#include "clapack.h"
#include "f2cP.h"

/* Table of constant values */

static bool c_true = true;
static integer c__2 = 2;
static double c_b34 = 1.;
static integer c__1 = 1;
static double c_b36 = 0.;
static bool c_false = false;

/* Subroutine */ int dtgevc_(const char *side, const char *howmny, bool *select, 
	integer *n, double *s, integer *lds, double *p, integer *ldp, 
	double *vl, integer *ldvl, double *vr, integer *ldvr, integer 
	*mm, integer *m, double *work, integer *info)
{
    /* System generated locals */
    integer p_dim1, p_offset, s_dim1, s_offset, vl_dim1, vl_offset, vr_dim1, 
	    vr_offset, i__1, i__2, i__3, i__4, i__5;
    double d__1, d__2, d__3, d__4, d__5, d__6;

    /* Local variables */
    integer i__, j, ja, jc, je, na, im, jr, jw, nw;
    double big;
    bool lsa, lsb;
    double ulp, sum[4]	/* was [2][2] */;
    integer ibeg, ieig, iend;
    double dmin__, temp, xmax, sump[4]	/* was [2][2] */, sums[4]	
	    /* was [2][2] */;
    double cim2a, cim2b, cre2a, cre2b, temp2, bdiag[2], acoef, scale;
    bool ilall;
    integer iside;
    double sbeta;
    bool il2by2;
    integer iinfo;
    double small;
    bool compl_x; // djmw changed variable from "compl" to compl_x because the c++ compiler protested.
    double anorm, bnorm;
    bool compr;
    double temp2i;
    double temp2r;
    bool ilabad, ilbbad;
    double acoefa, bcoefa, cimaga, cimagb;
    bool ilback;
    double bcoefi, ascale, bscale, creala, crealb;
    double bcoefr, salfar, safmin;
    double xscale, bignum;
    bool ilcomp, ilcplx;
    integer ihwmny;


/*  -- LAPACK routine (version 3.1) -- */
/*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/*     November 2006 */

/*     .. Scalar Arguments .. */
/*     .. */
/*     .. Array Arguments .. */
/*     .. */


/*  Purpose */
/*  ======= */

/*  DTGEVC computes some or all of the right and/or left eigenvectors of */
/*  a pair of real matrices (S,P), where S is a quasi-triangular matrix */
/*  and P is upper triangular.  Matrix pairs of this type are produced by */
/*  the generalized Schur factorization of a matrix pair (A,B): */

/*     A = Q*S*Z**T,  B = Q*P*Z**T */

/*  as computed by DGGHRD + DHGEQZ. */

/*  The right eigenvector x and the left eigenvector y of (S,P) */
/*  corresponding to an eigenvalue w are defined by: */

/*     S*x = w*P*x,  (y**H)*S = w*(y**H)*P, */

/*  where y**H denotes the conjugate tranpose of y. */
/*  The eigenvalues are not input to this routine, but are computed */
/*  directly from the diagonal blocks of S and P. */

/*  This routine returns the matrices X and/or Y of right and left */
/*  eigenvectors of (S,P), or the products Z*X and/or Q*Y, */
/*  where Z and Q are input matrices. */
/*  If Q and Z are the orthogonal factors from the generalized Schur */
/*  factorization of a matrix pair (A,B), then Z*X and Q*Y */
/*  are the matrices of right and left eigenvectors of (A,B). */

/*  Arguments */
/*  ========= */

/*  SIDE    (input) CHARACTER*1 */
/*          = 'R': compute right eigenvectors only; */
/*          = 'L': compute left eigenvectors only; */
/*          = 'B': compute both right and left eigenvectors. */

/*  HOWMNY  (input) CHARACTER*1 */
/*          = 'A': compute all right and/or left eigenvectors; */
/*          = 'B': compute all right and/or left eigenvectors, */
/*                 backtransformed by the matrices in VR and/or VL; */
/*          = 'S': compute selected right and/or left eigenvectors, */
/*                 specified by the bool array SELECT. */

/*  SELECT  (input) LOGICAL array, dimension (N) */
/*          If HOWMNY='S', SELECT specifies the eigenvectors to be */
/*          computed.  If w(j) is a real eigenvalue, the corresponding */
/*          real eigenvector is computed if SELECT(j) is .TRUE.. */
/*          If w(j) and w(j+1) are the real and imaginary parts of a */
/*          complex eigenvalue, the corresponding complex eigenvector */
/*          is computed if either SELECT(j) or SELECT(j+1) is .TRUE., */
/*          and on exit SELECT(j) is set to .TRUE. and SELECT(j+1) is */
/*          set to .FALSE.. */
/*          Not referenced if HOWMNY = 'A' or 'B'. */

/*  N       (input) INTEGER */
/*          The order of the matrices S and P.  N >= 0. */

/*  S       (input) DOUBLE PRECISION array, dimension (LDS,N) */
/*          The upper quasi-triangular matrix S from a generalized Schur */
/*          factorization, as computed by DHGEQZ. */

/*  LDS     (input) INTEGER */
/*          The leading dimension of array S.  LDS >= max(1,N). */

/*  P       (input) DOUBLE PRECISION array, dimension (LDP,N) */
/*          The upper triangular matrix P from a generalized Schur */
/*          factorization, as computed by DHGEQZ. */
/*          2-by-2 diagonal blocks of P corresponding to 2-by-2 blocks */
/*          of S must be in positive diagonal form. */

/*  LDP     (input) INTEGER */
/*          The leading dimension of array P.  LDP >= max(1,N). */

/*  VL      (input/output) DOUBLE PRECISION array, dimension (LDVL,MM) */
/*          On entry, if SIDE = 'L' or 'B' and HOWMNY = 'B', VL must */
/*          contain an N-by-N matrix Q (usually the orthogonal matrix Q */
/*          of left Schur vectors returned by DHGEQZ). */
/*          On exit, if SIDE = 'L' or 'B', VL contains: */
/*          if HOWMNY = 'A', the matrix Y of left eigenvectors of (S,P); */
/*          if HOWMNY = 'B', the matrix Q*Y; */
/*          if HOWMNY = 'S', the left eigenvectors of (S,P) specified by */
/*                      SELECT, stored consecutively in the columns of */
/*                      VL, in the same order as their eigenvalues. */

/*          A complex eigenvector corresponding to a complex eigenvalue */
/*          is stored in two consecutive columns, the first holding the */
/*          real part, and the second the imaginary part. */

/*          Not referenced if SIDE = 'R'. */

/*  LDVL    (input) INTEGER */
/*          The leading dimension of array VL.  LDVL >= 1, and if */
/*          SIDE = 'L' or 'B', LDVL >= N. */

/*  VR      (input/output) DOUBLE PRECISION array, dimension (LDVR,MM) */
/*          On entry, if SIDE = 'R' or 'B' and HOWMNY = 'B', VR must */
/*          contain an N-by-N matrix Z (usually the orthogonal matrix Z */
/*          of right Schur vectors returned by DHGEQZ). */

/*          On exit, if SIDE = 'R' or 'B', VR contains: */
/*          if HOWMNY = 'A', the matrix X of right eigenvectors of (S,P); */
/*          if HOWMNY = 'B' or 'b', the matrix Z*X; */
/*          if HOWMNY = 'S' or 's', the right eigenvectors of (S,P) */
/*                      specified by SELECT, stored consecutively in the */
/*                      columns of VR, in the same order as their */
/*                      eigenvalues. */

/*          A complex eigenvector corresponding to a complex eigenvalue */
/*          is stored in two consecutive columns, the first holding the */
/*          real part and the second the imaginary part. */

/*          Not referenced if SIDE = 'L'. */

/*  LDVR    (input) INTEGER */
/*          The leading dimension of the array VR.  LDVR >= 1, and if */
/*          SIDE = 'R' or 'B', LDVR >= N. */

/*  MM      (input) INTEGER */
/*          The number of columns in the arrays VL and/or VR. MM >= M. */

/*  M       (output) INTEGER */
/*          The number of columns in the arrays VL and/or VR actually */
/*          used to store the eigenvectors.  If HOWMNY = 'A' or 'B', M */
/*          is set to N.  Each selected real eigenvector occupies one */
/*          column and each selected complex eigenvector occupies two */
/*          columns. */

/*  WORK    (workspace) DOUBLE PRECISION array, dimension (6*N) */

/*  INFO    (output) INTEGER */
/*          = 0:  successful exit. */
/*          < 0:  if INFO = -i, the i-th argument had an illegal value. */
/*          > 0:  the 2-by-2 block (INFO:INFO+1) does not have a complex */
/*                eigenvalue. */

/*  Further Details */
/*  =============== */

/*  Allocation of workspace: */
/*  ---------- -- --------- */

/*     WORK( j ) = 1-norm of j-th column of A, above the diagonal */
/*     WORK( N+j ) = 1-norm of j-th column of B, above the diagonal */
/*     WORK( 2*N+1:3*N ) = real part of eigenvector */
/*     WORK( 3*N+1:4*N ) = imaginary part of eigenvector */
/*     WORK( 4*N+1:5*N ) = real part of back-transformed eigenvector */
/*     WORK( 5*N+1:6*N ) = imaginary part of back-transformed eigenvector */

/*  Rowwise vs. columnwise solution methods: */
/*  ------- --  ---------- -------- ------- */

/*  Finding a generalized eigenvector consists basically of solving the */
/*  singular triangular system */

/*   (A - w B) x = 0     (for right) or:   (A - w B)**H y = 0  (for left) */

/*  Consider finding the i-th right eigenvector (assume all eigenvalues */
/*  are real). The equation to be solved is: */
/*       n                   i */
/*  0 = sum  C(j,k) v(k)  = sum  C(j,k) v(k)     for j = i,. . .,1 */
/*      k=j                 k=j */

/*  where  C = (A - w B)  (The components v(i+1:n) are 0.) */

/*  The "rowwise" method is: */

/*  (1)  v(i) := 1 */
/*  for j = i-1,. . .,1: */
/*                          i */
/*      (2) compute  s = - sum C(j,k) v(k)   and */
/*                        k=j+1 */

/*      (3) v(j) := s / C(j,j) */

/*  Step 2 is sometimes called the "dot product" step, since it is an */
/*  inner product between the j-th row and the portion of the eigenvector */
/*  that has been computed so far. */

/*  The "columnwise" method consists basically in doing the sums */
/*  for all the rows in parallel.  As each v(j) is computed, the */
/*  contribution of v(j) times the j-th column of C is added to the */
/*  partial sums.  Since FORTRAN arrays are stored columnwise, this has */
/*  the advantage that at each step, the elements of C that are accessed */
/*  are adjacent to one another, whereas with the rowwise method, the */
/*  elements accessed at a step are spaced LDS (and LDP) words apart. */

/*  When finding left eigenvectors, the matrix in question is the */
/*  transpose of the one in storage, so the rowwise method then */
/*  actually accesses columns of A and B at each step, and so is the */
/*  preferred method. */

/*  ===================================================================== */

/*     .. Parameters .. */
/*     .. */
/*     .. Local Scalars .. */
/*     .. */
/*     .. Local Arrays .. */
/*     .. */
/*     .. External Functions .. */
/*     .. */
/*     .. External Subroutines .. */
/*     .. */
/*     .. Intrinsic Functions .. */
/*     .. */
/*     .. Executable Statements .. */

/*     Decode and Test the input parameters */

    /* Parameter adjustments */
    --select;
    s_dim1 = *lds;
    s_offset = 1 + s_dim1;
    s -= s_offset;
    p_dim1 = *ldp;
    p_offset = 1 + p_dim1;
    p -= p_offset;
    vl_dim1 = *ldvl;
    vl_offset = 1 + vl_dim1;
    vl -= vl_offset;
    vr_dim1 = *ldvr;
    vr_offset = 1 + vr_dim1;
    vr -= vr_offset;
    --work;

    /* Function Body */
    if (lsame_(howmny, "A")) {
	ihwmny = 1;
	ilall = true;
	ilback = false;
    } else if (lsame_(howmny, "S")) {
	ihwmny = 2;
	ilall = false;
	ilback = false;
    } else if (lsame_(howmny, "B")) {
	ihwmny = 3;
	ilall = true;
	ilback = true;
    } else {
	ihwmny = -1;
	ilall = true;
    }

    if (lsame_(side, "R")) {
	iside = 1;
	compl_x = false;
	compr = true;
    } else if (lsame_(side, "L")) {
	iside = 2;
	compl_x = true;
	compr = false;
    } else if (lsame_(side, "B")) {
	iside = 3;
	compl_x = true;
	compr = true;
    } else {
	iside = -1;
    }

    *info = 0;
    if (iside < 0) {
	*info = -1;
    } else if (ihwmny < 0) {
	*info = -2;
    } else if (*n < 0) {
	*info = -4;
    } else if (*lds < std::max(1_integer,*n)) {
	*info = -6;
    } else if (*ldp < std::max(1_integer,*n)) {
	*info = -8;
    }
    if (*info != 0) {
	i__1 = -(*info);
	xerbla_("DTGEVC", &i__1);
	return 0;
    }

/*     Count the number of eigenvectors to be computed */

    if (! ilall) {
	im = 0;
	ilcplx = false;
	i__1 = *n;
	for (j = 1; j <= i__1; ++j) {
	    if (ilcplx) {
		ilcplx = false;
		goto L10;
	    }
	    if (j < *n) {
		if (s[j + 1 + j * s_dim1] != 0.) {
		    ilcplx = true;
		}
	    }
	    if (ilcplx) {
		if (select[j] || select[j + 1]) {
		    im += 2;
		}
	    } else {
		if (select[j]) {
		    ++im;
		}
	    }
L10:
	    ;
	}
    } else {
	im = *n;
    }

/*     Check 2-by-2 diagonal blocks of A, B */

    ilabad = false;
    ilbbad = false;
    i__1 = *n - 1;
    for (j = 1; j <= i__1; ++j) {
	if (s[j + 1 + j * s_dim1] != 0.) {
	    if (p[j + j * p_dim1] == 0. || p[j + 1 + (j + 1) * p_dim1] == 0. 
		    || p[j + (j + 1) * p_dim1] != 0.) {
		ilbbad = true;
	    }
	    if (j < *n - 1) {
		if (s[j + 2 + (j + 1) * s_dim1] != 0.) {
		    ilabad = true;
		}
	    }
	}
/* L20: */
    }

    if (ilabad) {
	*info = -5;
    } else if (ilbbad) {
	*info = -7;
    } else if (compl_x && *ldvl < *n || *ldvl < 1) {
	*info = -10;
    } else if (compr && *ldvr < *n || *ldvr < 1) {
	*info = -12;
    } else if (*mm < im) {
	*info = -13;
    }
    if (*info != 0) {
	i__1 = -(*info);
	xerbla_("DTGEVC", &i__1);
	return 0;
    }

/*     Quick return if possible */

    *m = im;
    if (*n == 0) {
	return 0;
    }

/*     Machine Constants */

    safmin = dlamch_("Safe minimum");
    big = 1. / safmin;
    dlabad_(&safmin, &big);
    ulp = dlamch_("Epsilon") * dlamch_("Base");
    small = safmin * *n / ulp;
    big = 1. / small;
    bignum = 1. / (safmin * *n);

/*     Compute the 1-norm of each column of the strictly upper triangular */
/*     part (i.e., excluding all elements belonging to the diagonal */
/*     blocks) of A and B to check for possible overflow in the */
/*     triangular solver. */

    anorm = (d__1 = s[s_dim1 + 1], abs(d__1));
    if (*n > 1) {
	anorm += (d__1 = s[s_dim1 + 2], abs(d__1));
    }
    bnorm = (d__1 = p[p_dim1 + 1], abs(d__1));
    work[1] = 0.;
    work[*n + 1] = 0.;

    i__1 = *n;
    for (j = 2; j <= i__1; ++j) {
	temp = 0.;
	temp2 = 0.;
	if (s[j + (j - 1) * s_dim1] == 0.) {
	    iend = j - 1;
	} else {
	    iend = j - 2;
	}
	i__2 = iend;
	for (i__ = 1; i__ <= i__2; ++i__) {
	    temp += (d__1 = s[i__ + j * s_dim1], abs(d__1));
	    temp2 += (d__1 = p[i__ + j * p_dim1], abs(d__1));
/* L30: */
	}
	work[j] = temp;
	work[*n + j] = temp2;
/* Computing MIN */
	i__3 = j + 1;
	i__2 = std::min(i__3,*n);
	for (i__ = iend + 1; i__ <= i__2; ++i__) {
	    temp += (d__1 = s[i__ + j * s_dim1], abs(d__1));
	    temp2 += (d__1 = p[i__ + j * p_dim1], abs(d__1));
/* L40: */
	}
	anorm = std::max(anorm,temp);
	bnorm = std::max(bnorm,temp2);
/* L50: */
    }
    ascale = 1. / std::max(anorm,safmin);
    bscale = 1. / std::max(bnorm,safmin);

/*     Left eigenvectors */

    if (compl_x) {
	ieig = 0;

/*        Main loop over eigenvalues */

	ilcplx = false;
	i__1 = *n;
	for (je = 1; je <= i__1; ++je) {

/*           Skip this iteration if (a) HOWMNY='S' and SELECT=.FALSE., or */
/*           (b) this would be the second of a complex pair. */
/*           Check for complex eigenvalue, so as to be sure of which */
/*           entry(-ies) of SELECT to look at. */

	    if (ilcplx) {
		ilcplx = false;
		goto L220;
	    }
	    nw = 1;
	    if (je < *n) {
		if (s[je + 1 + je * s_dim1] != 0.) {
		    ilcplx = true;
		    nw = 2;
		}
	    }
	    if (ilall) {
		ilcomp = true;
	    } else if (ilcplx) {
		ilcomp = select[je] || select[je + 1];
	    } else {
		ilcomp = select[je];
	    }
	    if (! ilcomp) {
		goto L220;
	    }

/*           Decide if (a) singular pencil, (b) real eigenvalue, or */
/*           (c) complex eigenvalue. */

	    if (! ilcplx) {
		if ((d__1 = s[je + je * s_dim1], abs(d__1)) <= safmin && (
			d__2 = p[je + je * p_dim1], abs(d__2)) <= safmin) {

/*                 Singular matrix pencil -- return unit eigenvector */

		    ++ieig;
		    i__2 = *n;
		    for (jr = 1; jr <= i__2; ++jr) {
			vl[jr + ieig * vl_dim1] = 0.;
/* L60: */
		    }
		    vl[ieig + ieig * vl_dim1] = 1.;
		    goto L220;
		}
	    }

/*           Clear vector */

	    i__2 = nw * *n;
	    for (jr = 1; jr <= i__2; ++jr) {
		work[(*n << 1) + jr] = 0.;
/* L70: */
	    }
/*                                                 T */
/*           Compute coefficients in  ( a A - b B )  y = 0 */
/*              a  is  ACOEF */
/*              b  is  BCOEFR + i*BCOEFI */

	    if (! ilcplx) {

/*              Real eigenvalue */

/* Computing MAX */
		d__3 = (d__1 = s[je + je * s_dim1], abs(d__1)) * ascale, d__4 
			= (d__2 = p[je + je * p_dim1], abs(d__2)) * bscale, 
			d__3 = std::max(d__3,d__4);
		temp = 1. / std::max(d__3,safmin);
		salfar = temp * s[je + je * s_dim1] * ascale;
		sbeta = temp * p[je + je * p_dim1] * bscale;
		acoef = sbeta * ascale;
		bcoefr = salfar * bscale;
		bcoefi = 0.;

/*              Scale to avoid underflow */

		scale = 1.;
		lsa = abs(sbeta) >= safmin && abs(acoef) < small;
		lsb = abs(salfar) >= safmin && abs(bcoefr) < small;
		if (lsa) {
		    scale = small / abs(sbeta) * std::min(anorm,big);
		}
		if (lsb) {
/* Computing MAX */
		    d__1 = scale, d__2 = small / abs(salfar) * std::min(bnorm,big);
		    scale = std::max(d__1,d__2);
		}
		if (lsa || lsb) {
/* Computing MIN */
/* Computing MAX */
		    d__3 = 1., d__4 = abs(acoef), d__3 = std::max(d__3,d__4), d__4 
			    = abs(bcoefr);
		    d__1 = scale, d__2 = 1. / (safmin * std::max(d__3,d__4));
		    scale = std::min(d__1,d__2);
		    if (lsa) {
			acoef = ascale * (scale * sbeta);
		    } else {
			acoef = scale * acoef;
		    }
		    if (lsb) {
			bcoefr = bscale * (scale * salfar);
		    } else {
			bcoefr = scale * bcoefr;
		    }
		}
		acoefa = abs(acoef);
		bcoefa = abs(bcoefr);

/*              First component is 1 */

		work[(*n << 1) + je] = 1.;
		xmax = 1.;
	    } else {

/*              Complex eigenvalue */

		d__1 = safmin * 100.;
		dlag2_(&s[je + je * s_dim1], lds, &p[je + je * p_dim1], ldp, &
			d__1, &acoef, &temp, &bcoefr, &temp2, &bcoefi);
		bcoefi = -bcoefi;
		if (bcoefi == 0.) {
		    *info = je;
		    return 0;
		}

/*              Scale to avoid over/underflow */

		acoefa = abs(acoef);
		bcoefa = abs(bcoefr) + abs(bcoefi);
		scale = 1.;
		if (acoefa * ulp < safmin && acoefa >= safmin) {
		    scale = safmin / ulp / acoefa;
		}
		if (bcoefa * ulp < safmin && bcoefa >= safmin) {
/* Computing MAX */
		    d__1 = scale, d__2 = safmin / ulp / bcoefa;
		    scale = std::max(d__1,d__2);
		}
		if (safmin * acoefa > ascale) {
		    scale = ascale / (safmin * acoefa);
		}
		if (safmin * bcoefa > bscale) {
/* Computing MIN */
		    d__1 = scale, d__2 = bscale / (safmin * bcoefa);
		    scale = std::min(d__1,d__2);
		}
		if (scale != 1.) {
		    acoef = scale * acoef;
		    acoefa = abs(acoef);
		    bcoefr = scale * bcoefr;
		    bcoefi = scale * bcoefi;
		    bcoefa = abs(bcoefr) + abs(bcoefi);
		}

/*              Compute first two components of eigenvector */

		temp = acoef * s[je + 1 + je * s_dim1];
		temp2r = acoef * s[je + je * s_dim1] - bcoefr * p[je + je * 
			p_dim1];
		temp2i = -bcoefi * p[je + je * p_dim1];
		if (abs(temp) > abs(temp2r) + abs(temp2i)) {
		    work[(*n << 1) + je] = 1.;
		    work[*n * 3 + je] = 0.;
		    work[(*n << 1) + je + 1] = -temp2r / temp;
		    work[*n * 3 + je + 1] = -temp2i / temp;
		} else {
		    work[(*n << 1) + je + 1] = 1.;
		    work[*n * 3 + je + 1] = 0.;
		    temp = acoef * s[je + (je + 1) * s_dim1];
		    work[(*n << 1) + je] = (bcoefr * p[je + 1 + (je + 1) * 
			    p_dim1] - acoef * s[je + 1 + (je + 1) * s_dim1]) /
			     temp;
		    work[*n * 3 + je] = bcoefi * p[je + 1 + (je + 1) * p_dim1]
			     / temp;
		}
/* Computing MAX */
		d__5 = (d__1 = work[(*n << 1) + je], abs(d__1)) + (d__2 = 
			work[*n * 3 + je], abs(d__2)), d__6 = (d__3 = work[(*
			n << 1) + je + 1], abs(d__3)) + (d__4 = work[*n * 3 + 
			je + 1], abs(d__4));
		xmax = std::max(d__5,d__6);
	    }

/* Computing MAX */
	    d__1 = ulp * acoefa * anorm, d__2 = ulp * bcoefa * bnorm, d__1 = 
		    std::max(d__1,d__2);
	    dmin__ = std::max(d__1,safmin);

/*                                           T */
/*           Triangular solve of  (a A - b B)  y = 0 */

/*                                   T */
/*           (rowwise in  (a A - b B) , or columnwise in (a A - b B) ) */

	    il2by2 = false;

	    i__2 = *n;
	    for (j = je + nw; j <= i__2; ++j) {
		if (il2by2) {
		    il2by2 = false;
		    goto L160;
		}

		na = 1;
		bdiag[0] = p[j + j * p_dim1];
		if (j < *n) {
		    if (s[j + 1 + j * s_dim1] != 0.) {
			il2by2 = true;
			bdiag[1] = p[j + 1 + (j + 1) * p_dim1];
			na = 2;
		    }
		}

/*              Check whether scaling is necessary for dot products */

		xscale = 1. / std::max(1.,xmax);
/* Computing MAX */
		d__1 = work[j], d__2 = work[*n + j], d__1 = std::max(d__1,d__2), 
			d__2 = acoefa * work[j] + bcoefa * work[*n + j];
		temp = std::max(d__1,d__2);
		if (il2by2) {
/* Computing MAX */
		    d__1 = temp, d__2 = work[j + 1], d__1 = std::max(d__1,d__2), 
			    d__2 = work[*n + j + 1], d__1 = std::max(d__1,d__2), 
			    d__2 = acoefa * work[j + 1] + bcoefa * work[*n + 
			    j + 1];
		    temp = std::max(d__1,d__2);
		}
		if (temp > bignum * xscale) {
		    i__3 = nw - 1;
		    for (jw = 0; jw <= i__3; ++jw) {
			i__4 = j - 1;
			for (jr = je; jr <= i__4; ++jr) {
			    work[(jw + 2) * *n + jr] = xscale * work[(jw + 2) 
				    * *n + jr];
/* L80: */
			}
/* L90: */
		    }
		    xmax *= xscale;
		}

/*              Compute dot products */

/*                    j-1 */
/*              SUM = sum  conjg( a*S(k,j) - b*P(k,j) )*x(k) */
/*                    k=je */

/*              To reduce the op count, this is done as */

/*              _        j-1                  _        j-1 */
/*              a*conjg( sum  S(k,j)*x(k) ) - b*conjg( sum  P(k,j)*x(k) ) */
/*                       k=je                          k=je */

/*              which may cause underflow problems if A or B are close */
/*              to underflow.  (E.g., less than SMALL.) */


/*              A series of compiler directives to defeat vectorization */
/*              for the next loop */

/* $PL$ CMCHAR=' ' */
/* DIR$          NEXTSCALAR */
/* $DIR          SCALAR */
/* DIR$          NEXT SCALAR */
/* VD$L          NOVECTOR */
/* DEC$          NOVECTOR */
/* VD$           NOVECTOR */
/* VDIR          NOVECTOR */
/* VOCL          LOOP,SCALAR */
/* IBM           PREFER SCALAR */
/* $PL$ CMCHAR='*' */

		i__3 = nw;
		for (jw = 1; jw <= i__3; ++jw) {

/* $PL$ CMCHAR=' ' */
/* DIR$             NEXTSCALAR */
/* $DIR             SCALAR */
/* DIR$             NEXT SCALAR */
/* VD$L             NOVECTOR */
/* DEC$             NOVECTOR */
/* VD$              NOVECTOR */
/* VDIR             NOVECTOR */
/* VOCL             LOOP,SCALAR */
/* IBM              PREFER SCALAR */
/* $PL$ CMCHAR='*' */

		    i__4 = na;
		    for (ja = 1; ja <= i__4; ++ja) {
			sums[ja + (jw << 1) - 3] = 0.;
			sump[ja + (jw << 1) - 3] = 0.;

			i__5 = j - 1;
			for (jr = je; jr <= i__5; ++jr) {
			    sums[ja + (jw << 1) - 3] += s[jr + (j + ja - 1) * 
				    s_dim1] * work[(jw + 1) * *n + jr];
			    sump[ja + (jw << 1) - 3] += p[jr + (j + ja - 1) * 
				    p_dim1] * work[(jw + 1) * *n + jr];
/* L100: */
			}
/* L110: */
		    }
/* L120: */
		}

/* $PL$ CMCHAR=' ' */
/* DIR$          NEXTSCALAR */
/* $DIR          SCALAR */
/* DIR$          NEXT SCALAR */
/* VD$L          NOVECTOR */
/* DEC$          NOVECTOR */
/* VD$           NOVECTOR */
/* VDIR          NOVECTOR */
/* VOCL          LOOP,SCALAR */
/* IBM           PREFER SCALAR */
/* $PL$ CMCHAR='*' */

		i__3 = na;
		for (ja = 1; ja <= i__3; ++ja) {
		    if (ilcplx) {
			sum[ja - 1] = -acoef * sums[ja - 1] + bcoefr * sump[
				ja - 1] - bcoefi * sump[ja + 1];
			sum[ja + 1] = -acoef * sums[ja + 1] + bcoefr * sump[
				ja + 1] + bcoefi * sump[ja - 1];
		    } else {
			sum[ja - 1] = -acoef * sums[ja - 1] + bcoefr * sump[
				ja - 1];
		    }
/* L130: */
		}

/*                                  T */
/*              Solve  ( a A - b B )  y = SUM(,) */
/*              with scaling and perturbation of the denominator */

		dlaln2_(&c_true, &na, &nw, &dmin__, &acoef, &s[j + j * s_dim1]
, lds, bdiag, &bdiag[1], sum, &c__2, &bcoefr, &bcoefi, 
			 &work[(*n << 1) + j], n, &scale, &temp, &iinfo);
		if (scale < 1.) {
		    i__3 = nw - 1;
		    for (jw = 0; jw <= i__3; ++jw) {
			i__4 = j - 1;
			for (jr = je; jr <= i__4; ++jr) {
			    work[(jw + 2) * *n + jr] = scale * work[(jw + 2) *
				     *n + jr];
/* L140: */
			}
/* L150: */
		    }
		    xmax = scale * xmax;
		}
		xmax = std::max(xmax,temp);
L160:
		;
	    }

/*           Copy eigenvector to VL, back transforming if */
/*           HOWMNY='B'. */

	    ++ieig;
	    if (ilback) {
		i__2 = nw - 1;
		for (jw = 0; jw <= i__2; ++jw) {
		    i__3 = *n + 1 - je;
		    dgemv_("N", n, &i__3, &c_b34, &vl[je * vl_dim1 + 1], ldvl, 
			     &work[(jw + 2) * *n + je], &c__1, &c_b36, &work[(
			    jw + 4) * *n + 1], &c__1);
/* L170: */
		}
		dlacpy_(" ", n, &nw, &work[(*n << 2) + 1], n, &vl[je * 
			vl_dim1 + 1], ldvl);
		ibeg = 1;
	    } else {
		dlacpy_(" ", n, &nw, &work[(*n << 1) + 1], n, &vl[ieig * 
			vl_dim1 + 1], ldvl);
		ibeg = je;
	    }

/*           Scale eigenvector */

	    xmax = 0.;
	    if (ilcplx) {
		i__2 = *n;
		for (j = ibeg; j <= i__2; ++j) {
/* Computing MAX */
		    d__3 = xmax, d__4 = (d__1 = vl[j + ieig * vl_dim1], abs(
			    d__1)) + (d__2 = vl[j + (ieig + 1) * vl_dim1], 
			    abs(d__2));
		    xmax = std::max(d__3,d__4);
/* L180: */
		}
	    } else {
		i__2 = *n;
		for (j = ibeg; j <= i__2; ++j) {
/* Computing MAX */
		    d__2 = xmax, d__3 = (d__1 = vl[j + ieig * vl_dim1], abs(
			    d__1));
		    xmax = std::max(d__2,d__3);
/* L190: */
		}
	    }

	    if (xmax > safmin) {
		xscale = 1. / xmax;

		i__2 = nw - 1;
		for (jw = 0; jw <= i__2; ++jw) {
		    i__3 = *n;
		    for (jr = ibeg; jr <= i__3; ++jr) {
			vl[jr + (ieig + jw) * vl_dim1] = xscale * vl[jr + (
				ieig + jw) * vl_dim1];
/* L200: */
		    }
/* L210: */
		}
	    }
	    ieig = ieig + nw - 1;

L220:
	    ;
	}
    }

/*     Right eigenvectors */

    if (compr) {
	ieig = im + 1;

/*        Main loop over eigenvalues */

	ilcplx = false;
	for (je = *n; je >= 1; --je) {

/*           Skip this iteration if (a) HOWMNY='S' and SELECT=.FALSE., or */
/*           (b) this would be the second of a complex pair. */
/*           Check for complex eigenvalue, so as to be sure of which */
/*           entry(-ies) of SELECT to look at -- if complex, SELECT(JE) */
/*           or SELECT(JE-1). */
/*           If this is a complex pair, the 2-by-2 diagonal block */
/*           corresponding to the eigenvalue is in rows/columns JE-1:JE */

	    if (ilcplx) {
		ilcplx = false;
		goto L500;
	    }
	    nw = 1;
	    if (je > 1) {
		if (s[je + (je - 1) * s_dim1] != 0.) {
		    ilcplx = true;
		    nw = 2;
		}
	    }
	    if (ilall) {
		ilcomp = true;
	    } else if (ilcplx) {
		ilcomp = select[je] || select[je - 1];
	    } else {
		ilcomp = select[je];
	    }
	    if (! ilcomp) {
		goto L500;
	    }

/*           Decide if (a) singular pencil, (b) real eigenvalue, or */
/*           (c) complex eigenvalue. */

	    if (! ilcplx) {
		if ((d__1 = s[je + je * s_dim1], abs(d__1)) <= safmin && (
			d__2 = p[je + je * p_dim1], abs(d__2)) <= safmin) {

/*                 Singular matrix pencil -- unit eigenvector */

		    --ieig;
		    i__1 = *n;
		    for (jr = 1; jr <= i__1; ++jr) {
			vr[jr + ieig * vr_dim1] = 0.;
/* L230: */
		    }
		    vr[ieig + ieig * vr_dim1] = 1.;
		    goto L500;
		}
	    }

/*           Clear vector */

	    i__1 = nw - 1;
	    for (jw = 0; jw <= i__1; ++jw) {
		i__2 = *n;
		for (jr = 1; jr <= i__2; ++jr) {
		    work[(jw + 2) * *n + jr] = 0.;
/* L240: */
		}
/* L250: */
	    }

/*           Compute coefficients in  ( a A - b B ) x = 0 */
/*              a  is  ACOEF */
/*              b  is  BCOEFR + i*BCOEFI */

	    if (! ilcplx) {

/*              Real eigenvalue */

/* Computing MAX */
		d__3 = (d__1 = s[je + je * s_dim1], abs(d__1)) * ascale, d__4 
			= (d__2 = p[je + je * p_dim1], abs(d__2)) * bscale, 
			d__3 = std::max(d__3,d__4);
		temp = 1. / std::max(d__3,safmin);
		salfar = temp * s[je + je * s_dim1] * ascale;
		sbeta = temp * p[je + je * p_dim1] * bscale;
		acoef = sbeta * ascale;
		bcoefr = salfar * bscale;
		bcoefi = 0.;

/*              Scale to avoid underflow */

		scale = 1.;
		lsa = abs(sbeta) >= safmin && abs(acoef) < small;
		lsb = abs(salfar) >= safmin && abs(bcoefr) < small;
		if (lsa) {
		    scale = small / abs(sbeta) * std::min(anorm,big);
		}
		if (lsb) {
/* Computing MAX */
		    d__1 = scale, d__2 = small / abs(salfar) * std::min(bnorm,big);
		    scale = std::max(d__1,d__2);
		}
		if (lsa || lsb) {
/* Computing MIN */
/* Computing MAX */
		    d__3 = 1., d__4 = abs(acoef), d__3 = std::max(d__3,d__4), d__4 
			    = abs(bcoefr);
		    d__1 = scale, d__2 = 1. / (safmin * std::max(d__3,d__4));
		    scale = std::min(d__1,d__2);
		    if (lsa) {
			acoef = ascale * (scale * sbeta);
		    } else {
			acoef = scale * acoef;
		    }
		    if (lsb) {
			bcoefr = bscale * (scale * salfar);
		    } else {
			bcoefr = scale * bcoefr;
		    }
		}
		acoefa = abs(acoef);
		bcoefa = abs(bcoefr);

/*              First component is 1 */

		work[(*n << 1) + je] = 1.;
		xmax = 1.;

/*              Compute contribution from column JE of A and B to sum */
/*              (See "Further Details", above.) */

		i__1 = je - 1;
		for (jr = 1; jr <= i__1; ++jr) {
		    work[(*n << 1) + jr] = bcoefr * p[jr + je * p_dim1] - 
			    acoef * s[jr + je * s_dim1];
/* L260: */
		}
	    } else {

/*              Complex eigenvalue */

		d__1 = safmin * 100.;
		dlag2_(&s[je - 1 + (je - 1) * s_dim1], lds, &p[je - 1 + (je - 
			1) * p_dim1], ldp, &d__1, &acoef, &temp, &bcoefr, &
			temp2, &bcoefi);
		if (bcoefi == 0.) {
		    *info = je - 1;
		    return 0;
		}

/*              Scale to avoid over/underflow */

		acoefa = abs(acoef);
		bcoefa = abs(bcoefr) + abs(bcoefi);
		scale = 1.;
		if (acoefa * ulp < safmin && acoefa >= safmin) {
		    scale = safmin / ulp / acoefa;
		}
		if (bcoefa * ulp < safmin && bcoefa >= safmin) {
/* Computing MAX */
		    d__1 = scale, d__2 = safmin / ulp / bcoefa;
		    scale = std::max(d__1,d__2);
		}
		if (safmin * acoefa > ascale) {
		    scale = ascale / (safmin * acoefa);
		}
		if (safmin * bcoefa > bscale) {
/* Computing MIN */
		    d__1 = scale, d__2 = bscale / (safmin * bcoefa);
		    scale = std::min(d__1,d__2);
		}
		if (scale != 1.) {
		    acoef = scale * acoef;
		    acoefa = abs(acoef);
		    bcoefr = scale * bcoefr;
		    bcoefi = scale * bcoefi;
		    bcoefa = abs(bcoefr) + abs(bcoefi);
		}

/*              Compute first two components of eigenvector */
/*              and contribution to sums */

		temp = acoef * s[je + (je - 1) * s_dim1];
		temp2r = acoef * s[je + je * s_dim1] - bcoefr * p[je + je * 
			p_dim1];
		temp2i = -bcoefi * p[je + je * p_dim1];
		if (abs(temp) >= abs(temp2r) + abs(temp2i)) {
		    work[(*n << 1) + je] = 1.;
		    work[*n * 3 + je] = 0.;
		    work[(*n << 1) + je - 1] = -temp2r / temp;
		    work[*n * 3 + je - 1] = -temp2i / temp;
		} else {
		    work[(*n << 1) + je - 1] = 1.;
		    work[*n * 3 + je - 1] = 0.;
		    temp = acoef * s[je - 1 + je * s_dim1];
		    work[(*n << 1) + je] = (bcoefr * p[je - 1 + (je - 1) * 
			    p_dim1] - acoef * s[je - 1 + (je - 1) * s_dim1]) /
			     temp;
		    work[*n * 3 + je] = bcoefi * p[je - 1 + (je - 1) * p_dim1]
			     / temp;
		}

/* Computing MAX */
		d__5 = (d__1 = work[(*n << 1) + je], abs(d__1)) + (d__2 = 
			work[*n * 3 + je], abs(d__2)), d__6 = (d__3 = work[(*
			n << 1) + je - 1], abs(d__3)) + (d__4 = work[*n * 3 + 
			je - 1], abs(d__4));
		xmax = std::max(d__5,d__6);

/*              Compute contribution from columns JE and JE-1 */
/*              of A and B to the sums. */

		creala = acoef * work[(*n << 1) + je - 1];
		cimaga = acoef * work[*n * 3 + je - 1];
		crealb = bcoefr * work[(*n << 1) + je - 1] - bcoefi * work[*n 
			* 3 + je - 1];
		cimagb = bcoefi * work[(*n << 1) + je - 1] + bcoefr * work[*n 
			* 3 + je - 1];
		cre2a = acoef * work[(*n << 1) + je];
		cim2a = acoef * work[*n * 3 + je];
		cre2b = bcoefr * work[(*n << 1) + je] - bcoefi * work[*n * 3 
			+ je];
		cim2b = bcoefi * work[(*n << 1) + je] + bcoefr * work[*n * 3 
			+ je];
		i__1 = je - 2;
		for (jr = 1; jr <= i__1; ++jr) {
		    work[(*n << 1) + jr] = -creala * s[jr + (je - 1) * s_dim1]
			     + crealb * p[jr + (je - 1) * p_dim1] - cre2a * s[
			    jr + je * s_dim1] + cre2b * p[jr + je * p_dim1];
		    work[*n * 3 + jr] = -cimaga * s[jr + (je - 1) * s_dim1] + 
			    cimagb * p[jr + (je - 1) * p_dim1] - cim2a * s[jr 
			    + je * s_dim1] + cim2b * p[jr + je * p_dim1];
/* L270: */
		}
	    }

/* Computing MAX */
	    d__1 = ulp * acoefa * anorm, d__2 = ulp * bcoefa * bnorm, d__1 = 
		    std::max(d__1,d__2);
	    dmin__ = std::max(d__1,safmin);

/*           Columnwise triangular solve of  (a A - b B)  x = 0 */

	    il2by2 = false;
	    for (j = je - nw; j >= 1; --j) {

/*              If a 2-by-2 block, is in position j-1:j, wait until */
/*              next iteration to process it (when it will be j:j+1) */

		if (! il2by2 && j > 1) {
		    if (s[j + (j - 1) * s_dim1] != 0.) {
			il2by2 = true;
			goto L370;
		    }
		}
		bdiag[0] = p[j + j * p_dim1];
		if (il2by2) {
		    na = 2;
		    bdiag[1] = p[j + 1 + (j + 1) * p_dim1];
		} else {
		    na = 1;
		}

/*              Compute x(j) (and x(j+1), if 2-by-2 block) */

		dlaln2_(&c_false, &na, &nw, &dmin__, &acoef, &s[j + j * 
			s_dim1], lds, bdiag, &bdiag[1], &work[(*n << 1) + j], 
			n, &bcoefr, &bcoefi, sum, &c__2, &scale, &temp, &
			iinfo);
		if (scale < 1.) {

		    i__1 = nw - 1;
		    for (jw = 0; jw <= i__1; ++jw) {
			i__2 = je;
			for (jr = 1; jr <= i__2; ++jr) {
			    work[(jw + 2) * *n + jr] = scale * work[(jw + 2) *
				     *n + jr];
/* L280: */
			}
/* L290: */
		    }
		}
/* Computing MAX */
		d__1 = scale * xmax;
		xmax = std::max(d__1,temp);

		i__1 = nw;
		for (jw = 1; jw <= i__1; ++jw) {
		    i__2 = na;
		    for (ja = 1; ja <= i__2; ++ja) {
			work[(jw + 1) * *n + j + ja - 1] = sum[ja + (jw << 1) 
				- 3];
/* L300: */
		    }
/* L310: */
		}

/*              w = w + x(j)*(a S(*,j) - b P(*,j) ) with scaling */

		if (j > 1) {

/*                 Check whether scaling is necessary for sum. */

		    xscale = 1. / std::max(1.,xmax);
		    temp = acoefa * work[j] + bcoefa * work[*n + j];
		    if (il2by2) {
/* Computing MAX */
			d__1 = temp, d__2 = acoefa * work[j + 1] + bcoefa * 
				work[*n + j + 1];
			temp = std::max(d__1,d__2);
		    }
/* Computing MAX */
		    d__1 = std::max(temp,acoefa);
		    temp = std::max(d__1,bcoefa);
		    if (temp > bignum * xscale) {

			i__1 = nw - 1;
			for (jw = 0; jw <= i__1; ++jw) {
			    i__2 = je;
			    for (jr = 1; jr <= i__2; ++jr) {
				work[(jw + 2) * *n + jr] = xscale * work[(jw 
					+ 2) * *n + jr];
/* L320: */
			    }
/* L330: */
			}
			xmax *= xscale;
		    }

/*                 Compute the contributions of the off-diagonals of */
/*                 column j (and j+1, if 2-by-2 block) of A and B to the */
/*                 sums. */


		    i__1 = na;
		    for (ja = 1; ja <= i__1; ++ja) {
			if (ilcplx) {
			    creala = acoef * work[(*n << 1) + j + ja - 1];
			    cimaga = acoef * work[*n * 3 + j + ja - 1];
			    crealb = bcoefr * work[(*n << 1) + j + ja - 1] - 
				    bcoefi * work[*n * 3 + j + ja - 1];
			    cimagb = bcoefi * work[(*n << 1) + j + ja - 1] + 
				    bcoefr * work[*n * 3 + j + ja - 1];
			    i__2 = j - 1;
			    for (jr = 1; jr <= i__2; ++jr) {
				work[(*n << 1) + jr] = work[(*n << 1) + jr] - 
					creala * s[jr + (j + ja - 1) * s_dim1]
					 + crealb * p[jr + (j + ja - 1) * 
					p_dim1];
				work[*n * 3 + jr] = work[*n * 3 + jr] - 
					cimaga * s[jr + (j + ja - 1) * s_dim1]
					 + cimagb * p[jr + (j + ja - 1) * 
					p_dim1];
/* L340: */
			    }
			} else {
			    creala = acoef * work[(*n << 1) + j + ja - 1];
			    crealb = bcoefr * work[(*n << 1) + j + ja - 1];
			    i__2 = j - 1;
			    for (jr = 1; jr <= i__2; ++jr) {
				work[(*n << 1) + jr] = work[(*n << 1) + jr] - 
					creala * s[jr + (j + ja - 1) * s_dim1]
					 + crealb * p[jr + (j + ja - 1) * 
					p_dim1];
/* L350: */
			    }
			}
/* L360: */
		    }
		}
		il2by2 = false;
L370:
		;
	    }

/*           Copy eigenvector to VR, back transforming if */
/*           HOWMNY='B'. */

	    ieig -= nw;
	    if (ilback) {

		i__1 = nw - 1;
		for (jw = 0; jw <= i__1; ++jw) {
		    i__2 = *n;
		    for (jr = 1; jr <= i__2; ++jr) {
			work[(jw + 4) * *n + jr] = work[(jw + 2) * *n + 1] * 
				vr[jr + vr_dim1];
/* L380: */
		    }

/*                 A series of compiler directives to defeat */
/*                 vectorization for the next loop */


		    i__2 = je;
		    for (jc = 2; jc <= i__2; ++jc) {
			i__3 = *n;
			for (jr = 1; jr <= i__3; ++jr) {
			    work[(jw + 4) * *n + jr] += work[(jw + 2) * *n + 
				    jc] * vr[jr + jc * vr_dim1];
/* L390: */
			}
/* L400: */
		    }
/* L410: */
		}

		i__1 = nw - 1;
		for (jw = 0; jw <= i__1; ++jw) {
		    i__2 = *n;
		    for (jr = 1; jr <= i__2; ++jr) {
			vr[jr + (ieig + jw) * vr_dim1] = work[(jw + 4) * *n + 
				jr];
/* L420: */
		    }
/* L430: */
		}

		iend = *n;
	    } else {
		i__1 = nw - 1;
		for (jw = 0; jw <= i__1; ++jw) {
		    i__2 = *n;
		    for (jr = 1; jr <= i__2; ++jr) {
			vr[jr + (ieig + jw) * vr_dim1] = work[(jw + 2) * *n + 
				jr];
/* L440: */
		    }
/* L450: */
		}

		iend = je;
	    }

/*           Scale eigenvector */

	    xmax = 0.;
	    if (ilcplx) {
		i__1 = iend;
		for (j = 1; j <= i__1; ++j) {
/* Computing MAX */
		    d__3 = xmax, d__4 = (d__1 = vr[j + ieig * vr_dim1], abs(
			    d__1)) + (d__2 = vr[j + (ieig + 1) * vr_dim1], 
			    abs(d__2));
		    xmax = std::max(d__3,d__4);
/* L460: */
		}
	    } else {
		i__1 = iend;
		for (j = 1; j <= i__1; ++j) {
/* Computing MAX */
		    d__2 = xmax, d__3 = (d__1 = vr[j + ieig * vr_dim1], abs(
			    d__1));
		    xmax = std::max(d__2,d__3);
/* L470: */
		}
	    }

	    if (xmax > safmin) {
		xscale = 1. / xmax;
		i__1 = nw - 1;
		for (jw = 0; jw <= i__1; ++jw) {
		    i__2 = iend;
		    for (jr = 1; jr <= i__2; ++jr) {
			vr[jr + (ieig + jw) * vr_dim1] = xscale * vr[jr + (
				ieig + jw) * vr_dim1];
/* L480: */
		    }
/* L490: */
		}
	    }
L500:
	    ;
	}
    }

    return 0;

/*     End of DTGEVC */

} /* dtgevc_ */
