There is one prototype of lalsd
available, please see below.
lalsd( const char uplo, const int_t smlsiz, const int_t n, VectorD& d, VectorE& e, MatrixB& b, const Scalar >, int_t& rank );
lalsd (short for $FRIENDLY_NAME)
provides a C++ interface to LAPACK routines SLALSD, DLALSD, CLALSD, and
ZLALSD. lalsd uses the
singular value decomposition of A to solve the least squares problem
of finding X to minimize the Euclidean norm of each column of A*X-B,
where A is N-by-N upper bidiagonal, and X and B are N-by-NRHS. The solution
X overwrites B.
The singular values of A smaller than RCOND times the largest singular value are treated as zero in solving the least squares problem; in this case a minimum norm solution is returned. The actual singular values are returned in D in ascending order.
This code makes very mild assumptions about floating point arithmetic. It will work on machines with a guard digit in add/subtract, or on those binary machines without guard digits which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2. It could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none.
The selection of the LAPACK routine is done during compile-time, and
is determined by the type of values contained in type VectorD.
The type of values is obtained through the value_type
meta-function typename value_type<VectorD>::type. The dispatching table below illustrates
to which specific routine the code path will be generated.
Table 1.365. Dispatching of lalsd
|
Value type of VectorD |
LAPACK routine |
|---|---|
|
|
SLALSD |
|
|
DLALSD |
|
|
CLALSD |
|
|
ZLALSD |
Defined in header boost/numeric/bindings/lapack/auxiliary/lalsd.hpp.
Parameters
The definition of term 1
The definition of term 2
The definition of term 3.
Definitions may contain paragraphs.
#include <boost/numeric/bindings/lapack/auxiliary/lalsd.hpp> using namespace boost::numeric::bindings; lapack::lalsd( x, y, z );
this will output
[5] 0 1 2 3 4 5