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[467,467,100,36,36,100,4,4,100,467,467,100,"a70e23d3b79c108d39c8b19392172f4776c9b043","2024-03-26 09:18:42 -0400"]
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* @license Apache-2.0
*
* Copyright (c) 2020 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
&nbsp;
'use strict';
&nbsp;
// MODULES //
&nbsp;
var abs = require( '@stdlib/math/base/special/abs' );
var sum = require( './ndarray.js' );
&nbsp;
&nbsp;
// MAIN //
&nbsp;
/**
* Computes the sum of absolute values (L1 norm) of double-precision floating-point strided array elements using pairwise summation.
*
* ## Method
*
* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`.
*
* ## References
*
* - 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).
*
* @param {PositiveInteger} N - number of indexed elements
* @param {Float64Array} x - input array
* @param {integer} stride - stride length
* @returns {number} sum
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
* var N = x.length;
*
* var v = dasumpw( N, x, 1 );
* // returns 5.0
*/
function dasumpw( N, x, stride ) {
var ix;
var s;
var i;
&nbsp;
if ( N &lt;= 0 ) {
return 0.0;
}
if ( N === 1 || stride === 0 ) {
return abs( x[ 0 ] );
}
if ( stride &lt; 0 ) {
ix = (1-N) * stride;
} else {
ix = 0;
}
if ( N &lt; 8 ) {
// Use simple summation...
s = 0.0;
for ( i = 0; i &lt; N; i++ ) {
s += abs( x[ ix ] );
ix += stride;
}
return s;
}
return sum( N, x, stride, ix );
}
&nbsp;
&nbsp;
// EXPORTS //
&nbsp;
module.exports = dasumpw;
&nbsp;</pre></td></tr></table></pre>

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