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* @license Apache-2.0
*
* Copyright (c) 2021 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 unary callback to elements in a four-dimensional input ndarray and assigns results to elements in an equivalently shaped output ndarray.
*
* @private
* @param {Object} x - object containing input ndarray meta data
* @param {string} 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 {Array<Function>} x.accessors - data buffer accessors
* @param {Object} y - object containing output ndarray meta data
* @param {string} 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 {Array<Function>} y.accessors - data buffer accessors
* @param {Callback} fcn - unary callback
* @returns {void}
*
* @example
* var Complex64Array = require( '@stdlib/array/complex64' );
* var Complex64 = require( '@stdlib/complex/float32/ctor' );
* var realf = require( '@stdlib/complex/float32/real' );
* var imagf = require( '@stdlib/complex/float32/imag' );
*
* function scale( z ) {
* return new Complex64( realf(z)*10.0, imagf(z)*10.0 );
* }
*
* // Create data buffers:
* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
* var ybuf = new Complex64Array( 4 );
*
* // Define the shape of the input and output arrays:
* var shape = [ 1, 1, 2, 2 ];
*
* // Define the array strides:
* var sx = [ 4, 4, 2, 1 ];
* var sy = [ 4, 4, 2, 1 ];
*
* // Define the index offsets:
* var ox = 0;
* var oy = 0;
*
* // Define getters and setters:
* function getter( buf, idx ) {
* return buf.get( idx );
* }
*
* function setter( buf, idx, value ) {
* buf.set( value, idx );
* }
*
* // Create the input and output ndarray-like objects:
* var x = {
* 'dtype': 'complex64',
* 'data': xbuf,
* 'shape': shape,
* 'strides': sx,
* 'offset': ox,
* 'order': 'row-major',
* 'accessors': [ getter, setter ]
* };
* var y = {
* 'dtype': 'complex64',
* 'data': ybuf,
* 'shape': shape,
* 'strides': sy,
* 'offset': oy,
* 'order': 'row-major',
* 'accessors': [ getter, setter ]
* };
*
* // Apply the unary function:
* unary4d( x, y, scale );
*
* var v = y.data.get( 0 );
*
* var re = realf( v );
* // returns 10.0
*
* var im = imagf( v );
* // returns 20.0
*/
function unary4d( x, y, fcn ) {
var xbuf;
var ybuf;
var get;
var set;
var dx0;
var dx1;
var dx2;
var dx3;
var dy0;
var dy1;
var dy2;
var dy3;
var sh;
var S0;
var S1;
var S2;
var S3;
var sx;
var sy;
var ix;
var iy;
var i0;
var i1;
var i2;
var i3;
// Note on variable naming convention: S#, dx#, dy#, i# where # corresponds to the loop number, with `0` being the innermost loop...
// Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments...
sh = x.shape;
sx = x.strides;
sy = y.strides;
if ( x.order === 'row-major' ) {
// For row-major ndarrays, the last dimensions have the fastest changing indices...
S0 = sh[ 3 ];
S1 = sh[ 2 ];
S2 = sh[ 1 ];
S3 = sh[ 0 ];
dx0 = sx[ 3 ]; // offset increment for innermost loop
dx1 = sx[ 2 ] - ( S0*sx[3] );
dx2 = sx[ 1 ] - ( S1*sx[2] );
dx3 = sx[ 0 ] - ( S2*sx[1] ); // offset increment for outermost loop
dy0 = sy[ 3 ];
dy1 = sy[ 2 ] - ( S0*sy[3] );
dy2 = sy[ 1 ] - ( S1*sy[2] );
dy3 = sy[ 0 ] - ( S2*sy[1] );
} else { // order === 'column-major'
// For column-major ndarrays, the first dimensions have the fastest changing indices...
S0 = sh[ 0 ];
S1 = sh[ 1 ];
S2 = sh[ 2 ];
S3 = sh[ 3 ];
dx0 = sx[ 0 ]; // offset increment for innermost loop
dx1 = sx[ 1 ] - ( S0*sx[0] );
dx2 = sx[ 2 ] - ( S1*sx[1] );
dx3 = sx[ 3 ] - ( S2*sx[2] ); // offset increment for outermost loop
dy0 = sy[ 0 ];
dy1 = sy[ 1 ] - ( S0*sy[0] );
dy2 = sy[ 2 ] - ( S1*sy[1] );
dy3 = sy[ 3 ] - ( S2*sy[2] );
}
// Set the pointers to the first indexed elements in the respective ndarrays...
ix = x.offset;
iy = y.offset;
// Cache references to the input and output ndarray buffers...
xbuf = x.data;
ybuf = y.data;
// Cache accessors:
get = x.accessors[ 0 ];
set = y.accessors[ 1 ];
// Iterate over the ndarray dimensions...
for ( i3 = 0; i3 < S3; i3++ ) {
for ( i2 = 0; i2 < S2; i2++ ) {
for ( i1 = 0; i1 < S1; i1++ ) {
for ( i0 = 0; i0 < S0; i0++ ) {
set( ybuf, iy, fcn( get( xbuf, ix ) ) );
ix += dx0;
iy += dy0;
}
ix += dx1;
iy += dy1;
}
ix += dx2;
iy += dy2;
}
ix += dx3;
iy += dy3;
}
}
// EXPORTS //
module.exports = unary4d;
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