Class xlifepp::HMatrix#

template<typename T, typename I> class HMatrix#

describes a matrix represented by a hierarchical structure (tree), each node being a block matrix a leaf is either a standard matrix or an approximate matrix

Public Functions

HMatrix(ClusterTree&, ClusterTree&, number_t, number_t, number_t = 0, const string_t& = "", SymType = _noSymmetry, HMatrixMethod = _standardHM, HMAdmissibilityRule = _boxesRule, real_t = 1)#: main constructor

HMatrix(const HMatrix<T, I>&)#: copy constructor

void addFELargeMatrix(const LargeMatrix<T>&)#: add FE LargeMatrix to current HMatrix

number_t averageRank() const#: average rank of admissible leaves

std::pair<number_t, number_t> averageSize() const#: average size of leaves

void buildTree()#: build the tree

inline HMatrixNode<T, I> *child(number_t d = 1)#: access to child at depth d

void clear()#: clear all and deallocate matrix pointers

inline void clearMatrices()#: clear matrices

inline const ClusterTree *colTree() const#: access to col cluster tree pointer

void copy(const HMatrix<T, I>&)#: copy all (full copy), do not clear

dimPair dimValues() const#: return dimensions of values, (1,1) when scalar

std::list<HMatrixNode<T, I>*> getLeaves(AccessType, number_t, number_t&, bool = true) const#: get all leaves ordered by row/col to avoid data races

std::list<HMatrixNode<T, I>*> getLeaves(bool = true) const#: get all leaves

void initCounter(number_t n = 0)#: initialize internal counter of HMatrixNode<T,I> for counting some operations

void load(const LargeMatrix<T>&, HMApproximationMethod = _noHMApproximation)#: load Hmatrix<T> from LargeMatrix<T>

void lu()#: LU Factorization.

std::vector<T> &multMatrixVector(const std::vector<T>&, std::vector<T>&) const#

matrix vector product (recursive)

Hmatrix * Vector.

std::vector<T> &multMatrixVectorOmp(const std::vector<T>&, std::vector<T>&) const#: matrix vector product (non recursive-omp)

inline number_t nbNonZero() const#: number of T coefficients used to represent the matrix

real_t norm2() const#: Frobenius norm.

real_t norminfty() const#: infinite norm

number_t numberOfCols() const#: return number of cols counted in T

number_t numberOfRows() const#: return number of rows counted in T

HMatrix<T, I> &operator=(const HMatrix<T, I>&)#: assign operator

void printStructure(std::ostream&, bool all = false, bool shift = false) const#: print matrix structure

inline HMatrixNode<T, I> *root()#: access to root node

inline const ClusterTree *rowTree() const#: access to row cluster tree pointer

void saveStructureToFile(const string_t&) const#: save matrix structure to file

void setClusterCol(ClusterTree*)#: change the col ClusterTree pointer

void setClusterRow(ClusterTree*)#: change the row ClusterTree pointer

void stopCounter()#: stop internal counter of HMatrixNode<T,I>

LargeMatrix<T> toLargeMatrix(StorageType st = _dense, AccessType at = _row) const#: convert HMatrix to LargeMatrix

void updateInfo()#: update tree info (depth, number of nodes, …)

Public Members

HMAdmissibilityRule admRule_#: block admissible rule

number_t colmin_#: minimum size of block matrix -> not split if nbrow < rowmin and nbcol < colmin

number_t depth#: maximal depth (info)

real_t eta_#: ratio in the criteria diam(Br) < 2*eta*dist(Br,Bc) (default eta = 1)

FactorizationType factorization_#: one of _noFactorization, _lu, _ldlt, _ldlstar; default is _noFactorization

HMatrixMethod method_#: method to define admissible block

string_t name#: optional name, useful for documentation

number_t nbAdmissibles#: number of admissible blocks (info)

number_t nbAppMatrices#: number of approximate matrices (info)

number_t nbLeaves#: number of leaves (info)

number_t nbNodes#: number of nodes (info)

StrucType strucType_#: structure of values (scalar, vector, matrix)

SymType sym#: type of symmetry (if has symmetry, only lower part is stored)

ValueType valueType_#: type of values (real, complex)