kernelLog1pf

Evaluate a correction term for single-precision base-2 and base-10 logarithms when 1 + f is in [√2/2, √2].

Installation

npm install @stdlib/math-base-special-kernel-log1pf

Usage

var kernelLog1pf = require( '@stdlib/math-base-special-kernel-log1pf' );

kernelLog1pf( f )

Evaluates a correction term for single-precision base-2 and base-10 logarithms when 1 + f is in [√2/2, √2].

var v = kernelLog1pf( 1.0 );
// returns ~0.1931

v = kernelLog1pf( 1.4142135381698608 );
// returns ~0.4672

v = kernelLog1pf( NaN );
// returns NaN

Notes

• This function is a helper function for computing logarithms in base e. Argument reduction and adding the final term of the polynomial must be done by the caller for increased accuracy when different bases are used.

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var sqrtf = require( '@stdlib/math-base-special-sqrtf' );
var kernelLog1pf = require( '@stdlib/math-base-special-kernel-log1pf' );

var opts = {
    'dtype': 'float32'
};
var x = uniform( 100, sqrtf( 2.0 ) / 2.0, sqrtf( 2.0 ), opts );

logEachMap( 'kernelLog1pf(%0.4f) = %0.4f', x, kernelLog1pf );

C APIs

Usage

#include "stdlib/math/base/special/kernel_log1pf.h"

stdlib_base_kernel_log1pf( f )

Evaluates a correction term for single-precision base-2 and base-10 logarithms when 1 + f is in [√2/2, √2].

float out = stdlib_base_kernel_log1pf( 1.0f );
// returns ~0.1931f

The function accepts the following arguments:

• f: [in] float input value.

float stdlib_base_kernel_log1pf( const float f );

Examples

#include "stdlib/math/base/special/kernel_log1pf.h"
#include <stdio.h>

int main( void ) {
    const float x[] = { 0.7071f, 0.7856f, 0.8642f, 0.9428f, 1.0213f, 1.0999f, 1.1785f, 1.2570f, 1.3356f, 1.4142f };

    float out;
    int i;
    for ( i = 0; i < 10; i++ ) {
        out = stdlib_base_kernel_log1pf( x[ i ] );
        printf ( "kernelLog1pf(%f) = %f\n", x[ i ], out );
    }
}

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.

Community

Copyright

Copyright © 2016-2026. The Stdlib Authors.