1 // Generated from mat.rs.tera template. Edit the template, not the generated file.
2
3 use crate::{f64::math, swizzles::*, DMat2, DMat4, DQuat, DVec2, DVec3, EulerRot, Mat3};
4 #[cfg(not(target_arch = "spirv"))]
5 use core::fmt;
6 use core::iter::{Product, Sum};
7 use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
8
9 /// Creates a 3x3 matrix from three column vectors.
10 #[inline(always)]
11 #[must_use]
dmat3(x_axis: DVec3, y_axis: DVec3, z_axis: DVec3) -> DMat312 pub const fn dmat3(x_axis: DVec3, y_axis: DVec3, z_axis: DVec3) -> DMat3 {
13 DMat3::from_cols(x_axis, y_axis, z_axis)
14 }
15
16 /// A 3x3 column major matrix.
17 ///
18 /// This 3x3 matrix type features convenience methods for creating and using linear and
19 /// affine transformations. If you are primarily dealing with 2D affine transformations the
20 /// [`DAffine2`](crate::DAffine2) type is much faster and more space efficient than
21 /// using a 3x3 matrix.
22 ///
23 /// Linear transformations including 3D rotation and scale can be created using methods
24 /// such as [`Self::from_diagonal()`], [`Self::from_quat()`], [`Self::from_axis_angle()`],
25 /// [`Self::from_rotation_x()`], [`Self::from_rotation_y()`], or
26 /// [`Self::from_rotation_z()`].
27 ///
28 /// The resulting matrices can be use to transform 3D vectors using regular vector
29 /// multiplication.
30 ///
31 /// Affine transformations including 2D translation, rotation and scale can be created
32 /// using methods such as [`Self::from_translation()`], [`Self::from_angle()`],
33 /// [`Self::from_scale()`] and [`Self::from_scale_angle_translation()`].
34 ///
35 /// The [`Self::transform_point2()`] and [`Self::transform_vector2()`] convenience methods
36 /// are provided for performing affine transforms on 2D vectors and points. These multiply
37 /// 2D inputs as 3D vectors with an implicit `z` value of `1` for points and `0` for
38 /// vectors respectively. These methods assume that `Self` contains a valid affine
39 /// transform.
40 #[derive(Clone, Copy)]
41 #[repr(C)]
42 pub struct DMat3 {
43 pub x_axis: DVec3,
44 pub y_axis: DVec3,
45 pub z_axis: DVec3,
46 }
47
48 impl DMat3 {
49 /// A 3x3 matrix with all elements set to `0.0`.
50 pub const ZERO: Self = Self::from_cols(DVec3::ZERO, DVec3::ZERO, DVec3::ZERO);
51
52 /// A 3x3 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
53 pub const IDENTITY: Self = Self::from_cols(DVec3::X, DVec3::Y, DVec3::Z);
54
55 /// All NAN:s.
56 pub const NAN: Self = Self::from_cols(DVec3::NAN, DVec3::NAN, DVec3::NAN);
57
58 #[allow(clippy::too_many_arguments)]
59 #[inline(always)]
60 #[must_use]
new( m00: f64, m01: f64, m02: f64, m10: f64, m11: f64, m12: f64, m20: f64, m21: f64, m22: f64, ) -> Self61 const fn new(
62 m00: f64,
63 m01: f64,
64 m02: f64,
65 m10: f64,
66 m11: f64,
67 m12: f64,
68 m20: f64,
69 m21: f64,
70 m22: f64,
71 ) -> Self {
72 Self {
73 x_axis: DVec3::new(m00, m01, m02),
74 y_axis: DVec3::new(m10, m11, m12),
75 z_axis: DVec3::new(m20, m21, m22),
76 }
77 }
78
79 /// Creates a 3x3 matrix from three column vectors.
80 #[inline(always)]
81 #[must_use]
from_cols(x_axis: DVec3, y_axis: DVec3, z_axis: DVec3) -> Self82 pub const fn from_cols(x_axis: DVec3, y_axis: DVec3, z_axis: DVec3) -> Self {
83 Self {
84 x_axis,
85 y_axis,
86 z_axis,
87 }
88 }
89
90 /// Creates a 3x3 matrix from a `[f64; 9]` array stored in column major order.
91 /// If your data is stored in row major you will need to `transpose` the returned
92 /// matrix.
93 #[inline]
94 #[must_use]
from_cols_array(m: &[f64; 9]) -> Self95 pub const fn from_cols_array(m: &[f64; 9]) -> Self {
96 Self::new(m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8])
97 }
98
99 /// Creates a `[f64; 9]` array storing data in column major order.
100 /// If you require data in row major order `transpose` the matrix first.
101 #[inline]
102 #[must_use]
to_cols_array(&self) -> [f64; 9]103 pub const fn to_cols_array(&self) -> [f64; 9] {
104 [
105 self.x_axis.x,
106 self.x_axis.y,
107 self.x_axis.z,
108 self.y_axis.x,
109 self.y_axis.y,
110 self.y_axis.z,
111 self.z_axis.x,
112 self.z_axis.y,
113 self.z_axis.z,
114 ]
115 }
116
117 /// Creates a 3x3 matrix from a `[[f64; 3]; 3]` 3D array stored in column major order.
118 /// If your data is in row major order you will need to `transpose` the returned
119 /// matrix.
120 #[inline]
121 #[must_use]
from_cols_array_2d(m: &[[f64; 3]; 3]) -> Self122 pub const fn from_cols_array_2d(m: &[[f64; 3]; 3]) -> Self {
123 Self::from_cols(
124 DVec3::from_array(m[0]),
125 DVec3::from_array(m[1]),
126 DVec3::from_array(m[2]),
127 )
128 }
129
130 /// Creates a `[[f64; 3]; 3]` 3D array storing data in column major order.
131 /// If you require data in row major order `transpose` the matrix first.
132 #[inline]
133 #[must_use]
to_cols_array_2d(&self) -> [[f64; 3]; 3]134 pub const fn to_cols_array_2d(&self) -> [[f64; 3]; 3] {
135 [
136 self.x_axis.to_array(),
137 self.y_axis.to_array(),
138 self.z_axis.to_array(),
139 ]
140 }
141
142 /// Creates a 3x3 matrix with its diagonal set to `diagonal` and all other entries set to 0.
143 #[doc(alias = "scale")]
144 #[inline]
145 #[must_use]
from_diagonal(diagonal: DVec3) -> Self146 pub const fn from_diagonal(diagonal: DVec3) -> Self {
147 Self::new(
148 diagonal.x, 0.0, 0.0, 0.0, diagonal.y, 0.0, 0.0, 0.0, diagonal.z,
149 )
150 }
151
152 /// Creates a 3x3 matrix from a 4x4 matrix, discarding the 4th row and column.
153 #[inline]
154 #[must_use]
from_mat4(m: DMat4) -> Self155 pub fn from_mat4(m: DMat4) -> Self {
156 Self::from_cols(m.x_axis.xyz(), m.y_axis.xyz(), m.z_axis.xyz())
157 }
158
159 /// Creates a 3D rotation matrix from the given quaternion.
160 ///
161 /// # Panics
162 ///
163 /// Will panic if `rotation` is not normalized when `glam_assert` is enabled.
164 #[inline]
165 #[must_use]
from_quat(rotation: DQuat) -> Self166 pub fn from_quat(rotation: DQuat) -> Self {
167 glam_assert!(rotation.is_normalized());
168
169 let x2 = rotation.x + rotation.x;
170 let y2 = rotation.y + rotation.y;
171 let z2 = rotation.z + rotation.z;
172 let xx = rotation.x * x2;
173 let xy = rotation.x * y2;
174 let xz = rotation.x * z2;
175 let yy = rotation.y * y2;
176 let yz = rotation.y * z2;
177 let zz = rotation.z * z2;
178 let wx = rotation.w * x2;
179 let wy = rotation.w * y2;
180 let wz = rotation.w * z2;
181
182 Self::from_cols(
183 DVec3::new(1.0 - (yy + zz), xy + wz, xz - wy),
184 DVec3::new(xy - wz, 1.0 - (xx + zz), yz + wx),
185 DVec3::new(xz + wy, yz - wx, 1.0 - (xx + yy)),
186 )
187 }
188
189 /// Creates a 3D rotation matrix from a normalized rotation `axis` and `angle` (in
190 /// radians).
191 ///
192 /// # Panics
193 ///
194 /// Will panic if `axis` is not normalized when `glam_assert` is enabled.
195 #[inline]
196 #[must_use]
from_axis_angle(axis: DVec3, angle: f64) -> Self197 pub fn from_axis_angle(axis: DVec3, angle: f64) -> Self {
198 glam_assert!(axis.is_normalized());
199
200 let (sin, cos) = math::sin_cos(angle);
201 let (xsin, ysin, zsin) = axis.mul(sin).into();
202 let (x, y, z) = axis.into();
203 let (x2, y2, z2) = axis.mul(axis).into();
204 let omc = 1.0 - cos;
205 let xyomc = x * y * omc;
206 let xzomc = x * z * omc;
207 let yzomc = y * z * omc;
208 Self::from_cols(
209 DVec3::new(x2 * omc + cos, xyomc + zsin, xzomc - ysin),
210 DVec3::new(xyomc - zsin, y2 * omc + cos, yzomc + xsin),
211 DVec3::new(xzomc + ysin, yzomc - xsin, z2 * omc + cos),
212 )
213 }
214
215 /// Creates a 3D rotation matrix from the given euler rotation sequence and the angles (in
216 /// radians).
217 #[inline]
218 #[must_use]
from_euler(order: EulerRot, a: f64, b: f64, c: f64) -> Self219 pub fn from_euler(order: EulerRot, a: f64, b: f64, c: f64) -> Self {
220 let quat = DQuat::from_euler(order, a, b, c);
221 Self::from_quat(quat)
222 }
223
224 /// Creates a 3D rotation matrix from `angle` (in radians) around the x axis.
225 #[inline]
226 #[must_use]
from_rotation_x(angle: f64) -> Self227 pub fn from_rotation_x(angle: f64) -> Self {
228 let (sina, cosa) = math::sin_cos(angle);
229 Self::from_cols(
230 DVec3::X,
231 DVec3::new(0.0, cosa, sina),
232 DVec3::new(0.0, -sina, cosa),
233 )
234 }
235
236 /// Creates a 3D rotation matrix from `angle` (in radians) around the y axis.
237 #[inline]
238 #[must_use]
from_rotation_y(angle: f64) -> Self239 pub fn from_rotation_y(angle: f64) -> Self {
240 let (sina, cosa) = math::sin_cos(angle);
241 Self::from_cols(
242 DVec3::new(cosa, 0.0, -sina),
243 DVec3::Y,
244 DVec3::new(sina, 0.0, cosa),
245 )
246 }
247
248 /// Creates a 3D rotation matrix from `angle` (in radians) around the z axis.
249 #[inline]
250 #[must_use]
from_rotation_z(angle: f64) -> Self251 pub fn from_rotation_z(angle: f64) -> Self {
252 let (sina, cosa) = math::sin_cos(angle);
253 Self::from_cols(
254 DVec3::new(cosa, sina, 0.0),
255 DVec3::new(-sina, cosa, 0.0),
256 DVec3::Z,
257 )
258 }
259
260 /// Creates an affine transformation matrix from the given 2D `translation`.
261 ///
262 /// The resulting matrix can be used to transform 2D points and vectors. See
263 /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
264 #[inline]
265 #[must_use]
from_translation(translation: DVec2) -> Self266 pub fn from_translation(translation: DVec2) -> Self {
267 Self::from_cols(
268 DVec3::X,
269 DVec3::Y,
270 DVec3::new(translation.x, translation.y, 1.0),
271 )
272 }
273
274 /// Creates an affine transformation matrix from the given 2D rotation `angle` (in
275 /// radians).
276 ///
277 /// The resulting matrix can be used to transform 2D points and vectors. See
278 /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
279 #[inline]
280 #[must_use]
from_angle(angle: f64) -> Self281 pub fn from_angle(angle: f64) -> Self {
282 let (sin, cos) = math::sin_cos(angle);
283 Self::from_cols(
284 DVec3::new(cos, sin, 0.0),
285 DVec3::new(-sin, cos, 0.0),
286 DVec3::Z,
287 )
288 }
289
290 /// Creates an affine transformation matrix from the given 2D `scale`, rotation `angle` (in
291 /// radians) and `translation`.
292 ///
293 /// The resulting matrix can be used to transform 2D points and vectors. See
294 /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
295 #[inline]
296 #[must_use]
from_scale_angle_translation(scale: DVec2, angle: f64, translation: DVec2) -> Self297 pub fn from_scale_angle_translation(scale: DVec2, angle: f64, translation: DVec2) -> Self {
298 let (sin, cos) = math::sin_cos(angle);
299 Self::from_cols(
300 DVec3::new(cos * scale.x, sin * scale.x, 0.0),
301 DVec3::new(-sin * scale.y, cos * scale.y, 0.0),
302 DVec3::new(translation.x, translation.y, 1.0),
303 )
304 }
305
306 /// Creates an affine transformation matrix from the given non-uniform 2D `scale`.
307 ///
308 /// The resulting matrix can be used to transform 2D points and vectors. See
309 /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
310 ///
311 /// # Panics
312 ///
313 /// Will panic if all elements of `scale` are zero when `glam_assert` is enabled.
314 #[inline]
315 #[must_use]
from_scale(scale: DVec2) -> Self316 pub fn from_scale(scale: DVec2) -> Self {
317 // Do not panic as long as any component is non-zero
318 glam_assert!(scale.cmpne(DVec2::ZERO).any());
319
320 Self::from_cols(
321 DVec3::new(scale.x, 0.0, 0.0),
322 DVec3::new(0.0, scale.y, 0.0),
323 DVec3::Z,
324 )
325 }
326
327 /// Creates an affine transformation matrix from the given 2x2 matrix.
328 ///
329 /// The resulting matrix can be used to transform 2D points and vectors. See
330 /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
331 #[inline]
from_mat2(m: DMat2) -> Self332 pub fn from_mat2(m: DMat2) -> Self {
333 Self::from_cols((m.x_axis, 0.0).into(), (m.y_axis, 0.0).into(), DVec3::Z)
334 }
335
336 /// Creates a 3x3 matrix from the first 9 values in `slice`.
337 ///
338 /// # Panics
339 ///
340 /// Panics if `slice` is less than 9 elements long.
341 #[inline]
342 #[must_use]
from_cols_slice(slice: &[f64]) -> Self343 pub const fn from_cols_slice(slice: &[f64]) -> Self {
344 Self::new(
345 slice[0], slice[1], slice[2], slice[3], slice[4], slice[5], slice[6], slice[7],
346 slice[8],
347 )
348 }
349
350 /// Writes the columns of `self` to the first 9 elements in `slice`.
351 ///
352 /// # Panics
353 ///
354 /// Panics if `slice` is less than 9 elements long.
355 #[inline]
write_cols_to_slice(self, slice: &mut [f64])356 pub fn write_cols_to_slice(self, slice: &mut [f64]) {
357 slice[0] = self.x_axis.x;
358 slice[1] = self.x_axis.y;
359 slice[2] = self.x_axis.z;
360 slice[3] = self.y_axis.x;
361 slice[4] = self.y_axis.y;
362 slice[5] = self.y_axis.z;
363 slice[6] = self.z_axis.x;
364 slice[7] = self.z_axis.y;
365 slice[8] = self.z_axis.z;
366 }
367
368 /// Returns the matrix column for the given `index`.
369 ///
370 /// # Panics
371 ///
372 /// Panics if `index` is greater than 2.
373 #[inline]
374 #[must_use]
col(&self, index: usize) -> DVec3375 pub fn col(&self, index: usize) -> DVec3 {
376 match index {
377 0 => self.x_axis,
378 1 => self.y_axis,
379 2 => self.z_axis,
380 _ => panic!("index out of bounds"),
381 }
382 }
383
384 /// Returns a mutable reference to the matrix column for the given `index`.
385 ///
386 /// # Panics
387 ///
388 /// Panics if `index` is greater than 2.
389 #[inline]
col_mut(&mut self, index: usize) -> &mut DVec3390 pub fn col_mut(&mut self, index: usize) -> &mut DVec3 {
391 match index {
392 0 => &mut self.x_axis,
393 1 => &mut self.y_axis,
394 2 => &mut self.z_axis,
395 _ => panic!("index out of bounds"),
396 }
397 }
398
399 /// Returns the matrix row for the given `index`.
400 ///
401 /// # Panics
402 ///
403 /// Panics if `index` is greater than 2.
404 #[inline]
405 #[must_use]
row(&self, index: usize) -> DVec3406 pub fn row(&self, index: usize) -> DVec3 {
407 match index {
408 0 => DVec3::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
409 1 => DVec3::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
410 2 => DVec3::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
411 _ => panic!("index out of bounds"),
412 }
413 }
414
415 /// Returns `true` if, and only if, all elements are finite.
416 /// If any element is either `NaN`, positive or negative infinity, this will return `false`.
417 #[inline]
418 #[must_use]
is_finite(&self) -> bool419 pub fn is_finite(&self) -> bool {
420 self.x_axis.is_finite() && self.y_axis.is_finite() && self.z_axis.is_finite()
421 }
422
423 /// Returns `true` if any elements are `NaN`.
424 #[inline]
425 #[must_use]
is_nan(&self) -> bool426 pub fn is_nan(&self) -> bool {
427 self.x_axis.is_nan() || self.y_axis.is_nan() || self.z_axis.is_nan()
428 }
429
430 /// Returns the transpose of `self`.
431 #[inline]
432 #[must_use]
transpose(&self) -> Self433 pub fn transpose(&self) -> Self {
434 Self {
435 x_axis: DVec3::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
436 y_axis: DVec3::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
437 z_axis: DVec3::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
438 }
439 }
440
441 /// Returns the determinant of `self`.
442 #[inline]
443 #[must_use]
determinant(&self) -> f64444 pub fn determinant(&self) -> f64 {
445 self.z_axis.dot(self.x_axis.cross(self.y_axis))
446 }
447
448 /// Returns the inverse of `self`.
449 ///
450 /// If the matrix is not invertible the returned matrix will be invalid.
451 ///
452 /// # Panics
453 ///
454 /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
455 #[inline]
456 #[must_use]
inverse(&self) -> Self457 pub fn inverse(&self) -> Self {
458 let tmp0 = self.y_axis.cross(self.z_axis);
459 let tmp1 = self.z_axis.cross(self.x_axis);
460 let tmp2 = self.x_axis.cross(self.y_axis);
461 let det = self.z_axis.dot(tmp2);
462 glam_assert!(det != 0.0);
463 let inv_det = DVec3::splat(det.recip());
464 Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose()
465 }
466
467 /// Transforms the given 2D vector as a point.
468 ///
469 /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
470 ///
471 /// This method assumes that `self` contains a valid affine transform.
472 ///
473 /// # Panics
474 ///
475 /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
476 #[inline]
477 #[must_use]
transform_point2(&self, rhs: DVec2) -> DVec2478 pub fn transform_point2(&self, rhs: DVec2) -> DVec2 {
479 glam_assert!(self.row(2).abs_diff_eq(DVec3::Z, 1e-6));
480 DMat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
481 }
482
483 /// Rotates the given 2D vector.
484 ///
485 /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
486 ///
487 /// This method assumes that `self` contains a valid affine transform.
488 ///
489 /// # Panics
490 ///
491 /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
492 #[inline]
493 #[must_use]
transform_vector2(&self, rhs: DVec2) -> DVec2494 pub fn transform_vector2(&self, rhs: DVec2) -> DVec2 {
495 glam_assert!(self.row(2).abs_diff_eq(DVec3::Z, 1e-6));
496 DMat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
497 }
498
499 /// Transforms a 3D vector.
500 #[inline]
501 #[must_use]
mul_vec3(&self, rhs: DVec3) -> DVec3502 pub fn mul_vec3(&self, rhs: DVec3) -> DVec3 {
503 let mut res = self.x_axis.mul(rhs.x);
504 res = res.add(self.y_axis.mul(rhs.y));
505 res = res.add(self.z_axis.mul(rhs.z));
506 res
507 }
508
509 /// Multiplies two 3x3 matrices.
510 #[inline]
511 #[must_use]
mul_mat3(&self, rhs: &Self) -> Self512 pub fn mul_mat3(&self, rhs: &Self) -> Self {
513 Self::from_cols(
514 self.mul(rhs.x_axis),
515 self.mul(rhs.y_axis),
516 self.mul(rhs.z_axis),
517 )
518 }
519
520 /// Adds two 3x3 matrices.
521 #[inline]
522 #[must_use]
add_mat3(&self, rhs: &Self) -> Self523 pub fn add_mat3(&self, rhs: &Self) -> Self {
524 Self::from_cols(
525 self.x_axis.add(rhs.x_axis),
526 self.y_axis.add(rhs.y_axis),
527 self.z_axis.add(rhs.z_axis),
528 )
529 }
530
531 /// Subtracts two 3x3 matrices.
532 #[inline]
533 #[must_use]
sub_mat3(&self, rhs: &Self) -> Self534 pub fn sub_mat3(&self, rhs: &Self) -> Self {
535 Self::from_cols(
536 self.x_axis.sub(rhs.x_axis),
537 self.y_axis.sub(rhs.y_axis),
538 self.z_axis.sub(rhs.z_axis),
539 )
540 }
541
542 /// Multiplies a 3x3 matrix by a scalar.
543 #[inline]
544 #[must_use]
mul_scalar(&self, rhs: f64) -> Self545 pub fn mul_scalar(&self, rhs: f64) -> Self {
546 Self::from_cols(
547 self.x_axis.mul(rhs),
548 self.y_axis.mul(rhs),
549 self.z_axis.mul(rhs),
550 )
551 }
552
553 /// Returns true if the absolute difference of all elements between `self` and `rhs`
554 /// is less than or equal to `max_abs_diff`.
555 ///
556 /// This can be used to compare if two matrices contain similar elements. It works best
557 /// when comparing with a known value. The `max_abs_diff` that should be used used
558 /// depends on the values being compared against.
559 ///
560 /// For more see
561 /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
562 #[inline]
563 #[must_use]
abs_diff_eq(&self, rhs: Self, max_abs_diff: f64) -> bool564 pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f64) -> bool {
565 self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
566 && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
567 && self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
568 }
569
570 #[inline]
as_mat3(&self) -> Mat3571 pub fn as_mat3(&self) -> Mat3 {
572 Mat3::from_cols(
573 self.x_axis.as_vec3(),
574 self.y_axis.as_vec3(),
575 self.z_axis.as_vec3(),
576 )
577 }
578 }
579
580 impl Default for DMat3 {
581 #[inline]
default() -> Self582 fn default() -> Self {
583 Self::IDENTITY
584 }
585 }
586
587 impl Add<DMat3> for DMat3 {
588 type Output = Self;
589 #[inline]
add(self, rhs: Self) -> Self::Output590 fn add(self, rhs: Self) -> Self::Output {
591 self.add_mat3(&rhs)
592 }
593 }
594
595 impl AddAssign<DMat3> for DMat3 {
596 #[inline]
add_assign(&mut self, rhs: Self)597 fn add_assign(&mut self, rhs: Self) {
598 *self = self.add_mat3(&rhs);
599 }
600 }
601
602 impl Sub<DMat3> for DMat3 {
603 type Output = Self;
604 #[inline]
sub(self, rhs: Self) -> Self::Output605 fn sub(self, rhs: Self) -> Self::Output {
606 self.sub_mat3(&rhs)
607 }
608 }
609
610 impl SubAssign<DMat3> for DMat3 {
611 #[inline]
sub_assign(&mut self, rhs: Self)612 fn sub_assign(&mut self, rhs: Self) {
613 *self = self.sub_mat3(&rhs);
614 }
615 }
616
617 impl Neg for DMat3 {
618 type Output = Self;
619 #[inline]
neg(self) -> Self::Output620 fn neg(self) -> Self::Output {
621 Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
622 }
623 }
624
625 impl Mul<DMat3> for DMat3 {
626 type Output = Self;
627 #[inline]
mul(self, rhs: Self) -> Self::Output628 fn mul(self, rhs: Self) -> Self::Output {
629 self.mul_mat3(&rhs)
630 }
631 }
632
633 impl MulAssign<DMat3> for DMat3 {
634 #[inline]
mul_assign(&mut self, rhs: Self)635 fn mul_assign(&mut self, rhs: Self) {
636 *self = self.mul_mat3(&rhs);
637 }
638 }
639
640 impl Mul<DVec3> for DMat3 {
641 type Output = DVec3;
642 #[inline]
mul(self, rhs: DVec3) -> Self::Output643 fn mul(self, rhs: DVec3) -> Self::Output {
644 self.mul_vec3(rhs)
645 }
646 }
647
648 impl Mul<DMat3> for f64 {
649 type Output = DMat3;
650 #[inline]
mul(self, rhs: DMat3) -> Self::Output651 fn mul(self, rhs: DMat3) -> Self::Output {
652 rhs.mul_scalar(self)
653 }
654 }
655
656 impl Mul<f64> for DMat3 {
657 type Output = Self;
658 #[inline]
mul(self, rhs: f64) -> Self::Output659 fn mul(self, rhs: f64) -> Self::Output {
660 self.mul_scalar(rhs)
661 }
662 }
663
664 impl MulAssign<f64> for DMat3 {
665 #[inline]
mul_assign(&mut self, rhs: f64)666 fn mul_assign(&mut self, rhs: f64) {
667 *self = self.mul_scalar(rhs);
668 }
669 }
670
671 impl Sum<Self> for DMat3 {
sum<I>(iter: I) -> Self where I: Iterator<Item = Self>,672 fn sum<I>(iter: I) -> Self
673 where
674 I: Iterator<Item = Self>,
675 {
676 iter.fold(Self::ZERO, Self::add)
677 }
678 }
679
680 impl<'a> Sum<&'a Self> for DMat3 {
sum<I>(iter: I) -> Self where I: Iterator<Item = &'a Self>,681 fn sum<I>(iter: I) -> Self
682 where
683 I: Iterator<Item = &'a Self>,
684 {
685 iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
686 }
687 }
688
689 impl Product for DMat3 {
product<I>(iter: I) -> Self where I: Iterator<Item = Self>,690 fn product<I>(iter: I) -> Self
691 where
692 I: Iterator<Item = Self>,
693 {
694 iter.fold(Self::IDENTITY, Self::mul)
695 }
696 }
697
698 impl<'a> Product<&'a Self> for DMat3 {
product<I>(iter: I) -> Self where I: Iterator<Item = &'a Self>,699 fn product<I>(iter: I) -> Self
700 where
701 I: Iterator<Item = &'a Self>,
702 {
703 iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
704 }
705 }
706
707 impl PartialEq for DMat3 {
708 #[inline]
eq(&self, rhs: &Self) -> bool709 fn eq(&self, rhs: &Self) -> bool {
710 self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
711 }
712 }
713
714 #[cfg(not(target_arch = "spirv"))]
715 impl AsRef<[f64; 9]> for DMat3 {
716 #[inline]
as_ref(&self) -> &[f64; 9]717 fn as_ref(&self) -> &[f64; 9] {
718 unsafe { &*(self as *const Self as *const [f64; 9]) }
719 }
720 }
721
722 #[cfg(not(target_arch = "spirv"))]
723 impl AsMut<[f64; 9]> for DMat3 {
724 #[inline]
as_mut(&mut self) -> &mut [f64; 9]725 fn as_mut(&mut self) -> &mut [f64; 9] {
726 unsafe { &mut *(self as *mut Self as *mut [f64; 9]) }
727 }
728 }
729
730 #[cfg(not(target_arch = "spirv"))]
731 impl fmt::Debug for DMat3 {
fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result732 fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
733 fmt.debug_struct(stringify!(DMat3))
734 .field("x_axis", &self.x_axis)
735 .field("y_axis", &self.y_axis)
736 .field("z_axis", &self.z_axis)
737 .finish()
738 }
739 }
740
741 #[cfg(not(target_arch = "spirv"))]
742 impl fmt::Display for DMat3 {
fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result743 fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
744 write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
745 }
746 }
747