basisincompleteordered.hpp

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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
 
/*
 Copyright (C) 2007, 2008 Mark Joshi
 
 This file is part of QuantLib, a free-software/open-source library
 for financial quantitative analysts and developers - http://quantlib.org/
 
 QuantLib is free software: you can redistribute it and/or modify it
 under the terms of the QuantLib license.  You should have received a
 copy of the license along with this program; if not, please email
 <quantlib-dev@lists.sf.net>. The license is also available online at
 <http://quantlib.org/license.shtml>.
 
 This program is distributed in the hope that it will be useful, but WITHOUT
 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
 FOR A PARTICULAR PURPOSE.  See the license for more details.
*/
 
 
#ifndef quantlib_basis_incomplete_ordered_hpp
#define quantlib_basis_incomplete_ordered_hpp
 
#include <ql/math/matrix.hpp>
#include <valarray>
 
namespace QuantLib {
 
    class BasisIncompleteOrdered {
      public:
        BasisIncompleteOrdered(Size euclideanDimension);
        //! return value indicates if the vector was linearly independent
        bool addVector(const Array& newVector);
        Size basisSize() const;
        Size euclideanDimension() const;
        Matrix getBasisAsRowsInMatrix() const;
      private:
        std::vector<Array> currentBasis_;
        Size euclideanDimension_;
        Array newVector_;
    };
 
/*! Given a collection of vectors, w_i, find a collection of vectors x_i such that
x_i is orthogonal to w_j for i != j, and <x_i, w_i> = <w_i, w_i>
 
This is done by performing GramSchmidt on the other vectors and then projecting onto
the orthogonal space.
 
This class is tested in
 
    MatricesTest::testOrthogonalProjection();
*/
 
    class OrthogonalProjections
    {
    public:
        OrthogonalProjections(const Matrix& originalVectors,
                              Real multiplierCutOff,
                               Real tolerance  );
 
        const std::valarray<bool>& validVectors() const;
        const std::vector<Real>& GetVector(Size index) const;
 
        Size numberValidVectors() const;
 
 
    private:
 
        //! inputs
        Matrix originalVectors_;
        Real multiplierCutoff_;
        Size numberVectors_;
        Size numberValidVectors_;
        Size dimension_;
 
        //!outputs
        std::valarray<bool> validVectors_;
        std::vector<std::vector<Real> > projectedVectors_;
 
        //!workspace
        Matrix orthoNormalizedVectors_;
 
 
    };
 
}
 
#endif