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@stdlib/math-base-tools-evalpoly
Advanced tools
Evaluate a polynomial using double-precision floating-point arithmetic.
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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-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 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
evalpoly()
.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 © 2016-2024. The Stdlib Authors.
0.2.2 (2024-07-26)
<section class="commits">189c569
- docs: update related packages sections (#2194) (by stdlib-bot)c742a6f
- docs: rename variable (by Athan Reines)6fa2c20
- style: add missing spaces (by Athan Reines)ac93021
- docs: update examples and rearrange tests (by Athan Reines)e459df4
- bench: refactor to avoid value creation during benchmarking (by Athan Reines)5d61c88
- test: update messages and assertions (by Athan Reines)aa37d2f
- docs: update description and examples (by Athan Reines)A total of 1 person contributed to this release. Thank you to this contributor:
FAQs
Evaluate a polynomial using double-precision floating-point arithmetic.
The npm package @stdlib/math-base-tools-evalpoly receives a total of 36,428 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 0 open source maintainers collaborating on the project.
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