logaddexp

Evaluates the natural logarithm of exp(x) + exp(y).

Log-domain computations are commonly used to increase accuracy and avoid underflow and overflow when very small or very large numbers are represented directly as limited-precision, floating-point numbers. For example, in statistics, evaluating logaddexp() is useful when probabilities are so small as to exceed the normal range of floating-point numbers.

Installation

npm install @stdlib/math-base-special-logaddexp

Alternatively,

To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm 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.

Usage

var logaddexp = require( '@stdlib/math-base-special-logaddexp' );

logaddexp( x, y )

Evaluates the natural logarithm of exp(x) + exp(y).

var v = logaddexp( 90.0, 90.0 );
// returns ~90.6931

v = logaddexp( -20.0, 90.0 );
// returns 90.0

v = logaddexp( 0.0, -100.0 );
// returns ~3.7201e-44

v = logaddexp( NaN, 1.0 );
// returns NaN

Examples

var incrspace = require( '@stdlib/array-base-incrspace' );
var logaddexp = require( '@stdlib/math-base-special-logaddexp' );

var x = incrspace( -100.0, 100.0, 1.0 );

var v;
var i;
var j;
for ( i = 0; i < x.length; i++ ) {
    for ( j = i; j < x.length; j++ ) {
        v = logaddexp( x[ i ], x[ j ] );
        console.log( 'x: %d, y: %d, f(x, y): %d', x[ i ], x[ j ], v );
    }
}

C APIs

Usage

#include "stdlib/math/base/special/logaddexp.h"

stdlib_base_logaddexp( x, y )

Evaluates the natural logarithm of exp(x) + exp(y).

double out = stdlib_base_logaddexp( 90.0, 90.0 );
// returns ~90.6931

out = stdlib_base_logaddexp( -20.0, 90.0 );
// returns 90.0

The function accepts the following arguments:

x: [in] double input value.
y: [in] double input value.

double stdlib_base_logaddexp( const double x, const double y );

Examples

#include "stdlib/math/base/special/logaddexp.h"
#include <stdlib.h>
#include <stdio.h>

int main( void ) {
    double x;
    double y;
    double v;
    int i;
    
    for ( i = 0; i < 100; i++ ) {
        x = ( ( (double)rand() / (double)RAND_MAX ) * 200.0 ) - 100.0;
        y = ( ( (double)rand() / (double)RAND_MAX ) * 200.0 ) - 100.0;
        v = stdlib_base_logaddexp( x, y );
        printf( "x: %lf, y: %lf, logaddexp(x, y): %lf\n", x, y, v );
    }
}

Notice

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.