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#include "rb_lapack.h"
extern VOID dlaed0_(integer* icompq, integer* qsiz, integer* n, doublereal* d, doublereal* e, doublereal* q, integer* ldq, doublereal* qstore, integer* ldqs, doublereal* work, integer* iwork, integer* info);
static VALUE
rblapack_dlaed0(int argc, VALUE *argv, VALUE self){
VALUE rblapack_icompq;
integer icompq;
VALUE rblapack_qsiz;
integer qsiz;
VALUE rblapack_d;
doublereal *d;
VALUE rblapack_e;
doublereal *e;
VALUE rblapack_q;
doublereal *q;
VALUE rblapack_info;
integer info;
VALUE rblapack_d_out__;
doublereal *d_out__;
VALUE rblapack_q_out__;
doublereal *q_out__;
doublereal *qstore;
doublereal *work;
integer *iwork;
integer n;
integer ldq;
integer ldqs;
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 = NumRu::Lapack.dlaed0( icompq, qsiz, d, e, q, [:usage => usage, :help => help])\n\n\nFORTRAN MANUAL\n SUBROUTINE DLAED0( ICOMPQ, QSIZ, N, D, E, Q, LDQ, QSTORE, LDQS, WORK, IWORK, INFO )\n\n* Purpose\n* =======\n*\n* DLAED0 computes all eigenvalues and corresponding eigenvectors of a\n* symmetric tridiagonal matrix using the divide and conquer method.\n*\n\n* Arguments\n* =========\n*\n* ICOMPQ (input) INTEGER\n* = 0: Compute eigenvalues only.\n* = 1: Compute eigenvectors of original dense symmetric matrix\n* also. On entry, Q contains the orthogonal matrix used\n* to reduce the original matrix to tridiagonal form.\n* = 2: Compute eigenvalues and eigenvectors of tridiagonal\n* matrix.\n*\n* QSIZ (input) INTEGER\n* The dimension of the orthogonal matrix used to reduce\n* the full matrix to tridiagonal form. QSIZ >= N if ICOMPQ = 1.\n*\n* N (input) INTEGER\n* The dimension of the symmetric tridiagonal matrix. N >= 0.\n*\n* D (input/output) DOUBLE PRECISION array, dimension (N)\n* On entry, the main diagonal of the tridiagonal matrix.\n* On exit, its eigenvalues.\n*\n* E (input) DOUBLE PRECISION array, dimension (N-1)\n* The off-diagonal elements of the tridiagonal matrix.\n* On exit, E has been destroyed.\n*\n* Q (input/output) DOUBLE PRECISION array, dimension (LDQ, N)\n* On entry, Q must contain an N-by-N orthogonal matrix.\n* If ICOMPQ = 0 Q is not referenced.\n* If ICOMPQ = 1 On entry, Q is a subset of the columns of the\n* orthogonal matrix used to reduce the full\n* matrix to tridiagonal form corresponding to\n* the subset of the full matrix which is being\n* decomposed at this time.\n* If ICOMPQ = 2 On entry, Q will be the identity matrix.\n* On exit, Q contains the eigenvectors of the\n* tridiagonal matrix.\n*\n* LDQ (input) INTEGER\n* The leading dimension of the array Q. If eigenvectors are\n* desired, then LDQ >= max(1,N). In any case, LDQ >= 1.\n*\n* QSTORE (workspace) DOUBLE PRECISION array, dimension (LDQS, N)\n* Referenced only when ICOMPQ = 1. Used to store parts of\n* the eigenvector matrix when the updating matrix multiplies\n* take place.\n*\n* LDQS (input) INTEGER\n* The leading dimension of the array QSTORE. If ICOMPQ = 1,\n* then LDQS >= max(1,N). In any case, LDQS >= 1.\n*\n* WORK (workspace) DOUBLE PRECISION array,\n* If ICOMPQ = 0 or 1, the dimension of WORK must be at least\n* 1 + 3*N + 2*N*lg N + 2*N**2\n* ( lg( N ) = smallest integer k\n* such that 2^k >= N )\n* If ICOMPQ = 2, the dimension of WORK must be at least\n* 4*N + N**2.\n*\n* IWORK (workspace) INTEGER array,\n* If ICOMPQ = 0 or 1, the dimension of IWORK must be at least\n* 6 + 6*N + 5*N*lg N.\n* ( lg( N ) = smallest integer k\n* such that 2^k >= N )\n* If ICOMPQ = 2, the dimension of IWORK must be at least\n* 3 + 5*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: The algorithm failed to compute an eigenvalue while\n* working on the submatrix lying in rows and columns\n* INFO/(N+1) through mod(INFO,N+1).\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*\n* =====================================================================\n*\n\n");
return Qnil;
}
if (rb_hash_aref(rblapack_options, sUsage) == Qtrue) {
printf("%s\n", "USAGE:\n info, d, q = NumRu::Lapack.dlaed0( icompq, qsiz, d, e, q, [: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_icompq = argv[0];
rblapack_qsiz = argv[1];
rblapack_d = argv[2];
rblapack_e = argv[3];
rblapack_q = argv[4];
if (argc == 5) {
} else if (rblapack_options != Qnil) {
} else {
}
icompq = NUM2INT(rblapack_icompq);
if (!NA_IsNArray(rblapack_d))
rb_raise(rb_eArgError, "d (3th argument) must be NArray");
if (NA_RANK(rblapack_d) != 1)
rb_raise(rb_eArgError, "rank of d (3th argument) must be %d", 1);
n = NA_SHAPE0(rblapack_d);
if (NA_TYPE(rblapack_d) != NA_DFLOAT)
rblapack_d = na_change_type(rblapack_d, NA_DFLOAT);
d = NA_PTR_TYPE(rblapack_d, doublereal*);
if (!NA_IsNArray(rblapack_q))
rb_raise(rb_eArgError, "q (5th argument) must be NArray");
if (NA_RANK(rblapack_q) != 2)
rb_raise(rb_eArgError, "rank of q (5th 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_DFLOAT)
rblapack_q = na_change_type(rblapack_q, NA_DFLOAT);
q = NA_PTR_TYPE(rblapack_q, doublereal*);
qsiz = NUM2INT(rblapack_qsiz);
ldqs = icompq == 1 ? MAX(1,n) : 1;
if (!NA_IsNArray(rblapack_e))
rb_raise(rb_eArgError, "e (4th argument) must be NArray");
if (NA_RANK(rblapack_e) != 1)
rb_raise(rb_eArgError, "rank of e (4th argument) must be %d", 1);
if (NA_SHAPE0(rblapack_e) != (n-1))
rb_raise(rb_eRuntimeError, "shape 0 of e must be %d", n-1);
if (NA_TYPE(rblapack_e) != NA_DFLOAT)
rblapack_e = na_change_type(rblapack_e, NA_DFLOAT);
e = NA_PTR_TYPE(rblapack_e, doublereal*);
{
na_shape_t shape[1];
shape[0] = n;
rblapack_d_out__ = na_make_object(NA_DFLOAT, 1, shape, cNArray);
}
d_out__ = NA_PTR_TYPE(rblapack_d_out__, doublereal*);
MEMCPY(d_out__, d, doublereal, 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_DFLOAT, 2, shape, cNArray);
}
q_out__ = NA_PTR_TYPE(rblapack_q_out__, doublereal*);
MEMCPY(q_out__, q, doublereal, NA_TOTAL(rblapack_q));
rblapack_q = rblapack_q_out__;
q = q_out__;
qstore = ALLOC_N(doublereal, (ldqs)*(n));
work = ALLOC_N(doublereal, (((icompq == 0) || (icompq == 1)) ? 1 + 3*n + 2*n*LG(n) + 2*pow(n,2) : icompq == 2 ? 4*n + pow(n,2) : 0));
iwork = ALLOC_N(integer, (((icompq == 0) || (icompq == 1)) ? 6 + 6*n + 5*n*LG(n) : icompq == 2 ? 3 + 5*n : 0));
dlaed0_(&icompq, &qsiz, &n, d, e, q, &ldq, qstore, &ldqs, work, iwork, &info);
free(qstore);
free(work);
free(iwork);
rblapack_info = INT2NUM(info);
return rb_ary_new3(3, rblapack_info, rblapack_d, rblapack_q);
}
void
init_lapack_dlaed0(VALUE mLapack, VALUE sH, VALUE sU, VALUE zero){
sHelp = sH;
sUsage = sU;
rblapack_ZERO = zero;
rb_define_module_function(mLapack, "dlaed0", rblapack_dlaed0, -1);
}
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