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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.
*/
'use strict';
// MODULES //
var kernel0d = require( './0d.js' );
var kernel1d = require( './1d.js' );
var kernel2d = require( './2d.js' );
var kernel3d = require( './3d.js' );
var kernel4d = require( './4d.js' );
var kernel5d = require( './5d.js' );
var kernel6d = require( './6d.js' );
var kernel7d = require( './7d.js' );
var kernel8d = require( './8d.js' );
var kernel9d = require( './9d.js' );
var kernel10d = require( './10d.js' );
// VARIABLES //
var KERNELS = [
kernel0d,
kernel1d,
kernel2d,
kernel3d,
kernel4d,
kernel5d,
kernel6d,
kernel7d,
kernel8d,
kernel9d,
kernel10d
];
var MAX_DIMS = KERNELS.length - 1;
// MAIN //
/**
* Returns a kernel for applying a one-dimensional strided array function to an input ndarray and assigning results to an output ndarray.
*
* @param {integer} ndims - number of loop dimensions
* @returns {(Function|null)} kernel function or null
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
* var gcusum = require( '@stdlib/blas/ext/base/ndarray/gcusum' );
*
* // 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
*
* // Define the array shapes:
* var xsh = [ 1, 3, 2, 2 ];
* var ysh = [ 1, 3, 2, 2 ];
*
* // Define the array strides:
* var sx = [ 12, 4, 2, 1 ];
* var sy = [ 12, 4, 2, 1 ];
*
* // Define the index offsets:
* var ox = 0;
* var oy = 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 initial sum:
* var initial = {
* 'dtype': 'float64',
* 'data': new Float64Array( [ 0.0 ] ),
* 'shape': [ 1, 3 ],
* 'strides': [ 0, 0 ],
* 'offset': 0,
* 'order': 'row-major'
* };
*
* // Create an output ndarray descriptor:
* var y = {
* 'dtype': 'float64',
* 'data': ybuf,
* 'shape': ysh,
* 'strides': sy,
* 'offset': oy,
* 'order': 'row-major'
* };
*
* // Initialize ndarray descriptors representing subarray views:
* var views = [
* {
* 'dtype': x.dtype,
* 'data': x.data,
* 'shape': [ 2, 2 ],
* 'strides': [ 2, 1 ],
* 'offset': x.offset,
* 'order': x.order
* },
* {
* 'dtype': y.dtype,
* 'data': y.data,
* 'shape': [ 2, 2 ],
* 'strides': [ 2, 1 ],
* 'offset': y.offset,
* 'order': y.order
* },
* {
* 'dtype': initial.dtype,
* 'data': initial.data,
* 'shape': [],
* 'strides': [ 0 ],
* 'offset': initial.offset,
* 'order': initial.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
* };
*
* // Resolve a kernel:
* var kernel = resolveKernel( 2 );
*
* // Apply strided function:
* kernel( gcusum, [ x, y, initial ], views, [ 1, 3 ], [ 12, 4 ], [ 12, 4 ], strategy, strategy, {} );
*
* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );
* // returns [ [ [ [ 1.0, 3.0 ], [ 6.0, 10.0 ] ], [ [ 5.0, 11.0 ], [ 18.0, 26.0 ] ], [ [ 9.0, 19.0 ], [ 30.0, 42.0 ] ] ] ]
*/
function resolveKernel( ndims ) {
if ( ndims < 0 || ndims > MAX_DIMS ) {
return null;
}
return KERNELS[ ndims ];
}
// EXPORTS //
module.exports = resolveKernel;
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