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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.
npm install @stdlib/math-base-tools-evalpolyAlternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (see README).
The branches.md 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.
var evalpoly = require( '@stdlib/math-base-tools-evalpoly' );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 123.0The coefficients should be ordered in ascending degree, thus matching summation notation.
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- 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.
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 ) );
}@stdlib/math-base/tools/evalrational: evaluate a rational function using double-precision floating-point arithmetic.
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.
See LICENSE.
Copyright © 2016-2025. The Stdlib Authors.
