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Calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.
import dsumkbn from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-dsumkbn@deno/mod.js';Computes the sum of double-precision floating-point strided array elements using an improved 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 N = x.length;
var v = dsumkbn( N, x, 1 );
// returns 1.0The 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 the strided array are accessed at runtime. For example, to compute the sum of every other element in the strided array,
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 = dsumkbn( 4, x, 2 );
// returns 5.0Note 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 = dsumkbn( 4, x1, 2 );
// returns 5.0Computes the sum of double-precision floating-point strided array elements using an improved 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 = dsumkbn.ndarray( 3, x, 1, 0 );
// returns 1.0The 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 the strided array starting from the second value
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 = dsumkbn.ndarray( 4, x, 2, 1 );
// returns 5.0- If
N <= 0, both functions return0.0.
var discreteUniform = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform' ).factory;
import filledarrayBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@deno/mod.js';
import dsumkbn from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-dsumkbn@deno/mod.js';
var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) );
console.log( x );
var v = dsumkbn( x.length, x, 1 );
console.log( v );- 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.
@stdlib/blas-ext/base/dnansumkbn: calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using an improved Kahan–Babuška algorithm.@stdlib/blas-ext/base/dsum: calculate the sum of double-precision floating-point strided array elements.@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/dsumors: calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.@stdlib/blas-ext/base/dsumpw: calculate the sum of double-precision floating-point strided array elements using pairwise summation.@stdlib/blas-ext/base/gsumkbn: calculate the sum of strided array elements using an improved Kahan–Babuška algorithm.@stdlib/blas-ext/base/ssumkbn: calculate the sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.
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