https://github.com/stdlib-js/ndarray-dispatch-by
Create an ndarray function interface which accepts a callback function and performs multiple dispatch.
https://github.com/stdlib-js/ndarray-dispatch-by
accessor array dispatch javascript matrix multidimensional multimethod multimethods multiple-dispatch ndarray node node-js nodejs stdlib tensor vector
Last synced: 9 months ago
JSON representation
Create an ndarray function interface which accepts a callback function and performs multiple dispatch.
- Host: GitHub
- URL: https://github.com/stdlib-js/ndarray-dispatch-by
- Owner: stdlib-js
- License: apache-2.0
- Created: 2023-02-02T04:42:17.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-03-10T02:31:34.000Z (11 months ago)
- Last Synced: 2025-04-12T17:57:18.886Z (10 months ago)
- Topics: accessor, array, dispatch, javascript, matrix, multidimensional, multimethod, multimethods, multiple-dispatch, ndarray, node, node-js, nodejs, stdlib, tensor, vector
- Language: JavaScript
- Homepage: https://github.com/stdlib-js/stdlib
- Size: 1.03 MB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Security: SECURITY.md
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README
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# dispatchBy
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> Create an [ndarray][@stdlib/ndarray/ctor] function interface which performs multiple dispatch.
## Installation
```bash
npm install @stdlib/ndarray-dispatch-by
```
Alternatively,
- 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]).
- If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).
- 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]).
The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships.
To 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.
## Usage
```javascript
var dispatchBy = require( '@stdlib/ndarray-dispatch-by' );
```
#### dispatchBy( fcns, types, data, nargs, nin, nout )
Returns an [ndarray][@stdlib/ndarray/ctor] function interface which performs multiple dispatch.
```javascript
console.log( 'TODO' );
```
The function accepts the following arguments:
- **fcns**: list of [ndarray][@stdlib/ndarray/ctor] functions.
- **types**: one-dimensional list of [ndarray][@stdlib/ndarray/ctor] argument [data types][@stdlib/ndarray/dtypes]. The length of `types` must be the number of [ndarray][@stdlib/ndarray/ctor] functions multiplied by `nin+nout`. If `fcns` is a function, rather than a list, the number of [ndarray][@stdlib/ndarray/ctor] functions is computed as `types.length / (nin+nout)`.
- **data**: [ndarray][@stdlib/ndarray/ctor] function data (e.g., callbacks). If a list, the length of `data` must equal the number of [ndarray][@stdlib/ndarray/ctor] functions. If `null`, a returned [ndarray][@stdlib/ndarray/ctor] function interface does **not** provide a `data` argument to an invoked [ndarray][@stdlib/ndarray/ctor] function.
- **nargs**: total number of [ndarray][@stdlib/ndarray/ctor] function interface arguments.
- **nin**: number of input [ndarrays][@stdlib/ndarray/ctor].
- **nout**: number of output [ndarrays][@stdlib/ndarray/ctor].
## Notes
- A returned [ndarray][@stdlib/ndarray/ctor] function interface has the following signature:
```text
f( x, y, ... )
```
where
- **x**: [ndarray][@stdlib/ndarray/ctor].
- **y**: [ndarray][@stdlib/ndarray/ctor].
- **...**: additional [ndarrays][@stdlib/ndarray/ctor].
- The number of [ndarray][@stdlib/ndarray/ctor] function interface parameters is derived from `nargs`, the number of input [ndarrays][@stdlib/ndarray/ctor] is derived from `nin`, and the number of output [ndarrays][@stdlib/ndarray/ctor] is derived from `nout`.
- An [ndarray][@stdlib/ndarray/ctor] function (i.e., a value provided for the `fcns` argument) should have the following signature:
```text
f( arrays[, data] )
```
where
- **arrays**: array containing input and output [ndarrays][@stdlib/ndarray/ctor].
- **data**: [ndarray][@stdlib/ndarray/ctor] function data (e.g., a callback).
- For convenience, a single [ndarray][@stdlib/ndarray/ctor] function may be provided which will be invoked whenever the [ndarray][@stdlib/ndarray/ctor] argument data types match a sequence of types in `types`. Providing a single [ndarray][@stdlib/ndarray/ctor] function is particularly convenient for the case where, regardless of array data types, traversing arrays remains the same, but the [ndarray][@stdlib/ndarray/ctor] function `data` differs (e.g., callbacks which differ based on the array data types). For example, the following
```javascript
var unary = require( '@stdlib/ndarray-base-unary-by' );
function foo( x ) {
return x * 10.0;
}
function bar( x ) {
return x * 5.0;
}
var fcns = [
unary,
unary
];
var types = [
'float64', 'float64',
'float32', 'float32'
];
var data = [
foo,
bar
];
var fcn = dispatchBy( fcns, types, data, 2, 1, 1 );
```
is equivalent to
```javascript
var unary = require( '@stdlib/ndarray-base-unary-by' );
function foo( x ) {
return x * 10.0;
}
function bar( x ) {
return x * 5.0;
}
var types = [
'float64', 'float64',
'float32', 'float32'
];
var data = [
foo,
bar
];
var fcn = dispatchBy( unary, types, data, 2, 1, 1 );
```
## Examples
```javascript
console.log( 'TODO' );
```
* * *
## See Also
- [`@stdlib/ndarray-array`][@stdlib/ndarray/array]: multidimensional arrays.
- [`@stdlib/ndarray-ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor.
* * *
## Notice
This 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.
For 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].
#### Community
[![Chat][chat-image]][chat-url]
---
## License
See [LICENSE][stdlib-license].
## Copyright
Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/ndarray-dispatch-by.svg
[npm-url]: https://npmjs.org/package/@stdlib/ndarray-dispatch-by
[test-image]: https://github.com/stdlib-js/ndarray-dispatch-by/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/ndarray-dispatch-by/actions/workflows/test.yml?query=branch:main
[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/ndarray-dispatch-by/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/ndarray-dispatch-by?branch=main
[chat-image]: https://img.shields.io/gitter/room/stdlib-js/stdlib.svg
[chat-url]: https://app.gitter.im/#/room/#stdlib-js_stdlib:gitter.im
[stdlib]: https://github.com/stdlib-js/stdlib
[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors
[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/ndarray-dispatch-by/tree/deno
[deno-readme]: https://github.com/stdlib-js/ndarray-dispatch-by/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/ndarray-dispatch-by/tree/umd
[umd-readme]: https://github.com/stdlib-js/ndarray-dispatch-by/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/ndarray-dispatch-by/tree/esm
[esm-readme]: https://github.com/stdlib-js/ndarray-dispatch-by/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/ndarray-dispatch-by/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/ndarray-dispatch-by/main/LICENSE
[@stdlib/ndarray/array]: https://github.com/stdlib-js/ndarray-array
[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/ndarray-ctor
[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/ndarray-dtypes