meanpn

Compute the arithmetic mean along one or more ndarray dimensions using a two-pass error correction algorithm.

The arithmetic mean is defined as

Installation

npm install @stdlib/stats-meanpn

Usage

var meanpn = require( '@stdlib/stats-meanpn' );

meanpn( x[, options] )

Computes the arithmetic mean along one or more ndarray dimensions using a two-pass error correction algorithm.

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

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

var y = meanpn( x );
// returns <ndarray>[ 1.25 ]

The function has the following parameters:

• x: input ndarray. Must have a real-valued or "generic" data type.
• options: function options (optional).

The function accepts the following options:

• dims: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input ndarray.
• dtype: output ndarray data type. Must be a real-valued floating-point or "generic" data type.
• keepdims: boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions. Default: false.

By default, the function performs a reduction over all elements in a provided input ndarray. To perform a reduction over specific dimensions, provide a dims option.

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

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

var y = meanpn( x, {
    'dims': [ 0 ]
});
// returns <ndarray>[ -0.5, 3.0 ]

y = meanpn( x, {
    'dims': [ 1 ]
});
// returns <ndarray>[ 1.5, 1.0 ]

y = meanpn( x, {
    'dims': [ 0, 1 ]
});
// returns <ndarray>[ 1.25 ]

By default, the function excludes reduced dimensions from the output ndarray. To include the reduced dimensions as singleton dimensions, set the keepdims option to true.

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

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

var y = meanpn( x, {
    'dims': [ 0 ],
    'keepdims': true
});
// returns <ndarray>[ [ -0.5, 3.0 ] ]

y = meanpn( x, {
    'dims': [ 1 ],
    'keepdims': true
});
// returns <ndarray>[ [ 1.5 ], [ 1.0 ] ]

y = meanpn( x, {
    'dims': [ 0, 1 ],
    'keepdims': true
});
// returns <ndarray>[ [ 1.25 ] ]

By default, the function returns an ndarray having a data type determined by the function's output data type policy. To override the default behavior, set the dtype option.

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

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

meanpn.assign( x, out[, options] )

Computes the arithmetic mean along one or more ndarray dimensions using a two-pass error correction algorithm and assigns results to a provided output ndarray.

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 = meanpn.assign( x, y );
// returns <ndarray>[ 1.25 ]

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

The method has the following parameters:

• x: input ndarray. Must have a real-valued or "generic" data type.
• out: output ndarray.
• options: function options (optional).

The method accepts the following options:

• dims: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input ndarray.

Notes

• Setting the keepdims option to true can be useful when wanting to ensure that the output ndarray is broadcast-compatible with ndarrays having the same shape as the input ndarray.
• The output data type policy only applies to the main function and specifies that, by default, the function must return an ndarray having a real-valued floating-point or "generic" data type. For the assign method, the output ndarray is allowed to have any supported output data type.

Examples

var uniform = require( '@stdlib/random-uniform' );
var getDType = require( '@stdlib/ndarray-dtype' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var meanpn = require( '@stdlib/stats-meanpn' );

// Generate an array of random numbers:
var x = uniform( [ 5, 5 ], 0.0, 20.0 );
console.log( ndarray2array( x ) );

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

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

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

References

• Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." Communications of the ACM 9 (7). Association for Computing Machinery: 496–99. doi:10.1145/365719.365958.
• Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In Proceedings of the 30th International Conference on Scientific and Statistical Database Management. New York, NY, USA: Association for Computing Machinery. doi:10.1145/3221269.3223036.

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.

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License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.