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Compute the relative error exponential.
The relative error exponential is defined as
npm install @stdlib/math-base-special-expm1relvar expm1rel = require( '@stdlib/math-base-special-expm1rel' );Computes the relative error exponential.
var v = expm1rel( 0.0 );
// returns 1.0
v = expm1rel( 1.0 );
// returns ~1.718
v = expm1rel( -1.0 );
// returns ~0.632
v = expm1rel( NaN );
// returns NaN- When
xis near zero,exp(x)-1can suffer catastrophic cancellation (i.e., a significant loss in precision).expm1relavoids such a loss in precision.
var randu = require( '@stdlib/random-base-randu' );
var expm1rel = require( '@stdlib/math-base-special-expm1rel' );
var x;
var y;
var a;
var i;
for ( i = 0; i < 100; i++ ) {
x = (randu()*100.0) - 50.0;
a = x.toFixed( 3 );
y = expm1rel( x );
console.log( '(e^%d - 1)/%d = %d', a, a, y );
}#include "stdlib/math/base/special/expm1rel.h"Computes the relative error exponential.
double out = stdlib_base_expm1rel( 0.0 );
// returns 1.0
out = stdlib_base_expm1rel( 1.0 );
// returns ~1.718The function accepts the following arguments:
-
x:
[in] doubleinput value.
double stdlib_base_expm1rel( const double x );#include "stdlib/math/base/special/expm1rel.h"
#include <stdlib.h>
#include <stdio.h>
int main( void ) {
double x;
double v;
int i;
for ( i = 0; i < 100; i++ ) {
x = ( ( (double)rand() / (double)RAND_MAX ) * 100.0 ) - 50.0;
v = stdlib_base_expm1rel( x );
printf( "(e^%lf - 1)/%lf = %lf\n", x, x, v );
}
}-
@stdlib/math-base/special/exp: natural exponential function. -
@stdlib/math-base/special/expm1: compute exp(x) - 1.
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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