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DSYEVD Example Program in Fortran
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* =============================================================================
*
* DSYEVD Example.
* ==============
*
* Program computes all eigenvalues and eigenvectors of a real symmetric
* matrix A using divide and conquer algorithm, where A is:
*
* 6.39 0.13 -8.23 5.71 -3.18
* 0.13 8.37 -4.46 -6.10 7.21
* -8.23 -4.46 -9.58 -9.25 -7.42
* 5.71 -6.10 -9.25 3.72 8.54
* -3.18 7.21 -7.42 8.54 2.51
*
* Description.
* ============
*
* The routine computes all eigenvalues and, optionally, eigenvectors of an
* n-by-n real symmetric matrix A. The eigenvector v(j) of A satisfies
*
* A*v(j) = lambda(j)*v(j)
*
* where lambda(j) is its eigenvalue. The computed eigenvectors are
* orthonormal.
* If the eigenvectors are requested, then this routine uses a divide and
* conquer algorithm to compute eigenvalues and eigenvectors.
*
* Example Program Results.
* ========================
*
* DSYEVD Example Program Results
*
* Eigenvalues
* -17.44 -11.96 6.72 14.25 19.84
*
* Eigenvectors (stored columnwise)
* -0.26 0.31 -0.74 0.33 0.42
* -0.17 -0.39 -0.38 -0.80 0.16
* -0.89 0.04 0.09 0.03 -0.45
* -0.29 -0.59 0.34 0.31 0.60
* -0.19 0.63 0.44 -0.38 0.48
* =============================================================================
*
* .. Parameters ..
INTEGER N
PARAMETER ( N = 5 )
INTEGER LDA
PARAMETER ( LDA = N )
INTEGER LWMAX
PARAMETER ( LWMAX = 1000 )
*
* .. Local Scalars ..
INTEGER INFO, LWORK, LIWORK
*
* .. Local Arrays ..
INTEGER IWORK( LWMAX )
DOUBLE PRECISION A( LDA, N ), W( N ), WORK( LWMAX )
DATA A/
$ 6.39, 0.00, 0.00, 0.00, 0.00,
$ 0.13, 8.37, 0.00, 0.00, 0.00,
$ -8.23,-4.46,-9.58, 0.00, 0.00,
$ 5.71,-6.10,-9.25, 3.72, 0.00,
$ -3.18, 7.21,-7.42, 8.54, 2.51
$ /
*
* .. External Subroutines ..
EXTERNAL DSYEVD
EXTERNAL PRINT_MATRIX
*
* .. Intrinsic Functions ..
INTRINSIC INT, MIN
*
* .. Executable Statements ..
WRITE(*,*)'DSYEVD Example Program Results'
*
* Query the optimal workspace.
*
LWORK = -1
LIWORK = -1
CALL DSYEVD( 'Vectors', 'Upper', N, A, LDA, W, WORK, LWORK,
$ IWORK, LIWORK, INFO )
LWORK = MIN( LWMAX, INT( WORK( 1 ) ) )
LIWORK = MIN( LWMAX, IWORK( 1 ) )
*
* Solve eigenproblem.
*
CALL DSYEVD( 'Vectors', 'Upper', N, A, LDA, W, WORK, LWORK,
$ IWORK, LIWORK, INFO )
*
* Check for convergence.
*
IF( INFO.GT.0 ) THEN
WRITE(*,*)'The algorithm failed to compute eigenvalues.'
STOP
END IF
*
* Print eigenvalues.
*
CALL PRINT_MATRIX( 'Eigenvalues', 1, N, W, 1 )
*
* Print eigenvectors.
*
CALL PRINT_MATRIX( 'Eigenvectors (stored columnwise)', N, N, A,
$ LDA )
STOP
END
*
* End of DSYEVD Example.
*
* =============================================================================
*
* Auxiliary routine: printing a matrix.
*
SUBROUTINE PRINT_MATRIX( DESC, M, N, A, LDA )
CHARACTER*(*) DESC
INTEGER M, N, LDA
DOUBLE PRECISION A( LDA, * )
*
INTEGER I, J
*
WRITE(*,*)
WRITE(*,*) DESC
DO I = 1, M
WRITE(*,9998) ( A( I, J ), J = 1, N )
END DO
*
9998 FORMAT( 11(:,1X,F6.2) )
RETURN
END
Parent topic: DSYEVD Example