typegpu/chunk-BJSN5UVV.cjs.map

A thin layer between JS and WebGPU/WGSL that improves development experience and allows for faster iteration.

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 \"name\": \"typegpu\",\n  \"private\": true,\n  \"version\": \"0.5.9\",\n  \"description\": \"A thin layer between JS and WebGPU/WGSL that improves development experience and allows for faster iteration.\",\n  \"license\": \"MIT\",\n  \"type\": \"module\",\n  \"exports\": {\n    \"./package.json\": \"./package.json\",\n    \".\": \"./src/index.ts\",\n    \"./data\": \"./src/data/index.ts\",\n    \"./std\": \"./src/std/index.ts\"\n  },\n  \"publishConfig\": {\n    \"directory\": \"dist\",\n    \"linkDirectory\": false,\n    \"main\": \"./dist/index.js\",\n    \"types\": \"./dist/index.d.ts\",\n    \"exports\": {\n      \"./package.json\": \"./dist/package.json\",\n      \".\": {\n        \"types\": \"./dist/index.d.ts\",\n        \"module\": \"./dist/index.js\",\n        \"import\": \"./dist/index.js\",\n        \"default\": \"./dist/index.cjs\"\n      },\n      \"./data\": {\n        \"types\": \"./dist/data/index.d.ts\",\n        \"module\": \"./dist/data/index.js\",\n        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\"devDependencies\": {\n    \"@ark/attest\": \"^0.46.0\",\n    \"@typegpu/tgpu-dev-cli\": \"workspace:*\",\n    \"@types/node\": \"^22.13.14\",\n    \"@webgpu/types\": \"catalog:\",\n    \"arktype\": \"catalog:\",\n    \"jiti\": \"^2.4.2\",\n    \"tgpu-jit\": \"workspace:*\",\n    \"tsup\": \"catalog:\",\n    \"typescript\": \"catalog:\",\n    \"unplugin-typegpu\": \"workspace:*\",\n    \"wesl\": \"0.6.7\",\n    \"wgpu-matrix\": \"^3.4.0\"\n  },\n  \"packageManager\": \"pnpm@10.4.1+sha512.c753b6c3ad7afa13af388fa6d808035a008e30ea9993f58c6663e2bc5ff21679aa834db094987129aa4d488b86df57f7b634981b2f827cdcacc698cc0cfb88af\",\n  \"dependencies\": {\n    \"tinyest\": \"workspace:~0.1.1\",\n    \"typed-binary\": \"^4.3.1\"\n  }\n}\n","// The version is inlined during build-time 🎉\n// It helps us identify problems when two versions of\n// TypeGPU are used at the same time.\nimport { version } from '../../package.json';\n\nexport const $internal = Symbol(`typegpu:${version}:$internal`);\n/**\n * A 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Please provide it using pipeline.with(layout, bindGroup).(...)`,\n    );\n\n    // Set the prototype explicitly.\n    Object.setPrototypeOf(this, MissingBindGroupsError.prototype);\n  }\n}\n\nexport class MissingVertexBuffersError extends Error {\n  constructor(layouts: Iterable<TgpuVertexLayout<WgslArray | Disarray>>) {\n    super(\n      `Missing vertex buffers for layouts: '${\n        [...layouts].map((layout) => getName(layout) ?? '<unnamed>').join(', ')\n      }'. Please provide it using pipeline.with(layout, buffer).(...)`,\n    );\n\n    // Set the prototype explicitly.\n    Object.setPrototypeOf(this, MissingVertexBuffersError.prototype);\n  }\n}\n","import { createDualImpl } from '../shared/generators.ts';\nimport { $repr } from '../shared/repr.ts';\nimport { $internal } from '../shared/symbols.ts';\nimport type { SelfResolvable } from '../types.ts';\nimport { snip } from './dataTypes.ts';\nimport { vec2f, vec3f, vec4f } from './vector.ts';\nimport type {\n  AnyWgslData,\n  m2x2f,\n  m3x3f,\n  m4x4f,\n  mat2x2,\n  Mat2x2f,\n  mat3x3,\n  Mat3x3f,\n  mat4x4,\n  Mat4x4f,\n  matBase,\n  v2f,\n  v3f,\n  v4f,\n  VecKind,\n} from './wgslTypes.ts';\n\n// --------------\n// Implementation\n// --------------\n\ntype vBase = {\n  kind: VecKind;\n  length: number;\n  [n: number]: number;\n};\n\ninterface MatSchemaOptions<TType extends string, ValueType> {\n  type: TType;\n  rows: 2 | 3 | 4;\n  columns: 2 | 3 | 4;\n  makeFromElements(...elements: number[]): ValueType;\n}\n\ntype MatConstructor<\n  ValueType extends matBase<ColumnType>,\n  ColumnType extends vBase,\n> = (...args: (number | ColumnType)[]) => ValueType;\n\nfunction createMatSchema<\n  TType extends string,\n  ValueType extends matBase<ColumnType>,\n  ColumnType extends vBase,\n>(\n  options: MatSchemaOptions<TType, ValueType>,\n): { type: TType; [$repr]: ValueType } & MatConstructor<ValueType, ColumnType> {\n  const MatSchema = {\n    [$internal]: true,\n    [$repr]: undefined as unknown as ValueType,\n    type: options.type,\n    identity: identityFunctions[options.columns],\n    translation: options.columns === 4 ? translation4 : undefined,\n    scaling: options.columns === 4 ? scaling4 : undefined,\n    rotationX: options.columns === 4 ? rotationX4 : undefined,\n    rotationY: options.columns === 4 ? rotationY4 : undefined,\n    rotationZ: options.columns === 4 ? rotationZ4 : undefined,\n  } as unknown as AnyWgslData;\n\n  const construct = createDualImpl(\n    // CPU implementation\n    (...args: (number | ColumnType)[]): ValueType => {\n      const elements: number[] = [];\n\n      for (const arg of args) {\n        if (typeof arg === 'number') {\n          elements.push(arg);\n        } else {\n          for (let i = 0; i < arg.length; ++i) {\n            elements.push(arg[i] as number);\n          }\n        }\n      }\n\n      if (\n        elements.length !== 0 &&\n        elements.length !== options.columns * options.rows\n      ) {\n        throw new Error(\n          `'${options.type}' constructor called with invalid number of arguments.`,\n        );\n      }\n\n      for (let i = elements.length; i < options.columns * options.rows; ++i) {\n        elements.push(0);\n      }\n\n      return options.makeFromElements(...elements);\n    },\n    // GPU implementation\n    (...args) =>\n      snip(\n        `${MatSchema.type}(${args.map((v) => v.value).join(', ')})`,\n        MatSchema,\n      ),\n    MatSchema.type,\n  );\n\n  return Object.assign(construct, MatSchema) as unknown as {\n    type: TType;\n    [$repr]: ValueType;\n  } & MatConstructor<ValueType, ColumnType>;\n}\n\nabstract class mat2x2Impl<TColumn extends v2f>\n  implements mat2x2<TColumn>, SelfResolvable {\n  public readonly [$internal] = true;\n  public readonly columns: readonly [TColumn, TColumn];\n  public readonly length = 4;\n  public abstract readonly kind: string;\n  [n: number]: number;\n\n  constructor(...elements: number[]) {\n    this.columns = [\n      this.makeColumn(elements[0] as number, elements[1] as number),\n      this.makeColumn(elements[2] as number, elements[3] as number),\n    ];\n  }\n\n  abstract makeColumn(e0: number, e1: number): TColumn;\n\n  get [0]() {\n    return this.columns[0].x;\n  }\n\n  get [1]() {\n    return this.columns[0].y;\n  }\n\n  get [2]() {\n    return this.columns[1].x;\n  }\n\n  get [3]() {\n    return this.columns[1].y;\n  }\n\n  set [0](value: number) {\n    this.columns[0].x = value;\n  }\n\n  set [1](value: number) {\n    this.columns[0].y = value;\n  }\n\n  set [2](value: number) {\n    this.columns[1].x = value;\n  }\n\n  set [3](value: number) {\n    this.columns[1].y = value;\n  }\n\n  *[Symbol.iterator]() {\n    yield this[0];\n    yield this[1];\n    yield this[2];\n    yield this[3];\n  }\n\n  '~resolve'(): string {\n    return `${this.kind}(${\n      Array.from({ length: this.length })\n        .map((_, i) => this[i])\n        .join(', ')\n    })`;\n  }\n}\nclass mat2x2fImpl extends mat2x2Impl<v2f> implements m2x2f {\n  public readonly kind = 'mat2x2f';\n\n  makeColumn(e0: number, e1: number): v2f {\n    return vec2f(e0, e1);\n  }\n}\n\nabstract class mat3x3Impl<TColumn extends v3f>\n  implements mat3x3<TColumn>, SelfResolvable {\n  public readonly [$internal] = true;\n  public readonly columns: readonly [TColumn, TColumn, TColumn];\n  public readonly length = 12;\n  public abstract readonly kind: string;\n  [n: number]: number;\n\n  constructor(...elements: number[]) {\n    this.columns = [\n      this.makeColumn(\n        elements[0] as number,\n        elements[1] as number,\n        elements[2] as number,\n      ),\n      this.makeColumn(\n        elements[3] as number,\n        elements[4] as number,\n        elements[5] as number,\n      ),\n      this.makeColumn(\n        elements[6] as number,\n        elements[7] as number,\n        elements[8] as number,\n      ),\n    ];\n  }\n\n  abstract makeColumn(x: number, y: number, z: number): TColumn;\n\n  get [0]() {\n    return this.columns[0].x;\n  }\n\n  get [1]() {\n    return this.columns[0].y;\n  }\n\n  get [2]() {\n    return this.columns[0].z;\n  }\n\n  get [3]() {\n    return 0;\n  }\n\n  get [4]() {\n    return this.columns[1].x;\n  }\n\n  get [5]() {\n    return this.columns[1].y;\n  }\n\n  get [6]() {\n    return this.columns[1].z;\n  }\n\n  get [7]() {\n    return 0;\n  }\n\n  get [8]() {\n    return this.columns[2].x;\n  }\n\n  get [9]() {\n    return this.columns[2].y;\n  }\n\n  get [10]() {\n    return this.columns[2].z;\n  }\n\n  get [11]() {\n    return 0;\n  }\n\n  set [0](value: number) {\n    this.columns[0].x = value;\n  }\n\n  set [1](value: number) {\n    this.columns[0].y = value;\n  }\n\n  set [2](value: number) {\n    this.columns[0].z = value;\n  }\n\n  set [3](_: number) {}\n\n  set [4](value: number) {\n    this.columns[1].x = value;\n  }\n\n  set [5](value: number) {\n    this.columns[1].y = value;\n  }\n\n  set [6](value: number) {\n    this.columns[1].z = value;\n  }\n\n  set [7](_: number) {}\n\n  set [8](value: number) {\n    this.columns[2].x = value;\n  }\n\n  set [9](value: number) {\n    this.columns[2].y = value;\n  }\n\n  set [10](value: number) {\n    this.columns[2].z = value;\n  }\n\n  set [11](_: number) {}\n\n  *[Symbol.iterator]() {\n    for (let i = 0; i < 12; i++) {\n      yield this[i] as number;\n    }\n  }\n\n  '~resolve'(): string {\n    return `${this.kind}(${this[0]}, ${this[1]}, ${this[2]}, ${this[4]}, ${\n      this[5]\n    }, ${this[6]}, ${this[8]}, ${this[9]}, ${this[10]})`;\n  }\n}\n\nclass mat3x3fImpl extends mat3x3Impl<v3f> implements m3x3f {\n  public readonly kind = 'mat3x3f';\n  makeColumn(x: number, y: number, z: number): v3f {\n    return vec3f(x, y, z);\n  }\n}\n\nabstract class mat4x4Impl<TColumn extends v4f>\n  implements mat4x4<TColumn>, SelfResolvable {\n  public readonly [$internal] = true;\n  public readonly columns: readonly [TColumn, TColumn, TColumn, TColumn];\n  public abstract readonly kind: string;\n\n  constructor(...elements: number[]) {\n    this.columns = [\n      this.makeColumn(\n        elements[0] as number,\n        elements[1] as number,\n        elements[2] as number,\n        elements[3] as number,\n      ),\n      this.makeColumn(\n        elements[4] as number,\n        elements[5] as number,\n        elements[6] as number,\n        elements[7] as number,\n      ),\n      this.makeColumn(\n        elements[8] as number,\n        elements[9] as number,\n        elements[10] as number,\n        elements[11] as number,\n      ),\n      this.makeColumn(\n        elements[12] as number,\n        elements[13] as number,\n        elements[14] as number,\n        elements[15] as number,\n      ),\n    ];\n  }\n\n  abstract makeColumn(x: number, y: number, z: number, w: number): TColumn;\n\n  public readonly length = 16;\n  [n: number]: number;\n\n  get [0]() {\n    return this.columns[0].x;\n  }\n\n  get [1]() {\n    return this.columns[0].y;\n  }\n\n  get [2]() {\n    return this.columns[0].z;\n  }\n\n  get [3]() {\n    return this.columns[0].w;\n  }\n\n  get [4]() {\n    return this.columns[1].x;\n  }\n\n  get [5]() {\n    return this.columns[1].y;\n  }\n\n  get [6]() {\n    return this.columns[1].z;\n  }\n\n  get [7]() {\n    return this.columns[1].w;\n  }\n\n  get [8]() {\n    return this.columns[2].x;\n  }\n\n  get [9]() {\n    return this.columns[2].y;\n  }\n\n  get [10]() {\n    return this.columns[2].z;\n  }\n\n  get [11]() {\n    return this.columns[2].w;\n  }\n\n  get [12]() {\n    return this.columns[3].x;\n  }\n\n  get [13]() {\n    return this.columns[3].y;\n  }\n\n  get [14]() {\n    return this.columns[3].z;\n  }\n\n  get [15]() {\n    return this.columns[3].w;\n  }\n\n  set [0](value: number) {\n    this.columns[0].x = value;\n  }\n\n  set [1](value: number) {\n    this.columns[0].y = value;\n  }\n\n  set [2](value: number) {\n    this.columns[0].z = value;\n  }\n\n  set [3](value: number) {\n    this.columns[0].w = value;\n  }\n\n  set [4](value: number) {\n    this.columns[1].x = value;\n  }\n\n  set [5](value: number) {\n    this.columns[1].y = value;\n  }\n\n  set [6](value: number) {\n    this.columns[1].z = value;\n  }\n\n  set [7](value: number) {\n    this.columns[1].w = value;\n  }\n\n  set [8](value: number) {\n    this.columns[2].x = value;\n  }\n\n  set [9](value: number) {\n    this.columns[2].y = value;\n  }\n\n  set [10](value: number) {\n    this.columns[2].z = value;\n  }\n\n  set [11](value: number) {\n    this.columns[2].w = value;\n  }\n\n  set [12](value: number) {\n    this.columns[3].x = value;\n  }\n\n  set [13](value: number) {\n    this.columns[3].y = value;\n  }\n\n  set [14](value: number) {\n    this.columns[3].z = value;\n  }\n\n  set [15](value: number) {\n    this.columns[3].w = value;\n  }\n\n  *[Symbol.iterator]() {\n    for (let i = 0; i < 16; i++) {\n      yield this[i] as number;\n    }\n  }\n\n  '~resolve'(): string {\n    return `${this.kind}(${\n      Array.from({ length: this.length })\n        .map((_, i) => this[i])\n        .join(', ')\n    })`;\n  }\n}\n\nclass mat4x4fImpl extends mat4x4Impl<v4f> implements m4x4f {\n  public readonly kind = 'mat4x4f';\n\n  makeColumn(x: number, y: number, z: number, w: number): v4f {\n    return vec4f(x, y, z, w);\n  }\n}\n\n// ----------\n// Matrix ops\n// ----------\n\n/**\n * Returns a 2-by-2 identity matrix.\n * @returns {m2x2f} The result matrix.\n */\nexport const identity2 = createDualImpl(\n  // CPU implementation\n  () => mat2x2f(1, 0, 0, 1),\n  // GPU implementation\n  () => ({\n    value: `mat4x4f(\n      1.0, 0.0,\n      0.0, 1.0\n    )`,\n    dataType: mat2x2f,\n  }),\n  'identity2',\n);\n\n/**\n * Returns a 3-by-3 identity matrix.\n * @returns {m3x3f} The result matrix.\n */\nexport const identity3 = createDualImpl(\n  // CPU implementation\n  () => mat3x3f(1, 0, 0, 0, 1, 0, 0, 0, 1),\n  // GPU implementation\n  () => ({\n    value: `mat4x4f(\n      1.0, 0.0, 0.0,\n      0.0, 1.0, 0.0,\n      0.0, 0.0, 1.0,\n    )`,\n    dataType: mat3x3f,\n  }),\n  'identity3',\n);\n\n/**\n * Returns a 4-by-4 identity matrix.\n * @returns {m4x4f} The result matrix.\n */\nexport const identity4 = createDualImpl(\n  // CPU implementation\n  () => mat4x4f(1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1),\n  // GPU implementation\n  () => ({\n    value: `mat4x4f(\n      1.0, 0.0, 0.0, 0.0,\n      0.0, 1.0, 0.0, 0.0,\n      0.0, 0.0, 1.0, 0.0,\n      0.0, 0.0, 0.0, 1.0\n    )`,\n    dataType: mat4x4f,\n  }),\n  'identity4',\n);\n\nconst identityFunctions = {\n  2: identity2,\n  3: identity3,\n  4: identity4,\n};\n\n/**\n * Creates a 4-by-4 matrix which translates by the given vector v.\n * @param {v3f} vector - The vector by which to translate.\n * @returns {m4x4f} The translation matrix.\n */\nexport const translation4 = createDualImpl(\n  // CPU implementation\n  (vector: v3f) =>\n    // deno-fmt-ignore\n    mat4x4f(\n      1, 0, 0, 0,\n      0, 1, 0, 0,\n      0, 0, 1, 0,\n      vector.x, vector.y, vector.z, 1,\n    ),\n  // GPU implementation\n  (vector) => ({\n    value: `mat4x4f(\n        1, 0, 0, 0,\n        0, 1, 0, 0,\n        0, 0, 1, 0, \n        ${vector.value}.x, ${vector.value}.y, ${vector.value}.z, 1\n      )`,\n    dataType: mat4x4f,\n  }),\n  'translation4',\n);\n\n/**\n * Creates a 4-by-4 matrix which scales in each dimension by an amount given by the corresponding entry in the given vector.\n * @param {v3f} vector - A vector of three entries specifying the factor by which to scale in each dimension.\n * @returns {m4x4f} The scaling matrix.\n */\nexport const scaling4 = createDualImpl(\n  // CPU implementation\n  (vector: v3f) =>\n    // deno-fmt-ignore\n    mat4x4f(\n      vector.x, 0, 0, 0,\n      0, vector.y, 0, 0,\n      0, 0, vector.z, 0,\n      0, 0, 0, 1,\n    ),\n  // GPU implementation\n  (vector) => ({\n    value: `mat4x4f(\n        ${vector.value}.x, 0, 0, 0,\n        0, ${vector.value}.y, 0, 0,\n        0, 0, ${vector.value}.z, 0, \n        0, 0, 0, 1\n      )`,\n    dataType: mat4x4f,\n  }),\n  'scaling4',\n);\n\n/**\n * Creates a 4-by-4 matrix which rotates around the x-axis by the given angle.\n * @param {number} angle - The angle by which to rotate (in radians).\n * @returns {m4x4f} The rotation matrix.\n */\nexport const rotationX4 = createDualImpl(\n  // CPU implementation\n  (a: number) =>\n    // deno-fmt-ignore\n    mat4x4f(\n      1, 0, 0, 0,\n      0, Math.cos(a), Math.sin(a), 0,\n      0, -Math.sin(a), Math.cos(a), 0,\n      0, 0, 0, 1,\n    ),\n  // GPU implementation\n  (a) =>\n    snip(\n      `mat4x4f(\n        1, 0, 0, 0,\n        0, cos(${a.value}), sin(${a.value}), 0,\n        0, -sin(${a.value}), cos(${a.value}), 0,\n        0, 0, 0, 1\n      )`,\n      mat4x4f,\n    ),\n  'rotationX4',\n);\n\n/**\n * Creates a 4-by-4 matrix which rotates around the y-axis by the given angle.\n * @param {number} angle - The angle by which to rotate (in radians).\n * @returns {m4x4f} The rotation matrix.\n */\nexport const rotationY4 = createDualImpl(\n  // CPU implementation\n  (a: number) =>\n    // deno-fmt-ignore\n    mat4x4f(\n      Math.cos(a), 0, -Math.sin(a), 0,\n      0, 1, 0, 0,\n      Math.sin(a), 0, Math.cos(a), 0,\n      0, 0, 0, 1,\n    ),\n  // GPU implementation\n  (a) =>\n    snip(\n      `mat4x4f(\n        cos(${a.value}), 0, -sin(${a.value}), 0,\n        0, 1, 0, 0,\n        sin(${a.value}), 0, cos(${a.value}), 0,\n        0, 0, 0, 1\n      )`,\n      mat4x4f,\n    ),\n  'rotationY4',\n);\n\n/**\n * Creates a 4-by-4 matrix which rotates around the z-axis by the given angle.\n * @param {number} angle - The angle by which to rotate (in radians).\n * @returns {m4x4f} The rotation matrix.\n */\nexport const rotationZ4 = createDualImpl(\n  // CPU implementation\n  (a: number) =>\n    // deno-fmt-ignore\n    mat4x4f(\n      Math.cos(a), Math.sin(a), 0, 0,\n      -Math.sin(a), Math.cos(a), 0, 0,\n      0, 0, 1, 0,\n      0, 0, 0, 1,\n    ),\n  // GPU implementation\n  (a) =>\n    snip(\n      `mat4x4f(\n        cos(${a.value}), sin(${a.value}), 0, 0,\n        -sin(${a.value}), cos(${a.value}), 0, 0,\n        0, 0, 1, 0,\n        0, 0, 0, 1\n      )`,\n      mat4x4f,\n    ),\n  'rotationZ4',\n);\n\n// ----------\n// Public API\n// ----------\n\n/**\n * Schema representing mat2x2f - a matrix with 2 rows and 2 columns, with elements of type f32.\n * Also a constructor function for this matrix type.\n *\n * @example\n * const zero2x2 = mat2x2f(); // filled with zeros\n *\n * @example\n * const mat = mat2x2f(0, 1, 2, 3);\n * mat.columns[0] // vec2f(0, 1)\n * mat.columns[1] // vec2f(2, 3)\n *\n * @example\n * const mat = mat2x2f(\n *  vec2f(0, 1), // column 0\n *  vec2f(1, 2), // column 1\n * );\n *\n * @example\n * const buffer = root.createBuffer(d.mat2x2f, d.mat2x2f(0, 1, 2, 3)); // buffer holding a d.mat2x2f value, with an initial value of ((0, 1), (2, 3))\n */\nexport const mat2x2f = createMatSchema<'mat2x2f', m2x2f, v2f>({\n  type: 'mat2x2f',\n  rows: 2,\n  columns: 2,\n  makeFromElements: (...elements: number[]) => new mat2x2fImpl(...elements),\n}) as Mat2x2f;\n\n/**\n * Schema representing mat3x3f - a matrix with 3 rows and 3 columns, with elements of type f32.\n * Also a constructor function for this matrix type.\n *\n * @example\n * const zero3x3 = mat3x3f(); // filled with zeros\n *\n * @example\n * const mat = mat3x3f(0, 1, 2, 3, 4, 5, 6, 7, 8);\n * mat.columns[0] // vec3f(0, 1, 2)\n * mat.columns[1] // vec3f(3, 4, 5)\n * mat.columns[2] // vec3f(6, 7, 8)\n *\n * @example\n * const mat = mat3x3f(\n *  vec3f(0, 1, 2), // column 0\n *  vec3f(2, 3, 4), // column 1\n *  vec3f(5, 6, 7), // column 2\n * );\n *\n * @example\n * const buffer = root.createBuffer(d.mat3x3f, d.mat3x3f()); // buffer holding a d.mat3x3f value, with an initial value of mat3x3f filled with zeros\n */\nexport const mat3x3f = createMatSchema<'mat3x3f', m3x3f, v3f>({\n  type: 'mat3x3f',\n  rows: 3,\n  columns: 3,\n  makeFromElements: (...elements: number[]) => new mat3x3fImpl(...elements),\n}) as Mat3x3f;\n\n/**\n * Schema representing mat4x4f - a matrix with 4 rows and 4 columns, with elements of type f32.\n * Also a constructor function for this matrix type.\n *\n * @example\n * const zero4x4 = mat4x4f(); // filled with zeros\n *\n * @example\n * const mat = mat4x4f(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15);\n * mat.columns[0] // vec4f(0, 1, 2, 3)\n * mat.columns[1] // vec4f(4, 5, 6, 7)\n * mat.columns[2] // vec4f(8, 9, 10, 11)\n * mat.columns[3] // vec4f(12, 13, 14, 15)\n *\n * @example\n * const mat = mat4x4f(\n *  vec4f(0, 1, 2, 3),     // column 0\n *  vec4f(4, 5, 6, 7),     // column 1\n *  vec4f(8, 9, 10, 11),   // column 2\n *  vec4f(12, 13, 14, 15), // column 3\n * );\n *\n * @example\n * const buffer = root.createBuffer(d.mat4x4f, d.mat4x4f()); // buffer holding a d.mat4x4f value, with an initial value of mat4x4f filled with zeros\n */\nexport const mat4x4f = createMatSchema<'mat4x4f', m4x4f, v4f>({\n  type: 'mat4x4f',\n  rows: 4,\n  columns: 4,\n  makeFromElements: (...elements: number[]) => new mat4x4fImpl(...elements),\n}) as Mat4x4f;\n\nexport function matToArray(mat: m2x2f | m3x3f | m4x4f): number[] {\n  if (mat.kind === 'mat3x3f') {\n    return [\n      mat[0],\n      mat[1],\n      mat[2],\n      mat[4],\n      mat[5],\n      mat[6],\n      mat[8],\n      mat[9],\n      mat[10],\n    ] as number[];\n  }\n\n  return Array.from({ length: mat.length }).map((_, idx) => mat[idx] as number);\n}\n","import { $internal } from '../shared/symbols.ts';\nimport type { AnyData } from './dataTypes.ts';\nimport type { Ptr } from './wgslTypes.ts';\n\nexport function ptrFn<T extends AnyData>(\n  inner: T,\n): Ptr<'function', T, 'read-write'> {\n  return {\n    [$internal]: true,\n    type: 'ptr',\n    inner,\n    addressSpace: 'function',\n    access: 'read-write',\n  } as Ptr<'function', T, 'read-write'>;\n}\n\nexport function ptrPrivate<T extends AnyData>(\n  inner: T,\n): Ptr<'private', T, 'read-write'> {\n  return {\n    [$internal]: true,\n    type: 'ptr',\n    inner,\n    addressSpace: 'private',\n    access: 'read-write',\n  } as Ptr<'private', T, 'read-write'>;\n}\n\nexport function ptrWorkgroup<T extends AnyData>(\n  inner: T,\n): Ptr<'workgroup', T, 'read-write'> {\n  return {\n    [$internal]: true,\n    type: 'ptr',\n    inner,\n    addressSpace: 'workgroup',\n    access: 'read-write',\n  } as Ptr<'workgroup', T, 'read-write'>;\n}\n\nexport function ptrStorage<\n  T extends AnyData,\n  TAccess extends 'read' | 'read-write' = 'read',\n>(inner: T, access: TAccess = 'read' as TAccess): Ptr<'storage', T, TAccess> {\n  return {\n    [$internal]: true,\n    type: 'ptr',\n    inner,\n    addressSpace: 'storage',\n    access,\n  } as Ptr<'storage', T, TAccess>;\n}\n\nexport function ptrUniform<T extends AnyData>(\n  inner: T,\n): Ptr<'uniform', T, 'read'> {\n  return {\n    [$internal]: true,\n    type: 'ptr',\n    inner,\n    addressSpace: 'uniform',\n    access: 'read',\n  } as Ptr<'uniform', T, 'read'>;\n}\n\nexport function ptrHandle<T extends AnyData>(\n  inner: T,\n): Ptr<'handle', T, 'read'> {\n  return {\n    [$internal]: true,\n    type: 'ptr',\n    inner,\n    addressSpace: 'handle',\n    access: 'read',\n  } as Ptr<'handle', T, 'read'>;\n}\n"]}