Revision 1265

trunk/src/linad99/dveigen.cpp (revision 1265)
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  }
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  dvar_matrix m1=symmetrize(m);
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  int n=m1.rowsize();
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  int cmin=m1.colmin();
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  int rmin=m1.rowmin();
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  m1.colshift(1);     // set minimum column and row indices to 1
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  m1.rowshift(1);
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  dvar_vector diag(1,n);
......
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  tri_dag(m1,diag,off_diag);
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  get_eigen(diag,off_diag,m1); // eigenvalues are returned in diag
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           // eigenvalues are returned in columns of z
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  // eigenvalues are returned in diag
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  get_eigen(diag,off_diag,m1);
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  // eigenvalues are returned in columns of z
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  return diag;
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}
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/** Householder transformation for eigenvalue computation.
......
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  ADUNCONST(dvar_vector,d)
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  ADUNCONST(dvar_vector,e)
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  int n=d.size();
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  int m,l,iter,i,k;
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  int m,l,iter,i;
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  dvariable s,r,p,g,f,dd,c,b;
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  for (i=2;i<=n;i++) e[i-1]=e[i];
......
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          g=c*r-b;
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          /* Next loop can be omitted if eigenvectors not wanted */
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          #ifdef EIGEN_VECTORS
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            for (k=1;k<=n;k++)
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            for (int k=1;k<=n;k++)
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            {
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              f=z[k][i+1];
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              z[k][i+1]=s*z[k][i]+c*f;
......
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  int n=d.size();
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  int m,l,iter,i,k;
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  int m,l,iter,i;
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  dvariable s,r,p,g,f,dd,c,b;
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  for (i=2;i<=n;i++) e[i-1]=e[i];
trunk/src/linad99/dveigenv.cpp (revision 1265)
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  dvar_matrix m1=symmetrize(m);
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  int n=m1.rowsize();
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  int imin=m.colmin();
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  m1.colshift(1);     // set minimum column and row indices to 1
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  m1.rowshift(1);
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  dvar_vector diag(1,n);

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