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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';
// MAIN //
/**
* Applies a quaternary callback to elements in a one-dimensional input ndarrays and assigns results to elements in an equivalently shaped output ndarray.
*
* @private
* @param {Object} x - object containing input ndarray meta data
* @param {*} x.dtype - data type
* @param {Collection} x.data - data buffer
* @param {NonNegativeIntegerArray} x.shape - dimensions
* @param {IntegerArray} x.strides - stride lengths
* @param {NonNegativeInteger} x.offset - index offset
* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style)
* @param {Object} y - object containing input ndarray meta data
* @param {*} y.dtype - data type
* @param {Collection} y.data - data buffer
* @param {NonNegativeIntegerArray} y.shape - dimensions
* @param {IntegerArray} y.strides - stride lengths
* @param {NonNegativeInteger} y.offset - index offset
* @param {string} y.order - specifies whether `y` is row-major (C-style) or column-major (Fortran-style)
* @param {Object} z - object containing input ndarray meta data
* @param {*} z.dtype - data type
* @param {Collection} z.data - data buffer
* @param {NonNegativeIntegerArray} z.shape - dimensions
* @param {IntegerArray} z.strides - stride lengths
* @param {NonNegativeInteger} z.offset - index offset
* @param {string} z.order - specifies whether `z` is row-major (C-style) or column-major (Fortran-style)
* @param {Object} w - object containing input ndarray meta data
* @param {*} w.dtype - data type
* @param {Collection} w.data - data buffer
* @param {NonNegativeIntegerArray} w.shape - dimensions
* @param {IntegerArray} w.strides - stride lengths
* @param {NonNegativeInteger} w.offset - index offset
* @param {string} w.order - specifies whether `w` is row-major (C-style) or column-major (Fortran-style)
* @param {Object} u - object containing output ndarray meta data
* @param {*} u.dtype - data type
* @param {Collection} u.data - data buffer
* @param {NonNegativeIntegerArray} u.shape - dimensions
* @param {IntegerArray} u.strides - stride lengths
* @param {NonNegativeInteger} u.offset - index offset
* @param {string} u.order - specifies whether `u` is row-major (C-style) or column-major (Fortran-style)
* @param {Callback} fcn - quaternary callback
* @returns {void}
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* function fcn( a, b, c, d ) {
* return a + b + c + d;
* }
*
* // Create data buffers:
* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
* var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );
* var zbuf = new Float64Array( [ 2.0, 2.0, 2.0, 2.0, 2.0 ] );
* var wbuf = new Float64Array( [ 3.0, 3.0, 3.0, 3.0, 3.0 ] );
* var ubuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
*
* // Define the shape of the input and output arrays:
* var shape = [ 5 ];
*
* // Define the array strides:
* var sx = [ 1 ];
* var sy = [ 1 ];
* var sz = [ 1 ];
* var sw = [ 1 ];
* var su = [ 1 ];
*
* // Define the index offsets:
* var ox = 0;
* var oy = 0;
* var oz = 0;
* var ow = 0;
* var ou = 0;
*
* // Create the input and output ndarray-like objects:
* var x = {
* 'dtype': 'float64',
* 'data': xbuf,
* 'shape': shape,
* 'strides': sx,
* 'offset': ox,
* 'order': 'row-major'
* };
* var y = {
* 'dtype': 'float64',
* 'data': ybuf,
* 'shape': shape,
* 'strides': sy,
* 'offset': oy,
* 'order': 'row-major'
* };
* var z = {
* 'dtype': 'float64',
* 'data': zbuf,
* 'shape': shape,
* 'strides': sz,
* 'offset': oz,
* 'order': 'row-major'
* };
* var w = {
* 'dtype': 'float64',
* 'data': wbuf,
* 'shape': shape,
* 'strides': sw,
* 'offset': ow,
* 'order': 'row-major'
* };
* var u = {
* 'dtype': 'float64',
* 'data': ubuf,
* 'shape': shape,
* 'strides': su,
* 'offset': ou,
* 'order': 'row-major'
* };
*
* // Apply the quaternary function:
* quaternary1d( x, y, z, w, u, fcn );
*
* console.log( u.data );
* // => <Float64Array>[ 7.0, 8.0, 9.0, 10.0, 11.0 ]
*/
function quaternary1d( x, y, z, w, u, fcn ) {
var xbuf;
var ybuf;
var zbuf;
var wbuf;
var ubuf;
var dx;
var dy;
var dz;
var dw;
var du;
var S0;
var ix;
var iy;
var iz;
var iw;
var iu;
var i;
// Note on variable naming convention: S#, where # corresponds to the loop number, with `0` being the innermost loop...
// Extract loop variables: dimensions and loop offset (pointer) increments...
S0 = x.shape[ 0 ];
dx = x.strides[ 0 ];
dy = y.strides[ 0 ];
dz = z.strides[ 0 ];
dw = w.strides[ 0 ];
du = u.strides[ 0 ];
// Set the pointers to the first indexed elements in the respective ndarrays...
ix = x.offset;
iy = y.offset;
iz = z.offset;
iw = w.offset;
iu = u.offset;
// Cache references to the input and output ndarray buffers...
xbuf = x.data;
ybuf = y.data;
zbuf = z.data;
wbuf = w.data;
ubuf = u.data;
// Iterate over the ndarray dimensions...
for ( i = 0; i < S0; i++ ) {
ubuf[ iu ] = fcn( xbuf[ ix ], ybuf[ iy ], zbuf[ iz ], wbuf[ iw ] );
ix += dx;
iy += dy;
iz += dz;
iw += dw;
iu += du;
}
}
// EXPORTS //
module.exports = quaternary1d;
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