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Multiply a double-precision floating-point number by an integer power of two.
import ldexp from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-ldexp@esm/index.mjs';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 1.0If 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- This function is the inverse of
frexp.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">
import randu from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@esm/index.mjs';
import round from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-round@esm/index.mjs';
import pow from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-pow@esm/index.mjs';
import frexp from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-frexp@esm/index.mjs';
import ldexp from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-ldexp@esm/index.mjs';
var sign;
var frac;
var exp;
var x;
var f;
var v;
var i;
for ( i = 0; i < 100; i++ ) {
if ( randu() < 0.5 ) {
sign = -1.0;
} else {
sign = 1.0;
}
// Generate a random number:
frac = randu() * 10.0;
exp = round( randu()*616.0 ) - 308;
x = sign * frac * pow( 10.0, exp );
// Break the number into a normalized fraction and an integer power of two:
f = frexp( x );
// Reconstitute the original number:
v = ldexp( f[ 0 ], f[ 1 ] );
console.log( '%d = %d * 2^%d = %d', x, f[ 0 ], f[ 1 ], v );
}
</script>
</body>
</html>@stdlib/math-base/special/frexp: split a double-precision floating-point number into a normalized fraction and an integer power of two.
This package is part of stdlib, a standard library 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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