npm package: @stdlib/blas-base-snrm2
Description: Calculate the L2-norm of a single-precision floating-point vector.
Author: The Stdlib Authors
Latest version: 0.3.1

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# snrm2

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

> Calculate the L2-norm of a single-precision floating-point vector.

<section class="intro">

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

<!-- <equation class="equation" label="eq:l2_norm" align="center" raw="\|\mathbf{x}\|_2 = \sqrt{x_0^2 + x_1^2 + \ldots + x_{N-1}^2}" alt="L2-norm definition."> -->

<div class="equation" align="center" data-raw-text="\|\mathbf{x}\|_2 = \sqrt{x_0^2 + x_1^2 + \ldots + x_{N-1}^2}" data-equation="eq:l2_norm">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@247c6b352fc1002f11ba3e7ed389f067380a8a87/lib/node_modules/@stdlib/blas/base/snrm2/docs/img/equation_l2_norm.svg" alt="L2-norm definition.">
    <br>
</div>

<!-- </equation> -->

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/blas-base-snrm2
```

</section>

<section class="usage">

## Usage

```javascript
var snrm2 = require( '@stdlib/blas-base-snrm2' );
```

#### snrm2( N, x, stride )

Computes the [L2-norm][l2-norm] of a single-precision floating-point vector `x`.

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

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

var z = snrm2( x.length, x, 1 );
// returns 3.0
```

The function has the following parameters:

-   **N**: number of indexed elements.
-   **x**: input [`Float32Array`][@stdlib/array/float32].
-   **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 [L2-norm][l2-norm] of every other element in `x`,

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

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

var z = snrm2( 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.

<!-- eslint-disable stdlib/capitalized-comments -->

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

var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -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 z = snrm2( 4, x1, 2 );
// returns 5.0
```

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

#### snrm2.ndarray( N, x, stride, offset )

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

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

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

var z = snrm2.ndarray( x.length, x, 1, 0 );
// returns 3.0
```

The function has the following additional parameters:

-   **offset**: starting index for `x`.

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 `x` starting from the second value

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

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

var z = snrm2.ndarray( 4, x, 2, 1 );
// returns 5.0
```

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If `N <= 0`, both functions return `0.0`.
-   `snrm2()` corresponds to the [BLAS][blas] level 1 function [`snrm2`][snrm2].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var snrm2 = require( '@stdlib/blas-base-snrm2' );

var opts = {
    'dtype': 'float32'
};
var x = discreteUniform( 10, 0, 100, opts );
console.log( x );

var out = snrm2( x.length, x, 1 );
console.log( out );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/blas/base/snrm2.h"
```

#### c_snrm2( N, \*X, stride )

Computes the L2-norm of a single-precision floating-point vector.

```c
const float x[] = { 1.0f, 2.0f, 2.0f, -7.0f, -2.0f, 3.0f, 4.0f, 2.0f };

float norm = c_snrm2( 4, x, 2 );
// returns 5.0f
```

The function accepts the following arguments:

-   **N**: `[in] CBLAS_INT` number of indexed elements.
-   **X**: `[in] float*` input array.
-   **stride**: `[in] CBLAS_INT` index increment for `X`.

```c
float c_snrm2( const CBLAS_INT N, const float *X, const CBLAS_INT stride );
```

#### c_snrm2_ndarray( N, \*X, stride, offset )

Computes the L2-norm of a single-precision floating-point vector using alternative indexing semantics.

```c
const float x[] = { 1.0f, 2.0f, 2.0f, -7.0f, -2.0f, 3.0f, 4.0f, 2.0f };

float norm = c_snrm2_ndarray( 4, x, 2, 0 );
// returns 5.0f
```

The function accepts the following arguments:

-   **N**: `[in] CBLAS_INT` number of indexed elements.
-   **X**: `[in] float*` input array.
-   **stride**: `[in] CBLAS_INT` index increment for `X`.
-   **offset**: `[in] CBLAS_INT` starting index for `X`.

```c
float c_snrm2_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT stride, const CBLAS_INT offset );
```

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/blas/base/snrm2.h"
#include <stdio.h>

int main( void ) {
    // Create a strided array:
    const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };

    // Specify the number of indexed elements:
    const int N = 8;

    // Specify a stride:
    const int strideX = 1;

    // Compute the L2-norm:
    float l2 = c_snrm2( N, x, strideX );

    // Print the result:
    printf( "L2-norm: %f\n", l2 );

    // Compute the L2-norm:
    l2 = c_snrm2_ndarray( N, x, -strideX, 7 );

    // Print the result:
    printf( "L2-norm: %f\n", l2 );
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

* * *

<section class="references">

## 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].

</section>

<!-- /.references -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/blas-base/dnrm2`][@stdlib/blas/base/dnrm2]</span><span class="delimiter">: </span><span class="description">calculate the L2-norm of a double-precision floating-point vector.</span>
-   <span class="package-name">[`@stdlib/blas-base/gnrm2`][@stdlib/blas/base/gnrm2]</span><span class="delimiter">: </span><span class="description">calculate the L2-norm of a vector.</span>

</section>

<!-- /.related -->

<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->


<section class="main-repo" >

* * *

## 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

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

</section>

<!-- /.stdlib -->

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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-base-snrm2/main/LICENSE

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

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

[snrm2]: http://www.netlib.org/lapack/explore-html/df/d28/group__single__blas__level1.html

[@stdlib/array/float32]: https://www.npmjs.com/package/@stdlib/array-float32

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

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

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

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