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Clean up finished. Could shrink Lanczos to around 400 lines at a push

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This commit is contained in:
paboyle 2017-06-21 02:50:09 +01:00
parent 7e35286860
commit e8b95bd35b
2 changed files with 62 additions and 56 deletions
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114
lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
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@ -39,10 +39,11 @@ namespace Grid {
IRLdiagonaliseWithQR,
IRLdiagonaliseWithEigen
};
////////////////////////////////////////////////////////////////////////////////
// Helper class for sorting the evalues AND evectors by Field
// Use pointer swizzle on vectors
////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////
// Helper class for sorting the evalues AND evectors by Field
// Use pointer swizzle on vectors
////////////////////////////////////////////////////////////////////////////////
template<class Field>
class SortEigen {
private:
@ -90,7 +91,9 @@ class SortEigen {
/////////////////////////////////////////////////////////////
template<class Field>
class ImplicitlyRestartedLanczos {
private:
int MaxIter; // Max iterations
int Nstop; // Number of evecs checked for convergence
int Nk; // Number of converged sought
@ -122,6 +125,29 @@ public:
diagonalisation(_diagonalisation)
{ };
////////////////////////////////
// Helpers
////////////////////////////////
static RealD normalise(Field& v)
{
RealD nn = norm2(v);
nn = sqrt(nn);
v = v * (1.0/nn);
return nn;
}
void orthogonalize(Field& w, std::vector<Field>& evec, int k)
{
typedef typename Field::scalar_type MyComplex;
MyComplex ip;
for(int j=0; j<k; ++j){
ip = innerProduct(evec[j],w);
w = w - ip * evec[j];
}
normalise(w);
}
/* Rudy Arthur's thesis pp.137
------------------------
Require: M > K P = M − K †
@ -167,9 +193,10 @@ until convergence
std::vector<RealD> lme(Nm);
std::vector<RealD> lme2(Nm);
std::vector<RealD> eval2(Nm);
Eigen::MatrixXd Qt = Eigen::MatrixXd::Zero(Nm,Nm);
std::vector<int> Iconv(Nm);
Eigen::MatrixXd Qt = Eigen::MatrixXd::Zero(Nm,Nm);
std::vector<int> Iconv(Nm);
std::vector<Field> B(Nm,grid); // waste of space replicating
Field f(grid);
@ -218,6 +245,7 @@ until convergence
// Implicitly shifted QR transformations
Qt = Eigen::MatrixXd::Identity(Nm,Nm);
for(int ip=k2; ip<Nm; ++ip){
// Eigen replacement for qr_decomp ???
qr_decomp(eval,lme,Nm,Nm,Qt,eval2[ip],k1,Nm);
}
@ -354,10 +382,32 @@ private:
if ( beta < tiny ) std::cout << GridLogMessage << " beta is tiny "<<beta<<std::endl;
}
///////////////////////////////////////////////////////////////////
//
//
///////////////////////////////////////////////////////////////////
void diagonalize_Eigen(std::vector<RealD>& lmd, std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd & Qt, // Nm x Nm
GridBase *grid)
{
Eigen::MatrixXd TriDiag = Eigen::MatrixXd::Zero(Nk,Nk);
for(int i=0;i<Nk;i++) TriDiag(i,i) = lmd[i];
for(int i=0;i<Nk-1;i++) TriDiag(i,i+1) = lme[i];
for(int i=0;i<Nk-1;i++) TriDiag(i+1,i) = lme[i];
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXd> eigensolver(TriDiag);
for (int i = 0; i < Nk; i++) {
lmd[Nk-1-i] = eigensolver.eigenvalues()(i);
}
for (int i = 0; i < Nk; i++) {
for (int j = 0; j < Nk; j++) {
Qt(Nk-1-i,j) = eigensolver.eigenvectors()(j,i);
}
}
}
///////////////////////////////////////////////////////////////////////////
// File could end here if settle on Eigen ???
///////////////////////////////////////////////////////////////////////////
void qr_decomp(std::vector<RealD>& lmd, // Nm
std::vector<RealD>& lme, // Nm
int Nk, int Nm, // Nk, Nm
@ -570,50 +620,6 @@ void diagonalize_lapack(std::vector<RealD>& lmd,
abort();
}
void diagonalize_Eigen(std::vector<RealD>& lmd, std::vector<RealD>& lme,
int Nk, int Nm,
Eigen::MatrixXd & Qt, // Nm x Nm
GridBase *grid)
{
Eigen::MatrixXd TriDiag = Eigen::MatrixXd::Zero(Nk,Nk);
for(int i=0;i<Nk;i++) TriDiag(i,i) = lmd[i];
for(int i=0;i<Nk-1;i++) TriDiag(i,i+1) = lme[i];
for(int i=0;i<Nk-1;i++) TriDiag(i+1,i) = lme[i];
Eigen::SelfAdjointEigenSolver<Eigen::MatrixXd> eigensolver(TriDiag);
for (int i = 0; i < Nk; i++) {
lmd[Nk-1-i] = eigensolver.eigenvalues()(i);
}
for (int i = 0; i < Nk; i++) {
for (int j = 0; j < Nk; j++) {
Qt(Nk-1-i,j) = eigensolver.eigenvectors()(j,i);
}
}
}
static RealD normalise(Field& v)
{
RealD nn = norm2(v);
nn = sqrt(nn);
v = v * (1.0/nn);
return nn;
}
void orthogonalize(Field& w, std::vector<Field>& evec, int k)
{
typedef typename Field::scalar_type MyComplex;
MyComplex ip;
for(int j=0; j<k; ++j){
ip = innerProduct(evec[j],w); // are the evecs normalised? ; this assumes so.
w = w - ip * evec[j];
}
normalise(w);
}
};
}
#endif

4
tests/debug/Test_synthetic_lanczos.cc
View File

@ -133,8 +133,8 @@ int main (int argc, char ** argv)
int Nconv;
RealD eresid = 1.0e-6;
ImplicitlyRestartedLanczos<LatticeComplex> IRL(HermOp,X,Nk,Nm,eresid,Nit);
ImplicitlyRestartedLanczos<LatticeComplex> ChebyIRL(HermOp,Cheby,Nk,Nm,eresid,Nit);
ImplicitlyRestartedLanczos<LatticeComplex> IRL(HermOp,X,Nk,Nk,Nm,eresid,Nit);
ImplicitlyRestartedLanczos<LatticeComplex> ChebyIRL(HermOp,Cheby,Nk,Nk,Nm,eresid,Nit);
LatticeComplex src(grid); gaussian(RNG,src);
{