time-to-botec

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


      1 /**
      2 * @license Apache-2.0
      3 *
      4 * Copyright (c) 2020 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 dsumkbn = require( '@stdlib/blas/ext/base/dsumkbn' );
     24 
     25 
     26 // MAIN //
     27 
     28 /**
     29 * Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.
     30 *
     31 * ## Method
     32 *
     33 * -   This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974).
     34 *
     35 * ## References
     36 *
     37 * -   Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106).
     38 *
     39 * @param {PositiveInteger} N - number of indexed elements
     40 * @param {Float64Array} x - input array
     41 * @param {integer} stride - stride length
     42 * @returns {number} arithmetic mean
     43 *
     44 * @example
     45 * var Float64Array = require( '@stdlib/array/float64' );
     46 *
     47 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
     48 * var N = x.length;
     49 *
     50 * var v = dmeankbn( N, x, 1 );
     51 * // returns ~0.3333
     52 */
     53 function dmeankbn( N, x, stride ) {
     54 	if ( N <= 0 ) {
     55 		return NaN;
     56 	}
     57 	if ( N === 1 || stride === 0 ) {
     58 		return x[ 0 ];
     59 	}
     60 	return dsumkbn( N, x, stride ) / N;
     61 }
     62 
     63 
     64 // EXPORTS //
     65 
     66 module.exports = dmeankbn;