Prototype

There is one prototype of spgvd available, please see below.

spgvd( const int_t itype, const char jobz, MatrixAP& ap,
        MatrixBP& bp, VectorW& w, MatrixZ& z );

Description

spgvd (short for $FRIENDLY_NAME) provides a C++ interface to LAPACK routines SSPGVD and DSPGVD. spgvd computes all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, of the form A*x(lambda)*B*x, A*Bx(lambda)*x, or B*A*x=(lambda)*x. Here A and B are assumed to be symmetric, stored in packed format, and B is also positive definite. If eigenvectors are desired, it uses a divide and conquer algorithm.

The divide and conquer algorithm 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.

The selection of the LAPACK routine is done during compile-time, and is determined by the type of values contained in type MatrixAP. The type of values is obtained through the value_type meta-function typename value_type<MatrixAP>::type. The dispatching table below illustrates to which specific routine the code path will be generated.

Definition

Defined in header boost/numeric/bindings/lapack/driver/spgvd.hpp.

Parameters or Requirements on Types

Complexity

Example

#include <boost/numeric/bindings/lapack/driver/spgvd.hpp>
using namespace boost::numeric::bindings;

lapack::spgvd( x, y, z );

this will output

[5] 0 1 2 3 4 5

Notes

See Also