{"id":49064456,"url":"https://github.com/stdlib-js/ndarray-flatten","last_synced_at":"2026-04-20T04:03:02.491Z","repository":{"id":314011205,"uuid":"1053264307","full_name":"stdlib-js/ndarray-flatten","owner":"stdlib-js","description":"Return a flattened copy of an input ndarray.","archived":false,"fork":false,"pushed_at":"2026-04-09T03:25:49.000Z","size":2495,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-04-09T05:26:15.986Z","etag":null,"topics":["array","copy","flat","flatten","javascript","matrix","multidimensional","ndarray","node","node-js","nodejs","reshape","stdlib","tensor","transform"],"latest_commit_sha":null,"homepage":"https://github.com/stdlib-js/stdlib","language":"JavaScript","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/stdlib-js.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":"NOTICE","maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null},"funding":{"github":["stdlib-js"],"open_collective":"stdlib","tidelift":"npm/@stdlib/stdlib"}},"created_at":"2025-09-09T07:59:51.000Z","updated_at":"2026-04-09T03:18:15.000Z","dependencies_parsed_at":"2025-10-03T11:33:07.776Z","dependency_job_id":null,"html_url":"https://github.com/stdlib-js/ndarray-flatten","commit_stats":null,"previous_names":["stdlib-js/ndarray-flatten"],"tags_count":8,"template":false,"template_full_name":null,"purl":"pkg:github/stdlib-js/ndarray-flatten","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stdlib-js%2Fndarray-flatten","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stdlib-js%2Fndarray-flatten/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stdlib-js%2Fndarray-flatten/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stdlib-js%2Fndarray-flatten/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/stdlib-js","download_url":"https://codeload.github.com/stdlib-js/ndarray-flatten/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stdlib-js%2Fndarray-flatten/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32032304,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-20T00:18:06.643Z","status":"online","status_checked_at":"2026-04-20T02:00:06.527Z","response_time":94,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["array","copy","flat","flatten","javascript","matrix","multidimensional","ndarray","node","node-js","nodejs","reshape","stdlib","tensor","transform"],"created_at":"2026-04-20T04:02:56.724Z","updated_at":"2026-04-20T04:02:57.725Z","avatar_url":"https://github.com/stdlib-js.png","language":"JavaScript","funding_links":["https://github.com/sponsors/stdlib-js","https://opencollective.com/stdlib","https://tidelift.com/funding/github/npm/@stdlib/stdlib"],"categories":[],"sub_categories":[],"readme":"\u003c!--\n\n@license Apache-2.0\n\nCopyright (c) 2025 The Stdlib Authors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n   http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\n--\u003e\n\n\n\u003cdetails\u003e\n  \u003csummary\u003e\n    About stdlib...\n  \u003c/summary\u003e\n  \u003cp\u003eWe believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.\u003c/p\u003e\n  \u003cp\u003eThe library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.\u003c/p\u003e\n  \u003cp\u003eWhen you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.\u003c/p\u003e\n  \u003cp\u003eTo join us in bringing numerical computing to the web, get started by checking us out on \u003ca href=\"https://github.com/stdlib-js/stdlib\"\u003eGitHub\u003c/a\u003e, and please consider \u003ca href=\"https://opencollective.com/stdlib\"\u003efinancially supporting stdlib\u003c/a\u003e. We greatly appreciate your continued support!\u003c/p\u003e\n\u003c/details\u003e\n\n# flatten\n\n[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] \u003c!-- [![dependencies][dependencies-image]][dependencies-url] --\u003e\n\n\u003e Return a flattened copy of an input [ndarray][@stdlib/ndarray/ctor].\n\n\u003csection class=\"intro\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.intro --\u003e\n\n\u003csection class=\"installation\"\u003e\n\n## Installation\n\n```bash\nnpm install @stdlib/ndarray-flatten\n```\n\nAlternatively,\n\n-   To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]).\n-   If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).\n-   For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]).\n\nThe [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships.\n\nTo view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.\n\n\u003c/section\u003e\n\n\u003csection class=\"usage\"\u003e\n\n## Usage\n\n```javascript\nvar flatten = require( '@stdlib/ndarray-flatten' );\n```\n\n#### flatten( x\\[, options] )\n\nReturns a flattened copy of an input [ndarray][@stdlib/ndarray/ctor].\n\n```javascript\nvar array = require( '@stdlib/ndarray-array' );\n\nvar x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );\n// returns \u003cndarray\u003e\n\nvar y = flatten( x );\n// returns \u003cndarray\u003e[ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]\n```\n\nThe function accepts the following arguments:\n\n-   **x**: input [ndarray][@stdlib/ndarray/ctor].\n-   **options**: function options (_optional_).\n\nThe function accepts the following options:\n\n-   **order**: order in which input [ndarray][@stdlib/ndarray/ctor] elements should be flattened. Must be one of the following:\n\n    -   `'row-major'`: flatten elements in lexicographic order. For example, given a two-dimensional input [ndarray][@stdlib/ndarray/ctor] (i.e., a matrix), flattening in lexicographic order means flattening the input [ndarray][@stdlib/ndarray/ctor] row-by-row.\n    -   `'column-major'`: flatten elements in colexicographic order. For example, given a two-dimensional input [ndarray][@stdlib/ndarray/ctor] (i.e., a matrix), flattening in colexicographic order means flattening the input [ndarray][@stdlib/ndarray/ctor] column-by-column.\n    -   `'any'`: flatten according to the physical layout of the input [ndarray][@stdlib/ndarray/ctor] data in memory, regardless of the stated [order][@stdlib/ndarray/orders] of the input [ndarray][@stdlib/ndarray/ctor].\n    -   `'same'`: flatten according to the stated [order][@stdlib/ndarray/orders] of the input [ndarray][@stdlib/ndarray/ctor].\n\n    Default: `'row-major'`.\n\n-   **depth**: maximum number of input [ndarray][@stdlib/ndarray/ctor] dimensions to flatten.\n\n-   **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having the same [data type][@stdlib/ndarray/dtypes] as a provided input [ndarray][@stdlib/ndarray/ctor].\n\nBy default, the function flattens all dimensions of the input [ndarray][@stdlib/ndarray/ctor]. To flatten to a desired depth, specify the `depth` option.\n\n```javascript\nvar array = require( '@stdlib/ndarray-array' );\n\nvar x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );\n// returns \u003cndarray\u003e\n\nvar y = flatten( x, {\n    'depth': 1\n});\n// returns \u003cndarray\u003e[ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]\n```\n\nBy default, the input [ndarray][@stdlib/ndarray/ctor] is flattened in lexicographic order. To flatten elements in a different order, specify the `order` option.\n\n```javascript\nvar array = require( '@stdlib/ndarray-array' );\n\nvar x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );\n// returns \u003cndarray\u003e\n\nvar y = flatten( x, {\n    'order': 'column-major'\n});\n// returns \u003cndarray\u003e[ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]\n```\n\nBy default, the output ndarray [data type][@stdlib/ndarray/dtypes] is inferred from the input [ndarray][@stdlib/ndarray/ctor]. To return an ndarray with a different [data type][@stdlib/ndarray/dtypes], specify the `dtype` option.\n\n```javascript\nvar array = require( '@stdlib/ndarray-array' );\nvar dtype = require( '@stdlib/ndarray-dtype' );\n\nvar x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );\n// returns \u003cndarray\u003e\n\nvar y = flatten( x, {\n    'dtype': 'float32'\n});\n// returns \u003cndarray\u003e[ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]\n\nvar dt = String( dtype( y ) );\n// returns 'float32'\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.usage --\u003e\n\n\u003csection class=\"notes\"\u003e\n\n## Notes\n\n-   The function **always** returns a copy of input [ndarray][@stdlib/ndarray/ctor] data, even when an input [ndarray][@stdlib/ndarray/ctor] already has the desired number of dimensions.\n\n\u003c/section\u003e\n\n\u003c!-- /.notes --\u003e\n\n\u003csection class=\"examples\"\u003e\n\n## Examples\n\n\u003c!-- eslint no-undef: \"error\" --\u003e\n\n```javascript\nvar discreteUniform = require( '@stdlib/random-array-discrete-uniform' );\nvar array = require( '@stdlib/ndarray-array' );\nvar ndarray2array = require( '@stdlib/ndarray-to-array' );\nvar flatten = require( '@stdlib/ndarray-flatten' );\n\nvar xbuf = discreteUniform( 12, -100, 100, {\n    'dtype': 'generic'\n});\n\nvar x = array( xbuf, {\n    'shape': [ 2, 2, 3 ],\n    'dtype': 'generic'\n});\nconsole.log( ndarray2array( x ) );\n\nvar y = flatten( x );\nconsole.log( ndarray2array( y ) );\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.examples --\u003e\n\n\u003c!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --\u003e\n\n\u003csection class=\"related\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.related --\u003e\n\n\n\u003csection class=\"main-repo\" \u003e\n\n* * *\n\n## Notice\n\nThis package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.\n\nFor more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].\n\n#### Community\n\n[![Chat][chat-image]][chat-url]\n\n---\n\n## License\n\nSee [LICENSE][stdlib-license].\n\n\n## Copyright\n\nCopyright \u0026copy; 2016-2026. The Stdlib [Authors][stdlib-authors].\n\n\u003c/section\u003e\n\n\u003c!-- /.stdlib --\u003e\n\n\u003c!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --\u003e\n\n\u003csection class=\"links\"\u003e\n\n[npm-image]: http://img.shields.io/npm/v/@stdlib/ndarray-flatten.svg\n[npm-url]: https://npmjs.org/package/@stdlib/ndarray-flatten\n\n[test-image]: https://github.com/stdlib-js/ndarray-flatten/actions/workflows/test.yml/badge.svg?branch=main\n[test-url]: https://github.com/stdlib-js/ndarray-flatten/actions/workflows/test.yml?query=branch:main\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/ndarray-flatten/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/ndarray-flatten?branch=main\n\n\u003c!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/ndarray-flatten.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/ndarray-flatten/main\n\n--\u003e\n\n[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg\n[chat-url]: https://stdlib.zulipchat.com\n\n[stdlib]: https://github.com/stdlib-js/stdlib\n\n[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors\n\n[umd]: https://github.com/umdjs/umd\n[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules\n\n[deno-url]: https://github.com/stdlib-js/ndarray-flatten/tree/deno\n[deno-readme]: https://github.com/stdlib-js/ndarray-flatten/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/ndarray-flatten/tree/umd\n[umd-readme]: https://github.com/stdlib-js/ndarray-flatten/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/ndarray-flatten/tree/esm\n[esm-readme]: https://github.com/stdlib-js/ndarray-flatten/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/ndarray-flatten/blob/main/branches.md\n\n[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/ndarray-flatten/main/LICENSE\n\n[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/ndarray-ctor\n\n[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/ndarray-dtypes\n\n[@stdlib/ndarray/orders]: https://github.com/stdlib-js/ndarray-orders\n\n\u003c!-- \u003crelated-links\u003e --\u003e\n\n\u003c!-- \u003c/related-links\u003e --\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.links --\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fndarray-flatten","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstdlib-js%2Fndarray-flatten","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fndarray-flatten/lists"}