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@stdlib/math-base-special-kernel-log1p

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kernelLog1p

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

Installation

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

Usage

var kernelLog1p = require( '@stdlib/math-base-special-kernel-log1p' );
kernelLog1p( f )

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

var v = kernelLog1p( 1.0 );
// returns ~0.1931

v = kernelLog1p( 1.4142135623730951 );
// returns ~0.4672

v = kernelLog1p( NaN );
// returns NaN

Notes

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var sqrt = require( '@stdlib/math-base-special-sqrt' );
var kernelLog1p = require( '@stdlib/math-base-special-kernel-log1p' );

var opts = {
    'dtype': 'float64'
};
var x = uniform( 100, sqrt( 2.0 ) / 2.0, sqrt( 2.0 ), opts );

logEachMap( 'kernelLog1p(%0.4f) = %0.4f', x, kernelLog1p );

C APIs

Usage
#include "stdlib/math/base/special/kernel_log1p.h"
stdlib_base_kernel_log1p( f )

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

double out = stdlib_base_kernel_log1p( 1.0 );
// returns ~0.1931

out = stdlib_base_kernel_log1p( 1.4142135623730951 );
// returns ~0.4672

The function accepts the following arguments:

  • f: [in] double input value.
double stdlib_base_kernel_log1p( const double f );
Examples
#include "stdlib/math/base/special/kernel_log1p.h"
#include <stdio.h>

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

    double out;
    int i;
    for ( i = 0; i < 10; i++ ) {
        out = stdlib_base_kernel_log1p( x[ i ] );
        printf ( "x[ i ]: %lf, out: %lf\n", x[ i ], out );
    }
}

See Also


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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