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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 loopOrder = require( '@stdlib/ndarray/base/unary-loop-interchange-order' );
var blockSize = require( '@stdlib/ndarray/base/unary-tiling-block-size' );
var takeIndexed = require( '@stdlib/array/base/take-indexed' );
var zeros = require( '@stdlib/array/base/zeros' );
var incrementOffsets = require( './increment_offsets.js' );
var setViewOffsets = require( './set_view_offsets.js' );
var offsets = require( './offsets.js' );
// MAIN //
/**
* Performs a reduction over an input ndarray and assigns results to a provided output ndarray via loop blocking.
*
* @private
* @param {Function} fcn - reduction function
* @param {Array<Object>} arrays - ndarrays
* @param {Array<Object>} views - initialized ndarray-like objects representing sub-array views
* @param {IntegerArray} strides - loop dimension strides for the input ndarray
* @param {Options} opts - function options
* @returns {void}
*
* @example
* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
* var accessors = require( '@stdlib/array/base/accessors' );
* var Float64Array = require( '@stdlib/array/float64' );
* var filled = require( '@stdlib/array/base/filled' );
* var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
* var base = require( '@stdlib/ndarray/base/every' );
*
* // Create data buffers:
* var xbuf = toAccessorArray( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ) );
* var ybuf = toAccessorArray( filled( false, 3 ) );
*
* // Define the array shapes:
* var xsh = [ 1, 3, 2, 2 ];
* var ysh = [ 1, 3 ];
*
* // Define the array strides:
* var sx = [ 12, 4, 2, 1 ];
* var sy = [ 3, 1 ];
*
* // Define the index offsets:
* var ox = 0;
* var oy = 0;
*
* // Create an input ndarray-like object:
* var x = {
* 'dtype': 'float64',
* 'data': xbuf,
* 'shape': xsh,
* 'strides': sx,
* 'offset': ox,
* 'order': 'row-major',
* 'accessors': accessors( xbuf ).accessors
* };
*
* // Create an output ndarray-like object:
* var y = {
* 'dtype': 'generic',
* 'data': ybuf,
* 'shape': ysh,
* 'strides': sy,
* 'offset': oy,
* 'order': 'row-major',
* 'accessors': accessors( ybuf ).accessors
* };
*
* // 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
* }
* ];
*
* // Perform a reduction:
* blockedunary2d( base, [ x, y ], views, [ 12, 4 ], {} );
*
* var arr = ndarray2array( y.data, y.shape, y.strides, y.offset, y.order );
* // returns [ [ true, false, true ] ]
*/
function blockedunary2d( fcn, arrays, views, strides, opts ) {
var bsize;
var ybuf;
var set;
var dv0;
var dv1;
var ov1;
var sh;
var s0;
var s1;
var sv;
var ov;
var iv;
var i0;
var i1;
var j0;
var j1;
var N;
var x;
var y;
var o;
var k;
// Note on variable naming convention: S#, dv#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop...
N = arrays.length;
x = arrays[ 0 ];
y = arrays[ 1 ];
// Resolve the loop interchange order:
o = loopOrder( y.shape, strides, y.strides );
sh = o.sh;
sv = [ o.sx, o.sy ];
for ( k = 2; k < N; k++ ) {
sv.push( takeIndexed( arrays[k].strides, o.idx ) );
}
// Determine the block size:
bsize = blockSize( x.dtype, y.dtype );
// Resolve a list of pointers to the first indexed elements in the respective ndarrays:
ov = offsets( arrays );
// Cache a reference to the output ndarray buffer:
ybuf = y.data;
// Cache accessors:
set = y.accessors[1];
// Cache offset increments for the innermost loop...
dv0 = [];
for ( k = 0; k < N; k++ ) {
dv0.push( sv[k][0] );
}
// Initialize loop variables...
ov1 = zeros( N );
dv1 = zeros( N );
iv = zeros( N );
// Iterate over blocks...
for ( j1 = sh[1]; j1 > 0; ) {
if ( j1 < bsize ) {
s1 = j1;
j1 = 0;
} else {
s1 = bsize;
j1 -= bsize;
}
for ( k = 0; k < N; k++ ) {
ov1[ k ] = ov[k] + ( j1*sv[k][1] );
}
for ( j0 = sh[0]; j0 > 0; ) {
if ( j0 < bsize ) {
s0 = j0;
j0 = 0;
} else {
s0 = bsize;
j0 -= bsize;
}
// Compute index offsets and loop offset increments for the first ndarray elements in the current block...
for ( k = 0; k < N; k++ ) {
iv[ k ] = ov1[k] + ( j0*sv[k][0] );
dv1[ k ] = sv[k][1] - ( s0*sv[k][0] );
}
// Iterate over the non-reduced ndarray dimensions...
for ( i1 = 0; i1 < s1; i1++ ) {
for ( i0 = 0; i0 < s0; i0++ ) {
setViewOffsets( views, iv );
set( ybuf, iv[1], fcn( views, opts ) );
incrementOffsets( iv, dv0 );
}
incrementOffsets( iv, dv1 );
}
}
}
}
// EXPORTS //
module.exports = blockedunary2d;
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