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flattenBy

Flatten an ndarray according to a callback function.

Installation

npm install @stdlib/ndarray-flatten-by

Alternatively,

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

The branches.md 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

var flattenBy = require( '@stdlib/ndarray-flatten-by' );

flattenBy( x[, options], fcn[, thisArg] )

Flattens an ndarray according to a callback function.

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

function scale( value ) {
    return value * 2.0;
}

var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
// returns <ndarray>

var y = flattenBy( x, scale );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ]

The function accepts the following arguments:

• x: input ndarray.
• options: function options (optional).
• fcn: callback function.
• thisArg: callback execution context (optional).

The function accepts the following options:

• order: order in which input ndarray elements should be flattened. Must be one of the following:

  • 'row-major': flatten elements in lexicographic order. For example, given a two-dimensional input ndarray (i.e., a matrix), flattening in lexicographic order means flattening the input ndarray row-by-row.
  • 'column-major': flatten elements in colexicographic order. For example, given a two-dimensional input ndarray (i.e., a matrix), flattening in colexicographic order means flattening the input ndarray column-by-column.
  • 'any': flatten according to the physical layout of the input ndarray data in memory, regardless of the stated order of the input ndarray.
  • 'same': flatten according to the stated order of the input ndarray.

  Default: 'row-major'.

• depth: maximum number of input ndarray dimensions to flatten.

• dtype: output ndarray data type. By default, the function returns an ndarray having the same data type as a provided input ndarray.

By default, the function flattens all dimensions of the input ndarray. To flatten to a desired depth, specify the depth option.

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

function scale( value ) {
    return value * 2.0;
}

var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
// returns <ndarray>

var opts = {
    'depth': 1
};

var y = flattenBy( x, opts, scale );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ [ 2.0, 4.0 ], [ 6.0, 8.0 ], [ 10.0, 12.0 ] ]

By default, the input ndarray is flattened in lexicographic order. To flatten elements in a different order, specify the order option.

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

function scale( value ) {
    return value * 2.0;
}

var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
// returns <ndarray>

var opts = {
    'order': 'column-major'
};

var y = flattenBy( x, opts, scale );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ 2.0, 6.0, 10.0, 4.0, 8.0, 12.0 ]

By default, the output ndarray data type is inferred from the input ndarray. To return an ndarray with a different data type, specify the dtype option.

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

function scale( value ) {
    return value * 2.0;
}

var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
// returns <ndarray>

var opts = {
    'dtype': 'float32'
};
var y = flattenBy( x, opts, scale );
// returns <ndarray>

var dt = String( dtype( y ) );
// returns 'float32'

var arr = ndarray2array( y );
// returns [ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ]

To set the callback function execution context, provide a thisArg.

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

function scale( value ) {
    this.count += 1;
    return value * 2.0;
}

var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
// returns <ndarray>

var ctx = {
    'count': 0
};

var y = flattenBy( x, scale, ctx );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ]

var count = ctx.count;
// returns 6

Notes

• The function always returns a copy of input ndarray data, even when an input ndarray already has the desired number of dimensions.

• The callback function is provided the following arguments:

  • value: current array element.
  • indices: current array element indices.
  • arr: the input ndarray.

• The order in which array elements are traversed and passed to a provided callback function is not guaranteed to match the order of array elements in an ndarray view. Accordingly, a provided callback should avoid making assumptions regarding the order of provided elements.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var array = require( '@stdlib/ndarray-array' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var flattenBy = require( '@stdlib/ndarray-flatten-by' );

function scale( value ) {
    return value * 2.0;
}

var xbuf = discreteUniform( 12, -100, 100, {
    'dtype': 'generic'
});

var x = array( xbuf, {
    'shape': [ 2, 2, 3 ],
    'dtype': 'generic'
});
console.log( ndarray2array( x ) );

var y = flattenBy( x, scale );
console.log( ndarray2array( y ) );

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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.

Community

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.