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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 format = require( '@stdlib/string/format' );
var base = require( './base.js' );
// MAIN //
/**
* Multiplies a double-precision floating-point M-by-N matrix `A` by a double-precision floating-point scalar using alternative indexing semantics.
*
* @param {string} type - specifies the type of matrix `A`. Must be one of the following: `'general'`, `'upper'`, `'lower'`, `'upper-hessenberg'`, `'symmetric-banded-lower'`, `'symmetric-banded-upper'`, or `'banded'`.
* @param {NonNegativeInteger} KL - lower bandwidth of `A` (i.e., the number of sub-diagonals). Referenced only if type is `'symmetric-banded-lower'` or `'banded'`.
* @param {NonNegativeInteger} KU - upper bandwidth of `A` (i.e., the number of super-diagonals). Referenced only if type is `'symmetric-banded-upper'` or `'banded'`.
* @param {number} gamma - the matrix `A` is multiplied by `β/γ`
* @param {number} beta - the matrix `A` is multiplied by `β/γ`
* @param {NonNegativeInteger} M - number of rows in matrix `A`
* @param {NonNegativeInteger} N - number of columns in matrix `A`
* @param {Float64Array} A - input matrix
* @param {integer} strideA1 - stride of the first dimension of `A`
* @param {integer} strideA2 - stride of the second dimension of `A`
* @param {NonNegativeInteger} offsetA - starting index for `A`
* @throws {TypeError} first argument must be a valid order
* @throws {RangeError} fourth argument must be greater than or equal to max(1,N)
* @returns {Float64Array} scaled matrix `A`
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); // => [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]
*
* dlascl( 'general', 0, 0, 1.0, 2.0, 3, 2, A, 2, 1, 0 );
* // A => <Float64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ]
*/
function dlascl( type, KL, KU, gamma, beta, M, N, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len, max-params
if ( type !== 'general' && type !== 'upper' && type !== 'lower' && type !== 'upper-hessenberg' && type !== 'symmetric-banded-lower' && type !== 'symmetric-banded-upper' && type !== 'banded' ) {
throw new TypeError( format( 'invalid argument. First argument must be a valid matrix type. Value: `%s`.', type ) );
}
return base( type, KL, KU, gamma, beta, M, N, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len
}
// EXPORTS //
module.exports = dlascl;
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