time-to-botec

Benchmark sampling in different programming languages
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entropy.js (1712B)


      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 ln = require( '@stdlib/math/base/special/ln' );
     25 var GAMMA = require( '@stdlib/constants/float64/eulergamma' );
     26 
     27 
     28 // MAIN //
     29 
     30 /**
     31 * Returns the differential entropy for a Fréchet distribution with shape `alpha`, scale `s`, and location `m`.
     32 *
     33 * @param {PositiveNumber} alpha - shape parameter
     34 * @param {PositiveNumber} s - scale parameter
     35 * @param {number} m - location parameter
     36 * @returns {PositiveNumber} entropy
     37 *
     38 * @example
     39 * var y = entropy( 1.0, 1.0, 0.0 );
     40 * // returns ~2.154
     41 *
     42 * @example
     43 * var y = entropy( 5.0, 2.0, 0.0 );
     44 * // returns ~0.776
     45 *
     46 * @example
     47 * var y = entropy( NaN, 1.0, 0.0 );
     48 * // returns NaN
     49 *
     50 * @example
     51 * var y = entropy( 1.0, NaN, 0.0 );
     52 * // returns NaN
     53 *
     54 * @example
     55 * var y = entropy( 1.0, 1.0, NaN );
     56 * // returns NaN
     57 */
     58 function entropy( alpha, s, m ) {
     59 	if (
     60 		isnan( alpha ) ||
     61 		isnan( s ) ||
     62 		isnan( m ) ||
     63 		alpha <= 0.0 ||
     64 		s <= 0.0
     65 	) {
     66 		return NaN;
     67 	}
     68 	return 1.0 + ( GAMMA / alpha ) + GAMMA + ln( s / alpha );
     69 }
     70 
     71 
     72 // EXPORTS //
     73 
     74 module.exports = entropy;