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[i1]=e[i]; 
...  ...  
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g=c*rb; 
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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[i1]=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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