time-to-botec

Benchmark sampling in different programming languages
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pdf.js (2223B)

      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 isnan = require( '@stdlib/math/base/assert/is-nan' );
     24 var sqrt = require( '@stdlib/math/base/special/sqrt' );
     25 var exp = require( '@stdlib/math/base/special/exp' );
     26 var pow = require( '@stdlib/math/base/special/pow' );
     27 var ln = require( '@stdlib/math/base/special/ln' );
     28 var PI = require( '@stdlib/constants/float64/pi' );
     29 
     30 
     31 // MAIN //
     32 
     33 /**
     34 * Evaluates the probability density function (PDF) for a lognormal distribution with location parameter `mu` and scale parameter `sigma` at a value `x`.
     35 *
     36 * @param {number} x - input value
     37 * @param {number} mu - location parameter
     38 * @param {PositiveNumber} sigma - scale parameter
     39 * @returns {number} evaluated PDF
     40 *
     41 * @example
     42 * var y = pdf( 2.0, 0.0, 1.0 );
     43 * // returns ~0.157
     44 *
     45 * @example
     46 * var y = pdf( 1.0, 0.0, 1.0 );
     47 * // returns ~0.399
     48 *
     49 * @example
     50 * var y = pdf( 1.0, 3.0, 1.0 );
     51 * // returns ~0.004
     52 *
     53 * @example
     54 * var y = pdf( -1.0, 4.0, 2.0 );
     55 * // returns 0.0
     56 *
     57 * @example
     58 * var y = pdf( NaN, 0.0, 1.0 );
     59 * // returns NaN
     60 *
     61 * @example
     62 * var y = pdf( 0.0, NaN, 1.0 );
     63 * // returns NaN
     64 *
     65 * @example
     66 * var y = pdf( 0.0, 0.0, NaN );
     67 * // returns NaN
     68 *
     69 * @example
     70 * // Negative scale parameter:
     71 * var y = pdf( 2.0, 0.0, -1.0 );
     72 * // returns NaN
     73 */
     74 function pdf( x, mu, sigma ) {
     75 	var s2;
     76 	var A;
     77 	var B;
     78 	if (
     79 		isnan( x ) ||
     80 		isnan( mu ) ||
     81 		isnan( sigma ) ||
     82 		sigma <= 0.0
     83 	) {
     84 		return NaN;
     85 	}
     86 	if ( x <= 0.0 ) {
     87 		return 0.0;
     88 	}
     89 	s2 = pow( sigma, 2.0 );
     90 	A = 1.0 / ( sqrt( 2.0 * s2 * PI ) );
     91 	B = -1.0 / ( 2.0 * s2 );
     92 	return (1.0/x) * A * exp( B * pow( ln(x) - mu, 2.0 ) );
     93 }
     94 
     95 
     96 // EXPORTS //
     97 
     98 module.exports = pdf;