ndarray.js (2833B)
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 float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); 24 25 26 // MAIN // 27 28 /** 29 * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm. 30 * 31 * ## Method 32 * 33 * - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows 34 * 35 * ```tex 36 * \begin{align*} 37 * \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ 38 * &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ 39 * &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ 40 * &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) 41 * \end{align*} 42 * ``` 43 * 44 * ## References 45 * 46 * - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). 47 * - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). 48 * 49 * @param {PositiveInteger} N - number of indexed elements 50 * @param {Float32Array} x - input array 51 * @param {integer} stride - stride length 52 * @param {NonNegativeInteger} offset - starting index 53 * @returns {number} arithmetic mean 54 * 55 * @example 56 * var Float32Array = require( '@stdlib/array/float32' ); 57 * var floor = require( '@stdlib/math/base/special/floor' ); 58 * 59 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); 60 * var N = floor( x.length / 2 ); 61 * 62 * var v = snanmeanwd( N, x, 2, 1 ); 63 * // returns 1.25 64 */ 65 function snanmeanwd( N, x, stride, offset ) { 66 var mu; 67 var ix; 68 var v; 69 var n; 70 var i; 71 72 if ( N <= 0 ) { 73 return NaN; 74 } 75 if ( N === 1 || stride === 0 ) { 76 return x[ offset ]; 77 } 78 ix = offset; 79 mu = 0.0; 80 n = 0; 81 for ( i = 0; i < N; i++ ) { 82 v = x[ ix ]; 83 if ( v === v ) { 84 n += 1; 85 mu = float64ToFloat32( mu + float64ToFloat32( float64ToFloat32( v-mu ) / n ) ); // eslint-disable-line max-len 86 } 87 ix += stride; 88 } 89 if ( n === 0 ) { 90 return NaN; 91 } 92 return mu; 93 } 94 95 96 // EXPORTS // 97 98 module.exports = snanmeanwd;