time-to-botec

Benchmark sampling in different programming languages
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factory.js (1820B)


      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 
     27 
     28 // MAIN //
     29 
     30 /**
     31 * Returns a function for evaluating the cumulative distribution function (CDF) for a Gumbel distribution with location parameter `mu` and scale parameter `beta`.
     32 *
     33 * @param {number} mu - location parameter
     34 * @param {PositiveNumber} beta - scale parameter
     35 * @returns {Function} CDF
     36 *
     37 * @example
     38 * var cdf = factory( 0.0, 3.0 );
     39 *
     40 * var y = cdf( 10.0 );
     41 * // returns ~0.965
     42 *
     43 * y = cdf( -2.0 );
     44 * // returns ~0.143
     45 */
     46 function factory( mu, beta ) {
     47 	if (
     48 		isnan( mu ) ||
     49 		isnan( beta ) ||
     50 		beta <= 0
     51 	) {
     52 		return constantFunction( NaN );
     53 	}
     54 	return cdf;
     55 
     56 	/**
     57 	* Evaluates the cumulative distribution function (CDF) for a Gumbel distribution.
     58 	*
     59 	* @private
     60 	* @param {number} x - input value
     61 	* @returns {Probability} evaluated CDF
     62 	*
     63 	* @example
     64 	* var y = cdf( -2.0 );
     65 	* // returns <number>
     66 	*/
     67 	function cdf( x ) {
     68 		var z;
     69 		if ( isnan( x ) ) {
     70 			return NaN;
     71 		}
     72 		z = ( x - mu ) / beta;
     73 		return exp( -exp( -z ) );
     74 	}
     75 }
     76 
     77 
     78 // EXPORTS //
     79 
     80 module.exports = factory;