docs: add ts files

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Author: aayush0325

lib/node_modules/@stdlib/lapack/base/dlascl/docs/types/index.d.ts

@@ -0,0 +1,117 @@
+/*
+* @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.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { Layout } from '@stdlib/types/blas';
+
+/**
+* Interface describing `dlascl`.
+*/
+interface Routine {
+	/**
+	* Multiplies a real M by N matrix `A` by a real scalar `CTO/CFROM`.
+	*
+	* @param order - storage layout
+	* @param type - specifies the type of matrix `A`
+	* @param KL - lower band width of `A`. Referenced only if type is `symmetric-banded-lower` or `banded`.
+	* @param KU - upper band width of `A`. Referenced only if type is `symmetric-banded-upper` or `banded`.
+	* @param CFROM - the matrix `A` are multiplied by `CTO / CFROM`
+	* @param CTO - the matrix `A` are multiplied by `CTO / CFROM`
+	* @param M - number of rows in matrix `A`
+	* @param N - number of columns in matrix `A`
+	* @param A - input matrix
+	* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
+	* @returns 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 ]
+	*/
+	( order: Layout, type: string, KL: number, KU: number, CFROM: number, CTO: number, M: number, N: number, A: Float64Array, LDA: number ): Float64Array;
+
+	/**
+	* Multiplies a real M by N matrix `A` by a real scalar `CTO/CFROM` using alternative indexing semantics.
+	*
+	* @param type - specifies the type of matrix `A`
+	* @param KL - lower band width of `A`. Referenced only if type is `symmetric-banded-lower` or `banded`.
+	* @param KU - upper band width of `A`. Referenced only if type is `symmetric-banded-upper` or `banded`.
+	* @param CFROM - the matrix `A` are multiplied by `CTO / CFROM`
+	* @param CTO - the matrix `A` are multiplied by `CTO / CFROM`
+	* @param M - number of rows in matrix `A`
+	* @param N - number of columns in matrix `A`
+	* @param A - input matrix
+	* @param strideA1 - stride of the first dimension of `A`
+	* @param strideA2 - stride of the second dimension of `A`
+	* @param offsetA - starting index for `A`
+	* @returns 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.ndarray( '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 ]
+	*/
+	ndarray( type: string, KL: number, KU: number, CFROM: number, CTO: number, M: number, N: number, A: Float64Array, strideA1: number, strideA2: number, offsetA: number ): Float64Array;
+}
+
+/**
+* Multiplies a real M by N matrix `A` by a real scalar `CTO/CFROM`.
+*
+* @param order - storage layout
+* @param type - specifies the type of matrix `A`
+* @param KL - lower band width of `A`. Referenced only if type is `symmetric-banded-lower` or `banded`.
+* @param KU - upper band width of `A`. Referenced only if type is `symmetric-banded-upper` or `banded`.
+* @param CFROM - the matrix `A` are multiplied by `CTO / CFROM`
+* @param CTO - the matrix `A` are multiplied by `CTO / CFROM`
+* @param M - number of rows in matrix `A`
+* @param N - number of columns in matrix `A`
+* @param A - input matrix
+* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`)
+* @returns 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 ]
+*
+* @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.ndarray( '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 ]
+*/
+declare var dlascl: Routine;
+
+
+// EXPORTS //
+
+export = dlascl;