time-to-botec

Benchmark sampling in different programming languages
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factory.js (1919B)


      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 constantFunction = require( '@stdlib/utils/constant-function' );
     24 var isnan = require( '@stdlib/math/base/assert/is-nan' );
     25 var exp = require( '@stdlib/math/base/special/exp' );
     26 var NINF = require( '@stdlib/constants/float64/ninf' );
     27 
     28 
     29 // MAIN //
     30 
     31 /**
     32 * Returns a function for evaluating the probability density function (PDF) for a Gumbel distribution with location parameter `mu` and scale parameter `beta`.
     33 *
     34 * @param {number} mu - location parameter
     35 * @param {PositiveNumber} beta - scale parameter
     36 * @returns {Function} PDF
     37 *
     38 * @example
     39 * var pdf = factory( 4.0, 2.0 );
     40 *
     41 * var y = pdf( 10.0 );
     42 * // returns ~0.0237
     43 *
     44 * y = pdf( 3.0 );
     45 * // returns ~0.159
     46 */
     47 function factory( mu, beta ) {
     48 	if ( isnan( mu ) || isnan( beta ) || beta <= 0.0 ) {
     49 		return constantFunction( NaN );
     50 	}
     51 	return pdf;
     52 
     53 	/**
     54 	* Evaluates the probability density function (PDF) for a Gumbel distribution.
     55 	*
     56 	* @private
     57 	* @param {number} x - input value
     58 	* @returns {number} evaluated PDF
     59 	*
     60 	* @example
     61 	* var y = pdf( 2.3 );
     62 	* // returns <number>
     63 	*/
     64 	function pdf( x ) {
     65 		var z;
     66 		if ( isnan( x ) ) {
     67 			return NaN;
     68 		}
     69 		if ( x === NINF ) {
     70 			return 0.0;
     71 		}
     72 		z = ( x - mu ) / beta;
     73 		return ( 1.0 / beta ) * exp( -z - exp( -z ) );
     74 	}
     75 }
     76 
     77 
     78 // EXPORTS //
     79 
     80 module.exports = factory;