src/math/SquareMatrix3.hpp

/*
 * Copyright (c) 2005 The University of Notre Dame. All Rights Reserved.
 *
 * The University of Notre Dame grants you ("Licensee") a
 * non-exclusive, royalty free, license to use, modify and
 * redistribute this software in source and binary code form, provided
 * that the following conditions are met:
 *
 * 1. Acknowledgement of the program authors must be made in any
 *    publication of scientific results based in part on use of the
 *    program.  An acceptable form of acknowledgement is citation of
 *    the article in which the program was described (Matthew
 *    A. Meineke, Charles F. Vardeman II, Teng Lin, Christopher
 *    J. Fennell and J. Daniel Gezelter, "OOPSE: An Object-Oriented
 *    Parallel Simulation Engine for Molecular Dynamics,"
 *    J. Comput. Chem. 26, pp. 252-271 (2005))
 *
 * 2. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 *
 * 3. Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
 *    documentation and/or other materials provided with the
 *    distribution.
 *
 * This software is provided "AS IS," without a warranty of any
 * kind. All express or implied conditions, representations and
 * warranties, including any implied warranty of merchantability,
 * fitness for a particular purpose or non-infringement, are hereby
 * excluded.  The University of Notre Dame and its licensors shall not
 * be liable for any damages suffered by licensee as a result of
 * using, modifying or distributing the software or its
 * derivatives. In no event will the University of Notre Dame or its
 * licensors be liable for any lost revenue, profit or data, or for
 * direct, indirect, special, consequential, incidental or punitive
 * damages, however caused and regardless of the theory of liability,
 * arising out of the use of or inability to use software, even if the
 * University of Notre Dame has been advised of the possibility of
 * such damages.
 */
 
/**
 * @file SquareMatrix3.hpp
 * @author Teng Lin
 * @date 10/11/2004
 * @version 1.0
 */
#ifndef MATH_SQUAREMATRIX3_HPP
#define  MATH_SQUAREMATRIX3_HPP
#include <vector>
#include "Quaternion.hpp"
#include "SquareMatrix.hpp"
#include "Vector3.hpp"
#include "utils/NumericConstant.hpp"
namespace oopse {

  template<typename Real>
  class SquareMatrix3 : public SquareMatrix<Real, 3> {
  public:

    typedef Real ElemType;
    typedef Real* ElemPoinerType;
            
    /** default constructor */
    SquareMatrix3() : SquareMatrix<Real, 3>() {
    }

    /** Constructs and initializes every element of this matrix to a scalar */ 
    SquareMatrix3(Real s) : SquareMatrix<Real,3>(s){
    }

    /** Constructs and initializes from an array */ 
    SquareMatrix3(Real* array) : SquareMatrix<Real,3>(array){
    }


    /** copy  constructor */
    SquareMatrix3(const SquareMatrix<Real, 3>& m)  : SquareMatrix<Real, 3>(m) {
    }
            
    SquareMatrix3( const Vector3<Real>& eulerAngles) {
      setupRotMat(eulerAngles);
    }
            
    SquareMatrix3(Real phi, Real theta, Real psi) {
      setupRotMat(phi, theta, psi);
    }

    SquareMatrix3(const Quaternion<Real>& q) {
      setupRotMat(q);

    }

    SquareMatrix3(Real w, Real x, Real y, Real z) {
      setupRotMat(w, x, y, z);
    }
            
    /** copy assignment operator */
    SquareMatrix3<Real>& operator =(const SquareMatrix<Real, 3>& m) {
      if (this == &m)
        return *this;
      SquareMatrix<Real, 3>::operator=(m);
      return *this;
    }


    SquareMatrix3<Real>& operator =(const Quaternion<Real>& q) {
      this->setupRotMat(q);
      return *this;
    }

    /**
     * Sets this matrix to a rotation matrix by three euler angles
     * @ param euler
     */
    void setupRotMat(const Vector3<Real>& eulerAngles) {
      setupRotMat(eulerAngles[0], eulerAngles[1], eulerAngles[2]);
    }

    /**
     * Sets this matrix to a rotation matrix by three euler angles
     * @param phi
     * @param theta
     * @psi theta
     */
    void setupRotMat(Real phi, Real theta, Real psi) {
      Real sphi, stheta, spsi;
      Real cphi, ctheta, cpsi;

      sphi = sin(phi);
      stheta = sin(theta);
      spsi = sin(psi);
      cphi = cos(phi);
      ctheta = cos(theta);
      cpsi = cos(psi);

      this->data_[0][0] = cpsi * cphi - ctheta * sphi * spsi;
      this->data_[0][1] = cpsi * sphi + ctheta * cphi * spsi;
      this->data_[0][2] = spsi * stheta;
                
      this->data_[1][0] = -spsi * ctheta - ctheta * sphi * cpsi;
      this->data_[1][1] = -spsi * stheta + ctheta * cphi * cpsi;
      this->data_[1][2] = cpsi * stheta;

      this->data_[2][0] = stheta * sphi;
      this->data_[2][1] = -stheta * cphi;
      this->data_[2][2] = ctheta;
    }


    /**
     * Sets this matrix to a rotation matrix by quaternion
     * @param quat
     */
    void setupRotMat(const Quaternion<Real>& quat) {
      setupRotMat(quat.w(), quat.x(), quat.y(), quat.z());
    }

    /**
     * Sets this matrix to a rotation matrix by quaternion
     * @param w the first element 
     * @param x the second element
     * @param y the third element
     * @param z the fourth element
     */
    void setupRotMat(Real w, Real x, Real y, Real z) {
      Quaternion<Real> q(w, x, y, z);
      *this = q.toRotationMatrix3();
    }

    void setupSkewMat(Vector3<Real> v) {
        setupSkewMat(v[0], v[1], v[2]);
    }

    void setupSkewMat(Real v1, Real v2, Real v3) {
        this->data_[0][0] = 0;
        this->data_[0][1] = -v3;
        this->data_[0][2] = v2;
        this->data_[1][0] = v3;
        this->data_[1][1] = 0;
        this->data_[1][2] = -v1;
        this->data_[2][0] = -v2;
        this->data_[2][1] = v1;
        this->data_[2][2] = 0;
        
        
    }


    /**
     * Returns the quaternion from this rotation matrix
     * @return the quaternion from this rotation matrix
     * @exception invalid rotation matrix
     */            
    Quaternion<Real> toQuaternion() {
      Quaternion<Real> q;
      Real t, s;
      Real ad1, ad2, ad3;    
      t = this->data_[0][0] + this->data_[1][1] + this->data_[2][2] + 1.0;

      if( t > NumericConstant::epsilon ){

        s = 0.5 / sqrt( t );
        q[0] = 0.25 / s;
        q[1] = (this->data_[1][2] - this->data_[2][1]) * s;
        q[2] = (this->data_[2][0] - this->data_[0][2]) * s;
        q[3] = (this->data_[0][1] - this->data_[1][0]) * s;
      } else {

        ad1 = this->data_[0][0];
        ad2 = this->data_[1][1];
        ad3 = this->data_[2][2];

        if( ad1 >= ad2 && ad1 >= ad3 ){

          s = 0.5 / sqrt( 1.0 + this->data_[0][0] - this->data_[1][1] - this->data_[2][2] );
          q[0] = (this->data_[1][2] - this->data_[2][1]) * s;
          q[1] = 0.25 / s;
          q[2] = (this->data_[0][1] + this->data_[1][0]) * s;
          q[3] = (this->data_[0][2] + this->data_[2][0]) * s;
        } else if ( ad2 >= ad1 && ad2 >= ad3 ) {
          s = 0.5 / sqrt( 1.0 + this->data_[1][1] - this->data_[0][0] - this->data_[2][2] );
          q[0] = (this->data_[2][0] - this->data_[0][2] ) * s;
          q[1] = (this->data_[0][1] + this->data_[1][0]) * s;
          q[2] = 0.25 / s;
          q[3] = (this->data_[1][2] + this->data_[2][1]) * s;
        } else {

          s = 0.5 / sqrt( 1.0 + this->data_[2][2] - this->data_[0][0] - this->data_[1][1] );
          q[0] = (this->data_[0][1] - this->data_[1][0]) * s;
          q[1] = (this->data_[0][2] + this->data_[2][0]) * s;
          q[2] = (this->data_[1][2] + this->data_[2][1]) * s;
          q[3] = 0.25 / s;
        }
      }             

      return q;
                
    }

    /**
     * Returns the euler angles from this rotation matrix
     * @return the euler angles in a vector 
     * @exception invalid rotation matrix
     * We use so-called "x-convention", which is the most common definition. 
     * In this convention, the rotation given by Euler angles (phi, theta, psi), where the first 
     * rotation is by an angle phi about the z-axis, the second is by an angle  
     * theta (0 <= theta <= 180)about the x-axis, and thethird is by an angle psi about the
     * z-axis (again). 
     */            
    Vector3<Real> toEulerAngles() {
      Vector3<Real> myEuler;
      Real phi;
      Real theta;
      Real psi;
      Real ctheta;
      Real stheta;
                
      // set the tolerance for Euler angles and rotation elements

      theta = acos(std::min(1.0, std::max(-1.0,this->data_[2][2])));
      ctheta = this->data_[2][2]; 
      stheta = sqrt(1.0 - ctheta * ctheta);

      // when sin(theta) is close to 0, we need to consider singularity
      // In this case, we can assign an arbitary value to phi (or psi), and then determine 
      // the psi (or phi) or vice-versa. We'll assume that phi always gets the rotation, and psi is 0
      // in cases of singularity.  
      // we use atan2 instead of atan, since atan2 will give us -Pi to Pi. 
      // Since 0 <= theta <= 180, sin(theta) will be always non-negative. Therefore, it never
      // change the sign of both of the parameters passed to atan2.

      if (fabs(stheta) <= oopse::epsilon){
        psi = 0.0;
        phi = atan2(-this->data_[1][0], this->data_[0][0]);  
      }
      // we only have one unique solution
      else{    
        phi = atan2(this->data_[2][0], -this->data_[2][1]);
        psi = atan2(this->data_[0][2], this->data_[1][2]);
      }

      //wrap phi and psi, make sure they are in the range from 0 to 2*Pi
      if (phi < 0)
        phi += M_PI;

      if (psi < 0)
        psi += M_PI;

      myEuler[0] = phi;
      myEuler[1] = theta;
      myEuler[2] = psi;

      return myEuler;
    }
            
    /** Returns the determinant of this matrix. */
    Real determinant() const {
      Real x,y,z;

      x = this->data_[0][0] * (this->data_[1][1] * this->data_[2][2] - this->data_[1][2] * this->data_[2][1]);
      y = this->data_[0][1] * (this->data_[1][2] * this->data_[2][0] - this->data_[1][0] * this->data_[2][2]);
      z = this->data_[0][2] * (this->data_[1][0] * this->data_[2][1] - this->data_[1][1] * this->data_[2][0]);

      return(x + y + z);
    }            

    /** Returns the trace of this matrix. */
    Real trace() const {
      return this->data_[0][0] + this->data_[1][1] + this->data_[2][2];
    }
            
    /**
     * Sets the value of this matrix to  the inversion of itself. 
     * @note since simple algorithm can be applied to inverse the 3 by 3 matrix, we hide the 
     * implementation of inverse in SquareMatrix class
     */
    SquareMatrix3<Real>  inverse() const {
      SquareMatrix3<Real> m;
      double det = determinant();
      if (fabs(det) <= oopse::epsilon) {
        //"The method was called on a matrix with |determinant| <= 1e-6.",
        //"This is a runtime or a programming error in your application.");
        std::vector<int> zeroDiagElementIndex;
        for (int i =0; i < 3; ++i) {
            if (fabs(this->data_[i][i]) <= oopse::epsilon) {
                zeroDiagElementIndex.push_back(i);
            }
        }

        if (zeroDiagElementIndex.size() == 2) {
            int index = zeroDiagElementIndex[0];
            m(index, index) = 1.0 / this->data_[index][index];
        }else if (zeroDiagElementIndex.size() == 1) {

            int a = (zeroDiagElementIndex[0] + 1) % 3;
            int b = (zeroDiagElementIndex[0] + 2) %3;
            double denom = this->data_[a][a] * this->data_[b][b] - this->data_[b][a]*this->data_[a][b];
            m(a, a) = this->data_[b][b] /denom;
            m(b, a) = -this->data_[b][a]/denom;

            m(a,b) = -this->data_[a][b]/denom;
            m(b, b) = this->data_[a][a]/denom;
                
        }
      
/*
        for(std::vector<int>::iterator iter = zeroDiagElementIndex.begin(); iter != zeroDiagElementIndex.end() ++iter) {
            if (this->data_[*iter][0] > oopse::epsilon || this->data_[*iter][1] ||this->data_[*iter][2] ||
                this->data_[0][*iter] > oopse::epsilon || this->data_[1][*iter] ||this->data_[2][*iter] ) {
                std::cout << "can not inverse matrix" << std::endl;
            }
        }
*/
      } else {

          m(0, 0) = this->data_[1][1]*this->data_[2][2] - this->data_[1][2]*this->data_[2][1];
          m(1, 0) = this->data_[1][2]*this->data_[2][0] - this->data_[1][0]*this->data_[2][2];
          m(2, 0) = this->data_[1][0]*this->data_[2][1] - this->data_[1][1]*this->data_[2][0];
          m(0, 1) = this->data_[2][1]*this->data_[0][2] - this->data_[2][2]*this->data_[0][1];
          m(1, 1) = this->data_[2][2]*this->data_[0][0] - this->data_[2][0]*this->data_[0][2];
          m(2, 1) = this->data_[2][0]*this->data_[0][1] - this->data_[2][1]*this->data_[0][0];
          m(0, 2) = this->data_[0][1]*this->data_[1][2] - this->data_[0][2]*this->data_[1][1];
          m(1, 2) = this->data_[0][2]*this->data_[1][0] - this->data_[0][0]*this->data_[1][2];
          m(2, 2) = this->data_[0][0]*this->data_[1][1] - this->data_[0][1]*this->data_[1][0];

          m /= det;
        }
      return m;
    }

    SquareMatrix3<Real> transpose() const{
      SquareMatrix3<Real> result;
                
      for (unsigned int i = 0; i < 3; i++)
        for (unsigned int j = 0; j < 3; j++)              
          result(j, i) = this->data_[i][j];

      return result;
    }
    /**
     * Extract the eigenvalues and eigenvectors from a 3x3 matrix.
     * The eigenvectors (the columns of V) will be normalized. 
     * The eigenvectors are aligned optimally with the x, y, and z
     * axes respectively.
     * @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is
     *     overwritten             
     * @param w will contain the eigenvalues of the matrix On return of this function
     * @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are 
     *    normalized and mutually orthogonal.              
     * @warning a will be overwritten
     */
    static void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v); 
  };
  /*=========================================================================

  Program:   Visualization Toolkit
  Module:    $RCSfile: SquareMatrix3.hpp,v $

  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
  All rights reserved.
  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.

  This software is distributed WITHOUT ANY WARRANTY; without even
  the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
  PURPOSE.  See the above copyright notice for more information.

  =========================================================================*/
  template<typename Real>
  void SquareMatrix3<Real>::diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, 
                                        SquareMatrix3<Real>& v) {
    int i,j,k,maxI;
    Real tmp, maxVal;
    Vector3<Real> v_maxI, v_k, v_j;

    // diagonalize using Jacobi
    jacobi(a, w, v);
    // if all the eigenvalues are the same, return identity matrix
    if (w[0] == w[1] && w[0] == w[2] ) {
      v = SquareMatrix3<Real>::identity();
      return;
    }

    // transpose temporarily, it makes it easier to sort the eigenvectors
    v = v.transpose(); 
        
    // if two eigenvalues are the same, re-orthogonalize to optimally line
    // up the eigenvectors with the x, y, and z axes
    for (i = 0; i < 3; i++) {
      if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same
        // find maximum element of the independant eigenvector
        maxVal = fabs(v(i, 0));
        maxI = 0;
        for (j = 1; j < 3; j++) {
          if (maxVal < (tmp = fabs(v(i, j)))){
            maxVal = tmp;
            maxI = j;
          }
        }
            
        // swap the eigenvector into its proper position
        if (maxI != i) {
          tmp = w(maxI);
          w(maxI) = w(i);
          w(i) = tmp;

          v.swapRow(i, maxI);
        }
        // maximum element of eigenvector should be positive
        if (v(maxI, maxI) < 0) {
          v(maxI, 0) = -v(maxI, 0);
          v(maxI, 1) = -v(maxI, 1);
          v(maxI, 2) = -v(maxI, 2);
        }

        // re-orthogonalize the other two eigenvectors
        j = (maxI+1)%3;
        k = (maxI+2)%3;

        v(j, 0) = 0.0; 
        v(j, 1) = 0.0; 
        v(j, 2) = 0.0;
        v(j, j) = 1.0;

        /** @todo */
        v_maxI = v.getRow(maxI);
        v_j = v.getRow(j);
        v_k = cross(v_maxI, v_j);
        v_k.normalize();
        v_j = cross(v_k, v_maxI);
        v.setRow(j, v_j);
        v.setRow(k, v_k);


        // transpose vectors back to columns
        v = v.transpose();
        return;
      }
    }

    // the three eigenvalues are different, just sort the eigenvectors
    // to align them with the x, y, and z axes

    // find the vector with the largest x element, make that vector
    // the first vector
    maxVal = fabs(v(0, 0));
    maxI = 0;
    for (i = 1; i < 3; i++) {
      if (maxVal < (tmp = fabs(v(i, 0)))) {
        maxVal = tmp;
        maxI = i;
      }
    }

    // swap eigenvalue and eigenvector
    if (maxI != 0) {
      tmp = w(maxI);
      w(maxI) = w(0);
      w(0) = tmp;
      v.swapRow(maxI, 0);
    }
    // do the same for the y element
    if (fabs(v(1, 1)) < fabs(v(2, 1))) {
      tmp = w(2);
      w(2) = w(1);
      w(1) = tmp;
      v.swapRow(2, 1);
    }

    // ensure that the sign of the eigenvectors is correct
    for (i = 0; i < 2; i++) {
      if (v(i, i) < 0) {
        v(i, 0) = -v(i, 0);
        v(i, 1) = -v(i, 1);
        v(i, 2) = -v(i, 2);
      }
    }

    // set sign of final eigenvector to ensure that determinant is positive
    if (v.determinant() < 0) {
      v(2, 0) = -v(2, 0);
      v(2, 1) = -v(2, 1);
      v(2, 2) = -v(2, 2);
    }

    // transpose the eigenvectors back again
    v = v.transpose();
    return ;
  }

  /**
   * Return the multiplication of two matrixes  (m1 * m2). 
   * @return the multiplication of two matrixes
   * @param m1 the first matrix
   * @param m2 the second matrix
   */
  template<typename Real> 
  inline SquareMatrix3<Real> operator *(const SquareMatrix3<Real>& m1, const SquareMatrix3<Real>& m2) {
    SquareMatrix3<Real> result;

    for (unsigned int i = 0; i < 3; i++)
      for (unsigned int j = 0; j < 3; j++)
        for (unsigned int k = 0; k < 3; k++)
          result(i, j)  += m1(i, k) * m2(k, j);                

    return result;
  }

  template<typename Real> 
  inline SquareMatrix3<Real> outProduct(const Vector3<Real>& v1, const Vector3<Real>& v2) {
    SquareMatrix3<Real> result;

    for (unsigned int i = 0; i < 3; i++) {
      for (unsigned int j = 0; j < 3; j++) {
        result(i, j)  = v1[i] * v2[j];                
      }
    }
            
    return result;        
  }

    
  typedef SquareMatrix3<double> Mat3x3d;
  typedef SquareMatrix3<double> RotMat3x3d;

} //namespace oopse
#endif // MATH_SQUAREMATRIX_HPP

Revision:	2611
Committed:	Mon Mar 13 22:42:40 2006 UTC (18 years, 4 months ago) by tim
File size:	18463 byte(s)
Log Message:	LangevinDynamics in progress
#	User	Rev	Content
1	gezelter	2204	/*
2	gezelter	1930	* Copyright (c) 2005 The University of Notre Dame. All Rights Reserved.
3	tim	1563	*
4	gezelter	1930	* The University of Notre Dame grants you ("Licensee") a
5			* non-exclusive, royalty free, license to use, modify and
6			* redistribute this software in source and binary code form, provided
7			* that the following conditions are met:
8			*
9			* 1. Acknowledgement of the program authors must be made in any
10			* publication of scientific results based in part on use of the
11			* program. An acceptable form of acknowledgement is citation of
12			* the article in which the program was described (Matthew
13			* A. Meineke, Charles F. Vardeman II, Teng Lin, Christopher
14			* J. Fennell and J. Daniel Gezelter, "OOPSE: An Object-Oriented
15			* Parallel Simulation Engine for Molecular Dynamics,"
16			* J. Comput. Chem. 26, pp. 252-271 (2005))
17			*
18			* 2. Redistributions of source code must retain the above copyright
19			* notice, this list of conditions and the following disclaimer.
20			*
21			* 3. Redistributions in binary form must reproduce the above copyright
22			* notice, this list of conditions and the following disclaimer in the
23			* documentation and/or other materials provided with the
24			* distribution.
25			*
26			* This software is provided "AS IS," without a warranty of any
27			* kind. All express or implied conditions, representations and
28			* warranties, including any implied warranty of merchantability,
29			* fitness for a particular purpose or non-infringement, are hereby
30			* excluded. The University of Notre Dame and its licensors shall not
31			* be liable for any damages suffered by licensee as a result of
32			* using, modifying or distributing the software or its
33			* derivatives. In no event will the University of Notre Dame or its
34			* licensors be liable for any lost revenue, profit or data, or for
35			* direct, indirect, special, consequential, incidental or punitive
36			* damages, however caused and regardless of the theory of liability,
37			* arising out of the use of or inability to use software, even if the
38			* University of Notre Dame has been advised of the possibility of
39			* such damages.
40	tim	1563	*/
41	gezelter	1930
42	tim	1563	/**
43			* @file SquareMatrix3.hpp
44			* @author Teng Lin
45			* @date 10/11/2004
46			* @version 1.0
47			*/
48	gezelter	2204	#ifndef MATH_SQUAREMATRIX3_HPP
49	tim	1592	#define MATH_SQUAREMATRIX3_HPP
50	tim	2611	#include <vector>
51	tim	1586	#include "Quaternion.hpp"
52	tim	1563	#include "SquareMatrix.hpp"
53	tim	1586	#include "Vector3.hpp"
54	tim	2146	#include "utils/NumericConstant.hpp"
55	tim	1563	namespace oopse {
56
57	gezelter	2204	template<typename Real>
58			class SquareMatrix3 : public SquareMatrix<Real, 3> {
59			public:
60	tim	1630
61	gezelter	2204	typedef Real ElemType;
62			typedef Real* ElemPoinerType;
63	tim	1563
64	gezelter	2204	/** default constructor */
65			SquareMatrix3() : SquareMatrix<Real, 3>() {
66			}
67	tim	1563
68	gezelter	2204	/** Constructs and initializes every element of this matrix to a scalar */
69			SquareMatrix3(Real s) : SquareMatrix<Real,3>(s){
70			}
71	tim	1644
72	gezelter	2204	/** Constructs and initializes from an array */
73			SquareMatrix3(Real* array) : SquareMatrix<Real,3>(array){
74			}
75	tim	1644
76
77	gezelter	2204	/** copy constructor */
78			SquareMatrix3(const SquareMatrix<Real, 3>& m) : SquareMatrix<Real, 3>(m) {
79			}
80	gezelter	1930
81	gezelter	2204	SquareMatrix3( const Vector3<Real>& eulerAngles) {
82			setupRotMat(eulerAngles);
83			}
84	tim	1586
85	gezelter	2204	SquareMatrix3(Real phi, Real theta, Real psi) {
86			setupRotMat(phi, theta, psi);
87			}
88	tim	1586
89	gezelter	2204	SquareMatrix3(const Quaternion<Real>& q) {
90			setupRotMat(q);
91	tim	1606
92	gezelter	2204	}
93	tim	1586
94	gezelter	2204	SquareMatrix3(Real w, Real x, Real y, Real z) {
95			setupRotMat(w, x, y, z);
96			}
97	tim	1586
98	gezelter	2204	/** copy assignment operator */
99			SquareMatrix3<Real>& operator =(const SquareMatrix<Real, 3>& m) {
100			if (this == &m)
101			return *this;
102			SquareMatrix<Real, 3>::operator=(m);
103			return *this;
104			}
105	tim	1569
106	gezelter	1930
107	gezelter	2204	SquareMatrix3<Real>& operator =(const Quaternion<Real>& q) {
108			this->setupRotMat(q);
109			return *this;
110			}
111	gezelter	1930
112	gezelter	2204	/**
113			* Sets this matrix to a rotation matrix by three euler angles
114			* @ param euler
115			*/
116			void setupRotMat(const Vector3<Real>& eulerAngles) {
117			setupRotMat(eulerAngles[0], eulerAngles[1], eulerAngles[2]);
118			}
119	tim	1569
120	gezelter	2204	/**
121			* Sets this matrix to a rotation matrix by three euler angles
122			* @param phi
123			* @param theta
124			* @psi theta
125			*/
126			void setupRotMat(Real phi, Real theta, Real psi) {
127			Real sphi, stheta, spsi;
128			Real cphi, ctheta, cpsi;
129	tim	1569
130	gezelter	2204	sphi = sin(phi);
131			stheta = sin(theta);
132			spsi = sin(psi);
133			cphi = cos(phi);
134			ctheta = cos(theta);
135			cpsi = cos(psi);
136	tim	1569
137	gezelter	2204	this->data_[0][0] = cpsi * cphi - ctheta * sphi * spsi;
138			this->data_[0][1] = cpsi * sphi + ctheta * cphi * spsi;
139			this->data_[0][2] = spsi * stheta;
140	tim	1586
141	gezelter	2204	this->data_[1][0] = -spsi * ctheta - ctheta * sphi * cpsi;
142			this->data_[1][1] = -spsi * stheta + ctheta * cphi * cpsi;
143			this->data_[1][2] = cpsi * stheta;
144	tim	1586
145	gezelter	2204	this->data_[2][0] = stheta * sphi;
146			this->data_[2][1] = -stheta * cphi;
147			this->data_[2][2] = ctheta;
148			}
149	tim	1586
150
151	gezelter	2204	/**
152			* Sets this matrix to a rotation matrix by quaternion
153			* @param quat
154			*/
155			void setupRotMat(const Quaternion<Real>& quat) {
156			setupRotMat(quat.w(), quat.x(), quat.y(), quat.z());
157			}
158	tim	1569
159	gezelter	2204	/**
160			* Sets this matrix to a rotation matrix by quaternion
161			* @param w the first element
162			* @param x the second element
163			* @param y the third element
164			* @param z the fourth element
165			*/
166			void setupRotMat(Real w, Real x, Real y, Real z) {
167			Quaternion<Real> q(w, x, y, z);
168			*this = q.toRotationMatrix3();
169			}
170	tim	1569
171	tim	2596	void setupSkewMat(Vector3<Real> v) {
172			setupSkewMat(v[0], v[1], v[2]);
173			}
174
175			void setupSkewMat(Real v1, Real v2, Real v3) {
176			this->data_[0][0] = 0;
177			this->data_[0][1] = -v3;
178			this->data_[0][2] = v2;
179			this->data_[1][0] = v3;
180			this->data_[1][1] = 0;
181			this->data_[1][2] = -v1;
182			this->data_[2][0] = -v2;
183			this->data_[2][1] = v1;
184			this->data_[2][2] = 0;
185
186
187			}
188
189
190
191	gezelter	2204	/**
192			* Returns the quaternion from this rotation matrix
193			* @return the quaternion from this rotation matrix
194			* @exception invalid rotation matrix
195			*/
196			Quaternion<Real> toQuaternion() {
197			Quaternion<Real> q;
198			Real t, s;
199			Real ad1, ad2, ad3;
200			t = this->data_[0][0] + this->data_[1][1] + this->data_[2][2] + 1.0;
201	tim	1569
202	tim	2336	if( t > NumericConstant::epsilon ){
203	tim	1586
204	gezelter	2204	s = 0.5 / sqrt( t );
205			q[0] = 0.25 / s;
206			q[1] = (this->data_[1][2] - this->data_[2][1]) * s;
207			q[2] = (this->data_[2][0] - this->data_[0][2]) * s;
208			q[3] = (this->data_[0][1] - this->data_[1][0]) * s;
209			} else {
210	tim	1586
211	tim	2332	ad1 = this->data_[0][0];
212			ad2 = this->data_[1][1];
213			ad3 = this->data_[2][2];
214	tim	1586
215	gezelter	2204	if( ad1 >= ad2 && ad1 >= ad3 ){
216	tim	1586
217	gezelter	2204	s = 0.5 / sqrt( 1.0 + this->data_[0][0] - this->data_[1][1] - this->data_[2][2] );
218			q[0] = (this->data_[1][2] - this->data_[2][1]) * s;
219			q[1] = 0.25 / s;
220			q[2] = (this->data_[0][1] + this->data_[1][0]) * s;
221			q[3] = (this->data_[0][2] + this->data_[2][0]) * s;
222			} else if ( ad2 >= ad1 && ad2 >= ad3 ) {
223			s = 0.5 / sqrt( 1.0 + this->data_[1][1] - this->data_[0][0] - this->data_[2][2] );
224			q[0] = (this->data_[2][0] - this->data_[0][2] ) * s;
225			q[1] = (this->data_[0][1] + this->data_[1][0]) * s;
226			q[2] = 0.25 / s;
227			q[3] = (this->data_[1][2] + this->data_[2][1]) * s;
228			} else {
229	tim	1586
230	gezelter	2204	s = 0.5 / sqrt( 1.0 + this->data_[2][2] - this->data_[0][0] - this->data_[1][1] );
231			q[0] = (this->data_[0][1] - this->data_[1][0]) * s;
232			q[1] = (this->data_[0][2] + this->data_[2][0]) * s;
233			q[2] = (this->data_[1][2] + this->data_[2][1]) * s;
234			q[3] = 0.25 / s;
235			}
236			}
237	tim	1586
238	gezelter	2204	return q;
239	tim	1586
240	gezelter	2204	}
241	tim	1586
242	gezelter	2204	/**
243			* Returns the euler angles from this rotation matrix
244			* @return the euler angles in a vector
245			* @exception invalid rotation matrix
246			* We use so-called "x-convention", which is the most common definition.
247			* In this convention, the rotation given by Euler angles (phi, theta, psi), where the first
248			* rotation is by an angle phi about the z-axis, the second is by an angle
249			* theta (0 <= theta <= 180)about the x-axis, and thethird is by an angle psi about the
250			* z-axis (again).
251			*/
252			Vector3<Real> toEulerAngles() {
253			Vector3<Real> myEuler;
254			Real phi;
255			Real theta;
256			Real psi;
257			Real ctheta;
258			Real stheta;
259	tim	1586
260	gezelter	2204	// set the tolerance for Euler angles and rotation elements
261	tim	1586
262	gezelter	2204	theta = acos(std::min(1.0, std::max(-1.0,this->data_[2][2])));
263			ctheta = this->data_[2][2];
264			stheta = sqrt(1.0 - ctheta * ctheta);
265	tim	1586
266	gezelter	2204	// when sin(theta) is close to 0, we need to consider singularity
267			// In this case, we can assign an arbitary value to phi (or psi), and then determine
268			// the psi (or phi) or vice-versa. We'll assume that phi always gets the rotation, and psi is 0
269			// in cases of singularity.
270			// we use atan2 instead of atan, since atan2 will give us -Pi to Pi.
271			// Since 0 <= theta <= 180, sin(theta) will be always non-negative. Therefore, it never
272			// change the sign of both of the parameters passed to atan2.
273	tim	1586
274	gezelter	2204	if (fabs(stheta) <= oopse::epsilon){
275			psi = 0.0;
276			phi = atan2(-this->data_[1][0], this->data_[0][0]);
277			}
278			// we only have one unique solution
279			else{
280			phi = atan2(this->data_[2][0], -this->data_[2][1]);
281			psi = atan2(this->data_[0][2], this->data_[1][2]);
282			}
283	tim	1586
284	gezelter	2204	//wrap phi and psi, make sure they are in the range from 0 to 2*Pi
285			if (phi < 0)
286			phi += M_PI;
287	tim	1586
288	gezelter	2204	if (psi < 0)
289			psi += M_PI;
290	tim	1586
291	gezelter	2204	myEuler[0] = phi;
292			myEuler[1] = theta;
293			myEuler[2] = psi;
294	tim	1586
295	gezelter	2204	return myEuler;
296			}
297	tim	1563
298	gezelter	2204	/** Returns the determinant of this matrix. */
299			Real determinant() const {
300			Real x,y,z;
301	tim	1594
302	gezelter	2204	x = this->data_[0][0] * (this->data_[1][1] * this->data_[2][2] - this->data_[1][2] * this->data_[2][1]);
303			y = this->data_[0][1] * (this->data_[1][2] * this->data_[2][0] - this->data_[1][0] * this->data_[2][2]);
304			z = this->data_[0][2] * (this->data_[1][0] * this->data_[2][1] - this->data_[1][1] * this->data_[2][0]);
305	tim	1594
306	gezelter	2204	return(x + y + z);
307			}
308	gezelter	1930
309	gezelter	2204	/** Returns the trace of this matrix. */
310			Real trace() const {
311			return this->data_[0][0] + this->data_[1][1] + this->data_[2][2];
312			}
313	tim	1594
314	gezelter	2204	/**
315			* Sets the value of this matrix to the inversion of itself.
316			* @note since simple algorithm can be applied to inverse the 3 by 3 matrix, we hide the
317			* implementation of inverse in SquareMatrix class
318			*/
319			SquareMatrix3<Real> inverse() const {
320			SquareMatrix3<Real> m;
321			double det = determinant();
322			if (fabs(det) <= oopse::epsilon) {
323			//"The method was called on a matrix with \|determinant\| <= 1e-6.",
324			//"This is a runtime or a programming error in your application.");
325	tim	2611	std::vector<int> zeroDiagElementIndex;
326			for (int i =0; i < 3; ++i) {
327			if (fabs(this->data_[i][i]) <= oopse::epsilon) {
328			zeroDiagElementIndex.push_back(i);
329			}
330			}
331	tim	1563
332	tim	2611	if (zeroDiagElementIndex.size() == 2) {
333			int index = zeroDiagElementIndex[0];
334			m(index, index) = 1.0 / this->data_[index][index];
335			}else if (zeroDiagElementIndex.size() == 1) {
336	tim	1594
337	tim	2611	int a = (zeroDiagElementIndex[0] + 1) % 3;
338			int b = (zeroDiagElementIndex[0] + 2) %3;
339			double denom = this->data_[a][a] * this->data_[b][b] - this->data_[b][a]*this->data_[a][b];
340			m(a, a) = this->data_[b][b] /denom;
341			m(b, a) = -this->data_[b][a]/denom;
342
343			m(a,b) = -this->data_[a][b]/denom;
344			m(b, b) = this->data_[a][a]/denom;
345
346			}
347
348			/*
349			for(std::vector<int>::iterator iter = zeroDiagElementIndex.begin(); iter != zeroDiagElementIndex.end() ++iter) {
350			if (this->data_[iter][0] > oopse::epsilon \|\| this->data_[iter][1] \|\|this->data_[*iter][2] \|\|
351			this->data_[0][iter] > oopse::epsilon \|\| this->data_[1][iter] \|\|this->data_[2][*iter] ) {
352			std::cout << "can not inverse matrix" << std::endl;
353			}
354			}
355			*/
356			} else {
357
358			m(0, 0) = this->data_[1][1]this->data_[2][2] - this->data_[1][2]this->data_[2][1];
359			m(1, 0) = this->data_[1][2]this->data_[2][0] - this->data_[1][0]this->data_[2][2];
360			m(2, 0) = this->data_[1][0]this->data_[2][1] - this->data_[1][1]this->data_[2][0];
361			m(0, 1) = this->data_[2][1]this->data_[0][2] - this->data_[2][2]this->data_[0][1];
362			m(1, 1) = this->data_[2][2]this->data_[0][0] - this->data_[2][0]this->data_[0][2];
363			m(2, 1) = this->data_[2][0]this->data_[0][1] - this->data_[2][1]this->data_[0][0];
364			m(0, 2) = this->data_[0][1]this->data_[1][2] - this->data_[0][2]this->data_[1][1];
365			m(1, 2) = this->data_[0][2]this->data_[1][0] - this->data_[0][0]this->data_[1][2];
366			m(2, 2) = this->data_[0][0]this->data_[1][1] - this->data_[0][1]this->data_[1][0];
367
368			m /= det;
369			}
370	gezelter	2204	return m;
371			}
372	tim	2583
373			SquareMatrix3<Real> transpose() const{
374			SquareMatrix3<Real> result;
375
376			for (unsigned int i = 0; i < 3; i++)
377			for (unsigned int j = 0; j < 3; j++)
378			result(j, i) = this->data_[i][j];
379
380			return result;
381			}
382	gezelter	2204	/**
383			* Extract the eigenvalues and eigenvectors from a 3x3 matrix.
384			* The eigenvectors (the columns of V) will be normalized.
385			* The eigenvectors are aligned optimally with the x, y, and z
386			* axes respectively.
387			* @param a symmetric matrix whose eigenvectors are to be computed. On return, the matrix is
388			* overwritten
389			* @param w will contain the eigenvalues of the matrix On return of this function
390			* @param v the columns of this matrix will contain the eigenvectors. The eigenvectors are
391			* normalized and mutually orthogonal.
392			* @warning a will be overwritten
393			*/
394			static void diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w, SquareMatrix3<Real>& v);
395			};
396			/*=========================================================================
397	tim	1569
398	tim	1616	Program: Visualization Toolkit
399			Module: $RCSfile: SquareMatrix3.hpp,v $
400	tim	1592
401	tim	1616	Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
402			All rights reserved.
403			See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
404	tim	1594
405	gezelter	2204	This software is distributed WITHOUT ANY WARRANTY; without even
406			the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
407			PURPOSE. See the above copyright notice for more information.
408	tim	1594
409	gezelter	2204	=========================================================================*/
410			template<typename Real>
411			void SquareMatrix3<Real>::diagonalize(SquareMatrix3<Real>& a, Vector3<Real>& w,
412			SquareMatrix3<Real>& v) {
413			int i,j,k,maxI;
414			Real tmp, maxVal;
415			Vector3<Real> v_maxI, v_k, v_j;
416	tim	1594
417	gezelter	2204	// diagonalize using Jacobi
418			jacobi(a, w, v);
419			// if all the eigenvalues are the same, return identity matrix
420			if (w[0] == w[1] && w[0] == w[2] ) {
421			v = SquareMatrix3<Real>::identity();
422			return;
423			}
424	tim	1594
425	gezelter	2204	// transpose temporarily, it makes it easier to sort the eigenvectors
426			v = v.transpose();
427	tim	1616
428	gezelter	2204	// if two eigenvalues are the same, re-orthogonalize to optimally line
429			// up the eigenvectors with the x, y, and z axes
430			for (i = 0; i < 3; i++) {
431			if (w((i+1)%3) == w((i+2)%3)) {// two eigenvalues are the same
432			// find maximum element of the independant eigenvector
433			maxVal = fabs(v(i, 0));
434			maxI = 0;
435			for (j = 1; j < 3; j++) {
436			if (maxVal < (tmp = fabs(v(i, j)))){
437			maxVal = tmp;
438			maxI = j;
439			}
440			}
441	tim	1616
442	gezelter	2204	// swap the eigenvector into its proper position
443			if (maxI != i) {
444			tmp = w(maxI);
445			w(maxI) = w(i);
446			w(i) = tmp;
447	tim	1594
448	gezelter	2204	v.swapRow(i, maxI);
449			}
450			// maximum element of eigenvector should be positive
451			if (v(maxI, maxI) < 0) {
452			v(maxI, 0) = -v(maxI, 0);
453			v(maxI, 1) = -v(maxI, 1);
454			v(maxI, 2) = -v(maxI, 2);
455			}
456	tim	1594
457	gezelter	2204	// re-orthogonalize the other two eigenvectors
458			j = (maxI+1)%3;
459			k = (maxI+2)%3;
460	tim	1594
461	gezelter	2204	v(j, 0) = 0.0;
462			v(j, 1) = 0.0;
463			v(j, 2) = 0.0;
464			v(j, j) = 1.0;
465	tim	1594
466	gezelter	2204	/** @todo */
467			v_maxI = v.getRow(maxI);
468			v_j = v.getRow(j);
469			v_k = cross(v_maxI, v_j);
470			v_k.normalize();
471			v_j = cross(v_k, v_maxI);
472			v.setRow(j, v_j);
473			v.setRow(k, v_k);
474	tim	1594
475
476	gezelter	2204	// transpose vectors back to columns
477			v = v.transpose();
478			return;
479			}
480			}
481	tim	1594
482	gezelter	2204	// the three eigenvalues are different, just sort the eigenvectors
483			// to align them with the x, y, and z axes
484	tim	1594
485	gezelter	2204	// find the vector with the largest x element, make that vector
486			// the first vector
487			maxVal = fabs(v(0, 0));
488			maxI = 0;
489			for (i = 1; i < 3; i++) {
490			if (maxVal < (tmp = fabs(v(i, 0)))) {
491			maxVal = tmp;
492			maxI = i;
493			}
494			}
495	tim	1594
496	gezelter	2204	// swap eigenvalue and eigenvector
497			if (maxI != 0) {
498			tmp = w(maxI);
499			w(maxI) = w(0);
500			w(0) = tmp;
501			v.swapRow(maxI, 0);
502			}
503			// do the same for the y element
504			if (fabs(v(1, 1)) < fabs(v(2, 1))) {
505			tmp = w(2);
506			w(2) = w(1);
507			w(1) = tmp;
508			v.swapRow(2, 1);
509			}
510	tim	1594
511	gezelter	2204	// ensure that the sign of the eigenvectors is correct
512			for (i = 0; i < 2; i++) {
513			if (v(i, i) < 0) {
514			v(i, 0) = -v(i, 0);
515			v(i, 1) = -v(i, 1);
516			v(i, 2) = -v(i, 2);
517			}
518			}
519	tim	1563
520	gezelter	2204	// set sign of final eigenvector to ensure that determinant is positive
521			if (v.determinant() < 0) {
522			v(2, 0) = -v(2, 0);
523			v(2, 1) = -v(2, 1);
524			v(2, 2) = -v(2, 2);
525	tim	1616	}
526	gezelter	1930
527	gezelter	2204	// transpose the eigenvectors back again
528			v = v.transpose();
529			return ;
530			}
531	gezelter	1930
532	gezelter	2204	/**
533			* Return the multiplication of two matrixes (m1 * m2).
534			* @return the multiplication of two matrixes
535			* @param m1 the first matrix
536			* @param m2 the second matrix
537			*/
538			template<typename Real>
539			inline SquareMatrix3<Real> operator *(const SquareMatrix3<Real>& m1, const SquareMatrix3<Real>& m2) {
540			SquareMatrix3<Real> result;
541	gezelter	1930
542	gezelter	2204	for (unsigned int i = 0; i < 3; i++)
543			for (unsigned int j = 0; j < 3; j++)
544			for (unsigned int k = 0; k < 3; k++)
545			result(i, j) += m1(i, k) * m2(k, j);
546	gezelter	1930
547	gezelter	2204	return result;
548			}
549	gezelter	1930
550	gezelter	2204	template<typename Real>
551			inline SquareMatrix3<Real> outProduct(const Vector3<Real>& v1, const Vector3<Real>& v2) {
552			SquareMatrix3<Real> result;
553
554			for (unsigned int i = 0; i < 3; i++) {
555			for (unsigned int j = 0; j < 3; j++) {
556			result(i, j) = v1[i] * v2[j];
557			}
558			}
559	gezelter	1930
560	gezelter	2204	return result;
561			}
562	gezelter	1930
563
564	gezelter	2204	typedef SquareMatrix3<double> Mat3x3d;
565			typedef SquareMatrix3<double> RotMat3x3d;
566	tim	1586
567			} //namespace oopse
568			#endif // MATH_SQUAREMATRIX_HPP
569	tim	1616