@stdlib/math-base-special-log1p

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log1p

Evaluate the natural logarithm of 1+x.

Installation

npm install @stdlib/math-base-special-log1p

Usage

var log1p = require( '@stdlib/math-base-special-log1p' );

log1p( x )

Evaluates the natural logarithm of 1+x.

var v = log1p( 4.0 );
// returns ~1.609

v = log1p( -1.0 );
// returns -Infinity

v = log1p( Infinity );
// returns Infinity

v = log1p( 0.0 );
// returns 0.0

v = log1p( -0.0 );
// returns -0.0

v = log1p( NaN );
// returns NaN

For x < -1, the function returns NaN, as the natural logarithm is not defined for negative numbers.

var v = log1p( -2.0 );
// returns NaN

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var log1p = require( '@stdlib/math-base-special-log1p' );

var opts = {
    'dtype': 'float64'
};
var x = discreteUniform( 100, 0, 100, opts );

logEachMap( 'log1p( %0.4f ) = %0.4f', x, log1p );

C APIs

Usage

#include "stdlib/math/base/special/log1p.h"

stdlib_base_log1p( x )

Evaluates the natural logarithm of 1+x.

double out = stdlib_base_log1p( 4.0 );
// returns ~1.609

out = stdlib_base_log1p( -1.0 );
// returns -Infinity

The function accepts the following arguments:

• x: [in] double input value.

double stdlib_base_log1p( const double x );

Examples

#include "stdlib/math/base/special/log1p.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;
        v = stdlib_base_log1p( x );
        printf( "log1p(%lf) = %lf\n", x, v );
    }
}

See Also

• @stdlib/math-base/special/ln: evaluate the natural logarithm of a double-precision floating-point number.
• @stdlib/math-base/special/log: compute the base b logarithm of a double-precision floating-point number.

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.

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Copyright

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