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This commit is contained in:
jiri 2011-01-18 14:37:05 +00:00
parent 600b5b3abd
commit 4534c2e56a
21 changed files with 753 additions and 138 deletions
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5
csrmat.cc
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@ -30,6 +30,9 @@ namespace LA {
/*
Commented out by Roman for ICC
#define INSTANTIZE(T) \
template void CSRMat<T>::gemm(const T beta, const CSRMat &a, const char transa, const CSRMat &b, const char transb, const T alpha); \
template CSRMat<T> & CSRMat<T>::operator*=(const T &a); \
@ -45,8 +48,8 @@ template void CSRMat<T>::put(int fd, bool dimen, bool transp) const; \
INSTANTIZE(double)
INSTANTIZE(complex<double>)
*/
//// forced instantization of functions in the header in the corresponding object file
template class CSRMat<double>;

8
csrmat.h
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@ -71,6 +71,7 @@ public:
CSRMat & operator=(const CSRMat &rhs);
void copyonwrite();
void resize(const SPMatindex nn, const SPMatindex mm);
void dealloc(void) {resize(0,0);}
void moveto(GPUID destination);
void clear();
~CSRMat();
@ -128,5 +129,12 @@ public:
*/
};
template <typename T>
std::ostream & operator<<(std::ostream &s, const CSRMat<T> &x);
template <class T>
std::istream& operator>>(std::istream &s, CSRMat<T> &x);
}//namespace
#endif //_CSRMAT_H_

17
davidson.h
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@ -33,26 +33,21 @@ namespace LA {
//therefore the whole implementation must be a template in a header
//Note that for efficiency in a direct CI case the diagonalof() should cache its result
template <typename T, typename Matrix>
extern void davidson(const Matrix &bigmat, NRVec<T> &eivals, NRVec<T> *eivecs, const char *eivecsfile,
int nroots=1, const bool verbose=0, const double eps=1e-6,
const bool incore=1, int maxit=100, const int maxkrylov = 500,
void (*initguess)(NRVec<T> &)=NULL);
//@@@options: left eigenvectors by matrix transpose, overridesymmetric (for nrmat)
//@@@small matrix gdiagonalize - shift complex roots up (option to gdiagonalize?)
//@@@test gdiagonalize whether it sorts the roots and what for complex ones
//@@@implement left eigenvectors for nonsymmetric case
//Davidson algorithm: J. Comp. Phys. 17:817 (1975)
//@@@implement left eigenvectors for nonsymmetric case
template <typename T, typename Matrix>
void davidson(const Matrix &bigmat, NRVec<T> &eivals, NRVec<T> *eivecs, const char *eivecsfile,
int nroots, const bool verbose, const double eps,
const bool incore, int maxit, const int maxkrylov,
void (*initguess)(NRVec<T> &))
extern void davidson(const Matrix &bigmat, NRVec<T> &eivals, NRVec<T> *eivecs, const char *eivecsfile,
int nroots=1, const bool verbose=0, const double eps=1e-6,
const bool incore=1, int maxit=100, const int maxkrylov = 500,
void (*initguess)(NRVec<T> &)=NULL)
{
bool flag=0;
int n=bigmat.nrows();
@ -87,7 +82,7 @@ smallH=0;
//default guess based on lowest diagonal element of the matrix
if(initguess) (*initguess)(vec1);
if(initguess) initguess(vec1);
else
{
const T *diagonal = bigmat.diagonalof(vec2,false,true);

1
fourindex.h
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@ -226,6 +226,7 @@ public:
inline matel4<I,T> *getlist() const {return list;}
inline I size() const {return nn;}
void resize(const I n);
void dealloc(void) {resize(0);}
void copyonwrite();
unsigned long length() const;
inline void add(const I i, const I j, const I k, const I l, const T elem)

1
la.h
View File

@ -42,6 +42,7 @@
#include "smat.h"
#include "sparsemat.h"
#include "sparsesmat.h"
#include "csrmat.h"
#include "vec.h"
using namespace LA;

53
la_traits.h
View File

@ -220,8 +220,30 @@ static inline normtype norm (const complex<C> &x) {return std::abs(x);}
static inline void axpy (complex<C> &s, const complex<C> &x, const complex<C> &c) {s+=x*c;}
static inline void get(int fd, complex<C> &x, bool dimensions=0, bool transp=0) {if(sizeof(complex<C>)!=read(fd,&x,sizeof(complex<C>))) laerror("read error");}
static inline void put(int fd, const complex<C> &x, bool dimensions=0, bool transp=0) {if(sizeof(complex<C>)!=write(fd,&x,sizeof(complex<C>))) laerror("write error");}
static void multiget(size_t n,int fd, complex<C> *x, bool dimensions=0){ssize_t r=read(fd,x,n*sizeof(complex<C>)); if((ssize_t)(n*sizeof(complex<C>))!=r) {std::cout<<"read returned "<<r<<std::endl; laerror("read error");}}
static void multiput(size_t n, int fd, const complex<C> *x, bool dimensions=0) {ssize_t r=write(fd,x,n*sizeof(complex<C>)); if((ssize_t)(n*sizeof(complex<C>))!=r) {std::cout<<"write returned "<<r<<std::endl; laerror("write error");}}
static void multiget(size_t n,int fd, complex<C> *x, bool dimensions=0)
{
size_t total=0;
ssize_t r;
do{
r=read(fd,x+total,(n-total)*sizeof(complex<C>));
if(r<0 || r==0 && n!=0 ) {std::cout<<"read returned "<<r<<std::endl; laerror("read error");}
else total += r/sizeof(complex<C>);
if(r%sizeof(complex<C>)) laerror("read error 2");
}
while(total < n);
}
static void multiput(size_t n, int fd, const complex<C> *x, bool dimensions=0)
{
size_t total=0;
ssize_t r;
do{
r=write(fd,x+total,(n-total)*sizeof(complex<C>));
if(r<0 || r==0 && n!=0 ) {std::cout<<"write returned "<<r<<std::endl; laerror("write error");}
else total += r/sizeof(complex<C>);
if(r%sizeof(complex<C>)) laerror("write error 2");
}
while(total < n);
}
static void copy(complex<C> *dest, complex<C> *src, unsigned int n) {memcpy(dest,src,n*sizeof(complex<C>));}
static void clear(complex<C> *dest, unsigned int n) {memset(dest,0,n*sizeof(complex<C>));}
static void copyonwrite(complex<C> &x) {};
@ -232,6 +254,7 @@ static inline C realpart(const complex<C> &x) {return x.real();}
static inline C imagpart(const complex<C> &x) {return x.imag();}
};
//non-complex scalars
template<typename C>
struct LA_traits_aux<C, scalar_true> {
@ -248,8 +271,30 @@ static inline normtype norm (const C &x) {return std::abs(x);}
static inline void axpy (C &s, const C &x, const C &c) {s+=x*c;}
static inline void put(int fd, const C &x, bool dimensions=0, bool transp=0) {if(sizeof(C)!=write(fd,&x,sizeof(C))) laerror("write error");}
static inline void get(int fd, C &x, bool dimensions=0, bool transp=0) {if(sizeof(C)!=read(fd,&x,sizeof(C))) laerror("read error");}
static void multiget(size_t n,int fd, C *x, bool dimensions=0){ssize_t r=read(fd,x,n*sizeof(C)); if((ssize_t)(n*sizeof(C))!=r) {std::cout<<"read returned "<<r<<std::endl; laerror("read error");}}
static void multiput(size_t n, int fd, const C *x, bool dimensions=0) {ssize_t r=write(fd,x,n*sizeof(C)); if((ssize_t)(n*sizeof(C))!=r) {std::cout<<"write returned "<<r<<std::endl; laerror("write error");}}
static void multiget(size_t n,int fd, C *x, bool dimensions=0)
{
size_t total=0;
ssize_t r;
do{
r=read(fd,x+total,(n-total)*sizeof(C));
if(r<0 || r==0 && n!=0 ) {std::cout<<"read returned "<<r<<std::endl; laerror("read error");}
else total += r/sizeof(C);
if(r%sizeof(C)) laerror("read error 2");
}
while(total < n);
}
static void multiput(size_t n, int fd, const C *x, bool dimensions=0)
{
size_t total=0;
ssize_t r;
do{
r=write(fd,x+total,(n-total)*sizeof(C));
if(r<0 || r==0 && n!=0 ) {std::cout<<"write returned "<<r<<std::endl; laerror("write error");}
else total += r/sizeof(C);
if(r%sizeof(C)) laerror("write error 2");
}
while(total < n);
}
static void copy(C *dest, C *src, unsigned int n) {memcpy(dest,src,n*sizeof(C));}
static void clear(C *dest, unsigned int n) {memset(dest,0,n*sizeof(C));}
static void copyonwrite(C &x) {};

4
laerror.h
View File

@ -30,9 +30,9 @@ class LAerror
};
#ifdef __GNUG__
#define laerror(X) { LA::laerror2(X, __PRETTY_FUNCTION__); }
#define laerror(X) LA::laerror2(X, __PRETTY_FUNCTION__)
#else
#define laerror(X) { LA::laerror2(X, __func__); }
#define laerror(X) LA::laerror2(X, __func__)
#endif
extern void laerror2(const char *, const char *);

49
mat.cc
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@ -150,7 +150,7 @@ void NRMat<T>::put(int fd, bool dim, bool transp) const {
}
}
}else{
LA_traits<T>::multiput(nn*mm,fd,
LA_traits<T>::multiput((size_t)nn*(size_t)mm,fd,
#ifdef MATPTR
v[0]
#else
@ -202,7 +202,7 @@ void NRMat<T>::get(int fd, bool dim, bool transp){
}
}
}else{
LA_traits<T>::multiget(nn*mm,fd,
LA_traits<T>::multiget((size_t)nn*(size_t)mm,fd,
#ifdef MATPTR
v[0]
#else
@ -838,8 +838,9 @@ NRMat<T>& NRMat<T>::transposeme(const int _n) {
return *this;
}
/***************************************************************************//**
* icreate complex double-precision matrix from real double-precision matrix \f$A\f$
* create complex double-precision matrix from real double-precision matrix \f$A\f$
* @param[in] rhs real double-precision matrix \f$A\f$
* @param[in] imagpart flag indicating whether the matrix \f$A\f$ should be considered as a real
* or imaginary part of the complex matrix being created
@ -877,6 +878,43 @@ NRMat<complex<double> >::NRMat(const NRMat<double> &rhs, bool imagpart): nn(rhs.
#endif
}
/***************************************************************************//**
* create double-precision matrix from complex double-precision matrix \f$A\f$
* @param[in] rhs complex double-precision matrix \f$A\f$
* @param[in] imagpart flag indicating whether the matrix \f$A\f$ should be taken as the real
* or imaginary part of the input complex matrix
******************************************************************************/
template<>
NRMat<double>::NRMat(const NRMat<complex<double> > &rhs, bool imagpart): nn(rhs.nrows()), mm(rhs.ncols()), count(new int(1)) {
const int nn_mm = nn*mm;
#ifdef CUDALA
if(location == cpu){
#endif
#ifdef MATPTR
v = new double*[n];
v[0] = new double[nn_mm];
for(register int i=1; i<n; i++) v[i] = v[i-1] + m;
cblas_dcopy(nn_mm, ((double *)&rhs[0][0]) + (imagpart?1:0), 2, v[0], 1);
#else
v = new double[nn_mm];
cblas_dcopy(nn_mm, ((double *) &rhs[0][0]) + (imagpart?1:0), 2, v , 1);
#endif
#ifdef CUDALA
}else{
v = (double *)gpualloc(sizeof(double)*nn_mm);
cublasDcopy(nn_mm, ((double*)&rhs[0][0])+ (imagpart?1:0), 2, v , 1);
TEST_CUBLAS("cublasDcopy");
}
#endif
}
/***************************************************************************//**
* output of a matrix of general type via lawritemat
******************************************************************************/
@ -1156,8 +1194,9 @@ void NRMat<complex<double> >::randomize(const double &x) {
#endif
for(register int i=0; i<nn; ++i){
for(register int j=0; j<mm; ++j){
(*this)(i,j).real() = x*(2.*random()/(1. + RAND_MAX) - 1.);
(*this)(i,j).imag() = x*(2.*random()/(1. + RAND_MAX) - 1.);
const double re = x*(2.*random()/(1. + RAND_MAX) - 1.);
const double im = x*(2.*random()/(1. + RAND_MAX) - 1.);
(*this)(i,j) = complex<double>(re, im);
}
}
#ifdef CUDALA

8
mat.h
View File

@ -80,6 +80,8 @@ public:
//! complexifying constructor
NRMat(const typename LA_traits_complex<T>::NRMat_Noncomplex_type &rhs, bool imagpart = false);
//! explicit decomplexifying constructor
explicit NRMat(const NRMat<complex<T> > &rhs, bool imagpart = false);
//! explicit constructor converting symmetric matrix stored in packed form into a <code>NRMat<T></code> object
explicit NRMat(const NRSMat<T> &rhs);
@ -280,6 +282,9 @@ public:
//! resize the matrix
void resize(int n, int m);
//! deallocate the matrix
void dealloc(void) {resize(0,0);}
//! get the pointer to the data
inline operator T*();
//! get the const pointer to the data
@ -332,6 +337,8 @@ public:
explicit NRMat(const SparseMat<T> &rhs); // dense from sparse
//! explicit constructor converting sparse symmetric matrix into \c NRMat<T> object
explicit NRMat(const SparseSMat<T> &rhs);
//! explicit constructor converting sparse CSR matrix into \c NRMat<T> object
explicit NRMat(const CSRMat<T> &rhs);
//! add up given sparse matrix
NRMat & operator+=(const SparseMat<T> &rhs);
@ -618,7 +625,6 @@ inline T* NRMat<T>::operator[](const int i) {
if (i < 0 || i >= nn) laerror("Mat [] out of range");
if (!v) laerror("unallocated matrix");
#endif
NOT_GPU(*this);
#ifdef MATPTR
return v[i];
#else

8
matexp.h
View File

@ -42,8 +42,8 @@ else
for(i=order-1; i>=0; i--)
{
//std::cerr<<"TEST polynom0 "<<i<<'\n';
if(i<order-1) z=y*x;
y=z+c[i];
if(i<order-1) {LA_traits<T>::deallocate(z); z=y*x;} //for large matrices avoid storing 4 ones simultaneously
LA_traits<T>::deallocate(y); y=z+c[i];
}
}
@ -346,9 +346,11 @@ int power;
NRVec<typename LA_traits<V>::normtype> taylor2=exp_aux<M,typename LA_traits<V>::normtype>(mat,power,maxpower,maxtaylor,scale);
V tmp;
bool washere=0;
for(int i=1; i<=(1<<power); ++i) //unfortunatelly, here we have to repeat it many times, unlike if the matrix is stored explicitly
{
washere=1;
if(i>1) rhs=result; //apply again to the result of previous application
else result=rhs;
tmp=rhs; //now rhs can be used as scratch
@ -361,6 +363,8 @@ for(int i=1; i<=(1<<power); ++i) //unfortunatelly, here we have to repeat it man
}
}
if(!washere) laerror("integer overflow due to unrealistically big power - use maxpower argument in exptimes()");
return;
}

364
nonclass.cc
View File

@ -240,6 +240,41 @@ linear_solve_do(a,&B[0],1,a.nrows(),det,n);
}
// Roman, complex version of linear_solve()
extern "C" void FORNAME(zgesv)(const int *N, const int *NRHS, double *A, const int *LDA,
int *IPIV, double *B, const int *LDB, int *INFO);
void linear_solve(NRMat< complex<double> > &A, NRMat< complex<double> > *B, complex<double> *det, int n)
{
int r, *ipiv;
if (A.nrows() != A.ncols()) laerror("linear_solve() call for non-square matrix");
if (B && A.nrows() != B->ncols()) laerror("incompatible matrices in linear_solve()");
A.copyonwrite();
if (B) B->copyonwrite();
ipiv = new int[A.nrows()];
n = A.nrows();
int nrhs = B ? B->nrows() : 0;
int lda = A.ncols();
int ldb = B ? B->ncols() : A.nrows();
FORNAME(zgesv)(&n, &nrhs, (double *)A[0], &lda, ipiv,
B ? (double *)(*B)[0] : (double *)0, &ldb, &r);
if (r < 0) {
delete[] ipiv;
laerror("illegal argument in lapack_gesv");
}
if (det && r>=0) {
*det = A[0][0];
for (int i=1; i<A.nrows(); ++i) *det *= A[i][i];
//change sign of det by parity of ipiv permutation
for (int i=0; i<A.nrows(); ++i) *det = -(*det);
}
delete [] ipiv;
if (r>0 && B) laerror("singular matrix in zgesv");
}
//other version of linear solver based on gesvx
//------------------------------------------------------------------------------
@ -793,6 +828,18 @@ extern "C" void FORNAME(dggev)(const char *JOBVL, const char *JOBVR, const FINT
double *VL, const FINT *LDVL, double *VR, const FINT *LDVR,
double *WORK, const FINT *LWORK, FINT *INFO );
extern "C" void FORNAME(zgeev)(const char *JOBVL, const char *JOBVR, const FINT *N,
complex<double> *A, const FINT *LDA, complex<double> *W, complex<double> *VL, const FINT *LDVL,
complex<double> *VR, const FINT *LDVR, complex<double> *WORK, const FINT *LWORK,
double *RWORK, FINT *INFO );
extern "C" void FORNAME(zggev)(const char *JOBVL, const char *JOBVR, const FINT *N,
complex<double> *A, const FINT *LDA, complex<double> *B, const FINT *LDB, complex<double> *W, complex<double> *WBETA,
complex<double> *VL, const FINT *LDVL, complex<double> *VR, const FINT *LDVR,
complex<double> *WORK, const FINT *LWORK, double *RWORK, FINT *INFO );
//statics for sorting
static int *gdperm;
@ -904,11 +951,12 @@ void gdiagonalize(NRMat<double> &a, NRVec<double> &wr, NRVec<double> &wi,
#endif
delete[] work;
//std::cout <<"TEST dgeev\n"<<wr<<wi<<*vr<<*vl<<std::endl;
if (r < 0) laerror("illegal argument in ggev/geev in gdiagonalize()");
if (r > 0) laerror("convergence problem in ggev/geev in gdiagonalize()");
//std::cout <<"TEST dgeev\n"<<wr<<wi<<*vr<<*vl<<std::endl;
if(biorthonormalize && vl && vr)
{
if(b || beta) laerror("@@@ biorthonormalize not implemented yet for generalized non-symmetric eigenproblem");//metric b would be needed
@ -968,6 +1016,7 @@ void gdiagonalize(NRMat<double> &a, NRVec<double> &wr, NRVec<double> &wi,
}
}
if(sorttype>0)
{
NRVec<int> perm(n);
@ -997,12 +1046,119 @@ void gdiagonalize(NRMat<double> &a, NRVec<double> &wr, NRVec<double> &wi,
}
//most general complex routine
template<>
void gdiagonalize(NRMat<complex<double> > &a, NRVec< complex<double> > &w,
NRMat< complex<double> >*vl, NRMat< complex<double> > *vr,
const bool corder, int n, const int sorttype, const int biorthonormalize,
NRMat<complex<double> > *b, NRVec<complex<double> > *beta)
{
if(n<=0) n = a.nrows();
if (n > a.ncols() || n>a.nrows() ) laerror("gdiagonalize() call for a non-square matrix");
if (n > w.size())
laerror("inconsistent dimension of eigen vector in gdiagonalize()");
if (vl) if (n > vl->nrows() || n > vl->ncols())
laerror("inconsistent dimension of vl in gdiagonalize()");
if (vr) if (n > vr->nrows() || n > vr->ncols())
laerror("inconsistent dimension of vr in gdiagonalize()");
if (beta) if(n > beta ->size()) laerror("inconsistent dimension of beta in gdiagonalize()");
if(b) if(n > b->nrows() || n > b->ncols())
laerror("inconsistent dimension of b in gdiagonalize()");
if(b && !beta || beta && !b) laerror("missing array for generalized diagonalization");
a.copyonwrite();
w.copyonwrite();
if (vl) vl->copyonwrite();
if (vr) vr->copyonwrite();
if (beta) beta->copyonwrite();
if (b) b->copyonwrite();
char jobvl = vl ? 'V' : 'N';
char jobvr = vr ? 'V' : 'N';
complex<double> work0;
FINT lwork = -1;
FINT r;
FINT lda=a.ncols();
FINT ldb=0;
if(b) ldb=b->ncols();
FINT ldvl= vl?vl->ncols():lda;
FINT ldvr= vr?vr->ncols():lda;
double *rwork = new double[n*(b?8:2)];
#ifdef FORINT
FINT ntmp = n;
if(b) FORNAME(zggev)(&jobvr, &jobvl, &ntmp, a, &lda, *b, &ldb, w, *beta, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, &work0, &lwork, rwork, &r);
else FORNAME(zgeev)(&jobvr, &jobvl, &ntmp, a, &lda, w, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, &work0, &lwork, rwork, &r);
#else
if(b) FORNAME(zggev)(&jobvr, &jobvl, &n, a, &lda, *b, &ldb, w, *beta, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, &work0, &lwork, rwork, &r);
else FORNAME(zgeev)(&jobvr, &jobvl, &n, a, &lda, w, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, &work0, &lwork, rwork, &r);
#endif
lwork = (FINT) work0.real();
complex<double> *work = new complex<double>[lwork];
#ifdef FORINT
if(b) FORNAME(zggev)(&jobvr, &jobvl, &ntmp, a, &lda, *b, &ldb, w, *beta, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, work, &lwork, rwork, &r);
else FORNAME(zgeev)(&jobvr, &jobvl, &ntmp, a, &lda, w, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, work, &lwork, rwork, &r);
#else
if(b) FORNAME(zggev)(&jobvr, &jobvl, &n, a, &lda, *b, &ldb, w, *beta, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, work, &lwork, rwork, &r);
else FORNAME(zgeev)(&jobvr, &jobvl, &n, a, &lda, w, vr?vr[0]:(complex<double> *)0,
&ldvr, vl?vl[0]:(complex<double> *)0, &ldvl, work, &lwork, rwork, &r);
#endif
delete[] work;
delete[] rwork;
//std::cout <<"TEST zg(g|e)ev\n"<<w<<*vr<<*vl<<std::endl;
if (r < 0) laerror("illegal argument in ggev/geev in gdiagonalize()");
if (r > 0) laerror("convergence problem in ggev/geev in gdiagonalize()");
if(biorthonormalize && vl && vr)
{
if(b || beta) laerror("@@@ biorthonormalize not implemented yet for generalized non-hermitian eigenproblem");//metric b would be needed
for(int i=0; i<n; ++i)
{
//calculate scaling paramter
complex<double> tmp;
cblas_zdotc_sub(n,(*vr)[i],1,(*vl)[i], 1, &tmp);
tmp = 1./tmp;
std::cout <<"scaling by "<<tmp<<"\n";
if(biorthonormalize==1) cblas_zscal(n,&tmp,(*vl)[i],1);
if(biorthonormalize==2) cblas_zscal(n,&tmp,(*vr)[i],1);
}
}
if(sorttype>0)
{
laerror("sorting not implemented in complex gdiagonalize");
}
if (corder) {
if (vl) vl->transposeme(n);
if (vr) vr->transposeme(n);
}
}
template<>
void gdiagonalize(NRMat<double> &a, NRVec< complex<double> > &w,
NRMat< complex<double> >*vl, NRMat< complex<double> > *vr,
const bool corder, int n, const int sorttype, const int biorthonormalize,
NRMat<double> *b, NRVec<double> *beta)
{
if(!corder) laerror("gdiagonalize() corder 0 not implemented");
if(n<=0) n = a.nrows();
if(n> a.nrows() || n == a.nrows() && n != a.ncols()) laerror("gdiagonalize() call for a non-square matrix");
@ -1020,19 +1176,43 @@ void gdiagonalize(NRMat<double> &a, NRVec< complex<double> > &w,
i = 0;
while (i < n) {
if (wi[i] == 0) {
if(corder)
{
if (vl) for (int j=0; j<n; j++) (*vl)[j][i] = (*rvl)[i][j];
if (vr) for (int j=0; j<n; j++) (*vr)[j][i] = (*rvr)[i][j];
}
else
{
if (vl) for (int j=0; j<n; j++) (*vl)[i][j] = (*rvl)[i][j];
if (vr) for (int j=0; j<n; j++) (*vr)[i][j] = (*rvr)[i][j];
}
i++;
} else {
if (vl)
for (int j=0; j<n; j++) {
if(corder)
{
(*vl)[j][i] = complex<double>((*rvl)[i][j], (*rvl)[i+1][j]);
(*vl)[j][i+1] = complex<double>((*rvl)[i][j], -(*rvl)[i+1][j]);
}
else
{
(*vl)[i][j] = complex<double>((*rvl)[i][j], (*rvl)[i+1][j]);
(*vl)[i+1][j] = complex<double>((*rvl)[i][j], -(*rvl)[i+1][j]);
}
}
if (vr)
for (int j=0; j<n; j++) {
if(corder)
{
(*vr)[j][i] = complex<double>((*rvr)[i][j], (*rvr)[i+1][j]);
(*vr)[j][i+1] = complex<double>((*rvr)[i][j], -(*rvr)[i+1][j]);
}
else
{
(*vr)[i][j] = complex<double>((*rvr)[i][j], (*rvr)[i+1][j]);
(*vr)[i+1][j] = complex<double>((*rvr)[i][j], -(*rvr)[i+1][j]);
}
}
i += 2;
}
@ -1043,35 +1223,78 @@ void gdiagonalize(NRMat<double> &a, NRVec< complex<double> > &w,
}
const NRMat<double> realpart(const NRMat< complex<double> > &a)
template<>
const NRMat<double> realpart<NRMat< complex<double> > >(const NRMat< complex<double> > &a)
{
#ifdef CUDALA
if(location == cpu){
#endif
NRMat<double> result(a.nrows(), a.ncols());
cblas_dcopy(a.nrows()*a.ncols(), (const double *)a[0], 2, result, 1);
#ifdef CUDALA
}else{
laerror("not implemented for cuda yet");
}
#endif
return result;
}
const NRMat<double> imagpart(const NRMat< complex<double> > &a)
template<>
const NRMat<double> imagpart<NRMat< complex<double> > >(const NRMat< complex<double> > &a)
{
#ifdef CUDALA
if(location == cpu){
#endif
NRMat<double> result(a.nrows(), a.ncols());
cblas_dcopy(a.nrows()*a.ncols(), (const double *)a[0]+1, 2, result, 1);
#ifdef CUDALA
}else{
laerror("not implemented for cuda yet");
}
#endif
return result;
}
const NRMat< complex<double> > realmatrix (const NRMat<double> &a)
template<>
const NRMat< complex<double> > realmatrix<NRMat<double> > (const NRMat<double> &a)
{
#ifdef CUDALA
if(location == cpu){
#endif
NRMat <complex<double> > result(a.nrows(), a.ncols());
cblas_dcopy(a.nrows()*a.ncols(), a, 1, (double *)result[0], 2);
#ifdef CUDALA
}else{
laerror("not implemented for cuda yet");
}
#endif
return result;
}
const NRMat< complex<double> > imagmatrix (const NRMat<double> &a)
template<>
const NRMat< complex<double> > imagmatrix<NRMat<double> > (const NRMat<double> &a)
{
#ifdef CUDALA
if(location == cpu){
#endif
NRMat< complex<double> > result(a.nrows(), a.ncols());
cblas_dcopy(a.nrows()*a.ncols(), a, 1, (double *)result[0]+1, 2);
#ifdef CUDALA
}else{
laerror("not implemented for cuda yet");
}
#endif
return result;
}
const NRMat< complex<double> > complexmatrix (const NRMat<double> &re, const NRMat<double> &im)
template<>
const NRMat< complex<double> > complexmatrix<NRMat<double> > (const NRMat<double> &re, const NRMat<double> &im)
{
if(re.nrows()!=im.nrows() || re.ncols() != im.ncols()) laerror("incompatible sizes of real and imaginary parts");
NRMat< complex<double> > result(re.nrows(), re.ncols());
@ -1080,57 +1303,60 @@ const NRMat< complex<double> > complexmatrix (const NRMat<double> &re, const NRM
return result;
}
template<>
const SparseSMat< complex<double> > complexmatrix<SparseSMat<double> >(const SparseSMat<double> &re, const SparseSMat<double> &im) {
if(re.nrows()!=im.nrows() || re.ncols() != im.ncols()) laerror("incompatible sizes of real and imaginary parts");
SparseSMat< complex<double> > result(re.nrows(),re.ncols());
complex<double> tmp;
SparseSMat<double>::iterator pre(re);
for(; pre.notend(); ++pre) {
tmp = pre->elem;
result.add(pre->row,pre->col,tmp,false);
}
NRMat<double> matrixfunction(NRMat<double> a, complex<double>
(*f)(const complex<double> &), const bool adjust)
{
int n = a.nrows();
NRMat< complex<double> > u(n, n), v(n, n);
NRVec< complex<double> > w(n);
/*
NRMat<complex<double> > a0=complexify(a);
*/
gdiagonalize(a, w, &u, &v);//a gets destroyed, eigenvectors are rows
NRVec< complex<double> > z = diagofproduct(u, v, 1, 1);
/*
std::cout <<"TEST matrixfunction\n"<<w<<u<<v<<z;
std::cout <<"TEST matrixfunction1 "<< u*a0 - diagonalmatrix(w)*u<<std::endl;
std::cout <<"TEST matrixfunction2 "<< a0*v.transpose(1) - v.transpose(1)*diagonalmatrix(w)<<std::endl;
std::cout <<"TEST matrixfunction3 "<< u*v.transpose(1)<<diagonalmatrix(z)<<std::endl;
NRVec< complex<double> > wz(n);
for (int i=0; i<a.nrows(); i++) wz[i] = w[i]/z[i];
std::cout <<"TEST matrixfunction4 "<< a0<< v.transpose(true)*diagonalmatrix(wz)*u<<std::endl;
*/
SparseSMat<double>::iterator pim(im);
for(; pim.notend(); ++pim) {
tmp = complex<double>(0,1)*(pim->elem);
result.add(pim->row,pim->col,tmp,false);
}
for (int i=0; i<a.nrows(); i++) w[i] = (*f)(w[i])/z[i];
u.diagmultl(w);
NRMat< complex<double> > r(n, n);
r.gemm(0.0, v, 'c', u, 'n', 1.0);
double inorm = cblas_dnrm2(n*n, (double *)r[0]+1, 2);
if (inorm > 1e-10) {
std::cout << "norm = " << inorm << std::endl;
laerror("nonzero norm of imaginary part of real matrixfunction");
}
return realpart(r);
return result;
}
NRMat<double> matrixfunction(NRSMat<double> a, double (*f) (double))
{
int n = a.nrows();
NRVec<double> w(n);
NRMat<double> v(n, n);
diagonalize(a, w, &v, 0);
template<>
const SparseSMat< complex<double> > realmatrix<SparseSMat<double> >(const SparseSMat<double> &re) {
SparseSMat< complex<double> > result(re.nrows(),re.ncols());
complex<double> tmp;
for (int i=0; i<a.nrows(); i++) w[i] = (*f)(w[i]);
NRMat<double> u = v;
v.diagmultl(w);
NRMat<double> r(n, n);
r.gemm(0.0, u, 't', v, 'n', 1.0);
return r;
SparseSMat<double>::iterator pre(re);
for(; pre.notend(); ++pre) {
tmp = pre->elem;
result.add(pre->row,pre->col,tmp,false);
}
return result;
}
template<>
const SparseSMat< complex<double> > imagmatrix<SparseSMat<double> >(const SparseSMat<double> &im) {
SparseSMat< complex<double> > result(im.nrows(),im.ncols());
complex<double> tmp;
SparseSMat<double>::iterator pim(im);
for(; pim.notend(); ++pim) {
tmp = complex<double>(0,1)*(pim->elem);
result.add(pim->row,pim->col,tmp,false);
}
return result;
}
NRMat<double> realmatrixfunction(NRMat<double> a, double (*f) (const double))
{
int n = a.nrows();
@ -1145,6 +1371,7 @@ NRMat<double> realmatrixfunction(NRMat<double> a, double (*f) (const double))
return r;
}
NRMat<complex<double> > complexmatrixfunction(NRMat<double> a, double (*fre) (const double), double (*fim) (const double))
{
int n = a.nrows();
@ -1169,6 +1396,16 @@ NRMat<complex<double> > complexmatrixfunction(NRMat<double> a, double (*fre) (co
// instantize template to an addresable function
complex<double> myccopy (const complex<double> &x)
{
return x;
}
double mycopy (const double x)
{
return x;
}
complex<double> myclog (const complex<double> &x)
{
return log(x);
@ -1193,14 +1430,37 @@ double sqrtinv (const double x)
NRMat<double> log(const NRMat<double> &a)
{
return matrixfunction(a, &myclog, 1);
return matrixfunction(a, &myclog);
}
NRMat<complex<double> > log(const NRMat<complex<double> > &a)
{
return matrixfunction(a, &myclog);
}
NRMat<double> exp0(const NRMat<double> &a)
{
return matrixfunction(a, &mycexp, 1);
return matrixfunction(a, &mycexp);
}
NRMat<complex<double> > exp0(const NRMat<complex<double> > &a)
{
return matrixfunction(a, &mycexp);
}
NRMat<complex<double> > copytest(const NRMat<complex<double> > &a)
{
return matrixfunction(a, &myccopy);
}
NRMat<double> copytest(const NRMat<double> &a)
{
return matrixfunction(a, &myccopy);
}
const NRVec<double> diagofproduct(const NRMat<double> &a, const NRMat<double> &b,

125
nonclass.h
View File

@ -88,8 +88,8 @@ extern const NRVec<T> diagofproduct(const NRMat<T> &a, const NRMat<T> &b,\
extern T trace2(const NRMat<T> &a, const NRMat<T> &b, bool trb=0); \
extern T trace2(const NRSMat<T> &a, const NRSMat<T> &b, const bool diagscaled=0);\
extern T trace2(const NRSMat<T> &a, const NRMat<T> &b, const bool diagscaled=0);\
extern void linear_solve(NRMat<T> &a, NRMat<T> *b, double *det=0,int n=0); /*solve Ax^T=b^T (b is nrhs x n) */ \
extern void linear_solve(NRSMat<T> &a, NRMat<T> *b, double *det=0, int n=0); /*solve Ax^T=b^T (b is nrhs x n) */\
extern void linear_solve(NRMat<T> &a, NRMat<T> *b, T *det=0,int n=0); /*solve Ax^T=b^T (b is nrhs x n) */ \
extern void linear_solve(NRSMat<T> &a, NRMat<T> *b, T *det=0, int n=0); /*solve Ax^T=b^T (b is nrhs x n) */\
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); \
@ -104,36 +104,28 @@ declare_la(complex<double>)
// Separate declarations
//general nonsymmetric matrix and generalized diagonalization
//corder =0 ... C rows are eigenvectors, =1 ... C columns are eigenvectors
extern void gdiagonalize(NRMat<double> &a, NRVec<double> &wr, NRVec<double> &wi,
NRMat<double> *vl, NRMat<double> *vr, const bool corder=1, int n=0, const int sorttype=0, const int biorthonormalize=0,
NRMat<double> *b=NULL, NRVec<double> *beta=NULL);
extern void gdiagonalize(NRMat<double> &a, NRVec< complex<double> > &w,
NRMat<double> *b=NULL, NRVec<double> *beta=NULL); //this used real storage of eigenvectors like dgeev
template<typename T>
extern void gdiagonalize(NRMat<T> &a, NRVec< complex<double> > &w,
NRMat< complex<double> >*vl, NRMat< complex<double> > *vr,
const bool corder=1, int n=0, const int sorttype=0, const int biorthonormalize=0,
NRMat<double> *b=NULL, NRVec<double> *beta=NULL);
extern NRMat<double> matrixfunction(NRSMat<double> a, double (*f) (double));
extern NRMat<double> realmatrixfunction(NRMat<double> a, double (*f) (double)); //a has to by in fact symmetric
extern NRMat<complex<double> > complexmatrixfunction(NRMat<double> a, double (*fre) (double), double (*fim) (double)); //a has to by in fact symmetric
extern NRMat<double> matrixfunction(NRMat<double> a, complex<double> (*f)(const complex<double> &),const bool adjust=0);
NRMat<T> *b=NULL, NRVec<T> *beta=NULL); //eigenvectors are stored in complex matrices for T both double and complex
extern complex<double> sqrtinv(const complex<double> &);
extern double sqrtinv(const double);
//functions on matrices
inline NRMat<double> sqrt(const NRSMat<double> &a) { return matrixfunction(a,&std::sqrt); }
inline NRMat<double> sqrtinv(const NRSMat<double> &a) { return matrixfunction(a,&sqrtinv); }
inline NRMat<double> realsqrt(const NRMat<double> &a) { return realmatrixfunction(a,&std::sqrt); }
inline NRMat<double> realsqrtinv(const NRMat<double> &a) { return realmatrixfunction(a,&sqrtinv); }
inline NRMat<double> log(const NRSMat<double> &a) { return matrixfunction(a,&std::log); }
extern NRMat<double> log(const NRMat<double> &a);
extern NRMat<double> exp0(const NRMat<double> &a);
extern const NRMat<double> realpart(const NRMat< complex<double> >&);
extern const NRMat<double> imagpart(const NRMat< complex<double> >&);
extern const NRMat< complex<double> > realmatrix (const NRMat<double>&);
extern const NRMat< complex<double> > imagmatrix (const NRMat<double>&);
extern const NRMat< complex<double> > complexmatrix (const NRMat<double>&, const NRMat<double>&);
//complex,real,imaginary parts of various entities
template<typename T>
extern const typename LA_traits<T>::realtype realpart(const T&);
template<typename T>
extern const typename LA_traits<T>::realtype imagpart(const T&);
template<typename T>
extern const typename LA_traits<T>::complextype realmatrix (const T&);
template<typename T>
extern const typename LA_traits<T>::complextype imagmatrix (const T&);
template<typename T>
extern const typename LA_traits<T>::complextype complexmatrix (const T&, const T&);
//Cholesky decomposition
extern void cholesky(NRMat<double> &a, bool upper=1);
@ -315,5 +307,84 @@ return r;
}
//matrix functions via diagonalization
extern NRMat<double> realmatrixfunction(NRMat<double> a, double (*f) (double)); //a has to by in fact symmetric
extern NRMat<complex<double> > complexmatrixfunction(NRMat<double> a, double (*fre) (double), double (*fim) (double)); //a has to by in fact symmetric
template<typename T>
NRMat<T> matrixfunction(NRSMat<T> a, double (*f) (double)) //of symmetric/hermitian matrix
{
int n = a.nrows();
NRVec<double> w(n);
NRMat<T> v(n, n);
diagonalize(a, w, &v, 0);
for (int i=0; i<a.nrows(); i++) w[i] = (*f)(w[i]);
NRMat<T> u = v;
NRVec<T> ww=w; //diagmultl needs same type
v.diagmultl(ww);
NRMat<T> r(n, n);
r.gemm(0.0, u, 't', v, 'n', 1.0); //gemm will use 'c' for complex ones
return r;
}
template<typename T>
extern NRMat<T> matrixfunction(NRMat<T> a, complex<double> (*f)(const complex<double> &)) //of a general real/complex matrix
{
int n = a.nrows();
NRVec<complex<double> > w(n);
NRMat<complex<double> > u(n,n),v(n,n);
#ifdef debugmf
NRMat<complex<double> > a0=a;
#endif
gdiagonalize<T>(a, w, &u, &v, false,n,0,false,NULL,NULL);//a gets destroyed, eigenvectors are rows
NRVec< complex<double> > z = diagofproduct(u, v, 1, 1);
#ifdef debugmf
std::cout <<"TEST matrixfunction\n"<<w<<u<<v<<z;
std::cout <<"TEST matrixfunction1 "<< u*a0 - diagonalmatrix(w)*u<<std::endl;
std::cout <<"TEST matrixfunction2 "<< a0*v.transpose(1) - v.transpose(1)*diagonalmatrix(w)<<std::endl;
std::cout <<"TEST matrixfunction3 "<< u*v.transpose(1)<<diagonalmatrix(z)<<std::endl;
#endif
NRVec< complex<double> > wz(n);
for (int i=0; i<a.nrows(); i++) wz[i] = w[i]/z[i];
#ifdef debugmf
std::cout <<"TEST matrixfunction4 "<< a0<< v.transpose(true)*diagonalmatrix(wz)*u<<std::endl;
#endif
for (int i=0; i<a.nrows(); i++) w[i] = (*f)(w[i])/z[i];
u.diagmultl(w);
NRMat< complex<double> > r(n, n);
r.gemm(0.0, v, 'c', u, 'n', 1.0);
return (NRMat<T>) r; //convert back to real if applicable by the explicit decomplexifying constructor; it is NOT checked to which accuracy the imaginary part is actually zero
}
extern complex<double> sqrtinv(const complex<double> &);
extern double sqrtinv(const double);
//functions on matrices
inline NRMat<double> sqrt(const NRSMat<double> &a) { return matrixfunction(a,&std::sqrt); }
inline NRMat<double> sqrtinv(const NRSMat<double> &a) { return matrixfunction(a,&sqrtinv); }
inline NRMat<double> realsqrt(const NRMat<double> &a) { return realmatrixfunction(a,&std::sqrt); }
inline NRMat<double> realsqrtinv(const NRMat<double> &a) { return realmatrixfunction(a,&sqrtinv); }
inline NRMat<double> log(const NRSMat<double> &a) { return matrixfunction(a,&std::log); }
extern NRMat<double> log(const NRMat<double> &a);
extern NRMat<complex<double> > log(const NRMat<complex<double> > &a);
extern NRMat<complex<double> > exp0(const NRMat<complex<double> > &a);
extern NRMat<complex<double> > copytest(const NRMat<complex<double> > &a);
extern NRMat<double> copytest(const NRMat<double> &a);
extern NRMat<double> exp0(const NRMat<double> &a);
}//namespace
#endif

4
smat.cc
View File

@ -58,7 +58,7 @@ void NRSMat<T>::put(int fd, bool dim, bool transp) const {
if(sizeof(int) != write(fd,&nn,sizeof(int))) laerror("cannot write");
if(sizeof(int) != write(fd,&nn,sizeof(int))) laerror("cannot write");
}
LA_traits<T>::multiput(NN2,fd,v,dim);
LA_traits<T>::multiput((size_t)nn*(nn+1)/2,fd,v,dim);
}
/***************************************************************************//**
@ -89,7 +89,7 @@ void NRSMat<T>::get(int fd, bool dim, bool transp) {
}else{
copyonwrite();
}
LA_traits<T>::multiget(NN2,fd,v,dim);
LA_traits<T>::multiget((size_t)nn*(nn+1)/2,fd,v,dim);
}

1
smat.h
View File

@ -159,6 +159,7 @@ public:
void clear() {copyonwrite(); LA_traits<T>::clear(v,NN2);}; //zero out
void resize(const int n);
void dealloc(void) {resize(0);}
inline operator T*();
inline operator const T*() const;

6
sparsemat.cc
View File

@ -1245,6 +1245,9 @@ return *this;
/*
Commented out by Roman for ICC
#define INSTANTIZE(T) \
template SparseMat<T> & SparseMat<T>::oplusequal(const SparseMat<T> &rhs);\
template SparseMat<T> & SparseMat<T>::oplusequal(const NRMat<T> &rhs);\
@ -1291,9 +1294,8 @@ template void SparseMat<T>::permuteindices(const NRVec<SPMatindex> &p);\
INSTANTIZE(double)
INSTANTIZE(complex<double>) //some functions are not OK for hermitean matrices, needs a revision!!!
*/
//////////////////////////////////////////////////////////////////////////////
//// forced instantization in the corresponding object file

1
sparsemat.h
View File

@ -120,6 +120,7 @@ public:
void get(int fd, bool dimensions=1, bool transposed=false);
void put(int fd, bool dimensions=1, bool transposed=false) const;
void resize(const SPMatindex n, const SPMatindex m); //destructive
void dealloc(void) {resize(0,0);}
void incsize(const SPMatindex n, const SPMatindex m); //increase size without destroying the data
void transposeme();
const SparseMat transpose() const;

33
sparsesmat.cc
View File

@ -257,6 +257,36 @@ if(divide)
return divide?NULL:&r[0];
}
template <class T>
SparseSMat<T> SparseSMat<T>::submatrix(const int fromrow, const int torow, const int fromcol, const int tocol) const
{
#ifdef DEBUG
if(fromrow<0 || fromrow>=nn|| torow<0 || torow>=nn || fromcol<0 || fromcol>=mm || tocol<0 || tocol>=mm || fromrow>torow || fromcol>tocol){
laerror("invalid submatrix specification");
}
#endif
const int m = tocol - fromcol + 1;
const int n = torow - fromrow + 1;
SparseSMat<T> result(n, m);
typename SparseSMat<T>::iterator p(*this);
for(; p.notend(); ++p)
if(p->row>=fromrow && p->row<= torow && p->col >= fromcol && p->col <= tocol)
result.add(p->row-fromrow, p->col-fromcol, p->elem, false);
return result;
}
template <class T>
void SparseSMat<T>::storesubmatrix(const int fromrow, const int fromcol, const SparseSMat<T> &rhs)
{
const int tocol = fromcol + rhs.ncols() - 1;
const int torow = fromrow + rhs.nrows() - 1;
#ifdef DEBUG
if(fromrow<0 || fromrow>=nn || torow>=nn || fromcol<0 || fromcol>=mm || tocol>=mm) laerror("bad indices in storesubmatrix");
#endif
typename SparseSMat<T>::iterator p(rhs);
for(; p.notend(); ++p) add(p->row+fromrow, p->col+fromcol, p->elem, false);
}
template <class T>
@ -305,6 +335,7 @@ void SparseSMat<T>::put(int fd, bool dimen, bool transp) const {
/* Commented out by Roman for ICC
#define INSTANTIZE(T) \
template void SparseSMat<T>::gemm(const T beta, const SparseSMat &a, const char transa, const SparseSMat &b, const char transb, const T alpha); \
@ -321,8 +352,8 @@ template void SparseSMat<T>::put(int fd, bool dimen, bool transp) const; \
INSTANTIZE(double)
INSTANTIZE(complex<double>)
*/
//// forced instantization of functions in the header in the corresponding object file
template class SparseSMat<double>;

4
sparsesmat.h
View File

@ -61,9 +61,11 @@ public:
explicit SparseSMat(const SparseMat<T> &rhs);
explicit SparseSMat(const NRSMat<T> &rhs);
explicit SparseSMat(const NRMat<T> &rhs);
explicit SparseSMat(const CSRMat<T> &rhs);
SparseSMat & operator=(const SparseSMat &rhs);
void copyonwrite();
void resize(const SPMatindex nn, const SPMatindex mm);
void dealloc(void) {resize(0,0);}
inline void setcoldim(int i) {mm=(SPMatindex)i;};
//std::map<SPMatindex,T> *line(SPMatindex n) const {return v[n];};
typedef std::map<SPMatindex,T> *ROWTYPE;
@ -100,6 +102,8 @@ public:
int nrows() const {return nn;}
int ncols() const {return mm;}
SparseSMat<T> cholesky(void) const;
SparseSMat submatrix(const int fromrow, const int torow, const int fromcol, const int tocol) const;
void storesubmatrix(const int fromrow, const int fromcol, const SparseSMat &rhs);
class iterator {//not efficient, just for output to ostreams
private:

157
t.cc
View File

@ -62,9 +62,10 @@ NRVec<double> x(1.,10);
NRVec<double> y(2.,10);
NRVec<double> z(-2.,10);
cout.setf(ios::scientific);
//cc:cout.setf(ios::fixed);
cout.precision(12);
//cout.setf(ios::scientific);
cc:cout.setf(ios::fixed);
cout.precision(10);
cin.exceptions ( ifstream::eofbit | ifstream::failbit | ifstream::badbit );
if(0) test(x);
@ -415,6 +416,50 @@ cout <<v.transpose(1)*u;
}
if(0)
{
NRMat<double> a;
cin >>a;
int n=a.nrows();
NRMat<complex<double> > u(n,n),v(n,n);
NRVec<complex<double> >w(n);
gdiagonalize(a,w,&u,&v,0,n,0,1);
cout <<u;
cout <<w;
cout <<v;
NRVec<complex<double> >z=diagofproduct(u,v,1,1);
cout <<z;
for(int i=0;i<a.nrows();++i) w[i]/=z[i];//account for normalization of eigenvectors
cout <<u*v.transpose(1); //check biorthonormality
u.diagmultl(w);
cout <<v.transpose(1)*u;
}
if(1)
{
NRMat<complex<double> > a;
cin >>a;
int n=a.nrows();
NRMat<complex<double> > u(n,n),v(n,n);
NRVec<complex<double> >w(n);
gdiagonalize(a,w,&u,&v,0,n,0,1);
cout <<u;
cout <<w;
cout <<v;
NRVec<complex<double> >z=diagofproduct(u,v,1,1);
cout <<z;
for(int i=0;i<a.nrows();++i) w[i]/=z[i];//account for normalization of eigenvectors
cout <<u*v.transpose(1); //check biorthonormality
u.diagmultl(w);
cout <<v.transpose(1)*u;
}
if(0)
{
@ -773,8 +818,42 @@ for(int i=1; i<4;i++) b=b*b;
if(0)
{
NRMat<double> a;
NRMat<double> aa,bb,cc;
cin >>aa;
cc=copytest(aa);
cout <<cc;
NRMat<complex<double> > a,b,c;
a=complexify(aa);
c=copytest(a);
cout <<c;
b=log(a);
cout <<b;
cout <<exp(b);
}
if(0)
{
NRMat<complex<double> > a,b,c;
cin>>a;
c=copytest(a);
cout <<c;
b=log(a);
cout <<b;
cout <<exp(b);
}
if(0)
{
NRMat<double> a,b,c;
cin >>a;
c=copytest(a);
cout <<c;
}
if(0)
{
NRMat<double> a;
NRMat<double> b=exp(a);
NRMat<double> c=log(b);
cout <<a;
@ -1163,6 +1242,7 @@ cout <<a.oplus(b);
cout <<a.otimes(b);
}
//test of general square matrix eigenvector derivatives
if(0)
{
@ -1236,21 +1316,28 @@ tmp.diagonalof(wrg);
for(int i=0; i<n; ++i)
for(int j=0; j<n; ++j)
if(i!=j) tmp(i,j) /= (wr[j] - wr[i]); else tmp(i,j) = 0.;
cout <<" old X matrix \n"<<tmp<<endl;
cout <<" old X matrix (tmp) \n"<<tmp<<endl;
NRMat<double> Y = tmp;
NRMat<double> S = vr.transpose() * vr;
cout <<"test S\n"<<S;
NRMat<double> tmp2 = S * tmp;
cout <<"test tmp2\n"<<tmp2;
Y.copyonwrite();
for(int i=0; i<n; ++i) Y(i,i) -= tmp2(i,i);
cout <<"Y matrix \n"<< Y;
NRMat<double> numX = inverse(vr) * vrd;
NRMat<double> vri = inverse(vr);
NRMat<double> numX = vri * vrd;
cout <<" numerical X matrix \n"<< numX;
cout <<" numerical X matrix test = "<< (vr * numX - vrd).norm()<<endl;
vrg = vr * Y;
vlg = - (Y*vri).transpose();
//and compare
cout <<"eigenvalue numerical derivative\n"<<wrd<<endl;
cout <<"eigenvalue analytic derivative\n"<<wrg<<endl;
@ -1261,9 +1348,17 @@ cout <<"right eigenvector numerical derivative\n"<<vrd<<endl;
cout <<"right eigenvector analytic derivative\n"<<vrg<<endl;
cout <<"right eigenvector derivative error = "<<(vrd-vrg).norm()<<endl;
//and for left eigenvectors
cout <<"left eigenvector numerical derivative\n"<<vld<<endl;
cout <<"left eigenvector analytic derivative\n"<<vlg<<endl;
cout <<"left eigenvector derivative error = "<<(vld-vlg).norm()<<endl;
}
//@@@@@@@make this derivative check in complex version
if(0)
{
try { laerror("test catch exception"); }
@ -1415,7 +1510,9 @@ cout <<"symmetry error "<<(het-he).norm()<<endl;
if(0)
{
NRSMat<double> hd(100);
int n;
cin >>n;
NRSMat<double> hd(n);
hd.randomize(1);
SparseSMat<double> h(hd);
NRMat<double> rd = hd*hd;
@ -1425,14 +1522,22 @@ NRMat<double> r2(rx);
cout <<"Error = "<<(r2-rd).norm()<<endl;
}
if(0)
{
SparseSMat<complex<double> > h;
cin>>h;
h *= complex<double>(0,1);
SparseSMat<double> h0;
cin>>h0;
cout <<"matrix read\n"; cout.flush();
SparseSMat<double> h1 = h0; //.submatrix(0,2047,0,2047);
SparseSMat<complex<double> > h = imagmatrix(h1);
double t=clock()/((double) (CLOCKS_PER_SEC));
SparseSMat<complex<double> > r = exp(h);
cout <<"SparseSMat time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
SparseSMat<complex<double> > r = h*h;
cout <<"SparseSMat mult time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
cout.flush();
t=clock()/((double) (CLOCKS_PER_SEC));
r = exp(h);
cout <<"SparseSMat exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
cout.flush();
if(h.nrows()<=1024)
{
NRSMat<complex<double> > h3(h);
@ -1443,6 +1548,7 @@ cout <<"errorx = "<<(r2-NRSMat<complex<double> >(r)).norm()<<endl;
}
}
if(0)
{
int n;
@ -1598,7 +1704,7 @@ cgpu.moveto(cpu);
cout << "Error = "<<(c-cgpu).norm()<<endl;
}
if(1)
if(0)
{
int n;
cin >>n;
@ -1627,6 +1733,31 @@ c.moveto(gpu1);
cout << "Error = "<<(c-cgpu).norm()<<endl;
}
/*
if(0)
{
CSRMat<double> h0;
cin>>h0;
cout <<"matrix read\n"; cout.flush();
CSRMat<double> h1 = h0;
CSRMat<complex<double> > h = imagmatrix(h1);
double t=clock()/((double) (CLOCKS_PER_SEC));
CSRMat<complex<double> > r = h*h;
cout <<"CSRMat mult time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
cout.flush();
t=clock()/((double) (CLOCKS_PER_SEC));
r = exp(h);
cout <<"CSRMat exp time "<<clock()/((double) (CLOCKS_PER_SEC))-t <<"\n";
cout.flush();
if(h.nrows()<=1024)
{
NRMat<complex<double> > h2(h);
NRMat<complex<double> >r2 = exp(h2);
cout <<"error = "<<(r2-NRMat<complex<double> >(r)).norm()<<endl;
}
}
*/

39
vec.cc
View File

@ -793,14 +793,14 @@ NRVec<complex<double> >::otimes(const NRVec<complex<double> > &b, const bool con
if(conj){
const cuDoubleComplex alpha = make_cuDoubleComplex(scale.real(), -scale.imag());
cublasZgerc(b.nn, nn, alpha, (cuDoubleComplex*)(b.v), 1, (cuDoubleComplex*)(v), 1, (cuDoubleComplex*)(result[0]), 1);
cublasZgerc(b.nn, nn, alpha, (cuDoubleComplex*)(b.v), 1, (cuDoubleComplex*)(v), 1, (cuDoubleComplex*)(result[0]), b.nn);
TEST_CUBLAS("cublasZgerc");
result.conjugateme();
}else{
const cuDoubleComplex alpha = make_cuDoubleComplex(scale.real(), +scale.imag());
cublasZgeru(b.nn, nn, alpha, (cuDoubleComplex*)(b.v), 1, (cuDoubleComplex*)(v), 1, (cuDoubleComplex*)(result[0]), 1);
cublasZgeru(b.nn, nn, alpha, (cuDoubleComplex*)(b.v), 1, (cuDoubleComplex*)(v), 1, (cuDoubleComplex*)(result[0]), b.nn);
TEST_CUBLAS("cublasZgeru");
}
}
@ -839,6 +839,9 @@ NRVec<complex<double> > complexify(const NRVec<double> &rhs) {
/***************************************************************************//**
* forced instantization in the corespoding object file
******************************************************************************/
/*
Commented out by Roman for ICC
#define INSTANTIZE(T) \
template void NRVec<T>::put(int fd, bool dim, bool transp) const; \
template void NRVec<T>::get(int fd, bool dim, bool transp); \
@ -855,19 +858,7 @@ INSTANTIZE(unsigned short)
INSTANTIZE(unsigned int)
INSTANTIZE(unsigned long)
INSTANTIZE(unsigned long long)
template class NRVec<double>;
template class NRVec<complex<double> >;
template class NRVec<char>;
template class NRVec<short>;
template class NRVec<int>;
template class NRVec<long>;
template class NRVec<long long>;
template class NRVec<unsigned char>;
template class NRVec<unsigned short>;
template class NRVec<unsigned int>;
template class NRVec<unsigned long>;
template class NRVec<unsigned long long>;
*/
#define INSTANTIZE_DUMMY(T) \
template<> void NRVec<T>::gemv(const T beta, const NRMat<T> &a, const char trans, const T alpha, const NRVec<T> &x) { laerror("gemv on unsupported types"); } \
@ -878,6 +869,11 @@ template<> void NRVec<T>::gemv(const LA_traits_complex<T>::Component_type beta,
template<> NRVec<T> & NRVec<T>::normalize(LA_traits<T>::normtype *) {laerror("normalize() impossible for integer types"); return *this;} \
template<> const NRMat<T> NRVec<T>::otimes(const NRVec<T> &b,const bool conj, const T &scale) const {laerror("otimes presently implemented only for double and complex double"); return NRMat<T> ();}
// Roman
// following gemv are not implemented
template<> void NRVec<double>::gemv(const double beta, const SparseMat<double> &a, const char trans, const double alpha, const NRVec<double> &x, bool s) { laerror("gemv on unsupported types"); }
template<> void NRVec< complex<double> >::gemv(const complex<double> beta, const SparseMat< complex<double> > &a, const char trans, const complex<double> alpha, const NRVec< complex<double> > &x, bool s) { laerror("gemv on unsupported types"); }
INSTANTIZE_DUMMY(char)
INSTANTIZE_DUMMY(short)
@ -902,4 +898,17 @@ INSTANTIZE_DUMMY(complex<unsigned long long>)
INSTANTIZE_DUMMY(complex<complex<double> >)
INSTANTIZE_DUMMY(complex<complex<float> >)
template class NRVec<double>;
template class NRVec<complex<double> >;
template class NRVec<char>;
template class NRVec<short>;
template class NRVec<int>;
template class NRVec<long>;
template class NRVec<long long>;
template class NRVec<unsigned char>;
template class NRVec<unsigned short>;
template class NRVec<unsigned int>;
template class NRVec<unsigned long>;
template class NRVec<unsigned long long>;
}//namespace

3
vec.h
View File

@ -287,6 +287,9 @@ public:
//! resize the current vector
void resize(const int n);
//!deallocate the current vector
void dealloc(void) {resize(0);}
//! determine the norm of this vector
inline const typename LA_traits<T>::normtype norm() const;