2c:null 2d:["$","title",null,{"children":"IX | David | Observable"}] 32:Te36,class NDArray { /** * N-dimensional array backed by nested arrays. * @param {Array} data - Nested array, e.g. [[1, 2], [3, 4]]. * @param {number[]|null} [size=null] - Dimensions; inferred from data if null. * @param {Object} [options] * @param {boolean} [options.skipValidation=false] - Skip structure validation. */ constructor(data, size = null, { skipValidation = false } = {}) { this.data = Array.isArray(data) ? data : [data]; if (!size) { this.size = this._inferSize(this.data); } else { this.size = Uint32Array.from(size); if (!skipValidation) this._validate(this.data, this.size); } } _inferSize(data) { const size = []; for (let cur = data; Array.isArray(cur) && cur.length > 0; cur = cur[0]) { size.push(cur.length); } return new Uint32Array(size.length ? size : [0]); } _validate(data, size, depth = 0) { if (depth >= size.length) { if (Array.isArray(data)) { throw new Error(`Data has more nesting than size dimensions (${size.length})`); } return; } if (!Array.isArray(data)) { throw new Error(`Expected array at depth ${depth}, got ${typeof data}`); } if (data.length !== size[depth]) { throw new Error(`Expected ${size[depth]} elements at depth ${depth}, got ${data.length}`); } for (const item of data) this._validate(item, size, depth + 1); } /** Checks the number of indices and their bounds (shared by get/set). */ _checkIndices(indices) { if (indices.length !== this.size.length) { throw new Error(`Expected ${this.size.length} indices, got ${indices.length}`); } indices.forEach((idx, i) => { if (idx < 0 || idx >= this.size[i]) { throw new Error(`Index ${idx} out of bounds for dimension ${i} (size ${this.size[i]})`); } }); } get(...indices) { this._checkIndices(indices); return indices.reduce((cur, idx) => cur[idx], this.data); } set(value, ...indices) { this._checkIndices(indices); const parent = indices.slice(0, -1).reduce((cur, idx) => cur[idx], this.data); parent[indices[indices.length - 1]] = value; } /** Calls callback(value, indices, array) for each element. */ forEach(callback, { noMutate = false } = {}) { const indices = new Uint32Array(this.size.length); const iterate = (data, dim) => { if (dim === this.size.length) { callback(data, noMutate ? indices.subarray(0) : new Uint32Array(indices), this); return; } for (let i = 0; i < this.size[dim]; i++) { indices[dim] = i; iterate(data[i], dim + 1); } }; iterate(this.data, 0); } /** Returns a new NDArray with callback applied to each element. */ map(callback, options) { const result = NDArray.fill(undefined, this.size); this.forEach((v, idx, arr) => result.set(callback(v, idx, arr), ...idx), options); return result; } static fill(value, size) { const build = (dim) => dim >= size.length ? value : Array.from({length: size[dim]}, () => build(dim + 1)); return new NDArray(build(0), size, {skipValidation: true}); } static zeros(size) { return NDArray.fill(0, size); } clone() { const copy = (data, dim) => dim >= this.size.length ? data : data.map((item) => copy(item, dim + 1)); return new NDArray(copy(this.data, 0), this.size, {skipValidation: true}); } toNestedArray() { return this.clone().data; } get ndim() { return this.size.length; } get totalSize() { return this.size.reduce((prod, dim) => prod * dim, 1); } }33:[] 30:{"id":"f347268b49237fed","slug":"ix","title":"IX","thumbnail":"0b7843c010f428c93e183b1be231a3bbf6229557f28c29f0cd2c33665759319b","access_level":"public","create_time":"$D2025-08-31T15:49:52.187Z","update_time":"$D2026-10-03T18:19:38.412Z","view_time":null,"first_public_time":"$D2026-10-03T20:59:12.312Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"cd42f0d98191a7df","login":"dvd101x","name":"David","avatar_url":"https://avatars-next.observableusercontent.com/665b28399b8c69493837e25bfd6b1e60e5c83f5f646e274cf39b5146449e30c6","tier":"starter_2024"},"version":442,"publish_version":442,"role":null,"authored":false,"authors":[{"type":"individual","id":"c454621e13d910d3","login":"dvd101x","name":"David","avatar_url":"https://avatars-next.observableusercontent.com/665b28399b8c69493837e25bfd6b1e60e5c83f5f646e274cf39b5146449e30c6","tier":null}],"members":[{"type":"individual","id":"c454621e13d910d3","login":"dvd101x","name":"David","avatar_url":"https://avatars-next.observableusercontent.com/665b28399b8c69493837e25bfd6b1e60e5c83f5f646e274cf39b5146449e30c6","tier":null,"role":"editor"},{"type":"team","id":"cd42f0d98191a7df","login":"dvd101x","name":"David","avatar_url":"https://avatars-next.observableusercontent.com/665b28399b8c69493837e25bfd6b1e60e5c83f5f646e274cf39b5146449e30c6","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"IX","cells":[{"id":368,"value":"# IX\n\nAn idea to make a library like numpy in javascript.\n\n```js\nconst A = ix.array([[1,2],[3, 4]])\nA.add(2)\n```","pinned":true,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":400,"value":"range(0, -10, -1)","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":401,"value":"range(0, -10, -2).toArray()","pinned":true,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":0,"value":"# nd array\nthis is an attempt to explore the implementations of ndarray by stdlib and ndarray. The idea is to have a class system to manage.\n- Arrays that are nested\n - Rectangular \n - Converted to strided arrays\n - with buffer being an array\n - with buffer being a typed array\n - Kept as nested arrays\n - Non rectangular\n - Kept as nested arrays\n- Strided arrays ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":283,"value":"# Strategy\n\nCheck num.js, @stdlib/ndarray and ndarray. Use them to implement functions in numpy / scipy. Make my own version to check if I understand it. If there is not much difference in performance then use my own.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":389,"value":"# Class system\n\n- ixRange\n- ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":201,"value":"function cumprod(x) {\n const n = x.length;\n const y = x.constructor(n);\n let acc = 1;\n for (let i = 0; i < n; i++) {\n acc *= x[i];\n y[i] = acc;\n }\n return y;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":264,"value":"function isClose(a, b, rtol = 1e-5, atol = 1e-8) {\n // Emulates the isclose implemented in python\n // abs(a-b) <= max(rel_tol * max(abs(a), abs(b))\n // When comparing x to 0.0, isclose(x, 0) is computed as abs(x) <= rel_tol * abs(x)\n const {abs, max} = Math;\n return b === 0.0\n ? abs(a) <= rtol * abs(a)\n : abs(a - b) <= max(rtol * max(abs(a), abs(b)), atol);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":332,"value":"function isCloseScalar(a, b, rtol = 1e-5, atol = 1e-8) {\n // emulates the isClose implemented by numpy\n // to be used as a base for isClose for ndarrays\n const {abs} = Math;\n return abs(a - b) <= atol + rtol * abs(b);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":272,"value":"function gt(a, b) {\n return !equal(a, b) && a > b;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":277,"value":"function ge(a, b) {\n return equal(a, b) || a > b;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":275,"value":"function lt(a, b) {\n return !equal(a, b) && a < b;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":279,"value":"function le(a, b) {\n return equal(a, b) || a < b;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":323,"value":"function equal(a, b) {\n return isClose(a, b);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":380,"value":"function sub2ind(shape, strides, offset, subindices) {\n // converts [1, 1] to a flat buffer index, e.g. 3 for shape [2,2]\n let ind = offset;\n for (let i = 0; i < shape.length; i++) {\n ind += strides[i] * subindices[i];\n }\n return ind;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":257,"value":"function range(...args) {\n return args.length === 1 ? new NumRange(0, args[0]) : new NumRange(...args);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":162,"value":"class NumRange {\n constructor(start = 0, end, step = 1) {\n this.start = start;\n this.end = end;\n this.step = step;\n }\n *[Symbol.iterator]() {\n const condition =\n this.step > 0 ? (i) => lt(i, this.end) : (i) => gt(i, this.end);\n for (let i = this.start; condition(i); i += this.step) {\n yield i;\n }\n }\n toArray() {\n return [...this];\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":335,"value":"range(10) instanceof NumRange","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":130,"value":"range(10).toArray()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"test = new NDArray([[[[[1]]]]])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":57,"value":"test.get(...new Uint32Array([0, 0, 0, 0, 0]))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":15,"value":"$32","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"{\n // Example usage:\n let results = \"\";\n const matrix = new NDArray(\n [\n [1, 2],\n [3, 4]\n ],\n [2, 2]\n );\n\n function put(text) {\n results += text + \"\\n\";\n }\n put(matrix.size);\n put(matrix.get(0, 1));\n matrix.set(99, 0, 1);\n put(matrix.get(0, 1)); // 99\n matrix.forEach(\n (value, indices) => {\n put(`Value at ${indices}: ${value}`);\n },\n { noMutate: true }\n );\n return results;\n const mapped = matrix.map((value, indices) => value * 2, { noMutate: true });\n\n put(mapped.toNestedArray()); // [[2, 4], [6, 8]]\n\n const cube = new NDArray(\n [\n [\n [1, 2],\n [3, 4]\n ],\n [\n [5, 6],\n [7, 8]\n ]\n ],\n [2, 2, 2]\n );\n cube.forEach((val, idx) => put(`Value ${val} at ${idx}`));\n\n const zeros = NDArray.zeros([2, 2]);\n put(zeros.toNestedArray()); // [[0, 0], [0, 0]]\n\n return htl`

${results}

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