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# dnannsumors

> Calculate the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var dnannsumors = require( '@stdlib/blas/ext/base/dnannsumors' );
```

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

Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.

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

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

var v = dnannsumors( 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`][@stdlib/array/float64].
-   **strideX**: index increment for `x`.
-   **out**: output [`Float64Array`][@stdlib/array/float64] 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`,

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

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

var v = dnannsumors( 4, 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`][mdn-typed-array] views.

<!-- eslint-disable stdlib/capitalized-comments -->

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

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

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

Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation and alternative indexing semantics.

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

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

var v = dnannsumors.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`][mdn-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

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

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

</section>

<!-- /.usage -->

<section class="notes">

## Notes

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

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
var bernoulli = require( '@stdlib/random/base/bernoulli' );
var Float64Array = require( '@stdlib/array/float64' );

var filledarrayBy = require( '@stdlib/array/filled-by' );
var dnannsumors = require( '@stdlib/blas/ext/base/dnannsumors' );

function rand() {
    if ( bernoulli( 0.8 ) > 0 ) {
        return discreteUniform( 0, 100 );
    }
    return NaN;
}

var x = filledarrayBy( 10, 'float64', rand );
console.log( x );

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

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/blas/ext/base/dnannsum`][@stdlib/blas/ext/base/dnannsum]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements, ignoring NaN values.</span>
-   <span class="package-name">[`@stdlib/blas/ext/base/dnannsumkbn`][@stdlib/blas/ext/base/dnannsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using an improved Kahan–Babuška algorithm.</span>
-   <span class="package-name">[`@stdlib/blas/ext/base/dnannsumkbn2`][@stdlib/blas/ext/base/dnannsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.</span>
-   <span class="package-name">[`@stdlib/blas/ext/base/dnannsumpw`][@stdlib/blas/ext/base/dnannsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using pairwise summation.</span>
-   <span class="package-name">[`@stdlib/blas/ext/base/dsumors`][@stdlib/blas/ext/base/dsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="links">

[@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64

[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray

<!-- <related-links> -->

[@stdlib/blas/ext/base/dnannsum]: https://github.com/stdlib-js/blas/tree/main/ext/base/dnannsum

[@stdlib/blas/ext/base/dnannsumkbn]: https://github.com/stdlib-js/blas/tree/main/ext/base/dnannsumkbn

[@stdlib/blas/ext/base/dnannsumkbn2]: https://github.com/stdlib-js/blas/tree/main/ext/base/dnannsumkbn2

[@stdlib/blas/ext/base/dnannsumpw]: https://github.com/stdlib-js/blas/tree/main/ext/base/dnannsumpw

[@stdlib/blas/ext/base/dsumors]: https://github.com/stdlib-js/blas/tree/main/ext/base/dsumors

<!-- </related-links> -->

</section>

<!-- /.links -->
