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feat: add stats/dmean #8794

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stats/dmean
iampratik13 Dec 4, 2025
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fix: lint error
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290 changes: 290 additions & 0 deletions lib/node_modules/@stdlib/stats/dmean/README.md
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<!--

@license Apache-2.0

Copyright (c) 2025 The Stdlib Authors.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

-->

# dmean

> Compute the [arithmetic mean][arithmetic-mean] of a double-precision floating-point [ndarray][@stdlib/ndarray/ctor] along one or more dimensions.

<section class="intro">

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

<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> -->

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

<!-- <div class="equation" align="center" data-raw-text="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" data-equation="eq:arithmetic_mean">
<img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@42d8f64d805113ab899c79c7c39d6c6bac7fe25c/lib/node_modules/@stdlib/stats/strided/dmean/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
<br>
</div> -->

<!-- </equation> -->

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var dmean = require( '@stdlib/stats/dmean' );
```

#### dmean( x\[, options] )

Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point [ndarray][@stdlib/ndarray/ctor] along one or more dimensions.

```javascript
var array = require( '@stdlib/ndarray/array' );

var x = array( [ 1.0, 2.0, -2.0, 4.0 ] );

var y = dmean( x );
// returns <ndarray>

var v = y.get();
// returns 1.25
```

The function has the following parameters:

- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or "generic" [data type][@stdlib/ndarray/dtypes]. Input values are internally converted to double-precision floating-point format for computation.
- **options**: function options (_optional_).

The function accepts the following options:

- **dims**: list of dimensions along which to compute the mean. If not provided, the function computes the mean over all elements in the input [ndarray][@stdlib/ndarray/ctor].
- **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a real-valued floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. Default: `'float64'`.
- **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.

By default, the function computes the mean over all elements in the input [ndarray][@stdlib/ndarray/ctor]. To compute the mean along specific dimensions, provide a `dims` option.

```javascript
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var array = require( '@stdlib/ndarray/array' );

var x = array( [ 1.0, 2.0, -2.0, 4.0 ], {
'shape': [ 2, 2 ],
'order': 'row-major'
});
var v = ndarray2array( x );
// returns [ [ 1.0, 2.0 ], [ -2.0, 4.0 ] ]

var y = dmean( x, {
'dims': [ 0 ]
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ -0.5, 3.0 ]

y = dmean( x, {
'dims': [ 1 ]
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ 1.5, 1.0 ]

y = dmean( x, {
'dims': [ 0, 1 ]
});
// returns <ndarray>

v = y.get();
// returns 1.25
```

By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`.

```javascript
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var array = require( '@stdlib/ndarray/array' );

var x = array( [ 1.0, 2.0, -2.0, 4.0 ], {
'shape': [ 2, 2 ],
'order': 'row-major'
});

var v = ndarray2array( x );
// returns [ [ 1.0, 2.0 ], [ -2.0, 4.0 ] ]

var y = dmean( x, {
'dims': [ 0 ],
'keepdims': true
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ -0.5, 3.0 ] ]

y = dmean( x, {
'dims': [ 1 ],
'keepdims': true
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ 1.5 ], [ 1.0 ] ]

y = dmean( x, {
'dims': [ 0, 1 ],
'keepdims': true
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ 1.25 ] ]
```

By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a `'float64'` [data type][@stdlib/ndarray/dtypes]. To override the default behavior, set the `dtype` option.

```javascript
var getDType = require( '@stdlib/ndarray/dtype' );
var array = require( '@stdlib/ndarray/array' );

var x = array( [ 1.0, 2.0, -2.0, 4.0 ], {
'dtype': 'generic'
});

var y = dmean( x, {
'dtype': 'float64'
});
// returns <ndarray>

var dt = String( getDType( y ) );
// returns 'float64'
```

#### dmean.assign( x, out\[, options] )

Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point [ndarray][@stdlib/ndarray/ctor] along one or more dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor].

```javascript
var array = require( '@stdlib/ndarray/array' );
var zeros = require( '@stdlib/ndarray/zeros' );

var x = array( [ 1.0, 2.0, -2.0, 4.0 ] );
var y = zeros( [] );

var out = dmean.assign( x, y );
// returns <ndarray>

var v = out.get();
// returns 1.25

var bool = ( out === y );
// returns true
```

The method has the following parameters:

- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or generic [data type][@stdlib/ndarray/dtypes].
- **out**: output [ndarray][@stdlib/ndarray/ctor].
- **options**: function options (_optional_).

The method accepts the following options:

- **dims**: list of dimensions along which to compute the mean. If not provided, the function computes the mean over all elements in the input [ndarray][@stdlib/ndarray/ctor].

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- The function performs double-precision floating-point arithmetic internally, regardless of the input array's data type. Input values are converted to `float64` format for computation, ensuring consistent precision across different input types.
- If any element in the input array is `NaN`, the computed mean for the corresponding reduction will be `NaN`.
- For empty arrays or reductions over dimensions with zero elements, the function returns `NaN`.
- Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor].
- The output [ndarray][@stdlib/ndarray/ctor] for the main function defaults to `'float64'` data type to preserve the precision of the double-precision computation. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] data type is determined by the provided output array.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var getDType = require( '@stdlib/ndarray/dtype' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var dmean = require( '@stdlib/stats/dmean' );

// Generate an array of random numbers:
var xbuf = discreteUniform( 25, 0, 20, {
'dtype': 'generic'
});

// Wrap in an ndarray:
var x = new ndarray( 'generic', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

// Perform a reduction:
var y = dmean( x, {
'dims': [ 0 ]
});

// Resolve the output array data type:
var dt = getDType( y );
console.log( dt );

// Print the results:
console.log( ndarray2array( y ) );
```

</section>

<!-- /.examples -->

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

<section class="related">

</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="links">

[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor

[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes

[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes

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

</section>

<!-- /.links -->
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