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#include "rb_lapack.h"
extern VOID slaed1_(integer* n, real* d, real* q, integer* ldq, integer* indxq, real* rho, integer* cutpnt, real* work, integer* iwork, integer* info);
static VALUE
rblapack_slaed1(int argc, VALUE *argv, VALUE self){
VALUE rblapack_d;
real *d;
VALUE rblapack_q;
real *q;
VALUE rblapack_indxq;
integer *indxq;
VALUE rblapack_rho;
real rho;
VALUE rblapack_cutpnt;
integer cutpnt;
VALUE rblapack_info;
integer info;
VALUE rblapack_d_out__;
real *d_out__;
VALUE rblapack_q_out__;
real *q_out__;
VALUE rblapack_indxq_out__;
integer *indxq_out__;
real *work;
integer *iwork;
integer n;
integer ldq;
VALUE rblapack_options;
if (argc > 0 && TYPE(argv[argc-1]) == T_HASH) {
argc--;
rblapack_options = argv[argc];
if (rb_hash_aref(rblapack_options, sHelp) == Qtrue) {
printf("%s\n", "USAGE:\n info, d, q, indxq = NumRu::Lapack.slaed1( d, q, indxq, rho, cutpnt, [:usage => usage, :help => help])\n\n\nFORTRAN MANUAL\n SUBROUTINE SLAED1( N, D, Q, LDQ, INDXQ, RHO, CUTPNT, WORK, IWORK, INFO )\n\n* Purpose\n* =======\n*\n* SLAED1 computes the updated eigensystem of a diagonal\n* matrix after modification by a rank-one symmetric matrix. This\n* routine is used only for the eigenproblem which requires all\n* eigenvalues and eigenvectors of a tridiagonal matrix. SLAED7 handles\n* the case in which eigenvalues only or eigenvalues and eigenvectors\n* of a full symmetric matrix (which was reduced to tridiagonal form)\n* are desired.\n*\n* T = Q(in) ( D(in) + RHO * Z*Z' ) Q'(in) = Q(out) * D(out) * Q'(out)\n*\n* where Z = Q'u, u is a vector of length N with ones in the\n* CUTPNT and CUTPNT + 1 th elements and zeros elsewhere.\n*\n* The eigenvectors of the original matrix are stored in Q, and the\n* eigenvalues are in D. The algorithm consists of three stages:\n*\n* The first stage consists of deflating the size of the problem\n* when there are multiple eigenvalues or if there is a zero in\n* the Z vector. For each such occurrence the dimension of the\n* secular equation problem is reduced by one. This stage is\n* performed by the routine SLAED2.\n*\n* The second stage consists of calculating the updated\n* eigenvalues. This is done by finding the roots of the secular\n* equation via the routine SLAED4 (as called by SLAED3).\n* This routine also calculates the eigenvectors of the current\n* problem.\n*\n* The final stage consists of computing the updated eigenvectors\n* directly using the updated eigenvalues. The eigenvectors for\n* the current problem are multiplied with the eigenvectors from\n* the overall problem.\n*\n\n* Arguments\n* =========\n*\n* N (input) INTEGER\n* The dimension of the symmetric tridiagonal matrix. N >= 0.\n*\n* D (input/output) REAL array, dimension (N)\n* On entry, the eigenvalues of the rank-1-perturbed matrix.\n* On exit, the eigenvalues of the repaired matrix.\n*\n* Q (input/output) REAL array, dimension (LDQ,N)\n* On entry, the eigenvectors of the rank-1-perturbed matrix.\n* On exit, the eigenvectors of the repaired tridiagonal matrix.\n*\n* LDQ (input) INTEGER\n* The leading dimension of the array Q. LDQ >= max(1,N).\n*\n* INDXQ (input/output) INTEGER array, dimension (N)\n* On entry, the permutation which separately sorts the two\n* subproblems in D into ascending order.\n* On exit, the permutation which will reintegrate the\n* subproblems back into sorted order,\n* i.e. D( INDXQ( I = 1, N ) ) will be in ascending order.\n*\n* RHO (input) REAL\n* The subdiagonal entry used to create the rank-1 modification.\n*\n* CUTPNT (input) INTEGER\n* The location of the last eigenvalue in the leading sub-matrix.\n* min(1,N) <= CUTPNT <= N/2.\n*\n* WORK (workspace) REAL array, dimension (4*N + N**2)\n*\n* IWORK (workspace) INTEGER array, dimension (4*N)\n*\n* INFO (output) INTEGER\n* = 0: successful exit.\n* < 0: if INFO = -i, the i-th argument had an illegal value.\n* > 0: if INFO = 1, an eigenvalue did not converge\n*\n\n* Further Details\n* ===============\n*\n* Based on contributions by\n* Jeff Rutter, Computer Science Division, University of California\n* at Berkeley, USA\n* Modified by Francoise Tisseur, University of Tennessee.\n*\n* =====================================================================\n*\n* .. Local Scalars ..\n INTEGER COLTYP, CPP1, I, IDLMDA, INDX, INDXC, INDXP,\n $ IQ2, IS, IW, IZ, K, N1, N2\n* ..\n* .. External Subroutines ..\n EXTERNAL SCOPY, SLAED2, SLAED3, SLAMRG, XERBLA\n* ..\n* .. Intrinsic Functions ..\n INTRINSIC MAX, MIN\n* ..\n\n");
return Qnil;
}
if (rb_hash_aref(rblapack_options, sUsage) == Qtrue) {
printf("%s\n", "USAGE:\n info, d, q, indxq = NumRu::Lapack.slaed1( d, q, indxq, rho, cutpnt, [:usage => usage, :help => help])\n");
return Qnil;
}
} else
rblapack_options = Qnil;
if (argc != 5 && argc != 5)
rb_raise(rb_eArgError,"wrong number of arguments (%d for 5)", argc);
rblapack_d = argv[0];
rblapack_q = argv[1];
rblapack_indxq = argv[2];
rblapack_rho = argv[3];
rblapack_cutpnt = argv[4];
if (argc == 5) {
} else if (rblapack_options != Qnil) {
} else {
}
if (!NA_IsNArray(rblapack_d))
rb_raise(rb_eArgError, "d (1th argument) must be NArray");
if (NA_RANK(rblapack_d) != 1)
rb_raise(rb_eArgError, "rank of d (1th argument) must be %d", 1);
n = NA_SHAPE0(rblapack_d);
if (NA_TYPE(rblapack_d) != NA_SFLOAT)
rblapack_d = na_change_type(rblapack_d, NA_SFLOAT);
d = NA_PTR_TYPE(rblapack_d, real*);
if (!NA_IsNArray(rblapack_indxq))
rb_raise(rb_eArgError, "indxq (3th argument) must be NArray");
if (NA_RANK(rblapack_indxq) != 1)
rb_raise(rb_eArgError, "rank of indxq (3th argument) must be %d", 1);
if (NA_SHAPE0(rblapack_indxq) != n)
rb_raise(rb_eRuntimeError, "shape 0 of indxq must be the same as shape 0 of d");
if (NA_TYPE(rblapack_indxq) != NA_LINT)
rblapack_indxq = na_change_type(rblapack_indxq, NA_LINT);
indxq = NA_PTR_TYPE(rblapack_indxq, integer*);
cutpnt = NUM2INT(rblapack_cutpnt);
if (!NA_IsNArray(rblapack_q))
rb_raise(rb_eArgError, "q (2th argument) must be NArray");
if (NA_RANK(rblapack_q) != 2)
rb_raise(rb_eArgError, "rank of q (2th argument) must be %d", 2);
ldq = NA_SHAPE0(rblapack_q);
if (NA_SHAPE1(rblapack_q) != n)
rb_raise(rb_eRuntimeError, "shape 1 of q must be the same as shape 0 of d");
if (NA_TYPE(rblapack_q) != NA_SFLOAT)
rblapack_q = na_change_type(rblapack_q, NA_SFLOAT);
q = NA_PTR_TYPE(rblapack_q, real*);
rho = (real)NUM2DBL(rblapack_rho);
{
na_shape_t shape[1];
shape[0] = n;
rblapack_d_out__ = na_make_object(NA_SFLOAT, 1, shape, cNArray);
}
d_out__ = NA_PTR_TYPE(rblapack_d_out__, real*);
MEMCPY(d_out__, d, real, NA_TOTAL(rblapack_d));
rblapack_d = rblapack_d_out__;
d = d_out__;
{
na_shape_t shape[2];
shape[0] = ldq;
shape[1] = n;
rblapack_q_out__ = na_make_object(NA_SFLOAT, 2, shape, cNArray);
}
q_out__ = NA_PTR_TYPE(rblapack_q_out__, real*);
MEMCPY(q_out__, q, real, NA_TOTAL(rblapack_q));
rblapack_q = rblapack_q_out__;
q = q_out__;
{
na_shape_t shape[1];
shape[0] = n;
rblapack_indxq_out__ = na_make_object(NA_LINT, 1, shape, cNArray);
}
indxq_out__ = NA_PTR_TYPE(rblapack_indxq_out__, integer*);
MEMCPY(indxq_out__, indxq, integer, NA_TOTAL(rblapack_indxq));
rblapack_indxq = rblapack_indxq_out__;
indxq = indxq_out__;
work = ALLOC_N(real, (4*n + pow(n,2)));
iwork = ALLOC_N(integer, (4*n));
slaed1_(&n, d, q, &ldq, indxq, &rho, &cutpnt, work, iwork, &info);
free(work);
free(iwork);
rblapack_info = INT2NUM(info);
return rb_ary_new3(4, rblapack_info, rblapack_d, rblapack_q, rblapack_indxq);
}
void
init_lapack_slaed1(VALUE mLapack, VALUE sH, VALUE sU, VALUE zero){
sHelp = sH;
sUsage = sU;
rblapack_ZERO = zero;
rb_define_module_function(mLapack, "slaed1", rblapack_slaed1, -1);
}
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