@stdlib/math-base-special-ldexp

Multiply a double-precision floating-point number by an integer power of two.

Usage no npm install needed!

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README

ldexp

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Multiply a double-precision floating-point number by an integer power of two.

Installation

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

Usage

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

ldexp( frac, exp )

Multiplies a double-precision floating-point number by an integer power of two; i.e., x = frac * 2^exp.

var x = ldexp( 0.5, 3 ); // => 0.5 * 2^3 = 0.5 * 8
// returns 4.0

x = ldexp( 4.0, -2 ); // => 4 * 2^(-2) = 4 * (1/4)
// returns 1.0

If frac equals positive or negative zero, NaN, or positive or negative infinity, the function returns a value equal to frac.

var x = ldexp( 0.0, 20 );
// returns 0.0

x = ldexp( -0.0, 39 );
// returns -0.0

x = ldexp( NaN, -101 );
// returns NaN

x = ldexp( Infinity, 11 );
// returns Infinity

x = ldexp( -Infinity, -118 );
// returns -Infinity

Installation

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

Notes

  • This function is the inverse of frexp.

Examples

var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var pow = require( '@stdlib/math-base-special-pow' );
var frexp = require( '@stdlib/math-base-special-frexp' );
var ldexp = require( '@stdlib/math-base-special-ldexp' );

var sign;
var frac;
var exp;
var x;
var f;
var v;
var i;

/*
* 1) Generate random numbers.
* 2) Break each number into a normalized fraction and an integer power of two.
* 3) Reconstitute the original number.
*/
for ( i = 0; i < 100; i++ ) {
    if ( randu() < 0.5 ) {
        sign = -1.0;
    } else {
        sign = 1.0;
    }
    frac = randu() * 10.0;
    exp = round( randu()*616.0 ) - 308;
    x = sign * frac * pow( 10.0, exp );
    f = frexp( x );
    v = ldexp( f[ 0 ], f[ 1 ] );
    console.log( '%d = %d * 2^%d = %d', x, f[ 0 ], f[ 1 ], v );
}

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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License

See LICENSE.

Copyright

Copyright © 2016-2021. The Stdlib Authors.