/*  -- translated by f2c (version 20100827).
   You must link the resulting object file with libf2c:
	on Microsoft Windows system, link with libf2c.lib;
	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
	or, if you install libf2c.a in a standard place, with -lf2c -lm
	-- in that order, at the end of the command line, as in
		cc *.o -lf2c -lm
	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,

		http://www.netlib.org/f2c/libf2c.zip
*/

#include "f2c.h"

/* Table of constant values */

static integer c__1 = 1;

/* Subroutine */ int splicingdlasd7_(integer *icompq, integer *nl, integer *nr, 
	integer *sqre, integer *k, doublereal *d__, doublereal *z__, 
	doublereal *zw, doublereal *vf, doublereal *vfw, doublereal *vl, 
	doublereal *vlw, doublereal *alpha, doublereal *beta, doublereal *
	dsigma, integer *idx, integer *idxp, integer *idxq, integer *perm, 
	integer *givptr, integer *givcol, integer *ldgcol, doublereal *givnum,
	 integer *ldgnum, doublereal *c__, doublereal *s, integer *info)
{
    /* System generated locals */
    integer givcol_dim1, givcol_offset, givnum_dim1, givnum_offset, i__1;
    doublereal d__1, d__2;

    /* Local variables */
    static integer i__, j, m, n, k2;
    static doublereal z1;
    static integer jp;
    static doublereal eps, tau, tol;
    static integer nlp1, nlp2, idxi, idxj;
    extern /* Subroutine */ int splicingdrot_(integer *, doublereal *, integer *, 
	    doublereal *, integer *, doublereal *, doublereal *);
    static integer idxjp;
    extern /* Subroutine */ int splicingdcopy_(integer *, doublereal *, integer *, 
	    doublereal *, integer *);
    static integer jprev;
    extern doublereal splicingdlapy2_(doublereal *, doublereal *), splicingdlamch_(char *);
    extern /* Subroutine */ int splicingdlamrg_(integer *, integer *, doublereal *, 
	    integer *, integer *, integer *), splicingxerbla_(char *, integer *, 
	    ftnlen);
    static doublereal hlftol;


/*  -- LAPACK auxiliary routine (version 3.2) --   
    -- LAPACK is a software package provided by Univ. of Tennessee,    --   
    -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--   
       November 2006   


    Purpose   
    =======   

    DLASD7 merges the two sets of singular values together into a single   
    sorted set. Then it tries to deflate the size of the problem. There   
    are two ways in which deflation can occur:  when two or more singular   
    values are close together or if there is a tiny entry in the Z   
    vector. For each such occurrence the order of the related   
    secular equation problem is reduced by one.   

    DLASD7 is called from DLASD6.   

    Arguments   
    =========   

    ICOMPQ  (input) INTEGER   
            Specifies whether singular vectors are to be computed   
            in compact form, as follows:   
            = 0: Compute singular values only.   
            = 1: Compute singular vectors of upper   
                 bidiagonal matrix in compact form.   

    NL     (input) INTEGER   
           The row dimension of the upper block. NL >= 1.   

    NR     (input) INTEGER   
           The row dimension of the lower block. NR >= 1.   

    SQRE   (input) INTEGER   
           = 0: the lower block is an NR-by-NR square matrix.   
           = 1: the lower block is an NR-by-(NR+1) rectangular matrix.   

           The bidiagonal matrix has   
           N = NL + NR + 1 rows and   
           M = N + SQRE >= N columns.   

    K      (output) INTEGER   
           Contains the dimension of the non-deflated matrix, this is   
           the order of the related secular equation. 1 <= K <=N.   

    D      (input/output) DOUBLE PRECISION array, dimension ( N )   
           On entry D contains the singular values of the two submatrices   
           to be combined. On exit D contains the trailing (N-K) updated   
           singular values (those which were deflated) sorted into   
           increasing order.   

    Z      (output) DOUBLE PRECISION array, dimension ( M )   
           On exit Z contains the updating row vector in the secular   
           equation.   

    ZW     (workspace) DOUBLE PRECISION array, dimension ( M )   
           Workspace for Z.   

    VF     (input/output) DOUBLE PRECISION array, dimension ( M )   
           On entry, VF(1:NL+1) contains the first components of all   
           right singular vectors of the upper block; and VF(NL+2:M)   
           contains the first components of all right singular vectors   
           of the lower block. On exit, VF contains the first components   
           of all right singular vectors of the bidiagonal matrix.   

    VFW    (workspace) DOUBLE PRECISION array, dimension ( M )   
           Workspace for VF.   

    VL     (input/output) DOUBLE PRECISION array, dimension ( M )   
           On entry, VL(1:NL+1) contains the  last components of all   
           right singular vectors of the upper block; and VL(NL+2:M)   
           contains the last components of all right singular vectors   
           of the lower block. On exit, VL contains the last components   
           of all right singular vectors of the bidiagonal matrix.   

    VLW    (workspace) DOUBLE PRECISION array, dimension ( M )   
           Workspace for VL.   

    ALPHA  (input) DOUBLE PRECISION   
           Contains the diagonal element associated with the added row.   

    BETA   (input) DOUBLE PRECISION   
           Contains the off-diagonal element associated with the added   
           row.   

    DSIGMA (output) DOUBLE PRECISION array, dimension ( N )   
           Contains a copy of the diagonal elements (K-1 singular values   
           and one zero) in the secular equation.   

    IDX    (workspace) INTEGER array, dimension ( N )   
           This will contain the permutation used to sort the contents of   
           D into ascending order.   

    IDXP   (workspace) INTEGER array, dimension ( N )   
           This will contain the permutation used to place deflated   
           values of D at the end of the array. On output IDXP(2:K)   
           points to the nondeflated D-values and IDXP(K+1:N)   
           points to the deflated singular values.   

    IDXQ   (input) INTEGER array, dimension ( N )   
           This contains the permutation which separately sorts the two   
           sub-problems in D into ascending order.  Note that entries in   
           the first half of this permutation must first be moved one   
           position backward; and entries in the second half   
           must first have NL+1 added to their values.   

    PERM   (output) INTEGER array, dimension ( N )   
           The permutations (from deflation and sorting) to be applied   
           to each singular block. Not referenced if ICOMPQ = 0.   

    GIVPTR (output) INTEGER   
           The number of Givens rotations which took place in this   
           subproblem. Not referenced if ICOMPQ = 0.   

    GIVCOL (output) INTEGER array, dimension ( LDGCOL, 2 )   
           Each pair of numbers indicates a pair of columns to take place   
           in a Givens rotation. Not referenced if ICOMPQ = 0.   

    LDGCOL (input) INTEGER   
           The leading dimension of GIVCOL, must be at least N.   

    GIVNUM (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 )   
           Each number indicates the C or S value to be used in the   
           corresponding Givens rotation. Not referenced if ICOMPQ = 0.   

    LDGNUM (input) INTEGER   
           The leading dimension of GIVNUM, must be at least N.   

    C      (output) DOUBLE PRECISION   
           C contains garbage if SQRE =0 and the C-value of a Givens   
           rotation related to the right null space if SQRE = 1.   

    S      (output) DOUBLE PRECISION   
           S contains garbage if SQRE =0 and the S-value of a Givens   
           rotation related to the right null space if SQRE = 1.   

    INFO   (output) INTEGER   
           = 0:  successful exit.   
           < 0:  if INFO = -i, the i-th argument had an illegal value.   

    Further Details   
    ===============   

    Based on contributions by   
       Ming Gu and Huan Ren, Computer Science Division, University of   
       California at Berkeley, USA   

    =====================================================================   



       Test the input parameters.   

       Parameter adjustments */
    --d__;
    --z__;
    --zw;
    --vf;
    --vfw;
    --vl;
    --vlw;
    --dsigma;
    --idx;
    --idxp;
    --idxq;
    --perm;
    givcol_dim1 = *ldgcol;
    givcol_offset = 1 + givcol_dim1;
    givcol -= givcol_offset;
    givnum_dim1 = *ldgnum;
    givnum_offset = 1 + givnum_dim1;
    givnum -= givnum_offset;

    /* Function Body */
    *info = 0;
    n = *nl + *nr + 1;
    m = n + *sqre;

    if (*icompq < 0 || *icompq > 1) {
	*info = -1;
    } else if (*nl < 1) {
	*info = -2;
    } else if (*nr < 1) {
	*info = -3;
    } else if (*sqre < 0 || *sqre > 1) {
	*info = -4;
    } else if (*ldgcol < n) {
	*info = -22;
    } else if (*ldgnum < n) {
	*info = -24;
    }
    if (*info != 0) {
	i__1 = -(*info);
	splicingxerbla_("DLASD7", &i__1, (ftnlen)6);
	return 0;
    }

    nlp1 = *nl + 1;
    nlp2 = *nl + 2;
    if (*icompq == 1) {
	*givptr = 0;
    }

/*     Generate the first part of the vector Z and move the singular   
       values in the first part of D one position backward. */

    z1 = *alpha * vl[nlp1];
    vl[nlp1] = 0.;
    tau = vf[nlp1];
    for (i__ = *nl; i__ >= 1; --i__) {
	z__[i__ + 1] = *alpha * vl[i__];
	vl[i__] = 0.;
	vf[i__ + 1] = vf[i__];
	d__[i__ + 1] = d__[i__];
	idxq[i__ + 1] = idxq[i__] + 1;
/* L10: */
    }
    vf[1] = tau;

/*     Generate the second part of the vector Z. */

    i__1 = m;
    for (i__ = nlp2; i__ <= i__1; ++i__) {
	z__[i__] = *beta * vf[i__];
	vf[i__] = 0.;
/* L20: */
    }

/*     Sort the singular values into increasing order */

    i__1 = n;
    for (i__ = nlp2; i__ <= i__1; ++i__) {
	idxq[i__] += nlp1;
/* L30: */
    }

/*     DSIGMA, IDXC, IDXC, and ZW are used as storage space. */

    i__1 = n;
    for (i__ = 2; i__ <= i__1; ++i__) {
	dsigma[i__] = d__[idxq[i__]];
	zw[i__] = z__[idxq[i__]];
	vfw[i__] = vf[idxq[i__]];
	vlw[i__] = vl[idxq[i__]];
/* L40: */
    }

    splicingdlamrg_(nl, nr, &dsigma[2], &c__1, &c__1, &idx[2]);

    i__1 = n;
    for (i__ = 2; i__ <= i__1; ++i__) {
	idxi = idx[i__] + 1;
	d__[i__] = dsigma[idxi];
	z__[i__] = zw[idxi];
	vf[i__] = vfw[idxi];
	vl[i__] = vlw[idxi];
/* L50: */
    }

/*     Calculate the allowable deflation tolerence */

    eps = splicingdlamch_("Epsilon");
/* Computing MAX */
    d__1 = abs(*alpha), d__2 = abs(*beta);
    tol = max(d__1,d__2);
/* Computing MAX */
    d__2 = (d__1 = d__[n], abs(d__1));
    tol = eps * 64. * max(d__2,tol);

/*     There are 2 kinds of deflation -- first a value in the z-vector   
       is small, second two (or more) singular values are very close   
       together (their difference is small).   

       If the value in the z-vector is small, we simply permute the   
       array so that the corresponding singular value is moved to the   
       end.   

       If two values in the D-vector are close, we perform a two-sided   
       rotation designed to make one of the corresponding z-vector   
       entries zero, and then permute the array so that the deflated   
       singular value is moved to the end.   

       If there are multiple singular values then the problem deflates.   
       Here the number of equal singular values are found.  As each equal   
       singular value is found, an elementary reflector is computed to   
       rotate the corresponding singular subspace so that the   
       corresponding components of Z are zero in this new basis. */

    *k = 1;
    k2 = n + 1;
    i__1 = n;
    for (j = 2; j <= i__1; ++j) {
	if ((d__1 = z__[j], abs(d__1)) <= tol) {

/*           Deflate due to small z component. */

	    --k2;
	    idxp[k2] = j;
	    if (j == n) {
		goto L100;
	    }
	} else {
	    jprev = j;
	    goto L70;
	}
/* L60: */
    }
L70:
    j = jprev;
L80:
    ++j;
    if (j > n) {
	goto L90;
    }
    if ((d__1 = z__[j], abs(d__1)) <= tol) {

/*        Deflate due to small z component. */

	--k2;
	idxp[k2] = j;
    } else {

/*        Check if singular values are close enough to allow deflation. */

	if ((d__1 = d__[j] - d__[jprev], abs(d__1)) <= tol) {

/*           Deflation is possible. */

	    *s = z__[jprev];
	    *c__ = z__[j];

/*           Find sqrt(a**2+b**2) without overflow or   
             destructive underflow. */

	    tau = splicingdlapy2_(c__, s);
	    z__[j] = tau;
	    z__[jprev] = 0.;
	    *c__ /= tau;
	    *s = -(*s) / tau;

/*           Record the appropriate Givens rotation */

	    if (*icompq == 1) {
		++(*givptr);
		idxjp = idxq[idx[jprev] + 1];
		idxj = idxq[idx[j] + 1];
		if (idxjp <= nlp1) {
		    --idxjp;
		}
		if (idxj <= nlp1) {
		    --idxj;
		}
		givcol[*givptr + (givcol_dim1 << 1)] = idxjp;
		givcol[*givptr + givcol_dim1] = idxj;
		givnum[*givptr + (givnum_dim1 << 1)] = *c__;
		givnum[*givptr + givnum_dim1] = *s;
	    }
	    splicingdrot_(&c__1, &vf[jprev], &c__1, &vf[j], &c__1, c__, s);
	    splicingdrot_(&c__1, &vl[jprev], &c__1, &vl[j], &c__1, c__, s);
	    --k2;
	    idxp[k2] = jprev;
	    jprev = j;
	} else {
	    ++(*k);
	    zw[*k] = z__[jprev];
	    dsigma[*k] = d__[jprev];
	    idxp[*k] = jprev;
	    jprev = j;
	}
    }
    goto L80;
L90:

/*     Record the last singular value. */

    ++(*k);
    zw[*k] = z__[jprev];
    dsigma[*k] = d__[jprev];
    idxp[*k] = jprev;

L100:

/*     Sort the singular values into DSIGMA. The singular values which   
       were not deflated go into the first K slots of DSIGMA, except   
       that DSIGMA(1) is treated separately. */

    i__1 = n;
    for (j = 2; j <= i__1; ++j) {
	jp = idxp[j];
	dsigma[j] = d__[jp];
	vfw[j] = vf[jp];
	vlw[j] = vl[jp];
/* L110: */
    }
    if (*icompq == 1) {
	i__1 = n;
	for (j = 2; j <= i__1; ++j) {
	    jp = idxp[j];
	    perm[j] = idxq[idx[jp] + 1];
	    if (perm[j] <= nlp1) {
		--perm[j];
	    }
/* L120: */
	}
    }

/*     The deflated singular values go back into the last N - K slots of   
       D. */

    i__1 = n - *k;
    splicingdcopy_(&i__1, &dsigma[*k + 1], &c__1, &d__[*k + 1], &c__1);

/*     Determine DSIGMA(1), DSIGMA(2), Z(1), VF(1), VL(1), VF(M), and   
       VL(M). */

    dsigma[1] = 0.;
    hlftol = tol / 2.;
    if (abs(dsigma[2]) <= hlftol) {
	dsigma[2] = hlftol;
    }
    if (m > n) {
	z__[1] = splicingdlapy2_(&z1, &z__[m]);
	if (z__[1] <= tol) {
	    *c__ = 1.;
	    *s = 0.;
	    z__[1] = tol;
	} else {
	    *c__ = z1 / z__[1];
	    *s = -z__[m] / z__[1];
	}
	splicingdrot_(&c__1, &vf[m], &c__1, &vf[1], &c__1, c__, s);
	splicingdrot_(&c__1, &vl[m], &c__1, &vl[1], &c__1, c__, s);
    } else {
	if (abs(z1) <= tol) {
	    z__[1] = tol;
	} else {
	    z__[1] = z1;
	}
    }

/*     Restore Z, VF, and VL. */

    i__1 = *k - 1;
    splicingdcopy_(&i__1, &zw[2], &c__1, &z__[2], &c__1);
    i__1 = n - 1;
    splicingdcopy_(&i__1, &vfw[2], &c__1, &vf[2], &c__1);
    i__1 = n - 1;
    splicingdcopy_(&i__1, &vlw[2], &c__1, &vl[2], &c__1);

    return 0;

/*     End of DLASD7 */

} /* splicingdlasd7_ */

