time-to-botec

Benchmark sampling in different programming languages
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main.js (3261B)


      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 isPositiveInteger = require( '@stdlib/assert/is-positive-integer' ).isPrimitive;
     24 var isnan = require( '@stdlib/math/base/assert/is-nan' );
     25 var Float64Array = require( '@stdlib/array/float64' );
     26 
     27 
     28 // MAIN //
     29 
     30 /**
     31 * Returns an accumulator function which incrementally computes a moving arithmetic mean.
     32 *
     33 * @param {PositiveInteger} W - window size
     34 * @throws {TypeError} must provide a positive integer
     35 * @returns {Function} accumulator function
     36 *
     37 * @example
     38 * var accumulator = incrmmean( 3 );
     39 *
     40 * var mu = accumulator();
     41 * // returns null
     42 *
     43 * mu = accumulator( 2.0 );
     44 * // returns 2.0
     45 *
     46 * mu = accumulator( -5.0 );
     47 * // returns -1.5
     48 *
     49 * mu = accumulator( 3.0 );
     50 * // returns 0.0
     51 *
     52 * mu = accumulator( 5.0 );
     53 * // returns 1.0
     54 *
     55 * mu = accumulator();
     56 * // returns 1.0
     57 */
     58 function incrmmean( W ) {
     59 	var delta;
     60 	var buf;
     61 	var mu;
     62 	var N;
     63 	var i;
     64 	if ( !isPositiveInteger( W ) ) {
     65 		throw new TypeError( 'invalid argument. Must provide a positive integer. Value: `' + W + '`.' );
     66 	}
     67 	buf = new Float64Array( W );
     68 	mu = 0.0;
     69 	i = -1;
     70 	N = 0;
     71 
     72 	return accumulator;
     73 
     74 	/**
     75 	* If provided a value, the accumulator function returns an updated mean. If not provided a value, the accumulator function returns the current mean.
     76 	*
     77 	* @private
     78 	* @param {number} [x] - input value
     79 	* @returns {(number|null)} mean or null
     80 	*/
     81 	function accumulator( x ) {
     82 		var k;
     83 		if ( arguments.length === 0 ) {
     84 			if ( N === 0 ) {
     85 				return null;
     86 			}
     87 			return mu;
     88 		}
     89 		// Update the index for managing the circular buffer:
     90 		i = (i+1) % W;
     91 
     92 		// Case: incoming value is NaN, the sliding mean is automatically NaN...
     93 		if ( isnan( x ) ) {
     94 			N = W; // explicitly set to avoid `N < W` branch
     95 			mu = NaN;
     96 		}
     97 		// Case: initial window...
     98 		else if ( N < W ) {
     99 			N += 1;
    100 			delta = x - mu;
    101 			mu += delta / N;
    102 		}
    103 		// Case: outgoing value is NaN, and, thus, we need to compute the sample mean...
    104 		else if ( isnan( buf[ i ] ) ) {
    105 			N = 1;
    106 			mu = x;
    107 			for ( k = 0; k < W; k++ ) {
    108 				if ( k !== i ) {
    109 					if ( isnan( buf[ k ] ) ) {
    110 						N = W; // explicitly set to avoid `N < W` branch
    111 						mu = NaN;
    112 						break; // mean is automatically NaN, so no need to continue
    113 					}
    114 					N += 1;
    115 					delta = buf[ k ] - mu;
    116 					mu += delta / N;
    117 				}
    118 			}
    119 		}
    120 		// Case: neither the current mean nor the incoming value are NaN, so we need to update the sample mean...
    121 		else if ( isnan( mu ) === false ) {
    122 			delta = x - buf[ i ];
    123 			mu += delta / W;
    124 		}
    125 		// Case: the current mean is NaN, so nothing to do until the buffer no longer contains NaN values...
    126 
    127 		buf[ i ] = x;
    128 		return mu;
    129 	}
    130 }
    131 
    132 
    133 // EXPORTS //
    134 
    135 module.exports = incrmmean;