There is one prototype of bdsdc
available, please see below.
bdsdc( const char uplo, const char compq, const int_t n, VectorD& d, VectorE& e, MatrixU& u, MatrixVT& vt, VectorQ& q, VectorIQ& iq );
bdsdc
(short for $FRIENDLY_NAME)
provides a C++ interface to LAPACK routines SBDSDC and DBDSDC. bdsdc
computes the singular value decomposition
(SVD) of a real N-by-N (upper or lower) bidiagonal matrix B: B = U *
S * VT, using a divide and conquer method, where S is a diagonal matrix
with non-negative diagonal elements (the singular values of B), and U
and VT are orthogonal matrices of left and right singular vectors, respectively.
bdsdc
can be used to
compute all singular values, and optionally, singular vectors or singular
vectors in compact form.
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 X-MP, Cray Y-MP, Cray C-90, or Cray-2. It could conceivably fail on hexadecimal or decimal machines without guard digits, but we know of none. See DLASD3 for details.
The code currently calls DLASDQ if singular values only are desired. However, it can be slightly modified to compute singular values using the divide and conquer method.
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.
Defined in header boost/numeric/bindings/lapack/computational/bdsdc.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/computational/bdsdc.hpp> using namespace boost::numeric::bindings; lapack::bdsdc( x, y, z );
this will output
[5] 0 1 2 3 4 5