Prototype

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 );

Description

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.

Definition

Defined in header boost/numeric/bindings/lapack/computational/bdsdc.hpp.

Parameters or Requirements on Types

Complexity

Example

#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

Notes

See Also