Evaluate a polynomial.
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Evaluate a [polynomial][polynomial] using double-precision floating-point arithmetic.
x can be expressed asmath
c_nx^n + c_{n-1}x^{n-1} + \ldots + c_1x^1 + c_0 = \sum_{i=0}^{n} c_ix^ic_n, c_{n-1}, ..., c_0 are constants.bash
npm install @stdlib/math-base-tools-evalpolyscript tag without installation and bundlers, use the [ES Module][es-module] available on the [esm][esm-url] branch (see [README][esm-readme]).deno][deno-url] branch (see [README][deno-readme] for usage intructions).umd][umd-url] branch (see [README][umd-readme]).javascript
var evalpoly = require( '@stdlib/math-base-tools-evalpoly' );c and degree n at a value x, where n = c.length-1.javascript
var v = evalpoly( [ 3.0, 2.0, 1.0 ], 10 ); // => 3*10^0 + 2*10^1 + 1*10^2
// returns 123.0javascript
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 38.0evalpoly().javascript
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 ) );
}
