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https://github.com/stdlib-js/stats-base-smean

Calculate the arithmetic mean of a single-precision floating-point strided array.
https://github.com/stdlib-js/stats-base-smean

arithmetic-mean array average avg central-tendency float float32 javascript math mathematics mean node node-js nodejs statistics stats stdlib strided strided-array typed

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Calculate the arithmetic mean of a single-precision floating-point strided array.

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README

        


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# smean

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

> Calculate the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array.

The [arithmetic mean][arithmetic-mean] is defined as

```math
\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i
```

## Installation

```bash
npm install @stdlib/stats-base-smean
```

Alternatively,

- To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]).
- If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).
- For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]).

The [branches.md][branches-url] 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

```javascript
var smean = require( '@stdlib/stats-base-smean' );
```

#### smean( N, x, stride )

Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x`.

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

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

var v = smean( N, x, 1 );
// returns ~0.3333
```

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 `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,

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

var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );

var v = smean( N, x, 2 );
// returns 1.25
```

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

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

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 N = floor( x0.length / 2 );

var v = smean( N, x1, 2 );
// returns 1.25
```

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

Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using alternative indexing semantics.

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

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

var v = smean.ndarray( N, x, 1, 0 );
// returns ~0.33333
```

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 [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value

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

var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );

var v = smean.ndarray( N, x, 2, 1 );
// returns 1.25
```

## Notes

- If `N <= 0`, both functions return `NaN`.

## Examples

```javascript
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float32Array = require( '@stdlib/array-float32' );
var smean = require( '@stdlib/stats-base-smean' );

var x;
var i;

x = new Float32Array( 10 );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
console.log( x );

var v = smean( x.length, x, 1 );
console.log( v );
```

* * *

## See Also

- [`@stdlib/stats-base/dmean`][@stdlib/stats/base/dmean]: calculate the arithmetic mean of a double-precision floating-point strided array.
- [`@stdlib/stats-base/dsmean`][@stdlib/stats/base/dsmean]: calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.
- [`@stdlib/stats-base/mean`][@stdlib/stats/base/mean]: calculate the arithmetic mean of a strided array.
- [`@stdlib/stats-base/sdsmean`][@stdlib/stats/base/sdsmean]: calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation.
- [`@stdlib/stats-base/snanmean`][@stdlib/stats/base/snanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values.

* * *

## 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 © 2016-2024. The Stdlib [Authors][stdlib-authors].

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

[test-image]: https://github.com/stdlib-js/stats-base-smean/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/stats-base-smean/actions/workflows/test.yml?query=branch:main

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

[chat-image]: https://img.shields.io/gitter/room/stdlib-js/stdlib.svg
[chat-url]: https://app.gitter.im/#/room/#stdlib-js_stdlib:gitter.im

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

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

[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean

[@stdlib/array/float32]: https://github.com/stdlib-js/array-float32

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

[@stdlib/stats/base/dmean]: https://github.com/stdlib-js/stats-base-dmean

[@stdlib/stats/base/dsmean]: https://github.com/stdlib-js/stats-base-dsmean

[@stdlib/stats/base/mean]: https://github.com/stdlib-js/stats-base-mean

[@stdlib/stats/base/sdsmean]: https://github.com/stdlib-js/stats-base-sdsmean

[@stdlib/stats/base/snanmean]: https://github.com/stdlib-js/stats-base-snanmean