typegpu
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A thin layer between JS and WebGPU/WGSL that improves development experience and allows for faster iteration.
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implementation\n (matrix, vector) => ({\n value: `(${\n (mat4x4f.translation(vector as unknown as v3f) as unknown as Snippet)\n .value\n } * ${matrix.value})`,\n dataType: matrix.dataType,\n }),\n 'translate4',\n);\n\n/**\n * Scales the given 4-by-4 matrix in each dimension by an amount given by the corresponding entry in the given vector.\n * @param {m4x4f} matrix - The matrix to be modified.\n * @param {v3f} vector - A vector of three entries specifying the factor by which to scale in each dimension.\n * @returns {m4x4f} The scaled matrix.\n */\nexport const scale4 = createDualImpl(\n // CPU implementation\n (matrix: m4x4f, vector: v3f) => {\n return mul(mat4x4f.scaling(vector), matrix);\n },\n // GPU implementation\n (matrix, vector) => ({\n value: `(${\n (mat4x4f.scaling(vector as unknown as v3f) as unknown as Snippet)\n .value\n } * ${matrix.value})`,\n dataType: matrix.dataType,\n }),\n 'scale4',\n);\n\n/**\n * Rotates the given 4-by-4 matrix around the x-axis by the given angle.\n * @param {m4x4f} matrix - The matrix to be modified.\n * @param {number} angle - The angle by which to rotate (in radians).\n * @returns {m4x4f} The rotated matrix.\n */\nexport const rotateX4 = createDualImpl(\n // CPU implementation\n (matrix: m4x4f, angle: number) => {\n return mul(mat4x4f.rotationX(angle), matrix);\n },\n // GPU implementation\n (matrix, angle) => ({\n value: `(${\n (mat4x4f.rotationX(angle as unknown as number) as unknown as Snippet)\n .value\n } * ${matrix.value})`,\n dataType: matrix.dataType,\n }),\n 'rotateX4',\n);\n\n/**\n * Rotates the given 4-by-4 matrix around the y-axis by the given angle.\n * @param {m4x4f} matrix - The matrix to be modified.\n * @param {number} angle - The angle by which to rotate (in radians).\n * @returns {m4x4f} The rotated matrix.\n */\nexport const rotateY4 = createDualImpl(\n // CPU implementation\n (matrix: m4x4f, angle: number) => {\n return mul(mat4x4f.rotationY(angle), matrix);\n },\n // GPU implementation\n (matrix, angle) => ({\n value: `(${\n (mat4x4f.rotationY(angle as unknown as number) as unknown as Snippet)\n .value\n } * ${matrix.value})`,\n dataType: matrix.dataType,\n }),\n 'rotateY4',\n);\n\n/**\n * Rotates the given 4-by-4 matrix around the z-axis by the given angle.\n * @param {m4x4f} matrix - The matrix to be modified.\n * @param {number} angle - The angle by which to rotate (in radians).\n * @returns {m4x4f} The rotated matrix.\n */\nexport const rotateZ4 = createDualImpl(\n // CPU implementation\n (matrix: m4x4f, angle: number) => {\n return mul(mat4x4f.rotationZ(angle), matrix);\n },\n // GPU implementation\n (matrix, angle) => ({\n value: `(${\n (mat4x4f.rotationZ(angle as unknown as number) as unknown as Snippet)\n .value\n } * ${matrix.value})`,\n dataType: matrix.dataType,\n }),\n 'rotateZ4',\n);\n","import { snip, type Snippet } from '../data/dataTypes.ts';\nimport { bool, f32 } from '../data/numeric.ts';\nimport { vec2b, vec3b, vec4b } from '../data/vector.ts';\nimport { VectorOps } from '../data/vectorOps.ts';\nimport {\n type AnyBooleanVecInstance,\n type AnyFloatVecInstance,\n type AnyNumericVecInstance,\n type AnyVec2Instance,\n type AnyVec3Instance,\n type AnyVecInstance,\n isVecInstance,\n type v2b,\n type v3b,\n type v4b,\n} from '../data/wgslTypes.ts';\nimport { createDualImpl } from '../shared/generators.ts';\nimport { isSnippetNumeric, sub } from './numeric.ts';\n\nfunction correspondingBooleanVectorSchema(value: Snippet) {\n if (value.dataType.type.includes('2')) {\n return vec2b;\n }\n if (value.dataType.type.includes('3')) {\n return vec3b;\n }\n return vec4b;\n}\n\n// comparison\n\n/**\n * Checks whether `lhs == rhs` on all components.\n * Equivalent to `all(eq(lhs, rhs))`.\n * @example\n * allEq(vec2f(0.0, 1.0), vec2f(0.0, 2.0)) // returns false\n * allEq(vec3u(0, 1, 2), vec3u(0, 1, 2)) // returns true\n */\nexport const allEq = createDualImpl(\n // CPU implementation\n <T extends AnyVecInstance>(lhs: T, rhs: T) => all(eq(lhs, rhs)),\n // GPU implementation\n (lhs, rhs) => snip(`all(${lhs.value} == ${rhs.value})`, bool),\n 'allEq',\n);\n\n/**\n * Checks **component-wise** whether `lhs == rhs`.\n * This function does **not** return `bool`, for that use-case, wrap the result in `all`, or use `allEq`.\n * @example\n * eq(vec2f(0.0, 1.0), vec2f(0.0, 2.0)) // returns vec2b(true, false)\n * eq(vec3u(0, 1, 2), vec3u(2, 1, 0)) // returns vec3b(false, true, false)\n * all(eq(vec4i(4, 3, 2, 1), vec4i(4, 3, 2, 1))) // returns true\n * allEq(vec4i(4, 3, 2, 1), vec4i(4, 3, 2, 1)) // returns true\n */\nexport const eq = createDualImpl(\n // CPU implementation\n <T extends AnyVecInstance>(lhs: T, rhs: T) =>\n VectorOps.eq[lhs.kind](lhs, rhs),\n // GPU implementation\n (lhs, rhs) =>\n snip(\n `(${lhs.value} == ${rhs.value})`,\n correspondingBooleanVectorSchema(lhs),\n ),\n 'eq',\n);\n\n/**\n * Checks **component-wise** whether `lhs != rhs`.\n * This function does **not** return `bool`, for that use-case, wrap the result in `any`.\n * @example\n * ne(vec2f(0.0, 1.0), vec2f(0.0, 2.0)) // returns vec2b(false, true)\n * ne(vec3u(0, 1, 2), vec3u(2, 1, 0)) // returns vec3b(true, false, true)\n * any(ne(vec4i(4, 3, 2, 1), vec4i(4, 2, 2, 1))) // returns true\n */\nexport const ne = createDualImpl(\n // CPU implementation\n <T extends AnyVecInstance>(lhs: T, rhs: T) => not(eq(lhs, rhs)),\n // GPU implementation\n (lhs, rhs) =>\n snip(\n `(${lhs.value} != ${rhs.value})`,\n correspondingBooleanVectorSchema(lhs),\n ),\n 'ne',\n);\n\n/**\n * Checks **component-wise** whether `lhs < rhs`.\n * This function does **not** return `bool`, for that use-case, wrap the result in `all`.\n * @example\n * lt(vec2f(0.0, 0.0), vec2f(0.0, 1.0)) // returns vec2b(false, true)\n * lt(vec3u(0, 1, 2), vec3u(2, 1, 0)) // returns vec3b(true, false, false)\n * all(lt(vec4i(1, 2, 3, 4), vec4i(2, 3, 4, 5))) // returns true\n */\nexport const lt = createDualImpl(\n // CPU implementation\n <T extends AnyNumericVecInstance>(lhs: T, rhs: T) =>\n VectorOps.lt[lhs.kind](lhs, rhs),\n // GPU implementation\n (lhs, rhs) =>\n snip(\n `(${lhs.value} < ${rhs.value})`,\n correspondingBooleanVectorSchema(lhs),\n ),\n 'lt',\n);\n\n/**\n * Checks **component-wise** whether `lhs <= rhs`.\n * This function does **not** return `bool`, for that use-case, wrap the result in `all`.\n * @example\n * le(vec2f(0.0, 0.0), vec2f(0.0, 1.0)) // returns vec2b(true, true)\n * le(vec3u(0, 1, 2), vec3u(2, 1, 0)) // returns vec3b(true, true, false)\n * all(le(vec4i(1, 2, 3, 4), vec4i(2, 3, 3, 5))) // returns true\n */\nexport const le = createDualImpl(\n // CPU implementation\n <T extends AnyNumericVecInstance>(lhs: T, rhs: T) =>\n or(lt(lhs, rhs), eq(lhs, rhs)),\n // GPU implementation\n (lhs, rhs) =>\n snip(\n `(${lhs.value} <= ${rhs.value})`,\n correspondingBooleanVectorSchema(lhs),\n ),\n 'le',\n);\n\n/**\n * Checks **component-wise** whether `lhs > rhs`.\n * This function does **not** return `bool`, for that use-case, wrap the result in `all`.\n * @example\n * gt(vec2f(0.0, 0.0), vec2f(0.0, 1.0)) // returns vec2b(false, false)\n * gt(vec3u(0, 1, 2), vec3u(2, 1, 0)) // returns vec3b(false, false, true)\n * all(gt(vec4i(2, 3, 4, 5), vec4i(1, 2, 3, 4))) // returns true\n */\nexport const gt = createDualImpl(\n // CPU implementation\n <T extends AnyNumericVecInstance>(lhs: T, rhs: T) =>\n and(not(lt(lhs, rhs)), not(eq(lhs, rhs))),\n // GPU implementation\n (lhs, rhs) =>\n snip(\n `(${lhs.value} > ${rhs.value})`,\n correspondingBooleanVectorSchema(lhs),\n ),\n 'gt',\n);\n\n/**\n * Checks **component-wise** whether `lhs >= rhs`.\n * This function does **not** return `bool`, for that use-case, wrap the result in `all`.\n * @example\n * ge(vec2f(0.0, 0.0), vec2f(0.0, 1.0)) // returns vec2b(true, false)\n * ge(vec3u(0, 1, 2), vec3u(2, 1, 0)) // returns vec3b(false, true, true)\n * all(ge(vec4i(2, 2, 4, 5), vec4i(1, 2, 3, 4))) // returns true\n */\nexport const ge = createDualImpl(\n // CPU implementation\n <T extends AnyNumericVecInstance>(lhs: T, rhs: T) => not(lt(lhs, rhs)),\n // GPU implementation\n (lhs, rhs) =>\n snip(\n `(${lhs.value} >= ${rhs.value})`,\n correspondingBooleanVectorSchema(lhs),\n ),\n 'ge',\n);\n\n// logical ops\n\n/**\n * Returns **component-wise** `!value`.\n * @example\n * not(vec2b(false, true)) // returns vec2b(true, false)\n * not(vec3b(true, true, false)) // returns vec3b(false, false, true)\n */\nexport const not = createDualImpl(\n // CPU implementation\n <T extends AnyBooleanVecInstance>(value: T): T =>\n VectorOps.neg[value.kind](value),\n // GPU implementation\n (value) => snip(`!(${value.value})`, value.dataType),\n 'not',\n);\n\n/**\n * Returns **component-wise** logical `or` result.\n * @example\n * or(vec2b(false, true), vec2b(false, false)) // returns vec2b(false, true)\n * or(vec3b(true, true, false), vec3b(false, true, false)) // returns vec3b(true, true, false)\n */\nexport const or = createDualImpl(\n // CPU implementation\n <T extends AnyBooleanVecInstance>(lhs: T, rhs: T) =>\n VectorOps.or[lhs.kind](lhs, rhs),\n // GPU implementation\n (lhs, rhs) => snip(`(${lhs.value} | ${rhs.value})`, lhs.dataType),\n 'or',\n);\n\n/**\n * Returns **component-wise** logical `and` result.\n * @example\n * and(vec2b(false, true), vec2b(true, true)) // returns vec2b(false, true)\n * and(vec3b(true, true, false), vec3b(false, true, false)) // returns vec3b(false, true, false)\n */\nexport const and = createDualImpl(\n // CPU implementation\n <T extends AnyBooleanVecInstance>(lhs: T, rhs: T) =>\n not(or(not(lhs), not(rhs))),\n // GPU implementation\n (lhs, rhs) => snip(`(${lhs.value} & ${rhs.value})`, lhs.dataType),\n 'and',\n);\n\n// logical aggregation\n\n/**\n * Returns `true` if each component of `value` is true.\n * @example\n * all(vec2b(false, true)) // returns false\n * all(vec3b(true, true, true)) // returns true\n */\nexport const all = createDualImpl(\n // CPU implementation\n (value: AnyBooleanVecInstance) => VectorOps.all[value.kind](value),\n // GPU implementation\n (value) => snip(`all(${value.value})`, bool),\n 'all',\n);\n\n/**\n * Returns `true` if any component of `value` is true.\n * @example\n * any(vec2b(false, true)) // returns true\n * any(vec3b(false, false, false)) // returns false\n */\nexport const any = createDualImpl(\n // CPU implementation\n (value: AnyBooleanVecInstance) => !all(not(value)),\n // GPU implementation\n (value) => snip(`any(${value.value})`, bool),\n 'any',\n);\n\n// other\n\n/**\n * Checks whether the given elements differ by at most the `precision` value.\n * Checks all elements of `lhs` and `rhs` if arguments are vectors.\n * @example\n * isCloseTo(0, 0.1) // returns false\n * isCloseTo(vec3f(0, 0, 0), vec3f(0.002, -0.009, 0)) // returns true\n *\n * @param {number} precision argument that specifies the maximum allowed difference, 0.01 by default.\n */\nexport const isCloseTo = createDualImpl(\n // CPU implementation\n <T extends AnyFloatVecInstance | number>(\n lhs: T,\n rhs: T,\n precision = 0.01,\n ) => {\n if (typeof lhs === 'number' && typeof rhs === 'number') {\n return Math.abs(lhs - rhs) < precision;\n }\n if (isVecInstance(lhs) && isVecInstance(rhs)) {\n return VectorOps.isCloseToZero[lhs.kind](\n sub(lhs, rhs),\n precision,\n );\n }\n return false;\n },\n // GPU implementation\n (lhs, rhs, precision = snip(0.01, f32)) => {\n if (isSnippetNumeric(lhs) && isSnippetNumeric(rhs)) {\n return snip(\n `(abs(f32(${lhs.value}) - f32(${rhs.value})) <= ${precision.value})`,\n bool,\n );\n }\n if (!isSnippetNumeric(lhs) && !isSnippetNumeric(rhs)) {\n return snip(\n // https://www.w3.org/TR/WGSL/#vector-multi-component:~:text=Binary%20arithmetic%20expressions%20with%20mixed%20scalar%20and%20vector%20operands\n // (a-a)+prec creates a vector of a.length elements, all equal to prec\n `all(abs(${lhs.value} - ${rhs.value}) <= (${lhs.value} - ${lhs.value}) + ${precision.value})`,\n bool,\n );\n }\n return snip('false', bool);\n },\n 'isCloseTo',\n);\n\nexport type SelectOverload = {\n <T extends number | boolean | AnyVecInstance>(f: T, t: T, cond: boolean): T;\n <T extends AnyVecInstance>(\n f: T,\n t: T,\n cond: T extends AnyVec2Instance ? v2b\n : T extends AnyVec3Instance ? v3b\n : v4b,\n ): T;\n};\n\n/**\n * Returns `t` if `cond` is `true`, and `f` otherwise.\n * Component-wise if `cond` is a vector.\n * @example\n * select(1, 2, false) // returns 1\n * select(1, 2, true) // returns 2\n * select(vec2i(1, 2), vec2i(3, 4), true) // returns vec2i(3, 4)\n * select(vec2i(1, 2), vec2i(3, 4), vec2b(false, true)) // returns vec2i(1, 4)\n */\nexport const select: SelectOverload = createDualImpl(\n // CPU implementation\n <T extends number | boolean | AnyVecInstance>(\n f: T,\n t: T,\n cond: AnyBooleanVecInstance | boolean,\n ) => {\n if (typeof cond === 'boolean') {\n return cond ? t : f;\n }\n return VectorOps.select[(f as AnyVecInstance).kind](\n f as AnyVecInstance,\n t as AnyVecInstance,\n cond,\n );\n },\n // GPU implementation\n (f, t, cond) =>\n snip(`select(${f.value}, ${t.value}, ${cond.value})`, f.dataType),\n 'select',\n);\n","import { snip, type Snippet } from '../data/dataTypes.ts';\nimport { i32, u32 } from '../data/numeric.ts';\nimport {\n type AnyWgslData,\n type atomicI32,\n type atomicU32,\n isWgslData,\n Void,\n} from '../data/wgslTypes.ts';\nimport { createDualImpl } from '../shared/generators.ts';\ntype AnyAtomic = atomicI32 | atomicU32;\n\nexport const workgroupBarrier = createDualImpl(\n // CPU implementation\n () => console.warn('workgroupBarrier is a no-op outside of GPU mode.'),\n // GPU implementation\n () => snip('workgroupBarrier()', Void),\n 'workgroupBarrier',\n);\n\nexport const storageBarrier = createDualImpl(\n // CPU implementation\n () => console.warn('storageBarrier is a no-op outside of GPU mode.'),\n // GPU implementation\n () => snip('storageBarrier()', Void),\n 'storageBarrier',\n);\n\nexport const textureBarrier = createDualImpl(\n // CPU implementation\n () => console.warn('textureBarrier is a no-op outside of GPU mode.'),\n // GPU implementation\n () => snip('textureBarrier()', Void),\n 'textureBarrier',\n);\n\nexport const atomicLoad = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicLoad(&${a.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicLoad',\n);\n\nexport const atomicStore = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): void => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (!isWgslData(a.dataType) || a.dataType.type !== 'atomic') {\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n }\n return snip(`atomicStore(&${a.value}, ${value.value})`, Void);\n },\n 'atomicStore',\n);\n\nconst atomicTypeFn = (a: Snippet, _value: Snippet): AnyWgslData[] => {\n if (a.dataType.type === 'atomic' && a.dataType.inner.type === 'i32') {\n return [a.dataType, i32];\n }\n return [a.dataType as AnyWgslData, u32];\n};\n\nexport const atomicAdd = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicAdd(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicAdd',\n atomicTypeFn,\n);\n\nexport const atomicSub = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicSub(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicSub',\n atomicTypeFn,\n);\n\nexport const atomicMax = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicMax(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicMax',\n atomicTypeFn,\n);\n\nexport const atomicMin = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicMin(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicMin',\n atomicTypeFn,\n);\n\nexport const atomicAnd = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicAnd(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicAnd',\n atomicTypeFn,\n);\n\nexport const atomicOr = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicOr(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicOr',\n atomicTypeFn,\n);\n\nexport const atomicXor = createDualImpl(\n // CPU implementation\n <T extends AnyAtomic>(a: T, value: number): number => {\n throw new Error('Atomic operations are not supported outside of GPU mode.');\n },\n // GPU implementation\n (a, value) => {\n if (isWgslData(a.dataType) && a.dataType.type === 'atomic') {\n return snip(`atomicXor(&${a.value}, ${value.value})`, a.dataType.inner);\n }\n throw new Error(\n `Invalid atomic type: ${JSON.stringify(a.dataType, null, 2)}`,\n );\n },\n 'atomicXor',\n atomicTypeFn,\n);\n"]}