time-to-botec

Benchmark sampling in different programming languages
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asinh.js (1568B)


      1 /**
      2 * @license Apache-2.0
      3 *
      4 * Copyright (c) 2018 The Stdlib Authors.
      5 *
      6 * Licensed under the Apache License, Version 2.0 (the "License");
      7 * you may not use this file except in compliance with the License.
      8 * You may obtain a copy of the License at
      9 *
     10 *    http://www.apache.org/licenses/LICENSE-2.0
     11 *
     12 * Unless required by applicable law or agreed to in writing, software
     13 * distributed under the License is distributed on an "AS IS" BASIS,
     14 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     15 * See the License for the specific language governing permissions and
     16 * limitations under the License.
     17 */
     18 
     19 'use strict';
     20 
     21 // MODULES //
     22 
     23 var isinfinite = require( './../../../../../base/assert/is-infinite' );
     24 var isnan = require( './../../../../../base/assert/is-nan' );
     25 var ln = require( './../../../../../base/special/ln' );
     26 var sqrt = require( './../../../../../base/special/sqrt' );
     27 
     28 
     29 // MAIN //
     30 
     31 /**
     32 * Computes the hyperbolic arcsine of a number.
     33 *
     34 * @param {number} x - input value
     35 * @returns {number} hyperbolic arcsine (in radians)
     36 *
     37 * @example
     38 * var v = asinh( 0.0 );
     39 * // returns 0.0
     40 *
     41 * @example
     42 * var v = asinh( 2.0 );
     43 * // returns ~1.444
     44 *
     45 * @example
     46 * var v = asinh( -2.0 );
     47 * // returns ~-1.444
     48 *
     49 * @example
     50 * var v = asinh( NaN );
     51 * // returns NaN
     52 */
     53 function asinh( x ) {
     54 	if (
     55 		x === 0.0 || // +-0.0
     56 		isnan( x ) ||
     57 		isinfinite( x )
     58 	) {
     59 		return x;
     60 	}
     61 	if ( x > 0 ) {
     62 		return ln( x + sqrt( (x*x) + 1 ) );
     63 	}
     64 	// Better precision for large negative `x`:
     65 	return -ln( -x + sqrt( (x*x) + 1 ) );
     66 }
     67 
     68 
     69 // EXPORTS //
     70 
     71 module.exports = asinh;