HLIBpro
1.2
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Classes | |
class | TAdmCondition |
Defines basic interface for admissibility conditions. More... | |
class | TAlgAdmCond |
base class for algebraic admissibility conditions More... | |
class | TStdAlgAdmCond |
Standard admissibility condition based on matrix graph criteria. More... | |
class | TAlgCTBuilder |
Base class for cluster tree construction algorithms based on graph partitioning with graph defined by a sparse matrix. More... | |
class | TNDAlgCTBuilder |
Enhances algebraic clustering by nested dissection. More... | |
class | TPartAlgCTBuilder |
Enhances algebraic clustering by allowing the user to define the first level of index partitioning, e.g. define which index belongs to which son cluster. More... | |
class | TAlgPartStrat |
Base class for partitioning strategies for algebraic clustering. More... | |
class | TBFSAlgPartStrat |
Graph partitioning using BFS algorithm and FM optimisation. More... | |
class | TMLAlgPartStrat |
Multi level graph partitioning. More... | |
class | TMETISAlgPartStrat |
Graph partitioning using METIS. More... | |
class | TScotchPartStrat |
Graph partitioning using Scotch. More... | |
class | TChacoPartStrat |
Graph partitioning using CHACO. More... | |
class | TBCBuilder |
Recursively build block cluster tree with supplied admissibility condition. More... | |
class | TDDBCBuilder |
Build blockclusters in case of domain decomposition. More... | |
class | TBlockCluster |
Representing a node in a block cluster tree as product of two clusters. More... | |
class | TBlockClusterTree |
Represents a block cluster tree. More... | |
class | TBSPCTBuilder |
Base class for all cluster tree constructors based on geometry data. More... | |
class | TBSPNDCTBuilder |
Combines binary space partitioning with nested dissection based on connectivity defined by a sparse matrix. More... | |
class | TBSPPartCTBuilder |
Enhances BSP by allowing the user to define the first level of index partitioning by a given vector. More... | |
class | TBSPPartStrat |
Base class for partitioning strategies for geometrical BSP clustering. More... | |
class | TGeomBSPPartStrat |
Partition according to geometrical volume of index sets. More... | |
class | TCardBSPPartStrat |
Partition according to cardinality of index sets. More... | |
class | TPCABSPPartStrat |
Partition according to principle component analysis. More... | |
class | TNDBSPPartStrat |
Special partition strategy to optimized nested dissection clustering. More... | |
class | TAutoBSPPartStrat |
Automatic choice of best partitioning strategy. More... | |
class | TCluster |
Represents a node in a cluster tree with an arbitrary number of sons. More... | |
class | TClusterBasis< T > |
class representing a nested cluster basis More... | |
class | TDenseClusterBasisBuilder< T > |
class for constructing cluster bases using dense matrices More... | |
class | THClusterBasisBuilder< T > |
class for constructing cluster bases using H-matrices More... | |
class | TClusterTree |
Represents a cluster tree with permutation of index sets. More... | |
class | TDiGraph |
Class for directed graph represented by adjacency matrix in sparse format (assuming sparse graph!) More... | |
class | TFVS |
Uses a heuristic algorithm to compute feedback vertex set of a directed graph represented by a sparse matrix. More... | |
class | TGeomCluster |
Extend standard cluster by bounding box. More... | |
class | TGraph |
Class for a undirected graph stored as adjacency matrix in CRS representation. More... | |
class | TEWGraph |
Represents undirected graph with edge weights. More... | |
class | TNodeSet |
Represents a set of nodes by an array. More... | |
class | TStdAdmCond |
Standard admissibility for FEM/BEM applications normal : adm iff min( diam(τ), diam(σ) ) ≤ η·dist(τ,σ) use_max: adm iff max( diam(τ), diam(σ) ) ≤ η·dist(τ,σ) More... | |
class | TWeakStdAdmCond |
Combination of standard and weak admissibility. More... |
Typedefs | |
typedef int | weight_t |
type for edge weights | |
typedef idx_t | node_t |
Basic type for storing node names. |
This modules provides all classes for index set and cluster management, e.g. cluster trees, block cluster trees.