time-to-botec

Benchmark sampling in different programming languages
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nanmeanpn.js (2509B)

      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 // MAIN //
     22 
     23 /**
     24 * Computes the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm.
     25 *
     26 * ## Method
     27 *
     28 * -   This implementation uses a two-pass approach, as suggested by Neely (1966).
     29 *
     30 * ## References
     31 *
     32 * -   Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958).
     33 * -   Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036).
     34 *
     35 * @param {PositiveInteger} N - number of indexed elements
     36 * @param {NumericArray} x - input array
     37 * @param {integer} stride - stride length
     38 * @returns {number} arithmetic mean
     39 *
     40 * @example
     41 * var x = [ 1.0, -2.0, NaN, 2.0 ];
     42 * var N = x.length;
     43 *
     44 * var v = nanmeanpn( N, x, 1 );
     45 * // returns ~0.3333
     46 */
     47 function nanmeanpn( N, x, stride ) {
     48 	var ix;
     49 	var v;
     50 	var s;
     51 	var t;
     52 	var n;
     53 	var i;
     54 	var o;
     55 
     56 	if ( N <= 0 ) {
     57 		return NaN;
     58 	}
     59 	if ( N === 1 || stride === 0 ) {
     60 		return x[ 0 ];
     61 	}
     62 	if ( stride < 0 ) {
     63 		ix = (1-N) * stride;
     64 	} else {
     65 		ix = 0;
     66 	}
     67 	o = ix;
     68 
     69 	// Compute an estimate for the mean...
     70 	s = 0.0;
     71 	n = 0;
     72 	for ( i = 0; i < N; i++ ) {
     73 		v = x[ ix ];
     74 		if ( v === v ) {
     75 			n += 1;
     76 			s += v;
     77 		}
     78 		ix += stride;
     79 	}
     80 	if ( n === 0 ) {
     81 		return NaN;
     82 	}
     83 	s /= n;
     84 
     85 	// Compute an error term...
     86 	t = 0.0;
     87 	ix = o;
     88 	for ( i = 0; i < N; i++ ) {
     89 		v = x[ ix ];
     90 		if ( v === v ) {
     91 			t += v - s;
     92 		}
     93 		ix += stride;
     94 	}
     95 	return s + (t/n);
     96 }
     97 
     98 
     99 // EXPORTS //
    100 
    101 module.exports = nanmeanpn;