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ndarray-input-casting-policies

List of input ndarray casting policies.

https://github.com/stdlib-js/ndarray-input-casting-policies

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array casting data dtype dtypes javascript multidimensional ndarray node node-js nodejs stdlib types util utilities utility utils
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List of input ndarray casting policies.

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array casting data dtype dtypes javascript multidimensional ndarray node node-js nodejs stdlib types util utilities utility utils
Created 10 months ago · Last pushed 9 months ago
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README.md

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Policies

NPM version Build Status Coverage Status <!-- dependencies -->

List of input ndarray casting policies.

## Installation ```bash npm install @stdlib/ndarray-input-casting-policies ``` 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 policies = require( '@stdlib/ndarray-input-casting-policies' ); ``` #### policies() Returns a list of input ndarray casting policies. ```javascript var out = policies(); // e.g., returns [ 'none', 'promoted', ... ] ``` The output array contains the following policies: - `none`: no guidance on specific casting behavior. An input ndarray may or may not be cast depending on the needs of an implementation. - `promoted`: cast an input ndarray to a promoted data type. - `accumulation`: cast an input ndarray to a data type amenable to accumulation. - `output`: cast an input ndarray to the data type of the output ndarray.
## Notes - The following is some general guidance for the casting policies listed above: - **none**: applies whenever an input ndarray casting behavior should be entirely left up to an implementation. For example, an implementation may choose to cast internally in order to take advantage of specialized algorithms operating on specific data types. - **promoted**: applies whenever an input ndarray should be cast to the data type resolved from applying the rules of [type promotion][@stdlib/ndarray/promotion-rules] to an implementation's input and output ndarrays. For example, suppose an implementation is computing the sum and the data type of the input ndarray is `int32` and the data type of the output ndarray is `float32`. In this scenario, casting `int32` to `float32` is not desirable as not all `int32` values can be safely represented in `float32`, thus potentially leading to significant accumulated numerical error. Instead, we can promote `int32` to `float64`, compute the sum, and then downcast the result for more accurate summation. - **accumulation**: applies whenever an input ndarray should be cast to a data type amenable to accumulation, irrespective of the output ndarray or other input ndarrays. For example, suppose an implementation is computing the sum and determining whether the sum passes a threshold, and further suppose that the data type of the input ndarray is `int8` and the data type of the output ndarray is `bool`. In this scenario, as `int8` has a small range of values, computing the sum has a high risk of overflow, rendering the results potentially meaningless, and type promotion is not applicable. As such, an implementation may prefer to internally cast `int8` to a data type more amenable to accumulation, such as `int32`. - **output**: applies whenever an input ndarray should always be cast to the data type of the output ndarray. This might apply when an implementation wraps a type homogeneous interface, such as those commonly found in BLAS/LAPACK routines. - Whether an implementation supports a casting policy depends on the implementation. Supporting casting policies is mainly envisioned for generalized utilities wrapping lower-level APIs and needing to accommodate varied use cases (e.g., [`@stdlib/ndarray-base/unary-reduce-strided1d-dispatch`][@stdlib/ndarray/base/unary-reduce-strided1d-dispatch]). Exposing casting policies as part of user-facing APIs is generally not a good idea.
## Examples ```javascript var indexOf = require( '@stdlib/utils-index-of' ); var policies = require( '@stdlib/ndarray-input-casting-policies' ); var POLICIES = policies(); function isPolicy( str ) { if ( indexOf( POLICIES, str ) === -1 ) { return false; } return true; } var bool = isPolicy( 'none' ); // returns true bool = isPolicy( 'output' ); // returns true bool = isPolicy( 'promoted' ); // returns true bool = isPolicy( 'beep' ); // returns false ```
* * * ## 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].

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Standard library for JavaScript.

Citation (CITATION.cff) 

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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