# @stdlib/blas-ext-base-dnannsumkbn

Calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using an improved Kahan–Babuška algorithm.

## Usage no npm install needed!

``````<script type="module">
import stdlibBlasExtBaseDnannsumkbn from 'https://cdn.skypack.dev/@stdlib/blas-ext-base-dnannsumkbn';
</script>``````

# dnannsumkbn

Calculate the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.

## Installation

``````npm install @stdlib/blas-ext-base-dnannsumkbn
``````

## Usage

``````var dnannsumkbn = require( '@stdlib/blas-ext-base-dnannsumkbn' );
``````

#### dnannsumkbn( N, x, strideX, out, strideOut )

Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.

``````var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var out = new Float64Array( 2 );

var v = dnannsumkbn( x.length, x, 1, out, 1 );
// returns <Float64Array>[ 1.0, 3 ]
``````

The function has the following parameters:

• N: number of indexed elements.
• x: input `Float64Array`.
• strideX: index increment for `x`.
• out: output `Float64Array` whose first element is the sum and whose second element is the number of non-NaN elements.
• strideOut: index increment for `out`.

The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the sum of every other element in `x`,

``````var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 1.0, 2.0, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
var out = new Float64Array( 2 );
var N = floor( x.length / 2 );

var v = dnannsumkbn( N, x, 2, out, 1 );
// returns <Float64Array>[ 5.0, 2 ]
``````

Note that indexing is relative to the first index. To introduce an offset, use `typed array` views.

``````var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );

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 out0 = new Float64Array( 4 );
var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element

var N = floor( x0.length / 2 );

var v = dnannsumkbn( N, x1, 2, out1, 1 );
// returns <Float64Array>[ 5.0, 4 ]
``````

#### dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )

Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics.

``````var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var out = new Float64Array( 2 );

var v = dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 );
// returns <Float64Array>[ 1.0, 3 ]
``````

The function has the following additional parameters:

• offsetX: starting index for `x`.
• offsetOut: starting index for `out`.

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 every other value in `x` starting from the second value

``````var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var out = new Float64Array( 4 );
var N = floor( x.length / 2 );

var v = dnannsumkbn.ndarray( N, x, 2, 1, out, 2, 1 );
// returns <Float64Array>[ 0.0, 5.0, 0.0, 4 ]
``````

## Notes

• If `N <= 0`, both functions return a sum equal to `0.0`.

## Examples

``````var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var dnannsumkbn = require( '@stdlib/blas-ext-base-dnannsumkbn' );

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 out = new Float64Array( 2 );
dnannsumkbn( x.length, x, 1, out, 1 );
console.log( out );
``````

## References

• Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." Zeitschrift Für Angewandte Mathematik Und Mechanik 54 (1): 39–51. doi:10.1002/zamm.19740540106.

## 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.