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java.lang.Objectno.uib.cipr.matrix.AbstractMatrix
no.uib.cipr.matrix.LowerSymmDenseMatrix
public class LowerSymmDenseMatrix
Lower symmetric dense matrix. It has the same storage layout as the
DenseMatrix
, but only refers to
elements below or on the main diagonal. The remaining elements are never
accessed nor changed, and is known only by symmetry.
Nested Class Summary |
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Nested classes/interfaces inherited from interface no.uib.cipr.matrix.Matrix |
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Matrix.Norm |
Field Summary |
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Fields inherited from class no.uib.cipr.matrix.AbstractMatrix |
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numColumns, numRows |
Constructor Summary | |
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LowerSymmDenseMatrix(int n)
Constructor for LowerSymmDenseMatrix |
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LowerSymmDenseMatrix(Matrix A)
Constructor for LowerSymmDenseMatrix |
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LowerSymmDenseMatrix(Matrix A,
boolean deep)
Constructor for LowerSymmDenseMatrix |
Method Summary | |
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void |
add(int row,
int column,
double value)
A(row,column) += value |
LowerSymmDenseMatrix |
copy()
Creates a deep copy of the matrix |
double |
get(int row,
int column)
Returns A(row,column) |
double[] |
getData()
Returns the matrix contents. |
Matrix |
multAdd(double alpha,
Matrix B,
Matrix C)
C = alpha*A*B + C |
Vector |
multAdd(double alpha,
Vector x,
Vector y)
y = alpha*A*x + y |
Matrix |
rank1(double alpha,
Matrix C)
A = alpha*C*CT + A . |
Matrix |
rank1(double alpha,
Vector x,
Vector y)
A = alpha*x*yT + A . |
Matrix |
rank2(double alpha,
Matrix B,
Matrix C)
A = alpha*B*CT + alpha*C*BT + A . |
Matrix |
rank2(double alpha,
Vector x,
Vector y)
A = alpha*x*yT + alpha*y*xT + A . |
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 |
transAmultAdd(double alpha,
Matrix B,
Matrix C)
C = alpha*AT*B + C |
Vector |
transMultAdd(double alpha,
Vector x,
Vector y)
y = alpha*AT*x + y |
Matrix |
transpose()
Transposes the matrix in-place. |
Matrix |
transRank1(double alpha,
Matrix C)
A = alpha*CT*C + A The matrices must be
square and of the same size |
Matrix |
transRank2(double alpha,
Matrix B,
Matrix C)
A = alpha*BT*C + alpha*CT*B + A . |
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. |
Methods inherited from class no.uib.cipr.matrix.AbstractMatrix |
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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, iterator, max, max, mult, mult, mult, mult, multAdd, multAdd, norm, norm1, normF, normInf, numColumns, numRows, rank1, rank1, rank1, rank1, rank2, rank2, scale, set, toString, transABmult, transABmult, transABmultAdd, transABmultAdd, transAmult, transAmult, transAmultAdd, transBmult, transBmult, transBmultAdd, transBmultAdd, transMult, transMult, transMultAdd, transpose, transRank1, transRank2 |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public LowerSymmDenseMatrix(int n)
n
- Size of the matrix. Since the matrix must be square, this
equals both the number of rows and columnspublic LowerSymmDenseMatrix(Matrix A)
A
- Matrix to copy. It must be a square matrix, and only the lower
triangular part is copiedpublic LowerSymmDenseMatrix(Matrix A, boolean deep)
A
- Matrix to copy. It must be a square matrix, and only the lower
triangular part is copieddeep
- If false, a shallow copy is made. In that case, A
must be a dense matrixMethod Detail |
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public void add(int row, int column, double value)
Matrix
A(row,column) += value
add
in interface Matrix
public double get(int row, int column)
Matrix
A(row,column)
get
in interface Matrix
public void set(int row, int column, double value)
Matrix
A(row,column) = value
set
in interface Matrix
public LowerSymmDenseMatrix copy()
Matrix
copy
in interface Matrix
copy
in class AbstractMatrix
public Matrix multAdd(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*A*B + C
multAdd
in interface Matrix
multAdd
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 transAmultAdd(double alpha, Matrix B, Matrix C)
Matrix
C = alpha*AT*B + C
transAmultAdd
in interface Matrix
transAmultAdd
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 rank1(double alpha, Vector x, Vector y)
Matrix
A = alpha*x*yT + A
. The matrix must be
square, and the vectors of the same length
rank1
in interface Matrix
rank1
in class AbstractMatrix
public Matrix rank2(double alpha, Vector x, Vector y)
Matrix
A = alpha*x*yT + alpha*y*xT + A
.
The matrix must be square, and the vectors of the same length
rank2
in interface Matrix
rank2
in class AbstractMatrix
public Vector multAdd(double alpha, Vector x, Vector y)
Matrix
y = alpha*A*x + y
multAdd
in interface Matrix
multAdd
in class AbstractMatrix
x
- Vector of size A.numColumns()
y
- Vector of size A.numRows()
public Vector transMultAdd(double alpha, Vector x, Vector y)
Matrix
y = alpha*AT*x + y
transMultAdd
in interface Matrix
transMultAdd
in class AbstractMatrix
x
- Vector of size A.numRows()
y
- Vector of size A.numColumns()
public Matrix rank1(double alpha, Matrix C)
Matrix
A = alpha*C*CT + A
. The matrices must be
square and of the same size
rank1
in interface Matrix
rank1
in class AbstractMatrix
public Matrix transRank1(double alpha, Matrix C)
Matrix
A = alpha*CT*C + A
The matrices must be
square and of the same size
transRank1
in interface Matrix
transRank1
in class AbstractMatrix
public Matrix rank2(double alpha, Matrix B, Matrix C)
Matrix
A = alpha*B*CT + alpha*C*BT + A
.
This matrix must be square
rank2
in interface Matrix
rank2
in class AbstractMatrix
B
- Matrix with the same number of rows as A
and
the same number of columns as C
C
- Matrix with the same number of rows as A
and
the same number of columns as B
public Matrix transRank2(double alpha, Matrix B, Matrix C)
Matrix
A = alpha*BT*C + alpha*CT*B + A
.
This matrix must be square
transRank2
in interface Matrix
transRank2
in class AbstractMatrix
B
- Matrix with the same number of rows as C
and
the same number of columns as A
C
- Matrix with the same number of rows as B
and
the same number of columns as A
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 solver
solve
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 solver
solve
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
solver
transSolve
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 solver
transSolve
in interface Matrix
transSolve
in class AbstractMatrix
b
- Vector of size A.numColumns()
x
- Vector of size A.numRows()
public Matrix transpose()
Matrix
transpose
in interface Matrix
transpose
in class AbstractMatrix
public double[] getData()
public Matrix set(Matrix B)
Matrix
A=B
. The matrices must be of the same size
set
in interface Matrix
set
in class AbstractMatrix
public Matrix zero()
Matrix
zero
in interface Matrix
zero
in class AbstractMatrix
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