@stdlib/math-base-tools-evalpoly

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

Evaluate a polynomial using double-precision floating-point arithmetic.

A polynomial in a variable x can be expressed as

where c_n, c_{n-1}, ..., c_0 are constants.

Installation

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

Usage

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

evalpoly( c, x )

Evaluates a polynomial having coefficients c and degree n at a value x, where n = c.length-1.

var v = evalpoly( [ 3.0, 2.0, 1.0 ], 10 ); // => 3*10^0 + 2*10^1 + 1*10^2
// returns 123.0

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

evalpoly.factory( c )

Uses code generation to in-line coefficients and return a function for evaluating a polynomial using double-precision floating-point arithmetic.

var polyval = evalpoly.factory( [ 3.0, 2.0, 1.0 ] );

var v = polyval( 10.0 ); // => 3*10^0 + 2*10^1 + 1*10^2
// returns 123.0

v = polyval( 5.0 ); // => 3*5^0 + 2*5^1 + 1*5^2
// returns 38.0

Notes

• For hot code paths in which coefficients are invariant, a compiled function will be more performant than evalpoly().
• While code generation can boost performance, its use may be problematic in browser contexts enforcing a strict content security policy (CSP). If running in or targeting an environment with a CSP, avoid using code generation.

Examples

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

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

// Evaluate the polynomial at random values:
var v;
var i;
for ( i = 0; i < 100; i++ ) {
    v = uniform( 0.0, 100.0 );
    console.log( 'f(%d) = %d', v, evalpoly( coef, v ) );
}

// Generate an `evalpoly` function:
var polyval = evalpoly.factory( coef );
for ( i = 0; i < 100; i++ ) {
    v = uniform( -50.0, 50.0 );
    console.log( 'f(%d) = %d', v, polyval( v ) );
}

See Also

• @stdlib/math-base/tools/evalrational: evaluate a rational function using double-precision floating-point arithmetic.

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.