snansumkbn2.js (2872B)
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 var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); 25 var abs = require( '@stdlib/math/base/special/abs' ); 26 27 28 // MAIN // 29 30 /** 31 * Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm. 32 * 33 * ## Method 34 * 35 * - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). 36 * 37 * ## References 38 * 39 * - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). 40 * 41 * @param {PositiveInteger} N - number of indexed elements 42 * @param {Float32Array} x - input array 43 * @param {integer} stride - stride length 44 * @returns {number} sum 45 * 46 * @example 47 * var Float32Array = require( '@stdlib/array/float32' ); 48 * 49 * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); 50 * var N = x.length; 51 * 52 * var v = snansumkbn2( N, x, 1 ); 53 * // returns 1.0 54 */ 55 function snansumkbn2( N, x, stride ) { 56 var sum; 57 var ccs; 58 var ix; 59 var cs; 60 var cc; 61 var v; 62 var t; 63 var c; 64 var i; 65 66 if ( N <= 0 ) { 67 return 0.0; 68 } 69 if ( N === 1 || stride === 0 ) { 70 if ( isnanf( x[ 0 ] ) ) { 71 return 0.0; 72 } 73 return x[ 0 ]; 74 } 75 if ( stride < 0 ) { 76 ix = (1-N) * stride; 77 } else { 78 ix = 0; 79 } 80 sum = 0.0; 81 ccs = 0.0; // second order correction term for lost low order bits 82 cs = 0.0; // first order correction term for lost low order bits 83 for ( i = 0; i < N; i++ ) { 84 v = x[ ix ]; 85 if ( isnanf( v ) === false ) { 86 t = float64ToFloat32( sum + v ); 87 if ( abs( sum ) >= abs( v ) ) { 88 c = float64ToFloat32( float64ToFloat32( sum-t ) + v ); 89 } else { 90 c = float64ToFloat32( float64ToFloat32( v-t ) + sum ); 91 } 92 sum = t; 93 t = float64ToFloat32( cs + c ); 94 if ( abs( cs ) >= abs( c ) ) { 95 cc = float64ToFloat32( float64ToFloat32(cs-t) + c ); 96 } else { 97 cc = float64ToFloat32( float64ToFloat32(c-t) + cs ); 98 } 99 cs = t; 100 ccs = float64ToFloat32( ccs + cc ); 101 } 102 ix += stride; 103 } 104 return float64ToFloat32( sum + float64ToFloat32( cs + ccs ) ); 105 } 106 107 108 // EXPORTS // 109 110 module.exports = snansumkbn2;