larfb_gett(3)

NAME
larfb_gett - larfb_gett: step in ungtsqr_row

SYNOPSIS

  Functions
subroutine clarfb_gett (ident, m, n, k, t, ldt, a, lda, b, ldb, work, ldwork)
CLARFB_GETT
subroutine dlarfb_gett (ident, m, n, k, t, ldt, a, lda, b, ldb, work, ldwork)
DLARFB_GETT
subroutine slarfb_gett (ident, m, n, k, t, ldt, a, lda, b, ldb, work, ldwork)
SLARFB_GETT
subroutine zlarfb_gett (ident, m, n, k, t, ldt, a, lda, b, ldb, work, ldwork)
ZLARFB_GETT

Detailed Description

Function Documentation

  subroutine clarfb_gett (character ident, integer m, integer n, integer k, complex, dimension( ldt, * ) t, integer ldt, complex, dimension( lda, * ) a, integer lda, complex, dimension( ldb, * ) b, integer ldb, complex, dimension( ldwork, * ) work, integer ldwork)

CLARFB_GETT

Purpose:

    !>
    !> CLARFB_GETT applies a complex Householder block reflector H from the
    !> left to a complex (K+M)-by-N   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.
    !>

Parameters
    IDENT

    !>          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.
    !>

    M

    !>          M is INTEGER
    !>          The number of rows of the matrix B.
    !>          M >= 0.
    !>

    N

    !>          N is INTEGER
    !>          The number of columns of the matrices A and B.
    !>          N >= 0.
    !>

    K

    !>          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.
    !>

    T

    !>          T is COMPLEX array, dimension (LDT,K)
    !>          The upper-triangular K-by-K matrix T in the representation
    !>          of the block reflector.
    !>

    LDT

    !>          LDT is INTEGER
    !>          The leading dimension of the array T. LDT >= K.
    !>

    A

    !>          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.
    !>

    LDA

    !>          LDB is INTEGER
    !>          The leading dimension of the array A. LDA >= max(1,K).
    !>

    B

    !>          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.
    !>

    LDB

    !>          LDB is INTEGER
    !>          The leading dimension of the array B. LDB >= max(1,M).
    !>

    WORK

    !>          WORK is COMPLEX array,
    !>          dimension (LDWORK,max(K,N-K))
    !>

    LDWORK

    !>          LDWORK is INTEGER
    !>          The leading dimension of the array WORK. LDWORK>=max(1,K).
    !>
    !>

Author
    Univ. of Tennessee

    Univ. of California Berkeley

    Univ. of Colorado Denver

    NAG Ltd.

Contributors:

    !>
    !> November 2020, Igor Kozachenko,
    !>                Computer Science Division,
    !>                University of California, Berkeley
    !>
    !>

Further Details:

    !>
    !>    (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
    !>
    !>

Definition at line 390 of file clarfb_gett.f.

  subroutine dlarfb_gett (character ident, integer m, integer n, integer k, double precision, dimension( ldt, * ) t, integer ldt, double precision, dimension( lda, * ) a, integer lda, double precision, dimension( ldb, * ) b, integer ldb, double precision, dimension( ldwork, * ) work, integer ldwork)

DLARFB_GETT

Purpose:

    !>
    !> DLARFB_GETT applies a real Householder block reflector H from the
    !> left to a real (K+M)-by-N   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.
    !>

Parameters
    IDENT

    !>          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.
    !>

    M

    !>          M is INTEGER
    !>          The number of rows of the matrix B.
    !>          M >= 0.
    !>

    N

    !>          N is INTEGER
    !>          The number of columns of the matrices A and B.
    !>          N >= 0.
    !>

    K

    !>          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.
    !>

    T

    !>          T is DOUBLE PRECISION array, dimension (LDT,K)
    !>          The upper-triangular K-by-K matrix T in the representation
    !>          of the block reflector.
    !>

    LDT

    !>          LDT is INTEGER
    !>          The leading dimension of the array T. LDT >= K.
    !>

    A

    !>          A is DOUBLE PRECISION 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.
    !>

    LDA

    !>          LDB is INTEGER
    !>          The leading dimension of the array A. LDA >= max(1,K).
    !>

    B

    !>          B is DOUBLE PRECISION 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.
    !>

    LDB

    !>          LDB is INTEGER
    !>          The leading dimension of the array B. LDB >= max(1,M).
    !>

    WORK

    !>          WORK is DOUBLE PRECISION array,
    !>          dimension (LDWORK,max(K,N-K))
    !>

    LDWORK

    !>          LDWORK is INTEGER
    !>          The leading dimension of the array WORK. LDWORK>=max(1,K).
    !>
    !>

Author
    Univ. of Tennessee

    Univ. of California Berkeley

    Univ. of Colorado Denver

    NAG Ltd.

Contributors:

    !>
    !> November 2020, Igor Kozachenko,
    !>                Computer Science Division,
    !>                University of California, Berkeley
    !>
    !>

Further Details:

    !>
    !>    (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**T ) * ( A_in ) =
    !>       ( B_out )        ( B_in )                          ( B_in )
    !>                  = ( I - ( V1 ) * T * ( V1**T, V2**T ) ) * ( 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**T ) * ( A1_in )
    !>       ( B1_out )        (     0 )                          (     0 )
    !>
    !>       ( A2_out ) := H * ( A2_in ) = ( I - V * T * V**T ) * ( A2_in )
    !>       ( B2_out )        ( B2_in )                          ( B2_in )
    !>
    !>    If IDENT != 'I':
    !>
    !>       The computation for column block 1:
    !>
    !>       A1_out: = A1_in - V1*T*(V1**T)*A1_in
    !>
    !>       B1_out: = - V2*T*(V1**T)*A1_in
    !>
    !>       The computation for column block 2, which exists if N > K:
    !>
    !>       A2_out: = A2_in - V1*T*( (V1**T)*A2_in + (V2**T)*B2_in )
    !>
    !>       B2_out: = B2_in - V2*T*( (V1**T)*A2_in + (V2**T)*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**T)*B2_in )
    !>
    !>       B2_out: = B2_in - V2*T*( A2_in + (V2**T)*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**T) * W2 = (unit_lower_tr_of_(A1)**T) * W2
    !>       col2_(3) W2: = W2 + (V2**T) * B2 = W2 + (B1**T) * 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**T) * W1 = (unit_lower_tr_of_(A1)**T) * 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**T) * B2 = W2 + (B1**T) * 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**T) * W2
    !>                      = (unit_lower_tr_of_(A1)**T) * W2
    !>      end if
    !>      col2_(3)  W2: = W2 + (V2**T) * B2 = W2 + (B1**T) * 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**T) * W1
    !>                    = (unit_lower_tr_of_(A1)**T) * 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
    !>
    !>

Definition at line 390 of file dlarfb_gett.f.

  subroutine slarfb_gett (character ident, integer m, integer n, integer k, real, dimension( ldt, * ) t, integer ldt, real, dimension( lda, * ) a, integer lda, real, dimension( ldb, * ) b, integer ldb, real, dimension( ldwork, * ) work, integer ldwork)

SLARFB_GETT

Purpose:

    !>
    !> SLARFB_GETT applies a real Householder block reflector H from the
    !> left to a real (K+M)-by-N   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.
    !>

Parameters
    IDENT

    !>          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.
    !>

    M

    !>          M is INTEGER
    !>          The number of rows of the matrix B.
    !>          M >= 0.
    !>

    N

    !>          N is INTEGER
    !>          The number of columns of the matrices A and B.
    !>          N >= 0.
    !>

    K

    !>          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.
    !>

    T

    !>          T is REAL array, dimension (LDT,K)
    !>          The upper-triangular K-by-K matrix T in the representation
    !>          of the block reflector.
    !>

    LDT

    !>          LDT is INTEGER
    !>          The leading dimension of the array T. LDT >= K.
    !>

    A

    !>          A is REAL 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.
    !>

    LDA

    !>          LDB is INTEGER
    !>          The leading dimension of the array A. LDA >= max(1,K).
    !>

    B

    !>          B is REAL 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.
    !>

    LDB

    !>          LDB is INTEGER
    !>          The leading dimension of the array B. LDB >= max(1,M).
    !>

    WORK

    !>          WORK is REAL array,
    !>          dimension (LDWORK,max(K,N-K))
    !>

    LDWORK

    !>          LDWORK is INTEGER
    !>          The leading dimension of the array WORK. LDWORK>=max(1,K).
    !>
    !>

Author
    Univ. of Tennessee

    Univ. of California Berkeley

    Univ. of Colorado Denver

    NAG Ltd.

Contributors:

    !>
    !> November 2020, Igor Kozachenko,
    !>                Computer Science Division,
    !>                University of California, Berkeley
    !>
    !>

Further Details:

    !>
    !>    (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**T ) * ( A_in ) =
    !>       ( B_out )        ( B_in )                          ( B_in )
    !>                  = ( I - ( V1 ) * T * ( V1**T, V2**T ) ) * ( 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**T ) * ( A1_in )
    !>       ( B1_out )        (     0 )                          (     0 )
    !>
    !>       ( A2_out ) := H * ( A2_in ) = ( I - V * T * V**T ) * ( A2_in )
    !>       ( B2_out )        ( B2_in )                          ( B2_in )
    !>
    !>    If IDENT != 'I':
    !>
    !>       The computation for column block 1:
    !>
    !>       A1_out: = A1_in - V1*T*(V1**T)*A1_in
    !>
    !>       B1_out: = - V2*T*(V1**T)*A1_in
    !>
    !>       The computation for column block 2, which exists if N > K:
    !>
    !>       A2_out: = A2_in - V1*T*( (V1**T)*A2_in + (V2**T)*B2_in )
    !>
    !>       B2_out: = B2_in - V2*T*( (V1**T)*A2_in + (V2**T)*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**T)*B2_in )
    !>
    !>       B2_out: = B2_in - V2*T*( A2_in + (V2**T)*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**T) * W2 = (unit_lower_tr_of_(A1)**T) * W2
    !>       col2_(3) W2: = W2 + (V2**T) * B2 = W2 + (B1**T) * 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**T) * W1 = (unit_lower_tr_of_(A1)**T) * 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**T) * B2 = W2 + (B1**T) * 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**T) * W2
    !>                      = (unit_lower_tr_of_(A1)**T) * W2
    !>      end if
    !>      col2_(3)  W2: = W2 + (V2**T) * B2 = W2 + (B1**T) * 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**T) * W1
    !>                    = (unit_lower_tr_of_(A1)**T) * 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
    !>
    !>

Definition at line 390 of file slarfb_gett.f.

  subroutine zlarfb_gett (character ident, integer m, integer n, integer k, complex*16, dimension( ldt, * ) t, integer ldt, complex*16, dimension( lda, * ) a, integer lda, complex*16, dimension( ldb, * ) b, integer ldb, complex*16, dimension( ldwork, * ) work, integer ldwork)

ZLARFB_GETT

Purpose:

    !>
    !> ZLARFB_GETT applies a complex Householder block reflector H from the
    !> left to a complex (K+M)-by-N   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.
    !>

Parameters
    IDENT

    !>          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.
    !>

    M

    !>          M is INTEGER
    !>          The number of rows of the matrix B.
    !>          M >= 0.
    !>

    N

    !>          N is INTEGER
    !>          The number of columns of the matrices A and B.
    !>          N >= 0.
    !>

    K

    !>          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.
    !>

    T

    !>          T is COMPLEX*16 array, dimension (LDT,K)
    !>          The upper-triangular K-by-K matrix T in the representation
    !>          of the block reflector.
    !>

    LDT

    !>          LDT is INTEGER
    !>          The leading dimension of the array T. LDT >= K.
    !>

    A

    !>          A is COMPLEX*16 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.
    !>

    LDA

    !>          LDB is INTEGER
    !>          The leading dimension of the array A. LDA >= max(1,K).
    !>

    B

    !>          B is COMPLEX*16 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.
    !>

    LDB

    !>          LDB is INTEGER
    !>          The leading dimension of the array B. LDB >= max(1,M).
    !>

    WORK

    !>          WORK is COMPLEX*16 array,
    !>          dimension (LDWORK,max(K,N-K))
    !>

    LDWORK

    !>          LDWORK is INTEGER
    !>          The leading dimension of the array WORK. LDWORK>=max(1,K).
    !>
    !>

Author
    Univ. of Tennessee

    Univ. of California Berkeley

    Univ. of Colorado Denver

    NAG Ltd.

Contributors:

    !>
    !> November 2020, Igor Kozachenko,
    !>                Computer Science Division,
    !>                University of California, Berkeley
    !>
    !>

Further Details:

    !>
    !>    (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
    !>
    !>

Definition at line 390 of file zlarfb_gett.f.

Author

Generated automatically by Doxygen for LAPACK from the source code.