There is one prototype of syevd
available, please see below.
syevd( const char jobz, MatrixA& a, VectorW& w );
syevd (short for $FRIENDLY_NAME)
provides a C++ interface to LAPACK routines SSYEVD and DSYEVD. syevd computes all eigenvalues and,
optionally, eigenvectors of a real symmetric matrix A. 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.
Because of large use of BLAS of level 3, syevd
needs N**2 more workspace than DSYEVX.
The selection of the LAPACK routine is done during compile-time, and
is determined by the type of values contained in type MatrixA.
The type of values is obtained through the value_type
meta-function typename value_type<MatrixA>::type. The dispatching table below illustrates
to which specific routine the code path will be generated.
Defined in header boost/numeric/bindings/lapack/driver/syevd.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/driver/syevd.hpp> using namespace boost::numeric::bindings; lapack::syevd( x, y, z );
this will output
[5] 0 1 2 3 4 5