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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';
 
// MODULES //
 
var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
var getStride = require( '@stdlib/ndarray/base/stride' );
var getOffset = require( '@stdlib/ndarray/base/offset' );
var getData = require( '@stdlib/ndarray/base/data-buffer' );
var strided = require( '@stdlib/blas/ext/base/dwaxpb' ).ndarray;
var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
 
 
// MAIN //
 
/**
* Multiplies each element in an input one-dimensional double-precision floating-point ndarray by a scalar constant and adds a scalar constant before assigning the results to elements in a one-dimensional double-precision floating-point output ndarray.
*
* ## Notes
*
* -   The function expects the following ndarrays:
*
*     -   a one-dimensional input ndarray.
*     -   a one-dimensional output ndarray.
*     -   a zero-dimensional ndarray containing the scalar constant to multiply.
*     -   a zero-dimensional ndarray containing the scalar constant to add.
*
* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
* @returns {ndarray} output ndarray
*
* @example
* var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = new Float64Vector( [ -2.0, 1.0, 3.0, -5.0 ] );
* var w = new Float64Vector( [ 0.0, 0.0, 0.0, 0.0 ] );
*
* var alpha = scalar2ndarray( 5.0, {
*     'dtype': 'float64'
* });
*
* var beta = scalar2ndarray( 3.0, {
*     'dtype': 'float64'
* });
*
* var out = dwaxpb( [ x, w, alpha, beta ] );
* // returns <ndarray>[ -7.0, 8.0, 18.0, -22.0 ]
*
* var bool = ( out === w );
* // returns true
*/
function dwaxpb( arrays ) {
	var alpha;
	var beta;
	var x;
	var w;
 
	x = arrays[ 0 ];
	w = arrays[ 1 ];
	alpha = ndarraylike2scalar( arrays[ 2 ] );
	beta = ndarraylike2scalar( arrays[ 3 ] );
	strided( numelDimension( x, 0 ), alpha, beta, getData( x ), getStride( x, 0 ), getOffset( x ), getData( w ), getStride( w, 0 ), getOffset( w ) ); // eslint-disable-line max-len
	return w;
}
 
 
// EXPORTS //
 
module.exports = dwaxpb;