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@stdlib/math-base-tools-evalpoly
Advanced tools
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Evaluate a polynomial.
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-evalpoly
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 123.0
The 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.
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
evalpoly().var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var evalpoly = require( '@stdlib/math-base-tools-evalpoly' );
var polyval;
var coef;
var sign;
var v;
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 );
}
// Evaluate the polynomial at random values...
for ( i = 0; i < 100; i++ ) {
v = randu() * 100.0;
console.log( 'f(%d) = %d', v, evalpoly( coef, v ) );
}
// Generate an `evalpoly` function...
polyval = evalpoly.factory( coef );
for ( i = 0; i < 100; i++ ) {
v = (randu()*100.0) - 50.0;
console.log( 'f(%d) = %d', v, polyval( v ) );
}
@stdlib/math-base/tools/evalrational: evaluate a rational function.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 © 2016-2023. The Stdlib Authors.
FAQs
Evaluate a polynomial using double-precision floating-point arithmetic.
The npm package @stdlib/math-base-tools-evalpoly receives a total of 117,204 weekly downloads. As such, @stdlib/math-base-tools-evalpoly popularity was classified as popular.
We found that @stdlib/math-base-tools-evalpoly demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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