@stdlib/math-base-tools-evalpoly-compile

About stdlib...

We 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.

The 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.

When 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.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

evalpoly

Compile a module for evaluating a polynomial.

Installation

npm install @stdlib/math-base-tools-evalpoly-compile

Usage

var compile = require( '@stdlib/math-base-tools-evalpoly-compile' );

compile( c[, options] )

Compiles a module string containing an exported function which evaluates a polynomial having coefficients c.

var str = compile( [ 3.0, 2.0, 1.0 ] );
// returns <string>

The function supports the following options:

• dtype: input argument floating-point data type (e.g., float64 or float32). Default: 'float64'.

In the example above, the output string would correspond to the following module:

'use strict';

// MAIN //

/**
* Evaluates a polynomial.
*
* ## Notes
*
* -   The implementation uses [Horner's rule][horners-method] for efficient computation.
*
* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method
*
* @private
* @param {number} x - value at which to evaluate the polynomial
* @returns {number} evaluated polynomial
*/
function evalpoly( x ) {
    if ( x === 0.0 ) {
        return 3.0;
    }
    return 3.0 + (x * (2.0 + (x * 1.0)));
}


// EXPORTS //

module.exports = evalpoly;

The coefficients should be ordered in ascending degree, thus matching summation notation.

By default, the function assumes double-precision floating-point arithmetic. To emulate single-precision floating-point arithmetic, set the dtype option to 'float32'.

var str = compile( [ 3.0, 2.0, 1.0 ], {
    'dtype': 'float32'
});
// returns <string>

In the previous example, the output string would correspond to the following module:

'use strict';

// MODULES //

var float64ToFloat32 = require( '@stdlib/number-float64-base-to-float32' );


// MAIN //

/**
* Evaluates a polynomial.
*
* ## Notes
*
* -   The implementation uses [Horner's rule][horners-method] for efficient computation.
*
* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method
*
* @private
* @param {number} x - value at which to evaluate the polynomial
* @returns {number} evaluated polynomial
*/
function evalpoly( x ) {
    if ( x === 0.0 ) {
        return 3.0;
    }
    return float64ToFloat32(3.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * 1.0)))); // eslint-disable-line max-len
}


// EXPORTS //

module.exports = evalpoly;

Notes

• The function is intended for non-browser environments for the purpose of generating module files.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var compile = require( '@stdlib/math-base-tools-evalpoly-compile' );

// Create an array of random coefficients:
var coef = discreteUniform( 10, -100, 100 );

// Compile a module for evaluating a polynomial:
var str = compile( coef );
console.log( str );

---

Notice

This package is part of 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, see the main project repository.

Community

---

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.

Changelog

0.3.0 (2024-07-27)

<section class="features">

Features

• c4ccb4b - add support for single-precision floating-point arithmetic emulation

</section> <!-- /.features --> <section class="bug-fixes">

Bug Fixes

• 1cfdb61 - allow array-like objects

</section> <!-- /.bug-fixes --> <section class="commits">

Commits

<details>

• 1cfdb61 - fix: allow array-like objects (by Athan Reines)
• c4ccb4b - feat: add support for single-precision floating-point arithmetic emulation (by Athan Reines)

</details> </section> <!-- /.commits --> <section class="contributors">

Contributors

A total of 1 person contributed to this release. Thank you to this contributor:

• Athan Reines

</section> <!-- /.contributors --> </section> <!-- /.release --> <section class="release" id="v0.2.1">