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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 hasEqualValuesIndexed = require( '@stdlib/array/base/assert/has-equal-values-indexed' );
var isMostlySafeCast = require( '@stdlib/ndarray/base/assert/is-mostly-safe-data-type-cast' );
var isNegativeInteger = require( '@stdlib/assert/is-negative-integer' ).isPrimitive;
var isArrayLikeObject = require( '@stdlib/assert/is-array-like-object' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var promoteDataTypes = require( '@stdlib/ndarray/base/promote-dtypes' );
var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' );
var ndarraylike2ndarray = require( '@stdlib/ndarray/base/ndarraylike2ndarray' );
var getShape = require( '@stdlib/ndarray/base/shape' );
var getDType = require( '@stdlib/ndarray/base/dtype' );
var ndims = require( '@stdlib/ndarray/base/ndims' );
var join = require( '@stdlib/array/base/join' );
var format = require( '@stdlib/string/format' );
var normalizeArrays = require( './normalize_arrays.js' );
var broadcastArrays = require( './broadcast_arrays.js' );
var resolveDataTypes = require( './resolve_dtypes.js' );
var resolveShape = require( './resolve_shape.js' );
var base = require( './base.js' );
// MAIN //
/**
* Concatenates a list of ndarrays along a specified ndarray dimension and assigns results to a provided output ndarray.
*
* @param {ArrayLikeObject<ndarrayLike>} arrays - array-like object containing input ndarrays
* @param {ndarrayLike} out - output ndarray
* @param {NegativeInteger} [dim] - dimension along which to concatenate input ndarrays
* @throws {TypeError} first argument must be an array of ndarray-like objects
* @throws {RangeError} first argument must contain one or more ndarrays
* @throws {TypeError} second argument must be an ndarray-like object
* @throws {TypeError} third argument must be a negative integer
* @throws {Error} must provide ndarrays which can be safely cast to a common data type
* @returns {ndarrayLike} output ndarray
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
*
* 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>[ [ -1.0, 2.0, -5.0, 6.0, -7.0 ], [ -3.0, 4.0, 8.0, -9.0, 10.0 ] ]
*
* var bool = ( out === z );
* // returns true
*/
function assign( arrays, out, dim ) {
var arrs;
var view;
var osh;
var sh;
var dt;
var d;
if ( !isArrayLikeObject( arrays ) || arrays.length < 1 ) {
throw new TypeError( format( 'invalid argument. First argument must be an array of ndarrays. Value: `%s`.', arrays ) );
}
if ( !isndarrayLike( out ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be an ndarray. Value: `%s`.', out ) );
}
if ( arguments.length > 2 ) {
if ( !isNegativeInteger( dim ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a negative integer. Value: `%s`.', dim ) );
}
} else {
dim = -1;
}
// Normalize the list of input ndarrays:
arrs = normalizeArrays( arrays );
// Normalize the output ndarray:
view = ndarraylike2ndarray( out );
// Broadcast the input ndarrays to a common shape:
arrs = broadcastArrays( arrs, dim );
// Apply type promotion rules to the data types of the input ndarrays:
dt = promoteDataTypes( resolveDataTypes( arrs ) );
if ( dt === null ) {
throw new Error( format( 'invalid argument. Unable to apply type promotion rules when resolving a data type to which the input ndarrays can be safely cast. Data types: [%s].', join( resolveDataTypes( arrs ), ', ' ) ) );
}
// Verify that the data types of the input ndarrays can be safely cast to the data type of the output ndarray:
if ( !isMostlySafeCast( dt, getDType( view ) ) ) {
throw new Error( format( 'invalid argument. The list of input ndarrays cannot be safely cast to the data of the output ndarray. Input data types: [%s]. Output data type: %s.', join( resolveDataTypes( arrs ), ', ' ), getDType( view ) ) );
}
// Normalize the dimension index:
d = normalizeIndex( dim, ndims( arrs[ 0 ] )-1 );
// Resolve the expected shape of the output ndarray:
sh = resolveShape( arrs, d );
// Resolve the actual shape of the output ndarray:
osh = getShape( view, false );
// Verify that the expected and actual shapes are equal:
if ( !hasEqualValuesIndexed( osh, sh ) ) {
throw new TypeError( format( 'invalid argument. Second argument is not broadcast compatible with the list of input ndarrays. Array shape: (%s). Desired shape: (%s).', join( osh, ', ' ), join( sh, ', ' ) ) );
}
// Perform concatenation:
base( arrs, d, view );
return out;
}
// EXPORTS //
module.exports = assign;
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