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unaryReduceStrided1d

Perform a reduction over a list of specified dimensions in an input ndarray via a one-dimensional strided array reduction function and assign results to a provided output ndarray.

Usage

import unaryReduceStrided1d from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-reduce-strided1d@esm/index.mjs';

You can also import the following named exports from the package:

import { factory } from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-reduce-strided1d@esm/index.mjs';

unaryReduceStrided1d( fcn, arrays, dims[, options] )

Performs a reduction over a list of specified dimensions in an input ndarray via a one-dimensional strided array reduction function and assigns results to a provided output ndarray.

import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@esm/index.mjs';
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-array@esm/index.mjs';
import getStride from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-stride@esm/index.mjs';
import getOffset from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-offset@esm/index.mjs';
import getData from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-data-buffer@esm/index.mjs';
import numelDimension from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel-dimension@esm/index.mjs';
var gsum = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-gsum' ).ndarray;

function wrapper( arrays ) {
    var x = arrays[ 0 ];
    return gsum( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) );
}

// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
var ybuf = new Float64Array( [ 0.0, 0.0, 0.0 ] );

// Define the array shapes:
var xsh = [ 1, 3, 2, 2 ];
var ysh = [ 1, 3 ];

// Define the array strides:
var sx = [ 12, 4, 2, 1 ];
var sy = [ 3, 1 ];

// Define the index offsets:
var ox = 0;
var oy = 0;

// Create an input ndarray-like object:
var x = {
    'dtype': 'float64',
    'data': xbuf,
    'shape': xsh,
    'strides': sx,
    'offset': ox,
    'order': 'row-major'
};

// Create an output ndarray-like object:
var y = {
    'dtype': 'float64',
    'data': ybuf,
    'shape': ysh,
    'strides': sy,
    'offset': oy,
    'order': 'row-major'
};

// Perform a reduction:
unaryReduceStrided1d( wrapper, [ x, y ], [ 2, 3 ] );

var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );
// returns [ [ 10.0, 26.0, 42.0 ] ]

The function accepts the following arguments:

• fcn: function which will be applied to a one-dimensional subarray and should reduce the subarray to a single scalar value.
• arrays: array-like object containing one input ndarray and one output ndarray, followed by any additional ndarray arguments.
• dims: list of dimensions over which to perform a reduction.
• options: function options which are passed through to fcn (optional).

Each provided ndarray should be an object with the following properties:

• dtype: data type.
• data: data buffer.
• shape: dimensions.
• strides: stride lengths.
• offset: index offset.
• order: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style).

TODO: document factory method

Notes

• The output ndarray and any additional ndarray arguments are expected to have the same dimensions as the non-reduced dimensions of the input ndarray. When calling the reduction function, any additional ndarray arguments are provided as zero-dimensional ndarray-like objects.

• The reduction function is expected to have the following signature:

  fcn( arrays[, options] )
  

  where

  • arrays: array containing a one-dimensional subarray of the input ndarray and any additional ndarray arguments as zero-dimensional ndarrays.
  • options: function options (optional).

• For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing a reduction in order to achieve better performance.

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">

import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@esm/index.mjs';
import zeros from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zeros@esm/index.mjs';
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-to-array@esm/index.mjs';
import numelDimension from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-numel-dimension@esm/index.mjs';
import getData from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-data-buffer@esm/index.mjs';
import getStride from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-stride@esm/index.mjs';
import getOffset from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-offset@esm/index.mjs';
var gsum = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-gsum' ).ndarray;
import unaryReduceStrided1d from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-unary-reduce-strided1d@esm/index.mjs';

function wrapper( arrays ) {
    var x = arrays[ 0 ];
    return gsum( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
}

var N = 10;
var x = {
    'dtype': 'generic',
    'data': discreteUniform( N, -5, 5, {
        'dtype': 'generic'
    }),
    'shape': [ 1, 5, 2 ],
    'strides': [ 10, 2, 1 ],
    'offset': 0,
    'order': 'row-major'
};
var y = {
    'dtype': 'generic',
    'data': zeros( 2 ),
    'shape': [ 1, 2 ],
    'strides': [ 2, 1 ],
    'offset': 0,
    'order': 'row-major'
};

unaryReduceStrided1d( wrapper, [ x, y ], [ 1 ] );

console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );

</script>
</body>
</html>

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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

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