public class LowerTriangPackMatrix extends AbstractMatrix
LowerTriangDenseMatrix,
this matrix exploits the sparsity by only storing about half the matrix. As
such, the triangular matrix
| a11 | |||
| a21 | a22 | ||
| a31 | a32 | a33 | |
| a41 | a42 | a43 | a44 |
is packed as follows:
| a11 | a21 | a31 | a41 | a22 | a32 | a42 | a33 | a43 | a44 |
Matrix.NormnumColumns, numRows| Constructor and Description |
|---|
LowerTriangPackMatrix(int n)
Constructor for LowerTriangPackMatrix
|
LowerTriangPackMatrix(Matrix A)
Constructor for LowerTriangPackMatrix
|
LowerTriangPackMatrix(Matrix A,
boolean deep)
Constructor for LowerTriangPackMatrix
|
| Modifier and Type | Method and Description |
|---|---|
void |
add(int row,
int column,
double value)
A(row,column) += value |
LowerTriangPackMatrix |
copy()
Creates a deep copy of the matrix
|
double |
get(int row,
int column)
Returns
A(row,column) |
double[] |
getData()
Returns the matrix contents.
|
Iterator<MatrixEntry> |
iterator() |
Vector |
mult(double alpha,
Vector x,
Vector y)
y = alpha*A*x |
void |
set(int row,
int column,
double value)
A(row,column) = value |
Matrix |
set(Matrix B)
A=B. |
Matrix |
solve(Matrix B,
Matrix X)
X = A\B. |
Vector |
solve(Vector b,
Vector x)
x = A\b. |
Vector |
transMult(double alpha,
Vector x,
Vector y)
y = alpha*AT*x |
Matrix |
transSolve(Matrix B,
Matrix X)
X = AT\B. |
Vector |
transSolve(Vector b,
Vector x)
x = AT\b. |
Matrix |
zero()
Zeros all the entries in the matrix, while preserving any underlying
structure.
|
add, add, check, checkMultAdd, checkMultAdd, checkRank1, checkRank1, checkRank2, checkRank2, checkSize, checkSolve, checkSolve, checkTransABmultAdd, checkTransAmultAdd, checkTransBmultAdd, checkTransMultAdd, checkTranspose, checkTranspose, checkTransRank1, checkTransRank2, isSquare, max, max, mult, mult, mult, multAdd, multAdd, multAdd, multAdd, norm, norm1, normF, normInf, numColumns, numRows, rank1, rank1, rank1, rank1, rank1, rank1, rank2, rank2, rank2, rank2, scale, set, toString, transABmult, transABmult, transABmultAdd, transABmultAdd, transAmult, transAmult, transAmultAdd, transAmultAdd, transBmult, transBmult, transBmultAdd, transBmultAdd, transMult, transMultAdd, transMultAdd, transpose, transpose, transRank1, transRank1, transRank2, transRank2clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitforEach, spliteratorpublic LowerTriangPackMatrix(int n)
n - Size of the matrix. Since the matrix must be square, this
equals both the number of rows and columnspublic LowerTriangPackMatrix(Matrix A)
A - Matrix to copy contents from. Only the entries of the relevant
part are copiedpublic LowerTriangPackMatrix(Matrix A, boolean deep)
A - Matrix to copy contents from. Only the entries of the relevant
part are copieddeep - True if the copy is deep, else false (giving a shallow copy).
For shallow copies, A must be a packed matrixpublic void add(int row,
int column,
double value)
MatrixA(row,column) += valueadd in interface Matrixadd in class AbstractMatrixpublic void set(int row,
int column,
double value)
MatrixA(row,column) = valueset in interface Matrixset in class AbstractMatrixpublic double get(int row,
int column)
MatrixA(row,column)get in interface Matrixget in class AbstractMatrixpublic LowerTriangPackMatrix copy()
Matrixcopy in interface Matrixcopy in class AbstractMatrixpublic Vector mult(double alpha, Vector x, Vector y)
Matrixy = alpha*A*xmult in interface Matrixmult in class AbstractMatrixx - Vector of size A.numColumns()y - Vector of size A.numRows()public Vector transMult(double alpha, Vector x, Vector y)
Matrixy = alpha*AT*xtransMult in interface MatrixtransMult in class AbstractMatrixx - Vector of size A.numRows()y - Vector of size A.numColumns()public Matrix solve(Matrix B, Matrix X)
MatrixX = A\B. Not all matrices support this operation, those that
do not throw UnsupportedOperationException. Note that it is
often more efficient to use a matrix decomposition and its associated
solversolve in interface Matrixsolve in class AbstractMatrixB - Matrix with the same number of rows as A, and the
same number of columns as XX - Matrix with a number of rows equal A.numColumns()
, and the same number of columns as Bpublic Vector solve(Vector b, Vector x)
Matrixx = A\b. Not all matrices support this operation, those that
do not throw UnsupportedOperationException. Note that it is
often more efficient to use a matrix decomposition and its associated
solversolve in interface Matrixsolve in class AbstractMatrixb - Vector of size A.numRows()x - Vector of size A.numColumns()public Matrix transSolve(Matrix B, Matrix X)
MatrixX = AT\B. Not all matrices support this
operation, those that do not throw
UnsupportedOperationException. Note that it is often more
efficient to use a matrix decomposition and its associated transpose
solvertransSolve in interface MatrixtransSolve in class AbstractMatrixB - Matrix with a number of rows equal A.numColumns()
, and the same number of columns as XX - Matrix with the same number of rows as A, and the
same number of columns as Bpublic Vector transSolve(Vector b, Vector x)
Matrixx = AT\b. Not all matrices support this
operation, those that do not throw
UnsupportedOperationException. Note that it is often more
efficient to use a matrix decomposition and its associated solvertransSolve in interface MatrixtransSolve in class AbstractMatrixb - Vector of size A.numColumns()x - Vector of size A.numRows()public Iterator<MatrixEntry> iterator()
iterator in interface Iterable<MatrixEntry>iterator in class AbstractMatrixpublic double[] getData()
public Matrix set(Matrix B)
MatrixA=B. The matrices must be of the same sizeset in interface Matrixset in class AbstractMatrixCopyright © 2015. All Rights Reserved.