@stdlib/math-base-tools-evalpoly-compile
v0.2.1
Published
Compile a module for evaluating a polynomial.
Downloads
840
Readme
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 )
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>
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))); // eslint-disable-line max-len
}
// EXPORTS //
module.exports = evalpoly;
The coefficients should be ordered in ascending degree, thus matching summation notation.
Notes
- The function is intended for non-browser environments for the purpose of generating module files.
Examples
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var compile = require( '@stdlib/math-base-tools-evalpoly-compile' );
var coef;
var sign;
var str;
var i;
// Create an array of random coefficients...
coef = new Float64Array( 10 );
for ( i = 0; i < coef.length; i++ ) {
if ( randu() < 0.5 ) {
sign = -1.0;
} else {
sign = 1.0;
}
coef[ i ] = sign * round( randu()*100.0 );
}
// Compile a module for evaluating a polynomial:
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.