sliceDimensionFrom

Return a read-only shifted view of an input ndarray along a specified dimension.

Installation

npm install @stdlib/ndarray-slice-dimension-from

Alternatively,

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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).

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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 sliceDimensionFrom = require( '@stdlib/ndarray-slice-dimension-from' );

sliceDimensionFrom( x, dim, start[, options] )

Returns a read-only shifted view of an input ndarray along a specified dimension.

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

var buffer = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var shape = [ 3, 2 ];
var strides = [ 2, 1 ];
var offset = 0;

var x = ndarray( 'generic', buffer, shape, strides, offset, 'row-major' );
// returns <ndarray>

var sh = x.shape;
// returns [ 3, 2 ]

var arr = ndarray2array( x );
// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]

var y = sliceDimensionFrom( x, 0, 1 );
// returns <ndarray>

sh = y.shape;
// returns [ 2, 2 ]

arr = ndarray2array( y );
// returns [ [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]

The function accepts the following arguments:

x: input ndarray.
dim: index of dimension along which to slice. 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.
start: starting index (inclusive). If provided an integer less than zero, the corresponding element along the specified dimension is resolved relative to the last element along that dimension. For negative integers, the last element corresponds to the value -1.
options: function options.

The function supports the following options:

strict: boolean indicating whether to enforce strict bounds checking.

By default, the function throws an error when provided a starting index which exceeds array bounds. To return an empty array when a starting index exceeds array bounds, set the strict option to false.

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

var buffer = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var shape = [ 3, 2 ];
var strides = [ 2, 1 ];
var offset = 0;

var x = ndarray( 'generic', buffer, shape, strides, offset, 'row-major' );
// returns <ndarray>

var sh = x.shape;
// returns [ 3, 2 ]

var arr = ndarray2array( x );
// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]

var y = sliceDimensionFrom( x, 1, 20, {
    'strict': false
});
// returns <ndarray>

sh = y.shape;
// returns [ 3, 0 ]

arr = ndarray2array( y );
// returns []

Examples

var array = require( '@stdlib/ndarray-array' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var zeroTo = require( '@stdlib/array-base-zero-to' );
var sliceDimensionFrom = require( '@stdlib/ndarray-slice-dimension-from' );

// Create a linear ndarray buffer:
var buf = zeroTo( 27 );

// Create an ndarray:
var x = array( buf, {
    'shape': [ 3, 3, 3 ]
});

// Get the last two rows of each matrix:
var y1 = sliceDimensionFrom( x, 1, 1 );
// returns <ndarray>

var a1 = ndarray2array( y1 );
// returns [ [ [ 3, 4, 5 ], [ 6, 7, 8 ] ], [ [ 12, 13, 14 ], [ 15, 16, 17 ] ], [ [ 21, 22, 23 ], [ 24, 25, 26 ] ] ]

// Get the last columns of each matrix:
var y2 = sliceDimensionFrom( x, 2, 1 );
// returns <ndarray>

var a2 = ndarray2array( y2 );
// returns [ [ [ 1, 2 ], [ 4, 5 ], [ 7, 8 ] ], [ [ 10, 11 ], [ 13, 14 ], [ 16, 17 ] ], [ [ 19, 20 ], [ 22, 23 ], [ 25, 26 ] ] ]

// Get the last two matrices:
var y3 = sliceDimensionFrom( x, 0, 1 );
// returns <ndarray>

var a3 = ndarray2array( y3 );
// returns [ [ [ 9, 10, 11 ], [ 12, 13, 14 ], [ 15, 16, 17 ] ], [ [ 18, 19, 20 ], [ 21, 22, 23 ], [ 24, 25, 26 ] ] ]

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.