Package no.uib.cipr.matrix
Class UnitLowerTriangDenseMatrix
- java.lang.Object
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- no.uib.cipr.matrix.AbstractMatrix
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- no.uib.cipr.matrix.LowerTriangDenseMatrix
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- no.uib.cipr.matrix.UnitLowerTriangDenseMatrix
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- All Implemented Interfaces:
java.lang.Iterable<MatrixEntry>,Matrix
public class UnitLowerTriangDenseMatrix extends LowerTriangDenseMatrix
Unit lower triangular dense matrix. Almost the same as theLowerTriangDenseMatrix, but additionally assumes the main diagonal to be all ones. However it does not access it, so it may be actually be different.
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Nested Class Summary
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Nested classes/interfaces inherited from interface no.uib.cipr.matrix.Matrix
Matrix.Norm
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Field Summary
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Fields inherited from class no.uib.cipr.matrix.AbstractMatrix
numColumns, numRows
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Constructor Summary
Constructors Constructor Description UnitLowerTriangDenseMatrix(int n)Constructor for UnitLowerTriangDenseMatrixUnitLowerTriangDenseMatrix(Matrix A)Constructor for UnitLowerTriangDenseMatrixUnitLowerTriangDenseMatrix(Matrix A, boolean deep)Constructor for UnitLowerTriangDenseMatrix
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidadd(int row, int column, double value)A(row,column) += valueUnitLowerTriangDenseMatrixcopy()Creates a deep copy of the matrixdoubleget(int row, int column)ReturnsA(row,column)double[]getData()Returns the matrix contents.java.util.Iterator<MatrixEntry>iterator()Matrixmult(double alpha, Matrix B, Matrix C)C = alpha*A*BVectormult(double alpha, Vector x, Vector y)y = alpha*A*xvoidset(int row, int column, double value)A(row,column) = valueMatrixset(Matrix B)A=B.Matrixsolve(Matrix B, Matrix X)X = A\B.Vectorsolve(Vector b, Vector x)x = A\b.MatrixtransAmult(double alpha, Matrix B, Matrix C)C = alpha*AT*BVectortransMult(double alpha, Vector x, Vector y)y = alpha*AT*xMatrixtransSolve(Matrix B, Matrix X)X = AT\B.VectortransSolve(Vector b, Vector x)x = AT\b.Matrixzero()Zeros all the entries in the matrix, while preserving any underlying structure.-
Methods inherited from class no.uib.cipr.matrix.AbstractMatrix
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
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Constructor Detail
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UnitLowerTriangDenseMatrix
public UnitLowerTriangDenseMatrix(int n)
Constructor for UnitLowerTriangDenseMatrix- Parameters:
n- Size of the matrix. Since the matrix must be square, this equals both the number of rows and columns
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UnitLowerTriangDenseMatrix
public UnitLowerTriangDenseMatrix(Matrix A)
Constructor for UnitLowerTriangDenseMatrix- Parameters:
A- Matrix to copy from. Only the strictly lower triangular part is copied
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UnitLowerTriangDenseMatrix
public UnitLowerTriangDenseMatrix(Matrix A, boolean deep)
Constructor for UnitLowerTriangDenseMatrix- Parameters:
A- Matrix to copy from. Only the strictly lower triangular part is copieddeep- If true,Ais copied, else a shallow copy is made and the matrices share underlying storage. For this,Amust be a dense matrix
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Method Detail
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add
public void add(int row, int column, double value)Description copied from interface:MatrixA(row,column) += value- Specified by:
addin interfaceMatrix- Overrides:
addin classLowerTriangDenseMatrix
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get
public double get(int row, int column)Description copied from interface:MatrixReturnsA(row,column)- Specified by:
getin interfaceMatrix- Overrides:
getin classLowerTriangDenseMatrix
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set
public void set(int row, int column, double value)Description copied from interface:MatrixA(row,column) = value- Specified by:
setin interfaceMatrix- Overrides:
setin classLowerTriangDenseMatrix
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copy
public UnitLowerTriangDenseMatrix copy()
Description copied from interface:MatrixCreates a deep copy of the matrix- Specified by:
copyin interfaceMatrix- Overrides:
copyin classLowerTriangDenseMatrix- Returns:
- A
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zero
public Matrix zero()
Description copied from interface:MatrixZeros all the entries in the matrix, while preserving any underlying structure. Useful for general, unstructured matrices.
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mult
public Vector mult(double alpha, Vector x, Vector y)
Description copied from interface:Matrixy = alpha*A*x- Specified by:
multin interfaceMatrix- Overrides:
multin classAbstractMatrixx- Vector of sizeA.numColumns()y- Vector of sizeA.numRows()- Returns:
- y
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transMult
public Vector transMult(double alpha, Vector x, Vector y)
Description copied from interface:Matrixy = alpha*AT*x- Specified by:
transMultin interfaceMatrix- Overrides:
transMultin classAbstractMatrixx- Vector of sizeA.numRows()y- Vector of sizeA.numColumns()- Returns:
- y
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mult
public Matrix mult(double alpha, Matrix B, Matrix C)
Description copied from interface:MatrixC = alpha*A*B- Specified by:
multin interfaceMatrix- Overrides:
multin classAbstractMatrixB- Matrix such thatB.numRows() == A.numColumns()andB.numColumns() == C.numColumns()C- Matrix such thatC.numRows() == A.numRows()andB.numColumns() == C.numColumns()- Returns:
- C
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transAmult
public Matrix transAmult(double alpha, Matrix B, Matrix C)
Description copied from interface:MatrixC = alpha*AT*B- Specified by:
transAmultin interfaceMatrix- Overrides:
transAmultin classAbstractMatrixB- Matrix such thatB.numRows() == A.numRows()andB.numColumns() == C.numColumns()C- Matrix such thatC.numRows() == A.numColumns()andB.numColumns() == C.numColumns()- Returns:
- C
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solve
public Matrix solve(Matrix B, Matrix X)
Description copied from interface:MatrixX = A\B. Not all matrices support this operation, those that do not throwUnsupportedOperationException. Note that it is often more efficient to use a matrix decomposition and its associated solver- Specified by:
solvein interfaceMatrix- Overrides:
solvein classAbstractMatrix- Parameters:
B- Matrix with the same number of rows asA, and the same number of columns asXX- Matrix with a number of rows equalA.numColumns(), and the same number of columns asB- Returns:
- X
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solve
public Vector solve(Vector b, Vector x)
Description copied from interface:Matrixx = A\b. Not all matrices support this operation, those that do not throwUnsupportedOperationException. Note that it is often more efficient to use a matrix decomposition and its associated solver- Specified by:
solvein interfaceMatrix- Overrides:
solvein classAbstractMatrix- Parameters:
b- Vector of sizeA.numRows()x- Vector of sizeA.numColumns()- Returns:
- x
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transSolve
public Matrix transSolve(Matrix B, Matrix X)
Description copied from interface:MatrixX = AT\B. Not all matrices support this operation, those that do not throwUnsupportedOperationException. Note that it is often more efficient to use a matrix decomposition and its associated transpose solver- Specified by:
transSolvein interfaceMatrix- Overrides:
transSolvein classAbstractMatrix- Parameters:
B- Matrix with a number of rows equalA.numColumns(), and the same number of columns asXX- Matrix with the same number of rows asA, and the same number of columns asB- Returns:
- X
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transSolve
public Vector transSolve(Vector b, Vector x)
Description copied from interface:Matrixx = AT\b. Not all matrices support this operation, those that do not throwUnsupportedOperationException. Note that it is often more efficient to use a matrix decomposition and its associated solver- Specified by:
transSolvein interfaceMatrix- Overrides:
transSolvein classAbstractMatrix- Parameters:
b- Vector of sizeA.numColumns()x- Vector of sizeA.numRows()- Returns:
- x
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iterator
public java.util.Iterator<MatrixEntry> iterator()
- Specified by:
iteratorin interfacejava.lang.Iterable<MatrixEntry>- Overrides:
iteratorin classAbstractMatrix
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getData
public double[] getData()
Returns the matrix contents. Ordering depends on the underlying storage assumptions
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