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jiri
parent
12c88e6872
commit
8ec7c11a6e
10
la_traits.h
10
la_traits.h
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@ -219,8 +219,9 @@ static void copy(complex<C> *dest, complex<C> *src, unsigned int n) {memcpy(dest
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static void clear(complex<C> *dest, unsigned int n) {memset(dest,0,n*sizeof(complex<C>));}
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static void copyonwrite(complex<C> &x) {};
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static void clearme(complex<C> &x) {x=0;};
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static inline complex<C> conjugate(complex<C> &x) {return complex<C>(x.real(),-x.imag());};
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static inline C realpart(complex<C> &x) {return x.real();}
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static inline complex<C> conjugate(const complex<C> &x) {return complex<C>(x.real(),-x.imag());};
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static inline C realpart(const complex<C> &x) {return x.real();}
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static inline C imagpart(const complex<C> &x) {return x.imag();}
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};
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//non-complex scalars
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@ -243,8 +244,9 @@ static void copy(C *dest, C *src, unsigned int n) {memcpy(dest,src,n*sizeof(C));
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static void clear(C *dest, unsigned int n) {memset(dest,0,n*sizeof(C));}
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static void copyonwrite(C &x) {};
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static void clearme(complex<C> &x) {x=0;};
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static inline C conjugate(C&x) {return x;};
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static inline C realpart(C &x) {return x;}
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static inline C conjugate(const C &x) {return x;};
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static inline C realpart(const C &x) {return x;}
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static inline C imagpart(const C &x) {return 0;}
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};
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2
mat.h
2
mat.h
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@ -128,7 +128,7 @@ public:
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const T trace() const;
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//members concerning sparse matrix
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SparseSMat<T> & operator*(const SparseSMat<T> &rhs) const;
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SparseSMat<T> operator*(const SparseSMat<T> &rhs) const;
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explicit NRMat(const SparseMat<T> &rhs); // dense from sparse
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explicit NRMat(const SparseSMat<T> &rhs); // dense from sparse
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NRMat & operator+=(const SparseMat<T> &rhs);
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@ -30,11 +30,11 @@ namespace LA {
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//dense times sparse (not necessarily symmetric)
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template <typename T>
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SparseSMat<T> & NRMat<T>::operator*(const SparseSMat<T> &rhs) const
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SparseSMat<T> NRMat<T>::operator*(const SparseSMat<T> &rhs) const
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{
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SparseSMat<T> r(nn,rhs.ncols());
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if(mm!=rhs.nrows()) laerror("incompatible sizes in NRMat*SparseSMat");
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for(SPMatindex k=0; k<nn; ++k) //summation loop
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for(SPMatindex k=0; k<mm; ++k) //summation loop
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{
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std::map<SPMatindex,T> * kl = rhs.line(k);
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if(kl)
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@ -71,6 +71,7 @@ void SparseSMat<T>::gemm(const T beta, const SparseSMat &a, const char transa, c
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{
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(*this) *= beta;
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if(alpha==(T)0) return;
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if(a.nn!=a.mm || b.nn!=b.mm || nn!=mm) laerror("SparseSMat::gemm implemented only for square symmetric matrices");
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if(a.nn!=b.nn || a.nn!=nn) laerror("incompatible sizes in SparseSMat::gemm");
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copyonwrite();
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@ -89,13 +90,10 @@ for(SPMatindex k=0; k<nn; ++k) //summation loop
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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); }
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else
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for(p=a.v[k]->begin(), i=0; p!=a.v[k]->end(); ++p,++i) { ai[i] = p->first; av[i] = p->second; }
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if(tolower(transb)=='c')
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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); }
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else
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for(p=b.v[k]->begin(), i=0; p!=b.v[k]->end(); ++p,++i) { bi[i] = p->first; bv[i] = p->second; }
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for(p=b.v[k]->begin(), i=0; p!=b.v[k]->end(); ++p,++i) { bi[i] = p->first; bv[i] = p->second; }
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//make multiply via blas
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NRMat<T> prod=av.otimes(bv,false,alpha);
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NRMat<T> prod=av.otimes(bv,tolower(transb)=='c',alpha);
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//scatter the results -- probably the computational bottleneck
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for(i=0; i<prod.nrows(); ++i) for(j=0; j<prod.ncols(); ++j)
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@ -127,7 +125,7 @@ return *this;
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template <class T>
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void SparseSMat<T>::axpy(const T alpha, const SparseSMat &x, const bool transp)
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{
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if(nn!=x.nn) laerror("incompatible matrix dimensions in SparseSMat::axpy");
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if(nn!=x.nn || mm!=x.mm) laerror("incompatible matrix dimensions in SparseSMat::axpy");
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if(alpha==(T)0) return;
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copyonwrite();
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for(SPMatindex i=0; i<nn; ++i) if(x.v[i])
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@ -148,7 +146,8 @@ simplify();
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template <class T>
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void SparseSMat<T>::gemv(const T beta, NRVec<T> &r, const char trans, const T alpha, const NRVec<T> &x) const
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{
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if(nn!=r.size() || nn!= x.size()) laerror("incompatible matrix vector dimensions in SparseSMat::gemv");
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if(nn!=r.size() || mm!= x.size()) laerror("incompatible matrix vector dimensions in SparseSMat::gemv");
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if(trans) laerror("transposition not implemented yet in SparseSMat::gemv");
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r *= beta;
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if(alpha == (T)0) return;
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r.copyonwrite();
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@ -236,6 +235,7 @@ return std::sqrt(sum);
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template <class T>
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const T* SparseSMat<T>::diagonalof(NRVec<T> &r, const bool divide, bool cache) const
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{
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if(nn!=mm) laerror("non-square matrix in SparseSMat::diagonalof");
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if(nn!=r.size()) laerror("incompatible vector size in diagonalof()");
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NRVec<T> *rr;
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@ -266,8 +266,7 @@ void SparseSMat<T>::get(int fd, bool dimen, bool transp) {
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if(dimen) {
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if(2*sizeof(SPMatindex)!=read(fd,&dim,2*sizeof(SPMatindex))) laerror("read() error in SparseSMat::get ");
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if(dim[0]!=dim[1]) laerror("SparseSMat must be square (nonsquare read in ::get)");
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resize(dim[0]);
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resize(dim[0],dim[1]);
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}
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else copyonwrite();
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@ -288,7 +287,7 @@ void SparseSMat<T>::put(int fd, bool dimen, bool transp) const {
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errno=0;
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if(dimen) {
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if(sizeof(SPMatindex)!=write(fd,&nn,sizeof(SPMatindex))) laerror("cannot write() 1 in SparseSMat::put");
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if(sizeof(SPMatindex)!=write(fd,&nn,sizeof(SPMatindex))) laerror("cannot write() 2 in SparseSMat::put");
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if(sizeof(SPMatindex)!=write(fd,&mm,sizeof(SPMatindex))) laerror("cannot write() 2 in SparseSMat::put");
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}
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typename SparseSMat<T>::iterator p(*this);
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90
sparsesmat.h
90
sparsesmat.h
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@ -50,20 +50,25 @@ class SparseSMat
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{
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protected:
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SPMatindex nn;
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SPMatindex mm;
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std::map<SPMatindex,T> **v;
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int *count;
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public:
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SparseSMat() : nn(0), v(NULL), count(NULL) {};
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explicit SparseSMat(const SPMatindex n); //prevent double -> int -> SparseSMat
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SparseSMat() : nn(0), mm(0), v(NULL), count(NULL) {};
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explicit SparseSMat(const SPMatindex n, const SPMatindex m); //prevent double -> int -> SparseSMat
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explicit SparseSMat(const SPMatindex n);
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SparseSMat(const SparseSMat &rhs);
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explicit SparseSMat(const SparseMat<T> &rhs);
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explicit SparseSMat(const NRSMat<T> &rhs);
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explicit SparseSMat(const NRMat<T> &rhs);
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SparseSMat & operator=(const SparseSMat &rhs);
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void copyonwrite();
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void resize(const SPMatindex n);
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std::map<SPMatindex,T> *line(SPMatindex n) const {return v[n];};
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void clear() {resize(nn);}
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void resize(const SPMatindex nn, const SPMatindex mm);
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inline void setcoldim(int i) {mm=(SPMatindex)i;};
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//std::map<SPMatindex,T> *line(SPMatindex n) const {return v[n];};
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typedef std::map<SPMatindex,T> *ROWTYPE;
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inline typename SparseSMat<T>::ROWTYPE & operator[](const SPMatindex i) {return v[i];};
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void clear() {resize(nn,mm);}
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unsigned long long simplify();
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~SparseSMat();
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inline int getcount() const {return count?*count:0;}
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@ -83,7 +88,7 @@ public:
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void gemv(const T beta, NRVec<T> &r, const char trans, const T alpha, const NRVec<T> &x) const;
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inline const NRVec<T> operator*(const NRVec<T> &rhs) const {NRVec<T> result(nn); this->gemv((T)0,result,'n',(T)1,rhs); return result;};
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typename LA_traits<T>::normtype norm(const T scalar=(T)0) const;
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inline const SparseSMat operator*(const SparseSMat &rhs) const {SparseSMat<T> r(nn); r.gemm(0,*this,'n',rhs,'n',1); return r;}; //!!!NOT A GENERAL ROUTINE, JUST FOR THE CASES WHEN THE RESULT STAYS SYMMETRIC
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inline const SparseSMat operator*(const SparseSMat &rhs) const {SparseSMat<T> r(nn,mm); r.gemm(0,*this,'n',rhs,'n',1); return r;}; //!!!NOT A GENERAL ROUTINE, JUST FOR THE CASES WHEN THE RESULT STAYS SYMMETRIC
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void gemm(const T beta, const SparseSMat &a, const char transa, const SparseSMat &b, const char transb, const T alpha); //this := alpha*op( A )*op( B ) + beta*this !!!NOT A GENERAL ROUTINE, JUST FOR THE CASES WHEN THE RESULT STAYS SYMMETRIC
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inline void add(const SPMatindex n, const SPMatindex m, const T elem, const bool both=true);
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inline unsigned long long length() {return simplify();};
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@ -92,7 +97,7 @@ public:
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void get(int fd, bool dimen, bool transp);
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void put(int fd, bool dimen, bool transp) const;
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int nrows() const {return nn;}
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int ncols() const {return nn;}
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int ncols() const {return mm;}
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SparseSMat<T> cholesky(void) const;
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class iterator {//not efficient, just for output to ostreams
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@ -103,14 +108,15 @@ public:
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typename std::map<SPMatindex,T>::iterator *col;
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typename std::map<SPMatindex,T>::iterator mycol;
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SPMatindex mynn;
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SPMatindex mymm;
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std::map<SPMatindex,T> **myv;
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public:
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//compiler-generated iterator & operator=(const iterator &rhs);
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//compiler-generated iterator(const iterator &rhs);
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iterator(): p(NULL),row(0),col(NULL),mynn(0),myv(NULL) {};
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iterator(const SparseSMat &rhs) : mynn(rhs.nn), myv(rhs.v), col(NULL) {row=0; p= &my; operator++();}
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iterator(): p(NULL),row(0),col(NULL),mynn(0),mymm(0),myv(NULL) {};
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iterator(const SparseSMat &rhs) : mynn(rhs.nn), mymm(rhs.mm), myv(rhs.v), col(NULL) {row=0; p= &my; operator++();}
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iterator operator++() {
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if(col) //finish column list
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{
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@ -156,10 +162,19 @@ public:
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iterator end() const {return iterator(NULL);}
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};
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template <typename T>
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SparseSMat<T>::SparseSMat(const SPMatindex n)
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:nn(n),
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:nn(n), mm(n),
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count(new int(1))
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{
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v= new std::map<SPMatindex,T> * [n];
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memset(v,0,nn*sizeof(std::map<SPMatindex,T> *));
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}
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template <typename T>
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SparseSMat<T>::SparseSMat(const SPMatindex n, const SPMatindex m)
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:nn(n), mm(m),
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count(new int(1))
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{
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v= new std::map<SPMatindex,T> * [n];
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@ -168,7 +183,7 @@ memset(v,0,nn*sizeof(std::map<SPMatindex,T> *));
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template <typename T>
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SparseSMat<T>::SparseSMat(const NRSMat<T> &rhs)
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:nn(rhs.nrows()),
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:nn(rhs.nrows()), mm(rhs.ncols()),
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count(new int(1))
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{
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v= new std::map<SPMatindex,T> * [nn];
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@ -179,14 +194,14 @@ for(i=0; i<nn; ++i) for(j=0; j<=i; ++j) if(std::abs(rhs(i,j))>SPARSEEPSILON) (*t
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template <typename T>
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SparseSMat<T>::SparseSMat(const NRMat<T> &rhs)
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:nn(rhs.nrows()),
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:nn(rhs.nrows()), mm(rhs.ncols()),
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count(new int(1))
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{
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if(rhs.nrows()!=rhs.ncols()) laerror("non-square matrix in SparseSMat constructor from NRMat");
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v= new std::map<SPMatindex,T> * [nn];
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memset(v,0,nn*sizeof(std::map<SPMatindex,T> *));
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int i,j;
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for(i=0; i<nn; ++i) for(j=0; j<nn; ++j) if(std::abs(rhs(i,j))>SPARSEEPSILON) (*this).add(i,j,rhs(i,j),false);
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for(i=0; i<nn; ++i) for(j=0; j<mm; ++j) if(std::abs(rhs(i,j))>SPARSEEPSILON) (*this).add(i,j,rhs(i,j),false);
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}
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@ -195,6 +210,7 @@ SparseSMat<T>::SparseSMat(const SparseSMat &rhs)
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{
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v = rhs.v;
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nn = rhs.nn;
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mm = rhs.mm;
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count = rhs.count;
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if(count) (*count)++;
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}
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@ -205,6 +221,7 @@ template <typename T>
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NRSMat<T>::NRSMat(const SparseSMat<T> &rhs)
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: nn(rhs.nrows())
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{
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if(rhs.nrows()!=rhs.ncols()) laerror("cannot transform rectangular matrix to NRSMat");
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count = new int(1);
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v=new T[nn2];
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memset(v,0,nn2*sizeof(T));
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@ -251,13 +268,14 @@ SparseSMat<T>::~SparseSMat()
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template <typename T>
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void SparseSMat<T>::resize(const SPMatindex n)
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void SparseSMat<T>::resize(const SPMatindex n, const SPMatindex m)
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{
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if(!count)
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{
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if(n==0) return;
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count = new int(1);
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nn=n;
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mm=m;
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v= new std::map<SPMatindex,T> * [nn];
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for(SPMatindex i=0; i<nn; ++i) v[i]=NULL;
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return;
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@ -270,13 +288,15 @@ if(*count > 1) //it was shared
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{
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count = new int(1);
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nn=n;
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mm=m;
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v= new std::map<SPMatindex,T> * [nn];
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for(SPMatindex i=0; i<nn; ++i) v[i]=NULL;
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}
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else {v=NULL; nn=0; count=NULL;}
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else {v=NULL; nn=0; mm=0; count=NULL;}
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}
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else //it was not shared
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{
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mm=m;
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//delete all trees
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for(SPMatindex i=0; i<nn; ++i) if(v[i]) {delete v[i]; v[i]=NULL;}
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if(n!=nn)
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@ -305,6 +325,7 @@ SparseSMat<T> & SparseSMat<T>::operator=(const SparseSMat &rhs)
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}
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v = rhs.v;
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nn = rhs.nn;
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mm = rhs.mm;
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count = rhs.count;
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if(count) (*count)++;
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}
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@ -335,7 +356,7 @@ template <typename T>
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void SparseSMat<T>::add(const SPMatindex n, const SPMatindex m, const T elem, const bool both)
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{
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#ifdef DEBUG
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if(n>=nn || m>=nn) laerror("illegal index in SparseSMat::add()");
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if(n>=nn || m>=mm) laerror("illegal index in SparseSMat::add()");
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#endif
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if(!v[n]) v[n] = new std::map<SPMatindex,T>;
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@ -377,8 +398,7 @@ std::ostream & operator<<(std::ostream &s, const SparseSMat<T> &x)
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{
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SPMatindex n;
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n = x.nrows();
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s << n << " "<< n<< std::endl;
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s << x.nrows() << " "<< x.ncols()<< std::endl;
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typename SparseSMat<T>::iterator p(x);
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for(; p.notend(); ++p) s << (int)p->row << ' ' << (int)p->col << ' ' << (typename LA_traits_io<T>::IOtype) p->elem << '\n';
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@ -393,28 +413,31 @@ std::istream& operator>>(std::istream &s, SparseSMat<T> &x)
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long i,j;
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s >> n >> m;
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if(n!=m) laerror("SparseSMat must be square");
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x.resize(n);
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x.resize(n,m);
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s >> i >> j;
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typename LA_traits_io<T>::IOtype tmp;
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while(i>=0 && j>=0)
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{
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s>>tmp;
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if(i>=n||j>=m) laerror("bad index in SparseSMat::operator>>");
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x.add(i,j,tmp,false);
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s >> i >> j;
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}
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return s;
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}
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template <typename T>
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SparseSMat<T> SparseSMat<T>::transpose(bool conj) const
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{
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SparseSMat<T> r(nn);
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SparseSMat<T> r(mm,nn);
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typename SparseSMat<T>::iterator p(*this);
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for(; p.notend(); ++p) r.add(p->col, p->row, (conj?LA_traits<T>::conjugate(p->elem):p->elem), false);
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return r;
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}
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//Cholesky decomposition, pivoted, positive semidefinite, not in place
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//it is NOT checked that the input matrix is symmetric/hermitean
|
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//result.transpose(true)*result reproduces the original matrix
|
||||
|
|
@ -423,7 +446,7 @@ return r;
|
|||
template <typename T>
|
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SparseSMat<T> SparseSMat<T>::cholesky(void) const
|
||||
{
|
||||
|
||||
if(nn!=mm) laerror("Cholesky defined only for square matrices");
|
||||
//we need real values for sorting, if T is already real it makes just an unnecessary copy of one vector
|
||||
NRVec<typename LA_traits<T>::normtype> diagreal(nn);
|
||||
{
|
||||
|
|
@ -451,6 +474,7 @@ for(int i=0; i<nn; ++i) invpivot[pivot[i]]=i;
|
|||
//copy-permute upper triangle
|
||||
SparseSMat<T> r;
|
||||
r.nn=nn;
|
||||
r.mm=nn;
|
||||
r.count = new int(1);
|
||||
r.v = new std::map<SPMatindex,T> * [nn];
|
||||
for(SPMatindex i=0; i<nn; ++i)
|
||||
|
|
@ -545,5 +569,27 @@ return r;
|
|||
}
|
||||
|
||||
|
||||
|
||||
//outer product expected to be sparse
|
||||
template<typename T>
|
||||
SparseSMat<T> otimes_sparse(const NRVec<T> &lhs, const NRVec<T> &rhs, const bool conjugate=false, const T &scale=1)
|
||||
{
|
||||
SparseSMat<T> r(lhs.size(),rhs.size());
|
||||
for(SPMatindex i=0; i<lhs.size(); ++i)
|
||||
if(lhs[i])
|
||||
{
|
||||
for(SPMatindex j=0; j<rhs.size(); ++j)
|
||||
if(rhs[j])
|
||||
{
|
||||
T x=lhs[i]*(conjugate?LA_traits<T>::conjugate(rhs[j]):rhs[j])*scale;
|
||||
if(std::abs(x)>SPARSEEPSILON) r.add(i,j,x);
|
||||
}
|
||||
}
|
||||
return r;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
}//namespace
|
||||
#endif //_SPARSESMAT_H_
|
||||
|
|
|
|||
6
t.cc
6
t.cc
|
|
@ -1555,17 +1555,17 @@ if(1)
|
|||
{
|
||||
int n;
|
||||
cin >>n;
|
||||
SparseSMat<double> bh(n);
|
||||
SparseSMat<double> bh(n,n);
|
||||
for(int i=0; i<=n/400; ++i) for(int j=i; j<n; ++j) {if((double)random()/RAND_MAX>0.995 || i==j)
|
||||
{bh.add(i,j,(double)random()/RAND_MAX*(i==j?10.:(random()>RAND_MAX/2?1:-1)),false);}}
|
||||
if(n<1000) cout <<"Random matrix\n"<<bh;
|
||||
SparseSMat<double> bb(n);
|
||||
SparseSMat<double> bb(n,n);
|
||||
bb.gemm(0.,bh,'c',bh,'n',1.);
|
||||
if(n<1000) cout <<"Input matrix\n"<<bb;
|
||||
cout <<"Original filling = "<<bb.simplify()<<endl;
|
||||
SparseSMat<double> b = bb.cholesky();
|
||||
if(n<1000) cout <<"Cholesky result\n"<<b;
|
||||
SparseSMat<double> br(n);
|
||||
SparseSMat<double> br(n,n);
|
||||
br.gemm(0.,b,'c',b,'n',1.);
|
||||
if(n<1000) cout <<"Result of reconstruction\n"<<br;
|
||||
if(n<1000) cout <<"Difference\n"<<br-bb;
|
||||
|
|
|
|||
3
vec.h
3
vec.h
|
|
@ -113,6 +113,8 @@ public:
|
|||
inline const T dot(const T *a, const int stride=1) const; // ddot with a stride-vector
|
||||
inline T & operator[](const int i);
|
||||
inline const T & operator[](const int i) const;
|
||||
typedef T ROWTYPE;
|
||||
inline void setcoldim(int i) {}; //dummy
|
||||
inline int size() const;
|
||||
inline operator T*(); //get a pointer to the data
|
||||
inline operator const T*() const; //get a pointer to the data
|
||||
|
|
@ -145,6 +147,7 @@ public:
|
|||
#include "mat.h"
|
||||
#include "smat.h"
|
||||
#include "sparsemat.h"
|
||||
#include "sparsesmat.h"
|
||||
|
||||
namespace LA {
|
||||
// formatted I/O
|
||||
|
|
|
|||
Loading…
Reference in New Issue