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snansumors

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

Installation

npm install @stdlib/blas-ext-base-snansumors

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

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

snansumors( N, x, stride )

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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;

var v = snansumors( N, x, 1 );
// returns 1.0

The function has the following parameters:

• N: number of indexed elements.
• x: input Float32Array.
• stride: index increment for the strided array.

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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, 2.0, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
var N = 4;

var v = snansumors( N, x, 2 );
// returns 5.0

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

var Float32Array = require( '@stdlib/array-float32' );

var x0 = new Float32Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var v = snansumors( 4, x1, 2 );
// returns 5.0

snansumors.ndarray( N, x, stride, offset )

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

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;

var v = snansumors.ndarray( N, x, 1, 0 );
// returns 1.0

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 every other value in x starting from the second value

var Float32Array = require( '@stdlib/array-float32' );

var x = new Float32Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );

var v = snansumors.ndarray( 4, x, 2, 1 );
// returns 5.0

Notes

• If N <= 0, both functions return 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.

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var snansumors = require( '@stdlib/blas-ext-base-snansumors' );

function rand() {
    if ( bernoulli( 0.7 ) > 0 ) {
        return discreteUniform( 0, 100 );
    }
    return NaN;
}

var x = filledarrayBy( 10, 'float32', rand );
console.log( x );

var v = snansumors( x.length, x, 1 );
console.log( v );

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See Also

• @stdlib/blas-ext/base/dnansumors: calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using ordinary recursive summation.
• @stdlib/blas-ext/base/gnansumors: calculate the sum of strided array elements, ignoring NaN values and using ordinary recursive summation.
• @stdlib/blas-ext/base/snansum: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values.
• @stdlib/blas-ext/base/snansumkbn2: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.
• @stdlib/blas-ext/base/snansumpw: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using pairwise summation.
• @stdlib/blas-ext/base/ssumors: calculate the sum of single-precision floating-point strided array elements using ordinary recursive summation.

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.