evalrational
Compile a C function for evaluating a rational function.
Usage
var compile = require( '@stdlib/math/base/tools/evalrational-compile-c' );
compile( P, Q )
Compiles a C function for evaluating a rational function having coefficients P
and Q
.
var P = [ 3.0, 2.0, 1.0 ];
var Q = [ -1.0, -2.0, -3.0 ];
var str = compile( P, Q );
// returns <string>
The function supports the following options
:
- dtype: input argument floating-point data type (e.g.,
double
orfloat
). Default:'double'
. - name: function name. Default:
'evalpoly'
.
In the example above, the output string would correspond to the following function:
/**
* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)).
*
* ## Notes
*
* - Coefficients should be sorted in ascending degree.
* - The implementation uses [Horner's rule][horners-method] for efficient computation.
*
* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method
*
* @param x value at which to evaluate the rational function
* @returns evaluated rational function
*/
static double evalrational( const double x ) {
double ax;
double ix;
double s1;
double s2;
if ( x == 0.0 ) {
return -3.0;
}
if ( x < 0.0 ) {
ax = -x;
} else {
ax = x;
}
if ( ax <= 1.0 ) {
s1 = 3.0 + (x * (2.0 + (x * 1.0)));
s2 = -1.0 + (x * (-2.0 + (x * -3.0)));
} else {
ix = 1.0 / x;
s1 = 1.0 + (ix * (2.0 + (ix * 3.0)));
s2 = -3.0 + (ix * (-2.0 + (ix * -1.0)));
}
return s1 / s2;
}
To generate a function having a custom name and supporting single-precision floating-point numbers, provide the corresponding options.
var P = [ 3.0, 2.0, 1.0 ];
var Q = [ -1.0, -2.0, -3.0 ];
var opts = {
'dtype': 'float',
'name': 'rational123'
};
var str = compile( P, Q, opts );
// returns <string>
For the previous example, the output string would correspond to the following function:
/**
* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)).
*
* ## Notes
*
* - Coefficients should be sorted in ascending degree.
* - The implementation uses [Horner's rule][horners-method] for efficient computation.
*
* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method
*
* @param x value at which to evaluate the rational function
* @returns evaluated rational function
*/
static float rational123( const float x ) {
float ax;
float ix;
float s1;
float s2;
if ( x == 0.0f ) {
return -3.0f;
}
if ( x < 0.0f ) {
ax = -x;
} else {
ax = x;
}
if ( ax <= 1.0f ) {
s1 = 3.0f + (x * (2.0f + (x * 1.0f)));
s2 = -1.0f + (x * (-2.0f + (x * -3.0f)));
} else {
ix = 1.0f / x;
s1 = 1.0f + (ix * (2.0f + (ix * 3.0f)));
s2 = -3.0f + (ix * (-2.0f + (ix * -1.0f)));
}
return s1 / s2;
}
Notes
- The coefficients should be ordered in ascending degree, thus matching summation notation.
- The function is intended for non-browser environments for the purpose of generating module files.
Examples
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/evalrational-compile-c' );
var sign;
var str;
var P;
var Q;
var i;
// Create two arrays of random coefficients...
P = new Float64Array( 10 );
Q = new Float64Array( 10 );
for ( i = 0; i < P.length; i++ ) {
if ( randu() < 0.5 ) {
sign = -1.0;
} else {
sign = 1.0;
}
P[ i ] = sign * round( randu()*100.0 );
Q[ i ] = sign * round( randu()*100.0 );
}
// Compile a function for evaluating a rational function:
str = compile( P, Q );
console.log( str );