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#include "rb_lapack.h"
extern VOID sgelss_(integer* m, integer* n, integer* nrhs, real* a, integer* lda, real* b, integer* ldb, real* s, real* rcond, integer* rank, real* work, integer* lwork, integer* info);
static VALUE
rblapack_sgelss(int argc, VALUE *argv, VALUE self){
VALUE rblapack_a;
real *a;
VALUE rblapack_b;
real *b;
VALUE rblapack_rcond;
real rcond;
VALUE rblapack_lwork;
integer lwork;
VALUE rblapack_s;
real *s;
VALUE rblapack_rank;
integer rank;
VALUE rblapack_work;
real *work;
VALUE rblapack_info;
integer info;
VALUE rblapack_a_out__;
real *a_out__;
VALUE rblapack_b_out__;
real *b_out__;
integer lda;
integer n;
integer m;
integer nrhs;
integer ldb;
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 s, rank, work, info, a, b = NumRu::Lapack.sgelss( a, b, rcond, [:lwork => lwork, :usage => usage, :help => help])\n\n\nFORTRAN MANUAL\n SUBROUTINE SGELSS( M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, WORK, LWORK, INFO )\n\n* Purpose\n* =======\n*\n* SGELSS computes the minimum norm solution to a real linear least\n* squares problem:\n*\n* Minimize 2-norm(| b - A*x |).\n*\n* using the singular value decomposition (SVD) of A. A is an M-by-N\n* matrix which may be rank-deficient.\n*\n* Several right hand side vectors b and solution vectors x can be\n* handled in a single call; they are stored as the columns of the\n* M-by-NRHS right hand side matrix B and the N-by-NRHS solution matrix\n* X.\n*\n* The effective rank of A is determined by treating as zero those\n* singular values which are less than RCOND times the largest singular\n* value.\n*\n\n* Arguments\n* =========\n*\n* M (input) INTEGER\n* The number of rows of the matrix A. M >= 0.\n*\n* N (input) INTEGER\n* The number of columns of the matrix A. N >= 0.\n*\n* NRHS (input) INTEGER\n* The number of right hand sides, i.e., the number of columns\n* of the matrices B and X. NRHS >= 0.\n*\n* A (input/output) REAL array, dimension (LDA,N)\n* On entry, the M-by-N matrix A.\n* On exit, the first min(m,n) rows of A are overwritten with\n* its right singular vectors, stored rowwise.\n*\n* LDA (input) INTEGER\n* The leading dimension of the array A. LDA >= max(1,M).\n*\n* B (input/output) REAL array, dimension (LDB,NRHS)\n* On entry, the M-by-NRHS right hand side matrix B.\n* On exit, B is overwritten by the N-by-NRHS solution\n* matrix X. If m >= n and RANK = n, the residual\n* sum-of-squares for the solution in the i-th column is given\n* by the sum of squares of elements n+1:m in that column.\n*\n* LDB (input) INTEGER\n* The leading dimension of the array B. LDB >= max(1,max(M,N)).\n*\n* S (output) REAL array, dimension (min(M,N))\n* The singular values of A in decreasing order.\n* The condition number of A in the 2-norm = S(1)/S(min(m,n)).\n*\n* RCOND (input) REAL\n* RCOND is used to determine the effective rank of A.\n* Singular values S(i) <= RCOND*S(1) are treated as zero.\n* If RCOND < 0, machine precision is used instead.\n*\n* RANK (output) INTEGER\n* The effective rank of A, i.e., the number of singular values\n* which are greater than RCOND*S(1).\n*\n* WORK (workspace/output) REAL array, dimension (MAX(1,LWORK))\n* On exit, if INFO = 0, WORK(1) returns the optimal LWORK.\n*\n* LWORK (input) INTEGER\n* The dimension of the array WORK. LWORK >= 1, and also:\n* LWORK >= 3*min(M,N) + max( 2*min(M,N), max(M,N), NRHS )\n* For good performance, LWORK should generally be larger.\n*\n* If LWORK = -1, then a workspace query is assumed; the routine\n* only calculates the optimal size of the WORK array, returns\n* this value as the first entry of the WORK array, and no error\n* message related to LWORK is issued by XERBLA.\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 for computing the SVD failed to converge;\n* if INFO = i, i off-diagonal elements of an intermediate\n* bidiagonal form did not converge to zero.\n*\n\n* =====================================================================\n*\n\n");
return Qnil;
}
if (rb_hash_aref(rblapack_options, sUsage) == Qtrue) {
printf("%s\n", "USAGE:\n s, rank, work, info, a, b = NumRu::Lapack.sgelss( a, b, rcond, [:lwork => lwork, :usage => usage, :help => help])\n");
return Qnil;
}
} else
rblapack_options = Qnil;
if (argc != 3 && argc != 4)
rb_raise(rb_eArgError,"wrong number of arguments (%d for 3)", argc);
rblapack_a = argv[0];
rblapack_b = argv[1];
rblapack_rcond = argv[2];
if (argc == 4) {
rblapack_lwork = argv[3];
} else if (rblapack_options != Qnil) {
rblapack_lwork = rb_hash_aref(rblapack_options, ID2SYM(rb_intern("lwork")));
} else {
rblapack_lwork = Qnil;
}
if (!NA_IsNArray(rblapack_a))
rb_raise(rb_eArgError, "a (1th argument) must be NArray");
if (NA_RANK(rblapack_a) != 2)
rb_raise(rb_eArgError, "rank of a (1th argument) must be %d", 2);
lda = NA_SHAPE0(rblapack_a);
n = NA_SHAPE1(rblapack_a);
if (NA_TYPE(rblapack_a) != NA_SFLOAT)
rblapack_a = na_change_type(rblapack_a, NA_SFLOAT);
a = NA_PTR_TYPE(rblapack_a, real*);
rcond = (real)NUM2DBL(rblapack_rcond);
m = lda;
if (!NA_IsNArray(rblapack_b))
rb_raise(rb_eArgError, "b (2th argument) must be NArray");
if (NA_RANK(rblapack_b) != 2)
rb_raise(rb_eArgError, "rank of b (2th argument) must be %d", 2);
if (NA_SHAPE0(rblapack_b) != m)
rb_raise(rb_eRuntimeError, "shape 0 of b must be lda");
nrhs = NA_SHAPE1(rblapack_b);
if (NA_TYPE(rblapack_b) != NA_SFLOAT)
rblapack_b = na_change_type(rblapack_b, NA_SFLOAT);
b = NA_PTR_TYPE(rblapack_b, real*);
ldb = MAX(m,n);
if (rblapack_lwork == Qnil)
lwork = 3*MIN(m,n) + MAX(MAX(2*MIN(m,n),MAX(m,n)),nrhs);
else {
lwork = NUM2INT(rblapack_lwork);
}
{
na_shape_t shape[1];
shape[0] = MIN(m,n);
rblapack_s = na_make_object(NA_SFLOAT, 1, shape, cNArray);
}
s = NA_PTR_TYPE(rblapack_s, real*);
{
na_shape_t shape[1];
shape[0] = MAX(1,lwork);
rblapack_work = na_make_object(NA_SFLOAT, 1, shape, cNArray);
}
work = NA_PTR_TYPE(rblapack_work, real*);
{
na_shape_t shape[2];
shape[0] = lda;
shape[1] = n;
rblapack_a_out__ = na_make_object(NA_SFLOAT, 2, shape, cNArray);
}
a_out__ = NA_PTR_TYPE(rblapack_a_out__, real*);
MEMCPY(a_out__, a, real, NA_TOTAL(rblapack_a));
rblapack_a = rblapack_a_out__;
a = a_out__;
{
na_shape_t shape[2];
shape[0] = MAX(m, n);
shape[1] = nrhs;
rblapack_b_out__ = na_make_object(NA_SFLOAT, 2, shape, cNArray);
}
b_out__ = NA_PTR_TYPE(rblapack_b_out__, real*);
{
VALUE __shape__[3];
__shape__[0] = m < n ? rb_range_new(rblapack_ZERO, INT2NUM(m), Qtrue) : Qtrue;
__shape__[1] = Qtrue;
__shape__[2] = rblapack_b;
na_aset(3, __shape__, rblapack_b_out__);
}
rblapack_b = rblapack_b_out__;
b = b_out__;
sgelss_(&m, &n, &nrhs, a, &lda, b, &ldb, s, &rcond, &rank, work, &lwork, &info);
rblapack_rank = INT2NUM(rank);
rblapack_info = INT2NUM(info);
{
VALUE __shape__[2];
__shape__[0] = m < n ? Qtrue : rb_range_new(rblapack_ZERO, INT2NUM(n), Qtrue);
__shape__[1] = Qtrue;
rblapack_b = na_aref(2, __shape__, rblapack_b);
}
return rb_ary_new3(6, rblapack_s, rblapack_rank, rblapack_work, rblapack_info, rblapack_a, rblapack_b);
}
void
init_lapack_sgelss(VALUE mLapack, VALUE sH, VALUE sU, VALUE zero){
sHelp = sH;
sUsage = sU;
rblapack_ZERO = zero;
rb_define_module_function(mLapack, "sgelss", rblapack_sgelss, -1);
}
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