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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\u003c!-- lint disable maximum-heading-length --\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# UnaryStrided1dDispatchBy\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 Constructor for performing a reduction on an input ndarray according to a callback function.\n\n\u003csection class=\"installation\"\u003e\n\n## Installation\n\n```bash\nnpm install @stdlib/ndarray-base-unary-reduce-strided1d-dispatch-by\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 UnaryStrided1dDispatchBy = require( '@stdlib/ndarray-base-unary-reduce-strided1d-dispatch-by' );\n```\n\n#### UnaryStrided1dDispatchBy( table, idtypes, odtypes, policies )\n\nConstructor for performing a reduction on an input ndarray according to a callback function.\n\n```javascript\nvar base = require( '@stdlib/stats-base-ndarray-max-by' );\n\nvar table = {\n    'default': base\n};\n\nvar dtypes = [ 'float64', 'float32', 'generic' ];\nvar policies = {\n    'output': 'same',\n    'casting': 'none'\n};\n\nvar unary = new UnaryStrided1dDispatchBy( table, [ dtypes ], dtypes, policies );\n```\n\nThe constructor has the following parameters:\n\n-   **table**: strided reduction function dispatch table. Must have the following properties:\n\n    -   **default**: default strided reduction function which should be invoked when provided ndarrays have data types which do not have a corresponding specialized implementation.\n\n    A dispatch table may have the following additional properties:\n\n    -   **types**: one-dimensional list of ndarray data types describing specialized input ndarray argument signatures. Only the input ndarray argument data types should be specified. Output ndarray and additional input ndarray argument data types should be omitted and are not considered during dispatch. The length of `types` must equal the number of strided functions specified by `fcns` (i.e., for every input ndarray data type, there must be a corresponding strided reduction function in `fcns`).\n    -   **fcns**: list of strided reduction functions which are specific to specialized input ndarray argument signatures.\n\n-   **idtypes**: list containing lists of supported input data types for each input ndarray argument.\n\n-   **odtypes**: list of supported output data types.\n\n-   **policies**: dispatch policies. Must have the following properties:\n\n    -   **output**: output data type [policy][@stdlib/ndarray/output-dtype-policies].\n    -   **casting**: input ndarray casting [policy][@stdlib/ndarray/input-casting-policies].\n\n#### UnaryStrided1dDispatchBy.prototype.apply( x\\[, ...args]\\[, options], clbk\\[, thisArg] )\n\nPerforms a reduction on a provided input ndarray according to a callback function.\n\n```javascript\nvar ndarray = require( '@stdlib/ndarray-base-ctor' );\nvar base = require( '@stdlib/stats-base-ndarray-max-by' );\n\nvar table = {\n    'default': base\n};\n\nvar dtypes = [ 'float64', 'float32', 'generic' ];\nvar policies = {\n    'output': 'same',\n    'casting': 'none'\n};\n\nvar unary = new UnaryStrided1dDispatchBy( table, [ dtypes ], dtypes, policies );\n\nvar xbuf = [ -1.0, 2.0, -3.0 ];\nvar x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );\n\nfunction clbk( v ) {\n    return v * 2.0;\n}\n\nvar y = unary.apply( x, clbk );\n// returns \u003cndarray\u003e\n\nvar v = y.get();\n// returns 4.0\n```\n\nThe method has the following parameters:\n\n-   **x**: input ndarray.\n-   **...args**: additional input ndarray arguments (_optional_).\n-   **options**: function options (_optional_).\n-   **clbk**: callback function.\n-   **thisArg**: callback function execution context (_optional_).\n\nThe method accepts the following options:\n\n-   **dims**: list of dimensions over which to perform a reduction.\n-   **dtype**: output ndarray data type. Setting this option overrides the output data type policy.\n-   **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions. Default: `false`.\n\nBy default, the method returns an ndarray having a data type determined by the output data type policy. To override the default behavior, set the `dtype` option.\n\n```javascript\nvar ndarray = require( '@stdlib/ndarray-base-ctor' );\nvar base = require( '@stdlib/stats-base-ndarray-max-by' );\nvar getDType = require( '@stdlib/ndarray-dtype' );\n\nvar table = {\n    'default': base\n};\n\nvar dtypes = [ 'float64', 'float32', 'generic' ];\nvar policies = {\n    'output': 'same',\n    'casting': 'none'\n};\n\nvar unary = new UnaryStrided1dDispatchBy( table, [ dtypes ], dtypes, policies );\n\nvar xbuf = [ -1.0, 2.0, -3.0 ];\nvar x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );\n\nfunction clbk( v ) {\n    return v * 2.0;\n}\n\nvar opts = {\n    'dtype': 'float64'\n};\nvar y = unary.apply( x, opts, clbk );\n// returns \u003cndarray\u003e\n\nvar dt = String( getDType( y ) );\n// returns 'float64'\n```\n\n#### UnaryStrided1dDispatchBy.prototype.assign( x\\[, ...args], out\\[, options], clbk\\[, thisArg] )\n\nPerforms a reduction on a provided input ndarray according to a callback function and assigns results to a provided output ndarray.\n\n```javascript\nvar base = require( '@stdlib/stats-base-ndarray-max-by' );\nvar dtypes = require( '@stdlib/ndarray-dtypes' );\nvar ndarray = require( '@stdlib/ndarray-base-ctor' );\n\nvar idt = dtypes( 'real_and_generic' );\nvar odt = idt;\nvar policies = {\n    'output': 'same',\n    'casting': 'none'\n};\n\nvar table = {\n    'default': base\n};\nvar unary = new UnaryStrided1dDispatchBy( table, [ idt ], odt, policies );\n\nvar xbuf = [ -1.0, 2.0, -3.0 ];\nvar x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );\n\nvar ybuf = [ 0.0 ];\nvar y = new ndarray( 'generic', ybuf, [], [ 0 ], 0, 'row-major' );\n\nfunction clbk( v ) {\n    return v * 2.0;\n}\n\nvar out = unary.assign( x, y, clbk );\n// returns \u003cndarray\u003e\n\nvar v = out.get();\n// returns 4.0\n\nvar bool = ( out === y );\n// returns true\n```\n\nThe method has the following parameters:\n\n-   **x**: input ndarray.\n-   **args**: additional input ndarray arguments (_optional_).\n-   **out**: output ndarray.\n-   **options**: function options (_optional_).\n-   **clbk**: callback function.\n-   **thisArg**: callback function execution context (_optional_).\n\nThe method accepts the following options:\n\n-   **dims**: list of dimensions over which to perform a reduction.\n\n\u003c/section\u003e\n\n\u003c!-- /.usage --\u003e\n\n\u003csection class=\"notes\"\u003e\n\n## Notes\n\n-   A strided reduction function should have the following signature:\n\n    ```text\n    f( arrays, clbk, thisArg )\n    ```\n\n    where\n\n    -   **arrays**: array containing an input ndarray, followed by any additional ndarray arguments.\n    -   **clbk**: callback function.\n    -   **thisArg**: callback function execution context.\n\n-   The output data type policy only applies to the `apply` method. For the `assign` method, the output ndarray is allowed to have any supported output data type.\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 base = require( '@stdlib/stats-base-ndarray-max-by' );\nvar filledarrayBy = require( '@stdlib/array-filled-by' );\nvar uniform = require( '@stdlib/random-base-uniform' );\nvar dtypes = require( '@stdlib/ndarray-dtypes' );\nvar dtype = require( '@stdlib/ndarray-dtype' );\nvar ndarray2array = require( '@stdlib/ndarray-to-array' );\nvar ndarray = require( '@stdlib/ndarray-ctor' );\nvar UnaryStrided1dDispatchBy = require( '@stdlib/ndarray-base-unary-reduce-strided1d-dispatch-by' );\n\n// Define the supported input and output data types:\nvar idt = dtypes( 'real_and_generic' );\nvar odt = idt;\n\n// Define dispatch policies:\nvar policies = {\n    'output': 'same',\n    'casting': 'none'\n};\n\n// Define a dispatch table:\nvar table = {\n    'default': base\n};\n\n// Create an interface for performing a reduction:\nvar maxBy = new UnaryStrided1dDispatchBy( table, [ idt ], odt, policies );\n\n// Define a function for creating an object with a random value:\nfunction random() {\n    return {\n        'value': uniform( -1.0, 1.0 )\n    };\n}\n\n// Generate an array of random numbers:\nvar xbuf = filledarrayBy( 100, 'generic', random );\n\n// Wrap in an ndarray:\nvar x = new ndarray( 'generic', xbuf, [ 10, 10 ], [ 10, 1 ], 0, 'row-major' );\n\n// Define an accessor function:\nfunction accessor( v ) {\n    return v.value * 100.0;\n}\n\n// Perform a reduction:\nvar opts = {\n    'dims': [ 0 ]\n};\nvar y = maxBy.apply( x, opts, accessor );\n\n// Resolve the output array data type:\nvar dt = dtype( y );\nconsole.log( dt );\n\n// Print the results:\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\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\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## 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-base-unary-reduce-strided1d-dispatch-by.svg\n[npm-url]: https://npmjs.org/package/@stdlib/ndarray-base-unary-reduce-strided1d-dispatch-by\n\n[test-image]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/actions/workflows/test.yml/badge.svg?branch=main\n[test-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/actions/workflows/test.yml?query=branch:main\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by?branch=main\n\n\u003c!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/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-base-unary-reduce-strided1d-dispatch-by/tree/deno\n[deno-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/tree/umd\n[umd-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/tree/esm\n[esm-readme]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/ndarray-base-unary-reduce-strided1d-dispatch-by/blob/main/branches.md\n\n[@stdlib/ndarray/output-dtype-policies]: https://github.com/stdlib-js/ndarray-output-dtype-policies\n\n[@stdlib/ndarray/input-casting-policies]: https://github.com/stdlib-js/ndarray-input-casting-policies\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-base-unary-reduce-strided1d-dispatch-by","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstdlib-js%2Fndarray-base-unary-reduce-strided1d-dispatch-by","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fndarray-base-unary-reduce-strided1d-dispatch-by/lists"}