[] add metering mode to CLI

1 files changed, 403 insertions, 0 deletions

diff --git a/contrib/libs/clapack/cggsvd.c b/contrib/libs/clapack/cggsvd.c
new file mode 100644
index 0000000000..9415098a22
--- /dev/null
+++ b/contrib/libs/clapack/cggsvd.c
@@ -0,0 +1,403 @@
+/* cggsvd.f -- translated by f2c (version 20061008).
+   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"
+#include "blaswrap.h"
+
+/* Table of constant values */
+
+static integer c__1 = 1;
+
+/* Subroutine */ int cggsvd_(char *jobu, char *jobv, char *jobq, integer *m, 
+	integer *n, integer *p, integer *k, integer *l, complex *a, integer *
+	lda, complex *b, integer *ldb, real *alpha, real *beta, complex *u, 
+	integer *ldu, complex *v, integer *ldv, complex *q, integer *ldq, 
+	complex *work, real *rwork, integer *iwork, integer *info)
+{
+    /* System generated locals */
+    integer a_dim1, a_offset, b_dim1, b_offset, q_dim1, q_offset, u_dim1, 
+	    u_offset, v_dim1, v_offset, i__1, i__2;
+
+    /* Local variables */
+    integer i__, j;
+    real ulp;
+    integer ibnd;
+    real tola;
+    integer isub;
+    real tolb, unfl, temp, smax;
+    extern logical lsame_(char *, char *);
+    real anorm, bnorm;
+    logical wantq;
+    extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *, 
+	    integer *);
+    logical wantu, wantv;
+    extern doublereal clange_(char *, integer *, integer *, complex *, 
+	    integer *, real *), slamch_(char *);
+    extern /* Subroutine */ int ctgsja_(char *, char *, char *, integer *, 
+	    integer *, integer *, integer *, integer *, complex *, integer *, 
+	    complex *, integer *, real *, real *, real *, real *, complex *, 
+	    integer *, complex *, integer *, complex *, integer *, complex *, 
+	    integer *, integer *);
+    integer ncycle;
+    extern /* Subroutine */ int xerbla_(char *, integer *), cggsvp_(
+	    char *, char *, char *, integer *, integer *, integer *, complex *
+, integer *, complex *, integer *, real *, real *, integer *, 
+	    integer *, complex *, integer *, complex *, integer *, complex *, 
+	    integer *, integer *, real *, complex *, complex *, integer *);
+
+
+/*  -- LAPACK driver routine (version 3.2) -- */
+/*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
+/*     November 2006 */
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  CGGSVD computes the generalized singular value decomposition (GSVD) */
+/*  of an M-by-N complex matrix A and P-by-N complex matrix B: */
+
+/*        U'*A*Q = D1*( 0 R ),    V'*B*Q = D2*( 0 R ) */
+
+/*  where U, V and Q are unitary matrices, and Z' means the conjugate */
+/*  transpose of Z.  Let K+L = the effective numerical rank of the */
+/*  matrix (A',B')', then R is a (K+L)-by-(K+L) nonsingular upper */
+/*  triangular matrix, D1 and D2 are M-by-(K+L) and P-by-(K+L) "diagonal" */
+/*  matrices and of the following structures, respectively: */
+
+/*  If M-K-L >= 0, */
+
+/*                      K  L */
+/*         D1 =     K ( I  0 ) */
+/*                  L ( 0  C ) */
+/*              M-K-L ( 0  0 ) */
+
+/*                    K  L */
+/*         D2 =   L ( 0  S ) */
+/*              P-L ( 0  0 ) */
+
+/*                  N-K-L  K    L */
+/*    ( 0 R ) = K (  0   R11  R12 ) */
+/*              L (  0    0   R22 ) */
+/*  where */
+
+/*    C = diag( ALPHA(K+1), ... , ALPHA(K+L) ), */
+/*    S = diag( BETA(K+1),  ... , BETA(K+L) ), */
+/*    C**2 + S**2 = I. */
+
+/*    R is stored in A(1:K+L,N-K-L+1:N) on exit. */
+
+/*  If M-K-L < 0, */
+
+/*                    K M-K K+L-M */
+/*         D1 =   K ( I  0    0   ) */
+/*              M-K ( 0  C    0   ) */
+
+/*                      K M-K K+L-M */
+/*         D2 =   M-K ( 0  S    0  ) */
+/*              K+L-M ( 0  0    I  ) */
+/*                P-L ( 0  0    0  ) */
+
+/*                     N-K-L  K   M-K  K+L-M */
+/*    ( 0 R ) =     K ( 0    R11  R12  R13  ) */
+/*                M-K ( 0     0   R22  R23  ) */
+/*              K+L-M ( 0     0    0   R33  ) */
+
+/*  where */
+
+/*    C = diag( ALPHA(K+1), ... , ALPHA(M) ), */
+/*    S = diag( BETA(K+1),  ... , BETA(M) ), */
+/*    C**2 + S**2 = I. */
+
+/*    (R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N), and R33 is stored */
+/*    ( 0  R22 R23 ) */
+/*    in B(M-K+1:L,N+M-K-L+1:N) on exit. */
+
+/*  The routine computes C, S, R, and optionally the unitary */
+/*  transformation matrices U, V and Q. */
+
+/*  In particular, if B is an N-by-N nonsingular matrix, then the GSVD of */
+/*  A and B implicitly gives the SVD of A*inv(B): */
+/*                       A*inv(B) = U*(D1*inv(D2))*V'. */
+/*  If ( A',B')' has orthnormal columns, then the GSVD of A and B is also */
+/*  equal to the CS decomposition of A and B. Furthermore, the GSVD can */
+/*  be used to derive the solution of the eigenvalue problem: */
+/*                       A'*A x = lambda* B'*B x. */
+/*  In some literature, the GSVD of A and B is presented in the form */
+/*                   U'*A*X = ( 0 D1 ),   V'*B*X = ( 0 D2 ) */
+/*  where U and V are orthogonal and X is nonsingular, and D1 and D2 are */
+/*  ``diagonal''.  The former GSVD form can be converted to the latter */
+/*  form by taking the nonsingular matrix X as */
+
+/*                        X = Q*(  I   0    ) */
+/*                              (  0 inv(R) ) */
+
+/*  Arguments */
+/*  ========= */
+
+/*  JOBU    (input) CHARACTER*1 */
+/*          = 'U':  Unitary matrix U is computed; */
+/*          = 'N':  U is not computed. */
+
+/*  JOBV    (input) CHARACTER*1 */
+/*          = 'V':  Unitary matrix V is computed; */
+/*          = 'N':  V is not computed. */
+
+/*  JOBQ    (input) CHARACTER*1 */
+/*          = 'Q':  Unitary matrix Q is computed; */
+/*          = 'N':  Q is not computed. */
+
+/*  M       (input) INTEGER */
+/*          The number of rows of the matrix A.  M >= 0. */
+
+/*  N       (input) INTEGER */
+/*          The number of columns of the matrices A and B.  N >= 0. */
+
+/*  P       (input) INTEGER */
+/*          The number of rows of the matrix B.  P >= 0. */
+
+/*  K       (output) INTEGER */
+/*  L       (output) INTEGER */
+/*          On exit, K and L specify the dimension of the subblocks */
+/*          described in Purpose. */
+/*          K + L = effective numerical rank of (A',B')'. */
+
+/*  A       (input/output) COMPLEX array, dimension (LDA,N) */
+/*          On entry, the M-by-N matrix A. */
+/*          On exit, A contains the triangular matrix R, or part of R. */
+/*          See Purpose for details. */
+
+/*  LDA     (input) INTEGER */
+/*          The leading dimension of the array A. LDA >= max(1,M). */
+
+/*  B       (input/output) COMPLEX array, dimension (LDB,N) */
+/*          On entry, the P-by-N matrix B. */
+/*          On exit, B contains part of the triangular matrix R if */
+/*          M-K-L < 0.  See Purpose for details. */
+
+/*  LDB     (input) INTEGER */
+/*          The leading dimension of the array B. LDB >= max(1,P). */
+
+/*  ALPHA   (output) REAL array, dimension (N) */
+/*  BETA    (output) REAL array, dimension (N) */
+/*          On exit, ALPHA and BETA contain the generalized singular */
+/*          value pairs of A and B; */
+/*            ALPHA(1:K) = 1, */
+/*            BETA(1:K)  = 0, */
+/*          and if M-K-L >= 0, */
+/*            ALPHA(K+1:K+L) = C, */
+/*            BETA(K+1:K+L)  = S, */
+/*          or if M-K-L < 0, */
+/*            ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0 */
+/*            BETA(K+1:M) = S, BETA(M+1:K+L) = 1 */
+/*          and */
+/*            ALPHA(K+L+1:N) = 0 */
+/*            BETA(K+L+1:N)  = 0 */
+
+/*  U       (output) COMPLEX array, dimension (LDU,M) */
+/*          If JOBU = 'U', U contains the M-by-M unitary matrix U. */
+/*          If JOBU = 'N', U is not referenced. */
+
+/*  LDU     (input) INTEGER */
+/*          The leading dimension of the array U. LDU >= max(1,M) if */
+/*          JOBU = 'U'; LDU >= 1 otherwise. */
+
+/*  V       (output) COMPLEX array, dimension (LDV,P) */
+/*          If JOBV = 'V', V contains the P-by-P unitary matrix V. */
+/*          If JOBV = 'N', V is not referenced. */
+
+/*  LDV     (input) INTEGER */
+/*          The leading dimension of the array V. LDV >= max(1,P) if */
+/*          JOBV = 'V'; LDV >= 1 otherwise. */
+
+/*  Q       (output) COMPLEX array, dimension (LDQ,N) */
+/*          If JOBQ = 'Q', Q contains the N-by-N unitary matrix Q. */
+/*          If JOBQ = 'N', Q is not referenced. */
+
+/*  LDQ     (input) INTEGER */
+/*          The leading dimension of the array Q. LDQ >= max(1,N) if */
+/*          JOBQ = 'Q'; LDQ >= 1 otherwise. */
+
+/*  WORK    (workspace) COMPLEX array, dimension (max(3*N,M,P)+N) */
+
+/*  RWORK   (workspace) REAL array, dimension (2*N) */
+
+/*  IWORK   (workspace/output) INTEGER array, dimension (N) */
+/*          On exit, IWORK stores the sorting information. More */
+/*          precisely, the following loop will sort ALPHA */
+/*             for I = K+1, min(M,K+L) */
+/*                 swap ALPHA(I) and ALPHA(IWORK(I)) */
+/*             endfor */
+/*          such that ALPHA(1) >= ALPHA(2) >= ... >= ALPHA(N). */
+
+/*  INFO    (output) INTEGER */
+/*          = 0:  successful exit. */
+/*          < 0:  if INFO = -i, the i-th argument had an illegal value. */
+/*          > 0:  if INFO = 1, the Jacobi-type procedure failed to */
+/*                converge.  For further details, see subroutine CTGSJA. */
+
+/*  Internal Parameters */
+/*  =================== */
+
+/*  TOLA    REAL */
+/*  TOLB    REAL */
+/*          TOLA and TOLB are the thresholds to determine the effective */
+/*          rank of (A',B')'. Generally, they are set to */
+/*                   TOLA = MAX(M,N)*norm(A)*MACHEPS, */
+/*                   TOLB = MAX(P,N)*norm(B)*MACHEPS. */
+/*          The size of TOLA and TOLB may affect the size of backward */
+/*          errors of the decomposition. */
+
+/*  Further Details */
+/*  =============== */
+
+/*  2-96 Based on modifications by */
+/*     Ming Gu and Huan Ren, Computer Science Division, University of */
+/*     California at Berkeley, USA */
+
+/*  ===================================================================== */
+
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+/*     .. Executable Statements .. */
+
+/*     Decode and test the input parameters */
+
+    /* Parameter adjustments */
+    a_dim1 = *lda;
+    a_offset = 1 + a_dim1;
+    a -= a_offset;
+    b_dim1 = *ldb;
+    b_offset = 1 + b_dim1;
+    b -= b_offset;
+    --alpha;
+    --beta;
+    u_dim1 = *ldu;
+    u_offset = 1 + u_dim1;
+    u -= u_offset;
+    v_dim1 = *ldv;
+    v_offset = 1 + v_dim1;
+    v -= v_offset;
+    q_dim1 = *ldq;
+    q_offset = 1 + q_dim1;
+    q -= q_offset;
+    --work;
+    --rwork;
+    --iwork;
+
+    /* Function Body */
+    wantu = lsame_(jobu, "U");
+    wantv = lsame_(jobv, "V");
+    wantq = lsame_(jobq, "Q");
+
+    *info = 0;
+    if (! (wantu || lsame_(jobu, "N"))) {
+	*info = -1;
+    } else if (! (wantv || lsame_(jobv, "N"))) {
+	*info = -2;
+    } else if (! (wantq || lsame_(jobq, "N"))) {
+	*info = -3;
+    } else if (*m < 0) {
+	*info = -4;
+    } else if (*n < 0) {
+	*info = -5;
+    } else if (*p < 0) {
+	*info = -6;
+    } else if (*lda < max(1,*m)) {
+	*info = -10;
+    } else if (*ldb < max(1,*p)) {
+	*info = -12;
+    } else if (*ldu < 1 || wantu && *ldu < *m) {
+	*info = -16;
+    } else if (*ldv < 1 || wantv && *ldv < *p) {
+	*info = -18;
+    } else if (*ldq < 1 || wantq && *ldq < *n) {
+	*info = -20;
+    }
+    if (*info != 0) {
+	i__1 = -(*info);
+	xerbla_("CGGSVD", &i__1);
+	return 0;
+    }
+
+/*     Compute the Frobenius norm of matrices A and B */
+
+    anorm = clange_("1", m, n, &a[a_offset], lda, &rwork[1]);
+    bnorm = clange_("1", p, n, &b[b_offset], ldb, &rwork[1]);
+
+/*     Get machine precision and set up threshold for determining */
+/*     the effective numerical rank of the matrices A and B. */
+
+    ulp = slamch_("Precision");
+    unfl = slamch_("Safe Minimum");
+    tola = max(*m,*n) * dmax(anorm,unfl) * ulp;
+    tolb = max(*p,*n) * dmax(bnorm,unfl) * ulp;
+
+    cggsvp_(jobu, jobv, jobq, m, p, n, &a[a_offset], lda, &b[b_offset], ldb, &
+	    tola, &tolb, k, l, &u[u_offset], ldu, &v[v_offset], ldv, &q[
+	    q_offset], ldq, &iwork[1], &rwork[1], &work[1], &work[*n + 1], 
+	    info);
+
+/*     Compute the GSVD of two upper "triangular" matrices */
+
+    ctgsja_(jobu, jobv, jobq, m, p, n, k, l, &a[a_offset], lda, &b[b_offset], 
+	    ldb, &tola, &tolb, &alpha[1], &beta[1], &u[u_offset], ldu, &v[
+	    v_offset], ldv, &q[q_offset], ldq, &work[1], &ncycle, info);
+
+/*     Sort the singular values and store the pivot indices in IWORK */
+/*     Copy ALPHA to RWORK, then sort ALPHA in RWORK */
+
+    scopy_(n, &alpha[1], &c__1, &rwork[1], &c__1);
+/* Computing MIN */
+    i__1 = *l, i__2 = *m - *k;
+    ibnd = min(i__1,i__2);
+    i__1 = ibnd;
+    for (i__ = 1; i__ <= i__1; ++i__) {
+
+/*        Scan for largest ALPHA(K+I) */
+
+	isub = i__;
+	smax = rwork[*k + i__];
+	i__2 = ibnd;
+	for (j = i__ + 1; j <= i__2; ++j) {
+	    temp = rwork[*k + j];
+	    if (temp > smax) {
+		isub = j;
+		smax = temp;
+	    }
+/* L10: */
+	}
+	if (isub != i__) {
+	    rwork[*k + isub] = rwork[*k + i__];
+	    rwork[*k + i__] = smax;
+	    iwork[*k + i__] = *k + isub;
+	} else {
+	    iwork[*k + i__] = *k + i__;
+	}
+/* L20: */
+    }
+
+    return 0;
+
+/*     End of CGGSVD */
+
+} /* cggsvd_ */