revier_glam/f64/
dmat2.rs

1// Generated from mat.rs.tera template. Edit the template, not the generated file.
2
3use crate::{f64::math, swizzles::*, DMat3, DVec2, Mat2};
4#[cfg(not(target_arch = "spirv"))]
5use core::fmt;
6use core::iter::{Product, Sum};
7use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
8
9/// Creates a 2x2 matrix from two column vectors.
10#[inline(always)]
11pub const fn dmat2(x_axis: DVec2, y_axis: DVec2) -> DMat2 {
12    DMat2::from_cols(x_axis, y_axis)
13}
14
15/// A 2x2 column major matrix.
16#[derive(Clone, Copy)]
17#[cfg_attr(feature = "cuda", repr(align(16)))]
18#[repr(C)]
19pub struct DMat2 {
20    pub x_axis: DVec2,
21    pub y_axis: DVec2,
22}
23
24impl DMat2 {
25    /// A 2x2 matrix with all elements set to `0.0`.
26    pub const ZERO: Self = Self::from_cols(DVec2::ZERO, DVec2::ZERO);
27
28    /// A 2x2 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
29    pub const IDENTITY: Self = Self::from_cols(DVec2::X, DVec2::Y);
30
31    /// All NAN:s.
32    pub const NAN: Self = Self::from_cols(DVec2::NAN, DVec2::NAN);
33
34    #[allow(clippy::too_many_arguments)]
35    #[inline(always)]
36    const fn new(m00: f64, m01: f64, m10: f64, m11: f64) -> Self {
37        Self {
38            x_axis: DVec2::new(m00, m01),
39            y_axis: DVec2::new(m10, m11),
40        }
41    }
42
43    /// Creates a 2x2 matrix from two column vectors.
44    #[inline(always)]
45    pub const fn from_cols(x_axis: DVec2, y_axis: DVec2) -> Self {
46        Self { x_axis, y_axis }
47    }
48
49    /// Creates a 2x2 matrix from a `[f64; 4]` array stored in column major order.
50    /// If your data is stored in row major you will need to `transpose` the returned
51    /// matrix.
52    #[inline]
53    pub const fn from_cols_array(m: &[f64; 4]) -> Self {
54        Self::new(m[0], m[1], m[2], m[3])
55    }
56
57    /// Creates a `[f64; 4]` array storing data in column major order.
58    /// If you require data in row major order `transpose` the matrix first.
59    #[inline]
60    pub const fn to_cols_array(&self) -> [f64; 4] {
61        [self.x_axis.x, self.x_axis.y, self.y_axis.x, self.y_axis.y]
62    }
63
64    /// Creates a 2x2 matrix from a `[[f64; 2]; 2]` 2D array stored in column major order.
65    /// If your data is in row major order you will need to `transpose` the returned
66    /// matrix.
67    #[inline]
68    pub const fn from_cols_array_2d(m: &[[f64; 2]; 2]) -> Self {
69        Self::from_cols(DVec2::from_array(m[0]), DVec2::from_array(m[1]))
70    }
71
72    /// Creates a `[[f64; 2]; 2]` 2D array storing data in column major order.
73    /// If you require data in row major order `transpose` the matrix first.
74    #[inline]
75    pub const fn to_cols_array_2d(&self) -> [[f64; 2]; 2] {
76        [self.x_axis.to_array(), self.y_axis.to_array()]
77    }
78
79    /// Creates a 2x2 matrix with its diagonal set to `diagonal` and all other entries set to 0.
80    #[doc(alias = "scale")]
81    #[inline]
82    pub const fn from_diagonal(diagonal: DVec2) -> Self {
83        Self::new(diagonal.x, 0.0, 0.0, diagonal.y)
84    }
85
86    /// Creates a 2x2 matrix containing the combining non-uniform `scale` and rotation of
87    /// `angle` (in radians).
88    #[inline]
89    pub fn from_scale_angle(scale: DVec2, angle: f64) -> Self {
90        let (sin, cos) = math::sin_cos(angle);
91        Self::new(cos * scale.x, sin * scale.x, -sin * scale.y, cos * scale.y)
92    }
93
94    /// Creates a 2x2 matrix containing a rotation of `angle` (in radians).
95    #[inline]
96    pub fn from_angle(angle: f64) -> Self {
97        let (sin, cos) = math::sin_cos(angle);
98        Self::new(cos, sin, -sin, cos)
99    }
100
101    /// Creates a 2x2 matrix from a 3x3 matrix, discarding the 2nd row and column.
102    #[inline]
103    pub fn from_mat3(m: DMat3) -> Self {
104        Self::from_cols(m.x_axis.xy(), m.y_axis.xy())
105    }
106
107    /// Creates a 2x2 matrix from the first 4 values in `slice`.
108    ///
109    /// # Panics
110    ///
111    /// Panics if `slice` is less than 4 elements long.
112    #[inline]
113    pub const fn from_cols_slice(slice: &[f64]) -> Self {
114        Self::new(slice[0], slice[1], slice[2], slice[3])
115    }
116
117    /// Writes the columns of `self` to the first 4 elements in `slice`.
118    ///
119    /// # Panics
120    ///
121    /// Panics if `slice` is less than 4 elements long.
122    #[inline]
123    pub fn write_cols_to_slice(self, slice: &mut [f64]) {
124        slice[0] = self.x_axis.x;
125        slice[1] = self.x_axis.y;
126        slice[2] = self.y_axis.x;
127        slice[3] = self.y_axis.y;
128    }
129
130    /// Returns the matrix column for the given `index`.
131    ///
132    /// # Panics
133    ///
134    /// Panics if `index` is greater than 1.
135    #[inline]
136    pub fn col(&self, index: usize) -> DVec2 {
137        match index {
138            0 => self.x_axis,
139            1 => self.y_axis,
140            _ => panic!("index out of bounds"),
141        }
142    }
143
144    /// Returns a mutable reference to the matrix column for the given `index`.
145    ///
146    /// # Panics
147    ///
148    /// Panics if `index` is greater than 1.
149    #[inline]
150    pub fn col_mut(&mut self, index: usize) -> &mut DVec2 {
151        match index {
152            0 => &mut self.x_axis,
153            1 => &mut self.y_axis,
154            _ => panic!("index out of bounds"),
155        }
156    }
157
158    /// Returns the matrix row for the given `index`.
159    ///
160    /// # Panics
161    ///
162    /// Panics if `index` is greater than 1.
163    #[inline]
164    pub fn row(&self, index: usize) -> DVec2 {
165        match index {
166            0 => DVec2::new(self.x_axis.x, self.y_axis.x),
167            1 => DVec2::new(self.x_axis.y, self.y_axis.y),
168            _ => panic!("index out of bounds"),
169        }
170    }
171
172    /// Returns `true` if, and only if, all elements are finite.
173    /// If any element is either `NaN`, positive or negative infinity, this will return `false`.
174    #[inline]
175    pub fn is_finite(&self) -> bool {
176        self.x_axis.is_finite() && self.y_axis.is_finite()
177    }
178
179    /// Returns `true` if any elements are `NaN`.
180    #[inline]
181    pub fn is_nan(&self) -> bool {
182        self.x_axis.is_nan() || self.y_axis.is_nan()
183    }
184
185    /// Returns the transpose of `self`.
186    #[must_use]
187    #[inline]
188    pub fn transpose(&self) -> Self {
189        Self {
190            x_axis: DVec2::new(self.x_axis.x, self.y_axis.x),
191            y_axis: DVec2::new(self.x_axis.y, self.y_axis.y),
192        }
193    }
194
195    /// Returns the determinant of `self`.
196    #[inline]
197    pub fn determinant(&self) -> f64 {
198        self.x_axis.x * self.y_axis.y - self.x_axis.y * self.y_axis.x
199    }
200
201    /// Returns the inverse of `self`.
202    ///
203    /// If the matrix is not invertible the returned matrix will be invalid.
204    ///
205    /// # Panics
206    ///
207    /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
208    #[must_use]
209    #[inline]
210    pub fn inverse(&self) -> Self {
211        let inv_det = {
212            let det = self.determinant();
213            glam_assert!(det != 0.0);
214            det.recip()
215        };
216        Self::new(
217            self.y_axis.y * inv_det,
218            self.x_axis.y * -inv_det,
219            self.y_axis.x * -inv_det,
220            self.x_axis.x * inv_det,
221        )
222    }
223
224    /// Transforms a 2D vector.
225    #[inline]
226    pub fn mul_vec2(&self, rhs: DVec2) -> DVec2 {
227        #[allow(clippy::suspicious_operation_groupings)]
228        DVec2::new(
229            (self.x_axis.x * rhs.x) + (self.y_axis.x * rhs.y),
230            (self.x_axis.y * rhs.x) + (self.y_axis.y * rhs.y),
231        )
232    }
233
234    /// Multiplies two 2x2 matrices.
235    #[inline]
236    pub fn mul_mat2(&self, rhs: &Self) -> Self {
237        Self::from_cols(self.mul(rhs.x_axis), self.mul(rhs.y_axis))
238    }
239
240    /// Adds two 2x2 matrices.
241    #[inline]
242    pub fn add_mat2(&self, rhs: &Self) -> Self {
243        Self::from_cols(self.x_axis.add(rhs.x_axis), self.y_axis.add(rhs.y_axis))
244    }
245
246    /// Subtracts two 2x2 matrices.
247    #[inline]
248    pub fn sub_mat2(&self, rhs: &Self) -> Self {
249        Self::from_cols(self.x_axis.sub(rhs.x_axis), self.y_axis.sub(rhs.y_axis))
250    }
251
252    /// Multiplies a 2x2 matrix by a scalar.
253    #[inline]
254    pub fn mul_scalar(&self, rhs: f64) -> Self {
255        Self::from_cols(self.x_axis.mul(rhs), self.y_axis.mul(rhs))
256    }
257
258    /// Returns true if the absolute difference of all elements between `self` and `rhs`
259    /// is less than or equal to `max_abs_diff`.
260    ///
261    /// This can be used to compare if two matrices contain similar elements. It works best
262    /// when comparing with a known value. The `max_abs_diff` that should be used used
263    /// depends on the values being compared against.
264    ///
265    /// For more see
266    /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
267    #[inline]
268    pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f64) -> bool {
269        self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
270            && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
271    }
272
273    #[inline]
274    pub fn as_mat2(&self) -> Mat2 {
275        Mat2::from_cols(self.x_axis.as_vec2(), self.y_axis.as_vec2())
276    }
277}
278
279impl Default for DMat2 {
280    #[inline]
281    fn default() -> Self {
282        Self::IDENTITY
283    }
284}
285
286impl Add<DMat2> for DMat2 {
287    type Output = Self;
288    #[inline]
289    fn add(self, rhs: Self) -> Self::Output {
290        self.add_mat2(&rhs)
291    }
292}
293
294impl AddAssign<DMat2> for DMat2 {
295    #[inline]
296    fn add_assign(&mut self, rhs: Self) {
297        *self = self.add_mat2(&rhs);
298    }
299}
300
301impl Sub<DMat2> for DMat2 {
302    type Output = Self;
303    #[inline]
304    fn sub(self, rhs: Self) -> Self::Output {
305        self.sub_mat2(&rhs)
306    }
307}
308
309impl SubAssign<DMat2> for DMat2 {
310    #[inline]
311    fn sub_assign(&mut self, rhs: Self) {
312        *self = self.sub_mat2(&rhs);
313    }
314}
315
316impl Neg for DMat2 {
317    type Output = Self;
318    #[inline]
319    fn neg(self) -> Self::Output {
320        Self::from_cols(self.x_axis.neg(), self.y_axis.neg())
321    }
322}
323
324impl Mul<DMat2> for DMat2 {
325    type Output = Self;
326    #[inline]
327    fn mul(self, rhs: Self) -> Self::Output {
328        self.mul_mat2(&rhs)
329    }
330}
331
332impl MulAssign<DMat2> for DMat2 {
333    #[inline]
334    fn mul_assign(&mut self, rhs: Self) {
335        *self = self.mul_mat2(&rhs);
336    }
337}
338
339impl Mul<DVec2> for DMat2 {
340    type Output = DVec2;
341    #[inline]
342    fn mul(self, rhs: DVec2) -> Self::Output {
343        self.mul_vec2(rhs)
344    }
345}
346
347impl Mul<DMat2> for f64 {
348    type Output = DMat2;
349    #[inline]
350    fn mul(self, rhs: DMat2) -> Self::Output {
351        rhs.mul_scalar(self)
352    }
353}
354
355impl Mul<f64> for DMat2 {
356    type Output = Self;
357    #[inline]
358    fn mul(self, rhs: f64) -> Self::Output {
359        self.mul_scalar(rhs)
360    }
361}
362
363impl MulAssign<f64> for DMat2 {
364    #[inline]
365    fn mul_assign(&mut self, rhs: f64) {
366        *self = self.mul_scalar(rhs);
367    }
368}
369
370impl Sum<Self> for DMat2 {
371    fn sum<I>(iter: I) -> Self
372    where
373        I: Iterator<Item = Self>,
374    {
375        iter.fold(Self::ZERO, Self::add)
376    }
377}
378
379impl<'a> Sum<&'a Self> for DMat2 {
380    fn sum<I>(iter: I) -> Self
381    where
382        I: Iterator<Item = &'a Self>,
383    {
384        iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
385    }
386}
387
388impl Product for DMat2 {
389    fn product<I>(iter: I) -> Self
390    where
391        I: Iterator<Item = Self>,
392    {
393        iter.fold(Self::IDENTITY, Self::mul)
394    }
395}
396
397impl<'a> Product<&'a Self> for DMat2 {
398    fn product<I>(iter: I) -> Self
399    where
400        I: Iterator<Item = &'a Self>,
401    {
402        iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
403    }
404}
405
406impl PartialEq for DMat2 {
407    #[inline]
408    fn eq(&self, rhs: &Self) -> bool {
409        self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis)
410    }
411}
412
413#[cfg(not(target_arch = "spirv"))]
414impl AsRef<[f64; 4]> for DMat2 {
415    #[inline]
416    fn as_ref(&self) -> &[f64; 4] {
417        unsafe { &*(self as *const Self as *const [f64; 4]) }
418    }
419}
420
421#[cfg(not(target_arch = "spirv"))]
422impl AsMut<[f64; 4]> for DMat2 {
423    #[inline]
424    fn as_mut(&mut self) -> &mut [f64; 4] {
425        unsafe { &mut *(self as *mut Self as *mut [f64; 4]) }
426    }
427}
428
429#[cfg(not(target_arch = "spirv"))]
430impl fmt::Debug for DMat2 {
431    fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
432        fmt.debug_struct(stringify!(DMat2))
433            .field("x_axis", &self.x_axis)
434            .field("y_axis", &self.y_axis)
435            .finish()
436    }
437}
438
439#[cfg(not(target_arch = "spirv"))]
440impl fmt::Display for DMat2 {
441    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
442        write!(f, "[{}, {}]", self.x_axis, self.y_axis)
443    }
444}
revier_glam/f64/dmat2.rs

revier_glam/f64/
dmat2.rs
