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@stdlib/number-float64-base-exponent
Advanced tools
Return an integer corresponding to the unbiased exponent of a double-precision floating-point number.
@stdlib/number-float64-base-exponent is a package that provides functionality to extract the exponent from a double-precision floating-point number (float64). This can be useful in various numerical computations where understanding the exponent part of a floating-point number is necessary.
Extract Exponent
This feature allows you to extract the exponent from a given double-precision floating-point number. In this example, the exponent of 4.0 is extracted, which is 2.
const exponent = require('@stdlib/number-float64-base-exponent');
const exp = exponent(4.0); // returns 2
The math-float64-exponent package provides similar functionality to extract the exponent from a float64 number. It is comparable to @stdlib/number-float64-base-exponent in terms of functionality but may differ in implementation details and additional features.
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
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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:
[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.
Copyright © 2016-2024. The Stdlib Authors.
FAQs
Return an integer corresponding to the unbiased exponent of a double-precision floating-point number.
We found that @stdlib/number-float64-base-exponent demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 4 open source maintainers collaborating on the project.
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