time-to-botec

Benchmark sampling in different programming languages
Log | Files | Refs | README

dasumpw.js (2073B)

      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 abs = require( '@stdlib/math/base/special/abs' );
     24 var sum = require( './ndarray.js' );
     25 
     26 
     27 // MAIN //
     28 
     29 /**
     30 * Computes the sum of absolute values (L1 norm) of double-precision floating-point strided array elements using pairwise summation.
     31 *
     32 * ## Method
     33 *
     34 * -   This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`.
     35 *
     36 * ## References
     37 *
     38 * -   Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050).
     39 *
     40 * @param {PositiveInteger} N - number of indexed elements
     41 * @param {Float64Array} x - input array
     42 * @param {integer} stride - stride length
     43 * @returns {number} sum
     44 *
     45 * @example
     46 * var Float64Array = require( '@stdlib/array/float64' );
     47 *
     48 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
     49 * var N = x.length;
     50 *
     51 * var v = dasumpw( N, x, 1 );
     52 * // returns 5.0
     53 */
     54 function dasumpw( N, x, stride ) {
     55 	var ix;
     56 	var s;
     57 	var i;
     58 
     59 	if ( N <= 0 ) {
     60 		return 0.0;
     61 	}
     62 	if ( N === 1 || stride === 0 ) {
     63 		return abs( x[ 0 ] );
     64 	}
     65 	if ( stride < 0 ) {
     66 		ix = (1-N) * stride;
     67 	} else {
     68 		ix = 0;
     69 	}
     70 	if ( N < 8 ) {
     71 		// Use simple summation...
     72 		s = 0.0;
     73 		for ( i = 0; i < N; i++ ) {
     74 			s += abs( x[ ix ] );
     75 			ix += stride;
     76 		}
     77 		return s;
     78 	}
     79 	return sum( N, x, stride, ix );
     80 }
     81 
     82 
     83 // EXPORTS //
     84 
     85 module.exports = dasumpw;