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SUBROUTINE ZGET52( LEFT, N, A, LDA, B, LDB, E, LDE, ALPHA, BETA,
$ WORK, RWORK, RESULT ) * * -- LAPACK test routine (version 3.1) -- * Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. * November 2006 * * .. Scalar Arguments .. LOGICAL LEFT INTEGER LDA, LDB, LDE, N * .. * .. Array Arguments .. DOUBLE PRECISION RESULT( 2 ), RWORK( * ) COMPLEX*16 A( LDA, * ), ALPHA( * ), B( LDB, * ), $ BETA( * ), E( LDE, * ), WORK( * ) * .. * * Purpose * ======= * * ZGET52 does an eigenvector check for the generalized eigenvalue * problem. * * The basic test for right eigenvectors is: * * | b(i) A E(i) - a(i) B E(i) | * RESULT(1) = max ------------------------------- * i n ulp max( |b(i) A|, |a(i) B| ) * * using the 1-norm. Here, a(i)/b(i) = w is the i-th generalized * eigenvalue of A - w B, or, equivalently, b(i)/a(i) = m is the i-th * generalized eigenvalue of m A - B. * * H H _ _ * For left eigenvectors, A , B , a, and b are used. * * ZGET52 also tests the normalization of E. Each eigenvector is * supposed to be normalized so that the maximum "absolute value" * of its elements is 1, where in this case, "absolute value" * of a complex value x is |Re(x)| + |Im(x)| ; let us call this * maximum "absolute value" norm of a vector v M(v). * If a(i)=b(i)=0, then the eigenvector is set to be the jth coordinate * vector. The normalization test is: * * RESULT(2) = max | M(v(i)) - 1 | / ( n ulp ) * eigenvectors v(i) * * * Arguments * ========= * * LEFT (input) LOGICAL * =.TRUE.: The eigenvectors in the columns of E are assumed * to be *left* eigenvectors. * =.FALSE.: The eigenvectors in the columns of E are assumed * to be *right* eigenvectors. * * N (input) INTEGER * The size of the matrices. If it is zero, ZGET52 does * nothing. It must be at least zero. * * A (input) COMPLEX*16 array, dimension (LDA, N) * The matrix A. * * LDA (input) INTEGER * The leading dimension of A. It must be at least 1 * and at least N. * * B (input) COMPLEX*16 array, dimension (LDB, N) * The matrix B. * * LDB (input) INTEGER * The leading dimension of B. It must be at least 1 * and at least N. * * E (input) COMPLEX*16 array, dimension (LDE, N) * The matrix of eigenvectors. It must be O( 1 ). * * LDE (input) INTEGER * The leading dimension of E. It must be at least 1 and at * least N. * * ALPHA (input) COMPLEX*16 array, dimension (N) * The values a(i) as described above, which, along with b(i), * define the generalized eigenvalues. * * BETA (input) COMPLEX*16 array, dimension (N) * The values b(i) as described above, which, along with a(i), * define the generalized eigenvalues. * * WORK (workspace) COMPLEX*16 array, dimension (N**2) * * RWORK (workspace) DOUBLE PRECISION array, dimension (N) * * RESULT (output) DOUBLE PRECISION array, dimension (2) * The values computed by the test described above. If A E or * B E is likely to overflow, then RESULT(1:2) is set to * 10 / ulp. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) COMPLEX*16 CZERO, CONE PARAMETER ( CZERO = ( 0.0D+0, 0.0D+0 ), $ CONE = ( 1.0D+0, 0.0D+0 ) ) * .. * .. Local Scalars .. CHARACTER NORMAB, TRANS INTEGER J, JVEC DOUBLE PRECISION ABMAX, ALFMAX, ANORM, BETMAX, BNORM, ENORM, $ ENRMER, ERRNRM, SAFMAX, SAFMIN, SCALE, TEMP1, $ ULP COMPLEX*16 ACOEFF, ALPHAI, BCOEFF, BETAI, X * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, ZLANGE EXTERNAL DLAMCH, ZLANGE * .. * .. External Subroutines .. EXTERNAL ZGEMV * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, DCONJG, DIMAG, MAX * .. * .. Statement Functions .. DOUBLE PRECISION ABS1 * .. * .. Statement Function definitions .. ABS1( X ) = ABS( DBLE( X ) ) + ABS( DIMAG( X ) ) * .. * .. Executable Statements .. * RESULT( 1 ) = ZERO RESULT( 2 ) = ZERO IF( N.LE.0 ) $ RETURN * SAFMIN = DLAMCH( 'Safe minimum' ) SAFMAX = ONE / SAFMIN ULP = DLAMCH( 'Epsilon' )*DLAMCH( 'Base' ) * IF( LEFT ) THEN TRANS = 'C' NORMAB = 'I' ELSE TRANS = 'N' NORMAB = 'O' END IF * * Norm of A, B, and E: * ANORM = MAX( ZLANGE( NORMAB, N, N, A, LDA, RWORK ), SAFMIN ) BNORM = MAX( ZLANGE( NORMAB, N, N, B, LDB, RWORK ), SAFMIN ) ENORM = MAX( ZLANGE( 'O', N, N, E, LDE, RWORK ), ULP ) ALFMAX = SAFMAX / MAX( ONE, BNORM ) BETMAX = SAFMAX / MAX( ONE, ANORM ) * * Compute error matrix. * Column i = ( b(i) A - a(i) B ) E(i) / max( |a(i) B| |b(i) A| ) * DO 10 JVEC = 1, N ALPHAI = ALPHA( JVEC ) BETAI = BETA( JVEC ) ABMAX = MAX( ABS1( ALPHAI ), ABS1( BETAI ) ) IF( ABS1( ALPHAI ).GT.ALFMAX .OR. ABS1( BETAI ).GT.BETMAX .OR. $ ABMAX.LT.ONE ) THEN SCALE = ONE / MAX( ABMAX, SAFMIN ) ALPHAI = SCALE*ALPHAI BETAI = SCALE*BETAI END IF SCALE = ONE / MAX( ABS1( ALPHAI )*BNORM, ABS1( BETAI )*ANORM, $ SAFMIN ) ACOEFF = SCALE*BETAI BCOEFF = SCALE*ALPHAI IF( LEFT ) THEN ACOEFF = DCONJG( ACOEFF ) BCOEFF = DCONJG( BCOEFF ) END IF CALL ZGEMV( TRANS, N, N, ACOEFF, A, LDA, E( 1, JVEC ), 1, $ CZERO, WORK( N*( JVEC-1 )+1 ), 1 ) CALL ZGEMV( TRANS, N, N, -BCOEFF, B, LDA, E( 1, JVEC ), 1, $ CONE, WORK( N*( JVEC-1 )+1 ), 1 ) 10 CONTINUE * ERRNRM = ZLANGE( 'One', N, N, WORK, N, RWORK ) / ENORM * * Compute RESULT(1) * RESULT( 1 ) = ERRNRM / ULP * * Normalization of E: * ENRMER = ZERO DO 30 JVEC = 1, N TEMP1 = ZERO DO 20 J = 1, N TEMP1 = MAX( TEMP1, ABS1( E( J, JVEC ) ) ) 20 CONTINUE ENRMER = MAX( ENRMER, TEMP1-ONE ) 30 CONTINUE * * Compute RESULT(2) : the normalization error in E. * RESULT( 2 ) = ENRMER / ( DBLE( N )*ULP ) * RETURN * * End of ZGET52 * END |