EvaluateLinearAlgebraUnaryAlgo.h

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#ifndef ALGORITHMS_MATH_EVALUATELINEARALGEBRAUNARY_H
#define ALGORITHMS_MATH_EVALUATELINEARALGEBRAUNARY_H

#include <Core/Algorithms/Base/AlgorithmBase.h>
#include <Core/Datatypes/MatrixFwd.h>
#include <boost/optional.hpp>
#include <Core/Algorithms/Math/share.h>

/// \addtogroup Algorithms_Math
/// @{
///  

namespace SCIRun {
namespace Core {
namespace Algorithms {
namespace Math {

/// 
/// \class EvaluateLinearAlgebraUnaryAlgorithm
///
/// \brief Computes several unary operations on general matrices
///
/// \tparam _MatrixType the type of the matrix of which we are computing the
/// eigendecomposition; this is expected to be an instantiation of the Matrix
/// class template. Currently, only real matrices are supported.
///
/// The eigenvalues and eigenvectors of a matrix \f$ A \f$ are scalars
/// \f$ \lambda \f$ and vectors \f$ v \f$ such that \f$ Av = \lambda v \f$.  If
/// \f$ D \f$ is a diagonal matrix with the eigenvalues on the diagonal, and
/// \f$ V \f$ is a matrix with the eigenvectors as its columns, then \f$ A V =
/// V D \f$. The matrix \f$ V \f$ is almost always invertible, in which case we
/// have \f$ A = V D V^{-1} \f$. This is called the eigendecomposition.
///
/// Call the function compute() to compute the eigenvalues and eigenvectors of
/// a given matrix. Alternatively, you can use the 
/// EigenSolver(const MatrixType&, bool) constructor which computes the
/// eigenvalues and eigenvectors at construction time. Once the eigenvalue and
/// eigenvectors are computed, they can be retrieved with the eigenvalues() and
/// eigenvectors() functions. The pseudoEigenvalueMatrix() and
/// pseudoEigenvectors() methods allow the construction of the
/// pseudo-eigendecomposition.
///
/// The documentation for EigenSolver(const MatrixType&, bool) contains an
/// example of the typical use of this class.
///
/// \note The implementation is adapted from
/// <a href="http://math.nist.gov/javanumerics/jama/">JAMA</a> (public domain).
/// Their code is based on EISPACK.
///
/// \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver
///

  class SCISHARE EvaluateLinearAlgebraUnaryAlgorithm : public AlgorithmBase
  {
  public:
    enum Operator
    {
      NEGATE,
      TRANSPOSE,
      SCALAR_MULTIPLY
    };

    typedef SCIRun::Core::Datatypes::DenseMatrixConstHandle Inputs;
    typedef boost::tuple<Operator, boost::optional<double> > Parameters;
    typedef SCIRun::Core::Datatypes::DenseMatrixHandle Outputs;

    EvaluateLinearAlgebraUnaryAlgorithm();
    Outputs run(const Inputs& matrix, const Parameters& params) const;

    AlgorithmOutput run_generic(const AlgorithmInput& input) const;
  };
}}}}


/*! @} End of Doxygen Groups*/

#endif