# evalpoly
> Compile a module for evaluating a [polynomial][@stdlib/math/base/tools/evalpoly].
## Usage
```javascript
var compile = require( '@stdlib/math/base/tools/evalpoly-compile' );
```
#### compile( c )
Compiles a module `string` containing an exported function which evaluates a [polynomial][@stdlib/math/base/tools/evalpoly] having coefficients `c`.
```javascript
var str = compile( [ 3.0, 2.0, 1.0 ] );
// returns
```
In the example above, the output `string` would correspond to the following module:
```javascript
'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
```javascript
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 );
```
[@stdlib/math/base/tools/evalpoly]: https://www.npmjs.com/package/@stdlib/math/tree/main/base/tools/evalpoly