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java.lang.Objectno.uib.cipr.matrix.AbstractMatrix
no.uib.cipr.matrix.UpperSymmDenseMatrix
public class UpperSymmDenseMatrix
Upper symmetrix dense matrix. It has the same storage layout as the
DenseMatrix
, but only refers to
elements above 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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UpperSymmDenseMatrix(int n)
Constructor for UpperSymmDenseMatrix |
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UpperSymmDenseMatrix(Matrix A)
Constructor for UpperSymmDenseMatrix |
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UpperSymmDenseMatrix(Matrix A,
boolean deep)
Constructor for UpperSymmDenseMatrix |
Method Summary | |
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void |
add(int row,
int column,
double value)
A(row,column) += value |
UpperSymmDenseMatrix |
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 . |
String |
toString()
|
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, 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 UpperSymmDenseMatrix(int n)
n
- Size of the matrix. Since the matrix must be square, this
equals both the number of rows and columnspublic UpperSymmDenseMatrix(Matrix A)
A
- Matrix to copy. It must be a square matrix, and only the upper
triangular part is copiedpublic UpperSymmDenseMatrix(Matrix A, boolean deep)
A
- Matrix to copy. It must be a square matrix, and only the upper
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 UpperSymmDenseMatrix 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
public String toString()
toString
in class AbstractMatrix
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