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* @license Apache-2.0
*
* Copyright (c) 2026 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.
*/
/* eslint-disable max-len, max-params */
'use strict';
// MODULES //
var wrap = require( './callback_wrapper.js' );
// MAIN //
/**
* Applies a one-dimensional strided array function to an input ndarray according to a callback function.
*
* ## Notes
*
* - The `views`, `shape`, and `stridesX` parameters are unused. Providing empty arrays for these parameters is recommended in order to ensure a monomorphic API.
*
* @private
* @param {Function} fcn - wrapper for a one-dimensional strided array function
* @param {Array<Object>} arrays - ndarray descriptors
* @param {ndarrayLike} ref - original input ndarray provided to a callback function
* @param {Array<Object>} views - initialized ndarray descriptors representing subarray views
* @param {Array<integer>} shape - loop dimensions
* @param {Array<integer>} stridesX - loop dimension strides for the input ndarray
* @param {Object} strategyX - strategy for marshaling data to and from an input ndarray view
* @param {NonNegativeIntegerArray} ibuf - workspace for storing iteration indices
* @param {NonNegativeIntegerArray} ldims - list of loop dimensions
* @param {NonNegativeIntegerArray} cdims - list of "core" dimensions
* @param {Options} opts - function options
* @param {boolean} hasOpts - boolean indicating whether to pass an options argument to a strided array function
* @param {Function} clbk - callback function
* @param {*} thisArg - callback execution context
* @returns {void}
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
* var zeros = require( '@stdlib/array/base/zeros' );
* var gfillBy = require( '@stdlib/blas/ext/base/ndarray/gfill-by' );
* var strategy = require( '@stdlib/ndarray/base/kernels/generic/unary-strided1d/strategy' );
*
* function clbk( value, idx ) {
* return ( idx[ 0 ]*10 ) + idx[ 1 ];
* }
*
* // Create a data buffer:
* var xbuf = new Float64Array( 4 );
*
* // Define the array shape:
* var xsh = [ 2, 2 ];
*
* // Define the array strides:
* var sx = [ 2, 1 ];
*
* // Define the index offset:
* var ox = 0;
*
* // Create an input ndarray descriptor:
* var x = {
* 'dtype': 'float64',
* 'data': xbuf,
* 'shape': xsh,
* 'strides': sx,
* 'offset': ox,
* 'order': 'row-major'
* };
*
* // Create an ndarray descriptor for the starting index (inclusive):
* var start = {
* 'dtype': 'float64',
* 'data': new Float64Array( [ 0.0 ] ),
* 'shape': [],
* 'strides': [ 0 ],
* 'offset': 0,
* 'order': 'row-major'
* };
*
* // Create an ndarray descriptor for the ending index (exclusive):
* var end = {
* 'dtype': 'float64',
* 'data': new Float64Array( [ 4.0 ] ),
* 'shape': [],
* 'strides': [ 0 ],
* 'offset': 0,
* 'order': 'row-major'
* };
*
* // Resolve an input strategy for the input ndarray:
* var strategyX = strategy( x );
*
* // Create a workspace array for storing iteration indices:
* var ibuf = zeros( xsh.length );
*
* // Define the loop and core dimensions:
* var ldims = [];
* var cdims = [ 0, 1 ];
*
* // Apply strided function:
* kernel( gfillBy, [ x, start, end ], x, [], [], [], strategyX, ibuf, ldims, cdims, {}, false, clbk, {} );
*
* var arr = ndarray2array( x.data, x.shape, x.strides, x.offset, x.order );
* // returns [ [ 0.0, 1.0 ], [ 10.0, 11.0 ] ]
*/
function kernel( fcn, arrays, ref, views, shape, stridesX, strategyX, ibuf, ldims, cdims, opts, hasOpts, clbk, thisArg ) {
var f;
f = wrap( ref, arrays[ 0 ], ibuf, ldims, [], cdims, clbk, thisArg );
arrays[ 0 ] = strategyX.input( arrays[ 0 ] );
if ( hasOpts ) {
fcn( arrays, opts, f );
} else {
fcn( arrays, f );
}
strategyX.output( arrays[ 0 ] );
}
// EXPORTS //
module.exports = kernel;
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