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wgpu-matrix
Advanced tools
Fast 3d math library for webgpu
ortho
, perspective
, frustum
are differentcompare
// wgpu-matrix
const t = mat4.translation([x, y, z]);
const p = mat4.perspective(fov, aspect, near, far);
const r = mat4.rotationX(rad);
// gl-matrix
const t = mat4.create();
mat4.fromTranslation(t, [x, y, z]);
const p = mat4.create();
mat4.perspective(p, fov, aspect, near, far);
const r = mat4.create();
mat4.fromXRotation(r, rad);
note that if you want to pre-create matrices you can still do this in wgpu-matrix
const t = mat4.create();
mat4.translation([x, y, z], t);
const p = mat4.create();
mat4.perspective(fov, aspect, near, far, p);
const r = mat4.create();
mat4.rotationX(rad, r);
import {
vec3,
mat4,
} from 'https://wgpu-matrix.org/dist/3.x/wgpu-matrix.module.js';
const fov = 60 * Math.PI / 180
const aspect = width / height;
const near = 0.1;
const far = 1000;
const perspective = mat4.perspective(fov, aspect, near, far);
const eye = [3, 5, 10];
const target = [0, 4, 0];
const up = [0, 1, 0];
const view = mat4.lookAt(eye, target, up);
Note: for translation, rotation, and scaling there are 2 versions of each function. One generates a translation, rotation, or scaling matrix. The other translates, rotates, or scales a matrix.
const t = mat4.translation([1, 2, 3]); // a translation matrix
const r = mat4.rotationX(Math.PI * 0.5); // a rotation matrix
const s = mat4.scaling([1, 2, 3]); // a scaling matrix
const m = mat4.identity();
const t = mat4.translate(m, [1, 2, 3]); // m * translation([1, 2, 3])
const r = mat4.rotateX(m, Math.PI * 0.5); // m * rotationX(Math.PI * 0.5)
const s = mat4.scale(m, [1, 2, 3]); // m * scaling([1, 2, 3])
Functions take an optional destination to hold the result.
const m = mat4.create(); // m = new mat4
mat4.identity(m); // m = identity
mat4.translate(m, [1, 2, 3], m); // m *= translation([1, 2, 3])
mat4.rotateX(m, Math.PI * 0.5, m); // m *= rotationX(Math.PI * 0.5)
mat4.scale(m, [1, 2, 3], m); // m *= scaling([1, 2, 3])
There is also the minified version
import {
vec3,
mat4,
} from 'https://wgpu-matrix.org/dist/3.x/wgpu-matrix.module.min.js';
// ... etc ...
and a UMD version
<script src="https://wgpu-matrix.org/dist/3.x/wgpu-matrix.js"></script>
<script>
const { mat4, vec3 } = wgpuMatrix;
const m = mat4.identity();
...
</script>
or UDM min version
<script src="https://wgpu-matrix.org/dist/3.x/wgpu-matrix.min.js"></script>
...
or via npm
npm install --save wgpu-matrix
then using a build process
import {vec3, mat3} from 'wgpu-matrix';
// ... etc ...
Examples:
const view = mat4.lookAt( // view is Float32Array
[10, 20, 30], // position
[0, 5, 0], // target
[0, 1, 0], // up
);
const view2 = mat4.lookAt( // view2 is Float32Array
new Float32Array([10, 20, 30]), // position
new Float64Array([0, 5, 0], // target
[0, 1, 0], // up
);
const a = vec2.add([1, 2], [3, 4]); // a is Float32Array
const b = vec2.add([1, 2], [3, 4], [0, 0]); // b is number[]
const j = vec2d.add([1, 2], [3, 4]); // j is Float64Array
const k = vec2d.add([1, 2], [3, 4], [0, 0]); // b is number[]
const f32 = new Float32Array(2);
const x = vec2d.add([1, 2], [3, 4]); // x is number[]
const y = vec2d.add([1, 2], [3, 4], f32); // y is Float32Array
etc...
Note: You're unlikely to need any thing except mat3
, mat4
, quat
,
vec2
, vec3
, and vec4
but, there are 3 sets of functions,
each one returning a different default
mat4.identity() // returns Float32Array
mat4d.identity() // returns Float64Array
mat4n.identity() // returns number[]
Similarly there's mat3d
, mat3n
, quatd
, quatn
,
vec2d
, vec2n
, vec3d
, vec3n
, vec4d
, vec4n
.
Just to be clear, identity
, like most functions, takes a destination so
const f32 = new Float32Array(16);
const f64 = new Float64Array(16);
const arr = new Array<number>(16).fill(0);
mat4.identity() // returns Float32Array
mat4.identity(f32) // returns Float32Array (f32)
mat4.identity(f64) // returns Float64Array (f64)
mat4.identity(arr) // returns number[] (arr)
mat4d.identity() // returns Float64Array
mat4d.identity(f32) // returns Float32Array (f32)
mat4d.identity(f64) // returns Float64Array (f64)
mat4d.identity(arr) // returns number[] (arr)
mat4n.identity() // returns number[]
mat4n.identity(f32) // returns Float32Array (f32)
mat4n.identity(f64) // returns Float64Array (f64)
mat4n.identity(arr) // returns number[] (arr)
The only difference between the sets of functions is what type they default to returning.
mat4.perspective
,
mat4.ortho
, and
mat4.frustum
all return matrices with Z clip space from 0 to 1 (unlike most WebGL matrix libraries which return -1 to 1)
mat4.create
makes an all zero matrix if passed no parameters.
If you want an identity matrix call mat4.identity
mat3
uses the space of 12 elements
// a mat3
[
xx, xy, xz, ?
yx, yy, yz, ?
zx, zy, zz, ?
]
This is because WebGPU requires mat3s to be in this format and since this library is for WebGPU it makes sense to match so you can manipulate mat3s in TypeArrays directly.
vec3
in this library uses 3 floats per but be aware that an array of
vec3
in a Uniform Block or other structure in WGSL, each vec3 is
padded to 4 floats! In other words, if you declare
struct Foo {
bar: vec3<f32>[3];
};
then bar[0] is at byte offset 0, bar[1] at byte offset 16, bar[2] at byte offset 32.
See the WGSL spec on alignment and size.
WebGPU follows the same conventions as OpenGL, Vulkan, Metal for matrices. Some people call this "column major". The issue is the columns of a traditional "math" matrix are stored as rows when declaring a matrix in code.
[
x1, x2, x3, x4, // <- column 0
y1, y2, y3, y4, // <- column 1
z1, z2, z3, z4, // <- column 2
w1, w2, w3, w4, // <- column 3
]
To put it another way, the translation vector is in elements 12, 13, 14
[
xx, xy, xz, 0, // <- x-axis
yx, yy, yz, 0, // <- y-axis
zx, zy, zz, 0, // <- z-axis
tx, ty, tz, 1, // <- translation
]
This issue has confused programmers since at least the early 90s 😌
Most functions take an optional destination as the last argument. If you don't supply it, a new one (vector, matrix) will be created for you.
// convenient usage
const persp = mat4.perspective(fov, aspect, near, far);
const camera = mat4.lookAt(eye, target, up);
const view = mat4.inverse(camera);
// performant usage
// at init time
const persp = mat4.create();
const camera = mat4.create();
const view = mat4.create();
// at usage time
mat4.perspective(fov, aspect, near, far, persp);
mat4.lookAt(eye, target, up, camera);
mat4.inverse(camera, view);
For me, most of the stuff I do in WebGPU, the supposed performance I might lose from using the convenient style is so small as to be unmeasurable. I'd prefer to stay convenient and then, if and only if I find a performance issue, then I might bother to switch to the performant style.
As the saying goes premature optimization is the root of all evil. 😉
In JavaScript there should be no difference in the API except for the removable of setDefaultType
.
In TypeScript, 3.x should mostly be type compatible with 2.x. 3.x is an attempt to fix the casting that was necessary in 2.x.
// 2.x
device.queue.writeData(buffer, 0, mat4.identity() as Float32Array); // sadness! 😭
// 3.x
device.queue.writeData(buffer, 0, mat4.identity()); // Yay! 🎉
In TypeScript the differences are as follows
In 3.x each function has a default type but if you pass it a destination it returns the type of the destination
mat4.identity() // returns Float32Array
mat4.identity(new Float32Array(16)); // returns Float32Array
mat4.identity(new Float64Array(16)); // returns Float64Array
mat4.identity(new Array(16)); // returns number[]
const a: Mat4 = ...; // a = Float32Array
const b: Mat4d = ...; // b = Float64Array
const c: Mat4n = ...; // c = number[]
This is means code like this
const position: Mat4 = [10, 20, 30];
No longer works because Mat4
is a Float32Array
.
BUT, functions take any of the normal types as an argument just like they used to
const position = [10, 20, 30]; // number[]
const target = vec3.create(1, 2, 3); // Float32Array
const up = new Float64Array([0, 1, 0]); // Float64Array
// Works fine, even those types are different, just like 2.x did
const view = mat4.lookAt(position, target, up); // Float32Array
If you really want types for each concrete type there's
Float32Array
types: Mat3
, Mat4
, Quat
, Vec2
, Vec3
, Vec4
Float64Array
types: Mat3d
, Mat4d
, Quatd
, Vec2d
, Vec3d
, Vec4d
,number[]
types: Mat3n
, Mat4n
, Quatn
, Vec2n
, Vec3n
, Vec4n
mat4.identity() // returns Float32Array
mat4d.identity() // returns Float64Array
mat4n.identity() // returns number[]
Similarly there's mat3d
, mat3n
, quatd
, quatn
,
vec2d
, vec2n
, vec3d
, vec3n
, vec4d
, vec4n
.
Note: that in general you're unlikely to need any of these. Just use the same ones you were using in 2.x
mat4.lookAt
changed from a "camera matrix" to a "view matrix" (same as gluLookAt).
If you want a matrix that orients an something in world space see
mat4.aim
.
Sorry about this change but people are used to lookAt making a a view matrix
and it seemed prudent to make this change now and save more people from
frustration going forward.git clone https://github.com/greggman/wgpu-matrix.git
cd wgpu-matrix
npm i
npm run build
npm test
You can run tests in the browser by starting a local server
npx servez
Now go to wherever your server serves pages. In the case of servez
that's
probably http://localhost:8080/test/.
By default the tests test the minified version. To test the source use src=true
as in http://localhost:8080/test/?src=true.
To limit which tests are run use grep=<regex>
. For example
http://localhost:8080/test/?src=true&grep=mat3.*?translate
runs only tests with mat3
followed by translate
in the name of test.
FAQs
fast matrix math library for WebGPU
The npm package wgpu-matrix receives a total of 3,670 weekly downloads. As such, wgpu-matrix popularity was classified as popular.
We found that wgpu-matrix demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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