glam/f64/
dmat3.rs

1// Generated from mat.rs.tera template. Edit the template, not the generated file.
2
3use crate::{
4    euler::{FromEuler, ToEuler},
5    f64::math,
6    swizzles::*,
7    DMat2, DMat4, DQuat, DVec2, DVec3, EulerRot, Mat3,
8};
9use core::fmt;
10use core::iter::{Product, Sum};
11use core::ops::{Add, AddAssign, Div, DivAssign, Mul, MulAssign, Neg, Sub, SubAssign};
12
13#[cfg(feature = "zerocopy")]
14use zerocopy_derive::*;
15
16/// Creates a 3x3 matrix from three column vectors.
17#[inline(always)]
18#[must_use]
19pub const fn dmat3(x_axis: DVec3, y_axis: DVec3, z_axis: DVec3) -> DMat3 {
20    DMat3::from_cols(x_axis, y_axis, z_axis)
21}
22
23/// A 3x3 column major matrix.
24///
25/// This 3x3 matrix type features convenience methods for creating and using linear and
26/// affine transformations. If you are primarily dealing with 2D affine transformations the
27/// [`DAffine2`](crate::DAffine2) type is much faster and more space efficient than
28/// using a 3x3 matrix.
29///
30/// Linear transformations including 3D rotation and scale can be created using methods
31/// such as [`Self::from_diagonal()`], [`Self::from_quat()`], [`Self::from_axis_angle()`],
32/// [`Self::from_rotation_x()`], [`Self::from_rotation_y()`], or
33/// [`Self::from_rotation_z()`].
34///
35/// The resulting matrices can be use to transform 3D vectors using regular vector
36/// multiplication.
37///
38/// Affine transformations including 2D translation, rotation and scale can be created
39/// using methods such as [`Self::from_translation()`], [`Self::from_angle()`],
40/// [`Self::from_scale()`] and [`Self::from_scale_angle_translation()`].
41///
42/// The [`Self::transform_point2()`] and [`Self::transform_vector2()`] convenience methods
43/// are provided for performing affine transforms on 2D vectors and points. These multiply
44/// 2D inputs as 3D vectors with an implicit `z` value of `1` for points and `0` for
45/// vectors respectively. These methods assume that `Self` contains a valid affine
46/// transform.
47#[derive(Clone, Copy)]
48#[cfg_attr(feature = "bytemuck", derive(bytemuck::Pod, bytemuck::Zeroable))]
49#[cfg_attr(
50    feature = "zerocopy",
51    derive(FromBytes, Immutable, IntoBytes, KnownLayout)
52)]
53#[repr(C)]
54pub struct DMat3 {
55    pub x_axis: DVec3,
56    pub y_axis: DVec3,
57    pub z_axis: DVec3,
58}
59
60impl DMat3 {
61    /// A 3x3 matrix with all elements set to `0.0`.
62    pub const ZERO: Self = Self::from_cols(DVec3::ZERO, DVec3::ZERO, DVec3::ZERO);
63
64    /// A 3x3 identity matrix, where all diagonal elements are `1`, and all off-diagonal elements are `0`.
65    pub const IDENTITY: Self = Self::from_cols(DVec3::X, DVec3::Y, DVec3::Z);
66
67    /// All NAN:s.
68    pub const NAN: Self = Self::from_cols(DVec3::NAN, DVec3::NAN, DVec3::NAN);
69
70    #[allow(clippy::too_many_arguments)]
71    #[inline(always)]
72    #[must_use]
73    const fn new(
74        m00: f64,
75        m01: f64,
76        m02: f64,
77        m10: f64,
78        m11: f64,
79        m12: f64,
80        m20: f64,
81        m21: f64,
82        m22: f64,
83    ) -> Self {
84        Self {
85            x_axis: DVec3::new(m00, m01, m02),
86            y_axis: DVec3::new(m10, m11, m12),
87            z_axis: DVec3::new(m20, m21, m22),
88        }
89    }
90
91    /// Creates a 3x3 matrix from three column vectors.
92    #[inline(always)]
93    #[must_use]
94    pub const fn from_cols(x_axis: DVec3, y_axis: DVec3, z_axis: DVec3) -> Self {
95        Self {
96            x_axis,
97            y_axis,
98            z_axis,
99        }
100    }
101
102    /// Creates a 3x3 matrix from a `[f64; 9]` array stored in column major order.
103    /// If your data is stored in row major you will need to `transpose` the returned
104    /// matrix.
105    #[inline]
106    #[must_use]
107    pub const fn from_cols_array(m: &[f64; 9]) -> Self {
108        Self::new(m[0], m[1], m[2], m[3], m[4], m[5], m[6], m[7], m[8])
109    }
110
111    /// Creates a `[f64; 9]` array storing data in column major order.
112    /// If you require data in row major order `transpose` the matrix first.
113    #[inline]
114    #[must_use]
115    pub const fn to_cols_array(&self) -> [f64; 9] {
116        [
117            self.x_axis.x,
118            self.x_axis.y,
119            self.x_axis.z,
120            self.y_axis.x,
121            self.y_axis.y,
122            self.y_axis.z,
123            self.z_axis.x,
124            self.z_axis.y,
125            self.z_axis.z,
126        ]
127    }
128
129    /// Creates a 3x3 matrix from a `[[f64; 3]; 3]` 3D array stored in column major order.
130    /// If your data is in row major order you will need to `transpose` the returned
131    /// matrix.
132    #[inline]
133    #[must_use]
134    pub const fn from_cols_array_2d(m: &[[f64; 3]; 3]) -> Self {
135        Self::from_cols(
136            DVec3::from_array(m[0]),
137            DVec3::from_array(m[1]),
138            DVec3::from_array(m[2]),
139        )
140    }
141
142    /// Creates a `[[f64; 3]; 3]` 3D array storing data in column major order.
143    /// If you require data in row major order `transpose` the matrix first.
144    #[inline]
145    #[must_use]
146    pub const fn to_cols_array_2d(&self) -> [[f64; 3]; 3] {
147        [
148            self.x_axis.to_array(),
149            self.y_axis.to_array(),
150            self.z_axis.to_array(),
151        ]
152    }
153
154    /// Creates a 3x3 matrix with its diagonal set to `diagonal` and all other entries set to 0.
155    #[doc(alias = "scale")]
156    #[inline]
157    #[must_use]
158    pub const fn from_diagonal(diagonal: DVec3) -> Self {
159        Self::new(
160            diagonal.x, 0.0, 0.0, 0.0, diagonal.y, 0.0, 0.0, 0.0, diagonal.z,
161        )
162    }
163
164    /// Creates a 3x3 matrix from a 4x4 matrix, discarding the 4th row and column.
165    #[inline]
166    #[must_use]
167    pub fn from_mat4(m: DMat4) -> Self {
168        Self::from_cols(
169            DVec3::from_vec4(m.x_axis),
170            DVec3::from_vec4(m.y_axis),
171            DVec3::from_vec4(m.z_axis),
172        )
173    }
174
175    /// Creates a 3x3 matrix from the minor of the given 4x4 matrix, discarding the `i`th column
176    /// and `j`th row.
177    ///
178    /// # Panics
179    ///
180    /// Panics if `i` or `j` is greater than 3.
181    #[inline]
182    #[must_use]
183    pub fn from_mat4_minor(m: DMat4, i: usize, j: usize) -> Self {
184        match (i, j) {
185            (0, 0) => Self::from_cols(m.y_axis.yzw(), m.z_axis.yzw(), m.w_axis.yzw()),
186            (0, 1) => Self::from_cols(m.y_axis.xzw(), m.z_axis.xzw(), m.w_axis.xzw()),
187            (0, 2) => Self::from_cols(m.y_axis.xyw(), m.z_axis.xyw(), m.w_axis.xyw()),
188            (0, 3) => Self::from_cols(m.y_axis.xyz(), m.z_axis.xyz(), m.w_axis.xyz()),
189            (1, 0) => Self::from_cols(m.x_axis.yzw(), m.z_axis.yzw(), m.w_axis.yzw()),
190            (1, 1) => Self::from_cols(m.x_axis.xzw(), m.z_axis.xzw(), m.w_axis.xzw()),
191            (1, 2) => Self::from_cols(m.x_axis.xyw(), m.z_axis.xyw(), m.w_axis.xyw()),
192            (1, 3) => Self::from_cols(m.x_axis.xyz(), m.z_axis.xyz(), m.w_axis.xyz()),
193            (2, 0) => Self::from_cols(m.x_axis.yzw(), m.y_axis.yzw(), m.w_axis.yzw()),
194            (2, 1) => Self::from_cols(m.x_axis.xzw(), m.y_axis.xzw(), m.w_axis.xzw()),
195            (2, 2) => Self::from_cols(m.x_axis.xyw(), m.y_axis.xyw(), m.w_axis.xyw()),
196            (2, 3) => Self::from_cols(m.x_axis.xyz(), m.y_axis.xyz(), m.w_axis.xyz()),
197            (3, 0) => Self::from_cols(m.x_axis.yzw(), m.y_axis.yzw(), m.z_axis.yzw()),
198            (3, 1) => Self::from_cols(m.x_axis.xzw(), m.y_axis.xzw(), m.z_axis.xzw()),
199            (3, 2) => Self::from_cols(m.x_axis.xyw(), m.y_axis.xyw(), m.z_axis.xyw()),
200            (3, 3) => Self::from_cols(m.x_axis.xyz(), m.y_axis.xyz(), m.z_axis.xyz()),
201            _ => panic!("index out of bounds"),
202        }
203    }
204
205    /// Creates a 3D rotation matrix from the given quaternion.
206    ///
207    /// # Panics
208    ///
209    /// Will panic if `rotation` is not normalized when `glam_assert` is enabled.
210    #[inline]
211    #[must_use]
212    pub fn from_quat(rotation: DQuat) -> Self {
213        glam_assert!(rotation.is_normalized());
214
215        let x2 = rotation.x + rotation.x;
216        let y2 = rotation.y + rotation.y;
217        let z2 = rotation.z + rotation.z;
218        let xx = rotation.x * x2;
219        let xy = rotation.x * y2;
220        let xz = rotation.x * z2;
221        let yy = rotation.y * y2;
222        let yz = rotation.y * z2;
223        let zz = rotation.z * z2;
224        let wx = rotation.w * x2;
225        let wy = rotation.w * y2;
226        let wz = rotation.w * z2;
227
228        Self::from_cols(
229            DVec3::new(1.0 - (yy + zz), xy + wz, xz - wy),
230            DVec3::new(xy - wz, 1.0 - (xx + zz), yz + wx),
231            DVec3::new(xz + wy, yz - wx, 1.0 - (xx + yy)),
232        )
233    }
234
235    /// Creates a 3D rotation matrix from a normalized rotation `axis` and `angle` (in
236    /// radians).
237    ///
238    /// # Panics
239    ///
240    /// Will panic if `axis` is not normalized when `glam_assert` is enabled.
241    #[inline]
242    #[must_use]
243    pub fn from_axis_angle(axis: DVec3, angle: f64) -> Self {
244        glam_assert!(axis.is_normalized());
245
246        let (sin, cos) = math::sin_cos(angle);
247        let (xsin, ysin, zsin) = axis.mul(sin).into();
248        let (x, y, z) = axis.into();
249        let (x2, y2, z2) = axis.mul(axis).into();
250        let omc = 1.0 - cos;
251        let xyomc = x * y * omc;
252        let xzomc = x * z * omc;
253        let yzomc = y * z * omc;
254        Self::from_cols(
255            DVec3::new(x2 * omc + cos, xyomc + zsin, xzomc - ysin),
256            DVec3::new(xyomc - zsin, y2 * omc + cos, yzomc + xsin),
257            DVec3::new(xzomc + ysin, yzomc - xsin, z2 * omc + cos),
258        )
259    }
260
261    /// Creates a 3D rotation matrix from the given euler rotation sequence and the angles (in
262    /// radians).
263    #[inline]
264    #[must_use]
265    pub fn from_euler(order: EulerRot, a: f64, b: f64, c: f64) -> Self {
266        Self::from_euler_angles(order, a, b, c)
267    }
268
269    /// Extract Euler angles with the given Euler rotation order.
270    ///
271    /// Note if the input matrix contains scales, shears, or other non-rotation transformations then
272    /// the resulting Euler angles will be ill-defined.
273    ///
274    /// # Panics
275    ///
276    /// Will panic if any input matrix column is not normalized when `glam_assert` is enabled.
277    #[inline]
278    #[must_use]
279    pub fn to_euler(&self, order: EulerRot) -> (f64, f64, f64) {
280        glam_assert!(
281            self.x_axis.is_normalized()
282                && self.y_axis.is_normalized()
283                && self.z_axis.is_normalized()
284        );
285        self.to_euler_angles(order)
286    }
287
288    /// Creates a 3D rotation matrix from `angle` (in radians) around the x axis.
289    #[inline]
290    #[must_use]
291    pub fn from_rotation_x(angle: f64) -> Self {
292        let (sina, cosa) = math::sin_cos(angle);
293        Self::from_cols(
294            DVec3::X,
295            DVec3::new(0.0, cosa, sina),
296            DVec3::new(0.0, -sina, cosa),
297        )
298    }
299
300    /// Creates a 3D rotation matrix from `angle` (in radians) around the y axis.
301    #[inline]
302    #[must_use]
303    pub fn from_rotation_y(angle: f64) -> Self {
304        let (sina, cosa) = math::sin_cos(angle);
305        Self::from_cols(
306            DVec3::new(cosa, 0.0, -sina),
307            DVec3::Y,
308            DVec3::new(sina, 0.0, cosa),
309        )
310    }
311
312    /// Creates a 3D rotation matrix from `angle` (in radians) around the z axis.
313    #[inline]
314    #[must_use]
315    pub fn from_rotation_z(angle: f64) -> Self {
316        let (sina, cosa) = math::sin_cos(angle);
317        Self::from_cols(
318            DVec3::new(cosa, sina, 0.0),
319            DVec3::new(-sina, cosa, 0.0),
320            DVec3::Z,
321        )
322    }
323
324    /// Creates an affine transformation matrix from the given 2D `translation`.
325    ///
326    /// The resulting matrix can be used to transform 2D points and vectors. See
327    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
328    #[inline]
329    #[must_use]
330    pub fn from_translation(translation: DVec2) -> Self {
331        Self::from_cols(
332            DVec3::X,
333            DVec3::Y,
334            DVec3::new(translation.x, translation.y, 1.0),
335        )
336    }
337
338    /// Creates an affine transformation matrix from the given 2D rotation `angle` (in
339    /// radians).
340    ///
341    /// The resulting matrix can be used to transform 2D points and vectors. See
342    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
343    #[inline]
344    #[must_use]
345    pub fn from_angle(angle: f64) -> Self {
346        let (sin, cos) = math::sin_cos(angle);
347        Self::from_cols(
348            DVec3::new(cos, sin, 0.0),
349            DVec3::new(-sin, cos, 0.0),
350            DVec3::Z,
351        )
352    }
353
354    /// Creates an affine transformation matrix from the given 2D `scale`, rotation `angle` (in
355    /// radians) and `translation`.
356    ///
357    /// The resulting matrix can be used to transform 2D points and vectors. See
358    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
359    #[inline]
360    #[must_use]
361    pub fn from_scale_angle_translation(scale: DVec2, angle: f64, translation: DVec2) -> Self {
362        let (sin, cos) = math::sin_cos(angle);
363        Self::from_cols(
364            DVec3::new(cos * scale.x, sin * scale.x, 0.0),
365            DVec3::new(-sin * scale.y, cos * scale.y, 0.0),
366            DVec3::new(translation.x, translation.y, 1.0),
367        )
368    }
369
370    /// Creates an affine transformation matrix from the given non-uniform 2D `scale`.
371    ///
372    /// The resulting matrix can be used to transform 2D points and vectors. See
373    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
374    ///
375    /// # Panics
376    ///
377    /// Will panic if all elements of `scale` are zero when `glam_assert` is enabled.
378    #[inline]
379    #[must_use]
380    pub fn from_scale(scale: DVec2) -> Self {
381        // Do not panic as long as any component is non-zero
382        glam_assert!(scale.cmpne(DVec2::ZERO).any());
383
384        Self::from_cols(
385            DVec3::new(scale.x, 0.0, 0.0),
386            DVec3::new(0.0, scale.y, 0.0),
387            DVec3::Z,
388        )
389    }
390
391    /// Creates an affine transformation matrix from the given 2x2 matrix.
392    ///
393    /// The resulting matrix can be used to transform 2D points and vectors. See
394    /// [`Self::transform_point2()`] and [`Self::transform_vector2()`].
395    #[inline]
396    pub fn from_mat2(m: DMat2) -> Self {
397        Self::from_cols((m.x_axis, 0.0).into(), (m.y_axis, 0.0).into(), DVec3::Z)
398    }
399
400    /// Creates a 3x3 matrix from the first 9 values in `slice`.
401    ///
402    /// # Panics
403    ///
404    /// Panics if `slice` is less than 9 elements long.
405    #[inline]
406    #[must_use]
407    pub const fn from_cols_slice(slice: &[f64]) -> Self {
408        Self::new(
409            slice[0], slice[1], slice[2], slice[3], slice[4], slice[5], slice[6], slice[7],
410            slice[8],
411        )
412    }
413
414    /// Writes the columns of `self` to the first 9 elements in `slice`.
415    ///
416    /// # Panics
417    ///
418    /// Panics if `slice` is less than 9 elements long.
419    #[inline]
420    pub fn write_cols_to_slice(&self, slice: &mut [f64]) {
421        slice[0] = self.x_axis.x;
422        slice[1] = self.x_axis.y;
423        slice[2] = self.x_axis.z;
424        slice[3] = self.y_axis.x;
425        slice[4] = self.y_axis.y;
426        slice[5] = self.y_axis.z;
427        slice[6] = self.z_axis.x;
428        slice[7] = self.z_axis.y;
429        slice[8] = self.z_axis.z;
430    }
431
432    /// Returns the matrix column for the given `index`.
433    ///
434    /// # Panics
435    ///
436    /// Panics if `index` is greater than 2.
437    #[inline]
438    #[must_use]
439    pub fn col(&self, index: usize) -> DVec3 {
440        match index {
441            0 => self.x_axis,
442            1 => self.y_axis,
443            2 => self.z_axis,
444            _ => panic!("index out of bounds"),
445        }
446    }
447
448    /// Returns a mutable reference to the matrix column for the given `index`.
449    ///
450    /// # Panics
451    ///
452    /// Panics if `index` is greater than 2.
453    #[inline]
454    pub fn col_mut(&mut self, index: usize) -> &mut DVec3 {
455        match index {
456            0 => &mut self.x_axis,
457            1 => &mut self.y_axis,
458            2 => &mut self.z_axis,
459            _ => panic!("index out of bounds"),
460        }
461    }
462
463    /// Returns the matrix row for the given `index`.
464    ///
465    /// # Panics
466    ///
467    /// Panics if `index` is greater than 2.
468    #[inline]
469    #[must_use]
470    pub fn row(&self, index: usize) -> DVec3 {
471        match index {
472            0 => DVec3::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
473            1 => DVec3::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
474            2 => DVec3::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
475            _ => panic!("index out of bounds"),
476        }
477    }
478
479    /// Returns `true` if, and only if, all elements are finite.
480    /// If any element is either `NaN`, positive or negative infinity, this will return `false`.
481    #[inline]
482    #[must_use]
483    pub fn is_finite(&self) -> bool {
484        self.x_axis.is_finite() && self.y_axis.is_finite() && self.z_axis.is_finite()
485    }
486
487    /// Returns `true` if any elements are `NaN`.
488    #[inline]
489    #[must_use]
490    pub fn is_nan(&self) -> bool {
491        self.x_axis.is_nan() || self.y_axis.is_nan() || self.z_axis.is_nan()
492    }
493
494    /// Returns the transpose of `self`.
495    #[inline]
496    #[must_use]
497    pub fn transpose(&self) -> Self {
498        Self {
499            x_axis: DVec3::new(self.x_axis.x, self.y_axis.x, self.z_axis.x),
500            y_axis: DVec3::new(self.x_axis.y, self.y_axis.y, self.z_axis.y),
501            z_axis: DVec3::new(self.x_axis.z, self.y_axis.z, self.z_axis.z),
502        }
503    }
504
505    /// Returns the diagonal of `self`.
506    #[inline]
507    #[must_use]
508    pub fn diagonal(&self) -> DVec3 {
509        DVec3::new(self.x_axis.x, self.y_axis.y, self.z_axis.z)
510    }
511
512    /// Returns the determinant of `self`.
513    #[inline]
514    #[must_use]
515    pub fn determinant(&self) -> f64 {
516        self.z_axis.dot(self.x_axis.cross(self.y_axis))
517    }
518
519    /// If `CHECKED` is true then if the determinant is zero this function will return a tuple
520    /// containing a zero matrix and false. If the determinant is non zero a tuple containing the
521    /// inverted matrix and true is returned.
522    ///
523    /// If `CHECKED` is false then the determinant is not checked and if it is zero the resulting
524    /// inverted matrix will be invalid. Will panic if the determinant of `self` is zero when
525    /// `glam_assert` is enabled.
526    ///
527    /// A tuple containing the inverted matrix and a bool is used instead of an option here as
528    /// regular Rust enums put the discriminant first which can result in a lot of padding if the
529    /// matrix is aligned.
530    #[inline(always)]
531    #[must_use]
532    fn inverse_checked<const CHECKED: bool>(&self) -> (Self, bool) {
533        let tmp0 = self.y_axis.cross(self.z_axis);
534        let tmp1 = self.z_axis.cross(self.x_axis);
535        let tmp2 = self.x_axis.cross(self.y_axis);
536        let det = self.z_axis.dot(tmp2);
537        if CHECKED {
538            if det == 0.0 {
539                return (Self::ZERO, false);
540            }
541        } else {
542            glam_assert!(det != 0.0);
543        }
544        let inv_det = DVec3::splat(det.recip());
545        (
546            Self::from_cols(tmp0.mul(inv_det), tmp1.mul(inv_det), tmp2.mul(inv_det)).transpose(),
547            true,
548        )
549    }
550
551    /// Returns the inverse of `self`.
552    ///
553    /// If the matrix is not invertible the returned matrix will be invalid.
554    ///
555    /// # Panics
556    ///
557    /// Will panic if the determinant of `self` is zero when `glam_assert` is enabled.
558    #[inline]
559    #[must_use]
560    pub fn inverse(&self) -> Self {
561        self.inverse_checked::<false>().0
562    }
563
564    /// Returns the inverse of `self` or `None` if the matrix is not invertible.
565    #[inline]
566    #[must_use]
567    pub fn try_inverse(&self) -> Option<Self> {
568        let (m, is_valid) = self.inverse_checked::<true>();
569        if is_valid {
570            Some(m)
571        } else {
572            None
573        }
574    }
575
576    /// Returns the inverse of `self` or `DMat3::ZERO` if the matrix is not invertible.
577    #[inline]
578    #[must_use]
579    pub fn inverse_or_zero(&self) -> Self {
580        self.inverse_checked::<true>().0
581    }
582
583    /// Transforms the given 2D vector as a point.
584    ///
585    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `1`.
586    ///
587    /// This method assumes that `self` contains a valid affine transform.
588    ///
589    /// # Panics
590    ///
591    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
592    #[inline]
593    #[must_use]
594    pub fn transform_point2(&self, rhs: DVec2) -> DVec2 {
595        glam_assert!(self.row(2).abs_diff_eq(DVec3::Z, 1e-6));
596        DMat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs + self.z_axis.xy()
597    }
598
599    /// Rotates the given 2D vector.
600    ///
601    /// This is the equivalent of multiplying `rhs` as a 3D vector where `z` is `0`.
602    ///
603    /// This method assumes that `self` contains a valid affine transform.
604    ///
605    /// # Panics
606    ///
607    /// Will panic if the 2nd row of `self` is not `(0, 0, 1)` when `glam_assert` is enabled.
608    #[inline]
609    #[must_use]
610    pub fn transform_vector2(&self, rhs: DVec2) -> DVec2 {
611        glam_assert!(self.row(2).abs_diff_eq(DVec3::Z, 1e-6));
612        DMat2::from_cols(self.x_axis.xy(), self.y_axis.xy()) * rhs
613    }
614
615    /// Creates a left-handed view matrix using a facing direction and an up direction.
616    ///
617    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=forward`.
618    ///
619    /// # Panics
620    ///
621    /// Will panic if `dir` or `up` are not normalized when `glam_assert` is enabled.
622    #[inline]
623    #[must_use]
624    pub fn look_to_lh(dir: DVec3, up: DVec3) -> Self {
625        Self::look_to_rh(-dir, up)
626    }
627
628    /// Creates a right-handed view matrix using a facing direction and an up direction.
629    ///
630    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=back`.
631    ///
632    /// # Panics
633    ///
634    /// Will panic if `dir` or `up` are not normalized when `glam_assert` is enabled.
635    #[inline]
636    #[must_use]
637    pub fn look_to_rh(dir: DVec3, up: DVec3) -> Self {
638        glam_assert!(dir.is_normalized());
639        glam_assert!(up.is_normalized());
640        let f = dir;
641        let s = f.cross(up).normalize();
642        let u = s.cross(f);
643
644        Self::from_cols(
645            DVec3::new(s.x, u.x, -f.x),
646            DVec3::new(s.y, u.y, -f.y),
647            DVec3::new(s.z, u.z, -f.z),
648        )
649    }
650
651    /// Creates a left-handed view matrix using a camera position, a focal point and an up
652    /// direction.
653    ///
654    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=forward`.
655    ///
656    /// # Panics
657    ///
658    /// Will panic if `up` is not normalized when `glam_assert` is enabled.
659    #[inline]
660    #[must_use]
661    pub fn look_at_lh(eye: DVec3, center: DVec3, up: DVec3) -> Self {
662        Self::look_to_lh(center.sub(eye).normalize(), up)
663    }
664
665    /// Creates a right-handed view matrix using a camera position, a focal point and an up
666    /// direction.
667    ///
668    /// For a view coordinate system with `+X=right`, `+Y=up` and `+Z=back`.
669    ///
670    /// # Panics
671    ///
672    /// Will panic if `up` is not normalized when `glam_assert` is enabled.
673    #[inline]
674    pub fn look_at_rh(eye: DVec3, center: DVec3, up: DVec3) -> Self {
675        Self::look_to_rh(center.sub(eye).normalize(), up)
676    }
677
678    /// Transforms a 3D vector.
679    #[inline]
680    #[must_use]
681    pub fn mul_vec3(&self, rhs: DVec3) -> DVec3 {
682        let mut res = self.x_axis.mul(rhs.x);
683        res = res.add(self.y_axis.mul(rhs.y));
684        res = res.add(self.z_axis.mul(rhs.z));
685        res
686    }
687
688    /// Transforms a 3D vector by the transpose of `self`.
689    #[inline]
690    #[must_use]
691    pub fn mul_transpose_vec3(&self, rhs: DVec3) -> DVec3 {
692        DVec3::new(
693            self.x_axis.dot(rhs),
694            self.y_axis.dot(rhs),
695            self.z_axis.dot(rhs),
696        )
697    }
698
699    /// Multiplies two 3x3 matrices.
700    #[inline]
701    #[must_use]
702    pub fn mul_mat3(&self, rhs: &Self) -> Self {
703        self.mul(rhs)
704    }
705
706    /// Adds two 3x3 matrices.
707    #[inline]
708    #[must_use]
709    pub fn add_mat3(&self, rhs: &Self) -> Self {
710        self.add(rhs)
711    }
712
713    /// Subtracts two 3x3 matrices.
714    #[inline]
715    #[must_use]
716    pub fn sub_mat3(&self, rhs: &Self) -> Self {
717        self.sub(rhs)
718    }
719
720    /// Multiplies a 3x3 matrix by a scalar.
721    #[inline]
722    #[must_use]
723    pub fn mul_scalar(&self, rhs: f64) -> Self {
724        Self::from_cols(
725            self.x_axis.mul(rhs),
726            self.y_axis.mul(rhs),
727            self.z_axis.mul(rhs),
728        )
729    }
730
731    /// Multiply `self` by a scaling vector `scale`.
732    /// This is faster than creating a whole diagonal scaling matrix and then multiplying that.
733    /// This operation is commutative.
734    #[inline]
735    #[must_use]
736    pub fn mul_diagonal_scale(&self, scale: DVec3) -> Self {
737        Self::from_cols(
738            self.x_axis * scale.x,
739            self.y_axis * scale.y,
740            self.z_axis * scale.z,
741        )
742    }
743
744    /// Divides a 3x3 matrix by a scalar.
745    #[inline]
746    #[must_use]
747    pub fn div_scalar(&self, rhs: f64) -> Self {
748        let rhs = DVec3::splat(rhs);
749        Self::from_cols(
750            self.x_axis.div(rhs),
751            self.y_axis.div(rhs),
752            self.z_axis.div(rhs),
753        )
754    }
755
756    /// Returns true if the absolute difference of all elements between `self` and `rhs`
757    /// is less than or equal to `max_abs_diff`.
758    ///
759    /// This can be used to compare if two matrices contain similar elements. It works best
760    /// when comparing with a known value. The `max_abs_diff` that should be used used
761    /// depends on the values being compared against.
762    ///
763    /// For more see
764    /// [comparing floating point numbers](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/).
765    #[inline]
766    #[must_use]
767    pub fn abs_diff_eq(&self, rhs: Self, max_abs_diff: f64) -> bool {
768        self.x_axis.abs_diff_eq(rhs.x_axis, max_abs_diff)
769            && self.y_axis.abs_diff_eq(rhs.y_axis, max_abs_diff)
770            && self.z_axis.abs_diff_eq(rhs.z_axis, max_abs_diff)
771    }
772
773    /// Takes the absolute value of each element in `self`
774    #[inline]
775    #[must_use]
776    pub fn abs(&self) -> Self {
777        Self::from_cols(self.x_axis.abs(), self.y_axis.abs(), self.z_axis.abs())
778    }
779
780    #[inline]
781    pub fn as_mat3(&self) -> Mat3 {
782        Mat3::from_cols(
783            self.x_axis.as_vec3(),
784            self.y_axis.as_vec3(),
785            self.z_axis.as_vec3(),
786        )
787    }
788}
789
790impl Default for DMat3 {
791    #[inline]
792    fn default() -> Self {
793        Self::IDENTITY
794    }
795}
796
797impl Add for DMat3 {
798    type Output = Self;
799    #[inline]
800    fn add(self, rhs: Self) -> Self {
801        Self::from_cols(
802            self.x_axis.add(rhs.x_axis),
803            self.y_axis.add(rhs.y_axis),
804            self.z_axis.add(rhs.z_axis),
805        )
806    }
807}
808
809impl Add<&Self> for DMat3 {
810    type Output = Self;
811    #[inline]
812    fn add(self, rhs: &Self) -> Self {
813        self.add(*rhs)
814    }
815}
816
817impl Add<&DMat3> for &DMat3 {
818    type Output = DMat3;
819    #[inline]
820    fn add(self, rhs: &DMat3) -> DMat3 {
821        (*self).add(*rhs)
822    }
823}
824
825impl Add<DMat3> for &DMat3 {
826    type Output = DMat3;
827    #[inline]
828    fn add(self, rhs: DMat3) -> DMat3 {
829        (*self).add(rhs)
830    }
831}
832
833impl AddAssign for DMat3 {
834    #[inline]
835    fn add_assign(&mut self, rhs: Self) {
836        *self = self.add(rhs);
837    }
838}
839
840impl AddAssign<&Self> for DMat3 {
841    #[inline]
842    fn add_assign(&mut self, rhs: &Self) {
843        self.add_assign(*rhs);
844    }
845}
846
847impl Sub for DMat3 {
848    type Output = Self;
849    #[inline]
850    fn sub(self, rhs: Self) -> Self {
851        Self::from_cols(
852            self.x_axis.sub(rhs.x_axis),
853            self.y_axis.sub(rhs.y_axis),
854            self.z_axis.sub(rhs.z_axis),
855        )
856    }
857}
858
859impl Sub<&Self> for DMat3 {
860    type Output = Self;
861    #[inline]
862    fn sub(self, rhs: &Self) -> Self {
863        self.sub(*rhs)
864    }
865}
866
867impl Sub<&DMat3> for &DMat3 {
868    type Output = DMat3;
869    #[inline]
870    fn sub(self, rhs: &DMat3) -> DMat3 {
871        (*self).sub(*rhs)
872    }
873}
874
875impl Sub<DMat3> for &DMat3 {
876    type Output = DMat3;
877    #[inline]
878    fn sub(self, rhs: DMat3) -> DMat3 {
879        (*self).sub(rhs)
880    }
881}
882
883impl SubAssign for DMat3 {
884    #[inline]
885    fn sub_assign(&mut self, rhs: Self) {
886        *self = self.sub(rhs);
887    }
888}
889
890impl SubAssign<&Self> for DMat3 {
891    #[inline]
892    fn sub_assign(&mut self, rhs: &Self) {
893        self.sub_assign(*rhs);
894    }
895}
896
897impl Neg for DMat3 {
898    type Output = Self;
899    #[inline]
900    fn neg(self) -> Self::Output {
901        Self::from_cols(self.x_axis.neg(), self.y_axis.neg(), self.z_axis.neg())
902    }
903}
904
905impl Neg for &DMat3 {
906    type Output = DMat3;
907    #[inline]
908    fn neg(self) -> DMat3 {
909        (*self).neg()
910    }
911}
912
913impl Mul for DMat3 {
914    type Output = Self;
915    #[inline]
916    fn mul(self, rhs: Self) -> Self {
917        Self::from_cols(
918            self.mul(rhs.x_axis),
919            self.mul(rhs.y_axis),
920            self.mul(rhs.z_axis),
921        )
922    }
923}
924
925impl Mul<&Self> for DMat3 {
926    type Output = Self;
927    #[inline]
928    fn mul(self, rhs: &Self) -> Self {
929        self.mul(*rhs)
930    }
931}
932
933impl Mul<&DMat3> for &DMat3 {
934    type Output = DMat3;
935    #[inline]
936    fn mul(self, rhs: &DMat3) -> DMat3 {
937        (*self).mul(*rhs)
938    }
939}
940
941impl Mul<DMat3> for &DMat3 {
942    type Output = DMat3;
943    #[inline]
944    fn mul(self, rhs: DMat3) -> DMat3 {
945        (*self).mul(rhs)
946    }
947}
948
949impl MulAssign for DMat3 {
950    #[inline]
951    fn mul_assign(&mut self, rhs: Self) {
952        *self = self.mul(rhs);
953    }
954}
955
956impl MulAssign<&Self> for DMat3 {
957    #[inline]
958    fn mul_assign(&mut self, rhs: &Self) {
959        self.mul_assign(*rhs);
960    }
961}
962
963impl Mul<DVec3> for DMat3 {
964    type Output = DVec3;
965    #[inline]
966    fn mul(self, rhs: DVec3) -> Self::Output {
967        self.mul_vec3(rhs)
968    }
969}
970
971impl Mul<&DVec3> for DMat3 {
972    type Output = DVec3;
973    #[inline]
974    fn mul(self, rhs: &DVec3) -> DVec3 {
975        self.mul(*rhs)
976    }
977}
978
979impl Mul<&DVec3> for &DMat3 {
980    type Output = DVec3;
981    #[inline]
982    fn mul(self, rhs: &DVec3) -> DVec3 {
983        (*self).mul(*rhs)
984    }
985}
986
987impl Mul<DVec3> for &DMat3 {
988    type Output = DVec3;
989    #[inline]
990    fn mul(self, rhs: DVec3) -> DVec3 {
991        (*self).mul(rhs)
992    }
993}
994
995impl Mul<DMat3> for f64 {
996    type Output = DMat3;
997    #[inline]
998    fn mul(self, rhs: DMat3) -> Self::Output {
999        rhs.mul_scalar(self)
1000    }
1001}
1002
1003impl Mul<&DMat3> for f64 {
1004    type Output = DMat3;
1005    #[inline]
1006    fn mul(self, rhs: &DMat3) -> DMat3 {
1007        self.mul(*rhs)
1008    }
1009}
1010
1011impl Mul<&DMat3> for &f64 {
1012    type Output = DMat3;
1013    #[inline]
1014    fn mul(self, rhs: &DMat3) -> DMat3 {
1015        (*self).mul(*rhs)
1016    }
1017}
1018
1019impl Mul<DMat3> for &f64 {
1020    type Output = DMat3;
1021    #[inline]
1022    fn mul(self, rhs: DMat3) -> DMat3 {
1023        (*self).mul(rhs)
1024    }
1025}
1026
1027impl Mul<f64> for DMat3 {
1028    type Output = Self;
1029    #[inline]
1030    fn mul(self, rhs: f64) -> Self {
1031        self.mul_scalar(rhs)
1032    }
1033}
1034
1035impl Mul<&f64> for DMat3 {
1036    type Output = Self;
1037    #[inline]
1038    fn mul(self, rhs: &f64) -> Self {
1039        self.mul(*rhs)
1040    }
1041}
1042
1043impl Mul<&f64> for &DMat3 {
1044    type Output = DMat3;
1045    #[inline]
1046    fn mul(self, rhs: &f64) -> DMat3 {
1047        (*self).mul(*rhs)
1048    }
1049}
1050
1051impl Mul<f64> for &DMat3 {
1052    type Output = DMat3;
1053    #[inline]
1054    fn mul(self, rhs: f64) -> DMat3 {
1055        (*self).mul(rhs)
1056    }
1057}
1058
1059impl MulAssign<f64> for DMat3 {
1060    #[inline]
1061    fn mul_assign(&mut self, rhs: f64) {
1062        *self = self.mul(rhs);
1063    }
1064}
1065
1066impl MulAssign<&f64> for DMat3 {
1067    #[inline]
1068    fn mul_assign(&mut self, rhs: &f64) {
1069        self.mul_assign(*rhs);
1070    }
1071}
1072
1073impl Div<DMat3> for f64 {
1074    type Output = DMat3;
1075    #[inline]
1076    fn div(self, rhs: DMat3) -> Self::Output {
1077        rhs.div_scalar(self)
1078    }
1079}
1080
1081impl Div<&DMat3> for f64 {
1082    type Output = DMat3;
1083    #[inline]
1084    fn div(self, rhs: &DMat3) -> DMat3 {
1085        self.div(*rhs)
1086    }
1087}
1088
1089impl Div<&DMat3> for &f64 {
1090    type Output = DMat3;
1091    #[inline]
1092    fn div(self, rhs: &DMat3) -> DMat3 {
1093        (*self).div(*rhs)
1094    }
1095}
1096
1097impl Div<DMat3> for &f64 {
1098    type Output = DMat3;
1099    #[inline]
1100    fn div(self, rhs: DMat3) -> DMat3 {
1101        (*self).div(rhs)
1102    }
1103}
1104
1105impl Div<f64> for DMat3 {
1106    type Output = Self;
1107    #[inline]
1108    fn div(self, rhs: f64) -> Self {
1109        self.div_scalar(rhs)
1110    }
1111}
1112
1113impl Div<&f64> for DMat3 {
1114    type Output = Self;
1115    #[inline]
1116    fn div(self, rhs: &f64) -> Self {
1117        self.div(*rhs)
1118    }
1119}
1120
1121impl Div<&f64> for &DMat3 {
1122    type Output = DMat3;
1123    #[inline]
1124    fn div(self, rhs: &f64) -> DMat3 {
1125        (*self).div(*rhs)
1126    }
1127}
1128
1129impl Div<f64> for &DMat3 {
1130    type Output = DMat3;
1131    #[inline]
1132    fn div(self, rhs: f64) -> DMat3 {
1133        (*self).div(rhs)
1134    }
1135}
1136
1137impl DivAssign<f64> for DMat3 {
1138    #[inline]
1139    fn div_assign(&mut self, rhs: f64) {
1140        *self = self.div(rhs);
1141    }
1142}
1143
1144impl DivAssign<&f64> for DMat3 {
1145    #[inline]
1146    fn div_assign(&mut self, rhs: &f64) {
1147        self.div_assign(*rhs);
1148    }
1149}
1150
1151impl Sum<Self> for DMat3 {
1152    fn sum<I>(iter: I) -> Self
1153    where
1154        I: Iterator<Item = Self>,
1155    {
1156        iter.fold(Self::ZERO, Self::add)
1157    }
1158}
1159
1160impl<'a> Sum<&'a Self> for DMat3 {
1161    fn sum<I>(iter: I) -> Self
1162    where
1163        I: Iterator<Item = &'a Self>,
1164    {
1165        iter.fold(Self::ZERO, |a, &b| Self::add(a, b))
1166    }
1167}
1168
1169impl Product for DMat3 {
1170    fn product<I>(iter: I) -> Self
1171    where
1172        I: Iterator<Item = Self>,
1173    {
1174        iter.fold(Self::IDENTITY, Self::mul)
1175    }
1176}
1177
1178impl<'a> Product<&'a Self> for DMat3 {
1179    fn product<I>(iter: I) -> Self
1180    where
1181        I: Iterator<Item = &'a Self>,
1182    {
1183        iter.fold(Self::IDENTITY, |a, &b| Self::mul(a, b))
1184    }
1185}
1186
1187impl PartialEq for DMat3 {
1188    #[inline]
1189    fn eq(&self, rhs: &Self) -> bool {
1190        self.x_axis.eq(&rhs.x_axis) && self.y_axis.eq(&rhs.y_axis) && self.z_axis.eq(&rhs.z_axis)
1191    }
1192}
1193
1194impl AsRef<[f64; 9]> for DMat3 {
1195    #[inline]
1196    fn as_ref(&self) -> &[f64; 9] {
1197        unsafe { &*(self as *const Self as *const [f64; 9]) }
1198    }
1199}
1200
1201impl AsMut<[f64; 9]> for DMat3 {
1202    #[inline]
1203    fn as_mut(&mut self) -> &mut [f64; 9] {
1204        unsafe { &mut *(self as *mut Self as *mut [f64; 9]) }
1205    }
1206}
1207
1208impl fmt::Debug for DMat3 {
1209    fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
1210        fmt.debug_struct(stringify!(DMat3))
1211            .field("x_axis", &self.x_axis)
1212            .field("y_axis", &self.y_axis)
1213            .field("z_axis", &self.z_axis)
1214            .finish()
1215    }
1216}
1217
1218impl fmt::Display for DMat3 {
1219    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
1220        if let Some(p) = f.precision() {
1221            write!(
1222                f,
1223                "[{:.*}, {:.*}, {:.*}]",
1224                p, self.x_axis, p, self.y_axis, p, self.z_axis
1225            )
1226        } else {
1227            write!(f, "[{}, {}, {}]", self.x_axis, self.y_axis, self.z_axis)
1228        }
1229    }
1230}
glam/f64/dmat3.rs

glam/f64/
dmat3.rs
