working on tensor
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2b20bff532
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@ -193,6 +193,7 @@ template<typename T>
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void Tensor<T>::put(int fd) const
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void Tensor<T>::put(int fd) const
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{
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{
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shape.put(fd,true);
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shape.put(fd,true);
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groupsizes.put(fd,true);
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cumsizes.put(fd,true);
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cumsizes.put(fd,true);
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data.put(fd,true);
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data.put(fd,true);
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}
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}
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@ -202,6 +203,7 @@ void Tensor<T>::get(int fd)
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{
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{
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shape.get(fd,true);
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shape.get(fd,true);
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myrank=calcrank(); //is not stored but recomputed
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myrank=calcrank(); //is not stored but recomputed
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groupsizes.put(fd,true);
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cumsizes.get(fd,true);
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cumsizes.get(fd,true);
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data.get(fd,true);
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data.get(fd,true);
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}
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}
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28
tensor.h
28
tensor.h
@ -89,6 +89,7 @@ template<typename T>
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class Tensor {
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class Tensor {
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int myrank;
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int myrank;
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NRVec<indexgroup> shape;
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NRVec<indexgroup> shape;
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NRVec<LA_largeindex> groupsizes; //group sizes of symmetry index groups (a function of shape but precomputed for efficiency)
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NRVec<LA_largeindex> cumsizes; //cumulative sizes of symmetry index groups (a function of shape but precomputed for efficiency)
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NRVec<LA_largeindex> cumsizes; //cumulative sizes of symmetry index groups (a function of shape but precomputed for efficiency)
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NRVec<T> data;
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NRVec<T> data;
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@ -101,12 +102,14 @@ private:
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public:
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public:
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//constructors
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//constructors
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Tensor() : myrank(0) {};
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Tensor() : myrank(0) {};
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Tensor(const NRVec<indexgroup> &s) : shape(s), data((int)getsize()), myrank(calcrank()) {data.clear();}; //general tensor
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Tensor(const NRVec<indexgroup> &s) : shape(s), data((int)calcsize()), myrank(calcrank()) {}; //general tensor
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Tensor(const indexgroup &g) {shape.resize(1); shape[0]=g; data.resize(getsize()); myrank=calcrank(); data.clear();}; //tensor with a single index group
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Tensor(const indexgroup &g) {shape.resize(1); shape[0]=g; data.resize(calcsize()); myrank=calcrank();}; //tensor with a single index group
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Tensor(const Tensor &rhs): myrank(rhs.myrank), shape(rhs.shape), groupsizes(rhs.groupsizes), cumsizes(rhs.cumsizes), data(rhs.data) {};
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void clear() {data.clear();};
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int rank() const {return myrank;};
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int rank() const {return myrank;};
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int calcrank(); //is computed from shape
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int calcrank(); //is computed from shape
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LA_largeindex getsize(); //set redundant data and return total size
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LA_largeindex calcsize(); //set redundant data and return total size
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LA_largeindex size() const {return data.size();};
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LA_largeindex size() const {return data.size();};
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void copyonwrite() {shape.copyonwrite(); data.copyonwrite();};
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void copyonwrite() {shape.copyonwrite(); data.copyonwrite();};
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inline Signedpointer<T> lhs(const SUPERINDEX &I) {int sign; LA_largeindex i=index(&sign,I); return Signedpointer<T>(&data[i],sign);};
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inline Signedpointer<T> lhs(const SUPERINDEX &I) {int sign; LA_largeindex i=index(&sign,I); return Signedpointer<T>(&data[i],sign);};
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@ -116,18 +119,24 @@ public:
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inline Signedpointer<T> lhs(LA_index i1...) {va_list args; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); return Signedpointer<T>(&data[i],sign); };
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inline Signedpointer<T> lhs(LA_index i1...) {va_list args; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); return Signedpointer<T>(&data[i],sign); };
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inline T operator()(LA_index i1...) {va_list args; ; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];};
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inline T operator()(LA_index i1...) {va_list args; ; int sign; LA_largeindex i; va_start(args,i1); i= vindex(&sign, i1,args); if(sign==0) return 0; return sign>0 ?data[i] : -data[i];};
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inline Tensor& operator=(const Tensor &rhs) {myrank=rhs.myrank; shape=rhs.shape; groupsizes=rhs.groupsizes; cumsizes=rhs.cumsizes; data=rhs.data; return *this;};
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inline Tensor& operator*=(const T &a) {data*=a; return *this;};
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inline Tensor& operator*=(const T &a) {data*=a; return *this;};
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inline Tensor operator*(const T &a) const {Tensor r(*this); r *=a; return r;};
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inline Tensor& operator/=(const T &a) {data/=a; return *this;};
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inline Tensor& operator/=(const T &a) {data/=a; return *this;};
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inline Tensor operator/(const T &a) const {Tensor r(*this); r /=a; return r;};
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void put(int fd) const;
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void put(int fd) const;
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void get(int fd);
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void get(int fd);
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//@@@TODO - unwinding to full size in a specified index
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//@@@TODO - unwinding to full size in a specified index
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//@@@TODO - contractions - basic and efficient
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//@@@TODO - contractions - basic and efficient? first contraction in a single index; between a given group+index in group at each tensor
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//@@@dodelat indexy
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//@@@ dvojite rekurzivni loopover s callbackem - nebo iterator s funkci next???
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//@@@ dvojite rekurzivni loopover s callbackem - nebo iterator s funkci next???
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//@@@nebo inverse index function?
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//@@@nebo inverse index function?
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//@@@ stream i/o na zaklade tohoto
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//@@@ stream i/o na zaklade tohoto
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//@@@permuteindexgroups
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//@@@symmetreize a group, antisymmetrize a group, expand a (anti)symmetric grtoup
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//@@@@@@+= -= + - on same shape
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};
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};
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@ -148,8 +157,9 @@ return r;
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template<typename T>
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template<typename T>
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LA_largeindex Tensor<T>::getsize()
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LA_largeindex Tensor<T>::calcsize()
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{
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{
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groupsizes.resize(shape.size());
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cumsizes.resize(shape.size());
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cumsizes.resize(shape.size());
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LA_largeindex s=1;
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LA_largeindex s=1;
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for(int i=0; i<shape.size(); ++i)
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for(int i=0; i<shape.size(); ++i)
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@ -160,13 +170,13 @@ for(int i=0; i<shape.size(); ++i)
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switch(shape[i].symmetry)
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switch(shape[i].symmetry)
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{
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{
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case 0:
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case 0:
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s *= longpow(shape[i].range,shape[i].number);
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s *= groupsizes[i] = longpow(shape[i].range,shape[i].number);
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break;
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break;
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case 1:
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case 1:
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s *= simplicial(shape[i].number,shape[i].range);
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s *= groupsizes[i] = simplicial(shape[i].number,shape[i].range);
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break;
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break;
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case -1:
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case -1:
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s *= simplicial(shape[i].number,shape[i].range-shape[i].number+1);
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s *= groupsizes[i] = simplicial(shape[i].number,shape[i].range-shape[i].number+1);
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break;
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break;
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default:
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default:
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laerror("illegal index group symmetry");
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laerror("illegal index group symmetry");
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