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jiri
2010-01-07 16:10:12 +00:00
parent bd843de786
commit 5f5f0343a6
7 changed files with 517 additions and 27 deletions
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164
sparsesmat.cc
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@@ -27,6 +27,45 @@
namespace LA {
//dense times sparse (not necessarily symmetric)
template <typename T>
SparseSMat<T> & NRMat<T>::operator*(const SparseSMat<T> &rhs) const
{
SparseSMat<T> r(nn,rhs.ncols());
if(mm!=rhs.nrows()) laerror("incompatible sizes in NRMat*SparseSMat");
for(SPMatindex k=0; k<nn; ++k) //summation loop
{
std::map<SPMatindex,T> * kl = rhs.line(k);
if(kl)
{
//gather the data
typename std::map<SPMatindex,T>::iterator p;
int i,j;
NRVec<T> kline(kl->size());
NRVec<SPMatindex> klineind(kl->size());
for(p=kl->begin(), i=0; p!=kl->end(); ++p,++i)
{
klineind[i] = p->first;
kline[i] = p->second;
}
NRVec<T> kcol = column(k);
//multiply
NRMat<T> prod=kcol.otimes(kline,false,1.);
//scatter the results
for(i=0; i<prod.nrows(); ++i) for(j=0; j<prod.ncols(); ++j)
add(i,klineind[j],prod(i,j),false);
}
}
r.simplify();
return r;
}
//matrix is assummed symmetric, no transposition, but possibly make conjugation
template <typename T>
void SparseSMat<T>::gemm(const T beta, const SparseSMat &a, const char transa, const SparseSMat &b, const char transb, const T alpha)
{
@@ -46,16 +85,14 @@ for(SPMatindex k=0; k<nn; ++k) //summation loop
//gather the data
typename std::map<SPMatindex,T>::iterator p;
int i,j;
for(p=a.v[k]->begin(), i=0; p!=a.v[k]->end(); ++p,++i)
{
ai[i] = p->first;
av[i] = p->second;
}
for(p=b.v[k]->begin(), i=0; p!=b.v[k]->end(); ++p,++i)
{
bi[i] = p->first;
bv[i] = p->second;
}
if(tolower(transa)=='c')
for(p=a.v[k]->begin(), i=0; p!=a.v[k]->end(); ++p,++i) { ai[i] = p->first; av[i] = LA_traits<T>::conjugate(p->second); }
else
for(p=a.v[k]->begin(), i=0; p!=a.v[k]->end(); ++p,++i) { ai[i] = p->first; av[i] = p->second; }
if(tolower(transb)=='c')
for(p=b.v[k]->begin(), i=0; p!=b.v[k]->end(); ++p,++i) { bi[i] = p->first; bv[i] = LA_traits<T>::conjugate(p->second); }
else
for(p=b.v[k]->begin(), i=0; p!=b.v[k]->end(); ++p,++i) { bi[i] = p->first; bv[i] = p->second; }
//make multiply via blas
NRMat<T> prod=av.otimes(bv,false,alpha);
@@ -96,8 +133,13 @@ copyonwrite();
for(SPMatindex i=0; i<nn; ++i) if(x.v[i])
{
if(!v[i]) v[i] = new std::map<SPMatindex,T>;
typename std::map<SPMatindex,T>::iterator p;
for(p=x.v[i]->begin(); p!=x.v[i]->end(); ++p) (*v[i])[p->first] = p->second * alpha;
typename std::map<SPMatindex,T>::iterator p,q;
for(p=x.v[i]->begin(); p!=x.v[i]->end(); ++p)
{
q=v[i]->find(p->first);
if(q!=v[i]->end()) q->second += p->second * alpha;
else (*v[i])[p->first] = p->second * alpha;
}
}
simplify();
}
@@ -165,26 +207,105 @@ for(SPMatindex i=0; i<nn; ++i)
return *this;
}
template <class T>
typename LA_traits<T>::normtype SparseSMat<T>::norm(const T scalar) const
{
typename LA_traits<T>::normtype sum=0;
for(SPMatindex i=0; i<nn; ++i)
if(v[i])
if(v[i]) //line present
{
typename std::map<SPMatindex,T>::iterator p;
p= v[i]->find(i);
if(p!=v[i]->end()) sum += LA_traits<T>::sqrabs(p->second - scalar);
else sum += LA_traits<T>::sqrabs(scalar);
bool diagonal_present=false;
for(p=v[i]->begin(); p!=v[i]->end(); ++p) //loop over all existing elements
{
if(i==p->first) {diagonal_present=true; sum += LA_traits<T>::sqrabs(p->second - scalar);}
else sum += LA_traits<T>::sqrabs(p->second);
}
if(!diagonal_present) sum += LA_traits<T>::sqrabs(scalar); //there was zero on the diagonal
}
else sum += LA_traits<T>::sqrabs(scalar); //missing diagonal element
else sum += LA_traits<T>::sqrabs(scalar); //missing whole line, subtracted diagonal element contributes
return std::sqrt(sum);
}
//get diagonal, do not construct a new object, but store in existing one
template <class T>
const T* SparseSMat<T>::diagonalof(NRVec<T> &r, const bool divide, bool cache) const
{
if(nn!=r.size()) laerror("incompatible vector size in diagonalof()");
NRVec<T> *rr;
r.copyonwrite();
if(divide) {rr=new NRVec<T>(nn); *rr=(T)0;}
else {r=(T)0; rr=&r;}
for(SPMatindex i=0; i<nn; ++i)
if(v[i])
{
typename std::map<SPMatindex,T>::iterator p;
p= v[i]->find(i);
if(p!=v[i]->end()) (*rr)[i] += p->second;
}
if(divide)
{
for(unsigned int i=0; i<nn; ++i) if((*rr)[i]!=0.) r[i]/=(*rr)[i];
delete rr;
}
return divide?NULL:&r[0];
}
template <class T>
void SparseSMat<T>::get(int fd, bool dimen, bool transp) {
errno=0;
SPMatindex dim[2];
if(dimen) {
if(2*sizeof(SPMatindex)!=read(fd,&dim,2*sizeof(SPMatindex))) laerror("read() error in SparseSMat::get ");
if(dim[0]!=dim[1]) laerror("SparseSMat must be square (nonsquare read in ::get)");
resize(dim[0]);
}
else copyonwrite();
do {
if(2*sizeof(SPMatindex)!=read(fd,&dim,2*sizeof(SPMatindex))) laerror("read() error 2 in SparseSMat::get");
if(dim[0]==(SPMatindex) -1 || dim[1]==(SPMatindex) -1) break;
typename LA_traits_io<T>::IOtype tmp;
LA_traits<T>::get(fd,tmp,dimen,transp); // general way to work when elem is some complex class again
if(transp) add(dim[0],dim[1],tmp,false); else add(dim[1],dim[0],tmp,false);
}
while(1);
}
template <class T>
void SparseSMat<T>::put(int fd, bool dimen, bool transp) const {
errno=0;
if(dimen) {
if(sizeof(SPMatindex)!=write(fd,&nn,sizeof(SPMatindex))) laerror("cannot write() 1 in SparseSMat::put");
if(sizeof(SPMatindex)!=write(fd,&nn,sizeof(SPMatindex))) laerror("cannot write() 2 in SparseSMat::put");
}
typename SparseSMat<T>::iterator p(*this);
for(; p.notend(); ++p) {
if(sizeof(SPMatindex)!=write(fd,&(p->row),sizeof(SPMatindex))) laerror("cannot write() 3 in SparseSMat::put");
if(sizeof(SPMatindex)!=write(fd,&(p->col),sizeof(SPMatindex))) laerror("cannot write() 4 in SparseSMat::put");
typename LA_traits_io<T>::IOtype tmp = p->elem;
LA_traits<T>::put(fd,tmp,dimen,transp); // general way to work when elem is some non-scalar class again
}
SPMatindex sentinel[2];
sentinel[0] = sentinel[1] = (SPMatindex) -1;
if(2*sizeof(SPMatindex) != write(fd,&sentinel,2*sizeof(SPMatindex))) laerror("cannot write() 5 in SparseSMat::put");
}
#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); \
@@ -195,6 +316,9 @@ template SparseSMat<T> & SparseSMat<T>::operator=(const T &a); \
template SparseSMat<T> & SparseSMat<T>::operator+=(const T &a); \
template SparseSMat<T> & SparseSMat<T>::operator-=(const T &a); \
template LA_traits<T>::normtype SparseSMat<T>::norm(const T scalar) const; \
template const T* SparseSMat<T>::diagonalof(NRVec<T> &r, const bool divide, bool cache) const; \
template void SparseSMat<T>::get(int fd, bool dimen, bool transp); \
template void SparseSMat<T>::put(int fd, bool dimen, bool transp) const; \
INSTANTIZE(double)
@@ -205,4 +329,10 @@ INSTANTIZE(complex<double>)
template class SparseSMat<double>;
template class SparseSMat<complex<double> >;
/*activate this if needed
template void SparseSMat<NRMat<double> >::put(int fd, bool dimen, bool transp) const;
template void SparseSMat<NRMat<double> >::get(int fd, bool dimen, bool transp);
*/
}//namespace