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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 broadcastArrayExceptDimensions = require( '@stdlib/ndarray/base/broadcast-array-except-dimensions' );
var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' );
var isInteger = require( '@stdlib/assert/is-integer' );
var indicesComplement = require( '@stdlib/array/base/indices-complement' );
var nditerStacks = require( '@stdlib/ndarray/iter/stacks' );
var getShape = require( '@stdlib/ndarray/shape' );
var getStrides = require( '@stdlib/ndarray/strides' );
var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
var getDtype = require( '@stdlib/ndarray/dtype' );
var getOrder = require( '@stdlib/ndarray/order' );
var getData = require( '@stdlib/ndarray/data-buffer' );
var ndarray = require( '@stdlib/ndarray/ctor' );
var format = require( '@stdlib/string/format' );
var base = require( '@stdlib/ndarray/base/assign' );
var output = require( './output.js' );
// MAIN //
/**
* Concatenates a list of ndarrays along a specified ndarray dimension and assigns results to a provided output ndarray.
*
* @param {ArrayLikeObject<ndarray>} arrays - array-like object containing input ndarrays
* @param {ndarray} out - output ndarray
* @param {NegativeInteger} dim - dimension along which the ndarrays are concatenated
* @throws {TypeError} first argument must be an array of ndarray-like objects
* @throws {RangeError} first argument must have more than one ndarray
* @throws {TypeError} second argument must be an array of ndarray-like objects
* @returns {ndarray} output ndarray
*
* @example
* var ndarray = require( '@stdlib/ndarray/ctor' );
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray2array = require( '@stdlib/ndarray/to-array' );
*
* var xbuf = new Float64Array( [ -1.0, 2.0, -3.0, 4.0 ] );
* var x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
*
* var ybuf = new Float64Array( [ -5.0, 6.0, -7.0, 8.0, -9.0, 10.0 ] );
* var y = new ndarray( 'float64', ybuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
*
* var z = new ndarray( 'float64', new Float64Array( 10 ), [ 2, 5 ], [ 5, 1 ], 0, 'row-major' );
*
* var out = assign( [ x, y ], z, -1 );
* // returns <ndarray>
*
* var bool = ( out === z );
* // returns true
*
* var arr = ndarray2array( z );
* // returns [ [ -1.0, 2.0, -5.0, 6.0, -7.0 ], [ -3.0, 4.0, 8.0, -9.0, 10.0 ] ]
*/
function assign( arrays, out, dim ) {
var istacks;
var ostacks;
var strides;
var shapes;
var dtypes;
var orders;
var odata;
var oord;
var arrs;
var err;
var osh;
var odt;
var mi;
var N;
var d;
var s;
var i;
var v;
if ( arguments.length > 1 ) {
if ( !isInteger( dim ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a negative integer. Value: `%s`.', dim ) );
}
if ( isNonNegativeInteger( dim ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a negative integer. Value: `%s`.', dim ) );
}
}
N = arrays.length;
arrs = [];
if ( N < 1 ) {
throw new RangeError( format( 'invalid argument. First argument must have one or more ndarrays. Value: `%s`.', N ) );
}
if ( !isndarrayLike( out ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be an ndarray-like object. Value: `%s`.', out ) );
}
// Unpack the ndarrays and standardize ndarray meta data:
shapes = [];
strides = [];
dtypes = [];
orders = [];
for ( i = 0; i < N; i++ ) {
if ( !isndarrayLike( arrays[ i ] ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an array of ndarray-like objects. Value: `%s`.', arrays[ i ] ) );
}
arrs[ i ] = arrays[ i ];
shapes.push( getShape( arrs[ i ] ) );
strides.push( getStrides( arrs[ i ] ) );
dtypes.push( getDtype( arrs[ i ] ) );
orders.push( getOrder( arrs[ i ] ) );
}
// Determine the ndarray with max-rank:
mi = 0;
for ( i = 1; i < N; i++ ) {
if ( shapes[ i ].length > shapes[ mi ].length ) {
mi = i;
}
}
// Broadcast all ndarrays to shape of max-rank ndarray:
for ( i = 0; i < N; i++ ) {
if ( i === mi ) {
continue;
}
arrs[ i ] = broadcastArrayExceptDimensions( arrs[ i ], shapes[ mi ], [ dim ] ); // eslint-disable-line max-len
shapes[ i ] = getShape( arrs[ i ] );
}
// Normalize dimension index:
d = normalizeIndex( dim, shapes[ mi ].length - 1 );
// Validate the output ndarray:
err = output( shapes, dtypes, orders, d, out );
if ( err ) {
throw err;
}
osh = getShape( out );
if ( osh.length === 1 ) {
odt = getDtype( out );
odata = getData( out );
oord = getOrder( out );
for ( i = 0; i < arrs.length; i++ ) {
v = ndarray( odt, odata, arrs[ i ].shape, shape2strides( arrs[ i ].shape, oord ), 0, oord ); // eslint-disable-line max-len
base( [ arrs[ i ], v ] );
}
return out;
}
// Create iterator for output subarrays:
ostacks = nditerStacks( out, indicesComplement( osh.length, [ d ] ) );
// Assign each input subarray to relevant output subarray:
for ( i = 0; i < arrs.length; i++ ) {
istacks = nditerStacks( arrs[ i ], indicesComplement( arrs[ i ].shape.length, [ d ] ) ); // eslint-disable-line max-len
while ( true ) {
s = istacks.next();
if ( s.done ) {
break;
}
base( [ s.value, ostacks.next().value ] );
}
}
return out;
}
// EXPORTS //
module.exports = assign;
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