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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 ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
var strided = require( '@stdlib/blas/base/gger' ).ndarray;
// MAIN //
/**
* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` is an `M` element ndarray, `y` is an `N` element ndarray, and `A` is an `M` by `N` matrix.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - first one-dimensional input ndarray.
* - second one-dimensional input ndarray.
* - a two-dimensional input ndarray.
* - a zero-dimensional ndarray containing a scalar constant.
*
* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
* @returns {Object} output ndarray
*
* @example
* var ndarray = require( '@stdlib/ndarray/base/ctor' );
* var vector = require( '@stdlib/ndarray/vector/ctor' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = vector( [ 1.0, 2.0 ], 'generic' );
* var y = vector( [ 3.0, 4.0, 5.0 ], 'generic' );
* var A = new ndarray( 'generic', [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
*
* var alpha = scalar2ndarray( 2.0, {
* 'dtype': 'generic'
* });
*
* var z = gger( [ x, y, A, alpha ] );
* // returns <ndarray>[ [ 7.0, 10.0, 13.0 ], [ 16.0, 21.0, 26.0 ] ]
*
* var bool = ( z === A );
* // returns true
*/
function gger( arrays ) {
var alpha = ndarraylike2scalar( arrays[ 3 ] );
var x = arrays[ 0 ];
var y = arrays[ 1 ];
var A = arrays[ 2 ];
strided( numelDimension( A, 0 ), numelDimension( A, 1 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), getStride( A, 0 ), getStride( A, 1 ), getOffset( A ) ); // eslint-disable-line max-len
return A;
}
// EXPORTS //
module.exports = gger;
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