time-to-botec/js/node_modules/@stdlib/math/base/special/logaddexp
NunoSempere b6addc7f05 feat: add the node modules
Necessary in order to clearly see the squiggle hotwiring.
2022-12-03 12:44:49 +00:00
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lib feat: add the node modules 2022-12-03 12:44:49 +00:00
package.json feat: add the node modules 2022-12-03 12:44:49 +00:00
README.md feat: add the node modules 2022-12-03 12:44:49 +00:00

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.

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

var x;
var v;
var i;
var j;

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