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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 isLayout = require( '@stdlib/blas/base/assert/is-layout' );
var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' );
var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var max = require( '@stdlib/math/base/special/max' );
var format = require( '@stdlib/string/format' );
var type2char = require( './type2char.json' );
var isType = require( './is_type.js' );
var base = require( './base.js' );
// MAIN //
/**
* Multiplies a double-precision floating-point M-by-N matrix `A` by a double-precision floating-point scalar.
*
* @param {string} order - storage layout
* @param {string} type - specifies the type of matrix `A`
* @param {NonNegativeInteger} KL - lower bandwidth of `A` (i.e., the number of sub-diagonals)
* @param {NonNegativeInteger} KU - upper bandwidth of `A` (i.e., the number of super-diagonals)
* @param {number} gamma - the matrix `A` is multiplied by `beta/gamma`
* @param {number} beta - the matrix `A` is multiplied by `beta/gamma`
* @param {NonNegativeInteger} M - number of rows in matrix `A`
* @param {NonNegativeInteger} N - number of columns in matrix `A`
* @param {Float64Array} A - input matrix
* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
* @throws {TypeError} first argument must be a valid order
* @throws {TypeError} second argument must be a valid matrix type
* @throws {RangeError} tenth 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( 'row-major', 'general', 0, 0, 1.0, 2.0, 3, 2, A, 2 );
* // A => <Float64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ]
*/
function dlascl( order, type, KL, KU, gamma, beta, M, N, A, LDA ) {
var sa1;
var sa2;
var T;
var s;
if ( !isLayout( order ) ) {
throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) );
}
if ( !isType( type ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a valid matrix type. Value: `%s`.', type ) );
}
T = type2char[ type ];
if ( gamma === 0.0 ) {
throw new TypeError( format( 'invalid argument. Fifth argument must be non-zero. Value: `%s`.', gamma ) );
}
if ( isnan( gamma ) ) {
throw new TypeError( format( 'invalid argument. Fifth argument must be a valid number. Value: `%s`.', gamma ) );
}
if ( isnan( beta ) ) {
throw new TypeError( format( 'invalid argument. Sixth argument must be a valid number. Value: `%s`.', beta ) );
}
if ( M < 0 ) {
throw new TypeError( format( 'invalid argument. Seventh argument must be a nonnegative integer. Value: `%s`.', M ) );
}
if ( N < 0 ) {
throw new TypeError( format( 'invalid argument. Eighth argument must be a nonnegative integer. Value: `%s`.', N ) );
}
if ( ( T === 'B' || T === 'Q' ) && N !== M ) {
throw new TypeError( format( 'invalid argument. Seventh and eighth arguments must be equal. Values: [%s, %s].', M, N ) );
}
// FIXME: need more comprehensive validation
// FIXME: include some of the validation in the ndarray interface
if ( isRowMajor( order ) ) {
s = N;
} else if ( T === 'G' || T === 'U' || T === 'L' || T === 'H' ) {
s = M;
} else if ( T === 'B' ) {
s = KL + 1;
} else if ( T === 'Q' ) {
s = KU + 1;
} else {
s = (2*KL) + KU + 1;
}
if ( LDA < max( 1, s ) ) {
throw new RangeError( format( 'invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.', s, LDA ) );
}
if ( isColumnMajor( order ) ) {
sa1 = 1;
sa2 = LDA;
} else { // order === 'row-major'
sa1 = LDA;
sa2 = 1;
}
return base( T, KL, KU, gamma, beta, M, N, A, sa1, sa2, 0 );
}
// EXPORTS //
module.exports = dlascl;
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