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Evaluate a polynomial using single-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-evalpolyf
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (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 evalpolyf = require( '@stdlib/math-base-tools-evalpolyf' );
Evaluates a polynomial having coefficients c
and degree n
at a value x
, where n = c.length-1
.
var Float32Array = require( '@stdlib/array-float32' );
var v = evalpolyf( new Float32Array( [ 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 single-precision floating-point arithmetic.
var Float32Array = require( '@stdlib/array-float32' );
var polyval = evalpolyf.factory( new Float32Array( [ 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
evalpolyf()
. - 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 evalpolyf = require( '@stdlib/math-base-tools-evalpolyf' );
// Create an array of random coefficients:
var coef = discreteUniform( 10, -100, 100, {
'dtype': 'float32'
});
// 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, evalpolyf( coef, v ) );
}
// Generate an `evalpolyf` function:
var polyval = evalpolyf.factory( coef );
for ( i = 0; i < 100; i++ ) {
v = uniform( -50.0, 50.0 );
console.log( 'f(%d) = %d', v, polyval( v ) );
}
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.
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