public class LowerTriangDenseMatrix extends AbstractMatrix
DenseMatrix
, but only refers to
elements below or on the main diagonal. The remaining elements are assumed to
be zero, but since they are never accessed, they need not be.Matrix.Norm
numColumns, numRows
Constructor and Description |
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LowerTriangDenseMatrix(int n)
Constructor for LowerTriangDenseMatrix
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LowerTriangDenseMatrix(Matrix A)
Constructor for LowerTriangDenseMatrix
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LowerTriangDenseMatrix(Matrix A,
boolean deep)
Constructor for LowerTriangDenseMatrix
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LowerTriangDenseMatrix(Matrix A,
int k)
Constructor for LowerTriangDenseMatrix
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LowerTriangDenseMatrix(Matrix A,
int k,
boolean deep)
Constructor for LowerTriangDenseMatrix
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Modifier and Type | Method and Description |
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void |
add(int row,
int column,
double value)
A(row,column) += value |
LowerTriangDenseMatrix |
copy()
Creates a deep copy of the matrix
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double |
get(int row,
int column)
Returns
A(row,column) |
double[] |
getData()
Returns the matrix contents.
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java.util.Iterator<MatrixEntry> |
iterator() |
Matrix |
mult(double alpha,
Matrix B,
Matrix C)
C = alpha*A*B |
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 . |
Matrix |
transAmult(double alpha,
Matrix B,
Matrix C)
C = alpha*AT*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.
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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, 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, transAmultAdd, transAmultAdd, transBmult, transBmult, transBmultAdd, transBmultAdd, transMult, transMultAdd, transMultAdd, transpose, transpose, transRank1, transRank1, transRank2, transRank2
public LowerTriangDenseMatrix(int n)
n
- Size of the matrix. Since the matrix must be square, this
equals both the number of rows and columnspublic LowerTriangDenseMatrix(Matrix A)
A
- Matrix to copy from. Only the lower triangular part is copiedpublic LowerTriangDenseMatrix(Matrix A, boolean deep)
A
- Matrix to copy from. Only the lower triangular part is copieddeep
- If true, A
is copied, else a shallow copy is
made and the matrices share underlying storage. For this,
A
must be a dense matrixpublic LowerTriangDenseMatrix(Matrix A, int k)
A
- Matrix to copy from. Only the lower triangular part is copiedk
- Size of matrix to refer.
k<min(numRows,numColumns)
public LowerTriangDenseMatrix(Matrix A, int k, boolean deep)
A
- Matrix to copy from. Only the lower triangular part is copiedk
- Size of matrix to refer.
k<min(numRows,numColumns)
deep
- If true, A
is copied, else a shallow copy is
made and the matrices share underlying storage. For this,
A
must be a dense matrixpublic void add(int row, int column, double value)
Matrix
A(row,column) += value
public double get(int row, int column)
Matrix
A(row,column)
public void set(int row, int column, double value)
Matrix
A(row,column) = value
public LowerTriangDenseMatrix copy()
Matrix
copy
in interface Matrix
copy
in class AbstractMatrix
public Vector mult(double alpha, Vector x, Vector y)
Matrix
y = alpha*A*x
mult
in interface Matrix
mult
in class AbstractMatrix
x
- Vector of size A.numColumns()
y
- Vector of size A.numRows()
public Vector transMult(double alpha, Vector x, Vector y)
Matrix
y = alpha*AT*x
transMult
in interface Matrix
transMult
in class AbstractMatrix
x
- Vector of size A.numRows()
y
- Vector of size A.numColumns()
public Matrix mult(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*A*B
mult
in interface Matrix
mult
in class AbstractMatrix
B
- Matrix such that B.numRows() == A.numColumns()
and B.numColumns() == C.numColumns()
C
- Matrix such that C.numRows() == A.numRows()
and
B.numColumns() == C.numColumns()
public Matrix transAmult(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*AT*B
transAmult
in interface Matrix
transAmult
in class AbstractMatrix
B
- Matrix such that B.numRows() == A.numRows()
and
B.numColumns() == C.numColumns()
C
- Matrix such that C.numRows() == A.numColumns()
and B.numColumns() == C.numColumns()
public Matrix solve(Matrix B, Matrix X)
Matrix
X = 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 Matrix
solve
in class AbstractMatrix
B
- Matrix with the same number of rows as A
, and
the same number of columns as X
X
- Matrix with a number of rows equal A.numColumns()
,
and the same number of columns as B
public Vector solve(Vector b, Vector x)
Matrix
x = 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 Matrix
solve
in class AbstractMatrix
b
- Vector of size A.numRows()
x
- Vector of size A.numColumns()
public Matrix transSolve(Matrix B, Matrix X)
Matrix
X = 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 Matrix
transSolve
in class AbstractMatrix
B
- Matrix with a number of rows equal A.numColumns()
,
and the same number of columns as X
X
- Matrix with the same number of rows as A
, and
the same number of columns as B
public Vector transSolve(Vector b, Vector x)
Matrix
x = 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 Matrix
transSolve
in class AbstractMatrix
b
- Vector of size A.numColumns()
x
- Vector of size A.numRows()
public java.util.Iterator<MatrixEntry> iterator()
iterator
in interface java.lang.Iterable<MatrixEntry>
iterator
in class AbstractMatrix
public double[] getData()
public Matrix set(Matrix B)
Matrix
A=B
. The matrices must be of the same sizeset
in interface Matrix
set
in class AbstractMatrix