Panics
315    ///
316    /// Panics if `slice` is less than 9 elements long.
317    #[inline]
318    pub const fn from_cols_slice(slice: &[f32]) -> Self {
319        Self::new(
320            slice[0], slice[1], slice[2], slice[3], slice[4], slice[5], slice[6], slice[7],
321            slice[8],
322        )
323    }
324
325    /// Writes the columns of `self` to the first 9 elements in `slice`.
326    ///
327    /// # Panics
328    ///
329    /// Panics if `slice` is less than 9 elements long.
330    #[inline]
331    pub fn write_cols_to_slice(self, slice: &mut [f32]) {
332        slice[0] = self.x_axis.x;
333        slice[1] = self.x_axis.y;
334        slice[2] = self.x_axis.z;
335        slice[3] = self.y_axis.x;
336        slice[4] = self.y_axis.y;
337        slice[5] = self.y_axis.z;
338        slice[6] = self.z_axis.x;
339        slice[7] = self.z_axis.y;
340        slice[8] = self.z_axis.z;
341    }
342
343    /// Returns the matrix column for the given `index`.
344    ///
345    /// # Panics
346    ///
347    /// Panics if `index` is greater than 2.
348    #[inline]
349    pub fn col(&self, index: usize) -> Vec3 {
350        match index {
351            0 => self.x_axis,
352            1 => self.y_axis,
353            2 => self.z_axis,
354            _ => panic!("index out of bounds"),
355        }
356    }
357
358    /// Returns a mutable reference to the matrix column for the given `index`.
359    ///
360    /// # Panics
361    ///
362    /// Panics if `index` is greater than 2.
363    #[inline]
364    pub fn col_mut(&mut self, index: usize) -> &mut Vec3 {
365        match index {
366            0 => &mut self.x_axis,
367            1 => &mut self.y_axis,
368            2 => &mut self.z_axis,
369            _ => panic!("index out of bounds"),
370        }
371    }
372
373    /// Returns the matrix row for the given `index`.
374    ///
375    /// # Panics
376    ///
377    /// Panics if `index` is greater than 2.
378    #[inline]
379    pub fn row(&self, index: usize) -> Vec3 {
380        match index {
381            0 => Vec3::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
382            1 => Vec3::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
383            2 => Vec3::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
384            _ => panic!("index out of bounds"),
385        }
386    }
387
388    /// Returns `true` if, and only if, all elements are finite.
389    /// If any element is either `NaN`, positive or negative infinity, this will return `false`.
390    #[inline]
391    pub fn is_finite(&self) -> bool {
392        self.x_axis.is_finite() && self.y_axis.is_finite() && self.z_axis.is_finite()
393    }
394
395    /// Returns `true` if any elements are `NaN`.
396    #[inline]
397    pub fn is_nan(&self) -> bool {
398        self.x_axis.is_nan() || self.y_axis.is_nan() || self.z_axis.is_nan()
399    }
400
401    /// Returns the transpose of `self`.
402    #[must_use]
403    #[inline]
404    pub fn transpose(&self) -> Self {
405        Self {
406            x_axis: Vec3::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
407            y_axis: Vec3::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
408            z_axis: Vec3::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
409        }
410    }
411
412    /// Returns the determinant of `self`.
413    #[inline]
414    pub fn determinant(&self) -> f32 {
415        self.z_axis.dot(self.x_axis.cross(self.y_axis))
416    }
417
418    /// Returns the inverse of `self`.
419    ///
420    /// If the matrix is not invertible the returned matrix will be invalid.
421    ///
422    /// # Panics
423    ///
424    /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
425    #[must_use]
426    #[inline]
427    pub fn inverse(&self) -> Self {
428        let tmp0 = self.y_axis.cross(self.z_axis);
429        let tmp1 = self.z_axis.cross(self.x_axis);
430        let tmp2 = self.x_axis.cross(self.y_axis);
431        let det = self.z_axis.dot(tmp2);
432        glam_assert!(det != 0.0);
433        let inv_det = Vec3::splat(det.recip());
434        Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose()
435    }
436
437    /// Transforms the given 2D vector as a point.
438    ///
439    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
440    ///
441    /// This method assumes that `self` contains a valid affine transform.
442    ///
443    /// # Panics
444    ///
445    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
446    #[inline]
447    pub fn transform_point2(&self, rhs: Vec2) -> Vec2 {
448        glam_assert!(self.row(2).abs_diff_eq(Vec3::Z, 1e-6));
449        Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
450    }
451
452    /// Rotates the given 2D vector.
453    ///
454    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
455    ///
456    /// This method assumes that `self` contains a valid affine transform.
457    ///
458    /// # Panics
459    ///
460    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
461    #[inline]
462    pub fn transform_vector2(&self, rhs: Vec2) -> Vec2 {
463        glam_assert!(self.row(2).abs_diff_eq(Vec3::Z, 1e-6));
464        Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
465    }
466
467    /// Transforms a 3D vector.
468    #[inline]
469    pub fn mul_vec3(&self, rhs: Vec3) -> Vec3 {
470        let mut res = self.x_axis.mul(rhs.x);
471        res = res.add(self.y_axis.mul(rhs.y));
472        res = res.add(self.z_axis.mul(rhs.z));
473        res
474    }
475
476    /// Transforms a [`Vec3A`].
477    #[inline]
478    pub fn mul_vec3a(&self, rhs: Vec3A) -> Vec3A {
479        self.mul_vec3(rhs.into()).into()
480    }
481
482    /// Multiplies two 3x3 matrices.
483    #[inline]
484    pub fn mul_mat3(&self, rhs: &Self) -> Self {
485        Self::from_cols(
486            self.mul(rhs.x_axis),
487            self.mul(rhs.y_axis),
488            self.mul(rhs.z_axis),
489        )
490    }
491
492    /// Adds two 3x3 matrices.
493    #[inline]
494    pub fn add_mat3(&self, rhs: &Self) -> Self {
495        Self::from_cols(
496            self.x_axis.add(rhs.x_axis),
497            self.y_axis.add(rhs.y_axis),
498            self.z_axis.add(rhs.z_axis),
499        )
500    }
501
502    /// Subtracts two 3x3 matrices.
503    #[inline]
504    pub fn sub_mat3(&self, rhs: &Self) -> Self {
505        Self::from_cols(
506            self.x_axis.sub(rhs.x_axis),
507            self.y_axis.sub(rhs.y_axis),
508            self.z_axis.sub(rhs.z_axis),
509        )
510    }
511
512    /// Multiplies a 3x3 matrix by a scalar.
513    #[inline]
514    pub fn mul_scalar(&self, rhs: f32) -> Self {
515        Self::from_cols(
516            self.x_axis.mul(rhs),
517            self.y_axis.mul(rhs),
518            self.z_axis.mul(rhs),
519        )
520    }
521
522    /// Returns true if the absolute difference of all elements between `self` and `rhs`
523    /// is less than or equal to `max_abs_diff`.
524    ///
525    /// This can be used to compare if two matrices contain similar elements. It works best
526    /// when comparing with a known value. The `max_abs_diff` that should be used used
527    /// depends on the values being compared against.
528    ///
529    /// For more see
530    /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
531    #[inline]
532    pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f32) -> bool {
533        self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
534            && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
535            && self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
536    }
537
538    #[inline]
539    pub fn as_dmat3(&self) -> DMat3 {
540        DMat3::from_cols(
541            self.x_axis.as_dvec3(),
542            self.y_axis.as_dvec3(),
543            self.z_axis.as_dvec3(),
544        )
545    }
546}
547
548impl Default for Mat3 {
549    #[inline]
550    fn default() -> Self {
551        Self::IDENTITY
552    }
553}
554
555impl Add<Mat3> for Mat3 {
556    type Output = Self;
557    #[inline]
558    fn add(self, rhs: Self) -> Self::Output {
559        self.add_mat3(&rhs)
560    }
561}
562
563impl AddAssign<Mat3> for Mat3 {
564    #[inline]
565    fn add_assign(&mut self, rhs: Self) {
566        *self = self.add_mat3(&rhs);
567    }
568}
569
570impl Sub<Mat3> for Mat3 {
571    type Output = Self;
572    #[inline]
573    fn sub(self, rhs: Self) -> Self::Output {
574        self.sub_mat3(&rhs)
575    }
576}
577
578impl SubAssign<Mat3> for Mat3 {
579    #[inline]
580    fn sub_assign(&mut self, rhs: Self) {
581        *self = self.sub_mat3(&rhs);
582    }
583}
584
585impl Neg for Mat3 {
586    type Output = Self;
587    #[inline]
588    fn neg(self) -> Self::Output {
589        Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
590    }
591}
592
593impl Mul<Mat3> for Mat3 {
594    type Output = Self;
595    #[inline]
596    fn mul(self, rhs: Self) -> Self::Output {
597        self.mul_mat3(&rhs)
598    }
599}
600
601impl MulAssign<Mat3> for Mat3 {
602    #[inline]
603    fn mul_assign(&mut self, rhs: Self) {
604        *self = self.mul_mat3(&rhs);
605    }
606}
607
608impl Mul<Vec3> for Mat3 {
609    type Output = Vec3;
610    #[inline]
611    fn mul(self, rhs: Vec3) -> Self::Output {
612        self.mul_vec3(rhs)
613    }
614}
615
616impl Mul<Mat3> for f32 {
617    type Output = Mat3;
618    #[inline]
619    fn mul(self, rhs: Mat3) -> Self::Output {
620        rhs.mul_scalar(self)
621    }
622}
623
624impl Mul<f32> for Mat3 {
625    type Output = Self;
626    #[inline]
627    fn mul(self, rhs: f32) -> Self::Output {
628        self.mul_scalar(rhs)
629    }
630}
631
632impl MulAssign<f32> for Mat3 {
633    #[inline]
634    fn mul_assign(&mut self, rhs: f32) {
635        *self = self.mul_scalar(rhs);
636    }
637}
638
639impl Mul<Vec3A> for Mat3 {
640    type Output = Vec3A;
641    #[inline]
642    fn mul(self, rhs: Vec3A) -> Vec3A {
643        self.mul_vec3a(rhs)
644    }
645}
646
647impl From<Mat3A> for Mat3 {
648    #[inline]
649    fn from(m: Mat3A) -> Self {
650        Self {
651            x_axis: m.x_axis.into(),
652            y_axis: m.y_axis.into(),
653            z_axis: m.z_axis.into(),
654        }
655    }
656}
657
658impl Sum<Self> for Mat3 {
659    fn sum<I>(iter: I) -> Self
660    where
661        I: Iterator<Item = Self>,
662    {
663        iter.fold(Self::ZERO, Self::add)
664    }
665}
666
667impl<'a> Sum<&'a Self> for Mat3 {
668    fn sum<I>(iter: I) -> Self
669    where
670        I: Iterator<Item = &'a Self>,
671    {
672        iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
673    }
674}
675
676impl Product for Mat3 {
677    fn product<I>(iter: I) -> Self
678    where
679        I: Iterator<Item = Self>,
680    {
681        iter.fold(Self::IDENTITY, Self::mul)
682    }
683}
684
685impl<'a> Product<&'a Self> for Mat3 {
686    fn product<I>(iter: I) -> Self
687    where
688        I: Iterator<Item = &'a Self>,
689    {
690        iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
691    }
692}
693
694impl PartialEq for Mat3 {
695    #[inline]
696    fn eq(&self, rhs: &Self) -> bool {
697        self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
698    }
699}
700
701#[cfg(not(target_arch = "spirv"))]
702impl AsRef<[f32; 9]> for Mat3 {
703    #[inline]
704    fn as_ref(&self) -> &[f32; 9] {
705        unsafe { &*(self as *const Self as *const [f32; 9]) }
706    }
707}
708
709#[cfg(not(target_arch = "spirv"))]
710impl AsMut<[f32; 9]> for Mat3 {
711    #[inline]
712    fn as_mut(&mut self) -> &mut [f32; 9] {
713        unsafe { &mut *(self as *mut Self as *mut [f32; 9]) }
714    }
715}
716
717#[cfg(not(target_arch = "spirv"))]
718impl fmt::Debug for Mat3 {
719    fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
720        fmt.debug_struct(stringify!(Mat3))
721            .field("x_axis", &self.x_axis)
722            .field("y_axis", &self.y_axis)
723            .field("z_axis", &self.z_axis)
724            .finish()
725    }
726}
727
728#[cfg(not(target_arch = "spirv"))]
729impl fmt::Display for Mat3 {
730    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
731        write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
732    }
733}
revier_glam/f32/mat3.rs

revier_glam/f32/
mat3.rs
