program cndrv4 c c ... Construct matrices A and M in LAPACK-style band form. c Matries A and M are derived from the finite c element discretization of the 1-dimensional c convection-diffusion operator c (d^2u/dx^2) + rho*(du/dx) c on the interval [0,1] with zero boundary condition using c piecewise linear elements. c c ... Call CNBAND to find eigenvalues LAMBDA such that c A*x = M*x*LAMBDA. c c ... Use mode 3 of CNAUPD. c c\BeginLib c c\Routines called: c cnband ARPACK banded eigenproblem solver. c slapy2 LAPACK routine to compute sqrt(x**2+y**2) carefully. c claset LAPACK routine to initialize a matrix to zero. c caxpy Level 1 BLAS that computes y <- alpha*x+y. c scnrm2 Level 1 BLAS that computes the norm of a vector. c cgbmv Level 2 BLAS that computes the band matrix vector product. c c\Author c Richard Lehoucq c Danny Sorensen c Chao Yang c Dept. of Computational & c Applied Mathematics c Rice University c Houston, Texas c c\SCCS Information: @(#) c FILE: nbdr4.F SID: 2.5 DATE OF SID: 10/17/00 RELEASE: 2 c c\Remarks c 1. None c c\EndLib c c------------------------------------------------------------------------- c c %-------------------------------------% c | Define leading dimensions for all | c | arrays. | c | MAXN - Maximum size of the matrix | c | MAXNEV - Maximum number of | c | eigenvalues to be computed | c | MAXNCV - Maximum number of Arnoldi | c | vectors stored | c | MAXBDW - Maximum bandwidth | c %-------------------------------------% c integer maxn, maxnev, maxncv, maxbdw, lda, & lworkl, ldv parameter ( maxn = 1000, maxnev = 25, maxncv=50, & maxbdw=50, lda = maxbdw, ldv = maxn) c c %--------------% c | Local Arrays | c %--------------% c integer iparam(11), iwork(maxn) logical select(maxncv) Complex & a(lda,maxn), m(lda,maxn), fac(lda,maxn), & workl(3*maxncv*maxncv+5*maxncv), workd(3*maxn), & workev(2*maxncv), v(ldv, maxncv), & resid(maxn), d(maxncv), ax(maxn), mx(maxn) Real & rwork(maxn), rd(maxncv,3) c c %---------------% c | Local Scalars | c %---------------% c character which*2, bmat integer nev, ncv, ku, kl, info, j, & n, idiag, isup, isub, maxitr, mode, & nconv logical rvec Real & tol Complex & rho, h, sigma c c %------------% c | Parameters | c %------------% c Complex & one, zero, two, four, six parameter (one = (1.0E+0, 0.0E+0) , & zero = (0.0E+0, 0.0E+0) , & two = (2.0E+0, 0.0E+0) , & four = (4.0E+0, 0.0E+0) , & six = (6.0E+0, 0.0E+0) ) c c %-----------------------------% c | BLAS & LAPACK routines used | c %-----------------------------% c Real & scnrm2, slapy2 external scnrm2, cgbmv, caxpy, slapy2, claset c c %-----------------------% c | Executable Statements | c %-----------------------% c c %-------------------------------------------------% c | The number NX is the number of interior points | c | in the discretization of the 2-dimensional | c | convection-diffusion operator on the unit | c | square with zero Dirichlet boundary condition. | c | The number N(=NX*NX) is the dimension of the | c | matrix. A generalized eigenvalue problem is | c | solved (BMAT = 'G'). NEV is the number of | c | eigenvalues (closest to the shift SIGMA) to be | c | approximated. Since the shift and invert mode | c | is used, WHICH is set to 'LM'. The user can | c | modify NX, NEV and NCV to solve problems of | c | different sizes, and to get different parts the | c | spectrum. However, the following conditions | c | must be satisfied: | c | N <= MAXN | c | NEV <= MAXNEV | c | NEV + 2 <= NCV <= MAXNCV | c %-------------------------------------------------% c n = 100 nev = 4 ncv = 10 if ( n .gt. maxn ) then print *, ' ERROR with _NBDR4: N is greater than MAXN ' go to 9000 else if ( nev .gt. maxnev ) then print *, ' ERROR with _NBDR4: NEV is greater than MAXNEV ' go to 9000 else if ( ncv .gt. maxncv ) then print *, ' ERROR with _NBDR4: NCV is greater than MAXNCV ' go to 9000 end if bmat = 'G' which = 'LM' sigma = (1.0E+1, 0.0E+0) c c %----------------------------------------------------% c | The work array WORKL is used in CNAUPD as | c | workspace. Its dimension LWORKL has to be set as | c | illustrated below. The parameter TOL determines | c | the stopping criterion. If TOL<=0, machine machine | c | precision is used. Setting INFO=0 indicates that | c | we using a randomly generated vector to start the | c | the ARNOLDI process. | c %----------------------------------------------------% c lworkl = 3*ncv**2+5*ncv info = 0 tol = 0.0 c c %---------------------------------------------------% c | IPARAm(3) specifies the maximum number of Arnoldi | c | iterations allowed. Mode 3 of CNAUPD is used | c | (IPARAm(7) = 3). All these options can be changed | c | by the user. For details, see the documentation | c | in cnband. | c %---------------------------------------------------% c maxitr = 300 mode = 3 c iparam(3) = maxitr iparam(7) = mode c c %--------------------------------------------% c | Construct matrices A and M in LAPACK-style | c | banded form. | c %--------------------------------------------% c c %---------------------------------------------% c | Zero out the workspace for banded matrices. | c %---------------------------------------------% c call claset('A', lda, n, zero, zero, a, lda) call claset('A', lda, n, zero, zero, m, lda) call claset('A', lda, n, zero, zero, fac, lda) c c %-------------------------------------% c | KU, KL are number of superdiagonals | c | and subdiagonals within the band of | c | matrices A and M. | c %-------------------------------------% c kl = 1 ku = 1 c c %---------------% c | Main diagonal | c %---------------% c h = one / cmplx(n+1) idiag = kl+ku+1 do 30 j = 1, n a(idiag,j) = two / h m(idiag,j) = four * h / six 30 continue c c %-------------------------------------% c | First subdiagonal and superdiagonal | c %-------------------------------------% c isup = kl+ku isub = kl+ku+2 rho = (1.0E+1, 0.0E+0) do 40 j = 1, n-1 a(isup,j+1) = -one/h + rho/two a(isub,j) = -one/h - rho/two m(isup,j+1) = one*h / six m(isub,j) = one*h / six 40 continue c c %-----------------------------------------------% c | Call ARPACK banded solver to find eigenvalues | c | and eigenvectors. Eigenvalues are returned in | c | the one dimensional array D. Eigenvectors | c | are returned in the first NCONV (=IPARAM(5)) | c | columns of V. | c %-----------------------------------------------% c rvec = .true. call cnband(rvec, 'A', select, d, v, ldv, sigma, & workev, n, a, m, lda, fac, kl, ku, which, & bmat, nev, tol, resid, ncv, v, ldv, iparam, & workd, workl, lworkl, rwork, iwork, info) c if ( info .eq. 0) then c nconv = iparam(5) c c %-----------------------------------% c | Print out convergence information | c %-----------------------------------% c print *, ' ' print *, '_NBDR4 ' print *, '====== ' print *, ' ' print *, ' The size of the matrix is ', n print *, ' Number of eigenvalue requested is ', nev print *, ' The number of Arnoldi vectors generated', & ' (NCV) is ', ncv print *, ' The number of converged Ritz values is ', & nconv print *, ' What portion of the spectrum ', which print *, ' The number of Implicit Arnoldi ', & ' update taken is ', iparam(3) print *, ' The number of OP*x is ', iparam(9) print *, ' The convergence tolerance is ', tol print *, ' ' c do 90 j = 1, nconv c c %----------------------------% c | Compute the residual norm. | c | || A*x - lambda*x || | c %----------------------------% c call cgbmv('Notranspose', n, n, kl, ku, one, & a(kl+1,1), lda, v(1,j), 1, zero, & ax, 1) call cgbmv('Notranspose', n, n, kl, ku, one, & m(kl+1,1), lda, v(1,j), 1, zero, & mx, 1) call caxpy(n, -d(j), mx, 1, ax, 1) rd(j,1) = real (d(j)) rd(j,2) = aimag(d(j)) rd(j,3) = scnrm2(n, ax, 1) rd(j,3) = rd(j,3) / slapy2(rd(j,1), rd(j,2)) 90 continue call smout(6, nconv, 3, rd, maxncv, -6, & 'Ritz values (Real,Imag) and relative residuals') else c c %-------------------------------------% c | Either convergence failed, or there | c | is error. Check the documentation | c | for cnband. | c %-------------------------------------% c print *, ' ' print *, ' Error with _band, info= ', info print *, ' Check the documentation of _band ' print *, ' ' c end if c 9000 end