About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

gnrm2

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]

> Calculate the L2-norm of a vector.

The [L2-norm][l2-norm] is defined as

Installation

``bash npm install @stdlib/blas-base-gnrm2`

`Usage`

`javascript var gnrm2 = require( '@stdlib/blas-base-gnrm2' );`

#### gnrm2( N, x, stride )

Computes the [L2-norm][l2-norm] of a vector.

`javascript var x = [ 1.0, -2.0, 2.0 ];

var z = gnrm2( x.length, x, 1 ); // returns 3.0`

The function has the following parameters:

- N: number of indexed elements. - x: input [Array][mdn-array] or [typed array][mdn-typed-array]. - stride: stride length.

The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [L2-norm][l2-norm] of every other element:

`javascript var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];

var z = gnrm2( 4, x, 2 ); // returns 5.0`

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

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

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 z = gnrm2( 4, x1, 2 ); // returns 5.0`

If N is less than or equal to 0, the function returns 0.

#### gnrm2.ndarray( N, x, stride, offset )

Computes the [L2-norm][l2-norm] of a vector using alternative indexing semantics.

`javascript var x = [ 1.0, -2.0, 2.0 ];

var z = gnrm2.ndarray( x.length, x, 1, 0 ); // returns 3.0`

The function has the following additional parameters:

- offset: starting index.

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 [L2-norm][l2-norm] for every other value in the strided array starting from the second value:

`javascript var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];

var z = gnrm2.ndarray( 4, x, 2, 1 ); // returns 5.0`

`Notes`

- If N <= 0, both functions return 0.0. -gnrm2() corresponds to the [BLAS][blas] level 1 function [dnrm2][dnrm2] with the exception that this implementation works with any array type, not just Float64Arrays. Depending on the environment, the typed versions ([dnrm2][@stdlib/blas/base/dnrm2], [snrm2][@stdlib/blas/base/snrm2], etc.) are likely to be significantly more performant. - Both functions support array-like objects having getter and setter accessors for array element access (e.g., [@stdlib/array-base/accessor][@stdlib/array/base/accessor]).

`Examples`

`javascript var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); var gnrm2 = require( '@stdlib/blas-base-gnrm2' );

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

var out = gnrm2( x.length, x, 1 ); console.log( out );`

*

`References`

- Blue, James L. 1978. "A Portable Fortran Program to Find the Euclidean Norm of a Vector." _ACM Transactions on Mathematical Software_ 4 (1). New York, NY, USA: Association for Computing Machinery: 15–23. doi:[10.1145/355769.355771][@blue:1978a]. - Anderson, Edward. 2017. "Algorithm 978: Safe Scaling in the Level 1 BLAS." _ACM Transactions on Mathematical Software_ 44 (1). New York, NY, USA: Association for Computing Machinery: 1–28. doi:[10.1145/3061665][@anderson:2017a].

*

`Notice`

This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].

#### Community

[![Chat][chat-image]][chat-url]

---

`License`

See [LICENSE][stdlib-license].

`Copyright`

[npm-image]: http://img.shields.io/npm/v/@stdlib/blas-base-gnrm2.svg [npm-url]: https://npmjs.org/package/@stdlib/blas-base-gnrm2

[test-image]: https://github.com/stdlib-js/blas-base-gnrm2/actions/workflows/test.yml/badge.svg?branch=v0.3.1 [test-url]: https://github.com/stdlib-js/blas-base-gnrm2/actions/workflows/test.yml?query=branch:v0.3.1

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/blas-base-gnrm2/main.svg [coverage-url]: https://codecov.io/github/stdlib-js/blas-base-gnrm2?branch=main

[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg [chat-url]: https://stdlib.zulipchat.com

[stdlib]: https://github.com/stdlib-js/stdlib

[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors

[umd]: https://github.com/umdjs/umd [es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules

[deno-url]: https://github.com/stdlib-js/blas-base-gnrm2/tree/deno [deno-readme]: https://github.com/stdlib-js/blas-base-gnrm2/blob/deno/README.md [umd-url]: https://github.com/stdlib-js/blas-base-gnrm2/tree/umd [umd-readme]: https://github.com/stdlib-js/blas-base-gnrm2/blob/umd/README.md [esm-url]: https://github.com/stdlib-js/blas-base-gnrm2/tree/esm [esm-readme]: https://github.com/stdlib-js/blas-base-gnrm2/blob/esm/README.md [branches-url]: https://github.com/stdlib-js/blas-base-gnrm2/blob/main/branches.md

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-base-gnrm2/main/LICENSE

[l2-norm]: https://en.wikipedia.org/wiki/Euclidean_distance

[blas]: http://www.netlib.org/blas

[dnrm2]: http://www.netlib.org/lapack/explore-html/de/da4/group__double__blas__level1.html

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

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

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

[@stdlib/blas/base/dnrm2]: https://www.npmjs.com/package/@stdlib/blas-base-dnrm2

[@stdlib/blas/base/snrm2]: https://www.npmjs.com/package/@stdlib/blas-base-snrm2

[@blue:1978a]: https://doi.org/10.1145/355769.355771

[@anderson:2017a]: https://doi.org/10.1145/3061665


  
    About stdlib...
  

  We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

  The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

  When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

  To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

`gnrm2`

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]

> Calculate the L2-norm of a vector.

The [L2-norm][l2-norm] is defined as

`Installation`

``bash npm install @stdlib/blas-base-gnrm2 `

`Usage`

`javascript var gnrm2 = require( '@stdlib/blas-base-gnrm2' ); `

#### gnrm2( N, x, stride )

Computes the [L2-norm][l2-norm] of a vector.

`javascript var x = [ 1.0, -2.0, 2.0 ];

var z = gnrm2( x.length, x, 1 ); // returns 3.0 `

The function has the following parameters:

- N: number of indexed elements. - x: input [Array][mdn-array] or [typed array][mdn-typed-array]. - stride: stride length.

The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [L2-norm][l2-norm] of every other element:

`javascript var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];

var z = gnrm2( 4, x, 2 ); // returns 5.0 `

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

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

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 z = gnrm2( 4, x1, 2 ); // returns 5.0 `

If N is less than or equal to 0, the function returns 0.

#### gnrm2.ndarray( N, x, stride, offset )

Computes the [L2-norm][l2-norm] of a vector using alternative indexing semantics.

`javascript var x = [ 1.0, -2.0, 2.0 ];

var z = gnrm2.ndarray( x.length, x, 1, 0 ); // returns 3.0 `

The function has the following additional parameters:

- offset: starting index.

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 [L2-norm][l2-norm] for every other value in the strided array starting from the second value:

`javascript var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];

var z = gnrm2.ndarray( 4, x, 2, 1 ); // returns 5.0 `

`Notes`

- If N <= 0, both functions return 0.0. - gnrm2() corresponds to the [BLAS][blas] level 1 function [dnrm2][dnrm2] with the exception that this implementation works with any array type, not just Float64Arrays. Depending on the environment, the typed versions ([dnrm2][@stdlib/blas/base/dnrm2], [snrm2][@stdlib/blas/base/snrm2], etc.) are likely to be significantly more performant. - Both functions support array-like objects having getter and setter accessors for array element access (e.g., [@stdlib/array-base/accessor][@stdlib/array/base/accessor]).

`Examples`

`javascript var discreteUniform = require( '@stdlib/random-array-discrete-uniform' ); var gnrm2 = require( '@stdlib/blas-base-gnrm2' );

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

var out = gnrm2( x.length, x, 1 ); console.log( out ); `

*

`References`

*

`Notice`

For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].

#### Community

[![Chat][chat-image]][chat-url]

---

`License`

See [LICENSE][stdlib-license].

`Copyright`

[npm-image]: http://img.shields.io/npm/v/@stdlib/blas-base-gnrm2.svg [npm-url]: https://npmjs.org/package/@stdlib/blas-base-gnrm2

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/blas-base-gnrm2/main.svg [coverage-url]: https://codecov.io/github/stdlib-js/blas-base-gnrm2?branch=main

[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg [chat-url]: https://stdlib.zulipchat.com

[stdlib]: https://github.com/stdlib-js/stdlib

[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors

[umd]: https://github.com/umdjs/umd [es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-base-gnrm2/main/LICENSE

[l2-norm]: https://en.wikipedia.org/wiki/Euclidean_distance

[blas]: http://www.netlib.org/blas

[dnrm2]: http://www.netlib.org/lapack/explore-html/de/da4/group__double__blas__level1.html

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

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

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

[@stdlib/blas/base/dnrm2]: https://www.npmjs.com/package/@stdlib/blas-base-dnrm2

[@stdlib/blas/base/snrm2]: https://www.npmjs.com/package/@stdlib/blas-base-snrm2

[@blue:1978a]: https://doi.org/10.1145/355769.355771

[@anderson:2017a]: https://doi.org/10.1145/3061665

@stdlib/blas-base-gnrm2

gnrm2

Installation

Usage

Notes

Examples

References

See Also

Notice

License

Copyright

@stdlib/blas-base-gnrm2

gnrm2

Installation

Usage

Notes

Examples

References

See Also

Notice

License

Copyright

`Usage`

`Notes`

`Examples`

`References`

`See Also`

`Notice`

`License`

`Copyright`

`@stdlib/blas-base-gnrm2`

`gnrm2`

`Installation`

`Usage`

`Notes`

`Examples`

`References`

`See Also`

`Notice`

`License`

`Copyright`