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/* |
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* Copyright (C) 2000-2004 Object Oriented Parallel Simulation Engine (OOPSE) project |
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* |
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* Contact: oopse@oopse.org |
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* |
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* This program is free software; you can redistribute it and/or |
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* modify it under the terms of the GNU Lesser General Public License |
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* as published by the Free Software Foundation; either version 2.1 |
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* of the License, or (at your option) any later version. |
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* All we ask is that proper credit is given for our work, which includes |
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* - but is not limited to - adding the above copyright notice to the beginning |
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* of your source code files, and to any copyright notice that you may distribute |
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* with programs based on this work. |
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* |
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* This program is distributed in the hope that it will be useful, |
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* but WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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* GNU Lesser General Public License for more details. |
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* |
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* You should have received a copy of the GNU Lesser General Public License |
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* along with this program; if not, write to the Free Software |
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* Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. |
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* Copyright (c) 2005 The University of Notre Dame. All Rights Reserved. |
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* |
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* The University of Notre Dame grants you ("Licensee") a |
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* non-exclusive, royalty free, license to use, modify and |
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* redistribute this software in source and binary code form, provided |
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* that the following conditions are met: |
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* |
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* 1. Acknowledgement of the program authors must be made in any |
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* publication of scientific results based in part on use of the |
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* program. An acceptable form of acknowledgement is citation of |
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* the article in which the program was described (Matthew |
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* A. Meineke, Charles F. Vardeman II, Teng Lin, Christopher |
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* J. Fennell and J. Daniel Gezelter, "OOPSE: An Object-Oriented |
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* Parallel Simulation Engine for Molecular Dynamics," |
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* J. Comput. Chem. 26, pp. 252-271 (2005)) |
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* |
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* 2. Redistributions of source code must retain the above copyright |
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* notice, this list of conditions and the following disclaimer. |
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* |
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* 3. Redistributions in binary form must reproduce the above copyright |
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* notice, this list of conditions and the following disclaimer in the |
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* documentation and/or other materials provided with the |
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* distribution. |
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* |
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* This software is provided "AS IS," without a warranty of any |
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* kind. All express or implied conditions, representations and |
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* warranties, including any implied warranty of merchantability, |
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* fitness for a particular purpose or non-infringement, are hereby |
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* excluded. The University of Notre Dame and its licensors shall not |
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* be liable for any damages suffered by licensee as a result of |
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* using, modifying or distributing the software or its |
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* derivatives. In no event will the University of Notre Dame or its |
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* licensors be liable for any lost revenue, profit or data, or for |
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* direct, indirect, special, consequential, incidental or punitive |
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* damages, however caused and regardless of the theory of liability, |
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* arising out of the use of or inability to use software, even if the |
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* University of Notre Dame has been advised of the possibility of |
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* such damages. |
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*/ |
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/** |
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* @file SquareMatrix.hpp |
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* @author Teng Lin |
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#ifndef MATH_SQUAREMATRIX_HPP |
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#define MATH_SQUAREMATRIX_HPP |
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|
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#include "Vector3d.hpp" |
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#include "math/RectMatrix.hpp" |
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#include "utils/NumericConstant.hpp" |
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|
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namespace oopse { |
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|
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/** |
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* @class SquareMatrix SquareMatrix.hpp "math/SquareMatrix.hpp" |
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* @brief A square matrix class |
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* @template Real the element type |
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* @template Dim the dimension of the square matrix |
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*/ |
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template<typename Real, int Dim> |
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class SquareMatrix{ |
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public: |
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/** |
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* @class SquareMatrix SquareMatrix.hpp "math/SquareMatrix.hpp" |
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* @brief A square matrix class |
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* @template Real the element type |
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* @template Dim the dimension of the square matrix |
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*/ |
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template<typename Real, int Dim> |
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class SquareMatrix : public RectMatrix<Real, Dim, Dim> { |
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public: |
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typedef Real ElemType; |
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typedef Real* ElemPoinerType; |
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|
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/** default constructor */ |
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SquareMatrix() { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = 0.0; |
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} |
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/** default constructor */ |
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SquareMatrix() { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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this->data_[i][j] = 0.0; |
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} |
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|
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/** Constructs and initializes every element of this matrix to a scalar */ |
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SquareMatrix(double s) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = s; |
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} |
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/** Constructs and initializes every element of this matrix to a scalar */ |
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SquareMatrix(Real s) : RectMatrix<Real, Dim, Dim>(s){ |
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} |
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|
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/** copy constructor */ |
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SquareMatrix(const SquareMatrix<Real, Dim>& m) { |
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*this = m; |
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} |
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|
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/** destructor*/ |
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~SquareMatrix() {} |
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/** Constructs and initializes from an array */ |
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SquareMatrix(Real* array) : RectMatrix<Real, Dim, Dim>(array){ |
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} |
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|
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/** copy assignment operator */ |
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SquareMatrix<Real, Dim>& operator =(const SquareMatrix<Real, Dim>& m) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = m.data_[i][j]; |
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} |
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|
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/** |
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* Return the reference of a single element of this matrix. |
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* @return the reference of a single element of this matrix |
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* @param i row index |
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* @param j colum index |
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*/ |
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double& operator()(unsigned int i, unsigned int j) { |
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return data_[i][j]; |
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} |
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|
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/** |
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* Return the value of a single element of this matrix. |
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* @return the value of a single element of this matrix |
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* @param i row index |
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* @param j colum index |
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*/ |
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double operator()(unsigned int i, unsigned int j) const { |
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return data_[i][j]; |
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} |
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/** copy constructor */ |
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SquareMatrix(const RectMatrix<Real, Dim, Dim>& m) : RectMatrix<Real, Dim, Dim>(m) { |
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} |
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|
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/** copy assignment operator */ |
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SquareMatrix<Real, Dim>& operator =(const RectMatrix<Real, Dim, Dim>& m) { |
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RectMatrix<Real, Dim, Dim>::operator=(m); |
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return *this; |
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} |
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|
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/** Retunrs an identity matrix*/ |
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|
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/** |
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* Returns a row of this matrix as a vector. |
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* @return a row of this matrix as a vector |
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* @param row the row index |
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*/ |
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Vector<Real, Dim> getRow(unsigned int row) { |
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Vector<Real, Dim> v; |
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static SquareMatrix<Real, Dim> identity() { |
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SquareMatrix<Real, Dim> m; |
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|
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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if (i == j) |
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m(i, j) = 1.0; |
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else |
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m(i, j) = 0.0; |
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|
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for (unsigned int i = 0; i < Dim; i++) |
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v[i] = data_[row][i]; |
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return m; |
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} |
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|
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return v; |
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} |
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/** |
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* Retunrs the inversion of this matrix. |
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* @todo need implementation |
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*/ |
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SquareMatrix<Real, Dim> inverse() { |
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SquareMatrix<Real, Dim> result; |
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|
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/** |
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* Sets a row of this matrix |
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* @param row the row index |
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* @param v the vector to be set |
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*/ |
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void setRow(unsigned int row, const Vector<Real, Dim>& v) { |
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Vector<Real, Dim> v; |
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return result; |
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} |
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|
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for (unsigned int i = 0; i < Dim; i++) |
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data_[row][i] = v[i]; |
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} |
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/** |
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* Returns the determinant of this matrix. |
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* @todo need implementation |
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*/ |
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Real determinant() const { |
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Real det; |
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return det; |
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} |
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|
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/** |
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* Returns a column of this matrix as a vector. |
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* @return a column of this matrix as a vector |
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* @param col the column index |
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*/ |
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Vector<Real, Dim> getColum(unsigned int col) { |
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Vector<Real, Dim> v; |
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/** Returns the trace of this matrix. */ |
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Real trace() const { |
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Real tmp = 0; |
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|
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for (unsigned int i = 0; i < Dim ; i++) |
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tmp += this->data_[i][i]; |
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|
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for (unsigned int i = 0; i < Dim; i++) |
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v[i] = data_[i][col]; |
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return tmp; |
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} |
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|
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return v; |
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} |
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/** Tests if this matrix is symmetrix. */ |
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bool isSymmetric() const { |
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for (unsigned int i = 0; i < Dim - 1; i++) |
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for (unsigned int j = i; j < Dim; j++) |
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if (fabs(this->data_[i][j] - this->data_[j][i]) > epsilon) |
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return false; |
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|
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return true; |
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} |
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|
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/** |
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* Sets a column of this matrix |
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* @param col the column index |
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* @param v the vector to be set |
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*/ |
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void setColum(unsigned int col, const Vector<Real, Dim>& v){ |
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Vector<Real, Dim> v; |
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/** Tests if this matrix is orthogonal. */ |
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bool isOrthogonal() { |
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SquareMatrix<Real, Dim> tmp; |
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|
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for (unsigned int i = 0; i < Dim; i++) |
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data_[i][col] = v[i]; |
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} |
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tmp = *this * transpose(); |
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|
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/** Negates the value of this matrix in place. */ |
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inline void negate() { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = -data_[i][j]; |
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} |
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|
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/** |
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* Sets the value of this matrix to the negation of matrix m. |
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* @param m the source matrix |
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*/ |
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inline void negate(const SquareMatrix<Real, Dim>& m) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = -m.data_[i][j]; |
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} |
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|
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/** |
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* Sets the value of this matrix to the sum of itself and m (*this += m). |
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* @param m the other matrix |
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*/ |
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inline void add( const SquareMatrix<Real, Dim>& m ) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] += m.data_[i][j]; |
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} |
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|
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/** |
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* Sets the value of this matrix to the sum of m1 and m2 (*this = m1 + m2). |
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* @param m1 the first matrix |
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* @param m2 the second matrix |
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*/ |
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inline void add( const SquareMatrix<Real, Dim>& m1, const SquareMatrix<Real, Dim>& m2 ) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = m1.data_[i][j] + m2.data_[i][j]; |
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} |
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|
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/** |
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* Sets the value of this matrix to the difference of itself and m (*this -= m). |
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* @param m the other matrix |
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*/ |
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inline void sub( const SquareMatrix<Real, Dim>& m ) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] -= m.data_[i][j]; |
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} |
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|
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/** |
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* Sets the value of this matrix to the difference of matrix m1 and m2 (*this = m1 - m2). |
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* @param m1 the first matrix |
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* @param m2 the second matrix |
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*/ |
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inline void sub( const SquareMatrix<Real, Dim>& m1, const Vector &m2){ |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = m1.data_[i][j] - m2.data_[i][j]; |
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} |
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|
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/** |
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* Sets the value of this matrix to the scalar multiplication of itself (*this *= s). |
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* @param s the scalar value |
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*/ |
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inline void mul( double s ) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] *= s; |
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} |
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return tmp.isDiagonal(); |
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} |
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|
|
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/** |
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* Sets the value of this matrix to the scalar multiplication of matrix m (*this = s * m). |
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* @param s the scalar value |
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* @param m the matrix |
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*/ |
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inline void mul( double s, const SquareMatrix<Real, Dim>& m ) { |
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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data_[i][j] = s * m.data_[i][j]; |
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} |
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/** Tests if this matrix is diagonal. */ |
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bool isDiagonal() const { |
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for (unsigned int i = 0; i < Dim ; i++) |
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for (unsigned int j = 0; j < Dim; j++) |
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if (i !=j && fabs(this->data_[i][j]) > epsilon) |
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return false; |
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|
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return true; |
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} |
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|
|
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/** |
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* Sets the value of this matrix to the multiplication of this matrix and matrix m |
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* (*this = *this * m). |
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* @param m the matrix |
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*/ |
172 |
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inline void mul(const SquareMatrix<Real, Dim>& m ) { |
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SquareMatrix<Real, Dim> tmp(*this); |
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|
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for (unsigned int i = 0; i < Dim; i++) |
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for (unsigned int j = 0; j < Dim; j++) { |
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/** Tests if this matrix is the unit matrix. */ |
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bool isUnitMatrix() const { |
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if (!isDiagonal()) |
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return false; |
171 |
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|
172 |
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for (unsigned int i = 0; i < Dim ; i++) |
173 |
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if (fabs(this->data_[i][i] - 1) > epsilon) |
174 |
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return false; |
175 |
|
|
176 |
< |
data_[i][j] = 0.0; |
177 |
< |
for (unsigned int k = 0; k < Dim; k++) |
243 |
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data_[i][j] = tmp.data_[i][k] * m.data_[k][j] |
244 |
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} |
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} |
246 |
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|
247 |
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/** |
248 |
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* Sets the value of this matrix to the left multiplication of matrix m into itself |
249 |
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* (*this = m * *this). |
250 |
< |
* @param m the matrix |
251 |
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*/ |
252 |
< |
inline void leftmul(const SquareMatrix<Real, Dim>& m ) { |
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< |
SquareMatrix<Real, Dim> tmp(*this); |
254 |
< |
|
255 |
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for (unsigned int i = 0; i < Dim; i++) |
256 |
< |
for (unsigned int j = 0; j < Dim; j++) { |
257 |
< |
|
258 |
< |
data_[i][j] = 0.0; |
259 |
< |
for (unsigned int k = 0; k < Dim; k++) |
260 |
< |
data_[i][j] = m.data_[i][k] * tmp.data_[k][j] |
261 |
< |
} |
262 |
< |
} |
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return true; |
177 |
> |
} |
178 |
|
|
179 |
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/** |
180 |
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* Sets the value of this matrix to the multiplication of matrix m1 and matrix m2 |
181 |
< |
* (*this = m1 * m2). |
182 |
< |
* @param m1 the first matrix |
183 |
< |
* @param m2 the second matrix |
184 |
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*/ |
185 |
< |
inline void mul(const SquareMatrix<Real, Dim>& m1, |
271 |
< |
const SquareMatrix<Real, Dim>& m2 ) { |
272 |
< |
for (unsigned int i = 0; i < Dim; i++) |
273 |
< |
for (unsigned int j = 0; j < Dim; j++) { |
274 |
< |
|
275 |
< |
data_[i][j] = 0.0; |
276 |
< |
for (unsigned int k = 0; k < Dim; k++) |
277 |
< |
data_[i][j] = m1.data_[i][k] * m2.data_[k][j] |
278 |
< |
} |
179 |
> |
/** Return the transpose of this matrix */ |
180 |
> |
SquareMatrix<Real, Dim> transpose() const{ |
181 |
> |
SquareMatrix<Real, Dim> result; |
182 |
> |
|
183 |
> |
for (unsigned int i = 0; i < Dim; i++) |
184 |
> |
for (unsigned int j = 0; j < Dim; j++) |
185 |
> |
result(j, i) = this->data_[i][j]; |
186 |
|
|
187 |
< |
} |
188 |
< |
|
189 |
< |
/** |
190 |
< |
* Sets the value of this matrix to the scalar division of itself (*this /= s ). |
191 |
< |
* @param s the scalar value |
192 |
< |
*/ |
193 |
< |
inline void div( double s) { |
287 |
< |
for (unsigned int i = 0; i < Dim; i++) |
288 |
< |
for (unsigned int j = 0; j < Dim; j++) |
289 |
< |
data_[i][j] /= s; |
290 |
< |
} |
291 |
< |
|
292 |
< |
inline SquareMatrix<Real, Dim>& operator=(const SquareMatrix<Real, Dim>& v) { |
293 |
< |
if (this == &v) |
294 |
< |
return *this; |
295 |
< |
|
296 |
< |
for (unsigned int i = 0; i < Dim; i++) |
297 |
< |
data_[i] = v[i]; |
298 |
< |
|
299 |
< |
return *this; |
300 |
< |
} |
301 |
< |
|
302 |
< |
/** |
303 |
< |
* Sets the value of this matrix to the scalar division of matrix v1 (*this = v1 / s ). |
304 |
< |
* @paran v1 the source matrix |
305 |
< |
* @param s the scalar value |
306 |
< |
*/ |
307 |
< |
inline void div( const SquareMatrix<Real, Dim>& v1, double s ) { |
308 |
< |
for (unsigned int i = 0; i < Dim; i++) |
309 |
< |
data_[i] = v1.data_[i] / s; |
310 |
< |
} |
187 |
> |
return result; |
188 |
> |
} |
189 |
> |
|
190 |
> |
/** @todo need implementation */ |
191 |
> |
void diagonalize() { |
192 |
> |
//jacobi(m, eigenValues, ortMat); |
193 |
> |
} |
194 |
|
|
195 |
< |
/** |
196 |
< |
* Multiples a scalar into every element of this matrix. |
197 |
< |
* @param s the scalar value |
198 |
< |
*/ |
199 |
< |
SquareMatrix<Real, Dim>& operator *=(const double s) { |
200 |
< |
this->mul(s); |
201 |
< |
return *this; |
202 |
< |
} |
195 |
> |
/** |
196 |
> |
* Jacobi iteration routines for computing eigenvalues/eigenvectors of |
197 |
> |
* real symmetric matrix |
198 |
> |
* |
199 |
> |
* @return true if success, otherwise return false |
200 |
> |
* @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is |
201 |
> |
* overwritten |
202 |
> |
* @param w will contain the eigenvalues of the matrix On return of this function |
203 |
> |
* @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are |
204 |
> |
* normalized and mutually orthogonal. |
205 |
> |
*/ |
206 |
> |
|
207 |
> |
static int jacobi(SquareMatrix<Real, Dim>& a, Vector<Real, Dim>& d, |
208 |
> |
SquareMatrix<Real, Dim>& v); |
209 |
> |
};//end SquareMatrix |
210 |
|
|
321 |
– |
/** |
322 |
– |
* Divides every element of this matrix by a scalar. |
323 |
– |
* @param s the scalar value |
324 |
– |
*/ |
325 |
– |
SquareMatrix<Real, Dim>& operator /=(const double s) { |
326 |
– |
this->div(s); |
327 |
– |
return *this; |
328 |
– |
} |
211 |
|
|
212 |
< |
/** |
331 |
< |
* Sets the value of this matrix to the sum of the other matrix and itself (*this += m). |
332 |
< |
* @param m the other matrix |
333 |
< |
*/ |
334 |
< |
SquareMatrix<Real, Dim>& operator += (const SquareMatrix<Real, Dim>& m) { |
335 |
< |
add(m); |
336 |
< |
return *this; |
337 |
< |
} |
212 |
> |
/*========================================================================= |
213 |
|
|
214 |
< |
/** |
215 |
< |
* Sets the value of this matrix to the differerence of itself and the other matrix (*this -= m) |
341 |
< |
* @param m the other matrix |
342 |
< |
*/ |
343 |
< |
SquareMatrix<Real, Dim>& operator -= (const SquareMatrix<Real, Dim>& m){ |
344 |
< |
sub(m); |
345 |
< |
return *this; |
346 |
< |
} |
214 |
> |
Program: Visualization Toolkit |
215 |
> |
Module: $RCSfile: SquareMatrix.hpp,v $ |
216 |
|
|
217 |
< |
/** set this matrix to an identity matrix*/ |
217 |
> |
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen |
218 |
> |
All rights reserved. |
219 |
> |
See Copyright.txt or http://www.kitware.com/Copyright.htm for details. |
220 |
|
|
221 |
< |
void identity() { |
222 |
< |
for (unsigned int i = 0; i < Dim; i++) |
223 |
< |
for (unsigned int i = 0; i < Dim; i++) |
353 |
< |
if (i == j) |
354 |
< |
data_[i][j] = 1.0; |
355 |
< |
else |
356 |
< |
data_[i][j] = 0.0; |
357 |
< |
} |
221 |
> |
This software is distributed WITHOUT ANY WARRANTY; without even |
222 |
> |
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR |
223 |
> |
PURPOSE. See the above copyright notice for more information. |
224 |
|
|
225 |
< |
/** Sets the value of this matrix to the inversion of itself. */ |
360 |
< |
void inverse() { |
361 |
< |
inverse(*this); |
362 |
< |
} |
225 |
> |
=========================================================================*/ |
226 |
|
|
227 |
< |
/** |
228 |
< |
* Sets the value of this matrix to the inversion of other matrix. |
366 |
< |
* @ param m the source matrix |
367 |
< |
*/ |
368 |
< |
void inverse(const SquareMatrix<Real, Dim>& m); |
369 |
< |
|
370 |
< |
/** Sets the value of this matrix to the transpose of itself. */ |
371 |
< |
void transpose() { |
372 |
< |
for (unsigned int i = 0; i < Dim - 1; i++) |
373 |
< |
for (unsigned int j = i; j < Dim; j++) |
374 |
< |
std::swap(data_[i][j], data_[j][i]); |
375 |
< |
} |
227 |
> |
#define VTK_ROTATE(a,i,j,k,l) g=a(i, j);h=a(k, l);a(i, j)=g-s*(h+g*tau); \ |
228 |
> |
a(k, l)=h+s*(g-h*tau) |
229 |
|
|
230 |
< |
/** |
378 |
< |
* Sets the value of this matrix to the transpose of other matrix. |
379 |
< |
* @ param m the source matrix |
380 |
< |
*/ |
381 |
< |
void transpose(const SquareMatrix<Real, Dim>& m) { |
382 |
< |
|
383 |
< |
if (this == &m) { |
384 |
< |
transpose(); |
385 |
< |
} else { |
386 |
< |
for (unsigned int i = 0; i < Dim; i++) |
387 |
< |
for (unsigned int j =0; j < Dim; j++) |
388 |
< |
data_[i][j] = m.data_[i][j]; |
389 |
< |
} |
390 |
< |
} |
230 |
> |
#define VTK_MAX_ROTATIONS 20 |
231 |
|
|
232 |
< |
/** Returns the determinant of this matrix. */ |
233 |
< |
double determinant() const { |
232 |
> |
// Jacobi iteration for the solution of eigenvectors/eigenvalues of a nxn |
233 |
> |
// real symmetric matrix. Square nxn matrix a; size of matrix in n; |
234 |
> |
// output eigenvalues in w; and output eigenvectors in v. Resulting |
235 |
> |
// eigenvalues/vectors are sorted in decreasing order; eigenvectors are |
236 |
> |
// normalized. |
237 |
> |
template<typename Real, int Dim> |
238 |
> |
int SquareMatrix<Real, Dim>::jacobi(SquareMatrix<Real, Dim>& a, Vector<Real, Dim>& w, |
239 |
> |
SquareMatrix<Real, Dim>& v) { |
240 |
> |
const int n = Dim; |
241 |
> |
int i, j, k, iq, ip, numPos; |
242 |
> |
Real tresh, theta, tau, t, sm, s, h, g, c, tmp; |
243 |
> |
Real bspace[4], zspace[4]; |
244 |
> |
Real *b = bspace; |
245 |
> |
Real *z = zspace; |
246 |
|
|
247 |
< |
} |
247 |
> |
// only allocate memory if the matrix is large |
248 |
> |
if (n > 4) { |
249 |
> |
b = new Real[n]; |
250 |
> |
z = new Real[n]; |
251 |
> |
} |
252 |
|
|
253 |
< |
/** Returns the trace of this matrix. */ |
254 |
< |
double trace() const { |
255 |
< |
double tmp = 0; |
256 |
< |
|
257 |
< |
for (unsigned int i = 0; i < Dim ; i++) |
258 |
< |
tmp += data_[i][i]; |
253 |
> |
// initialize |
254 |
> |
for (ip=0; ip<n; ip++) { |
255 |
> |
for (iq=0; iq<n; iq++) { |
256 |
> |
v(ip, iq) = 0.0; |
257 |
> |
} |
258 |
> |
v(ip, ip) = 1.0; |
259 |
> |
} |
260 |
> |
for (ip=0; ip<n; ip++) { |
261 |
> |
b[ip] = w[ip] = a(ip, ip); |
262 |
> |
z[ip] = 0.0; |
263 |
> |
} |
264 |
|
|
265 |
< |
return tmp; |
266 |
< |
} |
265 |
> |
// begin rotation sequence |
266 |
> |
for (i=0; i<VTK_MAX_ROTATIONS; i++) { |
267 |
> |
sm = 0.0; |
268 |
> |
for (ip=0; ip<n-1; ip++) { |
269 |
> |
for (iq=ip+1; iq<n; iq++) { |
270 |
> |
sm += fabs(a(ip, iq)); |
271 |
> |
} |
272 |
> |
} |
273 |
> |
if (sm == 0.0) { |
274 |
> |
break; |
275 |
> |
} |
276 |
|
|
277 |
< |
/** Tests if this matrix is symmetrix. */ |
278 |
< |
bool isSymmetric() const { |
279 |
< |
for (unsigned int i = 0; i < Dim - 1; i++) |
280 |
< |
for (unsigned int j = i; j < Dim; j++) |
281 |
< |
if (fabs(data_[i][j] - data_[j][i]) > epsilon) |
412 |
< |
return false; |
413 |
< |
|
414 |
< |
return true; |
415 |
< |
} |
277 |
> |
if (i < 3) { // first 3 sweeps |
278 |
> |
tresh = 0.2*sm/(n*n); |
279 |
> |
} else { |
280 |
> |
tresh = 0.0; |
281 |
> |
} |
282 |
|
|
283 |
< |
/** Tests if this matrix is orthogona. */ |
284 |
< |
bool isOrthogonal() const { |
285 |
< |
SquareMatrix<Real, Dim> t(*this); |
283 |
> |
for (ip=0; ip<n-1; ip++) { |
284 |
> |
for (iq=ip+1; iq<n; iq++) { |
285 |
> |
g = 100.0*fabs(a(ip, iq)); |
286 |
|
|
287 |
< |
t.transpose(); |
287 |
> |
// after 4 sweeps |
288 |
> |
if (i > 3 && (fabs(w[ip])+g) == fabs(w[ip]) |
289 |
> |
&& (fabs(w[iq])+g) == fabs(w[iq])) { |
290 |
> |
a(ip, iq) = 0.0; |
291 |
> |
} else if (fabs(a(ip, iq)) > tresh) { |
292 |
> |
h = w[iq] - w[ip]; |
293 |
> |
if ( (fabs(h)+g) == fabs(h)) { |
294 |
> |
t = (a(ip, iq)) / h; |
295 |
> |
} else { |
296 |
> |
theta = 0.5*h / (a(ip, iq)); |
297 |
> |
t = 1.0 / (fabs(theta)+sqrt(1.0+theta*theta)); |
298 |
> |
if (theta < 0.0) { |
299 |
> |
t = -t; |
300 |
> |
} |
301 |
> |
} |
302 |
> |
c = 1.0 / sqrt(1+t*t); |
303 |
> |
s = t*c; |
304 |
> |
tau = s/(1.0+c); |
305 |
> |
h = t*a(ip, iq); |
306 |
> |
z[ip] -= h; |
307 |
> |
z[iq] += h; |
308 |
> |
w[ip] -= h; |
309 |
> |
w[iq] += h; |
310 |
> |
a(ip, iq)=0.0; |
311 |
|
|
312 |
< |
return isUnitMatrix(*this * t); |
313 |
< |
} |
312 |
> |
// ip already shifted left by 1 unit |
313 |
> |
for (j = 0;j <= ip-1;j++) { |
314 |
> |
VTK_ROTATE(a,j,ip,j,iq); |
315 |
> |
} |
316 |
> |
// ip and iq already shifted left by 1 unit |
317 |
> |
for (j = ip+1;j <= iq-1;j++) { |
318 |
> |
VTK_ROTATE(a,ip,j,j,iq); |
319 |
> |
} |
320 |
> |
// iq already shifted left by 1 unit |
321 |
> |
for (j=iq+1; j<n; j++) { |
322 |
> |
VTK_ROTATE(a,ip,j,iq,j); |
323 |
> |
} |
324 |
> |
for (j=0; j<n; j++) { |
325 |
> |
VTK_ROTATE(v,j,ip,j,iq); |
326 |
> |
} |
327 |
> |
} |
328 |
> |
} |
329 |
> |
} |
330 |
|
|
331 |
< |
/** Tests if this matrix is diagonal. */ |
332 |
< |
bool isDiagonal() const { |
333 |
< |
for (unsigned int i = 0; i < Dim ; i++) |
334 |
< |
for (unsigned int j = 0; j < Dim; j++) |
335 |
< |
if (i !=j && fabs(data_[i][j]) > epsilon) |
431 |
< |
return false; |
432 |
< |
|
433 |
< |
return true; |
434 |
< |
} |
435 |
< |
|
436 |
< |
/** Tests if this matrix is the unit matrix. */ |
437 |
< |
bool isUnitMatrix() const { |
438 |
< |
if (!isDiagonal()) |
439 |
< |
return false; |
440 |
< |
|
441 |
< |
for (unsigned int i = 0; i < Dim ; i++) |
442 |
< |
if (fabs(data_[i][i] - 1) > epsilon) |
443 |
< |
return false; |
444 |
< |
|
445 |
< |
return true; |
446 |
< |
} |
447 |
< |
|
448 |
< |
protected: |
449 |
< |
double data_[Dim][Dim]; /**< matrix element */ |
450 |
< |
|
451 |
< |
};//end SquareMatrix |
452 |
< |
|
453 |
< |
|
454 |
< |
/** Negate the value of every element of this matrix. */ |
455 |
< |
template<typename Real, int Dim> |
456 |
< |
inline SquareMatrix<Real, Dim> operator -(const SquareMatrix& m) { |
457 |
< |
SquareMatrix<Real, Dim> result(m); |
458 |
< |
|
459 |
< |
result.negate(); |
460 |
< |
|
461 |
< |
return result; |
331 |
> |
for (ip=0; ip<n; ip++) { |
332 |
> |
b[ip] += z[ip]; |
333 |
> |
w[ip] = b[ip]; |
334 |
> |
z[ip] = 0.0; |
335 |
> |
} |
336 |
|
} |
463 |
– |
|
464 |
– |
/** |
465 |
– |
* Return the sum of two matrixes (m1 + m2). |
466 |
– |
* @return the sum of two matrixes |
467 |
– |
* @param m1 the first matrix |
468 |
– |
* @param m2 the second matrix |
469 |
– |
*/ |
470 |
– |
template<typename Real, int Dim> |
471 |
– |
inline SquareMatrix<Real, Dim> operator + (const SquareMatrix<Real, Dim>& m1, |
472 |
– |
const SquareMatrix<Real, Dim>& m2) { |
473 |
– |
SquareMatrix<Real, Dim>result; |
337 |
|
|
338 |
< |
result.add(m1, m2); |
339 |
< |
|
340 |
< |
return result; |
338 |
> |
//// this is NEVER called |
339 |
> |
if ( i >= VTK_MAX_ROTATIONS ) { |
340 |
> |
std::cout << "vtkMath::Jacobi: Error extracting eigenfunctions" << std::endl; |
341 |
> |
return 0; |
342 |
|
} |
479 |
– |
|
480 |
– |
/** |
481 |
– |
* Return the difference of two matrixes (m1 - m2). |
482 |
– |
* @return the sum of two matrixes |
483 |
– |
* @param m1 the first matrix |
484 |
– |
* @param m2 the second matrix |
485 |
– |
*/ |
486 |
– |
template<typename Real, int Dim> |
487 |
– |
inline SquareMatrix<Real, Dim> operator - (const SquareMatrix<Real, Dim>& m1, |
488 |
– |
const SquareMatrix<Real, Dim>& m2) { |
489 |
– |
SquareMatrix<Real, Dim>result; |
343 |
|
|
344 |
< |
result.sub(m1, m2); |
345 |
< |
|
346 |
< |
return result; |
344 |
> |
// sort eigenfunctions these changes do not affect accuracy |
345 |
> |
for (j=0; j<n-1; j++) { // boundary incorrect |
346 |
> |
k = j; |
347 |
> |
tmp = w[k]; |
348 |
> |
for (i=j+1; i<n; i++) { // boundary incorrect, shifted already |
349 |
> |
if (w[i] >= tmp) { // why exchage if same? |
350 |
> |
k = i; |
351 |
> |
tmp = w[k]; |
352 |
> |
} |
353 |
> |
} |
354 |
> |
if (k != j) { |
355 |
> |
w[k] = w[j]; |
356 |
> |
w[j] = tmp; |
357 |
> |
for (i=0; i<n; i++) { |
358 |
> |
tmp = v(i, j); |
359 |
> |
v(i, j) = v(i, k); |
360 |
> |
v(i, k) = tmp; |
361 |
> |
} |
362 |
> |
} |
363 |
|
} |
364 |
< |
|
365 |
< |
/** |
366 |
< |
* Return the multiplication of two matrixes (m1 * m2). |
367 |
< |
* @return the multiplication of two matrixes |
368 |
< |
* @param m1 the first matrix |
369 |
< |
* @param m2 the second matrix |
370 |
< |
*/ |
371 |
< |
template<typename Real, int Dim> |
372 |
< |
inline SquareMatrix<Real, Dim> operator *(const SquareMatrix<Real, Dim>& m1, |
373 |
< |
const SquareMatrix<Real, Dim>& m2) { |
374 |
< |
SquareMatrix<Real, Dim> result; |
375 |
< |
|
376 |
< |
result.mul(m1, m2); |
377 |
< |
|
378 |
< |
return result; |
364 |
> |
// insure eigenvector consistency (i.e., Jacobi can compute vectors that |
365 |
> |
// are negative of one another (.707,.707,0) and (-.707,-.707,0). This can |
366 |
> |
// reek havoc in hyperstreamline/other stuff. We will select the most |
367 |
> |
// positive eigenvector. |
368 |
> |
int ceil_half_n = (n >> 1) + (n & 1); |
369 |
> |
for (j=0; j<n; j++) { |
370 |
> |
for (numPos=0, i=0; i<n; i++) { |
371 |
> |
if ( v(i, j) >= 0.0 ) { |
372 |
> |
numPos++; |
373 |
> |
} |
374 |
> |
} |
375 |
> |
// if ( numPos < ceil(RealType(n)/RealType(2.0)) ) |
376 |
> |
if ( numPos < ceil_half_n) { |
377 |
> |
for (i=0; i<n; i++) { |
378 |
> |
v(i, j) *= -1.0; |
379 |
> |
} |
380 |
> |
} |
381 |
|
} |
511 |
– |
|
512 |
– |
/** |
513 |
– |
* Return the multiplication of matrixes m and vector v (m * v). |
514 |
– |
* @return the multiplication of matrixes and vector |
515 |
– |
* @param m the matrix |
516 |
– |
* @param v the vector |
517 |
– |
*/ |
518 |
– |
template<typename Real, int Dim> |
519 |
– |
inline Vector<Real, Dim> operator *(const SquareMatrix<Real, Dim>& m, |
520 |
– |
const SquareMatrix<Real, Dim>& v) { |
521 |
– |
Vector<Real, Dim> result; |
382 |
|
|
383 |
< |
for (unsigned int i = 0; i < Dim ; i++) |
384 |
< |
for (unsigned int j = 0; j < Dim ; j++) |
385 |
< |
result[i] += m(i, j) * v[j]; |
526 |
< |
|
527 |
< |
return result; |
383 |
> |
if (n > 4) { |
384 |
> |
delete [] b; |
385 |
> |
delete [] z; |
386 |
|
} |
387 |
+ |
return 1; |
388 |
+ |
} |
389 |
+ |
|
390 |
+ |
|
391 |
+ |
typedef SquareMatrix<RealType, 6> Mat6x6d; |
392 |
|
} |
393 |
|
#endif //MATH_SQUAREMATRIX_HPP |
394 |
+ |
|