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* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
'use strict';
// MODULES //
var numel = require( '@stdlib/ndarray/base/numel' );
var vind2bind = require( '@stdlib/ndarray/base/vind2bind' );
var copyIndexed = require( '@stdlib/array/base/copy-indexed' );
var zeros = require( '@stdlib/array/base/zeros' );
var setViewOffsets = require( './set_view_offsets.js' );
var offsets = require( './offsets.js' );
// VARIABLES //
var MODE = 'throw';
// MAIN //
/**
* Applies a one-dimensional strided array function to a list of specified dimensions in an ndarray.
*
* @private
* @param {Function} fcn - wrapper for a one-dimensional strided array reduction function
* @param {Array<Object>} arrays - ndarrays
* @param {Array<Object>} views - initialized ndarray-like objects representing sub-array views
* @param {NonNegativeIntegerArray} shape - loop dimensions
* @param {IntegerArray} stridesX - loop dimension strides for the ndarray
* @param {Object} strategyX - strategy for marshaling data to and from an ndarray view
* @param {Options} opts - function options
* @returns {void}
*
* @example
* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
* var getStride = require( '@stdlib/ndarray/base/stride' );
* var getOffset = require( '@stdlib/ndarray/base/offset' );
* var getData = require( '@stdlib/ndarray/base/data-buffer' );
* var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
* var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
* var gsorthp = require( '@stdlib/blas/ext/base/gsorthp' ).ndarray;
*
* function wrapper( arrays ) {
* var x = arrays[ 0 ];
* var o = arrays[ 1 ];
* return gsorthp( numelDimension( x, 0 ), ndarraylike2scalar( o ), getData( x ), getStride( x, 0 ), getOffset( x ) );
* }
*
* // Create data buffers:
* var xbuf = [ 12.0, 11.0, 10.0, 9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ];
*
* // Define the array shapes:
* var xsh = [ 3, 2, 2 ];
*
* // Define the array strides:
* var sx = [ 4, 2, 1 ];
*
* // Define the index offsets:
* var ox = 0;
*
* // Create an ndarray-like object:
* var x = {
* 'dtype': 'generic',
* 'data': xbuf,
* 'shape': xsh,
* 'strides': sx,
* 'offset': ox,
* 'order': 'row-major'
* };
*
* // Create an ndarray-like object for the sort order:
* var sortOrder = {
* 'dtype': 'generic',
* 'data': [ 1.0 ],
* 'shape': [ 1 ],
* 'strides': [ 0 ],
* 'offset': 0,
* 'order': 'row-major'
* };
*
* // Initialize ndarray-like objects representing sub-array views:
* var views = [
* {
* 'dtype': x.dtype,
* 'data': x.data,
* 'shape': [ 2, 2 ],
* 'strides': [ 2, 1 ],
* 'offset': x.offset,
* 'order': x.order
* },
* {
* 'dtype': sortOrder.dtype,
* 'data': sortOrder.data,
* 'shape': [],
* 'strides': [ 0 ],
* 'offset': sortOrder.offset,
* 'order': sortOrder.order
* }
* ];
*
* // Define an input strategy:
* function inputStrategy( x ) {
* return {
* 'dtype': x.dtype,
* 'data': x.data,
* 'shape': [ 4 ],
* 'strides': [ 1 ],
* 'offset': x.offset,
* 'order': x.order
* };
* }
*
* // Define an output strategy:
* function outputStrategy( x ) {
* return x;
* }
*
* var strategy = {
* 'input': inputStrategy,
* 'output': outputStrategy
* }
*
* // Apply strided function:
* nullarynd( wrapper, [ x, sortOrder ], views, [ 3 ], [ 4 ], strategy, {} );
*
* var arr = ndarray2array( x.data, x.shape, x.strides, x.offset, x.order );
* // returns [ [ [ 9.0, 10.0 ], [ 11.0, 12.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ], [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ]
*/
function nullarynd( fcn, arrays, views, shape, stridesX, strategyX, opts ) {
var len;
var arr;
var iv;
var io;
var N;
var v;
var i;
var j;
N = arrays.length;
// Compute the total number of elements over which to iterate:
len = numel( shape );
// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
iv = offsets( arrays );
// Shallow copy the list of views to an internal array so that we can update with reshaped views without impacting the original list of views:
v = copyIndexed( views );
// Iterate based on the linear **view** index, regardless as to how the data is stored in memory...
io = zeros( N );
for ( i = 0; i < len; i++ ) {
for ( j = 0; j < N; j++ ) {
arr = arrays[ j ];
io[ j ] = vind2bind( shape, arr.strides, iv[ j ], arr.order, i, MODE ); // eslint-disable-line max-len
}
setViewOffsets( views, io );
v[ 0 ] = strategyX.input( views[ 0 ] );
fcn( v, opts );
strategyX.output( views[ 0 ] );
}
}
// EXPORTS //
module.exports = nullarynd;
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