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dnanasumors
Calculate the sum of absolute values (L1 norm) of doubleprecision floatingpoint strided array elements, ignoring
NaN
values and using ordinary recursive summation.
The L1 norm is defined as
Installation
npm install @stdlib/blasextbasednanasumors
Usage
var dnanasumors = require( '@stdlib/blasextbasednanasumors' );
dnanasumors( N, x, stride )
Computes the sum of absolute values (L1 norm) of doubleprecision floatingpoint strided array elements, ignoring NaN
values and using ordinary recursive summation.
var Float64Array = require( '@stdlib/arrayfloat64' );
var x = new Float64Array( [ 1.0, 2.0, NaN, 2.0 ] );
var N = x.length;
var v = dnanasumors( N, x, 1 );
// returns 5.0
The function has the following parameters:
 N: number of indexed elements.

x: input
Float64Array
. 
stride: index increment for
x
.
The N
and stride
parameters determine which elements in x
are accessed at runtime. For example, to compute the sum of absolute values (L1 norm) every other element in x
,
var Float64Array = require( '@stdlib/arrayfloat64' );
var floor = require( '@stdlib/mathbasespecialfloor' );
var x = new Float64Array( [ 1.0, 2.0, NaN, 7.0, NaN, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );
var v = dnanasumors( N, x, 2 );
// returns 5.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/arrayfloat64' );
var floor = require( '@stdlib/mathbasespecialfloor' );
var x0 = new Float64Array( [ 2.0, 1.0, NaN, 2.0, 2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = dnanasumors( N, x1, 2 );
// returns 9.0
dnanasumors.ndarray( N, x, stride, offset )
Computes the sum of absolute values (L1 norm) of doubleprecision floatingpoint strided array elements, ignoring NaN
values and using ordinary recursive summation and alternative indexing semantics.
var Float64Array = require( '@stdlib/arrayfloat64' );
var x = new Float64Array( [ 1.0, 2.0, NaN, 2.0 ] );
var N = x.length;
var v = dnanasumors.ndarray( N, x, 1, 0 );
// returns 5.0
The function has the following additional parameters:

offset: starting index for
x
.
While typed array
views mandate a view offset based on the underlying buffer
, the offset
parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values (L1 norm) every other value in x
starting from the second value
var Float64Array = require( '@stdlib/arrayfloat64' );
var floor = require( '@stdlib/mathbasespecialfloor' );
var x = new Float64Array( [ 2.0, 1.0, NaN, 2.0, 2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );
var v = dnanasumors.ndarray( N, x, 2, 1 );
// returns 9.0
Notes
 If
N <= 0
, both functions return0.0
.  Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation is acceptable; in all other cases, exercise due caution.
Examples
var randu = require( '@stdlib/randombaserandu' );
var round = require( '@stdlib/mathbasespecialround' );
var Float64Array = require( '@stdlib/arrayfloat64' );
var dnanasumors = require( '@stdlib/blasextbasednanasumors' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
if ( randu() < 0.2 ) {
x[ i ] = NaN;
} else {
x[ i ] = round( randu()*100.0 );
}
}
console.log( x );
var v = dnanasumors( x.length, x, 1 );
console.log( v );
See Also

@stdlib/blasext/base/dnanasum
: calculate the sum of absolute values (L1 norm) of doubleprecision floatingpoint strided array elements, ignoring NaN values.
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 20162024. The Stdlib Authors.