numeric-linalg
Educational material on the SciPy implementation of numerical linear algebra algorithms
Name | Size | Mode | |
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lapack/SRC/clarfb_gett.f | 18562B | -rw-r--r-- |
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*> \brief \b CLARFB_GETT * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * *> \htmlonly *> Download CLARFB_GETT + dependencies *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/clarfb_gett.f"> *> [TGZ]</a> *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/clarfb_gett.f"> *> [ZIP]</a> *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/clarfb_gett.f"> *> [TXT]</a> *> \endhtmlonly *> * Definition: * =========== * * SUBROUTINE CLARFB_GETT( IDENT, M, N, K, T, LDT, A, LDA, B, LDB, * $ WORK, LDWORK ) * IMPLICIT NONE * * .. Scalar Arguments .. * CHARACTER IDENT * INTEGER K, LDA, LDB, LDT, LDWORK, M, N * .. * .. Array Arguments .. * COMPLEX A( LDA, * ), B( LDB, * ), T( LDT, * ), * $ WORK( LDWORK, * ) * .. * *> \par Purpose: * ============= *> *> \verbatim *> *> CLARFB_GETT applies a complex Householder block reflector H from the *> left to a complex (K+M)-by-N "triangular-pentagonal" matrix *> composed of two block matrices: an upper trapezoidal K-by-N matrix A *> stored in the array A, and a rectangular M-by-(N-K) matrix B, stored *> in the array B. The block reflector H is stored in a compact *> WY-representation, where the elementary reflectors are in the *> arrays A, B and T. See Further Details section. *> \endverbatim * * Arguments: * ========== * *> \param[in] IDENT *> \verbatim *> IDENT is CHARACTER*1 *> If IDENT = not 'I', or not 'i', then V1 is unit *> lower-triangular and stored in the left K-by-K block of *> the input matrix A, *> If IDENT = 'I' or 'i', then V1 is an identity matrix and *> not stored. *> See Further Details section. *> \endverbatim *> *> \param[in] M *> \verbatim *> M is INTEGER *> The number of rows of the matrix B. *> M >= 0. *> \endverbatim *> *> \param[in] N *> \verbatim *> N is INTEGER *> The number of columns of the matrices A and B. *> N >= 0. *> \endverbatim *> *> \param[in] K *> \verbatim *> K is INTEGER *> The number or rows of the matrix A. *> K is also order of the matrix T, i.e. the number of *> elementary reflectors whose product defines the block *> reflector. 0 <= K <= N. *> \endverbatim *> *> \param[in] T *> \verbatim *> T is COMPLEX array, dimension (LDT,K) *> The upper-triangular K-by-K matrix T in the representation *> of the block reflector. *> \endverbatim *> *> \param[in] LDT *> \verbatim *> LDT is INTEGER *> The leading dimension of the array T. LDT >= K. *> \endverbatim *> *> \param[in,out] A *> \verbatim *> A is COMPLEX array, dimension (LDA,N) *> *> On entry: *> a) In the K-by-N upper-trapezoidal part A: input matrix A. *> b) In the columns below the diagonal: columns of V1 *> (ones are not stored on the diagonal). *> *> On exit: *> A is overwritten by rectangular K-by-N product H*A. *> *> See Further Details section. *> \endverbatim *> *> \param[in] LDA *> \verbatim *> LDB is INTEGER *> The leading dimension of the array A. LDA >= max(1,K). *> \endverbatim *> *> \param[in,out] B *> \verbatim *> B is COMPLEX array, dimension (LDB,N) *> *> On entry: *> a) In the M-by-(N-K) right block: input matrix B. *> b) In the M-by-N left block: columns of V2. *> *> On exit: *> B is overwritten by rectangular M-by-N product H*B. *> *> See Further Details section. *> \endverbatim *> *> \param[in] LDB *> \verbatim *> LDB is INTEGER *> The leading dimension of the array B. LDB >= max(1,M). *> \endverbatim *> *> \param[out] WORK *> \verbatim *> WORK is COMPLEX array, *> dimension (LDWORK,max(K,N-K)) *> \endverbatim *> *> \param[in] LDWORK *> \verbatim *> LDWORK is INTEGER *> The leading dimension of the array WORK. LDWORK>=max(1,K). *> *> \endverbatim * * Authors: * ======== * *> \author Univ. of Tennessee *> \author Univ. of California Berkeley *> \author Univ. of Colorado Denver *> \author NAG Ltd. * *> \ingroup larfb_gett * *> \par Contributors: * ================== *> *> \verbatim *> *> November 2020, Igor Kozachenko, *> Computer Science Division, *> University of California, Berkeley *> *> \endverbatim * *> \par Further Details: * ===================== *> *> \verbatim *> *> (1) Description of the Algebraic Operation. *> *> The matrix A is a K-by-N matrix composed of two column block *> matrices, A1, which is K-by-K, and A2, which is K-by-(N-K): *> A = ( A1, A2 ). *> The matrix B is an M-by-N matrix composed of two column block *> matrices, B1, which is M-by-K, and B2, which is M-by-(N-K): *> B = ( B1, B2 ). *> *> Perform the operation: *> *> ( A_out ) := H * ( A_in ) = ( I - V * T * V**H ) * ( A_in ) = *> ( B_out ) ( B_in ) ( B_in ) *> = ( I - ( V1 ) * T * ( V1**H, V2**H ) ) * ( A_in ) *> ( V2 ) ( B_in ) *> On input: *> *> a) ( A_in ) consists of two block columns: *> ( B_in ) *> *> ( A_in ) = (( A1_in ) ( A2_in )) = (( A1_in ) ( A2_in )) *> ( B_in ) (( B1_in ) ( B2_in )) (( 0 ) ( B2_in )), *> *> where the column blocks are: *> *> ( A1_in ) is a K-by-K upper-triangular matrix stored in the *> upper triangular part of the array A(1:K,1:K). *> ( B1_in ) is an M-by-K rectangular ZERO matrix and not stored. *> *> ( A2_in ) is a K-by-(N-K) rectangular matrix stored *> in the array A(1:K,K+1:N). *> ( B2_in ) is an M-by-(N-K) rectangular matrix stored *> in the array B(1:M,K+1:N). *> *> b) V = ( V1 ) *> ( V2 ) *> *> where: *> 1) if IDENT == 'I',V1 is a K-by-K identity matrix, not stored; *> 2) if IDENT != 'I',V1 is a K-by-K unit lower-triangular matrix, *> stored in the lower-triangular part of the array *> A(1:K,1:K) (ones are not stored), *> and V2 is an M-by-K rectangular stored the array B(1:M,1:K), *> (because on input B1_in is a rectangular zero *> matrix that is not stored and the space is *> used to store V2). *> *> c) T is a K-by-K upper-triangular matrix stored *> in the array T(1:K,1:K). *> *> On output: *> *> a) ( A_out ) consists of two block columns: *> ( B_out ) *> *> ( A_out ) = (( A1_out ) ( A2_out )) *> ( B_out ) (( B1_out ) ( B2_out )), *> *> where the column blocks are: *> *> ( A1_out ) is a K-by-K square matrix, or a K-by-K *> upper-triangular matrix, if V1 is an *> identity matrix. AiOut is stored in *> the array A(1:K,1:K). *> ( B1_out ) is an M-by-K rectangular matrix stored *> in the array B(1:M,K:N). *> *> ( A2_out ) is a K-by-(N-K) rectangular matrix stored *> in the array A(1:K,K+1:N). *> ( B2_out ) is an M-by-(N-K) rectangular matrix stored *> in the array B(1:M,K+1:N). *> *> *> The operation above can be represented as the same operation *> on each block column: *> *> ( A1_out ) := H * ( A1_in ) = ( I - V * T * V**H ) * ( A1_in ) *> ( B1_out ) ( 0 ) ( 0 ) *> *> ( A2_out ) := H * ( A2_in ) = ( I - V * T * V**H ) * ( A2_in ) *> ( B2_out ) ( B2_in ) ( B2_in ) *> *> If IDENT != 'I': *> *> The computation for column block 1: *> *> A1_out: = A1_in - V1*T*(V1**H)*A1_in *> *> B1_out: = - V2*T*(V1**H)*A1_in *> *> The computation for column block 2, which exists if N > K: *> *> A2_out: = A2_in - V1*T*( (V1**H)*A2_in + (V2**H)*B2_in ) *> *> B2_out: = B2_in - V2*T*( (V1**H)*A2_in + (V2**H)*B2_in ) *> *> If IDENT == 'I': *> *> The operation for column block 1: *> *> A1_out: = A1_in - V1*T*A1_in *> *> B1_out: = - V2*T*A1_in *> *> The computation for column block 2, which exists if N > K: *> *> A2_out: = A2_in - T*( A2_in + (V2**H)*B2_in ) *> *> B2_out: = B2_in - V2*T*( A2_in + (V2**H)*B2_in ) *> *> (2) Description of the Algorithmic Computation. *> *> In the first step, we compute column block 2, i.e. A2 and B2. *> Here, we need to use the K-by-(N-K) rectangular workspace *> matrix W2 that is of the same size as the matrix A2. *> W2 is stored in the array WORK(1:K,1:(N-K)). *> *> In the second step, we compute column block 1, i.e. A1 and B1. *> Here, we need to use the K-by-K square workspace matrix W1 *> that is of the same size as the as the matrix A1. *> W1 is stored in the array WORK(1:K,1:K). *> *> NOTE: Hence, in this routine, we need the workspace array WORK *> only of size WORK(1:K,1:max(K,N-K)) so it can hold both W2 from *> the first step and W1 from the second step. *> *> Case (A), when V1 is unit lower-triangular, i.e. IDENT != 'I', *> more computations than in the Case (B). *> *> if( IDENT != 'I' ) then *> if ( N > K ) then *> (First Step - column block 2) *> col2_(1) W2: = A2 *> col2_(2) W2: = (V1**H) * W2 = (unit_lower_tr_of_(A1)**H) * W2 *> col2_(3) W2: = W2 + (V2**H) * B2 = W2 + (B1**H) * B2 *> col2_(4) W2: = T * W2 *> col2_(5) B2: = B2 - V2 * W2 = B2 - B1 * W2 *> col2_(6) W2: = V1 * W2 = unit_lower_tr_of_(A1) * W2 *> col2_(7) A2: = A2 - W2 *> else *> (Second Step - column block 1) *> col1_(1) W1: = A1 *> col1_(2) W1: = (V1**H) * W1 = (unit_lower_tr_of_(A1)**H) * W1 *> col1_(3) W1: = T * W1 *> col1_(4) B1: = - V2 * W1 = - B1 * W1 *> col1_(5) square W1: = V1 * W1 = unit_lower_tr_of_(A1) * W1 *> col1_(6) square A1: = A1 - W1 *> end if *> end if *> *> Case (B), when V1 is an identity matrix, i.e. IDENT == 'I', *> less computations than in the Case (A) *> *> if( IDENT == 'I' ) then *> if ( N > K ) then *> (First Step - column block 2) *> col2_(1) W2: = A2 *> col2_(3) W2: = W2 + (V2**H) * B2 = W2 + (B1**H) * B2 *> col2_(4) W2: = T * W2 *> col2_(5) B2: = B2 - V2 * W2 = B2 - B1 * W2 *> col2_(7) A2: = A2 - W2 *> else *> (Second Step - column block 1) *> col1_(1) W1: = A1 *> col1_(3) W1: = T * W1 *> col1_(4) B1: = - V2 * W1 = - B1 * W1 *> col1_(6) upper-triangular_of_(A1): = A1 - W1 *> end if *> end if *> *> Combine these cases (A) and (B) together, this is the resulting *> algorithm: *> *> if ( N > K ) then *> *> (First Step - column block 2) *> *> col2_(1) W2: = A2 *> if( IDENT != 'I' ) then *> col2_(2) W2: = (V1**H) * W2 *> = (unit_lower_tr_of_(A1)**H) * W2 *> end if *> col2_(3) W2: = W2 + (V2**H) * B2 = W2 + (B1**H) * B2] *> col2_(4) W2: = T * W2 *> col2_(5) B2: = B2 - V2 * W2 = B2 - B1 * W2 *> if( IDENT != 'I' ) then *> col2_(6) W2: = V1 * W2 = unit_lower_tr_of_(A1) * W2 *> end if *> col2_(7) A2: = A2 - W2 *> *> else *> *> (Second Step - column block 1) *> *> col1_(1) W1: = A1 *> if( IDENT != 'I' ) then *> col1_(2) W1: = (V1**H) * W1 *> = (unit_lower_tr_of_(A1)**H) * W1 *> end if *> col1_(3) W1: = T * W1 *> col1_(4) B1: = - V2 * W1 = - B1 * W1 *> if( IDENT != 'I' ) then *> col1_(5) square W1: = V1 * W1 = unit_lower_tr_of_(A1) * W1 *> col1_(6_a) below_diag_of_(A1): = - below_diag_of_(W1) *> end if *> col1_(6_b) up_tr_of_(A1): = up_tr_of_(A1) - up_tr_of_(W1) *> *> end if *> *> \endverbatim *> * ===================================================================== SUBROUTINE CLARFB_GETT( IDENT, M, N, K, T, LDT, A, LDA, B, LDB, $ WORK, LDWORK ) IMPLICIT NONE * * -- LAPACK auxiliary routine -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * * .. Scalar Arguments .. CHARACTER IDENT INTEGER K, LDA, LDB, LDT, LDWORK, M, N * .. * .. Array Arguments .. COMPLEX A( LDA, * ), B( LDB, * ), T( LDT, * ), $ WORK( LDWORK, * ) * .. * * ===================================================================== * * .. Parameters .. COMPLEX CONE, CZERO PARAMETER ( CONE = ( 1.0E+0, 0.0E+0 ), $ CZERO = ( 0.0E+0, 0.0E+0 ) ) * .. * .. Local Scalars .. LOGICAL LNOTIDENT INTEGER I, J * .. * .. EXTERNAL FUNCTIONS .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL CCOPY, CGEMM, CTRMM * .. * .. Executable Statements .. * * Quick return if possible * IF( M.LT.0 .OR. N.LE.0 .OR. K.EQ.0 .OR. K.GT.N ) $ RETURN * LNOTIDENT = .NOT.LSAME( IDENT, 'I' ) * * ------------------------------------------------------------------ * * First Step. Computation of the Column Block 2: * * ( A2 ) := H * ( A2 ) * ( B2 ) ( B2 ) * * ------------------------------------------------------------------ * IF( N.GT.K ) THEN * * col2_(1) Compute W2: = A2. Therefore, copy A2 = A(1:K, K+1:N) * into W2=WORK(1:K, 1:N-K) column-by-column. * DO J = 1, N-K CALL CCOPY( K, A( 1, K+J ), 1, WORK( 1, J ), 1 ) END DO IF( LNOTIDENT ) THEN * * col2_(2) Compute W2: = (V1**H) * W2 = (A1**H) * W2, * V1 is not an identity matrix, but unit lower-triangular * V1 stored in A1 (diagonal ones are not stored). * * CALL CTRMM( 'L', 'L', 'C', 'U', K, N-K, CONE, A, LDA, $ WORK, LDWORK ) END IF * * col2_(3) Compute W2: = W2 + (V2**H) * B2 = W2 + (B1**H) * B2 * V2 stored in B1. * IF( M.GT.0 ) THEN CALL CGEMM( 'C', 'N', K, N-K, M, CONE, B, LDB, $ B( 1, K+1 ), LDB, CONE, WORK, LDWORK ) END IF * * col2_(4) Compute W2: = T * W2, * T is upper-triangular. * CALL CTRMM( 'L', 'U', 'N', 'N', K, N-K, CONE, T, LDT, $ WORK, LDWORK ) * * col2_(5) Compute B2: = B2 - V2 * W2 = B2 - B1 * W2, * V2 stored in B1. * IF( M.GT.0 ) THEN CALL CGEMM( 'N', 'N', M, N-K, K, -CONE, B, LDB, $ WORK, LDWORK, CONE, B( 1, K+1 ), LDB ) END IF * IF( LNOTIDENT ) THEN * * col2_(6) Compute W2: = V1 * W2 = A1 * W2, * V1 is not an identity matrix, but unit lower-triangular, * V1 stored in A1 (diagonal ones are not stored). * CALL CTRMM( 'L', 'L', 'N', 'U', K, N-K, CONE, A, LDA, $ WORK, LDWORK ) END IF * * col2_(7) Compute A2: = A2 - W2 = * = A(1:K, K+1:N-K) - WORK(1:K, 1:N-K), * column-by-column. * DO J = 1, N-K DO I = 1, K A( I, K+J ) = A( I, K+J ) - WORK( I, J ) END DO END DO * END IF * * ------------------------------------------------------------------ * * Second Step. Computation of the Column Block 1: * * ( A1 ) := H * ( A1 ) * ( B1 ) ( 0 ) * * ------------------------------------------------------------------ * * col1_(1) Compute W1: = A1. Copy the upper-triangular * A1 = A(1:K, 1:K) into the upper-triangular * W1 = WORK(1:K, 1:K) column-by-column. * DO J = 1, K CALL CCOPY( J, A( 1, J ), 1, WORK( 1, J ), 1 ) END DO * * Set the subdiagonal elements of W1 to zero column-by-column. * DO J = 1, K - 1 DO I = J + 1, K WORK( I, J ) = CZERO END DO END DO * IF( LNOTIDENT ) THEN * * col1_(2) Compute W1: = (V1**H) * W1 = (A1**H) * W1, * V1 is not an identity matrix, but unit lower-triangular * V1 stored in A1 (diagonal ones are not stored), * W1 is upper-triangular with zeroes below the diagonal. * CALL CTRMM( 'L', 'L', 'C', 'U', K, K, CONE, A, LDA, $ WORK, LDWORK ) END IF * * col1_(3) Compute W1: = T * W1, * T is upper-triangular, * W1 is upper-triangular with zeroes below the diagonal. * CALL CTRMM( 'L', 'U', 'N', 'N', K, K, CONE, T, LDT, $ WORK, LDWORK ) * * col1_(4) Compute B1: = - V2 * W1 = - B1 * W1, * V2 = B1, W1 is upper-triangular with zeroes below the diagonal. * IF( M.GT.0 ) THEN CALL CTRMM( 'R', 'U', 'N', 'N', M, K, -CONE, WORK, LDWORK, $ B, LDB ) END IF * IF( LNOTIDENT ) THEN * * col1_(5) Compute W1: = V1 * W1 = A1 * W1, * V1 is not an identity matrix, but unit lower-triangular * V1 stored in A1 (diagonal ones are not stored), * W1 is upper-triangular on input with zeroes below the diagonal, * and square on output. * CALL CTRMM( 'L', 'L', 'N', 'U', K, K, CONE, A, LDA, $ WORK, LDWORK ) * * col1_(6) Compute A1: = A1 - W1 = A(1:K, 1:K) - WORK(1:K, 1:K) * column-by-column. A1 is upper-triangular on input. * If IDENT, A1 is square on output, and W1 is square, * if NOT IDENT, A1 is upper-triangular on output, * W1 is upper-triangular. * * col1_(6)_a Compute elements of A1 below the diagonal. * DO J = 1, K - 1 DO I = J + 1, K A( I, J ) = - WORK( I, J ) END DO END DO * END IF * * col1_(6)_b Compute elements of A1 on and above the diagonal. * DO J = 1, K DO I = 1, J A( I, J ) = A( I, J ) - WORK( I, J ) END DO END DO * RETURN * * End of CLARFB_GETT * END