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glam/f32/neon/
mat3a.rs

1// Generated from mat.rs.tera template. Edit the template, not the generated file.
2
3#[cfg(feature = "f64")]
4use crate::DMat3;
5
6use crate::{
7    euler::{FromEuler, ToEuler},
8    f32::math,
9    swizzles::*,
10    EulerRot, Mat2, Mat3, Mat4, Quat, Vec2, Vec3, Vec3A,
11};
12use core::fmt;
13use core::iter::{Product, Sum};
14use core::ops::{Add, AddAssign, Div, DivAssign, Mul, MulAssign, Neg, Sub, SubAssign};
15
16use core::arch::aarch64::*;
17
18#[cfg(feature = "zerocopy")]
19use zerocopy_derive::*;
20
21/// Creates a 3x3 matrix from three column vectors.
22#[inline(always)]
23#[must_use]
24pub const fn mat3a(x_axis: Vec3A, y_axis: Vec3A, z_axis: Vec3A) -> Mat3A {
25    Mat3A::from_cols(x_axis, y_axis, z_axis)
26}
27
28/// A 3x3 column major matrix.
29///
30/// This 3x3 matrix type features convenience methods for creating and using linear and
31/// affine transformations. If you are primarily dealing with 2D affine transformations the
32/// [`Affine2`](crate::Affine2) type is much faster and more space efficient than
33/// using a 3x3 matrix.
34///
35/// Linear transformations including 3D rotation and scale can be created using methods
36/// such as [`Self::from_diagonal()`], [`Self::from_quat()`], [`Self::from_axis_angle()`],
37/// [`Self::from_rotation_x()`], [`Self::from_rotation_y()`], or
38/// [`Self::from_rotation_z()`].
39///
40/// The resulting matrices can be use to transform 3D vectors using regular vector
41/// multiplication.
42///
43/// Affine transformations including 2D translation, rotation and scale can be created
44/// using methods such as [`Self::from_translation()`], [`Self::from_angle()`],
45/// [`Self::from_scale()`] and [`Self::from_scale_angle_translation()`].
46///
47/// The [`Self::transform_point2()`] and [`Self::transform_vector2()`] convenience methods
48/// are provided for performing affine transforms on 2D vectors and points. These multiply
49/// 2D inputs as 3D vectors with an implicit `z` value of `1` for points and `0` for
50/// vectors respectively. These methods assume that `Self` contains a valid affine
51/// transform.
52#[derive(Clone, Copy)]
53#[cfg_attr(feature = "bytemuck", derive(bytemuck::Pod, bytemuck::Zeroable))]
54#[cfg_attr(
55    feature = "zerocopy",
56    derive(FromBytes, Immutable, IntoBytes, KnownLayout)
57)]
58#[repr(C)]
59pub struct Mat3A {
60    pub x_axis: Vec3A,
61    pub y_axis: Vec3A,
62    pub z_axis: Vec3A,
63}
64
65impl Mat3A {
66    /// A 3x3 matrix with all elements set to `0.0`.
67    pub const ZERO: Self = Self::from_cols(Vec3A::ZERO, Vec3A::ZERO, Vec3A::ZERO);
68
69    /// A 3x3 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
70    pub const IDENTITY: Self = Self::from_cols(Vec3A::X, Vec3A::Y, Vec3A::Z);
71
72    /// All NAN:s.
73    pub const NAN: Self = Self::from_cols(Vec3A::NAN, Vec3A::NAN, Vec3A::NAN);
74
75    #[allow(clippy::too_many_arguments)]
76    #[inline(always)]
77    #[must_use]
78    const fn new(
79        m00: f32,
80        m01: f32,
81        m02: f32,
82        m10: f32,
83        m11: f32,
84        m12: f32,
85        m20: f32,
86        m21: f32,
87        m22: f32,
88    ) -> Self {
89        Self {
90            x_axis: Vec3A::new(m00, m01, m02),
91            y_axis: Vec3A::new(m10, m11, m12),
92            z_axis: Vec3A::new(m20, m21, m22),
93        }
94    }
95
96    /// Creates a 3x3 matrix from three column vectors.
97    #[inline(always)]
98    #[must_use]
99    pub const fn from_cols(x_axis: Vec3A, y_axis: Vec3A, z_axis: Vec3A) -> Self {
100        Self {
101            x_axis,
102            y_axis,
103            z_axis,
104        }
105    }
106
107    /// Creates a 3x3 matrix from a `[f32; 9]` array stored in column major order.
108    /// If your data is stored in row major you will need to `transpose` the returned
109    /// matrix.
110    #[inline]
111    #[must_use]
112    pub const fn from_cols_array(m: &[f32; 9]) -> Self {
113        Self::new(m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8])
114    }
115
116    /// Creates a `[f32; 9]` array storing data in column major order.
117    /// If you require data in row major order `transpose` the matrix first.
118    #[inline]
119    #[must_use]
120    pub const fn to_cols_array(&self) -> [f32; 9] {
121        let [x_axis_x, x_axis_y, x_axis_z] = self.x_axis.to_array();
122        let [y_axis_x, y_axis_y, y_axis_z] = self.y_axis.to_array();
123        let [z_axis_x, z_axis_y, z_axis_z] = self.z_axis.to_array();
124
125        [
126            x_axis_x, x_axis_y, x_axis_z, y_axis_x, y_axis_y, y_axis_z, z_axis_x, z_axis_y,
127            z_axis_z,
128        ]
129    }
130
131    /// Creates a 3x3 matrix from a `[[f32; 3]; 3]` 3D array stored in column major order.
132    /// If your data is in row major order you will need to `transpose` the returned
133    /// matrix.
134    #[inline]
135    #[must_use]
136    pub const fn from_cols_array_2d(m: &[[f32; 3]; 3]) -> Self {
137        Self::from_cols(
138            Vec3A::from_array(m[0]),
139            Vec3A::from_array(m[1]),
140            Vec3A::from_array(m[2]),
141        )
142    }
143
144    /// Creates a `[[f32; 3]; 3]` 3D array storing data in column major order.
145    /// If you require data in row major order `transpose` the matrix first.
146    #[inline]
147    #[must_use]
148    pub const fn to_cols_array_2d(&self) -> [[f32; 3]; 3] {
149        [
150            self.x_axis.to_array(),
151            self.y_axis.to_array(),
152            self.z_axis.to_array(),
153        ]
154    }
155
156    /// Creates a 3x3 matrix with its diagonal set to `diagonal` and all other entries set to 0.
157    #[doc(alias = "scale")]
158    #[inline]
159    #[must_use]
160    pub const fn from_diagonal(diagonal: Vec3) -> Self {
161        Self::new(
162            diagonal.x, 0.0, 0.0, 0.0, diagonal.y, 0.0, 0.0, 0.0, diagonal.z,
163        )
164    }
165
166    /// Creates a 3x3 matrix from a 4x4 matrix, discarding the 4th row and column.
167    #[inline]
168    #[must_use]
169    pub fn from_mat4(m: Mat4) -> Self {
170        Self::from_cols(
171            Vec3A::from_vec4(m.x_axis),
172            Vec3A::from_vec4(m.y_axis),
173            Vec3A::from_vec4(m.z_axis),
174        )
175    }
176
177    /// Creates a 3x3 matrix from the minor of the given 4x4 matrix, discarding the `i`th column
178    /// and `j`th row.
179    ///
180    /// # Panics
181    ///
182    /// Panics if `i` or `j` is greater than 3.
183    #[inline]
184    #[must_use]
185    pub fn from_mat4_minor(m: Mat4, i: usize, j: usize) -> Self {
186        match (i, j) {
187            (0, 0) => Self::from_cols(
188                Vec3A::from_vec4(m.y_axis.yzww()),
189                Vec3A::from_vec4(m.z_axis.yzww()),
190                Vec3A::from_vec4(m.w_axis.yzww()),
191            ),
192            (0, 1) => Self::from_cols(
193                Vec3A::from_vec4(m.y_axis.xzww()),
194                Vec3A::from_vec4(m.z_axis.xzww()),
195                Vec3A::from_vec4(m.w_axis.xzww()),
196            ),
197            (0, 2) => Self::from_cols(
198                Vec3A::from_vec4(m.y_axis.xyww()),
199                Vec3A::from_vec4(m.z_axis.xyww()),
200                Vec3A::from_vec4(m.w_axis.xyww()),
201            ),
202            (0, 3) => Self::from_cols(
203                Vec3A::from_vec4(m.y_axis.xyzw()),
204                Vec3A::from_vec4(m.z_axis.xyzw()),
205                Vec3A::from_vec4(m.w_axis.xyzw()),
206            ),
207            (1, 0) => Self::from_cols(
208                Vec3A::from_vec4(m.x_axis.yzww()),
209                Vec3A::from_vec4(m.z_axis.yzww()),
210                Vec3A::from_vec4(m.w_axis.yzww()),
211            ),
212            (1, 1) => Self::from_cols(
213                Vec3A::from_vec4(m.x_axis.xzww()),
214                Vec3A::from_vec4(m.z_axis.xzww()),
215                Vec3A::from_vec4(m.w_axis.xzww()),
216            ),
217            (1, 2) => Self::from_cols(
218                Vec3A::from_vec4(m.x_axis.xyww()),
219                Vec3A::from_vec4(m.z_axis.xyww()),
220                Vec3A::from_vec4(m.w_axis.xyww()),
221            ),
222            (1, 3) => Self::from_cols(
223                Vec3A::from_vec4(m.x_axis.xyzw()),
224                Vec3A::from_vec4(m.z_axis.xyzw()),
225                Vec3A::from_vec4(m.w_axis.xyzw()),
226            ),
227            (2, 0) => Self::from_cols(
228                Vec3A::from_vec4(m.x_axis.yzww()),
229                Vec3A::from_vec4(m.y_axis.yzww()),
230                Vec3A::from_vec4(m.w_axis.yzww()),
231            ),
232            (2, 1) => Self::from_cols(
233                Vec3A::from_vec4(m.x_axis.xzww()),
234                Vec3A::from_vec4(m.y_axis.xzww()),
235                Vec3A::from_vec4(m.w_axis.xzww()),
236            ),
237            (2, 2) => Self::from_cols(
238                Vec3A::from_vec4(m.x_axis.xyww()),
239                Vec3A::from_vec4(m.y_axis.xyww()),
240                Vec3A::from_vec4(m.w_axis.xyww()),
241            ),
242            (2, 3) => Self::from_cols(
243                Vec3A::from_vec4(m.x_axis.xyzw()),
244                Vec3A::from_vec4(m.y_axis.xyzw()),
245                Vec3A::from_vec4(m.w_axis.xyzw()),
246            ),
247            (3, 0) => Self::from_cols(
248                Vec3A::from_vec4(m.x_axis.yzww()),
249                Vec3A::from_vec4(m.y_axis.yzww()),
250                Vec3A::from_vec4(m.z_axis.yzww()),
251            ),
252            (3, 1) => Self::from_cols(
253                Vec3A::from_vec4(m.x_axis.xzww()),
254                Vec3A::from_vec4(m.y_axis.xzww()),
255                Vec3A::from_vec4(m.z_axis.xzww()),
256            ),
257            (3, 2) => Self::from_cols(
258                Vec3A::from_vec4(m.x_axis.xyww()),
259                Vec3A::from_vec4(m.y_axis.xyww()),
260                Vec3A::from_vec4(m.z_axis.xyww()),
261            ),
262            (3, 3) => Self::from_cols(
263                Vec3A::from_vec4(m.x_axis.xyzw()),
264                Vec3A::from_vec4(m.y_axis.xyzw()),
265                Vec3A::from_vec4(m.z_axis.xyzw()),
266            ),
267            _ => panic!("index out of bounds"),
268        }
269    }
270
271    /// Creates a 3D rotation matrix from the given quaternion.
272    ///
273    /// # Panics
274    ///
275    /// Will panic if `rotation` is not normalized when `glam_assert` is enabled.
276    #[inline]
277    #[must_use]
278    pub fn from_quat(rotation: Quat) -> Self {
279        glam_assert!(rotation.is_normalized());
280
281        let x2 = rotation.x + rotation.x;
282        let y2 = rotation.y + rotation.y;
283        let z2 = rotation.z + rotation.z;
284        let xx = rotation.x * x2;
285        let xy = rotation.x * y2;
286        let xz = rotation.x * z2;
287        let yy = rotation.y * y2;
288        let yz = rotation.y * z2;
289        let zz = rotation.z * z2;
290        let wx = rotation.w * x2;
291        let wy = rotation.w * y2;
292        let wz = rotation.w * z2;
293
294        Self::from_cols(
295            Vec3A::new(1.0 - (yy + zz), xy + wz, xz - wy),
296            Vec3A::new(xy - wz, 1.0 - (xx + zz), yz + wx),
297            Vec3A::new(xz + wy, yz - wx, 1.0 - (xx + yy)),
298        )
299    }
300
301    /// Creates a 3D rotation matrix from a normalized rotation `axis` and `angle` (in
302    /// radians).
303    ///
304    /// # Panics
305    ///
306    /// Will panic if `axis` is not normalized when `glam_assert` is enabled.
307    #[inline]
308    #[must_use]
309    pub fn from_axis_angle(axis: Vec3, angle: f32) -> Self {
310        glam_assert!(axis.is_normalized());
311
312        let (sin, cos) = math::sin_cos(angle);
313        let (xsin, ysin, zsin) = axis.mul(sin).into();
314        let (x, y, z) = axis.into();
315        let (x2, y2, z2) = axis.mul(axis).into();
316        let omc = 1.0 - cos;
317        let xyomc = x * y * omc;
318        let xzomc = x * z * omc;
319        let yzomc = y * z * omc;
320        Self::from_cols(
321            Vec3A::new(x2 * omc + cos, xyomc + zsin, xzomc - ysin),
322            Vec3A::new(xyomc - zsin, y2 * omc + cos, yzomc + xsin),
323            Vec3A::new(xzomc + ysin, yzomc - xsin, z2 * omc + cos),
324        )
325    }
326
327    /// Creates a 3D rotation matrix from the given euler rotation sequence and the angles (in
328    /// radians).
329    #[inline]
330    #[must_use]
331    pub fn from_euler(order: EulerRot, a: f32, b: f32, c: f32) -> Self {
332        Self::from_euler_angles(order, a, b, c)
333    }
334
335    /// Extract Euler angles with the given Euler rotation order.
336    ///
337    /// Note if the input matrix contains scales, shears, or other non-rotation transformations then
338    /// the resulting Euler angles will be ill-defined.
339    ///
340    /// # Panics
341    ///
342    /// Will panic if any input matrix column is not normalized when `glam_assert` is enabled.
343    #[inline]
344    #[must_use]
345    pub fn to_euler(&self, order: EulerRot) -> (f32, f32, f32) {
346        glam_assert!(
347            self.x_axis.is_normalized()
348                && self.y_axis.is_normalized()
349                && self.z_axis.is_normalized()
350        );
351        self.to_euler_angles(order)
352    }
353
354    /// Creates a 3D rotation matrix from `angle` (in radians) around the x axis.
355    #[inline]
356    #[must_use]
357    pub fn from_rotation_x(angle: f32) -> Self {
358        let (sina, cosa) = math::sin_cos(angle);
359        Self::from_cols(
360            Vec3A::X,
361            Vec3A::new(0.0, cosa, sina),
362            Vec3A::new(0.0, -sina, cosa),
363        )
364    }
365
366    /// Creates a 3D rotation matrix from `angle` (in radians) around the y axis.
367    #[inline]
368    #[must_use]
369    pub fn from_rotation_y(angle: f32) -> Self {
370        let (sina, cosa) = math::sin_cos(angle);
371        Self::from_cols(
372            Vec3A::new(cosa, 0.0, -sina),
373            Vec3A::Y,
374            Vec3A::new(sina, 0.0, cosa),
375        )
376    }
377
378    /// Creates a 3D rotation matrix from `angle` (in radians) around the z axis.
379    #[inline]
380    #[must_use]
381    pub fn from_rotation_z(angle: f32) -> Self {
382        let (sina, cosa) = math::sin_cos(angle);
383        Self::from_cols(
384            Vec3A::new(cosa, sina, 0.0),
385            Vec3A::new(-sina, cosa, 0.0),
386            Vec3A::Z,
387        )
388    }
389
390    /// Creates an affine transformation matrix from the given 2D `translation`.
391    ///
392    /// The resulting matrix can be used to transform 2D points and vectors. See
393    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
394    #[inline]
395    #[must_use]
396    pub fn from_translation(translation: Vec2) -> Self {
397        Self::from_cols(
398            Vec3A::X,
399            Vec3A::Y,
400            Vec3A::new(translation.x, translation.y, 1.0),
401        )
402    }
403
404    /// Creates an affine transformation matrix from the given 2D rotation `angle` (in
405    /// radians).
406    ///
407    /// The resulting matrix can be used to transform 2D points and vectors. See
408    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
409    #[inline]
410    #[must_use]
411    pub fn from_angle(angle: f32) -> Self {
412        let (sin, cos) = math::sin_cos(angle);
413        Self::from_cols(
414            Vec3A::new(cos, sin, 0.0),
415            Vec3A::new(-sin, cos, 0.0),
416            Vec3A::Z,
417        )
418    }
419
420    /// Creates an affine transformation matrix from the given 2D `scale`, rotation `angle` (in
421    /// radians) and `translation`.
422    ///
423    /// The resulting matrix can be used to transform 2D points and vectors. See
424    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
425    #[inline]
426    #[must_use]
427    pub fn from_scale_angle_translation(scale: Vec2, angle: f32, translation: Vec2) -> Self {
428        let (sin, cos) = math::sin_cos(angle);
429        Self::from_cols(
430            Vec3A::new(cos * scale.x, sin * scale.x, 0.0),
431            Vec3A::new(-sin * scale.y, cos * scale.y, 0.0),
432            Vec3A::new(translation.x, translation.y, 1.0),
433        )
434    }
435
436    /// Creates an affine transformation matrix from the given non-uniform 2D `scale`.
437    ///
438    /// The resulting matrix can be used to transform 2D points and vectors. See
439    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
440    ///
441    /// # Panics
442    ///
443    /// Will panic if all elements of `scale` are zero when `glam_assert` is enabled.
444    #[inline]
445    #[must_use]
446    pub fn from_scale(scale: Vec2) -> Self {
447        // Do not panic as long as any component is non-zero
448        glam_assert!(scale.cmpne(Vec2::ZERO).any());
449
450        Self::from_cols(
451            Vec3A::new(scale.x, 0.0, 0.0),
452            Vec3A::new(0.0, scale.y, 0.0),
453            Vec3A::Z,
454        )
455    }
456
457    /// Creates an affine transformation matrix from the given 2x2 matrix.
458    ///
459    /// The resulting matrix can be used to transform 2D points and vectors. See
460    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
461    #[inline]
462    pub fn from_mat2(m: Mat2) -> Self {
463        Self::from_cols((m.x_axis, 0.0).into(), (m.y_axis, 0.0).into(), Vec3A::Z)
464    }
465
466    /// Creates a 3x3 matrix from the first 9 values in `slice`.
467    ///
468    /// # Panics
469    ///
470    /// Panics if `slice` is less than 9 elements long.
471    #[inline]
472    #[must_use]
473    pub const fn from_cols_slice(slice: &[f32]) -> Self {
474        Self::new(
475            slice[0], slice[1], slice[2], slice[3], slice[4], slice[5], slice[6], slice[7],
476            slice[8],
477        )
478    }
479
480    /// Writes the columns of `self` to the first 9 elements in `slice`.
481    ///
482    /// # Panics
483    ///
484    /// Panics if `slice` is less than 9 elements long.
485    #[inline]
486    pub fn write_cols_to_slice(&self, slice: &mut [f32]) {
487        slice[0] = self.x_axis.x;
488        slice[1] = self.x_axis.y;
489        slice[2] = self.x_axis.z;
490        slice[3] = self.y_axis.x;
491        slice[4] = self.y_axis.y;
492        slice[5] = self.y_axis.z;
493        slice[6] = self.z_axis.x;
494        slice[7] = self.z_axis.y;
495        slice[8] = self.z_axis.z;
496    }
497
498    /// Returns the matrix column for the given `index`.
499    ///
500    /// # Panics
501    ///
502    /// Panics if `index` is greater than 2.
503    #[inline]
504    #[must_use]
505    pub fn col(&self, index: usize) -> Vec3A {
506        match index {
507            0 => self.x_axis,
508            1 => self.y_axis,
509            2 => self.z_axis,
510            _ => panic!("index out of bounds"),
511        }
512    }
513
514    /// Returns a mutable reference to the matrix column for the given `index`.
515    ///
516    /// # Panics
517    ///
518    /// Panics if `index` is greater than 2.
519    #[inline]
520    pub fn col_mut(&mut self, index: usize) -> &mut Vec3A {
521        match index {
522            0 => &mut self.x_axis,
523            1 => &mut self.y_axis,
524            2 => &mut self.z_axis,
525            _ => panic!("index out of bounds"),
526        }
527    }
528
529    /// Returns the matrix row for the given `index`.
530    ///
531    /// # Panics
532    ///
533    /// Panics if `index` is greater than 2.
534    #[inline]
535    #[must_use]
536    pub fn row(&self, index: usize) -> Vec3A {
537        match index {
538            0 => Vec3A::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
539            1 => Vec3A::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
540            2 => Vec3A::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
541            _ => panic!("index out of bounds"),
542        }
543    }
544
545    /// Returns `true` if, and only if, all elements are finite.
546    /// If any element is either `NaN`, positive or negative infinity, this will return `false`.
547    #[inline]
548    #[must_use]
549    pub fn is_finite(&self) -> bool {
550        self.x_axis.is_finite() && self.y_axis.is_finite() && self.z_axis.is_finite()
551    }
552
553    /// Returns `true` if any elements are `NaN`.
554    #[inline]
555    #[must_use]
556    pub fn is_nan(&self) -> bool {
557        self.x_axis.is_nan() || self.y_axis.is_nan() || self.z_axis.is_nan()
558    }
559
560    /// Returns the transpose of `self`.
561    #[inline]
562    #[must_use]
563    pub fn transpose(&self) -> Self {
564        let x = self.x_axis.0;
565        let y = self.y_axis.0;
566        let z = self.z_axis.0;
567        unsafe {
568            let tmp0 = vreinterpretq_f32_u64(vsetq_lane_u64(
569                vgetq_lane_u64(vreinterpretq_u64_f32(y), 0),
570                vreinterpretq_u64_f32(x),
571                1,
572            ));
573            let tmp1 = vreinterpretq_f32_u64(vzip2q_u64(
574                vreinterpretq_u64_f32(x),
575                vreinterpretq_u64_f32(y),
576            ));
577            Mat3A::from_cols(
578                Vec3A::from(vsetq_lane_f32(vgetq_lane_f32(z, 0), vuzp1q_f32(tmp0, z), 3)),
579                Vec3A::from(vuzp2q_f32(tmp0, vdupq_laneq_f32(z, 1))),
580                Vec3A::from(vsetq_lane_f32(vgetq_lane_f32(z, 2), vuzp1q_f32(tmp1, z), 2)),
581            )
582        }
583    }
584
585    /// Returns the diagonal of `self`.
586    #[inline]
587    #[must_use]
588    pub fn diagonal(&self) -> Vec3A {
589        Vec3A::new(self.x_axis.x, self.y_axis.y, self.z_axis.z)
590    }
591
592    /// Returns the determinant of `self`.
593    #[inline]
594    #[must_use]
595    pub fn determinant(&self) -> f32 {
596        self.z_axis.dot(self.x_axis.cross(self.y_axis))
597    }
598
599    /// If `CHECKED` is true then if the determinant is zero this function will return a tuple
600    /// containing a zero matrix and false. If the determinant is non zero a tuple containing the
601    /// inverted matrix and true is returned.
602    ///
603    /// If `CHECKED` is false then the determinant is not checked and if it is zero the resulting
604    /// inverted matrix will be invalid. Will panic if the determinant of `self` is zero when
605    /// `glam_assert` is enabled.
606    ///
607    /// A tuple containing the inverted matrix and a bool is used instead of an option here as
608    /// regular Rust enums put the discriminant first which can result in a lot of padding if the
609    /// matrix is aligned.
610    #[inline(always)]
611    #[must_use]
612    fn inverse_checked<const CHECKED: bool>(&self) -> (Self, bool) {
613        let tmp0 = self.y_axis.cross(self.z_axis);
614        let tmp1 = self.z_axis.cross(self.x_axis);
615        let tmp2 = self.x_axis.cross(self.y_axis);
616        let det = self.z_axis.dot(tmp2);
617        if CHECKED {
618            if det == 0.0 {
619                return (Self::ZERO, false);
620            }
621        } else {
622            glam_assert!(det != 0.0);
623        }
624        let inv_det = Vec3A::splat(det.recip());
625        (
626            Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose(),
627            true,
628        )
629    }
630
631    /// Returns the inverse of `self`.
632    ///
633    /// If the matrix is not invertible the returned matrix will be invalid.
634    ///
635    /// # Panics
636    ///
637    /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
638    #[inline]
639    #[must_use]
640    pub fn inverse(&self) -> Self {
641        self.inverse_checked::<false>().0
642    }
643
644    /// Returns the inverse of `self` or `None` if the matrix is not invertible.
645    #[inline]
646    #[must_use]
647    pub fn try_inverse(&self) -> Option<Self> {
648        let (m, is_valid) = self.inverse_checked::<true>();
649        if is_valid {
650            Some(m)
651        } else {
652            None
653        }
654    }
655
656    /// Returns the inverse of `self` or `Mat3A::ZERO` if the matrix is not invertible.
657    #[inline]
658    #[must_use]
659    pub fn inverse_or_zero(&self) -> Self {
660        self.inverse_checked::<true>().0
661    }
662
663    /// Transforms the given 2D vector as a point.
664    ///
665    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
666    ///
667    /// This method assumes that `self` contains a valid affine transform.
668    ///
669    /// # Panics
670    ///
671    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
672    #[inline]
673    #[must_use]
674    pub fn transform_point2(&self, rhs: Vec2) -> Vec2 {
675        glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
676        Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
677    }
678
679    /// Rotates the given 2D vector.
680    ///
681    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
682    ///
683    /// This method assumes that `self` contains a valid affine transform.
684    ///
685    /// # Panics
686    ///
687    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
688    #[inline]
689    #[must_use]
690    pub fn transform_vector2(&self, rhs: Vec2) -> Vec2 {
691        glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
692        Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
693    }
694
695    /// Creates a left-handed view matrix using a facing direction and an up direction.
696    ///
697    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=forward`.
698    ///
699    /// # Panics
700    ///
701    /// Will panic if `dir` or `up` are not normalized when `glam_assert` is enabled.
702    #[inline]
703    #[must_use]
704    pub fn look_to_lh(dir: Vec3, up: Vec3) -> Self {
705        Self::look_to_rh(-dir, up)
706    }
707
708    /// Creates a right-handed view matrix using a facing direction and an up direction.
709    ///
710    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=back`.
711    ///
712    /// # Panics
713    ///
714    /// Will panic if `dir` or `up` are not normalized when `glam_assert` is enabled.
715    #[inline]
716    #[must_use]
717    pub fn look_to_rh(dir: Vec3, up: Vec3) -> Self {
718        glam_assert!(dir.is_normalized());
719        glam_assert!(up.is_normalized());
720        let f = dir;
721        let s = f.cross(up).normalize();
722        let u = s.cross(f);
723
724        Self::from_cols(
725            Vec3A::new(s.x, u.x, -f.x),
726            Vec3A::new(s.y, u.y, -f.y),
727            Vec3A::new(s.z, u.z, -f.z),
728        )
729    }
730
731    /// Creates a left-handed view matrix using a camera position, a focal point and an up
732    /// direction.
733    ///
734    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=forward`.
735    ///
736    /// # Panics
737    ///
738    /// Will panic if `up` is not normalized when `glam_assert` is enabled.
739    #[inline]
740    #[must_use]
741    pub fn look_at_lh(eye: Vec3, center: Vec3, up: Vec3) -> Self {
742        Self::look_to_lh(center.sub(eye).normalize(), up)
743    }
744
745    /// Creates a right-handed view matrix using a camera position, a focal point and an up
746    /// direction.
747    ///
748    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=back`.
749    ///
750    /// # Panics
751    ///
752    /// Will panic if `up` is not normalized when `glam_assert` is enabled.
753    #[inline]
754    pub fn look_at_rh(eye: Vec3, center: Vec3, up: Vec3) -> Self {
755        Self::look_to_rh(center.sub(eye).normalize(), up)
756    }
757
758    /// Transforms a 3D vector.
759    #[inline]
760    #[must_use]
761    pub fn mul_vec3(&self, rhs: Vec3) -> Vec3 {
762        self.mul_vec3a(rhs.into()).into()
763    }
764
765    /// Transforms a [`Vec3A`].
766    #[inline]
767    #[must_use]
768    pub fn mul_vec3a(&self, rhs: Vec3A) -> Vec3A {
769        let mut res = self.x_axis.mul(rhs.xxx());
770        res = res.add(self.y_axis.mul(rhs.yyy()));
771        res = res.add(self.z_axis.mul(rhs.zzz()));
772        res
773    }
774
775    /// Transforms a 3D vector by the transpose of `self`.
776    #[inline]
777    #[must_use]
778    pub fn mul_transpose_vec3(&self, rhs: Vec3) -> Vec3 {
779        self.mul_transpose_vec3a(rhs.into()).into()
780    }
781
782    /// Transforms a [`Vec3A`] by the transpose of `self`.
783    #[inline]
784    #[must_use]
785    pub fn mul_transpose_vec3a(&self, rhs: Vec3A) -> Vec3A {
786        Vec3A::new(
787            self.x_axis.dot(rhs),
788            self.y_axis.dot(rhs),
789            self.z_axis.dot(rhs),
790        )
791    }
792
793    /// Multiplies two 3x3 matrices.
794    #[inline]
795    #[must_use]
796    pub fn mul_mat3(&self, rhs: &Self) -> Self {
797        self.mul(rhs)
798    }
799
800    /// Adds two 3x3 matrices.
801    #[inline]
802    #[must_use]
803    pub fn add_mat3(&self, rhs: &Self) -> Self {
804        self.add(rhs)
805    }
806
807    /// Subtracts two 3x3 matrices.
808    #[inline]
809    #[must_use]
810    pub fn sub_mat3(&self, rhs: &Self) -> Self {
811        self.sub(rhs)
812    }
813
814    /// Multiplies a 3x3 matrix by a scalar.
815    #[inline]
816    #[must_use]
817    pub fn mul_scalar(&self, rhs: f32) -> Self {
818        Self::from_cols(
819            self.x_axis.mul(rhs),
820            self.y_axis.mul(rhs),
821            self.z_axis.mul(rhs),
822        )
823    }
824
825    /// Multiply `self` by a scaling vector `scale`.
826    /// This is faster than creating a whole diagonal scaling matrix and then multiplying that.
827    /// This operation is commutative.
828    #[inline]
829    #[must_use]
830    pub fn mul_diagonal_scale(&self, scale: Vec3) -> Self {
831        Self::from_cols(
832            self.x_axis * scale.x,
833            self.y_axis * scale.y,
834            self.z_axis * scale.z,
835        )
836    }
837
838    /// Divides a 3x3 matrix by a scalar.
839    #[inline]
840    #[must_use]
841    pub fn div_scalar(&self, rhs: f32) -> Self {
842        let rhs = Vec3A::splat(rhs);
843        Self::from_cols(
844            self.x_axis.div(rhs),
845            self.y_axis.div(rhs),
846            self.z_axis.div(rhs),
847        )
848    }
849
850    /// Returns a matrix containing the reciprocal `1.0/n` of each element of `self`.
851    #[inline]
852    #[must_use]
853    pub fn recip(&self) -> Self {
854        Self::from_cols(
855            self.x_axis.recip(),
856            self.y_axis.recip(),
857            self.z_axis.recip(),
858        )
859    }
860
861    /// Returns true if the absolute difference of all elements between `self` and `rhs`
862    /// is less than or equal to `max_abs_diff`.
863    ///
864    /// This can be used to compare if two matrices contain similar elements. It works best
865    /// when comparing with a known value. The `max_abs_diff` that should be used used
866    /// depends on the values being compared against.
867    ///
868    /// For more see
869    /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
870    #[inline]
871    #[must_use]
872    pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f32) -> bool {
873        self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
874            && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
875            && self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
876    }
877
878    /// Takes the absolute value of each element in `self`
879    #[inline]
880    #[must_use]
881    pub fn abs(&self) -> Self {
882        Self::from_cols(self.x_axis.abs(), self.y_axis.abs(), self.z_axis.abs())
883    }
884
885    #[cfg(feature = "f64")]
886    #[inline]
887    #[must_use]
888    pub fn as_dmat3(&self) -> DMat3 {
889        DMat3::from_cols(
890            self.x_axis.as_dvec3(),
891            self.y_axis.as_dvec3(),
892            self.z_axis.as_dvec3(),
893        )
894    }
895}
896
897impl Default for Mat3A {
898    #[inline]
899    fn default() -> Self {
900        Self::IDENTITY
901    }
902}
903
904impl Add for Mat3A {
905    type Output = Self;
906    #[inline]
907    fn add(self, rhs: Self) -> Self {
908        Self::from_cols(
909            self.x_axis.add(rhs.x_axis),
910            self.y_axis.add(rhs.y_axis),
911            self.z_axis.add(rhs.z_axis),
912        )
913    }
914}
915
916impl Add<&Self> for Mat3A {
917    type Output = Self;
918    #[inline]
919    fn add(self, rhs: &Self) -> Self {
920        self.add(*rhs)
921    }
922}
923
924impl Add<&Mat3A> for &Mat3A {
925    type Output = Mat3A;
926    #[inline]
927    fn add(self, rhs: &Mat3A) -> Mat3A {
928        (*self).add(*rhs)
929    }
930}
931
932impl Add<Mat3A> for &Mat3A {
933    type Output = Mat3A;
934    #[inline]
935    fn add(self, rhs: Mat3A) -> Mat3A {
936        (*self).add(rhs)
937    }
938}
939
940impl AddAssign for Mat3A {
941    #[inline]
942    fn add_assign(&mut self, rhs: Self) {
943        *self = self.add(rhs);
944    }
945}
946
947impl AddAssign<&Self> for Mat3A {
948    #[inline]
949    fn add_assign(&mut self, rhs: &Self) {
950        self.add_assign(*rhs);
951    }
952}
953
954impl Sub for Mat3A {
955    type Output = Self;
956    #[inline]
957    fn sub(self, rhs: Self) -> Self {
958        Self::from_cols(
959            self.x_axis.sub(rhs.x_axis),
960            self.y_axis.sub(rhs.y_axis),
961            self.z_axis.sub(rhs.z_axis),
962        )
963    }
964}
965
966impl Sub<&Self> for Mat3A {
967    type Output = Self;
968    #[inline]
969    fn sub(self, rhs: &Self) -> Self {
970        self.sub(*rhs)
971    }
972}
973
974impl Sub<&Mat3A> for &Mat3A {
975    type Output = Mat3A;
976    #[inline]
977    fn sub(self, rhs: &Mat3A) -> Mat3A {
978        (*self).sub(*rhs)
979    }
980}
981
982impl Sub<Mat3A> for &Mat3A {
983    type Output = Mat3A;
984    #[inline]
985    fn sub(self, rhs: Mat3A) -> Mat3A {
986        (*self).sub(rhs)
987    }
988}
989
990impl SubAssign for Mat3A {
991    #[inline]
992    fn sub_assign(&mut self, rhs: Self) {
993        *self = self.sub(rhs);
994    }
995}
996
997impl SubAssign<&Self> for Mat3A {
998    #[inline]
999    fn sub_assign(&mut self, rhs: &Self) {
1000        self.sub_assign(*rhs);
1001    }
1002}
1003
1004impl Neg for Mat3A {
1005    type Output = Self;
1006    #[inline]
1007    fn neg(self) -> Self::Output {
1008        Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
1009    }
1010}
1011
1012impl Neg for &Mat3A {
1013    type Output = Mat3A;
1014    #[inline]
1015    fn neg(self) -> Mat3A {
1016        (*self).neg()
1017    }
1018}
1019
1020impl Mul for Mat3A {
1021    type Output = Self;
1022    #[inline]
1023    fn mul(self, rhs: Self) -> Self {
1024        Self::from_cols(
1025            self.mul(rhs.x_axis),
1026            self.mul(rhs.y_axis),
1027            self.mul(rhs.z_axis),
1028        )
1029    }
1030}
1031
1032impl Mul<&Self> for Mat3A {
1033    type Output = Self;
1034    #[inline]
1035    fn mul(self, rhs: &Self) -> Self {
1036        self.mul(*rhs)
1037    }
1038}
1039
1040impl Mul<&Mat3A> for &Mat3A {
1041    type Output = Mat3A;
1042    #[inline]
1043    fn mul(self, rhs: &Mat3A) -> Mat3A {
1044        (*self).mul(*rhs)
1045    }
1046}
1047
1048impl Mul<Mat3A> for &Mat3A {
1049    type Output = Mat3A;
1050    #[inline]
1051    fn mul(self, rhs: Mat3A) -> Mat3A {
1052        (*self).mul(rhs)
1053    }
1054}
1055
1056impl MulAssign for Mat3A {
1057    #[inline]
1058    fn mul_assign(&mut self, rhs: Self) {
1059        *self = self.mul(rhs);
1060    }
1061}
1062
1063impl MulAssign<&Self> for Mat3A {
1064    #[inline]
1065    fn mul_assign(&mut self, rhs: &Self) {
1066        self.mul_assign(*rhs);
1067    }
1068}
1069
1070impl Mul<Vec3A> for Mat3A {
1071    type Output = Vec3A;
1072    #[inline]
1073    fn mul(self, rhs: Vec3A) -> Self::Output {
1074        self.mul_vec3a(rhs)
1075    }
1076}
1077
1078impl Mul<&Vec3A> for Mat3A {
1079    type Output = Vec3A;
1080    #[inline]
1081    fn mul(self, rhs: &Vec3A) -> Vec3A {
1082        self.mul(*rhs)
1083    }
1084}
1085
1086impl Mul<&Vec3A> for &Mat3A {
1087    type Output = Vec3A;
1088    #[inline]
1089    fn mul(self, rhs: &Vec3A) -> Vec3A {
1090        (*self).mul(*rhs)
1091    }
1092}
1093
1094impl Mul<Vec3A> for &Mat3A {
1095    type Output = Vec3A;
1096    #[inline]
1097    fn mul(self, rhs: Vec3A) -> Vec3A {
1098        (*self).mul(rhs)
1099    }
1100}
1101
1102impl Mul<Mat3A> for f32 {
1103    type Output = Mat3A;
1104    #[inline]
1105    fn mul(self, rhs: Mat3A) -> Self::Output {
1106        rhs.mul_scalar(self)
1107    }
1108}
1109
1110impl Mul<&Mat3A> for f32 {
1111    type Output = Mat3A;
1112    #[inline]
1113    fn mul(self, rhs: &Mat3A) -> Mat3A {
1114        self.mul(*rhs)
1115    }
1116}
1117
1118impl Mul<&Mat3A> for &f32 {
1119    type Output = Mat3A;
1120    #[inline]
1121    fn mul(self, rhs: &Mat3A) -> Mat3A {
1122        (*self).mul(*rhs)
1123    }
1124}
1125
1126impl Mul<Mat3A> for &f32 {
1127    type Output = Mat3A;
1128    #[inline]
1129    fn mul(self, rhs: Mat3A) -> Mat3A {
1130        (*self).mul(rhs)
1131    }
1132}
1133
1134impl Mul<f32> for Mat3A {
1135    type Output = Self;
1136    #[inline]
1137    fn mul(self, rhs: f32) -> Self {
1138        self.mul_scalar(rhs)
1139    }
1140}
1141
1142impl Mul<&f32> for Mat3A {
1143    type Output = Self;
1144    #[inline]
1145    fn mul(self, rhs: &f32) -> Self {
1146        self.mul(*rhs)
1147    }
1148}
1149
1150impl Mul<&f32> for &Mat3A {
1151    type Output = Mat3A;
1152    #[inline]
1153    fn mul(self, rhs: &f32) -> Mat3A {
1154        (*self).mul(*rhs)
1155    }
1156}
1157
1158impl Mul<f32> for &Mat3A {
1159    type Output = Mat3A;
1160    #[inline]
1161    fn mul(self, rhs: f32) -> Mat3A {
1162        (*self).mul(rhs)
1163    }
1164}
1165
1166impl MulAssign<f32> for Mat3A {
1167    #[inline]
1168    fn mul_assign(&mut self, rhs: f32) {
1169        *self = self.mul(rhs);
1170    }
1171}
1172
1173impl MulAssign<&f32> for Mat3A {
1174    #[inline]
1175    fn mul_assign(&mut self, rhs: &f32) {
1176        self.mul_assign(*rhs);
1177    }
1178}
1179
1180impl Div<Mat3A> for f32 {
1181    type Output = Mat3A;
1182    #[inline]
1183    fn div(self, rhs: Mat3A) -> Self::Output {
1184        Mat3A::from_cols(
1185            self.div(rhs.x_axis),
1186            self.div(rhs.y_axis),
1187            self.div(rhs.z_axis),
1188        )
1189    }
1190}
1191
1192impl Div<&Mat3A> for f32 {
1193    type Output = Mat3A;
1194    #[inline]
1195    fn div(self, rhs: &Mat3A) -> Mat3A {
1196        self.div(*rhs)
1197    }
1198}
1199
1200impl Div<&Mat3A> for &f32 {
1201    type Output = Mat3A;
1202    #[inline]
1203    fn div(self, rhs: &Mat3A) -> Mat3A {
1204        (*self).div(*rhs)
1205    }
1206}
1207
1208impl Div<Mat3A> for &f32 {
1209    type Output = Mat3A;
1210    #[inline]
1211    fn div(self, rhs: Mat3A) -> Mat3A {
1212        (*self).div(rhs)
1213    }
1214}
1215
1216impl Div<f32> for Mat3A {
1217    type Output = Self;
1218    #[inline]
1219    fn div(self, rhs: f32) -> Self {
1220        self.div_scalar(rhs)
1221    }
1222}
1223
1224impl Div<&f32> for Mat3A {
1225    type Output = Self;
1226    #[inline]
1227    fn div(self, rhs: &f32) -> Self {
1228        self.div(*rhs)
1229    }
1230}
1231
1232impl Div<&f32> for &Mat3A {
1233    type Output = Mat3A;
1234    #[inline]
1235    fn div(self, rhs: &f32) -> Mat3A {
1236        (*self).div(*rhs)
1237    }
1238}
1239
1240impl Div<f32> for &Mat3A {
1241    type Output = Mat3A;
1242    #[inline]
1243    fn div(self, rhs: f32) -> Mat3A {
1244        (*self).div(rhs)
1245    }
1246}
1247
1248impl DivAssign<f32> for Mat3A {
1249    #[inline]
1250    fn div_assign(&mut self, rhs: f32) {
1251        *self = self.div(rhs);
1252    }
1253}
1254
1255impl DivAssign<&f32> for Mat3A {
1256    #[inline]
1257    fn div_assign(&mut self, rhs: &f32) {
1258        self.div_assign(*rhs);
1259    }
1260}
1261
1262impl Mul<Vec3> for Mat3A {
1263    type Output = Vec3;
1264    #[inline]
1265    fn mul(self, rhs: Vec3) -> Vec3 {
1266        self.mul_vec3a(rhs.into()).into()
1267    }
1268}
1269
1270impl Mul<&Vec3> for Mat3A {
1271    type Output = Vec3;
1272    #[inline]
1273    fn mul(self, rhs: &Vec3) -> Vec3 {
1274        self.mul(*rhs)
1275    }
1276}
1277
1278impl Mul<&Vec3> for &Mat3A {
1279    type Output = Vec3;
1280    #[inline]
1281    fn mul(self, rhs: &Vec3) -> Vec3 {
1282        (*self).mul(*rhs)
1283    }
1284}
1285
1286impl Mul<Vec3> for &Mat3A {
1287    type Output = Vec3;
1288    #[inline]
1289    fn mul(self, rhs: Vec3) -> Vec3 {
1290        (*self).mul(rhs)
1291    }
1292}
1293
1294impl From<Mat3> for Mat3A {
1295    #[inline]
1296    fn from(m: Mat3) -> Self {
1297        Self {
1298            x_axis: m.x_axis.into(),
1299            y_axis: m.y_axis.into(),
1300            z_axis: m.z_axis.into(),
1301        }
1302    }
1303}
1304
1305impl Sum<Self> for Mat3A {
1306    fn sum<I>(iter: I) -> Self
1307    where
1308        I: Iterator<Item = Self>,
1309    {
1310        iter.fold(Self::ZERO, Self::add)
1311    }
1312}
1313
1314impl<'a> Sum<&'a Self> for Mat3A {
1315    fn sum<I>(iter: I) -> Self
1316    where
1317        I: Iterator<Item = &'a Self>,
1318    {
1319        iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
1320    }
1321}
1322
1323impl Product for Mat3A {
1324    fn product<I>(iter: I) -> Self
1325    where
1326        I: Iterator<Item = Self>,
1327    {
1328        iter.fold(Self::IDENTITY, Self::mul)
1329    }
1330}
1331
1332impl<'a> Product<&'a Self> for Mat3A {
1333    fn product<I>(iter: I) -> Self
1334    where
1335        I: Iterator<Item = &'a Self>,
1336    {
1337        iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
1338    }
1339}
1340
1341impl PartialEq for Mat3A {
1342    #[inline]
1343    fn eq(&self, rhs: &Self) -> bool {
1344        self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
1345    }
1346}
1347
1348impl fmt::Debug for Mat3A {
1349    fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
1350        fmt.debug_struct(stringify!(Mat3A))
1351            .field("x_axis", &self.x_axis)
1352            .field("y_axis", &self.y_axis)
1353            .field("z_axis", &self.z_axis)
1354            .finish()
1355    }
1356}
1357
1358impl fmt::Display for Mat3A {
1359    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
1360        if let Some(p) = f.precision() {
1361            write!(
1362                f,
1363                "[{:.*}, {:.*}, {:.*}]",
1364                p, self.x_axis, p, self.y_axis, p, self.z_axis
1365            )
1366        } else {
1367            write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
1368        }
1369    }
1370}