#include <MatSparse_Type.h>
Inheritance diagram for MatSparse(Type)::
Public Methods | |
| MatSparse(Type) () | |
| MatSparse(Type) (int n, int max_nonzeroes, bool symm_storage=false) | |
| MatSparse(Type) (int nrows, int ncolumns, int max_nonzeroes, bool symm_storage=false) | |
| MatSparse(Type) (int n, const VecSimple(int) &offsets, bool symm_storage=false) | |
| MatSparse(Type) (const SparseDS &addresses, bool symm_storage=false) | |
| MatSparse(Type) (const MatDense(Type) &M, real drop_tolerance=1.0e-12) | |
| MatSparse(Type) (const MatSparse(Type) &X) | |
| MatSparse(Type) (const Matrix(prm_Type) &pm) | |
| virtual | ~MatSparse(Type) (;) virtual int getNoRows() const |
| virtual int | getNoColumns () const |
| virtual int | getNoNonzeroes () const |
| virtual void | size (int &m, int &n) const |
| int | size () const |
| bool | ok () |
| virtual int | getWork (const MatrixWork work_tp=MATVEC_WORK) const |
| virtual real | getStorage () const |
| SparseDS& | pattern () |
| virtual bool | makeItSimilar (Handle(Matrix(Type)) &M) const |
| virtual bool | redim (const Matrix(prm_Type) &pm) |
| bool | redim (int n, int max_nonzeroes, bool symm_storage=false) |
| bool | redim (int nrows, int ncolumns, int max_nonzeroes, bool symm_storage=false) |
| bool | redim (const SparseDS &addresses, bool symm_storage=false) |
| virtual void | optimizeDataStructure () |
| void | compressPattern (real threshold) |
| virtual bool | redim (const VecSimple(int) &ivec, const VecSimple(int) &jvec, int new_nrows, int new_ncolumns) |
| virtual void | getIndexSet (VecSimple(int) &ivec, VecSimple(int) &jvec) const |
| virtual bool | validIndexSet (const VecSimple(int) &ivec, const VecSimple(int) &jvec, const int new_nrows, const int new_ncolumns) |
| virtual Type& | elm (int i, int j) |
| MatSparse(Type)& | operator= (Type a) |
| MatSparse(Type)& | operator= (const MatSparse(Type) &X) |
| virtual void | fill (const Matrix(Type) &X) |
| virtual void | fill (Type a) |
| int | idx (int i, int j) const |
| Type& | operator() (int i, int j) |
| const Type& | operator() (int i, int j) const |
| Type& | operator() (int ij) |
| const Type& | operator() (int ij) const |
| virtual void | assemble (const Mat(Type) &em, const VecSimple(int) &idx_row_trans, const VecSimple(int) &idx_col_trans, int elm_no) |
| virtual void | add (Matrix(Type) &bb, Matrix(Type) &cb) |
| virtual void | add (Matrix(Type) &bb, char s, Matrix(Type) &cb) |
| virtual void | add (Matrix(Type) &bb, Type b, Matrix(Type) &cb) |
| virtual void | add (Type a, Matrix(Type) &bb, Type b, Matrix(Type) &cb) |
| void | add (MatSparse(Type) &y, int power) |
| void | add (Type value) |
| virtual void | mult (Type value) |
| virtual void | prod (const Vector(Type) &xb, Vector(Type) &yb, TransposeMode tpmode=NOT_TRANSPOSED, bool add_to_yb=false) const |
| virtual void | colManip (LinEqConstraint &constraint_eq, Vec(Type) &vc, VecSimple(bool) &essential_dof) |
| virtual void | rowManip (LinEqConstraint &constraint_eq, Vec(Type) &vc, VecSimple(bool) &essential_dof) |
| bool | factRILU (real omega=0.0, int level=0) |
| void | forwBackRILU (Vec(Type) &b, Vec(Type) &x) |
| bool | factLU () |
| void | forwBackLU (Vec(Type) &b, Vec(Type) &x) |
| bool | factAMG () |
| void | forwBackAMG (Vec(Type) &b, Vec(Type) &x) |
| virtual bool | factorize (const FactStrategy &fstrategy) |
| virtual void | forwBack (Vector(Type) &bb, Vector(Type) &xb) |
| virtual void | SSOR1it (Vector(Type) &xnew, const Vector(Type) &xold, const Vector(Type) &b, real omega, TransposeMode tpmode=NOT_TRANSPOSED) const |
| virtual void | SSORsolve (Vector(Type) &y, const Vector(Type) &c, real omega, TransposeMode tpmode=NOT_TRANSPOSED) const |
| virtual void | SOR1it (Vector(Type) &xnew, const Vector(Type) &xold, const Vector(Type) &b, real omega, TransposeMode tpmode=NOT_TRANSPOSED) const |
| virtual void | SORsolve (Vector(Type) &y, const Vector(Type) &c, real omega, TransposeMode tpmode=NOT_TRANSPOSED) const |
| virtual void | Jacobi1it (Vector(Type) &xnew, const Vector(Type) &xold, const Vector(Type) &b, TransposeMode tpmode=NOT_TRANSPOSED) const |
| virtual void | Jacobisolve (Vector(Type) &y, const Vector(Type) &c, TransposeMode tpmode=NOT_TRANSPOSED) const |
| virtual void | print (Os os, const char *header=NULL, int nentries_per_line=3) const |
| virtual void | printAscii (Os os, const char *header=NULL) const |
| virtual void | printIndexed (Os os, const char *header=NULL) const |
| virtual void | scan (Is is) |
| virtual void | save (const char *filename, const char *name="X") const |
| virtual void | load (const char *filename, const char *name="X") |
| CLASS_INFO | VIRTUAL_CAST (MatSparse(Type)) |
Friends | |
| Os& | operator<< (Os &os, const MatSparse(Type) &X) |
| Is& | operator>> (Is &is, MatSparse(Type) &X) |
NAME: MatSparse(Type) - general sparse matrix
DESCRIPTION:
This class implements the compressed sparse row storage scheme for representation of sparse matrices with arbitrary sparsity patterns. The class "SparseDS" is used to keep track of the nonzero entries.
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In addition to the usual constructors, there is a specialized version that accepts a existing "SparseDS" object as argument. Another version specific to sparse matrices, receives a dense matrix of type "MatDense(Type)" (or equivalently, "Mat(Type)"). A sparse matrix is then generated by applying a threshold parameter "drop_tolerance" to each entry of the dense matrix. There is also a constructor which accept a vector containing information on the offset for each stored diagonal. The lower diagonals have negative offset and the upper diagonals positive offset. Objects of type "MatSparse(Type)" can be used to represent rectangular matrices. However, there is not yet support for a symmetric storage scheme. |
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See documentation of one of the overloaded constructor. |
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See documentation of one of the overloaded constructor. |
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See documentation of one of the overloaded constructor. |
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See documentation of one of the overloaded constructor. |
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See documentation of one of the overloaded constructor. |
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See documentation of one of the overloaded constructor. |
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See documentation of one of the overloaded constructor. |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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See documentation of one of the overloaded functions. |
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as usual, this function permits matrix adressing using the logical index spaces for "(i,j)" from 1 to "nrows" and "ncolumns", respectively. Reimplemented from Matrix(Type). |
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performs Relaxed Incomplete LU factorization using the relaxation parameter "omega". Currently, no fill-in is allowed. |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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performs the triangular solves needed in connection to a RILU factrorization, see "factRILU". |
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Reimplemented from Matrix(Type). |
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returns the number of columns in the current object when viewed (logically) as a full matrix. Reimplemented from Matrix(Type). |
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returns the number of nonzero entries represented in the current object. Note that this function does not take symmetric storage formats into account. That is, it also counts entry "a(j,i)" even if this value is not stored due to symmetry properties. This function does not check for stored zero entries, but counts all entries represented by the chosen matrix format. Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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returns the operation count for the last computation of the type indicated by the "MatrixWork" argument. Reimplemented from Matrix(Type). |
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quite similar to "save", this function permits Matlab data files to be entered into the current vector object. If available, the binary format is used, otherwise it reads plain ASCII files. The version implemented in this base class is dummy, stating that the described functionality is not available. To overrule this behaviour, the "load" function should be implemented for the specific format(s). Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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calls the "compressPattern" function in order to eliminate the storage of (numerically) zero entries. The compression is done using the threshold value set when the "MatSparse" object is created, typically through a menu choice in the "Matrix_prm" sub menu. Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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See documentation of one of the overloaded functions. Reimplemented from Matrix(Type). |
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See documentation of one of the overloaded functions. |
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See documentation of one of the overloaded functions. |
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See documentation of one of the overloaded functions. |
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the specialized version of this function accepts a "SparseDS" object as input. Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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saves the current vector object in a file that is readable for Matlab. If available, the utilities for Matlab's internal binary data file format is used. Otherwise, the output is given as a plain ASCII file that can be loaded in Matlab. The version implemented in this base class is dummy, stating that the described functionality is not available. To overrule this behaviour, the "save" function should be implemented for the specific format(s). Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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Reimplemented from Matrix(Type). |
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