glam/f32/sse2/
mat3a.rs

1// Generated from mat.rs.tera template. Edit the template, not the generated file.
2
3use crate::{
4    euler::{FromEuler, ToEuler},
5    f32::math,
6    swizzles::*,
7    DMat3, EulerRot, Mat2, Mat3, Mat4, Quat, Vec2, Vec3, Vec3A,
8};
9use core::fmt;
10use core::iter::{Product, Sum};
11use core::ops::{Add, AddAssign, Div, DivAssign, Mul, MulAssign, Neg, Sub, SubAssign};
12
13#[cfg(target_arch = "x86")]
14use core::arch::x86::*;
15#[cfg(target_arch = "x86_64")]
16use core::arch::x86_64::*;
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        unsafe {
565            let tmp0 = _mm_shuffle_ps(self.x_axis.0, self.y_axis.0, 0b01_00_01_00);
566            let tmp1 = _mm_shuffle_ps(self.x_axis.0, self.y_axis.0, 0b11_10_11_10);
567
568            Self {
569                x_axis: Vec3A(_mm_shuffle_ps(tmp0, self.z_axis.0, 0b00_00_10_00)),
570                y_axis: Vec3A(_mm_shuffle_ps(tmp0, self.z_axis.0, 0b01_01_11_01)),
571                z_axis: Vec3A(_mm_shuffle_ps(tmp1, self.z_axis.0, 0b10_10_10_00)),
572            }
573        }
574    }
575
576    /// Returns the determinant of `self`.
577    #[inline]
578    #[must_use]
579    pub fn determinant(&self) -> f32 {
580        self.z_axis.dot(self.x_axis.cross(self.y_axis))
581    }
582
583    /// Returns the inverse of `self`.
584    ///
585    /// If the matrix is not invertible the returned matrix will be invalid.
586    ///
587    /// # Panics
588    ///
589    /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
590    #[inline]
591    #[must_use]
592    pub fn inverse(&self) -> Self {
593        let tmp0 = self.y_axis.cross(self.z_axis);
594        let tmp1 = self.z_axis.cross(self.x_axis);
595        let tmp2 = self.x_axis.cross(self.y_axis);
596        let det = self.z_axis.dot(tmp2);
597        glam_assert!(det != 0.0);
598        let inv_det = Vec3A::splat(det.recip());
599        Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose()
600    }
601
602    /// Transforms the given 2D vector as a point.
603    ///
604    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
605    ///
606    /// This method assumes that `self` contains a valid affine transform.
607    ///
608    /// # Panics
609    ///
610    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
611    #[inline]
612    #[must_use]
613    pub fn transform_point2(&self, rhs: Vec2) -> Vec2 {
614        glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
615        Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
616    }
617
618    /// Rotates the given 2D vector.
619    ///
620    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
621    ///
622    /// This method assumes that `self` contains a valid affine transform.
623    ///
624    /// # Panics
625    ///
626    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
627    #[inline]
628    #[must_use]
629    pub fn transform_vector2(&self, rhs: Vec2) -> Vec2 {
630        glam_assert!(self.row(2).abs_diff_eq(Vec3A::Z, 1e-6));
631        Mat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
632    }
633
634    /// Creates a left-handed view matrix using a facing direction and an up direction.
635    ///
636    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=forward`.
637    ///
638    /// # Panics
639    ///
640    /// Will panic if `dir` or `up` are not normalized when `glam_assert` is enabled.
641    #[inline]
642    #[must_use]
643    pub fn look_to_lh(dir: Vec3, up: Vec3) -> Self {
644        Self::look_to_rh(-dir, up)
645    }
646
647    /// Creates a right-handed view matrix using a facing direction and an up direction.
648    ///
649    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=back`.
650    ///
651    /// # Panics
652    ///
653    /// Will panic if `dir` or `up` are not normalized when `glam_assert` is enabled.
654    #[inline]
655    #[must_use]
656    pub fn look_to_rh(dir: Vec3, up: Vec3) -> Self {
657        glam_assert!(dir.is_normalized());
658        glam_assert!(up.is_normalized());
659        let f = dir;
660        let s = f.cross(up).normalize();
661        let u = s.cross(f);
662
663        Self::from_cols(
664            Vec3A::new(s.x, u.x, -f.x),
665            Vec3A::new(s.y, u.y, -f.y),
666            Vec3A::new(s.z, u.z, -f.z),
667        )
668    }
669
670    /// Creates a left-handed view matrix using a camera position, a focal point and an up
671    /// direction.
672    ///
673    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=forward`.
674    ///
675    /// # Panics
676    ///
677    /// Will panic if `up` is not normalized when `glam_assert` is enabled.
678    #[inline]
679    #[must_use]
680    pub fn look_at_lh(eye: Vec3, center: Vec3, up: Vec3) -> Self {
681        Self::look_to_lh(center.sub(eye).normalize(), up)
682    }
683
684    /// Creates a right-handed view matrix using a camera position, a focal point and an up
685    /// direction.
686    ///
687    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=back`.
688    ///
689    /// # Panics
690    ///
691    /// Will panic if `up` is not normalized when `glam_assert` is enabled.
692    #[inline]
693    pub fn look_at_rh(eye: Vec3, center: Vec3, up: Vec3) -> Self {
694        Self::look_to_rh(center.sub(eye).normalize(), up)
695    }
696
697    /// Transforms a 3D vector.
698    #[inline]
699    #[must_use]
700    pub fn mul_vec3(&self, rhs: Vec3) -> Vec3 {
701        self.mul_vec3a(rhs.into()).into()
702    }
703
704    /// Transforms a [`Vec3A`].
705    #[inline]
706    #[must_use]
707    pub fn mul_vec3a(&self, rhs: Vec3A) -> Vec3A {
708        let mut res = self.x_axis.mul(rhs.xxx());
709        res = res.add(self.y_axis.mul(rhs.yyy()));
710        res = res.add(self.z_axis.mul(rhs.zzz()));
711        res
712    }
713
714    /// Multiplies two 3x3 matrices.
715    #[inline]
716    #[must_use]
717    pub fn mul_mat3(&self, rhs: &Self) -> Self {
718        self.mul(rhs)
719    }
720
721    /// Adds two 3x3 matrices.
722    #[inline]
723    #[must_use]
724    pub fn add_mat3(&self, rhs: &Self) -> Self {
725        self.add(rhs)
726    }
727
728    /// Subtracts two 3x3 matrices.
729    #[inline]
730    #[must_use]
731    pub fn sub_mat3(&self, rhs: &Self) -> Self {
732        self.sub(rhs)
733    }
734
735    /// Multiplies a 3x3 matrix by a scalar.
736    #[inline]
737    #[must_use]
738    pub fn mul_scalar(&self, rhs: f32) -> Self {
739        Self::from_cols(
740            self.x_axis.mul(rhs),
741            self.y_axis.mul(rhs),
742            self.z_axis.mul(rhs),
743        )
744    }
745
746    /// Divides a 3x3 matrix by a scalar.
747    #[inline]
748    #[must_use]
749    pub fn div_scalar(&self, rhs: f32) -> Self {
750        let rhs = Vec3A::splat(rhs);
751        Self::from_cols(
752            self.x_axis.div(rhs),
753            self.y_axis.div(rhs),
754            self.z_axis.div(rhs),
755        )
756    }
757
758    /// Returns true if the absolute difference of all elements between `self` and `rhs`
759    /// is less than or equal to `max_abs_diff`.
760    ///
761    /// This can be used to compare if two matrices contain similar elements. It works best
762    /// when comparing with a known value. The `max_abs_diff` that should be used used
763    /// depends on the values being compared against.
764    ///
765    /// For more see
766    /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
767    #[inline]
768    #[must_use]
769    pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f32) -> bool {
770        self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
771            && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
772            && self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
773    }
774
775    /// Takes the absolute value of each element in `self`
776    #[inline]
777    #[must_use]
778    pub fn abs(&self) -> Self {
779        Self::from_cols(self.x_axis.abs(), self.y_axis.abs(), self.z_axis.abs())
780    }
781
782    #[inline]
783    pub fn as_dmat3(&self) -> DMat3 {
784        DMat3::from_cols(
785            self.x_axis.as_dvec3(),
786            self.y_axis.as_dvec3(),
787            self.z_axis.as_dvec3(),
788        )
789    }
790}
791
792impl Default for Mat3A {
793    #[inline]
794    fn default() -> Self {
795        Self::IDENTITY
796    }
797}
798
799impl Add for Mat3A {
800    type Output = Self;
801    #[inline]
802    fn add(self, rhs: Self) -> Self {
803        Self::from_cols(
804            self.x_axis.add(rhs.x_axis),
805            self.y_axis.add(rhs.y_axis),
806            self.z_axis.add(rhs.z_axis),
807        )
808    }
809}
810
811impl Add<&Self> for Mat3A {
812    type Output = Self;
813    #[inline]
814    fn add(self, rhs: &Self) -> Self {
815        self.add(*rhs)
816    }
817}
818
819impl Add<&Mat3A> for &Mat3A {
820    type Output = Mat3A;
821    #[inline]
822    fn add(self, rhs: &Mat3A) -> Mat3A {
823        (*self).add(*rhs)
824    }
825}
826
827impl Add<Mat3A> for &Mat3A {
828    type Output = Mat3A;
829    #[inline]
830    fn add(self, rhs: Mat3A) -> Mat3A {
831        (*self).add(rhs)
832    }
833}
834
835impl AddAssign for Mat3A {
836    #[inline]
837    fn add_assign(&mut self, rhs: Self) {
838        *self = self.add(rhs);
839    }
840}
841
842impl AddAssign<&Self> for Mat3A {
843    #[inline]
844    fn add_assign(&mut self, rhs: &Self) {
845        self.add_assign(*rhs);
846    }
847}
848
849impl Sub for Mat3A {
850    type Output = Self;
851    #[inline]
852    fn sub(self, rhs: Self) -> Self {
853        Self::from_cols(
854            self.x_axis.sub(rhs.x_axis),
855            self.y_axis.sub(rhs.y_axis),
856            self.z_axis.sub(rhs.z_axis),
857        )
858    }
859}
860
861impl Sub<&Self> for Mat3A {
862    type Output = Self;
863    #[inline]
864    fn sub(self, rhs: &Self) -> Self {
865        self.sub(*rhs)
866    }
867}
868
869impl Sub<&Mat3A> for &Mat3A {
870    type Output = Mat3A;
871    #[inline]
872    fn sub(self, rhs: &Mat3A) -> Mat3A {
873        (*self).sub(*rhs)
874    }
875}
876
877impl Sub<Mat3A> for &Mat3A {
878    type Output = Mat3A;
879    #[inline]
880    fn sub(self, rhs: Mat3A) -> Mat3A {
881        (*self).sub(rhs)
882    }
883}
884
885impl SubAssign for Mat3A {
886    #[inline]
887    fn sub_assign(&mut self, rhs: Self) {
888        *self = self.sub(rhs);
889    }
890}
891
892impl SubAssign<&Self> for Mat3A {
893    #[inline]
894    fn sub_assign(&mut self, rhs: &Self) {
895        self.sub_assign(*rhs);
896    }
897}
898
899impl Neg for Mat3A {
900    type Output = Self;
901    #[inline]
902    fn neg(self) -> Self::Output {
903        Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
904    }
905}
906
907impl Neg for &Mat3A {
908    type Output = Mat3A;
909    #[inline]
910    fn neg(self) -> Mat3A {
911        (*self).neg()
912    }
913}
914
915impl Mul for Mat3A {
916    type Output = Self;
917    #[inline]
918    fn mul(self, rhs: Self) -> Self {
919        Self::from_cols(
920            self.mul(rhs.x_axis),
921            self.mul(rhs.y_axis),
922            self.mul(rhs.z_axis),
923        )
924    }
925}
926
927impl Mul<&Self> for Mat3A {
928    type Output = Self;
929    #[inline]
930    fn mul(self, rhs: &Self) -> Self {
931        self.mul(*rhs)
932    }
933}
934
935impl Mul<&Mat3A> for &Mat3A {
936    type Output = Mat3A;
937    #[inline]
938    fn mul(self, rhs: &Mat3A) -> Mat3A {
939        (*self).mul(*rhs)
940    }
941}
942
943impl Mul<Mat3A> for &Mat3A {
944    type Output = Mat3A;
945    #[inline]
946    fn mul(self, rhs: Mat3A) -> Mat3A {
947        (*self).mul(rhs)
948    }
949}
950
951impl MulAssign for Mat3A {
952    #[inline]
953    fn mul_assign(&mut self, rhs: Self) {
954        *self = self.mul(rhs);
955    }
956}
957
958impl MulAssign<&Self> for Mat3A {
959    #[inline]
960    fn mul_assign(&mut self, rhs: &Self) {
961        self.mul_assign(*rhs);
962    }
963}
964
965impl Mul<Vec3A> for Mat3A {
966    type Output = Vec3A;
967    #[inline]
968    fn mul(self, rhs: Vec3A) -> Self::Output {
969        self.mul_vec3a(rhs)
970    }
971}
972
973impl Mul<&Vec3A> for Mat3A {
974    type Output = Vec3A;
975    #[inline]
976    fn mul(self, rhs: &Vec3A) -> Vec3A {
977        self.mul(*rhs)
978    }
979}
980
981impl Mul<&Vec3A> for &Mat3A {
982    type Output = Vec3A;
983    #[inline]
984    fn mul(self, rhs: &Vec3A) -> Vec3A {
985        (*self).mul(*rhs)
986    }
987}
988
989impl Mul<Vec3A> for &Mat3A {
990    type Output = Vec3A;
991    #[inline]
992    fn mul(self, rhs: Vec3A) -> Vec3A {
993        (*self).mul(rhs)
994    }
995}
996
997impl Mul<Mat3A> for f32 {
998    type Output = Mat3A;
999    #[inline]
1000    fn mul(self, rhs: Mat3A) -> Self::Output {
1001        rhs.mul_scalar(self)
1002    }
1003}
1004
1005impl Mul<&Mat3A> for f32 {
1006    type Output = Mat3A;
1007    #[inline]
1008    fn mul(self, rhs: &Mat3A) -> Mat3A {
1009        self.mul(*rhs)
1010    }
1011}
1012
1013impl Mul<&Mat3A> for &f32 {
1014    type Output = Mat3A;
1015    #[inline]
1016    fn mul(self, rhs: &Mat3A) -> Mat3A {
1017        (*self).mul(*rhs)
1018    }
1019}
1020
1021impl Mul<Mat3A> for &f32 {
1022    type Output = Mat3A;
1023    #[inline]
1024    fn mul(self, rhs: Mat3A) -> Mat3A {
1025        (*self).mul(rhs)
1026    }
1027}
1028
1029impl Mul<f32> for Mat3A {
1030    type Output = Self;
1031    #[inline]
1032    fn mul(self, rhs: f32) -> Self {
1033        self.mul_scalar(rhs)
1034    }
1035}
1036
1037impl Mul<&f32> for Mat3A {
1038    type Output = Self;
1039    #[inline]
1040    fn mul(self, rhs: &f32) -> Self {
1041        self.mul(*rhs)
1042    }
1043}
1044
1045impl Mul<&f32> for &Mat3A {
1046    type Output = Mat3A;
1047    #[inline]
1048    fn mul(self, rhs: &f32) -> Mat3A {
1049        (*self).mul(*rhs)
1050    }
1051}
1052
1053impl Mul<f32> for &Mat3A {
1054    type Output = Mat3A;
1055    #[inline]
1056    fn mul(self, rhs: f32) -> Mat3A {
1057        (*self).mul(rhs)
1058    }
1059}
1060
1061impl MulAssign<f32> for Mat3A {
1062    #[inline]
1063    fn mul_assign(&mut self, rhs: f32) {
1064        *self = self.mul(rhs);
1065    }
1066}
1067
1068impl MulAssign<&f32> for Mat3A {
1069    #[inline]
1070    fn mul_assign(&mut self, rhs: &f32) {
1071        self.mul_assign(*rhs);
1072    }
1073}
1074
1075impl Div<Mat3A> for f32 {
1076    type Output = Mat3A;
1077    #[inline]
1078    fn div(self, rhs: Mat3A) -> Self::Output {
1079        rhs.div_scalar(self)
1080    }
1081}
1082
1083impl Div<&Mat3A> for f32 {
1084    type Output = Mat3A;
1085    #[inline]
1086    fn div(self, rhs: &Mat3A) -> Mat3A {
1087        self.div(*rhs)
1088    }
1089}
1090
1091impl Div<&Mat3A> for &f32 {
1092    type Output = Mat3A;
1093    #[inline]
1094    fn div(self, rhs: &Mat3A) -> Mat3A {
1095        (*self).div(*rhs)
1096    }
1097}
1098
1099impl Div<Mat3A> for &f32 {
1100    type Output = Mat3A;
1101    #[inline]
1102    fn div(self, rhs: Mat3A) -> Mat3A {
1103        (*self).div(rhs)
1104    }
1105}
1106
1107impl Div<f32> for Mat3A {
1108    type Output = Self;
1109    #[inline]
1110    fn div(self, rhs: f32) -> Self {
1111        self.div_scalar(rhs)
1112    }
1113}
1114
1115impl Div<&f32> for Mat3A {
1116    type Output = Self;
1117    #[inline]
1118    fn div(self, rhs: &f32) -> Self {
1119        self.div(*rhs)
1120    }
1121}
1122
1123impl Div<&f32> for &Mat3A {
1124    type Output = Mat3A;
1125    #[inline]
1126    fn div(self, rhs: &f32) -> Mat3A {
1127        (*self).div(*rhs)
1128    }
1129}
1130
1131impl Div<f32> for &Mat3A {
1132    type Output = Mat3A;
1133    #[inline]
1134    fn div(self, rhs: f32) -> Mat3A {
1135        (*self).div(rhs)
1136    }
1137}
1138
1139impl DivAssign<f32> for Mat3A {
1140    #[inline]
1141    fn div_assign(&mut self, rhs: f32) {
1142        *self = self.div(rhs);
1143    }
1144}
1145
1146impl DivAssign<&f32> for Mat3A {
1147    #[inline]
1148    fn div_assign(&mut self, rhs: &f32) {
1149        self.div_assign(*rhs);
1150    }
1151}
1152
1153impl Mul<Vec3> for Mat3A {
1154    type Output = Vec3;
1155    #[inline]
1156    fn mul(self, rhs: Vec3) -> Vec3 {
1157        self.mul_vec3a(rhs.into()).into()
1158    }
1159}
1160
1161impl Mul<&Vec3> for Mat3A {
1162    type Output = Vec3;
1163    #[inline]
1164    fn mul(self, rhs: &Vec3) -> Vec3 {
1165        self.mul(*rhs)
1166    }
1167}
1168
1169impl Mul<&Vec3> for &Mat3A {
1170    type Output = Vec3;
1171    #[inline]
1172    fn mul(self, rhs: &Vec3) -> Vec3 {
1173        (*self).mul(*rhs)
1174    }
1175}
1176
1177impl Mul<Vec3> for &Mat3A {
1178    type Output = Vec3;
1179    #[inline]
1180    fn mul(self, rhs: Vec3) -> Vec3 {
1181        (*self).mul(rhs)
1182    }
1183}
1184
1185impl From<Mat3> for Mat3A {
1186    #[inline]
1187    fn from(m: Mat3) -> Self {
1188        Self {
1189            x_axis: m.x_axis.into(),
1190            y_axis: m.y_axis.into(),
1191            z_axis: m.z_axis.into(),
1192        }
1193    }
1194}
1195
1196impl Sum<Self> for Mat3A {
1197    fn sum<I>(iter: I) -> Self
1198    where
1199        I: Iterator<Item = Self>,
1200    {
1201        iter.fold(Self::ZERO, Self::add)
1202    }
1203}
1204
1205impl<'a> Sum<&'a Self> for Mat3A {
1206    fn sum<I>(iter: I) -> Self
1207    where
1208        I: Iterator<Item = &'a Self>,
1209    {
1210        iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
1211    }
1212}
1213
1214impl Product for Mat3A {
1215    fn product<I>(iter: I) -> Self
1216    where
1217        I: Iterator<Item = Self>,
1218    {
1219        iter.fold(Self::IDENTITY, Self::mul)
1220    }
1221}
1222
1223impl<'a> Product<&'a Self> for Mat3A {
1224    fn product<I>(iter: I) -> Self
1225    where
1226        I: Iterator<Item = &'a Self>,
1227    {
1228        iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
1229    }
1230}
1231
1232impl PartialEq for Mat3A {
1233    #[inline]
1234    fn eq(&self, rhs: &Self) -> bool {
1235        self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
1236    }
1237}
1238
1239impl fmt::Debug for Mat3A {
1240    fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
1241        fmt.debug_struct(stringify!(Mat3A))
1242            .field("x_axis", &self.x_axis)
1243            .field("y_axis", &self.y_axis)
1244            .field("z_axis", &self.z_axis)
1245            .finish()
1246    }
1247}
1248
1249impl fmt::Display for Mat3A {
1250    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
1251        if let Some(p) = f.precision() {
1252            write!(
1253                f,
1254                "[{:.*}, {:.*}, {:.*}]",
1255                p, self.x_axis, p, self.y_axis, p, self.z_axis
1256            )
1257        } else {
1258            write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
1259        }
1260    }
1261}