--- trunk/OOPSE-3.0/src/math/SquareMatrix.hpp	2004/10/17 01:19:11	1586
+++ trunk/OOPSE-3.0/src/math/SquareMatrix.hpp	2005/01/25 17:45:23	1957
@@ -1,35 +1,51 @@
-/*
- * Copyright (C) 2000-2004  Object Oriented Parallel Simulation Engine (OOPSE) project
- * 
- * Contact: oopse@oopse.org
- * 
- * This program is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public License
- * as published by the Free Software Foundation; either version 2.1
- * of the License, or (at your option) any later version.
- * All we ask is that proper credit is given for our work, which includes
- * - but is not limited to - adding the above copyright notice to the beginning
- * of your source code files, and to any copyright notice that you may distribute
- * with programs based on this work.
- * 
- * 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
- * GNU Lesser General Public License for more details.
- * 
- * You should have received a copy of the GNU Lesser General Public License
- * along with this program; if not, write to the Free Software
- * Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
+ /*
+ * 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 SquareMatrix.hpp
  * @author Teng Lin
  * @date 10/11/2004
  * @version 1.0
  */
-#ifndef MATH_SQUAREMATRIX_HPP 
+ #ifndef MATH_SQUAREMATRIX_HPP 
 #define MATH_SQUAREMATRIX_HPP 
 
 #include "math/RectMatrix.hpp"
@@ -45,273 +61,332 @@ namespace oopse {
     template<typename Real, int Dim>
     class SquareMatrix : public RectMatrix<Real, Dim, Dim> {
         public:
+            typedef Real ElemType;
+            typedef Real* ElemPoinerType;
 
-        /** default constructor */
-        SquareMatrix() {
-            for (unsigned int i = 0; i < Dim; i++)
-                for (unsigned int j = 0; j < Dim; j++)
-                    data_[i][j] = 0.0;
-         }
+            /** default constructor */
+            SquareMatrix() {
+                for (unsigned int i = 0; i < Dim; i++)
+                    for (unsigned int j = 0; j < Dim; j++)
+                        data_[i][j] = 0.0;
+             }
 
-        /** copy constructor */
-        SquareMatrix(const RectMatrix<Real, Dim, Dim>& m)  : RectMatrix<Real, Dim, Dim>(m) {
-        }
-        
-        /** copy assignment operator */
-        SquareMatrix<Real, Dim>& operator =(const RectMatrix<Real, Dim, Dim>& m) {
-            RectMatrix<Real, Dim, Dim>::operator=(m);
-            return *this;
-        }
-                               
-        /** Retunrs  an identity matrix*/
+            /** Constructs and initializes every element of this matrix to a scalar */ 
+            SquareMatrix(Real s) : RectMatrix<Real, Dim, Dim>(s){
+            }
 
-       static SquareMatrix<Real, Dim> identity() {
-            SquareMatrix<Real, Dim> m;
+            /** Constructs and initializes from an array */ 
+            SquareMatrix(Real* array) : RectMatrix<Real, Dim, Dim>(array){
+            }
+
+
+            /** copy constructor */
+            SquareMatrix(const RectMatrix<Real, Dim, Dim>& m) : RectMatrix<Real, Dim, Dim>(m) {
+            }
             
-            for (unsigned int i = 0; i < Dim; i++) 
-                for (unsigned int j = 0; j < Dim; j++) 
-                    if (i == j)
-                        m(i, j) = 1.0;
-                    else
-                        m(i, j) = 0.0;
+            /** copy assignment operator */
+            SquareMatrix<Real, Dim>& operator =(const RectMatrix<Real, Dim, Dim>& m) {
+                RectMatrix<Real, Dim, Dim>::operator=(m);
+                return *this;
+            }
+                                   
+            /** Retunrs  an identity matrix*/
 
-            return m;
-        }
+           static SquareMatrix<Real, Dim> identity() {
+                SquareMatrix<Real, Dim> m;
+                
+                for (unsigned int i = 0; i < Dim; i++) 
+                    for (unsigned int j = 0; j < Dim; j++) 
+                        if (i == j)
+                            m(i, j) = 1.0;
+                        else
+                            m(i, j) = 0.0;
 
-        /** Retunrs  the inversion of this matrix. */
-         SquareMatrix<Real, Dim>  inverse() {
-             SquareMatrix<Real, Dim> result;
+                return m;
+            }
 
-             return result;
-        }        
+            /** 
+             * Retunrs  the inversion of this matrix. 
+             * @todo need implementation
+             */
+             SquareMatrix<Real, Dim>  inverse() {
+                 SquareMatrix<Real, Dim> result;
 
-        /** Returns the determinant of this matrix. */
-        double determinant() const {
-            double det;
-            return det;
-        }
+                 return result;
+            }        
 
-        /** Returns the trace of this matrix. */
-        double trace() const {
-           double tmp = 0;
-           
-            for (unsigned int i = 0; i < Dim ; i++)
-                tmp += data_[i][i];
+            /**
+             * Returns the determinant of this matrix.
+             * @todo need implementation
+             */
+            Real determinant() const {
+                Real det;
+                return det;
+            }
 
-            return tmp;
-        }
+            /** Returns the trace of this matrix. */
+            Real trace() const {
+               Real tmp = 0;
+               
+                for (unsigned int i = 0; i < Dim ; i++)
+                    tmp += data_[i][i];
 
-        /** Tests if this matrix is symmetrix. */            
-        bool isSymmetric() const {
-            for (unsigned int i = 0; i < Dim - 1; i++)
-                for (unsigned int j = i; j < Dim; j++)
-                    if (fabs(data_[i][j] - data_[j][i]) > oopse::epsilon) 
-                        return false;
-                    
-            return true;
-        }
+                return tmp;
+            }
 
-        /** Tests if this matrix is orthogonal. */            
-        bool isOrthogonal() {
-            SquareMatrix<Real, Dim> tmp;
+            /** Tests if this matrix is symmetrix. */            
+            bool isSymmetric() const {
+                for (unsigned int i = 0; i < Dim - 1; i++)
+                    for (unsigned int j = i; j < Dim; j++)
+                        if (fabs(data_[i][j] - data_[j][i]) > oopse::epsilon) 
+                            return false;
+                        
+                return true;
+            }
 
-            tmp = *this * transpose();
+            /** Tests if this matrix is orthogonal. */            
+            bool isOrthogonal() {
+                SquareMatrix<Real, Dim> tmp;
 
-            return tmp.isDiagonal();
-        }
+                tmp = *this * transpose();
 
-        /** Tests if this matrix is diagonal. */
-        bool isDiagonal() const {
-            for (unsigned int i = 0; i < Dim ; i++)
-                for (unsigned int j = 0; j < Dim; j++)
-                    if (i !=j && fabs(data_[i][j]) > oopse::epsilon) 
+                return tmp.isDiagonal();
+            }
+
+            /** Tests if this matrix is diagonal. */
+            bool isDiagonal() const {
+                for (unsigned int i = 0; i < Dim ; i++)
+                    for (unsigned int j = 0; j < Dim; j++)
+                        if (i !=j && fabs(data_[i][j]) > oopse::epsilon) 
+                            return false;
+                        
+                return true;
+            }
+
+            /** Tests if this matrix is the unit matrix. */
+            bool isUnitMatrix() const {
+                if (!isDiagonal())
+                    return false;
+                
+                for (unsigned int i = 0; i < Dim ; i++)
+                    if (fabs(data_[i][i] - 1) > oopse::epsilon)
                         return false;
                     
-            return true;
-        }
+                return true;
+            }         
 
-        /** Tests if this matrix is the unit matrix. */
-        bool isUnitMatrix() const {
-            if (!isDiagonal())
-                return false;
-            
-            for (unsigned int i = 0; i < Dim ; i++)
-                if (fabs(data_[i][i] - 1) > oopse::epsilon)
-                    return false;
+            /** Return the transpose of this matrix */
+            SquareMatrix<Real,  Dim> transpose() const{
+                SquareMatrix<Real,  Dim> result;
                 
-            return true;
-        }         
+                for (unsigned int i = 0; i < Dim; i++)
+                    for (unsigned int j = 0; j < Dim; j++)              
+                        result(j, i) = data_[i][j];
 
-        void diagonalize() {
-            jacobi(m, eigenValues, ortMat);
-        }
-
-        /**
-         * Finds the eigenvalues and eigenvectors of a symmetric matrix
-         * @param eigenvals a reference to a vector3 where the
-         * eigenvalues will be stored. The eigenvalues are ordered so
-         * that eigenvals[0] <= eigenvals[1] <= eigenvals[2].
-         * @return an orthogonal matrix whose ith column is an
-         * eigenvector for the eigenvalue eigenvals[i]
-         */
-        SquareMatrix<Real, Dim>  findEigenvectors(Vector<Real, Dim>& eigenValues) {
-            SquareMatrix<Real, Dim> ortMat;
-            
-            if ( !isSymmetric()){
-                throw();
+                return result;
             }
             
-            SquareMatrix<Real, Dim> m(*this);
-            jacobi(m, eigenValues, ortMat);
+            /** @todo need implementation */
+            void diagonalize() {
+                //jacobi(m, eigenValues, ortMat);
+            }
 
-            return ortMat;
-        }
-        /**
-         * Jacobi iteration routines for computing eigenvalues/eigenvectors of 
-         * real symmetric matrix
-         *
-         * @return true if success, otherwise return false
-         * @param a source matrix
-         * @param w output eigenvalues 
-         * @param v output eigenvectors 
-         */
-        bool jacobi(const SquareMatrix<Real, Dim>& a, Vector<Real, Dim>& w, 
-                              SquareMatrix<Real, Dim>& v);
+            /**
+             * Jacobi iteration routines for computing eigenvalues/eigenvectors of 
+             * real symmetric matrix
+             *
+             * @return true if success, otherwise return false
+             * @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. 
+             */
+           
+            static int jacobi(SquareMatrix<Real, Dim>& a, Vector<Real, Dim>& d, 
+                                  SquareMatrix<Real, Dim>& v);
     };//end SquareMatrix
 
 
-#define ROT(a,i,j,k,l) g=a(i, j);h=a(k, l);a(i, j)=g-s*(h+g*tau);a(k, l)=h+s*(g-h*tau)
-#define MAX_ROTATIONS 60
+/*=========================================================================
 
-template<typename Real, int Dim>
-bool SquareMatrix<Real, Dim>::jacobi(const SquareMatrix<Real, Dim>& a, Vector<Real, Dim>& w, 
-                              SquareMatrix<Real, Dim>& v) {
-    const int N = Dim;                                                                       
-    int i, j, k, iq, ip;
-    double tresh, theta, tau, t, sm, s, h, g, c;
-    double tmp;
-    Vector<Real, Dim> b, z;
+  Program:   Visualization Toolkit
+  Module:    $RCSfile: SquareMatrix.hpp,v $
 
-    // initialize
-    for (ip=0; ip<N; ip++) {
-        for (iq=0; iq<N; iq++)
-            v(ip, iq) = 0.0;
-        v(ip, ip) = 1.0;
-    }
-    
-    for (ip=0; ip<N; ip++) {
-        b(ip) = w(ip) = a(ip, ip);
-        z(ip) = 0.0;
-    }
+  Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
+  All rights reserved.
+  See Copyright.txt or http://www.kitware.com/Copyright.htm for details.
 
-    // begin rotation sequence
-    for (i=0; i<MAX_ROTATIONS; i++) {
-        sm = 0.0;
-        for (ip=0; ip<2; ip++) {
-            for (iq=ip+1; iq<N; iq++)
-                sm += fabs(a(ip, iq));
+     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.
+
+=========================================================================*/
+
+#define VTK_ROTATE(a,i,j,k,l) g=a(i, j);h=a(k, l);a(i, j)=g-s*(h+g*tau);\
+        a(k, l)=h+s*(g-h*tau)
+
+#define VTK_MAX_ROTATIONS 20
+
+    // Jacobi iteration for the solution of eigenvectors/eigenvalues of a nxn
+    // real symmetric matrix. Square nxn matrix a; size of matrix in n;
+    // output eigenvalues in w; and output eigenvectors in v. Resulting
+    // eigenvalues/vectors are sorted in decreasing order; eigenvectors are
+    // normalized.
+    template<typename Real, int Dim>
+    int SquareMatrix<Real, Dim>::jacobi(SquareMatrix<Real, Dim>& a, Vector<Real, Dim>& w, 
+                                        SquareMatrix<Real, Dim>& v) {
+        const int n = Dim;  
+        int i, j, k, iq, ip, numPos;
+        Real tresh, theta, tau, t, sm, s, h, g, c, tmp;
+        Real bspace[4], zspace[4];
+        Real *b = bspace;
+        Real *z = zspace;
+
+        // only allocate memory if the matrix is large
+        if (n > 4) {
+            b = new Real[n];
+            z = new Real[n]; 
         }
-        
-        if (sm == 0.0)
-            break;
 
-        if (i < 4)
-            tresh = 0.2*sm/(9);
-        else
-            tresh = 0.0;
+        // initialize
+        for (ip=0; ip<n; ip++) {
+            for (iq=0; iq<n; iq++) {
+                v(ip, iq) = 0.0;
+            }
+            v(ip, ip) = 1.0;
+        }
+        for (ip=0; ip<n; ip++) {
+            b[ip] = w[ip] = a(ip, ip);
+            z[ip] = 0.0;
+        }
 
-        for (ip=0; ip<2; ip++) {
-            for (iq=ip+1; iq<N; iq++) {
-                g = 100.0*fabs(a(ip, iq));
-                if (i > 4 && (fabs(w(ip))+g) == fabs(w(ip))
-                    && (fabs(w(iq))+g) == fabs(w(iq))) {
-                    a(ip, iq) = 0.0;
-                } else if (fabs(a(ip, iq)) > tresh) {
-                    h = w(iq) - w(ip);
-                    if ( (fabs(h)+g) == fabs(h)) {
-                        t = (a(ip, iq)) / h;
-                    } else {
-                        theta = 0.5*h / (a(ip, iq));
-                        t = 1.0 / (fabs(theta)+sqrt(1.0+theta*theta));
+        // begin rotation sequence
+        for (i=0; i<VTK_MAX_ROTATIONS; i++) {
+            sm = 0.0;
+            for (ip=0; ip<n-1; ip++) {
+                for (iq=ip+1; iq<n; iq++) {
+                    sm += fabs(a(ip, iq));
+                }
+            }
+            if (sm == 0.0) {
+                break;
+            }
 
-                        if (theta < 0.0)
-                            t = -t;
-                    }
+            if (i < 3) {                                // first 3 sweeps
+                tresh = 0.2*sm/(n*n);
+            } else {
+                tresh = 0.0;
+            }
 
-                    c = 1.0 / sqrt(1+t*t);
-                    s = t*c;
-                    tau = s/(1.0+c);
-                    h = t*a(ip, iq);
-                    z(ip) -= h;
-                    z(iq) += h;
-                    w(ip) -= h;
-                    w(iq) += h;
-                    a(ip, iq)=0.0;
-                    
-                    for (j=0;j<ip-1;j++) 
-                        ROT(a,j,ip,j,iq);
+            for (ip=0; ip<n-1; ip++) {
+                for (iq=ip+1; iq<n; iq++) {
+                    g = 100.0*fabs(a(ip, iq));
 
-                    for (j=ip+1;j<iq-1;j++) 
-                        ROT(a,ip,j,j,iq);
+                    // after 4 sweeps
+                    if (i > 3 && (fabs(w[ip])+g) == fabs(w[ip])
+                        && (fabs(w[iq])+g) == fabs(w[iq])) {
+                        a(ip, iq) = 0.0;
+                    } else if (fabs(a(ip, iq)) > tresh) {
+                        h = w[iq] - w[ip];
+                        if ( (fabs(h)+g) == fabs(h)) {
+                            t = (a(ip, iq)) / h;
+                        } else {
+                            theta = 0.5*h / (a(ip, iq));
+                            t = 1.0 / (fabs(theta)+sqrt(1.0+theta*theta));
+                            if (theta < 0.0) {
+                                t = -t;
+                            }
+                        }
+                        c = 1.0 / sqrt(1+t*t);
+                        s = t*c;
+                        tau = s/(1.0+c);
+                        h = t*a(ip, iq);
+                        z[ip] -= h;
+                        z[iq] += h;
+                        w[ip] -= h;
+                        w[iq] += h;
+                        a(ip, iq)=0.0;
 
-                    for (j=iq+1; j<N; j++) 
-                        ROT(a,ip,j,iq,j);
-                    for (j=0; j<N; j++) 
-                        ROT(v,j,ip,j,iq);
+                        // ip already shifted left by 1 unit
+                        for (j = 0;j <= ip-1;j++) {
+                            VTK_ROTATE(a,j,ip,j,iq);
+                        }
+                        // ip and iq already shifted left by 1 unit
+                        for (j = ip+1;j <= iq-1;j++) {
+                            VTK_ROTATE(a,ip,j,j,iq);
+                        }
+                        // iq already shifted left by 1 unit
+                        for (j=iq+1; j<n; j++) {
+                            VTK_ROTATE(a,ip,j,iq,j);
+                        }
+                        for (j=0; j<n; j++) {
+                            VTK_ROTATE(v,j,ip,j,iq);
+                        }
+                    }
                 }
             }
-        }//for (ip=0; ip<2; ip++) 
 
-        for (ip=0; ip<N; ip++) {
-            b(ip) += z(ip);
-            w(ip) = b(ip);
-            z(ip) = 0.0;
+            for (ip=0; ip<n; ip++) {
+                b[ip] += z[ip];
+                w[ip] = b[ip];
+                z[ip] = 0.0;
+            }
         }
-        
-    } // end for (i=0; i<MAX_ROTATIONS; i++) 
 
-    if ( i >= MAX_ROTATIONS )
-        return false;
+        //// this is NEVER called
+        if ( i >= VTK_MAX_ROTATIONS ) {
+            std::cout << "vtkMath::Jacobi: Error extracting eigenfunctions" << std::endl;
+            return 0;
+        }
 
-    // sort eigenfunctions
-    for (j=0; j<N; j++) {
-        k = j;
-        tmp = w(k);
-        for (i=j; i<N; i++) {
-            if (w(i) >= tmp) {
-            k = i;
-            tmp = w(k);
+        // sort eigenfunctions                 these changes do not affect accuracy 
+        for (j=0; j<n-1; j++) {                  // boundary incorrect
+            k = j;
+            tmp = w[k];
+            for (i=j+1; i<n; i++) {                // boundary incorrect, shifted already
+                if (w[i] >= tmp) {                   // why exchage if same?
+                    k = i;
+                    tmp = w[k];
+                }
             }
+            if (k != j) {
+                w[k] = w[j];
+                w[j] = tmp;
+                for (i=0; i<n; i++) {
+                    tmp = v(i, j);
+                    v(i, j) = v(i, k);
+                    v(i, k) = tmp;
+                }
+            }
         }
-    
-        if (k != j) {
-            w(k) = w(j);
-            w(j) = tmp;
-            for (i=0; i<N; i++)  {
-                tmp = v(i, j);
-                v(i, j) = v(i, k);
-                v(i, k) = tmp;
+        // insure eigenvector consistency (i.e., Jacobi can compute vectors that
+        // are negative of one another (.707,.707,0) and (-.707,-.707,0). This can
+        // reek havoc in hyperstreamline/other stuff. We will select the most
+        // positive eigenvector.
+        int ceil_half_n = (n >> 1) + (n & 1);
+        for (j=0; j<n; j++) {
+            for (numPos=0, i=0; i<n; i++) {
+                if ( v(i, j) >= 0.0 ) {
+                    numPos++;
+                }
             }
+            //    if ( numPos < ceil(double(n)/double(2.0)) )
+            if ( numPos < ceil_half_n) {
+                for (i=0; i<n; i++) {
+                    v(i, j) *= -1.0;
+                }
+            }
         }
-    }
 
-    //    insure eigenvector consistency (i.e., Jacobi can compute
-    //    vectors that are negative of one another (.707,.707,0) and
-    //    (-.707,-.707,0). This can reek havoc in
-    //    hyperstreamline/other stuff. We will select the most
-    //    positive eigenvector.
-    int numPos;
-    for (j=0; j<N; j++) {
-        for (numPos=0, i=0; i<N; i++) if ( v(i, j) >= 0.0 ) numPos++;
-        if ( numPos < 2 ) for(i=0; i<N; i++) v(i, j) *= -1.0;
+        if (n > 4) {
+            delete [] b;
+            delete [] z;
+        }
+        return 1;
     }
 
-    return true;
-}
 
-#undef ROT
-#undef MAX_ROTATIONS
-
 }
-
 #endif //MATH_SQUAREMATRIX_HPP 
+