#include "blaswrap.h" /* -- translated by f2c (version 19990503). You must link the resulting object file with the libraries: -lf2c -lm (in that order) */ #include "f2c.h" /* Common Block Declarations */ struct { doublereal ops, itcnt; } latime_; #define latime_1 latime_ /* Table of constant values */ static integer c__1 = 1; /* Subroutine */ int dlaein_(logical *rightv, logical *noinit, integer *n, doublereal *h__, integer *ldh, doublereal *wr, doublereal *wi, doublereal *vr, doublereal *vi, doublereal *b, integer *ldb, doublereal *work, doublereal *eps3, doublereal *smlnum, doublereal * bignum, integer *info) { /* System generated locals */ integer b_dim1, b_offset, h_dim1, h_offset, i__1, i__2, i__3, i__4; doublereal d__1, d__2, d__3, d__4; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ static integer ierr; static doublereal temp, norm, vmax, opst; extern doublereal dnrm2_(integer *, doublereal *, integer *); static integer i__, j; extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *, integer *); static doublereal scale, w, x, y; extern doublereal dasum_(integer *, doublereal *, integer *); static char trans[1]; static doublereal vcrit; static integer i1, i2, i3; static doublereal rootn, vnorm, w1; extern doublereal dlapy2_(doublereal *, doublereal *); static doublereal ei, ej, absbii, absbjj, xi; extern integer idamax_(integer *, doublereal *, integer *); extern /* Subroutine */ int dladiv_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); static doublereal xr; extern /* Subroutine */ int dlatrs_(char *, char *, char *, char *, integer *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, integer *); static char normin[1]; static doublereal nrmsml, growto, rec; static integer its; #define b_ref(a_1,a_2) b[(a_2)*b_dim1 + a_1] #define h___ref(a_1,a_2) h__[(a_2)*h_dim1 + a_1] /* -- LAPACK auxiliary routine (instrumented to count operations) -- Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., Courant Institute, Argonne National Lab, and Rice University September 30, 1994 Common block to return operation count. Purpose ======= DLAEIN uses inverse iteration to find a right or left eigenvector corresponding to the eigenvalue (WR,WI) of a real upper Hessenberg matrix H. Arguments ========= RIGHTV (input) LOGICAL = .TRUE. : compute right eigenvector; = .FALSE.: compute left eigenvector. NOINIT (input) LOGICAL = .TRUE. : no initial vector supplied in (VR,VI). = .FALSE.: initial vector supplied in (VR,VI). N (input) INTEGER The order of the matrix H. N >= 0. H (input) DOUBLE PRECISION array, dimension (LDH,N) The upper Hessenberg matrix H. LDH (input) INTEGER The leading dimension of the array H. LDH >= max(1,N). WR (input) DOUBLE PRECISION WI (input) DOUBLE PRECISION The real and imaginary parts of the eigenvalue of H whose corresponding right or left eigenvector is to be computed. VR (input/output) DOUBLE PRECISION array, dimension (N) VI (input/output) DOUBLE PRECISION array, dimension (N) On entry, if NOINIT = .FALSE. and WI = 0.0, VR must contain a real starting vector for inverse iteration using the real eigenvalue WR; if NOINIT = .FALSE. and WI.ne.0.0, VR and VI must contain the real and imaginary parts of a complex starting vector for inverse iteration using the complex eigenvalue (WR,WI); otherwise VR and VI need not be set. On exit, if WI = 0.0 (real eigenvalue), VR contains the computed real eigenvector; if WI.ne.0.0 (complex eigenvalue), VR and VI contain the real and imaginary parts of the computed complex eigenvector. The eigenvector is normalized so that the component of largest magnitude has magnitude 1; here the magnitude of a complex number (x,y) is taken to be |x| + |y|. VI is not referenced if WI = 0.0. B (workspace) DOUBLE PRECISION array, dimension (LDB,N) LDB (input) INTEGER The leading dimension of the array B. LDB >= N+1. WORK (workspace) DOUBLE PRECISION array, dimension (N) EPS3 (input) DOUBLE PRECISION A small machine-dependent value which is used to perturb close eigenvalues, and to replace zero pivots. SMLNUM (input) DOUBLE PRECISION A machine-dependent value close to the underflow threshold. BIGNUM (input) DOUBLE PRECISION A machine-dependent value close to the overflow threshold. INFO (output) INTEGER = 0: successful exit = 1: inverse iteration did not converge; VR is set to the last iterate, and so is VI if WI.ne.0.0. ===================================================================== Parameter adjustments */ h_dim1 = *ldh; h_offset = 1 + h_dim1 * 1; h__ -= h_offset; --vr; --vi; b_dim1 = *ldb; b_offset = 1 + b_dim1 * 1; b -= b_offset; --work; /* Function Body */ *info = 0; /* ** Initialize */ opst = 0.; /* ** GROWTO is the threshold used in the acceptance test for an eigenvector. */ rootn = sqrt((doublereal) (*n)); growto = .1 / rootn; /* Computing MAX */ d__1 = 1., d__2 = *eps3 * rootn; nrmsml = max(d__1,d__2) * *smlnum; /* ** Increment op count for computing ROOTN, GROWTO and NRMSML */ opst += 4; /* ** Form B = H - (WR,WI)*I (except that the subdiagonal elements and the imaginary parts of the diagonal elements are not stored). */ i__1 = *n; for (j = 1; j <= i__1; ++j) { i__2 = j - 1; for (i__ = 1; i__ <= i__2; ++i__) { b_ref(i__, j) = h___ref(i__, j); /* L10: */ } b_ref(j, j) = h___ref(j, j) - *wr; /* L20: */ } /* ** */ opst += *n; /* ** */ if (*wi == 0.) { /* Real eigenvalue. */ if (*noinit) { /* Set initial vector. */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { vr[i__] = *eps3; /* L30: */ } } else { /* Scale supplied initial vector. */ vnorm = dnrm2_(n, &vr[1], &c__1); d__1 = *eps3 * rootn / max(vnorm,nrmsml); dscal_(n, &d__1, &vr[1], &c__1); /* ** */ opst += *n * 3 + 2; /* ** */ } if (*rightv) { /* LU decomposition with partial pivoting of B, replacing zero pivots by EPS3. */ i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { ei = h___ref(i__ + 1, i__); if ((d__1 = b_ref(i__, i__), abs(d__1)) < abs(ei)) { /* Interchange rows and eliminate. */ x = b_ref(i__, i__) / ei; b_ref(i__, i__) = ei; i__2 = *n; for (j = i__ + 1; j <= i__2; ++j) { temp = b_ref(i__ + 1, j); b_ref(i__ + 1, j) = b_ref(i__, j) - x * temp; b_ref(i__, j) = temp; /* L40: */ } } else { /* Eliminate without interchange. */ if (b_ref(i__, i__) == 0.) { b_ref(i__, i__) = *eps3; } x = ei / b_ref(i__, i__); if (x != 0.) { i__2 = *n; for (j = i__ + 1; j <= i__2; ++j) { b_ref(i__ + 1, j) = b_ref(i__ + 1, j) - x * b_ref( i__, j); /* L50: */ } } } /* L60: */ } if (b_ref(*n, *n) == 0.) { b_ref(*n, *n) = *eps3; } /* ** Increment op count for LU decomposition */ latime_1.ops += (*n - 1) * (*n + 1); /* ** */ *(unsigned char *)trans = 'N'; } else { /* UL decomposition with partial pivoting of B, replacing zero pivots by EPS3. */ for (j = *n; j >= 2; --j) { ej = h___ref(j, j - 1); if ((d__1 = b_ref(j, j), abs(d__1)) < abs(ej)) { /* Interchange columns and eliminate. */ x = b_ref(j, j) / ej; b_ref(j, j) = ej; i__1 = j - 1; for (i__ = 1; i__ <= i__1; ++i__) { temp = b_ref(i__, j - 1); b_ref(i__, j - 1) = b_ref(i__, j) - x * temp; b_ref(i__, j) = temp; /* L70: */ } } else { /* Eliminate without interchange. */ if (b_ref(j, j) == 0.) { b_ref(j, j) = *eps3; } x = ej / b_ref(j, j); if (x != 0.) { i__1 = j - 1; for (i__ = 1; i__ <= i__1; ++i__) { b_ref(i__, j - 1) = b_ref(i__, j - 1) - x * b_ref( i__, j); /* L80: */ } } } /* L90: */ } if (b_ref(1, 1) == 0.) { b_ref(1, 1) = *eps3; } /* ** Increment op count for UL decomposition */ latime_1.ops += (*n - 1) * (*n + 1); /* ** */ *(unsigned char *)trans = 'T'; } *(unsigned char *)normin = 'N'; i__1 = *n; for (its = 1; its <= i__1; ++its) { /* Solve U*x = scale*v for a right eigenvector or U'*x = scale*v for a left eigenvector, overwriting x on v. */ dlatrs_("Upper", trans, "Nonunit", normin, n, &b[b_offset], ldb, & vr[1], &scale, &work[1], &ierr); /* ** Increment opcount for triangular solver, assuming that ops DLATRS = ops DTRSV, with no scaling in DLATRS. */ latime_1.ops += *n * *n; /* ** */ *(unsigned char *)normin = 'Y'; /* Test for sufficient growth in the norm of v. */ vnorm = dasum_(n, &vr[1], &c__1); /* ** */ opst += *n; /* ** */ if (vnorm >= growto * scale) { goto L120; } /* Choose new orthogonal starting vector and try again. */ temp = *eps3 / (rootn + 1.); vr[1] = *eps3; i__2 = *n; for (i__ = 2; i__ <= i__2; ++i__) { vr[i__] = temp; /* L100: */ } vr[*n - its + 1] -= *eps3 * rootn; /* ** */ opst += 4; /* ** L110: */ } /* Failure to find eigenvector in N iterations. */ *info = 1; L120: /* Normalize eigenvector. */ i__ = idamax_(n, &vr[1], &c__1); d__2 = 1. / (d__1 = vr[i__], abs(d__1)); dscal_(n, &d__2, &vr[1], &c__1); /* ** */ opst += (*n << 1) + 1; /* ** */ } else { /* Complex eigenvalue. */ if (*noinit) { /* Set initial vector. */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { vr[i__] = *eps3; vi[i__] = 0.; /* L130: */ } } else { /* Scale supplied initial vector. */ d__1 = dnrm2_(n, &vr[1], &c__1); d__2 = dnrm2_(n, &vi[1], &c__1); norm = dlapy2_(&d__1, &d__2); rec = *eps3 * rootn / max(norm,nrmsml); dscal_(n, &rec, &vr[1], &c__1); dscal_(n, &rec, &vi[1], &c__1); /* ** */ opst += *n * 6 + 5; /* ** */ } if (*rightv) { /* LU decomposition with partial pivoting of B, replacing zero pivots by EPS3. The imaginary part of the (i,j)-th element of U is stored in B(j+1,i). */ b_ref(2, 1) = -(*wi); i__1 = *n; for (i__ = 2; i__ <= i__1; ++i__) { b_ref(i__ + 1, 1) = 0.; /* L140: */ } i__1 = *n - 1; for (i__ = 1; i__ <= i__1; ++i__) { absbii = dlapy2_(&b_ref(i__, i__), &b_ref(i__ + 1, i__)); ei = h___ref(i__ + 1, i__); if (absbii < abs(ei)) { /* Interchange rows and eliminate. */ xr = b_ref(i__, i__) / ei; xi = b_ref(i__ + 1, i__) / ei; b_ref(i__, i__) = ei; b_ref(i__ + 1, i__) = 0.; i__2 = *n; for (j = i__ + 1; j <= i__2; ++j) { temp = b_ref(i__ + 1, j); b_ref(i__ + 1, j) = b_ref(i__, j) - xr * temp; b_ref(j + 1, i__ + 1) = b_ref(j + 1, i__) - xi * temp; b_ref(i__, j) = temp; b_ref(j + 1, i__) = 0.; /* L150: */ } b_ref(i__ + 2, i__) = -(*wi); b_ref(i__ + 1, i__ + 1) = b_ref(i__ + 1, i__ + 1) - xi * * wi; b_ref(i__ + 2, i__ + 1) = b_ref(i__ + 2, i__ + 1) + xr * * wi; /* ** */ opst += (*n - i__ << 2) + 6; /* ** */ } else { /* Eliminate without interchanging rows. */ if (absbii == 0.) { b_ref(i__, i__) = *eps3; b_ref(i__ + 1, i__) = 0.; absbii = *eps3; } ei = ei / absbii / absbii; xr = b_ref(i__, i__) * ei; xi = -b_ref(i__ + 1, i__) * ei; i__2 = *n; for (j = i__ + 1; j <= i__2; ++j) { b_ref(i__ + 1, j) = b_ref(i__ + 1, j) - xr * b_ref( i__, j) + xi * b_ref(j + 1, i__); b_ref(j + 1, i__ + 1) = -xr * b_ref(j + 1, i__) - xi * b_ref(i__, j); /* L160: */ } b_ref(i__ + 2, i__ + 1) = b_ref(i__ + 2, i__ + 1) - *wi; /* ** */ opst += (*n - i__) * 7 + 4; /* ** */ } /* Compute 1-norm of offdiagonal elements of i-th row. */ i__2 = *n - i__; i__3 = *n - i__; work[i__] = dasum_(&i__2, &b_ref(i__, i__ + 1), ldb) + dasum_( &i__3, &b_ref(i__ + 2, i__), &c__1); /* ** */ opst += (*n - i__ << 1) + 4; /* ** L170: */ } if (b_ref(*n, *n) == 0. && b_ref(*n + 1, *n) == 0.) { b_ref(*n, *n) = *eps3; } work[*n] = 0.; i1 = *n; i2 = 1; i3 = -1; } else { /* UL decomposition with partial pivoting of conjg(B), replacing zero pivots by EPS3. The imaginary part of the (i,j)-th element of U is stored in B(j+1,i). */ b_ref(*n + 1, *n) = *wi; i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { b_ref(*n + 1, j) = 0.; /* L180: */ } for (j = *n; j >= 2; --j) { ej = h___ref(j, j - 1); absbjj = dlapy2_(&b_ref(j, j), &b_ref(j + 1, j)); if (absbjj < abs(ej)) { /* Interchange columns and eliminate */ xr = b_ref(j, j) / ej; xi = b_ref(j + 1, j) / ej; b_ref(j, j) = ej; b_ref(j + 1, j) = 0.; i__1 = j - 1; for (i__ = 1; i__ <= i__1; ++i__) { temp = b_ref(i__, j - 1); b_ref(i__, j - 1) = b_ref(i__, j) - xr * temp; b_ref(j, i__) = b_ref(j + 1, i__) - xi * temp; b_ref(i__, j) = temp; b_ref(j + 1, i__) = 0.; /* L190: */ } b_ref(j + 1, j - 1) = *wi; b_ref(j - 1, j - 1) = b_ref(j - 1, j - 1) + xi * *wi; b_ref(j, j - 1) = b_ref(j, j - 1) - xr * *wi; /* ** */ opst += (j - 1 << 2) + 6; /* ** */ } else { /* Eliminate without interchange. */ if (absbjj == 0.) { b_ref(j, j) = *eps3; b_ref(j + 1, j) = 0.; absbjj = *eps3; } ej = ej / absbjj / absbjj; xr = b_ref(j, j) * ej; xi = -b_ref(j + 1, j) * ej; i__1 = j - 1; for (i__ = 1; i__ <= i__1; ++i__) { b_ref(i__, j - 1) = b_ref(i__, j - 1) - xr * b_ref( i__, j) + xi * b_ref(j + 1, i__); b_ref(j, i__) = -xr * b_ref(j + 1, i__) - xi * b_ref( i__, j); /* L200: */ } b_ref(j, j - 1) = b_ref(j, j - 1) + *wi; /* ** */ opst += (j - 1) * 7 + 4; /* ** */ } /* Compute 1-norm of offdiagonal elements of j-th column. */ i__1 = j - 1; i__2 = j - 1; work[j] = dasum_(&i__1, &b_ref(1, j), &c__1) + dasum_(&i__2, & b_ref(j + 1, 1), ldb); /* ** */ opst += (j - 1 << 1) + 4; /* ** L210: */ } if (b_ref(1, 1) == 0. && b_ref(2, 1) == 0.) { b_ref(1, 1) = *eps3; } work[1] = 0.; i1 = 1; i2 = *n; i3 = 1; } i__1 = *n; for (its = 1; its <= i__1; ++its) { scale = 1.; vmax = 1.; vcrit = *bignum; /* Solve U*(xr,xi) = scale*(vr,vi) for a right eigenvector, or U'*(xr,xi) = scale*(vr,vi) for a left eigenvector, overwriting (xr,xi) on (vr,vi). */ i__2 = i2; i__3 = i3; for (i__ = i1; i__3 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__3) { if (work[i__] > vcrit) { rec = 1. / vmax; dscal_(n, &rec, &vr[1], &c__1); dscal_(n, &rec, &vi[1], &c__1); scale *= rec; vmax = 1.; vcrit = *bignum; } xr = vr[i__]; xi = vi[i__]; if (*rightv) { i__4 = *n; for (j = i__ + 1; j <= i__4; ++j) { xr = xr - b_ref(i__, j) * vr[j] + b_ref(j + 1, i__) * vi[j]; xi = xi - b_ref(i__, j) * vi[j] - b_ref(j + 1, i__) * vr[j]; /* L220: */ } } else { i__4 = i__ - 1; for (j = 1; j <= i__4; ++j) { xr = xr - b_ref(j, i__) * vr[j] + b_ref(i__ + 1, j) * vi[j]; xi = xi - b_ref(j, i__) * vi[j] - b_ref(i__ + 1, j) * vr[j]; /* L230: */ } } w = (d__1 = b_ref(i__, i__), abs(d__1)) + (d__2 = b_ref(i__ + 1, i__), abs(d__2)); if (w > *smlnum) { if (w < 1.) { w1 = abs(xr) + abs(xi); if (w1 > w * *bignum) { rec = 1. / w1; dscal_(n, &rec, &vr[1], &c__1); dscal_(n, &rec, &vi[1], &c__1); xr = vr[i__]; xi = vi[i__]; scale *= rec; vmax *= rec; } } /* Divide by diagonal element of B. */ dladiv_(&xr, &xi, &b_ref(i__, i__), &b_ref(i__ + 1, i__), &vr[i__], &vi[i__]); /* Computing MAX */ d__3 = (d__1 = vr[i__], abs(d__1)) + (d__2 = vi[i__], abs( d__2)); vmax = max(d__3,vmax); vcrit = *bignum / vmax; /* ** */ opst += 9; /* ** */ } else { i__4 = *n; for (j = 1; j <= i__4; ++j) { vr[j] = 0.; vi[j] = 0.; /* L240: */ } vr[i__] = 1.; vi[i__] = 1.; scale = 0.; vmax = 1.; vcrit = *bignum; } /* L250: */ } /* ** Increment op count for loop 260, assuming no scaling */ latime_1.ops += (*n << 2) * (*n - 1); /* ** Test for sufficient growth in the norm of (VR,VI). */ vnorm = dasum_(n, &vr[1], &c__1) + dasum_(n, &vi[1], &c__1); /* ** */ opst += *n << 1; /* ** */ if (vnorm >= growto * scale) { goto L280; } /* Choose a new orthogonal starting vector and try again. */ y = *eps3 / (rootn + 1.); vr[1] = *eps3; vi[1] = 0.; i__3 = *n; for (i__ = 2; i__ <= i__3; ++i__) { vr[i__] = y; vi[i__] = 0.; /* L260: */ } vr[*n - its + 1] -= *eps3 * rootn; /* ** */ opst += 4; /* ** L270: */ } /* Failure to find eigenvector in N iterations */ *info = 1; L280: /* Normalize eigenvector. */ vnorm = 0.; i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { /* Computing MAX */ d__3 = vnorm, d__4 = (d__1 = vr[i__], abs(d__1)) + (d__2 = vi[i__] , abs(d__2)); vnorm = max(d__3,d__4); /* L290: */ } d__1 = 1. / vnorm; dscal_(n, &d__1, &vr[1], &c__1); d__1 = 1. / vnorm; dscal_(n, &d__1, &vi[1], &c__1); /* ** */ opst += (*n << 2) + 1; /* ** */ } /* ** Compute final op count */ latime_1.ops += opst; /* ** */ return 0; /* End of DLAEIN */ } /* dlaein_ */ #undef h___ref #undef b_ref