time-to-botec

Benchmark sampling in different programming languages
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dvarmtk.js (1684B)


      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 variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm.
     25 *
     26 * @param {PositiveInteger} N - number of indexed elements
     27 * @param {number} mean - mean
     28 * @param {number} correction - degrees of freedom adjustment
     29 * @param {Float64Array} x - input array
     30 * @param {integer} stride - stride length
     31 * @returns {number} variance
     32 *
     33 * @example
     34 * var Float64Array = require( '@stdlib/array/float64' );
     35 *
     36 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
     37 *
     38 * var v = dvarmtk( x.length, 1.0/3.0, 1, x, 1 );
     39 * // returns ~4.3333
     40 */
     41 function dvarmtk( N, mean, correction, x, stride ) {
     42 	var ix;
     43 	var M2;
     44 	var d;
     45 	var n;
     46 	var i;
     47 
     48 	n = N - correction;
     49 	if ( N <= 0 || n <= 0.0 ) {
     50 		return NaN;
     51 	}
     52 	if ( N === 1 || stride === 0 ) {
     53 		return 0.0;
     54 	}
     55 	if ( stride < 0 ) {
     56 		ix = (1-N) * stride;
     57 	} else {
     58 		ix = 0;
     59 	}
     60 	M2 = 0.0;
     61 	for ( i = 0; i < N; i++ ) {
     62 		d = x[ ix ] - mean;
     63 		M2 += d * d;
     64 		ix += stride;
     65 	}
     66 	return M2 / n;
     67 }
     68 
     69 
     70 // EXPORTS //
     71 
     72 module.exports = dvarmtk;