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1 // Generated from mat.rs.tera template. Edit the template, not the generated file.
2 
3 use crate::{f32::math, swizzles::*, DMat2, Mat3, Mat3A, Vec2};
4 use core::fmt;
5 use core::iter::{Product, Sum};
6 use core::ops::{Add, AddAssign, Div, DivAssign, Mul, MulAssign, Neg, Sub, SubAssign};
7 
8 use core::arch::aarch64::*;
9 
10 #[repr(C)]
11 union UnionCast {
12     a: [f32; 4],
13     v: Mat2,
14 }
15 
16 /// Creates a 2x2 matrix from two column vectors.
17 #[inline(always)]
18 #[must_use]
mat2(x_axis: Vec2, y_axis: Vec2) -> Mat219 pub const fn mat2(x_axis: Vec2, y_axis: Vec2) -> Mat2 {
20     Mat2::from_cols(x_axis, y_axis)
21 }
22 
23 /// A 2x2 column major matrix.
24 ///
25 /// SIMD vector types are used for storage on supported platforms.
26 ///
27 /// This type is 16 byte aligned.
28 #[derive(Clone, Copy)]
29 #[repr(transparent)]
30 pub struct Mat2(pub(crate) float32x4_t);
31 
32 impl Mat2 {
33     /// A 2x2 matrix with all elements set to `0.0`.
34     pub const ZERO: Self = Self::from_cols(Vec2::ZERO, Vec2::ZERO);
35 
36     /// A 2x2 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
37     pub const IDENTITY: Self = Self::from_cols(Vec2::X, Vec2::Y);
38 
39     /// All NAN:s.
40     pub const NAN: Self = Self::from_cols(Vec2::NAN, Vec2::NAN);
41 
42     #[allow(clippy::too_many_arguments)]
43     #[inline(always)]
44     #[must_use]
new(m00: f32, m01: f32, m10: f32, m11: f32) -> Self45     const fn new(m00: f32, m01: f32, m10: f32, m11: f32) -> Self {
46         unsafe {
47             UnionCast {
48                 a: [m00, m01, m10, m11],
49             }
50             .v
51         }
52     }
53 
54     /// Creates a 2x2 matrix from two column vectors.
55     #[inline(always)]
56     #[must_use]
from_cols(x_axis: Vec2, y_axis: Vec2) -> Self57     pub const fn from_cols(x_axis: Vec2, y_axis: Vec2) -> Self {
58         unsafe {
59             UnionCast {
60                 a: [x_axis.x, x_axis.y, y_axis.x, y_axis.y],
61             }
62             .v
63         }
64     }
65 
66     /// Creates a 2x2 matrix from a `[f32; 4]` array stored in column major order.
67     /// If your data is stored in row major you will need to `transpose` the returned
68     /// matrix.
69     #[inline]
70     #[must_use]
from_cols_array(m: &[f32; 4]) -> Self71     pub const fn from_cols_array(m: &[f32; 4]) -> Self {
72         Self::new(m[0], m[1], m[2], m[3])
73     }
74 
75     /// Creates a `[f32; 4]` array storing data in column major order.
76     /// If you require data in row major order `transpose` the matrix first.
77     #[inline]
78     #[must_use]
to_cols_array(&self) -> [f32; 4]79     pub const fn to_cols_array(&self) -> [f32; 4] {
80         unsafe { *(self as *const Self as *const [f32; 4]) }
81     }
82 
83     /// Creates a 2x2 matrix from a `[[f32; 2]; 2]` 2D array stored in column major order.
84     /// If your data is in row major order you will need to `transpose` the returned
85     /// matrix.
86     #[inline]
87     #[must_use]
from_cols_array_2d(m: &[[f32; 2]; 2]) -> Self88     pub const fn from_cols_array_2d(m: &[[f32; 2]; 2]) -> Self {
89         Self::from_cols(Vec2::from_array(m[0]), Vec2::from_array(m[1]))
90     }
91 
92     /// Creates a `[[f32; 2]; 2]` 2D array storing data in column major order.
93     /// If you require data in row major order `transpose` the matrix first.
94     #[inline]
95     #[must_use]
to_cols_array_2d(&self) -> [[f32; 2]; 2]96     pub const fn to_cols_array_2d(&self) -> [[f32; 2]; 2] {
97         unsafe { *(self as *const Self as *const [[f32; 2]; 2]) }
98     }
99 
100     /// Creates a 2x2 matrix with its diagonal set to `diagonal` and all other entries set to 0.
101     #[doc(alias = "scale")]
102     #[inline]
103     #[must_use]
from_diagonal(diagonal: Vec2) -> Self104     pub const fn from_diagonal(diagonal: Vec2) -> Self {
105         Self::new(diagonal.x, 0.0, 0.0, diagonal.y)
106     }
107 
108     /// Creates a 2x2 matrix containing the combining non-uniform `scale` and rotation of
109     /// `angle` (in radians).
110     #[inline]
111     #[must_use]
from_scale_angle(scale: Vec2, angle: f32) -> Self112     pub fn from_scale_angle(scale: Vec2, angle: f32) -> Self {
113         let (sin, cos) = math::sin_cos(angle);
114         Self::new(cos * scale.x, sin * scale.x, -sin * scale.y, cos * scale.y)
115     }
116 
117     /// Creates a 2x2 matrix containing a rotation of `angle` (in radians).
118     #[inline]
119     #[must_use]
from_angle(angle: f32) -> Self120     pub fn from_angle(angle: f32) -> Self {
121         let (sin, cos) = math::sin_cos(angle);
122         Self::new(cos, sin, -sin, cos)
123     }
124 
125     /// Creates a 2x2 matrix from a 3x3 matrix, discarding the 2nd row and column.
126     #[inline]
127     #[must_use]
from_mat3(m: Mat3) -> Self128     pub fn from_mat3(m: Mat3) -> Self {
129         Self::from_cols(m.x_axis.xy(), m.y_axis.xy())
130     }
131 
132     /// Creates a 2x2 matrix from the minor of the given 3x3 matrix, discarding the `i`th column
133     /// and `j`th row.
134     ///
135     /// # Panics
136     ///
137     /// Panics if `i` or `j` is greater than 2.
138     #[inline]
139     #[must_use]
from_mat3_minor(m: Mat3, i: usize, j: usize) -> Self140     pub fn from_mat3_minor(m: Mat3, i: usize, j: usize) -> Self {
141         match (i, j) {
142             (0, 0) => Self::from_cols(m.y_axis.yz(), m.z_axis.yz()),
143             (0, 1) => Self::from_cols(m.y_axis.xz(), m.z_axis.xz()),
144             (0, 2) => Self::from_cols(m.y_axis.xy(), m.z_axis.xy()),
145             (1, 0) => Self::from_cols(m.x_axis.yz(), m.z_axis.yz()),
146             (1, 1) => Self::from_cols(m.x_axis.xz(), m.z_axis.xz()),
147             (1, 2) => Self::from_cols(m.x_axis.xy(), m.z_axis.xy()),
148             (2, 0) => Self::from_cols(m.x_axis.yz(), m.y_axis.yz()),
149             (2, 1) => Self::from_cols(m.x_axis.xz(), m.y_axis.xz()),
150             (2, 2) => Self::from_cols(m.x_axis.xy(), m.y_axis.xy()),
151             _ => panic!("index out of bounds"),
152         }
153     }
154 
155     /// Creates a 2x2 matrix from a 3x3 matrix, discarding the 2nd row and column.
156     #[inline]
157     #[must_use]
from_mat3a(m: Mat3A) -> Self158     pub fn from_mat3a(m: Mat3A) -> Self {
159         Self::from_cols(m.x_axis.xy(), m.y_axis.xy())
160     }
161 
162     /// Creates a 2x2 matrix from the minor of the given 3x3 matrix, discarding the `i`th column
163     /// and `j`th row.
164     ///
165     /// # Panics
166     ///
167     /// Panics if `i` or `j` is greater than 2.
168     #[inline]
169     #[must_use]
from_mat3a_minor(m: Mat3A, i: usize, j: usize) -> Self170     pub fn from_mat3a_minor(m: Mat3A, i: usize, j: usize) -> Self {
171         match (i, j) {
172             (0, 0) => Self::from_cols(m.y_axis.yz(), m.z_axis.yz()),
173             (0, 1) => Self::from_cols(m.y_axis.xz(), m.z_axis.xz()),
174             (0, 2) => Self::from_cols(m.y_axis.xy(), m.z_axis.xy()),
175             (1, 0) => Self::from_cols(m.x_axis.yz(), m.z_axis.yz()),
176             (1, 1) => Self::from_cols(m.x_axis.xz(), m.z_axis.xz()),
177             (1, 2) => Self::from_cols(m.x_axis.xy(), m.z_axis.xy()),
178             (2, 0) => Self::from_cols(m.x_axis.yz(), m.y_axis.yz()),
179             (2, 1) => Self::from_cols(m.x_axis.xz(), m.y_axis.xz()),
180             (2, 2) => Self::from_cols(m.x_axis.xy(), m.y_axis.xy()),
181             _ => panic!("index out of bounds"),
182         }
183     }
184 
185     /// Creates a 2x2 matrix from the first 4 values in `slice`.
186     ///
187     /// # Panics
188     ///
189     /// Panics if `slice` is less than 4 elements long.
190     #[inline]
191     #[must_use]
from_cols_slice(slice: &[f32]) -> Self192     pub const fn from_cols_slice(slice: &[f32]) -> Self {
193         Self::new(slice[0], slice[1], slice[2], slice[3])
194     }
195 
196     /// Writes the columns of `self` to the first 4 elements in `slice`.
197     ///
198     /// # Panics
199     ///
200     /// Panics if `slice` is less than 4 elements long.
201     #[inline]
write_cols_to_slice(self, slice: &mut [f32])202     pub fn write_cols_to_slice(self, slice: &mut [f32]) {
203         slice[0] = self.x_axis.x;
204         slice[1] = self.x_axis.y;
205         slice[2] = self.y_axis.x;
206         slice[3] = self.y_axis.y;
207     }
208 
209     /// Returns the matrix column for the given `index`.
210     ///
211     /// # Panics
212     ///
213     /// Panics if `index` is greater than 1.
214     #[inline]
215     #[must_use]
col(&self, index: usize) -> Vec2216     pub fn col(&self, index: usize) -> Vec2 {
217         match index {
218             0 => self.x_axis,
219             1 => self.y_axis,
220             _ => panic!("index out of bounds"),
221         }
222     }
223 
224     /// Returns a mutable reference to the matrix column for the given `index`.
225     ///
226     /// # Panics
227     ///
228     /// Panics if `index` is greater than 1.
229     #[inline]
col_mut(&mut self, index: usize) -> &mut Vec2230     pub fn col_mut(&mut self, index: usize) -> &mut Vec2 {
231         match index {
232             0 => &mut self.x_axis,
233             1 => &mut self.y_axis,
234             _ => panic!("index out of bounds"),
235         }
236     }
237 
238     /// Returns the matrix row for the given `index`.
239     ///
240     /// # Panics
241     ///
242     /// Panics if `index` is greater than 1.
243     #[inline]
244     #[must_use]
row(&self, index: usize) -> Vec2245     pub fn row(&self, index: usize) -> Vec2 {
246         match index {
247             0 => Vec2::new(self.x_axis.x, self.y_axis.x),
248             1 => Vec2::new(self.x_axis.y, self.y_axis.y),
249             _ => panic!("index out of bounds"),
250         }
251     }
252 
253     /// Returns `true` if, and only if, all elements are finite.
254     /// If any element is either `NaN`, positive or negative infinity, this will return `false`.
255     #[inline]
256     #[must_use]
is_finite(&self) -> bool257     pub fn is_finite(&self) -> bool {
258         self.x_axis.is_finite() && self.y_axis.is_finite()
259     }
260 
261     /// Returns `true` if any elements are `NaN`.
262     #[inline]
263     #[must_use]
is_nan(&self) -> bool264     pub fn is_nan(&self) -> bool {
265         self.x_axis.is_nan() || self.y_axis.is_nan()
266     }
267 
268     /// Returns the transpose of `self`.
269     #[inline]
270     #[must_use]
transpose(&self) -> Self271     pub fn transpose(&self) -> Self {
272         Self(unsafe {
273             vsetq_lane_f32(
274                 vgetq_lane_f32(self.0, 2),
275                 vsetq_lane_f32(vgetq_lane_f32(self.0, 1), self.0, 2),
276                 1,
277             )
278         })
279     }
280 
281     /// Returns the determinant of `self`.
282     #[inline]
283     #[must_use]
determinant(&self) -> f32284     pub fn determinant(&self) -> f32 {
285         unsafe {
286             let abcd = self.0;
287             let badc = vrev64q_f32(abcd);
288             let dcba = vextq_f32(badc, badc, 2);
289             let prod = vmulq_f32(abcd, dcba);
290             let det = vsubq_f32(prod, vdupq_laneq_f32(prod, 1));
291             vgetq_lane_f32(det, 0)
292         }
293     }
294 
295     /// Returns the inverse of `self`.
296     ///
297     /// If the matrix is not invertible the returned matrix will be invalid.
298     ///
299     /// # Panics
300     ///
301     /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
302     #[inline]
303     #[must_use]
inverse(&self) -> Self304     pub fn inverse(&self) -> Self {
305         unsafe {
306             const SIGN: float32x4_t = crate::neon::f32x4_from_array([1.0, -1.0, -1.0, 1.0]);
307             let abcd = self.0;
308             let badc = vrev64q_f32(abcd);
309             let dcba = vextq_f32(badc, badc, 2);
310             let prod = vmulq_f32(abcd, dcba);
311             let sub = vsubq_f32(prod, vdupq_laneq_f32(prod, 1));
312             let det = vdupq_laneq_f32(sub, 0);
313             let tmp = vdivq_f32(SIGN, det);
314             glam_assert!(Mat2(tmp).is_finite());
315             //let dbca = simd_swizzle!(abcd, [3, 1, 2, 0]);
316             let dbca = vsetq_lane_f32(
317                 vgetq_lane_f32(abcd, 0),
318                 vsetq_lane_f32(vgetq_lane_f32(abcd, 3), abcd, 0),
319                 3,
320             );
321             Self(vmulq_f32(dbca, tmp))
322         }
323     }
324 
325     /// Transforms a 2D vector.
326     #[inline]
327     #[must_use]
mul_vec2(&self, rhs: Vec2) -> Vec2328     pub fn mul_vec2(&self, rhs: Vec2) -> Vec2 {
329         unsafe {
330             let abcd = self.0;
331             let xxyy = vld1q_f32([rhs.x, rhs.x, rhs.y, rhs.y].as_ptr());
332             let axbxcydy = vmulq_f32(abcd, xxyy);
333             // let cydyaxbx = simd_swizzle!(axbxcydy, [2, 3, 0, 1]);
334             let cydyaxbx = vextq_f32(axbxcydy, axbxcydy, 2);
335             let result = vaddq_f32(axbxcydy, cydyaxbx);
336             *(&result as *const float32x4_t as *const Vec2)
337         }
338     }
339 
340     /// Multiplies two 2x2 matrices.
341     #[inline]
342     #[must_use]
mul_mat2(&self, rhs: &Self) -> Self343     pub fn mul_mat2(&self, rhs: &Self) -> Self {
344         unsafe {
345             let abcd = self.0;
346             let xxyy0 = vzip1q_f32(rhs.0, rhs.0);
347             let xxyy1 = vzip2q_f32(rhs.0, rhs.0);
348             let axbxcydy0 = vmulq_f32(abcd, xxyy0);
349             let axbxcydy1 = vmulq_f32(abcd, xxyy1);
350             let cydyaxbx0 = vextq_f32(axbxcydy0, axbxcydy0, 2);
351             let cydyaxbx1 = vextq_f32(axbxcydy1, axbxcydy1, 2);
352             let result0 = vaddq_f32(axbxcydy0, cydyaxbx0);
353             let result1 = vaddq_f32(axbxcydy1, cydyaxbx1);
354             Self(vreinterpretq_f32_u64(vsetq_lane_u64(
355                 vgetq_lane_u64(vreinterpretq_u64_f32(result1), 0),
356                 vreinterpretq_u64_f32(result0),
357                 1,
358             )))
359         }
360     }
361 
362     /// Adds two 2x2 matrices.
363     #[inline]
364     #[must_use]
add_mat2(&self, rhs: &Self) -> Self365     pub fn add_mat2(&self, rhs: &Self) -> Self {
366         Self(unsafe { vaddq_f32(self.0, rhs.0) })
367     }
368 
369     /// Subtracts two 2x2 matrices.
370     #[inline]
371     #[must_use]
sub_mat2(&self, rhs: &Self) -> Self372     pub fn sub_mat2(&self, rhs: &Self) -> Self {
373         Self(unsafe { vsubq_f32(self.0, rhs.0) })
374     }
375 
376     /// Multiplies a 2x2 matrix by a scalar.
377     #[inline]
378     #[must_use]
mul_scalar(&self, rhs: f32) -> Self379     pub fn mul_scalar(&self, rhs: f32) -> Self {
380         Self(unsafe { vmulq_f32(self.0, vld1q_dup_f32(&rhs)) })
381     }
382 
383     /// Divides a 2x2 matrix by a scalar.
384     #[inline]
385     #[must_use]
div_scalar(&self, rhs: f32) -> Self386     pub fn div_scalar(&self, rhs: f32) -> Self {
387         Self(unsafe { vdivq_f32(self.0, vld1q_dup_f32(&rhs)) })
388     }
389 
390     /// Returns true if the absolute difference of all elements between `self` and `rhs`
391     /// is less than or equal to `max_abs_diff`.
392     ///
393     /// This can be used to compare if two matrices contain similar elements. It works best
394     /// when comparing with a known value. The `max_abs_diff` that should be used used
395     /// depends on the values being compared against.
396     ///
397     /// For more see
398     /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
399     #[inline]
400     #[must_use]
abs_diff_eq(&self, rhs: Self, max_abs_diff: f32) -> bool401     pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f32) -> bool {
402         self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
403             && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
404     }
405 
406     /// Takes the absolute value of each element in `self`
407     #[inline]
408     #[must_use]
abs(&self) -> Self409     pub fn abs(&self) -> Self {
410         Self::from_cols(self.x_axis.abs(), self.y_axis.abs())
411     }
412 
413     #[inline]
as_dmat2(&self) -> DMat2414     pub fn as_dmat2(&self) -> DMat2 {
415         DMat2::from_cols(self.x_axis.as_dvec2(), self.y_axis.as_dvec2())
416     }
417 }
418 
419 impl Default for Mat2 {
420     #[inline]
default() -> Self421     fn default() -> Self {
422         Self::IDENTITY
423     }
424 }
425 
426 impl Add<Mat2> for Mat2 {
427     type Output = Self;
428     #[inline]
add(self, rhs: Self) -> Self::Output429     fn add(self, rhs: Self) -> Self::Output {
430         self.add_mat2(&rhs)
431     }
432 }
433 
434 impl AddAssign<Mat2> for Mat2 {
435     #[inline]
add_assign(&mut self, rhs: Self)436     fn add_assign(&mut self, rhs: Self) {
437         *self = self.add_mat2(&rhs);
438     }
439 }
440 
441 impl Sub<Mat2> for Mat2 {
442     type Output = Self;
443     #[inline]
sub(self, rhs: Self) -> Self::Output444     fn sub(self, rhs: Self) -> Self::Output {
445         self.sub_mat2(&rhs)
446     }
447 }
448 
449 impl SubAssign<Mat2> for Mat2 {
450     #[inline]
sub_assign(&mut self, rhs: Self)451     fn sub_assign(&mut self, rhs: Self) {
452         *self = self.sub_mat2(&rhs);
453     }
454 }
455 
456 impl Neg for Mat2 {
457     type Output = Self;
458     #[inline]
neg(self) -> Self::Output459     fn neg(self) -> Self::Output {
460         Self(unsafe { vnegq_f32(self.0) })
461     }
462 }
463 
464 impl Mul<Mat2> for Mat2 {
465     type Output = Self;
466     #[inline]
mul(self, rhs: Self) -> Self::Output467     fn mul(self, rhs: Self) -> Self::Output {
468         self.mul_mat2(&rhs)
469     }
470 }
471 
472 impl MulAssign<Mat2> for Mat2 {
473     #[inline]
mul_assign(&mut self, rhs: Self)474     fn mul_assign(&mut self, rhs: Self) {
475         *self = self.mul_mat2(&rhs);
476     }
477 }
478 
479 impl Mul<Vec2> for Mat2 {
480     type Output = Vec2;
481     #[inline]
mul(self, rhs: Vec2) -> Self::Output482     fn mul(self, rhs: Vec2) -> Self::Output {
483         self.mul_vec2(rhs)
484     }
485 }
486 
487 impl Mul<Mat2> for f32 {
488     type Output = Mat2;
489     #[inline]
mul(self, rhs: Mat2) -> Self::Output490     fn mul(self, rhs: Mat2) -> Self::Output {
491         rhs.mul_scalar(self)
492     }
493 }
494 
495 impl Mul<f32> for Mat2 {
496     type Output = Self;
497     #[inline]
mul(self, rhs: f32) -> Self::Output498     fn mul(self, rhs: f32) -> Self::Output {
499         self.mul_scalar(rhs)
500     }
501 }
502 
503 impl MulAssign<f32> for Mat2 {
504     #[inline]
mul_assign(&mut self, rhs: f32)505     fn mul_assign(&mut self, rhs: f32) {
506         *self = self.mul_scalar(rhs);
507     }
508 }
509 
510 impl Div<Mat2> for f32 {
511     type Output = Mat2;
512     #[inline]
div(self, rhs: Mat2) -> Self::Output513     fn div(self, rhs: Mat2) -> Self::Output {
514         rhs.div_scalar(self)
515     }
516 }
517 
518 impl Div<f32> for Mat2 {
519     type Output = Self;
520     #[inline]
div(self, rhs: f32) -> Self::Output521     fn div(self, rhs: f32) -> Self::Output {
522         self.div_scalar(rhs)
523     }
524 }
525 
526 impl DivAssign<f32> for Mat2 {
527     #[inline]
div_assign(&mut self, rhs: f32)528     fn div_assign(&mut self, rhs: f32) {
529         *self = self.div_scalar(rhs);
530     }
531 }
532 
533 impl Sum<Self> for Mat2 {
sum<I>(iter: I) -> Self where I: Iterator<Item = Self>,534     fn sum<I>(iter: I) -> Self
535     where
536         I: Iterator<Item = Self>,
537     {
538         iter.fold(Self::ZERO, Self::add)
539     }
540 }
541 
542 impl<'a> Sum<&'a Self> for Mat2 {
sum<I>(iter: I) -> Self where I: Iterator<Item = &'a Self>,543     fn sum<I>(iter: I) -> Self
544     where
545         I: Iterator<Item = &'a Self>,
546     {
547         iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
548     }
549 }
550 
551 impl Product for Mat2 {
product<I>(iter: I) -> Self where I: Iterator<Item = Self>,552     fn product<I>(iter: I) -> Self
553     where
554         I: Iterator<Item = Self>,
555     {
556         iter.fold(Self::IDENTITY, Self::mul)
557     }
558 }
559 
560 impl<'a> Product<&'a Self> for Mat2 {
product<I>(iter: I) -> Self where I: Iterator<Item = &'a Self>,561     fn product<I>(iter: I) -> Self
562     where
563         I: Iterator<Item = &'a Self>,
564     {
565         iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
566     }
567 }
568 
569 impl PartialEq for Mat2 {
570     #[inline]
eq(&self, rhs: &Self) -> bool571     fn eq(&self, rhs: &Self) -> bool {
572         self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis)
573     }
574 }
575 
576 #[cfg(not(target_arch = "spirv"))]
577 impl AsRef<[f32; 4]> for Mat2 {
578     #[inline]
as_ref(&self) -> &[f32; 4]579     fn as_ref(&self) -> &[f32; 4] {
580         unsafe { &*(self as *const Self as *const [f32; 4]) }
581     }
582 }
583 
584 #[cfg(not(target_arch = "spirv"))]
585 impl AsMut<[f32; 4]> for Mat2 {
586     #[inline]
as_mut(&mut self) -> &mut [f32; 4]587     fn as_mut(&mut self) -> &mut [f32; 4] {
588         unsafe { &mut *(self as *mut Self as *mut [f32; 4]) }
589     }
590 }
591 
592 impl core::ops::Deref for Mat2 {
593     type Target = crate::deref::Cols2<Vec2>;
594     #[inline]
deref(&self) -> &Self::Target595     fn deref(&self) -> &Self::Target {
596         unsafe { &*(self as *const Self as *const Self::Target) }
597     }
598 }
599 
600 impl core::ops::DerefMut for Mat2 {
601     #[inline]
deref_mut(&mut self) -> &mut Self::Target602     fn deref_mut(&mut self) -> &mut Self::Target {
603         unsafe { &mut *(self as *mut Self as *mut Self::Target) }
604     }
605 }
606 
607 impl fmt::Debug for Mat2 {
fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result608     fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
609         fmt.debug_struct(stringify!(Mat2))
610             .field("x_axis", &self.x_axis)
611             .field("y_axis", &self.y_axis)
612             .finish()
613     }
614 }
615 
616 impl fmt::Display for Mat2 {
fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result617     fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
618         if let Some(p) = f.precision() {
619             write!(f, "[{:.*}, {:.*}]", p, self.x_axis, p, self.y_axis)
620         } else {
621             write!(f, "[{}, {}]", self.x_axis, self.y_axis)
622         }
623     }
624 }
625