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flattenShapeFrom

Flatten a shape starting from a specified dimension.

Installation

npm install @stdlib/ndarray-base-flatten-shape-from

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 flattenShapeFrom = require( '@stdlib/ndarray-base-flatten-shape-from' );

flattenShapeFrom( shape, dim )

Flattens a shape starting from a specified dimension.

var sh = flattenShapeFrom( [ 3, 3, 2 ], 1 );
// returns [ 3, 6 ]

The function accepts the following parameters:

• shape: array shape.
• dim: dimension to start flattening from.

flattenShapeFrom.assign( shape, dim, out )

Flattens a shape starting from a specified dimension and assigns results to a provided output array.

var sh = [ 0, 0 ];

var out = flattenShapeFrom.assign( [ 3, 3, 2 ], 1, sh );
// returns [ 3, 6 ]

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

The function accepts the following parameters:

• shape: array shape.
• dim: dimension to start flattening from. If provided an integer less than zero, the dimension index is resolved relative to the last dimension, with the last dimension corresponding to the value -1.
• out: output array.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var zip = require( '@stdlib/array-base-zip' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var flattenShapeFrom = require( '@stdlib/ndarray-base-flatten-shape-from' );

var opts = {
    'dtype': 'int32'
};
var d1 = discreteUniform( 100, 1, 10, opts );
var d2 = discreteUniform( d1.length, 1, 10, opts );
var d3 = discreteUniform( d1.length, 1, 10, opts );
var d4 = discreteUniform( d1.length, 1, 10, opts );

var dims = discreteUniform( d1.length, -4, 3, opts );
var shapes = zip( [ d1, d2, d3, d4 ] );

logEachMap( 'shape: (%s). dim: %d. flattened: (%s).', shapes, dims, flattenShapeFrom );

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C APIs

Usage

#include "stdlib/ndarray/base/flatten_shape_from.h"

stdlib_ndarray_flatten_shape_from( ndims, *shape, dim, *out )

Flattens a shape starting from a specified dimension.

const int64_t ndims = 3;
const int64_t shape[] = { 2, 3, 10 };
int64_t out[ 2 ];

stdlib_ndarray_flatten_shape( ndims, shape, 1, out );

The function accepts the following arguments:

• ndims: [in] int64_t number of dimensions.
• shape: [in] int64_t* array shape (dimensions).
• dim: [in] int64_t dimension to start flattening from.
• out: [out] int64_t* output array.

int8_t stdlib_ndarray_flatten_shape_from( const int64_t ndims, const int64_t *shape, const int64_t dim, int64_t *out );

Examples

#include "stdlib/ndarray/base/flatten_shape_from.h"
#include <stdio.h>
#include <inttypes.h>

int main( void ) {
    const int64_t shape[] = { 2, 3, 4, 10 };
    const int64_t ndims = 4;
    const int64_t dim = 2;
    int64_t out[ 3 ];

    stdlib_ndarray_flatten_shape_from( ndims, shape, dim, out );

    int i;
    printf( "shape = ( " );
    for ( i = 0; i < ndims-dim+1; i++ ) {
        printf( "%"PRId64"", out[ i ] );
        if ( i < ndims-dim ) {
            printf( ", " );
        }
    }
    printf( " )\n" );
}

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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.