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Return an integer corresponding to the unbiased exponent of a double-precision floating-point number.
npm install @stdlib/number-float64-base-exponent
var exponent = require( '@stdlib/number-float64-base-exponent' );
Returns an integer
corresponding to the unbiased exponent of a double-precision floating-point number.
var exp = exponent( 3.14e307 ); // => 2**1021 ~ 1e307
// returns 1021
exp = exponent( 3.14e-307 ); // => 2**-1019 ~ 1e-307
// returns -1019
exp = exponent( -3.14 );
// returns 1
exp = exponent( 0.0 );
// returns -1023
exp = exponent( NaN );
// returns 1024
var randu = require( '@stdlib/random-base-uniform' );
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var pow = require( '@stdlib/math-base-special-pow' );
var exponent = require( '@stdlib/number-float64-base-exponent' );
var frac;
var exp;
var x;
var e;
var i;
// Generate random numbers and extract their exponents...
for ( i = 0; i < 100; i++ ) {
frac = randu( 0.0, 10.0 );
exp = discreteUniform( -323, 323 );
x = frac * pow( 10.0, exp );
e = exponent( x );
console.log( 'x: %d. unbiased exponent: %d.', x, e );
}
#include "stdlib/number/float64/base/exponent.h"
Returns an integer corresponding to the unbiased exponent of a double-precision floating-point number.
#include <stdint.h>
int32_t out = stdlib_base_float64_exponent( 3.14 );
The function accepts the following arguments:
-
x:
[in] double
input value.
int32_t stdlib_base_float64_exponent( const double x );
#include "stdlib/number/float64/base/exponent.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>
int main( void ) {
double x[] = { 4.0, 0.0, -0.0, 1.0, -1.0, 3.14, -3.14, 1.0e308, -1.0e308, 1.0/0.0, -1.0/0.0, 0.0/0.0 };
int32_t out;
int i;
for ( i = 0; i < 12; i++ ) {
out = stdlib_base_float64_exponent( x[ i ] );
printf( "%lf => out: %" PRId32 "\n", x[ i ], out );
}
}
-
@stdlib/number-float32/base/exponent
: return an integer corresponding to the unbiased exponent of a single-precision floating-point number.
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.
See LICENSE.
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