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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 dwapx = require( '@stdlib/blas/ext/base/dwapx' ).ndarray;
var dwax = require( '@stdlib/blas/ext/base/dwax' ).ndarray;
// VARIABLES //
var M = 5;
// MAIN //
/**
* Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and adds a scalar constant before assigning the results to elements in a double-precision floating-point strided array `w` using alternative indexing semantics.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {number} alpha - first scalar constant
* @param {number} beta - second scalar constant
* @param {Float64Array} x - input array
* @param {integer} strideX - `x` stride length
* @param {NonNegativeInteger} offsetX - starting `x` index
* @param {Float64Array} w - output array
* @param {integer} strideW - `w` stride length
* @param {NonNegativeInteger} offsetW - starting `w` index
* @returns {Float64Array} output array
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
*
* dwaxpb( x.length, 5.0, 3.0, x, 1, 0, w, 1, 0 );
* // w => <Float64Array>[ 8.0, 13.0, 18.0, 23.0, 28.0 ]
*/
function dwaxpb( N, alpha, beta, x, strideX, offsetX, w, strideW, offsetW ) {
var ix;
var iw;
var m;
var i;
if ( N <= 0 ) {
return w;
}
// Fast path: when alpha = 1.0, delegate to dwapx (w = x + beta)
if ( alpha === 1.0 ) {
return dwapx( N, beta, x, strideX, offsetX, w, strideW, offsetW );
}
// Fast path: when beta = 0.0, delegate to dwax (w = alpha * x)
if ( beta === 0.0 ) {
return dwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW );
}
ix = offsetX;
iw = offsetW;
// Use loop unrolling if both strides are equal to `1`...
if ( strideX === 1 && strideW === 1 ) {
m = N % M;
// If we have a remainder, run a clean-up loop...
if ( m > 0 ) {
for ( i = 0; i < m; i++ ) {
w[ iw ] = ( alpha * x[ ix ] ) + beta;
ix += strideX;
iw += strideW;
}
}
if ( N < M ) {
return w;
}
for ( i = m; i < N; i += M ) {
w[ iw ] = ( alpha * x[ ix ] ) + beta;
w[ iw+1 ] = ( alpha * x[ ix+1 ] ) + beta;
w[ iw+2 ] = ( alpha * x[ ix+2 ] ) + beta;
w[ iw+3 ] = ( alpha * x[ ix+3 ] ) + beta;
w[ iw+4 ] = ( alpha * x[ ix+4 ] ) + beta;
ix += M;
iw += M;
}
return w;
}
for ( i = 0; i < N; i++ ) {
w[ iw ] = ( alpha * x[ ix ] ) + beta;
ix += strideX;
iw += strideW;
}
return w;
}
// EXPORTS //
module.exports = dwaxpb;
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