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Base

Base ndarray extended BLAS functions.

Installation

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

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 ns = require( '@stdlib/blas-ext-base-ndarray' );

ns

Namespace containing base ndarray extended BLAS functions.

var o = ns;
// returns {...}

The namespace exposes the following APIs:

• csum( arrays ): compute the sum of all elements in a one-dimensional single-precision complex floating-point ndarray.
• csumkbn( arrays ): compute the sum of all elements in a one-dimensional single-precision complex floating-point ndarray using an improved Kahan–Babuška algorithm.
• dcircshift( arrays ): circularly shift the elements of a one-dimensional double-precision floating-point ndarray by a specified number of positions.
• dcusum( arrays ): compute the cumulative sum of a one-dimensional double-precision floating-point ndarray.
• dcusumkbn( arrays ): compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.
• dcusumkbn2( arrays ): compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
• dcusumors( arrays ): compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation.
• dcusumpw( arrays ): compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using pairwise summation.
• dindexOf( arrays ): return the first index of a search element in a one-dimensional double-precision floating-point ndarray.
• dlastIndexOf( arrays ): return the last index of a search element in a one-dimensional double-precision floating-point ndarray.
• dlinspace( arrays ): fill a one-dimensional double-precision floating-point ndarray with linearly spaced values over a specified interval.
• dnansum( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.
• dnansumkbn( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.
• dnansumkbn2( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.
• dnansumors( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.
• dnansumpw( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using pairwise summation.
• dsorthp( arrays ): sort a one-dimensional double-precision floating-point ndarray using heapsort.
• dsortins( arrays ): sort a one-dimensional double-precision floating-point ndarray using insertion sort.
• dsortsh( arrays ): sort a one-dimensional double-precision floating-point ndarray using Shellsort.
• dsum( arrays ): compute the sum of all elements in a one-dimensional double-precision floating-point ndarray.
• dsumkbn( arrays ): compute the sum of all elements in a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.
• dsumkbn2( arrays ): compute the sum of all elements in a one-dimensional double-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
• dsumors( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation.
• dsumpw( arrays ): compute the sum of a one-dimensional double-precision floating-point ndarray using pairwise summation.
• gcircshift( arrays ): circularly shift the elements of a one-dimensional ndarray by a specified number of positions.
• gcusum( arrays ): compute the cumulative sum of a one-dimensional ndarray.
• gcusumkbn( arrays ): compute the cumulative sum of a one-dimensional ndarray using an improved Kahan–Babuška algorithm.
• gcusumkbn2( arrays ): compute the cumulative sum of a one-dimensional ndarray using a second-order iterative Kahan–Babuška algorithm.
• gcusumors( arrays ): compute the cumulative sum of a one-dimensional ndarray using ordinary recursive summation.
• gcusumpw( arrays ): compute the cumulative sum of a one-dimensional ndarray using pairwise summation.
• gfindIndex( arrays, clbk[, thisArg] ): return the index of the first element in a one-dimensional ndarray which passes a test implemented by a predicate function.
• gfindLastIndex( arrays, clbk[, thisArg] ): return the index of the last element in a one-dimensional ndarray which passes a test implemented by a predicate function.
• gindexOf( arrays ): return the first index of a search element in a one-dimensional ndarray.
• gjoinBetween( arrays ): return a string by joining one-dimensional ndarray elements using a specified separator for each pair of consecutive elements.
• gjoin( arrays ): return a string created by joining one-dimensional ndarray elements using a specified separator.
• glastIndexOf( arrays ): return the last index of a search element in a one-dimensional ndarray.
• glinspace( arrays ): fill a one-dimensional ndarray with linearly spaced values over a specified interval.
• gnansum( arrays ): compute the sum of a one-dimensional ndarray, ignoring NaN values.
• gnansumkbn( arrays ): compute the sum of a one-dimensional ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.
• gnansumkbn2( arrays ): compute the sum of a one-dimensional ndarray, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.
• gnansumors( arrays ): compute the sum of a one-dimensional ndarray, ignoring NaN values and using ordinary recursive summation.
• gnansumpw( arrays ): compute the sum of a one-dimensional ndarray, ignoring NaN values and using pairwise summation.
• gsort( arrays ): sort a one-dimensional ndarray.
• gsorthp( arrays ): sort a one-dimensional ndarray using heapsort.
• gsum( arrays ): compute the sum of all elements in a one-dimensional ndarray.
• gsumkbn( arrays ): compute the sum of all elements in a one-dimensional ndarray using an improved Kahan–Babuška algorithm.
• gsumkbn2( arrays ): compute the sum of all elements in a one-dimensional ndarray using a second-order iterative Kahan–Babuška algorithm.
• gsumors( arrays ): compute the sum of all elements in a one-dimensional ndarray using ordinary recursive summation.
• gsumpw( arrays ): compute the sum of all elements in a one-dimensional ndarray using pairwise summation.
• scircshift( arrays ): circularly shift the elements of a one-dimensional single-precision floating-point ndarray by a specified number of positions.
• scusum( arrays ): compute the cumulative sum of a one-dimensional single-precision floating-point ndarray.
• scusumkbn( arrays ): compute the cumulative sum of a one-dimensional single-precision floating-point ndarray using an improved Kahan–Babuška algorithm.
• scusumkbn2( arrays ): compute the cumulative sum of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
• scusumors( arrays ): compute the cumulative sum of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
• sindexOf( arrays ): return the first index of a search element in a one-dimensional single-precision floating-point ndarray.
• slastIndexOf( arrays ): return the last index of a search element in a one-dimensional single-precision floating-point ndarray.
• slinspace( arrays ): fill a one-dimensional single-precision floating-point ndarray with linearly spaced values over a specified interval.
• snansum( arrays ): compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.
• snansumkbn( arrays ): compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.
• snansumkbn2( arrays ): compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.
• snansumors( arrays ): compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.
• snansumpw( arrays ): compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using pairwise summation.
• ssorthp( arrays ): sort a one-dimensional single-precision floating-point ndarray using heapsort.
• ssum( arrays ): compute the sum of all elements in a one-dimensional single-precision floating-point ndarray.
• ssumkbn( arrays ): compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using an improved Kahan–Babuška algorithm.
• ssumkbn2( arrays ): compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
• ssumors( arrays ): compute the sum of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
• ssumpw( arrays ): compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using pairwise summation.
• zsum( arrays ): compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray.
• zsumkbn( arrays ): compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray using an improved Kahan–Babuška algorithm.

Examples

var objectKeys = require( '@stdlib/utils-keys' );
var ns = require( '@stdlib/blas-ext-base-ndarray' );

console.log( objectKeys( ns ) );

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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 © 2016-2026. The Stdlib Authors.