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svd_solve implemented

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Jiri Pittner
2026-02-11 16:56:12 +01:00
parent 36983222e8
commit f8923b1a3f
3 changed files with 61 additions and 5 deletions
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3
nonclass.cc
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@@ -918,9 +918,6 @@ void singular_decomposition(NRMat<std::complex<double> > &a, NRMat<std::complex<
}
//QR decomposition
//extern "C" void FORNAME(dgeqrf)(const int *M, const int *N, double *A, const int *LDA, double *TAU, double *WORK, int *LWORK, int *INFO);

39
nonclass.h
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@@ -158,13 +158,50 @@ extern void linear_solve(NRMat<T> &a, NRVec<T> &b, double *det=0, int n=0); \
extern void linear_solve(NRSMat<T> &a, NRVec<T> &b, double *det=0, int n=0); \
extern void diagonalize(NRMat<T> &a, NRVec<LA_traits<T>::normtype> &w, const bool eivec=1, const bool corder=1, int n=0, NRMat<T> *b=NULL, const int itype=1); \
extern void diagonalize(NRSMat<T> &a, NRVec<LA_traits<T>::normtype> &w, NRMat<T> *v, const bool corder=1, int n=0, NRSMat<T> *b=NULL, const int itype=1);\
extern void singular_decomposition(NRMat<T> &a, NRMat<T> *u, NRVec<LA_traits<T>::normtype> &s, NRMat<T> *v, const bool vnotdagger=0, int m=0, int n=0);
extern void singular_decomposition(NRMat<T> &a, NRMat<T> *u, NRVec<LA_traits<T>::normtype> &s, NRMat<T> *v, const bool vnotdagger=0, int m=0, int n=0); \
/*NOTE!!! all versions of diagonalize DESTROY A and generalized diagonalize also B matrix */
declare_la(double)
declare_la(std::complex<double>)
//svd_solve without contamination from nullspace, b is n x nrhs, result returns in b, A is destroyed
template<typename T>
NRVec<T> svd_solve(NRMat<T> &a, const NRVec<T> &b, double thres=1e-12)
{
if(b.size()!=a.nrows()) laerror("size mismatch in svd_solve");
NRVec<double> w(a.ncols());
NRMat<T> u(a.nrows(),a.ncols());
NRMat<T> vt(a.ncols(),a.ncols());
singular_decomposition(a,&u,w,&vt,false);
NRVec<T> utb = b*u;
for(int i=0; i<w.size(); ++i) utb[i] = w[i]>thres ? utb[i]/w[i] : 0.;
return utb*vt;
}
template<typename T>
NRMat<T> svd_solve(NRMat<T> &a, const NRMat<T> &b, double thres=1e-12)
{
if(b.nrows()!=a.nrows()) laerror("size mismatch in svd_solve");
NRVec<double> w(a.ncols());
NRMat<T> u(a.nrows(),a.ncols());
NRMat<T> vt(a.ncols(),a.ncols());
singular_decomposition(a,&u,w,&vt,false);
NRVec<T> ww(w.size());
for(int i=0; i<w.size(); ++i) ww[i] = w[i]>thres ? 1./w[i] : 0.;
NRMat<T> utb(a.ncols(),b.ncols());
utb.gemm((T)0,u,'c',b,'n',(T)1);
utb.diagmultl(ww);
NRMat<T> res(a.ncols(),b.ncols());
res.gemm((T)0,vt,'c',utb,'n',(T)1);
return res;
}
// Separate declarations
//general nonsymmetric matrix and generalized diagonalization
//corder =0 ... C rows are eigenvectors, =1 ... C columns are eigenvectors

24
t.cc
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@@ -4665,7 +4665,7 @@ NRMat<double> b = explicit_matrix<double,NRMat<double> >(a);
cout <<"Error = "<<(a-b).norm()<<endl;
}
if(1)
if(0)
{
int m;
int which;
@@ -4696,5 +4696,27 @@ for(int i=0; i<m; ++i)
}
if(0)
{
NRMat<double> a;
NRVec<double> b;
cin >>a>>b;
NRMat<double> aa(a);
NRVec<double> x = svd_solve(aa,b);
cout <<x;
cout <<"Error = "<< (a*x-b).norm()<<endl;
}
if(1)
{
NRMat<double> a;
NRMat<double> b;
cin >>a>>b;
NRMat<double> aa(a);
NRMat<double> x = svd_solve(aa,b);
cout <<x;
cout <<"Error = "<< (a*x-b).norm()<<endl;
}
}//main