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dapxsumkbn2

Add a scalar constant to each double-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.

Usage

import dapxsumkbn2 from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-dapxsumkbn2@deno/mod.js';

dapxsumkbn2( N, alpha, x, strideX )

Adds a scalar constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';

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

var v = dapxsumkbn2( x.length, 5.0, x, 1 );
// returns 16.0

The function has the following parameters:

• N: number of indexed elements.
• alpha: scalar constant.
• x: input Float64Array.
• strideX: stride length for x.

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

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';

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

var v = dapxsumkbn2( 4, 5.0, x, 2 );
// returns 25.0

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

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';

var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -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 v = dapxsumkbn2( 4, 5.0, x1, 2 );
// returns 25.0

dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )

Adds a scalar constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';

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

var v = dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 );
// returns 16.0

The function has the following additional parameters:

• offsetX: 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 access every other element starting from the second element:

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';

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

var v = dapxsumkbn2.ndarray( 4, 5.0, x, 2, 1 );
// returns 25.0

Notes

• If N <= 0, both functions return 0.0.

Examples

import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@deno/mod.js';
import dapxsumkbn2 from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-dapxsumkbn2@deno/mod.js';

var x = discreteUniform( 10, -100, 100, {
    'dtype': 'float64'
});
console.log( x );

var v = dapxsumkbn2( x.length, 5.0, x, 1 );
console.log( v );

References

• Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." Computing 76 (3): 279–93. doi:10.1007/s00607-005-0139-x.

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See Also

• @stdlib/blas-ext/base/dapxsum: add a scalar constant to each double-precision floating-point strided array element and compute the sum.
• @stdlib/blas-ext/base/dsumkbn2: calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.
• @stdlib/blas-ext/base/gapxsumkbn2: add a scalar constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
• @stdlib/blas-ext/base/sapxsumkbn2: add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.

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Notice

This package is part of stdlib, a standard library 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

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