LAPACK 3.3.1
Linear Algebra PACKage

clanhs.f

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00001       REAL             FUNCTION CLANHS( NORM, N, A, LDA, WORK )
00002 *
00003 *  -- LAPACK auxiliary routine (version 3.2) --
00004 *  -- LAPACK is a software package provided by Univ. of Tennessee,    --
00005 *  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
00006 *     November 2006
00007 *
00008 *     .. Scalar Arguments ..
00009       CHARACTER          NORM
00010       INTEGER            LDA, N
00011 *     ..
00012 *     .. Array Arguments ..
00013       REAL               WORK( * )
00014       COMPLEX            A( LDA, * )
00015 *     ..
00016 *
00017 *  Purpose
00018 *  =======
00019 *
00020 *  CLANHS  returns the value of the one norm,  or the Frobenius norm, or
00021 *  the  infinity norm,  or the  element of  largest absolute value  of a
00022 *  Hessenberg matrix A.
00023 *
00024 *  Description
00025 *  ===========
00026 *
00027 *  CLANHS returns the value
00028 *
00029 *     CLANHS = ( max(abs(A(i,j))), NORM = 'M' or 'm'
00030 *              (
00031 *              ( norm1(A),         NORM = '1', 'O' or 'o'
00032 *              (
00033 *              ( normI(A),         NORM = 'I' or 'i'
00034 *              (
00035 *              ( normF(A),         NORM = 'F', 'f', 'E' or 'e'
00036 *
00037 *  where  norm1  denotes the  one norm of a matrix (maximum column sum),
00038 *  normI  denotes the  infinity norm  of a matrix  (maximum row sum) and
00039 *  normF  denotes the  Frobenius norm of a matrix (square root of sum of
00040 *  squares).  Note that  max(abs(A(i,j)))  is not a consistent matrix norm.
00041 *
00042 *  Arguments
00043 *  =========
00044 *
00045 *  NORM    (input) CHARACTER*1
00046 *          Specifies the value to be returned in CLANHS as described
00047 *          above.
00048 *
00049 *  N       (input) INTEGER
00050 *          The order of the matrix A.  N >= 0.  When N = 0, CLANHS is
00051 *          set to zero.
00052 *
00053 *  A       (input) COMPLEX array, dimension (LDA,N)
00054 *          The n by n upper Hessenberg matrix A; the part of A below the
00055 *          first sub-diagonal is not referenced.
00056 *
00057 *  LDA     (input) INTEGER
00058 *          The leading dimension of the array A.  LDA >= max(N,1).
00059 *
00060 *  WORK    (workspace) REAL array, dimension (MAX(1,LWORK)),
00061 *          where LWORK >= N when NORM = 'I'; otherwise, WORK is not
00062 *          referenced.
00063 *
00064 * =====================================================================
00065 *
00066 *     .. Parameters ..
00067       REAL               ONE, ZERO
00068       PARAMETER          ( ONE = 1.0E+0, ZERO = 0.0E+0 )
00069 *     ..
00070 *     .. Local Scalars ..
00071       INTEGER            I, J
00072       REAL               SCALE, SUM, VALUE
00073 *     ..
00074 *     .. External Functions ..
00075       LOGICAL            LSAME
00076       EXTERNAL           LSAME
00077 *     ..
00078 *     .. External Subroutines ..
00079       EXTERNAL           CLASSQ
00080 *     ..
00081 *     .. Intrinsic Functions ..
00082       INTRINSIC          ABS, MAX, MIN, SQRT
00083 *     ..
00084 *     .. Executable Statements ..
00085 *
00086       IF( N.EQ.0 ) THEN
00087          VALUE = ZERO
00088       ELSE IF( LSAME( NORM, 'M' ) ) THEN
00089 *
00090 *        Find max(abs(A(i,j))).
00091 *
00092          VALUE = ZERO
00093          DO 20 J = 1, N
00094             DO 10 I = 1, MIN( N, J+1 )
00095                VALUE = MAX( VALUE, ABS( A( I, J ) ) )
00096    10       CONTINUE
00097    20    CONTINUE
00098       ELSE IF( ( LSAME( NORM, 'O' ) ) .OR. ( NORM.EQ.'1' ) ) THEN
00099 *
00100 *        Find norm1(A).
00101 *
00102          VALUE = ZERO
00103          DO 40 J = 1, N
00104             SUM = ZERO
00105             DO 30 I = 1, MIN( N, J+1 )
00106                SUM = SUM + ABS( A( I, J ) )
00107    30       CONTINUE
00108             VALUE = MAX( VALUE, SUM )
00109    40    CONTINUE
00110       ELSE IF( LSAME( NORM, 'I' ) ) THEN
00111 *
00112 *        Find normI(A).
00113 *
00114          DO 50 I = 1, N
00115             WORK( I ) = ZERO
00116    50    CONTINUE
00117          DO 70 J = 1, N
00118             DO 60 I = 1, MIN( N, J+1 )
00119                WORK( I ) = WORK( I ) + ABS( A( I, J ) )
00120    60       CONTINUE
00121    70    CONTINUE
00122          VALUE = ZERO
00123          DO 80 I = 1, N
00124             VALUE = MAX( VALUE, WORK( I ) )
00125    80    CONTINUE
00126       ELSE IF( ( LSAME( NORM, 'F' ) ) .OR. ( LSAME( NORM, 'E' ) ) ) THEN
00127 *
00128 *        Find normF(A).
00129 *
00130          SCALE = ZERO
00131          SUM = ONE
00132          DO 90 J = 1, N
00133             CALL CLASSQ( MIN( N, J+1 ), A( 1, J ), 1, SCALE, SUM )
00134    90    CONTINUE
00135          VALUE = SCALE*SQRT( SUM )
00136       END IF
00137 *
00138       CLANHS = VALUE
00139       RETURN
00140 *
00141 *     End of CLANHS
00142 *
00143       END
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