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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 daxpy = require( '@stdlib/blas/base/daxpy' ).ndarray;
var dscal = require( '@stdlib/blas/base/dscal' ).ndarray;
// VARIABLES //
var M = 5;
// MAIN //
/**
* Multiplies a double-precision floating-point strided array `x` by a constant and adds the result to a double-precision floating-point strided array `y` multiplied by a constant.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {number} alpha - first scalar constant
* @param {Float64Array} x - input array
* @param {integer} strideX - `x` stride length
* @param {NonNegativeInteger} offsetX - starting `x` index
* @param {number} beta - second scalar constant
* @param {Float64Array} y - output array
* @param {integer} strideY - `y` stride length
* @param {NonNegativeInteger} offsetY - starting `y` 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 y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] );
*
* daxpby( x.length, 5.0, x, 1, 0, 2.0, y, 1, 0 );
* // y => <Float64Array>[ 9.0, 16.0, 23.0, 30.0, 37.0 ]
*/
function daxpby( N, alpha, x, strideX, offsetX, beta, y, strideY, offsetY ) {
var ix;
var iy;
var m;
var i;
if ( N <= 0 ) {
return y;
}
// Fast path: when alpha = 0.0, delegate to dscal (y = beta * y)
if ( alpha === 0.0 ) {
return dscal( N, beta, y, strideY, offsetY );
}
// Fast path: when beta = 1.0, delegate to daxpy (y = alpha * x + y)
if ( beta === 1.0 ) {
return daxpy( N, alpha, x, strideX, offsetX, y, strideY, offsetY );
}
ix = offsetX;
iy = offsetY;
// Use loop unrolling if both strides are equal to `1`...
if ( strideX === 1 && strideY === 1 ) {
m = N % M;
// If we have a remainder, run a clean-up loop...
if ( m > 0 ) {
for ( i = 0; i < m; i++ ) {
y[ iy ] = ( alpha * x[ ix ] ) + ( beta * y[ iy ] );
ix += strideX;
iy += strideY;
}
}
if ( N < M ) {
return y;
}
for ( i = m; i < N; i += M ) {
y[ iy ] = ( alpha * x[ ix ] ) + ( beta * y[ iy ] );
y[ iy+1 ] = ( alpha * x[ ix+1 ] ) + ( beta * y[ iy+1 ] );
y[ iy+2 ] = ( alpha * x[ ix+2 ] ) + ( beta * y[ iy+2 ] );
y[ iy+3 ] = ( alpha * x[ ix+3 ] ) + ( beta * y[ iy+3 ] );
y[ iy+4 ] = ( alpha * x[ ix+4 ] ) + ( beta * y[ iy+4 ] );
ix += M;
iy += M;
}
return y;
}
for ( i = 0; i < N; i++ ) {
y[ iy ] = ( alpha * x[ ix ] ) + ( beta * y[ iy ] );
ix += strideX;
iy += strideY;
}
return y;
}
// EXPORTS //
module.exports = daxpby;
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