Press n or j to go to the next uncovered block, b, p or k for the previous block.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 10x 10x 10x 2x 2x 2x 2x 2x | /**
* @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 base = require( './base.js' );
// MAIN //
/**
* Computes the reciprocal pivot growth factor norm(A)/norm(U) for a general banded matrix `A` using alternating indexing semantics.
*
* ## Notes
*
* - The norm is used. If this is much less than 1, the stability of the LU factorization of the (equilibrated) matrix `A` could be poor. This also means that the solution `X`, estimated condition numbers, and error bounds could be unreliable.
* - Matrix `AB` is the matrix A in band storage, in rows 0 to `KL+KU`. The j-th column of A is stored in the j-th column of the matrix `AB` as `AB( KU+i-j, j ) = A( i, j )` for `max( 0, j - KU ) <= i <= min( N - 1, j + KL )`.
* - Matrix `AFB` stores the details of the LU factorization of the band matrix `A`, as computed by `DGBTRF`. `U` is stored as an upper triangular band matrix with KL+KU superdiagonals in rows 0 to `KL+KU+1`, and the multipliers used during the factorization are stored in rows `KL+KU+1` to `2*KL+KU`.
* - The leading dimension of `AB`, `LDAB` >= `KL+KU+1`.
* - The leading dimension of `AFB`, `LDAFB` >= `2*KL+KU+1`.
*
* @param {NonNegativeInteger} N - number of rows in matrix `A`
* @param {NonNegativeInteger} KL - number of subdiagonals within the band of matrix `A`
* @param {NonNegativeInteger} KU - number of superdiagonals within the band of matrix `A`
* @param {NonNegativeInteger} NCOLS - number of columns in matrix `A`
* @param {Float64Array} AB - the matrix A in band storage
* @param {integer} strideAB1 - stride of the first dimension of `AB`
* @param {integer} strideAB2 - stride of the second dimension of `AB`
* @param {NonNegativeInteger} offsetAB - index offset for `AB`
* @param {Float64Array} AFB - details of the LU factorization of the band matrix `A`
* @param {integer} strideAFB1 - stride of the first dimension of `AFB`
* @param {integer} strideAFB2 - stride of the second dimension of `AFB`
* @param {NonNegativeInteger} offsetAFB - index offset for `AFB`
* @returns {number} the reciprocal pivot growth factor
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var AB = new Float64Array( [ 0.0, 2.0, 5.0, 8.0, 1.0, 4.0, 7.0, 10.0, 3.0, 6.0, 9.0, 0.0 ] );
* var AFB = new Float64Array( [ 0.0, 0.0, 5.0, 8.0, 0.0, 4.0, 7.0, 10.0, 3.0, 6.0, 9.0, 1.8272, 0.3333, 0.1111, -0.2716, 0.0 ] );
*
* var out = dlagbrpvgrw( 4, 1, 1, 4, AB, 4, 1, 0, AFB, 4, 1, 0 );
* // returns 1.0
*/
function dlagbrpvgrw( N, KL, KU, NCOLS, AB, strideAB1, strideAB2, offsetAB, AFB, strideAFB1, strideAFB2, offsetAFB ) { // eslint-disable-line max-len, max-params
return base( N, KL, KU, NCOLS, AB, strideAB1, strideAB2, offsetAB, AFB, strideAFB1, strideAFB2, offsetAFB ); // eslint-disable-line max-len
}
// EXPORTS //
module.exports = dlagbrpvgrw;
|